Authors
Peixi Qin, Waresi Tuersong, Zhuolin Tao, Bingyan Huang, Lili Tan, Hui Liu, Junlong Zhao, Min Hu
Published in
Frontiers in microbiology. Volume 17. Pages 1780611. Epub Aug 03, 2026.
Abstract
Wastewater treatment plants (WWTPs) serve as critical nodes for monitoring urban biological hazards, yet the raw influent-the primary entry point for pathogens and antibiotic resistance genes (ARGs)-remains less characterized compared to treated effluent, particularly at the level of individual facilities, as most prior studies have pooled samples or focused on post-treatment matrices.
In this descriptive study, we performed metagenomic sequencing on influent samples collected from six municipal WWTPs, with each plant treated as an independent unit to profile its specific microbial community, pathogen composition, and antibiotic resistome.
Across all samples, a total of 853 bacterial and 232 eukaryotic pathogen species were identified. An exploratory risk index, calculated by integrating species abundance with established risk group classifications, assigned the highest heuristic score to Tangxun Lake (2150), reflecting its concurrent enrichment of both enteric and respiratory pathogens. The pathogen distribution exhibited plant-specific patterns: enteric pathogens including Escherichia coli, Vibrio cholerae, and Campylobacter jejuni were predominantly detected in Huangpu road and Nantaizi Lake, whereas respiratory pathogens such as Mycobacterium tuberculosis and Legionella pneumophila were more abundant in Xinzhuang, Jinyang, and Tangxun Lake. A core set of ARGs-comprising multidrug efflux pumps, β-lactamases, and tetracycline resistance genes-was consistently present across all six facilities, collectively accounting for approximately 60% of the total ARG abundance detected. In addition, exploratory correlations between mobile genetic elements (e.g., plasmids and transposases) and clinically relevant ARGs were observed across the dataset, warranting further investigation.
By generating plant-specific hazard inventories rather than pooled averages, this study provides a descriptive baseline that enables facility-specific surveillance prioritization.
PMID:
42609329
Bibliographic data and abstract were imported from PubMed on 18 Aug 2026.
Read full publication at:
Please sign in
to see all details.
Advertisement
Stats
- Recommendations n/a n/a positive of 0 vote(s)
- Views 8
- Comments 0