Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 4,621

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

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

Open access
Zivanov, Jasenko, Nakane, Takanori, Forsberg, Björn O, Kimanius, Dari, Hagen, Wim JH, Lindahl, Erik, Scheres, Sjors HW·2018·eLife
DOI 10.7554/elife.42166

Published version of a preprint

Open this paper in CoChat — free account

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.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.7554/elife.42166

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 1 references

Research works printed but not linked: 64

  1. Abrishami, 2015, Alignment of direct detection device micrographs using a robust Optical Flow approach, Journal of Structural Biology, 189, 163, 10.1016/j.jsb.2015.02.001 · DOI
  2. Bai, 2015, Sampling the conformational space of the catalytic subunit of human gamma-secretase, eLife, 4, e11182, 10.7554/eLife.11182 · DOI
  3. Bai, 2015, An atomic structure of human γ-secretase, Nature, 525, 212, 10.1038/nature14892 · DOI · Paper page
  4. Bartesaghi, 2015, 2.2 Å resolution cryo-EM structure of β-galactosidase in complex with a cell-permeant inhibitor, Science, 348, 1147, 10.1126/science.aab1576 · DOI
  5. Bartesaghi, 2018, Atomic Resolution Cryo-EM Structure of β-Galactosidase, Structure, 26, 848, 10.1016/j.str.2018.04.004 · DOI
  6. Bharat, 2015, Advances in Single-Particle Electron Cryomicroscopy Structure Determination applied to Sub-tomogram Averaging, Structure, 23, 1743, 10.1016/j.str.2015.06.026 · DOI
  7. Biyani, 2017, Focus: The interface between data collection and data processing in cryo-EM, Journal of Structural Biology, 198, 124, 10.1016/j.jsb.2017.03.007 · DOI
  8. Brilot, 2012, Beam-induced motion of vitrified specimen on holey carbon film, Journal of Structural Biology, 177, 630, 10.1016/j.jsb.2012.02.003 · DOI · Paper page
  9. Brown, 2015, Tools for macromolecular model building and refinement into electron cryo-microscopy reconstructions, Acta Crystallographica Section D Biological Crystallography, 71, 136, 10.1107/S1399004714021683 · DOI
  10. Cheng, 2018, High Resolution Single Particle Cryo-Electron Microscopy using Beam-Image Shift, 10.1101/306241 · DOI
  11. de la Rosa-Trevín, 2016, Scipion: A software framework toward integration, reproducibility and validation in 3D electron microscopy, Journal of Structural Biology, 195, 93, 10.1016/j.jsb.2016.04.010 · DOI
  12. de Val, 2012, Structural analysis of haemin demetallation by L-chain apoferritins, Journal of Inorganic Biochemistry, 112, 77, 10.1016/j.jinorgbio.2012.02.031 · DOI
  13. DeRosier, 2000, Correction of high-resolution data for curvature of the Ewald sphere, Ultramicroscopy, 81, 83, 10.1016/S0304-3991(99)00120-5 · DOI
  14. Eades, 2006, Obtaining TEM images with a uniform deviation parameter, Ultramicroscopy, 106, 432, 10.1016/j.ultramic.2005.12.002 · DOI
  15. Ekiert, 2012, Cross-neutralization of influenza A viruses mediated by a single antibody loop, Nature, 489, 526, 10.1038/nature11414 · DOI · Paper page
  16. Fernandez-Leiro, 2016, Unravelling biological macromolecules with cryo-electron microscopy, Nature, 537, 339, 10.1038/nature19948 · DOI
  17. Ferraro, 2017, Cisplatin Binding Sites in Human H-Chain Ferritin, Inorganic Chemistry, 56, 9064, 10.1021/acs.inorgchem.7b01072 · DOI
  18. Glaeser, 2011, Precise beam-tilt alignment and collimation are required to minimize the phase error associated with coma in high-resolution cryo-EM, Journal of Structural Biology, 174, 1, 10.1016/j.jsb.2010.12.005 · DOI
  19. Grant, 2018, cisTEM, user-friendly software for single-particle image processing, eLife, 7, e35383, 10.7554/eLife.35383 · DOI
  20. Grigorieff, 2007, FREALIGN: high-resolution refinement of single particle structures, Journal of Structural Biology, 157, 117, 10.1016/j.jsb.2006.05.004 · DOI
  21. Hall, 1991, The STAR file: a new format for electronic data transfer and archiving, Journal of Chemical Information and Modeling, 31, 326, 10.1021/ci00002a020 · DOI
  22. He, 2017, Helical reconstruction in RELION, Journal of Structural Biology, 198, 163, 10.1016/j.jsb.2017.02.003 · DOI · Paper page
  23. Hryc, 2017, Accurate model annotation of a near-atomic resolution cryo-EM map, PNAS, 114, 3103, 10.1073/pnas.1621152114 · DOI
  24. Iudin, 2016, EMPIAR: a public archive for raw electron microscopy image data, Nature Methods, 13, 387, 10.1038/nmeth.3806 · DOI · Paper page
  25. Jiang, 2008, Backbone structure of the infectious epsilon15 virus capsid revealed by electron cryomicroscopy, Nature, 451, 1130, 10.1038/nature06665 · DOI
  26. Kimanius, 2016, Accelerated cryo-EM structure determination with parallelisation using GPUs in RELION-2, eLife, 5, e18722, 10.7554/eLife.18722 · DOI
  27. Krivanek, 1995, Effect of three-fold astigmatism on high resolution electron micrographs, Ultramicroscopy, 60, 103, 10.1016/0304-3991(95)00050-B · DOI
  28. Kucukelbir, 2014, Quantifying the local resolution of cryo-EM density maps, Nature Methods, 11, 63, 10.1038/nmeth.2727 · DOI
  29. Li, 2013, Electron counting and beam-induced motion correction enable near-atomic-resolution single-particle cryo-EM, Nature Methods, 10, 584, 10.1038/nmeth.2472 · DOI
  30. Mastronarde, 2005, Automated electron microscope tomography using robust prediction of specimen movements, Journal of Structural Biology, 152, 36, 10.1016/j.jsb.2005.07.007 · DOI
  31. McLeod, 2017, Robust image alignment for cryogenic transmission electron microscopy, Journal of Structural Biology, 197, 279, 10.1016/j.jsb.2016.12.006 · DOI
  32. McMullan, 2009, Detective quantum efficiency of electron area detectors in electron microscopy, Ultramicroscopy, 109, 1126, 10.1016/j.ultramic.2009.04.002 · DOI
  33. Merk, 2016, Breaking Cryo-EM Resolution Barriers to Facilitate Drug Discovery, Cell, 165, 1698, 10.1016/j.cell.2016.05.040 · DOI
  34. Mindell, 2003, Accurate determination of local defocus and specimen tilt in electron microscopy, Journal of Structural Biology, 142, 334, 10.1016/S1047-8477(03)00069-8 · DOI
  35. Moriya, 2017, High-resolution Single Particle Analysis from Electron Cryo-microscopy Images Using SPHIRE, Journal of Visualized Experiments, 123, 10.3791/55448 · DOI
  36. Nakane, 2018, Characterisation of molecular motions in cryo-EM single-particle data by multi-body refinement in RELION, eLife, 7, e36861, 10.7554/eLife.36861 · DOI
  37. Naydenova, 2017, Measuring the effects of particle orientation to improve the efficiency of electron cryomicroscopy, Nature Communications, 8, 629, 10.1038/s41467-017-00782-3 · DOI
  38. Nelder, 1965, A Simplex Method for Function Minimization, The Computer Journal, 7, 308, 10.1093/comjnl/7.4.308 · DOI · Paper page
  39. Patwardhan, 2017, Trends in the Electron Microscopy Data Bank (EMDB), Acta Crystallographica Section D Structural Biology, 73, 503, 10.1107/S2059798317004181 · DOI
  40. Punjani, 2017, cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination, Nature Methods, 14, 290, 10.1038/nmeth.4169 · DOI · Paper page
  41. Rohou, 2015, CTFFIND4: Fast and accurate defocus estimation from electron micrographs, Journal of Structural Biology, 192, 216, 10.1016/j.jsb.2015.08.008 · DOI · Paper page
  42. Rosenthal, 2003, Optimal determination of particle orientation, absolute hand, and contrast loss in single-particle electron cryomicroscopy, Journal of Molecular Biology, 333, 721, 10.1016/j.jmb.2003.07.013 · DOI · Paper page
  43. Rubinstein, 2015, Alignment of cryo-EM movies of individual particles by optimization of image translations, Journal of Structural Biology, 192, 188, 10.1016/j.jsb.2015.08.007 · DOI
  44. Russo, 2018, Ewald sphere correction using a single side-band image processing algorithm, Ultramicroscopy, 187, 26, 10.1016/j.ultramic.2017.11.001 · DOI
  45. Saxton, 1995, Observation of lens aberrations for very high-resolution electron microscopy. I. Theory, Journal of Microscopy, 179, 201, 10.1111/j.1365-2818.1995.tb03633.x · DOI
  46. Scheres, 2012, Prevention of overfitting in cryo-EM structure determination, Nature Methods, 9, 853, 10.1038/nmeth.2115 · DOI · Paper page
  47. Scheres, 2012, A Bayesian view on cryo-EM structure determination, Journal of Molecular Biology, 415, 406, 10.1016/j.jmb.2011.11.010 · DOI · Paper page
  48. Scheres, 2012, RELION: implementation of a Bayesian approach to cryo-EM structure determination, Journal of Structural Biology, 180, 519, 10.1016/j.jsb.2012.09.006 · DOI · Paper page
  49. Scheres, 2015, Semi-automated selection of cryo-EM particles in RELION-1.3, Journal of Structural Biology, 189, 114, 10.1016/j.jsb.2014.11.010 · DOI · Paper page
  50. Tan, 2017, Addressing preferred specimen orientation in single-particle cryo-EM through tilting, Nature Methods, 14, 793, 10.1038/nmeth.4347 · DOI
  51. Tan, 2018, Sub-2 Å Ewald Curvature Corrected Single-Particle Cryo-EM, 10.1101/305599 · DOI
  52. Tang, 2007, EMAN2: an extensible image processing suite for electron microscopy, Journal of Structural Biology, 157, 38, 10.1016/j.jsb.2006.05.009 · DOI
  53. Tegunov, 2018, Real-time cryo-EM data pre-processing with Warp, bioRxiv, 10.1101/338558 · DOI
  54. van Heel, 1996, A new generation of the IMAGIC image processing system, Journal of Structural Biology, 116, 17, 10.1006/jsbi.1996.0004 · DOI
  55. Voss, 2009, DoG Picker and TiltPicker: software tools to facilitate particle selection in single particle electron microscopy, Journal of Structural Biology, 166, 205, 10.1016/j.jsb.2009.01.004 · DOI
  56. Wolf, 2006, Ewald sphere correction for single-particle electron microscopy, Ultramicroscopy, 106, 376, 10.1016/j.ultramic.2005.11.001 · DOI
  57. Woolford, 2007, The Laplacian of Gaussian and arbitrary z-crossings approach applied to automated single particle reconstruction, Journal of Structural Biology, 159, 122, 10.1016/j.jsb.2007.03.003 · DOI
  58. Yu, 2008, 3.88 A structure of cytoplasmic polyhedrosis virus by cryo-electron microscopy, Nature, 453, 415, 10.1038/nature06893 · DOI
  59. Zemlin, 1978, Coma-free alignment of high resolution electron microscopes with the aid of optical diffractograms, Ultramicroscopy, 3, 49, 10.1016/S0304-3991(78)80006-0 · DOI
  60. Zhang, 2008, Near-atomic resolution using electron cryomicroscopy and single-particle reconstruction, PNAS, 105, 1867, 10.1073/pnas.0711623105 · DOI
  61. Zhang, 2016, Gctf: Real-time CTF determination and correction, Journal of Structural Biology, 193, 1, 10.1016/j.jsb.2015.11.003 · DOI
  62. Zheng, 2017, MotionCor2: anisotropic correction of beam-induced motion for improved cryo-electron microscopy, Nature Methods, 14, 331, 10.1038/nmeth.4193 · DOI
  63. Zhu, 2018, Pushing the resolution limit by correcting the Ewald sphere effect in single-particle Cryo-EM reconstructions, Nature Communications, 9, 1552, 10.1038/s41467-018-04051-9 · DOI
  64. Zivanov, 2018, A Bayesian approach to beam-induced motion correction in cryo-EM single-particle analysis, 10.1101/384537 · DOI

Cited by

Items 101–179 of 179

Metadata

Authors
Zivanov, J., Nakane, T., Forsberg, B. O., Kimanius, D., Hagen, W. J., Lindahl, E., & Scheres, S. H.
Venue
eLife
Publisher
eLife Sciences Publications, Ltd
Published
2018-11-09
Volume
7
ISSN
2050-084X (ISSN-L)
DOI
10.7554/elife.42166
OpenAlex
W2899714098
Cited by
4,621
References
1
FWCI
198.08
Type
journal article
Language
en
Open access
gold
Licence
Funders
  • Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (SNF: P2BSP2 168735)
  • Japan Society for the Promotion of Science (Overseas Research Fellowship)
  • Swedish National Infrastructure for Computing (2017/12-54)
  • Vetenskapsrådet (2017-04641)
  • Knut och Alice Wallenbergs Stiftelse
  • Medical Research Council (MC_UP_A025_1013)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.