Modelling genotypes in their physical microenvironment to predict single- and multi-cellular behaviour

Buffa, F.; Voukantsis, D.; Kahn, K.; Hadley, M.; Wilson, R.

doi:10.1101/360446

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bioRxiv · 10.1101/360446

Modelling genotypes in their physical microenvironment to predict single- and multi-cellular behaviour

Buffa, F.·Voukantsis, D.·Kahn, K.·Hadley, M.·Wilson, R.

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Abstract

A cells phenotype is the set of observable characteristics resulting from the interaction of the genotype with the surrounding environment, determining cell behaviour. Deciphering genotype-phenotype relationships has been crucial to understand normal and disease biology. Analysis of molecular pathways has provided an invaluable tool to such understanding; however, it does typically not consider the physical microenvironment, which is a key determinant of phenotype.\n\nIn this study, we present a novel modelling framework that enables to study the link between genotype, signalling networks and cell behaviour in a 3D microenvironment. To achieve this we bring together Agent Based Modelling, a powerful computational modelling technique, and gene networks. This combination allows biological hypotheses to be tested in a controlled stepwise fashion, and it lends itself naturally to model a heterogeneous population of cells acting and evolving in a dynamic microenvironment, which is needed to predict the evolution of complex multi-cellular dynamics. Importantly, this enables modelling co-occurring intrinsic perturbations, such as mutations, and extrinsic perturbations, such as nutrients availability, and their interactions.\n\nUsing cancer as a model system, we illustrate the how this framework delivers a unique opportunity to identify determinants of single-cell behaviour, while uncovering emerging properties of multi-cellular growth.\n\nAvailability and ImplementationFreely available on the web at http://www.microc.org. Research Resource Identification Initiative ID (https://scicrunch.org/): SCR 016672

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Buffa, F., Voukantsis, D., Kahn, K., Hadley, M., Wilson, R.. 2018-07-03. Modelling genotypes in their physical microenvironment to predict single- and multi-cellular behaviour. https://doi.org/10.1101/360446

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