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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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Connectivity diagram of key components in the EGFR signaling pathway. Each gate represents a series of reactions resulting in the production of the substance connected to the curved side. The substances connected to the flat side of a gate are the inputs. The initial inputs are set by the state of EGF species (internal and external). The connections show all paths between key components in the EGFR signaling pathway. Red connections indicate inhibition and all others activation. A connection is colored black or green if inactivation of the input disables activation of the output. Disconnection of one of the substances in orange or red does not affect activity of the output. The diagram clearly shows which paths carry signal that do not affect the overall activation of the component (red and orange wires), and which paths carry signals that are necessary to activate the component (green and black wires).
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Figure 6: Connectivity diagram of key components in the EGFR signaling pathway. Each gate represents a series of reactions resulting in the production of the substance connected to the curved side. The substances connected to the flat side of a gate are the inputs. The initial inputs are set by the state of EGF species (internal and external). The connections show all paths between key components in the EGFR signaling pathway. Red connections indicate inhibition and all others activation. A connection is colored black or green if inactivation of the input disables activation of the output. Disconnection of one of the substances in orange or red does not affect activity of the output. The diagram clearly shows which paths carry signal that do not affect the overall activation of the component (red and orange wires), and which paths carry signals that are necessary to activate the component (green and black wires).

Mentions: As a result of our simulations under extensive perturbation of the computational model, we can generate dependence relationships between key components in the EGFR signaling pathway. We exhaustively examined all conditions across the EGFR signaling pathway where components achieve active and inactive states. Activity/inactivity values for the molecular activities were compiled for each key component in order to map dependency of activity between these components. The resulting dependencies are summarized in Figure 6. The diagram includes all the interface components from Figure 1; interfaces are connected if one is the input to a module and the other is the output of a module or if the connection between them in Figure 1 is between the modules. That is, two interface components are connected in this diagram if they are connected in the full model in the same module or the connection between them does not pass other interfaces. We try to simplify the connection between these interfaces by concentrating only on their activity/inactivity state and deduce whether a component is required for the activation of another component or not (Additional Files 9, 10, 11, 12, 13, 14, 15, 16, and 17). A molecular component is defined as active if its observed profile corresponds to a profile of ERK-PP, where there are at least 5000 molecules for a period of 60 minutes. We inhibit specific reactions (column headings of Additional Files 9, 10, 11, 12, 13, 14, 15, 16, and 17) to generate the various knock-out conditions needed for inferring which connections are required or not. A connection is colored black or green if inactivation of the input disables activation of the output. Inactivation of one of the substances in orange or red does not affect activity of the output. In the case that a substance has only orange connections then one is required for activation but not both. The red connections denote inhibition and all others activation. Therefore, this representation of the EGFR signaling pathway provides a summary of the key mechanisms controlling signal transduction between components, and also suggests an intuitive way of understanding how the activation or inactivation of each component can affect the whole system. This representation captures the relations between substances but is not intended to be perceived as purely Boolean. We stress that deactivation of a red/orange input may still affect the amplitude or duration of activity of the signal, however, it remains active.


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)

Connectivity diagram of key components in the EGFR signaling pathway. Each gate represents a series of reactions resulting in the production of the substance connected to the curved side. The substances connected to the flat side of a gate are the inputs. The initial inputs are set by the state of EGF species (internal and external). The connections show all paths between key components in the EGFR signaling pathway. Red connections indicate inhibition and all others activation. A connection is colored black or green if inactivation of the input disables activation of the output. Disconnection of one of the substances in orange or red does not affect activity of the output. The diagram clearly shows which paths carry signal that do not affect the overall activation of the component (red and orange wires), and which paths carry signals that are necessary to activate the component (green and black wires).
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 6: Connectivity diagram of key components in the EGFR signaling pathway. Each gate represents a series of reactions resulting in the production of the substance connected to the curved side. The substances connected to the flat side of a gate are the inputs. The initial inputs are set by the state of EGF species (internal and external). The connections show all paths between key components in the EGFR signaling pathway. Red connections indicate inhibition and all others activation. A connection is colored black or green if inactivation of the input disables activation of the output. Disconnection of one of the substances in orange or red does not affect activity of the output. The diagram clearly shows which paths carry signal that do not affect the overall activation of the component (red and orange wires), and which paths carry signals that are necessary to activate the component (green and black wires).
Mentions: As a result of our simulations under extensive perturbation of the computational model, we can generate dependence relationships between key components in the EGFR signaling pathway. We exhaustively examined all conditions across the EGFR signaling pathway where components achieve active and inactive states. Activity/inactivity values for the molecular activities were compiled for each key component in order to map dependency of activity between these components. The resulting dependencies are summarized in Figure 6. The diagram includes all the interface components from Figure 1; interfaces are connected if one is the input to a module and the other is the output of a module or if the connection between them in Figure 1 is between the modules. That is, two interface components are connected in this diagram if they are connected in the full model in the same module or the connection between them does not pass other interfaces. We try to simplify the connection between these interfaces by concentrating only on their activity/inactivity state and deduce whether a component is required for the activation of another component or not (Additional Files 9, 10, 11, 12, 13, 14, 15, 16, and 17). A molecular component is defined as active if its observed profile corresponds to a profile of ERK-PP, where there are at least 5000 molecules for a period of 60 minutes. We inhibit specific reactions (column headings of Additional Files 9, 10, 11, 12, 13, 14, 15, 16, and 17) to generate the various knock-out conditions needed for inferring which connections are required or not. A connection is colored black or green if inactivation of the input disables activation of the output. Inactivation of one of the substances in orange or red does not affect activity of the output. In the case that a substance has only orange connections then one is required for activation but not both. The red connections denote inhibition and all others activation. Therefore, this representation of the EGFR signaling pathway provides a summary of the key mechanisms controlling signal transduction between components, and also suggests an intuitive way of understanding how the activation or inactivation of each component can affect the whole system. This representation captures the relations between substances but is not intended to be perceived as purely Boolean. We stress that deactivation of a red/orange input may still affect the amplitude or duration of activity of the signal, however, it remains active.

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