➔ Poster
AuthorsPooja Gupta 1,2,*, Soroush Sharbati 3, Ralf Einspanier 3, Christof Schuette 1,2, Annika Gramatke 3, Max von Kleist 1, Jutta Sharbati 3
1 : Institute of Mathematics, Freie Universität Berlin
2 : Mathematics for Life and Materials Sciences, Zuse Institute Berlin
3 : Institute of Veterinary Biochemistry, Freie Universität Berlin
* : Corrsponding author
Abstract
Predicting adverse effects of chemicals with respect to their distinguishing temporal and dose-dependent mode of action denotes a formidable challenge in toxicological research. In this project, we addressed the aforementioned problems by developing a framework for predicting the toxicity of chemicals using real-time cell impedance measurements and transcriptomics data (mRNA and miRNA) obtained from rat intestinal cell line IEC-6.
Real-time cell impedance measurements provide a novel, fast and cost effective
in vitro method that may be used to probe compounds' toxicity. In order to improve the interpretability and usability of this experimental method, we developed a mathematical model for quantifying the cytotoxicity of chemicals (in terms of its 50% inhibitory concentration IC50 and cell growth rate). Estimated IC50 values for the apparently toxic compounds were in good agreement with literature knowledge. Furthermore, a computational analysis of the transcriptomics data was undertaken to identify the ‘molecular mechanism of action' of the test chemicals. Our analysis showed that 2-acetylamino-fluorene and benzo-[a]-pyrene were severely genotoxic, with several genes differentially expressed even at very low doses.
Taken together, by developing a foundation work for modeling impedance measurements and analyzing transcriptomics datasets for predicting cytotoxicity, our study contributed to the goal of improving
in vitro strategies for genotoxicity testing.
