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An integrative framework reveals signaling-to-transcription events in toll-like receptor signaling

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Item Type:Article
Title:An integrative framework reveals signaling-to-transcription events in toll-like receptor signaling
Creators Name:Mertins, P., Przybylski, D., Yosef, N., Qiao, J., Clauser, K., Raychowdhury, R., Eisenhaure, T.M., Maritzen, T., Haucke, V., Satoh, T., Akira, S., Carr, S.A., Regev, A., Hacohen, N. and Chevrier, N.
Abstract:Building an integrated view of cellular responses to environmental cues remains a fundamental challenge due to the complexity of intracellular networks in mammalian cells. Here, we introduce an integrative biochemical and genetic framework to dissect signal transduction events using multiple data types and, in particular, to unify signaling and transcriptional networks. Using the Toll-like receptor (TLR) system as a model cellular response, we generate multifaceted datasets on physical, enzymatic, and functional interactions and integrate these data to reveal biochemical paths that connect TLR4 signaling to transcription. We define the roles of proximal TLR4 kinases, identify and functionally test two dozen candidate regulators, and demonstrate a role for Ap1ar (encoding the Gadkin protein) and its binding partner, Picalm, potentially linking vesicle transport with pro-inflammatory responses. Our study thus demonstrates how deciphering dynamic cellular responses by integrating datasets on various regulatory layers defines key components and higher-order logic underlying signaling-to-transcription pathways.
Keywords:Pathogen-Sensing Pathways, Toll-Like Receptors, TLRs, Phosphoproteomics, Protein-Protein Interactions, Large-Scale In Vitro Kinase Assay, Signaling, Transcriptional Network Analysis
Source:Cell Reports
ISSN:2211-1247
Publisher:Cell Press / Elsevier
Volume:19
Number:13
Page Range:2853-2866
Date:27 June 2017
Official Publication:https://doi.org/10.1016/j.celrep.2017.06.016
PubMed:View item in PubMed

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