MEGARes and AMR++, v3.0: an updated comprehensive database of antimicrobial resistance determinants and an improved software pipeline for classification using high-throughput sequencing.
MEGARes and AMR++, v3.0: an updated comprehensive database of antimicrobial resistance determinants and an improved software pipeline for classification using high-throughput sequencing.
复制标题
DOI:
10.1093/nar/gkac1047
复制
发表时间:
2023-01-06
影响因子:
14.9
通讯作者:
Boucher, Christina
中科院分区:
文献类型:
--
作者:
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
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.
登录
查看更多内容
影响因子:
11.4
作者:
Liguori, Krista;Keenum, Ishi;Davis, Benjamin C.;Calarco, Jeanette;Milligan, Erin;Harwood, Valerie J.;Pruden, Amy
通讯作者:
Pruden, Amy
DOI:
10.1093/bioinformatics/btp163
发表时间:
2009-06-01
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
作者:
Cock PJ;Antao T;Chang JT;Chapman BA;Cox CJ;Dalke A;Friedberg I;Hamelryck T;Kauff F;Wilczynski B;de Hoon MJ
通讯作者:
de Hoon MJ
DOI:
10.1093/bioinformatics/bts565
发表时间:
2012-12-01
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
作者:
Fu L;Niu B;Zhu Z;Wu S;Li W
通讯作者:
Li W
DOI:
10.1016/j.ijfoodmicro.2022.109821
发表时间:
2022-07-08
影响因子:
5.4
作者:
Hull, Dawn M.;Harrell, Erin;Thakur, Siddhartha
通讯作者:
Thakur, Siddhartha
影响因子:
3.7
作者:
通讯作者:
--