| The availability of sequenced and annotated genomes, coupled with a tremendous knowledge base in scientific literature, has facilitated the construction of genome-scale models (GENREs) of metabolism for a wide variety of organisms. Pseudomonas aeruginosa is a ubiquitous Gram-negative bacterium capable of surviving in many natural environments, in addition to causing both acute infections in immunocompromised patients and chronic lifelong infections in the lungs of Cystic Fibrosis (CF) patients.;In this dissertation, I present a metabolic GENRE of the opportunistic pathogen, P. aeruginosa PAO1. The reconstruction, which accounts for the function of approximately 19% of the P. aeruginosa genome including multiple virulence-related pathways, was validated using gene essentiality data, substrate utilization data, and yield data under several conditions.;To explore changes in metabolism that occur in P. aeruginosa during infection of the CF lung, I integrate the model with existing microarray data from P. aeruginosa isolated from the sputum of a CF patient over multiple years. This analysis provides a novel perspective on the metabolic processes active in P. aeruginosa during infection, and offers predictions of novel drug targets against this pathogen. To further explore the relationship between metabolism and virulence in P. aeruginosa, I perform a series of metabolic phenotyping experiments on mutants of P. aeruginosa PAO1 deficient in genes shown previously to be essential for virulence. These experiments reveal interesting features of metabolism in P. aeruginosa , and suggest the possible presence of several currently uncharacterized pathways.;Finally, I present the first ever reconciliation of metabolic GENREs of two organisms, P. aeruginosa and its non-pathogenic cousin, Pseudomonas putida. This reconciliation involves refining the models to remove differences reflective of noise in model construction, rather than biological differences between the organisms. With these reconciled models, I present the first ever genome-scale network comparison between a pathogen and a non-pathogen, offering insight into metabolic differences that might contribute to the virulence of P. aeruginosa.;With this dissertation, I present a series of genome-scale network analyses of the deadly pathogen P. aeruginosa, and I provide a set of tools that will be of great value for studying this pathogen by future researchers. |
