Evidence map›Paper›PMID 31020611›Full record

ArticleAmbio2020

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

Yuzhan Yang, Yang Hou, Min Ma, Aibin Zhan

Abstract read
In one paragraph

Article in Ambio, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
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  7. Article
  8. Urbanization and Waterborne Pathogen Emergence in Low-Income Countries: Where and How to Conduct Surveys?International journal of environmental research and public health · 2020
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yuzhan YangResearch Center for Eco-Environmental Sciences, Chinese Academy of Sciences, 18 Shuangqing Road, Haidian District, Beijing, 100085, China.
Yang HouBeijing Dongcheng District Food and Drug Safety Monitoring Center, 12-14 Zhushikou Street East, Beijing, 100050, China. dc_syakzx@163.com.
Min MaResearch Center for Eco-Environmental Sciences, Chinese Academy of Sciences, 18 Shuangqing Road, Haidian District, Beijing, 100085, China.
Aibin ZhanResearch Center for Eco-Environmental Sciences, Chinese Academy of Sciences, 18 Shuangqing Road, Haidian District, Beijing, 100085, China. azhan@rcees.ac.cn.ORCID http://orcid.org/0000-0003-1416-1238

Funding

Chinese Academy of Science ZDRW-ZS-2016-5Innovation in Cross-functional Team Program of the Chinese Academy of Sciences 2015National Key R&D Program of China 2016YFC0500406National Natural Science Foundation of China 31572228National Natural Science Foundation of China 31800419State Key Joint Laboratory of Environment Simulation and Pollution Control 15K01ESPCRWater Pollution Control and Treatment Special Project 2018ZX07105-001
6 · The paper itself

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.

Indexed as

EcosystemRiversBacteriaChinaEnvironmental MonitoringHumansNitrogenNitrogenCommunity structureEarly warningEnvironmental filteringPotential pathogen bacteriaRisk assessmentWater pollution

Identifiers

PMID31020611
PMCPMC6888796

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.