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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.

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Behavior of ERK-PP in response to complete inhibition of crucial reactions. For each specific reaction that is inhibited, the molecular profile of ERK-PP is plotted over time.
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Figure 4: Behavior of ERK-PP in response to complete inhibition of crucial reactions. For each specific reaction that is inhibited, the molecular profile of ERK-PP is plotted over time.

Mentions: An important characteristic of the EGFR signaling cascade is its ability to maintain output reproducibility, despite input variation or system perturbation. Design features, like network redundancy, may attribute to this functional robustness. Our first analysis consists of systematic inhibition of each reaction in the model separately. We include in Figure 4 simulation of the pathway under nine different knock-out perturbations. Additional simulations are given in Additional Files 2, 3, 4, 5, 6, 7, and 8. These simulations show regions of robustness in the signaling network. Evidence of robustness in the signaling network is particularly apparent in the Grb2 module, where insensitivity by the system to all single knock-outs is observed. This suggests for the presence of redundancy in the signaling network, which allows for signal sustainability even when parts of the signaling network are inactive. For instance, inhibition of a suggested target for kinase inhibitors, v23, did not have significant affect on signal transduction, except for the slight delay recorded in the activation of ERK. Note that the inhibition of either gateway reactions, v16 (leading to the Shc independent signaling pathway) and v22 (leading to the Shc dependent signaling pathway), do not inhibit ERK activation, but inhibition of both reactions does inhibit ERK activation. Although the EGF module may not contain as much redundancy as the Grb2 module, two pathways leading to the activation of internalized and external EGF receptors contribute to signal transduction. The simulations describe the sole dependence of ERK-PP signal response on the activation of external EGF receptors (v3), but the association of GAP with external receptors to form the EGFR signaling complex (v8) is not a necessary process for signal transduction. The inhibition of the v8 reaction does, however, drastically delay the activation of ERK and limit the amplitude of the signal response. Thus, the contribution of activated, internalized EGF receptors to EGF signaling remains unresolved.


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)

Behavior of ERK-PP in response to complete inhibition of crucial reactions. For each specific reaction that is inhibited, the molecular profile of ERK-PP is plotted over time.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 4: Behavior of ERK-PP in response to complete inhibition of crucial reactions. For each specific reaction that is inhibited, the molecular profile of ERK-PP is plotted over time.
Mentions: An important characteristic of the EGFR signaling cascade is its ability to maintain output reproducibility, despite input variation or system perturbation. Design features, like network redundancy, may attribute to this functional robustness. Our first analysis consists of systematic inhibition of each reaction in the model separately. We include in Figure 4 simulation of the pathway under nine different knock-out perturbations. Additional simulations are given in Additional Files 2, 3, 4, 5, 6, 7, and 8. These simulations show regions of robustness in the signaling network. Evidence of robustness in the signaling network is particularly apparent in the Grb2 module, where insensitivity by the system to all single knock-outs is observed. This suggests for the presence of redundancy in the signaling network, which allows for signal sustainability even when parts of the signaling network are inactive. For instance, inhibition of a suggested target for kinase inhibitors, v23, did not have significant affect on signal transduction, except for the slight delay recorded in the activation of ERK. Note that the inhibition of either gateway reactions, v16 (leading to the Shc independent signaling pathway) and v22 (leading to the Shc dependent signaling pathway), do not inhibit ERK activation, but inhibition of both reactions does inhibit ERK activation. Although the EGF module may not contain as much redundancy as the Grb2 module, two pathways leading to the activation of internalized and external EGF receptors contribute to signal transduction. The simulations describe the sole dependence of ERK-PP signal response on the activation of external EGF receptors (v3), but the association of GAP with external receptors to form the EGFR signaling complex (v8) is not a necessary process for signal transduction. The inhibition of the v8 reaction does, however, drastically delay the activation of ERK and limit the amplitude of the signal response. Thus, the contribution of activated, internalized EGF receptors to EGF signaling remains unresolved.

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