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Selfishness versus functional cooperation in a stochastic protocell model.
Elias Zintzaras1, Mauro Santos, Eörs Szathmáry
1Collegium Budapest, Institute for Advanced Study, Szentháromság u. 2, H-1014 Budapest, Hungary.
Journal of Theoretical Biology
|September 15, 2010
Summary
Designing artificial systems to evolve complexity requires managing internal competition. Preventing strong competition between replicators in artificial cells allows for catalyst proliferation and improved efficiency, offering insights into metabolic complexity evolution.
Area of Science:
- Origin of Life Studies
- Artificial Life Research
- Evolutionary Biology
Background:
- Darwin's theory provides a foundation for evolution, but modern evolutionary theory struggles to predict future complexity.
- Major evolutionary transitions suggest complexity arises when individual competition is reduced.
- The concept of multi-level selection is crucial for understanding the emergence of complexity.
Purpose of the Study:
- To design an artificial system capable of evolving increased complexity.
- To investigate the role of competition and selection levels in the emergence of complexity.
- To explore potential evolutionary pathways for metabolic complexity in artificial cells.
Main Methods:
- Analysis of the dynamical behavior of competing replicators within compartments.
- Modeling artificial cell design to mitigate strong internal competition.
- Simulating scenarios with equal probability selection of replicators.
Main Results:
- A proliferation of differentiated catalysts can evolve in designed artificial cells.
- Improvement in the catalytic efficiency of ribozymes is achievable.
- Preventing strong internal competition facilitates the evolution of complexity.
Conclusions:
- Artificial cells with controlled internal competition can foster the evolution of complexity.
- Experimental evolution in these systems serves as models for artificial adaptive systems.
- This research provides insights into the evolutionary paths toward metabolic complexity.
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