Evidence map›Paper›PMID 34194406›Full record

ArticleFrontiers in microbiology2021

Synergistic Application of Molecular Markers and Community-Based Microbial Source Tracking Methods for Identification of Fecal Pollution in River Water During Dry and Wet Seasons.

Hongxia Liang, Zhisheng Yu, Bobo Wang, Fabrice Ndayisenga, Ruyin Liu, Hongxun Zhang, Gang Wu

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 27% of its field
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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Article
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

7 authors at 3 institutions in 1 country.

Hongxia LiangCollege of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China.
Zhisheng YuCollege of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China.
Bobo WangCollege of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China.
Fabrice NdayisengaCollege of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China.
Ruyin LiuCollege of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China.
Hongxun ZhangCollege of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China.
Gang WuState Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, University of Chinese Academy of Sciences, Beijing, China.
University of Chinese Academy of Sciences · CNInstitute of Microbiology · CNResearch Center for Eco-Environmental Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is important to track fecal sources from humans and animals that negatively influence the water quality of rural rivers and human health. In this study, microbial source tracking (MST) methods using molecular markers and the community-based FEAST (fast expectation-maximization microbial source tracking) program were synergistically applied to distinguish the fecal contributions of multiple sources in a rural river located in Beijing, China. The performance of eight markers were evaluated using 133 fecal samples based on real-time quantitative (qPCR) technique. Among them, six markers, including universal (BacUni), human-associated (HF183-1 and BacH), swine-associated (Pig-2-Bac), ruminant-associated (Rum-2-Bac), and avian-associated (AV4143) markers, performed well in the study. A total of 96 water samples from the river and outfalls showed a coordinated composition of fecal pollution, which revealed that outfall water might be a potential input of the Fsq River. In the FEAST program, bacterial 16S rRNA genes of 58 fecal and 12 water samples were sequenced to build the "source" library and "sink," respectively. The relative contribution (<4.01% of sequence reads) of each source (i.e., human, swine, bovine, or sheep) was calculated based on simultaneous screening of the operational taxonomic units (OTUs) of sources and sinks, which indicated that community-based MST methods could be promising tools for identifying fecal sources from a more comprehensive perspective. Results of the qPCR assays indicated that fecal contamination from human was dominant during dry weather and that fecal sources from swine and ruminant were more prevalent in samples during the wet season than in those during the dry season, which were consistent with the findings predicted by the FEAST program using a very small sample size. Information from the study could be valuable for the development of improved regulation policies to reduce the levels of fecal contamination in rural rivers.

Indexed as

dry and wet seasonsFEAST programfecal pollutionhigh-throughput sequencingmicrobial source trackingmolecular markersreal-time quantitative PCR

Identifiers

PMID34194406
PMCPMC8236858
OpenAlexW3170675522

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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.