UC San Diego

Genome-scale models of microbial metabolism have become a commonly used tool in the systems biology toolbox. These tools can predict, based solely on an organism’s genome sequence, its metabolic capabilities and unique phenotypes in different conditions and under unique perturbations. Furthermore, an array of in-silico methods have been developed that can be applied to these models to more deeply characterize an organism, re-engineer it and even to design effective ways to interrupt and kill it. This dissertation discusses the creation and analysis of multiple genome-scale models of metabolism for different microbial pathogens.

Chapter 1 describes aspects of systems biology that are used throughout this thesis. Topics include the theory and practice of metabolic network reconstruction, genome-scale modelling and flux balance analysis.

Chapter 2 focuses on the reconstruction and analysis of multiple genome-scale metabolic reconstructions of diverse Escherichia coli strains. The results highlight strain-specific adaptations to nutritional environments.

Chapter 3 details comparative genome-scale modelling of multiple S. aureus strains to identify strain-specific pathogenic characteristics and unique metabolic capabilities that are related to infectious capabilities.

Chapter 4 engages in a comparative metabolic network analysis and modelling of four Leptospira species that provide insight into pathogenesis of Leptospirosis.

Chapter 5 examines seven industrially relevant strains of E. coli using transcriptomics and genome-scale models to quantifying variation between the strains that will likely have an impact on host strain selection for metabolic engineering applications.

Chapter 6 conducts an in-depth analysis of existing metabolic network reconstructions and identifies areas where they may need further development.

Chapter 7 details the construction of an updated comprehensive and high-quality genome-scale reconstruction for Escherichia coli K-12 MG1655. The model is experimentally validated with gene-knockout studies. Extension to the model are provided, including an application involving production of reactive oxygen species.

Chapter 8 describes the reconstruction of a metabolic network and associated three-dimensional protein structures for Staphlyococcus aureus USA300. The model is used to examine basic S. aureus biochemistry.

Chapter 9 examines the current state and predicted future of systems biology applications for studying, examining and comparing microbial pathogens.