Powered by OpenAIRE graph

RelA and RelB-dependent transcriptome analysis in lymphotoxin-ß receptor stimulated mouse embryonic fibroblasts

RelA and RelB-dependent transcriptome analysis in lymphotoxin-ß receptor stimulated mouse embryonic fibroblasts

Abstract

Background: Lymphotoxin signaling via the lymphotoxin-ß receptor (LTßR) has been implicated in several biological processes, ranging from development of secondary lymphoid organs, maintenance of splenic tissue, host defense against pathogens, autoimmunity, and lipid homeostasis. The major transcription factor that is activated by LTßR crosslinking is NF-?B. Two signaling pathways have been described that result in the activation of classical p50-RelA and alternative p52-RelB NF-?B heterodimers. Results: Using microarray analysis, we investigated the transcriptional response downstream of the LTßR in mouse embryoni fibroblasts (MEF) and its regulation by the RelA and RelB subunits of NF-?B. We describe novel LTßR-responsive genes that are regulated by RelA and/or RelB. Interestingly, we found that the majority of LTßR-regulated genes require the presence of both RelA and RelB, suggesting significant crosstalk between the two NF-?B activation pathways. Gene Ontology (GO) analysis confirmed that LTßR-NF-?B target genes are predominantly involved in the regulation of immune responses. However, other biological processes, such as apoptosis/cell death, cell cycle, angiogenesis, and taxis were also regulated by LTßR signaling. Moreover, we show that activation of the LTßR inhibits the expression of a key adipogenic transcription factor, peroxisome proliferator activated receptor-? (pparg), suggesting that LTßR signaling may interfere with adipogenic differentiation. Conclusions: Thus, microarray analysis of LTßR-stimulated fibroblasts revealed further insight into the transcriptional response of LTßR signaling and its regulation by the NF-?B family members RelA and RelB. Keywords: cell type comparison (wt vs relA-/- vs relB-/-) after genetic modification using a time course Overall design: for each cell type (wt, relA-/-, relB-/-) two time points were analysed (0h as control and 10h) using 3 technical replicates resulting in 18 samples in total

Keywords

Transcriptomics

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average