Department of Biological Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, China.
State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, China; University of Chinese Academy of Sciences, Beijing, China.
Environ Pollut. 2019 Nov;254(Pt B):113108. doi: 10.1016/j.envpol.2019.113108. Epub 2019 Aug 28.
Taihu Lake is one of the largest freshwater lakes in China and serves as an important source for drinking water. This lake is suffering from eutrophication, cyanobacterial blooms and fecal pollution, and the inflow Tiaoxi River is one of the main contributors. The goal here was to characterize the bacterial community structure of Tiaoxi River water by next-generation sequencing (NGS), paying attention to bacteria that are either fecal-associated or pathogenic, and to examine the relationship between environmental parameters and bacterial community structure. Water samples collected from 15 locations in three seasons, and fecal samples collected from different hosts and wastewater samples were used for bacterial community analysis. The phyla Proteobacteria, Actinobacteria, Bacteroidetes, and Cyanobacteria were predominant in most of the water samples tested. In fecal samples, Bacteroidetes, Firmicutes, and Proteobacteria were abundant, while wastewater samples were dominated by Proteobacteria, Bacteroidetes, Acidobacteria, and Chloroflexi. The cluster analysis and principal coordinate analysis indicated that bacterial community structure was significantly different between water, fecal and sewage samples. Shared OTUs between water samples and chicken, pig, and human fecal samples ranged from 4.5 to 9.8% indicating the presence of avian, pig and human fecal contamination in Tiaoxi River. At genus level, five bacterial genera of fecal origin and sequences of seven potential pathogens were detected in many locations and their presence was correlated well with the land use pattern. The sequencing data revealed that Faecalibacterium could be a potential target for human-associated microbial source-tracking qPCR assays. Our results suggest that pH, conductivity, and temperature were the main environmental factors in shaping the bacterial community based on redundancy analysis. Overall, NGS is a valuable tool for preliminary investigation of environmental samples to identify the potential human health risk, providing specific information about fecal and potentially pathogenic bacteria that can be followed up by specific methods.
太湖是中国最大的淡水湖泊之一，是重要的饮用水源。该湖正遭受富营养化、蓝藻水华和粪便污染，其入湖河流太滆运河是主要污染源之一。本研究采用下一代测序（NGS）技术，对太滆运河水体中的细菌群落结构进行了特征分析，重点关注与粪便相关或具有致病性的细菌，并研究了环境参数与细菌群落结构之间的关系。本研究共采集了三个季节、15 个位置的水样，以及不同宿主的粪便样本和污水样本进行细菌群落分析。在大多数检测的水样中，优势菌门为变形菌门、放线菌门、拟杆菌门和蓝藻门。在粪便样本中，拟杆菌门、厚壁菌门和变形菌门丰度较高，而污水样本则以变形菌门、拟杆菌门、酸杆菌门和绿弯菌门为主。聚类分析和主坐标分析表明，水样、粪便和污水样本之间的细菌群落结构存在显著差异。水样与鸡、猪和人粪便样本之间的共有 OTUs 为 4.5%至 9.8%，表明太滆运河存在禽、猪和人粪便污染。在属水平上，在许多地点都检测到了五个源自粪便的细菌属和七个潜在病原体的序列，它们的存在与土地利用模式密切相关。测序数据表明，粪杆菌可能是人类相关微生物溯源 qPCR 检测的潜在靶标。冗余分析结果表明，pH、电导率和温度是影响细菌群落结构的主要环境因素。总之，NGS 是一种用于初步调查环境样本的有价值的工具，可以识别潜在的人类健康风险，提供有关粪便和潜在致病性细菌的具体信息，这些信息可以通过特定方法进行跟进。
