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Computational modeling of the EGFR network elucidates control mechanisms regulating signal dynamics.

Wang DY, Cardelli L, Phillips A, Piterman N, Fisher J - BMC Syst Biol (2009)

Bottom Line: Our analysis, done through simulation of various perturbations, suggests that the EGFR pathway contains regions of functional redundancy in the upstream parts; in the event of low EGF stimulus or partial system failure, this redundancy helps to maintain functional robustness.Simulation of this abstract model suggests that without redundancies in the upstream modules, signal transduction through the entire pathway could be attenuated.The insights gained from simulating this executable model facilitate the formulation of specific hypotheses regarding the control mechanisms of the EGFR signaling, and further substantiate the benefit to construct abstract executable models of large complex biological networks.

View Article: PubMed Central - HTML - PubMed

Affiliation: MRC Biostatistics Unit, University of Cambridge, Cambridge, UK. dyqw2@cam.ac.uk

ABSTRACT

Background: The epidermal growth factor receptor (EGFR) signaling pathway plays a key role in regulation of cellular growth and development. While highly studied, it is still not fully understood how the signal is orchestrated. One of the reasons for the complexity of this pathway is the extensive network of inter-connected components involved in the signaling. In the aim of identifying critical mechanisms controlling signal transduction we have performed extensive analysis of an executable model of the EGFR pathway using the stochastic pi-calculus as a modeling language.

Results: Our analysis, done through simulation of various perturbations, suggests that the EGFR pathway contains regions of functional redundancy in the upstream parts; in the event of low EGF stimulus or partial system failure, this redundancy helps to maintain functional robustness. Downstream parts, like the parts controlling Ras and ERK, have fewer redundancies, and more than 50% inhibition of specific reactions in those parts greatly attenuates signal response. In addition, we suggest an abstract model that captures the main control mechanisms in the pathway. Simulation of this abstract model suggests that without redundancies in the upstream modules, signal transduction through the entire pathway could be attenuated. In terms of specific control mechanisms, we have identified positive feedback loops whose role is to prolong the active state of key components (e.g., MEK-PP, Ras-GTP), and negative feedback loops that help promote signal adaptation and stabilization.

Conclusions: The insights gained from simulating this executable model facilitate the formulation of specific hypotheses regarding the control mechanisms of the EGFR signaling, and further substantiate the benefit to construct abstract executable models of large complex biological networks.

Show MeSH
Molecular profiles of molecular components at different EGF concentrations. 50 ng/ml(green line), 25 ng/ml (blue line), and 0.5 ng/ml (red line). The (EGF-EGFR*)2 indicates the dimerized and autophosphorylated form of the EGF receptor. Shc* and Raf* is the phosphorylated form of cellular Shc and Raf. Ras-GTP is the formed complex of Ras and GTP. MEK-PP and ERK-PP are the doubly phosphorylated forms of MEK and ERK.
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Figure 2: Molecular profiles of molecular components at different EGF concentrations. 50 ng/ml(green line), 25 ng/ml (blue line), and 0.5 ng/ml (red line). The (EGF-EGFR*)2 indicates the dimerized and autophosphorylated form of the EGF receptor. Shc* and Raf* is the phosphorylated form of cellular Shc and Raf. Ras-GTP is the formed complex of Ras and GTP. MEK-PP and ERK-PP are the doubly phosphorylated forms of MEK and ERK.

Mentions: Our model of the EGFR signaling pathway is an updated version of previous models [17,21]. It is comprised of 148 molecular processes and 103 variable molecular species (Figure 1, Additional File 1). The signal cascade is initiated by induction of EGF to the system in the presence of other signaling molecules. We traced the dynamics of several important contributors to the signal cascade at varying levels of EGF stimulus, as shown in Figure 2. Results of these simulations are compared to simulations of previous models [17,21]. The close resemblance of simulations serves as a sanity check to the correctness of our translation from a mathematical to a computational model.


Computational modeling of the EGFR network elucidates control mechanisms regulating signal dynamics.

Wang DY, Cardelli L, Phillips A, Piterman N, Fisher J - BMC Syst Biol (2009)

Molecular profiles of molecular components at different EGF concentrations. 50 ng/ml(green line), 25 ng/ml (blue line), and 0.5 ng/ml (red line). The (EGF-EGFR*)2 indicates the dimerized and autophosphorylated form of the EGF receptor. Shc* and Raf* is the phosphorylated form of cellular Shc and Raf. Ras-GTP is the formed complex of Ras and GTP. MEK-PP and ERK-PP are the doubly phosphorylated forms of MEK and ERK.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2807436&req=5

Figure 2: Molecular profiles of molecular components at different EGF concentrations. 50 ng/ml(green line), 25 ng/ml (blue line), and 0.5 ng/ml (red line). The (EGF-EGFR*)2 indicates the dimerized and autophosphorylated form of the EGF receptor. Shc* and Raf* is the phosphorylated form of cellular Shc and Raf. Ras-GTP is the formed complex of Ras and GTP. MEK-PP and ERK-PP are the doubly phosphorylated forms of MEK and ERK.
Mentions: Our model of the EGFR signaling pathway is an updated version of previous models [17,21]. It is comprised of 148 molecular processes and 103 variable molecular species (Figure 1, Additional File 1). The signal cascade is initiated by induction of EGF to the system in the presence of other signaling molecules. We traced the dynamics of several important contributors to the signal cascade at varying levels of EGF stimulus, as shown in Figure 2. Results of these simulations are compared to simulations of previous models [17,21]. The close resemblance of simulations serves as a sanity check to the correctness of our translation from a mathematical to a computational model.

Bottom Line: Our analysis, done through simulation of various perturbations, suggests that the EGFR pathway contains regions of functional redundancy in the upstream parts; in the event of low EGF stimulus or partial system failure, this redundancy helps to maintain functional robustness.Simulation of this abstract model suggests that without redundancies in the upstream modules, signal transduction through the entire pathway could be attenuated.The insights gained from simulating this executable model facilitate the formulation of specific hypotheses regarding the control mechanisms of the EGFR signaling, and further substantiate the benefit to construct abstract executable models of large complex biological networks.

View Article: PubMed Central - HTML - PubMed

Affiliation: MRC Biostatistics Unit, University of Cambridge, Cambridge, UK. dyqw2@cam.ac.uk

ABSTRACT

Background: The epidermal growth factor receptor (EGFR) signaling pathway plays a key role in regulation of cellular growth and development. While highly studied, it is still not fully understood how the signal is orchestrated. One of the reasons for the complexity of this pathway is the extensive network of inter-connected components involved in the signaling. In the aim of identifying critical mechanisms controlling signal transduction we have performed extensive analysis of an executable model of the EGFR pathway using the stochastic pi-calculus as a modeling language.

Results: Our analysis, done through simulation of various perturbations, suggests that the EGFR pathway contains regions of functional redundancy in the upstream parts; in the event of low EGF stimulus or partial system failure, this redundancy helps to maintain functional robustness. Downstream parts, like the parts controlling Ras and ERK, have fewer redundancies, and more than 50% inhibition of specific reactions in those parts greatly attenuates signal response. In addition, we suggest an abstract model that captures the main control mechanisms in the pathway. Simulation of this abstract model suggests that without redundancies in the upstream modules, signal transduction through the entire pathway could be attenuated. In terms of specific control mechanisms, we have identified positive feedback loops whose role is to prolong the active state of key components (e.g., MEK-PP, Ras-GTP), and negative feedback loops that help promote signal adaptation and stabilization.

Conclusions: The insights gained from simulating this executable model facilitate the formulation of specific hypotheses regarding the control mechanisms of the EGFR signaling, and further substantiate the benefit to construct abstract executable models of large complex biological networks.

Show MeSH