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Updated: May 10, 2026
Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
Published on: October 15, 2019
High-throughput sequencing reveals differences in microbial community structure and diversity in the conjunctival
Fengjiao Li1, Shuo Yang2, Ji Ma3
1Department of Opthalmology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, Shandong, China.
Background:
To investigate the differences in bacterial and fungal community structure and diversity in conjunctival tissue of healthy and diabetic mice.
Methods:
RNA-seq assays and high-throughput sequencing of bacterial 16 S rDNA and fungal internal transcribed spacer (ITS) gene sequences were used to identify differentially expressed host genes and fungal composition profiles in conjunctival tissues of diabetic BKS-db/db mice and BKS (control) mice. Functional enrichment analysis of differentially expressed genes and the correlation between the relative abundance of bacterial and fungal taxa in the intestinal mucosa were also performed.
Results:
Totally, 449 differential up-regulated genes and 1,006 down-regulated genes were identified in the conjunctival tissues of diabetic mice. The differentially expressed genes were mainly enriched in metabolism-related functions and pathways. A decrease in conjunctival bacterial species diversity and abundance in diabetic mice compared to control mice. In contrast, fungal species richness and diversity were not affected by diabetes. The microbial colonies were mainly associated with cellular process pathways regulating carbohydrate and lipid metabolism, as well as cell growth and death. Additionally, some interactions between bacteria and fungi at different taxonomic levels were also observed.
Conclusion:
The present study revealed significant differences in the abundance and composition of bacterial and fungal communities in the conjunctival tissue of diabetic mice compared to control mice. The study also highlighted interactions between bacteria and fungi at different taxonomic levels. These findings may have implications for the diagnosis and treatment of diabetes.
