Subgingival organism
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA397298 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR5903446.fastq.gz | Fastqsanger.gz | |||
| SRR5903446_1.fastq.gz | Fastqsanger.gz | |||
| SRR5903446_2.fastq.gz | Fastqsanger.gz | |||
| SRR5933802_1.fastq.gz | Fastqsanger.gz | |||
| SRR5933802_2.fastq.gz | Fastqsanger.gz |
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Similar Datasets
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: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:Human sub-gingival plaque bacterial microbiome Targeted Locus (Loci)
| PRJNA173044 | ENA
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.
2010-05-21 | GSE21929 | GEO
Project description:Characterization of extracellular DNA in subgingival plaque using Hiseq 16S rRNA sequencing
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Project description:Defining Porphyromonas gingivalis strains from subgingival plaque
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Project description:Subgingival plaque/faeces/serum Raw sequence reads
| PRJNA956150 | 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:Objectives M-bM-^@M-^STo determine whether inflammation biomarkers can be used as indicators of therapeutic response, an exploratory study was performed to ascertain whether short term improvements in risk parameters will have measureable effects on a pre-defined panel of plaque inflammation biomarkers. Methods and Results M-bM-^@M-^S Patients (n=121) with peripheral arterial disease were enrolled into one of three sub-studies based upon the presence of hypercholesterolemia, hypertension, or diabetes. Patients were randomized to 6 weeks of drug treatment vs. placebo and underwent catheter excision of atherosclerotic tissue from one extremity at baseline and the contralateral extremity after treatment. Simvastatin 40mg once daily reduced LDL-C by 43% (p<0.01), losartan 50mg once daily reduced diastolic blood pressure by 4 mm Hg (p=0.099), and pioglitazone 30mg once daily reduced serum glucose by 66mg/dL (p=0.008). Despite these effects, there were no consistent treatment effects on a large panel of plaque protein, RNA and lipid biomarkers. Conclusions M-bM-^@M-^S Short term treatment with drugs that improve cardiovascular risk parameters did not result in a measureable reduction in the levels of peripheral arterial plaque inflammation biomarkers. Further studies are required to identify biomarkers that are sufficiently predictive to be used to identify drug candidates for testing in large cardiovascular outcome studies. (ClinicalTrials.gov: NCT00720577) Human peripheral atherosclerosis plaque was extracted from lower extremities, and RNA, lipids and proteins extracted. RNA was analyzed in an Agilent two-color platform.
2012-05-15 | E-GEOD-37824 | biostudies-arrayexpress