Understanding hierarchical and metabolic regulation of metabolic networks through Bayesian constraint modelling

Integration of datasets for understanding the interplay between the various levels of cellular organization is an important aspect of today's (systems) biology. Consequently, regulation of metabolic pathways has received a lot of attention. However, more quantitative analyses that relate changes in metabolic fluxes to changes in transcript or protein levels, have revealed a remarkable lack of understanding of the regulation of metabolic networks. It is currently impossible to rationalize, let alone predict, which enzymes in a metabolic pathway should be regulated through enzyme levels, and which by allosteric regulation.

In this project we will examine how physiologically relevant functional constraints (homeostasis of metabolites, specific flux changes, robustness, stability) can be used to explore the space of possible regulatory responses of metabolic pathways to different conditions. Using and extending previously developed kinetic models of primary metabolism in both Saccharomyces cerevisiae and Lactococcus lactis, the relation between changes in enzyme levels and physiological constraints will be evaluated. These constraints allow us to compute feasible enzyme activity profiles, which can be compared to experimental data sets. The approach will be extended to the dynamic regime, and to a stochastic approach that can deal with parameter uncertainties.

Our analysis will result in valuable insight in the design principles of regulation of metabolism in general, and of two industrially important microorganisms in particular. Understanding the design principles of metabolic regulation is of primary interest in systems biology, medicine and metabolic engineering.

Coordinator: Prof. B. Teusink, VU University Amsterdam, Faculty of Earth and Life Sciences, Centre for Integrative Bioinformatics (IBIVU)