Zebrafish embryos and larvae have become popular vertebrate models because their body walls are transparent, which enables live imaging of target organs using fluorescent protein transgenes or dye staining. Software packages for the quantification of these fluorescent signals are available from both commercial and noncommercial sources; however, their algorithms are complicated and their resources (code) have mostly not been openly shared. In this study, we developed a simple and robust open-source software tool named "ZF-Mapper" for the quantification of the fluorescence intensity of each pixel in zebrafish images with batch image file processing capability. Using this software, we can evaluate the three-dimensional (3D) distribution of fluorescence intensity among zebrafish cells by analyzing each image pixel. We tested ZF-Mapper for the analysis of zebrafish with macrophage-specific enhanced green fluorescent protein (EGFP) and obtained results that were equivalent to those acquired using the conventional image analysis software ImageJ. We further applied ZF-Mapper to the analysis of zebrafish with cancer cell xenografts and quantified the amount of implanted melanoma cells labeled with a tdTomato red fluorescent protein in the whole body and the tail region. In addition, by combining ZF-Mapper with R freeware, we created an interactive 3D scatter plot of the fluorescence intensities of macrophage-EGFPs in zebrafish. In summary, we developed the Python-based freeware ZF-Mapper for the quantification of fluorescent signals in multiple zebrafish images, which enables fluorescence-based zebrafish screening. We provide the source code and the executable application software for Windows (.exe) and macOS (.app).
Keywords: screening; Python; batch analysis; fluorophores; high throughput.