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The probability of permanence

P F Stadler1, R Happel

  • 1Institut für Theoretische Chemie, Universität Wien, Austria.

Mathematical Biosciences
|January 1, 1993
PubMed
Summary

Cooperation is rare in autocatalytic networks. Larger networks are less probable, suggesting hypercycles alone can't sustain genetic information in early RNA worlds.

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Area of Science:

  • Systems chemistry
  • Origin of life research
  • Biophysics

Background:

  • Autocatalytic networks are fundamental to understanding self-organization and the origin of life.
  • Hypercycle models propose a mechanism for maintaining genetic information through cyclic interactions.
  • Previous research has explored cooperation in simplified chemical systems.

Purpose of the Study:

  • To investigate the probability of cooperation in autocatalytic networks of varying sizes.
  • To assess the feasibility of evolving larger cooperative networks from smaller ones.
  • To evaluate the sufficiency of hypercycle interactions for genetic information maintenance in a pure RNA world.

Main Methods:

  • Numerical experiments simulating autocatalytic networks.
  • Analysis of cooperation probability as a function of network size (n).
  • Modeling the evolutionary process of incorporating new species into existing cooperative networks.

Main Results:

  • Cooperation becomes exceedingly rare in autocatalytic networks exceeding approximately five species.
  • The probability of cooperative behavior in random networks decreases exponentially with the number of interacting species.
  • The evolution of larger, persistent cooperative networks is significantly less probable than maintaining small ones.

Conclusions:

  • Hypercycle-type interactions alone are insufficient to maintain genetic information for more than a few species in an RNA world.
  • The inherent instability of cooperation in larger networks poses a significant challenge to early life evolution.
  • Alternative or complementary mechanisms are likely required for the emergence of complex genetic systems.

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