Genome models characterize bacterial species

A certain nonpathogenic strain of bacteria, Escherichia coli K-12 MG1655, has been invaluable in the laboratory for studying microbial metabolism systems biology. However, the accumulating number of E. coli srtains being sequence is making it obvious that K-12 MG1655 constitutes only a tiny fraction of the genomic diversity among species of E. coli.

In order to better understand the metabolic potential of E. coli species, a team of researchers led by Jonathan Monk from the University of California in San Diego, including Ramy Aziz from Cairo University, constructed genome-scale models (GEMs) of metabolism, which match metabolic genes with metabolic pathways, for 55 fully sequenced strains of E. coli.

The team used the GEMs to examine the ability of different strains to grow in some 650 different nutrient environments. They found that the growth profiles of a strain corresponded with their pathogenicity and ability to adapt to their surroundings. The GEMs were also used to predict whether a strain could synthesize certain vitamins essential for growth and allowed the team to define the differences between the strains of E. coli species based on common metabolic capabilities.

"The fact that we were able to validate 80% of the computational predictions is stunning, knowing that these predictions were computed for 55 genomes," says Aziz. "There is still a lot of work to do, given that the functions of over a third of E. coli gene products still remain unknown and thus not yet in the models."

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