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lambda组成的系统长期以来一直被用作 一个简单的范例，说明基因调控如何驱动在可选择的细胞命运和可遗传的细胞命运之间做出选择 细胞身份的记忆，以及从一种细胞状态切换到另一种细胞状态。噬菌体Lambda已经被广泛地 用遗传和生化方法来描述的。这是第一批尝试创造出 对一个生命系统的定量叙述，以数学模型的形式连接微观 在细胞内发生物理化学反应，使其具有系统级的性质。然而，这些模式仍然有限 预测能力，由于缺乏基于实验的对所需基因调控的描述 时空分辨率。 我们在这场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 Lambda系统，以及由此产生的细胞命运，在单个噬菌体和细胞的分辨率下， 分子，以及空间和时间中的离散事件。为了实现这一目标，我们将使用单细胞和单细胞- 分子荧光显微镜，结合先进的图像和数据分析算法，允许 美国将检测单个噬菌体颗粒以及DNA和RNA的单个分子，计算绝对蛋白质 单个细胞中的数量，并测量转录事件的离散时间序列。通过使用简单、 粗粒度的理论模型，我们将我们的实验结果提炼成一般原理，这些原理提出了 我们对lambda的系统级理解。然后应用相同的实验和理论工具，作必要的修改 在必要的情况下，对更高的系统。 作为拟议工作的成果，(1)我们将推进对基因的量化叙事的形成 在细胞、“中观”尺度上的调控，提供了微观细节之间缺失的联系 体外获得的分子相互作用和系统水平的表型。(2)我们会透露在何种程度上 观察到的基因调控的异质性(“噪音”)和细胞命运的选择是真正的生化的表现。 随机性，或者相反，代表着我们无法测量关键的“隐藏变量”，这些变量具有确定性 对细胞行为的影响。(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审问，并最终将 进一步加深我们对基因调控如何在人类健康和环境中决定细胞命运的理解 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.