Automated Image-Based Phenotypic Analysis in Zebrafish Embryos

作者：Vogt Andreas; Cholewinski Andrzej; Shen Xiaoqiang; Nelson Scott G; Lazo John S; Tsang Michael; Hukriede Neil A^*

来源：Developmental Dynamics, 2009, 238(3): 656-663.

DOI：10.1002/dvdy.21892

• cognition network technology
• high-content screening
• angiogenesis
• pironetin
• zebrafish

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.

• 出版日期2009-3