Project description:Integrated multi-omic analyses of the genomic modifications by 5-(4′-Hydroxyphenyl)-γ-valerolactone metabolites in TNFalpha-stimulated primary human brain microvascular endothelial cells. We exposed human brain microvascular endothelial cells to mixture of 2 metabolites of 5-(4′-Hydroxyphenyl)-γ-valerolactone after they have been exposed to TNF. Total RNA has been extracted and expression of mRNA, miRNas, snoRNAs and lncRNAs has been obtained using microarrays.
Project description:The aim of this study was to explore the gene expression and metabolites among multisite adipose-derived mesenchymal stem cells, and investigate the metabolic pathway of multisite adipose-derived mesenchymal stem cells using a multi-omics analysis. Subcutaneous adipose-derived mesenchymal stem cells (SASCs), perirenal adipose-derived mesenchymal stem cells (PASCs), and epididymal adipose-derived mesenchymal stem cells (EASCs) were isolated from Sprague Dawley rats. RNA and metabolites were extracted and sequenced using transcriptomics and metabolomics analyses, respectively. There were 720 differentially expressed genes (DEGs) in EASCs and 688 DEGs in PASCs compared with SASCs; there were 166 unique DEGs in EASCs, 134 unique DEGs in PASCs, and 554 common DEGs between EASCs and PASCs. Furthermore, there were 220 differential metabolites in EASCs, 249 differential metabolites in PASCs, 83 unique differential metabolites in EASCs, 112 unique differential metabolites in PASCs, and 137 common differential metabolites between EASCs and PASCs. The transcriptomics and metabolomics analyses identified four hub genes, one in EASCs and three in PASCs. There are functional differences among multisite adipose-derived mesenchymal stem cells that may be related to the hub genes Atac2, Rrm1, Rrm2, and Gla. The relevant signaling pathways are the Ras signaling pathway, HIF-1 signaling pathway, and the p53 signaling pathway.
Project description:Elucidation of complex molecular networks requires integrative analysis of molecular features and changes at different levels of information flow and regulation. Accordingly, high throughput functional genomics tools such as transcriptomics, proteomics, metabolomics and lipidomics have emerged to provide system-wide investigations. Unfortunately, analysis of different types of biomolecules requires specific sample extraction procedures in combination with specific analytical instrumentation. The most efficient extraction protocols often only cover a restricted type of biomolecules due to their different physicochemical properties. Therefore, several sets/aliquots of samples are needed for extracting different molecules. Here we adapted a bi-phasic fractionation method to extract proteins, metabolites and lipids from the same sample (3-in-1) for liquid chromatography-tandem mass spectrometry (LC-MS/MS) multi-omics. To demonstrate utility of the improved method, we used bacteria-primed Arabidopsis leaves to generate multi-omics datasets from the same sample. In total, we were able to analyze 1849 proteins, 1967 metabolites and 424 lipid species in single samples. The molecules cover a wide range of biological and molecular processes. Our results have shown the clear advantages of the multi-omics method, including sample conservation, high reproducibility and tight correlation between different types of biomolecules.
Project description:Joint profiling of chromatin accessibility and gene expression from the same single cell provides critical information about cell types in a tissue and cell states during a dynamic process. These emerging multi-omics techniques help the investigation of cell-type resolved gene regulatory mechanisms. Here, we developed in situ SHERRY after ATAC-seq (ISSAAC-seq), a highly sensitive and flexible single cell multi-omics method to interrogate chromatin accessibility and gene expression from the same single cell. We demonstrated that ISSAAC-seq is sensitive and provides high quality data with orders of magnitude more features than existing methods. Using the joint profiles from thousands of nuclei from the mouse cerebral cortex, we uncovered major and rare cell types together with their cell-type specific regulatory elements and expression profiles. Finally, we revealed distinct dynamics and relationships of transcription and chromatin accessibility during an oligodendrocyte maturation trajectory.
Project description:The gut microbiome has been implicated in multiple human chronic gastrointestinal (GI) disorders. Determining its mechanistic role in disease pathogenesis has been difficult due to the apparent disconnect between animal and human studies and a lack of an integrated multi-omics view in the context of disease-specific physiological changes. We integrated longitudinal multi-omics data from the gut microbiome, metabolome, host epigenome and transcriptome in the context of irritable bowel syndrome (IBS) host physiology. We identified IBS subtype-specific and symptom-related variation in microbial composition and function. A subset of identified changes in microbial metabolites correspond to host physiological mechanisms that are relevant to IBS. By integrating multiple data layers, we identified purine metabolism as a novel host-microbial metabolic pathway in IBS with translational potential. Our study highlights the importance of longitudinal sampling and integrating complementary multi-omics data to identify functional mechanisms that can serve as therapeutic targets in a comprehensive treatment strategy for chronic GI diseases.
Project description:There are distinct interactions among microbial compositions, metabolites, and host genomes in RCC and LCC as revealed by multi-omics analysis, which brings a new dimension to understanding the role of gut microbiota in tumorigenesis of RCC and LCC.
Project description:Multi-omics molecular profiling was performed on post-radical prostatectomy material from a cohort of 132 patients with localized prostate adenocarcinoma. Unsupervised classification techniques were used to build a comprehensive classification of prostate tumours based on three molecular levels: DNA copy number, DNA methylation, and mRNA expression.
Project description:Multi-omics molecular profiling was performed on post-radical prostatectomy material from a cohort of 132 patients with localized prostate adenocarcinoma. Unsupervised classification techniques were used to build a comprehensive classification of prostate tumours based on three molecular levels: DNA copy number, DNA methylation, and mRNA expression.