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：
9376483
负责人：
Ido Golding
金额：
$ 31.7万
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 2021-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9376483
关键词：
Affect Algorithmic Analysis Bacteria Bacteriophage lambda Bacteriophages Behavior Binding Biochemical Cell Cycle Cell Cycle Progression Cell model Cells Cereals Cytolysis DNA Data Analyses Disease Distal Escherichia coli Event Exhibits Fluorescence Microscopy Funding Gene Expression Regulation Genes Genetic Genetic Transcription Genome Goals Health Heterogeneity Human Image Analysis In Vitro Individual Infection Inherited Knowledge Link Logic Lysogeny Lytic Maintenance Measures Memory Microscopic Modeling Molecular Noise Organism Outcome Phase Phenotype Property Proteins RNA Regulation Resolution Series System Theoretical model Time Time Study Transcriptional Regulation Uncertainty Virulent Virus Work base cell behavior cell growth chemical reaction combinatorial discrete time flexibility mathematical model particle promoter single molecule spatiotemporal tool transcription factor

项目摘要

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.

项目概要该系统由大肠杆菌及其病毒、噬菌体 lambda 组成，长期以来一直被用作基因调控驱动不同细胞命运之间选择的一个简单范例，即可遗传性细胞身份的记忆，以及从一种细胞状态到另一种细胞状态的转换，噬菌体 lambda 已被广泛使用。它是尝试创建的第一个测试平台之一。以连接微观世界的数学模型的形式对生命系统进行定量叙述然而，这些模型仍然有局限性。预测能力，由于缺乏基于实验的基因调控描述时空分辨率。我们在这一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，在个体噬菌体和细胞的分辨率下，个体为了实现这一目标，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，可以我们可以检测单个噬菌体颗粒以及单个 DNA 和 RNA 分子，计算绝对蛋白质单个细胞中的数字，并通过使用简单的方法测量转录事件的离散时间序列。粗粒度的理论模型，我们将实验结果提炼成一般原理，从而推进然后应用相同的实验和理论工具，并进行必要的修改。经必要修改，到更高的系统。作为拟议工作的成果，（1）我们将推进基因定量叙述的形成细胞“介观”尺度的调控，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表型（2）我们将揭示这种相互作用的程度。观察到的基因调控和细胞命运选择的异质性（“噪音”）是真正生化的表现随机性，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 (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，并最终将进一步加深我们对基因调控如何在人类健康背景下驱动细胞命运选择的理解疾病。