Autocatalytic chemical ecosystems

In origins-of-life research, a key challenge is to explain the emergence of polymers of sufficient length to confer the complex functions needed for genetic inheritance. Previous studies have demonstrated that prebiotic environments enabling multilevel selection can facilitate the survival of cooperating polymers such as ribozymes, which allows that complex functions undertaken today by long polymers might have originated from multiple simpler functions undertaken by shorter polymers. To further investigate this possibility, we developed a new computational model of cooperative catalytic and replicating polymer systems that avoids tracking all possible polymer sequences. This approach scales well computationally, avoiding the need to set an a priori cap on polymer length. We first validated this model by replicating key conclusions of previous studies, for example that the persistence of cooperative synthetase-ligase systems is facilitated by both intrinsic factors (shorter length, higher catalytic efficiency) and by factors that promote multilevel-selection (compartmentalization, slower diffusion). We then explored the effects of introducing a mutation inhibitor into a cooperative synthetase-ligase system. The results support the possibility that mutation inhibition could have arisen, not through the appearance of a single proofreading polymerase, but through the emergence of distinct, mutation inhibiting catalysts.

doi: 10.1007/s00239-026-10323-6

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

The origins of genetic information processing remain a mystery in prebiotic chemistry research. Genetic systems encode information as digital sequences of nucleotide residues and require multiple interdependent and complex components that were likely to have been established late in the prebiotic evolutionary process. Candidate predecessor systems are potentially insightful for examining how genetic systems could have been scaffolded by alternatives that were simpler, yet capable of performing comparable functions. Some researchers have proposed that relative concentrations of simple chemical species (i.e., chemical compositions) could encode heritable information in an analog manner. While conceptually plausible, it is difficult to explain how most forms of analog inheritance (which can be highly sensitive to interference) could underpin emergent characteristics that are necessary for adaptive evolution afforded by high-fidelity, polymer-based digital inheritance. Here, by simulating bistable reaction systems with two simple autocatalytic cycles in lattices of connected flow reactors, we show that without linear polymers, it is still possible to encode spatial configurations of discrete states of chemical compositions that are heritable and mutable. Different configurations can have differing likelihoods of propagating to new environments, which means that they can respond to at least some types of selective processes. Taken together, these spatial configurations are heritable, mutable, and selectable (HMS). They are similar to analog inheritance because they depend on chemical compositions, and they are similar to digital inheritance because they consist of spatially distributed, discretized units. Although such discrete HMS spatial configurations are far less heritable, more mutable, and less selectable than nucleotide-sequence-based digital inheritance, they represent a possible bridge between analog and digital inheritance in complex chemical systems.

doi: 10.26434/chemrxiv-2023-mk784-v2

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