E-GEOD-21031
Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: PRJNA126453
PROVIDER: E-GEOD-21031 | ExpressionAtlas | 2015-09-15
REPOSITORIES: ExpressionAtlas
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| E-GEOD-21031-analysis-methods.tsv | Tabular | |||
| E-GEOD-21031-atlasExperimentSummary.Rdata | Rdata | |||
| E-GEOD-21031-configuration.xml | Xml | |||
| E-GEOD-21031-percentile-ranks.tsv | Tabular | |||
| E-GEOD-21031.condensed-sdrf.tsv | Tabular |
Items per page: 5 1 - 5 of 87 |
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Project description:Time-series of IL-6 stimulated primary mouse hepatocytes
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Project description:RNA-seq analysis of primary hepatocytes isolated from C57BL/6N mice, stimulated with IL-1β recombinant protein to examine the transcriptional response to inflammatory signaling.
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Project description:Circadian time series RNAseq in mouse primary chondrocytes
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Project description:Cytokines such as TNF-alpha and IL-1beta are known for their contribution to inflammatory processes in liver . In contrast, the cytokine IL-17 has not yet been assigned a role in liver diseases. IL-17 can cooperate with TNF-alpha to induce a synergistic response on several target genes in different cell lines, but no data exist for primary hepatocytes. To enhance our knowledge on the impact of IL-17 alone and combined with TNF-alpha in primary murine hepatocytes a comprehensive microarray study was designed. IL-1beta was included as this cytokine is suggested to act in a similar manner as the combination of TNF-alpha and IL-17, especially with respect to its role in mRNA stabilization. Results: The present microarray analysis demonstrates that primary murine hepatocytes responded to IL-17 stimulation by upregulation of chemokines and genes, which are functionally responsible to increase and sustain inflammation. Cxcl2, Nfkbiz and Zc3h12a were strongly induced, whereas the majority of the genes were only very moderately upregulated. Promoter analysis revealed involvement of NF-kappaB in the activation of many genes. Combined stimulation of TNF-alpha/IL-17 resulted in enhanced induction of gene expression, but significantly synergistic effects could be applied only to a few genes, such as Nfkbiz, Cxcl2, Zc3h12 and Steap4. Comparison of the gene expression profile obtained after stimulation of TNF-alpha/IL-17 versus IL-1 proposed a IL-1beta-like effect of the latter cytokine combination. Moreover, evidence was provided that modulation of mRNA stability may be a major mechanism by which IL-17 regulates gene expression in primary hepatocytes. This assumption was exemplarily proven for Nfkbiz mRNA for the first time in hepatocytes. Our studies also suggest that RNA stability can partially be correlated to the existence of AU rich elements, but further mechanisms like the RNase-activity of the upregulated Zc3h12a have to be considered. Conclusions: Our microarray analysis gives new insights in IL-17 induced gene expression in primary hepatocytes highlighting the crosstalk with the NF-kappaB signalling pathway. Gene expression profile suggests IL-17 a role in sustaining liver inflammatory processes most likely by RNA stabilization. Altogether, our results provide evidence that IL-17 alone and in concert with TNF-alpha may play a role in inflammatory liver diseases. Primary murine hepatocytes of three animals stimulated for 1 or 4h by TNF-alpha, IL-1beta, IL-17 or TNF-alpha followed by IL-17 were used for microarray analysis.
2010-03-07 | E-GEOD-19272 | biostudies-arrayexpress
Project description:External stimulations of cells by hormones, growth factors or cytokines activate signal transduction pathways that subsequently induce a rearrangement of cellular gene expression. The representation and analysis of changes in the gene response is complicated, and essentially consists of multiple layered temporal responses. In such situations, matrix factorization techniques may provide efficient tools for the detailed temporal analysis. Related methods applied in bioinformatics intentionally do not take prior knowledge into account. In signal processing, factorization techniques incorporating data properties like second-order spatial and temporal structures have shown a robust performance. However, large-scale biological data rarely imply a natural order that allows the definition of an autocorrelation function. We therefore develop the concept of graph-autocorrelation. We encode prior knowledge like transcriptional regulation, protein interactions or metabolic pathways as a weighted directed graph. By linking features along this underlying graph, we introduce a partial ordering of the samples to define an autocorrelation function. Using this framework as constraint to the matrix factorization task allows us to set up the fast and robust graph decorrelation (GraDe) algorithm. To analyze the alterations in the gene response in IL-6 stimulated primary mouse hepatocytes by GraDe, a time-course microarray experiment was performed. Extracted gene expression profiles show that IL-6 activates genes involved in cell cycle progression and cell division in a time-resolved manner. On the contrary, genes linked to metabolic and apoptotic processes are down-regulated indicating that IL-6 mediated priming rendered hepatocytes more responsive towards cell proliferation and reduces expenses for the energy household. Primary mouse hepatocytes were used in the analysis comprising stimulations with 1 nM IL-6 for 1 h, 2 h, 4 h and an unstimulated control (0 h), each performed in triplicate.
2010-04-07 | E-GEOD-21031 | biostudies-arrayexpress
Project description:Mass spectrometry analysis of conditioned media fractions from mouse primary hepatocytes that induced fructose uptake
2024-08-02 | PXD054506 | JPOST Repository
Project description:This SuperSeries is composed of the following subset Series: GSE5099: Expression Data from Macrophage Maturation and Polarization Experiment GSE35433: Genome-wide analysis of human macrophages stimulated with IL-4 (20ng/ml) (Illumina) GSE35434: Genome-wide analysis of human macrophages stimulated with IL-4 (10ng/ml) (Illumina) GSE35435: Genome-wide analysis of mouse macrophages stimulated with IL-4 (bone marrow macrophages) (Affymetrix) GSE35436: Genome-wide analysis of mouse macrophages stimulated with IL-4 (Biogel and thioglycollate macrophages) (Affymetrix) Refer to individual Series
2012-09-29 | E-GEOD-35495 | biostudies-arrayexpress
Project description:To identify HGF/Met regulated genes, we performed expression microarray analysis after inducible activation of Met receptor in primary cultures of hepatocytes established from wild-type control (Alb-Cre +/-) and Met conditional knockout mice (Alb-Cre +/-; Met Fl/Fl). Keywords: time series design
2006-10-02 | GSE4451 | GEO
Project description:In this study, we combined mouse genetics and quantitative proteomics to characterize in a comprehensive manner the VAV1 interactome. A line of knock-in mouse expressing endogenous VAV1 molecules with a genetic tag permitting affinity purification was generated and combined with affinity purification and mass spectrometry (AP-MS) to analyze the VAV1 signaling complex that assembles in primary CD4+ T cells over 300 s of activation. This allowed us to describe in a time-resolved manner the interactome of VAV1 in primary CD4+ T cells and to identify 44 previously unknown bindings partners of VAV1. The dataset contains mass spectrometry results from the analysis of AP-MS purifications (based on affinity purification on Streptactin beads of One-Strep-tagged proteins) starting from CD4+ T cells which were either non stimulated or stimulated with pervanadate for different time lengths. Control samples for each time point were prepared from wild-type mice. 8 different conditions were thus analyzed: - VAV1-OST transgenic mice, CD4+ T cells non stimulated (noted Vav_0) - VAV1-OST transgenic mice, CD4+ T cells stimulated 30s (noted Vav_30) - VAV1-OST transgenic mice, CD4+ T cells stimulated 120s (noted Vav_120) - VAV1-OST transgenic mice, CD4+ T cells stimulated 300s (noted Vav_300) - WT mice, CD4+ T cells non stimulated (noted WT_0) - WT mice, CD4+ T cells stimulated 30s (noted WT_30) - WT mice, CD4+ T cells stimulated 120s (noted WT_120) - WT mice, CD4+ T cells stimulated 300s (noted WT_300) Four biological replicates were prepared for these 8 different conditions (noted S1, S2, S3, S4), yielding 32 analyzed samples. Three technical nanoLC-MS runs were acquired for each sample (noted R1, R2, R3), except for some samples of the biological series S4 for which 2 technical nanoLC-MS runs were performed. This led to 91 nanoLC-MS raw files composing the dataset.
2018-06-26 | PXD004217 | Pride