Serial Block Face‐Scanning Electron Microscopy as a Burgeoning Technology

Author:

Marshall Andrea G.1,Neikirk Kit1,Stephens Dominique C.1,Vang Larry1,Vue Zer1,Beasley Heather K.1,Crabtree Amber1,Scudese Estevão23,Lopez Edgar Garza4,Shao Bryanna1,Krystofiak Evan5,Rutledge Sharifa6,Davis Jaimaine7,Murray Sandra A.8,Damo Steven M.910,Katti Prasanna11,Hinton Antentor1ORCID

Affiliation:

1. Department of Molecular Physiology and Biophysics Vanderbilt University Nashville TN 37232 USA

2. Laboratory of Biosciences of Human Motricity (LABIMH) of the Federal University of State of Rio de Janeiro (UNIRIO) Rio de Janeiro Brazil

3. Sport Sciences and Exercise Laboratory (LaCEE) Catholic University of Petrópolis (UCP) Catholic 25685‐100 Brazil

4. Department of Internal Medicine University of Iowa Iowa City IA 52242 USA

5. Department of Cell and Developmental Biology Vanderbilt University Nashville TN 37232 USA

6. Department of Chemistry University of Alabama in Huntsville Huntsville AL 35899 USA

7. Department of Biochemistry, Cancer Biology, Neuroscience, Pharmacology Meharry Medical College Nashville TN 37232 USA

8. Department of Cell Biology University of Pittsburgh Pittsburgh PA 15261 USA

9. Department of Life and Physical Sciences Fisk University Nashville TN 37208 USA

10. Center for Structural Biology Vanderbilt University Nashville TN 37232 USA

11. National Heart, Lung and Blood Institute National Institutes of Health 9000 Rockville Pike Bethesda MD 20892 USA

Abstract

AbstractSerial block face scanning electron microscopy (SBF‐SEM), also referred to as serial block‐face electron microscopy, is an advanced ultrastructural imaging technique that enables three‐dimensional visualization that provides largerx‐ and y‐axis ranges than other volumetric EM techniques. While SEM is first introduced in the 1930s, SBF‐SEM is developed as a novel method to resolve the 3D architecture of neuronal networks across large volumes with nanometer resolution by Denk and Horstmann in 2004. Here, the authors provide an accessible overview of the advantages and challenges associated with SBF‐SEM. Beyond this, the applications of SBF‐SEM in biochemical domains as well as potential future clinical applications are briefly reviewed. Finally, the alternative forms of artificial intelligence‐based segmentation which may contribute to devising a feasible workflow involving SBF‐SEM, are also considered.

Funder

National Institutes of Health

Chan Zuckerberg Initiative

Silicon Valley Community Foundation

National Science Foundation

Burroughs Wellcome Fund

Publisher

Wiley

Subject

General Biochemistry, Genetics and Molecular Biology,Biomedical Engineering,Biomaterials

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