Interferometric 3D Super-Resolution Imaging and Structure and Stoichiometry Mapping in Living Cells

活细胞中的干涉 3D 超分辨率成像以及结构和化学计量图

• 批准号: 9751889
• 负责人: Fang Huang
• 金额: $ 37.58万
• 依托单位: PURDUE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-01 至 2021-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9751889
• 关键词: 3-Dimensional; Actins; Biological; Biological Process; Biology; Biomedical Research; Cell division; Cells; Collaborations; Color; Cytokinesis; Data; Data Set; Development; Disease; Dyes; Event; Fission Yeast; Fluorescence Microscopy; Generations; Growth Cones; Health; Hour; Image; Imagery; Inferior; Knowledge; Label; Macromolecular Complexes; Methods; Mission; Modeling; Molecular; Myosin ATPase; Nanoscopy; Nanostructures; Neurons; Positioning Attribute; Proteins; Public Health; Research; Resolution; Sampling; Specificity; Structure; System; Thick; Thinness; Time; United States National Institutes of Health; Universities; adaptive optics; base; cell motility; high resolution imaging; imaging modality; improved; in vivo; macromolecular assembly; nanoscale; public health relevance; single molecule; stoichiometry; temporal measurement; three-dimensional modeling; tool; ultra high resolution

Abstract We are in an exciting era of biology where the inner workings of cells can be explored by rapidly developing imaging methods. Fluorescence microscopy has two major advantages: labeling specificity and live cell compatibility. However, it is limited by diffraction to approximately 250 nm resolution. The recent advent of single molecule switching nanoscopy (SMSN, also known as PALM/STORM/FPALM) has overcome this fundamental limit by stochastically switching single dyes on and off such that their emission events are separated in time. This allows their center positions to be localized with high precision in space leading to a reconstructed super resolved image with a resolution down to ~25 nm. However, its biological application is limited for two reasons: (1) SMSN applications are typically limited to fixed samples due to the poor temporal resolution and (2) the application been limited to structures close to the coverslip in thin samples because of its inferior resolution in the depth direction (z) and rapidly deteriorating resolution in thick samples. Further, SMSN generates thousands to millions of precise single molecule positions per dataset - a large amount of information rarely explored due to the lack of data quantification methods. Overcoming these hurdles will allow visualization and quantification of nanostructures in living cells, determine the stoichiometry of fluorescently tagged proteins and thus drastically expand the breadth of SMSN applications. We propose to (1) develop interferometric SMSN for ultra-high resolution imaging in live cells and thick samples capturing 3D live cell dynamics through an imaging depth up to 50 µm with isotropic 5-10 nm resolution; (2) develop structure and stoichiometry mapping in space, time and multiple color to build high- resolution 3D models of macromolecular complexes and large protein assemblies in live cell; and (3) further improve the resolution by another order of magnitude (~1 nm precision) of the reconstructed model by a high- content system allowing statistical quantification over thousands of cells (~3000 cells per hour). Applying these developments, we will study the distinct molecular organization and function of three different myosins during cytokinesis in live fission yeast and neuronal motility focusing on the growth cones in live neuron. The proposed research will, for the first time, make ultra-high resolution visualization of cells possible in thick and live samples, allow building highly-resolved and evolving structure and stoichiometry models of macromolecular assemblies and protein clusters in vivo and further categorizing them based on their live-cell context. This allows us to determine the  organization of myosin molecules in vivo, visualize their interaction with actin network and study their function in tension generation within the cytokinetic ring during cell division. The proposed research is enthusiastically supported by my close collaboration with Martin Booth, adaptive optics expert from Oxford University, Daniel Suter neuron biologist from Purdue University and Thomas Pollard, whose research focuses on molecular basis of cellular motility and cytokinesis from Yale University.

抽象的 我们正处于一个令人兴奋的生物学时代，可以通过快速发展来探索细胞的内部工作 成像方法。荧光显微镜具有两个主要优点：标记特异性和活细胞 兼容性。但是，它受衍射限制为大约250 nm的分辨率。最近的冒险 单分子开关纳米镜检查（SMSN，也称为Palm/Storm/FPALM）已经克服了这一点 通过随机打开单染料和关闭单染料的基本限制，使其排放事件为 及时分开。这使他们的中心位置可以在空间中以高精度定位，导致 重建的超级分辨图像，分辨率低至约25 nm。但是，其生物学应用是 限制有两个原因：（1）SMSN应用程序通常限制为固定样品，因为临时性差 分辨率和（2）应用程序仅限于薄薄样品中盖玻片接近的结构 在深度方向（Z）的下分辨率下分辨率，并在厚样品中迅速恶化分辨率。此外，SMSN 每个数据集产生数千至数百万个精确的单分子位置 - 大量 由于缺乏数据量化方法，很少探索信息。克服这些障碍将允许 可视化和定量活细胞中的纳米结构，确定荧光的化学计量法 标记的蛋白质，因此大大扩展了SMSN应用的宽度。 我们建议（1）开发用于在活细胞中超高分辨率成像和厚的超高分辨率成像的干涉率SMSN 通过各向同性5-10 nm的成像深度捕获3D活细胞动力学的样品 解决; （2）在空间，时间和多种颜色中开发结构和化学计量映射，以构建高 - 大分子复合物的分辨率3D模型和活细胞中的大蛋白质组件； （3）进一步 通过高 - 重建模型的另一个数量级（〜1 nm精度）提高分辨率 内容系统允许统计量化数千个细胞（每小时约3000个单元）。应用这些 发展过程中，我们将研究三种不同的分子组织和三种不同肌动物的功能 活裂变酵母和神经元运动中的细胞因子，重点是活神经元中的生长锥。 拟议的研究将首次使细胞的超高分辨率可视化在 厚实的样品，允许建造高度分辨和不断发展的结构以及化学计量模型的模型 大分子组件和蛋白质簇在体内，并根据其活细胞进一步对它们进行分类 语境。这使我们能够在体内确定肌球蛋白分子的组织，可视化它们的相互作用 通过肌动蛋白网络并研究细胞分裂中细胞动力环内张力产生的功能。 我与马丁·布斯（Martin Booth）的紧密合作，自适应的人的紧密合作，得到了拟议的研究 牛津大学的光学专家，普渡大学的丹尼尔·萨特神经元生物学家和托马斯·波拉德（Thomas Pollard） 其研究重点是耶鲁大学的细胞运动和细胞因子的分子基础。