Gene Regulation in Phage Lambda: A Real-Time Study with Single-Event Resolution

项目摘要 由大肠杆菌及其病毒噬菌体λ组成的系统长期以来一直是 一个简单的范例，基因调控的方式驱动选择替代细胞的命运，遗传 存储单元身份，以及从一个单元状态切换到另一个。噬菌体λ已经广泛地被 用遗传学和生物化学方法表征。这是第一批尝试创建 一个生命系统的定量叙述，以数学模型的形式连接微观 细胞中的物理化学反应对系统级性质的影响。然而，这些模型仍然具有有限的 预测能力，由于缺乏基于实验的描述基因调控在所需的时间， 时空分辨率 我们在这次竞争性更新中的目标是通过量化基因调控来继续缩小这一知识差距， λ系统，以及由此产生的细胞命运，在单个细胞和细胞的分辨率下， 分子和时空中的离散事件。为了实现这一目标，我们将使用单细胞和单- 分子荧光显微镜，结合先进的图像和数据分析算法， 我们检测单个噬菌体颗粒和单个DNA和RNA分子，计算绝对蛋白 数字，并测量离散的时间序列的转录事件。通过使用简单， 粗粒度的理论模型，我们提取我们的实验结果到一般原则，其中提出 我们对lambda的系统级理解。然后应用相同的实验和理论工具， 更高的系统。 作为拟议工作的成果，（1）我们将推进基因的定量叙述的形成 调节在细胞，“中观”尺度，提供了微观细节之间的缺失环节， 体外获得的分子相互作用和系统水平的表型。(2)我们将在多大程度上揭示 观察到的基因调控和细胞命运选择的异质性（“噪音”）是真正的生物化学反应的表现。 随机性，或者相反，代表我们无法测量关键的“隐藏变量”，这些变量具有确定性， 影响细胞行为。(3)为该项目开发的实验、计算和理论工具将 继续直接应用于更高系统中类似问题的询问，并最终将 进一步了解基因调控如何在人类健康背景下驱动细胞命运选择， 疾病

Project Summary The system comprising the bacterium Escherichia coli and its virus, bacteriophage lambda, has long served as a simple paradigm for the way gene regulation drives the choice between alternative cellular fates, the inheritable memory of cell identity, and the switching from one cell state to another. Phage lambda has been extensively characterized using genetic and biochemical approaches. It was one of the first testbeds for the attempt to create a quantitative narrative for a living system, in the form of mathematical models connecting the microscopic physical-chemical reactions in the cell to the system-level properties. However, these models still have limited predictive power, due to the absence of an experimentally-based description of gene regulation at the required spatiotemporal resolution. Our goal in this competitive renewal is to continue closing this knowledge gap by quantifying gene regulation in the lambda system, and the resulting cell fate, at the resolution of individual phages and cells, individual molecules, and discrete events in space and time. To achieve this goal, we will use single-cell and single- molecule fluorescence microscopy, which, combined with advanced image and data analysis algorithms, allow us to detect individual phage particles and individual molecules of DNA and RNA, count absolute protein numbers in individual cells, and measure the discrete time-series of transcription events. By using simple, coarse-grained theoretical models, we distill our experimental findings into general principles, which advance our system-level understanding of lambda. The same experimental and theoretical tools are then applied, mutatis mutandis, to higher systems. As outcomes of the proposed work, (1) we will advance the formation of a quantitative narrative for gene regulation at the cellular, “mesoscopic” scale, providing the missing link between the microscopic details of molecular interactions obtained in vitro and the system-level phenotype. (2) We will reveal to what degree the observed heterogeneity (“noise”) in gene regulation and cell-fate choice are a manifestation of true biochemical stochasticity, or instead, represent our inability to measure critical “hidden variables”, which have a deterministic effect on cell behavior. (3) The experimental, computational and theoretical tools developed for the project will continue to be directly applied for the interrogation of analogous questions in higher systems, and will ultimately further our understanding of how gene regulation drives cell-fate choices in the context of human health and disease.