Enzyme-based Biosensors: Recent Advances and Applications in Healthcare 9811569819, 9789811569814

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Sanjukta Patra Debasree Kundu Manashjit Gogoi   Editors

Enzyme-based Biosensors: Recent Advances and Applications in Healthcare

Enzyme-based Biosensors: Recent Advances and Applications in Healthcare

Sanjukta Patra • Debasree Kundu • Manashjit Gogoi Editors

Enzyme-based Biosensors: Recent Advances and Applications in Healthcare

Editors Sanjukta Patra Department of Biosciences and Bioengineering Indian Institute of Technology Guwahati Guwahati, Assam, India

Debasree Kundu Department of Biosciences and Bioengineering Indian Institute of Technology Guwahati Guwahati, Assam, India

Manashjit Gogoi Biomedical Engineering Department North Eastern Hill University Shillong, Meghalaya, India

ISBN 978-981-15-6981-4 ISBN 978-981-15-6982-1 https://doi.org/10.1007/978-981-15-6982-1

(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 Paper in this product is recyclable.

Preface

Rapid development of science and technology in last few decades, the lifestyle of mankind, and the environment have changed drastically. The changes in human lifestyle and exposure to adverse environment are major causes of large number of non-communicable diseases such as cardiovascular disease (CVD), cancer, and diabetes. CVDs, cancer, and diabetes are the leading non-communicable diseases and responsible for deaths of large number of people globally. Whereas poor hygiene, lack of resources like quality drinking water, food, and medicines to increasing number of populations cause large numbers of infectious diseases. Biosensors have been extensively used for disease detection, diagnosis, human health monitoring, and health management. Enzymes are drawing tremendous attention as biological recognition elements for the development of biosensors due to their high selectivity and specificity towards their substrate. These biosensors help in rapid diagnosis of different diseases and their management in places where access to sophisticated instruments and facilities is limited. In short, biosensors can play a vital role in healthcare management in rural area and resource-limited settings. This book reviews the applications of different enzymatic biosensors in healthcare sector, their challenges, and future scopes. Chapter 1 focuses on the application of different enzymatic biosensors in healthcare sector and how they are helping in managing different diseases. It also gives an overview of existing commercial biosensors available in the market. Chapter 2 reviews how different types of enzymes are entrapped/immobilised in different biological matrices for maintaining their stability and reusability for potential biosensor applications. Chapter 3 highlights different common cardiac biomarkers detecting different cardiac ailments along with their clinical characteristics. The chapter also explains the challenges and future perspectives of enzymatic biosensor platforms used for the diagnosis of heart diseases. Chapter 4 discusses the different types of enzyme-based biosensors based on the type of transducer used and their applications in detecting some of the most prevalent cancer types. The chapter also highlights the various challenges faced in the cancer diagnostics and the future roadmap for improving the performances of biosensors.

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Chapter 5 elaborates different types of enzymatic biosensors for glucose sensing. This chapter also highlights the challenges and future prospects in glucose sensing biosensors. Chapter 6 focuses on several enzymes-based biosensors for detection of pancreatitis and their limitations and future scopes. Chapter 7 provides insight into the different types of prognostic and diagnostic biomarkers associated with gut diseases and applications biosensor for detection of these diseases. Chapter 8 discusses the enzyme-based biosensors for detecting different metabolic diseases and the challenges faced by these biosensors in working in real-world settings. Future scope focusing on the advanced strategies to fulfil unmet clinical needs are also discussed. Chapter 9 presents different existing malarial biomarkers focusing on the proteinbased biomarkers and the application for developing advanced rapid and reliable point-of-care (POC) detection techniques. Chapter 10 elaborates on the significant advancements, scope, and challenges in the application of enzymes on biosensor platforms in the diagnosis of highly communicable infectious diseases like tuberculosis (TB) and neglected tropical diseases (NTDs). Chapter 11 elucidates about different piezoelectric biosensors used in the field of healthcare including the applications of wearable health monitoring system, early diagnostic biomarkers for Alzheimer’s disease, cancer, CVDs, Corona virus detection, etc. Chapter 12 presents an overview about recent advancement on the paper-based low-cost biosensors used disease diagnosis and their potential in early diagnosis and treatment applications. Chapter 13 represents potential applications of wearable enzymatic biosensors used in different healthcare applications along with their challenges and future scopes. Chapter 14 provides an overview on limitations, applicability and future market scope of enzymatic biosensors, and how personal healthcare biosensors can be used in different socio-economic settings. In nutshell, this book depicts the current status and future prospects of enzymatic biosensors for healthcare applications. This book deals with the basics of biosensors, different applications of enzymatic biosensors as well as their commercial potentials. The target group of the book is postgraduate, Ph.D. students, and advanced researchers. It will be helpful for both novices as well as the experts working in the field of biosensors. Guwahati, Assam, India Guwahati, Assam, India Shillong, Meghalaya, India

Sanjukta Patra Debashree Kundu Manashjit Gogoi

Acknowledgement

First of all, the editors would like to thank almighty God for providing us with the motivation and strength to complete this endeavour of editing this book. The editors would like to sincerely thank Dr. Bhavik Sawhney, Editor, Biomedicine, and all the board members from Springer Nature for their approval and for granting us this opportunity to edit this book. We would like to express our sincere gratitude to Ms. Vaishnavi Venkatesh, Project Coordinator (Books), Springer Nature for constantly following up on the editing process and helping us to complete this assignment. The editors express their heartfelt gratitude to all the contributors of this book for their contributions. Their contributions are sincerely appreciated and gratefully acknowledged. Prof. Sanjukta Patra expresses heartfelt thankfulness to little Paridhi. It is her shared time which has brought this book in black and white. The motivation of her husband Rajesh has made the completion possible. The support of her parents, parents in law, and siblings has kept her moving ahead. Dr. Debshree expresses her sincere gratitude to her husband and family members for their constant support and motivation. Dr. Manashjit Gogoi expresses his thankfulness to his beloved sons Aditya, Atanu, wife Mayuri who sacrificed a lot and kept him inspired to finish this task. He is also thankful to his sister-in-law Hewali, and his parents, brothers, and in-laws for their constant support, unconditional love, and blessings.

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Contents

1

Enzymatic Biosensors for Healthcare Applications . . . . . . . . . . . . . Bethuel Daurai, Shrimanta S. Ramchiary, and Manashjit Gogoi

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Choice of Enzyme Immobilization Matrices Used in Biosensor for Healthcare Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sanjeev Bhandari, Manashjit Gogoi, and Mrityunjoy Mahato

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Enzymatic Biosensor Platforms for Diagnosis of Heart Diseases . . . Jasmeen Kaur, Rohit Srivastava, and Vivek Borse

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Enzyme-Based Biosensor Platforms for Detection of Cancer . . . . . . Anna Anandita, Dakshita Snud Sharma, Nandini Singh, Rajesh Kumar Singh, Vinay Sharma, and Dharitri Rath

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Enzymatic Biosensor Platforms for Early Diagnosis of Diabetes . . . 109 Prabhjot Singh, Satish Kumar Pandey, and Nishima Wangoo

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Enzymatic Biosensors for Detection of Pancreatitis . . . . . . . . . . . . . 127 Bethuel Daurai, Arup Jyoti Baruah, and Manashjit Gogoi

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Enzymatic Biosensing Platforms for Gut Diseases . . . . . . . . . . . . . . 151 Damini Verma, Amit K. Yadav, and Pratima R. Solanki

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Enzymatic Biosensor Platforms for Non-infectious Diseases: Diagnosis of Metabolic Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . 173 Gurpreet Kaur, Naveen K. Singh, and Kuldeep Gupta

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Protein-Based Biomarkers for the Diagnosis of Malaria in Point-of-Care Settings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217 Babina Chakma, Priyamvada Jain, and Pranab Goswami

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Enzymatic Biosensor Platforms for Infectious Disease Diagnosis: Focus on Tuberculosis and Neglected Tropical Diseases . . . . . . . . . 237 Satakshi Hazra, Munna Singh Thakur, and Sanjukta Patra

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Piezoelectric Biosensors in Healthcare . . . . . . . . . . . . . . . . . . . . . . . 255 Akshpreet Kaur, Parveen Kumar, Ankur Gupta, and Gaurav Sapra

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Low-Cost Paper-Based Analytical Devices and Their Application in Healthcare System . . . . . . . . . . . . . . . . . . . . . . . . . . 273 Girish Chandra Mohanta and Satish Kumar Pandey

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Nano-inspired Point-of-Care Enzyme-Based Wearable Biosensors for Global Health Care . . . . . . . . . . . . . . . . . . . . . . . . . 293 Vinay Kumar and Kavita Arora

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Commercialized Enzymatic Biosensors in Healthcare Against the Conventional Methods . . . . . . . . . . . . . . . . . . . . . . . . . 323 Akshath Uchangi Satyaprasad

Editors and Contributors

About the Editors Sanjukta Patra works at the Department of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Assam, India. Holding a Ph.D. in Biotechnology from the Central Food Technological Research Institute, Mysuru, her areas of expertise include biosensors, enzyme and microbial technology, environmental biotechnology, and metagenomics. To date, she has published 51 peerreviewed international research articles, authored 17 book chapters, and has three patents to her credit. Debasree Kundu is a Post-Doctoral Fellow at the Department of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Assam, India. Holding a Ph.D. in Microbiology, with a focus on microbial and enzymatic degradation of xenobiotics, she is currently investigating pesticide-induced adaptive response in microbes using proteomic approaches. To date, apart from having granted a patent to her credit, she has authored 21 research articles and ten book chapters. Manashjit Gogoi is an Assistant Professor at the Department of Biomedical Engineering, North-Eastern Hill University, Shillong, Meghalaya, India. Holding a Ph.D. in Biomedical Engineering from the Indian Institute of Technology—Bombay, Mumbai, India, his research chiefly focuses on biosensors, point-of-care devices, nanomedicine for drug delivery, and tissue engineering. To date, he has edited one book, published 20 research articles, and 20 book chapters.

Contributors Uchangi Satyaprasad Akshath Nitte University Centre for Science Education and Research-NUCSER, Nitte University, Mangalore, Karnataka, India Anna Anandita Department of Chemical Engineering, Indian Institute of Technology, Jammu, Jammu and Kashmir, India

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Kavita Arora Advanced Instrumentation Research Facility and School of Computational & Integrative Sciences, Jawaharlal Nehru University, New Delhi, India Arup Jyoti Baruah Department General Surgery, North Eastern Indira Gandhi Regional Institute of Health & Medical Sciences, Shillong, Meghalaya, India Sanjeev Bhandari Physics Division, Department of Basic Sciences and Social Sciences, School of Technology, North-Eastern Hill University, Shillong, Meghalaya, India Vivek Borse NanoBioSens Laboratory, Centre for Nanotechnology, Indian Institute of Technology Guwahati, Guwahati, Assam, India Babina Chakma Global Consulting Admin, Syneos Health, Bengaluru, Karnataka, India Bethuel Daurai Department of Biomedical Engineering, North-Eastern Hill University, Shillong, Meghalaya, India Manashjit Gogoi Department of Biomedical Engineering, North-Eastern Hill University, Shillong, Meghalaya, India Pranab Goswami Biosensors and Biofuel Cell Lab, Department of Bioscience and Bioengineering, Indian Institute of Technology Guwahati, Guwahati, Assam, India Ankur Gupta Department of Cardiology, PGIMER, Chandigarh, India Kuldeep Gupta Department of Radiology and Radiological Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD, USA Satakshi Hazra Department of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Guwahati, Assam, India Priyamvada Jain Medical Electronics Business Unit, TATA Elxsi, Bangalore, Karnataka, India Akshpreet Kaur UIET, Panjab University, Chandigarh, India Gurpreet Kaur Department of Life Sciences, University of Hyderabad, Hyderabad, India Jasmeen Kaur NanoBios Laboratory, Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, Maharashtra, India Parveen Kumar E-waste Laboratory, CSIO – CSIR, Chandigarh, India Vinay Kumar Department of Physiology and Cell Biology, Department of Internal Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, USA Mrityunjoy Mahato Physics Division, Department of Basic Sciences and Social Sciences, School of Technology, North-Eastern Hill University, Shillong, Meghalaya, India

Editors and Contributors

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Girish Chandra Mohanta Nanotechnology Lab (H-1), CSIR-Central Scientific Instruments Organizations (CSIR-CSIO), Chandigarh, India Satish Pandey Central Scientific Instrument Organization (CSIO), Chandigarh, India Satish Kumar Pandey Nanotechnology Lab (H-1), CSIR-Central Scientific Instruments Organizations (CSIR-CSIO), Chandigarh, India Sanjukta Patra Department of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Guwahati, Assam, India Shrimanta S. Ramchiary Department of Biomedical Engineering, North-Eastern Hill University, Shillong, Meghalaya, India Dharitri Rath Department of Chemical Engineering, Indian Institute of Technology, Jammu, Jammu and Kashmir, India Gaurav Sapra UIET, Panjab University, Chandigarh, India Dakshita Snud Sharma Department of Chemical Engineering, Indian Institute of Technology, Jammu, Jammu and Kashmir, India Vinay Sharma Department of Biosciences and Bioengineering, Indian Institute of Technology, Jammu, Jammu and Kashmir, India Nandini Singh Department of Bioengineering and Biotechnology, Birla Institute of Technology, Mesra, India Naveen K. Singh Department of Electrical and Computer Engineering, University of California, San Diego, CA, USA Prabhjot Singh Centre for Nanoscience and Nanotechnology, Panjab University, Chandigarh, India Senior Secondary Residential School for Meritorious Students, Ludhiana, Punjab, India Rajesh Kumar Singh Department of Chemical Engineering, Indian Institute of Technology, Jammu, Jammu and Kashmir, India Pratima Solanki Special Center for Nanoscience, Jawaharlal Nehru University, New Delhi, India Rohit Srivastava NanoBios Laboratory, Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, Maharashtra, India Munna Singh Thakur Center for Nanomaterials and MEMS, Nitte Meenakshi Institute of Technology, Bengaluru, Karnataka, India Damini Verma Special Center for Nanoscience, Jawaharlal Nehru University, New Delhi, India

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Editors and Contributors

Nishima Wangoo Department of Applied Sciences, UIET, Panjab University, Chandigarh, India Amit K. Yadav Special Center for Nanoscience, Jawaharlal Nehru University, New Delhi, India

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Enzymatic Biosensors for Healthcare Applications Bethuel Daurai, Shrimanta S. Ramchiary, and Manashjit Gogoi

1.1

Introduction

By developing the oxygen electrode in 1956, Leland C. Clark, Jr. established himself as the originator of the biosensor idea and ushered in a new era in the sensor technology (Clark Jr 1956; Clark Jr and Lyons 1962). Glucose was trapped by a dialysis membrane in the Clark oxygen electrode, and the proportionality between the concentration of glucose and the decreasing oxygen concentration was established. A lot of different enzymes were used in this study since it was so successful at catalyzing many different variants utilizing the same basic design. Since this groundbreaking study, the biosensor industry has expanded dramatically, and enzyme biosensors in particular have become one of the most widely used in the biomedical industry (Turner et al. 1987). A biosensor device is small or compact and contains a biological or biologically derived sensing element that is integrated or connected to a transducer. Biosensors are of many types and characteristics which can be categorized based on the biological elements and the transducers used (Mohanty and Kougianos 2006). Typically, a biosensor can be electrochemical, optical, mechanical, piezoelectric, calorimetric, etc. based on the use of type of transducer Another component of a biosensor may be signal processing unit. An electrochemical transducer produces out in the form of voltage, current, or resistance (Zhang et al. 2000). To interpret these signals corresponding to the concentration of the analyte, a signal processing unit is required to correctly process and display the value of concentration of the analyte. Low-power consuming signal processing unit is specifically required when it comes to implantable biosensor and point-of-care (POC) devices (Haider and Islam 2010).

B. Daurai · S. S. Ramchiary · M. Gogoi (✉) Department of Biomedical Engineering, North-Eastern Hill University, Shillong, Meghalaya, India # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Patra et al. (eds.), Enzyme-based Biosensors: Recent Advances and Applications in Healthcare, https://doi.org/10.1007/978-981-15-6982-1_1

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Enzymes are biological catalysts that react with molecules known as substrates and convert them into products. Binding of enzymes to their substrate is necessary for their activation for catalysis. They are very specific to the substrate and also to the chemical reaction. This specific nature of enzymes to bind to their respective substrate makes them useful in biosensing. In 1894, Emil Fischer proposed the lock and key model explaining the geometric complimentary of enzymes and substrates. This early model failed to explain the stabilization of enzyme during the transition stage. In 1958, Daniel Koshland described the change in the active sites due to the interaction of enzymes and substrates. Substrates don’t bind to the active site of the enzyme, but the amino acids of the active site are molded to the precise position to perform catalysis. In enzymatic biosensors, enzymes are used as a biological component to detect analytes. In an enzymatic biosensor, the enzyme is immobilized to the transducer surface to detect the analyte. Here the analyte can also be a substrate of the enzyme. Immobilization techniques are directly related with the performance of the biosensor and can change the accuracy, sensitivity, selectivity, and even the stability of the biosensor.

1.2

Types of Enzymatic Biosensors

The basic components of all biosensors are the biological sensing material and the transducer with the option of a signal conditioner system. In the following section, biosensors are categorized based on the use of different types of transducers and discussed.

1.2.1

Amperometric Biosensors

1.2.1.1 First-Generation Amperometric Biosensors In the first generation, the enzyme capable of converting a substrate into an electroactive quantifiable byproduct is immobilized on the transducer surface (Dzyadevych et al. 2008; Rocchitta et al. 2016). The first-generation biosensor is based on oxidases and dehydrogenases. The rise and fall of oxygen concentration can affect sensor response and reduce sensor linearity in this generation biosensors (Wang 1999). In the first generation, the concentration of the measured analyte is exactly proportional to the NADH concentration in the case of dehydrogenase enzymes. Implantable biosensors have a challenge since NADH is necessary for the generation of a signal in the matrix (Lee and Tsai 2009). First-generation biosensors are sensitive and have a very quick reaction time (Rocchitta et al. 2012). To produce a repeatable surface and sensor response, firstgeneration biosensors frequently need electrode treatment, and matrix effects linked to interference often need correction (Dzyadevych et al. 2008). Also, after repeated use, particularly in unadulterated or complicated biological matrices, the transducer surface of amperometric biosensors is damaged, which affects the biosensor response (Prodromidis and Karayannis 2002).

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1.2.1.2 Second-Generation Amperometric Biosensors In the second generation, oxidizing substances are used as mediators between the enzyme and the transducer which carries electrons (Bartlett et al. 1991). By removing oxygen dependency and the effects of interfering molecules, this method enables operation at low potentials. Ferricyanide and ferrocene are the two most popular and well-known mediators (Chaubey and Malhotra 2002). Electrons are transferred to the electrode surface from the enzyme’s redox reaction using the mediators. Mediators are added to the sample or immobilized on the electrode (Habermüller et al. 2000). Ideal mediators should be inert and nonreactive in normal circumstances and do not participate in the electron transfer (Scheller et al. 1991). The redox potential of the mediators is also an important parameter (Chaubey and Malhotra 2002). With more redox potential, the mediators will be more reactive than the other chemicals in the sample. Immobilized mediators often have stability issues and because of this, they are less frequently used compared to the first generation. 1.2.1.3 Third-Generation Amperometric Biosensors Bioelectrocatalysis, which involves a direct exchange of electrons between an electrode and an enzyme, is the basis for third-generation biosensors (Bhattarai and Hameed 2020). Three components make up a third-generation biosensor: an electrode (with surface to receive electrons), a reducing or oxidizing agent (connecting element) to assure signal transmission, and an enzyme as the biorecognition element (Prodromidis and Karayannis 2002). Performance is enhanced by connecting the redox reaction site of the electrode surface using a reducing or oxidizing agent. Third-generation biosensors are under research and development stage and hence they still have limited use for analysis by the end users in the real world (Mahdizadeh et al. 2022). Third-generation biosensors, however, have incredibly quick reaction times and are mostly unaffected by oxygen/cofactor (mediator) concentrations.

1.2.2

Optical Enzymatic Biosensors

Optical biosensors use enzymes as the biological recognition element. Based on the transduction mechanism, enzymatic optical biosensor can be categorized (Choi 2004) as absorptiometry, luminescence, chemiluminescence types, etc. Absorption by reflection or transmission of light through a material is an absorptiometry type. Luminescence type of transducer makes use of the luminescence property of materials (Blum et al. 1989). With separate wavelength of excitation, a separate longer emission could be achieved. Chemiluminescence makes use of the reaction of the reagent and analyte to give an optically readable output. There are also other optical enzymatic biosensors like the interferometry, surface plasmon resonance (SPR), fiber optic, acoustic photometry, etc. Enzyme immobilization in optical biosensors is done by either chemical or physical method. Both approaches aim to maintain the enzymes on the solid substrate and prevent solution washing. Adsorption on solid surfaces or polymeric

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gels, entrapment in inorganic or organic polymeric gels, and confinement within semipermeable membranes are all examples of physically immobilizing an enzyme. Enzymes may be chemically immobilized by either intermolecular cross-linking of the biomolecules or covalently attaching the enzymes to functionalized solid materials. While chemical immobilization may provide more stable and long-lasting biosensors, the enzymatic performance is often not as excellent as that of physically immobilized enzymes.

1.2.2.1 Absorbance Optical Biosensors The Beer-Lambert law explains this kind of transducer type where the concentration of an analyte is measured by measuring the absorbance or reflectance of light through the analyte. Some of the biosensors used in this approach include photometric features, meaning they can measure changes in analyte or product absorbance at certain wavelengths (Choi 2004). The typical absorbance transducers use a single fiber or fiber bundle to provide light to the analyte-sensitive reagent phase and then return the transmitted or reflected light through the same fiber to a measuring device or detector. The biosensor can record these variations in transmission intensity because changes in the chemical environment may alter how the biorecognition element is absorbed. It becomes challenging to accurately measure transmitted light in nontransparent measuring environments, and in these circumstances, the intensity of the reflected light may be utilized to gauge the color of the recognition element, analyte, or product. 1.2.2.2 Chemiluminescence The chemiluminescence feature of an optical biosensor causes the emission of light as a result of the interaction between the reagent material and analyte (Choi 2004). Enzyme-linked reactions can be used in enzyme-based chemiluminescent assays, often combining an oxidase and a peroxidase. H2O2 is produced as a result of processes that are catalyzed by oxidases. This peroxide may then be used to oxidize a chemiluminescent reagent, primarily luminol, producing light that can be detected by a light sensor. This method has been used in the determination of glucose, cholesterol, and lactate with the appropriate oxidase and dehydrogenase enzyme for the analytes (Kuswandi et al. 2001).

1.2.3

Piezoelectric Enzymatic Biosensor

In this type of biosensor, the transduction is done by a piezoelectric quartz crystal. The total applicability and sensitivity of this biosensing system are determined by the enzyme (biorecognition element), the transducer, and the parameters of the assay environment (Bunde et al. 1998). Quartz crystal microbalance (QCM) has shown many applications in biosensing. These biosensors are different from electrochemical and optical ones, because they can quantify the attached material directly (Pohanka 2021). They are, therefore, making them easy for construction. The change in frequency of the quartz crystal bounded with a specific material can be correlated

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to the mass of that material. The frequency may increase or decrease with the increase or decrease in the mass of the material. Its application in healthcare has been recently under research. Because it is label-free, the cost of a biosensor can be reduced.

1.3

Significance of Enzymes as Biomarkers

Enzymes are biological catalysts that have extensively been utilized in industries, for example, food and beverage industry, brewery production, and cleaning agents, to regulate as well as speed reactions to rapidly and accurately produce different necessary products (Godfrey and Reichelt 1982; Polaina and MacCabe 2007). Additionally, enzymes are frequently used in laboratories, such as stereospecific bioconversion, recycling trash into useful goods or eco-friendly replacements, etc. (Bershtein and Tawfik 2008). There are many metabolic illnesses that are caused by abnormalities in the enzyme metabolic system. Researchers from all around the world have focused on the increasingly clinical uses of enzymes including acid phosphatase, alkaline phosphate, alanine transaminase, aspartate transaminase, creatine kinase, lipase, alpha-amylase, protease, lactate dehydrogenase, etc. (Patel 1995). Enzymes have already been used for the detection of diseases related to the heart, kidneys, and liver, autoimmune disease, cancer, mental illness like schizophrenia, etc. “Diagnostic enzymes” is the term used for the enzymes of the human body that are medically used for the diagnosis and prognosis of diseases (Singh et al. 2019). Enzymes are used in diagnostics because of the high selectivity of the enzyme as a substrate. Enzyme activities are very specific to the action of the reaction, for example, in the hydrolysis of sugar by amylase which can help in the determination of glucose level in detection of diseases like diabetes. Depending on the degree of the condition, a sick state often results in tissue destruction. When this occurs, disease-specific enzymes with increased enzyme activity are released into the bloodstream. These increased levels of enzymes in the body fluids like blood, urine, and saliva can be determined and can be correlated with a specific disease. In the following section, application of enzymes as biomarkers for diagnosis of some major diseases is discussed.

1.3.1

Enzymes as Biomarker for Cardiovascular Diseases

Cardiovascular diseases are often linked to atherosclerosis, where plaque made of fat is accumulated in the arteries. Narrowing down of the blood vessels leads to hypertension, heart block, heart attack, peripheral artery disorders, etc. Some of the contributing factors for these diseases are obesity, stress, inactivity, food habit, hereditary, and even poor mental health like depression. Creatine kinase (CK; E.C. 2.7.3.2) catalyzes the production of adenine triphosphate from adenine diphosphate and creatinine phosphate. Three isoforms of CK are

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CK-MM, CK-MB, and CK-BB. CK-MB are the most precise and specific biomarkers for the detection of myocardial infarction (Panteghini 1988; Apple 1989). A normal level of CK in an adult human male is between 0.038 and 0.174 U/mL, whereas in adult human female, the normal level of CK is between 0.026 and 0.14 U/mL. Myocardial infarction, muscular dystrophy, and inflammatory responses cause CK levels to go as high as 2 U/mL in the blood serum, which aids in the early prognosis of illness states (Vainzof et al. 1985). Glycogen phosphorylase (GP) (EC 2.4.1.1), an important part of carbohydrate metabolism, is played by the glycolytic enzyme GP, which mobilizes glycogen. GP is found in three separate physiologically distinct isoforms, GPMM, GPLL, and GPBB (Krause et al. 1996). GPBB acts as an identifier or marker for the detection of acute myocardial infarction, acute coronary syndrome, and even pregnancy and preterm preeclampsia (Stejskal et al. 2007; Singh et al. 2018). Gelatinases catalyze the breakdown of gelatin to create polypeptides, peptides, and amino acids. The two isoforms, gelatinase A (EC 3.4.24.24) and gelatinase B (EC 3.4.24.35), both have been used as biomarkers for the prediction and early detection of heart disease like heart blockages and acute myocardial infarction (Gopcevic et al. 2017). Other than heart disease, gelatinase has also been used as a marker for detecting acute kidney damage and myocardial fibrosis when combined with lipocalin (Gyöngyösi et al. 2017; Bulluck et al. 2018). A digestive enzyme called salivary amylase (EC 3.2.1.1) is also reported as biomarker for heart failure and psychological stress. When detected in urine, amylase has also been found to be a helpful biomarker for renal disease (Strahler et al. 2010; Suska et al. 2012; Żyłka et al. 2016).

1.3.2

Enzymes as Biomarker for Liver Diseases

Several enzymes are released into the blood circulation when it is under stress or injured because of hepatitis virus, fatty liver, alcohol abuse, and other certain drugs, and measuring the amount of these enzyme catalysts helps in detection of the specific diseases (Adams et al. 2005; Calvaruso and Craxì 2009). A few major enzymes that aid in the identification of liver conditions and diseases are discussed in the following section. Aminotransferases (transaminases) convert amino acids to oxoacids by transferring amino groups. The two clinically significant enzymes included in the aminotransferases group are alanine aminotransferase (ALT) and aspartate aminotransferase (AST) (Huang et al. 2006). The ALT concentration range in an adult person is between 5 and 35 U/L, and anything over this range denotes liver, heart, and muscle damage or illness. Detection or determination is done using chromatography, calorimetry, or spectrophotometry techniques, but recently researchers have come up with affordable paper-based analytical devices (PADs) and POC biosensors (Bacon 2002; Huang et al. 2006; Kang et al. 2011). The normal level of aspartate aminotransferase (AST) (EC 2.6.1.1) in healthy human adults range from 5 to 40 U/ L (Kaplan 2002; Prati et al. 2002; Huang et al. 2006). However, with significant

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injury, the level of AST may increase to as high as 20 times over the normal level. Many other organs, tissues, and cells like the muscle fiber, blood, kidney, and pancreas also contain AST. It can be used to track cardiac, hepatic parenchymal, and muscular disorders in both people and animals by combining the results with other enzymes. When an imaging method like ultrasonography or ultrasound elastography is not available, the AST-to-platelet ratio index may be a helpful measure to check for liver fibrosis which is a common condition in hepatitis B (Lesmana et al. 2011). Alkaline phosphate (ALP) (EC 3.1.3.1) is a biocatalyst in the hydrolysis of phosphate ester bonds in an alkaline environment (Corathers 2006; Sharma et al. 2014). ALP is a helpful indicator of liver illness, especially cholestatic conditions when there is a blockage in the bile duct, which are seen in obstructive jaundice (Frey et al. 1990; Fargo et al. 2017). Gamma-glutamyl transferase (GGT) (EC 2.3.2.2), which aids in the transportation of proteins and amino acids and also in breaking them down is present in all human cells (Kunutsor 2016). Mostly found in the liver, kidney, and pancreas, GGT in serum is produced in the liver. GGT is considered a biomarker for hepatobiliary disease. GGT is moderately elevated because of toxic or infectious hepatitis (two to five times) (Huber et al. 2004). GGT rises 5–30 times the normal in serum when the intrahepatic biliary is obstructed. Other diseases and conditions like pancreatitis, rheumatoid arthritis, alcohol abuse, muscular dystrophy, and pulmonary disease show increase in serum GGT. GGT-to-platelet ratio index also determines liver fibrosis in the absence of ultrasound elastography. In few researches, GGT is also used as a biomarker for nephrotoxicity (Hu et al. 2017).

1.3.3

Enzymes as Biomarker for Cancer

Cancer is characterized as a condition in which a group of cells develops improperly, leading to their unchecked expansion and spread. If this growth is allowed to continue, it might be fatal. Additionally, 90% of cancer-related fatalities result from a process known as metastasis. Several enzymes increase in concentration in various body fluids when this condition occurs. The following are some of the enzymes that can indicate cancer. There are five types of acid phosphatases (ACP) (E.C. 3.1.3.2), namely, erythrocytic, macrophage, lysosomal, and osteoclastic. They are present in humans and based on the origin and sequence length, they are different from one another. They also differ based on the amount of resistance to tartrate and fluoride (Nakanishi et al. 1998). ACP levels in prostate gland are 100 times higher than in any other part of the body. Since prostate cancer cells produce prostatic acid phosphatase in high levels, it is utilized to track the progression of the disease (Taira et al. 2007). Cathepsin D (CD) is a catalyst used for breaking down proteins into polypeptide. Prepro-cathepsin-D is produced from it in the rough endoplasmic reticulum and is present in almost all tissues, cells, and organs. Breast cancer’s prognosis is

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influenced by CD, which is indicated with the overexpression of epithelial breast cancer cells (Sun et al. 2016). Cysteine cathepsins (CCs) are proteases that are produced during tumorigenic phenomena like angiogenesis, apoptosis, and invasion. The increase in the concentration of this enzyme indicates several types of cancers. There are 11 isoforms of CCs (B, C, F, L, K, V, S, X/Z, H, W, and O) having different effects in the human body (Joyce and Hanahan 2004; Turk et al. 2004). Some of the cancers where CCs rise are in breast cancer, ovarian cancer, uterus cancer, cervical cancer, lung cancer, and brain tumor. CCs are also used as biomarkers for inflammatory myopathies, periodontitis, and rheumatoid arthritis (Hemalatha et al. 2013). Cyclooxygenase-2 (COX-2) is a catalyst for the conversion of arachidonic acid to prostaglandin H2. According to some research, COX-2 functions as a biomarker in the development of malignancies, such as bladder, stomach, and breast cancers (Hwang et al. 1998; Shirahama and Sakakura 2001; Van Rees et al. 2002). Dehydrogenases are a family of enzymes that include two dehydrogenases that are utilized for cancer prognosis: sorbitol dehydrogenase (SDH) and lactate dehydrogenase (El-Kabbani et al. 2004). The reaction of polyhydric alcohols D-sorbitol and D-fructose is catalyzed by sorbitol dehydrogenase utilizing NAD+/NADH as a mediator. It is commonly found in seminal vesicles, livers, and kidneys (Holmes 1978). An increase in SDH level in serum indicates prostate cancer and precancerous colorectal neoplasms (Szabó et al. 2010; Uzozie et al. 2014). Some other researches also suggest that increase in SDH also indicates liver damage and parenchymal hepatic disease. Lactate dehydrogenase (LDH) is a catalyst in the formation of lactate from pyruvate and vice versa during glycolysis and glyconeogenesis. It is used as a biomarker for various cancers like breast cancer, oral cancer, prostate cancer, pancreatic cancer, colorectal cancer, etc. (Singh et al. 2019). It has been extensively used in researches for early detection of various cancers and for the prognosis of acute leukemia and sickle cell disease (Kato et al. 2013; Walaa Fikry 2017). Tartrate-resistant acid phosphatase (TRAP) hydrolyzes phosphate esters to release oxygen. TRAP is found in high level in bone osteoclasts and lesser in dendritic cells and activated macrophages (Hayman 2008). The two isoforms of TRAP are TRAP5a and TRAP5b (Mira-Pascual et al. 2020). High level of TRAP5a in serum indicates breast cancer and systemic lupus erythematosus (Chen et al. 2015, 2017). TRAP5b increases in serum in case of multiple myeloma and bone metastasis originating from other cancers (Koizumi and Ogata 2002; Mose et al. 2003; Terpos et al. 2003). In cancer with high incidences of bone metastases, TRAP5b can be used for diagnosis and prognosis of breast cancer, lung cancer, myeloma, and prostate cancer. Thymidine kinase (TK) helps in the catalysis of thymine from thymidine. TK has two isoforms: TK1 and TK2. TK1 is a biomarker for malignancy for biomarkers in colon cancer, uterine cancer, prostate cancer, breast cancer, stomach cancer, chronic lymphocytic leukemia, and acute lymphoblastic leukemia (Singh et al. 2019). Recent research showed the use of TK1 in early detection of neoplasia (He et al. 2010).

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In prostate cancer, the most common biomarkers are prostate-specific antigen, prostate cancer gene 3, and enzymes like human kallikrein 3 and human glandular kallikrein2 (Sarkar et al. 2022). With relevant type of biorecognition element and transduction process, many combinations of biosensors can be developed.

1.3.4

Enzymes as Biomarkers for Other Diseases

Creatinine, blood urea nitrogen, cystatin C, and uric acid are some of the common biomarkers of kidney diseases. All of them are not enzymes but take part in an enzymatic reaction making them feasible for an enzymatic biosensor. Salivary enzymes have also been used to determine neurological disorders and stress levels (Nater et al. 2006). There are many diseases where enzymes can be used as biomarkers. Pancreatic alpha-amylase and lipase are enzymes that catalyze the hydrolysis of starch and triglycerides, respectively. Alpha-amylase increases three to five times in the initial days and returns back to normal, but lipase stays elevated for a longer time. According to the American Board of Internal Medicine, the normal range of serum alpha-amylase is 25–125 U/L and serum lipase is 10–140 U/L. Glucose-6-phosphatase has also been used as a biomarker for hypoglycemia (Froissart et al. 2011). The use of acid phosphatase as a biomarker in serum was reported by Devi et al. (2017).

1.4

Enzymatic Biosensors for Various Diseases

The most researched biosensors right now are enzymatic ones, and these research articles demonstrate several innovative developments as have been discussed below:

1.4.1

Biosensors for Cardiovascular Diseases

An aptamer-based label-free capacitive biosensor was developed using non-faradaic impedance spectroscopy for detection of cardiac C-reactive protein (CRP) based on charge distribution. The biosensor had low binding affinity toward RNA aptamer, whereas it could be operated without any reagent (Qureshi et al. 2010a, b). In another study, a POC biosensor that is used to monitor cardiovascular illness by detecting neutrophil gelatinase-associated lipocalin (NGAL) was developed using electrochemical impedance spectroscopy (EIS) measurement technique (Gonzalez and La Belle 2012). Nanowire integrated microfluidic biosensors were developed for detection of cardiovascular biomarkers (related to heart failure stage diagnosis) such as myoglobin (Myo), creatine kinase MB (CK-MB), cardiac troponin I (cTnI), and b-type natriuretic peptide (BNP). Though this biosensor had good specificity, it was not cost-effective (Lee et al. 2012). A highly sensitive, stable, and controllable biosensor for the detection of cholesterol was developed using a layer by layer of carbon nanotube/gold nanoparticle-centered bienzyme (Cai et al. 2013). Similarly,

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cholesterol enzymatic biosensor based on nanohybrid composites (CSPPygC3N4H+) has been developed which was affordable, biocompatible, as well as environmental friendly (Shrestha et al. 2017). Another study was done on fluorescence resonance energy transfer (FRET) biosensors for visual detection of guanosine monophosphate (cGMP), cyclic adenosine (cAMP), and Ca2+ in cardiac cells (Thunemann et al. 2014). More advanced and highly sensitive biosensors were investigated for detection of cardiac troponin I (Fathil et al. 2017; Radha Shanmugam et al. 2017). Recently, a promising potential for an electrochemical biosensing platform based on graphene quantum dots (GQDs) for the early identification of acute myocardial infarction (AMI) was investigated and LOD was found to be 0.01 ng/mL (Tabish et al. 2022). Biosensors for cardiovascular disease detection are very common and commercially available. Enzyme as a biomarker or enzyme as a biorecognition element is shown in most of the biosensor but synthetic biorecognition element for biosensing is also mentioned. Table 1.1 lists a comprehensive list of biosensors, both enzymatic and nonenzymatic type.

1.4.2

Biosensors for Liver Diseases

A multiplexed assay using giant magnetoresistive (GMR) biosensor for early detection of cirrhosis was developed by using cirrhotic protein biomarkers intercellular adhesion molecule-1 and mac-2 (Ng et al. 2020). In another study, a surfaceenhanced Raman spectroscopy (SERS)-based biosensor was developed for detection of liver diseases serologically by integrating convolutional neural network (CNN) classifier with gold-silver (Au-Ag) nanocomplex-decorated zinc oxide (ZnO) nanopillars on paper (Cheng et al. 2021). Similarly, an enzymatic biosensor for detection of hepatocellular carcinoma (HCC) using serum biomarker alphafetoprotein (AFP) had been developed for early diagnosis of liver disease (Attia et al. 2022).

1.4.3

Biosensors for Diabetes

A glucose enzymatic biosensor for detection of diabetes was developed using derivatives of oxidase and dehydrogenase of glucose, which rely on flavin adenine dinucleotide (Ferri et al. 2011). In another study, several surface modifications to nanowires of Pt were done for improving its catalytic activity toward immobilized glucose oxidase cross-linked on the surface of the electrode using glutaraldehyde. Three generations of these biosensors were studied utilizing cyclic voltammetry. The response current, coefficient of determination (R21st gen = 0.834, R22nd gen = 0.955, R23rd gen = 0.921), and glucose sensitivity improved with each successive newer generation (Shi et al. 2010). A glucose biosensor using potentiometric transducer made of zinc oxide (ZnO) nanowire electrode was developed for measuring glucose concentration for detection of diabetes (Usman Ali et al. 2010). Similarly, glass electrode glucose enzymatic biosensors have been developed for different analytes

Based on functionalized carbon nanotubes (CNTs)

Fluorescent-tagged genetically encoded

FRET biosensors (tagged biosensor)

Microfluidic channels integrated with nanowire-based biosensors

Technical strategy Label-free detection based on non-faradaic impedance spectroscopy Measurement-based on electrochemical impedance spectroscopy (EIS)

Bienzyme biosensor

Neutrophil gelatinaseassociated lipocalin (NGAL) detection biosensor Single sitespecific polyaniline (PANI) nanowire biosensor

Biosensor Aptamer-based capacitive biosensor

The high cost of assembling

Better sensitivity requires an optimal combination of

Cardiovascular disease (detection of cholesterol) Cardiovascular system

Low-cost efficiency

Cardiovascular disease (diagnosis of heart failure stages)

Detection of the b-type natriuretic peptide (BNP), myoglobin (Myo), creatine kinase MB (CK-MB), and cardiac troponin I (cTnI) Layer-by-layer amassed and carbon nanotubes/gold nanoparticles centered Förster resonance energy transfer based

Detects up to the only certain level of diluted concentration

Cardiovascular disease

Immobilizing monoclonal antibodies (against NGAL) onto gold disk electrodes

Limitations Low binding affinity

Applications Cardiovascular disease

Mechanism Detection based on charge distribution of CRP

Thunemann et al. (2014)

Visualizing cGMP, cAMP, and Ca2+ in cells

Enzymatic Biosensors for Healthcare Applications (continued)

Cai et al. (2013) High sensitivity, stability, and controllability

Lee et al. (2012)

Gonzalez and La Belle (2012)

Point-of-care biosensor

Good specificity with ultrahigh sensitivity

References Qureshi et al. (2010a, b)

Advantages Reagent less processing

Table 1.1 Recent advancements in cardiac biosensors, including technological approaches used in their operation, healthcare applications, benefits, and drawbacks

1 11

GQDs-based electrochemical biosensor

Identification of troponin and myoglobin

Acute myocardial infarction (AMI) detection

Cardiovascular disease (cholesterol detection in human serum)

Cardiovascular disease

Multiplexed and simultaneous detection of two isoform of troponins ChOx immobilization on CSPPy-gC3N4H+ nanohybrid composite

Detection based on EIS and MottSchottky analysis

Doping of engineered g-C3N4H+ nanosheets with cylindrical spongyshaped polypyrrole EIS

Cardiovascular disease

Cardiac troponin I (label free detection)

Covalent binding immobilization of MAb-cTnI via

Applications

Substrate-gate coupled FET-based biosensor Flexible zinc oxide nanostructured biosensor Nanohybrid composite-based cholesterol biosensors

Mechanism

Technical strategy

Biosensor

Table 1.1 (continued)

Low recovery, low efficiency, the usage of reagents, several steps in handling, and the length of the inquiry cost of antibody manufacturing, poor performance and stability under stress, and very high temperatures

Poor long-term stability

Limit of detection

fluorescence nanomaterials Limit of detection

Limitations

Shrestha et al. (2017)

Tabish et al. (2022)

Strong interactions between cTnI and GQDs, minimal biomarker use, and electrode reusability

Radha Shanmugam et al. (2017)

Fathil et al. (2017)

References

Cost-effective, biocompatible, eco-friendly

Early diagnosis

Improved the sensitive detection

Advantages

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with solutions (chitosan, polyethylenimine, polystyrene sulfonate, etc.). The surface of the electrode was modified using different films of Au, Ag, Co, etc. for determining the catalytic activity of glucose oxidase using cyclic voltammetry (Qiu et al. 2012; Wang et al. 2012; Khun et al. 2012). Another study on voltammetry was done where a working chip electrode was developed for direct electron transfer to the electrode using a flavin adenine dinucleotide-glucose dehydrogenase enzyme immobilized on its surface by crosslinking. The enzyme’s active site was engineered to be less maltose-specific after it was isolated from Burkholderia cepacia (Yamashita et al. 2013). Similarly, an Au electrode was coated with a thin cysteamine film covering a double layer of immobilized glucose oxidase submerged in a chitosan (CS) solution. The glucose concentration was determined using cyclic voltammetry (Zhang et al. 2014). In another study, carbon nanotubes (multiwalled CNTs) coated with tiny tantalum (Ta) plates were used as electrodes. This electrode was again coated with a Nafion film immobilized glucose oxidase. Cyclic voltammetry transducer was then used to measure concentration of glucose (Cui et al. 2013). Amperometric glucose biosensors were developed using multiwalled CNTs by co-immobilizing adenine dinucleotide flavin and glucose dehydrogenase (made using the enzyme from Aspergillus oryzae) (Monošík et al. 2012). Another amperometric glucose biosensor was developed using electrochemical polymerization of Nphenylglycine film. It was made using the covalent immobilization of glucose oxidase on an N-phenylglycine surface that resulted from an interaction between the film and amino-carboxyl groups present in the glucose oxidase (Homma et al. 2014). In another study, an amperometric biosensor was made using carbon paste electrodes coated with silicon grease paste. This silicon grease paste was modified with glucose oxidase and maghemite (Fe2O3, γ-Fe2O3) nanoparticles. It was inserted into the hollow of the glass electrode, after which the current was measured using an amperometric transducer (Baratella et al. 2013). In a study comparing chronoamperometry and cyclic voltammetry, a gold electrode coated with Au-chitosan nanocomposites was electrodeposited via chronoamperometry. A thin film of nickel (Ni) was deposited on the surface of the electrode, and glucose oxidase immobilized on it. Chronoamperometry and cyclic voltammetry were used for the assessment of glucose oxidase catalytic activity (Zhao et al. 2013; Mathew and Sandhyarani 2013). In a similar study, a Pt electrode was electrooxidized with a polyvinylferrocenium perchlorate layer to determine glucose using cyclic voltammetry and amperometry. At the same time as Pt nanoparticles were electrodeposited on the modified electrode with electropolymerization of glucose oxidase and poly(o-phenylenediamine) on the electrode (Turkmen et al. 2014). Optical enzymatic biosensors were developed for determination of glucose concentration. Based on chemiluminescence, fluorescence, and phosphorescence techniques, the emission produced electrochemically was converted into an electrical signal for detection of glucose. In a study, an optical biosensor using a poly (luminol-aniline) nanowire composite was developed to measure glucose concentration (Li et al. 2010). In another study, optical enzymatic biosensor was developed

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using modified electrode surface coated in a layer of CS and glucose oxidase inside a produced glass carbon electrode covered with Au nanoparticles and CNTs for detection of glucose (Haghighi et al. 2011). Similarly, in a study, a Nafion film-wrapped electrode was taken in a glass carbon electrode modified with CNTs. Glucose oxidase and palladium (Pd) nanoparticles were placed on the surface of the modified electrode. The electrochemiluminescence technique was employed to ascertain the glucose content in them (Haghighi and Bozorgzadeh 2011). Another biosensor containing a solution of glucose oxidase, Au nanoparticles, CNTs, and Nafion film applied to CNTs was developed to measure glucose. It was prepared on graphite supports (5 × 5 × 30 mm) disseminated in a solution of ethanol-Nafion (Zargoosh et al. 2012). A glucose biosensor based on microarray plates doped with sol film using the fluorescence intensity was developed with rubidium (Rb) fluorophores. The glucose levels were determined as glucose oxidase might be found in the silica sol-gel (Chang et al. 2010). In another study, a glucose biosensor was developed using a hydrogel carrying a sol-gel matrix with glucose oxidase substrate that was immobilized to the egg membrane with coordination polymers made of crystalline iridium (Ir). The glucose levels were estimated using the phosphorescence technique (Ho et al. 2014). Zhang et al. developed a piezoelectric biosensor for real-time monitoring blood glucose level for the prophylaxis and treatment of diabetes using a flexible selfpowered implantable skin-like glucometer. It is based on the piezo-enzymaticreaction coupling effect of GOx@ZnO nanowire arrays. This device converts the mechanical energy to piezoelectric impulse for determination of blood glucose concentration (Zhang et al. 2018). In another study of piezoelectric biosensor, a quartz crystal microbalance (QCM) biosensor for detection of hemoglobin A1c (HbA1c) was developed. The variations in resonance frequency of QCM allow for the quantitative measurement of HbA1c. The HbA1c LOD with respect to hemoglobin is 0.147%. This biosensor aids in the creation of beneficial HbA1c sensing devices (Park and Lee 2018) (Fig. 1.1). The features of the abovementioned enzymatic glucose biosensors are summarized in Table 1.2. Enzymatic glucose sensors are typically electrochemical and optical transducers. Electrochemical transducers were employed more commonly in the past due to their great sensitivity, durability, simplicity of instrumentation, cheap cost, remarkable compatibility, and possibility for downsizing. Because the immobilization of the enzyme to the electrode in electrochemical transducers runs the risk of losing enzymatic function, optical transducers are growing in popularity (Mathew and Sandhyarani 2013).

1.4.4

Biosensors for Kidney Diseases

Premanode and Toumazou (2007) developed a new biosensor based on immobilized creatininase, creatinine, and urease employing ion-sensitive field effect transistors (ISFETs) for real-time monitoring in peritoneal dialysis. With a weak inversion at

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Fig. 1.1 The custom-made fluidic modules for QCM biosensor (Park and Lee 2018)

pH 6–8 and 37 °C, the circuitry demonstrated a linear relationship between urea and creatinine at the ranges of 0–200 and 0–20 mM, respectively (PD) (Fig. 1.2). Oleg Palygin et al. (2015) used two different sensor designs for ex vivo and in vivo protocols for creation of enzymatic microelectrode biosensors to measure endogenous ATP or H2O2 in the kidney. These protocols involved the detection of analyte by oxidation of H2O2 on a platinum/iridium (Pt-Ir) wire electrode and for reduction of H2O2 on a mediator-coated Au electrode, respectively. After calibration to known analyte concentrations, real-time amperometry is utilized to identify changes in the final concentration (Fig. 1.3). Pallavi Dasgupta et al. (2020) developed a practical point-of-care (POC) device using electrochemical biosensor that uses screen-printed electrodes for estimation of highly selective creatinine over the range of 0.2–4 mg/dL in a sample volume of 300 L without pre-processing. Creatinine is converted via a mono-enzymatic pathway to 1-methylhydantoin, whose concentration is measured by forming a complex with cobalt. This complex is validated via optical spectroscopy (Fig. 1.4). As it was already discussed, several innovative biosensors have been developed that may be used with a variety of physiological fluids that are frequently easy to get, can be miniaturized, and are particularly tempting for the POC market for patients with chronic kidney disease (CKD). For measuring the signs of renal disease, there are already portable and handheld POC equipment on the market. Examples of products that use enzymatic processes to detect creatinine electrochemically include StatSensor (Nova Biomedical, Waltham, MA, USA) and i-STAT (crea-cartridge,

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Table 1.2 Enzymatic biosensors’ overview Construction of sensor Glucose oxidase immobilized on a carbon paste electrode covered with surface-active maghemite nanoparticles Sol-gel-encased glucose oxidase was put onto a microarray with a Rb-fluorophore layer Fe phthalocyanine-modified CNTs covered with titanium dioxide layer and glucose oxidase immobilized therein A glassy carbon electrode covered with multi-walled CNTs and glucose oxidase immobilized on Pd nanoparticles Glucose oxidase is immobilized on a chitosan layer on multiwalled CNTs that are covered in gold nanoparticles on the surface of glassy carbon electrodes Egg membrane covered with glucose oxidase immobilized in hydrogel and crystalline Ir substrate Covalently immobilized glucose oxidase on a polymerized Nphenylglycine layer on the electrode surface Glucose oxidase immobilized on an Au-glass electrode using a chitosan-magnetic coating Gelatin, silicon oxide, polyvinyl alcohol, Prussian blue, and a selfassembled monolayer of cysteamine were used to immobilize glucose oxidase onto a Pt nanowire electrode Immobilized glucose oxidase on composite poly(luminolaniline) nanowire-coated graphite electrode Chitosan-Au nanostructures on an Au electrode are covered in a nickel hydroxide coating with glucose oxidase immobilized on it Co-immobilized flavin adenine dinucleotide and glucose

Transducer Amperometry

LOD 2.0 μmol/L

Reference Baratella et al. (2013)

Fluorescence

60.0 μmol/ L

Chang et al. (2010)

Cyclic voltammetry

30.0 μmol/ L

Cui et al. (2013)

Electrochemiluminescence

50.0 nmol/ L

Haghighi and Bozorgzadeh (2011)

Electrochemiluminescence

0.5 μmol/L

Haghighi et al. (2011)

Phosphorescence

10.0 μmol/ L

Ho et al. (2014)

Amperometry

30.0 μmol/ L

Homma et al. (2014)

Potentiometry

–

Khun et al. (2012)

Cyclic voltammetry

–

Shi et al. (2010)

Electrochemiluminescence

30.0 nmol/ L

Li et al. (2010)

Cyclic voltammetry, chronoamperometry

100.0 nmol/ L

Mathew and Sandhyarani (2013)

Amperometry

4.0 μmol/L

Monošík et al. (2012) (continued)

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Table 1.2 (continued) Construction of sensor dehydrogenase on a multi-walled carbon nanotube electrode in a chitosan layer Glucose oxidase mounted on a glassy carbon electrode with an Au thin film coating Pt nanoparticles covered with Pt electrode modified by polyvinylferrocenium concurrently immobilized glucose oxidase with poly(ophenylenediamine) Immobilized glucose oxidase on ZnO-Ag nanowire Glucose oxidase immobilized on a glassy carbon electrode covered with magnetic-silica-Au coreshell nanoparticles For direct electron transfer, flavin adenine dinucleotide-glucose dehydrogenase is immobilized on the surface of a functioning chip electrode Carbon nanotube film on graphite supports with glucose oxidase immobilized on Au nanoparticles Immobilized glucose oxidase on a thin cysteamine layer overlaying an Au electrode Glucose oxidase is immobilized on a silicon oxide electrode using phytic acid nanoparticles Coupling effect of GOx@ZnO nanowire arrays Mass changes of QCM caused by size enlargement of conjugated Au nanoparticles with thiolterminated SAMs on QCM sensor surface due to gold staining by hydrogen peroxide (H2O2) generated from enzymatic HbA1c assay

Transducer

LOD

Reference

Cyclic voltammetry, differential pulse voltammetry, amperometry Cyclic voltammetry, amperometry

0.3 μmol/L

Qiu et al. (2012)

20.0 μmol/ L

Turkmen et al. (2014)

Potentiometry

–

Cyclic voltammetry

0.2 μmol/L

Usman Ali et al. (2010) Wang et al. (2012)

Voltammetry

–

Yamashita et al. (2013)

Chemiluminescence, fluorescence

1.0 μmol/L

Zargoosh et al. (2012)

Cyclic voltammetry

50 and 300 μmol/L

Zhang et al. (2014)

Differential pulse voltammetry

10.0 μmol/ L

Zhao et al. (2013)

Piezoelectric

–

Quartz crystal microbalance (QCM)

0.147% HbA1c

Zhang et al. (2018) Park and Lee (2018)

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Fig. 1.2 Block diagram of the sensor system (Premanode and Toumazou 2007)

Fig. 1.3 Diagram of the biosensor’s protocol system (Palygin et al. 2015)

Abbott Point of Care Inc., Princeton, NJ, USA). The StatSensor is a simple device with significant potential that can quantify creatinine from a finger-prick sample, in contrast to the i-STAT device which has a volume requirement of 100 L and makes finger-prick sampling difficult. Despite these encouraging developments, POC sensing technology development remains difficult, necessitating substantial further research efforts. Notably, interaction with a number of the substances present in bodily fluids, including ascorbic acid, glucose, fructose, and ketone bodies, may have an impact on the measurement’s accuracy. Even when dealing with a complex

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Fig. 1.4 Serum creatinine electrochemical biosensor schematic (Dasgupta et al. 2020)

matrix like whole blood, conflicting reactions and signals may be reduced by using antibody-based sensors rather than enzymatic ones.

1.4.5

Biosensors for Neurological Diseases

Biosensors for neurological disease (ND) serve two purposes: they may be utilized to find new biomarkers and to be used as diagnostic instruments. These sensors include a wide variety of technologies, from experimental proofs of concept to commercially available kits. These sensors have detection efficiencies that are on par with or beyond those of the traditional test. Multistep immunoassays are a common part of the processes employed in clinical labs nowadays to diagnose ND. Due to the immunoassay’s reliance on antibody-antigen (Ab-Ag) interaction, these tests are easily adapted for use in biosensor, including Roche Diagnostics’ portable therapeutic drug monitor and Biacore® SPR (surface plasmon resonance). With the use of microarrays from firms like Affymetrix®, Agilent (gene-based), and Ciphergen, extensive biomarker discovery is now taking place (protein based). There are also studies on detection of neurological diseases but gene- and DNA-based biosensors have more commercial presence. Table 1.3 depicts a quick list of biosensor firms and platforms available commercially. Due to their prevalence in the diagnostic society, description of these biosensors is focused in this chapter.

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Table 1.3 Platforms and technologies for biosensors Company Affymetrix® Agilent Applied Biosystems Biobarcode

Platform probe/technology GeneChip® DNA-based microarray DNA-based microarray, uses 60-mer probes DNA-based microarray and protein biomarker discovery Nonenzymatic amplification

Cepheid Ciphergen

DNA-based microarray ProteinChip: protein, peptide, and Ab microarrays xMAP technology: cDNA or peptide/ protein/Ab-coated beads GeneCube™, geneCard™: genetic-, proteomic-, and immunogenic-based TDM technology: Ab-based handheld device Invader® technology: nucleic acid quantitation

Luminex Plexigen Roche Diagnostics Third Wave Technologies

Target analyte type Genetic Genetic Genetic, proteomic Genetic, proteomic, immunogenic, small molecules, complex targets Genetic Proteomic, immunogenic Genetic, proteomic, immunogenic Genetic, proteomic, immunogenic Drug analytes, potentially any Ag-Ab pair Genetic

The binding contact between Ag and Ab is detected by immunosensors. On the other hand, immobilized immunogenic peptides are employed to identify specific Abs in biological fluids. Immunoglobulins or immobilized Abs are used for detecting the presence of particular Ags. These sensors make use of the ease of different physical transducers while minimizing, and in some instances like eliminating, time-consuming washing and separating processes. After exposure to an acid (such as HCl or H2SO4), a base (such as tetraethylamine), a denaturant (such as urea), or a high salt concentration, many immunosensors may be recovered. The probes may be cost-effectively reused after being rejuvenated. Surface plasmon resonance (SPR) is used by a broad variety of immunosensors to identify and quantify neurological biomarkers. The interaction between particular anti-ADDL Abs and amyloid-β-derived diffusible ligands (ADDLs) has been quantified using an optical biosensor based on SPR for the detection of Alzheimer’s disease (AD) (Haes et al. 2005). To assess the pathogenic threshold for HD, normal and enlarged polyglutamine tracts have been characterized using Biacore® SPR devices (Bennett et al. 2002). Although the HD trait marker is easily recognized, other markers are required to better understand the age of illness start and progression. SPR is often used to find cancer biomarkers. There are several instances of prostate-specific antigen (PSA) detection, a marker for prostate cancer, at nano- to femtomolar levels (Yu et al. 2004; Huang et al. 2005). Additional instances of PSA detection using microcantilever and amperometric technology are available (Sarkar et al. 2002; Lee et al. 2005; Wee et al. 2005). The piezoelectric immunosensor array

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for acute leukemia is another cancer diagnostic concept using clinical immunophenotyping (Wang et al. 2004). Chips made from proteins or peptides have been utilized to find biomarkers. The Protein Chip platform is provided by Ciphergen Biosystems, Inc. for the identification and evaluation of biomarkers. Using this platform, a wide variety of biomarkers have been established for the diagnosis of Alzheimer’s disease (AD) (Carrette et al. 2003; Haes et al. 2005). Using surface-enhanced laser desorption/ionization time-offlight (SELDI-TOF) mass spectrometry, Ciphergen protein arrays have discovered a unique panel of early-stage AD biomarkers from CSF samples. Multiplexed analyte detection and quantification employing protein (e.g., Ab) and nucleic acid (e.g., cDNA) complexed probes are both possible with Luminex bead-based array devices. Seven hundred and fifty-six cervical cancer patient sera were studied utilizing Luminex systems. Human papillomaviruses (HPVs) come in more than 100 varieties, many of which are responsible for proliferative illnesses like cervical cancer. In this investigation, in situ affinity-purified recombinant HPV proteins against 27 Abs were simultaneously detected (Waterboer et al. 2005). According to the Luminex xMAP® technology requirements, the assay may test up to 100 distinct Ags concurrently in each reaction well. The collaboration between Luminex Corporation and Zeus Scientific for providing test kits for autoimmune disease was announced in May 2005 by Luminex Corporation. High-throughput gene expression profiling is offered by SuperArray Bioscience Corporation using Plexigen’s geneCube™ technology, which makes use of stacked detection arrays. The arrays may screen for a broad range of targets in bodily fluids and can be functionalized using nucleic acids, proteins, or antibodies. In a few of days, the system can examine tens of thousands of samples. Based on the BMI-1 oncogene pathway, the study team discovered an 11-gene signature for the chance of developing cancer. The expression of these cancer-related genes was examined using an Affymetrix® microarray (Glinsky et al. 2005). The 11-gene signature was linked to a higher chance of survival by the authors when it was paired with a statistical analysis of patient therapeutic outcome data. Additionally, they were successful in doing so for 11 distinct cancer types. To find disease signatures, the same approach is being used to study AD and other NDs.

1.5

Challenges and Future Scope

Since their introduction into the medical industry, biosensors have seen significant advancement. However, technology constantly leaves behind certain options that require additional study and development. Recognizing tiny molecules, improving sensitivity and selectivity in detecting various analytes, cross-linking, and immobilizing bioreceptors on the substrate are the key problems. Multiple biomarkers must be detected simultaneously using a single device in order to diagnose PCs (Shergujri et al. 2019). Microfluidics and biomarkers’ pattern software can be combined in the near future to create promising devices for use in this field (Tothill 2009). Biosensor sensitivity amplification has been a significant problem.

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There are various methods for increasing sensitivity. To increase the sensitivity of these devices, nanorods with high aspect ratios are chosen over spherical nanoparticles. Observing protein and protein interactions is more difficult than observing nucleic acid interactions since new amplification tools are not yet accessible. This situation is further enhanced by the complex interaction of the proteins and their increased nonspecific binding to solid supports. Consequently, it is anticipated that the potential for protein-nanoparticle hybrids would be completely promoted by nanoparticles that include mixed monolayers (Wang 2005). Most sensors require calibration prior to each usage as well as incubation in buffer solutions. Some sensors have a maximum concentration at which they can detect an analyte. This component is also influenced by the biosensor’s stability. Because bioreceptors are sensitive to variations in temperature, pressure, and pH value, long-term preservation and use of bioreceptors is a significant difficulty. Any modifications to the regular surroundings could cause the senses to become less sensitive. As the environmental circumstances change over time, biosensors with a higher stability range are considerably more favored. The stability of the biosensors in a changing environment is currently a significant challenge. Biosensors have been needed to detect numerous analytes for specificity in some cases. Multiple analytes may be required for the validation of some specific malignant cells. Therefore, it is necessary to build a dual-sensing capability in order to increase the biosensor’s specificity (Liu et al. 2017). Due to their immense potential in both research and commercial applications, biosensors are quickly becoming a necessity in today’s society. Reduction in cost and detectability of a variety of analytes are the advantages that can be achieved by combination of microfluidic technology and 3D printing. According to the World Health Organization (WHO), biosensor devices should be affordable, sensitive, specific, quick, dependable, equipment-free, and easily distributable (Ding et al. 2015). Enzymatic biosensors can be specialized for detection and diagnosis of diseases for treatment and lifesaving procedures (Sarkar et al. 2022). Despite the benefits of utilizing enzymes, several drawbacks, such as the enzyme’s quick loss of activity as a result of interactions with the electrode surface, result in a biosensor’s lifetime of only 2–4 weeks. However, this can be avoided if the enzyme is properly stabilized by selecting an appropriate matrix and a better method to immobilize the enzyme.

1.6

Conclusion

As enzymes are very specific to their respective substrates, use of an enzyme to detect a substrate or vice versa is very applicable in healthcare. Enzymes have been extensively used in amperometric, optical, and even piezoelectric biosensors. Biosensors based on enzymes have several uses in the fields of food, medicine, and environmental monitoring. Electrochemical and optical types of transductions are one of the most common types. In optical type, physical and chemical process of

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immobilization of enzyme is used. In electrochemical type, the enzymes themselves are used in the reaction to determine the action of the analyte on the enzyme. In healthcare, they can be used for estimation of various analytes. Enzymatic biosensors as an amperometric biosensor have been extensively used for detection of glucose using glucose oxidase as the biorecognition element. Commercially available biosensors are also mostly based on enzymatic biosensor because of their sensitivity, specificity, and necessary substrate combination of selectivity. The present trend in biosensor is to reduce the cost which is mainly due to the high cost of biological identification element. This will make biosensors available for point-of-care application. The development of tiny, self-contained devices for a variety of chemical or biological analyses, which play an increasingly significant role in our contemporary society, is centered on enzyme-based biosensors employing optical or electrochemical transducers. They will undoubtedly become more significant in the coming years. Acknowledgments We sincerely acknowledge the generous funding received from the Department of Biotechnology, India (No. BT/PR24652/NER/95/795/2017; Dated: 06/03/2019), sanction to Dr. Manashjit Gogoi for carrying out this piece of work.

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Vainzof M, Zatz M, Otto PA et al (1985) Serum CK-MB activity in progressive muscular dystrophy: is it of nosologic value? Am J Med Genet 22:81–87 Van Rees BP, Saukkonen K, Ristimäki A et al (2002) Cyclooxygenase-2 expression during carcinogenesis in the human stomach. J Pathol 196:171–179 Walaa Fikry ME (2017) Lactate dehydrogenase (LDH) as prognostic marker in acute leukemia quantitative method. J Blood Disord Transfus 8:1–8 Wang J (1999) Amperometric biosensors for clinical and therapeutic drug monitoring: a review. J Pharm Biomed Anal 19:47–53 Wang J (2005) Nanomaterial-based electrochemical biosensors. Analyst 130:421–426. https://doi. org/10.1039/B414248A Wang H, Zeng H, Liu Z et al (2004) Immunophenotyping of acute leukemia using an integrated piezoelectric immunosensor array. Anal Chem 76:2203–2209. https://doi.org/10.1021/ AC035102X Wang AJ, Li YF, Li ZH et al (2012) Amperometric glucose sensor based on enhanced catalytic reduction of oxygen using glucose oxidase adsorbed onto core-shell Fe3O4@silica@Au magnetic nanoparticles. Mater Sci Eng C 32:1640–1647. https://doi.org/10.1016/J.MSEC.2012. 04.055 Waterboer T, Sehr P, Michael KM et al (2005) Multiplex human papillomavirus serology based on in situ–purified glutathione S-transferase fusion proteins. Clin Chem 51:1845–1853. https://doi. org/10.1373/CLINCHEM.2005.052381 Wee KW, Kang GY, Park J et al (2005) Novel electrical detection of label-free disease marker proteins using piezoresistive self-sensing micro-cantilevers. Biosens Bioelectron 20:1932– 1938. https://doi.org/10.1016/J.BIOS.2004.09.023 Yamashita Y, Ferri S, Huynh ML et al (2013) Direct electron transfer type disposable sensor strip for glucose sensing employing an engineered FAD glucose dehydrogenase. Enzym Microb Technol 52:123–128. https://doi.org/10.1016/J.ENZMICTEC.2012.11.002 Yu F, Persson B, Löfås S, Knoll W (2004) Surface plasmon fluorescence immunoassay of free prostate-specific antigen in human plasma at the femtomolar level. Anal Chem 76:6765–6770. https://doi.org/10.1021/AC048937W/SUPPL_FILE/AC048937WSI20040720_055958.PDF Zargoosh K, Chaichi MJ, Shamsipur M et al (2012) Highly sensitive glucose biosensor based on the effective immobilization of glucose oxidase/carbon-nanotube and gold nanoparticle in nafion film and peroxyoxalate chemiluminescence reaction of a new fluorophore. Talanta 93:37–43. https://doi.org/10.1016/J.TALANTA.2011.11.029 Zhang S, Wright G, Yang Y (2000) Materials and techniques for electrochemical biosensor design and construction. Biosens Bioelectron 15:273–282 Zhang Y, Li Y, Wu W et al (2014) Chitosan coated on the layers’ glucose oxidase immobilized on cysteamine/Au electrode for use as glucose biosensor. Biosens Bioelectron 60:271–276. https:// doi.org/10.1016/J.BIOS.2014.04.035 Zhang W, Zhang L, Gao H et al (2018) Self-powered implantable skin-like glucometer for real-time detection of blood glucose level in vivo. Nanomicro Lett 10:1–11. https://doi.org/10.1007/ S40820-017-0185-X/FIGURES/6 Zhao W, Ni Y, Zhu Q et al (2013) Innovative biocompatible nanospheres as biomimetic platform for electrochemical glucose biosensor. Biosens Bioelectron 44:1–5. https://doi.org/10.1016/J. BIOS.2012.12.036 Żyłka A, Gala-Błądzińska A, Dumnicka P et al (2016) Is urinary NGAL determination useful for monitoring kidney function and assessment of cardiovascular disease? A 12-month observation of patients with type 2 diabetes. Dis Markers 2016:8489543

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Choice of Enzyme Immobilization Matrices Used in Biosensor for Healthcare Applications Sanjeev Bhandari, Manashjit Gogoi, and Mrityunjoy Mahato

2.1

Introduction

Immobilization of the enzymes means confining the specific enzyme molecules to a suitable support solid matrix, which are mostly inert polymer and inorganic materials (Sirisha et al. 2016). Enzymes have low reusability factor and low structural stability; thus, developing an enzyme-based sensor with high reproducibility is a challenging task (Kawaguti et al. 2006; Jesionowski et al. 2014). These limitations lead to confined and conditional uses of the enzyme-based sensor within narrow pH range, low thermal stability, and the loss of catalytic activity after one cycle (Liese and Hilterhaus 2013; Gray et al. 2013; Dicosimo et al. 2013). Studies have been conducted to find appropriate matrices which allow to retain enzyme structure under different sensing environments (Bornscheuer 2003; Betancor and Luckarift 2008; Badalo et al. 2006; Chen et al. 2008). In this regard, researchers have explored various nanostructure-/nanocomposites-based matrices for immobilization of the enzymes (Kim et al. 2006). Enzyme-based biosensors have been applied for sensing urea, glucose, cholesterol, penicillin, or other disease biomarker (Bostick and Hercules 1975; Ismail and Adeloju 2010; Raja et al. 2011). Biosensor is an analytical device used to detect biomarkers like antibodies, enzymes, and oligonucleotides at low concentrations (Malhotra and Chaubey 2003; Ispas et al. 2012). Biosensors also have wide applications in detecting toxins (in food and water), environmental monitoring, S. Bhandari · M. Mahato (✉) Physics Division, Department of Basic Sciences and Social Sciences, School of Technology, NorthEastern Hill University, Shillong, Meghalaya, India e-mail: [email protected] M. Gogoi Department of Biomedical Engineering, School of Technology, North-Eastern Hill University, Shillong, Meghalaya, India # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Patra et al. (eds.), Enzyme-based Biosensors: Recent Advances and Applications in Healthcare, https://doi.org/10.1007/978-981-15-6982-1_2

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Fig. 2.1 Different types of enzyme immobilization techniques. (Reprinted with permission from Sirisha et al. (2016), Advances in Food and Nutrition Research 79 (2016))

agriculture, etc. (Angela Leung et al. 2007; Kalyani et al. 2020; Zhang et al. 2018) due to their high specificity, high sensitivity, rapid response, and low cost (Amine et al. 2006). There are several ways to immobilize enzyme on the substrate, namely, adsorption, covalent bonding, entrapment, and ionic binding (Cordeiro et al. 2011). Adsorption method involves hydrophobic interaction, whereas covalent binding involves the formation of covalent bonds between the matrix and side chain amino acids (such as arginine, aspartic acid, etc.) (Hsieh et al. 2000; Fu et al. 2011). Entrapment method involves binding of the enzyme to the polymeric network using covalent or non-covalent bonds, in which the enzymes are bound with water as shown in Fig. 2.1 (Foulds and Lowe 1986). The water-soluble matrices such as polysaccharide derivatives, glass, synthetic polymers, etc. are used for immobilization of enzymes using adsorption methods (Wu and Lia 2008; Rosa et al. 2002). Different types of entrapment techniques such as gel entrapment, microencapsulation, and fiber entrapment are used for enzyme immobilization (Dinelli 1972; Wadiack and Carbonell 1975).

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Required Properties of Matrices for Enzyme Function

Immobilization of the enzyme is done by selecting the appropriate matrix. Hence, the supporting matrix must have the following properties (Sirisha et al. 2016): 1. The enzyme should be operational under various conditions and the matrix should have mechanical and thermal resistance. 2. The selected matrix should enhance the enzyme specificity (Magner 2013). 3. Pore diameter should be of the appropriate range, because if pore size is large, then surface area will decrease and if pore size is small, the protein will be excluded (Hartmann and Kostrov 2013; Tran and Balkus 2011). 4. The matrix after immobilization should behave inertly and not interfere in any reaction. 5. The matrix should be stable and highly regenerable. 6. The hydrophobicity of the matrix should be minimized so that the protein is prevented from denaturing (Zhou and Hartmann 2012; Rodrigues et al. 2013). 7. The support matrix should have antimicrobial properties.

2.2

Variety of Reported Matrices

2.2.1

Nanocellulose (CNC)/Gold Nanoparticle (AuNP) Nanocomposite

CNC/AuNP matrix for enzyme immobilization was prepared using the following two steps by Mahmoud et al. (2009). At first, CNCs were prepared by grounding flax fibers with a 20-mesh screen to obtain 0.85 mm fiber size followed by mixing of flax fibers (5 g) in 20 mL acid solution. Later, H2O2 (10 mL) was added dropwise on the prepared mixture. The solution temperature was cooled till 45 °C for 3 h followed by dilution with deionized water (DI) and centrifuging (10,000 rpm) to achieve a pH 6. Firstly, the prepared CNC resin was mixed with ion-exchange resin, namely, DOWEX MR-3 for 2 days, and removed using filtration (Whatman 541) followed by sonication for 35 min. Secondly, gold(III) chloride trihydrate (HAuCl4
3H2O, 10 mM) and R-CD were added to CNC (23 mg/mL) along with sodium borohydride (0.1 M, 20 μL) till a reddish color of AuNPs/CNCs is obtained. The solution was centrifuged (10,000 rpm) and washed three times to remove unbound AuNPs. The resulting AuNP/CNC colloid was incubated in an ethanol solution (0.05 M) of thioctic acid (Thc) for 24 h. The CNC/AuNP (0.5 mL, 6 mg) was mixed with CGTase enzyme (7–8 mg/mL) in a 0.1 M phosphate buffer (0.5 M NaCl at pH 7.2) followed by centrifuging to get a supernatants. The enzyme loading capacity of the nanocomposite was found to be 220 mg/g of AuNPs/CNCs. The maximum CGTase binding activity was leveled at 50,000 U/g of AuNPs/CNCs.

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AuNP/Silica Nanocomposite

AuNP/mesoporous silica composite was used to immobilize the enzyme (Bai et al. 2007); poly(ethylene oxide) (P123, 0.4 mM) and potassium chloride (KCl, 30 mM) were mixed with HCl (2.0 M, 30 mL) at 38 °C followed by addition of tetraethyl orthosilicate (TEOS, 2.1 g, 20 mM) under stirring for 8 min. The solution was kept for 1 day and autoclaved at 100 °C for 24 h and collected after filtration, washing with water at room temperature. The prepared powder was slurred with HCl/EtOH solution at 78 °C for 6 h for removal of templates. Later, silica (SBA-15) was dissolved in ethanol solution of silane (APTS) and refluxed at 80–90 °C for 24 h to give H2N-SBA-15 and washed with ethanol. HAuCl4 (2 mL) was added to H2N-SBA-15 and stirred for 30 min which resulted in colorless solution and the silica powder turned yellowish. Reduction of Au(III) was done using NaBH4 solution (0.1 M, 1 mL) with AuCl4 adsorbed H2N-SBA-15 and stirred for 10 min. The red wine solid GNPs/SPA-15 was collected after washing with distilled water. Before using glucose oxidase (GOx), it was oxidized to carbaldehydes by reacting GOx solution (5 mL) in 0.1 M PBS buffer (pH 6.86) with sodium metaperiodate (30 mg) for 1 h at 4 °C in the dark. Next, GNPs-SBA-15 (2 mg) with polyvinyl alcohol (PVA, 1 mL) was stirred for 1 h to get a composite gel which was dropped (8 μL) on Au electrode and allowed to dry and dipped in 2-aminoethanethiol aqueous solution (20 mM) for 2 h. This modified electrode was dipped in GOx (20 μM with 0.1 M) for 80 min. Figure 2.2 shows the different steps used in the immobilization of the enzyme in the matrix. The biosensor exhibits an excellent bioelectrocatalytic response to glucose with linear range of 0.02–14 mM and high sensitivity of 6.1 mA/M/cm2. Au/H2N-SBA-15/IO4- oxidized GOx have large surface area which result in high enzyme loading, thereby resulting in high sensitivity because sensitivity depends on the concentration of the enzyme loaded in the matrix.

2.2.3

NCC/PEI/AuNP Nanocomposite

GOx was immobilized on nanocomposite of PEI-treated NCC/AuNPs in three steps (Incani et al. 2013); firstly, nanocrystalline cellulose (NCC) colloidal suspension was prepared by dispersing NCC in deionized water and sonicating for 3 min. Secondly, polyethylenimine (PEI) treatment on NCC/AuNPs was done by adding the NCC solution with PEI (2 mL) under stirring for 1 h at room temperature. The pH was made to 1.5 with the help of HCl (5% v/v) followed by centrifuging (20,000 rpm) for 20 min and washing with water to obtain NCC/PEI/AuNPs which was freeze-dried overnight. The nanocomposite was thiol modified by suspending the NCC/PEI/ AuNPs in the 3-mercaptopropionic acid (3MPA, 0.05 M, ethanol solvent), centrifuging at 20,000 rpm for 20 min, and washing with ethanol two times to get NCC/PEI/AuNPs-S(3MPA). Glucose oxidase (GOx) was immobilized on the thiolmodified nanocomposite by suspending 5 g NCC/PEI/AuNPs-S(3MPA) in 50 mM 2-(N-morpholino) ethanesulfonic acid (MES) and 500 mM sodium chloride (NaCl)

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Fig. 2.2 Fabrication processes of the Au electrode modified GOD/GNPs-SBA-15. (Reprinted with permission from Bai et al. (2007), Sensors and Actuators B 124 (2007))

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at pH 5 under stirring for 24 h. The resultant solution was suspended in GOx (3 mL, 5 g) followed by centrifuging and washing with water twice to get NCC/PEI/AuNPsS(3MPA)-NHGOx nanocomposite with immobilized enzyme.

2.2.4

Polydopamine/Magnetic-Chitin (MCT) Nanocomposite

Magnetic-chitin (MCT) particles (size 1.5 nm) were modified with dopamine for immobilization of amylase (Sureshkumar and Lee 2011). Chitin (CT, 3 g) was added with hydrochloric acid (HCl, 6 M, 80 mL) under stirring at 4 °C for 48 h and the supernatant was mixed with 50 mL of iron chloride (FeCl3
6H2O) and ferrous sulfate (FeSO4
7H2O) in 2:1 ratio. Sodium hydroxide (NaOH, 1.5 M) was slowly added to get chitosan magnetic particles. The prepared MCT solution was stirred overnight with dopamine (2 mg/mL) to produce DMCT particles. The polydopamine surface was further modified with glutaraldehyde (GA) by adding DMCT (1 g) with GA (10 mL, 8% v/v) for 2 h at 4 °C to get DMCT-GA. Figure 2.3 shows the steps used in the immobilization of the enzyme by adding DMCT-GA (1 g) with α-amylase (80 mg/L) at 4 °C in a rotary shaker for 24 h. The immobilized α-amylase retained

Fig. 2.3 Schematic diagram of polydopamine coating and amylase immobilization on magnetic-chitin microparticles. (Reprinted with permission from Sureshkumar and Lee (2011))

MCT

Dopamine

2HN D-amylase

GA DMCT

N H N H

N H

DMCT-GA 2HN D-amylase

N H N H N H

N H N H N H

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over 70% of its original activity after six times of repeated use (Sureshkumar and Lee 2011).

2.2.5

Calcium Carbonate (CaCO3) Nanoparticles

GOx was immobilized with CaCO3 nanoparticles by mixing nano-CaCO3 colloidal suspension (2 mg/mL) in deionized water under stirring for overnight (Shan et al. 2007). Next, GOx solution (2 mg/mL) was mixed with deionized water. Later, a proper amount of GOx/nano-CaCO3 mixture (60 μg of GOx, 30 μg of CaCO3) was spread on a platinum disk electrode and kept for drying overnight at 4 °C. The modified disk electrode was kept in glutaraldehyde vapor at room temperature for 15 min and the electrode was characterized using SEM (Fig. 2.4). The biosensor exhibited a low detection limit (0.1 M), a wide linear range of 0.001–12 mM, and a high sensitivity of 58.1 mA/cm2/M. The enzyme loading capacity of the nanocomposite was found to be 60 g of GOx. The enzyme activity was found best when the pH was 6.5.

2.2.6

Metallic Biosilica

Butyrylcholinesterase enzyme was immobilized in metallic biosilica (Luckarift et al. 2004); silica-condensing synthetic peptide (R5, 100 mg/mL) was prepared in deionized water and silicic acid was prepared by tetramethyl orthosilicate (TMOS) with HCl (1 mM). The TMOS (10 mg/mL), R5 peptide (10 μL), and butyrylcholinesterase (80 μL) were mixed at room temperature for 5 min. The silica particles with immobilized enzyme were collected after centrifuging (10 s, 14,000 rpm) and washing two times with deionized water. The enzyme loading capacity in the biosilica nanospheres was found to be 220 mg enzyme/g silica (20% w/w).

2.2.7

Graphene Oxide

Horseradish peroxidase (HRP) was immobilized on graphene oxide in two steps (Zhang et al. 2010); firstly, graphene oxide (GO) was prepared using a hammer method (Hummers and Offeman 1958); typically, graphite powder (100 g) and sodium nitrate (50 g) were mixed in 2.3 L of sulfuric acid followed by cooling at 0 °C in ice bath. Next, potassium permanganate was added in a controlled manner. Later the ice bath was removed and the temperature was kept at 35 °C for 30 min which resulted in a brownish grey color paste. Afterward, 4.6 L of water was added to the paste which resulted in the rise of temperature (98 °C) and maintained for 15 min. The solution was further diluted with 14 L of warm water and treated with hydrogen peroxide (3%). The suspension was filtered to obtain a yellow brown cake which was washed with warm water to give graphene oxide residue. Next, the

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Fig. 2.4 SEM photographs of (a) nano-CaCO3 and (b) GOx/nano-CaCO3 films. (Reprinted with permission from Shan et al. (2007), Biosensors and Bioelectronics 22 (2007))

powder form of graphene oxide was obtained by centrifuging and dehydration (40 °C) over phosphorus pentoxide in the vacuum chamber. The GO (0.1 M) was added to a PBS solution of HRP enzymes and incubated for 30 min on ice bath and later centrifuged. The resultant supernatant after centrifugation was used to determine the enzyme loading. Figure 2.5 shows the AFM image of GO mixed with HRP and also the model of immobilizing the HRP on the GO matrix. The maximum loading of HRP on GO at pH 7.0 is about 100 μg/mg of GO.

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Fig. 2.5 AFM images of the GO-bound HRP with (a) lower and (b) higher enzyme loadings. (c) Schematic model of the GO-bound HRP. (d) Reaction rates of GO-bound HRP versus HRP concentration. (Reprinted with permission from Zhang et al. (2010), Langmuir, 26 (2010))

2.2.8

Chitosan/AuNP Nanocomposite

GOx was immobilized on chitosan/AuNP matrix using the following steps (Luo et al. 2004); initially, AuNPs were prepared by adding trisodium citrate (1%, 2.5 mL) with boiling HAuCl4 (0.01%, 100 mL) which resulted in the formation of AuNP (size 17 nm). The immobilization of the GOx with the chitosan and AuNPs was done using electrochemical deposition wherein a clean pair of electrodes were dipped in the solution containing chitosan (0.5%), AuNP (0.8 nM), and GOx (5 mg/mL) for 5 min. At 3 V H+ was reduced to H2 at the cathode and released, and chitosan hydrogel incorporated with GOx and gold nanoparticles was electrodeposited on the cathode surface. Later the electrode is removed from the solution and rinsed thoroughly with water. Figure 2.6 shows the UV-visible studies of individual components and mixed, which conforms to the immobilization of the GOx on the chitosan/gold nanoparticle matrix. The biosensor exhibited a linear range from 5.0 M to 2.4 mM. The immobilized GOx can retain activity (up to pH 9.0), indicating that

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Fig. 2.6 UV-Vis absorption spectra of (a) chitosan solution, (b) chitosan mixed with GOx, (c) gold nanoparticles, (d) chitosan mixed with GOx and gold nanoparticles. (Reprinted with permission from Luo et al. (2004), Analytical Biochemistry, 334 (2004))

the deposited chitosan and gold nanoparticles provide a biocompatible microenvironment for GOx.

2.2.9

SnO2 Hollow Nanotubes

Enzymes such as GOx, HRP, or lipase were immobilized on the SnO2 nanotubes (Anwar et al. 2017). At first, tin(II) chloride (SnCl2, 0.4 g) was dissolved in the mixture of DMF (2.5 mL) and ethanol (2.5 mL) in the ratio of 1:1. Later PVP (0.5 g) was added to the prepared solution and kept for 3 h at 50 °C followed by electrospining at 0.5 mL/h at 14–15 kV. The final product after electrospining was collected and dried overnight in the oven at 120 °C. In order to form SnO2 nanoparticles and for removal of excess PVP, the product was thermally annealed in air for 1 h at 500 °C. The immobilization of the enzyme was done by adding SnO2 nanoparticles and was functionalized by adding glutaraldehyde (0.6 M) with the SnO2 nanoparticles. These functionalized nanoparticles were added to the enzyme (1 mg) such as GOx, HRP, or lipase and incubated for 24 h (150 rpm, 4 °C). The unbound enzyme was removed by separating the supernatant after centrifugation (13,000 rpm, 10 min, and 4 °C) (Fig. 2.7) The bonded lipase showed a half-life value of 4.5 h at 70 °C and retained 91% of its original activity even after ten repetitive cycles of use.

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Fig. 2.7 Schematic diagram showing the synthesis of SnO2 hollow nanotubes followed by their functionalization and enzyme immobilization. (Reprinted with permission from Anwar et al. (2017), Scientific Reports (2017))

2.2.10 GCE/Clay/Glutaraldehyde Nanocomposite GOx was immobilized in the nanocomposites in two steps (Seleci et al. 2012); firstly, the modification of the clay was done by dispersing the sodium mont in water (at room temperature, for 24 h). Next, methylamine (0.02 mmol) solution was added to Mont solution and stirred (24 h, room temperature) and washed with water and methanol mixture (1:1 ratio) to get modified mont (M-Mont). The GCE electrode was polished with alumina slurry (0.5 mm) and the electrode was cleaned by ultrasonication for 2 min in ethanol and water mixture (1:1 ratio). The M-mont solution (1 mg/mL in PBS), bovine serum albumin (BSA, 1 mg/mL, 2.5 mL), GOx (0.5 mg), and glutaraldehyde (2.5 mL, 5% in PBS) were mixed and were drop casted on the GCE surface and dried. The optimized biosensor showed a very good linearity between 0.05 and 1.0 mM, and a limit of detection to glucose of 0.038 mM.

2.2.11 PB/Chitosan Nanocomposite Modified electrodes were immobilized in the following manner (Zhang et al. 2013). Initially, Pt electrodes were cleaned with piranha solution (7:3 mixture of H2SO4/ H2O2) under sonication for 30 min. Next, two different solution were prepared: one consisting of potassium ferrocyanide (K4[Fe(CN)6], 0.01 M) and potassium chloride (KCl, 0.1 M) and hydrogen chloride (HCl, 0.1 M) and the other of iron(III) chloride

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Fig. 2.8 SEM images of (a) PB/Pt, (b) Chi/PB/Pt, (c) Chi/PB/Pt, and (d) GOx/Chi-IL/PB/Pt. (Reprinted with permission from Zhang et al. (2013), Sensors and Actuators B 176 (2013))

(FeCl3+, 0.01 M), KCl (0.1 M), and HCl (0.1 M). The pre-treated electrode was dipped in the first solution for 1 min and 30 s followed by dipping in the second solution for 1 min to get 30 layers of PB coating on the modified electrode. The immobilization of the enzyme was done by adding GOx (10 mg/mL) and 1-butyl-3methylimidazolium tetrafluoroborate ([bmim] BF4, 4% v/v) in chitosan solution (1 mg/mL). Later this enzyme mixture (5 μL) was dropped on the PB-modified electrode to give GOx/Chi/PB/Pt and was characterized using SEM (Fig. 2.8). The biosensor exhibited satisfactory storage stability over 40 days with retention of 90.4% activity. This biosensor exhibited a linear range from 0.01 to 4.2 mM, a low detection limit of 5 μM, and a sensitivity of 37.8 A/mM/cm2. The sensitivity of the biosensor increased when GOx (36 U) was added to the matrix.

2.2.12 Chitosan-Glutaraldehyde (GA) Nanocomposite Chitosan matrix cross-linked with GA was used for the enzyme (peroxidase) using the following two steps (Miao and Tan 2000). Firstly, carbon paste electrode (CPE) was made by mixing graphite powder (5 g) and silicone oil (3 mL) in a mortar which resulted in carbon paste. This carbon paste was packed inside a glass tube with 3.5 mm inner diameter and 5 mm outer diameter, and a copper wire was inserted in the glass tube containing the carbon paste. Secondly, chitosan (1 g) was dissolved in

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acetic acid (100 mL, 0.8% v/v) to give chitosan solution followed by stirring (250 rpm, 3 h) at room temperature. Next, HRP solution was prepared by dissolving HRP (66 mg) in a phosphate buffer (0.02 M, pH 7) containing glycerol (5 mL) followed by drop casting through pipet on the CPE and keeping it for 1 h of drying. Later, the chitosan solution (5 mL, 1%) was pipetted to cover the enzyme on modified CP, and glutaraldehyde (0.025% m/v) was drop casted on the chitosancovered HRP electrode. The biosensor showed linearity for H2O2 concentration in the range of 4.7 × 10-5 to 2.0 × 10-3 M.

2.2.13 Chitin/Lignin Nanocomposite Lipase was immobilized onto chitin-lignin material using the following procedure (Zdarta et al. 2015). Initially, chitin-lignin mixture (1:1) was dissolved lignin in hydrogen peroxide (15%) followed by stirring (1000 rpm, 30 min). Chitin was added under stirring for 2 h and washed with distilled water and dried for 24 h at temperature of 105 °C. The enzyme lipase (0.5 mg/cm3 in PBS buffer) was added into chitin/lignin (250 mg) in a conical flask followed by shaking to give a precipitate and filtered under reduced pressure and kept for drying for 24 h. The enzyme immobilization was also confirmed using NMR studies of chitin-lignin, lipase, and chitin/lignin/lipase as shown in Fig. 2.9. The nanocomposite retains 80% catalytic activity after 20 reaction cycles.

2.2.14 Chitosan-Albumin-Based Macroporous Protein Cryogel (MPC) MPC was used for immobilization of the enzyme in two steps (Hedström et al. 2008). Firstly, aqueous solution of hen egg albumin (15% w/v) was mixed under stirring with chitosan (2% w/v in 0.5% acetic acid). A glutaraldehyde (cross-linker) solution was added under stirring for 15 s and poured in the plastic column (13 mm inner diameter) and frozen at -18 °C for 15 h and washed with distilled water. GOx (15 U/mL) and HRP (113 U/mL) were mixed with albumin/chitosan solution before the addition of glutaraldehyde. The enzyme containing cryogel was placed in a glass tube (10 mm inner diameter) and attached with the flow injection analysis (FIA) system. The enzymes GOx and HRP retained approximately 80% of enzyme activity when integrated in the MPC structure.

2.2.15 Poly-vinyl Resin Support Immobilization of GOx and cholesterol oxidase (COx) on organic support was carried out with the following process (Jha et al. 2014). Initially, the membrane was prepared by mixing poly-vinyl resin (2 mL of 4% (w/v)) with chloroform and ethylene dichloride mixture (1:1 v/v). The enzymes GOx and COx (5 U/mL each) were added to the membrane mixture under stirring for 2 min and air-dried for 4–6 h.

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Fig. 2.9 NMR spectra of (a) the chitin-lignin material, (b) the native lipase, and (c) the product following 24 h of immobilization of the enzyme. (Reprinted with permission from Zdarta et al. (2015), Mar Drugs (2015))

The unbound enzymes were removed by washing with distilled water and stored at room temperature. The prepared membrane was incubated with glutaraldehyde (0.5%). There was a decline in the activity of native GOx and COx enzymes within 5 and 25 days, respectively, whereas immobilized GOx and COx showed detectable activity till 65 days of storage.

2.2.16 PANI Film Immobilization of alcohol oxidase (AOX) on PANI film was carried out in two steps (Kuswandi et al. 2014). Firstly, aniline (0.3 g) was purified under vacuum with continuous stirring followed by mixing with HCl solution (1.0 M, 10 mL). Another solution was made by mixing ammonium peroxydisulfate (0.18 g) with HCl

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(10 mL). These two solutions were mixed for 30 s and washed with water and centrifuged three times to get a supernatant green color PANI particles. These PANI particles were filtered in 55 mm glass fiber filter (Whatman GFA) and were drop casted on polystyrene substrate and was dried in dark to give a PANI film. The PANI film was immersed in PBS buffer solution (pH 7, 0.1 M) and then AOX solution (10 μL) was drop coated on the PANI film and kept for 30 min for drying. The biosensor has a linear response in an ethanol concentration range of 0.01–0.8%; limit detection of the biosensor was 0.001%, with reproducibility (RSD) of 1.6% and a lifetime of 7 weeks.

2.2.17 Polytyramine Films The penicillinase enzyme was entrapped into a polytyramine matrix by galvanostatic polymerization of tyramine (Ismail and Adeloju 2010). Initially, stock solution of penicillinase (74 U/mL) and penicillin-G (0.01 M) was made by dissolving in milliQ water. Next, tyramine (4-hydroxyphenethylamine) was dissolved in milli-Q water containing orthophosphoric acid (1 mL) to give a concentration of 0.1 M. Later, electro-polymerization of monomers was done using three electrode systems in which platinum was used as a working electrode after polishing with alumina (0.3 μm). The monomer solutions such as tyramine (0.03 M), penicillinase (37 U/ mL), penicillin (3 mM), and KNO3 (0.01 M) were kept in the electrode cell, and a current density of 0.8 mA/cm2 was applied for 40 s, which resulted in polytyraminepenicillinase films.

2.2.18 MoS2/TiO2/Au Nanocomposite HRP was immobilized on MoS2/TiO2/Au composite in four steps (Tang et al. 2018). At first, MoS2 was prepared by dissolving sodium molybdate dihydrate (Na2Mo4
2H2O) in pure water (25 mL) and sonicated for 5 min. The pH was adjusted with HCl (0.1 M, 6.5) and L-cysteine (0.5 g) was added. The mixture was kept in autoclave for 36 h at 200 °C and cooled. The black precipitate was collected, washed, and dried at 60 °C to get MoS2. Titanium tetrachloride (3.6 mL) solution (38 mL) was kept in an ice-water bath under stirring for 10 min till a white suspension is obtained. The MoS2 nanospheres (0.25 g) were added under stirring followed by addition of chloroform (3.6 mL) to obtain a black suspension and kept in autoclave for 12 h at 60 °C to get MoS2-TiO2. MoS2-TiO2 (36 mg) was dispersed in pure water (36 mL) followed by addition of hydrogen tetrachloroaurate (HAuCl4
3H2O, 0.01 M) and sodium citrate (4 mL, 0.01 M) under stirring. The sodium bromide (0.1 M) was added and stirred for 30 min. The resultant MoS2/TiO2/ Au composite was centrifuged, washed, and dried for 8 h. HRP was added to MoS2/ TiO2/Au along with chitosan solution (1 mL, in 0.2 M acetic acid) under sonication (20 min) and drop casted on glass carbon electrode (GCE) and dried as shown in Fig. 2.10. Aptamer solution (tetracycline, 3 mL) was immobilized on modified GCE

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Fig. 2.10 Schematic diagram showing the immobilization process on the prepared MoS2/TiO2/Au composite. (Reprinted with permission from Tang et al. (2018), Sensors and Actuators B 258 (2018))

(drying for 12 h) followed by dropping of avidin-HRP solution (5 μg/mL, 5 μL) on the surface of the aptasensor for 15 min and washed with water and stored at 4 °C. The prepared aptasensor showed a linear range from 1.5 × 10-10 to 6.0 × 10-6 M, and a detection limit of 5 × 10-11 M.

2.3

Conclusion

Matrices for enzyme immobilization are important for its reusability and to retain enzyme structure after storage or after reuse. Effort has been made to summarize the various types of enzyme immobilization matrices which can be used in healthcare and industrial applications. Different enzymes are found in literature such as lipase, GOx, HRP, COx, amylase, butyrylcholinesterase, etc., and various support matrices are found such as SnO2 hollow nanotubes, graphene oxide, CaCO3, chitin/lignin, PB/chitosan, GCE/clay/glutaraldehyde, chitosan/glutaraldehyde, CNC/AuNPs, etc. The essential parameters of enzyme immobilization such as reaction temperature, centrifugation speed, reaction time, storage temperature, pH, etc. have been summarized. At the end, Tables 2.1 and 2.2 summarize enzymes and support matrices used for biosensor development useful in healthcare and industrial application. Acknowledgments Authors acknowledge DST-SERB, Government of India, for the financial support through SERB projects (No. EMR/2016/002634 and EMR/2016/004219) sanctioned to Dr. Mrityunjoy Mahato. Dr. Manashjit Gogoi would like to acknowledge DBT, Government of India, for the DBT-Twin project (No: 102/IFD/SAN/2494/2018-2019). Sanjeev Bhandari thanks SERB for providing the Non-Net JRF fellowship.

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47

Table 2.1 Different types of support matrix for enzyme immobilization for healthcare biosensor application S. no. 1. 2.

10.

Support matrix AuNPs/SBA-15 NCC/PEI/AuNPssilica Polydopaminechitin CaCO3 Chitosan/AuNPs GCE/clay/ glutaraldehyde PB film with chitosan Chitosan with glutaraldehyde Albumin/chitosan cryogel Organic support

11.

3. 4. 5. 6. 7. 8. 9.

Healthcare application Glucose biosensor Glucose biosensor

Enzyme used in biosensor GOx GOx

Biotechnological application Glucose biosensor Glucose biosensor Glucose biosensor

α-Amylase GOx GOx GOx

Sureshkumar and Lee (2011) Shan et al. (2007) Luo et al. (2004) Seleci et al. (2012)

Glucose biosensor

GOx

Zhang et al. (2013)

Hydrogen peroxide biosensor Glucose biosensor

HRP

Miao and Tan (2000) Hedström et al. (2008) Jha et al. (2014)

HRP GOx and COD

PANI film

Cholesterol biosensor Alcohol biosensor

12.

Polytyramine Films

Penicillin biosensor

Penicillium

13.

MoS2/TiO2/AuNPs

Tetracycline biosensor

HRP

Alcohol oxidase

References Bai et al. (2007) Incani et al. (2013)

Kuswandi et al. (2014) Ismail and Adeloju (2010) Tang et al. (2018)

GOx glucose oxidase, HRP horseradish peroxidase, COx cholesterol oxidase, CGTase cyclodextrin glycosyltransferase, NCC nanocrystalline cellulose, MoS2 molybdenum disulfide, TiO2 titanium dioxide, AuNPs gold nanoparticles, PB Persian blue, GCE glass carbon electrode, 3MPA 3-mercaptopropionic acid, PEI polyethylenimine Table 2.2 Different types of support matrix for enzyme immobilization in industrial applications S. no. 1. 2. 3. 4. 5.

Support matrix CNC/AuNPs Metallic biosilica Graphene oxide SnO2 hollow nanotubes Chitin/lignin

Immobilization enzyme CGTase Butyrylcholinesterase HRP Lipase, GOx, and HRP Lipase

References Mahmoud et al. (2009) Luckarift et al. (2004) Zhang et al. (2010) Anwar et al. (2017) Zdarta et al. (2015)

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Enzymatic Biosensor Platforms for Diagnosis of Heart Diseases Jasmeen Kaur, Rohit Srivastava, and Vivek Borse

Abbreviations ACC ACS AHA AMI ANP AST BNP CAD CC CDC ChEt ChOx CK-MB CRP cTn

American College of Cardiology Acute coronary syndrome American Heart Association Acute myocardial infarction Atrial natriuretic peptide Aspartate aminotransferase B-type natriuretic peptide Coronary artery disease Chronocoulometry Centers for Disease Control and Prevention Cholesterol esterase Cholesterol oxidase Creatine kinase-MB C-reactive protein Cardiac troponin

Jasmeen Kaur and Vivek Borse contributed equally with all other contributors. J. Kaur · R. Srivastava NanoBios Laboratory, Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India V. Borse (✉) NanoBioSens Lab, Department of Medical Devices, National Institute of Pharmaceutical Education & Research (NIPER), Hyderabad, Telangana, India Department of Pharmaceuticals, Ministry of Chemicals and Fertilizers, Government of India, Hyderabad, Telangana, India e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Patra et al. (eds.), Enzyme-based Biosensors: Recent Advances and Applications in Healthcare, https://doi.org/10.1007/978-981-15-6982-1_3

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CV CVDs DET DPV ECG ELISA ESC FAD GO GPDH H-FABP HQ HRP IMA LDH MIP MWCNTs NAD NT-proBNP OCP PANI PB PBNPs PD PDDA PEI POCT PPI PVP PW rGO sCD40L SELEX SPCE SPE SWCNTs SWV TC WHO

J. Kaur et al.

Cyclic voltammetry Cardiovascular diseases Direct electron transfer Differential pulse voltammetry Electrocardiogram Enzyme-linked immunosorbent assay European Society of Cardiology Flavin adenine dinucleotide Graphene oxide Glycerol-3-phosphate dehydrogenase Heart-type fatty acid-binding protein Hydroquinone Horseradish peroxidase Ischemia-modified albumin Lactate dehydrogenase Molecularly imprinted polymers Multi-walled carbon nanotubes Nicotinamide adenine dinucleotide N-terminal proBNP Open circuit potential Polyaniline Prussian blue Prussian blue nanoparticles 1,10-Phenanthroline-5,6-dione Poly(diallyl dimethylammonium chloride) Polyethyleneimine Point-of-care testing Poly(propylene imine) Polyvinylpyrrolidone Prussian white Reduced graphene oxide Soluble fragment CD40 ligand Systematic evolution of ligands by exponential enrichment Screen-printed carbon electrode Screen-printed electrode Single-walled carbon nanotubes Square wave voltammetry Total cholesterol World Health Organization

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Enzymatic Biosensor Platforms for Diagnosis of Heart Diseases

3.1

53

Introduction

Heart diseases are the leading cause of fatalities across the world. It involves a range of disorders related to the heart and blood vessels, hence also known as cardiovascular or cardiac diseases. Some common heart diseases include coronary artery disease (CAD), atherosclerosis, peripheral artery disease, acute myocardial infarction (AMI), cerebrovascular disease, heart failure, rheumatic heart disease, cardiomyopathy, and congenital heart defects, among many others. The World Health Organization (WHO) has reported 17.9 million deaths in 2016 (representing 31% of all global deaths) and estimated almost 23.6 million deaths by 2030 (WHO 2017 2021). Early and rapid diagnosis is extremely important to reduce the high rate of mortality due to cardiovascular diseases (CVDs). Researchers across the globe are focusing on the best means to diagnose, analyze risk, and manage patients with suspected CVDs. The routine diagnosis of CVDs includes assessing clinical symptoms, characterizing the chest pain, evaluating changes in the electrocardiogram (ECG), observing the echocardiogram (cardiac imaging), and measuring several specific cardiac biomarkers in blood. The interest in biomarker testing has increased considerably in the last two decades due to its fundamental role in diagnosing and monitoring CVDs. Assessment of the appropriate concentrations of cardiac biomarkers plays a significant role, especially in the diagnostic profile of patients with atypical symptoms and a nondiagnostic ECG (McDonnell et al. 2009). Estimating the elevated levels of cardiac biomarkers can predict cardiovascular risk and aid in diagnosing several CVDs. An ideal biomarker should fulfill certain criteria, including high clinical sensitivity and specificity, rapid release for timely diagnosis, longer elevated time for the efficient diagnosis, and importantly, measurable qualitatively as well as quantitatively (Yang and Min Zhou 2006). Several analytical procedures have been developed to quantify the concentration of cardiac biomarkers as part of laboratory analysis. Enzyme-linked immunosorbent assay (ELISA) is one of the standard procedures that offers high sensitivity and specificity. However, the conventional laboratory testing techniques for the detection of biomarkers include complicated assay procedures, require skilled technicians, and are costly and time-consuming. Early and rapid analysis of cardiac biomarkers is essential for timely diagnosis and better clinical decision-making. Point-of-care testing (POCT), on the other hand, offers testing at or near the patient’s site and allows rapid results, thereby helping in better diagnosis as well as monitoring and management of the patients. Testing the cardiac biomarkers using the POCTs reduces the turnaround time, accelerates decision-making, and expedites treatment. POCT has been prevalent for over a long time now, explicitly utilizing the various forms of biosensors. Biosensors are analytical devices that consist of a biorecognition element (that recognizes the analyte of interest), usually immobilized on a transducer exteriorly (that translates the biochemical signal produced during recognition into a measurable one). The biorecognition element employed can be of the classical ones such as enzymes, nucleic acids, antibodies, whole cells, etc., or the recently emerging entities such as phages, aptamers, molecularly imprinted polymers, affibodies, etc. (Justino et al. 2015). The biosensors may operate through

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various transduction methods such as calorimetric, optical, electrochemical, piezoelectric, etc., to generate detectable signals. Broadly, the biosensors can be categorized as catalytic- or affinity-based biosensors depending on the nature of the biorecognition element used. Catalytic biosensors are mostly used to detect redox-active target molecules that undergo a catalytic reaction on the surface of a biocatalyst, such as enzymes, microorganisms, etc. For example, cholesterol oxidase is used as a bioreceptor as well as a biocatalyst for the detection of cholesterol. In contrast, affinity biosensors use the interaction of certain bioreceptor molecules such as antibodies, aptamers, synthetic DNA, molecularly imprinted polymers (MIP), etc., to the target analyte to create a signal using a transducer. Enzymes are the most primitive bioreceptor molecules used in biosensor applications and can be employed in both catalytic and affinity biosensors. In the catalytic-based biosensors, enzymes act as catalysts and carry out biochemical reactions by binding to the target analyte, whose steady-state concentration, either formed or lost due to the enzyme’s biocatalytic reaction, is measured directly. In affinity-based biosensors, enzymes are used as accelerators or signal amplifiers in electrochemical reactions (Sanati et al. 2019). The excellent biocatalytic activity and high specificity are the key advantages of enzymatic biosensors. This chapter describes the different enzymatic biosensors developed for the detection of cardiac biomarkers with examples.

3.2

Cardiac Biomarkers

Cardiac biomarkers are the biological agents discharged into the bloodstream in response to the underlying pathophysiological changes in the myocardial tissue. For instance, the pathophysiology of acute coronary syndrome (ACS) involves the deposition of lipids and inflammatory and cellular materials leading to the formation of atherosclerotic plaque, followed by tissue inflammation. Further, the plaque becomes unstable over time, resulting in its rupturing, and hence, triggers clot/ thrombus formation. The thrombus formation may block the blood flow to the heart, a condition called ischemia, causing a shortage of oxygen, finally leading to a cardiac stroke (heart attack). The lipid deposition in the coronary arteries can be identified by measuring the levels of cholesterol. Increased cholesterol levels are associated with high blood pressure and can damage arteries by forming atherosclerotic plaques. Hence, cholesterol is an important biomarker associated with a high risk of CVDs. Similarly, thrombin is involved in blood coagulation (thrombus formation) and various pro-inflammatory activities, making it a biomarker of interest for evaluating clinical hemorrhagic risk or thrombosis. The biomarkers are typically classified based on the pathological process they reflect (Jacob and Khan 2018; McDonnell et al. 2009), such as: 1. Inflammation, e.g., soluble fragment CD40 ligand (sCD40L), C-reactive protein (CRP), myeloperoxidase, and homocysteine

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Table 3.1 Cardiac biomarkers and their clinical characteristics (Adapted from Burcu Bahadir and Kemal Sezgintürk 2015; Pedrero et al. 2014; Qureshi et al. 2012) Cardiac biomarker Cholesterol

Myoglobin CK-MB cTnI cTnT CRP

BNP NTproBNP H-FABP MPO

Type of CVD indicator Indicator of hypertension, arteriosclerosis, and myocardial infarction

Specificity High

AMI (early indicator) AMI/diagnosis of reinfarction AMI AMI Inflammation

Low Medium

ACS/heart failure/ ventricular overload ACS/heart failure/ ventricular overload Myocardial necrosis Inflammation

High

0.01–0.1 ng/mL 0.05–0.1 ng/mL Low risk 3– 15 × 103 ng/mL –

High

0.25–2 ng/mL

Low Low

≥6 ng/mL >350 ng/mL

High High High

Cutoff levels Total cholesterol (TC) 6.2) (Ahmadraji and Killard 2016) 70–200 ng/mL 10 ng/mL

2. Myocardial ischemia, e.g., heart-type fatty acid-binding protein (H-FABP) and ischemia-modified albumin (IMA) 3. Necrosis, e.g., cardiac troponins, creatine kinase-MB (CK-MB), and myoglobin 4. Hemodynamic stress, e.g., natriuretic peptides (NPs): atrial natriuretic peptide (ANP), B-type natriuretic peptide (BNP), and N-terminal proBNP (NT-proBNP) 5. Plaque instability, e.g., choline and pregnancy-associated plasma protein-A (PAPP-A) Some of the clinically used biomarkers are summarized in Table 3.1. Traditionally, the enzymatic activities of lactate dehydrogenase (LDH), aspartate aminotransferase (AST), and creatine kinase (CK) were used to diagnose ACS (Jacob and Khan 2018). However, these enzymes were replaced by other biomarkers that are detected much earlier with better sensitivity and specificity. Myoglobin is one of the earliest markers that increases within 1–4 h of the beginning of necrosis. The typical serum concentration ranges from 30 to 90 ng/mL, which can rise to 900 ng/mL during AMI (Burcu Bahadir and Kemal Sezgintürk 2015). However, it has a low cardiac specificity as it is expressed in skeletal muscle cells as well. Creatine kinase isoform (CK-MB) has a slow dynamic change increasing within 4–9 h of necrosis but may increase in the non-MI situation. It is an important biomarker for AMI-diagnosed patients as its increase is associated with the infarct size that can further help diagnose reinfarction (Costa et al. 2008). Cardiac troponins (cTnT and cTnI) play a central role in myocyte contraction and are more specific to necrosis than the other biomarkers. Because of their high

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specificity and sensitivity, they are considered the “gold standard” biomarkers for AMI diagnosis. Although cTnI and cTnT are not the early markers as their level increases within 4–9 h of necrosis, these show elevated levels for a longer time (7–10 days post-AMI onset) (Dasgupta and Wahed 2014). Its highest level is closely linked to the infarct extent. The European Society of Cardiology and the American College of Cardiology (ESC/ACC) have reframed MI based on the rise and/or fall of the concentration of troponin biomarker, with at least one value above the 99th percentile of a healthy population with assay imprecision of 10% or less (Thygesen et al. 2012). While small amounts of cTnT are also expressed in skeletal muscles, cTnI has a nearly absolute myocardial tissue specificity. C-reactive protein is a plasma protein identified as a biomarker of inflammation, and its high levels can predict cardiovascular risk. According to the American Heart Association (AHA) and the Centers for Disease Control and Prevention (CDC), CRP concentration below 1 mg/mL is regarded as low risk, between 1 and 3 mg/mL is considered as moderate risk, and greater than 3 mg/mL is considered as high risk. During an acute phase of inflammation, the concentration can rise to 1000-folds, often leading to cardiovascular risk (Qureshi et al. 2012). BNP and NT-proBNP are the most common natriuretic peptides released in the blood plasma in response to volume or pressure overload by the cardiac ventricular cells (Wang et al. 2020). These are considered the most vital biomarkers for diagnosing heart failure and for risk assessment in patients with suspected heart failure.

3.3

Enzymatic Biosensors for the Detection of Cardiac Biomarkers

Enzymes are proteins that catalyze various biochemical reactions and, in turn, allow the recognition of several analytes of interest. They enable the detection of a wide array of analytes directly by detecting the substrate or the product of the enzymatic reaction or indirectly by detecting the inhibitors and mediators of the catalytic reaction (Justino et al. 2015). Compared to other biosensing techniques, enzymatic biosensors offer several significant advantages, including ease of preparation, quick response time, high sensitivity, the likelihood of reusing the enzymes (as they are not consumed during the analysis), and the availability of highly pure enzymes commercially. Moreover, enzymatic recognition can be easily combined with different transducers, i.e., calorimetric, optical, electrochemical, and piezoelectric, thereby allowing detection flexibility and a broad range of applications. Among all the transduction mechanisms, the electrochemical transducer is most commonly employed in enzymatic biosensors, possibly because the first biosensor developed by Clark and Lyons in the 1960s was an enzymatic electrochemical biosensor. Optical biosensing with enzymatic biosensors employs either colorimetric, fluorescent, or luminescent substrates of the enzymes that produce a measurable response. Enzyme-based optical biosensors are quite well studied and reported but relatively less common for cardiac biomarkers. Electrochemical sensing offers quick response, high sensitivity, and easy miniaturization and has low power requirements.

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The association of the high sensitivity and selectivity of biocatalysts to the userfriendly, low-cost, and portable electrochemical instrumentation allows real-time and POC analysis of complex analytes. There are several electrochemical techniques employed for detecting cardiac biomarkers. Amperometry is the most frequently used analytical technique; it involves applying an appropriate potential to the working electrode to initiate a redox reaction of an electroactive element. The generated current is relative to the target analyte concentration. Based on the electron transmission routes among the redox enzyme and the electrode, enzymatic amperometric biosensors are classified as first-generation, second-generation, and thirdgeneration biosensors. The first-generation enzymatic amperometric biosensors involve natural enzyme co-substrate or product-based electron transfer, while the second-generation enzymatic amperometric biosensors involve artificial redox mediator-based electron transfer. However, the third-generation enzymatic amperometric biosensors involve direct electron transfer (Monteiro and Almeida 2019). Different voltammetric methods such as cyclic voltammetry, square wave voltammetry (SWV), differential pulse voltammetry (DPV), and stripping voltammetry have been employed for the electrochemical analysis of enzymatic biosensors. Electrochemiluminescence has also been used as the basis of several enzyme-based biosensors. The electrogenerated chemiluminescence biosensor systems involve the enzyme-catalyzed reactions that generate H2O2, coupled with the luminol light-emitting reaction (Zhang et al. 2012). The produced H2O2 as a result of an enzymatic reaction oxidizes luminol to produce chemiluminescence. Based on this principle, the luminol-H2O2 ECL system has significantly expanded the applications of enzymatic biosensors for detecting several analytes. Enzymatic biosensors are one of the most advanced analytical devices that are widely accepted commercially. Nevertheless, conventional enzyme-based biosensors are inadequate for selectivity, sensitivity, and stability. The recent advancements in the field of nanotechnology and material sciences have opened ways for enhancing the sensitivity of enzymatic biosensors. The enzymenanomaterial bioconjugates provide more surface area for the immobilization of a larger number of enzymes and thus, offer improved catalytic activity. Other advantages of nanomaterials, such as enhanced electrical and optical properties, also improve the accuracy and lifetime of enzymatic biosensors. With the developments in microfluidics and lab-on-a-chip methods, the fabrication of highly sensitive, user-friendly, and portable POC devices for the detection of cardiac biomarkers has become a lot easier.

3.3.1

Catalytic Biosensors for the Detection of Cardiac Biomarkers

Enzymes have been extensively used as bioreceptors in the development of various biosensors because of their highly selective nature. A majority of catalytic biosensors employ enzymes as the bioreceptor molecule. The proximity of the enzyme to the transducer surface is essential for efficient sensitivity in enzymebased catalytic biosensors, which is attained by immobilization of the enzymes on

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the transducer surface. Enzyme immobilization is a complex and vital requirement that determines the accuracy, precision, and lifetime of the developed biosensors. For electrochemical sensing, enzymes are generally immobilized on the electrode surface, and the redox reaction of the analyte with the enzyme produces measurable signals. The electron transmission among the active site of the enzyme and the electrode’s surface is responsible for the analytical performance of the fabricated biosensor. Stable immobilization of the enzyme on the electrode surface is important, especially for third-generation biosensors, as it would allow the study of the direct electron transfer mechanism of the enzyme that can help develop highly sensitive and specific biosensors. Moreover, one of the significant challenges in the development of enzymatic biosensors is to ensure the functionality of the immobilized enzyme over time. Nanostructured materials have been extensively explored as a substrate for stable immobilization of enzymes with intact activity as well as for the efficient transmission between the redox enzymes and the electrode surface. The mechanical, catalytic, and optoelectronic properties of nanomaterials have been exploited to enhance the sensitivity and shelf life of enzymatic biosensors. Even distribution of both the nanostructure and the enzyme is a key requirement to ensure high sensitivity and maintain the biological activity of the enzyme.

3.3.1.1 Cholesterol Biosensors Clinical routine analysis of blood cholesterol levels is essential for preventing the risks of many heart diseases. Rapid detection of cholesterol with high selectivity and sensitivity is imperative for diagnosing and managing various heart diseases. The majority of the reported cholesterol biosensors are electrochemical enzymatic biosensors, which involve a simple experimental setup with inexpensive chemicals. The most commonly used enzymes in cholesterol biosensors are cholesterol esterase (ChEt) and cholesterol oxidase (ChOx) because of their high selectivity toward esterified and free cholesterol, respectively. ChEt catalyzes the hydrolysis of esterase-esterified cholesterol. On the other hand, ChOx is a flavin adenine dinucleotide (FAD) containing flavoenzyme that uses the flavin cofactor to oxidize cholesterol to cholest-5-en-3-one in the presence of oxygen and subsequently isomerize it to cholest-4-en-3-one (Basu et al. 2007). Molecular oxygen recycles the reduced cofactor and generates H2O2. H2O2 is the final product of the reaction of ChOx on cholesterol and hence, following the formation of H2O2 is one of the common approaches used in cholesterol biosensors to determine cholesterol concentration. Table 3.2 summarizes various enzyme-based catalytic biosensors for cholesterol detection. Electrocatalysis of H2O2 is the basis of many electrochemical cholesterol biosensors. The underlying mechanism of these biosensors involves oxidation or reduction of H2O2 (produced by the action of ChOx on cholesterol) by HRP immobilized onto the sensing surface along with a redox mediator to enhance the electron transfer. For example, hydroxymethyl ferrocene and HRP-modified carbon paste electrode was developed for ChOx-based biosensor, where hydroxymethyl ferrocene was used as a redox mediator (Charpentier and El Murr 1995). Similarly, Li et al. immobilized ChEs, HRP, ChOx, and potassium ferrocyanide on

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Table 3.2 Recent enzyme-based catalytic biosensors for cholesterol detection Technique Differential pulse voltammetry (DPV)

Electrode/matrix ChOx/ KMWNTs/GCE and ChEt/ChOx/ KMWNTs/GCE

Range 0.050– 16.0 μmol/L

LOD 10.0 nmol/L (free cholesterol) and 12.0 nmol/L (esterified cholesterol) 38.7 ng/dL (1 nM)

PDMS microchip with three reservoirs— waste, buffer, and sample reservoirs Amperometry (ChEt/ChOx)FG/Gr electrode Electrochemiluminescence ChOx/AuNPs/lcys-rGO/GCE Potentiometry ChOx/InN QDs

38.7 μg/dL (1 μM) and 270.6 mg/dL (7 mM)

Amperometry

50 μM– 10 mM

1 μM

0–15 mM

0.2 mM

0–10 mM

2 mM

2.5–25 μM

0.5 μM

4 μM to 5 mM

1.33 μM

0.1–10 mM

0.075 mM

Amperometry

ChOx/G/PVP/ PANI/paper electrode Amperometry ChOx/PBNP/ SPEs Amperometry Triton X-100/ SPE (Ag paste electrode) Amperometry ChOx/Fc-RGOP/ GCE Electrochemiluminescence ChOx/CHIT/ CeO2-NG/GCE Cyclic voltammetry ChOx/QDs/PPI/ GCE

50–300 μM

15 μM

3.3 μM to 1.0 mM 1 × 10-6 to 1 × 10-3 M

1.1 μM –

Reference Li et al. (2011)

Ruecha et al. (2011)

Manjunatha et al. (2012) Zhang et al. (2012) ul Hassan Alvi et al. (2013) Ruecha et al. (2014) Cinti et al. (2015) Ahmadraji and Killard (2016) Halder et al. (2017) Du et al. (2017) Mokwebo et al. (2018)

ChOx cholesterol oxidase, ChEt cholesterol esterase, H2O2 hydrogen peroxide, KMWNTs potassium-doped multi-walled carbon nanotubes, GCE glassy carbon electrode, FG functionalized graphene, Gr graphite, AuNPs gold nanoparticles, l-cys L-cysteine, rGO reduced graphene oxide, QDs quantum dots, G graphene, PVP polyvinylpyrrolidone, PANI polyaniline, PBNPs Prussian blue nanoparticles, SPE screen-printed electrodes, Fc ferrocene, RGOP polymer functionalized reduced graphene oxide, CHIT chitosan, CeO2 ceria nanocomposites, NG nitrogen-doped graphene, PPI poly(propylene imine), ECL electrochemiluminescence

screen-printed carbon electrodes (SPCE), where potassium ferrocyanide was used as a redox mediator (Li et al. 2005). A disposable screen-printed total cholesterol biosensor was also reported that used an ink media containing ChEt and cholesterol dehydrogenase as enzymes, a nicotinamide adenine dinucleotide (NAD) as the

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coenzyme, and a 1,10-phenanthroline-5,6-dione (PD) as the electron mediator (Fang et al. 2011). Several other cholesterol biosensors are based on the direct oxidation or reduction of H2O2, eliminating the use of HRP and redox mediators. These biosensors are simple, more precise, and inexpensive to fabricate. The direct electron transfer (DET) of enzymes on an electrode requires a biocompatible matrix for immobilization to retain the native structure of redox enzymes (Manjunatha et al. 2012). Several nanostructured materials have been used to modify electrodes to provide better enzyme immobilization and facilitate the DET of enzymes. For instance, potassium-doped MWCNTs have been used to detect free and esterified cholesterol (Li et al. 2011). The direct chemistry of enzymes cholesterol oxidase and esterase was explored by immobilizing them on KMWNT-modified glassy carbon electrode. The biosensor provided an increased effective area for enzyme immobilization and accelerated the electron transmission among the enzyme and the electrode, giving an enhanced electrochemical response in the range of 0.05–16 μmol/L. The electrocatalytic activity of Prussian blue nanoparticles (PBNPs) deposited on screen-printed electrodes (SPEs) was also utilized to develop a cholesterol biosensor based on DET (Cinti et al. 2015). At low applied potential, Prussian blue (PB) is electrochemically reduced to Prussian white (PW), which further catalyzes the reduction of H2O2 (produced by the oxidation of cholesterol by ChOx). The PBNP-modified electrode thus developed offered low-cost fabrication with excellent sensitivity, reproducibility, and linear range (0–15 mM). Some of the recent cholesterol biosensors use hybrid nanostructures to develop a more stable and electrochemically active biosensor to achieve better selectivity and sensitivity. A nanocomposite composed of graphene (G), polyaniline (PANI), and polyvinylpyrrolidone (PVP) was used to modify paper-based electrodes (Fig. 3.1a) (Ruecha et al. 2014). An excellent electrocatalytic activity was shown by the modified electrode toward the oxidation of H2O2 produced by ChOx. The CdTe/ CdSe/ZnSe core-multishell quantum dots and poly(propylene imine) dendrimer (PPI) were used as nanocomposite materials for a ChOx-based biosensor by Mokwebo and co-workers (2018). An efficient electron transfer was achieved between ChOx and the PPI/QD-modified electrode with a linear range of detection, i.e., 0.1–10 mM. A hybrid nanomaterial system has also been used for the development of a redox mediator-based cholesterol biosensor. Ferrocene was used as the redox mediator anchored on the reduced graphene oxide nanosheets using a polymeric matrix, polyethylenimine (PEI) (Fig. 3.1b) (Halder et al. 2017). The functional nanocomposite system prepared was electrochemically active and provided a biocompatible microenvironment for the attachment of redox enzymes (ChOx), allowing it to retain its catalytic activity. The hybrid biosensing system for cholesterol offered high stability, good reproducibility, excellent selectivity, and sensitivity with a limit of detection of 0.5 μM.

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Fig. 3.1 (a) The enzymatic reaction between cholesterol and ChOx on G/PVP/PANI-modified paper-based biosensor (Ruecha et al. 2014). (b) Schematic illustration of structure, electron transfer, and bioelectrocatalysis of Fc-RGOP-enzyme systems (Halder et al. 2017)

3.3.2

Affinity Biosensors for the Detection of Cardiac Biomarkers

Affinity biosensors commonly use antibodies (immunosensors) and aptamers (aptasensors) as biorecognition elements. The interaction between the biorecognition element and the analyte of interest forms a complex that generates a detectable signal. Enzymes are used as labels in affinity biosensors for additional signal enhancement to improve their sensitivity. Enzyme-based affinity biosensors are the most common type of biosensors developed for the detection of cardiac biomarkers. Some of the recently developed enzyme-based affinity biosensors for the detection of cardiac biomarkers are summarized in Table 3.3, along with their analytical performances.

Amperometry

Amperometry

Amperometry

Cyclic voltammetry (CV)

Amperometry

cTnT

CRP

cTnI

NTproBNP

cTnI

Analyte Technique Immunosensors cTnT Amperometry

Anti-cTnl/PDDARGO/Au electrode

Anti-NT-proBNP/ DpAu/BSA-CNTs/Au electrode

PS/CMWCNTs/PEG nanofibers/GCE

Anti-CRP/protein A/PEI/MWCNT/SPE

Anti-cTnT/aminoMWCNT/SPCE

Anti-cTnT/COOHCNT/PEI/Au electrode

Electrode/matrix/ capture probe

Anti-cTnl-HRP

AuNCs-HRP-Ab2

Anti-cTnI-HRP

Anti-CRP-HRP

Anti-cTnT-HRP

Anti-cTnT-HRP

Signal probe

Table 3.3 Recent enzyme-based affinity biosensors for cardiac biomarkers

Signal generated by electrocatalytic reduction of H2O2 by HRP Signal generated by electrocatalytic reduction of H2O2 by HRP Signal generated by electrocatalytic reduction of H2O2 by HRP Signal generated by electrocatalytic reduction of H2O2 by HRP [Fe(CN)6]3-/4- used as a redox mediator Signal generated by electrocatalytic reduction of H2O2 by HRP HQ used as a redox mediator Signal generated by electrocatalytic

Assay format

0.1–10 ng/ mL

0.02– 100 ng/ mL

Li et al. (2017)

Zhuo et al. (2011)

6 pg/mL

0.024 ng/ mL

Rezaei et al. (2018)

0.04 ng/ mL

Buch and Rishpon (2008)

0.5 ng/ mL 0.5– 200 ng/ mL 0.5–2 ng/ mL

Freitas et al. (2014)

GomesFilho et al. (2013)

0.016 ng/ mL

0.033 ng/ mL

0.1–10 ng/ mL

Reference

0.02– 0.32 ng/ mL

LOD

Range

62 J. Kaur et al.

Amperometry

Open circuit potential (OCP)

Potentiometry

Amperometry

Amperometry

Amperometry

BNP

cTnI

CTnI

cTnT

cTnT

cMyo

Anti-cMyo/suspended carbon mesh/substrate-

Anti-cTnT-biotin/ streptavidin microspheres/SPE

Anti-cTnT/poly (o-ABA)/GCE

Anti-cTnI/polypyrrole/ screen-printed gold electrode

Anti-cTnl/AuNP/ITO electrode

Anti-BNP/AuNPs-SPhe-SPCE

Polyclonal anticMyo

Anti-cTnT-HRP

Anti-cTnT-HRP

Anti-cTnI-HRP

Anti-cTnI-HRP

Anti-BNP-HRP

reduction of H2O2 by HRP Signal generated by electrocatalytic reduction of H2O2 by HRP HQ used as a redox mediator Signal generated by electrocatalytic reduction of H2O2 by HRP HQ used as a redox mediator Signal generated by HRP activity on ophenylenediamine in the presence of H2O2 Signal generated by electrocatalytic reduction of H2O2 by HRP HQ used as a redox mediator Signal generated by electrocatalytic reduction of H2O2 by HRP Generation of electroactive species 0.1 and 10 ng/mL

0.05– 5.0 ng/mL

Sharma et al. (2018)

0.43 pg/ mL

Enzymatic Biosensor Platforms for Diagnosis of Heart Diseases (continued)

Silva et al. (2010)

Mattos et al. (2013)

Purvis et al. (2003)

0.2 ng/ mL

0.016 ng/ mL

10 pg/ mL (0.4 pM)

Saleh Ahammad et al. (2011)

–

1–100 ng/ mL

0.01– 100 ng/ mL

Serafín et al. (2018)

4 pg/mL

0.014 and 15 ng/mL

3 63

Technique

Chronocoulometry (CC)

Electrochemiluminescence

Piezoelectric

Piezoelectric

Analyte

cTnI

cTnI

CRP

CRP

Table 3.3 (continued)

Anti-CRP/MNPs/QCM electrode

ELISA—anti CRP pre-coated PS 96-well microtiter plate

Anti cTnI/PEI-RGO

Anti-cTnI-biotin/ avidin/ITO electrode

bound IDA nanoelectrodes

Electrode/matrix/ capture probe (PAP) by β-gal activity on PAPG substrate combined with redox cycling electrochemical species (PAP/PQI) Signal generated by an electrocatalytic reduction of GP by GPDH Ru(NH3)63+ used as a redox mediator Signal generated by the luminol- H2O2 ECL system SBP amplifies the signal in the presence of H2O2 Precipitate production on electrode by HRP activity on AEC substrate Precipitate production on electrode by HRP activity on AEC substrate Ab + Polyclonal β-gal labeled antiIgG

AuNPs-HRP/HRPAnti-CRP (AB2)

Fe3O4@SiO2@AuHRP-anti CRP-HRP

Anti-cTnI-SBP

Anti-cTnl-GPDH

Assay format

Signal probe

0.001– 100 ng/ mL

0.01– 200 ng/ mL

5– 30,000 pg/ mL

–

Range 0.001– 100 ng/ mL

Gan et al. (2012)

Zhou et al. (2013)

0.3 pg/ mL

Tang et al. (2018)

3.3 pg/ mL

3 pg/mL

Dutta et al. (2015)

Reference

10 pg/ mL

LOD

64 J. Kaur et al.

Amperometry

Amperometry

Fluorescence

Chemiluminescence

Chemiluminescence

CRP

NTproBNP

cTnI

hs-CRP

cTnI

NT-proBNP Ag/EDC-NHS/COOHMBs as capture probe (competitive assay format) Au/SPE used as the working electrode ELISA: antibody immobilized microwell plate LFIA: asymmetric polysulfone membrane (ASPM) + substrate pad (LUMINOL + luminol enhancer [p-coumaric acid] + H2O2 generator [choline chloride]) + NC membrane coated with capture, detection and control Abs + choline oxidase enzyme

Anti-CRP/COOHMBs/Au/SPE

AuNP-anti cTnIHRP

Anti-CRP-HRP

ALP

Anti-NT-proBNPHRP

Anti-CRPBiotin + Strep-HRP

In situ formation of fluorescent Si-PDs by ALP activity Signal generated by the luminol/H2O2 CL system H2O2 is generated as a result of oxidation of choline chloride by choline oxidase

Signal generated by electrocatalytic reduction of H2O2 by HRP TMB used as redox mediator Signal generated by an electrocatalytic reduction of H2O2 by HRP TMB used as a redox mediator

Joung et al. (2014)

1.05 ng/ mL

0.019 ng/ mL

1– 10,000 ng/ mL

–

Enzymatic Biosensor Platforms for Diagnosis of Heart Diseases (continued)

Han and Kim (2019)

Liu et al. (2020)

0.1 ng/ mL

–

EstebanFernández de Ávila et al. (2013a)

EstebanFernández De Ávila et al. (2013b)

0.02 ng/ mL

21 pg/ mL

0.12– 42.9 ng/ mL

0.5– 1000 ng/ mL

3 65

Chemiluminescence

cTnI

Thrombin

Differential pulse voltammetry (DPV)

Aptasensors Thrombin Differential pulse voltammetry (DPV)

Technique

Analyte

Table 3.3 (continued)

TBA2-AuNPsignal probe + SAALP

G-quadruplex/ hemin/HRP/AuPd/ poly(ophenylenediamine) nanoprobes

MCH/aptamer/AuNP/ GCE

Anti-cTnI-ALP

Signal probe

MCH/TBA1/AuNPs/ WSe2/GCE

Electrode/matrix/ capture probe ELISA: anti-cTnI immobilized microwell plate Anti-cTnI/MBs

Aptamer-based sandwich assay + ECC redox cycling triggered by ALP acting on substrate AAP Aptamer based sandwich assay + Signal amplification by HRP, HRP-mimicking DNAzyme and AuPd NP poly (phenylenediamine) acts as the redox mediator and the signal generated is enhanced by

Assay format Signal generated by the luminol/H2O2 CL system Signal generated as a result of enzymatic chemiluminescence and magnetic immunoassay

20 fM

100 fM– 20 nM

Wang et al. (2017)

Wang et al. (2018)

Liu et al. (2014)

0.1 ng/ mL

190 fg/ mL

Reference

LOD

0–1 ng/ mL

0.1–50 ng/ mL

Range

66 J. Kaur et al.

Amperometry

Differential pulse voltammetry (DPV)

Chemiluminescence

Thrombin

cTnI

cTnI

Integrated microfluidic platform: aptamer (TnI2) coated magnetic beads

MCH/NTH-Tro4/ SPGE

Aptamer-streptavidinAuNPs/FeDC-SPCE

1° Ab + 2° Ab/HRP

Fe3O4/PDDA/ Au@Pt-HRPGHD-Tro6 hybrid nanoprobes

Ab-AuNPs-HRP

electrocatalytic reduction of H2O2 by HRP Aptamer-based sandwich assay + signal enhancement by electrocatalytic reduction of H2O2 by HRP Aptamer-based sandwich assay + signal amplification by HRP, HRP-mimicking DNAzyme and Au@Pt nanozymes Signal generated is enhanced by electrocatalytic reduction of H2O2 by HRP and HQ is used as a redox mediator Enzyme-linked DNA aptamer assay: protein sandwiched b/w aptamer and 1° Ab. Further, HRP labeled 2° Ab is added along with

Gopinathan et al. (2019) 12 ng/L 60– 2400 ng/L

Enzymatic Biosensor Platforms for Diagnosis of Heart Diseases (continued)

Sun et al. (2019)

Yeh et al. (2014)

7.5 pg/ mL

1.5 pM

10 pg/mL to 100 ng/ mL

10 pM– 100 nM

3 67

Technique

Electrode/matrix/ capture probe Signal probe HRP substrate to produce luminescence

Assay format

Range

LOD

Reference

COOH-CNT carboxylated carbon nanotubes, PEI polyethylenimine, MWCNTs multi-walled carbon nanotubes, SPCE screen-printed carbon electrodes, SPE screen-printed electrode, PS polystyrene, CMWCNTs carboxylated multi-walled carbon nanotubes, PEG polyethylene glycol, GCE glassy carbon electrode, ELISA enzyme-linked immunosorbent assay, Si-PDs silicon polymer dots, MNPs silicon dioxide-coated magnetic Fe O nanoparticles, QCM quartz crystal microbalance, AEC 3-amino-9-ethylcarbazole, SA-ALP streptavidin-conjugated alkaline phosphatase, ECC electrochemical-chemical-chemical, ALP alkaline 3 4 phosphatase, AAP ascorbic acid 2-phosphate, FeDC ferrocene dicarboxylic acid, GHD G-quadruplex/hemin DNAzyme

Analyte

Table 3.3 (continued)

68 J. Kaur et al.

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3.3.2.1 Immunosensors Immunosensors are biosensors that use antibodies as bioreceptors and involve antigen-antibody interactions on the surface of a transducer for the qualitative or quantitative detection of the target analyte (i.e., antigen). These are a type of affinity biosensors and are based on the irreversible binding of antibodies to antigens, forming an antigen-antibody (Ab-Ag) complex, which is detected, processed, and displayed as a signal. Typically, the immunosensors consist of a capture probe, to which the antigen binds, and a signal probe, which binds to the antigen forming a sandwiched structure. The capture probe is generally a capture antibody immobilized on the surface of the transducer, and the signal probe is generally a labeled secondary antibody. “Labels” in immunosensors are the electroactive materials bound to the secondary antibody that can produce an enhanced signal by undergoing a catalytic reaction during the measurement. Enzymes are frequently used as “labels” in immunosensors for signal amplification. The enzyme-labeled secondary antibody is added to the Ag-Ab complex formed on the transducer surface to complete the sandwich assay format, followed by the addition of a suitable substrate for the enzyme. The catalytic activity of the enzyme label leads to the formation of a product that is either electroactive (for electrochemical signal) or produces an optical signal (fluorescence, chemiluminescence, etc.). Several enzymelabeled immunosensors have been developed for the detection of cardiac biomarkers. The most commonly used enzymes in immunosensor applications are oxidoreductases such as oxidases, peroxidases, dehydrogenases, etc. that catalyze redox reactions of the substrate by transfer of electrons or hydrogen. Horseradish peroxidase (HRP) is a frequently used enzyme in immunosensors. HRP tagged secondary antibody is used as the signal probe and H2O2 as the substrate in most of these enzyme-based immunosensors. An amperometric signal is generated by the electrocatalytic reduction of H2O2 by HRP in these biosensors. Some of the recently developed immunosensors for cardiac biomarker detection are based on this mechanism and are tabulated in Table 3.3. Redox mediators such as hydroquinone (HQ), potassium ferricyanide [Fe(CN)6]3-, etc. are also used in some of these biosensors for mediating electron transfer. For instance, [Fe(CN)6]3-/4- was used as a redox mediator to facilitate the electron transfer and signal amplification in a cTnI immunosensor (Fig. 3.2a) (Rezaei et al. 2018). (FAD)-dependent glycerol-3-phosphate dehydrogenase (GPDH) has also been used as an enzyme label in a cTnI immunosensor that also uses Ru(NH3)63+ as an electron mediator to obtain a high signal-to-background ratio (Fig. 3.2b) (Dutta et al. 2015). Further, advancements in material sciences, nanotechnology, and microfluidics have allowed the development of highly sensitive and portable immunosensors to detect cardiac biomarkers. Nanostructured materials have been incorporated in cardiac immunosensors to enhance their sensitivity and reproducibility. It provides a larger surface area for the attachment of more capture antibodies and better accessibility to cardiac targets to increase their binding efficiency. Enzymenanoparticle bioconjugates further allow the development of ultrasensitive immunosensors. Many enzyme-labeled secondary antibodies can be coated on nanoparticles, further amplifying signals in conventional sandwich immunoassays.

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Fig. 3.2 (a) Schematic of the immunosensor developed using CNT-whiskered nanofibers (WNFs) for cTnI detection along with the detection mechanism (Rezaei et al. 2018). (b) Schematic representation of a washing-free electrochemical immunosensor using GPDH and Ru(NH3)63+. GP, GPDH, AA, AOx, Ru(III), Ru(II), and ITO represent glycerol-3-phosphate, glycerol-3-phosphate dehydrogenase, L-ascorbic acid, L-ascorbate oxidase, Ru(NH3)63+, Ru(NH3)62+, and indiumtin-oxide, respectively (Dutta et al. 2015)

Carbon-based nanomaterials, particularly carbon nanotubes [both single-walled carbon nanotubes (SWCNTs) and multi-walled carbon nanotubes (MWCNTs)] and derivatives of graphene [graphene oxide (GO) and reduced graphene oxide (rGO)], have been reported in the past two decades for their use as electrodes in biosensors (Rowley-Neale et al. 2018; Tîlmaciu and Morris 2015). This material possesses several characteristic properties, including chemical, electrical, and optical properties that enable lower limits of detection. It has a large surface area that allows the immobilization of a large number of bioreceptor molecules. Additionally, it promotes rapid electron transfer, increasing the catalytic reaction of many electroactive species. Gomes Filho et al. developed an electrochemical immunosensor based on CNTs for the detection of cTnT (Gomes-Filho et al. 2013). The polyethylenimine (PEI) polymer was used to covalently bind carboxylated CNTs on the surface of the electrode. The modified electrode was used for the typical sandwich immunoassay, and an amperometric signal was generated by HRP conjugated to Anti-cTnT on reacting with H2O2. The concentration of cTnT was directly proportional to the signal generated, and a linear detection range of 0.1–10 ng/mL was obtained. Freitas and co-workers developed another cTnT immunosensor based on the amino-functionalized MWCNTs on an SPCE (Freitas et al. 2014). The amino-MWCNT/SPCE was used for a sandwich-type immunoassay in which a signal was generated by electrocatalytic reduction of H2O2 by HRP conjugated to the secondary antibody. The amino-functionalization of the MWCNTs was done to achieve oriented immobilization of antibodies via their Fc region to enhance the efficiency of the immunosensor by achieving a lower limit of detection, i.e., 0.016 ng/mL. Recently, CNTs were incorporated into nanofibrous

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structures to stabilize the nanotubes on the electrode surface (Rezaei et al. 2018). The fabricated CNT-whiskered nanofibers (WNFs) combined the merits of both nanofibers (i.e., good interconnectivity, high porosity, and large surface area-tovolume ratio) and CNTs (i.e., rapid electron transfer and electrocatalytic activity) to enable better sensing applications. Based on these nanocomposite nanofibers, a sandwich-type immunosensor for the detection of cTnI was developed. HRP conjugated to a secondary antibody was used to generate an electrochemical signal. However, the active site of HRP was relatively far from the electrode in the fabricated setup that did not allow direct electron transfer. Hence, [Fe(CN)6]3-/4was used as a redox mediator to facilitate the electron transfer and signal amplification (Fig. 3.2a). The developed biosensor showed good reproducibility and repeatability with a limit of detection of 0.04 ng/mL. Li et al. used poly(diallyl dimethylammonium chloride) (PDDA) to covalently bind RGO on the surface of the gold electrode (Li et al. 2017). This PDDA-RGO-modified gold electrode was further used to immobilize the anti-cTnI antibody to develop a sandwich immunoassay for the detection of cTnI. The electrocatalytic reduction of H2O2 by HRP, conjugated to a secondary antibody, was measured by amperometry, reporting a detection limit of 0.024 ng/mL. Gold nanoparticles have also been used to modify electrodes because of their strong biomolecule adsorption capability and ability to promote electron transfer between the enzyme and the electrode (Saleh Ahammad et al. 2011; Serafín et al. 2018). Other electrode modifications have also been used in enzyme-based immunosensors for enhanced sensitivity of cardiac biomarkers such as polymer films to allow a stable and irreversible immobilization of biorecognition elements (Mattos et al. 2013) and magnetic beads to reduce matrix effects in immunosensors (Esteban-Fernández de Ávila et al. 2013a, b), etc.

3.3.2.2 Aptasensors Aptasensors use aptamers as biorecognition elements, which are synthetic oligonucleotides selected randomly by a method known as the systematic evolution of ligands by exponential enrichment (SELEX) (Wu and Kwon 2016). Recently, aptasensors have gained a lot of attention in analyzing AMI biomarkers (Table 3.3) due to their high affinity and specificity. Aptamers are also advantageous over antibodies due to their in vitro chemical synthesis, stable modification and functionalization, longer shelf life, smaller size, and lower immunogenicity. Aptamers are particularly fascinating as they can change the conformation on interacting with the analyte of interest. Further, applying nanostructures to aptasensing significantly increases the surface concentration of aptamers, thereby enhancing its sensitivity. Enzymes are used for the signal amplification of the aptamer-antibody or aptamer-aptamer sandwich assays. For instance, a sandwich-type aptasensor was developed for the detection of thrombin that used WSe2 nanosheet- and gold nanoparticle-modified electrode for immobilizing capture aptamers (Fig. 3.3a) (Wang et al. 2018). Gold nanoparticles functionalized with biotinylated DNA strand and thrombin aptamer were used as signal probes. Once the analyte is sandwiched

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Fig. 3.3 (a) Schematic illustration of the fabrication of thrombin aptasensor and the mechanism of detection (Wang et al. 2018). (b) a—Synthetic procedures of G-quadruplex/hemin/HRP/AuPd/poly (o-phenylenediamine) probes. b—Schematic illustration of the preparation process of the biosensor (Wang et al. 2017)

between the capture and the signal probes, streptavidin-conjugated alkaline phosphatase was added along with its substrate to trigger an electrochemical-chemicalchemical (ECC) redox cycling at the electrode for signal enhancement to achieve a low detection limit of 190 fg/mL. Similarly, Yeh et al. used aptamer-antibody sandwich assay along with HRP-based signal enhancement to detect thrombin (Yeh et al. 2014). Antibody- and HRP-labeled gold nanoparticles act as the signal probes. The use of gold nanoparticles allows greater surface area for immobilization of a large number of HRP molecules, thereby increasing the sensitivity (LoD of 1.5 pM for thrombin).

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Although enzymes are commonly used as signal enhancers in aptamer-based sensing methods, their low stability and decreased activity over time have compelled researchers to look for additional or alternative labels. For example, Wang and co-workers used multiple labels, including HRP, HRP-mimicking DNAzyme (G-quadruplex/hemin), and Au-Pd nanoparticles, for the signal amplification in a sandwich-type aptasensor for thrombin to achieve a wide range of detection between 100 fM and 20 nM (Fig. 3.3b) (Wang et al. 2017). Another study used HRP-, HRP-mimicking DNAzyme (G-quadruplex/hemin)-, and Au@Pt nanozyme-based aptasensors for the ultrasensitive detection of cTnI (Sun et al. 2019). The presence of the analyte caused the enzymatic action of HRP using H2O2 as a substrate and HQ as a redox mediator to enhance the aptameric signal and obtain a limit of detection of 7.5 pg/mL.

3.4

Challenges and Future Prospects

Inappropriate management of cardiovascular diseases can lead to an increased number of hospitalizations and a greater risk of premature deaths. The development of point-of-care diagnostic solutions has become necessary for efficient risk stratification and the prevention of associated complications. The wide applicability of enzymes in catalytic biosensors as well as labels in affinity biosensors for the detection of cardiac biomarkers has been prevalent for a long time and is still quite common. This is because of the high selectivity of enzymes toward analytes and their excellent efficiency. However, there are certain drawbacks in using enzymes such as limited sensitivity, low operational stability, short lifetimes, decreased activity over time, and isolation and purification costs. Efforts have been made to improve the sensitivity and signal stability of enzymatic biosensors using nanotechnology-based platforms over the past decade. Nanomaterials have been used in electrochemical enzymatic biosensors for improving the charge transfer between the enzyme and the electrode, better enzyme immobilization and stability, and enhanced electrocatalysis (Kucherenko et al. 2019). Signal amplification of enzymatic biosensors has also been achieved using multienzyme labels and by combining enzymatic reactions with redox cycling (Yang 2012). Nonetheless, the commercialization of these biosensors is still a major challenge. Improvements in device fabrication using microfluidics and lab-on-a-chip technologies, along with better nano-assembly, can lead to the realization of these enzymatic biosensors at a commercial scale. Interdisciplinary expertise involving nanotechnology, material sciences, biochemistry, and electrochemistry may also help overcome numerous limitations of enzymatic biosensors. Multiplexed detection of several analytes using different enzymes with the same transduction mechanism or an array of transducers is also an area that needs exploration. Researchers have also started exploring alternate labels that mimic the activity of the enzymes. The last decade has witnessed a tremendous increase in the use of “artificial enzymes,” which are nanomaterials exhibiting similar properties to that of enzymes (Campuzano et al. 2020). These artificial enzymes are cost-effective and stable alternatives to enzymes. The

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advancements in the fields of biologicals, material engineering, and nanotechnology hold a great potential to develop innovative sensors and similar technologies.

3.5

Conclusion

Enzymatic biosensor platforms marked the beginning of the biosensor era. The classical glucose biosensor developed by Clark and Lyons was based on the use of an immobilized glucose oxidase enzyme. Since then, enzymatic biosensors have also been immensely used for the detection of cardiac enzymes as well as biomarkers. However, unstable enzyme activity and limited sensitivity are potential drawbacks of enzymatic biosensors. These drawbacks led to the development of more innovative approaches involving nanotechnology and bioelectronics to improve the performance of biosensors. A wide range of other biomolecules such as antibodies, aptamers, nucleotides, and molecular imprinted polymers have become more common in biosensors to develop a more sensitive and innovative system. Furthermore, drastic advances in technology have enhanced the capability for more efficient and sensitive biosensors. Acknowledgments Dr. Vivek Borse would like to acknowledge the Department of Science and Technology, Ministry of Science and Technology, Government of India, for the INSPIRE Faculty Award (IFA18-ENG266, DST/INSPIRE/04/2018/000991). Conflict of Interest The authors report no conflict of interest.

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Enzyme-Based Biosensor Platforms for Detection of Cancer Anna Anandita, Dakshita Snud Sharma, Nandini Singh, Rajesh Kumar Singh, Vinay Sharma, and Dharitri Rath

4.1

Introduction

4.1.1

Components of Biosensor

Biosensors are the devices that are used to detect the abnormal levels of numerous biological components present in various cancer samples, popularly known as cancer biomarkers. Figure 4.1 shows a schematic of the various components of a typical biosensor, namely, bioreceptor (or biorecognition element), transducer and detector. The biological recognition element in a biosensor is the component that interacts precisely with the target molecules, the transducer then transforms this interaction into a quantifiable signal and a signal processor which converts it to a readable format. Biosensors find use in numerous domains, from environmental and agricultural monitoring to biological analysis to food safety to defence and security. They are gaining popularity as they are more beneficial than that of the traditional methods because of the fact that they can be made portable, easier to mass-produce and available in an affordable price (Gorodetskaya and Gorodetsky 2015). The biorecognition element in a biosensor could be an antibody, microorganisms

Anna Anandita and Dakshita Snud Sharma contributed equally with all other contributors. A. Anandita · D. S. Sharma · R. K. Singh · D. Rath (✉) Department of Chemical Engineering, Indian Institute of Technology, Jammu, Jammu and Kashmir, India e-mail: [email protected] N. Singh Department of Bioengineering and Biotechnology, Birla Institute of Technology, Mesra, India V. Sharma Department of Biosciences and Bioengineering, Indian Institute of Technology, Jammu, Jammu and Kashmir, India # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Patra et al. (eds.), Enzyme-based Biosensors: Recent Advances and Applications in Healthcare, https://doi.org/10.1007/978-981-15-6982-1_4

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Fig. 4.1 Schematic of a biosensor: Typically, it has bioreceptor molecules that are sensitive to the target analyte and a transducer which converts the signal generated into a measurable signal which then is detected by the detector. The analyte can be virus, bacteria or DNA and bioreceptors can be antibodies, Enzymes, ssDNA, protein or aptamer

(whole-cell biosensors), biological tissues and organelles, enzymes or nucleic acid, which are typically immobilised onto the surface of the sensor (Moharana and Pattanayak 2020). The method of transduction is determined by the physiochemical change generated by the sensing element. As a result, biosensors based on diverse transducers can be electrochemical (amperometric, conductometric and potentiometric), optical (absorbance, fluorescence and chemiluminescence), colorimetric and piezoelectric (acoustic and ultrasonic).

4.1.2

Enzyme-Based Biosensors

Enzyme-based biosensors are increasingly being used for the development of biosensors for cancer detection; however, there are many hurdles for a success story to develop it as a commercialised product available in the market as this is the most complex of the diseases being detected. These are the devices where enzymes are used as the biorecognition element (Fig. 4.1), or it could be used as a reporter molecule as well. Based on the transduction mechanisms, these sensors could be classified as optical (Borisov and Wolfbeis 2008), piezoelectric (Skládal 2016) and electrochemical (Ronkainen et al. 2010) sensors that have been studied in the literature. These are used in various applications including the food industry to address the issues of food quality and safety, as well as their maintenance and

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processing (Mehrotra 2016). They may be used to monitor the ageing of beer (Ghasemi-Varnamkhasti et al. 2012), identify pathogens and pollutants in food (Arora et al. 2011; Ercole et al. 2003) and quantify pesticides in dairy products (Amaro et al. 2011; Bäcker et al. 2013). Enzyme-based biosensors are employed in plant biology to monitor a dynamic process under physiological conditions in order to propose methodologies to describe the natural process, such as metabolite conversion or signalling event triggering. They are also being developed to monitor and detect analyte metabolism, regulation or transport components (Tian et al. 2012; Topell and Glockshuber 2002). However, perhaps the widest applications of the enzymes-based biosensors are that in the biomedical diagnostics for various diseases, and the most successful commercial story is that of the glucose sensors till date. These are now increasingly employed towards the detection of various diseases including that of diagnosing infectious diseases (Mehrotra 2016). They offer advantages in the clinical market such as rapid extra-laboratory analysis and substantial cost reductions (Ispas et al. 2012). Additionally, they are also frequently used in medicine to diagnose contagious infections; quantify cardiac biomarkers, clinical immunophenotyping of acute leukaemia and the influence of oxazaborolidines on oral health; and to detect numerous cancer markers efficiently and precisely. With the integration of other advanced technologies such as microfluidics, nanotechnology, etc., miniaturisation of these biosensors is possible towards the detection of biomarkers in a sensitive and specific manner. The primary goal is to create a portable device that can incorporate all of the different steps involved in biomarker detection (Shi et al. 2019). Figure 4.2 presents pictorially these various avenues in which one can employ the enzyme-based biosensors. Despite rapid advancement of biosensors based on numerous biorecognition elements, enzyme biosensors remain one of the most extensively employed in the biomedical domain (Wilson and Hu 2000).

4.1.3

Cancer: Worldwide Burden

Cancer is a multifactorial disease characterised by uncontrolled cell proliferation and the ability to infiltrate or spread to other regions of the body. It is always important to have a look at the cancer statistics globally as that signifies the burden of global health it carries. Based on GLOBOCAN estimates, it has a significant socioeconomic burden, resulting in about 19.3 million new cases and 10 million deaths in 2020 worldwide (Sung et al. 2021). A per cent-wise data of most prevalent cancers worldwide has been depicted in Fig. 4.3. The only good news is that it is also a fact now that if one can detect cancer in early stages, it is curable and there are several evidence for the same (Chen et al. 2020a). However, due to low biomarker levels in the early stages, detecting cancer biomarkers in the circulation is difficult (D’Agata et al. 2017). Thus, it is quite pertinent to design and develop methodologies to develop sensitive analytical methods to detect cancer at early stages. Cancer biomarker detection plays an important role in early-stage cancer diagnosis, design of

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Medical Diagnosis (both clinical and laboratory use)

Manufacturing of pharmaceuticals and replacement organs

Food Analysis

Applications of Enzyme Based Biosensors

Environmental Field Monitoring

Analyte Transducer Detection of system for biological warefare agents

Blocomponent

Signal Drug development

Study of Biomolecules and their interaction

Quality Control

Crime Detection

Fig. 4.2 Schematic depicting the various fields of applications in which enzyme-based biosensors are currently employed. As the figure depicts, there are huge number of applications in which the enzyme-based biosensors are employed, which includes medical diagnostics as well. (Created with BioRender.com)

treatment and therapies. The quantification of these cancer biomarkers in patient samples can also determine the stage and progression of cancer. As a result, the innovation of novel analytical techniques for the sensitive and selective diagnosis of cancer molecular fingerprints in patients’ blood is gaining increasing attention and popularity over the last few decades (Kelley 2017). Furthermore, there is a need to develop hand-held devices to perform these analytical assays at convenient locations and with less amount of infrastructure as well as technical expertise. Biosensing platforms incorporating enhanced functionality for sensitive target sensing provide appealing alternatives to conventional bulky instruments used in the pathological set-up (Bellassai and Spoto 2016). The target analytes in case of cancer are the various biomarkers overexpressed or underexpressed in our body fluids. The identification of these accurate biomarkers is the first step towards early

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NUMBER OF NEW CASES WORLDWIDE

12%

12% 48% 11%

8% 3%

6%

Fig. 4.3 Depiction of estimated number of new cases, worldwide, due to numerous types of cancer, in both sexes, across all ages (Data Source: World (n.d.)). The majorly diagnosed types are breast cancer, lung cancer and colorectal cancer

diagnosis of cancer, which is still a daunting task in case of many cancer types, as it needs several biomarkers being detected simultaneously (Cheng and Fu 2022; Liu et al. 2018). Recognition of biomolecules such as antibodies, peptides, aptamers and nucleic acids requires development of highly sensitive and specific assay. Biomarkers for cancer can be classified as genomic biomarker, transcriptomic biomarker, epigenomics biomarker, proteomic biomarker and metabolomic biomarker. Many well-known cancer biomarkers such as protein-based biomarkers, methylated circulating DNA, microRNA, exosomes, circulating tumour cells, etc. are used to detect several cancers (Henry and Hayes 2012; Nassar et al. 2021). In a recent study, some of the biomarkers were discovered in much higher concentrations in the fluids collected from the uterus during uterine lavage than in serum. An in vivo optical nanosensor prototype composed of an antibody-functionalised carbon nanotube complex capable of detection of these biomarkers without invasive procedure has been developed (Williams et al. 2018). Using DNA probes supported by DNA origami nanostructures, a simple, label-free and amplification-free electrochemical biosensor was created to detect miRNA for the first time, with methylene blue (MB) acting as the hybridisation redox indicator (Han et al. 2019). Enzyme-based

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biosensors are excellent platforms for creating non-invasive diagnostics that could provide molecular-level data for personalised medicine applications. In this chapter, we discuss the major biosensor platforms currently offered; the wide variety of enzyme-based biosensors, namely, electrochemical, piezoelectrical and optical; and the different nanomaterials used in biosensors; their fabrication and applications in disease diagnosis, mostly cancer diagnosis; and their recent progress. This will follow a discussion on the various types of cancer biosensors and their analytical performance in the healthcare industry. Finally, we have critical comments and analysis of the significance of the progress made so far in this area.

4.2

Biosensor Platforms

4.2.1

Types of Platforms

The various platforms used to develop these sensors promise to perform laboratory operations on a small scale by providing advantages such as reduced analysis time, less usage of reagents, portability, ease of use and real-time operation. This is the idea conceived for designing microfluidics lab-on-a-chip devices to be used for many such analytical protocols. This is a scale-down approach and has been used to develop various other technologies such as inkjet printing, DNA chips, etc. Whiteside’s group is one of the pioneers in the microfluidics-based lab-on-a-chip technology that has successfully downscaled and miniaturised the biosensors for point-of-care amenability and as an alternative to conventional laboratory techniques (Weibel and Whitesides 2006). The most popular polymer substrates used are polymethyl methacrylate (PMMA), polytetrafluoroethylene (PTFE) and polydimethylsiloxane (PDMS) due to their biocompatibility (Choi 2020). Among these, PDMS biosensors are widely employed, as they are affordable and have excellent selectivity and low reagent consumption (Nasseri et al. 2018). They are made up of numerous channels that allow nucleic acid testing stages. PDMS (polydimethylsiloxane) is also being used extensively for the fabrication of flexible and stretchable sensor due to its elastomeric properties. Feng et al. have developed a biosensor for PSA detection using a new microfluidic–electrochemical (FEC) detection system on a PDMS platform which includes gold nanoflower-modified screenprinted electrodes (Feng et al. 2021). PMMA is another popular substrate recently being used in the fabrication of biosensor platforms. Sri et al. introduced a carbon dot–PMMA nanocomposite to develop an electrochemical biosensor for the detection of tumour necrosis factor-alpha (TNF-α) to obtain excellent biocompatibility, exceptional electrocatalytic conductivity and large surface area (Sri et al. 2021). Some of these recently developed platforms are represented in Fig. 4.4. Poly(methyl methacrylate), or PMMA, is a well-known substrate for microfluidics-based biosensor fabrication owing to its cheap cost. Wongkaew et al. developed a novel multi-channel PMMA microfluidic biosensor with interdigitated ultramicroelectrode arrays for electrochemical detection of target sequence RNA from Cryptosporidium parvum (Wongkaew et al. 2013). A low-cost CO2 laser

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Fig. 4.4 Schematic illustration of recent developments in biosensor fabrication technology and platforms used. (a) Chip design of the paper/PMMA hybrid PnP device (Sanjay et al. 2020); (b) Scheme of the construction of the electrochemical biosensor and development of the μFEC system for PSA detection (Feng et al. 2021); (c) Schematic diagram of the configuration of the sensor system and sensor unit (Park et al. 2019)

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etching technique has been used to create a poly(methyl methacrylate) (PMMA) microfluidic device for the detection of carcinoembryonic antigens (CEA). The device has been created with the aid of numerical simulation and has the ability to operate continuously. Based on immunoassay using magnetic particles and electrochemical sensing, the target CEA is detected (van Anh et al. 2016). Recently, Sanjay et al. have developed a reusable, cost-effective and eco-friendly hybrid plug-andplay (PnP) device for high-sensitivity immunoassay using analyte enrichment and made of poly(methyl methacrylate) (PMMA) and paper. High-sensitivity detection of infectious illnesses, malignancies, cancer and other significant biomolecules has a lot of potential for this reusable PnP gadget (Sanjay et al. 2020). Polytetrafluoroethylene (PTFE) is a commonly used fluoropolymer made up of carbon and fluorine atoms. It is known by the common name Teflon and finds application in various industries, material fabrication, etc. Park et al. used porous polytetrafluoroethylene (PTFE) membranes coated with parylene-A that has been vapour-deposited with an amine functional, to create a portable urea sensor for usage in fast flow situations. On the parylene-A-coated PTFE membranes, the ureahydrolysing enzyme urease was immobilised using glutaraldehyde. A polydimethylsiloxane (PDMS) fluidic chamber was used to build the ureaseimmobilised membranes, and a screen-printed carbon three-electrode system was employed for electrochemical analysis (Park et al. 2019). Previously, Vaidya et al. developed a glucose sensor by using PTFE membranes with a pore size of 0.02 μm. The negatively charged hydrogel layer-coated PTFE membrane offered the enzyme electrode good protection, particularly when ionic interferants like ascorbic acid and uric acid were present (Vaidya and Wilkins 1994). Paper-based biosensors are another type of substrate that have been conveniently used to design chip-based biosensors. Paper is convenient to use due to its high diffusion of sample due to capillary effect. Paper sensing platform can be used in various design formats such as lateral flow assay (LFA), paper-based analytical microfluidic devices (μPADs) and dipstick test (Silveira et al. 2016). Enzyme embedded paper-based biosensor can use a variety of papers including cellulose and nitrocellulose paper materials. Their unique properties, such as their simplicity, affordability and ease of manufacture, modification and functionalisation, have enabled rapid, on-site POC testing. Recently, Suvanasuthi et al. demonstrated a μPAD using polylactic acid filament and wax filament to create hydrophobic barriers on the paper for the discriminative detection of dengue virus serotypes (Suvanasuthi et al. 2022). Wang et al. created a wax-printed multilayered “PAD” for the colorimetric detection of carcinoembryonic antigen (CEA), with the ability to change the flow or storage of sample solutions in the sensing zones, thanks to a movable and rotatable detection layer (Wang et al. 2020a). Sene et al. created a lateral flow assay (LFA) using anti-IL-6 antibodies coupled to gold nanoparticles for quick and colorimetric IL-6 detection using a paper substrate (Eiras 2020).

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4.2.2

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Recent Advancements in Cancer Biosensors

Striving towards developing new platforms continues to make use of the above established once to obtain an integrated platform with more functionalities and better sensitivities. Recently, three-dimensional printing, also sometimes referred to as additive manufacturing, helps to fabricate rapid biomedical diagnostic devices with high precision, low cost and complex geometry. These modern fabrication techniques can overcome the various limitations faced in the conventional fabrication processes such as screen-printed electrode produced by printed circuit board technology (Moreira et al. 2016), photolithography, etc. (Shakibania et al. 2022). In this regard, Zhao et al. used an approach for fabrication of biosensor and developed an electrochemical biosensor for the detection of cytokeratin 18, a bladder cancer biomarker, by chemically modifying the working electrode with bismuth suphide semiconductor nanocrystals (Bi2S3NCs). Bondancia et al. fabricated a flexible electrode for the detection of p53 cancer biomarker by screen-printing the interdigitated electrodes on bacterial nanocellulose substrates and coating the electrode with chitosan as well as chondroitin sulphate (Bondancia et al. 2022). The other important avenue is to increase the sensitivities of the existing devices, such as that reported by Carneiro et al. who have developed an electrochemical biosensor by a passive direct methanol fuel cell (DMFC) assembly, modified by a layer of a molecularly imprinted polymer (MIP) on a carbon fabric anode electrode containing Pt/Ru nanoparticles for the detection of cancer biomarker, CEA (Carneiro et al. 2022). Wang et al. have developed a first of its kind plasmonic biosensor by using atomically thin two-dimensional phase change nanomaterial with unique integration of atomically thin Ge2Sb2Te5 with plasmonic substrate. 10-15 mol/L was the limit of detection achieved through this platform which can be used in the detection of TNF-α cancer marker (Wang et al. 2021). Ucci et al. demonstrated a label-free biosensor based on surface plasmon resonance imaging for the detection of alpha-fetoprotein (AFP), a recognised liver cancer biomarker. This platform used an antibody-functionalised sensing film and signal amplification by detection antibody to obtain a sandwich immunoassay which provided a limit of detection equal to 1.5 ng/mL in a saline buffer (Ucci et al. 2021). Similarly, Wong et al. for the first time reported the detection of circulating microRNA as a biomarker for breast cancer by using a surface plasmon resonance imaging biosensor (Wong et al. 2021). Nanostructured metal oxides (NMOs) have lately gained prominence to be materials that give a practical surface for biomolecule immobilisation with pre-decided orientation, improved conformation as well as higher biological activity and hence possess better sensing properties. NMOs with desirable functions and surface charge characteristics, as well as distinctive optical, electrical and molecular properties, present intriguing scaffold for integrating biorecognition constituents with signal amplification transducers. The features of the metal oxide–biomolecule interface can be tailored to improve the implementation of an NMO-based biosensor by designing the shape, size of the particle, surface area, functional behaviour, adsorption capability and properties like electron transfer. These intriguing NMOs

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are likely to be used in a generation of point-of-care compatible, intelligent biosensors (Solanki et al. 2011).

4.2.3

Challenges Faced and Their Troubleshooting

The primary challenge faced is the stability of the enzyme(s) on the substrate. Since the enzymes are proteins, they need to maintain their particular 3D configuration in order for their active sites to be available all the time, even after immobilisation. However, the immobilisation of enzymes on the substrate is crucial for the fabrication of the device which enables the device more stable, specific and efficient for the generation of signal to detect accurately (Rocchitta et al. 2016). The best immobilisation technique must be chosen because different methods have different benefits and drawbacks (Nguyen et al. 2019). The biocompatible substrate material must be selected which has the ability to hold the enzyme without the loss of inherent property of the enzyme or need to chemically modify the surface having amine or carboxylic groups available to make peptide bond with the selected enzyme. Overheating during the drying process after the application of enzyme on the surface may deform the enzyme, leading to functional loss of enzyme even after rehydration (Ortiz-Martínez et al. 2021). To avoid this situation, temperature and pressure should be optimised and it is a tedious task.

4.3

Enzyme-Based Biosensors in Cancer Detection

4.3.1

Signal Generation and Transduction Mechanisms

An enzyme-based biosensor typically implements enzyme as the recognition element, immobilising enzymes on the surface of the transducer’s support platform/ matrix, and/or enzymes being used as the reporter molecules. As the analyte and enzyme react, it becomes crucial to comprehend the enzymes as well as their reaction kinetics. Enzymes are proteins with a macromolecular size that function as biological catalysts. Enzymes catalyse and accelerate chemical/biological reactions without undergoing any chemical change, and in the process convert the substrate into desired product (Malhotra and Ali 2018). An enzyme-based reaction can be given by: E þ S Ð ES

k cat

→ EþP

One of the most common ways in which enzyme kinetics is described is to assume that they follow the Michaelis–Menten equation:

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υ=

89

V max ½S] K m þ ½S]

where υ = velocity of the reaction Vmax = maximum rate achieved by the system Km = Michaelis constant [S] = concentration of any substrate S Turnover number of an enzyme (kcat or catalytic rate constant) is the maximum number of molecules of substrate converted to product per active site per unit time of different substrates to different products (Roskoski 2015). Several synthetic smallmolecule models have turnover numbers below 10, while native enzymes frequently have counts in the thousands. Therefore, turnover number is a crucial factor to consider when assessing the effectiveness of developed proteins. There are various methods for calculating a reaction’s turnover number, but they all involve continuously supplying substrate under reaction conditions until the reaction stops. The analyte concentration is directly related to the presence of specific analytes. Now in order to quantify the analytes, one can monitor the proton concentration (H+), gas release or uptake, light emission, absorption or reflectance, heat emission and other changes. The transducer converts these changes into quantifiable signals, and the analyte of interest is identified. Immobilised enzymes have been used in certain biosensors, in which the transducer surface is immobilised with specific enzymes (Nguyen et al. 2019). Because of the high cost and low stability of enzymes, there has long been a quest for an alternative, one of them being metalloporphyrins in enzyme mimetic (metalloporphyrin)-based biosensors. Based on the transduction event, biosensors can be classified as electrochemical, optical and piezoelectrical biosensors, which would be briefly discussed below (Fig. 4.5).

4.3.1.1 Electrochemical Enzyme-Based Biosensor In an electrochemical biosensor, the biorecognition element reacts with the target analytes in a selective manner and results in an electrical signal generation which then gets transmitted to a signal processor through a transducer. An electrochemical sensor includes a biological recognition element and an electrochemical transducer. Depending on the type of bioreceptor molecules used, there are two classifications: affinity sensors and biocatalytic devices. Enzymes, entire cells, tissue slices and other biocatalytic sensors can be classified into numerous categories based on the substance of their recognition elements (Huang et al. 2017). Electrochemical enzyme-based biosensors have been widely used as a subclass of electrochemical biosensors. They may use enzyme as biorecognition element as well as labelling element, for example, Li et al. developed a screen-printed immunosensor to measure the α-1-fetoprotein (AFP) in human serum by using horseradish peroxidase (HRP)labelled AFP antibody entrapped in a chitosan membrane (Li et al. 2003). Similarly, an aptamer-based biosensor used glucose dehydrogenase as labelling enzyme to

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Fig. 4.5 Classification of different types of enzyme-based biosensors based on the various transduction mechanisms. Primarily, optical, piezoelectric and electrochemical methods of transduction have been employed for cancer detection

screen thrombin in sample (Ikebukuro et al. 2007). Various components recognise the target molecules specifically, catalyse the substrate reaction and create electroactive species. Various electrodes such as indium tin oxide, glassy carbon and gold electrodes have been employed in the development of electrochemical biosensors for cancer biomarker detection. The most common example of an electrochemical enzyme-based biosensor is that of the oxidoreductase-based glucometer which quantifies the glucose level of patient in the form of an amperometric signal. The performance of this amperometric device is dependent upon the working pH and temperature parameters. Three generations of amperometric enzyme-based glucose monitoring biosensors have come into play, each next generation better than the previous one in terms of overcoming the limitations faced. Recently, an electrochemical biosensor has been reported which uses an enzyme as biocomponent for the detection of target analyte. Singh et al. have developed a nanoparticle-based electrochemical sensor for the detection of asparagine, wherein the presence of Lasparaginase hydrolyses L-asparagine into L-aspartate and ammonia. The working electrode has been modified so as to detect the liberated ammonium ions by observing change in potential in ion-sensitive electrode (ISE) (Singh et al. 2022). In another similar study, Zhao et al. developed an electrochemical biosensor for the detection of bisphenol A by using tyrosinase enzyme as the biocomponent attached on the glassy carbon electrode surface. The detection limit achieved through this platform was better than that achieved from earlier developed biosensors (Zhao et al. 2022). Wen et al. created an enzyme-based electrochemical DNA biosensor to track miRNAs linked to oesophageal squamous cell carcinoma (ESCC). Thiolated capture DNA probes with tetrahedron structures were fixed on a gold electrode surface, and hybridisation was carried out utilising a sandwich-assay procedure. 3, 3′, 5 was converted to its oxidised form through an enzyme reaction. 5′-Tetramethylbenzidine (TMB) was used, and the TMB signal was measured using amperometry and

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CV. Even when the detection process was run while there were various miRNAs and serum samples present, the genosensor maintained good selectivity. Recently, Castrovilli et al. developed a new promising environment-friendly electrochemical amperometric laccase-based biosensor catechol detection (Castrovilli et al. 2022).

4.3.1.2 Optical Enzyme-Based Biosensor An enzyme-based optical biosensor is a biosensor that employs enzyme as the recognition element, an optical fibre or optical fibre bundle as a platform for the biological recognition element and a transducer for the resulting signal (e.g. absorbance, chemiluminescence, fluorescence, etc.). They can detect a wide range of analytes in a sensitive and selective approach, including viruses, toxins, antibodies, tumour biomarkers and tumour cells. These biosensors offer large-scale high-throughput sensitivity screening of a diverse range of samples for a variety of parameters, as well as the development of novel analytical equipment with reduced size (Damborský et al. 2016). The optical transducer is a critical component that allows the target analytes to be measured by converting the reciprocity between analyte and biomolecule into a measurable value signal. Most enzyme biosensors mainly employ optical transducers such as absorption/reflectance, fluorescence, interferometric, SPR, optrode-based fibre, evanescent wave fibre and resonant mirror optical biosensors. Fluorescence detection is employed by the majority of commercial systems (Zhu et al. 2019). An optical biosensor was designed that utilises immobilised haloalkane dehalogenase (HLD), a halide degrading enzyme, to detect halogenated organics in ambient and water supply samples (Shahar et al. 2019a, b). Sonthanasamy et al. (2020) produced a bi-enzyme biosensor for arginine assessment while using the distinct biorecognition capabilities of two urea cycle enzymes, arginase and urease. With a repeatability RSD of 5.0%, the enzyme-based biosensor exhibited repeatable photoluminescence detection of arginine. Nurlely et al. (2022) developed an optical enzyme-based biosensor for formaldehyde detection based on AOx enzyme encapsulated in a biocompatible sol–gel film and NBCM-modified polyacrylate membrane that demonstrated fast response and high sensitivity and selectivity with a noteworthy shelf life of more than 2 weeks. 4.3.1.3 Piezoelectric Enzyme-Based Biosensor Piezoelectric biosensors are a category of analytical instrument that records affinity interactions. A piezoelectric platform, also known as a piezoelectric crystal, is a sensor component that operates on the basis of oscillations that change in response to the presence of a mass on the piezoelectric crystal surface. They are essentially massbased biosensors that operate on the acoustic principle (sound vibrations). When a mechanical force is applied to the sensor, it produces electrical impulses. When a sensing molecule is connected to the surface of a piezoelectric biosensor, a mechanical vibration begins, and the interaction between the analyte and sensing element can be transformed into an electrical signal proportional to the amount of analyte present (Malhotra et al. 2017). Quartz crystal microbalance (QCM) sensors are the ones that convert the change in mass to readable signals via recording the frequency or change in damping for a crystal resonator. When an enzyme-based product is

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adsorbed onto the sensor surface in an enzyme-based QCM biosensor, the frequency of resonance lowers (Nguyen et al. 2019). Because of its extraordinary sensitivity to environmental conditions, the sensing mechanism requires the use of isolation equipment to prevent any potential sources of interference, such as vibration. In a variety of applications, these biosensors have been utilised to detect targets such as hormones, pathogens and cells. Zhang et al. (2019) have devised a four-step approach for designing a piezoelectric enzyme-based biosensor.

4.3.2

Reporter Molecules

Nanomaterials are described as having a critical dimension of less than 100 nm, a high surface-to-volume ratio, enhanced electrical conductivity, remarkable magnetic characteristics and higher catalytic activity. Nanomaterials are significant as they improve numerous enzyme-based characteristics such as activity, thermal stability and pH resistance which are among the key parameters examined when determining the efficacy of an immobilisation procedure. Ever since, several sectors have been using nanomaterials to develop biosensors with improved sensitivity, selectivity and specificity. Figure 4.6 shows the different classes of nanomaterials implemented as reporter molecules for design and development of reporter molecules for cancer detection (Cavalcante et al. 2021).

4.3.2.1 Metallic Nanoparticles Gold nanoparticles (AuNPs) have several characteristics that are quite important for the identification and therapy of cancers. They have characteristics like conductivity and catalytic activity that gives them applicability in nucleotide recognition (Anik et al. 2019). AuNPs are small and have the ability to penetrate and deposit on the tumour site, bind to different proteins and medications, target delivery medications and have high biocompatibility. AuNPs have a wide range of applications in tumour detection and therapy. Cetuximab and gemcitabine nano-conjugated in gold have Metallic Gold NP

Quantum dot

Silver NP

TiO2/Iron NP

Carbon-based Fullerene

Graphene

Carbon nanotubes

Others Magnetic NP

Photonic Crystals

Fig. 4.6 Types of nanomaterials used. Primarily, metallic nanoparticles, carbon-based nanoparticles and various others like magnetic nanoparticles and photonic have been employed for cancer detection. (Created with BioRender.com)

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been found to be highly targeted in pancreatic cancer cells with strong epidermal growth factor receptor (EGFR) expression (Peng et al. 2019). Paimard et al. described an impedimetric test for identifying human mucin one protein (MUC1) wherein the authors’ covalent binding strategy for binding MUC1 to the gold nanocomposite and multi-walled nanotube MWCNT achieved a LOD of 2.7 nm, very good stability as well as selectivity. Because of their mature production, stability and notably strong X-ray absorption capability, AuNPs have gained increased interest in tumour imaging. Huang et al. discovered that the anti-EGFR antibody AuNRs (gold nanorods) may destroy tumour cells at lower laser intensity without causing damage to normal cells due to excessive heat (Qin et al. 2018). AuNPs can also be utilised to stabilise other drug carriers, such as liposomes, while improving their transport efficiency. Silver nanoparticles (AgNPs) have many excellent properties like signal amplification, high extinction coefficients, high scattering to extinction ratio and field enhancements; thus, they are used in many electrochemical and optical sensors.

4.3.2.2 Carbon-Based Nanoparticles Graphene is a carbon-based single-layered structure that forms a honeycomb lattice and has immense application in electrochemical biosensor development due to its more surface area and excellent electrical conductivity and biocompatibility. Graphene oxide (GO) is a derivative of graphene that has multiple functional groups, and large surfaces are for biomolecule attachment. Graphene nanocomposites between AuNP and graphene are another class of graphene-based nanomaterials that are used as electrode material. Due to their unique advantages, graphene, its nanocomposites and its derivatives provide high sensitivity and lower detection limits in a biosensor. Moreover, since they are cheaper and free of metallic impurities, they are preferable for the fabrication of biosensing platforms (Jozghorbani et al. 2021). Ai’s group was the first to develop a graphene-based electrochemical biosensor in which GCE was modified with graphene nanosheets and deposited with dendritic gold nanostructure to give a conductive and highly electroactive electrode surface (Zhang et al. 2012). Further, Rasheed et al. developed an electrochemical sensor for BRCA1, a gene related to breast cancer (Senel et al. 2019). Zhang and group established a paper electrode on gold nanoflower for electrochemical detection for monitoring the levels of hydrogen peroxide from live breast cancer cells in real time (Zhang et al. 2017). Graphene quantum dots (GQDs) coupled with electrochemical biosensors find many applications in cancer diagnosis. They belong to the class of zero-dimensional semiconductor nanocrystal and are of a size equivalent to biomolecules; hence, they can be used for fabricating detection platforms of various biomolecules. Graphene quantum dots have been used for prostate cancer detection by screening a specific biomarker, PSA (Tabish et al. 2021). Carbon nanotubes (CNT) are such an example of nanomaterial that has paved the way for the fabrication of new and improved biosensing devices, particularly electrochemical biosensors. These biosensors offer high performance of amperometric enzyme electrodes and immunosensor and nucleic acid-sensing devices. CNT can be classified on the basis of the number of walls as single-wall carbon nanotube and

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multi-wall carbon nanotube. Many different types of CNT-based biosensors have been established, such as CNT-based oxidase biosensors, CNT-based dehydrogenase biosensors, CNT-based peroxidase and catalase biosensors and CNT-based electrochemical DNA biosensors (Lin et al. 2005). Aliakbarinodehi et al. (2016) explored the electrochemical characterisation of abiraterone, a recent and widely used prostate cancer medicine, in interaction with the CYP3A4 enzyme and MWCNTs. Other investigations have used extremely water-soluble SWCNTs functionalised with PEGylated phospholipids as a non-invasive diagnostic tool for cancer medication loading and delivery (Liu et al. 2007, 2008). Several series of CNT are being conjugated to enzymes and thereby developing biosensors to investigate a wide range of cancer biomarkers (Pérez et al. 2019; Sireesha et al. 2018). Carbon dots (CDs) are another type of carbon-based nanomaterial that have excellent optical properties and have been used in the detection of nucleic acids, proteins and glucose. They can exist as composites and act as excellent electrode materials used for the detection of microRNA. They are used in biosensing (for cancer diagnosis and cancer biomarker detection) and bioimaging (in vitro, in vivo) (Pourmadadi et al. 2022).

4.3.2.3 Magnetic Nanoparticles Magnetic nanoparticles (MNPs) have lately made significant contributions to oncology, with profound consequences not only in cancer diagnosis but also in the prognosis, and therapeutic applications. Magnetic separation has become increasingly significant in next-generation immunoassays, wherein nanoparticles are utilised to boost sensitivity as well as detect multiple analytes (Stueber et al. 2021). Cancerous cells produce an enormous number of exosomes, which are nanovesicles that can be used to identify and categorise cancerous cells (Eivazzadeh-Keihan et al. 2021). For the separation and purification of these exosomes, various polymer-coated iron oxide nanoparticles could be employed, or eliminating other free proteins from the sample. This is proved to be a faster and efficient exosome purification method as compared to the existing techniques, even when compared to the nanoparticle purification methods (Chang et al. 2018). Further, PEG-coated nanoparticles were used to adsorb monoclonal antibodies by steric exclusion principle, with 98% recovery, which was significantly higher than could be achieved by standard monoclonal antibody purification methods (Gagnon et al. 2014). 4.3.2.4 Photonic Crystals Photonic crystals (PCs) are comprised of periodic dielectric or metallo-dielectric nanostructures that are intended to influence electromagnetic wave propagation. Owing to the growing necessity to address significant challenges in healthcare, PC-based biosensors remain high on the agenda (Sinibaldi 2021). Utilising a PC as a screening aid may be advantageous for multiplexing, fluidic design, device miniaturisation (-TAS) and integration, enabling for the processing of minute doses of patient samples. This allows effective complicated diagnostic tests with reduced cost, resource and chemical consumption than conventional systems, as well as

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drastically improved biosensor performance with respect to sensitivity, accuracy and detection limit (Dahman et al. 2017). The target miRNA sequence miR-21, which has been linked to the development of breast cancer, has a LOD of about 0.60 pM (George et al. 2013) A 2D-PC structure was used to conduct a detailed examination on the association and dissociation kinetics for interleukin (IL)-10, a cytokine that appears to be significant in the progression of human stomach cancer and its immunological escape (Chen et al. 2019). Widely used in biosensing applications, particularly in the identification of cancer biomarkers, were PC nanobeam cavities. These photonic systems benefit from their ultra-small volume in the optical mode and hence better Q factor of the order 104 (Liang et al. 2013). Colloidal crystal PS self-assembled spheres were used in another promising 3D-PC method to find cancer biomarkers.

4.3.3

Types of Cancer Diagnostics

The inception and creation of cancer cells can be caused by multifactorial alterations. However, no one gene is uniformly mutated throughout this process, but rather a group of them, which complicates illness diagnosis. All the changes that occur in tumours from different organs, as well as within tumours from the same organ, can be so varied and overlapping that it is difficult to choose a single alteration or marker for the diagnosis of certain malignancies (Karunakaran et al. 2015). Many cancer biomarkers have been identified as analytes for cancer diagnosis and biosensing. A few landmark biomarkers are mentioned as follows: BRCA1, for example, is a potential predictive biomarker for breast and ovarian cancer as it can assess the probability of acquiring cancer (Easton et al. 1995); prostate-specific antigen (PSA) is a prostate cancer screening biomarker (Lin et al. 2008); KRAS and anti-EGFR antibodies are predictive biomarkers for colorectal cancer (Allegra et al. 2009); HER2 is predictive biomarker for gastric cancer and breast cancer (Shen et al. 2013; Piccart-Gebhart et al. 2005); CEA is a colorectal cancer biomarker that can be used to monitor the disease (Locker et al. 2016); AFP, LDH and betaHCG are germ cell tumour biomarkers (Gilligan et al. 2010); and CA15-3 and CEA are prognostic biomarkers used to assess response and progression in metastatic breast cancer (Harris et al. 2016). Detection of cancer at the early stage and routine monitoring of patients is crucial to addressing the objective of significantly reducing the death rate and boosting pharmacological therapy efficacy (Dancey et al. 2012; Diamandis et al. 2010). Cancer could be caused by a variety of genetic and environmental causes (Karunakaran et al. 2015). Clinical testing is difficult due to the wide range of cancer causes. The development of the disease and the production of cancer cells might be caused by multiple alterations (genetic and epigenetic). Biosensors are great platforms for developing non-invasive diagnostics that could deliver molecular-level information for individualised medicine applications (Hamburg and Collins 2010; Ranjan et al. 2017). Enzymes participate in cancer-related biosensing in a number of ways, for example, as a signal producer as in the case of a study wherein Zeng et al. developed

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a colorimetric biosensor for screening cancer-derived exosomes by horseradish peroxidase-encapsulated DNA nanoflower (HRP-DF) which recognises exosomes and gives out a colorimetric signal due to HRP-catalysed reaction (Zeng et al. 2021). Song et al. developed a strategy based on DNA framework-enabled bulk enzyme heterojunction (BEH) method that can provide ultra-sensitive monitoring in a single step for the biomarker sarcosine that could lead to early-stage prostate cancer precision diagnostics. An enzymatic cascade reaction of sulfhydryl oxidases (SOXs) and horseradish peroxidases (HRPs) as signal transducers forms the basis of the biosensing mechanism (Song et al. 2020). Kilic et al. demonstrated for the first time an enzyme-based electrochemical microRNA (miRNA) detection approach based on biosensing of mir-21 from real total RNA sample from breast cancer cells amplified by enzyme alkaline phosphatase (Kilic et al. 2012). Enzymes are also used as biorecognition element, such as in the therapeutic drug monitoring that involves the measurement of the drug concentration in the biofluids of patients to better monitor the dosage of these prescribed medicines. Alvau et al. have described the construction of an enzyme-based electrochemical biosensor for detecting and quantifying the antineoplastic prodrug CPT-11 in the concentration range of 10–10,000 ng/mL, which is commonly seen in plasma samples of patients receiving chemotherapy for treatment of colorectal cancer. An acetylcholinesterase (AChE)and choline oxidase (ChOx)-based biosensor has been developed for drug monitoring of the anticancer agent irinotecan (a drug commonly used in the treatment of colorectal cancer) (Alvau et al. 2018). Certain enzymes can act as biomarker for a certain cancer; Moura et al. presented an electrochemical biosensor which uses a unique biosensing mechanism combining immunologic- and enzyme-based biorecognition elements for the detection of alkaline phosphatase activity in exosomes which is a potential biomarker of breast carcinoma (Moura et al. 2022). Point-of-care diagnostics is the next big thing in the biomedical industry and cancer diagnosis is one of the many applications of these platforms. Some recent examples of cancer detection biosensors based on electrochemical and optical transduction mechanisms have been discussed in Table 4.1.

4.3.4

Challenges Faced and Their Troubleshooting

The biggest challenge faced in cancer detection is that most of the clinicians still rely on the biopsy results, and it remains the gold standard as the confirmatory test. However, this is an invasive technique requiring a good pathological set-up and trained clinicians. Although integrated devices are trying to replace this bulky equipment, there is a still long to go before we realise it in its completion. One of the parallel developments in this regard is to use the body fluid for cancer detection and typing is the liquid biopsy. This technique is alternative to the invasive cancer diagnosis and monitoring procedures (Martins et al. 2021). The liquid biopsy is drastically revolutionsing in the field of clinical oncology, which makes it easier to sample tumours, provide continuous monitoring through repeated sampling, enable the creation of individualised treatment plans and test for therapeutic resistance

Ovarian

Oral

Prostate

Colorectal

Range: 0.3–1.0 fmol 132 μA/mM/cm Limit: 10-6–10-7 M Range: 2–486 μM

Bulk enzyme heterojunction Nanostructured zirconium oxide with organic functional anti-CYFRA-21-1

Sarcosine

Amino-functionalised graphene/ thionine/gold particle nanocomposites

50 nM

Tetrahedral DNA nanostructures

Sarcosine

IL-8, IL-6, vascular endothelial growth factor and EGFR Epidermal growth factor receptor

0.2 ng/mL

PCA3 and SCHLAP1

PET

Carcinoembryonic antigen

10 pg/mL Range: 0.01–100 ng/ mL 5 pg/mL Range: 0.05–200 ng/ mL 1 pg/mL

1 pg/mL

TMPRSS2–ETS fusion genes

Amino-functionalised graphene/ thionine/gold particle nanocomposites

Epidermal growth factor receptor

PET

Carcinoembryonic antigen As-synthesised new methylene blue/ NH2-SWCNT/AuNP nanocomposites

DNA–gold interaction

Methylscape

Vascular endothelial growth factor C

Substrate Amino-functionalised graphene/ thionine/gold particle nanocomposites

(continued)

Wang et al. (2020b)

Chakraborty et al. (2021) Koo et al. (2019) Song et al. (2020) Song et al. (2020) Sheng et al. (2021)

Wang et al. (2020b)

Sina et al. (2018) Chakraborty et al. (2021) Sun et al. (2021)

Reference Wang et al. (2020b)

Type of cancer detected Breast

Target biomarker Epidermal growth factor receptor

Table 4.1 Biosensors used for cancer detection Sensitivity, limit of detection and selectivity 5 pg/mL Range: 0.05–200 ng/ mL –

Enzyme-Based Biosensor Platforms for Detection of Cancer

Transduction mechanism Electrochemical

4 97

Prostate

Lung

Breast

Gastric

Type of cancer detected

–

MoS2 flakes modified with thiolated DNA probe Silica microfibre

miRNA21

HER2

PSA

NAP2

miRNA-155

PMPC-g-AuNPs

Modified La(III)-metal-organic framework and silver nanoparticles ECL probe

0.17 nm/nM

Gold-coated optical fibre

HER2

50 ng/mL Range: 10 ng/mL–3 μg/ mL

0.008 pM

–

0.1 nm/(ng/mL)

–

HER2

Modified La(III)-metal-organic framework and silver nanoparticles Single polarisation fibre

5 pg/mL Range: 0.05–200 ng/ mL –

miRNA-155

Amino-functionalised graphene/ thionine/gold particle nanocomposites

PET

Carcinoembryonic antigen

Epidermal growth factor receptor

Substrate

Target biomarker

Sensitivity, limit of detection and selectivity 5 pg/mL Range: 0.05–200 ng/ mL 1 pg/mL

Afzalinia and Mirzaee (2020) Caucheteur et al. (2020) Loyez et al. (2021) CatalánGómez et al. (2020) Sun et al. (2020) Afzalinia and Mirzaee (2020) Chen et al. (2020b) Seok and Ju (2020)

Chakraborty et al. (2021) Wang et al. (2020b)

Reference

Abbreviations: PET polyethylene terephthalate, TMPRSS2 transmembrane protease serine 2, PCA3 prostate cancer antigen 3 gene, SCHLAP1 second chromosome locus associated with prostate-1, IL interleukin, La lanthanum, HER2 human epidermal growth factor receptor 2, MoS molybdenum disulphide, NAP-2 neutrophil activating protein-2, PMPC-g-AuNPs poly(2-methacryloyloxyethyl phosphorylcholine)-grafted AuNPs, AuNPs2 gold nanoparticles, ECL electrochemiluminescence, PSA prostate-specific antigen

Optical

Transduction mechanism

Table 4.1 (continued) 98 A. Anandita et al.

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(Lone et al. 2022). It is composed of isolating tumour-derived components such as circulating tumour cells, circulating cell-free DNA, circulating micro-RNAs, tumour-derived exosomes, enzymes, tumour-educated platelets and other biomolecules, which are giving a broad view of potential future clinical practise applications (Freitas et al. 2021). The enzyme biomarkers are very important for fabrication of point-of-care diagnostic devices, as they have redox potency, which is used for electrochemical signal, redox-based chemical reaction and optical signal (Alvarado-Ramírez et al. 2021; Katz et al. 2001). The metal nanomaterials and some electro-conductive materials are used for signal enhancement, which often interact with active site of the enzyme, leading to loss of the biological function, specificity and stability (OrtizMartínez et al. 2021). Here the main challenge is to protect the biological nature of the enzyme and integrate it with signal enhancer to read the change in redox potency during reaction with the target molecules. To achieve this, the fabrication of diagnostic device is designed by preferring the biological activity, and attaching the components to the enzyme on residual parts, leaving the active sites (Nguyen et al. 2019; Ortiz-Martínez et al. 2021). However, recently many computer-based modelling have been developed to achieve the goal, such as Internet of Things (IoT)-based cancer monitoring systems, which combine embedded systems and wireless sensor networks to diagnose cancer using algorithms and machine learning approaches. In this context, a model employing IoT to detect colorectal cancer in elderly patients was developed. In another example, a cuckoo search algorithm was employed, wherein the extraction occurs through local binary patterning with IoT-enabled sensing and the use of random forest and multi-layer perceptron classifier, for breast cancer diagnosis (Fitzgerald et al. 2022; Roberts and Gandhi 2022). A comprehensive approach to cancer detection at a preliminary phase can increase treatment efficacy, with fewer complications and greater long-term lifespan. However, as detection techniques get more comprehensive, identifying insignificant alterations among tumours that could evolve to life-threatening cancer can be challenging. Sensors assisted by artificial intelligence developments will enable to identify cancer-specific signals in real time in the coming years. To lessen the societal burden of cancer, risk-based diagnosis and prevention must be both economical and broadly available.

4.4

Conclusion and Critical Thinking

Enzymes can be used as biological recognition elements as well as signal enhancers and provide high sensitivity and high selectivity towards specific target but also present some disadvantages such as possibility of loss of activity upon immobilisation. The enzyme-based biosensors can be classified as optical, electrochemical or piezoelectric based on the transduction event employed for their detection. In the current chapter, we introduce the readers to the basic definition of biosensors and the concept of enzyme-based sensors. The importance of developing an integrated system for such diagnostics is definitely going to be game-changer in

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the future. Hence, various platforms used for developing such portable devices were elaborated, and the recent trends such as the use of paper-microfluidic devices were discussed. One of the complexities that comes in the cancer detection is the fact that there is a need to detect multiple biomarkers simultaneously in order for the specific detection of a particular type of cancer. Hence, multi-analyte detection becomes essential for identification of a particular type of cancer. Additionally, the other important need is the early-stage detection, which however requires detection of biomarkers in very low concentrations in the body fluid. Hence, a very sensitive device needs to be developed. In this context, the use of various reporter particles, specifically the use of nanomaterials for developing signal-enhanced assays, was discussed in this chapter. As cancer is a complex disease to be detected, there are several challenges being faced currently by the enzyme-based biosensors. One of the important lacunae exists due to non-availability of specific and validated biomarkers for certain types of cancer. The other disadvantage is the stability and thereby retaining functionality of the enzymes when employed in the integrated sensors. Hence, there are emerging strategies to use nanoparticles and other nanomaterials to replace these biological entities. Additionally, there is an increasing trend to replace the traditional biopsy techniques with what is known as the “liquid biopsy”, in which a body fluid is used to identify and characterise the tumour cells. This can also be used for real-time monitoring of the disease progression. The future of diagnostics however is going to rely a lot on the use of computer software; there are already a lot of progress in the cancer diagnostics using the machine learning approaches which include image identification, deep learning technology and pattern recognition. The only downside of this approach is that it requires a lot of data to be fed to the algorithms prior to the identification phase. Hence, this approach would take its own time to mature before it is being practised by the clinicians on a regular basis.

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Enzymatic Biosensor Platforms for Early Diagnosis of Diabetes Prabhjot Singh, Satish Kumar Pandey, and Nishima Wangoo

Abbreviations FAD GDH GOx NADH NADP PANI PDMS PQQ T2D TCNQ WHO

Flavin adenine dinucleotide Glucose-1-dehydrogenase Glucose oxidase Nicotinamide adenine dinucleotide Nicotinamide adenine dinucleotide phosphate Polyaniline Polydimethylsiloxane Pyrroloquinoline quinone Type 2 diabetes mellitus Tetracyanoquinodimethane World Health Organization

P. Singh Centre for Nanoscience and Nanotechnology, Panjab University, Chandigarh, India S. K. Pandey Department of Biotechnology, School of Life Sciences, Mizoram University, Aizawl, India Materials Science & Sensor Applications (MSSA), CSIR-Central Scientific Instruments Organizations (CSIR-CSIO), Chandigarh, India N. Wangoo (✉) Department of Applied Sciences, UIET, Panjab University, Chandigarh, India e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Patra et al. (eds.), Enzyme-based Biosensors: Recent Advances and Applications in Healthcare, https://doi.org/10.1007/978-981-15-6982-1_5

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Introduction

The complex nature of disease onset and progression in case of diabetes presents great challenges for global healthcare (Yoo and Lee 2010). Thus, an early diagnosis may allow patients to get proper treatment well in time for the prevention, regulation, or reversal of diabetes (Inzucchi 2012). Type 2 diabetes mellitus is approaching to epidemic levels in the past two or three decades. Type 2 diabetes mellitus (T2D) is a metabolic disease currently affecting 9% of the global adult population, with prevalence expected to double by 2035 (Lam and LeRoith 2012). Though the major burden of the disease is largely preventable through healthy diet and exercise, T2D is predicted to become the seventh leading cause of death by 2030 (Alexander 2015). According to WHO, the number of people with diabetes rose from 108 million in 1980 to 422 million in 2014 (Zhou et al. 2016). Further, global occurrence of diabetes among adults over 18 years of age rose from 4.7% in 1980 to 8.5% in 2014 (Sarwar et al. 2010). There are many factors that may be responsible for this abrupt rise in the diabetic patients worldwide. In the twenty-first century, the world is changing at a rapid pace, which may be due to change in nature of jobs, eating habits and decrease in physical activity (Lindström et al. 2006). This resulted in obesity and change in lifestyle that may be the most common factor observed in the patients suffering from diabetes mellitus (Wing et al. 2001). In particular, the irregular glucose level originating from the metabolic disorders is termed as diabetes mellitus, which is the most prevalent chronic disorder. The irregularity in glucose levels mainly results from the dysfunction of insulin activity (Association AD 2014). Thus, an efficient method for the blood glucose monitoring is vital for patients suffering from diabetes mellitus. The persisting high blood glucose levels induces a hyperglycaemic condition that may lead to severe medical ramifications such as cardiovascular and renal disorders (Aung et al. 2014; Moher et al. 2008). So far, various therapeutics have been developed which deliver dose-dependent treatment for diabetes mellitus. However, a precise monitoring of short-term and long-term blood glucose levels is required for the right selection of therapeutic dosage for the patients suffering from type 2 diabetes. Therefore, a number of invasive and non-invasive techniques including chromatography, immunoassay, electrochemical, and capillary electrophoresis have been used to develop biosensors for glucose sensing (Engström et al. 2008; Vargas et al. 2019; Chen et al. 2005; He et al. 2012). Among these methods, the enzyme-based electrochemical sensors have emerged as an efficient method for the development of both invasive and non-invasive glucose sensors (Heller and Feldman 2008). An invasive electrochemical sensor exploits the measurement of glucose levels directly from blood using a glucometer or microdialysis implant, whereas the non-invasive method utilizes monitoring via biofluids such as tear or sweat using wearable detectors (Heise et al. 2007; Farandos et al. 2015). However, the reliability of this method is still under consideration for quality measurements as the results obtained depend upon the correlation between glucose levels in biofluids and blood (Lee et al. 2018). Among several techniques, the enzymatic biosensors have emerged as most reliable and quick platforms providing point-of-care analysis owing to the specificity of enzymatic reactions.

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Most of the enzyme-based biosensors utilize optical and electrochemical analysis. The optical analysis requires the use of costly spectrophotometer which is not suitable for the development of the economically manageable and portable diagnostic kit. On the other hand, the amperometric detection using enzyme-based electrochemical setup provides the opportunity for the development of user friendly, portable and point-of-care detection kit for glucose sensing. Type 2 diabetes mellitus is a cell dysfunction disease, in which the cells do not respond to the insulin as they do in the healthy state. However, there is experimental evidence that pancreatic islets cells, also called islets of Langerhans may regenerate and which makes the early diabetic situation reversible (Reinberg et al. 1952). This study strengthens the need of early diagnosis of diabetic biomarkers using innovative technological solutions.

5.2

Principle of Enzymatic Glucose Biosensing

A biosensor may be defined as a compact assembly of integrated elements including a transducer which is sensitive to produce a signal based on the specific physiochemical change occurred during a biologic/enzymatic process. Among different type of transducers, the electrochemical transducer gained much attention due to reproducibility in results, ease of fabrication and cost effectiveness (Yoo and Lee 2010). Generally, an amperometric electrochemical biosensor is based on direct measurement of the change in current which may resulted from the change in target concentration due to specific enzymatic reaction. Currently, three enzymes including hexokinase, glucose oxidase (GOx) and glucose-1-dehydrogenase (GDH) are being used for the glucose detection biosensing platforms (Yoo and Lee 2010; Hussain et al. 2005; Heller and Feldman 2008). The spectrophotometric hexokinase assay is used as a reference method in clinical laboratories which involves the conversion of glucose into NADH by action of enzyme hexokinase and glucose-6-phosphate dehydrogenase. This enzymatic reaction sequence resulted into the formation of a coloured product with a strong absorbance at 450 nm which was detected by a spectrophotometer (Scheer et al. 1978). However, the use of hexokinase is not suitable for the point-of-care equipment development due to requirement of a costly spectrophotometer setup.

5.3

Generations of Enzyme-Based Electrochemical Glucose Sensors

Generally, most of the commercially existing glucose sensors utilize glucose oxidase (GOx) enzyme due to its economical nature along with greater sensitivity and specificity (Clark and Lyons 1962). In 1962, Clark and Lyons projected the early idea of glucose enzyme-based electrodes sensors. From the last few years, the scientific community has made tremendous efforts to improve GOx enzyme-based amperometric sensors for blood glucose monitoring (Wang 2001). The first glucose

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Scheme 5.1 The enzymatic oxidation of glucose to gluconolactone by glucose oxidase (GOx) with subsequent formation of hydrogen peroxide

sensor was made-up by Clark and Lyons, which involved the entrapment of GOx on an oxygen electrode by using a semi-permeable dialysis membrane that was used to catalyse the oxidation of glucose in the existence of O2 molecules (Scheme 5.1). The glucose oxidase (GOx)-based biosensors utilizes the production of hydrogen peroxide during the oxidation of β-D-glucose (Wilson and Hu 2000)(Fig. 5.1). In particular, the basic reaction in case of GOx-based biosensors involves the conversion of β-D-glucose into gluconic acid and hydrogen peroxide as oxidized products (Yoo and Lee 2010). Finally, the amount of glucose was determined by amperometric sensor obtained by the change in current resulted from the oxidation of hydrogen peroxide into oxygen using platinum electrode. However, the high overpotential applied to platinum electrode also facilitates the oxidation of other analytes such as ascorbic acid and lactic acid instead of hydrogen peroxide. Recently, efforts have been made to rectify this selectivity issue using platinum nanoparticles. On the other hand, the GOx enzymatic action also facilitated by a redox cofactor such as flavin adenine dinucleotide (FAD) which acts as an initial electron acceptor. Subsequently, the GOx-FAD enzyme unit has been immobilized over the TiO2 electrode using nanotubes for the direct electron transfer increasing the selectivity and sensitivity of glucose biosensors (Si et al. 2011). Glucose þ GOx - FADþ → Glucolactone þ FADH2

ð5:1Þ

GOx - FADH2 þ O2 → GOx - FAD þ H2 O2

ð5:2Þ

A major limitation of GOx-based biosensors is its dependency on the concentration of dissolved oxygen. Therefore, a hindered oxygen supply may affect the precision measurement of glucose biosensor (Wang 2008). In order to tackle this issue, glucose dehydrogenase (GDH) enzyme-based biosensors have been explored in the past decade. Researchers have provided a smart solution to overcome this problem with use of two working electrodes, which are covered with enzyme and other determining current alteration (Updike and Hicks 1967). Guilbault and Lubrano described first time to monitor H2O2 product during GOx-based glucose estimation using amperometric technique. Since 1973, various amperometric enzyme electrodes have been reported (Guilbault and Lubrano 1973).

Enzymatic Biosensor Platforms for Early Diagnosis of Diabetes

Fig. 5.1 Schematic diagram of glucose biosensor used for glucose monitoring in humans (dimensions are in millimetres). (Reproduced with permission from Wilson and Hu 2000)

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GOx-based glucose sensing reaction contains reduction of the flavin group in the GOx-FAD complex when react with glucose to reduce the GOx-FAD into GOx-FADH2. Based on nature of oxidation mediator(s), amperometric glucose sensor can be broadly categorized into three generations. The biological mediator oxygen, which is used as electron acceptor, and the electrode potentiostat at a potential positive of the known standard potential of GOx, are used as the oxidation mediator to regenerate GOx-FAD in the first-, second- and third-generation amperometric-based glucose sensors, correspondingly.

5.3.1

First-Generation Glucose Biosensors

In this generation, amperometric glucose sensors involved the oxygen as oxidation mediator to generate GOx-FAD and sense glucose molecules with help of monitoring the utilization of oxygen molecules or production of hydrogen peroxide in the procedure of the enzymatic reaction. In the GOx-mediated reaction, oxygen is used as an electron acceptor that makes the electron transfer very fast. In the electrochemical reaction, reduction of oxygen is generally used to observer the oxygen utilization for glucose estimation. However, anodic oxidation and cathodic reduction of hydrogen peroxide are employed to monitor the generation of hydrogen peroxide via enzymatic reaction. Moreover, to improve the enzymatic cycling, anodic oxidation of hydrogen peroxide can certainly regenerate or replenish oxygen. Measurements of oxygen utilization or hydrogen peroxide formation in the first-generation amperometric glucose biosensor have the advantage of being stable, simple, and easy to perform along with ability to miniature into device (Witkowska Nery et al. 2016). Response of this glucose sensor directly depends on the presence of oxygen concentration in working solution and plays a significant role in the measurement of glucose. Normal oxygen concentrations are about one order of magnitude lower in contrast to the physiological conditions is known as “oxygen deficit”. In the firstgeneration glucose sensors, the upper limit of linearity is significantly reduced due to oxygen deficit. On the other hand, sensitivity of biosensors to detect glucose is also limited by the oxygen levels in solution. To overcome these drawbacks of oxygendependent amperometric glucose sensors, researches have made an attempt to improve the sensitivity and upper limit of linearity by use of mass transport-limiting film. This film is offered to enhance the oxygen and glucose permeability ratio, consequently improve the oxygen deficit by using cylindrical electrode. Researchers also made oxygen rich carbon electrodes having enzyme or fabricated an air diffusion biocathode using oxygen directly from air to improve the oxygen supply to overcome the oxygen constraint.

5.3.2

Second-Generation Electrochemical Glucose Sensors

Oxygen deficit problem was one of the main drawbacks of the first-generation electrochemical sensors. It mainly occurs due to low solubility of O2 in the biological

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fluids such as blood. In order to eradicate this problem, an artificial oxidation mediator was introduced as a substitute of oxygen. Artificial electron mediators such as ferrocene, ferricyanide, quinine and tetracyanoquinodimethane (TCNQ) were used for the increased redox shuttle between GOx and electrodes (Wang and Stahl 2020). In the second-generation glucose sensors, artificial oxidation mediator can be either immobilized directly to enzyme or a solution state mediator can be diffused into and out of the enzyme active site. Moreover, it can entrap with enzymes and form a thin film involving redox-transmission polymer which can make electrons shuttle to form enzyme active sites (Witkowska Nery et al. 2016). Use of artificial electron acceptors in biosensors to make shuttle electrons using redoxcentre of enzyme to the surface of working electrodes is usually known as secondgeneration electrochemical sensors (Mao et al. 2003). Conducting organic, ferrocene derivatives, ferricyanide, phenoxazine compounds, quinone compounds, transitionmetal complexes, and phenothiazine compounds are more frequently used as effective mediators for GOx enzyme (Wang 2008). Remarkably, ferricyanide is not suggested as a very much capable electron mediator for glucose oxidase enzyme in few scientific reports, but the reaction mechanism remains unknown at current (Mao et al. 2003). The reaction mechanism of second-generation electrochemical glucose sensors contains the following three stages: (1) FAD reaction centres of GOx is reduced into FADH2, via the transfer of electrons and protons of glucose molecules. (2) Movement of electrons from the FADH2 centres to the artificial mediators, and consequently the mediators initiated the redox reaction. (3) The transport of electrons through the artificial mediators to the electrode.

5.3.3

Third-Generation Electrochemical Glucose Sensors

Third-generation glucose sensors are more advanced as they work in the absence of mediators. This particular feature renders them as an ideal sensing model. Detection of glucose at low potentials can be achieved by this biosensor through direct electrical communications GOx reaction centre (Si et al. 2011). Generally this generation of glucose sensor involves electron communication of enzymes which depends noticeably on the distance between the electrode surface and the redox active cofactor (Fruk et al. 2009; Alwarappan et al. 2012a). Several attempts have been made to overcome the long electron-tunneling distance to realize the direct electrochemistry of enzymes. Apoproteins modified electrodes and apoenzymes conjugated gold nanoparticles modified electrodes were widely adopted and used methods to make parallel redox enzymes reaction on the surface of electrodes (Fruk et al. 2009; Zayats et al. 2008). Though this process is operative in electrodes with electrically wiring redox enzymes, which complicated the processes and consequently inhibit its application in practice. Electrically wire enzymes were offered that involved and transform it from an oxidase to a hydrogenase through biocatalytically embedding Pt nanoclusters into GOx via thermodynamically reducing different metal salts to metallic nanoclusters with the reduced cofactor FADH2 (Chen et al. 2013). Scientific community has also been described to attain the direct

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electrochemistry of GOx with use of various nanoparticles/nanomaterials including graphene oxide (Wang et al. 2009a). In another report, Shan et al. used polyvinylpyrrolidone-protected graphene into the electrochemistry reaction of GOx and glucose sensing. In recent years, nanomaterial has been extensively used in the development of electrochemical-based sensors. In this context, it has been reported that graphene-GOx was used for glucose detection, and the advancement of glucose monitoring with nanotechnology-based biosensing is significant for the point of care. Further, nanomaterials such as graphene have been involved into improvement of electrochemistry-based biosensing (Alwarappan et al. 2010, 2012b). In another study, detection of glucose was achieved by direct electron transfer from GOx, which was immobilized PANI nanotubes (Wang et al. 2009b). Usually, the electron transfer between the electrode surface and buried redox active site of the GOx enzyme makes the conformational alteration of the enzyme, which possibly will result in an observable loss of enzyme activity. Balance between the enzyme and electrochemical reaction is a significant factor for the development of third-generation electrochemical glucose sensors, and it looks that scientific community still have a long way to go in this direction. It has been observed that thirdgeneration electrochemical sensors are absolutely expected to be globally recognized through successfully involving the redox active site of the enzyme to the electrode via using nano-sized conducting wires of little interference to the enzyme conformation (Chen et al. 2013).

5.4

Glucose Biosensors Based on Glucose Dehydrogenase

Other enzyme glucose dehydrogenases (GDHs) have been reported for the development of electrochemical-based biosensor for the glucose monitoring. Reaction mechanism of glucose dehydrogenase-based biosensor can be categorized via their numerous cofactors such as FAD, pyrroloquinoline quinone (PQQ), and nicotinamide adenine dinucleotide phosphate (NADP). In the glucose oxidase-based biosensor, oxygen is used as an external electron acceptor. In contrast to GOx, GDH utilizes strong redox cofactors such as pyrroloquinoline-quinone (PQQ) or nicotinamide adenine dinucleotide phosphate (NADP) for the oxidation of glucose to gluconolactone. Glucose þ PQQ ðoxidizedÞ → Gluconolactone þ PQQ ðreducedÞ

ð5:3Þ

Glucose þ NADþ → Gluconolactone þ NADHþ Though, GDHs are not capable to utilize oxygen, thus bypassing the issue of oxygen supplies. Hence, GDH-based electrochemical biosensor is independent of the oxygen concentration (Tseng et al. 2010). On the other hand, FAD/PQQ-GDH based sensor has wide-ranging substrate specificity, which is involved in the catalysis of other analytes present in the blood (for example, maltose). Protein engineering of the enzymes plays an important role to overcome this problem and which has

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offered to remove the enzymes’ activity toward other analytes, resultant in increased substrate specificity (Hofer et al. 2011; Yamaoka et al. 2008). Exogenous NADP is required for GDH-based electrochemical biosensor due to NADP is not physically bound to GDH enzyme (Abdellaoui et al. 2016). It has been found that NADPH was not oxidized directly within the biosensor due to the direct oxidation of NADPH can get impulsively polymerised products. These oxidation products significantly enhanced the potential of the electrode. Consequently, electrocatalytic molecules are used to subordinate the employed potential to the extent to avoid the NADPH oxidation. Even though GDH enzyme offered to operate without oxygen, but reaction is firmly restricted due to its substrate specificity along with prone to react with other molecules, resultant over estimation of glucose readings (Abdellaoui et al. 2016; Floré and Delanghe 2009). Hence, bio-engineering of GDH enzymes is crucial to reduce such potential due to intrinsic enzymatic reactions which consequently raise the consistency of glucose detection by using GDH enzyme.

5.5

Direct Monitoring of Blood Glucose Using Electrochemical Sensing

Glucose acts as a primary source of energy in the body. The optimum concentration of circulating glucose in blood and homeostatic system is maintained by complex biological processes such as insulin activity, gluconeogenesis and glycogenolysis which operates in a synergic manner. The dysfunction of glucose process owing to metabolic or genetic disorders resulted in manifestation of diabetes mellitus. In the direct monitoring of glucose, irregular spikes in the venous plasma glucose level are considered as a first indication of the metabolic impairment related to diabetes mellitus (Stahl et al. 2002).

5.5.1

Invasive Glucose Monitoring: Invasive-Based Glucose Biosensor

The standard technique of invasive mode for glucose monitoring requires the sample collection from venous plasma using a needle. However, an expert is required for the venous plasma collection and impurity purification prior to glucose analysis using portable kit. Thus, the blood samples are generally taken from fingertips using capillary which was subjected to glucometer for glucose monitoring. According to the recommendations of International Federation of Clinical Chemistry and Laboratory Medicine, the glucose recorded from whole blood is converted to the corresponding glucose in plasma using a conversion factor (D’Orazio et al. 2006; Fogh-Andersen et al. 1990; Fogh-Andersen and D’Orazio 1998) (Fig. 5.2). Unfortunately, the majority of times, a disease progression such as diabetes mellitus is often goes undetected due to its reputation as a silent killer as well as the lack in regular check-ups practice by the individuals. Therefore, recent advancements have been focused on the implantable systems for continuous glucose

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Fig. 5.2 Expanded view of an electrochemical blood glucose monitoring strip used for diabetes management

monitoring systems. The early implant prototypes encountered many drawbacks such as non-biocompatibility, short life time, non-specific catalytic reactions (Lucisano et al. 2016; Gough et al. 2010). Several efforts have been made to improve the efficiency of implants which include the use of polydimethylsiloxane (PDMS) layering and co-immobilization of excess catalyse. On the other hand, the low efficiency of implants also regarded to the slow diffusion of glucose in the tissue. Recent advances in the development of microdialysis catheters for the continuous monitoring of glucose have emerged as a parallel implant-based approach. The microdialysis techniques utilizes the specific diffusion glucose in very small quantities from interstitial fluids through catheters to the immobilized enzymatic biosensors.

5.5.1.1 Disposable Strip-Based Glucose Monitoring Generally, venous plasma is used to measure the concentration of glucose in blood, it is considered as the gold standard test for accurate assessment of glucose level in the circulating blood (Stahl et al. 2002). Collection of the plasma from blood using needle is an invasive process and also it is difficult for the patients to isolate the plasma by their own. Hence, blood strip test for the measurement of glucose level in the blood plasma is generally used which is offered capillary blood drawn from fingertips of patients or individuals. These strips contain a multilayer capillary channel to draw the blood samples efficiently and use precisely to the biosensor

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strips for measurement of glucose in small amount of blood samples. After blood is taken up by the disposable biosensor strips, it will be inserted into the glucometer device for the measurement of glucose in the circulating blood (Sun et al. 2012). For accurate detection of glucose level in blood by this mechanism, it is required to keep time interval constant between blood sample collection and glucose measurement. The International Federation of Clinical Chemistry and Laboratory Medicine suggested that glucose concentration measured by this method corresponds to the level of glucose in the plasma with the help of glucometer devices (D’Orazio et al. 2006). With the help of impedance-based method, estimate the haematocrit ratio which is used to precisely calculate the glucose level in the circulating blood with the use of plasma via glucometer device (Villena Gonzales et al. 2019; Weng et al. 2017).

5.5.1.2 Implantable Biosensors for Continuous Glucose Mentoring Microdialysis and biocompatible implantable biosensors devices have been established for continuous blood glucose monitoring in the patient (Nichols et al. 2013). It has been reported that implantable biosensor for glucose monitoring is associated with various problems, such as a poor biocompatibility and tiny lifespan. To overcome these issues, scientific communities used a nonporous PDMS layer which co-immobilize with the catalase enzyme to increase the lifespan of the test (Lucisano et al. 2016; Gough et al. 2010). These devices are used just like an oximetry type for glucose monitoring which faces an oxygen deficit problem (Li et al. 2007). This oxygen deficit problem is improved with help regeneration of the oxygen with involvement of GOx and catalase enzyme to limit the diffusion of glucose by a two-dimensional membrane, consequently enhancing the oxygen glucose concentration ratio. However, microdialysis technique is an intravenous blood collection process, which involves a microdialysis probe along with a semipermeable membrane and it is injected into the vein (Heise et al. 2007; Rooyackers et al. 2013). Venous blood is perfused constantly via a probe, and present glucose molecules in the dialysate are monitored with the help of a connected sensor (Nichols et al. 2013) (Fig. 5.3). On the other hand, the implant-based device also faces challenges in the accurate measurement due to interference from the various electroactive chemicals as given in Table 5.1.

5.5.2

Non-invasive Methods for Glucose Monitoring

The non-invasive detection of the early onset of metabolic dysfunction related to insulin resistivity is done by monitoring the glucose levels in various biofluids such as saliva, tear, or sweat. Most of non-invasive glucose sensor utilizes the wireless signal communication which may be powered by a radio frequency source (Kim et al. 2017; Falk et al. 2013). The equipment used for the continuous non-invasive glucose monitoring depends upon the selection of biofluid. The graphene-based transparent lens has been explored for the continuous monitoring of glucose using

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Fig. 5.3 The foreign body response to a percutaneous glucose sensor upon tissue implantation. Arrows in the magnified area show diffusion of glucose from blood vessels toward the sensor through native tissue (e.g., adipocytes), the collagen capsule, localized inflammatory cells, and biofouling layer near the sensor surface. As illustrated, glucose may be consumed by native tissue or inflammatory cells prior to reaching the sensor. (Reproduced with permission from Nichols et al. 2013) Table 5.1 List of potential electrochemical interfering species problematic to amperometric enzyme-based glucose biosensorsa (reproduced with permission from Nichols et al. 2013)

Interfering species Exogenous drugs or drug metabolite

Endogenous species

a b

Acetaminophen Dopamine Ibuprofen Methyldopa Salicylic acid Tetracycline Tolbutamide L-Ascorbic acid Bilirubin (unconjugated) Cholesterol Creatinine Galactose Triglycerides Urea Uric acid

Test concentration recommended (μmol/ L) 1324 5.87 2425 71 4340 34 2370 170 342

Therapeutic (or biological) concentration (μmol/L)b 66–200 1.96 48.5–340 4.73–35.5 720–2170 4.5–11.3 200–400 23–85 5–21

13,000 442 200 mg/dL, and HbA1C greater than or equal to 6.5% is diagnosed as diabetic. Diabetes mellitus can be classified into various types depending upon the cause and symptoms developed, viz., type 1, type 2, type 1.5 (also called type 3), MODY (maturity-onset diabetes of the young), diabetes associated with pancreatic defects (chronic pancreatitis, hemochromatosis, cystic fibrosis), other endocrinopathies associated with diabetes (Cushing’s syndrome, growth hormone adenoma, hyperthyroidism), and diabetes due to infection (measles, mumps, coxsackievirus, CMV). Type 1 DM is the most uncommon (~ 10% cases), usually seen in children of less than 20 years of age and thin physique. Type 1 DM patients have complete lack of insulin due to β-cell destruction or damage. The major reasons identified for causing type 1 DM include genetic factors as well as environmental factors (life style). The

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genetic factors include MHCII genes associated with DR-3/DR-4 and DQ-8 (DQ-8 has the greatest inheritance risk). The genetic defects known for non-MHC genes include PTPN-22 gene polymorphism and cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) polymorphism. The environmental factors such as obesity, lack o physical activity, diet etc., leading to type 1 DM, y caused by viral infection leading to the activation of CD8T cells and hence β-cell destruction. The inflammation of CD4T cells via cytokines (IFN-γ/TNF-α) and CD8T cells causes the destruction of β cells. Further, the antibodies formed against glutamic acid decarboxylase and insulin cell autoantigen (ICA-512) induce rapid autoimmune response. The hyperglycemia and ketosis result when there >90% damage of β cells. Type 2 DM is the most common diabetic disorder (~80% cases). It is not an autoimmune disorder which involves multifactorial etiology, viz., genetic and environmental. The genetic factors include polymorphism of genes like TCF-7-L-2 (transcription factor 7-like 2 gene). The environmental factors responsible include obesity, sedentary lifestyle, and poor dietary habits. The reason for type 2 DM is mainly by insulin resistance but can also involve some amount of β-cell destruction. Insulin resistance may be defined as a decreased response of peripheral tissue to insulin mainly due to central obesity. The increased amounts of free fatty acids (FFA) reach tissues like the liver and muscles where it is converted to intracellular triglycerides, which upon oxidation form toxic substances like diacylglycerol and ceramide. These end products inhibit insulin signal and hence cause insulin resistance. Further, adipokines (adipose tissue cytokines) also regulate glucose level via pro-hyperglycemic adipokines like resistin and retinol binding protein (RBP-4) which increases the glucose level and anti-hyperglycemic adipokines leptin and adiponectin responsible for reducing the glucose level. Obesity can lead to the reduced secretion of adiponectin leading to insulin resistance. Further, FFA within macrophages and β cells activate inflammasomes to release interleukin-1β which in turn causes insulin resistance. Moreover, peroxisome proliferator-activated receptor γ (PPAR-γ), a nuclear receptor for the activation of adiponectin and responsible for FFA deposition in the adipose tissue, upon mutation leads to insulin resistance. Type 2 DM may also result from β-cell damage caused by free fatty acids, amyloids, and abnormal incretin secretion. Incretin is a hormone released by the intestine, involved in insulin activation and glucagon inhibition. Obesity leads to abnormal incretin secretion. Recently, scientists have introduced type 1.5 DM, which falls between the types 1 and 2. Latent autoimmune diabetes of adults (LADA) is a variant of type 1 DM but is late in onset. The treatment requires insulin therapy. MODY is monogenic diabetes, hereditary in origin, and autosomal dominant, occurs in young patients (~25 years of age), and is not caused by obesity or β-cell destruction. It is maternally inherited diabetes accompanied by deafness due to mitochondrial DNA mutation.

8.3.1

Biomarkers for Diabetes Mellitus

The most commonly used biomarkers for diabetes are blood glucose and HbA1c. The normal levels of these markers for prediabetic and diabetic individuals are

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mentioned in the text above. There are various other potential biomarkers for diabetes (mentioned in Table 8.2). The 1,5-anhydroglucitol is a naturally occurring monosaccharide found in all foods. Its concentration decreases under hyperglycemic condition above 180 mg/dL and returns to normal in 2 weeks in the absence of any further hyperglycemic episode. The 1,5-anhydroglucitol, though rarely used, determines the occurrence of recent hyperglycemia and can be used as a complementary test to HbA1c and fructosamine estimation. Another prospective diabetes marker is adiponectin. Adiponectin is an adipocyte-derived peptide hormone that has anti-inflammatory and insulin-sensitizing properties. The low serum levels of adiponectin have been associated with the development of diabetes. Fetuins are various transport glycoproteins in the blood which are manufactured in the liver, which are also a diabetes biomarker. The various biomarkers for diabetes have been reviewed by Dorcely et al. (2017). Diabetes mellitus manifests itself as high blood glucose levels (also called hyperglycemia), which in turn makes way for other complications like blindness, cardiovascular disorders, kidney damage, etc. The severe ramifications of diabetes make it very necessary for close personal monitoring of blood glucose levels; hence, the presence of accurate and convenient glucose sensors is crucial. Among the various blood glucose sensors developed, the optical and the electrochemical sensors are most widely investigated and accepted (Martinkova and Pohanka 2015). The optical sensors involve an enzymatic conversion of glucose into its by-products accompanied by a change in color which is proportional to the concentration of glucose. Optical methods being qualitative do not provide the exact glucose levels and fail to identify hypoglycemic events. The quantitative measurements of optical sensors involve the use of bulky instruments like spectrophotometers, making it suitable for use in only hospitals and unsuitable for regular use at home. Electrochemical glucose sensors being quantitative provide a simple and accurate method of glucose measurement and are hence more widely applied. The most common type of glucose sensor used is amperometric enzyme-based glucose sensor. The enzyme-based electrochemical biosensors for blood glucose detection can be invasive or non-invasive. • The invasive methods involve the attachment of a disposable strip to the glucometer, and blood drawn using a needle is collected on the strip, to give glucose levels in under a minute. The drawback of such monitoring system is that it is not continuous, and hence the blood glucose spikes might go unnoticed. • Implantable glucose sensors are also used, providing continuous glucose measurements from intravenous blood, but have the disadvantage of being invasive and being susceptible to biofouling.

8.3.2

Challenges

The non-invasive monitoring methods employ biological fluids like tears, saliva, interstitial fluids (ISF), and sweat, which contain glucose levels holding direct

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Table 8.2 Biomarkers for diabetes mellitus S. no. 1

Biomarker HbA1c

Type of DM Diabetes and prediabetes, average glucose level for 3 months Average blood glucose levels for 2–3 weeks Reflects shortterm glycemia

2

Fructosamine (FA)

3

Glycated albumin (GA)

4

1,5-Anhydroglucitol

Used to detect recent hyperglycemic episode

5

α-Hydroxybutyrate

Diabetes

6

Linoleoylglycerophosphocholine

Diabetes

7

Ceramide

Prediabetes

8

miRNA (miR-192, miR-193b, miR-15a)

Prediabetes

9

IL-18

Diabetes and prediabetes

10

IL-1 receptor antagonist

Prediabetes and diabetes

Role in DM Hba1c is formed when glucose attaches to the N terminal of hemoglobin Fructosamine is formed when serum proteins are glycosylated It represents the ratio of glycosylated albumin to total albumin Is a naturally occurring monosaccharide in all foods. Its level decreases under hyperglycemic condition and returns to normal after 2 weeks in the absence of hyperglycemia α-Hydroxybutyrate is a marker for insulin resistance and lipid oxidation, both of which precede the development of diabetes and cardiovascular disease LGPC is a potential biomarker for insulin resistance and impaired glucose metabolism Specific long-chain fatty acid-containing dihydroceramides are significantly elevated in the plasma of individuals susceptible to developing diabetes miR-192, regulates p53; miR-193b, brown adipocyte differentiation and inflammation reduction; miR-15a, promotes insulin synthesis. Many miRNAs have been found to be correlated with prediabetes IL-18 increases during hyperglycemia. High IL-18 is linked with the progression from prediabetes to diabetes It is an anti-inflammatory marker which increases upon the induction of IL-1 (continued)

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Table 8.2 (continued) S. no.

Biomarker

Type of DM

Role in DM pathway due to higher glucose and fatty acid metabolism during overfeeding

correlation with blood glucose levels. It is to be noted that the glucose levels in these body fluids are much less than the glucose concentration in the blood, viz., the glucose concentration range in the blood is 2–40 × 10-3 M, in ISF is 1.99–22.2 × 10-3 M, in saliva is 0.008–1.77 × 10-3 M, in sweat is 0.01–1.11 × 10-3 M, and in tears is 0.05–5 × 10-3 M (Martinkova and Pohanka 2015). Hence, the sensor should be developed and optimized as per the specific range of the body fluid to be analyzed. There are various other challenges associated with the different body fluids to be used for analysis. The tears, although have low interference and impurities present, but energy source for glucose sensor implanted in the contact lens to function autonomously for continuous glucose monitoring and providing data wirelessly is a challenge. For saliva, the collection of sample is easy, but the large amounts of impurities in saliva provide interference. The measurement from ISF has been developed and is also being used, which involve wearable devices with iontophoresis or reverse iontophoresis on the skin. The monitoring from sweat is applicable as well as accessible, but the patient requires to sweat for each measurement. The invasive methods are very widely used but are inconvenient for the patient due to the requirement of frequent pricking, while the non-invasive methods are being investigated to develop methods which provide accurate, continuous measurements without the trauma of pricking.

8.3.3

Generation of Glucose Sensor

Research focusing on glucose sensing has invested more than four decades over the development of glucometer, and this progress can be divided into three different generations (Fig. 8.3). • The first generation of glucose oxidase sensors measures the oxygen consumed or the hydrogen peroxide produced, which reacts with the electrode to measure glucose concentration. The high positive overpotential of 1 V versus Ag/AgCl used to detect glucose also facilitates nonspecific reactions like oxidation of lactic acid, uric acid, ascorbic acid, etc. The incorporation of platinum electrodes, as additional mediators, helps improve the selectivity by lowering the overpotential and hence preventing nonspecific reactions. Platinum is very reactive toward hydrogen peroxide, which reduces side reactions, but the high positive potential is still a challenge. In another approach, Prussian blue (PB) has also been used as

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Fig. 8.3 Generation of enzyme-based sensor based on the source and transfer of electron toward electrode

an electrocatalytic mediator, which lowers the potential to 0 V versus Ag/AgCl, and it uses the reduction of hydrogen peroxide at negative potentials, leading to the current generation proportional to its concentration. • The second generation of glucose oxidase-based sensors involves direct interaction between a redox mediator and enzyme. Redox mediators like ferrocene being in contact with glucose oxidase act as diffusional electron mediators, leading to the increase in current in the presence of glucose. But ferrocene or ferricyanide being toxic is not recommended for in vivo use due to the possible leaching out from the sensor. • The third generation of glucose oxidase-based sensors depends on the use of genetically engineered enzymes, designed to facilitate direct electron transfer from the enzyme to the nanostructured electrode. Electrodes treated with nanotubes, like TiO2 (1DHS TiO2), facilitate direct electron transfer between the enzyme and the electrode. While most of the commercially used glucose sensors are based on the first- and second-generation glucose oxidase-based sensors, the research for selective and more energetically efficient detection systems is under way.

8.3.4

Enzymes for Glucose Sensor

The use of enzymes for glucose sensors is a widely accepted mechanism involving the rapid action of these enzymes (with high catalytic turnover) on glucose in an energetically favorable reaction to produce by-products which can be measured (Table 8.3). The most used enzyme is glucose oxidase (GOx), which oxidizes glucose to gluconic acid and hydrogen peroxide. Another potential enzyme that can be used for glucose estimation is glucose dehydrogenase (GDH) which is independent of oxygen. The type of GDH sensor depends on the cofactor used, viz., FAD (bound state), pyrroloquinoline quinone (PQQ) (bound state), and nicotinamide adenine dinucleotide (NAD(P); unbound state). Due to the broad substrate

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Table 8.3 State-of-the-art enzyme-based sensor for diabetes management Enzymes used in assay Glucose oxidase

Strategy/type of biosensor Amperometry (Baratella et al. 2013)

Biomarker Glucose

Fluorescence (Chang et al. 2010)

Glucose

Glucose oxidase

Cyclic voltammetry (Cui et al. 2013)

Glucose

Glucose oxidase

Electrochemiluminescence (Haghighi and Bozorgzadeh 2011)

Glucose

Glucose oxidase

Electrochemiluminescence (Haghighi and Bozorgzadeh 2011)

Glucose

Glucose oxidase

Phosphorescence (Ho et al. 2014)

Glucose

Glucose oxidase

Amperometry (Homma et al. 2014)

Glucose

Glucose oxidase

Electrochemiluminescence (Li et al. 2010)

Glucose

Glucose oxidase

Cyclic voltammetry (Zhang et al. 2014)

Glucose

Glucose oxidase

Differential pulse voltammetry (Zhao et al. 2013)

Glucose

Glucose oxidase

Role of enzyme in assay GOx on surface active maghemite nanoparticles coated carbon paste electrode GOx in sol-gel on microarray filled with Rb-fluorophore film GOx on TiO2 filmcoated carbon nanotubes modified using Fe-phthalocyanine GOx immobilized on Pd nanoparticles in multi-walled carbon nanotubes coated glassy carbon electrode GOx immobilized onto chitosan layer on multi-walled carbon nanotubes coated by au nanoparticles on glassy carbon electrode GOx immobilized in hydrogel with crystalline Ir substrate, coordination polymers coated egg membrane GOx covalently attached on N-phenylglycine film on electrode GOx on poly (luminol-aniline) nanowire composites coated graphite electrode GOx on thin film of cysteamine covering au electrode GOx on silicon oxidephytic acid nanoparticles coated glassy carbon electrode

LOD 2 μM/L

60 μM/L 30 μM/L

50 μM/L

0.5 μM/L

10 μM/L

30 μM/L

30 nM/L

50–300 μM/ L 10 μM/L

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specificity of FAD/PQQ-GDH, the system tends to detect other analytes from the sample like maltose. Although genetically engineered GDH has been employed to increase its specificity for glucose, the NAD(P) tends to get directly oxidized and may beget spontaneously polymerized oxidation products, leading to the high overpotential and significant fouling of electrodes.

8.4

Cancer

Cancer is an uncontrolled proliferation of cells leading to the formation of tumor due to nuclear instability caused by DNA damage. Cancer is a multi-stage process of accumulation of mutations in both proto-oncogenes and tumor suppressor genes leading to increase in growth stimulation, loss of division control, and immortality of cells. For example, colon cancer manifests by stepwise mutation in tumor suppressor genes (APC, TGF-β, and p53) and proto-oncogenes (KRAS). Tumors can be benign or malignant. Benign tumors are localized, encapsulated, and non-cancerous and can be removed surgically, while malignant tumors are metastatic and travel to new regions to form secondary tumors, via the circulatory system and lymphatic system, and true cancers. The initial cell mass (tumor) formed due to increased cell division usually due to single gene mutation is called the polyp stage (or small adenoma), followed by further gene mutation due to increased cell division forming intermediate adenoma, which further leads to the mutation of more genes and hence enhanced cell division rate to form late adenoma. True cancer if formed by further DNA damage caused late adenoma leading to a metastatic stage where the tumor cells acquire all characteristics of cancer. On the basis of origin, cancers can be classified as carcinoma (cancer of epithelial cells, e.g., lung cancer, breast cancer, uterine cancer, colon cancer, skin cancer, prostate cancer), sarcoma (cancer of solid connective tissue, e.g., muscle, bone, and fibroblast cancer), leukemia (cancer of white blood cells), lymphoma (cancer of lymphatic system cells), and myeloma (cancer of specialized white blood cells, e.g., antibody-secreting cells). Cancerous cells have a certain set of properties. • They are capable of neoplastic transformation, i.e., cells lose identity to form undifferentiated cells. • They can undergo uncontrolled rapid cell division due to the mutation of both proto-oncogenes and tumor suppressor genes. • Cancer cells are self-sufficient for growth signal as they are capable of autocrine stimulation (activation by growth factors secreted by the cancer cells themselves, RTK receptor hyperactivation, and downstream signaling targets hyperactivation). • Further, they are insensitive to antigrowth signals, due to loss of function of tumor suppressor genes like TGF-β, SMAD4, p15, p16, p21, p53, RB, etc. Due to loss of function of p53 and overexpression of anti-apoptotic genes like BCL-2, the cancer cells can evade apoptosis and are hence immortal. The cancer cells do not undergo senescence due to loss of function of p53 and overexpression of hTERT (human telomerase reverse transcriptase).

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• The cell mass formed by uncontrolled cell division is capable of developing angiogenesis by the activation of VEGF (vascular endothelial growth factor) via HIF-1 (hypoxia-inducible factor-1). • The loss of cell adhesion properties cancer cells can invade a circulatory system and lymphatic system and spread to new regions.

8.4.1

Cancer Biomarker

The molecular pathogenesis of cancer involves the mutation of three types of genes, viz., genes involved in cell proliferation (stimulation of proto-oncogenes and loss of function of tumor suppressor genes), genes involved in the regulation of apoptosis (overexpression of anti-apoptotic genes and loss of function of pro-apoptotic genes), and mutation for loss of function of DNA repair pathways (Table 8.4 lists the cancer biomarkers). The causes of cancer are basically DNA damage caused by radiations (ionizing and non-ionizing radiations), chemical agents (intercalating agents, base analogues, reactive oxygen species), or biological agents (virus infection, e.g., hepatitis B virus, liver cancer; papillomavirus, cervical carcinoma). The various tumor suppressor genes whose loss of function can lead to cancer can be classified as gatekeeper genes (inhibit proliferation) and caretaker genes (involved in DNA repair). The gatekeeper genes include p53 (major tumor suppressor gene), retinoblastoma (RB), INK4 (inhibitors of cell cycle, p15, p16, p21), APC, PTEN (inhibits cell division by inhibiting the activation of Akt kinase), TGF-β receptor, and SMAD4. The caretaker genes include the ones involved in doublestrand break repair system, DNA mismatch repair system, DNA excision repair system, and DNA trans-lesion system and PARP-1 (works in DNA repair system; is a biomarker for specific proteolytic activity involved in apoptosis and autophagy). The loss-of-function mutation of tumor suppressor gene is recessive, hence should occur in both alleles to be effective, except for p53, which has a negative dormant effect. p53 is also called the guardian of the genome as it controls cell division at three levels, viz., DNA repair, cell cycle, and apoptosis. The active p53 tetramer is formed by the assembly of protein monomers formed from both alleles of the gene; hence, mutation in even a single allele can lead to the formation of inactive tetramers and hence affect the cell. Retinoblastoma (RB), first identified in retina cancer, plays a leading role in G1 phase of cell cycle, by inhibiting E2F and arresting the cell in G1 phase. The sporadic form of loss of function of RB needs mutation in both alleles (two hits are required to cause cancer), while the hereditary form (with one allele already mutated) requires only one hit of mutation to cause cancer. At least one gain-of-function mutation in the proto-oncogenes leads to the formation of oncogenes (dominantly mutated allele) leading to unregulated cell proliferation. HER-2 (a key role player in breast cancer), an EGF family growth factor receptor upon mutation, undergoes overstimulation leading to the uncontrolled activation of Ras-raf and hence cell proliferation. Further, the overactivation of Ras by point mutation of glycine to valine by loss of GTPase activity constitutively activates Ras-MAP pathway and hence uncontrolled division. The deletion of

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Table 8.4 A list of biomarkers used for cancer diagnosis S. no. 1

Biomarker Beta-2-microglobulin (B2M)

2

Beta-human chorionic gonadotropin (beta-hCG) BRCA1 and BRCA2 gene mutations BCR-ABL fusion gene (Philadelphia chromosome)

3 4

5

C-kit/CD117

6 7

CA15-3/CA27.29 CA19-9

8 9 10 11 12

CA-125 CA 27.29 Calcitonin CD20 CD22

13

CD25

14

CD30

15 16 17

CD33 Chromosome 17p deletion Chromosomes 3, 7, 17, and 9p21 Des-gamma-carboxy prothrombin (DCP) DPD gene mutation

18 19 20 21 22 23 24 25 26 27

EGFR gene mutation FGFR2 and FGFR3 gene mutations Fibrin/fibrinogen FLT3 gene mutations Gastrin HE4 HER-2/neu gene amplification or protein overexpression JAK2 gene mutation

Type of cancer Multiple myeloma, chronic lymphocytic leukemia, and some lymphomas Choriocarcinoma and germ cell tumors Ovarian and breast cancer Chronic myeloid leukemia, acute lymphoblastic leukemia, and acute myelogenous leukemia Gastrointestinal stromal tumor, mucosal melanoma, acute myeloid leukemia, and mast cell disease Breast cancer Pancreatic, gallbladder, bile duct, and gastric cancers Ovarian cancer Breast cancer Medullary thyroid cancer Non-Hodgkin lymphoma Hairy cell leukemia and B-cell neoplasms Non-Hodgkin (T-cell) lymphoma Mycosis fungoides and peripheral T-cell lymphoma Acute myeloid leukemia Chronic lymphocytic leukemia Bladder cancer

Matrix Blood, urine, or cerebrospinal fluid Urine or blood Blood and/or tumor Blood or bone marrow Tumor, blood, or bone marrow

Blood Blood Blood Blood Blood Blood Blood and bone marrow Blood Tumor Blood Blood Urine

Hepatocellular carcinoma

Blood

Breast, colorectal, gastric, and pancreatic cancers Non-small cell lung cancer Bladder cancer

Blood

Bladder cancer Acute myeloid leukemia Gastrin-producing tumor (gastrinoma) Ovarian cancer Breast, ovarian, bladder, pancreatic, and stomach cancers Certain types of leukemia

Urine Blood Blood

Tumor Tumor

Blood Tumor

(continued)

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Table 8.4 (continued) S. no.

Biomarker

Type of cancer

28

KRAS gene mutation

29

30

Microsatellite instability (MSI) and/or mismatch repair deficiency (dMMR) Neuron-specific enolase (NSE)

Colorectal cancer and non-small cell lung cancer Colorectal cancer and other solid tumors

31 32

Nuclear matrix protein 22 PCA3 mRNA

33 34 35

Prostate-specific antigen (PSA) ROS1 gene rearrangement Somatostatin receptor

36

Thyroglobulin

Small cell lung cancer and neuroblastoma Bladder cancer Prostate cancer

Matrix Blood and bone marrow Tumor Tumor

Blood

Prostate cancer

Urine Urine (collected after digital rectal exam) Blood

Non-small cell lung cancer Neuroendocrine tumors affecting the pancreas or gastrointestinal tract (GEP-NETs) Thyroid cancer

Tumor Tumor (by diagnostic imaging) Blood

regulatory region of Ras also leads to the activation of Ras as oncogene, caused by the insertion of viral Gag portion in regulatory region and hence uncontrolled activation of protein kinase domain and leading to Ras-MAP pathway. Various chromosomal translocations can also lead to the activation of proto-oncogenes. For instance, translocation of C-myc (from heterochromatin region) on chromosome 8 to IgH locus (euchromatin region) on chromosome 14 causes its overexpression leading to Burkitt lymphoma. Further, Abl translocation from chromosome 9 to euchromatin region of chromosome 22 (bcr locus) can lead to the overactivation of Abl gene and hence chronic myeloid leukemia.

8.4.2

Biosensor for Cancer Detection

Cancer, in about 200 different forms, viz., breast cancer, lung cancer, prostate cancer, etc., is the most feared disease and is among the leading causes of death. Breast cancer is the most common form of cancer and has been found to be among the leading cause of death in women worldwide (Ranjan et al. 2020). Despite the existence of various technologies like mammography, sonography, tomography, etc., the exact diagnosis of the disease at early stage is still not certain. Further, the lack of availability of expensive technologies in underdeveloped countries makes the situation even worse. Development of more efficient, highly sensitive, non-invasive, and low-cost technologies is essential for the better diagnosis and prevention of disease progression.

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8.4.2.1 Sensors for Breast Cancer Researchers across the globe have attempted to develop biosensors for breast cancer using electrochemical transducers and overexpression of biomarkers like BRCA1 gene, VEGF, EGFR, MUC1, HER-2, CA15-3, etc. (Mittal et al. 2017). Recently, Swisher et al. (2014) have developed an electrochemical sensor for the detection of breast cancer using the enzymatic activity of cathepsin as biomarker. Cathepsin is a class of protease enzymes which cut the peptide at their signature sequences. It was observed that cathepsin level was increased in various biological fluids during breast cancer progression. A ferrocene-labeled (redox mediator) tetrapeptide H2N-(CH2) 4CO-Leu-Arg-Phe-Gly-NH-CH2-Fc was immobilized over electrode through the carbon nanofiber. Cathepsin B cleaves the peptide at the site between arginine (Arg) and phenylalanine (Phe) and causes the release of the ferrocene from the electrode surface, leading to an exponential decay of the corresponding electrochemical signal (Fig. 8.4). The decay of exponential electrochemical (current) signal was found to be in good correlation with cathepsin B. Breast cancer is the second most common cancer around the world after lung cancer. There are several types of breast cancer depending on which part of breast tissue turns into tumor such as lobules, ducts, and connective tissue. It can spread to other parts of the body through the blood or lymph vessels or both. There are various types of biomarker known such as BRACA-1, BRACA-2, HER-2 aka neu or ErB2, etc. Among this, HER-2 is overexpressed in 20–30% of human breast cancer and directly associated with most fast-growing cancer cells in the breast (Cho et al. 2003). The second region which makes it a suitable target for breast cancer diagnosis because the extracellular domain (ECD) of HER-2 is frequently sliced and released into blood circulation. Approximately 45% of breast cancer patient serum ECD of HER-2 was detected. A normal person has HER-2 levels between 2 and 15 ng/mL, while a breast cancer patient has a higher level of HER-2, usually falling between

Fig. 8.4 Schematic diagram of the electrochemical biosensor for breast cancer involving cleavage of tetrapeptide H2N-(CH2)4-CO-Leu-Arg-Phe-Gly-NH-CH2-Fc at the VACNF NEA tip by cathepsin. The digestion of the peptide between arginine (Arg) and phenylalanine (Phe) releases Fc into solution causing an exponential decay of the electrochemical signal

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Input light

Tapered fiber

193

WGM

Analyte

Direction of flow

b

Antibody Biomarker Protein G 3-APS/ crosslinker

Fig. 8.5 Schematic of OFRR (a) and working principle of OFFR sensor (b). (Adapted from Gohring et al. 2010)

15 and 75 ng/mL. Monitoring the blood levels of HER-2 can help evaluate the effectiveness of cancer treatments; hence, Gohring et al. (2010) developed an optical fluidic ring resonator (OFRR)-based biosensor. It has been reported to be a labelfree, rapid, low-cost technology with a physiologically relevant detection range of 13–100 ng/mL in 30 min time. The concept of OFRR is like whispering galleries that help to intensify the sound through resonance. OFRR consists of a set of optical waveguides connected with computer-programmed input and output (detector) and follows the principle of constructive interference and total internal reflection. When the light at resonance frequency passed through the waveguide, due to constructive interference, it fosters the intensity over multiple round tips and is recorded by the output detector. The OFRR and microfluidic system are integrated to build an OFRR sensor for the detection of HER-2. To support circulating whispering gallery modes (WGM), a thin-walled capillary with high Q ring resonator was used. Inside of OFRR, the evanescent field of WGM was extended about 100 nm core area and functionalized with anti-HER-2 antibody to capture the HER-2 from biological fluids (Fig. 8.5). When analytes are captured on the OFRR inner surface; changes happen in the effective refractive index (neff) hence caused alteration in WGM. The change in

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Fig. 8.6 Schematic of PCR-free “sandwich-like” colorimetric biosensor with magnetic bead platform for the detection of breast cancer 1 (BRCA1) DNA. (Adapted from Yang et al. 2017)

WGM resonance wavelength (λ) was calculated with the below equation. R is the OFRR radius, and m, an integer number, is the angular momentum of the WGM.

2πRneeff = mλ Moreover because of high Q-factor, the OFRR can reach the limit of detection ~10-7 refractive index unit (RIU), i.e., equivalent to subpicogram/mm2 of analyte placed this type of sensor among the sensitive class of biosensor (Zhu et al. 2008). BReast CAncer gene 1 (BRCA1) is another well-known biomarker for breast cancer detection. Yang and coworkers (Yang et al. 2017) developed a magnetic microparticle-based sandwich structure DNA biosensor using a tetrahedronstructured reporter probe (TSRP) for the detection of breast cancer-associated BRCA1 gene (Fig. 8.6). The three vertices of the tetrahedron were designed to contain digoxin, providing an ample space for the binding of three anti-dig-labeled horseradish peroxidases for a single probe, while the fourth one was labeled with a detection probe complementary to the target sequence. The LOD of detection was found to be as low as 10 fM. In the detection process, the sample containing target gene sequence, the MMPs covered by capture probes, and TSRP interacts to form a sandwich complex. Absence of the target sequence does not allow the formation of the sandwich complex. The formation of the sandwich complex is detected by the separation and addition of TMB and H2O2 substrate, leading to the formation of blue color. The intensity of the color formed is directly proportional to the concentration of the target DNA sequence in the sample.

8.4.3

Sensor for Lung Cancer

Another most common cause of cancer-related death is due to lung cancer. The cytokeratin fragment 21–1 (CYFRA 21-1) and neuron-specific enolase (NSE) are the common biomarkers for non-small cell lung cancer (NSCLC) and small cell lung

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Fig. 8.7 Schematic drawing of the plasmonic chip and the detection assay. (Adapted from Toma et al. (2018))

cancer (SCLC), respectively (Cheng et al. 2015; Hatzakis et al. 2002). Recently, Toma et al. (2018) have developed a rapid quantitative assay for neuron-specific enolase (NSE) by using a disposable silver plasmonic chip functionalized with an antibody-coated polydopamine (PDA) particle (Fig. 8.7). This plasmonic chip with a functionalized layer was used for the excitation of propagating surface plasmon resonance. The detection of NSE was done by a fluorescence-based sandwich immunoassay by using surface plasmon-enhanced fluorescence (SPF) spectroscopy. The developed biosensor provided close to linear sensor response for the detection of NSE at clinically significant concentration (12 ng/mL) in diluted human serum. The detection limit for NSE is 1.4 ng/mL (30 pM) in a diluted human serum.

8.4.4

Sensor for Ovarian Cancer

Carbohydrate antigen-125 (CA-125) is a well-known cancer biomarker for the diagnosis of ovarian cancer. It is also known as mucin 16 or MUC 16 protein expressed by MUC-16 gene. It is an approved biomarker for the diagnosis (detection and therapy) of patients presenting pelvic mass. Although CA-125 is known for ovarian cancer, it has been also associated with other types of cancer such as lung, breast, gastrointestinal, and endometrial. Zhao and Ma (2018) developed an ultrasensitive label-free amperometric immunosensor on polyalanine-polythionine redox for the detection of carcinoma antigen CA-125, with LOD of 0.00125 U/mL. Under this work, they have employed a three-dimensional nanocomposite consisting of polyaniline-polythionine (PANI-PThi) as a matrix hydrogel with impregnated gold nanoparticle (Fig. 8.8). The 3D hydrogel protects the sensor surface from biofouling (nonspecific adsorption of biological fluid constituents over the sensor surface) without hampering conductivity because of the high conductivity of PANI-PThi

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Fig. 8.8 Schematic drawing of the amperometry immunosensor for CA-125 detection. (Reproduced by permission of Elsevier (Zhao and Ma 2018))

complex. Moreover, highly negative surface charge generated by the phosphate group of PThi prevents from biofouling. Furthermore, PANI-PThi gel and AuNPs have the capability to synergistically catalyze the oxidation of H2O2. Hence, in the presence of H2O2, enhanced current signal was observed. Accordingly, the prepared immunosensor has shown good conductivity and stability in the human serum.

8.4.5

Other Sensors for Cancer

The p53 is known as major tumor suppressor gene, whose loss of function can lead to cancer. This gene is directly or indirectly involved in double-strand break repair system, DNA mismatch repair system, DNA excision repair system, and DNA translation system. Normally, loss-of-function mutation of the tumor suppressor gene is recessive, hence should occur in both alleles to be effective, except for p53, which has a negative dormant effect. The p53 is also called the guardian of the genome as it controls cell division at three levels, viz., DNA repair, cell cycle, and apoptosis any mutation in it can lead to mutation. Hence, Shen and coworkers (Shen et al. 2018) developed a palindromic molecular beacon (PMB; DNA sequence with C-rich region, nicking site, target recognition sequence, and palindromic sequence)based colorimetric assay using the integration of SDA (strand displacement

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Fig. 8.9 Schematic representation of colorimetric assay for p53 gene based on palindromic molecule beacon-based cascade amplification. (Adapted from Shen et al. 2018)

amplification) and HRP-mimicking DNAzyme amplification for the quantitative detection of p53 gene level (Fig. 8.9). The PMB hairpin in presence of target sequence, opens hybridize with each other via palindromic sequence as well as target via target recognition sequence and initiate polymerization displacement by polymerase, leading to peeling off from the target and recycling. The amplification product formed is nicked in the presence of nickase at the nicking site, generating a new site for replication and displacement. The nicked fragment formed, in the the conversion of 2,2′-azino-bis presence of hemin, catalyzes (3-ethylbenzothiazoline)-6-sulfonate disodium salt (ABTS) by H2O2, to color the product. Hence, the presence of a target can be detected by a visible change in color. In another study, Li et al. (2014) reported the development of a highly sensitive detection system for cell membrane protein tyrosine kinase-7 (biomarker for T-cell acute lymphoblastic leukemia) on single living cells by aptamer and nicking enzyme-assisted fluorescence signal amplification in microfluidic droplets. Tong et al. (2009) and Zhu et al. (2006) have reported the usefulness of gold nanorods and nanotemplate-engineered nanoparticles containing gadolinium, respectively, for enhanced in vitro and in vivo imaging. The gadolinium nanoparticles being hemocompatible and enzymatically metabolized, induces relativities in bulk water signal has been suggested to be useful as MRI tumor contrast enhancement agent. It enables the two-point characterization of cells and allows differentiation between premalignant cells and differentiated epithelial cells and normal cells, in vitro (Kannan et al. 2018). A comparative list of various enzymes and transduction platforms used for the detection of different types of cancer was mentioned in Table 8.5. Most of the enzyme-based sensors for cancer diagnosis were indirect assay where enzymatic

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Table 8.5 Various enzyme-based cancer sensors and their sensing parameters Disorder Breast cancer, ovarian cancer (Pakchin et al. 2018) Breast cancer, gastric cancer (Gohring et al. 2010)

Strategy/type of biosensor Chitosan-gold nanoparticle/ multi-walled carbon nanotube/graphene oxide (CSAuNP/MWCNT/GO) Magnetic beads modified with enzymes, affibody, and optofluidic ring resonatorbased biosensor

Breast cancer, colorectal cancer (Shen et al. 2018)

PMB probe-DNAzymebased colorimetric sandwich assay

Breast cancer, ovarian cancer (Yang et al. 2017) T-cell acute lymphoblastic leukemia (Li et al. 2014)

Enzyme-based 3D DNA detection nanostructured reporter probe, colorimetric assay Fluorescence based

Biomarker CA-125

Human epidermal receptor (HER-2)/ neu/cerbB2 p53

BRCA1

PTK7

Enzyme used in assay Lactate oxidase

Magnetic beads modified with enzymes and affibody HRPmimicking DNAzyme, polymerase, nickase HRP

Nicking enzyme

LOD 0.002 μ/ mL

13–100 ng/ mL

10 pM

10 fM

0.4 nM

products or by-products are used for signal detection. Major advantages associated with enzyme-based signal amplification associated with turnover rate of enzymes, however turnout time for assay is longer compared to direct assay.

8.5

Cardiovascular Diseases

Cardiovascular diseases (CVDs) involve disorders of the heart and blood vessels including coronary heart disease (disease of blood vessels supplying blood to heart muscles), cerebrovascular disease (disease of blood vessels supplying blood to the brain), peripheral arterial disease (disease of blood vessels supplying blood to limbs), rheumatic heart disease (damage of heart valves and muscles due to rheumatic fever), congenital heart disease (malformations of the heart from birth), and deep vein thrombosis and pulmonary embolism (blood clots in leg veins that dislodge and move to the lungs and heart). Some common types of CVDs are as follows. • Coronary heart disease: Also called coronary artery disease, it occurs due to damage to blood vessels supplying blood to the heart. The coronary arteries become narrow due to atherosclerosis and deposition of fatty substances like cholesterol or other cellular waste products in the damaged artery, leading to

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blockage or reduced blood flow in the artery. Such blockage depending upon its severity may result in angina and heart attack. Cerebrovascular disease: It involves various conditions, involving permanent or temporary damage to the brain due to ischemia (lack of sufficient blood flow) or bleeding from one or more cerebral blood vessels. The reason for such damage could be stroke, stenosis (narrowing of blood vessels), thrombosis (clot formation), embolism (blockage), aneurysms (enlargement of artery to weakness in arterial wall), or hemorrhage (blood vessel rupture). The cerebrovascular problems are diagnosed by cerebral angiography, carotid ultrasound, CAT scan, Doppler ultrasound, electroencephalogram, lumber puncture, magnetic resonance imaging, magnetic resonance angiogram, etc. Peripheral arterial disease: It is a restricted flow in blood vessels supplying or collecting blood to and from different regions of body other than brain and heart, due to deposition of cholesterol (atherosclerosis) or blood clots due to injury. The symptoms include hair loss in limbs, pain/numbness in limbs, sores or ulcers on legs and feet, etc. The peripheral arterial disease is diagnosed by ankle-brachial index, ultrasound scan, angiography, and blood tests, computed tomographic angiography, and magnetic resonance angiography. Rheumatic heart disease: It is caused as a result of rheumatic fever. Rheumatic fever is an inflammatory disease of the connective tissue of the heart, brain, joints, and skin. As a result of inflammation, the heart valves become weak, making it harder for the heart to function normally, resulting in heart failure. Congenital heart disease: It is basically a defect or abnormality rather than a disease. It develops when the heart or blood vessels near the heart do not develop normally before birth. The various types of congenital defects include aortic valve stenosis (AVS), atrial septal defect (ASD), coarctation of the aorta (CoA), complete atrioventricular canal defect (CAVC), dextro-transposition of the great arteries, Ebstein’s anomaly, hypoplastic left heart syndrome, single ventricle defects, tricuspid atresia, ventricular septal defect (VSD), etc. Deep vein thrombosis: It involves the formation of blood clot in the deep veins of commonly leg or pelvis. The clot formation could be because of various reasons including decreased blood flow rate, increased tendency to form blood clot, and injury to blood vessel wall. The life-threatening outcome of deep vein thrombosis is the potential of the clot to dislodge from the vein in the leg/pelvis and travel via the right side of heart arteries to the blood vessels of the lungs and disrupt blood supply. Such a condition is called pulmonary embolism.

8.5.1

Cardiac Biomarkers

Table 8.6 enlists the various CVD biomarkers. (a) Cardiac troponin (cTn): It is a complex protein, composed of three globular contractile regulatory proteins, present at regular intervals in striated muscle thin filament that prevents contraction by inhibiting actin-myosin interaction. The

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Table 8.6 List of common biomarkers for the detection and diagnosis of CVDs S. no. 1

Biomarker Cardiac troponin

Condition Acute myocardial infarction (AMI)

2

High-sensitivity cardiac troponin

AMI

3

Heart-type fatty acid-binding protein

AMI and acute coronary syndrome (ACS)

4

High-sensitivity C-reactive protein

Cardiovascular disease risk assessment

5

Growth differentiation factor 15

ACS, CAD, HF

6

Fibrinogen

7

Galectin-3 (Gal3)

HF

8

miRNAs

MI

Features Advantage: Cardiac troponins are sensitive and specific biomarkers for cardiomyocyte injury than creatine kinase and myoglobin Disadvantage: Delayed increase in circulating levels and requires serial sampling for 6–9 h Advantage: Increase the accuracy of AMI diagnosis Disadvantage: Associated with other health conditions and disorders. Capability to quantify its level in at least 50% of healthy individuals Advantage: H-FABP are useful indicators in addition to cTn for high-risk patients for the early diagnosis of ACS Disadvantage: Released in high amount only 7–36 h before a serious heart condition Advantage: HsCRP is positively correlated to cardiovascular disease and can detect low levels of CRP for accurate and early risk evaluation Disadvantage: Not very specific with heart condition, high expression in body also associated with inflammation and cancer Advantage: It is a strong predictor of all cachexia, cardiovascular diseases, and all-cause death Disadvantage: Not very specific with only heart condition associated with renal failure and cancer Advantage: Studies suggest increased fibrinogen levels are linked to increased risk of CVD Disadvantage: Prone to false-positive mean levels of fibrinogen, 3 to 6 months after hospitalization Advantage: It is an FDA 2010 approved risk stratification marker of HF Disadvantage: Lack of specificity, associated with tumor Advantage: Several miRNAs have been found to increase after myocardial infarction, but their use in diagnosis is not very common Disadvantage: Associated with complex detection process

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development of assay for high-sensitivity cTn helps to diagnose ongoing myocardial injury in stable patients, leading to accurate AMI detection. Fatty acid-binding proteins (FABP) are transport proteins involved in the transport of fatty acids through membranes and are tissue specific, viz., liver-type FABP, intestinal-type FABP, heart-type FABP, etc. Heart-type FABP (H-FABP) are involved in myocardial fatty acid metabolism and increase in conditions of acute ischemic strokes and intense exercise. H-FABP is released into the cytoplasm in the early stages of acute myocardial infarction. Fatty acid-binding protein: Cytoplasmic FABP are a family of transport proteins that carry out the transport of fatty acids through the membranes. FABP, being tissue specific, is of various types, which include liver-type, intestinal-type, brain-type, and heart-type FABP (H-FABP). H-FABP is a low molecular weight protein constituting 132 amino acids and has an important role in myocardial fatty acid metabolism. It is present in high concentrations in cardiomyocytes and in small quantities in the brain, kidney, and skeletal tissue. The levels of H-FABP can increase under conditions like acute ischemic strokes and intense exercise. H-FABP is rapidly released into the cytosol early in AMI. C-reactive protein (CRP): It is an innate immune response protein belongs to the pentraxin family and is a nonspecific inflammation marker. Several studies have shown a correlation between CRP and cardiovascular disease. HsCRP detects lower levels of CRP, viz., 100 parasites/μL are present (0.002% parasitemia) (Shiff et al. 1993). The ParaSight®-F test used the dipstick approach where gold nanoparticles or dye-conjugated monoclonal antibody against HRP II is used to capture the HRP II from the peripheral blood. The immunochromatography technique relies on the migration of liquid across the nitrocellulose membrane. On the nitrocellulose membrane, a second anti-HRP II monoclonal antibody is applied which acts as the immobile phase. The gold nanoparticles or dye-conjugated antibody reacts with the parasite antigen in the peripheral blood to form antigen-antibody complex in the mobile phase. The antigen-antibody complex migrates in the mobile phase along the strip enabling the labelled antigen to be captured by the monoclonal antibody of the immobile phase and produces a visible colored line. Few drawbacks of the primitive immunochromatographic RDT was that it required many manual steps; however, the later kits were simplified and required to only add the anticoagulated blood, and everything was packaged in the cassette format. Most of the RDTs in the market are based on HRP II as they are more sensitive than the RDTs based on LDH with sensitivity as high as 96.3% vs. 82.6%, respectively (Li et al. 2017). There has been an increasing requirement for the highsensitivity detection of malaria by RDT (50–200 parasites/μL) because of high asymptomatic cases which contribute to transmission (Slater et al. 2019). Recently, the new Alere™ Ultra-sensitive Malaria Ag P. falciparum RDT (uRDT) was developed which reported higher sensitivity than the current RDTs (Yeung et al. 2020).

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Although RDTs have been used to detect malaria in the past few decades, there have been major limitations in terms of stability and performance issues in terms of both sensitivity and specificity while detecting asymptomatic cases (Jain et al. 2014). To bridge these gaps and limitations, other diagnostic technologies with improved performance are required. The following section will discuss on these advanced sensors that have the capabilities to overcome the limitations of RDTs.

9.2.2.2 Advanced Biosensors Most advanced HRP II-based malaria biosensors developed are electrochemical immunosensors. Electrochemical immunosensors harness the property of specificity of the antigens to antibodies to form a stable complex that gives a signal change of either current (amperometric), voltage (potentiometric), resistance, or impedance (conductimetric and impedance spectroscopy). Electrochemical immunosensors serve some great advantages such as easy miniaturization, fast response time, low detection limits, and easy surface modification and can be used to study a vast array of analytes. The first disposable amperometric HRP II-based immunosensor was developed using disposable screen-printed electrodes (SPEs). The SPEs were modified with multiwall carbon nanotubes (MWCNTs) and Au nanoparticles (AuNPs). A sandwich enzyme-linked immunosorbent assay format was employed for the biosensor with alkaline phosphatase (ALP)-conjugated antibodies. Amperometric measurements were applied using ALP hydrolysis of 1-naphthyl phosphate that yielded results with a detection limit of 8.0 ng/mL, a sensitivity of 96%, and a specificity of 94% (Sharma et al. 2008). The same authors further enhanced the amperometric immunosensors for the detection of early stages of malaria and at low parasitemia. They modified the SPEs with alumina sol-gel (Al2O3), AuNP and antiHRP II antibody detected HRP II antigen with a sensitivity of 92% and a specificity of 90% (Sharma et al. 2010). The same group developed another immunosensor with a different approach. They developed a piezoelectric immunosensor where they added mixed self-assembled monolayers (SAMs) of thioctic acid and 1-dodecanethiol that were formed on the gold surface of quartz crystal. The immunosensor detected HRP II in the linear range of 15–60 ng/mL with a detection limit of 12 ng/mL. It was found that even after 14 days of storage, 50% of the activity still remained (Sharma et al. 2011). Apart from AuNPs, other materials such as magnetic nanoparticles (MNPs) have been also employed to develop immunosensors for the highly sensitive detection of HRP II. The immunosensor used both magnetic micro- and nanoparticles and a sandwich assay format using a secondary monoclonal antibody labelled with the horseradish peroxidase (HRP) enzyme. Both optical and electrochemical detection methods were studied and compared. The electrochemical magneto-immunosensor coupled with magnetic nanoparticles had shown better analytical performance in terms of detection limit (0.36 ng mL-1) (de Souza Castilho et al. 2011). Recently, an amperometric immunosensor was developed using the sandwich ELISA assay format with HRP as the enzyme label. The electrochemical signal was generated using a 3,3′,5,5′-tetramethylbenzidine dihydrochloride (TMB)/H2O2 system. The sensor achieved a limit of detection (LOD) of 2.14 ng mL-1 in buffer

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samples and 2.95 ng mL-1 in 100% spiked serum samples. The assay signal was further amplified using AuNPs conjugated detection antibody-enzyme, and a detection limit of 36 pg mL-1 was achieved in buffer samples and 40 pg mL-1 in serum samples (Hemben et al. 2017). Another powerful technique used for HRP II detection was electrochemical impedance spectroscopy which used self-assembled monolayer of mercaptopropylphosphonic acid and was modified with copper-doped zinc oxide nanofiber interface for detection. The impedimetric detection showed a high sensitivity (28.5 kΩ/(gm/mL)/cm2) in the detection ranges of 10 attogram/mL–10μg/mL and a detection limit of 6 attogram/mL. In addition, the proposed biosensor is highly selective to targeted HRP II protein with a relative standard deviation of 1.9% in the presence of various interferences of non-specific molecules (Paul et al. 2016). Optical- and colorimetric-based systems reported till date are mostly based on ELISA and lateral flow immunoassays. ELISA-based detection sensitivity is high and comparable to electrochemical immunosensors, whereas colorimetric immunoassays suffer from lower sensitivity due to the coffee ring effect which can lead to non-homogeneous color development (Kakoti et al. 2015). The colorimetric methods on the other hand are considered better from the point-of-care (PoC) viewpoint as they provide equipment-free readout with naked eye detection with low-skilled technician. Gold nanoparticles conjugated with Ni(II)nitrilotriacetic acid (NTA) has been also used to detect HRP II. HRP II molecules are expected to bind and localize multiple nanoparticles due to multiple binding sites of nickel, thus developing higher signal. Swartz et al. developed sensors based on Ni(II)NTAfunctionalized gold, silver, and magnetic nanoparticles using the Ni(II)NTA chelation chemistry (Swartz et al. 2011). The same authors improved the optical assay sensitivity and platform stability by using negatively charged Peg4-thiol as spacer ligand to obtain low nanomolar limits (6.6–7.4 nM) of HRP II concentration and maintain excellent stability at 37 °C when stored for 4 weeks (Gulka et al. 2015). A unique detection system inspired by the coffee ring phenomenon using Ni(II)NTA gold-plated polystyrene microspheres (AuPSs) and Ni(II)NTA-functionalized glass was also developed by the same group (Gulka et al. 2014). The HRP II protein reacted with Ni(II)NTA-functionalized particles and was allowed to be dropped on a Ni(II)NTA-functionalized glass surface and then allowed to dry. As the drop of the reaction mix evaporates due to radial diffusion of the particle-protein conjugates, rings of aggregated Ni(II)NTA AuPSs become visible which gets prominent with higher concentration of analyte. The metal ion binding property of HRP II was exploited and metal-based phosphorescent probes such as the cyclometalated iridium complexes that can selectively bind to histidine moiety of HRP II to give stabile and efficient emission (Davis et al. 2015). The limit of detection using the probe was found to be 12.8 nM in solution, and when the protein was immobilized on the surface of a 50μm magnetic agarose particle, the limit of detection was 14.5 nM. Another label-free method of detection developed by our group was using Ni (II)NTA chelation chemistry and a complexometric indicator dye murexide (Chakma et al. 2016). The dye has binding affinity for both histidine and Ni2+, based on which indicator displacement assay was developed. HRP II competes with

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the dye due to its large number of histidine moieties, displacing Ni2+ from the murexide-Ni2+complex, thus regenerating the original color of the dye. The assay was performed both spectrophotometrically in the solution and optically on paperbased platform. The limit of detection calculated for spectrophotometric assay was 7.62 nM and for paper-based platform was 30 nM without any interfering signals from serum proteins. Although there has been extensive research and development of ultrasensitive sensors to detect HRP II, there are still big gaps that need to be filled in order to bring these sensors to the field, most importantly cost, stability, and ease of use. This can be done by performing more clinical trials that will help to translate the technology to the field.

9.3

Lactate Dehydrogenase (LDH)

9.3.1

Genetic and Protein Structure

Lactate dehydrogenase (LDH) is a terminal enzyme in the glycolytic pathway of Plasmodium, catalyzing the interconversion of pyruvate and NADH to lactate and NAD+. The Plasmodium parasite is a voracious scavenger of blood glucose. Infestation of the RBC by this parasite increases the RBC glucose consumption by up to 100-fold. This glucose acts as the principal source of ATP generation via anaerobic respiration, for the parasite during the intraerythrocytic stages. In this process, the NAD+ is regenerated by the conversion of pyruvate to lactate, while the mitochondria contribute minimally to the ATP pool (Fry et al. 1990). The absence of F0 α- and β-subunits of the mitochondrial F0–F1 ATP synthase further confirms the absence of mitochondrial role in energy generation to a certain degree. Researchers believe that the absence of mitochondrial involvement in energy generation cannot however be ascertained due to a reason which is twofold: (Chanda et al. 2009) parts of the genome sequence are still not known, and (Hume et al. 2008) the A+T-rich genome of the parasite causes difficulty in annotating enzymes (Olszewski and Llinás 2011). Since the parasite depends heavily on glycolysis for ATP generation, enzymes involved in this pathway are highly overexpressed (Roth Jr. 1990). Molecular proof of this was found when the P. falciparum LDH (PfLDH) RNA expression levels were studied. The PfLDH mRNA expression gradually increases, with the peak expression being at 24–30 h in the intraerythrocytic cycle. This expression declines to zero in the schizont stage. As a result, the PfLDH enzyme activity was also found to peak, at around the same time (Pfaller et al. 1982). In vitro, the parasite LDH can be cloned as a monomer, which assembles into its native tetrameric configuration in solution (Fig. 9.1). These solutions are primarily homogeneous with the major fraction corresponding to the homotetramer (136 kDa). Although some minor heterogeneity resulting from fractions that roughly correspond to the monomeric (34 kDa), dimeric (68 kDa), and octameric (272 kDa) forms of the enzyme may be present as well, (Jain et al. 2016a) each monomer of the enzyme

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Fig. 9.1 Crystal structure of Plasmodium vivax lactate dehydrogenase complexed to APADH, adapted from PDB file 2AA3, solved to a resolution of 2.05 Å. The structure shows the presence of four (A1–A4) identical monomer chains (colored differently for clarity). One molecule of APADH (illustrated as blue spheres) binds to each monomer chain, in the Rossmann fold (Pfaller et al. 1982)

consists of two domains, namely, (Chanda et al. 2009) the larger domain, containing the cofactor (NADH) binding Rossmann fold, and (Hume et al. 2008) the smaller domain containing the catalytic residues (His 195, Asp 168, Arg 171). These residues are conserved across LDHs of all Plasmodium species except the LDH of P. knowlesi, which lacks His 195. The active site of the enzyme is located between these two domains. Each monomer of the Plasmodium LDH (pLDH) enzyme can bind one cofactor molecule, totalling to four NADH per pLDH enzyme. Being a homotetramer, each of the four cofactors occupies identical positions in each monomer (Brown et al. 2004). In recent years, pLDH has been a subject of increasing interest as a valuable biomarker for the detection of malaria. The viability of pLDH as a malaria biomarker stems from some significant structural and kinetic differences it possesses, from its mammalian counterparts that ascertain the much desired selectivity, and from its high signal-to-noise ratios in a sensor. PvLDH (Plasmodium vivax LDH) and PfLDH, enzymes of the two malarial parasites causing serious disease, share merely 26% and 29% sequence identity, respectively, with human LDH A (hLDH A). The structural difference between pLDH and human LDH (hLDH) appears in the form of a five amino acid residue insertion (“DKEWN” corresponding to amino acids D, aspartic acid; E, glutamic acid; K, lysine; W, tryptophan; and N, asparagine) in the active site loop of pLDH which is absent in hLDH. This stretch of amino acids closes down over the active site during catalysis and also causes a displacement of ~1 Å of the nicotinamide moiety of the NADH cofactor (Dunn et al. 1996; Winter et al. 2003). The DKEWN insertion has been previously exploited as a common diagnostic epitope for pLDHs by Hurdayal et al., owing to the fact that this insertion is

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conserved across all five Plasmodium species. Antibodies generated against this insertion have the potential to selectively detect pLDH from human LDH isoforms (Hurdayal et al. 2010; Kaushal and Kaushal 2014). The DKEWN moiety was later also discovered in the LDH I and II of T. gondii (Yang and Parmley 1995, 1997). However, this feature was absent in few other apicomplexan parasites like Cryptosporidium parvum, which causes cryptosporidiosis, a parasitic infection of the mammalian intestinal tract. pLDH differs kinetically from hLDH in (Chanda et al. 2009) lacking substrate inhibition in the presence of excess substrate pyruvate (Sessions et al. 1997) and (Hume et al. 2008) showing higher affinity to the synthetic cofactor APAD+ (3-acetylpyridine adenine dinucleotide) (Swartz et al. 2011; Chaikuad et al. 2005) as compared to the natural cofactor NAD+. A single amino acid substitution in pLDH (Ser163Leu) confers reduced substrate inhibition in this enzyme. This single amino acid substitution has also been exploited as a general method to reduce substrate inhibition in other L-lactate dehydrogenase enzymes (Hewitt et al. 1999). Alternatively, the Ser 163 in hLDH interacts with the amine group of NADH via hydrogen bond. This interaction leads to the slow release of the reduced cofactor from the active site due to the formation of a covalent adduct with pyruvate, ultimately leading to substrate inhibition by pyruvate. However, the mechanism for the lower substrate inhibition has also been stated to be the weaker binding of pyruvate to enzyme-cofactor complex rather than slower release of NAD+ (Gomez et al. 1997). APAD+ is a synthetic NAD+ analogue which has a methyl group replacing the nicotinamide amide nitrogen (Fig. 9.2a). The structural basis of this preference may be the presence of a number of substitutions in the cofactor-binding groove of pLDHs that distinguish them from human LDHs. When the active site residues of PvLDH are overlaid with those of hLDH A, it becomes clear that the cofactor is displaced within the binding pocket, relative to its placement in human LDH enzymes (Fig. 9.3). This displacement is observed in the nicotinamide moiety, which is shifted by about 1 Å relative to its position in the hLDH A structure. A similar displacement was also seen for the PfLDH enzyme. In PfLDH-APADH complexes, there is a displacement (0.45 Å) both of the acetyl-pyridine ring of APADH and of the imidazole ring of His 195 in the APADH structure when compared to the NADH structure. Similarly for PvLDH-APADH complexes, there is a displacement of 0.3 Å of both the acetyl-pyridine ring of APADH and the imidazole ring of His 195 when compared to the NADH structure (Fig. 9.2b, c). Kinetic increase in entropy on APAD+ binding, leading to a change in the rate of active site movement, and a higher oxidation potential of APAD+ than NAD+, leading to faster hydride transfer to APAD+, are ascribed as few of the reasons for this cofactor preference by pLDHs (Pfaller et al. 1982). The presence of a long substrate specificity loop in pLDH renders this enzyme a unique substrate specificity, not seen in other dehydrogenases. The enzyme shows higher catalytic efficiency with substrates having lesser methylene groups, as seen when pyruvate is replaced with α-ketobutyrate as a substrate. pLDH can be distinguished from the LDH of T. gondii in showing absence of any activity with

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Fig. 9.2 Placement of APADH and NADH in Plasmodium LDH enzymes. (a) Scheme of the chemical composition of the nicotinamide ring of NADH and the equivalent acetyl-pyridine ring in APADH. The nicotinamide amine group is replaced by an acetyl group in APADH. (b) Overlay of PfLDH-APADH (off-white) and PfLDH-NADH (orange) structures. (c) Overlay of PvLDHAPADH (blue) and PvLDH-NADH (yellow) structures (Pfaller et al. 1982)

phenylpyruvate as a substrate (Shoemark et al. 2007). Although LDH from P. falciparum and T. gondii have very similar structures, the presence of an additional loop insertion of two residues and several changes in the active site of LDH

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Fig. 9.3 Cofactor placement in Plasmodium and human LDH enzymes. (a) Overlay of NADH from PvLDH-NADH (blue) and PfLDH-NADH (yellow) complexes with catalytic residues shown. Residue 54 is an isoleucine in PvLDH and a valine in PfLDH. (b) Overlay of NADH from PvLDHNADH (blue) and hLDH A-NADH (green) complexes with catalytic residues shown. (c) Detail of binding interactions between the nicotinamide group, position 163, and surrounding residues. Left panel (green) shows the arrangement for human (and all non-apicomplexan) LDHs; right panel (gold) shows the same region from Plasmodium LDH structures. Hydrogen bonds are shown as dashed lines, and the conserved bound water molecule is shown as a red sphere (Pfaller et al. 1982)

from T. gondii enable it to catalyze phenylpyruvate (Kavanagh et al. 2004; Dando et al. 2001). In conclusion, pLDH is an attractive target for developing malaria biosensor because of several important attributes (Chanda et al. 2009). It is highly overexpressed in the parasite, making it easy to detect in the blood of malaria patients (Hume et al. 2008). It has unique structural and kinetic features which can be targeted for the development of a selective biosensor (Msellem et al. 2009). It can be used for monitoring response to therapy in malaria patients, as its clearance rates closely correspond to that of the parasite. In a promising study, pfLDH concentrations shows to have declined by 99.7% 2 days after treatment began (Moody 2002). pLDH shows a remarkably conserved sequence, with little to no gene polymorphism. A recent study showed that L1a was the major allele for PfLDH, representing between 80% and 100% isolates in P. falciparum populations, from various geographical locations (Simpalipan et al. 2018). These attributes make pLDH a valuable target for developing a selective and sensitive biosensor for the detection of malaria.

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Types of LDH-Based Detection Schemes

The last decade has seen an increased research output in the field of pLDH-based malaria sensors. Few of the salient efforts in this area are highlighted in Table 9.1. On close examination, we find that the pLDH-based malarial biosensor research is more inclined toward colorimetric sensors. The reason may be attributed to some advantages of this biosensing platform such as better scope of converting them to portable devices, cheaper infrastructure requirements, and small sample volume needed for the analysis. From the sensitivity point of view, few nanomaterialbased sensors for pLDH showed the lowest detection limits in the picomolar range, which is a significant improvement over the conventional malaria detection methods. Notably, a higher sensitivity is an important requirement especially for the diagnosis of asymptomatic submicroscopic infections. Additionally, the selectivity to clearly differentiate different Plasmodium species is also a highly desirable performance factor for malarial diagnostics. While PoC-based sensors are cheaper and portable, the sensitivity and selectivity functions so far served by them are not adequate for the detection of submicroscopic infections and differentiation of Plasmodium species. An effort put forth by Dirkzwager et al. involved the capture of PfLDH by surface-bound DNA aptamer. Colorimetric detection of the target PfLDH was then achieved by exploiting the enzyme activity of PfLDH, on a colored substrate (nitrotetrazolium dye). Since this approach incorporates the functional activity of PfLDH in a secondary enzymatic reaction for generating the signal, it considerably reduces the number of false-positive signals, which may occur on non-specific binding of serum proteins to antibodies (Dirkzwager et al. 2015). Recently, there has been a great push toward the development of PoC sensors for malaria diagnosis with emphasis on pLDH. Therefore, further improvements by Dirkzwager et al. involved the detection of both PfLDH and PvLDH using specific aptamers (Cheung et al. 2017) and development of two point-of-care platforms: well based and syringe based (Fig. 9.4a) (Dirkzwager et al. 2016). Aptamers have been seen to widely influence research in the field of pLDH-based sensors. While a majority of sensors involved the use of DNA aptamers directed against pLDH coupled with nanolabels such as AuNP or silver nanoclusters, molecular modifications of the aptamer itself showed promising results (Fig. 9.4b) (Shiu et al. 2017). In an innovative report, 12 aptamers that recognize PfLDH were integrated into a rectangular DNA origami. The captured PfLDH was shown to retain enzymatic activity, and protein-aptamer binding was observed dynamically using high-speed AFM (Godonoga et al. 2016). Relatively few reports on electrochemical pLDH sensors exist, though all show sensitive subnanomolar to femtomolar detection of pLDH. The electrochemical detection of pLDH has so far been quite straightforward, involving the covalent immobilization of DNA aptamer on gold electrode, followed by impedance measurements, to generate a response curve (Miranda et al. 2017; Lee et al. 2012). Non-covalent attachment of DNA aptamer to GCE was achieved by Jain et al.

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Table 9.1 List of pLDH-based malaria sensors Sensor DNA-scaffolded silver nanoclusters with a DNA aptamer DNA origami assembly using a DNA aptamer Adenosine monophosphate protected goldsilver bimetallic nanoclusters Au-AGNC@AMP used as fluorescent probes Split DNA aptamer integrated with G-quadruplex tweezers DNA aptamers integrated with a DNA origami nanobox DNA probes complementary to 26-mer ssDNAs of ldh gene of Plasmodium Sandwich immunoassay on gold screenprinted electrode and HRP-labelled antiPfLDH antibody coupled to AuNP as reporter probe DNA aptamer covalently bound to gold electrode DNA aptamer covalently bound to gold electrode Anti-PfLDH-magnetic bead (for separation) followed by colorimetric enzyme assay Salt or cationic surfactant-based aggregation of non-covalently attached ssDNA aptamer to AuNP DNA aptamer-graphene oxide-glassy carbon electrode Hairpin stabilized fluorescent silver nanoclusters Cationic polymer-mediated aggregation of AuNP in the presence of DNA aptamer

Surface-bound aptamer captures target (PfLDH) followed by colorimetric enzyme assay Surface-bound aptamer captures target (PfLDH and PvLDH) followed by colorimetric enzyme assay Aptamer-decorated microbeads capture target (PfLDH) followed by colorimetric enzyme assay, developed on two point-ofcare formats (well based and syringe based)

LOD 0.2 nM (PfLDH) 500 nM (PfLDH) 0.1 nM (PvLDH)

Sensor platform Fluorescence

Not reported Not reported 0.25 pmol/μ L (target DNA) 19 pg/mL (PfLDH)

Colorimetric

AFM imaging Fluorescence

Fluorescence (FRET) High-resolution melting

Ref Wang et al. (2017) Godonoga et al. (2016) Zhang et al. (2020) Shiu et al. (2017) Tang et al. (2018) Jain et al. (2017a)

Electrochemical

Hemben et al. (2018)

0.84 pM (PfLDH) 1 pM (PfLDH) 21.1 parasites/μL 281 pM (PfLDH)

Electrochemical

Miranda et al. (2017) Lee et al. (2012) Markwalter et al. (2016) Jain et al. (2016a)

0.5 fM

Electrochemical

Not reported 8.3 pM (PvLDH) 10.3 pM (PfLDH) 4.9 ng/mL (PfLDH)

Fluorescence

Electrochemical Colorimetric Colorimetric

Colorimetric

Jain et al. (2017a) Jain et al. (2017b) Jeon et al. (2013)

Colorimetric

Dirkzwager et al. (2015)

Not reported

Colorimetric

Cheung et al. (2017)

5 ng/mL

Colorimetric

Dirkzwager et al. (2016)

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Fig. 9.4 (a) Aptamer decorated microbeads for the capture of PfLDH (Dirkzwager et al. 2016). (b) Detection of PfLDH using a split aptamer nanotweezer (Shiu et al. 2017). In both (a) and (b), detection of target is achieved in a colorimetric assay exploiting the enzyme activity of PfLDH

(2016b), by exploiting the hydrophobic interactions and π-π stacking between DNA aptamer and graphene oxide.

9.4

Other Promising Malaria Biomarkers

9.4.1

Glutamate Dehydrogenase

Glutamate dehydrogenases (GDHs) are ubiquitous enzymes that are generally involved in ammonium assimilation (NADP-dependent GDHs) or glutamate catabolism (NAD-dependent GDHs). P. falciparum expresses three GDH isozymes. PfGDH1 is a NADP-dependent glutamate dehydrogenase which is a homohexamer with a subunit of Mr 49,500 (Wagner et al. 1998). It plays an important role in the parasite’s redox metabolism (Roth Jr. 1990). There are few differences between the parasite and human GDH which makes it a potential target biomarker. The differences are the following: Firstly, the parasite GDH possesses a unique N

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terminal residue extension which is not found in the mature human enzyme and is present throughout the intraerythrocytic cycle. Secondly, GDHs are absent in the host RBC making them a potent biomarker (Wagner et al. 1998). Initially, PfGDH1 was used to detect the presence of P. falciparum using Western blotting (RodríguezAcosta et al. 1998). GDH-based sensors using monoclonal antibodies in combination with colloidal gold was develop an immunochromatographic assay for the diagnosis of P. falciparum. This assay showed a sensitivity and specificity of 86.6% and 96.4%, respectively (Li et al. 2005). In the last few years, aptamers against PfGDH1 were screened and found to be a good alternative to monoclonal antibodies. Based on which, a label-free capacitive aptasensor was constructed by grafting thiolated ssDNA aptamer on a gold electrode (Singh et al. 2018). The sensor showed a LoD of 0.77 pM in serum with dynamic range 100 fM–100 nM. Subsequently, the authors integrated the process into an extended-gate field-effect transistor (EgFET) as it enables for sensitive and simple electrochemical measurements without requiring a typical redox marker. The NG3 aptamers were immobilized on interdigitated gold microelectrodes (IDμE) and connected to the FET to construct a sensitive and stable miniaturized aptaFET biosensor (Singh et al. 2019). The aptaFET biosensor showed a detection range of 100 fM–10 nM which was obtained with LoDs in buffer and serum being 16.7 pM and 48.6 pM, respectively. The FET-based potentiometric sensor was highly selective in the presence of interfering agents making it suitable to be used in real samples.

9.4.1.1 Aldolase Aldolase is a key enzyme in the glycolytic pathway of the parasite. It catalyzes the cleavage of fructose 1,6-bisphosphate into glyceraldehyde 3-phosphate and dihydroxyacetone phosphate (Srivastava et al. 1990). The enzyme is a homotetrameric protein with each subunit of approximately 40 kDa (Döbeli et al. 1990). Aldolase is localized in the cytoplasm of the parasite as an active and soluble form and is also found to be associated with the membrane fraction as an insoluble form. The enzyme has high degree of sequence diversity from the host and thus has the potential as a drug target as well as a biomarker for malaria diagnostics. Most aldolase-based detection systems are immunochromatographic assays. Many reports have shown poor sensitivity of aldolase RDTs which encouraged studying more its genetic diversity. Moreover, P. falciparum and P. vivax aldolase genes are highly conserved, thus making it a poor marker to differentiate between the two species.

9.5

Conclusion

A thorough discussion on the structural and functional roles of the two important malaria biomarkers has been done here. This information equips us with knowledge, crucial for developing an understanding of the various pros and cons of each of these biomarkers and its informed use in a malaria biosensor. Detection schemes such as electrochemical, colorimetric, and fluorescence based have been discussed, in both

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assay and point-of-care formats. Recent advancements in aptamer-based point-ofcare sensors have paved the way for a reliable and portable malaria sensor in the near future.

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Wang W-X, Cheung Y-W, Dirkzwager RM, Wong W-C, Tanner JA, Li H-W, Yuqing W (2017) Specific and sensitive detection of Plasmodium falciparum lactate dehydrogenase by DNA-scaffolded silver nanoclusters combined with an aptamer. Analyst 142:800–807 Winter VJ, Cameron A, Tranter R, Sessions RB, Brady RL (2003) Crystal structure of Plasmodium berghei lactate dehydrogenase indicates the unique structural differences of these enzymes are shared across the Plasmodium genus. Mol Biochem Parasitol 131(1):1–10 Yang S, Parmley SF (1995) A bradyzoite stage-specifically expressed gene of Toxoplasma gondii encodes a polypeptide homologous to lactate dehydrogenase. Mol Biochem Parasitol 73(1–2): 291–294 Yang S, Parmley SF (1997) Toxoplasma gondii expresses two distinct lactate dehydrogenase homologous genes during its life cycle in intermediate hosts. Gene 184(1):1–12 Yeung S, McGregor D, James N et al (2020) Performance of ultrasensitive rapid diagnostic tests for detecting asymptomatic Plasmodium falciparum. Am J Trop Med Hyg 102(2):307–309 Zhang C-X, Tanner JA, Li H-W, Wu Y (2020) A novel fluorescence probe of Plasmodium vivax lactate dehydrogenase based on adenosine monophosphate protected bimetallic nanoclusters. Talanta 213:120850

Enzymatic Biosensor Platforms for Infectious Disease Diagnosis: Focus on Tuberculosis and Neglected Tropical Diseases

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Satakshi Hazra, Munna Singh Thakur, and Sanjukta Patra

10.1

Introduction

10.1.1 Overview Biosensors have transformed the concept behind the improved diagnosis of various infectious diseases in the last few decades, ushering in the development of a number of novel platforms for the same. A number of biomarkers for infectious diseases like TB and NTDs are now effectively detected on these biosensing platforms in no time. Keeping in mind the public health concerns to thwart the spread of debilitating infectious diseases, simple and rapid diagnoses are considered crucial as part of effective control programs. Thus, biosensors are inevitable in this realm of clinical diagnostics where several applications including robust, cost-effective, specific, and hassle-free detection of biomarkers (analytes) are achievable. The building blocks of a biosensor must include one biorecognition element (bioreceptor) and one transducer. The bioreceptor element reacts with the analyte in the sample specimen and generates the biological response which is thereafter converted to a readable electronic output signal via the transducer. Receptor-based biosensors allow robust and specific biomolecular recognition events which fall into either of the following two categories: (1) affinity recognition and (2) catalytic recognition (Lim and Ahmed 2016). Enzymes are multifaceted protein moieties that have been engineered over the years and used as efficient bioreceptors in a myriad of catalytic applications in S. Hazra · S. Patra (✉) Department of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Guwahati, Assam, India e-mail: [email protected] M. S. Thakur Center for Nanomaterials and MEMS, Nitte Meenakshi Institute of Technology, Bengaluru, Karnataka, India # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Patra et al. (eds.), Enzyme-based Biosensors: Recent Advances and Applications in Healthcare, https://doi.org/10.1007/978-981-15-6982-1_10

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Fig. 10.1 Schematic representation of comparative features in conventional diagnosis and biosensor-based diagnosis

several clinical diagnosis platforms. Thus, these lucrative biocatalysts are attractive candidates when it comes to design biosensing modules for rapid detection. Enzymatic bioreceptors have heightened capture efficiencies when it comes to picking analytes from complex human samples, and this is one major attribute which makes them promising in the diagnosis of infectious diseases. TB, counted as one of the three major infectious diseases that include HIV/AIDS and malaria, continues to be a major public health threat in the present-day world. Moreover, in contrast to these “big three” infectious diseases, another group collectively termed as the NTDs, primarily affecting the tropics and subtropics, have been intensely researched upon over the years in search of effective control programs. Interestingly, these NTDs are now said to affect the disease progression of the “big three” diseases too and thus entail an attractive arena of research for clinical diagnostics (Hazra and Patra 2018). Barring cumbersome traditional laboratory models to diagnose these diseases which are often time-consuming, an alternative and rapid diagnosis of both TB and NTDs is essential for the early initiation of treatment. This ensures reduced comorbidities and improved mortality rates in high-risk population groups. Since both TB and NTDs are highly communicable, there is a pressing need to develop simple commercial biosensors that will ease the process of diagnosis and help in the effective management of such diseases. A schematic representation of the conventional laboratory diagnosis (for, e.g., enzyme-linked immunosorbent assays, culture-based methods, and microscopic techniques) as compared to the point-of-care (POC) biosensorbased diagnosis (for, e.g., immunochromatography dipsticks, nanotechnology-based sensors, and nucleic acid amplification techniques) in infectious diseases is shown in Fig. 10.1.

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10.1.2 Why Are Enzymes Useful as Biorecognition Elements? A biosensing device is considered ideal for an infectious disease if its bioreceptor is capable of correctly capturing the molecule of interest from the clinical sample followed by the determination of concentration of the same with adequate reproducibility. Infectious diseases can be categorized based on an infection caused by either a virus, bacteria, parasite, or fungus leading to the expression of proteins called “virulence factors” in the host (Roberts et al. 2002). Some of these virulence factors emerge as pathogenic biomarkers in patient body fluids. Three major criteria, e.g., specificity, sensitivity, and predictive capacity, must be fulfilled in order to certify an infectious disease biomarker for its diagnostic potential. These biomarkers are recognized by either classical receptors like enzymes and antibodies or ultramodern receptors like aptamers and phages integrated onto biosensors (Justino et al. 2015). Categorically, in TB and NTDs, these analytes are present in clinical samples like blood, sputum, urine, cerebrospinal fluid (CSF), etc. Essentially, enzyme-based biosensors are analytical devices that amalgamate the biocatalytic transformation of analytes along with a transducer to generate an output signal commensurate to the exact proportion of the target in the clinical sample. In contrary to conventional catalysts, enzymes bear distinct active sites functioning in close proximity with a transition metal ion inside the protein matrix. The redox centers harbor unique electron densities which are modified by the constituting peptides and adjacent functional groups in the vicinity of the proteinaceous scaffold to mimic the energy levels of the incoming substrate molecules, thereby allowing swift bioconversion of the substrates (Masa and Schuhmann 2016). The simplest form of enzymatic biosensors is able to carry out reversible reduction or oxidation on the electrode surface upon the application of electrochemically active potential. Enzymatic sensors are further sub-grouped into substrate only or/and additional inhibitorbased sensors. Reversible inhibition sensors can be regenerated for multiple use, but irreversible inhibition sensors are mostly single-use biosensors. The use of inhibition-based enzymatic sensors has limited applications in clinical diagnostics, but holds great potential for the real-time monitoring of environmental samples. Metabolically, two critical steps which determine the course of any biochemical reaction for an enzymatic bioreceptor are (1) target association with the enzyme binding site and (2) catalytic transformation by the enzyme active site. It is also imperative to note that certain enzymatic bioreceptors undergo inhibitory reactions upon target association which leads to the decrease/consumption of the analyte (Wang et al. 2014). Overall, the enzymatic reactions on the biosensing platform are rendered due to the production or consumption of electrons during the biochemical reaction. Thus, each measurable and quantifiable output signal from an enzyme-based biosensor is culminated due to altered ion concentrations, emission or absorption energies in the form of light or heat, release of gaseous substances, etc. generated during the course of the reaction (Grieshaber et al. 2008). Moreover, the substrate-specific nature of enzymatic bioreceptors is particularly attractive when it comes to infectious disease diagnosis as it leads to little or no by-product formation (Cass 2007). Moreover, enzyme-based biosensors are more specific than

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Table 10.1 Desirable qualities of biosensors for infectious disease diagnosis Characteristic Specificity

Sensitivity

Limit of linearity Limit of detection Short assay time Stability

Reusability Shelf life

Reaction volume Power consumption Multiplexing

Advantages in enzyme-based biosensors Enzymes are capable of selectively recognizing the target analyte from a pool of similar molecules showing little or no cross-reactivity to interfering substances in the sample due to its substrate-specific nature Enzymes can recognize minute amounts of target analyte allowing the biosensor to produce a measurable signal without pre-processing or concentrating clinical samples The response range of enzymatic biosensors is linear over a wide range of analyte concentrations which is advantageous for the correct calibration of the sensor Enzyme molecules can generate reproducible signals at the lowest biomarker concentrations above a critical threshold that can be analyzed through various enzyme-coupled and/or enzyme-linked amplification strategies Enzymatic bioreceptors have short recovery times which adds to their efficient response (typically in minutes) Enzymes can be easily immobilized on biosensing surfaces for the repeated monitoring of analytes in real time ensuring that the output signal is stable over a period of time Enzymes are not destroyed after biocatalysis on the biosensing surface and can be regenerated through effective cycling methods Enzymes are operational under an extensive range of diverse environmental conditions and provide prolonged operational flexibility in detecting biomarkers from a variety of biological samples Enzymes can produce reproducible results in small fluid volumes and require less reagents and consequently lower costs Enzymatic reactions have low energy requirements and can be carried out with modest instrumentation Enzyme-based bioassays can be multiplexed easily for detecting multiple pathogen-specific antigens

microorganism-based biosensors for infectious diseases. Other attractive features which make enzymes the “smart molecules” in contemporary diagnostics for infectious diseases are summarized in Table 10.1.

10.2

Biosensing Strategies in Infectious Diseases

10.2.1 Novel Biomarkers for Infectious Diseases: The Role of Enzymes in Detection Biomarkers can be classified into various types. For example, there are pathogenspecific biomarkers and host-specific biomarkers that reflect or predict the outcome of any diseased state (Mayeux 2004). There are two ingredients in a complete biosensing strategy: the first is the selection of a characteristic signal or biomarker indicative of the disease, and the second is the technology to detect and measure it accurately (McNerney and Daley 2011). For infectious diseases, diagnostic methods

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that can detect the presence, determine the activity, or enumerate the concentration of biomarkers from blood, sputum, and urine reproducibly and noninvasively are ideal for enzyme-based biosensors in POC settings. Enzymes are significant as they can react with a wide spectrum of chemical substances found intracellularly or released extracellularly by pathogens. Enzymes can cleave nucleic acid (DNA/RNA) biomarkers in a nuclease-triggered fashion to generate shorter fragments from genomic DNA of pathogens which can be later amplified by PCR (enzyme-assisted nucleic acid amplification). Clinically, this forms the basis of confirmation toward the presence of specific genes of interest harbored by pathogens. This strategy has also been used for the detection of targets in many biosensor nanodevices where nuclease-assisted DNA/RNA target recycling and signal amplification have been studied. Isothermal strand displacement reaction that utilizes polymerases and endonucleases has been applied for the diagnostics of infectious diseases (Toley et al. 2015; Lafleur et al. 2016). Polymerase-like enzymatic reactions also hold promise toward naked eye quantitative nucleic acid detection through loop-mediated isothermal amplification reactions that can be carried out in single tubes and thus advantageous for POC settings. As an alternative to traditional PCR, another strategy, known as the recombinase polymerase amplification, exploits enzymes known as recombinases for the detection of diseases (Abd El Wahed et al. 2015). The thermostable helicase group of enzymes that help in unwinding nucleic acids has also been successfully incorporated into POC in vitro diagnostics (Barreda-García et al. 2018). Another partially isothermal technique, the nucleic acid sequence-based amplification (NASBA), resembles retroviral RNA replication, generating ssRNA as the final product that can be utilized for biosensing. Three enzymes such as T7 DNA-dependent RNA polymerase, RNase H, and reverse transcriptase are integral to the emerging synthetic gene network/CRISPR-based diagnostic principle reported by Collins and coworkers for the detection of the deadly Zika viral infection (Pardee et al. 2016).

10.2.2 Enzymes as Detection Probes The successful use of enzymes as detection probes for infectious diseases relies on the satisfactory electrochemical communicability between the redox site of the immobilized enzyme on the sensing surface and the electrode. Moreover, the active site should not be perturbed upon immobilization or entrapment of the enzyme on the sensing surface (Ferreira et al. 2013). Also, an indirect electrochemical detection mechanism in DNA-based biosensors has shown considerable improvement in detection sensitivities by the incorporation of enzymes. Successful integration of a redox active enzyme as a label onto a target DNA sequence catalyzes a redox reaction and generates an appropriate electrochemical signal. For example, horseradish peroxidase-labelled DNA probes are useful in electrochemical genosensors. Enzyme labels are also useful in monitoring infectious agents’ analytes amperometrically through indirect RNA hybridization too. Modification of

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traditional ELISA platforms (bypassing multiple washing and incubation steps) has been successfully employed for the detection of infectious diseases’ biomarkers on POC strip tests or dipsticks, DRSB, etc. The use of protease enzyme as a probing label was successfully employed for the detection of Listeria monocytogenes, a well-known causative agent of food poisoning by colorimetric color production on a gold-sputtered paper surface. This innovative technology based on protease-based cleavage of pathogen-specific peptides coupled with a simple and easy visual interpretation could also be applied for the detection of other infectious diseases (Alhogail et al. 2016). Enzymes evolved from pathogens can be detected on paper POC devices by employing substrates and subsequent pH-specific color change mechanism upon enzymatic catalysis which has been employed in the detection of E. coli and Enterococcus spp. (Jokerst et al. 2012; Adkins et al. 2017).

10.2.3 Enzyme-Catalyzed Amplification TB and NTDs often have patient biomarkers in suboptimal concentrations; hence, ultrasensitive detection is always a necessity in clinical diagnosis kits. Herein comes the utility of fine-tuning the enzymes capable of amplifying signals through cascade interactions, redox cycling techniques, etc. In recent years, use of multi-enzyme labels and nanobioconjugates in non-conventional enzymatic systems has allowed ultrasensitive detection in biosensors. Such electrochemical redox cycling technique is a viable option to improve the signal-to-noise ratio along with manifold detection possibilities (Karra and Gorski 2013). Also, enzymes can be coupled to IgG antibodies in the form of enzyme-antibody conjugates or integrated with DNA to form DNAzymes to detect infectious antigens immobilized on the sensor surface. Signature DNA sequence IS6110 of the Mtb genome could be selectively detected through enzyme-assisted target recycling amplification technique through redox nanoprobes based on the novel strategy of nicking endonucleases (Chen et al. 2018). Also, an application of robust helicase enzyme in another isothermal signal amplification technique from the research by Barreda-García and group highlights an alternative mechanism for Mtb detection that takes place at a constant temperature bypassing complex thermocycling programs, making it highly suitable for upcoming microfluidic approaches for the construction of POC devices (Barreda-García et al. 2015, 2016).

10.2.4 Tuberculosis Diagnosis It is noteworthy that in case of TB, the paucity of tubercle bacilli in patient specimens has largely shifted the domain of biomarker detection toward circulating antigens which are signature molecules secreted by the bacilli in the patient (Fig. 10.2). Enzyme-linked assays for tuberculosis detection: Recently, enzyme-linked oligonucleotide assays (ELONA) have been proven to be fruitful with SELEX-generated

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Fig. 10.2 Characteristic features of an ideal TB biomarker to be considered for biosensing

oligonucleotides/aptamers in detecting tuberculosis antigens on biosensing approaches from clinical samples (Golichenari et al. 2018). ELONA is a modification of traditional enzyme-linked immunosorbent (ELISA)-like assays which improves the capability of enzymes entailing them with heightened specificity and sensitivity. For example, aptamers directed toward detecting the 10-kDa culture filtrate protein (CFP-10) and the 6-kDa early secreted antigen target (ESAT-6)secreted heterodimer were successful in diagnosing TB from clinical sputum samples (Rotherham et al. 2012). Another DNase I enzyme-assisted cleavage and amplification technology-based IFN-γ detection was put forward by Yan and coworkers for a fruitful electrochemical graphene-based aptasensing platform (Yan et al. 2013). Moreover, an application of RecJf exonuclease enzyme in dual signal amplification strategy using graphene/AuNP-modified electrode and IFN-γ aptamers was shown by Yin and group (Yin et al. 2017). Also, a novel technique using aptamer dot blots for Mtb quantitation in sputum samples was illustrated by Li et al. in 2018. Interestingly, this work uses enzyme-linked aptamer assay via the recognition of lipoarabinomannan residues for smartphone-based point-of-need Mtb detection (Li et al. 2018). Improved nanodiagnostics have smoothened the process of reliable detection for TB with the advent of various nanoparticles (NPs) that possess some highly tunable features. For example, gold nanoprobes with alkaline phosphatase as the detection enzyme immobilized on a microchip rendered promising results for the detection of Mtb (Zhu et al. 2017). Zhou et al. described a metal organic framework-based enzymatic amplification strategy (hemin/G-quadruplex) superior to single enzyme-tagged models toward the detection of tuberculosis electrochemically (Zhou et al. 2020). The use of enzymes as fluorescent reporter molecules for TB diagnosis was successfully shown by Sule et al. where TB-specific biocatalyst beta-lactamase precursor was assayed in a reporter enzyme fluorescence (REF)

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format with a fluorogenic substrate CDG-3. The results were comparable to TB diagnosis gold standards (Sule et al. 2019). Enzymes have been also used in aptamer-based labels for the production of colorimetric naked eye detection of end products for latent TB detection in dot blot assay format (Li et al. 2018).

10.2.5 NTDs’ Diagnosis Traditional methods to detect the various types of NTDs are time-consuming, require skilled expertise to interpret results, and most importantly cannot be performed in remote locations in situ. In endemic places across the globe, several of these NTDs require a portable and on-spot result indicating devices which tend to be promising in this context. Moreover, biological probes like enzymes are superior compared to other catalytic sensors employing microbes, organelles, cells, or tissues in regard to diagnosing NTDs which might show overlapping symptoms, and patients often harbor multiple causative agents at any given point of time (Hazra and Patra 2018). Specificity to recognize rapidly and the ability to be used continuously multiple times reinforce the applicability of enzymatic biosensors for detecting NTDs. Moreover, enzymes can detect low levels of analytes (LODs) giving reproducible results. Enzymes have always been a fruitful target to detect in patient samples as enzymes (e.g., proteases) have specific recognition motifs which can be used to study their activities. Whole cell biosensors employing such mechanisms have developed considerably to detect NTDs’ target enzymes (Webb et al. 2016). Enzymes have various modes of catalytic mechanisms. For example, the inhibition studies of an enzyme found to play a role during the pathological cycle of the parasites in NTDs have many potential pharmacological applications in clinical diagnosis. These enzymatic targets have been immobilized onto sensor surfaces eliciting a screening-based mechanism for finding out inhibitors worthy of treating such infections. Similarly, the specificity of the inhibitors can be evaluated through the utilization of similar binding studies with the enzymes that interact with the parasite in the host (human) system (Calil et al. 2016). Thus, studies on the inhibition of target enzymes and their underlying mechanisms also have diagnostic implications regarding the enzyme-based NTDs’ diagnosis. Similarly, ligands capable of reacting with such enzymes can be immobilized onto sensor surfaces to detect the presence of target parasite and their respective enzymes from clinical samples. Enzymes have also been used as signaling tags in NTDs’ disease detection on electrochemical biosensing platforms like fluorophores and NPs. One good example of enzymes being used as a screening tool was demonstrated by Opassi et al. that uses Trypanosoma cruzi (causative agent of Chagas disease) farnesyl pyrophosphate synthase on a surface plasmon-driven platform (Opassi et al. 2020). The compounds giving significant responses to the target protein on the sensing surface provide valuable input toward the fragment-based drug discovery of leads in American trypanosomiasis disease. A simple modification of the conventional loop-mediated isothermal amplification (LAMP) technique, i.e. multiplex LAMP (mLAMP) in combination with the dot enzyme-linked immunosorbent assay (dot-ELISA) setup

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was reported by Nkouawa and group for cysticercosis in a cost-effective and sensitive lateral flow dipstick format for the differential detection of the human Taenia species (Nkouawa et al. 2016). There lies a tremendous scope of enzymes for use as sensing elements of cysticercosis other than the traditional ELISA-based approaches. Dengue fever is another NTD where a vast majority of detection prototypes follow sensing principles using enzymes in the traditional antigen-antibody detection-based ELISA platforms. Confirmatory detection of dengue has been possible through various biosensor modalities like electrochemical, optical, microfluidic, as well as smartphone-based operations. The application of molecular scissors like EcoRI enzyme for cleaving multiple signaling molecules and generating detectable signals is a useful molecular tool for the detection of dengue (Fletcher et al. 2010). Alternatively, easier and miniaturized microfabricated paper-based POC prototype for dengue was explored by Thiha and Ibrahim on a lab-on-compact-disc (LOCDELISA) format (Thiha and Ibrahim 2015). A pictorial representation summarizing the different modalities of enzyme-based biosensing platforms commonly studied for various types of infectious diseases is depicted in Fig. 10.3.

10.3

Challenges with Enzymatic Biosensing

Enzymes face a lot of challenges when they are used on biosensing nanodevices for in vitro diagnostics. Although enzymes are highly selective and sensitive, activity of the enzyme-based biosensor decreases over time due to the limited lifetime of protein molecules. The limitations of natural enzymes include its requirement for optimum pH and costly purification techniques which are time-consuming. Another drawback is its poor stability and limited efficiency at elevated temperatures. One interesting approach of utilizing temperature-based enzymatic catalysis can be seen where the temperature output of a reaction containing the analyte is corroborated to the temperature output of a reaction without the analyte in order to generate a measurable signal. Thus, biosensors which have used the temperature-sensitive limitation of enzymes in a fruitful and positive approach are most suitable for the POC format. These sensors are commonly used for monitoring pesticide contaminations and disease-causing bacteria, but also generate reproducible results in measuring serum cholesterol levels based on enzymatically produced heat of oxidation and decomposition (Patel et al. 2016). A tabular representation of enzymatic challenges in biosensors and ways to address them is highlighted in Table 10.2.

10.4

Recent Progress in Enzyme-Based Biosensing

10.4.1 Future Prospects of Enzyme-Based Biosensing Infectious diseases require POC testing methods to ensure on-site determination of suspects where resources are limited. In all POC methods known so far, enzymes are widely applied as labels in the generation of response in immunoassay-based

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Fig. 10.3 Schematic representation of different modes of enzyme-based biosensing platforms for infectious diseases: (a) conventional enzyme-based biorecognition where the analyte is converted to a colorimetric product in the presence of coenzymes in a redox mechanism, (b) detection of a competitive (reversible) or a noncompetitive (irreversible) inhibitor through substrate addition and washing steps, (c) enzyme-based biorecognition for capturing nucleic acids and oligonucleotides where the reporter probe emits a signal upon cleavage by the enzyme, (d) enzyme-based signal amplification in detection label applied for aptasensing of analytes from clinical samples through biotin-streptavidin chemistry, (e) nanozymes detect enzymatic biomarkers (e.g., proteases) from biofluids and pathogens through capture nanoprobes through a colorimetric mechanism, and (f) modified sandwich ELISA recognition format where the secondary antibody is conjugated to enzyme-mimetic nanoparticles for the efficient detection of analytes from clinical samples

formats. This limits the application of enzymes for the detection of pathogen-specific biomarkers as biorecognition elements. Since enzymes are composed of two parts, the apoenzyme (protein part) and the coenzyme/cofactor (non-protein part), the versatility in the selective modification of either of these two conjugating domains accentuates the future application of enzymes on test strip-based as well as dipstickbased diagnostics. For example, functional nanostructuring of these cofactors or coenzymes and reconstituting them to the apoenzymes before immobilization onto electrode surfaces is a novel approach to improve electrical conductivity which is

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Table 10.2 Disadvantages of use of enzymes in sensors for infectious diseases and ways to address them Challenging disadvantages Reduced signal output due to interfering/fouling substances in sample matrices on the sensing surface Loss of enzymes in close contact with the transducing surface upon reacting with their substrate Sensitivity of biological enzymes to external conditions like pH, temperature, and chemicals coming in contact with the biosensing platform Reduced signal output in case of detecting low levels of biomarkers from patient samples

Sensor device modification processes, complex power sources, high chemical electrolysis rates, other processes like thermal lysis leading to heat dissipation which affects enzyme stability and shelf life Reduced electrical conductivity of sensor surface hindering the passage of electrons to the enzyme active site

Reduced sensitivity of enzymatic electrodes

Reduced suitability for incorporating into portable biosensors, stability issues over time

Reduced stability of enzymes in selfpowered biosensors

Toxic enzyme mediator systems limit application in in vivo

Alternative ways to address Enzyme bioengineering, hybrid biomaterials on sensing surfaces ensuring the stability of enzymes

References Nguyen et al. (2019)

Enzyme immobilization through covalent bonding chemistry, encapsulating enzymes in 3D matrix Enzyme bioengineering to increase stability in test strips, direct electrocatalysis through non-enzymatic biosensing Improvement of detection sensitivity by the integration of enzymes with biocompatible nanoarchitectural materials, thereby enhancing enzyme activity Self-powered biosensors, enzymatic biofuel cells, etc.

Williams and Blanch (1994)

Modification of enzymes to make them biocompatible with graphenebased biosensing surfaces which provide large (2D sheet) surfaces facilitating the percolation of electrons to enzyme redox centers Using carbon nanotubes, mesoporous materials and composites flexible carbon fibers and related nanostructures which are versatile in tensile strength, elasticity and can be tuned to escalate the sensitivity Enzyme-based nanoassembly methods are attractive for the fabrication of the enzyme-substrate reactions. 2D, 3D, and microarray printing for incorporation into wearable and paper-based sensors ensure better stability of an enzyme within nanostructures Replacement through synthetic bioreceptor molecules will enhance the diagnostic performance and improve the lifespan of these sensors Use of recyclable and environmentally friendly natural

Niu et al. (2016)

Johnson et al. (2014)

Sin et al. (2014)

Patel et al. (2016)

Patel et al. (2016), Pacios et al. (2011)

Othman et al. (2016)

Kozitsina et al. (2018)

GonzalezSolino and (continued)

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Table 10.2 (continued) Challenging disadvantages

Alternative ways to address

References

bioelectrochemical devices, and miniaturization of such devices requiring compartmentalization using membranes makes them complicated and impossible Enzyme purification is costly and time-consuming

mediator alternatives and incorporating them into polymeric enzymatic biofuel cells integrated with microfluidic device and/or bioelectrodes Incorporating non-enzymatic approaches reduces the overall cost and labor-intensive processes Enzyme structure can be modified through deglycosylation and oligomerization procedures, and alternatively by reducing the distance between enzyme and surface through tunneling

Lorenzo (2018)

Large size of the enzyme results in the inaccessibility of the redox center, making it difficult to obtain direct electron transfer

–

Pereira et al. (2018)

being used by many researchers in current times. Moreover, use of enzymatic substrates that are able to produce insoluble colored compounds can be carefully chosen for paper-based POC biosensors where there is a hassle-free signal readout from the precipitated colored product. Use of engineered non-biological molecules and artificial analogues mimicking the active site of enzymes around the redoxactive metal center is also a futuristic alternative in the field of enzymatic biosensors (Patil et al. 2018). Processes that bypass the labor-intensive and multiple analysis steps of traditional ELISA are gaining importance in the last decade. Careful implementation of competitive or non-competitive formats for detecting immunocomplexes (classical antigen-antibody conjugates) in immunoassays that are able to generate signals by itself in label-free procedures in simple YES/NO format is now being considered as a useful substitute for miniaturized sensing platforms. Toward this end, molecularly imprinted polymers (MIPs) are also rapidly evolving as a novel class of non-enzymatic substitutes capable of efficiently and reliably catalyzing chemical reactions for which there are no known enzymes. Thus, non-enzymatic biosensing tools are gaining grounds due to their extensive compatibility to nanoengineered materials, supramolecular compounds, electrically conductive polymers, MIPs, and other biomimetics. Extended shelf lives, universality, and robustness to the extremes of the environment make non-enzymatic sensors superior to traditional enzyme biosensors. Bioelectrochemists are in search of newer ways to incorporate enzymes having improved direct electron transfer mobilities that enhance device sensitivity. Chemically modified 3D printed enzyme in miniaturized scaffolds, catalytic antibodies, and artificial RNAzyme and DNAzyme also holds promise because of its potential to surpass traditional ELISA in infectious disease diagnostics (Singh et al. 2015; Papadakis et al. 2019).

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10.4.2 Nanozymes for Biosensing The field of nanozymes is an upcoming arena of research where biochemical, diagnostic, and therapeutic activities of NPs are exploited for their enhanced enzyme-mimicking catalytic properties. Nanozymes are inorganic enzyme mimics that are efficient in detecting pathogenic microorganisms and their products with crucial advantages like durability, higher stability, lower costs, the possibility of naked eye detection, independent of solution turbidity, multifunctionality, etc. that circumvent the drawbacks of traditional enzymes used in biosensing. Nanomaterials are carefully tuned to exhibit multiple enzyme-like properties (e.g., oxidase, peroxidase, catalase, superoxide dismutase, nuclease, etc.) and bio-fabricated on lateral flow paper strips, chips, and immunoassay platforms to generate colorimetric, fluorometric, and electrochemical responses upon reacting with analytes. Metals and metallic oxides and sulfides, bimetallic alloy NPs, carbon materials, metalconjugated organic frameworks (MOFs), and other nanomaterials are now being considered as superior biorecognition elements in enzyme-based biosensors because of their versatile bioconjugation and interfacing capabilities. These nanozymes can interact and cleave/digest analytes to produce changes and thus can also be exploited toward undermining the location of the disease as well as assessing biomarker levels in human bodies. Nanozymes are shown to be successful toward the detection of several known infectious pathogens like Pseudomonas, Salmonella, Enterobacter, Vibrio, Escherichia, Bacillus, Listeria, as well as Ebola virus (Sun et al. 2020; Munir et al. 2020). Thus, nanozymes are an important tool superseding natural enzymes that holds promise toward the analysis of various substrates or enzymes of pathogens in NTDs. Integrated metallic core/shell nanostructure-based nanozyme aptasensors also hold promise for a naked eye quantitative determination of microbial pathogens for which no known biosensing tool is formulated yet.

10.5

Summary and Outlook

Commercial biosensors for infectious diseases which are enzyme-based have shown continuous development in the last few decades. Low-cost and disposable enzyme test kits (e.g., dipsticks and microfabricated paper-based colorimetric kits) have become attractive alternatives to complex clinical diagnostics. Thus, futuristic enzymatic biosensors that are expected to contribute maximally to medical diagnostic’s global biosensors market share should ideally employ multiplex detection for detecting resistant forms of infectious diseases in a single-step assay format. Sub-second enzymatic processes are an attractive approach for affordable diagnostics toward the improvement of healthcare quality, but their cost and instability have thwarted their applications in the next-generation biological and chemical sensors. The use of enzyme-based biosensors is limited in peripheral facilities, mainly due to the absence of cold storage facilities and because purified enzymes often tend to have limited shelf lives. Moreover, mediators used for enzymatic reactions have several criteria that must be met. For example, (1) accurate and

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reversible redox behavior, (2) minimally responsive to the enzyme’s substrate, (3) appropriateness to nullify the effect of interfering compounds, (4) resistant toward fluctuations in pH and ionic concentrations, and (5), most importantly, non-toxic are some of the attributes that indicate the suitability of a mediator for an enzyme (Leca-Bouvier and Blum 2010). There is a strong inclination towards the application of synthetic enzymes (Schlosser and Li 2009) and various non-enzymatic catalysts that amalgamate both the domains of broad substrate and product spectrums. Toward this end, our chapter gives the audience an opportunity to know more about elucidating theoretical issues of enzymes in biosensors and methods to increase their practical applications in sensors and biodevices for infectious diseases. Thus, we enable our readers to get a glimpse of the paradigm shift from enzymatic to non-enzymatic biosensing approaches that is highlighted by the need to develop more stable and rapid detection in integrated formats for benchtop and portable biosensors. The present development trends in this regard are pitched toward device miniaturization with minimal reagent requirements, paper-based test kits, and lab-on-a-chip and multiplexed detection on biochip sensing devices with minimum sample pre-treatment steps ensuring lower power demands. Although multi-enzyme systems have several advantages over the traditional one-step enzyme-substrate assays, use of more than one enzyme has limited application due to insufficient knowledge on conjugate enzyme immobilization approaches and methods of signal amplifications in such cases. Herein, it can be conceptualized that a combination of more than one enzyme would provide versatility in the detection of various analytes when it comes to infectious diseases as more than one biomarker can be effectively detected on a common platform efficiently. The reduction of overall time and cost are primary issues that can be solved with multi-enzyme disposable biosensing systems precisely. Taken together, the outlook of this chapter is directed toward insights and challenges of enzymatic biosensors to overcome the pitfalls of conventional and traditional diagnostics wherein the authors have provided a glimpse of the upcoming techniques in allied areas of nanotechnology, surface chemistry, bioengineering, and electrical engineering that augment the future use and application of enzymes in clinical diagnostics. Acknowledgments SH acknowledges the Indian Institute of Technology Guwahati for providing infrastructural facilities and PhD research fellowship and the Department of Biotechnology, Government of India (BT/PR22952/NER/95/572/2017), for funding the necessary research. Declaration of Competing Interest Authors have no conflict of interest.

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Piezoelectric Biosensors in Healthcare

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Akshpreet Kaur, Parveen Kumar, Ankur Gupta, and Gaurav Sapra

11.1

Introduction

Biosensors are highly sensitive analytical devices capable of converting a biological reaction into a readable electrical signal using biomaterials. The biologically active materials includes enzymes, cells, DNA, antibodies, etc. that are engineered to interact with biological systems to provide medical treatment and diagnosis (Coulet and Blum 2019). An American biochemist “L.L Clark” invented the first biosensor in 1950, and in 1977, “Cammann” introduced the term “biosensor” for the first time (Cammann 1977). According to IUPAC nomenclature, biosensors are integrated receptor-transducer devices, which are able to provide selective quantitative or semiquantitative analytical information using a biological recognition element (Singh et al. 2020). A typical biosensor consists of three main units—biosensing unit, transduction unit, and output unit. A biologically active component (DNA, proteins, enzymes, or antibodies) is incorporated on the surface of the biosensing element that selectively recognizes the biological target analyte and produces a signal which is detected by the transduction unit. The transduction unit is responsible for converting the biorecognition event into an electrical signal which may be in the form of change in voltage, current, resonant characteristics, temperature, optical properties, etc. Based on the type of transducer used in the transduction unit, biosensors are categorized into piezoelectric, electrochemical, optical, thermal, etc. (Gupta 2020). A. Kaur · G. Sapra (✉) UIET, Panjab University, Chandigarh, India e-mail: [email protected] P. Kumar E-waste Laboratory, CSIO – CSIR, Chandigarh, India A. Gupta Department of Cardiology, PGIMER, Chandigarh, India # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Patra et al. (eds.), Enzyme-based Biosensors: Recent Advances and Applications in Healthcare, https://doi.org/10.1007/978-981-15-6982-1_11

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Fig. 11.1 Mechanism of a typical biosensor

Piezoelectric biosensors are extremely responsive tools offering exciting advantages over other biosensors such as flexibility, fast response, simple operation, low cost, mass production, and real-time and label-free transduction (Tombelli 2012). The basic mechanism of a typical biosensor is shown in Fig. 11.1. In this chapter, piezoelectric biosensors are discussed along with their types, operating principle, material considerations, and applications such as biomechanical energy harvesting, wearable health monitoring, and early diagnostic biomarkers for Alzheimer’s disease, cancer, cardiovascular diseases, and COVID-19. Quintessentially, piezoelectric biosensors have revolutionized the healthcare system providing early clinical diagnosis and therapeutic interventions.

11.2

Operating Principle of Piezoelectric Biosensor

Biosensors that are based on the principle of piezoelectric effect are termed as piezoelectric biosensors. The term “piezoelectric” is deduced from a Greek word piezein-elektro which means “press-electric” signifying mechanical and electrical coupling. Piezoelectric effect is the ability of certain materials like piezoelectric quartz crystal (PQC) to generate an electric voltage in response to the mechanical stress. The French scientists Jacques Curie and Pierre Curie first demonstrated the piezoelectric effect in 1880 (Curie and Curie 1880). In piezoelectric biosensors, a piezoelectric element with sensing molecules is incorporated onto the sensor which interacts with the target analyte. The biomolecular interaction gives rise to mechanical vibrations which results in change in mass of the crystal and therefore changes resonance frequency of a piezoelectric crystal (Pohanka 2018a, b). This correlation between mass and resonant frequency during biomolecular interaction forms the basis of piezoelectric biosensors which is given by Sauerbrey’s equation (Eq. 11.1) (Sauerbrey 1959). Δf =

- 2f 02 Δm Δm = - 2:3 × 106 f 20 p A A ρq μq

ð11:1Þ

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Types of Piezoelectric Biosensor

Piezoelectric biosensors can be broadly categorized into three types—acoustic wave biosensor, cantilever biosensor, and piezoelectric immunosensors—which are discussed below (Ngeh-Ngwainbi et al. 1990). Acoustic wave biosensor can be further classified into two types based on their wave guiding process—surface acoustic wave (SAW) and bulk acoustic wave (BAW). Quartz crystal microbalance (QCM) and thickness shear mode (TSM) are BAW devices (Tombelli 2012). Figure 11.2 shows the types of piezoelectric biosensors.

11.3.1 Acoustic Wave Biosensors Acoustic biosensor technology forms an extremely interdisciplinary area of research and has gained huge recognition spanning from electrical engineers to cell biologists due to their ability to detect any type of analyte, i.e., label-free detection (Becker and Cooper 2011). Acoustic wave biosensors are also known as mass sensors as they are based on the principle of mass-based detection. In acoustic wave biosensors, biosensing element such as piezoelectric quartz crystal (PQC) interacts with the target analyte during biomolecular interaction. During biomolecular interaction, adsorption of analyte by the sensing element takes place which results in change in mass density. A voltage signal at the resonant frequency of the PQC is supplied by an oscillator to measure the change in resonant frequency due to change in mass density. The resonance frequency in acoustic biosensors is very sensitive to the system mass (Gouvêa 2011). Acoustic sensors can be classified into two types based

Fig. 11.2 Types of piezoelectric biosensors

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Fig. 11.3 Schematic of a typical OCM (Skládal 2016)

on their wave guiding process—surface acoustic wave (SAW) and bulk acoustic wave (BAW) (Tombelli 2012). SAW devices comprise electrodes on the same side of the crystal, and the propagation of wave is confided to the crystal surface. In BAW devices, mechanical deformations propagate through the volume of the crystal. Quartz crystal microbalance (QCM) and thickness shear mode (TSM) are BAW devices (Bunde et al. 1998). Quartz Crystal Microbalance (QCM) QCM is a novel highly sensitive diagnostic platform with short detection time. QCM is constructed by sandwiching a thin quartz crystal disc between two electrodes as shown in Fig. 11.3 (Lim et al. 2020). When quartz crystal is subjected to an external electric field, mechanical stresses are produced in the crystal. This mechanical stress induces an alternating voltage in the piezoelectric crystal causing it to oscillate in the perpendicular direction to the surface of the plate (Chen et al. 2018). QCM is the most popular piezoelectric biosensor used in disease biosensing for the measurement of shift in resonant frequency due to change in the mass density which is an intrinsic property of all substances. Due to its very fast response around 30 min to 1 h and label-free detection, it has become a versatile tool for the early diagnosis of various infectious disease biomarkers such as viral infections and bacterial infection (Pohanka 2020) which are discussed subsequently in the chapter (Sin et al. 2014).

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11.3.2 Cantilever Biosensors Cantilever-based sensors operate on the principle of atomic force microscopy (AFM) invented by Binning et al. AFM has provided an effective platform to detect pathogens and in the measurement of density, viscosity, and flow rate by the changes in vibrational frequency. A microcantilever with a sharp tip oscillating at a frequency of the sensor surface is employed for the surface characterization of the sensor as shown in Fig. 11.4 (Caygill et al. 2010). A CCD chip is used for the detection of the reflected beam due to incident laser beam. The deformation in the tip of the microcantilever occurs when it interacts with a biological component. The capacitor plates are utilized to detect the microcantilever deformations which occur due to the adsorption of analyte on the one side of the cantilever structure. The deformation is directly proportional to the concentration of analyte. Cantilever array sensors have been instrumental in the detection of various viruses such as HIV (Kuznetsov et al. 2003), dengue (Ferreira et al. 2008), influenza (Owen et al. 2007), etc.

11.3.3 Piezoelectric Immunosensors Piezoelectric immunosensors are a class of biosensors which are used to investigate various biomolecular compounds. Piezoelectric immunosensors are constructed by immobilizing a specific antibody to the biosensing element in order to recognize antigens making the immunosensor specific for the diagnosis of infectious diseases.

Fig. 11.4 Working mechanism of cantilever sensor using AFM (Caygill et al. 2010)

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Fig. 11.5 Principle of Piezoelectric immunosensor consisting of piezoelectric crystal (blue disc), antigens (red balls) andantibodies depicted with Y letter owing to their typical structure (Pohanka 2018a, b)

The operating principle of Piezoelectric immunosensors is based on changes in oscillation frequency of the electrical signal owing to antibody – antigen reaction resulting in variation of bioreceptor mass that is sensed by piezo crystal (Fig. 11.5) The variation in mass is due to integration or breakdown of immune complexes on the surface of the biosensor. Recent research shows that sized analytes are suitable for piezoelectric immunosensors due to their high molecular weight which evidently causes higher decrease of oscillation frequency (Pohanka 2018a, b).

11.4

Material Consideration for Piezoelectric Biosensors

Piezoelectric materials are a class of powerful biomaterials that exploit piezoelectric effect occurring due to the internal polarization of material ions due to applied mechanical stress. They can be categorized into inorganic and organic piezoelectric materials (Chorsi et al. 2019). For usage in a biosensor, biocompatibility and non-toxicity are essential requirements. Piezoelectric materials interfaced with sensors provide an exciting platform for biomedical diagnostic and monitoring devices (Akmal and Ahmad 2020).

11.4.1 Inorganic Piezoelectric Materials The phenomenon of piezoelectricity in inorganic materials is described by the movement of ions in the interior of crystal. The application of mechanical stress onto the piezoelectric material results in change in the atomic structure of the crystal leading to shift in ionic balance, thus creating dipole moment. Inorganic piezoelectric materials include quartz, lead zirconate titanate (PZT), zinc oxide (ZnO), aluminum nitride (AlN), barium titanate (BaTIO3), etc. They are non-toxic or can be encapsulated with biocompatible materials in order to minimize the toxicity (Luo et al. 2013; Bongrain et al. 2015).

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11.4.2 Organic Piezoelectric Materials The phenomenon of piezoelectricity in organic materials is described by the orientation of dipoles in the molecular structure of the bulk polymers which is realized by applying high electric field. Organic materials have been widely explored in the field of biosensing and energy harvesting applications owing to their outstanding characteristics such as biocompatibility, low cost, environment-friendly nature, mechanical flexibility, and simple fabrication. Organic piezoelectric materials include PVDF, glycine, PLLA, graphene, silk, diphenylalanine peptide nanotubes (PNT), etc. PVDF is the most commonly used polymer for energy harvesting and biosensing applications. The inert nature and piezoelectric capability of PVDF allow its use in surgical meshes and wound healing, respectively. The advent of piezoelectricity in graphene has opened new routes for its usage in biomedical applications due to its excellent properties of flexibility and stretchability (Zaszczyńska et al. 2020). Hybrid nanogenerators have emerged as a new technology exploiting innovative nanocomposite materials which combine organic and inorganic materials to exhibit better performance and stability of devices. These nanogenerators are being widely used in various bioelectronic and biomedical devices (Bairagi and Ali 2020).

11.5

Piezoelectric Biosensor Applications

Biosensors have made a paradigm shift in healthcare from centralized system in lab to decentralized at the point of care. This has made the diagnosis process very rapid providing better pharmacologic responses to therapeutic intervention. Biomarkers form a non-invasive approach to indicate the presence of a disease or disease predisposition in the near future. A specific biomarker is crucial for early disease diagnosis and corresponding successful prognosis. Piezoelectric biosensors act as a promising technology for biomarker analysis owing to their fast response and robust and user-friendly multianalyte evaluating capability. A biomarker may be biological such as DNA or proteins or non-biological like glucose (Gouvêa 2011). Piezoelectric biosensors employed for the detection of various biomarkers for the early diagnosis of various diseases such as Alzheimer’s disease, cancer, cardiovascular disease, and coronavirus are discussed in this section. The section also discusses wearable piezoelectric biosensing devices for health monitoring.

11.5.1 Alzheimer’s Disease Detection Alzheimer’s disease is a neurodegenerative disorder with tau protein as a biomarker that leads to memory loss and damage of cognitive functions. The detection of tau protein in the cerebrospinal fluid (CSF) acts as a hallmark of Alzheimer’s disease (Ameri et al. 2020) To detect the presence of tau protein, a QCM immunosensor was developed by exploiting sandwich-structured piezoelectric biosensing unit. The

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Fig. 11.6 (a) Direct assay of tau protein on piezoelectric biosensor with mAb1 as primary receptor and corresponding dose-response relationship. (b) Dose-response relationship trend corresponding to sandwich-structured tau-based piezoelectric immunosensor (Li et al. 2018)

change in mass at the surface of the biosensing element results in change in frequency. The comparison of tau binding capability and dose-response relationship in direct and sandwich mode is shown in Fig. 11.6(a) and (b), respectively (Li et al. 2018). Cantilever-based piezoelectric biosensors have also been used for the early diagnosis of Alzheimer’s disease by detecting deflection in beam due to the stress experienced on the surface. The design of the system incorporated a microslit of 5 μm owing to its better-quality factor (Q factor) in comparison to conventional structure as shown in Fig. 11.7(a). Figure 11.7(b) shows the resonance frequency resonated by a PZT self-actuator and measured by laser Doppler vibrometer (LDV) (Chae et al. 2017).

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a (1) Slit cantilever

Air-liquid interface formation

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b

(1) Q>20

(2) Q=2~4

(2) Conventional cantilever more viscous damping effects

Fig. 11.7 (a) Schematic showing microslit-based cantilever and conventional cantilever structure. (b) Resonant frequency and Q factor corresponding to microslit cantilever (red) and conventional cantilever (black) (Chae et al. 2017)

11.5.2 Cancer Diagnosis Cancer has been one of the major causes of death in developed as well as developing countries. Specifically, most female deaths associated with cancer have been due to breast cancer, and in males, the leading cause has been lung cancer (Bray et al. 2018). Researchers have not been able to find a particular reason leading to the development of cancer cells. There are various factors including genetic and environmental that cause the onset of the disease. The development of cancer is mainly due to exposure to carcinogenic toxins, chemicals, etc. The early diagnosis of cancer cells using biomarkers plays a significant role in the treatment and monitoring of the disease (Vineis et al. 2010). Different biomarkers have been found to be associated with different types of cancers as listed in Table 11.1. Su et al. (2013) demonstrated a cost-effective and highly sensitive piezoelectric biosensor with PZT ceramic resonator (Fig. 11.8a) acting as a transducer for the label-free diagnosis of cancer biomarkers such as prostate-specific antigen (PSA) and a-fetoprotein (AFP). Piezoelectric-based smart-touch fine needles (STFM) (Fig. 11.8b) have been presented to determine abnormal tissue stiffness useful for cancer diagnosis (Sharma et al. 2019). Loo et al. (2011) reported a fast and sensitive-based piezoelectric microcantilever sensor (PEMS) (Fig. 11.8c) for the early detection of biomarker HER2 usually found in the blood of breast cancer patients.

11.5.3 Cardiovascular Diseases Though cardiovascular diseases can be prevented, they are the leading cause of death with heart failure increasing at a rapid rate. The increase in the level of concentration of cholesterol is the major cause of cardiac diseases. Biomarkers for cardiac diseases act as early detectors of symptoms of the disease. A wearable piezoelectric-based pulse wave velocity (PWV) sensor has been developed to evaluate pulse wave

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Table 11.1 Biomarkers associated with different types of cancers (Gouvêa 2011) S. no. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14.

Type of cancer Breast Bladder Cervix Colon Esophagus Leukemia Liver Lung Melanoma Ovarian Pancreas Prostate Solid tumors Stomach

Associated biomarker ER, PR, HER2, CA15-3, CA125, CA27.29, CEA BRCA1, BRCA2, MUC-1, CEA, NY-BR-1, ING-1 BAT, FDP, NMP22, HA-Hase, BLCA-4, CYFRA 21-1 P53, Bcl-2, Brn-3a, MCM, SCC-Ag, TPA, CYFRA 21-1, VEGF, M-CSF HNPCC, FAP, CEA, CA19-9, CA24-2, p53 SCC Chromosomal aberrations AFP, CEA NY-ESO-1, CEA, CA19-9, SCC, CYFRA21-1, NSE Tyrosinase, NY-ESO-1 CA125, AFP, hCG, p53, CEA CA19-9, CEA, MIC-1 PSA, PAP Circulating tumor cells in biological fluids, expression of targeted growth factor receptors CA72-4, CEA, CA19-9

velocity in the radial artery to monitor blood flow and blood pressure (Richards et al. 2020). ZnO nanowire-based highly sensitive immunodevice has been developed for the detection of three biomarkers: human heart-type fatty acid binding protein (FABP), cardiac troponin I (cTnI), and myoglobin (Guo et al. 2019). Pohanka (2018a, b) developed piezoelectric immunosensor for the detection of tumor necrosis factor alpha (TNFα) which is a potential biomarker for the diagnosis of cardiovascular diseases as shown in Fig. 11.9(a). A quartz crystal-based piezoelectric biosensor to detect apolipoprotein E polymorphisms has been reported for the prognosis and early diagnosis of cardiovascular disease (Tombelli et al. 2000). Piezoelectric nanofiber-based implantable pressure biosensor (Fig. 11.9b) has been used to monitor in vivo micropressure changes at the cardiovascular walls which play a significant role to detect atrioventricular heart block and thrombus formation (Li et al. 2019).

11.5.4 Coronavirus Detection In 2004, Zuo et al. (2004) presented the first piezoelectric-based immunosensor for the detection of coronavirus. The immunosensor was fabricated by immobilizing horse polyclonal antibody onto the surface of piezoelectric quartz crystal (PQC) to detect SARS-associated coronavirus (SARS-Cov), and adsorption of SARS antigen leads to change in the mass of PQC, thereby making a shift in resonant frequency (Fig. 11.10). In 2006, Velanki and Ji (2006) reported the second microcantileverbased piezoelectric immunosensor for the detection of feline infectious protein (FIP) which acts as a biomarker for coronavirus detection (Antiochia 2020).

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Fig. 11.8 Piezoelectric biosensors used for the diagnosis of cancer. (a) Schematic of ceramic resonator and piezoelectric biosensor setup (up) and photograph of fabricated PZT ceramic resonator (below) (Su et al. 2013). (b) Design and experimental setup of STFM (Sharma et al. 2019). (c) Piezoelectric microcantilever sensor (PEMS) for breast cancer diagnosis (Loo et al. 2011)

11.5.5 Wearable Health Monitoring Wearable devices have gained substantial interest for providing continuous and realtime physiological signals such as heart rate, step counter, calorie count, etc. Biosensors can be integrated with innovative wearable platforms to non-invasively monitor biomarkers in biofluids such as tears, saliva, sweat, interstitial fluid (ISI), etc. (Kim et al. 2019). There has been significant advancement in wearable biosensors for health monitoring and disease diagnostics (Zou et al. 2020). Piezoelectric biosensor units have been used as self-powered wearable electronic skin device to non-invasively detect lactate, glucose, urea, and uric acid by utilizing enzyme/ZnO nanowires. The mechanical motion of the body during exercise forms the basis of piezoelectric signal depending upon analyte sweat concentration. Figure 11.11(a) shows the flexible piezoelectric electronic skin adhered to the human wrist for the real-time monitoring of physiological conditions by analyzing perspiration components (Han et al. 2017). Scarpa et al. (2020) demonstrated a wearable piezoelectric mass biosensor to monitor sweat pH which helps in the detection of bacterial skin infections and body hydration. The device was fabricated by using

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Real-time monitoring and analysis of micropressure changes at outside of cardiovascular wall

Fig. 11.9 (a) Schematic of detection of TNFα by piezoelectric immunosensor (Pohanka 2018a, b). (b) Implantable piezoelectric biosensor to detect micropressure changes at cardiovascular walls (Li et al. 2019) Fig. 11.10 Schematic of adsorption mechanism of SARS-Cov (Zuo et al. 2004)

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Fig. 11.11 Wearable piezoelectric biosensors. (a) Self-powered wearable electronic skin device for the real-time monitoring of lactate, glucose, uric acid, and urea (Han et al. 2017). (b) Prototype of wearable in-ear pressure sensing device (Park et al. 2015). (c) Design and applications of textileZnO-based wearable piezoelectric biosensing device (Mao et al. 2019). (d) Wearable microfluidic cytometric system (Furniturewalla et al. 2018)

AlN membranes and polyimide substrate integrating with pH-responsive hydrogels. Piezoelectric thin film-based in-ear pressure sensing device was developed to monitor heart rate as shown in Fig. 11.11(b) (Park et al. 2015). A textile-ZnObased self-powered piezoelectric biosensing device has been reported to monitor the physiological conditions of athletes in real time like moving speed, frequency, joint angle, sweat, etc. by employing the coupling mechanism of piezoelectric effect and enzyme reaction (Fig. 11.11c) (Mao et al. 2019). A microfluidic cytometric system wearable on the wrist (Fig. 11.11d) was developed for the portable biomarker analysis for remote health monitoring (Furniturewalla et al. 2018). Wearable biosensor emerged as a promising point-of-care device owing to its portability, non-invasive procedure, low cost, high speed, and low power requirements.

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Moreover, the wearable devices can be made self-powered by integrating them with biomechanical energy harvesting technologies (Rodrigues et al. 2020).

11.5.6 Biomechanical Energy Harvesting Piezoelectric phenomenon has been widely used to scavenge the mechanical motion of the body into electric energy which is termed biomechanical energy harvesting. Biomechanical energy harvesting is a part of a paradigm shift that is on horizon to power bioelectronics making them self-powered devices (Gupta et al. 2020). Zhao et al. (2014) developed a self-powered piezoelectric biosensor based on ZnO nanowire nanogenerator that is capable of harvesting energy as well as acting as a biosensing device. The self-powered nano-system generated a piezoelectric output response corresponding to human immunoglobulin G (IgG).

11.6

Conclusions

Herein, piezoelectric biosensors were systematically summarised investigating its different types, design, material considerations and various applications in the field of healthcare with an intent to assist researchers for the development of smart and innovative biosensors. Piezoelectric biosensors form a group of analytical devices that has shown remarkable potential for early diagnosis and treatment of various diseases. Importantly, research advances of piezoelectric biosensors for detection of Alzheimer’s, cancer, coronavirus and cardiovascular diseases were discussed. Further, progress in piezoelectric biosensors in wearable health monitoring and biomechanical energy harvesting was investigated for realising non-invasive and selfpowered bio-sensing technologies.

11.7

Challenges and Future Scope

Despite incessant advancement in the development of piezoelectric biosensors in the field of healthcare, the availability of high-quality innovative nanomaterials and their complex mechanism of fabrication, tailoring, processing, interfacing, and characterization are some of the great challenges that need to be addressed for next-generation cost-effective biosensing technologies. A prospective research dimension could be to improve signal-to-noise ratio, enhancement in transduction mechanism, and signal amplification to realize commercial piezoelectric biosensors for rapid disease monitoring and diagnosis. Acknowledgments Akshpreet Kaur is thankful for the financial support in the form of DST-INSPIRE Fellowship (DST/INSPIRE/Fellowship/2018/IF190152) by the Department of Science and Technology (DST), Ministry of Science and Technology, Government of India. Dr. Parveen Kumar acknowledges DST, New Delhi, for providing INSPIRE Faculty grant.

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Low-Cost Paper-Based Analytical Devices and Their Application in Healthcare System

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Girish Chandra Mohanta and Satish Kumar Pandey

12.1

Introduction

In biomedical research, rapid, easy-to-perform, accurate, and low-cost detection of analytes is an important need for the on-site detection system. In clinical research laboratories, immunological assays are frequently utilized for the detection of biomarkers in biological fluids such as blood, serum, and urine, and they offer sensitive in addition to reliable results. Conventional enzyme-linked immunosorbent assay (ELISA) is used to quantitatively analyze analytes or specific biomarkers with consistent and accurate results. However, ELISA requires a skilled person to execute the experiments, assess the results, sophisticated and long procedure use of these analytical tools in a resource-limited laboratory is difficult (Nie et al. 2012). Hence, there is an urgent necessity for the development of user-friendly and economical detection systems to provide untrained operators with the capacity to easily detect analytes (e.g., protein, bacterial cells, virus, etc.) and assess the results in resourcelimited settings (Gong and Sinton 2017; Li et al. 2012; Nilghaz et al. 2016). In recent era, paper-based biosensors play a vital role in the area of immunodiagnostic/clinical diagnostics; include diagnosis of diseases, monitoring health conditions, detection of pathogens (e.g., bacteria, fungi) (Hu et al. 2014). Paper-based biosensors are also monitoring water and food safety and quality (Hu et al. 2014). In this context, paperbased microfluidic methods empower the fabrication of economical, simple, easy-toperform, and portable diagnostic test platforms. In this microfluidic technology uses

G. C. Mohanta Materials Science & Sensor Applications (MSSA), CSIR-Central Scientific Instruments Organizations (CSIR-CSIO), Chandigarh, India S. K. Pandey (✉) Materials Science & Sensor Applications (MSSA), CSIR-Central Scientific Instruments Organizations (CSIR-CSIO), Chandigarh, India Department of Biotechnology School of Life Sciences, Mizoram University Aizawl, Aizawl, India # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Patra et al. (eds.), Enzyme-based Biosensors: Recent Advances and Applications in Healthcare, https://doi.org/10.1007/978-981-15-6982-1_12

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paper as substrate to make microfluidic channels with patterning of hydrophobic materials on hydrophilic paper (Costa et al. 2014) and investigates biological substance in the blood, urine, saliva, sweat, tear etc. The sample is applied to the device which is wicked to a detection zone by capillary action without the need to use an external pump (Warren et al. 2014). Detection of interest of analyte from the sample is assisted by using a chemical reaction which brings a change in color, electrochemical properties, and light absorption or emission. Among these detection techniques, the most often used detection approach is based on colorimetric change. In this colorimetric change method, results can be easily assessed by the development of a color product made through ligand-analyte binding like antibody-antigen, which can be measured using handheld scanners (Park et al. 2013). Following are advantages of paper-based biosensors: (1) adsorption properties (2) high surface-tovolume ratio (3) capillary action (4) concordance with biological samples and (5) chemical functional groups for the immobilization of biological molecules such as proteins and antibodies (Pelton 2009; Cate et al. 2015). On other hand paper also permits for easy dispose via incineration. Moreover, paper matrix has the capability to store and transport reagents and reduce the necessity for users to handle chemical solutions (Singh et al. 2018). Diagnostics is the most significant step in the treatment of any disease. Globally, more than 6.0 billion people live in settings classified as low and middle wages (Sher et al. 2017) and they do not have access to the advance high-end medical services and diagnostic technologies for disease detection (Asghar et al. 2016; Safavieh et al. 2016). Therefore, it is an urgent need to develop economical and portable point-ofcare (POC) diagnostic devices, which can offer rapid and precise results. World Health Organization (WHO) made a vital policy and guidelines for future diagnostics using the ASSURED acronym. ASSURED stands for affordable, sensitive, specific, user-friendly, rapid and robust, equipment-free, and deliverable (Mabey et al. 2004). Rapid and on-site diagnostic devices provide a promising solution with various advantages, including affordability, sustainability, portability, disposability, and simplicity. Moreover, POC diagnostic tools are easy to handle along with minimal sample quantity requirement (Lee et al. 2010). The field of point of care has experienced great developments in the last few years and paper based microfluidic diagnostic test play a key role in the clinical and environmental diagnostics in resource-constrained settings (Novak et al. 2013; Safavieh et al. 2017). Disposable paper-based diagnostic tests are ideal candidates for point-ofcare diagnostic purposes, exclusively in personalized healthcare (Fig. 12.1). These POC tests are also suitable for the food industry, import and export industry, security, and food quality monitoring applications (López-Marzo and Merkoçi 2016; Sher et al. 2017).

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Fig. 12.1 Schematic lustrations of disposable paper-based diagnostic tests for point of care diagnostic device for exclusively in personalized healthcare

12.2

Paper-Based Point of Care Technology

The paper-based lateral flow assay (LFA)/dipstick test are well-known technology, used in various analytes detection in clinical setup. These paper based device are routinely used to detect interest of analytes in body fluid such as glucose and hormone in urine (Sher et al. 2017). For glucose monitoring in urine samples, urine is introduced to the dipstick and the resultant color change is assessed by comparing the results with the standard color chart of glucose level (Yetisen et al. 2013). On the other hand, other immunoassay such as Latex agglutination and radioimmunoassays were also established (Rivas et al. 2014). Subsequently the lateral flow technology was introduced in the field of healthcare sector and first time that was utilized in human pregnancy tests and this rapid home diagnostic test, have gained wide popularity (Ngom et al. 2010). Applications of lateral flow based immunoassays are used in several areas including food safety, quality of food, veterinary diagnostics and environmental monitoring (Yetisen et al. 2013). Poor detection limits and low sensitivities of LFAs restricted their utility and applications. Consequently, efforts are being made to overcome these limitations and for example wax pillars used as deferral barriers to upsurge the sensitivity of LFA (Sher et al. 2017).

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Paper-Based Microfluidic Technology

Recently, paper is using as a substrate for the fabrication of microfluidic device (Martinez et al. 2010). A paper based microfluidic device is inexpensive, easily available, disposable and biocompatible with several biological samples (Pelton 2009). Microfluidic device can also be used to conduct several biological assays simultaneously such as monitoring of nitrate in the saliva and uric acid in the biological samples (Li et al. 2010). Different Microfluidic device fabrication methods are used for the development of bioassay, which included photolithography (Martinez et al. 2008a, b), inkjet printing (Abe et al. 2008), polydimethylsiloxane (PDMS) plotting (Bruzewicz et al. 2008), wax printing, wax dipping (Songjaroen et al. 2011), wax screen printing (Dungchai et al. 2011), and plasma treatment (Li et al. 2008). It has been proposed that above fabrication methods are cost effective, simple, and easy to execute (Martinez et al. 2010).

12.4

Detection Methods

Different detection methods used in the development biosensor in healthcare sector. Detection techniques such as (a) colorimetric method, (b) chemiluminescence, (c) electrochemiluminescence, (d) fluorescence, and (e) electrochemical based techniques can be used in paper-based biosensors to distinguish the presence or absence of an analyte in the samples (Sher et al. 2017) Fig. 12.2. In sensor development, the above mentioned techniques have been widely used and it has been found that they provide sensitive and rapid results, compared to conventional methods such as the ELISA.

12.4.1 Colorimetric Methods Colorimetric based analysis is a most widely used method for quantification of concentration of a chemical element or chemical compound in a solution with the assistance of a color component. This method is suitable to both organic and inorganic compounds and could be used with or without an enzymatic step. This techniques employed to detect the presence and concentration of an analyte by estimating the color formation or color change by (a) direct imaging by means of a single-lens reflex (SLR) camera, mobile devices and low-cost desktop scanners in combination with software (MATLAB) for quantification (Ellerbee et al. 2009), or (b) Conventional spectrophotometers via assessing the absorbance of the sample at particular wavelengths. Colorimetric analysis is the most frequently used methods one as it provides precise results at a lower cost. Colorimetric assay, development of color or color change can be convinced via using enzyme, enzyme based immunoassay, gold nanoparticles (Sher et al. 2017; Lin et al. 2020).

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Fig. 12.2 Different detection methods and its mechanism. In colorimetric method (a), the signal is a colored precipitate product. In chemiluminescence (b), the reaction itself emits light. In fluorescence detection (c), the antibody is labeled with a fluorophore

12.4.1.1 Enzyme Based Detection Enzymatic detection is attained by way of a reaction between an enzyme and a specific substrate which makes an enzyme-substrate complex and produces a color change. (Nilghaz et al. 2016; Silveira et al. 2016). Proteins and glucose were detected in artificial urine samples by using photolithography fabricated paper devices (Martinez et al. 2008a, b). In the presence of the glucose oxidase enzyme, oxidation of glucose to gluconic acid, and production of hydrogen peroxide occurs. Enzyme horseradish peroxidase (HRP) is involved in the reduction of Hydrogen peroxide and oxidation of iodide to iodine, consequently leading into the formation of a brown color. Simultaneously, tetra-bromophenol blue (TBP) is used to detect proteins, and proteins are interacted electrostatically with TBP to change their color from yellow to blue. Another study, active ingredients of antibiotics beta-lactams was detected by way of a competitive enzymatic assay by nitrocefin, and resulted in color change indicating the presence of antibiotics (Boehle et al. 2018). 12.4.1.2 Paper-Based ELISA An immunoassay is a biological test and exhibits interaction between an antigen and an antibody, which is specific to a particular antigen. Traditional, Enzyme Linked immunosorbent Assay (ELISA) needs a huge volume of reagents, lengthy procedures, in addition to tedious washing steps. Paper-based ELISA contains a piece of filter paper, with well volumes as low as 3 μL. This approach is more advantageous owing to the enhanced adsorbent properties of paper, substantially

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smaller volume (1–5 μL) of sample constraint, also rapid blocking step. Cellulose fibers made-up paper greatly reduces reaction time due to high surface-to-volume ratio, and consequently cuts the diagnostic procedure of paper based ELISA, and is completed within an hour in comparison to conventional ELISA (took 4 h) (Cheng et al. 2010) IgG antibody was immobilized on paper, and bovine serum albumin (BSA) was used as blocking reagent. Then, IgG antibody interact with alkaline phosphatase (ALP)-conjugated IgG antibody (Zhu et al. 2018) Yellow colored substrate 5-bromo-4-chloro-3-indolyl phosphate/nitro blue tetrazolium (BCIP/ NBT) was introduced on the sample zone to form a conjugate, which subsequently made a purple precipitate. Obtained colorimetric result can be scanned by potable scanner and, which was then quantified using the suitable software.

12.4.1.3 Gold and Silver Nanoparticles Gold nanoparticles (GNPs) are commonly practiced to tag antibody as a detector molecule in immunoassay. Specific interactions of analyte (e.g., antigen) of interest with GNPs-tag antibody, a color formation is taken place due to aggregation of gold nanoparticles. Quantification of color information in which the pixel values correlate with analyte concentrations can be assessed by imaging software. Tsai et al. reported that diagnosis of tuberculosis was achieved by using gold nanoparticle-tagged antibodies (Tsai et al. 2017). Surface plasmon resonance (SPR) technique is used to quantify the changes in the aggregation properties of gold nanoparticles. Surface plasmon resonance (SPR) technique uses plasmons effect, it is a quantum wave produced once it is disturbed from their equilibrium with a large number of electrons. Researchers utilized the SPR method to study the consequence of a single-stranded nucleic acid hybridization with a target causing aggregation, and color change was measured by a mobile device or image scanner. In biosensor development, GNP play a significant role due to biological compatibility and high surface area for bioconjugation. In one of the study, it has been found that GNPs leak from the paper membranes during the washing step, to overcome this matter GNPs stabilize with chitosan molecules (Li et al. 2017). Silver nanoparticles (AgNPs) were also reported in paper-based sensor developments. In this direction, Ferreira et al. reported that silver AgNPs was used to assess the ascorbic acid (AA) by paperbased sensors (Ferreira et al. 2015). Quantifications of Ascorbic acid were evaluated by a color change from light yellow to grey, when it was reacted with AgNPs that were impregnated in the device. The color intensity or color change was measured through a mobile scanner or a custom made scanner that measures the transmittance of light, in the test zones of device (Fig. 12.3).

12.4.2 Chemiluminescence Chemiluminescence involves the emission of light, as the result of a chemical reaction, once reactive intermediate molecules produce through an emission upon returning to ground state from their excited state. Detection of uric acid by using chemiluminescent phenomena which used an enzyme based reaction that produced

Low-Cost Paper-Based Analytical Devices and Their Application. . .

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Fig. 12.3 Schematic illustration of a conventional LFA strip integrated SPR-based modular device

hydrogen peroxide as a by-product when decaying the substrate (Yu et al. 2011). Association of chemiluminescence technique with immunochemical assay is popularly known as a Chemiluminescence immunoassay (CLIA). Like with other immunoassays such as ELISA, CLIA uses chemical probes which can produce light emission by chemical reaction towards tagged antibodies. Recently, CLIA has expanded growing attention in various fields of sciences, including life science, medical diagnosis, pharmaceutical analysis, food safety and environmental monitoring owing to its high sensitivity and specificity. In addition to simple equipment and wide linear range of application make its more demanding techniques.

12.4.3 Fluorescence The detection of luminescence from fluorophores molecules is achieved resulting from interactions with the sample molecule by Fluorescence-based techniques. Fluorometry technique is used to estimate the intensity of fluorescence (Wu et al. 2018). Paper based testing device is reported which is based on the principles of fluorescence for the detection of a toxic compound hydrogen sulfide (H2S) (Petruci and Cardoso 2016). This paper-based device is made up of light emitting diode (LED) and spectrometer, along with a paper strip that is infused with fluorescein mercury acetate (FMA) on the surface. The reaction occurred between H2S and FMA was measured at 470 nm wavelength. It has been observed that the limit of

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detection of H2S gas was found to be three parts per billion (ppb) as well as response time of the device was within 60 s.

12.4.4 Electrochemistry Typically, electrochemical based biosensors/sensor involved three electrodes: (1) a working electrode, (2) a reference electrode, and (3) a counter electrode (Mettakoonpitak et al. 2016) Fig. 12.4. The sample is sensed while the electrolytic solution make connection between working electrode and counter electrode, its consequently provide current to the sample on the working electrode (Liana et al. 2012; Busa et al. 2016). These electrodes can be developed by using a screen printed method on nitrocellulose paper/plastic with carbon ink and silver/silver chloride ink (Nie et al. 2010). In recent years, graphite pencils are used as an additional source for fabrication of electrodes (Silveira et al. 2016). High concentrations of metals (lead and cadmium) in the living system can lead to tumor or cancer progression. Therefore, their detection is needed and critical for assessing altered health conditions, such heavy metal concentrations can be precisely detected with electrochemical techniques. Electrochemical approach has been utilized for the detection of cancer, where cancerous cells were tagged with gold nanoparticles (Lee et al. 2018). On other hand, potentiometric devices is also used to estimate the presence and absence of analytes and this can also be used for the quantification of analytes (Grieshaber et al. 2008). Additionally, conductometric based sensors can determine the current changes between electrode, once analyte interact with specific reagent on electrode. It has been reported that these types of electrochemical technique are mostly based on enzymatic reaction. Change in the conductance of solution via enzymatic reaction is used to estimate the amount of analytes (Grieshaber et al. 2008). Paper-based multi-analytes electrochemical sensors were utilized for detection of glucose, lactate, and uric acid (Zhao et al. 2015). Detection of these analytes based on corresponding enzymes and electrical signals were produced once electrontransfer mediators are deposited in test zones resultant with analytes. Generally, Fig. 12.4 Diagrammatic presentation of typical Screenprinted electrodes (SPEs)

Working Electrode

Counter Electrode Reference Electrode

Electrode Connector

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carbon electrodes were connected with screen-printed silver strips which assisted as contact pads for electrical interfacing with potentiostat via metal clips.

12.4.5 Electrochemiluminescence (ECL) Electrochemiluminescence is a type of electrochemical reactions in solutions at electrode surfaces and produced luminescence during electron-transfer reactions to form excited states that emit light. In this reaction, electrochemically produced intermediates involving an extremely exergonic reaction to generate an electronically excited state and emits light when letup to a lower-level state (Nie et al. 2012; Gong and Sinton 2017). In the mid-1960, first detailed ECL study was reported (Hu et al. 2014; Nilghaz et al. 2016). It has been stated that ECL has several benefits over electrochemistry chemiluminescence (CL), and photoluminescence (PL). First, ECL based electrochemical reaction permits the regulation of the time and position of the light emitting reaction on provided potential. Second, generation of excited states in ECL is achieved selectively organized by changing the electrode potentials and more selective than CL. Third, in various cases, ECL emitters could be regenerated after emission (Singh et al. 2018). An ECL technique does not require a light source in contrast to PL technique. Consequently, it provides several benefits to avoid issues for instance scattered light and luminescent impurities. It has been observed that ECL technique is more selective as well as it has less electrode fouling in comparison to electrochemical technique. This technique has been become popular in biosensor and analytical chemistry due to its following qualities (1) extensive adaptability, (2) simple instrument operation, (3) signal noise very low, (4) wider working range, (5) along with high sensitivity. ECL technology has been extensively used in different biological application such as immunoassay, food and water quality testing, and pharmaceutical investigation. ECL method has been used for wide range applications in different field of biological and chemical sciences specifically, in biosensing immunoassays and DNA Probe assays for clinical diagnostics. Likewise, ECL coupled with capillary electrophoresis detection immunosensors for biological and pharmaceutical analysis has been reported (Park et al. 2018). On the other hand ECL based biosensors and biosensing techniques have also been recognized by using nanomaterials and nanoparticles (Nie et al. 2012; Li et al. 2014; Zhang et al. 2019).

12.5

Applications of Paper-Based Diagnostics Test

12.5.1 Sensing Method Used in Microfluidic Paper-Based Analytical Devices Several sensing procedures have been established to measure the results of diagnostic tests and these sensing techniques are colorimetric, electrochemical, chemiluminescence (CL), electro-chemiluminescence (ECL), and fluorescence. In this section

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of book chapter, we focus on these sensing devices and methods. How these sensing procedures can be combined with the cellulose and flexible paper-based diagnostics devices.

12.5.2 Colorimetric Detection The ability of colorimetric diagnostic tests provide a yes/no or semiquantitative response. Microfluidic paper-based analytical devices (μPADs) have been extensively used for colorimetric based detection (Lee et al. 2018). This diagnostic test is based on reactions between the target molecules and chemical substances, and these chemical substances comprised acid–base indicators, dyes, antibody/antigen, aptamers and enzymes. For examples of this method, litmus paper is exploited to determine the pH value of any solution. Results obtained from this technique can be observed either directly with naked eye or software using electronic devices such as mobile or computer. Mobile or computer software is the ideal procedure because naked eye visualization is frequently affected by numerous factors like dissimilar lighting environments, variations in color perception, and the different colors of dry/wet papers (Lee et al. 2018) (Fig. 12.5).

Fig. 12.5 Development of Paper based Microfluidic device for multi-pathogens detection test using specific bioreceptors

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Measurement of the levels of glucose and protein in artificial urine was assessed by colorimetric method (Lee et al. 2018). Lately, a μPAD was employed to use the colorimetric technique for human papillomavirus (HPV)16 DNA detection by using cervical samples (Silveira et al. 2016). The detection device was made-up of paper and pressure sensitive adhesive sheets to extract, amplify, and detect nucleic acids from samples and can be used for rapid detection of cervical cancer in resource limited sites. This handy, economical, and disposable device can be also used in the remote and onsite detection. Furthermore, several sensing platforms have been documented to detect viruses and bacterial pathogens (Singh et al. 2018). These biosensors use modified gold nanoparticles with specific recognition molecules and are transferred to a nitrocellulose paper, where bacteria samples cause nanoparticles aggregation. Change in color of nanoparticles after aggregation can be observed by naked eye and the image of the nanoparticle aggregate spot can be captured by using a cellular phone camera. Generally, MATLAB techniques based image analysis tool used to quantify the color intensities of the image. Colorimetric Paper based microfluidic are often used for urine analysis. Recently, simultaneous detection of proteins and glucose in artificial urine has been reported by using colorimetric detection methods (Cretich et al. 2010). Positive results for the glucose assay is assessed via change in color from clear to brown, which is achieved due to the oxidation of iodide to iodine. In the protein assay, a positive result is revealed by color change from yellow to blue using tetrabromophenol blue reagent. Commercially available, rapid test for analysis of urinary protein is used colorimetric approach for the detection such as Chemstrip, AimStick, and Multistix (Hossain et al. 2009). Generally, a single indicator dye is used to detect a corresponding analyte on paper based microfluidic. However, a more precise technique has been established to quantity the concentration of a single analyte by the use of multiple indicators (Grieshaber et al. 2008). Different concentrations of single analyte are detected by use of various different indicators and results are demonstrated in the making of multiple colors corresponding to various analyte concentrations. On other hand, this detection approach also improves the ability to distinguish different concentration analytes with the visualization of color change. Selection of paper substrates and amount of reagents is a key factor in color development and consistency of the assay (Zhao et al. 2015). It has been found that thicker paper staff provides higher resistance towards the flow of solution and as consequence exhibit poor color development. Thinner paper substrates are used to overcome the high resistance in the flow of solution and better color read. It has been recommended that colorimetric assay process can considerably increase the sensitivity for POC assays development with the use of flexible transparent materials (Wu et al. 2018).

12.5.3 Electrochemical Detection Electrochemical techniques is appropriate for paper based POC assay due to its economical, portability, high selectivity, sensitivity, easy to execute, and minimal instrumentation (Ahmed et al. 2016). Electrochemical sensing assay has been used to

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Fig. 12.6 Illustrative representation of electrochemical detection with an enzyme-linked immunoassay

simultaneously to quantity the interest of molecules in the biological samples. In this assay, an electric current flow through the electrodes and the chemical reaction is occurred on the electrode and resultant a specific behavior in terms of signature signals. These sensors comprise of three electrodes: (1) a working electrode, (2) a reference electrode, and (3) a counter electrode (Li et al. 2011). Conductive ink was used to develop the electrochemical sensors on the paper substrates. For the development of screen printed electrode silver and graphene inks are mostly used (Li et al. 2011). On electrode strip, interest of analyte is detected at the working electrode and counter electrode is used to regulate the current flow via reference electrode (LópezMarzo and Merkoçi 2016). Typically, the reference electrode is made-up of AgCl/ Ag and help to maintain constant potential. Responsibility of the counter electrode is made a connection with the electrolyte solution and consequently that allows the electric current to flow in the working (Songjaroen et al. 2011). Electrochemical detection devices have been demonstrated to be cost-effective and simple for resource-constrained settings with using a mobile phone (Vella et al. 2012). Electrochemical paper-based using microfluidic device was used for the detection of glucose from the blood samples (Sununta et al. 2018). Electrochemical based immune assay was demonstrated for detection of four cancer biomarkers, such as antigen 153 (CA153), CEA, CA-125, and AFP (Martinez et al. 2010) Fig. 12.6. Electrochemical sensors are label-free and do not require a light source that makes it a smart way for POC applications.

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12.5.4 Chemiluminescence Detection Chemiluminescence (CL) is an emission of light due to chemical reaction, in this technique electrons move from an excited state to a lower energy level via conversion of chemical energy into light energy. Reaction of several compounds with hydrogen peroxide or oxygen is resulted into the compound decomposing and light being emitted (Im et al. 2016). For instance, reaction of organic reagent luminol (5-amino-2, 3-dihydro-1, 4-phthalazinedione, or 3-aminophthalhy-drazide) with hydrogen peroxide generated light. These techniques have several advantages such as low-cost equipment, wide range of detection, easy to perform and lower limits of detection. Fabrication of device for uric acid detection was established which is based on an enzymatic reaction, producing hydrogen peroxide in disintegration of the substrate. The generated peroxide react with rhodamine derivative in acidic medium resultant to produce CL (Sechi et al. 2013). The performance of device was evaluated with using various concentrations of uric acid solution in saline under optimized conditions. Microfluidic based sandwich CL-ELISA was executed for the simultaneous detection of various tumor. Validation of the performance of the device was assessed with various tumor antigens such as AFP, CA125, and CEA at different concentrations in phosphate-buffered saline (PBS) under homogenous conditions. The CL intensity varies linearly with the increasing concentrations of antigen with dynamic ranges.

12.5.5 Electro-chemiluminescence Detection Combination of chemiluminescence and electrochemical techniques based detection approach is known as Electro-Chemiluminescence (ECL) detection (ECL) methods. Effect of electrochemical reactions is the generation of light. ECL based biological assay have many advantages such as enhanced sensitivity and better dynamic concentration response range (Martinez et al. 2010). This technique also has some key quality like small sample volume, no need for light source and modest instrumentation (Im et al. 2016). ECL is extensively used technique in clinical diagnosis, and various commercial immunoassay are existing on the market for the diagnosis of communicable (infectious disease) and non-communicable disease (Yamada et al. 2014). ECL techniques has been integrated with paper-based immunodeviceand it was demonstrated to detect the presence of specific tumor biomarkers in the biological fluids (Yetisen et al. 2013, 2017). The performance of the ECL paperbased immunodevice was investigated via consuming 2.0 μL of standard specific tumor biomarkers sample solutions under the optimized conditions. The dynamic range of this method and signal-to-noise ratio make this technique more attractive in the field of clinical diagnostic and basic research laboratory.

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12.5.6 Fluorescence Fluorescence is an optical phenomenon in which compounds absorb energy in the form of photons and the emission of light by a compound. This technique of sensing of signal is established once interaction of target elements and fluorescent dyes known as fluorophores (Wang et al. 2016a; Cho et al. 2017). First time fluorescence method was demonstrated in paper microzone plates. Fluorescence involves three stages during the detection procedure such as (1) excitation, (2) lifetime (excitedstate), and (3) emission. The sensing technique comprises of (1) induces luminescence in a fluorophore by a source of light at a fixed wavelength, (2) isolation of emission photons from excitation photons, and (3), generation of an electrical signal after emission photons detection as an indicator. Addition of several fluorescent brightening agents can be used to fluoresce the paper. Though, these paper materials could increase the auto-fluorescence and consequence in false positives. One study, DNA has been effectively detected on paper strips which were immobilized with customized DNA oligonucleotides (Almeida et al. 2018). It has been observed that paper may serve as a future option for modest and economical approach for DNA detection. It was demonstrated that poly microgels tied with an oligonucleotide was spotted onto a paper strip and it was employed for the rolling circle amplification (RCA)–hybridization-based detection (Hu et al. 2017). The fluorescence intensities of paper were measured with and without DNA target in terms of relative intensities unit (RFU) and result obtained from the study quantitate DNA with a LOD of 100 pM. On the other hand, a paper microfluidic device was fabricated for the detection of lactoferrin in the tear sample and this techniques used the fluorescence signal which was emitted via the lactoferrin-terbium complexes to achieve antibodyfree biosensing (Hu et al. 2014).

12.6

Future of Paper-Based Diagnosis

The paper based device have truly changed the present-day of diagnostics approach in the field of biomedical research, fertility, DNA analysis, environmental monitoring and food safety (Skurtys and Aguilera 2008; Pelton 2009; Park et al. 2013; Warren et al. 2014; Sicard et al. 2015; Lantigua et al. 2017). Paper-based microfluidics diagnostics is also the most interesting technique for a large number of pharmaceutical industries and non-profit organizations, who attempt to develop POC diagnostic tests for resource-limited settings. Even though many POC diagnostic devices have been invented and established, for their commercialization it is mandatory to transition from academia to industry. In general, these paper-based diagnosis have the following limitations: (1) retention and evaporation of samples are major issues and can cause serious problems during the shipping process (Xia et al. 2016), (2) disparity in the specificity and sensitivity of paper-based POC device is the main worry of the modern era as it plays a vital role in avoiding false-positive results (Fobel et al. 2014), and (3) reagents used in these POC device, such as protein, carbohydrate, antigens, and antibodies, must be protect with the harsh

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environmental conditions met during transport, distribution and storage procedures (Hu et al. 2014; Gong and Sinton 2017). The Integration of digital microfluidics with paper is an alternate successful area to implement multifaceted and multistep tests. Paper based digital microfluidics can employ micro-to-nanometer-sized liquid samples on an array of electrodes using electric fields (Fobel et al. 2014). Movement of droplets from one electrode to another is generally known as electrowetting and this phenomenon involves electrostatic forces, which can be exploited to mix, dispense, split, and merge several liquid drops. There is an urgent need to develop paper-based digital devices using economical and scalable techniques various application in research and clinical healthcare such as ELISA. Paper-based digital devices can indeed rise in the field of POC in clinical diagnostics in future. In the recent era, another area of immense interest is evolved that involves smartphone and lens less imaging-based disease detection along with quantification (Wang et al. 2011). Market of smartphone is rising at unmatched pace and it is estimated that the number of smartphone user is increased to around 2.6 billion worldwide since 2020 (Wang et al. 2011; Sher et al. 2017; Cai et al. 2020; Mathaweesansurn et al. 2020). Recent smartphones are armed with high-resolution digital cameras and have advanced computing features and it can simply be integrated with paper-based microfluidic devices for resource-limit settings. They can also offer a practical solution for data acquisition and results investigation. Though, in the recent past limited efforts have been made to combine camera enable phones with paper-based microfluidics device. Further research should be executed in the near future to entirely operate their assistance to develop POC diagnostics in both resource-rich and resource-constrained setup. For disease diagnosis smartphones can be used for instant on-site detection and/or later expert opinion by medical expert, which quicken the clinical decision-making process. Paper is a made of nonhomogeneous medium of cellulose fibers and it is used to detection of complex analytes that is a challenging task (Fronczek et al. 2013; Park et al. 2013). Though, this non-homogeneity problem related with paper can be solved by smartphones device. The indefinite optical signals arising from non-homogenous cellulose fibers over a significant area can be reduce by smartphones. Moreover, continuous illumination situations can also equalize the signal alterations over a range of wavelengths by use of white LEDs. Interestingly, capturing of images without lens has arisen as another option for POC diagnostic devices and it is suitable for evolving imaging platforms with high resolution. This technology is also provides wide-ranging field-of-view that is appropriate to capture image with entire surface in few seconds (Ozcan and Demirci 2008). Complementary metaloxide semiconductor image and light source sensor is required for lens-less imaging and it is well-suited with cell-phone platforms. It has been demonstrated that smartphones integrated with microfluidics and nano-electronics, and it provides a bright future for technology-driven diagnostics in clinical setups. (Li and Diamandis 2016). With the advancement of smartphone detection technology that could be used and significantly reduced the several tasks such as detection, data processing, and power, overcome the complexity of the paper-based diagnostic devices (Ng and Wheeler 2015). For the development of smartphone based portable POC devices are

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urgent need at present era, for that joint efforts from scientist of different fields are required to overcome the existing problem during the development of POC devices (Wang et al. 2016b). The group effort between the academia and industry can provide to extend the impact of paper-based diagnostic procedures and it could be accomplished by way of beginning bilateral projects, contractual research, consulting engagements, and public–private partnerships in the field of paper-based POC diagnostics (Jokerst et al. 2012; Pronk et al. 2015).

12.7

Conclusion

Management for disease in resource-limited sites where current expensive diagnostic assays are not suitable, paper-based POC assays can offer an encouraging solution. These devices are portable, easy to execute, economical, and it can be very useful in POC testing even in the developed nations. These technologies are low-cost, easily made-up, and Eco-friendly and these features make them a suitable option for clinical applications. This book chapter presents the modern advancements associated to the production and sensing mechanisms of paper-based microfluidics and challenges related with these devices are also conferred in detail and future directions are offers. Though various fabrication and biosensing procedures have been projected and it is tested in laboratories or pathology. There is still scope for further improvements in specificity, sensitivity, and reliability. Before the commercialization of such devices and their widespread usage in real-world clinical applications.

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Nano-inspired Point-of-Care Enzyme-Based Wearable Biosensors for Global Health Care Vinay Kumar

13.1

13

and Kavita Arora

Introduction to Noninvasive Wearable Health Care Diagnosis

WHO in 2018 has issued statement, “Universal Health Coverage-Everyone, Everywhere” under thematic slogan “health for all”, considering the fact that that besides the 20% people who get hospitalized each year more than 75% of world population stays under sub-health category who need regular health checkups to sustain life health quality (Tseng et al. 2018; WHO 2018). In India, given the fact that the number of hospitalizations have increased from 16.6 to 37 in 1000 from 1994 to 2014 (Pandey et al. 2017), the remaining population who needs regular health checkups retains the major part among “The 5A’s challenges” (Awareness, Accessibility, Availability, Affordability, Accountability) of healthcare in India (Kasthuri 2018). The 5A’s challenges are in accordance with the 2018 World Health Organization theme emphasizes “Universal Health Coverage-everyone, everywhere,” and this throws that goal into clear perspective. This has drawn public attention throughout the world and hence urged researchers to develop personalized point-of-care diagnostic (PoC) methods/devices that can address the rising health care monitoring demands of the sub-health category preferably by using noninvasive samples. Availability of noninvasive easy to operate and economically viable devices to serve preventive and personalized real-time monitoring is expected to bring a

V. Kumar Department of Physiology and Cell Biology, Department of Internal Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, USA e-mail: [email protected] K. Arora (✉) Advanced Instrumentation Research Facility and School of Computational & Integrative Sciences, Jawaharlal Nehru University, New Delhi, India e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Patra et al. (eds.), Enzyme-based Biosensors: Recent Advances and Applications in Healthcare, https://doi.org/10.1007/978-981-15-6982-1_13

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paradigm shift to Personalized PoC clinical diagnosis. Given the fact that the concept of wearable sensors has already been accepted by the masses in the form of smart watches, fitness bands, spectacles, etc., the demand for such devices is on a sharp increasing trend. Noninvasive clinical diagnosis can be performed on almost all biological fluids which are secreted out from the body, e.g., sweat, saliva and sputum, urine, tears, nasal secretions/swabs, ear swabs, breath, etc. These biological fluids have been shown to contain various biomarkers which can be used for various clinical diagnosis applications. The PoC devices, which are used for detection of these noninvasive samples are known as biosensors. There had been various biosensor products which have evolved from simple detection strips, kits or handy devices to wearable devices which offer convenience, smaller size, high flexibility, and ability for long-term, in situ, in vivo monitoring (Yager et al. 2008) that have the capacity to be coupled to wireless communication. Their real-world examples included pregnancy detection kits, glucose monitoring strips, blood pressure, heartbeat, blood oxygen monitors, temperature monitors, etc. to high-end wearable devices such as apple watch, fitness tracker bands (from Fitbits, Samsung, titan, Mi, etc.). To achieve PoC devices various multidisciplinary approaches are being used to interface advanced nanofabrication technologies, microfluidics, nano materials, wireless signal transfer, and desired biological recognition materials. These next generation noninvasive wearable PoC biosensors require minimal energy and impose minimal risk of infection/adverse reaction, highly specific and user friendly (Kim et al. 2019). Although various choices of enzymatic and affinity interactions based bioelements are available for fabrication of these PoC biosensors, this chapter is an attempt to collate available wearable point-of-care (PoC) biosensor devices for noninvasive clinical diagnosis.

13.2

Biosensors

Biosensor is a gift of technological advancements, which is used to detect an analyte of interest using the interface of a biological component integrated to a physicochemical detector and transducer component (Hooda et al. 2018). However, as per IUPAC, a biosensor can be defined as “a device that uses specific biochemical reactions mediated by isolated enzymes, immunosystems, tissues, organelles or whole cells to detect chemical compounds usually by electrical, thermal or optical signals.” In simpler words, a biosensor device measures biological or chemical reactions occurring at the detector surface by generating signals proportional to the concentration of an analyte in the reaction (Bhalla et al. 2016). A sensor device may also be called a biosensor that determines concentration of biological substrates and other parameters even if they do not utilize a biological recognition element directly, e.g., synthetic or semisynthetic biomimetic polymers/molecules, e.g., peptide nucleic acids (PNA), molecular imprinted polymers (MIPs), synzymes, aptamers, engineered proteins, etc. (Arora et al. 2006).

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= Analyte

Transducer

Biorecognition

Impurity

Signal display/readout

Fig. 13.1 A schematic typical diagram of a biosensor. (Arora 2019 # John Wiley and Sons 2019)

As shown in Fig. 13.1, biosensor consists of three units: a biorecognition element, transducer, and an output device for signal display. This biorecognition element may consist of any biologically or chemically active molecule capable of specific biomolecular interaction with the analyte of interest. As mentioned above, such molecules may be synthetic molecules (peptide nucleic acids, synzymes, etc.) or polymers (biological/synthesized) or biomolecules such as enzymes, microorganisms/whole cells, tissues, organelles, antibodies, cell receptors, nucleic acids, engineered proteins, etc. Furthermore, transducer is a device used to change the energy type. A biosensor’s transducer translates the biorecognition event into an electrical signal. The term “signalization” describes the transformation of energy that occurs here. Depending on the type of transducer, the amount of analyte-bioreceptor interactions will be represented by an optical or electrical signal. Electrochemical, optical, piezoelectric (mass), and thermal transducers might be used in conjunction with biological recognition elements on a biolayer to pick up any signal. This is the most interesting feature of a biosensor device that depending on desired phenomena intended to be captured, a biorecognition element and a transducer interface can be tailor made as per customized requirements. Provided the fact that there are a wide range of materials available for transducer elements such as polymers, conducting polymers, biopolymers, nanomaterials, nanocomposites, etc., besides comprehensive options to choose a biorecognition element. That is proportional to the concentration of an analyte or a group of analytes. Such available opportunities to customize the performance of a biosensor provides various characteristics such as stability, shelf life, accuracy, response time, sensitivity, specificity, easy handling, and reproducibility. An additional component of a biosensor is an electrical system for transforming the signal into a form suitable for visual representation. Signal conditioning operations, such as amplification and digitization, are carried out through a network of intricate electrical circuits. The biosensor’s readout then provides a numerical representation of the processed signals. Biomolecular interaction occurring on the biolayer surface of a biosensor can be affinity or catalytic. Accordingly, a biosensor can be categorized as “affinity biosensor” or “catalytic biosensor” (Fig. 13.1). An affinity biosensor generally comprise of biorecognition element consisting of antigen–antibody interaction, DNA–DNA

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interaction, DNA–protein interaction, receptor–ligand interaction, synthetic/biomimetic receptor–ligand interactions, etc. while catalytic biosensors comprise of enzymes/synzymes or abzymes, some polymers, nanocomposites, etc. In a biosensor device, the biological component plays the most important role, i.e., biorecognition and it is important to note that most of the biological molecules have a very short lifetime in solution phase. Thus, to utilize their bioactivity for biosensor fabrication, they have to be fixed in a suitable matrix. These support matrices are required to play an important role to facilitate rapid signal/electron transfer and transduction along with providing a favorable measurement for adding stability and enhancing biological activity that can lead to rapid electron transfer at the electrode surface. The immobilization of the biological component against the environmental conditions results in decreased biomolecular activity. This biomolecular activity can be retained by the selection of desired matrix, immobilization method, and reaction conditions. Various immobilization techniques, e.g., physical adsorption, cross-linking, gel entrapment, covalent coupling, etc. have been used for immobilization. Next important role in a biosensor device is of a suitable immobilization matrix which will not only expected provide the stability to biomolecule and facilitate its bioactivity but is also expected to provide favorable environment for biomolecular recognition event along while playing a critical role for transferring/transducing the generated signal to the processor or display unit or wireless communication device. Therefore, choice of a suitable immobilization support matrix is inclining toward use of nanomaterials among available choices such as metallic surfaces, polymeric membranes, carbon materials, etc. Materials which have undisputedly shown to display ubiquitous applications owing to their unique optical, electronic, physical, or mechanical properties with bracing features compared to bulk characteristics are either nanomaterials or their composites. In fact, use of nanomaterials and nanofabrication technologies is heralded as one of the core tools and techniques that fits into any discipline of science and applications as potential contributors. Nanomaterials may be used in any form ranging from single, fused, aggregated, or agglomerated, or combinational, to various nano-shapes such as spherical, tubular, rods, wires, triangles, plates, sheets, ribbons and irregular or as components to composites, core-shells, etc. (Kumar and Arora 2020; Arora 2018). These varied features or composites impart differential performance features for desired applications to cater to customized needs of the application. Examples of these nanomaterials may include carbon-based materials, metals, organic, or inorganic materials. Common structural types of nanomaterials may include nanotubes, dendrimers, quantum dots, nanoparticles, nanowires, fullerenes, etc. Unique and exciting properties of nanomaterials are shown to be successfully implemented in varied scientific studies and applications ranging from building materials, electronics, cosmetics, pharmaceuticals, food processing, food quality control, medicine and clinical diagnostics, i.e., biosensors (Kumar and Arora 2020; Arora 2018, 2019). Indeed, both nanomaterials and nanofabrication technologies have revolutionized performance of biosensors through multidimensional roles ranging from providing:

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stable support for immobilization of biomolecular receptors, ease of immobilization, efficient signal transduction, signal enhancer, label, sometimes serving as sensing receptor, being able to work at nano/micro levels and ability of dealing/catering variety of signals (ranging from optical, magnetic, electrochemical, thermal, etc.) as per desired phenomena being measured. Already research journals are flooded with applications of nanomaterials of all disciplines, viz. chemical, physical, and life sciences. Application of nanomaterials in life science may include laboratory research, therapeutics, and clinical diagnostics for detection of diseases, pathogens, viruses, bacteria, fungi, plants, human, food quality control, environmental monitoring, etc. Therefore, nano inspired PoC biosensors having applications in the area such as clinical diagnosis, environmental monitoring, food quality, defence, drug discovery, and many more are serving the prime objective to improve the quality of life. As mentioned in the previous section, these biosensors sense target biomarkers in bodily fluids that are indicators of a disease (such as cell extracts, blood, urine, saliva, sweat, etc.). Owing to the vast range of research articles available in the field of nano inspired PoC biosensors, this chapter will be focused on comprehensive overview of noninvasive wearable PoC clinical diagnostic devices that originated from initial quest to monitor glucose levels in clinical samples.

13.3

Glucose Biosensors

One of the most prevailed lifelong chronic diseases in human is diabetes and conferring to International Diabetes Federation, approximately 463 million adults between ages 20 and 79 years, were living with diabetes in 2019, which is expected to grow 700 million by 2045 (The International Diabetes Federation (IDF) 2021). This disease is characterized by imbalance of glucose level in the body and mainly caused by genetic factors, immune disorders, and unhealthy lifestyle. Majority of detection technologies for monitoring glucose level rely on blood or serum analysis, hence noninvasive glucose sensing platforms are of great interest as it eliminates suffering from pain/infections produced by the invasive glucose sensing platforms (Tang et al. 2020). These noninvasive PoC sensors use other bodily fluids (such as sweat, saliva, tears, interstitial fluids) and do not come in contact with the blood removing the risk of exposure to the immune system (Juska and Pemble 2020a, b). Glucose sensing via biosensor-based platform was first reported by Clark and Lyons in 1962 (Clark Jr and Lyons 1962) that worked by converting electro-inactive substrates to electroactive substances. After patent in 1970, Clark’s technology was commercialized by Yellow Springs Instrument Company in 1975 to launch the first glucose analyzer which was based on the amperometric detection of hydrogen peroxide from the samples of whole blood. Down the line with enormous progress in the field of nanotechnology focused has been transferred to nanobiosensors in order to take advantage of some of the highly nature of the applied polymer. To name few such nano materials are carbon nanotube/nanoelectrode ensembles (Lin et al. 2004; Juska and Pemble 2020a, b), graphene (Baek et al.

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2020), carbon/graphene quantum dots (Buk and Pemble 2019; Buk et al. 2019), metal nanoparticles (Juska et al. 2019; Yuan et al. 2019), and dendrimers (Xu et al. 2009). Therefore, with the advancement in the field of nano-biosensors, it is interesting to summarize some of the wearable noninvasive glucose biosensors, which monitor glucose concentration from blood, interstitial fluid, urine, sweat, saliva, and tear. Li et al. (2019) conducted research on 12 randomly selected volunteers to measure blood glucose noninvasively by acquiring Raman spectra from microvessels in human nailfold and mean prediction performance of the 12 volunteers was obtained as an RMSEP (Root Mean Square Error of Prediction) of 0.45 mmol/L and R2 of 0.95 with no time lag (Li et al. 2019). System integrates an ultrathin (~3 μm) skin-like nanostructured biosensor with paper battery powered electrochemical twin channels which measure blood glucose from skin surface with high sensitivity (130.4 μA/mM), owing to its extreme conformability (Chen et al. 2017). Lipani et al. (2018) reported a noninvasive, interstitial fluid-borne glucose monitoring system based on a miniaturized pixel array platform which is able to track blood sugar in healthy human subjects (Lipani et al. 2018). Kim et al. (2018) developed an interesting wearable device to measure sweat alcohol/interstitial fluidglucose in human subjects having food/alcohol through sweat stimulation at anode, besides extraction of interstitial fluid at a cathode which allows monitor two epidermal biofluids at the same time (Kim et al. 2018). Choi et al. (2015) explained microwave noninvasive continuous blood glucose monitor sensor which encompasses two spatially disjoined split-ring resonators. In split-ring resonators, one ring cooperates with the variation in glucose level of the test sample, whereas the other ring used as a reference control (Choi et al. 2015). Baghelani et al. (2020) reported a highly sensitive, noninvasive biosensor with zero power consumption for real-time glucose (from interstitial fluid) monitoring using split-ring microwave resonators technology. This biosensor could detect glucose range of 2–25 mM and can be taped over the patient’s skin with reader which can be embedded in a smartwatch (Baghelani et al. 2020). He et al. (2019) described a unique sweat analysis patch from silk fabric-derived carbon textile which can be used to detect six health-related biomarkers such as glucose (detection range of 25–300 μM), lactate, ascorbic acid, uric acid, Na+, and K+ (He et al. 2019). Yu et al. (2020) accounted a flexible and fully perspiration-powered integrated battery-free electronic skin containing multimodal sensors with glucose detection range of 40–200 μM. Throughout extended physical activities, this biosensor can monitor not only metabolites such as urea, NH4+, glucose, pH but also the skin temperature and data can be wirelessly transmitted using Bluetooth (Yu et al. 2020). In another study, Bandodkar et al. (2019) presented a wireless electronic sensing platform with biofuel cells which combines chronometric microfluidic platforms with embedded colorimetric assays. This device can concurrently screen glucose (0–400 μM), sweat rate/ loss, pH, lactate, and chloride (Bandodkar et al. 2019). Lee et al. (2017) presented a wearable/disposable sweat-based glucose monitoring device which not only measure glucose (0–1 mM) but also feedback transdermal drug delivery can be performed (Lee et al. 2017). Bae et al. (2019) devised a microfluidics-integrated glucose (0.01–1 mM) sensor patch comprised of an omnidirectionally stretchable

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nanoporous gold electrochemical biosensor and a stretchable passive microfluidic device (Bae et al. 2019). Toi et al. (2019) displayed an electrochemical sensor patch with Au nanowrinkles partly cover the reduced graphene oxide (rGO)/polyurethane composite fiber. This biosensor is nonenzymatic, and it can continuously detect glucose levels (0–1.71 mM) in sweat (Toi et al. 2019). Zhao et al. (2019a, b) demonstrated an elastic gold fiber-based three-electrode electrochemical biosensor which can achieve a linear range of 0–500 μM and a sensitivity of 11.7 μA mM1 cm-2. This nano biosensor utilizes highly stretchable fiber with high conductivity, facile enzyme immobilization, and strain-insensitive properties (Zhao et al. 2019a, b). Emaminejad et al. (2017) studied perspiration-based wearable biosensors with electrochemically enhanced iontophoresis interface to detect/measure glucose 0–100 μM in sweat (Emaminejad et al. 2017). Arakawa et al. (2020) developed a wearable cellulose acetate-coated mouthguard biosensor for salivary glucose (1.75–10,000 μM) measurement, in vivo (Arakawa et al. 2020). Furthermore, Jung et al. (2017) developed a lab-on-a-chip device to measure glucose (1–10 mg/dL) in saliva based on micro-electro-mechanical system and optical measurement technology (Jung et al. 2017). Moreover, Park et al. (2018) fabricated of a soft, wireless power transfer circuit smart contact lens which can monitor glucose (0–0.9 mM) in real time in tears by exploiting transparent and stretchable nanostructures (Park et al. 2018). Continuous glucose monitoring with the use of smartphones is also a need of our time. To achieve this goal, Lin et al. (2018) devised a noninvasive, nonenzymatic and continuous glucose (0–20 mM) detection with phenylboronic acid (PBA)-based HEMA contact lens and data can be seen on smartphone (Lin et al. 2018). In another interesting study, Elsherif et al. (2018) developed wearable contact lens optical sensor with photonic microstructure printed on a glucose-selective hydrogel film functionalized with phenylboronic acid for the nonstop quantification of glucose (0–50 mM) at physiological conditions (Elsherif et al. 2018). Meanwhile, an another study to develop glucose biosensor, Zhang et al. (2020) copolymerized a rigid phenylboronic acid-containing graphene oxide-based monomer with a glucosesensitive monomer (i.e., 3-acrylamidophenylboronic acid (3-APBA)) onto a double bond-modified quartz crystal microbalance chip to fabricate a hybrid hydrogelcoated quartz crystal microbalance sensor which can be employed to monitor glucose (0–36 mg/L) (Zhang et al. 2020). Further sections are devoted to wearable biosensors for a variety of clinically relevant parameters, including glucose, in addition to many others, in light of the enormous advances made in glucose sensing.

13.4

Noninvasive PoC Wearable Biosensors

With the rising demands to pave the way toward achieving easy and convenient accessibility to gather information about levels of biomarkers for clinical diagnostic purposes, alternative biological fluids which are secreted out of the body are being given attention. These fluids include sweat, saliva, sputum, urine, tears, nasal secretions/swabs, ear swabs, and breath, etc. An increasing number of studies are being conducted in the field of clinical diagnosis to elucidate the connection between

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Table 13.1 Typical composition of body fluids (Corrie et al. 2015 # Royal Society of Chemistry 2015)

Body fluid Blood

Sampling techniques Needle, lancet

pH 7.35–7.45

Unique proteins (%, in comparison to plasma) NA

Saliva

Swab

6.2–7.4

38, 31

0.2–5 mg mL-1

Urine

Passive collection or catheter Lumbar puncture

4.5–8.0

30

7.31–7.35

40, 28

6.5–7.5 7.5–7.6 4.0–6.8 7.2–7.4

34 – 20 32