Evidence map›Paper›PMID 30696861›Full record

ArticleScientific reports2019

Microbiome Alteration in Type 2 Diabetes Mellitus Model of Zebrafish.

Fumiyoshi Okazaki, Liqing Zang, Hiroko Nakayama, Zhen Chen, Zi-Jun Gao, Hitoshi Chiba, Shu-Ping Hui, Takahiko Aoki, Norihiro Nishimura, Yasuhito Shimada

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

21 citing papers in PubMed, 47 citations in OpenAlex.

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  8. Inhibitory Effects ofFoods (Basel, Switzerland) · 2024
    Article
  9. Article
  10. Review
  11. Review
  12. Application of zebrafish in the study of the gut microbiome.Animal models and experimental medicine · 2022
    Review
  13. Article
  14. Gut Microbiota: An Important Player in Type 2 Diabetes Mellitus.Frontiers in cellular and infection microbiology · 2022
    Review
  15. Article
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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

10 authors at 3 institutions in 1 country.

Fumiyoshi OkazakiDepartment of Life Sciences, Graduate School of Bioresources, Mie University, 1577 Kurimamachiya, Tsu, Mie, 514-8507, Japan.
Liqing ZangMie University Zebrafish Drug Screening Center, Tsu, Mie, Japan.ORCID 0000-0001-6936-795X
Hiroko NakayamaMie University Zebrafish Drug Screening Center, Tsu, Mie, Japan.
Zhen ChenFaculty of Health Sciences, Hokkaido University, Kita-12, Nishi-5, Kita-ku, Sapporo, 060-0812, Japan.
Zi-Jun GaoFaculty of Health Sciences, Hokkaido University, Kita-12, Nishi-5, Kita-ku, Sapporo, 060-0812, Japan.
Hitoshi ChibaDepartment of Nutrition, Sapporo University of Health Sciences, Nakanuma Nishi-4-2-1-15, Higashi-ku, Sapporo, 007-0894, Japan.
Shu-Ping HuiFaculty of Health Sciences, Hokkaido University, Kita-12, Nishi-5, Kita-ku, Sapporo, 060-0812, Japan.
Takahiko AokiDepartment of Life Sciences, Graduate School of Bioresources, Mie University, 1577 Kurimamachiya, Tsu, Mie, 514-8507, Japan.
Norihiro NishimuraMie University Zebrafish Drug Screening Center, Tsu, Mie, Japan.
Yasuhito ShimadaDepartment of Bioinformatics, Mie University Advanced Science Research Promotion Center, Tsu, Mie, Japan. shimada.yasuhito@mie-u.ac.jp.
Mie University · JPHokkaido University · JPSapporo University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the gut microbiota in metabolic disorders, including type 2 diabetes mellitus (T2DM), is now gaining importance due to its potential role in disease risk and progression. We previously established a zebrafish model of T2DM, which shows glucose intolerance with insulin resistance and responds to anti-diabetic drugs. In this study, we analysed the gut microbiota of T2DM zebrafish by deep sequencing the 16S rRNA V3-V4 hypervariable regions, and imputed a functional profile using predictive metagenomic tools. While control and T2DM zebrafish were fed with the same kind of feed, the gut microbiota in T2DM group was less diverse than that of the control. Predictive metagenomics profiling using PICRUSt revealed functional alternation of the KEGG pathways in T2DM zebrafish. Several amino acid metabolism pathways (arginine, proline, and phenylalanine) were downregulated in the T2DM group, similar to what has been previously reported in humans. In summary, we profiled the gut microbiome in T2DM zebrafish, which revealed functional similarities in gut bacterial environments between these zebrafish and T2DM affected humans. T2DM zebrafish can become an alternative model organism to study host-bacterial interactions in human obesity and related diseases.

Indexed as

AnimalsBacteriaDiabetes MellitusDisease Models, AnimalGastrointestinal MicrobiomeGlucose IntoleranceMaleMetagenomeMetagenomicsRNA, Ribosomal, 16SZebrafishRNA, Ribosomal, 16S

Identifiers

PMID30696861
PMCPMC6351536
OpenAlexW2914206185

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.