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Potential pathogen communities in highly polluted river ecosystems: Geographical distribution and environmental influence

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Abstract

Risks of pathogenic bacteria to the health of both human beings and water ecosystems have been widely acknowledged. However, traditional risk assessment methods based on fecal indicator bacteria and/or pure culture are not comprehensive at the community level, mainly owing to the limited taxonomic coverage. Here, we combined the technique of high-throughput sequencing and the concept of metacommunity to assess the potential pathogenic bacterial communities in an economically and ecologically crucial but highly polluted river—the North Canal River (NCR) in Haihe River Basin located in North China. NCR presented a significant environmental gradient, with the highest, moderate, and lowest levels of pollution in the up-, middle, and downstream. After multiple analyses, we successfully identified 48 genera, covering nine categories of potential pathogens (mainly human pathogens). The most abundant genus was Acinetobacter, which was rarely identified as a pathogen bacterium in previous studies of NCR. At the community level, we observed significant geographical variation of community composition and structure. Such a high level of geographical variation was mainly derived from differed abundance of species among sections along the river, especially the top seven Operational Taxonomic Units (OTUs). For example, relative abundance of OTU1 (Gammaproteobacteria/Acinetobacter) increased significantly from upstream towards downstream. Regarding the underlying mechanisms driving community geographical variation, environmental filtering was identified as the dominant ecological process and total nitrogen as the most influential environmental variable. Altogether, this study provided a comprehensive profile of potential pathogenic bacteria in NCR and revealed the underlying mechanisms of community succession. Owing to their high abundance and wide geographical distribution, we suggest that potential pathogens identified in this study should be incorporated into future monitoring and management programs in NCR. By revealing the correlation between environmental factors and community composition, the results obtained in this study have significant implications for early warning and risk assessment of potential pathogen bacteria, as well as management practices in highly polluted river ecosystems.

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Data accessibility

The high-throughput sequencing data have been deposited into NCBI Sequence Read Archive (SRA) (accession no.: PRJNA504486).

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Acknowledgements

Great thanks to Yangchun Gao and Xuena Huang for help during the field sampling, and Ping Ni for assistance in the measurement of water parameters. This work was supported by the National Nature Science Foundation of China [Grant Nos.: 31800419; 31572228], the Water Pollution Control and Treatment Special Project [Grant No.: 2018ZX07105-001], National Key R&D Program of China [Grant No.: 2016YFC0500406], the Innovation in Cross-functional Team Program of the Chinese Academy of Sciences [Grant No.: No.: 2015], Chinese Academy of Science [Grant No.: ZDRW-ZS-2016-5], and the State Key Joint Laboratory of Environment Simulation and Pollution Control [RCEES, Chinese Academy of Sciences; Grant No.: 15K01ESPCR].

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Authors and Affiliations

  1. Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, 18 Shuangqing Road, Haidian District, Beijing, 100085, China

    Yuzhan Yang, Min Ma & Aibin Zhan

  2. Beijing Dongcheng District Food and Drug Safety Monitoring Center, 12-14 Zhushikou Street East, Beijing, 100050, China

    Yang Hou

  3. University of Chinese Academy of Sciences, 19A Yuquan Road, Shijingshan District, Beijing, 100049, China

    Aibin Zhan

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  1. Yuzhan Yang
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Yang, Y., Hou, Y., Ma, M. et al. Potential pathogen communities in highly polluted river ecosystems: Geographical distribution and environmental influence. Ambio 49, 197–207 (2020). https://doi.org/10.1007/s13280-019-01184-z

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