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Overflow metabolism in Escherichia coli results from efficient proteome allocation

Author

Listed:
  • Markus Basan

    (University of California at San Diego
    Institute of Molecular Systems Biology)

  • Sheng Hui

    (University of California at San Diego)

  • Hiroyuki Okano

    (University of California at San Diego
    Section of Molecular Biology, University of California at San Diego)

  • Zhongge Zhang

    (Section of Molecular Biology, University of California at San Diego)

  • Yang Shen

    (Section of Molecular Biology, University of California at San Diego)

  • James R. Williamson

    (The Skaggs Institute for Chemical Biology, The Scripps Research Institute)

  • Terence Hwa

    (University of California at San Diego
    Section of Molecular Biology, University of California at San Diego
    Institute for Theoretical Studies)

Abstract

Overflow metabolism refers to the seemingly wasteful strategy in which cells use fermentation instead of the more efficient respiration to generate energy, despite the availability of oxygen. Known as the Warburg effect in the context of cancer growth, this phenomenon occurs ubiquitously for fast-growing cells, including bacteria, fungi and mammalian cells, but its origin has remained unclear despite decades of research. Here we study metabolic overflow in Escherichia coli, and show that it is a global physiological response used to cope with changing proteomic demands of energy biogenesis and biomass synthesis under different growth conditions. A simple model of proteomic resource allocation can quantitatively account for all of the observed behaviours, and accurately predict responses to new perturbations. The key hypothesis of the model, that the proteome cost of energy biogenesis by respiration exceeds that by fermentation, is quantitatively confirmed by direct measurement of protein abundances via quantitative mass spectrometry.

Suggested Citation

  • Markus Basan & Sheng Hui & Hiroyuki Okano & Zhongge Zhang & Yang Shen & James R. Williamson & Terence Hwa, 2015. "Overflow metabolism in Escherichia coli results from efficient proteome allocation," Nature, Nature, vol. 528(7580), pages 99-104, December.
  • Handle: RePEc:nat:nature:v:528:y:2015:i:7580:d:10.1038_nature15765
    DOI: 10.1038/nature15765
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    Cited by:

    1. Christian Schulz & Tjasa Kumelj & Emil Karlsen & Eivind Almaas, 2021. "Genome-scale metabolic modelling when changes in environmental conditions affect biomass composition," PLOS Computational Biology, Public Library of Science, vol. 17(5), pages 1-22, May.
    2. Robert Planqué & Josephus Hulshof & Bas Teusink & Johannes C Hendriks & Frank J Bruggeman, 2018. "Maintaining maximal metabolic flux by gene expression control," PLOS Computational Biology, Public Library of Science, vol. 14(9), pages 1-20, September.
    3. Marcelo Rivas-Astroza & Raúl Conejeros, 2020. "Metabolic flux configuration determination using information entropy," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-19, December.

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