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

First Authors Stephan Daetwyler
Authors Stephan Daetwyler, Ulrik G√ľnther, Carl D. Modes, Kyle Harrington, Jan Huisken
Corresponding Authors Kyle Harrington, Jan Huisken
Last Authors Jan Huisken
Journal Name Development (Cambridge, England) (Development)
Volume 146
Issue 6
Article Number dev173757
PubMed ID 30824551
WebOfScience Link WOS:000462859300012
Open Access true
Print Publication Date 2019-03-21
Online Publication Date
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 analyse 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 using 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.
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Affiliated With Huisken, Modes, Postdoc first author, Postdocs
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Acknowledged Services Computer Department, Fish Facility
Publication Status Published
Edoc Link
Sfx Link
DOI 10.1242/dev.173757
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Visible On MPI-CBG Website true
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Created By thuem
Added Date 2019-03-08
Last Edited By thuem
Last Edited Date 2019-04-15 10:17:18.617
Library ID 7354
Document ID
Entry Complete true
eDoc Compliant true
Include in Edoc Report true
Author Affiliations Complete false