A computational model of inhibition of HIV-1 by interferon-alpha
Type 1 interferons such as interferon-alpha (IFN) inhibit replication of Human immunodeficiency virus (HIV-1) by upregulating the expression of genes that interfere with specific steps in the viral life cycle. This pathway thus represents a potential target for immune-based therapies that can alter the dynamics of host-virus interactions to benefit the host. To obtain a deeper mechanistic understanding of how IFN impacts spreading HIV-1 infection, we modeled the interaction of HIV-1 with CD4 T cells and IFN as a dynamical system. This model was then tested using experimental data from a cell culture model of spreading HIV-1 infection. We found that a model in which IFN induces reversible cellular states that block both early and late stages of HIV-1 infection, combined with a saturating rate of conversion to these states, was able to successfully fit the experimental dataset. Sensitivity analysis showed that the potency of inhibition by IFN was particularly dependent on specific network parameters and rate constants. This model will be useful for designing new therapies targeting the IFN network in HIV-1-infected individuals, as well as potentially serving as a template for understanding the interaction of IFN with other viruses.\n\nAuthor SummaryInterferon-alpha (IFN) is a key component of the host response to HIV-1, but the details of how IFN regulates infection are still incompletely understood. To provide a deeper understanding of the dynamics of how IFN inhibits HIV-1, we simulated the interaction of IFN and HIV-1 as a computational model and compared this model to an experimental dataset. We identify a model structure that is able to fit many key features of the data. Furthermore, we use the model to predict optimal strategies for targeting the IFN pathway therapeutically. We anticipate that this model will be useful for further analysis of HIV-IFN interactions and will help to guide new therapeutic strategies.