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Cited by 865

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cisTEM, user-friendly software for single-particle image processing

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Grant, Timothy, Rohou, Alexis, Grigorieff, Nikolaus·2018·eLife
DOI 10.7554/elife.35383

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Abstract

We have developed new open-source software called cisTEM (computational imaging system for transmission electron microscopy) for the processing of data for high-resolution electron cryo-microscopy and single-particle averaging. cisTEM features a graphical user interface that is used to submit jobs, monitor their progress, and display results. It implements a full processing pipeline including movie processing, image defocus determination, automatic particle picking, 2D classification, ab-initio 3D map generation from random parameters, 3D classification, and high-resolution refinement and reconstruction. Some of these steps implement newly-developed algorithms; others were adapted from previously published algorithms. The software is optimized to enable processing of typical datasets (2000 micrographs, 200 k – 300 k particles) on a high-end, CPU-based workstation in half a day or less, comparable to GPU-accelerated processing. Jobs can also be scheduled on large computer clusters using flexible run profiles that can be adapted for most computing environments. cisTEM is available for download from cistem.org.

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Research works printed but not linked: 53

  1. Abeyrathne, 2016, Ensemble cryo-EM uncovers inchworm-like translocation of a viral IRES through the ribosome, eLife, 5, e14874, 10.7554/eLife.14874 · DOI
  2. Bartesaghi, 2014, Structure of β-galactosidase at 3.2-Å resolution obtained by cryo-electron microscopy, PNAS, 111, 11709, 10.1073/pnas.1402809111 · DOI
  3. Bartesaghi, 2015, 2.2 A resolution cryo-EM structure of β-galactosidase in complex with a cell-permeant inhibitor, Science, 348, 1147, 10.1126/science.aab1576 · DOI · Paper page
  4. Chen, 2009, Molecular interactions in rotavirus assembly and uncoating seen by high-resolution cryo-EM, PNAS, 106, 10644, 10.1073/pnas.0904024106 · DOI
  5. Chen, 2013, High-resolution noise substitution to measure overfitting and validate resolution in 3D structure determination by single particle electron cryomicroscopy, Ultramicroscopy, 135, 24, 10.1016/j.ultramic.2013.06.004 · DOI · Paper page
  6. Cheng, 2015, A primer to single-particle cryo-electron microscopy, Cell, 161, 438, 10.1016/j.cell.2015.03.050 · DOI · Paper page
  7. Conesa Mingo, 2018, Scipion web tools: Easy to use cryo-EM image processing over the web, Protein Science, 27, 269, 10.1002/pro.3315 · DOI
  8. Crowther, 1996, MRC image processing programs, Journal of Structural Biology, 116, 9, 10.1006/jsbi.1996.0003 · DOI · Paper page
  9. Desfosses, 2014, SPRING - an image processing package for single-particle based helical reconstruction from electron cryomicrographs, Journal of Structural Biology, 185, 15, 10.1016/j.jsb.2013.11.003 · DOI
  10. Frank, 1996, SPIDER and WEB: processing and visualization of images in 3D electron microscopy and related fields, Journal of Structural Biology, 116, 190, 10.1006/jsbi.1996.0030 · DOI · Paper page
  11. Grant, 2015, Automatic estimation and correction of anisotropic magnification distortion in electron microscopes, Journal of Structural Biology, 192, 204, 10.1016/j.jsb.2015.08.006 · DOI
  12. Grant, 2015, Measuring the optimal exposure for single particle cryo-EM using a 2.6 Å reconstruction of rotavirus VP6, eLife, 4, e06980, 10.7554/eLife.06980 · DOI · Paper page
  13. Grigorieff, 2000, Resolution measurement in structures derived from single particles, Acta Crystallographica Section D Biological Crystallography, 56, 1270, 10.1107/S0907444900009549 · DOI
  14. Grigorieff, 2007, FREALIGN: high-resolution refinement of single particle structures, Journal of Structural Biology, 157, 117, 10.1016/j.jsb.2006.05.004 · DOI · Paper page
  15. Grigorieff, 2016, Frealign: An exploratory tool for single-particle Cryo-EM, Methods in enzymology, 579, 191, 10.1016/bs.mie.2016.04.013 · DOI
  16. Harauz, 1986, Exact filters for general geometry 3-dimensional reconstruction, Optik, 73, 146
  17. Henderson, 2013, Avoiding the pitfalls of single particle cryo-electron microscopy: Einstein from noise, PNAS, 110, 18037, 10.1073/pnas.1314449110 · DOI
  18. Hohn, 2007, SPARX, a new environment for Cryo-EM image processing, Journal of Structural Biology, 157, 47, 10.1016/j.jsb.2006.07.003 · DOI · Paper page
  19. Iudin, 2016, EMPIAR: a public archive for raw electron microscopy image data, Nature Methods, 13, 387, 10.1038/nmeth.3806 · DOI · Paper page
  20. Kimanius, 2016, Accelerated cryo-EM structure determination with parallelisation using GPUs in RELION-2, eLife, 5, e18722, 10.7554/eLife.18722 · DOI · Paper page
  21. Lander, 2009, Appion: an integrated, database-driven pipeline to facilitate EM image processing, Journal of Structural Biology, 166, 95, 10.1016/j.jsb.2009.01.002 · DOI · Paper page
  22. Loveland, 2017, Ensemble cryo-EM elucidates the mechanism of translation fidelity, Nature, 546, 113, 10.1038/nature22397 · DOI
  23. Lyumkis, 2013, Likelihood-based classification of cryo-EM images using FREALIGN, Journal of Structural Biology, 183, 377, 10.1016/j.jsb.2013.07.005 · DOI · Paper page
  24. Mastronarde, 2017, Automated tilt series alignment and tomographic reconstruction in IMOD, Journal of Structural Biology, 197, 102, 10.1016/j.jsb.2016.07.011 · DOI · Paper page
  25. Matthews, 1968, Solvent content of protein crystals, Journal of Molecular Biology, 33, 491, 10.1016/0022-2836(68)90205-2 · DOI · Paper page
  26. McDonough, 1995, Detection of Signals in Noise
  27. McMullan, 2016, Direct electron detectors, Methods in Enzymology, 579, 1, 10.1016/bs.mie.2016.05.056 · DOI
  28. McMullan, 2015, Thon rings from amorphous ice and implications of beam-induced Brownian motion in single particle electron cryo-microscopy, Ultramicroscopy, 158, 26, 10.1016/j.ultramic.2015.05.017 · DOI
  29. 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 · Paper page
  30. Moriya, 2017, High-resolution single particle analysis from electron cryo-microscopy images using SPHIRE, Journal of Visualized Experiments, 10.3791/55448 · DOI
  31. Oldham, 2016, Structure of the transporter associated with antigen processing trapped by herpes simplex virus, eLife, 5, e21829, 10.7554/eLife.21829 · DOI
  32. Penczek, 2014, CTER-rapid estimation of CTF parameters with error assessment, Ultramicroscopy, 140, 9, 10.1016/j.ultramic.2014.01.009 · DOI
  33. Punjani, 2017, cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination, Nature Methods, 14, 290, 10.1038/nmeth.4169 · DOI · Paper page
  34. Reboul, 2018, Single-particle cryo-EM-Improved ab initio 3D reconstruction with SIMPLE/PRIME, Protein Science, 27, 51, 10.1002/pro.3266 · DOI
  35. 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
  36. Roseman, 2004, FindEM--a fast, efficient program for automatic selection of particles from electron micrographs, Journal of Structural Biology, 145, 91, 10.1016/j.jsb.2003.11.007 · DOI
  37. Scheres, 2012, Prevention of overfitting in cryo-EM structure determination, Nature Methods, 9, 853, 10.1038/nmeth.2115 · DOI · Paper page
  38. Scheres, 2005, Maximum-likelihood multi-reference refinement for electron microscopy images, Journal of Molecular Biology, 348, 139, 10.1016/j.jmb.2005.02.031 · DOI · Paper page
  39. 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
  40. Sheth, 2015, Visualization and quality assessment of the contrast transfer function estimation, Journal of Structural Biology, 192, 222, 10.1016/j.jsb.2015.06.012 · DOI
  41. Sigworth, 2004, Classical detection theory and the cryo-EM particle selection problem, Journal of Structural Biology, 145, 111, 10.1016/j.jsb.2003.10.025 · DOI
  42. Sindelar, 2012, Optimal noise reduction in 3D reconstructions of single particles using a volume-normalized filter, Journal of Structural Biology, 180, 26, 10.1016/j.jsb.2012.05.005 · DOI
  43. Stewart, 2004, Noise bias in the refinement of structures derived from single particles, Ultramicroscopy, 102, 67, 10.1016/j.ultramic.2004.08.008 · DOI
  44. Subramaniam, 2016, Resolution advances in cryo-EM enable application to drug discovery, Current Opinion in Structural Biology, 41, 194, 10.1016/j.sbi.2016.07.009 · DOI
  45. Subramaniam, 2013, Structure of trimeric HIV-1 envelope glycoproteins, PNAS, 110, E4172, 10.1073/pnas.1313802110 · DOI
  46. 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 · Paper page
  47. Thon, 1966, Zur Defokussierungsabhängigkeit des Phasenkontrastes bei der elektronenmikroskopischen Abbildung, Zeitschrift für Naturforschung A, 21a, 476, 10.1515/zna-1966-0417 · DOI · Paper page
  48. van Heel, 1996, A new generation of the IMAGIC image processing system, Journal of Structural Biology, 116, 17, 10.1006/jsbi.1996.0004 · DOI · Paper page
  49. Van Heel, 1982, Detection of objects in quantum-noise-limited images, Ultramicroscopy, 7, 331, 10.1016/0304-3991(82)90258-3 · DOI
  50. van Heel, 2013, Finding trimeric HIV-1 envelope glycoproteins in random noise, PNAS, 110, E4175, 10.1073/pnas.1314353110 · DOI
  51. 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 · Paper page
  52. Zhang, 2016, Gctf: Real-time CTF determination and correction, Journal of Structural Biology, 193, 1, 10.1016/j.jsb.2015.11.003 · DOI
  53. Zhou, 2015, Structure and conformational states of the bovine mitochondrial ATP synthase by cryo-EM, eLife, 4, e10180, 10.7554/eLife.10180 · DOI · Paper page

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Metadata

Authors
Grant, T., Rohou, A., & Grigorieff, N.
Venue
eLife
Publisher
eLife Sciences Publications, Ltd
Published
2018-03-07
Volume
7
ISSN
2050-084X (ISSN-L)
DOI
10.7554/elife.35383
OpenAlex
W2791354025
Cited by
865
References
2
FWCI
52.04
Type
journal article
Language
en
Open access
gold
Licence
Funders
Howard Hughes Medical Institute

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