Automated image-based phenotypic analysis in zebrafish embryos
Version of Record online: 22 FEB 2009
Copyright © 2009 Wiley-Liss, Inc.
Volume 238, Issue 3, pages 656–663, March 2009
How to Cite
Vogt, A., Cholewinski, A., Shen, X., Nelson, S. G., Lazo, J. S., Tsang, M. and Hukriede, N. A. (2009), Automated image-based phenotypic analysis in zebrafish embryos. Dev. Dyn., 238: 656–663. doi: 10.1002/dvdy.21892
- Issue online: 22 FEB 2009
- Version of Record online: 22 FEB 2009
- Manuscript Accepted: 10 JAN 2009
- NIH. Grant Numbers: R01DH053287, R01DK069403, P30DK079307, R01HL088016, CA78039, U54MH07441
- Fiske Drug Discovery Fund
- cognition network technology;
- high-content screening;
Presently, the zebrafish is the only vertebrate model compatible with contemporary paradigms of drug discovery. Zebrafish embryos are amenable to automation necessary for high-throughput chemical screens, and optical transparency makes them potentially suited for image-based screening. However, the lack of tools for automated analysis of complex images presents an obstacle to using the zebrafish as a high-throughput screening model. We have developed an automated system for imaging and analyzing zebrafish embryos in multi-well plates regardless of embryo orientation and without user intervention. Images of fluorescent embryos were acquired on a high-content reader and analyzed using an artificial intelligence-based image analysis method termed Cognition Network Technology (CNT). CNT reliably detected transgenic fluorescent embryos (Tg(fli1:EGFP)y1) arrayed in 96-well plates and quantified intersegmental blood vessel development in embryos treated with small molecule inhibitors of anigiogenesis. The results demonstrate it is feasible to adapt image-based high-content screening methodology to measure complex whole organism phenotypes. Developmental Dynamics 238:656–663, 2009. © 2009 Wiley-Liss, Inc.