Salivary microbiota in periodontal diseases
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB79725 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Salivary microbiota in periodontal diseases
| PRJEB61123 | ENA
Project description:The effect of oral microbiota on the intestinal microbiota has garnered growing attention as a mechanism linking periodontal diseases to systemic diseases. However, the salivary microbiota is diverse and comprises numerous bacteria with a largely similar composition in healthy individuals and periodontitis patients. Thus, the systemic effects of small differences in the oral microbiota are unclear. In this study, we explored how health-associated and periodontitis-associated salivary microbiota differently colonized the intestine and their subsequent systemic effects by analyzing the hepatic gene expression and serum metabolomic profiles. The salivary microbiota was collected from a healthy individual and a periodontitis patient and gavaged into C57BL/6NJcl[GF] mice. Samples were collected five weeks after administration. Gut microbial communities were analyzed by 16S ribosomal RNA gene sequencing. Hepatic gene expression profiles were analyzed using a DNA microarray and quantitative polymerase chain reaction. Serum metabolites were analyzed by capillary electrophoresis time-of-flight mass spectrometry. The gut microbial composition at the genus level was significantly different between periodontitis-associated microbiota-administered (PAO) and health-associated oral microbiota-administered (HAO) mice. The hepatic gene expression profile demonstrated a distinct pattern between the two groups, with higher expression of Neat1, Mt1, Mt2, and Spindlin1, which are involved in lipid and glucose metabolism. Disease-associated metabolites such as 2-hydroxyisobutyric acid and hydroxybenzoic acid were elevated in PAO mice. These metabolites were significantly correlated with Bifidobacterium, Atomobium, Campylobacter, and Haemophilus, which are characteristic taxa in PAO mice. Conversely, health-associated oral microbiota were associated with higher levels of beneficial serum metabolites in HAO mice. The multi-omics approach used in this study revealed that periodontitis-associated oral microbiota is associated with the induction of disease phenotype when they colonized the gut of germ-free mice.
2022-08-17 | GSE198570 | GEO
Project description:Salivary Shotgun Metagenome for Autoimmune Diseases
| PRJEB9340 | ENA
Project description:Characterization of Diseases with Salivary Gland Involvement
| PRJNA547657 | ENA
Project description:Characterization of Diseases with Salivary Gland Involvement
| PRJNA547658 | ENA
Project description:Onset of chronic periodontitis is associated with an aberrant polymicrobial community, termed dysbiosis. Findings of a recent model of its etiology suggested that dysbiosis holds a conserved metabolic signature as an emergent property. The purpose of this study was to identify robust biomarkers for periodontal inflammation severity. Furthermore, we investigated disease-associated metabolic signatures of periodontal microbiota using a salivary metabolomics approach. Collection of whole saliva samples was performed before and after removal of supragingival plaque (debridement). Periodontal inflamed surface area (PISA) was employed as an indicator of periodontal inflammatory status. Based on multivariate analyses using pre-debridement salivary metabolomics data, we found that the metabolites associated with higher PISA included cadaverine and hydrocinnamate, while uric acid and ethanolamine were associated with lower PISA. Next, we focused on dental plaque metabolic byproducts by selecting significantly decreased salivary metabolites following debridement. Metabolite set enrichment analysis revealed that polyamine metabolism, arginine and proline metabolism, butyric acid metabolism, and lysine degradation were distinctive metabolic signatures of dental plaque in the high PISA group, which may have relevance to the metabolic signatures of disease-associated communities. Collectively, our findings identified potential biomarkers of periodontal inflammatory status, while they also provide insight into metabolic signatures of dysbiotic communities.
2016-10-23 | ST000496 | MetabolomicsWorkbench
Project description:Periodontitis can impair the osteogenic differentiation of human periodontal mesenchymal stem cells, but the underlying molecular mechanisms are still poorly understood. Long noncoding RNAs (lncRNAs) have been demonstrated to play significant roles under both physiologic and pathological conditions. We performed comprehensive lncRNAs profiling by lncRNA microarray to identify differentially expressed long noncoding RNA expression between Periodontal ligament stem cells from healthy Periodontal tissue and periodontal ligament stem cells from inflammatory periodontal tissue. Our analysis identified 233 lncRNAs and 423 mRNAs that were differently expressed (fold change >2.0, p-value < 0.05) between the two groups of cells. The GO analysis revealed that the significantly down-regulated biological processes included multicellular organismal process, developmental process and multicellular organismal development and the significantly up-regulated biological processes included cellular process, biological regulation and response to stimulus in periodontal ligament stem cells from inflammatory periodontal tissue. The Pathway analysis revealed that the differentially expressed mRNAs may involved in Focal adhesion, ECM-receptor interaction, Bacterial invasion of epithelial cells, Long-term depression, Circadian entrainment and HIF-1 signaling pathway.
2016-02-19 | GSE78074 | GEO
Project description:Periodontitis can impair the osteogenic differentiation of human periodontal mesenchymal stem cells, but the underlying molecular mechanisms are still poorly understood. Long noncoding RNAs (lncRNAs) have been demonstrated to play significant roles under both physiologic and pathological conditions. We performed comprehensive lncRNAs profiling by lncRNA microarray to identify differentially expressed long noncoding RNA expression between Periodontal ligament stem cells from healthy Periodontal tissue and periodontal ligament stem cells from inflammatory periodontal tissue. Our analysis identified 233 lncRNAs and 423 mRNAs that were differently expressed (fold change >2.0, p-value < 0.05) between the two groups of cells. The GO analysis revealed that the significantly down-regulated biological processes included multicellular organismal process, developmental process and multicellular organismal development and the significantly up-regulated biological processes included cellular process, biological regulation and response to stimulus in periodontal ligament stem cells from inflammatory periodontal tissue. The Pathway analysis revealed that the differentially expressed mRNAs may involved in Focal adhesion, ECM-receptor interaction, Bacterial invasion of epithelial cells, Long-term depression, Circadian entrainment and HIF-1 signaling pathway. Two-condition experiment, periodontal ligament stem cells from healthy periodontal tissue (hPDLSCs) vs. periodontal ligament stem cells from inflammatory periodontal tissue (pPDLSCs), Biological replicates: 3 control replicates (hPDLSCs), 3 testing replicates (pPDLSCs).
2016-02-19 | E-GEOD-78074 | biostudies-arrayexpress
Project description:Periodontal disease associated microbiota before and after antimicrobial therapy Metagenome
| PRJNA892459 | ENA
Project description:We report the application of high throughput Illumina sequencing for profiling of small RNAs in saliva of patients who were diagnosed with chronic periodontitis as compared to healthy controls. To date, there is no published literature on salivary microRNA profiling done using the high throughput next-generation sequencing analysis in patients diagnosed with chronic periodontitis. Also, this is the first study of its kind done in an Indian population. The objectives of the study were to profile microRNAs expressed in saliva of patients diagnosed with chronic periodontitis, to identify differentially expressed microRNAs between chronic periodontitis and healthy patients and to identify putative salivary microRNAs which can serve as biomarkers for periodontal disease.
2018-10-30 | GSE121910 | GEO