Salmonella is a major cause of human and animal enteric disease. Salmonella consists of 2 species: bongeri and enterica and the latter can be further divided into subspecies (I-VI). The majority of human and animal infections are caused by Salmonella enterica subspecies I. Salmonella enterica subspecies enterica can be further divided into over 2,500 antigenically distinct serovars (Popoff et al. 2004). The serovars can also be classified on the basis of the types of infection caused and in humans, the 2 most dominant Salmonella serovars are Typhimurium and Enteritidis which can be acquired from various animal and environmental sources. The availability of genome sequencing has enabled a greater understanding of the similarities and differences between bacterial species and provided further insights into the disease potentials and the ecological niche of the Salmonella serovars. In collaboration with researchers at the Veterinary Laboratories Agency (Weybridge) in the UK, we developed a model of Salmonella Typhimurium LT2, iMA945, which incorporated 945 ORFs and included 1,964 reactions and 1,036 metabolites. We followed a similar approach as with the construction of the M. genitalium model but were additionally able to make use of phenotype data in a modification of GrowMatch. Specifically, using Phenotyping MicroArrayTM (Biolog), we were able to incorporate several substrate utilization differences that were highlighted among Escherichia coli, S. Typimurium LT2, S. Typhimurium DT104 and S. Enteritidis PT4. We were able to make comparisons for over 200 of the substrates and found that the model iMA945 correctly identified 133 out of a total of 144 growth substrates genes (i.e., sensitivity of 92%) and 38 out of a total of 57 non-growth substrates (i.e., specificity of 67%). This implies that the model was 85% correct in its overall accuracy in growth predictions (i.e., 171 of 201). Most of the mismatches (63%) were over-predictions of the metabolic capabilities (i.e., predicting growth when none is observed in vivo) instead of under-predictions (i.e., predicting no growth when growth is observed in vivo).
AbuOun, M., P.F. Suthers, G.I. Jones, B.R. Carter, M.P. Saunders, C.D. Maranas, M.J. Woodward, and M.F. Anjun (2009), "Genome scale reconstruction of a Salmonella metabolic model: comparison of similarity and differences with a commensal Escherichia coli strain," Journal of Biological Chemistry, 284(43):29480-8.
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