Oral Microbiome Shifts From Caries-Free to Caries-Affected Status in 3-Year-Old Chinese Children: A Longitudinal Study - Xu, He; Tian, Jing; Hao, Wenjing; Zhang, Qian; Zhou, Qiong; Shi, Weihua; Qin, Man; He, Xuesong; Chen, Feng (Frontiers in Microbiology, 2018)
As one of the most prevalent human infectious diseases, dental caries results from dysbiosis of the oral microbiota driven by multiple factors. However, little is known about the distinct microbiota dynamics, and particularly the change in species association pattern during disease transition. Here, we reported a twelve-month longitudinal study of 144 3-year-old caries-free children. Oral examinations and supragingival plaque collections were carried out at the beginning and every subsequent six months, for a total of three time points. The caries-affected (CA) group consisted of 10 subjects who underwent the transition from caries-free to caries state at 6-month follow-up but had not received any dental treatment until the end of the study. The caries-free (CF) group consisted of 19 subjects who were selected from 58 children that remained caries-free during the entire follow-up. Using the V3-V4 16S rRNA gene sequencing, we monitored the shift of supragingival microbiome during caries initiation and progression over the 12-month. Principle coordinates analyses revealed two major shifting patterns in microbial structures during caries initiation and progression in the CA group, but not in the CF group. Dynamic co-occurring OTU network study showed significant increase in both the number and intensity of microbial correlations, as well as the formation of tight clusters of specific bacteria in the CA group. Furthermore, enhanced correlations within species were detected within the CA group, including positive ones between CA-enriched taxa, and negative ones between CF-enriched and CA-enriched species. Our data suggested that coordinated microbial interactions could be essential to caries pathogenesis; furthermore, significant microbial shifts occur not only during caries development, but even in the sub-clinical state. Using supragingival microbiome profiles, we constructed a caries-onset prediction model with a prediction accuracy of 93.1%. Our study indicated that the microbial shifts prior to the onset of caries might potentially be used for the early diagnosis and prediction of caries.