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MEGARes 2.0: a database for classification of antimicrobial drug, biocide and metal resistance determinants in metagenomic sequence data.
Doster, Enrique; Lakin, Steven M; Dean, Christopher J; Wolfe, Cory; Young, Jared G; Boucher, Christina; Belk, Keith E; Noyes, Noelle R; Morley, Paul S.
Afiliação
  • Doster E; Veterinary Education, Research, and Outreach (VERO) Program, Texas A&M University and West Texas A&M University, Canyon, TX 79016, USA.
  • Lakin SM; Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN 55455, USA.
  • Dean CJ; Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO 80523, USA.
  • Wolfe C; Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO 80523, USA.
  • Young JG; Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN 55455, USA.
  • Boucher C; Department of Clinical Sciences, Colorado State University, Fort Collins, CO 80523, USA.
  • Belk KE; Veterinary Education, Research, and Outreach (VERO) Program, Texas A&M University and West Texas A&M University, Canyon, TX 79016, USA.
  • Noyes NR; Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL 32611, USA.
  • Morley PS; Department of Animal Sciences, Colorado State University, Fort Collins, CO 80523, USA.
Nucleic Acids Res ; 48(D1): D561-D569, 2020 01 08.
Article em En | MEDLINE | ID: mdl-31722416
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Resistência Microbiana a Medicamentos / Bases de Dados Genéticas / Metagenômica / Bases de Dados de Produtos Farmacêuticos / Genes Bacterianos / Anti-Infecciosos Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Resistência Microbiana a Medicamentos / Bases de Dados Genéticas / Metagenômica / Bases de Dados de Produtos Farmacêuticos / Genes Bacterianos / Anti-Infecciosos Idioma: En Ano de publicação: 2020 Tipo de documento: Article