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Highly Resolved Community Sewage Metagenomics Unveiling Landscape and Transmission Patterns of Antibiotic Resistome in Hong Kong Populations

  • Jiahui Ding
  • , Mengying Wang
  • , Xiaoqing Xu
  • , Dou Wang
  • , Xi Chen
  • , Shuxian Li
  • , Xiawan Zheng
  • , You Che
  • , Yu Deng
  • , Tommy T. Y. Lam
  • , Liguan Li*
  • , Tong Zhang*
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

The increasing global burden of antimicrobial resistance (AMR) has been identified as a critical public health crisis, necessitating the development of robust, real-time surveillance frameworks to evaluate AMR dynamics. Sewage surveillance is emerging as a promising tool that utilizes sewage fingerprinting to provide comprehensive and unbiased information on antibiotic resistance genes (ARGs) within human populations. Here, we conducted a large-scale, year-long field surveillance of resistome in the community sewage using both short- and long-read metagenomic sequencing. We examined samples collected from 95 geographically distributed sites across Hong Kong, covering a population of 4.8 million residents, during summer and winter seasons. Our findings revealed distinct seasonal patterns through high-resolution resistome profiling. We found that the resistome structures shifted from the community sewage collected at sewer manholes to the influent of wastewater treatment plants (WWTPs), driven by taxonomic variation. Notably, community sewage exhibited a significantly higher similarity to the resistome of human feces than WWTP influent, which provides insights for selecting suitable sampling sites for epidemiological ARG surveillance. The application of long-read sequencing markedly enhanced our understanding of the phylogenetic diversity of ARG hosts and uncovered a broad spectrum of potentially mobile ARGs with varied genetic backgrounds. Furthermore, we observed multiple local ARG transmission patterns and subsequently evaluated their potential threats to public health based on the gene trees to inform future epidemiological control strategies. Overall, this work expands our current understanding of community sewage for population-level AMR monitoring and establishes a baseline for advancing sewage surveillance efforts to better combat AMR. © 2026 The Author(s). Advanced Science published by Wiley-VCH GmbH.
Original languageEnglish
Article numbere08389
Number of pages16
JournalAdvanced Science
Online published27 Feb 2026
DOIs
Publication statusOnline published - 27 Feb 2026
Externally publishedYes

Funding

This study was financially supported by Theme-based Research Scheme (No. T21-705/20-N) of Research Grants Council of Hong Kong, General Research Funds (No. 17202522), Health and Medical Research Fund (No. COVID1903015). J.D., M.W., X.C., and S.L. thank the University of Hong Kong for the Postgraduate Studentship (PGS). We appreciate the assistance of Hong Kong SAR Government for sewage sample collection. We express our great thanks to Vicky Fung and thank Lilian Y L Chan for the technical support with the high-performance computing service.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 6 - Clean Water and Sanitation
    SDG 6 Clean Water and Sanitation

Research Keywords

  • antimicrobial resistance
  • ARG mobility
  • genetic context
  • host tracking
  • nanopore sequencing
  • sewage surveillance

RGC Funding Information

  • RGC-funded

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