Biocultural Drivers of Salivary Microbiota in Australian Aboriginal and Torres Strait Islander Children

Oral microbiota of patients with phenylketonuria: A nation-based cross-sectional study

AIM

The oral microenvironment contributes to microbial composition and immune equilibrium. It is considered to be influenced by dietary habits. Phenylketonuria (PKU) patients, who follow a lifelong low-protein diet, exhibit higher prevalence of oral diseases such as periodontitis, offering a suitable model to explore the interplay between diet, oral microbiota and oral health.

MATERIALS AND METHODS

We conducted 16S rDNA sequencing on saliva and subgingival plaque from 109 PKU patients (ages 6-68 years) and 114 age-matched controls and correlated oral microbial composition and dental health.

RESULTS

PKU patients exhibited worse dental health, reduced oral microbial diversity and a difference in the abundance of specific taxa, especially Actinobacteriota species, compared to controls. PKU patients with poor periodontal health exhibited higher alpha diversity than the orally healthy ones, marked by high abundance of the genus Tannerella. Notably, the observed taxonomic differences in PKU patients with normal indices of decayed/missing/filled teeth, plaque control record, gingival bleeding index and periodontal screening and recording index generally differed from microbial signatures of periodontitis.

CONCLUSIONS

PKU patients' reduced microbial diversity may be due to their diet's metabolic challenges disrupting microbial and immune balance, thus increasing oral inflammation. Higher alpha diversity in PKU patients with oral inflammation is likely related to expanded microbial niches.

Oral microbiota analyses of paediatric Saudi population reveals signatures of dental caries

BACKGROUND

Oral microbiome sequencing has revealed key links between microbiome dysfunction and dental caries. However, these efforts have largely focused on Western populations, with few studies on the Middle Eastern communities. The current study aimed to identify the composition and abundance of the oral microbiota in saliva samples of children with different caries levels using machine learning approaches.

METHODS

Oral microbiota composition and abundance were identified in 250 Saudi participants with high dental caries and 150 with low dental caries using 16 S rRNA sequencing on a NextSeq 2000 SP flow cell (Illumina, CA) using 250 bp paired-end reads, and attempted to build a classifier using random forest models to assist in the early detection of caries.

RESULTS

The ADONIS test results indicate that there was no significant association between sex and Bray-Curtis dissimilarity (p ~ 0.93), but there was a significant association with dental caries status (p ~ 0.001). Using an alpha level of 0.05, five differentially abundant operational taxonomic units (OTUs) were identified between males and females as the main effect along with four differentially abundant OTUs between high and low dental caries. The mean metrics for the optimal hyperparameter combination using the model with only differentially abundant OTUs were: Accuracy (0.701); Matthew's correlation coefficient (0.0509); AUC (0.517) and F1 score (0.821) while the mean metrics for random forest model using all OTUs were:0.675; 0.054; 0.611 and 0.796 respectively.

CONCLUSION

The assessment of oral microbiota samples in a representative Saudi Arabian population for high and low metrics of dental caries yields signatures of abundances and diversity.

Heritage-specific oral microbiota in Indigenous Australian dental calculus

Background and objectives

Aboriginal Australians and Torres Strait Islanders (hereafter respectfully referred to as Indigenous Australians) experience a high burden of chronic non-communicable diseases (NCDs). Increased NCD risk is linked to oral diseases mediated by the oral microbiota, a microbial community influenced by both vertical transmission and lifestyle factors. As an initial step towards understanding the oral microbiota as a factor in Indigenous health, we present the first investigation of oral microbiota in Indigenous Australian adults.

Methodology

Dental calculus samples from Indigenous Australians with periodontal disease (PD; n = 13) and non-Indigenous individuals both with (n = 19) and without PD (n = 20) were characterized using 16S ribosomal RNA gene amplicon sequencing. Alpha and beta diversity, differentially abundant microbial taxa and taxa unique to different participant groups were analysed using QIIME2.

Results

Samples from Indigenous Australians were more phylogenetically diverse (Kruskal–Wallis H = 19.86, P = 8.3 × 10−6), differed significantly in composition from non-Indigenous samples (PERMANOVA pseudo-F = 10.42, P = 0.001) and contained a relatively high proportion of unique taxa not previously reported in the human oral microbiota (e.g. Endomicrobia). These patterns were robust to stratification by PD status. Oral microbiota diversity and composition also differed between Indigenous individuals living in different geographic regions.

Conclusions and implications

Indigenous Australians may harbour unique oral microbiota shaped by their long relationships with Country (ancestral homelands). Our findings have implications for understanding the origins of oral and systemic NCDs and for the inclusion of Indigenous peoples in microbiota research, highlighting the microbiota as a novel field of enquiry to improve Indigenous health.

Predicting dental caries increment using salivary biomarkers in a remote Indigenous Australian child population

BACKGROUND

The burden of childhood dental caries amongst Indigenous Australians is higher than in other Australians. Because of differences in lifestyle and the evolutionary history of the oral microbiota, associated risk indicators may differ. Here, we evaluate associations between caries increment, salivary biomarkers and baseline caries among children aged 5-17 years residing in a remote rural Indigenous community.

METHODS

This study was part of a trial assessing cost-effectiveness of an intervention to prevent dental caries among children. Baseline epidemiology and application of topical caries-preventive measures was conducted in 2015, followed-up in 2016 and 2017. Children who did not consent or failed to attend the prevention visits but did attend for follow-up epidemiology constituted a natural comparison group for evaluating the intervention. Saliva flow, pH, buffering and bacterial loads were measured at all visits. Caries was scored by the International Caries Detection and Assessment system. Outcome was caries increment. Explanatory variables were sex, being in experimental or comparison group, baseline caries, saliva flowrate and buffering, pH, and salivary loads of mutans streptococci (MS), Lactobacilli (LB), and yeast. Chi Square tests compared caries incidence in relation to explanatory variables and Generalised Linear Models explored associations between explanatory and outcome variables.

RESULTS

Of 408 participants at baseline, only 208 presented at 2-year follow-up. Of caries-free children at baseline, significantly fewer had incipient (p = 0.01) and advanced (p = 0.04) caries after two years. Children in the experimental group experienced fewer tooth surfaces with advanced caries (p = 0.02) than comparison children. Having caries at baseline (p = 0.02) and low salivary flow-rates (p < 0.001) saw a significant increase in advanced caries after two years. Children with high salivary loads of MS (p = 0.03) and LB (p = 0.004) experienced more advanced carious surfaces. Multivariable analysis revealed 58% reduction (p = 0.001) in advanced caries among children with high salivary flow rates. Caries increment was 61% (p = 0.03) more for incipient and 121% (p = 0.007) more for advanced caries among children who harboured higher loads of MS.

CONCLUSION

As with other ethnicities, children with low salivary flow and those with high MS had higher incipient and advanced caries increments after two years. Such risk assessments facilitate targeted preventive interventions for such communities.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry (ANZCTR), No: ACTRN12615000693527: 3 July 2015.