ABIN-1 negatively regulates NF-κB by inhibiting processing of the p105 precursor
ABSTRACT p105 plays dual roles in NF-kappaB signaling: in its precursor form it inhibits NF-kappaB activation, but limited processing by the ubiquitin system generates the p50 active subunit of the transcription factor. Here we show that ABIN-1, an A20-binding protein that is also known to attenuate NF-kappaB activation, inhibits p105 processing. p105 and ABIN-1 physically interact with one another, but the binding is not necessary for inhibition of processing. Rather, it appears to stabilize ABIN-1 and to increase its level, which further augments its inhibitory effect. Deletion of the processing inhibitory domain (PID) of p105 abrogates the inhibition which also requires the ABIN homology domain (AHD)-2 of ABIN-1. Together, the effects of ABIN-1 on p105 processing and of p105 on stabilizing ABIN-1 act to potentiate the NF-kappaB inhibitory activity of ABIN-1.
- SourceAvailable from: Qi Wu
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- "TNIP1, also known as A20 binding inhibitors of NF-κB (ABIN1), can interact with TNFAIP3 and IκB kinase γ/NF-κB essential modulator (IKKγ/NEMO) and acts as a negative regulator of NF-κB signal pathway . Additionally, TNIP1 was also involved in inhibiting the processing of the p105, a precursor of NF-κB . It has been reported that SNP rs7708392 (C/G) on 5q33.1 that resides within an intron of TNIP1 is associated with the disease risk of SLE in the Caucasian population . "
ABSTRACT: Background. TNFα-induced protein 3 (TNFAIP3) interacting with protein 1 (TNIP1) acts as a negative regulator of NF-κB and plays an important role in maintaining the homeostasis of immune system. A recent genome-wide association study (GWAS) showed that the polymorphism of TNIP1 was associated with the disease risk of SLE in Caucasian. In this study, we investigated whether the association of TNIP1 with SLE was replicated in Chinese population. Methods. The association of TNIP1 SNP rs7708392 (G/C) was determined by high resolution melting (HRM) analysis with unlabeled probe in 285 SLE patients and 336 healthy controls. Results. A new SNP rs79937737 located on 5 bp upstream of rs7708392 was discovered during the HRM analysis. No association of rs7708392 or rs79937737 with the disease risk of SLE was found. Furthermore, rs7708392 and rs79937737 were in weak linkage disequilibrium (LD). Hypotypes analysis of the two SNPs also showed no association with SLE in Chinese population. Conclusions. High resolution melting analysis with unlabeled probes proves to be a powerful and efficient genotyping method for identifying and screening SNPs. No association of rs7708392 or rs79937737 with the disease risk of SLE was observed in Chinese population.07/2012; 2012:265823. DOI:10.1155/2012/265823
Journal of Genetics 04/2010; 90(1):e10-20. DOI:10.1007/s12041-011-0025-6 · 1.01 Impact Factor
- "The A20-binding inhibitor of NF-κB activation (ABIN-1), also named as Naf1 (Nef-associated factor-1) or TNIP1 (TNFAIP3-interacting protein 1) is proved to bind A20 and modulates the inhibitory effect of A20 on NF-κB signalling (Fukushi et al. 1999; Cohen et al. 2009; Verstrepen et al. 2009). NF-κB play a role in the modulation of genes expressed in trophoblast giant cells during the course of early embryogenesis, and is therefore relevant to tissue remodelling and morphogenesis of placenta (Muggia et al. 1999). "
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ABSTRACT: Author Summary Glucocorticoids (GCs) are steroid hormones produced by the human body in response to environmental stressors. Despite their key role as physiological regulators and widely administered pharmaceuticals, little is known about the genetic basis of inter-individual and inter-ethnic variation in GC response. As GC action is mediated by the regulation of gene expression, we profiled transcript abundance and protein secretion in EBV-transformed B lymphocytes from a panel of 114 individuals, including those of both African and European ancestry. Combining these molecular traits with genome-wide genetic data, we found that genotype-treatment interactions at polymorphisms near genes affected GC regulation of expression for 26 genes and of secretion for IL6. A novel statistical approach revealed that these interactions could be distinguished into distinct types, with some showing genotypic effects only in GC-treated samples and others showing genotypic effects only in control-treated samples, with differing phenotypic and molecular interpretations. The insights into the genetic basis of variation in GC response and the statistical tools for identifying gene-treatment interactions that we provide will aid future efforts to identify genetic predictors of response to this and other treatments.PLoS Genetics 07/2011; 7(7):e1002162. DOI:10.1371/journal.pgen.1002162 · 8.17 Impact Factor