Meta-analysis of caries microbiome studies can improve upon disease prediction outcomes.

As one of the most prevalent infective diseases worldwide, it is crucial that we not only know the constituents of the oral microbiome in dental caries but also understand its functionality. Herein, we present a reproducible meta-analysis to effectively report the key components and the associated functional signature of the oral microbiome in dental caries. Publicly available sequencing data were downloaded from online repositories and subjected to a standardized analysis pipeline before analysis. Meta-analyses identified significant differences in alpha and beta diversities of carious microbiomes when compared to healthy ones. Additionally, machine learning and receiver operator characteristic analysis showed an ability to discriminate between healthy and disease microbiomes. We identified from importance values, as derived from random forest analyses, a group of genera, notably containing Selenomonas, Aggregatibacter, Actinomyces and Treponema, which can be predictive of dental caries. Finally, we propose the most appropriate study design for investigating the microbiome of dental caries by synthesizing the studies, which had the most accurate differentiation based on random forest modelling. In conclusion, we have developed a non-biased, reproducible pipeline, which can be applied to microbiome meta-analyses of multiple diseases, but importantly we have derived from our meta-analysis a key group of organisms that can be used to identify individuals at risk of developing dental caries based on oral microbiome inhabitants.

An In Vitro Evaluation of Denture Cleansing Regimens against a Polymicrobial Denture Biofilm Model.

Denture stomatitis (DS) is an inflammatory disease resulting from a polymicrobial biofilm perturbation at the denture surface-palatal mucosa interface. Recommendations made by dental health care professionals often lack clarity for appropriate denture cleaning. This study investigated the efficacy of brushing with off-the-shelf denture cleanser (DC) tablets (Poligrip®) vs. two toothpastes (Colgate® and Crest®) in alleviating the viable microorganisms (bacteria and fungi) in an in vitro denture biofilm model. Biofilms were grown on poly(methyl)methacrylate (PMMA) discs, then treated daily for 7 days with mechanical disruption (brushing), plus Poligrip® DC, Colgate® or Crest® toothpastes. Weekly treatment with Poligrip® DC on day 7 only was compared to daily modalities. All treatment parameters were processed to determine viable colony forming units for bacteria and fungi using the Miles and Misra technique, and imaged by confocal laser scanning microscopy (CLSM). Brushing with daily DC therapy was the most effective treatment in reducing the viable biofilm over 7 days of treatment. Brushing only was ineffective in controlling the viable bioburden, which was confirmed by CLSM imaging. This data indicates that regular cleansing of PMMA with DC was best for polymicrobial biofilms.