Evidence map›Paper›PMID 39672961›Full record

ArticleNature microbiology2025

Metabolic rearrangement enables adaptation of microbial growth rate to temperature shifts.

Benjamin D Knapp, Lisa Willis, Carlos Gonzalez, Harsh Vashistha, Joanna Jammal-Touma, Mikhail Tikhonov, Jeffrey Ram, Hanna Salman, Josh E Elias, Kerwyn Casey Huang

Abstract read
PubMed Publisher
In one paragraph

Article in Nature microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Living Hydrogels: Harnessing Microorganism-Material Synergy for Next-Generation Therapeutics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Gut Bacteria Strategies ofMicroorganisms · 2025
    Article
  18. 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

10 authors.

Benjamin D KnappBiophysics Program, Stanford University, Stanford, CA, USA.
Lisa WillisDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
Carlos GonzalezDepartment of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA.
Harsh VashisthaDepartment of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA, USA.
Joanna Jammal-ToumaDepartment of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA, USA.
Mikhail TikhonovDepartment of Physics, Washington University in St Louis, St Louis, MO, USA.ORCID http://orcid.org/0000-0002-9558-1121
Jeffrey RamDepartment of Physiology, Wayne State University, Detroit, MI, USA.
Hanna SalmanDepartment of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA, USA.ORCID http://orcid.org/0000-0002-5847-524X
Josh E EliasChan Zuckerberg Biohub, San Francisco, CA, USA.ORCID http://orcid.org/0000-0002-8063-3259
Kerwyn Casey HuangBiophysics Program, Stanford University, Stanford, CA, USA. kchuang@stanford.edu.ORCID http://orcid.org/0000-0002-8043-8138

Funding

National Science Foundation (NSF) EF-2125383
6 · The paper itself

Abstract

Temperature is a key determinant of microbial behaviour and survival in the environment and within hosts. At intermediate temperatures, growth rate varies according to the Arrhenius law of thermodynamics, which describes the effect of temperature on the rate of a chemical reaction. However, the mechanistic basis for this behaviour remains unclear. Here we use single-cell microscopy to show that Escherichia coli exhibits a gradual response to temperature upshifts with a timescale of ~1.5 doublings at the higher temperature. The response was largely independent of initial or final temperature and nutrient source. Proteomic and genomic approaches demonstrated that adaptation to temperature is independent of transcriptional, translational or membrane fluidity changes. Instead, an autocatalytic enzyme network model incorporating temperature-sensitive Michaelis-Menten kinetics recapitulates all temperature-shift dynamics through metabolome rearrangement, resulting in a transient temperature memory. The model successfully predicts alterations in the temperature response across nutrient conditions, diverse E. coli strains from hosts with different body temperatures, soil-dwelling Bacillus subtilis and fission yeast. In sum, our model provides a mechanistic framework for Arrhenius-dependent growth.

Indexed as

Adaptation, PhysiologicalEscherichia coliBacillus subtilisKineticsMetabolomeProteomicsSchizosaccharomycesSingle-Cell AnalysisTemperature

Identifiers

What OpenQuestion holds

Textmetadata
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.