Quantitative Modeling of TLR Signaling Reveals Missing Negative Feedback Guiding Identification of TANK-IKKε Checkpoint
Nathan P. ManesiD, Fengkai Zhang, Bin Lin, Jing SuniD, Sergio A. HassaniD, Anthony A. Armstrong, Yuting Shao, Jessica M. Calzola, Pauline R. Kaplan-Stafford, Rachel A. GottschalkiD, Matthew J. MarinoiD, Doeun KimiD, Ronald N. GermainiD, Martin Meier‐SchellersheimiD, Iain D. C. FraseriD, Aleksandra Nita‐LazariD
Abstract
Toll-like receptor (TLR) signaling must be activated rapidly and then terminated to support host defense without sustained inflammation. We developed a rule-based model of mouse macrophage TLR4 signaling at the molecular-interaction level using measured protein copy numbers, RNA-seq-based abundance estimates, literature- and structure-informed reaction rates, and 979 dynamic experimental constraints. The trained model reproduced much of the TLR4-induced NF-{kappa}B and MAP kinase response but consistently failed to capture deactivation of MyD88, TRAF6-associated species, and IKK/{beta}. The recurrent model failure conveyed important biological information, localizing missing regulation to the proximal MyD88-IRAK-TRAF6 module and guiding experimental evaluation of IKK{varepsilon} and its scaffold TANK. Loss of IKK{varepsilon} enhanced transcriptional, cytokine, MAP kinase, and NF-{kappa}B responses to MyD88-specific TLR ligands. TANK deficiency produced a similar cellular phenotype and abolished stimulus-induced IKK{varepsilon} phosphorylation. Deficiency of either protein increased IRAK1 and TRAF6 ubiquitination without increasing MyD88 ubiquitination, placing the inhibitory checkpoint at or immediately downstream of the IRAK1-TRAF6 ubiquitin-signaling node. Overlapping but non-identical in vivo phenotypes further supported a shared regulatory axis with additional protein-specific functions. Our study presents a model-experiment discovery cycle where quantitative pathway discordance identifies missing biology and reveals a TANK-dependent IKK{varepsilon} checkpoint that restrains MyD88-driven inflammation.
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