Automated image-based phenotypic analysis in zebrafish embryos.
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.
Vogt
Andreas
A
Department of Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh, Pennsylvania 15213, USA.
Cholewinski
Andrzej
A
Shen
Xiaoqiang
X
Nelson
Scott G
SG
Lazo
John S
JS
Tsang
Michael
M
Hukriede
Neil A
NA
D020533:Angiogenesis Inhibitors / Q000494:pharmacology; D000818:Animals; D004625:Embryo, Nonmammalian / Q000098:blood supply / Q000187:drug effects / Q000196:embryology* / Q000378:metabolism*; D017930:Genes, Reporter / Q000235:genetics; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D010641:Phenotype; D015027:Zebrafish / Q000196:embryology* / Q000235:genetics / Q000378:metabolism*
D020533:Angiogenesis Inhibitors