Project description:The impact of mono-chronic S. stercoralis infection on the gut microbiome and microbial activities in infected participants was explored. The 16S rRNA gene sequencing of a longitudinal study with 2 sets of human fecal was investigated. Set A, 42 samples were matched, and divided equally into positive (Pos) and negative (Neg) for S. stercoralis diagnoses. Set B, 20 samples of the same participant in before (Ss+PreT) and after (Ss+PostT) treatment was subjected for 16S rRNA sequences and LC-MS/MS to explore the effect of anti-helminthic treatment on microbiome proteomes.
Project description:The objectives of this study were to establish a microbiome profile for oral epithelial dysplasia using archival lesion swab samples to characterize the community variations and the functional potential of the microbiome using 16S rRNA gene sequencing
Project description:Off-target amplification can lead to false positive human brain microbiome detection. 16s rRNA amplicon samples from brain tissue of healthy and Parkinson's disease patients.
| EGAD00001006553 | EGA
Project description:16s rRNA gene amplicon dataset of Schmidtea mediterranea
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.
Project description:Sensitive models of climate change impacts would require a better integration of multi-omics approaches that connect the abundance and activity of microbial populations. Here, we show that climate is a fundamental driver of the protein abundance of microbial populations (metaproteomics), yet not their genomic abundance (16S rRNA gene amplicon sequencing), supporting the hypothesis that metabolic activity may be more closely linked to climate than community composition.
Project description:In this RNA-Seq dataset, we describe transcriptomic changes in whole dissected intestinal tracts taken from adult zebrafish that were either fed normally or subjected to a prolonged starvation/refeeding regimen. Analysis of this RNA-Seq data revealed starvation-induced alterations in transcript levels for many genes, including a decrease in lipid metabolism and an increase in innate immune responses. Refeeding for as little as 3 days after starvation was sufficient to restore most transcripts to their baseline pre-starvation levels. These host RNA-Seq results are accompanied by a 16S rRNA gene sequencing dataset from similarly treated adult zebrafish to define changes in intestinal microbiome composition associated with starvation and refeeding.
