Computational 3D histological phenotyping of whole zebrafish by X-ray histotomography

  1. Yifu Ding
  2. Daniel J Vanselow
  3. Maksim A Yakovlev
  4. Spencer R Katz
  5. Alex Y Lin
  6. Darin P Clark
  7. Phillip Vargas
  8. Xuying Xin
  9. Jean E Copper
  10. Victor A Canfield
  11. Khai C Ang
  12. Yuxin Wang
  13. Xianghui Xiao
  14. Francesco De Carlo
  15. Damian B van Rossum
  16. Patrick La Riviere
  17. Keith Cheng  Is a corresponding author
  1. Penn State College of Medicine, United States
  2. Duke University, United States
  3. The University of Chicago, United States
  4. Motorola Mobility, United States
  5. Argonne National Laboratory, United States

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.

Data availability

ViewTool is publically 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 resolution scans, including raw projection data, are available from researchers upon request as a download or by transfer to physical media.

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Yifu Ding

    The Jake Gittlen Laboratories for Cancer Research, Penn State College of Medicine, Hershey, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4629-5858
  2. Daniel J Vanselow

    The Jake Gittlen Laboratories for Cancer Research, Penn State College of Medicine, Hershey, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9221-8634
  3. Maksim A Yakovlev

    The Jake Gittlen Laboratories for Cancer Research, Penn State College of Medicine, Hershey, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Spencer R Katz

    The Jake Gittlen Laboratories for Cancer Research, Penn State College of Medicine, Hershey, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5586-3562
  5. Alex Y Lin

    The Jake Gittlen Laboratories for Cancer Research, Penn State College of Medicine, Hershey, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Darin P Clark

    Center for In Vivo Microscopy, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Phillip Vargas

    Department of Radiology, The University of Chicago, Chicago, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Xuying Xin

    The Jake Gittlen Laboratories for Cancer Research, Penn State College of Medicine, Hershey, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Jean E Copper

    The Jake Gittlen Laboratories for Cancer Research, Penn State College of Medicine, Hershey, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Victor A Canfield

    The Jake Gittlen Laboratories for Cancer Research, Penn State College of Medicine, Hershey, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4359-1790
  11. Khai C Ang

    The Jake Gittlen Laboratories for Cancer Research, Penn State College of Medicine, Hershey, United States
    Competing interests
    The authors declare that no competing interests exist.
  12. Yuxin Wang

    Motorola Mobility, Chicago, United States
    Competing interests
    The authors declare that no competing interests exist.
  13. Xianghui Xiao

    Advanced Photon Source, Argonne National Laboratory, Lemont, United States
    Competing interests
    The authors declare that no competing interests exist.
  14. Francesco De Carlo

    Advanced Photon Source, Argonne National Laboratory, Lemont, United States
    Competing interests
    The authors declare that no competing interests exist.
  15. Damian B van Rossum

    The Jake Gittlen Laboratories for Cancer Research, Penn State College of Medicine, Hershey, United States
    Competing interests
    The authors declare that no competing interests exist.
  16. Patrick La Riviere

    Department of Radiology, The University of Chicago, Chicago, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3415-9864
  17. Keith Cheng

    The Jake Gittlen Laboratories for Cancer Research, Penn State College of Medicine, Hershey, United States
    For correspondence
    kcheng76@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5350-5825

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

  1. Richard M White, Memorial Sloan Kettering Cancer Center, United States

Publication history

  1. Received: January 5, 2019
  2. Accepted: May 4, 2019
  3. Accepted Manuscript published: May 7, 2019 (version 1)
  4. 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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  1. Yifu Ding
  2. Daniel J Vanselow
  3. Maksim A Yakovlev
  4. Spencer R Katz
  5. Alex Y Lin
  6. Darin P Clark
  7. Phillip Vargas
  8. Xuying Xin
  9. Jean E Copper
  10. Victor A Canfield
  11. Khai C Ang
  12. Yuxin Wang
  13. Xianghui Xiao
  14. Francesco De Carlo
  15. Damian B van Rossum
  16. Patrick La Riviere
  17. Keith Cheng
(2019)
Computational 3D histological phenotyping of whole zebrafish by X-ray histotomography
eLife 8:e44898.
https://doi.org/10.7554/eLife.44898

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