Modelling the prebiotic origins of regulation & agency in evolving protocell ecologies

Abstract

How did natural systems develop the first mechanisms of regulation and what for? How could they turn into adaptive agents in a minimal (though deeply meaningful) biological sense? A novel simulation platform, Araudia, has been implemented to address these questions, which are deeply interrelated, in a prebiotic scenario where metabolically diverse protocells are allowed to modify their dynamic behaviour in response to changes in their boundary conditions (e.g., nutrient concentrations in the medium) and/or in the activity of other protocells, including cross-feeding relationships. We extend consumer-resource models (CRMs) to a stochastic evolutionary framework in which novelty appears bottom-up (i.e., from small changes at the individual protocell level), and a short-term memory may also come forth and spread in the population, to demonstrate that simple adaptive/learning processes can have relevant effects at somatic times (i.e., within the lifetime of single protocells). Our interest in exploring the interplay between metabolic-physiological aspects and ecological-evolutionary ones derives from the fact that it provides a complex causal domain, where various spatial and temporal scales intermingle, and where both the actual and the potential (pathways/behaviours) must be considered. It is in such a complex domain where the appearance of regulation acquires full significance, as an effective means to navigate phenotypic spaces that become too big for unguided exploration, given the large number of possible functionalities (or functional states) accessible to each proto-cellular agent. The results obtained for several minimalist cases below show that, despite the non-trivial combination of --both endogenous and exogenous--factors involved in the constitution of regulatory mechanisms, these are bound to play a critical role in the survival of infra-biological systems, especially under rapidly changing environmental conditions that longer-term adaptive mechanisms would not be able to cope with.