Subgingival microbiota in individuals with severe chronic periodontitis.
OBJECTIVE
Subgingival microorganisms are potentially associated with periodontal diseases. However, the correlation between the variance in the periodontal microbiome and the prevalence and severity of periodontitis remains unclear. The aim of this study was to determine the subgingival microbiota in Taiwanese individuals with severe chronic periodontitis (SP).


METHODS
The composition of the subgingival microbiota in healthy and diseased individuals was compared using a 16S rRNA metagenomic approach and quantitative polymerase chain reaction (qPCR). A total of 20 samples, including 10 from healthy individuals and 10 from SP patients, were analyzed.


RESULTS
We found high microbial diversity, with an average of 774 classified phylotypes per sample and a total of six bacterial phyla across all samples. Cluster analysis by principal component analysis and heat map showed that the bacterial communities were different in the two groups. Streptococcus dominated across all the healthy samples, whereas Prevotella, Porphyromonas, and Treponema were highly abundant across all diseased samples. At least 13 bacterial genera were conserved among all the samples. Only eight genera, including Lautropia, Parvimonas, Actinomyces, Capnocytophaga, Paludibacter, Streptococcus, Haemophilus, and Corynebacterium, were significantly enriched in the healthy group, and six genera, including Porphyromonas, Treponema, Tannerella, Aggregatibacter, Peptostreptococcus, and Filifactor, were significantly enriched in the diseased group. Furthermore, a trend of abundance of bacteria at the species level measured by qPCR in all samples was consistent with the 16S rRNA metagenomics results.


CONCLUSIONS
This study is the first in Taiwan to provide a picture of the microbiome in SP via 16S rRNA metagenomics.
Department of Oral Maxillofacial Surgery, Chang Gung Memorial Hospital, Tao-Yuan County, Taiwan.
Chi-Ying
CY
Tsai
Department of Computer Science, National Tsing Hua University, Hsin-Chu City, Taiwan; Department of Computer Science and Information Engineering, Providence University, Taichung County, Taiwan.
Chuan Yi
CY
Tang
Department of Computer Science, National Tsing Hua University, Hsin-Chu City, Taiwan.
Te-Sheng
TS
Tan
Department of Computer Science and Information Engineering, Providence University, Taichung County, Taiwan.
Kuan-Hsueh
KH
Chen
Department of Computer Science, National Tsing Hua University, Hsin-Chu City, Taiwan.
Ki-Hok
KH
Liao
Department of Medical Laboratory Science and Biotechnology, Yuanpei University, Hsin-Chu City, Taiwan. Electronic address: d918229@gmail.com.
Ming-Li
ML
Liou
D001419:Bacteria / Q000145:classification* / Q000235:genetics / Q000302:isolation & purification*; D001483:Base Sequence; D044822:Biodiversity; D055113:Chronic Periodontitis / Q000382:microbiology*; D005881:Gingiva / Q000382:microbiology*; D006801:Humans; D064307:Microbiota / Q000235:genetics*; D012336:RNA, Ribosomal, 16S / Q000235:genetics; D060888:Real-Time Polymerase Chain Reaction; D017422:Sequence Analysis, DNA; D013624:Taiwan
D012336:RNA, Ribosomal, 16S
16S rRNA metagenomics; severe chronic periodontitis