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ZEYNEP ALTINTAS, PhD, is the head of the Biosensors and Receptor Development Group at the Technical University of Berlin, Germany. She serves as an expert reviewer for EU and Wisconsin Groundwater Coordinating Council (USA) funded projects, in addition to acting as a reviewer for several important journals in her areas of expertise. She is also a member of the Royal Society of Chemistry (RSC).
List of Contributors xi
Preface xv
Acknowledgments xvii
Section 1 Introduction to Biosensors, Recognition Elements, Biomarkers, and Nanomaterials 1
1 General Introduction to Biosensors and Recognition Receptors 3Frank Davis and Zeynep Altintas
1.1 Introduction to Biosensors 3
1.2 Enzyme- Based Biosensors 4
1.3 DNA- and RNA-Based Biosensors 5
1.4 Antibody-Based Biosensors 7
1.5 Aptasensors 8
1.6 Peptide-Based Biosensors 10
1.7 MIP-Based Biosensor 11
1.8 Conclusions 12
References 13
2 Biomarkers in Health Care 17Adama Marie Sesay, Pirkko Tervo, and Elisa Tikkanen
2.1 Introduction 17
2.2 Biomarkers 18
2.2.1 Advantage and Utilization of Biomarkers 18
2.2.2 Ideal Characteristics of Biomarkers 19
2.3 Biological Samples and Biomarkers 20
2.4 Personalized Health and Point-of-Care Technology 22
2.5 Use of Biomarkers in Biosensing Technology 24
2.6 Biomarkers in Disease Diagnosis 26
2.7 Conclusions 29
References 30
3 The Use of Nanomaterials and Microfluidics in Medical Diagnostics 35Jon Ashley and Yi Sun
3.1 Introduction 35
3.2 Nanomaterials in Medical Diagnostics (Bottom-Up Approach) 36
3.2.1 Carbon Nanomaterials 37
3.2.2 Metallic Nanoparticles 39
3.2.2.1 Quantum Dots 39
3.2.2.2 Magnetic Nanoparticles (Fe2O3, FeO, and Fe3O4) 41
3.2.2.3 Gold Nanoparticles 41
3.2.2.4 Silver Nanoparticles 42
3.2.2.5 Nanoshells 42
3.2.2.6 Nanocages 43
3.2.2.7 Nanowires 43
3.2.3 Polymer-Based Nanoparticles 44
3.3 Application of Microfluidic Devices in Clinical Diagnostics (Top-Down Approach) 45
3.3.1 Unique Features of Microfluidic Devices 45
3.3.2 Applications of Microfluidic Devices in Medical Diagnostics 46
3.3.2.1 Types of Microfluidic POC Devices 47
3.3.2.2 Benchtop Microfluidic Instruments 47
3.3.2.3 Small, Lightweight Microfluidic Devices 49
3.3.2.4 Simple Un-instrumented Microfluidic Systems 50
3.4 Integration of Microfluidics with Nanomaterials 52
3.5 Future Perspectives of Nanomaterial and Microfluidic-Based Diagnostics 53
References 54
Section 2 Biosensor Platforms for Disease Detection and Diagnostics 59
4 SPR-Based Biosensor Technologies in Disease Detection and Diagnostics 61Zeynep Altintas and Wellington M. Fakanya
4.1 Introduction 61
4.2 Basic Theoretical Principles 63
4.3 SPR Applications in Disease Detection and Diagnostics 66
4.3.1 SPR Biosensors in Cancer Detection 66
4.3.2 SPR Sensors in Cardiac Disease Detection 68
4.3.3 SPR Sensors in Infectious Disease Detection 71
4.4 Conclusions 72
References 74
5 Piezoelectric-Based Biosensor Technologies in Disease Detection and Diagnostics 77Zeynep Altintas and Noor Azlina Masdor
5.1 Introduction 77
5.2 QCM Biosensors 78
5.3 Disease Diagnosis Using QCM Biosensors 80
5.3.1 Cancer Detection Using QCM Biosensors 82
5.3.2 Cardiovascular System Disorder Detection Using Biosensors 85
5.3.3 Pathogenic Disease Detection Using QCM Biosensors 88
5.4 Conclusions 90
References 91
6 Electrochemical-Based Biosensor Technologies in Disease Detection and Diagnostics 95Andrea Ravalli and Giovanna Marrazza
6.1 Introduction 95
6.2 Electrochemical Biosensors: Definitions, Principles, and Classifications 96
6.3 Biomarkers in Clinical Applications 102
6.3.1 Electrochemical Biosensors for Tumor Markers 102
6.3.2 Electrochemical Biosensors for Cardiac Markers 110
6.3.3 Electrochemical Biosensors for Autoimmune Disease 115
6.3.4 Electrochemical Biosensors for Autoimmune Infectious Disease 116
6.4 Conclusions 118
References 118
7 MEMS-Based Cell Counting Methods 125Mustafa Kangul, Eren Aydin, Furkan Gokce, Ozge Zorlu, Ebru Ozgur, and Haluk Kulah
7.1 Introduction 125
7.2 MEMS-Based Cell Counting Methods 126
7.2.1 Optical Cell Counting Methods 126
7.2.1.1 Quantification of the Cells by Detecting Luminescence 127
7.2.1.2 Quantification of the Cells via High-Resolution Imaging Techniques 130
7.3 Electrical and Electrochemical Cell Counting Methods 131
7.3.1 Impedimetric Cell Quantification 133
7.3.2 Voltammetric and Amperometric Cell Quantification 135
7.4 Gravimetric Cell Counting Methods 136
7.4.1 Deflection-Based Cell Quantification 136
7.4.2 Resonant-Based Cell Quantification 138
7.4.2.1 Theory of the Resonant-Based Sensors 138
7.4.2.2 Actuation and Sensing Methods of Resonators in MEMS Applications 140
7.4.2.3 Resonator Structure Types Used for Cell Detection Applications 145
7.5 Conclusion and Comments 149
References 151
8 Lab-on-a-Chip Platforms for Disease Detection and Diagnosis 155Ziya Isiksacan, Mustafa Tahsin Guler, Ali Kalantarifard, Mohammad Asghari, and Caglar Elbuken
8.1 Introduction 155
8.2 Continuous Flow Platforms 156
8.3 Paper-Based LOC Platforms 161
8.4 Droplet-Based LOC Platforms 166
8.5 Digital Microfluidic-Based LOC Platforms 169
8.6 CD-Based LOC Platforms 172
8.7 Wearable LOC Platforms 174
8.8 Conclusion and Outlook 176
References 177
Section 3 Nanomaterial's Applications in
Biosensors and Diagnostics 183
9 Applications of Quantum Dots in Biosensors and Diagnostics 185Zeynep Altintas, Frank Davis, and Frieder W. Scheller
9.1 Introduction 185
9.2 Quantum Dots: Optical Properties, Synthesis, and Surface Chemistry 186
9.3 Biosensor Applications of QDs 187
9.4 Other Biological Applications of QDs 191
9.5 Water Solubility and Cytotoxicity 194
9.6 Conclusion 196
References 197
10 Applications of Molecularly Imprinted Nanostructures in Biosensors and Diagnostics 201Deniz Aktas-Uygun, Murat Uygun, and Sinan Akgol
10.1 Introduction 201
10.2 Molecular Imprinted Polymers 202
10.3 Imprinting Approaches 204
10.4 Molecularly Imprinted Nanostructures 205
10.5 MIP Biosensors in Medical Diagnosis 207
10.6 Diagnostic Applications of MIP Nanostructures 210
10.7 Conclusions 212
References 213
11 Smart Nanomaterials: Applications in Biosensors and Diagnostics 219Frank Davis, Flavio M. Shimizu, and Zeynep Altintas
11.1 Introduction 219
11.2 Metal Nanoparticles 221
11.3 Magnetic Nanoparticles 226
11.4 Carbon Nanotubes 231
11.5 Graphene 235
11.6 Nanostructured Metal Oxides 242
11.7 Nanostructured Hydrogels 247
11.8 Nanostructured Conducting Polymers 254
11.9 Conclusions and Future Trends 260
References 262
12 Applications of Magnetic Nanomaterials in Biosensors and Diagnostics 277Zeynep Altintas
12.1 Introduction 277
12.2 MNP-Based Biosensors for Disease Detection 279
12.3 MNPs in Cancer Diagnosis and Therapy 284
12.4 Cellular Applications of MNPs in Biosensing, Imaging, and Therapy 289
12.5 Conclusions 290
References 291
13 Graphene Applications in Biosensors and Diagnostics 297Adina Arvinte and Adama Marie Sesay
13.1 Introduction 297
13.2 Graphene and Biosensors 298
13.2.1 Structure 298
13.2.2 Preparation 299
13.2.3 Properties 301
13.2.4 Commercialization in the Field of Graphene Sensors 302
13.2.5 Latest Developments in Graphene-based Diagnosis 303
13.3 Medical Applications of Graphene 303
13.3.1 Electrochemical Graphene Biosensors for Medical Diagnostics 304
13.3.1.1 Glucose Detection 304
13.3.1.2 Cysteine Detection 307
13.3.1.3 Cholesterol Detection 309
13.3.1.4 Hydrogen Peroxide (H2O2) 310
13.3.1.5 Glycated Hemoglobin 312
13.3.1.6 Neurotransmitters 312
13.3.1.7 Amyloid-Beta Peptide 315
13.3.2 Electrochemical Graphene Aptasensors 316
13.3.2.1 Nucleic Acids 316
13.3.2.2 Cancer Cell 318
13.3.3 Optical Graphene Sensors for Medical Diagnostics 319
13.4 Conclusions 322
Acknowledgments 322
References 322
Section 4 Organ-Specific Health Care Applications for Disease Cases Using Biosensors 327
14 Optical Biosensors and Applications to Drug Discovery for Cancer Cases 329Zeynep Altintas
14.1 Introduction 329
14.2 Biosensor Technology and Coupling Chemistries 332
14.3 Optical Biosensors for Drug Discovery 335
14.4 Computational Simulations and New Approaches for Drug-Receptor Interactions 341
14.5 Conclusions 343
References 344
15 Biosensors for Detection of Anticancer Drug-DNA Interactions 349Arzum Erdem, Ece Eksin, and Ece Kesici
15.1 Introduction 349
15.2 Electrochemical Techniques 351
15.3 Optical Techniques 356
15.4 Electrochemical Impedance Spectroscopy Technique 358
15.5 QCM Technique 360
15.6 Conclusions 361
Acknowledgments 361
References 361
Index
Frank Davis1 and Zeynep Altintas2
1 Department of Engineering and Applied Design, University of Chichester, Chichester, UK
2 Technical University of Berlin, Berlin, Germany
There are laboratory tests and protocols for the detection of various biomarkers, which can be used to diagnose heart attack, stroke, cancer, multiple sclerosis, or any other conditions. However, these laboratory protocols often require costly equipment, and skilled technical staff, and hospital attendance and have time constraints. Much cheaper methods can provide cost-effective analysis at home, in a doctor's surgery, or in an ambulance. Rapid diagnosis will also aid in the treatment of many conditions. Biosensors generically offer simplified reagentless analyses for a range of biomedical [1-8] and industrial applications [9, 10]. Due to this, biosensor technology has continued to develop into an ever-expanding and multidisciplinary field during the last few decades.
The IUPAC definition of a biosensor is "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." From this definition, we can gain an understanding of what a biosensor requires.
Most sensors consist of three principal components:
There exist many methods for detecting binding events such as electrochemical methods including potentiometry, amperometry, and AC impedance; optical methods such as surface plasmon resonance; and piezoelectric methods that measure mass changes such as quartz crystal microbalance (QCM) and surface acoustic wave techniques. A detailed description of these would be outside the remit of this introduction, but they are described in many reviews and elsewhere in this book. Instead this chapter focuses on introducing the recognition receptors used in biosensors.
Leyland Clark coated an oxygen electrode with a film containing the enzyme glucose oxidase and a dialysis membrane to develop one of the earliest biosensors [11]. This could be used to measure levels of glucose in blood; the enzyme converted the glucose to gluconolactone and hydrogen peroxide with a concurrent consumption of oxygen. The drop in dissolved oxygen could be measured at the electrode and, with careful calibration, levels of blood glucose calculated. This led to the widespread use of enzymes in biosensors, mainly driven by the desire to provide detection of blood glucose. Diabetes is one of the major health issues in the world today and is predicted to affect an estimated 300 million people by 2045 [12]. The world market for biosensors was approximately $15-16 billion in 2016. In 2009 approximately half of the world biosensor market was for point-of-care applications and about 32% of the world commercial market for blood glucose monitoring [13].
Enzymes are excellent candidates for use in biosensors, for example, they have high selectivities; glucose oxidase will only interact with glucose and is unaffected by other sugars. Being highly catalytic, enzymes display rapid substrate turnovers, which is important since otherwise they could rapidly become saturated or fail to generate sufficient active species to be detected. However, they demonstrate some disadvantages: for instance, a suitable enzyme for the target of interest may simply not exist. Also enzymes can be difficult and expensive to extract in sufficient quantities and can also be unstable, rapidly denaturing, and becoming useless. They can also be subject to poisoning by a variety of species. Moreover, detection of enzyme turnover may be an issue, for instance, in the glucose oxidase reaction; it is possible to directly electrochemically detect either consumption of oxygen [11] or production of hydrogen peroxide. However in samples such as blood and saliva, there can be other electroactive substances such as ascorbate, which also undergo a redox reaction and lead to false readings. These types of biosensors are often called "first-generation biosensors." To address this issue of interference, a second generation of glucose biosensors was developed where a small redox-active mediating molecule such as a ferrocene derivative was used to shuttle electrons between the enzyme and an electrode [14]. The mediator readily reacts with the enzyme, thereby avoiding competition by ambient oxygen. This allowed much lower potentials to be used in the detection of glucose, thereby reducing the problem of oxidation of interferents and increasing signal accuracy and reliability. Figure 1.1 shows a schematic of a second-generation glucose biosensor.
Figure 1.1 Schematic of a second-generation biosensor.
Third-generation biosensors have also been developed where the enzyme is directly wired to the electrode, using such materials as osmium-containing redox polymers [15] or conductive polymers such as polyaniline [16]. More recently nanostructured materials such as metal nanoparticles, carbon nanotubes, and graphene have been used to facilitate direct electron transfer between the enzyme and the electrode as described in later chapters. As an alternative to glucose oxidase, sensors based on glucose dehydrogenase have also been developed.
The techniques for glucose sensing using glucose oxidase can be applied to almost any oxidase enzymes, allowing sensors to be developed based on cholesterol oxidase, lactate oxidase, peroxidase enzymes, and many others. Sensors have also been constructed using urease, which converts urea to ammonia, causing a change in local pH that can be detected potentiometrically or optically by combining the enzyme with a suitable optical dye. Enzyme cascades have also been developed; for example, cholesterol esters can be determined using electrodes containing cholesterol esterase and cholesterol oxidase. Applications of enzyme-containing biosensors have been widely reviewed [16-18].
DNA is contained within all living cells as a blueprint for making proteins, and it can be thought of as a molecular information storage device. RNA also has a wide number of applications in living things, including acting as a messenger between DNA and the ribosomes that synthesize proteins and as a regulator of gene expression. Both DNA and RNA are polymeric species based on a sugar-phosphate backbone with nucleic bases as side chains, in DNA, namely, adenine, cytosine, guanine, and thymine. In RNA uracil is utilized instead of thymine. It is the specific binding between base pairs, that is, guanine to cytosine or adenine to thymine (uracil), that determine the structure of these polymers, in the case of DNA leading to a double helix structure (Figure 1.2) [19].
Figure 1.2 Schematic of interstrand binding in DNA.
DNA sensors are usually of a format where one oligonucleotide chain is bound to a suitable transducer, that is, an electrode, surface plasmon resonance (SPR) chip, quartz crystal microbalance (QCM), and so on, and is exposed to a solution containing an oligonucleotide strand of interest [20]. The surface-bound oligonucleotide is selected to be complementary to the oligonucleotide of interest, and the bound and solution strands will undergo sequence-specific hybridization as the recognition event.
An in-depth review of DNA sensing is outside the scope of this introduction and has been reviewed elsewhere [20-24]; however, a few examples are given here. A method based on ruthenium-mediated guanine oxidation allowed selective electrochemical detection of messenger RNA from tumors at 500?zmol?L-1 levels [25]. A sandwich-type assay using magnetic beads and fluorescence analysis utilized a complementary nucleotide to dengue fever virus RNA to allow detection at levels as low as 50?pmol?L-1 [26]. Five different probe DNAs could be immobilized onto an SPR-imaging chip and simultaneously used to determine binding of RNA sequences found in several pathogenic bacteria such as Brucella abortus, Escherichia coli, and Staphylococcus aureus [27] for use in food safety.
Antibodies are natural Y-shaped proteins produced by living systems, usually as a defense mechanism against invading bacteria or viruses. They bind to specific species (antigens) with an extremely high degree of specificity by a mixture of hydrogen bonds and other non-covalent interactions, with the binding taking place in the cleft of the protein molecule...
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