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

Yifu Ding, Daniel J. Vanselow, Maksim A. Yakovlev, Spencer R. Katz, Alex Y. Lin, Darin P. Clark, Phillip Vargas, Xuying Xin, Jean E. Copper, Victor A. Canfield, Khai C. Ang, Yuxin Wang, Xianghui Xiao, Francesco De Carlo, Damian B.Van Rossum, Patrick La Riviere, Keith C. Cheng

Research output: Contribution to journalArticle

2 Citations (Scopus)

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. 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.

Original languageEnglish (US)
Article numbere44898
JournaleLife
Volume8
DOIs
StatePublished - May 2019

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Zebrafish
X-Rays
Tissue
X rays
Brain
Histology
X Ray Tomography
Phenotype
Synchrotrons
Cell Shape
Atlases
Motor Neurons
Cell Size
Neurons
Tomography
Vertebrates
Blood
Color
Erythrocytes
Cells

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)
  • Immunology and Microbiology(all)
  • Biochemistry, Genetics and Molecular Biology(all)

Cite this

Ding, Y., Vanselow, D. J., Yakovlev, M. A., Katz, S. R., Lin, A. Y., Clark, D. P., ... Cheng, K. C. (2019). Computational 3d histological phenotyping of whole zebrafish by x-ray histotomography. eLife, 8, [e44898]. https://doi.org/10.7554/eLife.44898
Ding, Yifu ; Vanselow, Daniel J. ; Yakovlev, Maksim A. ; Katz, Spencer R. ; Lin, Alex Y. ; Clark, Darin P. ; Vargas, Phillip ; Xin, Xuying ; Copper, Jean E. ; Canfield, Victor A. ; Ang, Khai C. ; Wang, Yuxin ; Xiao, Xianghui ; Carlo, Francesco De ; Rossum, Damian B.Van ; Riviere, Patrick La ; Cheng, Keith C. / Computational 3d histological phenotyping of whole zebrafish by x-ray histotomography. In: eLife. 2019 ; Vol. 8.
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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. 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.",
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Ding, Y, Vanselow, DJ, Yakovlev, MA, Katz, SR, Lin, AY, Clark, DP, Vargas, P, Xin, X, Copper, JE, Canfield, VA, Ang, KC, Wang, Y, Xiao, X, Carlo, FD, Rossum, DBV, Riviere, PL & Cheng, KC 2019, 'Computational 3d histological phenotyping of whole zebrafish by x-ray histotomography', eLife, vol. 8, e44898. https://doi.org/10.7554/eLife.44898

Computational 3d histological phenotyping of whole zebrafish by x-ray histotomography. / Ding, Yifu; Vanselow, Daniel J.; Yakovlev, Maksim A.; Katz, Spencer R.; Lin, Alex Y.; Clark, Darin P.; Vargas, Phillip; Xin, Xuying; Copper, Jean E.; Canfield, Victor A.; Ang, Khai C.; Wang, Yuxin; Xiao, Xianghui; Carlo, Francesco De; Rossum, Damian B.Van; Riviere, Patrick La; Cheng, Keith C.

In: eLife, Vol. 8, e44898, 05.2019.

Research output: Contribution to journalArticle

TY - JOUR

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AU - Ding, Yifu

AU - Vanselow, Daniel J.

AU - Yakovlev, Maksim A.

AU - Katz, Spencer R.

AU - Lin, Alex Y.

AU - Clark, Darin P.

AU - Vargas, Phillip

AU - Xin, Xuying

AU - Copper, Jean E.

AU - Canfield, Victor A.

AU - Ang, Khai C.

AU - Wang, Yuxin

AU - Xiao, Xianghui

AU - Carlo, Francesco De

AU - Rossum, Damian B.Van

AU - Riviere, Patrick La

AU - Cheng, Keith C.

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Ding Y, Vanselow DJ, Yakovlev MA, Katz SR, Lin AY, Clark DP et al. Computational 3d histological phenotyping of whole zebrafish by x-ray histotomography. eLife. 2019 May;8. e44898. https://doi.org/10.7554/eLife.44898