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

噬菌体 Lambda 中的基因调控：单事件分辨率的实时研究

基本信息

批准号：
8894519
负责人：
Ido Golding
金额：
$ 29.74万
依托单位：
BAYLOR COLLEGE OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2008
资助国家：
美国
起止时间：
2008-08-04 至 2016-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8894519
关键词：
Address Algorithms Bacteria Bacteriophage lambda Bacteriophages Beds Binding Biochemical Cell Death Cells Cereals Cytolysis Cytoplasm DNA Data Analyses Dependence Diffusion Disease Dosage Compensation (Genetics)Escherichia coli Event Fluorescence Microscopy Funding Gene Dosage Gene Expression Gene Expression Regulation Genes Genetic Genetic Transcription Genomics Goals Health Heterogeneity Human Image Analysis In Vitro Individual Infection Kinetics Knowledge Life Life Cycle Stages Lysogeny Maps Measures Memory Messenger RNA Methods Microscopic Modeling Mono-S Noise Organism Outcome Phenotype Play Production Property Proteins RNA Regulation Resolution Role Series Shapes System Testing Theoretical model Time Time Study Transcriptional Regulation Viral Genome Virus Work base biochemical tools biophysical tools cell behavior chemical reaction improved mathematical model particle promoter research study single molecule spatiotemporal tool transcription factor

项目摘要

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

描述（由申请人提供）：包含大肠杆菌及其病毒、噬菌体 lambda 的系统长期以来一直作为基因调控驱动替代细胞状态、细胞状态的遗传记忆和细胞状态之间选择的简单范例。从一种状态切换到另一种状态。 lambda 系统已使用遗传和生化方法进行了广泛的表征。最近，它成为尝试形成生命系统定量叙述的首批试验台之一，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，由于缺乏在所需时空分辨率下基于实验的基因调控描述，这些模型的预测能力仍然有限。我们在这一竞争性更新中的目标是通过在单个噬菌体和细胞、细胞中的单个基因拷贝、单个分子的分辨率下量化 lambda 系统中的基因调控来继续缩小这一知识差距以及空间和时间上的离散事件。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，计算单个噬菌体中的绝对蛋白质数量。细胞并测量转录的离散时间序列。通过使用简单、粗粒度的理论模型，我们能够将实验结果提炼成一般原理，从而改进对 lambda 的系统级理解，并可以直接应用于更高系统中的发现。拟议工作的成果将是在细胞“介观”尺度上对基因调控进行定量描述，为当前存在的两个描述水平之间架起一座桥梁：利用传统生化获得的控制基因调控的分子相互作用的微观细节体外生物物理工具，以及使用遗传和基因组方法绘制的大规模（“宏观”）基因网络拓扑。具体来说，这项工作将使我们能够解决以下问题：（1）在基因调控中观察到的异质性（“噪音”）在多大程度上是实际生化随机性的表现，或者代表我们无法测量细胞“隐藏变量” ，哪些对细胞行为有确定性影响？ (2) 除了同质细胞质中的简单扩散之外，空间效应在基因调控中发挥什么作用？最终，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高等多细胞系统以及人类健康和疾病背景下驱动细胞命运选择的理解