MEGARes and AMR++, v3.0: an updated comprehensive database of antimicrobial resistance determinants and an improved software pipeline for classification using high-throughput sequencing

Nathalie Bonin, Enrique Doster, Hannah Worley, Lee J. Pinnell, Jonathan E. Bravo, Peter Ferm, Simone Marini, Mattia Prosperi, Noelle Noyes, Paul S. Morley, Christina Boucher

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

Antimicrobial resistance (AMR) is considered a critical threat to public health, and genomic/metagenomic investigations featuring high-throughput analysis of sequence data are increasingly common and important. We previously introduced MEGARes, a comprehensive AMR database with an acyclic hierarchical annotation structure that facilitates high-throughput computational analysis, as well as AMR++, a customized bioinformatic pipeline specifically designed to use MEGARes in high-throughput analysis for characterizing AMR genes (ARGs) in metagenomic sequence data. Here, we present MEGARes v3.0, a comprehensive database of published ARG sequences for antimicrobial drugs, biocides, and metals, and AMR++ v3.0, an update to our customized bioinformatic pipeline for high-throughput analysis of metagenomic data (available at MEGLab.org). Database annotations have been expanded to include information regarding specific genomic locations for single-nucleotide polymorphisms (SNPs) and insertions and/or deletions (indels) when required by specific ARGs for resistance expression, and the updated AMR++ pipeline uses this information to check for presence of resistance-conferring genetic variants in metagenomic sequenced reads. This new information encompasses 337 ARGs, whose resistance-conferring variants could not previously be confirmed in such a manner. In MEGARes 3.0, the nodes of the acyclic hierarchical ontology include 4 antimicrobial compound types, 59 resistance classes, 233 mechanisms and 1448 gene groups that classify the 8733 accessions.

Original languageEnglish (US)
Pages (from-to)D744-D752
JournalNucleic acids research
Volume51
Issue number1 D
DOIs
StatePublished - Jan 6 2023

Bibliographical note

Funding Information:
School of Veterinary Medicine and Biomedical Sciences Texas A&M University (to E.D., L.J.P., P.S.M.);Minnesota Agricultural Research, Education and Extension Technology Transfer Program (to N.R.N., H.W., P.F.); NIH [R01-AI141810 to N.B., J.B., S.M.,M.P., N.R.N., C.B.]. Funding for open access charge: NIH NIAID [R01-AI141810].

Publisher Copyright:
© 2023 The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.

PubMed: MeSH publication types

  • Journal Article
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

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