Abstract
Cryo-electron tomography and subtomogram averaging (STA) has developed rapidly in recent years. It provides structures of macromolecular complexes in situ and in cellular context at or below subnanometer resolution and has led to unprecedented insights into the inner working of molecular machines in their native environment, as well as their functional relevant conformations and spatial distribution within biological cells or tissues. Given the tremendous potential of cryo-electron tomography STA in in situ structural cell biology, we previously developed emClarity, a graphics processing unit-accelerated image-processing software that offers STA and classification of macromolecular complexes at high resolution. However, the workflow remains challenging, especially for newcomers to the field. In this protocol, we describe a detailed workflow, processing and parameters associated with each step, from initial tomography tilt-series data to the final 3D density map, with several features unique to emClarity. We use four different samples, including human immunodeficiency virus type 1 Gag assemblies, ribosome and apoferritin, to illustrate the procedure and results of STA and classification. Following the processing steps described in this protocol, along with a comprehensive tutorial and guidelines for troubleshooting and parameter optimization, one can obtain density maps up to 2.8 Å resolution from six tilt series by cryo-electron tomography STA.
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Data availability
The Gag dataset (five tilt series) and apoferritin dataset (six tilt series) have been deposited in the EMPIAR database under accession codes EMPIAR-10643 and EMPIAR-10787, respectively. The resulting final reconstructions have been deposited in EMDB under the following accession codes: Gag-T8I, EMD-13390; Gag-WT, EMD-13354; apoferritin, EMD-13271; and ribosome, EMD-13270.
Code availability
The emClarity software is freely available at https://github.com/bHimes/emClarity/wiki. The tutorial documentation is available at https://github.com/ffyr2w/emClarity-tutorial.
References
Zhang, P. Advances in cryo-electron tomography and subtomogram averaging and classification. Curr. Opin. Struct. Biol. 58, 249–258 (2019).
Kaplan, M. et al. In situ imaging and structure determination of biomolecular complexes using electron cryo-tomography. Methods Mol. Biol. 2215, 83–111 (2021).
Turk, M. & Baumeister, W. The promise and the challenges of cryo-electron tomography. FEBS Lett. 594, 3243–3261 (2020).
Mahamid, J. et al. Visualizing the molecular sociology at the HeLa cell nuclear periphery. Science 351, 969–972 (2016).
Forster, F. & Hegerl, R. Structure determination in situ by averaging of tomograms. Methods Cell Biol. 79, 741–767 (2007).
Bykov, Y. S. et al. The structure of the COPI coat determined within the cell. eLife https://doi.org/10.7554/eLife.32493 (2017).
Zhang, Y. et al. Molecular architecture of the luminal ring of the Xenopus laevis nuclear pore complex. Cell Res. 30, 532–540 (2020).
Pfeffer, S. et al. Structure of the native Sec61 protein-conducting channel. Nat. Commun. 6, 8403 (2015).
Cassidy, C. K. et al. CryoEM and computer simulations reveal a novel kinase conformational switch in bacterial chemotaxis signaling. eLife https://doi.org/10.7554/eLife.08419 (2015).
Dodonova, S. O., Prinz, S., Bilanchone, V., Sandmeyer, S. & Briggs, J. A. G. Structure of the Ty3/Gypsy retrotransposon capsid and the evolution of retroviruses. Proc. Natl Acad. Sci. USA 116, 10048–10057 (2019).
Mattei, S., Glass, B., Hagen, W. J., Krausslich, H. G. & Briggs, J. A. The structure and flexibility of conical HIV-1 capsids determined within intact virions. Science 354, 1434–1437 (2016).
Dick, R. A. et al. Structures of immature EIAV Gag lattices reveal a conserved role for IP6 in lentivirus assembly. PLoS Pathog. 16, e1008277 (2020).
Schur, F. K. et al. An atomic model of HIV-1 capsid-SP1 reveals structures regulating assembly and maturation. Science 353, 506–508 (2016).
Qu, K. et al. Structure and architecture of immature and mature murine leukemia virus capsids. Proc. Natl Acad. Sci. USA 115, E11751–E11760 (2018).
von Kugelgen, A. et al. In situ structure of an intact lipopolysaccharide-bound bacterial surface layer. Cell 180, 348–358 e315 (2020).
Tegunov, D., Xue, L., Dienemann, C., Cramer, P. & Mahamid, J. Multi-particle cryo-EM refinement with M visualizes ribosome-antibiotic complex at 3.5 A in cells. Nat. Methods 18, 186–193 (2021).
Lucic, V., Rigort, A. & Baumeister, W. Cryo-electron tomography: the challenge of doing structural biology in situ. J. Cell Biol. 202, 407–419 (2013).
Wan, W. & Briggs, J. A. Cryo-electron tomography and subtomogram averaging. Methods Enzymol. 579, 329–367 (2016).
Turonova, B., Schur, F. K. M., Wan, W. & Briggs, J. A. G. Efficient 3D-CTF correction for cryo-electron tomography using NovaCTF improves subtomogram averaging resolution to 3.4A. J. Struct. Biol. 199, 187–195 (2017).
Heumann, J. M., Hoenger, A. & Mastronarde, D. N. Clustering and variance maps for cryo-electron tomography using wedge-masked differences. J. Struct. Biol. 175, 288–299 (2011).
Nicastro, D. et al. The molecular architecture of axonemes revealed by cryoelectron tomography. Science 313, 944–948 (2006).
Chen, M. et al. Convolutional neural networks for automated annotation of cellular cryo-electron tomograms. Nat. Methods 14, 983–985 (2017).
Galaz-Montoya, J. G., Flanagan, J., Schmid, M. F. & Ludtke, S. J. Single particle tomography in EMAN2. J. Struct. Biol. 190, 279–290 (2015).
Galaz-Montoya, J. G. et al. Alignment algorithms and per-particle CTF correction for single particle cryo-electron tomography. J. Struct. Biol. 194, 383–394 (2016).
Bharat, T. A. & Scheres, S. H. Resolving macromolecular structures from electron cryo-tomography data using subtomogram averaging in RELION. Nat. Protoc. 11, 2054–2065 (2016).
Bharat, T. A. M., Russo, C. J., Lowe, J., Passmore, L. A. & Scheres, S. H. W. Advances in single-particle electron cryomicroscopy structure determination applied to sub-tomogram averaging. Structure 23, 1743–1753 (2015).
Castano-Diez, D., Kudryashev, M., Arheit, M. & Stahlberg, H. Dynamo: a flexible, user-friendly development tool for subtomogram averaging of cryo-EM data in high-performance computing environments. J. Struct. Biol. 178, 139–151 (2012).
Maurer, U. E. et al. The structure of herpesvirus fusion glycoprotein B-bilayer complex reveals the protein–membrane and lateral protein–protein interaction. Structure 21, 1396–1405 (2013).
Forster, F., Pruggnaller, S., Seybert, A. & Frangakis, A. S. Classification of cryo-electron sub-tomograms using constrained correlation. J. Struct. Biol. 161, 276–286 (2008).
Hrabe, T. et al. PyTom: a python-based toolbox for localization of macromolecules in cryo-electron tomograms and subtomogram analysis. J. Struct. Biol. 178, 177–188 (2012).
Winkler, H. 3D reconstruction and processing of volumetric data in cryo-electron tomography. J. Struct. Biol. 157, 126–137 (2007).
Himes, B. A. & Zhang, P. emClarity: software for high-resolution cryo-electron tomography and subtomogram averaging. Nat. Methods 15, 955–961 (2018).
Liu, C. et al. The architecture of inactivated SARS-CoV-2 with postfusion spikes revealed by cryo-EM and cryo-ET. Structure 28, 1218–1224 e1214 (2020).
Watanabe, R. et al. The in situ structure of Parkinson’s disease-linked LRRK2. Cell 182, 1508–1518 e1516 (2020).
Sutton, G. et al. Assembly intermediates of orthoreovirus captured in the cell. Nat. Commun. 11, 4445 (2020).
Tan, T. Y. et al. Capsid protein structure in Zika virus reveals the flavivirus assembly process. Nat. Commun. 11, 895 (2020).
Unchwaniwala, N. et al. Subdomain cryo-EM structure of nodaviral replication protein A crown complex provides mechanistic insights into RNA genome replication. Proc. Natl Acad. Sci. USA 117, 18680–18691 (2020).
Gibson, K. H. et al. An asymmetric sheath controls flagellar supercoiling and motility in the leptospira spirochete. eLife https://doi.org/10.7554/eLife.53672 (2020).
Cassidy, C. K. et al. Structure and dynamics of the E. coli chemotaxis core signaling complex by cryo-electron tomography and molecular simulations. Commun. Biol. 3, 24 (2020).
Rohou, A. & Grigorieff, N. CTFFIND4: fast and accurate defocus estimation from electron micrographs. J. Struct. Biol. 192, 216–221 (2015).
Scheres, S. H. & Chen, S. Prevention of overfitting in cryo-EM structure determination. Nat. Methods 9, 853–854 (2012).
Rosenthal, P. B. & Henderson, R. Optimal determination of particle orientation, absolute hand, and contrast loss in single-particle electron cryomicroscopy. J. Mol. Biol. 333, 721–745 (2003).
Mastronarde, D. N. & Held, S. R. Automated tilt series alignment and tomographic reconstruction in IMOD. J. Struct. Biol. 197, 102–113 (2017).
Scheres, S. H. RELION: implementation of a Bayesian approach to cryo-EM structure determination. J. Struct. Biol. 180, 519–530 (2012).
Grant, T., Rohou, A. & Grigorieff, N. cisTEM, user-friendly software for single-particle image processing. eLife https://doi.org/10.7554/eLife.35383 (2018).
Heymann, J. B. Guidelines for using Bsoft for high resolution reconstruction and validation of biomolecular structures from electron micrographs. Protein Sci. 27, 159–171 (2018).
Mendonca, L. et al. CryoET structures of immature HIV Gag reveal six-helix bundle. Commun. Biol. 4, 481 (2021).
Acknowledgements
We are grateful to Y. Zhu for discussion and critical reading of the manuscript. We acknowledge Diamond for access and support of the CryoEM facilities at the UK national Electron Bio-Imaging Centre (eBIC, proposal CM26464), funded by the Wellcome Trust, Medical Research Council (MRC) and Biotechnology and Biological Sciences Research Council (BBSRC). The computational aspects of this research were supported by the Wellcome Trust Core Award grant number 203141/Z/16/Z and the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC). This work was supported by the National Institutes of Health grants AI150481, the UK Wellcome Trust Investigator Award 206422/Z/17/Z, the UK Biotechnology and Biological Sciences Research Council grant BB/S003339/1, and the European Research Council Advanced Grant (ERC AdG) grant 101021133.
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P.Z. conceived the research and designed the experiments. Y.S. prepared the apoferritin on graphene grids, and D.C. collected data. T.N., L.M. and Y.S. performed tomography reconstruction and STA and classification. T.F. wrote the emClarity tutorial. B.A.H. and T.F. updated code/binaries with new features in later versions of emClarity. T.N. and P.Z. wrote the manuscript with support from all the authors.
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Nature Protocols thanks Peter J. Peters and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Key references using this protocol
Liu, C. et al. Structure 28, 1218–1224.e1214 (2020): https://doi.org/10.1016/j.str.2020.10.001
Watanabe, R. et al. Cell 182, 1508–1518.e1516 (2020): https://doi.org/10.1016/j.cell.2020.08.004
Sutton, G. et al. Nat. Commun. 11, 4445 (2020): https://doi.org/10.1038/s41467-020-18243-9
Tan, T. Y. et al. Nat. Commun. 11, 895 (2020): https://doi.org/10.1038/s41467-020-14647-9
Unchwaniwala, N. et al. Proc. Natl Acad. Sci. USA 117, 18680–18691 (2020): https://doi.org/10.1073/pnas.2006165117
Gibson, K. H. et al. eLife 9, e53672 (2020): https://doi.org/10.7554/eLife.53672
Cassidy, C. K. et al. Commun. Biol. 3, 24 (2020): https://doi.org/10.1038/s42003-019-0748-0
Key data used in this protocol
Eisenstein, F. et al. J. Struct. Biol. 208, 107–114 (2019): https://doi.org/10.1016/j.jsb.2019.08.006
Schur, F. K. et al. Science 353 506–508 (2016): https://doi.org/10.1126/science.aaf9620
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Ni, T., Frosio, T., Mendonça, L. et al. High-resolution in situ structure determination by cryo-electron tomography and subtomogram averaging using emClarity. Nat Protoc 17, 421–444 (2022). https://doi.org/10.1038/s41596-021-00648-5
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DOI: https://doi.org/10.1038/s41596-021-00648-5
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