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 BoninEnrique DosterHannah WorleyLee J PinnellJonathan E BravoPeter FermSimone MariniMattia A ProsperiNoelle NoyesPaul S MorleyChristina BoucherPublished in: Nucleic acids research (2022)
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.
Keyphrases
- antimicrobial resistance
- high throughput
- antibiotic resistance genes
- public health
- copy number
- microbial community
- wastewater treatment
- electronic health record
- single cell
- genome wide
- staphylococcus aureus
- adverse drug
- big data
- anaerobic digestion
- data analysis
- poor prognosis
- machine learning
- gene expression
- dna methylation
- healthcare
- randomized controlled trial
- squamous cell carcinoma
- systematic review
- deep learning
- radiation therapy
- long non coding rna
- human health
- locally advanced
- health risk