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UNIVERSITY of CALIFORNIA, SAN DIEGO Comparative Systems UNIVERSITY OF CALIFORNIA, SAN DIEGO Comparative Systems Biology Analysis of Microbial Pathogens A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Chemical Engineering by Jonathan Mayock Monk Committee in charge: Professor Bernhard Ø. Palsson, Chair Professor Michael Heller, Co-Chair Professor Guarav Arya Professor Victor Nizet Professor Milton Saier 2015 Copyright Jonathan Mayock Monk, 2015 All rights reserved Signature Page The dissertation of Jonathan Mayock Monk is approved, and it is acceptable in quality and form for publication on microfilm and electronically: Co- Chair Chair University of California, San Diego 2015 iii DEDICATION Dedication This work is dedicated to my parents, for the love and support they have given me that has enabled me to achieve this milestone. iv EPIGRAPH Epigraph The true delight is in the finding out rather than in the knowing. - Isaac Asimov v TABLE OF CONTENTS Table of Contents Signature Page ............................................................................................................... iii Dedication ...................................................................................................................... iv Epigraph .......................................................................................................................... v Table of Contents ........................................................................................................... vi List of Figures ............................................................................................................... xvi List of Tables ............................................................................................................... xviii Acknowledgements ...................................................................................................... xix Vita .............................................................................................................................. xxiii Abstract of the Dissertation ..........................................................................................xxvi Chapter 1 Using Genome-Scale Models to Predict Biological Capabilities ...................... 1 1.1 Introduction ........................................................................................................... 2 1.2 A network reconstruction is the systematic assembly of knowledge ...................... 4 1.3 Converting a genome-scale reconstruction to a computational model. .................. 5 1.3.1 What is needed to create a new cell? ............................................................. 8 1.4 Validation and reconciliation of qualitative model predictions ...............................10 1.4.1 Genetic and environmental parameters .........................................................11 1.4.2 Classification of model predictions .................................................................12 1.4.3 Discovering new metabolic capabilities using model false negatives. ............13 vi 1.4.4 Adaptive laboratory evolution can be used as a part of the discovery process. ...............................................................................................................................15 1.5 Quantitative phenotype prediction through optimality principles ...........................17 1.5.1 Workflow for quantitative phenotype prediction. .............................................18 1.5.2 Flux variability analysis (FVA) calculates possible flux states. .......................19 1.5.3 Types of possible (evolutionarily optimal) quantitative predictions. ................20 1.5.4 From optimality principles to prospective design ............................................22 1.6 Multi-omic data integration: constraining and exploring possible phenotypic states ..................................................................................................................................23 1.6.1 Workflow for multi-omic data integration. .......................................................24 1.6.2 Converting data to model constraints. ............................................................24 1.6.3 Cell-type and condition-specific models .........................................................25 1.6.4 Quantifying uncertainty with Flux variability analysis (FVA) and Sampling. ....25 1.6.5 Using computed states to drive discovery and experimentation. ....................26 1.7 Moving beyond metabolism to molecular biology .................................................27 1.7.1 Computing properties of the proteome. ..........................................................28 1.7.2 GEM-PRO -- A structural biology view of cellular networks ............................28 1.7.3 Modeling molecular biology and metabolism with ME-Models. ......................29 1.8 Perspective ..........................................................................................................32 1.9 Acknowledgments ................................................................................................33 vii Chapter 2 Comparative Genome-scale metabolic reconstructions of multiple Escherichia coli strains highlight strain-specific adaptations to nutritional environments ................... 45 2.1 Abstract ................................................................................................................46 2.2 Introduction ..........................................................................................................46 2.3 Results .................................................................................................................48 2.3.1 Characteristics of E. coli core and pan metabolic content ..............................48 2.3.2 The ability to catabolize different nutrient sources distinguishes metabolic models of E. coli strains ..........................................................................................50 2.3.3 A set of substrates differentiate pathogenic strains from commensal (non- pathogenic) strains .................................................................................................51 2.3.4 Metabolic models combined with gap-filling methods facilitate investigation into the genetic basis of strain-specific auxotrophies ..............................................53 2.3.5 Experimental validation of unique nutrients shows high model accuracy .......54 2.4 Discussion ...........................................................................................................56 2.5 Materials and Methods .........................................................................................60 2.5.1 Strain specific model reconstruction ..............................................................60 2.5.2 Gap Filling .....................................................................................................61 2.5.3 In silico growth simulations ............................................................................62 2.5.4 Heatmap and phylogenetic tree construction .................................................62 2.5.5 Decision tree construction .............................................................................63 2.5.6 Strains ...........................................................................................................63 viii 2.5.7 Carbon source testing ....................................................................................63 2.6 Acknowledgements ..............................................................................................65 Chapter 3 Comparative genome-scale modelling of multiple S. aureus strains identifies strain-specific pathogenic characteristics and unique metabolic capabilities .................. 73 3.1 Abstract ................................................................................................................74 3.2 Background ..........................................................................................................75 3.3 Results .................................................................................................................78 3.3.1 Building an initial reconstruction of S. aureus as a species ............................78 3.3.2 Characteristics of the S. aureus core and pan-genomes ................................79 3.3.3 Analysis of atypical S. aureus genes .............................................................81 3.3.4 Characteristics of S. aureus core and pan metabolic content.........................82 3.3.5 Determining strain-specific auxotrophies .......................................................83 3.3.6 Calculating alternative nutrient sources .........................................................85 3.3.7 Prediction of essential metabolic genes .........................................................86 3.3.8 S. aureus strains share a core set of ubiquitous genes encoding proteins involved in transcription and translation ..................................................................86 3.3.9 Construction of a virulome for the S. aureus species .....................................88 3.4 Discussion ...........................................................................................................90 3.5 Acknowledgements ..............................................................................................94 Chapter 4 Comparative metabolic network analysis and modelling of four Leptospira species provides insight into pathogenesis of Leptospirosis
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