Dataset Information

Multi-omic analysis reveals bacteria may have a role in dental erosion

ABSTRACT: NMR was performed on 11 saliva samples; 5 from participants classified as having dental erosion and 6 from healthy control participants with no dental erosion to assess the differences in metabolome between the two groups. NMR analysis alone revealed no significant differences between the dental erosion and healthy controls. However, bacterial mRNA sequencing of the oral microbiome from the same saliva samples was performed and the bacterial gene expression profiles was correlated to metabolite concentrations in the groups. The dental erosion group had strong correlations between metabolites associated with protein degradation and amino acid fermentation (formate, butyrate, propionate, 5-aminopentanoate, acetate, glycine, phenylalanine, dimethyl sulfone) and increased activity of species including 4 Prevotella species, Actinomyces graevenitzii, Tannerella species, and 2 Selenomas species, to name a few. Whereas in the healthy control group, the only positive correlations between metabolite concentrations and bacterial activity was for urea and 5-aminopentanoate; urea was positively correlated with Aggregatibacter actinomycetecomytans, Lysinibacillus fusiformis, and Veillonella tobetsuensis, and 5-aminopentanoate was positively correlated with 3 different Leptotrichia species, Streptococcus parasanguinis, and 2 Prevotella species.

ORGANISM(S): Human Homo Sapiens

TISSUE(S): Saliva

DISEASE(S): Dental Erosion

SUBMITTER: Leanne Cleaver

PROVIDER: ST002265 | MetabolomicsWorkbench | Tue Aug 02 00:00:00 BST 2022

REPOSITORIES: MetabolomicsWorkbench

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	mwtab	Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:It has been suggested that the etiology of respiratory allergies (RA) can be partly explained by DNA methylation changes caused by adverse environmental and lifestyle factors experienced early in life. Longitudinal, prospective studies can aid in the unravelment of the epigenetic mechanisms involved in the disease development. High compliance rates can be expected in these studies when data is collected using non-invasive and convenient procedures. Saliva is an attractive biofluid to analyze changes in DNA methylation patterns. We investigated in a pilot study the differential methylation in saliva of RA (n=5) compared to healthy controls (n=5) using the Illumina Methylation 450K BeadChip platform. We evaluated the results against the results obtained in mononuclear blood cells from the same individuals. Differences in methylation patterns from saliva and mononuclear blood cells were clearly distinguishable (PAdj<0.001 and |Δβ|>0.2), though the methylation status of about 96% of the cg-sites was comparable between peripheral blood mononuclear cells and saliva. When comparing RA cases with healthy controls, the number of differentially methylated sites (DMS) in saliva and blood were 485 and 437, respectively, of which 216 were in common. The methylation levels of these sites were significantly correlated between blood and saliva. Pyrosequencing analysis of 3 selected DMS in the PM20D1, STK32C, and FGFR2 genes, confirmed the absolute levels of methylation as well as the differences between cases and controls as observed from the array data. Our findings show that saliva can be used for genome-wide methylation analysis and that it is possible to identify DMS to distinguish RA cases from healthy controls. The results were replicated in blood cells of the same individuals and confirmed by selected pyrosequencing analysis. This study provides a proof-of-concept that the analysis of DNA methylation profiles in saliva may offer distinct opportunities for molecular epidemiology studies of RA.

Project description:It has been suggested that the etiology of respiratory allergies (RA) can be partly explained by DNA methylation changes caused by adverse environmental and lifestyle factors experienced early in life. Longitudinal, prospective studies can aid in the unravelment of the epigenetic mechanisms involved in the disease development. High compliance rates can be expected in these studies when data is collected using non-invasive and convenient procedures. Saliva is an attractive biofluid to analyze changes in DNA methylation patterns. We investigated in a pilot study the differential methylation in saliva of RA (n=5) compared to healthy controls (n=5) using the Illumina Methylation 450K BeadChip platform. We evaluated the results against the results obtained in mononuclear blood cells from the same individuals. Differences in methylation patterns from saliva and mononuclear blood cells were clearly distinguishable (PAdj<0.001 and |ÎÎ²|>0.2), though the methylation status of about 96% of the cg-sites was comparable between peripheral blood mononuclear cells and saliva. When comparing RA cases with healthy controls, the number of differentially methylated sites (DMS) in saliva and blood were 485 and 437, respectively, of which 216 were in common. The methylation levels of these sites were significantly correlated between blood and saliva. Pyrosequencing analysis of 3 selected DMS in the PM20D1, STK32C, and FGFR2 genes, confirmed the absolute levels of methylation as well as the differences between cases and controls as observed from the array data. Our findings show that saliva can be used for genome-wide methylation analysis and that it is possible to identify DMS to distinguish RA cases from healthy controls. The results were replicated in blood cells of the same individuals and confirmed by selected pyrosequencing analysis. This study provides a proof-of-concept that the analysis of DNA methylation profiles in saliva may offer distinct opportunities for molecular epidemiology studies of RA. Bisulphite converted DNA from the 10 samples were hybridised to the Illumina Infinium 450k Human Methylation Beadchip

Project description:Neuroepigenetics considers genetic sequences and the interplay with environmental influences to elucidate vulnerability risk for various neurological and psychiatric disorders. However, evaluating DNA methylation of brain tissue is challenging owing to the issue of tissue specificity. Consequently, peripheral surrogate tissues were used, resulting in limited progress compared with other epigenetic studies, such as cancer research. Therefore, we developed databases to establish correlations between the brain and peripheral tissues in the same individuals. Four tissues, resected brain tissue, blood, saliva, and buccal mucosa (buccal), were collected from 19 patients (aged 13–73 years) who underwent neurosurgery. Moreover, their genome-wide DNA methylation was assessed using the Infinium HumanMethylationEPIC BeadChip arrays to determine the cross-tissue correlation of each combination. These correlation analyses were conducted with all methylation sites and with variable CpGs, and with when these were adjusted for cellular proportions. For the averaged data for each CpG across individuals, the saliva–brain correlation (r = 0.90) was higher than that for blood–brain (r = 0.87) and buccal–brain (r = 0.88) comparisons. Among individual CpGs, blood had the highest proportion of CpGs correlated to the brain at nominally significant levels (19.0%), followed by saliva (14.4%) and buccal (9.8%). These results were similar to the previous IMAGE-CpG results; however, the correlation analysis between the correlation coefficients of the datasets revealed a relatively low degree of correlation (brain vs. blood: r = 0.27, saliva; r = 0.18, and buccal; r = 0.24). To the best of our knowledge, this is the fourth study in the literature initiating the development of databases for correlations between the brain and peripheral tissues in the same individuals. We present the first database developed from an Asian population, specifically Japanese samples (AMAZE-CpG), which would contribute to interpreting individual epigenetic study results from various Asian populations.

Project description:Background and aims. The etiopathology of inflammatory bowel diseases is still poorly understood. To date, only few little data are available on the microbiota composition in ulcerative colitis (UC), representing a major subform of inflammatory bowel diseases. Currently, one of the main challenges is to unravel the interactions between genetics and environmental factors in the onset or during the progression and maintenance of the disease. The aim of the present study was to analyse twin pairs discordant for UC for both gut microbiota dysbiosis and host expression profiles at a mucosal level and to get insight into the functional genomic crosstalk between microbiota and mucosal epithelium in vivo. Methods. Biopsies were sampled from the sigmoid colon of both healthy and diseased siblings from UC discordant twin pairs but also from healthy twins. Microbiota profiles were assessed by 16S rDNA libraries while mRNA expression profiles were analysed from the same volunteers using Affymetrix microarrays. Results. UC patients showed a dysbiotic microbiota with lower diversity and more species belonging to Actinobacteria and Proteobacteria phyla. On the contrary, their healthy siblings’ microbiota contained more bacteria from the Lachnospiracea and Ruminococcaceae family than did healthy individuals . Sixty-three host transcripts significantly correlated with bacterial genera in healthy individuals whereas only 43 and 32 correlated with bacteria in healthy and UC siblings from discordant pairs, respectively. Several transcripts related to oxidative and immune responses were differentially expressed between unaffected and UC siblings. Conclusion. A loss of crosstalk between gut microbiota and host was highlighted in UC patients. This defect was also striking in healthy siblings from discordant pairs, as was the lower biodiversity within the microbiota. Our results suggest disease-relevant interactions between host transcriptome and microbiota. Moreover, unusual aerobic bacteria were noticed in UC mucosal microbiota, whereas healthy siblings from discordant pairs had higher percentages of potentially beneficialusual commensal bacterial species.

Project description:Background and aims. The etiopathology of inflammatory bowel diseases is still poorly understood. To date, only few little data are available on the microbiota composition in ulcerative colitis (UC), representing a major subform of inflammatory bowel diseases. Currently, one of the main challenges is to unravel the interactions between genetics and environmental factors in the onset or during the progression and maintenance of the disease. The aim of the present study was to analyse twin pairs discordant for UC for both gut microbiota dysbiosis and host expression profiles at a mucosal level and to get insight into the functional genomic crosstalk between microbiota and mucosal epithelium in vivo. Methods. Biopsies were sampled from the sigmoid colon of both healthy and diseased siblings from UC discordant twin pairs but also from healthy twins. Microbiota profiles were assessed by 16S rDNA libraries while mRNA expression profiles were analysed from the same volunteers using Affymetrix microarrays. Results. UC patients showed a dysbiotic microbiota with lower diversity and more species belonging to Actinobacteria and Proteobacteria phyla. On the contrary, their healthy siblingsM-bM-^@M-^Y microbiota contained more bacteria from the Lachnospiracea and Ruminococcaceae family than did healthy individuals . Sixty-three host transcripts significantly correlated with bacterial genera in healthy individuals whereas only 43 and 32 correlated with bacteria in healthy and UC siblings from discordant pairs, respectively. Several transcripts related to oxidative and immune responses were differentially expressed between unaffected and UC siblings. Conclusion. A loss of crosstalk between gut microbiota and host was highlighted in UC patients. This defect was also striking in healthy siblings from discordant pairs, as was the lower biodiversity within the microbiota. Our results suggest disease-relevant interactions between host transcriptome and microbiota. Moreover, unusual aerobic bacteria were noticed in UC mucosal microbiota, whereas healthy siblings from discordant pairs had higher percentages of potentially beneficialusual commensal bacterial species. Paired samples (twins) were analyzed to obtain data independent of genetic variation

Project description:Pancreatic cancer is the fourth leading cause of cancer death. Lack of early detection technology for pancreatic cancer invariably leads to a typical clinical presentation of incurable disease at initial diagnosis. Oral fluid (saliva) meets the demand for non-invasive, accessible, and highly efficient diagnostic medium. The level of salivary analytes, such as mRNA and microflora, vary upon disease onset; thus possess valuable signatures for early detection and screening. In this study, we evaluated the performance and translational utilities of the salivary transcriptomic and microbial biomarkers for non-invasive detection of early pancreatic cancer. Two biomarker discovery technologies were used to profile transcriptome in saliva supernatant and microflora in saliva pellet. The Affymetrix Human Genome U133 Plus 2.0 Array was used to discover altered gene expression in saliva supernatant. The Human Oral Microbe Identification Microarray (HOMIM) was used to investigate microflora shift in saliva pellet. Biomarkers selected from both studies were subjected to an independent clinical validation using a cohort of 30 early pancreatic cancer, 30 chronic pancreatitis and 30 healthy matched-control saliva samples. Two panels of salivary biomarkers, including eleven mRNA biomarkers and two microbial biomarkers were discovered and validated for pancreatic cancer detection. The logistic regression model with the combination of three mRNA biomarkers (ACRV1, DMXL2 and DPM1) yielded a ROC-plot AUC value of 0.974 (95% CI, 0.896 to 0.997; P < 0.0001) with 93.3% sensitivity and 90% specificity in distinguishing pancreatic cancer patients from healthy subjects. The logistic regression model with the combination of two bacterial biomarkers (Neisseria elongata and Streptococcus mitis) yielded a ROC-plot AUC value of 0.895 (95% CI, 0.784 to 0.961; P < 0.0001) with 96.4% sensitivity and 82.1% specificity in distinguishing pancreatic cancer patients from healthy subjects. Importantly, the logistic regression model with the combination of four biomarkers (mRNA biomarkers, ACRV1, DMXL2 and DPM1; bacterial biomarker, S. mitis) could differentiate pancreatic cancer patients from all non-cancer subjects (chronic pancreatitis and healthy control), yielding a ROC-plot AUC value of 0.949 (95% CI, 0.877 to 0.985; P < 0.0001) with 92.9% sensitivity and 85.5% specificity. This study comprehensively compared the salivary transcriptome and microflora between pancreatic cancer and control subjects. We have discovered and validated eleven mRNA biomarkers and two microbial biomarkers for early detection of pancreatic cancer in saliva. The logistic regression model with four salivary biomarkers can detect pancreatic cancer specifically without the complication of chronic pancreatitis. This is the first report demonstrating the value of multiplex salivary biomarkers for the non-invasive detection of a high impact systemic cancer. Keywords: Salivary biomarker, pancreatic cancer, early detection, salivary transcriptome, salivary microflora This study, which was approved by the UCLA Institutional Review Board, started sample collection in February 2006 and ended in April 2008. It had a discovery and verification phase, followed by an independent validation phase. All patients with clinically diagnosed early or locally advanced pancreatic cancer, chronic pancreatitis and matched healthy control were recruited from the UCLA Medical Center. The controls were matched for gender, age, ethnicity and smoking history. We chose early and locally advanced pancreatic cancers because they were considered early stage diseases. All patients were recently diagnosed with primary disease, and had not received any prior treatment in the form of chemotherapy, radiotherapy, surgery, or alternative remedies. No subjects had a history of prior malignancy, immunodeficiency, autoimmune disorders, hepatitis, or HIV infection. Written informed consent was obtained from all patients who agreed to serve as saliva donors. Unstimulated saliva samples were collected and processed as previously described. The saliva bank of pancreatic disease at the UCLA Dental Research Institute has collected 283 saliva samples since 2006. Of these, 114 samples, from 42 pancreatic cancer patients, 30 chronic pancreatitis patients and 42 healthy control subjects, met the following eligibility criteria: the disease subjectsâ?? samples were obtained immediately after primary diagnosis from patients without evidence of metastasis; the saliva sample was free of blood (Table 1 in accompanying manuscript). Of the 114 samples, 12 pancreatic cancer samples and 12 healthy control samples were chosen for the discovery and verification phase. The transcriptomic approach profiled the saliva supernatant samples from 12 pancreatic cancer patients and 12 healthy control subjects using the Affymetrix Human Genome U133 Plus 2.0 Array platform.

Dataset Information

Multi-omic analysis reveals bacteria may have a role in dental erosion

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets