Dataset Information

Relationship between dental and periodontal health status and the salivary microbiome: bacterial diversity, co-occurrence networks and predictive models.

ABSTRACT: The present study used 16S rRNA gene amplicon sequencing to assess the impact on salivary microbiome of different grades of dental and periodontal disease and the combination of both (hereinafter referred to as oral disease), in terms of bacterial diversity, co-occurrence network patterns and predictive models. Our scale of overall oral health was used to produce a convenience sample of 81 patients from 270 who were initially recruited. Saliva samples were collected from each participant. Sequencing was performed in Illumina MiSeq with 2?×?300 bp reads, while the raw reads were processed according to the Mothur pipeline. The statistical analysis of the 16S rDNA sequencing data at the species level was conducted using the phyloseq, DESeq2, Microbiome, SpiecEasi, igraph, MixOmics packages. The simultaneous presence of dental and periodontal pathology has a potentiating effect on the richness and diversity of the salivary microbiota. The structure of the bacterial community in oral health differs from that present in dental, periodontal or oral disease, especially in high grades. Supragingival dental parameters influence the microbiota's abundance more than subgingival periodontal parameters, with the former making a greater contribution to the impact that oral health has on the salivary microbiome. The possible keystone OTUs are different in the oral health and disease, and even these vary between dental and periodontal disease: half of them belongs to the core microbiome and are independent of the abundance parameters. The salivary microbiome, involving a considerable number of OTUs, shows an excellent discriminatory potential for distinguishing different grades of dental, periodontal or oral disease; considering the number of predictive OTUs, the best model is that which predicts the combined dental and periodontal status.

SUBMITTER: Relvas M

PROVIDER: S-EPMC7806737 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Relationship between dental and periodontal health status and the salivary microbiome: bacterial diversity, co-occurrence networks and predictive models.

Relvas M M Regueira-Iglesias A A Balsa-Castro C C Salazar F F Pacheco J J JJ Cabral C C Henriques C C Tomás I I

Scientific reports 20210113 1

The present study used 16S rRNA gene amplicon sequencing to assess the impact on salivary microbiome of different grades of dental and periodontal disease and the combination of both (hereinafter referred to as oral disease), in terms of bacterial diversity, co-occurrence network patterns and predictive models. Our scale of overall oral health was used to produce a convenience sample of 81 patients from 270 who were initially recruited. Saliva samples were collected from each participant. Sequen ...[more]

PMID: 33441710

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Project description:The healthy microbiota show remarkable variability within and among individuals. In addition to external exposures, ecological relationships (both oppositional and symbiotic) between microbial inhabitants are important contributors to this variation. It is thus of interest to assess what relationships might exist among microbes and determine their underlying reasons. The initial Human Microbiome Project (HMP) cohort, comprising 239 individuals and 18 different microbial habitats, provides an unprecedented resource to detect, catalog, and analyze such relationships. Here, we applied an ensemble method based on multiple similarity measures in combination with generalized boosted linear models (GBLMs) to taxonomic marker (16S rRNA gene) profiles of this cohort, resulting in a global network of 3,005 significant co-occurrence and co-exclusion relationships between 197 clades occurring throughout the human microbiome. This network revealed strong niche specialization, with most microbial associations occurring within body sites and a number of accompanying inter-body site relationships. Microbial communities within the oropharynx grouped into three distinct habitats, which themselves showed no direct influence on the composition of the gut microbiota. Conversely, niches such as the vagina demonstrated little to no decomposition into region-specific interactions. Diverse mechanisms underlay individual interactions, with some such as the co-exclusion of Porphyromonaceae family members and Streptococcus in the subgingival plaque supported by known biochemical dependencies. These differences varied among broad phylogenetic groups as well, with the Bacilli and Fusobacteria, for example, both enriched for exclusion of taxa from other clades. Comparing phylogenetic versus functional similarities among bacteria, we show that dominant commensal taxa (such as Prevotellaceae and Bacteroides in the gut) often compete, while potential pathogens (e.g. Treponema and Prevotella in the dental plaque) are more likely to co-occur in complementary niches. This approach thus serves to open new opportunities for future targeted mechanistic studies of the microbial ecology of the human microbiome.

Project description:Understanding of the oral microbiome in relation to periodontal disease in older adults is limited. The composition and diversity of the subgingival microflora and their oligotypes in health and levels of periodontal disease were investigated in this study on older postmenopausal women. The 16S rRNA gene was sequenced using the Illumina MiSeq platform in 1,206 women aged 53 to 81 y. Presence and severity of periodontal disease were defined by Centers for Disease Control and Prevention/American Academy of Periodontology criteria. Composition of the microbiome was determined by 16S rRNA amplicon sequencing and the abundance of taxa described by the centered log2-ratio (CLR) transformed operational taxonomic unit (OTU) values. Differences according to periodontal disease status were determined by analysis of variance with Bonferroni correction. Bacteria oligotypes associated with periodontal disease and health were determined by minimum entropy decomposition and their functions estimated in silico using PICRUSt. Prevalence of none/mild, moderate, and severe periodontal disease was 25.1%, 58.3%, and 16.6%, respectively. Alpha diversity of the microbiome differed significantly across the 3 periodontal disease categories. β-Diversity differed between no/mild and severe periodontal disease, although considerable overlap was noted. Of the 267 bacterial species identified at ≥0.02% abundance, 56 (20.9%) differed significantly in abundance according to periodontal disease status. Significant linear correlations for pocket depth and clinical attachment level with bacterial amounts were observed for several taxa. Of the taxa differing in abundance according to periodontal disease status, 53% had multiple oligotypes appearing to differ between none/mild and severe periodontal disease. Among older women, taxonomic differences in subgingival microbiome composition and diversity were observed in relation to clinical periodontal disease measures. Potential differences in bacterial subspecies (oligotypes) and their function were also identified in periodontal disease compared with health.

Project description:BackgroundPrevious studies reported varyingly positive, negative, or no relationships between caries and periodontitis. Therefore, the aim was to assess the potential co-occurrence of caries experience and periodontal inflammation on the same teeth.MethodsThis cross-sectional study used data from the Lithuanian National Oral Health Survey. The study included a stratified random sample of 1405 individuals aged 34-78, recruited from 5 Lithuanian cities and 10 peri-urban/rural areas (response rate 52%). Information about sociodemographic (age, sex, education, residence), behavioral (sugar-containing diet, tooth brushing frequency, use of interdental care products, last dental visit, smoking) and biological (systemic disease, use of medication and xerostomia) determinants was collected using the World Health Organization (WHO) Oral Health Questionnaire for Adults supplemented with additional questions. Clinical data were recorded using the WHO criteria and collected by one trained and calibrated examiner. Dental caries status was recorded as sound, decayed, missing, filled surfaces. Subsequently for the analyses, status was recorded at a tooth-level as decayed- and filled-teeth (DT and FT) including proximal, buccal, and oral surfaces. Two measures were used for periodontal status. The probing pocket depth (PPD) was measured at six sites and recorded at a tooth level into the absence of PPD or presence of PPD ≥ 4 mm. Bleeding on probing (BOP) was measured at the same six sites and was recorded as either present or absent at a tooth-level. Univariable and multivariable 2-level random intercept binary logistic regression analyses were utilized.ResultsPositive associations were found between DT and BOP (OR 1.42, 95% CI 1.20-1.67), FT and BOP (OR 2.07, 95% CI 1.82-2.23), DT and PPD (OR 1.38, 95% CI 1.15-1.67) and FT and PPD (OR 2.01, 95% CI 1.83-2.20).ConclusionsOur findings add evidence for the co-occurrence of periodontal inflammation and caries on the same teeth. This suggests the need for increased emphasis on a transdisciplinary approach in designing oral health interventions that target dental caries and periodontal disease simultaneously. In addition, longitudinal studies exploring the co-occurrence of caries and periodontal disease at the same sites, taking into consideration the levels of both conditions and genetic variation, are warranted.

Dataset Information

Relationship between dental and periodontal health status and the salivary microbiome: bacterial diversity, co-occurrence networks and predictive models.

Publications

Relationship between dental and periodontal health status and the salivary microbiome: bacterial diversity, co-occurrence networks and predictive models.

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