Micro- and Nanosystems for Biotechnology

by Love, J. Christopher

• ISBN13: 9783527332816
• ISBN10: 3527332812
• Edition: 1st
• Format: Hardcover
• Copyright: 2016-08-08
• Publisher: Wiley-Blackwell

Summary

Emphasizing their emerging capabilities, this volume provides a strong foundation for an understanding of how micro- and nanotechnologies used in biomedical research have evolved from concepts to working platforms.

Volume editor Christopher Love has assembled here a highly interdisciplinary group of authors with backgrounds ranging from chemical engineering right up to materials science to reflect how the intersection of ideas from biology with engineering disciplines has spurred on innovations. In fact, a number of the basic technologies described are reaching the market to advance the discovery and development of biopharmaceuticals.

The first part of the book focuses on microsystems for single-cell analysis, examining tools and techniques used to isolate cells from a range of biological samples, while the second part is dedicated to tiny technologies for modulating biological systems at the scale of individual cells, tissues or whole organisms. New tools are described which have a great potential for (pre)clinical development of interventions in a range of illnesses, such as cancer and neurological diseases.

Besides describing the promising applications, the authors also highlight the ongoing challenges and opportunities in the field.

Author Biography

J. Christopher Love is associate professor in chemical engineering at the Koch Institute for Integrative Cancer Research at the Massachusetts Institute of Technology(MIT, USA). He is also an associate member at the Eli and Edythe L. Broad Institute, and at the Ragon Institute of MGH, MIT, and Harvard (USA). Dr. Love received his Ph.D. in 2004 at Harvard University (USA). He extended his research into immunology at Harvard Medical School from 2004-2007. His research centers on using simple microsystems to monitor cells from clinical samples in human disease, and on developing new approaches to manufacture biologic drugs efficiently and affordably. Dr. Love was named a Dana Scholar for Human Immunology and a Keck Distinguished Young Scholar in Medical Research in 2009. He is also a Camille Dreyfus Teacher-Scholar.

Sang Yup Lee is Distinguished Professor at the Department of Chemical and Biomolecular Engineering at the Korea Advanced Institute of Science and Technology (KAIST). He is currently the Director of the Center for Systems and Synthetic Biotechnology, Director of the BioProcess Engineering Research Center, and Director of the Bioinformatics Research Center. He has published more than 500 journal papers, 64 books and book chapters, and more than 580 patents (either registered or applied). He received numerous awards, including the National Order of Merit, the Merck Metabolic Engineering Award, the ACS Marvin Johnson Award, Charles Thom Award, Amgen Biochemical Engineering Award, Elmer Gaden Award, POSCO TJ Park Prize, and HoAm Prize. He currently is Fellow of American Association for the Advancement of Science, the American Academy of Microbiology, American Institute of Chemical Engineers, Society for Industrial Microbiology and Biotechnology, American Institute of Medical and Biological Engineering, the World Academy of Science, the Korean Academy of Science and Technology, and the National Academy of Engineering of Korea. He is also Foreign Member of National Academy of Engineering USA. He is currently honorary professor of the University of Queensland (Australia), honorary professor of the Chinese Academy of Sciences, honorary professor of Wuhan University (China), honorary professor of Hubei University of Technology (China), honorary professor of Beijing University of Chemical Technology (China), and advisory professor of the Shanghai Jiaotong University (China). Lee is the Editor-in-Chief of the Biotechnology Journal and Associate Editor and board member of numerous other journals. Lee is currently serving as a member of Presidential Advisory Committee on Science and Technology (Korea).

Jens Nielsen is Professor and Director to Chalmers University of Technology (Sweden) since 2008. He obtained an MSc degree in Chemical Engineering and a PhD degree (1989) in Biochemical Engineering from the Technical University of Denmark (DTU) and after that established his independent research group and was appointed full Professor there in 1998. He was Fulbright visiting professor at MIT in 1995-1996. At DTU, he founded and directed the Center for Microbial Biotechnology. Jens Nielsen has published more than 350 research papers, co-authored more than 40 books and he is inventor of more than 50 patents. He has founded several companies that have raised more than 20 million in venture capital. He has received numerous Danish and international awards and is member of the Academy of Technical Sciences (Denmark), the National Academy of Engineering (USA), the Royal Danish Academy of Science and Letters, the American Institute for Medical and Biological Engineering and the Royal Swedish Academy of Engineering Sciences.

Professor Gregory Stephanopoulos is the W. H. Dow Professor of Chemical Engineering at the Massachusetts Institute of Technology (MIT, USA) and Director of the MIT Metabolic Engineering Laboratory. He is also Instructor of Bioengineering at Harvard Medical School (since 1997). He received his BS degree from the National Technical University of Athens and his PhD from the University of Minnesota (USA). He has co-authored approximately 400 research papers and 50 patents, along with the first textbook on Metabolic Engineering. He has been recognized by numerous awards from the American Institute of Chemical Engineers (AIChE) (Wilhelm, Walker and Founders awards), American Chemical Society (ACS), Society of industrial Microbiology (SIM), BIO (Washington Carver Award), the John Fritz Medal of the American Association of Engineering Societies, and others. In 2003 he was elected member of the National Academy of Engineering (USA) and in 2014 President of AIChE.

Table of Contents

List of Contributors XI

About the Series Editors XVII

Preface XIX

Part I Microsystems for Single-Cell Analysis 1

1 Types of Clinical Samples and Cellular Enrichment Strategies 3
KohMeng Aw Yong, Zeta Tak For Yu, Krystal Huijiao Guan, and Jianping Fu

1.1 Introduction 3

1.2 Types of Clinical Samples 4

1.2.1 Solid Clinical Samples 4

1.2.1.1 Cellular Subtypes Found in Solid Clinical Samples 5

1.2.2 Liquid Clinical Samples and Cellular Subtypes 8

1.2.2.1 Blood 8

1.2.2.2 Bone Marrow 9

1.2.2.3 Placental or Umbilical Cord Blood 10

1.2.2.4 Urine 10

1.2.2.5 Cerebrospinal Fluid (CSF) 10

1.2.2.6 Saliva 11

1.3 Sample Processing and Conventional Methods of Cell Enrichment 11

1.3.1 Processing Solid Clinical Samples 11

1.3.1.1 Processing Liquid Samples 12

1.3.2 Cell Enrichment 12

1.3.2.1 Laser Capture Microdissection (LCM) 12

1.3.2.2 Density Gradient Centrifugation 13

1.3.2.3 Fluorescence-Activated Cell Sorting (FACS) 13

1.3.2.4 Magnetic Activated Cell Sorting (MACS) 15

1.3.2.5 CellSearchTM 15

1.4 Microscale/Nanoscale Devices for Cellular Enrichment 16

1.4.1 Filtration Approaches 16

1.4.2 Hydrodynamic Mechanisms 17

1.4.3 Surface Treatments 19

1.4.4 Magnetophoresis 19

1.4.5 Electrophoresis 20

1.4.6 Acoustophoresis 21

1.4.7 Optical Tweezers/Traps 22

1.5 Conclusion 23

References 23

2 Genome-Wide Analysis of Single Cells and the Role of Microfluidics 29
Sayantan Bose and Peter A. Sims

2.1 Motivation for Single-Cell Analysis of Genomes and Transcriptomes 29

2.2 Single-Cell Genomics 30

2.2.1 Major Technical Challenges 30

2.2.2 Approaches to Single-Cell Genomics 31

2.2.3 The Application and Impact of Microfluidics in Single-Cell Genomics 34

2.3 Single-Cell Transcriptomics 36

2.3.1 Major Technical Challenges 36

2.3.2 Approaches to Single-Cell Transcriptomics 39

2.3.3 Application and Impact of Microfluidics in Single-Cell Transcriptomics 42

2.4 The Future of Genome-Wide Single-Cell Analysis with Microfluidics 45

2.4.1 Recent Advances in the Scalability of Single-Cell Analysis using Microfluidics 45

2.4.2 How Microfluidics will Expand the Application-Space for Single-Cell Analysis 46

2.4.3 Outstanding Hurdles for Genome-Wide Analysis of Single Cells 47

2.4.4 Prospects for Clinical Applications of Microfluidic Single-Cell Analysis 48

Keywords and Definitions 48

References 49

3 Cellular Immunophenotyping: Industrial Technologies and Emerging Tools 57
Kara Brower and Rong Fan

3.1 Cellular Immune Status and Immunophenotyping 57

3.2 Surface Marker Phenotyping 60

3.2.1 Multicolor Flow Cytometry 60

3.2.2 Commercial Flow Cytometers 62

3.2.3 High-Content Imaging Cytometry 63

3.2.4 Current Limitations and Further Development of Flow Cytometry 64

3.3 Functional Phenotyping 65

3.3.1 ELISpot Technologies 66

3.3.2 Multiplexed Immunoassays 67

3.3.3 Emerging Single-Cell Technologies 68

3.4 Conclusion 70

Keywords and Definitions 71

References 71

4 Microsystem Assays for Studying the Interactions between Single Cells 75
Vandana Kaul and Navin Varadarajan

4.1 Introduction 75

4.2 Advantages of Single-Cell Analysis over Conventional Assay Systems 80

4.3 Analysis of Cell–Cell Communication between Pairs of Single Cells 81

4.3.1 Integrated Microfluidic Coculture Systems and Microwell Arrays 81

4.3.1.1 Microengraving 81

4.3.1.2 T-Cell Proliferation 82

4.3.1.3 T-Cell Cytotoxicity 82

4.3.1.4 NK-Cell Cytotoxicity 84

4.3.1.5 High-Throughput Stem Cell Coculture Array 84

4.3.1.6 Microfluidics-Based Single-Cell RNA-seq for Intercellular Communication 85

4.3.1.7 Single-Cell Signaling Chip 85

4.3.2 DEP Arrays 87

4.3.2.1 Tumor Cell–Endothelial Cell Interaction 87

4.3.2.2 Immune-Cell Cytotoxicity 88

4.3.3 Microfluidic Hydrodynamic Trapping 89

4.3.3.1 Sequential Hydrodynamic Trapping Device 89

4.3.3.2 Intercellular Communication via Gap Junctions 89

4.3.3.3 Cell–Cell Fusion 90

4.3.4 Optical Methods 91

4.3.4.1 Laser-Guided Cell Micropatterning 91

4.3.4.2 Optical Tweezers 91

4.3.4.3 Optoelectronic Tweezers 93

4.3.5 Magnetic Methods 93

4.3.5.1 Magnetic Pattern Arrays 94

4.3.5.2 Magnetic Microflaps 94

4.3.6 Acoustic Methods 94

4.3.6.1 Ultrasonic StandingWaves (USWs) for 2D and 3D Cell–Cell Interaction 95

4.3.6.2 Standing Surface AcousticWaves for Cell Patterning 96

4.3.6.3 Ultrasonic-Based Method for Cell–Cell Interactions in Microwell Arrays 96

4.4 Conclusions 97

Acknowledgments 98

References 98

5 Modeling Microvascular Disease 105
Hope K.A. Gole and Wilbur A. Lam

5.1 Introduction 105

5.2 Microvascular Disease 106

5.3 Macromodeling 107

5.4 Micromodeling 109

5.4.1 Fabrication 110

5.4.2 Design and General Applications 112

5.4.3 Disease-Specific Applications 115

5.4.4 Advantages and Disadvantages 120

5.5 Summary 122

References 122

Part II Tiny Technologies for Modulating Biological Systems 127

6 Nanotechnologies for the Bioelectronic Interface 129
BenjaminW. Avants, Hongkun Park, and Jacob T. Robinson

6.1 Introduction 129

6.2 Modeling the Bioelectronic Interface 130

6.3 Experimental Approaches for Extra-Cellular Coupling 132

6.4 State-of-the-Art Extra-Cellular Nanoscale Interfaces 133

6.5 Experimental Approaches for Intra-Cellular Coupling 134

6.6 State-of-the-Art Intra-Cellular Nanoscale Interfaces 135

6.7 Experimental Approaches for In-Cell Coupling 137

6.8 Outlook 138

References 139

7 Intracellular Delivery of Biomolecules byMechanical Deformation 143
Armon Sharei, Shirley Mao, Robert Langer, and Klavs F. Jensen

7.1 Introduction 143

7.2 Delivery Concept 148

7.2.1 Design 149

7.2.2 Governing Parameters 150

7.3 Cytosolic Delivery by Diffusion 151

7.3.1 Modeling Diffusion 153

7.3.2 Imaging of Membrane Disruptions 157

7.4 Applicability across Cell Types and Delivery Materials 158

7.4.1 Flexibility in Addressing Different Delivery Material 162

7.4.2 Enabling New Research and Clinical Applications 164

7.4.2.1 Cell Reprogramming 164

7.4.2.2 Quantum Dot delivery 166

7.4.2.3 Immune Cell Delivery 166

7.5 Summary 167

7.6 Appendix 169

7.6.1 Device Design Guidelines for New Cell Types 169

7.6.2 Design Parameters 169

7.6.3 Device Nomenclature 170

7.6.4 Defining Delivery Efficiency 171

7.6.5 Device Recovery 171

7.6.6 Reagent Use 171

Acknowledgments 173

Conflict of Interest 173

Keywords and Definitions 174

References 174

8 Microfluidics for Studying Pharmacodynamics of Antibiotics 177
Ritika Mohan, Amit V. Desai, Chotitath Sanpitakseree, and Paul J.A. Kenis

8.1 Background on Antibiotic Resistance 177

8.2 Methods for Antibiotic Susceptibility Testing (AST) 178

8.2.1 Conventional Methods 178

8.2.2 Integrated Microfluidic-Based Approaches 179

8.2.3 Translation of Microfluidic-Based Approaches 182

8.3 Applying Pharmacokinetics/Pharmacodynamics to AST 184

8.3.1 Significance of PK/PD 184

8.3.2 Advantages of Microfluidic-Based Approaches for PK/PD Analysis 185

8.4 Application of Microfluidic-Based Approach for PK/PD Modeling 185

8.4.1 PD Modeling 186

8.4.1.1 Monomicrobial Cultures: MIC Determination of E. coli against Amikacin 188

8.4.1.2 Polymicrobial AST: MIC Determination of E. coli and P. aeruginosa against Amikacin 189

8.4.2 PK Modeling 192

8.5 Summary and Future Outlook 194

Acknowledgments 196

References 196

9 Microsystems Models of Pathophysiology 203
Marie-Elena Brett and David K.Wood

9.1 Vascular and Hematologic Pathologies 205

9.1.1 Thrombosis 205

9.1.2 Sickle Cell Disease 208

9.1.3 Malaria 212

9.1.4 Atherosclerosis 213

9.1.5 Model Limitations and Future Opportunities 214

9.2 Organ-Specific Pathologies 217

9.2.1 Lung 218

9.2.2 Brain 220

9.2.3 Kidney 222

9.2.4 Liver 224

9.2.5 Challenges and Opportunities 226

9.2.5.1 Considerations and Challenges 227

9.2.5.2 Opportunities 230

9.3 Cancer 230

9.3.1 Microscale Tumor Models 231

9.3.2 Metastasis 232

9.3.3 Drug Delivery and Pharmacokinetics 236

9.4 Summary 237

References 238

10 Microfluidic Systems forWhole-Animal Screening with C. elegans 245
Navid Ghorashian, Sertan Kutal Gökçe, and Adela Ben-Yakar

10.1 Importance 245

10.2 Introduction 245

10.3 A Versatile Animal Model: Caenorhabditis elegans (C. elegans) 246

10.3.1 C. elegans Culturing Techniques 247

10.3.2 C. elegans as a Model of Neurological Disease 247

10.3.3 C. elegans as a Drug-Screening Model 249

10.3.4 Current State of the Art in Automated C. elegans Screening 249

10.4 Microfluidics 251

10.4.1 Microfluidic Device Fabrication 251

10.4.2 Fluid Dynamics Modeling in Microfluidics 252

10.4.3 Microfluidics Interfacing with Multiwell Plates 255

10.4.4 Microfluidic Flow Control and Valve Multiplexing 255

10.5 Microfluidics for C. elegans Biology 257

10.5.1 MicrofluidicWorm Immobilization and High-Resolution Optical Interrogation Platforms 257

10.5.1.1 Single Trap Microfluidic Platforms forWorm Processing One at a Time 258

10.5.1.2 Multitrap Microfluidic Platforms to Enable ParallelWorm Processing 262

10.5.2 Microfluidic Population Delivery for Serial Processing 264

10.6 Conclusions and Future Directions 266

Author Contributions 266

References 266

Index 273