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: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: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:Periodontitis is an extremely prevalent disease worldwide and is driven by complex dysbiotic microbiota. Here we analyzed the transcriptional activity of the periodontal pocket microbiota from all domains of life as well as the human host in health and chronic periodontitis. Bacteria showed strong enrichment of 18 KEGG functional modules in chronic periodontitis, including bacterial chemotaxis, flagellar assembly, type III secretion system, type III CRISPR-Cas system, and two component system proteins. Upregulation of these functions was driven by the red-complex pathogens and candidate pathogens, e.g. Filifactor alocis, Prevotella intermedia, Fretibacterium fastidiosum and Selenomonas sputigena. Nine virulence factors were strongly up-regulated, among them the arginine deiminase arcA from Porphyromonas gingivalis and Mycoplasma arginini. Viruses and archaea accounted for about 0.1% and 0.22% of total putative mRNA reads, respectively, and a protozoan, Entamoeba gingivalis, was highly enriched in periodontitis. Fourteen human transcripts were enriched in periodontitis, including a gene for a ferric iron binding protein, indicating competition with the microbiota for iron, and genes associated with cancer, namely nucleolar phosphoprotein B23, ankyrin-repeat domain 30B-like protein and beta-enolase. The data provide evidence on the level of gene expression in vivo for the potentially severe impact of the dysbiotic microbiota on human health.
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Project description:Several ecological hypotheses (e.g., specific plaque, non-specific plaque and keystone pathogen) regarding the etiology of periodontitis have been proposed since the 1990s, most of which have been centered on the concept of dysbiosis associated with periodontitis. Nevertheless, none of the existing hypotheses have presented mechanistic interpretations on how and why dysbiosis actually occurs. Hubbell's neutral theory of biodiversity offers a powerful null model to test hypothesis regarding the mechanism of community assembly and diversity maintenance from the metagenomic sequencing data, which can help to understand the forces that shape the community dynamics such as dysbiosis. Here we reanalyze the dataset from Abusleme et al.'s comparative study of the oral microbial communities from periodontitis patients and healthy individuals. Our study demonstrates that 14 out of 61 communities (23%) passed the neutrality test, a percentage significantly higher than the previous reported neutrality rate of 1% in human microbiome (Li & Ma 2016, Scientific Reports). This suggests that, while the niche selection may play a predominant role in the assembly and diversity maintenance in oral microbiome, the effect of neutral dynamics may not be ignored. However, no statistically significant differences in the neutrality passing rates were detected between the periodontitis and healthy treatments with Fisher's exact probability test and multiple testing corrections, suggesting that the mechanism of community assembly is robust against disturbances such as periodontitis. In addition, our study confirmed previous finding that periodontitis patients exhibited higher biodiversity. These findings suggest that while periodontitis may significantly change the community composition measured by diversity (i.e., the exhibition or 'phenotype' of community assembly), it does not seem to cause the 'mutation' of the 'genotype" (mechanism) of community assembly. We argue that the 'phenotypic' changes explain the observed link (not necessarily causal) between periodontitis and community dysbiosis, which is certainly worthy of further investigation.
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Project description:Intestinal inflammation is frequently associated with an alteration of the gut microbiota, termed dysbiosis, which is characterized by a reduced abundance of obligate anaerobic bacteria and an expansion of facultative Proteobacteria such as commensal E. coli. The mechanisms enabling the outgrowth of Proteobacteria during inflammation are incompletely understood. Metagenomic sequencing revealed bacterial formate oxidation and aerobic respiration to be overrepresented metabolic pathways in a chemically induced murine model of colitis. Dysbiosis was accompanied by increased formate levels in the gut lumen. Formate was of microbial origin since no formate was detected in germ-free mice. Complementary studies using commensal E. coli strains as model organisms indicated that formate dehydrogenase and terminal oxidase genes provided a fitness advantage in murine models of colitis. In vivo, formate served as electron donor in conjunction with oxygen as the terminal electron acceptor. This work identifies bacterial formate oxidation and oxygen respiration as metabolic signatures for inflammation-associated dysbiosis.
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Project description:Inflammation is a driven force in modulating microbial communities, but little is known about the interplay between colonizing microorganisms and the immune response in periodontitis. Since local and systemic inflammation may play a whole role in disease, we aimed to evaluate the oral and fecal microbiome of patients with periodontitis and to correlate the oral microbiome data with levels of inflammatory mediator in saliva. Methods: Nine patients with periodontitis (P) in Stage 3/Grade B and nine age-matched non-affected controls (H) were evaluated. Microbial communities of oral biofilms (the supra and subgingival from affected and non-affected sites) and feces were determined by sequencing analysis of the 16SrRNA V3-V4 region. Salivary levels of 40 chemokines and cytokines were correlated with oral microbiome data. Results: Supragingival microbial communities of P differed from H (Pielou's evenness index, and Beta diversity, and weighted UniFrac), since relative abundance (RA) of Defluviitaleaceae, Desulfobulbaceae, Mycoplasmataceae, Peptostreococcales-Tissierellales, and Campylobacteraceae was higher in P, whereas Muribaculaceae and Streptococcaceae were more abundant in H. Subgingival non-affected sites of P did not differ from H, except for a lower abundance of Gemellaceae. The microbiome of affected periodontitis sites (PD ≥ 4 mm) clustered apart from the subgingival sites of H. Oral pathobionts was more abundant in sub and supragingival biofilms of P than H. Fecal samples of P were enriched with Acidaminococcus, Clostridium, Lactobacillus, Bifidobacterium, Megasphaera, and Romboutsia when compared to H. The salivary levels of interleukin 6 (IL-6) and inflammatory chemokines were positively correlated with the RA of several recognized and putative pathobionts, whereas the RA of beneficial species, such as Rothia aeria and Haemophilus parainfluenzae was negatively correlated with the levels of Chemokine C-C motif Ligand 2 (CCL2), which is considered protective. Dysbiosis in patients with periodontitis was not restricted to periodontal pockets but was also seen in the supragingival and subgingival non-affected sites and feces. Subgingival dysbiosis revealed microbial signatures characteristic of different immune profiles, suggesting a role for candidate pathogens and beneficial organisms in the inflammatory process of periodontitis.
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Project description:Failure to attenuate inflammation coupled with consequent microbiota changes drives the development of bone-destructive periodontitis. Quercetin, a plant-derived polyphenolic flavonoid, has been linked with health benefits in both humans and animals. Using a systematic approach, we investigated the effect of orally delivered Quercetin on host inflammatory response, oral microbial composition and periodontal disease phenotype. In vivo, quercetin supplementation diminished gingival cytokine expression, inflammatory cell infiltrate and alveolar bone loss. Microbiome analyses revealed a healthier oral microbial composition in Quercetin-treated versus vehicle-treated group characterized by reduction in the number of pathogenic species including Enterococcus, Neisseria and Pseudomonas and increase in the number of non-pathogenic Streptococcus sp. and bacterial diversity. In vitro, Quercetin diminished inflammatory cytokine production through modulating NF-κB:A20 axis in human macrophages following challenge with oral bacteria and TLR agonists. Collectively, our findings reveal that Quercetin supplement instigates a balanced periodontal tissue homeostasis through limiting inflammation and fostering an oral cavity microenvironment conducive of symbiotic microbiota associated with health. This proof of concept study provides key evidence for translational studies to improve overall health.
| S-EPMC8663773 | biostudies-literature
Project description:Periodontitis is a chronic and multifactorial inflammatory disease that can lead to tooth loss. At present, the diagnosis for periodontitis is primarily based on clinical examination and radiographic parameters. Detecting the periodontal pathogens at the subgingival plaque requires skilled professionals to collect samples. Periodontal pathogens are also detected on various mucous membranes in patients with periodontitis. In this study, we characterized the oral microbiome profiles from buccal mucosa and supragingival space in a total of 272 healthy subjects as a control group, and periodontitis patients as a disease group. We identified 13 phyla, 193 genera, and 527 species and determined periodontitis-associated taxa. Porphyromonasgingivalis, Tannerellaforsythia, Treponemadenticolar, Filifactoralocis, Porphyromonasendodontalis, Fretibacteriumfastiosum and Peptostreptococcus species were significantly increased in both the buccal mucosa and the supragingival space in periodontitis patients. The identified eight periodontitis-associated bacterial species were clinically validated in an independent cohort. We generated the prediction model based on the oral microbiome profiles using five machine learning algorithms, and validated its capability in predicting the status of patients with periodontitis. The results showed that the oral microbiome profiles from buccal mucosa and supragingival space can represent the microbial composition of subgingival plaque and further be utilized to identify potential microbial biomarkers for the diagnosis of periodontitis. Besides, bacterial community interaction network analysis found distinct patterns associated with dysbiosis in periodontitis. In summary, we have identified oral bacterial species from buccal and supragingival sites which can predict subgingival bacterial composition and can be used for early diagnosis of periodontitis. Therefore, our study provides an important basis for developing easy and noninvasive methods to diagnose and monitor periodontitis.
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