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A complete data processing workflow for cryo-ET and subtomogram averaging

Abstract

Electron cryotomography is currently the only method capable of visualizing cells in three dimensions at nanometer resolutions. While modern instruments produce massive amounts of tomography data containing extremely rich structural information, data processing is very labor intensive and the results are often limited by the skills of the personnel rather than the data. We present an integrated workflow that covers the entire tomography data processing pipeline, from automated tilt series alignment to subnanometer resolution subtomogram averaging. Resolution enhancement is made possible through the use of per-particle per-tilt contrast transfer function correction and alignment. The workflow greatly reduces human bias, increases throughput and more closely approaches data-limited resolution for subtomogram averaging in both purified macromolecules and cells.

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Fig. 1: Diagram of cryo-ET data processing workflow.
Fig. 2: Results of iterative tomogram alignment and reconstruction.
Fig. 3: Particle extraction and initial model generation.
Fig. 4: Subtomogram refinement.

Data availability

The subtomogram averages are deposited in the Electron Microscopy Data Bank (EMDB): EMD-0529 and EMD-0530.

Code availability

EMAN2.3 is a free and open source software available from http://eman2.org with source code on GitHub (https://github.com/cryoem/eman2).

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Acknowledgements

This work was partially supported by NIH grant nos. R01GM080139 and P01GM121203, the Welch Foundation (grant no. Q-1967-20180324), BCM BMB department seed funds and a Houston Area Molecular Biophysics Program training grant from the Keck Center of the Gulf Coast Consortium (NIH grant no. T32 GM008280-30). We also thank early users for testing the workflow and providing valuable feedback.

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Authors

Contributions

M.C., J.M.B. and S.J.L. designed and implemented the protocol. X.S., Z.W. and S.Y.S. provided test datasets. M.C., J.M.B. and S.Y.S. tested and refined the protocol. M.C., J.M.B. and S.J.L. wrote the manuscript.

Corresponding author

Correspondence to Steven J. Ludtke.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Rita Strack was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Integrated supplementary information

Supplementary Figure 1 Tiling strategy for tomogram reconstruction.

(a) Reconstruction of individual tiles. Each tile is padded to the size of the dashed box during the reconstruction, and clipped to the size of the solid box. (b) The per-tile weighting function and slice view of a masked tile. (c) Overlapping tiles to reduce edge effects. (d) Resulting by-tile reconstruction.

Supplementary Figure 2 Subtilt CTF determination.

We measure CTF in each tilt image by tiling the tilt images and calculating coherent power spectra along strips parallel to the tilt axis. These power spectra, geometric information from the tilt angle, and the 3D position of each extracted particle are used to determine per-particle defoci. Once CTF curves have been fit to the data, the parameters are used to phase flip individual particle subtilt images for subsequent processing.

Supplementary Figure 3 Determination of tilt axis rotation angle using Fourier sum approach.

(a) Filtered and masked images from the center tilt and a high angle tilt in a tilt series. (b) Coherent average of Fourier transform intensity of all translationally aligned and masked images in the tilt series. (c) Plot of the average intensity of (b) along a ray at different orientation. The peak annotated by the dashed line is the tilt axis orientation. Note the points at 0 and 90 degrees are set to zero to avoid the impact from background pattern.

Supplementary Figure 4 Comparison of automatic tilt series alignment protocol.

(a) An example of successful case for both IMOD and EMAN2 pipeline. From left to right: 45 degree tilt image; center slice view of the tomogram from ETDB (using IMOD); center slice view of the tomogram reconstructed in EMAN2. (b) An example of ‘failed’ case for IMOD that is successful aligned by EMAN2. Note the large amount of ice contaimination in high angle tilt images that likely leads to the failure of original IMOD alignment.

Supplementary Figure 5 Comparison of different reconstruction methods.

(a) A tomogram slice view of the flagellum of an anucleated Trypanosoma brucei cell, recontructed with tiled direct Fourier transform. Cyan box shows the tile to zoom in for comparison. (b) Slice view of tomogram reconstructed by direct Fourier transform (FT), tiled direct Fourier transform, back projection (BP) and SIRT, from left to right. The tomograms are filtered identically to be comparable.

Supplementary Figure 6 Comparison of structures solved by different software packages using the ribosome dataset from EMPIAR-10064.

Averaged structures solved by PEET (grey, 13Å), EMAN2 (cyan, 8.5Å) and PyTom (yellow, 11.2Å) are viewed from three orientations. A high resolution structrue (blue, EMD-5592) filtered to 10Å is shown for comparison.

Supplementary Figure 7 Comparison of structures solved by different software packages using the ribosome dataset from EMPIAR-10045.

Averaged structures solved by EMClarity (grey, 7.8Å), EMAN2 (cyan, 9.3Å) and Relion (yellow, 13Å) are viewed from three orientations. A high resolution structrue (blue, EMD-2858) filtered to 10Å is shown for comparison.

Supplementary information

Supplementary Information

Supplementary Figs. 1–7.

Reporting Summary

Supplementary Tables

Supplementary Tables 1 and 2

Supplementary Video 1

Tomogram of an E. coli bacterium with gold fiducials. Result of automatic tilt series alignment and tomogram reconstruction.

Supplementary Video 2

Tomogram of purified apoferritin without fiducials. Result of automatic fiducial-less tilt series alignment. The dataset is from EMPIAR-10171.

Supplementary Video 3

Subtomogram averaging of purified ribosomes. Result of subtomogram averaging with subtilt alignment using the dataset from EMPIAR-10064.

Supplementary Video 4

Subtomogram averaging of AcrAB-TolC drug pumps from cellular tomograms. Result of subtomogram averaging with subtilt alignment using particles from cellular tomograms of E. coli overexpressing AcrAB-TolC drug pumps.

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Chen, M., Bell, J.M., Shi, X. et al. A complete data processing workflow for cryo-ET and subtomogram averaging. Nat Methods 16, 1161–1168 (2019). https://doi.org/10.1038/s41592-019-0591-8

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