Collaborative Research: From ecological dynamics to adaptive evolution during the origin of life

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This study explores the idea that the earliest adaptive evolution operated on self-amplifying cycles of chemical reactions, in contrast to most prior studies, which have assumed that evolution requires elements that carry information in the form of nucleic acids (DNA or RNA). Understanding how the origin of life came about is important because it shapes our expectations about life on earth as it exists today and because it aids us in making predictions about whether and in what form life may exist elsewhere in the universe. This project combines theoretical and laboratory research to address the fundamental question of how mixtures of chemicals could self-organize into evolving systems, as must have occurred during the origin of life. The project tests the hypothesis that interactions among multiple such cycles can change over time, similar to the way in which natural ecosystems change as species invade or go extinct, and that such chemical ecological change can gradually morph into more familiar gene-based evolution. In addition to helping explain how life came to be, the work will likely yield new computational tools for ecological and biochemical research and has the potential to lead to new strategies for chemical engineering. Moreover, the work contributes to breaking down boundaries between the fields of evolutionary biology, ecology, computer science, and systems chemistry. The research will bring together and train a diverse team of researchers whose primary expertise is in biology, chemistry, physics, or computer science. Lastly, this project will produce a set of educational resources, designed to make this new perspective on the interplay between chemistry, ecology, and evolution accessible to students across these fields.The project entails three strands of theoretical research. First, the researchers will develop mathematical and computational tools for analyzing chemical or ecological networks and detecting adaptive evolutionary dynamics. Second, they will conduct analyses of digital ecosystems, composed of numerous digital species interacting in a virtual environment, to understand how patterns of species-species interaction and the spatial structure of the environment affect the capacity for ecological change to resemble evolution. Third, the team will use computer simulations of realistic chemical reaction networks to see if similar factors affect the emergence of adaptive behaviors in chemistry and ecology. These theoretical studies will be combined with laboratory experiments in which the chemical composition of complex mixtures that are driven out of equilibrium by periodic dilution using a flux of chemical food will be tracked over time using liquid-chromatography mass-spectrometry. Statistical analyses of the resulting time courses will be used to detect adaptive behaviors.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.