Journal of virology 2017 11 08() pii 10.1128/JVI.01667-17
HIV viremia rebounds rapidly after treatment interruption, and a variety of strategies are being explored to reduce or control viral reactivation post-treatment. This viral rebound arises from reactivation of individual latently infected cells, which spread during ongoing rounds of productive infection. The level of virus produced by the initial individual reactivating cells is not known, although it may have major implications for the ability of different immune interventions to control viral rebound. Here we use data from both HIV and SIV treatment interruption studies to estimate the initial viral load post-interruption and thereby the initial individual reactivation event. Using a barcoded virus (SIVmac239M) to track reactivation from individual latent cells, we use the observed viral growth rates and frequency of reactivation to model the dynamics of reactivation to estimate that a single reactivated latent cell can produce an average viral load equivalent to ≈0.1-0.5 vRNA copies/ml. Modelling of treatment interruption in HIV suggests an initial viral load equivalent of ≈0.6-1 vRNA copies/ml. These low viral loads immediately following latent cell reactivation provide a window of opportunity for viral control by host immunity, before further replication allows viral spread. This work shows initial levels of viral production that must be controlled in order to successfully suppress HIV reactivation following treatment interruption.Importance:Current treatment for HIV is able to suppress viral replication and prevent disease progression. However, treatment cannot eradicate infection, because the virus lies silent within latently infected cells. If treatment is stopped, the virus usually rebounds above the level of detection within a few weeks. There are a number of approaches being tested aimed at either eradicating latently infected cells, or controlling the virus if it returns.Studying both the small pool of latently infected cells and the early events during viral reactivation are difficult, because these involve very small levels of virus that are difficult to measure directly. Here, we combine experimental data and mathematical modelling to understand the very early events during viral reactivation from latency in both HIV infection of humans and SIV infection of monkeys. We find that the initial levels of virus are low, which may help in designing therapies to control early viral reactivation.