Defining the causes and consequences of viral rebound

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Treatment of HIV-infected individuals with antiretroviral therapy (ART) can often suppress plasma viral loads to undetectable levels. However HIV persists during therapy and if ART is stopped then viral loads rapidly rebound allowing disease progression to continue. While it is clear that reservoirs of latently-infected CD4+ T cells and potentially other rare infected cells can serve as a source of replication-competent virus to rekindle infection, many questions remain about how and why rebound occurs if ART is discontinued. Particular areas where more study is needed include determining what can initiate the rebound process, how the timing and magnitude of rebound relates to the size and characteristics of the underlying latent reservoir, and defining what the consequences of allowing rebound to occur are. The overall goal of this PO1 application is to develop a more complete understanding of HIV rebound by using the bone marrow-liver-thymus (BLT) mouse, a highly relevant humanized mouse model for studying HIV in vivo. This model supports multi-lineage human immune reconstitution in many tissues within the mouse and represents one of the most advanced small animal models available for investigating HIV persistence and pathogenesis. We and others have shown that the BLT mouse model can be efficiently infected with HIV and forms authentic post-integration latency in resting CD4+ T cells. Viral loads can be suppressed using clinically relevant ART drugs, and if ART is stopped then viral loads quickly rebound. We have further advanced this model by utilizing a phenotypically neutral, genetically diverse barcoded HIV swarm to perform the infections. This allows a latent reservoir to be formed with diverse genetically tagged viruses. Rebound can then be tracked both through monitoring of viral loads to test the timing and magnitude of virus re-emergence in the plasma or tissues, and deep-sequencing of the rebounding virus to quantify the number of individual barcoded variants contributing to the rebound. This combined approach will provide an unprecedented view of HIV reservoir formation and viral rebound. In project 1 we will use this model to determine the contribution of Pre- ART infection time to spontaneous viral rebound (Aim 1), test whether common physiologic/pharmacologic stimuli alter the frequency of rebound (Aim 2), and quantify the effects of structured treatment interruption (STI) on the size and diversity of the latent HIV reservoir (Aim 3). Together, these studies will test key, clinically relevant parameters to determine how they affect rebound of HIV upon stopping ART, and will assess the consequences of allowing rebound to occur. This will provide new insights into the mechanisms contributing to HIV rebound.