Abstract
A major challenge in systems biology is to develop a detailed dynamic understanding of the functions and behaviors in a particular cellular system, which depends on the elements and their inter-relationships in a specific network. Computational modeling plays an integral part in the study of network dynamics and uncovering the underlying mechanisms. Here we proposed a systematic approach that incorporates discrete dynamic modeling and experimental data to reconstruct a phenotype-specific network of cell signaling. A dynamic analysis of the insulin signaling system in liver cells provides a proof-of-concept application of the proposed methodology. Our group recently identified that double-stranded RNA-dependent protein kinase (PKR) plays an important role in the insulin signaling network. The dynamic behavior of the insulin signaling network is tuned by a variety of feedback pathways, many of which have the potential to cross talk with PKR. Given the complexity of insulin signaling, it is inefficient to experimentally test all possible interactions in the network to determine which pathways are functioning in our cell system. Our discrete dynamic model provides an in silico model framework that integrates potential interactions and assesses the contributions of the various interactions on the dynamic behavior of the signaling network. Simulations with the model generated testable hypothesis on the response of the network upon perturbation, which were experimentally evaluated to identify the pathways that function in our particular liver cell system. The modeling in combination with the experimental results enhanced our understanding of the insulin signaling dynamics and aided in generating a context-specific signaling network.
Highlights
A major challenge in current molecular biology is to understand the dynamic behavior of biological systems
The simulation result suggests plausible dynamic profiles of the interacting network upon insulin stimulation, and based upon the components and interactions potentially involved in our particular cell system (Figure 1, see Introduction: Insulin signaling transduction in liver cells)
The insulin receptor substrate (IRS) and PKR activity are maintained in a stationary state prior to insulin stimulation
Summary
A major challenge in current molecular biology is to understand the dynamic behavior of biological systems. Over the past decade researchers have successfully identified genes and proteins involved in many different signaling processes and assembled them into pathways and networks. To use these interaction maps to develop a detailed dynamic understanding of the functions and behaviors that are specific to a biological system has yet to be realized. Networks and interaction maps in the literature or databases are obtained from different cellular systems and conditions, and may not be applicable to all systems and under all conditions. It is unclear which pathways are relevant to a particular system that is under investigation
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