Sources and Consequences of noise in cell cycle regulation

描述(由申请人提供)： 遗传网络运行中的单细胞变异(噪声)是细胞系统体积较小的必然结果，导致分子(基因、mRNAs、蛋白质)数量较少，可能导致重要遗传控制电路功能的波动。在这种噪音有害的地方，噪音抑制机制很可能已经演变；在某些情况下，噪音也可能是有益的，因为它允许从动态的死胡同中突破，或者通过使种群多样化以适应不断变化的环境。尽管这一主题意义重大，但到目前为止，关于噪声的经验结果在很大程度上局限于简单的合成基因电路。我们建议在更复杂和生理相关的情况下分析单细胞变异：真核细胞中细胞周期遍历的稳健性和细胞周期间隔的持续时间。我们开发了一种定量的全自动延时荧光显微镜装置，允许半自动分析细胞周期调节基因的表达和细胞周期调节因子的重新定位，在整个多细胞周期家系的生成过程中。这一能力可以与大量可用信息结合在一起，这些信息涉及对发芽酵母细胞周期的调节、系统扰乱细胞周期的遗传试剂的可用性，以及有用的细胞周期引擎确定性数学模型。我们将检验这一假设，即G1长度的可变性是由于细胞周期开始时的双稳。我们将在野生型和突变型中产生关于细胞和核大小与细胞周期转变时间关系的定量单细胞数据，为核质大小耦合模型提供约束。我们将使用合成启动子策略和单细胞成像相结合的方法，解决什么样的启动子结构可能导致基因表达单细胞不同水平的可变性的问题。我们已经获得了细胞周期启动过程中随机分子变异的直接证据；我们将从遗传学和随机建模的角度来研究这一发现。为了在更动态的深度上追求这些想法，我们开发了微流控方法，允许在单个监控细胞从单个细胞增殖到微集落时周期性地脉冲基因表达。利用这项技术，我们将测试细胞周期引擎对简要的调控因子强制表达的反应，并寻找模式锁定和其他信息的动态行为。我们将把这些分析工具扩展到有丝分裂调节，测试有丝分裂振荡器的复杂设计功能以抑制噪声的假设。这些结果应该有助于阐明单细胞分辨率下细胞周期引擎的健壮性和动力学等基本问题，以及基本复杂遗传电路操作中的可变性的优点和缺点。

DESCRIPTION (provided by applicant): Single-cell variation (noise) in the operation of genetic networks is an inevitable consequence of the small size of cellular systems, leading to small numbers of molecules (genes, mRNAs, proteins) that may cause fluctuations in the function of important genetic control circuits. Where such noise is deleterious, it is likely that noise suppression mechanisms have evolved; noise could also be beneficial in some cases, by allowing breakout from dynamical dead-ends or by diversifying a population to meet a changing environment. Despite the significance of this topic, empirical results on noise have so far been largely restricted to simple synthetic gene circuits. We propose analysis of single-cell variation in a much more complex and physiologically relevant situation: the robustness of cell cycle traversal and duration of cell cycle intervals in the eukaryote S. cerevisiae. We have developed a quantitative fully automated time- lapse fluorescent microscopy setup allowing semi-automated analysis of cell-cycle-regulated gene expression and relocation of cell cycle regulators, throughout the generation of complete multi-cell cycle pedigrees. This capability can be integrated with the enormous amount of information available about the regulation of the budding yeast cell cycle, the availability of genetic reagents to systematically perturb the cell cycle, and useful deterministic mathematical models of the cell cycle engine. We will test the hypothesis that variability in G1 length is due to bistability at cell cycle Start. We will generate quantitative single-cell data on the relationship of cell and nuclear size to cell cycle transition times, in wild-type and mutants, to provide constraints for models on nucleo-cytoplasmic size coupling. We will attack the question of what promoter architectures may lead to different levels of single-cell variability in gene expression, using a synthetic promoter strategy combined with single-cell imaging. We have obtained direct evidence for stochastic molecular variation in cell cycle Start; we will pursue this finding genetically and with stochastic modeling. To pursue these ideas in more dynamic depth, we have developed microfluidic methods that allow periodic pulses of gene expression in individual monitored cells as they proliferate from single cells into microcolonies. With this technology we will test the response of the cell cycle engine to brief forced expression of regulators, and looking for mode-locking and other informative dynamic behaviors. We will extend these analytical tools to mitotic regulation, testing the hypothesis that the complex design of the mitotic oscillator functions to suppress noise. The results should shed light on fundamental questions of robustness and dynamics of the cell cycle engine at single-cell resolution, and on the advantages and disadvantages of variability in the operation of a fundamental complex genetic circuit.