Adaptive modulation of the global cellular growth state of unicellular organisms is crucial for their survival in fluctuating nutrient environments. Because these organisms must be able to respond reliably to ever varying and unpredictable nutritional conditions, their nutrient signaling networks must have a certain in-built robustness. In eukaryotes, such as the budding yeast Saccharomyces cerevisiae, distinct nutrient signals are relayed by specific plasma membrane receptors to signal transduction pathways that are interconnected in complex information-processing networks, which 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 literature-curated 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.

单细胞生物的全球细胞生长状态的适应性调节对于它们在波动的营养环境中的生存至关重要。因为这些生物必须能够对不断变化和不可预测的营养条件做出可靠的反应，所以它们的营养信号网络必须具有一定的内在稳健性。在真核生物中，例如出芽酵母Saccharomyces cerevisiae, 不同的营养信号由特定的质膜受体传递到信号转导通路，这些通路在复杂的信息处理网络中相互连接，这些网络已经得到很好的表征。然而，信号网络的复杂性混淆了对控制系统整体监管“逻辑”的解释。在这里，我们提出了一种文献整理的出芽酵母中综合营养信号网络的分子机制，重点是对碳和氮信号的早期时间响应。我们建立了该网络的计算模型，以将文献整理的定量实验数据与我们提出的分子机制相协调。我们评估了我们对模型动力学参数值的估计的稳健性。我们通过比较突变菌株的预测与相同菌株的定性实验观察来测试模型。最后，我们使用该模型来预测许多经历复杂营养变化的突变菌株中的营养反应转录因子活性。