Datasets used to discover the microbial signatures of oral dysbiosis, periodontitis and edentulism in humans.
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ABSTRACT:
SUBMITTER: Colby Hunter M
PROVIDER: S-EPMC5137327 | biostudies-literature | 2017 Feb
REPOSITORIES: biostudies-literature
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Datasets used to discover the microbial signatures of oral dysbiosis, periodontitis and edentulism in humans.
Colby Hunter M M Pozhitkov Alex E AE Noble Peter A PA
Data in brief 20161119
This article provides supporting data for the research article 'Microbial Signatures of Oral Dysbiosis, Periodontitis and Edentulism Revealed by Gene Meter Methodology' (M.C. Hunter, A.E. Pozhitkov, P.A. Noble, 2016) [1]. In that article, we determined the microbial abundance signatures for patient with periodontics, edentulism, or health using Gene Meter Technology. Here we provide the data used to make the DNA microarray and the resulting microbial abundance data that was determined using the ...[more]
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Project description: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.
| S-EPMC4410737 | biostudies-literature
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.
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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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Project description:ObjectivesWe have previously characterized the main osteoimmunological events that occur during ligature periodontitis. This study aims to determine the polymicrobial community shifts that occur during disease development.MethodsPeriodontitis was induced in C57BL/6 mice using the ligature-induced periodontitis model. Healthy oral mucosa swabs and ligatures were collected every 3 days from 0 to 18 days post-ligature placement. Biofilm samples were evaluated by 16SrRNA gene sequencing (Illumina MiSeq) and QIIME. Time-course changes were determined by relative abundance, diversity, and rank analyses (PERMANOVA, Bonferroni-adjusted).ResultsMicrobial differences between health and periodontal inflammation were observed at all phylogenic levels. An evident microbial community shift occurred in 25 genera during the advancement of "gingivitis" (3-6 days) to periodontitis (9-18 days). From day 0 to 18, dramatic changes were identified in Streptococcus levels, with an overall decrease (54.04%-0.02%) as well an overall increase of Enterococcus and Lactobacillus (23.7%-73.1% and 10.1%-70.2%, respectively). Alpha-diversity decreased to its lowest at 3 days, followed by an increase in diversity as disease advancement. Beta-diversity increased after ligature placement, indicating that bone loss develops in response to a greater microbial variability (p = 0.001). Levels of facultative and strict anaerobic bacteria augmented over the course of disease progression, with a total of eight species significantly different during the 18-day period.ConclusionThe data supports that murine gingival inflammation and alveolar bone loss develop in response to microbiome shifts. Bacterial diversity increased during progression to bone loss. These findings further support the utilization of the periodontitis ligature model for microbial shift analysis under different experimental conditions.
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Project description:An emerging concept is the tight relationship between dysbiosis (microbiota imbalance) and disease. The increase in knowledge about alterations in microbial communities that reside within the host has made a strong impact not only on dental science, but also on immunology and microbiology as well as on our understanding of several diseases. Periodontitis is a well-characterized human disease associated with dysbiosis, characterized by the accumulation of multiple bacteria that play individual and critical roles in bone loss around the teeth. Dysbiosis is largely dependent on cooperative and competitive interactions among oral microbes during the formation of the pathogenic biofilm community at gingival sites. Oral pathobionts play different and synergistic roles in periodontitis development, depending on their host-damaging and immunostimulatory activities. Host immune responses to oral pathobionts act as a double-edged sword not only by protecting the host against pathobionts, but also by promoting alveolar bone loss. Recent studies have begun to elucidate the roles of individual oral bacteria, including a new type of pathobionts that possess strong immunostimulatory activity, which is critical for alveolar bone loss. Better understanding of the roles of oral pathobionts is expected to lead to a better understanding of periodontitis disease and to the development of novel preventive and therapeutic approaches for the disease.
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Project description:BackgroundTo examine the microbial profiles in parenchyma tissues in bladder cancer.MethodsTissue samples of cancerous bladder mucosa were collected from patients diagnosed with bladder cancer (22 carcinoma tissues and 12 adjacent normal tissues). The V3-V4 region of the bacterial 16S rRNA gene was PCR amplified, followed by sequencing on an Illumina MiSeq platform. Bioinformatics analysis for microbial classification and functional assessment was performed to assess bladder microbiome diversity and variations.ResultsThe predominant phylum in both tissues was Proteobacteria. The cancerous tissues exhibited lower species richness and diversity. Beta diversity significantly differed between the cancerous and normal tissues. Lower relative abundances of the microbial genera Lactobacillus, Prevotella_9, as well as Ruminococcaceae were observed, whereas those of Cupriavidus spp., an unknown genus of family Brucellaceae, and Acinetobacter, Anoxybacillus, Escherichia-Shigella, Geobacillus, Pelomonas, Ralstonia, and Sphingomonas were higher in the cancerous tissues. These findings indicate that these genera may be potentially utilized as biomarkers for bladder cancer. PICRUSt analysis revealed that several pathways involved in the metabolism of harmful chemical compounds were enriched in the cancer tissues, thereby providing evidence that environmental factors are strongly associated with bladder cancer etiology.ConclusionThis is the first study that has described and analyzed the dysbiotic motifs of urinary microbiota in the parenchymatous tissues of bladder cancer via 16S rRNA gene sequencing. Our results suggest that changes in the bladder microbiome may serve as biomarkers for bladder cancer, possibly assisting in disease screening and monitoring.
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Project description:Candida albicans has been detected in root carious lesions. The current study aimed to explore the action of this fungal species on the microbial ecology and the pathogenesis of root caries. Here, by analyzing C. albicans in supragingival dental plaque collected from root carious lesions and sound root surfaces of root-caries subjects as well as caries-free individuals, we observed significantly increased colonization of C. albicans in root carious lesions. Further in vitro and animal studies showed that C. albicans colonization increased the cariogenicity of oral biofilm by altering its microbial ecology, leading to a polymicrobial biofilm with enhanced acidogenicity, and consequently exacerbated tooth demineralization and carious lesion severity. More importantly, we demonstrated that the cariogenicity-promoting activity of C. albicans was dependent on PHR2. Deletion of PHR2 restored microbial equilibrium and led to a less cariogenic biofilm as demonstrated by in vitro artificial caries model or in vivo root-caries rat model. Our data indicate the critical role of C. albicans infection in the occurrence of root caries. PHR2 is the major factor that determines the ecological impact and caries-promoting activity of C. albicans in a mixed microbial consortium.
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