A Computational Model Predicting Disruption of Blood Vessel Development

Abstract

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.

Consensus report on the future of animal-free systemic toxicity testing

“…Some promising first results come from an in silico modeling platform: A novel multi-cellular agent-based model (ABMs) of vasculogenesis using the CompuCell3D (http://www.compucell3d.org/) modeling environment supplemented with semi-automatic knowledgebase creation has been developed by ePA. Dynamic cell ABMs have been shown to simulate complex developing systems and, consequently, display a potential to simulate adverse effects (Kleinstreuer et al, 2013;Hester et al, 2011;Shirinifard et al, 2013) and aberrant tissue fusion (Ray and Niswander, 2012).…”

BioCAE: A New Strategy of Complex Biological Systems for Biofabrication of Tissues and Organs

“…Modelling and simulation of diffusion process in tissue spheroids CFD [14] Agent-based virtual tissue simulations CC3D [17] Cell compressibility, motility and contact inhibition on the growth of tumor cell clusters CC3D [18] Multiscale modeling of the early CD8 T cell immune response in lymph nodes CC3D [19] Multi-scale knowledge on cardiac development CC3D [20] The cell behavior ontology CC3D [21] Cell differentiation in the transition to multicellularity CC3D [22] Dynamics of cell aggregates fusion CC3D [36] A multi-cell model of tumor evolution CC3D [37] Virtual tissues MAS [38] Disruption of blood vessel development CC3D [39] Tumor growth and angiogenesis CC3D [40] Agent-oriented in silico liver (ILS) MAS [41] Model of thrombus development MAS (TS) [42] Three-dimensional multi-scale tumor model MAS [43] A multi-scale model of dendritic cell education and trafficking in the lung CM [44] Multi-scale model of follicular development CM [45] Multi-scale in silico leukocytes model MAS [46] Multi-scale model of organogenesis CM [47] Limitations of spheroids under inappropriate conditions FE [48] Finite lower levels occur at multiple time scales influencing the behavior of the organ. Multi-scale models are usually based on the continuum modeling and/or MAS approaches which can be decomposed into N single-scale mathematical models and several physical processes.…”

“…Multi-scale models are usually based on the continuum modeling and/or MAS approaches which can be decomposed into N single-scale mathematical models and several physical processes. Various works have already been done which apply many multi-scale methods in several biological systems [14,[17][18][19][20][21][22][36][37][38][39][40][41][42][43][44][45][46][47][48][49]: a good review is proposed in Table 1.…”

Applicability of Computational Systems Biology in Toxicology

“…The use of computational toxicology has, for example, proven useful in the development of predictive signatures for various in vivo end-points by integration of the ToxCast data with in vivo data [9][10][11][12][13] and for the proposal of an adverse outcome pathway for disruption of embryonic vascular development [14].…”