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Noise reduction strategies in metagenomic chromosome confirmation capture to link antibiotic resistance genes to microbial hosts
The gut microbiota is a reservoir for antimicrobial resistance genes (ARGs). With current sequencing methods, it is difficult to assign ARGs to their microbial hosts, particularly if these ARGs are located on plasmids. Metagenomic chromosome conformation capture approaches (meta3C and Hi-C) have rec...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Microbiology Society
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10327510/ https://www.ncbi.nlm.nih.gov/pubmed/37272920 http://dx.doi.org/10.1099/mgen.0.001030 |
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author | McCallum, Gregory E. Rossiter, Amanda E. Quraishi, Mohammed Nabil Iqbal, Tariq H. Kuehne, Sarah A. van Schaik, Willem |
author_facet | McCallum, Gregory E. Rossiter, Amanda E. Quraishi, Mohammed Nabil Iqbal, Tariq H. Kuehne, Sarah A. van Schaik, Willem |
author_sort | McCallum, Gregory E. |
collection | PubMed |
description | The gut microbiota is a reservoir for antimicrobial resistance genes (ARGs). With current sequencing methods, it is difficult to assign ARGs to their microbial hosts, particularly if these ARGs are located on plasmids. Metagenomic chromosome conformation capture approaches (meta3C and Hi-C) have recently been developed to link bacterial genes to phylogenetic markers, thus potentially allowing the assignment of ARGs to their hosts on a microbiome-wide scale. Here, we generated a meta3C dataset of a human stool sample and used previously published meta3C and Hi-C datasets to investigate bacterial hosts of ARGs in the human gut microbiome. Sequence reads mapping to repetitive elements were found to cause problematic noise in, and may importantly skew interpretation of, meta3C and Hi-C data. We provide a strategy to improve the signal-to-noise ratio by discarding reads that map to insertion sequence elements and to the end of contigs. We also show the importance of using spike-in controls to quantify whether the cross-linking step in meta3C and Hi-C protocols has been successful. After filtering to remove artefactual links, 87 ARGs were assigned to their bacterial hosts across all datasets, including 27 ARGs in the meta3C dataset we generated. We show that commensal gut bacteria are an important reservoir for ARGs, with genes coding for aminoglycoside and tetracycline resistance being widespread in anaerobic commensals of the human gut. |
format | Online Article Text |
id | pubmed-10327510 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Microbiology Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-103275102023-07-08 Noise reduction strategies in metagenomic chromosome confirmation capture to link antibiotic resistance genes to microbial hosts McCallum, Gregory E. Rossiter, Amanda E. Quraishi, Mohammed Nabil Iqbal, Tariq H. Kuehne, Sarah A. van Schaik, Willem Microb Genom Research Articles The gut microbiota is a reservoir for antimicrobial resistance genes (ARGs). With current sequencing methods, it is difficult to assign ARGs to their microbial hosts, particularly if these ARGs are located on plasmids. Metagenomic chromosome conformation capture approaches (meta3C and Hi-C) have recently been developed to link bacterial genes to phylogenetic markers, thus potentially allowing the assignment of ARGs to their hosts on a microbiome-wide scale. Here, we generated a meta3C dataset of a human stool sample and used previously published meta3C and Hi-C datasets to investigate bacterial hosts of ARGs in the human gut microbiome. Sequence reads mapping to repetitive elements were found to cause problematic noise in, and may importantly skew interpretation of, meta3C and Hi-C data. We provide a strategy to improve the signal-to-noise ratio by discarding reads that map to insertion sequence elements and to the end of contigs. We also show the importance of using spike-in controls to quantify whether the cross-linking step in meta3C and Hi-C protocols has been successful. After filtering to remove artefactual links, 87 ARGs were assigned to their bacterial hosts across all datasets, including 27 ARGs in the meta3C dataset we generated. We show that commensal gut bacteria are an important reservoir for ARGs, with genes coding for aminoglycoside and tetracycline resistance being widespread in anaerobic commensals of the human gut. Microbiology Society 2023-06-05 /pmc/articles/PMC10327510/ /pubmed/37272920 http://dx.doi.org/10.1099/mgen.0.001030 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License. This article was made open access via a Publish and Read agreement between the Microbiology Society and the corresponding author’s institution. |
spellingShingle | Research Articles McCallum, Gregory E. Rossiter, Amanda E. Quraishi, Mohammed Nabil Iqbal, Tariq H. Kuehne, Sarah A. van Schaik, Willem Noise reduction strategies in metagenomic chromosome confirmation capture to link antibiotic resistance genes to microbial hosts |
title | Noise reduction strategies in metagenomic chromosome confirmation capture to link antibiotic resistance genes to microbial hosts |
title_full | Noise reduction strategies in metagenomic chromosome confirmation capture to link antibiotic resistance genes to microbial hosts |
title_fullStr | Noise reduction strategies in metagenomic chromosome confirmation capture to link antibiotic resistance genes to microbial hosts |
title_full_unstemmed | Noise reduction strategies in metagenomic chromosome confirmation capture to link antibiotic resistance genes to microbial hosts |
title_short | Noise reduction strategies in metagenomic chromosome confirmation capture to link antibiotic resistance genes to microbial hosts |
title_sort | noise reduction strategies in metagenomic chromosome confirmation capture to link antibiotic resistance genes to microbial hosts |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10327510/ https://www.ncbi.nlm.nih.gov/pubmed/37272920 http://dx.doi.org/10.1099/mgen.0.001030 |
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