FBCA, A Multiscale Modeling Framework Combining Cellular Automata and Flux Balance Analysis
Alex Graudenzi, Davide Maspero and Chiara Damiani
Multiscale computational models are powerful instruments to investigate the properties of biological systems, provide explanations about their complex behaviours and predict their likely future evolution. We here investigate the relation among the metabolic properties of cells and the emerging population dynamics of multi-cellular systems, such as tissues and organs, especially in abnormal circumstances, such as cancer origination and development.
To this end, we introduce FBCA (Flux Balance Cellular Automata) a multiscale modeling framework that combines a cellular automaton representation of the spatial/morphological dynamics of multi-cellular systems, i.e., the Cellular Potts Model, with a model of the metabolic activity of individual cells, as modeled via Flux Balance Analysis.With this framework, it is possible to investigate, both qualitatively and quantitatively, the dynamics and the spatial behavior of cell sub-populations in a variety of experimental scenarios.
In particular, we here show the results of a simplified model of intestinal crypt, which is the locus in which colorectal cancer is supposed to originate. We show that competition and selection phenomena are indeed largely driven by the metabolic properties of the cell sub-populations populating the crypt, leading to often non predictable dynamics. Finally, we present a scenario in which cancer recurrence is explained by the presence of non-dominant drug-resistant subclones.
Keywords: Cellular potts model, metabolic networks, flux balance analysis, population dynamics, multi-cellular systems