Ecological connectivity of genomic markers of antimicrobial resistance in Escherichia coli in Hong Kong

Antibiotic-resistant Escherichia coli (E. coli) is a major contributor to the global burden of antimicrobial resistance (AMR). While the One Health concept emphasizes the connection of human, animal, and environmental health, genome-resolved and quantitatively integrated analyses of microbial exchange across ecological compartments remain limited. Here we show that E. coli populations from urban aquatic ecosystems in Hong Kong, representing human, animal, and environmental sources, exhibit close genetic relatedness. Using Nanopore long-read sequencing, we generated near-complete genomes for 1016 E. coli isolates collected over one year. These isolates encompassed all main phylogroups, 223 sequence types, 141 antibiotic resistance gene subtypes, and 2647 circular plasmids. 142 clonal strain-sharing events were detected between human-associated and environmental water samples. Additionally, 195 plasmids were shared across all three source-attributed sectors. Conjugation assays confirmed that several plasmids were functionally transmissible across ecological boundaries. To quantify these patterns, we established a genomic framework integrating sequence type similarity, genetic relatedness, and clonal sharing to assess ecological connectivity. Our results indicate that ecological connectivity may facilitate AMR dissemination, highlighting the importance of integrated strategies to monitor and manage resistance risks across sectors within the One Health framework.

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Publication Details

Journal
Nature Communications
Published
2025-08-08
DOI
https://doi.org/10.1038/s41467-025-62455-w
Citations
4
Primary Topic
Antibiotic Resistance in Bacteria
Type
article
Field-Weighted Citation Impact
2.36

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article

Ecological connectivity of genomic markers of antimicrobial resistance in Escherichia coli in Hong Kong

Ethan R. Wyrsch, Veronica M. Jarocki, Steven P. Djordjevic, Xi Chen et al.
4 citations
Nature Communications
Antibiotic Resistance in Bacteria
2.36
article

Ecological connectivity of genomic markers of antimicrobial resistance in Escherichia coli in Hong Kong

Ethan R. Wyrsch, Veronica M. Jarocki, Steven P. Djordjevic, Xi Chen, Lei Liu, Tong Zhang, Chunxiao Wang, Qinling Tang, Yunqi Lin, Dou Wang, Xiaoqing Xu, Yu Deng, You Che
article en
4 citations

Abstract

Antibiotic-resistant Escherichia coli (E. coli) is a major contributor to the global burden of antimicrobial resistance (AMR). While the One Health concept emphasizes the connection of human, animal, and environmental health, genome-resolved and quantitatively integrated analyses of microbial exchange across ecological compartments remain limited. Here we show that E. coli populations from urban aquatic ecosystems in Hong Kong, representing human, animal, and environmental sources, exhibit close genetic relatedness. Using Nanopore long-read sequencing, we generated near-complete genomes for 1016 E. coli isolates collected over one year. These isolates encompassed all main phylogroups, 223 sequence types, 141 antibiotic resistance gene subtypes, and 2647 circular plasmids. 142 clonal strain-sharing events were detected between human-associated and environmental water samples. Additionally, 195 plasmids were shared across all three source-attributed sectors. Conjugation assays confirmed that several plasmids were functionally transmissible across ecological boundaries. To quantify these patterns, we established a genomic framework integrating sequence type similarity, genetic relatedness, and clonal sharing to assess ecological connectivity. Our results indicate that ecological connectivity may facilitate AMR dissemination, highlighting the importance of integrated strategies to monitor and manage resistance risks across sectors within the One Health framework.

Nature CommunicationsVol. 16(1)
University of Technology Sydney (AU), Agriculture and Food (AU), HKU-Pasteur Research Pole (HK), University of Hong Kong (HK)
Research Grants Council, University Grants Committee, Science, Technology and Innovation Commission of Shenzhen Municipality
Sustainable cities and communities
Openalex Percentile: Top 11%
Antibiotic Resistance in Bacteria
2.36
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