TY - JOUR
T1 - MEGARes 2.0
T2 - A database for classification of antimicrobial drug, biocide and metal resistance determinants in metagenomic sequence data
AU - Doster, Enrique
AU - Lakin, Steven M.
AU - Dean, Christopher J.
AU - Wolfe, Cory
AU - Young, Jared G.
AU - Boucher, Christina
AU - Belk, Keith E.
AU - Noyes, Noelle R.
AU - Morley, Paul S.
N1 - Publisher Copyright:
© 2019 The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.
PY - 2020/1/1
Y1 - 2020/1/1
N2 - 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.
AB - 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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U2 - 10.1093/nar/gkz1010
DO - 10.1093/nar/gkz1010
M3 - Article
C2 - 31722416
AN - SCOPUS:85077669476
SN - 0305-1048
VL - 48
SP - D561-D569
JO - Nucleic acids research
JF - Nucleic acids research
IS - D1
ER -