Automated prior knowledge-based quantification of neuronal patterns in the spinal cord of zebrafish.

Abstract

To reliably assess the effects of unknown chemicals on the development of fluorescently labeled sensory-, moto- and interneuron populations in the spinal cord of zebrafish, automated data analysis is essential. For the evaluation of a high-throughput screen of a large chemical library, we developed a new method for the automated extraction of quantitative information from green fluorescent protein (eGFP) and red fluorescent protein (RFP) labeled spinal cord neurons in double-transgenic zebrafish embryos. The methodology comprises region of interest detection, intensity profiling with reference comparison and neuron distribution histograms. All methods were validated on a manually evaluated pilot study using a Notch inhibitor dose-response experiment. The automated evaluation showed superior performance to manual investigation regarding time consumption, information detail and reproducibility. Being part of GNU General Public Licence (GNU-GPL) licensed open-source MATLAB toolbox Gait-CAD, an implementation of the presented methods is publicly available for download at http://sourceforge.net/projects/zebrafishimage/.