Comprehensive logic based analyses of Toll-like receptor 4 signal transduction pathway.
Among the 13 TLRs in the vertebrate systems, only TLR4 utilizes both Myeloid differentiation factor 88 (MyD88) and Toll/Interleukin-1 receptor (TIR)-domain-containing adapter interferon-β-inducing Factor (TRIF) adaptors to transduce signals triggering host-protective immune responses. Earlier studies on the pathway combined various experimental data in the form of one comprehensive map of TLR signaling. But in the absence of adequate kinetic parameters quantitative mathematical models that reveal emerging systems level properties and dynamic inter-regulation among the kinases/phosphatases of the TLR4 network are not yet available. So, here we used reaction stoichiometry-based and parameter independent logical modeling formalism to build the TLR4 signaling network model that captured the feedback regulations, interdependencies between signaling kinases and phosphatases and the outcome of simulated infections. The analyses of the TLR4 signaling network revealed 360 feedback loops, 157 negative and 203 positive; of which, 334 loops had the phosphatase PP1 as an essential component. The network elements' interdependency (positive or negative dependencies) in perturbation conditions such as the phosphatase knockout conditions revealed interdependencies between the dual-specific phosphatases MKP-1 and MKP-3 and the kinases in MAPK modules and the role of PP2A in the auto-regulation of Calmodulin kinase-II. Our simulations under the specific kinase or phosphatase gene-deficiency or inhibition conditions corroborated with several previously reported experimental data. The simulations to mimic Yersinia pestis and E. coli infections identified the key perturbation in the network and potential drug targets. Thus, our analyses of TLR4 signaling highlights the role of phosphatases as key regulatory factors in determining the global interdependencies among the network elements; uncovers novel signaling connections; identifies potential drug targets for infections.
Lab-5, National Center for Cell Science, Pune, Maharashtra, India.
Mahesh Kumar
MK
Padwal
Lab-5, National Center for Cell Science, Pune, Maharashtra, India.
Uddipan
U
Sarma
Lab-5, National Center for Cell Science, Pune, Maharashtra, India.
Bhaskar
B
Saha
D000818:Animals; D003198:Computer Simulation; D004926:Escherichia coli / Q000502:physiology; D004927:Escherichia coli Infections / Q000235:genetics / Q000378:metabolism* / Q000382:microbiology; D025461:Feedback, Physiological; D053263:Gene Regulatory Networks; D051379:Mice; D018345:Mice, Knockout; D008962:Models, Theoretical; D010744:Phosphoric Monoester Hydrolases / Q000037:antagonists & inhibitors / Q000378:metabolism; D010930:Plague / Q000235:genetics / Q000378:metabolism* / Q000382:microbiology; D015398:Signal Transduction; D051197:Toll-Like Receptor 4 / Q000235:genetics / Q000378:metabolism*; D015010:Yersinia pestis / Q000502:physiology
D051197:Toll-Like Receptor 4; D010744:Phosphoric Monoester Hydrolases