Quantification of macromolecular interactions in GAL network

The functioning of cellular networks is governed by nonlinear system dynamics. The yeast Saccharomyces cerevisiae has long been a preferred model organism for studying such cellular regulatory systems. Perhaps, the most extensively studied genetic switch in yeast is the GAL network. Its behaviour arises from the complex interplay of multiple feedback loops the interaction of which is determined by their biochemical parameters. Direct estimation of these parameters is possible only with modeling, which often remains seriously unconstrained. In order to overcome this barrier we opened each feedback loop genetically and titrated the protein concentration of the signal transducers. Using quantitative proteomics, we were able to determine in vivo macromolecular interaction constants by minimizing the interference from other feedback loops. Some of these in vivo parameter values were in good agreement with previously published in vitro measurements. Moreover the resulting open loop relations along with equivalence relations, mapped the parameter space of deterministic bistability for the GAL network. Feedback splitting and transition rates successfully predicted bistability region both correlating with the hysteresis behaviour of the system and validating the parameter determination in our models.