English Individual Oral

[Elenor Waas]

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Background: There is a recognized need to deliver oral health information to people during clinical encounters to enable them to develop personal skills in managing their own oral health. Traditional approaches to individual oral health education have been shown to be largely ineffective and new approaches are required to address personal motivations for preventive behaviour. This systematic review aims to identify and assess the effectiveness of behaviour models as a basis for individual oral health promotion.

Methods: Electronic databases were searched for articles evaluating the effectiveness of health behaviour models in oral and general health between 2000 and 2007. Eighty-nine studies were retrieved and data were extracted from the 32 studies that met the inclusion criteria.

Results: Thirty-two studies were identified in the fields of clinical prevention and health education, motivational interviewing (MI), counselling, and models based interventions. MI interventions were found to be the most effective method for altering health behaviours in a clinical setting.

Conclusions: There is a need to develop an effective model for chairside oral health promotion that incorporates this evidence and allows oral health professionals to focus more on the underlying social determinants of oral disease during the clinical encounter. There is potential to further develop the MI approach within the oral health field.

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Different molecular techniques have been used to characterize the human oral microbiome, but the vast majority of studies are based on 16S ribosomal RNA sequencing12,13. Using mass spectrometry (MS)-based proteomics profiling as a tool for characterizing the oral microbiome is still unconventional. However, it has the potential to provide information about the functional and active microbiome through revealing the levels of individual proteins expressed by different organisms. Furthermore, metaproteomics can identify the proteins expressed by the host, and thus, elucidate possible interactions between the host and potential pathogenic species.

Based on an optimized sample preparation protocol for metaproteomics of ancient dental calculus and state-of-the-art mass spectrometry technology, we here analyze 22 dental calculus samples from 21 archeological individuals. To identify potential divergence from the medieval microbiome, modern samples of calculus and plaque are collected from seven healthy volunteers and analyzed with identical methodology. The overall aim of the presented study is to characterize the Danish medieval oral microbiome by proteomics, in order to learn more about the individualized oral health, and possibly diet, in this specific population, as well as to compare the results to modern healthy individuals.

We observe that the set of individuals we investigated can be divided in two groups: one health-predisposed and another more susceptible to oral disease. In both groups, the oral microbiome is more heterogeneous than in modern Danish individuals. We also use high pH reversed-phase fractionation in combination with TMT labelling. We show it greatly improves sensitivity for identifying more peptides in archeological samples, highlighting the potential of this strategy for future quantitative proteomics analyses of archeological remains.

The 22 samples come from a medieval parish cemetery located in Tjrby, Jutland, Denmark (Fig. 1). While there is evidence of a wooden church from around 1050 CE, all burials used in this study date from the establishment of a Romanesque stone church approximately a century later until its abandonment during the Reformation (ca. 1537 CE)14. The site represents an ordinary Danish medieval village, and thus the individuals should show a relative degree of uniformity in terms of lifeways and social status, allowing the recovery of proteomes that are fairly comparable.

This site was chosen because the material is well-curated and easily accessible, but also of interest because it is one of few Danish cemeteries from the medieval period that has been fully excavated. Tjrby, in its mundaneness, gives insight into the Danish medieval oral microbiomes of a relatively large number of average individuals. By studying individual oral microbiomes, future comparison with other assemblages, either contemporary or more ancient, should be more nuanced.

Individuals were considered the least periodontally healthy when more than half of the observations were assigned scores of 3, or any scores of 4 were present. Similarly, scores were given to individuals that had one or more gross caries (Supplementary Fig. 3), and when more than two teeth were lost antemortem. Widespread periodontium involvement, deep pocket formation, and gross carious lesions are all risk factors to the ultimate adverse outcome, the loss of the tooth or its functionality. The different scores and observations were evaluated and combined into a single score. Minor caries, limited antemortem tooth loss (AMTL), and some slight periodontal pocket formation, can be considered within the range of normal medieval health. The resulting Pathology Score (Supplementary Table 1) varies from one individual with three positive scores (unhealthiest) to five individuals with three negative scores, which can be considered the healthiest for this assemblage.

To identify similarities and differences between all samples, unsupervised hierarchical clustering of LFQ intensities was performed for all protein entries observed in at least half of the medieval samples (Fig. 2a). The clustering separates the modern samples from the archeological ones and the modern plaque from the modern calculus. Within the medieval samples, two main groups were defined by the cluster analysis, with 16 Tjrby samples falling into Group 1 (G1), and the rest (Tjrby 5, 6, 18, 21, 22, and 23) comprising Group 2 (G2). Subsequent bioinformatic analysis were performed based on these groups. One individual in G2, Tjrby 18, a particularly senescent individual removed from the bioarchaeological analysis (Supplementary Note 2), is also an outlier in terms of his bacterial and human proteome profiles (Figs. 2a and 6, see below).

The majority of the identified proteins were of bacterial origin, of which approximately 90% could be assigned to genus level. In order to assess the relative contribution of different bacterial genera to the total bacterial protein mass, the fractional bacterial genus distribution was calculated by summing all LFQ protein intensities mapped to the taxonomic rank of genus and dividing the result by the total summed protein intensity of all bacterial proteins within each sample (Supplementary Data 1). The top 20 genera found in the samples were visualized as differentially color-coded bar-graphs sorted by the most abundant genera in the medieval samples (Fig. 2b). From this plot, it is evident that the separation of the two groups of medieval individuals is related to the level of abundance of specific genera (Fig. 2b). Actinomyces spp., a prominent group of facultative anaerobic Gram-positive bacteria, is the predominant genus in all but one individual. After Actinomyces spp., the genera Olsenella and Fretibacterium, both of which have been implicated in periodontitis26, are the most abundant in G1. Conversely, G2 is characterized by the presence of oral commensals Lautropia mirabilis, Neisseria spp., Streptococcus spp., and Cardiobacterium spp. (Fig. 2b).

Bacterial genera differentially expressed between sample groups. The significantly differentially expressed bacterial genera between G1 (right) and G2 (left) are colored based on the coloring code from Fig. 2. Other interesting genera, not passing the significant threshold are named in the plot

Several virulence factors were identified from these species, and their level of expression are, almost without exception, higher in G1 and absent in modern plaque and calculus (Table 2). For example, the fimbrial proteins identified from the keystone pathogen P. gingivalis are critical mediators of initial adhesion and for the invasion of host cells31, and together with gingipains, they play several roles in pathogenicity. Several proteins from Methanobrevibacter oralis, an archaeal genus believed to be an important periodontal disease pathogen32,33, are also more abundant in G1 (Table 2). Although not specific to either group, Desulfomicrobium orale is an emerging pathogen of interest27,34. D. orale is absent in the modern samples and at very low abundance in three of the healthy archeological individuals (Supplementary Data 2). Lactobacillus spp., one of the major lactic acid fermenting bacterial genera, is also present with higher abundance in G1.

Both groups contain pathogenic genera and species involved in conditions of the periodontium, but G1 is defined by pathogenic species, whereas G2 is characterized by a number of commensal genera. When comparing the quantitative metaproteome profiles of the two groups with the bioarchaeological analysis, we found no association with biological age, chronological age, size of calculus samples, location of the calculus samples within the mouth or on the tooth, or presence of periapical lesions (Supplementary Fig. 4). Neither group can be said to be healthy based on the pathological scores (Supplementary Table 1), but the G2 group only has one individual with gross carious lesions compared to nearly half of the individuals in the G1 group. This suggests that the metaproteome profiles to some extent correlate with caries status.

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