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 我们正处于一个激动人心的生物学时代，可以通过快速发展的细胞来探索细胞的内部运作 荧光显微镜成像方法有两大优点：标记特异性和活细胞。 然而，它受到最近出现的大约 250 nm 分辨率的限制。 单分子开关纳米显微镜（SMSN，也称为 PALM/STORM/FPALM）克服了这个问题 通过随机地打开和关闭单一染料来实现基本限制，使得它们的发射事件是 这使得它们的中心位置能够在空间上高精度定位，从而产生 重建的超分辨率图像的分辨率低至~25 nm，但其生物学应用却很有限。 受到两个原因的限制：(1) SMSN 应用通常由于较差的时间性而仅限于固定样本。 分辨率和（2）该应用仅限于薄样品中靠近盖玻片的结构，因为它的 深度方向 (z) 的分辨率较差，并且厚样品中的分辨率迅速恶化。 每个数据集生成数千到数百万个精确的单分子位置 - 大量 由于缺乏数据量化方法而很少探索的信息将能够克服这些障碍。 活细胞中纳米结构的可视化和定量，确定荧光的化学计量 标记蛋白质，从而极大地扩展了 SMSN 应用的广度。 我们建议 (1) 开发干涉式 SMSN，用于活细胞和厚膜中的超高分辨率成像 通过高达 50 µm 的各向同性 5-10 nm 成像深度捕获 3D 活细胞动态的样品 分辨率；（2）开发空间、时间和多种颜色的结构和化学计量映射，以构建高分辨率 活细胞中大分子复合物和大型蛋白质组装体的分辨率 3D 模型；以及 (3) 进一步 将重建模型的分辨率提高另一个数量级（~1 nm 精度） 内容系统允许对数千个细胞（每小时约 3000 个细胞）进行统计量化。 随着进展，我们将研究三种不同肌球蛋白的不同分子组织和功能 活裂殖酵母中的胞质分裂和集中于活神经元生长锥的神经元运动。 拟议的研究将首次使细胞的超高分辨率可视化成为可能 厚且活的样品，允许构建高分辨率和不断发展的结构和化学计量模型 体内大分子组装体和蛋白质簇，并根据其活细胞进一步对它们进行分类 这使我们能够确定体内肌球蛋白分子的组织，可视化它们的相互作用。 与肌动蛋白网络并研究它们在细胞分裂过程中细胞因子环内张力产生中的功能。 拟议的研究得到了我与马丁·布斯 (Martin Booth) 的密切合作的热情支持，自适应 牛津大学光学专家、普渡大学神经元生物学家 Daniel Suter 和 Thomas Pollard， 他的研究重点是耶鲁大学细胞运动和胞质分裂的分子基础。