Evidence map›Paper›PMID 31363068›Full record

ArticleScience signaling2019

Slow growth determines nonheritable antibiotic resistance in

Mauricio H Pontes, Eduardo A Groisman

Open access · bronzeAbstract read
In one paragraph

Article in Science signaling, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 129 papers.

0numbers the graph read from it
0cells of the map it votes in
129citing papers in PubMed
26.7field-weighted citation impact, top 1% 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

129 citing papers in PubMed, 210 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Microorganisms · 2026
    Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Netupitant Exhibits Potent Activity onACS infectious diseases · 2025
    Article
  17. Review
  18. Article
  19. Article
  20. Article

69 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Mauricio H PontesDepartment of Microbial Pathogenesis, Yale School of Medicine, 295 Congress Avenue, New Haven, CT 06536, USA.ORCID 0000-0002-2618-2039
Eduardo A GroismanDepartment of Microbial Pathogenesis, Yale School of Medicine, 295 Congress Avenue, New Haven, CT 06536, USA. eduardo.groisman@yale.edu.ORCID 0000-0001-6860-7691
Yale University · US

Funding

REGULATION OF SALMONELLA VIRULENCE BY THE PHOP PROTEINR01AI049561 · NIAID · YALE UNIVERSITY · PI Eduardo Groisman · 2001 to 2026
$9.7M
NIAID NIH HHS R01 AI049561
6 · The paper itself

Abstract

Bacteria can withstand killing by bactericidal antibiotics through phenotypic changes mediated by their preexisting genetic repertoire. These changes can be exhibited transiently by a large fraction of the bacterial population, giving rise to tolerance, or displayed by a small subpopulation, giving rise to persistence. Apart from undermining the use of antibiotics, tolerant and persistent bacteria foster the emergence of antibiotic-resistant mutants. Persister formation has been attributed to alterations in the abundance of particular proteins, metabolites, and signaling molecules, including toxin-antitoxin modules, adenosine triphosphate, and guanosine (penta) tetraphosphate, respectively. Here, we report that persistent bacteria form as a result of slow growth alone, despite opposite changes in the abundance of such proteins, metabolites, and signaling molecules. Our findings argue that transitory disturbances to core activities, which are often linked to cell growth, promote a persister state regardless of the underlying physiological process responsible for the change in growth.

Indexed as

Drug Resistance, BacterialSalmonella enterica

Identifiers

PMID31363068
PMCPMC7206539
OpenAlexW2966075625

What OpenQuestion holds

Textmetadata
LicenceTDM
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.