Computational 3D histological phenotyping of whole zebrafish by X-ray histotomography
- Penn State College of Medicine, United States
- Duke University, United States
- The University of Chicago, United States
- Motorola Mobility, United States
- Argonne National Laboratory, United States
- Cited 2
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Abstract
Organismal phenotypes frequently involve multiple organ systems. Histology is a powerful way to detect cellular and tissue phenotypes, but is largely descriptive and subjective. To determine how synchrotron-based X-ray micro-tomography (micro-CT) can yield 3-dimensional whole-organism images suitable for quantitative histological phenotyping, we scanned whole zebrafish, a small vertebrate model with diverse tissues, at ~1-micron voxel resolutions. Using micro-CT optimized for cellular characterization (histotomography), brain nuclei were computationally segmented and assigned to brain regions. Shape and volume were computed for populations of nuclei such as those of motor neurons and red blood cells. Striking individual phenotypic variation was apparent from color maps of computed cell density. Unlike histology, histotomography allows the detection of phenotypes that require millimeter scale context in multiple planes. We expect the computational and visual insights into 3D tissue architecture provided by histotomography to be useful for reference atlases, hypothesis generation, comprehensive organismal screens, and diagnostics.
Article and author information
Author details
Patrick La Riviere
Funding
NIH Office of the Director (R24-OD018559)
- Patrick La Riviere
- Keith Cheng
National Institutes of Health (R24-RR017441)
- Patrick La Riviere
- Keith Cheng
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: All procedures on live animals were approved by the Institutional Animal Care and Use Committee (IACUC) at the Pennsylvania State University, ID: PRAMS201445659, Groundwork for a Synchrotron MicroCT Imaging Resource for Biology (SMIRB).
Reviewing Editor
- Richard M White, Memorial Sloan Kettering Cancer Center, United States
Publication history
- Received: January 5, 2019
- Accepted: May 4, 2019
- Accepted Manuscript published: May 7, 2019 (version 1)
- Version of Record published: June 11, 2019 (version 2)
Copyright
© 2019, Ding et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Further reading
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- Developmental Biology
- Neuroscience
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- Developmental Biology
