Opioid Receptors: Methods and Protocols [2nd ed.] 9781071608838, 9781071608845

Table of contents :
Front Matter ....Pages i-xv
Front Matter ....Pages 1-1
Overview of Genetic Analysis of Human Opioid Receptors (Santi M. Spampinato)....Pages 3-13
Renilla Luciferase Reporter Assay to Study 3′-UTR-Driven Posttranscriptional Regulation of OPRM1 (Gabriele Vincelli, Andrea Bedini)....Pages 15-26
Fluorescence Colocalization Analysis of Cellular Distribution of MOR-1 (Vittoria Borgonetti, Nicoletta Galeotti)....Pages 27-34
Monitoring Opioid Receptor Interaction in Living Cells by Bioluminescence Resonance Energy Transfer (BRET) (Monica Baiula)....Pages 35-43
Bioluminescence Resonance Energy Transfer (BRET) to Detect the Interactions Between Kappa Opioid Receptor and Nonvisual Arrestins (Andrea Bedini)....Pages 45-58
Functionalization and Bioconjugation of Nanoruby for Long-Term, Ultrasensitive Imaging of Μu-Opioid Receptors (Rashmi Pillai, Mark Connor, Varun K. A. Sreenivasan)....Pages 59-70
Immunohistochemical Analysis of Opioid Receptors in Peripheral Tissues (Yvonne Schmidt, Halina Machelska)....Pages 71-82
Real-Time Quantitative Reverse Transcription PCR for Detection of Opioid Receptors in Immune Cells (Melih Özgür Celik, Dominika Labuz, Halina Machelska)....Pages 83-95
Front Matter ....Pages 97-97
Quantitative Analysis of MOR-1 Internalization in Spinal Cord of Morphine-Tolerant Mice (Vittoria Borgonetti, Nicoletta Galeotti)....Pages 99-108
GTPγS-Autoradiography for Studies of Opioid Receptor Functionality (Alfhild Grönbladh, Mathias Hallberg)....Pages 109-116
Evaluating Opioid-Mediated Adenylyl Cyclase Inhibition in Live Cells Using a BRET-Based Assay (Preeti Manandhar, Shivani Sachdev, Marina Santiago)....Pages 117-125
Patch Clamp Analysis of Opioid-Induced Kir3 Currents in Mouse Peripheral Sensory Neurons Following Nerve Injury (Viola Seitz, Philip Stötzner, Dominika Labuz, Halina Machelska)....Pages 127-137
Opioid Modulation of Neuronal Iron and Potential Contributions to NeuroHIV (Bradley Nash, Elena Irollo, Renato Brandimarti, Olimpia Meucci)....Pages 139-162
An in Vitro Assay to Study the Role of Opioids in Modulating Immune Cell Adhesion (Monica Baiula)....Pages 163-169
Assessing Cell Viability Effects of Opioids in Primary Cortical Cells from Rat (Alfhild Grönbladh, Erik Nylander, Sofia Zelleroth, Mathias Hallberg)....Pages 171-180
The Quest for More Effective Analgesics with Reduced Abuse Liability and Fewer Adverse Effects: Promises, Pitfalls, and Future Perspectives of Biased Agonists at Opioid Receptors (Andrea Bedini)....Pages 181-192
Front Matter ....Pages 193-193
Mechanical Nociception in Mice and Rats: Measurement with Automated von Frey Equipment (Gabriele Campana, Roberto Rimondini)....Pages 195-198
Evaluation of Murine Macrophage Cytokine Production After In Vivo Morphine Treatment (Silvia Franchi, Mara Castelli, Sarah Moretti, Alberto Panerai, Paola Sacerdote)....Pages 199-207
Measurement of Macrophage Toll-Like Receptor 4 Expression After Morphine Treatment (Mara Castelli, Alberto Panerai, Paola Sacerdote, Silvia Franchi)....Pages 209-217
Front Matter ....Pages 219-219
Conditioned Place Preference (CPP) in Rats: From Conditioning to Reinstatement Test (Maria Scherma, Liana Fattore, Walter Fratta, Paola Fadda)....Pages 221-229
Analysis of Opioid-Seeking Behavior Through the Intravenous Self-Administration Reinstatement Model in Rats (Liana Fattore, Paola Fadda, Mary Tresa Zanda, Walter Fratta)....Pages 231-245
Induction of a High Alcohol Consumption in Rats and Mice: Role of Opioid Receptors in Rats and Mice (Roberto Rimondini, Gabriele Campana)....Pages 247-251
Early-Life Stress as a Probe to Study the Opioid System in Developing Rodents (Stefano Loizzo, Alberto Loizzo)....Pages 253-258
Evaluation of μ-Opioid System Functionality in Mouse Pups: Ultrasonic Vocalizations as an Index of Infant Attachment (Francesca R. D’Amato)....Pages 259-265
Back Matter ....Pages 267-270

Citation preview

Methods in Molecular Biology 2201

Santi M. Spampinato Editor

Opioid Receptors Methods and Protocols 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.

Opioid Receptors Methods and Protocols Second Edition

Edited by

Santi M. Spampinato Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy

Editor Santi M. Spampinato Department of Pharmacy and Biotechnology University of Bologna Bologna, Italy

ISSN 1064-3745 ISSN 1940-6029 (electronic) Methods in Molecular Biology ISBN 978-1-0716-0883-8 ISBN 978-1-0716-0884-5 (eBook) https://doi.org/10.1007/978-1-0716-0884-5 © Springer Science+Business Media, LLC, part of Springer Nature 2021 This work is subject to copyright. All rights are reserved 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 Humana 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.

Dedication To my wife, Anna, for her love, patience and encouragement To my grandchildren Aurora and Santi

v

Preface Opioid receptors, beyond their involvement in pain transmission, play a number of relevant physiological roles in the central nervous system and in peripheral organs. Opioid receptors can be considered a crossroads where endogenous opioid peptides and foreign opioids and opiates meet the cell and transmit their messages to another vast array of stimulus-response mechanism. In recent years, studies on their emerging roles have been favored by numerous and fruitful techniques that have opened new avenues of preclinical and clinical research that demands multidisciplinary approaches. The post-genomic era has opened up novel opportunities for the exploitation of these novel technologies. As an increasing number of investigators seek to harness the fruits of knowledge in these emerging fields, it is essential that well-tested protocols are made available to researchers. With this in mind, it is apposite to provide a collection of protocols to favor innovative studies on opioid receptors written by experts who are routinely employing these techniques in their laboratories. This book presents the protocols in the stepwise “cookbook” style of this well-known book series and summarizes of state-of-the art methods that have been utilized for understanding opioid receptor functionality at molecular, cellular, structural, and organism levels. Opioid Receptors: Methods and Protocols—Second Edition is, hence, an invaluable guide for researchers in the fields of neuroscience, biochemistry, pharmacology, and molecular biology. Part I of this book (Chapters 1–8) focuses on procedures to evaluate genetics of opioid receptors as well as their transcriptional and posttranscriptional regulation. An overview of genetic analysis of opioid receptors with sequencing methods is included (Chapter 1). A technique for the posttranscriptional analysis of opioid receptor genes is presented (Chapter 2). Furthermore, a protocol dedicated to co-localization and cellular distribution of opioid receptors is described (Chapter 3), and the use of bioluminescence energy transfer in living cells to investigate protein-protein interactions of opioid receptors is included (Chapters 4 and 5). Imaging of opioid receptors is investigated adopting an ultrasensitive technique based on bioconjugation of nanoruby (Chapter 6), and these receptors are detected in peripheral tissues by immunohistochemistry (Chapter 7) and in immune cells by real-time reverse transcription PCR (Chapter 8). Part II (Chapters 9–16) illustrates methods for the analysis of opioid receptors activated by selective agonists. A technique aimed to monitor internalization and interaction of mu opioid receptors in the spinal cord of morphine-tolerant mice is reported (Chapter 9). Strategies for analysis of signaling events modulated by opioid receptors activated by agonist ligands are described. Following opioid receptor activation, GTP will replace GDP on the α-subunit of the G-protein, leading to a dissociation of the βγ-subunit. The [35S]GTPγS autoradiography assay, described in Chapter 10, is useful to monitor opioid receptor activation in discrete brain areas. Thereafter is described a technique to evaluate opioid-mediated adenylyl cyclase inhibition in living cells by a bioluminescence-based assay (Chapter 11). The development of a whole-cell patch clamp to investigate the activation of inwardly rectifying potassium channel opioid receptor agonists in peripheral sensory neurons following nerve injury is reported (Chapter 12).

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Clinical studies indicate that opioids may exacerbate the symptoms of HIV-associated neurocognitive disorders (HAND). Interestingly, morphine increases neuronal iron and ferritin levels, suggesting that opioids may also modulate neuronal iron homeostasis. Understanding how opioids regulate neuronal iron metabolism may help to identify novel drug targets in HAND with potential relevance to other neurocognitive disorders. New molecular approaches that can be used to understand how opioids modulate neuronal iron are described in Chapter 13. Procedures to investigate two innovative research areas involving opioid receptors in modulating immune cell adhesion (Chapter 14) and brain cortical cell viability (Chapter 15) are reported. Finally, biased agonists at opioid receptors have attracted increasing interest in the last decade as they have emerged as more effective and safer candidate analgesics. In Chapter 16, promises, pitfalls, and future perspective of biased agonists at MOR and KOR opioid receptors are discussed. Methodological insights are provided with regard to the most appropriate experimental settings to be employed aiming at developing novel biased KOR agonists. Part III (Chapters 17–19) reports experimental techniques to investigate opioid receptor-mediated functions at organismal level in a physiological or pathological context. In Chapter 17 is described the analysis of cutaneous stimulation-induced sensory input by von Frey hairs. The immunosuppressive effects mediated by opioids are central to the in vivo activation of opioid receptors, and Chapters 18 and 19 explain strategies toward attaining this objective. Part IV (Chapters 20–24) showcases protocols for the analysis of behavioral effects induced by opioids. Opioid addiction represents an important health concern, and animal models have been crucial in understanding the neurobiology and pathophysiology of this complex disease. Although animal models of addiction do not fully reproduce the human condition, they do permit investigation of specific elements of this process as well as identification of potential therapeutic targets. In Chapter 20, a step-by-step description of morphine-conditioned place preference model is reported that represents a useful preclinical model extensively used to study the rewarding/aversive effect of drugs. In Chapter 21, a procedure to evaluate heroin-seeking reinstatement in the rat is described that is useful to study the mechanisms underlying relapse to heroin and vulnerability factors that enhance the resumption of heroin-seeking behavior. In Chapter 22 is presented a procedure to investigate the role of opioid receptors in alcoholism by adopting a model that combines chronic ethanol exposure procedures with voluntary ethanol drinking in rodents. Chapter 23 considers an animal model to study the pathophysiological alterations connected to hypothalamic-pituitary-adrenal axis hyperactivity. This alteration is induced by an early-life stressful procedure involving the endogenous opioid system. Behavioral tests designed to evaluate the activity and involvement of opioid receptors in pups are described in Chapter 24. I sincerely hope that these protocols will help both experienced and new entrants in this field to carry out their experiments successfully. Finally, I would like to thank all the authors for their outstanding contributions and the series editor, Professor John M. Walker, for valuable editorial help. Bologna, Italy

Santi M. Spampinato

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

PART I

TRANSCRIPTIONAL AND POST-TRANSCRIPTIONAL ANALYSIS AND CELLULAR DETECTION OF OPIOID RECEPTORS

1 Overview of Genetic Analysis of Human Opioid Receptors. . . . . . . . . . . . . . . . . . . Santi M. Spampinato 2 Renilla Luciferase Reporter Assay to Study 30 -UTR-Driven Posttranscriptional Regulation of OPRM1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gabriele Vincelli and Andrea Bedini 3 Fluorescence Colocalization Analysis of Cellular Distribution of MOR-1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vittoria Borgonetti and Nicoletta Galeotti 4 Monitoring Opioid Receptor Interaction in Living Cells by Bioluminescence Resonance Energy Transfer (BRET) . . . . . . . . . . . . . . . . . . . . Monica Baiula 5 Bioluminescence Resonance Energy Transfer (BRET) to Detect the Interactions Between Kappa Opioid Receptor and Nonvisual Arrestins. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Andrea Bedini 6 Functionalization and Bioconjugation of Nanoruby for Long-Term, Ultrasensitive Imaging of Mu-Opioid Receptors . . . . . . . . . . . . . Rashmi Pillai, Mark Connor, and Varun K. A. Sreenivasan 7 Immunohistochemical Analysis of Opioid Receptors in Peripheral Tissues. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yvonne Schmidt and Halina Machelska 8 Real-Time Quantitative Reverse Transcription PCR for Detection of Opioid Receptors in Immune Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ¨ zgu ¨ r Celik, Dominika Labuz, and Halina Machelska Melih O

PART II

v vii xiii

3

15

27

35

45

59

71

83

ANALYSIS OF SIGNALING EVENTS MODULATED BY OPIOID RECEPTORS

9 Quantitative Analysis of MOR-1 Internalization in Spinal Cord of Morphine-Tolerant Mice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 Vittoria Borgonetti and Nicoletta Galeotti 10 GTPγS-Autoradiography for Studies of Opioid Receptor Functionality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 Alfhild Gro¨nbladh and Mathias Hallberg

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12

13

14

15

16

Contents

Evaluating Opioid-Mediated Adenylyl Cyclase Inhibition in Live Cells Using a BRET-Based Assay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Preeti Manandhar, Shivani Sachdev, and Marina Santiago Patch Clamp Analysis of Opioid-Induced Kir3 Currents in Mouse Peripheral Sensory Neurons Following Nerve Injury . . . . . . . . . . . . . . . Viola Seitz, Philip Sto¨tzner, Dominika Labuz, and Halina Machelska Opioid Modulation of Neuronal Iron and Potential Contributions to NeuroHIV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bradley Nash, Elena Irollo, Renato Brandimarti, and Olimpia Meucci An in Vitro Assay to Study the Role of Opioids in Modulating Immune Cell Adhesion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Monica Baiula Assessing Cell Viability Effects of Opioids in Primary Cortical Cells from Rat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Alfhild Gro¨nbladh, Erik Nylander, Sofia Zelleroth, and Mathias Hallberg The Quest for More Effective Analgesics with Reduced Abuse Liability and Fewer Adverse Effects: Promises, Pitfalls, and Future Perspectives of Biased Agonists at Opioid Receptors . . . . . . . . . . . . . . Andrea Bedini

PART III 17

18

19

127

139

163

171

181

MODEL SYSTEMS TO STUDYING OPIOID RECEPTORMEDIATED FUNCTIONS

Mechanical Nociception in Mice and Rats: Measurement with Automated von Frey Equipment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195 Gabriele Campana and Roberto Rimondini Evaluation of Murine Macrophage Cytokine Production After In Vivo Morphine Treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199 Silvia Franchi, Mara Castelli, Sarah Moretti, Alberto Panerai, and Paola Sacerdote Measurement of Macrophage Toll-Like Receptor 4 Expression After Morphine Treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209 Mara Castelli, Alberto Panerai, Paola Sacerdote, and Silvia Franchi

PART IV 20

117

BEHAVIORAL EFFECTS MEDIATED BY OPIOID RECEPTORS

Conditioned Place Preference (CPP) in Rats: From Conditioning to Reinstatement Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221 Maria Scherma, Liana Fattore, Walter Fratta, and Paola Fadda

Contents

21

22

23

24

Analysis of Opioid-Seeking Behavior Through the Intravenous Self-Administration Reinstatement Model in Rats. . . . . . . . . . . . . . . . . . . . . . . . . . . Liana Fattore, Paola Fadda, Mary Tresa Zanda, and Walter Fratta Induction of a High Alcohol Consumption in Rats and Mice: Role of Opioid Receptors in Rats and Mice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Roberto Rimondini and Gabriele Campana Early-Life Stress as a Probe to Study the Opioid System in Developing Rodents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Stefano Loizzo and Alberto Loizzo Evaluation of μ-Opioid System Functionality in Mouse Pups: Ultrasonic Vocalizations as an Index of Infant Attachment . . . . . . . . . . . . . . . . . . . Francesca R. D’Amato

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

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Contributors MONICA BAIULA • Department of Pharmacy and Biotechnology (FaBiT), University of Bologna, Bologna, Italy ANDREA BEDINI • Department of Pharmacy and Biotechnology (FaBiT), University of Bologna, Bologna, Italy VITTORIA BORGONETTI • Department of Neuroscience, Psychology, Drug Research and Child Health (Neurofarba), University of Florence, Florence, Italy RENATO BRANDIMARTI • Department of Pharmacology & Physiology, Drexel University College of Medicine, Philadelphia, PA, USA; Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy GABRIELE CAMPANA • Department of Pharmacy and Biotechnology (FaBiT), University of Bologna, Bologna, Italy MARA CASTELLI • Department of Pharmacological and Biomolecular Science, University of Milano, Milan, Italy ¨ ZGU¨R CELIK • Department of Experimental Anesthesiology, Charite´— MELIH O Universit€ atsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany MARK CONNOR • Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, Macquarie Park, NSW, Australia FRANCESCA R. D’AMATO • Institute of Biochemistry and Cellular Biology, National Research Council, Rome, Italy PAOLA FADDA • Division of Neuroscience and Clinical Pharmacology, Department of Biomedical Sciences, University of Cagliari, Cittadella Universitaria di Monserrato, Cagliari, Italy; Institute of Neuroscience-Cagliari, CNR National Research Council of Italy, Cagliari, Italy; National Institute of Neuroscience (INN), University of Cagliari, Cagliari, Italy LIANA FATTORE • Institute of Neuroscience-Cagliari, CNR National Research Council of Italy, Cagliari, Italy; Division of Neuroscience and Clinical Pharmacology, Department of Biomedical Sciences, University of Cagliari, Cittadella Universitaria di Monserrato, Cagliari, Italy SILVIA FRANCHI • Department of Pharmacological and Biomolecular Science, University of Milano, Milan, Italy WALTER FRATTA • Division of Neuroscience and Clinical Pharmacology, Department of Biomedical Sciences, University of Cagliari, Cittadella Universitaria di Monserrato, Cagliari, Italy; National Institute of Neuroscience (INN), University of Cagliari, Cagliari, Italy NICOLETTA GALEOTTI • Department of Neuroscience, Psychology, Drug Research and Child Health (Neurofarba), University of Florence, Florence, Italy ALFHILD GRO¨NBLADH • The Beijer Laboratory, Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden; Division of Biological Research on Drug Dependence, Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden

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Contributors

MATHIAS HALLBERG • The Beijer Laboratory, Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden; Division of Biological Research on Drug Dependence, Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden ELENA IROLLO • Department of Pharmacology & Physiology, Drexel University College of Medicine, Philadelphia, PA, USA DOMINIKA LABUZ • Department of Experimental Anesthesiology, Charite´— Universit€ atsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany STEFANO LOIZZO • Department of Cardiovascular, Endocrine-Metabolic Diseases and Aging, ` , Rome, Italy Istituto Superiore di Sanita ALBERTO LOIZZO • Department of Cardiovascular, Endocrine-Metabolic Diseases and ` , Rome, Italy Aging, Istituto Superiore di Sanita HALINA MACHELSKA • Department of Experimental Anesthesiology, Charite´— Universit€ atsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany PREETI MANANDHAR • Department of Biomedical Sciences, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW, Australia OLIMPIA MEUCCI • Department of Pharmacology & Physiology, Drexel University College of Medicine, Philadelphia, PA, USA; Department of Microbiology & Immunology, Drexel University College of Medicine, Philadelphia, PA, USA; Center for Neuroimmunology and CNS Therapeutics, Institute for Molecular Medicine and Infectious Disease, Drexel University College of Medicine, Philadelphia, PA, USA SARAH MORETTI • Department of Pharmacological and Biomolecular Science, University of Milano, Milan, Italy BRADLEY NASH • Department of Pharmacology & Physiology, Drexel University College of Medicine, Philadelphia, PA, USA ERIK NYLANDER • The Beijer Laboratory, Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden; Division of Biological Research on Drug Dependence, Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden ALBERTO PANERAI • Department of Pharmacological and Biomolecular Science, University of Milano, Milan, Italy RASHMI PILLAI • EMBL Australia Node in Single Molecule Science, School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia; Department of Physics and Astronomy, Faculty of Science and Engineering, Macquarie University, Macquarie Park, NSW, Australia ROBERTO RIMONDINI • Medical and Surgical Sciences Department (DIMEC), University of Bologna, Bologna, Italy PAOLA SACERDOTE • Department of Pharmacological and Biomolecular Science, University of Milano, Milan, Italy SHIVANI SACHDEV • Department of Biomedical Sciences, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW, Australia MARINA SANTIAGO • Department of Biomedical Sciences, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW, Australia MARIA SCHERMA • Division of Neuroscience and Clinical Pharmacology, Department of Biomedical Sciences, University of Cagliari, Cittadella Universitaria di Monserrato, Cagliari, Italy YVONNE SCHMIDT • Department of Experimental Anesthesiology, Charite´— Universit€ atsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany

Contributors

xv

VIOLA SEITZ • Department of Experimental Anesthesiology, Charite´—Universit€ atsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany; Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany SANTI M. SPAMPINATO • Department of Pharmacy and Biotechnology (FaBiT), University of Bologna, Bologna, Italy VARUN K. A. SREENIVASAN • EMBL Australia Node in Single Molecule Science, School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia; Department of Physics and Astronomy, Faculty of Science and Engineering, Macquarie University, Macquarie Park, NSW, Australia PHILIP STO¨TZNER • Department of Experimental Anesthesiology, Charite´— Universit€ atsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany GABRIELE VINCELLI • Evotec, Princeton, NJ, USA MARY TRESA ZANDA • Division of Neuroscience and Clinical Pharmacology, Department of Biomedical Sciences, University of Cagliari, Cittadella Universitaria di Monserrato, Cagliari, Italy SOFIA ZELLEROTH • The Beijer Laboratory, Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden; Division of Biological Research on Drug Dependence, Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden

Part I Transcriptional and Post-Transcriptional Analysis and Cellular Detection of Opioid Receptors

Chapter 1 Overview of Genetic Analysis of Human Opioid Receptors Santi M. Spampinato Abstract The human μ-opioid receptor gene (OPRM1), due to its genetic and structural variation, has been a target of interest in several pharmacogenetic studies. The μ-opioid receptor (MOR), encoded by OPRM1, contributes to regulate the analgesic response to pain and also controls the rewarding effects of many drugs of abuse, including opioids, nicotine, and alcohol. Genetic polymorphisms of opioid receptors are candidates for the variability of clinical opioid effects. The non-synonymous polymorphism A118G of the OPRM1 has been repeatedly associated with the efficacy of treatments for pain and various types of dependence. Genetic analysis of human opioid receptors has evidenced the presence of numerous polymorphisms either in exonic or in intronic sequences as well as the presence of synonymous coding variants that may have important effects on transcription, mRNA stability, and splicing, thus affecting gene function despite not directly disrupting any specific residue. Genotyping of opioid receptors is still in its infancy and a relevant progress in this field can be achieved by using advanced gene sequencing techniques described in this review that allow researchers to obtain vast quantities of data on human genomes and transcriptomes in a brief period of time and with affordable costs. Key words Exon, Gene polymorphism, Intron, Mu-opioid receptor, Mutation, Next-generation sequencing, Opioid receptor genes

1

Introduction Opioid receptors belong to the rhodopsin family of G-proteincoupled receptors (GPCRs) and modulate downstream signaling through interactions with heterotrimeric G proteins. They are classified into μ-opioid receptor (MOR), δ-opioid receptor (DOR), and κ-opioid receptor (KOR) and correspond to the OPRM1, OPRD1, and OPRK1 genes, respectively. These receptors have seven transmembrane domains, three intracellular loops, three extracellular loops, an extracellular N-terminus, and an intracellular C-terminus. All three receptors present a high homology within the transmembrane domains, which are arranged in a helical pattern, but have less homology in the extracellular regions. There are also many similarities in their binding pockets that, once activated by an agonist, may result in activation of the opioid receptor and

Santi M. Spampinato (ed.), Opioid Receptors: Methods and Protocols, Methods in Molecular Biology, vol. 2201, https://doi.org/10.1007/978-1-0716-0884-5_1, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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subsequent downstream signaling. Differences of the extracellular loops contribute to influence ligand–receptor interaction and allow varying degrees of selectivity between different endogenous opioid peptides and opioid receptors. MOR is activated by met-enkephalin, endomorphins, and β-endorphin. Leu-enkephalin and deltorphin have been shown to activate DOR, while dynorphins constitute a family of peptides specific for the KOR. Many of the endogenous opioid peptides show some affinity for more than one opioid receptor. Differences among intracellular regions contribute to the specificity of downstream signaling and account for the different pathways activated by the opioid receptors [1–3]. Intracellular receptor domains interact with heterotrimeric Gi/ G0 proteins, which when activated by the binding of an agonist modulate the separation of α and βγ subunits. G protein subunits may alter ion channel activity and decrease cell membrane potential, as well as activate MAPK pathways producing changes in gene expression [4]. Albeit the different opioid receptors display similar signaling pathways, the differences in the intracellular domains of MOR, DOR, and KOR result, when activated by agonists, in the expression of different phenotypes. MOR and DOR activation contributes to analgesia and results in rewarding effects, while KOR activation may cause aversion and dysphoria. Opioid receptors may form heterodimers that also occur in vivo and have been shown to regulate unique phenotypes different from those modulated by individual receptors, adding further complexity to opioid receptor signaling [5].

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Genetic Polymorphisms of Opioid Receptors Genome sequencing of different ethnic groups has identified 3324 polymorphisms in the OPRM1 gene, which occupies a region of approximately 200 kb on the long arm of chromosome 6 [6]. The majority of these polymorphisms display a low frequency and seem to possess a limited relevance at the population level. However, 1395 of the known genetic variants have allele frequencies greater than 1% in the considered population. The most common and most studied non-synonymous SNP is rs1799971; this polymorphism is located in exon 1, where a change from adenosine (A) to guanosine (G) in nucleotide position 118 (A118G) results in a change in amino acid sequence in which asparagine (Asn) 40 is replaced by aspartic acid (Asp) (designated N40D) and occurs more frequently in non-African populations [6]. Manglik et al. [7] have confirmed that after elimination of this extracellular domain, the basic threedimensional structure of the receptor is not modified. Previous studies have reported that this SNP could be associated with addictive behaviors for several drugs, but more

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extensive studies did not confirm these preliminary observations, and the A118G polymorphism has been reported either to increase or to reduce the risk of substance abuse. Other investigators have showed that pain-related evoked potential responses were lower among individuals with G alleles compared to AA homozygotes [8]. However, other researchers did not confirm any association between OPRM1 SNPs (including A118G) and increased pain sensitivity or chronic widespread pain [9]. As regards ethnic diversity, in comparison to non-Hispanic whites, African Americans report higher levels of pain and disability associated with several pain conditions [10–15]. In addition, higher experimental pain sensitivity has been observed among African Americans [16, 17]. Though literature is limited regarding Hispanics, higher pain and inadequate analgesia have been reported [18]. Among Asians, carriers of the rare G allele on A118G revealed generally increased clinical pain and analgesic response differences [19], although limited ethnic group comparisons exist. Previously, Bond et al. [20] have reported that A118G resulted in increased signaling through MOR by the endogenous opioid peptide β-endorphin; however, recently, other studies did not confirm this hypothesis [21, 22]. Several functional effects have been linked to the A118G polymorphism. The G allele of A118G creates a novel CpG-methylation site, preventing upregulation of OPRM1 in response to prolonged opioid administration [22]. mRNAs with the variant G allele are less abundant in human brain than the A allele and studies on cell lines have ascertained that the A118G variant may reduce the expression of MOR at the cell surface [23, 24]. Decreased accumulation of the second-messenger cAMP-transfected cells was observed in the presence of morphine, methadone, and DAMGO [24]. This reduced signaling, following DAMGO activation, has also been shown in human postmortem brain tissue [25]. In contrast, other data suggest that β-endorphin has higher binding affinity and increased signaling at the different opioid receptors [20]. In addition to genetic variation, the OPRM1 gene also displays significant structural variations. Alternative splicing of 15 known exons produces at least 23 previously described splice variants; 16 of these variants may be translated into protein products [26]. Despite the large number of total exons, individual splice variants contain only 3–5 exons. The 30 -UTR of OPRM1 is also known to vary in size, with some isoforms in both mice and humans known to have UTRs greater than 10 kb in length [27]. Considering the potential role of 30 -UTRs in regulating transcript expression through miRNA binding and other mechanisms, the UTR length in OPRM1 may participate in the regulation of protein levels of the different isoforms [28].

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Fig. 1 Mutations in the OPRM1 gene related to the exonic organization. (a) Locations of polymorphisms in the gene. (b) Exonic organization of mRNA. (c) Sequence of the mu-opioid receptor protein. The position of five mutations that produce an amino acid exchange frequently reported (5%) is indicated in the protein sequence (reproduced from ref. [58] with permission from Springer)

Other OPRM1 polymorphisms are found at high frequency, and therefore any functional consequence would be relevant for opioid therapy [6]. In the OPRM1 sequence 24 SNPs have been identified that cause an amino acid exchange or were proposed to cause any functional consequence or occurred frequently. However, only five SNPs have a reported frequency of at least 5%: G-172T, C17T, A118G, IVS2–31G>A, and IVS2–691C>G (Fig. 1). Lo¨tsch and Geisslinger [29, 30] have showed that the IVS2691C>G (44.5%) and the IVS2-31G>A (8.9%) SNPs in intron 2 do not affect opioid pharmacodynamics whereas G172T and C17T SNPs have been poorly studied. Therefore, at the moment, the clinical interest remains strictly restricted to the A118G SNP. The human OPRK1 gene is located on chromosome 8q11.2. It presents at least four major exons and three introns, and the 30 -UTR region of 3096 nucleotides in length [31]. The G36T SNP (rs1051660) may be associated with drug dependence. Xuei et al. [32] have examined 13 SNPs throughout OPRK1 gene in alcohol-dependent Caucasians and observed a number of gene variants linked with an increased risk for alcohol dependence. An insertion of 830 bp was found 1389 bp upstream of the transcription start site of OPRK1 [33] and it has been proposed that this could be associated with alcohol dependence in Caucasians. OPDR1 gene polymorphisms have been poorly investigated [34].

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Analysis of Gene Variants of Opioid Receptors Structural variations of opioid receptors comprise different types of genomic variants including deletions, duplications, inversions, transpositions, translocations, and complex rearrangements. Different individuals may differ by thousands of variants. Approaches to identify the genetic basis of rare Mendelian disorders have been largely based on well-established techniques such as positional cloning and linkage analysis followed by targeted candidate gene screening. Recently, investigations of these rare Mendelian disorders have received a great contribution due to the technical advance of a new DNA sequencing technology termed “next-generation sequencing,” also known as deep resequencing, or massively parallel sequencing, which is speeding up the investigation of rare disorders [35]. DNA sequencing was originally developed in 1975 by Sanger and Coulson [36] that adopted a method based on polyacrylamide gel electrophoresis, which allows DNA fragments to be distinguished by their size. This technique is still used widely today. This “Sanger sequencing” or first-generation sequencing is founded on the use of oligonucleotide primers on either side of the selected DNA sequence followed by the addition of DNA polymerase and a mixture of nucleotide “building blocks” enabling the generation of multiple copies of the original DNA sample. The use of chain-terminating nucleotides in 1977 [37] allowed the generation of a whole array of different copies of the original DNA sequence “chain stopped” at all possible lengths, which are then separated out on gel or capillary system by electrophoresis. Using known specific labeled nucleotides (A, C, T, or G) it is possible to assemble the original DNA sequence. In 1977 Maxam and Gilbert [38] published a sequencing method employing radioactive labeling of double-stranded DNA fragments. The DNA was then cleaved by base-specific chemical reactions and the fragments were separated by electrophoresis. In the same year another method was published that was an improvement of Sanger’s method with the dideoxy or chain termination method. Instead of chemical cleavage of the DNA, the process depends on 32P-labeled chain-terminating dideoxy nucleotides, which prevent further extension of the sequence upon incorporation. Each reaction generates fragments of increasing size, ending at the base specified by the reaction, i.e., each A, T, C, or G. In 1986, Leroy Hood at Caltech, in collaboration with Applied Biosystems (ABI), published the first report of sequencing data being collected through a computer [39]. This technology, based on Sanger’s dideoxy method, uses sequencing primers fluorescently end-labeled with four different colors to represent each base.

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Reactions are then run simultaneously through a polyacrylamide tube gel, with the DNA recognized by its fluorescence as it passes a detector. Innovative ABI instruments were released in the following years with dedicated sequencing facilities set up with the eventual aim of sequencing the human genome. The development of the Applied Biosystems capillary sequencer (ABI 3700) in the late 1990s allowed simultaneous sequencing of up to 96 samples through separate capillaries filled with non-cross-linked polymer matrix [40]. This method has been used in several studies focused on human receptor genotyping [41, 42]. A further improvement was the ABI TaqMan SNP genotyping assay (Applied Biosystems) adopted to carry out OPRM1 genotyping by Bortsov et al. [43], Wang et al. [44], and Ashenhurst et al. [34]. Rhodin et al. [45] have employed the Handy Bio-Strand method for the SNP genotyping of OPRM1 A118G (rs1799971). Briefly, the amplified DNA was spotted on a microporous nylon thread (Bio-Strand) and hybridized with allele-specific oligonucleotide competitive hybridization. The Cy5 oligonucleotide Cy5-Tag1 was used as a landmark. Next-generation sequencing may also enable the elucidation of the contribution of rare alleles in common disorders, potentially offering significant breakthroughs in our understanding. Furthermore, based on current thinking, the whole genome does not need to be sequenced to identify polymorphisms restricted to opioid receptors. Next-generation sequencing consists of multiple, short, overlapping reads of fragments of DNA which can be aligned against a reference genome or assembled “de novo” if no information of the reference genome is available [46]. It is more faster than the previously available Sanger sequencing method but, due to the need for overlapping reads to allow fragments to be aligned, the required number of reads per nucleotide position is increased. This means that thousands or millions of pieces of DNA can be sequenced at the same time. This technique is less affordable in genomic regions with extensive nucleotide repeats. Eighty-five percent of pathogenic mutations causing Mendelian disorders are found within the segments coding for proteins (exons) [47], which collectively are referred to as the “human exome” [48]. Whole-“exome” sequencing uses this technique except that complementary strands to known exons (i.e., the protein-coding regions of each gene) are used to extract fragments covering the exonic regions of a gene prior to starting sequencing. Initially DNA is fragmented into multiple short segments known as “shotgun library”; thereafter, adaptors are bound to the ends of each fragment. The adaptors consist of short sequences of DNA that have priming sites within them for the subsequent amplification steps. The segments of DNA (complete with adaptors) are then mixed with probes that correspond to specific regions within

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the exome. The shotgun library is then “enriched” for the sequences of interest, using beads or a solid plate to allow physical separation of the exome from the remaining DNA, and this is washed away. Custom arrays can be designed to enrich for specific groups of genes of interest, the whole exome, and exon-flanking regions. Several manufacturers, adopting different techniques, sell nextgeneration sequencing platforms [49]. The most common DNA sequencing techniques comprise the Illumina (previously known as Solexa) and the 454 method (also known as Roche FLX). In the 454 method, DNA is broken into small fragments that are attached to DNA adaptors. Thereafter, small beads containing brief oligonucleotide sequences matching parts of the adaptors are added. Thus, one DNA fragment binds to each bead. DNA stands are amplified on beads and denatured to obtain single-stranded fragments. Single beads are transferred into wells on a plate together with polymerase enzyme beads for sequencing. In this technique, the pyrosequencing method has been adopted that allows shotgun sequencing without cloning any of the DNA. Pyrosequencing involves a DNA synthesis reaction, where each of the four dNTP bases is applied one after another. During the DNA synthesis reaction, nucleotides are added separately (i.e., only A, then T, then C, then G) and a phosphate group is released when a nucleotide is incorporated. Pyrosequencing method measures the amount of phosphate released as each dNTP is added to the reaction and incorporated, allowing determination of the sequence of each fragment [51]. This method can produce 1 million bases of sequence with 99.5% accuracy [50, 51]. In the Illumina method, DNA is sheared into short fragments; then adaptors (short DNA sequences) are bound to the DNA fragments and these complexes are put onto a hollow slide with a lawn of primers. DNA fragments bind to a complementary primer on the slide surface and are amplified in clusters before sequencing takes place. Once each segment of DNA is amplified, fluorescent nucleotides are added, together with DNA polymerase and sequencing primers. Fluorescently labeled chain-terminating nucleotides are incorporated into the sequence and measured by a detector. However, the incorporation of the chain-terminating nucleotide is reversible, allowing the synthesis to continue until another chain-terminating nucleotide is incorporated, so the bases in each sequence are measured one at a time. The method can produce 1 billion bases of 30–40 base sequences in a single run [51]. As fluorescent-tagged bases are incorporated to each strand on each bead, in real time, laser activation of the fluorescence can be read. Computers monitor each cluster, and can determine the sequence of many clusters at the same time.

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Lo¨tsch and Geisslinger [51] have employed a pyrosequencing assay to investigate OPRM1 polymorphisms. Deo and colleagues [52] have genotyped their samples using a beadchip (Illumina, San Diego, California, USA) microarray containing a total of 1350 SNPs within 130 candidate genes implicated in addiction and alcoholism. Finally, Lee et al. [53] have the Illumina GoldenGate platform to investigate OPRM1 polymorphisms.

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Pharmacogenetics of Opioid Addiction In recent years several studies have been focused on pharmacogenetics of opioid drugs that may cause addiction [54, 55]. Medications are employed to mitigate opioid addiction; these include naltrexone, buprenorphine, and methadone. Naltrexone is a pure MOR antagonist and may cause withdrawal symptoms if administered to addicted persons. Buprenorphine is a partial MOR agonist, behaving as an antagonist if opioid agonists are administered. Buprenorphine may cause withdrawal symptoms if administered to an opioid-addicted individual who has taken an opioid agonist in the past 6–24 h. Finally methadone, a full MOR agonist, is widely employed to control opioid addiction. Methadone is a mixture of (R) and (S) enantiomers and only the (R) isomer acts as MOR agonist. Genetic variability may be involved in the therapeutic response to pharmacotherapy for opioid addiction. It should be considered that pharmacotherapy in opioid-addicted persons should include regular counseling, treatment of simultaneous diseases, and social assistance. Pharmacogenetics research of opioid addiction has mainly involved methadone [56]. Among the most investigated DNA variants for dose requirement of methadone and therapeutic response are SNP rs1045642 in ABCB1 (adenosine triphosphate (ATP)-binding cassette subfamily B member 1) and CYP2B6*6 haplotype SNPs. SNP rs1045642 did not influence methadone plasma concentrations, methadone dose, or methadone response in a meta-analysis [54]. CYP2B6*6 homozygotes had significantly higher (R)- and (S)-enantiomer methadone plasma levels than noncarriers [54]. However, CYP2B6*6 homozygotes did not differ from noncarriers in therapeutic response or daily dose of methadone. Progress in pharmacogenetics of opioid addiction has yielded some biological insights into methadone dose requirements, related to common variants in a locus 50 to OPRM1. An OPRD1 common variant (rs678849) could also be promising for prediction of therapeutic response to buprenorphine versus methadone [54]. A issue still lacking is the need for randomized, doubleblind, controlled, three-arm trials of naltrexone versus buprenorphine versus methadone, with a sufficiently large population that

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genome-wide significance may be achieved by genotyping participants for common SNPs.

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Opioid Receptor Genotyping and Personalized Medicine Sequencing technology has advanced massively since its birth in the 1970s. Scientists may use many technologies potentially allowing sequencing of whole genomes in a day for less than $1000. The next step and a current hot topic is to provide further insight into the workings of the body in health and disease by looking at the proteins active in particular cell types. This can be achieved in part by looking at the messenger RNA (transcriptomics) and noncoding RNAs showing how genetics affects the cell system in combination with environmental influences. Opioid receptors are linked to different diseases and their pharmacological treatments. Many opioid analgesics are opioid receptor agonists and treatments for addiction include the use of opioid agonists or antagonists. Pharmacogenetic analysis of OPRM1 polymorphisms could help to guide treatment decisions and patients can be prescribed the therapeutic options with the best efficacy and the greatest tolerability. The vast majority of pharmacogenetic studies on OPRM1 have analyzed the effects of A118G; this represents one of the first genetic variants that may be linked with pharmacological outcome. However, intronic and synonymous coding variants in many genes have been shown to have important effects on transcription, mRNA stability, and splicing, thus affecting gene function despite not directly disrupting any specific residue. Opioid receptors have numerous genetic and structural variations, all of which are potential relevant to the field of pharmacogenetics. With the speed at which next-generation sequencing technology is becoming increasingly common [57], future studies can and must start to focus on all of the genetic variations present in the opioid receptor genes.

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endorphin binding and activity: possible implications for opiate addiction. Proc Natl Acad Sci U S A 95:9608–9613 21. Mague SD, Blendy JA (2010) OPRM1 SNP (A118G): involvement in disease development, treatment response, and animal models. Drug Alcohol Depend 108:172–182 22. Oertel BG, Doehring A, Roskam B et al (2012) Genetic-epigenetic interaction modulates mu-opioid receptor regulation. Hum Mol Genet 21:4751–4760 23. Zhang Y, Wang D, Johnson AD et al (2005) Allelic expression imbalance of human mu opioid receptor (OPRM1) caused by variant A118G. J Biol Chem 280:32,618–32,624 24. Kroslak T, Laforge KS, Gianotti RJ (2007) The single nucleotide polymorphism A118G alters functional properties of the human mu opioid receptor. J Neurochem 103:77–87 25. Oertel BG, Kettner M, Scholich K et al (2009) A common human micro-opioid receptor genetic variant diminishes the receptor signaling efficacy in brain regions processing the sensory information of pain. J Biol Chem 284:6530–6535 26. http://www.ensembl.org. Accessed 26 Jan 2020 27. Ide S, Han W, Kasai S et al (2005) Characterization of the 30 untranslated region of the human mu-opioid receptor (MOR-1) mRNA. Gene 364:139–145 28. Wu Q, Law PY, Wei LN et al (2008) Posttranscriptional regulation of mouse mu opioid receptor (MOR1) via its 30 untranslated region: a role for microRNA23b. FASEB J 22:4085–4095 29. Lo¨tsch J, Geisslinger G (2005) Are mu-opioid receptor polymorphisms important for clinical opioid therapy? Trends Mol Med 11:82–89 30. Lo¨tsch J, Geisslinger G (2010) A critical appraisal of human genotyping for pain therapy. Trends Pharmacol Sci 31:312–317 31. Yuferov V, Fussell D, LaForge KS et al (2004) Redefinition of the human kappa opioid receptor gene (OPRK1) structure and association of haplotypes with opiate addiction. Pharmacogenetics 14:793–804 32. Xuei X, Dick D, Flury-Wetherill L et al (2006) Association of the kappa-opioid system with alcohol dependence. Mol Psychiatry 11:1016–1024 33. Edenberg HJ, Wang J, Tian H et al (2008) A regulatory variation in OPRK1, the gene encoding the kappa-opioid receptor, is associated with alcohol dependence. Hum Mol Genet 17:1783–1789

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47. Cooper DN, Krawczak M, Antonorakis SE (1995) The nature and mechanisms of human gene mutation. In: Scriver C, Beaudet AL, Sly WS et al (eds) The metabolic and molecular bases of inherited disease, 7th edn. McGrawHill, New York, pp 259–291 48. Stenson PD, Ball EV, Howells K et al (2009) The Human Gene Mutation Database: providing a comprehensive central mutation database for molecular diagnostics and personalized genomics. Hum Genomics 4:69–72 49. Singleton AB (2011) Exome sequencing: a transformative technology. Lancet Neurol 10:942–946 50. Su Z, Ning B, Fang H et al (2011) Nextgeneration sequencing and its applications in molecular diagnostics. Expert Rev Mol Diagn 11:333–343 51. Lo¨tsch J, Geisslinger G (2006) Relevance of frequent mu-opioid receptor polymorphisms for opioid activity in healthy volunteers. Pharmacogenomics J 6:200–210 52. Deo AJ, Huang YY, Hodgkinson CA et al (2013) A large-scale candidate gene analysis of mood disorders: evidence of neurotrophic tyrosine kinase receptor and opioid receptor signaling dysfunction. Psychiatr Genet 23:47–55 53. Lee MR, Gallen CL, Zhang X et al (2011) Functional polymorphism of the mu-opioid receptor gene (OPRM1) influences reinforcement learning in humans. PLoS One 6:e24203 54. Crist RC, Reiner BC, Berrettini WH (2019) A review of opioid addiction genetics. Curr Opin Psychol 27:31–35 55. Dennis BB, Bawor M, Thabane L et al (2014) Impact of ABCB1 and CYP2B6 genetic polymorphisms on methadone metabolism, dose and treatment response in patients with opioid addiction: a systematic review and metaanalysis. PLoS One 9(1):e86114 56. Berrettini W (2017) A brief review of the genetics and pharmacogenetics of opioid use disorders. Dialogues Clin Neurosci 19:229–236 57. Foo J-N, Liu J-J, Tan E-K (2012) Wholegenome and whole-exome sequencing in neurological diseases. Nat Rev Neurol 8:508–517 58. Spampinato SM (2015) Overview of genetic analysis of human opioid receptors. In: Spampinato SM (ed) Opioid receptors: methods and protocols, vol 1230. Springer, New York, p 13

Chapter 2 Renilla Luciferase Reporter Assay to Study 30 -UTR-Driven Posttranscriptional Regulation of OPRM1 Gabriele Vincelli and Andrea Bedini Abstract MOR expression levels at a specific cell type or tissue significantly contribute to its role in pain transmission and in other responses involving opioid receptors. Therefore, molecular processes regulating MOR levels have gained more and more interest. Recently, posttranscriptional regulation mechanisms have been shown to play a relevant role in influencing MOR expression levels, with polymorphisms and mutations within OPRM1 30 -UTR region impacting the differential opioid-mediated response observed within individuals. Here we report a Renilla luciferase reporter assay format suitable for dissecting the contribution of different and distinct OPRM1 30 -UTR elements to MOR expression levels in a model of glial cells, both under basal conditions and following specific treatments. Key words Mu opioid receptor, 30 -UTR, Posttranscriptional regulation, Gene reporter assay, Renilla luciferase

1

Introduction The regulation of OPRM1 is pivotal since the expression of this receptor modulates the activity of endogenous and exogenous ligands. MOR, the primary product of OPRM1, is expressed not only in neurons but also in immune system cells [1] and in glial cells [2]. The importance of MOR regulation in these cell types emerges from the influence that they can exert on opioid analgesia: for example, glia is a key modulator of neuropathic pain, a chronic status where opioid analgesics become not only inactive, but sometimes even detrimental [3]. The expression of MOR is regulated at nearly all levels: epigenetic [4], transcriptional [5], posttranscriptional [5], translational [6], and posttranslational [7]. The regulation at mRNA level plays a relevant role in modulating MOR expression. Several studies have been focused on the OPRM1 promoter to elucidate the transcriptional regulation of MOR [8]; however, in the last years, interest for the 30 -UTR of OPRM1 mRNA has increased. This region is about

Santi M. Spampinato (ed.), Opioid Receptors: Methods and Protocols, Methods in Molecular Biology, vol. 2201, https://doi.org/10.1007/978-1-0716-0884-5_2, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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13,000 nucleotides long and thus represents a potential site for an extensive posttranscriptional regulation [9]. Till now, several miRNAs have been shown to regulate MOR expression through the binding to the 30 -UTR [10–12]. Furthermore, recent studies highlighted the significant contributions of single-nucleotide polymorphisms within OPRM 30 -UTR to methadone efficacy in treating opioid dependence [13], as well as the role of specific AU-rich element-binding proteins in stabilizing OPRM1 mRNA [14], thus highlighting the interest in dissecting the contribution of different 30 -UTR elements to MOR expression in the frame of diverse physiological and pathological conditions. A gene reporter assay is a technique that uses a reporter gene, which encodes for an easily detectable enzyme that is not expressed in humans and does not need posttranslational modifications, fused to the regulatory element of interest. The activity of the reporter protein (for instance the emitted light) is used as a readout of gene expression, so that the effect of the regulatory element can be isolated from the native context and studied individually (Fig. 1). The same gene without any regulatory element inserted is used as control. So far, several reporter genes have been constructed, such as β-galactosidase, firefly luciferase, Renilla luciferase, and Cypridina luciferase. The substrate of Renilla luciferase (coelenterazine h) is different from that used by firefly luciferase (D-luciferin), making it possible to use the two proteins in the same assay: in dual-luciferase assays one of them is used as the reporter and the other as an internal reference expressed from a constitutive promoter [15]. The presence of an internal reference is useful to normalize sample-to-sample variation, especially due to transfection efficiencies. However, attention has to be paid on this issue, as a perfectly constitutive and universally non-inducible promoter has not yet been described. The most commonly used ones can sometimes lead to misinterpretation of the results [15–17]. Moreover, the modern advancement of the available commercial transfection reagents has allowed the improvement of transfection efficiency so that experiments carried out with one luciferase often present a lower coefficient of variation when compared to normalized ones [18]. Therefore, in many cases it is possible to design the experiment without an internal reference (see Note 1), which also displays the advantage of reducing the number of plasmids that are transfected in the cells to carry out the experiments. As for the dual-luciferase assays, an independent assay using the unregulated luciferase control (i.e., the same vector lacking the 30 -UTR regulatory element) is still needed to allow comparison across the treatments (Fig. 1). Here we describe a gene reporter assay-based method to study the 30 -UTR regulation of MOR expression by distinct 30 -UTR elements in U87-MG cells, a widely used cell model of human glia, this both under basal conditions and after specific treatments.

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Fig. 1 Schematic representation of the gene reporter assay described in this chapter. The transfected plasmids will produce mRNA molecules, in a quantity depending on the promoter and on the effect of the treatments. The mRNA will be translated into protein that will give a luminescent readout. The observed difference between the signals emerging from cells transfected with the regulated or unregulated plasmids is due to the 30 -UTR, as this is the only sequence that varies between them

This method employs an optimized Renilla luciferase developed by SwitchGear Genomics, called RenSP, that presents an enhanced overall enzymatic activity; moreover, this luciferase is fused with a PEST domain that increases the protein turnover, reducing therefore its accumulation, that could otherwise interfere with the measurement of expression changes [19]. SwitchGear has a library of plasmids expressing RenSP under the regulation of different 30 -UTRs, including the one of OPRM1. Similarly, reporter vectors bearing the desired OPRM1 30 -UTR elements may be specifically built up by the researcher; within this frame, to further dissect the contribution of distinct 30 -UTR elements, specific regions within the abovementioned plasmid may be modified by point mutations or deletions (see Note 2). As an unregulated control we used the empty vector, which expresses RenSP from the same promoter, but has a minimal 30 -UTR sequence (see Note 3). This method is also suitable for high-throughput applications.

2 2.1

Materials Cell Plating

1. 70–80% Confluent U87-MG cells (see Note 6). 2. Neubauer cell counting chamber (see Note 4). 3. Trypan blue solution (0.4%). 4. Sterile 96-well polystyrene black plate with clear bottom, tissue culture treated. 5. 100 Antibiotic-antimycotic solution.

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6. U87-MG medium: Eagle’s minimal essential medium (EMEM), 10% FBS, 2 mM L-glutamine. Add to 445 mL of EMEM, 10 mL of filtered FBS, and 5 mL of L-glutamine 200 mM. Store at 4  C. Before usage heat the medium at 37  C and add 1 antibiotic-antimycotic solution. 7. 1 Trypsin/EDTA solution. 8. Sterile PBS. 2.2

Transfection

1. Opti-MEM® (Life Technologies). 2. Lipofectamine ®2000 transfection reagent (Life Technologies). 3. pLightSwitch_3UTR vector DNA (SwitchGear Genomics): One control vector and one or more vectors regulated by distinct elements within the OPRM1 30 -UTR (see Notes 2 and 3).

2.3 Treatments and Readings

1. U87-MG medium. 2. Compounds that should be evaluated are dissolved in a sterile solution suitable for cell culture. 3. LightSwitch Assay Reagent (SwitchGear Genomics). 4. A plate luminometer.

3

Methods The following protocol is set to evaluate the effect of treatments at 24 h performing the assay in triplicate. The design of the experiment is shown in Fig. 2. Twelve wells are needed in total: three that will contain untransfected and vehicle-treated (see Note 5) cells for background measurement (white wells); six wells with cells that will be transfected with the unregulated control plasmid (patterned wells); six wells with cells that will be transfected with the 30 -UTR regulated plasmid (gray wells). For each transfected plasmid, three wells will be treated with the vehicle alone (see Note 5), while three wells will be treated with the compound of interest (black box). To add different time points or different treatments, the number of wells has to be scaled up adding, for each one, three wells for the unregulated plasmid and three for the regulated one. However, no further background wells have to be added. Similarly, if the experiment aims at comparing the contribution of different 30 -UTR elements to MOR expression, the number of wells has to be scaled up adding, for each further regulated plasmid, three wells for the vehicle-treated group and three wells for each compound-treated group. Always mix thoroughly all the solutions (unless indicated otherwise) and prepare a master mix when it is possible, to increase uniformity in the assay conditions. Perform all the passages under a sterile tissue culture hood until step 5 in Subheading 3.3.

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Fig. 2 Schematic representation of the experimental design proposed in this chapter. White wells: cells not transfected and treated with only the vehicle for background measurements. Patterned wells: cells to be transfected with the unregulated control plasmid. Gray wells: cells to be transfected with the 30 -UTRregulated plasmid. Boxed wells: cells that have to be treated with the compound of interest. All the other cells have to be treated only with the vehicle (see Note 5) 3.1

Cell Plating

1. Replace the medium of a 70–80% confluent U87-MG flask (see Note 6) with 10 mL of trypsin and incubate for 5 min at 37  C (see Note 7). 2. Transfer the content of the flask in a 15 mL tube. 3. Spin the cells and resuspend the pellet in 1 mL of PBS. 4. Counts the number of cells using a Neubauer chamber. Use Trypan blue staining to count viable cells (see ref. [18, 20] and Note 4). 5. Per each well that has to be seeded add in a tube 15,000 cells suspended in U87-MG medium in a final volume of 100 μL per well. Prepare the mix for one extra well. In the reported example, 240,000 cells in 1.6 mL are needed for 16 wells (see Note 8). 6. Mix thoroughly and seed the cells by pipetting 100 μL of the cell suspension in each well (see Note 9). 7. Incubate the plate for 24 h at 37  C in 95% air and 5% CO2 atmosphere.

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Transfection

The transfection step is carried out using Lipofectamine® 2000. This reagent is guaranteed by the manufacturer to give a very high efficiency of transfection that is a prerequisite for this experiment (see Note 10). The following protocol is used for the transfection of one of the two plasmids (e.g., the control one) in six wells (Fig. 2). The same procedure has to be used for the other plasmid as well. If multiple plasmids bearing different 30 -UTR elements are to be transfected, the following procedure has to be followed for each further plasmid. Prepare all the mixes for one extra well: in this example for seven wells. 1. Check on an inverted microscope the condition of the cells in each well. Check that they are all healthy, attached, with a normal shape and at similar confluence. 2. Prepare in a tube 500 ng of DNA per each well that has to be transfected diluted in Opti-MEM® to a final volume of 65 μl. In the example 3.5 μg of DNA is diluted in 65 μL of OptiMEM® (see Notes 11 and 12). 3. Prepare in a second tube 1.5 μL of Lipofectamine® 2000 reagent per each well that has to be transfected diluted in Opti-MEM® to a final volume of 65 μL. For instance, 10.5 μL of Lipofectamine® 2000 is diluted in 65 μL of OptiMEM® (see Note 11). 4. Add the diluted DNA to the diluted transfection reagent, vortex for 20 s, and incubate for 20 min at room temperature. 5. Add Opti-MEM® to reach a final volume of 100 μL per each well that has to be transfected. In the example the final volume is 700 μL. 6. Remove the medium from the wells that have to be transfected (see Fig. 2) and add to each one 100 μL of the transfection mix, paying attention to not peel off the cells (see Note 13). 7. Replace the medium of the untransfected background wells with 100 μL of Opti-MEM® each (Fig. 2, white wells). 8. Incubate the plate for 24 h at 37  C in 95% air and 5% CO2 atmosphere.

3.3 Treatments and Readings

1. The day before performing the first gene reporter experiment reconstitute the 100 LightSwitch Assay Reagent. Add 100 μL of the provided “Substrate Solvent” to the tube of lyophilized “Assay Substrate.” Dissolve and aliquot in tubes protected from light, so that each tube has the substrate needed for one experiment: consider that, being a 100 substrate, 1 μL for each well is needed. Store each aliquot at 80  C and thaw aliquots few minutes before use. Avoid additional freeze-thaw cycles.

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2. Check on an inverted microscope the condition of the cells in each well. Check that they are all healthy, attached, and with a normal shape. 3. Prepare two tubes, one containing fresh U87-MG medium (basal medium, see Note 5) and the other containing U87-MG medium adding the compound to be tested at the desired concentration (treatment medium). Consider at least 100 μL per well. Prepare in excess. 4. Replace the medium in all the untransfected wells and in those that are not going to be treated with the compound of interest (Fig. 2, unboxed wells, vehicle treated) with 100 μL of basal medium (see Note 5). 5. Replace the medium in the wells that have to be treated with the compound of interest (Fig. 2, boxed wells) with 100 μL of treatment medium. 6. Incubate the plate at 37  C in 95% air and 5% CO2 atmosphere for the desired amount of time (24 h in this example; see also Note 14). 7. Thaw the “Assay Buffer” provided with the LightSwitch substrate. 8. Few minutes before the treatment time is over dilute 1:100 the provided 100 substrate in “Assay Buffer” for a final volume of 100 μL per well (see Note 15). 9. When the treatment time has ended add 100 μL of 1 substrate to each well (see Notes 16–18). 10. Incubate for 30 min at room temperature protected from light (see Note 19). 11. Read in a plate luminometer. For each well read the light emission for 10 s and report the value of counts/s as the total counts divided by 10 (see Note 20). 3.4

Data Analysis

1. Report the values of counts/s of each well in an Excel worksheet (or equivalent). 2. Calculate the average of the signal from background wells. 3. Subtract the background average signal from the signals of all the other wells. 4. Calculate the average of the background-corrected signal for the three wells whose cells were transfected with the control plasmid and treated with only the vehicle; afterwards, express the corrected signal of every well in proportion. 5. Calculate the mean and standard deviation of the signals for each experimental group.

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Fig. 3 Results of a pilot experiment. A stabilizing effect of the treatment on the mRNA level is observed. The graph is reported using mean  SD of each calculated treatment/vehicle ratio (n ¼ 3)

6. For each plasmid employed in the experiment (i.e., the unregulated control plasmid and the regulated one) calculate the ratio of the means of treatment/vehicle. A difference between these values reflects a specific effect of the treatment on the 30 -UTR-mediated modulation of gene expression. 7. Perform statistical analysis (e.g., a t-test) to evaluate the significance of the difference between these two values observed. As an example, Fig. 3 reports the results of an experiment in which the treatment stabilized the OPRM1 mRNA, through the 30 -UTR.

4

Notes 1. Check the coefficient of variation (CV) as the ratio between the standard deviation and the mean within each experimental group: this should be around 10%. If the CV observed is significantly greater than 10%, it is advisable to use an internal reference control [16]. Many of them are available. SwitchGear Genomics offers a dual-luciferase system (LightSwitch dualassay system) that uses a secreted Cypridina luciferase expressed from a constitutive TK promoter. This method has the advantage that the reference luciferase can be measured from a small aliquot taken from each well, while the rest of the assay remains unchanged. Another easy method is to use a dual-luciferase approach, as for example the Dual-Glo® system

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(Promega). This consists of a homogeneous reagent system that allows the subsequent detection of two different luciferases (firefly and Renilla) within the same well. In this case a control vector expressing an unregulated and constitutively expressed firefly luciferase is needed (as for example the vector pGL4.13 by Promega). Finally, a vector expressing an unregulated and constitutively expressed β-galactosidase can be used (as for example pSV-β-galactosidase control vector by Promega, using the Beta-Glo® Assay System to detect the signal). The last option has the disadvantage that the two reporter signals have to be detected in two different plates. In case an endogenous control is included, perform an independent experiment transfecting only the plasmid encoding for this protein to evaluate the effect of the treatment on its expression. Check that no significant difference is observed in endogenous control expression between the cells treated with the compound of interest and those treated with vehicle only. 2. The OPRM1 30 -UTR is more than 13,000 nucleotides (nt) long [9]. Studying the whole regulatory element at once can give several problems (e.g., the resulting plasmid would be about 16 kbp long and it would be difficult to manipulate, transfect, etc.). Moreover, the plasmid available from SwitchGear Genomics contains only the first 500 nt of the OPRM1 30 -UTR. It is advisable to perform experiments using only portions of the 30 -UTR, maybe trying to narrow the interested portion. If interested in studying different portions of the OPRM1 30 -UTR, it may be necessary to clone it in the multiple cloning site of the empty pLightSwitch_3UTR vector. 3. Several control plasmids are available from SwitchGear Genomics: some contain 30 -UTRs of housekeeping genes with different lengths, while others contain non-conserved, noncoding, and non-repetitive human genomic fragments. The easiest control consists instead of the empty vector, containing only a minimal 30 -UTR before the poly-A signal. The use of this vector would avoid any unwanted and unexpected unspecific effect that a longer 30 -UTR can provide. 4. Other counting methods are suitable. It is advisable to always include a viability control to exclude possible dead cells from the count. 5. In this example the vehicle is U87-MG medium alone. If the compound of interest is dissolved in a particular solvent (e.g., ethanol or DMSO) an equal amount of that solvent has to be added to the vehicle. If possible always prefer to dissolve the compound in cell culture water.

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6. For U87-MG the use of cells over the 17th passage should be avoided as a change in some signaling pathways can be observed. 7. The use of trypsin to detach cells from the flask will also help to avoid cell clamps that would make the counting step difficult. Always check the flask content at the microscope before spinning the cells down, to control if a longer exposure to trypsin is needed. 8. It is advisable to plate 3–6 extra wells for backup purpose. During all the operations, uniformity among wells is crucial. It can sometimes happen that some wells present not wellattached cells or clamps of cells. 9. Plating the cells in the wells of the external perimeter of the plate should be avoided to prevent evaporation of samples that could produce artifacts. It is also preferable to fill these wells with medium. 10. Other reagents yielding high transfection efficiency could be used according to their manufacturer recommendations. 11. These steps are designed to be carried out in a small volume to facilitate the DNA-liposome formation. If a bigger amount of wells has to be transfected, the 65 μL volume can be increased, keeping the 1:1 volume proportion of DNA:lipofectamine. Try to keep the volume of this mix to about 10–20% of the final transfection master mix volume. 12. If an internal reference is necessary, the DNA of the plasmid expressing this luciferase has to be considered in the 500 ng of DNA. A usually good ratio between the reporter and reference plasmids is 20:1 in mass. If the total 500 ng of DNA is not changed the quantity of needed Lipofectamine® 2000 remains the same. 13. When removing the medium pay attention not to touch the bottom of the wells with the tip to avoid the detachment of cells. To facilitate the medium removal process it is possible to lean the plate forward. When adding solutions, instead, pipette on the wall of the well to avoid the detachment of cells. 14. If different timings are included in the experiment, replace the medium of each well with basal medium after 24 h from the transfection to block this process. Afterwards, treat the cells so that the treatment times will expire all at the same moment, to increase uniformity in the plate readings. If treatments longer than 24 h are performed plate 10,000 cells instead of 15,000 on day 1. If a combination of long and short times is used include consistent vehicle-treated controls. 15. Prepare in small excess. Mix thoroughly, but avoid vortexing to reduce the formation of bubbles.

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16. If possible use a multichannel pipette. If it is not possible try to be as precise as possible in pipetting. Rapidity is also important as otherwise the incubation time can vary from the first and last wells. 17. The substrate also contains a lysis agent. Therefore, it is sufficient to add it in a 1:1 ratio in each well (i.e., 100 μL in each well). If the luciferase signal is low, it is possible to freeze and thaw the plate to help the lysis of the cells and the release of the luciferase protein. 18. In case an internal reference has been added and a dualluciferase approach has not been chosen, it is necessary to split the samples (see Note 1). In case the LightSwitch dualassay system has been chosen, it is sufficient to take a 20 μL sample for the detection of the Cypridina luciferase signal to be tested in a new plate. In case the galactosidase approach has been chosen, instead, each sample has to be divided into two halves: freeze and thaw the plate and use the pipette tip as a scraper to detach the cells from the well. Collect the 100 μL samples in clean tubes and use 50 μL for the luciferase assay in a new plate, mixing the sample with 50 μL of LightSwitch Assay Reagent. Use the other 50 μL of sample for the assessment of the other reporter activity with the Beta-Glo® Assay System. In all cases refer to the protocols provided by the manufacturer. 19. If more than one plate is used, add the substrate at different times, so that every plate will be read at the luminometer after exactly 30 min. 20. If there is a high number of wells to be read it can be possible to reduce the reading time of each well to reduce the gap between the readings of the first and last wells. References 1. Bo¨rner C, Kraus J, Bedini A et al (2008) T-cell receptor/CD28-mediated activation of human T lymphocytes induces expression of functional μ-opioid receptors. Mol Pharmacol 74:496–504 2. Watkins LR, Hutchinson MR, Johnston IN et al (2005) Glia: novel counter-regulators of opioid analgesia. Trends Neurosci 28:661–669 3. Watkins LR, Hutchinson MR, Milligan ED, Maier SF (2007) “Listening” and “talking” to neurons: implications of immune activation for pain control and increasing the efficacy of opioids. Brain Res Rev 56:148–169 4. Hwang CK, Song KY, Kim CS et al (2007) Evidence of endogenous mu opioid receptor regulation by epigenetic control of the promoters. Mol Cell Biol 27:4720–5736

5. Wei LN, Loh HH (2002) Regulation of opioid receptor expression. Curr Opin Pharmacol 2:69–75 6. Song KY, Hwang CK, Kim CS et al (2007) Translational repression of mouse mu opioid receptor expression via leaky scanning. Nucleic Acids Res 35:1501–1513 7. Williams JT, Ingram SL, Henderson G et al (2013) Regulation of μ-opioid receptors: desensitization, phosphorylation, internalization, and tolerance. Pharmacol Rev 65:223–254 8. Bedini A, Baiula M, Spampinato S (2008) Transcriptional activation of human mu-opioid receptor gene by insulin-like growth factor-I in neuronal cells is modulated

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by the transcription factor REST. J Neurochem 105:2166–2178 9. Ide S, Han W, Kasai S et al (2005) Characterization of the 30 untranslated region of the human mu-opioid receptor (MOR-1) mRNA. Gene 364:139–145 10. Wu Q, Law PY, Wei LN, Loh HH (2008) Posttranscriptional regulation of mouse mu opioid receptor (MOR1) via its 30 untranslated region: a role for microRNA23b. FASEB J 22:4085–4095 11. Ni J, Gao Y, Gong S et al (2013) Regulation of μ–opioid type 1 receptors by microRNA134 in dorsal root ganglion neurons following peripheral inflammation. Eur J Pain 17:313–323 12. Lu Z, Xu J, Xu M et al (2014) Morphine regulates expression of μ-opioid receptor MOR-1A, an intron-retention carboxyl terminal splice variant of the μ-opioid receptor (OPRM1) gene via miR-103/miR-107. Mol Pharmacol 85:368–380 13. Crist RC, Doyle GA, Nelson EC et al (2018) A polymorphism in the OPRM1 30 -untranslated region is associated with methadone efficacy in treating opioid dependence. Pharmacogenomics J 18:173–179 14. Hwang CK, Wagley Y, Law PY et al (2017) Phosphorylation of poly(rC) binding protein 1 (PCBP1) contributes to stabilization of mu opioid receptor (MOR) mRNA via interaction with AU-rich element RNA-binding protein

1 (AUF1) and poly A binding protein (PABP). Gene 20:113–130 15. Shifera AS, Hardin JA (2010) Factors modulating expression of Renilla luciferase from control plasmids used in luciferase reporter gene assays. Anal Biochem 396:167–172 16. Matuszyk J, Ziolo E, Cebrat M et al (2002) Nurr1 affects pRL-TK but not phRG-B internal control plasmid in genetic reporter system. Biochem Biophys Res Commun 28 (1036):1039 17. Ho CK, Strauss JF 3rd (2004) Activation of the control reporter plasmids pRL-TK and pRL-SV40 by multiple GATA transcription factors can lead to aberrant normalization of transfection efficiency. BMC Biotechnol 30:4–10 18. Switchgear technical note. Co-transfection controls with reporter assays. http:// switchgeargenomics.com/sites/default/files/ pdf/LightSwitch_CoTfx.pdf. Accessed 23 Apr 2014 19. Switchgear technical note. LightSwitch System Overview. http://switchgeargenomics.com/ sites/default/files/pdf/LightSwitch_Manual. pdf. Accessed 23 Apr 2014 20. Bastidas O Cell counting with neubauer chamber. Basic hemocytometer usage. Celeromics technical note. www.celeromics.com/en/res ources/docs/Articles/Cell-counting-Neu bauer-chamber.pdf. Accessed 15 Feb 2020

Chapter 3 Fluorescence Colocalization Analysis of Cellular Distribution of MOR-1 Vittoria Borgonetti and Nicoletta Galeotti Abstract The interaction between neurons and glia is pivotal for the development of chronic opioid tolerance. One of the most important mechanisms of cell-to-cell interaction is the Notch signaling pathway. In this chapter we propose a double-immunofluorescence method to observe and quantify the colocalization of Notch-1 and mu-opioid receptor (MOR-1), using both neuronal and astrocyte markers. Key words Morphine, Immunofluorescence

1

Tolerance,

Notch

signaling,

Colocalization,

Mu-opioid

receptor,

Introduction Morphine tolerance is a complex phenomenon involving many cellular processes. Although several hypotheses have been formulated, it is still not fully understood. In a first attempt, research has been focusing the attention only on neural mechanisms involved in opioid tolerance [1]. However, recently a key role for glia cell activation in the development and maintenance of chronic opioid tolerance has been speculated [2, 3]. In particular, it has been demonstrated that chronic systemic morphine administration may increase astrocyte activation in the spinal cord [4, 5]. The presence of opioid receptors in glial cells is still debated [6, 7] and may suggest the existence of a neuron-glia interaction, which is crucial for the development of opioid tolerance. One of the most important mechanisms of cell-to-cell interaction is the Notch signaling pathway [8]. Indeed, it has been reported that, in morphinetolerant mice, MOR-1 activation triggers Notch-1 neuronal signaling activation and this event was mediated by the expression of Jagged from activated astrocyte cells. Double-immunofluorescence technique allows to determine the localization of Notch-1 and MOR-1 in neuronal cells obtained from spinal sections of

Santi M. Spampinato (ed.), Opioid Receptors: Methods and Protocols, Methods in Molecular Biology, vol. 2201, https://doi.org/10.1007/978-1-0716-0884-5_3, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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morphine-tolerant mice [9]. A double-immunofluorescence procedure can be carried out in order to examine the co-distribution of two (or more) different markers [10]. An important aspect of colocalization analysis by immunofluorescence is represented by its quantification. In this chapter, we describe a brief and simple protocol to investigate the localization of two different targets in the same sample. In particular, we investigate the localization of Notch-1 in spinal cord neurons (using NeuN as a typical marker [11]) and in astrocytes (using GFAP as typical marker [12]). Moreover, we report the analysis of MOR-1 localization together with Notch-1 and with pJNK (a marker of astrocyte activation [13]) which is useful to highlight the possible astrocyte localization. To quantify the colocalization of these targets we used an open-source plug-in for ImageJ, i.e., EzColocalization [14].

2 2.1

Materials Solutions

1. NaCl 0.9% (w/v) dissolved in ddH2O (isotonic saline solution). 2. Morphine hydrochloride was dissolved in isotonic saline solution in order to obtain solutions containing 10, 15, 20, or 30 mg/kg solutions.

2.2 Immunofluorescence Buffers

1. Paraformaldehyde (PFA) fixative 4%: For 1 L, add 40 g of paraformaldehyde powder to 1000 mL of preheated (60  C) phosphate-buffered saline (PBS). Using a pipette, add 1 N NaOH dropwise until the solution becomes clear. After that, the solution can be cooled and filtered. Adjust the pH to 7 with 1 N HCl. 2. Sucrose solutions: Prepare 30, 20, and 10% (w/v) sucrose solutions by solubilizing sucrose powder in 1000 mL of PBS 1. 3. Citrate solution: For 1 L, add 2.941 g of sodium citrate to 1000 mL of ddH2O. Adjust pH to 6 with HCl. Then, add 0.5 mL of Tween 20 (see Note 1). 4. PBS low molarity: For 1 L, add 100 mL of 10 isotonic saline solution to 50 mL of 2 phosphate buffer (7.7 g NaOH + 29.2 g NaH2PO4 in 1 L of H2O) and dilute to the final volume with ddH2O. 5. 0.3% Triton X-100 in PBS: For 100 mL, add 100 mL of PBS low molarity to 0.3 mL of Triton X-100. 6. Blocking solution: Dissolve 0.5% bovine serum albumin in 0.3% Triton X-100/PBS.

MOR-1 and Notch-1 Colocalization

29

7. UltraCruz® Aqueous Mounting Medium with DAPI (Santa Cruz Biotechnology). 2.3

Antibodies

1. Use specific antibodies against MOR-1, Notch-1, cleaved Notch-1, NeuN, GFAP, and JNK phosphorylated on Thr183/Tyr185. Suitable working dilutions are assayed in preliminary experiments. Secondary anti-rabbit and anti-goat antibodies are used.

2.4

Other Materials

1. Hot plate apparatus. 2. Cryostat. 3. Microscope slides. 4. Fluorescence microscope. 5. PAP pen for immunostaining. 6. ImageJ software.

2.5 Morphine Nociceptive Tolerance

1. Animals: Male CD1 mice weighing 24–26 g and 4 weeks old are used. 2. Tolerance to morphine-induced antinociception is evaluated as previously described [15]: Inject to mice twice daily with sc morphine hydrochloride solutions at 10:00 AM and 8:00 PM. Administer 10 mg/kg on day 1; on day 2 inject 15 mg/kg; on day 3 inject 20 mg/kg and on day 4 inject 30 mg/kg. 3. Perform the hot plate test to evaluate the development of tolerance to morphine-induced antinociception. Place mice inside a hot plate apparatus set at 50.0  0.1  C and 52.50  0.1  C. Register the nociceptive response for thermal sensitivity as latency to licking in seconds. 4. Sacrifice mice by cervical dislocation for removal of the spinal cord for in vitro analysis on day 5, 30 min after morphine administration.

3

Methods

3.1 Internalization of MOR-1 Assessed by Immunofluorescence Analysis

1. Preparation of the sample for immunofluorescence analysis: Perfuse mice transcardially for 5 min with 4% paraformaldehyde in 0.1 M PBS (1). After perfusion, quickly remove the spinal cord, postfix it for 18 h with the same fixative at 4  C, and transfer them sequentially to 10%, 20%, and then 30% sucrose solution for 24 h at each concentration. Store spinal cords at 80  C until cryostat sectioning. Cutting of the spinal cord can be carried out using the cryostat, at the internal temperature of 20  C. Cut spinal cord transverse sections at a thickness of approximately

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15 μm. Obtain five sections for each slide and preserve them in the refrigerator at 20  C. 2. MOR-1 spinal cord localization: Remove the slides with spinal cord sections from the refrigerator and let them stay for 1 h at room temperature. Thereafter, wash each slice twice for 5 min with 0.3% Triton X-100/PBS. To break the protein cross-links use the citrate solution, which allows unmasking the antigens and epitopes, enhancing the staining intensity of antibodies. For this step, preheat citrate buffer to 95  C and soak slides in the flask containing citrate for 20 min. Remove the flask from the hot plate and cool it at room temperature for another 20 min. Thereafter, wash three times with 0.3% Triton X-100/PBS for 5 min each. Block the sections with blocking solution for 2 h at room temperature. Remove the blocking solution and incubate sections with double immunostaining (see Note 2): (a) Notch-1/NeuN (b) Notch-1/GFAP (c) MOR-1/p-JNK (d) MOR-1/Notch-1 Dilute the antibodies in 0.5% bovine serum albumin containing 0.3% Triton X-100/PBS solution and incubate slices with antibodies at 4  C overnight. Rinse slices three times with 0.3% Triton X-100/PBS for 5 min and incubate the sections with secondary antibody labeled with Invitrogen Alexa Fluor 488 for NeuN, GFAP (490–525, 1:400), and Cruz Fluor 594 for MOR-1 and Notch-1 (592–614, 1:400; Santa Cruz Biotechnology) for 2 h at room temperature in the dark (see Note 3). Gently wash the tissue three times as previously described. Use DAPI, which is present in the mounting medium, to counterstain nuclei. Allow slides to dry for 1–2 h before storing them at 4  C, protected from light. We use a Leica DM6000B digital camera with appropriate excitation and emissions filters for each fluorophore to acquire representative images. Acquire images at 5, 10, 20, and 40 magnification using a digital camera. 3. Quantification of colocalization: EzColocalization is an opensource plug-in for ImageJ which allows to measure colocalization in microscopic images [14] (see Note 4). The plug-in is composed of four modules, namely Inputs, Cell filters, Visualization, and Analysis. Not all modules may be necessary at the same time and for the same protocol. In this chapter we described for example the quantification of Notch-1 and NeuN colocalization.

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4. Settings: Images file must be (see Note 5): (a) Monochromatic (not RGB or CMYK formats). (b) 8-bit, 16-bit, or 32-bit (c) In a format that maintains the original pixel intensity values (i.e., TIFF, RAW, LIF, JPEG). First of all it is necessary to set the Bio-Formats Import Options in the ImageJ program. After that click on Image, type and set 8-bit. Split channels of the image obtaining three different channels: C1 (NeuN, green), C2 (Notch-1, red), and C3 (DAPI, blue). Before moving on, shut down the DAPI channel (see Note 6). 5. Inputs: This section represents the lists of images, alignment, and threshold options. In the section “Images for analysis” set the channel 1 in Reporter 1 and in the channel 2 Reporter 2. For the purpose of this analysis the option “Cell identification input,” which is useful to individuate intracellular and extracellular pixels, is not needed. 6. Visualization: This tab is useful to set the analysis and the right metric for quantifying the localization. The panel contains three sections: heat maps, scatterplots, and metric matrices. Heat maps are color images that show the relative magnitude of reporter signals for each image. Heat map images allow identifying the signal intensity of different cells in a visual range in order to highlight the heterogeneity among cells (i.e., localization, average signal intensity). If cells are heterogeneous, then it may be appropriate to limit the analysis to a subpopulation of cells by using the cell filters in EzColocalization so that measurements are not an average of multiple populations. Moreover, this function indicates if the pixels of the background are at similar level compared to pixels containing target and are able to analyze only pixels with signal greater than background levels using threshold [16]. Scatterplot is the relationship between the signal intensities for different channels. This represents a key point for the determination of the metrics for colocalization analysis. As reported in Fig. 1, in this analysis the scatterplot indicates a linear relationship between the intensities of each channel and for these types of relationship the recommended metrics are the Pearson’s correlation coefficient (PCC), the intensity correlation quotient (ICQ), the Spearman’s rank correlation coefficient (SRC), and the threshold overlap score (TOS). Metric matrices calculate the values of a colocalization metric for many threshold combinations. In EzColocalization up to six different colocalization metrics can be used: TOS with linear or logarithmic scaling, PCC, SRCC, Manders’ colocalization coefficients M1 and M2, and ICQ.

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Fig. 1 Scatter plot of double-immunofluorescence staining of Notch-1 and NeuN in the dorsal horn of spinal cord

7. Analysis: This tab includes three subtabs, namely “analysis metrics,” “metrics info,” and “custom.” The analysis metrics subtab has six metrics for measuring colocalization using two reports (see Note 7). For our analysis, and for the results obtained from the scatterplot, we used PCC metrics to determine the colocalization. PCC is the covariance of two variables divided by the product of their standard deviations [16]. PCC is characterized by determined value range: 1, which indicates anticolocalization. +1, which indicates colocalization. 0, which indicates that there is no colocalization. “Metric info” is a subtab of the “Analysis” tab, which is useful to understand the meaning of each analysis metric. In custom subtab, users can write their own code to analyze images (see Note 8).

MOR-1 and Notch-1 Colocalization

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Notes 1. Citrate solution may need some time to reach the temperature of 95–100  C. Thus, it is recommended to start with a hot plate temperature of 250–300  C for 30 min and control the temperature of citrate solution with a thermometer. When citrate solution reaches 90  C turn down the hot plate temperature gradually. 2. For the double-immunostaining analysis it is necessary that the two antibodies for the two different targets were obtained from different species. Alternatively, antibodies originating from the same species could be visualized by using secondary antibodies conjugated to different fluorophores. 3. Conversely to primary antibodies, which can be added to the slices simultaneously, secondary antibodies must be added separately 2 h apart each. This is important to prevent possible interferences between them. 4. Download: To download and install the ImageJ software go to https://imagej.nih.gov/ij/download.html. The next step is to download the EzColocalization plug-in from http://sites.imagej.net/EzColocalization/plugins. When saving the file, the user should delete the timestamp at the end of the name of the EzColocalization file. 5. For image analysis we used high-magnification image (20 and 40). For images at 20 magnification, measures should be taken in a region of interest in the entire superficial dorsal horn. For images at 40 magnification, measures can be taken on the entire optical section. 6. Use the following settings in the “Bio-Format Import Options” tab: Stack viewing: Hyperstack Color options: Composite and Autoscale 7. To measure the colocalization of three reports the metrics recommended are ICQ, Manders’ coefficients, and TOS. 8. The analysis of the results can be carried out using Microsoft Excel or other spreadsheet software.

References 1. Schulz S, Mayer D, Pfeiffer M et al (2004) Morphine induces terminal μ-opioid receptor desensitization by sustained phosphorylation of serine-375. EMBO J 23:3282–3289 2. Eidson LN, Murphy AZ (2019) Inflammatory mediators of opioid tolerance: implications for

dependency and addiction. Peptides 115:51–58 3. Hutchinson MR, Bland ST, Johnson KW et al (2007) Opioid-induced glial activation: mechanisms of activation and implications for opioid analgesia, dependence, and reward. Sci World J 7:98–111

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4. Chen ML, Cao H, Chu YX et al (2012) Role of P2X7 receptor-mediated IL-18/IL-18R signaling in morphine tolerance: multiple glialneuronal dialogues in the rat spinal cord. J Pain 13:945–958 5. Raghavendra V, Tanga F, Rutkowski MD et al (2003) Anti-hyperalgesic and morphinesparing actions of propentofylline following peripheral nerve injury in rats: mechanistic implications of spinal glia and proinflammatory cytokines. Pain 104:655–664 6. Corder G, Tawfik VL, Wang D et al (2017) Loss of μ opioid receptor signaling in nociceptors, but not microglia, abrogates morphine tolerance without disrupting analgesia. Nat Med 23:164–173 7. Sheng-Chin Kao XZ (2011) Absence of mu opioid receptor mRNA expression in astrocytes and microglia of rat spinal cord. Neuroreport 23:378–384 8. Pierfelice T, Alberi L, Gaiano N (2011) Notch in the vertebrate nervous system: an old dog with new tricks. Neuron 69:840–855 9. Sanna MD, Borgonetti V, Galeotti N (2020) μ Opioid receptor-triggered Notch-1 activation contributes to morphine tolerance: role of neuron—glia communication. Mol Neurobiol 57:331–345

10. Mason DY, Micklem K, Jones M (2000) Double immunofluorescence labelling of routinely processed paraffin sections. J Pathol 191:452–461 11. Wolf HK, Buslei R, Schmidt-Kastner R et al (1996) NeuN: a useful neuronal marker for diagnostic histopathology. J Histochem Cytochem 44:1167–1171 12. Hol EM, Pekny M (2015) Glial fibrillary acidic protein (GFAP) and the astrocyte intermediate filament system in diseases of the central nervous system. Curr Opin Cell Biol 32:121–130 13. Ji RR, Kawasaki Y, Zhuang ZY et al (2006) Possible role of spinal astrocytes in maintaining chronic pain sensitization: review of current evidence with focus on bFGF/JNK pathway. Neuron Glia Biol 2:259–269 14. Stauffer W, Sheng H, Lim HN (2018) EzColocalization: an ImageJ plugin for visualizing and measuring colocalization in cells and organisms. Sci Rep 8:15764 15. Galeotti N, Farzad M, Bianchi E, Ghelardini C (2014) PKC-mediated potentiation of morphine analgesia by St. John’s Wort in rodents and humans. J Pharmacol Sci 124:409–417 16. Adler J, Parmryd I (2010) Quantifying colocalization by correlation: the Pearson correlation coefficient is superior to the Mander’s overlap coefficient. Cytometry A 77(8):733–742

Chapter 4 Monitoring Opioid Receptor Interaction in Living Cells by Bioluminescence Resonance Energy Transfer (BRET) Monica Baiula Abstract Bioluminescence resonance energy transfer (BRET) is a natural phenomenon that has been successfully applied for the study of protein–protein interactions, including opioid receptor oligomers. The discovery of opioid receptor homomers and heteromers has brought to the discovery of new functions and new way of signaling and trafficking; therefore, opioid receptor oligomers may be considered as novel drug targets. Fusing receptors of interest with Renilla luciferase and with a fluorescent protein (such as EYFP) it is possible to study opioid receptor dimerization using BRET. Key words BRET, Renilla luciferase, Enhanced yellow fluorescent protein, Receptor dimerization, Opioid receptor

1

Introduction Biological processes proceed through a sequence of specific protein–protein interactions along intracellular signaling cascades. Characterization of these interactions is essential to the understanding of cellular mechanisms. Bioluminescence resonance energy transfer (BRET) is a natural phenomenon that has been successfully applied to the identification and characterization of protein–protein interactions in living cells and displays an important role in the discovery of novel drugs [1– 4]. Further development of BRET application has greatly improved knowledge on G protein-coupled receptors (GPCRs) and especially on opioid receptor dimerization [5]. BRET was first described in marine organisms such as Renilla reniformis and Aequorea victoria, in which an enzyme (Renilla luciferase and aequorin, respectively) catalyzes the oxidation of the endogenous substrate coelenterazine to coelenteramide resulting in bioluminescence [6, 7]; if endogenous green fluorescent protein (GFP) is in close proximity then part of energy deriving

Santi M. Spampinato (ed.), Opioid Receptors: Methods and Protocols, Methods in Molecular Biology, vol. 2201, https://doi.org/10.1007/978-1-0716-0884-5_4, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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from bioluminescent reaction is transferred to GFP which emits light at a characteristic wavelength. BRET is a non-radiative dipole-dipole energy transfer that occurs between a luminescent donor enzyme and an acceptor fluorescent protein when they are in close proximity, within 100 A˚ (Fig. 1). The efficiency of energy transfer depends on several factors such as the distance between donor and acceptor molecule, relative dipole orientation, and need of overlap between emission spectrum of the donor and absorption spectrum of the acceptor. To study receptor interactions using BRET, the proteins of interest are genetically fused either to the donor Rluc or to an acceptor fluorescent protein, usually a variant of GFP. Depending on the Rluc variant, substrate, and acceptor fluorescent protein, several types of BRET have been developed: the most common techniques are BRET1 and BRET2 [4, 8]. BRET1 uses Rluc as donor and GFP or enhanced yellow fluorescent protein (EYFP) as acceptor, while in BRET2 the acceptor is GFP2 and the substrate is DeepBlueC (coelenterazine 400a), resulting in a better separation of donor and acceptor emission spectra, although BRET2 signal is weaker. As coelenterazine is extremely instable in aqueous environment, the use of a protected form of coelenterazine h, named EnduRen, provides stability and ensures real-time monitoring of BRET signal for several hours: “extended BRET” (eBRET) uses EnduRen substrate that penetrates and is cleaved to coelenterazine h by esterases only in living cells [9, 10]. BRET has been extensively used to demonstrate homo- and heterodimerization of GPCR [4, 11] and in particular of opioid receptors [11–13]. Over the last two decades it has become clear that GPCRs do not act solely as monomer but can interact with themselves or with other receptor types to form homomers and heteromers. Therefore, it is possible that in a context-dependent way different effects mediated by a receptor originate from homomer/heteromer-specific signaling cascade, as they display different signaling and novel pharmacological properties. Opioid homomers and heteromers have been among the first studied [14, 15]. All three opioid receptors can form homomers while heteromers have been observed between δ opioid receptor (DOR) and κ opioid receptor (KOR) or μ opioid receptor (MOR) [16]. Moreover, opioid receptor can form heteromers with other types of receptor: DOR can heterodimerize with nociceptin receptor [17] and can form oligomers with β2-adrenergic receptors [18] and chemokine receptors [19]; in addition, MOR, DOR, and KOR oligomerize with cannabinoid receptor CB1 [20]. Opioid receptor oligomers can be considered as novel drug targets: in fact, ligands targeting selectively oligomers could be

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Fig. 1 BRET assay to monitor opioid receptor homo/heterodimerization. To study any possible interaction the first receptor is fused to Rluc, as energy donor, and the second to EYFP, as energy acceptor. (a) If the receptors do not interact (distance >100 A˚) there is no energy transfer from donor to acceptor and the only signal detectable is from coelenterazine h oxidation. (b) After adding luciferase substrate, coelenterazine h, if the receptors are in close proximity (0.9). 6. Subtract the mean BRET ratio value of vehicle-treated samples to their corresponding ligand-treated mean BRET ratio value and propagate the error accordingly (see Note 15): these values will provide net BRET values, representing the net effect of the ligand on the interaction between KOR and arrestin. 7. Plot the net BRET values obtained as in step 6 of Subheading 3.4 in an XY graph having on the X-axis (this time use a linear scale) the F/L values (as calculated in step 2 of this section), and on the Y-axis the net BRET values determined in step 6 of this section (Fig. 3b). This will provide a net BRET curve. This curve will allow for the quantification of the effect of the ligand of interest on the opioid receptor/arrestin interaction (see Note 16). 8. Perform the statistical analysis of the obtained net BRET curve by interpolating it with a one-site binding (hyperbola) curve model; the R2 value reports the goodness of this interpolation (>0.9). 9. Determine the net BRET max value from the curve obtained as indicated in step 7 of this section (this value corresponds to the BMax in the one-site binding curve model); the net BRET max value is a quantitative evaluation of the ligand of interest’s ability to influence the interaction between KOR and arrestin, allowing comparison between different experimental replicates of the same treatment or between different treatments.

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Notes 1. A relevant issue in generating chimeric constructs for BRET is whether to fuse the donor/acceptor with the N-terminus or C-terminus of the protein of interest: one of the preliminary procedures in setting up a BRET assay, in fact, is to find out the best configuration for the chimeric protein to be employed. GPCRs are usually fused to RLuc at their C-terminus, whereas arrestin-2 and arrestin-3 are fused to Venus at their N-terminus. This tagging configuration has proved successful [5, 6]. This configuration for KOR/RLuc and Venus/arrestin chimeras should be effective in most of BRET assays. 2. HEK-293 cells have been selected for the BRET assay presented in this chapter as they are a model of human cells that can be easily cultured and transfected with the various plasmids required for the described technique. Furthermore, they do not express endogenous opioid receptors or other related GPCRs that could interfere with the BRET assay. Other cell models can be used, e.g., COS-7; however, it is important that alternative cell models are easily transfected and are similar to HEK-293 cells in terms of GPCR expression. It could be necessary to tailor both plasmid amounts and transfection conditions in alternate cell lines. 3. The transfection step is carried out using Lipofectamine® 2000. This reagent is guaranteed by the manufacturer to yield a high transfection efficiency and that is a prerequisite for the BRET assay described in this chapter. Other reagents yielding high transfection efficiency could be used according to the manufacturers’ recommendations. 4. Calcium and magnesium divalent cations are crucial for cell adhesion; therefore it is important that the DPBS solution employed in this BRET assay contains the correct amount of both. Different DPBS formulations are available, both with and without magnesium chloride and calcium chloride. Check the formulation of the selected DPBS and adjust for calcium chloride and magnesium chloride concentration if necessary. 5. The BRET protocol described in this chapter has been set up using the coelenterazine h substrate provided by DiscoverX; other providers or types of substrate suitable for RLuc could be used according to their manufacturers’ recommendations. 6. Transfecting 200 ng/well of KOR/RLuc (donor) plasmid should yield expression levels of the corresponding protein sufficient to successfully perform the BRET assay described in this chapter (the optimal amount of donor plasmid in the proposed BRET format should range from 50 to 250 ng). In

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case of weak luminescence signal, it could be useful to adjust the amount of donor plasmid transfected. If this is the case, prepare a 6-well plate of HEK-293 cells and transfect each well with various amounts of donor plasmid (include an untransfected well). Twenty-four hours after transfection plate the cells into a 96-well plate with white walls (as indicated in day 2) and perform detection of basal luminescence 48 h after transfection (as indicated in day 3). This will allow the experimenter to determine the optimal concentration of donor plasmid to be transfected to obtain KOR/RLuc expression levels that are significantly higher than background. 7. The transfection of 24 μg of Venus/arrestin-3-encoding plasmid may sometimes yield expression levels of the corresponding chimeric protein lower than those obtained by transfecting the same amount of Venus/arrestin-2-encoding plasmid. To overcome this issue it could be useful to increase the amount of Venus/arrestin-3-encoding plasmid to be transfected (e.g.: use 48 μg instead of 24 μg). 8. If transfecting increased amounts of Venus/arrestin-3, adjust the quantities of “junk” DNA accordingly. 9. If transfecting increased amounts of Venus/arrestin-3, adjust the quantity of Lipofectamine® 2000 accordingly. In case of cell toxicity due to the increased amount of the transfection reagent employed, reduce the amount of Lipofectamine® 2000 reagent to 35–40 μL. 10. HEK-293 cells are weakly adherent to the bottom of tissue culture plates; therefore they can be easily detached by pipetting the media in the plate up and down; alternatively, a cell scraper can be used to gently detach the cells. If other cell types are used in the BRET assay presented in this chapter, they must be detached according to their standard culture procedures. 11. To minimize well-to-well variability and as pipetting errors, use of a multichannel pipette is recommended. Add the solutions carefully by pipetting them on the walls of the wells in order to prevent detaching the transfected cells. 12. In the BRET format described in this chapter the timing is crucial to precisely evaluate any effect elicited by the KOR ligand of interest on KOR/arrestin interactions; therefore it is important to estimate in advance the amount of time required for substrate dilution and administration so the plate readings occur at the desired time points after ligand administration. 13. Coelenterazine h is light sensitive: dilute the stock solution immediately before using it and keep it protected from directlight sources. Diluted coelenterazine h solution may be added

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to the wells using a multichannel pipette if direct illumination of the remaining stock is prevented. 14. If there is an interaction between KOR and arrestin, the data will result in sigmoidal curves on the BRET ratio graph built as indicated in Subheading 3.4, step 4 (Fig. 3a); if there is no interaction between KOR and arrestin, the data will result in a flat line parallel to the X-axis. If the KOR ligand of interest promoted a further increase in the interaction between KOR and arrestin over basal, the resulting sigmoidal curve will be shifted to the left (Fig. 3a). 15. Alternatively to the indications reported in Subheading 3.4, step 6, it is possible to calculate the net BRET value for each of the wells read as indicated in Subheading 3.3, step 9, as follows: calculate the ratio between the higher wavelength signal (542 nm) and the lower one (460 nm) so BRET ratio values will be calculated for each well. Then subtract the BRET ratio values of vehicle-treated wells from those of the ligand-treated wells so six net BRET values will be obtained per each of the transfection groups prepared on day 1. Then, calculate the net BRET mean values for every transfection group and proceed with Subheading 3.4, step 7. 16. If the KOR ligand of interest promoted the interaction between KOR and arrestin the data will result in a hyperbolic saturation curve for the net BRET graph built as indicated in Subheading 3.4, step 7 (Fig. 3b); otherwise either no curve or a flat line parallel to the X-axis will be obtained.

Acknowledgments The author acknowledges Prof. V. Gurevich for providing the plasmid backbones and Prof. C. Chavkin, Dr. Selena S. Shattauer, and Mrs. Jamie R. Kuhar for their practical support with KOR subcloning into the donor plasmid and for their critical review of the experimental procedures presented in this chapter. References 1. Jockers R (2014) Comment on “The use of BRET to study receptor-protein interactions”. Front Endocrinol (Lausanne) 5:3. https://doi. org/10.3389/fendo.2014.00003 2. Xu Y, Piston DW, Johnson CH (1999) A bioluminescence resonance energy transfer (BRET) system: application to interacting circadian clock proteins. Proc Natl Acad Sci U S A 96(1):151–156 3. De A, Jasani A, Arora R et al (2013) Evolution of BRET biosensors from live cell to tissue-

scale in vivo imaging. Front Endocrinol (Lausanne) 4:131. eCollection 2013. Review 4. Drinovec L, Kubale V, Nøhr Larsen J et al (2012) Mathematical models for quantitative assessment of bioluminescence resonance energy transfer: application to seven transmembrane receptors oligomerization. Front Endocrinol (Lausanne) 3:104. https://doi.org/10. 3389/fendo.2012.00104. eCollection 2012 5. Gimenez LE, Kook S, Vishnivetskiy SA et al (2012) Role of receptor-attached phosphates

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in binding of visual and non-visual arrestins to G protein-coupled receptors. J Biol Chem 287 (12):9028–9040. https://doi.org/10.1074/ jbc.M111.311803. Epub 2012 Jan 24 6. Gurevich VV, Gurevich EV (2019) Plethora of functions packed into 45 kDa arrestins: biological implications and possible therapeutic strategies. Cell Mol Life Sci 76 (22):4413–4421 7. Pradhan AA, Smith ML, Kieffer BL (2012) Ligand-directed signaling within the opioid receptor family. Br J Pharmacol 167 (5):960–969. https://doi.org/10.1111/j. 1476-5381.2012.02075.x. Review

8. Kenakin T, Christopoulos A (2013) Signalling bias in new drug discovery: detection, quantification and therapeutic impact. Nat Rev Drug Discov 12(3):205–216. https://doi.org/10. 1038/nrd3954. Epub 2012 Feb 15. Review 9. Bruchas MR, Chavkin C (2010) Kinase cascades and ligand-directed signaling at the kappa opioid receptor. Psychopharmacology 210(2):137–147. https://doi.org/10.1007/ s00213-010-1806-y 10. Bruchas MR, Roth BL (2016) New technologies for elucidating opioid receptor function. Trends Pharmacol Sci 37(4):279–289

Chapter 6 Functionalization and Bioconjugation of Nanoruby for Long-Term, Ultrasensitive Imaging of Mu-Opioid Receptors Rashmi Pillai, Mark Connor, and Varun K. A. Sreenivasan Abstract Sensitive and long-term fluorescence imaging of G-protein-coupled receptors enables exploration of molecular level details of these therapeutically relevant proteins, including their expression, localization, signaling, and intracellular trafficking. In this context, labeling these receptors with bright and photostable fluorescent probes is necessary to overcome current imaging problems such as optical background and photobleaching. Here, we describe the procedures to functionalize nanoruby (and other similar nanoparticles) with NeutrAvidin (a streptavidin analog) and to apply this bioconjugate for ultrasensitive, long-term imaging of μ-opioid receptors heterologously expressed in AtT-20 cells. The receptor targeting is mediated via a biotinylated primary antibody, rendering this methodology extendable to other G-protein-coupled or, more generally, cell-surface receptors. Nanoruby-based time-gated imaging enables indefinitely long visualization of single particles even in high-autofluorescence media, such as serum, by completely suppressing autofluorescence and any laser backscatter. Key words Click chemistry, Fluorescence, G-protein-coupled receptor, Lifetime, Nanoparticle, Opioid, Photoluminescence, Nanoruby, Single-particle, Time-gated microscopy

1

Introduction G-protein-coupled receptors (GPCRs) are the largest family of transmembrane mammalian proteins with over 800 identified, unique receptors [1]. Upon activation, GPCRs undergo changes at the nano- and microscale, including the rearrangement of oligomeric receptor complexes, association with and dissociation from intracellular proteins, altered lateral diffusion along the plasma membrane, receptor clustering, internalization, and subsequent trafficking via intracellular organelles [2, 3]. Tools and techniques that enable continuous and long-term, sensitive and specific, singlemolecule-level imaging of GPCRs are necessary to elucidate these mechanisms with fine spatiotemporal detail.

Santi M. Spampinato (ed.), Opioid Receptors: Methods and Protocols, Methods in Molecular Biology, vol. 2201, https://doi.org/10.1007/978-1-0716-0884-5_6, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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Advances in nanotechnology over the last two decades have resulted in an arsenal of nanoparticle probes that overcome many limitations of organic fluorophores used for fluorescence imaging. Limited sensitivity due to optical background and photobleaching are the two main challenges faced during single-molecule-level imaging, especially in samples containing biological fluids and during deep-tissue imaging. Quantum dots [4], nanodiamonds [5], up-conversion nanoparticles [6], and nanorubies [7] are examples of nanoparticles that each features a subset of advantageous properties such as photostability, long photoluminescence lifetimes (see Note 1), anti-Stokes fluorescence emission, biochemical and biophysical inertness, colloidal stability in physiological media, biocompatibility, and ease of functionalization and bioconjugation [8, 9]. In this chapter, we describe detailed methodologies for functionalization and bioconjugation of silica-coated nanoruby (SiNR) followed by steps to label μ-opioid receptor (μOR) in live cells. Functionalization introduces reactive, organic chemical groups on the surface of otherwise inert and inorganic nanomaterials. The reactive functional groups in turn serve as anchor points to bioconjugate ligands, antibodies, or in this case NeutrAvidin (NA), a streptavidin analog. μOR is an exemplary GPCR and is the primary target of analgesic drugs, such as morphine. In the methodology described below, functionalization of SiNR with azide group is achieved using a heterobifunctional linker (silane-PEG-azide) via a facile procedure called silanization. The polyethylene glycol (PEG) serves as a spacer between the silane group that reacts to the surface of SiNR and the reactive azide functional group, and enhances the colloidal stability of the functionalized SiNR by introducing steric stability [10]. Since steric stability is less affected by high ionic concentration, the azidefunctionalized SiNR (SiNR-PEG-azide) is colloidally stable in physiological solutions such as saline buffers and cell culture media [11]. Moreover, the procedure can also be modified to vary the average number of reactive azide groups per nanoparticle by varying the ratio between (monofunctional) silane-PEG-methoxy and silane-PEG-azide reagents. As the next step, the reactive azide group on the functionalized SiNR is conjugated to alkynated NA via click chemistry [12]. Procedures for alkynation of NA and then the conjugation of alkynated NA to the SiNR-PEG-azide to form SiNR-NA are described. The use of a copper-free variant of click chemistry ensures that all reagents used during bioconjugation are biocompatible and nontoxic, and also simplifies the reaction [13, 14]. In the end, procedures for labeling of μOR in live cells using the SiNR-NA for ultrasensitive photoluminescence imaging are described.

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It is noteworthy that NA can be replaced with any protein that has reactive amine groups for alkynation, such as IgG antibodies. Moreover, the facile nature of the functionalization, conjugation, and receptor labeling procedures allows the methodology to be modified and extended to other silica-coated or silica-based nanomaterials (e.g., silica-coated up-conversion nanoparticle and fluorescent silica nanoparticle) as well as to other G-protein-coupled receptors with suitable antibodies. The final labeling procedure can also be altered to target μOR in paraformaldehyde-fixed cells.

2 2.1

Materials Equipment

1. Benchtop centrifuge, with a maximum rotational centrifugal force of 16,000  g. 2. Dynamic light scattering for hydrodynamic size and zeta potential measurements (Zetasizer Nano-ZS, Malvern, USA). 3. Sonicator, water bath type. 4. Benchtop vortex mixer. 5. Infrared spectrometer Fisher, USA).

(Nicolet

iS5

FTIR,

Thermo

6. Fluorimeter (optional). 7. Wide-field, epi-illumination, time-gated, photoluminescence, microscope with optics appropriate for nanoruby detection [15] (see Notes 2–4). 8. Rotary mixer. 9. Heating block. 2.2 Reagents, Samples, and Consumables

1. 60 nm Processed and cleaned nanoruby (Catalog Nos. NR2-AAA, NR5-AAA, or NR8-AAA; Lucigem, Australia; lucigem.com.au) (see Notes 5–7). 2. Purified water, resistivity 18 MΩ cm (water). 3. Monofunctional, silane-functionalized polyethylene glycol, MW 2000 (silane-PEG-methoxy) (Catalog No. M-SIL-2K; Laysan Bio, USA). 4. Heterobifunctional, silane- and azide-functionalized polyethylene glycol, MW 3400 (silane-PEG-azide; Catalog No. PG2-DBSL-3k-2; Nanocs, USA) (see Note 8). 5. NHS-ester-functionalized dibenzocyclooctyne (DBCO-NHS; Catalog No. DB-NS-02; Nanocs, USA). 6. Dimethyl sulfoxide (DMSO). 7. NeutrAvidin (NA; Catalog No. 31000; Thermo Fisher Scientific, USA) (see Note 9).

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8. Phosphate-buffered saline (PBS; pH 7.2). 9. Desalting column with a molecular weight cutoff of 7 kDa. 10. Ethanolamine (optional negative control). 11. Fluorescently labeled biotin (see Note 10). 12. AtT-20 cells, heterologously expressing μOR with N-terminal hemagglutinin tag (HA-μOR; available upon request from authors) at 70–80% confluency in a 75 cm2 tissue culture flask (see Note 11). 13. Cell culture media: DMEM supplemented with 10% (v/v) FBS, 1% (v/v) penicillin/streptomycin, and 100 μg mL 1 hygromycin (see Note 12). 14. Biotinylated, anti-HA antibody (Catalog No. BIOT-101L, BioLegend, USA). 15. Eight-chambered coverslip-bottom slides (see Note 13). 16. 3.7% (w/v) Paraformaldehyde in PBS (optional, if labeling/ imaging fixed cells). 17. Low-serum media: Phenol-red free Leibovitz’s L-15 media (for prolonged support of cells in room air) supplemented with 1% (w/v) bovine serum albumin.

3

Methods

3.1 Functionalization of Silica-Coated Nanoruby with Azide Groups, by Silanization

The following steps to functionalize SiNR with azide groups can be scaled without altering concentrations (see Notes 6 and 14). 1. Rinse 0.16 mg of SiNR by centrifuging the colloid at 13,500  g, and discard the supernatant using a pipette and resuspending the pellet in 100 μL water (see Notes 15––17). 2. Prepare 100 μL aqueous silane-PEG solution containing silane-PEG-azide and silane-PEG-methoxy at a concentration of 120 mM (see Notes 18–20). 3. Add 100 μL of the silane-PEG solution prepared in step 2 into colloidal SiNR prepared in step 1, such that the final silanePEG concentration is 60 mM (see Note 21). 

4. Incubate the mixture overnight at 40 C, to allow silane groups to react with the hydroxyl groups on the silica surface, leading to the formation of covalent Si–O–Si bonds. 5. Remove excess, unreacted silane-PEG from the functionalized SiNR (SiNR-PEG-azide): centrifuge the colloid at 13,500  g, discard the supernatant using a pipette, and resuspend the pellet in 500 μL water.

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6. Repeat step 5 for a total of five times to ensure complete removal of unbound silane-PEG reagents, but in the final step  resuspend in 100 μL water. Store at 4 C for bioconjugation with NA within 1 week. 7. Confirm functionalization of SiNR with silane-PEG reagents to form SiNR-PEG-azide, by means of infrared spectroscopy. Verify the presence of peaks at 2850–3000 cm 1 corresponding to C–H groups [16]. 3.2 Alkynation of NeutrAvidin with DBCO-NHS

Below are the steps required for alkynation of NA, with DBCO group. The reactive NHS group of DBCO-NHS reacts to primary amines present in NA. Carry out these steps using a sterile workflow to avoid potential microbial contamination and degradation of NA. 1. Freshly prepare a 1 mL of 10 mM DBCO-NHS solution in DMSO (see Note 22). 2. Prepare 100 μL of 0.4 mM NA solution in PBS. 3. To the NA solution add 16 μL of the 10 mM DBCO-NHS solution such that DBCO-NHS is in fourfold molar excess of NA. Adjust the reaction volume to 200 μL by adding 84 μL of PBS and mix thoroughly (see Note 23). 4. Allow the reaction to continue for 1 h under stirring at room temperature using a rotary mixer. 5. Remove the excess, unreacted DBCO-NHS from the DBCOfunctionalized NA by eluting the reaction product through a 7 kDa MWCO desalting column with PBS as the eluent (see Note 24). 6. Store the eluate containing DBCO-conjugated NA  (NA-DBCO) in sterile vial and store at 4 C, for use within a week.

3.3 Bioconjugation of AzideFunctionalized Nanoruby to Alkynated NeutrAvidin by Click Chemistry

This procedure is the final step of the conjugation reaction to form SiNR-NA. The azide group on SiNR-PEG-azide (Subheading 3.1) undergoes copper-free click reaction with DBCO group on NA-DBCO (Subheading 3.2) to form the SiNR-NA conjugate. 1. Rinse 0.16 mg of SiNR-PEG-azide: centrifuge the colloid at 13,500  g, discard the supernatant using a pipette, and resuspend the pellet in 84 μL PBS such that the final volume after the following step is 100 μL (see Notes 15 and 25). 2. Add 16 μL of 0.2 mM NA-DBCO to the SiNR-PEG-azide colloid and mix gently and thoroughly (see Note 26). 3. Allow the click reaction to occur over 3 h at room temperature under gentle stirring.

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4. Remove unreacted NA-DBCO from the NA-conjugated SiNR (SiNR-NA): Centrifuge the colloid at 13,500  g, discard the supernatant using a pipette, and resuspend the pellet in 200 μL PBS. 5. Repeat the above step for a total of five times to ensure complete removal of unreacted and loosely bound NA-DBCO.  Store the SiNR-NA conjugate at 4 C for use within 1 week (see Note 27). 6. Confirm and assay the biotin-binding capacity of SiNR-NA using fluorescently labeled biotin: Incubate 0.08 mg SiNRNA suspended in 100 μL PBS with 1 μM (final concentration) of fluorescently labeled biotin for 5 min, rinse five times by centrifugation with PBS, and measure the ratio of photoluminescence emission between nanoruby and fluorescently labeled biotin (see Note 10). 3.4 Labeling μOpioid Receptor in Live Cells with NeutrAvidinConjugated Nanoruby

The steps below detail the procedures to immunologically label HA-μOR expressed on the plasma membrane of AtT-20 cells using a biotinylated antibody, which is subsequently targeted with SiNR-NA. The suggested volumes of reagents should be scaled appropriately depending on the size of the chamber/dish used while maintaining the concentrations. 1. Plate cells suspended in cell culture media into an eightchambered coverslip-bottom slides and incubate overnight in  a humidified incubator set at 37 C with 5% CO2. 2. Bring cells to room temperature and replace the cell culture media with low-serum media after 15 min. 3. Incubate for a further 20 min at room temperature. 4. Prepare an immunolabeling solution by diluting biotinylated anti-HA antibody in low-serum media at a dilution factor recommended by the manufacturer (see Note 28). 5. Replace the low-serum media with the immunolabeling solution and incubate for 1 h at room temperature. 6. Rinse the cells thrice with low-serum media. 7. Remove low-serum media, add 30–150 μg/mL SiNR-NA colloid prepared in low-serum media to cells, and incubate for 10 min at room temperature with gentle rocking. 8. Rinse the cells three times with low-serum media. 9. If performing live-cell imaging, skip to step 12. 10. Rinse cells twice with PBS. 11. Fix the cells by incubating the cells with 3.7% paraformaldehyde solution prepared in PBS for 20 min. Rinse twice with PBS.

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Fig. 1 (a) Schematic of labeling HA-μOR expressed on the plasma membrane of a cell using SiNR-NA, via a biotinylated antibody against HA-epitope. (b–i) Bright-field (top) and time-gated wide-field photoluminescence (bottom) images of nanoruby-labeled HA-μOR expressed in AtT-20 cells. FLAG-tagged μOR expressed in control cells is not targeted by the anti-HA antibody. Scale bar 20 μm applies to all images. Reprinted with permission from [17]. Copyright 2017 American Chemical Society

12. Acquire images using a (time-gated) wide-field photoluminescence microscope (see Notes 3 and 4) (Fig. 1).

4

Notes 1. Photoluminescence is a generic term including phosphorescence and fluorescence, which are specific terms for emission characterized with long and short lifetimes. 2. Nanoruby’s sharp photoluminescence emission at 692.9 and 694.3 nm is optimally excited at 405 or 550 nm (Fig. 2a). Thus, the recommended optical elements include 1 W 532 nm excitation laser, 650 nm long-pass dichroic beam splitter, a band-pass filter to selectively transmit nanoruby photoluminescence emission, and a sensitive camera (e.g., EMCCD). 3. The photoluminescence lifetime of nanoruby is in the order of milliseconds (Fig. 2b) [17]. Thus, nanoruby is best imaged with wide-field photoluminescence microscopy methods as opposed to scanning-based microscopy (e.g., confocal microscopy). This is because increasing the pixel-dwell time in a confocal microscope to match the nanoruby photoluminescence lifetime can result in very slow image acquisition times, for example 3  10 3s  512 px  512 px  13 min for acquiring one image. 4. Time-gated microscopy exploits the difference between the photoluminescence lifetimes of nanoruby (millisecond) and other fluorophores (including tissue autofluorescence; nanosecond) to enhance the contrast of nanoruby detection

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Fig. 2 (a) Photoluminescence excitation-emission matrix of ruby, including cross-sectional emission spectra (above) at 532 nm excitation (green arrow) and cross-sectional excitation spectra (right) with emission detection at 692 nm (red arrow). (b) Decay of photoluminescence emission from ruby, following termination of 532 nm excitation, is described by a single exponential model with a lifetime, τ, of 3.7 ms. (c) Photostability of nanoruby compared with enhanced green fluorescent protein (EGFP) [22]

[15]. Time-gated imaging requires the laser and camera to be electronically triggerable with sub-millisecond response times. The photostable emission (Fig. 2c) also enables long-term, uninterrupted imaging and tracking of nanoruby particles. 5. Nanoruby AAA is purified nanoruby that is colloidally stable in water [18]. NR2 AAA, NR5 AAA, and NR8 AAA have increasing chromium doping, and thus increasing photoluminescence brightness. Nanoruby can also be obtained by request from the authors. 6. Standard procedures used for silica coating of nanoparticles can be followed to prepare SiNR (Fig. 3) [18, 19]. 7. The procedures described here are applicable to SiNR or other nanoparticles featuring silica surface (e.g., fluorescent silica nanoparticles (sicastar®-greenF; Micromod, Germany)). Note

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Fig. 3 (a) Schematic of silica coating, functionalization, and conjugation of NR. (b) Transmission electron micrograph of NR and SiNR. Scale bar 100 nm. (c) Hydrodynamic diameter (top) and zeta potential (bottom) of SiNR, after its functionalization, and bioconjugation [16]. The percentages of silane-PEG-azide in the total silane-PEG reagent used during functionalization step are shown in brackets. Part (b) reprinted (adapted) with permission from [18]. Copyright 2017 American Chemical Society

that functionalization of sicastar®-greenF nanoparticles smaller than 40 nm with PEG reagents resulted in colloidally unstable products. 8. Use of longer PEG linker for sil-PEG-azide than sil-PEGmethoxy ensures that the azide group is exposed to the solvent. 9. NA is a cost-effective analog of avidin or streptavidin and is devoid of glycosylation or RYD sequence [20]. The latter two properties result in reduced off-target binding [21].

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10. The fluorescent label on biotin should be chosen carefully, depending on the nanoparticle being used. PromoFluor555P, Biotin (PromoKine, Germany) is spectrally compatible with both SiNR and sicastar®-greenF. 11. Suggested negative control: AtT-20 cells, heterologously expressing μOR without hemagglutinin tag at 70–80% confluency in a 75 cm2 tissue culture flask. Available upon request from authors. 12. Use appropriate selection antibiotic for negative-control AtT-20 cells. 13. Removable 8-well chamber (Catalog No. 80841, DKSH) allows removal of the polymer chamber wall from the supplied glass slide and readhesion onto a coverslip. 14. It is recommended that dynamic light scattering-based measurement of hydrodynamic diameter and zeta potential of the colloid is carried out at every step of functionalization and bioconjugation to ensure colloidal stability (Fig. 3). Follow instructions provided in the instrument manual for sample preparation, data acquisition, and analysis/interpretation. 15. Care is to be taken while pipetting the supernatant to minimize loss of SiNR. In general, resuspension can be expedited by alternating sonication and vortex-assisted mixing. If complete resuspension is impossible, it might be prudent to remove the aggregates by centrifugation for 2–5 min at ~200  g. 16. SiNR, once dried, cannot be satisfactorily resuspended into a colloid. Therefore, it is advisable to measure the mass of SiNR by means of photoluminescence intensity measurements. Firstly, establish an intensity calibration curve using a series of reference samples with increasing dilution of SiNR. Dry these reference samples, measure the mass, and plot an intensity versus mass calibration curve. This curve can be used to measure SiNR concentration in future samples. It is crucial that the parameters of the spectrometer remain constant and that the nanoruby colloid is stable with no sedimentation. 17. The quoted mass of SiNR is the mass of the nanoruby, excluding the mass of the silica coating. However, the mass of the nanoparticles stated here is not stringent since the concentrations of silane-PEG-methoxy and silane-PEG-azide used are in excess, as confirmed separately by infrared spectroscopy in our preliminary experiments [16]. 18. Dissolution of silane-PEG-methoxy and silane-PEG-azide in  water can be expedited by warming up to 40 C. Prepare this solution fresh every time, because the silane functional group is unstable in moisture.

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19. The fraction of silane-PEG-azide in the silane-PEG mixture can be varied between 0.1% and 20%. Higher fraction of silanePEG-azide, however, increases the susceptibility to aggregate during functionalization [16]. Our preliminary data confirms that 0.1% and 1% silane-PEG-azide does not cause aggregation (Fig. 3). 20. It is advisable to prepare a negative control sample where silane-PEG-methoxy is the only silane-PEG reagent. 21. It may be difficult or impossible to fully resuspend the SiNR pellet after centrifugation in a PEG-containing solution. Therefore, it is advisable to fully resuspend SiNR to form a stable colloid in water in step 1 (Subheading 3.1), prior to the addition of PEG-containing solution. 22. Guidelines provided by the manufacturer are to be strictly followed, due to the unstable nature of DBCO-NHS. 23. It is recommended that a negative control of this functionalization reaction is carried out in parallel. We suggest inactivating the NHS group of the DBCO-NHS by overnight preincubation with a fivefold molar excess of ethanolamine in room temperature. Use the inactivated DBCO-NHS as a negative control when alkynating NA, while maintaining other reaction conditions unchanged. 24. The desalting column appropriate for the volume of the solution must be chosen and can be either centrifugation based or gravity based. Follow the user manual for equilibration and elution parameters, including the force of centrifugation and the elution volumes. 25. Suggested negative control: use SiNR functionalized only to silane-PEG-methoxy, i.e., without silane-PEG-azide as specified in Note 20. 26. Two suggested negative controls: (a) Use NA functionalized to ethanolamine-inactivated DBCO-NHS as specified in Note 23. (b) Use NA without any functionalization. 27. Storage of the SiNR-NA conjugate longer than 1 week resulted in aggregates. 28. For BIOT-101L (BioLegend, USA), 500-fold dilution is appropriate. References 1. Hauser AS, Attwood MM, Rask-Andersen M et al (2017) Trends in GPCR drug discovery: new agents, targets and indications. Nat Rev Drug Discov 16:829–842 2. Grushevskyi EO, Kukaj T, Schmauder R et al (2019) Stepwise activation of a class C GPCR

begins with millisecond dimer rearrangement. Proc Natl Acad Sci U S A 116:10,150–10,155 3. Vukojevic V, Ming Y, D’Addario C et al (2008) Mu-opioid receptor activation in live cells. FASEB J 22:3537–3548

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4. Chan WCW, Nie SM (1998) Quantum dot bioconjugates for ultrasensitive nonisotopic detection. Science 281(5385):2016–2018 5. Chao JI, Perevedentseva E, Chung PH et al (2007) Nanometer-sized diamond particle as a probe for biolabeling. Biophys J 93:2199–2208 6. Nadort A, Sreenivasan VKA, Song Z et al (2013) Quantitative imaging of single upconversion nanoparticles in biological tissue. PLoS One 8(5):e63292. https://doi.org/10.1371/ journal.pone.0063292 7. Edmonds AM, Sobhan MA, Sreenivasan VKA et al (2013) Nano-ruby: a promising fluorescent probe for background-free cellular imaging. Part Part Syst Charact 30:506–513. https://doi.org/10.1002/ppsc.201200112 8. Sreenivasan VKA, Zvyagin AV, Goldys EM (2013) Luminescent nanoparticles and their applications in the life sciences. J Phys Condens Matter 25(19):194101. https://doi.org/10. 1088/0953-8984/25/19/194101 9. Reineck P, Francis A, Orth A et al (2016) Brightness and photostability of emerging red and near-IR fluorescent nanomaterials for bioimaging. Adv Opt Mater 4:1549–1557 10. Ottewill RH, Satgurunathan R (1987) Nonionic latices in aqueous media part 1. Preparation and characterization of polystyrene latices. Colloid Polym Sci 265:845–853. https://doi. org/10.1007/bf01418462 11. Laurent S, Forge D, Port M et al (2008) Magnetic iron oxide nanoparticles: synthesis, stabilization, vectorization, physicochemical characterizations, and biological applications. Chem Rev 108:2064–2110. https://doi.org/ 10.1021/cr068445e 12. Li N, Binder WH (2011) Click-chemistry for nanoparticle-modification. J Mater Chem 21:16,717–16,734. https://doi.org/10. 1039/C1JM11558H 13. Ning X, Guo J, Wolfert MA et al (2008) Visualizing metabolically labeled glycoconjugates of living cells by copper-free and fast huisgen cycloadditions. Angew Chem Int Ed Engl 47:2253–2255. https://doi.org/10.1002/ anie.200705456

14. Koo H, Lee S, Na JH et al (2012) Bioorthogonal copper-free click chemistry in vivo for tumor-targeted delivery of nanoparticles. Angew Chem Int Ed Engl 51 (47):11,836–11,840. https://doi.org/10. 1002/anie.201206703 15. Razali WAW, Sreenivasan VKA et al (2016) Wide-field time-gated photoluminescence microscopy for fast ultrahigh-sensitivity imaging of photoluminescent probes. J Biophotonics 9(8):848–858. https://doi.org/10. 1002/jbio.201600050 16. Pillai RR (2017) Development of biofunctional ruby nanoparticles for optical imaging of opioid receptors. Masters by Research, Macquarie University 17. Pflitsch C, Siddiqui RA, Atakan B (2008) Phosphorescence properties of sol–gel derived ruby measured as functions of temperature and Cr3 + content. Appl Phys A 90(3):527–532. https://doi.org/10.1007/s00339-007-4315z 18. Sreenivasan VKA, Wan Razali WA et al (2017) Development of bright and biocompatible nanoruby and its application to backgroundfree time-gated imaging of G-protein-coupled receptors. ACS Appl Mater Interfaces 9:39,197–39,208. https://doi.org/10.1021/ acsami.7b12665 19. Graf C, Vossen DLJ, Imhof A et al (2003) A general method to coat colloidal particles with silica. Langmuir 19:6693–6700. https://doi. org/10.1021/la0347859 20. Scientific T (2019) NeutrAvidin protein. Thermofisher scientific. https://www.thermofisher. com/order/catalog/product/31000. Accessed 2 Dec 2019 21. Sreenivasan VKA, Kelf TA, Grebenik EA et al (2013) A modular design of low-background bioassays based on a high-affinity molecular pair barstar:barnase. Proteomics 13:1437–1443 22. Sreenivasan VKAC (2012) Fluorescent nanoparticles: a probe to study the molecular trafficking of somatostatin. Macquarie University, Sydney, Australia

Chapter 7 Immunohistochemical Analysis of Opioid Receptors in Peripheral Tissues Yvonne Schmidt and Halina Machelska Abstract Immunohistochemical staining is widely used to identify opioid receptors in specific cell types throughout the nervous system. Opioid receptors are not restricted to the central nervous system, but are also present in peripheral sensory neurons, where their activation exerts analgesic effects without inducing centrally mediated side effects. Here, we describe immunohistochemical analysis of μ-opioid receptors in the peripheral sensory neuron cell bodies, along the axons and their peripheral endings in the hind paw skin, as well as in the spinal cord, under naı¨ve and sciatic nerve damage conditions in mice. Importantly, we consider the ongoing debate on the specificity of antibodies. Key words Antibodies, Dorsal root ganglion, Immunohistochemistry, Immunofluorescence, Opioid receptors, Peripheral neurons, Specificity controls

1

Introduction Apart from the central nervous system (CNS), all three classical opioid receptors (μ, δ, κ) are also localized in peripheral sensory neurons and in immune cells [1, 2]. The advantage of targeting peripheral opioid receptors is efficient analgesia without CNS-mediated side effects such as respiratory depression, sedation, nausea, and addiction [3–6]. Peripheral opioid receptors are mainly synthetized in small- and medium-size dorsal root ganglion (DRG) neurons, which co-express prototypical sensory neuropeptides, such as substance P and calcitonin gene-related peptide (CGRP) [7–11]. Peripheral opioid receptors are transported from the DRG cell bodies to accumulate at the neuron peripheral terminals [9, 12–16]. Expression and function of these receptors are modulated by tissue damage. Following traumatic nerve injury such as chronic constriction injury (CCI) of the sciatic nerve, all three opioid receptors were detected in sensory fibers [17], and μ- and δ-receptors were upregulated [18–20] at the CCI site. Additionally, targeting and

Santi M. Spampinato (ed.), Opioid Receptors: Methods and Protocols, Methods in Molecular Biology, vol. 2201, https://doi.org/10.1007/978-1-0716-0884-5_7, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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G-protein coupling of μ-receptors in the axonal membranes were enhanced in CCI compared to intact nerves [21]. Consequently, activation of all three opioid receptors at the CCI site by exogenous [18, 21–25] and immune cell-derived opioids [17, 26–28] resulted in efficient attenuation of CCI-triggered mechanical or heat hypersensitivity. Immunohistochemistry has become ubiquitous in neuroscience and has been extensively used to detect opioid receptors. In contrast to, e.g., Western blot, immunohistochemistry offers the advantage of identifying the anatomical structure, cell type, and subcellular localization of a given protein. Although the principles of immunohistochemical reactions are relatively simple, many studies may have led to flawed conclusions, mostly because of often overlooked nonspecific staining by antibodies, including those to opioid receptors [20, 29–32]. Moreover, the staining specificity might be even tissue dependent [20, 33], suggesting the need for antibody specificity verification in each tissue of interest and method [20, 33, 34]. In this chapter, we describe immunohistochemical analysis of μ-opioid receptors along the peripheral neuronal pathways, the DRG, the nerve trunk and its endings in the hind paw skin, and in the spinal cord under naı¨ve and sciatic nerve damage conditions. We also put a strong emphasis on the antibodies’ specificity control experiments.

2

Materials

2.1 Buffers and Solutions

1. Wash buffer (1
phosphate-buffered saline [PBS]): For 1 L use 8 g of NaCl (final concentration 137 mM), 0.2 g of KCl (final concentration 2.7 mM), 1.44 g of Na2HPO4 (final concentration 10 mM), and 0.24 g of KH2PO4 (final concentration 2 mM), add up to a volume of approximately 800 mL with distilled water, adjust the pH to 7.4, and add the remaining distilled water to obtain a total volume of 1 L. 2. Dilution buffer (PBS+): To 1
PBS add 0.3% Triton X-100 and 1% bovine serum albumin (BSA); stir constantly until the solution is cleared. 3. Paraformaldehyde (PFA) fixative (4%): For 1 L of final solution, add 800 mL of 1
PBS to a glass beaker on a stir plate in a ventilated hood. Dissolve 40 g of PFA powder by heating the solution to approximately 60  C while constantly stirring. It may be necessary to add a few drops of 1 M NaOH to the solution to make it clear. Afterwards, cool it down to room temperature, filter through a standard filter paper, and adjust the pH to 7.4. 4. Zamboni’s fixative: Mix 75 mL of saturated aqueous picric acid and 75 mL of distilled water, and filter it. Add 18 g of PFA and

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heat the solution to 60  C while stirring constantly. Dropwise add 10–12 mL of 2.5% NaOH until the solution clears. Filter the solution again and cool it to room temperature. Fill up to 1 L with PO4 buffer (3 g of NaH2PO4 and 33.77 g of Na2HPO4 dissolved in 1 L of distilled water), and adjust the pH to 7.4 (see Note 1). 5. Sucrose solution: Dissolve 10–30% sucrose in 1
PBS, and adjust to pH 7.4. 2.2 Antibodies and Antigens

1. Primary antibodies to opioid receptors: In our experimental conditions, rabbit polyclonal anti-μ-receptor (Ab10275; Abcam) specifically stained μ-receptors in the spinal cord, sciatic nerve, and skin dermis, but not in the DRG, as judged by the use of tissue from mice lacking all three opioid receptors (triple μ-, δ-, and κ-receptor knockout mice) [20] (see Note 2). Other opioid receptor antibodies we used still await specificity validation in knockout mouse tissue. However, it is advisable to choose affinity-purified antibodies that were validated in the desired staining method by the company. 2. Antibodies to neuronal markers: For example, polyclonal guinea pig anti-α-CGRP (Bachem; see Note 3) to stain peptidergic sensory neurons, and chicken anti-neurofilament 200 (NF200; Millipore) to stain myelinated sensory neurons. 3. Immunizing peptides: Use specific immunizing opioid receptor peptides (ideally from the same company from which you acquired the antibodies) for a preabsorption control staining (see Subheading 3.6). 4. Fluorescent secondary antibodies: We used Texas Red alone or in combination with fluorescein isothiocyanate (FITC) or Alexa Flour dyes (e.g., Alexa 488, Alexa 568). The Alexa Flour dyes are recommended when greater photostability or higher fluorescence intensity is needed. Isolectin B4 (IB4) coupled to FITC (e.g., Sigma-Aldrich) can be used as a marker of nonpeptidergic sensory neurons. 5. Biotinylated secondary antibodies: We used a Vectastain Elite ABC kit (Vector Laboratories) for the respective species IgG, which contains a secondary antibody coupled to biotin and an avidin-peroxidase complex. 6. Peroxidase substrate: We used a 3,30 -diaminobenzidine (DAB) peroxidase substrate kit (Vector Laboratories), according to the manufacturer’s instructions.

2.3

Other Materials

1. Surgical dissection tools (e.g., Fine Science Tools): Surgical scissors and forceps (e.g., student standard pattern forceps, student surgical scissors, student Vannas spring scissors, fine

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Vannas spring scissors, Dumont #5 forceps, fine forceps with curved tips). 2. Dissection microscope. 3. Cryostat. 4. Polysine slides (e.g., Thermo Scientific, Menzel Gl€aser). 5. PAP pen: It can be used to create a water-repellent barrier that keeps reagents localized on tissue specimens (prevents wasting reagents by keeping liquid pooled in a small droplet). 6. Mounting medium for fluorescent staining: We used Mowiol, prepared according to the manufacturer’s instructions. 7. Mounting medium for DAB staining. 8. Fluorescence microscope.

3

Methods All procedures involving animals must be approved beforehand by the local ethics committee.

3.1

Surgeries

See also chapters by Celik et al. and Seitz et al. in this volume. 1. To perform the CCI and sham surgery, anesthetize the mouse by placing it in an anesthesia induction chamber connected to an anesthesia machine delivering a gaseous mixture of isoflurane (2.5%) and oxygen (2 L/min), until the animal loses the consciousness. Subsequently, take the animal from the induction chamber, place it on a dissection table, cover its nose by a tube attached to anesthesia machine, and continue anesthesia (isoflurane 2.5% and oxygen 2 L/min) throughout the duration of the surgery. 2. Open the skin at the right mid-thigh by making an incision (approximately 1 cm long), and cut the underlying muscle. 3. Expose the sciatic nerve using fine forceps with curved, smooth tips. For the CCI, place three loose silk sutures (4/0) around the nerve with about 1 mm spacing (see Note 4) and tie them carefully, until they elicit a brief twitch in the respective hind limb. For sham surgery, leave the nerve intact. 4. Close the wound with two or three silk sutures.

3.2

Animal Perfusion

1. It is recommended to perform the perfusion in a chemical fume hood. 2. Deeply anesthetize the animal (in an anesthesia induction chamber; see Subheading 3.1, step 1), and make a midline skin incision from the thoracic inlet to the pelvis. Hold the tip

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of the sternum with forceps and make an incision on the left and right sides of the thoracic cavity to expose the heart. 3. Gently grasp the heart and identify the left ventricle. Place the needle (21 gauge) into the left ventricle toward the aorta and clamp or hold it in place. Start to perfuse the animal with about 40–50 mL of 1
PBS at room temperature (using a pump or a 50 mL syringe). Immediately afterwards incise the right atrium to allow the perfusate to exit the circulation. 4. When the fluid exiting the mouse is clear of blood (see Note 5), stop the PBS perfusion and change to cold 4% PFA (keep the bottle on ice). Slowly perfuse the animal with approximately 40–50 mL of PFA. This should result in visible extension/ stretching of the limbs. After perfusion is complete, immediately start to remove the tissues (see Subheading 3.3). 3.3

Tissue Isolation

1. Start with dissecting the paw tissue; use a sharp razor blade. Take off the skin and subcutaneous tissue from the plantar side of the hind paw by cutting just below the bone. 2. To isolate the sciatic nerve, remove the fur at the level of the mid-thigh. Proceed with step 2 described in Subheading 3.1 to isolate a piece of the sciatic nerve containing the CCI ligatures, the corresponding part of sham- and/or non-operated nerves. The part of injured nerves should include the ligation site and sites proximal and distal to it. 3. To isolate the spinal cord, remove the fur and skin on the back of the mouse. Cut the spine (with surrounding muscle) as far posterior as possible (until the level at which the femur head joints the pelvis). Then, cut along the spine on both sides and remove the spine at the level of the ribs (including at least one pair of ribs). 4. Pin the spine on a rubber dish (bearing in mind the cranial– caudal orientation) under a dissection microscope and open the lamina of the vertebral arch starting at the cranial end by cutting it alternately on the right and left sides. 5. Take out the spinal cord by gently holding the cranial part of the spine with forceps, and carefully cut off the spinal nerves. 6. Identify the lumbar enlargement of the spinal cord and isolate it. 7. To isolate the DRG, identify the most cranial vertebra that lacks an articulation with a rib and mark it as the first lumbar (L1) vertebra [37]. 8. Isolate the DRGs that supply the sciatic nerve (in mice mainly L3 and L4; a minor supply comes from L5 DRG) [37] (see Note 6).

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9. Postfix tissues for 2 h in 4% PFA in 1
PBS (DRG, sciatic nerve, and spinal cord) or in Zamboni’s fixative (paw skin) for 5–8 h at 4  C. 10. Exchange the fixative solution with 10% sucrose solution (in 1
PBS) at 4  C overnight; optionally, change to a 30% sucrose solution after 1 h. 11. On the next day, freeze the tissues in a water-soluble frozen section medium and cut them on a cryostat, or store at 80  C until further processing. 12. Prepare approximately 10 μm thick sections of the DRG, sciatic nerves, and spinal cord, and approximately 12 μm thick sections of the paw tissue. Mount sections on polysine-coated slides. 13. Let the slides dry for at least half an hour at room temperature. 3.4 Single and Double Immunofluorescence

1. Place the slides horizontally in a plastic slide box (covered with wet paper to create a “moist chamber”; alternatively, use commercially available slide moist chamber). 2. Wash the slides twice for 5 min with 1
PBS. 3. Expose the slides to the dilution buffer (including 5% normal serum from the host species of the secondary antibody) for 1 h. 4. To examine single staining or the co-expression of opioid receptors with neuronal markers, incubate the sections overnight with rabbit polyclonal antibodies to the respective opioid receptor (we used the μ-receptor Ab10275 from Abcam [see Subheading 2.2] at a concentration of 1:800) [20] alone or in combination with polyclonal guinea pig anti-α-CGRP (1:800) or chicken anti-NF200 (1:500) appropriately diluted in the dilution buffer. 5. On the next day, wash the slides (3–4 times for 10 min, preferably under mild agitation, e.g., on a shaker) with 1
PBS; the most convenient is to use a glass box for microscopic slides filled with 1
PBS. 6. Incubate the slides for 1 h with the secondary antibodies, e.g., goat anti-rabbit conjugated to Texas Red alone or combined with goat anti-guinea pig conjugated to FITC, or goat antichicken conjugated to FITC (both at a dilution of 1:200). Secondary antibodies coupled to Alexa Flour dyes can be used at a concentration of 1:1000. 7. To identify opioid receptors in non-peptidergic C fibers, apply IB4 conjugated to FITC (1:150), according to the procedure described for the secondary antibodies (see step 6).

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8. Thereafter, wash the sections with PBS (3–4 times for 10 min), carefully remove as much remaining PBS as possible, and mount the slides in Mowiol (see Note 7). 3.5 DAB Immunohistochemistry

1. Follow step 1 in Subheading 3.4. 2. Incubate the slides for 45 min in PBS+ with 0.3–0.6% H2O2 and 40–50% methanol to block endogenous peroxidase; alternatively use 0.3% H2O2 and 0.1% sodium azide in PBS, because some antigens can be damaged by the use of methanol. 3. Wash the slides (3–4 times for 10 min, preferably under mild agitation) with 1
PBS. 4. Expose the slides to the dilution buffer (including 5% normal serum from the host species of the secondary antibody) for 1 h. 5. To examine the expression of opioid receptors, incubate the sections overnight with rabbit polyclonal antibodies to the respective opioid receptor (we used μ-receptor Ab10275 from Abcam [see Subheading 2.2] at a concentration of 1:1500) [20], diluted in PBS+. 6. On the next day, wash the slides (3–4 times for 10 min, preferably under mild agitation) with 1
PBS. 7. Expose the slides to the secondary antibody solution (follow the instructions on the ABC Elite kit) for approximately 1 h. 8. Wash the slides (3–4 times for 10 min, preferably under mild agitation) with 1
PBS (no PBS+ at this step). 9. Incubate the slides in the biotin-peroxidase solution for 30–60 min (follow the instructions on the kit; instead of PBS + use 1
PBS as a buffer). 10. Wash the slides with 1
PBS (3–4 times for 10 min). 11. Prepare DAB (follow the instructions on the kit), and stain the slides for 30 s up to 2 min (the time should be determined on a “positive” slide and should be similar for all slides; see Note 8). 12. Rinse the slides twice with tap water after DAB staining. 13. Dehydrate the slides in alcohol of increasing concentrations (70%, 80%, and 100%), and clear them in xylene solutions of increasing concentrations (70%, 80%, and 100%). 14. Mount the slides in Entellan and air-dry them under the hood.

3.6 Antibody Specificity Controls

1. Include slides without staining with the primary antibody in each staining procedure to verify the staining specificity of the secondary antibody. 2. Preabsorption test: To exclude antigen-independent nonspecific interactions of the primary antibody, incubate the primary antibody with the respective immunizing peptide: add the peptide to the primary antibody solution in a five- to tenfold

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excess (or according to the instructions on the data sheet) and leave it on a shaker at room temperature for at least 3 h before applying the solution to a slide (see Note 9). The lack of staining in this experiment will confirm that the antibody selectively binds to its commercial immunizing peptide. However, this does not guarantee specific staining of the native protein, and it is now clear that the preabsorption test must be supported by additional control experiments (see Note 10). 3. Cell lines with and without a protein of interest can be employed; we have used human embryonic kidney (HEK) 293 cells [20]. Transiently transfect HEK 293 cells with plasmids containing the full-length cDNA (approximately 2 μg) of the respective mouse opioid receptor. Ideally, transfect HEK 293 cells with μ-, δ-, or κ-opioid receptor cDNA, respectively. Use a transfection agent (e.g., X-tremeGENE HP DNA transfection reagent; Roche) following the protocol of the manufacturer. Test the opioid receptor antibody in question on all transfected and on untransfected HEK 293 cells. Wash cells in 1
PBS (in a cell plate dish), fix them in 4% PFA and 4% sucrose in PBS for 15 min at room temperature, wash again, and permeabilize in 0.25% TritonX-100 in PBS for 5 min. Wash again and block cells with 10% BSA in PBS for 30 min at 37  C, and incubate with the primary antibody in 3% BSA/PBS for 2 h at 37  C. After washing, incubate the sections with a fluorophore-conjugated secondary antibody in 3% BSA/PBS for 45 min at 37  C. Wash again and mount in Mowiol. However, the data obtained from experiments using cell lines might also not be predictive for ex vivo antibody staining (see Note 11). 4. Ideally, use tissue from animals genetically lacking the opioid receptor in question (see Note 12). We used tissue from the triple μ-, δ-, and κ-receptor knockout mice (see Note 2). To check for possible cross-reaction of a given opioid receptor antibody with the other opioid receptors, it is recommended to use tissue from mice lacking only one opioid receptor type of interest.

4

Notes 1. We prepared the phosphate buffer and Zamboni’s fixative according to the instructions kindly provided by Dr. Stanley J. Watson (Department of Pharmacology, University of Michigan Medical School, Ann Arbor, MI, USA). 2. Regardless of the antibody specificity, there is no guarantee that each batch of the same antibody type will produce satisfactory staining quality. We and other researches had batches

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producing good intensity staining and batches producing no staining at all [20, 35]. The triple μ-, δ-, and κ-receptor knockout mice were provided by Drs. Brigitte L. Kieffer and Claire Gave´riaux-Ruff (Institut de Genetique et de Biologie Moleculaire et Cellulaire, CNRS/INSERM/ULP, Strasbourg, France) [36]. 3. This antibody is also commonly used by other researchers; however, we had no opportunity to test it in tissue from mice lacking CGRP. 4. Close the fine forceps, place them underneath the nerve, and lift the nerve up; while doing this, slowly open the forceps (ideally the forceps are wrapped with a rubber band that limits the opening according to the desired width of the ligated nerve part), thereby freeing the nerve part of surrounding tissue. We usually place the two outer ligatures first, which results in a twitch of the corresponding hind limb. Then we place the middle ligature; this is often not accompanied by a visible limb twitch. 5. The color change of the liver from red to skin color is normally easily visible and a good sign that the perfusion is working properly. 6. The DRG can be identified within the intervertebral foramen. If necessary, carefully cut the remaining vertebral arch behind the DRG on both sides and remove the arch to have better access to the DRG. Use fine scissors and forceps to free the DRG of interest from the spinal nerves, and place it in the fixative solution. 7. Use between 40 and 50 μL of Mowiol and apply it in a T-shape onto the slide (the shorter line of the T in direction to the left end of the slide). Then, carefully put a cover slip onto the slide and lower it from left to right trying to avoid air bubbles under the slip. 8. The DAB kits we used suggested incubation times between 2 and 10 min; however, we experienced that a shorter time of about 30–60 s is sufficient to develop a clear signal. Longer incubation times may lead to increases in background staining. 9. Per concentration of the antibody, tissue type, and treatment, use at least one slide with the respective opioid receptor antibody alone and one slide with the opioid receptor antibody preincubated with the corresponding immunizing peptide mixture. 10. The ongoing debate about the lack of specificity of opioid receptor antibodies and G-protein-coupled receptor antibodies in general indicates that the disappearance of staining after preabsorption with immunizing peptides is an insufficient

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indicator for specific labeling in immunohistochemistry [33, 38, 39]. We have made similar observations. Thus, although the preabsorption of the anti-μ-receptor (Ab10275; Abcam) with the μ-receptor peptide (Abcam) resulted in the absence of staining, the antibody similarly stained DRG from wild-type and triple μ-, δ-, and κ-receptor knockout mice [20]. 11. Although in our experiments the anti-μ-receptor positively stained HEK 293 cells transfected with the mouse μ-receptor and did not stain untransfected or δ-receptor-transfected HEK 293 cells, it was still not specific to μ-receptors in mouse DRG [20] (see Note 10). 12. Since the antibody specificity might depend on the tissue type [20, 33], we strongly recommend to test all tissues of interest both in wild-type and knockout animals. Per concentration of the antibody and per tissue type, use at least one slide with opioid receptor knockout tissue and one slide with opioid receptor wild-type tissue.

Acknowledgments This work was supported by the Deutsche Forschungsgemeinschaft grant (MA 2437/1-4; H.M). References 1. Zo¨llner C, Stein C (2007) Opioids. Handb Exp Pharmacol 177:31–63 ¨ M (2020) Opioid recep2. Machelska H, Celik O tors in immune and glial cells—implications for pain control. Front Immunol 11:300 3. Kalso E, Smith L, McQuay HJ, Andrew Moore R (2002) No pain, no gain: clinical excellence and scientific rigour—lessons learned from IA morphine. Pain 98:269–275 4. Stein C, Machelska H (2011) Modulation of peripheral sensory neurons by the immune system: implications for pain therapy. Pharmacol Rev 63:860–881 5. Sawynok J, Liu J (2014) Contributions of peripheral, spinal, and supraspinal actions to analgesia. Eur J Pharmacol 734:114–121 ¨ (2018) Advances in 6. Machelska H, Celik MO achieving opioid analgesia without side effects. Front Pharmacol 9:1388 7. Minami M, Maekawa K, Yabuuchi K et al (1995) Double in situ hybridization study on coexistence of mu-, delta- and kappa-opioid

receptor mRNAs with preprotachykinin A mRNA in the rat dorsal root ganglia. Brain Res Mol Brain Res 30:203–210 8. Li JL, Ding YQ, Li YQ, Nomura S et al (1998) Immunocytochemical localization of mu-opioid receptor in primary afferent neurons containing substance P or calcitonin gene-related peptide. A light and electron microscope study in the rat. Brain Res 794:347–352 9. Mousa SA, Cheppudira BP, Shaqura M et al (2007) Nerve growth factor governs the enhanced ability of opioids to suppress inflammatory pain. Brain 130:502–513 10. Gaveriaux-Ruff C, Nozaki C, Nadal X et al (2011) Genetic ablation of delta opioid receptors in nociceptive sensory neurons increases chronic pain and abolishes opioid analgesia. Pain 152:1238–1248 11. Weibel R, Reiss D, Karchewski L et al (2013) Mu opioid receptors on primary afferent nav1.8 neurons contribute to opiate-induced

Immunohistochemistry of Opioid Receptors analgesia: insight from conditional knockout mice. PLoS One 8:e74706 12. Hassan AHS, Ableitner A, Stein C et al (1993) Inflammation of the rat paw enhances axonal transport of opioid receptors in the sciatic nerve and increases their density in the inflamed tissue. Neuroscience 55:185–195 13. Li JL, Kaneko T, Mizuno N (1996) Effects of peripheral nerve ligation on expression of mu-opioid receptor in sensory ganglion neurons: an immunohistochemical study in dorsal root and nodose ganglion neurons of the rat. Neurosci Lett 214:91–94 14. Coggeshall RE, Zhou S, Carlton SM (1997) Opioid receptors on peripheral sensory axons. Brain Res 764:126–132 15. Zhang X, Bao L, Arvidsson U, Elde R et al (1998) Localization and regulation of the delta-opioid receptor in dorsal root ganglia and spinal cord of the rat and monkey: evidence for association with the membrane of large dense-core vesicles. Neuroscience 82:1225–1242 16. Wenk HN, Honda CN (1999) Immunohistochemical localization of delta opioid receptors in peripheral tissues. J Comp Neurol 408:567–579 17. Labuz D, Schmidt Y, Schreiter A et al (2009) Immune cell-derived opioids protect against neuropathic pain in mice. J Clin Invest 119:278–286 18. Truong W, Cheng C, Xu QG et al (2003) Mu opioid receptors and analgesia at the site of a peripheral nerve injury. Ann Neurol 53:366–375 19. Kabli N, Cahill CM (2007) Anti-allodynic effects of peripheral delta opioid receptors in neuropathic pain. Pain 127:84–93 20. Schmidt Y, Gave´riaux-Ruff C, Machelska M (2013) μ-Opioid receptor antibody reveals tissue-dependent specific staining and increased neuronal μ-receptor immunoreactivity at the injured nerve trunk in mice. PLoS One 8:e79099 21. Mousa SA, Shaqura M, Al-Madol M et al (2017) Accessibility of axonal G protein coupled mu-opioid receptors requires conceptual changes of axonal membrane targeting for pain modulation. J Control Release 268:352–363 22. Cayla C, Labuz D, Machelska H et al (2012) Impaired nociception and peripheral opioid antinociception in mice lacking both kinin B1 and B2 receptors. Anesthesiology 116:448–457

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23. Labuz D, Machelska H (2013) Stronger antinociceptive efficacy of opioids at the injured nerve trunk than at its peripheral terminals in neuropathic pain. J Pharmacol Exp Ther 346:535–544 ¨ , Zimmer A et al (2016) 24. Labuz D, Celik MO Distinct roles of exogenous opioid agonists and endogenous opioid peptides in the peripheral control of neuropathy-triggered heat pain. Sci Rep 6:32,799 25. Rodriguez-Gaztelumendi A, Spahn V et al (2018) Analgesic effects of a novel pH-dependent μ-opioid receptor agonist in models of neuropathic and abdominal pain. Pain 159:2277–2284 26. Labuz D, Schreiter A, Schmidt Y et al (2010) T lymphocytes containing β-endorphin ameliorate mechanical hypersensitivity following nerve injury. Brain Behav Immun 24:1045–1053 27. Liou JT, Liu FC, Mao CC et al (2011) Inflammation confers dual effects on nociceptive processing in chronic neuropathic pain model. Anesthesiology 114:660–672 ¨ , Labuz D, Henning K et al (2016) 28. Celik MO Leukocyte opioid receptors mediate analgesia via Ca(2+)-regulated release of opioid peptides. Brain Behav Immun 57:227–242 29. Michel MC, Wieland T, Tsujimoto G (2009) How reliable are G-protein-coupled receptor antibodies? Naunyn Schmiedebergs Arch Pharmacol 379:385–388 30. Scherrer G, Imamachi N, Cao YQ et al (2009) Dissociation of the opioid receptor mechanisms that control mechanical and heat pain. Cell 137:1148–1159 31. Baker M (2015) Reproducibility crisis: Blame it on the antibodies. Nature 521:274–276 32. Bradbury A, Plu¨ckthun A (2015) Reproducibility: standardize antibodies used in research. Nature 518:27–29 33. Jositsch G, Papadakis T, Haberberger RV et al (2009) Suitability of muscarinic acetylcholine receptor antibodies for immunohistochemistry evaluated on tissue sections of receptor genedeficient mice. Naunyn Schmiedebergs Arch Pharmacol 379:389–395 34. Lorincz A, Nusser Z (2008) Specificity of immunoreactions: the importance of testing specificity in each method. J Neurosci 28:9083–9086 35. Couchman JR (2009) Commercial antibodies: the good, bad, and really ugly. J Histochem Cytochem 57:7–8

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36. Karaji AG, Reiss D, Matifas A et al (2011) Influence of endogenous opioid systems on T lymphocytes as assessed by the knockout of mu, delta and kappa opioid receptors. J Neuroimmune Pharmacol 6:608–616 37. Rigaud M, Gemes G, Barabas ME et al (2008) Species and strain differences in rodent sciatic nerve anatomy: implications for studies of neuropathic pain. Pain 136:188–201

38. Saper CB (2005) An open letter to our readers on the use of antibodies. J Comp Neurol 493:477–478 39. Uhlen M, Bandrowski A, Carr S et al (2016) A proposal for validation of antibodies. Nat Methods 13:823–887

Chapter 8 Real-Time Quantitative Reverse Transcription PCR for Detection of Opioid Receptors in Immune Cells Melih O¨zgu¨r Celik, Dominika Labuz, and Halina Machelska Abstract Real-time quantitative reverse transcription-PCR (qRT-PCR) is a highly sensitive molecular biology method based on the amplification of the cDNA of mRNA to detect and quantify the levels of mRNA of interest. In this chapter, we describe real-time qRT-PCR to detect and quantify mRNA of opioid receptors in immune cells. Specifically, we analyze mouse immune cells isolated from the blood and sciatic nerves exposed to a chronic constriction injury, which represents a model of neuropathic pain. We describe in detail the requirements and techniques to induce the chronic constriction injury, to isolate immune cells from the blood and injured nerves, to isolate the total RNA from immune cells, to perform a cDNA reverse transcription from the total RNA, and to perform real-time qRT-PCR for μ-, δ-, and κ-opioid receptor mRNAs. Key words qRT-PCR, Immune cells, Opioid receptors, mRNA, Chronic constriction injury, Neuropathic pain

1

Introduction Opioid receptors, μ (MOR), δ (DOR), and κ (KOR), are widely distributed in the peripheral and the central nervous system, and their activation produces analgesia. In contrast to opioid receptors in the brain, the activation of opioid receptors in peripheral sensory neurons is devoid of side effects such as respiratory depression, sedation, nausea, vomiting, and addiction. Targeting peripheral opioid receptors is thus of great interest, especially because many painful syndromes originate in peripheral tissues (e.g., skin, joints, viscera) [1]. All three peripheral opioid receptors contribute to the attenuation of experimental neuropathic pain [2], and their activation at the nerve injury site was particularly effective [3]. The underlying mechanisms include the upregulation of neuronal opioid receptors at the nerve injury site [4] and the enhanced agonist access to these receptors as a result of blood-nerve barrier disruption [5, 6].

Santi M. Spampinato (ed.), Opioid Receptors: Methods and Protocols, Methods in Molecular Biology, vol. 2201, https://doi.org/10.1007/978-1-0716-0884-5_8, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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Importantly, injured nerves are infiltrated by immune cells, including macrophages, neutrophils, and lymphocytes. Interestingly, these immune cells also express opioid receptors (MOR, DOR, and KOR) and contribute to analgesia [7]. Opioid receptors in immune cells have similar pharmacological and biochemical characteristics, and are encoded by the same genes as neuronal receptors [8, 9]. However, they are difficult to identify with conventional molecular biology methods (e.g., PCR, Northern blotting) because they are expressed at relatively low levels in immune cells and their expression may be influenced by factors such as in vivo condition (physiological vs. pathological), type and duration of the disease, type and duration of in vivo pharmacological treatment, immune cell populations, tissue they originate from, and methodological challenges (e.g., isolation of sufficient number of viable cells, RNA yield, PCR primer design). In this chapter, we describe the real-time quantitative reverse transcription-PCR (qRT-PCR) methodology to detect MOR, DOR, and KOR mRNAs in mouse immune cells isolated from the blood and sciatic nerves exposed to a chronic constriction injury (CCI), which represents a model of neuropathic pain.

2 2.1

Materials Reagents

1. 1 RPMI 1640 growth medium. 2. HEPES. 3. Fetal bovine serum (FBS). 4. Isoflurane. 5. Trypan blue stain. 6. Trizol. 7. Chloroform. 8. Isopropanol. 9. Glycogen. 10. Ethanol (EtOH). 11. Heparin. 12. β-Mercaptoethanol.

2.2

Enzymes

1. Collagenase. 2. Hyaluronidase.

2.3

Fluorescein Dyes

1. Fluorescein amidite (FAM). 2. Acridine orange/propidium iodide fluorescence dye.

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2.4 Digestive Solution

1. 10 mL RPMI 1640 medium, 0.5 mL HEPES, 30 mg collagenase, 10 mg hyaluronidase, and 200 μL FBS (2%).

2.5

1. RNeasy Plus Mini Kit.

Commercial Kits

2. Superscript IV VILO Master Mix with ezDNase Enzyme (Thermo Fisher). 3. TaqMan Fast Advanced Master Mix (Thermo Fisher). 4. TaqMan Gene Expression Mm01188089_m1–FAM).

Assay

for

MOR

(Oprm1,

5. TaqMan Gene Expression Mm01180757_m1–FAM).

Assay

for

DOR

(Oprd1,

6. TaqMan Gene Expression Mm01230885_m1–FAM).

Assay

for

KOR

(Oprk1,

7. TaqMan Gene Expression Assay for a housekeeping gene glyceraldehyde-3-phosphate dehydrogenase (GAPDH) (Mm99999915_g1–FAM). 2.6 Surgical Dissection Tools for CCI

This section is also described in the chapter by Seitz et al. in this volume. 1. Sharp straight dissecting scissors. 2. Two sharp x-curved tip forceps (Nr. 4314, RK Instruments): On the tips of one of the forceps, a piece of tape is placed (see Note 1). 3. Holding forceps with straight smooth tips (Nr. 1091; RK Instruments). 4. Silk thread (4/0). 5. Suture needles (1/2 circle). 6. Electric shaver.

2.7 Animals and Other Materials

1. Male C57BL/6J mice (8–10 weeks old). 2. Anesthesia induction chamber. 3. Anesthesia machine. 4. Oxygen bottle. 5. Surgical blade (no. 21). 6. Cell strainer (70 μm). 7. Polypropylene tubes (15 and 50 mL). 8. Cell scraper (25 cm). 9. Centrifuge tubes (1.5 mL). 10. Phase-maker tube. 11. Erythrocyte lysis buffer. 12. Luna dual-fluorescence cell counter (Logos).

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13. Luna cell counting slide (Logos). 14. Thermomixer. 15. Micropipettes (1, 10, 100, 1000 μL). 16. DS-11 spectrophotometer. 17. 96-Well reaction plate. 18. Adhesive PCR plate seal. 19. qPCR instrument. 20. ddH2O. 21. RNA storage solution.

3

Methods All procedures involving animals must be approved beforehand by the local ethics committee.

3.1 CCI of the Sciatic Nerve

This section is also described in the chapter by Seitz et al. in this volume. 1. To perform the CCI, anesthetize the mouse by placing it in an anesthesia induction chamber connected to an anesthesia machine delivering a gaseous mixture of isoflurane (2.5%) and oxygen (2 L/min), until the animal loses the consciousness. Subsequently, take the animal from the induction chamber, place it on a dissection table, cover its nose by a tube attached to an anesthesia machine, and continue anesthesia (isoflurane 2.5% and oxygen 2 L/min) throughout the duration of the surgery. 2. Shave the right hind leg of the mouse and clean the shaved area with alcohol (70% EtOH). 3. Lift the skin with sharp curved tip forceps without tape and using the sharp straight scissors cut the skin at the right mid-thigh by making an incision (approximately 1 cm long), expose the underlying biceps femoris muscle, hold it with the sharp curved tip forceps without tape, and cut it with the scissors. 4. Gently lift the muscle with the sharp curved tip forceps without tape and carefully free the sciatic nerve from the surrounding tissue using the second forceps with sharp curved tips with the tape (see Note 1). 5. For the CCI, place the forceps with the sharp curved tips with the tape under the nerve and gently lift the nerve. The tape on the forceps assures to expose the nerve at the 1 cm length (see Note 1). Place three loose silk sutures (4/0) around the nerve with about 1 mm spacing (see Note 2). To make sure that the

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sutures are placed loosely, tie them carefully by making two knots (on each suture, using hand and forceps with the sharp curved tips without the tape), until they elicit a brief twitch in the respective hind limb. Typically, the twitch is seen when placing the first knots on the first and the second sutures. 6. Using the straight-holding forceps and the suture needle, close the skin with a silk suture. Typically, one suture is sufficient, but use the second one, if the cut of the skin is longer than 1 cm (see step 3 above). 3.2 Immune Cell Isolation from Blood

1. Sacrifice the mouse 2 days after CCI by an overdose of isoflurane according to the protocol approved by your local ethics committee. 2. Decapitate the mouse and collect ~0.6 mL of blood in a tube containing heparin. Immediately afterwards, isolate the immune cells from the injured nerve of the same mouse (see Subheading 3.3, steps 1–4), and then continue with next steps in this section. 3. Centrifuge the sample at 380  g for 5 min at 4  C, and discard the supernatant. 4. Disturb the remaining pellet via gentle shaking and place the sample on ice. 5. Repeat steps 1–4 for the next two mice. 6. Pool cell pellets from three mice in a 50 mL falcon tube (see Note 3), and resuspend the sample in 5 mL of erythrocyte lysis buffer. Vortex the solution thoroughly for approximately 5 s and incubate on ice for 5 min. 7. Add 20 mL of RPMI 1640 medium, vortex for approximately 5 s, centrifuge the solution at 380  g for 5 min at 4  C, and discard the supernatant. 8. Disturb the remaining pellet via gentle shaking, resuspend the pellet in 1 mL RPMI 1640 medium, and keep on ice. 9. Mix 18 μL of the pellet solution from step 8 with 2 μL of acridine orange/propidium iodide fluorescence stain in a new centrifuge tube. Apply 10 μL of this mixture to a cell-counting slide and load the slide in an automated cell counter to verify cell viability and to count the cell numbrs. Alternatively, cell numbers and viability can be verified by Neubauer chamber using trypan blue exclusion method. 10. Centrifuge the solution from step 8 at 380  g for 5 min at 4  C and discard the supernatant. 11. Repeat steps 6–10 for a desired number of samples. 12. Continue with the RNA extraction (see Subheading 3.4).

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3.3 Immune Cell Isolation from Injured Nerves

1. Isolate the ligated part of the sciatic nerve (approximately 1 cm long) from the same mice from whom the blood was taken, immediately after collecting the blood (see Subheading 3.2, step 2). 2. To isolate the ligated part of the nerve, spray the right hind leg of the mouse (where the CCI was performed) with 70% EtOH to avoid hair contamination during the nerve isolation. Using the straight sharp dissecting scissors, cut and remove the skin at the right mid-thigh (approximately 2 cm long). Expose the underlying biceps femoris muscle, and gently lift it with the curved sharp tip forceps without tape. 3. Free the sciatic nerve from the surrounding tissue by placing the forceps with the curved sharp tip with the tape under the nerve. This way, approximately 1 cm of the nerve is exposed. Lift the nerve using the forceps with the curved sharp tip with the tape, already under the nerve, and cut the ligated part of the sciatic nerve (approximately 1 cm long), including the ligation site and sites distal and proximal to it. 4. Place the isolated nerve fragment on a sterile tissue culture dish and cut it into small pieces using surgical blade (no. 21). Afterwards, place the minced nerve fragments in 2 mL digestive solution in a 15 mL falcon tube on ice. 5. Repeat steps 1–4 for the next two mice. 6. Pool three isolated nerve fragments in a 15 mL falcon tube (see Note 3), mix thoroughly for approximately 5 s using a vortex, and incubate at 37  C for 60 min in an incubator. Vortex the solution every 10 min during the incubation. 7. Filter the solution through a 70 μm cell strainer attached to 50 mL falcon tube. Wash the sieve using 30 mL of RPMI 1640 medium and scrape the surface of the sieve after pouring 6 mL RPMI 1640 medium (up to 30 mL) using the sterile cell scraper (25 cm) to aid the filtering/washing procedure. 8. Centrifuge the filtered solution at 380  g for 5 min at 4  C and discard the supernatant. 9. Disturb the remaining pellet via gentle shaking and resuspend the pellet in 5 mL of erythrocyte lysis buffer. Vortex the solution thoroughly for approximately 5 s and incubate on ice for 5 min. 10. Add 20 mL of RPMI 1640 medium, vortex for approximately 5 s, centrifuge the solution at 380  g for 5 min at 4  C, and discard the supernatant. 11. Disturb the remaining pellet via gentle shaking, resuspend the pellet in 1 mL RPMI 1640 medium, and keep on ice.

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12. Mix 18 μL of the pellet solution from step 11 with 2 μL of acridine orange/propidium iodide fluorescence stain in a new centrifuge tube. Apply 10 μL of this mixture to a cell-counting slide and load the slide in an automated cell counter to verify cell viability and to count the cell numbers. Alternatively, cell numbers and viability can be verified by Neubauer chamber using trypan blue exclusion method. 13. Centrifuge the solution from step 11 at 380  g for 5 min at 4  C and discard the supernatant. 14. Repeat steps 6–13 for a desired number of samples. 15. Continue with the RNA extraction (see Subheading 3.4). 3.4 Extraction of Total RNA by Trizol

1. Add 1 mL Trizol reagent to the cell pellets (from Subheading 3.2, step 10, and Subheading 3.3, step 13), vortex for approximately 15 s, and keep it at room temperature for 5 min. 2. Centrifuge the lysate for 5 min at 12,000  g at 4  C and transfer the clear supernatant to a phase-maker tube. 3. Add 0.2 mL of chloroform (see Note 4), mix vigorously for 15 s, and incubate for 5 min at room temperature. 4. Centrifuge the solution for 5 min at 12,000  g at 4  C and transfer the aqueous phase into a new 1.5 mL sterile centrifuge tube: the homogenate will be separated in three layers, where the upper aqueous phase contains the RNA. 5. Add 0.5 mL of ice-cold isopropanol and 0.5 μL of glycogen (10 μg) to the aqueous phase and incubate the solution for 10 min at room temperature. 6. Centrifuge the solution for 10 min at 12,000  g at 4  C and discard the supernatant. 7. Resuspend the pellet in 1 mL of ice-cold 75% EtOH, vortex the solution for 2 s, and centrifuge for 5 min at 12,000  g at 4  C. 8. Discard the supernatant, resuspend the pellet in 1 mL of ice-cold 75% EtOH, vortex the solution for 2 s, and centrifuge for 5 min at 12,000  g at 4  C. 9. Discard the supernatant and air-dry the RNA pellet for 10 min at room temperature. 10. Resuspend the RNA pellet in 40 μL of ddH2O water and incubate at 55  C for 5 min in a thermomixer. 11. Continue with RNA cleanup protocol (see Subheading 3.5).

3.5 RNA Cleanup Protocol Using Qiagen RNeasy Plus Mini Kit

1. Add 350 μL of RLT buffer to the RNA solution (from Subheading 3.4, step 10). Add 10 μL of β-mercaptoethanol for every 1 mL of RLT buffer. 2. Transfer the lysate to a gDNA eliminator spin column and centrifuge for 60 s at 8000  g.

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3. Save the flow through and add 350 μL of 70% EtOH. Mix well by pipetting (using 100 μL micropipette). 4. Transfer 700 μL of the sample to the RNeasy spin column and centrifuge for 30 s at 8000  g. 5. Add 700 μL RW1 buffer and centrifuge for 30 s at 8000  g. 6. Add 500 μL RPE buffer and centrifuge for 30 s at 8000  g. 7. Add 500 μL RPE buffer and centrifuge for 2 min at 8000  g. 8. Place the RNeasy spin column in a new 2 mL collection tube and centrifuge for 1 min at 12,000  g. 9. Add 30 μL of RNA storage solution, incubate for 1 min, and centrifuge for 1 min at 8000  g. 10. Add 30 μL of RNA storage solution, incubate for 1 min, and centrifuge for 1 min at 8000  g. 11. Measure the RNA quantity and quality (see Subheading 3.6) and ideally continue with the cDNA synthesis (see Subheading 3.7), or store the samples at 80  C until further experiments. 3.6 Measuring Total RNA Concentration and Quality by Using Spectrophotometer

1. Use nanodrop or a similar spectrophotometer to measure RNA concentration and quality. 2. Clean the spectrophotometer before use and press the nucleic acid/RNA tab. 3. Add 1 μL of “blank” solution (the solution used to dissolve RNA, e.g., RNA storage solution; see Subheading 3.5, step 10) to the lower pedestal and lower the arm to calibrate the spectrophotometer. 4. When the measurement is complete, lift the arm and clean the spectrophotometer. 5. Add 1 μL of the RNA sample (Subheading 3.5, step 10) to the lower pedestal to measure the total RNA concentration. 6. Check the 260/280 value of the RNA sample to estimate the possible contaminants (e.g., DNA). The 260/280 value of the RNA sample should be above 2 (see Note 5). 7. If the 260/280 value of the RNA sample is below 2, all steps in Subheadings 3.4 and 3.5 must be optimized to remove any contaminants (see Note 5). 8. If the RNA concentrations are below 70 ng/μL, all steps in Subheadings 3.2–3.4 should be optimized to increase the RNA concentration (see Note 6).

3.7 Reverse Transcription Protocol for Superscript IV VILO Master Mix

For each RNA sample, a reverse transcription (RT) and a no-RT control (all reaction components of the kit without the RT enzyme) reaction needs to be prepared.

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1. Treat all RNA samples with ezDNase enzyme to remove any remaining DNA contaminants. Hence, for each RNA sample, prepare a solution in a 1.5 mL centrifuge tube containing 1 μL of 10 ezDNase buffer, 1 μL of ezDNase enzyme, 1 μL of template RNA (200 ng/μL) (see Note 7), and 7 μL of nucleasefree water. Gently mix the solution, incubate it at 37  C in a thermomixer for 2 min, centrifuge for 5 s, and place on ice. 2. For the RT reaction, add 4 μL of Superscript IV VILO Master Mix and 6 μL of nuclease-free water to the 10 μL reaction mix from step 1. 3. For the no-RT reaction, add 4 μL of Superscript IV VILO no-RT control and 6 μL of nuclease-free water to the 10 μL reaction mix from step 1. 4. Gently mix the solutions (from steps 2 and 3) and incubate them at 25  C for 10 min in a thermomixer to anneal primers. 5. Incubate the solutions from step 4 at 50  C in a thermomixer for 10 min to reverse transcribe RNA. 6. Incubate the solutions from step 5 at 85  C in a thermomixer for 5 min to inactivate the RT enzyme. 7. Use the obtained cDNA for qRT-PCR (see Subheadings 3.8–3.10) or store at 20  C for up to 1 week, or at 80  C for a long term. 3.8 TaqMan Gene Expression Assays for MOR, DOR, and KOR

1. Thaw cDNA samples, no-RT controls (from Subheading 3.7, step 7), TaqMan fast advanced master mix, and TaqMan gene expression assays for the genes of interest (MOR, DOR, KOR) and for GAPDH, on ice. Mix the reagents by gentle vortexing. 2. Centrifuge all cDNA and the no-RT control samples for 5 s. 3. Dilute the cDNA samples and the no-RT controls using nuclease-free water. We dilute the cDNA at a ratio of 1:4 (see Note 8). 4. For each cDNA sample and the no-RT controls, prepare 20 μL of reaction solution consisting of the following components: 10 μL of 2 TaqMan Fast advanced master mix, 1 μL of TaqMan gene expression assay for MOR, 7 μL of water, and 2 μL of cDNA (1:4 diluted). Additionally, prepare a no-template control (all reaction components of the kit without the cDNA) to monitor contamination and primer-dimer formation. 5. Repeat step 4 using 1 μL of TaqMan gene expression assay for DOR. 6. Repeat step 4 using 1 μL of TaqMan gene expression assay for KOR. 7. Repeat step 4 using 1 μL of TaqMan gene expression assay for GAPDH.

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8. Mix the samples and centrifuge for 5 s. 9. Transfer 20 μL of qRT-PCR reaction mix, 20 μL of no-template control, and 20 μL of no-RT control from steps 4 to 8 into a 96-well reaction plate. 10. Seal the plate with the adhesive PCR tape and place it in the qPCR instrument (see Subheading 3.9). 3.9

Real-Time PCR

1. Create the experimental document in the qPCR instrument’s software using the following parameters: 2 min at 50  C, 1 min at 95  C, then 40 cycles of 15 s at 95  C, and 40 cycles of 45 s at 60  C, and start the reaction. 2. To analyze the data from TaqMan assays in the real-time PCR instrument, the amplification plots for the entire plate should be visible and the threshold value should be adjustable, in case the automated threshold value needs to be changed. The threshold value should be set carefully to allow accurate determination of Ct values, taking the early cycles of amplification into account to eliminate the background noise. 3. Use the comparative Ct method (ΔΔCt) to analyze the data (see Subheading 3.10).

3.10

ΔΔCt Method

1. For each sample, calculate the mean Ct value for the genes of interest (MOR, DOR, KOR), the housekeeping gene GAPDH, and the no-template and no-RT controls. 2. Any Ct value around the 35th cycle for the gene of interest can be unspecific and should not be included in Ct calculations. Check the Ct values for the no-RT controls. Their Ct values should be higher than the 35th cycle. However, if there is a Ct value below the 35th cycle for the no-RT controls, you still can use the Ct value of the gene of interest, providing that it is at least 6 cycles lower than the Ct value of its no-RT control. If this Ct value difference is lower than 6 cycles, the samples (both of the gene of interest and the no-RT control) should not be included in Ct calculations. 3. Any Ct value below the 35th cycle for the no-template control indicates that the TaqMan gene expression assay components are contaminated. The experiments should be repeated with fresh TaqMan Fast advanced master mix, TaqMan gene expression assay, and nuclease-free water. 4. Normalize the data by subtracting the Ct value of GAPDH from the Ct value of the gene of interest for the same sample. This normalized value is the ΔCt value. Use the ΔCt values from the samples of interest to calculate the fold change in mRNA expression. To do so, calculate the difference between their ΔCt values to generate the ΔΔCt values. Finally, apply the ΔΔCt values to compute the relative fold change between groups using the 2 ΔΔCt formula [10].

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Notes 1. To free and lift the sciatic nerve for the CCI, use the forceps with the sharp curved tips with a tape. Place the tape on the forceps tips so that the distance between the tips is 0.7 cm. This allows to expose the nerve at the length of 1 cm and prevents excessive stretching of the nerve. 2. To induce CCI, place the first suture on the nerve on the side closer to the spinal cord, the second suture on the nerve side closer to the paw, and the third suture in the middle of the exposed nerve, between the first two sutures. 3. The number of immune cells sufficient to measure opioid receptor mRNAs may depend on the type of nerve injury, its duration, immune cell type, the tissue type they originate from, the animal species, strain, sex and age, and the RNA extraction method. In our study, we collected immune cells from male C57BL/6J mice (8–10 weeks old), 2 days following CCI of the sciatic nerve. Under these conditions, pooling blood from three mice was sufficient to obtain ~2.1  106 blood immune cells, and pooling three sciatic nerve fragments was sufficient to obtain ~1.6  106 immune cells infiltrating the CCI nerve, as quantified in a Neubauer chamber [7]. From these cells, we were able to extract ~100 ng/μL of total RNA using Trizol extraction, which was sufficient to measure the mRNAs of all three MOR, DOR, and KOR, and of a housekeeping gene GAPDH. This represented one sample for each mRNA, and for statistical analysis we obtained eight samples for each opioid receptor mRNA [7]. Note that under these conditions, opioid receptor mRNA levels in immune cells from blood were lower compared to immune cells from injured nerves [7]. When using different experimental conditions, optimization of the methodology might be needed to extract sufficient amount of RNA in order to continue with the cDNA production prior to qPCR (e.g., different enzymes and incubation time for tissue digestion and immune cell isolation, different number of pooled animals, or RNA extraction protocols). 4. In the RNA extraction protocol, we used phase-maker tubes during the chloroform-Trizol phase separation. These tubes create a tight seal between the two phases that allows easy isolation of the aqueous phase, which contains the total RNA. This helps to reduce the risk of contamination and increases the RNA yield. 5. It is essential to measure the RNA quality after RNA extraction. In principle the 260/280 value of the RNA sample should be

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2 or more. Any value below 2 indicates impurities and therefore the RNA extraction/cleaning protocol needs to be optimized to avoid low qPCR yield and DNA contamination. 6. It is important to extract sufficient amount of RNA before the RT reaction. The RNA yield must be measured after the RNA extraction and optimization needs to be done if the yield is lower than ~70 ng/μL. Optimization can include pooling of more tissue/cells or adjustments in the RNA extraction/ cleanup protocol. Alternatively, RNA extraction kits for low amount of starting material can be used (e.g., RNeasy Micro Kit). 7. We used 200 ng/μL of RNA as a template in the RT mix. Depending on the RT kit used, the amount of template RNA that needs to be added to the reactions might differ. This amount can be modified depending on the following: (a) the GAPDH Ct value: GAPDH Ct values should be ~18. If the Ct value is lower than 18 (e.g., 14–17), then less template RNA can be used in the RT mix. If the GAPDH Ct value is higher than 18 (e.g., 19–21), then more template RNA can be used in the RT mix; (b) impurities in no-RT control: use lower amount of template RNA or treat the samples with DNase; (c) the Ct value of the gene of interest: if the Ct value of gene of interest is around 35, then more template RNA can be used in RT mix. 8. It is common to dilute cDNA prior to qPCR. We diluted the cDNA at a ratio of 1:4 with nuclease-free water. The dilution ratio can be modified depending on the following: (a) the GAPDH Ct value: dilute the cDNA at a higher ratio using nuclease-free water, if the GAPDH Ct value is less than ~18; (b) impurities in no-RT control: dilute the cDNA at a higher ratio using nuclease-free water, if the no-RT control Ct value is less than 35; (c) the Ct value of the gene of interest: use higher concentration of cDNA in the qPCR reaction, if the Ct value of the gene of interest is ~35.

Acknowledgments This work was supported by grants from the Deutsche Forschungsgemeinschaft (MA 2437/4-1, MA 6432/2-1). References ¨ (2018) Advances in 1. Machelska H, Celik MO achieving opioid analgesia without side effects. Front Pharmacol 9:1388 2. Stein C, Machelska H (2011) Modulation of peripheral sensory neurons by the immune

system: implications for pain therapy. Pharmacol Rev 63:860–881 3. Labuz D, Machelska H (2013) Stronger antinociceptive efficacy of opioids at the injured nerve trunk than at its peripheral terminals in

Opioid Receptor mRNA in Immune Cells neuropathic pain. J Pharmacol Exp Ther 346:535–544 4. Schmidt Y, Gave´riaux-Ruff C, Machelska H (2013) μ-Opioid receptor antibody reveals tissue-dependent specific staining and increased neuronal μ-receptor immunoreactivity at the injured nerve trunk in mice. PLoS One 8:11 5. Abram SE, Yi J, Fuchs A, Hogan QH (2006) Permeability of injured and intact peripheral nerves and dorsal root ganglia. Anesthesiology 105:146–153 6. Mousa SA, Shaqura M, Al-Madol M et al (2017) Accessibility of axonal G protein coupled mu-opioid receptors requires conceptual changes of axonal membrane targeting for pain modulation. J Control Release 268:352–363

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¨ , Labuz D, Henning K et al (2016) 7. Celik MO Leukocyte opioid receptors mediate analgesia via Ca2+ regulated release of opioid peptides. Brain Behav Immun 57:227–242 8. Gave´riaux C, Peluso J, Simonin F et al (1995) Identification of κ- and δ-opioid receptor transcripts in immune cells. FEBS Lett 369:272–276 9. Ninkovic´ J, Roy S (2013) Role of the mu opioid receptor in opioid modulation of immune function. Amino Acids 45:9–24 10. Livak KJ, Schmittgen TD (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2 ΔΔCT method. Methods 25:402–408

Part II Analysis of Signaling Events Modulated by Opioid Receptors

Chapter 9 Quantitative Analysis of MOR-1 Internalization in Spinal Cord of Morphine-Tolerant Mice Vittoria Borgonetti and Nicoletta Galeotti Abstract The biological process of opioid analgesic tolerance remains nowadays elusive. In particular the mechanism by which opioid receptor desensitization occurs has not been completely elucidated to date. One possible hypothesis involves the internalization of MOR. Here, we describe a simple in vitro protocol to investigate the localization of MOR-1 after repeated morphine administration in the spinal cord of morphine-tolerant mice, using western blotting and immunofluorescence techniques. Key words Morphine, Tolerance, μ-Opioid receptor, Internalization

1

Introduction Opioid receptors, i.e., mu (MOR), delta (DOR), and kappa (KOR), are G-protein-coupled receptors which inhibit pain transmission actin on ascending pain pathways [1]. Opioid agonists produce their pharmacological effects by preferentially binding MOR, which is widely expressed in neurons, modulating intracellular processes connected to pain [2]. Opioids are currently considered the most active pain-relieving drugs. However, their repeated use leads to the development of a tolerance state, which prevents opioid ability to provide long-term analgesia [3, 4]. This phenomenon is extremely complex and characterized by the desensitization, internalization, and phosphorylation of MOR [5]. In particular, it has been reported that prolonged opioid exposure leads to the increase of MOR phosphorylation, mediated by different kinases, such as G-protein-coupled receptor kinases (GRKs), Ca2+/calmodulin-dependent protein kinase II (CaMKII), protein kinase C (PKC), and mitogen-activated kinases (MAPKs) [6]. Ser 375 belongs to a group of 20 key phosphorylation sites in the C-terminus of MOR. It is accessible to protein kinases and involved in receptor phosphorylation, which is pivotal for the development

Santi M. Spampinato (ed.), Opioid Receptors: Methods and Protocols, Methods in Molecular Biology, vol. 2201, https://doi.org/10.1007/978-1-0716-0884-5_9, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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of opioid tolerance following chronic morphine treatment [7– 9]. The mechanism by which opioid receptor desensitization occurs has not been completely elucidated to date. One possible hypothesis involves the internalization of MOR [10]. Indeed, the phosphorylation process induces a change in the receptor conformation, leading to an increased affinity of the receptors for cytosolic β-arrestin proteins, which promotes the passage from membrane to cytosol [11–13]. Internalization of MOR has been demonstrated in different in vitro and in vivo models. However, contrasting opinion on the role played by internalization in the development of morphine tolerance still exists [6]. In this chapter we report a simple method to investigate the localization of MOR-1 after repeated morphine administration in the spinal cord of morphine-tolerant mice. Tissues lysates are processed in order to separate the membrane and the cytosol compartments and MOR-1 expression is analyzed by western blotting. Furthermore, a protocol for direct observation of the different cellular localization of MOR-1 and MOR-1 phosphorylated on Ser 375 in the dorsal horn spinal cord of tolerant mice by immunofluorescence technique is described. Together, these methods are useful to investigate the internalization of MOR-1 and the possible correlation with morphine tolerance evolution [14].

2 2.1

Materials Solutions

1. NaCl 0.9% (w/v) dissolved in ddH2O (isotonic saline solution). 2. Morphine hydrochloride was dissolved in isotonic saline solution in order to obtain solutions containing 10, 15, 20, or 30 mg/kg.

2.2 Western Blot Analysis

1. Tris–HCl 0.5 M pH 6.8 (dissolve 3 g of Trizma in 50 mL of ddH2O; adjust pH with 37% v/v HCl); Tris–HCl 1.5 M pH 8.8 (dissolve 9.1 g of Trizma in 50 mL of of ddH2O; adjust pH with 37% v/v HCl); Tris–HCl 1.0 M pH 7.5 (dissolve 6 g of Trizma in 50 mL of ddH2O; adjust pH with 37% v/v HCl). 2. Lysis buffer composition: 25 mM Tris–HCl pH 7.5, 25 mM NaCl, 5 mM EGTA, 2.5 mM EDTA, 2 mM NaPP, 4 mM PNFF, 1 mM Na3VO4, 1 mM PMSF, 20 μg/mL leupeptin, 50 μg/mL aprotinin, and 0.1% SDS (see Note 1). 3. Lysis buffer with 0.2% v/v Triton X-100: For 10 mL of solution, add 20 μL of Triton X-100 to 9.980 mL of lysis buffer. 4. PBS (10): For 1000 mL, dissolve NaCl (80 g), KCl (2.1 g), Na2HPO4 (15 g), and KH2PO4 (1.4 g) in a final volume of 1000 mL of ddH2O and adjust pH to 7.4.

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5. PBS (1): For 1 L of solution, dilute 100 mL of PBS (10) and 900 mL of ddH2O. 6. 10% Running gel: For 1 gel, use 1.21 mL of acrylamide 40%, 0.67 mL of bis-acrylamide 2%, 1.25 mL of Tris–HCl 1.5 M pH 8.8, 0.05 mL of SDS 10%, and 1.79 mL of ddH2O. To promote polymerization, add 0.05 mL of ammonium persulfate (APS) and 0.005 mL TEMED (see Note 2). 7. Stacking gel buffer: For 1 gel, use 0.24 mL of acrylamide 40%, 0.13 mL of bis-acrylamide 2%, 0.625 Tris–HCl 0.5 M pH 6.8, 0.025 mL of SDS 10%, and 1.45 mL of ddH2O. To promote polymerization, we used 0.025 mL ammonium persulfate (APS) and 0.005 mL of TEMED. 8. SDS-PAGE running buffer: For 1 L, use 14.4 g of glycine, 3 g of Trizma base, and 5 mL of SDS 10% and add ddH2O up to 1000 mL. 9. Transfer buffer: For 1 L use 14.4 g of glycine, 3 g of Trizma base, and 100 mL of methanol and add ddH2O up to the final volume. 10. SDS-PAGE sample loading buffer (4): For 10 mL of solution, use 2.5 mL 1 M Tris–HCl pH 6.8, 1.0 g of SDS, 0.8 mL of 0.1% bromophenol blue, and 4 mL glycerol. Adjust the final volume to 10 mL with ddH2O. To complete the solution, add 10% β-mercaptoethanol immediately prior to use. 11. Ponceau S solution. 12. 0.1% Tween/PBS: For 1 L, add 100 mL of PBS (10) to 1 mL of Tween 20 and dilute with 900 mL of ddH2O. 13. Blocking solution: 5% Low-fat milk (50 mg/mL) and 3% low-fat milk (30 mg/mL) in 0.1% Tween/PBS. 14. Chemiluminescence solution: Dilute 0.5 mL Tris–HCl 1.5 M pH 8.8 with 4.5 mL of ddH2O (solution a), then mix 0.5 mL Tris–HCl 1.5 M pH 8.8 with 50 μL luminol and 22 μL p-coumaric acid, and dilute with 4.5 mL of ddH2O (solution b) (see Note 3). Finally, mix 0.5 mL Tris–HCl 1.5 M pH 8.8 with 3 μL of H2O2 30% and dilute with 4.5 mL of ddH2O (solution C). 2.3 Immunofluorescence

1. Paraformaldehyde (PFA) fixative 4%: For 1 L, add 40 g of paraformaldehyde powder to 1000 mL of preheated (60  C) PBS solution. Using a pipette, add 1 N NaOH dropwise until the solution becomes clear. After that, the solution can be cooled and filtered. Adjust the pH to 7 with 1 N HCl. 2. Sucrose solution: Prepare 30%, 20%, and 10% (w/v) solutions by solubilizing sucrose powder in 1000 mL of PBS 1.

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3. Citrate solution: For 1 L, add 2.941 g of sodium citrate to 1000 mL of ddH2O. Adjust pH to 6 with HCl. Then, add 0.5 mL of Tween 20 (see Note 4). 4. PBS low molarity: For 1 L, add 100 mL of 10 isotonic saline solution (90 g NaCl in 1 L ddH2O) to 50 mL of 2 PO4 buffer (7.7 g NaOH + 29.2 g NaH2PO4 in 1 L of H2O) and dilute to the final volume with ddH2O. 5. 0.3% Triton X-100/PBS: For 100 mL, add 100 mL of PBS low molarity to 0.3 mL of Triton X-100. 6. Blocking solution: Dissolve 0.5% bovine serum albumin in 0.3% Triton X-100/PBS. 7. Aqueous mounting medium with DAPI. 2.4

Antibodies

1. For western blotting analysis use specific antibodies against MOR-1 and against ß-actin to normalize the signal intensity. 2. For immunofluorescence assays: use specific antibodies against MOR-1 and MOR-1 phosphorylated on Ser375. Suitable working dilutions are assayed in preliminary experiments. 3. For western blotting secondary a goat anti-mouse antibody is used diluted with 3% milk in 0.1% Tween/PBS (for 10 mL, dissolve 300 mg of dried skim milk in 10 mL of 0.1% Tween/ PBS). For immunofluorescence assays use anti-rabbit and antigoat fluorescence antibodies.

2.5 Morphine Nociceptive Tolerance

2.6

Other Materials

1. Animals: Male CD1 mice (24–26 g, 4 weeks old) are used. 2. To induce morphine tolerance inject mice s.c. twice daily with morphine hydrochloride solutions at 10:00 AM and 8:00 PM. On day 1 inject 10 mg/kg; on day 2 inject 15 mg/kg; on day 3 inject 20 mg/kg s.c.; and on day 4 inject 30 mg/kg s.c [15]. 1. Hot plate apparatus. 2. Surgical dissection tools. 3. Mini gel tank. 4. Bolt mini blot module. 5. Cryostat. 6. Microscope slides. 7. Fluorescence microscope. 8. Nitrocellulose membrane. 9. Protein ladder. 10. PAP pen for immunostaining.

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Methods

3.1 Morphine Nociceptive Tolerance

1. Male CD1 mice (24–26 g, 4 weeks old) are employed. 2. Induction of morphine tolerance: inject mice s.c. twice daily with morphine hydrochloride solutions at 10:00 AM and 8:00 PM. Administer 10 mg/kg; on day 2 inject 15 mg/kg; on day 3 inject 20 mg/kg; and on day 4 inject 30 mg/kg [15]. 3. Perform the hot plate test to evaluate the development of analgesic tolerance. Place mice inside a hot plate apparatus set at 50.0  0.1  C and 52.50  0.1  C. Express the nociceptive response for thermal sensitivity as latency to licking in seconds. 4. Sacrifice mice by cervical dislocation and remove the spinal cord for in vitro analysis on day 5, 30 min after morphine administration (see Note 5).

3.2 Preparation of Whole-Cell Lysate, Membrane, and Cytosolic Fraction

1. Isolate the lumbar spinal cord and rapidly store at

80  C.

2. Homogenize the frozen samples in lysis buffer with a pestle. Then, freeze ( 80  C) and thaw (room temperature) samples for three times and sonicate each sample on ice for 2 min. Centrifuge the homogenate at 9000  g for 15 min at 4  C to preserve protein content. Collect the supernatant and discard the pellet. 3. Repeat centrifugation of the supernatant again at 100,000  g for 60 min at 4  C. The resulting supernatant contains the cytosol fraction. Resuspend the pellet in the lysis buffer containing 0.2% Triton X-100, sonicate for 5 min, and incubate for 45 min at 4  C. Then centrifuge at 100,000  g for 60 min at 4  C and collect the supernatant, which contains the membrane fraction. The pellet can be discarded. 4. Quantify the total protein concentration using the bicinchoninic acid method (see Note 6).

3.3 Internalization of MOR-1 Assessed by Western Blotting Analysis

1. Running and stacking gel preparation: The two solutions differ in their pH and in the concentration of acrylamide. In particular, the running possesses a pH of 8.8 and more narrow meshes due to the higher presence of acrylamide compared to stacking gel, which is characterized by a pH of 6.8 and a lower percentage of acrylamide. Indeed, the stacking gel is useful to uniform the front of the run while the running gel is responsible for the separation of the proteins in the sample. Add the catalytic converter (TEMED and APS) and fill the space between the two glass slides (which are 0.75 nm apart) with the solutions. Load the running gel first and cover the gel with ddH2O to improve the polymerization without O2. At the end of the polymerization, gently remove water with blotting paper and

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load the stacking gel. Rapidly, insert the 10-well combs, which promote polymerization in the absence of O2. 2. Sample preparation: Thaw the samples and briefly spin them for 5 min. Use 40 μg of protein for each sample (the quantity of each sample depends on the protein concentration obtained with bicinchoninic acid assay). For each sample add 5 μL of SDS-PAGE sample loading buffer (4). Repeat centrifugation for 5 min and boil each sample for 3 min in a wet thermostat in order to denature protein structure belonging to higher order than primary. The maximum sample quantity that we could load was 20 μL. For the cellular localization of MOR-1 receptor use this set of spinal cord samples: membranes obtained from control mice and morphine-treated mice and cytosol from control mice and morphine-treated mice. 3. SDS-PAGE electrophoresis: For this operation use a chamber system for protein electrophoresis. Fill the chamber with SDS-PAGE running buffer and insert the gel-containing glass. Gently load the samples in the appropriate wells and start the course by applying a potential difference of 110 V. The running buffer contains SDS, a strong anionic detergent which confers a negative electric charge to maintain a persistent m/z ratio so that the separation of proteins can be linked only to their molecular weight and not to the electric charge. Stop the course when the blue band of bromophenol blue is located in the lowest part of the gel. 4. Blotting membranes: After gel electrophoresis, transfer the proteins to a solid support membrane. To do this operation it is necessary to assemble, into an accurate support, the so-called sandwich. Starting from the anode, assemble the sandwich following this order: (a) Sponge; (b) filter paper; (c) gel; (d) nitrocellulose membrane; (e) filter paper; and (f) sponge. Apply a voltage of 100 V for 2 h to transfer the proteins from the gel to the membrane. Put the membrane between the gel and the positive electrode so that the proteins possessing a negative electric charge can migrate from the gel to the membrane. Buffer contains methanol, which is necessary to split the linker between proteins and SDS. For the whole duration of the process keep the tank immersed in ice, to prevent the overheating of the instrument. To evaluate if the transfer has been correctly performed, use the Ponceau S solution. The decolorization can be obtained after three washes of 5 min with 0.1% Tween/PBS. 5. Blocking solution step: After the blotting phase, block the unspecific sites by soaking each membrane with 25 mL of blocking solution for 2 h at room temperature on a rocker

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shaker. This step is necessary for blocking unspecific sites which could be wrongly targeted by the antibody. 6. Identification of MOR-1 localization: After the blocking phase, incubate the membrane overnight at 4  C with specific antibody for MOR-1 (1:500 in 5% dried skim milk containing 0.1% Tween/PBS). The day after, remove the antibody solution and wash three times with 0.1% Tween/PBS for 10 min each. With MOR-1 antibody being a mouse monoclonal MOR antibody, a solution of goat anti-mouse antibody in 3% dried skim milk solution can be incubated for 2 h at room temperature. Thereafter, remove the antibody by washing three times with 0.1% Tween/PBS. 7. Chemiluminescence system to detect western blot signals: Add 10 mL of solution “a” to the membrane. A few minutes before the signal capture, add 1 mL of solution “b” and solution “c” for each membrane. The reaction between H2O2, luminol, and coumaric acid produces the emission of an electromagnetic radiation catalyzed by peroxidase (HRP) which is conjugated to the secondary antibody. Food wrap can be used for the detection, as it is cheap and confers an excellent sensitivity. Each film can be used only once for each membrane. For the signal detection we use a GE ImageQuant 350 (GE Life Sciences) instrument. Densitometry analysis using image processing software (such as ImageJ) can be used to determine the quantity of protein present in the western blotting bands. The molecular weight of MOR-1 is 50 kDa: use a protein ladder, which is designed for monitoring protein separation during electrophoresis and for indicating the sizing of proteins, for the identification of the correct band. Using this method, we found that, in morphine-tolerant mice, MOR-1 was expressed mainly in the cytosol compartments compared to membrane fraction, indicating an internalization of this receptor [14]. 3.4 Internalization of MOR-1 Assessed by Immunofluorescence

1. Preparation of the sample for immunofluorescence analysis: Mice were perfused transcardially for 5 min with 4% paraformaldehyde in 0.1 M PBS (1). After perfusion, spinal cords were quickly removed, postfixed for 18 h with the same fixative at 4  C, and transferred sub-sequentially to 10%, 20%, and then 30% sucrose solution for 24 h at each concentration. Store spinal cords at 80  C until cryostat sectioning. Perfusion is a necessary process, which allows to eliminate all the blood from the tissue, and consequently the analysis of the tissue with immunofluorescence techniques, without the problem of the antibody’s signal masking by hemoglobin. Cutting of the spinal cord can be carried out using the cryostat, at the internal temperature of 20  C. Cut spinal cord transverse sections at a thickness of approximately

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15 μm. Obtain five sections for each slide and preserve them in the refrigerator at 20  C. 2. MOR-1 and p-MOR-1 spinal cord localization: Remove the slides with spinal cord sections from the refrigerator and let them stay for 1 h at room temperature. After that, wash slices twice for 5 min with 0.3% Triton X-100/PBS. To break the protein cross-links use the citrate solution, which allows to unmask the antigens and epitopes enhancing staining intensity of antibodies. For this step, preheat citrate buffer to 95–100  C (see Note 6) and soak slides in the flask containing citrate for 20 min. Remove the flask from the hot plate and leave it to cool at room temperature for another 20 min. 3. Wash three times with 0.3% Triton X-100/PBS for 5 min each. Block the sections with blocking solution for 2 h at room temperature. To keep the reagent localized on tissue specimens we use the PAP pen (sigma). Remove the blocking solution and incubate sections with MOR-1 (1:100) and MOR-1 phosphorylated on Ser375 (1:100) in 0.5% bovine serum albumin containing 0.3% Triton X-100/PBS solution at 4  C overnight. 4. Rinse slices three times with 0.3% Triton X-100/PBS for 5 min and incubate the sections with secondary antibody labeled with Invitrogen Alexa Fluor 488 for p-MOR (490–525, 1:400) and Cruz Fluor 594 for MOR-1 (592–614, 1:400; Santa Cruz Biotechnology) for 2 h at room temperature in the dark. Gently wash the tissue three times as described previously. Use DAPI, which is present in the mounting medium, to counterstain nuclei. Allow slides to dry for 1–2 h before storing them at 4  C, protected from light. You can use a Leica digital camera with appropriate excitation and emissions filters for each fluorophore to acquire representative images. Acquire images at 20 and 40 magnification using a digital camera. Immunofluorescence experiments show a selective membrane localization of MOR-1 in the spinal cord dorsal horn of control mice. In mice with repeated morphine treatment an increase of MOR-1 receptors from membrane to the cytosol is indicated with a marked cytosolic immunostaining. To confirm the internalization induced by morphine repeated administration of p-MOR-1 signal in immunostained sections by automatic thresholding images can be quantified using FIJI software (distributed by ImageJ). Measures should be taken with images at 20 magnification in a region of interest in the dorsal horn and with images at 40 magnification on the entire optical section. Measures should be taken in a scale of pixel intensity ranging from 0 to 255. Data can be then analyzed using GraphPad Prism 5.0. From these analyses the increase of p-MOR-1 expression in the spinal cord dorsal horn in the tolerant mice compared to control group can be observed [14].

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Notes 1. One tablet of protease and phosphatase inhibitor cocktail (Roche) was dissolved in 50 mL of lysis buffer. The working solution with inhibitors is stable for 1 month at +2–8  C. To preserve the protease and phosphatase inhibitor efficiency, in our lab we add the inhibitor cocktail to the lysis buffer immediately before use. 2. TEMED and APS should be added simultaneously to the solution immediately before the loading on the solid support both in running and stacking gel. 3. For luminol solution, dissolve 0.3 g of luminol (Sigma) in 7.5 mL of DMSO and for p-coumaric acid dissolve 0.022 g of p-coumaric acid (Sigma) in 1 mL of DMSO. These solutions can be stored at 20  C for up to 12 months. 4. This solution can be stored at +2–8  C for up to 12 months. 5. Protein concentration can be quantified using different methods. In our lab we routinely use the bicinchoninic acid (BCA) and Bradford assays. Each method possesses its own advantages and disadvantages and for this reason they can be individually chosen on the basis of the operator experience. 6. Citrate solution may need some time to reach the temperature of 95–100  C. Thus, it is recommended to start with a hot plate temperature of 250–300  C for 30 min and control the temperature of citrate solution with a thermometer. When citrate solution reaches 90  C turn down the hot plate temperature gradually.

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6. Koch T, Ho¨llt V (2008) Role of receptor internalization in opioid tolerance and dependence. Pharmacol Ther 117:199–206 7. Arttamangkul S, Heinz DA, Bunzow JR et al (2018) Cellular tolerance at the μ-opioid receptor is phosphorylation dependent. Elife 7:1–18 8. El Kouhen R, Burd AL, Erickson-Herbrandson LJ et al (2001) Phosphorylation of Ser363, Thr370, and Ser 375 residues within the carboxyl tail differentially regulates μ-opioid receptor internalization. J Biol Chem 276:12,774–12,780 9. Schulz S, Mayer D, Pfeiffer M et al (2004) Morphine induces terminal μ-opioid receptor desensitization by sustained phosphorylation of serine-375. EMBO J 23:3282–3289 10. Beaulieu JM (2005) Morphine-induced μ-opioid receptor internalization: a paradox

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solved in neurons. J Neurosci 25:10,061–10,063 11. Dang VC, Christie MJ (2012) Mechanisms of rapid opioid receptor desensitization, resensitization and tolerance in brain neurons. Br J Pharmacol 165:1704–1716 12. Manabe S, Miyano K, Fujii Y et al (2019) Possible biased analgesic of hydromorphone through the G protein-over b-arrestinmediated pathway: cAMP, CellKey™, and receptor internalization analyses. J Pharmacol Sci 140:171–177

13. Gurevich EV, Gurevich VV (2014) Arrestins— pharmacology and therapeutic potential. Handbook of Experimental Pharmacology. Springer, New York, pp 427–443 14. Sanna MD, Borgonetti V, Galeotti N (2020) μ-Opioid receptor-triggered notch-1 activation contributes to morphine tolerance: role of neuron—glia communication. Mol Neurobiol 57:331–345 15. Galeotti N, Farzad M, Bianchi E, Ghelardini C (2014) PKC-mediated potentiation of morphine analgesia by St. John’s wort in rodents and humans. J Pharmacol Sci 124:409–417

Chapter 10 GTPγS-Autoradiography for Studies of Opioid Receptor Functionality Alfhild Gro¨nbladh and Mathias Hallberg Abstract The opioid receptors have been an interesting target for the drug industry for decades. These receptors were pharmacologically characterized in the 1970s and several drugs and peptides have emerged over the years. In 2012, the crystal structures were also demonstrated, with new data on the receptor sites, and thus new possibilities will appear. The role of opioids in the brain has attracted considerable interest in several diseases, especially pain and drug dependence. The opioid receptors are G-protein-coupled receptors (GPCR) that are Gi coupled which make them suitable for studying the receptor functionality. The [35S] GTPγS autoradiography assay is a good option that has the benefit of generating both anatomical and functional data in the area of interest. It is based on the first step of the signaling mechanism of GPCRs. When a ligand binds to the receptor GTP will replace GDP on the a-subunit of the G-protein, leading to a dissociation of the βγ-subunit. These subunits will start a cascade of second messengers and subsequently a physiological response. Key words Brain, Functional autoradiography, G-proteins, GTPgammaS, Opioid receptors

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Introduction The marketed drugs in the world today focus on over 100 different targets. Most of these are enzymes and receptors, whereas the Gprotein-coupled receptors (GPCR) seem to be the largest and predominating target family. Approximately 800 human GPCRs have been verified and reported [1]. Five main families of human GPCRs have been reported. These are termed adhesion, frizzled/ Taste2, glutamate, rhodopsin, and secretin [2]. A majority of these are not fully characterized. Interestingly, today many of the newly discovered GPCRs lack natural ligands. The phenomenon of receptors based on DNA sequences without known ligands have been referred to as a deorphanization [3]. The last years GPCRs have been particularly highlighted through the Nobel Prize in Chemistry in 2012 since Robert J. Lefkowitz and Brian K. Kobilka shared the prize for their work on GPCRs. Furthermore, with regard to

Santi M. Spampinato (ed.), Opioid Receptors: Methods and Protocols, Methods in Molecular Biology, vol. 2201, https://doi.org/10.1007/978-1-0716-0884-5_10, © Springer Science+Business Media, LLC, part of Springer Nature 2021

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opioids, in the same year the first crystal structures of the mu, delta, and kappa receptors binding to various ligands were disclosed [4– 6]. For the mu opioid receptor, the binding sites were reported to be wider and larger than previously estimated. Thus, these data bring more understanding to how alkaloids such as morphine and large peptides such as b-endorphin can bind and activate the same receptor. The opioid receptors that were cloned during the 1990s [7–10] are GPCRs that originally were classified based on their pharmacological profile as well as tissue distribution. The opioid receptors are divided into three different subclasses: the mu, delta, and kappa opioid receptors. These receptor subclasses all contain seven transmembrane helixes and one of the intracellular loops interact with G-proteins. There are four different subclasses of G-proteins, Gs, Go, Gq, and Gi. Overall, different receptors bind to specific G-proteins. The focus of this protocol is however on the opioid receptors which are all Gi coupled. Opioid peptides as well as opioid receptors are involved in the processing of pain and also in several behavioral processes such as dependence, reward, stress, and sedation. To understand the roles of the opioid system it is important to study new ligands, functionality, as well as distribution of receptors. Nevertheless, when developing new ligands or studying a certain receptor system it is important to have a reliable functional assay. In the case of GPCR signaling the first step is mediated through G-proteins. These are well characterized and can be studied through assays. The GTPγS binding assay is a suitable technique for determining whether in particular Gi-coupled receptors are activated by different potential agonists. The [35S]GTPγS binding assay was first described in the 1980s for b-adrenergic and muscarinic receptors [11, 12]. The technique was later also shown to be useful in order to map the anatomical distributions of receptors, including the mu opioid receptor [13, 14]. Comprehensive reviews of the development of the [35S]GTPγS binding assay as well as applications have been published over the years [15–18]. The GTPγS assay measures the increase in the guanine nucleotide exchange in the heterotrimeric G-protein. Briefly, in the absence of ligand the receptor will be inactive and the a-units of the G-proteins will be bound to guanosine diphosphate (GDP). When the receptor is ligand activated, guanosine triphosphate (GTP) will replace the GDP, which will cause the GTP-bound a-subunit to dissociate from the bg-subunit; see Fig. 1. These subunits will later trigger new targets and thus activate the second messenger system. By replacing the GTP with the non-hydrolyzable [35S]GTPγS and by administering high concentrations of GDP in the assay a ligand-activated response can be measured.

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Fig. 1 Binding of the agonist to the active receptor site generates an exchange of GDP for GTP and subsequently an activation of the second messenger system. (1) An agonist binding to the receptor; (2) guanosine triphosphate (GTP) will replace the GDP; (3) the GTP-bound a-subunit dissociates from the bg-subunit and activates a target protein. These subunits will later trigger new targets and thus activate the second messenger system; (4) the GDP/a-subunit will “return” to a receptor. The GTPγS assay utilize non-hydrolyzable [35S]GTPγS instead of GTP in order to measure the activity

This chapter describes GTPγS binding assay. We aim to highlight crucial factors with regard to the GTPγS binding assay and will have a focus on the brain of rodents. We retain that the GTPγS binding assay or GTPγS autoradiography is a well-functioning and reliable assay. The technique is straightforward and suitable for the Gi-coupled opioid receptors.

2 2.1

Materials Coating of Slides

2.1.1 Preparation of a Gelatin Buffer Containing 0.5% Gelatin and 0.05% KCr(SO4)2

2.1.2 Cryostat/Sectioning

1. Add the gelatin to q.s. 100% water and heat to approximately 60
C. Dissolve the 0.05% KCr(SO4)2 in a separate beaker. 2. Mix the two solutions when the gelatin solution is ready and has started to cool down. 3. Dip the slides when the solution has reached room temperature and dry under a fan before storage in their original cartons at 20
C until use (see Note 4). The sectioning is done with a cryostat at 20
C. In comparison with ordinary autoradiography where brain slices between 10 and 14 μm are usually used the GTPγS slices are thicker. In most research groups 20 μm is selected for the GTPS assay. This is sufficient to receive a quality picture of the receptor functionality and still enough slices to get a reasonable number of autoradiograms from each region (see Notes 2 and 6–9).

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Fig. 2 Representative autoradiograms from rat brain (coronal sections, bregma 1.60 mm) displaying the (a) basal binding, (b) DAMGO-stimulated [35S]GTPγS, and (c) unspecific binding, i.e., basal binding in the presence of cold GTP

Mount the slices on the gelatin-coated slides. For a rat brain (with coronal slicing) we usually mount 3–4 slices per slide but this of course differs depending on species, aim of the autoradiography, or use of sagittal or coronal frozen sections (an example of coronal slices is shown in Fig. 2). Dry the glass slides completely before storing at 80
C (see Note 3). Drying of the slides overnight is commonly preferred. 2.1.3 Assay Buffer

Prepare the assay buffer: 50 mM Tris–HCl, 4 mM MgCl2, 0.3 mM EGTA, and 100 mM NaCl (pH 7.4) at room temperature.

2.1.4 Washing Buffer

Prepare the washing buffer: 50 mM Tris–HCl (pH 7.4 at 4
C) (see Note 15).

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Methods Carry out all procedures at room temperature unless otherwise specified.

3.1 Preparation of Brain (Tissue)

3.2 GTPγS Incubations

After sacrifice (usually by decapitation) of the animals the whole brains (tissue) are rapidly removed. The brains, or tissue, are fresh frozen in isopentane (35
C  5
C) for 30 s (see Note 1). After being frozen the tissue is stored at 80
C until further use. 1. Incubate the slides in the assay buffer for 10 min at room temperature. 2. Move the slides into a humid chamber and incubate the slides in the assay buffer containing 10 mU/mL adenosine deaminase (ADA) and 2 mM GDP in room temperature for 15 min (see Note 12). 3. Add 0.04 nM [35S]GTPγS to the assay buffer (containing 10 mU/mL ADA and 2 mM GDP) and stimulate the receptors with the ligands of choice (for example DAMGO, DPDPE, and

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CI-977) for the respective subtypes. Incubate for 2 h in 25
C (see Notes 10, 11, and 13–17). 4. Wash the slides with ice-cold 50 mM Tris–HCl, pH 7.4, for 2 min. Repeat the step. 5. Wash the slides with distilled water for 30 s. 6. Dry the slides with a fan until they are completely dry. 7. In order to confirm the selectivity of the stimulation an antagonist (for example naloxone (1 μM)) should be added on the subsequent slides. 8. Under the same conditions as described above, the basal levels are determined in the absence of agonist. The nonspecific binding is determined by incubating the sections in the presence of unlabeled GTPγS. All procedures and incubation steps should be as described above. 3.3 Film or Phosphor Imaging

After being dried overnight, the sections are exposed to film together with the standards (microscales) for 2–3 days, or longer depending on the ligand. In our laboratory we recently used the Kodak BioMax MR-1 film. The films are developed either manually or using a film processor, for example the Konica medical film processor SRX-101A (Konica Europe GmbH, Hohenbrunn, Germany) (Gronbladh et al., 2013).

3.4

The slides are digitalized (for example using an Epson Perfection 4870 photo scanner) and analyzed using a program suitable for determining the receptor functionality. An example of representative figures is demonstrated in Fig. 2. In our lab and others we use the ImageJ (National Institutes of Health, Bethesda, MD, USA) image processing software [19–21]. The optical densities can be converted to nCi/g using a standard curve calculated from the [14C]-microscales, previous described by Sim et al. (1997) [20].

4

Analysis of Data

Notes 1. When lowering the dissected brain into the isopentane (35
C) be careful not to drop it since the brain will be deformed just before freezing. 2. The frozen brains or tissues can be stored in different ways. The brains or tissues can either be wrapped in cold foil, placed in small plastic bags and put on dry ice, or placed in a plastic container with 2–3 mL of isopentane (