Hu Anyi, Wang Hongjie, Li Jiangwei, Mulla Sikandar I, Qiu Quanyi, Tang Lina, Rashid Azhar, Wu Yang, Sun Qian, Yu Chang-Ping
CAS Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China.
CAS Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
J Hazard Mater. 2020 Nov 5;398:122820. doi: 10.1016/j.jhazmat.2020.122820. Epub 2020 May 23.
Rivers are a significant reservoir of antibiotic resistance genes (ARGs), yet the biogeographic pattern of riverine ARGs and its underlying driving forces remain poorly understood. Here, we used metagenomic approach to investigate the spatio-temporal variation of ARGs in two adjacent sub-watersheds viz. North River (NR) and West River (WR), China. The results demonstrated that Bacitracin (22.8 % of the total ARGs), multidrug (20.7 %), sulfonamide (15.2 %) and tetracycline (10.9 %) were the dominant ARG types. SourceTracker analysis indicated that sewage treatment plants as the main source of ARGs, while animal feces mainly contributed in spreading the ARGs in the upstream of NR. Random forest and network analyses confirmed that NR was under the influence of fecal pollution. PCoA analysis demonstrated that the composition of ARGs changed along with the anthropogenic gradients, while the Raup-Crick null model showed that homogenizing selection mediated by class 1 integron intI1 resulted in stable ARG communities at whole watershed scale. Structural equation models revealed that microbial community, grassland and several non-antibiotic micropollutants may also play certain roles in influencing the distribution of ARGs. Overall, the observed deterministic formation of ARGs in riverine systems calls effective management strategies to mitigate the risks of antibiotic resistance on public health.
河流是抗生素抗性基因（ARGs）的重要储存库，但河流中ARGs的生物地理模式及其潜在驱动力仍知之甚少。在此，我们采用宏基因组学方法研究了中国相邻的两个子流域即北江（NR）和西江（WR）中ARGs的时空变化。结果表明，杆菌肽（占ARGs总数的22.8%）、多药抗性（20.7%）、磺胺类（15.2%）和四环素（10.9%）是主要的ARG类型。SourceTracker分析表明，污水处理厂是ARGs的主要来源，而动物粪便主要促使ARGs在北江上游扩散。随机森林和网络分析证实北江受到粪便污染的影响。主坐标分析（PCoA）表明，ARGs的组成随人为梯度而变化，而劳普-克里克（Raup-Crick）零模型表明，由1类整合子intI1介导的同质化选择导致整个流域尺度上ARG群落的稳定。结构方程模型表明，微生物群落、草地和几种非抗生素微污染物在影响ARGs分布方面也可能发挥一定作用。总体而言，在河流系统中观察到的ARGs确定性形成需要有效的管理策略来降低抗生素抗性对公众健康的风险。
