Bistability of compartmentalized autocatalytic systems at the dawn of hereditary variation

Inheritance is central to life, but its first chemical basis may have preceded the complex molecules that store genetic information in modern organisms. Molecules in autocatalytic chemical networks facilitate the formation of more instances of the same molecules. They have long been proposed as simpler candidates for primitive heredity, yet it has remained unclear how such systems could show stable, selectable variation rather than mere short-term adjustment to changing conditions. Here we show that two mutually interacting autocatalytic networks can form alternative stable chemical states, maintained by weak cross-catalysis and switched by environmental change when enclosed in reproducing compartments. Rare compartments dominated by the previously unfavored autocatalyst arise through stochastic partitioning at division and are then amplified by selection in a changed environment, producing an analog of genetic adaptation before template-based replication. The results suggest that primitive inheritance could have been attractor-based, collective, and chemical, rather than sequence-based from the outset. They also identify a concrete dynamical signature to seek in experimental systems chemistry: compartmentalized autocatalytic networks that retain memory of past states while remaining able to switch under selection. Such behavior would extend evolutionary reasoning to a pregenetic stage of life’s origin and clarify how protocell-level evolution could begin before modern genes existed.

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Journal
Proceedings of the National Academy of Sciences
Published
2026-09-21
DOI
https://doi.org/10.1073/pnas.2621400123
Primary Topic
Origins and Evolution of Life
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article
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Bistability of compartmentalized autocatalytic systems at the dawn of hereditary variation

András Szilágyi, Eörs Szathmáry, Alexa Iván
Proceedings of the National Academy of Sciences
Origins and Evolution of Life
article

Bistability of compartmentalized autocatalytic systems at the dawn of hereditary variation

András Szilágyi, Eörs Szathmáry, Alexa Iván
article en

Abstract

Inheritance is central to life, but its first chemical basis may have preceded the complex molecules that store genetic information in modern organisms. Molecules in autocatalytic chemical networks facilitate the formation of more instances of the same molecules. They have long been proposed as simpler candidates for primitive heredity, yet it has remained unclear how such systems could show stable, selectable variation rather than mere short-term adjustment to changing conditions. Here we show that two mutually interacting autocatalytic networks can form alternative stable chemical states, maintained by weak cross-catalysis and switched by environmental change when enclosed in reproducing compartments. Rare compartments dominated by the previously unfavored autocatalyst arise through stochastic partitioning at division and are then amplified by selection in a changed environment, producing an analog of genetic adaptation before template-based replication. The results suggest that primitive inheritance could have been attractor-based, collective, and chemical, rather than sequence-based from the outset. They also identify a concrete dynamical signature to seek in experimental systems chemistry: compartmentalized autocatalytic networks that retain memory of past states while remaining able to switch under selection. Such behavior would extend evolutionary reasoning to a pregenetic stage of life’s origin and clarify how protocell-level evolution could begin before modern genes existed.

Proceedings of the National Academy of SciencesVol. 123(39)
Eötvös Loránd University (HU), Parmenides Foundation (DE), HUN-REN Centre for Ecological Research (HU)
Life in Land
Openalex Percentile: Top 10%
Origins and Evolution of Life
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Bistability of compartmentalized autocatalytic systems at the dawn of hereditary variation — András Szilágyi, Eörs Szathmáry, et al. · Proceedings of the National Academy of Sciences (2026) | TGRS Research Map | TGRS