Modeling and Analysis of the Macronutrient Signaling Network in Budding Yeast

Abstract

In eukaryotes, distinct nutrient signals are relayed by specic plasma membrane receptors to signal transduction pathways that are interconnected in complex information-processing networks. The function of these networks is to govern robust cellular responses to unpredictable changes in the nutritional environment of the cell. In the budding yeast, Saccharomyces cerevisiae, these nutrient signaling pathways and their interconnections have been well characterized. However the complexity of the signaling network confounds the interpretation of the overall regulatory`logic' of the control system. Here, we propose a literaturecurated molecular mechanism of the integrated nutrient signaling network in budding yeast, focusing on early temporal responses to carbon and nitrogen signaling. We build a computational model of this network to reconcile literature-curated quantitative experimental data with our proposed molecular mechanism. We evaluate the robustness of our estimates of the model's kinetic parameter values. We test the model by comparing predictions made in mutant strains with qualitative experimental observations made in the same strains. Finally, we use the model to predict nutrient-responsive transcription factor activities in a number of mutant strains undergoing complex nutrient shifts.suppressing carbon-adaptation and general stress responses when glucose is plentiful, while up-regulating ribosome biogenesis and overall growth rate [6,7,8,9]. When glucose is in short supply, the Snf1 pathway shuts o catabolite repression and up-regulates carbon adaptation responses [10,11]. In the presence of rich nitrogen sources, the TORC1 pathway activates nitrogen catabolite repression (NCR) and up-regulates ribosome biogenesis via the Sch9-kinase branch [12,13,14,15]. In response to declining nitrogen status, the Tap42-Sit4/PP2A phosphatase branch activates nitrogen adaptation responses [16].While the upstream sensing mechanisms are nutrient specic, the downstream signal-processing network is characterized by crosstalk among the signaling pathways just described. Consequently, how the cell responds to specic combinations of nutrients depends on complex interactions among key regulatory enzymes in the network [17,18,19,20,21]. In yeast, the pathways responsive to particular nutrients have been well studied, but the molecular decision-making carried out by the network as a whole remains unclear. The complexity of the system obfuscates the interpretation of experimental observations, based on genetic and environmental perturbations that interrogate the nutrient adaptation responses [22].In the study of such complex biochemical control systems, dynamical modeling has proven to be useful in determining cellular behaviors that result from entangled molecular interactions [23,24,25]. These dynamical models are often presented as systems of nonlinear ordinary dierential equations (ODEs) built from biochemical rate laws describing the reaction steps that constitute the biochemical interaction network.Previous authors have pub...