EMBO ReportsMolecular BiologyPeer-reviewed journal article
The proximity-based protein interaction landscape of the transcription factor p65 NF-kappaB/RELA and its gene-regulatory logics
Lisa Leib, J. Unternaehrer Juli, Liane Jurida, Christin Mayr‐Buro, Jasmin PriesteriD, Hendrik Weiser, Stefanie Wirth, Simon Hanel, Daniel HeylmanniD, Axel WeberiD, Michael Lienhard SchmitziD, Argyris PapantonisiD, Marek BartkuhniD, Jochen WilhelmiD, Uwe LinneiD, Johanna Meier‐SoelchiD, Michael KrachtiD
Abstract
The protein interactome of p65 / RELA, the most active subunit of the transcription factor (TF) NF-{kappa}B, has not been previously determined in living cells. Using p65-miniTurbo fusion proteins, we identified by biotin tagging > 350 RELA interactors from untreated and IL-1-stimulated cells, including many TFs (47 % of all interactors) and > 50 epigenetic regulators belonging to different classes of chromatin remodeling complexes. According to point mutants of p65, the interactions primarily require intact dimerization rather than DNA binding properties. A targeted RNAi screen for 38 interactors and subsequent functional transcriptome and bioinformatics studies identified gene regulatory (sub)networks, each controlled by RELA in combination with one of the TFs ZBTB5, GLIS2, TFE3 / TFEB or S100A8 / A9. The remarkably large, dynamic and versatile high resolution interactome of RELA and its gene-regulatory logics provides a rich resource and a new framework for explaining how RELA cooperativity determines gene expression patterns. HighlightsO_LIIdentification of > 350 largely dimerization-dependent interactors of p65 / RELA by miniTurboID C_LIO_LIThe interactome is dominated by transcription factors and epigenetic regulator complexes C_LIO_LIFunctional validation of 38 high confidence interactors by targeted siRNA screen C_LIO_LIIdentification of genetic networks regulated by RELA and six of its interactors in the IL-1 response C_LI
- organism: human
- assay: proteomics
- research focus: cell type annotation
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: protein structure prediction
- approach: experimental assay
- Citations
- 6
- FWCI
- 2.24
- Field percentile
- top 14%
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