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<p>Agricultural and urban wastewater acts as a primary vehicle for transporting human pathogens and antimicrobial resistance genes (ARGs) into aquatic ecosystems. This study presents an integrated framework combining metagenomic sequencing, quantitative PCR (qPCR), microbial source tracking (MST), meta-MLST genotyping, and quantitative microbial risk assessment (QMRA) to systematically assess the occurrence, sources, and public health risks of microbial contaminants in the Sanjiangyuan watershed from 2023 to 2024. Metagenomic profiling identified over 30 high-risk bacterial and viral pathogens, with Salmonella enterica, Campylobacter jejuni, Vibrio cholerae, and Adenovirus exhibiting clear seasonal peaks. Zoonotic pathogens, including Brucella and Leptospira, were exclusively detected in agricultural effluents. Meta-MLST analysis revealed epidemic sequence types of <i>V. cholerae</i> (e.g., ST69) and <i>V. parahaemolyticus</i> (e.g., ST925, ST2141) in agricultural effluents. MST markers (BacHum, BacCow, qC160F) revealed dual contributions of human and livestock fecal pollution, and were significantly correlated with nutrient indicators such as nitrate and COD. Meta-MLST confirmed epidemic sequence types of V. cholerae and V. parahaemolyticus, indicating environmental circulation of clinically relevant strains. Resistome analysis revealed 772 to 972 ARG subtypes across sites, dominated by multidrug, β-lactam, and tetracycline resistance genes. Notably, mobile ARGs were frequently co-localized with virulence factors (VFs) in opportunistic pathogens such as <i>Pseudomonas aeruginosa</i> and <i>Acinetobacter baumannii</i>, indicating elevated mobility and pathogenicity. Seasonal variation showed the highest resistome risk in October, with 55% of ARGs classified as high-risk and associated with mobile genetic elements. Our findings underscore the value of integrating resistome analysis into risk-based frameworks to enhance early warning of microbial threats and health-relevant ARGs. This approach supports targeted mitigation strategies in highland watersheds facing mixed-source pollution.</p><p></p>

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Metagenomics with comprehensive validation as a supplementary tool for QMRA in SanjiangYuan watershed

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月1日

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  • Zixuan Zhang,
  • Miaomiao Teng,
  • Wen Li,
  • Hongbo Ma,
  • Wanting Zhou,
  • Fengchang Wu

摘要

Agricultural and urban wastewater acts as a primary vehicle for transporting human pathogens and antimicrobial resistance genes (ARGs) into aquatic ecosystems. This study presents an integrated framework combining metagenomic sequencing, quantitative PCR (qPCR), microbial source tracking (MST), meta-MLST genotyping, and quantitative microbial risk assessment (QMRA) to systematically assess the occurrence, sources, and public health risks of microbial contaminants in the Sanjiangyuan watershed from 2023 to 2024. Metagenomic profiling identified over 30 high-risk bacterial and viral pathogens, with Salmonella enterica, Campylobacter jejuni, Vibrio cholerae, and Adenovirus exhibiting clear seasonal peaks. Zoonotic pathogens, including Brucella and Leptospira, were exclusively detected in agricultural effluents. Meta-MLST analysis revealed epidemic sequence types of V. cholerae (e.g., ST69) and V. parahaemolyticus (e.g., ST925, ST2141) in agricultural effluents. MST markers (BacHum, BacCow, qC160F) revealed dual contributions of human and livestock fecal pollution, and were significantly correlated with nutrient indicators such as nitrate and COD. Meta-MLST confirmed epidemic sequence types of V. cholerae and V. parahaemolyticus, indicating environmental circulation of clinically relevant strains. Resistome analysis revealed 772 to 972 ARG subtypes across sites, dominated by multidrug, β-lactam, and tetracycline resistance genes. Notably, mobile ARGs were frequently co-localized with virulence factors (VFs) in opportunistic pathogens such as Pseudomonas aeruginosa and Acinetobacter baumannii, indicating elevated mobility and pathogenicity. Seasonal variation showed the highest resistome risk in October, with 55% of ARGs classified as high-risk and associated with mobile genetic elements. Our findings underscore the value of integrating resistome analysis into risk-based frameworks to enhance early warning of microbial threats and health-relevant ARGs. This approach supports targeted mitigation strategies in highland watersheds facing mixed-source pollution.