Evolutionary Dynamics of a Population of Cells with a Toxin Suppressor Gene

• Published in: Transactions on Computational Systems Biology XIII Vol. 6575; pp. 1 - 12
• Main Authors: Häkkinen, Antti, Biddle, Fred G., Smolander, Olli-Pekka, Yli-Harja, Olli, Ribeiro, Andre S.
• Format: Book Chapter
• Language: English
• Published: Germany Springer Berlin / Heidelberg 2011; Springer Berlin Heidelberg
• Series: Lecture Notes in Computer Science
• Subjects: High Mutation Rate; Mutation Rate; Neutral Mutation; Noise Strength; Stochastic Simulation Algorithm
• ISBN: 9783642197475; 3642197477
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-642-19748-2_1

Environmental changes are known to trigger evolutionary changes, e.g. by favoring higher mutation rates. We study the evolutionary dynamics of a delayed stochastic genetic circuit using a simulator developed for this aim. We model a cell population subject to selection and environmental changes. Each cell contains a self-repressing gene whose protein degrades a toxin. Allowing mutations, we study the adaptability of this circuit and how the genotypic and phenotypic diversities of the population evolve. Neutral mutations and equally beneficial evolutionary pathways are found to generate complex phenotypic distributions. We find optimal mutation rates dependent on the amount of toxin and show that shifting environmental conditions trigger transient increases in diversity. The results support the hypothesis that evolvability is a selectable trait.