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Downloads/Cobratoolbox UC San Diego UC San Diego Electronic Theses and Dissertations Title A stoichiometric model of Escherichia coli 's macromolecular synthesis machinery and its integration with metabolism Permalink https://escholarship.org/uc/item/1z9752m7 Author Thiele, Ines Publication Date 2009 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA, SAN DIEGO A stoichiometric model of Escherichia coli's macromolecular synthesis machinery and its integration with metabolism. A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Bioinformatics by Ines Thiele Committee in charge: Professor Bernhard Ø. Palsson, Chair Professor Steven P. Briggs, Co-Chair Professor Alexander Hoffmann Professor Milton H. Saier Professor Julian I. Schroeder 2009 Copyright Ines Thiele, 2009 All rights reserved. The dissertation of Ines Thiele is approved, and it is acceptable in quality and form for publication on microfilm and electronically: Co-Chair Chair University of California, San Diego 2009 iii DEDICATION To Renate, Steffen, Dana, and Ronan. iv TABLE OF CONTENTS Signature Page . iii Dedication . iv Table of Contents . v List of Figures . viii List of Tables . x Acknowledgements . xi Vita and Publications . xiii Abstract of the Dissertation . xv Chapter 1 Introduction to molecular systems biology . 1 1.1 Constraint-based reconstruction and analysis . 2 1.2 Basic principles underlying the constraint-ba-sed reconstruction & analysis approach . 4 1.3 Reconstruction of metabolic networks in a nutshell . 6 1.4 Mathematical characterization of network capabilities . 8 1.5 Tools for analyzing network states. 9 1.6 Preview of the dissertation . 11 Chapter 2 Escherichia coli ............................... 13 2.1 Key properties . 13 2.2 E.coli by numbers . 16 2.3 Conclusion . 21 Chapter 3 A protocol for generating a high-quality genome-scale metabolic recon- struction . 22 3.1 Introduction . 23 3.2 General procedure . 29 3.3 Materials . 30 3.3.1 Equipment . 30 3.3.2 Equipment setup . 31 3.4 Procedure . 33 3.4.1 Creating a draft reconstruction . 33 3.4.2 Manual reconstruction refinement . 35 3.4.3 Conversion from reconstruction to mathematical model . 59 3.4.4 Network evaluation = 'Debugging mode' . 61 3.4.5 Data assembly and Dissemination . 77 3.5 Timing . 78 3.6 Troubleshooting . 78 v 3.7 Anticipated Results . 79 Chapter 4 State-of the art reconstructions of cellular networks . 83 4.1 Available metabolic reconstructions . 83 4.1.1 Metabolic reconstructions of Escherichia coli . 84 4.2 Reconstruction jamborees . 86 4.3 Reconstruction of other cellular networks . 91 4.3.1 Reconstruction of signaling networks . 91 4.3.2 Reconstruction of transcriptional regulatory networks . 92 4.3.3 Reconstruction of transcription and translation . 93 4.3.4 Reconstruction of integrated networks . 93 Chapter 5 From Biology to computers - Representation of biological processes in computable format . 94 5.1 Transcription: From DNA to RNA . 95 5.2 Translation . 100 5.3 Protein Maturation. 103 5.4 Metallo-ions incorporation. 104 5.5 Protein Folding. 108 5.6 mRNA degradation. 111 5.7 tRNA and rRNA processing. 112 Chapter 6 Genome-scale reconstruction of Escherichia coli's transcriptional and translational machinery . 113 6.1 Introduction . 114 6.2 Methods . 118 6.3 Results and Discussion . 123 6.3.1 Legacy data. 124 6.3.2 Reconstruction approach. 124 6.3.3 Unique properties of the 'E-matrix'. 124 6.3.4 'E-matrix' versus available databases. 126 6.3.5 Knowledge gaps. 127 6.3.6 Network topology. 128 6.3.7 Validation of the 'E-matrix' functionality - Ribosome pro- duction. 129 6.3.8 The effect of in silico rRNA operon deletions on ribosome production. 129 6.3.9 Integration of '-omics' data into 'E-matrix'. 132 6.3.10 Defining functional modules. 134 6.3.11 Integration with other cellular functions. 135 6.4 Conclusion . 136 Chapter 7 Functional characterization of alternate optimal solutions of Escherichia coli's transcriptional & translational machinery . 138 7.1 Introduction . 139 7.2 Material and Methods . 142 7.3 Results . 154 vi 7.4 Conclusion . 161 Chapter 8 An integrated model of macromolecular synthesis and metabolism of Escherichia coli. ..............................163 8.1 Introduction . 163 8.2 Materials and Methods . 165 8.2.1 Constraint-based reconstruction and modeling appro-ach . 165 8.2.2 Reconstruction of the 'ME'-matrix . 166 8.3 Results & Discussion . 175 8.3.1 Properties of the reconstruction . 175 8.3.2 Model Validation . 180 8.3.3 Novel Application . 185 8.4 Conclusion . 196 Chapter 9 Conclusion: Towards whole-cell modeling . 198 9.1 Constraint-based reconstruction and analysis approach as tool of choice . 198 9.2 Challenges in reconstructing non-metabolic functions . 199 9.3 Integration of metabolism and macromolecular synthesis - A stiff matrix . 200 9.4 Applications of integrated models . 201 9.5 What's next . 202 Chapter 10 Glossary . 205 Bibliography . 209 vii LIST OF FIGURES Figure 1.1: Bringing genomes to life . 3 Figure 1.2: General workflow for reconstructing cellular networks . 7 Figure 2.2: Dependency of cellular properties and growth rate in E. coli. 18 Figure 3.1: Overview of the procedure to iteratively reconstruct metabolic networks 24 Figure 3.2: Refinement of reconstruction content . 28 Figure 3.3: Information used for draft reconstruction . 33 Figure 3.4: Example of a draft reconstruction . 34 Figure 3.5: Assessing the metabolic "environment" or "connectivity" of a metabolite 37 Figure 3.6: Examples of possible Gene-protein-reaction associations . 41 Figure 3.7: Conversion of reconstruction into a condition-specific model . 47 Figure 3.8: Example of biomass composition determination for Pseudomonas putida KT 2440. 48 Figure 3.9: Flow chart to calculate the fractional contribution of a precursor to the biomass reaction . 50 Figure 3.10: Determination of the content of soluble pool . 51 Figure 3.11: Calculation of biomass coefficient of ions . 52 Figure 3.12: Growth-associated maintenance cost . 54 Figure 3.13: Schematic representation of the assembly of the biomass reaction . 56 Figure 3.14: Layout of excel sheets as input for xls2model function. 59 Figure 3.15: Model in Matlab format and the COBRA Toolbox . 60 Figure 3.16: Example of a stoichiometrically balanced cycle . 64 Figure 3.17: Flow chart on debugging network reactions that cannot carry flux . 65 Figure 3.18: Gap analysis. 80 Figure 3.19: Network evaluation . 81 Figure 3.20: Physiological properties that can be important for network evaluation 82 Figure 4.1: Growth of genome sequences and genome-scale metabolic reconstructions 84 Figure 4.2: List of information that needs to be associated with each metabolite and each reaction in the consensus reconstruction . 88 Figure 4.3: Workflow of the Salmonella reconstruction jamboree . 90 Figure 5.1: Examples of transcription units in E. coli . 95 Figure 6.1: Overview of constraint-based reconstruction and analysis . 116 Figure 6.2: Content of the 'E-matrix' . 117 Figure 6.3: Comparison of in vivo and in silico maximal number of ribosomes . 128 Figure 6.4: rRNA operon deletion study . 130 Figure 6.5: Integration of "-omics" data into 'E-matrix' as reaction constraints . 133 Figure 6.6: Schematic representation of in silico functional modules . 135 Figure 7.1: Schematic illustration of alternate optimal solutions . 140 Figure 7.2: Schematic representation of the mRNA and protein pools present in the E-matrix. 145 viii Figure 7.3: Schematic representation of the participation of tr/tr enzymes in net- work reactions . 146 Figure 7.4: Illustration of reduction of flux span . 149 Figure 7.5: Properties of AOS in E-matrix . 155 Figure 7.6: Principal component analysis . 160 Figure 8.1: Functional synergy between the metabolic network and the.
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