Differential Analysis of Oral Microbiota in db/db Mouse Model of Type 2 Diabetes Utilizing 16S rRNA Sequencing

ObjectiveTo investigate the changes in oral microbiota of db/db mice and provide an experimental basis for exploring the relationship between type 2 diabetes mellitus and oral microecology.MethodsEight 10-week-old male db/db mice were designated as the diabetes experimental group (db/db group), while eight 10-week-old male db/m mice were assigned as the normal control group (db/m group). After a 5-day adaptive feeding period, tail venous blood samples were collected on the 6th and 37th days, and fasting blood glucose (FBG) levels and oral glucose tolerance test (OGTT) were performed for both groups to verify the reliability of the diabetes model. On the 15th day of feeding with the same diet, oral microbiota samples were collected from the buccal mucosa, dorsal and ventral tongue surfaces, oral floor mucosa, hard palate mucosa, and the gingival areas of both the upper and lower jaws of the two groups. Genomic DNA from the oral microbiota was extracted, and the V3-V4 regions of the 16S ribosomal RNA (16S rRNA) gene were amplified using a GeneAmp 9700 thermocycler. The composition of the oral microbiota was evaluated through double-labelled amplification and sequencing on the Illumina MiSeq platform, followed by bioinformatics analysis using QIIME software(version 1.6.0).ResultsThe FBG levels and OGTT results on the 6th and 37th days after the start of the experiment indicated that db/db mice exhibited more pronounced symptoms of type 2 diabetes compared to db/m mice. Alpha diversity (α diversity) analysis showed no significant difference in the diversity of oral microbiota between the two groups (P>0.05); however, there was a significant difference in richness (P<0.05). Principal coordinate analysis(PCoA) revealed differences in the oral microbiota composition between the db/db group and db/m group (P<0.05). Species composition analysis and LEfSe analysis demonstrated that the relative abundance of oral microbiota in db/db group mice, predominantly composed of p_Proteobacteria, increased significantly at the phylum level (P<0.05). At the genus level, the relative abundances of g_Proteus and g_Enterococcus showed a significant increase (P<0.001).ConclusionThe composition and diversity of oral microbiota in db/db mice with type 2 diabetes mellitus significantly differed from those without the disease.

Institutions

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-04-01
DOI
https://doi.org/10.12300/j.issn.1674-5817.2024.119
Primary Topic
Urban and spatial planning
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Differential Analysis of Oral Microbiota in db/db Mouse Model of Type 2 Diabetes Utilizing 16S rRNA Sequencing

SHILAP Revista de lepidopterología
Urban and spatial planning
article

Differential Analysis of Oral Microbiota in db/db Mouse Model of Type 2 Diabetes Utilizing 16S rRNA Sequencing

article en

Abstract

ObjectiveTo investigate the changes in oral microbiota of db/db mice and provide an experimental basis for exploring the relationship between type 2 diabetes mellitus and oral microecology.MethodsEight 10-week-old male db/db mice were designated as the diabetes experimental group (db/db group), while eight 10-week-old male db/m mice were assigned as the normal control group (db/m group). After a 5-day adaptive feeding period, tail venous blood samples were collected on the 6th and 37th days, and fasting blood glucose (FBG) levels and oral glucose tolerance test (OGTT) were performed for both groups to verify the reliability of the diabetes model. On the 15th day of feeding with the same diet, oral microbiota samples were collected from the buccal mucosa, dorsal and ventral tongue surfaces, oral floor mucosa, hard palate mucosa, and the gingival areas of both the upper and lower jaws of the two groups. Genomic DNA from the oral microbiota was extracted, and the V3-V4 regions of the 16S ribosomal RNA (16S rRNA) gene were amplified using a GeneAmp 9700 thermocycler. The composition of the oral microbiota was evaluated through double-labelled amplification and sequencing on the Illumina MiSeq platform, followed by bioinformatics analysis using QIIME software(version 1.6.0).ResultsThe FBG levels and OGTT results on the 6th and 37th days after the start of the experiment indicated that db/db mice exhibited more pronounced symptoms of type 2 diabetes compared to db/m mice. Alpha diversity (α diversity) analysis showed no significant difference in the diversity of oral microbiota between the two groups (P>0.05); however, there was a significant difference in richness (P<0.05). Principal coordinate analysis(PCoA) revealed differences in the oral microbiota composition between the db/db group and db/m group (P<0.05). Species composition analysis and LEfSe analysis demonstrated that the relative abundance of oral microbiota in db/db group mice, predominantly composed of p_Proteobacteria, increased significantly at the phylum level (P<0.05). At the genus level, the relative abundances of g_Proteus and g_Enterococcus showed a significant increase (P<0.001).ConclusionThe composition and diversity of oral microbiota in db/db mice with type 2 diabetes mellitus significantly differed from those without the disease.

SHILAP Revista de lepidopterología
Soochow University (CN), The First People's Hospital of Changzhou (CN), First Affiliated Hospital of Soochow University (CN), Changzhou Third People's Hospital (CN)
Openalex Percentile: Top 54%
Urban and spatial planning
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.