ZFIN ID: ZDB-PUB-130717-1
Methods for Automated High-Throughput Toxicity Testing Using Zebrafish Embryos
Alshut, R., Legradi, J., Liebel, U., Yang, L., van Wezel, J., Strähle, U., Mikut, R., and Reischl, M.
Date: 2010
Source: KI 2010: Advances in Artificial Intelligence   6359: 219-226 (Chapter)
Registered Authors: Legradi, Jessica, Liebel, Urban, Mikut, Ralf, Strähle, Uwe, Yang, Lixin
Keywords: none
MeSH Terms: none
PubMed: none Full text @ KI 2010: Advances in Artificial Intelligence
ABSTRACT

In this paper, an automated process to extract experiment-specific parameters out of microscope images of zebrafish embryos is presented and applied to experiments consisting of toxicological treated zebrafish embryos. The treatments consist of a dilution series of several compounds.

A custom built graphical user interface allows an easy labeling and browsing of the image data. Subsequently image-specific features are extracted for each image based on image processing algorithms. By means of feature selection, the most significant features are determined and a classification divides the images in two classes. Out of the classification results dose-response curves as well as frequently used general indicators of substance’s acute toxicity can be automatically calculated. Exemplary the median lethal dose is determined. The presented approach was designed for real high-throughput screening including data handling and the results are stored in a long-time data storage and prepared to be processed on a cluster computing system being build up in the KIT. It provides the possibility to test any amount of chemical substances in high-throughput and is, in combination with new screening microscopes, able to manage ten thousands of risk tests required e.g. in the REACH framework or for drug discovery.

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