Darwinian properties and their trade-offs in autocatalytic RNA reaction networks

Baptiste Saudemont,Sandeep Ameta,Simon Arsène,Philippe Nghe,Sophie Foulon,Bryce E. Clifton,Andrew D. Griffiths

doi:10.1038/s41467-021-21000-1

Abstract

Discovering autocatalytic chemistries that can evolve is a major goal in systems chemistry and a critical step towards understanding the origin of life. Autocatalytic networks have been discovered in various chemistries, but we lack a general understanding of how network topology controls the Darwinian properties of variation, differential reproduction, and heredity, which are mediated by the chemical composition. Using barcoded sequencing and droplet microfluidics, we establish a landscape of thousands of networks of RNAs that catalyze their own formation from fragments, and derive relationships between network topology and chemical composition. We find that strong variations arise from catalytic innovations perturbing weakly connected networks, and that growth increases with global connectivity. These rules imply trade-offs between reproduction and variation, and between compositional persistence and variation along trajectories of network complexification. Overall, connectivity in reaction networks provides a lever to balance variation (to explore chemical states) with reproduction and heredity (persistence being necessary for selection to act), as required for chemical evolution.

Highlights

Discovering autocatalytic chemistries that can evolve is a major goal in systems chemistry and a critical step towards understanding the origin of life
We develop a method to generate a wide diversity of reaction networks and measure the relationship between network topology and product formation in a prebiotically relevant experimental model of autocatalytic sets of RNAs7,11,16
We developed a method to generate and measure a high diversity of such RNA reaction networks, using droplet microfluidics coupled to barcoded Next-Generation Sequencing (Fig. 1b, c and Supplementary Fig. 1)

Summary

Introduction

Discovering autocatalytic chemistries that can evolve is a major goal in systems chemistry and a critical step towards understanding the origin of life. Sustaining evolution in reaction networks without template-based replication is by no means trivial, and autocatalytic networks that could support the Darwinian properties of variation, differential reproduction, and heredity are not known[15,25] These properties need to be mediated by chemical compositions (the chemical species present and their concentrations)[26] without the copying of a sequence. We deduce network parameters that control properties central to Darwinian evolution: reproduction, interpreted as the accumulation of autocatalytic species, and variation, interpreted as changes in species fractions We found how these parameters depend on the specificity of the interactions between the catalysts produced during the reaction and their substrates. These molecular rules are found to impose trade-offs between the Darwinian properties they control, predicting how evolutionary trajectories can be constrained in a scenario where networks expand by successive accretion of novel species

Methods

Results

Conclusion