Abstract
Predictive modelling of complex biological systems and biophysical interactions requires the inclusion of multiple nano- and micro-scale events. In many scenarios, however, numerical solutions alone do not necessarily enhance the understanding of the system. Instead, this work explores the use of an agent-based model with visualization capabilities to elucidate interactions between single cells. We present a model of juxtacrine signalling, using Cell Studio, an agent-based modelling system, based on gaming and three-dimensional visualization tools. The main advantages of the system are its ability to apply any cell geometry and to dynamically visualize the diffusion and interactions of the molecules within the cells in real time. These provide an excellent tool for obtaining insight about different biological scenarios, as the user may view the dynamics of a system and observe its emergent behaviour as it unfolds. The agent-based model was validated against the results of a mean-field model of Notch receptors and ligands in two neighbouring cells. The conversion to an agent-based model is described in detail. To demonstrate the advantages of the model, we further created a filopodium-mediated signalling model. Our model revealed that diffusion and endocytosis alone are insufficient to produce significant signalling in a filopodia scenario. This is due to the bottleneck at the cell-filopodium contact region and the long distance to the end of the filopodium. However, allowing active transport of ligands into filopodia enhances the signalling significantly compared with a face-to-face scenario. We conclude that the agent-based approach can provide insights into mechanisms underlying cell signalling. The open-source model can be found in the Internet hosting service GitHub.