School of Civil Engineering and Architecture, Chuzhou University, Chuzhou, China.
Fisheries Research Institute, Anhui Academy of Agricultural Sciences, Hefei, China.
Water Environ Res. 2021 Aug;93(8):1322-1332. doi: 10.1002/wer.1517. Epub 2021 Feb 17.
The health of urban rivers is threatened by multiple anthropogenic stressors. Bacterial communities in rivers can quickly respond to different types of polluted environments, making them useful for water quality assessments and predictive insights. However, research on river bacterial communities has largely ignored interactions between these communities. Here, 16S rRNA amplicon sequencing analysis is used to comprehensively analyze the bacterial communities in the water and sediments in different types of anthropogenically impacted urban river. The results show that distinct differences occur in the bacterial communities in the river sediment and water with different pollution types. The changes in the bacterial communities in sediments were more pronounced than those in the water. A modular analysis further showed that the microbial co-occurrence network under different types of pollution had a nonrandom modular structure, and this structure was mainly driven by classification correlation and bacterial function. Genes identified for nitrogen cycling in all the river water and sediment samples included major functional genes for nitrogen fixation, assimilatory nitrogen reduction, nitrification, denitrification, and ammonification. Carbon degradation genes were mainly observed in the carbon cycle. Taken together, the above findings provide further insights into microbial communities in urban river ecosystems under anthropogenic contamination. PRACTITIONER POINTS: The physical and chemical indicators of the four types of pollution drive bacterial community structure. Bacterial community has C, N, P metabolic genes indicating its ecological effect. River bacteria were connected more frequently in the same or similar type of pollution in the co-occurrence network. Microbe-environment correlations and microbe-microbe interactions were combined to determine crucial indicators.
城市河流的健康受到多种人为压力源的威胁。河流中的细菌群落可以快速响应不同类型的污染环境，使其成为水质评估和预测洞察力的有用工具。然而，河流细菌群落的研究在很大程度上忽略了这些群落之间的相互作用。在这里，使用 16S rRNA 扩增子测序分析全面分析了不同人为影响的城市河流中水体和沉积物中的细菌群落。结果表明，不同污染类型的河流沉积物和水中的细菌群落存在明显差异。沉积物中细菌群落的变化比水体中更为明显。模块化分析进一步表明，不同类型污染下微生物共生网络具有非随机的模块化结构，这种结构主要由分类相关性和细菌功能驱动。在所有河水和沉积物样本中鉴定出的氮循环基因包括固氮、同化氮还原、硝化、反硝化和氨化的主要功能基因。在碳循环中主要观察到碳降解基因。综上所述，这些发现为受人为污染影响的城市河流生态系统中的微生物群落提供了更深入的了解。
四种污染类型的物理和化学指标驱动细菌群落结构。
细菌群落具有 C、N、P 代谢基因，表明其具有生态效应。
在共生网络中，具有相同或相似污染类型的河流细菌连接更为频繁。
微生物-环境相关性和微生物-微生物相互作用相结合，确定关键指标。
