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Visualizing local and global chromatin architecture, and gene expression in the individual cell by structural (SUSHI) and temporal (3D-SMRT) single molecule imaging

通过结构 (SUSHI) 和时间 (3D-SMRT) 单分子成像可视化局部和整体染色质结构以及单个细胞中的基因表达

基本信息

批准号：
9306084
负责人：
David Grunwald
金额：
$ 33万
依托单位：
UNIV OF MASSACHUSETTS MED SCH WORCESTER
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-09-30 至 2020-06-30
项目状态：
已结题

项目摘要

DESCRIPTION (provided by applicant): Responding to the NIH's 4D Nucleome FOA for Imaging Tools, we propose here two novel imaging methods. When combined, these methods provide nanometer spatial resolution, and millisecond to hour temporal resolution of dynamic chromatin architecture rearrangement and its relation to cell activation and transcription. The first novel technique, termed SUSHI (SUb-zeroº-Stochastic-High-resolution-Imaging platform), enables quantitative, stochastic, single molecule imaging by combining intelligent labeling design with cryogenic fluorescence and emitter control using polarized excitation and depletion. This results in 1-5 nanometer isotropic structural resolution of nuclear chromatin, and the ability to discern DNA elements such as enhancers, suppressors or gene loci that can be mapped and tracked. The second method, termed 3D-SMRT Microscopy (three-dimensional Single-Molecule Real-Time microscopy, manuscript submitted), is an expansion on the recently described MFM (multi-focus microscopy). It provides real-time, simultaneous, multicolor, 30-80 nanometer-resolution tracking in the living cell at a millisecond to hour timescale. By implementing a well thought out labeling strategy, this method also allows for the detection of DNA elements and their nuclear movement in time and space. To be able to analyze hundreds of cells in different activation states, we also describe our streamlined image processing workflows for both SUSHI and 3D-SMRT, permitting the automated analysis of multiple loci of hundreds of single cells and many activation states. We will make the imaging platforms available to all members of the 4D Nucleome consortium by placing the microscopes in a core facility at UMMS, and will share all data processing techniques via code sharing. We focus on the FOS gene locus, as this "immediate-early response" gene has low to no expression of c-Fos mRNA and protein at rest. Upon activation, however, there is a rapid induction of c-Fos, which persists only for a few hours. Heat maps depicting intrachromosomal interaction matrices around the FOS gene indicate extensive looping at this locus. By labeling DNA in a living cell, we can resolve chromatin looping changes around the locus and its surrounding enhancers, determine potential gene locus positional movements toward the nuclear periphery and nuclear pores, and correlate this with mRNA expression and export, both at rest and upon activation. By collaborating with members of the 4D Nucleome consortium, we envision the final stage of this project to include direct correlation with biochemical, structural and genome-wide mapping derived data, thereby shedding light on how genomic information specifies proper execution of spatial and temporal gene expression at rest, upon activation, during cellular development and in diseased states.

描述（由申请人提供）：响应 NIH 的 4D Nucleome FOA for Imaging Tools，我们在此提出两种新颖的成像方法。当结合起来时，这些方法提供了动态染色质结构重排及其与细胞激活和转录的关系的纳米空间分辨率和毫秒到小时时间分辨率。第一项新技术称为 SUSHI（SUb-零度随机高分辨率成像平台），通过将智能标记设计与低温荧光和使用偏振激发和耗尽的发射器控制相结合，实现定量、随机、单分子成像。这导致核染色质具有 1-5 纳米各向同性结构分辨率，并且能够识别可以绘制和追踪的 DNA 元件，例如增强子、抑制子或基因位点。第二种方法称为 3D-SMRT 显微镜（三维单分子实时显微镜，已提交手稿），是最近描述的 MFM（多焦点显微镜）的扩展。它以毫秒到小时的时间尺度对活细胞进行实时、同步、多色、30-80 纳米分辨率的跟踪。通过实施深思熟虑的标记策略，该方法还可以检测 DNA 元素及其在时间和空间上的核运动。为了能够分析处于不同激活状态的数百个细胞，我们还描述了 SUSHI 和 3D-SMRT 的简化图像处理工作流程，允许自动分析数百个单细胞和许多激活状态的多个位点。我们将通过将显微镜放置在 UMMS 的核心设施中，向 4D Nucleome 联盟的所有成员提供成像平台，并将通过代码共享来共享所有数据处理技术。我们关注 FOS 基因位点，因为这种“立即早期反应”基因在静止状态下 c-Fos mRNA 和蛋白质的表达较低甚至没有。然而，激活后，c-Fos 会快速诱导，但仅持续几个小时。描绘 FOS 基因周围染色体内相互作用矩阵的热图表明该基因座存在广泛的循环。通过标记活细胞中的 DNA，我们可以解析基因座及其周围增强子周围的染色质循环变化，确定基因座向核周边和核孔的潜在位置运动，并将其与静态和激活时的 mRNA 表达和输出相关联。通过与 4D Nucleome 联盟的成员合作，我们设想该项目的最后阶段包括与生化、结构和全基因组图谱衍生数据的直接关联，从而揭示基因组信息如何指定静止时、激活时、细胞发育期间和患病状态下的空间和时间基因表达的正确执行。