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MEGARes 2.0: a database for classification of antimicrobial drug, biocide and metal resistance determinants in metagenomic sequence data

Antimicrobial resistance (AMR) is a threat to global public health and the identification of genetic determinants of AMR is a critical component to epidemiological investigations. High-throughput sequencing (HTS) provides opportunities for investigation of AMR across all microbial genomes in a sampl...

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Autores principales: Doster, Enrique, Lakin, Steven M, Dean, Christopher J, Wolfe, Cory, Young, Jared G, Boucher, Christina, Belk, Keith E, Noyes, Noelle R, Morley, Paul S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7145535/
https://www.ncbi.nlm.nih.gov/pubmed/31722416
http://dx.doi.org/10.1093/nar/gkz1010
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author Doster, Enrique
Lakin, Steven M
Dean, Christopher J
Wolfe, Cory
Young, Jared G
Boucher, Christina
Belk, Keith E
Noyes, Noelle R
Morley, Paul S
author_facet Doster, Enrique
Lakin, Steven M
Dean, Christopher J
Wolfe, Cory
Young, Jared G
Boucher, Christina
Belk, Keith E
Noyes, Noelle R
Morley, Paul S
author_sort Doster, Enrique
collection PubMed
description Antimicrobial resistance (AMR) is a threat to global public health and the identification of genetic determinants of AMR is a critical component to epidemiological investigations. High-throughput sequencing (HTS) provides opportunities for investigation of AMR across all microbial genomes in a sample (i.e. the metagenome). Previously, we presented MEGARes, a hand-curated AMR database and annotation structure developed to facilitate the analysis of AMR within metagenomic samples (i.e. the resistome). Along with MEGARes, we released AmrPlusPlus, a bioinformatics pipeline that interfaces with MEGARes to identify and quantify AMR gene accessions contained within a metagenomic sequence dataset. Here, we present MEGARes 2.0 (https://megares.meglab.org), which incorporates previously published resistance sequences for antimicrobial drugs, while also expanding to include published sequences for metal and biocide resistance determinants. In MEGARes 2.0, the nodes of the acyclic hierarchical ontology include four antimicrobial compound types, 57 classes, 220 mechanisms of resistance, and 1,345 gene groups that classify the 7,868 accessions. In addition, we present an updated version of AmrPlusPlus (AMR ++ version 2.0), which improves accuracy of classifications, as well as expanding scalability and usability.
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spelling pubmed-71455352020-04-13 MEGARes 2.0: a database for classification of antimicrobial drug, biocide and metal resistance determinants in metagenomic sequence data Doster, Enrique Lakin, Steven M Dean, Christopher J Wolfe, Cory Young, Jared G Boucher, Christina Belk, Keith E Noyes, Noelle R Morley, Paul S Nucleic Acids Res Database Issue Antimicrobial resistance (AMR) is a threat to global public health and the identification of genetic determinants of AMR is a critical component to epidemiological investigations. High-throughput sequencing (HTS) provides opportunities for investigation of AMR across all microbial genomes in a sample (i.e. the metagenome). Previously, we presented MEGARes, a hand-curated AMR database and annotation structure developed to facilitate the analysis of AMR within metagenomic samples (i.e. the resistome). Along with MEGARes, we released AmrPlusPlus, a bioinformatics pipeline that interfaces with MEGARes to identify and quantify AMR gene accessions contained within a metagenomic sequence dataset. Here, we present MEGARes 2.0 (https://megares.meglab.org), which incorporates previously published resistance sequences for antimicrobial drugs, while also expanding to include published sequences for metal and biocide resistance determinants. In MEGARes 2.0, the nodes of the acyclic hierarchical ontology include four antimicrobial compound types, 57 classes, 220 mechanisms of resistance, and 1,345 gene groups that classify the 7,868 accessions. In addition, we present an updated version of AmrPlusPlus (AMR ++ version 2.0), which improves accuracy of classifications, as well as expanding scalability and usability. Oxford University Press 2019-11-13 /pmc/articles/PMC7145535/ /pubmed/31722416 http://dx.doi.org/10.1093/nar/gkz1010 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Database Issue
Doster, Enrique
Lakin, Steven M
Dean, Christopher J
Wolfe, Cory
Young, Jared G
Boucher, Christina
Belk, Keith E
Noyes, Noelle R
Morley, Paul S
MEGARes 2.0: a database for classification of antimicrobial drug, biocide and metal resistance determinants in metagenomic sequence data
title MEGARes 2.0: a database for classification of antimicrobial drug, biocide and metal resistance determinants in metagenomic sequence data
title_full MEGARes 2.0: a database for classification of antimicrobial drug, biocide and metal resistance determinants in metagenomic sequence data
title_fullStr MEGARes 2.0: a database for classification of antimicrobial drug, biocide and metal resistance determinants in metagenomic sequence data
title_full_unstemmed MEGARes 2.0: a database for classification of antimicrobial drug, biocide and metal resistance determinants in metagenomic sequence data
title_short MEGARes 2.0: a database for classification of antimicrobial drug, biocide and metal resistance determinants in metagenomic sequence data
title_sort megares 2.0: a database for classification of antimicrobial drug, biocide and metal resistance determinants in metagenomic sequence data
topic Database Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7145535/
https://www.ncbi.nlm.nih.gov/pubmed/31722416
http://dx.doi.org/10.1093/nar/gkz1010
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