An Introduction to the Evolutionary Ecology of Viruses

DeFilippis, Victor R.; Villarreal, Luis P.

doi:10.1016/b978-012362675-2/50005-7

Cited by 35 publications

(40 citation statements)

References 305 publications

(249 reference statements)

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“…Fitness values are taken as the mean direct progeny per individual, which is proportional to the replication rate. Other factors that may have an influence on fitness (11,12) are not considered. Individuals in the model are referred to as sequences or genomes instead of viruses.…”

Section: Methodsmentioning

confidence: 99%

“…The long-term survival probability of a virus should consider parameters other than replication capacity (such as particle stability, transmissibility, etc. [11,12,15]). Despite their limitations, relative fitness values, determined by growth competition experiments between two viral populations in cell culture and in vivo, are providing insights into basic features of quasispecies evolution as well as viral disease progression (5,15,49).…”

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confidence: 99%

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Modeling Viral Genome Fitness Evolution Associated with Serial Bottleneck Events: Evidence of Stationary States of Fitness

Lázaro

Escarmı́s

Domingo

et al. 2002

J Virol

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Evolution of fitness values upon replication of viral populations is strongly influenced by the size of the virus population that participates in the infections. While large population passages often result in fitness gains, repeated plaque-to-plaque transfers result in average fitness losses. Here we develop a numerical model that describes fitness evolution of viral clones subjected to serial bottleneck events. The model predicts a biphasic evolution of fitness values in that a period of exponential decrease is followed by a stationary state in which fitness values display large fluctuations around an average constant value. This biphasic evolution is in agreement with experimental results of serial plaque-to-plaque transfers carried out with foot-and-mouth disease virus (FMDV) in cell culture. The existence of a stationary phase of fitness values has been further documented by serial plaque-to-plaque transfers of FMDV clones that had reached very low relative fitness values. The statistical properties of the stationary state depend on several parameters of the model, such as the probability of advantageous versus deleterious mutations, initial fitness, and the number of replication rounds. In particular, the size of the bottleneck is critical for determining the trend of fitness evolution.The initial steps in virus evolution are generation of diversity (through mutation, recombination, and genome segment reassortment in multipartite genomes), competition among the generated variants, and selection of those mutants showing the largest phenotypic advantage in a given environment (see overviews in references 9, 14, 17, 28, 30, and 40). Because of high mutation rates during viral RNA biosynthesis (2, 18), RNA viruses replicate as complex mutant swarms termed viral quasispecies (14,(21)(22)(23)(24). The degree of adaptation of a viral quasispecies to a given environment is often quantitated by a relative fitness value, which measures the replication capacity of a viral population relative to a reference mutant distinguishable either genotypically or phenotypically (15,26,33,37). The long-term survival probability of a virus should consider parameters other than replication capacity (such as particle stability, transmissibility, etc. [11,12,15]). Despite their limitations, relative fitness values, determined by growth competition experiments between two viral populations in cell culture and in vivo, are providing insights into basic features of quasispecies evolution as well as viral disease progression (5,15,49).Because of the large variations in viral population size during infections in vivo, a focus of interest has been the study of the influence of virus population size on the evolution of fitness values (reviewed in reference 15). Experimental results with several RNA viruses have documented that large population passages often result in fitness gains (7,26,43,45,58) while repeated bottleneck events (serial plaque-to-plaque transfers being an extreme example) lead to average fitness losses (6,19,25,27,59,60),...

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Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

Modeling Viral Genome Fitness Evolution Associated with Serial Bottleneck Events: Evidence of Stationary States of Fitness

Lázaro

Escarmı́s

Domingo

et al. 2002

J Virol

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“…If this process occurs at sufficient frequency, then the host and virus trees may often match, giving a false impression of cospeciation. Second, the ability to jump species boundaries may be dependent on the phylogenetic distance between hosts, so that it is easier to establish a new infection in a closely related host species than in a more distantly related one (5,8). This model at least has a veneer of biological reality as it is evident that as host gene sequences diverge, especially the cellular receptors to which viruses bind, the less likely it is that an invading virus will be able to infect a foreign cell type and establish a productive infection.…”

Section: ϫ5mentioning

confidence: 99%

Molecular Clocks and the Puzzle of RNA Virus Origins

Holmes

2003

J Virol

140

132

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Although the ultimate origins of RNA viruses are uncertain, it seems reasonable to assume that these infectious agents have a long evolutionary history, appearing with, or perhaps before, the first cellular life-forms (38). While the RNA viruses we see today may not date back quite this far, the evidence that some DNA viruses have evolved with their vertebrate hosts over many millions of years (24) makes an equally ancient history for RNA viruses a natural expectation. Yet a very different picture of RNA virus origins is painted if their gene sequences are compared; by using the best estimates for rates of evolutionary change (nucleotide substitution) and assuming an approximate molecular clock (21, 33), it can be inferred that the families of RNA viruses circulating today could only have appeared very recently, probably not more than about 50,000 years ago. Hence, if evolutionary rates are accurate and relatively constant, present-day RNA viruses may have originated more recently than our own species.Before discussing the solutions to this apparent paradox, it is important to determine exactly why the molecular clock estimates of RNA virus origins are so recent. The key to establishing a timescale of viral evolution lies in accurately determining the rate of nucleotide substitution. Most analyses undertaken to date suggest that the average rate of nucleotide substitution in RNA viruses is ϳ10 Ϫ3 substitutions per site per year, with an approximately fivefold range around this (21). The fact that broadly similar rates are found in RNA viruses with very different genome organizations and lifestyles implies that both the error rate associated with RNA polymerase, estimated to be about one mutation per genome replication (10), and the rate of viral replication are roughly constant. If the average substitution rate of ϳ10 Ϫ3 substitutions/site/year is accurate, then, on average, every nucleotide position will have fixed 1 substitution after ϳ1,000 years of evolution (corresponding to an average divergence time between two lineages of only 500 years). This also corresponds to an evolutionary (corrected) distance (d) between two sequences of 1.0, the maximum that can be reliably estimated through sequence comparisons; larger distances will be inherently inaccurate because of uncounted multiple substitutions at single sites. Of course, reality is a little more complex because viral genomes are a patchwork of synonymous sites, where mutations do not change the encoded amino acid, and nonsynonymous sites, where mutations alter amino acids and which usually evolve more slowly. If we conservatively assume that the substitution rate at nonsynonymous sites is roughly 100-fold less than that at synonymous sites, at ϳ10 Ϫ5 substitutions/site/year, then a distance d of 1 corresponds to a divergence time of ϳ50,000 years ago, although the greater influence of natural selection at nonsynonymous sites is likely to increase the variance around this. Hence, if two RNA viruses have an evolutionary distance of Ͻ1.0 at nonsynonymous si...

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“…VEE studies the impact of the evolutionary response of viruses to the hosts, and other interacting environmental factors, which are shaping their observed diversity and distribution patterns [18]. Although the role of evolutionary processes in driving viruses to new or more severe outcomes of diseases is known, the study of ecological and historical scenario, in which pathogen-host interaction evolves, is not always so well considered.…”

Section: Viral Evolutionary Ecologymentioning

confidence: 99%

“…The new approach called Viral Evolutionary Ecology (VEE) [17,18] combined with epidemiology will help us to better explain many emerging viral diseases by encompassing the complex interface between such factors as genetic structure, evolutionary biology and ecology of pathogens [19], and environmental aspects such as biodiversity, society, and human impact on natural ecosystems, all of them closely interplaying in ways often as yet unknown [20,21]. This complimentary approach has been previously considered under the field of Evolutionary Epidemiology [22][23][24], however, the impact in the study of viral emergence needs to be highlighted.…”

Section: Introductionmentioning

confidence: 99%