Modeling microevolution in a changing environment: the evolving quasispecies and the diluted champion process

Bianconi, Ginestra; Fichera, Davide; Franz, Silvio; Peliti, Luca

doi:10.1088/1742-5468/2011/08/p08022

Cited by 9 publications

(8 citation statements)

References 22 publications

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Section: Discussionmentioning

confidence: 99%

“…The dilution terms φ x/y are obtained from the conditions iẋ i = 0 and iẏ i = 0, respectively, and keep the sizes of the two populations fluctuating around constant values. This constraint applies to the stationary phase of the adaptive race, while we ignore some of the effects of a changing viral load [2, 3, 9,28] and also neglect immune system memory [29] and unspecific recognition [17].To facilitate a systematic study of the effects of demographic noise by means of simulations and theoretical analysis, our starting point is the underlying stochastic master equation [20] which has rarely been used in this context. Its deterministic limit leads to Eq.…”

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confidence: 99%

“…This assumption is of course violated for some biological scenarios, where immune response modulates the viral load [2, 9,28] and may well lead to extinction of the virus [3,40]. We expect that more detailed models including these and other effects relevant in biological situations [17,29] will also be amenable to theoretical analysis based on the stochastic averaging techniques used here.We acknowledge helpful comments by anonymous reviewers and financial support by the Deutsche Forschungsgemeinschaft in the framework of the SFB/TR12 -Symmetries and Universality in Mesoscopic Systems. * Present address: Laboratory of Computational Neuroscience, EPF Lausanne, 1015 Lausanne, Switzerland.…”

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Periodic versus Intermittent Adaptive Cycles in Quasispecies Coevolution

2014

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We study an abstract model for the coevolution between mutating viruses and the adaptive immune system. In sequence space, these two populations are localized around transiently dominant strains. Delocalization or error thresholds exhibit a novel interdependence because immune response is conditional on the viral attack. An evolutionary chase is induced by stochastic fluctuations and can occur via periodic or intermittent cycles. Using simulations and stochastic analysis, we show how the transition between these two dynamic regimes depends on mutation rate, immune response, and population size.Evolution is commonly pictured as a dynamic process on a fitness landscape in sequence space. In general, this landscape depends not only on the genotype but varies dynamically as a function of the environment and coevolving interaction partners [1]. Prominent biological examples are the coevolutionary dynamics between the adaptive immune system and virus populations such as HIV [2, 3] or influenza [4], or between bacteria and their phages [5]. Continuous evolutionary innovations allow the virus to transiently escape immune suppression, triggering subsequent adaptations of the immune system. These dynamics can lead to coevolutionary cycles, which have been generally described in two different forms [4, 6]: either as an intermittent series of quasistationary states connected by stochastic jumps, or as periodic and largely deterministic oscillations. From a modeling perspective, this highly complex process is determined by three main features [7]. First, mutation rates are high and populations are large, which implies large genetic heterogeneity within the populations [8]. This has often been pictured in terms of broad quasispecies distributions around peaks in the fitness landscape [9, 10]. At the same time, continuous adaption and coevolutionary arms races are driven by strong ecological interactions [6, 11]. These modulate effective fitness landscapes [2,12,13] and lead to nontrivial nonlinear population dynamics. Finally, stochastic effects in finite populations become especially pronounced whenever the first two issues are relevant at the same time [11,[14][15][16].Here, we offer a synthetic perspective on these processes. In our model [see Fig. 1(a)], we consider a population of N viruses represented by their genotypes (binary sequences of length L and frequency x i ) and replication rates r i = 1. A small number n of these genotypes corresponding to particularly virulent strains have a fitness advantage α over the unit baseline, giving r i = 1 + α for i = p, q, . . .. Offspring sequences undergo mutations with per-base rate µ x . In the absence of immune suppression, and in the stationary state, the viral population localizes as so-called quasispecies around any of the fittest genotypes, provided the mutation rate is smaller than Eigen's error threshold µ c ≈ ln Fig. 1(a), right]. In the deterministic limit (N → ∞), our model is described by [20]where i and j run over all 2 L sequences. The fitness advantage α of ...

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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Periodic versus Intermittent Adaptive Cycles in Quasispecies Coevolution

2014

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“…The fact that viral generation time is the only viral parameter leaving its mark on the genomic mutation rate in this approximation is reminiscent of the fact that genomic mutation rates are of a similar order of magnitude among different classes of viruses [117]. These coevolutionary models have been further extended from single-stranded sequences to double-stranded DNA replication [120] as well as to finite viral populations [121]. Still they leave a demand for more realistic models of the complex interplay between viruses and adaptive immunity.…”

Section: Models For Viral Evolution and Host Pathogen Co-evolutionmentioning

confidence: 99%

Running Loose or Getting Lost: How HIV-1 Counters and Capitalizes on APOBEC3-Induced Mutagenesis through Its Vif Protein

Münk

Jensen

Zielonka

et al. 2012

Viruses

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Human immunodeficiency virus-1 (HIV-1) dynamics reflect an intricate balance within the viruses’ host. The virus relies on host replication factors, but must escape or counter its host’s antiviral restriction factors. The interaction between the HIV-1 protein Vif and many cellular restriction factors from the APOBEC3 protein family is a prominent example of this evolutionary arms race. The viral infectivity factor (Vif) protein largely neutralizes APOBEC3 proteins, which can induce in vivo hypermutations in HIV-1 to the extent of lethal mutagenesis, and ensures the production of viable virus particles. HIV-1 also uses the APOBEC3-Vif interaction to modulate its own mutation rate in harsh or variable environments, and it is a model of adaptation in a coevolutionary setting. Both experimental evidence and the substantiation of the underlying dynamics through coevolutionary models are presented as complementary views of a coevolutionary arms race.

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Universality Classes: Perceptron Versus Sphere Models

Altieri¹

2019

Jamming and Glass Transitions

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Modeling microevolution in a changing environment: the evolving quasispecies and the diluted champion process

Cited by 9 publications

References 22 publications

Periodic versus Intermittent Adaptive Cycles in Quasispecies Coevolution

Periodic versus Intermittent Adaptive Cycles in Quasispecies Coevolution

Running Loose or Getting Lost: How HIV-1 Counters and Capitalizes on APOBEC3-Induced Mutagenesis through Its Vif Protein

Universality Classes: Perceptron Versus Sphere Models

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