This project has always focused on understanding regulation of intracellular signaling pathways emanating from heterotrimeric G proteins. We plan to use a systems biology approach to study how subunits of heterotrimeric Gi/o trigger neurite outgrowth in the Neuro-2A cell line and primary hippocampal and cortical neurons. Neurite outgrowth requires the stimulation of a transcriptional program and recent multivariable experiments in our laboratory indicate that 33 transcription factors are activated by signals that trigger neurite outgrowth in Neuro-2A cells. In the coming term we propose to blend graph theory analyses with differential equation-based models to define quantitatively the information processing ability of the regulatory motifs from the G protein subunits to the transcription factors. We will continue the development and implementation of new computer programs that use massively parallel programs running on IBM Blue-Gene to identify large motifs and how small motifs come together to form these larger units. We will develop differential equation- based models to define the information processing capability of individual motifs and interacting groups of small motifs. The multiple modeling approaches will in turn be integrated with multivariable experiments using reverse phase protein arrays and transcription factor profiling arrays to test, refine and validate the regulatory topology model of signaling networks. The central hypothesis for the proposed studies is that the organization of small regulatory motifs results in larger integrated units that allow for coordinated information processing within the central signaling network to regulate multiple transcription factors that are required for stimulus triggered cellular state change. From these studies we anticipate that we will gain initial insights into how the organization of regulatory signaling networks enables a cell to make state change decisions.
The overall goal of this study is to understand the design principles of how regulatory networks are organized within cells. For this we plan to use both experiments and mathematical models to define how various components within a brain cell are connected to one another. Understanding the relationship between intracellular organization and decision making in brain cells will allow us to identify new drug targets and develop new approaches to treat complex diseases.
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