Adaptation Rates of Lytic Viruses Depend Critically on Whether Host Cells Survive the Bottleneck

Patwa, Zaheerabbas; Wahl, Lindi M.

doi:10.1111/j.1558-5646.2009.00887.x

Cited by 12 publications

(21 citation statements)

References 49 publications

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“…These populations often experience sudden environmental changes that can drastically affect their size, e.g. by leading to population bottlenecks under which the colony of reduced size is more prone to fluctuations [32][33][34][35]. The coupling between the different forms of randomness, therefore, generates feedback loops between & 2018 The Author(s) Published by the Royal Society.…”

Section: Introductionmentioning

confidence: 99%

Eco-evolutionary dynamics of a population with randomly switching carrying capacity

Wienand

Frey

Mobilia

2018

J. R. Soc. Interface.

132

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Environmental variability greatly influences the eco-evolutionary dynamics of a population, i.e. it affects how its size and composition evolve. Here, we study a well-mixed population of finite and fluctuating size whose growth is limited by a randomly switching carrying capacity. This models the environmental fluctuations between states of resources abundance and scarcity. The population consists of two strains, one growing slightly faster than the other, competing under two scenarios: one in which competition is solely for resources, and one in which the slow (cooperating) strain produces a public good (PG) that benefits also the fast (free-riding) strain. We investigate how the coupling of demographic and environmental (external) noise affects the population's eco-evolutionary dynamics. By analytical and computational means, we study the correlations between the population size and its composition, and discuss the social-dilemma-like 'eco-evolutionary game' characterizing the PG production. We determine in what conditions it is best to produce a PG; when cooperating is beneficial but outcompeted by free riding, and when the PG production is detrimental for cooperators. Within a linear noise approximation to populations of varying size, we also accurately analyse the coupled effects of demographic and environmental noise on the size distribution.

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Section: Introductionmentioning

confidence: 99%

Eco-evolutionary dynamics of a population with randomly switching carrying capacity

Wienand

Frey

Mobilia

2018

J. R. Soc. Interface.

132

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“…On the other hand, the paper by Lehe et al (2012) on the rate of a beneficial mutations surfing on the wave of a range expansion is based on a pioneering paper of R. A. Fisher and seems to be related to a class of branching diffusion processes. Another paper on the applications of branching processes is that of Patwa and Wahl (2010), who applied these processes to estimate the substitution rate at which beneficial mutations occur and fix in populations of lytic viruses whose growth is controlled by periodic population bottlenecks. A multitype Galton–Watson process was applied directly by Serra and Haccou (2007) to study the dynamics of escape mutants, when the expected number of offspring by mutant genotypes is so small that they are doomed to extinction.…”

Section: Introductionmentioning

confidence: 99%

On the inclusion of self regulating branching processes in the working paradigm of evolutionary and population genetics

Mode¹,

Sleeman²,

Raj³

2013

Front. Gene.

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The principal goal of this methodological paper is to suggest to a general audience in the genetics community that the consideration of recent developments of self regulating branching processes may lead to the possibility of including this class of stochastic processes as part of working paradigm of evolutionary and population genetics. This class of branching processes is self regulating in the sense that an evolving population will grow only to a total population size that can be sustained by the environment. From the mathematical point of view the class processes under consideration belongs to a subfield of probability and statistics sometimes referred to as computational applied probability and stochastic processes. Computer intensive methods based on Monte Carlo simulation procedures have been used to empirically work out the predictions of a formulation by assigning numerical values to some point in the parameter space and computing replications of realizations of the process over thousands of generations of evolution. Statistical methods are then used on such samples of simulated data to produce informative summarizations of the data that provide insights into the evolutionary implications of computer experiments. Briefly, it is also possible to embed deterministic non-linear difference equations in the stochastic process by using a statistical procedure to estimate the sample functions of the process, which has interesting methodological implications as to whether stochastic or deterministic formulations may be applied separately or in combination in the study of evolution. It is recognized that the literature on population genetics contains a substantial number of papers in which Monte Carlo simulation methods have been used. But, this extensive literature is beyond the scope of this paper, which is focused on potential applications of self regulating branching processes in evolutionary and population genetics.

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“…This can lead to coupling between DN and environmental variability (EV), with external factors affecting the population size, which in turn modulates the DN strength. The interplay between EV and DN plays a key role in microbial communities [56][57][58][59][60][61][62][63]: the variations of their composition and size are vital to understand the mechanisms of antimicrobial resistance [26,58], and may lead to population bottlenecks, where new colonies consisting of few individuals are prone to fluctuations [56,59,[61][62][63]. Interactions between microbial communities and environment have also been found to influence cooperative behavior in Pseudomonas fluorescens biofilms [60][61][62].…”

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confidence: 99%

Population Dynamics in a Changing Environment: Random versus Periodic Switching

et al. 2020

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Environmental changes greatly influence the evolution of populations. Here, we study the dynamics of a population of two strains, one growing slightly faster than the other, competing for resources in a timevarying binary environment modeled by a carrying capacity switching either randomly or periodically between states of abundance and scarcity. The population dynamics is characterized by demographic noise (birth and death events) coupled to a varying environment. We elucidate the similarities and differences of the evolution subject to a stochastically and periodically varying environment. Importantly, the population size distribution is generally found to be broader under intermediate and fast random switching than under periodic variations, which results in markedly different asymptotic behaviors between the fixation probability of random and periodic switching. We also determine the detailed conditions under which the fixation probability of the slow strain is maximal.

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Adaptation Rates of Lytic Viruses Depend Critically on Whether Host Cells Survive the Bottleneck

Cited by 12 publications

References 49 publications

Eco-evolutionary dynamics of a population with randomly switching carrying capacity

Eco-evolutionary dynamics of a population with randomly switching carrying capacity

On the inclusion of self regulating branching processes in the working paradigm of evolutionary and population genetics

Population Dynamics in a Changing Environment: Random versus Periodic Switching

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