Oh2007 - Genome-scale metabolic network of Bacillus subtilis (iYO844)

Oh2007 - Genome-scale metabolic network of
Bacillus subtilis (iYO844)

This model is described in the article:

Genome-scale reconstruction
of metabolic network in Bacillus subtilis based on
high-throughput phenotyping and gene essentiality data.

Oh YK, Palsson BO, Park SM,
Schilling CH, Mahadevan R.
J. Biol. Chem. 2007 Sep; 282(39):
28791-28799
Abstract:

In this report, a genome-scale reconstruction of Bacillus
subtilis metabolism and its iterative development based on the
combination of genomic, biochemical, and physiological
information and high-throughput phenotyping experiments is
presented. The initial reconstruction was converted into an in
silico model and expanded in a four-step iterative fashion.
First, network gap analysis was used to identify 48 missing
reactions that are needed for growth but were not found in the
genome annotation. Second, the computed growth rates under
aerobic conditions were compared with high-throughput
phenotypic screen data, and the initial in silico model could
predict the outcomes qualitatively in 140 of 271 cases
considered. Detailed analysis of the incorrect predictions
resulted in the addition of 75 reactions to the initial
reconstruction, and 200 of 271 cases were correctly computed.
Third, in silico computations of the growth phenotypes of
knock-out strains were found to be consistent with experimental
observations in 720 of 766 cases evaluated. Fourth, the
integrated analysis of the large-scale substrate utilization
and gene essentiality data with the genome-scale metabolic
model revealed the requirement of 80 specific enzymes
(transport, 53; intracellular reactions, 27) that were not in
the genome annotation. Subsequent sequence analysis resulted in
the identification of genes that could be putatively assigned
to 13 intracellular enzymes. The final reconstruction accounted
for 844 open reading frames and consisted of 1020 metabolic
reactions and 988 metabolites. Hence, the in silico model can
be used to obtain experimentally verifiable hypothesis on the
metabolic functions of various genes.

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