Computer Simulation of the Evolution of Microbial Population: Overcoming Local Minima When Reaching a Peak on the Fitness Landscape

Abstract

The study focuses on the mechanisms of crossing the valleys of fitness by a population of haploid microorganisms, whose fitness depends on allelic values at two different loci and is determined by a complex landscape, the shape of which corresponds to the pattern “a mountain in the field surrounded by a trench”; these mechanisms are analyzed using computer modeling. We have studied the influence of various biological factors on the evolutionary perspective of microbial colonies, the reproduction rate of which is controlled by a protein consisting of two subunits encoded at different loci. Molecular genetic (mutation rate, affinity of subunits), population (fitness function landscape and population density), and ecological (concentration of available substrate in the habitat, flow intensity) factors have been considered. Our results demonstrate that the difference in fitness for various allelic combinations, while determining the shape of the fitness landscape, sets the optimal mutation rates to overcome its valleys and opens a window of opportunity for the evolution of the population toward the state of the highest average fitness. Moreover, depending on the fitness landscape type, either gradual or saltational evolutionary regimes are optimal for reaching the peak.