Distribution and correlation between antibiotic resistance genes and host-associated markers before and after swine fever in the longjiang watershed

Zhang, Yang; Li, Kaiming; Wu, Yongjie; Liu, Yi; Wu, Renren; Zhong, Yi; Xiao, Shijie; Mao, Han; Li, Guodong; Wang, Yishu; Li, Wenjing

Distribution and correlation between antibiotic resistance genes and host-associated markers before and after swine fever in the longjiang watershed

2022

Antibiotic resistance genes (ARGs) are abundantly shed in feces. Thus, it is crucial to identify their host sources so that ARG pollution can be effectively mitigated and aquatic ecosystems can be properly conserved. Here, spatiotemporal variations and sources of ARGs in the Longjiang watershed of South China were investigated by linking them with microbial source tracker (MST) indicators. The most frequently detected ARGs (>90%) were sulI, sulII, blaTEM, tetW, ermF, and the mobile element intI1. Spatial distribution analyses showed that tributaries contributed significantly more sulI, sulII, and ermF contamination to the Longjiang watershed than the main channel. MST indicator analysis revealed that the Longjiang watershed was contaminated mainly by human fecal pollution. Livestock- and poultry-associated fecal pollution significantly declined after the swine fever outbreak. The occurrence of most ARGs is largely explained by human fecal pollution. In contrast, pig fecal pollution might account for the prevalence of tetO. Moreover, combined human-pig fecal pollution contributed to the observed blaNDM₋₁ distribution in the Longjiang watershed. Subsequent analysis of the characteristics of MST markers disclosed that the relatively lower specificities of BacHum and Rum-2-Bac may lead to inaccurate results of tracking ARG pollution source. The present study determined spatiotemporal variations and ARG origins in the Longjiang watershed by combining MST markers. It also underscored the necessity of using multiple MST markers simultaneously to identify and characterize ARG pollution sources accurately.

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