Systems analysis identifies an essential role for SHANK-associated RH domain-interacting protein (SHARPIN) in macrophage Toll-like receptor 2 (TLR2) responses.

Precise control of the innate immune response is essential to ensure host defense against infection while avoiding inflammatory disease. Systems-level analyses of Toll-like receptor (TLR)-stimulated macrophages suggested that SHANK-associated RH domain-interacting protein (SHARPIN) might play a role in the TLR pathway. This hypothesis was supported by the observation that macrophages derived from chronic proliferative dermatitis mutation (cpdm) mice, which harbor a spontaneous null mutation in the Sharpin gene, exhibited impaired IL-12 production in response to TLR activation. Systems biology approaches were used to define the SHARPIN-regulated networks. Promoter analysis identified NF-κB and AP-1 as candidate transcription factors downstream of SHARPIN, and network analysis suggested selective attenuation of these pathways. We found that the effects of SHARPIN deficiency on the TLR2-induced transcriptome were strikingly correlated with the effects of the recently described hypomorphic L153P/panr2 point mutation in Ikbkg [NF-κB Essential Modulator (NEMO)], suggesting that SHARPIN and NEMO interact. We confirmed this interaction by co-immunoprecipitation analysis and furthermore found it to be abrogated by panr2. NEMO-dependent signaling was affected by SHARPIN deficiency in a manner similar to the panr2 mutation, including impaired p105 and ERK phosphorylation and p65 nuclear localization. Interestingly, SHARPIN deficiency had no effect on IκBα degradation and on p38 and JNK phosphorylation. Taken together, these results demonstrate that SHARPIN is an essential adaptor downstream of the branch point defined by the panr2 mutation in NEMO.

Genome-wide histone acetylation data improve prediction of mammalian transcription factor binding sites.

MOTIVATION: Histone acetylation (HAc) is associated with open chromatin, and HAc has been shown to facilitate transcription factor (TF) binding in mammalian cells. In the innate immune system context, epigenetic studies strongly implicate HAc in the transcriptional response of activated macrophages. We hypothesized that using data from large-scale sequencing of a HAc chromatin immunoprecipitation assay (ChIP-Seq) would improve the performance of computational prediction of binding locations of TFs mediating the response to a signaling event, namely, macrophage activation. RESULTS: We tested this hypothesis using a multi-evidence approach for predicting binding sites. As a training/test dataset, we used ChIP-Seq-derived TF binding site locations for five TFs in activated murine macrophages. Our model combined TF binding site motif scanning with evidence from sequence-based sources and from HAc ChIP-Seq data, using a weighted sum of thresholded scores. We find that using HAc data significantly improves the performance of motif-based TF binding site prediction. Furthermore, we find that within regions of high HAc, local minima of the HAc ChIP-Seq signal are particularly strongly correlated with TF binding locations. Our model, using motif scanning and HAc local minima, improves the sensitivity for TF binding site prediction by approximately 50% over a model based on motif scanning alone, at a false positive rate cutoff of 0.01. AVAILABILITY: The data and software source code for model training and validation are freely available online at http://magnet.systemsbiology.net/hac.