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Comprehensive logic based analyses of Toll-like receptor 4 signal transduction pathway.

Padwal MK, Sarma U, Saha B - PLoS ONE (2014)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Lab-5, National Center for Cell Science, Pune, Maharashtra, India.

ABSTRACT
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.

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Relative participation of phosphatases in feedback loops.Figures show number of remaining feedback loops in different phosphatases knockout conditions.
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pone-0092481-g003: Relative participation of phosphatases in feedback loops.Figures show number of remaining feedback loops in different phosphatases knockout conditions.

Mentions: An important element in the feedback loops are the phosphatase of the network [14]. Our simulations identify 360 feedback loops, of which 157 were negative and 203 were positive feedback loops. Most of these feedback loops emerged from the kinase-phosphatase interactions in the network. We explored the role of phosphatases involved in TLR4 signaling and calculated their contribution in the total feedback loops of the network. Figure 3 shows the schematics of relative contribution of different phosphatases, alone and in combinations in determining the total number of feedback loops in the system. To decipher the relative contribution of various phosphatases we systematically knocked out a target phosphatase and calculated the remaining feedback loops for each of the knockout conditions (Figure 3). The phosphatase PP1, as we found from the in-silico knock down, is the most contributory phosphatase in determining the total number of feedback loops (Figure 3) as ∼93% (334 out of 360) feedback loops required PP1 as an essential component.


Comprehensive logic based analyses of Toll-like receptor 4 signal transduction pathway.

Padwal MK, Sarma U, Saha B - PLoS ONE (2014)

Relative participation of phosphatases in feedback loops.Figures show number of remaining feedback loops in different phosphatases knockout conditions.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3974726&req=5

pone-0092481-g003: Relative participation of phosphatases in feedback loops.Figures show number of remaining feedback loops in different phosphatases knockout conditions.
Mentions: An important element in the feedback loops are the phosphatase of the network [14]. Our simulations identify 360 feedback loops, of which 157 were negative and 203 were positive feedback loops. Most of these feedback loops emerged from the kinase-phosphatase interactions in the network. We explored the role of phosphatases involved in TLR4 signaling and calculated their contribution in the total feedback loops of the network. Figure 3 shows the schematics of relative contribution of different phosphatases, alone and in combinations in determining the total number of feedback loops in the system. To decipher the relative contribution of various phosphatases we systematically knocked out a target phosphatase and calculated the remaining feedback loops for each of the knockout conditions (Figure 3). The phosphatase PP1, as we found from the in-silico knock down, is the most contributory phosphatase in determining the total number of feedback loops (Figure 3) as ∼93% (334 out of 360) feedback loops required PP1 as an essential component.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Lab-5, National Center for Cell Science, Pune, Maharashtra, India.

ABSTRACT
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.

Show MeSH
Related in: MedlinePlus