Human saliva metagenome
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA348169 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR5141580_1.fastq.gz | Fastqsanger.gz | |||
| SRR5141580_2.fastq.gz | Fastqsanger.gz | |||
| SRR5141590_1.fastq.gz | Fastqsanger.gz | |||
| SRR5141590_2.fastq.gz | Fastqsanger.gz | |||
| SRR5141600_1.fastq.gz | Fastqsanger.gz |
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2013-08-15 | E-GEOD-49875 | biostudies-arrayexpress
Project description:Human saliva microbiota is phylogenetically divergent among host individuals yet their roles in health and disease are poorly appreciated. We employed a microbial functional gene microarray, HuMiChip 1.0, to reconstruct the global functional profiles of human saliva microbiota from ten healthy and ten caries-active adults. Saliva microbiota in the pilot population featured a vast diversity of functional genes. No significant distinction in gene number or diversity indices was observed between healthy and caries-active microbiota. However, co-presence network analysis of functional genes revealed that caries-active microbiota was more divergent in non-core genes than healthy microbiota, despite both groups exhibited a similar degree of conservation at their respective core genes. Furthermore, functional gene structure of saliva microbiota could potentially distinguish caries-active patients from healthy hosts. Microbial functions such as Diaminopimelate epimerase, Prephenate dehydrogenase, Pyruvate-formate lyase and N-acetylmuramoyl-L-alanine amidase were significantly linked to caries. Therefore, saliva microbiota carried disease-associated functional signatures, which could be potentially exploited for caries diagnosis. The DMFT INDEX (Decayed, Missing, Filled [DMF] teeth index used in dental epidemiology) values are provided for each sample
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Project description:The objective of this study was analysis of the whole saliva transcriptome to search for biomarkers of psychosocial stressor exposure and substance use in young adults drawn from a population-based longitudinal cohort, the Oregon Youth Substance Use Project. We conducted genome-wide gene expression analysis on whole saliva RNA from 48 individuals stratified by psychosocial stressor exposure using an Affymetrix Gene ST 1.0 array. We applied Weighted Gene Co-expression Network Analysis (WCGNA) to characterize the high-level structure in the data and to relate expression patterns among samples to participant clinical characteristics. This approach finds clusters of correlated genes (modules) which can reflect clinical, histological, or intracellular organization and function. Using WCGNA, we constructed a gene expression network from saliva genome-wide gene expression data, which we found to be similar to a network we constructed from publicly available cell-free saliva genome-wide gene expression data. Functional characterization of the WGCNA modules suggested that the samples varied in composition between an expression profile similar to circulating antigen presenting cell types and a glycoprotein-containing expression profile. We identified a significant relation between one module of whole saliva genome-wide gene expression and smoking behavior, and one with psychosocial stressor exposure. The smoking-related module was related to mitochondrial gene expression, and ever-smokers were found to have reduced overall mitochondrial gene expression. To determine whether reduced expression could be explained by reduction in mitochondrial DNA, we measured mtDNA copy number variation within genomic DNA from 400 OYSUP participants. Surprisingly, we found that more frequent smoking is associated with increased mtDNA copy number. The network structure of whole saliva and its association with clinically assessed exposures and behaviors are reported here for the first time.
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