Similar Datasets
Project description:FAN (Factor associated with neutral sphingomyelinase activation) is an adaptor protein that constitutively binds to TNF-R1. Microarray analysis was performed in fibroblasts derived from wild-type or FAN knockout mouse embryos to evaluate the role of FAN in TNF-induced gene expression. We used microarrays to detail the global programme of gene expression underlying cellularisation and identified distinct classes of up-regulated genes during this process. Keywords: genetic modification
2009-08-31 | GSE12275 | GEO
Project description:FAN (Factor associated with neutral sphingomyelinase activation) is an adaptor protein that constitutively binds to TNF-R1. Microarray analysis was performed in fibroblasts derived from wild-type or FAN knockout mouse embryos to evaluate the role of FAN in TNF-induced gene expression. We used microarrays to detail the global programme of gene expression underlying cellularisation and identified distinct classes of up-regulated genes during this process. Experiment Overall Design: MEFs were derived from C57BL/6 embryos that were either wild type or FAN-/-. Cells were either grown in DMEM 0%FCS for 24h or DMEM 0% FCS for 8h followed by incubation in DMEM 0% FCS containing 50ng/ml TNF for 16h. These four conditions were each used to generate total RNA (RNeasy MidiKit, Qiagen) which was sent to AROS applied biotechnology (Sweden) for Affymetrix GeneChip Mouse Genome 430 2.0 Array analysis.
2009-09-04 | E-GEOD-12275 | biostudies-arrayexpress
Project description:All cells and organisms exhibit stress-coping mechanisms to ensure survival. Cytoplasmic protein-RNA assemblies termed stress granules are increasingly recognized to promote cellular survival under stress. Thus, they might represent tumor vulnerabilities that are currently poorly explored. The translation-inhibitory eIF2α kinases are established as main drivers of stress granule assembly. Using a systems approach, we identify the translation enhancers PI3K and MAPK/p38 as pro-stress-granule-kinases. They act through the metabolic master regulator mammalian target of rapamycin complex 1 (mTORC1) to promote stress granule assembly. When highly active, PI3K is the main driver of stress granules; however, the impact of p38 becomes apparent as PI3K activity declines. PI3K and p38 thus act in a hierarchical manner to drive mTORC1 activity and stress granule assembly. Of note, this signaling hierarchy is also present in human breast cancer tissue. Importantly, only the recognition of the PI3K-p38 hierarchy under stress enabled the discovery of p38’s role in stress granule formation. In summary, we assign a new pro-survival function to the key oncogenic kinases PI3K and p38, as they hierarchically promote stress granule formation.
2020-01-03 | MODEL2001030002 | BioModels
Project description:All cells and organisms exhibit stress-coping mechanisms toensure survival. Cytoplasmic protein-RNA assemblies termedstress granules are increasingly recognized to promote cellularsurvival under stress. Thus, they might represent tumor vul-nerabilities that are currently poorly explored. The translation-inhibitory eIF2αkinases are established as main drivers ofstress granule assembly. Using a systems approach, we identifythe translation enhancers PI3K and MAPK/p38 as pro-stress-granule-kinases. They act through the metabolic master regu-lator mammalian target of rapamycin complex 1 (mTORC1) topromote stress granule assembly. When highly active, PI3K is themain driver of stress granules; however, the impact of p38becomes apparent as PI3K activity declines. PI3K and p38 thusact in a hierarchical manner to drive mTORC1 activity and stressgranule assembly. Of note, this signaling hierarchy is also presentin human breast cancer tissue. Importantly, only the recognition ofthe PI3K-p38 hierarchy under stress enabled the discovery of p38’srole in stress granule formation. In summary, we assign a new pro-survival function to the key oncogenic kinases PI3K and p38, as theyhierarchically promote stress granule formation
2020-01-03 | BIOMD0000000907 | BioModels
Project description:Thirty-five adult (8-16 week old) C57BL/6 mice (which had undergone previous behavioral protocols) were anesthetized with isoflurane, and the brains were removed quickly, embedded in OCT, and frozen in a dry ice-ethanol mixture. The interval between decapitation and complete freezing was always less than 3 minutes. The brain was warmed up to -20oC, and cut into 10-14 m sections with a cryostat (Leica). Serial coronal sections were kept on slides in 100% ethanol until sectioning was complete. Tissue was then processed with hematoxylin and eosin (H&E) staining for cell layer visualization, followed by dehydration with increasing concentrations of ethanol and then xylene. We focused on two cell types, the Purkinje (Pk) and granule cells (gc) of the flocculus. We used an Arcturus PixCell II laser capture microdissection (LCM) scope to locate and capture cells from the appropriate areas, obtaining ten samples per cell type per mouse. We estimate that each Pk sample contained about 50-100 Purkinje cells, and each gc sample contained a few thousand granule cells. Granule cell samples (dorsal flocculus) were captured before Purkinje cell samples, to reduce contamination of the Purkinje cell samples by granule cell material. Samples were removed from the LCM caps with RNEasy lysis buffer (Qiagen) containing 1% -mercaptoethanol, then frozen at -80oC. For each mouse, all the samples of a given cell type were pooled together; samples from different mice were not pooled. Total RNA samples were isolated using RNEasy kits (Qiagen), then amplified in two rounds of in vitro transcription (IVT) using the Ambion MessageAmp aRNA kit. IVT-amplified samples were hybridized to microarrays if the end product after the second round of amplification was of concentration greater than or equal to 0.2 g/l, and at least 10 times the negative control signal (measured after two rounds of amplification of a blank sample). Due to the small starting sample sizes, samples often were rejected due to insufficient quantity for hybridization: thus, 18/35 granule cell samples and 23/35 Purkinje cell samples survived this quality control process, and were run on arrays (41 arrays total). Mus musculus spotted cDNA microarrays (MM arrays) containing ~42,000 spots were obtained from the Stanford Functional Genomics facility (complete information at http://www.microarray.org/), in order to analyze gene expression in each cell type. We used a type II experimental design, where all experimental samples were hybridized against a common reference sample for multi-way comparison. The reference sample comprised mRNA extracted from neonatal and adult brain and liver, and amplified twice by IVT. We used standard protocols for cDNA labeling, as well as array hybridization, washing, scanning, and data analysis (http://cmgm.stanford.edu/pbrown/protocols/index.html). A cell type comparison design experiment design type compares cells of different type for example different cell lines. Keywords: cell_type_comparison_design
2006-10-04 | GSE5954 | GEO