Biological Sciences Division
Published May 7, 2019 | Version v1
Journal article Open

Computational 3d histological phenotyping of whole zebrafish by x-ray histotomography

Creators

  • 1. Pennsylvania State University
  • 2. Duke University
  • 3. University of Chicago
  • 4. Omnivision Technologies, Inc.
  • 5. Brookhaven National Laboratory
  • 6. Argonne National Laboratory

Description

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. Micro-CT optimized for cellular characterization (histotomography) allows brain nuclei to be computationally segmented and assigned to brain regions, and cell shapes and volumes to be computed for motor neurons and red blood cells. Striking individual phenotypic variation was apparent from color maps of computed densities of brain nuclei. Unlike histology, the histotomography also allows the study of 3-dimensional structures of millimeter scale that cross multiple tissue planes. We expect the computational and visual insights into 3D cell and tissue architecture provided by histotomography to be useful for reference atlases, hypothesis generation, comprehensive organismal screens, and diagnostics.

Data availability

ViewTool is publicly available (http://3D.fish). Digital histology is publicly available from our Zebrafish Lifespan Atlas (http://bio-atlas.psu.edu) (Cheng, 2004). Registered and unregistered 8-bit reconstructions of the heads of five zebrafish larvae involved in analysis are available on Dryad (https://datadryad.org/) along with scripts written for cell nuclei detection, analysis, and sample registration. Full bit-depth scans, including raw projection data, are available from researchers upon request as a download or transfer to physical media. Due to the large size of these files, use of a traditional repository at the time of publication was impractical.

The following data sets were generated:

Ding Y Vanselow D Yakovlev M Katz S Lin A Clark D Vargas P Xin X Copper J Canfield V Ang K Wang Y Xiao X Carlo FD Rossum Dv Riviere PL Cheng K (2019) Dryad Digital Repository Data from: Computational 3D histological phenotyping of whole zebrafish by X-ray histotomography. https://doi.org/10.5061/dryad.4nb12g2

The following previously published data sets were used:

Ronneberger O Liu K Rath M Rueß D Mueller T Skibbe H Drayer B Schmidt T Filippi A Nitschke R Brox T Burkhardt H Driever W (2012) ViBE-Z ViBE-Z: A Framework for 3D Virtual Colocalization Analysis in Zebrafish Larval Brains. http://vibez.informatik.uni-freiburg.de/ViBE-Z_96hpf_v1.h5

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Additional details

Identifiers

DOI
10.7554/eLife.44898
Other
oai:uchicago.tind.io:9939

Funding

National Institutes of Health
Office of the Director
National Institutes of Health
R24-RR017441
Huck Institutes of the Life Sciences
Pilot award funding
Institute for Cyber Science, PSU
Pilot award funding
Jake Gittlen Memorial Golf Tournament
Pilot award funding
Pennsylvania Tobacco Fund
Penn State Zebrafish Functional Genomics Core
Huck Institutes of the Life Sciences
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UChicago Information

Division(s)
Biological Sciences Division
Department(s)
Radiology