Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Expression data from TNF-stimulated mouse glomeruli

ABSTRACT: The specific contribution of the two TNF-receptors Tnfr1 and Tnfr2 to TNF-induced inflammation in the glomerulus is unknown. In mice, TNF exposure induces glomerular expression of inflammatory mediators like adhesion molecules and chemokines in vivo, and glomerular accumulation of leukocytes. To examine Tnfr-specific inflammatory responses in intrinsic glomerular cells but not infiltrating leukocytes we performed microarray gene expression profiling on intact glomeruli isolated from wild-type and Tnfr-deficient mice following TNF exposure in vitro. Glomeruli were isolated from male C57BL/6J wild-type and Tnfr-deficient mice applying a magnetic bead-based isolation technique. Isolated intact glomeruli were stimulated with TNF for 12 hours in vitro for subsequent RNA extraction and hybridization on Affymetrix microarrays.

ORGANISM(S): Mus musculus

SUBMITTER: Volker Vielhauer

PROVIDER: E-GEOD-43928 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Distinct contributions of TNF receptor 1 and 2 to TNF-induced glomerular inflammation in mice.

Taubitz Anela A Schwarz Martin M Eltrich Nuru N Lindenmeyer Maja T MT Vielhauer Volker V

PloS one 20130715 7

TNF is an important mediator of glomerulonephritis. The two TNF-receptors TNFR1 and TNFR2 contribute differently to glomerular inflammation in vivo, but specific mechanisms of TNFR-mediated inflammatory responses in glomeruli are unknown. We investigated their expression and function in murine kidneys, isolated glomeruli ex vivo, and glomerular cells in vitro. In normal kidney TNFR1 and TNFR2 were preferentially expressed in glomeruli. Expression of both TNFRs and TNF-induced upregulation of TNF ...[more]

PMID: 23869211

Similar Datasets

Project description:Glomerular diseases account for the majority of cases with chronic renal failure. Several genes have been identified with key relevance for glomerular function. Quite a few of these genes show a specific or preferential mRNA expression in the renal glomerulus. To identify additional candidate genes involved in glomerular function in humans we generated a human renal glomerulus-specific transcript dataset (GTD) by comparing gene expression profiles from human glomeruli and tubulointerstitium obtained from six transplant living donors using Affymetrix HG-U133A arrays. This analysis resulted in 677 genes with prominent overrepresentation in the glomerulus. Genes with ‘a prior’i established known prominent glomerular expression served for validation and were all found in the novel expression library (e.g. CDKN1, DAG1, DDN, EHD3, MYH9, NES, NPHS1, NPHS2, PDPN, PLA2R1, PLCE1, PODXL, PTPRO, SYNPO, TCF21, TJP1, WT1). The mRNA expression for several novel glomerulus-enriched genes identified in REGGEL was validated by qRT-PCR. Gene ontology and pathway analysis identified biological processes previously not reported to be of relevance in glomeruli including among others axon guidance. This finding was further validated by assessing the expression of the axon guidance molecules neuritin (NRN1) and roundabout receptor ROBO1 and -2. Glomerular disease associated differential mRNA regulation of ROBO2 was found in diabetic nephropathy. In summary, using a comparative strategy on microdissected nephrons novel transcripts with predominant expression in the human glomerulus could be identified. A systematic analysis of this glomerulus-specifc gene expression library allows the detection of target molecules and biological processes involved in glomerular biology and renal disease. Sample from kidney biopsies of 6 transplant Living Donors (LD) were microdissected into tubular and glomerular compartment and separately hybridized an Affymetrix HG-U133A microarrays. Background correction and quantile normalization was ferformed using RMAexpress Version 0.3 as part of a dataset of 88 samples for glomeruli and 84 samples for tubuli. All data are reported in log2 scale. A background filter cut-off was defined to lower the count of false positive calls using the highest signal value obtained from non-human Affymetrix control oligonucleotides multiplied by a factor of 1.2, following previous studies: Schmid H, Boucherot A, Yasuda Y, et al.: Modular activation of nuclear factor-kappaB transcriptional programs in human diabetic nephropathy. Diabetes 55:2993-3003, 2006 A linear model was fit to compensate differences in expression due to separate sample processing of the compartments. Subsequently, genes were selected based on foldchange.

Dataset Information

Expression data from TNF-stimulated mouse glomeruli

Publications

Distinct contributions of TNF receptor 1 and 2 to TNF-induced glomerular inflammation in mice.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure