EVOMORPHYS SIGNED

Project "EVOMORPHYS" data sheet

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 Partnership

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 Project objective

My project focuses on answering one fundamental question: what are the drivers of Life’s morphological complexity and diversity? I claim that this question can only be addressed by a Newtonian-Darwinian synthesis that considers how Evolution exploits the physical properties of living matter. I will investigate how the evolutionary process explores the phase space of possible interactions between physical (mechanics, reaction-diffusion) and biological (cell signalling, proliferation, migration) processes and generates configurations that compute functional phenotypes. In particular, I will combine experiments in biology and physics, as well as mathematical models and Artificial-Life (ALife) numerical simulations. The latter will be based on physics’ first principles, symmetry-breaking processes and a genetic algorithm. First, I will investigate how geometry affects signalling by (i) imaging the embryonic development of colour patterns and skin geometries of multiple squamate species with various scale-to-colour pattern correspondences, (ii) generating CRISPR/Cas9 scaleless mutants in two lizard species to study the effect of skin 3D geometry on colour patterning, and (iii) performing ALife experiments to explore how the evolutionary process can modify signalling events and exploit geometry to generate new patterns. Second, I will analyse how growth can affect geometry by (i) performing in-silico experiments where coupling between growth and morphogenesis is systematically explored and (ii) evaluating how much the in-silico model captures morphologies generated with physics laboratory experiments using 3D layered polymeric gels. Third, I will build a Newtonian-Darwinian framework by coupling geometry, signalling, growth and mechanics in extensive open-ended ALife experiments. The results of the EVOMORPHYS project will constitute a novel framework for understanding how Evolution exploits physics to generate the morphological diversity and complexity of Life forms.