Evidence map›Paper›PMID 37520377›Full record

ArticleFrontiers in microbiology2023

Meta-analysis reveals variations in microbial communities from diverse stony coral taxa at different geographical distances.

Peng-Tao Pei, Lu Liu, Xiao-Li Jing, Xiao-Lu Liu, Lu-Yang Sun, Chen Gao, Xiao-Han Cui, Jing Wang, Zhong-Lian Ma, Shu-Yue Song and 2 more

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

12 authors.

Peng-Tao PeiKey Laboratory of Marine Drugs, The Ministry of Education of China, Institute of Evolution and Marine Biodiversity, School of Medicine and Pharmacy, Ocean University of China, Qingdao, China.
Lu LiuSchool of Pharmacy, Fujian Health College, Fuzhou, China.
Xiao-Li JingHigh Performance Computing and System Simulation Platform, National Laboratory for Marine Science and Technology (Qingdao), Qingdao, China.
Xiao-Lu LiuSingle-Cell Center, Chinese Academy of Science Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Shandong Energy Institute, Qingdao New Energy Shandong Laboratory, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, China.
Lu-Yang SunSingle-Cell Center, Chinese Academy of Science Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Shandong Energy Institute, Qingdao New Energy Shandong Laboratory, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, China.
Chen GaoSingle-Cell Center, Chinese Academy of Science Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Shandong Energy Institute, Qingdao New Energy Shandong Laboratory, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, China.
Xiao-Han CuiSingle-Cell Center, Chinese Academy of Science Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Shandong Energy Institute, Qingdao New Energy Shandong Laboratory, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, China.
Jing WangSingle-Cell Center, Chinese Academy of Science Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Shandong Energy Institute, Qingdao New Energy Shandong Laboratory, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, China.
Zhong-Lian MaKey Laboratory of Marine Drugs, The Ministry of Education of China, Institute of Evolution and Marine Biodiversity, School of Medicine and Pharmacy, Ocean University of China, Qingdao, China.
Shu-Yue SongKey Laboratory of Marine Drugs, The Ministry of Education of China, Institute of Evolution and Marine Biodiversity, School of Medicine and Pharmacy, Ocean University of China, Qingdao, China.
Zhi-Hua SunDepartment of Mathematics, Ocean University of China, Qingdao, China.
Chang-Yun WangKey Laboratory of Marine Drugs, The Ministry of Education of China, Institute of Evolution and Marine Biodiversity, School of Medicine and Pharmacy, Ocean University of China, Qingdao, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coral-associated microbial communities play a vital role in underpinning the health and resilience of reef ecosystems. Previous studies have demonstrated that the microbial communities of corals are affected by multiple factors, mainly focusing on host species and geolocation. However, up-to-date, insight into how the coral microbiota is structured by vast geographic distance with rich taxa is deficient. In the present study, the coral microbiota in six stony coral species collected from the coastal area of three countries, including United States of America (USA), Australia and Fiji, was used for analysis. It was found that the geographic influence on the coral microbiota was stronger than the coral host influence, even though both were significant. Interestingly, the contribution of the deterministic process to bacterial community composition increased as geographical distance grew. A total of 65 differentially abundant features of functions in coral microbial communities were identified to be associated with three geolocations. While in the same coastal area of USA, the similar relationship of coral microbiota was consistent with the phylogenetic relationship of coral hosts. In contrast to the phylum Proteobacteria, which was most abundant in other coral species in USA, Cyanobacteria was the most abundant phylum in

Indexed as

16S rRNA genediversity analysislarge geographical distancemicrobiomestony coral

Identifiers

PMID37520377
PMCPMC10374221

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