Microbial biomarkers as indication of dynamic and heterogeneous urban water environments

Water samples for the 16S rRNA gene and water quality analyses were collected from around 155 km of river segments surrounding the urban areas in Xi'an, China. Multiple statistical analyses showed that the dynamic shifts of microbial communities in the Chan, Ba, and Feng Rivers from the spring to the summer seasons were apparent but little in the Zao River. The heterogeneity of microbial distributions was more due to the influence of hydrologic conditions and various sources of inflows in the rivers. The LEfSe analysis showed that the Chan and Zao Rivers, both more impacted by the sewage effluents, were more differentially abundant with bacteria related to polluted water, but the Ba and Feng Rivers, both on the outer side of the city, were more abundant with microbial communities in soil and freshwater environments in the summer. Multiple statistical analyses indicated that environmental variables had significant impacts on microbial communities. The geographical information system-based spatial analysis showed heterogeneity of microbial community distributions along the rivers. This study showed that the high-throughput sequencing analysis could identify some pathogenic bacteria that would significantly threaten public health and eco-environments in urban rivers.