Optimizing within-host viral fitness: infected cell lifespan and virion production rate

Abstract

We explore how an infected cell's virion production rate can affect the relative fitness of a virus within a host. We perform an invasion analysis, based on an age-structured model of viral dynamics, to derive the within-host relative viral fitness. We find that for chronic infections, in the absence of trade-offs between viral life history stages, natural selection favors viral strains whose virion production rate maximizes viral burst size. We then show how various life history trade-offs such as that between virion production and immune system recognition and clearance of virally infected cells can lead to natural selection favoring production rates lower than the one that maximizes burst size. Our findings suggest that HIV replication rates should vary between cells with different life spans, as has been suggested by recent observation. Published by Elsevier Ltd.

Pathogen responses to host immunity: the impact of time delays and memory on the evolution of virulence

“…Such a suggestion has previously been made for viruses replicating within host cells (Almogy et al 2002;Coombs et al 2003;Gilchrist et al 2004). Infected host cells are probed by active T cells with non-specific T-cell receptors (TCRs) and the number of antigens on the surface of the cell that are recognized by these TCRs is directly proportional to the replication rate of the virus within that cell.…”

“…In an epidemiological context the fitness of the pathogen may be defined by its basic reproductive ratio, R 0 , which is measured as the number of number of secondary cases infected by a single infected host in a completely susceptible population (Anderson & May 1992). Therefore, the overall infectiousness of a given host will depend on the total number of infectious particles produced by that host over the lifetime of the infection, and the transmissibility of the pathogen at any moment in time will be directly proportional to its abundance within the host Antia & Lipsitch 1997;Ganusov et al 2002;Gilchrist et al 2004). Therefore, since infection may be chronic, the appropriate measure of the pathogen's fitness is its 'lifetime' reproductive success, i.e.…”

“…At present we have no a priori information about the shape of the trade-off between replication rate (r) and stimulation of the primary immune response (l 0 ). Therefore, we assume there is a monotonic increasing relationship between pathogen replication and immune stimulation, such as may occur through cells infected with high reproducing pathogens presenting more targets for the cell-directed immune response (Almogy et al 2002;Gilchrist et al 2004). In the simplest scenario, there might be a linear relationship between r and l 0 although other functional forms may be possible, such as an accelerating relationship due to increased rates of stimulation, or a decelerating relationship due to immune exhaustion.…”

“…Once again, these functional relationships are placed within the full dynamic models described previously and the cumulative pathogen load over the duration of the infection is calculated as the measurement of pathogen fitness. Regardless of whether there is immune memory or not, a concave relationship between pathogen virulence and immune stimulation tends to result in pathogen fitness being maximized at the highest values of r ( figure 3a,b), suggesting that a pathogen should evolve maximal virulence (r à /N), irrespective of the strength of the immune response (Gilchrist et al 2004). Such a concave trade-off implies that the pathogen experiences diminishing costs, in terms of increased stimulation of the immune system, and so it will always benefit from a further increase in replication rate.…”

Reassessing the Human Immunodeficiency Virus Type 1 Life Cycle through Age-Structured Modeling: Life Span of Infected Cells, Viral Generation Time, and Basic Reproductive Number,R0

“…Age-structured models of virus dynamics based on partial differential equations have received attention recently (5,11,14,24). In these systems, classes of infected cells are structured according to the time that has passed since the cells were infected with a viral particle.…”