Note: Intro -- Systems Biology of Tuberculosis -- Introduction -- References -- Contents -- Contributors -- Chapter 1: Modeling Mycobacterium tuberculosis H37Rv In Silico -- 1 Introduction -- 2 The Reconstruction Process -- 3 Network Characterization -- 4 Extending the Model to Account for Host-Pathogen Interactions -- 5 Applications of Metabolic Models of M. tuberculosis -- 6 Future Directions and Applications -- References -- Chapter 2: Software Platform for Metabolic Network Reconstruction of Mycobacterium tuberculosis -- 1 Issues in Drug Discovery for Tuberculosis -- 2 Knowledge Integration: A Challenge in Precision Modeling -- 3 Needs for Virtual Big Science -- 4 Open Source Drug Discovery for Tuberculosis -- 5 OSDD Mtb Metabolome Challenge -- 6 Software Platform for Open Collaborative Network Reconstruction -- 7 Sustainability of Large-Scale Interaction Map Development -- 8 Can We Scale-Up? -- References -- Chapter 3: Probing Gene Regulatory Networks to Decipher Host-Pathogen Interactions -- 1 Introduction -- 2 Delineation of Mycobacterial Genes That Mediate Adaptation and Survival in Macrophages -- 3 Host Factors That Support Intracellular MTB -- 4 Capturing the Host Cellular Responses to MTB Infection Through Genome-Wide Expression Pro ling -- 5 Analyzing Transcript Pro les Within a Dynamical Framework -- 6 Cis -Regulatory Map of the Human Genome -- 7 Gene Expression Pro ling Can Also Unravel Perturbations in the Host Molecular Interaction Network -- 8 Modeling Drug Treatments and Mycobacterial Persistence -- 9 Extracting Protein Interaction Networks from Gene Expression Data to Understand Latency -- 10 Future Perspective -- References -- Chapter 4: Metabolism of Mycobacterium tuberculosis -- 1 Introduction -- 2 Central Metabolism of M. tuberculosis -- 3 Experimental Systems for Systems Biology -- 4 Metabolic Model Building. , 5 Metabolic Models of M. tuberculosis -- 6 Metabolic Models of Host-Pathogen Systems -- 6.1 Applications of the Models -- 6.1.1 Using Models to Interrogate Genome Annotation -- 6.1.2 Interpretation of Experimental Data -- Gene Essentiality Data -- Transcriptome Data -- Stable Isotope Metabolite Pro ling -- 13 C Metabolic Flux Analysis -- 7 Future Challenges -- References -- Chapter 5: Protein-Protein Interaction in the -Omics Era: Understanding Mycobacterium tuberculosis Function -- 1 Introduction -- 2 Microbial PPI Systems -- 2.1 The Y2H System -- 2.2 The E. coli BacterioMatch System -- 2.3 The Bacterial Adenylate Cyclase Two-Hybrid System -- 2.4 Protein Fragment Complementation -- 3 Shared Properties of Microbial Interaction Systems -- 4 Is Yeast the Optimal Host for Studying Mycobacterial PPIs? -- 5 Speci city and False Positives of PPI Technologies -- 6 How Can PPI Technologies Help Us Understand Mtb Virulence? -- 7 Impact of the Y2H System on Mtb Research -- 7.1 Mtb WhiB3 -- 7.2 Secretion -- 7.3 Mtb Two-Component Signaling Proteins and Sigma Factors -- 7.4 DNA Repair -- 7.5 Other -- 8 Protein-Protein Interaction in Other Pathogens -- 9 Considerations for Mycobacterial PPIs -- 9.1 Some Mycobacterial Proteins Interact Exclusively in Their Native Environment -- 9.2 Some Mycobacterial Proteins Require More Than One Protein for Interaction -- 9.3 Post-translational Modi cation Can Affect PPI in the Y2H System -- 10 Molecules That Dissociate or Force Protein-Protein Interaction -- 11 In Silico Methods for Predicting PPI -- 12 Integrative Physiology: The Emergence of Systems Biology? -- 13 Conclusions -- References -- Chapter 6: Host-Pathogen Interactions -- 1 Introduction -- 2 Functional Genomics to Identify Mycobacterial Virulence Genes -- 3 In Silico Mycobacterial Genomics. , 4 Functional Genomics to Recognise Host Genes Mediating the Response to Mycobacteria -- 5 Transcriptional Pro ling Mycobacteria Interactions with Phagocytes -- 6 Transcriptional Pro ling the Interplay Between Host and Pathogen -- 7 Systems Biology and Modelling the Dialogue Between Host and Pathogen -- 8 Interaction Databases and Network Maps -- 9 Models of Host-Pathogen Interactions -- 10 Future Perspective -- References -- Chapter 7: A Systems Biology Approach for Understanding Granuloma Formation and Function in Tuberculosis -- 1 Introduction -- 1.1 Granuloma Formation and Function -- 1.2 Key Cellular and Molecular Players Relevant to Granulomas -- 1.3 A Systems Biology Approach to Understanding Granuloma Formation and Function -- 2 Experimental and Computational Models of Tuberculosis Granulomas -- 2.1 Experimental Models -- 2.2 Computational Models of Tuberculosis Granuloma -- 3 What Are Examples of Questions That Systems Biology Can Address? -- 3.1 Which Factors In uence the Ability of a Granuloma to Control Infection? -- 3.2 What Is the Role of TNF in Granuloma Formation and Function? -- 3.2.1 Prediction I: Establishment of a TNF Concentration Gradient Within a Granuloma -- 3.2.2 Prediction II: A Critical Role for TNFR1 Internalization Kinetics -- 3.2.3 Prediction III: A Critical Synergy Between Individual TNF Activities -- 3.3 What Are the Mechanisms Underlying TB Reactivation Following Anti-TNF Therapies? -- 3.4 What Is the Impact of Lymph Node Processes on Granuloma Formation and Function in the Lung? -- 3.4.1 Prediction I: Antigen Presenting Cell Migration and Immunogenicity Are Key Regulatory Mechanisms in TB Granuloma Formation and Maintenance -- 3.4.2 Prediction II: Differential Roles of Effector Lymphocytes in TB Containment and Clearance -- 4 Conclusions and Future Directions -- References. , Chapter 8: Stochastic Gene Expression in Bacterial Pathogens: A Mechanism for Persistence? -- 1 Persistence -- 2 Persistence in M. tuberculosis -- 3 Noise -- 3.1 Langevin Equations -- 3.2 Master Equations -- 3.3 Exact Stochastic Simulation -- 4 Emergence of Distinct Functional Phenotypes -- 5 Noise and Persistence: Conclusions -- References -- Chapter 9: Drug Discovery -- 1 Introduction -- 2 Choosing a Strategy for Therapeutic Intervention -- 3 Target Identi cation -- 4 The TargetTB Pipeline -- 5 Polypharmacology, Combination Targets, and Drug Repurposing -- 6 Addressing Drug Resistance -- 7 Targeting Host-Pathogen Interactions and Critical Host Factors -- 8 Future Perspectives -- References -- Chapter 10: Immunological Biomarkers for Tuberculosis: Potential for a Combinatorial Approach -- 1 T Cell Responses -- 1.1 Overview -- 1.2 Natural Memory Immunity -- 1.3 Adaptive Immunity -- 1.4 Regulation of Immunity -- 1.5 T Cell Biomarkers -- 2 Properties of Antigen Presenting Cells -- 2.1 Overview -- 2.2 Sputum Macrophages -- 2.3 Macrophages in Bronchoalveolar Lavage -- 2.4 Peripheral Blood Monocytes -- 2.5 Biomarkers Based on Monocytes and Macrophages -- 3 Humoral Responses -- 3.1 Overview -- 3.2 Antibody Pro les -- 3.3 Antibodies as Biomarkers -- 4 Conclusions -- References -- Index.