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:Purpose: The goal of this study is to compare endothelial small RNA transcriptome to identify the target of OASL under basal or stimulated conditions by utilizing miRNA-seq. Methods: Endothelial miRNA profilies of siCTL or siOASL transfected HUVECs were generated by illumina sequencing method, in duplicate. After sequencing, the raw sequence reads are filtered based on quality. The adapter sequences are also trimmed off the raw sequence reads. rRNA removed reads are sequentially aligned to reference genome (GRCh38) and miRNA prediction is performed by miRDeep2. Results: We identified known miRNA in species (miRDeep2) in the HUVECs transfected with siCTL or siOASL. The expression profile of mature miRNA is used to analyze differentially expressed miRNA(DE miRNA). Conclusions: Our study represents the first analysis of endothelial miRNA profiles affected by OASL knockdown with biologic replicates.
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:Nitrate-reducing iron(II)-oxidizing bacteria are widespread in the environment contribute to nitrate removal and influence the fate of the greenhouse gases nitrous oxide and carbon dioxide. The autotrophic growth of nitrate-reducing iron(II)-oxidizing bacteria is rarely investigated and poorly understood. The most prominent model system for this type of studies is enrichment culture KS, which originates from a freshwater sediment in Bremen, Germany. To gain insights in the metabolism of nitrate reduction coupled to iron(II) oxidation under in the absence of organic carbon and oxygen limited conditions, we performed metagenomic, metatranscriptomic and metaproteomic analyses of culture KS. Raw sequencing data of 16S rRNA amplicon sequencing, shotgun metagenomics (short reads: Illumina; long reads: Oxford Nanopore Technologies), metagenome assembly, raw sequencing data of shotgun metatranscriptomes (2 conditions, triplicates) can be found at SRA in https://www.ncbi.nlm.nih.gov/bioproject/PRJNA682552. This dataset contains proteomics data for 2 conditions (heterotrophic and autotrophic growth conditions) in triplicates.
Project description:A metaproteomics analysis was conducted on the infant fecal microbiome to characterize global protein expression in 8 samples obtained from infants with a range of early-life experiences. Samples included breast-, formula- or mixed-fed, mode of delivery, and antibiotic treatment and one set of monozygotic twins. Although label-free mass spectrometry-based proteomics is routinely used for the identification and quantification of thousands of proteins in complex samples, the metaproteomic analysis of the gut microbiome presents particular technical challenges. Among them: the extreme complexity and dynamic range of member taxa/species, the need for matched, well-annotated metagenomics databases, and the high inter-protein sequence redundancy/similarity between related members. In this study, a metaproteomic approach was developed for assessment of the biological phenotype and functioning, as a complement to 16S rRNA sequencing analysis to identify constituent taxa. A sample preparation method was developed for recovery and lysis of bacterial cells, followed by trypsin digestion, and pre-fractionation using Strong Cation Exchange chromatography. Samples were then subjected to high performance LC-MS/MS. Data was searched against the Human Microbiome Project database, and a homology-based meta-clustering strategy was used to combine peptides from multiple species into representative proteins. Bacterial taxonomies were also identified, based on species-specific protein sequences, and protein metaclusters were assigned to pathways and functional groups. The results obtained demonstrate the applicability of this approach for performing qualitative comparisons of human fecal microbiome composition, physiology and metabolism, and also provided a more detailed assessment of microbial composition in comparison to 16S rRNA.