Genome scale reconstruction of a Salmonella metabolic model: comparison of similarity and differences with a commensal Escherichia coli strain

Abstract

Salmonella are closely related to commensal Escherichia coli but have gained virulence factors enabling them to behave as enteric pathogens. Less well studied are the similarities and differences that exist between the metabolic properties of these organisms that may contribute toward niche adaptation of Salmonella pathogens. To address this, we have constructed a genome scale Salmonella metabolic model (iMA945). The model comprises 945 open reading frames or genes, 1964 reactions, and 1036 metabolites. There was significant overlap with genes present in E. coli MG1655 model iAF1260. In silico growth predictions were simulated using the model on different carbon, nitrogen, phosphorous, and sulfur sources. These were compared with substrate utilization data gathered from high throughput phenotyping microarrays revealing good agreement. Of the compounds tested, the majority were utilizable by both Salmonella and E. coli. Nevertheless a number of differences were identified both between Salmonella and E. coli and also within the Salmonella strains included. These differences provide valuable insight into differences between a commensal and a closely related pathogen and within different pathogenic strains opening new avenues for future explorations.

FIGURE 1.

A, a Venn diagram that showsthe homology overlap between the S. typhimurium model iMA945 and the E. coli model iAF1260. B, classification of the ORFs included in iMA945 grouped into COG functional categories. The length of each bar represents the number of genes in each COG that is included in the model. The percent assigned to each class refers to the coverage of the total number in the genome accounted for in the model. Some of the ORFs do not currently have a COG functional category assignment (here represented as N/A). Note that although each ORF is only counted once within each COG functional category, some ORFs have multiple COG category assignments.