Mitochondrial Medicine: Volume 2: Assessing Mitochondria (Methods in Molecular Biology, 2276) [2nd ed. 2021] 1071612654, 9781071612651

Table of contents :
Preface
Contents
Contributors
Chapter 1: Mitochondrial Dysfunction in Mitochondrial Medicine: Current Limitations, Pitfalls, and Tomorrow
1 Introduction
2 Methods to Assess Mitochondrial Dysfunctions
2.1 Basis in Bioenergetic
2.2 Analyses of Maximal ETC Activities
2.3 Structural Analyses: BN-PAGE
2.4 Functional Analyses: Respiration Rates
2.4.1 Devices
The O2K Oxygraph
The Seahorse XF
2.4.2 Permeabilized Tissues and Cells
2.4.3 Intact Cells
2.5 Mitochondrial Membrane Potential
2.6 Metabolites Dosages and Metabolomics
2.6.1 Metabolite Measurements
2.6.2 Metabolomics
3 Discussion
References
Chapter 2: Preparation of ``Functional´´ Mitochondria: A Challenging Business
1 Introduction
2 Isolated Mitochondria: Addressing Composition and Function
3 First Step: The Inevitable
4 Isolating ``Intact´´ Mitochondria: A Challenging Business
5 Reproducibility and Quality Control: Guarantee for Successful Analysis
6 Conclusion
References
Chapter 3: Isolation and Quality Control of Functional Mitochondria
1 Introduction
2 Materials
2.1 Mitochondria Fractionation
2.2 Linear Saccharose Gradient
2.3 Marker Enzyme Assays
2.3.1 Succinate Dehydrogenase (SDH) Assay
2.3.2 Acidic Phosphatase Assay
2.3.3 Basic Phosphatase Assay
2.3.4 Catalase Assay
2.3.5 Glucose-6-Phospatase (G-6-Pase) Assay
2.3.6 JC-1 Uptake Assay
3 Methods
3.1 Subcellular Fractionation
3.1.1 Preparation of Linear Saccharose Gradient
3.1.2 Homogenization
3.1.3 Differential Centrifugation
3.1.4 Isopycnic Density Gradient Centrifugation
3.2 Protein Measurement
3.3 Marker Enzyme Assays
3.3.1 Mitochondria: Succinate Dehydrogenase (SDH) (See Ref. 7)
3.3.2 Lysosomes: Acid Phosphatase (See Ref. 8)
3.3.3 Plasma Membrane: Basic Phosphatase (See Ref. 8)
3.3.4 Peroxisome: Catalase (See Ref. 9)
3.3.5 Endoplasmic Reticulum: Glucose-6-Phophatase (See Ref. 10)
3.3.6 Mitochondria (Functional Integrity): JC-1 Uptake Assay (See Ref. 11)
4 Notes
References
Chapter 4: Purification of Functional Platelet Mitochondria Using a Discontinuous Percoll Gradient
1 Introduction
2 Materials
2.1 Solutions
2.2 Optional Solutions
2.3 Percoll Gradient Preparation
2.4 Blood Collection Preparation
3 Methods
3.1 Platelet Isolation
3.2 Crude Mitochondrial Extraction
3.3 Mitochondria Purification
3.4 Mitochondrial Yield by Flow Cytometry
3.5 Mitochondrial Yield by Bicinchoninic Acid Assay (BCA)
4 Notes
References
Chapter 5: Mechanical Permeabilization as a New Method for Assessment of Mitochondrial Function in Insect Tissues
1 Introduction
2 Materials
2.1 Solutions
2.2 Substrates
2.3 Uncoupler
2.4 Inhibitors
3 Methods
3.1 Insects
3.2 Sample Preparation
3.2.1 A. aegypti Head Dissection (Fig. 1a-c)
3.2.2 D. melanogaster Thorax Dissection (Fig. 1d-g)
3.3 Mechanical Permeabilization and Respirometry Measurements Protocols
3.3.1 A. aegypti Heads
3.3.2 D. melanogaster Thorax
3.4 Data Interpretation
3.5 Protocols Validation
3.5.1 A. aegypti Heads
3.5.2 D. melanogaster Thorax
3.6 Troubleshooting
4 Notes
References
Chapter 6: Analysis of Mitochondrial Retrograde Signaling in Yeast Model Systems
1 Introduction
2 Materials
2.1 Cells and Growth Media
2.2 Buffers, Reagents, and Labware
2.2.1 Real-Time PCR
2.2.2 Protein Extraction
2.2.3 SDS-Polyacrylamide Gel Electrophoresis
2.2.4 Western Blotting
3 Methods
3.1 Analysis of RTG-Dependent Target Gene mRNAs
3.1.1 Cell Growth and Low pH Shift
3.1.2 RNA Isolation and Real-Time PCR
3.2 Analysis of CIT2p-GFP
3.2.1 Cell Lysis
3.2.2 Western Blot
3.2.3 Fluorescence Microscopy
3.3 Analysis of Rtg3p Phosphorylation
3.3.1 Total Yeast Protein Extraction
3.3.2 Western Blotting
4 Notes
References
Chapter 7: Native Gel Electrophoresis and Immunoblotting to Analyze Electron Transport Chain Complexes
1 Introduction
2 Materials
2.1 Preparation for Native Electrophoresis (See Note 1)
2.2 Preparation for Western Blotting
3 Methods
3.1 Protocol Native Electrophoresis
3.2 Sample Preparation
3.3 Immunoblotting
4 Notes
References
Chapter 8: Measuring Mitochondrial Hydrogen Peroxide Levels and Glutathione Redox Equilibrium in Drosophila Neuron Subtypes Us...
1 Introduction
1.1 Redox Sensitive Green Fluorescent Proteins to Detect Glutathione Redox Equilibrium and H2O2 Levels
1.2 Directing Cell-Specific Gene Expression in Drosophila
1.3 Capturing and Measuring Oxidation Status of Mito-roGFP2-Grx1 and Mito-roGFP-Orp1 in Drosophila Dopaminergic Neuron Mitocho...
2 Materials
2.1 Drosophila Stocks
2.2 Food Preparation
2.3 Anesthetizing Flies
2.4 Drosophila Brain Dissection and Immunolabeling
2.5 Mounting the Brains on Microscope Slides
2.6 Dopaminergic Neuron Cluster Image Capture
2.7 Measuring roGFP Fluorescence Reporters
3 Methods
3.1 Standard Corn Meal Molasses Drosophila Food Preparation
3.2 Drosophila Stocks and Maintenance
3.3 Crossing Drosophila to Obtain Progeny Expressing Mito-roGFP2-Grx1 or Mito-roGFP2-Orp1 in Dopaminergic Cells
3.4 Drosophila Brain Dissection
3.5 Tyrosine Hydroxylase Immunolabeling
3.6 Mounting Drosophila Brains on Microscope Slides
3.7 Capturing Images of roGFP2s in Dopaminergic Neuron Mitochondria
3.8 Image Processing
3.9 Data Analysis
4 Notes
References
Chapter 9: Assessment of Mitochondrial Cell Metabolism by Respiratory Chain Electron Flow Assays
1 Introduction
2 Materials
2.1 Equipment
2.2 Cells and Reagents
3 Methods
3.1 Optimization of Saponin Concentration and Cell Density
3.2 Electron Flux Assay Mix Preparation
3.3 Cell Suspension
3.4 Step-by-Step Instructions
3.5 Analysis of the Results
3.6 Interpretation of the Results
4 Notes
References
Chapter 10: Whole-Cell and Mitochondrial dNTP Pool Quantification from Cells and Tissues
1 Introduction
2 Materials
2.1 General Equipment
2.2 Whole-Cell dNTP Isolation from Cells
2.3 Whole-Cell dNTP Isolation from Tissues
2.4 Mitochondrial dNTP Isolation
2.5 Binding, Polymerization, and Detection
3 Methods
3.1 Whole-Cell dNTP Isolation from Cells
3.2 Whole-Cell dNTP Isolation from Tissues
3.3 Mitochondrial dNTP Isolation
3.4 Affinity Capture of Oligonucleotides (Fig. 1 I)
3.5 Preparation of Standard Series and Sample Dilutions
3.6 Polymerase Reaction and Detection (Fig. 1 II-III)
3.7 Data Analysis
4 Notes
References
Chapter 11: Single-Particle Tracking Method in Fluorescence Microscopy to Monitor Bioenergetic Responses of Individual Mitocho...
1 Introduction
2 Materials
2.1 Solutions
2.2 Fluorescence Imaging
3 Methods
3.1 Rat Heart Extraction
3.2 Extraction of Cardiac Mitochondria
3.3 Coverslip Preparation
3.4 Experimental Procedure for Mitochondria Imaging
3.5 Imaging of Mitochondria
3.6 Treatment of Images with ``Fiji´´
3.7 Mitochondria Follow-Up with ``TrackMate´´
3.8 Python Scripts for Quantitative Analyses
4 Notes
References
Chapter 12: Investigation of Mitochondrial ADP-Ribosylation Via Immunofluorescence
1 Introduction
2 Materials
3 Methods
3.1 Cell Seeding
3.2 Treatment of Cells to Increase Mitochondrial ADP-Ribosylation
3.3 Fixation and Permeabilization
3.4 Blocking and Immunostaining
3.5 DAPI Staining and Mounting
3.6 Analysis/Quantification of the Immunofluorescence Signal
4 Notes
References
Chapter 13: Assessment of Mitochondrial Ca2+ Uptake
1 Introduction
2 Materials
2.1 Chemical Fluorescent Indicator Components
2.2 Components for the Use of Genetically Encoded Ca2+ Indicators
2.3 Components for Mitoplast Isolation and Patch-Clamp Recordings
2.4 Components for Measuring Cellular O2 Consumption Rates
3 Methods
3.1 Measuring Indirect Ca2+ Uptake Via Calcium Green
3.2 Measuring Direct Mitochondrial Ca2+ Uptake Via Fura-2 or Rhod-2
3.3 Transfection of Genetically Encoded Ca2+ Indicators
3.4 Real-Time Recordings of [Ca2+]cyto and [Ca2+]mito
3.5 Mitoplast Patch-Clamping Recording
3.6 Assessing Ca2+-Dependent Changes in Mitochondrial Metabolism
4 Notes
References
Chapter 14: Assessment of Mitochondrial Membrane Potential and NADH Redox State in Acute Brain Slices
1 Introduction
2 Materials
2.1 Equipment
2.2 Reagents for NADH Determination
2.3 Reagents for Mitochondrial Membrane Potential Determination
3 Methods
3.1 Acute Brain Slices Preparation Procedure
3.2 NADH Determination Procedure
3.3 Mitochondrial Membrane Potential Determination Procedure
4 Notes
References
Chapter 15: Evaluation of Mitochondria Content and Function in Live Cells by Multicolor Flow Cytometric Analysis
1 Introduction
2 Material
2.1 Preparation of the Single-Cell Suspension
2.2 Detection of Mitochondrial Mass, Activity, and ROS (See Notes 1 and 2)
2.3 Surface Marker Staining
3 Methods
3.1 Tissue Harvest and Generation of the Single-Cell Suspension
3.2 Quantification of Mitochondria Mass and Membrane Potential
3.3 Surface Marker Staining
3.4 Reactive Oxygen Species Detection
3.5 Data Analysis
4 Note
References
Chapter 16: Analysis of Mitochondrial Dysfunction During Cell Death
1 Introduction
2 Materials
2.1 Assessment of Cytochrome c Release from the Mitochondria of Apoptotic Cells
2.2 Assessment of the Mitochondrial Membrane Potential Alterations in Apoptosis
2.3 Assessment of Oxygen Consumption in Intact Apoptotic Cells
2.4 Assessment of Mitochondrial Respiration in Apoptotic Cells with Digitonin-Permeabilized Plasma Membrane
2.5 Assessment of Mitochondrial Production of Superoxide Radical
3 Methods
3.1 Evaluation of Cytochrome c Release from the Mitochondria of Apoptotic Cells
3.2 Assessment of the Mitochondrial Membrane Potential
3.3 Assessment of Oxygen Consumption in Intact Apoptotic Cells
3.4 Assessment of Mitochondrial Respiration in Apoptotic Cells with Digitonin-Permeabilized Plasma Membrane
3.5 Assessment of Mitochondrial Superoxide Radical Production
4 Notes
References
Chapter 17: Modified Blue Native Gel Approach for Analysis of Respiratory Supercomplexes
1 Introduction
2 Materials (See Note 1)
2.1 General Solutions for Running BN Gels
2.2 Compromise Buffer (CB) for Incubations and BN Gel Extraction
2.3 Solutions for In-Gel Complex V Assay
3 Methods
3.1 Mitochondrial Incubation and Sample Extraction for BN Gel Analysis
3.2 BN Gel Electrophoresis
3.3 Cx-V In-Gel Assay
4 Notes
References
Chapter 18: Patch-Clamp Recording of the Activity of Ion Channels in the Inner Mitochondrial Membrane
1 Introduction
2 Materials
2.1 Stock Solutions
2.2 Mitochondria Isolation
2.3 Mitoplast Preparation
2.4 Patch-Clamp Recordings
2.5 Single-Mitoplast PCR
3 Methods
3.1 Mitochondria Isolation
3.2 Mitoplast Preparation
3.3 Patch-Clamp Recordings
3.4 Single-Mitoplast PCR
4 Notes
References
Chapter 19: Assessment of Mitochondrial Protein Glutathionylation as Signaling for CO Pathway
1 Introduction
2 Materials
2.1 Mitochondria Isolation from Cell Culture
2.2 Mitochondria Isolation from Brain Cortex
2.3 CO Treatment
2.4 Immunoprecipitation
2.5 Immunoblotting
3 Methods
3.1 CO Treatment
3.2 Mitochondria Isolation from Cell Culture
3.3 Mitochondria Isolation from Brain Tissue
3.4 Immunoprecipitation of Proteins in Isolated Mitochondria
3.5 Immunoblotting
4 Notes
References
Chapter 20: 3D Optical Cryo-Imaging Method: A Novel Approach to Quantify Renal Mitochondrial Bioenergetics Dysfunction
1 Introduction
1.1 Mitochondrial Dysfunction
1.2 Optical Metabolic Imaging
2 Materials
2.1 Optical Components
2.2 Mechanical Components
2.3 Sample Preparation Requirements
3 Methods
3.1 Black Mounting Medium (BMM) Preparation
3.2 Kidney Sample Preparation
3.3 Cryo-Imaging Procedure
3.3.1 Mounting
3.3.2 Image Acquisition
3.4 Image Processing
3.5 Data Interpretation
4 Notes
References
Chapter 21: Simultaneous Quantification of Mitochondrial ATP and ROS Production Using ATP Energy Clamp Methodology
1 Introduction
1.1 2DOG ATP Energy Clamp
1.2 Use of the 2DOG ATP Energy Clamp to Quantify ATP Production in Isolated Mitochondria and Simultaneous Assessment of H2O2 P...
1.3 Utilization in Recent Studies
2 Materials
2.1 Isolation of Mitochondria
2.2 Assay Incubation
2.3 Sample Preparation for NMR Spectroscopy
2.4 NMR Spectroscopy
3 Methods
3.1 Isolation of Mitochondria from Tissue
3.2 Further Purification of Isolated Mitochondria (See Note 6)
3.3 Assay Incubation
3.4 Fluorescent Assessment of H2O2 Production
3.5 Processing the Well Contents for NMR-Based ATP Assay
3.6 NMR Spectroscopy for Quantifying ATP Production
3.7 Calculation of ATP Production Rates
4 Notes
References
Chapter 22: High-Throughput Image Analysis of Lipid-Droplet-Bound Mitochondria
1 Introduction
1.1 Background
1.2 Training Images Used for WEKA Training Set
1.3 Mitochondria Morphological Parameters That Describe Mitochondrial Networking
1.4 Segmentation of Cytosolic Mitochondria Versus Peridroplet Mitochondria Reveals Significant Differences in H2O2 Levels
1.4.1 Trainable WEKA Segmentation Is Significantly More Effective at Mitochondrial Segmentation Compared to Conventional Thres...
1.4.2 Validation of Machine-Learning Classifier
1.5 Benefits of a Software Macro
2 Materials
2.1 Primary Brown Adipocytes Culture
2.1.1 Primary Preadipocytes Isolated from BAT Growth Media
2.1.2 Primary Preadipocytes Differentiation Media to BA
2.1.3 Adenoviral Transduction to Deliver H2O2 Reporters
2.2 Microscopy
2.2.1 Basic Requirements of a Confocal Microscopy System
2.2.2 Basic Requirements of Images
2.2.3 Fluorophores and Imaging Settings
2.3 Analysis
2.3.1 Training a WEKA Classifier
2.3.2 Using a Macro
3 Methods
3.1 Primary Pre-adipocytes Transfer to an Imaging Plate
3.2 Transduction of BA with Adenovirus Encoding H2O2 Reporters
3.3 Microscopy
3.4 Image Analysis (See Note 12)
3.4.1 Brown Adipocyte (BA) Analysis
3.4.2 Using WEKA Classifiers
4 Notes
References
Chapter 23: Cell Energy Budget Platform for Multiparametric Assessment of Cell and Tissue Metabolism
1 Introduction
2 Materials
2.1 Critical Equipment
2.2 Cells and Reagents
2.3 Solutions
3 Methods
3.1 T-ECA and L-ECA Assays
3.2 OCR Assay
3.2.1 Rates of Cellular Oxygen Consumption
3.2.2 Conduction of Measurements Using Animal Tissue
3.3 ATP Analysis
3.4 Total Protein (Biomass) Analysis
3.5 Data Processing and CEB Analysis
3.6 Examples and Interpretation of CEB Data
3.7 Conclusions
4 Notes
References
Chapter 24: Fluorescence-Based Assay For Measuring OMA1 Activity
1 Introduction
2 Materials
2.1 Fluorogenic Reporter Peptide (AFRATDHG): Serves as the Substrate for the OMA1 Assay
2.2 Protein Sample/Unknown
2.3 TPEN (Used as an OMA1 Inhibitor)
2.4 OMA1 Buffer
2.5 96-Well Microplate
2.6 Plate Reader
3 Methods
3.1 Procedure
3.2 Analysis
4 Notes
References
Chapter 25: Studying Mitochondrial Network Formation by In Vivo and In Vitro Reconstitution Assay
1 Introduction
2 Materials
2.1 Observation of MNF in Cells
2.2 In Vitro Reconstitution System
2.2.1 Protein Purification
2.2.2 Mitochondria Isolation
2.2.3 In Vitro Reconstitution Assay
3 Methods
3.1 Cell Transfection and Observation
3.2 In Vitro Reconstitution System
3.2.1 Motor Protein Purification
3.2.2 Mitochondrial Isolation
3.2.3 Flow Chamber Assembly
3.2.4 Preparation of Polymerized Microtubule Filaments
3.2.5 Gliding Assays to Confirm the Activity of Purified Motor Proteins
3.2.6 In Vitro Reconstitution of MNF
4 Notes
References
Chapter 26: Extraction of Functional Mitochondria Based on Membrane Stiffness
1 Introduction
2 Materials
3 Methods
3.1 Design and Fabrication of the Microfluidics-Based Cell Shredder
3.2 Cell Culture
3.3 Cell Disruptions and Mitochondria Extraction
3.3.1 Optimization of Mitochondria Extraction by the Dounce Homogenizer
3.3.2 Optimization of Mitochondria Extraction by the Microscale Cell Shredder
3.4 Cell Disruption Efficiency Determined by Flow Cytometer
3.5 Determination of Total Protein Yield (Bradford Assay)
3.6 Characterization of Mitochondrial Membrane Potential
3.7 Characterization of Mitochondrial Integrity (Citrate Synthase Assay)
4 Notes
References
Chapter 27: A Protocol for Untargeted Metabolomic Analysis: From Sample Preparation to Data Processing
1 Introduction
2 Materials
3 Method
3.1 LC/MS Protocol
3.2 LC Method Setup
3.3 MS Method Setup
3.4 Acquisition Sequence Order
3.5 Biofluid Sample Preparation and Metabolite Extraction for Positively Charged Polar Metabolites
3.6 Data Analysis
4 Notes
Box 1 Definitions of Common Terms
References
Chapter 28: A Method for Analysis of Nitrotyrosine-Containing Proteins by Immunoblotting Coupled with Mass Spectrometry
1 Introduction
2 Materials
2.1 2D Electrophoresis
2.2 Immunoblotting
2.3 Staining
2.4 Chemiluminescence Detection
2.5 In-Gel Digestion and nLC-MS/MS Analysis
3 Methods
3.1 Sample Preparation and Isoelectric Focusing
3.2 SDS-PAGE
3.3 Immunoblotting and Chemiluminescence Detection
3.4 In-Gel Digestion
3.5 Analysis of Tryptic Digests from Spots with nLC-MS/MS
4 Notes
References
Chapter 29: In Vivo Visualization and Quantification of Mitochondrial Morphology in C. elegans
1 Introduction
2 Materials
3 Methods
3.1 Culture of C. elegans
3.2 Microscopy Slide Preparation
3.3 Imaging of Mitochondria
3.4 Automated Image Analysis (See Note 11)
3.5 Mitochondrial Quantification
4 Notes
References
Chapter 30: Assessing Impact of Platinum Complexes on Mitochondrial Functions
1 Introduction
2 Materials
2.1 Equipment
2.2 Primer
2.3 Solutions
2.4 Fluorescent Dyes
2.5 Cell Culture Components
3 Methods
3.1 Synthesis of TPP+-PtII (a)
3.2 Synthesis of TPP+-PtII (b)
3.3 Synthesis of TPP+-PtIV (a)
3.4 Synthesis of TPP+-PtIV (b)
3.5 Mitochondrial Uptake
3.6 Determination of Mitochondrial Superoxide (mtSOX)
3.7 Mitochondrial Membrane Potential (JC-1 Assay)
3.8 Mitochondrial Morphology
3.9 mtDNA Damage
3.10 Transcription of Mitochondrial Genes
3.11 Mitochondrial Bioenergetics
3.11.1 Oxygen Consumption Rate (OCR)
3.11.2 Extracellular Acidification Rate (ECAR)
3.12 Proteins Relevant to Mitochondrion-Mediated Apoptosis
4 Notes
References
Chapter 31: In Silico Modeling of the Mitochondrial Pumping Complexes with Markov State Models
1 Introduction
2 Ransac Model of the bc1 Complex
3 Markov State Models
4 States and Reactions
5 Estimation of Rate Constants
6 The Membrane Potential and Charge Transfer Reactions
7 Thermodynamics and Interactions
8 Simulations
9 Protein Conformation
References
Chapter 32: Monitoring the Mitochondrial Presequence Import Pathway In Living Mammalian Cells with a New Molecular Biosensor
1 Introduction
2 Materials
2.1 Recombinant Vectors
2.1.1 pCI-Neo Mammalian Expression Vectors Encoding Probes 1, 2, and 3
2.1.2 Recombinant Lentiviral Vector Encoding Probe 1
2.2 Materials and Reagents
2.2.1 Equipment and Cell Culture Material
2.2.2 Cell Culture Media, Buffers, Reagents
2.2.3 Transfection Reagents
2.2.4 Chemical Compounds
2.2.5 Immunocytochemistry
3 Methods
3.1 Cell Culture: Seeding, Transfection or Lentiviral Transduction, Induction of the Probes
3.1.1 HEK293T Cells
3.1.2 Human Primary Fibroblasts
3.1.3 Mouse Primary Cortical Neurons
3.2 Mitochondrial Import Reporter Assay
3.2.1 Induction of the Mitochondrial Import Probe
3.2.2 RGFP Fluorescence Assay
3.2.3 Luciferase Bioluminescence Reporter Assay (Rluc)
3.2.4 Analysis of the Results
4 Notes
References
Index

Citation preview

Methods in Molecular Biology 2276

Volkmar Weissig Marvin Edeas Editors

Mitochondrial Medicine Volume 2: Assessing Mitochondria Second Edition

METHODS

IN

MOLECULAR BIOLOGY

Series Editor John M. Walker School of Life and Medical Sciences University of Hertfordshire Hatfield, Hertfordshire, UK

For further volumes: http://www.springer.com/series/7651

For over 35 years, biological scientists have come to rely on the research protocols and methodologies in the critically acclaimed Methods in Molecular Biology series. The series was the first to introduce the step-by-step protocols approach that has become the standard in all biomedical protocol publishing. Each protocol is provided in readily-reproducible step-bystep fashion, opening with an introductory overview, a list of the materials and reagents needed to complete the experiment, and followed by a detailed procedure that is supported with a helpful notes section offering tips and tricks of the trade as well as troubleshooting advice. These hallmark features were introduced by series editor Dr. John Walker and constitute the key ingredient in each and every volume of the Methods in Molecular Biology series. Tested and trusted, comprehensive and reliable, all protocols from the series are indexed in PubMed.

Mitochondrial Medicine Volume 2: Assessing Mitochondria Second Edition

Edited by

Volkmar Weissig Department of Pharmaceutical Sciences, Midwestern University, Glendale, AZ, USA

Marvin Edeas Cochin Hospital, Cochin Institute, INSERM U1016, PARIS, France

Editors Volkmar Weissig Department of Pharmaceutical Sciences Midwestern University Glendale, AZ, USA

Marvin Edeas Cochin Hospital Cochin Institute, INSERM U1016 PARIS, France

ISSN 1064-3745 ISSN 1940-6029 (electronic) Methods in Molecular Biology ISBN 978-1-0716-1265-1 ISBN 978-1-0716-1266-8 (eBook) https://doi.org/10.1007/978-1-0716-1266-8 © Springer Science+Business Media, LLC, part of Springer Nature 2021 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Science+Business Media, LLC, part of Springer Nature. The registered company address is: 1 New York Plaza, New York, NY 10004, U.S.A.

Preface It is our distinct pleasure to present the second edition of MiMB Mitochondrial Medicine to the ever increasing number of scientists and physicians who are as fascinated by this tiny organelle as we are. We started working on the first edition in September 2014 and were able to bring about one year later two volumes with a total of 70 chapters to the market. As of today (July 2020), 195K downloads have been recorded for Volume I1 and 90K downloads for volume II2. In light of the rapidly growing and expanding field of Mitochondrial Medicine, we readily accepted the invitation to compile a second edition, which we started to work on in March 2019. This second edition as offered here involves a total of 88 chapters with 45 of them written by new contributors who were not part of our first edition. The first and second editions combined subsequently present work from 115 mitochondrial laboratories from around the globe. We therefore believe these five volumes combined to be the most comprehensive source of know-how in the wide-ranging field of Mitochondrial Medicine. Dividing 87 chapters equally over three volumes proved to be a bit challenging. We chose the subtitle Targeting Mitochondria for volume I, Assessing Mitochondria for volume II, and Manipulating Mitochondria and Disease Specific Approaches for volume III while of course being well aware of significant overlaps between these three areas of research. For example, it is quite obvious that mitochondria are being targeted for the purpose of either assessing them or to manipulate them. We therefore ask all authors not to be too critical regarding the placement of their particular chapter. The reader we believe will anyway choose to download a chapter of his/her interest quite independently of its placement in one of the three volumes. All chapters in these three volumes were written for graduate students, postdoctoral associates, independent investigators in academia and industry as well as physicians by leading experts in their particular field. We are extremely grateful to them for having found the time to either update their chapter from the first edition or to write a new chapter. We will not forget that for many if not all of our contributors the worldwide COVID-19 pandemic posed additional and unexpected hurdles towards finishing their manuscript in due time. Thank you to all! The idea for our original book proposal leading to the first edition of MiMB Mitochondrial Medicine originated in our efforts to organize a series of annual conferences on Targeting Mitochondria (www.targeting-mitochondria.com), the tenth one of which meanwhile has taken place in November 2019 in Berlin, Germany. Due to the ongoing pandemic, our 11th conference (October 29–30, 2020) will be a virtual one but we are sure it will not be less exciting than all the previous editions. Last but not least we would like to sincerely thank John Walker, the series editor of Methods in Molecular Biology, for having invited us to compile this second edition and for his

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https://link.springer.com/book/10.1007/978-1-4939-2257-4. https://link.springer.com/book/10.1007/978-1-4939-2288-8.

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unlimited guidance and help throughout the entire process. We also owe sincere thanks to Patrick Marton, the Executive Editor of the Springer Protocol Series, for always having been available in assisting us throughout the entire project. Glendale, AZ, USA Paris, France

Volkmar Weissig Marvin Edeas

Contents Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Contributors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1 Mitochondrial Dysfunction in Mitochondrial Medicine: Current Limitations, Pitfalls, and Tomorrow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Naig Gueguen, Guy Lenaers, Pascal Reynier, Volkmar Weissig, and Marvin Edeas 2 Preparation of “Functional” Mitochondria: A Challenging Business. . . . . . . . . . . Stefan Lehr, Sonja Hartwig, and Jorg Kotzka 3 Isolation and Quality Control of Functional Mitochondria . . . . . . . . . . . . . . . . . . . Sonja Hartwig, Jorg Kotzka, and Stefan Lehr 4 Purification of Functional Platelet Mitochondria Using a Discontinuous Percoll Gradient . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jacob L. Le´ger, Nicolas Pichaud, and Luc H. Boudreau 5 Mechanical Permeabilization as a New Method for Assessment of Mitochondrial Function in Insect Tissues. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Alessandro Gaviraghi, Yan Aveiro, Stephanie S. Carvalho, Rodiesley S. Rosa, Matheus P. Oliveira, and Marcus F. Oliveira 6 Analysis of Mitochondrial Retrograde Signaling in Yeast Model Systems . . . . . . . Nicoletta Guaragnella, Masˇa Zˇdralevic´, Zdena Palkova´, and Sergio Giannattasio 7 Native Gel Electrophoresis and Immunoblotting to Analyze Electron Transport Chain Complexes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gisela Beutner and George A. Porter Jr. 8 Measuring Mitochondrial Hydrogen Peroxide Levels and Glutathione Redox Equilibrium in Drosophila Neuron Subtypes Using Redox-Sensitive Fluorophores and 3D Imaging. . . . . . . . . . . . . . . . . . . . . . . Lori M. Buhlman, Petros P. Keoseyan, Kathryn Houlihan, and Amber N. Juba 9 Assessment of Mitochondrial Cell Metabolism by Respiratory Chain Electron Flow Assays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Flavia Radogna, De´borah Ge´rard, Mario Dicato, and Marc Diederich 10 Whole-Cell and Mitochondrial dNTP Pool Quantification from Cells and Tissues. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Juan C. Landoni, Liya Wang, and Anu Suomalainen 11 Single-Particle Tracking Method in Fluorescence Microscopy to Monitor Bioenergetic Responses of Individual Mitochondria . . . . . . . . . . . . . . Camille Colin, Emmanuel Suraniti, Emma Abell, Audrey Se´mont, Neso Sojic, Philippe Diolez, and Ste´phane Arbault

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Investigation of Mitochondrial ADP-Ribosylation Via Immunofluorescence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ann-Katrin Hopp and Michael O. Hottiger Assessment of Mitochondrial Ca2+ Uptake . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Andra´s T. Deak, Claire Jean-Quartier, Alexander I. Bondarenko, Lukas N. Groschner, Roland Malli, Wolfgang F. Graier, and Markus Waldeck-Weiermair Assessment of Mitochondrial Membrane Potential and NADH Redox State in Acute Brain Slices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Andrey Y. Vinokurov, Viktor V. Dremin, Gennadii A. Piavchenko, Olga A. Stelmashchuk, Plamena R. Angelova, and Andrey Y. Abramov Evaluation of Mitochondria Content and Function in Live Cells by Multicolor Flow Cytometric Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hsiu-Han Fan, Tsung-Lin Tsai, Ivan L. Dzhagalov, and Chia-Lin Hsu Analysis of Mitochondrial Dysfunction During Cell Death . . . . . . . . . . . . . . . . . . . Vladimir Gogvadze and Boris Zhivotovsky Modified Blue Native Gel Approach for Analysis of Respiratory Supercomplexes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sergiy M. Nadtochiy, Megan Ngai, and Paul S. Brookes Patch-Clamp Recording of the Activity of Ion Channels in the Inner Mitochondrial Membrane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Piotr Bednarczyk, Rafał P. Kampa, Shur Gałecka, Aleksandra Se˛k, Agnieszka Walewska, and Piotr Koprowski Assessment of Mitochondrial Protein Glutathionylation as Signaling for CO Pathway . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ana S. Almeida, Cla´udia Figueiredo-Pereira, and Helena L. A. Vieira 3D Optical Cryo-Imaging Method: A Novel Approach to Quantify Renal Mitochondrial Bioenergetics Dysfunction . . . . . . . . . . . . . . . . . Shima Mehrvar, Amadou K. S. Camara, and Mahsa Ranji Simultaneous Quantification of Mitochondrial ATP and ROS Production Using ATP Energy Clamp Methodology . . . . . . . . . . . . . . . . . . . . . . . . Liping Yu, Brian D. Fink, and William I. Sivitz High-Throughput Image Analysis of Lipid-Droplet-Bound Mitochondria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nathanael Miller, Dane Wolf, Nour Alsabeeh, Kiana Mahdaviani, Mayuko Segawa, Marc Liesa, and Orian S. Shirihai Cell Energy Budget Platform for Multiparametric Assessment of Cell and Tissue Metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dmitri B. Papkovsky and Alexander V. Zhdanov Fluorescence-Based Assay For Measuring OMA1 Activity. . . . . . . . . . . . . . . . . . . . Julia Tobacyk and Lee Ann MacMillan-Crow Studying Mitochondrial Network Formation by In Vivo and In Vitro Reconstitution Assay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Wanqing Du, Xiangjun Di, and Qian Peter Su

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Extraction of Functional Mitochondria Based on Membrane Stiffness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Md Habibur Rahman, Qinru Xiao, Shirui Zhao, An-Chi Wei, and Yi-Ping Ho A Protocol for Untargeted Metabolomic Analysis: From Sample Preparation to Data Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Amanda L. Souza and Gary J. Patti A Method for Analysis of Nitrotyrosine-Containing Proteins by Immunoblotting Coupled with Mass Spectrometry . . . . . . . . . . . . . . . . . . . . . . Matej Kohutiar and Adam Eckhardt In Vivo Visualization and Quantification of Mitochondrial Morphology in C. elegans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R. de Boer, R. L. Smith, W. H. De Vos, E. M. M. Manders, and H. van der Spek Assessing Impact of Platinum Complexes on Mitochondrial Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Suxing Jin and Xiaoyong Wang In Silico Modeling of the Mitochondrial Pumping Complexes with Markov State Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Roger Springett Monitoring the Mitochondrial Presequence Import Pathway In Living Mammalian Cells with a New Molecular Biosensor. . . . . . . . . . . . . . . . . Maxime Jacoupy, Emeline Hamon-Keromen, and Olga Corti

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Contributors EMMA ABELL • Univ. Bordeaux, INSERM, Centre de recherche Cardio- Thoracique de Bordeaux, U1045 & IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Universite´, Bordeaux, France; CHU de Bordeaux, Bordeaux, France ANDREY Y. ABRAMOV • Orel State University, Orel, Russia; UCL Queen Square Institute of Neurology, London, UK ANA S. ALMEIDA • CEDOC, Faculdade de Cieˆncia Me´dicas/NOVA Medical School, Universidade Nova de Lisboa, Lisboa, Portugal NOUR ALSABEEH • Department of Physiology, Faculty of Medicine, Kuwait University, Kuwait City, Kuwait PLAMENA R. ANGELOVA • UCL Queen Square Institute of Neurology, London, UK STE´PHANE ARBAULT • NSysA group, Univ. Bordeaux, CNRS, INP Bordeaux, ISM, UMR 5255, Talence, France YAN AVEIRO • Federal University of Rio de Janeiro, Institute of Medical Biochemistry Leopoldo de Meis, Rio De Janeiro, RJ, Brazil PIOTR BEDNARCZYK • Department of Physics and Biophysics, Institute of Biology, Warsaw University of Life Sciences—SGGW, Warsaw, Poland GISELA BEUTNER • Department of Pediatrics-Division Cardiology, University of Rochester, Rochester, NY, USA ALEXANDER I. BONDARENKO • Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, Graz, Austria LUC H. BOUDREAU • Department of Chemistry and Biochemistry, Universite de Moncton, Moncton, NB, Canada PAUL S. BROOKES • Department of Anesthesiology, University of Rochester Medical Center, Rochester, NY, USA LORI M. BUHLMAN • Arizona College of Graduate Studies, Midwestern University, Glendale, AZ, USA AMADOU K. S. CAMARA • Department of Anesthesiology and Anesthesia Research, Medical College of Wisconsin, Wauwatosa, WI, USA STEPHANIE S. CARVALHO • Federal University of Rio de Janeiro, Institute of Medical Biochemistry Leopoldo de Meis, Rio De Janeiro, RJ, Brazil CAMILLE COLIN • NSysA group, Univ. Bordeaux, CNRS, INP Bordeaux, ISM, UMR 5255, Talence, France; Univ. Bordeaux, INSERM, Centre de recherche Cardio- Thoracique de Bordeaux, U1045 & IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Universite´, Bordeaux, France; CHU de Bordeaux, Bordeaux, France OLGA CORTI • Sorbonne Universite´, Institut du Cerveau (ICM), Inserm U1127, CNRS UMR 7225, Paris, France R. DE BOER • Molecular Biology & Microbial Food Safety, Swammerdam Institute for Life Sciences (SILS), Faculty of Science (FNWI), University of Amsterdam, Amsterdam, The Netherlands W. H. DE VOS • Laboratory of Cell Biology and Histology, Department of Veterinary Sciences, Antwerp University, Antwerp, Belgium; Cell Systems and Imaging Research Group, Department of Molecular Biotechnology, Ghent University, Ghent, Belgium

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Contributors

ANDRA´S T. DEAK • Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, Graz, Austria XIANGJUN DI • Institute for Biomedical Materials & Devices (IBMD), Faculty of Science, University of Technology Sydney, Sydney, NSW, Australia MARIO DICATO • Laboratoire de Biologie Mole´culaire et Cellulaire du Cancer, Hoˆpital Kirchberg, Luxembourg, Luxembourg MARC DIEDERICH • College of Pharmacy, Seoul National University, Seoul, South Korea PHILIPPE DIOLEZ • Univ. Bordeaux, INSERM, Centre de recherche Cardio- Thoracique de Bordeaux, U1045 & IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Universite´, Bordeaux, France; CHU de Bordeaux, Bordeaux, France VIKTOR V. DREMIN • Orel State University, Orel, Russia; Aston University, Birmingham, UK WANQING DU • State Key Laboratory of Membrane Biology, Tsinghua University-Peking University Joint Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing, China IVAN L. DZHAGALOV • Institute of Microbiology and Immunology, National Yang-Ming University, Taipei, Taiwan ADAM ECKHARDT • Department of Translational Metabolism, Institute of Physiology, Academy of Sciences of the Czech Republic, Prague, Czech Republic MARVIN EDEAS • Universite´ de Paris, INSERM U1016, Institut Cochin, CNRS UMR8104, Paris, France; Laboratory of Excellence GR-Ex, Paris, France HSIU-HAN FAN • Institute of Microbiology and Immunology, National Yang-Ming University, Taipei, Taiwan CLA´UDIA FIGUEIREDO-PEREIRA • CEDOC, Faculdade de Cieˆncia Me´dicas/NOVA Medical School, Universidade Nova de Lisboa, Lisboa, Portugal BRIAN D. FINK • Division of Endocrinology and Metabolism, Department of Internal Medicine, The University of Iowa, Iowa City, IA, USA SHUR GAŁECKA • Laboratory of Intracellular Ion Channels, Nencki Institute of Experimental Biology, Warsaw, Poland ALESSANDRO GAVIRAGHI • Federal University of Rio de Janeiro, Institute of Medical Biochemistry Leopoldo de Meis, Rio De Janeiro, RJ, Brazil DE´BORAH GE´RARD • Laboratoire de Biologie Mole´culaire et Cellulaire du Cancer, Hoˆpital Kirchberg, Luxembourg, Luxembourg SERGIO GIANNATTASIO • Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, CNR, Bari, Italy VLADIMIR GOGVADZE • Division of Toxicology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Faculty of Medicine, MV Lomonosov Moscow State University, Moscow, Russia WOLFGANG F. GRAIER • Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, Graz, Austria LUKAS N. GROSCHNER • Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, Graz, Austria NICOLETTA GUARAGNELLA • Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, CNR, Bari, Italy; Department of Biosciences, Biotechnology and Biopharmaceutics, University of Bari “A. Moro”, Bari, Italy

Contributors

xiii

NAIG GUEGUEN • UMR CNRS 6015-INSERM U1083, MitoVasc Institute, University of Angers, Angers, France; Department of Biochemistry and Genetics, University Hospital of Angers, Angers, France EMELINE HAMON-KEROMEN • Sorbonne Universite´, Institut du Cerveau (ICM), Inserm U1127, CNRS UMR 7225, Paris, France SONJA HARTWIG • Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center at the Heinrich-Heine-University Duesseldorf, Leibniz Center for Diabetes Research, Duesseldorf, Germany; German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany YI-PING HO • Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China; Centre for Novel Biomaterials, The Chinese University of Hong Kong, Hong Kong SAR, China; Shun Hing Institute of Advanced Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China; The Ministry of Education Key Laboratory of Regeneration Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China ANN-KATRIN HOPP • Department of Molecular Mechanisms of Disease (DMMD), University of Zurich, Zurich, Switzerland MICHAEL O. HOTTIGER • Department of Molecular Mechanisms of Disease (DMMD), University of Zurich, Zurich, Switzerland KATHRYN HOULIHAN • Arizona College of Graduate Studies, Midwestern University, Glendale, AZ, USA CHIA-LIN HSU • Institute of Microbiology and Immunology, National Yang-Ming University, Taipei, Taiwan MAXIME JACOUPY • Sorbonne Universite´, Institut du Cerveau (ICM), Inserm U1127, CNRS UMR 7225, Paris, France CLAIRE JEAN-QUARTIER • Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, Graz, Austria SUXING JIN • State Key Laboratory of Coordination Chemistry, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, P. R. China AMBER N. JUBA • Arizona College of Graduate Studies, Midwestern University, Glendale, AZ, USA RAFAŁ P. KAMPA • Department of Physics and Biophysics, Institute of Biology, Warsaw University of Life Sciences—SGGW, Warsaw, Poland; Laboratory of Intracellular Ion Channels, Nencki Institute of Experimental Biology, Warsaw, Poland PETROS P. KEOSEYAN • Arizona College of Osteopathic Medicine, Midwestern University, Glendale, AZ, USA MATEJ KOHUTIAR • Department of Medical Chemistry and Clinical Biochemistry, 2nd Faculty of Medicine, Charles University in Prague and Motol University Hospital, Prague, Czech Republic PIOTR KOPROWSKI • Laboratory of Intracellular Ion Channels, Nencki Institute of Experimental Biology, Warsaw, Poland JORG KOTZKA • Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center at the Heinrich-Heine-University Duesseldorf, Leibniz Center for Diabetes Research, Duesseldorf, Germany; German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany JUAN C. LANDONI • Research Programs Unit, Stem Cells and Metabolism, University of Helsinki, Helsinki, Finland

xiv

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JACOB L. LE´GER • Department of Chemistry and Biochemistry, Universite de Moncton, Moncton, NB, Canada STEFAN LEHR • Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center at the Heinrich-Heine-University Duesseldorf, Leibniz Center for Diabetes Research, Duesseldorf, Germany; German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany GUY LENAERS • UMR CNRS 6015-INSERM U1083, MitoVasc Institute, University of Angers, Angers, France MARC LIESA • Division of Endocrinology, Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA LEE ANN MACMILLAN-CROW • Department of Pharmacology and Toxicology, University of Arkansas for Medical Sciences, Little Rock, AR, USA KIANA MAHDAVIANI • Department of Medicine, Obesity Research Center, Boston University School of Medicine, Boston, MA, USA ROLAND MALLI • Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, Graz, Austria E. M. M. MANDERS • van Leeuwenhoek Center for Advanced Microscopy, University of Amsterdam, Amsterdam, The Netherlands SHIMA MEHRVAR • University of Wisconsin-Milwaukee, Milwaukee, WI, USA NATHANAEL MILLER • Division of Endocrinology, Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Medicine, Obesity Research Center, Boston University School of Medicine, Boston, MA, USA SERGIY M. NADTOCHIY • Department of Neuroscience, University of Rochester Medical Center, Rochester, NY, USA; Department of Anesthesiology, University of Rochester Medical Center, Rochester, NY, USA MEGAN NGAI • Department of Anesthesiology, University of Rochester Medical Center, Rochester, NY, USA MARCUS F. OLIVEIRA • Federal University of Rio de Janeiro, Institute of Medical Biochemistry Leopoldo de Meis, Rio De Janeiro, RJ, Brazil MATHEUS P. OLIVEIRA • Federal University of Rio de Janeiro, Institute of Medical Biochemistry Leopoldo de Meis, Rio De Janeiro, RJ, Brazil ZDENA PALKOVA´ • Faculty of Science, Charles University, BIOCEV, Prague, Czech Republic DMITRI B. PAPKOVSKY • School of Biochemistry and Cell Biology, University College Cork, Cork, Ireland GARY J. PATTI • Department of Chemistry, Washington University in St. Louis, Saint Louis, MO, USA; Department of Medicine, Washington University in St. Louis, Saint Louis, MO, USA GENNADII A. PIAVCHENKO • Orel State University, Orel, Russia; I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia NICOLAS PICHAUD • Department of Chemistry and Biochemistry, Universite de Moncton, Moncton, NB, Canada GEORGE A. PORTER JR. • Departments of Pediatrics-Division Cardiology, Pharmacology and Physiology, and Medicine (Aab Cardiovascular Research Institute), University of Rochester, Rochester, NY, USA FLAVIA RADOGNA • Laboratoire de Biologie Mole´culaire et Cellulaire du Cancer, Hoˆpital Kirchberg, Luxembourg, Luxembourg

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MD HABIBUR RAHMAN • Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China; Centre for Novel Biomaterials, The Chinese University of Hong Kong, Hong Kong SAR, China MAHSA RANJI • Biophotonics Lab, Florida Atlantic University, Boca Raton, FL, USA PASCAL REYNIER • UMR CNRS 6015-INSERM U1083, MitoVasc Institute, University of Angers, Angers, France; Department of Biochemistry and Genetics, University Hospital of Angers, Angers, France RODIESLEY S. ROSA • Federal University of Rio de Janeiro, Institute of Medical Biochemistry Leopoldo de Meis, Rio De Janeiro, RJ, Brazil MAYUKO SEGAWA • Division of Endocrinology, Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA ALEKSANDRA SE˛K • Laboratory of Intracellular Ion Channels, Nencki Institute of Experimental Biology, Warsaw, Poland; Faculty of Chemistry, University of Warsaw, Warsaw, Poland AUDREY SE´MONT • Univ. Bordeaux, INSERM, Centre de recherche Cardio- Thoracique de Bordeaux, U1045 & IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Universite´, Bordeaux, France; CHU de Bordeaux, Bordeaux, France ORIAN S. SHIRIHAI • Division of Endocrinology, Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA WILLIAM I. SIVITZ • Division of Endocrinology and Metabolism, Department of Internal Medicine, The University of Iowa, Iowa City, IA, USA R. L. SMITH • Academisch Medisch Centrum Universiteit van, Amsterdam, The Netherlands NESO SOJIC • NSysA group, Univ. Bordeaux, CNRS, INP Bordeaux, ISM, UMR 5255, Talence, France AMANDA L. SOUZA • Life Science Mass Spectrometry Division, Thermo Fisher Scientific, San Jose, CA, USA ROGER SPRINGETT • CellSpex, Kent, UK OLGA A. STELMASHCHUK • Orel State University, Orel, Russia QIAN PETER SU • Institute for Biomedical Materials & Devices (IBMD), Faculty of Science, University of Technology Sydney, Sydney, NSW, Australia; School of Biomedical Engineering, Faculty of Engineering and IT, University of Technology Sydney, Sydney, NSW, Australia ANU SUOMALAINEN • Department of Neurology, University Hospital, Helsinki, Finland; Neuroscience Center, University of Helsinki, Helsinki, Finland EMMANUEL SURANITI • NSysA group, Univ. Bordeaux, CNRS, INP Bordeaux, ISM, UMR 5255, Talence, France JULIA TOBACYK • Department of Pharmacology and Toxicology, University of Arkansas for Medical Sciences, Little Rock, AR, USA TSUNG-LIN TSAI • Institute of Microbiology and Immunology, National Yang-Ming University, Taipei, Taiwan H. VAN DER SPEK • Molecular Biology & Microbial Food Safety, Swammerdam Institute for Life Sciences (SILS), Faculty of Science (FNWI), University of Amsterdam, Amsterdam, The Netherlands HELENA L. A. VIEIRA • CEDOC, Faculdade de Cieˆncia Me´dicas/NOVA Medical School, Universidade Nova de Lisboa, Lisboa, Portugal; UCIBIO, Faculdade de Cieˆncias e Tecnologia, Universidade Nova de Lisboa, Lisboa, Portugal; Instituto de Biologia Experimental e Tecnologica (iBET), Oeiras, Portugal ANDREY Y. VINOKUROV • Orel State University, Orel, Russia

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Contributors

MARKUS WALDECK-WEIERMAIR • Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, Graz, Austria AGNIESZKA WALEWSKA • Laboratory of Intracellular Ion Channels, Nencki Institute of Experimental Biology, Warsaw, Poland LIYA WANG • Department of Anatomy, Physiology and Biochemistry, Swedish University of Agricultural Sciences, Uppsala, Sweden XIAOYONG WANG • State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, P. R. China AN-CHI WEI • Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan VOLKMAR WEISSIG • Department of Pharmaceutical Sciences and Nanocenter of Excellence, Midwestern University College of Pharmacy at Glendale, Glendale, AZ, USA DANE WOLF • Division of Endocrinology, Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Medicine, Obesity Research Center, Boston University School of Medicine, Boston, MA, USA QINRU XIAO • Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China LIPING YU • Division of Endocrinology and Metabolism, Department of Internal Medicine, The University of Iowa, Iowa City, IA, USA ˇ DRALEVIC´ • Faculty of Medicine, University of Montenegro, Podgorica, Montenegro MASˇA Z SHIRUI ZHAO • Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China; Shun Hing Institute of Advanced Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China ALEXANDER V. ZHDANOV • School of Biochemistry and Cell Biology, University College Cork, Cork, Ireland BORIS ZHIVOTOVSKY • Division of Toxicology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Faculty of Medicine, MV Lomonosov Moscow State University, Moscow, Russia

Chapter 1 Mitochondrial Dysfunction in Mitochondrial Medicine: Current Limitations, Pitfalls, and Tomorrow Naig Gueguen, Guy Lenaers, Pascal Reynier, Volkmar Weissig, and Marvin Edeas Abstract Until recently restricted to hereditary mitochondrial diseases, mitochondrial dysfunction is now recognized as a key player and strategic factor in the pathophysiological of many human diseases, ranging from the metabolism, vascular, cardiac, and neurodegenerative diseases to cancer. Because of their participation in a myriad of cellular functions and signaling pathways, precisely identifying the cause of mitochondrial “dysfunctions” can be challenging and requires robust and controlled techniques. Initially limited to the analysis of the respiratory chain functioning, these analytical techniques now enlarge to the analyses of mitochondrial and cellular metabolism, based on metabolomic approaches. Here, we address the methods used to assay mitochondrial dysfunction, with a highlight on the techniques used in diagnosis on tissues and cells derived from patients, the information they provide, and their strength and weakness. Targeting mitochondrial dysfunction by various strategies is a huge challenge, requires robust methods of evaluation, and should be able to take into consideration the mitochondria dynamics and localization. The future of mitochondrial medicine is strongly related to a perfect comprehension of its dysfunction. Key words Mitochondrial Metabolomics

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dysfunctions,

Mitochondria

evaluation,

Bioenergetics,

Devices,

Introduction The contribution of mitochondrial dysfunctions in the onset and development of many diseases has been widely studied. These dysfunctions could interfere with many cellular, metabolic, and homoeostatic functions [1]. It is therefore not surprising that, beyond primary mitochondrial disorders, mitochondrial dysfunctions now impact most areas of medical. Mitochondrial dysfunction has been found in numerous common human diseases, including metabolic diseases [2] such as obesity and diabetes, heart diseases [3], neurodegenerative diseases, such as Parkinson’s, Alzheimer’s

Volkmar Weissig and Marvin Edeas (eds.), Mitochondrial Medicine: Volume 2: Assessing Mitochondria, Methods in Molecular Biology, vol. 2276, https://doi.org/10.1007/978-1-0716-1266-8_1, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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[4], or Huntington’s [5], infectious diseases [6], inflammation [7], and cancer [8]. Multiple reports have shown the impact of dysfunctional mitochondria on the immune response. One of the example is the COVID-19 pandemic caused by the coronavirus (SARS-CoV-2). Many recent studies revealed that human alveolar epithelial cells with dysfunctional mitochondria displayed increased production of pro-inflammatory cytokines which were found to be increased in COVID-19 [9, 10]. Recently, we proposed that not only the intracellular mitochondria dysfunction is a consequence of COVID-19 infection formation [6, 11] but also the less explored extracellular mitochondria (specifically platelets mitochondria) may affect blood coagulation, clot, and thrombosis formation [10– 15]. These extracellular mitochondria may represent a crucial intercellular mediators and may serve as strategic therapeutic targets in COVID-19 pathogenesis [11]. Historically, mitochondrial diseases have been largely addressed from the point of view of the defect of the respiratory chain and therefore of a defect in energetic homeostasis. However, mitochondria are now recognized to perform multiple additional cellular functions beyond energy production. For example, electron transfer chain (ETC) activity regulates the NADH/NAD+ redox state through NADH oxidation by complex I, [16] which impacts to hundreds of cellular reactions [17, 18]. Mitochondria are the major source of reactive oxygen species (ROS) [19], which not only contribute to normal cell function but also are linked to increased intracellular oxidative stress. ROS production regulates different signaling pathways, from metabolic rewiring to inflammatory response or cell survival [20, 21]. Mitochondria also integrate main cellular catabolic and anabolic pathways. They host not only whole or partial components of several converging catabolic cellular processes, i.e., glucose metabolism and the tricarboxylic acid (TCA) cycle, and the β-oxidation but also several biosynthetic pathways, such as folate and sulfur metabolism or heme biosynthesis. In addition to generating reducing equivalents that feed the OXPHOS system, the TCA cycle has numerous anabolic roles, providing precursors for the lipids, proteins, carbohydrates, and nucleotides biosynthesis [22]. TCA cycle metabolites also act as signaling molecules, affecting critical cellular processes that contribute to oncogenic transformation, such as nutrient signaling, HIF1α-dependent metabolic reprogramming, or histone acetylation and demethylation by acetyl-CoA and α-ketoglutarate, respectively [23]. Mitochondria are also involved in calcium homoeostasis [24], stress response and quality control [25], and initiation of caspase-dependent apoptosis [26]. Developing precise technologies to study mitochondrial physiology is getting much more important as the prevalence of common and inherited mitochondrial disease increases. Targeting

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mitochondrial dysfunction by various strategies is a huge challenge and need a robust methods of evaluation [27]. Here, we address the techniques commonly used in clinical diagnosis, the information that can be inferred from them, their limitations, pits, and pitfalls.

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Methods to Assess Mitochondrial Dysfunctions

2.1 Basis in Bioenergetic

Principles of mitochondrial bioenergetics have been largely reviewed over years [28]; therefore, only a rapid overview will be given here. Mitochondria are surrounded by the outer (OMM) and inner (IMM) membrane. The inner membrane is largely impermeant and constitutes the major barrier between the cytosol and the mitochondrial matrix. IMM forms multiple cristae, which host the ETC complexes and the enzymes involved in ATP synthesis, the F0F1-ATP synthase, the adenine nucleotide translocator (ANT), and the inorganic phosphate (Pi) transporter (PiC). The ETC system is composed of multisubunits enzymes functionally and physically linked together, the complex I (CI, NADH ubiquinone reductase), complex II (CII, succinate ubiquinone reductase), complex III (CIII, ubiquinol cytochrome c reductase), and complex IV (CIV, cytochrome c oxidase), which transfers the electron energetic potential from NADH/NAD+ (CI) and FADH2/FAD+ (CII) to the electrochemical proton gradient known as the protonmotive force (Δp). This process involved a series of oxidoreductase reactions in which electrons flow sequentially “downhill” along the ETC from a reduced to an oxidized state, ending to molecular oxygen reduction to a water molecule, or “respiration.” The release of free energy during electron transfer drives the proton pumping across the IMM at complexes CI, CIII, and CIV, in turn producing the Δp. Other oxidoreductases of the ETC are unable of proton pumping, particularly the complex II, the glycerol phosphate dehydrogenase, and the electrontransferring flavoprotein quinone oxidoreductase (ETF) linked to fatty acid β-oxidation. Thus, ten protons are extruded for each electron pair transferred from NADH to oxygen, or six protons for each electron pair transferred from FADH2 to O2, meaning that the H+/O2 and ATP/O2 stoichiometries differ according to the initial substrates. The fueling of reducing molecules, namely NADH and FADH2, to the ETC is mainly ensured by the TCA cycle and the β-oxidation pathways. According to the anaplerotic routes which feed TCA or the relative contribution of TCA or β-oxidation, the resulting NADH/FADH2 ratio differs, ultimately modifying the efficiency of ATP synthesis. The substrate oxidation module consists of all these reactions involved in substrate metabolisms and electron transport, finally generating Δp.

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The Δp is composed of the charge (Δψm) and chemical (ΔpH) components. The energy available in Δp drives the synthesis and transport of ATP, as the protons return to the matrix through the ATP synthase [29]. The ATP synthesis module includes, in addition to the ATP synthetase, the ANT that exchange the ADP/ATP and the PiC. The Δp is central to the physiological functions of mitochondria, connecting the substrate oxidation module to the ATP synthesis. Under most circumstances, proton flux is tightly coupled to OXPHOS. However, the Δp can also be dissipated by proton leak [30], in which protons return into the matrix independently of ATP synthesis, or be used for transport processes across the IMM of metabolite, ions, or calcium [31]. The total proton entry and extrusion are exactly balanced under steady-state conditions. Forward flux through ETC complexes requires a thermodynamic disequilibrium, i.e., the free energy available from electron transfer must be greater than that required to pump protons against the Δp. The Δp variations thus “dictate” the ETC activity: any decrease in the Δp is followed by an increase in electron transfer and proton pumping. In other words, the net flux of the proton current is reflected by the rate of mitochondrial oxygen consumption. Decrease in the Δp results from either proton leak or ATP synthesis, which is regulated by the cellular ATP demand. Any alteration in one the above described processes leads to a mitochondrial dysfunction. Subsequently, we shall describe the conventional methods for dissecting these processes, and identifying the primary site of impairment, starting with the methods used in the laboratory for the biochemical diagnosis of mitochondrial diseases. A complete set of these analyses will draw a picture of the mitochondrial energy-generating system. 2.2 Analyses of Maximal ETC Activities

Evaluation of individual respiratory chain complex activities is a routine biochemical approach for the diagnosis of mitochondrial disorders. Assays to quantify CI, CII, CIII, CIV, and ATP synthase enzymatic activities are performed either on tissue, mostly muscle or liver biopsies, or on cells as primary fibroblasts or lymphocytes. They require the preparation of tissue homogenates, after the elimination of cell debris and nuclei, or cell lysates, from either fresh or frozen sample. However, frozen samples are more commonly used because fresh samples must be processed immediately after sampling. Isolated activity of each complex can be analyzed by following the oxidation/reduction of specific substrates or substrate analogs by spectrophotometry. The spectrophotometric enzyme assays are: l

NADH:ubiquinone oxidoreductase (NUR, EC 7.1.1.2, NADH oxidation followed at 340 nm) for CI.

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l

Succinate:ubiquinone oxidoreductase (coupled to 2,6-Dichloroindophenol reduction followed at 600 nm) for CII (SUR, EC 1.3.5.1).

l

Succinate:cytochrome c oxidoreductase (CII + CIII, cytochrome c reduction at 550 nm).

l

Ubiquinol cytochrome c oxidoreductase for CIII (UCCR, EC 1.10.2.2, cytochrome c reduction at 550 nm).

l

Cytochrome c oxidase for CV (COX, EC 1.9.3.1, cytochrome c oxidation at 550 nm).

The measurement of complex V (oligomycin-sensitive ATPase) is more challenging and requires mitochondrial-enriched fractions and is often measured in cultured skin fibroblasts. Citrate synthase activity is often used for normalization of respiratory chain complex activities to mitochondrial mass. The activities normalized to CS and/or the ratios between mitochondrial enzymes give a much narrower range of normal values compared to activities expressed with respect to sample protein content, since the mitochondrial mass are highly variable among individuals and subjected to mitochondrial biogenesis regulation. While the principles of the different protocols are similar, nowadays, there is no universal assay for spectrophotometric quantification of ETC enzyme activities. According to laboratories, assays differ with respect to buffer conditions, reaction temperatures, substrate concentrations, supplementation in Ca2+ chelator (EDTA), or addition of bovine serum albumin. However, in an attempt to facilitate interlaboratory comparison of the results, some reference centers for the diagnosis of mitochondrial diseases have reevaluated and standardized their protocols [32]. Accurate enzymatic testing of tissue and cell samples can be hampered by different pitfalls. A frequent cause for problems is sample collection and handling. For optimal preservation of mitochondrial enzymes, samples must be immediately snap-frozen after collection and stored at 80  C, without any thawing until analysis. Other artifacts come from local anesthetic contamination of the sample, particularly lidocaine [32, 33], or, for studies on animals, from euthanasia procedures using CO2. Furthermore, one of the main difficulties in achieving reliable and reproducible dosages is the quality of the reagents, with strong variability between reactive references or even batches of reactive. Thus, these dosages require the inclusion of quality controls in each series, in order to validate the reaction mix. This quality is usually obtained from culture cells or animal tissue [34, 35], since the human tissues are limited. In addition, assays that determine the amounts of OXPHOS complexes, such as blue native (BN) gel electrophoresis followed by Western blot analysis, should be performed to decipher an ETC defect related to decreased catalytic activity or involving a lower enzyme quantity.

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2.3 Structural Analyses: BN-PAGE

ETC enzymes are all multimeric and encoded by both the mtDNA and nDNA, except for complex II that is fully encoded by the nuclear genome. Their assembly into a functional complex requires an intricate process assisted by chaperones [36]. Nowadays, the mechanisms of assembly for each complex are almost completely resolved [36, 37]. These assembly processes require the striking coordination of intra- and extramitochondrial transcription, translation, protein import into mitochondria, and protein folding and incorporation into assembly intermediates, up to the final complex assembly. Any disturbance in one of these processes would alter complexes assembly and compromised ETC function and energy production. Mutations that impair this assembly process are a frequent cause of mitochondrial inherited diseases [38, 39]. Complex misassembly is not only associated with an increasing number of mutations in ETC subunit genes or chaperones [40] but CI misassembly has also been recently observed in neurodegenerative diseases such as Alzheimer’s and Parkinson’s diseases [41], thus broadening the spectrum of assembly defect-associated diseases, and could be implied in the ageing process [42]. Finally, assembly of CI, III, and IV together leads to respiratory super complexes, adding a layer of complexity in the structural organization of the respiratory chain. The crystal structure of the super complex has recently been elucidated [43]. Although the pathways that lead to their formation and their function are still not completely clear [37, 44], they are now recognized as the final functional ETC unit, or “respirasome.” “Blue Native” polyacrylamide gel electrophoresis (BN-PAGE) [45] is a relatively easy approach for analyzing the assembly and abundance of OXPHOS complexes for the diagnosis of mitochondrial diseases [46, 47]. The assembly profile provides information for identifying disease-causing mutations and facilitates molecular investigation by highlighting potentially involved subunits [39, 48]. BN-PAGE is performed on isolated mitochondria or enrichedmitochondrial fractions from either tissues or cells. The protocols are described in the literature [46, 47, 49]. However, it should be stressed that results depend on the choice and concentration of the detergent and on the choice of the antibodies. After mitochondrial isolation, the mitochondrial membranes are solubilized using nonionic detergent. Because mitochondrial membranes have low cholesterol but high cardiolipin contents, [50], digitonin is preferentially used for super complexes analysis while β-dodecylmaltoside should be used for isolated complex visualization. However, both the concentration and the detergent to protein ratio must be carefully optimized to ensure that detergent concentration is above critical micelle concentration but below the detergent:protein ratio that would solubilize the complexbound cardiolipin, which are critical for their stability and activity.

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In addition, after transfer of the electrophoretic gels for Western blotting, the choice of the antibodies will determine whether the quantification of the abundance of the fully assembled complex is privileged or the detection of assembly intermediates. In principle, any subunit can be targeted and would allow the detection of the assembled complex, provided that the epitope is accessible for the antibody. However, according to the location of the subunit within the complex and the incorporation step during the assembly process, the assembly intermediates which could be detected and their number will vary (Fig. 1). Moreover, due to the relatively low dynamic range of chemiluminescence detection, the high intensity of the signal produced by the holoenzyme could blunt other bands of lower abundance, as the assembly intermediates. To address this issue, the detection of assembly factors that specifically bind intermediates, but detach once the holoenzymes are fully assembled should be preferred. In this case, only the assembly intermediates will be visualized. An example of CI assembly analysis using antibodies targeting assembly factors is illustrated in Fig. 1. It is therefore highly recommended to master the assembly pathway of the complex of interest and the location of the different subunits and assembly factors within the complex structure/intermediates before performing a BN-PAGE analysis. However, a normal respiratory chain enzyme activity/assembly does not exclude a functional impairment of the respiratory chain functioning, which may not be detectable by enzymatic measurements or assembly analyses. 2.4 Functional Analyses: Respiration Rates

Respiration studies are an efficient way to analyze ETC and metabolic activities of cells or tissues. The last, irreversible, step of electron transfer along the ETC is the transfer catalyzed by the CIV of four electrons to a molecule of oxygen to generate two molecules of water. The coupling between electron transport (oxidation) and proton pumping within ETC and the tight coupling between oxidation and phosphorylation through the Δp (51, 52) mean that the mitochondrial respiration rate is an accurate measure of the total ETC activity and mitochondrial ATP synthesis rate. According to the experimental design, information can be gained on multiple processes required for respiration, including substrate transport into the mitochondria, reducing equivalent production by TCA cycle or beta-oxidation and electron delivery to the respiratory chain, activities of the different complexes, ATP synthesis, proton leak, and mitochondrial metabolism. Beyond metabolic analysis, O2 consumption is now also used to analyze cytotoxicity.

2.4.1 Devices

The rate of mitochondrial O2 consumption could be determined by a number of methods, the two main approaches are amperometric O2 sensors [51] and O2-dependent quenching of porphyrin-based phosphors [52]. The amperometric approach, notably developed

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Fig. 1 Detection of CI assembly intermediates by targeting the CI assembly factors. (a) Schematic representation of the modular assembly of CI The CI holoenzyme results from the sequential assembly of ten intermediates (A.I.), assisted by at least 13 CI specific assembly factors. The Q earliest intermediate is composed of the NDUFS2, NDUFS3, NDUFS7, NDUFS8, and NDUFA5, stabilized by two specific assembly factors, namely NDUFAF3 and NDUFAF4 in a 170 kDa intermediate (1). The binding of Q module to the ND1 subunit and accessory subunits forms the 237 to 283 kDa (2) intermediates named Q/PP-a, which are stacked to the inner membrane by NDUFAF5 and NDUFAF6. The P module is assembled in four distinct intermediates, two distal, named PD-a and PD-b that contain ND4 and ND5 subunits, respectively, and two proximal, the PP-a and PP-b. The central PP-b intermediate (3) is the entry point for four of the seven MT-DNA-encoded subunit, i.e., ND2, ND3, ND6, and ND4L, and is bound by six assembly factors, among which, NDUFAF1. Then, the different modules progressively combine (4, 5), forming a Q/P intermediate stacked with the assembly factor NDUFAF2 (6). In the last step of the process, the 160 kDa N module (7), constituted by the catalytic NDUFV1, NDUFV2, NDUFS1, and the accessory NDUFA2 and NDUFS4 subunits, is added. Finally, once the CI assembly is completed, all the assembly factors are released, leaving a functional holoenzyme of 980 kDa (8). Nuclear-

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by Oroboros Instrument, has historically been the most common for in vitro and in vivo investigations of mitochondrial respiration. Nevertheless, phosphorescent probes are gaining interests since the introduction of the XF Extracellular Flux Analyzer by Seahorse Bioscience [53]. The O2K® Oxygraph

The O2K® oxygraph developed by Oroboros measures oxygen consumption by polarography with a Clark’s electrode. Briefly, oxygen diffuses through a Teflon membrane, which is permeable to uncharged gases, but not to water. A platinum/silver/KClcoupled electrode reduces oxygen and oxidizes silver, giving rise to a current, which is proportional to oxygen concentration within the physiological range of measurements. It operates in a closed chamber of 2 ml, with a stirring magnet to homogenize oxygen and biological material. The volume can be adjusted according to the cells, tissues, or mitochondria concentrations to analyze. Highresolution designs of Oroboros Instruments are optimized for high sensitivity, precision, and minimal measurement interferences (typically the detection limit is ~1 pmol/sec/ml and the quantification limit is ~2.5 pmol/s/ml, on site evaluations).

 Fig. 1 (continued) encoded subunit names were shortened by omitting the leading “NDUF.” Only the main subunits are indicated. The numbers refer to the corresponding intermediates that can be detected by BN-PAGE in panel b. (b) Study of CI assembly by BN-PAGE in two control fibroblasts (Ctr), one patient cell line with a known assembly defect [48] and cells lacking MT-DNA (143B Rho0). (b1) First, CI assembly was analyzed using “classical” antibodies targeting CI structural subunits located in different intermediates, i.e., NDUFS2 (Q, left panel), NDUFB6 (PD-a, middle panel), and NDUFS1 (N, right panel). In Ctr cells, anti-NDUFS2 antibody allowed the detection of the fully assembled holoenzyme (8), while Q/P A.I. (6) accumulated in the NDUFS4 mutated cells. No CI holoenzyme or A.I. could be detected in Rho0. Further hybridization with antiNDUFB6 and NDUFS1 antibodies highlighted the presence of the Pp-b/PD-a at ~700 kDa (5) and the N module (7), respectively. (b2) A.I. were then analyzed by targeting the assembly factor NDUFAF4 (Q), NDUFAF1 (Pp-b), and NDUFAF2 (Q/P). The detection of NDUFAF1 revealed a main band at ~400 kDa which matched with the described size for the Pp-b intermediate and two higher faint bands just below and above 800 kDa that matched the Q/Pp and Q/P intermediates, respectively. As expected, these intermediates containing the MT-DNA encoded subunits were not observed in Rho0 cells. NDUFAF4 antibody detected the expected bands for Q-containing intermediates, i.e., a main one for Q at 170 kDa (1) and fainter ones for Q/Pp-a (at ~240 kDa and ~280 kDa, (2)), Q/Pp (~750 kDa, (4), and Q/P (~880 kDa, (6)). As expected, only the smallest Q intermediates, constituted only of nDNA-encoded subunits, were detected in Rho0 cells. The Pp-b intermediate was detected on the same membrane by hybridizing anti-NDUFAF1 antibody. Finally, additional hybridization with NDUFAF2 antibody clearly highlighted the accumulation of the Q/P (6) that occurred in NDUFS4 cells and highlighted different higher molecular weights up to ~1100 kDa for this intermediate. Thus, since they do not bind the CI holoenzyme, whose intense signal can blunt the presence of A.I., the targeting of the assembly factors allows a more sensitive detection of these intermediates. The two combined approaches allow the identification of seven of the assembly intermediates in addition to the holoenzyme

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This is allowed by (1) closed, air-tight reaction chambers; (2) high sensitivity of the sensors with minimal noise/signal ratio; and (3) low O2-permeable materials, which minimizes O2 backdiffusion and overestimations of respiration. In these systems, instrumental background O2 consumption (i.e., nonbiological O2 flux, which constitutes potential sources of systematic error) can be corrected for accurate determinations of O2 consumption. The device can be fully calibrated, both for 0 and 100% oxygen signals and oxygen concentration within the respiratory medium according to the actual PO2 and O2 solubility. Therefore, real-time absolute quantitative measurements of oxygen concentration and fluxes can be measured, and robust comparison of inter-assays achieved. Normalization of fluxes to protein content or cell concentration can be easily achieved by recovering the samples within the chamber at the end of the experiment. O2K® oxygraphs are a fully open system, allowing as many injections of substrates or inhibitors as needed, and reoxygenation during the experiment time-course if needed, thus enabling extended substrate–uncoupler–inhibitor–titration protocols to be applied. Each complex of the ETC can be studied independently, on the same sample, using different substrate combinations. The capability of the O2k® system has recently expanded beyond respiration to permit simultaneous fluorescence-based measurements, potentiometric measurements of H+ concentrations (i.e., pH), of ΔΨm using triphenylphosphonium or fluorescent membrane potential probes, and Ca2+, as well as amperometric measurement of nitric oxide. There are however main limitations when considering the use of Oroboros technology: First, the O2k® is not a high-throughput technology, as only two samples can be performed at one time, and it is not automated. Because analysis using substrate–uncoupler– inhibitor–titration protocols take approximately one hour to complete, large-scale analyses are time-consuming. Second, analysis requires cell dissociation and suspension. As most cell culture– based studies are conducted on adherent cells, this system shows limits when the experimental objective is to assess cellular bioenergetics in intact cultured cells. According to cell types, cell detachment from the extracellular matrix could alter metabolism [54], in any way, analyses must be performed immediately and achieved rapidly after cell detachment. Third, despite the high sensitivity, the relative high volume of the chambers (500 μl to 2 ml) imposes a nonnegligible sample quantity. Typically, 10–40 μg of isolated mitochondria, 1–2 mg permeabilized tissue or 2–6·106 cells, according to cell types, are needed for one experiment.

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The Seahorse® XF Extracellular Flux Analyzer technology is based on solid state sensor probes for detection of oxygen and H+ concentrations, residing 200 μm above the cell/sample monolayer on a multi-well microplate format. Real-time measurements of oxygen concentrations are made by isolating a small volume of about 2 μl of medium above a monolayer of samples in a “transient microchamber” within the microplate. The technology based on fluorescence quenching is quite sensitive and has been optimized to avoid signal drifting. The main advantage of Seahorse® technology relies on its multi-wells plate format and automated system, allowing highthroughput analyses. Moreover, the small chamber volume is a great benefit when limited material is available. Finally, this system represented a technical breakthrough for the field of bioenergetics by providing the first instrument with the capacity to measure in vivo O2 consumption on intact adherent cells in culture. The XF Analyzer minimizes the potential limitation of oxygen diffusion for adherent cells by transiently limiting the volume of solution in which O2 is measured to just above the monolayer of cultured cells. Moreover, the capability of the system expands beyond respiration and allows simultaneous measurements of H+ extrusion (i.e., pH), as a reflect of glycolytic rates. However, there are main limitations to consider when analyzing mitochondrial respiration using the Seahorse® Analyzer. First, as for many miniaturized setups, high-throughput methods, the device loses in accuracy what it gains in rapidity. The biosensors are calibrated for 100% oxygen, using the supplier solution, not in the respiratory medium used. The calibration procedure does not consider the real oxygen concentration within the medium (oxygen solubility within the medium, real barometric pressure during the experimental course). However, the temporary microenvironment created over the cell layer is not completely sealed from atmospheric O2; thus, as O2 concentration declines with time, O2 gradient favors diffusion from the media to the micro-chambers. O2 gradient could also favor back-diffusion from the plastic of the wells. As the device back-diffusion of oxygen is not quantified and background correction is performed relative to the “background plate noise” determined on different “control” wells (devoid of sample), this could lead to an underestimation of cellular respiration rate. Thus, this system allows quite quantitative determination of O2 variation, but it did not allow absolute quantitative measurements of O2 concentration and fluxes. Second, inherent to the technologies based on fluorescence quenching is also the quite high variability between the different acquisitions (intra-assay variability (intraplate, inter-sensors) and more strikingly, inter-plates variability) [55]. This limits the comparison between different experiments. Third, the Seahorse® setup is not an open system, and only four ports surrounding the sensor are available that must be loaded

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before starting the analysis. This strongly limits the ETC substrates/inhibitors titration protocols. It is essential to perform robust optimization steps prior to any respiratory assay: the optimal concentration of each injectable reagent must be checked for each experimental condition. Care must be also taken not to overload the wells, which can cause O2 to quickly become depleted under phosphorylating conditions, leading to hypoxia. Finally, this device requires that samples adhere to the bottom of the well, which corresponds to an advantage when working on adherent cells, but could require coating of the samples in other conditions. To resume, when accurate measurement of O2 consumption and high versatility is aimed, as for diagnosis purpose, highresolution O2K® respirometry system should be used. However, if high-throughput dosages are needed as for the screening of drugs, or when the sample quantities are limited, the Seahorse® offers a much higher throughput platform than the traditional Clark electrode-based systems. 2.4.2 Permeabilized Tissues and Cells

Within tissues or cells, mitochondria are not accessible for many substrates and inhibitors, and the large catabolic processes that must be considered when dissecting ETC activity and mitochondrial metabolism greatly complicated the understanding of the results. Therefore, Isolation of mitochondria through tissue/cell culture homogenization and differential centrifugations is routinely used for assessment of mitochondrial respiration [56, 57]. Isolated mitochondria remain one of best approaches for studying mitochondrial bioenergetics free from the influence of cellular factors like the cytoskeleton, endoplasmic reticulum, cellular ATPases, together with a strict control on substrate supplies. It also allows the studies of distinct subcellular mitochondria, such as subsarcolemmal and intermyofibrillar mitochondria of skeletal muscle, which display different functional properties [58]. However, the disadvantages of isolated mitochondria include: 1. The disruptions of mitochondrial structure [59], of mitochondrial network, mitochondria–endoplasmic reticulum and mitochondria–cytoskeleton interactions, which may impact function [60–62]. 2. The purification process also bias the mitochondrial composition, by selecting high-density mitochondria, while discarding less dense ones during differential centrifugation steps [63]. 3. The purification process requires relatively large sample sizes (roughly 20  106 cells, or 100–150 mg wet weight of tissue) to obtain relevant yields. 4. The loss of micro-compartmentalization and metabolic channeling [64, 65].

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An alternative approach when the control of substrate supply is needed is the use of permeabilized tissues, mostly permeabilized muscle fibers, or cells using low concentration of plasma-selective detergents [66]. Saponin and digitonin, a saponin derivate, are mostly selective for cholesterol lipids, enriched in the plasma membrane. Therefore, the use of saponin (50–100 μg/ml) for tissue permeabilization or digitonin (10–30 μg/million cells) for cell permeabilization leaves intact all intracellular structures, including mitochondria. Permeabilized cell and skinned fiber techniques have several advantages for studies of mitochondrial function: 1. very small tissue samples are required; 2. all mitochondria can be investigated; 3. more importantly, mitochondria are studied in their natural surroundings, as the mitochondrial network is maintained as well as the potential interactions between mitochondria and other subcellular structures and organelles. However, the mitochondrial integrity after sample preparations must be carefully controlled by checking the absence of any stimulatory effect of cytochrome c, witnessing the maintenance of the mitochondrial membranes’ integrity. The classical respiration rate experiments to determine mitochondrial bioenergetic function were defined by Chance and Williams [67]. Substrate is added in the respiratory medium (defined as “state 2,” no ADP), followed by addition of ADP, allowing the ATP synthase to function. This induces a drop in Δp and thus accelerates the electron transport and proton pumping (“state 3”). On permeabilized fibers or cells, the presence of cellular ATPase activity maintains a high ADP/ATP ratio through constant ATP hydrolysis and subsequent ATP recycling by mitochondrial synthesis. State 4o is achieved by adding oligomycin, the ATP synthase inhibitor, to inhibit ATP synthesis, increasing back the Δp resulting in slowing down the respiration rate. Although state 2 and state 4 respiration are experimentally quite equivalent, state 4 is more conveniently used when referring to respiration under basal, non-phosphorylating conditions. Then, addition of a protonophore, such as FCCP (carbonyl cyanide-p-trifluoromethoxyphenylhydrazone), gives the uncoupled respiration (“state 3u”). State 3u is controlled exclusively by substrate oxidation module (including substrate uptake, activity of the NADH/FADH2 producing pathway, e.g., TCA cycle, activity of the ETC complexes, pool sizes of ubiquinone, and cytochrome c). Inhibition of any of these processes will decrease the state 3u rate, but due to the presence of controlled, unlimited substrates, state 3u mainly reflect the maximal ETC capacity for a given substrate, even if the TCA cycle activity could be sometimes rate-limiting.

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State 3 (ADP) is controlled, depending on the tissue and conditions, by both the ATP synthesis module (ANT, PiC, and ATP synthase) and substrate oxidation. Indeed, in some mitochondria, such as those from brown fat or liver, the ATP synthase activity is limited and displays a striking control over the ETC activity, meaning that the maximal ETC activity can only be reached in uncoupling conditions [68]. Comparing state 3u and state 3, when ADP is added in saturating concentration, will thus provide insight into the control exerted by the ATP synthesis module on the substrate oxidation one. State 4 is controlled predominantly by the proton leak and to a small extent by the activity of substrate transport. In optimal condition, mitochondria maintain a high Δp which restricts proton pumping and thus electron transport leading to slowdown of the respiration rate. An increased state 4o rate for a given substrate would indicate altered proton leak. Importantly, the specific subset of complexes and dehydrogenases engaged by these assays depends on the substrates provided. These respiratory states can be sequentially measured in the presence of different combinations of mitochondrial substrates, allowing multiple metabolic pathways or respiratory complexes to be probed. A typical titration protocol used in diagnosis pipelines, using substrates of CI, CI + CII, CII, and IV, is as followed (Fig. 2): First, state 2 (non-phosphorylating) respiration is initiated after adding pyruvate and malate. Second, the state 3 respirations are detailed for the different complexes: the CI-linked maximal phosphorylating respiration is stimulated by saturating ADP concentration (1.5 mM). Succinate (10 mM) is added to measure the combined CI and CII-linked respiration with convergent CI + II electron flow into the Q-junction corresponding to the maximal stimulated phosphorylating respiration (OXPHOS capacity). Rotenone is then used to inhibit CI activity and thus to obtain the maximal CII-linked phosphorylating respiration. Third, oligomycin is used to inhibit F0F1-ATP synthase and state 4o measurement. FCCP is sequentially added to uncouple mitochondria and measure the CII-linked respiration in state 3u. Antimycin A (2 μg/ml) is used to inhibit complex III and check for the non-mitochondrial oxidation. Finally, ascorbate + TMPD, the artificial complex IV substrates, allow the measurement of maximal COX-driven respiration rate, after inhibition of complex IV by potassium cyanide and subtraction of this nonspecific oxidation. The respiratory control ratio (RCR), defined as the quotient of maximal state 3 to state 4 respirations, is often used as an index of mitochondrial coupling of oxidation to phosphorylation for a given substrate combination. The RCR indeed integrates the increase in

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Fig. 2 Typical analyze traces of O2 consumption on permeabilized fibers. (a) Segmental analysis of ETC function using sequential substrates injections. Mitochondrial oxygen consumption measurements were performed at 37  C and atmospheric pressure using a high-resolution oxygraph (O2K, Oroboros Instrument, Innsbruck, Austria). Respiration rates on permeabilized fibers using 50 μg/ml saponin (30 minutes, 4  C) were measured in respiratory buffer (10 mM KH2PO4, 300 mM mannitol, 10 mM KCl, 5 mM MgCl2, 0.5 mM EGTA, and 1 mg/ml serum albumin bovine, pH 7.2) using substrates of CI, CI + CII, and CII as followed: first, state 2 (non-phosphorylating) respiration was measured after adding 2.5 mM pyruvate and 5 mM malate. Then, the CI-linked maximal phosphorylating respiration was stimulated by saturating ADP concentration (1.5 mM) and 3 mM NAD+, added to avoid TCA limitation by NAD+ availability. CI-linked maximal phosphorylating respiration was further stimulated with 5 mM glutamate, to check for any limitation of substrate availability by PDH activity. Succinate (10 mM) was then added to measure the combined CI and CII-linked respiration with convergent CI + II electron flow into the Q-junction corresponding to the maximal stimulated phosphorylating respiration (OXPHOS capacity). Rotenone (5 μM) was used to inhibit CI activity and thus to obtain the maximal CII-linked respiration. Thirdly, oligomycin (F0F1-ATP synthase inhibitor, 4 μg/ml) and FCCP (carbonyl cyanide-p-trifluoromethoxyphenylhydrazone, a mitochondrial uncoupler, 1 μM) were sequentially added to ensure that the cells were fully permeabilized. Antimycin A addition (2 μg/ml) was used to check for the non-mitochondrial oxidation. CIV maximal respiration was induced with 4 mM ascorbate and 0.3 mM TMPD,

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respiration rate in response to Δp use for ATP synthesis and the low respiration rate linked to proton leak in non-phosphorylating conditions. RCR values depend on almost every OXPHOS functional aspect and could therefore be a useful indicator of mitochondrial dysfunction. However, RCR determinations are sensitive to experimental inaccuracies; depending on the quality of sample preparations and accurate determination of background rate, state 4 rates can be significantly over/underestimated. Moreover, there are no absolute RCR values, as these ones are substrate- and tissuedependent. For example, substrates such as succinate or glycerol phosphate translocate fewer protons per electron pair than NADHlinked substrates, so the maintenance of the same Δp requires a higher respiration rate. Furthermore, under identical substrate conditions, different values may be observed for different tissues, reflecting different substrate oxidation kinetics, endogenous proton leak, or phosphorylating capacities [68]. Thus, careful cautions according to the experimental conditions should be recommended when interpreting RCR values. Permeabilized cells or fibers are also a useful model to assess the maximal activity of the main substrate-providing pathway, i.e., TCA cycle or beta-oxidation activities. Thus, different TCA cycle intermediates or mitochondrial shuttles substrates (malate/aspartate, glycerol phosphate shuttles) can be used to dissect specific regulations within these pathways. Similarly, the comparison of maximal respiration rates sustained in the presence of TCA cycle substrates (malate, pyruvate, glutamate, and succinate for a fully operating cycle) or in the presence of beta-oxidation substrates (short-chain or long-chain fatty acids complexed with coenzyme A or L-carnitine) allows determining the preferred metabolic pathways according to pathophysiological conditions, treatments, or tissues. Measurements of maximal respiratory chain complex activities, assembly, and linked respirations are the cornerstone on which the biochemical diagnosis of mitochondrial disorders is based. However, these can usefully be implemented by more integrative methods, approaching mitochondrial metabolism. 2.4.3 Intact Cells

The use of isolated mitochondria or permeabilized cells has been favored for years. Because the experimenter has control over conditions, i.e., substrates availability and respiratory states, this remains the method of choice to gain mechanistic insight into respiration chain function and dysfunctions. However, in the last

 Fig. 2 (continued) followed by CIV inhibition using 1 mM KCN and azide. (b) Analysis of O2 consumption linked to the stimulation of β-oxidation. β-oxidation was stimulated using palmitoyl-L-carnitine, supplemented with 2.5 mM malate (PCM). Antimycin A addition (2 μg/ml) was used to check for the non-mitochondrial oxidation. CIV maximal respiration was induced with 4 mM ascorbate and 0.3 mM TMPD, followed by CIV inhibition using 1 mM KCN and azide

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decades, respiration analyses on intact cells became prominent in the field. With whole cell models, intrinsic activity of respiratory chain complexes is difficult to test and respiration rates somehow difficult to interpret, since their activities are integrated with a myriad of parameters. However, overriding these complexities is the obvious higher physiological relevance. Using intact cells, mitochondria are present in a physiological environment with preserved interactions with the rest of the cell. Therefore, this model is ideal to assess metabolic pathways connected directly or indirectly to mitochondrial activities. A typical experiment using intact cells starts by the measurement of respiratory rate in the respiratory medium, e.g., cell culture medium, without any additions of inhibitors or uncoupler (Fig. 3). This state is defined as the basal or routine respiration. Routine respiration is the minimal rate of oxidative metabolism required to

Fig. 3 Typical analysis traces of O2 consumption on intact cells. Mitochondrial oxygen consumption measurements were performed at 37  C and atmospheric pressure using a high-resolution oxygraph (O2K, Oroboros Instrument, Innsbruck, Austria). Respiration rates on primary fibroblast cells were measured in either DMEMF12 medium (3 g/l glucose, 0.3 mM pyruvate) (red traces) or in low-glucose medium (0.5 g/l glucose) (green Traces). 4  106 cells were added in the oxygraphic chamber and the analysis started with routine respiration (R) measurement, which is defined as respiration in medium without additional substrates or effectors (cell endogenous respiration, corresponding to the cellular oxidative metabolism). Then, 1 mM glutamine was added, to test for cell metabolic dependence to glutaminolysis. F0F1-ATP synthase was inhibited with oligomycin (4 μg/ml), allowing the measurement of non-phosphorylating respiration (leak respiration). This non-phosphorylating respiration (O) was subtracted from routine (R) one to calculate the cellular phosphorylating respiration (R-O). This was followed by uncoupling of oxidative phosphorylation by stepwise titration of FCCP (carbonyl cyanide-p-trifluoromethoxyphenylhydrazone) up to optimum concentrations allowing the measurement of the maximal endogenous respiration (cellular oxidative capacity). The part of the maximal capacity use for oxidative metabolism was calculated as R/F, and the part of the maximal capacity use for oxidative ATP synthesis was calculated as (R-O)/F. Finally, respiration was inhibited by rotenone and antimycin A (2.5 μM and 2 μg/ml, respectively) to check for non-mitochondrial oxidation

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fulfill energy needs and support cell functions. The routine respiration of most mammalian cells corresponds neither to the state 3 (unlimited availability of substrate and ADP) nor to the state 4o (unlimited availability of substrate, but no ATP synthesis), but is generally an intermediate state between these ones, according to the ATP demand. Routine respiration is usually strongly controlled by ATP turnover, but in many cultured mammalian cells, aerobic glycolysis also contributes to the total ATP turnover [69], meaning that the routine respiration is not equivalent to cell metabolic rate. Routine respiration is further partly dependent on substrate oxidation (including substrate uptake, TCA cycle, activity of the ETC complexes. . .) and proton leak [70]. Therefore, routine respiration could differ according to the substrate availability in the incubation medium, to the oxidative ATP synthesis needs or in the presence of any agents decreasing the Δp (uncouplers). For example, routine respiration can be increased by decreasing glucose concentration (Fig. 3). A modification in routine rate integrates any of these changes and is therefore quite difficult to interpret, but the following steps can help to elucidate the pathway involved. Routine respiration measurement is followed by mitochondrial ATP synthesis inhibition, through oligomycin addition. The resulting respiration is defined as leak respiration. Indeed, as for permeabilized cells, this respiration rate in the presence of oligomycin is controlled predominantly not only by the proton leak but also, to a smaller extend, by the activity of substrate or ions (e.g., Ca2+) transports and substrate being oxidized. In intact cells, the substrates oxidized by the ETC are not under the control of the experimenter. Because the proton pumping is not equivalent according to the substrate used, the respiration rate required to maintain the Δp is also different. Thus, a modest change in leak respiration rate may indicate either a change in proton leak or a change in Δp caused by altered substrate oxidation or transport. However, a large increase in the respiration rate strongly suggests uncoupled mitochondria. This leak respiration rate is subtracted from the preceding routine state to estimate the in-situ phosphorylating respiration, i.e., the respiration rate linked to ATP synthesis. However, the proton leak is voltage-dependent, all the more important as the ΔΨ is high. Since ATP synthase inhibition results in an increase in ΔΨ, subtracting the oligomycin-insensitive respiration from the routine one slightly overvalues the part of proton leak involved in routine respiration and underestimates ATP synthesis. This remains nevertheless one of the best approaches to estimate in situ phosphorylating respiration when absolute quantitative values are not needed [71]. Also, calculating the part of the phosphorylating versus leak respirations within the routine one further helps to decipher which process explains a change in the routine respiration

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rate. While an increase in phosphorylating respiration most likely reflects the response of oxidative metabolism to increased energy demand, a decrease in the phosphorylating respiration could illustrate a decrease in energy needs, a metabolic rewiring from oxidative metabolism to “anaerobic” glycolytic one (the so-called Warburg effect), or a blockage in the ATP synthesis module. The next step involves uncoupler titration, e.g., FCCP titration, to obtain the maximal uncoupled respiration rate. As for uncoupled respiration measured on permeabilized cells, this one is control by the substrate oxidation pathways. However, there is a marked difference here: while on permeabilized cell, the uncoupled respiration is measured in the presence of unlimited availability of defined substrate(s), meaning that uncoupled respiration is mainly a reflect of maximal ETC capacity; on intact cells, the catabolic pathways supplying ETC with NADH or FADH2 is under complex metabolic regulation and can be rate-limiting. Therefore, the uncoupled respiration rate on intact cells reflects the maximal overall substrate oxidation capacity, from substrate uptake and catabolism to ETC activity, achievable by cells under the assay condition. A decrease in this maximal respiratory capacity is a reliable indicator of mitochondrial dysfunction but, because of these complexities, caution should be taken when interpreting which pathway is responsible for this dysfunction. Comparing the maximal uncoupled respiration obtained on permeabilized cells versus intact cells provides further clues to determine whether a reduced ETC capacity is involved or not. CCCP and FCCP are proton shuttling compounds selectively increasing the permeability of lipid membranes to protons. However, CCCP and FCCP also have high reactivity with thiol groups. Thiol-combining agents uncouple OXPHOS at low concentrations but inhibit respiration at high concentrations by the chemical modification of a small but significant number of mitochondrial thiol groups [72]. Moreover, sustained perturbation of ΔΨm, which is normally tightly controlled to ensure cell proliferation and survival, triggers cellular stress responses, eventually leading to cell apoptosis [72]. The optimal FCCP/CCCP concentration allowing the maximal respiration rate recording depends on cell types, medium composition (e.g., low glucose versus high glucose, fatty acids, or not. . .), and mitochondria physiological state (e.g., any drug which modifies the ΔΨm could change the optimal concentration). Therefore, careful FCCP/CCCP titration must be performed for each experimental condition to ensure the full achievement of uncoupling yet limiting the drop in ΔΨm. When using a Seahorse Analyzer, only two FCCP injections are allowed, therefore preliminary experiments must be performed before starting any complete experiment. Unappropriated uncoupler doses are a common bias observed when working on intact cells.

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Finally, the experiment ends by the addition of ETC inhibitors, rotenone, and antimycin A to determine residual oxygen consumption. Residual oxidation (Rox) is the respiration due to oxidative side reactions remaining after full inhibition of the electron transfer pathway. Mitochondrial respiration is frequently corrected for Rox as the non-mitochondrial respiration. However, Rox may be partly related to ROS production which consumes O2 and is increased upon ETC inhibitor additions [73]. From these different respiratory parameters can be inferred important ratios, particularly the spare respiratory capacity. The spare respiratory capacity is the ratio of the routine to the uncoupled respirations. With the cautions about the determination of maximum rates described above, spare respiratory capacity indicates the part of the ETC capacity that is used to sustain cell function, i.e., how close to its bioenergetic limit cells are operating [74]. While this ratio may be particularly informative, again, given the complexity of the mechanisms involved, cautions must be taken when interpreting it. For example, a decrease in spare capacity may reflect an increase in cellular ATP requirements and a system increasing its production, or a decrease in the substrate oxidation capacity that limits uncoupled respiration, depending on whether routine respiration increases or maximal respiration decreases. Similarly, an increase in spare capacity may suggest either a decrease in energy demand or a metabolic switch toward glycolysis, which then mostly ensures the ATP production, although the capacity of the ETC remains unchanged. When working with intact cells, cell metabolism “determines” which substrates mitochondria can used. However, the experimenter sets the extracellular conditions. The choice of the exact respiratory medium composition, i.e., the substrates composition and concentrations, the presence of hormones, growth factors, cytokines, may determine the outcome of the analysis. This could be a pitfall, but this also offers the opportunity to perform cell metabolic phenotyping. High concentration of glucose is often used in cell culture, but some cells prefer to oxidize other components of the medium, such as fatty acids or amino acids, particularly glutamine. For example, cancer cells undergo profound metabolic rewiring for rapid growth. They not only could derive most of their energy from glycolysis rather than OXPHOS but also could depend on oxidative glutaminolysis or modified TCA cycle activity to sustain their biosynthesis [75]. By modifying the medium composition, such as the glucose concentration (Fig. 3), or the presence of glutamine, the experimenter can easily test which specific pathway is preferentially used by cells to sustain their oxidative metabolism. 2.5 Mitochondrial Membrane Potential

The ΔΨm is central to the bioenergetic processes. It not only provides the driving force for ATP synthesis and dictates the ETC activity as detailed above but also regulates metabolites transport

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across the inner mitochondrial membrane [76], the mitochondrial NADPH synthesis through transhydrogenase reaction [77], the mitochondrial calcium buffering capacity [78], the ROS production [79], and the cell apoptotic pathway [80]. Because of its apparent simplicity, fluorescent monitoring of ΔΨm with “mitochondrial membrane potential indicators” is the most common technique used for monitoring mitochondrial function at the single cell or even at the single-mitochondrial levels. A number of cationic fluorescent probes have been developed for assessing changes in mitochondrial membrane potential in cultured cells using both microscopy and flow cytometry. This approach and the advantage/limits of the available dyes have been extensively reviewed elsewhere [81, 82]. It should be stressed that any of these cationic dyes, even at low concentration, inhibits the OXPHOS activity to some extend, particularly the phosphorylating respiration. Among these one, TMRM seems to display the lowest side effects [82]. However, this simplicity is counterbalanced by the limited information that can be inferred from this type of analysis. Indeed, it is particularly difficult to calibrate the signal measured with these probes [83–85]. Generally, studies are qualitative, indicating whether mitochondria are “depolarized” or not, or, at best, relative (semiquantitative); consequently, discrete variations are difficult to detect using classical fluorescence approaches, while mitochondrial ΔΨm is normally maintained by mitochondrial respiration and therefore only discrete variations occur from state 4 to state 3 transitions. Moreover, because ΔΨm results from the balance between ETC activity and the rate of back across into the matrix, its variations are difficult to interpret in absence of any information on mitochondrial metabolic states (respiration measurement). On isolated mitochondria or permeabilized cells, ΔΨm measures are typically performed using electrodes sensitive to potential such as triphenylmethyl phosphonium cation (TPP+) [86]. Since the development of technologies expanded beyond respiration to allow multiplexing (Oroboros O2K), assessment of respiration rates and ΔΨm (either fluorescence-based or potentiometric measurements (TPP+)) can be achieved simultaneously. Measurement of both proton fluxes and ΔΨm enables a full and quantitative description of ETC functioning and is essential to detect whether any change in ΔΨm is the primary or a secondary defect due to ETC inhibition. It allows detecting subtle changes in proton leak and coupling efficiency between mitochondrial preparations, experimental conditions, or treatments. Because the proton leak is nonohmic, increasing disproportionately at high Δp [68], it is more accurately determined by plotting the proton current (respiration rate) to voltage (ΔΨm) over a wide range of potentials in the absence of ATP synthesis [68]. This is achieved by progressively

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inhibiting ETC activity, for example, by titrating rotenone with mitochondria oxidizing NADH, and simultaneously assessing the respiration rate and ΔΨm in state 4o condition. Calculation of membrane potential is based on the Nernst equation and requires an estimate of the matrix volume over which the probe distributes. Thus, only the TPP+-based measurements enable the calculation of the absolute quantitative values, while the fluorescence-based technology is restricted to relative measurements. Moreover, the absolute values of ΔΨm can be calculated on isolated mitochondria, taking into account the “binding” factor of the TPP+ to membranes, while the absolute values of ΔΨm cannot be reasonably calculated on permeabilized cells, due to strongest unspecific binding [87]. Integrating the mechanistic studies of respiration rates and ΔΨm on permeabilized cells and the metabolic studies of respiration rates on intact cells provide a large picture of bioenergetic dysfunctions. These approaches can be complemented by metabolite dosages or more broadly by a cellular metabolomic analysis to obtain a broader picture of the cellular metabolism and its dysfunctions. 2.6 Metabolites Dosages and Metabolomics 2.6.1 Metabolite Measurements

2.6.2 Metabolomics

Defects in the mitochondrial energy production often lead to higher lactate production due to reduced pyruvate utilization by the mitochondria. Elevated lactate levels are easily detected in cell culture medium or, in vivo, in blood, urine, and/or CSF. Indeed, in cases of respiratory chain defect, the cytosolic, mitochondrial, or both, redox states (NAD+/NADH) often increase due to decrease in mitochondrial NADH oxidation and upregulation of glycolysis to support ATP needs. These increased redox states can be detected by the so-called “metabolic indicators,” i.e., an increase lactate/ pyruvate ratio shifted by the higher NADH/NAD cytosolic ratio, while a shift in the mitochondrial redox state increases the ratio of the 3-OH-butyrate to acetoacetate [88]. However, these features are neither specific nor sensitive as a diagnostic test since other defects in cellular metabolism could increase glycolytic rate and lactate production. Amino acid analysis can further reveal elevated alanine, as a by-product of the transamination of pyruvate by alanine aminotransferase, and confirm the hyperlactacidemia. In addition, elevated levels of several other metabolites can be observed upon ETC impairment. Particularly, increased levels of TCA cycle intermediates, such as malate, succinate, 2-oxoglutarate, and fumarate, are useful markers of mitochondrial metabolism dysfunction [40, 89]. As we enter the new era of omics technologies, targeted metabolomic or global unbiased approaches can strikingly improve the investigation of the multifaced mitochondrial functions.

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Metabolomics is defined as an integrative approach consisting in the comprehensive analysis of the metabolome comprising thousands of small molecules present in biological samples. Mass spectrometry (MS) coupled to liquid or gas chromatography is among the major analytical tools used in metabolomics. It enables comprehensive and systematic profiling of disease conditions and is mostly used for identifying biomarkers or drug targets in mitochondrial diseases [90]. Metabolomics is now used to analyze on a global scale the multitude of downstream effects of mitochondrial dysfunction, including not only the consequences of energy deficiency but also oxidative stress, NAD+/NADH redox imbalance, and large metabolic rewiring [91, 92]. For example, disturbed cellular dNTP pools and one-carbon metabolism have been evidenced in diseases associated with mtDNA maintenance defects [93, 94]. Also, the metabolomic signature of Opa1 deficiency, a gene involved in mitochondrial fusion, unexpectedly evidenced aspartate and glutamate depletions, two main precursors of the nucleotide synthesis pathways, which could partly explain the mtDNA maintenance defect observed in OPA1 disease [92, 95]. Thus, combining metabolomics and bioenergetics studies is a promising strategy to improve our understanding of the pathological mechanisms beyond the energetic deficiency, which is often limited in explaining the clinical phenotypes observed in patients [91, 96], and to identify new routes for therapeutic solutions. This was recently illustrated by reference [97] which demonstrated that methionine supplementation induces an upregulation of electron transport chain activity and respiration, related to an enhancement of mitochondrial pyruvate uptake and TCA cycle activity using a yeast model.

3

Discussion Because of their complex properties and strategic role in cellular metabolism, understanding mitochondrial functions and dysfunctions in diseases remains a huge challenge. However, the recent development of novel technologies allowing multiplexed and highthroughput analyses contributed to improve our capacities for subtle characterizations of mitochondrial dysfunctions. Integrating the mechanistic studies of respiration rates and ΔΨm on isolated mitochondria or permeabilized cells, and metabolic studies using intact cells and metabolomic approaches, now depicts a large overview of the cell metabolism and open a new area of mitochondrial medicine. However, integration of different data set, from the multidisciplinary approaches to create a more complete representation of the pathophysiological mechanisms, remains challenging and needs the development of robust integrative bioinformatic tools, to predict perturbations and ultimately translate our knowledge into improved patient care.

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Until recent years, the main vision was that the energetic deficit due to ineffective OXPHOS is the starting point for explaining the pathophysiology of mitochondrial disease. However, this energetic deficit alone often failed to explain the broad variability of affected organs and clinical presentations. Considering the recent progress resulting from the development of new technologies and omic approaches, this old view now seems outdated. Thus, mitochondria are now considered as master regulator of cellular homeostasis, named mitohormesis; not only do they orchestrate the metabolic stress response but also the ROS and proteostatic stress response, among which the unfolded protein response and the integrated stress response [98, 99]. Nowadays, increasing evidences are accumulating showing that these stress responses are main contributors to mitochondrial disease, rather than the OXPHOS defect by itself [100]. These recent and unexpected developments open exciting perspectives for therapeutic strategies of these disorders. After all, mitochondria are no more considered as the insidecell powerhouse, since forms of extracellular mitochondria can be found free (free Mitos), enclosed by a membrane as inside platelets or vesicles, or as cell-free circulating mtDNA [101]. Recently, Al Amir Dache et al. reported that blood contains intact cell-free fulllength mitochondrial DNA in dense and biologically stable structures over 0.22 μm in diameter and that these structures have specific mitochondrial proteins, double membranes, and a morphology resembling that of mitochondria [102]. More experimental studies suggest that mitochondria may be released and transferred between cells [102, 103]. These intriguing observations are only starting to be characterized, while their functions remain unknown. Whether they can elicit regenerative effects, induce paracrine or endocrine, pro- or anti-inflammatory immune responses [20, 104] and more largely participate in the patho-mechanisms of mitochondrial diseases are actually unsettled. Furthermore, the biochemical diagnosis of mitochondrial disease, usually performed on muscle or liver biopsy and primary fibroblasts cultured from skin biopsies, remains quite an invasive approach. Determining whether circulating blood mitochondria could be used to unravel mitochondrial dysfunction or be used as a biomarker of disease will enhance our diagnosis tools. The potential role of these intriguing mitochondria or its spinoffs in blood of patients remains to be elucidated in many pathologies [6, 11, 101]. The future of mitochondrial medicine is undoubtedly linked to better comprehension of its dysfunction. All new investigational drugs for the therapy of mitochondrial diseases have the potential to markedly alleviate clinical symptoms, and none has the capacity to actually cure a particular mitochondrial disease permanently [27].

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Chapter 2 Preparation of “Functional” Mitochondria: A Challenging Business Stefan Lehr, Sonja Hartwig, and Jorg Kotzka Abstract As the powerhouse of the cell, mitochondria, plays a crucial role in many aspects of life, whereby mitochondrial dysfunctions are associated with pathogenesis of many diseases, like neurodegenerative diseases, obesity, cancer, and metabolic as well as cardiovascular disorders. Mitochondria analysis frequently starts with isolation and enrichment procedures, which have become increasingly important in biomedical research. Unfortunately, isolation procedures can easily cause changes in the structural integrity of mitochondria during in vitro handling having impact on their function. This carries the risk that conclusions about isolated mitochondria may be drawn on the basis of experimental artifacts. Here we critically review a commonly used isolation procedure for mitochondria utilizing differential (gradient) centrifugation and depict major challenges to achieve “functional” mitochondria as basis for comprehensive physiological studies. Key words Isolation of mitochondria, Differential gradient centrifugation, Mitochondrial integrity

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Introduction Since their naming in 1898 by Carl Benda, the importance of mitochondria mediating several fundamental cellular processes is constantly growing. Due to the fact that mitochondria dysfunctions are involved in the pathophysiology of a wide variety of human diseases [1–3], dissecting mitochondria physiology is a main focus of recent biomedical sciences. Approximately, one in 200 individuals bears a pathogenic mutation in mitochondrial genes [4], affecting mitochondrial biogenesis and inheritance and therefore containing the risk to develop severe diseases including neurodegenerative diseases, aging, obesity, cancer and metabolic as well as cardiovascular disorders [5–9]. This underlines the importance to characterize exact composition and function of mitochondria in order to understand their role in cellular metabolism more precisely. Although, there have been made substantial improvements

Volkmar Weissig and Marvin Edeas (eds.), Mitochondrial Medicine: Volume 2: Assessing Mitochondria, Methods in Molecular Biology, vol. 2276, https://doi.org/10.1007/978-1-0716-1266-8_2, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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to investigating mitochondria in living cells including Oroboros O2k [10], Seahorse XF [11], and SNAP-Tag [12] technology, reflecting the natural cellular and physiological context, isolation of mitochondria is still required for certain issues. In this context, a major task of all these associated studies is to preserve the pristine mitochondrial structural integrity for analysis, which is indispensable linked to functionality of the organelles. Due to the complex organelle morphology enclosed by two membranes, i.e., the outer membrane with a large number of specialized proteins (porins) enabling pass of molecules less than 5000 Da and the inner membrane exhibiting a folding (cristae) to increase the surface area containing the complex respiratory transport chain, being critical for ATP production and last but not least the matrix harboring the wide variety of enzymes for metabolic pathways, e.g., citric acid cycle, mitochondrial ribosomes, tRNAs, and mitochondrial DNA, the preparation of mitochondria approximating the in vivo situation is tremendously challenging.

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Isolated Mitochondria: Addressing Composition and Function In order to dissect mitochondrial composition as well as function in detail and to allow direct manipulation of mitochondria by exposure to specific substrates and inhibitors, the major part of conducted studies utilizing isolated mitochondria [13, 14] achieved from diverse cellular and tissue sources. These isolation procedures are most frequently based on fundamental work of George Pallades group [15], done more than 60 years ago. They introduced a differential centrifugation workflow enabling separation of almost pure organelles with high yield, which have paved the way for such revolutionary discoveries like the oxidative phosphorylation mechanism [16], discovery of mitochondrial DNA [17], or the description of the mitochondrial ultrastructure [18]. Although, today diverse adapted methods are available to face almost all kinds of sample sources and scientific questions [19–26], preparation of functional mitochondria reflecting approximately the in vivo situation is still challenging.

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First Step: The Inevitable It is supposed that mitochondria in vivo develop complex tubularbranched structures [27, 28] undergoing complex remodeling of their morphology (fusion and fission) in respond to cellular cues [29], which are significantly different from the relatively homogeneous circular organelles occurring during standard isolation techniques [14]. It has been commonly assumed that isolation of mitochondria inevitably comes along with disruption of the native

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mitochondrial morphology. Thereby, the mitochondria network is disrupted and sealed again, which probably leads to a partial loss of soluble mitochondrial proteins [30]. Up to now, the functional consequences are largely unknown. In this context, studies comparing functionality of isolated mitochondria with mitochondria within permeabilized cells, leaving the organelles in their native surrounding [31], indicate impairments of mitochondrial function, e.g., regarding mitochondrial respiration [30, 32]. Accordingly, it should be carefully considered that during data interpretation, the common assumption isolated mitochondria preserve their complete functionality and composition will not be valid in any case.

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Isolating “Intact” Mitochondria: A Challenging Business Despite the known limitations, proper isolated mitochondria keep their compartment properties and provide a powerful tool for in-depth analysis, especially, when comparing samples achieved under identical conditions [14]. Accordingly, many scientific fields comprising metabolite and protein transport up to dynamic remodeling of mitochondria as well as recent biomedical concerns benefit from isolated, almost pure mitochondria. The most frequently applied method for isolation is differential centrifugation [13], whereby in a first step cell or tissue samples are carefully homogenized in an appropriate buffer preventing damaging of the organelles by mechanical forces, chemical reactions, or osmosis. In order to separate components of different size and density, e.g., cellular organelles, the homogenate is subjected to repeated centrifugation consecutively increasing sedimentation forces, enabling a rough fractionation of the cellular environment. To achieve pure organelles, i.e., mitochondria, the last purification step is an equilibrium density gradient centrifugation. Samples are centrifuged at high g-forces in a buffer gradient, e.g., sucrose gradient, focusing the target organelles in a concentration range of comparable density (isopycnic point), resulting in high-purity mitochondria. Although most studies are carried out based on this general isolation strategy, different sample sources and special scientific requirements need specific adaptions of the used protocols [14, 24–26], in order to achieve optimal results regarding purity as well as functionality. In the literature, a confusing diversity regarding utilized sedimentation forces, buffer compositions for homogenization, and gradient compositions are available, which should be carefully reviewed before use. In the end, the choice of a suitable separation protocol depends on the researcher’s requirements regarding organelle purity, yield, activity, and structural integrity. In some cases, the most important factor is purity, whereby activity, yield, and preparation time may be less important.

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In studies exploring cellular compartment metabolism, high activity of the organelles is often the most important requirement. For high-throughput experiments in comprehensive studies, where many samples are to be compared, it is important to shorten the time for sample preparation. From our point of view, the differential gradient centrifugation approach, closely monitored by appropriate quality control methods, offers the most valuable compromise between applied efforts (man power, expenses) and achievable yield, purity, activity, and functional integrity. In order to achieve valid results, isolation of “functional” mitochondria based on this methodology has some basic requirements and should follow a general workflow (Fig. 1, upper panel), illustrated and described in Chapter 2. This basic protocol provides a useful starting point for the isolation of mitochondria by differential gradient centrifugation. It describes preparation in detail and guide through critical steps of the separation method and how to control them regarding yield and organelle functionality. In laboratory routine, frequently separation protocols are utilized, which pass the last centrifugation step through a density gradient, which requires an ultracentrifuge and some experience. Fractionation solely by different sedimentation forces is also applied in commercial available isolation kits, but anyway results in a decreased enrichment performance [14]. In addition to the discussed differential (gradient) centrifugation strategy, it is to mention that isolation of mitochondria using integrated zone electrophoresis on a free-flow electrophoretic device [14, 33] represents a relevant alternative for preparing high purity organelles, which are particular appropriate for comprehensive proteomic studies. The major drawback of this method is that a special instrument, i.e., a free-flow apparatus, is necessary and that processing is time consuming and needs special expertise. Alternatively, a combination of simple differential centrifugation with a final purification of mitochondria utilizing anti-TOM22 magnetic beads can be also used. This reproducible protocol has been described to be suitable for various tissues yielding in the isolation of highly pure mitochondria avoiding non-mitochondrial contaminations [34]. Both methods provide pure mitochondria fractions with structural integrity, but coming along with much higher costs than applied for differential gradient centrifugation methods.

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Reproducibility and Quality Control: Guarantee for Successful Analysis Many recent studies in the field of biomedical research addressing potential mitochondrial dysfunction requires analysis properties in a highly parallel fashion. In order to achieve valid results, therefore it is crucial to utilize a standardized processing. In this context, it would be advantageous to collect samples successively and store

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Fig. 1 Impact of sample freezing on mitochondria structural integrity. Centrifugation-based isolation of mitochondria is performed according to a general strategy consisting out of three major processing steps shown in the upper panel. 1. Careful sample homogenization using a Potter, Douncer, or Ultra-Turrax device. 2. Consecutive differential centrifugation to separate cellular compartments according to size and density. 3. Increasing organelle purity due to equilibrium density gradient centrifugation, e.g., linear sucrose gradient, which enable concentration of mitochondria in the gradient fraction of comparable density (isopycnic point). To illustrate the importance of choosing appropriate sample material, the lower panels show a comparison of isolated mitochondria from fresh and frozen material. Measurement of citrate synthase (CS) activity, an enzyme in situ exclusively located in the mitochondrial matrix, allows monitoring structural integrity of mitochondria during processing. CS release and therefore significant CS activity in the homogenate

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them in a freezer before use. Accordingly, one might think that starting with frozen material for mitochondria isolation would simplify the workflow significantly. But unfortunately, the most striking prerequisite to isolate functional mitochondria is to use fresh (not frozen) material. Investigating the impact of sample freezing indicates dramatic consequences on mitochondria structure and functionality (Fig. 1 middle and lower panel). Monitoring activity of citrate synthase (CS) [35], an enzyme normally exclusively located in the mitochondrial matrix, reveals that freezing leads to a strong release of CS from the mitochondrial matrix into the homogenate. In contrast to fresh material, where approximately 5% of total CS activity is found in the homogenate, more than 40% of CS activity can be assigned to the homogenate if frozen material is used. This eightfold increase indicates that the mitochondria structure is significantly disrupted. Corresponding electron microscopy (EM) images confirm these observations and demonstrate the loss of structural integrity due to a nearly complete destruction of isolated mitochondria expected morphology (Fig. 1, lower panel). Accordingly, these observations strongly suggest that frozen material in any case is inappropriate for organelle isolation and therefore to study mitochondria composition, function, or physiological behavior. Another challenging point to enable reliable comparison of a huge number of samples is the initial homogenization step. In most laboratories, it is performed manually using Potter, Douncer, or ULTRA TURRAX homogenizers, potentially introducing significant variations. The utilized forces for homogenization are a highly subjective parameter, which carefully have to be validated. Due to the fact that organelle purity and functionality are the striking prerequisites for any study addressing isolated mitochondria, monitoring the whole isolation process is mandatory. Without an appropriate quality control, regarding mitochondria functionality and purity, no reasonable assessment of the organelle sample is possible. In this context, it is to mention that Western blot analysis of organelle specific proteins (e.g., mitochondria (anti-Tom20), lysosomes (anti-Lamp-1), endoplasmic reticulum (anti-BiP/ GRP78), and peroxisomes (anti-catalase)), which is frequently used as a standard method to examine product composition and therefore the isolation success, only allow to detect relative ä Fig. 1 (continued) (extramitochondrial activity) suggest disruption of mitochondria structure. To assign the total CS activity as control, CS activity of complete lysed mitochondria samples was set as 100%. Comparing activity levels of CS, in the homogenate of fresh and frozen samples impressively, shows that initial freezing destroys mitochondria structure and induce a release of CS from the mitochondrial matrix. This results in an eightfold increase in CS activity in the homogenate. Accordingly, in case of frozen sample, nearly half of the total CS activity is found outside of the mitochondria. In addition to that electron microscopy (EM) analysis of gradient fractions shows a more or less complete loss of the typical mitochondrial cristae structure resulting in blank membrane covers

Preparation of “Functional” Mitochondria: A Challenging Business

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distribution of the dedicated proteins but do not allow to assign mitochondria functionality. A more meaningful evaluation, allowing to determine mitochondria purity, can be achieved when additional biochemical assays are used. We recommend measuring activity of marker enzymes specific for mitochondria as well as contaminating cell compartments, i.e., succinate dehydrogenase for mitochondria, glucose-6-phosphatase for endoplasmatic reticulum [36], alkaline phosphatase for plasma membrane, acidic phosphatase for lysosomes [37], and catalase for peroxisomes [38]. These control assays are easily applicable with standard laboratory equipment and enable to calculate organelle distribution and to estimate some functional aspects. These assays are also very helpful during the establishing phase of the gradient centrifugation protocols, in order to select the region within the gradient corresponding to most pure and active mitochondria fraction. In order to assess “functional” integrity, measuring JC-1 uptake [39] or oxygen consumption, with the principle of a traditional Clark electrode [40] as read out for ATP production, should be mandatory. Both methods are appropriate to monitor the status of mitochondrial membrane potential. If possible, additional investigations of the isolated mitochondria by transmission electron microscopy allow assessing structural integrity of the inner and outer membranes as well as the mitochondrial matrix. It is worth mentioning that not using such research tools deprives the possibility of drawing well-founded conclusions about the integrity of organelles and thus the functional status of the underlying preparation. Accordingly, investigation of purity and morphology–function relationship should be an inherent part of any organelle fractionation procedures in order to avoid working with inappropriate sample material.

6

Conclusion Our recent knowledge suggest that available protocols fail to allow isolation of native, functional mitochondria. This has to be considered, when planning and interpreting the experiments. Emerging understanding of structure–function relationship and the effect of morphology changes during isolation may help to improve isolation methods or develop novel strategies for in-depth in situ analysis. Nevertheless, proper isolated mitochondria may approximate the “intact” status and still provide an indispensable tool to address future challenges of mitochondrial participation in the pathophysiology of diverse widespread diseases including neurodegenerative, muscular, cardiovascular, metabolic disorders, and cancer.

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References 1. Picard M, Wallace DC, Burelle Y (2016) The rise of mitochondria in medicine. Mitochondrion 30:105–116 2. Herst PM, Rowe MR, Carson GM, Berridge MV (2017) Functional mitochondria in health and disease. Front Endocrinol 8:296 3. Elliott HR, Samuels DC, Eden JA, Relton CL, Chinnery PF (2008) Pathogenic mitochondrial DNA mutations are common in the general population. Am J Hum Genet 83 (1030):254–260 4. Schon EA, DiMauro S, Hirano M (2012) Human mitochondrial DNA: roles of inherited and somatic mutations. Nat Rev Genet 13:878–890 5. Cherry C, Thompson B, Saptarshi N, Wu J, Hoh J (2016) A ‘mitochondria’ odyssey. Trends Mol Med 22:391–403 6. Wallace DC (2018) Mitochondrial genetic medicine. Nat Genet 50:1642–1649 7. Dai W, Jiang L (2019) Dysregulated mitochondrial dynamics and metabolism in obesity, diabetes, and cancer. Front Endocrinol (Lausanne) 10:570 8. Chan DC (2019) Mitochondrial dynamics and its involvement in disease. Annu Rev Pathol 15:235–259 9. Piaceri I, Rinnoci V, Bagnoli S, Failli Y, Sorbi S (2012) Mitochondria and Alzheimer’s disease. J Neurol Sci 322:31–34 10. Gnaiger E, Steinlechner-Maran R, Me´ndez G, Eberl T, Margreiter R (1995) Control of mitochondrial and cellular respiration by oxygen. J Bioenerg Biomembr 27:583–596 11. Divakaruni AS, Rogers GW, Murphy AN (2014) Measuring mitochondrial function in permeabilized cells using the Seahorse XF analyzer or a Clark-type oxygen electrode. Curr Protoc Toxicol 60:1–16 12. Stephan T, Roesch A, Riedel D, Jakobs S (2019) Live-cell STED nanoscopy of mitochondrial cristae. Sci Rep 9:12419 13. Frezza C, Cipolat S, Scorrano L (2007) Organelle isolation: functional mitochondria from mouse liver, muscle and cultured fibroblasts. Nat Protoc 2:287–295 14. Hartwig S, Feckler C, Lehr S, Wallbrecht K, Wolgast H, Mu¨ller-Wieland D, Kotzka J (2009) A critical comparison between two classical and a kit-based method for mitochondria isolation. J Proteome 11:3209–3214 15. Hogeboom GH, Schneider WC, Pallade GE (1948) Cytochemical studies of mammalian tissues. I. Isolation of intact mitochondria

from rat liver; some biochemical properties of mitochondria and submicroscopic particulate material. J Biol Chem 172:619–635 16. Mitchell P, Moyle J (1967) Chemiosmotic hypothesis of oxidative phosphorylation. Nature 213:137–139 17. Nass MM, Nass S (1963) Intramitochondrial fibers with DNA characteristics. I. Fixation and electron staining reactions. J Cell Biol 19:593–611 18. Palade GE (1952) The fine structure of mitochondria. Anat Rec 114:427–451 19. Graham JM (2001) Purification of a crude mitochondrial fraction by density-gradient centrifugation. Curr Protoc Cell Biol Chapter 3:Unit 3.4 20. Gollihue JL, Patel SP, Mashburn C, Eldahan KC, Sullivan PG, Rabchevsky AG (2017) Optimization of mitochondrial isolation techniques for intraspinal transplantation procedures. J Neurosci Methods 287:1–12 21. Le´ger JL, Jougleux JL, Savadogo F, Pichaud N, Boudreau LH (2019) Rapid isolation and purification of functional platelet mitochondria using a discontinuous Percoll gradient. Platelets 5:1–7 22. Knebel B, Go¨ddeke S, Hartwig S, Ho¨rbelt T, Fahlbusch P, Al-Hasani H, Jacob S, Koellmer C, Nitzgen U, Schiller M, Lehr S, Kotzka J (2018) Alteration of liver peroxisomal and mitochondrial functionality in the NZO mouse model of metabolic syndrome. Proteomics Clin Appl 12(1) 23. Liu Y, He J, Ji S, Wang Q et al (2008) A comparative study of early liver dysfunction in senescence-accelerated mouse using mitochondrial proteomics approaches. Mol Cell Proteomics 7:1737–1747 24. Stahl WL, Smith JC, Napolitano LM, Basford RE (1963) Brain mitochondria: I. Isolation of bovine brain mitochondria. J Cell Biol 19:293–307 25. Cannon B, Lindberg O (1979) Mitochondria from brown adipose tissue: isolation and properties. Methods Enzymol 55:65–78 26. Mela L, Seitz S (1997) Isolation of mitochondria with emphasis on heart mitochondria from small amounts of tissue. Methods Enzymol 55:39–46 27. Ogata T, Yamasaki Y (1997) Ultra-high-resolution scanning electron microscopy of mitochondria and sarcoplasmic reticulum arrangement in human red, white, and intermediate muscle fibres. Anat Rec 248:214–223

Preparation of “Functional” Mitochondria: A Challenging Business 28. Fang H, Chen M, Ding Y, Shang W, Xu J et al (2011) Imaging superoxide flash and metabolism-coupled mitochondrial permeability transition in living animals. Cell Res 21:1295–1304 29. Pernas L, Scorrano L (2016) Mito-morphosis: mitochondrial fusion, fission, and cristae remodeling as key mediators of cellular function. Annu Rev Physiol 78:505–531 30. Picard M, Taivassalo T, Ritchie D, Wright KJ, Thomas MT et al (2011) Mitochondrial structure and function are disrupted by standard isolation methods. PLoS One 6:e18317 31. Kuznetsov AV, Veksler V, Gellerich FN, Saks V, Margreiter R, Kunz WS (2008) Analysis of mitochondrial function in situ in permeabilized muscle fibres, tissues and cells. Nat Protoc 3:965–976 32. Saks V, Guzun R, Timohhina N, Tepp K, Varikmaa M et al (2010) Structure-function relationships in feedback regulation of energy fluxes in vivo in health and disease: mitochondrial interactosome. Biochim Biophys Acta 1797:678–697 33. Islinger M, Wildgruber R, Vo¨lkl A (2018) Preparative free-flow electrophoresis, a versatile technology complementing gradient

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centrifugation in the isolation of highly purified cell organelles. Electrophoresis 39:2288–2299 34. Franko A, Baris OR, Bergschneider E, von Toerne C, Hauck SM et al (2013) Efficient isolation of pure and functional mitochondria from mouse tissues using automated tissue disruption and enrichment with anti-TOM22 magnetic beads. PLoS One 8:e82392 35. Schulman JD, Blass JP (1971) Measurement of citrate synthase activity in human fibroblasts. Clin Chim Acta 33:467–469 36. Pennington RJ (1961) Biochemistry of dystrophic muscle. Mitochondrial succinatetetrazolium reductase and adenosine triphosphatase. Biochem J 80:649–654 37. Bergmeyer HU (1974) Methoden der enzymatischen analyse. Verlag Chemie, Weinheim 38. Aebi H (1984) Catalase in vitro. Methods Enzymol 105:121–126 39. Reers M, Smiley ST, Mottola-Hartshorn C, Chen A, Lin M, Chen LB (1995) Mitochondrial membrane potential monitored by JC-1 dye. Methods Enzymol 260:406–417 40. Li Z, Graham BH (2012) Measurement of mitochondrial oxygen consumption using a Clark electrode. Methods Mol Biol 837:63–72

Chapter 3 Isolation and Quality Control of Functional Mitochondria Sonja Hartwig, Jorg Kotzka, and Stefan Lehr Abstract Even in times, when the study of mitochondria in their natural cellular context is becoming more and more popular, some scientific questions still require the preparation of isolated mitochondria. Numerous protocols are available being adapted for different cell or tissue types allowing isolation of “pure” mitochondria trying to preserve their “structural and functional” integrity. In this chapter, we intend to provide a more general framework introducing differential isopycnic density gradient centrifugation strategy with a special focus sensitizing for the specific challenges coming along with this method and how to obtain “functional,” enriched, “intact” mitochondria. Due to the fact that in any study dealing with these organelles standardized processing is mandatory, here we describe a strategy addressing quality control of prepared intact mitochondria. The quality control should be an integrated part of all isolation processes. The underlying protocol should be seen as starting point and has to be carefully adjusted to cover different sample types used for the diverse research questions. Key words Sample pre-fractionation, Mitochondria enrichment, Isopycnic density gradient centrifugation, Marker enzymes

1

Introduction Mitochondria biology play a crucial role in many aspects of life, including in pathophysiology of many diseases, like neurodegenerative diseases, obesity, cancer, and metabolic disorders [1, 2]. In order to dissect the specific role of mitochondria, various scientific fields benefit from analysis of isolated, almost pure mitochondria. Due to the fact that there is a strong relationship between mitochondria structure and functionality, there are strong demands to preserve their “structural and functional” integrity during preparation. Today, numerous protocols are available enabling isolation of “pure” mitochondria, including differential gradient centrifugation [3, 4], affinity purification with Anti-TOM22 magnetic beads [5], or separation by free-flow electrophoresis [6]. In this context, the differential gradient centrifugation strategy offers the most valuable compromise between applied efforts (man power, expenses) and

Volkmar Weissig and Marvin Edeas (eds.), Mitochondrial Medicine: Volume 2: Assessing Mitochondria, Methods in Molecular Biology, vol. 2276, https://doi.org/10.1007/978-1-0716-1266-8_3, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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achievable yield, purity, activity, and functional integrity. In order to achieve high-quality mitochondria appropriate for further detailed investigations moreover, it is mandatory to monitor functionality and enrichment progress during the entire isolation process. If available, controlling resulting preparations by electron microscopy, which gives an excellent impression of achieved quality, is recommended. Here we describe the preparation of mitochondria in detail and guide through critical steps of the separation method and how to control them regarding yield and organelle functionality.

2

Materials

2.1 Mitochondria Fractionation

1. Potter S homogenizer with glass cylinders (15 ml) including appropriate plunger (for breaking up the tissue in a gentle way). 2. Ground in glass douncer (loose fit, for gently manual homogenization). 3. Centrifuges, corresponding rotors and tubes with capability for 11,000
g-force and 85,000
g-force, e.g., 70TI rotor and swing-out rotor SW28 for the Optima XPN-80 (Beckmann). 4. Homogenization buffer: 225 mM mannitol, 75 mM saccharose, 10 mM Tris/HCl, 0.5 mM EGTA, pH 7.4, and 0.5 mM DTT (see Note 1). 5. Resuspension buffer: 250 mM saccharose, 10 mM Tris/HCl, 0.5 mM EGTA, pH 7.4 and 0.5 mM DTT (see Note 1).

2.2 Linear Saccharose Gradient

1. Gradient mixer. 2. Ultracentrifuge tubes (e.g., Beckmann tubes for SW28 rotor). 3. Three different saccharose solutions in resuspension buffer: 24% (w/w), 54% (w/w), and 57% (w/w) (see Note 2).

2.3 Marker Enzyme Assays

2.3.1 Succinate Dehydrogenase (SDH) Assay

1.5 and 2 ml reaction tubes with corresponding stand, incubator for 37 C, the usage of a Multipette would be a benefit, and a photometer with corresponding solvent-resistant cuvette to measure at 405, 410, 490, and 815 nm are needed. For JC-1 assay a spectrofluorometer with an excitation wavelength of 490 nm and an emission wavelength of 590 nm is needed. 1. INT solution: 2.5 mg/ml p-Iodonitrotetrazolium in 0.05 M Na dihydrogen phosphate pH 7.5. 2. Na succinate solution: 0.01 M Na succinate in 0.05 M Na dihydrogen phosphate pH 7.5.

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3. Stop solution: Ethyl acetate:ethanol:TCA 5:5:1 (v/v/w). 2.3.2 Acidic Phosphatase Assay

1. Nitrophenylphosphate solution: 16 mM p-Nitrophenylphosphate in H2O. 2. Na acetate solution: 180 mM Na acetate pH 5.0 (adjustable with acetic acid). 3. Stop solution: 250 mM NaOH.

2.3.3 Basic Phosphatase Assay

1. Nitrophenylphosphate solution: 16 mM p-Nitrophenylphosphate in H2O. 2. Na borate solution: 250 mM Na borate pH 9.8 (adjustable with NaOH). 3. Stop solution: 250 mM NaOH. 4. 1 M MgCl2.

2.3.4 Catalase Assay

1. Catalase sample buffer: 20 mM Tris/HCl pH 7.0, 1% BSA, 2% Triton X-100. 2. Assay buffer: 20 mM Tris/HCl pH 7.0, 1% BSA, 0.25% H2O2. 3. Titanyl solution: Dissolve 22.5 mg titanium oxy sulfate sulfuric acid hydrate in 100 ml 1 M sulfuric acid (see Note 3).

2.3.5 Glucose-6-Phospatase (G-6-Pase) Assay

1. Saccharose buffer: 250 mM saccharose, 100 mM EDTA pH 7.2. 2. Cacodylate buffer: 100 mM cacodylic acid sodium salt adjusted to pH 6.5. 3. Glucose-6-phospate solution: 100 mM glucose-6-phospate (see Note 4). 4. Potassium dihydrogen phosphate solution: 200 μM potassium dihydrogen phosphate in H2O. 5. TCA solution: 8% trichloroacetic acid in H2O. 6. Fiske-Subbarow reagent: Dissolve 0.75 g sodium sulfite in 5 ml H2O. Also dissolve 6.85 g sodium disulfite and 0.125 g Amino-2-hydroxynaphthalin-4 sulfonic acid in 50 ml H2O. Mix both solutions and store it in a tightly capped amber bottle (see Note 5). 7. Ammonium heptamolybdate solution: 0.48% ammonium heptamolybdate in H2O (w/v).

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2.3.6 JC-1 Uptake Assay

1. 5x storage buffer: 50 mM HEPES, 1.25 M saccharose, 5 mM ATP, 0.4 mM ADP, 25 mM sodium succinate, 10 mM K2HPO4, 5 mM DTT. Weigh out all ingredients and dissolve it in H2O to 90% of calculated end volume (e.g., for 100 ml add 90 ml). Adjust pH to 7.5 with concentrated NaOH and fill up with H2O to 100% of calculated volume. Pass the buffer through a 0.2 μm filter and store 5–15 ml aliquots at 20  C. 2. 5
JC-1 assay buffer: 100 mM MOPS, 550 mM KCl, 50 mM ATP, 50 mM MgCl2, 50 mM sodium succinate, 5 mM EGTA. Weigh out all ingredients and dissolve it in H2O 90% of calculated end volume (e.g., for 50 ml add 45 ml). Adjust pH to 7.5 with concentrated NaOH and fill up with H2O to 100% of calculated volume. Pass the buffer trough a 0.2 μm filter and store 2 to 5 ml aliquots at 20  C. 3. JC-1 stain: Dissolve 25 μg JC-1 (5,50 ,6,60 -tetrachloro0 0 1,1 ,3,3 tetraethylbenzimidazol carbocyanine iodide) in 25 μl DMSO (see Note 6) to obtain a solution with 1 μg/μl (resulting concentration is 1.53 mM).

3

Methods Here we describe a protocol for reproducible mitochondria isolation from mouse liver with isopycnic saccharose gradient centrifugation. The general workflow and some typical electron microscopy images from such a preparation are shown in Fig. 1. Table 1 provides an example result for enzymatic quality check.

3.1 Subcellular Fractionation 3.1.1 Preparation of Linear Saccharose Gradient

1. Pipette 4 ml 57% saccharose solution in a 36 ml ultracentrifuge tube (for SW28 Beckmann rotor) as a pillow and place it in an angular tube stand. 2. Build up the gradient mixer, assure that you can stir the solution in the first chamber and put a blunt cannula at the end of the hose. 3. Fill 15 ml low 24% saccharose solution in the first chamber and 15 ml 54% saccharose solution in the second. 4. Position the blunt cannula in the angular positioned tube tight above the 57% pillow and fix it with a clip. 5. Open the taps and let the saccharose solutions flow by gravity into the tube (see Note 7). 6. Pull the blunt cannula carefully out, right the tube, and store it at 4  C until use.

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Fig. 1 Mitochondria isolation workflow shows the consecutive steps from homogenization, differential centrifugation up to the density gradient. Purification progress among the different processing steps is visualized by electron microscopy 3.1.2 Homogenization

1. Use a fresh liver tissue sample (obtained within 1 h of sacrifice) kept on ice in homogenization buffer. 2. Wash mice liver twice with 2 volumes of homogenization buffer and mince it into pieces with scissors. 3. Transfer liver pieces (in total about 1.5 g) to the 15 ml glass cylinder and add tenfold (w/v) homogenization buffer. 4. Homogenize the liver pieces by 10 strokes with the ground in glass douncer (see Note 8). 5. Take a 10% aliquot of the homogenate and store on ice (see Note 9).

3.1.3 Differential Centrifugation

1. Transfer homogenate to a 15 ml centrifugation tube and centrifuge at 666
g at 4  C for 15 min to remove cell debris. 2. After centrifugation, transfer the supernatant to a 70TI centrifugation tube and fill up to 30 ml with homogenization buffer and centrifuge at 11,000
g 4  C for 15 min. 3. Decant the supernatant and put it aside (mainly cytosolic proteins).

12,649  5076

2113  836

865  420

243  74

152  56

16  2

5.3  1.6

Homogenate

666
g supernatant

11,000
g pellet

Gradient fraction

56

13

1.8

666
g 249  59 supernatant

56  12

7.8  3.7

11,000
g pellet

Gradient fraction

100

464  161

Homogenate

1.51  0.5

3.54  0.6

1.73  0.4

1.96  0.6

0.07  0.01

0.51  0.4

6.06  1.7

11.95  3.4

0.5

4

51

100

Yield [%]

0.01  0.003

0.03  0.03

0.04  0.03

0.05  0.01

Specific activity [μmol mg1 min1]

29  16

128  60

627  159

1405  548

2

9

47

100

Yield [%]

Total activity [μmol/min]

Specific activity [μmol mg1 min1]

Total activity [μmol/min]

Yield [%]

Total activity [μmol/min]

Preperation step

Glucose-6-phosphatase

Basic phosphatase

3.2

2.6

0.7

1

Accumulation factor

5.2  1.9

7.8  2.9

4.4  1.0

6.0  2.0

Yield [%]

79  48

517  323

1.4

9

4126  1610 72

6195  2811 100

Total activity [μU/min]

Catalase

Peroxisomes

687  97

601  91

308  79

372  73

Specific activity [Fluor./mg]

JC-1 uptake

Specific activity [μmol mg1 min1]

Endoplasmatic reticulum

min ]

Acidic phosphatase

164.1  51.3

134.2  52.8

33.9  31.3

52.3  15.8

Specific activity [μmol mg

1

Plasma membrane

7

17

39

100

Yield [%]

1

Lysosomes

5649  5692

Total activity [μmol/min]

Total protein [mg]

Preperation step

Succinate dehydrogenase

Mitochondria

Table 1 Example of monitoring the subcellular fractionation process

14.6  5.2

31.9  18.1

27.9  8.8

25.6  10.1

Specific activity [μU mg1 min1]

1.9

1.7

0.8

1

Accumulation factor

Isolation and Quality Control of Functional Mitochondria

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4. Wash the pellet with homogenization buffer by pipetting carefully across, to remove the fluffy layer (yellowish layer above a darker tawny layer). 5. Resuspend the tawny pellet in 3–5 ml homogenization buffer, take an aliquot, transfer the resuspended pellet to a new 70TI tube, and add up to 30 ml with homogenization buffer and centrifuge again at 11,000
g for 15 min at 4  C. 6. Decant the supernatant and put it aside. 7. Resuspend the resulting tawny pellet in 2–3 ml resuspension buffer and again take an aliquot. 3.1.4 Isopycnic Density Gradient Centrifugation

1. Layer the resuspended pellet carefully onto a linear sucrose gradient. 2. Carry out centrifugation in a SW28 swing-out bucket rotor at 85,000
g for 60 min at 4  C without brakes (see Note 10). 3. After centrifugation, carefully remove the gradient tube from the rotor bucket and the enriched mitochondria show up in the middle of the tube as a light brown–yellowish ring. 4. Collect 2 ml aliquots by pipetting carefully from above in rotary movements with a wide opening pipette tip (see Note 11). 5. Determine the mitochondrial activity from the aliquots by measuring succinate dehydrogenase activity (see Subheading 3.3.1 SDH enzyme assay) and pool aliquots with highest activity (see Note 12). 6. Dilute pooled aliquots with fivefold volume (v/v) of resuspension buffer and transfer to 70TI tube follow a centrifugation at 11,000
g for 15 min and 4  C. 7. Resuspend resulting final mitochondria pellet in 1–2 ml resuspension buffer. 8. This mitochondria fraction is ready for further experiments including quality control assays.

3.2 Protein Measurement

Protein measurements from all steps of the mitochondria preparation should be done. Therefore take 10–20 μl of each fraction/ aliquot and mix it up with the same amount of 1 M NaOH to denature for protein measurement with standard Bradford assay.

3.3 Marker Enzyme Assays

With all these enzyme assays, you can measure the protein activity per ml and calculate the specific activity with the values from protein content and document your mitochondria enrichment and decrease of other organelles during preparation. For the different enzyme activity assays, you need different dilutions of your samples: succinate dehydrogenase delivers good results with a sample/aliquot dilution of 1:10 and 1:20, acidic phosphatase with 1:8 and 1:16, catalase 1:10, basic phosphatase pure and 1:2, and glucose-6-phosphatase 1:10 (see Note 13).

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3.3.1 Mitochondria: Succinate Dehydrogenase (SDH) (See Ref. 7)

The succinate dehydrogenase catalyzes the oxidation from succinate to fumarate under release of hydrogen. In vivo FAD would be reduced to FADH2, but under these test assay conditions the p-Iodonitrotetrazolium (INT), an artificial electron acceptor, would be reduced to formazan which turns from colorless to rusty red and can be measured at 490 nm. 1. Produce the INT solution: 100 μl for each sample/dilution is needed. 2. Prepare 2 ml reaction tubes with 20 μl of diluted samples and one only with resuspension buffer as a blank. 3. Add 300 μl Na succinate solution to each tube and incubate for 10–20 min at 37  C. 4. Add 100 μl INT solution and incubate 10 min at 37  C. 5. Stop the enzyme reaction by adding 1 ml stop solution. 6. Centrifuge the tubes for 2 min at 20,000 x g to get rid of precipitates. 7. Measure the extinction of supernatants at 490 nm. 8. Calculate the activity per ml and the specific activity: ΔE
V E ½ml=V P ½ml ½μmol ¼ εmol ½ml=μmol cm
d ½cm
t ½ min  ½ml
min  ΔE: extinctions difference (measured value  measured blank). VE/VP: enzyme assay volume/added sample volume, i.e., the entire dilution factor of the measured sample in the assay. εmol: molar extinctions coefficient [ml/μmol
cm] (for INT it is 0.0134). d: thickness of used cuvette [cm]. t: incubation time Na succinate solution with sample before adding INT solution. Calculate the specific activity [μmol/mg
min] in your sample by simple dividing through the protein concentration of the measured sample.

3.3.2 Lysosomes: Acid Phosphatase (See Ref. 8)

The acid phosphatase has a working optima at pH 4 to 5. In this assay, the conversion from p-nitrophenylphosphate and H2O to p-nitrophenol is the enzymatic step and with a pH increase by adding NaOH the “produced” nitrophenol shift to nitrophenolate ions and the solution gets yellow color and extinction could be measured at 410 nm. 1. Prepare an assay mix with 16 mM p-nitrophenylphosphate solution and the 180 mM Na acetate solution (1:1, v/v).

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2. Prepare 1.5 ml reaction tubes and add 25 μl of recommended sample dilutions and use resuspension buffer as blank. 3. Add 200 μl assay mix-solution to each tube and incubate for 20–30 min at 37  C. 4. Stop the enzyme reaction by adding 600 μl stop solution to each tube. 5. Centrifuge the tubes for 2 min at 20,000
g to get rid of precipitates. 6. Measure the extinction of supernatants at 410 nm. 7. Calculate the activity per ml and the specific activity: ΔE
V E ½ml=V P ½ml ½μmol ¼ εmol ½ml=μmol cm
d ½cm
t ½ min  ½ml
min  ΔE: extinctions difference (measured value  measured blank), VE/VP: enzyme assay volume/added sample volume, i.e., the entire dilution factor of the measured sample in the assay. εmol: molar extinctions coefficient [ml/μmol
cm] here for converted nitrophenol is 0.521. d: thickness of used cuvette [cm]. t: incubation time. Calculate the specific activity [μmol/mg
min] in your sample by simple dividing through the protein concentration of the measured sample. 3.3.3 Plasma Membrane: Basic Phosphatase (See Ref. 8)

The basic phosphatase has a working optima at pH 9–10. In this assay, the conversion from p-nitrophenylphosphate and H2O to p-nitrophenol is the enzymatic step and with a pH increase by adding NaOH the “produced” nitrophenol shift to nitrophenolate ions and the solution gets yellow color and extinction could be measured at 410 nm. 1. Prepare an assay mix with nitrophenylphosphate solution and the Na borate solution (1:1, v/v). Also add 1 M MgCl2 to a final concentration in the assay mix of 2 mM (i.e., 2 μl in 1 ml). 2. Prepare 1.5 ml reaction tubes with 25 μl of pure and diluted samples and use resuspension buffer as blank. 3. Add 200 μl assay mix-solution to each tube and incubate for 20–30 min at 37  C. 4. Stop the enzyme reaction by adding 600 μl stop solution to each tube. 5. Centrifuge the tubes for 2 min at 20,000
g to get rid of precipitates. 6. Measure the extinction of supernatants at 410 nm.

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7. Calculate the activity per ml and the specific activity: ΔE
V E ½ml=V P ½ml ½μmol ¼ εmol ½ml=μmol cm
d ½cm
t ½ min  ½ml
min  ΔE: extinctions difference (measured value  measured blank). VE/VP: enzyme assay volume/added sample volume, i.e., the entire dilution factor of the measured sample in the assay. εmol: molar extinctions coefficient [ml/μmol
cm] here for converted nitrophenol is 0.521. d: thickness of used cuvette [cm]. t: incubation time. Calculate the specific activity [μmol/mg
min] in your sample by simple dividing through the protein concentration of the measured sample. 3.3.4 Peroxisome: Catalase (See Ref. 9)

The catalase converts hydrogen peroxide to water and hydrogen. Titanoxid sulfate build up a yellow complex with hydrogen peroxide and the extinction of this complex could be measured at 405 nm (see Note 14). 1. Prepare the titanyl solution fresh (see Note 3). 2. Test assay buffer by adding 1 ml titanyl solution to 500 μl assay buffer, centrifuge for 5 min at 20,000
g and measure extinction from the supernatant at 405 nm. The value should be between OD 0.5 and 0.6. If this is not the case, you have to prepare the assay buffer fresh (see Note 15). 3. Mix 10 μl of the sample with 30 μl of the catalase sample buffer and do all further steps on ice (see Note 16). 4. Add 500 μl from the tested assay buffer and stop the reaction by adding 1 ml titanyl solution exactly after 1 min. 5. Centrifuge samples for 5 min at 20,000
g. 6. Measure the extinction at 405 nm against water and your “positive” blank (see Note 17). 7. Define E405nm 0.001 ¼ 0.001 U/ml and calculate the difference from extinction measured from sample to the “positive” blank and also calculate the activity and specific activity for catalase as follow: ΔE
V E ½ml=V P ½ml ½U ¼ εmol ½ml=U cm
d ½cm
t ½ min  ½ml
min  ΔE: extinctions difference (measured “positive” blank  measured value).

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VE/VP: enzyme assay volume/added sample volume, i.e., the complete dilution factor of the measured sample in the assay. εmol: molar extinctions coefficient [ml/U
cm] adaption 0.001 ¼ 1 U (see Note 18). d: thickness of used cuvette [cm]. t: incubation time before addition of titanyl solution. Calculate the specific activity [U/mg
min] in your sample by simple dividing through the protein concentration of the measured sample. 3.3.5 Endoplasmic Reticulum: Glucose-6-Phophatase (See Ref. 10)

The glucose-6-phosphatase (G-6-Pase) dephosphosphorylate G-6-P to glucose and free phosphate. Colorimetric measurement of free phosphate content could be done by Fiske-Subbarow method. In this assay, a blue complex is formed, when free phosphate is mixed with ammonium molybdate and 1-amino-2-naphthol-4-sulfonic acid, and could be measured at 815 nm. Important for this enzyme assay is to measure next to a blank the sample without or with substrate. To calculate the nmol/ml concentrations, a standard curve with potassium hydrogen phosphate has to be measured. 1. Prepare Fiske-Subbarow mix freshly by adding 3.75 ml FiskeSubbarow reagent and 10 ml perchloric acid (60%) to 86.25 ml ammonium heptamolybdate solution. 2. For each sample, you have to measure two values, one without substrate (endogenous Pi) and one with substrate (G-6-P) for enzymatic dephosphorylation combine in 2 ml tubes: For endogenous value: (a) 100 μl cacodylate buffer. (b) 100 μl saccharose buffer. (c) 100 μl H2O. For enzymatic value: (a) 100 μl cacodylate buffer. (b) 100 μl saccharose buffer. (c) 100 μl glucose-6-phosphate solution. 3. By adding 100 μl sample to each tube, the enzymatic reaction is started. 4. Incubate all samples for 30 min at 37  C. 5. During incubation, prepare a standard curve with the potassium hydrogen phosphate as replicates (0, 20, 50, 100, 150 to 200 nmol/ml). The volume of each standard sample is 1 ml (see Note 19).

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6. Stop the enzymatic reaction (step 4) in the sample tubes by adding 1.5 ml 8% TCA solution to each tube. 7. Centrifugate the sample for 10 min at 1000
g to get rid of precipitates. 8. Transfer 1 ml of the resulting supernatant to a new 2 ml tube and add 1 ml of the fresh prepared Fiske-Subbarow mix to each tube and also to the samples of the standard curve. 9. Vortex all samples and incubate for 30 min at RT. 10. Measure the standard curve, basal, and enzymatic samples at 815 nm. 11. Generate a x/y-graph with values from standard curve, y-axis is OD, and x-axis the known free phosphate (Pi) amount [nmol]. 12. To calculate the produced Pi amount, subtract the endogenous from the enzymatic OD, read off the Pi value from the standard curve and calculate the enzymatic activity as follows: Pi ½nmol=ml
V E ½ml=V P ½ml ½nmol ¼ t ½ min  ½ml
min  VE/VP: enzyme assay volume/ added sample volume, i.e., the complete dilution factor of the measured sample in the assay. t: incubation time before addition of titanyl solution. 3.3.6 Mitochondria (Functional Integrity): JC-1 Uptake Assay (See Ref. 11)

Uptake measurement of the fluorescent carbocyanine dye (JC-1) is a surrogate parameter for mitochondrial inner membrane integrity because it is only possible if electrochemical proton gradient is formed. Depending upon the transmembrane electric field, JC-1 will is taken up into mitochondrial matrix and if concentration raised more than 1 mM a red-orange fluorescence will occur at 590 nm, due to aggregation of dye within the matrix. 1. Prepare 1
buffer from storage and JC-1 assay buffer by 1:5 (v/v) dilution in H2O. 2. Prepare solution of the samples with storage buffer in a protein concentration of 0.4 mg/ml. 3. From this prepare a dilution row where you apply in total 10, 20, 30, and 40 μg protein in a volume of 100 μl (filled up with storage buffer) in a 2 ml reaction tube. 4. Add 1.9 ml 1
JC-1 assay buffer to each sample of the dilution row. 5. Add 2 μl JC-1 stain to the lid of the reaction tube. 6. Close the tube and vortex directly. 7. Incubate the samples 10 min at RT in the dark.

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8. Read the fluorescence of samples in a spectrofluorometer with an excitation wavelength of 490 nm and an emission wavelength of 590 nm. 9. Generate an x/y-graph with values from four samples of the dilution row, x-axis is the amount of protein, and y-axis is the fluorescence at 590 nm. 10. Calculate the fluorescence produced in the original sample per mg protein: ΔFL
dil FLU ¼ V
C mgP FLU: fluorescence units. mgP: milligram protein. ΔFL: fluorescence (sample)  fluorescence (blank). dil: dilution factor to prepare 0.4 mg/ml sample dilution. V: volume of the sample in [ml]. C: protein concentration [mg/ml].

4

Notes General note: Especially in face of the complexity of the workflow and the enormous biological variability, it appears that an extraordi nary diligence in each step of the analysis is of great importance. This begins with the first experimental step, i.e., sample collection and preparation, which frequently is underestimated. In this context, the close collaboration between the different scientific disciplines and the development of Standard Operation Procedures is of particular importance. 1. First do the pH adjustment of buffers with 2 M NaCl and then add required amount of DTT always fresh. 2. To bring high amounts of saccharose in solution quickly, warm up the solutions a little bit (30–40  C). 3. The titanyl solution needs up to 30 min at RT to get dissolved (clear solution) and is stable and usable at RT for 2 h. 4. Store the solution at 4  C, it is stable up to 4 weeks. 5. Store the solution in an amber bottle because it is light sensitive. A benefit is to prepare the solution 2 days before use and pass the solution through a 0.02 μm filter before storing. The solution is perishable, if it gets yellowish, throw it away and make a fresh one. 6. Use anhydrous solvents (i.e., in this case dimethyl sulfoxide (DMSO)) to dissolve cyanine dyes like JC-1.

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7. Test the gradient linearity by aliquoting the gradient up to 20 fractions and measure the saccharose concentration with a refractometer. 8. Make sure that the glass douncer reach the bottom of the cylinder and that the solution and the equipment are kept on ice. Prevent negative pressure while douncing by using loose fit douncer. 9. If you take aliquots from each step of fractionation, you can easily perform protein content measurement and marker enzyme assays. The results show the mitochondria enrichment and decrease of other organelles. For example, see Table 1. 10. The running down without brakes from here used high g-forces that increase the standby time, therefore you can go for lunch. 11. It is important to use a pipette tip with a wide opening to collect the gradient suspension carefully from the top of the surface. 12. The highest mitochondria content is located in a density of about 42% saccharose. The refractometer measurement helps, next to SDH activity assay, to identify the correct fraction. 13. For marker enzyme assays, different solutions are needed and best use resuspensions buffer for all samples. 14. In this assay, the decrease of catalase substrate is the indicator for enzyme activity. Adding H2O2 to titanyl solution results in yellow solution. If catalase is present, the H2O2 amount decreases and the solution get colorless. So, the decrease of color represents enzymatic activity. 15. H2O2 is light sensitive, therefore protect the buffer and assay samples from light. 16. The catalase is one of the quickest known enzymes; therefore, the exact compliance of incubation time and temperature of buffers is mandatory. 17. The positive blank is the maximum amount of H2O2 that could be measured within the assay. 18. There is no molar extinction coefficient known, so to calculate a relative activity adapt 0.001 OD difference ¼ 1 arbitrary unit. 19. This assay is very sensitive to free phosphate (Pi), so it is mandatory to use always disposable, phosphate-free plastic material because cleaning solution contains and leaves traces of free phosphate and therefore influence or rather damage your assay measurements.

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References 1. Nunnari J, Suomalainen A (2012) Mitochondria: in sickness and in health. Cell 148:1145–1159 2. Cherry C, Thompson B, Saptarshi N, Wu J, Hoh J (2016) A ‘Mitochondria’ Odyssey. Trends Mol Med 22:391–403 3. Frezza C, Cipolat S, Scorrano L (2007) Organelle isolation: functional mitochondria from mouse liver, muscle and cultured fibroblasts. Nat Protoc 2:287–295 4. Hartwig S, Feckler C, Lehr S, Wallbrecht K, Wolgast H, Mu¨ller-Wieland D, Kotzka J (2009) A critical comparison between two classical and a kit-based method for mitochondria isolation. Proteomics 9(11):3209–3214 5. Franko A, Baris OR, Bergschneider E, von Toerne C, Hauck SM et al (2013) Efficient isolation of pure and functional mitochondria from mouse tissues using automated tissue disruption and enrichment with anti-TOM22 magnetic beads. PLoS One 8:e82392

6. Islinger M, Wildgruber R, Vo¨lkl A (2018) Preparative free-flow electrophoresis, a versatile technology complementing gradient centrifugation in the isolation of highly purified cell organelles. Electrophoresis 39:2288–2299 7. Pennington RJ (1961) Biochemistry of dystrophic muscle. Mitochondrial succinatetetrazolium reductase and adenosine triphosphatase. Biochem J 80:649–654 8. Walter K, Schuett C (1974) In: Bergmeyer HU (ed) Methods in enzymatic analysis, vol 3. Academic Press, Inc, New York, pp 860–864 9. Aebi H (1984) Catalase in vitro. Methods Enzymol 105:121–126 10. Baginski ES, Foa PP, Zak B (1969) Determination of phosphate and phosphomonoesterases in biologic materials. Am J Med Technol 35:475–486 11. Reers M, Smith TW, Chen LB (1991) J-aggregate formation of a carbocyanine as a quantitative fluorescent indicator of membrane potential. Biochemistry 30:4480–4486

Chapter 4 Purification of Functional Platelet Mitochondria Using a Discontinuous Percoll Gradient Jacob L. Le´ger, Nicolas Pichaud, and Luc H. Boudreau Abstract The isolation of mitochondria is gaining importance in experimental and clinical laboratory settings. Of interest, mitochondria and mitochondrial components (i.e., circular mitochondrial DNA, N-formylated peptides, cardiolipin) have been involved in several human inflammatory pathologies, such as cancer, Alzheimer’s disease, Parkinson’s disease, and rheumatoid arthritis. While several mitochondrial isolation methods have been previously published, these techniques are aimed at yielding mitochondria from cell types other than platelets. In addition, little information is known on the number of platelet-derived microvesicles that can contaminate the mitochondrial preparation or even the overall quality as well as functional and structural integrity of mitochondria. Here we describe a purification method, using a discontinuous Percoll gradient, yielding mitochondria of high purity and integrity from human platelets. Key words Mitochondria isolation, Mitochondria membrane integrity, Percoll extraction method, Platelet-derived microvesicles, Platelet-derived mitochondria

1

Introduction Platelets are small mitochondria-containing anucleate cells (3–5 μm in size) that patrol the vasculature to maintain the homeostasis by preventing blood loss and promoting wound repair [1]. When exposed to physiological agonists such as thrombin, collagen, adenosine diphosphate, or immune-complexes, platelets can release small extension of their cytoplasm known as platelet-derived microvesicles (0.1–1 μm in size) in the extracellular milieu. Interestingly, the subpopulation of platelet-derived microvesicles is highly heterogeneous. In addition to releasing cell-derived microvesicles upon their activation, platelets also shed fully functional mitochondria in the extracellular milieu known as freeMitos [2]. Consequently, platelet-derived mitochondria and mitochondrial components are involved in the inflammatory response and contribute to amplify this important cellular process.

Volkmar Weissig and Marvin Edeas (eds.), Mitochondrial Medicine: Volume 2: Assessing Mitochondria, Methods in Molecular Biology, vol. 2276, https://doi.org/10.1007/978-1-0716-1266-8_4, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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While mitochondria are widely considered as the powerhouse of the cell by actively participating in the transduction of energy via the oxidative phosphorylation process (i.e., ATP generation) necessary for most metabolic reactions [3], they also participate in the immune response [2, 4]. The mitochondrion possesses numerous typical hallmarks of the bacteria such as unmethylated CpG motifs circular DNA [5], N-formylated peptides [6], and unique phospholipid cardiolipin embedded in their inner membrane [7]. When released in the extracellular milieu, these bacteria-like components can act as damage-associated molecular patterns (DAMPs) and may trigger important inflammatory responses [2, 5]. Therefore, the isolation of these organelles and their derived components is gaining importance in experimental and clinical laboratory settings [8–10]. Given the important role of mitochondria in the inflammatory response, it is essential to be able to characterize their physiology, as well as their involvement in the immune response and intercellular communication, by developing techniques allowing the rapid isolation of mitochondria that will preserve their functional properties. Our approach provides an ideal isolation method that contains fully functional mitochondria with a minimal presence of plateletderived microvesicles.

2

Materials Prepare all solutions using ultrapure water (prepared by purifying deionized water with a sensitivity of 18 MΩ-cm at 25
C and a total organic carbon content inferior to 5 ppb) and analytical grade reagents. Reagents are prepared at room temperature and stored at 4
C unless indicated otherwise.

2.1 Solutions [11–13]

1. Acid citrate dextrose (ACD-A): Sodium citrate dihydrate 75 mM, citric acid 38 mM, dextrose 136 mM, pH 4.5. To prepare 1000 mL of ACD-A, weigh 22.0 g of sodium citrate dihydrate and dissolve in 850 mL of water. Then, add 7.3 g of citric acid and 24.5 g of dextrose to the solution and mix. Adjust the pH to 4.5 with HCl solution, then complete the volume to 1000 mL with water. Filter the ACD-A solution through a 0.2 μM sterile pore. 2. Acid citrate dextrose (ACD-B): Sodium citrate dihydrate 45 mM, citric acid 25 mM, dextrose 81 mM, pH 4.5. To prepare 1000 mL of ACD-B, weigh 13.2 g of sodium citrate dihydrate and dissolve in 850 mL of water. Then, add 4.8 g of citric acid and 14.7 g of dextrose to the solution and mix.

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Adjust the pH to 4.5 with HCl solution, then complete the volume to 1000 mL with water. Filter the ACD-B solution through a 0.2 μM sterile pore. 3. Ethylenediaminetetraacetic acid solution (EDTA): EDTA 0.5 M, pH 8.0. To prepare 1000 mL of EDTA solution, weigh 186.1 g of EDTA and dissolve in 800 mL of water. Adjust the pH to 8.0 by adding 20.0 g of NaOH to the solution, then complete the volume to 1000 mL with water. Filter the EDTA solution through a 0.2 μM sterile filter. 4. Sucrose solution: Sucrose solution 2.5 M. To prepare 1000 mL of sucrose solution, weigh 855.0 g of sucrose and dissolve in 800 mL of water. Complete the volume to 1000 mL with water and filter the sucrose solution through a 0.2 μM sterile filter. 5. Tris buffer (TB): Tris(hydroxymethyl)aminomethane 1 M, pH 7.5. To prepare 50 mL of TB, dissolve 6.1 g of tris (hydroxymethyl)aminomethane in 30 mL of water and adjust the pH to 7.5 with HCl solution. Complete the volume to 50 mL with water and then filter the TB through a 0.2 μM sterile syringe filter. 6. Isolation buffer (IB): Sucrose 0.2 M, tris(hydroxymethyl)aminomethane 11 mM, EDTA 1 mM, pH 7.5. To prepare 1000 mL of IB, mix 80 mL of sucrose 2.5 M and 2 mL of EDTA 0.5 M with 718 mL of water. Add 1.33 g of tris (hydroxymethyl)aminomethane and dissolve completely and adjust pH to 7.5 with HCl solution. Complete the volume to 1000 mL and filter the IB through a 0.2 μM sterile filter. 7. Isolation buffer without EDTA (IB without EDTA): Sucrose 0.2 M, tris(hydroxymethyl)aminomethane 11 mM, pH 7.5. To prepare 1000 mL of IB without EDTA, mix 80 mL of sucrose 2.5 M and 720 mL of water. Add 1.33 g of tris (hydroxymethyl)aminomethane and dissolve completely and adjust pH to 7.5 with HCl solution. Complete the volume to 1000 mL and filter the IB through a 0.2 μM sterile filter. 8. Tyrode’s buffer 7.4 (TY7.4): NaCl 134 mM, KCl 2.9 mM, Na2HPO4 0.34 mM, NaHCO3 12 mM, HEPES 20 mM, MgCl2 1 mM, glucose 5 mM, bovine serum albumin (BSA) 0.5 mg/mL, pH 7.4. To prepare 1000 mL of TY7.4, dissolve 7.88 g NaCl, 0.22 g KCl, 0.048 g Na2HPO4, 1 g NaHCO3, 4.76 g HEPES, 0.9 g glucose, 0.5 g BSA, and 0.1 g MgCl2 in 800 mL of water. Adjust the pH to 7.4 with HCl or NaOH solutions and then complete the volume to 1000 mL with water. Filter the TY7.4 through a 0.2 μM sterile filter. 9. Tyrode’s buffer 6.5 (TY6.5): NaCl 134 mM, KCl 2.9 mM, Na2HPO4 0.34 mM, NaHCO3 12 mM, HEPES 20 mM, MgCl2 1 mM, glucose 5 mM, bovine serum albumin (BSA)

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0.5 mg/mL, pH 6.5. To prepare 50 mL of TY6.5, withdraw 50 mL of prepared TY7.4 and adjust the pH to 6.5 with HCl solution. Filter the TY6.5 through a 0.2 μM sterile syringe filter. 10. Protease inhibitor 10: 1 capsule of antiprotease (Roche) dissolved in 1 mL of IB. 11. Proteinase K: Proteinase K 5 mg/mL. Resuspend proteinase K (Sigma-Aldrich) to 5 mg/mL in TB. 12. Percoll solution 90% (PS90): 10% (v/v) 2.5 M sucrose solution to 90% (v/v) Percoll. To prepare 100 mL of Percoll solution 90%, mix 90 mL of Percoll Solution (GE Healthcare) with 10 mL of 2.5 M sucrose solution. Adjust the pH to 7.2 with HCl and KOH solutions. Filter the solution through a 1.2 μM Millipore filter. The solution is kept at 4
C for a week or at 20
C for a month. Refilter before use (see Note 1). 13. Percoll solution 15% (PS15): 16.7% (v/v) of PS90 to 83.3% (v/v) of IB. To prepare 10 mL of Percoll solution 15%, mix 1.67 mL of PS90 with 8.33 mL of IB. The solution is kept on ice until use for the discontinuous gradient. 2.2 Optional Solutions [14]

1. Respiration buffer (MiR05): EGTA 0.5 mM, MgCl2·6H2O 3 mM, lactobionic acid 60 mM, taurine 20 mM, KH2PO4 10 mM, HEPES 20 mM, D-sucrose 110 mM, BSA 1 g/L. To prepare 1000 mL of MiR05, dissolve under sterile conditions 0.19 g EGTA, 0.61 g MgCl2·6H2O, 2.5 g taurine, 1.36 g KH2PO4, 4.77 g HEPES, 37.65 g D-sucrose, and 1 g BSA in 800 mL of water. Combine with 120 mL of 0.5 M lactobionic acid solution (prepared in advance by dissolving 35.83 g lactobionic acid in 100 mL of water, adjusting the pH to 7.0 with KOH solution, and adjusting the volume to 200 mL with water). Finally, adjust the pH to 7.1 with KOH solution and complete the volume to 1000 mL. The solution is kept in aliquots at 20
C in plastic vials for up to a year.

2.3 Percoll Gradient Preparation [13, 15, 16]

1. Discontinuous Percoll gradient: Fill a 1.5 mL microcentrifuge tube with 500 μL of PS15 to prepare the 15% Percoll fraction and store on ice until the 0% Percoll fraction is ready (crude mitochondrial extract).

2.4 Blood Collection Preparation

1. Blood collection: Obtain approximately 80 mL of blood from consenting volunteers using 10 mL blood collection glass tubes already containing 1 mL of ACD-A (see Note 2). These tubes are prepared in advance under sterile conditions by adding the ACD-A through a needle and syringe.

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61

Methods

3.1 Platelet Isolation [11, 13]

1. Centrifuge blood in falcon tubes at 275  g for 15 min (without brake) at room temperature (RT). 2. Carefully withdraw the platelet-rich plasma (PRP) using a Pasteur pipette. 3. Add a volume of ACD-B to the PRP equivalent to 1/5 of the collected PRP and add 10 mM of EDTA. 4. Centrifuge PRP at 400  g for 2 min (without brake) at RT to remove the contaminating erythrocytes and leucocytes. 5. Collect and centrifuge the supernatant at 1300  g for 10 min (without brake) at RT to pellet the platelets. 6. Gently resuspend the platelet pellet in 500 μL of TY6.5 by doing some slow ups and downs with a P1000 micropipette. 7. Complete the volume to 40 mL with TY7.4. 8. Count total platelets in a 1:300 platelet dilution sample using a hemocytometer. 9. Add 10 mM of EDTA and centrifuge platelets at 1300  g for 10 min (without brake) at RT. 10. Slowly resuspend platelet pellet at 2  109 cells/mL in IB.

3.2 Crude Mitochondrial Extraction [13, 17]

1. Platelets are incubated with 150 μg/mL of proteinase K and mixed by inversion for 5 min at RT. 2. Homogenize the extract with a Wheaton overhead stirrer using a Teflon homogenizer adapter for 30–40 passes with speed set at 2.5–3.0 (see Note 6). 3. Add protease inhibitors cocktail (1) from the 10 concentrated stock (optional step). 4. Transfer mitochondrial extract to 1.5 mL microcentrifuge tubes. 5. Centrifuge the lysate at 1300  g for 10 min at 4
C to remove platelet debris. 6. Using a pipette, transfer the supernatant in a fresh tube and centrifuge at 8000  g for 10 min at 4
C to obtain the crude mitochondrial extract. 7. Pool the pelleted crude mitochondrial pellets using 250 μL of IB (see Note 3).

3.3 Mitochondria Purification

1. Carefully layer the resuspended crude mitochondria on top of the 15% Percoll prepared layer while avoiding the mixing of the layers (see Note 4). To do so, use a P100 micropipette, and carefully eject the crude mitochondria along the wall of the microcentrifuge tube and gently touch the Percoll layer. Pull

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Fig. 1 Transmission electron microscopy visualization of the purified mitochondria showing mitochondria (black arrowhead) and some remaining platelet debris (white arrowhead)

back the tip while keeping a small fluid bridge, slowly release the sample, and allow it to sit on top of the Percoll layer (see Note 7). 2. Centrifuge the sample at 21,000  g for 8 min at 4
C using a slow acceleration and deceleration. 3. Carefully remove the tube from the centrifuge and observe the two white layers. The bottom contains mostly purified mitochondria while the top contains platelet membrane debris, microparticles, and some mitochondria. 4. Using a P100 pipette, direct the tip to the bottom of the tube to collect the mitochondria layer while being careful not to collect the platelet membrane debris. 5. Resuspend the mitochondria in 1 mL of IB and centrifuge at 13,000  g for 10 min to remove the remaining Percoll. 6. The obtained pellet consists of purified platelet mitochondria (Fig. 1) [13]. 7. The purified mitochondria are resuspended in a buffer of choice and volume of choice depending on the downstream application as suggested below (Table 1). 3.4 Mitochondrial Yield by Flow Cytometry

1. Resuspend the purified mitochondria in 500 μL of IB without EDTA (see Note 5). 2. Take 1 μL of mitochondria, add 1 μL of MitoTracker™ Deep Red FM (1 μM) diluted according to the manufacturer’s protocol and 98 μL of PBS.

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Table 1 Buffer selection for platelet mitochondria resuspension Buffer with Respiration buffer EDTA Resuspension 2.2 mL volume Recipe

500 μL

IB (see MiR05 (see Subheading Subheading 2.2, 2.1, item 6) item 1)

Buffer without EDTA

Co-incubation buffer

500 μL

500 μL

IB without EDTA (see Subheading 2.1, item 7)

RPMI 1640 with 10% fetal bovine serum

Fig. 2 Overlay dot plot flow cytometry gating strategy to obtain a total count of the mitochondrial population

3. Incubate in the dark for 15 min. 4. Add 500 μL of PBS. 5. Assess the total count of mitochondria using a flow cytometer gating MitoTracker™ Deep Red FM positive events (Fig. 2) [13]. 3.5 Mitochondrial Yield by Bicinchoninic Acid Assay (BCA)

1. Alternatively, resuspend the purified mitochondria in 500 μL of IB buffer without EDTA. 2. Take 25 μL of mitochondria and add 25 μL of ice-cold NP40 lysis solution. 3. Keep on ice for 15 min while vortexing every 3 min. 4. Spin the mitochondrial sample at 10,000  g for 10 min at 4
C and collect proteins present in the supernatant and transfer to a new microcentrifuge tube.

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5. Proceed to determine the mitochondrial protein concentration using a spectrophotometer following the procedures described by the manufacturer of a micro BCA Protein Assay Kit (Pierce Chemical).

4

Notes 1. Aliquoted Percoll solutions should be refiltered in order to remove aggregated particles which can disrupt the cellular fractionation. 2. Blood tubes should be carefully examined for blood clots as they contain activated platelets. Activated platelets produce microparticles, which are discarded in the isolation of plateletderived mitochondria. 3. Verify the pH of the solutions, especially the IB, as it can shift into unfavorable range after a week of storage at 4
C. 4. Sudden movements while removing the tube of the centrifuge, after the purification step on the Percoll gradient, can disturb the mitochondrial layer on the gradient, rendering the purification ineffective. 5. When resuspending the purified mitochondrial pellet, keep in mind that in the presence of high concentrations of EDTA, mitochondrial respiration measurements, protein assays measurements, and biochemical measurements may be disturbed. 6. Note that the properties of the tissue homogenizer may vary depending on the equipment used. Adjustments should be made by the experimenter on the number of passes of the Teflon in order to obtain a mostly foamy looking substance. The foamy looking extract will then rest on ice and return to a liquid state substance. Other extraction methods have yet to be tested. 7. Separation issues may arise during the Percoll purification steps, as the Percoll solution can change density depending on the lot number. Additional adjustments could be necessary as specific organelle density can vary between donors. Typically, the mitochondria have a density ranging between 1.09 and 1.11 [18], while platelet membranes and microparticles are situated at around 1.04 and 1.06 [19]. This allows the separation of the two when the appropriate density of the Percoll solution is calculated. The following formula, obtained from the GE Percoll manufacturer’s product sheet, can be used to adjust the density of the 15% Percoll solution: ðρ  ρÞ  Vy ¼ Vi i ρ  ρy

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where: Vy: volume of IB in mL (8.33 mL). Vi: volume of PS90 in mL (1.67 mL). ρi: density of PS90 in mL (1.149 g/mL). ρy: density of IB in mL (~1.023 g/mL—can differ when measured). ρ: desired density of final 15% Percoll solution (>1.05 g/mL). The density of PS15 is adjusted by increasing the sucrose content of the IB used to dilute the PS90 to obtain the PS15. This new density IB should not be used for manipulations other than diluting the PS90 to PS15.

Acknowledgments This work was funded by the Canadian Institutes of Health Research (CIHR), New Brunswick Health Research Foundation (NBHRF), New Brunswick Innovation Foundation (NBIF), Natural Sciences and Engineering Research Council (NSERC), and the Universite´ de Moncton. References 1. Davı` G, Patrono C (2007) Platelet activation and atherothrombosis. N Engl J Med 357 (24):2482–2494. https://doi.org/10.1056/ NEJMra071014 2. Boudreau LH, Duchez A-C, Cloutier N, Soulet D, Martin N, Bollinger J, Pare´ A, Rousseau M, Naika GS, Le´vesque T et al (2014) Platelets release mitochondria serving as substrate for bactericidal group IIA-secreted phospholipase A2 to promote inflammation. Blood 124(14):2173–2183. https://doi.org/ 10.1182/blood-2014-05-573543 3. Saraste M (1999) Oxidative phosphorylation at the fin de Sie`cle. Science 283 (5407):1488–1493 4. Zhang Q, Raoof M, Chen Y, Sumi Y, Sursal T, Junger W, Brohi K, Itagaki K, Hauser CJ (2010) Circulating mitochondrial DAMPs cause inflammatory responses to injury. Nature 464(7285):104–107. https://doi.org/10. 1038/nature08780 5. Zhang L, Deng S, Zhao S, Ai Y, Zhang L, Pan P, Su X, Tan H, Wu D (2016) Intraperitoneal administration of mitochondrial DNA provokes acute lung injury and systemic inflammation via toll-like receptor 9. Int J Mol Sci 17(9):1425. https://doi.org/10.3390/ ijms17091425

6. Gray MW, Burger G, Lang BF (1999) Mitochondrial evolution. Science 283 (5407):1476–1481 7. Schlame M (2008) Cardiolipin synthesis for the assembly of bacterial and mitochondrial membranes. J Lipid Res 49(8):1607–1620. https://doi.org/10.1194/jlr.R700018JLR200 8. Hayakawa K, Bruzzese M, Chou SH-Y, Ning M, Ji X, Lo EH (2018) Extracellular mitochondria for therapy and diagnosis in acute central nervous system injury. JAMA Neurol 75(1):119–122. https://doi.org/10. 1001/jamaneurol.2017.3475 9. Marcoux G, Duchez A-C, Rousseau M, Le´vesque T, Boudreau LH, Thibault L, Boilard E (2017) Microparticle and mitochondrial release during extended storage of different types of platelet concentrates. Platelets 28 (3):272–280. https://doi.org/10.1080/ 09537104.2016.1218455 10. Wilkins HM, Carl SM, Weber SG, Ramanujan SA, Festoff BW, Linseman DA, Swerdlow RH (2015) Mitochondrial lysates induce inflammation and Alzheimer’s disease-relevant changes in microglial and neuronal cells. J Alzheimers Dis 45(1):305–318. https://doi.org/10. 3233/JAD-142334

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11. Doucet MS, Jougleux J-L, Poirier SJ, Cormier M, Le´ger JL, Surette ME, Pichaud N, Touaibia M, Boudreau LH (2019) Identification of peracetylated quercetin as a selective 12-lipoxygenase pathway inhibitor in human platelets. Mol Pharmacol 95(1):139–150. https://doi.org/10.1124/ mol.118.113480 12. Frezza C, Cipolat S, Scorrano L (2007) Organelle isolation: functional mitochondria from mouse liver, muscle and cultured filroblasts. Nat Protoc 2(2):287–295. https://doi.org/ 10.1038/nprot.2006.478 13. Le´ger JL, Jougleux J-L, Savadogo F, Pichaud N, Boudreau LH (2019) Rapid isolation and purification of functional platelet mitochondria using a discontinuous Percoll gradient. Platelets 31(2):258–264. https:// doi.org/10.1080/09537104.2019.1609666 14. Gnaiger E, Kuznetsov AV (2002) Mitochondrial respiration at low levels of oxygen and cytochrome c. Biochem Soc Trans 30 (2):252–258 15. Graham JM (2001) Purification of a crude mitochondrial fraction by density-gradient centrifugation. Curr Protoc Cell Biol

Chapter 3:Unit 3.4. https://doi.org/10. 1002/0471143030.cb0304s04 16. Kiss DS, Toth I, Jocsak G, Sterczer A, Bartha T, Frenyo LV, Zsarnovszky A (2016) Preparation of purified Perikaryal and Synaptosomal mitochondrial fractions from relatively small hypothalamic brain samples. MethodsX 3:417–429. https://doi.org/10.1016/j.mex.2016.05.004 17. Fukami MH, Salganicoff L (1973) Isolation and properties of human platelet mitochondria. Blood 42(6):913–918 18. Lo´pez-Mediavilla C, Orfao A, San Miguel J, Medina JM (1992) Developmental changes in rat liver mitochondrial populations analyzed by flow cytometry. Exp Cell Res 203(1):134–140. https://doi.org/10.1016/0014-4827(92) 90048-D 19. Perret B, Chap HJ, Douste-Blazy L (1979) Asymmetric distribution of arachidonic acid in the plasma membrane of human platelets a determination using purified phospholipases and a rapid method for membrane isolation. Biochim Biophys Acta Biomembr 556 (3):434–446. https://doi.org/10.1016/ 0005-2736(79)90131-7

Chapter 5 Mechanical Permeabilization as a New Method for Assessment of Mitochondrial Function in Insect Tissues Alessandro Gaviraghi, Yan Aveiro, Stephanie S. Carvalho, Rodiesley S. Rosa, Matheus P. Oliveira, and Marcus F. Oliveira Abstract Respirometry analysis is an effective technique to assess mitochondrial physiology. Insects are valuable biochemical models to understand metabolism and human diseases. Insect flight muscle and brain have been extensively used to explore mitochondrial function due to dissection feasibility and the low sample effort to allow oxygen consumption measurements. However, adequate plasma membrane permeabilization is required for substrates/modulators to reach mitochondria. Here, we describe a new method for study of mitochondrial physiology in insect tissues based on mechanical permeabilization as a fast and reliable method that do not require the use of detergents for chemical permeabilization of plasma membrane, while preserves mitochondrial integrity. Key words Metabolism, Bioenergetics, Animal models, Insect, Mitochondria, Respiration

1

Introduction In recent years, insects are increasing their importance as organism models for the study of human pathologies, evolutionary mechanisms, and drug discovery. This is due to the conservation between insects and mammals of various key mechanisms such as signaling pathways [1], energy metabolism [2–4], and organs structural and functional components [5]. Furthermore, insects are cost-effective, easy to rear, and have a relatively short-life cycle, which makes them easy to use in aging studies. The main insect used as organism model is the Drosophila melanogaster which has been used for more than 100 years in biomedical science. Just to highlight the importance of this organism, six Nobel prizes were awarded for discoveries in which Drosophila was used as a study model [6– 11]. Indeed, our understanding of key mechanisms involved in many physiological and pathological processes owes to the use of Drosophila as an organism model [12–17].

Volkmar Weissig and Marvin Edeas (eds.), Mitochondrial Medicine: Volume 2: Assessing Mitochondria, Methods in Molecular Biology, vol. 2276, https://doi.org/10.1007/978-1-0716-1266-8_5, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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The energy demand required for muscle contraction or physiological function is provided by the production of ATP through oxidative phosphorylation in mitochondria. This process occurs at the inner mitochondrial membrane and involves protein complexes which, through sequential redox reactions, generate a protonmotive force (pmf) that is used by the ATP synthase complex for ATP production. In fact, mitochondria play a fundamental role in cellular metabolism using the energy derived from oxidation of carbohydrates, lipids, and amino acids to generate ATP. In this sense, high-resolution respirometry is employed to assess mitochondrial physiology and cellular metabolism. This technique provides precise and dynamic information on the metabolic flow (oxygen consumption rate) concerning the transport of nutrients, oxidation efficiency, and phosphorylation capacity (ATP production). Highresolution respirometry represents a powerful tool for investigating cellular bioenergetic state, identifying potential biomarkers, and studying metabolic reprogramming in several diseases. Finally, high-resolution respirometry can be used in the conditions when amounts of cells or tissue are limiting. In recent years, several approaches were developed and validated to study mitochondrial physiology using chemically permeabilized tissues and cells in different animal species [18–25]. These methods allow bypassing the possible limitations due to the process of isolation of mitochondria such as loss of mitochondrial morphology [26], low recovery, and potential selection of distinct mitochondrial subpopulations [27]. The methods employed for cell or tissue permeabilization are mainly based on the treatment of the samples with either digitonin or saponin, two weak nonionic detergents. These chemicals allow the selective permeabilization of the plasma membrane by forming complexes with the cholesterol present in the plasma membrane. This is due to the nonhomogeneous distribution of the cholesterol in the different types of cellular membranes. Indeed, the cholesterol content in the plasma membrane of mammals is usually higher compared to organelles membranes (>20% of weight mass for the plasma membrane vs. ~3% in mitochondrial membranes) [28–31]. These chemical permeabilization methods were developed for mammalians cells and subsequently used for other organisms, including insects. However, the lipid composition of the plasma membrane is remarkably different between mammals and insects. Particularly, the cholesterol content in insect’s plasma membrane is ten times lower than their mammalian counterparts, while the phosphatidylethanolamine/phosphatidylcholine ratio is four times higher [32, 33]. These differences in the lipid composition determine the plasma membrane properties, and the cholesterol content plays a major role in membrane fluidity, permeability, and hydrophobicity [29, 31]. The very low content of

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cholesterol in insect plasma membranes is due to the inability of this class to synthesize cholesterol de novo, which is essentially obtained through the diet to supply their physiological requirements [34]. These unique insect membrane features have prompted us to develop and validate new approaches for insect plasma membrane permeabilization to allow studies of mitochondrial physiology in these organisms [35, 36]. In this chapter, we describe and validate two reliable protocols to assess mitochondrial physiology in situ using mechanically permeabilized tissues of the major arbovirus vector Aedes aegypti mosquitoes and D. melanogaster fruit flies in combination with high-resolution respirometry. Both protocols were based on a previously published method designed for A. aegypti flight muscle [36].

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1. Respiration buffer: 120 mM KCl, 5 mM KH2PO4, 3 mM HEPES, 1 mM EGTA, 1.5 mM MgCl2, and 0.2% fatty acid– free bovine serum albumin, adjusted to pH 7.2. Prepare in ultrapure double-distilled water, divide in aliquots, and store at
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1. ADP: Prepare 0.5 M of ADP in ultrapure double-distilled water. Neutralize to pH 7.2 with NaOH, check pH, divide in 0.2 mL aliquots, and store at
80  C. 2. Ascorbate: Prepare 0.8 M of ascorbate sodium salt in ultrapure double-distilled water. To avoid autooxidation, the solution should always be used fresh (see Note 1). 3. Cytochrome c: Prepare 2 mM of cytochrome c in ultrapure double-distilled water. The solution can be stored as 0.2 mL aliquots at
20  C (see Note 2). 4. G3P: Prepare 1 M of sn-glycerol 3-phosphate bis(cyclohexylammonium) salt in ultrapure double-distilled water. G3P solution can be stored as 0.2 mL aliquots at
20  C (see Note 3). 5. Glutamate: Prepare 1 M of L-glutamic acid in ultrapure doubledistilled water. Neutralize to pH 7.2 with NaOH, check pH, divide in 0.5 mL aliquots, and store at
20  C. 6. Malate: Prepare 0.5 M of L-malic acid in ultrapure doubledistilled water. Neutralize to pH 7.2 with NaOH, check pH, divide in 0.5 mL aliquots, and store at
20  C. 7. Proline: Prepare 0.5 M of L-proline in ultrapure doubledistilled water. The solution can be stored as 0.5 mL aliquots at
20  C.

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8. Pyruvate: Prepare 1 M of sodium pyruvate in ultrapure doubledistilled water; the solution should be used always fresh (see Note 4). 9. Succinate: Prepare 0.5 M of sodium succinate dibasic in ultrapure double-distilled water. Succinate solution can be stored as 0.5 mL aliquots at
20  C. 10. TMPD: Prepare 0.2 M of N,N,N0 ,N0 -Tetramethyl-p-phenylenediamine dihydrochloride in ultrapure double-distilled water. To avoid autooxidation, the solution should be fresh (see Note 5). 2.3

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1. FCCP: Prepare 1 mM of carbonyl cyanide p-(trifluoro-methoxy) phenyl-hydrazone in absolute ethanol. The stock solution can be stored as 0.1 mL aliquots at
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1. Antimycin A: Prepare a stock solution at 5 mM in absolute ethanol, divide in 0.2 mL aliquots, and store at
20  C. 2. Carboxyatractyloside: Prepare 5 mM of carboxyatractyloside potassium salt in ultrapure double-distilled water, divide in 0.2 mL aliquots, and store at
20  C. 3. KCN: Prepare 1 M of potassium cyanide in ultrapure doubledistilled water. The solution should be fresh (see Note 7). 4. Oligomycin: Prepare a stock solution at 4 mg/mL (5 mM) in absolute ethanol, divide in 0.2 mL aliquots, and store at
20  C. 5. Rotenone: Prepare a stock solution at 1 mM in absolute ethanol, divide in 0.2 mL aliquots, and store at
20  C. 6. Sodium azide: Prepare a stock solution at 4 M in ultrapure double-distilled water, divide in 0.5 mL aliquots, and store at
20  C. For a complete inhibition of cytochrome c oxidase (COX) activity, use 100 mM as final concentration.

3 3.1

Methods Insects

Aedes aegypti (Aedes-RIO strain [44]), obtained from F8–F10 eggs, were raised under a photoperiod of 12 h light/dark at 28  C and 70–80% relative humidity. Larvae were fed on a diet consisting of commercial dog chow, and the adults were maintained in a plastic cage in a 1:2 sex-ratio and fed ad libitum on cotton pads soaked with 10% (w/v) sucrose solution. Females 1–4 days after the emergence were utilized in the experiments. Drosophila melanogaster (w1118 strain) were raised under a photoperiod of 12 h light/dark in a B.O.D incubator at 25  C with a variation of 0.5  C, at normal levels of humidity (50% RH). Flies were fed on a diet consisting of 1% agar, 2.7% yeast extract,

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1.7% sucrose, 3.5% dextrose, and 8.3% cornmeal in a w/v relation with distilled water. After the culture medium is cooked, 1.1% propionic acid and 1.5% methylparaben v/v were added to the hot solution. Culture media changes were done twice a week. Males 1–6 days after hatching were utilized in the experiments. 3.2 Sample Preparation

1. Using an aspirator, collect the mosquitoes and transfer them to a closed container (see Note 8).

3.2.1 A. aegypti Head Dissection (Fig. 1a–c)

2. Since the cold anesthetize the mosquitoes, put the container on ice and wait 5–10 min until the mosquitoes stop moving. 3. Mosquitoes were then transferred to glass petri dishes on ice for the dissection (see Note 9). 4. Use fine-tipped forceps to immobilize the mosquito by holding the thorax gently against the glass petri dish. 5. Separate the head from the rest of the mosquito body severing the membrane that joins the head to the thorax supported by two laterals cervical sclerites [37] with a second fine-tipped forceps.

Fig. 1 Simplified scheme employed for insect tissues dissection. A. aegypti head dissection: (a) The mosquito was anesthetized by chilling on ice onto a precooled petri glass dish. (b) Forceps were used to immobilize the mosquito and, using another forceps, the head is separated by severing the membrane that joins the head to the thorax. (c) The heads are grouped in a microcentrifuge tube in the ice up to 15 units and then transferred to the respirometer chamber. D. melanogaster thorax dissection: (d) Paws and wings were gently removed. (e) Immobilize the fly using fine-tipped forceps and remove the head using a scalpel. (f) The abdomen was also removed using a tweezers and a scalpel. (g) The two thoraxes were immediately transferred to the respirometer chamber for mechanical permeabilization

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6. Group 15 heads in a microcentrifuge tube on ice and keep on cold. 7. Transfer the 15 heads to the Oroboros respirometer chamber (Oxygraph-2 k, O2k Oroboros Instruments, Innsbruck, Austria) filled with 2 mL of “respiration buffer” described above. 3.2.2 D. melanogaster Thorax Dissection (Fig. 1d–g)

1. Flies (1–6 days old after hatching) were anesthetized for 8 s in CO2 and transferred to a CO2 fly pad. Males were separated and transferred in a vial immersed on ice for 1.5 min. 2. Flies were transferred to a precooled petri dish in the dorsal position and dissected using scalpel and fine-tipped forceps. 3. Using fine-tipped forceps immobilize the fly by gently holding the abdomen against the surface and remove the head by using a scalpel. 4. Place the fly in lateral decubitus position and remove the abdomen from thorax by making a cut at the level of the mediotergite. 5. Immediately transfer two thoraces to the Oroboros respirometer chamber (Oxygraph-2 k, O2k Oroboros Instruments, Innsbruck, Austria) filled with 2 mL of the “respiration buffer.”

3.3 Mechanical Permeabilization and Respirometry Measurements Protocols 3.3.1 A. aegypti Heads

1. Place the heads stored in microcentrifuge tubes into the Oroboros chambers by shedding the microcentrifuge tubes content or transferring with forceps, if the samples get stick to the tube bottom. 2. Before closing the chamber, insert a Hamilton syringe in the stopper capillary (preferably 50 μL because the needle is larger) to avoid the exit of the tissues. Then close the chamber. 3. The heads tend to cluster once in the chamber with respiration buffer. Pull the stopper up and push down very carefully in order to disaggregate them. Make sure that the heads’ cluster is apart in small groups to facilitate the permeabilization and avoid formation of air bubbles (see Note 10). 4. Mechanical permeabilization is carried out inside the respirometer chamber by stirring at 750 rpm and by raising and lowering the stopper until the solution appears turbid and the heads are no longer observed (about 10 min). 5. Respirometry analysis is carried out at 27.5  C following the protocol established by our group [36]. 6. Start the substrate–uncoupler–inhibitor titration (SUIT) protocol by injecting 20 μL of a 1 M pyruvate (10 mM final concentration) in each respirometer chamber and wait for stabilization of oxygen consumption rates. Then add 40 μL of a 0.5 M Proline (10 mM final concentration) and wait for stabilization of oxygen consumption rates (red trace, see Fig. 2).

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Fig. 2 Simplified scheme of mechanical permeabilization and respirometry analyses for A. aegypti head. (a) The heads were transferred to the respirometer chamber. (b) Mechanical permeabilization is performed by magnetic stirring at 750 rpm raising and lowering the stopper of the respirometer for about 10 min. (c) The permeabilization was obtained when the solution appears turbid and the heads are no longer observed. (d) Start the substrate–uncoupler–inhibitor titration (SUIT) protocol. (e) Typical traces of oxygen consumption rates (red line) and concentration (blue line) from mechanically permeabilized heads using 10 mM pyruvate plus proline as substrate

7. Inject 4 μL of a 0.5 M ADP (1 mM final concentration) to stimulate oxygen consumption linked to ATP synthesis (see Note 11). 8. Make stepwise titrations of carbonyl cyanide p-(trifluoromethoxy) phenylhydrazone (FCCP) from 0.2 to 1.5 μM (0.4–3 μL of a 1 mM solution) to induce maximum uncoupled respiration.

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9. To determine the contribution of complex I on the electron flow, add 1 μL of a 1 mM rotenone (a complex I inhibitor) in order to reach a final concentration of 0.5 μM. 10. Add 1 μL of a 5 mM antimycin A (AA) (2.5 μM final concentration), to inhibit complex III and to fully block oxygen consumption linked to mitochondrial electron transfer system. 11. Raise the stopper using the Oroboros Stopper-Spacer to form an air bubble in the chamber and inject an oxygen-enriched gaseous mixture (70% O2 and 30% N2 mol/mol) using a 60 mL syringe to reach an oxygen concentration close to 500 nmol/mL (see Note 12). 12. Assess cytochrome c oxidase (COX) activity by adding 5 μL of a 0.8 M ascorbate (2 mM final concentration) and 5 μL of a 0.2 M N,N,N0 ,N0 -Tetramethyl-p-phenylenediamine dihydrochloride (0.5 mM final concentration) (TMPD), as an electron-donor regenerating system (see Note 13). 13. Add 4 μL of 1 M KCN (2 mM final concentration) to inhibit COX activity (see Note 14). 3.3.2 D. melanogaster Thorax

1. Transfer the two thoraces to the Oroboros chambers using a brush. 2. Before closing the chamber, insert a Hamilton syringe in the stopper capillary (preferably 50 μL because the needle is larger) to avoid the exit of the tissues. Then close the chamber. Make sure to eliminate all air bubbles in the solution (see Note 10). 3. Permeabilize mechanically the thoraces by stirring at 900 rpm for 7.5 min (other timepoints were tested and did not produce satisfactory results). 4. Reduce the stirring speed to 750 rpm and start the respirometry analysis at 27.5  C as previously established by our group [36] (see Note 15). 5. After starting the analysis, raise the stopper using the Oroboros Stopper-Spacer to form an air bubble in the chamber. Inject an oxygen-enriched gaseous mixture (70% O2 and 30% N2 mol/mol) using a 60 mL syringe to reach an oxygen concentration close to 500 nmol/mL (see Note 16). 6. Start the substrate–uncoupler–inhibitor titration (SUIT) protocol by injecting all substrates able to stimulate complex I, II, and glycerol phosphate dehydrogenase (red trace, see Fig. 3) as following: 20 μL of a 1 M pyruvate (10 mM final concentration), 20 μL of a 1 M glutamate (10 mM final concentration), 20 μL of a 0.5 M malate (5 mM final concentration), and wait for stabilization of oxygen consumption rates. Then add 10 μL of a 0.5 M succinate (5 mM final concentration), wait for stabilization of oxygen consumption rates, and add 30 μL of a 1 M glycerol-3-phosphate (15 mM final concentration).

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Fig. 3 Simplified scheme of mechanical permeabilization and respirometry analyses for D. melanogaster thoraces. (a) Two thoraces were transferred to the respirometer chamber. (b) Mechanical permeabilization was performed by magnetic stirring at 900 rpm for 7.5 min, then the stirring speed was reduced to 750 rpm. (c) An oxygen-enriched gaseous mixture (70% O2 and 30% N2 mol/mol) was injected through the stopper of each chamber using a 60 mL syringe to reach an oxygen concentration close to 500 nmol/mL. (d) Start the substrate–uncoupler–inhibitor titration (SUIT) protocol. (e) Typical traces of oxygen consumption rates (red line) and concentration (blue line) from mechanically permeabilized thoraces using all substrates able to stimulate complex I, II, and glycerol phosphate dehydrogenase

7. Inject 20 μL of a 0.5 M ADP (5 mM final concentration) to stimulate oxygen consumption linked to ATP synthesis (see Note 11). 8. Add 10 μL of a 2 mM cytochrome c (10 μM final concentration) (see Note 17). 9. Make stepwise titrations of FCCP from 0.2 to 1.5 μM (0.4–3 μL of a 1 mM solution) to induce maximum uncoupled respiration.

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10. Add 1 μL of a 5 mM antimycin a (AA) (2.5 μM final concentration) to inhibit complex III and to block oxygen consumption linked to mitochondrial electron transfer system. 11. Raise the stopper using the Oroboros Stopper-Spacer to form an air bubble in the chamber and inject an oxygen-enriched gaseous mixture (70% O2 and 30% N2 mol/mol) using a 60 mL syringe to reach an oxygen concentration close to 500 nmol/mL (see Note 12). 12. Assess COX activity by adding 5 μL of a 0.8 M ascorbate (2 mM final concentration) and 5 μL of a 0.2 M N,N,N0 ,N0 Tetramethyl-p-phenylenediamine dihydrochloride (0.5 mM final concentration) (TMPD), as an electron-donor regenerating system (see Note 13). 13. Add 4 μL of 1 M KCN (2 mM final concentration) to inhibit COX activity (see Note 14). 3.4 Data Interpretation

Starting from the oxygen consumption data obtained from the respirometry analysis, it is possible to calculate different respiratory states that characterize the mitochondrial metabolism (Fig. 4). 1. Leak: This metabolic state represents the oxygen consumption induced only by the addition of the oxidizable substrates. The respiratory rates of the leak state are essentially controlled by the magnitude of proton leak through the inner mitochondrial membrane. Higher the proton leak, higher the leak respiratory

Fig. 4 Schematic representation to calculate the mitochondrial metabolic states. Simplified scheme of the typical traces of oxygen consumption (red line) and concentration (blue line) obtained from respirometry analyses using the Oroboros system. Each mitochondrial metabolic state calculated is depicted in orange fonts

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rates [38]. Leak is calculated by subtracting from the oxygen consumption obtained after the addition of all the oxidizable substrates from that after adding AA. 2. OXPHOS: This metabolic state represents the oxygen consumption coupled to the ATP production and is obtained after the addition of ADP. OXPHOS is calculated by subtracting the substrates (leak) oxygen consumption rates from those after ADP addition. 3. ETS (electron transfer system): This metabolic state reflects the maximum oxygen consumption rates linked to mitochondrial electron transport system (ETS) without the effect of protonmotive force. To asses this, a proton ionophore (or uncoupler) is added to provide the maximal respiratory rates, in our case we used FCCP. The ETS state is calculated by subtracting the oxygen consumption rates obtained after FCCP from those obtained after adding AA. 4. Spare capacity: This metabolic state represents how much oxygen consumption can increase in response to increased energy demand. Thus, it represents the maximum capacity of the electron transport system. Spare capacity is calculated by subtracting the oxygen consumption rates obtained after FCCP from those obtained after adding ADP. 5. ROX (residual oxygen consumption): This metabolic state represents the oxygen consumption rates linked to cellular processes other than respiration, such as oxygenase activities, reactive oxygen species production. ROX is determined by quantifying the oxygen consumption rates obtained after addition of AA. 6. Cytochrome c oxidase (COX) activity: Represents the oxygen consumption rates specifically due to COX activity and is calculated by subtracting the oxygen consumption rates obtained after addition of ascorbate and TMPD from those after KCN (or sodium azide) addition. 7. Normalization of oxygen consumption data: This is a critical aspect and several parameters have been used in the literature to normalize respirometry data including tissue wet weight, protein content, citrate synthase activity, mitochondrial DNA, and others. Each normalizer has its limitations, but we think that using total protein content is a reliable solution. A group of insects belonging to the same cohort are used to quantify the protein content. For this purpose, the insects were dissected, and tissues homogenized in a ground glass potter in hypotonic buffer (25 mM potassium phosphate and 5 mM MgCl2, pH 7.2). Subsequently, the solution was centrifuged at 1500  g for 10 min, the supernatant was recovered, and the protein content was determined by the Lowry method [39] (see Note 18).

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The protocol designed here to assess respiratory rates in A. aegypti heads was suitable for quantitative identification of mitochondrial metabolic states (Fig. 5a, b) and represents an evolution of the method developed for the flight muscle [36]. This was accomplished by performing few changes in the permeabilization protocol to make it optimal for the analysis of the oxygen consumption of mosquito head. To validate the method described here, the following set of experiments was designed to confirm the integrity of inner mitochondrial membrane and OXPHOS coupling after mechanical permeabilization.

3.5 Protocols Validation 3.5.1 A. aegypti Heads

1. To assess the OXPHOS coupling, add 1 μL of a 4 mg/mL oligomycin (2 μg/mL final concentration), a powerful inhibitor of F1Fo ATP synthase complex, after the addition of ADP. A. aegypti

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Fig. 5 Quantitative comparison of respiratory rates and mitochondrial metabolic states obtained in A. aegypti and D. melanogaster samples. (a) and (c) Quantification of respiratory rates obtained in respirometry analyses using Oroboros. (b) and (d) Mitochondrial metabolic states calculated from oxygen consumption data as reported above. Data are expressed as mean O2 consumption rates (pmoles/s/μg protein)  standard error of the mean (SEM) of at least four different experiments

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Fig. 6 Intactness of mitochondrial inner membrane in mechanically permeabilized A. aegypti heads. Typical traces of oxygen concentration (blue line) and consumption rates (red line) from mechanically permeabilized heads in the presence of 5 μM carboxyatractyloside (CAT) (a) or 2 μg/mL oligomycin (oligo) (b). The strong inhibition of respiratory rates after CAT and oligomycin injection demonstrates the intactness of the inner mitochondrial membrane and the high degree of OXPHOS coupling. The addition of OXPHOS modulators pyruvate (Pyr), proline (Pro), ADP, and antimycin A (AA) is represented with an arrow and their concentrations were reported in the Methods section

2. To assess the integrity of the inner mitochondrial membrane, inject 2 μL of a 5 mM carboxyatractyloside (CAT) (5 μM final concentration), a highly selective and potent inhibitor of adenine nucleotide translocator (ANT) after the ADP addition [40]. Figure 6 shows that respiratory rates in mechanically permeabilized heads provided by Pyr + Pro under phosphorylating conditions (1 mM ADP) were reduced by 92% after oligomycin (Fig. 6a) or CAT (Fig. 6b) treatment. This indicates that mitochondrial inner membrane in mechanically permeabilized heads is intact, conferring high OXPHOS coupling when using Pyr + Pro as substrates. 3.5.2 D. melanogaster Thorax

The protocol designed here to assess respiratory rates in D. melanogaster flight muscle was suitable to quantitatively identify distinct mitochondrial metabolic states (Fig. 5c, d).

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Fig. 7 Mechanical permeabilization provides respiratory rates undistinguishable from chemical permeabilization. (a) Representative traces of oxygen consumption of mechanically permeabilized (red line) and chemically (saponin) permeabilized (green line) D. melanogaster thoraces. Oxygen concentration levels are depicted as blue traces. (b) Quantitative comparison of respiratory rates obtained using the two permeabilization methods (white—mechanical, black—chemical). Oxygen consumption rates obtained using both methods were quite similar, regardless the mitochondrial metabolic states. This indicates that mechanical permeabilization is sufficient to allow free access for substrates and OXPHOS modulators in D. melanogaster thoraces, without affecting mitochondrial structure and integrity. Data are expressed as mean O2 consumption rates (pmoles/s/μ g protein)  standard error of the mean (SEM) of at least six different experiments. Comparisons between groups were done by two-way ANOVA for repeated measurements and a posteriori Holm–Sidak post hoc test, adjusted for multiple comparisons

To validate the method described here, comparative respirometry experiments were performed using a protocol established for D. melanogaster [20, 21, 23, 41], which use the combination of chemical (using the detergent saponin) and mechanical permeabilization of flight muscle (Fig. 7). The isolated thoraxes are chemically permeabilized in saponin (50 μg/mL), prepared in ice-cold BIOPS (BIOPS: 2.77 mM CaK2EGTA, 7.23 mM K2EGTA, 5.77 mM Na2ATP, 6.56 mM MgCl2·6H2O, 20 mM taurine, 15 mM Na2phosphocreatine, 20 mM imidazole, 0.5 mM DTT, 50 mM MES hydrate), for 15 min in 80 rpm orbital shaker. The thoraces were then washed for 2 times for 5 min each in 2 mL of

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6 Pyr Glu Mal Succ

ADP G3P

Cytochrome c induced oxygen consumption

4 2

110

Cyt c

0 20

[pmol/s/µg protein]

440

O2 Consumption

O2 Concentration

550

81

0

25 Time [min]

Fig. 8 Representative traces of oxygen consumption rates associated to a correct (green line) and excessive (red line) permeabilization. The green trace represents an optimal permeabilization condition (7.5 min at 900 rpm) where a large increase in oxygen consumption is observed after the addition of ADP while a slight increase in oxygen consumption is obtained after the addition of cytochrome c. Instead, red trace represents an excessive permeabilization condition purposely obtained by increasing the stirring time to 10 min at 900 rpm, where a large increase in oxygen consumption is observed after the addition of cytochrome c. A significant increase in oxygen consumption after cytochrome c indicates the loss of mitochondrial integrity; in fact the mitochondrial outer membrane is impermeable to cytochrome c. In addition, excessive permeabilization (red trace) compromised inner mitochondrial membrane as ADP failed to increase respiratory rates as should be expected FCCP

Cyt c

AA 10

220

2

[nmol/ml]

330

8 Pyr Glu Mal Succ G3P

ADP

Cyt c

FCCP

6 AA

4

110

2

[pmol/s/µg protein]

440

O2 Concentration

O Concentration

550

0

0 20

25

30

35

40

Time [min]

Fig. 9 Representative traces of oxygen consumption rate associated to a correct (green line) and insufficient (orange line) permeabilization. The green trace represents an optimal permeabilization condition (7.5 min at 900 rpm) where a large increase in oxygen consumption is observed after the addition of ADP while a slight increase in oxygen consumption is obtained after the addition of cytochrome c. Instead, orange trace represents an insufficient permeabilization condition purposely obtained by reducing the stirring time to 3 min at 750 rpm, where only a slight increase in oxygen consumption was observed after the addition of substrates, ADP, and FCCP

ice-cold respiration buffer and then transferred to the Oroboros chambers containing 2 mL of respiration buffer. The SUIT protocol used was the same as described in the Methods section. 3.6

Troubleshooting

Figures 8 and 9 represent the two extreme cases of excessive and insufficient permeabilization of the tissues, respectively.

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Notes 1. Ascorbate is light sensitive, therefore protect the tubes with aluminum foil. 2. Use only cytochrome c from equine heart. 3. Do not use the G3P racemic mixture because only the L enantiomer is metabolized. 4. Pyruvate is an alpha keto acid which is unstable in aqueous solution; therefore, the solution should be fresh. 5. TMPD is light sensitive, therefore protect the tubes with aluminum foil. 6. FCCP is light sensitive, therefore the stock and working solutions have to be kept in tubes protected with aluminum foil. 7. KCN is photosensitive and hygroscopic, therefore protect the tubes with aluminum foil. 8. Be careful when handling with insects to avoid their escape. 9. Use a precooled petri dish to prevent contact with a warmer surface that can awaken the mosquitoes. 10. The presence of air bubbles in the chamber during the analysis causes alterations and instability in the detection of oxygen consumption. 11. If a significant increase in oxygen consumption is not observed, there may be problems with the permeabilization of the tissue. 12. COX activity is limited by low oxygen concentrations [42], so an oxygen-enriched gas mixture is injected to avoid oxygendeprivation during measurements. 13. Ascorbate is added first to maintain TMPD in a reduced state. 14. TMPD autoxidizes in an oxygen and concentration-dependent manner. 15. To validate the method described here, comparative respirometry experiments were performed using a protocol established for D. melanogaster studies [20, 21, 23, 41], which use the combination of chemical (using the detergent saponin) and mechanical permeabilization of the tissue. 16. The oxygen tension is increased to avoid potential effects of oxygen diffusion and electron transfer due to oxygen deficiency during measurements [19]. Also, injections of oxygenenriched gaseous mixture were performed once the oxygen concentration fell down below 150 nmol/mL into the O2k-chamber. 17. This step allows the evaluation of the integrity of the outer mitochondrial membrane. In fact, the external mitochondrial

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membrane is impermeable to cytochrome c [43], so a significant increase in oxygen consumption after its addition indicates the loss of mitochondrial integrity. 18. The protein content cannot be measured at the end of the respirometry analysis because the “respiration buffer” contains albumin which, being a protein, distorts the dosage of the protein content.

Acknowledgments We would like to thank Mrs. Geane C. Braz for the excellent technical assistance on maintenance of A. aegypti colony. This study was financed in part by the Coordenac¸˜ao de Aperfeic¸oamento de Pessoal de Nı´vel Superior—Brasil (CAPES)—Finance Code 001, by the Conselho Nacional de Desenvolvimento Cientifico e Tecnolo´gico (CNPq) [grant numbers 404153/2016-0 MFO, and 483334/2013-8 AG], and the Fundac¸˜ao Carlos Chagas Filho de Amparo a` Pesquisa do Estado do Rio de Janeiro (FAPERJ) [grant numbers E-26/102.333/2013, E-26/203.043/2016, and E-26/111.169/2011]. AG and MFO are CNPq fellows [grant numbers 402409/2012-4 and 303044/2017-9] and from PAPD-FAPERJ [grant number E-44/208702/2014]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. References 1. Stokes BA, Yadav S, Shokal U, Smith LC, Eleftherianos I (2015) Bacterial and fungal pattern recognition receptors in homologous innate signaling pathways of insects and mammals. Front Microbiol 6:19. https://doi.org/ 10.3389/fmicb.2015.00019 2. Beenakkers AMT, Van der Horst DJ, Van Marrewijk WJA (1984) Insect flight muscle metabolism. Insect Biochem 14:243–260. https:// doi.org/10.1016/0020-1790(84)90057-X 3. Rittschof CC, Schirmeier S (2018) Insect models of central nervous system energy metabolism and its links to behavior. Glia 66:1160–1175. https://doi.org/10.1002/ glia.23235 4. Yang Y, Xu S, Xu J, Guo Y, Yang G (2014) Adaptive evolution of mitochondrial energy metabolism genes associated with increased energy demand in flying insects. PLoS One 9: e99120. https://doi.org/10.1371/journal. pone.0099120 5. Baker KD, Thummel CS (2007) Diabetic larvae and obese flies-emerging studies of

metabolism in Drosophila. Cell Metab 6:257–266. https://doi.org/10.1016/j.cmet. 2007.09.002 6. Morgan TH, Bridges CB (1916) Sex-linked inheritance in Drosophila. Carnegie Institution of Washington, Washington 7. Muller HJ (1928) The production of mutations by X-rays. Proc Natl Acad Sci U S A 14:714–726. https://doi.org/10.1073/pnas. 14.9.714 8. The Nobel Prize in Physiology or Medicine 1995. In: NobelPrize.org. https://www. nobelprize.org/prizes/medicine/1995/sum mary/. Accessed 25 Nov 2019 9. Buck L, Axel R (1991) A novel multigene family may encode odorant receptors: a molecular basis for odor recognition. Cell 65:175–187. https://doi.org/10.1016/0092-8674(91) 90418-x 10. Lemaitre B, Nicolas E, Michaut L, Reichhart JM, Hoffmann JA (1996) The dorsoventral regulatory gene cassette sp€atzle/toll/cactus controls the potent antifungal response in

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20. Pichaud N, Ballard JWO, Tanguay RM, Blier PU (2011) Thermal sensitivity of mitochondrial functions in permeabilized muscle fibers from two populations of Drosophila simulans with divergent mitotypes. Am J Physiol Regul Integr Comp Physiol 301:R48–R59. https:// doi.org/10.1152/ajpregu.00542.2010 21. Pichaud N, Ballard JWO, Tanguay RM, Blier PU (2013) Mitochondrial haplotype divergences affect specific temperature sensitivity of mitochondrial respiration. J Bioenerg Biomembr 45:25–35. https://doi.org/10.1007/ s10863-012-9473-9 22. Saks VA, Veksler VI, Kuznetsov AV, Kay L, Sikk P, Tiivel T, Tranqui L, Olivares J, Winkler K, Wiedemann F, Kunz WS (1998) Permeabilized cell and skinned fiber techniques in studies of mitochondrial function in vivo. Mol Cell Biochem 184:81–100 23. Simard CJ, Pelletier G, Boudreau LH, HebertChatelain E, Pichaud N (2018) Measurement of mitochondrial oxygen consumption in permeabilized fibers of drosophila using minimal amounts of tissue. J Vis Exp (134):57376. https://doi.org/10.3791/57376 24. Veksler VI, Kuznetsov AV, Sharov VG, Kapelko VI, Saks VA (1987) Mitochondrial respiratory parameters in cardiac tissue: a novel method of assessment by using saponin-skinned fibers. Biochim Biophys Acta 892:191–196 25. Votion D-M, Gnaiger E, Lemieux H, Mouithys-Mickalad A, Serteyn D (2012) Physical fitness and mitochondrial respiratory capacity in horse skeletal muscle. PLoS One 7: e34890. https://doi.org/10.1371/journal. pone.0034890 26. Picard M, Taivassalo T, Ritchie D, Wright KJ, Thomas MM, Romestaing C, Hepple RT (2011) Mitochondrial structure and function are disrupted by standard isolation methods. PLoS One 6:e18317. https://doi.org/10. 1371/journal.pone.0018317 27. Piper HM, Sezer O, Schleyer M, Schwartz P, Hu¨tter JF, Spieckermann PG (1985) Development of ischemia-induced damage in defined mitochondrial subpopulations. J Mol Cell Cardiol 17:885–896 28. Jamieson GA, Robinson DM (2014) Mammalian cell membranes: volume 2: the diversity of membranes. Elsevier, London 29. Raffy S, Teissie´ J (1999) Control of lipid membrane stability by cholesterol content. Biophys J 76:2072–2080. https://doi.org/10.1016/ S0006-3495(99)77363-7 30. Korn ED (1969) Cell membranes: structure and synthesis. Annu Rev Biochem

Assessing Mitochondrial Function in Tissues 38:263–288. https://doi.org/10.1146/ annurev.bi.38.070169.001403 31. Subczynski WK, Pasenkiewicz-Gierula M, Widomska J, Mainali L, Raguz M (2017) High cholesterol/low cholesterol: effects in biological membranes: a review. Cell Biochem Biophys 75:369–385. https://doi.org/10. 1007/s12013-017-0792-7 32. Gimpl G, Klein U, Reil€ander H, Fahrenholz F (1995) Expression of the human oxytocin receptor in baculovirus-infected insect cells: high-affinity binding is induced by a cholesterol-cyclodextrin complex. Biochemistry 34:13794–13801 33. Dawaliby R, Trubbia C, Delporte C, Noyon C, Ruysschaert J-M, Van Antwerpen P, Govaerts C (2016) Phosphatidylethanolamine is a key regulator of membrane fluidity in eukaryotic cells. J Biol Chem 291:3658–3667. https:// doi.org/10.1074/jbc.M115.706523 34. Krebs KC, Lan Q (2003) Isolation and expression of a sterol carrier protein-2 gene from the yellow fever mosquito, Aedes aegypti. Insect Mol Biol 12:51–60. https://doi.org/10. 1046/j.1365-2583.2003.00386.x 35. Teulier L, Weber J-M, Crevier J, Darveau C-A (2016) Proline as a fuel for insect flight: enhancing carbohydrate oxidation in hymenopterans. Proc Biol Sci 283:20160333. https://doi.org/10.1098/rspb.2016.0333 36. Gaviraghi A, Oliveira MF (2019) A method for assessing mitochondrial physiology using mechanically permeabilized flight muscle of Aedes aegypti mosquitoes. Anal Biochem 576:33–41. https://doi.org/10.1016/j.ab. 2019.04.005 37. Snodgrass RE (1959) The anatomical life of the mosquito. Smithson Misc Coll 139, 87pp

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Chapter 6 Analysis of Mitochondrial Retrograde Signaling in Yeast Model Systems Nicoletta Guaragnella, Masˇa Zˇdralevic´, Zdena Palkova´, and Sergio Giannattasio Abstract Mitochondrial retrograde signaling is a mitochondria-to-nucleus communication pathway, conserved from yeast to humans, by which dysfunctional mitochondria relay signals that lead to cell stress adaptation in physiopathological conditions via changes in nuclear gene expression. The most comprehensive picture of components and regulation of retrograde signaling has been obtained in Saccharomyces cerevisiae, where retrograde-target gene expression is regulated by RTG genes. In this chapter, we describe methods to measure mitochondrial retrograde pathway activation at the level of mRNA and protein products in yeast model systems, including cell suspensions and microcolonies. In particular, we will focus on three major procedures: mRNA levels of RTG-target genes, such as those encoding for peroxisomal citrate synthase (CIT2), aconitase, and NAD+-specific isocitrate dehydrogenase subunit 1 by real-time PCR; expression analysis of CIT2-gene protein product (Cit2p-GFP) by Western blot and fluorescence microscopy; the phosphorylation status of transcriptional factor Rtg1/3p which controls RTG-target gene transcription. Key words Mitochondrial retrograde pathway, Yeast, RTG genes, CIT2, ACO1, IDH1

1

Introduction Cell homeostasis can be threatened by environmental stress and nutrient availability. The type and level of the insult are strong determinants of cell stress response, but the adaptive capacity of a cell will ultimately determine its fate. Cells can respond to stress either activating death pathways or using different pro-survival strategies to prevent inappropriate or premature regulated cell death (RCD) [1]. Mitochondria are at the crossroad of the complex regulatory network integrating pro-life and pro-death signals, but while their role in cell death processes is well established [2], how they are implicated in cell stress response and adaptation is only now becoming clear [3]. The best-characterized mechanism of cell response to

Volkmar Weissig and Marvin Edeas (eds.), Mitochondrial Medicine: Volume 2: Assessing Mitochondria, Methods in Molecular Biology, vol. 2276, https://doi.org/10.1007/978-1-0716-1266-8_6, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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mitochondrial dysfunction is the RTG pathway in yeast Saccharomyces cerevisiae. RTG pathway activation leads to a reconfiguration in the expression of a subset of nuclear genes enabling accommodation to changes in the mitochondrial state, such as mitochondrial DNA depletion. The molecular details of regulation of RTG-target gene expression have been elucidated [4]. Mitochondrial dysfunction can also alter cytosolic proteostasis. Mitochondrial precursor protein overaccumulation stress (mPOS), typically induced by protein misfolding in the mitochondrial inner membrane, can ultimately cause cell death [4, 5]. Specific retrograde transcriptional changes are activated to mitigate mPOS stress and suppress mPOSinduced cell death ([6] and ref. therein, [7]). The prototypical retrograde-target gene is CIT2, which encodes the peroxisomal isoform of citrate synthase active in the glyoxylate cycle. CIT2 expression is largely increased in cells with compromised mitochondrial functions, including those lacking mitochondrial DNA (ρ0) [8]. Both basal and upregulated expression of CIT2 is mainly dependent on RTG genes, encoding regulatory proteins central to yeast retrograde signaling (Fig. 1) (for refs. see [9]). Rtg1p and Rtg3p are basic helix-loop-helix/leucine zipper (bHLH/Zip) transcription factors that interact as a heterodimer to bind to target sites called R-boxes located in the promoter region of RTG-target genes [10]. Rtg3p is a phosphoprotein, localized with Rtg1p to the cytoplasm and phosphorylated on multiple sites when the RTG pathway is off. Activation of the pathway correlates with Rtg1/3p partial dephosphorylation and translocation to the nucleus. The most proximal sensor to mitochondrial dysfunction is the positive regulator Rtg2p, a cytoplasmic protein with an N-terminal ATP binding domain belonging to the actin/Hsp70/sugar kinase superfamily [11, 12]. Rtg2p regulates Rtg1/3p localization through dynamic interaction with Mks1p, a negative regulator of the RTG pathway. When bound to the functionally redundant 14-3-3 proteins Bmh1p and Bmh2p, Mks1p promotes the phosphorylation of Rtg3p, thus inhibiting the nuclear translocation of Rtg1/3p [13]. A second group of RTG-target genes (including ATO1 and ATO2) is activated in differentiated yeast colonies in a cell subpopulation, characterized by decreased mitochondrial respiration. This subpopulation differs from others, in which the CIT2 gene is activated, suggesting the presence of additional co-regulators that determine the targetspecific function of RTG regulators in colonies [14]. Expression of a third group of RTG-target genes is not under stringent regulation by RTG genes. This group includes genes encoding the first three enzymes of the TCA cycle, namely, mitochondrial citrate synthase (CIT1), aconitase (ACO1), and NAD+dependent isocitrate dehydrogenase (IDH1/2) which are regulated by Hap2/3/4/5 transcriptional complex in cells with robust

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Rtg2p

+ Mks1p Bmh1/2p

P

Mitochondrial dysfunction

P P

Rtg2p Mks1p

+

P

Bmh1/2p

P P Rtg3p P

Rtg3p P

Rtg1p

Rtg1p

Rtg3p P

Rtg1p Nucleus

Tumorigenesis

R box

CIT2

PCD resistance

Life span extension

Fig. 1 Regulation of RTG-dependent gene expression in response to mitochondrial dysfunction. The critical regulatory step of the RTG pathway is the dynamic interaction between Rtg2p and Mks1p. When the RTG pathway is inactive, Mks1p is found in its hyperphosphorylated form and interacts with Bmh1/2p to inhibit the nuclear translocation of Rtg1/3p, and hence the expression of RTG-target genes (such as CIT2). When the RTG pathway is activated, Mks1p becomes partially dephosphorylated and binds to Rtg2p, which causes Mks1p inactivation, releasing the inhibition from Rtg1/3p nuclear translocation and inducing the expression of RTG-target genes. RTG signaling activation has been implicated in life span extension, PCD resistance, and tumorigenesis (see text for details)

respiratory activity but come increasingly under the control of the RTG pathway in cells with compromised mitochondrial respiratory function [9]. The mitochondrial retrograde pathway is evolutionary conserved from yeast to mammals. Yet there are cell-specific differences in factors involved in the propagation of retrograde signaling in mammalian cells of various origins (for refs. see [15]). Although several potential target genes of the mammalian mitochondrial stress pathway have been reported in different cells, the complete genetic footprint of mitochondrial retrograde stress response remains unknown [16]. The retrograde response in yeast and related pathways in higher organisms share the common adaptive function of supporting cell survival. Indeed, activation of mitochondrial retrograde signaling

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has been shown to extend life span (for ref. see [17]) and to trigger cell resistance to proapoptotic stimuli both in yeast [18] and mammals ([16] and refs. therein). In addition, mitochondria have been suggested to have a tumor suppressor function since mitochondrial dysfunction provides a survival advantage to cancer cells [19, 20]. In this respect, mitochondrial retrograde signaling has also been associated with changes favoring cellular reprogramming towards tumorigenesis (for refs. see [16]). Hence, characterization of the genes regulated by the retrograde pathway is central to understanding the role of mitochondrial stress in ageing, cellular resistance to RCD and cancer progression. The existence of conserved RCD pathways in yeast sharing several biochemical and morphological features with mammalian apoptosis has been established [21]. This, together with the possibility of heterologous expression of human disease genes in yeast [22, 23], makes this organism a suitable experimental platform for unveiling both the mechanisms of mitochondrial retrograde response and their role in physiopathology [17, 24–26]. Detection of RTG signaling activation in yeast has mainly relied on Northern blotting analysis of readouts of certain RTG-target genes such as CIT2 and D-lactate dehydrogenase (DLD3) [27, 28]. Alternatively, β-galactosidase activity assay may be performed in yeast cells harboring an episomal CIT2 promoter sequence fused to the lacZ gene of E. coli [13, 29]. In addition to microarray technology, which needs dedicated laboratory facilities [30], real-time polymerase chain reaction (PCR) is a quantitative, accurate, and fast technique which allows for the analysis of large panels of selected gene transcripts [18, 31]. Recently, the level of CIT2-gene protein product (Cit2p) expression has also been used to measure activation of the RTG pathway in yeast cells either through immunoblot analysis or fluorescence microscopy analysis of yeast cells expressing Cit2p fused to green fluorescent protein (GFP) [14]. In this chapter, we will describe how to measure mitochondrial RTG-dependent retrograde signaling at the level of mRNA and protein products in yeast cell suspensions and microcolonies under different experimental settings. In the first experimental setting, shift to extracellular pH 3.00 is used to cause a transient RTG signaling activation in yeast cells in the presence of coupled mitochondria [18]. This causes upregulation of CIT2 mRNA while IDH1 and ACO1 mRNAs, whose transcription mainly depends on Hap2/3/4/5 complex (see above), remain unchanged (see Fig. 2b). The method used consists of measuring both the expression of RTG-target genes by real timePCR and the phosphorylation state of Rtg3p by immunoblotting analysis [32]. This procedure may be easily applied to detect RTG pathway activation in different steady-state and time-dependent conditions. In the second detection system, Cit2p-GFP levels are measured by Western blot and fluorescence microscopy in yeast microcolonies from wild-type and retrograde mutant cells.

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30,00 y = -3,2033CtCIT2 + 19,247

25,00

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R = 0,9902

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B 12

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Fig. 2 Expression analysis of RTG-target genes. (a) Standard curve of Ct values as a function of a log10 of CIT2 and ACT1 mRNA Varbitrary, determined by linear regression analysis. (b) mRNA levels of CIT2, IDH1, and ACO1 were measured by real-time PCR in cells grown in neutral and pH 3.00 YPR medium (see text for details). CIT2 mRNA levels, normalized with that of ACT1 mRNA, were reported in arbitrary units (a.u.)

2

Materials

2.1 Cells and Growth Media

1. Saccharomyces cerevisiae strains: W303-1B [Matα leu2 trp1 ura3 ade2 his3] (WT), W303-1B rtg2::LEU2 cells (Δrtg2) and W303-1B rtg3::LEU2 (Δrtg3) [18]. BY-Cit2p-GFP [MATα, his3Δ1, leu2Δ0, lys2Δ0, ura3Δ0, CIT2-yEGFPkanMX]; BY-rtg1-Cit2p-GFP [MATα, his3Δ1, leu2Δ0, lys2Δ0, ura3Δ0, rtg1::nat, CIT2-yEGFP-kanMX]; BY-rtg2Cit2p-GFP [MATα, his3Δ1, leu2Δ0, lys2Δ0, ura3Δ0, rtg2:: nat, CIT2-yEGFP-kanMX]; BY-rtg3-Cit2p-GFP [MATα, his3Δ1, leu2Δ0, lys2Δ0, ura3Δ0, rtg3::nat, CIT2-yEGFPkanMX], BY-mks1-Cit2p-GFP [MATα, his3Δ1, leu2Δ0, lys2Δ0, ura3Δ0, mks1::nat, CIT2-yEGFP-kanMX] [14].

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2. YPR medium: 1% Yeast extract (DIFCO), 2% Bacto Peptone (DIFCO), 2% raffinose. Solid YPD medium: 1% Yeast extract (DIFCO), 2% Bacto Peptone (DIFCO), 2% glucose, 2% Bacto Agar (DIFCO). 3. Acid YPR medium: 1% Yeast extract (DIFCO), 2% Bacto Peptone (DIFCO), 2% raffinose, set to pH 3.00 with HCl. 4. GMA agar (1% yeast extract, 3% glycerol, 1% ethanol, 2% agar). All media components were mixed in ultrapure water (prepared by purifying deionized water to attain a sensitivity of 18 MΩ cm at 25
C). Media were sterilized by autoclaving for 20 min at 121
C. 2.2 Buffers, Reagents, and Labware 2.2.1 Real-Time PCR

1. Presto mini RNA Yeast Kit (Geneaid) was used for RNA isolation providing all the buffers required (sorbitol buffer for cell wall digestion with zymolyase, RB buffer for cell lysis, W1 buffer for RNA binding, wash buffer for RNA washing steps, and RNAse-free water for RNA elution). 2. Sterile tips and Eppendorf tubes (0.2 ml; 1.5 and 2.0 ml) only for RNA use. 3. Zymolyase 20 T (from Arthrobacter luteus, Seikagaku Biobusiness), store at 4
C. 4. β-mercaptoethanol, store at 4
C. 5. 70% ethanol solution. 6. QuantiTect Reverse Transcription Kit (Qiagen) was used for cDNA synthesis providing all the buffers and reagents required (gDNA wipeout buffer for genomic DNA digestion, RNAsefree water, Quantiscript Reverse Transcriptase Buffer 5, Quantiscript Reverse Transcriptase and RT Primer mix for cDNA production). 7. QuantiTect SYBR Green PCR Kit (Qiagen) was used for absolute quantification of cDNA targets (i.e., CIT2) providing all the buffers and reagents required (QuantiTect SYBR Green PCR Master Mix containing HotStarTaq DNA Polymerase, QuantiTect SYBR Green PCR Buffer, dNTP mix and the fluorescent dye SYBR Green I, RNAse-free water). 8. 96 sterile multi-well plates and films (MicroAmp Fast Optical 96-well Reaction Plate, Applied Biosystems).

2.2.2 Protein Extraction

Rtg3 Phosphorylation Detection

1. Lysis buffer: 0.225 M NaOH/1% 2-mercaptoethanol, added with protein inhibitors: 10 mM NaF, 1 mM Na3VO4, and 2 mM phenylmethylsulfonyl fluoride (PMSF) (see Note 1). 2. SDS PAGE sample buffer: 100 mM Tris–HCl (pH 6.8), 4% sodium dodecyl sulphate (SDS), 20% glycerol, 100 mM dithiothreitol (DTT), 0.002% bromophenol blue.

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Cit2p-GFP Detection

3. Lysis buffer: 10 mM MES [2-(N-morpholino)ethanesulfonic acid] buffer (pH 6), supplemented with Complete protease inhibitor mixture (Roche Applied Science) and 1 mM AEBSF [4-(2-aminoethyl)benzenesulfonyl fluoride, Sigma]; cell disruption by glass beads (acid washed 425–600 μm, Sigma G8772). 4. SDS PAGE sample buffer: 50 mM Tris–HCl (pH 6.8), 10% glycerol, 2% SDS, 0.01% bromophenol blue, 0.6% DTT. 2.2.3 SDSPolyacrylamide Gel Electrophoresis

Rtg3 Phosphorylation Detection

1. Tris/Cl SDS pH 8.45: 3 M Tris–HCl, 0.3% SDS. 2. Stock acrylamide/bisacrylamide 30/0.8: Acrylamide 30 gr, bisacrylamide 0.8 gr (for 100 ml). Filter with 0.4 μm filters and store in a dark flask at 4
C. The solution is stable for 1 year if kept at 4
C. Weigh the powder in a fume cupboard using protective gloves and turn the ventilation on only after the H2O has been added. 3. Cathode buffer (Top): Tris–Tricine–SDS Buffer, pH 8.25, diluted 1:10. 4. Anode buffer (Bottom): 1 M Tris–HCl, pH 8.9. 5. Amersham Full-Range Rainbow Molecular Weight Marker (GE Healthcare). Cit2p-GFP Detection

6. 12% SDS-polyacrylamide gel. Mix ROTIPHORESE gel 30 (37,5:1) (Carl Roth GmbH+Co KG), #3029.1:0.5 M Tris, pH 8.8, 0.4% SDS:ultrapure H2O ¼ 4:2.5:3.5 (volume). 7. Running buffer: 25 mM Tris, 192 mM glycine, and 0.1% SDS, pH 8.6. 8. Precision Plus Protein Kaleidoscope Prestained Protein Standards, BIO-RAD, #1610375. 2.2.4 Western Blotting

Rtg3 Phosphorylation Detection

1. Transfer buffer: 9.93 mM 3-(Cyclohexylamino)-1-propanesulfonic acid (CAPS), 20% methanol, pH 11. 2. Polyvinylidene fluoride (PVDF) Immobilon-P 0.4 μm).

membranes

(Millipore,

3. TBS buffer: 20 mM Tris, 150 mM NaCl, pH 7.6 (see Note 2). 4. Blocking buffer: 5% (w/v) nonfat dry milk in TBS, pH 7.6. Cit2p-GFP Detection

5. Transfer buffer: 25 mM Tris, 192 mM glycine, 15% methanol.

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6. Polyvinylidene fluoride (PVDF) Immobilon-P 0.4 μm).

membranes

(Millipore,

7. Blocking buffer: 1% casein in PBS (10 mM Na2HPO4·12 H2O, 154 mM NaCl, pH 7.4).

3

Methods

3.1 Analysis of RTG-Dependent Target Gene mRNAs 3.1.1 Cell Growth and Low pH Shift

3.1.2 RNA Isolation and Real-Time PCR

1. Preculture yeast cells in 5 ml of liquid YPR medium and incubate on a rotary shaker at 150 rpm and 26
C for about 8 h. Dilute aliquot of the culture in liquid YPR medium and grow overnight (150 rpm and 26
C) up to exponential phase (OD600 about 0.7). Determine the concentration of cell suspension using a cell-counting chamber (Neubauer Improved). Collect cells (about 20  107 for each sample for RT PCR and 5  107 for protein extraction) by centrifugation at 3000  g for 5 min. An aliquot of the culture (about 20  107 for each sample for real-time PCR and 5  107 for protein extraction) is shifted to pH 3.00 and then collected. 1. Resuspend the cells grown at neutral pH or shifted to pH 3.00 in sorbitol buffer containing zymolyase (5 mg/sample) and incubate on a rotary shaker at 150 rpm and 30
C for 30 min (see Note 3). Collect the spheroplasts by centrifugation and proceed with RNA isolation (see Note 4). First lyse the cells in 300 μl RB buffer + β-mercaptoethanol, then transfer the lysate to a 2 ml RB column to allow RNA binding, perform the washing steps and elute RNA in 50 μl RNAse-free water. 2. Quantify RNA by UV spectrophotometric assay and evaluate its purity (usually A260/A280  2.0). 3. To avoid RNA degradation, cDNA synthesis must be performed immediately. The QuantiTect Reverse Transcription Kit allows synthesis of cDNA in two steps with a 20-min procedure. Unless otherwise stated, RNA manipulation must be performed on ice. First, to effectively remove contaminating genomic DNA (gDNA), incubate isolated RNA (1 μg per sample) at 42
C for 2 min with 2 μl of gDNA wipeout buffer in a final volume of 14 μl in RNase-free water. Then place the mixture on ice and use immediately for reverse transcription reaction. Prepare the reverse transcription master mix (1 μl Quantiscript Reverse Transcriptase, 4 μl Quantiscript RT buffer 5, and 1 μl RT primer Mix) and add 14 μl template RNA. Perform cDNA synthesis in a thermal cycler (Perkin Elmer GeneAmp PCR System 2400) using the following program: 42
C for 15 min, 95
C for 3 min. 4. Store cDNA at 20
C until use.

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5. Create standard curves for each cDNA target to be analyzed (CIT2, ACO1, IDH1) and a reference gene used for normalization (ACT1). To this aim, prepare serial dilutions (1:1; 1:5; 1:25; 1:125; 1:625; 1:3125) of one of the cDNA sample prepared (see Note 5). For each RTG-target and reference gene, prepare a reaction mixture to analyze six cDNA dilutions plus one blank (no cDNA) sample in triplicates, as follows: for one sample add 0.1 μl specific primers (100 pmol/μl) (CIT2: (F) 50 -CGGTTATGGTCATGCTGTGCT-30 and (R) 50 -GGT CCATGGCAAACTTACGCT -30 ; ACO1: (F) CATTTACCC CCGATTTGGCT and (R) GGTACAAGAACCGATCAAAC CG, IDH1; (F) TCGACAATGCCTCCATGCA and (R) AAAG CAGCGCCAATGTTGC ; ACT1: (F) 50 - CTTTGGCTCC ATCTTCCATG -30 and (R) 50 - CACCAATCCAGACGGAG TACTT-30 ), 10 μl 2 QuantiTect SYBR Green PCR Master Mix and 8.8 μl RNAse-free water. Calculate the total volume of the reaction mixture multiplying each volume by three times the number of samples plus 1 (24 in this case). For each diluted cDNA, add 3 μl cDNA to 57 μl reaction mixture and load 19 μl per well in triplicate in a 96-multi-well plate. Run the following real-time PCR program by using ABI Prism 7900HT System: 15 min 95
C; 40 cycles (15 s 95
C, 30 s 59
C, 30 s 72
C); dissociation cycle. To obtain the standard curve, report the mean Ct value for each diluted sample as a function of the logarithm (log10) of the arbitrary volume (Varbitrary) values corresponding to the dilution prepared (Fig. 2a). The linear equations obtained will be used to calculate the amounts of unknown samples. 6. For quantification of each RTG target (CIT2, IDH1, ACO1) and reference gene (ACT1) set up a reaction mixture as described at point 5. Calculate the total volume of the reaction mixture multiplying the volume of each component by three times the number of samples plus one blank sample plus 1. For each sample to be analyzed, add 3 μl cDNA to 57 μl reaction mixture and load 19 μl per well in triplicate in a 96-multi-well plate. Run the real-time PCR program as previously described. 7. To determine the amount of each RTG-target gene mRNA, calculate the log10(Varbitrary) using the respective standard curve:
log 10 V arbitrary ¼ ðCtYFG  b Þ=a: where YFG is Your Favorite Gene, a is the slope and b is the intercept of the calibration curve.

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The normalized amount of an RTG-target gene is the ratio between its Varbitrary value and that of ACT1 mRNA and is expressed in the mRNA levels expressed in arbitrary units (a.u.) (Fig. 2b). 3.2 Analysis of CIT2p-GFP 3.2.1 Cell Lysis

1. Harvest cells (50–100 mg) from 3 to 4 days old microcolonies of Cit2p-GFP producing strain (with genomic CIT2 gene fused with the gene encoding GFP) on GMA. Harvested cells can be stored at 70
C. 2. Resuspend harvested cells in 10 mM MES buffer, pH 6, supplemented with Complete protease inhibitor mixture and disrupt them using glass beads in FastPrep device. 3. Remove cell debris, centrifuge lysate for 3 min at 3000  g and collect the supernatant. 4. Determine protein concentration in the supernatant using a protein detection kit (Bio-Rad Protein Assay Dye Reagent Concentrate # 5000006). Store the supernatants at 70
C.

3.2.2 Western Blot

1. After denaturation in Laemmli sample buffer, separate samples by SDS-PAGE using 12% gels. 2. After transfer to a PVDF membrane (Immobilon-P, Millipore), check the amount of loaded protein by Coomassie blue staining of each membrane. 3. Detect Cit2p-GFP by mouse monoclonal anti-GFP antibody, horseradish peroxidase (HRP) conjugate (#sc-9996 HRP, Santa Cruz) and visualize peroxidase signal with SuperSignal West Pico (Pierce) on Super RX medical x-ray film (Fuji) (Fig. 3).

3.2.3 Fluorescence Microscopy

1. Grow cells expressing genomic CIT2-GFP (e.g., BY-Cit2pGFP and BY-mks1-Cit2p-GFP) under conditions in which RTG pathway is activated (e.g., three-day-old microcolonies on GMA) (see Note 6). 2. Harvest cells and assay Cit2p-GFP fluorescence in individual cells by fluorescence microscopy (e.g., Leica DMR) using GFP filter. In parallel, visualize all cells by differential interference contrast (DIC) or bright-field microscopy (Fig. 4).

3.3 Analysis of Rtg3p Phosphorylation 3.3.1 Total Yeast Protein Extraction

1. Harvest 5 ml of cells grown at neutral pH or shifted to pH 3.00 by centrifugation for 5 min at 3000  g (see Note 7). 2. Resuspend the pellet in 150 μl of freshly prepared lysis buffer. 3. Incubate on ice for 10 min. 4. Add with the equal volume of trichloroacetic acid (TCA), to a final concentration of 6.1%.

A

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BY-rtg3-Cit2p-GFP

BY-rtg2-Cit2p-GFP

BY-rtg1-Cit2p-GFP

BY-Cit2p-GFP

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Cit2p-GFP

B

Fig. 3 RTG pathway activity in three-day-old microcolonies on GMA detected by monitoring of Cit2p-GFP level. (a) Cit2p-GFP level in WT, rtg1, rtg2, rtg3, and mks1 strains (Western blot). (b) Protein loading controls (PVDF membrane stained by Coomassie blue)

5. Incubate on ice for 10 min. 6. Centrifuge for 10 min at 10,000  g and 4
C. 7. Remove supernatant completely and resuspend in 150 μl of SDS-PAGE sample buffer (see Note 8). 8. Heat for 10 min at 65
C. These samples can be stored at 20
C. 3.3.2 Western Blotting

1. Load equivalent amounts of total cellular protein extracts on 7.5% SDS-PAGE gels (Amersham Biosciences, Mighty Small II mini vertical electrophoresis unit). 2. Activate PVDF membrane by soaking in methanol for 5 min, rinse with distilled water, and equilibrate in transfer buffer at least for 5 min. Cut away the stacking gel and equilibrate the gel in transfer buffer; prepare the transfer stack in the following order (bottom-up): four Whatman paper sheets saturated in

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BY-mks1-Cit2p-GFP

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Cit2p-GFP

DIC

Fig. 4 RTG pathway activity detected at single-cell level by microscopy. Microcolonies of BY-Cit2p-GFP and BY-mks1-Cit2p-GFP strains were grown 3 days on GMA. DIC differential interference contrast

transfer buffer, the gel, activated PVDF membrane, four Whatman paper sheets saturated in transfer buffer; place the stack onto semidry transfer units TE 70 (Amersham Biosciences) and transfer proteins at 50 mA for 75 min (see Note 9). 3. Probe the membranes with polyclonal anti-Rtg3p antibody, diluted in blocking buffer at 1:1000 (v/v) and monoclonal anti-phosphoglycerate kinase (anti-Pgk1p) antibody, diluted 1:6000 (v/v) (Molecular Probes) (see Note 10). 4. Perform immunodetection with horseradish peroxidaseconjugated anti-rabbit (for Rtg3p) or anti-mouse (for Pgk1p) antibodies using chemiluminescence Western blotting reagents (Amersham ECL Western Blotting Detection Reagent, GE Healthcare Life Sciences). Immunofluorescent bands are visualized with high-performance Amersham Hyperfilm™ ECL (GE Healthcare) (Fig. 5). RTG signaling is inactive in Δrtg2 cells and the Rtg3p hyper-phosphorylated state is shown by the slower mobility of the immunoreactive band which is smeared likely due to multiple phosphorylations. The faster mobility of Rtg3p-immunoreactive band in WT cells shifted to pH 3.00 indicates RTG pathway activation [8].

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.00 3 H g3 T p rtg2 T t r W ∆ ∆ W

Rtg3p Pgk1p Fig. 5 Rtg3p phosphorylation state in WT and Δrtg2 cells in raffinose. Cell protein extracts were prepared from WT and Δrtg2 cells grown at neutral pH and from WT cells shifted to pH 3.00 and analyzed by immunoblot with anti-Rtg3p and anti-Pgk1p antibodies. Anti-Pgk1p antibody was used as cytosolic marker protein to normalize the quantity of proteins loaded. Cell extracts from Δrtg3 cells have been analyzed as a negative control

4

Notes 1. Since anti-Rtg3p antibody is not an anti-phosphoprotein antibody, it is highly recommended that set of specific protein degradation inhibitors be added to the cell lysis buffer. In this case, NaF, an inhibitor of serine/threonine and acidic phosphatases, Na3VO4, an inhibitor of tyrosine and alkaline phosphatases, and PMSF, an inhibitor of serine proteases, were added. 2. It is critical to use TBS buffer without any detergent, otherwise, you will have a very high background. 3. For cell wall digestion of 20  107 cells, 500 μl of sorbitol buffer + zymolyase were used. 4. For RNA isolation, centrifugation temperature must be between 20
C and 25
C. 5. Accurate pipetting is required when diluting template cDNA to create the standard curve. 6. Strains with genomic CIT2-GFP have to be used for RTG pathway detection via Cit2p-GFP. 7. To analyze several samples in different conditions, the amount of proteins to be loaded onto the gel must be determined. This can be done by measuring the OD600 before processing each sample and calculating the volume of each cell culture corresponding to the initial OD600 value. Equal loading of protein samples can also be confirmed by Ponceau staining of membranes prior to incubation with antibody.

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8. If the solution turns yellow after resuspension in SDS-PAGE buffer, add 5 μl Tris 1 M solution (untitrated) until the solution becomes blue. 9. Proteins bind to the membrane as soon as contact occurs, so it is important to place the gel correctly on the first try. 10. Primary antibody dilutions in blocking buffer can be stored at 20
C and used up to three times.

Acknowledgments The authors thank Derek Wilkinson for proofreading of the manuscript. Rtg3p antibody was kindly provided by Dr. Z. Liu, University of New Orleans, New Orleans (USA). This work was supported by the Ministry of Science of Montenegro, Project “New methods for risk stratification for the progression of cancer and Alzheimer‘s disease in patients in Montenegro—DEMONSTRATE” to SG and by Czech Science Foundation 19-09381S and by LQ1604 NPU II (MEYS) to ZP; ZP research was performed in BIOCEV supported by CZ.1.05/1.1.00/02.0109 provided by ERDF and MEYS. References 1. Portt L, Norman G, Clapp C, Greenwood M, Greenwood MT (2011) Anti-apoptosis and cell survival: a review. Biochim Biophys Acta 1813(1):238–259 2. Wang C, Youle RJ (2009) The role of mitochondria in apoptosis. Annu Rev Genet 43:95–118 3. Quiros PM, Mottis A, Auwerx J (2016) Mitonuclear communication in homeostasis and stress. Nat Rev Mol Cell Biol 17(4):213–226. https://doi.org/10.1038/nrm.2016.23 4. Coyne LP, Chen XJ (2018) mPOS is a novel mitochondrial trigger of cell death - implications for neurodegeneration. FEBS Lett 592 (5):759–775. https://doi.org/10.1002/ 1873-3468.12894 5. Wang X, Chen XJ (2015) A cytosolic network suppressing mitochondria-mediated proteostatic stress and cell death. Nature 524 (7566):481–484. https://doi.org/10.1038/ nature14859 6. Guaragnella N, Coyne LP, Chen XJ, Giannattasio S (2018) Mitochondria-cytosol-nucleus crosstalk: learning from Saccharomyces cerevisiae. FEMS Yeast Res 18(8):foy088. https:// doi.org/10.1093/femsyr/foy088 7. Boos F, Kramer L, Groh C, Jung F, Haberkant P, Stein F, Wollweber F, Gackstatter A, Zoller E, van der Laan M,

Savitski MM, Benes V, Herrmann JM (2019) Mitochondrial protein-induced stress triggers a global adaptive transcriptional programme. Nat Cell Biol 21(4):442–451. https://doi. org/10.1038/s41556-019-0294-5 8. Liao XS, Small WC, Srere PA, Butow RA (1991) Intramitochondrial functions regulate nonmitochondrial citrate synthase (CIT2) expression in Saccharomyces cerevisiae. Mol Cell Biol 11(1):38–46 9. Liu Z, Butow RA (2006) Mitochondrial retrograde signaling. Annu Rev Genet 40:159–185. https://doi.org/10.1146/annurev.genet.40. 110405.090613 10. Jia Y, Rothermel B, Thornton J, Butow RA (1997) A basic helix-loop-helix-leucine zipper transcription complex in yeast functions in a signaling pathway from mitochondria to the nucleus. Mol Cell Biol 17(3):1110–1117 11. Bork P, Sander C, Valencia A (1992) An ATPase domain common to prokaryotic cell cycle proteins, sugar kinases, actin, and hsp70 heat shock proteins. Proc Natl Acad Sci U S A 89(16):7290–7294 12. Koonin EV (1994) Yeast protein controlling inter-organelle communication is related to bacterial phosphatases containing the Hsp 70-type ATP-binding domain. Trends Biochem Sci 19(4):156–157

Mitochondrial RTG Pathway Detection in Yeast 13. Liu Z, Sekito T, Spirek M, Thornton J, Butow RA (2003) Retrograde signaling is regulated by the dynamic interaction between Rtg2p and Mks1p. Mol Cell 12(2):401–411 14. Podholova K, Plocek V, Resetarova S, Kucerova H, Hlavacek O, Vachova L, Palkova Z (2016) Divergent branches of mitochondrial signaling regulate specific genes and the viability of specialized cell types of differentiated yeast colonies. Oncotarget 7 (13):15299–15314. https://doi.org/10. 18632/oncotarget.8084 15. Butow RA, Avadhani NG (2004) Mitochondrial signaling: the retrograde response. Mol Cell 14(1):1–15 16. Guha M, Avadhani NG (2013) Mitochondrial retrograde signaling at the crossroads of tumor bioenergetics, genetics and epigenetics. Mitochondrion 13(6):577–591. https://doi.org/ 10.1016/j.mito.2013.08.007 17. Jazwinski SM, Kriete A (2012) The yeast retrograde response as a model of intracellular signaling of mitochondrial dysfunction. Front Physiol 3:139 18. Guaragnella N, Zdralevic M, Lattanzio P, Marzulli D, Pracheil T, Liu Z, Passarella S, Marra E, Giannattasio S (2013) Yeast growth in raffinose results in resistance to acetic-acid induced programmed cell death mostly due to the activation of the mitochondrial retrograde pathway. Biochim Biophys Acta 1833 (12):2765–2774. https://doi.org/10.1016/j. bbamcr.2013.07.017 19. Cuezva JM, Ortega AD, Willers I, SanchezCenizo L, Aldea M, Sanchez-Arago M (2009) The tumor suppressor function of mitochondria: translation into the clinics. Biochim Biophys Acta 1792(12):1145–1158. https://doi. org/10.1016/j.bbadis.2009.01.006 20. Compton S, Kim C, Griner NB, Potluri P, Scheffler IE, Sen S, Jerry DJ, Schneider S, Yadava N (2011) Mitochondrial dysfunction impairs tumor suppressor p53 expression/ function. J Biol Chem 286 (23):20297–20312. https://doi.org/10. 1074/jbc.M110.163063 21. Carmona-Gutierrez D, Bauer MA, Zimmermann A, Aguilera A, Austriaco N, Ayscough K, Balzan R, Bar-Nun S, Barrientos A, Belenky P, Blondel M, Braun RJ, Breitenbach M, Burhans WC, Buttner S, Cavalieri D, Chang M, Cooper KF, CorteReal M, Costa V, Cullin C, Dawes I, Dengjel J, Dickman MB, Eisenberg T, Fahrenkrog B, Fasel N, Frohlich KU, Gargouri A, Giannattasio S, Goffrini P, Gourlay CW, Grant CM, Greenwood MT,

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Guaragnella N, Heger T, Heinisch J, Herker E, Herrmann JM, Hofer S, JimenezRuiz A, Jungwirth H, Kainz K, Kontoyiannis DP, Ludovico P, Manon S, Martegani E, Mazzoni C, Megeney LA, Meisinger C, Nielsen J, Nystrom T, Osiewacz HD, Outeiro TF, Park HO, Pendl T, Petranovic D, Picot S, Polcic P, Powers T, Ramsdale M, Rinnerthaler M, Rockenfeller P, Ruckenstuhl C, Schaffrath R, Segovia M, Severin FF, Sharon A, Sigrist SJ, SommerRuck C, Sousa MJ, Thevelein JM, Thevissen K, Titorenko V, Toledano MB, Tuite M, Vogtle FN, Westermann B, Winderickx J, Wissing S, Wolfl S, Zhang ZJ, Zhao RY, Zhou B, Galluzzi L, Kroemer G, Madeo F (2018) Guidelines and recommendations on yeast cell death nomenclature. Microb Cell 5(1):4–31. https://doi.org/10.15698/ mic2018.01.607 22. Mager WH, Winderickx J (2005) Yeast as a model for medical and medicinal research. Trends Pharmacol Sci 26(5):265–273. https://doi.org/10.1016/j.tips.2005.03.004 23. Greenwood MT, Ludovico P (2009) Expressing and functional analysis of mammalian apoptotic regulators in yeast. Cell Death Differ 17 (5):737–745 24. Giannattasio S, Guaragnella N, Arbini AA, Moro L (2013) Stress-related mitochondrial components and mitochondrial genome as targets of anticancer therapy. Chem Biol Drug Des 81(1):102–112. https://doi.org/10. 1111/cbdd.12057 25. Guerra F, Arbini AA, Moro L (2017) Mitochondria and cancer chemoresistance. Biochim Biophys Acta 1858(8):686–699. https://doi. org/10.1016/j.bbabio.2017.01.012 26. Guaragnella N, Palermo V, Galli A, Moro L, Mazzoni C, Giannattasio S (2014) The expanding role of yeast in cancer research and diagnosis: insights into the function of the oncosuppressors p53 and BRCA1/2. FEMS Yeast Res 14(1):2–16. https://doi.org/10. 1111/1567-1364.12094 27. Dilova I, Powers T (2006) Accounting for strain-specific differences during RTG target gene regulation in Saccharomyces cerevisiae. FEMS Yeast Res 6(1):112–119. https://doi. org/10.1111/j.1567-1364.2005.00008.x 28. Giannattasio S, Liu Z, Thornton J, Butow RA (2005) Retrograde response to mitochondrial dysfunction is separable from TOR1/2 regulation of retrograde gene expression. J Biol Chem 280(52):42528–42535. https://doi. org/10.1074/jbc.M509187200

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29. Liao X, Butow RA (1993) RTG1 and RTG2: two yeast genes required for a novel path of communication from mitochondria to the nucleus. Cell 72(1):61–71 30. Epstein CB, Waddle JA, Hale W, Dave V, Thornton J, Macatee TL, Garner HR, Butow RA (2001) Genome-wide responses to mitochondrial dysfunction. Mol Biol Cell 12 (2):297–308

31. Miceli MV, Jazwinski SM (2005) Common and cell type-specific responses of human cells to mitochondrial dysfunction. Exp Cell Res 302(2):270–280. https://doi.org/10.1016/j. yexcr.2004.09.006 32. Sekito T, Thornton J, Butow RA (2000) Mitochondria-to-nuclear signaling is regulated by the subcellular localization of the transcription factors Rtg1p and Rtg3p. Mol Biol Cell 11 (6):2103–2115

Chapter 7 Native Gel Electrophoresis and Immunoblotting to Analyze Electron Transport Chain Complexes Gisela Beutner and George A. Porter Jr. Abstract Native electrophoresis is a powerful tool to analyze the mitochondrial electron transport chain complexes (Cx) I–V and their assembly into supercomplexes. Valuable information regarding the composition and bioenergetic regulation in physiological and pathological conditions can be obtained. This chapter compares different types of native electrophoresis to analyze mitochondrial supercomplexes. Key words Native electrophoresis (blue native, colorless native, clear native, hybrid), Mitochondrial supercomplexes

1

Introduction The mitochondrial electron transport chain (ETC) transduces the energy derived from the breakdown of various fuels into the bioenergetic currency of the cell, ATP. The ETC is composed of five massive protein complexes, which also assemble into supercomplexes called respirasomes (C-I, C-III, and C-IV) and synthasomes (C-V) that increase the efficiency of electron transport and ATP production. Various methods have been used for over 50 years to measure ETC function, but these protocols provide only limited information on the assembly of individual complexes and supercomplexes. Native electrophoresis is the tool of choice to identify and characterize mitochondrial membrane-bound supercomplexes. Several types of native electrophoresis are currently used, and the main difference between them is the use of the anionic dye Coomassie G250 and detergent during sample preparation or the electrophoresis itself. Most commonly used are blue native (BN) electrophoresis [1] and high-resolution clear native (hrCN) electrophoresis [2]. Colorless native (CLN; [3]) omits dye and

Volkmar Weissig and Marvin Edeas (eds.), Mitochondrial Medicine: Volume 2: Assessing Mitochondria, Methods in Molecular Biology, vol. 2276, https://doi.org/10.1007/978-1-0716-1266-8_7, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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detergent during the electrophoresis and provides only a limited resolution of protein complexes. However, a combination of BN and CLN, called hybrid electrophoresis [4, 5], is able to overcome this limitation. All mentioned protocols of native electrophoresis allow the separation of physiologically functional protein complexes by their molecular weight, by their netcharge, or by a combination thereof. In BN and hybrid electrophoresis, Coomassie 250G binds to the solubilized protein complexes and facilitates their migration toward the anode. This allows relatively high resolution of the bands of Coomassie-stained proteins that are visible as they migrate through the gel. However, Coomassie 250G may interfere with analytical methods following the native electrophoresis [2, 6, 7]. CLN electrophoresis is a variation of BN electrophoresis that avoids adding Coomassie G250 to the cathode buffer and the sample, while using the same technical conditions as for BN electrophoresis [8]. Separation of protein complexes depends primarily on the intrinsic charge and only secondary on the size of the protein complexes. Consequently, this technique is limited to the separation of acidic proteins. However, adding mild neutral and anionic detergents to the cathode buffer overcomes this limitation and results in a high resolution of the separated protein complexes (hrCN electrophoresis; [2]). The hybrid method combines the advantages of the charge given by Coomassie Blue G250 in BN electrophoresis with those of the CLN electrophoresis: after all proteins have entered the gradient gel, the blue cathode buffer is exchanged for a colorless buffer. A mild charge shift due to the Coomassie Blue G250 binding to the protein complexes is maintained and therefore this protocol allows all proteins to migrate through the gel. After completion of native electrophoresis, a number of options allow further analysis of the separated protein complexes. The proteins in clear or colorless native gels may be transferred to membranes for immunoblotting to visualize all proteins of interest independent of their intrinsic enzymatic activity. In contrast, in-gel assays (IGA; [7]) use the enzymatic activity of the ETC complex within the gel to visualize the active protein complexes. Entire lanes, parts of a lane, or single bands of a native gels can be used for denaturing 2D electrophoresis and subsequent immunoblotting. Single bands of a BN or hybrid PAGE may be further analyzed by electroelution [6] or mass spectrometry for in-depth analysis of a protein complex. This chapter outlines the protocols of different types of native electrophoresis and the transfer of these gels to perform immunoblotting. In-gel assays are described elsewhere in this book. The reader is advised to consider the strengths and weaknesses of the different techniques when designing experiments to test their particularly hypotheses.

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Materials

2.1 Preparation for Native Electrophoresis (See Note 1)

1. Anode buffer for BN/hrCN/hybrid electrophoresis: Dissolve 25 mM imidazole in H2O; pH 7.0 (7.0–7.5 for hybrid) at 4  C, store at 4  C. 2. Cathode buffer for hrCN: Dissolve 7.5 mM imidazole and 50 mM tricine in H2O; pH to 7.0 at 4  C; add 0.5 g sodium deoxycholate and 0.2 g dodecyl-maltoside per liter of buffer; store at 4  C. 3. Cathode buffer for BN (see Note 2): A: Deep blue cathode buffer: Dissolve 7.5 mM imidazole and 50 mM tricine in H2O; pH to 7.0 at 4  C; add 0.02 (w/v) Coomassie G-250; B: Light blue cathode buffer: Dissolve 7.5 mM imidazole and 50 mM tricine in H2O; pH to 7.0 at 4  C, add 0.002% Coomassie G250; Store buffers at 4  C. 4. Cathode buffer for hybrid (see Note 3): Buffer A: Dissolve 7.5 mM imidazole and 50 mM tricine in H2O; pH to 7.0–7.5 at 4  C; add 0.02% Coomassie G250. Buffer B: Same as Buffer A, but without Coomassie G250. 5. Acrylamide/bisacrylamide (AAB) (see Note 4): To 48 g acrylamide and 1.5 g bisacrylamide, add H2O to a total of 100 mL or alternatively use a premade acrylamide/bisacrylamide solution. 6. Gel buffer for BN/hrCN/hybrid: Dissolve 75 mM imidazole and 1.5 M aminocaproic acid in H2O; pH 7.0 as 4  C (pH 7.5 for hybrid). 7. Extraction buffer A: Dissolve 50 mM NaCl, 50 mM imidazole, 2 mM aminocaproic acid, 1 mM EDTA in H2O; pH 7.0 at 4  C. 8. Extraction buffer B (see Note 5): Dissolve 150 mM sodium acetate, 30 mM HEPES, 1 mM EDTA, 12% glycerol (w/v) in H2O; pH 7.5; store at 4  C. 9. Loading buffer for hrCN: Dissolve 0.1% Ponceau S in 50% glycerol. 10. Loading buffer for BN/hybrid: Add 5% Coomassie G250 (w/v) to 500 mM aminocaproic acid pH 7.0–7.5. Aliquot and store at 20  C. 11. Detergents: Dissolve 1% and 10% dodecyl-maltoside or digitonin (w/v) in H2O. Make aliquots of 200 μL and store frozen. 12. Molecular weight marker (see Note 6): Prepare according to the instructions of the supplier.

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2.2 Preparation for Western Blotting

1. Ponceau stain (500 mL): Prepare by adding 25 mL acetic acid and 0.5 g Ponceau S to 475 mL H2O; store at room temperature, can be reused multiple times. 2. Tris-buffered saline (TBS): Prepare by dissolving 200 mM NaCl, 25 mM Tris-Base, 2.7 mM KCl; pH to 7.5 and store at room temperature. 3. TBS-Tween (TBST): Prepare by adding 0.5 mL/L Tween 20 to TBS; store at room temperature. 4. Milk solids/TBS: Prepare by dissolving 5 g milk solids in 100 mL TBS; store at 4  C and use within three days. 5. 3% BSA/TBS: Prepare by dissolving 3 g bovine serum albumin (BSA, fraction V) in 100 mL TBS; store at 4  C and use within three days or store in aliquots at 20  C.

3

Methods

3.1 Protocol Native Electrophoresis

1. Prepare a 3–8% or 4–10% acrylamide/bisacrylamide (AAB) gradients for hrCN, BN, and hybrid gels, respectively. Table 1 summarizes the quantities of buffer, AAB, H2O, glycerol, ammonium persulfate (APS), and tetramethylethylenediamine (TEMED) used for a mini-gel (size of the gel: 85 mm wide  73 mm high  1.5 mm thick) or maxi-gel (size of the gel: 160 mm wide  200 mm high  1.5 mm thick) without a stacking gel. Assemblies of glass plates with native gels can be stored refrigerated in a plastic bag with a few mL of 1 gel buffer. In a moist environment, the gels are stable for use for up to a week.

Table 1 Quantities of ingredients needed to pour 1 mini or maxi PAGE. The volumes used in this table are calculated for 1 mini-gel or 1 maxi-gel, 1.5 mm thick. The volume of AAB is based on a 40% stock solution (37.5:1; 2.7% crosslinker). APS and TEMED are added after each column of the gradient mixer is filled with the first 3 or 4 ingredients of the respective gel 3–8% (mini)

4–10% (maxi)

3% (light)

8% (heavy)

4% (light)

10% (heavy)

AAB (mL)

0.4

1.3

2.5

7.7

CN/BN buffer (mL)

1.6

1.6

8.5

8.5

H2O (mL)

2.7

1.4

14

6.3

Glycerol (g)

0.4

2.5

Volume (mL)

4.7

4.7

25

25

APS (μL)

30

30

65

65

TEMED (μL)

5

5

10

10

Native Electrophoresis

107

2. To pour the native gel, place the gradient mixer on an elevated stirring plate to ensure that the gel-forming solutions will flow by gravity into the prepared gel chamber. Fill the outflow chamber of the gradient mixer with 4.7 mL/25 mL (mini/ maxi) of the heavy solution (see Note 7), and the other chamber of the gradient mixer with 4.7 mL/25 mL (mini/maxi) of the light solution. 3. Place a stir bar into the outflow chamber with the heavy solution and begin stirring using a stir bar speed that mixes quickly but does not cause bubbling. 4. Quickly add APS and TEMED to each chamber to initiate polymerization. 5. Open the stopcock between the two chambers of the gradient mixer and allow mixing for a few seconds before opening the outflow stopcock to pour the gel. Gravity will drain both chambers equally, and mixing of the light AAB solution into the heavy AAB solution will slowly decrease the acrylamide density from the bottom to the top of the gel. Use the entire content that is in the gradient mixer to pour the gel (see Note 8). When the gel has been poured, carefully mount the well comb into the gel to avoid bubbles and mixing of the layers. 6. Wash the gradient mixer immediately with ethanol to rinse out any gel, rinse with water and pour the second gel, if needed. Let the gels polymerize—usually less than 20 min is needed for mini-gels. 7. To run the gels, mount them into the electrode assembly clamp and fill the center/upper chamber with cathode buffer (Table 1) appropriate for the desired form of native electrophoresis. After checking this chamber for leaks, pour the anode buffer into the anode chamber below the gels and remove bubbles under the gels. 8. Gently pull out well combs and wash wells with the cathode buffer using a syringe or pipette before loading the gel with the samples. 9. Run gels in the cold room (4  C) or completely packed in ice: For CN mini PAGE, use 100 V for the first hour and 200 V until finished, usually an additional 1–1.5 h. Alternatively, run the mini-CN PAGE at 30–40 V overnight (see Notes 9 and 10). For BN maxi PAGE, use 100 V and run gels overnight (about 18 h) (see Note 10). 10. For hybrid gels, change the cathode buffer to the dye-free cathode buffer (Table 1) as soon as all proteins have entered the separation gel. 11. For BN PAGE, change the deep blue cathode buffer after about 1–2 h to the light blue cathode buffer.

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3.2 Sample Preparation

Membrane-bound mitochondrial supercomplexes must be extracted from the inner mitochondrial membrane (see Note 11). To preserve the integrity of mitochondrial supercomplexes, use either freshly isolated mitochondria or samples, which have been frozen and thawed for only one time as repeated freeze/thaw cycles can disassemble protein complexes. Calculations/volumes below are given for mini-gels (the well of a 10-well comb, 1.5 mm thick gel holds up to 35–40 μL) and maxi-gels (the well of a 15-well comb holds up to 200 μL). 1. Place desired amount (we use 10–50 μg protein for mini-gels and 50–200 μg for maxi-gels) of isolated mitochondria or cell/ tissue homogenate in microtubes and centrifuge at 17,000  g for 10–15 min at 4  C. This step removes some of the soluble mitochondrial matrix and/or cytosolic proteins. 2. Aspirate and discard the supernatant and add extraction buffer (Table 1) to amount desired to load onto the gel. Based on our equipment, we use 30 μL for a mini-gel and 100 μL for a maxigel, limiting the ratio protein/buffer to not more than 2 μg protein/μL buffer. Resuspend the sediment gently on ice. If desired, a general protease inhibitor mix might be added at this point. 3. Add detergent. We use 2–4 μg lauryl maltoside/μg protein and 4–6 μg digitonin/μg protein to solubilize isolated mitochondria. More detergent is needed if a cell or tissue homogenate is used (see Note 12). 4. Incubate on ice for 10–30 min and gently mix at beginning and occasionally during incubation by trituration and/or agitation of tube. 5. Centrifuge at 17,000  g for 10 min at 4  C to remove any membrane and tissue fragments. 6. Transfer supernatant to a new tube. For hrCN samples, add 1 μL hrCN loading buffer for every 10 μL sample volume. The total volume of the sample should be approximately 40 μL for a mini-gel well (130 μL for a maxi-gel). For BN and hybrid samples, add Coomassie G250 to the samples so that the ratio of dye:detergent is 1:4 (w/w) (see Note 13). 7. Load 30 and 120 μL of the samples into the wells of the minior maxi-gel, respectively. The remaining 10 μL from each sample is for a denaturing SDS gel to detect VDAC by immunoblotting as a loading control (see Note 14). 8. Load a suitable molecular weight marker into a designated well of the gel. 9. Run gels as outlined and transfer proteins onto membranes. Wet- and semidry transfer conditions are possible. The transfer conditions and timing depend on the available equipment (see Note 15).

Native Electrophoresis

3.3

Immunoblotting

109

1. When the transfer is finished, place the membrane into Ponceau S solution to visualize all transferred proteins. After 5–10 min, wash the excess Ponceau S off by rinsing the membrane 3–4 times with deionized H2O. Label the position of the marker proteins on the membrane with pencil and document Ponceau S stained membrane (photograph or scan). 2. Wash membrane three times for 10 min with TBS with gentle agitation to destain the transferred proteins. 3. Block membrane with milk solids/TBS for 1–2 h at room temperature or overnight in a cold room with gentle agitation. 4. Wash membrane for three times 10 min with TBST with gentle agitation. 5. Incubate with primary antibody overnight in the cold room with gentle agitation (see Note 16). 6. Remove antibody and wash membrane for three times 10 min with TBST with gentle agitation. 7. Incubate membrane with secondary antibody for 1–2 h at room temperature with gentle agitation (see Note 17). 8. Wash membrane three times for 10 min at room temperature with TBST with gentle agitation. 9. Proceed to detection of signal (see Note 18).

4

Notes 1. Important: All equipment used for native PAGES must be clean of detergent. To ensure this, wash all equipment with 0.1 M hydrochloric acid, followed by extensive rinsing with deionized H2O. 2. Coomassie G250 may interfere with the transfer of proteins as it binds tightly to nitrocellulose membranes. Coomassie 250G may also interfere with the ability of antibodies to detect the target proteins [2, 6, 7]. 3. The pH of protocols published for a hybrid of blue and clear/ colorless native electrophoresis varies from 7.0 to 7.5 [4, 5]. However, a pH of 7.0 at 4  C is used in many protocols, as it will facilitate the migration of negatively charged proteins. 4. Acrylamide/bisacrylamide: Acrylamide and bisacrylamide are both carcinogens and neurotoxins. In its liquid forms, acrylamide has a high potential of absorption through the skin and as a powder acrylamide and bisacrylamide are easily inhaled. Several suppliers now offer native gradient gels, which are commonly 1.0–1.5 mm thick and offered as mini-gel or analytical gel. However, hand-casting a gradient gel has the advantage to

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optimize the gel for the experimental needs. A disadvantage of hand-casting a gel is the toxicity of AAB. Assemblies of glass plates with CN or BN gels can be stored refrigerated wrapped in plastic with a few mL of 1 gel buffer to maintain moisture. The gels are stable for use for up to a week. 5. Using extraction buffer B results in better separated supercomplexes and more defined bands of mitochondrial supercomplexes ( [4] and unpublished data). In this extraction buffer, glycerol increases the stability of the solubilized protein complexes and allows the storage of aliquots of solubilized mitochondrial membrane protein complexes at 80  C [4]. 6. Native molecular weight marker range in size up to 1200 kD, which is still below the size of observed supercomplexes. An approximate estimation of the molecular weight of mitochondrial supercomplexes is possible using the considerations outlined in [9]. 7. To prevent trapping bubbles in the connecting tube between the two chambers of the gradient maker, add the heavy solution into the outflow chamber, open the stopcock connection between the heavy and light chamber gently and allow a drop of solution to go through to the other side. This pushes air bubbles from the connecting tube and stopcock. This cannot be done if both sides have already been filled because the equal pressure will prevent the bubble from moving through. 8. The entire content of the gradient mixer must be used for the specified gradient. If necessary, quantities may be adjusted to the available equipment. 9. The current during the run will be very low (95% viability. 4. Centrifuge the cells in a 50 mL Falcon tube at 340 rcf for 5 min to obtain a pellet of 3  106 cells (see Note 4). 5. Aspirate the supernatant and resuspend the cells in 3 mL of BIOLOG MAS (1) to reach a final concentration of 1  106 cells/mL to reach 30,000 cells/well. 6. To remove clumps, filter the cell suspension through a 70-micron nylon filter or slowly pipette up and down while avoiding bubbles.

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3.4 Step-by-Step Instructions

1. Pipet 30 μL of the assay mix per well into all wells using a multichannel pipettor and incubate at 37  C and 5% CO2 for 1 h to allow substrates to fully dissolve (Fig. 3a). 2. During this time, detach the cells and resuspend them in 1 BIOLOG MAS to reach a final concentration of 1  106 cells/ mL (Fig. 3b). 3. In all wells, add 30 μL of the cell suspension (3  104 cells) per well using a multichannel pipettor (see Note 5). 4. Load the MitoPlate™ S-1 into a microplate reader with automated temperature-controlled incubation (37  C) to perform a kinetic reading of the rate of purple color formation at a wavelength of 590 nm (Fig. 3c).

a)

Assay mix: BIOLOG MAS Redox Dye MC Saponin

30 μL / well

1 hr of incubation at 37°C to allow substrates to dissolve 1st sample 2nd sample 3rd sample

b) Harvest cells and resupend in BIOLOG MAS (3 × 106 cells/mL)

c)

30 μL / well

Kinetic analysis at 37°C on a microplate reader using OD590 nm

Fig. 3 MitoPlate™ S-1 assay steps. (a) STEP 1: Prepare an assay mix by combining 2 mL of 2 BIOLOG MAS, 1.33 mL of 6 Redox Dye MC, 20 μL of a 20 mg/mL saponin stock solution (see Note 4) and 650 μL of sterile water to reach a total volume of 4 mL. Pipet 30 μL per well of the assay mix using a multichannel pipettor into all wells and incubate at 37  C for 1 h to allow substrates to fully dissolve. (b) STEP 2: Detach the cells and resuspend them in 1 BIOLOG MAS to reach a final concentration of 1  106 cells/mL. In all wells, add 30 μL of the cell suspension (3  104 cells/well) using a multichannel pipettor. (c) STEP 3: Load the MitoPlate™ S-1 into a microplate reader, which provides automated temperature-controlled incubation, to perform kinetic reading of the rate of color formation using OD590 nm

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3.5 Analysis of the Results

The kinetic reading is conducted for 4–6 h maximum; then, the data can be collected when the purple color formation reached a plateau (Fig. 4a). The initial slope between 30 min and 2 h of MitoPlate™ S-1 incubation is analyzed to measure the electron flow rate into the ETC for each metabolic substrate (Fig. 4b). First, the absorbance from the “No substrate” control is subtracted from that of the other 31 substrates to normalize against the background signal. In addition, the well that is coated with 100 μM L-malate is used to normalize wells G2-H4 (G6-G8 and G10-H12) containing specific mitochondrial substrates requiring L-malate to be transported and metabolized by the cells. Then, the initial rate is calculated as the slope derived from a linear regression fitted to the linear portion of kinetic curves. Finally, the mean and the standard error of the mean (SEM) of the initial rates are calculated per substrate and per condition. Interesting substrates are defined as outliers of the linear regression model by calculating Cook’s distance. A substrate having a Cook’s distance higher than 4/n, where n is the number of observations (substrates), is considered an “interesting” substrate. In addition, the regression line equation is derived from fitting a linear regression to the substrates without interesting ones. The whole analysis can be performed using our in-house R script written with R 3.6.0 [28] and RStudio [29]. This script as well as the raw data set used for the present example with neuroblastoma cell lines is available as a Mendeley repository at the following doi: https://doi.org/10.17632/ b9mprfdvmv.1

3.6 Interpretation of the Results

The scatterplot of the obtained average slopes in BE-M17 and SH-SY5Y cells confirmed that SH-SY5Y cells present an increase in mitochondrial respiration when using succinate, isocitrate, fumarate, and malate as substrates compared to BE-M17 cells (Fig. 5a). Overall, BE-M17 cells have a 33% decrease in its mitochondrial activity compared to SH-SY5Y cells. The scatterplot of the mean initial rate of SK-N-AS cells versus BE-M17 cells shows an increase in electron flux when SK-N-AS cells use fumarate, succinate, isocitrate, and cis-aconitate as substrates compared to BE-M17 cells (Fig. 5b). Overall, BE-M17 cells have a 46% decrease in its mitochondrial activity compared to SK-N-AS cells. The scatterplot of the mean initial rate of SH-SY5Y versus SK-N-AS cells shows an increase in electron flux when SK-N-AS cells use succinate, malate, and cis-aconitate as substrates as compared to SH-SY5Y cells (Fig. 5c). Overall, SY-SY5Y cells have a 32% decrease in its mitochondrial activity compared to SK-N-AS cells. Such an investigation could hint at possible mutations or differential gene expression levels that alter the mitochondrial function in neuroblastoma. Our results are in line with other studies, which detected a succinate dehydrogenase (SDH) mutation in neuroblastoma tumors [30], leading to an accumulation of the oncometabolite succinate

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a SH-SY5Y

SK-N-AS

BE-M17

SK-N-AS

SH-SY5Y 1

2

3

4

5

6

7

BE-M17 8

9

10

11

12

A B C D E F G H

b

Fig. 4 Example of data processing for MitoPlate™ S-1 assay. (a) left panel: Profile of an 18 h kinetic analysis of MitoPlate™ S-1 with three different neuroblastoma cell lines. (a) right panel: The slope between 30 min and 2 h of MitoPlate™ S-1 incubation was analyzed to measure the electron flow rate into the ETC for each metabolic substrate. Kinetic graphs of color versus time for all wells were generated by SoftMax Pro 7.1 software. (b) The kinetics of the different substrates were normalized to their respective controls and are shown for three different neuroblastoma cell lines. One representative analysis of three independent experiments is shown

Quantification of Cellular Energy Metabolism

a)

Outliers_SHvsBE

0.005 y = 5.5 10

−6

a

No

a

Yes

0.005 0.67 x

0.004

0.004

0.003

0.003 BE-M17 cell line

BE-M17 cell line

b)

Change in electron flux between BE-M17 and SH-SY5Y cells

Succinic Acid

0.002

139

Change in electron flux between BE-M17 and SK-N-AS cells Outliers_SKvsBE

a

No

a

Yes

y = 1.7 10−5 0.54 x

Succinic Acid

0.002

L-Malic Acid

Fumaric Acid Fumaric Acid

0.001

0.001

D,L-Isocitric Acid D,L-Isocitric Acid

0.000

c)

0.001

0.002 SH-SY5Y cell line

0.003

0.004

0.005

0.000

0.001

0.002 SK-N-AS cell line

0.003

0.004

0.005

Change in electron flux between SH-SY5Y and SK-N-AS cells Outliers_SHvsSK

0.005

cis-Aconitic Acid

0.000

0.000

a

No

a

Yes

y = 3.5 10− 5 0.68 x

0.004

SH-SY5Y cell line

0.003

Succinic Acid

0.002 L-Malic Acid

0.001

cis-Aconitic Acid

0.000

0.000

0.001

0.002 SK-N-AS cell line

0.003

0.004

0.005

Fig. 5 Example of data determined from MitoPlate™ S-1 analysis. (a) The scatterplot of the initial mean rate of SH-SY5Y cells versus BE-M17 cells shows an increase in electron flux in SY-SY5Y cells when using isocitrate, succinate, fumarate, and malate as substrates compared to BE-M17 cells. The brown dashed line represents a line with a slope of 1, while the grey dashed line represents the linear regression model and the 95% confidence interval. Data points represent the mean of three independent biological replicates  SEM. (b) The scatterplot of the initial rate mean of SK-N-AS cells versus BE-M17 cells shows an increase in electron flux in SK-N-AS cells when using fumarate, succinate, isocitrate, and cis-aconitate as substrates compared to BE-M17 cells. The brown dashed line represents a line with a slope one of 1, while the grey dashed line represents the linear regression model and the 95% confidence interval. Data points represent the mean of three independent biological replicates  SEM. (c) The scatterplot of the initial rate mean of SK-N-AS cells versus SH-SY5Y cells shows an increase in electron flux in SK-N-AS cells when using cis-aconitate, succinate, and malate as substrates compared to SH-SY5Y cells. The brown dashed line represents a line with a slope one of 1, while the grey dashed line represents the linear regression model and the 95% confidence interval. Data points represent the mean of three independent biological replicates  SEM

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known to promote tumor progression [31]. Moreover, the high impact of SK-N-AS cells in mitochondrial activity respect to other neuroblastoma cell lines could be linked to the presence of more mitochondria [13].

4

Notes 1. BIOLOG suggests saponin from Sigma (SAE0073) presenting a high sapogenin content (20–35%). Other permeabilizing agents may be substituted for saponin, such as digitonin or cholesterol-sequestering toxins, but these must be validated before use. 2. Tissue analysis requires purified mitochondria; therefore, we omitted saponin from the assay mix. 3. If using a multichannel pipettor and a reagent reservoir, 4 mL of the mix are required per plate to fill tips accurately. 4. BIOLOG MAS is 2; thus, it should be diluted in distilled sterile water to produce a 1 stock solution before it is added to cells. 5. If using a multichannel pipettor and a reagent reservoir, at least 2 mL of cells are required per 1 sample plate to fill tips accurately.

Acknowledgments The authors thank M Scheckenburger and S Chateauvieux for helpful discussions, comments, and editions. FR thanks Te´le´vie Luxembourg. DG thanks the “Recherche Cancer et Sang” foundation. This work was supported by the “Recherche Cancer et Sang” Foundation, “Recherches Scientifiques Luxembourg,” “Een Haerz fir kriibskrank Kanner” Association, and Te´le´vie; MD received support from the Research Institute of Pharmaceutical Sciences, College of Pharmacy, Seoul National University; NRF grants 019R1A2C1009231 and 2011-0030001 (Tumor Microenvironment Global Core Research Center, GCRC); Brain Korea (BK21) PLUS and the Creative-Pioneering Researchers Program at SNU [Funding number: 370C-20160062]. References 1. Corbet C, Feron O (2017) Cancer cell metabolism and mitochondria: nutrient plasticity for TCA cycle fueling. Biochim Biophys Acta Rev Cancer 1868:7–15 2. Akram M (2014) Citric acid cycle and role of its intermediates in metabolism. Cell Biochem Biophys 68:475–478

3. Speijer D (2011) Oxygen radicals shaping evolution: why fatty acid catabolism leads to peroxisomes while neurons do without it: FADH (2)/NADH flux ratios determining mitochondrial radical formation were crucial for the eukaryotic invention of peroxisomes and

Quantification of Cellular Energy Metabolism catabolic tissue differentiation. BioEssays 33:88–94 4. Stanley IA, Ribeiro SM, Gimenez-Cassina A et al (2014) Changing appetites: the adaptive advantages of fuel choice. Trends Cell Biol 24:118–127 5. Sharma R, Ramanathan A (2020) The aging metabolome- biomarkers to hub metabolites. Proteomics 20(5-6):e1800407 6. Acin-Perez R, Carrascoso I, Baixauli F et al (2014) ROS-triggered phosphorylation of complex II by Fgr kinase regulates cellular adaptation to fuel use. Cell Metab 19:1020–1033 7. Murphy MP (2009) How mitochondria produce reactive oxygen species. Biochem J 417:1–13 8. Stefanatos R, Sanz A (2018) The role of mitochondrial ROS in the aging brain. FEBS Lett 592:743–758 9. van Opbergen CJM, den Braven L, Delmar M et al (2019) Mitochondrial dysfunction as substrate for arrhythmogenic cardiomyopathy: a search for new disease mechanisms. Front Physiol 10:1496 10. Masschelin PM, Cox AR, Chernis N et al (2019) The impact of oxidative stress on adipose tissue energy balance. Front Physiol 10:1638 11. Rangaraju V, Lewis TL Jr, Hirabayashi Y et al (2019) Pleiotropic mitochondria: the influence of mitochondria on neuronal development and disease. J Neurosci 39:8200–8208 12. Perillo B, Di Donato M, Pezone A et al (2020) ROS in cancer therapy: the bright side of the moon. Exp Mol Med 52(2):192–203 13. Radogna F, Cerella C, Gaigneaux A et al (2016) Cell type-dependent ROS and mitophagy response leads to apoptosis or necroptosis in neuroblastoma. Oncogene 35:3839–3853 14. Anderson NM, Mucka P, Kern JG et al (2018) The emerging role and targetability of the TCA cycle in cancer metabolism. Protein Cell 9:216–237 15. Cerella C, Radogna F, Dicato M et al (2013) Natural compounds as regulators of the cancer cell metabolism. Int J Cell Biol 2013:639401 16. Schnekenburger M, Florean C, Dicato M et al (2016) Epigenetic alterations as a universal feature of cancer hallmarks and a promising target for personalized treatments. Curr Top Med Chem 16:745–776

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17. Hanahan D, Weinberg RA (2011) Hallmarks of cancer: the next generation. Cell 144:646–674 18. Gonfloni S, Iannizzotto V, Maiani E et al (2014) P53 and Sirt1: routes of metabolism and genome stability. Biochem Pharmacol 92:149–156 19. Aminzadeh S, Vidali S, Sperl W et al (2015) Energy metabolism in neuroblastoma and Wilms tumor. Transl Pediatr 4:20–32 20. Xiao D, Ren P, Su H et al (2015) Myc promotes glutaminolysis in human neuroblastoma through direct activation of glutaminase 2. Oncotarget 6:40655–40666 21. Adeva-Andany MM, Carneiro-Freire N, SecoFilgueira M et al (2019) Mitochondrial betaoxidation of saturated fatty acids in humans. Mitochondrion 46:73–90 22. Cerella C, Gaigneaux A, Dicato M et al (2015) Antagonistic role of natural compounds in mTOR-mediated metabolic reprogramming. Cancer Lett 356:251–262 23. Cerella C, Dicato M, Diederich M (2014) Modulatory roles of glycolytic enzymes in cell death. Biochem Pharmacol 92:22–30 24. Parey K, Wirth C, Vonck J et al (2020) Respiratory complex I - structure, mechanism and evolution. Curr Opin Struct Biol 63:1–9 25. Lapuente-Brun E, Moreno-Loshuertos R, Acin-Perez R et al (2013) Supercomplex assembly determines electron flux in the mitochondrial electron transport chain. Science 340:1567–1570 26. He S, Liu Z, Oh DY et al (2013) MYCN and the epigenome. Front Oncol 3:1 27. Harenza JL, Diamond MA, Adams RN et al (2017) Transcriptomic profiling of 39 commonly-used neuroblastoma cell lines. Sci Data 4:170033 28. R Development Core Team (2010) R: a language and environment for statistical computing 29. RStudio Team (2015) RStudio: integrated development for R 30. Rapizzi E, Ercolino T, Fucci R et al (2014) Succinate dehydrogenase subunit B mutations modify human neuroblastoma cell metabolism and proliferation. Horm Cancer 5:174–184 31. Selak MA, Armour SM, MacKenzie ED et al (2005) Succinate links TCA cycle dysfunction to oncogenesis by inhibiting HIF-alpha prolyl hydroxylase. Cancer Cell 7:77–85

Chapter 10 Whole-Cell and Mitochondrial dNTP Pool Quantification from Cells and Tissues Juan C. Landoni, Liya Wang, and Anu Suomalainen Abstract Deoxynucleoside 50 -triphosphates (dNTPs) are the molecular building blocks for DNA synthesis, and their balanced concentration in the cell is fundamental for health. dNTP imbalance can lead to genomic instability and other metabolic disturbances, resulting in devastating mitochondrial diseases. The accurate and efficient measurement of dNTPs from different biological samples and cellular compartments is vital to understand the mechanisms behind these diseases and develop and scrutinize their possible treatments. This chapter describes an update on the most recent development of the traditional radiolabeled polymerase extension method and its adaptation for the measurement of whole-cell and mitochondrial dNTP pools from cultured cells and tissue samples. The solid-phase reaction setting enables an increase in efficiency, accuracy, and measurement scale. Key words dNTP, Nucleotide pools, mtDNA, Mitochondrial DNA depletion syndrome, Solid-phase detection

1

Introduction Deoxynucleoside 50 -triphosphates (dNTPs) are the metabolites that serve as building blocks for the synthesis of DNA in all living cells. In eukaryotes, dNTP metabolism is a highly regulated network of intermingled pathways, composed of the mostly cytosolic de novo biosynthesis pathway, dominating in proliferating cells, and the parallel cytosolic and mitochondrial salvage pathways, typical for postmitotic cells [1]. The concentration and balance of the four canonical dNTPs are crucial for healthy cellular metabolism and genetic stability. dNTP imbalance is known to alter DNA replication fidelity and repair, cell cycle progression, oncogenesis, apoptosis, and other key cellular processes [2]. Even though every DNA-containing cell in the body requires dNTPs for DNA replication and maintenance, genetic defects in the dNTP biosynthetic enzymes cause severe human diseases with

Volkmar Weissig and Marvin Edeas (eds.), Mitochondrial Medicine: Volume 2: Assessing Mitochondria, Methods in Molecular Biology, vol. 2276, https://doi.org/10.1007/978-1-0716-1266-8_10, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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remarkable and unexplained tissue specificity and manifestation diversity (reviewed by [3–6]). These multisystemic human disorders, known as mitochondrial DNA depletion syndromes, are characterized by the quantitative reduction of mitochondrial DNA copy number in affected organs, and the molecular mechanisms behind their pathogenesis remain poorly understood. The important interplay between dNTP metabolism and mitochondrial homeostasis is further underscored by genetic defects affecting mitochondrial DNA maintenance, which can secondarily affect dNTP pool balance [7, 8] and even consequently disturb nuclear DNA stability [9]. Recent breakthroughs in the treatment of mitochondrial DNA depletion syndrome have been reported. Several nucleotide-modulation possibilities exist for thymidine phosphorylase deficiency (reviewed by [10]), and more recently significant improvements have been reported in fatal thymidine kinase 2 deficiency by deoxynucleoside supplementation [11–13]. Measurement of dNTPs is crucial for the follow-up and mechanistic characterization of these therapeutic interventions. We present an updated state-of-the-art method for dNTP concentration measurement. The method takes advantage of the naturally evolved dNTP specificity of DNA polymerase enzymes, which proportionally incorporates the measured dNTPs together with radioactively labeled nucleotides onto designed oligonucleotides, from which radioactivity can be measured and the dNTP concentrations quantified. The method is based on the previously published radioactive polymerase assay [14], which is further developed and improved [15], and on ribonucleotide discrimination [16] and allows for mitochondrial dNTP pool measurement [17]. This chapter is an expansion on the most recent update of the method [18], which adapted the measurement to a solid-phase setting (Fig. 1), allowing for automation, improving efficiency, and circumventing laborious and hazardous steps.

2

Materials

2.1 General Equipment

1. Speed vacuum concentrator preferably with cooling trap. 2. Automated cell counter. 3. Centrifuge. 4. Scintillation vials and beta counter (MicroBeta2 from PerkinElmer). 5. Microplate washer.

2.2 Whole-Cell dNTP Isolation from Cells

1. 60% methanol in water at 20  C. 2. 1 Trypsin-EDTA. 3. Phosphate-buffered saline (PBS).

Whole-Cell and Mitochondrial dNTP Pool Quantification

145

Fig. 1 Graphic depiction of measurement reaction, using sample dCTP measurement as an example. S ¼ streptavidin; B ¼ biotin, dATP*/A* ¼ tritium-labeled adenosine; NNNNNN ¼ primer binding sequence. (I) Affinity capture of dCTP-oligo onto streptavidin-coated plate. (II) Polymerization reaction: primer binding, followed by the proportional incorporation of C bases from the sample and radiolabeled A bases from the excess 3H-dATP*. (III) Alkaline denaturation of DNA strand by sodium hydroxide and release of the newly synthesized radiolabeled strand for scintillation counting 2.3 Whole-Cell dNTP Isolation from Tissues

1. 100% methanol at 20  C. 2. Tissue homogenization buffer: 0.2 mM EGTA, 10 mM Tris– HCl pH 7.5, 0.5% bovine serum albumin (see Note 1). 3. Polytron tissue homogenizer or other suitable tissue homogenizer.

2.4 Mitochondrial dNTP Isolation

1. 60% methanol in water at 20  C. 2. Teflon-glass homogenizer. 3. Mitochondrial isolation buffer: 2 mM EGTA, 5 mM Tris–HCl pH 7.4, 320 mM sucrose) (see Note 1).

2.5 Binding, Polymerization, and Detection

1. HPLC-purified biotinylated [B] oligonucleotides (50 -30 ): dATP-oligo: [B] AAATAAATAAATAAATAAATGGACAGAG TATGTGTCTGTG. dTTP-oligo: [B] TTATTATTATTATTATTAGGACAGAG TATGTGTCTGTG. dCTP-oligo: [B] TTTGTTTGTTTGTTTGTTTGGGACA GAGTATGTGTCTGTG. dGTP-oligo: [B] TTTCTTTCTTTCTTTCTTTCGGACA GAGTATGTGTCTGTG (see Note 2). 2. Streptavidin-coated 96-well plate (BioBind Streptavidin Strip Assembled Solid by Thermo Scientific). 3. Binding solution: 0.1% TWEEN® 20 (Amresco) in PBS. 4. Universal primer (50 -30 ): CCTGTCTCATACACAGACAC (see Note 2).

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5. 50 mM NaOH solution (see Note 3). 6. Thermostable DNA polymerase and 10 optimized buffer (see Note 4). 7. 0.5 M dithiothreitol (DTT) (see Note 5). 8. dNTP mix stock, 40 mM dNTPs (10 mM each) (see Note 6). 9. [8-3H(N)]- Deoxyadenosine 50 -triphosphate Tetrasodium Salt in 1:1 ethanol:water mixture (PerkinElmer). 10. [Methyl-3H]- Deoxythymidine 50 -Triphosphate Tetrasodium Salt in 1:1 ethanol:water mixture (PerkinElmer). 11. TENT solution: 40 mM Tris–HCl, 1 mM EDTA, 50 mM NaCl, 0.1% TWEEN® 20, pH 8.0–8.8. 12. Ultima Gold™ liquid scintillation cocktail for aqueous and nonaqueous samples (PerkinElmer).

3

Methods

3.1 Whole-Cell dNTP Isolation from Cells

1. Culture at least 106 cells, varying the amounts according to cell size and type (see Note 7). 2. Wash cells thoroughly with PBS and detach with trypsinEDTA. 3. Count cell number (for future normalization) and then centrifuge the cells at 250  g, wash with PBS once more. Snap freeze and store the pellet at 80  C (max. 2–3 of days) or continue to step 4. 4. Add 1 ml of cold 60% methanol and mix thoroughly. 5. Incubate >1 h at 80  C or > 2 h at 20  C. 6. Centrifuge the lysate at 4 20,000  g) for 15 min.



C maximum speed (around

7. Heat the samples containing pellet and supernatant in a hot plate or boiling water for 3 min, followed by cooling down in ice water bath and repeat the centrifugation step (see Note 8). 8. Carefully transfer supernatant to a new tube avoiding debris from the pellet, and desiccate in speed vacuum until no liquid is visible (see Note 9). Store solid extract at 80  C, optimally for less than 3 days. 3.2 Whole-Cell dNTP Isolation from Tissues

1. All samples and solutions should be kept on ice. 2. Collect ~100 mg of tissue (e.g., murine gastrocnemius muscle), recording the exact weight (for normalization purposes). Snap freeze and store the tissue at 80  C overnight, or continue with fresh tissue (see Note 10).

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3. Add 1 ml of tissue homogenization buffer into the tube and homogenize using the polytron until no tissue debris is visible. Cool down the sample in an ice water bath if necessary, during homogenization. 4. Transfer homogenate into centrifuge tubes and spin at 2000  g 10 min at 4  C to remove fibrous tissue and other cell debris. 5. Split the supernatant into two separate centrifuge tubes. 6. Add cold 100% methanol to obtain a final 60% concentration, usually 400 μl of supernatant and 600 μl of methanol in each tube. 7. Continue with incubation as in Subheading 3.1, step 5. 3.3 Mitochondrial dNTP Isolation

1. For cells culture samples, collect 20–60 million cells, depending on cell size and proliferative rate (see Note 7). Wash cells thoroughly with PBS, detach with trypsin-EDTA and centrifuge the cells at 250  g, wash again with PBS and re-pellet. Continue to step 4. 2. If using tissue, collect ~150 mg of soft tissue such as liver. 3. All steps on ice onwards. 4. Resuspend/mix sample with mitochondrial isolation buffer and transfer to the Teflon-glass homogenizer. 5. Stroke 10 times and transfer homogenate into fresh centrifuge tube. 6. Pellet nuclei and other particles by 3 min 2000  g centrifugation at 4  C. Keep supernatant on ice and re-homogenize the pellet with 500 μl mitochondrial isolation buffer. 7. Repeat re-homogenization. 8. Combine supernatants and pellet mitochondria at 12,000  g for 10 min at 4  C. 9. Discard supernatant and resuspend the pellet with isolation buffer. 10. Save a small aliquot (~40 μl) for protein quantitation, and then repeat mitochondrial pelleting (12,000  g for 10 min at 4  C). 11. Snap freeze and store the pellet at 80  C overnight, or continue with dNTP extraction as described in Subheading 3.1, step 4.

3.4 Affinity Capture of Oligonucleotides (Fig. 1 I)

1. Design the location of each sample in the plate, considering four reaction wells per replicate of the sample and each reaction with duplicates. In addition, include wells for a 6-sample standard curve (24 wells).

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2. Create and distribute the master mix (0.25 μM of oligonucleotide in binding solution (0.1% TWEEN20 in PBS)). This equals 2.5 μl of 5 μM oligonucleotide and 47.5 μl binding solution per well. You will need four different mater mixes, one per measured nucleotide. 3. Incubate the plate at 37  C > 1.5 h on a shaking heater or incubator. 4. Discard the solution from the wells and wash thoroughly using an automated plate washer: 4 washes with 200 μl TENT solution. Tap plate against a drying paper to ensure the wells are dry. 3.5 Preparation of Standard Series and Sample Dilutions

1. Perform every step on ice. 2. Carefully prepare a dilution series from the commercial dNTP mixture, optimally starting from 1 μM stock obtaining the quantitative standard dilutions: 80 nM, 40 nM, 20 nM, 10 nM, 5 nM. Include also a water blank. 3. Dissolve the solid extract into 50–100 μl water, depending on the sample size and expected dNTP amount, vortex, and leave on ice for 10 min. Then quickly prepare working dilutions of each sample at different concentrations (e.g., 5 and 10), to ensure replicability and linearity of the result. Store the sample leftover back to 80  C rapidly (see Note 11). The working dilutions should be at least 50 μl in volume to suffice for the four reactions needed.

3.6 Polymerase Reaction and Detection (Fig. 1 II-III)

1. Calculate the molar concentration of the tritium-labeled dNTPs (3H-dNTP*), and desiccate the required amount to obtain a 0.75 μM concentration in a final master mix per reaction type, with reaction volume of 50 μl. 3H-dATP* is used for dTTP, dCTP, and dGTP quantitation, while 3 H-dTTP* is used for dATP. 2. To the tube containing the desiccated 3H-dNTP*, add the rest of the components in the master mix, as detailed below (Table 1). Prepare fresh before reaction and keep on ice. 3. Load the reaction mixture to each well. Ensure to match the bound oligonucleotide to the dNTP* present in the mix (3H-dTTP* to Oligo-dATP and 3H-dATP* to other oligos). 4. Incubate the plate on a flotation device in a 55  C water bath for 1 h. 5. Discard contents of the wells and perform washes as in step 3.4.4. 6. Add 60 μl of 50 mM NaOH and incubate for >3 min at room temperature to release freshly synthesized DNA (Fig. 1 III).

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Table 1 Polymerase reaction mixture composition Volume (μl)

Concentration

10 polymerase buffer

5

1

0.5 M DTT

0.5

5 mM

15 μM radiolabeled dNTP

(calculated and desiccated)

0.75 μM

5 μM primer

2.5

0.25 μM

Thermostable polymerase

(calculated from polymerase)

0.025 U/μl

Sample

12

H2O

29

Total volume

50

7. Transfer the DNA-containing NaOH solution into scintillation vials, add 3 ml of liquid scintillation cocktail, and measure radioactivity for 1 min in the beta counter. 3.7

Data Analysis

1. Export the counts per minute results, and analyze each reaction type (dATP, dTTP, dCTP, and dGTP) separately. 2. Subtract the background (the water blank count) from all raw data of each reaction. 3. Generate a standard curve by using linear regression method allowing the curve crossing the origin using data from standard samples. dNTP concentration on the x-axis and counts per minute on the y-axis (see Note 12). 4. Calculate the dNTP concentration in each sample by using the standard curve. Exclude samples outside of the linear range of the measured standards, and repeat by adapting sample dilution (see Note 11). 5. Normalize the final dNTP concentration by using dilution factors and sample volumes, and against cell number, tissue mass, or mitochondrial protein amount to obtain the final quantitative result (Eq. 1). Calculation of dNTP concentration from counts per minute

dNTP concentration ðnmol=x Þ ¼

Counts per minute Standard slope ðnM1 Þ

 Dilution coefficient  Dissolution volumeðLÞ

Normalization factor ðx ¼ cell number, mg tissue, or protein concentrationÞ

ð1Þ 6. Analyze the results from each replica and present the final result as mean  SD.

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Notes 1. The tissue homogenization buffer and mitochondrial isolation buffer can be stored in aliquots at 20  C for about a year. 2. The oligonucleotides should be HPLC-purified. When receiving stocks, they can be diluted into 5 μM concentration and stored at 20  C in small aliquots to avoid freeze–thawing. 3. 50 mM NaOH solution should be made fresh every 4–6 weeks. 4. The polymerase used in the method setup was DyNAzyme II DNA Polymerase by Thermo Fisher Scientific and its 10 commercial optimized buffer. 5. 0.5 M DTT should be stored in small aliquots at 20  C and only used once after thawing due to instability of the compound. A precipitate will be visible in the cold solution but it will dissolve when fully thawed. 6. The dNTP mix can be diluted up to 1 μM aliquots and stored at 20  C, to simplify future serial dilutions. This is easily done by a two-step 1:100 serial dilution (10 μl of dNTP mix into 990 μl of water, and 10 μl of the resulting solution into additional 990 μl of water). Avoid repeated freezing and thawing. 7. dNTP pool concentrations vary dramatically between different cell types and cell cycle stage. Furthermore, confluency and proliferative state should also be considered when comparing cell lines to one another. 8. The boiling step will denature and precipitate leftover proteins in solution. If the first pellet is too large, the supernatant can be transferred to a new tube before boiling and second centrifugation. N.B: the temperature increase might make the centrifuge tube caps pop open, which could lead to loss of sample and hazard to the researcher, ensure tube caps are held strongly and work in a fume hood. 9. The desiccation might take several hours and the samples and apparatus might warm-up. If the temperature rises significantly above room temperature, cool the samples in a freezer and continue the drying once cold. 10. Longer storage of tissue, even deep frozen, shows measurable signs of dNTP decay. If necessary, store sample as dried dNTP extract and keep the same storage conditions consistent within the experiment to avoid batch effects. 11. Due to the instability of dNTPs, the sample handling should be done on ice and as rapidly as possible, avoiding warm temperatures and freeze–thaw cycles. There is measurable decay of dNTPs even after overnight 80  C storage of dissolutions,

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so if remeasurement is necessary, repeat multiple samples and compare in a batch-specific manner. 12. The standard linear regression should have an R2 value very close to 1, commonly ~0.99. References 1. Wang L (2016) Mitochondrial purine and pyrimidine metabolism and beyond. Nucleosides Nucleotides Nucleic Acids 35:578–594 2. Mathews CK (2014) Deoxyribonucleotides as genetic and metabolic regulators. FASEB J 28:3832–3840 3. Viscomi C, Zeviani M (2017) MtDNAmaintenance defects: syndromes and genes. J Inherit Metab Dis 40:587–599 4. Gorman GS, Chinnery PF, DiMauro S et al (2016) Mitochondrial diseases. Nat Rev Dis Primers 2:16080 5. Nunnari J, Suomalainen A (2012) Mitochondria: in sickness and in health. Cell 148:1145–1159 6. Suomalainen A, Isohanni P (2010) Mitochondrial DNA depletion syndromes – many genes, common mechanisms. Neuromuscul Disord 20:429–437 7. Nikkanen J, Forsstro¨m S, Euro L et al (2016) Mitochondrial DNA replication defects disturb cellular dNTP pools and remodel one-carbon metabolism. Cell Metab 23:635–648 8. Dalla Rosa I, Ca´mara Y, Durigon R et al (2016) MPV17 loss causes deoxynucleotide insufficiency and slow DNA replication in mitochondria. PLoS Genet 12 9. H€am€al€ainen RH, Landoni JC, Ahlqvist KJ et al (2019) Defects in mtDNA replication challenge nuclear genome stability through nucleotide depletion and provide a unifying mechanism for mouse progerias. Nat Metab 1:958–965 10. Yadak R, Sillevis Smitt P, van Gisbergen MW et al (2017) Mitochondrial neurogastrointestinal encephalomyopathy caused by thymidine

phosphorylase enzyme deficiency: from pathogenesis to emerging therapeutic options. Front Cell Neurosci 11:31 11. Garone C, Garcia-Diaz B, Emmanuele V et al (2014) Deoxypyrimidine monophosphate bypass therapy for thymidine kinase 2 deficiency. EMBO Mol Med 6:1016–1027 12. Lopez-Gomez C, Levy RJ, Sanchez-Quintero MJ et al (2017) Deoxycytidine and deoxythymidine treatment for thymidine kinase 2 deficiency. Ann Neurol 81:641–652 13. Domı´nguez-Gonza´lez C, Madruga-Garrido M, Mavillard F et al (2019) Deoxynucleoside therapy for thymidine kinase 2–deficient myopathy. Ann Neurol 86:293–303 14. Solter AW, Handschumacher RE (1969) A rapid quantitative determination of deoxyribonucleoside triphosphates based on the enzymatic synthesis of DNA. Biochim Biophys Acta 174:585–590 15. Sherman PA, Fyfe JA (1989) Enzymatic assay for deoxyribonucleoside triphosphates using synthetic oligonucleotides as template primers. Anal Biochem 180:222–226 16. Ferraro P, Franzolin E, Pontarin G et al (2010) Quantitation of cellular deoxynucleoside triphosphates. Nucleic Acids Res 38 17. Martı´ R, Dorado B, Hirano M (2012) Measurement of mitochondrial dNTP pools. http://www.scopus.com/inward/record.url? eid¼2-s2.0-84856364625&partnerID¼40& md5¼f3c1af28bae6e1c780027884b84be24f 18. Landoni JC, Wang L, Suomalainen A (2018) Quantitative solid-phase assay to measure deoxynucleoside triphosphate pools. Biol Methods Protoc 3:bpy011

Chapter 11 Single-Particle Tracking Method in Fluorescence Microscopy to Monitor Bioenergetic Responses of Individual Mitochondria Camille Colin, Emmanuel Suraniti, Emma Abell, Audrey Se´mont, Neso Sojic, Philippe Diolez, and Ste´phane Arbault Abstract The spectroscopic methods commonly used to study mitochondria bioenergetics do not show the diversity of responses within a population of mitochondria (isolated or in a cell), and/or cannot measure individual dynamics. New methodological developments are necessary in order to improve quantitative and kinetic resolutions and eventually gain further insights on individual mitochondrial responses, such as studying activities of the mitochondrial permeability transition pore (mPTP). The work reported herein is devoted to study responses of single mitochondria within a large population after isolation from cardiomyocytes. Mitochondria were preloaded with a commonly used membrane potential sensitive dye (TMRM), they are then deposited on a plasma-treated glass coverslip and subsequently energized or inhibited by additions of usual bioenergetics effectors. Responses were analyzed by fluorescence microscopy over few thousands of mitochondria simultaneously with a single organelle resolution. We report an automatic method to analyze each image of time-lapse stacks based on the TrackMate-ImageJ plug-in and specially made Python scripts. Images are processed to eliminate defects of illumination inhomogeneity, improving by at least two orders of magnitude the signal/noise ratio. This method enables us to follow the track of each mitochondrion within the observed field and monitor its fluorescence changes, with a time resolution of 400 ms, uninterrupted over the course of the experiment. Such methodological improvement is a prerequisite to further study the role of mPTP in single mitochondria during calcium transient loading. Key words Mitochondria, Fluorescence microscopy, Membrane potential, Bioenergetics, Single organelle, Single particle tracking, Fiji software, TrackMate

1

Introduction The monitoring by microscopy of mitochondria, when isolated or when forming a network in cells, constitutes a major approach to resolve their organization, functioning, and activity under physiological [1] or pathological [2, 3] situations. Owing to the recent developments of microscopy techniques, these are increasingly used

Volkmar Weissig and Marvin Edeas (eds.), Mitochondrial Medicine: Volume 2: Assessing Mitochondria, Methods in Molecular Biology, vol. 2276, https://doi.org/10.1007/978-1-0716-1266-8_11, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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since they allow to follow-up responses in living cells or monitor resolved kinetics on minute sample quantities under a noninvasive manner. NADH and FAD autofluorescence can be used to monitor endogenously the mitochondrial bioenergetics when modulations of the respiratory chain are used. A large variety of fluorescent dyes can also be found to assess mitochondrial functions (membrane potential, ROS, pH. . .), their number continuously increasing in literature [4]. The most representative family is the one dedicated to monitor ΔΨ with high sensitivity and kinetic resolution, which includes dyes quoted as JC1, TMRE, or TMRM. [5–8] Microscopy approaches are used first for imaging and to a lower extent to resolve metabolic responses such as depolarization waves or transients by mitochondria under bioenergetic variations. There are now multiple reports at the level of single mitochondrion resolution from experiments in cells, notably in cardiomyocytes thanks to their organization, [9, 10] or for isolated mitochondria deposited on various supports (glass coverslip, modified or not, PDMS, etc.) [11–13]. However, only few remarkable events at single mitochondria are usually reported and shown in communications, while the response of populations, networks with an individual resolution would help in deciphering mechanisms and discriminating the existence of subpopulations (heteroplasmy, metabolic variations) [14]. To do so, automated image processing and data analysis protocols still need to be developed to promote largescale studies and statistics from individual mitochondria responses in microscopy; this is the aim of the present methodological development. We studied responses to bioenergetics effectors of mitochondria isolated from rat cardiomyocytes. After depositing on a glass coverslip, their membrane potential evolutions were monitored simultaneously from thousands of entities with a single mitochondrion resolution. This was made possible with microscopy image corrections and improvements (Fiji software functions) along with individual follow-up of objects over time and distance (TrackMate plug-in) and additional personalized scripts to generate matrices of data. All developed protocols are available free of charge from the authors upon request.

2 2.1

Materials Solutions

1. Extraction buffer: Saccharose 300 mM, Tris–HCl 10 mM, EGTA 50 mM, pH adjusted to7.2 with NaOH 0.5 M. 2. Digestion buffer: Saccharose 300 mM, Tris–HCl 10 mM, EGTA 50 mM, protease 0.1 mg.ml 1 (from Streptomyces griseus, Type XIV, ref: P5147), pH 7.2.

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3. Homogenization buffer: Saccharose 300 mM, Tris–HCl 10 mM, EGTA 50 mM, BSA 0.2% (W/v), pH adjusted to 7.2 with NaOH 0.5 M. 4. Respiration buffer: Saccharose 300 mM, KCl 100 mM, EGTA 1 mM, MgCl2 20 mM, KH2PO4 10 mM, BSA 0.2% (W/v), pH adjusted to 7.2 with NaOH 0.5 M. 5. Glutamate, malate, succinate (ref: G1626, M9138, S2378, respectively) stock solutions are prepared at 500 mM in respiration buffer. 6. ADP (Adenosine diphosphate, ref A2754) stock solution is prepared at 100 mM in respiration buffer. 7. Rotenone (ref R8875) stock solution is prepared at 1 mM in DMSO (see Note 1). 8. Oligomycin (ref 75351) stock solution is prepared at 1 mM in methanol (see Note 1). 9. C-ATR (carboxy-atractyloside potassium salt, ref C4992) stock solution is prepared at 5 mM in respiration buffer (see Note 1). 10. CCCP (Carbonyl cyanide 3-chlorophenylhydrazone, ref C2759) stock solution is prepared at 1 mM in acetone (see Note 1). 2.2 Fluorescence Imaging

1. Experiments were performed with an inverted epifluorescence microscope from Leica© (DMI 6000 B model) equipped with a 40 objective (dry; NA: 0.75; Leica HC PL APO), and a camera from Hamamatsu© (ORCA-Flash4.0). 2. Images were collected via MetaMorph (Molecular Devices©) and analyzed with Fiji and ImageJ (NIH free supply) software.

3

Methods

3.1 Rat Heart Extraction

1. Mitochondria are extracted from the heart of Wistar male rats (from Janvier Labs, France) according to the following procedure (see Note 2). 2. The rat is anesthetized by inhalation of isoflurane (4%) in an induction chamber for 2 min. 3. Once anesthesia observed, the rat is weighted and injected subcutaneously with 0.1 mL of heparin at 5000 U.mL 1. 4. The rat is placed back in the induction chamber (4% isoflurane) for further 3 min and euthanized by cervical dislocation. 5. The heart is rapidly extracted from the thorax and placed in cold extraction buffer, to stop contractions (see Note 2). 6. The heart is rinsed with extraction buffer, weighed, and unwanted tissue is removed.

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3.2 Extraction of Cardiac Mitochondria

1. Ventricular tissue is excised and thoroughly minced with sharp scissors. 2. Minced tissue is transferred to a beaker containing 30 mL of digestion buffer and placed on a magnetic stirrer for 7 min. 3. The solution is transferred to a Teflon-glass homogenizer and remaining digestion buffer is used to remove any tissue left in beaker. The partially digested tissue is homogenized for 3 min, to break up any remaining tissue. 4. The homogenate is centrifuged at 7500  g for 7 min. 5. The supernatant is discarded, and the pellet resuspended in 30 mL of homogenization buffer, homogenized for 2 min and transferred to a new centrifuge tube. 6. The solution is centrifuged at 680  g for 10 min. The supernatant is then filtered with a nylon filter and transferred into a new centrifuge tube. 7. The solution is centrifuged at 7000  g for 10 min. The supernatant is discarded, and the pellet resuspended in 40 μL homogenization buffer. 8. Mitochondrial protein quantification is performed with a classic Bradford assay, the resulting optical density is measured at 595 nm with a spectrophotometer (see Note 3).

3.3 Coverslip Preparation

1. Coverslips (12 mm diameter) are purchased from Fischer Scientific (Carolina Science & Math manufacturer; ref. NC9537307). 2. Coverslips are treated just before use with a low pressureoxygen plasma generator from Harrick Plasma© (ref. plasma cleaner) at 300 mTorr, 100% O2, for 10 min (see Note 4).

3.4 Experimental Procedure for Mitochondria Imaging

1. Before the experiment, a diluted solution of mitochondria is prepared at 0.1 mg.mL 1 in respiration buffer (see Note 5), supplemented with 10 nM of TMRM (Tetramethylrhodamine methyl ester perchlorate, purchased from Sigma, ref T5428). 2. After 10 min of incubation, 600 μL of the solution is deposited on the coverslip previously mounted on the microscope stage (see Note 6). 3. In bright field mode, the focus is on the top surface of the coverslip, and a 20-min interval is allowed for mitochondria to sediment (see Note 7).

3.5 Imaging of Mitochondria

1. The typical sequence for mitochondria imaging is the following: images are captured every 10 s for 20 min; exposure times are 40 ms to detect either TMRM fluorescence in mitochondria or for additional observations in bright field. Fluorescence images are obtained with a fibered light source (Leica, ref

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EL6000) set at its minimum power, while white light images were obtained with a fibered LED source (CoolLED, ref PE100) connected to the microscope. 2. Observations are achieved using a 40 objective (dry; N.A. 0.75), allowing large field views (332.8  322.8 μm area) and single mitochondria measurements. 3. N2.1-type filter (Leica) is used for TMRM detection (excitation: 515–560 nm, emission, long-pass >590 nm), and A-type filter (Leica) is used for endogenous NADH detection (excitation: 340–380 nm, emission: long-pass >425 nm). 4. The following sequence of solutions is used to induce the different bioenergetic stationary states in mitochondria: (1) addition of respiratory substrates; glutamate plus malate at 5 mM each, or succinate at 5 mM plus rotenone at 2 μM, or a combination of glutamate, malate, and succinate, all at 5 mM; (2) addition of ADP at 1 mM; (3) addition of oligomycin at 5 μM or C-ATR at 5 μM; and (4) addition of CCCP at 0.5 μM. 5. Ten images are taken for each step of the sequence (100 s), note that 10 images are taken before adding the first substrate. 3.6 Treatment of Images with “Fiji”

1. Before any data analysis, all images are stacked (image/stack/ images to stack) in a file (Stack 1; Fig. 1a) and duplicated (Stack 2; image/duplicate). A profile of the intensity variation versus a linear ROI (region of interest) can be drawn to check for the signal/noise ratio of the object detection (Fig. 1b). 2. On Stack 2, a Gaussian-type filter is applied with a factor of 60 to correct a shading effect (process/filters/Gaussian Blur) due to the illumination inhomogeneity of the lamp on the epifluorescence microscope. 3. The obtained Stack 2 (Fig. 1c) is subtracted from the original Stack 1 (image/process/image calculator/subtract) to generate a corrected Stack 3 (Fig. 1d). 4. A median filter with a factor of 2 is applied to Stack 3 to eliminate noise resulting from the subtraction (image/process/filters/median) and enhance the signal/noise ratio. This produces a final Stack 4 (Fig. 1e) used for further analyses. The result of the procedure on the image of a single mitochondrion is shown in Fig. 1f to compare with the original one in Fig. 1b.

3.7 Mitochondria Follow-Up with “TrackMate”

1. On Stack 4, a Fiji software plug-in called “TrackMate” [15] is applied (plug-in/Tracking/TrackMate). This plug-in enables to track the path of each individual mitochondrion over distance and time, according to two main steps. 2. The first step is to detect on each image, all possible objects that can be classified as mitochondria. To do so, the “DoG

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Fig. 1 Protocol for the treatment of microscopy images with “Fiji” software. (a) Raw image of mitochondria after 20 min. Sedimentation on a glass coverslip. Mitochondria were incubated with 10 nM TMRM membrane potential dye and energized by the addition of glutamate/malate/succinate at 5 mM. 10 images (every 10 s, 40 ms exposure time) are used to create the Stack 1. (b) Example of a fluorescence intensity profile for a single mitochondrion of the image at this stage of the treatment. (c) A Gaussian-type filter is applied (factor 60) to correct the shading effect due to the illumination inhomogeneity on the whole field, resulting images lead to Stack 2. (d) Stack 2 is subtracted from Stack 1 to generate corrected images in Stack 3. (e) Noise in the images of Stack 3 is corrected via a median filter (factor 2) and generates the final Stack 4. (f) Fluorescence intensity profile for a single mitochondrion, the same as in (b), after the full image processing

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detector” method is used with an “Estimated blob diameter” of 10 pixels, equivalent to 1.625 μm, and an intensity threshold between 1 and 5 AU. This method uses a difference of Gaussian fits to detect particles and is optimal for spots of small size (see Note 8). 3. The second step is aimed at identifying the same object over time; for this purpose, the “simple LAP Tracker” method is used (see Note 9). According to their identification, provided as a number assigned by TrackMate (see Note 10), a follow-up of the displacement of individual mitochondria is possible (Fig. 2a), though some boundaries need to be given: “Linking max distance” of 15 pixels, or 2.4375 μm; a “Gap-closing max distance” of 15 pixels, or 2.4375 μm; and a “Gap-closing max

Fig. 2 Follow-up with the TrackMate plug-in of “Fiji” software, of mitochondria mobility over time on the surface of a glass coverslip. (a) Display of all trajectories (named tracks) from individual mitochondria during a sequence of 20 images (200 s); each object is identified and shown here with a colored trajectory. (b) Shortcut of the whole image to display two mitochondria with very different behaviors along four images taken sequentially. (c) Graph of the fluorescence variations due to displacements for the two mitochondria shown in b. Data treatments were applied on the images of the sequence in Fig. 1

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frame gap” of 50 frames. Two different types of displacements of mitochondria on the surface along an experiment are compared in Fig. 2b. 4. Finally, the function “Analysis” is used to generate “Spots in track statistics” datasheets allowing further data analyses of displacements, intensity variations, etc. 3.8 Python Scripts for Quantitative Analyses

1. Specialized informatics scripts were written with “Python” 4.0, “Spyder” environment, and “Pandas, NumPy, and SciPy” libraries, to automatically process the analysis of data. These scripts are available free of charge upon request from the authors. 2. At the beginning of each script, two filters are used: (1) A filter of movement to discard mobile mitochondria (>3.25 μm displacement), which can distort the analysis and overall the statistics (example in Fig. 2c); (2) A time filter, to eliminate mitochondria that are not present enough (2 mg/ml in isolation buffer. 2. Incubate cells in growth medium or isolated mitochondria in mitochondrial storage buffer with 3.3 μM Fura-2-AM for 60 min or with 5 μM Rhod-2-AM for 30 min at room temperature in the dark (see Note 20). 3. After the incubation period, change growth medium to assay buffer or pellet the sample, wash with EGTA containing buffer (see Note 15), and let isolated mitochondria settle down onto the microscopy slides in the assay buffer for at least 20 min (see Note 19). 4. Transfer slide to the microscope and proceed with the measurement by real-time monitoring Fura-2 or Rhod-2 using an imaging system as described above with the excitation and emission filter settings displayed in (Table 2).

3.3 Transfection of Genetically Encoded Ca2+ Indicators

1. Grow adherent mammalian cells in its optimum culture medium in a humidified incubator (37  C, 5% CO2, 95% air) on perfusion chamber slides to 60–80% confluency. 2. For transient transfection of ~5  105 cells, mix 2 μg of a plasmid encoding a mitochondrial targeted GECI and an appropriate amount of transfection reagent with 1 ml of serum- and antibiotic-free transfection medium. Incubate cells in the incubator for 16–20 h and change back to complete culture medium. Experiments can be performed 24–72 h after transfection.

3.4 Real-Time Recordings of [Ca2 + ]cyto and [Ca2+]mito

Herein, we will describe the simultaneous measurement of Fura2 and mtD1GO-Cam in detail. For assessing mitochondrial Ca2+ using chemical fluorescent indicators (Fura-2, Rhod-2) or other mitochondrial-targeted genetically encoded Ca2+ indicators (mtRP, mtD3cpv, mito-GEM-GECO1), use appropriate filter settings as described in Tables 2 and 3. 1. Load mtD1GO-Cam transfected cells with Fura-2-AM in a concentration of 3.3 μM dissolved in storage buffer for at least 20 min (see Note 20). 2. Stop Fura-2-AM loading by washing the cells twice with storage buffer. 3. Keep cells in storage buffer prior to measurements (see Note 21). 4. Put a drop of immersion oil on top of the objective and place the perfusion chamber slide with the cells upside onto the droplet.

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5. Connect the chamber with the perfusion system and start the perfusion. 6. Set the cells in focus by turning the z-tuner of the microscope table or use the autofocus of the system in the white light mode. 7. Use the ocular for searching cells that have a high and good targeted expression of the mitochondrial cameleon using an excitation wavelength at ~480 nm and emission at ~510 nm (cpEGFP, see Notes 22 and 23). 8. For simultaneous illumination of Fura-2 and mtD1GO-Cam, use the time-lapse function of the imaging software in a triple wavelength mode. To gain better fluorescence sensitivity, use binning 2 or higher. Expose excitation of Fura-2 at 340 nm and 380 nm for 150 ms or 50 ms, respectively (see Note 24), and collect emitted light at 510 nm. The mitochondrial sensor gets excited for 400 ms (see Note 25) at 477 nm and emits at 510 nm (GFP, donor fluorescence) and 560 nm (FRET, acceptor fluorescence), respectively. Accordingly, the two sensors get recorded in the time-lapse mode within 600 ms or less (see Notes 24 and 25) by alternative exposes of the three excitation wavelengths without any fluorescence interference (Fig. 2). F340 F380

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Fig. 2 Simultaneous measurement of [Ca2+]cyto and [Ca2+]mito in the same individual cells. Original traces of (a) cytosolic and (b) mitochondrial Ca2+ signals and (c) their respective correlation over time upon cell stimulation with 100 μM histamine in intact mtD1GO-Cam expressing HeLa cells loaded with Fura-2. (a) Raw traces of Fura-2 signals at 340 nm (grey) and at 380 nm (blue) excitation. Inset image shows the cytosolic accumulation of Fura-2 (b) Raw traces of GFP signal (GFPraw, green) at 510 nm excitation and respective FRET signal (FRETraw, orange) at 560 nm excitation were plotted on the left y-axis. Red curve (Ratioraw) indicates the FRET ratio computed from the raw traces (FFRET/FGFP) was plotted on the right y-axis. Black curve represents photobleaching function (R0) assessed with a one phase exponential decay function. Inset image shows mitochondrial targeting of mtD1GO-Cam. (c) Fura-2 (black, left y-axis) and mtD1GO-CaM signals (red, right y-axis) were calculated from the raw traces shown in (a) and (b), respectively. Inset image is an overlay of previous insets. The scale bar is 10 μM

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9. Use an appropriate experimental design for cell stimulation via the perfusion system (e.g., 100 μM histamine in EB). 10. Analyze data of the recorded ratios from the two sensors separately to verify the spatiotemporal correlation of [Ca2+]cyto and [Ca2+]mito (see Note 26). 3.5 Mitoplast Patch-Clamping Recording

1. Mitochondria from cultured cells (e.g., HeLa) are freshly isolated by differential centrifugation steps (see Note 27) as previously described [10, 25]. 2. Mitoplast formation: Incubate isolated mitochondria kept on ice, in four volumes of hypotonic solution for 10 min. This results in mitochondria swelling and rupture of the outer membrane. Add 1 volume of hypertonic solution to equilibrate the tonicity (see Note 28). 3. For patch-clamp recordings, place 20–40 μl of mitoplast suspension to the recording chamber (depending on the size of mitochondrial pellet) and allow mitoplasts to settle down for 10 min prior to experimentation. 4. To form Gigaohm contact, position the pipette tip on the chosen mitoplast away from the “cap” region, which represents the attached remnants of the outer membrane. Press the pipette against the mitoplast and apply negative pressure to the pipette interior. When mitoplast-attached configuration is reached, single channel openings can be detected during voltage ramps. 5. Before obtaining whole-mitoplast configuration, capacitance transients are compensated and negative pressure is further applied until the patch is ruptured. 6. Alternatively, voltage steps of 300–600 mV and 10–20 ms duration may be applied. 7. Successful access to the matrix is accompanied by reappearance of capacitance transients. Mitoplast capacitance measured with Membrane Test tool of Clampex is around 1 pF. If membrane rupture is accompanied by a leak current, new mitoplast should be chosen and the procedure should be repeated again with a new pipette. 8. Following a successful membrane rupture, experiments are continued in the same way as they are done with cells. 9. For recordings of Ca2+ currents in mitoplast-attached and whole-mitoplast configuration, use respective pipette solutions described above. Signals obtained are sampled at 10 kHz and filtered at 1 kHz. 10. For recordings of Ca2+ currents in whole-mitoplast configuration, exchange Ca2+-free bath solution for Ca2+-containing bath solution by bath perfusion. We typically apply voltage

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Fig. 3 Patch-clamp recording of transmitochondrial Ca2+ flux. (a) Time course of the whole-mitoplast current development at
155 mV before and after addition of 3 mM Ca2+ followed by addition of 10 μM RuR. (b) Corresponding Ca2+ current responses to voltage ramps from
160 to 50 mV before and after addition of 10 μM RuR in the presence of 3 mM Ca2+

ramps from
160 to +60 mV to record whole-mitoplast Ca2+ currents (Fig. 3). 11. For recording whole-mitoplast monovalent cationic current carried by Na+, use 150 mM NaCl instead of Trizma and the same Cs-based pipette solution and voltage protocol. 12. Collect data using the Clampex software of pClamp (Molecular Devices, Sunnyvale, CA, USA). Signals obtained are sampled at 5 kHz and filtered at 1 kHz. 3.6 Assessing Ca2 + -Dependent Changes in Mitochondrial Metabolism

1. Harvest, resuspend, and dilute cells in standard growth medium. Typical cell seeding numbers vary from 5000 to 100,000 cells per well depending on the cell type, basal metabolic activity, proliferation rate, cell size, and the time of plating and must be determined empirically. 2. Gently seed 100 μl of cell suspension per well in XF96 Polystyrene Cell Culture Microplates (see Note 29). Wells A1, A12, H1, and H12 are to be left blank for background correction. 3. After seeding, place the microplate with the cells in an incubator at 37  C, gassed with 5% CO2 for 12 h to guarantee optimal adherence (see Note 30). 4. Fill each well of the utility plate with 200 μl of XF calibrant solution using a multichannel pipette and lower the XF96 sensor cartridge onto the plate, fully submerging the biosensors (see Note 31). 5. Seal both the cartridge and plate, covered by the lid, using parafilm in order to minimize evaporation and incubate at 37  C in a non-CO2 incubator.

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Table 4 Commonly used protocol template programmed using the Assay Wizard of the Seahorse XF96 Software Protocol start 1. Calibrate probes. 2. Equilibrate. 3. Loop 3 times. 4. Mix for 3 min 0 s. 5. Measure for 3 min 0 s. 6. Loop end. 7. Inject port A. 8. Loop 3 times. 9. Mix for 3 min 0 s. 10. Measure for 3 min 0 s. 11. Loop end. 12. Inject port B. 13. Loop 3 times. 14. Mix for 3 min 0 s. 15. Measure for 3 min 0 s. 16. Loop end. 17. Inject port C. 18. Loop 3 times. 19. Mix for 3 min 0 s. 20. Measure for 3 min 0 s. 21. Loop end. Program end

6. Switch on the instrument and open the XF software at least 12 h prior to the assay, in order to allow the system to stabilize at 37  C. Table 4 summarizes a commonly used protocol template that can be programmed and modified using the Assay Wizard of the Seahorse XF96 Software. 7. On the day of the assay, observe cells under the microscope to assure both sufficient viability and confluency (see Note 29). 8. Pre-warm non-buffered assay medium containing the desired amount of D-glucose and sodium pyruvate (typically 5.5 and 1 mM, respectively) to 37  C and adjust pH to 7.4 using NaOH.

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Fig. 4 Mitochondrial respiration assessed by the XF96 Extracellular Flux Analyzer from Seahorse Bioscience: an indirect way to determine mitochondrial Ca2+ uptake. O2 consumption rates (OCRs) of HeLa cells stably expressing control shRNA or shRNA targeting the mitochondrial Ca2+ uniporter (MCU shRNA). Cells were treated with 1 μM oligomycin, 500 nM FCCP, and 2.5 μM antimycin A to assess basal, coupled, maximal, and residual OCRs. Data represent means (n  30)

9. Carefully remove the growth medium from the microplate using a multichannel pipette, making sure that ~20 μl of media remains at the bottom of the well at all times. Wash cells two times before replenishing the well with a final volume of 150 μl of assay medium. 10. Incubate the cell plate in a non-CO2 incubator at 37  C until ready for use. 11. Prepare compound solutions for injection using assay medium and reconstituted reagents (see Notes 32 and 33). 12. Open the appropriate assay template and start the assay using the XF96 software. 13. Insert the sensor cartridge and the utility plate (without the lid) into the instrument for calibration. 14. Upon completion of the automated calibration process, replace the utility plate with the microplate containing the cells and click “continue” to start the actual measurement (Fig. 4).

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Notes 1. Add 8.2 g KCl, 0.114 g KH2PO4, 0.203 g MgCl2, 0.766 g HEPES, 1.351 g succinate, and 1.982 g glucose. Dissolve in 800 ml H2O while stirring for 5 min. Titrate KOH to adjust

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pH, then add 0.0114 g EGTA and adjust pH again. While adjusting pH, use low concentrations of acid or base at the end of titrations in order to avoid sudden drops or rises above or below the required pH. Continue stirring for 5 min and check the pH again. 2. For dissolving EGTA properly, adjust pH first to slightly basic conditions. During addition of the salt, pH will shift to lower values. After complete dissolution adjust pH again. 3. The vector contains an episomal replication site for cell lines that are latently infected with SV40 or express the SV40 large T antigen (e.g., COS-1, COS-7). 4. For transfection, use the culture medium of the cell line of choice without supplements like FCS, antibiotics, and antimycotics. 5. Transfection reagent and method depend on cell type and equipment of the lab. 6. The pcDNA3.1 (
) vector contains a neomycin resistance gene for creating stable mammalian host cell of choice. Transfect the cell line with the sensor plasmid using TransFast™ transfection reagent and transfection medium supplemented with an appropriate concentration of neomycin or G418 (Geneticin®) and feed the cells with selective medium every day. Stable cell colonies can be easily identified on a fluorescence microscope within 3–4 days after addition of G418. Pick and expand colonies in 96- or 48-well plates. 7. Storage buffer can be stored after sterile filtration in aliquots (of e.g., 30 ml) at 4  C for at least 3 months. 8. SB and EB are suitable for most non-excitable cell lines (e.g., HeLa, HUVEC, HEK293, COS), but need to be adjusted to distinct cell type and/or protocol of measurement. 9. Use low fluorescent immersion oil like a Cargille Immersion Oil Type HF or Type LDF (Optoteam, Vienna, Austria). 10. A FluxPak comprises sensor cartridges containing the fluorescent biosensor as well as the injection ports, utility plates, loading guides, and XF calibrant solution. 11. Non-buffered assay medium is usually based on the formulation of Dulbecco’s Modified Eagle Medium including L-glutamine but does not contain any buffering agent (i.e., sodium bicarbonate). Such medium can be obtained from, for example, Seahorse Bioscience or Sigma Aldrich. For measurements under Ca2+-free conditions, Ca2+-free assay medium has to be custom made or replaced by assay solution (6). 12. Dissolve reagents in DMSO at stock concentrations of 5–10 mM and store at
20  C.

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13. Try to use fresh isolated mitochondria, since frozen mitochondria display impaired membrane integrity. Furthermore, optimal number of strokes for dounce homogenization varies between cell types and homogenizer before impairing the integrity of mitochondrial membranes. Additional to up- and down-movements, rotation speed can increase homogenization outcome accordingly. Keep all samples during isolation on ice, precool centrifuges, all glassware, flasks, Eppis, and tools used during isolation process. Cell samples are handled at RT. 14. Optimal number of cells for each measurement can vary between cell types. Suitable protein content of isolated mitochondria additionally depends on mitochondrial integrity after isolation. If no or weak mitochondrial Ca2+ uptake is observed, we recommend using higher amounts of sample material per measurement. 15. Make sure to get rid of any excess Ca2+. In case of harvesting cells, wash away any leftover medium with PBS (at low speed according to cell line ~700  g). In case of isolated mitochondria, samples are usually prepared in EGTA/EDTA or other Ca2+ chelating agent containing buffers (at high speed for isolated organelles >10,000  g). 16. Fluorimeter cuvettes may vary for volume content. Try to stick to equal concentrations (compare Material section), if shifting down to lower volumes. Furthermore, make sure that the sample is mixed continuously during the measurement; otherwise both, the sensor and isolated mitochondria or cells, will settle down negatively affecting the readout. 17. Further pulses of various Ca2+ concentrations may be tried out. The optimal concentration is dependent on the individual cell line, number of mitochondria or cells. Calcium Green 5 N is best used within a concentration of 10–100 μM which also covers the range of MCU. For smaller concentration, one may change to a different sensor with a suitable Kd (Table 1). 18. Observation: The signal goes up upon Ca2+ addition and down when taken up by mitochondria. This can be repeated depending on mitochondrial uptake capacity and cell number (cave: always normalize to same cell number within samples to overcome laborious calculations afterwards). After a certain addition of Ca2+, the signal will not completely fall down to the last baseline followed by a steady increase of the signal. This is due to permeability pore opening and a release of excess calcium over a particular threshold known as induction of mitochondrial apoptosis. 19. When using a perfusion system on isolated mitochondria, carefully use slow perfusion 540 nm) level is done in the following mode: first 3 min (basic fluorescence level), FCCP introduction, and subsequent measurement to the moment of fluorescence level stabilization. In the experiment, an increase in the level of fluorescence should occur because of the effect of concentration quenching after the subsequent introduction of FCCP (Fig. 2), a decrease in the mitochondrial potential occurs, and the subsequent exit of the cation into the cytoplasm. The degree of increase in fluorescence is an indicator of the level of membrane mitochondrial potential and can be used to compare different types of brain.

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Fig. 2 Measurement of rhodamine 123 fluorescence in acute brain slices with complete depolarization of mitochondria upon application of FCCP 3.1 Acute Brain Slices Preparation Procedure

1. Cervical dislocation of the animal. 2. Separation of the head from the trunk in the cervical region of spinal cord by using large scissors or guillotine. 3. Dissection of the scalp along the sagittal line and opening of the cranium (generally starting in the areas of the nasal, temporal, and parietal bones). 4. Quick extraction of the brain with cerebellum, followed by periodic washing by cold HBSS (pH 7.4/4
C). It is important to avoid surface drying of the sample. 5. Performing a sagittal section of the brain in an ice-cold glass petri dish. 6. Excision of the brain regions of interest with subsequent preparation of slices with a thickness of 100–200 μm. Acute brain slices were cut on a vibratome, according to a standard brain tissue cutting procedure [17, 18], in ice-cold HBSS (pH 7.4/ 4
C).

3.2 NADH Determination Procedure

1. Prepared slices were maintained in the well of a glass slide, in 150 μl HBSS (pH 7.4/RT) for a minimum of 1 h before the measurement. 2. Then the level of NADH fluorescence is determined in a timedependent manner: (a) Record the basic level: 0–180 s. (b) Addition of 5 μl of FCCP.

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(c) Record of fluorescence level: 181–360 s. (d) Addition of 5 μl of NaCN. (e) Record of fluorescence level: 361–540 s. 3.3 Mitochondrial Membrane Potential Determination Procedure

1. One slice is transferred to a working solution of rhodamine 123 and incubated for 15 min. 2. The slice is washed using a large amount of HBSS (pH 7.4/ RT), placed in clean HBSS (pH 7.4/RT) and incubated for 5 min. Then the washing procedure is repeated two more times. 3. The prepared slice is placed in the well of a glass slide, to which 150 μl of HBSS (pH ¼ 7.4/RT) is added. 4. Then the level of fluorescence is determined at the settings of the laboratory setup closest to the fluorescence parameters of rhodamine 123: (a) Record of basic level: 0–180 s. (b) Addition of 5 μl of FCCP working solution. (c) Record of fluorescence level before reaching a plateau.

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Notes 1. Measurements of ΔΨm and NADH level in brain slices can be done using various systems including confocal microscopy but can be dome in less sophisticated systems. Here, we suggest an easy-to-implement system for measuring endogenous NADH and NAD(P)H content. The optical scheme is a standard scheme of reflected light microscopy. In this scheme, the microscope objective works both as a condenser and as an image-forming system. The key element for such optical schemes is a vertical illuminator. The main function of a vertical illuminator is to form a collimated light beam, direct it to the rear aperture of the lens, and then to the surface of the sample. The main component of a vertical illuminator in fluorescent studies is a dichroic mirror. This mirror deflects the exciting radiation coming from the horizontal illuminator by 90
to the vertical optical image-forming system. In addition, the dichroic mirror, located at an angle of 45
to the optical axes of the illuminator and the imageforming channel, passes fluorescent radiation coming out of the lens (see Fig. 3). 2. Acute brain slices are placed on glass coverslips just before the experiment. While imaging, tissue should be buffered using HEPES-buffered salt solution (HBSS medium).

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Fig. 3 Scheme of the experimental setup for measurement of endogenous fluorescence in acute brain slices. Excitation radiation (9) from an optical fiber passes through a collimator (8) and an extinction band filter (7) to cut out a narrow excitation band, and further through a dichroic mirror (4) and a planar apochromatic lens (5) is directed to the study area (6). In the image-forming channel, the back-reflected radiation from the source is filtered by a dichroic mirror (4) and an emission filter (3), and the fluorescent radiation through a longfocus lens (2) is registered by a highly sensitive cooled CCD camera (1). The field view of the system is a rectangular area of about 1 mm2 with a resolution of about 2 μm

3. This buffer allows the imaging of cells or slices in a static chamber avoiding the need for continuous CO2-equilibrated buffering. 4. FCCP is a lipid-soluble weak acid used as a mitochondrial uncoupling agent. FCCP is negatively charged allowing the anions to diffuse freely through nonpolar media, such as phospholipid membranes. It abolishes the obligatory linkage between the respiratory chain and the oxidative phosphorylation system which occurs in intact mitochondria.

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5. NaCN is a respiratory chain inhibitor and it blocks respiration in the presence of either ADP or uncouplers such as FCCP. It specifically blocks the cytochrome oxidase (complex IV) and prevents both coupled and uncoupled respirations despite the presence of substrates, including NADH, and succinate. 6. The registered NADH autofluorescence upon addition of FCCP represents both the non-mitochondrial NADH autofluorescence and the NAD(P)H autofluorescence. To ensure that only NAD(P)H autofluorescence is recorded and analyzed, background fluorescence is deducted from the total fluorescence output.

Acknowledgments This study was supported by the Russian Federation Government grant No. 075-15-2019-1877. VD kindly acknowledges the personal support from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No. 839888. References 1. Abramov AY, Angelova PR (2019) Mitochondrial dysfunction and energy deprivation in the mechanism of neurodegeneration. Turkish J Biochem 44(6):723–729 2. Chance B (1954) Spectrophotometry of intracellular respiratory pigments. Science 120 (3124):767–775 3. Chance B, Schoener B, Oshino R et al (1979) Oxidation-reduction ratio studies of mitochondria in freeze-trapped samples. NADH and flavoprotein fluorescence signals. J Biol Chem 254(11):4764–4771 4. Chance B, Thorell B (1959) Fluorescence measurements of mitochondrial pyridine nucleotide in aerobiosis and anaerobiosis. Nature 184:931–934 5. Bartolome F, Abramov AY (2015) Measurement of mitochondrial NADH and FAD autofluorescence in live cells. Methods Mol Biol 1264:263–270 6. Zamzami N, Marchetti P, Castedo M et al (1995) Sequential reduction of mitochondrial transmembrane potential and generation of reactive oxygen species in early programmed cell death. J Exp Med 182(2):367–377 7. Gasser UE, Hatten ME (1990) Neuron-glia interactions of rat hippocampal cells in vitro: glial-guided neuronal migration and neuronal

regulation of glial differentiation. J Neurosci 10(4):1276–1285 8. Angelova PR, Abramov AY (2014) Interaction of neurons and astrocytes underlies the mechanism of Abeta-induced neurotoxicity. Biochem Soc Trans 42(5):1286–1290 9. Angelova PR, Barilani M, Lovejoy C et al (2018) Mitochondrial dysfunction in parkinsonian mesenchymal stem cells impairs differentiation. Redox Biol 14:474–484 10. Arber C, Angelova PR, Wiethoff S et al (2017) iPSC-derived neuronal models of PANK2associated neurodegeneration reveal mitochondrial dysfunction contributing to early disease. PLoS One 12(9):e0184104 11. Kinghorn KJ, Castillo-Quan JI, Bartolome F et al (2015) Loss of PLA2G6 leads to elevated mitochondrial lipid peroxidation and mitochondrial dysfunction. Brain 138 (Pt 7):1801–1816 12. Ludtmann MHR, Angelova PR, Horrocks MH et al (2018) α-Synuclein oligomers interact with ATP synthase and open the permeability transition pore in Parkinson’s disease. Nat Commun 9(1):2293 13. Tufi R, Gandhi S, de Castro IP et al (2014) Enhancing nucleotide metabolism protects against mitochondrial dysfunction and

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neurodegeneration in a PINK1 model of Parkinson’s disease. Nat Cell Biol 16(2):157–166 14. Abeti R, Parkinson MH, Hargreaves IP et al (2016) Mitochondrial energy imbalance and lipid peroxidation cause cell death in Friedreich’s ataxia. Cell Death Dis 7:e2237 15. Kovac S, Domijan AM, Walker MC et al (2012) Prolonged seizure activity impairs mitochondrial bioenergetics and induces cell death. J Cell Sci 125(Pt 7):1796–1806 16. Kovac S, Preza E, Houlden H et al (2019) Impaired bioenergetics in mutant

mitochondrial DNA determines cell fate during seizure-like activity. Mol Neurobiol 56 (1):321–334 17. Angelova P, Muller W (2006) Oxidative modulation of the transient potassium current IA by intracellular arachidonic acid in rat CA1 pyramidal neurons. Eur J Neurosci 23 (9):2375–2384 18. Egorov AV, Angelova PR, Heinemann U et al (2003) Ca2+independent muscarinic excitation of rat medial entorhinal cortex layer V neurons. Eur J Neurosci 18(12):3343–3351

Chapter 15 Evaluation of Mitochondria Content and Function in Live Cells by Multicolor Flow Cytometric Analysis Hsiu-Han Fan, Tsung-Lin Tsai, Ivan L. Dzhagalov, and Chia-Lin Hsu Abstract To evaluate how a cell responds to the external stimuli, treatment, or alteration of the microenvironment, the quantity and quality of mitochondria are commonly used as readouts. However, it is challenging to apply mitochondrial analysis to the samples that are composed of mixed cell populations originating from tissues or when multiple cell populations are of interest, using methods such as Western blot, electron microscopy, or extracellular flux analysis. Flow cytometry is a technique allowing the detection of individual cell status and its identity simultaneously when used in combination with surface markers. Here we describe how to combine mitochondriaspecific dyes or the dyes targeting the superoxide produced by mitochondria with surface marker staining to measure the mitochondrial content and activity in live cells by flow cytometry. This method can be applied to all types of cells in suspension and is particularly useful for analysis of samples composed of heterogeneous cell populations. Key words Flow cytometry, FACS, Mitochondria, Quantification, Reactive oxygen species

1

Introduction Mitochondria is a double-membrane-bound organelle that plays a critical role in the generation of energy in most eukaryotic organisms [1]. Recently a surging number of studies aim to uncover the additional involvement of mitochondria in cellular functions, e.g., differentiation or effector actions. Assays such as Western blot, PCR-based measurement of mitochondrial DNA (mtDNA) copy numbers, electron and immunofluorescent microscopy, or extracellular flux analysis [2–4] are commonly applied to quantify the mitochondria amount or function. Western blot is the standard technique to evaluate the expression and modification of the target protein in the purified mitochondria. With the isolation of both mitochondrial DNA (mtDNA) and nuclear DNA, the quantitative PCR-based assay has been established to measure mtDNA copy

Volkmar Weissig and Marvin Edeas (eds.), Mitochondrial Medicine: Volume 2: Assessing Mitochondria, Methods in Molecular Biology, vol. 2276, https://doi.org/10.1007/978-1-0716-1266-8_15, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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number, which is a critical component of overall mitochondrial health. Electron and immunofluorescent microscopy are powerful tools to visualize the mitochondria morphology and spatial distribution in the cells. The newly developed extracellular flux analysis is specialized to measure the oxygen consumption rate and quantify mitochondrial respiration in living cells [5]. Take the study on mitochondrial protein, dynamin-related protein 1 (Drp1), as an example, by combining the Western blot and electron microscopy techniques, it is observed that the nutrient deprivation induces the dephosphorylation of Drp1 Serine 616 and 637 which subsequently leads to mitochondrial tabulation and elongation [6]. Numerous recent studies use extracellular flux analysis to evaluate the mitochondria activity via measuring the oxygen consumption rate—the rate of reserve capacity/spare respiratory capacity (SRC) is an indicator of mitochondria status which meaning the higher SRC it detects, the more ATP is supplied by mitochondria oxidative phosphorylation [7]. Although these abovementioned methods have all been instrumental in understanding the mitochondria biology, they are limited to analyze the homogenous cell population only. Compared to these classical methods, flow cytometry is a sensitive and timeefficient technique. In combination with surface marker staining, this method allows the detection of individual cell status from the heterogeneous cell population. Multiple mitochondria-specific and mitochondrial superoxide-detection fluorescent probes have been developed, enabling these probes to use in conjunction with surface markers. The application of these mitochondria-specific probes in flow cytometry overcomes the cell homogeneity requirement in classical methods and shortens the processing time, and, most importantly, provides broader applicability. The measurement of mitochondria mass or membrane potential has been essential to determine the status of intracellular ion homeostasis, energy metabolism, or as an indicator for cell stress/ survival in eukaryotic cells [8, 9]. MitoTracker™ Green FM has been used as a measurement of mitochondrial mass—non-fluorescent in aqueous solutions; it accumulates in the lipid environment of mitochondria and becomes fluorescent regardless of mitochondrial membrane potential [10]. It can be visualized under a microscope or quantified by flow cytometric analysis in the intact cells without the isolation of mitochondria. Based on its unique chemical properties, one can assume that the dye’s fluorescent intensity correlates with the mitochondria mass in the cells. Because mitochondria inner membrane is negatively charged, mitochondria-specific dyes are often cationic lipophilic dyes, e.g., JC-1 dye [11], rhodamine 123 [12], and tetramethylrhodamine [13], as well as thiol-reactive chloromethyl groups, including MitoTracker™ Red and MitoTracker™ Orange [14]. They are positively charged compounds that can be transported passively across

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the mitochondria membranes and accumulated within the mitochondria. When conjugated with different fluorescent chemicals, these membrane potential-dependent dyes are useful indicators of the mitochondria activity. Mitochondria activity can also be reflected by oxidative stress, one of the most important indexes of the cell metabolic status. By measuring the level of reactive oxygen species (ROS) produced [15], one can evaluate the active effector response and the metabolic change of the cell [16]. Cellular ROS level has multiple implications: high oxidative stress in the cell could lead to the activation of oxidative stress responding pathway or cell death [17], while it is also a sign of active inflammatory response in the macrophages [15, 18]. However, ROS are extremely versatile, making it a difficult parameter to measure. Although chromatography, mass spectrometry, or electrochemical sensors are capable of sensitive and accurate ROS detection, these methods require specialized equipment and the support of a well-established core facility. Several assays [19] have recently been developed to detect the intracellular cell ROS, including the fluorescence-dependent and chemiluminescence-derived methods. These techniques rely on the cell-permeable chemicals that react directly to the ROS and generating radical intermediates, which give rise to fluorescence, e.g., dihydroethidium (DHE) stain has been used to detect mitochondrial superoxide. Combining with flow cytometry, one now can apply cell-permeable fluorescent probes like CellROX™ for intracellular reactive oxygen species or MitoSOX™ for mitochondrial superoxide [20] to perform analysis of ROS on complex cell populations. The current protocol is a demonstration of how to combine surface marker staining and mitochondria- or ROS-specific dyes to measure the mitochondrial activities of the cells of interest within the heterogeneous cell population. It is worth noting that different staining procedures often are necessary to optimize the efficiency of different organelle-specific dye detection. We applied this technique to examine the mitochondria mass, membrane potential, total ROS, and mitochondrial superoxide in tissue macrophages (Mϕs). Depending on its biological functions, each organ forms its unique microenvironment. Even cells from the same lineage may behave distinctively when residing in different microenvironments or under stress. Immune cells, for example, maintain a versatile metabolic program adapting to their habitats and to satisfy the biosynthetic needs upon encountering antigens. By establishing an assay that spontaneously detects the cell identity and mitochondrial activities, it allows us to compare the immune cell status of different organs and, more importantly, the function and physiological role of the immune cells in homeostatic or disease settings [21]. We found that compared to splenic Mϕs (Fig. 1), the peritoneal cavity Mϕs harbored more mitochondria (Fig. 2a) and had higher mitochondrial activities (Fig. 2b). Moreover, the elevated

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Fig. 1 Gating strategy of peritoneal and splenic macrophages. Cells were pre-gated on FSC/SSC and PI
to obtain live singlets. Total peritoneal cells (a) and splenocytes (b) from 5.5 weeks old mice were stained with F4/80 and CD11b. Macrophages were defined as F4/80+ CD11b+ population. The results are representative of three independent experiments

mitochondria activity in peritoneal cavity Mϕs was also reflected in their ROS production capacity (Fig. 3). Together, these data suggested that tissue MΦs can adjust their metabolic profile according to the resideing microenvironment.

2

Material

2.1 Preparation of the Single-Cell Suspension

1. Dulbecco’s Modified Eagle Medium (DMEM). 2. Serum-free DMEM: DMEM, supplemented with 44 mM NaHCO3, 10 mM 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES), 100 U/mL penicillin, 100 mg/mL streptomycin, 2 mM L-glutamine, 1 mM sodium pyruvate, 1% MEM nonessential amino acids. 3. Phosphate-buffered saline (PBS): 137 mM NaCl, 2.7 mM KCl, 8 mM Na2HPO4, and 2 mM KH2PO4. 4. 5 mL syringe. 5. 24G needle. 6. 15 mL centrifuge tube. 7. 6 cm petri dish. 8. Ammonium–Chloride–Potassium (ACK) lysing buffer: 155 mM NH4Cl, 10 mM KHCO3, and 0.1 mM Na2EDTA. 9. Nylon mesh with pore size 75 μm.

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Fig. 2 Quantification of mitochondria mass and membrane potential in peritoneal and splenic macrophages. Cells were stained with mitochondria-specific dye for 15 min at 37  C, followed by surface marker staining. The fluorescent signal of stained cells was acquired by the flow cytometer and analyzed. (a) Mitochondria mass of peritoneal and splenic macrophages was quantified by MitoTracker™ Green staining of peritoneal and splenic macrophages. (b) Mitochondria membrane potential of peritoneal and splenic macrophages was evaluated by MitoTracker™ Red staining. The green and red represent mitochondria-specific staining, and the gray line shows fluorescence minus one (FMO). The results are representative of one experiment with n ¼ 3. The statistics of mitochondrial mass (c) and membrane potential (d) were performed by calculating the ΔMFI ¼ MFI (Mitochondria staining)—MFI (FMO) 2.2 Detection of Mitochondrial Mass, Activity, and ROS (See Notes 1 and 2)

1. MitoTracker Green FM, stock solution 1 mM in DMSO. 2. MitoTracker Red FM, stock solution 1 mM in DMSO. 3. CellROX™ Green (Thermo Fisher Scientific), stock solution 2.5 mM in DMSO. 4. MitoSOX™ (Thermo Fisher Scientific), stock solution 5 mM in DMSO. 5. Round-bottom FACS tube.

2.3 Surface Marker Staining

1. 2.4G2 hybridoma (ATCC® HB-197™) supernatant. 2. FACS buffer (1 PBS supplemented with 2% fetal bovine serum (FBS) and 1 mM EDTA). 3. PE-Cy7 Anti-mouse F4/80 (BioLegend, Cat#123114). 4. BV421 Anti-mouse F4/80 (BioLegend, Cat#123137).

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Fig. 3 Measurement of cellular and mitochondrial ROS in peritoneal and splenic macrophages. Cells were stained with surface marker staining, followed by reactive oxygen species-specific dye for 15 min at 37  C. The fluorescent signal of stained cells was acquired by the flow cytometer and analyzed. (a) The level of total cellular ROS in peritoneal and splenic macrophage was evaluated by CellROX staining. (b) MitoSOX™ staining of peritoneal and splenic macrophages measures the mitochondrial ROS level. The blue and purple represent mitochondria staining, and the gray one shows FMO. The results are representative of one experiment with n ¼ 3. The statistical analysis was done by calculating the ΔMFI ¼ MFI (reactive oxygen species staining)— MFI (FMO) for cellular (c) and mitochondrial (d) ROS

5. APC Anti-mouse CD11b (BioLegend, Cat#101212). 6. PE-Cy7 Anti-mouse CD11b (BioLegend, Cat#101215). 7. Propidium iodide solution. 8. DAPI.

3

Methods

3.1 Tissue Harvest and Generation of the Single-Cell Suspension

1. Euthanize the mouse by an approved method such as CO2 asphyxiation in a transparent acrylic chamber. Rinse the target area with 75% ethanol. 2. To harvest the peritoneal cells, intraperitoneally inject 5 mL serum-free DMEM medium with a 24G needle. Gently

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massage the peritoneal cavity, and harvest the peritoneal cellcontaining lavage as much as possible with the syringe. Transfer the lavage to a 15 mL centrifuge tube and leave on ice until assay. This is the peritoneal single-cell suspension. 3. Open the peritoneal cavity and locate the spleen. The spleen is at the left upper quadrant of the abdomen, carefully remove the surrounding connective tissue and harvest the spleen. 4. Dissociate the spleen by pressing gently with a syringe plunger in a 6 cm dish containing 5 mL ice-cold serum-free DMEM. Transfer the single-cell suspension to a 15 mL centrifuge tube, wash the 6 cm dish with an additional 2 mL serum-free DMEM, and pool the cell suspension together. This is the splenocyte single-cell suspension. 5. Centrifuge the cell suspension for 5 min at 450  g, 4  C and discard the supernatant. Resuspend the cell pellet with 2 mL ACK lysing buffer for 2 min at room temperature (RT) to lyse the red blood cells. At the end of the reaction, add 13 mL of PBS to the cell to neutralize the ACK lysing buffer. 6. Pellet the cells again by centrifuging for 5 min at 450  g, 4  C and resuspend peritoneal cells in 1 mL, splenocytes in 3 mL serum-free DMEM. 7. Filter cell suspension through nylon mesh to remove any clumps to obtain the single-cell suspension. Enumerate the cell number. 3.2 Quantification of Mitochondria Mass and Membrane Potential

1. Freshly prepare the mitochondria-specific dye working solution by mixing 0.1 μL MitoTracker stock solution to 1 mL ice-cold serum-free DMEM (see Note 3). 2. Add 1  106 peritoneal cells or 2  106 splenocytes to roundbottom FACS tubes, and pellet the cells by centrifuging for 5 min at 450  g, 4  C (see Note 4). Discard the supernatant. 3. Resuspend the cells in 100 μL of mitochondria-specific dye working solution and incubate for 15 min in 5% CO2 incubator at 37  C (see Note 5). 4. At the end of the incubation time, add 1 mL ice-cold FACS buffer to stop the reaction, and centrifuge for 5 min at 450  g, 4  C. Discard the supernatant. Cells are now ready to proceed with surface marker staining.

3.3 Surface Marker Staining

1. Resuspend the cells in 100 μL of 2.4G2 hybridoma supernatant and incubate on ice for 10 min to block Fc receptors. Wash the cells by adding 1 mL of ice-cold FACS buffer, and centrifuge for 5 min at 450  g, 4  C. Discard the supernatant.

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2. Resuspend the cells with 100 μL of FACS buffer containing the pre-titrated fluorescence-conjugated antibodies and incubate the mixture on ice for 20 min. Avoid light exposure during the incubation period. 3. Wash the cells by adding 1 mL of ice-cold FACS buffer, and centrifuge for 5 min at 450  g. Discard the supernatant. 4. Resuspend the pellet in 350 μL of FACS buffer containing 1 μg/mL propidium iodide (PI) and immediately analyze the samples on the flow cytometer. 3.4 Reactive Oxygen Species Detection

1. To measure cellular ROS, the samples should be stained with surface markers first (Subheading 3.3, steps 1–3), followed by reactive oxygen species detection procedures (see Note 6). 2. To make the CellROX working solution, add 0.4 μL CellROX stock to 200 μL of warm serum-free DMEM. MitoSOX working solution is made of 0.2 μL MitoSOX stock in 200 μL warm serum-free DMEM. Both working solutions should be freshly prepared. Resuspend the cell pellet from Subheading 3.3 in working solutions and incubate at 37  C for 30 min. For the control (fluorescence minus one, FMO), add 200 μL warm serum-free DMEM only. Avoid light exposure during the incubation period. 3. Add 1 mL ice-cold FACS buffer to each sample and centrifuge for 5 min at 450  g 4  C. Discard the supernatant. 4. Resuspend the pellet in 100 μL ice-cold FACS buffer containing 0.1 μL DAPI stock solution and immediately analyze the samples on the flow cytometer and perform data analysis (see Note 7).

3.5

Data Analysis

1. Once the data are collected, use the analytical software of choice to create a dot plot and gate on the populations of interest. FSC-A vs. SSC-A is used to identify cell populations, followed by FSC-A vs. FSC-H for singlet gating, FSC-A vs. PI to gate on live cells. Cell surface markers are used to mark the population of interests. Here, for example, we used F4/80 vs. CD11b for macrophages gating (Fig. 1). 2. To visualize the fluorescence of mitochondria-specific dye in the population of interests, choose the “Histogram” function (Figs. 2a, b and 3a, b). Calculate the mean fluorescence intensity (MFI) for each population of interest. 3. To perform statistical analysis, generate delta MFI (ΔMFI) for each cell population by calculating MFI (organelle-specific dyes)—MFI (FMO) (Figs. 2c, d, and 3c, d).

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Note 1. These organelle-specific dyes are very sensitive to freeze–thaw cycles as well as light and air exposure. Aliquot the stock solution in a small volume to avoid repeated freeze–thaw and light exposure and to minimize the dye from constant air exposure. 2. All of these mitochondria-specific dyes have cytotoxicity at high concentrations, a higher staining concentration than that used in the current protocol is not recommended. 3. To maintain good cell viability throughout the procedures, it is recommended to use a serum-free culture medium during the organelle-specific dyes staining step. 4. We recommend careful titration and optimization of the staining procedures for the cell population of interests. Once the conditions are set, fix the cell-to-dye ratio to maintain the consistent staining intensity. 5. To efficiently label the mitochondria-specific dyes, the reaction has to been performed at 37  C. We recommend proceeding with surface marker staining at 4  C upon the completion of the mitochondrial-dye staining to achieve the best staining results. 6. Due to the sensitivity of ROS-specific dyes and the versatile nature of ROS, perform the surface marker staining first, followed by the ROS-specific dye staining. Upon the completion of the ROS-specific dye staining procedure, analyze the sample immediately. 7. Before harvesting the sample, filter cell suspension through a cell strainer to avoid cell clumps.

Acknowledgments We would like to thank Dr. Chin-Wen Wei for the initial set up for this experimental system and Yu-Ting Hsieh for critically reading the manuscript. This work was supported by grants from Ministry of Science and Technology, Taiwan (MOST 107-2320-B-010-020, MOST 108-2628-B-010-005 to C.-L. H.; 107-2320-B-010 -016 -MY3, 106-2320-B-010 -026 -MY3 to I. L. D.) and Cancer Progression Research Center, National Yang-Ming University from The Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan.

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References 1. Spinelli JB, Haigis MC (2018) The multifaceted contributions of mitochondria to cellular metabolism. Nat Cell Biol 20(7):745–754. https://doi.org/10.1038/s41556-018-01241 2. Bass JJ, Wilkinson DJ, Rankin D, Phillips BE, Szewczyk NJ, Smith K, Atherton PJ (2017) An overview of technical considerations for Western blotting applications to physiological research. Scand J Med Sci Sports 27(1):4–25. https://doi.org/10.1111/sms.12702 3. Mumcuoglu EU, Hassanpour R, Tasel SF, Perkins G, Martone ME, Gurcan MN (2012) Computerized detection and segmentation of mitochondria on electron microscope images. J Microsc 246(3):248–265. https://doi.org/ 10.1111/j.1365-2818.2012.03614.x 4. Pelletier M, Billingham LK, Ramaswamy M, Siegel RM (2014) Chapter Seven—Extracellular flux analysis to monitor glycolytic rates and mitochondrial oxygen consumption. Methods Enzymol 542:125–149. https://doi.org/10. 1016/B978-0-12-416618-9.00007-8 5. Plitzko B, Loesgen S (2018) Measurement of oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) in culture cells for assessment of the energy metabolism. Bio-protocol 8(10):e2850. https://doi.org/ 10.21769/BioProtoc.2850 6. Rambold AS, Kostelecky B, Elia N, LippincottSchwartz J (2011) Tubular network formation protects mitochondria from autophagosomal degradation during nutrient starvation. Proc Natl Acad Sci U S A 108(25):10190–10195. https://doi.org/10.1073/pnas.1107402108 7. Divakaruni AS, Paradyse A, Ferrick DA, Murphy AN, Jastroch M (2014) Chapter Sixteen Analysis and interpretation of microplate-based oxygen consumption and pH data. Methods Enzymol 547:309–354. https://doi.org/10. 1016/B978-0-12-801415-8.00016-3 8. Van Blerkom J (2011) Mitochondrial function in the human oocyte and embryo and their role in developmental competence. Mitochondrion 11(5):797–813. https://doi.org/10.1016/j. mito.2010.09.012 9. Tait SWG, Green DR (2013) Mitochondrial regulation of cell death. Cold Spring Harb Perspect Biol 5(9):a008706. https://doi.org/10. 1101/cshperspect.a008706 10. Agnello M, Morici G, Rinaldi AM (2008) A method for measuring mitochondrial mass and activity. Cytotechnology 56(3):145–149. https://doi.org/10.1007/s10616-008-9143-2

11. Poot M, Zhang YZ, Kr€amer JA, Wells KS, Jones LJ, Hanzel DK, Lugade AG, Singer VL, Haugland RP (1996) Analysis of mitochondrial morphology and function with novel fixable fluorescent stains. J Histochem Cytochem 44 (12):1363–1372. https://doi.org/10.1177/ 44.12.8985128 12. Chen LB (1988) Fluorescent Labeling of Mitochondria. Methods Cell Biol 29:103–123. https://doi.org/10.1016/ S0091-679X(08)60190-9 13. Heiskanen KM, Bhat MB, Wang H-W, Ma J, Nieminen A-L (1999) Mitochondrial depolarization accompanies cytochrome C release during apoptosis in PC6 cells. J Biol Chem 274 (9):5654–5658. https://doi.org/10.1074/ jbc.274.9.5654 14. Wiederschain GY (2011) The molecular probes handbook. A guide to fluorescent probes and labeling technologies. Biochem Mosc 76 (11):1276–1276. https://doi.org/10.1134/ S0006297911110101 15. Chouchani ET, Pell VR, Gaude E, Aksentijevic´ D, Sundier SY, Robb EL, Logan A, Nadtochiy SM, Ord ENJ, Smith AC, Eyassu F, Shirley R, Hu C-H, Dare AJ, James AM, Rogatti S, Hartley RC, Eaton S, Costa ASH, Brookes PS, Davidson SM, Duchen MR, Saeb-Parsy K, Shattock MJ, Robinson AJ, Work LM, Frezza C, Krieg T, Murphy MP (2014) Ischaemic accumulation of succinate controls reperfusion injury through mitochondrial ROS. Nature 515 (7527):431–435. https://doi.org/10.1038/ nature13909 16. Chen X, Song M, Zhang B, Zhang Y (2016) Reactive oxygen species regulate T cell immune response in the tumor microenvironment. Oxidative Med Cell Longev 2016:10. https://doi. org/10.1155/2016/1580967 17. Volpe CMO, Villar-Delfino PH, dos Anjos PMF, Nogueira-Machado JA (2018) Cellular death, reactive oxygen species (ROS) and diabetic complications. Cell Death Dis 9(2):119. https://doi.org/10.1038/s41419-017-0135z 18. Tannahill GM, Curtis AM, Adamik J, PalssonMcDermott EM, McGettrick AF, Goel G, Frezza C, Bernard NJ, Kelly B, Foley NH, Zheng L, Gardet A, Tong Z, Jany SS, Corr SC, Haneklaus M, Caffrey BE, Pierce K, Walmsley S, Beasley FC, Cummins E, Nizet V, Whyte M, Taylor CT, Lin H, Masters SL, Gottlieb E, Kelly VP, Clish C, Auron PE,

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Chapter 16 Analysis of Mitochondrial Dysfunction During Cell Death Vladimir Gogvadze and Boris Zhivotovsky Abstract Mitochondria play a key role in various modes of cell death. Analysis of mitochondrial dysfunction and the release of proteins from the intermembrane space of mitochondria represent essential tools in cell death investigation. Here we describe how to evaluate release of intermembrane space proteins during apoptosis, alterations in the mitochondrial membrane potential, and oxygen consumption in apoptotic cells. Key words Mitochondria, Cell death, Respiration, Membrane potential, Reactive oxygen species

1

Introduction Investigation of various forms of cell death has become an important area of biomedical research. Recently, several cell death modalities in addition to necrosis and apoptosis have been described and characterized based on morphological and biochemical criteria [1]. The interaction between different forms of cell death is complicated and still a matter of debate. Mitochondria play a crucial role in the execution of various modes of cell death, although the precise mechanisms of their involvement are still unclear. Currently, it is widely accepted that mitochondria are important participants in the regulation of apoptosis, an evolutionarily conserved and genetically regulated process of critical importance for embryonic development and maintenance of tissue homeostasis in the adult organism [2]. Apoptosis is also involved in the spontaneous elimination of potentially malignant cells and therapeutically induced tumor regression, whereas defects in the apoptosis program may contribute to tumor progression and resistance to treatment [3]. The release of different proapoptotic proteins from the mitochondrial intermembrane space has been observed during the early stages of apoptotic cell death [4]. Among these proteins is a component of the mitochondrial respiratory chain, cytochrome c. Once in the cytosol, cytochrome c interacts with its adaptor

Volkmar Weissig and Marvin Edeas (eds.), Mitochondrial Medicine: Volume 2: Assessing Mitochondria, Methods in Molecular Biology, vol. 2276, https://doi.org/10.1007/978-1-0716-1266-8_16, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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molecule, Apaf-1, resulting in the recruitment, processing, and activation of pro-caspase-9, a member of the caspase family of cysteine proteases, in the presence of dATP or ATP [5]. Caspase9, in turn, cleaves and activates pro-caspase-3 and -7; these effector caspases are responsible for the cleavage of various proteins leading to biochemical and morphological features characteristic of apoptosis [6]. The mechanisms regulating cytochrome c release remain partly obscure. However, two distinct models for cytochrome c release have emerged, and these can be distinguished based on whether Ca2+ is required or not for the event. In one instance, mitochondrial Ca2+ overload causes opening of a nonspecific pore in the inner mitochondrial membrane, with subsequent swelling and rupture of the outer membrane followed by the release of cytochrome c and other intermembrane space proteins [7]. The Ca2+-independent model asserts that the release occurs without changes in mitochondrial volume or dissipation of the mitochondrial membrane potential. This mechanism involves specific pores in the outer mitochondrial membrane that are formed by certain proapoptotic members of the Bcl-2 family of proteins, such as Bax or Bak [8]. Truncated Bid, generated by caspase-8 and other proteases, induces a conformational change in Bax that allows this protein to insert into the outer membrane, oligomerize, and mediate cytochrome c release. In addition, Bax can modulate cytochrome c release by facilitation of opening of the permeability transition pore [9]. Permeabilization of the outer membrane can be stimulated by reactive oxygen species (ROS), including those produced by mitochondria. Thus, the assessment of ROS production, especially superoxide radical, can provide the information regarding the mechanisms of mitochondrial permeabilization. The following protocols represent basic tools widely used in estimating the release of intermembrane space proteins during apoptosis, assessment of the mitochondrial membrane potential in apoptotic cells, and analysis of mitochondrial oxygen consumption.

2

Materials

2.1 Assessment of Cytochrome c Release from the Mitochondria of Apoptotic Cells

In order to analyze the release of certain proteins from mitochondria during apoptosis, the cellular plasma membrane should be disrupted and the cytosolic fraction separated from the membrane material, including mitochondria. This can be achieved by incubation of cells in a solution containing digitonin, a steroid glycoside from Digitalis purpurea, which selectively permeabilizes the plasma membrane leaving the outer mitochondrial membrane intact. Plasma membrane permeabilization occurs due to the interaction of digitonin with cholesterol. The molecular weight of digitonin is

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about three times that of cholesterol; thus, digitonin binding to cholesterol permeabilizes the plasma membrane by disrupting the packing of lipids. At digitonin concentrations between 10 and 100 μg/ml, cholesterol-rich plasma membranes are permeabilized, whereas those of intracellular organelles are not [10]. 1. Cells of interest in culture (e.g., Jurkat cells, U 937, HeLa). 2. Apoptotic stimuli (e.g., etoposide, cisplatin, staurosporine). 3. Phosphate-buffered saline (PBS). 4. 1 M Tris: Dissolve 12.1 g of Tris in 100 ml of distilled water; adjust pH to 7.4 with HCl. 5. 1 M MgCl2  6H2O: Dissolve 203.3 mg of MgCl2  6H2O in 1 ml of distilled water. 6. 0.5 M EGTA: Dissolve 38.1 g of EGTA in 80 ml of distilled water, adjust pH to 7.4 using KOH, bring the solution to 100 ml, and store at 4  C. 7. 0.2% digitonin: Dissolve 10 mg of digitonin in 5 ml of distilled water, aliquot, and store at 20  C. 8. 10 ml of fractionation buffer: Weigh 0.11 g of KCl, transfer into 15 ml tubes, add 50 μl of 1 M Tris, 10 μl of 1 M MgCl2, 50 μl of 0.5 M EGTA, 0.5 ml of 0.2% digitonin solution, and make up to 10 ml with distilled water. Store at 4  C for 4–5 days. 9. Low-speed centrifuge. 10. Eppendorf centrifuge. 11. Reagents and equipment for electrophoresis in polyacrylamide gel and subsequent Western blotting. 2.2 Assessment of the Mitochondrial Membrane Potential Alterations in Apoptosis

Alteration of the mitochondrial membrane potential is one of the first responses of cells to any insult. The mitochondrial membrane potential, which drives oxidative phosphorylation [11] and mitochondrial calcium uptake [12], is generated by the electron transporting chain. When electron transport ceases, for example, during ischemia, the inner membrane potential can be built up at the expense of ATP, hydrolyzed by the mitochondrial ATP synthase. The relationship between mitochondrial depolarization and apoptosis remains controversial. Depending on cell death stimuli, some investigators consider a decrease in the mitochondrial membrane potential, an early irreversible signal for apoptosis [13], while others describe it as a late event [14]. 1. Cells of interest (e.g., Jurkat cells, U 937, HeLa). 2. RPMI-1640 medium supplemented with 5% (v/v) heatinactivated fetal bovine serum, 2 mM L-glutamine, penicillin (100 U/ml), and streptomycin (100 μg/ml).

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3. 25 mM TMRE stock solution: Dissolve 12.8 mg of tetramethylrhodamine methyl ester (TMRE; Molecular Probes) in 1 ml ethanol; store according to the manufacturer’s instructions. 4. HEPES buffer: 10 mM HEPES, 150 mM NaCl, 5 mM KCl, 1 mM MgCl2  6H2O, adjust pH to 7.4 with NaOH; store up to 2–3 days at 4  C. 5. 10 mM carbonyl cyanide 3-chlorophenylhydrazone (CCCP): Dissolve 4.1 mg of CCCP in 2 ml of ethanol, and store at 20  C. Dilute the stock solution to 1 mM by adding 50 μl of 10 mM CCCP to 450 μl of ethanol. 6. Flow cytometer (e.g., FACS; Becton Dickinson). 2.3 Assessment of Oxygen Consumption in Intact Apoptotic Cells

In many instances, apoptosis-inducing agents can directly affect mitochondria; thus, assessment of vital functions of mitochondria, such as respiration, provides important information concerning involvement of mitochondria in cell death process. Analysis of oxygen consumption can be performed using intact cells as well as cells with digitonin-permeabilized plasma membrane. In the latter case, the mitochondria can be supplied with 1. Cells of interest (Jurkat, U 937, HeLa). 2. Medium, in which cells were growing. 3. 10 mM CCCP (see above). 4. Oxygraph (Hansatech Instruments), or any other Clark-type oxygen electrode connected to computer or chart recorder. 5. Hamilton-type syringes (10 and 25 μl).

2.4 Assessment of Mitochondrial Respiration in Apoptotic Cells with DigitoninPermeabilized Plasma Membrane

1. Cells of interest. 2. 1 M Tris: Dissolve 12.1 g of Tris in 100 ml of distilled water; adjust pH to 7.4 with HCl. 3. 1 M MgCl2  6H2O: Dissolve 203.3 mg of MgCl2  6H2O in 1 ml of distilled water. 4. 0.5 M KH2PO4: Dissolve 340.2 mg of KH2PO4 in 5 ml of distilled water, adjust pH to 7.4, aliquot, and keep frozen. 5. 0.2% digitonin: Dissolve 10 mg of digitonin in 5 ml of distilled water, aliquot, and store at 20  C. 6. 10 ml of respiration buffer: Weigh 0.11 g of KCl, transfer into 15 ml tube, add 50 μl of 1 M Tris, 100 μl of 0.5 M KH2PO4, 10 μl of 1 M MgCl2, 0.5 ml of 0.2% digitonin, and make up to 10 ml with distilled water. Store at 4  C for 4–5 days. 7. Sodium succinate (0.5 M): Dissolve 135 mg of sodium succinate in 1 ml of distilled water, aliquot, and store frozen at 20  C up to 3 months.

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8. Sodium pyruvate (0.5 M): Dissolve 135 mg of sodium pyruvate in 1 ml of distilled water, aliquot, and store frozen at 20  C up to 3 months. 9. Malate (0.5 M): Dissolve 134.1 mg of malic acid in 5 ml of distilled water, adjust pH to 7.4 with KOH, aliquot, and store frozen at 20  C up to 3 months. 10. CCCP (10 mM): Dissolve 4.1 mg CCCP in 2 ml of ethanol, and store at 20  C. Dilute the stock solution to 1 mM by adding 50 μl of 10 mM CCCP in 450 μl of ethanol. 11. Rotenone (2.5 mM): Dissolve 1 mg rotenone in 1 ml ethanol, store at 20  C up to 3 months. 12. Malonate (0.5 M): Dissolve 260.15 mg of malonic acid in 5 ml of distilled water, adjust pH with KOH, aliquot, and store frozen at 20  C up to 6 months. 13. Ascorbate (0.5 M): Dissolve 440 mg of ascorbic acid in 5 ml of distilled water, adjust pH to 7.4 with KOH, aliquot, and store at 20  C up to 3 months. 14. Tetramethyl phenylenediamine (TMPD) (0.03 mM): Dissolve 4.9 mg of TMPD in 1 ml of ethanol, store at 20  C up to 3 months. 15. Oxygraph (Hansatech Instruments), or any other Clark-type electrode connected to computer or chart recorder. 16. Hamilton-type syringes (10 and 25 μl). 2.5 Assessment of Mitochondrial Production of Superoxide Radical

1. Cells of interest in culture (e.g., Jurkat cells, U 937, HeLa). 2. Apoptotic stimuli (e.g., etoposide, cisplatin, staurosporine). 3. Phosphate-buffered saline (PBS). 4. Dissolve the contents of one vial of MitoSOX™ (50 μg) in 13 μl of dimethyl sulfoxide (DMSO) to make a 5 mM MitoSOX™ reagent stock solution, or in 26 μl of DMSO to make a 2.5 mM MitoSOX™ solution. 5. Keep MitoSOX™ Red reagent desiccated and protected from light at –20  C. MitoSOX™ Red mitochondrial superoxide indicator has excitation/emission maxima of approximately 510/580 nm.

3

Methods

3.1 Evaluation of Cytochrome c Release from the Mitochondria of Apoptotic Cells

1. Incubate cells with and without apoptotic stimuli (type, concentration, and incubation time determined by cell type). 2. Harvest cells using trypsin, transfer into 15 ml tubes, count cells, and spin down at 200  g for 5 min. 3. Gently remove the supernatant, without touching the pellet.

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Cyt c cytosol Cyt c mitochondria GAPDH Fig. 1 Release of cytochrome c from mitochondria in neuroblastoma Tet21N cells during apoptosis induced by alpha-tocopheryl succinate (α-TOS). GAPDH was used as loading control

4. Resuspend cells at concentration of 1  106 cells in 100 μl of the fractionation buffer and transfer samples into Eppendorf tubes. 5. Take aliquots (2–3 μl) for protein determination. 6. Incubate samples at room temperature for 10–15 min. 7. In the end of the incubation, vortex cells briefly and spin samples down using Eppendorf centrifuge for 5 min at 10,000  g. 8. Gently, without touching the pellet, transfer supernatants (approx. 95 μl) from each sample into new Eppendorf tubes (see Note 1). 9. Add 95 μl of the fractionation buffer in each tube and resuspend the pellets. 10. Mix supernatant and pellet fractions with Laemmli buffer. Detection of proteins of interest is performed using polyacrylamide gel electrophoresis with subsequent blotting and probing with specific antibodies. A typical distribution of cytochrome c between mitochondria and cytosol in apoptotic cells is shown in Fig. 1. 3.2 Assessment of the Mitochondrial Membrane Potential

1. Prepare an aliquot of 0.3  106 cells in 300 μl of RPMI-1640 medium. 2. Dilute TMRE stock solution 1:1.000 with HEPES buffer (for a concentration of 25 μM). 3. Add an aliquot of the diluted (25 μM) TMRE to cells for a final concentration of 25 nM. 4. Incubate cells with TMRE 20 min at 37  C. 5. Further dilute the 25 μM TMRE 1:1.000 with HEPES buffer for a final concentration of 25 nM. Centrifuge cells for 5 min at 200  g at room temperature, and resuspend in fresh HEPES buffer containing 25 nM TMRE.

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6. Analyze membrane potential by flow cytometry according to the manufacturer’s instructions for the instrument used (see Note 2). 7. Use protonophore CCCP (5 μM) to dissipate the mitochondrial membrane potential completely as a positive control. 3.3 Assessment of Oxygen Consumption in Intact Apoptotic Cells

1. Calibrate the oxygen electrode according to the manufacturer protocol. 2. Add 0.3 ml of the medium to the oxygen electrode chamber under conditions of constant stirring. Set the rate of stirring 10–15 rpm. 3. Harvest cells (two to four million per measurement, depending on the cell type) and spin them down. 4. Remove the supernatant and start the program. Take 50–60 μl of the medium from the oxygen electrode chamber for resuspending the cell pellet, transfer medium with cells back to the chamber, and close the chamber with the plunger. The plunger has a stoppered central precision bore allowing additions to be made to the reaction mixture using a standard Hamilton-type syringe. Expel all air bubbles through the bore in the plunger (slight twisting of the plunger helps to gather the bubbles). The level of oxygen in the chamber will start decreasing as mitochondria consume oxygen. 5. After 3–4 min, add 10 μM CCCP through the bore in the plunger using Hamilton-type syringe. 6. After adding CCCP, the rate of respiration will increase as CCCP lowers the mitochondrial potential that stimulates oxygen consumption. 7. Express the rate of respiration as the amount of oxygen consumed by one million of cells in 1 min. The protocol allows measuring basal respiration, and respiration stimulated by CCCP (highest activity of the respiratory chain), which is not suppressed by the mitochondrial membrane potential or controlled by the activity of ATP synthase.

3.4 Assessment of Mitochondrial Respiration in Apoptotic Cells with DigitoninPermeabilized Plasma Membrane

Permeabilization of the plasma membrane allows measurement of mitochondrial activity in situ, without isolation of these organelles and the accompanying potential risk of mitochondrial damage. Selective disruption of the plasma membrane by digitonin makes mitochondria accessible to substrates for various respiratory complexes (see Note 3). The concentration of digitonin must be chosen carefully and usually should not exceed 0.01% (w/v), since higher concentrations might affect the outer mitochondrial membrane (see Note 4).

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1. Calibrate the oxygen electrode according to the manufacturer protocol. 2. Add 0.3 ml of the respiration buffer to the oxygen electrode chamber under conditions of constant stirring. Set the rate of stirring 20–25 rpm. 3. Harvest cells (two to four million per measurement, depending on the type of the cells), count them, and spin down in 15 ml tubes. 4. Remove the supernatant and start the program. Take 50–60 μl of the respiration buffer from the oxygen electrode chamber for resuspending the cell pellet, transfer the buffer with cells back to the chamber, and close the chamber with the plunger. Expel all air bubbles through the bore in the plunger (slight twisting of the electrode helps to gather the bubbles at the slot). The level of oxygen in the chamber will start decreasing as mitochondria consume oxygen. 5. Analysis of the activity of the respiratory complexes should be performed after uncoupling oxidation and phosphorylation by adding the protonophore CCCP (10 μM final concentrations) to get maximum rates of respiration. After 2–3 min, add succinate, a substrate of Complex II (10 mM final concentration); addition of substrate will stimulate respiration (see Note 5). After 3–4 min, add malonate (10 mM final concentration). The respiration will slow down as succinate dehydrogenase is inhibited. 6. After 3–4 min, add pyruvate and malate, substrates for Complex I (10 mM final concentration each) (see Note 6). Respiration will be stimulated. After 3–4 min, add rotenone, an inhibitor of Complex I (2.5 μM final concentration). This will slow down oxygen consumption. 7. After 3–4 min, add 5 mM ascorbate and 0.3 mM (TMPD), an artificial electron donor for cytochrome c. Respiration will be stimulated again. This approach allows the assessment of the Complexes I, II, and IV of the mitochondrial respiratory chain. A typical curve of mitochondrial oxygen consumption by permeabilized cells is shown in Fig. 2. 3.5 Assessment of Mitochondrial Superoxide Radical Production

1. Incubate cells with and without apoptotic stimuli (type, concentration, and incubation time determined by the cell type). 2. Harvest cells using trypsin, transfer into 15 ml tubes, count cells, and spin down at 200  g for 5 min. 3. Gently remove the supernatant, without touching the pellet. 4. Resuspend cells at concentration 1  106 cells/ml and aliquot in Eppendorf tubes (0.5 ml of suspension per tube).

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cells

250

CCCP succinate 200

O2 (nmol/ml)

malonate 150

pyruvate+ malate rotenone TMPD asc

100

50

0 0

200

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800 1000 Time (sec)

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Fig. 2 Assessment of mitochondrial respiration in digitonin-permeabilized cells

5. Add 1 μl of MitoSOX™ Red to each tube; for the background fluorescence, add 1 μl DMSO (see Note 7). 6. Incubate samples at 37  C for approx. 20 min. This incubation time can be increased to 40 min if necessary. 7. Add 0.5 ml medium, centrifuge the samples, and discard the supernatant. 8. Add 0.5 ml of prewarmed medium to the pellets and resuspend the cells. 9. Transfer the cell suspension to the flow cytometer measurement tube, mix, and record the fluorescence according to the manufacturer’s instructions (Fig. 3).

4

Notes 1. Separation of the mitochondria from the supernatant should be done thoroughly. Aliquots of supernatant should be taken without disturbing the pellet. 2. The analysis of the membrane potential should be done shortly after staining of the cells. TMRE is only accumulated by mitochondria with high membrane potential, and any delay in analysis may negatively affect the functional state of the mitochondria and therefore cause leakage of the dye.

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control

etoposide

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Fig. 3 Superoxide radical production in control and etoposide-treated neuroblastoma Tet21N cells

3. The concentration of digitonin can be determined experimentally by staining permeabilized cells with Trypan blue, a vital stain used to selectively color cells with damaged plasma membrane. The lowest concentration causing permeabilization of 90–95% cells should be used in the experiment. 4. Digitonin may precipitate after cooling; shake it vigorously before adding to the buffer. 5. Experiment can be started with analysis of Complex I activity instead of Complex II. 6. Pyruvate and malate can be mixed before the experiment and added together. 7. The working concentration of MitoSOX™ can vary depending on the type of cells.

Acknowledgments The work was supported by the Russian Science Foundation (grant 19-14-00122). The work in the authors’ laboratory is supported by Swedish and the Stockholm Cancer Societies. References 1. Galluzzi L, Vitale I, Aaronson SA et al (2018) Molecular mechanisms of cell death: recommendations of the nomenclature committee on cell death 2018. Cell Death Differ 25 (3):486–541 2. Kerr JF, Wyllie AH, Currie AR (1972) Apoptosis: a basic biological phenomenon with wideranging implications in tissue kinetics. Br J Cancer 26(4):239–257

3. Lowe SW, Lin AW (2000) Apoptosis in cancer. Carcinogenesis 21(3):485–495 4. Gogvadze V, Orrenius S, Zhivotovsky B (2006) Multiple pathways of cytochrome c release from mitochondria in apoptosis. Biochim Biophys Acta 1757(5–6):639–647 5. Zou H, Li Y, Liu X, Wang X (1999) An APAF1.Cytochrome c multimeric complex is a

Mitochondrial Alterations in Apoptosis functional apoptosome that activates procaspase-9. J Biol Chem 274 (17):11549–11556 6. Robertson JD, Orrenius S, Zhivotovsky B (2000) Review: nuclear events in apoptosis. J Struct Biol 129(2–3):346–358 7. Crompton M (1999) The mitochondrial permeability transition pore and its role in cell death. Biochem J 341(Pt 2):233–249 8. Martinou JC, Green DR (2001) Breaking the mitochondrial barrier. Nat Rev Mol Cell Biol 2 (1):63–67 9. Gogvadze V, Robertson JD, Zhivotovsky B, Orrenius S (2001) Cytochrome c release occurs via Ca2+-dependent and Ca2+- independent mechanisms that are regulated by Bax. J Biol Chem 276(22):19066–19071

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10. Mooney RA (1988) Use of digitonin permeabilized adipocytes for cAMP studies. Methods Enzymol 159:193–202 11. Mitchell P, Moyle J (1967) Chemiosmotic hypothesis of oxidative phosphorylation. Nature 213(5072):137–139 12. Carafoli E, Crompton M (1978) The regulation of intracellular calcium by mitochondria. Ann N Y Acad Sci 307:269–284 13. Zamzami N, Susin SA, Marchetti P, Hirsch T, Gomez-Monterrey I, Castedo M, Kroemer G (1996) Mitochondrial control of nuclear apoptosis. J Exp Med 183(4):1533–1544 14. Bossy-Wetzel E, Newmeyer DD, Green DR (1998) Mitochondrial cytochrome c release in apoptosis occurs upstream of DEVD-specific caspase activation and independently of mitochondrial transmembrane depolarization. EMBO J 17(1):37–49

Chapter 17 Modified Blue Native Gel Approach for Analysis of Respiratory Supercomplexes Sergiy M. Nadtochiy, Megan Ngai, and Paul S. Brookes Abstract In mitochondrial oxidative phosphorylation (Ox-Phos), individual electron transport chain complexes are thought to assemble into supramolecular entities termed supercomplexes (SCs). The technique of blue native (BN) gel electrophoresis has emerged as the method of choice for analyzing SCs. However, the process of sample extraction for BN gel analysis is somewhat tedious and introduces the possibility for experimental artifacts. Here we outline a streamlined method that eliminates a centrifugation step and provides a more representative sampling of a population of mitochondria on the final gel. Using this method, we show that SC composition does not appear to change dynamically with altered mitochondrial function. Key words Mitochondria, Supercomplexes, Blue-native, Clear-native, Permeability transition pore, Respiration

1

Introduction In mitochondrial oxidative phosphorylation (Ox-Phos), individual electron transport chain complexes are thought to assemble into supramolecular entities termed supercomplexes (SCs) [1]. The techniques of blue native (BN) and clear native (CN) gel electrophoresis have emerged as methods of choice for analyzing SCs and have provided evidence that SC assembly may be altered under conditions such as ROS generation [2] and swelling associated with opening of the mitochondrial permeability transition (PT) pore [3, 4]. However, the functional role of SCs has been questioned [5], and some technical challenges associated with their quantitative assessment have also been highlighted [6]. As such, it remains unclear whether SCs are regulated on a dynamic time scale of seconds to minutes, with changing mitochondrial function.

Volkmar Weissig and Marvin Edeas (eds.), Mitochondrial Medicine: Volume 2: Assessing Mitochondria, Methods in Molecular Biology, vol. 2276, https://doi.org/10.1007/978-1-0716-1266-8_17, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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Current native gel methods for SC analysis necessitate replacement of experimental incubation media with gel-compatible media, often accomplished via centrifugation of mitochondria [1]. However, many perturbations that are applied to mitochondria (e.g., PT pore opening) are known to alter mitochondrial density [7], thus raising the possibility that differences seen on BN gels may arise from centrifugal selection of mitochondrial subpopulations. Therefore, SCs visualized on BN gels may not represent the full mitochondrial population present in the original incubations. To address this potentially important experimental artifact, our objective herein was to develop an improved BN gel method, using a compromise buffer system compatible with both mitochondrial function and sample preparation for BN gels. By eliminating a centrifugation step, the proposed new method ensures the entire mitochondrial population is sampled and also realizes significant time savings. To validate the method, we exposed mitochondria to conditions of Ca2+ overload that induce PT pore opening and large amplitude swelling. Example results (Fig. 1) indicate that the method yields good resolution of SCs, with similar BN gel band patterns as those observed by existing methods. Based on our observations using this new method, the levels of SCs do not appear to change under conditions of PT pore opening. This observation contrasts with the idea that SC assembly state is dynamic in response to (and perhaps even regulates) mitochondrial function [5, 6]. Our results also suggest that some previously reported differences in SC assembly should be reassessed, to ensure they do not arise from differential sampling of dense vs. buoyant mitochondria by existing extraction methods.

2

Materials (See Note 1) The preparation of BN gels is addressed extensively in the accompanying article from Buetner and Porter in this volume [8]. For convenience, recipes for conventional BN gel and buffer systems are shown below, but this section will mostly focus on core differences between existing BN gel extraction buffers and those developed for this new method.

2.1 General Solutions for Running BN Gels

1. BN gel resolving buffer: 75 mM imidazole, 1.5 M aminocaproic acid. Dissolve 0.555 g imidazole plus 9.839 g aminocaproic acid in 50 ml water, then adjust pH to 7.0 at 4
C. Store refrigerated. This solution is a 3 buffer, so when preparing gels, it should contribute one-third of the final volume alongside other gel components (acrylamide, etc.).

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Fig. 1 Blue Native Supercomplexes and Mitochondrial PT Pore Opening. Isolated heart mitochondria [9] were incubated at 37
C, in conditions to induce PT pore opening and swelling, with succinate (5 mM) and rotenone (5 μM) present. Incubations took place either in respiration buffer at 0.5 mg/ml (Subheading 2.2, item 2) or in compromise buffer at 2 mg/ml (Subheading 2.2, item 3). Pore opening was initiated by addition of 100 μM CaCl2 to the incubation, and experiments were stopped after 10 min. (a) Blue native gel from control and Ca2+ treated mitochondria, processed according to existing BN gel methods involving centrifugation (Table 1 left column). Left image shows BN gel immediately following electrophoresis (note: blue color comes from the BN gel itself, not post-gel staining with Coomassie Blue). Right panel shows results of an in-gel Cx-V assay (Subheading 3.3), with white precipitate bands corresponding to active Cx-V in various assembly states. (b) Blue native gel from control and Ca2+ treated mitochondria, processed according to the novel BN gel method (Table 1 right column). Gel and Cx-V in-gel assay are as in panel b

2. BN gel loading buffer: 50 mM aminocaproic acid, 5% w/v Coomassie blue. Dissolve 0.066 g aminocaproic acid in 10 ml water, then pH to 7.0 at 4
C. Add 0.5 g Coomassie Brilliant Blue-G and mix to form a suspension, then recheck pH. Store refrigerated. 3. BN gel anode buffer: 25 mM imidazole. Dissolve 1.702 g imidazole in 1 L water, then adjust pH to 7.0 at 4
C. Store refrigerated. 4. BN gel cathode buffer: 7.5 mM imidazole, 50 mM tricine. Dissolve 0.511 g imidazole plus 8.958 g tricine in 1 L water, then adjust pH to 7.0 at 4
C. Store refrigerated. 5. Digitonin: Prepare a solution of 20% (w/v) by dissolving 0.2 g digitonin in 1 ml water (see Note 2).

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Table 1 Existing and modified sample extraction protocols for BN electrophoresis Typical native gel method 1 0.5 mg mito in 1 ml incubation (0.5 mg/ml)

Modified method 0.5 mg mito in 250 μl CB (2 mg/ml)

# 2 Centrifuge 14,000  g, 10 min to recover mito pellet, discard s/n

#

# 3 Resuspend pellet in 25 μl extraction buffer, add 10 μl 20% digitonin (5.7% final), mix, rest on ice 20 min #

#

3 Centrifuge 14,000  g, 5 min to remove insoluble material #

Centrifuge 14,000  g, 5 min to remove insoluble material #

5 Add 4 μl loading buffer, mix #

Add 30 μl loading buffer, mix #

6 Load 10 μl sample/well (128 μg), run gel

2.2 Compromise Buffer (CB) for Incubations and BN Gel Extraction

Add 10 μl 20% digitonin (0.8% final), mix, rest on ice 5 min (see Notes 7 and 8)

Load 40 μl sample/well (69 μg), run gel (see Note 9)

The recipe for existing BN gel extraction buffer is given below. In addition, a recipe for typical mitochondrial respiration buffer is shown. Finally, a recipe for our new “compromise buffer” (hereafter referred to as CB) is given (see Note 3). 1. Existing BN gel extraction buffer: 50 mM NaCl, 40 mM imidazole, 2 mM aminocaproic acid, 1 mM EDTA. Dissolve 0.146 g NaCl, 0.170 g imidazole, 0.013 g aminocaproic acid, and 0.019 g EDTA in 50 ml water. Then adjust pH to 7.0 at 4
C. Store refrigerated. 2. Mitochondrial incubation buffer: 120 mM KCl, 10 mM HEPES, 25 mM sucrose, 1 mM EGTA, 5 mM KH2PO4, 5 mM MgCl2. Dissolve 4.47 g KCl, 1.19 g HEPES, 4.28 g sucrose, 0.19 g EGTA, 0.034 g KH2PO4, and 0.508 g MgCl2 in 50 ml water, then adjust pH to 7.3 at 37
C. Store frozen in 5 ml aliquots. 3. Compromise incubation/extraction buffer (CB): 80 mM KCl, 2 mM HEPES, 40 mM imidazole, 10 mM sucrose, 5 mM aminocaproic acid, 1 mM EGTA, 2 mM KH2PO4, 2 mM MgCl2. Dissolve 2.98 g KCl, 0.238 g HEPES, 0.17 g imidazole, 1.712 g sucrose, 0.0325 g aminocaproic acid, 0.19 g EGTA, 0.014 g KH2PO4, and 0.203 g MgCl2 in 50 ml water, then adjust pH to 7.2 at 37
C. Store frozen in 5 ml aliquots.

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2.3 Solutions for In-Gel Complex V Assay

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For the assignment of identity to SCs on gels, an in-gel activity assay can be performed for one of the respiratory complexes. For the assay of Cx-V, a stock solution (Cx-V buffer A) is prepared as below. During the assay, a separate aliquot of this buffer is modified by addition of Mg2+, ATP, and lead nitrate, to yield Cx-V buffer B. 1. Cx-V buffer A: 35 mM Tris, 270 mM glycine. Dissolve 0.424 g Tris plus 2.027 g glycine in 100 ml water, then adjust pH to 8.3 at 25
C. Store refrigerated. 2. Cx-V buffer B: 35 mM Tris, 270 mM glycine, 135 mM MgSO4, 6.5 mM Pb(NO3)2, 7.8 mM ATP. To a 14 ml aliquot of buffer A, add 0.023 g MgSO4, 0.03 g Pb(NO3)2, and 0.06 g ATP (disodium salt). Mix and then recheck pH to 8.3 at 25
C. Do not store (see Notes 4 and 5).

3

Methods Typical starting material for BN gel analysis of SCs is isolated mitochondria. The isolation of mitochondria from a variety of tissues by differential centrifugation is covered extensively elsewhere in this volume and series. In brief, for validation of this method, we isolated mouse cardiac mitochondria, as previously described [9] (see Note 6).

3.1 Mitochondrial Incubation and Sample Extraction for BN Gel Analysis

Table 1 shows a comparison of the existing BN gel extraction and preparation methods and our streamlined method using compromise buffer (CB). Critical differences between the methods are as follows: First, instead of incubating mitochondria for experiments in one media, then pelleting and extracting in a different media, a single media (compromise buffer, CB) is used for the whole procedure. Second, instead of stopping experimental incubations by centrifuging mitochondria, incubations are stopped by direct addition of detergent (digitonin) to the experiment. Third, due to the lack of a centrifugation step to concentrate mitochondria, it is necessary to perform mitochondrial incubations at higher than normal concentration (2 mg/ml protein vs. typical 0.5 mg/ml). Lastly, the overall volumes for extraction are larger, so the final extract is more dilute. As such, it is necessary to load a greater volume onto the BN gel (40 μl vs. the usual 10 μl). Nevertheless, the new method still achieves protein loading in amounts that enable successful visualization of SCs on the final BN gels.

3.2 BN Gel Electrophoresis

The preparation and running of BN gels is addressed extensively in the accompanying article from Beutner and Porter in this volume [8]. For convenience, recipes for BN gel and buffer systems are given in Subheading 2.1 above. Typical BN gel methods use a 3–8% polyacrylamide gradient gel, prepared from a 37.5/1 acrylamide/

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bisacrylamide stock solution. Gels should be run at 40 V, 4
C (e.g., in a cold room) for 18 h, using standard mini-gel apparatus (e.g., Bio-Rad mini-Protean 3). 3.3 Cx-V In-Gel Assay

1. While gel is running, prepare Cx-V assay solution A, as in Subheading 2.3. 2. Remove gel from glass plates and place in a clean plastic box on a shaker platform for 2 h. in 14 ml buffer A (see Note 10). 3. After 1.5 h, prepare Cx-V assay buffer B, using a separate aliquot of buffer A (see Notes 3 and 4). 4. Transfer the gel to buffer B, on the shaker platform, then observe the formation of white precipitate bands for up to 2 h. The reaction can be stopped by washing the gel extensively in water (see Notes 10 and 11). 5. If desired, the gel can be fixed in a solution of 50% methanol prior to imaging or storage.

4

Notes 1. All chemicals should be of the highest grade available. Good quality deionized water (18 MΩ) should be used for all solutions. 2. Digitonin solutions must be freshly prepared immediately prior to use, from fresh digitonin powder (stored at minus 20
C). Aged powders or stock solutions will yield vastly inferior separation on final BN gels. 3. An important control during development of this method was to determine that the compromise buffer (CB) would indeed support mitochondrial function. Experiments to measure respiration using a Clark-type oxygen electrode (not shown) indicated that for mitochondria at 2 mg protein/ml, respiring on succinate as a respiratory substrate, a respiratory control ratio (state 3/state 2) of 5.0, was typically obtained. 4. The MgSO4, Pb(NO3)2, and ATP should all be weighed from fresh powders and added to the 14 ml aliquot of buffer “A” immediately before use. The pH of the solution should be rechecked, and corrected using NaOH if necessary, before use. If solution B sits unused for >30 min, discard and remake it. 5. Lead nitrate is toxic. Appropriate personal protective equipment should be worn. Leftover solutions should be disposed via appropriate hazardous waste channels.

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6. Mice were of the C57BL/6J strain, both sexes, and were maintained in an AAALAC accredited facility according to the NIH Guide for the Care and Use of Laboratory Animals (2011 update), with food and water available ad libitum and all procedures approved by local committee. 7. Following cessation of the experiment and establishment of an extraction (step 3 in Table 1), samples should be thoroughly mixed, but not too aggressively. We find the use of vortex mixer results in fewer SCs visible in the final gels, and as such we recommend to mix the incubation tubes gently by inversion once or twice during the 5 min. Rest on ice. We also find that 5 min. on ice is sufficient for optimal extraction, and the existing 20 min. Incubation is unnecessarily long. 8. Although the final concentration of digitonin is lower in the new method (0.8% vs. 5.7%), the ratio of digitonin to protein is similar, and this level of detergent still results in successful resolution of SCs (see results). 9. Comparison of gel loading volumes shows that the existing BN method loads ~128 μg protein per well in a 10 μl volume, whereas the new method loads about half the protein in four times the volume. Nevertheless, 40 μl is well within the volume range that can be accommodated by common gel apparatus (e.g., 10-well comb, 1.5-mm thick Bio-Rad mini-gel). 10. Plastic staining boxes used for gel handling, Western blotting, etc., are often contaminated with residues that can interfere with development of bands in the Cx-V in-gel assay. For this reason, we recommend to retain a dedicated box or set of boxes for exclusive use for this assay, not to be used for other purposes. 11. If desired, a separate gel can be used to perform the Cx-V assay in the presence of the Cx-V inhibitor oligomycin (1 μg/ml final concentration). However, since oligomycin is hydrophobic, care should be taken to not contaminate plastic containers, so that residual oligomycin does not interfere with future assays.

Acknowledgments Work in the lab of PSB is funded by a grant from the US National Institutes of Health (R01-HL071158). We thank George Porter and Gisela Beutner for critical discussions during the execution of these studies.

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References 1. Sch€agger H, Pfeiffer K (2000) Supercomplexes in the respiratory chains of yeast and mammalian mitochondria. EMBO J 19:1777–1783 2. Maranzana E, Barbero G, Falasca A, Lenaz G, Genova M (2013) Mitochondrial respiratory supercomplex association limits production of reactive oxygen species from complex I. Antioxid Redox Signal 19:1469–1480 3. Beutner G, Alanzalon R, Porter G (2017) Cyclophilin D regulates the dynamic assembly of mitochondrial ATP synthase into synthasomes. Sci Rep 7:14488 4. Alavian K, Beutner G, Lazrove E, Sacchetti S, Park H, Licznerski P, Li H, Nabili P, Hockensmith K, Graham M, Porter G, Jonas E (2014) An uncoupling channel within the c-subunit ring of the F1FO ATP synthase is the mitochondrial permeability transition pore. Proc Natl Acad Sci U S A 111:10580–10585

5. Fedor JG, Hirst J (2018) Mitochondrial Supercomplexes do not enhance catalysis by quinone channeling. Cell Metab 28:525–531 6. Jang S, Javadov S (2018) Current challenges in elucidating respiratory supercomplexes in mitochondria: methodological obstacles. Front Physiol 9:238 7. Hackenbrock CR (1966) Ultrastructural bases for metabolically linked mechanical activity in mitochondria. I. Reversible ultrastructural changes with change in metabolic steady state in isolated liver mitochondria. J Cell Biol 30:269–297 8. Buetner G, Porter G (2020) Native gel electrophoresis and Immunoblotting to analyze electron transport chain complexes 9. Smith CO, Wang YT, Nadtochiy SM, Miller JH, Jonas EA, Dirksen RT, Nehrke K, Brookes PS (2018) Cardiac metabolic effects of KNa1.2 channel deletion and evidence for its mitochondrial localization. FASEB J 32:6135–6149

Chapter 18 Patch-Clamp Recording of the Activity of Ion Channels in the Inner Mitochondrial Membrane Piotr Bednarczyk, Rafał P. Kampa, Shur Gałecka, Aleksandra Se˛k, Agnieszka Walewska, and Piotr Koprowski Abstract Mitochondria are intracellular organelles, which play a crucial role in the generation of ATP. Mitochondria are surrounded by a double membrane, consisting of a smooth outer membrane (OMM) and a markedly folded inner mitochondrial membrane (IMM). Mitochondrion that has been stripped of its outer membrane, leaving the inner membrane intact is called mitoplast. There is a number of different transport proteins located in the inner mitochondrial membrane including ion channels that mediate fluxes of potassium, calcium, and chloride ions. These channels regulate the mitochondrial membrane potential, respiration, and production of reactive oxygen species. The stability of mitoplasts offers the possibility of measuring the activity of ion channels from IMM using the patch-clamp technique. Electrophysiological measurements of currents through ion channels in the IMM permit discovery of unique properties of these channels with the aim of new specific pharmacological therapies. In this chapter, we describe the isolation of mitochondria, preparation of mitoplast for patch-clamp recordings and single-mitoplast PCR experiments, which can be helpful in mastering the technique of recording the activity of mitochondrial ion channels. Key words Mitochondria, Mitoplast, Patch-clamp technique, Inner mitochondrial membrane, Ion channel, PCR

1

Introduction Electrophysiological measurements are one of the biophysical methods used to explore the electrical activity of cells and investigate related molecular and cellular processes [1]. The patch-clamp technique historically originated from the work of Alan Hodgkin and Andrew Huxley, describing the recording of macroscopic currents by voltage-clamp experiments [2]. It allowed the determination of the physiological significance of ion flow through membrane channels and laid the foundation for the development of electrophysiological techniques. The work of Hodgkin and Huxley was awarded the Nobel Prize in 1963. Next, this technique was

Volkmar Weissig and Marvin Edeas (eds.), Mitochondrial Medicine: Volume 2: Assessing Mitochondria, Methods in Molecular Biology, vol. 2276, https://doi.org/10.1007/978-1-0716-1266-8_18, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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improved by Neher and Sakmann [3] for which they also received the Nobel Prize in Physiology or Medicine in 1991 [4]. In their technique, which we call nowadays “patch-clamp“one pipette sets up voltage and records ionic currents flowing through single channels residing in small membrane patch. The patch-clamp technique still remains one of the top methods for measuring single-molecule dynamics. Thanks to this technique, it is possible to record from small membrane objects to which other techniques are not adapted. It was used to discover new types of ion channels and their importance for the proper functioning of the cells [4]. Continuous improvement of the technique allowed for more accurate monitoring of the electrical function of cellular membranes [5]. By this technique, the activity of ion channels residing in the plasma membrane and those found in intracellular structures of cells of many types of tissues may be recorded. Different types of ion channels that can be studied by the patch-clamp technique are in fact present in multiple membrane compartments, e.g., largeconductance calcium-activated potassium (BKCa) channel is present in the plasma membrane [6] but also membranes of mitochondria [7, 8], lysosomes [9, 10], and nucleus [11]. At present, there are reports of successful use of the patch-clamp technique in studies of ion channels present in mitochondria from endothelial cells [8], cardiomyocytes [12], astrocytoma [13], skin fibroblasts [14], keratinocytes [15], and even from the Drosophila melanogaster [16]. The use of the patch-clamp technique has significantly contributed to the development of mitochondrial science. It allowed the discovery of the presence of ion channels in mitochondria and comparison with their counterparts in the cell membrane, like in the case of BKCa [17]. Channel activities discovered in mitochondria with the help of the patch-clamp technique include in addition to mitoBKCa, for instance, these of mitochondrial ATP-inhibited potassium channel (mitoKATP) [14, 18], mitochondrial megachannel also known as permeability transition pore (PTP) [19, 20], mito-TASK3 [21], and others like voltage-gated potassium channels [22, 23] or intermediate-conductance Ca2+-regulated potassium channel [24]. The patch-clamp technique is also uniquely suited to study the mechanosensitivity of channels including mitoBKCa [25]. Activation of mitochondrial potassium channels is associated with cytoprotection, and for this reason, they constitute important pharmacological targets [26, 27]. Due to the direct nature of measurements of single-channel activity using the patchclamp method, one can readily observe changes in the current flow after the application of potential activators or inhibitors of the tested channel. Thanks to this type of research, new ion channel activators could be discovered or cytoprotective activity of known substances based on the activation of mitochondrial potassium channels explained, e.g., flavonoids of natural origin— naringenin [28].

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Fig. 1 Schematic representation of the preparation of mitochondria, mitoplasts, and the patch-clamp experiments on the inner mitochondrial membrane. Mitoplasts are obtained by osmotic shock resulting in rupture of the outer mitochondrial membrane. Mitoplast patch-clamp experiments are carried out in the inside-out mode with the perfusion system. The matrix side of a mitoplast is exposed to externally added substances, and the ion channel activity from the inner mitochondrial membrane is recorded

This protocol describes the methodology, which is used for the patch-clamp experiments on mitoplasts along with practical tips and descriptions of the implementation of its individual stages. We described the methods for (1) the isolation of fresh mitochondria from cell cultures, (2) formation of mitoplast, (3) patch-clamp recordings on mitoplasts, (4) single-mitoplast PCR (Fig. 1). This protocol is ultimately optimized for recording mitoBKCa channels from human cell lines. For recording other types of channels, protocol has to be optimized—solutions might be modified to include the appropriate concentration of required modulators, e.g., higher concentration of Ca2+ ions to record PTP activity [19]. Mitochondria for patch-clamp recordings could be isolated not only from cell cultures but also from animal [23] or even plant tissues [29].

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The mitoplast could be formed either directly in the recording chamber or preformed and snap frozen in liquid nitrogen. However, it should be noted that the latter approach could not be feasible for mitochondria from all cell types or tissues, e.g., it was noticed that mitoplasts from mice heart were very fragile and only method in which mitoplasts were formed directly in the recording chamber was used in this case [12]. Two types of substance administration techniques for testing the pharmacological properties of channels can be employed. One of them is perfusion with the use of an external perfusion pump feeding the test substances from the second perfusion pipette, with a larger diameter than that used as a recording pipette (the recording pipette is inserted into the perfusion pipette tip from which the substance is administered). In the second approach, substances are directly added to the recording chamber. Succesful patch-clamp on mitoplast depends on the correct identification of the very object. For a trained eye, a mitoplast is easily recognized by the round shape and characteristic outer membrane cap under a phase-contrast microscope. More objective methods to identify mitoplast could be used during training, like fluorescent staining with potential sensitive dyes, which accumulate in mitochondria [30]. However, this requires the presence of a fluorescent microscope in the patch-clamp rig, and in addition, hydrophobic dyes could impact the activity of a channel. Therefore, at the end of our protocol, we described single-mitoplast PCR, a technique that can be employed with a standard patch-clamp setup to correlate the visual appearance of the object with the content of mitochondrial DNA (mtDNA) [31]. Altogether, the protocol can be helpful especially for the novice electrophysiologist in mastering the technique of recording the activity of mitochondrial ion channels.

2

Materials All chemicals need to be of the highest purity available. Ultrapure water is systematically used (resistance >18 MΩ cm at 25
C).

2.1

Stock Solutions

All solutions should be kept in the fridge or frozen when indicated. 1. 1.5 M KCl: Weigh 55.9 g of potassium chloride (KCl). Add water to 500 mL and mix. 2. 0.1 M CaCl2: Weigh 5.5 g of calcium chloride hexahydrate (CaCl2·H2O). Add water to 250 mL and mix. 3. 0.5 M HEPES, pH ¼ 7.2: Weigh 11.9 g of 4-(2-hydroxyethyl)1-piperazineethanesulfonic acid (HEPES). Add water to a volume of 90 mL and mix. Adjust pH to 7.2 with potassium hydroxide (KOH). Finally, add water to a volume of 100 mL.

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4. 0.1 M EGTA: Weigh 3.8 g of ethylene glycol-bis(β-aminoethyl ether)-N,N,N0 ,N0 -tetraacetic acid (EGTA). Add water to a volume of 200 mL. Adjust pH to 7.2 with potassium hydroxide (KOH) while mixing, and finally add water to a volume of 250 mL. 2.2 Mitochondria Isolation

1. Preparation solution (250 mM sucrose, 5 mM HEPES, pH ¼ 7.2): Weigh 21.4 g sucrose, add 2.5 mL of 0.5 M HEPES stock solution. Add water to a volume of 200 mL. Mix and adjust pH to 7.2 with potassium hydroxide (KOH). Add water to a volume of 250 mL, mix, and aliquot in 15 mL Falcon tubes. Store at 20
C. 2. Storage solution (150 mM KCl, 10 mM HEPES, pH ¼ 7.2): Mix 10 mL of 1.5 M KCl stock solution and 2 mL of 0.5 M HEPES stock solution. Add water to a volume of 90 mL and mix. Adjust pH to 7.2 with potassium hydroxide (KOH), and add water to a volume of 100 mL. 3. Glass potter homogenizer No. 19, 1 mL capacity. 4. Refrigerated benchtop centrifuge with rotors for 15 mL Falcon and Eppendorf tubes.

2.3 Mitoplast Preparation

1. Hypotonic solution (5 mM HEPES, 100 μM CaCl2, pH ¼ 7.2): Mix 2.5 mL of 0.5 M HEPES stock solution and 250 μL of 0.1 M CaCl2 stock solution. Add water to a volume of 200 mL. Mix, adjust pH to 7.2 with potassium hydroxide (KOH), and add water to a volume of 250 mL. 2. Hypertonic solution (750 mM KCl, 30 mM HEPES, 100 μM CaCl2, pH ¼ 7.2): Mix 125 mL of 1.5 M KCl stock solution with 7.5 mL of 0.5 M HEPES stock solution and 250 μL of 0.1 M CaCl2 stock solution. Add water to a volume of 200 mL. Mix, adjust pH to 7.2 with potassium hydroxide (KOH), and add water to a volume of 250 mL. 3. Sucrose solution (1.5 M sucrose, 30 mM HEPES, 100 μM CaCl2, pH ¼ 7.2): Weigh 12.84 g of sucrose, add 750 μL of 0.5 M HEPES stock solution and 25 μL of 0.1 M CaCl2 stock solution. Add water to a volume of 25 mL and mix. Aliquot in Eppendorf tubes and keep frozen at 20
C.

2.4 Patch-Clamp Recordings

1. Isotonic solution (150 mM KCl, 10 mM HEPES, and 100 μM CaCl2, pH ¼ 7.2): Mix 25 mL of 1.5 M KCl stock solution with 5 mL of 0.5 M HEPES stock solution and 250 μL of 0.1 M CaCl2 stock solution. Add water to a volume of 200 mL. Mix and adjust pH to 7.2 with potassium hydroxide (KOH), and add water to a volume of 250 mL.

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Fig. 2 Photographs of the patch-clamp setup. (a) (1) multibarrel pipette of four-channel perfusion system with tubings driven by a peristaltic pump (also shown in b); (2) a patch-clamp glass pipette with the recording AgCl electrode inside (also shown in b). The pipette is connected to a water-filled U-tube with a three-way valve for the application of the positive and negative pressure (not shown). In the back, a reference bath electrode with a 3 M KCl salt-agar bridge can be seen as well. (b) (3) An in-house made anti-vibration table; (4) joystick controllers of micromanipulators for positioning the multibarrel pipette of the perfusion system (left) and patch-clamp pipette (right); (5) inverted microscope; (6) macromanipulator for multiple-channel perfusion system with tubings; (7) macromanipulator with amplifier headstage and patch-clamp pipette holder; (8) fourchannel peristaltic pump; (9) oscilloscope; (10) digital-to-analog signal converter (digitizer); (11) amplifier; (12) a monitor of PC for recording and analysis of raw data. Objects 1–8 are enclosed in Faraday’s cage

2. Low-calcium solution, free 1 μM CaCl2 (150 mM KCl, 10 mM HEPES, 1 mM EGTA and 0.752 mM CaCl2,pH ¼ 7.2): Mix 25 mL of 1.5 M KCl stock solution with 5 mL of 0.5 M HEPES stock solution, 2.5 mL of 0.1 M EGTA stock solution, and 1.88 mL of 0.1 M CaCl2 stock solution. Add water to a volume of 200 mL. Mix and adjust pH to 7.2 with potassium hydroxide (KOH), and add water to a volume of 250 mL. 3. 0.22 μm syringe filters. 4. Patch-clamp borosilicate glass capillaries, 1.5 mm O. D.  0.86 mm I.D., e.g., Harvard Apparatus GC150-10. 5. Micropipette puller, e.g., Narishige PC-10, Sutter Instruments P-1000. 6. Patch-clamp setup (Fig. 2) equipped with a phase-contrast microscope with 300–400 magnification, patch-clamp amplifier, perfusion system (consisting of a holder with a multibarrel glass tube, a peristaltic pump, and Teflon tubing).

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2.5 SingleMitoplast PCR

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1. Materials needed for mitochondria isolation (see Subheading 2.2). 2. Deoxyribonuclease I (DNase I). 3. Materials needed for mitoplasts preparation (see Subheading 2.3). 4. Isotonic solution, syringe filters, patch-clamp glass capillaries, micropipette puller, patch-clamp setup (see Subheading 2.4). 5. Primers to amplify unique human mtDNA sequence (product size 152 bp): forward 50 -CGAAAGGACAAGAGAAATAAGG-30 , reverse 50 -CTGTAAAGTTTTAAGTTTTATGCG-30 . 6. Primers to amplify human nuclear DNA (GADPH gene: product size 268 bp): forward 50 -GAAGGTGAAGGTCGGAGTC-30 , reverse 50 -GAAGATGGTGATGGGATTC-30 . 7. PCR Reaction Mix: 12.5 μL Jump Start Red Taq Master Mix, 1 μL mtDNA forward primer (10 μM), 1 μL mtDNA reverse primer (10 μM), 1 μL nucDNA forward primer (10 μM), 1 μL nucDNA reverse primer (10 μM), 0.5 μL DMSO, ~5 μL of isotonic buffer containing mitoplast (mtDNA from mitoplast serves as a template for PCR), water to the final volume of 25 μL. 8. Thermoblock. 9. Ultrasonic water bath. 10. Thermocycler.

3

Methods

3.1 Mitochondria Isolation

1. Grow cells in 2–5 culture flasks (see Note 1). 2. All the following steps should be performed on ice or with ice-cold buffers. Precool homogenizer with the pestle in an ice bath before starting the procedure. Turn on the centrifuge and preset to 4
C. Wash cells with PBS (twice is recommended) and harvest them by scraping in 3.5 mL PBS per flask followed by collecting cells in the 15 or 50 mL Falcon tube (depend on cell culture flask). 3. Spin down cells at 400–800  g for 10 min (depend on cells type). 4. Resuspend the cell pellet in 2 mL of isolation solution and transfer to the precooled Potter homogenizer with a glass pestle.

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5. Homogenize cell suspension with homogenizer on ice with 8–10 gentle strokes (for primary cultures 6–8 gentle strokes is recommended). Transfer homogenate to the Eppendorf tube. 6. Spin down cell homogenate at 9200  g for 10 min. 7. Discard the supernatant and resuspend the pellet thoroughly by gentle pipetting. Centrifuge at 750–780  g for 10 min. 8. Transfer the mitochondria containing supernatant to a new Eppendorf tube and spin down mitochondria at 9200  g for 10 min. 9. Resuspend the pelleted mitochondria in storage solution and spin down at 9200  g for 10 min. Finally, resuspend the mitochondria in 300 μL of storage solution. Alternatively, pelleted mitochondria could be resuspended directly in isolation buffer. All of the steps should be performed at 4
C. 10. For each experimental day, fresh mitochondria should be isolated unless frozen mitoplasts are to be used (see below). 3.2 Mitoplast Preparation

Protocol A. Mitoplast preparation directly in the patch-clamp recording chamber. 1. Place 2 mL of hypotonic solution in 5 cm plastic petri dish serving as a recording chamber. 2. Add 2 μL of mitochondria suspension to the middle of the dish. Observe swelling of the mitochondria and formation of mitoplasts under the phase-contrast microscope of the patch-clamp setup. Long-distance objective is required. 3. After approximately 1–5 min, add gently 0.5 mL of hypertonic solution at the periphery of the dish to restore the isotonicity of the medium. 4. Proceed to the patch-clamp experiment. Protocol B. Mitoplast preparation for subsequent use or freezing. 1. Pipette 40 μL of hypotonic solution into an Eppendorf tube. Add 1 μL of isolated mitochondria. After 1–5 min when mitochondria are swollen, add 10 μL of sucrose solution (see Note 2). Place mitoplast on ice. Add 0.2–1 μL of mitoplast into the recording chamber and proceed with the patch-clamp experiment. 2. Aliquot 2–5 μL mitoplast into Eppendorf tubes, snap freeze in liquid nitrogen, and keep at 80
C. Mitoplasts can be kept frozen for up to a few months. When needed, place tube on ice and use mitoplasts directly in patch-clamp experiments.

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3.3 Patch-Clamp Recordings

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1. Set up a patch-clamp puller and pull patch-clamp pipettes with the resistance of 10–15 MΩ when filled with isotonic solution. 2. Switch on the patch-clamp rig (Fig. 2) and set up a recording chamber grounded by the reference electrode. For the recording from mitoplast prepared according to Protocol A, fill the chamber with hypotonic solution. Alternatively, if mitoplasts were preformed according to Protocol B, fill the recording chamber with isotonic solution. 3. Mount freshly pulled pipette filled with isotonic solution in the pipette holder. Apply slight positive pressure, i.e., blow (10–20 mmHg) to the recording pipette during all manipulations prior to capturing a mitoplast (see Note 3). 4. Recognize mitoplasts added to the recording chamber by the round shape, transparency, and presence of a “cap” (Fig. 3), features that distinguish these structures from the cellular debris that is also present in the preparation. 5. Using a micromanipulator move the recording pipette towards a mitoplast and when in close proximity switch the pressure from positive (blowing) into negative (sucking) in the range of 20 to 40 mmHg. The Gigaohm seal should form within few seconds after attachment of the mitoplast to the tip of the recording pipette. After that time, release the pressure. At this stage, the membrane patch could spontaneously be formed at the tip of the pipette and the mitoplast. Observe the tip of the recording pipette under the microscope. If the whole mitoplast is still attached to the pipette, you can excise membrane patch by tapping pipette holder to induce vibrations.

Fig. 3 Phase-contrast image of a single mitoplast attached to the patch-clamp pipette. Fractions of the outer mitochondrial membrane are visible as dark “cap” on top of the swollen mitoplast. The image was taken using an inverted microscope (Olympus IX71) equipped with ColorView IIIu camera

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Fig. 4 Representative recordings of the single-channel activity of mitochondrial large-conductance calciumactivated potassium channel (mitoBKCa). (a) The activity of three channels recorded at a constant voltage of 40 mV (matrix negative). (b) The activity of one channel blocked after perfusion of the tip of the recording pipette with BKCa channel inhibitor paxilline (1 μM). Both recordings were carried out in the presence of 100 μM Ca2+. “” indicates a closed state of the channel

6. Run voltage protocol in the range of 60 mV to +60 mV or apply one voltage to check for the presence of channel activity (Fig. 4) (see Note 4). 7. Transfer the tip of the recording pipette into the opening of the multibarrel glass tube to apply channel activators or blockers. 3.4 SingleMitoplast PCR

1. Isolate mitochondria according to the protocol described above (Subheading 3.1) with the addition of DNase I (see Note 5) to the cell suspension before homogenization to destroy any DNA, which is not protected from the enzyme activity by a lipid bilayer. 2. Prepare mitoplasts according to the protocol described in Subheading 3.2. 3. Pull micropipettes with the resistance around 2 MΩ, when the pipette tip is filled with isotonic solution. The tip of the pipette should be large enough to suck in the mitoplast. 4. Install a pipette in the micromanipulator with only very the tip filled with isotonic solution and close the suction port keeping slight positive pressure. Add mitoplasts to the recording chamber filled with either hypotonic solution and form mitoplast

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Fig. 5 Outline of the single-mitoplast PCR procedure. Pick up using a pipette transparent round object that has a dark cap. Use only one pipette for an object. Carry out PCR reaction and analyze products by standard agarose gel electrophoresis. If all PCR reactions containing pipette samples have a product corresponding to mtDNA, you correctly identified all mitoplasts. As a negative control, you can suck in some solution without any visible object. As positive reaction, use purified mtDNA at low concentration

according to Subheading 3.2, Protocol A or isotonic solution to use preformed mitoplast according to Subheading 3.2, Protocol B. Using a micromanipulator move the pipette towards a selected mitoplast, switch off positive pressure in the pipette and pick out the mitoplast by application of negative pressure (suction) to the pipette. Intact mitoplast should be sucked into the pipette interior (Fig. 5). 5. Take the pipette out of the recording chamber and put its tip into the PCR tube filled with PCR Reaction Mix. Break the pipette tip which contains mitoplast, so that it falls into reaction mix. Discard the rest of the pipette. 6. Incubate closed PCR tube at 95
C for 10 min to inactivate DNAses. 7. Next, briefly sonicate PCR tube in the ultrasonic water bath to allow efficient disruption of mitoplast and release of mtDNA. 8. Place PCR tube in a thermocycler and run the appropriate PCR program (see Note 6). 9. Separate PCR products using a standard 2% agarose gel electrophoresis and analyze the data.

4

Notes 1. Several cell lines have been successfully used in this protocol. The number of flasks and growth conditions depend on the type of cells used and should be determined experimentally. The mitochondria could be also obtained from fresh animal or plant tissues. 2. The use of sucrose solution reduces the formation of ice crystals during the freezing of mitoplasts. In addition, the higher density of the final preparation in comparison to isotonic

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solution directs the flow of mitoplasts to the bottom of the recording chamber and helps at micromanipulations during patch-clamping. 3. Pressure could be applied to the interior of the pipette by mouth or by various types of manual or automatic systems. Blowing into the micropipette during manipulations prevents clogging by debris, which prevails in the mitoplast preparations. 4. Exact voltage protocol and buffer composition depend on the type of channel to be recorded. In this protocol, as an example, buffer composition and voltage protocol are provided to record the activity of mitoBKCa channels. 5. The concentration of DNase I should be determined experimentally and no product should be present when supernatant fraction lacking mitoplasts is used as a template for PCR reaction. 6. Example program for PCR: 95°C – 3 min 95°C – 30 s 57°C – 30 s

25×

72°C – 40 s 72°C – 5 min 4°C – forever

For positive control reactions, use isolated nuclear DNA (nucDNA) and mtDNA. Prepare negative controls without mtDNA and nucDNA. Use the same primer sets as for singlemitoplasts PCR.

Acknowledgments This work was supported in part by grants from the National Science Center: 2016/21/B/NZ1/02769 to P.B., 2020/36/T/ NZ1/00116 to R.P.K., 2018/31/N/NZ1/00928 to A.W., and 2015/19/B/NZ1/02794 to P.K. References 1. Goodman MB, Lindsay TH, Lockery SR, Richmond JE (2012) Electrophysiological methods for Caenorhabditis elegans neurobiology. Methods Cell Biol 107:409–436. https:// doi.org/10.1016/B978-0-12-394620-1. 00014-X

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Patch-Clamp Technique for the Inner Mitochondrial Membrane 3. Neher E, Sakmann B (1976) Single-channel currents recorded from membrane of denervated frog muscle fibres. Nature 260 (5554):799–802. https://doi.org/10.1038/ 260799a0 4. Conforti L (2012) Chapter 20 - patch-clamp techniques. In: Sperelakis N (ed) Cell physiology source book, 4th edn. Academic Press, San Diego, pp 369–381 5. Hamill OP, Marty A, Neher E, Sakmann B, Sigworth FJ (1981) Improved patch-clamp techniques for high-resolution current recording from cells and cell-free membrane patches. Pflugers Arch 391(2):85–100. https://doi. org/10.1007/bf00656997 6. Pallotta BS, Magleby KL, Barrett JN (1981) Single channel recordings of Ca2+-activated K+ currents in rat muscle cell culture. Nature 293(5832):471–474. https://doi.org/10. 1038/293471a0 7. Siemen D, Loupatatzis C, Borecky J, Gulbins E, Lang F (1999) Ca2+-activated K channel of the BK-type in the inner mitochondrial membrane of a human glioma cell line. Biochem Biophys Res Commun 257 (2):549–554. https://doi.org/10.1006/bbrc. 1999.0496 8. Bednarczyk P, Koziel A, Jarmuszkiewicz W, Szewczyk A (2013) Large-conductance Ca(2 + )-activated potassium channel in mitochondria of endothelial EA.hy926 cells. Am J Physiol Heart Circ Physiol 304(11): H1415–H1427. https://doi.org/10.1152/ ajpheart.00976.2012 9. Chen CC, Cang C, Fenske S, Butz E, Chao YK, Biel M, Ren D, Wahl-Schott C, Grimm C (2017) Patch-clamp technique to characterize ion channels in enlarged individual endolysosomes. Nat Protoc 12(8):1639–1658. https:// doi.org/10.1038/nprot.2017.036 10. Cao Q, Zhong XZ, Zou Y, Zhang Z, Toro L, Dong XP (2015) BK channels alleviate lysosomal storage diseases by providing positive feedback regulation of lysosomal Ca2+ release. Dev Cell 33(4):427–441. https://doi.org/10. 1016/j.devcel.2015.04.010 11. Li B, Jie W, Huang L, Wei P, Li S, Luo Z, Friedman AK, Meredith AL, Han MH, Zhu XH, Gao TM (2014) Nuclear BK channels regulate gene expression via the control of nuclear calcium signaling. Nat Neurosci 17 (8):1055–1063. https://doi.org/10.1038/ nn.3744 12. Frankenreiter S, Bednarczyk P, Kniess A, Bork NI, Straubinger J, Koprowski P, Wrzosek A, Mohr E, Logan A, Murphy MP, Gawaz M, Krieg T, Szewczyk A, Nikolaev VO, Ruth P, Lukowski R (2017) cGMP-elevating

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compounds and ischemic conditioning provide Cardioprotection against ischemia and reperfusion injury via cardiomyocyte-specific BK channels. Circulation 136(24):2337–2355. https://doi.org/10.1161/ CIRCULATIONAHA.117.028723 13. Bednarczyk P, Wieckowski MR, Broszkiewicz M, Skowronek K, Siemen D, Szewczyk A (2013) Putative structural and functional coupling of the mitochondrial BKCa Channel to the respiratory chain. PLoS One 8(6):e68125. https://doi.org/10.1371/ journal.pone.0068125 14. Bednarczyk P, Kicinska A, Laskowski M, Kulawiak B, Kampa R, Walewska A, Krajewska M, Jarmuszkiewicz W, Szewczyk A (2018) Evidence for a mitochondrial ATP-regulated potassium channel in human dermal fibroblasts. Biochim Biophys Acta Bioenerg 1859(5):309–318. https://doi.org/10. 1016/j.bbabio.2018.02.005 15. Toczylowska-Maminska R, Olszewska A, Laskowski M, Bednarczyk P, Skowronek K, Szewczyk A (2014) Potassium channel in the mitochondria of human keratinocytes. J Invest Dermatol 134(3):764–772. https://doi.org/ 10.1038/jid.2013.422 16. Gururaja Rao S, Bednarczyk P, Towheed A, Shah K, Karekar P, Ponnalagu D, Jensen HN, Addya S, Reyes BAS, Van Bockstaele EJ, Szewczyk A, Wallace DC, Singh H (2019) BKCa (Slo) channel regulates mitochondrial function and lifespan in Drosophila melanogaster. Cell 8(9):945. https://doi.org/10.3390/ cells8090945 17. Balderas E, Zhang J, Stefani E, Toro L (2015) Mitochondrial BKCa channel. Front Physiol 6:104. https://doi.org/10.3389/fphys.2015. 00104 18. Laskowski M, Augustynek B, Bednarczyk P, Zochowska M, Kalisz J, O’Rourke B, Szewczyk A, Kulawiak B (2019) Single-channel properties of the ROMK-pore-forming subunit of the mitochondrial ATP-sensitive potassium channel. Int J Mol Sci 20(21):5323. https://doi.org/10.3390/ijms20215323 19. Szabo´ I, Zoratti M (1992) The mitochondrial megachannel is the permeability transition pore. J Bioenerg Biomembr 24(1):111–117. https://doi.org/10.1007/bf00769537 20. Urbani A, Giorgio V, Carrer A et al (2019) Purified F-ATP synthase forms a Ca2+-dependent high-conductance channel matching the mitochondrial permeability transition pore. Nat Commun 10(1):4341. https://doi.org/ 10.1038/s41467-019-12331-1 21. Toczyłowska-Mamin´ska R, Olszewska A, Laskowski M, Bednarczyk P, Skowronek K,

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Szewczyk A (2014) Potassium channel in the mitochondria of human keratinocytes. J Invest Dermatol 134(3):764–772. https://doi.org/ 10.1038/jid.2013.422 22. Szabo I, Bock J, Jekle A, Soddemann M, Adams C, Lang F, Zoratti M, Gulbins E (2005) A novel potassium channel in lymphocyte mitochondria. J Biol Chem 280 (13):12790–12798. https://doi.org/10. 1074/jbc.M413548200 23. Bednarczyk P, Kowalczyk JE, Beresewicz E, Dolowy K, Szewczyk A, Zablocka B (2010) Identification of a voltage-gated potassium channel in gerbil hippocampal mitochondria. Biochem Biophys Res Comm 397 (3):614–620. https://doi.org/10.1016/j. bbrc.2010.06.011 24. De Marchi U, Sassi N, Fioretti B, Catacuzzeno L, Cereghetti GM, Szabo I, Zoratti M (2009) Intermediate conductance Ca2+activated potassium channel (KCa3.1) in the inner mitochondrial membrane of human colon cancer cells. Cell Calcium 45 (5):509–516. https://doi.org/10.1016/j. ceca.2009.03.014 25. Walewska A, Kulawiak B, Szewczyk A, Koprowski P (2018) Mechanosensitivity of mitochondrial large-conductance calcium-activated potassium channels. Biochim Biophys Acta Bioenerg 1859(9):797–805. https://doi. org/10.1016/j.bbabio.2018.05.006 26. Szabo I, Zoratti M (2014) Mitochondrial channels: ion fluxes and more. Physiol Rev 94

(2):519–608. https://doi.org/10.1152/ physrev.00021.2013 27. Testai L, Rapposelli S, Martelli A, Breschi MC, Calderone V (2015) Mitochondrial potassium channels as pharmacological target for cardioprotective drugs. Med Res Rev 35 (3):520–553. https://doi.org/10.1002/med. 21332 28. Kampa RP, Kicinska A, Jarmuszkiewicz W, Pasikowska-Piwko M, Dolegowska B, Debowska R, Szewczyk A, Bednarczyk P (2019) Naringenin as an opener of mitochondrial potassium channels in dermal fibroblasts. Exp Dermatol 28(5):543–550. https://doi. org/10.1111/exd.13903 29. De Marchi U, Checchetto V, Zanetti M et al (2010) ATP-sensitive cation-channel in wheat (Triticum durum Desf.): identification and characterization of a plant mitochondrial channel by patch-clamp. Cell Physiol Biochem 26 (6):975–982. https://doi.org/10.1159/ 000324010 30. Dolga AM, Netter MF, Perocchi F et al (2013) Mitochondrial small conductance SK2 channels prevent glutamate-induced oxytosis and mitochondrial dysfunction. J Biol Chem 288 (15):10792–10804. https://doi.org/10. 1074/jbc.M113.453522 31. Kicinska A, Augustynek B, Kulawiak B, Jarmuszkiewicz W, Szewczyk A, Bednarczyk P (2016) A large-conductance calcium-regulated K+ channel in human dermal fibroblast mitochondria. Biochem J 473(23):4457–4471. https://doi.org/10.1042/BCJ20160732

Chapter 19 Assessment of Mitochondrial Protein Glutathionylation as Signaling for CO Pathway Ana S. Almeida, Cla´udia Figueiredo-Pereira, and Helena L. A. Vieira Abstract Protein glutathionylation is a posttranslational process that regulates protein function in response to redox cellular changes. Furthermore, carbon monoxide-induced cellular pathways involve reactive oxygen species (ROS) signaling and mitochondrial protein glutathionylation. Herein, it is described as a technique to assess mitochondrial glutathionylation due to low concentrations of CO exposure. Mitochondria are isolated from cell culture or tissue, followed by an immunoprecipitation assay, which allows the capture of any glutathionylated mitochondrial protein using a specific antibody coupled to a solid matrix that binds to glutathione antigen. The precipitated protein is further identified and quantified by immunoblotting analysis. Key words Glutathionylation, Carbon monoxide, Mitochondria, Glutathione, Immunoprecipitation

1

Introduction Protein glutathionylation is a posttranslation mechanism involved in redox response, which consists on the regulated formation of mixed disulfides between protein thiol and glutathione disulfide (GSSG) due to glutathione redox changes [1, 2]. The progressive glutathionylation of key proteins can be a molecular switch by which cells respond in an immediate and reversible fashion to oxidative stress by protecting cysteine residues [1, 2]. Still, it can alter protein activity, presenting a physiological signaling function, in the same way as the phosphorylation process. Mitochondria are key organelles for reactive oxygen species (ROS) generation, thus protein glutathionylation can be crucial for protecting mitochondria from this source of oxidative damage. Furthermore, changes in the redox state of mitochondrial proteins through thiol modifications can transduce redox signals and modulate mitochondrial activity [3].

Volkmar Weissig and Marvin Edeas (eds.), Mitochondrial Medicine: Volume 2: Assessing Mitochondria, Methods in Molecular Biology, vol. 2276, https://doi.org/10.1007/978-1-0716-1266-8_19, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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Several examples of mitochondrial protein glutathionylation or de-glutathionylation are described in the literature: (1) glutathionylation of complex II decreases after myocardial ischemia, limiting its electron transfer activity [4]; (2) glutathionylation of specific cysteine residues (C136 and C155) regulates activity of carnitine/ acylcarnitine carrier [5]; (3) glutathionylation of complex I protects against oxidative stress and is mediated by thiyl radical [6]; (4) ANT (ATP/ADP translocator) glutathionylation prevents cell death by improving its activity and limiting mitochondrial membrane permeabilization [7]; and (5) degradation of mitochondrial thymidine kinase-2 is modulated by glutathionylation [8]. Carbon monoxide (CO) is endogenously produced through the cleavage of heme group by heme oxygenase activity (HO), presenting several biological properties: anti-inflammatory, antiproliferative, and antiapoptotic, for review [9, 10]. Cell redox responses, such as ROS signaling, appear to be tightly involved in CO-induced pathways [11], namely in: anti-inflammation in macrophages [12]; cytoprotection in cardiomyocytes [13]; in neurons [14] or in astrocytes [7]; cardioprotection [15]; and antiproliferation in airway smooth muscle cells [16]. CO also modulates levels of oxidized glutathione, signaling through mitochondrial protein glutathionylation [7]. Herein a method for assessing CO-induced mitochondrial protein glutathionylation is described, in particular glutathionylation of the mitochondrial inner membrane protein ANT (ATP/ADP translocator). ANT presents critical thiol groups in cysteine residues (cysteine 56, 159, and 256), which can be oxidized and/or derivatized in order to modulate the pore-forming activity of ANT and cell death control [17, 18]. The described protocol can be used with other mitochondrial proteins. For assessing CO-induced mitochondrial protein glutathionylation, two different sources of mitochondria are used from cell culture (cell lines or primary cultures of astrocytes) and brain cortex.

2

Materials Prepare all solutions using ultrapure water (prepared by purifying deionized water to attain a sensitivity of 18 MΩ cm at 25  C) and analytical grade reagents. Prepare and store all the reagents at 4  C (unless indicated otherwise).

2.1 Mitochondria Isolation from Cell Culture

1. Phosphate buffer saline (PBS): 1.54 M NaCl, 34 mM Na2HPO4, 20 mM KH2PO4, pH 9.4. In 900 mL of water, dissolve 90 g of NaCl, 4.83 g of Na2PO4, and 2.72 g of KH2PO4. Mix and adjust pH. Make up to 1 L with water.

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2. Hypotonic buffer: 0.15 mM MgCl2, 10 mM KCl, 10 mM TrisHCl, pH 7.6. Weigh 1.43 mg of MgCl2, 74.56 mg of KCl, and 156.6 mg of Tris-HCl. Add water to a volume of 90 mL. Mix and adjust pH. Make up to 100 mL with water. Store at 4  C. 3. Homogenate buffer (2): 0.6 M sucrose, 10 mM TES, 0.4 mM EGTA, pH 7.2. Weigh 41.07 g of sucrose, 458.5 mg of TES, and 30.43 mg of EGTA. Add water to a volume of 190 mL. Mix and adjust pH. Make up to 200 mL with water. Store at 4  C. 4. Homogenate buffer (1): Dilute 1:2 homogenate buffer (2) in water. 2.2 Mitochondria Isolation from Brain Cortex

1. MIB buffer: 225 mM mannitol, 75 mM sucrose, 1 mM EGTA, 5 mM HEPES, pH 7.4. Weigh 10.25 g of mannitol, 6.42 g of sucrose, 75.09 mg of EGTA, and 279.88 mg of HEPES. Add water to a volume of 220 mL. Mix and increase pH until 8 in order to dissolve EGTA. Adjust pH to 7.4, make up to 250 mL and store at 4  C. 2. Brain mitochondrial buffer (complex I): 125 mM KCl, 2 mM K2HPO4, 1 mM MgCl2, 1 μM EGTA, 20 mM Tris–HCl, 5 mM glutamate, 5 mM malate, pH 7.2. Add to 220 mL, 2.33 g of KCl, 73.6 mg of K2HPO4, 50.8 mg of MgCl2, 25 μL of EGTA, 10 mM stock solution, 788 mg of tris-HCl, 233.92 mg of glutamate, and 167.63 mg of malate. Mix and adjust pH to 7.2 at 37  C. Make up to 250 mL with water and store at 4  C (see Note 1). 3. Percoll gradient: Dilute stock solution of Percoll in MIB buffer to obtain final Percoll concentrations of 15%, 24%, and 40% (v/v). Mix 0.75 mL of Percoll stock solution with 4.25 mL of MIB buffer, for 15% concentrated solution. In order to prepare the 24% and the 40% concentrated solutions, pipette 1.2 mL of Percoll and 3.8 mL of MIB and 2 mL of Percoll and 3 mL of MIB, respectively.

2.3

CO Treatment

1. CORM-A1 solution: Prepare a 5 mM solution of CORM-A1 (Sigma-Aldrich) in water. Filtrate the solution with 0.22 μM filter, aliquot, and store at 20  C. For each use, an aliquot should be thawed and rapidly added into the culture. 2. CO gas solution: Saturate PBS by bubbling 100% of CO gas for 30 min to produce 10 3 M stock solution. Hundred percent CO was purchased as compressed gas (Linde, Germany). Fresh stock solutions of CO gas should be prepared each day and sealed carefully (see Note 2).

2.4 Immunoprecipitation

1. 10% Triton X-100: Dilute 10 μL of Triton X-100 in 90 μL of water. 2. PBS (see Subheading 2.1, item 1).

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3. Loading buffer: 10% (v/v) glycerol; 10 mM DTT; 0.005% (w/v) Bromophenol Blue. To prepare 20 mL, weigh 30 mg of DTT and 0.001 mg of Bromophenol Blue. Solubilize both in 18 mL of water. Add 2 mL of glycerol, mix, and store at 4  C. 2.5

Immunoblotting

1. T-TBS buffer: 0.25 M Tris-HCL; 0.75 M NaCl. Weigh 7.88 g of Tris-HCl and 8.76 g of NaCl. Solubilize in 1 L of water. 2. Blocking buffer: T-TBS with 5% (w/v) milk. Weigh 5 g of milk and dilute in 100 mL of T-TBS buffer. 3. Running buffer (10): 0.25 M Tris, 1.92 M glycine, 35 mM SDS. Weigh 30 g of Tris, 144 g of glycine, and 10 g of SDS. Solubilize all the components in 1 L of water. 4. Running buffer (1): Dilute 100 mL of running buffer (10) in 900 mL of water. 5. Transfer buffer: Running buffer with 20% (v/v) of methanol. Add 200 mL of methanol to 800 mL of running buffer (1).

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Methods All the steps should be carried out at 4  C, unless indicated otherwise.

3.1

CO Treatment

1. Cell culture: Add CO gas solution to culture medium, to a final concentration of 50–100 μM. If you are using CORM-A1 solution, add it to the culture medium to a final concentration of 12.5–25 μM (see Note 3). At the required time point after CO exposure, proceed to mitochondrial isolation from cell culture (Subheading 3.2). 2. Tissue: After isolation from tissue, add CO gas solution (or CORM-A1 solution) directly to isolated mitochondria. Incubate mitochondria at 37  C and proceed to immunoprecipitation at the different time points after CO exposure (Subheading 3.4).

3.2 Mitochondria Isolation from Cell Culture

Adapted from Vieira et al. [19]. 1. Inoculate 175 cm2 T-flasks with primary cell culture of astrocytes or a cell line culture. 2. Maintain cells in culture until achieve the confluence. 3. Wash cell culture (175 cm2 T-flask) with 5 mL PBS at 4  C, in order to eliminate any serum. 4. Trypsinize the cells by adding 5 mL trypsin, followed by 5 min incubation at 37  C.

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5. Collect the cells in 10 mL of culture medium and centrifuge at 200  g for 10 min at 4  C. 6. Discard supernatant, wash the cells with 10 mL of PBS, and centrifuge at 200  g for 10 min at 4  C. 7. Discard supernatant, add 3.5 mL of hypotonic buffer, and incubate at 4  C during 5 min. 8. Add an equal volume (3.5 mL) of homogenization buffer twice concentrated (2) to a final volume of 7 mL. 9. Homogenize samples with a Dounce glass homogenizer at 4  C (see Note 4). 10. Remove the sample to a 50 mL tube, wash glass homogenizer with homogenization buffer (1) and add it to the sample. 11. Centrifuge cell extracts at 900  g for 10 min at 4  C (to remove nuclei and unbroken cells). 12. Remove supernatant to a clean tube and centrifuge at 10,000  g for 10 min at 4  C. 13. Resuspend mitochondrial pellet in 100 μL of homogenization buffer (1) and quantify the total amount of protein. 3.3 Mitochondria Isolation from Brain Tissue

The non-synaptic mitochondria isolation protocol was adapted by Queiroga et al. [7] from Kristia´n and colleagues and Sims [20–22]. 1. Sacrifice one male Wistar rat (see Notes 5 and 6) by cervical dislocation. 2. Remove cerebellum and underlying structures (only cortex is used). Isolate cortex 1 min after death. 3. Wash the cortex in MIB in a petri dish and cut it in small pieces. 4. Homogenize cortex manually ten times with tissue homogenizer and centrifuge the tissue extract at 1300  g for 3 min at 4  C. 5. Keep the supernatant, resuspend the pellet, and recentrifuge at 1300  g for 3 min at 4  C. 6. Pool together the two supernatant and centrifuge at 21,000  g for 10 min at 4  C in ultracentrifugation tubes. 7. Resuspend pellet in 3.5 mL of 15% Percoll solution and add it over the gradient (Fig. 1). 8. Centrifuge the gradient at 31,700  g for 8 min at 4  C. 9. Remove mitochondrial fraction from layer 24% and 40% with a syringe. Add MIB buffer to mitochondrial fraction to wash Percoll out by centrifugation at 16,700  g for 10 min at 4  C. 10. Resuspend pellet in 10 mL of MIB buffer supplemented with BSA 5 mg/mL and centrifuge at 6800  g for 10 min at 4  C.

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Fig. 1 Percoll gradient schema. Pipet 1.7 mL of 40% Percoll solution followed by 3.7 mL 24% Percoll and, finally, 3.5 mL 15% Percoll. Mitochondrial content will be found between 24% and 40% fractions of the gradient after centrifugation

11. Remove supernatant and resuspend mitochondria in 100 μL of MIB without EGTA. 12. Quantify total amount of protein. 3.4 Immunoprecipitation of Proteins in Isolated Mitochondria

1. Prepare microtubes with 50–100 μg of isolated mitochondria into 100 μL of homogenization buffer (1). 2. Permeabilize mitochondria by adding 5 μL of Triton X-100 at 10% (final concentration 0.5%). 3. Incubate mitochondria with 20 μL of anti-GSH (ViroGen, USA) during 1 h 30 min at 37  C. 4. Perform the immunoprecipitation by adding 15 μL of Protein A/G PLUS-Agarose beads (Santa Cruz Biotechnology, UK) and incubate them for 30 min at 37  C with extremely gentle shaking. 5. Discard the supernatant after 10 min of centrifugation at 10,000  g. Wash the pellet with PBS, followed by centrifugation at 500  g for 10 min, five times. 6. Resuspend the pellet (proteins attached to the beads) in 40 μL of loading buffer and freeze at 20  C for further immunoblot analysis.

3.5

Immunoblotting

1. Load the samples on a 12% SDS-PAGE gel in order to separate the proteins under reducing electrophoresis conditions. Run the electrophoresis at fixed voltage of 135–150 V during 30 min. 2. Electrically transfer the proteins to a nitrocellulose membrane (fixed 500 mA for 1 h). 3. Incubate the membrane at RT for 1 h with blocking buffer. 4. Dilute 1:1000 the primary antibody (anti-ANT, Abcam, UK) in blocking buffer and incubate the membrane for 2 h at RT. 5. Wash the membrane with T-TBS three times during 10 min.

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Fig. 2 Example of immunoblotting film image obtained after immunoprecipitation of glutathionylated proteins (α-GSH) of a mitochondrial isolate of astrocytes. The blot was incubated with primary antibody against ANT, which is the target glutathionylated mitochondrial protein

6. Incubate the blot with HRP-labeled anti-mouse IgG antibody (Abcam, UK), 1:5000 diluted in blocking buffer, for 1 h at RT. 7. Wash the membrane with T-TBS three times during 10 min. 8. Develop the blot using ECL (enhanced chemiluminescence) detection system (Fig. 2). 9. The area and intensity of bands (Fig. 2) can be quantified by densitometry analysis and presented as a percentage relative to control (100%) without any treatment. In this example, it can be observed that CO treatment increased the amount of glutathionylated ANT (30 kDa), compared to control.

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Notes 1. EGTA’s concentration can go up to 15 μM, in order to obtain more consistent results. 2. The concentration of CO in solution was determined spectrophotometrically by measuring the conversion of deoxymyoglobin to carbon monoxymyoglobin [23]. 3. Homogenize samples with the Dounce glass homogenizer 25 times with the loose-fitted pestle and then more 25 times with the tight-fitted pestle at 4  C. 4. Use CO saturated solution immediately after opening the vial, about 2 or 3 min. CO releases very easily, changing its final concentration. 5. Animals are allowed water and food ad libitum for the 24 h before death. 6. From one male Wistar rat (300–350 g) one might obtain 5 mg of non-synaptic mitochondria.

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Acknowledgments This work was supported by the Portuguese Fundac¸˜ao para a Cieˆncia e Tecnologia (FCT) for the grants FCT-ANR/ NEUNMC/0022/2012 and UID/Multi/04462/2013, I&D 2015-2020 iNOVA4Health – Programme in Translacional Medicine; and for ASA’s SFRH/BD/78440/2011 and CFP’s SFRH/ BD/106057/2015 fellowships. References 1. Gallogly MM, Mieyal JJ (2007) Mechanisms of reversible protein glutathionylation in redox signaling and oxidative stress. Curr Opin Pharmacol 7:381–391 2. Popov D (2014) Protein S-glutathionylation: from current basics to targeted modifications. Arch Physiol Biochem 120:123–130 3. Mailloux RJ, Treberg JR (2016) Protein S-glutathionlyation links energy metabolism to redox signaling in mitochondria. Redox Biol 8:110–118. https://doi.org/10.1016/j. redox.2015.12.010 4. Chen YR, Chen CL, Pfeiffer DR, Zweier JL (2007) Mitochondrial complex II in the postischemic heart. J Biol Chem 282:32640 5. Giangregorio N, Palmieri F, Indiveri C (2013) Glutathione controls the redox state of the mitochondrial carnitine/acylcarnitine carrier Cys residues by glutathionylation. Biochim Biophys Acta Gen Sub 1830:5299–5304 6. Kang PT, Zhang L, Chen CL, Chen J, Green KB, Chen YR (2012) Protein thiyl radical mediates S-glutathionylation of complex I. Free Radic Biol Med 53:962–973 7. Queiroga CSF, Almeida AS, Martel C, Brenner C, Alves PM, Vieira HLA (2010) Glutathionylation of adenine nucleotide translocase induced by carbon monoxide prevents mitochondrial membrane permeabilization and apoptosis. J Biol Chem 285:17077–17088. https://doi.org/10. 1074/jbc.M109.065052 8. Sun R, Eriksson S, Wang L (2012) Oxidative stress induced S-glutathionylation and proteolytic degradation of mitochondrial thymidine kinase 2. J Biol Chem 287:24304–24312 9. Ryter SW, Choi AMK (2016) Targeting heme oxygenase-1 and carbon monoxide for therapeutic modulation of inflammation. Transl Res 167:7–34 10. Figueiredo-Pereira C, Dias-Pedroso D, Soares NL, Vieira HLA (2020) CO-mediated cytoprotection is dependent on cell metabolism modulation. Redox Biol 32:101470

11. Almeida AS, Figueiredo-Pereira C, Vieira HLA (2015) Carbon monoxide and mitochondriamodulation of cell metabolism, redox response and cell death. Front Physiol 6:33 12. Zuckerbraun BS, Chin BY, Bilban M, de Costa d’Avila J et al (2007) Carbon monoxide signals via inhibition of cytochrome c oxidase and generation of mitochondrial reactive oxygen species. FASEB J 21:1099–1106 13. Suliman HB, Carraway MS, Ali AS, Reynolds CM, Welty-wolf KE, Piantadosi CA (2007) The CO / HO system reverses inhibition of mitochondrial biogenesis and prevents murine doxorubicin cardiomyopathy. J Clin Invest 117:3730–3741 14. Almeida AS, Soares NL, Vieira M, Gramsbergen JB, Vieira HLA (2016) Carbon monoxide releasing molecule-A1 (CORM-A1) improves neurogenesis: increase of neuronal differentiation yield by preventing cell death. PLoS One 11:e0154781 15. Scragg JL, Dallas ML, Wilkinson JA, Varadi G, Peers C (2008) Carbon monoxide inhibits L-type Ca2+ channels via redox modulation of key cysteine residues by mitochondrial reactive oxygen species. J Biol Chem 283:24412–24419 16. Taille´ C, El-Benna J, Lanone S, Boczkowski J, Motterlini R (2005) Mitochondrial respiratory chain and NAD(P)H oxidase are targets for the antiproliferative effect of carbon monoxide in human airway smooth muscle. J Biol Chem 280:25350–25360 17. Costantini P, Chernyak BV, Petronilli V, Bernardi P (1996) Modulation of the mitochondrial permeability transition pore by pyridine nucleotides and dithiol oxidation at two separate sites. J Biol Chem 271:6746–6751 18. Costantini P, Belzacq A-SS, Vieira HLA, Larochette N et al (2000) Oxidation of a critical thiol residue of the adenine nucleotide translocator enforces Bcl-2-independent permeability transition pore opening and apoptosis.

Mitochondrial Protein Glutathionylation Oncogene 19:307–314. https://doi.org/10. 1038/sj.onc.1203299 19. Vieira HLA, Boya P, Cohen I, Hamel CE et al (2002) Cell permeable BH3-peptides overcome the cytoprotective effect of Bcl-2 and Bcl-X(L). Oncogene 21:1963–1977 20. Kristian T, Fiskum G (2004) A fluorescencebased technique for screening compounds that protect against damage to brain mitochondria. Brain Res Protoc 13:176–182 21. Kristia´n T, Gertsch J, Bates TE, Siesjo¨ BK (2000) Characteristics of the calcium-triggered mitochondrial permeability transition in

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nonsynaptic brain mitochondria: effect of cyclosporin A and ubiquinone O. J Neurochem 74:1999–2009 22. Sims NR (1990) Rapid isolation of metabolically active mitochondria from rat brain and subregions using percoll density gradient centrifugation. J Neurochem 55:698–707 23. Motterlini R, Clark JE, Foresti R, Sarathchandra P, Mann BE, Green CJ (2002) Carbon monoxide-releasing molecules: characterization of biochemical and vascular activities. Circ Res 90:e17–e24

Chapter 20 3D Optical Cryo-Imaging Method: A Novel Approach to Quantify Renal Mitochondrial Bioenergetics Dysfunction Shima Mehrvar, Amadou K. S. Camara, and Mahsa Ranji Abstract Mitochondrial dysfunction contributes to various injuries and diseases. A mechanistic understanding of how dysfunctional mitochondria modulates metabolism is of paramount importance. Three-dimensional (3D) optical cryo-imager is a custom-designed device that can quantify the volumetric bioenergetics of organs in small animal models. The instrument captures the autofluorescence of bioenergetics indices (NADH and FAD) from tissues at cryogenic temperature. The quantified redox ratio (NADH/FAD) is used as an optical indicator of mitochondrial redox state. Key words Mitochondria, Redox state, Optical imaging, Bioenergetics, Fluorescence imaging

1

Introduction

1.1 Mitochondrial Dysfunction

Mitochondria play central roles in various key cellular processes such as ATP production (bioenergetics), the regulation of calcium homeostasis, cell death pathways, and also act as both source and scavenger of reactive oxygen species (ROS). Mitochondrial dysfunction is manifested in the derangement of any of these physiological processes. Thus, mitochondrial dysfunction inevitably leads to cellular damage, which has been linked to various diseases, such as Parkinson [1], obesity [2], Alzheimer [3], and cancer [4]. This connection to mitochondria suggests that various therapeutic interventions targeting mitochondria could lead to protection against cellular injury [3, 5–8]. Multiple approaches have been developed to assess mitochondrial dysfunction. For instance, mitochondrial function and dysfunction can be determined with isolated mitochondrial assays such as mitochondrial respiratory control [9]. In an intact cell assay, cell respiratory control can provide the rate of ATP production, the rate

Volkmar Weissig and Marvin Edeas (eds.), Mitochondrial Medicine: Volume 2: Assessing Mitochondria, Methods in Molecular Biology, vol. 2276, https://doi.org/10.1007/978-1-0716-1266-8_20, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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of proton leak, the coupling efficiency, the maximum respiratory rate, the respiratory control ratio, and the spare respiratory capacity [10]. 31Phosphorus nuclear magnetic resonance spectroscopy has also given insights into the bioenergetics state in vivo by providing an indicator of mitochondrial oxidative phosphorylation [11]. 1.2 Optical Metabolic Imaging

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Living tissues can be studied using optical imaging. A wide range of optical imaging techniques can be utilized to visualize tissue morphologies or to assess metabolic processes [12]. Optical metabolic imaging of tissue is classified into three main categories [13]: oxygenation imaging, fluorescence imaging of exogenous markers, and tissue autofluorescence imaging of the mitochondrial metabolites. Oxygenation imaging is performed by measuring blood oxygenation, for example, muscle blood oxygen consumption can be measured in vivo using diffuse optical imaging and spectroscopy [14]. Tissue oxygen consumption correlates with cytochrome oxidase levels in the tissues [15]. Therefore, whole-body respiration can be correlated with the overall rate of mitochondrial electron transport. However, the inference of mitochondrial dysfunction from changes in oxygen consumption is difficult due to the complexity of the whole organism and tissues [10]. Fluorescence imaging of exogenous markers allows tracking of cellular metabolic processes by using various metabolic markers, such as MitoSOX [16]. However, autofluorescence imaging of redox ratios can provide mitochondrial redox state of the tissue without the need for exogenous tagging. Two mitochondrial bioenergetics markers, namely, reduced nicotinamide adenine dinucleotide (NADH) and oxidized flavin adenine dinucleotide (FAD), are autofluorescents. NADH and FAD can be measured by fluorescence metabolic imaging techniques pioneered by Chance et al. [17]. 3D optical cryo-imaging provides a 3D measurement of NADH and FAD. The cryogenic temperature enables us to have higher quantum yield and preserves the metabolic state of the tissue. The ratio of these fluorophores (NADH/FAD), the redox ratio, provides a quantitative marker of the mitochondrial redox state of tissues. This work describes how 3D optical cryo-imaging can be utilized to quantitatively assess mitochondrial redox state, enabling us to determine altered mitochondrial metabolism in tissues, particularly in disease state.

Materials The 3D fluorescence cryo-imager was custom-designed in the Biophotonics Laboratory at the University of WisconsinMilwaukee. A computer with a graphical user interface (GUI) runs image acquisition, and the cryo-images are processed with a

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Fig. 1 A schematic view of 3D optical Cryo-imager. Major components of the system are labeled (reproduced from ref. 19 with permission from Springer)

written code (see Subheading 3). Figure 1 shows a schematic view of the system describing the optical and mechanical components of the instrument. 2.1 Optical Components

The optical components are located outside of the freezer and are the parts of two main light paths, namely the excitation light path and the emission light path. 1. The excitation light path (Fig. 2) includes: (a) Mercury arc lamp (see Note 1) as the light source. (b) Cold mirror. (c) Motorized filter wheel referred to the excitation filter wheel. (d) Controller for the filter wheel. (e) Band-pass optical filters for the selective excitation of fluorophores in the tissue (see Note 2). (f) Reflective mirror for air-guide of the light to the tissue. 2. The emission light path (Fig. 3) includes: (a) Motorized filter wheel named as emission filter wheel. (b) Controller for the filter wheel.

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Fig. 2 A schematic view of excitation path for the optical design of 3D optical Cryo-imager. Major components of the system are (1) Mercury-arc lamp, (2) Cold mirror, (3) Excitation filter wheel, and (4) Reflecting mirror

Fig. 3 A schematic view of two designs for the emission path of 3D optical Cryo-imager. (a) the filter wheel is in front of the zoom lens and camera. (b) the filter wheel is between the zoom lens and camera. Major components of the emission path are (1) Emission filter wheel, (2) Zoom lens, and (3) CCD Camera

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(c) Band-pass optical filters for the selective collection of emitted autofluorescence from the tissue (see Note 2). (d) Zoom lens. (e) Image recordings system, charge-coupled device (CCD) camera (see Note 3). 3. The emission path of the optical design can be arranged in two formats: (a) Design A: This is the most common design (Fig. 3a) that we use to ensure a large field of view, up to 40 mm (see Note 4). The filter wheel comes in front of the lens, and there is no space between the lens and camera. This allowed us to use comparably large (50 mm) optical filters and increase the efficiency of fluorescence light collection resulting to higher image contrast. (b) Design B: The emission filter wheel can come between the lens and the camera (Fig. 3b). Then, the camera and lens can get closer to the tissue with working distance as low as 100 mm, for capturing higher resolution images (see Note 5). We are working on optimizing the optical design that can increase the resolution of the images and the efficacy of light collection. 2.2 Mechanical Components

The mechanical part of the instrument works as an automotive cryo-microtome system to sequentially slice the tissue. The mechanical parts include: 1. Freezer ( 40  C). 2. Microtome blade. 3. Metallic sample holder. 4. AC motor for driving the blade (see Note 6). 5. Stepper motor for the movement of sample carrier. 6. Sensors for detecting the blade location and safety (see Note 7). 7. Sample holder. 8. Motorized XY scanning stage (used in the case of raster scanning see Note 8).

2.3 Sample Preparation Requirements

Sample preparation includes sample freezing, black mounting medium (BMM) preparation, and sample embedding. 1. Supplies needed for sample freezing: (a) Isopentane (2 methyl butane). (b) Liquid nitrogen. (c)

80  C freezer.

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2. Supplies needed for BMM preparation: (a) Polyvinyl alcohol. (b) Distilled water. (c) India ink or carbon black powder.

3

Methods

3.1 Black Mounting Medium (BMM) Preparation

1. Use a reliable fluorescent-free mounting medium. 2. Dilute polyvinyl alcohol and distilled water in a beaker with a ratio of 1:2 and placed on medium heat for 1 h. 3. Gradually add carbon black powder or India ink until there is no gray appearance. 4. Cool the BMM in a refrigerator before use.

3.2 Kidney Sample Preparation

1. On the day of the tissue harvest, deeply anesthetize the animals. Before tissue harvesting, flush the blood by infusing cold isotonic saline via a catheter placed in the aorta (see Note 9). 2. After complete flushing, remove the kidneys quickly and drop them into liquid nitrogen chilled isopentane. After 2 min in the cooled isopentane, move the kidney to liquid nitrogen and then store at 80  C freezer. 3. One day before initiating the cryo-imaging, place the frozen kidney on a bed of frozen BMM on top of an aluminum holder to keep the tissue in place, and then cover with more BMM. Embed the kidney samples in a way that for each sagittal slice, there will corresponding sagittal-sectioned images. Allow the whole sample block to rest in the 80  C freezer for a day.

3.3 Cryo-Imaging Procedure 3.3.1 Mounting

1. Mount the metal plate on the sample stage inside the freezer, ready to be sliced and imaged. In the GUI for image acquisition, the following parameters should be set: 2. Define the Z-resolution in the GUI which is typically 30 μm. 3. Save and label the folder where the images are saved. 4. Set the location of the excitation and emission filters in the filter wheels. 5. Set the exposure times.

3.3.2 Image Acquisition

1. Slice the tissue with a defined slicing size. 2. Set the excitation and emission filters for NADH. 3. Capture the NADH image and save for the specific slice. 4. Set the excitation and emission filters for FAD. 5. Capture the FAD image and save for the specific slice. 6. Repeat steps 1–5, until the entire sample is sliced and imaged (see Note 10).

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Fig. 4 3D optical Cryo-imaging reveals the effect of partial body irradiation (PBI) and lisinopril treatment on the mitochondrial redox ratio. (a) Representative three-dimensional rendered images of kidneys from each treatment: Nonirradiated (Control), partial body irradiated without (PBI), and with lisinopril treatment (PBI + Lisino). The fluorescence patterns for NADH, FAD, and the tissue redox ratio (NADH/FAD) are shown. (b) The corresponding intensity histogram distributions of the whole kidney redox ratio (reproduced from ref. 19 with permission from Springer) 3.4 Image Processing

The stack of NADH and FAD images from sagittal kidney slices makes the three-dimensional (3D) cryo-images of the kidney (Fig. 4a). The image processing is performed using the following steps: 1. Calibrate the images using flat field images (see Note 11). 2. Subtract the background low-intensity voxels with thresholding (see Note 12). 3. Calculate the redox ratio (NADH/FAD) voxel by voxel (Fig. 4a). 4. Quantify the 3D rendered image using the histogram of the redox ratio, which is a distribution of voxel intensities through the whole volume (Fig. 4b). 5. Calculate the mean of the redox ratio histograms as the optical marker for mitochondrial redox state (NADH/FAD) of the kidney. 6. Repeat the procedure (1–5) for all the samples imaged. 7. Analyze the statistical significance between different groups of the specific animal model. 8. Analyze the heterogeneity of redox ratio regionally for some applications [18, 19].

3.5 Data Interpretation

Changes in mitochondrial redox state due to various injuries or diseases have been studied using 3D optical cryo-imaging [18– 26]. Larger redox ratio (RR) suggests a more reduced and less

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oxidized mitochondria, while smaller RR suggests less reduced and more oxidized mitochondria. Comparing the mean redox ratio of the injured group with the control group, two scenarios may happen: First, the RR of the injured tissue is significantly less than the RR of the control. This happens during disease state, such as in diabetic wounds [22], diabetic-related injuries in kidneys [23], radiation-induced injuries to kidneys [19], and ischemiareperfusion injuries to hearts [18], livers [20], and lungs [24]. In such a situation, the injured tissue shows relatively more oxidized mitochondria when compared to their corresponding controls. These observations suggest that the oxidized mitochondria cause perturbations that interfere with the biochemical machinery of oxidative phosphorylation (OXPHOS), resulting in impaired ATP production [8, 18, 27]. Impaired ATP production can be a sign of mitochondrial dysfunction due to cellular injuries and/or disease to the organ. Second, the RR of injured tissue is significantly greater than RR of the control. For example, the redox state of tissues increases due to ischemic insult to organs [18, 20, 24]. Limiting O2 supplies during ischemia prevents the oxidation of NADH by mitochondria electron transport chain, and thus NADH builds up, causing the increase in redox ratio. The transgenic rat models with cytosolic p67phox [26] or Nox4 [25] mutation also show increased mitochondrial RR in kidneys that may contribute to the protective effects observed in salt-sensitive rats. As an example of redox ratio data interpretation in disease and treatment, here is a glimpse on the role of mitochondrial redox state in the development and treatment of renal radiation injury, which has been reported in reference [19]. In that study, the impact of irradiation on mitochondrial redox ratio was compared in three groups of rat kidneys: (1) nonirradiated controls, (2) leg out partial body irradiated (PBI), and (3) leg out PBI followed by lisinopril treatment (PBI+Lisino). The details of the animal injury model and treatment with lisinopril to mitigate the irradiation-induced injuries can be found in the following reports [28–30] as described briefly below. Representative examples of 3D cryo-images of the NADH and FAD fluorescence signals and their redox ratios (NADH/FAD) are shown in Fig. 4a. Figure 4b illustrates the corresponding redox ratio histograms of the same three representative kidneys from each group of rats. Comparing PBI rats to controls, lower NADH and higher FAD fluorescence signals were observed throughout the kidney, resulting in a lower redox ratio. These results suggest that irradiation oxidizes renal mitochondrial redox state and alters mitochondrial bioenergetics in the rat model of irradiation-induced kidney damage. When the PBI rats were treated with lisinopril after irradiation, the entire kidneys exhibited higher levels of

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redox ratios, i.e., reduced redox state when compared to kidneys of rats exposed to PBI without lisinopril. This result suggests that lisinopril mitigates irradiation damage by attenuating the oxidation of mitochondria leading to increase redox ratio and preserve mitochondrial function in the kidney. In conclusion, 3D optical cryo-imager introduces a novel method to study the correlation between disease progression and changes in the volumetric RR levels as a marker of mitochondrial oxidative state [18–26]. Furthermore, 3D optical cryo-imaging sets a stage for studying and evaluating treatment options and their effects on mitochondrial redox state of injured tissue [19]. The 3D volumetric redox ratio images can also provide information on the heterogeneity in the distribution in mitochondrial redox state [18], which will provide insights into how different parts of an organ responds differentially to stress/injury.

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Notes 1. LED light sources can be another choice. However, the LED should have high luminous intensity specifically for NADH and FAD excitation wavelengths. The mercury arc lamps’ spectrum has two peaks at the excitation wavelengths of NADH and FAD, making it a good choice to perform autofluorescence imaging. 2. The optical filters can be chosen to have a pair of excitations and emissions of any fluorophores. NADH and FAD are excited at 350 nm and 430 nm, respectively. The corresponding emission spectra of NADH and FAD peaks at 460 nm and 530 nm, respectively. 3. The camera should have high quantum efficiency because the autofluorescence signal is weak in biological tissues. Using a low sensor-size, such as ~4 μm, helps us to achieve higher resolution images. 4. The downside of this design is that the working distance cannot be lower than 250 mm, due to the size of emission filter wheel that should come between the lens and tissue. 5. The emission filter wheel makes an unavoidable space between the camera and zoom lens that decreases the collection light efficiency and makes the field of view smaller. Therefore, this design can only be used when the samples are small, i.e., the field of view 70%. These steps must be taken before the actual experiments are performed. 4. While possible to analyze BA images from widefield microscopes, the higher signal-to-noise ratio achieved with a confocal system is preferred, in addition to more resolution. Confocal microscopes, especially the Zeiss Airyscan, provide higher resolution and signal-to-noise ratio. Widefield and spinning disk microscopes are less suited in that regard. However, the authors have performed roGFP2 experiments on spinning disk microscopes with some degree of success; the dynamic range was less than on a confocal and resolution only sufficient for whole-cell quantification. High resolution becomes more important when comparing subcellular regions like a peridroplet vs. cytosolic mitochondrial compartment. In simpler terms, more resolution is almost always better when measuring parameters dependent on fluorescence intensity. 5. Some enhancements can improve poor quality images for analysis, such as a previously published filtering method utilizing a median filter [25] or utilizing built-in background subtraction in ImageJ, such as the rolling ball algorithm. Poor signal-to-

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noise ratio, low fluorescence in samples, and many other caveats of fluorescent microscopy influence the efficacy of image analysis. A recent publication details the ideal input image quality and common problems and artifacts encountered with analyses of this type [14]. For instance, out-of-focus images and images with resolutions less than 0.165 μm/px may not yield accurate results—the algorithms have not been validated at lower resolutions. 6. For best spectral separation, use separate tracks for each channel. 7. When creating a new classifier, always save both the ARFF (with [save data]) and MODEL (with [save classifier]) files; some updates to WEKA or FIJI occasionally break how classifiers behave, but you can always rebuild your classifier from the underlying ARFF in the new version to fix compatibility. It is not necessary to save the classifier (MODEL) until the training is complete, but always maintain a backup copy of the ARFF. When a new version of WEKA disrupts compatibility, just open the ARFF file in the WEKA interface, and click [train classifier]. The new MODEL file should be compatible. 8. Macros can be viewed and edited by anyone. This is the easiest way to learn to automate analyses: read and understand existing analysis workflows. Go to [plugins ! macros ! edit] and open the appropriate macro. The macros available on the bioRxiv link are supplemental material and are intended for use to repeat these analyses on new images. Because the macro and protocol published here are designated for use with images collected by our lab, some tweaking may be required to use with images composed of different channel orders. Changing channel order in a macro is straightforward, but you must decipher the file naming conventions of your microscope acquisition software. We will not cover them all here, but for instance “T1-C1-Z1.tiff” usually suggests an image at the first time point, with the first acquisition channel, in the first Zplane of a stack. Adjusting file names and pointers is straightforward in FIJI as long as you clearly understand basic multidimensional file names. This issue will certainly be evident when running the BA analysis macro; the channels of our acquisition could be different from the one in other labs. This macro specifically references channels by the convention “CN-OriginalImageName” where “N” is the channel number. 9. Differentiation can be assessed by lipid droplet count and size (nile red or oil red O staining), expression of UCP1 by Western blot, or oligomycin insensitive respiration after NE injection [23].

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10. BA differentiate to different degrees. Typically, a cell is considered differentiated if a majority of its cytosol contains lipid droplets as defined by the nile red channel. When imaging, we analyzed differentiated cells instead of undifferentiated preadipocytes. Also see Note 9. 11. The skill of mixing medium on the microscope without touching the dish takes much practice, especially when working through an incubation system. Some tips specific to the Zeiss LSM 880 confocal microscope outfitted with a clear Pecon environmental control box system follow. When ready to add and mix, open the top of the incubation chamber, push the transmitted light arm back, and brace your dominant arm on the top of the incubation chamber. Slowly lower your pipette into the sample until surface tension meets the tip and you can begin to aspirate. Move the tip down with the surface of the medium until it approaches the bottom of the dish, but do not touch the bottom. There will be a minute volume remaining. Re-add medium on the side of the dish, again utilizing surface tension to reduce disruption. Adding small volumes follows a similar procedure but does not require moving with the surface of the medium. Mixing is the same procedure—but combine the above steps for aspirating and adding medium. 12. All macros discussed and available from this chapter assume single-cell images cropped from larger fields of view (if necessary). This step could be automated, but we have yet to find a suitably accurate tool to crop individual cells without a significant number of errors. The intent of providing these macros is to facilitate training and learning; they represent years of learning and optimization and can be building blocks of future macros or protocols. FIJI provides a macro recorder to start learning the macro language. It also supports Python if there is experience. The individual will almost always need to edit/tweak these macros for channel order or data output columns if input or output requirements differ from our own. References 1. Joshi MS, Crouser ED, Julian MW et al (2000) Digital imaging analysis for the study of endotoxin-induced mitochondrial ultrastructure injury. Anal Cell Pathol 21:41–48 2. Mutterer J, Rasband W (2012) ImageJ macro language programmer’s reference guide v1.46d. RSB Homepage 1–45 3. Wikstrom JD, Mahdaviani K, Liesa M et al (2014) Hormone-induced mitochondrial fission is utilized by brown adipocytes as an amplification pathway for energy expenditure.

EMBO J 33:418–436. https://doi.org/10. 1002/embj.201385014 4. Zingaretti MC, Crosta F, Vitali A et al (2009) The presence of UCP1 demonstrates that metabolically active adipose tissue in the neck of adult humans truly represents brown adipose tissue. FASEB J 23:3113–3120. https://doi. org/10.1096/fj.09-133546 5. Benador IY, Veliova M, Mahdaviani K et al (2018) Mitochondria bound to lipid droplets have unique composition, bioenergetics, and

High-Throughput Mitochondrial Image Analysis dynamics that support lipid droplet expansion. Cell Metab 27:869 6. Mahdaviani K, Benador IY, Su S et al (2017) Mfn2 deletion in brown adipose tissue protects from insulin resistance and impairs thermogenesis. EMBO Rep 18:1123. https://doi.org/ 10.15252/embr.201643827 7. Leonard AP, Cameron RB, Speiser JL et al (2015) Quantitative analysis of mitochondrial morphology and membrane potential in living cells using high-content imaging, machine learning, and morphological binning. Biochim Biophys Acta 1853:348–360. https://doi. org/10.1016/j.bbamcr.2014.11.002 8. Valente AJ, Maddalena LA, Robb EL et al (2017) A simple ImageJ macro tool for analyzing mitochondrial network morphology in mammalian cell culture. Acta Histochem 119:315–326. https://doi.org/10.1016/j. acthis.2017.03.001 9. Cribbs JT, Strack S (2009) Functional characterization of phosphorylation sites in dynaminrelated protein 1. Methods Enzymol 457:231–253. https://doi.org/10.1016/ S0076-6879(09)05013-7 10. Chaudhry A, Shi R, Luciani DS (2019) A pipeline for multidimensional confocal analysis of mitochondrial morphology, function, and dynamics in pancreatic β-cells. Am J Physiol Metab 318:E87–E101. https://doi.org/10. 1152/ajpendo.00457.2019 11. Schindelin J, Arganda-Carreras I, Frise E et al (2012) Fiji: an open-source platform for biological-image analysis. Nat Methods 9:676–682. https://doi.org/10.1038/ nmeth.2019 12. Arganda-Carreras I, Kaynig V, Rueden C et al (2017) Trainable Weka Segmentation: a machine learning tool for microscopy pixel classification. Bioinformatics 33:2424–2426. https://doi.org/10.1093/bioinformatics/ btx180 13. Koopman WJH, Visch H-J, Smeitink JAM, Willems PHGM (2006) Simultaneous quantitative measurement and automated analysis of mitochondrial morphology, mass, potential, and motility in living human skin fibroblasts. Cytom Part A 69A:1–12. https://doi.org/10. 1002/cyto.a.20198 14. Harwig MC, Viana MP, Egner JM et al (2018) Methods for imaging mammalian mitochondrial morphology: a prospective on MitoGraph. Anal Biochem 552:81. https://doi. org/10.1016/j.ab.2018.02.022 15. Nguyen A, Beyersdorf J, Riethoven J-J, Pannier AK (2016) High-throughput screening of clinically approved drugs that prime

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polyethylenimine transfection reveals modulation of mitochondria dysfunction response improves gene transfer efficiencies. Bioeng Transl Med 1:123–135. https://doi.org/10. 1002/btm2.10017 16. Molina AA, Wikstrom JD, Stiles L et al (2009) Mitochondrial networking protects beta-cells from nutrient-induced apoptosis. Diabetes 58:2303–2315. https://doi.org/10.2337/ db07-1781 17. Wikstrom JD, Katzman SM, Mohamed H et al (2007) Beta-cell mitochondria exhibit membrane potential heterogeneity that can be altered by stimulatory or toxic fuel levels. Diabetes 56:2569–2578. https://doi.org/10. 2337/db06-0757 18. Twig G, Graf SA, Wikstrom JD et al (2006) Tagging and tracking individual networks within a complex mitochondrial web with photoactivatable GFP. Am J Physiol Cell Physiol 291:C176–C184. https://doi.org/ 10.1152/ajpcell.00348.2005 19. Morgan B, Sobotta MC, Dick TP (2011) Measuring E GSH and H 2O 2 with roGFP2-based redox probes. Free Radic Biol Med 51:1943–1951. https://doi.org/10.1016/j. freeradbiomed.2011.08.035 20. Criddle DN, Gillies S, Baumgartner-Wilson HK et al (2006) Menadione-induced reactive oxygen species generation via redox cycling promotes apoptosis of murine pancreatic acinar cells. J Biol Chem 281:40485–40492. https:// doi.org/10.1074/jbc.M607704200 21. Breiman L (2001) Random forests. Mach Learn 45:5–32. https://doi.org/10.1023/ A:1010933404324 22. Cannon B, Nedergaard J (2001) Cultures of adipose precursor cells from brown adipose tissue and of clonal brown-adipocyte-like cell lines. Methods Mol Biol 155:213–224. https://doi.org/10.1385/1-59259-2317:213 23. Assali EA, Jones AE, Veliova M et al (2018) NCLX prevents cell death during adrenergic activation of the brown adipose tissue. bioRxiv:464339. https://doi.org/10.1101/ 464339 24. Miller N, Wolf D, Alsabeeh N et al (2020) High-throughput image analysis of lipiddroplet-bound mitochondria. bioRxiv:985929. https://doi.org/10.1101/2020. 03.10.985929 25. Smith DD, Kovats S, Lee TD, Cano L (2006) Median filter algorithm for estimating the threshold of detection on custom protein arrays. Biotechniques 41:74–78. https://doi. org/10.2144/000112204

Chapter 23 Cell Energy Budget Platform for Multiparametric Assessment of Cell and Tissue Metabolism Dmitri B. Papkovsky and Alexander V. Zhdanov Abstract Specific bioenergetic signature reports on the current metabolic state of the cell, which may be affected by metabolic rearrangement, dysfunction or dysregulation of relevant signaling pathways, altered physiological condition or energy stress. A combined analysis of respiration, glycolytic flux, Krebs cycle activity, ATP levels, and total biomass allows informative initial assessment. Such simple, high-throughput, multiparametric methodology, called cell energy budget (CEB) platform, is presented here and demonstrated with particular cell and tissue models. The CEB uses a commercial fluorescent lanthanide probe pH-Xtra™ to measure extracellular acidification (ECA) associated with lactate (L-ECA) and combined lactate/CO2 (T-ECA), a phosphorescent probe MitoXpress®-Xtra to measure oxygen consumption rate (OCR), a bioluminescent ATP kit, and an absorbance-based total protein assay. All the assays are performed on a standard multi-label reader. Using the same readouts, the CEB approach can be extended to more detailed mechanistic studies, by targeting specific pathways in cell bioenergetics and measuring other cellular parameters, such as NAD(P)H, Ca2+, mitochondrial pH, membrane potential, redox state, with conventional fluorescent or luminescent probes. Key words Cell metabolism, Bioenergetics, Oxidative phosphorylation, Glycolysis, Extracellular acidification, Respiration, Oxygen consumption rate, Cell energy budget, O2 and pH sensitive probes, Time-resolved fluorescence, ATP assay

1

Introduction ATP levels in healthy mammalian cells are usually maintained at constant levels (1–10 mM depending on the cell type [1]), by the tight regulation of ATP production and consumption. The main energy-producing pathways, including oxidative phosphorylation (OXPHOS), glycolysis, the Krebs cycle, pentose phosphate pathway (PPP), glutaminolysis and β-oxidation of fatty acids, and substrate level phosphorylation (SLP), all work in a coordinated manner to maintain optimal energy status of the cell (Fig. 1). Each pathway normally has a significant spare capacity outside the

Volkmar Weissig and Marvin Edeas (eds.), Mitochondrial Medicine: Volume 2: Assessing Mitochondria, Methods in Molecular Biology, vol. 2276, https://doi.org/10.1007/978-1-0716-1266-8_23, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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ca Red rb uc ox ti yl ve ati on

Fig. 1 The concept of cell energy budget analysis. Cell bioenergetics, ion balance, redox state, and biosynthesis are maintained by the main metabolic pathways, which include glycolysis, glutaminolysis, pentose phosphate pathway, the Krebs cycle, and OXPHOS. Through these pathways, cells consume metabolic substrates, O2, and ADP and produce ATP, lactate, and CO2. Depending on substrate availability, activity of key enzymes, energy demand, or pharmacological treatments, these pathways contribute differently to cellular function. This can be assessed using CEB platform which is based on a parallel measurement of L-ECA, T-ECA, OCR, and ATP values and sample biomass (total protein content)

basal range (resting cell), and multiple regulatory mechanisms which allow the different pathways to compensate each other under stress or increased energy demand, so that the cell retains optimal ATP levels under changing conditions. Conversely, significant drops in ATP indicate serious bioenergetic problems leading to altered function and ultimately to cell death. Under a disease state associated with perturbed signaling or metabolism, spare capacity of one or several pathways may be reduced, thus decreasing cell adaptability to stress conditions [2]. Traditional “floating bar” indicators such as cellular ATP, ADP/ATP ratio, NAD(P)H, mitochondrial and cytosolic Ca2+, ΔpHm, membrane potentials (ΔΨp and ΔΨm), reactive oxygen species (ROS), and redox state are useful, but they provide narrow information on cell bioenergetics. Simultaneous measurement of extracellular acidification (ECA), total cellular ATP, oxygen consumption rate (OCR), and biomass under several different conditions allows for more systemic assessment of cell bioenergetics (OXPHOS, glycolysis, and Krebs cycle) and susceptibility of cells to stress [3–5]. According to the cell energy budget (CEB), two ECA assays are carried out in standard 96/384-well plates, one with unsealed samples (lactate-mediated, L-ECA, while CO2 is allowed to escape) and another with samples sealed under oil (total, T-ECA, lactate

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Fig. 2 Recommended plate layouts for CEB experiments. (a) A quick assessment of ATP dynamics is performed at the beginning of CEB analysis in order to check for glycolysis and OXPHOS deficiency or limited spare capacity. Cells are incubated in RM or RM-gal for up to 5 h with or without AntA. (b) A complete fourparametric analysis with two conditions (e.g., media with Glc alone and Glc/Gln/Pyr), 2 treatments (e.g., AntA (AA), FCCP/OM (F/O) plus mock (M)) and duplicated measurements can be performed on one plate. Protein assay performed in the wells highlighted in orange allows normalization for total cell biomass. Wells without cells are used for correction of temperature-dependent changes in probe fluorescence. The “two plate” format can be used to analyze more conditions, cell types, or replicates (adjustable). In this case, the L-ECA, T-ECA, and protein assays are performed on the first plate (CO2-free conditions), while the OCR and ATP assays are performed on the second plate

and CO2 combined), thus allowing to devise the glycolytic and non-glycolytic (predominantly Krebs cycle derived) ECA components. In addition, ATP, OCR, and total protein levels are measured in parallel or multiplexed manner. The measurements are typically performed in 30–50 sample wells which include different treatments, necessary controls, and replicates. Following quick preliminary analysis of cell bioenergetics (Fig. 2a), the whole set of CEB assays can be fitted on one plate (Fig. 2b). However, for a larger panel of samples, the two-plate format is better, with ECA and total protein measured sequentially on one plate, and OCR and ATP— on the other. For the initial examination of the OXPHOS and glycolytic fluxes, we also recommend kinetic analysis of ATP content in cells deprived of glucose or treated with OXPHOS inhibitors. The ECA and OCR assays use the long-decay photoluminescent probes pH-Xtra™ and MitoXpress®-Xtra (Agilent Technologies, Santa Clara, CA), for which fluorescence lifetime (LT) is

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measured by rapid lifetime determination (RLD) method (two time-resolved fluorescence (TR-F) intensity signals are measured at two delay times [6]). State-of-the-art multi-label plate readers, including PHERAstar, CLARIOstar or Omega series (BMG Labtech), Victor (PerkinElmer) or Synergy (BioTek) families, normally support the TR-F and RLD modes and contain necessary filters for pH-Xtra™ and MitoXpress®-Xtra probes. Measured LT signals and derived pH/[H+] and ECA, O2, and OCR values are calculated automatically by vendor software (BMG Labtech) or by manual or semiautomated post-processing of raw fluorescent data (PE, BioTek), using calibration functions provided here or in the original publications. Total ATP and total protein/biomass content are measured with standard chemiluminescence- and absorbance-based kits/ reagents, such as Promega and Pierce, respectively. The CEB platform can be extended with some other cell-based assays, e.g., with probes for mitochondrial membrane potential, ROS, Ca2+. This suite of assays provides detailed information on cell metabolic state, with high-sample throughput, adequate sensitivity, and flexibility. So far, analytical performance and practical potential of the CEB platform have been demonstrated in a number of metabolic and signaling studies performed by different labs [7–10]. Here we describe a four-parametric CEB platform based on the parallel measurement of ATP, ECA, OCR, and total ATP levels, normalized for cell biomass/total protein content. We provide standard step-by-step protocols for preparation and execution of individual CEB assays, processing of raw experimental data, determination of the key metabolic parameters, and comparative analysis of cell metabolism under different conditions. Analytical potential and flexibility of CEB planform are exemplified with several cell and tissue models and conditions.

2

Materials

2.1 Critical Equipment

1. Standard multi-label reader capable of TR-F/RLD, luminescence, and absorbance measurements in 96/384-well plates, equipped with temperature control, red-sensitive photodetector (up to 700 nm), software for kinetic assays, and a set of optical filters: l

l l

Excitation for pH-Xtra™ and 340–390 nm (optimum at 380 nm).

MitoXpress®-Xtra:

Emission for pH-Xtra™: 615
5 nm. Emission for MitoXpress®: 640–670 nm (optimum at 650 nm).

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309

Luminescence for ATP kit: No filter (empty slot, excitation lamp—OFF).

Absorbance for protein level analysis using BCA (bicinchoninic acid) assay: 560–580 nm. Recommended instruments are FLUOstar Omega (BMG Labtech, Germany), Synergy H1 (BioTek, USA), and Victor 4 (PerkinElmer, USA) families (see Note 1). l

2. Standard microbiological safety cabinet, tabletop class II, with HEPA filter. 3. CO2 and CO2-free incubators. 4. pH-meter. 5. Analytical balances. 6. Automatic pipettes P2, P20, P100, and P1000. 7. Standard centrifuges for 15/50 mL and 1.5 mL tubes (Eppendorf, Hettich). 2.2 Cells and Reagents

1. PC12 rat pheochromocytoma cell line from ATCC (LGC standards) (see Note 2). 2. pH-Xtra™ probe (PH-100) (Agilent). 3. MitoXpress®-Xtra HS OCR kit (MX-200) (Agilent). 4. CellTiter-Glo® Madison, WI).

ATP

measurement

kit

(Promega,

5. BCA™ Protein Assay kit (Pierce, Rockford, III). 6. Several 96-well plates, clear polystyrene, tissue culture grade. 7. One white 96-well plate. 8. Tissue culture flasks, 75 cm2, sterile. 9. 1.5 mL Eppendorf tubes. 10. 50 mL tubes. 11. 20 mL plastic syringe with 22 G needle. 12. Dulbecco’s Modified Eagle’s Medium (DMEM) without phenol red and glucose. 13. Roswell Park Memorial Institute (RPMI) 1640 medium. 14. Horse serum (HS). 15. Fetal bovine serum (FBS). 16. HEPES solution, 1 M, pH 7.2. 17. 10,000 U/mL penicillin, 10,000 μg/mL streptomycin solution. 18. Sodium pyruvate, 100 mM solution. 19. L-Glutamine, 200 mM solution. 20. D(+)-Glucose.

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21. D(+)-Galactose. 22. Phosphate-buffered saline tablets. 23. 0.25% trypsin/1 mM EDTA solution. 24. Collagen type IV from human placenta. 25. Nerve growth factor (NGF), 7S from mouse submaxillary glands. 26. Carbonyl (FCCP).

cyanide

4-(trifluoromethoxy)phenylhydrazone

27. Antimycin A (AntA). 28. Oligomycin (OM). 29. Dimethyl sulfoxide (DMSO). 2.3

Solutions

Prepare all solutions using ultrapure water (electrical resistivity of 18 MΩ cm at 25  C) and analytical/molecular biology grade reagents and store them as required (see Notes 3 and 4). 1. High serum medium (HSM): RPMI 1640 supplemented with 10% HS, 5% FBS, 100 U/mL penicillin/100 μg/mL streptomycin (P/S), and 10 mM HEPES, 500 mL. 2. Low serum medium (LSM): RPMI 1640 supplemented with 1% HS, P/S, HEPES and 100 nM NGF, 500 mL. 3. “pH medium” (PM): Powder DMEM reconstituted in deionized water, filter-sterilized and supplemented with 10 mM glucose, 2 mM L-glutamine, 1 mM sodium pyruvate, and NGF, 500 mL. 4. “Respiration medium” (RM) is PM buffered with 20 mM HEPES, 500 mL. 5. “Respiration medium with galactose” (RM-gal) is RM, in which glucose is replaced with galactose, 500 mL. 6. PBS is prepared by reconstituting tablets in deionized water, and sterilized by autoclaving, 0.2–1 L.

3

Methods

3.1 T-ECA and L-ECA Assays

The L-ECA assay measures the glycolytic component of medium acidification (i.e., lactate), using pH–Xtra™ probe [11] and unsealed samples with cells in a 96/384-well plate. The T-ECA assay measures acidification due to both lactate and CO2 (produced predominantly by the Krebs cycle and pentose-phosphate pathway), using samples sealed with mineral oil (see Note 5) and pH-Xtra™ probe. Phosphorescence LT of pH-Xtra™ probe increases with [H+] elevation (or pH reduction).

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1. Grow PC12 cells in suspension in a 75cm2 flask in HSM at low passage numbers. 2. Harvest the cells by centrifugation in a 50 mL Falcon tube at 150–200  g for 5 min (see Note 6), aspirate the supernatant. 3. Resuspend the cells in 20 mL of PBS, centrifuge again and aspirate the supernatant. 4. Resuspend the cells in 1 mL of trypsin, incubate at 37  C for 90 s, then resuspend again using a P1000 pipette. Neutralize trypsin with 10 mL of LSM. 5. Using a 20 mL syringe, pass cell suspension 8–10 times through a 22½ G needle to break cell aggregates (see Note 7). 6. Count cells and dilute to a concentration 2.5  105 cells/mL with LSM. 7. Seed the cells on a collagen IV coated 96-well plate at 5  104 cells/well (see Note 8). Adjust the final volume of medium to 200 μL. Fill the remaining (outer) wells with PBS (200 μL) to maintain uniform humidity and temperature across the plate. 8. Differentiate the cells in a humidified incubator at 5% CO2, 37  C for 4–5 days, changing LSM every 48 h (see Note 9). 9. Replace spent medium with 200 μL of RM and place the plate in CO2-free incubator for 2.5 h (37  C). 10. Switch on the reader and warm it up to 37  C. Select measurement settings for ECA and program the instrument to measure wells designated for ECA assays. 11. Reconstitute the content of 1 vial of pH-Xtra™ probe (10 μg) in 10 mL of PM. 12. Prepare stock solutions of all drugs for cell treatment using PM (see Note 10). 13. Warm up mineral oil at 37  C. 14. Aspirate RM and add 150 μL of PM to each well with cells. Replace PBS with 150 μL of PM in the wells used as “no cell” control. Leave the plate in the same conditions for 30 min (see Notes 9 and 11). 15. Replace spent PM with 100 μL of PM containing the probe. Add drug stock solutions (2–10 μL) according to the plate layout shown in Fig. 2b. 16. Gently add to the wells dedicated for T-ECA analysis 150 μL of prewarmed mineral oil. 17. Quickly insert the plate in the TR-F reader, start kinetic ECA measurements for 60–90 min (see Table 1) to generate raw signal profiles of pH-Xtra™ probe (Fig. 3a). 18. When the measurements are completed, take out the plate.

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Table 1 Typical instrument settings used in CEB assays

Assay method

PerkinElmer (Victor4)

BMG Labtech FLUOstar Omega

BioTek Synergy H1

T-ECA/L-ECA Mode: TR-F Excitation: 340
40 nm (Eu filter) Emission: 615 nm (Eu filter) Delay time 1: 100 μs Delay time 1: 300 μs Gate time 1: 30 μs Gate time 2: 30 μs Integration time: 1 s/well Repeats: 30–60 repeats every 2–3 min Temperature: 37  C

Mode: TR-F Excitation: 380
20 nm Emission: 615
8.5 nm Delay time 1: 100 μs Delay time 1: 300 μs Gate time 1: 30 μs Gate time 2: 30 μs Integration time: 1 s/well Repeats: 30–60 repeats every 2–3 min Temperature: 37  C

Mode: TR-F Excitation: 380
20 nm or 360
40 nm Emission: 620
10 nm Delay time 1: 100 μs Delay time 1: 300 μs Gate time 1: 30 μs Gate time 2: 30 μs Integration time: 1 s/well Repeats: 30–60 repeats every 2–3 min Temperature: 37  C

OCR

Mode: TR-F Excitation: 340
40 nm (Eu filter) Emission: 642
10 nm (Eu filter) Delay time 1: 30 μs Delay time 1: 70 μs Gate time 1: 30 μs Gate time 2: 30 μs Integration time: 1 s/well Repeats: 30–60 repeats every 2–3 min Temperature: 37  C

Mode: TR-F Excitation: 380
20 nm Emission: 655
50 nm Delay time 1: 30 μs Delay time 1: 70 μs Gate time 1: 30 μs Gate time 2: 30 μs Integration time: 1 s/well Repeats: 30–60 repeats every 2–3 min Temperature: 37  C

Mode: TR-F Excitation: 380
20 nm Emission: 645
15 nm Delay time 1: 30 μs Delay time 1: 70 μs Gate time 1: 30 μs Gate time 2: 30 μs Integration time: 1 s/well Repeats: 30–60 repeats every 2–3 min Temperature: 37  C

Total ATP

Mode: Chemiluminescence Emission aperture: Large Filter: none Integration time: 0.5 s Repeat: No (end-point)

Mode: Chemiluminescence Filter: none Integration time: 1 s Repeat: No

Mode: Chemiluminescence Filter: none Integration time: 1 s Repeat: No

Total protein (biomass)

Mode: Absorbance Filter: 560–580 nm Repeat: No

Mode: Absorbance Filter: 560–580 nm Repeat: No

Mode: Absorbance Filter: 560–580 nm Repeat: No

3.2

OCR Assay

3.2.1 Rates of Cellular Oxygen Consumption

Relative rates of cellular O2 consumption (OCRs) are measured with MitoXpress®-Xtra probe [5, 12, 13] in cells plated on 96/ 384-well plate and sealed with mineral oil (see Note 5). Probe phosphorescence signals are reversibly quenched by O2 and depletion of sample O2 due to cell respiration increases probe signal. 1. Seed and differentiate PC12 cells as in Sect. 3.1, steps 1–8.

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Fig. 3 Example of data processing for kinetic ECA assays. (a) Profiles of raw TR-F intensity signal (F1) produced by dPC12 cells in Glc/Gln/Pyr (top curve), Glc (middle) media, and blank without cells (bottom). (b) Lifetime (LT) profiles derived from (a). (c) Correction curve (nonspecific drift of probe signal due to temperature and gas equilibration) is determined from the LT profile of blank samples (bottom). (d) Corrected LT profiles for different samples. Blank gives a straight line at ~200 μs which corresponds to pH ¼ 7.44. E. Profiles of pH and [H+] derived from (d). (f) Linear sections corresponding to t1  t2 window in (e) used for calculation of ECA rates (slopes ΔpH/Δt or Δ[H+]/Δt). (g) Calculated mean L-ECA values (four replicates for each condition— error bars) show a drastic increase upon Gln/Pyr deprivation due to compensatory utilization of glycolysis. Measured on Victor2 reader (PE)

2. In the wells designated for OCR assay (including the wells used as “no cell” control), replace LSM with 200 μL of RM and leave the plate for 30 min in a CO2 incubator (see Note 11). 3. Switch on the reader, select OCR assay method and measurements of designated wells on the plate (Table 1). 4. Take a vial of MitoXpress®-Xtra probe (10 nM) and reconstitute its contents in 100 μL of RM (100 μM stock). Dilute probe stock 1:500 in PM to produce 1 solution (200 nM). 5. Prepare drug stocks in RM. (see Note 10).

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6. Warm up mineral oil at 37  C. 7. Replace RM in OCR assay wells with 100 μL of RM containing 1 probe to all assay wells. 8. Add 2–10 μL of drug stock solutions to designated wells according to plate map (Fig. 2). 9. Gently add to all OCR assay wells 150 μL of mineral oil prewarmed at 37  C. 10. Quickly insert the plate in the TR-F reader, start kinetic OCR measurements for 60–90 min to generate profiles of cell respiration (resemble Fig. 3a). 11. When the measurements are completed, take out the plate. 3.2.2 Conduction of Measurements Using Animal Tissue

Measurements were conducted using settings described in Sect. 3.2.1. All protocols involving animals were approved by the University College Cork Animal Experimentation Ethics Committee; experiments were conducted under license from the Irish Government in accordance with national and EU legislation (European Directive 2010/63/EU). Age- and weight-matched adult male C576Bl/J mice (Charles River Laboratories, UK) were exposed to chronic intermittent hypoxia (CIH, 14 days), comprising alternating periods of hypoxia (90 s; 5–6.5% O2) and normoxia (210 s, 21% O2) for 12 cycles/h, 8 h/day (N ¼ 6), as described previously [14]. In parallel, sham animals (N ¼ 6) were exposed to normoxia. Animals were anesthetized by 5% isoflurane inhalation in O2 and euthanized by cervical dislocation followed by immediate dissection of tissue samples. Three fragments of diaphragm muscle were excised from each animal. 1. Quickly wash tissues with Krebs buffer containing 10 mM glucose and 2 mM glutamine. 2. Carefully remove an excess of the washing medium. 3. Weigh fragments of the tissue and place into wells of 96-well plates (Fig. 5a). 4. Add 100 μL of OCR medium containing 200 nM MitoXpress®-Xtra dye in each well. 5. Quickly seal all wells, including “no tissue” controls, with 150 μL of prewarmed mineral oil. 6. Repeatedly measure fluorescence in TR-F mode at 37  C for ~60 min (see Note 12), take out the plate.

3.3

ATP Analysis

Normally, cells tend to maintain steady ATP levels, if permitted by spare capacity of their energy fluxes. CellTiter-Glo® Assay provides end-point measurement of total cellular ATP levels, which reflect cell energy status and viability. The assay does not show actual rates of ATP production and consumption, but demonstrates steady-

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state ATP levels at the time of cell lysis. Easy to perform, CellTiterGlo® Assay is the first choice for pilot examination of potential deficiencies in the Krebs cycle, OXPHOS, and glycolytic fluxes [10] (see Note 13). For this, cellular ATP dynamics should be analyzed in RM and RM-gal media, with or without OXPHOS inhibition (e.g., with AntA), as exemplified in Fig. 2a (see Note 14). 1. Seed and differentiate PC12 cells as described in Sect. 3.1, steps 1–8. 2. Incubate the cells with metabolic effectors according to the plan of the experiment in 100 μL of the medium. See plate map in Fig. 2b as an example. 3. Prepare CellTiter-Glo® reagent as per manufacturer’s protocol. 4. Add 100 μL of this reagent to each ATP assay well (200 μL total volume) (see Note 15). 5. Shake the plate intensively for 2 min. 6. Transfer samples into wells of a white 96-well plates (Greiner Bio One). 7. Switch on the reader, select ATP assay method (Table 1) and program it to measure designated wells on the plate. 8. Insert the plate and measure chemiluminescence in designated wells (end-point, one scan). 9. Take out the plate when finished. 3.4 Total Protein (Biomass) Analysis

1. Prepare a set of BSA protein standards (from BCA kit) in Eppendorf tubes as per manufacturer’s instructions using cell lysis buffer (see Note 16). 2. Add cell lysis buffer to designated wells (20–25 μL/well, 2–6 wells, Fig. 2) and incubate the plate on ice for 15 min. Collect cell lysates in 1.5 mL Eppendorf tubes, pooling repeats for the same condition. 3. Centrifuge the lysates at 14,000  g for 10 min. 4. Dispense 25 μL aliquots of each lysate into wells of a clear 96-well plate in duplicates. 5. Dispense protein standards from BCA kit (0–2.0 mg/mL range) to designated wells on the plate. 6. Mix reagents A and B from BCA kit, add 200 μL aliquots to all samples. Mix well and incubate the plate at 37  C for 30 min. 7. Switch on the reader, select protein assay method (Table 1) and program it to measure BCA assay wells. 8. Insert the BCA plate and measure absorbance in each assay well (one scan). 9. Remove the plate when finished and discard it.

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According to this protocol, a complete CEB analysis with one cell line and several different conditions/treatments can be performed in approximately 5–6 h, including plate preparation, preincubation in CO2-free conditions, drug treatment, measurement of L-ECA, T-ECA, OCR, ATP, and biomass. 3.5 Data Processing and CEB Analysis

Effects of different conditions and drug treatments on cell bioenergetics can be assessed qualitatively by examining raw signal profiles of the pH-Xtra™ and MitoXpress-Xtra® probes, which reflect relative changes in ECA and OCR levels. However, correct and quantitative comparison of different cell types or complex conditions requires calculation of ECA, OCR, and ATP values. Normalization of these values for total protein content accounts for the differences in cell morphology and numbers, especially upon prolonged manipulation or treatment of cells [5]. Once the L-ECA, T-ECA, OCR, and ATP are calculated, the differences or changes in glycolytic activity, respiration, and CO2 turnover can be determined. 1. Take the ECA assay data file and convert its TR-F intensity readings (see profiles in Fig. 3a) into LT values by applying the following transformation [6] (see Note 17): LT ¼ ðt 2  t 1 Þ= ln ðF 1 =F 2 Þ, where F1 and F2 are pairs of TR-F intensity signals at delay times t1 and t2. 2. Plot LT profiles for all sample wells (Fig. 3b). 3. Produce average LT profile for each cell type/condition. 4. Take “average LT drift” profile (“no cells” wells—Fig. 3c) and subtract it from all sample wells. This will produce corrected LF profiles (Fig. 3d) (see Note 18). 5. Transform corrected LT profiles into pH profiles (Fig. 3e) using the following equation: pH ¼ ð1893:4‐LTÞ=227:54: Alternatively, conversion into [H+] scale can be made ([H ] ¼ 10pH) (Fig. 3e). +

6. Select linear initial parts on the resulting pH/[H+] profiles (here—20–50 min, Fig. 3f) and calculate their slopes (ΔpH/ Δt or Δ[H+]/Δt  see Fig. 3g). This gives T-ECA and L-ECA values. 7. Take the OCR assay data file and process it according to steps 1–4 above. 8. Convert the resulting LT profiles for all sample wells into O2 concentration profiles, using the following transformation: ½O2  ¼ 4455:46  eLT=7:48284 :

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9. Select linear parts on these respiration profiles (resemble Fig. 3e) and calculate their slopes (ΔO2/Δt), which give average OCR values. 10. Take the ATP assay data file and calculate mean ATP signals for each condition or sample type (Fig. 2). 11. Take the total protein assay data file and generate a calibration curve from absorbance values for protein standards. 12. Calculate protein content for each sample type or condition used (Fig. 2). 13. Normalize the L-ECA, T-ECA, OCR, and ATP values for corresponding total protein content at each condition (Fig. 4). 14. Calculate the contribution of CO2 to the acidification (i.e., Krebs cycle activity), e.g., as (T-ECA  L-ECA) or (T-ECA  L-ECA)/T-ECA  100% (Fig. 4b). 15. Assess spare capacity of glycolysis, Krebs cycle, and OXPHOS [5] by comparing L-ECA, T-ECA, and OCR values for the resting and FCCP/OM- or AntA-treated cells (Fig. 4b) (see Note 19). 16. Finally, calculate OCR/L-ECA ratios (Fig. 4b), which reflect relative contribution of glycolysis and OXPHOS to ATP production [5]. 3.6 Examples and Interpretation of CEB Data

1. The initial demonstration of CEB analysis is with dPC12 cells grown on glucose and on glucose/glutamine/pyruvate, which gave the following L-ECA values: 0.009 and 0.003 pH/min (Fig. 3g), or after normalization for total protein (20 μg in all sample wells)—0.45 and 0.15 pH/min/mg protein (Fig. 4a). Their OCRs were 1.7 and 4.2 nmol/min/mg protein, and ATP—0.85 and 1.0 a.u. (Fig. 4b), respectively. Cells supplied with glucose alone showed increased glycolysis, which compensates for low OXPHOS flux in the absence of glutamine. Cells grown on complete medium produced significantly more CO2 than on glucose (Fig. 4b). The OCR/L-ECA ratio reports on shifts in the glycolytic and mitochondrial ATP production for different cells or treatments. The effects of mitochondrial uncoupling and inhibition on T-ECA, L-ECA, and OCR are shown in Fig. 4c, d, exemplifying spare glycolytic and respiratory capacity. Treatments with FCCP/OM and AntA both elevate ECA (Fig. 4c), but the inhibition of complex III increases L-ECA to a much higher degree than the uncoupling by two major reasons. First, by inhibiting the electron transport chain, AntA massively decrease amounts of pyruvate oxidized by mitochondria; instead, pyruvate is converted to lactate, which, upon extrusion from cells, contributes to ECA. Second, in the presence of AntA, the F1Fo ATP synthase becomes one of the main

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Fig. 4 Advanced CEB analysis in PC12 (a–d) and COX-deficient HCT116 cells (e). (a) The difference between T-ECA and L-ECA rates reflects the contribution of CO2 release to acidification; increased L-ECA values in Gln/Pyr free conditions show the activation of glycolytic flux. (b) Upon Gln/Pyr deprivation OCR decreases, although ATP levels remain practically unchanged thanks to activated glycolysis. As (a) suggests, the difference between T-ECA and L-ECA (ΔECA) in the medium with Glc/Gln/Pyr is significantly higher than in the medium supplemented with glucose only. The decrease in OCR-to-L-ECA ratio in the medium containing no Gln or Pyr also indicates a shift towards glycolytic ATP production. (c) Upon mitochondrial inhibition (5 μM AntA), cells convert more Pyr to lactate thus increasing the ECA. The difference in lactate production between cells with inhibited and activated respiration is shown as ΔpHL. ΔpHCO2 demonstrates the contribution of CO2 to T-ECA in cells with uncoupled mitochondria (1 μM FCCP/10 μM OM). Upon AntA treatment, ΔpHCO2 is minor. (d) OCR analysis reveals activation and inhibition of respiration in cells treated with FCCP/OM and AntA, respectively. (e) Effects of the metabolites and mitochondrial modulators on ECA in COX-deficient HCT116 cells. ECA rate analysis. Media containing different combinations of Glc (10 mM), Pyr (1 mM), and Gln (2 mM) were added to the cells 1 h prior to the analysis. Oligomycin (OM, 10 μM) and AntA (5 μM) were added immediately before the analysis. ΔCO2 demonstrates the contribution of CO2 in T-ECA (shown for Mock control only). N ¼ 4 for all experiments ( p-values are presented, t-test)

consumers of cellular ATP [15], thus further accelerating glycolytic flux. In contrast, FCCP/OM double-treatment activates pyruvate consumption and prevents the reversal of F1Fo ATP synthase; as a result, the rate of pyruvate-to-lactate conversion cannot reach maximal levels. On the other hand, T-ECA rates for FCCP/OM- and AntA-treated cells are quite

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similar because in uncoupled cells a decrease in lactate extrusion is compensated by an increase in CO2 release by NADHproducing enzymes of the Krebs cycle. For the same cells and conditions, OCR analysis showed drastic decrease in respiration upon inhibition and increase upon uncoupling of mitochondria (Fig. 4d). 2. For some tissue models, e.g., cells with mitochondrial malfunctions, such as fumarate hydratase or cytochrome c oxidase (COX) deficiency, OCR assay may not be very informative [10, 16, 17], while ATP and ECA assays remain essential tools for studying such cells. We found that in SCO2/ (COX-deficient) colonic carcinoma HCT116 cells, F1Fo ATP synthase maintains mitochondrial polarization (ΔΨm and ΔpH) by hydrolyzing ATP generated by glycolysis and substrate level phosphorylation [15]. Interestingly, total amounts of ATP in WT and COX-deficient cells were identical, showing that very efficient mechanisms control ATP levels even in the absence of OXPHOS. In COX-deficient cells, ATP pool was rapidly depleted when no glucose was available, while glutamine withdrawal, as well as mitochondrial uncoupling or inhibition, had negligible effect on ATP levels. More informative was ECA assay, which reports on both glycolytic rates and the balance of (de)carboxylation reactions. As expected, treatment of COX-deficient cells with OM decreased L-ECA rate. Indeed, the glycolytic flux was supposed to decrease because it did not have to supply the inhibited F1Fo ATPase with ATP. More intriguing were the substantial increase in L-ECA and the decrease in total CO2 production in cells treated with AntA (Fig. 4e). We proposed that complex III partially retains its activity, and residual electron and H+ fluxes help maintain the mitochondrial polarization, as confirmed by the changes in ROS and ΔΨm [15]. Similar to cells with normal glycolysis and OXPHOS, COX-deficient cells slightly increased their L-ECA rate in glutamine () conditions, suggesting that their glycolysis compensates for the loss of an additional source of ATP (Fig. 4e). With OXPHOS inhibited, the observed effect was attributed to the inhibition of the SLP flux, which is largely driven by glutamine-to-α-KG conversion [18]. 3. CEB platform was originally designed for cell models; however, it is also applicable for the analysis of animal tissues. Recently, we applied OCR analysis to confirm our finding that colonic epitheliocytes decrease O2 consumption in the rodent model of colitis [19], but large data variability did not allow OCR to reveal significant changes in respiration in colitis samples in standard statistical tests. We realized that unknown

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Fig. 5 Analysis of OCR by mouse diaphragm tissue samples. (a) A photograph of tissue samples in 96-well plate: 1–5 are different animals, a–c are replicates for each animal. (b) Corrected lifetime (LT) profiles for diaphragm fragments of different size (10.8, 7.2, and 3.2 mg), excised from one sham animal. Dashed line at 25 min shows LT values used for OCR calculation. (c) Quantitative analysis of the effect of chronic intermittent hypoxia (CIH) on respiration in mouse diaphragm (N ¼ 6 for both sham and CIH groups). Negative trend in LT values in CIH group is shown ( p ¼ 0.11, t-test). Each data point represents an average of 2–3 technical replicates (different fragments of the same diaphragm)

“dead” volumes inside the colon contribute to the total weight of tissue samples and impede accurate calculations. We hypothesized that for other tissues, for which the actual weight can be measured more accurately, data variability should be lower. Indeed, the OCR analysis of the effects of CIH on mouse diaphragm tissue was seen to work well. Individual fragments of the diaphragm ranged 5–8 mg showed almost linear relationship between their OCR and weight. Fragments outside this range usually produced outliers, and therefore were excluded from statistical analysis. We comprehended that for statistically accurate comparison of the two groups, changes in corrected LT values (see Fig. 3c) were more appropriate than OCR values. Indeed, due to the hyperbolic analytical relationship between probe LT and O2 concentration [20], LT values had a lower “noise” during the first 25 min of the experiment, from which the slopes were calculated (Fig. 5b). We found that the increase in LT values (μs/min/mg of tissue) was more pronounced for the sham group (Fig. 5c). A negative trend in CIH group suggested a moderate inhibition of the OCR in hypoxic diaphragm ( p ¼ 0.11, t-test). This result aligns well with the finding that CIH induces diaphragm muscle fatigue in rats [21]. We believe that the observed decrease in tissue respiration is due to oxidative stress-induced inhibition of mitochondrial function and mitophagy, which both have been shown for hypoxic diaphragm in a similar mouse model [22].

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Overall, the multiparametric CEB platform allows highthroughput quantitative assessment of basal activity and spare capacity of the main metabolic pathways involved in cell bioenergetics, providing detailed information about their changes and underlying regulatory mechanisms.

Notes 1. When choosing an instrument for CEB, ensure that it is spectrally compatible with the pH and O2 probes, provides sufficient sensitivity (signal-to-blank ratio, time resolution), scanning speed, and uniform temperature control of the plate, and supports the RLD mode with two TR-F intensity readings at different delay times [7]. Some readers allow direct calculation of probe LT by the software (FLUOstar Omega, Synergy H1) or in Excel from the intensity profiles (Victor2, 4, 5). Victor2 4, 5 reader Europium filter set (340 nm/ 615 nm) and Samarium filter set (340 nm/642 nm) are ideal for pH-Xtra™ and MitoXpress®-Xtra probes, respectively. Luminescence analysis is required for ATP measurement; absorbance at 560, 595, and 750 nm is used for total protein measurement using BCA, Bradford, and Lowry methods, respectively. 2. Many common cell lines and primary cells are suitable for CEB analysis. In PC12 cells both glycolysis and OCR are very active. However, for certain cells types (e.g., highly glycolytic), OCR measurements can be problematic, as illustrated by the Example 2 (Sect. 3.6) using COX-deficient HCT116 cells. 3. Perform all operations with cells under the laminar flow hood. For cell culture, all reagent solutions, unless supplied sterile, should be autoclaved (with high pressure saturated steam at 121  C for 20 min) or filtered through sterile filter (0.22 μm). 4. NGF is used for PC12 cell differentiation, it should be stored at 20  C and added to RM or PM immediately prior to application to the cells. For many cell lines, NGF is not required; however, other media, combination of substrates, growth and differentiation factors can be used. 5. High-viscosity mineral oil acts as a barrier for diffusion of gases (O2, CO2) to and from the sample. Partial penetration still occurs through plastic body of the plate and oil layer. 6. Optimal cell numbers depend on the cell type, size, metabolic activity, and experimental conditions. Preliminary experiments can be conducted to optimize seeding density for ECA and OCR assays.

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7. This may not be necessary for other cell types. 8. Collagen coating improves attachment of PC12 cells to plastic surface (optional for adherent cells). Normally, sterile stock solution of collagen IV (0.1%) in 0.25% acetic acid is prepared and used at 0.01% in 0.1% acetic acid (12–24 h incubation at RT). 9. While replacing the media or washing the cells, make sure that cells are not washed away from the wells. Automatic pipette (P200 or P1000) is preferred over vacuum pump or multi-well dispenser. 10. Drug solutions can be prepared as concentrated stocks (10–50). After drug addition, the total volume of medium should be equal in all samples. 11. At this stage, cells can be pretreated (for 30 min to 3 h) with different drugs, media (e.g., glucose, glutamine, or pyruvate deprivation). 12. The best reproducibility and accuracy are achieved when the total number of tissue fragments analyzed simultaneously does not exceed nine (three animals). 13. Using kinetic ATP analysis, OXPHOS flux can be probed using RM or other medium, in which glucose is substituted with an equivalent amount of galactose (RM-gal). Glycolytic flux can be examined using RM supplemented with OXPHOS inhibitors. Tis assay can be performed with or without FBS. 14. An end-point (e.g., 3 h) or kinetic ATP analysis in RM-gal medium can also be used to assess mitochondrial toxicity of new pharmaceutical entities [23]. 15. For quantitative analysis, ATP standards should be included to generate a calibration curve. 16. Cell lysis buffer contains 150 mM NaCl, 50 mM HEPES (pH ¼ 7.5), 1 mM EDTA, and 1% IGEPAL® CA-630. Alternative buffers (e.g., RIPA buffer compatible with BCA kit) or protein assays (e.g., Bradford or Lowry method with absorbance measurements at 595 and 750 nm, respectively) can also be used. 17. FLUOstar Omega reader data analysis software (MARS) provides automatic processing of raw fluorescent data, background correction, calculation of ECA/OCR values, and graphical representation. For PerkinElmer readers data processing is performed manually, using standard MS Excel templates for ECA and OCR assays (e.g., Agilent website). 18. Proper correction should produce flat LT profiles for “no cell” samples with pH close to 7.4 (see Fig. 3c, d).

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19. AntA is a potent inhibitor of mitochondrial complex III (cytochrome c reductase); FCCP is a mitochondrial uncoupler, capable of efficient transferring H+ across the inner mitochondrial membrane; OM is an inhibitor of both direct and reversed activities of mitochondrial complex V (F1Fo ATP synthase).

Acknowledgments Support of this work by the Science Foundation Ireland, grant 12/RC/2276_P2, is gratefully acknowledged. References 1. Beis I, Newsholme EA (1975) The contents of adenine nucleotides, phosphagens and some glycolytic intermediates in resting muscles from vertebrates and invertebrates. Biochem J 152:23–32 2. Lin MT, Beal MF (2006) Mitochondrial dysfunction and oxidative stress in neurodegenerative diseases. Nature 443:787–795 3. Hynes J, Natoli E, Will Y (2009) Fluorescent pH and oxygen probes of the assessment of mitochondrial toxicity in isolated mitochondria and whole cells. Curr Protoc Toxicol 2 (16):11–22 4. Ferrick DA, Neilson A, Beeson C (2008) Advances in measuring cellular bioenergetics using extracellular flux. Drug Discov Today 13:268–274 5. Zhdanov AV, Favre C, O’Flaherty L, Adam J, O’Connor R, Pollard PJ, Papkovsky DB (2011) Comparative bioenergetic assessment of transformed cells using a cell energy budget platform. Integr Biol (Camb) 3:1135–1142 6. Ballew RM, Demas J (1989) An error analysis of the rapid lifetime determination method for the evaluation of single exponential decays. Anal Chem 61:30–33 7. Favre C, Zhdanov A, Leahy M, Papkovsky D, O’Connor R (2010) Mitochondrial pyrimidine nucleotide carrier (PNC1) regulates mitochondrial biogenesis and the invasive phenotype of cancer cells. Oncogene 29:3964–3976 8. Zhdanov AV, Dmitriev RI, Papkovsky DB (2012) Bafilomycin A1 activates HIF-dependent signalling in human colon cancer cells via mitochondrial uncoupling. Biosci Rep 32:587–595 9. Zhdanov AV, Dmitriev RI, Papkovsky DB (2011) Bafilomycin A1 activates respiration of neuronal cells via uncoupling associated with

flickering depolarization of mitochondria. Cell Mol Life Sci 68:903–917 10. O’Flaherty L, Adam J, Heather LC, Zhdanov AV, Chung Y-L, Miranda MX, Croft J, Olpin S, Clarke K, Pugh CW, Griffiths J, Papkovsky D, Ashrafian H, Ratcliffe PJ, Pollard PJ (2010) Dysregulation of hypoxia pathways in fumarate hydratase-deficient cells is independent of defective mitochondrial metabolism. Hum Mol Genet 19:3844–3851 11. Hynes J, O’Riordan TC, Zhdanov AV, Uray G, Will Y, Papkovsky DB (2009) In vitro analysis of cell metabolism using a long-decay pH-sensitive lanthanide probe and extracellular acidification assay. Anal Biochem 390:21–28 12. Hynes J, Floyd S, Soini AE, O’Connor R, Papkovsky DB (2003) Fluorescence-based cell viability screening assays using water-soluble oxygen probes. J Biomol Screen 8:264–272 13. Zhdanov AV, Ogurtsov VI, Taylor CT, Papkovsky DB (2010) Monitoring of cell oxygenation and responses to metabolic stimulation by intracellular oxygen sensing technique. Integr Biol (Camb) 2:443–451 14. Lucking EF, O’Halloran KD, Jones JF (2014) Increased cardiac output contributes to the development of chronic intermittent hypoxiainduced hypertension. Exp Physiol 99:1312–1324 15. Zhdanov AV, Andreev DE, Baranov PV, Papkovsky DB (2017) Low energy costs of F1Fo ATP synthase reversal in colon carcinoma cells deficient in mitochondrial complex IV. Free Radic Biol Med 106:184–195 16. Sung HJ, Ma W, Wang P-y, Hynes J, O’Riordan TC, Combs CA, McCoy JP, Bunz F, Kang J-G, Hwang PM (2010) Mitochondrial respiration protects against oxygen-associated DNA damage. Nat Commun 1:5

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17. Matoba S, Kang J-G, Patino WD, Wragg A, Boehm M, Gavrilova O, Hurley PJ, Bunz F, Hwang PM (2006) p53 regulates mitochondrial respiration. Science 312:1650–1653 18. Kiss G, Konrad C, Doczi J, Starkov AA, Kawamata H, Manfredi G, Zhang SF, Gibson GE, Beal MF, Adam-Vizi V (2013) The negative impact of α-ketoglutarate dehydrogenase complex deficiency on matrix substrate-level phosphorylation. FASEB J 27:2392–2406 19. Zhdanov AV, Okkelman IA, Golubeva AV, Doerr B, Hyland NP, Melgar S, Shanahan F, Cryan JF, Papkovsky DB (2017) Quantitative analysis of mucosal oxygenation using ex vivo imaging of healthy and inflamed mammalian colon tissue. Cell Mol Life Sci 74:141–151 20. Dmitriev RI, Papkovsky DB (2012) Optical probes and techniques for O2 measurement

in live cells and tissue. Cell Mol Life Sci 69:2025–2039 21. Shortt CM, Fredsted A, Chow HB, Williams R, Skelly JR, Edge D, Bradford A, O’Halloran KD (2014) Reactive oxygen species mediated diaphragm fatigue in a rat model of chronic intermittent hypoxia. Exp Physiol 99:688–700 22. Giordano C, Lemaire C, Li T, Kimoff RJ, Petrof BJ (2015) Autophagy-associated atrophy and metabolic remodeling of the mouse diaphragm after short-term intermittent hypoxia. PLoS One 10:e0131068 23. Rana P, Aleo MD, Gosink M, Will Y (2019) Evaluation of in vitro mitochondrial toxicity assays and physicochemical properties for prediction of organ toxicity using 228 pharmaceutical drugs. Chem Res Toxicol 32:156–167

Chapter 24 Fluorescence-Based Assay For Measuring OMA1 Activity Julia Tobacyk and Lee Ann MacMillan-Crow Abstract Mitochondrial fusion depends on proteolytic processing of the dynamin-related GTPase protein, OPA1, which is regulated by the mitochondrial zinc metalloproteinase, OMA1. Last year we published a report describing a novel approach to directly measure the enzymatic activity of OMA1 in whole cell lysates. This fluorescence-based reporter assay utilizes an eight amino acid peptide sequence referred to as the S1 cleavage site where OMA1 cleaves within OPA1 and is flanked by a fluorophore and quencher. In this chapter, we provide additional insight into the OMA1 activity assay. Key words OMA1, Mitochondria, Protease, Fusion, Fluorescence-based reporter assay

1

Introduction Mitochondria are dynamic organelles that continually undergo fission and fusion to maintain normal mitochondrial health [1– 3]. Fusion is regulated by a dynamin-related GTPase called optic atrophy protein (OPA1), which is involved in fusion of the inner mitochondrial membrane. OPA1 exists in different splice isoforms that can be proteolytically processed at distinct sites (S1 and S2) [4] and its proteolytic cleavage results in the long (L-OPA1) and short (S-OPA1) forms of OPA1. The balance between the L-OPA1 and S-OPA1 forms of OPA1 is regulated by two metalloproteases called OMA1 and YME1L [5], which cleave OPA1 at S1 and S2 sites, respectively. YME1L constitutively cleaves OPA1 leading to a balanced accumulation of L- and S-OPA1 protein forms, which supports normal mitochondrial fusion [6]. OMA1 is a stress-induced protease, and different stress stimuli such as ROS production, heat shock, and ATP depletion have been shown to activate OMA1 [5, 7–9]. Understanding the precise mechanistic and functional roles of OMA1 has been difficult, since there is no crystal structure or specific OMA1 inhibitors available. Recently, we have published a

Volkmar Weissig and Marvin Edeas (eds.), Mitochondrial Medicine: Volume 2: Assessing Mitochondria, Methods in Molecular Biology, vol. 2276, https://doi.org/10.1007/978-1-0716-1266-8_24, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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report describing a sensitive method to measure OMA1 enzymatic activity for the first time [10]. Many researchers measure the L- and S-OPA1 via immunoblotting to indirectly measure OMA1 activity. A drawback using this technique is that it does not take into account additional substrates that are involved in the proteolytic processing of OPA1 including YME1L [5, 11, 12]. Researchers have also used a nonspecific metal chelator, o-phenanthroline, to validate the role for OMA1 in various cell models [11]; however, both YME1L and OMA1 are effectively inhibited by o-phenanthroline [11]. To address the specific role of OMA1, researchers have also relied on OMA1 knockout models [13– 15]. Several studies show that knocking out OMA1 in vivo has protective effects in renal injury [15], heart failure [14], and neurodegeneration [16] suggesting that OMA1 might be a therapeutic target for many diseases. Use of OMA1 knockout models in vitro and in vivo has verified the importance of OMA1 during disease and its regulatory role in mitochondrial quality control. Although these genetic techniques and models offer new opportunities to study the mechanism of OMA1, there are some potential limitations. For example, unknown compensatory or redundancy mechanisms might be activated during genetic manipulations and can complicate the interpretation in characterizing the precise role of OMA1. The newly described direct, real-time OMA1 activity assay will be an important tool to further characterize this mitochondrial protease. Additionally, we anticipate that this highthroughput assay could help to identify specific pharmacological agents that will inhibit and/or activate OMA1. During the development of our OMA1 activity assay, we used cellular knockout models as tools to validate OMA1 specificity. Using both mouse embryonic fibroblast OMA1 knockout cell line and transient OMA1 siRNA knockdown models, we detected a ~50% reduction in OMA1 activity using our assay [10]. Clearly, further development is needed since these results suggest that the remaining 50% of the activity is most likely due to other proteases cleaving the fluorogenic reporter peptide. It is important to note that YME1L knockdown did not alter OMA1 activity revealing that the nonspecific component is not due to YME1L [10]. We are currently addressing these issues by optimizing the fluorogenic reporter peptide and evaluating whether lysing procedures or addition of specific protease inhibitors might reduce the nonspecific component. In this chapter, we provide a detailed description of the OMA1 activity assay. The goal of this chapter is to provide readers with technical considerations for efficient assay design and its usage across multiple types of samples and under different conditions.

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Materials Prepare all solutions using ultrapure water and analytical grade reagents. Prepare and store all reagents at 4
C (unless indicated otherwise).

2.1 Fluorogenic Reporter Peptide (AFRATDHG): Serves as the Substrate for the OMA1 Assay

The OMA1 assay utilizes a fluorogenic eight amino acid peptide that incorporates the OPA1 S1 cleavage site where OMA1 cleaves [17] (Fig. 1a). This peptide includes an MCA (7-Methoxycoumarin-4-ylacetyl) fluorophore on the amino end and the fluorescence quencher DNP (2,4-Dinitrophenyl) on the carboxy terminus. When the peptide is cleaved by OMA1, the DNP quencher is released resulting in MCA fluorescence that is measured spectrofluorometrically (excitation/emission of 325/392) using a plate reader (Fig. 1b). We custom order this

Fig. 1 The methodology behind the OMA1 activity assay. (a). OMA1, a stressinduced mitochondrial protease, cleaves OPA1 at the S1 site between arginine (194) and alanine (195) resulting in a “long” L-OPA1 and a “short” S-OPA1. (b). A custom-made peptide (AFRATDHG) was synthesized based on the rat OMA1 S1 cleavage site within OPA1. OMA1 cleavage removes the quenching of DNP, which results in increased MCA fluorescence. OMM outer mitochondrial membrane, IMS inner mitochondrial space, IMM inner mitochondrial membrane, S1 site 1, S-OPA1 short OPA1), L-OPA1 long OPA1, MCA 7-Methoxycoumarin-4ylacetyl, DNP 2,4-Dinitrophenyl, Lys lysine

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peptide from LifeTein LLC. Upon arrival, the lyophilized peptide is resuspended in DMSO to a final concentration of 1 mM and stored in 50 μL aliquots at 80
C. We have shown that a working concentration of 5 μM produces a linear response [10]. Protect from light when handling the fluorogenic reporter peptide. 2.2 Protein Sample/ Unknown

The OMA1 assay can utilize protein from various sources, and it is important to optimize sample processing and quantity used in the assay within each laboratory (see Note 1). For example, in our laboratory, we have shown sufficient OMA1 activity using 5 μg of protein isolated using a RIPA lysis method and renal cells (see Note 1).

2.3 TPEN (Used as an OMA1 Inhibitor)

50 mM master stock solution of N,N,N0 ,N0 -Tetrakis (2-pyridylmethyl)ethylenediamine (TPEN): Add 10.67 mg of TPEN and dissolve in 0.5 mL of 100% ethanol (see Note 2).

2.4

OMA1 assay buffer: 50 mM Tris–HCl, 40 mM KCl. Add 15 mL of 100 mM Tris–HCl and 1.2 mL 1 mM of KCl. Make up to 30 mL with water. Store at 4
C. This buffer is good for long-term use.

OMA1 Buffer

2.5 96-Well Microplate

Use a black 96-well, solid bottom, non-treated, polystyrene, opaque microplate (costar) with no lid for the OMA1 activity assay (product number: 3915).

2.6

Use a fluorescent plate reader available at your institution. Since MCA has been chosen as the fluorophore, be sure the plate reader can read fluorescence at excitation/emission of 325/392 nm or if the plate reader is filter based, you can select 320/405 nm settings.

3

Plate Reader

Methods Carry out all procedures on ice unless otherwise specified.

3.1

Procedure

1. Before starting the OMA1 activity assay, measure the protein concentration of your samples (see Note 1). Preheat the plate reader to 37
C prior to reading. 2. Set up a template by arranging samples in a 96-well plate (Fig. 2). If you are adding additional treatments that involve adding a new compound into the assay (e.g., screening for drugs that modulate OMA1), it is important to determine whether the compound or its solvent reacts with the fluorogenic reporter substrate or possesses intrinsic fluorescence (see Note 3). Add reagents to each well of microplate in the following order: (1) OMA1 buffer, (2) protein samples, (3) TPEN, and (4) to start reaction 5 μM of fluorogenic substrate peptide.

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Fig. 2 Suggested layout of 96-well black microplate for the OMA1 activity assay. In this hypothetical example, the intent was to screen compounds for OMA1 inhibitors. For this experiment, the following conditions were used: (1) untreated sample, (2) untreated sample + TPEN, and (3) untreated sample + Drug X (e.g., an OMA1 inhibitor). It is important to include appropriate controls that will test for possible interferences in the assay

Each sample should be in triplicate. Make sure to include: (1) Blank (OMA1 buffer only), (2) substrate alone (AFRATDHG + OMA1 buffer), (3) samples without TPEN (OMA1 buffer + AFRATDHG + protein) and samples with protein (OMA1 buffer + AFRATDHG + protein + TPEN) as well as any compound controls (Fig. 2). 3. Measure relative fluorescence at excitation/emission of 325/392 nm or if the plate reader is filter based, select 320/405 nm settings, read fluorescence every 1 min for 30 min at 37
C. 3.2

Analysis

1. At each time point, measure the average fluorescence reported as relative fluorescence unit (RFU). Since the fluorogenic reporter substrate has modest intrinsic RFU, it is important to subtract this value (AFRATDHG alone) at each time point from the sample average (Sample X) to give you the corrected RFU for each sample. Corrected sample ½RFU ¼ ½Sample X  ½AFRATDHG alone: 2. Next, to obtain the OMA1 activity for each condition, you will utilize the TPEN values. Specifically, OMA1 activity is the difference between samples with and without TPEN: OMA1 activity ½RFU ¼ ½corrected sample X   ½corrected sample X þ TPEN:

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3. Report final activity by calculating the rate (slope) over time (30 min) using linear regression: Rate ½RFU= min  ¼

½OMA1 activity : Time

4. For the statistical analysis, compare rates between each condition using appropriate statistical tests.

4

Notes 1. During sample preparation, protein can be harvested from numerous sources (e.g., cells, tissues, microorganisms) using a variety of protein isolation methods (e.g., sonication, mechanical homogenization, use of detergent-based buffers). In addition, each lab typically uses a combination of different protease inhibitors during the protein isolation procedure. In our studies, we have predominantly used radioimmunoprecipitation assay (RIPA) lysis buffer supplemented with protease inhibitors to extract protein from cell lines and rat tissues [10]. Our preliminary studies have shown variability in OMA1 activity across different methods of cell lysing techniques. We recommend users to compare different methods of isolating proteins and selection of protease inhibitors within their laboratory practices. In our first report, we showed that 5 μg of protein resulted in a linear increase in fluorescence over a 30 min time frame [10]. Since OMA1 activity will likely vary between different cell lines and tissue types, we suggest performing a dose–response curve to determine the optimal protein concentration needed to achieve a linear increase in RFU over 30 min (Fig. 3. Line A). If too much protein was included, the reaction will saturate (Fig. 3. Line B), and if too little protein was used, the reaction will have a lag phase (Fig. 3. Line C). 2. Since o-phenanthroline has intrinsic fluorescence that interferes with the MCA fluorophore, TPEN was selected as an OMA1 inhibitor for the OMA1 activity assay. There may be variability in TPEN inhibition between different cell lines and tissue types. In our first report, we used a variety of cell types and showed that 200 μM TPEN inhibits ~90% of fluorescence [10]. We recommend each user perform a dose–response curve to assess the optimal working concentration of TPEN that results in a minimum of 80% inhibition. 3. As with any fluorescence-based enzymatic assay, it is important to note that the OMA1 assay may be subjected to interferences resulting in false-positive and/or false-negative readings. The sources of interference include: (1) fluorogenic reporter

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Fig. 3 Example of protein dose–response curve in OMA1 activity assay. It is important to determine the optimal amount of protein that results in a linear increase in RFU over the 30 min time course (Line A). Line B depicts what would occur with too low protein was included in the assay. Line C depicts what would occur if too much protein was added to the substrate, resulting in a saturated reaction

substrate interacts nonspecifically with a solute (e.g., a drug used in the assay may cleave the fluorogenic reporter peptide), (2) a solute possesses intrinsic fluorescence and it is absorbed at the 325/392 emission/excitation wavelength, and (3) solvent or solute interacts with the protein sample. For the last source of interference, we determined that the addition of DMSO above 1% results in decreased RFU. These types of interferences can be detected by measuring the fluorescence signal without the presence of cell lysates (Fig. 2). It is important to include internal controls of the fluorogenic reporter peptide with a solvent/solute/drug to determine whether there is an interaction and include the solvent/solute/drug alone in OMA1 assay buffer to determine if it possesses intrinsic fluorescence.

Acknowledgments Dr. Lee Ann MacMillan-Crow and UAMS have a financial interest in the technology discussed in this chapter. This financial interest has been reviewed and approved in accordance with the UAMS conflict of interest policies. References 1. Wai T, Langer T (2016) Mitochondrial dynamics and metabolic regulation. Trends Endocrinol Metab 27(2):105–117 2. Anand R, Langer T, Baker MJ (2013) Proteolytic control of mitochondrial function and

morphogenesis. Biochim Biophys Acta 1833 (1):195–204 3. Chen H, Chan DC (2009) Mitochondrial dynamics--fusion, fission, movement, and

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mitophagy—in neurodegenerative diseases. Hum Mol Genet 18(R2):R169–R176 4. Olichon A et al (2006) Mitochondrial dynamics and disease, OPA1. Biochim Biophys Acta 1763(5–6):500–509 5. Anand R et al (2014) The i-AAA protease YME1L and OMA1 cleave OPA1 to balance mitochondrial fusion and fission. J Cell Biol 204(6):919–929 6. Ruan Y et al (2013) Loss of Yme1L perturbates mitochondrial dynamics. Cell Death Dis 4: e896 7. Baker MJ et al (2014) Stress-induced OMA1 activation and autocatalytic turnover regulate OPA1-dependent mitochondrial dynamics. EMBO J 33(6):578–593 8. Ehses S et al (2009) Regulation of OPA1 processing and mitochondrial fusion by m-AAA protease isoenzymes and OMA1. J Cell Biol 187(7):1023–1036 9. Head B et al (2009) Inducible proteolytic inactivation of OPA1 mediated by the OMA1 protease in mammalian cells. J Cell Biol 187 (7):959–966 10. Tobacyk J et al (2019) The first direct activity assay for the mitochondrial protease OMA1. Mitochondrion 46:1–5 11. Rainbolt TK et al (2016) Reciprocal degradation of YME1L and OMA1 adapts

mitochondrial proteolytic activity during stress. Cell Rep 14(9):2041–2049 12. Rainbolt TK, Saunders JM, Wiseman RL (2015) YME1L degradation reduces mitochondrial proteolytic capacity during oxidative stress. EMBO Rep 16(1):97–106 13. Quiros PM et al (2012) Loss of mitochondrial protease OMA1 alters processing of the GTPase OPA1 and causes obesity and defective thermogenesis in mice. EMBO J 31 (9):2117–2133 14. Acin-Perez R et al (2018) Ablation of the stress protease OMA1 protects against heart failure in mice. Sci Transl Med 10(434):eaan4935 15. Xiao X et al (2014) OMA1 mediates OPA1 proteolysis and mitochondrial fragmentation in experimental models of ischemic kidney injury. Am J Physiol Renal Physiol 306(11): F1318–F1326 16. Korwitz A et al (2016) Loss of OMA1 delays neurodegeneration by preventing stressinduced OPA1 processing in mitochondria. J Cell Biol 212(2):157–166 17. Ishihara N et al (2006) Regulation of mitochondrial morphology through proteolytic cleavage of OPA1. EMBO J 25 (13):2966–2977

Chapter 25 Studying Mitochondrial Network Formation by In Vivo and In Vitro Reconstitution Assay Wanqing Du, Xiangjun Di, and Qian Peter Su Abstract Mitochondria change their morphologies from small isolated vesicles to large continuous networks across the cell cycles. The mitochondrial network formation (MNF) plays an important role in maintaining mitochondrial DNA integrity and interchanging mitochondrial materials. The disruption of the mitochondrial network affects mitochondrial functions, such as ATP production, integration of metabolism, calcium homeostasis, and regulation of apoptosis, leading to the abnormal development and several human diseases including neurodegenerative disease. In this unit, we describe the method of studying MNF, which is driven by microtubule-dependent motor protein, by in vivo imaging and single-molecule in vitro reconstitution assays. Key words Mitochondrial network formation (MNF), KIF5B, Single-molecule, In vitro reconstitution system

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Introduction Mitochondrial fusion, fission, and movement are the basic mechanisms for maintaining mitochondrial dynamics and morphology across the cell cycle [1]. Our previous research found that KIF5Bmediated mitochondrial tubulation is an additional mechanism for regulating mitochondrial morphological dynamics [2]. We proposed a modified model for mitochondrial network formation: the dynamic tubulation of mitochondria, driven by Kinesin-1 motor along microtubules, gives rise to highly dynamic nanotubules, and mitofusin-mediated fusion of these tubules forms lattices which eventually interconnect to generate the mitochondrial networks in cells or by an in vitro reconstitution system [2]. Here, we summarized the protocols of studying mitochondrial network formation (MNF) with in vivo imaging and more focused on the single-molecule in vitro reconstitution system. The system contains purified mitochondria as the membrane source and in vitro

Volkmar Weissig and Marvin Edeas (eds.), Mitochondrial Medicine: Volume 2: Assessing Mitochondria, Methods in Molecular Biology, vol. 2276, https://doi.org/10.1007/978-1-0716-1266-8_25, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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polymerized microtubules together with the purified motor protein KIF5B to provide the driving force [3, 4]. In addition, this in vitro assay can also be widely applied to reconstitute the autolysosome tubulation during autophagy [5], as well as other biological processes driven by kinesin motors [6, 7] along microtubules and myosin motors [8] along actin filaments.

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Materials All the solutions and buffers used in this study should be prepared using analytical grade reagents and dissolved in ddH2O, followed by filtration with the 0.2 μm syringe filters to remove all the impurities, which may contain autofluorescence during the total internal reflection fluorescence (TIRF) microscopy imaging. We do not add sodium azide (NaN3) to the solutions. Prepare and store all reagents, solutions, and buffers at room temperature (unless indicated otherwise). Diligently follow all waste disposal regulations when disposing of waste materials.

2.1 Observation of MNF in Cells

1. Culture medium: DMEM (high glucose) supplemented with 10% fetal bovine serum (FBS), penicillin, streptomycin, and GlutaMAX-I™. 2. Phosphate-buffered saline (PBS): pH 7.4, 135 mM NaCl, 4.7 mM KCl, 10 mM Na2HPO4, 2 mM NaH2PO4. 3. Amaxa Cell Line Nucleofector II Kit. 4. Normal Rat Kidney Epithelial (NRK) cells or Mouse Embryonic Fibroblast (MEF) cells. 5. Plasmid: TOM20-GFP. 6. Plasmid: Mito-YFP. 7. Microscope: Spinning disk confocal microscope equipped with 488, 561, and/or 647 nm laser.

2.2 In Vitro Reconstitution System 2.2.1 Protein Purification

1. ddH2O: MilliQ, Millipore, 18.2 MΩ cm at 25  C. 2. Wash buffer: 20 mM Tris–HCl, pH 7.5, 500 mM NaCl, 30 mM imidazole. 3. Elution buffer: 50 mM Tris–HCl, pH 8.0, 150 mM NaCl, 250 mM imidazole. 4. Storage buffer: 50 mM HEPES-KOH, pH 7.4, 300 mM NaCl, 1 mM MgCl2, 10% (w/v) sucrose, 50 mM ATP (see Note 1). Store at 4  C. 5. Sf9 cells. 6. Culture medium for insect cells. 7. Ni Sepharose 6 Fast Flow.

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1. Phosphate-buffered saline (PBS): pH 7.4, 135 mM NaCl, 4.7 mM KCl, 10 mM Na2HPO4, 2 mM NaH2PO4. 2. H-S buffer: 10 mM HEPES-KOH, pH 7.4, 320 mM sucrose, 5 mM MgSO4, 1 mM EGTA, 1 mM DTT, and protease inhibitors (see Note 2). Store at 4  C. 3. Dounce homogenizer. 4. Optima MAX-XP ultracentrifuge. 5. 5 mL ultracentrifuge tubes.

2.2.3 In Vitro Reconstitution Assay

1. Coverslips (No.1, thickness 170 μm, size 24  50 mm) and slides (size 24  60 mm). 2. Double-sided tapes (see Note 3). 3. Ultrasonic cleaner. 4. Acetone. 5. 1 M KOH solution in ddH2O. 6. HTS tubulin powder (see Note 3). Store at dissolving in buffer.

20  C before

7. HiLyte 647-labeled tubulin powder (see Note 3). Store at 20  C before dissolving in buffer. 8. General tubulin buffer (see Note 3). Store at 4  C. 9. Tubulin glycerol buffer (see Note 3). Store at 4  C. 10. Motility assay buffer (MAB)/BRB80: 80 mM PIPES-KOH, pH 6.8, 1 mM MgCl2, 1 mM EGTA. Store at 4  C for up to 1 month. 11. 3 mg/mL casein solution in MAB. Aliquot and store at 80  C for long-term storage; once taken out, store at 4  C for up to 1 month (see Note 4). 12. GLOX solution: 60 mg/mL glucose oxidase, 6 mg/mL catalase in PBS with 40% (v/v) glycerol. Divide into aliquots of 200 μL and store at 20  C for up to 2 months; once thawed, store at 4  C for up to 1 week (see Note 5). 13. ATP working solution (with an ATP regeneration system and an oxygen scavenger system): 10 mM phosphocreatine (PC), 300 μg/mL creatine kinase (CK), 20 μM taxol, 10 mM DTT, 0.1 mg/mL casein, 2.5% glucose, 100 GLOX, and 20 μM ATP in MAB (see Note 6). 14. Syringe and syringe filter (0.2 μm). 15. Inverted microscope with 561 nm and 640 nm lasers, high NA (>1.40) TIRF objective, TIRF illumination mode, EMCCD or sCMOS as detector. 16. CM-DiI and/or MitoTracker for mitochondrial membrane staining. 17. Dimethylformamide (DMF) or dimethyl sulfoxide (DMSO) as solvent for dye.

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Methods

3.1 Cell Transfection and Observation

1. Culture cells in culture medium and check the condition by stereoscopic microscope. 2. Transfect cells with 5 μg DNA (TOM20-GFP or Mito-YFP) via an Amaxa Nucleofector II using solution T (for NRK cells) or a MEF2 kit (for all other cells) and programs for each cell line individually. 3. Culture the transfected cells in growth medium for further analysis and visualize them by spinning disk microscopy. 4. Visualize the mitochondrial network formation (MNF) using a live-cell imaging system on a confocal microscope (FV1000, Olympus). Adjust the pinhole of the confocal microscope to 80–120 μm (Fig. 1).

3.2 In Vitro Reconstitution System 3.2.1 Motor Protein Purification

1. Use pFastBac DUAL as the vector for baculovirus expression. This vector does not contain a tag for purification, therefore introduce a histidine (6) tag before the first codon of fulllength KIF5B. Clone the histidine-tagged KIF5B coding sequence between the BamH I/XbaI sites of the pFastBac DUAL plasmid. 2. Express the full-length KIF5B motor protein using the Bac-toBac expression system. Grow the Sf9 cells in Lonza media to a density of ~2  106 cells/mL and then incubate the cells with virus containing the full-length KIF5B construct. After 60 h, collect and lyse the cells by freeze–thaw cycles, and centrifuge the cells at 4  C.

Fig. 1 NRK cells expressing the mitochondrial marker Mito-YFP were visualized by spinning disk microscopy with 515 nm laser. Scale bar, 10 μm

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3. Bond the soluble fraction in batches to Ni-NTA agarose and wash the resin with wash buffer. Elute the His6-tagged KIF5B with elution buffer. Concentrate the eluate and store it in storage buffer at 80  C (see Note 7). 3.2.2 Mitochondrial Isolation

1. Wash fresh rat liver (~2 g) or 20 dishes (15 cm in diameter) of cultured MEF cells with PBS for several times, homogenize it with a Dounce homogenizer in 4 mL of H-S buffer. 2. Centrifuge at 1000  g for 10 min at 4  C. 3. Discard the pellet and the centrifuge the supernatant at 11,400  g for 20 min at 4  C. 4. Resuspend the pellet in 500 μL H-S buffer and apply it on the top of a HEPES-buffered sucrose step density gradient (0.3 mL of 2.3 M, 1.7 mL of 1.7 M, and 1.5 mL of 1 M). 5. Centrifuge the gradient at 100,000  g for 30 min at 4  C. 6. Recover 500 μL of 1 M/1.7 M interface, dilute threefold with H-S buffer, and centrifuge for 10 min at 11,400  g. Repeat this wash step three times. 7. Characterize the purification by Western blot towards Tim23 and Kif5b, as well as transmission electron microscopy (TEM) imaging for mitochondria morphology (Fig. 2).

3.2.3 Flow Chamber Assembly

1. Clean the coverslips in a staining jar by sonicating in acetone for 30 min, then in 1 M KOH for 30 min. Then wash the coverslips with ddH2O for three times and store in ddH2O to keep the surface hydrophilic. 2. Assemble the flow chamber used for the single-molecule in vitro reconstitution assay (shown in Fig. 3, containing four individual channels) with cleaned coverslips and slides just before the experiments. Use strips of double-sided tapes (length ~ 40 mm, width ~2 mm, thickness ~200 μm, total volume ~15 μL) to stick the coverslips and slides together and to isolate the flow channels. Use wrapped filter papers to absorb and change the solution along the chamber/channel.

a

b

Fraction KIF5B TIM23 Fig. 2 Purification of mitochondria. (a) MEF cells were homogenized and centrifuged in OptiPrep density gradient medium. The distribution of KIF5B and the mitochondrial marker TIM23 in the fractions was monitored by Western blotting. (b) TEM analysis of purified mitochondria from rat liver. Scale bar, 0.5 μm. (Images from ref. [2])

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The flow chamber for in vitro reconstitution assay

Pipette tips

Double-side tape Channel #1

Wrapped filter paper

Channel #2 Flow

Channel #3 Channel #4

No.1 Coverslip

Slides

Fig. 3 The flow chamber used in the single-molecule in vitro reconstitution assay. For each channel, length ~40 mm, width ~2 mm, thickness ~200 μm, total volume ~15 μL 3.2.4 Preparation of Polymerized Microtubule Filaments

1. Dissolve the dark and/or HiLyte 647 tubulin powder in general tubulin buffer and tubulin glycerol buffer with GTP as described in the manufacturer’s manual to give a final concentration of 4 mg/mL protein. Aliquot the tubulin solution and store in the 80  C freezer after quick freezing in liquid nitrogen, protecting from light. 2. Mix the dark tubulin and dye-labeled tubulin at a molar ratio of 25:1. Add 1 mM GTP and 20 μM taxol to the tubulin solution. Incubate and polymerize the tubulin mix in a 37  C water bath for 30 min followed by 30 min centrifugation at 20,000  g to remove the tubulin dimers or short oligomers. Resuspend the pellet of microtubule filaments in MAB/BRB80 containing 20 μM taxol and keep the tube in a 37  C water bath for at least 1 day before using (see Note 8). 3. Check the length of the microtubule filaments by direct visualization with 640 nm TIRF illumination on an inverted microscope.

3.2.5 Gliding Assays to Confirm the Activity of Purified Motor Proteins

1. Prepare the gliding assay chambers by using hydrophilic coverslips. Incubate 15 μL of ~1 mg/mL full-length KIF5B in flow chamber channels for 5 min. 2. Block the kinesin-coated coverslips with 50 μL of 3 mg/mL casein for 5 min, and then incubate the chamber channel with 50 μL of 40 nM HyLite 647-labeled microtubules (see Note 9). Check the density of microtubule filaments by direct visualization with 640 nm TIRF illumination on an inverted microscope. 3. Add an ATP solution with an ATP regeneration system and an oxygen scavenger system subsequently into the chamber. 4. Record image sequences every 500 ms with TIRF illumination mode under 640 nm laser excitation (Fig. 4).

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Single frame

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Maximum intensity

DyLight647 Microtubule

Fig. 4 Gliding assay to confirm the activity of purified KIF5B motor proteins. The single frame (left panel) and maximum intensity projection (right panel) of the microtubule gliding track trajectory. The images were obtained every 500 ms for 60 s on a Nikon TIRF microscope under 640 nm laser illumination and processed with ImageJ. Scale bar, 10 μm 3.2.6 In Vitro Reconstitution of MNF

1. Incubate and coat the channels with 15 μL of 10 μg/mL antitubulin antibody for 5 min, wash and block the channel with 50 μL of 3 mg/mL casein for 5 min, allowing the fluorescentlabeled microtubule filaments to be immobilized on the coverslips (see Note 9). Check the length and density of the filaments by direct visualization with 640 nm TIRF illumination on an inverted microscope. 2. Label the mitochondria with CM-Dil or MitoTracker as described by the manufacturer’s instruction. For CM-Dil, add 0.5 μL mitochondria and 0.3 μL CM-Dil into 50 μL PBS. Mix and incubate at 37  C for 3 min; centrifuge at 12,000  g for 3 min, 4  C. Resuspend pellet with 50 μL MAB buffer. 3. Incubate full-length KIF5B (80 nM) with ~0.4 mg/mL mitochondria for 10 min on ice. 4. Incubate the motor-coated mitochondria into the microtubule-coated flow chambers. Check the density of the mitochondria by direct visualization with 561 nm TIRF illumination. 5. Add 60 μL of ATP solution containing 20 μM ATP, 20 μM taxol, 1 mg/mL casein, an ATP regeneration system, and an oxygen scavenger system into the chamber channel. 6. Visualize the formation of mitochondrial nanotubes and the networks using a Nikon TIRF microscope under 561 nm TIRF illumination with 500 ms interval time (Fig. 5), as well as scanning electron microscope (SEM).

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Isolated mitochondria from

a

MEF cells CM-DiI

Rat liver

SEM image after in vitro tubulation/MNF

b

- ATP

+ ATP 20μM

Fluorescent image contrast was enhanced to better visualize the nanotube.

Fig. 5 KIF5B drives mitochondrial network reformation in vitro. (a) Purified mitochondria were labeled with CM-DiI. Highly concentrated mitochondria were incubated with KIF5B, transferred into flow chamber channels coated with polymerized microtubules, and visualized in the presence of ATP. Images were collected with a TIRF microscope. Scale bar, 10 μm. (b) Channels from (a) was disassembled and mitochondria were analyzed by scanning electron microscope (SEM). Scale bar, 2 μm

4

Notes 1. When preparing the storage buffer for KIF5B protein, add the ATP freshly just before using. 2. When preparing the H-S buffer for mitochondria purification, add the protease inhibitors freshly just before using. 3. We recommend using the tapes of 200 μm thickness to assemble the flow chamber for the in vitro reconstitution assay. We recommend using the double-sided tape from 3 M (Cat. No. 200MP). We also recommend using the HTS tubulin, HiLyte 647 tubulin, general tubulin buffer, and tubulin glycerol buffer all from Cytoskeleton Corporation. 4. When preparing the casein solution in MAB, the pH value will be reduced after the casein powder is dissolved. Adjust the pH back to 6.8 with KOH powder. 5. When preparing the 100  GLOX solution, weigh and dissolve 60 mg glucose oxidase and 6 mg catalase powder in 500 μL PBS on a vortex shaker and avoid bubbles for few minutes. Centrifuge the yellow solution at 20,000  g for 1 min and

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discard the dark-colored pellet. Finally, add 500 μL 80% glycerol, mix and aliquot the solution into 100–200 μL. Store the GLOX solution at 20  C. 6. Prepare the ATP working solution freshly before each experiment and keep it on ice before adding it into the chamber. Immediately before adding the solution to the chamber, add the ATP and GLOX. Remember to warm the ATP solution before adding it into the chamber. 7. Add ATP to the storage buffer freshly before usage. To avoid multiple freeze–thaw cycles, we recommend making protein aliquots of no more than 5 μL per tube (every experiment needs ~0.4 μL kinesin solution). Store the protein aliquots in the 80  C freezer after quickly freezing them in liquid nitrogen. 8. Prewarm the buffers and centrifuge before dealing with microtubules because low temperatures cause rapid depolymerization of microtubule filaments. Cut the pipette tips when resuspending the microtubule pellet to avoid shearing forces. Sometimes the microtubule filaments are not long enough ( 1. 2. A flat-field correction is performed to buffer for spatial intensity variations (illumination heterogeneity). To this end, the image is divided by the corresponding image from the reference slide. 3. The flat-field corrected stack is then projected according to the maximum pixel intensity. This allows capturing the majority of the mitochondria in one image. A potential disadvantage of this procedure is superposition of mitochondria from different levels in the worm, although we found this effect to be limited due to the coarse axial sampling. 4. A duplicate image of the maximum projection image is pre-processed, by background subtraction (rolling ball radius ¼ 15) and local contrast enhancement (block size ¼ 15, slope ¼ 3), so as to buffer intensity variations between the different objects of interest (mitochondria). 5. Mitochondria are then specifically enhanced by means of a multi-scale Laplacian operator [19] (see Note 12). 6. The enhanced image is binarized according to an autothresholding procedure (Yen or Isodata), yielding a mask that can be used for analyzing the mitochondria in the original image. Before doing so, the mask should be filtered to only retain objects of a predefined size (>7 pixels), this is to avoid noise or debris from skewing the results.

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Using the mask, shape, and intensity metrics, individual mitochondria are extracted from the original image as well as the total number of mitochondria. In addition, general texture metrics can be calculated from a gray-level co-occurrence matrix analysis. We specifically calculate the average texture parameters over a horizontal and a vertical GLCM matrix with a 1 pixel offset (a reference pixel and its immediate neighbor) (see Note 13). 3.5 Mitochondrial Quantification

After feature extraction, results are summarized per worm or per condition, by averaging individual mitochondrial metrics. Dedicated statistical analyses can be performed in MATLAB 2017® or in R freeware. In a first approach, individual parameters can be statistically compared between conditions, by means of pairwise students t-tests or, in case of non-normal distributions, Wilcoxon rank sum tests. Subsequently, a more holistic cluster analysis can be performed, integrating all relevant features. To this end, the data set is first standardized (values are converted to Z-scores), so as to avoid differences in magnitude or range from pulling the weight too much towards one particular variable. Using the standardized data set, the different conditions (e.g., chemical treatments or RNAi) are then clustered using Euclidean distance as distance metric and the average value as linkage value for establishing the dendrogram. The same is done for the features and the final output is displayed in a two-dimensional clustergram, color-coded by the z-value (Fig. 3). This representation allows for quickly resolving conditions with similar effects on mitochondrial morphology.

Fig. 3 Mitochondrial morphological changes caused by 10 mM NaN3. Mitochondrial networks slowly deteriorate over time and become more fragmented. a ¼ 10 min, b ¼ 30 min, c ¼ 60 min, d ¼ 120 min, e ¼ 150 min, f ¼ 180 min, g ¼ 240 min, h ¼ Typical mitochondrial morphology after vulvar gonad protrusion

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Notes 1. Other strains such as SJ4103 [20] also service and are easier to maintain, yet the strain mentioned is preferred due to the fact that it lacks autofluorescent and birefringent gut granules, and the mitochondrial network in control animals is neatly organized and clearly distinguishable, making image analysis straightforward. 2. Glass-bottomed petri dishes have the advantage over traditional agar-pad microscopy slides as they do not need to be made beforehand, are sterile, do not dry out the worms, and importantly minimalize light refraction and background during image acquisition. 3. The type is irrelevant for imaging; they are merely needed to seal off the well. 4. Add the chemical of interest before the medium is poured and mix well with a magnetic bead stirrer, making sure that the chemical can withstand temperatures above ~50
C beforehand. Pour the NGM plates in a sterile environment when the medium has cooled to ~50
C, or you can comfortably hold the medium flask. The agarose in the NGM plates solidifies during cooling, which takes approximately 30 min. NGM plates without chemical additions can be stored at 4
C for approximately 2 months in a sealed container or petri dish sleeve. Plates including drugs or other chemicals should be used as quickly as possible, depending on the compound’s stability. Seeded plates can be kept for several days in a cool, dark, and dry environment. Ensure that the OP50 can grow normally when exposed to your chemical of interest. If this is not the case, OP50 stocks can be 5 concentrated, spread on the NGM plates, and “inactivated” by UV exposure, before drying at room temperature and placing the worms on the plates. 5. Because there is no food present, the larvae halt growth at the L1 stage. L1 worms can be kept for approximately 48 h in these conditions before use. 6. During this period, worms become adults and lay eggs. Therefore, the plates are prone to become overcrowded, rapidly reducing the E. coli food source. In this case, worms can be sterilized at the L4 stage by adding 5-fluoro-20 -deoxyuridine (FUdR) to the agar [21], or if FUdR may interfere with the experiments, meshed using a Sefar Nitex μM filter (Sefar AG Filtration Solutions, Heiden, Switzerland) every 24 h to rid the culture of progeny.

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Fig. 4 Heatmap obtained after analysis of a set of images from C. elegans worms treated with different chemical compounds or RNAi. The columns represent different features of mitochondrial shape and intensity as well as image texture, and the rows represent the different treatments. On the right, representative images are shown for the most dominant phenotypical patterns of mitochondrial networks (normal, fragmented, and complex)

7. Immediate analysis is essential as NaN3 inhibits the respiratory enzyme cytochrome oxidase and therefore affects mitochondria in the long run. After approximately 1 h of exposure to 10 mM NaN3 worm, mitochondrial networks become disengaged and they fragment (Fig. 4). This is particularly evident in muscles adjacent to the vulva, and prolonged NaN3 exposure can cause gonad protrusion through the vulva (Fig. 3). NaN3 is, however, still preferred above other immobilizing agents as its effects are rapid. Frequently used anesthetizing agents for in vivo analysis include levamisole (Tetramisole hydrochloride) or aldicarb, but these compounds show full paralyzing effects only after hours [22]. Fixating agents, such as formaldehyde, can also be used [23]. However, the effects of these chemicals and their relatively long-term incubation time to obtain full immobilization may affect mitochondrial morphology. 8. This area contains somatic muscle cells nr. 7, 8, and 9 from the D-lineage, which are present at hatching and have the highest exposure to the compound through ingestion. 9. C. elegans has distinct muscle segments which are divided into two dorsal and two ventral quadrants, with two rows of muscle cells per quadrant (http://www.wormatlas.org/hermaphro dite/muscleintro/MusIntroframeset.html). Each quadrant in

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an adult hermaphrodite is approximately 8 μm thick at the area just behind the posterior bulb. Typically, ~25 slices at 1 μm intervals will sufficiently cover the quadrant closest to the bottom coverslip. Because of the orientation of the muscle quadrants (see Note 10), it can be quicker to scan for the top of the worm and set this as the z-stack’s upper limit (~50 slices at 1 μm intervals). This limit no longer needs to be adjusted for each worm, thus speeding up image acquisition, although it will provide you with many useless images. 10. This should provide you with approximately 15–25 images per z-stack, of which, on average, six images provide sufficient muscle cross-sectional surface area so they can be used for image analysis. Because the nematode strain described here has the roller phenotype, the nematode’s rows of muscle are likely slightly corkscrewed when paralyzed. Depending on the position of the nematode in the well, the z-stack segmentation may not be optimal to obtain large surface area images of the muscle quadrants. In this case, select a different worm. 11. Traditional mitochondrial morphology analysis methods rely on blind-scoring by the researcher and, although adequate, have limited descriptive power due to the amount of variables that can be taken into account [23]. In addition, these scoring methods are time-consuming, labor-intensive, and due to their lack of sensitivity, a considerable amount of worms or muscle cells needs to be imaged before sufficient statistical power can be attained. 12. This requires the FeatureJ plugin by Erik Meijering (http:// www.imagescience.org/meijering/software/featurej/), which is part of the FIJI package but should be downloaded and installed when using ImageJ. 13. This requires the GLCM_Texture plugin by Julio Cabrera (http://rsbweb.nih.gov/ij/plugins/texture.html). References 1. Bess AS, Crocker TL, Ryde IT et al (2012) Mitochondrial dynamics and autophagy aid in removal of persistent mitochondrial DNA damage in Caenorhabditis elegans. Nucleic Acids Res 40:7916–7931 2. Shutt TE, McBride HM (2013) Staying cool in difficult times: mitochondrial dynamics, quality control and the stress response. Biochim Biophys Acta 1833:417–424 3. Yasuda K, Ishii T, Suda H et al (2006) Age-related changes of mitochondrial structure and function in Caenorhabditis elegans. Mech Ageing Dev 127:763–770

4. Jendrach M, Pohl S, Vo¨th M et al (2005) Morpho-dynamic changes of mitochondria during ageing of human endothelial cells. Mech Ageing Dev 126:813–821 5. Desler C, Hansen TL, Frederiksen JB et al (2012) Is there a link between mitochondrial reserve respiratory capacity and aging? J Aging Res 2012:192503 6. Galloway CA, Yoon Y (2013) Mitochondrial morphology in metabolic diseases. Antioxid Redox Signal 19:415–430 7. de Boer R, Smith RL, De Vos WH et al (2015) Caenorhabditis elegans as a model system for

Mitochondrial Morphology Quantification studying drug induced mitochondrial toxicity. PLoS One 10:e0126220 8. Markaki M, Tavernarakis N (2010) Modeling human diseases in Caenorhabditis elegans. Biotechnol J 5:1261–1276 9. Culetto E, Sattelle DB (2000) A role for Caenorhabditis elegans in understanding the function and interactions of human disease genes. Hum Mol Genet 9:869–877 10. Lezzerini M, Budovskaya Y (2013) A dual role of the Wnt signaling pathway during aging in Caenorhabditis elegans. Aging Cell 13:8 11. Luz AL, Rooney JP, Kubik LL et al (2015) Mitochondrial morphology and fundamental parameters of the mitochondrial respiratory chain are altered in Caenorhabditis elegans strains deficient in mitochondrial dynamics and homeostasis processes. PLoS One 10: e0130940 12. Koopman M, Michels H, Dancy BM et al (2016) A screening-based platform for the assessment of cellular respiration in Caenorhabditis elegans. Nat Protoc 11:1798–1816 13. Tsang WY, Lemire BD (2003) The role of mitochondria in the life of the nematode, Caenorhabditis elegans. Biochim Biophys Acta 1638:91–105 14. Addo MG, Cossard R, Pichard D et al (2010) Caenorhabditis elegans, a pluricellular model organism to screen new genes involved in mitochondrial genome maintenance. Biochim Biophys Acta 1802:765–773 15. Bratic I, Hench J, Trifunovic A (2010) Caenorhabditis elegans as a model system for mtDNA replication defects. Methods 51:437–443

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16. Dickinson DJ, Pani AM, Heppert JK et al (2015) Streamlined genome engineering with a self-excising drug selection cassette. Genetics 200:1035–1049 17. Labrousse AM, Zappaterra MD, Rube DA et al (1999) C. elegans dynamin-related protein DRP-1 controls severing of the mitochondrial outer membrane. Mol Cell 4:815–826 18. Sulston J, Hodgkin J (1988) Methods. In: Wood W (ed) The nematode Caenorhabditis elegans. Cold Spring Harbor Laboratory Press, New York, NY, pp 287–606 19. De Vos WH, Van Neste L, Dieriks B et al (2010) High content image cytometry in the context of subnuclear organization. Cytom Part A J Int Soc Anal Cytol 77:64–75 20. Benedetti C, Haynes CM, Yang Y et al (2006) Ubiquitin-like protein 5 positively regulates chaperone gene expression in the mitochondrial unfolded protein response. Genetics 174:229–239 21. Mitchell DH, Stiles JW, Santelli J et al (1979) Synchronous growth and aging of Caenorhabditis elegans in the presence of fluorodeoxyuridine. J Gerontol 34:28–36 22. Ramot D, Johnson BE, Berry TL et al (2008) The Parallel Worm Tracker: a platform for measuring average speed and drug-induced paralysis in nematodes. PLoS One 3:e2208 23. Giacomotto J, Brouilly N, Walter L et al (2013) Chemical genetics unveils a key role of mitochondrial dynamics, cytochrome c release and IP3R activity in muscular dystrophy. Hum Mol Genet 22:4562–4578

Chapter 30 Assessing Impact of Platinum Complexes on Mitochondrial Functions Suxing Jin and Xiaoyong Wang Abstract Platinum-based antitumor drugs play important roles in the clinical treatment of various tumors. Nevertheless, some deficiencies such as poor targeting ability, low bioavailability, in vivo deactivation, drug resistance, and side effects undermine the efficacy of these drugs. Mitochondria are important organelles which regulate the energy metabolism, physiological function, life span, and survival of the cells. Regulating or interfering with mitochondrial metabolism is of great significance in the prevention or treatment of cancers. Thus, a series of mitochondrion-targeted platinum complexes were prepared by modifying triphenylphosphine (TPP+) through chemical modifications, which endow traditional platinum drugs with new properties and mechanisms through interfering with mitochondrial DNA (mtDNA), mitochondrial membrane potential (MMP), mitochondrial morphology, mitochondrial bioenergetics, or production of reactive oxygen species (ROS), thereby opening a new path for the clinical application of platinum drugs. Here we introduce the synthesis of some TPP+-modified platinum (II, IV) complexes in details and the detection method of the activity parameters related to the mitochondrial functions. Key words Platinum complex, Mitochondrion, Triphenylphosphine, Synthesis, Detection

1

Introduction Platinum-based metallodrugs are the most widely used antitumor drugs in the clinic. Cisplatin, for example, was approved by the Food and Drug Administration (FDA) of the United States as an antitumor drug for clinical use in the treatment of cancers in 1979 and is widely used in the treatment of cervical cancer, bladder cancer, head and neck cancer, non-small cell lung cancer, and so on [1, 2]. Although platinum drugs have achieved huge success in cancer treatment, they also encountered problems such as systemic toxicity and drug resistance [3, 4]. To solve these problems and provide better chemotherapy to cancers, we need to explore and develop novel metallodrugs and to study new mechanisms of platinum drugs.

Volkmar Weissig and Marvin Edeas (eds.), Mitochondrial Medicine: Volume 2: Assessing Mitochondria, Methods in Molecular Biology, vol. 2276, https://doi.org/10.1007/978-1-0716-1266-8_30, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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Mitochondria are tiny organelles in cells, which provide almost all the energy needed for cell operation by producing adenosine triphosphate (ATP) [5]. Mitochondria are widely involved in signal transduction, energy metabolism, autophagy, apoptosis, and other cell processes, which is essential to maintain the normal physiological functions of the cells; furthermore, there are direct or indirect connections between the functions [6]. Calcium balance, for example, is related to the production of ATP, which is in turn related to the activation of calcium-sensitive citrate cycle enzyme, the production of ROS, the opening of mitochondrial transition pore, and the reduction of membrane potential that causes apoptosis [7]. Thus, it is important to regulate or intervene mitochondrial metabolic process in the prevention or treatment of cancers. Moreover, the excessive production of reactive oxygen species (ROS) in mitochondria could cause damage to mitochondrial DNA (mtDNA) and mitochondrial dysfunction, which would lead to cell apoptosis. The status of mitochondria (number, size, etc.) will change accordingly when cells are damaged. It was observed that the morphology of mitochondria in tumor cells is different from that in normal cells, and the function of mitochondria can be regulated by affecting the morphology or membrane integrity of mitochondria. The imbalance of fusion and division could also lead to mitochondrial dysfunction, fragmentation, increase of ROS and ATP production, followed by decreased membrane potential (MMP), which was regarded as a starting point for inducing apoptosis [8]. In addition, the membrane permeability may increase due to the high expression of mitochondrial membrane proteins Bak and Bax, leading to the release of proapoptotic proteins such as cytochrome c [9, 10]. Considering the multiple functions of metal complexes, intervention of mitochondrial morphology, MMP, ROS, and proteins may be accomplished through tactful design of platinum complexes, which have showed great potential in antitumor applications. Mitochondria have double-layer membranes, and the membrane potential is negative inside and positive outside, which could be exploited for targeting mitochondria. Selective accumulation of platinum drugs in mitochondria can intervene the status or function of mitochondria [11]. The MMP of cancer cells is higher than that of normal ones on the account of metabolic changes, which gives rise to the accumulation of positively charged compounds in mitochondria of cancer cells up to 10 times higher than that in normal cells [12]. Therefore, cationic molecules are preferentially taken up by tumor cells, leaving normal cells free of damage. Consequently, mitochondrion-targeting groups have two major characteristics: (1) delocalized positive charge(s) and (2) high lipophilicity. Triphenylphosphine cation (TPP+) is the most widely used such group for mitochondrial targeting

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[13]. Advantages of TPP+ have been well recognized, which make it easy to be introduced into platinum complexes by chemical synthesis [14]. Herein we describe the synthesis of different types of TPP+-modified TPP+-PtII and TPP+-PtIV complexes, and the experimental methods for testing their effects on mtDNA, MMP, bioenergetics, mitochondrial morphology, ROS, and apoptosisrelated proteins, etc. In-depth investigations on the functions of mitochondria interfered by these platinum complexes were carried out according to these methods.

2

Materials Prepare all solutions using ultrapure water and analytical grade reagents. Prepare and store all reagents at room temperature unless indicated otherwise.

2.1

Equipment

1. Three-necked round bottom flasks (150 and 250 mL). 2. Microtubes (1.5 mL, nonpyrogenic and Rnase-/Dnase-free). 3. Centrifuge tubes (10 mL). 4. Glass homogenizer.

2.2

Primer

The primer sequences of the selected genes in RT-qPCR [15]: 1. AS1-F: 50 -CCCTAACACCAGCCTAACCA-30 2. AS1-R: 50 -AAAGTGCATACCGCCAAAAG-30 3. BS1-F: 50 -CATGCCCATCGTCCTAGAAT-30 4. BS1-R: 50 -ACGGGCCCTATTTCAAAGAT-30 5. CS1-F: 50 -TCCAACTCATGAGACCCACA-30 6. CS1-R: 50 -TGAGGCTTGGATTAGCGTTT-30 7. DS1-F: 50 -ACTACAACCCTTCGCTGACG-30 8. DS1-R: 50 -GCGGTGATGTAGAGGGTGAT-30 9. AL1-F: 50 -CTGTTCTTTCATGGGGAAGC-30 10. AL1-R: 50 -AAAGTGCATACCGCCAAAAG-30 11. BL1-F: 50 -CATGCCCATCGTCCTAGAAT-30 12. BL1-R: 50 -TGTTGTCGTGCAGGTAGAGG-30 13. CL1-F: 50 -CACACGAGAAAACACCCTCA-30 14. CL1-R: 50 -CTATGGCTGAGGGGAGTCAG-30 15. DL1-F: 50 -CCCTTCGCCCTATTCTTCAT-30 16. DL1-R: 50 -GCGTAGCTGGGTTTGGTTTA-30 17. mt-ND1-F: 50 -ATATGAAGTCACCCTAGCCAT-30

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18. mt-ND1-R: 50 -CTGAGACTAGTTCGGACTCCC-30 19. mt-ND2-F: 50 -CGGACAATGAACCATAACCAA-30 20. mt-ND2-R: 50 -GTTTAATCCACCTCAACTGCC-30 21. mt-ND3-F: 50 -GCCCTACAAACAACTAACCTG-30 22. mt-ND3-R: 50 -ATTCGGTTCAGTCTAATCCTT-30 23. mt-ND4-F: 50 -TCTGTGCTAGTAACCACGTTC-30 24. mt-ND4-R: 50 -AAAACCCGGTAATGATGTCG-30 25. mt-ND4L-F: 50 -ACTAGTATATCGCTCACACC-30 26. mt-ND4L-R: 50 -CTAGTATGGCAATAGGCACA-30 27. mt-ND5-F: 50 -CTTACCACCCTCGTTAACCC-30 28. mt-ND5-R: 50 -ATAACTTCTTGGTCTAGGCACA-30 29. mt-ND6-F: 50 -ATATACTACAGCGATGGCTA-30 30. mt-ND6-R: 50 -AATCCTACCTCCATCGCTA-30 31. mt-CYB-F: 50 -TTATTGACTCCTAGCCGCAGA-30 32. mt-CYB-R: 50 -TAGTACGGATGCTACTTGTCCA-30 33. mt-CO1-F: 50 -AATAGGAGCTGTATTTGCCAT-30 34. mt-CO1-R: 50 -AGAAAGTTAGATTTACGCCGAT-30 35. mt-CO2-F: 50 -CTTTACATAACAGACGAGGTCA-30 36. mt-CO2-R: 50 -TTGAAGATTAGTCCGCCGTA-30 37. mt-CO3-F: 50 -CCACTCCTAAACACATCCGTA-30 38. mt-CO3-R: 50 -GCCAATAATGACGTGAAGTCC-30 39. mt-ATP6-F: 50 -CAACACTAAAGGACGAACCTG-30 40. mt-ATP6-R: 50 -TTAATCTTAGAGCGAAAGCCTA-30 41. mt-ATP8-F: 50 -TGCCCCAACTAAATACTACCG-30 42. mt-ATP8-R: 50 -ATGAATGAAGCGAACAGAT-30 43. REF-F: 50 -GGAGCGAGATCCCTCCAAAAT-30 44. REF-R: 50 -GGCTGTTGTCATACTTCTCATGG-30 2.3

Solutions

1. XF assay medium (Seahorse Bioscience): The constituents are based on Dulbecco’s Modified Eagle’s Medium (DMEM). No sodium bicarbonate (tissue culture buffering agent), glucose, glutamine/GlutaMAX, or sodium pyruvate is present. 2. Test solution for oxygen consumption rate (OCR) assay: Add glucose (25 mM) and pyruvate (1 mM, Sigma-Aldrich) into the XF assay medium and adjust the pH to 7.4. 3. Test solution for extracellular acidification rate (ECAR) assay: Add glutamine (2 mM, Sigma-Aldrich) into the XF assay medium and adjust the pH to 7.4.

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4. XF glycolysis stress test kit: (a) Glucose solution: Add XF assay medium (1 mL, see item 1) to glucose (0.45 g) to reach a final concentration of 2.5 mM. (b) Oligomycin solution: Add dimethyl sulfoxide (DMSO, 180 μL) to oligomycin to reach a final concentration of 5 mM. (c) 2-Deoxy-D-glucose (2-DG) solution: Add XF assay medium (16 mL, see item 1) to 2-DG, mix well until clear, and keep at 37  C until the solution becomes yellow. Add the medium to make the constant volume be 18 mL. Adjust the pH to 7.4 with 1 M NaOH. 5. XF cell mito stress test kit: (a) Oligomycin solution: see item 4b. (b) Carbonyl cyanide 4-(trifluoromethoxy)phenylhydrazone (FCCP) solution: Add DMSO (180 μL) to FCCP to reach a final concentration of 2.5 mM. (c) Rotenone solution: Add DMSO (180 μL) to rotenone to reach a final concentration of 2.5 mM. (d) Antimycin solution: Add DMSO (180 μL) to antimycin to reach a final concentration of 2.5 mM. 6. Radio immunoprecipitation assay (RIPA) lysis buffer: The main components are Tris–HCl (50 mM, pH 7.4), NaCl (150 mM), 1% Triton X-100, 1% sodium deoxycholate, 0.1% sodium dodecyl sulfate (SDS), inhibitors such as sodium orthovanadate, sodium fluoride, leupeptin, ethylenediaminetetraacetic acid (EDTA), and so on. 7. Cell lysis buffer: Add DTT (1 mM, 1 μL), PMSF (1 mM, 10 μL), NaF (0.1 mM, 10 μL) and 100 protease inhibitor cocktail (10 μL) to RIPA lysis buffer. 8. Polymerize acrylamide containing 0.1% SDS (Acryl/Bis solution 29:1, 40%) solution to form SDS-PAGE gel under the induction of ammonium persulfate and four methyl ethylenediamine. Perform protein electrophoresis using a noncontinuous system with the stacking gel of 5% (80 v) and the separation gel of 5% (60–212 kDa), 7.5% (30–120 kDa), 10% (18–75 kDa), 12.5% (15–60 kDa), 15% (15–43.5 kDa) (120 v), respectively. 9. Transfer buffer: Dissolve Tris–HCl (30.29 g) and glycine (144 g) in ultrapure water (1 L) to prepare 10 transfer buffer. Mix 10 transfer buffer (100 mL), methanol (200 mL), and ultrapure water (700 mL) to obtain 1 transfer buffer. 10. Phosphate-buffered saline (PBS): Dissolve NaCl (80.0 g), KCl (2.0 g), Na2HPO4 · 12H2O (36.3 g), and KH2PO4 (2.7 g) in

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ultrapure water (1 L) to prepare 10 PBS buffer. Mix 10 PBS buffer (100 mL) and ultrapure water (900 mL) to obtain 1 PBS buffer. 11. PBST buffer: Add Tween-20 (1 mL) in 1 PBS buffer (1 L). 12. Blocking buffer: Add skim milk (2 g) in PBST buffer (40 mL). 2.4

Fluorescent Dyes

1. MitoSOX™ working solution: Dissolve a vial of MitoSOX™ mitochondrial superoxide indicator in DMSO (13 μL) to make a MitoSOX™ reagent stock solution (5 mM). Dilute the MitoSOX™ reagent stock solution in PBS or incomplete cell culture to make a MitoSOX™ reagent working solution (5 μM). 2. JC-1 working solution: Dilute an appropriate amount of JC-1 (200) at a ratio of 50 μL JC-1 (200) to 8 mL ultrapure water and dissolve it by a vigorous vortex. Add JC-1 buffer solution (5, 2 mL) to get the JC-1 working solution. 3. JC-1 staining buffer: Dilute an appropriate amount of JC-1 (5) at a ratio of 1 mL JC-1 (5) to 4 mL ultrapure water to get the JC-1 working solution and place it on ice.

2.5 Cell Culture Components

1. HeLa and A 549 cells (ATCC, USA). 2. Cell culture medium: DMEM culture medium with 10% fetal bovine serum; store it at 4  C. 3. Trypsin: 0.25% trypsin in PBS buffer; store it at 4  C. 4. Washing buffer: PBS of pH 7.2 without calcium and magnesium. 5. Cell culture dishes (60 and 100 mm) and 6-well plates (Corning). 6. Standard 35 mm cell culture dish with glass bottom.

3

Methods

3.1 Synthesis of TPP+-PtII (a)

1. Stir p-methylbenzaldehyde (9.00 mL) and 2-acetylpyridine (9.00 mL) in NaOH (2%) aqueous solution (150 mL) at room temperature for 8 h to obtain a pale yellow solid. 2. Add 2-acetylpyridine (9.00 mL) to the above solid-liquid system, then adjust the concentration of NaOH aqueous solution to 20%. Raise the temperature to 50  C and stir the solution continuously for 8 h to obtain a brown-red oil. 3. Solidify the oil and remove the aqueous phase. Add ethanol (200 mL) to dissolve the oil, obtaining a dark red clear liquid. Add ammonium acetate (50.00 g) in batches under reflux at 60  C for 5 h. Evaporate part of the ethanol as the raw materials react almost completely and crystallize to obtain needle-like crystals. Recrystallize in ethanol to obtain the modified TPP ligand (TPP-TPy).

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4. Add aqueous solution of K2PtCl4 (5 mL) dropwise to the DMSO solution of TPP-TPy (5 mL) and stir for 12 h at 110  C. Add the mixture to concentrated HCl to precipitate the product. Redissolve the product in DMSO and add it dropwise to acetone (50 mL). Wash the product with diethyl ether and acetone twice to obtain the TPP+-modified platinum complex TPP+-PtII (a) [16]. 3.2 Synthesis of TPP+-PtII (b)

1. Add K2CO3 (3.37 g) into 2-(chloromethyl)pyridine hydrochloride (8.00 g) solution to adjust the pH to 7.0. Extract the reaction mixture with diethyl ether, and dry with anhydrous Na2SO4 and concentrate. Dissolve the residue (5.60 g) in 1,4-dioxane (25 mL) and add triphenylphosphine (11.54 g). Heat the mixture at 110  C, reflux for 12 h, and filter to obtain the solid product. Wash the solid with diethyl ether and dry under vacuum to get the modified ligand o-PPh3CH2PyCl. 2. Dissolve o-PPh3CH2PyCl (150 mg) in anhydrous N,Ndimethylformamide (DMF, 5 mL) and allow to react with AgNO3 (66 mg) under stirring for 5 h at 25  C. Centrifuge the reaction solution to obtain the yellow supernatant containing o-PPh3CH2PyNO3. 3. Stir cisplatin (150 mg) and AgNO3 (80 mg) in anhydrous DMF (3 mL) overnight in the dark at 45  C and obtain a pale yellow solution of cis-[Pt(NH3)2Cl(DMF)](NO3) after centrifugation. 4. Drop the above o-PPh3CH2PyNO3 solution into [cis-Pt (NH3)2Cl(DMF)](NO3) solution and stir in the dark at 55  C for 48 h. Filter the resulting golden solution and evaporate. Rinse the oily substance by dichloromethane (DCM), extract with hot methanol (100 mL), and concentrate the extract to 5 mL. Add extra diethyl ether to get a light yellow precipitate. Wash the precipitate with DCM and diethyl ether, and dry it in vacuum to obtain the final product TPP+-PtII (b) [17].

3.3 Synthesis of TPP+-PtIV (a)

1. Add hydrogen peroxide (30 wt%, 20 mL) to the suspension of cisplatin (400 mg) in H2O (12 mL) at 60  C. After 4 h, cool the bright yellow solution at room temperature overnight to afford yellow crystals. Filter the crystals and wash them with cold water to obtain oxoplatin. 2. Add EDC · HCl (211 mg) and NHS (127 mg) to the solution of (4-carboxybutyl)triphenylphosphonium bromide (433 mg) in acetonitrile (15 mL) and stir at room temperature for 12 h to get a colorless solution. Remove acetonitrile by rotary evaporation to yield a colorless raw product. Dissolve the product in DCM and wash it with water three times. Collect the organic layer and add anhydrous Na2SO4 to remove water. Finally, remove the solvent to gain the modified ligand TPP-NHS.

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3. Add a solution of TPP-NHS ester (194 mg) in anhydrous DMSO (5 mL) to the suspension of oxoplatin (100 mg) in anhydrous DMSO (10 mL) with vigorous stirring. Stir the mixture at 30  C for 72 h. Remove DMSO by addition of excessive diethyl ether. Extract the product with methanol and wash twice with methanol and ether. Dry the light yellow solid TPP+-PtIV (a) in vacuum [18]. 3.4 Synthesis of TPP+-PtIV (b)

1. Stir oxoplatin (50 mg) in DMF with (4-carboxybutyl)triphenylphosphonium bromide (200 mg), triethylamine (46 mg), and O-(benzotriazol-1-yl)-N,N,N0 ,N0 -tetramethyluronium tetrafluoroborate (TBTU, 144 mg) for 48 h. After filtration, collect the filtrate and remove DMF under high vacuum. 2. Add ethanol and water to the residue to gain the precipitation of desired product. Dissolve the crude product in methanol to obtain TPP+-PtIV (b) by multiple precipitation in diethyl ether [18].

3.5 Mitochondrial Uptake

1. Seed the cancer cells into a 10 cm petri dish and incubate overnight to 60–70% confluence. 2. Replace the cell culture medium with fresh growth medium and treat the cells with above mitochondrial-targeted platinum complex (see Subheadings 3.1–3.4, the same below) at the desired concentrations and 37  C for 24 h in an atmosphere of 5% CO2 and 95% air. 3. Collect the cells, suspend the cellular precipitate in mitochondrial isolation solution (1 mL), and cool on ice for 10 min. 4. Homogenize the cell suspension for 30 strokes using a tight pestle on ice and then centrifuge at 600  g and 4  C for 10 min (see Note 1). 5. Place the supernatant in a fresh tube and centrifuge again at 12,000 rpm (15,300  g) and 4  C for 15 min to obtain the mitochondrial deposition. 6. Digest the cell lysis solution by concentrated nitric acid (100 μL) at 95  C for 2 h, hydrogen peroxide (30%, 50 μL) at 95  C for 1.5 h, and concentrated hydrochloric acid (50 μL) at 37  C until the total volume is less than 50 μL. Add ultrapure water to each sample to reach 1 mL. 7. Test the Pt content in each sample by ICP-MS.

3.6 Determination of Mitochondrial Superoxide (mtSOX)

1. Seed cancer cells in a 6-well plate (Corning) at a density of 105 cells/mL and incubate overnight to 60–70% confluence. 2. Replace the cell culture medium with fresh growth medium, and incubate the cells with the complex at the desired concentrations at 37  C for 24 h in an atmosphere of 5% CO2 and 95% air.

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3. Wash the cells three times with PBS buffer and incubate with incomplete growth medium under 5 μM of mtSOX probe MitoSOX™ at 37  C for 10 min in situ (see Notes 2 and 3). 4. Trypsinize the cells, wash with PBS three times and resuspend in PBS (500 μL). 5. Analyze the cells on the BD FACSCalibur flow cytometer within 1 h. 3.7 Mitochondrial Membrane Potential (JC-1 Assay)

1. Seed cancer cells in a glass bottom cell culture dish (φ 2 mm, NEST) containing 1 mL of growth medium at 40% confluence. 2. Replace the cell culture medium with fresh growth medium and incubate the cells with the complex with desired concentrations at 37  C for 24 h. 3. Add the JC-1 working solution and incubate at 37  C for 20 min. Wash the cells thrice with JC-1 staining buffer before imaging (see Note 4). 4. Carry out the imaging by a confocal laser scanning fluorescence microscopy (Zeiss LSM710) with a 63 objective lens. Record the fluorescence of green channel (λex ¼ 488 nm, λem ¼ 510–545 nm) and red channel (λex ¼ 543 nm, λem ¼ 575–630 nm), respectively (see Fig. 1). Quantify the fluorescence intensities and correct total cell fluorescence (CTCF) values through ImageJ.

3.8 Mitochondrial Morphology

1. Plate cancer cells in 10 cm dishes and cultured at 37  C for 18 h. 2. Incubate the cells with indicated concentrations of complexes for 48 h, trypsinize, and collect the cells. 3. Fix the obtained pellets with 2.5% glutaraldehyde at 4  C overnight, wash the cells several times with PBS and further fix with 1% OsO4. 4. Dehydrate the samples using solutions of acetone (50%, 75%, 90%, and 100%) prior to impregnation in increasing concentrations (25%, 50%, 75%, and 100%) of resin in acetone over a period of 24 h. 5. Cut the cells into small segments with ultramicrotome, stain with 2% aqueous uranyl acetate and lead citrate. 6. Wash the sections with ultrapure water. 7. Observe the samples under transmission electron microscopy (JEOL JEM-1011) after drying (see Fig. 2).

3.9

mtDNA Damage

1. Seed cancer cells into 6-well plates, culture in cell culture medium with 10% (v/v) FBS at 37  C for 24 h.

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Fig. 1 Fluorescence changes of HeLa cells after treatment with the complex for 24 h and staining by JC-1 dye. JC-1 remains as monomers that emit green fluorescence when MMP is dissipated in apoptotic or abnormal cells, while assembles to form aggregates with red fluorescence when MMP is high in normal cells

Fig. 2 TEM images of mitochondria in A549 cells after treatment with TPP+-PtIV (b) for 24 h. The mitochondria in control group are identified with typical features, including the well-defined integral double membranes and regular cristae. The morphology of mitochondria in TPP+-PtIV (b)-group changed significantly, including the damage of mitochondria with distortion of cristae and partial or total cristolysis, even vacuoles

2. Replace the cell culture medium with fresh growth medium and incubate the cells with complexes on the desired concentrations at 37  C for 24 h. 3. Wash the attached cells twice with PBS (4  C), harvest by trypsinization (0.5 mL), and wash with PBS (1 mL). 4. Lyse the cell pallets in DNAzol reagent (1 mL), and extract the genomic DNA from the lysate with pure ethanol (0.5 mL) by incubating the sample at room temperature for 1–3 min. 5. Determine the amount of DNA with Nanodrop 1000 at 260 nm. Quantify the level of mtDNA damage in each tested

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region of the mitochondrial genome by comparing the relative amplification of two mtDNA fragments (long fragments and small ones) locating in the same mitochondrial genomic region, with the shorter fragments as internal normalization controls. 6. Perform the PCR using total DNA (5 ng, 1 μL), forward primer (1 μL), reverse primer (1 μL), SsoFast EvaGreen Supermix (5 μL), and nuclease-free water (2 μL, see Note 5). Conditions for the long fragments are 95  C for 10 min, followed by 39 cycles at 95  C for 10 s, 60  C for 10 s, and 72  C for 50 s. Perform the cycling for the short reaction at 95  C for 10 min, followed by 39 cycles at 95  C for 10 s, 62  C for 10 s, and 72  C for 10 s. 7. Calculate the mtDNA lesion using the reported methods: Lesion rate [lesion per 10 kb DNA] ¼ (1  2(ΔCq,longΔCq,short))  10,000 [bp]/size of long fragment [bp]. ΔCq,long ¼ Cq,sample  Cq,reference; ΔCq,short ¼ Cq,control  Cq,reference. 3.10 Transcription of Mitochondrial Genes

1. Seed cancer cells into 6-well plates, culture in cell culture medium with 10% (v/v) FBS at 37  C for 24 h. 2. Replace the cell culture medium with fresh growth medium and incubate the cells with the complex on the desired concentrations at 37  C for 24 h. 3. Wash the attached cells twice with PBS (4  C), add trizol reagent (1 mL), and keep in dark for 10 min. 4. Pipette the solution repeatedly and collect the suspension in 1.5 mL centrifuge tube. Add chloroform (200 μL) and shake for 30 s, and then leave the tube at room temperature for 5 min. 5. Centrifuge the solution at 12,000 rpm (15,300  g) for 15 min at 4  C, collect the upper water phase into a clean centrifuge tube, add isopropanol (500 μL) again and mix with the solution. Allow the solution to stand for 10 min, and then centrifugate at 12,000 rpm (15,300  g) and 4  C for 15 min to remove the supernatant. 6. Add ethanol (75%, 1 mL) and mix. Centrifuge the solution at 7500 rpm (5970  g) and 4  C for 5 min and remove the supernatant. Repeat the operation twice and dry the precipitation. 7. Add ultrapure water (50 μL) to dissolve the RNA precipitation. Determine the amount of RNA on Nanodrop 1000.

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8. Add 5 iScript reaction mix (4 μL), iScript reverse transcriptase (1 μL), RNA (1 μg), and a certain amount of ultrapure water to a centrifuge tube. Reverse-transcribed approximately 1 μg of total RNA to cDNA. 9. Analyze the expression of 13 mitochondrial code genome proteins by RT-qPCR. Perform the PCR by using cDNA (1 μL), forward primer (1 μL), reverse primer (1 μL), SsoFast EvaGreen Supermix (5 μL), and nuclease-free water (2 μL, see Note 5). The amplification program is 30 s at 95  C, followed by 49 cycles of 5 s at 95  C, and 5 s at 60  C. At the end of the amplification, assess the specificity of the gene by a melting curve between 65 and 95  C. Calculate the results according to the 2ΔΔCt method [see Subheading 3.9, step 7]. 3.11 Mitochondrial Bioenergetics 3.11.1 Oxygen Consumption Rate (OCR)

1. Seed cancer cells in XFe24-well cell culture plates at a density of 104 cells per well and then incubate for 24 h. 2. Replace the cell culture medium with fresh growth medium and treat the cells with the complex for 18 h. 3. Remove the cell culture medium and wash the cells with XF assay medium (see Subheading 2.3, item 2, same as below) thrice. Add XF assay medium (525 μL) to each well again (see Note 6). 4. Incubate the plate at 37  C in a CO2-free incubator for 1 h before the measurement. 5. Add oligomycin (1.0 μM, 75 μL), an inhibitor of ATP synthase complex, trifluorocarbonylcyanide phenylhydrazone (FCCP, 1.0 μM, 75 μL), an uncoupler of ATP synthesis, and a mixture (75 μL) of antimycin-A (1.0 μM), an inhibitor of complex III, and rotenone (1.0 μM), an inhibitor that prevents the transfer of electrons from the Fe–S center in complex I to ubiquinone, to A, B, and C holes, sequentially. 6. Determine OCR on a Seahorse XFe24 Cell Bioanalyzer (Seahorse Biosciences). Record the data during the measurement and analyze them using the average of four baseline rates and up to five test rates [19] (see Fig. 3).

3.11.2 Extracellular Acidification Rate (ECAR)

1. Seed cancer cells in XFe24-well cell culture plates at a density of 104 cells per well and incubate for 24 h. 2. Replace the cell culture medium with fresh growth medium and treat the cells with the complex for 18 h. 3. Remove the cell culture medium and wash the cells with XF assay medium (see Subheading 2.3, item 3, same as below) thrice. Finally, add XF assay medium (525 μL) in each well again (see Note 6).

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Fig. 3 (a) Overall mitochondrial OCR profiles of HeLa cells in response to the complex at 18 h. OCR for basal respiration ¼ OCRinitial  OCRantimycin A/rotenone, OCR for ATP production ¼ OCRbasal  OCRoligomycin, OCR for proton leak ¼ OCRoligomycin  OCRantimycin A/rotenone. (b) ECAR of HeLa cells in response to the complex at 18 h. ECAR for glycolysis ¼ ECARoligomycin  ECARglycose, ECAR for glycolytic capacity ¼ ECAR2-DG  ECARglycose, ECAR for glycolytic reserve ¼ ECAR2-DG  ECARoligomycin

4. Incubate the plate at 37  C in a CO2-free incubator for 1 h before the measurement. 5. Add glucose (10 mM, 75 μL), oligomycin (1 μM, 75 μL), and 2-DG (130 mM, 75 μL) to A, B, and C holes, sequentially. 6. Determine ECAR on a Seahorse XFe24 Cell Bioanalyzer (Seahorse Biosciences) and record the data during the measurement. Analyze the data using the average of four baseline rates and up to five test rates [19] (see Fig. 3). 3.12 Proteins Relevant to MitochondrionMediated Apoptosis

1. Seed the cancer cells into 10 cm petri dish and incubate overnight to 60–70% confluence. 2. Treat the cells with the desired concentration of drugs, collect and wash twice with ice-cold PBS. 3. Lyse the cell pellets in cell lysis buffer (100 μL) on ice for 30 min. Centrifuge the lysate at 12,000 rpm (15,300  g) and 4  C for 15 min to remove the cell debris (see Note 7). 4. Electrophorese the lysate (40–60 μg) on a 10–12% SDS-PAGE gel by Bio-Rad Mini-PROTEAN Tetra System (80 V, 20 min; 100 V, 1 h). 5. Transfer proteins to PVDF (Millipore, 0.22 μm) membranes in transfer buffer containing 0.033% SDS (90 V, 1.5 h) (see Notes 8 and 9). 6. Block the PVDF membranes at ambient temperature in blocking buffer for 1 h (see Note 10). 7. Incubate the membrane with monoclonal antibody (antiIMMT, Cyto c, PDK2, Bad, Bax, Bcl-2, caspase-3, caspase-9, p53, α-tubulin, etc.) at 4  C overnight (see Note 11).

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8. Wash the membranes with PBST for three times and incubate with the peroxidase-conjugated anti-rabbit IgG or anti-mouse IgG as secondary antibody in washing buffer at room temperature for 1 h (see Note 11). 9. Visualize the position of proteins by chemiluminescence HRP substrate (Millipore).

4

Notes 1. All the steps relating to mitochondrial separation should be carried out on ice or at 4  C, and the solutions should be precooled at 4  C. 2. Probe vials should be warmed to room temperature before opening. 3. The concentration of MitoSOX™ reagent working solution should not exceed 5 μM. 4. JC-1 (200) must be thoroughly dissolved and mixed with ultrapure water before adding JC-1 staining buffer (5). Preparing JC-1 staining buffer (1) and then adding JC-1 (200) will make JC-1 difficult to be fully dissolved and thus affect the subsequent detection. 5. The preparation of solutions in PCR experiments should be performed on ice. 6. In the Seahorse experiment, XF assay medium should be heated to 37  C in advance, and then corresponding drugs be added and pH be adjusted to 7.4. 7. All the lysed cell samples should be stored at 20  C. 8. The stacking position of sponge, filter paper (special filter paper for transfer film), transfer film, and gel should be checked carefully to ensure the correct transfer direction. 9. The relative sizes of sponge, filter paper (special filter paper for transfer film), transfer film, and gel should be examined thoroughly to avoid short circuit. 10. The membrane should be in contact with the blocking solution completely in order to avoid leaving the blocking solution for a long time. 11. All the antibodies were diluted with PBST. 12. Synthetic methods and the properties of the mitochondriontargeted platinum complexes may vary more or less; the above representative experimental procedures may need some modifications accordingly.

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Acknowledgments We acknowledge the National Natural Science Foundation of China (Grants 31570809, 21877059). References 1. Johnstone TC, Suntharalingam K, Lippard SJ (2016) The next generation of platinum drugs: targeted Pt(II) agents, nanoparticle delivery, and Pt(IV) prodrugs. Chem Rev 116:3436–3486 2. Deo KM, Ang DL, McGhie B et al (2018) Platinum coordination compounds with potent anticancer activity. Coord Chem Rev 375:148–163 3. Wang XY, Guo ZJ (2013) Targeting and delivery of platinum-based anticancer drugs. Chem Soc Rev 42:202–224 4. Wang XH, Wang XY, Guo ZJ (2019) Stimuliresponsive therapeutic metallodrugs. Chem Rev 119:1138–1192 5. Zhang W, Zhang SL, Hu XH et al (2015) Targeting tumor metabolism for cancer treatment: is pyruvate dehydrogenase kinases (PDKs) a viable anticancer target? Int J Biol Sci 11:1390–1400 6. Chipuk JE, Bouchier-Hayes L, Green DR (2016) Mitochondrial outer membrane permeabilization during apoptosis: the innocent bystander scenario. Cell Death Differ 13:1396–1402 7. Santo-Domingo J, Demaurex N (2010) Calcium uptake mechanisms of mitochondria. Biochim Biophys Acta (BBA) Bioenerg 1797:907–912 8. Youle RJ, Bliek AM (2012) Mitochondrial fission, fusion, and stress. Science 337:1062–1065 9. Martinou JC, Youle RJ (2011) Mitochondria in apoptosis: Bcl-2 family members and mitochondrial dynamics. Dev Cell 21:92–101 10. Souers AJ, Leverson JD, Boghaert ER et al (2013) ABT-199, a potent and selective Bcl-2 inhibitor, achieves antitumor activity while sparing platelets. Nat Med 19:202–208

11. Fulda S, Galluzzi L, Kroemer G (2010) Targeting mitochondria for cancer therapy. Nature 9:447–464 12. Chen LB (1988) Mitochondrial membrane potential in living cells. Annu Rev Cell Biol 4:155–181 13. Weinberg SE, Chandel NS (2015) Targeting mitochondria metabolism for cancer therapy. Nat Chem Biol 11:9–15 14. Zielonka J, Joseph J, Sikora A et al (2017) Mitochondria-targeted triphenylphosphonium-based compounds: syntheses, mechanisms of action, and therapeutic and diagnostic applications. Chem Rev 117:10043–10120 15. Guo Y, Guo ZJ, Wang XY et al (2019) Enhancing Cytotoxicity of a monofunctional platinum complex via a dual-DNA-damage approach. Inorg Chem 58:13150–13160 16. Wang K, Wang XY, Guo ZJ et al (2019) Restraining cancer cells by dual metabolic inhibition with a mitochondrion-targeted platinum (II) complex. Angew Chem Int Ed 58:4638–4643 17. Zhu ZZ, Guo ZJ, Wang XY et al (2019) Mitochondrion-targeted platinum complexes suppressing lung cancer through multiple pathways involving energy metabolism. Chem Sci 10:3089–3095 18. Jin SX, Guo ZJ, Wang XY et al (2018) Impact of mitochondrion-targeting group on the reactivity and cytostatic pathway of platinum (IV) complexes. Inorg Chem 57:11135–11145 19. Zhang J, Nuebel E, Koehler CM et al (2012) Measuring energy metabolism in cultured cells, including human pluripotent stem cells and differentiated cells. Nat Protoc 7:1068–1085

Chapter 31 In Silico Modeling of the Mitochondrial Pumping Complexes with Markov State Models Roger Springett Abstract The mechanism of proton pumping by the mitochondrial electron transport chain complexes is still enigmatic after decades of research. Recently, there has been interest in in silico Markov state models to model the mitochondrial pumping complexes at the microscopic level, and this chapter describes the methods of constructing and simulating such models. Key words Markov state models, Mitochondria, Proton pumping, Rate constants, Gillespie algorithm

1

Introduction The mitochondrial electron transport chain operates by Mitchell’s hypothesis of oxidative phosphorylation [1] in which redox free energy is first converted into a proton motive force (ΔP) by the three proton pumping complexes. The proton motive force is then used by the rotary ATP synthase and the ATP transport system to maintain the cytosolic phosphorylation potential far from equilibrium. The pumping complexes have been very amenable to study because the heme redox centers can be followed with optical spectroscopy [2], the iron sulfur (FeS) centers with electron paramagnetic resonance spectroscopy, and charge movement with timeresolved electrometry [3]. However, it has been 40 years since Mitchell’s hypothesis was accepted by the scientific community, 25 years since the first atomic resolution crystal structures of cytochrome oxidase [4] and the bc1 complex [5] were published, and 10 years for complex I [6], but the mechanism of proton pumping is still enigmatic. Currently missing is an in silico model that can provide a framework to understand the underlying principles used by the complexes to pump protons. Molecular dynamics is a popular method to model proton pumping function, particularly water

Volkmar Weissig and Marvin Edeas (eds.), Mitochondrial Medicine: Volume 2: Assessing Mitochondria, Methods in Molecular Biology, vol. 2276, https://doi.org/10.1007/978-1-0716-1266-8_31, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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and proton movement, but it cannot model electron transfer events or operate on the time scale of pumping. Markov state models are an alternative modeling paradigm, and several models have been published attempting to simulate complex I [7, 8], the bc1 complex [9–11], and cytochrome oxidase [12, 13] at the microscopic level. The goal of this chapter is to describe the methods of construction and simulation of Markov state models with an emphasis on the mitochondrial pumping complexes. The Ransac et al. model of the bc1 complex [9, 10] is used to illustrate the process.

2

Ransac Model of the bc1 Complex The bc1 complex operates via the modified Q cycle (Fig. 1) in which ubiquinol (UQH2) binds at the Qo center close to the P-side of the membrane. The two electrons are bifurcated, so that the first electron is passed to the iron sulfur center (FeS) in the iron sulfur protein (ISP), and the second is passed to low potential b-heme (bL). The ISP is mobile and is able to move between the Qo center (bL conformation) and c1 (c1 conformation) where the first electron can be transferred to heme c1 and then to cytochrome c (Cytc) that binds on the P-side of the membrane. The second electron is passed across the membrane to the high potential b-heme (bH) and then

Fig. 1 A cartoon of the bc1 complex showing the reaction sequence of the modified Q cycle. Electron transfers are shown in black, ISP movement in green, and substrate movement shown in gray

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used to reduce ubiquinone (UQ) bound at the Qi center to semiubiquinone (UQS) on the N-side of the membrane. This process is then repeated to provide a second electron to reduce UQS to UQH2 which is released into the membrane.

3

Markov State Models A state model is one in which the model exists in discrete states and transitions between states stochastically according to a set of rate constants that describe a set of reactions. A Markov state model is a state model that has no memory of previous states, and the probabilities that it will transition from one state to the next are only dependent on the current state and not the previous states it has visited. The Michaelis–Menten model of invertase [14] is an example of a very simple Markov state model. The states and elementary reactions of the model are shown in reaction 1 where the substrate (S) binds to an enzyme (E) to form the enzyme-substrate complex (ES). The bound substrate is converted to the product (P) to form the enzyme-product complex (EP), and then the product is released. ð1Þ In this example, the model can exist in three states (E, ES, and EP) with three elementary reactions connecting the states. The probability at any instant in time that it will transition to another state in an infinitesimal time interval of δt is given by kδt where k is the rate constant. For instance, when the model is in state EP, the probability of releasing the product and transitioning to E is k+3δt and for the product to revert to substrate to form ES is k2δt. The model is a Markov model because the transition probabilities are independent of the previous history: when the model is in state EP, the probability of it transitioning to state E or ES is independent of whether it was previously in state ES and the substrate converted to product or was in state E and the product bound. From a theoretical perspective, a Markov state model is a good model of an enzyme because an enzyme exists in different states, e.g., unbound, substrate bound, or product bound, with the enzyme transitions between states stochastically governed by thermal energy and the activation energy barriers, and the transition probabilities are independent of the previous history of the enzyme. The precise correspondence between the enzyme kinetics predicted by the model and those experimentally determined for invertase is evidenced that a Markov state models can be used to model enzyme function.

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Examining the chemistry of the invertase reaction, in which sucrose is hydrolyzed to glucose and fructose, immediately shows that reaction 1 is a simplification and that the EP state in reaction 1 actually has two products bound (glucose and fructose) which most likely can be released or bound independently (reaction 2). ð2Þ This is an example of granularity: how close the model must replicate the enzyme mechanism. This is particularly difficult to address for the conformational changes of an enzyme because molecular dynamics emphasizes that the protein conformation is a continuous variable, whereas a Markov state model has discrete states. This will be addressed in Subheading 9. Another difference between reactions 1 and 2 is that the former is a linear reaction mechanism, whereas the latter is branched. The complexity of the proton pumps means that the reaction mechanism will be highly branched, and this is contrary to the typical narrative describing the reaction mechanism (see the example in Subheading 2).

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States and Reactions The first task in developing a Markov state model is to define the states of the model. A rational approach is to define centers and the possible states of the centers based on the structure and function of the complex. The hemes and FeS center of the bc1 complex are redox centers which can be either oxidized or reduced. The Qo and Qi centers can either be empty or have UQH2, UQS, or UQ bound. Likewise, the Cytc binding site is a center which can either be empty or have reduced or oxidized Cytc bound. In the enzyme, the ISP moves between the c1 and the bL conformation, and this can be captured in the model as conformational center which has either the c1 or bL conformation. The state of the model is described by a state vector which describes the state of each center. For example, the centers in the state vector of the Ransac model are bL, bH, FeS, c1, Qo, Qi, Cytc, and ISP. The model has 2  2  2  2  4  4  3  2 ¼ 1536 states, and a typical state vector could be described as for the state with bL and bH reduced, FeS and c1 oxidized, the Qo site bound with UQH2, the Qi site empty, reduced Cytc bound at the Cytc center, and the ISP is in the bL conformation. The Ransac model combined the electron and proton transfer in the oxidation of UQH2 and so only needed to define UQH2,

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UQS, and UQ bound at the Qo and Qi centers. A more granular model could separate the electron and proton transfers and define all the oxidation intermediates. The next step is to define the rate constants connecting the states in the model. The large number of states of a typical model means that there are a very large number of rate constants which cannot be hand coded and must be generated automatically from a simpler and more functional definition of an elementary reaction. For instance, the electron transfer reaction from bL to bH in the bc1 complex connects states with bL reduced and bH oxidized to one with bL oxidized and bH reduced with the other centers not changing. In terms of state vectors, the initial and final states of the reaction could be described as and , respectively, where the star means any value for the center that does not change in the final state. This reaction connects 2  2  4  4  3  2 ¼ 384 pairs of states in the Ransac model. The 16 reactions of the Ransac model and their initial and final state vectors are given in Table 1. The large number of reactions in the model allows any state in the model to transition to multiple other states, so that the reaction sequence is highly branched.

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Estimation of Rate Constants Each reaction has a forward and reverse rate constants (kf and kr, respectively) which are related to the ΔG0 of the reaction by:
 k ΔG 0 ¼ kB T ln f ð1Þ kr where kB is Boltzmann’s constant and T is the absolute temperature in Kelvin. For one-electron transfers, the ΔG0 is given by:   ð2Þ ΔG 0 ¼  E am  E dm where Ema and Emd are the midpoint potentials of the electron acceptor and donor, respectively. For intra-protein proton transfers, the ΔG0 is given by:   ð3Þ ΔG 0 ¼ kB T ln ð10Þ pK a a  pK a d where pKaa and pKad are the pKa of the acceptor and donor site respectively. Where the proton transfer is a proton binding from the bulk media, the same expression can be used with the pKa of the bulk set to zero. It is often more convenient to use the chemical potential of protons (μH ¼ kBTln(10)pH) and the chemical potential of association (μHa ¼ kBTln(10)pKa) instead of the pH and pKa, respectively. In this case, the ΔG0 for proton transfer is:

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Table 1 The 16 reactions of the Ransac model and their initial and final state vectors Reaction

Initial state

Final state

MB UQH2 at Qo



MB UQ at Qo



ET UQH2 to FeS



ET UQS to FeS



ET UQH2 to bL



ET UQS to bL



ET bL to bH



ET bH to UQ at Qi



ET bH to UQSi



MB UQH2 at Qi



MB UQ at Qi



PM Rieske bL to c1



ET FeS to c1



PB reduced Cytc



PB oxidized Cytc



ET c1 to Cytc



MB molecular binding, ET electron transfer, PM protein movement, and PB protein binding. The centers of the state vectors are (bH, bL, FeS, c1, Qo, Qi, Cytc, ISP) with O oxidized, R reduced, E empty, B bL conformation, C c1 conformation

  ΔG 0 ¼ þ μHaa  μHda

ð4Þ

At the first sight, the large number of rate constants, which are typically difficult to measure experimentally, mean that the model has numerous adjustable parameters which reduce its predictive power. However, many rate constants can be estimated. For instance, the rate constants for electron transfer through a protein can be estimated from the Moser–Dutton ruler [15] in which the rate constant in the exergonic direction is given by:  2 ΔG 0  λ log ðkex Þ ¼ 15  0:6D  3:1 ð5Þ λ where D is the edge to edge distance in Å of the delocalized electron ring around the redox center and λ is the reorganization energy in eV, generally assumed to be 0.7 eV. This only requires the ΔG0, which is usually well known, and the distance, which can be obtained from the atomic structure. The rate constant in the endergonic direction can be calculated from the ΔG0 and the rate

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constant in the exergonic direction using Eq. (1). The sensitivity of the rate with separation is used by the bc1 complex to prevent short circuits: the FeS center is 8.9 Å from the Qo center when the ISP is in the bL position allowing very rapid electron transfer from UQH2 to FeS, but FeS is more than 28 Å from c1 in this conformation preventing further transfer to c1 at significant rates. When the ISP moves to the c1 position, the situation is reversed and the FeS center is now 11.1 Å from c1 but too far from the ubiquinol intermediates at Qo for significant electron transfer. To the first approximation, substrate binding can be assumed to be diffusion limited [16], so that the on rate constant (kon) is 109 to 1010 M1 s1 for small molecules. The off rate constant (koff) can then be calculated from Kd ¼ koff/kon. The concentrations of NADH in the matrix and UQ/UQH2 in the membrane are in the millimolar range [17], so the forward rates will be >106. This is much larger than the turnover number, and the substrate binding reactions are likely to operate close to equilibrium and unlikely to be kinetically limiting. However, the concentration of free protons in the matrix is only 108 M when the matrix has a pH of 8.0 giving diffusion-limited on-rates of 101 to 102 per second. This is slower than typical turnover rates of the bc1 complex (150e/s) and CytOx (40e/s) [17]. However, the protons are strongly buffered by inorganic phosphate, citrate, and bicarbonate and other matrix small molecules, so that concentration of exchangeable protons is in the millimolar range compared to the nanomolar range for free protons. Furthermore, proton binding can occur on disassociation of a water molecule at the binding site and ejection of the hydroxyl. These effects possibly explain how proton binding can be much faster than diffusion rates estimated using the free H+ concentration. Using a very simple model, Minneart [18] estimated the kon and koff of Cytc binding to CytOx to be 40  106 M1 s1 and 1200 s1, respectively, giving a Kd of 30 μM. The applicability of this model to CytOx has recently been questioned, and a review of the literature suggests that the kon is an order of magnitude greater and the Kd closer to 1 μM [13]. Proton transfers across a hydrogen bond are very fast and have been estimated to occur at a rate of 1011 to 1013 s1 [19]. There is no equivalent to the Moser–Dutton rule for intra-protein proton transfers, and the rates must be estimated to fit experimental data.

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The Membrane Potential and Charge Transfer Reactions The membrane potential across the inner membrane (ΔΨ ) is the result of charge separation across the dielectric membrane. For a simple homogeneous dielectric, the charge separation generates an electric field (E) within the membrane given by E ¼ ΔΨ /D, where

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D is the dielectric thickness. The free energy change for a charge q moving a distance d parallel to this electric field is given by ΔG ¼ qEd, so that ΔG ¼ αqΔΨ , where α is the fractional distance perpendicular to the membrane in the direction from the P-side to the N-side. The situation is more complicated for a protein which is likely to have a heterogeneous relative permittivity, and so α becomes the fractional dielectric distance, that is, the distance weighted by the relative permittivity along the path. A reasonable approximation where no experimental data is available is to assume that the fractional dielectric distance is equal to the fractional physical distance measured from the protein structure. This term must be added to the ΔG0 of an electron or proton transfer reaction, so that the ΔG0 for electron and proton transfers becomes:   ð6Þ ΔG 0 ¼  E am  E dm  αqΔΨ   ð7Þ ΔG 0 ¼ þ μHaa  μHda  αqΔΨ where q is 1 for an electron and +1 for a proton. This additional contribution to the ΔG0 will change the activation barrier and the rate constants of the reaction. In the absence of knowing precisely how the activation barrier will be affected, this term can be equally split between the forward and reverse rate constants, so they become: k0f ¼ kf e þ1=2αqΔΨ =kB T k0r ¼ kr e 1=2αqΔΨ =kB T

ð8Þ

where kf and kr are the rate constants in the absence of a membrane potential.

7

Thermodynamics and Interactions A major difference between the model and the enzyme is that the model uses forward and reverse rate constants to define the ΔG0 between states, whereas each state has a defined energy in the enzyme and the rate constants are determined by the ΔG0 and the activation energy (ΔG{) between states. The latter ensures that the energy is a state function and that the ΔG0 between any two states is independent of the path taken between the states. It is possible to define the rate constants for reactions between states in the model such that the ΔG0 between two states at the ends of two separate paths is different. If this occurs, the model breaks the second law of thermodynamics, and a thermodynamically inconsistent model cannot accurately simulate the enzyme. If there are no interactions between centers, then a model will generally be thermodynamically consistent but, when there are interactions, the rate constants must be implemented very carefully.

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For instance, there is anti-cooperativity between the bL and bH hemes in the bc1 complex [20], so that the midpoint potential of the bL heme depends on whether the bH heme is oxidized or reduced, and vice-versa. The origin of this anti-cooperativity is likely to be the electrostatic repulsion between the two hemes, which raises the energy of the state when both the hemes are reduced. This means that the rate constants for transfer of an electron between UQH2 at the Qo center and bL will depend on the oxidation state of bH and the rate constants for the electron transfer between bH and UQ or UQS at the Qi center will depend on the oxidation state of bL. The model will become thermodynamically inconsistent if the rate constants for these reactions are not specified very carefully. Another example is that the structure of the bc1 complex suggests that a hydrogen bond will form between UQH2 bound at the Qo center and the ISP [21]. This will affect the Kd, ΔG0, and rate constants of UQH2 binding depending on whether the ISP is in the c1 or bL conformation as this hydrogen bond can only form in the latter case. Furthermore, it will also affect the rate constants of ISP movement because the ΔG0 of this reaction will change depending on the intermediate bound at the Qo center. Interactions will be an important feature of proton pumping models because it is likely that these interactions facilitate the coupling of electron and proton transfers. In particular, the mechanism of coupling in CytOx is thought to be electrostatic in origin [22] such that the charge from the pump proton affects the midpoint potentials of the hemes changing the electron transfer equilibrium, and the charge from the electrons affect the pKa’s of the proton binding sites changing the proton-transfer equilibrium [23].

8

Simulations The numerical model can be simulated deterministically by using either coupled ordinary differential equations (ODE) or stochastically by using the Gillespie algorithm [24]. The ODE approach assembles the chemical master equation (CME) to calculate the time-dependent probability of finding an individual enzyme of the reaction mixture in a particular state (Pσ) where σ is the state. This probability is related to the concentration of enzymes in state σ (Cσ) by Pσ ¼ Cσ/CT, where CT is the concentration of the enzyme in the reaction mixture. The chemical master equation is a series of linear equations relating the rate of change in the probability of being in each state to the probability of all the states via a set of rate constants. It has the form:

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d dt

2

P1

3

6 7 6 P2 7 6 7 7 6 P 3 6 7 6 7 4 ⋮ 5 PN 2 P  kn,1 6 k 6 2,1 6 6 ¼ 6 k3,1 6 ⋮ 4 kN ,1 3 P1 7 6 6 P2 7 7 6 7 6 6 P3 7 7 6 4 ⋮ 5 PN 2

3

k1,3



k1,N



k2,N

k4,1 ⋮

k2,3 P  kn,3 ⋮

 ⋱

kN ,2

kN ,3



k3,N ⋮ P  kn,N

k1,2 P  kn,2

7 7 7 7 7 7 5

ð9Þ where N is the number of states, the sums are over all states n, and kr,c is the rate constant of the reaction which links states r and c. The rate constant is the kf of the reaction if state r is the reactant and state c is the product of the reaction, and it is the kr if vice-versa. Note that kn,n is zero because no reaction has the same state as reactant and product. Many of the off-diagonal elements are also zero for a large model because there are many pairs of states not linked by reactions. The chemical master equation can be written in matrix form as: b dP bP b ¼K dt

ð10Þ

b is a column matrix of probabilities and K b is the rate where P b constant matrix. The rows of K sum to zero, so that the determib is zero. The physical meaning of this can be understood nant of K by summing the linear equations of Eq. (9) where the left-hand side would be the rate of change of the sum of all the probabilities. As the probabilities must sum to 1, the left-hand side is zero and hence the right-hand side must also be zero for any set of state probabilities. For very simple models, the CME can be solved analytically, but the solution can be very complex (see [13] for the analytic solution of a six state model), but is usually solved numerically. The time evolution of the CME can be solved by the finite difference method where the probabilities of the states after some time

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b ðt þ δt Þ , is related to the probabilities before the step, step δt, P b ðt Þ, by. P b ðt þ δt Þ ¼ P b ðt Þ þ K bP b ðt Þδt P

ð11Þ

The step size must be very small compared to the fastest reaction to ensure the finite difference is a good approximation. The CME can also be solved in the steady state in which the left-hand side of Eq. (9) is zero. The CME then provides only N  1 equations (the final equation is equal to the sum of the other equations) and so cannot be used directly to solve for the N probabilities, and an additional equation is needed. This last equation can be the constraint that the sum of the probabilities of all the states must be 1. This allows an N  N matrix to be constructed of the form: 2 3 2 P 3  kn,1 0 k1,2 k1,3    k1,N P 6 7 6 7  kn,2 k2,3    k2,N 7 6 0 7 6 k2,1 6 7 6 7 P 6 0 7 ¼ 6 k3,1 k4,1  kn,3    k3,N 7 6 7 6 7 6 7 6 7 ⋮ ⋮ ⋮ ⋱ ⋮ 5 4⋮5 4 1 1 1 1  1 2 3 P1 6 7 6 P2 7 6 7 7 6 ð12Þ 6 P3 7 6 7 4 ⋮ 5 PN and the probabilities solved for by matrix inversion. Typically, an experimental technique does not measure the state probabilities themselves but rather measures the oxidation state of the redox centers or the rate of consumption or production of metabolites. The probability that a redox center is reduced can be calculated by summing the probabilities of all the states which have that center reduced. Similarly, the probability that a ubiquinone intermediate is present in the Qo or Qi center can be calculated from the sum of the probabilities of states with the intermediate at the center. The net metabolite flux, Jn, through a particular reaction can be calculated from: X kf P i  kr P f ð13Þ Jn ¼ where the sum is over all the pairs of states the reaction connects, and Pi and Pf are the probabilities of the pairs of initial and final states, respectively. Solving the CME numerically is an excellent approach for small models but impractical for large models due to the size of the matrix. For instance, the Ransac model has 1536 states and requires

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a matrix of 18 megabytes, assuming each matrix element is a double precision floating point number. This is quite feasible for a modern desktop PC but modeling the dimer would require a model of 1536  1536 states and a matrix of 40.5 terabytes. The Gillespie algorithm [24] is an alternative simulation method that does not require large quantities of memory. It was originally designed to follow chemical reactions where there are a finite number of reactant molecules, but it is also suited to follow a single enzyme as it passes through its possible states performing catalysis. The simulation starts with the enzyme in an initial state and calculates the dwell time and subsequent state based on the rate constants and two random numbers. As such it is a stochastic method, and no two simulations will produce precisely the same time evolution. This is exactly the way an individual enzyme turns over and the Gillespie algorithm provides the framework in which to explore how catalytic function emerges from the enzyme structure. The algorithm is very simple to implement. First, the reactions of the model are split into a list of all the possible half-reactions (the forward half-reaction and the reverse half-reaction) each with a single rate constant. This list is then parsed to determine which reactions are possible from the current state and the rate constants of all the possible half-reactions are summed to give the total relaxation rate (Σk) from the current state. A random number between 0 and 1, R1, is created and the dwell time set to ln (R1)/Σk. A second random number between 0 and 1, R2, is generated, and the list of half-reactions is parsed again to find which reaction spans R2Σk in the summation (see Fig. 2 for a graphical representation of the reaction choice). This reaction is chosen and executed to give the next state. This process is then repeated to create the time evolution of a single enzyme. If this process were repeated for an infinite number of enzymes, then the averaged data would precisely reproduce the time evolution simulated using the chemical master equation. For finite number of enzymes, the data contains stochastic noise which can be reduced by increasing the number of simulations; typically 104 to 106 simulations are required to calculate a time evolution with good signal to noise ratio.

Fig. 2 Graphical example of how a reaction is chosen with the Gillespie algorithm. Five reactions are available to the state with rate constants k1, . . ., k5 as indicated by the length of the bar. Σk is the sum of these constants, and, in this case, R2Σk chooses reaction 2

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Enzyme catalysis is an ergodic process in that the probability of a single enzyme in an infinite pool of catalyzing enzymes being in a particular state at an instant in time is equal to the probability that a single enzyme will be in the same state when sampled at random over an infinite period of time. In essence, each enzyme passes through all its possible states over time but spends longer in some states than others depending on the rate constants. This property allows the steady state of enzymes in a reaction mixture to be calculated from the time evolution of a single enzyme over a long period of time. Typically, the model must be followed for 107 reactions to give an estimate of the steady state and 109 reactions for publication quality data. The oxidation state of redox centers must be calculated during the simulation by summing the time that the model dwells with the redox center reduced and then normalizing to total time of the simulation. The flux through the reaction pathway can be calculated by counting the number of times a particular reaction was executed and normalizing to the simulation time.

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Protein Conformation Conformational changes of the pumping complexes are likely to prove critical to the proton pumping mechanism. The pumping by the membrane domain subunits of complex I is thought to undergo conformational changes coupled to the reduction of UQ [25–27], the ISP of the bc1 complex moves by tethered diffusion from the bL conformation to the c1 conformation as part of the electron transfer process [28, 29], and helix-X of CytOx subunit I has been found to unwind under certain conditions with a concomitant rotation of the heme a farnesyl side chain [30, 31]. Molecular dynamics highlight that the protein is in constant motion, so the conformational state of the protein is a continuous variable of very high dimensionality rather than the discrete steps used by a Markov state model. The movement of a peripheral residue can be expected to have little effect on catalysis, whereas certain movements will be critical. These important movements can be projected onto one or more intuitive variables, such as the diffusion path of the ISP, and the movement discretized [32]. The mitochondrial ADP/ATP carrier cycles between conformations in which the central substrate binding site is made accessible to the cytosolic side, to one in which access to the binding site is blocked to both sides, and to one where the binding site is accessible to the matrix made. These continuous conformational changes were modeled as 21 steps, and the simulations were able to reproduce the kinetic parameters of a series of mutants with good quantitative accuracy [33]. While the rate constants and free energy profile of this conformational change were estimated in that

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study, in the future, it would be possible to calculate them from molecular dynamic simulations [32]. Such profiles have been estimated for the movement of the ISP [29] and binding of ATP to the ADP/ATP carrier [34]. References 1. Mitchell P (1979) Keilin’s respiratory chain concept and its chemiosmotic consequences. Science 206(4423):1148–1159 2. Chance B, Williams GR (1956) The respiratory chain and oxidative phosphorylation. Adv Enzymol Relat Areas Mol Biol 17:65–134 3. Verkhovsky MI et al (2001) Charge translocation coupled to electron injection into oxidized cytochrome c oxidase from Paracoccus denitrificans. Biochemistry 40(24):7077–7083 4. Iwata S et al (1995) Structure at 2.8 A resolution of cytochrome c oxidase from Paracoccus denitrificans. Nature 376(6542):660–669 5. Xia D et al (1997) Crystal structure of the cytochrome bc1 complex from bovine heart mitochondria. Science 277(5322):60–66 6. Efremov RG, Baradaran R, Sazanov LA (2010) The architecture of respiratory complex I. Nature 465(7297):441–445 7. Ransac S, Arnarez C, Mazat JP (2010) The flitting of electrons in complex I: a stochastic approach. Biochim Biophys Acta 1797 (6-7):641–648 8. Ransac S, Heiske M, Mazat JP (2012) From in silico to in spectro kinetics of respiratory complex I. Biochim Biophys Acta 1817 (10):1958–1969 9. Ransac S, Parisey N, Mazat JP (2008) The loneliness of the electrons in the bc1 complex. Biochim Biophys Acta 1777(7-8):1053–1059 10. Ransac S, Mazat JP (2010) How does antimycin inhibit the bc(1) complex? A part-time twin. Biochim Biophys Acta 1797 (12):1849–1857 11. Kim N, Ripple MO, Springett R (2012) Measurement of the mitochondrial membrane potential and pH gradient from the redox poise of the Hemes of the bc1 complex. Biophys J 102(7):1194–1203 12. Kim N, Ripple MO, Springett R (2011) Spectral components of the alpha-band of cytochrome oxidase. Biochim Biophys Acta 1807 (7):779–787 13. Rocha M, Springett R (2018) Electron transfer between cytochrome c and the binuclear center of cytochrome oxidase. J Theor Biol 460:134–141

14. Michaelis L, Menten ML (1913) Die Kinetik der Invertinwirkung. Biochem Z 49:333–369 15. Moser CC et al (2006) Electron tunneling chains of mitochondria. Biochim Biophys Acta 1757(9–10):1096–1109 16. Alberty RA, Hammes GG (1958) Application of the theory of diffusion-controlled reactions to enzyme kinetics. J Phys Chem 62 (2):154–159 17. Rocha M, Springett R (2019) Measuring the functionality of the mitochondrial pumping complexes with multi-wavelength spectroscopy. Biochim Biophys Acta Bioenerg 1860 (1):89–101 18. Minnaert K (1961) The kinetics of cytochrome c oxidase. I. the system: cytochrome c-cytochrome oxidase-oxygen. Biochim Biophys Acta 50:23–34 19. Victoria D, Burton R, Crofts AR (2013) Role of the -PEWY-glutamate in catalysis at the Q (o)-site of the Cyt bc(1) complex. Biochim Biophys Acta 1827(3):365–386 20. Shinkarev VP, Crofts AR, Wraight CA (2001) The electric field generated by photosynthetic reaction center induces rapid reversed electron transfer in the bc1 complex. Biochemistry 40 (42):12584–12590 21. Link TA (1997) The role of the ’Rieske’ iron sulfur protein in the hydroquinone oxidation (Q(P)) site of the cytochrome bc1 complex. The ’proton-gated affinity change’ mechanism. FEBS Lett 412(2):257–264 22. Rich PR et al (1986) Coupling of charge and proton movement in cytochrome c oxidase. Biochim Biophys Acta 1275:91–95 23. Belevich I et al (2007) Exploring the proton pump mechanism of cytochrome c oxidase in real time. Proc Natl Acad Sci U S A 104 (8):2685–2690 24. Gillespie DT (1977) Exact stochastic simulation of coupled chemical-reactions. J Phys Chem 81(25):2340–2361 25. Efremov RG, Sazanov LA (2012) The coupling mechanism of respiratory complex I—A structural and evolutionary perspective. Biochim Biophys Acta 1817(10):1785–1795

Modeling the Mitochondrial Pumps 26. Efremov RG, Sazanov LA (2011) Structure of the membrane domain of respiratory complex I. Nature 476(7361):414–420 27. Brandt U (2011) A two-state stabilizationchange mechanism for proton-pumping complex I. Biochim Biophys Acta 1807 (10):1364–1369 28. Zhang Z et al (1998) Electron transfer by domain movement in cytochrome bc1. Nature 392(6677):677–684 29. Izrailev S et al (1999) Steered molecular dynamics simulation of the Rieske subunit motion in the cytochrome bc(1) complex. Biophys J 77(4):1753–1768 30. Ishigami I et al (2017) Crystal structure of CO-bound cytochrome c oxidase determined by serial femtosecond X-ray crystallography at

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room temperature. Proc Natl Acad Sci U S A 114(30):8011–8016 31. Shimada A et al (2017) A nanosecond timeresolved XFEL analysis of structural changes associated with CO release from cytochrome c oxidase. Sci Adv 3(7):e1603042 32. Prinz JH et al (2011) Markov models of molecular kinetics: generation and validation. J Chem Phys 134(17):174105 33. Springett R et al (2017) Modelling the free energy profile of the mitochondrial ADP/ATP carrier. Biochim Biophys Acta 1858 (11):906–914 34. Dehez F, Pebay-Peyroula E, Chipot C (2008) Binding of ADP in the mitochondrial ADP/ATP carrier is driven by an electrostatic funnel. J Am Chem Soc 130 (38):12725–12733

Chapter 32 Monitoring the Mitochondrial Presequence Import Pathway In Living Mammalian Cells with a New Molecular Biosensor Maxime Jacoupy, Emeline Hamon-Keromen, and Olga Corti Abstract Most mitochondrial proteins are encoded by the nuclear genome, synthesized in the cytosol, and imported into the organelle. Mitochondrial protein import is therefore vital for the maintenance of mitochondrial function and cell survival. Alterations in this process are suspected to contribute to various diseases, including neurodegenerative disorders, such as Alzheimer’s disease and Parkinson’s disease. Our understanding of the cytosolic signaling mechanisms and posttranslational modifications regulating the mitochondrial import process is still in its infancy and hampered by the lack of tools for its dynamic assessment in cells. We recently engineered an inducible molecular biosensor for monitoring one of the main mitochondrial import routes, the so-called presequence pathway, using a quantitative luminescence-based readout. Here, we provide basic guidelines for using this probe in common cell types of general use in the scientific community: HEK293T cells, human fibroblasts, and mouse primary neurons. These guidelines can serve as a starting point for the development of more elaborated protocols for the dynamic investigation of the presequence import pathway and its regulation in relevant physiological and pathological conditions. Key words Biosensor, Mitochondrial protein import, Presequence pathway, TOM machinery, Bioluminescence assay

1

Introduction Mitochondria exert crucial functions in metabolism, the production of ATP, cellular signaling, the response to stress, and the control of apoptosis. They originated from the incorporation by an ancestor eukaryotic host cell of a prokaryote related to α-proteobacteria, over 1.5 billion years ago [1]. Virtually all their genetic information was transferred to the nuclear genome during evolution. In humans, only 13 of the over 1500 proteins are encoded by the mitochondrial genome. Mitochondrial proteins encoded by nuclear genes and synthesized by cytosolic ribosomes

Maxime Jacoupy and Emeline Hamon-Keromen contributed equally to this work. Volkmar Weissig and Marvin Edeas (eds.), Mitochondrial Medicine: Volume 2: Assessing Mitochondria, Methods in Molecular Biology, vol. 2276, https://doi.org/10.1007/978-1-0716-1266-8_32, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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harbor specific signals that target them to receptors of the outer mitochondrial membrane (OMM). From there, they reach the appropriate mitochondrial subcompartment through five major import pathways [2–5]. Nearly two thirds of all mitochondrial proteins are translocated into the organelle by an N-terminal mitochondrial targeting signal (MTS), via the so-called presequence pathway [6]. The MTS is recognized by the TOM20 and TOM22 receptors [7, 8] of the translocase of outer mitochondrial membrane (TOM) and directs the transfer of the protein across the translocation channel, TOM40 [3, 9]. The protein is then pulled into the matrix through the TIM23 channel of the presequence translocase of the IMM (TIM23 complex). This process depends on the mitochondrial transmembrane potential (Δψmit) [10–14] and the presequence translocase-associated motor (PAM), including the ATP-driven mitochondrial heat shock protein 70 (mtHsp70). The protein is then generally processed by the matrix mitochondrial processing peptidase MPP [3, 15, 16], which removes the MTS, and by other peptidases, before being folded into its mature form with the help of mtHsp70 and other chaperones. Mitochondrial protein import has emerged in recent years as a process with remarkable plasticity in response to changes in metabolic requirements, stress, and disease [17]. Despite these advances, relatively little is known about the signaling cascades and cytosolic mechanisms regulating mitochondrial protein import in mammalian cells. The study of such mechanisms has been hampered by the lack of tools for the assessment of mitochondrial protein import in living cells. We recently developed a novel chemogenetic tool for assessing the presequence import pathway [18], exploiting the properties of the Renilla reniformis green fluorescent (RGFP) and luciferase (Rluc) proteins. In this anthozoan organism, bioluminescence is generated by a high-efficiency resonance energy transfer process involving interaction between RGFP and Rluc and conversion of the blue light emitted by the excited Rluc substrate coelenterazine (CLZ) into green light. This process can be reproduced in mammalian cells expressing a fusion construct between RGFP and Rluc; it is most efficient when the RGFP moiety is placed at the N-terminus of the fusion protein whereas it is inhibited by short N-terminal extensions [19]. In addition to the shift in emission wavelength, the interaction between RGFP and Rluc is associated with a strong cooperative effect, leading to a 40-fold increase in the intensity of the bioluminescent signal in the presence of low-quantum yield Rluc substrates, such as CLZ400A. Based on these principles, we designed two inducible modular biosensors (Probes 1 and 2) targeted to mitochondria by a classical MTS, predicted to yield a strong bioluminescent signal in the presence of CLZ400A only after import and the subsequent

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proteolytic removal of the MTS in the mitochondrial matrix [18]. Each probe consists of (1) the N-terminal cleavable MTS from the human dihydrolipoamide dehydrogenase (DLD), followed by (2) an RGFP-Rluc fusion separated by a short linker region containing a cMyc-tag, and (3) a C-terminal conditional FKBP-based destabilizing domain (DD), targeting the probe for proteasomal degradation under basal conditions, and stabilizing it in the presence of the small molecule Shield1. Probe 2 also contains a PEST degradation motif (rich in proline (P), glutamic acid (E), serine (S), and threonine (T)), as a means of optimizing the signalto-noise ratio and limiting potential toxicity for specific applications. We also generated a cytosolic control probe based on the backbone of Probe 1 but lacking the MTS (Probe 3). The validation of these tools has been described in [18]. Here, we provide basic guidelines for using these probes in three cell types (HEK293T cells, human fibroblasts, and mouse primary neurons), as a starting point for developing more elaborated protocols adapted to the users’ models of interest and specific biological questions.

2

Materials

2.1 Recombinant Vectors

See Fig. 1 for a graphical representation of the vectors.

2.1.1 pCI-Neo Mammalian Expression Vectors Encoding Probes 1, 2, and 3

1. pCI-Neo-Probe 1 (MTS—RGFP—cMyc-tag—Rluc—DD).

2.1.2 Recombinant Lentiviral Vector Encoding Probe 1

1. rLV-EF1-Probe 1 (MTS—RGFP—cMyc-tag—Rluc—DD) (see Note 1).

2.2 Materials and Reagents

1. Neon Transfection System, Invitrogen, or an equivalent device.

2.2.1 Equipment and Cell Culture Material

2. pCI-Neo-Probe 2 (MTS—RGFP—cMyc-tag—Rluc—DD— PEST). 3. pCI-Neo-Probe 3 (RGFP—cMyc-tag—Rluc—DD).

2. SpectraMax i3x microplate reader, Molecular Devices, or a similar device recording bioluminescent and fluorescent signals (see Note 2). 3. Black 96-well cell culture plates, coated with poly-D-lysine, with clear bottom (Greiner Bio-One 655,946, or equivalent); 384-well plates can also be used (see Note 3). 4. Multichannel pipettes (8 or 12 channels) and corresponding reagent reservoirs.

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Fig. 1 Mammalian expression plasmids and recombinant lentiviral vector for monitoring mitochondrial import through the presequence pathway in mammalian cells. (a–c) Maps of the mammalian pCI-Neo vectors encoding Probes 1–3 showing the domain composition of each probe. (d) Map of recombinant lentivirus encoding Probe 1 under control of the house-keeping EF1-α promoter. MTS: Mitochondrial Targeting Sequence, RGFP: Green Fluorescent Protein from Renilla reniformis, Rluc: luciferase from Renilla reniformis, DD: FKBP-based destabilizing domain, PEST: destabilizing motif rich in proline (P), glutamic acid (E), serine (S), and threonine (T). All the maps have been designed using the SnapGene software (Insightful Science; https:// snapgene.com)

2.2.2 Cell Culture Media, Buffers, Reagents

1. B-27 supplement (50, Gibco). 2. Dulbecco’s Phosphate-Buffered Saline without calcium and magnesium (DPBS, Gibco). 3. Dulbecco’s Modified Eagle Medium with high glucose (4.5 g/L), GlutaMAX supplement, pyruvate (DMEM-GlutaMAX, Gibco). 4. Fetal bovine serum (FBS). 5. L-Glutamine (200 mM, 100, Gibco). 6. Hank’s Balanced Salt Solution without calcium and magnesium (HBSS). 7. HEPES 1 M. 8. Neurobasal A medium (Gibco).

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9. Opti-MEM (Gibco). 10. Penicillin/Streptomycin (Gibco). 11. Trypsin-EDTA (0.05%, 1, Gibco). 2.2.3 Transfection Reagents

1. Lipofectamine 2000 (Invitrogen). 2. Lipofectamine RNAiMax (Invitrogen). 3. Neon™ Transfection System 100 μL Kit (Invitrogen).

2.2.4 Chemical Compounds

1. Carbonyl cyanide 3-chlorophenylhydrazone (CCCP, SigmaAldrich) (see Note 4). 2. Coelenterazine 400A (CLZ400A, Santa Cruz) (see Note 5). 3. Shield1 (0.5 mM, Takara) (see Note 6).

2.2.5 Immunocytochemistry

1. Normal Goat Serum (NGS, Gibco). 2. Paraformaldehyde 37%. 3. Triton X-100. 4. Anti-GFP antibody (Abcam, ab13970).

3

Methods When designing your experiment, we recommend to include three to six wells per condition of interest, including conditions treated with CCCP and not treated with Shield1 as controls for background luminescence. Do not use perimeter wells and fill them with medium or sterilized water to avoid evaporation throughout the plate.

3.1 Cell Culture: Seeding, Transfection or Lentiviral Transduction, Induction of the Probes 3.1.1 HEK293T Cells

These protocols have been optimized for experiments in HEK293T lines, human primary fibroblasts, and mouse primary cortical neurons (see Note 7 and Fig. 2a).

1. Plate 20,000 cells per well in black, PDL-coated 96-well plates. Use 200 μL per well of DMEM-GlutaMAX supplemented with 10% FBS and Penicillin/Streptomycin (see Note 8) as culture medium. 2. After 24 h, transfect cells with pCI-Neo-Probe 2 and, as a control, with pCI-Neo-Probe 3 (see Note 9). (a) Use Lipofectamine 2000 for transfection with plasmids only and follow the manufacturer’s instructions. As an indication, start with a total of 175 ng plasmid DNA, use a pCI-Neo-Probe to empty vector ratio of 1:6

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Fig. 2 Graphical illustration of the protocol for the presequence mitochondrial import assay, adapted to HEK293T cells, primary human fibroblasts, and primary cortical neurons. (a) HEK293T cells (left panel) are seeded at day 1 (D1), transfected using liposomes ( ) at day 2 (D2), and treated with Shield1/CCCP on day

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(see Note 10), and 0.6 μL of Lipofectamine 2000 in a total of 40 μL Opti-MEM per well. In case of co-transfection with another protein-encoding plasmid, you may start your optimization with 25 ng of pCI-Neo-Probe, 75 ng of the plasmid of interest, and 75 ng of empty vector (see Note 11). (b) For co-transfection with pCI-Neo-Probe and siRNAs, use Lipofectamine RNAiMax and follow the manufacturer’s instructions. As an indication, start with a total of 35 ng of plasmid DNA, use a pCI-Neo-Probe to empty vector/ plasmid of interest of 1:6 (see Note 10), 35 pM siRNA, and 0.6 μL of lipofectamine RNAiMax in a total of 40 μL Opti-MEM per well. 3. Add transfection mixture to each well, without changing the medium. 4. Perform reporter activity assay 48–72 h after transfection. 3.1.2 Human Primary Fibroblasts

1. Electroporate human primary fibroblasts with pCI-Neo-Probe 1 (see Note 12), following the manufacturer’s instructions with the following settings: one pulse of 1400 V during 20 ms. As an indication, start with a total of 175 ng of plasmid DNA per well and use a pCI-Neo-Probe to empty vector/plasmid of interest ratio of 2:1 (see Note 10). 2. Seed cells on black, PDL-coated 96-well plates at a density of 20,000 per well. Use 200 μL per well of DMEM-GlutaMAX supplemented with 10% FBS without antibiotics as culture medium. 3. Perform reporter activity assay 48–72 h after transfection.

3.1.3 Mouse Primary Cortical Neurons

1. Prepare mouse primary cortical neurons according to standard procedures (see Note 13).

ä Fig. 2 (continued) 4 (D4). Primary human fibroblasts (middle panel) are transfected by electroporation ( ), seeded at D1, and treated with Shield1/CCCP on D3. Primary mouse neurons (right panel) are seeded at D1, transduced with recombinant lentivirus ( ) on D7, and treated with Shield1/CCCP at D14 or later time points (see Note 15). (b) RGFP signals and background bioluminescence are measured for HEK293T cells and human fibroblasts before CLZ400A treatment. For primary neurons, bioluminescence is acquired first, and cells are immediately fixed and immuno-stained for RGFP fluorescence recording. After analysis (c), the data can be represented as line (d) or bar plots (e). (This figure was created using Servier Medical Art templates, which are licensed under a Creative Commons Attribution 3.0 Unported License; https://smart.servier.com. The image on panel (d) is based on data presented in [18])

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2. Plate the neurons at a density of 50,000 per well in black, PDL-coated 96-well plates. Cultivate the cells in 200 μL per well of Neurobasal A medium supplemented with 2% FBS, 1% L-Glutamine, Penicillin/Streptomycin, and 1 B27. 3. Change half of the medium every 2 days. 4. After 7 days in vitro, transduce the cells with the lentiviral vector expressing Probe 1 (see Note 12). As an indication, start with MOIs between 1 and 10 (see Note 14). 5. Perform reporter activity assay between day 7 and day 10 posttransduction (see Note 15). 3.2 Mitochondrial Import Reporter Assay 3.2.1 Induction of the Mitochondrial Import Probe 3.2.2 RGFP Fluorescence Assay

1. Treat the cells with 0.5 μM Shield1 6 h before bioluminescence recording (see Note 16). 2. Treat selected wells with CCCP (1–10 μM) as a control (see Note 17).

For each well, the bioluminescent signal emitted by the probe will be normalized to its fluorescent signal, to correct for potential inter-well differences in terms of transfection/transduction efficiency. Different procedures will be used to record fluorescent signals, depending on their intensity in the cell types of interest, as will become clear in the following paragraphs. For the following steps, use a multichannel pipette for media changes (see Note 18 and Fig. 2b). For HEK293T cells and primary fibroblasts: The fluorescent signal will be recorded immediately before the bioluminescence reporter assay, as follows: 1. Wash cells three times with 100 μL of HBSS—20 mM HEPES, pre-warmed at 37  C, and supplemented with 20 mM HEPES, leaving 100 μL in each well at the end of the procedure. 2. Record the total RGFP fluorescence from each well with a microplate spectrophotometer (see Note 2), at an excitation wavelength of 470 nm and an emission wavelength of 510 nm. For primary cortical neurons: In this cell type, the fluorescence signal may be too low to be detected as described above. In this case, after assaying for Rlucdependent bioluminescence, proceed as follows: 1. Wash cells three times with DPBS. 2. Fix cells with a 4% paraformaldehyde solution diluted in DPBS for 20 min at room temperature (RT). 3. Permeabilize cells with a 0.2% Triton X-100 solution diluted in DPBS for 10 min at RT, under gentle agitation.

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4. Wash cells three times with DPBS. 5. Block nonspecific binding of antibodies with a solution of 10% NGS diluted in DPBS. 6. Incubate cells with anti-GFP primary antibody diluted in 2% NGS overnight at 4  C. 7. Wash cells with DPBS and incubate with secondary antibody in 2% NGS diluted in DPBS for 45 min at RT. Protect from light (see Note 19). 8. Measure total RGFP fluorescence with a spectrophotometer. 3.2.3 Luciferase Bioluminescence Reporter Assay (Rluc)

For HEK293T cells and primary fibroblasts: 1. Add CLZ400A diluted in 100 μL of HBSS—20 mM HEPES, pre-warmed at 37  C, at a final concentration of 10 μM for cell lines, and 25 μM for primary fibroblasts. 2. Measure total bioluminescence before and immediately after addition of CLZ400A (see Note 20). As an indication, we recommend to collect bioluminescence signals every second for 5 min. For primary cortical neurons: 1. Wash cells three times with 100 μL of HBSS—20 mM HEPES, pre-warmed at 37  C, and supplemented with 20 mM HEPES, leaving 100 μL in each well at the end of the procedure. 2. Follow the procedure described in step 1, using 25 μM CLZ400A. 3. Follow the procedure in Subheading 3.2.2, step 2. to immunostain the cells with anti-GFP antibodies.

3.2.4 Analysis of the Results

1. Subtract any background bioluminescence from the signals recorded after the addition of CLZ400A to the culture medium (see Note 20). 2. Normalize bioluminescence signals to the total RGFP fluorescence in each well. 3. Subtract the normalized mean signal obtained for cells treated with CCCP (see Note 21 and Fig. 2c). 4. Option 1: (a) Represent the data normalized as indicated above obtained over the 5 min recording period as line plots (Fig. 2d). 5. Option 2: (a) Represent bioluminescence peaks as bar plots. Consider obtaining peak values as mean of the normalized bioluminescence signals recorded during the first 100 s (see Fig. 2e).

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Notes 1. Lentiviral vector was produced as previously described [18, 20] at titers of approximately 1  106 TU/μL, as estimated by quantitative PCR (qPCR) [21]. Store aliquots at 80  C and do not freeze and thaw more than once. 2. In our paper, we used the automated Functional Drug Screening System (FDSS) from Hamamatsu in most of our experiments [18]. For fluorescence recordings, automatic microscope settings can also be used, such as CellInsight™ CX5 High Content Screening (HCS). 3. You can also use 384-well plates, but in our hands, inter-well reproducibility is lower. 4. Prepare a stock solution at 20 mM CCCP in DMSO. Aliquot in dark tubes and store at 20  C. Discard aliquot after first use. 5. Prepare a stock solution at 50 mM CLZ400A in DMSO. Aliquot in dark tubes and store at 20  C. Do not freeze and thaw more than three times. 6. Store Shield1 at 20  C. Purchase small amounts and test after 3–6 months of storage, as Shield1 is unstable. 7. You can adapt the protocol to other cell types. 8. For transfection with RNAiMAX, do not add antibiotics. 9. In our hands, transient transfection of HEK293T cells with pCI-Neo-Probe 1 leads to mitochondrial toxicity, as judged by the loss of intensity of the mitochondrial fluorescent dye tetramethyl rhodamine methyl ester (TMRM) in cells with high expression levels of the probe [18]. Depending on the cell type of interest, the most adequate probe may be chosen. 10. In our hands, this ratio limits the toxicity of the probe and yields optimal results in terms of signal/noise ratio. You may have to adapt it to your experimental conditions. 11. If necessary, empty vector can be replaced by other proteinencoding plasmids of interest. 12. In our hands, expression of Probe 2 is extremely low in primary fibroblasts and primary neurons. We therefore recommend using pCl-Neo-Probe 1 in these cells. 13. This protocol has been adapted for primary mouse cortical neurons dissected at E14.5. Our dissection protocol is adapted from Scirretta et al. [22]. 14. According to your needs, you may transduce the cells at other time points, including before seeding.

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15. The time of transduction may be adapted according to your needs, but should not be shorter than 7 days. 16. Depending on your needs, you may adapt the time of induction (Shield1) for optimal signal/noise ratio. Induction times should be kept as short as possible for the signal of the probe to reliably reflect the import process. 17. You may consider optimizing the CCCP concentration and renewing the toxin, depending on the time of induction (Shield1). 18. If possible, use an electric multichannel pipette or be quick when changing the medium to avoid drying of the cells. Be careful not to generate bubbles, as these will disturb signal recording. 19. Wrap with aluminum foil to avoid bleaching of RGFP fluorescence. 20. Depending on the cell type and equipment used, you may want to check for background bioluminescence before addition of CLZ400A. 21. In our hands, a bioluminescence ratio of about 5 is observed between conditions without and with CCCP for induction times (Shield1) of 6 h and CCCP concentrations of 10 μM, without renewal.

Acknowledgments We thank the ICM iVector facility for generating and producing lentiviral particles. This work has received support from Institut national de la sante´ et de la recherche me´dicale, Association France Parkinson, Fondation de France (Engt 2012 00034508), Fondation ICM, “Investissements d’avenir” ANR-10-IAIHU-06, Institut de Recherches Servier/Les Laboratoires Servier, the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 821522 (PD-MitoQUANT; this Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation program and EFPIA and Parkinson’s UK). The material presented and views expressed here reflect the author’s view and neither IMI nor the European Union, EFPIA, or any Associated Partners are responsible for any use that may be made of the information contained herein. M.J. and E.H.K. were supported by fellowships from the French Ministry of Higher Education and Research and by Association France Parkinson.

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References 1. Archibald JM (2015) Endosymbiosis and eukaryotic cell evolution. Curr Biol 25(19): R911–R921 2. Chacinska A, Koehler CM, Milenkovic D, Lithgow T, Pfanner N (2009) Importing mitochondrial proteins: machineries and mechanisms. Cell 138:628–644 3. Neupert W, Hermann JM (2007) Translocation of proteins into mitochondria. Annu Rev Biochem 76:723–749 4. Pfanner N, Warscheid B, Wiedemann N (2019) Mitochondrial proteins: from biogenesis to functional networks. Nat Rev Mol Cell Biol 20(5):267–284 5. Wiedemann N, Pfanner N (2017) Mitochondrial machineries for protein import and assembly. Annu Rev Biochem 86:685–714 6. Vo¨gtle FN, Wortelkamp S, Zahedi RP, Becker D, Leidhold C, Gevaert K et al (2009) Global analysis of the mitochondrial n-proteome identifies a processing peptidase critical for protein stability. Cell 139:428–439 7. Abe Y, Shodai T, Muto T, Mihara K, Torii H, Nishikawa S et al (2000) Structural basis of presequence recognition by the mitochondrial protein import receptor Tom20. Cell 100 (5):551–560 8. van Wilpe S, Ryan MT, Hill K, Maarse AC, Meisinger C, Brix J et al (1999) Tom22 is a multifunctional organizer of the mitochondrial preprotein translocase. Nature 401 (6752):485–489 9. Melin J, Schulz C, Wrober L, Bernhard O, Chacinska A, Jahn O et al (2014) Presequence recognition by the tom40 channel contributes to precursor translocation into the mitochondrial matrix. Mol Cell Biol 34(18):3473–3485 10. Banerjee R, Gladkova C, Mapa K, Witte G, Mokranjac D (2015) Protein translocation channel of mitochondrial inner membrane and matrix-exposed import motor communicate via two-domain coupling protein. Elife 4: e11897 11. Demishtein-Zohary K, Gu¨nsel U, Marom M, Benerjee R, Neupert W, Azem A et al (2017) Role of Tim17 in coupling the import motor to the translocation channel of the mitochondrial presequence translocase. Elife 6:e22696 12. Kang PJ, Ostermann J, Shilling J, Neupert W, Craig EA, Pfanner N (1990) Requirement for

hsp70 in the mitochondrial matrix for translocation and folding of precursor proteins. Nature 348(6297):137–143 13. Schulz C, Rehling P (2014) Remodelling of the active presequence translocase drives motor-dependent mitochondrial protein translocation. Nat Commun 5:4349 14. Ting S-Y, Yan NL, Schilke BA, Craig EA (2017) Dual interaction of scaffold protein Tim44 of mitochondrial import motor with channel-forming translocase subunit Tim23. Elife 6:e23609 15. Fukasawa Y, Tsuji J, Fu S-C, Tomii K, Horton P, Imai K (2015) MitoFates: improved prediction of mitochondrial targeting sequences and their cleavage sites. Mol Cell Proteomics 14(4):1113–1126 16. Gakh O, Cavadini P, Isaya G (2002) Mitochondrial processing peptidases. Biochim Biophys Acta 1592(1):63–77 17. Harbauer AB, Zahedi R, Sickmann A, Pfanner N, Meisinger C (2014) The protein import machinery of mitochondria-a regulatory hub in metabolism, stress, and disease. Cell Metab 19(3):357–372 18. Jacoupy M, Hamon-Keromen E, Ordureau A, Erpapazoglou Z, Coge F, Corvol JC et al (2019) The PINK1 kinase-driven ubiquitin ligase Parkin promotes mitochondrial protein import through the presequence pathway in living cells. Sci Rep 9(1):11829 19. Molinari P, Casella I, Costa T (2008) Functional complementation of high-efficiency resonance energy transfer: a new tool for the study of protein binding interactions in living cells. Biochem J 409:251–261 20. Zennou V, Petit C, Guetard D, Nerhbass U, Montagnier L, Charneau P (2001) The HIV-1 DNA flap stimulates HIV vector-mediated cell transduction in the brain. Nat Biotechnol 19:446–450 21. Barczak W, Suchorska W, Rubis B, Kulcenty K (2015) Universal real-time PCR-based assay for lentiviral titration. Mol Biotechnol 57:195–200 22. Sciarretta C, Minichiello L (2010) The preparation of primary cortical neuron cultures and a practical application using immunofluorescent cytochemistry. Methods Mol Biol 633:221–231

INDEX A AcetylCoA ........................................................2, 131, 165 Acidic phosphatase ................................37, 43, 46, 47, 99 ACO1........................................................... 88, 90, 91, 95 Acrylamide................................... 93, 105–107, 109, 228, 231, 384, 390, 394, 413 Actin/Hsp70/sugar kinase superfamily ........................ 88 Actin filaments............................................................... 334 Adenosine diphosphate (ADP) .......................... 4, 13–15, 18, 44, 57, 69, 73, 75, 77, 79, 81, 155, 157, 161, 179, 201, 271, 272, 274, 275, 277, 280, 281, 306, 437, 438 Adenoviral transduction ............................................... 296 Adipocytes ............................................................ 285, 288 ADP, see Adenosine diphosphate (ADP) ADP-ribose-metabolizing enzyme............................... 166 ADP-ribosylation ................................................. 165–171 Aedes aegypti ................................... 69–73, 75, 78, 79, 83 Affinity-capture.............................................................. 145 Alkaline phosphatases ......................................37, 99, 112 Alzheimer .................................................... 1, 6, 100, 259 Anaerobic glycolysis ........................................................ 19 Animal models............................................................... 265 Antimycin A................................................ 14–17, 20, 70, 74, 180, 186, 190, 310, 420 Anti-ADP-ribose antibody ........................................... 167 Anti-BiP/GRP78 ............................................................ 36 Anti-catalase .................................................................... 36 Anti-Lamp-1.................................................................... 36 Anti-TOM20................................................................... 36 Anti-TOM22.............................................................34, 41 Apaf-1 ............................................................................ 216 Apoptosis .................................................... 2, 19, 90, 143, 188, 215–218, 220, 410, 421, 422, 441 Apoptotic cells...................................................... 215–222 Aspect ratio.................................................. 288, 294, 299 Astrocytoma .................................................................. 236 Ataxias............................................................................ 194 ATO1 ............................................................................... 88 ATO2 ............................................................................... 88 ATP synthase ...................................................3, 4, 13–15, 17, 18, 68, 75, 190, 217, 221, 271, 282, 317–319, 323, 386, 387, 420, 425 ATP/ADP translocator................................................. 250

ATP synthesis ............................................. 3, 4, 7, 13, 14, 16–21, 73, 75, 420 Autofluorescence.................................194–197, 201, 266

B Bak ........................................................................ 216, 410 Basic phosphatase........................................ 43, 46, 47, 49 BAT, see Brown adipose tissue (BAT) Bax ............................................................... 216, 410, 421 Bc1 complex ............................................... 425, 426, 428, 429, 431, 433, 437 BCA™ protein assay kit................................................ 309 Bcl-2 family ................................................................... 216 β-dodecylmaltoside β-oxidation .............................................. 2, 3, 16, 20, 129 Bicinchoninic assay.......................................................... 63 Bid.................................................................................. 216 Bioenergetics ....................................................... 3, 11–13, 20, 22, 23, 68, 103, 129, 130, 132, 153–163, 165, 194, 259–268, 306, 316, 318, 357, 411, 420, 421 BIOLOG ......................................................133–136, 140 Bioluminescence..................................442, 447–449, 451 Biosensors ..................................... 11, 184, 187, 441–451 Biotinylated oligonucleotides ....................................... 145 Bisacrylamide.......................................105, 106, 109, 231 BKCa ...................................................................... 236, 244 Blood oxygenation ........................................................ 259 Blue Native polyacrylamide gel electrophoresis (BN-PAGE) ...................................................6, 7, 9 Blue-Native Gel Electrophoresis ..............................5, 231 BN-PAGE, see Blue Native polyacrylamide gel electrophoresis (BN-PAGE) Bradford assay ................................................47, 156, 162 Brain slices ............................................................ 193–201 Brown adipose tissue (BAT)............................... 274, 275, 286, 288, 294, 298–300, 302

C Caenorhabditis elegans (C. elegans) ................... 397–406 Calcium Green .................................................... 174, 176, 177, 180, 188 Calcium homeostasis..................................................... 259 Calmodulin.................................................................... 174

Volkmar Weissig and Marvin Edeas (eds.), Mitochondrial Medicine: Volume 2: Assessing Mitochondria, Methods in Molecular Biology, vol. 2276, https://doi.org/10.1007/978-1-0716-1266-8, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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Cancers ...................................................2, 20, 31, 37, 41, 90, 100, 130, 140, 211, 224, 259, 343, 371, 409, 410, 416–418, 420, 421 Carbon monoxide (CO) ...................................... 249–256 Carbonyl cyanide p-trifluoromethoxyphenylhydrazone (FCCP) ........................................... 13, 15, 17, 70, 73, 75, 77, 82, 176, 180, 186, 190, 195–201, 307, 310, 317, 318, 323, 413, 420 Carboxyatractyloside.................................................70, 79 Cardiolipin...................................................................6, 58 Cardiomyocytes................................................... 154, 162, 236, 250, 350 Carnitine/acylcarnitine carrier ..................................... 250 Caspase-8 ....................................................................... 216 Caspase-9 .............................................................. 216, 421 Caspase-dependent apoptosis........................................... 2 Catalase ..............................................................37, 43, 46, 47, 50, 54, 335, 340 Cell death ...............................................87, 88, 130, 205, 215–224, 250, 259, 300, 306 CEB, see Cell Energy Budget (CEB) Cell Energy Budget (CEB) ................................ 306–308, 312, 316–320 CellRox™ ............................................205, 207, 208, 210 Cell shredder ........................................................ 344, 347 CellTiter-Glo® ............................................ 309, 313, 315 Cellular energy metabolism .......................................... 133 Cerebral spinal fluid (CSF) ................................... 22, 358, 362, 363, 369 Cervical dislocation .............................155, 198, 253, 313 Charge transfer reactions .............................................. 431 Citrate synthase (CS) .......................................... 5, 35, 36, 77, 88, 131, 345, 349, 354, 386 CLARIOstar .................................................................. 308 Clark electrode ................................................................ 37 Clear-native (CN) ...............................106, 107, 110, 227 CLZ400A ................................... 442, 445, 447, 449–451 CO, see Carbon monoxide (CO) Coagulation ....................................................................... 2 Coelenterazine ..................................................... 442, 445 Coenzyme A .................................................................... 16 Complex I........................................................2, 3, 73–75, 131, 133, 194, 195, 222, 224, 250, 251, 275, 420, 425, 426, 437 Complex II ............................................... 3, 14, 131, 133, 194, 222, 224, 250, 274 Complex III.................................................. 3, 14, 74, 76, 190, 317, 319, 323, 420 Complex IV ............................................... 3, 14, 195, 201 Compound Discoverer™ software .............................. 359 Coomassie G250 ........................ 103–105, 107, 109, 111 Coronavirus ....................................................................... 2 COVID-19 ........................................................................ 2 COX, see Cytochrome c oxidase (COX)

C2C12, see Mice muscle cell (C2C12) CRISPR/Cas9............................................................... 398 Cristae ..................................................3, 32, 36, 131, 133 Cryo-imaging ....................................................... 259–268 CIT2, see Peroxisomal citrate synthase (CIT2) Cit2p-GFP detection ...................................................... 93 Cysteine proteases ......................................................... 216 Cytochrome C............................. 3, 5, 13, 69, 75, 81–83, 131, 215–217, 219, 220, 222, 323, 410, 426 Cytochrome c oxidase (COX).............................. 3, 5, 70, 74, 76, 77, 82, 179, 319, 387 Cytokines .....................................................................2, 20 Cytosolic Ca2+ ..................................................... 189, 306

D Damage-associated molecular patterns (DAMPs) ........ 58 DAMPs, see Damage-associated molecular patterns (DAMPs) DAPI staining................................................................ 170 Deoxynucleoside 5’-triphosphates (dNTPs) ..............143, 144, 146, 148, 150 DHE, see Dihydroethidium (DHE) Diabetes ................................................... 1, 130, 274, 397 Differential centrifugations...............................12, 32, 34, 35, 45, 179, 182, 231 Digitonin ........................................... 6, 13, 68, 105, 107, 110, 140, 175, 176, 180, 216–218, 221, 224, 229–233 Digitonin-permeabilized plasma membrane ..... 218, 219, 221, 222 Dihydroethidium (DHE) ............................................. 205 Dihydrolipoamide dehydrogenase (DLD) .................. 443 dNTPs, see Deoxynucleoside 5’-triphosphates (dNTPs) Drosophila .......................................................67, 114–126 Drosophila melanogaster (D. melanogaster) ................. 67, 69–73, 75, 78, 80, 82, 116, 236 Drp1, see Dynamin-related protein 1 (Drp1) Dynamin related GTPase.............................................. 325 Dynamin-related protein 1 (Drp1) .............................. 204

E Electron transport chain (ETC) ................................2, 23, 103–112, 129, 194, 197, 227, 266, 317, 425 Endothelial cells ............................................................ 236 Energy clamp........................................................ 271–282 Epigenetic alterations.................................................... 130 Epilepsy.......................................................................... 194 ETC, see Electron transfer chain (ETC) Extracellular acidification............................ 306, 314, 420

F FACS.............................................................203–211, 218 FastRandomForest algorithm....................................... 288

MITOCHONDRIAL MEDICINE: VOLUME 2: ASSESSING MITOCHONDRIA Index 455 FCCP, see Carbonyl cyanide p-trifluoromethoxyphenylhydrazone (FCCP) F0F1-ATP synthase.............................................. 3, 14, 15 FIJI.................................... 154, 155, 157–159, 169, 286, 289, 297, 299, 301, 302, 399, 406 Fiji-ImageJ............................................................ 155, 286 Flow cytometry ....................................................... 21, 62, 63, 204, 205, 221 Fluorescent assessment of H2O2 production .............. 278 Fluorescence imaging .......................................... 155, 259 Fluorescence quenching ................................................. 11 Form Factor (FF) ................................................. 286–288 FreeMitos......................................................................... 57 FRET-based cameleons................................................. 174 Fumarate hydratase .............................................. 131, 319 Fura-2 .................................................................. 174, 178, 181, 182, 189

G GAL4 ........................................................... 115, 116, 120 GCamPs......................................................................... 174 GECOs .......................................................................... 174 Gillespie algorithm ............................................... 433, 436 Glucose-6-phosphatase ............................... 37, 46, 47, 51 Glucose-6-phosphate assay ............................................. 43 Glutaminolysis ......................................... 17, 20, 305, 306 Glutathione disulfide (GSSG) ............................. 114, 249 Glutathione redox equilibrium ........................... 114–126 Glutathionylation ................................................. 249, 250 Glycolytic fluxes .................................................. 307, 315, 318, 319, 322 Glycolytic rates .................................................11, 22, 319 Grx1 ............................................................................... 114 GSSG, see Glutathione disulfide (GSSG)

H H2O2 reporters .................................................... 296, 298 Head dissection ............................................................... 71 HEK 293, see Human embryonic kidney cell (HEK 293) Heme-oxygenase ........................................................... 250 HIF1α ................................................................................ 2 High-resolution accurate mass spectrometry (HRAM) .......................................... 363, 364, 375 High resolution clear native electrophoresis ............... 103 High-throughput mitochondrial image analysis ...................................................... 285–302 HILIC, see Hydrophilic interaction liquid chromatography (HILIC) HRAM, see High-resolution accurate mass spectrometry (HRAM) Human embryonic kidney cell (HEK 293)................344, 345, 349–354

Huntington ....................................................................... 2 Hybrid electrophoresis................................ 104, 105, 111 Hydrophilic interaction liquid chromatography (HILIC) .......................... 358, 359, 362–364, 376

I IDH1 ........................................................... 88, 90, 91, 95 ImageJ......................................................... 155, 286, 300, 339, 406, 417 Imaging of mitochondria .................................... 156, 400 IMM, see Inner Mitochondrial Membrane (IMM) Immunoblotting .................................. 90, 103–112, 252, 254, 255, 326, 383–394 Immunoprecipitation..........................251, 252, 254, 255 Inflammation ..................................................................... 2 In-gel complex V assay.................................................. 231 In-gel digestion .................................................... 389, 391 Inner mitochondrial membrane (IMM) .....................3, 4, 21, 68, 75, 79, 81, 107, 131, 216, 235–246, 272, 323, 325, 327, 383, 442 Insect tissues..............................................................67–83 Ion channels ......................................................... 235–246 Iron sulfur protein (ESP) ............................................. 426 Isolation of mitochondria.................................12, 34, 35, 58, 68, 179, 204, 231, 275, 276 Isopycnic density gradient centrifugation...................... 47

J JC-1 ............................................................ 37, 42, 44, 46, 52, 53, 204, 413, 417, 422

K Keratinocytes ................................................................. 236 KIF5B-mediated mitochondrial tubulation ................ 333 Kinesin-1........................................................................ 333 Krebs cycle .................................................. 129, 131, 194, 305–307, 310, 315, 317, 319

L L-carnitine ....................................................................... 16 Leak respiration .........................................................17, 18 Lentiviral transduction.................................................. 445 Lipid-droplet-bound mitochondria .................... 285–302 Lipid droplet number ................................................... 285 Lipid droplets ...................................................... 285, 286, 288, 299, 301, 302 Lipofectamine 2000............................................. 445, 447 Lipofectamine RNAiMax..................................... 445, 447 Liquid chromatography/mass spectrometry (LC/MS) ................................................. 358, 360, 361, 363, 365, 368, 371, 376, 377 Lisinopril........................................................................ 265

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456 Index M

Magnetic beads ................................................37, 41, 404 Malate ................................................... 14–16, 22, 69, 73, 131, 137, 139, 155, 157, 161, 219, 222, 224, 251, 274, 277, 280, 282 Marker enzyme assays ...............................................47–54 Markov state models ............................................ 425–438 MARylated proteins...................................................... 167 Mass spectrometry (MS)....................................... 23, 104, 133, 205, 322, 345, 347, 348, 358, 359, 361–368, 377, 383–395 Mechanical permeabilization ................ 71–73, 75, 80, 82 Membrane potentials ......................................20–22, 154, 158, 193, 204, 205, 207, 217, 221, 223, 272–274, 285, 306, 345, 410, 431, 432 Membrane stiffness .............................................. 343–354 Menten, M.L................................................................. 247 Metabolic diseases .....................................................1, 397 Metabolism................................................. 2, 3, 7, 10, 12, 16, 17, 19, 20, 22, 23, 31, 34, 67, 68, 75, 114, 129–140, 143, 144, 165, 173, 175, 194, 204, 259, 305–322, 359, 410, 441 Metabolomics .........................................22, 23, 357, 358, 368, 371, 372, 376, 378 MetaMorph ................................................................... 155 Mice muscle cell (C2C12).................................. 345, 346, 349–351, 353, 354 Michaelis, L. .................................................................. 247 Microfluidics-based cell shredder ........................ 345, 351 Microscale cell shredder.............................. 344, 346, 352 Microtubules .......................................333, 334, 338–341 MitoBKCa ............................................236, 237, 244, 246 Mitochondria enrichment.........................................47, 54 Mitochondria imaging .................................................. 156 Mitochondria isolation from brain cortex ................... 251 Mitochondria isolation from cell culture............ 250, 252 Mitochondrial DNA (mtDNA).................................6, 23, 24, 32, 77, 88, 144, 203, 238, 240, 245, 246, 397, 410, 411, 419 Mitochondrial DNA depletion syndromes .................. 144 Mitochondrial dNTP pools ................................. 143–151 Mitochondrial dysfunctions.......................................1–24, 34, 88–90, 130, 215–224, 259, 260, 266, 343, 359, 410 Mitochondrial extraction ................................................ 61 Mitochondrial functions ................................... 13, 21–23, 33, 67–83, 88, 133, 134, 137, 154, 165, 194, 227, 228, 232, 259, 267, 274, 275, 281, 320, 343, 359, 398, 409–423 Mitochondrial fusion .....................................23, 325, 333 Mitochondrial heat-shock protein 70 (mtHsp700) ................................................. 442 Mitochondrial hydrogen peroxide ...................... 114–126

Mitochondrial import reporter assay ........................... 448 Mitochondrial integrity ....................................13, 81, 83, 188, 344, 349 Mitochondrial membrane potentials................20, 21, 37, 161, 175, 193–201, 204, 216–218, 220, 221, 271, 308, 398, 417 Mitochondrial morphology .................................... 33, 68, 286–288, 397–406, 410, 411, 417 Mitochondrial network formation (MNF).................333, 334, 336, 339, 341 Mitochondrial permeability transition pore (mPTP) .............................................................. 275 Mitochondrial presequence import pathway...... 441–451 Mitochondrial protein glutathionylation............ 249–255 Mitochondrial protein import...................................... 442 Mitochondrial pumping complexes .................... 425–438 Mitochondrial retrograde signaling .......................87–100 Mitochondrial supercomplexes ........................... 107, 110 Mitochondrial superoxide .................................. 205, 219, 413, 416, 417 Mitochondrial targeting signal (MTS) ............... 442–444 Mitochondrial ultrastructure .......................................... 32 Mitochondrial uptake .......................................... 188, 416 Mitochondria mass...................................... 204, 205, 207 Mitochondria purification ..................................... 61, 340 Mitochondria-specific dyes .................................. 204, 211 Mitofusin-mediated fusion ........................................... 333 Mitoplast isolation ........................................................ 179 Mitoplast patch-clamping ............................................. 183 Mitoplast preparations ................................ 239, 242, 246 Mitoplasts ................................................... 179, 182, 189, 237, 238, 240, 242–246 Mito-roGFP2-Grx1 ............................114–116, 120, 125 Mito-roGFP2-Orp1 ............................115, 116, 120, 125 MitoSOX™ ................................................ 205, 207, 208, 219, 223, 224, 413, 417, 422 Mito-TASK3.................................................................. 236 MitoTracker™ Green .......................................... 204, 207 Mitotracker™ Orange .................................................. 204 Mitotracker™ Red ........................................................ 207 MitoXpress®-Xtra ............................................... 307–309, 312, 313, 318 Mono-ADP-ribosylhydrolase ....................................... 166 Mouse primary cortical neurons ......................... 445, 447 mPTP, see Mitochondrial permeability transition pore (mPTP) mtDNA, see Mitochondrial DNA (mtDNA) MtDNA damage .................................................. 417–419 mtHsp70, see Mitochondrial heat-shock protein 70 (mtHsp700) MTS, see Mitochondrial targeting signal (MTS) Multi-color flow cytometric analysis ................... 203–211 Multi-parametric cell energy budget platform .................................................... 305–323

MITOCHONDRIAL MEDICINE: VOLUME 2: ASSESSING MITOCHONDRIA Index 457 Muscle mitochondria ..........................274, 277, 280, 282 P Myocardial ischemia...................................................... 250 Myosine light chain kinase .................................. 174, 386

N NADH autofluorescence ..................................... 197, 201 NADH/NAD+ .............................................................. 2, 3 NADH Ubiquinone Reductase........................................ 3 NADPH.................................................................. 21, 194 Nanoscale liquid chromatography ............................... 384 Nanotubules .................................................................. 333 Native gel electrophoresis.................................... 103–112 Natural compounds ...................................................... 130 Nematodes................................................... 398, 399, 406 Neon™ Transfection System........................................ 445 Neurodegenerative diseases .............................1, 6, 37, 41 N-formylated peptides .................................................... 58 Nile red ........................................................ 288, 296, 301 Nitrotyrosine ........................................................ 383, 384 Nitrotyrosine-containing proteins ...................... 383–394 NMR Spectroscopy .............................275, 276, 278–280 NMR-based ATP assay ................................................. 278 Nobel Prizes ...................................................67, 235, 236 nucDNA, see Nuclear DNA (nucDNA) Nuclear DNA (nucDNA) ................................... 144, 203, 240, 246

O O2K®Oxygraph................................................................. 9 Obesity......................................................... 1, 32, 41, 259 Oligomycin ....................................................5, 13–15, 17, 18, 70, 75, 79, 155, 157, 176, 186, 190, 233, 271, 278, 310, 318, 413, 420, 421 OMA1................................................................... 325–331 OMA1 knockout models.............................................. 326 1D 1H NMR ................................................272, 279–281 1D 31P NMR................................................................. 281 Optic Atrophy Protein (OPA1) ....................23, 325–327 OPA1, see Optic Atrophy Protein (OPA1) Optical metabolic imaging ........................................... 259 Orbitrap mass spectrometer ......................................... 358 ORCA-Flash4.0 ............................................................ 155 Oroboros ................................................9, 10, 15, 17, 21, 32, 72–74, 76, 78, 81 Orp1 ..................................................................... 114, 288 Oxidoreductases ................................................... 3–5, 386 OXPHOS................................. 2, 4–6, 14–16, 19–21, 24, 75, 77, 79, 80, 129, 266, 307, 315, 317, 319, 322 Oxygen consumption .............................. 4, 9, 15, 17, 37, 72–78, 80–83, 130, 216, 218, 221, 222, 259 Oxygen consumption rate (OCR) ......................... 68, 81, 204, 306–309, 312–314, 316–320, 322, 412, 420 Oxygenation imaging ................................................... 259 Oxygraphs..................................... 9, 10, 15, 17, 218, 219

Parkinson’s disease ........................................................ 397 PARylation..................................................................... 166 Patch-clamp ........................................175, 179, 235–238, 240, 242, 243 Patch-clamp recording......................................... 184, 242 Pentose phosphate pathway (PPP) ............ 197, 305, 306 Pericams......................................................................... 174 Peri-droplet mitochondria ............................................ 286 Peri-droplet mitochondrial H2O2 production ............ 288 Permeabilization................................................10, 12, 13, 15, 16, 19, 21–23, 67–83, 134, 135, 167, 168, 175, 216, 221, 224, 250 Peroxisomal citrate synthase (CIT2)................. 88–92, 95 PHERAstar .................................................................... 308 Phosphorylating respiration ........................14, 15, 17–19 PH-Xtra™ ...........................................307–311, 316, 318 Plasma ...................................................13, 37, 46, 49, 61, 68, 69, 156, 162, 216, 217, 221, 224, 236, 346, 358, 361, 363, 368, 369, 377, 378 Platelet-derived microvesicles ...................................57, 58 Platelet-derived mitochondria ..................................57, 64 Platelet mitochondria................................................57–65 Platinum complexes ............................................. 409–422 Porins ............................................................................... 32 Pre-adipocytes ...................................................... 294, 302 Pre-sequence translocase-associated motor (PAM) ................................................................ 442 Primary brown adipocytes ............................................ 294 Primary fibroblasts ............................4, 17, 445, 447–450 Proapoptotic proteins ................................................... 215 Pro-caspase-9................................................................. 216 Proline................................................................69, 72, 79, 392, 443, 444 Protein measurements ........................................... 47, 318 Protein misfolding .......................................................... 88 Proton gradient ...........................................................3, 52 Proton leaks........................................................... 4, 7, 14, 16, 18, 21, 75, 260 Protonmotive force .............................................. 3, 68, 77 Purified motor proteins ....................................... 334, 338 Pyruvates........................................ 14–17, 22, 23, 70, 72, 73, 79, 82, 129, 131, 180, 185, 206, 219, 222, 224, 309, 310, 317, 318, 322, 386, 412, 444

R Radio Immunoprecipitation Assay (RIPA).................322, 328, 330, 413 Ransac model ...............................................428–430, 435 RCR, see Respiratory control ratio (RCR) Reactive Oxygen Species (ROS) ...............................2, 20, 21, 23, 77, 130, 154, 205, 207, 208, 210, 211, 216, 227, 249, 250, 259, 271, 277, 281, 288, 306, 308, 319, 410, 411

MITOCHONDRIAL MEDICINE: VOLUME 2: ASSESSING MITOCHONDRIA

458 Index

Real-time PCR ............................................ 90, 91, 94, 95 Recombinant vectors .................................................... 443 Redox balance ............................................................... 130 Redox cycling ................................................................ 288 Redox-sensitive green fluorescent protein (roGFP2) ........................114, 120, 125, 288, 300 Renilla reniformis green fluorescent protein (RGFP) 442–444, 447–449, 451 Residual oxygen consumption ....................................... 77 Respirasomes .......................................................... 11, 103 Respirations .......................................... 3, 7, 9–23, 33, 59, 63, 64, 69, 72, 73, 75, 77, 81, 83, 88, 129, 130, 137, 155, 186, 189, 195–197, 201, 204, 218, 219, 221–223, 229, 232, 274, 275, 277–280, 282, 310, 312, 314, 316–320 Respiration rates................................7, 11, 13–19, 22, 23 Respiratory chain electron flow........................... 129–140 Respiratory control ratio (RCR) ............ 14, 16, 232, 260 Respiratory Super-Complexes .......................................... 6 RGFP, see Renilla reniformis green fluorescent protein (RGFP) Rhod-2.................................................................. 174, 181 Rhodamine 123...................................195, 197–199, 204 roGFP2, see Redox-sensitive green fluorescent protein (roGFP2) ROS production................................................2, 20, 173, 206, 216, 271–282, 286, 325 ROS, see Reactive Oxygen Species (ROS) Rotenone ....................................... 14, 15, 17, 20, 22, 70, 74, 155, 157, 167, 176, 219, 222, 229, 413, 420 Routine respiration ............................................ 17, 18, 20 RTG genes....................................................................... 88 RTg2p........................................................................88, 89 Rtg3 phosphorylation detection ..............................92, 93

S Saccharomyces cerevisiae.............................................88, 91 SARS-CoV-2 ..................................................................... 2 SDS-PAGE, see Sodium dodecylsulfate polyacrylamide gel electrophoresis (SDS-PAGE) Seahorse®XF ................................................................... 11 Shear stress .......................................................... 345, 346, 348, 349, 351, 352 Signaling pathways ............................................. 2, 67, 115 Single particle-tracking ........................................ 153–162 Single-mitoplast ..................................237, 238, 243, 245 SIRT1 ............................................................................ 130 SIRTs, see Sirtuins Sirtuins (SIRTs)............................................................. 166 Skin fibroblasts ..........................................................5, 236

Sodium dodecylsulfate polyacrylamide gel electrophoresis (SDS-PAGE)........................................95, 97, 254, 384, 390, 394, 413, 421 State 3u......................................................................13, 14 Streptavidin.................................................................... 145 Stress responses ....................................... 2, 19, 24, 87, 89 Substrate level phosphorylation (SLP) ............... 305, 319 Succinate dehydrogenase assay....................................... 42 Succinate-energized muscle mitochondria .................. 274 Succinate ubiquinone reductase ....................................... 3 Superoxide ............................................................ 216, 224 Surface marker staining....................................... 204, 205, 207–209, 211 Synthasomes .................................................................. 103

T Tandem mass spectrometry .......................................... 384 TCA cycle .............................................2, 3, 7, 13, 16, 18, 20, 22, 23, 88, 129, 130, 132, 134, 194, 197 Tetramethylrhodamine ............................... 156, 204, 218 Tetrazolium redox dye................................ 131, 133, 134 Thermodynamics.............................................. 4, 432–433 Thermostable DNA polymerase................................... 146 Thorax dissection ............................................................ 71 3d imaging............................................................ 113–127 3d optical cryo-imaging.............................. 259, 265, 267 Thrombosis ....................................................................... 2 Thymidine kinase-2.............................................. 144, 250 Thymidine phosphorylase deficiency ........................... 144 TIM23 .................................................................. 337, 442 TIRF, see Total internal reflection fluorescence microscopy imaging (TIRF) Tissue auto-fluorescence imaging ................................ 259 Tissue macrophages ...................................................... 205 TMRM.................................................. 21, 154, 156–159, 161, 162, 450 TOM.............................................................................. 442 TOM20 ......................................................................... 442 TOM22 ......................................................................... 442 Total internal reflection fluorescence microscopy imaging (TIRF)......................................334, 335, 338–340 TPP+ ........................................................ 21, 22, 410, 411 TPP, see Triphenylphosphine (TPP+) TrackMate............................................154, 157, 159, 162 Transcription of mitochondrial genes................. 418, 420 Transfection reagents .................................. 178, 181, 187 Triphenylphosphine (TPP+)................................ 410, 415 Triphenylphosphonium .................................10, 415, 416 2D 13C/1H HSQC NMR.......................... 272, 279, 280 2d electrophoresis ........................................104, 383–386

MITOCHONDRIAL MEDICINE: VOLUME 2: ASSESSING MITOCHONDRIA Index 459 2-deoxyglucose (2DOG)........................... 271, 272, 274, W 275, 277–281 2DOG, see 2-deoxyglucose (2DOG) 2DOG ATP energy clamp ..................271, 272, 274, 275 tRNAs .............................................................................. 32 Tyrosine hydroxylase (TH) ................................ 115, 116, 121, 123, 124

U Ubiquinol ............................................................. 426, 431 Ubiquinol cytochrome c reductase .............................. 3, 5 Ubiquinone ........................................................... 3–5, 13, 386, 420, 427, 435 Ultima Gold™liquid scintillation cocktail.................... 146 Untargeted metabolomics ................................... 357–379 Untargeted metabolomics analysis...................... 357–397 Urine.................................... 22, 358, 361, 363, 369, 377

V Vanquish™ UHPLC system ............................... 363, 364

WEKA ......................................................... 286, 288–291, 297, 299, 301 WEKA segmentation .......................................... 290, 291, 294, 297, 299 Western blotting......................................... 7, 93, 98, 111, 217, 233, 337 Whole-body respiration ................................................ 259

X XF Extracellular Flux Analyzer...................................9, 11

Y Yeast .......................................................... 23, 70, 87–100, 114–117, 119, 176, 288, 399 Yeast protein extraction .................................................. 96 YME1L ................................................................. 325, 326