Ontology highlight
ABSTRACT:
PROVIDER: PRJNA903172 | ENA |
REPOSITORIES: ENA
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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:To investigate the TVA diet's effect on mouse gut microbiome, we fed C57/BL6 mice with TVA diet or CON diet for 18 days We then collected feces of the mice and performed 16S ribosomal RNA (rRNA) sequencing.
2023-09-21 | GSE202266 | GEO
Project description:Characterization of extracellular DNA in subgingival plaque using Hiseq 16S rRNA sequencing
| PRJNA330660 | ENA
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:Gut microbiota were assessed in 540 colonoscopy-screened adults by 16S rRNA gene sequencing of stool samples. Investigators compared gut microbiota diversity, overall composition, and normalized taxon abundance among these groups.
| 2255499 | ecrin-mdr-crc
Project description:Sequencing of 16S ribosomal RNA (rRNA) gene, which has improved the characterization of microbial community, has made it possible to detect a low level Helicobacter pylori (HP) sequences even in HP-negative subjects which were determined by a combination of conventional methods. This study was conducted to obtain a cutoff value for HP colonization in gastric mucosa biopsies and gastric juices by the pyrosequencing method. Corresponding author: Department of Internal Medicine, Seoul National University Bundang Hospital, Seoungnam, Gyeonggi-do, Korea; Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, Seoul, Korea (Tel., +82-31-787-7008; e-mail, nayoungkim49@empas.com). Microbial DNA from gastric mucosal samples [gastric antrum (n=63, mucosal biopsy), follow-up sample on gastric antrum (n=16, mucosal biopsy), and gastric body (n=18, mucosal biopsy)] and gastric juices (n=4, not mucosal biopsy) was amplified by nested PCR using universal bacterial primers, and the 16S rRNA genes were pyrosequenced.
2014-09-18 | E-GEOD-61493 | biostudies-arrayexpress
Project description:In this paper, we first report that EC smoking significantly increases the odds of gingival inflammation. Then, we seek to identify and explain the mechanism that underlies the relationship between EC smoking and gingival inflammation via the oral microbiome. We performed mediation analyses to assess if EC smoking affects the oral microbiome, which in turn affects gingival inflammation. For this, we collected saliva and subgingival samples from EC users and non-users and profiled their microbial compositions via 16S rRNA amplicon sequencing. We then performed α-diversity, β-diversity, and taxonomic differential analyses to survey the disparity in microbial composition between EC users and non-users. We found significant increases in α-diversity in EC users and disparities in β-diversity between EC users and non-users.
2022-12-09 | GSE201949 | GEO
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.
2023-05-31 | GSE222883 | GEO