Evidence map›Paper›PMID 26991085›Full record

ReviewNature chemical biology2016

Toxin-antitoxin systems in bacterial growth arrest and persistence.

Rebecca Page, Wolfgang Peti

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature chemical biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 387 papers.

0numbers the graph read from it
0cells of the map it votes in
387citing papers in PubMed
71.1field-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

387 citing papers in PubMed, 680 citations in OpenAlex.

  1. Article
  2. Article
  3. The role of toxin-antitoxin systems inJournal of bacteriology · 2026
    Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Structural mechanism of SAM-AMP and SAM-AMPNature communications · 2026
    Article
  10. Genomic profiling ofMicrobiology spectrum · 2026
    Article
  11. Article
  12. Review
  13. Microorganisms · 2026
    Review
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

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

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

2 authors at 1 institution in 1 country.

Rebecca PageDepartment of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, Rhode Island, USA.
Wolfgang PetiDepartment of Molecular Pharmacology, Physiology and Biotechnology, Brown University, Providence, Rhode Island, USA.
Brown University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bacterial persister cells constitute a subpopulation of genetically identical, metabolically slow-growing cells that are highly tolerant of antibiotics and other environmental stresses. Recent studies have demonstrated that gene loci known as toxin-antitoxin (TA) modules play a central role in the persister state. Under normal growth conditions, antitoxins potently inhibit the activities of the toxins. In contrast, under conditions of stress, the antitoxins are selectively degraded, freeing the toxins to inhibit essential cellular processes, such as DNA replication and protein translation. This inhibition results in rapid growth arrest. In this Review, we highlight recent discoveries of these multifaceted TA systems with a focus on the newly uncovered mechanisms, especially conditional cooperativity, that are used to regulate cell growth and persistence. We also discuss the potential for targeting TA systems for antimicrobial drug discovery.

Indexed as

Escherichia coliAnti-Bacterial AgentsAntitoxinsBacterial ToxinsDrug DiscoveryDrug Resistance, BacterialModels, BiologicalMutationAnti-Bacterial AgentsAntitoxinsBacterial Toxins

Identifiers

PMID26991085
OpenAlexW2298249827

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.