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MEGARes and AMR++, v3.0: an updated comprehensive database of antimicrobial resistance determinants and an improved software pipeline for classification using high-throughput sequencing.
Bonin, Nathalie; Doster, Enrique; Worley, Hannah; Pinnell, Lee J; Bravo, Jonathan E; Ferm, Peter; Marini, Simone; Prosperi, Mattia; Noyes, Noelle; Morley, Paul S; Boucher, Christina.
Afiliación
  • Bonin N; Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, USA.
  • Doster E; VERO Program, Veterinary Medicine and Biomedical Sciences, Texas A&M University, Canyon, TX, USA.
  • Worley H; Food-Centric Corridor, Infectious Disease Laboratory, Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, USA.
  • Pinnell LJ; VERO Program, Veterinary Medicine and Biomedical Sciences, Texas A&M University, Canyon, TX, USA.
  • Bravo JE; Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, USA.
  • Ferm P; Food-Centric Corridor, Infectious Disease Laboratory, Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, USA.
  • Marini S; Data Intelligence Systems Lab, Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA.
  • Prosperi M; Data Intelligence Systems Lab, Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA.
  • Noyes N; Food-Centric Corridor, Infectious Disease Laboratory, Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, USA.
  • Morley PS; VERO Program, Veterinary Medicine and Biomedical Sciences, Texas A&M University, Canyon, TX, USA.
  • Boucher C; Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, USA.
Nucleic Acids Res ; 51(D1): D744-D752, 2023 01 06.
Article en En | MEDLINE | ID: mdl-36382407
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Antiinfecciosos / Antibacterianos Idioma: En Revista: Nucleic Acids Res Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Antiinfecciosos / Antibacterianos Idioma: En Revista: Nucleic Acids Res Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos