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Functional signatures of oral dysbiosis during periodontitis progression revealed by microbial metatranscriptome analysis.

ABSTRACT: Periodontitis is a polymicrobial biofilm-induced inflammatory disease that affects 743 million people worldwide. The current model to explain periodontitis progression proposes that changes in the relative abundance of members of the oral microbiome lead to dysbiosis in the host-microbiome crosstalk and then to inflammation and bone loss. Using combined metagenome/metatranscriptome analysis of the subgingival microbiome in progressing and non-progressing sites, we have characterized the distinct molecular signatures of periodontitis progression.Metatranscriptome analysis was conducted on samples from subgingival biofilms from progressing and stable sites from periodontitis patients. Community-wide expression profiles were obtained using Next Generation Sequencing (Illumina). Sequences were aligned using 'bowtie2' against a constructed oral microbiome database. Differential expression analysis was performed using the non-parametric algorithm implemented on the R package 'NOISeqBio'. We summarized global functional activities of the oral microbial community by set enrichment analysis based on the Gene Ontology (GO) orthology.Gene ontology enrichment analysis showed an over-representation in the baseline of active sites of terms related to cell motility, lipid A and peptidoglycan biosynthesis, and transport of iron, potassium, and amino acids. Periodontal pathogens (Tannerella forsythia and Porphyromonas gingivalis) upregulated different TonB-dependent receptors, peptidases, proteases, aerotolerance genes, iron transport genes, hemolysins, and CRISPR-associated genes. Surprisingly, organisms that have not been usually associated with the disease (Streptococcus oralis, Streptococcus mutans, Streptococcus intermedius, Streptococcus mitis, Veillonella parvula, and Pseudomonas fluorenscens) were highly active transcribing putative virulence factors. We detected patterns of activities associated with progression of clinical traits. Among those we found that the profiles of expression of cobalamin biosynthesis, proteolysis, and potassium transport were associated with the evolution towards disease.We identified metabolic changes in the microbial community associated with the initial stages of dysbiosis. Regardless of the overall composition of the community, certain metabolic signatures are consistent with disease progression. Our results suggest that the whole community, and not just a handful of oral pathogens, is responsible for an increase in virulence that leads to progression.NCT01489839, 6 December 2011.

SUBMITTER: Yost S

PROVIDER: S-EPMC4410737 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Functional signatures of oral dysbiosis during periodontitis progression revealed by microbial metatranscriptome analysis.

Yost Susan S Duran-Pinedo Ana E AE Teles Ricardo R Krishnan Keerthana K Frias-Lopez Jorge J

Genome medicine 20150427 1

<h4>Background</h4>Periodontitis is a polymicrobial biofilm-induced inflammatory disease that affects 743 million people worldwide. The current model to explain periodontitis progression proposes that changes in the relative abundance of members of the oral microbiome lead to dysbiosis in the host-microbiome crosstalk and then to inflammation and bone loss. Using combined metagenome/metatranscriptome analysis of the subgingival microbiome in progressing and non-progressing sites, we have charact ...[more]

PMID: 25918553

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Project description:BackgroundOral microbiota is closely related to the homeostasis of the oral cavity and lungs. To provide potential information for the prediction, screening, and treatment strategies of individuals, this study compared and investigated the bacterial signatures in periodontitis and chronic obstructive pulmonary disease (COPD).Materials and methodsWe collected subgingival plaque and gingival crevicular fluid samples from 112 individuals (31 healthy controls, 24 patients with periodontitis, 28 patients with COPD, and 29 patients with both periodontitis and COPD). The oral microbiota was analyzed using 16S rRNA gene sequencing and diversity and functional prediction analysis were performed.ResultsWe observed higher bacterial richness in individuals with periodontitis in both types of oral samples. Using LEfSe and DESeq2 analyses, we found differentially abundant genera that may be potential biomarkers for each group. Mogibacterium is the predominant genus in COPD. Ten genera, including Desulfovibrio, Filifactor, Fretibacterium, Moraxella, Odoribacter, Pseudoramibacter Pyramidobacter, Scardovia, Shuttleworthia and Treponema were predominant in periodontitis. Bergeyella, Lautropia, Rothia, Propionibacterium and Cardiobacterium were the signature of the healthy controls. The significantly different pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) between healthy controls and other groups were concentrated in genetic information processing, translation, replication and repair, and metabolism of cofactors and vitamins.ConclusionsWe found the significant differences in the bacterial community and functional characterization of oral microbiota in periodontitis, COPD and comorbid diseases. Compared to gingival crevicular fluid, subgingival plaque may be more appropriate for reflecting the difference of subgingival microbiota in periodontitis patients with COPD. These results may provide potentials for predicting, screening, and treatment strategies for individuals with periodontitis and COPD.

Project description:Periodontitis is driven by disproportionate host inflammatory immune responses induced by an imbalance in the composition of oral bacteria; this instigates microbial dysbiosis, along with failed resolution of the chronic destructive inflammation. The objectives of this study were to identify microbial signatures for health and chronic periodontitis at the genus level and to propose a model of dysbiosis, including the calculation of bacterial ratios. Published sequencing data obtained from several different studies (196 subgingival samples from patients with chronic periodontitis and 422 subgingival samples from healthy subjects) were pooled and subjected to a new microbiota analysis using the same Visualization and Analysis of Microbial Population Structures (VAMPS) pipeline, to identify microbiota specific to health and disease. Microbiota were visualized using CoNet and Cytoscape. Dysbiosis ratios, defined as the percentage of genera associated with disease relative to the percentage of genera associated with health, were calculated to distinguish disease from health. Correlations between the proposed dysbiosis ratio and the periodontal pocket depth were tested with a different set of data obtained from a recent study, to confirm the relevance of the ratio as a potential indicator of dysbiosis. Beta diversity showed significant clustering of periodontitis-associated microbiota, at the genus level, according to the clinical status and independent of the methods used. Specific genera (Veillonella, Neisseria, Rothia, Corynebacterium, and Actinomyces) were highly prevalent (>95%) in health, while other genera (Eubacterium, Campylobacter, Treponema, and Tannerella) were associated with chronic periodontitis. The calculation of dysbiosis ratios based on the relative abundance of the genera found in health versus periodontitis was tested. Nonperiodontitis samples were significantly identifiable by low ratios, compared to chronic periodontitis samples. When applied to a subgingival sample set with well-defined clinical data, the method showed a strong correlation between the dysbiosis ratio, as well as a simplified ratio (Porphyromonas, Treponema, and Tannerella to Rothia and Corynebacterium), and pocket depth. Microbial analysis of chronic periodontitis can be correlated with the pocket depth through specific signatures for microbial dysbiosis.IMPORTANCE Defining microbiota typical of oral health or chronic periodontitis is difficult. The evaluation of periodontal disease is currently based on probing of the periodontal pocket. However, the status of pockets "on the mend" or sulci at risk of periodontitis cannot be addressed solely through pocket depth measurements or current microbiological tests available for practitioners. Thus, a more specific microbiological measure of dysbiosis could help in future diagnoses of periodontitis. In this work, data from different studies were pooled, to improve the accuracy of the results. However, analysis of multiple species from different studies intensified the bacterial network and complicated the search for reproducible microbial signatures. Despite the use of different methods in each study, investigation of the microbiota at the genus level showed that some genera were prevalent (up to 95% of the samples) in health or disease, allowing the calculation of bacterial ratios (i.e., dysbiosis ratios). The correlation between the proposed ratios and the periodontal pocket depth was tested, which confirmed the link between dysbiosis ratios and the severity of the disease. The results of this work are promising, but longitudinal studies will be required to improve the ratios and to define the microbial signatures of the disease, which will allow monitoring of periodontal pocket recovery and, conceivably, determination of the potential risk of periodontitis among healthy patients.

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Functional signatures of oral dysbiosis during periodontitis progression revealed by microbial metatranscriptome analysis.

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Functional signatures of oral dysbiosis during periodontitis progression revealed by microbial metatranscriptome analysis.

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