Evidence map›Paper›PMID 37158858›Full record

ArticleBMC ecology and evolution2023

The characteristics of the intestinal bacterial community from Oreochromis mossambicus and its interaction with microbiota from artificial fishery habitats.

Sheng Bi, Han Lai, Dingli Guo, Huadong Yi, Haiyang Li, Xuange Liu, Qiuxian Chen, Jiahui Chen, Zhilun Zhang, Xuchong Wei and 2 more

Open access · goldAbstract read
In one paragraph

Article in BMC ecology and evolution, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 41% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

12 authors at 1 institution in 1 country.

Sheng BiSchool of Agriculture, Shenzhen Campus of Sun Yat-sen University, Guangdong, 518107, China.
Han LaiState Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Provincial Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510006, China.
Dingli GuoState Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Provincial Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510006, China.
Huadong YiState Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Provincial Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510006, China.
Haiyang LiState Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Provincial Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510006, China.
Xuange LiuState Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Provincial Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510006, China.
Qiuxian ChenState Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Provincial Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510006, China.
Jiahui ChenState Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Provincial Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510006, China.
Zhilun ZhangState Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Provincial Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510006, China.
Xuchong WeiState Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Provincial Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510006, China.
Guifeng LiState Key Laboratory of Biocontrol, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong Provincial Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510006, China. liguif@mail.sysu.edu.cn.
Guorong XinSchool of Agriculture, Shenzhen Campus of Sun Yat-sen University, Guangdong, 518107, China. lssxgr@mail.sysu.edu.cn.
Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial habitats can allow many fish to flock together and interact and have been widely used to restore and protect fishery resources. The piece of research intends to elucidate the relationship of microbial communities between tilapia (Oreochromis mossambicus) intestines and artificial fishery habitats (water and sediments). Hence, 16 S rDNA sequencing technology was used to study the bacterial communities from intestines, water, and sediments.

resultsThe results showed that the tilapia intestines had the lowest richness of Operational Taxonomic Units (OTUs) and the lowest diversity of the bacterial community compared to water and sediments. The intestine, water, and sediment microbial communities shared many OTUs. Overall, 663 shared OTUs were identified from the tilapia intestines (76.20%), the surrounding water (71.14%), and sediment (56.86%) in artificial habitats. However, there were unique OTUs that were detected in different sample types. There were 81, 77 and 112 unique OTUs observed in tilapia intestines, the surrounding water and sediment, respectively. Proteobacteria, Cyanobacteria, Actinobacteria, Firmicutes, Fusobacteria, and Bacteroidetes were the most common and dominant bacterial phyla between the tilapia intestines and habitats. In the two groups, the microbial communities were similar in the taxonomic composition but different in the abundance of bacterial phyla. Interestingly, Firmicutes increased, while Fusobacteria decreased in artificial habitats. These findings indicated that the artificial habitats had fewer effects on the water environment and indicated that the mode of artificial habitats could have an effect on the enriched bacteria in the tilapia intestines.

conclusionsThis study analysed the bacterial communities of artificial habitats from the intestines, water, and sediments, which can explain the relationship between the tilapia intestines and habitats and strengthen the value of ecological services provided by artificial habitats.

Indexed as

MicrobiotaTilapiaVerbenaceaeAnimalsBacillotaFisheriesFusobacteriaFusobacteriumWaterWater16S rRNAHydrobiologyMicrobial ecologytilapia

Identifiers

PMID37158858
PMCPMC10165841
OpenAlexW4375955599

What OpenQuestion holds

Textmetadata
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.