16S rRNA gene amplicon sequencing of gut microbiota in gestational diabetes mellitus and their correlation with disease risk factors

From BugSigDB
Reviewed Marked as Reviewed by Claregrieve1 on 2022/06/17
study design
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
Authors
Wei J, Qing Y, Zhou H, Liu J, Qi C, Gao J
Journal
Journal of endocrinological investigation
Year
2021
Keywords:
16S rRNA gene amplicon sequencing, Gestational diabetes mellitus, Gut microbiota, qPCR
PURPOSE: Although the gut microbiota (GM) are associated with various diseases, their role in gestational diabetes mellitus (GDM) remains uncharacterized. Further study is urgently needed to expose the real relationship between GM and GDM. METHODS: We performed a prospective study in 33 pregnant Chinese individuals [15, GDM; 18, normal glucose tolerance (NGT)] to observe the fecal microbiota by 16S rRNA gene amplicon sequencing at 24-28 weeks of gestational age after a standard 75 g oral glucose tolerance test. Linear regression analysis was employed to assess the relationships between the GM and GDM clinical parameters. RESULTS: Sequencing showed no difference in the microbiota alpha diversity but a significant difference in the beta diversity between the GDM and NGT groups, with the relative abundances of Ruminococcus bromii, Clostridium colinum, and Streptococcus infantis being higher in the GDM group (P < 0.05). The quantitative PCR results validated the putative bacterial markers of R. bromii and S. infantis. Moreover, a strong positive correlation was found between S. infantis and blood glucose levels after adjusting for body mass index (P < 0.05). CONCLUSION: Three abnormally expressed intestinal bacteria (R. bromii, C. colinum, and S. infantis) were identified in GDM patients. S. infantis may confer an increased risk of GDM. Hence, the GM may serve as a potential therapeutic target for GDM.

Experiment 1


Reviewed Marked as Reviewed by Claregrieve1 on 2022/06/17

Curated date: 2021/06/29

Curator: Madhubani Dey

Revision editor(s): Madhubani Dey, WikiWorks, Peace Sandy

Subjects

Location of subjects
China
Host species Species from which microbiome was sampled. Contact us to have more species added.
Homo sapiens
Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology
Feces Cow dung,Cow pat,Droppings,Dung,Excrement,Excreta,Faeces,Fecal material,Fecal matter,Fewmet,Frass,Guano,Matières fécales@fr,Merde@fr,Ordure,Partie de la merde@fr,Piece of shit,Porción de mierda@es,Portion of dung,Portion of excrement,Portion of faeces,Portion of fecal material,Portion of fecal matter,Portion of feces,Portion of guano,Portion of scat,Portionem cacas,Scat,Spoor,Spraint,Stool,Teil der fäkalien@de,Feces,feces
Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology
Gestational diabetes diabetes in pregnancy,GDM,gestational diabetes,gestational diabetes mellitus,maternal gestational diabetes mellitus,Gestational diabetes
Group 0 name Corresponds to the control (unexposed) group for case-control studies
Pregnant individuals who are normal glucose tolerance (NGT)]
Group 1 name Corresponds to the case (exposed) group for case-control studies
Pregnant individuals with gestational diabetes
Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
Pregnant individuals with gestational diabetes
Group 0 sample size Number of subjects in the control (unexposed) group
18
Group 1 sample size Number of subjects in the case (exposed) group
15
Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any)
1 month

Lab analysis

Sequencing type
16S
16S variable region One or more hypervariable region(s) of the bacterial 16S gene
V4
Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance
Illumina

Statistical Analysis

Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).
relative abundances
Statistical test
LEfSe
Significance threshold p-value or FDR threshold used for differential abundance testing (if any)
0.05
MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?
No
LDA Score above Threshold for the linear discriminant analysis (LDA) score for studies using the popular LEfSe tool
2

Alpha Diversity

Shannon Estimator of species richness and species evenness: more weight on species richness
unchanged
Chao1 Abundance-based estimator of species richness
unchanged
Simpson Estimator of species richness and species evenness: more weight on species evenness
unchanged
Richness Number of species
unchanged

Signature 1

Reviewed Marked as Reviewed by Claregrieve1 on 2022/06/17

Curated date: 2021/08/16

Curator: Madhubani Dey

Revision editor(s): Madhubani Dey

Source: Figure 3b, 3c, Table S1

Description: Increased abundance of bacterial communities in GDM individuals as compared to NGT controls

Abundance in Group 1: increased abundance in Pregnant individuals with gestational diabetes

NCBI Quality ControlLinks
Clostridia
Clostridiales bacterium
Bacillota
Ruminococcus bromii
Salmonella enterica subsp. enterica serovar Infantis
[Clostridium] colinum

Revision editor(s): Madhubani Dey

Signature 2

Reviewed Marked as Reviewed by Claregrieve1 on 2022/06/17

Curated date: 2021/08/16

Curator: Madhubani Dey

Revision editor(s): Madhubani Dey

Source: Figure 3b, 3c, Table S1

Description: Decreased abundance of bacterial communities in GDM individuals as compared to NGT controls

Abundance in Group 1: decreased abundance in Pregnant individuals with gestational diabetes

NCBI Quality ControlLinks
Bacteroidales
Bacteroidota
Bacteroidia
Lachnobacterium

Revision editor(s): Madhubani Dey