Selfishness versus functional cooperation in a stochastic protocell model |
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Authors: | Elias Zintzaras,Mauro Santos,Eö rs Szathmá ry |
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Affiliation: | a Collegium Budapest, Institute for Advanced Study, Szentháromság u. 2, H-1014 Budapest, Hungary b Department of Biomathematics, University of Thessaly School of Medicine, 2 Panepistimiou Str, Biopolis, Larissa 41100, Greece c The Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Tufts University School of Medicine, 800 Washington Str, Boston, MA 02111, USA d Departament de Genètica i de Microbiologia, Grup de Biologia Evolutiva (GBE), Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, Spain e Institute of Biology, Eötvös University, 1/c Pázmány Péter sétány, H-1117 Budapest, Hungary f Parmenides Center for the Study of Thinking, Kirchplatz 1, D-82409 Munich/Pullach, Germany |
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Abstract: | How to design an “evolvable” artificial system capable to increase in complexity? Although Darwin’s theory of evolution by natural selection obviously offers a firm foundation, little hope of success seems to be expected from the explanatory adequacy of modern evolutionary theory, which does a good job at explaining what has already happened but remains practically helpless at predicting what will occur. However, the study of the major transitions in evolution clearly suggests that increases in complexity have occurred on those occasions when the conflicting interests between competing individuals were partly subjugated. This immediately raises the issue about “levels of selection” in evolutionary biology, and the idea that multi-level selection scenarios are required for complexity to emerge. After analyzing the dynamical behaviour of competing replicators within compartments, we show here that a proliferation of differentiated catalysts and/or improvement of catalytic efficiency of ribozymes can potentially evolve in properly designed artificial cells where the strong internal competition between the different species of replicators is somewhat prevented (i.e., by choosing them with equal probability). Experimental evolution in these systems will likely stand as beautiful examples of artificial adaptive systems, and will provide new insights to understand possible evolutionary paths to the evolution of metabolic complexity. |
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Keywords: | Artificial cells Functional complexity Monte Carlo methods Qβ replicase Ribozymes |
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