Expansion microscopy of zebrafish for neuroscience and developmental biology studies
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E10799.full.pdf
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Checksum (MD5)
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Author(s)
Odstrcil, Iris
Förster, Dominique
Ramirez, Alyson
Gagnon, James A.
Randlett, Owen
Schoppik, David
Engert, Florian
Baier, Herwig
Freifeld, Limor
Costa, Emma K.
Date Issued
December 2017
Journal
Proceedings of the National Academy of Sciences
Publisher
National Academy of Sciences (U.S.)
Citation
Freifeld, Limor et al. “Expansion Microscopy of Zebrafish for Neuroscience and Developmental Biology Studies.” Proceedings of the National Academy of Sciences 114, 50 (November 2017): E10799–E10808 © 2017 the Author(s)
Version
Final published version
Abstract
Expansion microscopy (ExM) allows scalable imaging of preserved 3D biological specimens with nanoscale resolution on fast diffraction-limited microscopes. Here, we explore the utility of ExM in the larval and embryonic zebrafish, an important model organism for the study of neuroscience and development. Regarding neuroscience, we found that ExM enabled the tracing of fine processes of radial glia, which are not resolvable with diffraction-limited microscopy. ExM further resolved putative synaptic connections, as well as molecular differences between densely packed synapses. Finally, ExM could resolve subsynaptic protein organization, such as ring-like structures composed of glycine receptors. Regarding development, we used ExM to characterize the shapes of nuclear invaginations and channels, and to visualize cytoskeletal proteins nearby. We detected nuclear invagination channels at late prophase and telophase, potentially suggesting roles for such channels in cell division. Thus, ExM of the larval and embryonic zebrafish may enable systematic studies of how molecular components are configured in multiple contexts of interest to neuroscience and developmental biology.
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Media Laboratory
McGovern Institute for Brain Research at MIT
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1073/PNAS.1706281114
