Theoretical models of the chemical origins of life depend on self-replication or autocatalysis, processes that arise from molecular interactions, recruitment, and cooperation. Such models often lack details about the molecules and reactions involved, giving little guidance to those seeking to detect signs of interaction, recruitment, or cooperation in the laboratory. Here, we develop minimal mathematical models of reactions involving specific chemical entities: amino acids and their condensation reactions to form de novo peptides. Reactions between two amino acids form a dipeptide product, which enriches linearly in time; subsequent recruitment of such products to form longer peptides exhibit super-linear growth. Such recruitment can be reciprocated: a peptide contributes to and benefits from the formation of one or more other peptides; in this manner, peptides can cooperate and thereby exhibit autocatalytic or exponential growth. We have started to test these predictions by quantitative analysis of de novo peptide synthesis conducted by wet-dry cycling of a five-amino acid mixture over 21 days. Using high-performance liquid chromatography, we tracked abundance changes for >60 unique peptide species. Some species were highly transient, with the emergence of up to 17 new species and the extinction of nine species between samplings, while other species persisted across many cycles. Of the persisting species, most exhibited super-linear growth, a sign of recruitment anticipated by our models. This work shows how mathematical modeling and quantitative analysis of kinetic data can guide the search for prebiotic chemistries that have the potential to cooperate and replicate.
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We thank David Baum, Hayley Boigenzahn, Stephanie Colon-Santos, and Lena Vincent for thoughtful feedback on the manuscript.
This research was funded by the Vilas Distinguished Achievement Professorship, the Office of the Vice Chancellor for Research and Graduate Education, the Wisconsin Institute for Discovery, all at the University of Wisconsin-Madison; an Accelerator Fund grant from the Wisconsin Alumni Research Foundation (WARF); grant U19 AI0104317 from the National Institutes of Health; and grants MCB-2029281 and CBET-2030750 from the US National Science Foundation.
Conflict of Interest
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
Materials & Correspondence
The data that support the findings of this study are available from J.Y. upon reasonable request.
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Sibilska-Kaminski, I.K., Yin, J. Toward Molecular Cooperation by De Novo Peptides. Orig Life Evol Biosph (2021). https://doi.org/10.1007/s11084-021-09603-6
- Amino acids
- de novo peptides
- Kinetic modeling
- Prebiotic chemistry