Issue 36, 2022

Collective adaptability in a replication network of minimal nucleobase sequences

Abstract

A major challenge for understanding the origins of life is to explore how replication networks can engage in an evolutionary process. Herein, we shed light on this problem by implementing a network constituted by two different types of extremely simple biological components: the amino acid cysteine and the canonical nucleobases adenine and thymine, connected through amide bonds to the cysteine amino group and oxidation of its thiol into three possible disulfides. Supramolecular and kinetic analyses revealed that both self- and mutual interactions between such dinucleobase compounds drive their assembly and replication pathways. Those pathways involving sequence complementarity led to enhanced replication rates, suggesting a potential bias for selection. The interplay of synergistic dynamics and competition between replicators was then simulated, under conditions that are not easily accessible with experiments, in an open reactor parametrized and constrained with the unprecedentedly complete experimental kinetic data obtained for our replicative network. Interestingly, the simulations show bistability, as a selective amplification of different species depending on the initial mixture composition. Overall, this network configuration can favor a collective adaptability to changes in the availability of feedstock molecules, with disulfide exchange reactions serving as 'wires' that connect the different individual auto- and cross-catalytic pathways.

Graphical abstract: Collective adaptability in a replication network of minimal nucleobase sequences

Supplementary files

Article information

Article type
Edge Article
Submitted
29 Apr. 2022
Accepted
05 Aug. 2022
First published
11 Aug. 2022
This article is Open Access

All publication charges for this article have been paid for by the Royal Society of Chemistry
Creative Commons BY-NC license

Chem. Sci., 2022,13, 10715-10724

Collective adaptability in a replication network of minimal nucleobase sequences

S. Vela-Gallego, Z. Pardo-Botero, C. Moya and A. de la Escosura, Chem. Sci., 2022, 13, 10715 DOI: 10.1039/D2SC02419E

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