芽殖酵母细胞命运抉择网络的建模和分子调控机制研究

Cell fate decision plays important roles in the cell proliferation, senescence and apoptosis. The uncorrect decision is closely related to the occurrence and development of major human diseases, e.g., prostate cancer and breast cancer. Therefore, the research about the underlying network and molecular regulation mechanism of cell fate decision is important. Cell fate selection involves in cell cycle regulation process, signal transduction process, as well as the crosstalk between them. We will choose the model organism, i.e., budding yeast, as the research object. Through the integration of multi-level data including the gene expression profile, transcriptional regulation, and protein-protein interactions, the molecular network of cell fate decision of budding yeast will be reconstructed. We will develop the sparse optimization model of dynamic network structure and decomposition algorithm, and improve the robustness of network modelling based on non-stationary measure minimize. The relationship between the nonlinear dynamical behavior and network statistical characteristics with biological phenotype will be explored and the key role of crosstalk between cell cycle regulation and signal transduction pathways also will be studied. Further, we will design biological experiments to test our theoretical model. We expect that we can reveal the molecular mechanism of the accurate and robust behavior of cell fate selection. The theory and methods developed in our project can be applied to the further research for the human disease induced by disordered fate selection in the future.

细胞命运抉择在细胞的增殖、衰老、凋亡等细胞生命活动中扮演着重要作用，抉择的紊乱往往与前列腺癌、乳腺癌等人类重大疾病的发生和发展密切相关，因此细胞命运抉择网络和分子调控机制的研究是当前一个十分重要的前沿研究课题。我们将以模式生物芽殖酵母为研究对象，以细胞周期调控网络与信号转导通路之间的对话为切入点，通过整合基因表达谱、转录调控以及蛋白与蛋白相互作用等多层次组学数据，重构芽殖酵母细胞命运抉择分子网络。进一步发展动态网络结构的稀疏最优化模型和分解算法，基于非平稳度量最小化标准提高网络模型稳健性，研究非线性动力学性态以及网络统计特征与生物表型的关系，然后设计生物实验进行验证，最终期望揭示精确而鲁棒的细胞命运抉择行为的分子调控机制。我们发展的理论和方法有望应用于命运抉择紊乱导致的人类复杂疾病分子网络的研究中。

细胞命运抉择伴随整个生命过程，在单细胞和多细胞生物体的增殖、分化等过程中起关键作用，是细胞生物学研究中最重要的前沿课题之一，揭示精确而鲁棒的细胞命运抉择行为的分子调控机制已经成为系统生物学和定量生物学的研究热点。理论上，我们建立了一个关于芽殖酵母细胞分子相互作用网络的全模型，证明了由一个核心的三节点前馈调节模块确保了细胞快速停滞及细胞状态快速可逆；建立了细胞命运抉择分子调控网络的随机模型，发现内噪声和外噪声满足一定的近似线性关系的时候确保了高精度的命运抉择；通过合作发现了细胞周期的START检验点由磷酸化Whi5的积分机制调控。实验上，我们研究了酵母细胞Cell cycle与Mating通路的外界调控因子，通过化学遗传学的手段，对多胺的代谢调控进行干扰，检测cell cycle和mating通路的变化；进行了功能小分子的高通量筛选研究，基于蛋白质设计的理念，提出了一个简单可行的小分子共价配体高通量筛选策略，验证了其普适性和高效性，并发现了新型的共价小分子抑制剂。通过本项目发展的理论和方法未来将可能应用于命运抉择紊乱导致的人类复杂疾病分子网络的研究中。