Principles in Microbiome Engineering

Matthew W. Chang, Dean’s Chair in Medicine and Associate Professor of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore (NUS)

• Preface xiii1 Diet-Based Microbiome Modulation: You are What You Eat 1Jiashu Li, Zeyang Qu, Feng Liu, Hao Jing, Yu Pan, Siyu Guo, and Chun Loong Ho1.1 Introduction 11.1.1 Microbiome Diversity in Human Body 11.1.1.1 Oral Microbiome 21.1.1.2 Gastrointestinal Microbiome 31.1.1.3 Skin Microbiome 41.1.1.4 Respiratory Microbiome 51.1.1.5 Urogenital Microbiome 51.1.2 Elements that Influence Microbiome Development 51.1.2.1 Prebiotics 61.1.2.2 Probiotics 61.1.2.3 Diet and Nutrition 71.1.3 Current Approaches Employed in Studying the Human Microbiome 71.2 Dietary Lifestyle Variation Affecting Host Microbiome 81.2.1 Dietary Role in Shaping the Microbiome 81.2.1.1 Protein and Polypeptides 81.2.1.2 Soluble Saccharides 91.2.1.3 Dietary Fibers 91.2.1.4 Lipids 101.2.2 The Socioeconomic Impact on Diet-Related Microbiome Changes 111.2.3 Age Groups and Dietary-Related Microbiome Changes 131.2.4 Continental Dietary Difference and Its Effect of the Local Microbiome 151.2.4.1 Asia 151.2.4.2 Europe 151.2.4.3 Australia 161.2.4.4 Africa 161.2.4.5 South America 161.2.4.6 North America 171.3 Dietary Modulation of Microbiome for Disease Treatment 171.3.1 Infection 171.3.1.1 Fecal Microbiota Transplantation (FMT) 171.3.1.2 Prebiotic-, Diet-, and Probiotic-Mediated Prevention of Pathogenic Infections 191.3.2 Inflammatory Disease 201.3.3 Cancer 211.3.4 Psychological Disease 221.3.4.1 Autism Spectrum Disorder 221.3.4.2 Neurodegenerative Diseases 231.3.5 Metabolic Disorder 231.3.5.1 Obesity 231.3.5.2 Diabetes 241.3.5.3 Non-alcoholic Fatty Liver Disease (NAFLD) 241.4 Challenges and Opportunities 251.4.1 Limitations in the Field 251.4.2 Current Microbiome Project Supporting Infrastructures 251.4.2.1 International and Local Initiatives 251.4.2.2 Global Foundations 271.5 Concluding Remarks 27Acknowledgments 28References 282 Microbiome Engineering for Metabolic Disorders 47Nikhil Aggarwal, Elvin W. C. Koh, Santosh Kumar Srivastava, Brendan F. L. Sieow, and In Young Hwang2.1 Introduction 472.2 Microbiome Engineering for Diabetes and Obesity 492.2.1 Microbiome Engineering for the Hypoglycemic Effect to Treat Diabetes and Obesity 502.2.2 Microbiome Engineering for Immune Modulation to Treat Diabetes 522.3 Microbiome Engineering to Modulate Gut–Liver Axis 542.3.1 Microbiome Engineering to Modulate Ammonia Metabolism 542.3.2 Microbiome Engineering to Modulate Phenylalanine Metabolism 552.3.3 Microbiome Engineering to Modulate Bile-Salt Metabolism 562.3.4 Microbiome Engineering to Modulate Fat Metabolism 572.4 Microbiome Engineering for Cardiovascular Diseases 582.4.1 Gut Microbiome Interventions for Cardiovascular Diseases 592.4.2 Role of Microbiome-Derived TMAO in Cardiovascular Diseases 602.5 Microbiome Engineering to Modulate Gut–Brain Axis 612.5.1 Exploratory Studies on the Development of Psychobiotics 642.6 Clinical Translation of Live Biotherapeutic Products 652.7 Conclusion and Future Directions 76References 763 Repurposing Microbes for Therapeutic Applications in Humans 93Kangsan Kim, Donghui Choe, Minjeong Kang, Bong Hyun Sung, Haseong Kim, Seung-Goo Lee, Dae-Hee Lee, and Byung-Kwan Cho3.1 Introduction 933.2 A Brief Overview of Microbiota and Human Health 943.2.1 Interactions Between Microbes and Their Compositions Affect the Host Metabolic Status 953.2.2 Host–Microbe Interactions Constitute an Essential Part of Host Metabolism 973.3 Systems Biology Approach to Analyze the Gut Microbiota Functions 983.3.1 Rational Design of Gut Microbiome Editing Strategies 983.3.2 High-Throughput Data-Driven Understanding of Gut Microbiota 1003.4 Engineering Microbiome to Treat Diseases 1023.4.1 Strain Selection for Microbiome Engineering 1023.4.2 Engineering Microbes to Sense and Respond to Disease-Related Perturbations 1033.4.3 Engineering Microbes to Express Therapeutic Proteins for Disease Treatment 1093.5 Perspectives and Conclusion 111References 1114 Modulating Residence Time and Biogeography of Engineered Probiotics 121Rana Said, Zachary J. S. Mays, and Nikhil U. Nair4.1 Introduction 1214.2 Adhesion Mechanisms 1224.3 Adhesion Modulation 1254.4 Functional Encapsulations and Biofilms that Modify Gastrointestinal Dynamics of Probiotics 1264.5 Metabolic Engineering to Modulate Gut Adaptation 1284.6 Conclusions 129References 1305 Microbiome Engineering for Next-Generation Precision Agriculture 137Mohd Firdaus Abdul-Wahab, Shruti Pavagadhi, Hitesh Tikariha, and Sanjay Swarup5.1 Background 1375.2 Systems Approach to Microbiome Engineering 1395.2.1 DBTL Framework for Microbiome Engineering 1395.2.2 Computational Tools for Robust Microbiome Engineering 1425.2.3 Genome-Scale Metabolic Modeling 1435.3 Synthetic Biology for Genome and Genetic Engineering of Phytobiomes 1445.4 Conclusion and Future Perspectives 146Acknowledgments 148References 1486 Biological Sensors for Microbiome Diagnostics 155Amy 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. Goodson6.1 Introduction 1556.1.1 The Malleable Microbiome 1556.1.2 Engineered Probiotics 1556.2 Diagnosing the Microbiome 1566.2.1 Microbiome Analyses 1566.2.1.1 Small Subunit rRNA Analysis 1566.2.1.2 Metagenomics and Metatranscriptomics 1576.2.1.3 Proteomics and Metabolomics 1576.2.2 Considerations and Future of Microbiome Diagnosis 1586.3 Types of Biosensors 1596.3.1 Riboswitches 1596.3.1.1 Riboswitches and Their Regulatory Mechanisms 1606.3.1.2 Design and Selection of Synthetic Riboswitches 1606.3.1.3 Riboswitches in Molecular Detection of Microbiome Metabolites 1616.3.2 Transcription Factors 1636.3.2.1 Transcription Factor Mining 1636.3.2.2 Engineering Transcription Factors 1646.3.2.3 Applications of Transcription Factors 1656.3.3 Two-Component Systems 1666.3.3.1 Introduction to Two-Component Systems 1666.3.3.2 Expression of Natural TCS Systems for Gut Diagnostics 1666.3.3.3 Engineering TCS-Based Sensors for the Microbiome 1676.3.4 G Protein-Coupled Receptors 1686.3.4.1 GPCRs and the Gut Microbiome 1686.3.4.2 GPCRs Engineered Into Yeast 1686.3.4.3 Recent Advances in Yeast GPCR-Based Sensors 1706.4 Testing and Utilizing Engineered Biosensors 1716.4.1 Cell-Free Protein Expression Systems (CFPS) for Biosensing 1716.4.2 In Vitro Testing 1736.4.2.1 In Vitro Models 1746.4.2.2 Organ-on-a-Chip 1746.4.2.3 In Vitro Host–Microbe Characterization 1746.4.3 Examples of Engineered Microbes 1766.4.3.1 Identifying Microbiome Changes In Situ 1766.4.3.2 Engineered Microbes for Disease Diagnostics 1766.4.3.3 Cancer 1776.4.3.4 Inflammatory Bowel Disease 1786.4.3.5 Infection 1786.4.3.6 Future Translation 1786.5 Conclusions/Summary 179Acknowledgments 180References 1807 Principles, Tools, and Applications of Synthetic Consortia Toward Microbiome Engineering 195Eliza Atkinson, Alice Boo, Huadong Peng, Guy-Bart Stan, and Rodrigo Ledesma-Amaro7.1 Introduction 1957.2 Advantages of Labor Division via Synthetic Microbial Consortia 1977.2.1 Providing Optimal Conditions 1987.2.2 Reducing the Metabolic Burden on the Host 1987.2.3 Reducing Crosstalk and Competition Within Synthetic Pathways 1997.3 Tools for Engineering Synthetic Consortia 2007.3.1 Genetic Manipulation Tools 2007.3.2 Cell-to-Cell Communication 2007.3.3 External and Intercellular Signal Molecules for Regulating Gene Expression and Population Composition 2017.3.4 Secretion and Exchange of Metabolites 2017.3.5 Analysis Tools 2027.3.6 Computational Models 2027.3.6.1 Dynamic/Deterministic Models 2027.3.6.2 Agent-Based Models 2037.3.6.3 Stoichiometric and Genome-Scale Metabolic Models 2037.4 Engineering Syntrophy 2057.5 Engineering Population Control 2067.6 Synthetic Microbial Consortia and the Human Microbiome 2077.7 Conclusions and Future Perspectives 208References 2098 Fecal Microbiota Transplantation for Microbiome Modulation: A Clinical View 219Peter C. Konturek, Thomas Hess, Walburga Dieterich, and Yurdagül Zopf8.1 Introduction 2198.2 Fecal Microbiota Transplantation (FMT) 2198.2.1 Recruitment of Potential Donors 2208.2.2 Administration of FMT 2208.2.3 Safety 2208.3 Clinical Application of Fecal Microbiota Therapy 2228.3.1 C. difficile Infection (CDI) 2228.3.2 Inflammatory Bowel Disease 2238.3.3 FMT as a Therapeutic Option to Eradicate Highly Drug-Resistant Enteric Bacteria Carriage 2248.3.4 FMT and Irritable Bowel Syndrome 2248.3.5 FMT and Slow-Transit Constipation 2258.3.6 FMT and Liver Diseases 2258.4 FMT – Novel Indications 2268.4.1 Chemotherapy-Induced Diarrhea 2268.4.2 Obesity and Metabolic Syndrome 2278.4.3 Graft-versus-Host Disease (GvHD) 2278.4.4 Autoimmune Diseases 2278.4.5 Neuropsychiatric Disorders 2288.5 Conclusion 228References 2289 Maternal Microbiota as a Therapeutic Target 233Ferit Saracoglu9.1 Introduction 2339.2 Human Maternal Microbiota 2339.2.1 Oral Microbiota 2339.2.2 Vaginal Microbiota 2349.2.3 Endometrial Microbiome 2349.2.4 Gut Microbiome 2369.2.4.1 Maternal Gut Microbiome and Immune Functions 2369.2.4.2 Gut and Brain Axis 2389.2.4.3 Epigenetic Regulation of Gut Microbiota 2389.2.5 Placental Microbime and Meconium 2399.3 Maternal Microbiota and Health 2409.3.1 Developmental Origins of Adult-Onset Diseases: Barker Hypothesis 2409.3.2 Maternal Microbiota and Obesity 2409.3.2.1 Maternal Diet and Gut Microbiota 2409.3.2.2 Body Mass Index, Insulin Resistance, and Obesity in Pregnancy 2419.3.2.3 Childhood Obesity 2419.3.3 Miscarriages and Microbiome 2429.3.4 Postpartum Microbiome 2429.3.4.1 Mode of Delivery 2429.3.4.2 Vaginal Seeding 2439.3.5 Maternal Microbiota and Gestational Age at Birth 2439.3.6 Maternal Microbiota and Maternal Inflammation and Intrauterine Infections 2449.4 Human Milk Microbiota and Infant Health 2459.5 Drug Treatment, Unhealthy Conditions, and Microbiome 2479.5.1 Perinatal Antibiotic Treatment 2479.5.2 Smoking 2499.5.3 Stress Under Pregnancy 2499.5.4 Autism Spectrum Disorders 2509.5.5 Critical Illness of Newborns 2509.6 Probiotic and Prebiotic Therapies as Modulators of Microbiome 250References 25210 Transcription Factor-Based Biosensors and Their Application in Microbiome Engineering 277Seong 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 LeeSummary 27710.1 Design: TF-Based Biosensors 27810.1.1 Transcriptional Repressors 27810.1.2 Transcriptional Activators 28210.1.3 One-Component Regulatory System or Two-Component Regulatory System 28310.1.4 Types of Output Modules 28410.1.5 Layered Genetic Circuits 28510.2 Build: TF-Based Biosensors 28610.2.1 Construction of Genetic Circuits 28610.2.1.1 Gene Synthesis 28710.2.1.2 Restriction Enzyme–Based Cloning 28710.2.1.3 Gibson Assembly 28810.2.2 Chassis 28810.3 Test: TF-Based Biosensors Application in Microbiome 28910.3.1 Diagnostics 28910.3.2 Therapeutics 29110.3.3 Biocontainment 29210.4 Learn: Strategies for TF-Based Biosensor Improvement 29310.5 Conclusions 294List of Abbreviations 294Acknowledgments 295References 295Index 305