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Background <p>Antibiotic resistance genes (ARGs) circulating among clinically relevant bacteria pose serious challenges to public health. Given the ancient and environmental bacterial origins of ARGs, a better understanding of the carriers of ARGs beyond the clinically most relevant species is urgently needed for longer-term resistance monitoring and intervention measures. While the risks of emerging ARGs from environmental sources have been recognized, the identification bottlenecks stem from the limitations of shotgun metagenomic sequencing and bioinformatic methods.</p> Results <p>We use long-read metagenomic sequencing and bacteria-specific methylation profiles to re-establish the links between established (well-described) or latent (absent in databases) ARGs and their bacterial and genetic contexts in wastewater. We analyze base modification data produced by PacBio SMRT sequencing using an in-house pipeline utilizing position weight matrices and UMAP visualizations, which we validate by a synthetic community with known bacterial composition. Our analysis reveals several previously unreported ARGs and ARG-host linkages in wastewater. For instance, we find that <i>Arcobacter</i>, a key wastewater associated taxon and emerging pathogen, carries a latent beta-lactamase gene with high predicted mobility potential. Of the other understudied beta-lactamases, we describe <i>bla</i>MCA within p<i>dif-</i>modules across highly varying contexts suggesting its recent acquisition events. Additionally, we uncover the wastewater resident taxa mediated carriage of clinically important ARGs.</p> Conclusions <p>By linking ARGs to their wider genetic contexts and hosts, our findings shed light on the previously unrecognized carriers of resistance genes in wastewater. The presented approach provides a valuable methodology for early identification of newly arising ARGs and their hosts.</p>

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Long-read metagenomics and methylation-based binning support the discovery of antibiotic resistance gene–host associations in complex communities

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月13日

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  • Melina Markkanen,
  • Heidi Putkuri,
  • Dovydas Kičiatovas,
  • Ville Mustonen,
  • Marko Virta,
  • Antti Karkman

摘要

Background

Antibiotic resistance genes (ARGs) circulating among clinically relevant bacteria pose serious challenges to public health. Given the ancient and environmental bacterial origins of ARGs, a better understanding of the carriers of ARGs beyond the clinically most relevant species is urgently needed for longer-term resistance monitoring and intervention measures. While the risks of emerging ARGs from environmental sources have been recognized, the identification bottlenecks stem from the limitations of shotgun metagenomic sequencing and bioinformatic methods.

Results

We use long-read metagenomic sequencing and bacteria-specific methylation profiles to re-establish the links between established (well-described) or latent (absent in databases) ARGs and their bacterial and genetic contexts in wastewater. We analyze base modification data produced by PacBio SMRT sequencing using an in-house pipeline utilizing position weight matrices and UMAP visualizations, which we validate by a synthetic community with known bacterial composition. Our analysis reveals several previously unreported ARGs and ARG-host linkages in wastewater. For instance, we find that Arcobacter, a key wastewater associated taxon and emerging pathogen, carries a latent beta-lactamase gene with high predicted mobility potential. Of the other understudied beta-lactamases, we describe blaMCA within pdif-modules across highly varying contexts suggesting its recent acquisition events. Additionally, we uncover the wastewater resident taxa mediated carriage of clinically important ARGs.

Conclusions

By linking ARGs to their wider genetic contexts and hosts, our findings shed light on the previously unrecognized carriers of resistance genes in wastewater. The presented approach provides a valuable methodology for early identification of newly arising ARGs and their hosts.