Genome Scale Metabolic Modeling and Analysis of Clostridium Difficile

Clostridium difficile is a pathogen of high clinical interest due to its persistence as a hospital-borne infection. Previous studies suggest that differences in metabolic capabilities are contributing factors to resistance and virulence. As a means of systematically understanding the linkage between genotype and phenotype of this organism we constructed a new genome-scale reconstruction of C. difficile strain 630 that builds and improves upon previous efforts. The model recapitulates experimental gene knockout predictions with 91% accuracy. We deploy constraint-based reconstruction and analysis along with flux-balance analysis to investigate metabolic capabilities by systematically predicting growth capabilities in over 180 nutrient environments. We utilize the reconstruction to build strain-specific models of 32 isolates including both symptomatic and asymptomatic strains and identified unique differentiating metabolic capabilities. We experimentally validate the models by generating Biolog phenotypic microarray data for all 32 of these strains and compared results to model predictions.