Ontology highlight
ABSTRACT:
PROVIDER: PRJNA386032 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR5520110.fastq.gz | Fastqsanger.gz | |||
| SRR5520120.fastq.gz | Fastqsanger.gz | |||
| SRR5520111.fastq.gz | Fastqsanger.gz | |||
| SRR5520121.fastq.gz | Fastqsanger.gz | |||
| SRR5520112.fastq.gz | Fastqsanger.gz |
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Project description:We investigated the association between subgingival bacterial profiles and gene expression patterns in gingival tissues of patients with periodontitis. A total of 120 patients undergoing periodontal surgery contributed with a minimum of two interproximal gingival papillae (range 2-4) from a maxillary posterior. Prior to tissue harvesting, subgingival plaque samples were collected from the mesial and distal aspects of each papilla. Gingival tissue RNA was extracted, reverse-transcribed, labeled, and hybridized with whole-genome microarrays (310 in total)
2009-12-21 | E-GEOD-16134 | biostudies-arrayexpress
Project description:We investigated the association between subgingival bacterial profiles and gene expression patterns in gingival tissues of patients with periodontitis.
2009-12-22 | GSE16134 | GEO
Project description:This study compared the subgingival microbiota of subjects with periodontitis to those with periodontal health using the Human Oral Microbe Identification Microarray (HOMIM).
2011-09-17 | GSE32159 | GEO
Project description:Analysis of gingival crevicular fluid (GCF) samples may give information of the identity of unattached (planktonic) subgingival bacteria, the 35 forefront candidates for systemic dispersal via ulcerated periodontal pocket epithelium. Our study represents the first one targeting the identity of bacteria in gingival crevicular fluid. Methodology/Principal findings: We determined bacterial species diversity in GCF samples of a group of periodontitis patients and delineated contributing bacterial and host-associated factors. Subgingival paper point (PP) samples from the same sites were taken for comparison. After DNA extraction, 16S rRNA genes were PCR amplified and DNA-DNA hybridization was performed using a microarray for over 300 bacterial species or groups. Altogether 133 species from 41 genera and 8 phyla 45 were detected with 9 to 62 and 18 to 64 species in GCF and PP samples, respectively, 46 per patient. Projection to latent structures by means of partial least squares (PLS) was applied to the multivariate data analysis. PLS regression analysis showed that species of genera including Campylobacter, Selenomonas, Porphyromonas, Catonella, Tannerella, Dialister, Peptostreptococcus, Streptococcus and Eubacterium had significant positive correlations and the number of teeth with low-grade attachment loss a significant negative correlation to species diversity in GCF samples. OPLS/O2PLS discriminant analysis revealed significant positive correlations to GCF sample group membership for species of genera Campylobacter, Leptotrichia, Prevotella, Dialister, Tannerella, Haemophilus, Fusobacterium, Eubacterium, and Actinomyces. Conclusions/Significance: Among a variety of detected species those traditionally classified as Gram-negative anaerobes growing in mature subgingival biofilms were the main predictors for species diversity in GCF samples as well as responsible for distinguishing GCF samples from PP samples. GCF bacteria may provide new prospects for studying dynamic properties of subgingival biofilms. The microbial profiles of GCF and subgingival plaque were analyzed from 17 subjects with periodontal disease.
2010-05-21 | E-GEOD-21929 | biostudies-arrayexpress
Project description:Dysbiosis of subgingival microbiome promotes the growth of periodontopathogens and the development of periodontitis, an irreversible chronic inflammatory disease. Untreated periodontitis leads to the destruction of connective tissues, alveolar bone resorption and ultimately to tooth loss. Periodontitis has been associated with inflammatory metabolic diseases such as type 2 diabetes. While periodontitis-induced inflammation is a key player in both, the development of subgingival microbiome dysbiosis and in the host-microbiome interaction, the effects of hyperglycemia on the regulation of the host genes controlling the inflammatory response and the host-microbiome interaction are still scarce. We investigated the impacts of a hyperglycemic microenvironment on the inflammatory response and gene expression of a gingival fibroblasts-macrophages coculture model stimulated with dysbiotic subgingival microbiomes. A coculture model composed of immortalized human gingival fibroblasts overlaid with U937 macrophages-likes cells were stimulated with subgingival microbiome collected from four healthy donors and four patients with periodontitis. Pro-inflammatory cytokines and matrix metalloproteinase were measured by a Luminex assay while the coculture RNA was submitted to a microarray analysis. Subgingival microbiomes were submitted to 16s rRNA gene sequencing. Data were analyzed by using an advanced multi-omics bioinformatic data integration model. Our results showed that krt76, krt27, pnma5, mansc4, rab41, thoc6, tm6sf2, and znf506 as well as the pro-inflammatory cytokines IL-1, GM-CSF, FGF2, IL-10, the metalloproteinases MMP3 and MMP8, and bacteria from the ASV 105, ASV 211, ASV 299, Prevotella, Campylobacter and Fretibacterium genera are key correlated variables contributing to periodontitis-induced inflammatory response in a hyperglycemic microenvironment. To conclude, our multi-omics integration analysis unveiled unique differentially interrelated bacterial genera, genes and pro-inflammatory cytokines involved in the regulation of the inflammatory response in a hyperglycemic microenvironment. These data also highlight the importance of considering hyperglycemic conditions in the development of new drugs or treatments for periodontal disease in link with type 2 diabetes.
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Project description:Gene expressions relate to the pathogenesis of periodontitis and have a crucial role in local tissue destruction and susceptibility to the disease. The aims of the present study were to explore comprehensive gene expressions/transcriptomes in periodontitis-affected gingival tissues, and to identify specific biological processes. The purpose of the present study was 1) to compare comprehensive gene expression/transcriptomes of periodontitis-affected gingival tissues with those of healthy tissues by using microarray and data mining technologies, and 2) to analyze significantly differentially expressed genes which belong to pathological pathways in periodontitis by qRT-PCR. Two distinct gingival samples including healthy and periodontal-affected gingiva were taken from 3 patients with severe chronic periodontitis. Total RNAs from 6 gingival tissue samples were used for microarray and data-mining analyses. Comparisons, gene ontology, and pathway frequency analyses were performed and identified significant biological pathways in periodontitis. Quantitative reverse transcription real-time polymerase chain reaction (qRT-PCR) analyse using 14 chronic periodontitis patients including 3 patients listed above and 14 healthy individuals showed 9 differentially expressed genes in leukocyte migration and cell communication pathways.
2010-08-13 | E-GEOD-23586 | biostudies-arrayexpress
Project description:Affymetrix GeneChip miRNA 3.0 microarrays were compared in gingival tissue biopsy samples from obese and normal weight patients with periodontitis
2017-05-31 | GSE59398 | GEO
Project description:We examined gene expression signatures in healthy and diseased gingival tissues in 90 patients. Analysis of the gingival tissue transcriptome in states of periodontal health and disease may reveal novel insights of the pathobiology of periodontitis. Keywords: gingival tissue disease state analysis
2008-12-22 | GSE10334 | GEO
Project description:This study evaluated the transcriptome of healthy gingival tissue in patients with a history of generalized aggressive periodontitis (GAgP) and chronic periodontitis (CP) and in subjects with no history of periodontitis (H), using microarray analysis.
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Project description:sc-RNAseq performed on gingival tissue isolated from healthy and periodontitis patients.
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