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A Computational Model Predicting Disruption of Blood Vessel Development
KLEINSTREUER, N., D. J. DIX, M. ROUNTREE, N. BAKER, N. SIPES, D. REIF, R. SPENCER, AND T. B. KNUDSEN. A Computational Model Predicting Disruption of Blood Vessel Development. Shayn M.Pierce (ed.), PLoS Computational Biology. Public Library of Science, San Francisco, CA, 9(4):1-20, (2013).
Traditional in vivo animal testing, usually at high test doses, is low-throughput and costly both in terms of financial and animal resources. These restrictions result in a relatively low number of compounds that have sufficient in vivo data to assess the potential for adverse effects on human development. Toxicity testing in the 21st century is moving toward using HTS assays to rapidly test thousands of chemicals against hundreds of molecular targets and biological pathways, to provide mechanistic information on chemical effects in human cells and small model organisms, and to construct predictive and mechanistic models. Virtual tissue simulations may someday serve as a surrogate to animal testing by providing in silico testing platforms based on computational systems biology. In conjunction with ToxCast HTS data, the model presented here has the potential to predict toxic effects caused by exposure to anti-angiogenic compounds, comparable to in vitro and in vivo angiogenesis assays.
Vascular development is a complex process regulated by dynamic biological networks that vary in topology and state across different tissues and developmental stages. Signals regulating de novo blood vessel formation (vasculogenesis) and remodeling (angiogenesis) come from a variety of biological pathways linked to endothelial cell (EC) behavior, extracellular matrix (ECM) remodeling and the local generation of chemokines and growth factors. Simulating these interactions at a systems level requires sufficient biological detail about the relevant molecular pathways and associated cellular behaviors, and tractable computational models that offset mathematical and biological complexity. Here, we describe a novel multicellular agent-based model of vasculogenesis using the CompuCell3D(http://www.compucell3d.org/) modeling environment supplemented with semi-automatic knowledgebase creation. The model incorporates vascular endothelial growth factor signals, pro- and anti-angiogenic inflammatory chemokine signals, and the plasminogen activating system of enzymes and proteases linked to ECM interactions, to simulate nascent EC organization, growth and remodeling. The model was shown to recapitulate stereotypical capillary plexus formation and structural emergence of non-coded cellular behaviors, such as a heterologous bridging phenomenon linking endothelial tip cells together during formation of polygonal endothelial cords. Molecular targets in the computational model were mapped to signatures of vascular disruption derived from in vitro chemical profiling using the EPA’s ToxCast high-throughput screening (HTS) dataset. Simulating the HTS data with the cell-agent based model of vascular development predicted adverse effects of a reference anti-angiogenic thalidomide analog, 5HPP-33, on in vitro angiogenesis with respect to both concentration-response and morphological consequences. These findings support the utility of cell agent-based models for simulating a morphogenetic series of events and for the first time demonstrate the applicability of these models for predictive toxicology. [The views expressed in this article are those of the authors and do not necessarily reflect the views or policies of the U.S. Environmental Protection Agency.]