Linking Dynamical and Population Genetic Models of Persistent Viral Infection

Abstract

This article develops a theoretical framework to link dynamical and population genetic models of persistent viral infection. This linkage is useful because, while the dynamical and population genetic theories have developed independently, the biological processes they describe are completely interrelated. Parameters of the dynamical models are important determinants of evolutionary processes such as natural selection and genetic drift. We develop analytical methods, based on coupled differential equations and Markov chain theory, to predict the accumulation of genetic diversity within the viral population as a function of dynamical parameters. These methods are first applied to the standard model of viral dynamics and then generalized to consider the infection of multiple host cell types by the viral population. Each cell type is characterized by specific parameter values. Inclusion of multiple cell types increases the likelihood of persistent infection and can increase the amount of genetic diversity within the viral population. However, the overall rate of gene sequence evolution may actually be reduced.

Optimal Foraging by Bacteriophages through Host Avoidance

“…This property may apply to many viruses infecting multicellular hosts with respect to tissue tropisms-differences in the ability to infect various tissues within the body. Viruses within a host are likely to be selected to use some tissues and not others, and the nature of selection on tissue tropism may parallel those found here for phages (Kelly et al 2003;Orive et al 2005). For many viruses, such as HIV, extensive evolution occurs on a semireproducible basis within the body (Guindon et al 2004) and is important to both transmission and virulence (Zhang et al 1993).…”

Synonymous Substitution Rates Predict HIV Disease Progression as a Result of Underlying Replication Dynamics

“…The pool of resting memory CD4þ T cells that carry integrated proviral genomes represents a stable reservoir for latent HIV infection. Although they may produce only a fraction of circulating viruses, modelling studies predict that such latently infected cells can still considerably impact mean generation times and replication rates [24,25]. The contribution of this reservoir to the free-floating virus population will become more important as CTL killing of infected activated CD4þ T cells becomes more efficient.…”

Modeling Within-Host Evolution of HIV: Mutation, Competition and Strain Replacement

“…These few examples demonstrate rapid variation of phenotype in chronic viral infections. Given the long course of HIV progression, we see that the ecological and evolutionary timescales are not separable (Kelly et al, 2003).…”

“…Shankarappa et al (1999) tracked viral evolution of nine HIVinfected men over a 6-12 year period. The number of mutations was found to increase linearly with a slope of approximately 1 point mutation every 2 months (see Kelly et al, 2003 for further discussion). Further, since HIV is diploid, recombination can occur during reverse transcription.…”