The Big Eye-dea: 3D/4D single cell resolution imaging of the mouse eye using lightsheet microscopy

Big Eye-dea：使用光片显微镜对小鼠眼睛进行 3D/4D 单细胞分辨率成像

• 批准号: 9166136
• 负责人: Katie Bentley
• 金额: $ 28.38万
• 依托单位: BETH ISRAEL DEACONESS MEDICAL CENTER
• 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 2017-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9166136
• 关键词: 4D Imaging; Adoption; Affect; Automobile Driving; Basic Science; Big Data; Blood Vessels; Case Study; Cells; Cellular Structures; Communities; Computer software; Data; Data Set; Development; Dimensions; Disease Progression; Disease model; Dissection; Environment; Evaluation; Eye; Eye diseases; Generations; Glaucoma; Goals; Growth; Image; Image Analysis; Imaging Device; Imaging Techniques; Investigation; Knowledge; Lead; Life; Light; Location; Mechanics; Methods; Microscope; Microscopy; Modeling; Morphogenesis; Morphology; Mus; Nerve Regeneration; Oxygen; Physiologic Intraocular Pressure; Physiologic pulse; Process; Property; Protocols documentation; Research; Research Personnel; Resolution; Retina; Retinal; Retinal Diseases; Slide; Software Tools; Structure; Techniques; Testing; Therapeutic; Time; Tissues; Traction; Validation; Vision; axon growth; cell behavior; cell motility; cell type; cellular imaging; coping; design; imaging modality; imaging system; improved; innovation; mouse model; nerve stem cell; neurovascular; novel; novel therapeutics; quantitative imaging; rapid technique; repaired; software development; stem cell therapy; success; therapeutic development; therapeutic evaluation; three dimensional structure; tissue processing; tool; user-friendly

Project Summary The long-term goal of this study is to optimize a new rapid, quantitative imaging approach utilizing lightsheet microscopy in order to dramatically improve the 3D and 4D cellular information obtainable from mouse models of eye disease. During retinal disease, significant changes in cell and tissue morphology are common. In retinopathies for example, excessive, thickened, bulbous, leaky blood vessels and abnormal `tufts' form, protruding out of their usual layered locations. These malformed vessels cause many problems including the generation of abnormal mechanical traction, which pulls on the different layers of the eye, eventually causing the retina to detach. Understanding how and why cells grow into abnormal three-dimensional structures is key to understanding retinal disease progression and treatment. However, current imaging techniques used to investigate retinas at the cellular level are limited in terms of 3D information, due to a practical issue that the naturally spherical eye tissue must be flattened to be viewed on a slide under the microscope. We therefore propose to optimize the first lightsheet microscope protocol for mouse eye imaging as its design permits imaging of large intact tissues, in their natural form, avoiding distortion through flattening of the 3D tissue. Furthermore, the faster dissection method and rapid image acquisition (less than a minute to image an entire eye) of the lightsheet microscope enables us to pursue the first robust method for live imaging of cell behavior in the eye. Previous attempts at live imaging have seen limited success due again to the excessive flattening and distortion of the spherical eye tissue required to transfer it onto a dish for conventional microscopy. In storing high-resolution cellular information across large sections of eye tissue, and potentially also over many time points in dynamic imaging, lightsheet microscopes generate very large datasets. The Big Data issues incurred can cause significant scaling issues for standard image analysis software. We therefore propose to develop easy to use, freely available computational software tools alongside optimization of the imaging protocol in order to facilitate rapid adoption of the technique and maximize the quantitative information obtainable by the wider community of eye disease researchers. Altogether we call this idea of an integrated 3D-4D imaging and analysis method the “Eye-dea approach”, standing for Eye – preserved Dimensional tissue Environment Analysis. In this study we propose to demonstrate the advantages of the Eye-dea approach by providing the first characterization of 3D and 4D cellular abnormalities in a retinopathy mouse model. Furthermore we will demonstrate that the approach can overcome a current barrier to therapeutic progress: a lack of 3D cellular imaging tools. Our test case is a potentially restorative glaucoma stem cell therapy. We will quantify the level of functional integration of neuronal progenitor cells into the retinal layers of the eye, not feasible with current imaging methods.

项目摘要 这项研究的长期目标是优化一种新的快速、定量的成像方法，利用光板 显微技术，以显著改进从小鼠模型中获得的3D和4D细胞信息 眼疾的症状。在视网膜疾病期间，细胞和组织形态的显著变化是常见的。在……里面 视网膜病变，例如，过度、增厚、球状、渗漏的血管和异常的“簇状”形态， 从它们通常的分层位置突出出来。这些畸形的血管造成了许多问题，包括 产生异常的机械牵引力，它拉动眼睛的不同层，最终导致 要分离的视网膜。了解细胞如何以及为什么会长成异常的三维结构是关键 以了解视网膜疾病的进展和治疗。然而，目前的成像技术用于 在细胞水平上研究视网膜在3D信息方面是有限的，因为一个实际问题是 自然球状的眼睛组织必须被扁平，才能在显微镜下的载玻片上观察到。因此，我们 建议在设计允许的情况下优化第一个用于小鼠眼睛成像的光片显微镜协议 以其自然形式对大的完整组织进行成像，避免通过扁平化3D组织而失真。 此外，更快的解剖方法和快速的图像采集(不到一分钟就可以对整个 眼睛)的光片显微镜使我们能够追求第一种健壮的细胞行为实时成像方法 在眼睛里。由于过度的扁平化，以前的实时成像的尝试再次取得了有限的成功 以及将其转移到常规显微镜的培养皿上所需的球形眼睛组织的扭曲。 在存储大片眼睛组织的高分辨率细胞信息时，可能还会超过 在动态成像的许多时间点，光片显微镜产生非常大的数据集。大数据 由此产生的问题可能会导致标准图像分析软件出现严重的缩放问题。因此，我们 建议开发易于使用、免费提供的计算软件工具，同时优化 成像协议，以促进该技术的快速采用和最大限度地提供定量信息 可由更广泛的眼病研究人员社区获得。总而言之，我们把这种综合的想法称为 3D-4D成像和分析方法“Eye-DEA Approach”，即眼保存维组织 环境分析。在这项研究中，我们建议通过以下方式展示Eye-DEA方法的优势 首次在视网膜病变小鼠模型中提供3D和4D细胞异常的特征。 此外，我们将证明该方法可以克服目前治疗进展的障碍： 缺乏3D细胞成像工具。我们的测试案例是一种潜在的恢复性青光眼干细胞疗法。我们会 量化神经前体细胞进入眼睛视网膜层的功能整合程度，而不是 用目前的成像方法是可行的。