Abstract
Cooperation is essential for evolution of biological complexity. Recent work has shown game theoretic arguments, commonly used to model biological cooperation, can also illuminate the dynamics of chemical systems. Here we investigate the types of cooperation possible in a real RNA system based on the Azoarcus ribozyme, by constructing a taxonomy of possible cooperative groups. We construct a computational model of this system to investigate the features of the real system promoting cooperation. We find triplet interactions among genotypes are intrinsically biased towards cooperation due to the particular distribution of catalytic rate constants measured empirically in the real system. For other distributions cooperation is less favored. We discuss implications for understanding cooperation as a driver of complexification in the origin of life.
Highlights
There has been a renewed interest in the importance of cooperation and collective behavior for both the emergence and evolution of biological complexity [1,2] and, importantly, for the origins of life itself [3]
The internal guide sequence (IGS)–tag triplet–triplet binding through nucleotide pairing is the key chemical and informational interaction that determines the rate at which one genotype will catalyze the covalent assembly of another ribozyme [15]
We further found that these enhanced rates of cooperation were well-explained by the heterogeneous distribution of catalytic rate constants
Summary
There has been a renewed interest in the importance of cooperation and collective behavior for both the emergence and evolution of biological complexity [1,2] and, importantly, for the origins of life itself [3]. The Azoracus catalytic RNA covalent self-assembly system [8] allows us to explore these concepts directly both experimentally and computationally. In this system, cooperation arises due to the interaction among distinct genotypes leading to collective fitness gain. Cooperation arises due to the interaction among distinct genotypes leading to collective fitness gain
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