Evidence map›Paper›PMID 28715501›Full record

ArticlePLoS computational biology2017

Diversity and distribution of nuclease bacteriocins in bacterial genomes revealed using Hidden Markov Models.

Connor Sharp, James Bray, Nicholas G Housden, Martin C J Maiden, Colin Kleanthous

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
7.5field-weighted citation impact, top 3% 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

38 citing papers in PubMed, 66 citations in OpenAlex.

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  15. Life (Basel, Switzerland) · 2022
    Article
  16. The evolution of spectrum in antibiotics and bacteriocins.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
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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

5 authors at 1 institution in 1 country.

Connor SharpDepartment of Biochemistry, University of Oxford, Oxford, United Kingdom.
James BrayDepartment of Zoology, University of Oxford, Oxford, United Kingdom.
Nicholas G HousdenDepartment of Biochemistry, University of Oxford, Oxford, United Kingdom.
Martin C J MaidenDepartment of Zoology, University of Oxford, Oxford, United Kingdom.
Colin KleanthousDepartment of Biochemistry, University of Oxford, Oxford, United Kingdom.ORCID http://orcid.org/0000-0002-3273-0302
University of Oxford · GB

Funding

Wellcome Trust
6 · The paper itself

Abstract

Bacteria exploit an arsenal of antimicrobial peptides and proteins to compete with each other. Three main competition systems have been described: type six secretion systems (T6SS); contact dependent inhibition (CDI); and bacteriocins. Unlike T6SS and CDI systems, bacteriocins do not require contact between bacteria but are diffusible toxins released into the environment. Identified almost a century ago, our understanding of bacteriocin distribution and prevalence in bacterial populations remains poor. In the case of protein bacteriocins, this is because of high levels of sequence diversity and difficulties in distinguishing their killing domains from those of other competition systems. Here, we develop a robust bioinformatics pipeline exploiting Hidden Markov Models for the identification of nuclease bacteriocins (NBs) in bacteria of which, to-date, only a handful are known. NBs are large (>60 kDa) toxins that target nucleic acids (DNA, tRNA or rRNA) in the cytoplasm of susceptible bacteria, usually closely related to the producing organism. We identified >3000 NB genes located on plasmids or on the chromosome from 53 bacterial species distributed across different ecological niches, including human, animals, plants, and the environment. A newly identified NB predicted to be specific for Pseudomonas aeruginosa (pyocin Sn) was produced and shown to kill P. aeruginosa thereby validating our pipeline. Intriguingly, while the genes encoding the machinery needed for NB translocation across the cell envelope are widespread in Gram-negative bacteria, NBs are found exclusively in γ-proteobacteria. Similarity network analysis demonstrated that NBs fall into eight groups each with a distinct arrangement of protein domains involved in import. The only structural feature conserved across all groups was a sequence motif critical for cell-killing that is generally not found in bacteriocins targeting the periplasm, implying a specific role in translocating the nuclease to the cytoplasm. Finally, we demonstrate a significant association between nuclease colicins, NBs specific for Escherichia coli, and virulence factors, suggesting NBs play a role in infection processes, most likely by enabling pathogens to outcompete commensal bacteria.

Indexed as

Anti-Infective AgentsBacterial ProteinsBacteriocinsComputer SimulationDeoxyribonucleasesGammaproteobacteriaGenome, BacterialMarkov ChainsPseudomonas aeruginosaAnti-Infective AgentsBacterial ProteinsBacteriocinsDeoxyribonucleases

Identifiers

PMID28715501
PMCPMC5536347
OpenAlexW2735764554

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.