학술논문

Bacterial diversity and community structure of supragingival plaques in adults with dental health or caries revealed by 16S pyrosequencing
Document Type
article
Source
Frontiers in Microbiology, Vol 7 (2016)
Subject
Dental Caries
Dental Plaque
pyrosequencing
bacterial diversity
16S rDNA
Microbiology
QR1-502
Language
English
ISSN
1664-302X
Abstract
Dental caries has a polymicrobial etiology within the complex oral microbial ecosystem. However, the overall diversity and structure of supragingival plaque microbiota in adult dental health and caries are not well understood. Here, 160 supragingival plaque samples from patients with dental health and different severities of dental caries were collected for bacterial genomic DNA extraction, pyrosequencing by amplification of the 16S rDNA V1–V3 hypervariable regions, and bioinformatic analysis. High-quality sequences (2,261,700) clustered into 10,365 operational taxonomic units (OTUs; 97% identity), representing 453 independent species belonging to 122 genera, 66 families, 34 orders, 21 classes, and 12 phyla. All groups shared 7522 OTUs, indicating the presence of a core plaque microbiome. Smooth rarefaction curves were suggestive of plaque microbial diversity. α diversity analysis showed that healthy plaque microbial diversity exceeded that of dental caries, with the diversity decreasing gradually with the severity of caries. The dominant phyla of plaque microbiota included Bacteroidetes, Actinobacteria, Proteobacteria, Firmicutes, Fusobacteria, and TM7. The dominant genera included Capnocytophaga, Prevotella, Actinomyces, Corynebacterium, Neisseria, Streptococcus, Rothia, and Leptotrichia. β diversity analysis showed that the plaque microbial community structure was similar in all groups and that group members were relatively constant, only showing differences in abundance. Analysis of composition differences identified 10 health-related and 21 caries-related genera. Key genera (27) that potentially contributed to plaque microbiota distributions between groups were identified. Finally, co-occurrence network analysis and function prediction were performed. Treatment strategies directed toward modulating microbial interactions and their functional output should be further developed.