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.
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.
Project description:Saliva (oral fluids) is an emerging biofluid poised for clinical diseases detection. Although the rationale for oral diseases applications (e.g. oral cancer) is clear, the rationale and relationship between systemic diseases and saliva biomarkers are unknown. In this study, we used mouse models of melanoma and non-small cell lung cancer and compared the transcriptome biomarker profiles of tumor-bearing mice to those of control mice. Microarray analysis showed that salivary transcriptomes were significantly altered in tumor-bearing mice vs. controls. Analysis of the transcriptomes in the mouse tumors, serum, salivary glands and saliva revealed that salivary biomarkers have multiple origins. Furthermore, we identified that the expression of two groups of significantly altered transcription factors Runx1, Mlxipl, Trim30 and Egr1, Tbx1, Nr1d1 in melanoma-bearing mice that can potentially be responsible for 82.6% of the up-regulated genes expression and 62.5% of the down-regulated gene expression in the mice saliva, respectively. We also confirmed that the ectopic production of nerve growth factor (NGF) in the melanoma tumor tissue as a tumor-released mediator that can induce expression of the transcription factor Egr-1 in the salivary gland. Taken together, our data support the conclusion that upon systemic disease development, a disease-specific change occurs in the salivary biomarker profile. Although the origins of the disease-specific salivary biomarkers are both systemic and local, stimulation of salivary gland by mediators released from remote tumors play an important role in regulating the salivary surrogate biomarker profiles.
Project description:Purpose:The aims of this study were to examine the salivary microbiota in conditions of periodontal health and disease and to explore microbial changes following nonsurgical periodontal treatment. Methods:Non-stimulated saliva samples were collected from 4 periodontally healthy participants at baseline and from 8 patients with chronic periodontitis at baseline and 3 months following nonsurgical periodontal therapy. The V3 and V4 regions of the 16S rRNA gene from the DNA of saliva samples were amplified and sequenced. The salivary microbial compositions of the healthy participants and patients with periodontitis prior to and following nonsurgical treatment of periodontitis were compared based on the relative abundance of various taxa. Results:On average, 299 operational taxonomic units were identified in each sample. The phylogenetic diversity in patients with periodontitis was higher than that in healthy participants and decreased following treatment. The abundance of the phylum Spirochaetes and the genus Treponema in patients with periodontitis was 143- and 134-fold higher than in the healthy control group, respectively, but decreased significantly following treatment. The species that were overabundant in the saliva of patients with periodontitis included the Peptostreptococcus stomatis group, Porphyromonas gingivalis, the Fusobacterium nucleatum group, Parvimonas micra, Porphyromonas endodontalis, Filifactor alocis, and Tannerella forsythia. The phylum Actinobacteria, the genus Streptococcaceae_uc, and the species Streptococcus salivarius group were more abundant in healthy participants than in those with periodontitis. There was a trend toward a decrease in disease-associated taxa and an increase in health-associated taxa following treatment. Conclusions:Our results revealed differences in the taxa of salivary microbiota between conditions of periodontal health and disease. The taxa found to be associated with health or disease have potential for use as salivary biomarkers for periodontal health or disease.
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.
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).
Project description:Periodontal disease (PD) is characterized by inflammation affecting the tissue surrounding the teeth, primarily affecting the soft tissues, like the gingiva. However, without proper treatment, the condition exacerbates and progresses to impact the deeper structures, as the alveolar bone. The periodontal inflammation leads to the alveolar bone resorption, that eventually results in the complete loss of tooth support. Given its potential consequences, periodontal disease is a significant public health concern, as one of the primary causes of tooth loss, contributing to issues such as impaired mastication, speech difficulties, low self-esteem, and quality of life. Notably, comorbidities, like hypertension, can exacerbate the progression and severity of periodontal disease. In addition, the coexistence of periodontal disease and hypertension is highly likely to occur due to sharing of several risk factors. A better understanding of the underling molecular mechanisms associated to the severity of periodontal disease in the context of hypertension would greatly contribute to the advancement of translational research in the field of periodontics. MicroRNAs, a class of small non-coding RNA molecules, have an important role in regulating gene expression at the post-transcriptional level. These molecules can regulate multiple mRNA targets through complementary base pairing between the miRNA 5' seed sequence and the mRNA 3' untranslated region (UTR). Therefore, microRNAs can potentially modulate a wide variety of cellular processes, in both normal and pathological contexts. Presently, most of the studies in the field concentrate on the periodontium soft tissues, while our understanding of microRNA modulation in the alveolar bone remains comparatively limited. We used microarray analysis to evaluate the expression profiles of microRNAs in the mandibles of Wistar and SHR rats with periodontal disease, compared to their respective control groups. Our aim was to identify microRNAs of interest that could possibly be associated to the periodontal disease-induced alveolar bone loss.