Evidence map›Paper›PMID 30051800›Full record

ReviewMicrobiology spectrum2018

Type I Toxin-Antitoxin Systems: Regulating Toxin Expression via Shine-Dalgarno Sequence Sequestration and Small RNA Binding.

Sara Masachis, Fabien Darfeuille

Open access · greenAbstract readReview
In one paragraph

Review in Microbiology spectrum, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
5.1field-weighted citation impact, top 4% 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

35 citing papers in PubMed, 50 citations in OpenAlex.

  1. Article
  2. Frontiers in cellular and infection microbiology · 2026
    Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Large Roles of Small Proteins.Annual review of microbiology · 2024
    Review
  8. Article
  9. Disentangling the pseudoknots of toxin translation.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  10. Article
  11. The global RNA-RNA interactome ofProceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Review
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.

Sara MasachisARNA Laboratory, INSERM U1212, CNRS UMR 5320, University of Bordeaux, F-33000 Bordeaux, France.
Fabien DarfeuilleARNA Laboratory, INSERM U1212, CNRS UMR 5320, University of Bordeaux, F-33000 Bordeaux, France.
Centre National de la Recherche Scientifique · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Toxin-antitoxin (TA) systems are small genetic loci composed of two adjacent genes: a toxin and an antitoxin that prevents toxin action. Despite their wide distribution in bacterial genomes, the reasons for TA systems being on chromosomes remain enigmatic. In this review, we focus on type I TA systems, composed of a small antisense RNA that plays the role of an antitoxin to control the expression of its toxin counterpart. It does so by direct base-pairing to the toxin-encoding mRNA, thereby inhibiting its translation and/or promoting its degradation. However, in many cases, antitoxin binding is not sufficient to avoid toxicity. Several

Indexed as

Gene Expression Regulation, BacterialAntitoxinsBacterial ProteinsBacterial ToxinsChromosomes, BacterialGenome, BacterialRNA, AntisenseRNA, BacterialRNA, MessengerToxin-Antitoxin SystemsAntitoxinsBacterial ProteinsBacterial ToxinsRNA, AntisenseRNA, BacterialRNA, Messenger

Identifiers

PMID30051800
PMCPMC11633621
OpenAlexW2898277406

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.