Evidence map›Paper›PMID 36830192›Full record

ArticleAntibiotics (Basel, Switzerland)2023

Systematic In Silico Assessment of Antimicrobial Resistance Dissemination across the Global Plasmidome.

Miquel Sánchez-Osuna, Jordi Barbé, Ivan Erill

Abstract read
In one paragraph

Article in Antibiotics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Miquel Sánchez-OsunaDepartament de Genètica i de Microbiologia, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain.ORCID 0000-0001-5267-4814
Jordi BarbéDepartament de Genètica i de Microbiologia, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain.
Ivan ErillDepartment of Biological Sciences, University of Maryland Baltimore County, Baltimore, MD 21250, USA.ORCID 0000-0002-7280-7191

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The emergence of pathogenic strains resistant to multiple antimicrobials is a pressing problem in modern healthcare. Antimicrobial resistance is mediated primarily by dissemination of resistance determinants via horizontal gene transfer. The dissemination of some resistance genes has been well documented, but few studies have analyzed the patterns underpinning the dissemination of antimicrobial resistance genes. Analyzing the %GC content of plasmid-borne antimicrobial resistance genes relative to their host genome %GC content provides a means to efficiently detect and quantify dissemination of antimicrobial resistance genes. In this work we automate %GC content analysis to perform a comprehensive analysis of known antimicrobial resistance genes in publicly available plasmid sequences. We find that the degree to which antimicrobial resistance genes are disseminated depends primarily on the resistance mechanism. Our analysis identifies conjugative plasmids as primary dissemination vectors and indicates that most broadly disseminated genes have spread from single genomic backgrounds. We show that resistance dissemination profiles vary greatly among antimicrobials, oftentimes reflecting stewardship measures. Our findings establish %GC content analysis as a powerful, intuitive and scalable method to monitor the dissemination of resistance determinants using publicly available sequence data.

Indexed as

antimicrobial resistancedisseminationevolutionGC contenthorizontal gene transfermobile genetic elementplasmid

Identifiers

PMID36830192
PMCPMC9951915

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.