Dynamic Stability as a Criterion for Metabolic Systems Analysis: An Ensemble Modeling Approach

Abstract

The metabolic system is one of the most complex, and yet, under-investigated areas that underlie many cellular functions and diseases. Although the basic functions and enzymes involved in major pathways have been elucidated many decades ago, how metabolic systems achieve homeostasis and robustness against cellular and environmental perturbations is still unknown. The situation is complicated by the lack of quantitative tools for analysis of metabolic systems, which are characterized by a large number of unknown parameters, which are themselves functions of cellular states and the environment.? Over the past few years, we have developed an Ensemble Modeling approach that circumvents the difficulty of parameter uncertainly and focuses on network structural properties.? The approach takes advantage of all possible information derived from data, and allows the prediction of boundaries of dynamic stability under parameter uncertainty.?? We have used microbial metabolism a model to demonstrate the utility of such an approach.? In particular, we have shown how the Ensemble Modeling approach facilitated synthetic pathway design and strain construction for production of fuels and chemicals.? Future directions on human metabolic modeling will also be discussed briefly.