Building a quiet cell cycle clock

细胞周期控制在真核生物王国和萌芽酵母中高度保守 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。这一建议继续使用真核细胞周期的系统级分析 这个模型系统。电池周期时钟功能具有高可靠性和低噪声，甚至 尽管组成时钟的各个组件和电路通常是已知的 变数很大。例如，众所周知，基因的表达在个体之间是高度不同的 细胞，然而细胞周期调控的基因表达在时间上是高度可靠的 和幅度。对Cyclin-CDK活性水平上升的阈值反应可以提供开关样 行为，但这样的开关往往以高度可变的起效时间为代价； 整个细胞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 多个独立振荡器有助于细胞周期控制的概念；而不耦合 振荡器导致高度可变和不规则的细胞周期事件序列，我们认为 其他独立振荡器与中心细胞周期蛋白-CDK的偶联(锁相) 振荡器可以产生一个健壮而准确的整体系统。这项提议延续了我们的 多细胞周期定量延时荧光显微镜的创新应用 时间尺度，结合半自动图像分析和深入的遗传和 定量分析以推动对细胞周期控制的系统水平的理解。 我们正在开发新的数学建模方法。在生物学方面有一种迫切的需要 对于简单但受实验约束的模型，可以揭示基本的控制原理。这个 所面临的挑战是在连接到 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 方法使用细胞周期控制网络的几何、低维表示 这仍然可以在实验上受到限制，这将产生可测试的预测。在一个新的 方向，以提供来自关键但未被探索的分支的进化对比 真核王国，我们将进行一次旨在饱和检测细胞周期的遗传筛查 绿藻--莱茵衣藻中的控制因子。我们发明了机器人 突变分离的微生物学方法，结合深度测序，允许 与传统方法相比，这个项目的速度有了很大的提高。

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.