Evidence map›Paper›PMID 24723921›Full record

ArticleFrontiers in microbiology2014

A mathematical model of metabolism and regulation provides a systems-level view of how Escherichia coli responds to oxygen.

Michael Ederer, Sonja Steinsiek, Stefan Stagge, Matthew D Rolfe, Alexander Ter Beek, David Knies, M Joost Teixeira de Mattos, Thomas Sauter, Jeffrey Green, Robert K Poole and 2 more

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Impact of Hydrogen Sulfide on Mitochondrial and Bacterial Bioenergetics.International journal of molecular sciences · 2021
    Review
  4. Article
  5. Bacterial Oxidases of the CytochromeAntioxidants & redox signaling · 2021
    Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Homeostasis of metabolites inRoyal Society open science · 2016
    Article
  15. Article
  16. Article
  17. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Michael EdererInstitute for System Dynamics, University of Stuttgart Stuttgart, Germany.
Sonja SteinsiekMax Planck Institute for Dynamics of Complex Technical Systems Magdeburg, Germany.
Stefan StaggeMax Planck Institute for Dynamics of Complex Technical Systems Magdeburg, Germany.
Matthew D RolfeDepartment of Molecular Biology and Biotechnology, The University of Sheffield Sheffield, UK.
Alexander Ter BeekMolecular Microbial Physiology, Swammerdam Institute for Life Sciences, University of Amsterdam Amsterdam, Netherlands.
David KniesInstitute for System Dynamics, University of Stuttgart Stuttgart, Germany.
M Joost Teixeira de MattosMolecular Microbial Physiology, Swammerdam Institute for Life Sciences, University of Amsterdam Amsterdam, Netherlands.
Thomas SauterLife Sciences Research Unit, Université du Luxembourg Luxembourg, Luxembourg.
Jeffrey GreenDepartment of Molecular Biology and Biotechnology, The University of Sheffield Sheffield, UK.
Robert K PooleDepartment of Molecular Biology and Biotechnology, The University of Sheffield Sheffield, UK.
Katja BettenbrockMax Planck Institute for Dynamics of Complex Technical Systems Magdeburg, Germany.
Oliver SawodnyInstitute for System Dynamics, University of Stuttgart Stuttgart, Germany.

Funding

Biotechnology and Biological Sciences Research Council BB/I004122/1
6 · The paper itself

Abstract

The efficient redesign of bacteria for biotechnological purposes, such as biofuel production, waste disposal or specific biocatalytic functions, requires a quantitative systems-level understanding of energy supply, carbon, and redox metabolism. The measurement of transcript levels, metabolite concentrations and metabolic fluxes per se gives an incomplete picture. An appreciation of the interdependencies between the different measurement values is essential for systems-level understanding. Mathematical modeling has the potential to provide a coherent and quantitative description of the interplay between gene expression, metabolite concentrations, and metabolic fluxes. Escherichia coli undergoes major adaptations in central metabolism when the availability of oxygen changes. Thus, an integrated description of the oxygen response provides a benchmark of our understanding of carbon, energy, and redox metabolism. We present the first comprehensive model of the central metabolism of E. coli that describes steady-state metabolism at different levels of oxygen availability. Variables of the model are metabolite concentrations, gene expression levels, transcription factor activities, metabolic fluxes, and biomass concentration. We analyze the model with respect to the production capabilities of central metabolism of E. coli. In particular, we predict how precursor and biomass concentration are affected by product formation.

Indexed as

Escherichia colifermentationmathematical modelingmetabolismregulationrespirationthermokinetic modeling

Identifiers

PMID24723921
PMCPMC3973912

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.