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 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…

• UD
  U.S. Department of Agriculture

  Award: 2018-51300-28563
• UO
  University of Minnesota
• NI
  National Institutes of Health

  Awards: 1R01AI141810-01, R01 1R01AI141810-01
• NI
  National Institute of Food and Agriculture

  Awards: 2015-68003-23048, 2018-51300-28563
• CO
  College of Veterinary Medicine and Biomedical Sciences, Texas A and M University