Institute for Quantitative Biomedicine, Rutgers University.
Institute for Quantitative Biomedicine, Rutgers University; Department of Biochemistry & Microbiology, Rutgers University;
J Vis Exp. 2022 Jan 31(179). doi: 10.3791/63387.
Recent advances in both instrumentation and image processing software have made single-particle cryo-electron microscopy (cryo-EM) the preferred method for structural biologists to determine high-resolution structures of a wide variety of macromolecules. Multiple software suites are available to new and expert users for image processing and structure calculation, which streamline the same basic workflow: movies acquired by the microscope detectors undergo correction for beam-induced motion and contrast transfer function (CTF) estimation. Next, particle images are selected and extracted from averaged movie frames for iterative 2D and 3D classification, followed by 3D reconstruction, refinement, and validation. Because various software packages employ different algorithms and require varying levels of expertise to operate, the 3D maps they generate often differ in quality and resolution. Thus, users regularly transfer data between a variety of programs for optimal results. This paper provides a guide for users to navigate a workflow across the popular software packages: cryoSPARC v3, RELION-3, and Scipion 3 to obtain a near-atomic resolution structure of the adeno-associated virus (AAV). We first detail an image processing pipeline with cryoSPARC v3, as its efficient algorithms and easy-to-use GUI allow users to quickly arrive at a 3D map. In the next step, we use PyEM and in-house scripts to convert and transfer particle coordinates from the best quality 3D reconstruction obtained in cryoSPARC v3 to RELION-3 and Scipion 3 and recalculate 3D maps. Finally, we outline steps for further refinement and validation of the resultant structures by integrating algorithms from RELION-3 and Scipion 3. In this article, we describe how to effectively utilize three processing platforms to create a single and robust workflow applicable to a variety of data sets for high-resolution structure determination.
近年来，仪器和图像处理软件都取得了重大进展，使得单颗粒冷冻电子显微镜（cryo-EM）成为结构生物学家确定各种大分子高分辨率结构的首选方法。新用户和专家用户都可以使用多种软件套件进行图像处理和结构计算，这些套件简化了相同的基本工作流程：显微镜探测器获取的电影需要进行校正以消除束流引起的运动和对比度传递函数（CTF）估计。接下来，从平均电影帧中选择和提取粒子图像，进行迭代 2D 和 3D 分类，然后进行 3D 重建、细化和验证。由于各种软件包使用不同的算法，并且操作需要不同程度的专业知识，因此它们生成的 3D 图谱在质量和分辨率上往往存在差异。因此，用户经常在各种程序之间传输数据以获得最佳结果。本文为用户提供了一个指南，指导他们在流行的软件包 cryoSPARC v3、RELION-3 和 Scipion 3 之间进行工作流程导航，以获得腺相关病毒（AAV）的近原子分辨率结构。我们首先详细介绍了使用 cryoSPARC v3 的图像处理管道，因为其高效的算法和易于使用的 GUI 允许用户快速获得 3D 图谱。在下一个步骤中，我们使用 PyEM 和内部脚本将来自 cryoSPARC v3 中获得的最佳质量 3D 重建的粒子坐标转换和传输到 RELION-3 和 Scipion 3，并重新计算 3D 图谱。最后，我们概述了通过整合 RELION-3 和 Scipion 3 的算法进一步细化和验证结果结构的步骤。在本文中，我们描述了如何有效地利用三个处理平台创建一个单一且强大的工作流程，该流程适用于各种数据集的高分辨率结构确定。
