Key result
Mathematical modeling of poliovirus replication predicts strand ratios that closely match observed experimental data.
Why the study?
A mathematical model is needed to describe and understand the dynamics and optimization of poliovirus replication within cells, including resource utilization effects.
Mathematical modeling suggests that the saturation of poliovirus replication is due to heavy resource use and that the virus has optimized its replication to match observed strand ratios.
Resource-limited model explains poliovirus saturation; leaves open in vivo validation before guiding antiviral timing.
We construct a mathematical model of the within-cell replication of poliovirus, a prototypic RNA virus, and use realistic parameter estimates to describe the increase of copy number of the viral genome. Our initial model is essentially an exponential growth model; we also consider modifications of this model to account for resource utilization. The saturation of viral replication dynamics observed in experimental systems can be explained in terms of heavy resource use by the virus. We then use our models to consider the conditions under which the growth of poliovirus is optimized. Intriguingly, if poliovirus has optimized its replication within cells, the predicted ratio of positive to negative strands is close to what is actually observed. We interpret our findings in terms of the evolution of life-history traits.
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Regoes et al. (2005) studied Poliovirus replication. Mathematical modeling was evaluated on Ratio of positive to negative strands. Mathematical modeling of within-cell poliovirus replication predicts a ratio of positive to negative strands that closely matches observed experimental data.