New tools for automated high-resolution cryo-EM structure determination in RELION-3
- MRC Laboratory of Molecular Biology, United Kingdom
- Stockholm University, Sweden
- European Molecular Biology Laboratory, Germany
Abstract
Here, we describe the third major release of RELION. CPU-based vector acceleration has been added in addition to GPU support, which provides flexibility in use of resources and avoids memory limitations. Reference-free autopicking with Laplacian-of-Gaussian filtering and execution of jobs from python allows non-interactive processing during acquisition, including 2D-classification, de novo model generation and 3D-classification. Per-particle refinement of CTF parameters and correction of estimated beam tilt provides higher-resolution reconstructions when particles are at different heights in the ice, and/or coma-free alignment has not been optimal. Ewald sphere curvature correction improves resolution for large particles. We illustrate these developments with publicly available data sets: together with a Bayesian approach to beam-induced motion correction it leads to resolution improvements of 0.2-0.7 Å compared to previous RELION versions.
Data availability
We mostly use publicly available data sets from the EMPIAR data base at EMBL-EBI. For this study, we have submitted to this data base our own data on the human gamma-secretase complex (EMPIAR-10194) and on the high-resolution apo-ferritin sample described in the text (EMPIAR-10200).
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An atomic structure of human gamma-secretase [2925 multi-frame micrographs composed of 20 frames each in MRCS format]Electron Microscopy Public Image Archive, EMPIAR-10194.
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Human apo-ferritin reconstructed in RELION-3.0Electron Microscopy Public Image Archive, EMPIAR-10200.
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2.2 A resolution cryo-EM structure of beta-galactosidase in complex with a cell-permeant inhibitorElectron Microscopy Public Image Archive, EMPIAR-10061.
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40 Degree Tilted Single-Particle CryoEM of Highly Preferred Orientated Influenza Hemagglutinin TrimerElectron Microscopy Public Image Archive, EMPIAR-10097.
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Bacteriophage P22 mature virion capsid proteinElectron Microscopy Public Image Archive, EMPIAR-10083.
Article and author information
Author details
Funding
Medical Research Council (MC_UP_A025_1013)
- Sjors HW Scheres
Swiss National Science Foundation (SNF: P2BSP2 168735)
- Jasenko Zivanov
Swedish Research Council (2017-04641)
- Erik Lindahl
Knut och Alice Wallenbergs Stiftelse
- Erik Lindahl
Japan Society for the Promotion of Science (Overseas Research Fellowship)
- Takanori Nakane
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2018, Zivanov et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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New tools for automated high-resolution cryo-EM structure determination in RELION-3
eLife 7:e42166.
https://doi.org/10.7554/eLife.42166
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Segmentation is a critical data processing step in many applications of cryo-electron tomography. Downstream analyses, such as subtomogram averaging, are often based on segmentation results, and are thus critically dependent on the availability of open-source software for accurate as well as high-throughput tomogram segmentation. There is a need for more user-friendly, flexible, and comprehensive segmentation software that offers an insightful overview of all steps involved in preparing automated segmentations. Here, we present Ais: a dedicated tomogram segmentation package that is geared towards both high performance and accessibility, available on GitHub. In this report, we demonstrate two common processing steps that can be greatly accelerated with Ais: particle picking for subtomogram averaging, and generating many-feature segmentations of cellular architecture based on in situ tomography data. Featuring comprehensive annotation, segmentation, and rendering functionality, as well as an open repository for trained models at aiscryoet.org, we hope that Ais will help accelerate research and dissemination of data involving cryoET.
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