Evidence map›Paper›PMID 37526274›Full record

ArticleNucleic acids research2023

A systematic approach to classify and characterize genomic islands driven by conjugative mobility using protein signatures.

Bioteau Audrey, Nicolas Cellier, Frédérique White, Pierre-Étienne Jacques, Vincent Burrus

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

17 citing papers in PubMed, 22 citations in OpenAlex.

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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 2 institutions in 2 countries.

Bioteau AudreyDépartement de biologie, Université de Sherbrooke, Sherbrooke, Québec, Canada.ORCID 0000-0003-0284-4891
Nicolas CellierCGI IMT Mines Albi, Albi, France.ORCID 0000-0002-3759-3546
Frédérique WhiteDépartement de biologie, Université de Sherbrooke, Sherbrooke, Québec, Canada.
Pierre-Étienne JacquesDépartement de biologie, Université de Sherbrooke, Sherbrooke, Québec, Canada.ORCID 0000-0002-3961-294X
Vincent BurrusDépartement de biologie, Université de Sherbrooke, Sherbrooke, Québec, Canada.ORCID 0000-0001-6318-6904
Université de Sherbrooke · CAIMT Mines Albi · FR

Funding

CIHR PJT-186081
6 · The paper itself

Abstract

Genomic islands (GIs) play a crucial role in the spread of antibiotic resistance, virulence factors and antiviral defense systems in a broad range of bacterial species. However, the characterization and classification of GIs are challenging due to their relatively small size and considerable genetic diversity. Predicting their intercellular mobility is of utmost importance in the context of the emerging crisis of multidrug resistance. Here, we propose a large-scale classification method to categorize GIs according to their mobility profile and, subsequently, analyze their gene cargo. We based our classification decision scheme on a collection of mobility protein motif definitions available in publicly accessible databases. Our results show that the size distribution of GI classes correlates with their respective structure and complexity. Self-transmissible GIs are usually the largest, except in Bacillota and Actinomycetota, accumulate antibiotic and phage resistance genes, and favour the use of a tyrosine recombinase to insert into a host's replicon. Non-mobilizable GIs tend to use a DDE transposase instead. Finally, although tRNA genes are more frequently targeted as insertion sites by GIs encoding a tyrosine recombinase, most GIs insert in a protein-encoding gene. This study is a stepping stone toward a better characterization of mobile GIs in bacterial genomes and their mechanism of mobility.

Indexed as

BacteriaDrug Resistance, BacterialGenomic IslandsGenome, BacterialRecombinasesTyrosineRecombinasesTyrosine

Identifiers

PMID37526274
PMCPMC10484663
OpenAlexW4385442729

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.