Mass-immigration shapes the antibiotic resistome of wastewater treatment plants

Lanping Zhang, Bob Adyari, Liyuan Hou, Xiaoyong Yang, Mahmoud Gad, Yuwen Wang, Cong Ma, Qian Sun, Qiang Tang, Yifeng Zhang, Chang-Ping Yu, Anyi Hu*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review


Wastewater treatment plants (WWTPs) are the hotspots for the spread of antibiotic resistance genes (ARGs) into the environment. Nevertheless, a comprehensive assessment of the city-level and short-term daily (inter-day) variations of ARG profiles in the whole process (influent-INF, activated sludge-AS and effluent-EF) of WWTPs is still lacking. Here, 285 ARGs and ten mobile gene elements were monitored in seven WWTPs in Xiamen for seven days via high-throughput qPCR. The average daily load of ARGs to WWTPs was about 1.32 × 1020 copies/d, and a total of 1.56 × 1018 copies/d was discharged to the environment across the entire city. Stochastic processes were the main force determining the assembly of ARG communities during sampling campaign, with their relative importance ranked in the order of INF > EFF > AS. There're little daily variations in ARG richness, abundance, β-diversity composition as well as assembly mechanisms. The results of SourceTracker, variation partitioning analysis, and hierarchical partitioning analysis indicated that bacteria and ARGs from upstream treatment processes played an increasingly dominant role in shaping ARG communities in AS and EFF, respectively, suggesting the importance of mass-immigration of bacteria and ARGs from the source on ARG transport in wastewater treatment processes. This emphasizes the need to revise the way we mitigate ARG contamination but focus on the source of ARGs in urban wastewater.
Original languageEnglish
Article number168193
JournalScience of the Total Environment
Number of pages13
Publication statusPublished - 2024


  • Wastewater treatment plant
  • Antibiotic resistance genes
  • Mass immigration
  • Assembly mechanisms
  • Daily variation


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