Browse
Submit Data
Databases
API
Help

Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

11 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Response of HK-2 cells to stimulation with IL6 and TNF-alpha (72 hours)

ABSTRACT: Abstract: Human kidney function declines with age, accompanied by stereotyped changes in gene expression and histopathology, but the mechanisms underlying these changes are largely unknown. We compared age-associated changes in global gene expression patterns in the human kidney with genome-wide maps of transcription factor occupancy in human cell lines to identify potential regulators of gene expression changes in the aging kidney. The strongest associations involved three inflammation-associated transcription factors: NFκB, STAT1 and STAT3. We found that the activity of these transcription factors increases with age in epithelial compartments of the renal cortex. Stimulation of renal tubular epithelial cells with the inflammatory cytokines IL-6 (a STAT3 activator), IFN-γ (a STAT1 activator), or TNFα (an NFκB activator) recapitulated age-associated gene expression changes. We found that common DNA variants in the two genes that encode the subunits of the canonical NFκB transcription factor (RELA and NFKB1) showed significant associations with kidney function and chronic kidney disease in gene association studies, providing the first evidence for a direct link between genetic variation in NFκB and individual differences in age-related phenotypes in the kidney. Our results point to chronic inflammation, mediated by NFκB, STAT1 and STAT3, as a dominant mechanism influencing gene expression changes during kidney aging. Biological triplicate experiments were performed for each cytokine treatment condition or control treatment.

ORGANISM(S): Homo sapiens

SUBMITTER: Zach O'Brown

PROVIDER: E-GEOD-68941 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Json Xml

Similar Datasets

Response of HK-2 cells to stimulation with IL6 and TNF-alpha (90 minutes)

Project description:Abstract: Human kidney function declines with age, accompanied by stereotyped changes in gene expression and histopathology, but the mechanisms underlying these changes are largely unknown. We compared age-associated changes in global gene expression patterns in the human kidney with genome-wide maps of transcription factor occupancy in human cell lines to identify potential regulators of gene expression changes in the aging kidney. The strongest associations involved three inflammation-associated transcription factors: NFκB, STAT1 and STAT3. We found that the activity of these transcription factors increases with age in epithelial compartments of the renal cortex. Stimulation of renal tubular epithelial cells with the inflammatory cytokines IL-6 (a STAT3 activator), IFN-γ (a STAT1 activator), or TNFα (an NFκB activator) recapitulated age-associated gene expression changes. We found that common DNA variants in the two genes that encode the subunits of the canonical NFκB transcription factor (RELA and NFKB1) showed significant associations with kidney function and chronic kidney disease in gene association studies, providing the first evidence for a direct link between genetic variation in NFκB and individual differences in age-related phenotypes in the kidney. Our results point to chronic inflammation, mediated by NFκB, STAT1 and STAT3, as a dominant mechanism influencing gene expression changes during kidney aging. Biological triplicate experiments were performed for each cytokine treatment condition or control treatment.

2015-07-01 | E-GEOD-68940 | biostudies-arrayexpress

Response of HK-2 cells to stimulation with IFN, IL6 and TNF-alpha in different combinations

Project description:Abstract: Human kidney function declines with age, accompanied by stereotyped changes in gene expression and histopathology, but the mechanisms underlying these changes are largely unknown. We compared age-associated changes in global gene expression patterns in the human kidney with genome-wide maps of transcription factor occupancy in human cell lines to identify potential regulators of gene expression changes in the aging kidney. The strongest associations involved three inflammation-associated transcription factors: NFκB, STAT1 and STAT3. We found that the activity of these transcription factors increases with age in epithelial compartments of the renal cortex. Stimulation of renal tubular epithelial cells with the inflammatory cytokines IL-6 (a STAT3 activator), IFN-γ (a STAT1 activator), or TNFα (an NFκB activator) recapitulated age-associated gene expression changes. We found that common DNA variants in the two genes that encode the subunits of the canonical NFκB transcription factor (RELA and NFKB1) showed significant associations with kidney function and chronic kidney disease in gene association studies, providing the first evidence for a direct link between genetic variation in NFκB and individual differences in age-related phenotypes in the kidney. Our results point to chronic inflammation, mediated by NFκB, STAT1 and STAT3, as a dominant mechanism influencing gene expression changes during kidney aging. Biological duplicate or triplicate experiments were profiled for each cytokine treatment or control condition

2015-07-01 | E-GEOD-68942 | biostudies-arrayexpress

Response of HK-2 cells to STAT3 activation by interleukin-6 and inhibition with S3I-201

2015-07-01 | GSE68826 | GEO

Response of HK-2 cells to stimulation with IFN, IL6 and TNF-alpha in different combinations

2015-07-01 | GSE68942 | GEO

Response of HK-2 cells to stimulation with IL6 and TNF-alpha (72 hours)

2015-07-01 | GSE68941 | GEO

Response of HK-2 cells to stimulation with IL6 and TNF-alpha (90 minutes)

2015-07-01 | GSE68940 | GEO

Opposing Roles of STAT1 and STAT3 in IL-21 Function in CD4+ T cells

Project description:Interleukin-21 (IL-21) is a type 1 cytokine essential for immune cell differentiation and function. Although IL-21 can activate several STAT family transcription factors, previous studies focused mainly on the role of STAT3 in IL-21 signaling. Here, we investigated the role of STAT1 and show that STAT1 and STAT3 have at least partially opposing roles in IL-21 signaling in CD4+ T cells. IL-21 induced STAT1 phosphorylation, and this was augmented in Stat3-deficient CD4+ T cells. RNA-Seq analysis of CD4+ T cells from Stat1- and Stat3-deficient mice revealed that both STAT1 and STAT3 are critical for IL-21-mediated gene regulation. Expression of some genes, including Tbx21 and Ifng, was differentially regulated by STAT1 and STAT3, and interestingly, ChIP-Seq analysis showed that STAT3 binding at Tbx21 and Ifng loci was attenuated in Stat1-deficient cells. Moreover, opposing actions of STAT1 and STAT3 on IFN- expression in CD4+ T cells were demonstrated in vivo during chronic lymphocytic choriomeningitis (LCMV) infection. Finally, IL-21-mediated induction of STAT1 phosphorylation, as well as IFNG and TBX21 expression, were higher in CD4+ T cells from patients with autosomal dominant hyper-IgE syndrome (AD-HIES), which is caused by STAT3 deficiency. These data indicate an interplay between STAT1 and STAT3 in fine-tuning IL-21 actions. Genome-wide transcription factors mapping and binding of STAT3 in mouse CD4+ T cells in both WT and Stat1-deficient mice. RNA-Seq is performed in mouse CD4+ T cells in WT, Stat1-deficient and Stat3-deficient mice.

2015-07-01 | E-GEOD-63204 | biostudies-arrayexpress

Asymmetry of STAT action in driving IL-27 and IL-6 transcriptional outputs and cytokine specificity

Project description:IL-6 and IL-27 have antagonistic and overlapping functions, signal through a shared receptor subunit and employ the same downstream STAT proteins. To evaluate the degree of specificity and redundancy for these cytokines, we quantified global transcriptomic changes induced by the two cytokines and determined the relative contributions of STAT1 and STAT3 using genetic models and ChIP-seq. We found a high degree of overlap of the transcriptomes induced by IL-6 and IL-27 and extremely few examples in which the cytokines acted in opposition. Using STAT deficient cells and T cells from patients with gain-of-function STAT1 mutations, we show that STAT3 was responsible for the overall transcriptional output driven by both cytokines, whereas STAT1 was the driver of cytokine specificity. STAT1 did not compensate for the lack STAT3; on the contrary, much of STAT1 binding to chromatin was STAT3 dependent. Thus, STAT1 shapes the specific cytokine signature superimposed upon STAT3’s action. Integrated analysis of transcriptome and transcription factor binding data from cytokine treated CD4+T cells

2015-05-27 | E-GEOD-65621 | biostudies-arrayexpress

ChIP seq: STAT1 and STAT3 transcription factors sense and interpret changes in inflammation through engagement of specific enhancers

Project description:Using ChIP-Seq analysis we explore regulation of gene expression changes during inflammatory peritonitis induced by challenge with bacterial ligands administered via the intra-peritoneal route. A resuspended lypholised supernatant of Staphylococcus epidermidis (SES) was administered with or without ex vivo generated CD4+ T-cells (Th1-polarised) to understand the role of adaptive immune responses in shaping inflammatory processes. To study the role of Signal transducer and Activator of Transcription 1 and 3 (STAT1/STAT3) we performed ChIP-seq on peritoneal membrane sections isolated from wt and Il-6 knockout mice three hours post-challenge. Membrane sections were snap frozen in liquid nitrogen prior to downstream processing using established ChIP-seq protocols (Illumina Truseq).

2022-04-04 | E-MTAB-10758 | biostudies-arrayexpress

Asymmetry of STAT action in driving IL-27 and IL-6 transcriptional outputs and cytokine specificity

2015-05-27 | GSE65621 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data