A comprehensive genome-scale reconstruction of Escherichia coli metabolism—2011

A comprehensive genome-scale reconstruction of Escherichia coli metabolism—2011

2011 | Jeffrey D Orth, Tom M Conrad, Jessica Na, Joshua A Lerman, Hojung Nam, Adam M Feist and Bernhard Ø Palsson
The article presents an updated genome-scale metabolic network reconstruction of *Escherichia coli* K-12 MG1655, named *iJO1366*. This reconstruction includes 1366 genes, 2251 metabolic reactions, and 1136 unique metabolites. The update was made using a new experimental screen of 1075 gene knockout strains, which identified cases where alternative pathways and isozymes are yet to be discovered. The reconstruction was also compared with its predecessor and experimental data sets to confirm its accuracy in predicting growth on different substrates and for gene knockout strains. Additionally, the reconstruction was mapped to the genomes of all available sequenced *E. coli* strains, including pathogens, leading to the identification of hundreds of unannotated genes in these organisms. The *iJO1366* reconstruction is expected to be widely used for studying the systems biology of *E. coli* and for metabolic engineering applications.The article presents an updated genome-scale metabolic network reconstruction of *Escherichia coli* K-12 MG1655, named *iJO1366*. This reconstruction includes 1366 genes, 2251 metabolic reactions, and 1136 unique metabolites. The update was made using a new experimental screen of 1075 gene knockout strains, which identified cases where alternative pathways and isozymes are yet to be discovered. The reconstruction was also compared with its predecessor and experimental data sets to confirm its accuracy in predicting growth on different substrates and for gene knockout strains. Additionally, the reconstruction was mapped to the genomes of all available sequenced *E. coli* strains, including pathogens, leading to the identification of hundreds of unannotated genes in these organisms. The *iJO1366* reconstruction is expected to be widely used for studying the systems biology of *E. coli* and for metabolic engineering applications.
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