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.

摘要 我们正处于一个激动人心的生物学时代，细胞的内部运作可以通过快速开发 成像方法荧光显微镜有两大优势：标记特异性和活细胞 兼容性.然而，它受到衍射的限制，分辨率约为250 nm。最近出现的 单分子切换纳米显微镜（SMSN，也称为PALM/STORM/FPAL）克服了这一点 通过随机开关单个染料的基本限制，使得它们的发射事件 在时间上分开。这允许它们的中心位置在空间中以高精度定位，从而导致 重建超分辨图像，分辨率低至~25 nm。然而，其生物学应用是 由于两个原因而受到限制：（1）由于较差的时域特性，SMSN应用通常限于固定样本。 分辨率和（2）应用程序被限制到结构接近盖片薄样品，因为它 在深度方向（z）上的低分辨率和在厚样品中的快速恶化的分辨率。此外，SMSN 每个数据集产生数千到数百万个精确的单分子位置-大量的 由于缺乏数据量化方法，很少对信息进行探讨。克服这些障碍将使 活细胞中纳米结构的可视化和定量， 标记的蛋白质，从而大大扩展了SMSN应用的广度。 我们建议（1）开发用于活细胞和厚细胞中超高分辨率成像的干涉SMSN 样品通过成像深度高达50 µm的各向同性5-10 nm捕获3D活细胞动态 （2）发展空间、时间和多种颜色的结构和化学计量映射， 活细胞中的大分子复合物和大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（约1 nm精度）， 内容物系统允许对数千个细胞进行统计定量（每小时约3000个细胞）。应用这些 发展，我们将研究不同的分子组织和功能的三种不同的肌球蛋白， 活分裂酵母中的胞质分裂和活神经元中的神经元运动集中于生长锥。 这项拟议中的研究将首次使细胞的超高分辨率可视化成为可能， 厚的和活的样品，允许建立高分辨率和不断发展的结构和化学计量模型， 大分子组装和蛋白质簇在体内，并进一步分类他们的基础上，他们的活细胞 上下文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的细胞动力学环内的张力产生中的功能。 这项研究得到了我与马丁·布斯（Martin Booth）的密切合作的热情支持， 牛津大学的光学专家、普渡大学的丹尼尔苏特神经元生物学家和托马斯波拉德， 来自耶鲁大学，主要研究细胞运动和胞质分裂的分子基础。