New tools for automated high-resolution cryo-EM structure determination in RELION-3

  1. Jasenko Zivanov
  2. Takanori Nakane
  3. Björn O Forsberg
  4. Dari Kimanius
  5. Wim JH Hagen
  6. Erik Lindahl  Is a corresponding author
  7. Sjors HW Scheres  Is a corresponding author
  1. MRC Laboratory of Molecular Biology, United Kingdom
  2. Stockholm University, Sweden
  3. 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).

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Jasenko Zivanov

    MRC Laboratory of Molecular Biology, Cambridge, United Kingdom
    Competing interests
    No competing interests declared.
  2. Takanori Nakane

    MRC Laboratory of Molecular Biology, Cambridge, United Kingdom
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2697-2767
  3. Björn O Forsberg

    Department of Biochemistry and Biophysics, Science for Life Laboratory, Stockholm University, Stockholm, Sweden
    Competing interests
    No competing interests declared.
  4. Dari Kimanius

    Department of Biochemistry and Biophysics, Science for Life Laboratory, Stockholm University, Stockholm, Sweden
    Competing interests
    No competing interests declared.
  5. Wim JH Hagen

    Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6229-2692
  6. Erik Lindahl

    Department of Biochemistry and Biophysics, Science for Life Laboratory, Stockholm University, Stockholm, Sweden
    For correspondence
    erik.lindahl@scilifelab.se
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2734-2794
  7. Sjors HW Scheres

    MRC Laboratory of Molecular Biology, Cambridge, United Kingdom
    For correspondence
    scheres@mrc-lmb.cam.ac.uk
    Competing interests
    Sjors HW Scheres, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0462-6540

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.

Reviewing Editor

  1. Edward H Egelman, University of Virginia, United States

Version history

  1. Received: September 19, 2018
  2. Accepted: November 6, 2018
  3. Accepted Manuscript published: November 9, 2018 (version 1)
  4. Version of Record published: November 22, 2018 (version 2)

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.

Metrics

  • 25,642
    views
  • 3,363
    downloads
  • 4,054
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Jasenko Zivanov
  2. Takanori Nakane
  3. Björn O Forsberg
  4. Dari Kimanius
  5. Wim JH Hagen
  6. Erik Lindahl
  7. Sjors HW Scheres
(2018)
New tools for automated high-resolution cryo-EM structure determination in RELION-3
eLife 7:e42166.
https://doi.org/10.7554/eLife.42166

Share this article

https://doi.org/10.7554/eLife.42166

Further reading

    1. Cell Biology
    2. Structural Biology and Molecular Biophysics
    Aaron JO Lewis, Frank Zhong ... Ramanujan S Hegde
    Research Article

    The protein translocon at the endoplasmic reticulum comprises the Sec61 translocation channel and numerous accessory factors that collectively facilitate the biogenesis of secretory and membrane proteins. Here, we leveraged recent advances in cryo-electron microscopy (cryo-EM) and structure prediction to derive insights into several novel configurations of the ribosome-translocon complex. We show how a transmembrane domain (TMD) in a looped configuration passes through the Sec61 lateral gate during membrane insertion; how a nascent chain can bind and constrain the conformation of ribosomal protein uL22; and how the translocon-associated protein (TRAP) complex can adjust its position during different stages of protein biogenesis. Most unexpectedly, we find that a large proportion of translocon complexes contains RAMP4 intercalated into Sec61’s lateral gate, widening Sec61’s central pore and contributing to its hydrophilic interior. These structures lead to mechanistic hypotheses for translocon function and highlight a remarkably plastic machinery whose conformations and composition adjust dynamically to its diverse range of substrates.

    1. Biochemistry and Chemical Biology
    2. Structural Biology and Molecular Biophysics
    Roberto Efraín Díaz, Andrew K Ecker ... James S Fraser
    Research Article

    Chitin is an abundant biopolymer and pathogen-associated molecular pattern that stimulates a host innate immune response. Mammals express chitin-binding and chitin-degrading proteins to remove chitin from the body. One of these proteins, Acidic Mammalian Chitinase (AMCase), is an enzyme known for its ability to function under acidic conditions in the stomach but is also active in tissues with more neutral pHs, such as the lung. Here, we used a combination of biochemical, structural, and computational modeling approaches to examine how the mouse homolog (mAMCase) can act in both acidic and neutral environments. We measured kinetic properties of mAMCase activity across a broad pH range, quantifying its unusual dual activity optima at pH 2 and 7. We also solved high-resolution crystal structures of mAMCase in complex with oligomeric GlcNAcn, the building block of chitin, where we identified extensive conformational ligand heterogeneity. Leveraging these data, we conducted molecular dynamics simulations that suggest how a key catalytic residue could be protonated via distinct mechanisms in each of the two environmental pH ranges. These results integrate structural, biochemical, and computational approaches to deliver a more complete understanding of the catalytic mechanism governing mAMCase activity at different pH. Engineering proteins with tunable pH optima may provide new opportunities to develop improved enzyme variants, including AMCase, for therapeutic purposes in chitin degradation.