School of Mathematics and Statistics, Wuhan University, Wuhan, P. R. China.
Biophys J. 2013 May 21;104(10):2282-94. doi: 10.1016/j.bpj.2013.03.057.
The specification and maintenance of cell fates is essential to the development of multicellular organisms. However, the precise molecular mechanisms in cell fate selection are, to our knowledge, poorly understood due to the complexity of multiple interconnected pathways. In this study, model-based quantitative analysis is used to explore how to maintain distinguished cell fates between cell-cycle commitment and mating arrest in budding yeast. We develop a full mathematical model of an interlinked regulatory network based on the available experimental data. By theoretically defining the Start transition point, the model is able to reproduce many experimental observations of the dynamical behaviors in wild-type cells as well as in Ste5-8A and Far1-S87A mutants. Furthermore, we demonstrate that a moderate ratio between Cln1/2→Far1 inhibition and Cln1/2→Ste5 inhibition is required to ensure a successful switch between different cell fates. We also show that the different ratios of the mutual Cln1/2 and Far1 inhibition determine the different cell fates. In addition, based on a new, definition of network entropy, we find that the Start point in wild-type cells coincides with the system's point of maximum entropy. This result indicates that Start is a transition point in the network entropy. Therefore, we theoretically explain the Start point from a network dynamics standpoint. Moreover, we analyze the biological bistablity of our model through bifurcation analysis. We find that the Cln1/2 and Cln3 production rates and the nonlinearity of SBF regulation on Cln1/2 production are potential determinants for irreversible entry into a new cell fate. Finally, the quantitative computations further reveal that high specificity and fidelity of the cell-cycle and mating pathways can guarantee specific cell-fate selection. These findings show that quantitative analysis and simulations with a mathematical model are useful tools for understanding the molecular mechanisms in cell-fate decisions.
细胞命运的特化和维持对于多细胞生物的发育至关重要。然而，由于多个相互关联的途径的复杂性，我们对细胞命运选择的精确分子机制知之甚少。在这项研究中，我们使用基于模型的定量分析来探索如何在芽殖酵母的细胞周期启动和交配停滞之间维持明显的细胞命运。我们基于现有的实验数据，构建了一个相互关联的调控网络的全数学模型。通过理论上定义起始转换点，该模型能够再现野生型细胞以及 Ste5-8A 和 Far1-S87A 突变体的许多实验观察结果。此外，我们证明了 Cln1/2→Far1 抑制和 Cln1/2→Ste5 抑制之间的适度比值对于确保不同细胞命运之间的成功转换是必要的。我们还表明，Cln1/2 和 Far1 之间相互抑制的不同比值决定了不同的细胞命运。此外，基于网络熵的新定义，我们发现野生型细胞中的起始点与系统的最大熵点重合。这一结果表明起始是网络熵的一个转折点。因此，我们从网络动力学的角度对起始点进行了理论解释。此外，我们通过分岔分析对模型的生物学双稳定性进行了分析。我们发现 Cln1/2 和 Cln3 的产生率以及 SBF 对 Cln1/2 产生的非线性调节是不可逆进入新细胞命运的潜在决定因素。最后，定量计算进一步揭示了细胞周期和交配途径的高特异性和保真度可以保证特定的细胞命运选择。这些发现表明，定量分析和数学模型模拟是理解细胞命运决策中分子机制的有用工具。
