Evidence map›Paper›PMID 38448523›Full record

ArticleScientific reports2024

Seasonal changes of prokaryotic microbial community structure in Zhangjiayan Reservoir and its response to environmental factors.

Xintao Yu, Yong Li, Yue Wu, Hui Gao, Wei Liu, Huan Liu, Sidan Gong, Honglian Wu

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
9.6field-weighted citation impact, top 2% 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

6 citing papers in PubMed, 21 citations in OpenAlex.

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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

8 authors at 1 institution in 1 country.

Xintao YuFaculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 610059, China.
Yong LiFaculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 610059, China. liyong@swjtu.edu.cn.
Yue WuSichuan Aqua Gathering Eco-environment Management Co., Ltd., Neijiang, 641000, China.
Hui GaoEastern Newly Developed Area Water Conservany Administrative Station, Pihe River Administrative Office, Sichuan Du Jiangyan Water Conservancy Development Center, Chengdu, 641400, China.
Wei LiuEastern Newly Developed Area Water Conservany Administrative Station, Pihe River Administrative Office, Sichuan Du Jiangyan Water Conservancy Development Center, Chengdu, 641400, China.
Huan LiuFaculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 610059, China.
Sidan GongFaculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 610059, China.
Honglian WuEastern Newly Developed Area Water Conservany Administrative Station, Pihe River Administrative Office, Sichuan Du Jiangyan Water Conservancy Development Center, Chengdu, 641400, China.
Southwest Jiaotong University · CN

Funding

the Key Laboratory Open Project of Southwest Jiaotong University ZD2022210017
6 · The paper itself

Abstract

As a typical sub-deep reservoir in the upper reaches of the Yangtze River in the southwest region, Zhangjiayan Reservoir is also an important source of drinking water. Exploring the role of microorganisms in the material cycle of water bodies is of great significance for preventing the exacerbation of eutrophication in the reservoir. In this study, water samples from the overlying water of five points in the reservoir were collected four times in spring (April), summer (July), autumn (November), and winter (January) of 2022-2023 using a gas-tight water sampler. Physicochemical factors were measured, and the microbial community structure was analyzed by high-throughput MiSeq sequencing of the V3-V4 hypervariable region of 16S rRNA gene in order to explore the relationship between physicochemical factors and microbial community structure and the dominant microbial populations that affect eutrophication of the reservoir. The following results were obtained through analysis. Among the 20 overlying water samples from Zhangjiayan Reservoir, a total of 66 phyla, 202 classes, 499 orders, 835 families, 1716 genera, and 27,904 ASVs of the bacterial domain were detected. The phyla Proteobacteria and Actinobacteria were dominant in the microbial community of the overlying water in Zhangjiayan Reservoir. At the genus level, hgcI_clade and Actinobacteria had the highest abundance and was the dominant population. The microbial community in the water of Zhangjiayan Reservoir has a high level of diversity. The diversity index ranked by numerical order was winter > autumn > summer > spring. Significant differences were found in the composition and structure of the microbial community between the spring/summer and autumn/winter seasons (p < 0.05). Total phosphorus, dissolved total phosphorus, soluble reactive phosphorus, and dissolved oxygen have a significant impact on the composition and structure of the microbial community (p < 0.01). The bacterial community in the overlying water of Zhangjiayan Reservoir showed a mainly positive correlation. Sphingomonas, Brevundimonas, and Blastomonas were the central populations of the bacterial community in the overlying water of Zhangjiayan Reservoir. This study indicates that environmental factors, such as phosphorus and other nutrients, have a significant impact on the formation of the microbial community structure in different seasons. Sphingomonas, Brevundimonas, and Blastomonas are key populations that may have a significant impact on eutrophication in Zhangjiayan Reservoir.

Indexed as

ActinobacteriaCaulobacteraceaeMicrobiotaHumansPhosphorusRNA, Ribosomal, 16SSeasonsWaterPhosphorusRNA, Ribosomal, 16SWater

Identifiers

PMID38448523
PMCPMC10918105
OpenAlexW4392500115

What OpenQuestion holds

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LicenceCC BY
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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.