Stochastic failure of cell infection post viral entry: Implications for infection outcomes and antiviral therapy
A virus infection can be initiated with very few or even a single infectious virion, and as such can become extinct, i.e. stochastically fail to take hold or spread significantly. There are many ways that a fully competent infectious virion, having successfully entered a cell, can fail to cause a productive infection, i.e. one that yields infectious virus progeny. Though many discrete, stochastic mathematical models (DSMs) have been developed and used to estimate a virus infection's extinction probability, these typically neglect infection failure post viral entry. The DSM presented herein introduces parameter $\gamma\in(0,1]$ which corresponds to the probability that a virion's entry into a cell will result in a productive cell infection. We derive an expression for the likelihood of infection extinction in this new DSM, and find that prophylactic therapy with an antiviral acting to reduce $\gamma$ is best at increasing an infection's extinction probability, compared to antivirals acting on the rates of virus production or virus entry into cells. Using the DSM, we investigate the difference in the fraction of cells consumed by so-called extinct versus established virus infections, and find that this distinction becomes biologically meaningless as the probability of extinction approaches 100%. We show that infections wherein virus is release by an infected cell as a single burst, rather than at a constant rate over the cell's infectious lifespan, has the same probability of infection extinction, despite previous claims to this effect [Pearson 2011, doi:10.1371/journal.pcbi.1001058]. Instead, extending previous work by others [Yan 2016, doi:10.1007/s00285-015-0961-5], we show how the assumed distribution for the stochastic virus burst size, affects the extinction probability and associated critical antiviral efficacy.
Code (1)
Similar Papers 제목 키워드 기반
Comparing antiviral strategies against COVID-19 via multiscale within-host modelling
Within-host models of COVID-19 infection dynamics enable the merits of different forms of antiviral therapy to be assessed in individual patients. A stochastic agent-based model of COVID-19 intracellular dynamics is intr…
Inheritance of intracellular viral RNA in a multiscale model of hepatitis C infection
Multiscale mathematical models of hepatitis C infection have been instrumental in our understanding of direct acting antivirals. These models include the mechanisms driving intracellular viral production and explicitly m…
Rate-Equation Modelling and Ensemble Approach to Extraction of Parameters for Viral Infection-Induced Cell Apoptosis and Necrosis
We develop a theoretical approach that uses physiochemical kinetics modelling to describe cell population dynamics upon progression of viral infection in cell culture, which results in cell apoptosis (programmed cell dea…
Cultural Vocal Bursts Intensity PredictionEpisome partitioning and symmetric cell divisions: quantifying the role of random events in the persistence of HPV infections
Human Papillomaviruses (HPV) are one of the most prevalent sexually transmitted infections (STI) and the most oncogenic viruses known to humans. The vast majority of HPV infections clear in less than 3 years, but the und…
Narrow escape to small windows on a small ball modeling the viral entry into the cell nucleus
A certain class of viruses replicates inside a cell if they can enter the nucleus through one of many small target pores, before being permanently trapped or degraded. We adopt for viral motion a switching stochastic pro…