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

  • Enrique Doster
  • , Steven M. Lakin
  • , Christopher J. Dean
  • , Cory Wolfe
  • , Jared G. Young
  • , Christina Boucher
  • , Keith E. Belk
  • , Noelle R. Noyes
  • , Paul S. Morley

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Pages (from-to)D561-D569
JournalNucleic acids research
Volume48
Issue numberD1
DOIs
StatePublished - Jan 8 2020

Bibliographical note

Publisher Copyright:
© 2019 The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Anti-Infective Agents/chemistry
  • Bacteria/drug effects
  • Databases, Genetic
  • Databases, Pharmaceutical
  • Disinfectants/chemistry
  • Drug Resistance, Microbial
  • Genes, Bacterial
  • Metagenome
  • Metagenomics/methods
  • Metals/chemistry
  • Software

PubMed: MeSH publication types

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

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