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Volume electron microscopy

An Author Correction to this article was published on 07 September 2022

This article has been updated

Abstract

Life exists in three dimensions, but until the turn of the century most electron microscopy methods provided only 2D image data. Recently, electron microscopy techniques capable of delving deep into the structure of cells and tissues have emerged, collectively called volume electron microscopy (vEM). Developments in vEM have been dubbed a quiet revolution as the field evolved from established transmission and scanning electron microscopy techniques, so early publications largely focused on the bioscience applications rather than the underlying technological breakthroughs. However, with an explosion in the uptake of vEM across the biosciences and fast-paced advances in volume, resolution, throughput and ease of use, it is timely to introduce the field to new audiences. In this Primer, we introduce the different vEM imaging modalities, the specialized sample processing and image analysis pipelines that accompany each modality and the types of information revealed in the data. We showcase key applications in the biosciences where vEM has helped make breakthrough discoveries and consider limitations and future directions. We aim to show new users how vEM can support discovery science in their own research fields and inspire broader uptake of the technology, finally allowing its full adoption into mainstream biological imaging.

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Fig. 1: A typical vEM workflow.
Fig. 2: vEM encompasses a collection of closely related imaging modalities.
Fig. 3: vEM as a multiscale multimodal imaging technique.
Fig. 4: Correlative and comparative vEM for function–structure studies.
Fig. 5: A typical vEM image analysis pipeline.
Fig. 6: Examples of multiscale vEM on organelles and cells.
Fig. 7: Examples of multiscale vEM on model organisms and connectomes.
Fig. 8: Examples of multiscale vEM in tissues and the clinical setting.

Code availability

The two example data analysis workflows for neuron and mitochondria segmentation can be found at: https://github.com/kreshuklab/vem-primer-examples.

Change history

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Acknowledgements

The authors thank E. Duke (European Molecular Biology Laboratory (EMBL) Hamburg) for comments on the manuscript. The work of C.J.P. and L.M.C. was supported by the Francis Crick Institute, which receives its core funding from Cancer Research UK (FC001999), the UK Medical Research Council (FC001999) and the Wellcome Trust (FC001999). R.G.P is supported by the National Health and Medical Research Council of Australia (grant APP1150083 and fellowship APP1156489) and by the Australian Research Council (DP200102559). K.D.M. is supported by the National Institutes of Health (NIH) (grant NS094499). A.W. was supported by the Howard Hughes Medical Institute, Janelia Research Campus. K.N. is funded in whole or in part with Federal funds from the National Cancer Institute, NIH, under Contract No. 75N91019D00024. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products or organizations imply endorsement by the US government. K.M. collaborates for a joint PhD degree between EMBL and Heidelberg University, Faculty of Biosciences, Heidelberg, Germany.

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Authors and Affiliations

Authors

Contributions

Introduction (L.M.C. and P.V.); Experimentation (L.M.C., C.J.P., C.G., K.M., K.D.M., R.G.P., N.L.S., Y.S., B.T. and P.V.); Results (L.M.C., C.G., K.M., K.D.M., C.P., B.T. and A.W.); Applications (L.M.C., C.J.P., C.G., K.D.M., R.G.P., N.L.S., Y.S., P.V. and A.W.); Reproducibility and data deposition (L.M.C., A.K., K.N. and Y.S.); Limitations and optimizations (L.M.C., K.N. and Y.S.); Outlook (L.M.C.); overview of the Primer (L.M.C.).

Corresponding author

Correspondence to Lucy M. Collinson.

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Competing interests

K.D.M. has founder’s equity interests in Aratome, LLC (Menlo Park, CA, USA), an enterprise that produces array tomography materials and services. All other authors declare no competing interests.

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Nature Reviews Methods Primers thanks Jacob Hoogenboom, Saskia Lippens and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Related links

3D Slicer: www.slicer.org

APEER: https://www.apeer.com/home/

ariadne: https://ariadne.ai/

BigDataProcessor: https://github.com/bigdataprocessor/bigdataprocessor2

BigWarp: https://imagej.net/plugins/bigwarp

Bio-Formats: https://www.openmicroscopy.org/bio-formats/

Bioimage Model Zoo: https://bioimage.io/#/

CDeep3M: https://github.com/CRBS/cdeep3m

CLEMSite: https://git.embl.de/lleti/clemsite

Dask: https://dask.org/

DeepImageJ: https://deepimagej.github.io/deepimagej/

DeepMIB: https://github.com/Ajaxels/MIB2

ec-CLEM: https://icy.bioimageanalysis.org/plugin/ec-clem/

elastix: https://elastix.lumc.nl/

Example data analysis workflows: https://github.com/kreshuklab/vem-primer-examples

Fiji Weka plugin: https://imagej.net/plugins/tws/

ilastik: https://www.ilastik.org/

Microscopy Image Browser: http://mib.helsinki.fi/

MitoEM data challenge: https://mitoem.grand-challenge.org/

MorphoLibJ: https://imagej.net/plugins/morpholibj

piTEAM: https://github.com/AllenInstitute/piTEAM

Reconstruct: https://synapseweb.clm.utexas.edu/software-0

SBEMimage: https://github.com/SBEMimage

scalable minds: https://scalableminds.com/

SegEM: http://segem.brain.mpg.de/

SerialEM: https://bio3d.colorado.edu/SerialEM/

The Lichtman lab at Harvard University: https://lichtmanlab.fas.harvard.edu/

TrakEM2: https://imagej.net/plugins/trakem2/

VAST: https://lichtman.rc.fas.harvard.edu/vast/

vEM community website: https://www.volumeem.org/

WaferMapper: https://lichtman.rc.fas.harvard.edu/LGN/WaferMapper.html

webKnossos: https://webknossos.org/

ZeroCostDL4Mic: https://github.com/HenriquesLab/ZeroCostDL4Mic

Supplementary information

Glossary

Connectomics

An interdisciplinary field combining systems neuroscience, applied physics and computer science to map the physical and functional connections of the brain in a range of species.

Vibratome

An instrument for sectioning tissue that utilizes a vibrating blade.

Membrane tubulation

The process of membrane reorganization that produces tubular membrane invaginations or outward-facing tubular membrane projections.

Ultra-thin sections

Sections thin enough to allow transmission of an electron beam (usually 100 nm or less).

Diamond knife

A specialized tool used in electron microscopy where diamond is used to produce an extremely sharp and durable knife edge capable of cutting ultra-thin sections of tissue (down to about 30 nm).

Ultramicrotome

An instrument for preparing ultra-thin sections for electron microscopy (EM).

Neural tracers

Fluorescent probes for imaging neuronal morphology.

Charging

A process that occurs in poorly conducting specimens in the scanning electron microscope as electrons are trapped and their excess negative charge causes surface potentials that distort the signal amplitude, focus and image geometry.

Isotropic voxels

3D pixels with the same size in x, y and z.

Segmentation

The process of delineating objects within an image, usually with the aim of visualizing and/or analysing different object classes. Segmentation may be performed manually or using algorithms.

Noise

Unwanted alterations of the pixel intensities in an image caused by different stages of the imaging process (electron gun, signal detection, amplification).

Fiducial

An object added to the field of view of a microscope during imaging that can be used as a point of reference during sample preparation, imaging and image analysis.

Classifier

An algorithm that categorizes an observation based on quantifiable properties.

Watershed transform

An image processing technique that can be used for image segmentation by modelling the intensity of greyscale images as topographical peaks.

Connectome

A map of the synaptic connections of the brain.

Choanocytes

Specialized cells found in sponges, contributing to feeding function via water circulation and filtration.

Tunnelling nanotubes

Extensions of the plasma membrane that form channels between cells whose proposed functions are to open communication channels between cells, for the exchange of organelles or other intracellular components.

Vitrification

Transformation of a substance into a non-crystalline, amorphous, glass-like solid. In cryo electron microscopy (cryo-EM), this involves cryopreservation of materials without hexagonal ice crystal formation, to maintain cellular components in a near-native state.

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Peddie, C.J., Genoud, C., Kreshuk, A. et al. Volume electron microscopy. Nat Rev Methods Primers 2, 51 (2022). https://doi.org/10.1038/s43586-022-00131-9

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