Principles in Microbiome Engineering

Preface xiii 1 Diet-Based Microbiome Modulation: You are What You Eat 1 Jiashu Li, Zeyang Qu, Feng Liu, Hao Jing, Yu Pan, Siyu Guo, and Chun Loong Ho 1.1 Introduction 1 1.1.1 Microbiome Diversity in Human Body 1 1.1.1.1 Oral Microbiome 2 1.1.1.2 Gastrointestinal Microbiome 3 1.1.1.3 Skin Microbiome 4 1.1.1.4 Respiratory Microbiome 5 1.1.1.5 Urogenital Microbiome 5 1.1.2 Elements that Influence Microbiome Development 5 1.1.2.1 Prebiotics 6 1.1.2.2 Probiotics 6 1.1.2.3 Diet and Nutrition 7 1.1.3 Current Approaches Employed in Studying the Human Microbiome 7 1.2 Dietary Lifestyle Variation Affecting Host Microbiome 8 1.2.1 Dietary Role in Shaping the Microbiome 8 1.2.1.1 Protein and Polypeptides 8 1.2.1.2 Soluble Saccharides 9 1.2.1.3 Dietary Fibers 9 1.2.1.4 Lipids 10 1.2.2 The Socioeconomic Impact on Diet-Related Microbiome Changes 11 1.2.3 Age Groups and Dietary-Related Microbiome Changes 13 1.2.4 Continental Dietary Difference and Its Effect of the Local Microbiome 15 1.2.4.1 Asia 15 1.2.4.2 Europe 15 1.2.4.3 Australia 16 1.2.4.4 Africa 16 1.2.4.5 South America 16 1.2.4.6 North America 17 1.3 Dietary Modulation of Microbiome for Disease Treatment 17 1.3.1 Infection 17 1.3.1.1 Fecal Microbiota Transplantation (FMT) 17 1.3.1.2 Prebiotic-, Diet-, and Probiotic-Mediated Prevention of Pathogenic Infections 19 1.3.2 Inflammatory Disease 20 1.3.3 Cancer 21 1.3.4 Psychological Disease 22 1.3.4.1 Autism Spectrum Disorder 22 1.3.4.2 Neurodegenerative Diseases 23 1.3.5 Metabolic Disorder 23 1.3.5.1 Obesity 23 1.3.5.2 Diabetes 24 1.3.5.3 Non-alcoholic Fatty Liver Disease (NAFLD) 24 1.4 Challenges and Opportunities 25 1.4.1 Limitations in the Field 25 1.4.2 Current Microbiome Project Supporting Infrastructures 25 1.4.2.1 International and Local Initiatives 25 1.4.2.2 Global Foundations 27 1.5 Concluding Remarks 27 Acknowledgments 28 References 28 2 Microbiome Engineering for Metabolic Disorders 47 Nikhil Aggarwal, Elvin W. C. Koh, Santosh Kumar Srivastava, Brendan F. L. Sieow, and In Young Hwang 2.1 Introduction 47 2.2 Microbiome Engineering for Diabetes and Obesity 49 2.2.1 Microbiome Engineering for the Hypoglycemic Effect to Treat Diabetes and Obesity 50 2.2.2 Microbiome Engineering for Immune Modulation to Treat Diabetes 52 2.3 Microbiome Engineering to Modulate Gut–Liver Axis 54 2.3.1 Microbiome Engineering to Modulate Ammonia Metabolism 54 2.3.2 Microbiome Engineering to Modulate Phenylalanine Metabolism 55 2.3.3 Microbiome Engineering to Modulate Bile-Salt Metabolism 56 2.3.4 Microbiome Engineering to Modulate Fat Metabolism 57 2.4 Microbiome Engineering for Cardiovascular Diseases 58 2.4.1 Gut Microbiome Interventions for Cardiovascular Diseases 59 2.4.2 Role of Microbiome-Derived TMAO in Cardiovascular Diseases 60 2.5 Microbiome Engineering to Modulate Gut–Brain Axis 61 2.5.1 Exploratory Studies on the Development of Psychobiotics 64 2.6 Clinical Translation of Live Biotherapeutic Products 65 2.7 Conclusion and Future Directions 76 References 76 3 Repurposing Microbes for Therapeutic Applications in Humans 93 Kangsan Kim, Donghui Choe, Minjeong Kang, Bong Hyun Sung, Haseong Kim, Seung-Goo Lee, Dae-Hee Lee, and Byung-Kwan Cho 3.1 Introduction 93 3.2 A Brief Overview of Microbiota and Human Health 94 3.2.1 Interactions Between Microbes and Their Compositions Affect the Host Metabolic Status 95 3.2.2 Host–Microbe Interactions Constitute an Essential Part of Host Metabolism 97 3.3 Systems Biology Approach to Analyze the Gut Microbiota Functions 98 3.3.1 Rational Design of Gut Microbiome Editing Strategies 98 3.3.2 High-Throughput Data-Driven Understanding of Gut Microbiota 100 3.4 Engineering Microbiome to Treat Diseases 102 3.4.1 Strain Selection for Microbiome Engineering 102 3.4.2 Engineering Microbes to Sense and Respond to Disease-Related Perturbations 103 3.4.3 Engineering Microbes to Express Therapeutic Proteins for Disease Treatment 109 3.5 Perspectives and Conclusion 111 References 111 4 Modulating Residence Time and Biogeography of Engineered Probiotics 121 Rana Said, Zachary J. S. Mays, and Nikhil U. Nair 4.1 Introduction 121 4.2 Adhesion Mechanisms 122 4.3 Adhesion Modulation 125 4.4 Functional Encapsulations and Biofilms that Modify Gastrointestinal Dynamics of Probiotics 126 4.5 Metabolic Engineering to Modulate Gut Adaptation 128 4.6 Conclusions 129 References 130 5 Microbiome Engineering for Next-Generation Precision Agriculture 137 Mohd Firdaus Abdul-Wahab, Shruti Pavagadhi, Hitesh Tikariha, and Sanjay Swarup 5.1 Background 137 5.2 Systems Approach to Microbiome Engineering 139 5.2.1 DBTL Framework for Microbiome Engineering 139 5.2.2 Computational Tools for Robust Microbiome Engineering 142 5.2.3 Genome-Scale Metabolic Modeling 143 5.3 Synthetic Biology for Genome and Genetic Engineering of Phytobiomes 144 5.4 Conclusion and Future Perspectives 146 Acknowledgments 148 References 148 6 Biological Sensors for Microbiome Diagnostics 155 Amy M. Ehrenworth Breedon, Kathryn R. Beabout, Heidi G. Coia, Christina M. Davis, Svetlana V. Harbaugh, Camilla A. Mauzy, M. Tyler Nelson, Roland J. Saldanha, Blake W. Stamps, and Michael S. Goodson 6.1 Introduction 155 6.1.1 The Malleable Microbiome 155 6.1.2 Engineered Probiotics 155 6.2 Diagnosing the Microbiome 156 6.2.1 Microbiome Analyses 156 6.2.1.1 Small Subunit rRNA Analysis 156 6.2.1.2 Metagenomics and Metatranscriptomics 157 6.2.1.3 Proteomics and Metabolomics 157 6.2.2 Considerations and Future of Microbiome Diagnosis 158 6.3 Types of Biosensors 159 6.3.1 Riboswitches 159 6.3.1.1 Riboswitches and Their Regulatory Mechanisms 160 6.3.1.2 Design and Selection of Synthetic Riboswitches 160 6.3.1.3 Riboswitches in Molecular Detection of Microbiome Metabolites 161 6.3.2 Transcription Factors 163 6.3.2.1 Transcription Factor Mining 163 6.3.2.2 Engineering Transcription Factors 164 6.3.2.3 Applications of Transcription Factors 165 6.3.3 Two-Component Systems 166 6.3.3.1 Introduction to Two-Component Systems 166 6.3.3.2 Expression of Natural TCS Systems for Gut Diagnostics 166 6.3.3.3 Engineering TCS-Based Sensors for the Microbiome 167 6.3.4 G Protein-Coupled Receptors 168 6.3.4.1 GPCRs and the Gut Microbiome 168 6.3.4.2 GPCRs Engineered Into Yeast 168 6.3.4.3 Recent Advances in Yeast GPCR-Based Sensors 170 6.4 Testing and Utilizing Engineered Biosensors 171 6.4.1 Cell-Free Protein Expression Systems (CFPS) for Biosensing 171 6.4.2 In Vitro Testing 173 6.4.2.1 In Vitro Models 174 6.4.2.2 Organ-on-a-Chip 174 6.4.2.3 In Vitro Host–Microbe Characterization 174 6.4.3 Examples of Engineered Microbes 176 6.4.3.1 Identifying Microbiome Changes In Situ 176 6.4.3.2 Engineered Microbes for Disease Diagnostics 176 6.4.3.3 Cancer 177 6.4.3.4 Inflammatory Bowel Disease 178 6.4.3.5 Infection 178 6.4.3.6 Future Translation 178 6.5 Conclusions/Summary 179 Acknowledgments 180 References 180 7 Principles, Tools, and Applications of Synthetic Consortia Toward Microbiome Engineering 195 Eliza Atkinson, Alice Boo, Huadong Peng, Guy-Bart Stan, and Rodrigo Ledesma-Amaro 7.1 Introduction 195 7.2 Advantages of Labor Division via Synthetic Microbial Consortia 197 7.2.1 Providing Optimal Conditions 198 7.2.2 Reducing the Metabolic Burden on the Host 198 7.2.3 Reducing Crosstalk and Competition Within Synthetic Pathways 199 7.3 Tools for Engineering Synthetic Consortia 200 7.3.1 Genetic Manipulation Tools 200 7.3.2 Cell-to-Cell Communication 200 7.3.3 External and Intercellular Signal Molecules for Regulating Gene Expression and Population Composition 201 7.3.4 Secretion and Exchange of Metabolites 201 7.3.5 Analysis Tools 202 7.3.6 Computational Models 202 7.3.6.1 Dynamic/Deterministic Models 202 7.3.6.2 Agent-Based Models 203 7.3.6.3 Stoichiometric and Genome-Scale Metabolic Models 203 7.4 Engineering Syntrophy 205 7.5 Engineering Population Control 206 7.6 Synthetic Microbial Consortia and the Human Microbiome 207 7.7 Conclusions and Future Perspectives 208 References 209 8 Fecal Microbiota Transplantation for Microbiome Modulation: A Clinical View 219 Peter C. Konturek, Thomas Hess, Walburga Dieterich, and Yurdagül Zopf 8.1 Introduction 219 8.2 Fecal Microbiota Transplantation (FMT) 219 8.2.1 Recruitment of Potential Donors 220 8.2.2 Administration of FMT 220 8.2.3 Safety 220 8.3 Clinical Application of Fecal Microbiota Therapy 222 8.3.1 C. difficile Infection (CDI) 222 8.3.2 Inflammatory Bowel Disease 223 8.3.3 FMT as a Therapeutic Option to Eradicate Highly Drug-Resistant Enteric Bacteria Carriage 224 8.3.4 FMT and Irritable Bowel Syndrome 224 8.3.5 FMT and Slow-Transit Constipation 225 8.3.6 FMT and Liver Diseases 225 8.4 FMT – Novel Indications 226 8.4.1 Chemotherapy-Induced Diarrhea 226 8.4.2 Obesity and Metabolic Syndrome 227 8.4.3 Graft-versus-Host Disease (GvHD) 227 8.4.4 Autoimmune Diseases 227 8.4.5 Neuropsychiatric Disorders 228 8.5 Conclusion 228 References 228 9 Maternal Microbiota as a Therapeutic Target 233 Ferit Saracoglu 9.1 Introduction 233 9.2 Human Maternal Microbiota 233 9.2.1 Oral Microbiota 233 9.2.2 Vaginal Microbiota 234 9.2.3 Endometrial Microbiome 234 9.2.4 Gut Microbiome 236 9.2.4.1 Maternal Gut Microbiome and Immune Functions 236 9.2.4.2 Gut and Brain Axis 238 9.2.4.3 Epigenetic Regulation of Gut Microbiota 238 9.2.5 Placental Microbime and Meconium 239 9.3 Maternal Microbiota and Health 240 9.3.1 Developmental Origins of Adult-Onset Diseases: Barker Hypothesis 240 9.3.2 Maternal Microbiota and Obesity 240 9.3.2.1 Maternal Diet and Gut Microbiota 240 9.3.2.2 Body Mass Index, Insulin Resistance, and Obesity in Pregnancy 241 9.3.2.3 Childhood Obesity 241 9.3.3 Miscarriages and Microbiome 242 9.3.4 Postpartum Microbiome 242 9.3.4.1 Mode of Delivery 242 9.3.4.2 Vaginal Seeding 243 9.3.5 Maternal Microbiota and Gestational Age at Birth 243 9.3.6 Maternal Microbiota and Maternal Inflammation and Intrauterine Infections 244 9.4 Human Milk Microbiota and Infant Health 245 9.5 Drug Treatment, Unhealthy Conditions, and Microbiome 247 9.5.1 Perinatal Antibiotic Treatment 247 9.5.2 Smoking 249 9.5.3 Stress Under Pregnancy 249 9.5.4 Autism Spectrum Disorders 250 9.5.5 Critical Illness of Newborns 250 9.6 Probiotic and Prebiotic Therapies as Modulators of Microbiome 250 References 252 10 Transcription Factor-Based Biosensors and Their Application in Microbiome Engineering 277 Seong Keun Kim, Seung Gyun Woo, Tae Hyun Kim, Seong Hyun Park, Jin Ju Lee, A Young Park, So Hyung Oh, Seong Kun Bak, Seung-Goo Lee, and Dae-Hee Lee Summary 277 10.1 Design: TF-Based Biosensors 278 10.1.1 Transcriptional Repressors 278 10.1.2 Transcriptional Activators 282 10.1.3 One-Component Regulatory System or Two-Component Regulatory System 283 10.1.4 Types of Output Modules 284 10.1.5 Layered Genetic Circuits 285 10.2 Build: TF-Based Biosensors 286 10.2.1 Construction of Genetic Circuits 286 10.2.1.1 Gene Synthesis 287 10.2.1.2 Restriction Enzyme–Based Cloning 287 10.2.1.3 Gibson Assembly 288 10.2.2 Chassis 288 10.3 Test: TF-Based Biosensors Application in Microbiome 289 10.3.1 Diagnostics 289 10.3.2 Therapeutics 291 10.3.3 Biocontainment 292 10.4 Learn: Strategies for TF-Based Biosensor Improvement 293 10.5 Conclusions 294 List of Abbreviations 294 Acknowledgments 295 References 295 Index 305