Abstract
The use of latency reversing agents (LRAs) is currently a promising approach to eliminate latent reservoirs of HIV-1. However, this strategy has not been successful in vivo. It has been proposed that cellular post-transcriptional mechanisms are implicated in the underperformance of LRAs, but it is not clear whether proviral regulatory elements like viral non-coding RNAs (vncRNAs) are also implicated. In order to visualize the complexity of the HIV-1 gene expression, we used experimental data to construct a gene regulatory network (GRN) of latent proviruses in resting CD4+ T cells. We then analyzed the dynamics of this GRN using Boolean and continuous mathematical models. Our simulations predict that vncRNAs are able to counteract the activity of LRAs, which may explain the failure of these compounds to reactivate latent reservoirs of HIV-1. Moreover, our results also predict that using inhibitors of histone methyltransferases, such as chaetocin, together with releasers of the positive transcription elongation factor (P-TEFb), like JQ1, may increase proviral reactivation despite self-repressive effects of vncRNAs.
Highlights
Combined antiretroviral therapy is currently the most effective approach to control the chronic infection of HIV-1
The Boolean model shows that the activation attractors can be reached with or without cellular stimulation of histone acetyltransferases (HATs) and Tumor Necrosis Factor (TNF) (Table 3), which agrees with previous observations that demonstrate the persistence of provirus expression in resting CD4+ T-cells (Razooky et al, 2015)
Several efforts to purge viral reservoirs have been performed using latency reversing agents (LRAs), none of them were effective in vivo (Bullen et al, 2014)
Summary
Combined antiretroviral therapy (cART) is currently the most effective approach to control the chronic infection of HIV-1. CART does not eliminate the virus even with treatment intensification (Dinoso et al, 2009) This occurs because HIV-1 is able to form long-lived reservoirs by remaining latent within resting memory CD4+ T-cells (Siliciano et al, 2003; Siliciano and Greene, 2011; Cohn et al, 2015). It has been proposed the use of LRAs in combination with cART to eliminate latently infected cells. Stochastic modeling of latently infected cells indicated that the clinical underperformance of LRAs is due to their inability to minimize the size of the viral reservoirs (Hill et al, 2014). This study suggested that LRAs must reduce the size of viral reservoirs
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