Kim, Bong-Soo
(Department of Life Science, Hallym University)
,
Han, Dong-Hun
(Department of Preventive and Social Dentistry, School of Dentistry, Seoul National University)
,
Lee, Ho
(Department of Oral and Maxillofacial Surgery, Section of Dentistry, SMG- SNU Boramae Medical Center)
,
Oh, Bumjo
(Department of Family Medicine, SMG-SNU Boramae Medical Center)
Salivary microbiota alterations can correlate with dental caries development in children, and mechanisms mediating this association need to be studied in further detail. Our study explored salivary microbiota shifts in children and their association with the incidence of dental caries with dentine i...
Salivary microbiota alterations can correlate with dental caries development in children, and mechanisms mediating this association need to be studied in further detail. Our study explored salivary microbiota shifts in children and their association with the incidence of dental caries with dentine involvement. Salivary samples were collected from children with caries and their subsequently matched caries-free controls before and after caries development. The microbiota was analyzed by 16S rRNA gene-based high-throughput sequencing. The salivary microbiota was more diverse in caries-free subjects than in those with dental caries with dentine involvement (DC). Although both groups exhibited similar shifts in microbiota composition, an association with caries was found by function prediction. Analysis of potential microbiome functions revealed that Granulicatella, Streptococcus, Bulleidia, and Staphylococcus in the DC group could be associated with the bacterial invasion of epithelial cells, phosphotransferase system, and ${\text\tiny{D}}-alanine$ metabolism, whereas Neisseria, Lautropia, and Leptotrichia in caries-free subjects could be associated with bacterial motility protein genes, linoleic acid metabolism, and flavonoid biosynthesis, suggesting that functional differences in the salivary microbiota may be associated with caries formation. These results expand the current understanding of the functional significance of the salivary microbiome in caries development, and may facilitate the identification of novel biomarkers and treatment targets.
Salivary microbiota alterations can correlate with dental caries development in children, and mechanisms mediating this association need to be studied in further detail. Our study explored salivary microbiota shifts in children and their association with the incidence of dental caries with dentine involvement. Salivary samples were collected from children with caries and their subsequently matched caries-free controls before and after caries development. The microbiota was analyzed by 16S rRNA gene-based high-throughput sequencing. The salivary microbiota was more diverse in caries-free subjects than in those with dental caries with dentine involvement (DC). Although both groups exhibited similar shifts in microbiota composition, an association with caries was found by function prediction. Analysis of potential microbiome functions revealed that Granulicatella, Streptococcus, Bulleidia, and Staphylococcus in the DC group could be associated with the bacterial invasion of epithelial cells, phosphotransferase system, and ${\text\tiny{D}}-alanine$ metabolism, whereas Neisseria, Lautropia, and Leptotrichia in caries-free subjects could be associated with bacterial motility protein genes, linoleic acid metabolism, and flavonoid biosynthesis, suggesting that functional differences in the salivary microbiota may be associated with caries formation. These results expand the current understanding of the functional significance of the salivary microbiome in caries development, and may facilitate the identification of novel biomarkers and treatment targets.
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가설 설정
(A) Numbers of observed operational taxonomic units (OTUs) in the initial and follow-up samples were compared between the caries-free (CF) and dental caries (DC) groups. (B) Changes in the Shannon diversity index were compared between groups using boxplot analyses. (C) The phylum compositions in the salivary microbiomes were compared among groups.
제안 방법
The salivary flow rate was measured in ml/min. Information on toothbrushing frequency, snack and fresh fruit and/or vegetable consumption, and exposure to second-hand smoke was obtained with a questionnaire.
The functions of the microbiota were predicted in PICRUSt and the statistical significance was analyzed with STAMP. The KEGG Orthology category for “bacterial invasion of epithelial cells” was different between the groups (Fig.
대상 데이터
Corrections were made using the Benjamini-Hochberg false discovery rate multiple testing correction [25]. All pyrosequencing reads have been deposited in the EMBL SRA database under the study accession number PRJEB19674 (http://www.ebi.ac.uk/ena/data/view/PRJEB19674).
Initial sampling started in 2009, and follow-up exams were conducted in 2012. Study participants were recruited from 13 community child centers since March 2009. We contacted the parents/guardians of 338 eligible children, of which 302 children were enrolled (89.
Three children were excluded from follow-up subjects, since they had one carious surface in their permanent tooth. Thus, the final sample was composed of 12 CF individuals and 12 DC patients with incidence of two or more surfaces of dental caries (Fig. S1). This study was approved by the Institutional Review Board of Pusan National University Hospital at the Yangsan campus (IRB No.
데이터처리
Changes in the saliva microbiota were set as the dependent variable, whereas body measurements and survey results were set as discriminatory variables. Categorical (sex, consumption of snacks, consumption of fresh fruits and/or vegetables, exposure to second-hand smoke) and continuous (age, salivary flow rate, toothbrushing frequency) variables were analyzed using chisquared and independent t-tests, respectively. The statistical differences in predicted functions of microbiota between groups were analyzed using the Statistical Analysis of Metagenomic Profiles (STAMP) software package [26].
이론/모형
The p value of functional prediction was determined by the Kruskal-Wallis test[24]. Corrections were made using the Benjamini-Hochberg false discovery rate multiple testing correction [25]. All pyrosequencing reads have been deposited in the EMBL SRA database under the study accession number PRJEB19674 (http://www.
The p values were determined with Kruskal-Wallis H and Mann-Whitney rank sum testing [24]. Multiple test corrections were made using Benjamini- Hochberg false discovery rates [25]. Results with p values of <0.
0) [23]. The p value of functional prediction was determined by the Kruskal-Wallis test[24]. Corrections were made using the Benjamini-Hochberg false discovery rate multiple testing correction [25].
Categorical (sex, consumption of snacks, consumption of fresh fruits and/or vegetables, exposure to second-hand smoke) and continuous (age, salivary flow rate, toothbrushing frequency) variables were analyzed using chisquared and independent t-tests, respectively. The statistical differences in predicted functions of microbiota between groups were analyzed using the Statistical Analysis of Metagenomic Profiles (STAMP) software package [26]. The p values were determined with Kruskal-Wallis H and Mann-Whitney rank sum testing [24].
Trimmed sequences were clustered by 97% similarity with the USEARCH program [19], and representative sequences in each cluster were selected to identify their taxonomic positions. The taxonomic assignments were conducted according to the RDP classifier against the EzTaxon-e database [20]. Chimera sequences were detected and removed by UCHIME for further analysis [21].
성능/효과
(A) Numbers of observed operational taxonomic units (OTUs) in the initial and follow-up samples were compared between the caries-free (CF) and dental caries (DC) groups. (B) Changes in the Shannon diversity index were compared between groups using boxplot analyses.
Analysis of predicted microbiota functions showed that “bacterial invasion of epithelial cells,”“phosphotransferase system,” “D-alanine metabolism,” and “starch and sucrose metabolism” were higher in the initial time, whereas predicted functions related to “bacterial motility proteins,” “linoleic acid metabolism,”“flavonoid biosynthesis,” and “biosynthesis of type II polyketide products” were higher in the follow-up groups.
1C). In crosssectional comparisons, the proportion of Firmicutes was higher in DC samples than in CF samples at both sampling times, whereas Actinobacteria at the initial measurement and Proteobacteria and Fusobacteria at the follow-up measurement were more prevalent in the CF samples than in the DC samples. However, the cross-sectional differences in the phylum composition between the CF and DC groups were not statistically significant (p > 0.
The proportions of Streptococcus were higher in DC than in CF samples at both sampling times. The proportions of Oribacterium were higher in the CF group at the initial time, whereas those of Actinomyces, Leptotrichia, and Atopobium were higher in the CF group at follow-up time than in the DC groups. Although these genera were different between the CF and DC groups, the statistical significances were relatively low (p < 0.
With respect to other Firmicutes genera, the proportions of Granulicatella and Gemella were significantly decreased in both groups (p < 0.05), whereas those of Vellionella (p < 0.05) and Oribacterium (p < 0.05 in the CF group) were increased.
후속연구
Although our results could be difficult to generalize owing to the limited number of subjects in each group, this study is valuable because it suggests that the functions of the salivary microbiota can be associated with dental caries development by prediction of longitudinal study. Further comprehensive prospective studies are needed to clarify the association between the salivary microbiome and dental caries development. In addition, although the salivary microbiome may not be a good indicator for the risk of developing dental caries, some evidence suggests that it may be a good indicator of ongoing functions associated with dental caries [12].
S5. However, these results were obtained from in silico prediction, and further studies including metatranscriptomics and metabolomics should be conducted to understand the ecological role of the salivary microbiome in dental caries development.
Moreover, different species may play distinct roles in caries development by participating in the bacterial invasion of epithelial cells, phosphotransferase system, and/or D-alanine metabolism, whereas other species associated with bacterial motility protein expression, linoleic acid metabolism, and flavonoid biosynthesis may block this occurrence. Nevertheless, further studies with a larger sample size are necessary to identify microbial biomarkers sufficient to prevent dental caries.
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