Stochastic model of vesicular stomatitis virus replication reveals mutational effects on virion production

We present the first complete stochastic model of vesicular stomatitis virus (VSV) intracellular replication. Previous models developed to capture VSVs intracellular replication have either been ODE-based or have not represented the complete replicative cycle, limiting our ability to understand the impact of the stochastic nature of early cellular infections on virion production between cells and how these dynamics change in response to mutations. Our model accurately predicts changes in mean virion production in gene-shuffled VSV variants and can capture the distribution of the number of viruses produced. This model has allowed us to enhance our understanding of intercellular variability in virion production, which appears to be influenced by the duration of the early phase of infection, and variation between variants, arising from balancing the time the genome spends in the active state, the speed of incorporating new genomes into virions, and the production of viral components. Being a stochastic model, we can also assess other effects of mutations beyond just the mean number of virions produced, including the probability of aborted infections and the standard deviation of the number of virions produced. Our model provides a biologically interpretable framework for studying the stochastic nature of VSV replication, shedding light on the mechanisms underlying variation in virion production. In the future, this model could enable the design of more complex viral phenotypes when attenuating VSV, moving beyond solely considering the mean number of virions produced. Author SummaryThis study presents the first complete stochastic model of vesicular stomatitis virus (VSV) replication. Our model captures the dynamic process of VSVs replication within host cells, accounting for the stochastic nature of early cellular infections and how these dynamics change in response to mutations. By accurately predicting changes in mean virion production and the distribution of viruses in gene-shuffled VSV variants, our model enhances our understanding of viral replication and the variation we see in virion production. Importantly, our findings shed light on the mechanisms underlying the production of VSV virions, revealing the influence of factors such as the duration of the early infection phase and the interplay between the genomes ability to switch into an inactive state and viral protein production. We go beyond assessing the mean number of virions produced and examine other effects of mutations, including the probability of aborted infections and the variability in virion production. This stochastic model provides a valuable framework for studying the complex nature of viral replication, contributing to our understanding of single-cell viral dynamics and variability. Ultimately, this knowledge could pave the way for designing more effective strategies to attenuate VSV.