Fully Automated Pipetting Sorting System for Different Morphological Phenotypes of Zebrafish Embryos

Abstract

Systems biology methods, such as transcriptomics and metabolomics, require large numbers of small model organisms, such as zebrafish embryos. Manual separation of mutant embryos from wild-type embryos is a tedious and time-consuming task that is prone to errors, especially if there are variable phenotypes of a mutant. Here we describe a zebrafish embryo sorting system with two cameras and image processing based on template-matching algorithms. In order to evaluate the system, zebrafish rx3 mutants that lack eyes due to a patterning defect in brain development were separated from their wild-type siblings. These mutants show glucocorticoid deficiency due to pituitary defects and serve as a model for human secondary adrenal insufficiencies. We show that the variable phenotypes of the mutant embryos can be safely distinguished from phenotypic wild-type zebrafish embryos and sorted from one petri dish into another petri dish or into a 96-well microtiter plate. On average, classification of a zebrafish embryo takes approximately 1 s, with a sensitivity and specificity of 87% to 95%, respectively. Other morphological phenotypes may be classified and sorted using similar techniques.