Evidence map›Paper›PMID 30132188›Full record

ReviewCurrent genetics2019

Autoregulation of bacterial gene expression: lessons from the MazEF toxin-antitoxin system.

Nela Nikolic

Open access · hybridAbstract readReview
In one paragraph

Review in Current genetics, 2019. 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
2.4field-weighted citation impact, top 11% 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

18 citing papers in PubMed, 28 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. HigB1 Toxin inFrontiers in microbiology · 2021
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Bacterial ribonucleases and their roles in RNA metabolism.Critical reviews in biochemistry and molecular biology · 2019
    Review
  16. Review
  17. Microorganisms · 2019
    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

1 author at 1 institution in 1 country.

Nela NikolicInstitute of Science and Technology (IST) Austria, 3400, Klosterneuburg, Austria. nela.nikolic@ist.ac.at.ORCID http://orcid.org/0000-0001-9068-6090
Institute of Science and Technology Austria · AT

Funding

Austrian Science Fund FWF V 738FP7 PEOPLE ISTFELLOW
6 · The paper itself

Abstract

Autoregulation is the direct modulation of gene expression by the product of the corresponding gene. Autoregulation of bacterial gene expression has been mostly studied at the transcriptional level, when a protein acts as the cognate transcriptional repressor. A recent study investigating dynamics of the bacterial toxin-antitoxin MazEF system has shown how autoregulation at both the transcriptional and post-transcriptional levels affects the heterogeneity of Escherichia coli populations. Toxin-antitoxin systems hold a crucial but still elusive part in bacterial response to stress. This perspective highlights how these modules can also serve as a great model system for investigating basic concepts in gene regulation. However, as the genomic background and environmental conditions substantially influence toxin activation, it is important to study (auto)regulation of toxin-antitoxin systems in well-defined setups as well as in conditions that resemble the environmental niche.

Indexed as

Gene Expression Regulation, BacterialBacteriaBacterial ProteinsBacterial ToxinsDNA-Binding ProteinsEndoribonucleasesEscherichia coliEscherichia coli ProteinsHomeostasisToxin-Antitoxin SystemsBacterial ProteinsBacterial ToxinsDNA-Binding ProteinsEndoribonucleasesEscherichia coli ProteinsMazE protein, E coliMazF protein, E coliAutoregulationFeedbackGene expressionMazFPhenotypic heterogeneityToxin–antitoxin system

Identifiers

PMID30132188
PMCPMC6343021
OpenAlexW2888146605

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.