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Dynamic fluctuations in a bacterial metabolic network

Author

Listed:
  • Shuangyu Bi

    (Max Planck Institute for Terrestrial Microbiology and Center for Synthetic Microbiology (SYNMIKRO)
    Shandong University)

  • Manika Kargeti

    (Max Planck Institute for Terrestrial Microbiology and Center for Synthetic Microbiology (SYNMIKRO))

  • Remy Colin

    (Max Planck Institute for Terrestrial Microbiology and Center for Synthetic Microbiology (SYNMIKRO))

  • Niklas Farke

    (University of Tübingen)

  • Hannes Link

    (University of Tübingen)

  • Victor Sourjik

    (Max Planck Institute for Terrestrial Microbiology and Center for Synthetic Microbiology (SYNMIKRO))

Abstract

The operation of the central metabolism is typically assumed to be deterministic, but dynamics and high connectivity of the metabolic network make it potentially prone to generating fluctuations. However, time-resolved measurements of metabolite levels in individual cells that are required to characterize such fluctuations remained a challenge, particularly in small bacterial cells. Here we use single-cell metabolite measurements based on Förster resonance energy transfer, combined with computer simulations, to explore the real-time dynamics of the metabolic network of Escherichia coli. We observe that steplike exposure of starved E. coli to glycolytic carbon sources elicits large periodic fluctuations in the intracellular concentration of pyruvate in individual cells. These fluctuations are consistent with predicted oscillatory dynamics of E. coli metabolic network, and they are primarily controlled by biochemical reactions around the pyruvate node. Our results further indicate that fluctuations in glycolysis propagate to other cellular processes, possibly leading to temporal heterogeneity of cellular states within a population.

Suggested Citation

  • Shuangyu Bi & Manika Kargeti & Remy Colin & Niklas Farke & Hannes Link & Victor Sourjik, 2023. "Dynamic fluctuations in a bacterial metabolic network," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-37957-0
    DOI: 10.1038/s41467-023-37957-0
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    References listed on IDEAS

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    4. Kevin S. Farquhar & Daniel A. Charlebois & Mariola Szenk & Joseph Cohen & Dmitry Nevozhay & Gábor Balázsi, 2019. "Role of network-mediated stochasticity in mammalian drug resistance," Nature Communications, Nature, vol. 10(1), pages 1-14, December.
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