Evidence map›Paper›PMID 27010473›Full record

ArticlePLoS computational biology2016

Cellular Growth Arrest and Persistence from Enzyme Saturation.

J Christian J Ray, Michelle L Wickersheim, Ameya P Jalihal, Yusuf O Adeshina, Tim F Cooper, Gábor Balázsi

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
3.1field-weighted citation impact, top 8% of its field
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

22 citing papers in PubMed, 37 citations in OpenAlex.

  1. Article
  2. Nonlethal deleterious mutation-induced stress accelerates bacterial aging.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. How Do Cells Adapt? Stories Told in Landscapes.Annual review of chemical and biomolecular engineering · 2020
    Review
  14. Diversity inmBio · 2019
    Article
  15. Article
  16. Power-law tail in lag time distribution underlies bacterial persistence.Proceedings of the National Academy of Sciences of the United States of America · 2019
    Article
  17. Article
  18. Article
  19. Article
  20. 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

6 authors at 3 institutions in 2 countries.

J Christian J RayThe University of Texas MD Anderson Cancer Center, Department of Systems Biology, Houston, Texas, United States of America.
Michelle L WickersheimDepartment of Molecular Biosciences, University of Kansas, Lawrence, Kansas, United States of America.
Ameya P JalihalCenter for Computational Biology, University of Kansas, Lawrence, Kansas, United States of America.
Yusuf O AdeshinaCenter for Computational Biology, University of Kansas, Lawrence, Kansas, United States of America.
Tim F CooperDepartment of Biology and Biochemistry, University of Houston, Houston, Texas, United States of America.
Gábor BalázsiThe University of Texas MD Anderson Cancer Center, Department of Systems Biology, Houston, Texas, United States of America.
University of Kansas · USThe University of Texas MD Anderson Cancer Center · USUniversity of Houston · US

Funding

Mentoring CoreP20GM103418 · NIGMS · UNIVERSITY OF KANSAS MEDICAL CENTER · PI Douglas E Wright · 2012 to 2026
$63.0M
Connecting the selection of noisy gene expression deviants to genetic evolutionDP2OD006481 · OD · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI BALAZSI, GABOR · 2009 to 2009
$2.3M
NIGMS NIH HHS P20 GM103418NIGMS NIH HHS P20GM103418NIH HHS 1DP2 OD006481NIH HHS DP2 OD006481
6 · The paper itself

Abstract

Metabolic efficiency depends on the balance between supply and demand of metabolites, which is sensitive to environmental and physiological fluctuations, or noise, causing shortages or surpluses in the metabolic pipeline. How cells can reliably optimize biomass production in the presence of metabolic fluctuations is a fundamental question that has not been fully answered. Here we use mathematical models to predict that enzyme saturation creates distinct regimes of cellular growth, including a phase of growth arrest resulting from toxicity of the metabolic process. Noise can drive entry of single cells into growth arrest while a fast-growing majority sustains the population. We confirmed these predictions by measuring the growth dynamics of Escherichia coli utilizing lactose as a sole carbon source. The predicted heterogeneous growth emerged at high lactose concentrations, and was associated with cell death and production of antibiotic-tolerant persister cells. These results suggest how metabolic networks may balance costs and benefits, with important implications for drug tolerance.

Indexed as

Models, Biologicalbeta-GalactosidaseCell Cycle CheckpointsCell ProliferationComputer SimulationEnzyme ActivationEnzymesEscherichia coliEscherichia coli ProteinsMetabolic Clearance RateMonosaccharide Transport ProteinsSymportersbeta-GalactosidaseEnzymesEscherichia coli ProteinsLacY protein, E coliMonosaccharide Transport ProteinsSymporters

Identifiers

PMID27010473
PMCPMC4820279
OpenAlexW2306812571

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.