Automated image-based phenotypic analysis in zebrafish embryos

Dev Dyn. 2009 Mar;238(3):656-63. doi: 10.1002/dvdy.21892.

Abstract

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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Angiogenesis Inhibitors / pharmacology
  • Animals
  • Embryo, Nonmammalian / blood supply
  • Embryo, Nonmammalian / drug effects
  • Embryo, Nonmammalian / embryology*
  • Embryo, Nonmammalian / metabolism*
  • Genes, Reporter / genetics
  • Image Processing, Computer-Assisted / methods*
  • Phenotype
  • Zebrafish / embryology*
  • Zebrafish / genetics
  • Zebrafish / metabolism*

Substances

  • Angiogenesis Inhibitors