Basic and applied uses of genome-scale metabolic network reconstructions of Escherichia coli

  title={Basic and applied uses of genome-scale metabolic network reconstructions of Escherichia coli},
  author={Douglas McCloskey and Bernhard O. Palsson and Adam M. Feist},
  journal={Molecular Systems Biology},
  pages={661 - 661}
The genome‐scale model (GEM) of metabolism in the bacterium Escherichia coli K‐12 has been in development for over a decade and is now in wide use. GEM‐enabled studies of E. coli have been primarily focused on six applications: (1) metabolic engineering, (2) model‐driven discovery, (3) prediction of cellular phenotypes, (4) analysis of biological network properties, (5) studies of evolutionary processes, and (6) models of interspecies interactions. In this review, we provide an overview of… 
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Software platforms to facilitate reconstructing genome-scale metabolic networks.
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The growing scope of applications of genome-scale metabolic reconstructions using Escherichia coli
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A comprehensive genome-scale reconstruction of Escherichia coli metabolism—2011
The initial genome‐scale reconstruction of the metabolic network of Escherichia coli K‐12 MG1655 was assembled in 2000 and an update has now been built, named iJO1366, which accounts for 1366 genes, 2251 metabolic reactions, and 1136 unique metabolites.
The global transcriptional regulatory network for metabolism in Escherichia coli exhibits few dominant functional states.
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The Escherichia coli MG1655 in silico metabolic genotype: its definition, characteristics, and capabilities.
  • J. Edwards, B. Palsson
  • Biology, Engineering
    Proceedings of the National Academy of Sciences of the United States of America
  • 2000
It was shown that based on stoichiometric and capacity constraints the in silico analysis was able to qualitatively predict the growth potential of mutant strains in 86% of the cases examined.
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This study demonstrates that the cellular objective of maximizing maintenance energy expenditure provides a better description of the underlying physiological state in recombinant microorganisms relevant to biotechnological applications.
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