MEGARes 2.0: a database for classification of antimicrobial drug, biocide and metal resistance determinants in metagenomic sequence data
MEGARes 2.0: a database for classification of antimicrobial drug, biocide and metal resistance determinants in metagenomic sequence data
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DOI：
10.1093/nar/gkz1010
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发表时间：
2020-01-08
影响因子：
14.9
通讯作者：
Morley, Paul S.
中科院分区：
文献类型：
--
作者：
Doster, Enrique;Lakin, Steven M.;Morley, Paul S.
抗菌素耐药性（AMR）是对全球公共卫生的威胁，确定AMR的遗传决定因素是流行病学调查的关键组成部分。高通量测序（HTS）为研究样品中所有微生物基因组（即宏基因组）的抗菌素耐药性提供了机会。此前，我们提出了MEGARes，这是一个手工策划的AMR数据库和注释结构，旨在促进宏基因组样本（即抗性组）内AMR的分析。与MEGARes一起，我们发布了AmrPlusPlus，这是一个与MEGARes接口的生物信息学管道，用于识别和量化包含在宏基因组序列数据集中的AMR基因。在这里，我们提出了MEGARes 2.0 (https://megares.meglab.org)，它包含了先前发表的抗微生物药物耐药序列，同时也扩展到包括已发表的金属和杀菌剂耐药决定因素的序列。在MEGARes 2.0中，无环层次本体的节点包括4种抗菌化合物类型，57类，220种耐药机制，1,345个基因群，对7,868个条目进行分类。此外，我们提出了AmrPlusPlus的更新版本（amr++ 2.0版本），该版本提高了分类的准确性，并扩展了可扩展性和可用性。
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.