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COPLA, a taxonomic classifier of plasmids

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TLDR
COPLA as mentioned in this paper is a bioinformatic tool for universal, species-independent, plasmid classification, which can assign plasmids to known and novel taxonomic units based on their genomic sequence.
Abstract
Plasmids are mobile genetic elements, key in the dissemination of antibiotic resistance, virulence determinants and other adaptive traits in bacteria. Obtaining a robust method for plasmid classification is necessary to better understand the genetics and epidemiology of many pathogens. Until now, plasmid classification systems focused on specific traits, which limited their precision and universality. The definition of plasmid taxonomic units (PTUs), based on average nucleotide identity metrics, allows the generation of a universal plasmid classification scheme, applicable to all bacterial taxa. Here we present COPLA, a software able to assign plasmids to known and novel PTUs, based on their genomic sequence. We implemented an automated pipeline able to assign a given plasmid DNA sequence to its cognate PTU, and assessed its performance using a sample of 1000 unclassified plasmids. Overall, 41% of the samples could be assigned to a previously defined PTU, a number that reached 63% in well-known taxa such as the Enterobacterales order. The remaining plasmids represent novel PTUs, indicating that a large fraction of plasmid backbones is still uncharacterized. COPLA is a bioinformatic tool for universal, species-independent, plasmid classification. Offered both as an automatable pipeline and an open web service, COPLA will help bacterial geneticists and clinical microbiologists to quickly classify plasmids.

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Journal ArticleDOI

Evolution of Plasmid Mobility: Origin and Fate of Conjugative and Nonconjugative Plasmids

TL;DR: The evolution of plasmid mobility is frequent, shapes the patterns of gene flow in bacteria, the dynamics of gene repertoires, and the ecology ofplasmids, according to a source-sink dynamic.
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Origins of transfer establish networks of functional dependencies for plasmid transfer by conjugation

TL;DR: In this paper , the authors identify hundreds of plasmids and chromosomes with conjugative origins of transfer in Escherichia coli and Staphylococcus aureus and propose a putative mechanism of transfer for ∼90% of them.
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The mobilome associated with Gram-negative bloodstream infections: A large-scale observational hybrid sequencing based study

TL;DR: Future surveillance should, in addition to tracking plasmids currently associated with clinically important genes, focus on identifying and monitoring the dissemination of high-risk plasmid groups with the potential to rapidly acquire and disseminate these genes.
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Rapid emergence of extensively drug-resistant Shigella sonnei in France

TL;DR: In this article , the authors detected a dramatic increase in the proportion of isolates simultaneously resistant to ciprofloxacin (CIP), third-generation cephalosporins (3GCs) and azithromycin (AZM) from 2015.
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Improved detection and classification of plasmids from circularized and fragmented assemblies

TL;DR: PlaSquid, a dockerized tool developed in Nextflow that expands plasmid detection and improves replicon typing and mobility groups classification schemes, outperforming previously available methods in both precision and sensitivity is presented.
References
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Journal ArticleDOI

In Silico Detection and Typing of Plasmids using PlasmidFinder and Plasmid Multilocus Sequence Typing

TL;DR: Two easy-to-use Web tools for in silico detection and characterization of whole-genome sequence (WGS) and whole-plasmid sequence data from members of the family Enterobacteriaceae are designed and developed.
Journal ArticleDOI

Identification of protein secretion systems in bacterial genomes

TL;DR: Online and standalone computational tools to accurately predict protein secretion systems and related appendages in bacteria with LPS-containing outer membranes are built and can be fully customized, which should facilitate the identification of novel systems.
Journal ArticleDOI

On the (im)possibility of reconstructing plasmids from whole-genome short-read sequencing data.

TL;DR: This study shows that it is possible to automatically predict small plasmids, and benchmark algorithms for automated plasmid sequence reconstruction from short-read sequencing data had the highest precision, but was restricted by the contents of its database and the contig length obtained from de novo assembly.
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