Gas cluster ion beam SEM for imaging of large tissue samples with 10 nm isotropic resolution

A Publisher Correction to this article was published on 04 December 2019

This article has been updated

Abstract

We demonstrate gas cluster ion beam scanning electron microscopy (SEM), in which wide-area ion milling is performed on a series of thick tissue sections. This three-dimensional electron microscopy technique acquires datasets with <10 nm isotropic resolution of each section, and these can then be stitched together to span the sectioned volume. Incorporating gas cluster ion beam SEM into existing single-beam and multibeam SEM workflows should be straightforward, increasing reliability while improving z resolution by a factor of three or more.

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Fig. 1: GCIB-SEM overview.
Fig. 2: Examples of GCIB-SEM imaging.

Data availability

The GCIB-SEM imaging data that support the findings of this study are available from the corresponding author upon reasonable request.

Code availability

GCIB-SEM flattening software and a small test dataset has been made available in the Supplementary Software and at Code Ocean (https://doi.org/10.24433/CO.4372524.v1)24.

Change history

  • 04 December 2019

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Acknowledgements

We thank S. Clerc-Rosset (EPFL) for processing the mouse brain tissue. We thank J. Kornfeld (MIT) for allowing the use of a flood-filling network that was trained on one of his SBEM datasets. We thank A. Eberle (Zeiss) for MultiSEM imaging our GCIB-SEM samples. We thank Y. Kubota (SOKENDAI) for providing the copper tape used in our ATUM collection tests. We thank W. Denk (Max Planck Institute) and M. Kormacheva (Max Planck Institute) for useful discussions. This work was funded by the Howard Hughes Medical Institute.

Author information

Affiliations

Authors

Contributions

K.J.H. performed experiments and wrote the manuscript. K.J.H., C.S.X. and H.F.H. conceived of the GCIB-SEM technique. K.J.H. and H.F.H. designed and built the prototype. K.J.H. and D.P. wrote the control software. K.J.H. wrote the analysis software. Z.L. provided fly brain tissue. G.W.K. provided mouse brain tissue. M.J. performed flood-fill network segmentations.

Corresponding author

Correspondence to Kenneth J. Hayworth.

Ethics declarations

Competing interests

A patent on the GCIB-SEM technology has been filed by HHMI. M.J. is an employee of Google AI.

Additional information

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

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

Supplementary information

Supplementary Information

Supplementary Figs. 1–26 and Notes 1–3.

Reporting Summary

Supplementary Video 1

GCIB-SEM dataset of three 1-µm-thick sections of fly brain tissue; data were acquired with 6 × 6 × 4 nm voxels using InLens-SE detection.

Supplementary Video 2

GCIB-SEM dataset of three 500-nm-thick sections of mouse cortex tissue; data were acquired with 8 × 8 × 6 nm voxels using both InLens-SE (top) and ESB (bottom) detection.

Supplementary Video 3

GCIB-SEM dataset of ten 1-µm-thick sections of mouse cortex tissue; data were acquired with 8 × 8 × 6 nm voxels using ESB detection.

Supplementary Video 4

GCIB-SEM dataset of two 10-µm-thick hot-knife sections of mouse cortex tissue; data acquired with 10 × 10 × 12 nm voxels using both ESB (left) and InLens-SE (right) detection.

Supplementary Software

Flattening software and test dataset.

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Hayworth, K.J., Peale, D., Januszewski, M. et al. Gas cluster ion beam SEM for imaging of large tissue samples with 10 nm isotropic resolution. Nat Methods 17, 68–71 (2020). https://doi.org/10.1038/s41592-019-0641-2

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