ARGs-OAP: online analysis pipeline for antibiotic resistance genes detection from metagenomic data using an integrated structured ARG-database

Abstract

Motivation: Environmental dissemination of antibiotic resistance genes (ARGs) has become an increasing concern for public health. Metagenomics approaches can effectively detect broad profiles of ARGs in environmental samples; however, the detection and subsequent classification of ARG-like sequences are time consuming and have been severe obstacles in employing metagenomic methods. We sought to accelerate quantification of ARGs in metagenomic data from environmental samples. Results: A Structured ARG reference database (SARG) was constructed by integrating ARDB and CARD, the two most commonly used databases. SARG was curated to remove redundant sequences and optimized to facilitate query sequence identification by similarity. A database with a hierarchical structure (type-subtype-reference sequence) was then constructed to facilitate classification (assigning ARG-like sequence to type, subtype and reference sequence) of sequences identified through similarity search. Utilizing SARG and a previously proposed hybrid functional gene annotation pipeline, we developed an online pipeline called ARGs-OAP for fast annotation and classification of ARG-like sequences from metagenomic data. We also evaluated and proposed a set of criteria important for efficiently conducting metagenomic analysis of ARGs using ARGs-OAP. Availability and Implementation: Perl script for ARGs-OAP can be downloaded from https://github.com/biofuture/Ublastx_stageone. ARGs-OAP can be accessed through http://smile.hku.hk/SARGs. Contact: zhangt@hku.hk or tiedjej@msu.edu Supplementary information: Supplementary data are available at Bioinformatics online.