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Noise reduction strategies in metagenomic chromosome confirmation capture to link antibiotic resistance genes to microbial hosts

Gregory E. McCallum, View ORCID ProfileAmanda E. Rossiter, Mohammed Nabil Quraishi, View ORCID ProfileTariq H. Iqbal, View ORCID ProfileSarah A. Kuehne, View ORCID ProfileWillem van Schaik
doi: https://doi.org/10.1101/2022.11.05.514866
Gregory E. McCallum
1Institute of Microbiology and Infection, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom
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Amanda E. Rossiter
1Institute of Microbiology and Infection, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom
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Mohammed Nabil Quraishi
2University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom
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Tariq H. Iqbal
1Institute of Microbiology and Infection, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom
2University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom
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Sarah A. Kuehne
1Institute of Microbiology and Infection, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom
3School of Dentistry, Institute of Clinical Sciences, University of Birmingham, Birmingham, United Kingdom
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Willem van Schaik
1Institute of Microbiology and Infection, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom
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  • For correspondence: w.vanschaik@bham.ac.uk
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Abstract

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 repetitive 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 for spurious links, 87 ARGs were linked 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 encoding for aminoglycoside and tetracycline resistance being widespread in anaerobic commensals of the human gut.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://github.com/gregmcc97/3C-HiC_analysis

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted November 05, 2022.
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Noise reduction strategies in metagenomic chromosome confirmation capture to link antibiotic resistance genes to microbial hosts
Gregory E. McCallum, Amanda E. Rossiter, Mohammed Nabil Quraishi, Tariq H. Iqbal, Sarah A. Kuehne, Willem van Schaik
bioRxiv 2022.11.05.514866; doi: https://doi.org/10.1101/2022.11.05.514866
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Noise reduction strategies in metagenomic chromosome confirmation capture to link antibiotic resistance genes to microbial hosts
Gregory E. McCallum, Amanda E. Rossiter, Mohammed Nabil Quraishi, Tariq H. Iqbal, Sarah A. Kuehne, Willem van Schaik
bioRxiv 2022.11.05.514866; doi: https://doi.org/10.1101/2022.11.05.514866

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