Accelerated cryo-EM structure determination with parallelisation using GPUs in RELION-2
- Stockholm University, Sweden
- MRC Laboratory of Molecular Biology,, United Kingdom
Abstract
By reaching near-atomic resolution for a wide range of specimens, single-particle cryo-EM structure determination is transforming structural biology. However, the necessary calculations come at increased computational costs, introducing a bottleneck that is currently limiting throughput and the development of new methods. Here, we present an implementation of the RELION image processing software that uses graphics processors (GPUs) to address the most computationally intensive steps of its cryo-EM structure determination workflow. Both image classification and high-resolution refinement have been accelerated more than an order-of-magnitude, and template-based particle selection has been accelerated two orders-of-magnitude on desktop hardware. Memory requirements on GPUs have been reduced to fit widely available hardware, and we show that the use of single precision arithmetic does not adversely affect results. This enables high-resolution cryo-EM structure determination in a matter of days on a single workstation.
Data availability
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RELION-2.0 reconstruction for beta-galactosidase data in EMPIAR-10061Publicly available at the EBI Protein Data Bank in Europe (accession no: EMD-4116).
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Beta-galactosidase Falcon-II micrographs plus manually selected coordinates by Richard HendersonPublicly available at the EBI Electron Microscopy Pilot Image Archive (accession no: EMPIAR-10017).
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Cryo-EM structure of the Plasmodium falciparum 80S ribosome bound to the anti-protozoan drug emetinePublicly available at the EBI Electron Microscopy Pilot Image Archive (accession no: EMPIAR-10028).
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2.2 A resolution cryo-EM structure of beta-galactosidase in complex with a cell-permeant inhibitorPublicly available at the EBI Electron Microscopy Pilot Image Archive (accession no: EMPIAR-10061).
Article and author information
Author details
Funding
Medical Research Council (MC UP A025 1013)
- Sjors HW Scheres
Vetenskapsrådet (2013-5901)
- Erik Lindahl
Horizon 2020 (EINFRA-2015-1-675728)
- Erik Lindahl
Swedish e-Science Research Centre
- Erik Lindahl
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2016, Kimanius 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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Accelerated cryo-EM structure determination with parallelisation using GPUs in RELION-2
eLife 5:e18722.
https://doi.org/10.7554/eLife.18722
Further reading
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- Structural Biology and Molecular Biophysics
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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