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Development of a biology-driven computational model for vertebrate neural tube closure as a tool in chemical developmental toxicity assessment
Citation:
Piersma, A., H. Heusinkveld, Y. Staal, G. Daston, R. Spencer, AND T. Knudsen. Development of a biology-driven computational model for vertebrate neural tube closure as a tool in chemical developmental toxicity assessment. 5th International Conference on Developmental Neurotoxicity Testing (DNT5), Konstanz, Konstanz, GERMANY, April 05 - 08, 2020.
Impact/Purpose:
Abstract submitted to the 5th International Conference on Developmental Neurotoxicity Testing (DNT5) Konstanz Germany April 2020.
Description:
Computational models of biological processes are expected to revolutionize chemical safety assessment in the not too far future. Such models provide the template for establishing quantitative adverse outcome pathway (AOP) networks that define critical key events that need monitoring in in vitro cell models, and provide algorithms for data integration towards defining safety profiles of chemicals at the level of the intact human. This project aims at modelling mammalian neural tube closure in silico, as a tool for defining the related AOP network and its critical key events that need monitoring in selected in vitro assays. The starting point was the retinoid signaling pathway, given that endogenous retinoic acid plays a crucial role in cell fate, pattern formation and morphogenesis in the early mammalian embryo. We have extensively mined the developmental biology and toxicology literature to generate a gene and cell compartment interaction map for neurulation. This system, produced in CellDesigner, maps the cascade of gene expression changes programmed in the embryo for positional effects on cellular processes (e.g., proliferation, migration, differentiation) ultimately resulting in neural fold elevation and closure from the neural plate. We are currently translating this map into a three-dimensional in silico neural tube closure model, produced in the CompuCell3d modeling environment, which is driven by the gene expression map. This model will finally enable to study in silico the consequences for neural tube closure of model compound-induced gene expression changes detected in relevant in vitro assays. This abstract does not reflect Agency policy