Building a quiet cell cycle clock

细胞周期控制在真核生物界是高度保守的， 模型系统一直是适用于人类发展问题的主要见解的来源 和疾病该建议继续使用细胞周期的系统水平分析， 这个模型系统。细胞周期“时钟”功能具有高可靠性和低噪声， 尽管构成时钟的各个部件和电路通常已知 高度可变。例如，已知基因表达在个体之间是高度可变的。 细胞，但细胞周期调控的基因表达可以高度可靠的时间方面 和振幅。对细胞周期蛋白-Cdk活性水平升高的阈值反应可以提供开关样的 行为，但这样的开关可以经常在高度可变的启动时间的成本来; 整个电池周期控制电路避免了这种可变性。我们正在追求一种新兴的 多个独立振荡器的概念有助于细胞周期控制;而非耦合 振荡器导致细胞周期事件的高度可变和不规则序列，我们提出， 其他独立振荡器与中心周期蛋白Cdk的耦合（“锁相”） 振荡器可以产生鲁棒且精确的整体系统。这一建议延续了我们的 定量延时荧光显微镜在多细胞周期中创新应用 时间尺度，结合半自动图像分析和深入的遗传和 定量分析，以推动细胞周期控制的系统级理解。 我们正在开发数学建模的新方法。在生物学中有一种迫切的需要 简单但受实验约束的模型，可以揭示基本的控制原理。的 挑战是在连接所需的细节与 生物真实性，以及透明度和洞察力所需的模型简单性。我们正在探索 使用细胞周期控制网络的几何低维表示的方法 这仍然可以通过实验来约束，这将产生可测试的预测。在一个新 方向，以提供进化的对比，从一个关键的，但探索不足的分支， 真核生物界，我们将进行一个基因筛选，旨在饱和检测细胞周期 绿色衣藻中的控制元素。我们设计了机器人 突变体分离的微生物学方法与深度测序相结合， 与传统方法相比，这个项目的速度大大加快。

Cell cycle control is highly conserved through the eukaryotic kingdom, and the budding yeast model system has been the source of major insights applicable to issues in human development and disease. This proposal continues systems-level analysis of the eukaryotic cell cycle using this model system. The cell cycle 'clock' functions with high reliability and low noise, even though individual components and circuits making up the clock are frequently known to be highly variable. For example, gene expression is known to be highly variable between individual cells, and yet cell-cycle-regulated gene expression can be highly reliable with respect to timing and amplitude. Threshold responses to rising cyclin-Cdk activity levels can provide switch-like behavior, but such switches can frequently come at the cost of highly variable onset time; the overall cell cycle control circuitry avoids this variability. We are pursuing an emerging concept of multiple independent oscillators contributing to cell cycle control; while uncoupled oscillators result in highly variable and irregular sequences of cell cycle events, we propose that coupling ('phase-locking') of otherwise independent oscillators to the central cyclin-Cdk oscillator can yield a robust and accurate overall system. This proposal continues our innovative use of quantitative time-lapse fluorescence microscopy, over multi-cell cycle timescales, combined with semi-automated image analysis and in-depth genetic and quantitative analysis to drive systems-level understanding of cell cycle control. We are developing new methods of mathematical modeling. There is a pressing need in biology for simple but experimentally constrained models that can reveal basic control principles. The challenge is to find the most illuminating balance between the detail required for a connection to biological reality, and model simplicity required for transparency and insight. We are exploring methods to use geometrical, low-dimensionality representations of the cell cycle control network that can still be experimentally constrained, and that will yield testable predictions. In a new direction to provide evolutionary contrast from a critical but underexplored branch of the eukaryotic kingdom, we will carry out a genetic screen aiming at saturated detection of cell cycle control elements in the green alga, Chlamydomonas reinhardtii. We have devised robotic methods for the microbiology of mutant isolation, which combined with deep sequencing, allows a massive speedup of this project compared to traditional means.