VISUALIZATION OF SUBCELLULAR DYNAMICS IN MULTICELLULAR ORGANISMS

多细胞生物体亚细胞动力学的可视化

• 批准号: 10361480
• 负责人: TOMAS KIRCHHAUSEN
• 金额: $ 44.25万
• 依托单位: BOSTON CHILDREN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-03-01 至 2024-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10361480
• 关键词: Algorithms; Biochemistry; Biological; Biological Models; Biology; Brain; Cell Differentiation process; Cells; Characteristics; Collaborations; Complex; Computer software; Computers; Consultations; Data Set; Development; Embryo; Endocytic Vesicle; Environment; Event; Fluorescence Microscopy; Hour; Image; Individual; Light; Lipids; Mediating; Membrane Protein Traffic; Microscopy; Modeling; Molecular; Noise; Optics; Organism; Phosphotransferases; Protein translocation; Research; Resolution; Signal Transduction; Time; Tissues; Visualization; Visualization software; Zebrafish; adaptive optics; complex data; data complexity; daughter cell; deep learning; live cell imaging; neurogenesis; neuron development; new technology; notch protein; novel; novel strategies; programs; recruit; single molecule; structural biology

Abstract Contemporary fluorescence microscopy connects our understanding of molecular events from biochemistry and structural biology with their activities in living cells. Lattice light sheet microscopy (LLSM) has made it possible for us to track phenomena such as endocytic vesicle assembly or lipid kinase recruitment across an entire cell with high resolution, in both space and time, and with nearly single-molecule sensitivity. Development during the past year of lattice light sheet microscopy with adaptive optics (AO-LLSM) has overcome the optical limitations that have so far restricted most studies to individual cells in culture, allowing us to achieve comparable resolution and sensitivity in the complex optical environment of an intact, living, multicellular organism. It promises to bridge the gap between cells and organisms, through high sensitivity, volumetric imaging, with diffraction-limited resolution, of living tissues and developing embryos. We propose a research program in three overlapping stages: implementation of AO-LLSM (in collaboration with its developer), development of the new kinds of visualization and analysis software required by the scale and complexity of the datasets, and use of AO-LLSM to solve a problem in vertebrate development. To meet the computational challenges of analyzing the 4D data sets (from low signal-to-noise, the often non- punctate characteristics of the objects being studied, the temporally varying spatial complexity of the data, and the size of the data sets), we will develop new approaches using deep learning and related algorithms, with consultation from experts. As a paradigm application, we will study the consequences of Notch signaling and the related membrane-traffic and protein translocation events for cell differentiation in zebrafish early neurogenesis. AO-LLSM will for the first time allow us to relate molecular signaling events occurring on a timescale of seconds at cell interfaces to the ultimate fate of daughter cells many hours later. We therefore expect that in the course of resolving some long- standing issues in cell fate determination, we will develop microscopy approaches and computer visualization tools that are widely applicable to a range of model systems and biological questions.

摘要 当代荧光显微镜将我们对分子事件的理解从 生物化学和结构生物学及其在活细胞中的活动。点阵光片显微术 （LLSM）使我们有可能跟踪现象，如内吞囊泡组装或脂质 在整个细胞中以高分辨率进行激酶募集，在空间和时间上， 单分子灵敏度。在过去一年中， 自适应光学（AO-LLSM）已经克服了迄今为止限制大多数光学系统的光学限制， 对培养中的单个细胞进行研究，使我们能够在细胞培养中实现可比的分辨率和灵敏度。 一个完整的、活的、多细胞有机体的复杂光学环境。它有望弥合差距 通过高灵敏度、体积成像和衍射限制， 活组织和发育中的胚胎的分辨率。我们提出了一个研究计划在三个 重叠阶段：AO-LLSM的实施（与其开发人员合作）， 的规模和复杂性所需的新型可视化和分析软件， 数据集，并使用AO-LLSM来解决脊椎动物发育中的问题。满足 分析4D数据集的计算挑战（从低信噪比，通常是非信噪比， 被研究对象的点状特征，时间变化的空间复杂性， 数据，以及数据集的大小），我们将开发使用深度学习和相关技术的新方法。 算法，与专家咨询。作为一个范例应用，我们将研究 Notch信号转导和相关的细胞膜运输和蛋白质易位事件 斑马鱼早期神经发生的分化。AO-LLSM将首次允许我们联系 分子信号事件发生在细胞界面的秒级上， 子细胞数小时后。因此，我们希望在解决一些长期- 在细胞命运决定的长期问题，我们将开发显微镜方法和计算机 可视化工具，广泛适用于一系列模型系统和生物问题。