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Development. 2019 Mar 1. pii: dev.173757. doi: 10.1242/dev.173757. [Epub ahead of print]

Multi-sample SPIM image acquisition, processing and analysis of vascular growth in zebrafish.

Author information

1
Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany.
2
Department of Cell Biology, UT Southwestern Medical Center, Dallas, Texas 75390, USA.
3
Center for Systems Biology Dresden, 01307 Dresden, Germany.
4
Chair of Scientific Computing for Systems Biology, Faculty of Computer Science, TU Dresden, 01069 Dresden, Germany.
5
Virtual Technology and Design, University of Idaho, Moscow, ID 83844, USA kharrington@uidaho.edu jhuisken@morgridge.org.
6
Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany kharrington@uidaho.edu jhuisken@morgridge.org.
7
Morgridge Institute for Research, Madison, WI 53715, USA.
8
Department of Integrative Biology, University of Wisconsin, Madison, WI 53706, USA.

Abstract

To quantitatively understand biological processes that occur over many hours or days, it is desirable to image multiple samples simultaneously and automatically process and analyze the resulting datasets. Here, we present a complete multi-sample preparation, imaging, processing, and analysis workflow to determine the development of the vascular volume in zebrafish. Up to five live embryos were mounted and imaged simultaneously over several days using selective plane illumination microscopy (SPIM). The resulting large imagery dataset of several terabytes was processed in an automated manner on a high-performance computer cluster and segmented with a novel segmentation approach that uses images of red blood cells as training data. This analysis yielded a precise quantification of growth characteristics of the whole vascular network, head vasculature, and tail vasculature over development. Our multi-sample platform demonstrates effective upgrades to conventional single-sample imaging platforms and paves the way for diverse quantitative long-term imaging studies.

KEYWORDS:

Growth models; Light sheet microscopy; Multi-sample imaging; SPIM; Segmentation; Vasculature; Zebrafish

PMID:
30824551
DOI:
10.1242/dev.173757
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