Amplification and sequencing of 16S amplicons are widely used for profiling the structure of oral microbiota. However, it remains not clear whether and to what degree DNA extraction and targeted 16S rRNA hypervariable regions influence the analysis. Based on a mock community consisting of five oral bacterial species in equal abundance, we compared the 16S amplicon sequencing results on the Illumina MiSeq platform from six frequently employed DNA extraction procedures and three pairs of widely used 16S rRNA hypervariable primers targeting different 16S rRNA regions. Technical reproducibility of selected 16S regions was also assessed. DNA extraction method exerted considerable influence on the observed bacterial diversity while hypervariable regions had a relatively minor effect. Protocols with beads added to the enzyme-mediated DNA extraction reaction produced more accurate bacterial community structure than those without either beads or enzymes. Hypervariable regions targeting V3-V4 and V4-V5 seemed to produce more reproducible results than V1-V3. Neither sequencing batch nor change of operator affected the reproducibility of bacterial diversity profiles. Therefore, DNA extraction strategy and 16S rDNA hypervariable regions both influenced the results of oral microbiota biodiversity profiling, thus should be carefully considered in study design and data interpretation.

Objectives: Childhood obesity/underweight status and caries are both important public health problems. This study aims to investigate the caries status and its association with body weight in 8-year-old children in Qingdao, China. Materials and Methods: We initiated a cross-sectional investigation on 744 children aged 8 years during the Oral Health Survey in 2012. Dental caries assessments were carried out and weight status was recorded accordingly. The resulting caries status including caries prevalence, dmft (deciduous dentition), and (dmft + DMFT) (mixed dentition), as well as BMI indices were analyzed for comparison and correlation. Results: The prevalence of dental caries among the 744 children aged 8 years participating in this survey was 86.3%. The caries status represented by dmft (deciduous dentition) and (dmft + DMFT) (mixed dentition) values was 4.31 and 4.85, respectively, and the restoration rate was extremely low, which was no more than 3.0%. Significant difference was found in dmft/(dmft + DMFT) values between different BMI groups, and underweight individuals were found to have the highest dmft/(dmft + DMFT) value. An inverse relationship between body BMI and dmft/(dmft + DMFT) index was identified based on Pearson's correlation. Conclusions: A severe state of caries disease was revealed in 8-year-old children in the Chinese city of Qingdao, for whom urgent dental intervention and treatment were needed. Furthermore, underweight individuals were found with the most severe caries experience, indicating caries may affect the development and growth of the afflicted children. Thus, more emphasis should be placed on improving their dental health, with caries prevention being given the priority.

Dental caries is one of the most prevalent chronic oral diseases, affecting approximately half of children worldwide. The microbial composition of dental caries may depend on age, oral health, diet, and geography, yet the effect of geography on these microbiomes is largely underexplored. Here, we profiled and compared saliva microbiota from 130 individuals aged 6 to 8 years old, representing both healthy children (H group) and children with caries-affected (C group) from two geographical regions of China: a northern city (Qingdao group) and a southern city (Guangzhou group). First, the saliva microbiota exhibited profound differences in diversity and composition between the C and H groups. The caries microbiota featured a lower alpha diversity and more variable community structure than the healthy microbiota. Furthermore, the relative abundance of several genera (e.g., Lactobacillus, Gemella, Cryptobacterium and Mitsuokella) was significantly higher in the C group than in the H group (p<0.05). Next, geography dominated over disease status in shaping salivary microbiota, and a wide array of salivary bacteria was highly predictive of the individuals’ city of origin. Finally, we built a universal diagnostic model based on 14 bacterial species, which can diagnose caries with 87% (AUC=86.00%) and 85% (AUC=91.02%) accuracy within each city and 83% accuracy across cities (AUC=92.17%). Although the detection rate of Streptococcus mutans in populations is not very high, it could be regarded as a single biomarker to diagnose caries with decent accuracy. These findings demonstrated that despite the large effect size of geography, a universal model based on salivary microbiota has the potential to diagnose caries across the Chinese child population.

Early childhood caries (ECC) is one of the most prevalent chronic diseases affecting children worldwide, and thus its etiology, diagnosis, and prognosis are of particular clinical significance. This study aims to test the ability of salivary microbiome and electrolytes in diagnosing ECC, and their interplays within the same population. We here simultaneously profiled salivary microbiome and biochemical components of 331 children (166 caries-free (H group) and 165 caries-active children (C group)) aged 4-6 years. We identified both salivary microbial and biochemical dysbiosis associated with ECC. Remarkably, K⁺, Cl^-, NH₄⁺, Na⁺, SO₄^2-, Ca²⁺, Mg²⁺, and Br^- were enriched while pH and NO₃^- were depleted in ECC. Moreover, the dmft index (ECC severity) positively correlated with Cl^-, NH₄⁺, Ca²⁺, Mg²⁺, Br^-, while negatively with pH and NO₃^-. Furthermore, machine-learning classification models were constructed based on these biomarkers from saliva microbiota, or electrolytes (and pH). Unexpectedly, the electrolyte-based classifier (AUROC = 0.94) outperformed microbiome-based (AUROC = 0.70) one and the composite-based one (with both microbial and biochemical data; AUC = 0.89) in predicting ECC. Collectively, these findings indicate ECC-associated alterations and interplays in the oral microbiota, electrolytes and pH, underscoring the necessity of developing diagnostic models with predictors from salivary electrolytes.