Predicting photosynthetic structures using thermodynamics and machine learning

Abstract

Oxygenic photosynthesis is responsible for nearly all biomass production on Earth, and may have been a prerequisite for the evolution of multicellular life. Life has evolved to perform photosynthesis under a wide range of illumination conditions, but with a common basic architecture of a light-harvesting antenna system coupled to a photochemical reaction centre. Using a general thermodynamic model of energy capture and diffusion in the antennae, coupled with a genetic algorithm to model their evolution, we reproduce qualitatively the antenna structures of multiple types of oxygenic photoautotrophs, including pigment composition, the linear absorption profile and the macrostructural topology, suggesting that the same simple physical principles underlie the development of distinct light-harvesting structures in various photosynthetic organisms. We finally apply our model toextra-solarlight-environments and comment on the relative viability of both oxygenic and anoxygenic photosynthesis on exoplanets orbiting other types of stars.