A Robust Single-Particle Cryo-Electron Microscopy (cryo-EM) Processing Workflow with cryoSPARC, RELION, and Scipion

Summary

This article describes how to effectively utilize three cryo-EM processing platforms, i.e., cryoSPARC v3, RELION-3, and Scipion 3, to create a single and robust workflow applicable to a variety of single-particle data sets for high-resolution structure determination.

Abstract

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.

Introduction

Cryo-electron microscopy (cryo-EM) and single-particle analysis (SPA) enable structure determination of a wide variety of biomolecular assemblies in their hydrated state, helping to illuminate the roles of these macromolecules in atomic detail. Improvements in microscope optics, computer hardware, and image processing software have made it possible to determine structures of biomolecules at resolution reaching beyond 2 Å^1,2,3. More than 2,300 cryo-EM structures were deposited in the Protein Data Bank (PDB) in 2020, compared to 192 structures in 2014⁴

Protocol

1. Creating a new cryoSPARC v3 project and importing data

NOTE: Data was acquired at Oregon Health and Science University (OHSU) in Portland using a 300 kV Titan Krios electron microscope equipped with a Falcon 3 direct electron detector. Images were collected in a counting mode with a total dose of 28.38 e⁻/Ų fractioned across 129 frames, and a defocus range from -0.5 µm to -2.5 µm, at a pixel size of 1.045 Å using EPU. The sample of AAV-DJ was provided by the staff of OHSU.

1. Open cryoSPARC v3 in a web browser and click the Projects header. Select....

Results

We have presented a comprehensive SPA pipeline to obtain a high-resolution structure using three different processing platforms: cryoSPARC v3, RELION-3, and Scipion 3. Figure 1 and Figure 4 summarize the general processing workflow, and Table 1 details refinement protocols. These protocols were used during refinements of a 2.3 Å structure of AAV, achieving near Nyquist resolution.

Movies were first imported to cr.......

Discussion

In this article, we present a robust SPA workflow for cryo-EM data processing across various software platforms to achieve high-resolution 3D reconstructions (Figure 1). This workflow is applicable to a wide variety of biological macromolecules. The subsequent steps of the protocol are outlined in Figure 4, including movie pre-processing, particle picking and classification, and multiple methods for structure refinements (Table 1

Materials

Name	Company	Catalog Number	Comments
CryoSPARC	Structura Biotechnology Inc.	https://cryosparc.com/
CTFFIND 4	Howard Hughes Medical Institute, UMass Chan Medical School	https://grigoriefflab.umassmed.edu/ctffind4
MotionCorr2	UCSF Macromolecular Structure Group	https://msg.ucsf.edu/software
Phenix	Computational Tools for Macromolecular Neutron Crystallography (MNC)	http://www.phenix-online.org/
PyEM	Univerisity of California, San Francisco	https://github.com/asarnow/pyem
RELION	MRC Laboratory of Structural Biology	https://www3.mrc-lmb.cam.ac.uk/relion/index.php/Main_Page
Scipion	Instruct Image Processing Center (I2PC), SciLifeLab	http://scipion.i2pc.es/
UCSF Chimera	UCSF Resource for Biocomputing, Visualization, and Informatics	https://www.cgl.ucsf.edu/chimera/