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ARGem: a new metagenomics pipeline for antibiotic resistance genes: metadata, analysis, and visualization

Antibiotic resistance is of crucial interest to both human and animal medicine. It has been recognized that increased environmental monitoring of antibiotic resistance is needed. Metagenomic DNA sequencing is becoming an attractive method to profile antibiotic resistance genes (ARGs), including a sp...

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Autores principales: Liang, Xiao, Zhang, Jingyi, Kim, Yoonjin, Ho, Josh, Liu, Kevin, Keenum, Ishi, Gupta, Suraj, Davis, Benjamin, Hepp, Shannon L., Zhang, Liqing, Xia, Kang, Knowlton, Katharine F., Liao, Jingqiu, Vikesland, Peter J., Pruden, Amy, Heath, Lenwood S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10558085/
https://www.ncbi.nlm.nih.gov/pubmed/37811141
http://dx.doi.org/10.3389/fgene.2023.1219297
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author Liang, Xiao
Zhang, Jingyi
Kim, Yoonjin
Ho, Josh
Liu, Kevin
Keenum, Ishi
Gupta, Suraj
Davis, Benjamin
Hepp, Shannon L.
Zhang, Liqing
Xia, Kang
Knowlton, Katharine F.
Liao, Jingqiu
Vikesland, Peter J.
Pruden, Amy
Heath, Lenwood S.
author_facet Liang, Xiao
Zhang, Jingyi
Kim, Yoonjin
Ho, Josh
Liu, Kevin
Keenum, Ishi
Gupta, Suraj
Davis, Benjamin
Hepp, Shannon L.
Zhang, Liqing
Xia, Kang
Knowlton, Katharine F.
Liao, Jingqiu
Vikesland, Peter J.
Pruden, Amy
Heath, Lenwood S.
author_sort Liang, Xiao
collection PubMed
description Antibiotic resistance is of crucial interest to both human and animal medicine. It has been recognized that increased environmental monitoring of antibiotic resistance is needed. Metagenomic DNA sequencing is becoming an attractive method to profile antibiotic resistance genes (ARGs), including a special focus on pathogens. A number of computational pipelines are available and under development to support environmental ARG monitoring; the pipeline we present here is promising for general adoption for the purpose of harmonized global monitoring. Specifically, ARGem is a user-friendly pipeline that provides full-service analysis, from the initial DNA short reads to the final visualization of results. The capture of extensive metadata is also facilitated to support comparability across projects and broader monitoring goals. The ARGem pipeline offers efficient analysis of a modest number of samples along with affordable computational components, though the throughput could be increased through cloud resources, based on the user’s configuration. The pipeline components were carefully assessed and selected to satisfy tradeoffs, balancing efficiency and flexibility. It was essential to provide a step to perform short read assembly in a reasonable time frame to ensure accurate annotation of identified ARGs. Comprehensive ARG and mobile genetic element databases are included in ARGem for annotation support. ARGem further includes an expandable set of analysis tools that include statistical and network analysis and supports various useful visualization techniques, including Cytoscape visualization of co-occurrence and correlation networks. The performance and flexibility of the ARGem pipeline is demonstrated with analysis of aquatic metagenomes. The pipeline is freely available at https://github.com/xlxlxlx/ARGem.
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spelling pubmed-105580852023-10-07 ARGem: a new metagenomics pipeline for antibiotic resistance genes: metadata, analysis, and visualization Liang, Xiao Zhang, Jingyi Kim, Yoonjin Ho, Josh Liu, Kevin Keenum, Ishi Gupta, Suraj Davis, Benjamin Hepp, Shannon L. Zhang, Liqing Xia, Kang Knowlton, Katharine F. Liao, Jingqiu Vikesland, Peter J. Pruden, Amy Heath, Lenwood S. Front Genet Genetics Antibiotic resistance is of crucial interest to both human and animal medicine. It has been recognized that increased environmental monitoring of antibiotic resistance is needed. Metagenomic DNA sequencing is becoming an attractive method to profile antibiotic resistance genes (ARGs), including a special focus on pathogens. A number of computational pipelines are available and under development to support environmental ARG monitoring; the pipeline we present here is promising for general adoption for the purpose of harmonized global monitoring. Specifically, ARGem is a user-friendly pipeline that provides full-service analysis, from the initial DNA short reads to the final visualization of results. The capture of extensive metadata is also facilitated to support comparability across projects and broader monitoring goals. The ARGem pipeline offers efficient analysis of a modest number of samples along with affordable computational components, though the throughput could be increased through cloud resources, based on the user’s configuration. The pipeline components were carefully assessed and selected to satisfy tradeoffs, balancing efficiency and flexibility. It was essential to provide a step to perform short read assembly in a reasonable time frame to ensure accurate annotation of identified ARGs. Comprehensive ARG and mobile genetic element databases are included in ARGem for annotation support. ARGem further includes an expandable set of analysis tools that include statistical and network analysis and supports various useful visualization techniques, including Cytoscape visualization of co-occurrence and correlation networks. The performance and flexibility of the ARGem pipeline is demonstrated with analysis of aquatic metagenomes. The pipeline is freely available at https://github.com/xlxlxlx/ARGem. Frontiers Media S.A. 2023-09-15 /pmc/articles/PMC10558085/ /pubmed/37811141 http://dx.doi.org/10.3389/fgene.2023.1219297 Text en Copyright © 2023 Liang, Zhang, Kim, Ho, Liu, Keenum, Gupta, Davis, Hepp, Zhang, Xia, Knowlton, Liao, Vikesland, Pruden and Heath. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Liang, Xiao
Zhang, Jingyi
Kim, Yoonjin
Ho, Josh
Liu, Kevin
Keenum, Ishi
Gupta, Suraj
Davis, Benjamin
Hepp, Shannon L.
Zhang, Liqing
Xia, Kang
Knowlton, Katharine F.
Liao, Jingqiu
Vikesland, Peter J.
Pruden, Amy
Heath, Lenwood S.
ARGem: a new metagenomics pipeline for antibiotic resistance genes: metadata, analysis, and visualization
title ARGem: a new metagenomics pipeline for antibiotic resistance genes: metadata, analysis, and visualization
title_full ARGem: a new metagenomics pipeline for antibiotic resistance genes: metadata, analysis, and visualization
title_fullStr ARGem: a new metagenomics pipeline for antibiotic resistance genes: metadata, analysis, and visualization
title_full_unstemmed ARGem: a new metagenomics pipeline for antibiotic resistance genes: metadata, analysis, and visualization
title_short ARGem: a new metagenomics pipeline for antibiotic resistance genes: metadata, analysis, and visualization
title_sort argem: a new metagenomics pipeline for antibiotic resistance genes: metadata, analysis, and visualization
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10558085/
https://www.ncbi.nlm.nih.gov/pubmed/37811141
http://dx.doi.org/10.3389/fgene.2023.1219297
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