Autocatalytic chemical ecosystems

Autocatalysis is thought to have played an important role in the earliest stages of the origin of life. An autocatalytic cycle (AC) is a set of reactions that results in stoichiometric increase in its constituent chemicals. When the reactions of multiple interacting ACs are active in a region of space, they can have interactions analogous to those between species in biological ecosystems. Prior studies of autocatalytic chemical ecosystems (ACEs) have suggested avenues for accumulating complexity, such as ecological succession, as well as obstacles such as competitive exclusion. We extend this ecological framework to investigate the effects of surface adsorption, desorption, and diffusion on ACE ecology. Simulating ACEs as particle-based stochastic reaction-diffusion systems in spatial environments-including open, two-dimensional reaction-diffusion systems and adsorptive mineral surfaces-we demonstrate that spatial structure can enhance ACE diversity by (i) permitting otherwise mutually exclusive ACs to coexist and (ii) subjecting new AC traits to selection.

doi: 10.1038/s44260-025-00045-z

Prior research on evolutionary mechanisms during the origin of life has mainly assumed the existence of populations of discrete entities with information encoded in genetic polymers. Recent theoretical advances in autocatalytic chemical ecology establish a broader evolutionary framework that allows for adaptive complexification prior to the emergence of bounded individuals or genetic encoding. This framework establishes the formal equivalence of cells, ecosystems and certain localized chemical reaction systems as autocatalytic chemical ecosystems (ACEs): food-driven (open) systems that can grow due to the action of autocatalytic cycles (ACs). When ACEs are organized in meta-ecosystems, whether they be populations of cells or sets of chemically similar environmental patches, evolution, defined as change in AC frequency over time, can occur. In cases where ACs are enriched because they enhance ACE persistence or dispersal ability, evolution is adaptive and can build complexity. In particular, adaptive evolution can explain the emergence of self-bounded units (e.g. protocells) and genetic inheritance mechanisms. We do this by laying out the parallels between a living cell (or organism) and a local ecosystem and between a population of cells/organisms and a meta-ecosystem of interconnected local ecosystems. This implies that both ecological change (e.g. ecological succession) and Darwinian evolution can be seen as formally equivalent in that each entails changes in the frequency of ACs in a meta-ecosystem. We then tie this insight to the origin of life and explore the two main differences between ecological change and Darwinian evolution, namely compartmentalization and genetics, and describe how prebiotic chemical processes might have bridged this apparent gap by gradually becoming more evolution-like and less ecology-like over time. We end by proposing that the conception of cells as chemical ecosystems provides a powerful new framework for guiding both theoretical and empirical studies of the origins of life.

doi: 10.1098/rsif.2023.0346

It is becoming widely accepted that very early in life's origin, even before the emergence of genetic encoding, reaction networks of diverse small chemicals might have manifested key properties of life, namely self-propagation and adaptive evolution. To explore this possibility, we formalize the dynamics of chemical reaction networks within the framework of chemical ecosystem ecology. To capture the idea that life-like chemical systems are maintained out of equilibrium by fluxes of energy-rich food chemicals, we model chemical ecosystems in well-mixed compartments that are subject to constant dilution by a solution with a fixed concentration of input chemicals. Modelling all chemical reactions as fully reversible, we show that seeding an autocatalytic cycle with tiny amounts of one or more of its member chemicals results in logistic growth of all member chemicals in the cycle. This finding justifies drawing an instructive analogy between an autocatalytic cycle and a biological species. We extend this finding to show that pairs of autocatalytic cycles can exhibit competitive, predator-prey, or mutualistic associations just like biological species. Furthermore, when there is stochasticity in the environment, particularly in the seeding of autocatalytic cycles, chemical ecosystems can show complex dynamics that can resemble evolution. The evolutionary character is especially clear when the network architecture results in ecological precedence, which makes a system's trajectory historically contingent on the order in which cycles are seeded. For all its simplicity, the framework developed here helps explain the onset of adaptive evolution in prebiotic chemical reaction networks, and can shed light on the origin of key biological attributes such as thermodynamic irreversibility and genetic encoding.

doi: 10.1016/j.jtbi.2020.110451