Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, China; Jiangsu Key Laboratory of Chemical Pollution Control and Resources Reuse, School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.
Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, China.
Sci Total Environ. 2022 Aug 15;834:155293. doi: 10.1016/j.scitotenv.2022.155293. Epub 2022 Apr 18.
River networks play important roles in dissemination of antibiotic resistance genes (ARGs). The occurrence, diversity, and abundance of ARGs in river networks have been widely investigated. However, the assembly processes that shaped ARGs profiles across space and time are largely unknown. Here, the dynamics of ARGs profiles in river networks (Taihu Basin) were revealed by high-throughput quantitative PCR followed by multiple statistical analyses to assess the underlying ecological processes. The results revealed clear variations for ARGs profiles across wet, normal, and dry seasons. Meanwhile, a significant negative correlation (p < 0.01) was observed between the similarity of ARGs profiles and geographic distance, indicating ARGs profiles exhibited distance-decay patterns. Null model analysis showed that ARGs profiles were mainly assembled via deterministic processes. Redundancy analysis followed by hierarchical partitioning revealed that environmental attributes (mainly pH and temperature) were the major factors affecting the dynamics of ARGs profiles. Together, these results indicated that environmental filtering was the dominant ecological process that shaped ARGs profiles. This study enhances our understanding how the antibiotic resistome is assembled in river networks and will be beneficial for the development of management strategies to control ARGs dissemination.
河流网络在抗生素耐药基因（ARGs）的传播中起着重要作用。河流网络中 ARGs 的发生、多样性和丰度已经得到了广泛的研究。然而，塑造 ARGs 图谱在时空上的组装过程在很大程度上是未知的。在这里，通过高通量定量 PCR 结合多种统计分析，揭示了河流网络（太湖流域）中 ARGs 图谱的动态，以评估潜在的生态过程。结果表明，ARGs 图谱在湿季、正常季和干季之间存在明显的差异。同时，ARGs 图谱的相似性与地理距离之间存在显著的负相关（p<0.01），表明 ARGs 图谱表现出距离衰减模式。零模型分析表明，ARGs 图谱主要通过确定性过程组装。冗余分析和层次分区显示，环境属性（主要是 pH 值和温度）是影响 ARGs 图谱动态的主要因素。总之，这些结果表明，环境过滤是塑造 ARGs 图谱的主要生态过程。本研究增强了我们对抗生素抗药性组在河流网络中组装方式的理解，并将有助于制定控制 ARGs 传播的管理策略。
