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

描述（由申请人提供）：包含细菌大肠杆菌及其病毒噬菌体λ的系统长期以来一直充当基因调节驱动在替代细胞状态之间的选择、细胞状态的可遗传记忆以及从一种状态切换到另一种状态的方式的简单范例。λ系统已被广泛使用的遗传和生物化学方法的特点。最近，它已成为试图为生命系统形成定量叙述的第一个试验台之一，以数学模型的形式将细胞中的微观物理化学反应与系统级特性联系起来。然而，这些模型仍然具有有限的预测能力，这是由于缺乏在所需的时空分辨率下对基因调控的基于实验的描述。 我们在这次竞争性更新中的目标是通过量化λ系统中的基因调控来继续缩小这一知识差距，以单个细胞和细胞，细胞中的单个基因拷贝，单个分子的分辨率。 以及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，使我们能够检测单个噬菌体颗粒和单个DNA和RNA分子，计算单个细胞中的绝对蛋白质数量，并测量转录的离散时间序列。 通过使用简单的，粗粒度的理论模型，我们能够将我们的实验结果提炼成一般原则，这提供了一个改进的系统级的理解lambda，并可以直接应用到更高的系统中的结果。 拟议的工作的结果将是在细胞的基因调控的定量描述，“介观”尺度，提供了一个桥梁之间的两个现有的描述水平：微观细节的分子相互作用的基因调控，获得使用传统的生物化学和生物物理工具在体外，和大规模（“宏观”）拓扑结构的基因网络，映射使用遗传和基因组学方法。具体来说，这项工作将使我们能够解决以下问题：（1）在多大程度上是观察到的异质性（“噪音”）在基因调控的实际生化随机性的表现，或相反，代表我们无法测量细胞的“隐藏变量”，有一个确定性的影响细胞的行为？(2)除了在同质细胞质中的简单扩散外，空间效应在基因调控中起什么作用？最终，在这项工作中开发的概念和实验工具将进一步加深我们对基因调控如何在更高的多细胞系统中以及在人类健康和疾病的背景下驱动细胞命运选择的理解

DESCRIPTION (provided by applicant): 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 states, the inheritable memory of cell state, and the switching from one state to another. The lambda system has been extensively characterized using genetic and biochemical approaches. More recently, it has served as one of the first test beds for the attempt to form a quantitative narrative for a living system, in the shape 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 at the resolution of individual phages and cells, individual gene copies in the cell, 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. By using simple, coarse-grained theoretical models we are able to distill our experimental findings into general principles, which provide an improved system-level understanding of lambda, and can be directly applied to findings in higher systems. The outcome of the proposed work will be a quantitative description of gene regulation at the cellular, "mesoscopic" scale, providing a bridge between the two currently-existing levels of description: the microscopic details of molecular interactions governing gene regulation, obtained using traditional biochemical and biophysical tools in vitro, and large scale ("macroscopic") topologies of gene networks, mapped using genetic and genomic methods. Specifically, the work will allow us to address the following questions: (1) To what degree is the observed heterogeneity ("noise") in gene regulation a manifestation of actual biochemical stochasticity, or instead represents our inability to measure cellular "hidden variables", which have a deterministic effect on cell behavior? (2) What role do spatial effects, beyond simple diffusion in a homogenous cytoplasm, play in gene regulation? Ultimately, the conceptual and experimental tools developed in this work will further our understanding of how gene regulation drives cell-fate choices in higher, multicellular systems, and in the context of human health and disease