ARGprofiler—a pipeline for large-scale analysis of antimicrobial resistance genes and their flanking regions in metagenomic datasets

Author:

Martiny Hannah-Marie1ORCID,Pyrounakis Nikiforos1,Petersen Thomas N1,Lukjančenko Oksana1,Aarestrup Frank M1,Clausen Philip T L C1,Munk Patrick1

Affiliation:

1. Research Group for Genomic Epidemiology, Technical University of Denmark , Henrik Danms Allé, Bygning 204 , Kongens Lyngby 2800, Denmark

Abstract

Abstract Motivation Analyzing metagenomic data can be highly valuable for understanding the function and distribution of antimicrobial resistance genes (ARGs). However, there is a need for standardized and reproducible workflows to ensure the comparability of studies, as the current options involve various tools and reference databases, each designed with a specific purpose in mind. Results In this work, we have created the workflow ARGprofiler to process large amounts of raw sequencing reads for studying the composition, distribution, and function of ARGs. ARGprofiler tackles the challenge of deciding which reference database to use by providing the PanRes database of 14 078 unique ARGs that combines several existing collections into one. Our pipeline is designed to not only produce abundance tables of genes and microbes but also to reconstruct the flanking regions of ARGs with ARGextender. ARGextender is a bioinformatic approach combining KMA and SPAdes to recruit reads for a targeted de novo assembly. While our aim is on ARGs, the pipeline also creates Mash sketches for fast searching and comparisons of sequencing runs. Availability and implementation The ARGprofiler pipeline is a Snakemake workflow that supports the reuse of metagenomic sequencing data and is easily installable and maintained at https://github.com/genomicepidemiology/ARGprofiler.

Funder

Novo Nordisk Foundation

Global Surveillance of Antimicrobial Resistance

European Union’s Horizon 2020

Publisher

Oxford University Press (OUP)

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