Prebiotic Competition between Information Variants, With Low Error Catastrophe Risks

Entropy

Radu Popa¹  Vily Marius Cimpoiasu² 

[1]Department of Biological Sciences, University of Southern California, 3616, Trousdale Parkway, 900089, Los Angeles, CA, USA

[2] E-Mail:

[3]Department of Biology and Environmental Engineering, Frontier Biology and Astrobiology Research Center, University of Craiova, 13 A.I. Cuza Street, 200585 Craiova, Romania

关键词: dynamic system;    prebiotic evolution;    error catastrophe;    energy;    autocatalysis;    BiADA;   

DOI  :  10.3390/e17085274

来源: mdpi

【 摘 要 】

During competition for resources in primitive networks increased fitness of an information variant does not necessarily equate with successful elimination of its competitors. If variability is added fast to a system, speedy replacement of pre-existing and less-efficient forms of order is required as novel information variants arrive. Otherwise, the information capacity of the system fills up with information variants (an effect referred as “error catastrophe”). As the cost for managing the system’s exceeding complexity increases, the correlation between performance capabilities of information variants and their competitive success decreases, and evolution of such systems toward increased efficiency slows down. This impasse impedes the understanding of evolution in prebiotic networks. We used the simulation platform Biotic Abstract Dual Automata (BiADA) to analyze how information variants compete in a resource-limited space. We analyzed the effect of energy-related features (differences in autocatalytic efficiency, energy cost of order, energy availability, transformation rates and stability of order) on this competition. We discuss circumstances and controllers allowing primitive networks acquire novel information with minimal “error catastrophe” risks. We present a primitive mechanism for maximization of energy flux in dynamic networks. This work helps evaluate controllers of evolution in prebiotic networks and other systems where information variants compete.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.