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An open-access volume electron microscopy atlas of whole cells and tissues

A Publisher Correction to this article was published on 03 November 2021

This article has been updated

Abstract

Understanding cellular architecture is essential for understanding biology. Electron microscopy (EM) uniquely visualizes cellular structures with nanometre resolution. However, traditional methods, such as thin-section EM or EM tomography, have limitations in that they visualize only a single slice or a relatively small volume of the cell, respectively. Focused ion beam-scanning electron microscopy (FIB-SEM) has demonstrated the ability to image small volumes of cellular samples with 4-nm isotropic voxels1. Owing to advances in the precision and stability of FIB milling, together with enhanced signal detection and faster SEM scanning, we have increased the volume that can be imaged with 4-nm voxels by two orders of magnitude. Here we present a volume EM atlas at such resolution comprising ten three-dimensional datasets for whole cells and tissues, including cancer cells, immune cells, mouse pancreatic islets and Drosophila neural tissues. These open access data (via OpenOrganelle2) represent the foundation of a field of high-resolution whole-cell volume EM and subsequent analyses, and we invite researchers to explore this atlas and pose questions.

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Fig. 1: Enhanced FIB-SEM configuration, operation, and resolution.
Fig. 2: Interphase HeLa cell.
Fig. 3: Mouse CTL engaging an ovarian cancer cell.
Fig. 4: Tissue sample datasets.

Data availability

All FIB-SEM datasets in this work have been deposited to OpenOrganelle repository (https://openorganelle.janelia.org) and made publicly available with DOIs: wild-type interphase HeLa cell 2017-06-21 (https://doi.org/10.25378/janelia.13114211), wild-type interphase HeLa cell 2017-08-09 (https://doi.org/10.25378/janelia.13114244), wild-type mitotic HeLa cell 2019-05-30 (https://doi.org/10.25378/janelia.13114472), wild-type THP-1 macrophage 2018-11-11 (https://doi.org/10.25378/janelia.13114343), wild-type immortalized T-cells (Jurkat) 2018-08-10  (https://doi.org/10.25378/janelia.13114259), wild-type immortalized breast cancer cell 2017-11-21 (https://doi.org/10.25378/janelia.13114352), killer T-cell attacking cancer cell 2020-02-04 (https://doi.org/10.25378/janelia.13114454), isolated murine pancreatic islets 2019-03-01 (https://doi.org/10.25378/janelia.13114499), Drosophila fan-shaped body from a 5-day-old male 2019-09-14 (https://doi.org/10.25378/janelia.13114529), Drosophila accessory calyx from a 5-day old male 2019-12-06 (https://doi.org/10.25378/janelia.13114514). Source data are provided with this paper.

Code availability

FIB-SEM image acquisition LabVIEW code used in this work is available from. https://github.com/cshanxu/Enhanced_FIB-SEM. Python code for resolution characterizations using ribosomes is available from. https://github.com/gleb-shtengel/FIB-SEM_resolution_evaluation.

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Acknowledgements

We thank K.J. Hayworth and W. Qiu at Howard Hughes Medical Institute (HHMI) Janelia Research Campus (JRC) for invaluable discussions and data collection support; P.K. Rivlin, S.M. Plaza and I.A. Meinertzhagen for the JRC EM shared resource; the FlyEM project team support for staining protocols development; the electron microscopy facility of MPI-CBG and of the CMCB Technology Platform at TU Dresden for their services; Y. Wu from the laboratory of P. De Camilli at Yale for advice. C.S.X., S.P., G.S., S.T., Z.L., H.A.P., N.I., D.B., A.V.W., M.F., T.C.W., J.L.-S. and H.F.H. are funded by Howard Hughes Medical Institute (HHMI). A.M. received support from the Carl Gustav Carus Faculty of Medicine at TU Dresden via a MeDDrive GRANT. A.M. and M.S. were supported with funds from the German Center for Diabetes Research (DZD e.V.) by the German Ministry for Education and Research (BMBF), from the German-Israeli Foundation for Scientific Research and Development (GIF) (grant I-1429-201.2/2017) and from the German Research Foundation (DFG) jointly with the Agence nationale de la recherche (ANR) (grant SO 818/6-1) to M.S. A.T.R. and I.M. are funded by Genentech/Roche. H.K.H and S.B.v.E. are funded by NIAID grant R01AI138625. R.V.F. is supported by NIH R01GM124348. T.C.W. is supported by NIH R01GM097194. J.C. is a fellow of the Damon Runyon Cancer Research Foundation.

Author information

Affiliations

Authors

Contributions

C.S.X. and H.F.H. supervised the project; C.S.X., S.P., G.S. and H.F.H. wrote the manuscript with input from all co-authors; C.S.X. developed the enhanced FIB-SEM platform for large-volume high-resolution imaging and optimized imaging conditions; C.S.X., S.P. and G.S. conducted FIB-SEM experiments; C.S.X. and S.P. performed image post-processing; S.P., G.S., A.M., A.T.R., H.K.H., S.B.v.E., Z.L., H.A.P., N.I., J.C., A.V.W. and M.F. prepared samples; G.S., A.M., A.T.R. and S.T. analysed data; D.B. prepared and uploaded data to the OpenOrganelle website; S.B.v.E., T.C.W., R.V.F., J.L.-S., I.M. and M.S. proposed biological questions and provided samples.

Corresponding authors

Correspondence to C. Shan Xu or Harald F. Hess.

Ethics declarations

Competing interests

Portions of the technology described here are covered by U.S. Patent 10,600,615 titled ‘Enhanced FIB-SEM systems for large-volume 3D imaging’, which was issued to C.S.X., K.J.H. and H.F.H. and assigned to Howard Hughes Medical Institute on 24 March 2020. The other authors declare no competing interests.

Additional information

Peer review information Nature thanks Robert Murphy, Jason Swedlow and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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

Extended data figures and tables

Extended Data Fig. 1 Isotropic voxel (representing the minimal voxel size dictated by the worst-case axial resolution) vs. volume for comparing different volume EM methods.

The light green space represents the Resolution-Volume regime accessible with enhanced FIB-SEM technology through long term imaging. The present work of whole cell volumes colored in yellow matches the resolutions at 4-nm isotropic voxels shown in Fig. 1b, compared to the prior work of smaller volumes colored in red. Adopted from ref. 1 with modifications.

Extended Data Fig. 2 Murine CTL engaging an ovarian cancer cell.

Zooms on regions showing different immunological synapse topology features. a, Interdigitation. b, Flat apposition. c, Filopodia caught between cells. Scale bars, 0.5 μm.

Extended Data Fig. 3 Edge transition distributions determined from ribosomes in cultured cells datasets.

a, Distributions of 37%–63% transition distances in X-, Y- (left), Ztop-(center), and Zbot- (right) directions. b, Distributions of 20%–80% transition distances in X-, Y- (left), Ztop-(center), and Zbot- (right) directions.

Source data

Extended Data Fig. 4 Cross-sections of the example of ribosomes from the dataset Interphase HeLa Cell 2017-06-21 and the profiles with the transition analysis.

The top three rows are the brightest ribosomes and the bottom three rows are the dimmest ribosomes.

Source data

Extended Data Fig. 5 Cross-sections of the example of ribosomes from the dataset Interphase HeLa Cell 2017-08-09 and the profiles with the transition analysis.

The top three rows are the brightest ribosomes and the bottom three rows are the dimmest ribosomes.

Source data

Extended Data Fig. 6 Cross-sections of the example of ribosomes from the dataset Wild-type THP-1 Macrophage 2018-11-11 and the profiles with the transition analysis.

The top three rows are the brightest ribosomes and the bottom three rows are the dimmest ribosomes.

Source data

Extended Data Fig. 7 Cross-sections of the example of ribosomes from the dataset Immortalized T-cells (Jurkat) 2018-08-10 and the profiles with the transition analysis.

The top three rows are the brightest ribosomes and the bottom three rows are the dimmest ribosomes.

Source data

Extended Data Fig. 8 Cross-sections of the example of ribosomes from the dataset Immortalized breast cancer cell (SUM159) 2017-11-21 and the profiles with the transition analysis.

The top three rows are the brightest ribosomes and the bottom three rows are the dimmest ribosomes.

Source data

Extended Data Fig. 9 Cross-sections of the example of ribosomes from the dataset Killer T-cell attacking cancer cell 2020-02-04 on Cancer Cell and the profiles with the transition analysis.

The top three rows are the brightest ribosomes and the bottom three rows are the dimmest ribosomes.

Source data

Extended Data Table 1 Descriptions of exemplary datasets with imaging conditions and estimated z-scaling factors

Supplementary information

Supplementary Information

This file contains Supplementary Methods, legends for Supplementary Videos 1 and 2, and Supplementary References.

Reporting Summary

Peer Review File

Supplementary Video 1

A new paradigm of high-resolution whole-cell imaging enabled by enhanced FIB-SEM.

Supplementary Video 2

T cell attacking cancer cell revealed by FIB-SEM with 4-nm voxels.

Source data

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Xu, C.S., Pang, S., Shtengel, G. et al. An open-access volume electron microscopy atlas of whole cells and tissues. Nature 599, 147–151 (2021). https://doi.org/10.1038/s41586-021-03992-4

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