Nanosensors for Point-of-Care Diagnostics of Pathogenic Bacteria 9819912172, 9789819912179

Table of contents :
Preface
Contents
Editors and Contributors
1: The Surface Biomarkers Present on the Bacterial Cell Surface
1.1 Introduction
1.2 Characteristics of Biomarkers
1.3 Biomarkers Present on Bacterial Surfaces
1.4 Conclusion
References
2: Optical Nanosensors and Their Integrated Approaches for the Detection of Pathogens
2.1 Introduction
2.2 Optical Techniques for Detection of Pathogenic Bacteria
2.2.1 Fluorescent Biosensors
2.2.2 Colorimetric Biosensors
2.2.3 SERS Biosensors
2.2.4 SPR Biosensors
2.3 Integrated Optical Biosensors
2.3.1 Microfluidics-Based Detection
2.3.2 Smartphone-Based Biosensors
2.3.3 Paper-Based Biosensors
2.4 Conclusion
References
3: Surface Plasmon Resonance (SPR)-Based Nanosensors for the Detection of Pathogenic Bacteria
3.1 Introduction
3.1.1 Prism-Based Surface Plasmon Resonance Sensors
3.1.2 Optical Fibre-Based Surface Plasmon Resonance Sensors
3.2 SPR-Based Analysis of Bacteria
3.2.1 E. coli
3.2.2 Tuberculosis
3.2.3 S. Typhimurium
3.2.4 Miscellaneous
3.3 Conclusion and Future Outlooks
References
4: Enzyme-Linked Immunosorbent Assay-Based Nanosensors for the Detection of Pathogenic Bacteria
4.1 Introduction
4.2 Evolution of ELISA
4.3 Pros and Cons of ELISA
4.4 Improvement in ELISA Using Nanomaterials
4.5 ELISA-Based Nanosensors for Detection of Pathogenic Bacteria
4.5.1 Electrochemical ELISA-Based Nanosensors
4.5.2 Optical ELISA-Based Nanosensors
4.6 Integration of Microfluidics with ELISA-Based Nanosensor
4.7 Challenges and Concluding Remarks
References
5: Nanosensor-Enabled Microfluidic Biosensors for the Detection of Pathogenic Bacteria
5.1 Introduction
5.2 Development of a Microfluidic Chip Nanosensor
5.2.1 Selection of Biomolecular Recognition Element
5.2.2 Selection of Microfluidic Chip Material
5.2.3 Selection of Nanomaterial (NM)
5.2.4 Selection of Detection Technique
5.3 Microfluidic Chip Nanosensors for Detecting Pathogenic Bacteria
5.3.1 Electrochemical Microfluidic Chip Nanosensors
5.3.2 Optical Microfluidic Chip Nanosensors
5.4 Conclusions
References
6: Electrochemical/Voltammetric/Amperometric Nanosensors for the Detection of Pathogenic Bacteria
6.1 Introduction
6.2 Electrochemical Nanosensors
6.3 Electrochemical Technique for Detection of Pathogenic Bacteria
6.3.1 Amperometric Detection of Pathogenic Bacteria
6.3.2 Potentiometric Detection of Pathogenic Bacteria
6.3.3 Voltammetry Detection of Pathogenic Bacteria
6.3.4 Impedance Detection of Pathogenic Bacteria
6.4 Nanomaterials Used in the Development of Nanosensors
6.4.1 Carbon-Based Nanotubes
6.4.2 Nanoparticles (NPs)
6.4.3 Graphene
6.4.4 Other Nanomaterials
6.5 Conclusions and Perspective
References
7: Quartz Crystal Microbalance (QCM)-Based Nanosensors for the Detection of Pathogenic Bacteria
7.1 Introduction
7.2 Quartz: A Piezoelectric Resonator
7.3 Nanoparticles in Quartz Crystal Microbalance
7.4 QCM as a Biosensor
7.5 Receptors for Target Recognition
7.5.1 Antigen and Antibody
7.5.2 Probes Containing Genetic Material
7.5.3 Nucleic Acid Probes
7.5.4 Molecularly Imprinted Polymers
7.6 Detection of Pathogenic Bacterial Spores
7.7 Detection of Campylobacter jejuni
7.8 Detection of Salmonella typhimurium
7.9 Detection of Listeria monocytogenes
7.10 Detection of E. coli
7.11 Conclusion
7.12 Limitations and Future Perspectives
References
8: Surface-Enhanced Raman Spectroscopy (SERS)-Based Nanosensor for the Detection of Pathogenic Bacteria
8.1 Introduction
8.2 Surface-Enhanced Raman Spectroscopy (SERS)
8.3 Principle Involved in the Detection of Bacteria Using SERS
8.3.1 Labelled Bacterial Detection
8.3.2 Label-Free Bacterial Detection
8.3.3 Hybrid-SERS Sensor
8.4 Conclusion and Future Prospects
References

Citation preview

Amitabha Acharya Nitin Kumar Singhal   Editors

Nanosensors for Point-ofCare Diagnostics of Pathogenic Bacteria

Nanosensors for Point-of-Care Diagnostics of Pathogenic Bacteria

Amitabha Acharya • Nitin Kumar Singhal Editors

Nanosensors for Point-of-Care Diagnostics of Pathogenic Bacteria

Editors Amitabha Acharya Nitin Kumar Singhal Nanobiology Lab, Biotechnology Division National Agri-Food Biotechnology Institute CSIR-Institute of Himalayan Bioresource Mohali, Punjab, India Technology Palampur, Himachal Pradesh, India

ISBN 978-981-99-1218-6 ISBN 978-981-99-1217-9 https://doi.org/10.1007/978-981-99-1218-6

(eBook)

# The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Preface

Over the centuries, global pandemics of infectious diseases, such as cholera, smallpox, influenza, and, lately Covid-19 have severely impacted the world’s health and economy. Even after the promising development in science and technology, prevention and treatment of infectious diseases are still major healthcare problems. Pathogens, such as bacteria, viruses, fungi, and protozoa, are mainly responsible for infectious diseases. These express different surface markers, lipoproteins, receptors, lipids, glycoproteins, glycopeptides, carbohydrates, etc. Identifying these biomarkers is crucial in pathogen detection/identification, its control and, inhibition. Despite advancements in pathogen identification, the standard conventional diagnostic methods still have limitations related to their specificity and sensitivity. So, in this context, researchers have utilized versatile nanostructure modalities for effective sensing, diagnosis, and prognosis of various infectious diseases. The book aims to provide comprehensive information related to bacterial detection strategies. The book is divided into eight chapters giving a recent outlook on the problem. The first chapter deals with the surface biomarkers on the bacterial cell surface. Pathogenic bacteria utilize several mechanisms to cause disease in human hosts. Bacterial pathogens express a wide range of molecules that bind host cell targets to facilitate various host responses. The molecular strategies bacteria use to interact with the host can be unique to specific pathogens or conserved across several species. Like all cells, bacteria have receptor sites on their cell surfaces, which allow them to bond with molecules and receive signals from outside cells. Sometimes, receptor sites are utilized by viruses, like these bacteriophages, to infect and harm the bacteria. This chapter has discussed common receptors on bacterial cell surfaces that can be targeted for diagnostic applications. In the second chapter, optical nanosensors and their integrated approaches for the detection of pathogens have been covered. There is a need for accurate techniques for pathogenic bacteria identification and detection to prevent and manage pathogenic diseases and assure food safety. In this chapter, examples of different fluorescent nanoparticle system which are being used for bacterial detection has been included. In the third chapter, Surface Plasmon Resonance (SPR)-based nanosensors have been discussed. Many nanoparticles (NPs) have been used for biological applications due to their characteristics such as the Surface Plasmon band localization in the visible spectrum. This chapter has covered examples of SPR nanosensors for sensitive and selective v

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Preface

detection of bacterial pathogens. The fourth chapter details the examples of EnzymeLinked Immunosorbent Assay (ELISA)-based nanosensors for detecting pathogenic bacteria. This chapter aims to present a comprehensive review that exposes how biosensors work in terms of bacterial detection via ELISA-based techniques. In the fifth chapter, nanosensors-enabled microfluidic biosensors have been discussed. The advent of lab-on-a-chip microfluidic technology has revolutionized clinical analysis, medical research, and diagnostics fields. Due to several inherent characteristics of microfluidic technologies, such as portability, less patient sample requirements, miniaturization, minimizing user intervention, cost-effectiveness, enhanced sensitivity and specificity, and higher throughput, these have been recently used a potent platform for multiple medical applications, including clinical microbiology. This chapter has included reports of different nanosensors used for the microfluidic-based detection of bacterial pathogens. The sixth chapter discuseed examples of different electrochemical/voltammetric or amperometric nanosensors. Electrochemical sensors are well-accepted powerful tools for detecting disease-related biomarkers and environmental and organic hazards. These have also found widespread interest in the last years for detecting waterborne and foodborne pathogens due to their labelfree character and high sensitivity. In Chap. 7, Quartz Crystal Microbalance (QCM)based nanosensors were discussed. QCM sensors are classified as piezoelectric sensors. The potential of piezoelectric immunosensors combined with specific antigen-antibody or receptor–ligand interactions are rapidly increasing as these have high sensitivity and specificity. The final chapter (Chap. 8), covers Surface Enhanced Raman Spectroscopy (SERS)-based nanosensors. SERS-based techniques could be the most reliable for routine analysis due to their excellent sensitivity, simple and low-cost instrumentation, and minimal required sample preparations. The higher sensitivity of SERS is obtained due to the very minute nanostructure, which must be put in place before and at the time of the analysis. Overall, this book will describe the bacterial cell surface biomarkers, which can be targeted for different diagnostic approaches including Point-of-Care Tests (POCT) of bacterial diseases. The book chapters are designed to promote many new diagnostic modalities, including establishing the importance of designing the futuristic nanomaterials for POCT applications. The book will unleash various nanodiagnostic techniques developed to detect, capture, and image bacteria through surface marker recognition. Palampur, India Mohali, India

Amitabha Acharya Nitin Kumar Singhal

Contents

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The Surface Biomarkers Present on the Bacterial Cell Surface . . . . . Alka Kumari, Sumeeta Kumari, and P. Anil Kumar

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Optical Nanosensors and Their Integrated Approaches for the Detection of Pathogens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sonam Kumari, Neeraj Dilbaghi, Ganga Ram Chaudhary, and Sandeep Kumar

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Surface Plasmon Resonance (SPR)-Based Nanosensors for the Detection of Pathogenic Bacteria . . . . . . . . . . . . . . . . . . . . . . Priyanka Thawany, Umesh K. Tiwari, and Akash Deep

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Enzyme-Linked Immunosorbent Assay-Based Nanosensors for the Detection of Pathogenic Bacteria . . . . . . . . . . . . . . . . . . . . . . Tanu Bhardwaj and Tarun Kumar Sharma

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Nanosensor-Enabled Microfluidic Biosensors for the Detection of Pathogenic Bacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tanu Bhardwaj and Tarun Kumar Sharma

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Electrochemical/Voltammetric/Amperometric Nanosensors for the Detection of Pathogenic Bacteria . . . . . . . . . . . . . . . . . . . . . . 113 Mofieed Ahmed and Rajan Patel

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Quartz Crystal Microbalance (QCM)-Based Nanosensors for the Detection of Pathogenic Bacteria . . . . . . . . . . . . . . . . . . . . . . 143 Nitesh Priyadarshi and Nitin Kumar Singhal

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Surface-Enhanced Raman Spectroscopy (SERS)-Based Nanosensor for the Detection of Pathogenic Bacteria . . . . . . . . . . . . 169 Vijay M. and Jugun Prakash Chinta

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Editors and Contributors

About the Editors Amitabha Acharya is working as a Principal Scientist at the Nanobiology Laboratory, Biotechnology Division, CSIR-IHBT, Palampur. He completed his PhD from the Department of Chemistry, IIT Bombay, under the supervision of Prof. CP Rao after obtaining his Master’s degree from BHU, India. At CSIR-IHBT, his group uses the nanotechnological platform for specific biomedical applications. The multidisciplinary group focused on developing anti-amyloidogenic and fibril destabilization nanomaterials and anti-bacterial/anti-biofilm nanomaterials. His group is also involved in designing novel nanozyme as point-of-care (PoC) diagnostics for biosensing and immunoassay applications specifically focusing on bacterial diseases. He has published over 40 articles in peer-reviewed international journals. He also has four patents to his credit. He has contributed to a monograph with Springer and authored more than four book chapters. He has served as a reviewer for several international journals and projects, and is a life member of several scientific societies and organizations. Nitin Kumar Singhal is a highly accomplished scientist with a strong background in Bio-Inorganic Chemistry. He received his MSc from the Indian Institute of Technology (IIT) Roorkee and his Ph.D from IIT Bombay, where he focused on the study of the synthesis of glycoconjugates and their interaction with lectin protein. After completing his Ph.D, Nitin conducted his postdoctoral research at Seoul National University in South Korea. After his postdoctoral studies, Dr. Nitin joined as a scientist at the National Agri-Food Biotechnology Institute in Mohali, India. Nitin has published more than 70 research papers in top-tier scientific journals, and his peers have widely recognized his work. Dr. Nitin received a Fulbright fellowship in 2018 and participated in the program to conduct cutting edge research. Nitin was also selected as an INSA member in the year 2021. He is known for his deep

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understanding of his field, innovative problem-solving approach, and dedication to his students.

Contributors Mofieed Ahmed Department of Biosciences, Jamia Millia Islamia, New Delhi, India Biophysical Chemistry Laboratory, Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India Tanu Bhardwaj Department of Medical Biotechnology, Gujarat Biotechnology University, Gujarat International Finance and Tec (GIFT) City, Gandhinagar, Gujarat, India Ganga Ram Chaudhary Department of Chemistry & Centre of Advanced Studies in Chemistry, Panjab University, Chandigarh, India Jugun Prakash Chinta Department of Chemistry, National Institute of Technology, Warangal, Telangana, India Akash Deep Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India CSIR-Central Scientific Instruments Organization (CSIR-CSIO), Sector 30C, Chandigarh, India Energy and Environment Unit, Institute of Nanoscience and Technology, Punjab, SAS Nagar, India Neeraj Dilbaghi Department of Bio and Nano Technology, Guru Jambheshwar University of Science and Technology, Hisar, Haryana, India Alka Kumari Microbial Type Culture Collection & Gene Bank (MTCC), CSIRInstitute of Microbial Technology, Chandigarh, India Sonam Kumari Department of Chemistry & Centre of Advanced Studies in Chemistry, Panjab University, Chandigarh, India Department of Bio and Nano Technology, Guru Jambheshwar University of Science and Technology, Hisar, Haryana, India Sumeeta Kumari Microbial Type Culture Collection & Gene Bank (MTCC), CSIR-Institute of Microbial Technology, Chandigarh, India P. Anil Kumar Microbial Type Culture Collection & Gene Bank (MTCC), CSIRInstitute of Microbial Technology, Chandigarh, India Sandeep Kumar Department of Bio and Nano Technology, Guru Jambheshwar University of Science and Technology, Hisar, Haryana, India Physics Department, Punjab Engineering College (Deemed to be University), Chandigarh, India

Editors and Contributors

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Rajan Patel Biophysical Chemistry Laboratory, Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India Nitesh Priyadarshi National Agri-Food Biotechnology Institute (NABI), Sector-81, S.A.S. Nagar, Mohali, Punjab, India Tarun Kumar Sharma Department of Medical Biotechnology, Gujarat Biotechnology University, Gujarat International Finance and Tec (GIFT) City, Gandhinagar, Gujarat, India Nitin Kumar Singhal National Agri-Food Biotechnology Institute (NABI), Sector-81, S.A.S. Nagar, Mohali, Punjab, India Priyanka Thawany Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India CSIR-Central Scientific Instruments Organization (CSIR-CSIO), Sector 30C, Chandigarh, India Umesh K. Tiwari Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India CSIR-Central Scientific Instruments Organization (CSIR-CSIO), Sector 30C, Chandigarh, India Vijay M. Department of Chemistry, National Institute of Technology, Warangal, Telangana, India

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The Surface Biomarkers Present on the Bacterial Cell Surface Alka Kumari, Sumeeta Kumari, and P. Anil Kumar

Abstract

Bacterial surface molecules such as flagella, polysaccharides, proteins like C-terminal anchored proteins, surface glycolytic enzymes, and lipoproteins aid the organism’s survival in hostile environments and can also be used as a biomarker for diagnosing infectious diseases caused by pathogens. Thus, recognition of molecular biomarkers found on bacterial cell surfaces becomes fundamental in disease recognition and further treatment. Therefore, an appropriate microbe-specific biomarker corresponding to the disease (microbial biomarker) or different types of biomarkers existing at detectable levels at various stages of the disease are crucial for the successful treatment of many infectious diseases. Biosensors have become critical components of point-of-care devices in recent years because they are directly responsible for the bioanalytical performance and are required for personalised healthcare management due to their ability to estimate the levels of biological markers. In addition, the early detection of a pathogen or a secreted microbial biomarker helps in limiting the damage caused by the pathogen or the host immune response. This chapter’s aim is to highlight the importance of these surface markers as diagnostic tools for diseases caused by various pathogenic bacteria. Keywords

Biomarker · Lipoproteins · Point of care · Infectious diseases

Alka Kumari and Sumeeta Kumari contributed equally with all other contributors. A. Kumari · S. Kumari · P. A. Kumar (✉) Microbial Type Culture Collection & Gene Bank (MTCC), CSIR-Institute of Microbial Technology, Chandigarh, India e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Acharya, N. K. Singhal (eds.), Nanosensors for Point-of-Care Diagnostics of Pathogenic Bacteria, https://doi.org/10.1007/978-981-99-1218-6_1

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1.1

A. Kumari et al.

Introduction

Several types of medical biomarkers occur at the surface of human cells as well as infectious pathogens such as viruses, bacteria, fungi, or parasites. Cell surfaces determine how a cell or pathogen can interact with its environment and are crucial for sending and receiving chemical signals; transporting metabolites, ions, and larger molecules; and attaching to neighbouring cells and the extracellular matrix. The surface of microbes is an intriguing interface that can act in various ways. There are many types of surface biomolecules found in bacteria, from complex structures such as flagella that propel the organism in aqueous media to polysaccharides, proteins like C-terminal anchored proteins, surface glycolytic enzymes, lipoproteins, and less sophisticated protein (Fischetti 2019). These surface biomolecules are important in elucidating the promising vaccine target and the molecular basis of pathogenicity and virulence, as biomarkers for diagnosis of disease, and in the detection of the pathogen during the early stages of infections to select the appropriate antibiotic for treatment (Wang et al. 2015; Pflughoeft et al. 2019). A biomarker is a measurable diagnostic indicator for assessing the risk or presence of a disease that is designed to describe as an indicator of normal biological processes, pathogenic processes, pharmacologic responses to therapeutic intervention, or any other measurable biological process (Sanjay et al. 2015). Effective treatment at an early stage is essential to limit the damage caused directly by the pathogen and by the host’s immune response (Pflughoeft et al. 2019). In addition, the unnecessary use of antibiotics when disease outbreaks occur could lead to widespread antibiotic resistance. Globally, excessive antibiotic usage is a major problem, particularly in developing countries where many antibiotics are available over the counter (Qureshi and Niazi 2020). Even treatable infectious diseases represent a significant hazard to patients in developing nations due to the high cost of diagnosis (Yager et al. 2008). According to a World Health Organization (WHO) global study on the effect of poverty on infectious illness (2012), infectious diseases kill 3.5 million people each year, predominantly the poor and young children in low- and middle-income nations (WHO 2012). Over 95% of infectious illness mortality are caused by a lack of competent diagnosis and treatment and adequate healthcare infrastructure (Yager et al. 2008). Various alternative methods are needed to identify the type of infection, for example, detecting an elevated blood level of bacterial- or viral-induced antibodies, specific biomarkers, or specific nucleic acid sequences (Qureshi and Niazi 2020). Clinical microbiology laboratories use existing methods to perform various bacterial identification tests for the diagnosis and treatment of infectious illnesses, such as culture-based techniques (Gram staining, chromogenic screening, disk diffusion method, agar dilution method, broth microdilution, etc.) and automated techniques (DNA microarray, DNA chip, loop-mediated isothermal amplification (LAMP), polymerase chain reaction (PCR), enzyme-linked immunosorbent assay (ELISA), matrix-associated laser desorption/ionisation time-of-flight mass spectroscopy (MALDI-TOF MS), etc.). However, culture-based techniques are very timeconsuming, and automated techniques are not cost-effective and require specialised

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The Surface Biomarkers Present on the Bacterial Cell Surface

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training (Landa et al. 2021). Hence, novel, simple, and cost-effective diagnostic technologies are urgently needed in order to assist healthcare professionals in making more convenient point-of-care (PoC) clinical decisions so that infectious viral and bacterial diseases can be detected earlier and thus prevented, secured, and treated in a timely manner (Qureshi and Niazi 2020). The WHO has provided recommendations for selecting a diagnostic test that meets the ASSURED (costeffective, sensitive, precise, user-friendly, reliable and quick, equipment-free, deliverable) benchmark criteria, which can aid in faster diagnosis, better healthcare, and lower waiting times and costs for results dissemination (Kosack et al. 2017).

1.2

Characteristics of Biomarkers

Biological responses to chemical exposure are influenced by genetic and environmental factors, as well as the properties and forms of the substance being exposed and the circumstances of its contact. There may be no effect, some adverse effects with recovery, or toxicity and morbidity. Biomarkers have been categorised by Perera and Weinstein (2000) based on the sequence of events that lead to disease (Perera and Weinstein 2000). It is more precise and sensitive to measure exposure to risk factors when biomarkers are used. Biomarker identification necessitates a determination of their relevance and validity. Relevance refers to a biomarker’s capability to provide relevant information to the public, healthcare providers, or health policy officials on a clinical questionnaire. A biomarker’s usefulness or effectiveness must be determined in order to determine its validity. A general classification of biomarkers is useful in understanding how to approach their role in determining the morpho-functional status of an organism. In general, biomarkers can be divided into three groups based on the following criteria: effect, exposure, and susceptibility: Biomarkers of effect—an organism’s biochemical, physiological, behavioural, or other alterations can be recognised depending on their magnitude as potential biomarkers of disease or health impairment. Biomarkers of exposure—exogenous chemicals or their metabolites or the outcome of an interaction between a xenobiotic agent and a target molecule or cell that is detected in a compartment within an organism. Biomarkers of susceptibility—indicators of an organism’s inherent or acquired capacity to respond to a certain xenobiotic substance’s challenge. A molecule must be linked to some event, such as the diagnosis of a particular disease, progression, or survival for a specific patient, in order to be classed as a biomarker. While not all biomarkers are equally useful, the majority of them do contribute to the knowledge that has already been acquired from clinical and pathological studies (Verma 2005; Madu and Lu 2010). A variety of biomarker applications have been developed (Hardin et al. 2011). It’s vital for biomarkers to be able to detect and evaluate the progression of disease.

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Ideal Biomarker •The ability to distinguish healthy individuals from patients •Expression should occur early in the progression of the disease •Easy to assay, less expensive •Give reproducible results and multiplexing is possible for screening purposes Factors that impact Sensitivity and Specificity •Sample type (biofluid vs. tissue) •The stability of the sample and the time needed for assaying the biomarker •Negative controls must be used properly. •Background profiling

Fig. 1.1 A description of ideal biomarkers and factors affecting their sensitivity and specificity Table 1.1 Biomarker’s ideal characteristics Characteristic Sensitivity Specificity Detectable Translatable Non-invasive Repeatable Diagnostic

Description The biomarker must be sensitive and should not produce false positives in the early detection of diseases/injuries A biomarker should provide information about the status of a specific organ or disease Measurement of biomarkers in the clinic should be simple and quick without requiring any specialised equipment In order for a biomarker to aid in the development of new drugs, it should be applicable to humans and pre-clinical species In order to access the biomarker, it must be present within biofluids It is imperative that the biomarker assay is robust and that the results are reproducible between laboratories Ideally, biomarkers should be easy to use, enabling clinicians to design treatment strategies based on their interpretation

Biomarkers can also be used to predict treatment outcomes and other clinical interventions. Biomarkers are also used in other areas, such as risk assessment, diagnosis, and medication development. A biomarker’s ideal characteristics include the following shown in Fig. 1.1 (Verma et al. 2011). There must be both biological and bioanalytic sensitivity, specificity for tissue or organ, and ease of accessibility for a biomarker to serve as a clinical biomarker. In addition, a prognostic marker would direct inpatient management and help the physician provide the appropriate treatment. There are both static and dynamic characteristics in every biomarker. A biomarker’s ideal characteristics has been illustrated in Table 1.1.

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Biomarkers Present on Bacterial Surfaces

1. Lipopolysaccharides (LPS) Gram-negative bacteria contain lipopolysaccharides (LPSs) as an essential component of their lipid bilayers in their outer membranes (OMs). As a result of the presence of these surface-exposed glycolipids, Gram-negative bacteria are in constant contact with their surroundings and are therefore protected against antimicrobials and aid in the development of antibiotic resistance (Paracini et al. 2022). The core section of LPS is made up of a nonrepeating oligosaccharide that substitutes the hydrophobic membrane anchor lipid A. The O antigen, a repetitive oligosaccharide, extends the core region in many bacteria. At the cytoplasmic leaflet of the inner membrane, the lipid A-core region and the O antigen are synthesised separately. In the periplasmic space, lipid A-core region is ligated with O antigen and thereafter transport of fully assembled LPS facilitated through periplasmic space to the outer membrane (Bos et al. 2004). LPS is an endotoxin and serves as the key stimulator of innate immune system (toll-like receptor 4) of humans, thus making it idealistic candidate for biomarker for early detection of pathogenic bacteria (Pal et al. 2015; Stromberg et al. 2017). A key indicator of infection, LPS is specific for serogroup (Gram-negative) and more stable than its protein counterparts, making it a viable option for early detection. LPS enables the detection and characterisation of pathotypes, which is critical for rapid infection prevention and treatment (Stromberg et al. 2017). In the LPS molecule, lipid A is the most conserved region and composed of six to seven fatty acid tails (Escherichia coli and Salmonella, respectively), which gives hydrophobic properties to its molecule (Raetz and Whitfield 2002; Meredith et al. 2006; Su and Ding 2015). Smooth (S form) and rough (R form) LPS are the two basic types of LPS (Hurley 1995; Raetz and Whitfield 2002). In organisms with S form, the distal end of LPS expands to a long-chain O-polysaccharide antigen (Oag (s)), which is a virulence indication (Nevola et al. 1985; Murray et al. 2003). O-antigen is absent in R-form LPS (Raetz and Whitfield 2002) but can still induce an immunogenic response (Jimesnez De Bagus et al. 1994). The O-antigen consists of repeated subunits, each of which contains 1–7 glycosyl residues, and is highly variable. Pathogenic Gram-negative bacteria that are harmful to human health include Acinetobacter, Bordetella, Burkholderia, Chlamydia, Campylobacter, E. coli, Haemophilius, Helicobacter, Legionella, Moraxella, Klebsiella, Proteus, Pseudomonas, Neisseria, Shigella, Salmonella, Yersinia, and others grouped into the Enterobacteriaceae family (Stromberg et al. 2017). These pathogens can cause nosocomial illnesses and are contaminants in food, water, and soil. They can also be exploited as bioterrorism agents (Deisingh 2004). For epidemiology, disease control, and therapy, detection of these pathogens, particularly E. coli, is critical. Despite being a part of the normal human intestinal microbiota and capable of colonising healthy people’s skin and nasal cavity, Klebsiella pneumoniae primarily affects the young and immunocompromised as a leading cause of hospital and community infections (including urinary tract infections, pneumonia, bacteraemia, and soft tissue infections) (Broberg et al. 2014). In the past, Klebsiella isolates were

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divided into serotypes and tracked using antisera for typing. Unique antibodies recognise different varieties of surface-exposed polysaccharides, such as O-antigens and K-antigens, resulting in diverse O and K serotypes. According to studies, there are 8 O-antigen serotypes and 77 K-antigen serotypes (Qrskov and Fife-Asbury 1977; Trautmann et al. 1997). As a result, LPS is an excellent target for detecting and identifying Gram-negative infections at an early stage (Stromberg et al. 2017). 2. Lipoarabinomannan (LAM) Glycolipids, which are the cell wall component of Mycobacterium tuberculosis, are key immunomodulators in tuberculosis. Lipoarabinomannan (LAM) in particular has a significant influence on the innate immune response. LAM has been extensively investigated for its immunomodulatory effects, and because it is a structurally different glycolipid component for all mycobacterial species’ envelopes, it is a brilliant model for studying glycolipids’ role in M. tuberculosis immunity. It is M. tuberculosis’ major carbohydrate antigen, accounting for up to 15% of the bacteria’s weight (Hunter et al. 1986). In some species, LAM has a mannan core, arabinan polymer branched out in several chains, and capping motifs at the end of the branched arabinan chains. In M. tuberculosis, the arabinan termini are transformed with oligomannoside caps to produce compounds referred to as ManLAM. The mannan core of LAM is covalently bound to a mannosyl phosphatidyl-inositol (MPI) lipid moiety including stearic acid, tuberculostearic, and palmitic residues (Chatterjee et al. 1988, 1991). In addition to LAM, its constituents LM and the phosphatidyl-myo-inositol mannosides (PIMs) have been demonstrated to have powerful immunomodulatory effects on immune system cells (Källenius et al. 2016). The capsule encircling M. tuberculosis contains a mannosecapped arabinomannan (ManAM), which is structurally linked to the ManAM component of LAM (Ortalo-Magné et al. 1996; Correia-Neves et al. 2019). Infection is followed by the release of highly conserved amphiphilic biomarkers, including LPS, lipoteichoic acid (LTA), and LAM into the bloodstream, all of which are biologically recognised by containing both hydrophilic and hydrophobic moieties (Table 1.2). These compounds are known to link with serum lipoproteins, including high- and low-density lipoproteins (HDL and LDL) (Jakhar et al. 2021; Lenz et al. 2022). These molecules are virulence factors that elicit the immune system of the host, but they also have capacity as biomarkers for bacterial infection diagnosis and therapeutic decision-making (Kubicek-Sutherland et al. 2017; Lenz et al. 2022). Tuberculosis (TB) is a leading cause of death worldwide, responsible for 1.7 million deaths in 2016. Death rate is also measurable, with 10.4 million people expected to be impacted by the disease in 2016, and the threat to global health is increased each year by the appearance of around 600,000 cases of drug-resistant tuberculosis (Global Tuberculosis Report 2018). Inconsistent microwell coating and high non-specific antibody binding are obstacles when using ELISAs to detect amphiphilic compounds, necessitating the use of accurately selected blocking and washing solutions, as well as specific types of microtiter plate material (Bantroch

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Table 1.2 Amphiphilic and lipid biomarkers used to diagnose the infectious disease Sr. No. 1.

Biomarker Lipopolysaccharide (LPS)

2.

Lipoteichoic acid (LTA)

3.

Lipoarabinomannan (LAM)

Disease Sepsis Urinary tract infection Antimicrobial resistance Sepsis

Location Blood Urine Any sample

Reference Feingold and Grunfeld (2011) Kubicek-Sutherland et al. (2017) Hrabák et al. (2013)

Blood

Tuberculosis

Urine Blood

Levels et al. (2003); Feingold and Grunfeld (2011); Triantafilou et al. (2012) Mukundan et al. (2012); Sakamuri et al. (2013)

et al. 1994). Lenz et al. devised an innovative analytical method for detecting amphiphilic compounds in a lipoprotein-coated ELISA format (Lenz et al. 2022). They used the natural interaction between synthetic and natural lipoproteins to acquire the amphiphilic LAM within the wells of a microplate. The signal-to-noise ratio for each of the four studied human lipoproteins exhibited a significant degree of variation. Natural human lipoproteins are composed of several molecules, but synthetic lipopeptide nanodiscs were able to capture both LAM and HDL, which could allow for higher reproducibility since individuals’ natural lipoproteins vary in composition. As a new approach to detecting amphiphilic molecules in their native form and structure, the lipoprotein capture ELISA developed by Lenz et al. (2022) provides a promising method for detecting very conserved virulence proteins generated by bacteria during infection as well as other relevant biomarkers (Lenz et al. 2022). 3. LipC The Lip family contains 24 putative carboxylic ester hydrolases. Investigations have been published on three of these members thus far: LipF (Rv3487c), LipH (Rv1399c), and LipY (Rv3097c) (Canaan et al. 2004; Deb et al. 2006; Shen et al. 2012). Recent studies have shown that the cell surface protein known as LipC may be present in both the capsule and the cell wall of the M. tuberculosis. LipC also induces cytokine production in macrophage-like THP-1 and lung epithelial A549 cells. Furthermore, M. tuberculosis LipC was heterologously expressed in active form and was isolated from Mycobacterium smegmatis, which was further purified, and biochemical investigation revealed that LipC hydrolyses short-chain esters. Their findings suggested that LipC may have a role in the course of active tuberculosis by aiding and enabling the consumption of lipid substrates for bacterial growth and replication as well as by regulating immunological responses (Shen et al. 2012). Affordable and rapid point-of-care (POC) have been developed for various disorders based on the detection of antibodies to antigen and/or epitopes selected after thorough consideration of their immunogenic ability in patients and controls have been developed (Shen et al. 2012). However, a recent WHO-sponsored

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assessment of the current marketable serological tests for tuberculosis diagnosis revealed that none of these tests gave accurate and trustworthy results for either extrapulmonary or pulmonary TB patients (Steingart et al. 2007; WHO 2008; Steingart et al. 2009). These tests are typically based on crude combinations of M. tuberculosis antigens or antigens that evoked antibodies in vaccinated animals, rather than a thorough investigation and selection of antigens relevant to human TB during the natural course of disease. Shen et al. (2012) identified a spectrum of promising candidates for developing a rapid POC test for tuberculosis and identified immunogenic epitopes of some of these highly immunogenic M. tuberculosis antigens (Samanich et al. 2001; Sartain et al. 2006; Shen et al. 2009; Singh et al. 2001, 2009). Grouping of immunodominant epitopes from numerous highly immunogenic proteins of M. tuberculosis is likely to advance the creation of a peptidebased rapid test for tuberculosis, as several antigens boost the sensitivity for antibody detection (Singh et al. 2001; Houghton et al. 2002; Ireton et al. 2010). LipC is a highly immunogenic cell surface-associated esterase of M. tuberculosis that evokes both antibodies and cytokines/chemokines. One or more of the six LipC epitopes identified could be useful in developing a diagnostic test (Shen et al. 2012). 4. Lipoteichoic Acid (LTA) Lipoteichoic acids are polyanionic polymers that are introduced into the cytoplasmic membrane’s outer leaflet via a lipid moiety. Through the peptidoglycan in the cell wall, the polymer passes onto the surface of Gram-positive bacteria. The cell wall lipoteichoic acids and teichoic acids of all Gram-positive bacteria have distinct chemical structures with the exception of Streptococcus pneumoniae. Other bacterial lipoteichoic acids have distinct repeating subunits and/or different lipid anchors. LTA is a significant mediator of inflammation in humans caused by Gram-positive bacteria, where it activates transcriptional factor nuclear factor kappa B (NFkB) via toll-like 2 (TLR2) receptors, resulting in the generation of pro-inflammatory cytokines (Lotz et al. 2004; Morath et al. 2005). Bloodstream bacterial infections (BSIs) are the primary cause of death in neonates and patients admitted to intensive care units (ICUs) or emergency rooms (ERs) and the third greatest cause of death after cancer and cardiovascular disease (Lukaszewski et al. 2008). Approximately 1 to 3% of the world’s hospitalised population may be affected, according to conservative estimates (Jagtap et al. 2018). When pathogens enter the circulation, pathogen-associated molecular patterns (PAMPs) are released as a result of bacterial mortality caused by antibiotics or the host’s immune response. PAMPs include endotoxin compounds like LTA in Gram-positive bacteria and LPS in Gram-negative bacteria, as well as lipoproteins, bacterial DNA, peptidoglycans, and other PAMPs. Endotoxins, particularly LPS, can enter the bloodstream via translocation from the human gut. Because of the inadequacies of present diagnostic procedures, the infection spreads, worsening the situation, which can only be treated with timely and evidence-based antimicrobial medication (Chaudhry et al. 2013). Antimicrobial resistance can be reduced by accurate diagnosis, which not only improves results but also minimises the use of

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LPS and LTA from bacterium (Gram +ve and Gram –ve)

Immobilization on nitrocellulose membrane without using receptors

Peptide or antibody-based AuNPs conjugator

Formation of spot indicates type of infection (Gram +ve and Gram –ve)

Fig. 1.2 Septiflo bioassay designed for the quick detection of blood infections and stratification of bacteria (Jagtap et al. 2018)

broad-spectrum antibiotics (Lee et al. 2013). It is therefore critical to detect infection early on before it becomes unmanageable. Furthermore, classifying bacterial Gram status at the time of infection will improve the antibiotic treatment plan. LTA is a transmembrane glycoprotein released by bacterial cell walls that could be used as a biomarker (Pai et al. 2018). Pai et al. (2018) suggested the direct use of LTA biomarker for the non-invasive detection of catheter biofilm burden. LTA, a non-invasive biofilm burden indicator, could be utilised as a surrogate endpoint in dialysis catheter research (Allon et al. 2018). Kubicek-Sutherland et al. (2017) have developed the two tailored assay for the direct detection of host lipoprotein such as LTA from Gram-positive bacteria and LPS from Gram-negative bacteria in the bloodstream. The semiquantitative assessment of LTA as a bioassay to detect early Gram-positive bloodstream infections has been examined in recent studies (Jagtap et al. 2018). A device, called Septiflo, has been developed by Jagtap et al. (2018) that can detect and stratify the Gram status of bloodstream bacterial infections from a drop of human plasma within 10 min (Fig. 1.2). It works on the basis of recognising PAMPs, such as LPS and LTA, which are released into the bloodstream during the start of Gram-negative and Gram-positive bacterial infections, respectively. In the absence of a receptor, biomarkers are gathered on a membrane, and Gram status specificity is provided by ligands attached to gold nanoparticles (AuNPs) used as signal amplification probes. The ultrasensitive colorimetric data can be read by eye without the use of an instrument down to a detection limit of 100 fg/ml (Jagtap et al. 2018). The assay’s simplicity, rapidity, cheap cost, receptor-less capture of biomarker, instrumentation-free signal output, and sub-pg/ml sensitivity are all unique design aspects that set it apart from other endotoxin detection methods. Septiflo offers a lot of promise as a point-of-care diagnostic tool for detecting septicaemia early on and ruling out non-infectious inflammations in the preclinical stage.

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5. The M-Protein Family The group A Streptococcus (GAS), Streptococcus pyogenes, is responsible for purulent skin lesions, pharyngitis, and post-infectious sequelae after an infection. GAS strains exhibit the M protein on their surfaces and can therefore be typed by using antibodies raised against the N-terminal portion of this coiled-coil α-helical molecule (Lancefield 1962). Approximately 100 types are known, and type-specific antibodies have long been known to confer immunity to strains carrying a specific M type by promoting the phagocytosis of GAS (Kuttner and Lenert 1943; Lancefield 1962). An M protein is a dimeric α-helical coiled-coil molecule capable of binding to several host components, including fibrinogen (Kantor 1965; Whitnack et al. 1984), Igs (Boyle et al. 1994; Kihlberg et al. 1999; Ji et al. 2022), kininogens (Ben Nasr et al. 1995), albumin (Retnoningrum and Cleary 1994; Kihlberg et al. 1999), and plasminogen (Berge and Sjobring 1993), and also factors that inhibit complement deposition on bacterial surface (Horstmann et al. 1988; Thern et al. 1995). Emm (classes I and II), Enn, and Mrp (FcrA) are related surface proteins that make up the M family of streptococcal proteins. Mga regulons of GAS OF+ strains always include all three M-family proteins in the order mrp, enn, and emm, succeeded by the scpA gene. In comparison, the organisation of the Mga regulons in OF- strains is significantly more variable and might include one or all three M-family genes, whereas the emm gene is constantly present (Hollingshead et al. 1994). In at least one instance, a further open reading frame encoding a surface protein of unknown function (orfX), which is controlled by Mga, was identified downstream of the scpA gene. Emm proteins (class I and class II) OF- GAS is almost exclusively found to contain class I Emm proteins. Their reactivity with monoclonal antibodies raised against their C-terminal repeats initially distinguished them from class II Emm proteins (Bessen et al. 1989). Most class I Emm proteins have been shown to bind albumin and/or fibrinogen, despite their remarkable diversity in binding properties. In the OF+ strains of GAS, these binding functions occur to have been divided between the Mrp and Emm (class II) proteins. The class II Emm proteins are commonly present in GAS of the OF- lineage and are the molecules typically recognised by M typing antisera. It has been discovered that none of the class II Emm proteins bind fibrinogen, a function that appears to be fulfilled by the Mrp proteins in the OF- strains. The class II Emm proteins have all been shown to bind Ig, although their specific binding preferences have varied. Enn As the third open reading frame in the Mga regulon, Enn proteins are almost exclusively found in OF+ strains. In general, recombinant Enn proteins expressed in E. coli have IgA binding activity (Bessen and Fischetti 1992). No Enn family members have been shown to possess antiphagocytic properties to date. It has been illustrated that the expression levels of enn genes are usually more than 30-fold lower than those of mrp and emm genes (Bessen and Fischetti 1992; Jeppson et al. 1992; Yung and Hollingshead 1996). As a consequence of their low

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expression level, the enn genes are thought to serve primarily as “reservoirs” for recombination with mrp and emm. Enn proteins may play a role in the time of infection despite the absence of evidence for their low expression in situ. Mrp (FcrA) Proteins encoding the MRP gene are often found in OF+ GAS strains and are consistently encoded downstream of the mga gene. All identified Mrp proteins bind both fibrinogen and human IgG (subclasses 1, 2, and 4). The absence of the conserved C-repeat regions distinguishes them from the Emm and Enn proteins. Sequencing the N-terminal domain of Mrp proteins from 37 distinct M serotypes confirmed the existence of only six distinct N-terminal Mrp regions. In at least four instances (Mrp 2, Mrp 64/14, Mrp 22, and Mrp 49), a Mrp protein has demonstrated antiphagocytic activity (Thern et al. 1998), which may be related to their ability to bind fibrinogen. 6. LMOf2365_0639 Listeria monocytogenes, a Gram-positive bacterium, is responsible for a significant number of foodborne illness deaths in humans. The surface proteins that are uniquely expressed in a wide variety of L. monocytogenes serotypes when grown in particular enrichment cultures have the potential to serve as biomarkers for the isolation and detection of L. monocytogenes using antibody-based methods. Zhang et al. (2016) identified 130 putative or known surface proteins on the L. monocytogenes serotype 4b strain F2365 genome (Zhang et al. 2016). As the presence of conserved regions among strains of L. monocytogenes that are variable among other Listeria species, the homologues of four surface proteins, LMOf2365_0578, LMOf2365_0581, LMOf2365_0639, and LMOf2365_2117, were evaluated for their potential as biomarkers. Only LMOf2365_0639 could be easily identified on the surface of living L. monocytogenes cells when immunofluorescence microscopy with PAb was used. In the case of some surface proteins on L. monocytogenes, such as InlB, the peptidoglycans must be cleaved prior to exposure to the surface (Jonquières et al. 1999). Surface proteins like LMOf2365_0578 and LMOf2365_0581 are only associated with the cell envelope in a noncovalent manner, and as a result, they can be removed from the cell envelope using a wash before immunofluorescence microscope imaging is performed. Despite high specificity for L. monocytogenes, all three monoclonal antibodies (M3644, M3651, and M3643) showed no or very marginal responses to other Listeria species, either in brain heart infusion cultures or enrichment cultures. Additionally, these MAbs recognised epitopes that are accessible on the surface of living cells in the N-terminal domain of LMOf2365_0639. Because of this, they can be easily utilised for the diagnostic isolation and detection of L. monocytogenes from environmental and food samples succeeding culture enrichment.

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Conclusion

Biomarkers play a critical role in improving the drug development process as well as in the larger biomedical research enterprise. Understanding the relationship between measurable biological processes and clinical outcomes is vital to expanding our arsenal of treatments for all diseases and deepening our understanding of normal, healthy physiology. Different surface biomarkers, such as polysaccharides, surface glycolytic enzymes, lipoproteins, and proteins, are used for the detection of infectious diseases caused by pathogenic Gram-positive and Gram-negative bacteria by using ELISA, nanoparticles, and biosensors. There are high standards for healthcare management to be met, and nanotechnology has increased the sensitivity of many diagnostic devices, which is essential for point-of-care diagnostics.

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Optical Nanosensors and Their Integrated Approaches for the Detection of Pathogens Sonam Kumari, Neeraj Dilbaghi, Ganga Ram Chaudhary, and Sandeep Kumar

Abstract

Bacterial contamination is one of the major reasons of waterborne and foodborne diseases and also fatalities that cultivate in the environment. The only way to prevent these diseases is the rapid detection of bacterial contamination with high accuracy at an early stage. Keeping in view the limitations of traditional methods in terms of time-consuming procedure and complex instrumentation with laborious sample preparation and trained personnel, the research fraternity has been putting efforts to explore nanomaterials to merge with sensing technology for the detection of microbial infection. Nanomaterials offer enormous benefits in terms of flexible morphology, high surface area, and enhanced optical, electrical, thermal, and mechanical properties. Foodborne and waterborne bacteria have long been monitored using nanomaterial-based optical biosensors. Nanomaterials

S. Kumari Department of Chemistry & Centre of Advanced Studies in Chemistry, Panjab University, Chandigarh, India Department of Bio and Nano Technology, Guru Jambheshwar University of Science and Technology, Hisar, Haryana, India N. Dilbaghi Department of Bio and Nano Technology, Guru Jambheshwar University of Science and Technology, Hisar, Haryana, India G. R. Chaudhary Department of Chemistry & Centre of Advanced Studies in Chemistry, Panjab University, Chandigarh, India S. Kumar (✉) Department of Bio and Nano Technology, Guru Jambheshwar University of Science and Technology, Hisar, Haryana, India Physics Department, Punjab Engineering College (Deemed to be University), Chandigarh, India # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Acharya, N. K. Singhal (eds.), Nanosensors for Point-of-Care Diagnostics of Pathogenic Bacteria, https://doi.org/10.1007/978-981-99-1218-6_2

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(like quantum dots, upconversion nanoparticles, and metal and metal oxides nanoparticles) offer significant enhancement in the optical abilities of the sensors. Further, the integrated optical sensing technologies can support various functions such as multiplexed detection, higher accuracy and sensitivity, and availability of signal readout and electrical control options on a single chip, making them suitable for point-of-care (POC) detection. This chapter covers the optical strategies for bacterial monitoring in food and water. In particular, fluorescence, colorimetric, surface-enhanced Raman scattering (SERS), and surface plasmon resonance (SPR) sensors are discussed along with their integration with other techniques like microfluidic, smartphone, and paper-based platforms. Keywords

Optical sensors · Pathogens · Nanomaterials · Integrated optical approaches

2.1

Introduction

Bacterial pollution and subsequent infection pose a serious hazard to human health. These are the major cause of waterborne and foodborne diseases. Foodborne and waterborne infections are majorly caused by different bacterial species, e.g., Staphylococcus, Bacillus, Salmonella, Vibrio, Shigella, Campylobacter, Listeria, and Escherichia genera (Wu et al. 2014). Pathogenic bacteria are a key source of the spread of many infectious illnesses such as cholera, tuberculosis, anthrax, pneumonia, and many others. According to a WHO report, contaminated water is considered to be responsible for 3.2% of global fatalities, largely due to bacterial diseases (Samota et al. 2022). Therefore, establishing reliable detection and monitoring systems for bacterial detection at early stages of infection is one of the most important measures to limit and control the risk of environmental contamination. The ability to identify and distinguish pathogens at low concentrations is critical in clinical practice. However, this identification can help health-care practitioners to choose the best antibiotic drugs against the bacterial infection. The most widely used conventional techniques for sensing of pathogens include culture-based approaches, enzyme-linked immunosorbent assay (ELISA), flow cytometry, and nucleic acid-based techniques (Hameed et al. 2018; Zhou et al. 2014). Despite offering high sensitivity, the conventional techniques offer many shortcomings. For example, culture-based methods suffer from tedious culture preparation and colony counting processes along with extremely slow growth or non-culturable bacterial cells in some cases (Law et al. 2014). Moreover, nucleicacid based approaches comprise of lengthy operation and requirement of large sample volume (Yadav et al. 2020). The immunological test also necessitates the use of sophisticated antibody labelling and repeated washing processes (Shen et al. 2021). In addition to these, all these techniques require highly skilled and experienced personnel. Therefore, alternative methods are required for simple and quick bacterial analysis.

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Nowadays, biosensors have been emerged as an effective diagnostic tool for precise and rapid analysis of infectious diseases. In comparison to traditional approaches, the use of biosensors can offer rapid, real-time, and on-site identification and determination of bacterial species (Ivnitski et al. 1999). A biosensor system consists of two basic components, a biological detection element and a physicochemical transducer. In order to create a signal, biological sensing components (i.e., aptamers, antibodies, enzymes, DNA, etc.) interact selectively with the analyte of interest. The transducer converts this interaction of biomolecules into a measurable and quantifiable signal. Furthermore, the sensitivity and efficiency of these biosensors can be improved by combining with nanotechnology. The merging of nanomaterials in biosensing design provides various benefits over traditional approaches, e.g., label-free detection, low limit of detection (LOD), real-time analysis, a reduced sample volume need, and high-throughput screening. This can be assigned to the attractive attributes of nanomaterials such as high surface-to-volume ratio, small size, enhanced surface reactivity, quantum confinement effect, and exceptional electrical/magnetic/optical properties (Bhardwaj et al. 2017). The increase in effective surface area of the sensors due to nanomaterials enhances the capture probability of an analyte. For detection of bacterial infection, different nanomaterials have been explored such as quantum dots (QDs), upconversion nanoparticles (UCNPs), metal and metal oxide nanoparticles (NPs), and nanoclusters (Kumar et al. 2019; Nehra et al. 2022, 2019). Furthermore, breakthroughs in nanotechnology have paved the door for the progress of fast and accurate sensing approaches for determination and identification of pathogenic bacteria. Sensitivity of nanoparticle-based sensors can be boosted by conjugating them with affinity ligands, antibodies, or aptamer (Kaittanis et al. 2010). Sensors can be categorized depending on their signal transduction mechanism. Among these, electrochemical and optical are the most widely adopted transduction methods for detection of bacteria. The interaction of the target with the recognition bioelement on the sensing surface can cause changes in different parameters (e.g. current, potential, conductance, or field effect), which are measured by the electrochemical approach. Optical biosensors are the devices that monitor the changes in light characteristics such as refractive index, absorption, fluorescence, or light scattering resulting from an analyte-receptor interaction (Garzón et al. 2019). The amount of analyte (bacteria) present in the solution can be quantified by analysing these changes in light properties. Optical nanosensors offer simplified detection of pathogens. They are well-known for their unique characteristics in terms of quantitative nature, fast, and label-free real-time sensing of several biological and chemical compounds with high specificity, sensitivity, and compact size at low cost (Damborský et al. 2016). The main optical methods reported for the detection of harmful bacteria are presented in Fig. 2.1. Modern biosensing has progressed from laboratory testing to near-patient on-site detection. This has been achieved by integration of sensing approaches with pointof-care (POC) devices (Chen et al. 2020). POC biosensors (that offer low-cost operation, ease of use, fast response, and real-sample analysis) are extremely sought due to the huge need for quick testing to control the spread of pathogenic infections

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Fig. 2.1 Schematic representation of different optical techniques with different nanostructures or bioreceptors for detection of pathogens (Adapted from Pebdeni et al. (2022), Copyright 2022, with permission from Elsevier)

(Rasmi et al. 2021). Furthermore, optical sensors combined with a microfluidic system may greatly simplify sample processing and make the experience more convenient. The introduction of new-generation biosensing platforms with smartphone-based technology marketed POC devices with broad clinical utility (Roy et al. 2022). Further, the use of paper-based biosensor platforms has also enabled the creation of simple, selective, sensitive, and portable devices for the sensing of a wide range of target analytes (Peixoto et al. 2019). Therefore, optical sensors are projected to perform a larger role in pathogen diagnoses and POC monitoring in different clinical and environmental situations.

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2.2

Optical Techniques for Detection of Pathogenic Bacteria

2.2.1

Fluorescent Biosensors

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In comparison to traditional detection approaches, the fluorescent sensors offer compactness, simple instrumentation, and electrical noise resistance with good sensitivity and selectivity (Bhardwaj et al. 2017). However, the use of traditional organic fluorophores can limit their performance due to their unstable nature with susceptibility towards photobleaching. Recently, nanomaterial-based fluorophores have emerged as an alternative to conventional fluorophores due to their superior properties in terms of stability and signal amplification capabilities (Deng et al. 2021). Several fluorescent nanomaterials, such as carbon dots (CDs), QDs, metal nanoparticles (NPs), and nanoclusters, have been widely utilized in biosensing and bioimaging due to their excellent photobleaching resistance, easy surface functionalization, high photoluminescence intensity, and controllable synthesis. Moreover, these fluorescent nanomaterials can be conjugated with aptamers for the sensing of target pathogen (He et al. 2022b). For the sensing of the target analyte, two different mechanisms can be followed, e.g. either the fluorescence quenching of nanomaterials by analyte or by the quencher through (i) photoinduced electron transfer (PET) or (ii) fluorescence resonance energy transfer (FRET). Analyte concentration may be estimated based on the extent of quenching or the intensity of the fluorescence restoration (He et al. 2022b). Among different fluorescent nanomaterials, QDs have gained a lot of attention as a fluorescent probe due to their small size, strong photo-stability, broad absorption/ excitation spectrum, limited emission spectrum, high quantum yield, and significant stroke shift (Park et al. 2017). The sensing of Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) has been reported using nitrogen-doped graphene QDs with high sensitivity in the range 0 to 9 × 107 (Safardoust-Hojaghan et al. 2017). Chitosan-functionalized cadmium sulphide (CTS@CdS) QDs have been utilized for the highly selective, affordable, and rapid detection of S. aureus. The inherent enzymatic character of QDs avoids the need of costly labels for specific detection. In the existence of S. aureus, hydrogen peroxide decomposition occurs that causes the quenching of fluorescence emission of QDs (Abdelhamid and Wu 2018). A fluorescence quenching system based on CdSe/ZnS QDs, free Au NPs, and IgY-functionalized gold NPs (IgY-AuNPs) was designed for the sensing of Vibrio parahaemolyticus (V. parahaemolyticus). Fluorescence quenching occurred as a result of charge transfer from CdSe/ZnS QDs to Au NPs. The fluorescence signal was regained upon binding of V. parahaemolyticus to IgY-AuNPs conjugates. This simple one-step approach can identify bacteria with a low detection limit of 10 cfu/ mL (Liu et al. 2017). Pseudomonas aeruginosa (P. aeruginosa) has been identified using the FRET method using aptamer as a bio-recognition element with 5-carboxyfluorescein-labelled complementary DNA (FAM-cDNA) as an energy donor and graphene quantum dots (GQDs) acting as an energy acceptor. In the absence of bacteria, FAM-cDNA@aptamer binds to the surface of GQDs, causing fluorescence quenching of FAM-cDNA through the FRET mechanism, which may

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Fig. 2.2 Schematic representation of fluorescent biosensor with double-layer channel with MNPs and QDs for detection of E. coli (Adapted from Xue et al. (2018), Copyright 2018, with permission from Elsevier)

be restored in the presence of P. aeruginosa (Gao et al. 2018). For the isolation and detection of Legionella pneumophila, antibody-conjugated magneto-fluorescent CaCO3 microbeads, Fe3O4 NPs, and AgInS/ZnS QDs have been utilized (Martynenko et al. 2019). Xue et al. (2018) reported on the specific separation of E. coli utilizing immune MNPs that concentrated the bacteria in a double layer channel, as well as the detection of the bacterium using immune QDs. To construct MNP-bacteria complexes, the bacteria were first trapped by immunological MNPs in the channel under magnetic field (Fig. 2.2). The immunological QDs were then employed for reaction with the target analyte in the channel, forming MNPsbacteria-QDs complex. Finally, these enriched complexes were collected followed by detection with the help of a portable optical device. Within 2 h, this suggested biosensor was able to detect E. coli at a concentration of 14 cfu/mL. Recently, UCNPs have attracted a lot of interest due to their inherent benefits in terms of long luminescence lifetimes, large anti-Stoke shifts, and no autofluorescence (He et al. 2022a). These are referred to as anti-stroke fluorescence probes that can convert near-infrared light to visible light (Liang et al. 2020). In order for the FRET process to work, the two fluorophores must be within 1 to 10 nanometres of each other for overlapping of the donor and acceptor molecules’ emission and absorption spectra (Rong et al. 2020). UCNPs act as an energy donor in

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the FRET process. For fast and specific measurement of E. coli, a new, selective, and sensitive fluorescent probe (based on aptamer conjugated core-shell UCNPs and 2D WS2 nanosheets as donor and acceptor, respectively) has been effectively created. Because of the strong van der Waals interaction between the basal plane of WS2 and the nucleobases of aptamer, the aptamer modified-UCNPs may be carried closest to the WS2 surface that caused the fluorescence quenching of aptamer-UCNPs by WS2 nanosheets via FRET process. However, in the case of E. coli presence, the fluorescence is restored due to the high affinity between the target and the aptamer. The detection limit of this sensing probe was found as low as 17 cfu/mL with excellent selectivity (Wang et al. 2020a). For the highly specific and sensitive detection of three pathogens (S. aureus, S. typhimurium, and V. parahaemolyticus), aptamersfunctionalized multicolour UCNPs were fabricated and coupled with MNPs (Wu et al. 2014). The independent fluorescent emission peaks of UCNPs were further modified by doping with various rare earth ions. The UCNPs@MNPs composite were used to collect and quantify all of the target microorganisms with a limit of detection of 25, 15, and 10 cfu mL-1 for S. aureus, S. typhimurium, and V. parahaemolyticus, respectively. The addition of hydrogen peroxide (HP) and tannic acid (TA) to UCNPs@guanidine composite can further improve the sensor sensitivity by boosting interaction between positive guanidine group and negative bacterial surface (Yin et al. 2019). CDs are a new form of carbon-based nanomaterial that has gotten a lot of interest because of its wide variety of sources, ease of functionalization, low toxicity, and great optical and physiochemical capabilities (Cui et al. 2020). Poly (vinylpyrrolidone) (PVP)@Ag:CD has been exploited for bacterial identification via electrostatic interactions with the negatively charged surface of bacteria (Roh et al. 2019). This interaction causes aggregation-induced quenching of fluorescence of CDs. Fluorescence sensor array made up of CDs (customized with distinct receptors such as boronic acid, polymyxin, and vancomycin) has been fabricated to quickly discriminate six types of bacteria using linear discriminant analysis (LDA) (Zheng et al. 2019a, b). CDs-encapsulated breakable organosilica nanocapsules (BONs) were created to generate core-shell CDs@BONs (Yang et al. 2018). In comparison to a traditional immunoassay utilizing CDs only, the fluorescent signals of CDs@BONs were enhanced by two orders of magnitude due to multiple CDs packed in each nanocapsule for detection of S. aureus in the range of 1 to 200 cfu mL-1.

2.2.2

Colorimetric Biosensors

Colorimetric analysis is a simple, cost-effective, and qualitative detection technique which can be done without the need for any sophisticated instruments. In this technique, the colour change due to presence of pathogenic bacteria can be observed through naked eyes. The integration of colorimetric probes with other techniques like UV-Vis spectrophotometer also offers the quantification of the bacteria (Liu et al. 2022). NPs offer electrostatic interaction with bacteria and lead to colour

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change. Au NPs have been most commonly used for the colorimetric detection of pathogens due to their unique optoelectronic, thermal, chemical, and biological capabilities (Castillo-Henríquez et al. 2020). The properties of Au NPs (such as shape, size, and aggregation) have a significant impact over their optical behaviours in terms of shift in the wavelength, change in colour, and Raman scattering enhancement (Ha Anh et al. 2022). The aggregating behaviour of Au NPs results in colour change from red to blue, and this ability has been examined for colorimetric sensing of a wide range of biomolecules (Kalimuthu et al. 2020). The colorimetric sensing of both gram-positive and gram-negative bacterial species has been reported with antibiotics (ATB)-conjugated Au NPs. Pertaining to the high specificity of ATB to bacterial strains, the transfer of ATB from Au NPs to bacterial surface results in agglomeration of AuNPs; therefore, this agglomeration causes visible colour change in the colloidal solution of NPs due to presence of bacteria. This colour change was further confirmed by the UV-Vis absorbance studies that showed a red shift in the surface plasmon band of Au NPs (Elliott et al. 2021). Further, Feng et al. demonstrated the colorimetric sensing of Shigella flexneri (S. flexneri) using Au NPs. In this case, the surface of Au NPs was complexed with bacteria-specific aptamer to prevent their salt-induced aggregation. The presence of S. flexneri causes its binding to the aptamer that leads to the aggregation of Au NPs, causing red to blue colour change with increasing salt concentration (Feng et al. 2019). In comparison to bare Au NPs, the conjugation of Au NPs with graphene oxide can improve the sensitivity of the nanosensor by offering more active sites for bacteria-specific label binding (Gupta et al. 2021). Further, 4-mercaptophenylboronic acid (MPBA) complexed with silver NPs (MPBA-AgNPs) has been utilized for E. coli detection. Here, MPBA acts as a recognition molecule, reacting with the cis-diol of saccharides on the surface of bacterial cells. The bacterial cells could hinder the aggregation of the AgNPs-based nanoprobe that results in colour change (Zheng et al. 2018). With the help of UV-Vis spectrometer, the presence of E. coli was quantified with a limit of detection of 0.9 × 104 cfu mL-1 in a dynamic range from 5 × 104 to 1 × 107 cfu mL-1 within 20 min, Fig. 2.3. Further, the use of MNPs has been suggested by various research groups for the fast separation and efficient enrichment of bacteria (Mocan et al. 2017). Colorimetric sensor based on a sandwich complex of magnetic Fe3O4 NPs and Au NPs with target bacteria (S. typhimurium)-specific complementary DNA sequence has been reported. This sandwich complex resulted in red shift in absorbance spectrum along with colour change from red, purple, to blue due to distance-dependent optical properties of Au NPs (Ma et al. 2017). Zhu et al. (2021) fabricated the highly sensitive colorimetric nanosensor with a detection limit of 3 cfu/mL for S. aureus based on Mn3O4 NPs with their surface functionalized with aptamer for modulating the oxidase-mimicking activity. The presence of aptamer inhibited the 3,3′,5,5′-tetramethylbenzidine (TMB) oxidation by obstructing the electron transfer process from NPs to TMB. This inhibition can be prevented in the presence of S. aureus due to their higher binding affinity with the aptamer that resulted in appreciable colour change. A sensitive colorimetric assay has also been reported by Sadsri et al. for the

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Fig. 2.3 Colorimetric detection of pathogenic bacteria (a) detection mechanism based on inhibition of MPBA-Ag NPs aggregation and (b) schematic illustration of different signal detection approaches like naked eyes, UV-Vis spectrometer, and smartphone (Adapted from Zheng et al. (2018), Copyright 2018, with permission from Elsevier)

visual detection of Vibrio parahaemolyticus (foodborne pathogen) using AuNPs and MNPs (Sadsri et al. 2020). Bacteria-specific aptamer was bounded with both nanoparticles and resulted in the formation of sandwich complex as MNPsaptamer-bacteria-specific aptamer-AuNPs. This sandwich complex can be magnetically separated from the solution. Besides these advancements, the performance of colorimetric biosensors is still limited in terms of their low detection limits (Wang et al. 2017b; Nehru et al. 2021).

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SERS Biosensors

The Raman spectrum is a very valuable tool based on the light interaction with chemical bonds of a material. It is a highly sensitive technique that can measure the very small changes in the structure of molecules. However, low-intensity Raman scattering of biological samples is difficult to examine (Han et al. 2022; Kuhar et al. 2018). Confluence of Raman scattering and nanotechnology led to the discovery of surface-enhanced Raman spectroscopy (SERS) in order to detect low-concentration analytes through chemical enhancements or plasmon-mediated amplification (Yang et al. 2021). SERS is a surface-sensitive sensing technique that involves the inelastic scattering of incoming light and a surface molecule, resulting in the molecule’s vibrational spectral peaks (Ha Anh et al. 2022). Raman scattering is amplified when the analyte is adsorbed on the surface of NPs (commonly gold and silver). SERS can provide higher-intensity Raman emissions with lower detection limits (Yonzon et al. 2005). For the fast and sensitive sensing of bacteria, the SERS detection technology has been integrated with the magnetic separation strategy (Kearns et al. 2017). In this case, lectin-modified MNPs trap and isolate the bacteria from the sample matrix through interacting with bacteria’s surface sugar moieties. Here, the bacteria form a compound with MNPs and bio-recognition molecules (antibodies); and the isolation of resultant SERS active complex was carried out from the matrix using magnets. In single pathogen testing for E. coli, S. aureus, and S. typhimurium, cell densities as low as 10 cfu/mL were easily identified with this detection assay. Along with single pathogen identification, SERS was also used to isolate and identify a combination of all these three bacterial strains inside the same sample matrix. The bacterial immobilization for detection process can be eliminated using ROX-aptamer-modified Au@Ag NP-coated glass slide (Fig. 2.4.) (Ma et al. 2023). In the presence of S. aureus, the ROX-aptamer gets bound to it and fell off from the substrate that results in decreased SERS signal intensity. This approach offered a detection limit of 6 cfu/mL in the range of 102 cfu/mL–107 cfu/mL. To enhance the sensitivity of the pathogen detection, a dual-recognition SERSbased test based on aptamer and vancomycin antibiotic has been devised (Pang et al. 2019). Aptamer-conjugated Fe3O4@Au MNPs were employed to capture the bacteria. Following that, non-targeted pathogens were washed away. SERS tags were then used to label the bacteria-aptamer-Fe3O4@Au complex to detect the analyte. Raman scattering of the Raman-active molecule was significantly improved due to specific analyte binding. Using this dual-recognition and SERS enhancement approach, a detection limit of 3 cells/mL with a broad dynamic linear range of 10 to 107 cells/mL was reached in less than 50 min without any interference from non-target bacteria. The binding of an advanced SERS nanotag (polydopamine-coated Au@Ag NPs) to the surface of bacteria can enhance the Raman signal by 108 times. This SERS nanotag offered a lowest detection limit of 10 colonies/mL within 30 min (Wang et al. 2020c). Antimicrobial peptide-modified MNPs and 4-mercaptophenylboronic acid (4-MPBA)-modified graphene oxide nanocomposites have also been reported as SERS tag. Here, distinct fingerprint patterns of 4-MBPA were formed after

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Fig. 2.4 S. aureus detection without immobilization using SERS biosensor based on ROXaptamer-modified Au@Ag NPs (Adapted from Ma et al. (2023), Copyright 2023, with permission from Elsevier)

interaction with the bacterial cell wall, and these patterns can be utilized to discriminate different kinds of pathogens (Yuan et al. 2018). To create an all-in-one ratiometric nanosensor for E. coli detection, the chemical integration of different materials was carried out such as MNPs with silver shell, 4-mercaptobenzoic acid (MBA) as SERS substrate, and the aptamer sequence as SERS substrate, SERS internal standard, and E. coli capture probe, respectively (Weng et al. 2021). For E. coli detection, the analyte cells were collected by nanosensors and thereafter magnetically enriched in 15 min followed by ratiometric SERS.

2.2.4

SPR Biosensors

SPR is a frequently used optical method that occurs at the metal-dielectric interface where the external light energy resonantly drives the metal’s free electrons. The resonance phenomena occur only at a particular angle of incidence, which is decided by the refractive index of medium close to the metal surface (Abadian et al. 2014). It has been reported for detection of biological molecules on the basis of refractive index change of a sensor surface due to binding of a target molecule (Shrivastav et al. 2021). The concentration of bacteria that are bound to the SPR surface is directly related to the change in resonance angle (Waswa et al. 2007).

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Fig. 2.5 Brucella melitensis detection using magnetic silica core-shell NP-based SPR biosensor with dual aptamers (Adapted from Dursun et al. (2022), Copyright 2022, with permission from Elsevier)

By monitoring variations in peak extinction intensity, a label-free and accurate detection of various bacterial species has been fabricated using an aptamerimmobilized localized surface plasmon resonance sensor (LSPR) (Yoo et al. 2015). For this, a multi-spot gold-capped nanoparticle array has been used that makes the LSPR peaks more sensitive and repeatable. Further, the aptamer modification allows for simple and fast detection, and the use of multiple spots with different aptamers on a single chip can offer the sensing of multiple bacteria in a single experiment. Dursun et al. (Dursun et al. 2022) reported the use of dual aptamers in magnetic silica core-shell NPs-based SPR biosensor for detection of Brucella melitensis (B. melitensis) (Fig. 2.5). Initially, the B70 aptamer was used for the purification of target bacteria cells from the sample, and thereafter, B46 aptamer was utilized to fabricate SPR sensor chips for specific B. melitensis detection with a detection limit of 27 ± 11 cells/mL. The simultaneous detection of RNAs from three different bacterial species like P. aeruginosa, S. typhimurium, and L. pneumophila was achieved using Au NPs as a signal amplification agent for the SPR approach. A self-assembled monolayer (SAM) technique was used to immobilize thiolated capture probe (CP), bearing a sequence corresponding to the target 16S rRNA of corresponding bacterial strain on the surface of sensor. The sequences were selectively hybridized and caused a reflectivity change in the presence of target sequence. One more hybridization reaction happens at the second targeted area of the target sequence after the addition of detector probe (DP) immobilized on Au NPs via their 5′-thiolated extremity. The combined amplification modalities of DNA-RNA-DNA sandwich assembly and Au

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NPs caused an increase in the SPR signal. The results confirmed that the suggested sensor can detect bacteria at a concentration as low as 10 pg mL-1, with a dynamic range of 0.01 to 100 ng mL-1 with excellent selectivity (Melaine et al. 2017). The conjugation of optical fibre SPR sensor has also been reported with polymerase chain reaction (PCR) for amplified sensing of pathogenic bacteria (Nguyen et al. 2017). Baccar et al. (2010) developed two different SPR biosensors for detection of two bacterial strains using functionalized gold substrate and immobilized Au NPs, respectively. The functionalization of gold substrate was carried out with thiol acid using the SAM approach for the first biosensor, and Au NPs were immobilized on a modified gold substrate for the second biosensor. Due to effective identification of bacteria, both types of biosensors demonstrated an increase in resonance angle with increased E. coli concentration. For the first and second biosensors, detection limits of 104 and 103 cfu mL-1 of E. coli bacteria were obtained, respectively, with good reproducibility. Due to adsorption of bacteria, the variations in refractive index below 5 × 10-3 can also be easily recognized. For detection of E. coli in water and juice samples, a highly sensitive, selective, and label-free fibre-optic SPR (FOSPR) sensor was developed (Zhou et al. 2018). The antimicrobial peptide Magainin I was employed as a bacterium recognition molecule with gold-coated AgNP-reduced graphene oxide nanocomposites for signal amplification. In comparison to gold film, an approximate increase of 1.5 times was observed for the sensitivity of the FOSPR sensor. Furthermore, without the use of a secondary antibody, this technique has offered a low detection limit of 5 × 102 cfu/ml with good stability and satisfactory recoveries of 88–110%.

2.3

Integrated Optical Biosensors

2.3.1

Microfluidics-Based Detection

Microfluidics, also known as miniaturized total analysis system (TAS), incorporate sample preparation, reaction, separation, detection, and analysis on the centimetrescale chip with a network of microchannels (Zhao et al. 2019). Microfluidics-based POC devices are currently being extensively studied due to their capacity to conduct measurements with tiny amounts of complicated fluids with high speed and efficiency. The measurements without the need for a competent operator have been addressed with the most potent use of lab-on-a-chip (LOC) technology (Mairhofer et al. 2009; Jagannath et al. 2022). Nowadays, microfluidic chips have been merged with an increasing number of optical biosensors to increase their overall performance of pathogen detection (Liao et al. 2019). Such integrated systems comprise microfluidics with an optical waveguide that acts as a critical component in the detection process. The integration of nano-dielectrophoretic microfluidic system with SERS offered highly sensitive detection of E. coli bacteria at extremely low levels, i.e. single cell/mL (Wang et al. 2017a).

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For label-free and fast optical detection of E. coli Dh5α cells from fluid samples, an integrated microsystem comprising dielectrophoretic surface-electrodes (for collecting cells), a rib waveguide, and a microfluidic channel was also developed (Petrovszki et al. 2021). A considerable alteration in the pattern of scattered light due to the bacterial cells was identified even with a modest magnification camera. This innovative approach could detect the E. coli bacteria with a detection limit of 102 cfu/mL. Cao et al. fabricated a microfluidic loop-mediated isothermal amplification (LAMP) device in conjunction with colorimetric and fluorescence analytic methods to identify four different bacteria (Salmonella, S. aureus, E. coli, and Shigella) (Cao et al. 2022). In this method, a ten-well microfluidic chip with pre-loaded LAMP primer sets was used to identify four foodborne bacteria species in just 45 min with a limit of detection of 8 × 103 cfu/mL. Further, fluorescent nanoparticles (CdSe/ZnS@SiO2–NH2) have been integrated with microfluidic device for S. typhimurium detection (Wang et al. 2014). Here, the fluorescent nanocomposite was fabricated by incorporating the CdSe/ZnS QDs into SiO2 nanospheres using a self-modified reverse microemulsion method for use as highly effective fluorescent markers. A two-step crosslinking technique using glutaraldehyde as the crosslinker allows the covalent coupling of the nanocomposite with bacteria. The fluorescent nanocomposite-labelled bacteria were concentrated near the margins of the microelectrodes in the microchannel by positive dielectrophoresis (DEP), and these can be further counted under the fluorescence microscope, offering a detection limit of 3.3 × 102 cfu/mL. Further, Man et al. fabricated the microfluidic colorimetric biosensor based on aptamer-polystyrene microsphere (PSs)-conjugated Au NPs for Salmonella detection (Fig. 2.6) (Man et al. 2021). The aggregation of Au NPs on the surface of bacteria-aptamer-PScysteamine conjugates caused visible change in colour that offered a detection limit of 6.0 × 101 cfu/mL along with recoveries range from 91.68% to 113.76%. A labelfree platform for pathogen detection, combining SPR and microfluidic technologies, has been developed for detection of S. aureus and E. coli (Tokel et al. 2015). Here, antibodies were functionalized on gold-coated surface of disposable microfluidic chips for specific and selective pathogen capture. Fluorescence imaging offered quantification of trapped E. coli in concentration range from 105 to 3.2 × 107 cfu/ mL, and the capture distribution was evaluated spatially along the microchannels.

2.3.2

Smartphone-Based Biosensors

A smartphone-based device has been found as one of the most convenient choices for POC device development due to their portable nature, ease of handling, prompt testing, functional readiness, cost-effectiveness, and data recording (Wang et al. 2020b). It can be easily linked to other technologies like unmanned devices, artificial intelligence, and human-machine interface. Due to the growing popularity and availability of customized mobile apps, data storage, and transfer, POC diagnostics has recently progressed in the direction of combining smartphone with a microfluidic device (Nguyen et al. 2020). Further, Li et al. (2019) reported on the integration of

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Fig. 2.6 Representation of microfluidic colorimeteric biosensing of Salmonella using thiolated polystyrene microspheres for aggregation of Au NPs. (a) 3D structural design of microfluidic chip and (b) detection strategy (Adapted from Man et al. (2021), Copyright 2021, with permission from Elsevier)

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Fig. 2.7 Schematics for E. coli detection on smartphone using GQD nanocomposites for aggregation of Au NPs. (a) 3D structural design of microfluidic chip and (b) detection strategy (Adapted from Li et al. (2019), Copyright 2019, with permission from Elsevier)

electrogenerated luminescence (ECL) detection with smartphone for E. coli detection (refer to Fig. 2.7). In this approach, GQD nanocomposites were synthesized to stabilize ECL emission due to their greater catalytic activity and amplification efficiency towards luminophores. Here, fluorescent signals were then collected with the help of a smartphone camera and analysed using an image analysis programme on the phone (app). This smartphone-based ECL system demonstrated a good linear response for E. coli detection in 10 cfu/mL to 107 cfu/mL concentration range by immobilizing a layer of analyte-specific antibodies on the electrode surface. Zheng et al. (2019a, b) created a microfluidics-based biosensor with smartphone imaging for quick and sensitive detection of E. coli based on Au NP aggregation. Using an HSL-based imaging programme, the E. coli content in chicken samples was determined with a limit of detection of 50 cfu/mL. For quick detection of Salmonella enteritidis in dairy products and water, the calcium nanoflower composite was prepared with streptavidin magnetic beads for further coupling with biotin-labelled antibody (Zeinhom et al. 2018). This combination offers specific bacteria collection through magnetic antibody, and further, signal amplification was achieved through nanoflower-based composite. This smartphone sensor offered a detection limit as low as 1.0 cfu/mL and 1.0 cfu/g for Salmonella enteritidis in tap water and milk/cheese, respectively. The integration of fluorescent NP-based detection by immunochromatographic test strips with a smartphone-based readout has been reported for detection of Salmonella spp. and E. coli (Rajendran et al. 2014). Silica NPs were doped with fluorescein isothiocyanate (FITC) and Ru (bpy) and then conjugated to the analyte-specific antibodies and employed in a standard lateral flow immunoassay (LFIA). High-resolution fluorescent images

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were analysed using the mobile phone’s rapid image processing programme that offered very quick detection of pathogens with concentrations as low as 105 cfu/mL without any pre-enrichment of the sample.

2.3.3

Paper-Based Biosensors

Paper-based analytical instruments are one of the most common POC devices for food safety and environmental monitoring. They have a number of benefits over other sensors, including ease of manufacture/operation, cheap cost, adaptability, and mobility (Pebdeni et al. 2022). In paper-based sensors, a variety of signal readouts have been used, including conductivity, colorimetry, fluorescence, and electrochemistry. Among these, the use of colorimetric technique for paper-based biosensors is the most popular and appealing because a particular pathogen can be readily observed by a simple colour change (Nguyen and Kim 2020). This colour change can be detected with the naked eye without the need for expensive and sophisticated apparatus. The use of fluorescent nanoparticles (GQDs and Au nanoclusters) in conjunction with a paper-based analytical device (PAD) has showed portable pathogen detection with good sensitivity (Yuan et al. 2022). Multiple antigens may be evaluated at the same time due to the distinct fluorescent colours and narrow emission band of GQDs and Au nanoclusters that boosts the multiplexity of the PAD-based immunoassay. Further, Eu-doped silicon NP (Eu@SiNPs)-based dual-emissive fluorescent probe was constructed via a one-pot synthetic approach that requires no further postmodification for the sensing of anthrax spore biomarker dipicolinic acid (DPA) (Na et al. 2020). This method realized the both ratiometric fluorescent detection and visual detection of Bacillus subtilis spores simultaneously with a low detection limit of 2.38 × 104 spore/mL. Furthermore, Eu@SiNPs-based test paper was also produced and utilized for efficient detection of DPA and simulant Bacillus anthracis spores in a simple, rapid, and visible manner. The paper-based microfluidic system can be made quantitative by using image processing to help identify the important colorimetric signals and estimate bacterial concentration (Somvanshi et al. 2022) (Fig. 2.8).

2.4

Conclusion

All around the world, pathogenic bacteria are the cause of a variety of infectious illnesses. The early and precise identification of various pathogenic microorganisms is critical for the effective handling of pathogenic infections. The complex instrumentation and inability of traditional approaches to detect pathogens in a short time interval demand the advent of new rapid technologies. Optical biosensors in combination with nanomaterials can offer enormous benefits for detection of pathogens such as selective, ultrasensitive, qualitative, and quantitative detection in a fast manner. These optical biosensors have been advanced to detect multiple analytes

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Fig. 2.8 Schematic for pathogen detection using GQDs and Au nanoclusters on paper-based analytical device with colour detection system (Adapted from Yuan et al. (2022), Copyright 2022, with permission from Elsevier)

in complicated sample matrices (like water, food, blood, urine, or serum) with minimal sample preparation. Pathogen detection has been carried out using fluorescent nanomaterials that can act as both FRET donors or acceptors. The SERS property of noble metal nanostructures on the other hand can be used to boost weak Raman signals for pathogen detection. Furthermore, the aggregation response of NPs can be utilized to confirm the presence of pathogenic bacteria in a simple yet effective colorimetric method. Moreover, the SPR approach utilizes the change in material refractive index in order to quantify the bacteria. Integrated optical sensors are projected to play a significant role in pathogen detection and point-of-care (POC) monitoring in diverse clinical and environmental situations. Acknowledgement Sonam Kumari thanks the University Grants Commission (UGC), Government of India, for providing financial assistance in the form of junior research fellowship (JRF) (award no. 71/CSIR-UGC NET JUNE 2019 dated 06-12-2019).

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Surface Plasmon Resonance (SPR)-Based Nanosensors for the Detection of Pathogenic Bacteria Priyanka Thawany, Umesh K. Tiwari, and Akash Deep

Abstract

Surface plasmon resonance (SPR) is a well-established phenomenon with applications in different fields of chemical, physical, and biological sciences. Surface plasmons are excited on a metal dielectric interface due to the collective oscillation of the electron cloud in response to incident electric field, which generates an evanescent wave at the metal-dielectric interface, which is sensitive to the surrounding refractive index changes. The SPR technique has also been extended for the development of biosensors for different analytes, including the pathogenic bacteria. SPR biosensors offer the advantages of direct and label-free detection. They work on the mechanism of recording the refractive index changes when the biosensor surface binds with a target analyte. The present chapter comprises the information on the applications of SPR biosensors for pathogenic bacteria. Biosensors based on the use of enzymatic reactions, metallic and magnetic nanoparticles, and nanosheets have been discussed. The applications of localized SPR (LSPR) and long-range SPRs (LRSPs) to develop highresolution SPR sensors have also been covered.

P. Thawany · U. K. Tiwari Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India CSIR-Central Scientific Instruments Organization (CSIR-CSIO), Sector 30C, Chandigarh, India A. Deep (✉) Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India CSIR-Central Scientific Instruments Organization (CSIR-CSIO), Sector 30C, Chandigarh, India Energy and Environment Unit, Institute of Nanoscience and Technology, SAS Nagar, Punjab, India e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Acharya, N. K. Singhal (eds.), Nanosensors for Point-of-Care Diagnostics of Pathogenic Bacteria, https://doi.org/10.1007/978-981-99-1218-6_3

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Keywords

Surface plasmon resonance · Biosensors · Bacteria · Refractive index

3.1

Introduction

Illnesses caused by bacteria are a health menace across the globe, which inflicts a huge burden on any nation’s economy. There are several classes of pathogenic bacteria that can cause infectious diseases by directly or indirectly contaminating food, water, and soil. The analysis of bacteria in different samples has become an important task to monitor the quality of food and water and to safeguard the supply chain quality. A large number of techniques are used for the detection of pathogenic bacteria. Conventional methods like enzyme-linked immunoassay (ELISA) (Bolton et al. 2019) and polymeric chain reaction (PCR) (ALVES et al. 2012) very much dominate the testing practices. Alternatively, to meet the demands of low-cost, portable, and rapid detection testing, various sensor systems have been developed, which primarily are based on principles of piezoelectric, colorimetric, electrochemical, and optical transduction technologies (Bu et al. 2019; Cesewski and Johnson 2020; Shahbazi et al. 2018; Zheng et al. 2019). Amongst optical transduction-based techniques for bacteria detection, surface plasmon resonance (SPR) methods are one of the most sensitive and accurate options (Park et al. 2022). The inherent advantages of SPR sensing methods include their real-time monitoring capability, highly sensitive interaction of bioreceptors with analytes, non-invasiveness, and label-free format (Dudak and Boyacı 2009; Ritzefeld and Sewald 2012; Welford 1991). The SPR technique provides the benefits of direct and label-free detection that basically relies on the measurement of change in the refractive index value when binding of the target with analyte takes place. The specific binding of the target analyte on a metallic sensor surface (attached to a biomolecular recognition elements) is investigated by resonantly excited surface plasmons. These modes of surface plasmons originate from the coupled oscillations of charge density and associated electromagnetic field. The phenomenon occurs at a distance up to about hundred nanometres from the metal surface. SPR biosensors have been developed based on the enzymatic reactions and metallic and magnetic nanoparticle assays and in combination with fluorescence spectroscopy.

3.1.1

Prism-Based Surface Plasmon Resonance Sensors

Surface plasmon resonance (SPR) is the result of an interaction between electromagnetic radiation and the free-flowing cloud of electrons within a metal. As a result, electromagnetic waves are induced in the near field region, which under certain specific conditions can cause resonance effects (Kawata et al. 2001). This resonance is significantly affected by the alterations at the surface due to physical conditions. The detection of these change forms the basis of a SPR-based biosensor (Ekgasit

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Fig. 3.1 A schematic of the prism-based SPR-based bioassay

et al. 2004b). To initiate SPR on a sensor surface, the formation of the evanescent field is required at the interface (Yoon and Kim 2007). The evanescent field occurs at the boundary of two materials having different refractive indices. The phenomenon takes place due to the total internal reflection of the electromagnetic radiation and is characterized by the exponential decay of intensity of light at the boundary (Grepstad and Skaar 2011). In the phenomenon, the total internal reflection occurs, and all the light should be reflected from the interface. Most of the photons are reflected from the interface, but a part of the electromagnetic field penetrates to form an electromagnetic evanescent field. If the incoming light is p-polarized at a particular angle and wavelength and incident on a metal-dielectric interface, the evanescent field induces surface plasmon polaritons or simply described as the electromagnetic waves excited within the electron cloud of the thin metal film, e.g. gold, silver, etc. (Ekgasit et al. 2004a). The energy of the incident photons must be diverted to induce these surface plasmon polaritons, and therefore the intensity of reflected light after the interaction must be decreased drastically. This decrease appears as a dip in the reflected light intensity and is generally referred to as the ‘SPR dip’. The surface plasmons at the metal-dielectric interface exhibit both electromagnetic wave and surface charge characteristics, which affect the perpendicular (to the surface) component of the electromagnetic field (evanescent in nature, depicting non-radiative nature of surface plasmons). It causes enhancement near the surface but decays exponentially in both the materials (faster in metal and slower in dielectric) as the distance increases. Figure 3.1. depicts the schematic of the SPR and evanescent field phenomena in a prism-based Kretchmann configuration. The length in the dielectric medium (e.g. the sample buffer) at which the intensity of the evanescent field becomes 1/e times of the initial value is known as the ‘penetration depth’. The penetration depth usually comes out to be half of the wavelength of light used. The penetration depth is also calculated for the metal region, which decides the thickness of metal film required to couple the incident light that excites the surface plasmons. For example, it is 50 nm for gold films (Liu et al. 2014; Shrivastav et al. 2021). Most of the commercial SPR instruments use a light source of a wavelength range of 600–800 nm; therefore, the penetration depth comes out to be 300–400 nm. The angle at which the SPR occurs depends upon the

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refractive index of the surrounding medium. The refractive index is altered as the macromolecules are adsorbed to the surface. There is a linear relationship between the amount of analyte bound to the surface and the SPR angle. Depending on different configurations, SPR biosensors measure the SPR dip by recording the change in SPR angle (angular interrogation), intensity changes, or wavelength shifts (spectral interrogation) (Shrivastav et al. 2021). The usual strategy for sample measurement involves the flow or passing over of a sample buffer on to a sensor chip which contains specific ligands. The interactions between the sample and sensor chip take place, and the SPR angles are recorded for different concentrations. For different samples, the chips with specific receptor ligands are available in the market, and accordingly, SPR responses can be obtained for a variety of sample-receptor interactions. The interaction of sample with ligand (e.g. aptamers, antibodies) happens in the near vicinity (~10 nm) because of the small size of the attached ligand. This interaction may happen at distance of about few hundreds of nanometres and leads to affect the SPR angle as the evanescent field decays with distance. Generally, the SPR is unable to detect the bio-interactions beyond 600 nm. The resonance wavelength and the angle of incidence of light for the SPR also vary with the amount of target binding happening at the interface. Since the light does not interfere with the sample, it is possible to analyse various categories of samples including food and human serum. This makes SPR a ubiquitous methodfinding application in various fields such as in food safety, drug development, and environment monitoring (Dostálek and Homola 2006; Ma et al. 2021; Narayan and Carroll 2017).

3.1.2

Optical Fibre-Based Surface Plasmon Resonance Sensors

In the case of the optical fibre SPR sensors, the prism is replaced by the core of an optical fibre. The development of SPR optical fibre sensors began in the early 1990s. The first study on one such sensor was reported by Jorgenson and Yee (Jorgenson and Yee 1993). This technique has been extensively used to detect analytes like pH, temperature, urea, glucose, different kinds of pollutants in water and environment, and various gases. Some of the advantages of the SPR optical fibre sensors (SPR-OF) include a small core diameter (~ μm), capability of analysing very small quantities of the sample, capability of online monitoring, and possibilities of remote sensing. In a SPR-OF sensor, a small portion of clad from the fibre is removed, and a thin metal layer is coated. The analyte to be sensed surrounds the metal layer. Just like the conventional SPR setup, a SPR-OF sensor has four main parts: (i) analyte, (ii) receptor, (iii) transducer, and (iv) detector. The receptor is immobilized on gold film or modified gold film via different chemistries. In an optical fibre, the light propagates through the phenomenon of total internal reflection (TIR), and the evanescent wave of the propagating ray excites the surface plasmons (Fig. 3.2). The wavelength dependence of the refractive index (n1) of a silica core optical fibre is given by the following Sellmeier dispersion relation:

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Fig. 3.2 Schematic of a surface plasmon-based optical fibre sensor

n1 ð λ Þ =

1þ

a1 λ 2 a2 λ 2 a3 λ 2 þ þ λ2 - b21 λ2 - b22 λ2 - b23

ð1Þ

where a1, a2, a3, b1, b2, and b3 are the Sellmeier coefficients and λ is the wavelength (in μm) of the light propagating in the medium. The dispersion relation of the metal layer is given by the Drude model, according to which the dielectric constant of a metal is given by: εm ðλÞ = εmr þ iεmi = 1 -

λ2 λ2 λ2p ðλc þ iλÞ

ð2Þ

where λp and λc are the plasma and collision wavelengths, respectively. The values of the characteristic wavelengths for different metals are available in the literature. There may be instances when multiple layers of different metals are coated on the optical fibre, and in such cases, the dispersion relations for all the different layers must be taken into consideration. In a typical SPR-OF sensor setup, the unpolarized light is introduced into the fibre. It may be noted that only the transverse magnetic (TM) mode of the light excites the surface plasmons. This is because of the cylindrical geometry of the fibre wherein it is not possible to maintain the polarization of the incident light. Therefore, only the component of E-vector of the light which is perpendicular to the core-metal interface is used to excite the surface plasmons at the metal-sensing medium interface. As frequency and wave-vectors of the excitation wave and surface plasmon wave are matched, the resonance condition is obtained. At the resonance condition, the maximum incident energy is transferred to the surface plasmons, and a sharp dip is obtained in the spectrum of the transmitted output power. Since an unpolarized light is used for the excitation of surface plasmons in the fibre-optic SPR sensor, the transmitted power at the output end of the fibre will be the sum of the affected perpendicular polarization (TM-polarized) corresponding to SPR and the unaffected polarization (TE-polarized). The next subsections of this chapter cover the examples of the application of SPR methods for the detection of pathogenic bacteria. As such, in most of the SPR-based

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methods, the performance is compared with commercially available methods like enzyme-linked immunosorbent assay (ELISA) and PCR analysis.

3.2

SPR-Based Analysis of Bacteria

3.2.1

E. coli

Escherichia coli (E. coli) is one of the most common and diverse bacteria. These are found in environment samples like food and water. E. coli is also found in the intestines of humans and certain other warm-blooded animals. Most strains of E. coli are harmless in nature, and in fact some strains are said to be good for health. The presence of E. coli is helpful in producing vitamin K and vitamin B12; it also maintains a protective space in the gut for other useful bacteria. Some strains of E. coli are known to be pathogenic and reported to cause infections, which lead to complications like diarrhoea, respiratory illness, urinary tract infections, pneumonia, etc. Shiga toxin-producing E. coli (STEC), E. coli O157, and enterotoxigenic E. coli (ETEC) are known as causes of diarrheal illnesses. The detection of such harmful strains of E. coli is considered very significant to screen various samples that are consumed daily by our society. A portable SPR biosensor for the detection of E. coli O157:H7 has been evaluated alongside the enzyme-linked immunoassay technique (ELISA). This SPR method was found to show four orders higher sensitivity than the ELISA kit (Wang et al. 2016). In particular, the ELISA technique can give false-positive results when the quantity of the above bacteria is too low, such as in dairy and meat products. In the SPR method, the bacteria-specific antibody was covalently attached via mercaptopropionic acid (MPA) over the gold surface. For regeneration of the gold surface, a solution of 0.1 M NaOH has been proposed, which also does not affect the binding properties of gold. The above-discussed SPR sensing technique delivered a detection limit of 1.87 × 103 CFU/mL (Wang et al. 2016). Recently, the SPR technique has also been coupled with a smartphone to design a biosensor for E. coli (Wen et al. 2022). The principle of this method is based on the phenomena of change in colour of gold nanoparticles from red to grey as sodium chloride is added. Interestingly, if E. coli is present in the sample, it reacts preferentially with the gold nanoparticles, and no change in the colour is observed. The presence of bacteria protects the sodium chloride to react with gold nanoparticles. Thus, the plasmonic properties of the gold nanoparticles allow a simple way of detecting the presence of E. coli (Wen et al. 2022). The schematic representation of the above smartphone-based sensing platform is presented in Fig. 3.3. The whole process included the incubation of bacterial suspensions with a gold nanoparticle (AuNP) colloid to perform the colour development (a and b). The pictures of the coloured bacteria/AuNP mixtures were captured with a smartphone, and the RGB signal was processed with an Android app. The limit of detection of the above simple method was 8 × 104 CFU/mL (Wen et al. 2022).

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Fig. 3.3 A schematic of the smartphone-based plasmonic sensing of E. coli (Wen et al. 2022)

A tail protein J from phage lambda has been reported as the sensing element for the SPR-based detection of E. coli K-12 (Shin and Lim 2018). First, the N-terminus of the tail protein J fragment was attached to a (His)6-tag. The purified protein was estimated with a size of 38 kDa with SDS-PAGE technique. It was then overexpressed, purified, and finally characterized using anti-His monoclonal antibodies. Different techniques like ELISA, dot blot, and microscopy were used to determine the specificity of the above probe to E. coli K-12. The SPR phenomenon was then used to generate the signals from the above 6HN-J-functionalized SPR biosensor. The biosensor offered a rapid and label-free detection of E. coli K-12 from 2 × 104 to 2 × 109 CFU/mL with a detection limit of 2 × 104 CFU/mL (Shin and Lim 2018). The crossed surface relief gratings can be used to enhance the evanescent electric field at the sensor surface. The system includes two orthogonally superimposed gratings, delivering a unique way of plasmonic energy exchange. Based on this, a sensor has been reported for the rapid and label-free detection of uropathogenic E. coli (UPEC) in PBS and human urine samples (Nair et al. 2018). This sensor worked within a concentration range of 103 to 109 CFU/mL and a detection limit of 100 CFU/mL. The detection limit parameter was three orders of magnitude lower than the recommended clinical limits for diagnosis of urinary tract infections. A SPR biosensor being benefited with low fouling has been proposed for the sensitive detection of pathogenic bacteria in food samples (Fig. 3.4) (Vaisocherová-Lísalová et al. 2016). For this, gold layer was functionalized with poly(carboxybetaine acrylamide) (pCBAA) followed by the attachment of

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Fig. 3.4 Scheme for the assay of bacteria on poly(carboxybetaine acrylamide)-modified gold SPR chip (Vaisocherová-Lísalová et al. 2016)

antibodies. The incubation of the above sensor with food samples allowed the capture of bacteria. The pCBAA monolayers were found helpful to avoid fouling as complex food samples were analysed. The sensor could detect E. coli O157:H7 in hamburger and cucumber samples with excellent values of sensitivity and specificity. The detection limits were determined to be 57 and 17 CFU/mL for hamburger and cucumber samples. Typically, SPR methods for the detection of bacteria allow the analysis at concentrations >103 colony forming units (CFU) per mL. As such, the attainment of even low detection limits is required for several harmful pathogens. SPR methods face limitations when there is a small change in the refractive index as analyte bounds to the surface or slow diffusion-driven mass transfer takes place from the sample to the sensor surface. In order to design amplification strategies, alternate types of SPR sensors have been suggested utilizing the localized surface plasmons on the nanostructured metallic surfaces (Wang et al. 2012). The long-range surface plasmons (LRSPs) propagate along the thin metal films, and their utilization offers the designing of high-resolution SPR biosensors. LRSP modes encounter fewer losses compared to the regular surface plasmons, and hence it is possible to obtain much accurate measurements in the refractive index variations. The profile of LRSP field can also be tuned, which allows to probe to higher distances from the metal surface than the regular surface plasmons. This is particularly advantageous for the analysis of large samples, like bacterial pathogens. In one of the studies, the gratingcoupled LRSPs were combined with magnetic nanoparticles (Fig. 3.5) (Wang et al. 2012). The use of the magnetic nanoparticles facilitated a faster delivery of the analyte to the sensor surface. They further helped in amplifying the refractive index changes upon the capture of the target analyte, i.e. E. coli O157:H7. This sensor setup allowed the detection of low concentrations of bacteria (50 CFU/mL). Apart from the standard prism-based SPR instruments, the use of optical fibres has also been gaining prominence due to portability. An optical fibre surface

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Fig. 3.5 SPR biosensor setup with magnetic nanoparticle enhanced LRSP for detection of E. coli (Wang et al. 2012)

plasmon resonance (OFSPR) sensor has been reported recently for E. coli O157:H7 in water and juice samples (Fig. 3.6.) (Zhou et al. 2018). In this study, an antimicrobial peptide (Magainin I) was used as the recognition element, while a composite material of silver nanoparticles with reduced graphene oxide was used for signal amplification. The nanocomposite was coated over the optical fibre, which was then covered with a gold film. Subsequently, Magainin I was immobilized on gold film to selectively capture the bacteria. As the analyte (E. coli O157:H7) was introduced to the sensor, it resulted in a wavelength shift of the SPR absorption peak, which exhibited a linear pattern against varying concentrations of the target bacteria (1.0 × 103 to 5.0 × 107 CFU/mL). A detection limit of 5.0 × 102 CFU/mL was reported. In OFSPR biosensor format, the application of layers of two-dimensional nanomaterials over the gold film can improve the penetration depth of the excitation light, thereby facilitating a better coupling of plasmon. In one of the studies, molybdenum disulphide (MoS2) nanosheets were adhered on to a OFSPR immunosensor surface (Fig. 3.7) (Kaushik et al. 2019). This biosensor was then used for the detection of E. coli. The monoclonal antibodies against E. coli were absorbed onto the MoS2 layer via hydrophobic interactions. The OFSPR immunosensor was found to have specificity, and it could deliver the detection from 1000 to 8000 CFU/mL with a detection limit of 94 CFU/mL.

3.2.2

Tuberculosis

Mycobacterium tuberculosis causes tuberculosis (TB). This bacterium commonly attacks the lungs. However, the TB bacteria can also attack other parts of the body

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Fig. 3.6 A schematic of the optical fibre SPR sensor for E. coli O157:H7 (Zhou et al. 2018)

Fig. 3.7 Design of a MoS2 coated optical fibre sensor for E. coli (Kaushik et al. 2019)

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also, e.g. kidney, spine, brain, etc. Since not all the infections by TB bacteria result in sickness, two TB-related conditions have been categorized: (i) latent TB infection (LTBI) and (ii) TB disease. Timely diagnosis and treatment of TB disease are critical to reduce the chances of severity and fatalities. The development of portable sensors for TB bacteria is an important healthcare activity. SPR setup, consisting of SensiQ Discovery two-channel manual SPR platform, has been used along with S2k chips (Luna-Moreno et al. 2019). The sensor was applied for the detection of Ag85 protein, which is a major secretory product of M. tuberculosis. The chips were modified by the chemical attachment with Ag85 antibodies. A portable SPR sensor prototype was developed, integrating the connection and mounting of S2k chips. The sensor was completed with the aid of a miniature detector device, microfluidic peristaltic pumps, electromagnetic valve, buffer container, and sample containers. The microfluidic system had a polycarbonate flow cell, which connected with a S2k chip for the analysis of tuberculosis. The sputum samples of the TB patients were investigated. The detection of Ag85 protein was achieved with a detection limit of 1 × 104 CFU/mL, which is comparable to other methods of bacterial detection in sputum samples. Two-dimensional (2D) materials have been recently recommended to increase the sensitivity of optical fibre SPR (OFSPR) biosensor and detection of TB disease (Kaur et al. 2022). The sensor included a probe made up with multimode fibre core, polymer clad, Ag as the plasmonic metal, and a layer of 2D material, e.g. carbon nanotubes (CNT), molybdenum disulphide (MoS2), and antimonene. The influence of the CNT, MoS, and antimonene was studied. The above sensor showed improved sensitivity with increasing refractive index (RI) of the TB sample. The 2D nanomaterial-based SPR fibre sensor could detect TB in the range of 1.343 RIU– 1.351 RIU.

3.2.3

S. Typhimurium

Salmonella enterica serovar typhimurium is a facultative anaerobe (Gram-negative), which is known to cause systemic infections in mice, resembling the typhoid fever from S. enterica serovar typhi in humans. The infection by Salmonella typhimurium can lead to self-limiting gastroenteritis in humans. Even in current times, infections from various species and serovars of the genus Salmonella threaten healthcare particularly in the developing countries. Typhoid fever can cause symptoms like headache, stomach pain, sustained high fever, and neurological abnormalities. Therefore, sensor development for this infection is considered a critical research activity. The contamination of leafy vegetables by S. typhimurium has caused many disease outbreaks. SPR assays have been developed for the detection of S. typhimurium in leafy vegetables by using monoclonal antibodies which were specific to it (Bhandari et al. 2019). For the study, samples of romaine lettuce were spiked with S. typhimurium at different concentrations between 0.9 and 5.9 log CFU/g. SPR experiments were run in three formats, i.e. one-step sandwich assay, direct assay, and sequential two-step sandwich assay. The pre-incubation one-step

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sandwich assay provided enhanced signals and ability to detect lower number of Salmonella than the other two types of assays studied. In the past decades, bacteriophages have become popular as the alternative sensing elements for the detection of pathogens. Bacteriophages are abundant in nature and show stability even in harsh environments. They also are known for their high specificity toward many host bacteria. Phages recognize the target hosts via binding of the receptors present at the tail proteins of the bacterial surface. These tail proteins are highly specific. SPR chips have also been used for the development of bacteriophage-based sensors. In one of the studies, a full-length tail protein from phage Det7 was immobilized over the CM5 chip via amine coupling (Hyeon et al. 2021). This formed as a sensing platform for the detection of S. typhimurium in the range of 5 × 104 to 5 × 107 CFU/mL. The purified tail protein with a molecular weight of 75 kDa exhibited specific binding to the host S. typhimurium, also making it specific in presence of E. coli. The detection of S. typhimurium has been reported with a Ω-shaped localized surface plasmon resonance optical fibre (LSPROF) biosensor (Xu et al. 2018). This biosensor has been advocated for its sensitivity and real-time label-free bacteria analysis. The effect of the unique geometry was outlined as a major factor for achieving an outstanding sensitivity. For the preparation of the sensor, the Ω-shaped optical fibre was functionalized with amino silane so as to allow the adsorption of AuNPs. Next, the thiol-modified aptamer DNA aptamer was bound to the sensor surface. The refractive index (RI) sensitivity of the above Ω-shaped LSPROF probe was 14 times better than the straight-shaped probe. The enhancement in the RI sensitivity was associated with the increase in the bending area. Aptamers were immobilized on the LSPROF probe for the specific capture of Salmonella typhimurium (Fig. 3.8). An intense change of the absorption peak was realized as the sensor was investigated from 5 × 102 to 1 × 108 CFU/mL bacteria concentration (Xu et al. 2018). The detection limit was 128 CFU/mL, and the sensor was also applicable in a chicken sample.

3.2.4

Miscellaneous

V. parahaemolyticus is known as a gram-negative bacterium, which is found in marine and estuarine environments. The pathogenicity of V. parahaemolyticus can emerge from the consumption of contaminated raw seafood (e.g. shellfish and mussels). This bacterium thrives in relatively warm water and less saline areas. Ill effects may include watery or bloody diarrhoea, nausea, vomiting, abdominal cramps, and fever. An aptamer-based SPR biosensor has been reported for the detection of V. parahaemolyticus (Ahn et al. 2018). This aptamer-based sensor was also evaluated for specificity against E. coli, L. monocytogenes, S. sonnei, and V. fischeri. The limit of detection for V. parahaemolyticus was observed to be 4 × 108 CFU/mL. Shigella bacteria are reported to cause an infection known as shigellosis. Shigella infection is associated with diarrhoea (sometimes bloody) and other issues like fever

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Fig. 3.8 Selectivity of (LSPROF) biosensor for Salmonella typhimurium in co-presence of E. coli, S. enterica, S. aureus, and Shigella (Xu et al. 2018)

and stomach cramps. People with critical illnesses and those with low immunity are susceptible to Shigella bacteria-related health issues. Some SPR sensors have been proposed for the detection of Shigella bacteria. The Ipa H protein and effector IpaH gene have been reported in multiple copy elements in plasmids and chromosomes where Shigella is in contact with epithelial cells. DNA aptamers, highly specific to the abovementioned species, have been sequenced and functionalized on gold SPR film for achieving the sensing of proteins in the range of 0–100 ng/mL (Song et al. 2018). Dothideomycete fungus Pseudocercospora fijiensis is a cause of Black Sigatoka or also known as black leaf streak disease. It is a significant foliar disease occurring in banana worldwide. The management of the above disease requires applications of fungicide, which is a burden on economy as well as the environment. Some SPR-based sensors have been reported for detection of P. fijiensis (Luna-Moreno et al. 2019). A covalent immobilization of polyclonal antibodies (anti-HF1) was done over a gold chip via a self-assembled monolayer of alkanethiols employing EDC/NHS method to form a SPR sensor for P. fijiensis (HF1 protein). The detection of this protein at an early stage in banana leaf extracts can indicate the chances of Black Sigatoka disease. The above sensing method was claimed to have no need of extraction steps (e.g. dilution/centrifugation/purification), which are otherwise invariably needed during the analysis with ELISA and PCR. The above SPR-based method was characterized with a detection limit of 11.7 μg/mL with sensitivity of 0.0021 units of reflectance per ng/mL. The analysis was possible from 9.1 to 122 μg/mL antigen concentration (Fig. 3.9) (Luna-Moreno et al. 2019).

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Fig. 3.9 Real-time SPR sensograms for different concentrations of HF1 (Luna-Moreno et al. 2019) [25]

Various nanomaterials, viz. zinc oxide (ZnO) and graphene, have also been utilized to improve the performance of the SPR biosensor. One such example includes the sensor for Pseudomonas and Pseudomonas-like bacteria (Kushwaha et al. 2018). In this design, a prism (BK-7 glass) base was coated with ZnO. It was further modified with gold layer, graphene, and different recognition layers. Water was used as a sensing medium. The above biosensor containing hybrid structures of graphene, Au, and ZnO was reported to yield an enhanced sensitivity for pseudomonas like bacteria. The presence of ZnO was reported helpful for attaining a larger shift in the resonance angle. The above biosensor showed a good sensitivity of 187.43 deg./RIU.

3.3

Conclusion and Future Outlooks

The utility of SPR biosensors for the analysis of pathogenic bacteria is now a wellestablished fact. Gold chip-based SPR methods have always been in the forefront. Highlights of the SPR biosensors include their rapid and real-time response, specificity, sensitivity, and minimum sample preparation/enrichment. The quantification

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of bacteria with SPR methods has been realized via many formats. Conventional SPR gold surfaces have been frequently used by modifying them with various categories of biorecognition elements, such as antibodies and DNA aptamers. In further developments, SPR methods have also been integrated with proper microfluidics, magnetic nanoparticles, etc. to attain greater sensitivities. As the SPR method is sensitive to changes in surface conditions, it also faces certain limitations. The refractive index changes tend to be proportional to the molecular weight of the analyte which binds to the surface. For analytes with molecular weights of lesser than 200 Daltons, a high binding capacity is required to provide sufficient material load to the surface for enabling the detection. The size of the particles that can be detected is further limited as the penetration of the evanescent field in the buffer remains in the range of 300–400 nm. The detection of larger analytes may not result in a linear change in the refractive index. Some macro-scale changes during the experiments, e.g. temperature, can also affect the measurements. New formats for the SPR biosensors for bacteria detection are being explored. The use of optical fibres is one of the interesting approaches. The translation of SPR-based Kretschmann configuration to the optical fibre counterparts allows certain unique features. Due to the flexibility of the fibre and grating facilities, several geometries and types of SPR optical fibre biosensors are being explored. These include simple gold-coated fibre, bent fibres (e.g. Ω-shaped, U-shaped), tilted fibre Bragg gratings, etc. Even the etching of the fibre can be controlled so as to attain special shapes like D-fibre. Mostly, multimode fibres are used for chemical and biological sensing because they provide large surface area for interaction, which leads to dynamic sensing range of the analyte with enhanced sensitivities. Further, plasmonic coupling at the optical fibre surfaces can be improved by coating them with nanomaterials. Nanostructure or pattern coatings can induce strong changes in the properties of light travelling through the fibre. Such platforms are promising because of their portability and low cost. As current research trends are suggesting, the future of SPR biosensor is likely to be highly dependent on the integration of gold and other noble metal surfaces with other functional nanostructures such as 2D metal dichalcogenides, graphene, 2D metal-organic frameworks, and 2D metal carbides (MXenes). Graphene is a promising nanomaterial for the above-said purpose due to its versatile properties which strengthen the SP signals. Likewise, other mentioned materials also allow better coupling of plasmons and also facilitate functionality to the sensor surface for the attachment of biorecognition molecules. The use of 2D nanomaterials favours the confinement of surface plasmons to a volume of multiple orders smaller than the diffraction limit of light, which results in a strong light-matter interaction. Acknowledgements Authors are thankful to CSIR India for project grants MLP-2006 and HCL-026 (Task 1.3). We also thank the Director, CSIR-CSIO, Chandigarh, India, for the infrastructure facilities.

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Enzyme-Linked Immunosorbent Assay-Based Nanosensors for the Detection of Pathogenic Bacteria Tanu Bhardwaj and Tarun Kumar Sharma

Abstract

Since its inception, enzyme-linked immunosorbent assay (ELISA) has been one of the promising methods for detecting bacterial pathogens. Although the method suffers from various disadvantages, like long incubation time, high reagent volume requirement, use of expensive equipment, etc., it is widely used due to its specificity, accuracy, and lack of any other better technique. In that perspective, to overcome the drawbacks of this method, research studies are always in place to get a desired and improved version of the ELISA test. In this chapter, we highlight such advancements in the field of ELISA. This chapter begins with the introduction, which covers the employment of ELISA to detect pathogenic bacteria. Further, we shed light on the historical journey of ELISA along with the most significant improvements that brought a major wave in the diagnosis industry. Then, the focus of the chapter shifts toward the new technologies working to improve ELISA tests, i.e., the use of nanosensors to overcome the drawbacks of conventional ELISA for the detection of pathogenic bacteria. Moreover, a special section has been illustrated in the chapter to discuss the utilization of microfluidics with nanosensors to achieve a portable, equipmentfree, and cost-effective ELISA test. Keywords

ELISA · Nanosensors · Microfluidic chip · Bacteria · Pathogens

T. Bhardwaj (✉) · T. K. Sharma (✉) Department of Medical Biotechnology, Gujarat Biotechnology University, Gujarat International Finance and Tec (GIFT) City, Gandhinagar, Gujarat, India e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Acharya, N. K. Singhal (eds.), Nanosensors for Point-of-Care Diagnostics of Pathogenic Bacteria, https://doi.org/10.1007/978-981-99-1218-6_4

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4.1

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Introduction

Infectious disease is an illness that occurs due to the presence and growth of a pathogenic microorganism (pathogen) in a host organism, i.e., the patient. The pathogen can be a virus, bacteria, fungi, protozoa, multicellular parasite, and prion. These pathogens are transmitted to other individuals by various means, like physical contact, contaminated food, body fluids, objects, airborne inhalation, water, vectors, etc. (Kumar et al. 2012). If we focus on bacteria, then this is absolutely true that they are not always pathogenic. Most bacterial species are harmless and help in balancing the environment where we live (Doron and Gorbach 2005). Approximately less than 1% of bacteria cause diseases in people. Human-infecting pathogenic bacteria are Bacillus anthracis, Bacillus subtilis, Brucella abortus, Campylobacter spp. (e.g., C. jejuni), Clostridium botulinum, Escherichia coli O157:H7, Legionella pneumophila, Listeria monocytogenes, Mycobacterium tuberculosis, Neisseria meningitidis, Salmonella typhimurium, Staphylococcus aureus, Yersinia enterocolitica, Yersinia pestis, Enterococcus faecium, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, etc. (Byrne et al. 2009). Although bacterial infections are easy to tackle, the results of bacterial resistance to antimicrobials can be deadly (Egli et al. 2002; Babaie et al. 2021). Hence, they should not be treated lightly. For instance, the main causing agents of food- and water-borne diseases are bacterial pathogens (Doron and Gorbach 2005; Zhang et al. 2021). Appropriate timely diagnosis of such bacterial infections is mandatory to control/prevent the spread and treat the disease. After an uninterrupted search for effective diagnostic tools for bacterial infections and countless efforts of research communities, the arena of diagnostics evolved and reached to a stage where diagnostic problems can be addressed to a great extent. Historically, classical methods for detecting bacterial infections were preferably microscopy and cell culture (Doron and Gorbach 2005; Srivastava et al. 2018; Bhardwaj et al. 2022). As a consequence of limitations, such as tedious preparations, longer turn-around time, poor sensitivity (in some cases), etc., the methods were taken over by biochemical (immunoassay/colorimetry-based) and advanced biotechnology (molecular genotyping, DNA microarray, etc.) methods (Srivastava et al. 2018; Bhardwaj et al. 2022). These methods depend on the detection of various pathogen-related proteins, toxins, nucleic acids, and antibodies for the diagnosis of bacterial infections (Bhardwaj et al. 2022). Though these methods are leading the market due to rapidity and better sensitivity (compared to classical methods), the requirement of sophisticated equipment and proprietary reagents limits their prominence in low- and middle-income countries. If we focus on biochemical immunoassay-based diagnosis, then enzyme-linked immunosorbent assay (ELISA) has always been one of the extensively used methods for the detection of pathogenic bacteria to diagnose an infectious disease. The method comprises detecting antibodies developed against the pathogen, surface markers of pathogens, or toxins produced by the pathogens using antigen-antibody interactions (Campbell et al. 2021). The most commonly reported enzymes in ELISA are peroxidases, glucose oxidase, alkaline phosphatase, catalase, luciferase,

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Fig. 4.1 A schematic diagram to show different types of ELISA (a, b, c, and d) and replacement of ELISA with biosensors (e) and nanosensors (f). (a) Direct ELISA. (b) Competitive ELISA. (c) Indirect ELISA. (d) Sandwich ELISA. (e) ELISA-based biosensors (immunosensors). (f) ELISAbased nanosensors. Created with BioRender.com

etc. (Cristea et al. 2015). Although multiple versions (Fig. 4.1a–d) of ELISA are available to achieve better sensitivity, specificity, and accuracy, still, the major limitations for this method are sensitivity, long turn-around time, requirement for highly trained professionals, and need for expensive equipment (Yadav et al. 2020; Sung and Seok Heo 2021). Due to these limitations, diagnostics is open for better alternatives, which can promise simple, fast, and sensitive detection of bacteria (Singhal et al. 2021). A biosensor is a well-studied detection platform for analyzing biological processes, like antigen-antibody interactions, DNA interactions, enzymatic interactions, etc. (Naresh and Lee 2021). Due to the involvement of antigen-antibody interaction in ELISA-based biosensors (Fig. 4.1e), they are known as immunosensors (Cristea et al. 2015). In contrast to the conventional plate-based ELISA technique, these immunosensors are reported for their better performance in terms of sensitivity, rapidity, inexpensiveness, easy operation, and requirement of low sample/reagent volumes (Dupont 2022). Further, to advance sensitivity, specificity, simplicity, and limit of detection (LOD), nanomaterials are incorporated into biosensors to bring a better performing sensor called nanobiosensor (Fig. 4.1f) (Beltrán-Pineda et al. 2021). The ELISA-based nanosensors arrive in the category of nanobiosensors/ nano-enzyme immunosensors due to the presence of antigen or antibody as the biomolecular recognition element (BRE). Hence, they can be used interchangeably in the chapter. The reported nanostructured materials employed in the fabrication of nanobiosensors are nanowires, carbon nanotubes (CNTs), thin films, nanoparticles

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(NP), nanodots, nanocomposites, and polymer nanomaterials (Hu et al. 2017; AbdelKarim et al. 2020). In this chapter, we shed light on the evolution of ELISA along with the most significant improvements that brought a major wave in the diagnosis industry. Then, the focus of the chapter shifts toward new technologies working to improve ELISA tests, i.e., the use of nanosensors for overcoming the drawbacks of conventional ELISA for the detection of pathogenic bacteria. Moreover, a special section has been added to discuss the utilization of microfluidics with nanosensors to achieve a portable, equipment-free, and cost-effective ELISA test.

4.2

Evolution of ELISA

The idea of ELISA in the mind of inventors arrived after the occurrence of major events of the invention of immunofluorescence and radioimmunoassay. In 1941, Albert H. Coons and his colleagues were the first who labeled antibodies with fluorescent dyes to determine an antigen in tissue sections (Coons 1961). Then, in 1960, instead of fluorescent dye, radioisotope labels were used to measure endogenous insulin in plasma by Yalow and Berson (Yalow and Berson 1960). These two events became the building block of immunoassays (enzyme immunoassay (EIA)), which were invented in 1971 by two separate research groups, i.e., Engvall and Perlmann (ELISA) and Van Weemen and Schuurs, for two different target antigens (Aydin 2015). Weemen and Schuurs tagged horseradish peroxidase (HRP) with human chorionic gonadotropin (HCG) (antigen) and immobilized HCG antibodies on cellulose for detection of HCG in urine (Weemen and van Weemen and Schuurs 1971). Engvall and Perlmann on the other hand determined the level of IgG in rabbit serum using alkaline phosphatase-linked antibodies (Engvall and Perlmann 1971). This technique is now known as direct ELISA (Fig. 4.1a), in which an enzymelabeled antigen or antibody enables the identification of an immobilized antibody or antigen on the surface of an ELISA 96-well plate (Aydin 2015). In the method, the target antibody or antigen is immobilized on the plate, followed by blocking with other proteins (bovine serum albumin/skimmed milk) to prevent non-specific adsorption of other proteins present in the sample. Then, an enzyme-labeled antigen or antibody is added, which gives color (colorimetric) proportional to the concentration of the target on the addition of a specific substrate (Sakamoto et al. 2018). Mostly, the method is suitable for high-molecular-weight antigens and has low sensitivity (Aydin 2015; Akash 2016; Sakamoto et al. 2018). This type of ELISA is rapid but less stringent; therefore, it can be applied for rapid applications, which do not require higher accuracy. Then, to improve the sensitivity of the methods, different versions of ELISA were introduced. For instance, competitive ELISA (Fig. 4.1b) was developed by Yorde and his coworkers in 1976 (Yorde et al. 1976). In this ELISA, the wells are coated with antigen-specific antibodies or antibody-specific antigens, which are then reacted with the sample and labeled antigens or antibodies (blocking is necessary for this type of ELISA too). A competition occurs between tagged and untagged (sample) antigens or antibodies

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for binding with their immobilized counterpart. With addition of substrate, a low concentration of antigens or antibodies in the sample leads to the generation of high absorbance and vice versa (Aydin 2015; Akash 2016; Sakamoto et al. 2018). This method, too, is preferred for the detection of macromolecules, as enzyme-conjugated low-molecular-weight targets can stay unrecognized by the immobilized antibody or antigen (Sakamoto et al. 2018). Following, sandwich ELISA (Fig. 4.1d), the most sensitive version of ELISA (2–5 times more sensitive than other ELISAs) was introduced in 1977 by Kato and his coworkers (Kato et al. 1977). In this method, wells are coated with primary/capturing antibodies for catching antigen on the surface of the plate, followed by a blocking step. Further, secondary/detection antibodies labeled with enzyme are added, which leads to the generation of signal on the addition of substrate (Aydin 2015; Akash 2016). Although dependence on two antibodies makes the method highly specific, this method demands money, long assay time (as an additional step is required), and preparation of two different antibodies (labor) (Sakamoto et al. 2018). Another version of ELISA was developed later in 1978 by Lindström and Wager, called indirect ELISA (Fig. 4.1c) (Lindström and Wager 1978). This method is used for the detection of antibodies in a sample (Sakamoto et al. 2018). The reason for calling this method indirect is with the addition of tagged secondary antibodies for the detection of an isotope of primary antibodies, which are in complex with the coated antigens (Aydin 2015; Akash 2016; Sakamoto et al. 2018). This method is more specific in comparison to direct ELISA as the conjugated secondary antibody is involved in the detection. Presently, a combination of different types of ELISA is also used for achieving more sensitivity and specificity, like indirect competitive ELISA (Sakamoto et al. 2018). In this method, the well plate is coated with the target antigen, followed by blocking. Further, free target antigens along with primary antibodies are added simultaneously, and competition is created between immobilized and free antigens for primary antibodies. The primary antibodies bound to immobilized antigens are detected using enzyme-conjugated secondary antibodies. Numerous other strategies have been integrated with ELISA for improving the sensitivity of the tests, like fluorescent ELISA, chemiluminescent ELISA, electrochemical ELISA, surface-enhanced Raman scattering (SERS) ELISA, plasmonic ELISA, pH-meter-based ELISA, glucose meter-based ELISA, digital ELISA, etc. (Huang et al. 2016; Liang et al. 2016). In fluorescent ELISA, the substrate used for the colorimetric signal is replaced with a fluorescent signal generating substrate (Zhan et al. 2016). The limitation of this substrate is the photobleaching effect, which impacts the reproducibility of the test (Huang et al. 2016). To overcome this issue, chemiluminescence signal generating substrate, like luminol, is used in chemiluminescent ELISA (Vidziunaite et al. 1995). These two modified versions of ELISA improved the LOD significantly (Vidziunaite et al. 1995). In electrochemical ELISA, the substrate creates an electrochemical signal on reaction with enzymelinked antigen/antibody, like 3,5,3′,5′-tetramethylbenzidine (TMB). TMB being a chromogenic dye can be used as an electrochemical substrate along with colorimetric analysis (Lee et al. 2011). In SERS ELISA, Raman reporters, like 3,3′-diethylthiatricarbocyanine iodide (DTTC), are used as substrate with

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nanostructures of noble metals as signal enhancers for Raman signal generation on reaction with enzyme-linked antigen/antibody. Raman reporters not only increase sensitivity but also have less photobleaching effects in contrast to fluorescent substrates and, hence, provide better performance (Hanson et al. 2016; Smolsky et al. 2017). For further improvement in sensitivity, plasmonic ELISA was introduced (Satija et al. 2016). In plasmonic ELISA, an enzyme (like catalase) was linked to detecting antigen/antibody, which catalyzed the aggregation of gold nanoparticles (AuNPs). This aggregation changed the localized surface plasmon resonance (LSPR) signal in accordance with the concentration of the enzyme (De La Rica and Stevens 2012). Further, 14-times sensitive ELISA, in contrast to optical-type ELISA, was developed by Zhang and his coworkers, which is called pH-meter-based ELISA. In this ELISA, the pH change is created on the addition of substrate in the presence of enzyme-linked detecting antigen/antibody in ELISA, which is measured using a pH meter. For instance, enzyme (glucose oxidase) and substrate (glucose) generated a product (gluconic acid), which varied the pH proportional to the concentration of enzyme (or we can say the target) (Zhang et al. 2016). Similarly, glucose-meter-based ELISA was introduced in invertase- or phosphataseenzyme linked antibody/antigen, which converted sucrose into glucose. The concentration of glucose was then measured using a glucose meter (Xiang et al. 2014). In the most sensitive type of ELISA, called digital ELISA, a single target molecule can be detected using microwells. Firstly, a sandwich-type complex is formed between primary antibody, antigen, and secondary antibody on a bead, which is made to settle in a single-molecule microwell. This gives a dot-like structure under the fluorescent microscope with a fluorogenic substrate (Rissin et al. 2017; PérezRuiz et al. 2018). Currently, other biomolecules, like aptamers, which are called rivals of antibodies, are replacing antibodies in ELISA tests (Vivekananda and Kiel 2006; Lavania et al. 2018; Taneja et al. 2020). This new aptamer-based ELISA is known as aptamer-linked immunosorbent assay (ALISA). Aptamers gift better stability, shelf life, uniformity, and an easy labeling process (without affecting specificity) to immunosorbent assays (Kaur et al. 2019).

4.3

Pros and Cons of ELISA

ELISA is a well-known technique finding application in clinics and hospitals all over the globe. It has also been found in the literature that the use of the technique is expanding in other fields, too, like food safety, water analysis, environmental analysis, biotechnology, etc. (Wu et al. 2019). The pros of the ELISA method are as follows: The pros of the ELISA method are: (1) Easy procedure, (2) Highly specific because the working principle is based on antigen-antibody reaction, (3) As radioactive tags or organic solvents are not involved in the analyses, the method is generally safe and eco-friendly, and (4) Cost-effective due to the involvement of low-cost reagents (Sakamoto et al. 2018). Unfortunately, each technique suffers from some cons, and ELISA has too, which are as follows: (1) Requirement of skilled staff and sophisticated equipments, (2) Expensive when it comes to

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preparation of antibodies due to the involvement of costly cell media, (3) The high number of cases of false-positive/false-negative results when blocking is inappropriately done, (4) Antibody instability while transport and inadequate storage, which impacts the performance of antibodies, (5) High sample and reagent volume requirement, (6) Monotonous long analyses (incubation time), and (7) Sensitivity issues (Sakamoto et al. 2018; Wu et al. 2019; Yadav et al. 2020; Sung and Seok Heo 2021). Due to the limitations of ELISA, diagnostics is open to valuable improvements in ELISA, which can promise simple, fast, and sensitive detection of the target analyte.

4.4

Improvement in ELISA Using Nanomaterials

The disadvantages of ELISA, on which research groups are working, are sensitivity, stability, accuracy, and simple operation (Wu et al. 2019). With the entry of nanomaterials (NMs) into ELISA, the traditional ELISA has been improved in many aspects, resulting in the expansion of the application of improved ELISA in research. NMs mostly employed are quantum dots (QDs), carbon dots, nanowires, CNTs, nanorods, nanoplates, nanosheets, nanodisks, thin films, NPs, nanodots, nanocomposites, nanoflowers, nanoballs, nanocones, and polymer nanomaterials (Hu et al. 2017; Abdel-Karim et al. 2020; Bobrinetskiy et al. 2021). It has already been mentioned in the Introduction section that ELISA-based biosensors (Fig. 4.1e) have overtaken the traditional ELISA methods in terms of sensitivity, portability, simplicity, and inexpensiveness. When NMs are incorporated into these ELISA-based biosensors for magnification of the sensor’s performance, then they are known as nanobiosensors/nano-enzyme immunosensors (Fig. 4.1f) (Sharma et al. 2021). In optical ELISA-based biosensors, NMs are demonstrated to improve any of the three parts of ELISA, i.e., adsorbent substrate (for antibody immobilization), the enzyme, or the chromogenic reagent (Wu et al. 2019). The strategy to use NMs involves (1) the use of bioimprints/magnetic nanoparticles (MNPs) as the adsorbent substrate; (2) nanozymic activity of NPs, nanocomposites, and nanosheets; (3) NPs as a carrier for enzyme loading; and (4) analyte-based aggregation/morphological variation in NPs (Liu et al. 2019; Wu et al. 2019). On the other hand, in electrochemical ELISA-based biosensors, the NM is engaged in performing any of the functions, like (1) to increase surface area for immobilization of antibodies and mass transport to generate an amplified signal and (2) carrier of enzyme/redox probe (work as a catalyst) to provide sensitive detection (Bobrinetskiy et al. 2021). NPs (gold and silver) and NMs (carbon-based, fullerene, titanium, silicon oxides) are demonstrated to provide a large surface area for strong adsorption of biomolecules and play a vital role in the stabilization of immobilized biomolecule (Huang et al. 2021; Thakur et al. 2022). Due to the high surface energy of certain NMs, like metal NPs (gold, platinum, and silver), they are known for their strong catalytic effect and are used as a catalyst in sensing. Along with this, NMs, like NPs and nanotubes, are employed for enhancing electron transfer reactions in biosensors (Huang et al. 2021). In a few ELISA designs, NMs can be used to improve more than one part of ELISA together (Wu et al. 2019). Prior to implementation in biosensors,

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these NMs need to be optimized for their performance as per the requirement of the application (Malik et al. 2013).

4.5

ELISA-Based Nanosensors for Detection of Pathogenic Bacteria

In ELISA-based nanosensors for the detection of pathogenic bacteria, or what we call nanozyme-based immunosensors, the basic working reaction is the same, i.e., ELISA, which occurs on the surface of the transducer using NMs. The target analyte can be the bacterial pathogen itself, surface markers of pathogens, or toxins. Majorly used detection methods are electrochemical and optical methods. Following is the illustration of various types of ELISA-based nanosensors for the detection of pathogenic bacteria or potential biomarkers. All the discussed nanosensors are summarized in Table 4.1.

4.5.1

Electrochemical ELISA-Based Nanosensors

In electrochemical ELISA-based nanosensors, change in voltage, current, or impedance is measured in response to an ELISA-based reaction on the surface of a sensor for quantifying the antigen (target analyte). Electrochemical ELISA-based nanosensors are majorly based on amperometric and voltammetric detection. Impedimetric (Leva-Bueno et al. 2020) and potentiometric (e.g., field-effect transistor-based) (Villamizar et al. 2008) detection methods are mostly known for the development of enzyme-free immunosensors; hence, they are not discussed in this chapter. A few examples of electrochemical ELISA-based nanosensors and their working principles are presented in Fig. 4.2. In amperometric detection methods, a voltage is applied to the electrode to investigate a target molecule, and the response is recorded in the form of variation in current proportional to the concentration of the analyte (Bhardwaj 2015). To detect the foodborne pathogen, Listeria monocytogenes (L. monocytogenes), a multiwalled CNT (MWCNT) fiber-based specific and sensitive enzymeimmunosensor, was reported (Lu et al. 2016) (Fig. 4.2a). In the study, HRP-labeled antibody against the bacteria was immobilized on the MWCNT fiber electrode, and the response of the immunosensor was analyzed by amperometry. In the absence of bacteria, a high current peak was observed in the presence of substrate, i.e., hydrogen peroxide (H2O2), due to the release of electrons during H2O2 and HRP reaction. Further, when bacteria were added, the current peak decreased due to hindrance created in electron transfer by the immunocomplex. The LOD of the sensor was 1.07 × 102 cfu/mL. Because of the excellent electrical and mechanical properties and large surface area of MWCNTs, the immunosensor was highly sensitive. For identification of Staphylococcus aureus (S. aureus), Staphylococcal enterotoxin B (SEB) exotoxin produced by the bacteria was electrochemically detected using signal amplifying HRP-nanosilica-functionalized MWCNTs

1. Gold electrodes modified with CNTs and AuNPs 2. Pt-Ni-Cu NCs peroxidase-like activity used for detection Optical ELISA-based Nanosensors

Gram-positive bacteria

Y. enterocolitica

Salmonella

S. enterica

Anti-Salmonella antibodies immobilized on MNPs for capturing the bacteria MWCNTs bound with tyrosinase used for detection instead of enzyme linked secondary antibodies Gold electrodes modified with GQDs

1. Glassy carbon electrode modified with CCLP (calcium cross-linked pectin)-AuNPs 2. AuNP-modified secondary antibodies Screen-printed carbon electrodes deposited with AuNPs

P. aeruginosa

S. pullorum and S. gallinarum

Detecting anti-SEB antibodies were labelled with HRPSiCNTs

Staphylococcal enteroxin B

Sandwich ELISA 1.Antibody (type not specified) 2. Pt-Ni-Cu NC

Sandwich ELISA: Antibody-antibody (type not specified) Sandwich ELISA 1. Monoclonal antibody 2. Polyclonal antibody Indirect ELISA: 1. Polyclonal antibody 2. MWCNTs bound with tyrosinase Direct ELISA: Monoclonal antibody

Sandwich ELISA:Rabbit polyclonal anti-SEB antibodies for both capture & detection Sandwich ELISA: 1. Monoclonal antibody 2. Anti-rabbit IgG antibody

Brandão et al. (2013) Chumyim et al. (2014) Savas and Altintas (2019) Han et al. (2020)

1.95 × 102 cfu/mL 1 × 104 cfu/mL