Stochastic model of evolving populations

Bonnaz, D.; Koch, Alain

doi:10.1088/0305-4470/31/2/004

Cited by 12 publications

(9 citation statements)

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“…The last 40 years have seen significant efforts to relax these assumptions and tailor the quasispecies theory to specific organisms, especially HIV: Several, more complex and more realistic fitness landscapes have been employed [37] , [49] , [54] , [55] , [58] , [60] , [76] – [78] . Simultaneously, population genetics-based approaches, which naturally consider stochastic effects associated with finite populations, have been developed [59] , [60] , [79] – [85] . The latter descriptions, however, while painting a more realistic picture of the organisms considered, often make marked deviations from the key predictions of the quasispecies theory.…”

Section: Discussionmentioning

confidence: 99%

Stochastic Simulations Suggest that HIV-1 Survives Close to Its Error Threshold

et al. 2012

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The use of mutagenic drugs to drive HIV-1 past its error threshold presents a novel intervention strategy, as suggested by the quasispecies theory, that may be less susceptible to failure via viral mutation-induced emergence of drug resistance than current strategies. The error threshold of HIV-1, , however, is not known. Application of the quasispecies theory to determine poses significant challenges: Whereas the quasispecies theory considers the asexual reproduction of an infinitely large population of haploid individuals, HIV-1 is diploid, undergoes recombination, and is estimated to have a small effective population size in vivo. We performed population genetics-based stochastic simulations of the within-host evolution of HIV-1 and estimated the structure of the HIV-1 quasispecies and . We found that with small mutation rates, the quasispecies was dominated by genomes with few mutations. Upon increasing the mutation rate, a sharp error catastrophe occurred where the quasispecies became delocalized in sequence space. Using parameter values that quantitatively captured data of viral diversification in HIV-1 patients, we estimated to be substitutions/site/replication, ∼2–6 fold higher than the natural mutation rate of HIV-1, suggesting that HIV-1 survives close to its error threshold and may be readily susceptible to mutagenic drugs. The latter estimate was weakly dependent on the within-host effective population size of HIV-1. With large population sizes and in the absence of recombination, our simulations converged to the quasispecies theory, bridging the gap between quasispecies theory and population genetics-based approaches to describing HIV-1 evolution. Further, increased with the recombination rate, rendering HIV-1 less susceptible to error catastrophe, thus elucidating an added benefit of recombination to HIV-1. Our estimate of may serve as a quantitative guideline for the use of mutagenic drugs against HIV-1.

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Section: Discussionmentioning

confidence: 99%

Stochastic Simulations Suggest that HIV-1 Survives Close to Its Error Threshold

et al. 2012

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“…To consider that all mutations are lethal, or to consider that they are all absent, are extreme, highly unlikely situations. When intermediate situations are studied, it can be seen that the presence of lethality does not prevent error catastrophe from taking place, but it does cause it to happen at much higher mutation rates, that is to say it increases the error threshold (Sardanyes et al 2014;Bonnaz and Koch 1998;Takeuchi and Hogeweg 2007;Tejero et al 2010). This result appears to be independent of the distribution of lethality over the sequence space.…”

Section: The Limits Of the Error Catastrophementioning

confidence: 95%

Theories of Lethal Mutagenesis: From Error Catastrophe to Lethal Defection

Tejero

Montero

Nuño

2015

Current Topics in Microbiology and Immunology

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RNA viruses get extinct in a process called lethal mutagenesis when subjected to an increase in their mutation rate, for instance, by the action of mutagenic drugs. Several approaches have been proposed to understand this phenomenon. The extinction of RNA viruses by increased mutational pressure was inspired by the concept of the error threshold. The now classic quasispecies model predicts the existence of a limit to the mutation rate beyond which the genetic information of the wild type could not be efficiently transmitted to the next generation. This limit was called the error threshold, and for mutation rates larger than this threshold, the quasispecies was said to enter into error catastrophe. This transition has been assumed to foster the extinction of the whole population. Alternative explanations of lethal mutagenesis have been proposed recently. In the first place, a distinction is made between the error threshold and the extinction threshold, the mutation rate beyond which a population gets extinct. Extinction is explained from the effect the mutation rate has, throughout the mutational load, on the reproductive ability of the whole population. Secondly, lethal defection takes also into account the effect of interactions within mutant spectra, which have been shown to be determinant for the understanding the extinction of RNA virus due to an augmented mutational pressure. Nonetheless, some relevant issues concerning lethal mutagenesis are not completely understood yet, as so survival of the flattest, i.e. the development of resistance to lethal mutagenesis by evolving towards mutationally more robust regions of sequence space, or sublethal mutagenesis, i.e., the increase of the mutation rate below the extinction threshold which may boost the adaptability of RNA virus, increasing their ability to develop resistance to drugs (including mutagens). A better design of antiviral therapies will still require an improvement of our knowledge about lethal mutagenesis.

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“…Essa substituição, que despreza as flutuações dessa freqüência, caracteriza a aproximação de campo médio utilizada por diversos autores [21,20].…”

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Técnicas de Modelagem de Processos Epidêmicos e Evolucionários

2006

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Stochastic model of evolving populations

Cited by 12 publications

References 14 publications

Stochastic Simulations Suggest that HIV-1 Survives Close to Its Error Threshold

Stochastic Simulations Suggest that HIV-1 Survives Close to Its Error Threshold

Theories of Lethal Mutagenesis: From Error Catastrophe to Lethal Defection

Técnicas de Modelagem de Processos Epidêmicos e Evolucionários

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