Программный Комплекс HEC 2.0 Для Моделирования Эволюции Прокариотических Сообществ

Lashin, Sergey A.

doi:10.17537/2014.9.585

Cited by 2 publications

(3 citation statements)

References 18 publications

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“…In this work, we used the HEC software package [34] to simulate the evolution of a population of haploid organisms, taking into account fitness landscapes of various shapes. It should be noted that our model is based on the idea of physicochemical interactions between subunits of the enzyme responsible for substrate utilization.…”

Section: Discussionmentioning

confidence: 99%

“…In order to build and explore the multilevel model described above, the Haploid Evolutionary Constructor (HEC) software package was used [33,34]. Previously, HEC was used to model various aspects of the functioning and evolution of microbial communities: the balance between adaptability and biological diversity in symbiotic communities [35], evolutionary trends in the bacterial community-bacteriophage system [36,37], changes in genome complexity in prokaryotic populations [38], and the influence of the spatial organization of the community on the evolution of its constituent microorganisms [37,39].…”

Section: Probabilitymentioning

confidence: 99%

“…(1) describes the linear leaching of part of the cells from the population. Finally, the volume of the environment (volume) has a direct effect on the size of the population by restraining its growth (methodological details related to the description of the volume of the environment in HEC models are given in our previous work [34]). If there is enough substrate in the environment and there are no inhibitory laws in the population that reduce the size of the population as it grows, then increase in volume is guaranteed to give an increase in the maximum possible population size.…”

Section: Influence Of Population and Environmental Parametersmentioning

confidence: 99%

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

et al. 2020

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Probabilitymentioning

confidence: 99%

Section: Influence Of Population and Environmental Parametersmentioning

confidence: 99%

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

et al. 2020

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Bacteriophages affect evolution of bacterial communities in spatially distributed habitats: a simulation study

et al. 2016

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BackgroundBacteriophages are known to be one of the driving forces of bacterial evolution. Besides promoting horizontal transfer of genes between cells, they may induce directional selection of cells (for instance, according to more or less resistance to phage infection). Switching between lysogenic and lytic pathways results in various types of (co)evolution in host-phage systems. Spatial (more generally, ecological) organization of the living environment is another factor affecting evolution. In this study, we have simulated and analyzed a series of computer models of microbial communities evolving in spatially distributed environments under the pressure of phage infection.ResultsWe modeled evolving microbial communities living in spatially distributed flowing environments. Non-specific nutrient supplied in the only spatial direction, resulting in its non-uniform distribution in environment. We varied the time and the location of initial phage infestation of cells as well as switched chemotaxis on and off. Simulations were performed with the Haploid evolutionary constructor software (http://evol-constructor.bionet.nsc.ru/).ConclusionSimulations have shown that the spatial location of initial phage invasion may lead to different evolutionary scenarios. Phage infection decreases the speciation rate by more than one order as far as intensified selection blocks the origin of novel viable populations/species, which could carve out potential ecological niches. The dependence of speciation rate on the invasion node location varied on the time of invasion. Speciation rate was found to be lower when the phage invaded fully formed community of sedentary cells (at middle and late times) at the species-rich regions. This is especially noticeable in the case of late-time invasion.Our simulation study has shown that phage infection affects evolution of microbial community slowing down speciation and stabilizing the system as a whole. This influencing varied in its efficiency depending on spatially-ecological factors as well as community state at the moment of phage invasion.Electronic supplementary materialThe online version of this article (doi:10.1186/s12866-015-0620-4) contains supplementary material, which is available to authorized users.

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Программный Комплекс HEC 2.0 Для Моделирования Эволюции Прокариотических Сообществ

Cited by 2 publications

References 18 publications

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

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

Bacteriophages affect evolution of bacterial communities in spatially distributed habitats: a simulation study

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