Quantifying dynamic regulation in metabolic pathways with non-parametric flux inference (Biophysical Journal)

One of the central tasks in systems biology is to understand how cells regulate their metabolism. Hierarchical regulation analysis (HRA) is a powerful tool to study this regulation at the metabolic, gene-expression and signaling levels. It has been widely applied to study the steady-state regulation; but analysis of the metabolic dynamics remains challenging because it is difficult to measure time-dependent metabolic flux. Here we develop a non-parametric method that uses Gaussian processes to accurately infer the dynamics of a metabolic pathway based only on metabolite measurements; from this we then go in to obtain a dynamical view of the hierarchical regulation processes invoked over time to control the activity in a pathway.