Evidence map›Paper›PMID 26819549›Full record

ArticlePerspectives in medicinal chemistry2016

Interfering with Bacterial Quorum Sensing.

Kerstin Reuter, Anke Steinbach, Volkhard Helms

Open access · hybridAbstract read
In one paragraph

Article in Perspectives in medicinal chemistry, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed
9.7field-weighted citation impact, top 2% 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

51 citing papers in PubMed, 126 citations in OpenAlex.

  1. Article
  2. Review
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  4. Review
  5. The effect of cCMP and cUMP on growth ofFrontiers in microbiology · 2025
    Article
  6. Review
  7. Review
  8. Article
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  11. Article
  12. Spiramycin DisarmsAntibiotics (Basel, Switzerland) · 2023
    Article
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  14. Article
  15. Article
  16. Review
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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

3 authors at 1 institution in 1 country.

Kerstin ReuterCenter for Bioinformatics, Saarland University, Saarbrücken, Germany.; Saarbrücken Graduate School of Computer Science, Saarland University, Saarbrücken, Germany.
Anke SteinbachDepartment of Drug Design and Optimization, Helmholtz-Institute for Pharmaceutical Research Saarland (HIPS), Saarland University, Saarbrücken, Germany.
Volkhard HelmsCenter for Bioinformatics, Saarland University, Saarbrücken, Germany.
Saarland University · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quorum sensing (QS) describes the exchange of chemical signals in bacterial populations to adjust the bacterial phenotypes according to the density of bacterial cells. This serves to express phenotypes that are advantageous for the group and ensure bacterial survival. To do so, bacterial cells synthesize autoinducer (AI) molecules, release them to the environment, and take them up. Thereby, the AI concentration reflects the cell density. When the AI concentration exceeds a critical threshold in the cells, the AI may activate the expression of virulence-associated genes or of luminescent proteins. It has been argued that targeting the QS system puts less selective pressure on these pathogens and should avoid the development of resistant bacteria. Therefore, the molecular components of QS systems have been suggested as promising targets for developing new anti-infective compounds. Here, we review the QS systems of selected gram-negative and gram-positive bacteria, namely, Vibrio fischeri, Pseudomonas aeruginosa, and Staphylococcus aureus, and discuss various antivirulence strategies based on blocking different components of the QS machinery.

Indexed as

autoinducerPseudomonas aeruginoasquorum sensing inhibitorsStaphylococcus aureusVibrio fischerivirulence

Identifiers

PMID26819549
PMCPMC4718088
OpenAlexW2287921014

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.