Insulin-signaling is a critical aspect of normal physiology and disease states like diabetes, obesity and cancer. In the presence of Insulin, Insulin receptor (IR) phosphorylates Insulin receptor substrate proteins (IRS) ultimately leading to signaling downstream via phosphatidylinositol 3-kinase (PI3K)-AKT pathway. PI3K-AKT pathway leads to activation of p70S6K1 and release of Eukaryotic translation initiation factor 4E (eIF4E) from its complex with Eukaryotic translation initiation factor 4E- binding protein 1(4E-BP1) culminating in translation initiation. The regulation of translation is a critical step in the control of Eukaryotic proliferation and differentiation programs. In this study, we developed a family of mechanistic models of Insulin-mediated translation regulation, which was composed of a system of ordinary differential equations. The objective of this study was to assemble a series of molecular modules describing different stages of Insulin-mediated regulation of translation initiation and to subsequently analyze these models for fragility and robustness. Kinetic parameters for these models were estimated by comparing simulations with experimental data. Using POETs and a Cross-Validation scheme, we developed an ensemble of models consistent with data. Model analysis clearly reveals that the network as a whole can be classified into three functionally and hierarchically distinct sub-modules: IR-IRS related module, PI3K-AKT module and eIF-ribosomal complexes module. Comparatively the eIF-ribosomal complexes module is the most robust, while the IR-IRS related module is the most fragile. Feedback loops are critical in terms of fragility, with emphasis on the control and role of IRS1. Knockout studies reveal the increased ability of multiple parameter knockouts to qualitatively control translation initiation relative to single parameter knockouts. Coupling analysis supports the criticality and modularity of the network and the importance of feedback loops and importance of species like IRS1, PI3K, AKT and mTORC1.
This preliminary program is subject to change.
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Model of Insulin-Mediated Eukaryotic Translation Initiation Identifies Distinct Functional Sub-Modules Highlighting the Key Role of IRS1 and mTORC1
Insulin-signaling is a critical aspect of normal physiology and disease states like diabetes, obesity and cancer. In the presence of Insulin, Insulin receptor (IR) phosphorylates Insulin receptor substrate proteins (IRS) ultimately leading to signaling downstream via phosphatidylinositol 3-kinase (PI3K)-AKT pathway. PI3K-AKT pathway leads to activation of p70S6K1 and release of Eukaryotic translation initiation factor 4E (eIF4E) from its complex with Eukaryotic translation initiation factor 4E- binding protein 1(4E-BP1) culminating in translation initiation. The regulation of translation is a critical step in the control of Eukaryotic proliferation and differentiation programs. In this study, we developed a family of mechanistic models of Insulin-mediated translation regulation, which was composed of a system of ordinary differential equations. The objective of this study was to assemble a series of molecular modules describing different stages of Insulin-mediated regulation of translation initiation and to subsequently analyze these models for fragility and robustness. Kinetic parameters for these models were estimated by comparing simulations with experimental data. Using POETs and a Cross-Validation scheme, we developed an ensemble of models consistent with data. Model analysis clearly reveals that the network as a whole can be classified into three functionally and hierarchically distinct sub-modules: IR-IRS related module, PI3K-AKT module and eIF-ribosomal complexes module. Comparatively the eIF-ribosomal complexes module is the most robust, while the IR-IRS related module is the most fragile. Feedback loops are critical in terms of fragility, with emphasis on the control and role of IRS1. Knockout studies reveal the increased ability of multiple parameter knockouts to qualitatively control translation initiation relative to single parameter knockouts. Coupling analysis supports the criticality and modularity of the network and the importance of feedback loops and importance of species like IRS1, PI3K, AKT and mTORC1.