The impact of host-cell dynamics on the fixation probability for lytic viruses

Patwa, Zaheerabbas; Wahl, Lindi M.

doi:10.1016/j.jtbi.2009.05.008

Cited by 9 publications

(18 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Under exponential growth, we can write and , with the solution to [5], [6]. The quantity is commonly referred to as the intrinsic growth rate.…”

Section: Resultsmentioning

confidence: 99%

“…Thus, if is used to calculate the mean, variance, or other moments of lysis time, those moments will be weighted by any systematic change in burst size with . Since gives the average number of progeny produced per unit time, it does not provide information about variance in burst size among cells lysing at the same time; that variance is in fact irrelevant to the growth rate equations because of the mass action assumption, but is relevant to the fate of genotypes when rare [6].…”

Section: Resultsmentioning

confidence: 99%

“…One such model is the growth of a bacterial virus (bacteriophage or ‘phage’) on a continual excess of hosts. In this system, phage fitness is thought to be completely determined by a mere three phenotypes, all easily measurable [1] and translatable into total fitness [2]–[6]. In addition, the system allows independent determination of phage fitness as an empirical check on the complete phenotype-fitness map.…”

Section: Introductionmentioning

confidence: 99%

“…In turn, growth rate is determined by host density and three phage parameters: burst size (fecundity), lysis time (time between infection and cell bursting to release progeny), and adsorption rate. When using large numbers of cells and phage, the process is appropriately modeled by mass action dynamics [1], [2], [5] unless one is concerned with the fate of rare mutants [6]. Furthermore, all 3 phage parameters can be measured in a single assay [1].…”

Section: Introductionmentioning

confidence: 99%

“…Unfortunately, use of the average generation time is known to underestimate actual phage growth rate, seriously so when cell density is low [9]. A more explicit formula has overcome this bias [5], [6], reviewed below, although even that model makes the unrealistic assumption that the phage parameters do not vary.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

The Phenotype-Fitness Map in Experimental Evolution of Phages

2011

View full text Add to dashboard Cite

Evolutionary biologists commonly interpret adaptations of organisms by reference to a phenotype-fitness map, a model of how different states of a phenotype affect fitness. Notwithstanding the popularity of this approach, it remains difficult to directly test these mappings, both because the map often describes only a small subset of phenotypes contributing to total fitness and because direct measures of fitness are difficult to obtain and compare to the map. Both limitations can be overcome for bacterial viruses (phages) grown in the experimental condition of unlimited hosts. A complete accounting of fitness requires 3 easily measured phenotypes, and total fitness is also directly measurable for arbitrary genotypes. Yet despite the presumed transparency of this system, directly estimated fitnesses often differ from fitnesses calculated from the phenotype-fitness map. This study attempts to resolve these discrepancies, both by developing a more exact analytical phenotype-fitness map and by exploring the empirical foundations of direct fitness estimates. We derive an equation (the phenotype-fitness map) for exponential phage growth that allows an arbitrary distribution of lysis times and burst sizes. We also show that direct estimates of fitness are, in many cases, plausibly in error because the population has not attained stable age distribution and thus violates the model underlying the phenotype-fitness map. In conjunction with data provided here, the new understanding appears to resolve a discrepancy between the reported fitness of phage T7 and the substantially lower value calculated from its phenotype-fitness map.

show abstract

“…Under exponential growth, we can write and , with the solution to [5], [6]. The quantity is commonly referred to as the intrinsic growth rate.…”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

The Phenotype-Fitness Map in Experimental Evolution of Phages

2011

View full text Add to dashboard Cite

show abstract

The Impact of Population Bottlenecks on Microbial Adaptation

LeClair

Wahl

2017

J Stat Phys

View full text Add to dashboard Cite

Viral host-adaptation: insights from evolution experiments with phages

Hall

Harrison

Brockhurst

2013

Current Opinion in Virology

View full text Add to dashboard Cite

Phages, viral parasites of bacteria, share fundamental features of pathogenic animal and plant viruses and represent a highly tractable empirical model system to understand viral evolution and in particular viral host-adaptation. Phage adaptation to a particular host genotype often results in improved fitness by way of parallel evolution whereby independent lineages hit upon identical adaptive solutions. By contrast, phage adaptation to an evolving host population leads to the evolution of increasing host-range over time and correlated phenotypic and genetic divergence between populations. Phage host-range expansion frequently occurs by a process of stepwise evolution of multiple mutations, and host-shifts are often constrained by mutational availability, pleiotropic costs or ecological conditions.

show abstract

The impact of host-cell dynamics on the fixation probability for lytic viruses

Cited by 9 publications

References 48 publications

The Phenotype-Fitness Map in Experimental Evolution of Phages

The Phenotype-Fitness Map in Experimental Evolution of Phages

The Impact of Population Bottlenecks on Microbial Adaptation

Viral host-adaptation: insights from evolution experiments with phages

Contact Info

Product

Resources

About