An ecological framework for the analysis of prebiotic chemical reaction networks

• Published in: Journal of theoretical biology Vol. 507; p. 110451
• Main Authors: Peng, Zhen, Plum, Alex M., Gagrani, Praful, Baum, David A.
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 21.12.2020
• Subjects: Autocatalytic cycle; Catalysis; Chemical ecosystem ecology; Chemical kinetics; Ecosystem; Logistic growth model; Models, Biological; Origin of Life; Chemical ecosystem ecology; Logistic growth model; Origin of life; Autocatalytic cycle; Chemical kinetics
• DOI: 10.1016/j.jtbi.2020.110451
• ISSN: 0022-5193; 1095-8541

[Display omitted] •Early life was an open chemical system of reversible reactions with branched autocatalytic cycles (ACs).•Individual ACs show logistic growth like a biological population.•Pairs of ACs can interact just like biological species, including competition, predation, etc.•Simple chemical ecosystems can exhibit successional dynamics and historical contingence, implying evolution.•A chemical ecosystem framework explains how adaptive evolution can precede genetic encoding. 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.