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Functional aspects of the EGF-induced MAP kinase cascade: a complex self-organizing system approach.

Kosmidis EK, Moschou V, Ziogas G, Boukovinas I, Albani M, Laskaris NA - PLoS ONE (2014)

Bottom Line: Our results provide a new "vista" of the EGF-induced MAP kinase cascade, from the perspective of complex self-organizing systems.The six identified groups may provide the means to experimentally follow the dynamics of this complex network.Also, the vulnerability analysis approach may be used for the development of novel therapeutic targets in the context of personalized medicine.

View Article: PubMed Central - PubMed

Affiliation: Laboratory of Physiology, Department of Medicine, Aristotle University of Thessaloniki, University Campus, Thessaloniki, Greece.

ABSTRACT
The EGF-induced MAP kinase cascade is one of the most important and best characterized networks in intracellular signalling. It has a vital role in the development and maturation of living organisms. However, when deregulated, it is involved in the onset of a number of diseases. Based on a computational model describing a "surface" and an "internalized" parallel route, we use systems biology techniques to characterize aspects of the network's functional organization. We examine the re-organization of protein groups from low to high external stimulation, define functional groups of proteins within the network, determine the parameter best encoding for input intensity and predict the effect of protein removal to the system's output response. Extensive functional re-organization of proteins is observed in the lower end of stimulus concentrations. As we move to higher concentrations the variability is less pronounced. 6 functional groups have emerged from a consensus clustering approach, reflecting different dynamical aspects of the network. Mutual information investigation revealed that the maximum activation rate of the two output proteins best encodes for stimulus intensity. Removal of each protein of the network resulted in a range of graded effects, from complete silencing to intense activation. Our results provide a new "vista" of the EGF-induced MAP kinase cascade, from the perspective of complex self-organizing systems. Functional grouping of the proteins reveals an organizational scheme contrasting the current understanding of modular topology. The six identified groups may provide the means to experimentally follow the dynamics of this complex network. Also, the vulnerability analysis approach may be used for the development of novel therapeutic targets in the context of personalized medicine.

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Graphical correspondence between groupings.A schematic representation of how functional groups change from a compositional perspective. The protein groupings for [EGF] = 5, 250, 5000 are compared in pairs. Groups have been ordered in terms of compactness. The color indicates the order of the groups with blue corresponding to the strongest functional cluster. Lines connect the proteins that change group, with the change of [EGF] level.
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pone-0111612-g002: Graphical correspondence between groupings.A schematic representation of how functional groups change from a compositional perspective. The protein groupings for [EGF] = 5, 250, 5000 are compared in pairs. Groups have been ordered in terms of compactness. The color indicates the order of the groups with blue corresponding to the strongest functional cluster. Lines connect the proteins that change group, with the change of [EGF] level.

Mentions: The extensive re-organization of protein function from a compositional perspective when moving from low to high EGF concentrations is illustrated in Fig. 2. Lines connect the proteins that change groups when different [EGF] levels are compared. Increasing [EGF] from 5 to 250 molecules/cell forces virtually all proteins to change clustering groups. Some group proteins either move together in a new cluster or segregate and re-organize in different groups, marking a new functional role. The changes are less pronounced but still in effect when [EGF] is increased from 250 to 5000 molecules/cell.


Functional aspects of the EGF-induced MAP kinase cascade: a complex self-organizing system approach.

Kosmidis EK, Moschou V, Ziogas G, Boukovinas I, Albani M, Laskaris NA - PLoS ONE (2014)

Graphical correspondence between groupings.A schematic representation of how functional groups change from a compositional perspective. The protein groupings for [EGF] = 5, 250, 5000 are compared in pairs. Groups have been ordered in terms of compactness. The color indicates the order of the groups with blue corresponding to the strongest functional cluster. Lines connect the proteins that change group, with the change of [EGF] level.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4221048&req=5

pone-0111612-g002: Graphical correspondence between groupings.A schematic representation of how functional groups change from a compositional perspective. The protein groupings for [EGF] = 5, 250, 5000 are compared in pairs. Groups have been ordered in terms of compactness. The color indicates the order of the groups with blue corresponding to the strongest functional cluster. Lines connect the proteins that change group, with the change of [EGF] level.
Mentions: The extensive re-organization of protein function from a compositional perspective when moving from low to high EGF concentrations is illustrated in Fig. 2. Lines connect the proteins that change groups when different [EGF] levels are compared. Increasing [EGF] from 5 to 250 molecules/cell forces virtually all proteins to change clustering groups. Some group proteins either move together in a new cluster or segregate and re-organize in different groups, marking a new functional role. The changes are less pronounced but still in effect when [EGF] is increased from 250 to 5000 molecules/cell.

Bottom Line: Our results provide a new "vista" of the EGF-induced MAP kinase cascade, from the perspective of complex self-organizing systems.The six identified groups may provide the means to experimentally follow the dynamics of this complex network.Also, the vulnerability analysis approach may be used for the development of novel therapeutic targets in the context of personalized medicine.

View Article: PubMed Central - PubMed

Affiliation: Laboratory of Physiology, Department of Medicine, Aristotle University of Thessaloniki, University Campus, Thessaloniki, Greece.

ABSTRACT
The EGF-induced MAP kinase cascade is one of the most important and best characterized networks in intracellular signalling. It has a vital role in the development and maturation of living organisms. However, when deregulated, it is involved in the onset of a number of diseases. Based on a computational model describing a "surface" and an "internalized" parallel route, we use systems biology techniques to characterize aspects of the network's functional organization. We examine the re-organization of protein groups from low to high external stimulation, define functional groups of proteins within the network, determine the parameter best encoding for input intensity and predict the effect of protein removal to the system's output response. Extensive functional re-organization of proteins is observed in the lower end of stimulus concentrations. As we move to higher concentrations the variability is less pronounced. 6 functional groups have emerged from a consensus clustering approach, reflecting different dynamical aspects of the network. Mutual information investigation revealed that the maximum activation rate of the two output proteins best encodes for stimulus intensity. Removal of each protein of the network resulted in a range of graded effects, from complete silencing to intense activation. Our results provide a new "vista" of the EGF-induced MAP kinase cascade, from the perspective of complex self-organizing systems. Functional grouping of the proteins reveals an organizational scheme contrasting the current understanding of modular topology. The six identified groups may provide the means to experimentally follow the dynamics of this complex network. Also, the vulnerability analysis approach may be used for the development of novel therapeutic targets in the context of personalized medicine.

Show MeSH