We report the development of a system for automated imaging and analysis of zebrafish transgenic embryos in multiwell plates. This demonstrates the ability to measure dose dependent effects of a small molecule, BCI, on Fibroblast Growth Factor reporter gene expression and provide technology for establishing high-throughput zebrafish chemical screens.
A major factor limiting the throughput of zebrafish chemical screens is the lack of methodology to systematically process 96-well plates for imaging and analysis. Because images of multicellular organisms are complex, low contrast, and heterogeneous in nature, existing image analysis algorithms fail to detect and quantify specific structures within the organism. Most published zebrafish chemical screens therefore involve visual examination of individual wells by dedicated personnel throughout the procedure. This usually prevents the generation of numerical readouts and a complete archiving of screen images and data. Furthermore, manual evaluation eliminates several key advantages of image-based screening, namely the ability to conduct retrospective analyses of screen performance, to examine phenotypic changes that were not the primary focus of the screening campaign (e.g., toxicity or developmental defects) and to cross-reference screening data with past or future screens using the same compound library.
In this report we highlight methodology for automated imaging and analysis of zebrafish embryos in multiwell plates without user intervention. We automated image capture on an ImageXpress Ultra laser scanning confocal reader (Molecular Devices, Sunnyvale, CA) to image Tg(dusp6:d2EGFP)pt6 embryos in 96 well plates and developed an image analysis algorithm based on Definiens’ Cognition Network Technology that quantified GFP expression in the heads of transgenic embryos. The method delivered graded responses and quantified the in vivo activity of a small molecule activator of FGF signaling. Similar results were obtained with the epifluorescence-based ArrayScan II (Cellomics Inc., Pittsburgh PA) documenting that it is possible to implement automated image capture of zebrafish embryos on a variety of commercially available plate readers 2. The development of methodology to automatically analyze multicellular organism images eliminated the need for visual scoring by a human observer and enabled the generation and archiving of numerical data and images for retrospective analysis and comparisons with future screens.
This work is funded by the NICHD/NIH (1R01HD053287) to Hukriede, NCI/NIH (P01 CA78039) to Vogt, and NHLBI/NIH (1R01HL088016) to Tsang.
Material Name | Type | Company | Catalogue Number | Comment |
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Tricaine (MS222) | Sigma | Cat.# A-5040 |