Transcriptome profiles of latently- and reactivated HIV-1 infected primary CD4+ T cells: A pooled data-analysis

Abstract

The main obstacle to cure HIV-1 is the latent reservoir. Antiretroviral therapy effectively controls viral replication, however, it does not eradicate the latent reservoir. Latent CD4⁺ T cells are extremely rare in HIV-1 infected patients, making primary CD4⁺ T cell models of HIV-1 latency key to understanding latency and thus finding a cure. In recent years several primary CD4⁺ T cell models of HIV-1 latency were developed to study the underlying mechanism of establishing, maintaining and reversing HIV-1 latency. In the search of biomarkers, primary CD4⁺ T cell models of HIV-1 latency were used for bulk and single-cell transcriptomics. A wealth of information was generated from transcriptome analyses of different primary CD4⁺ T cell models of HIV-1 latency using latently- and reactivated HIV-1 infected primary CD4⁺ T cells. Here, we performed a pooled data-analysis comparing the transcriptome profiles of latently- and reactivated HIV-1 infected cells of 5 in vitro primary CD4⁺ T cell models of HIV-1 latency and 2 ex vivo studies of reactivated HIV-1 infected primary CD4⁺ T cells from HIV-1 infected individuals. Identifying genes that are differentially expressed between latently- and reactivated HIV-1 infected primary CD4⁺ T cells could be a more successful strategy to better understand and characterize HIV-1 latency and reactivation. We observed that natural ligands and coreceptors were predominantly downregulated in latently HIV-1 infected primary CD4⁺ T cells, whereas genes associated with apoptosis, cell cycle and HLA class II were upregulated in reactivated HIV-1 infected primary CD4⁺ T cells. In addition, we observed 5 differentially expressed genes that co-occurred in latently- and reactivated HIV-1 infected primary CD4⁺ T cells, one of which, MSRB2, was found to be differentially expressed between latently- and reactivated HIV-1 infected cells. Investigation of primary CD4⁺ T cell models of HIV-1 latency that mimic the in vivo state remains essential for the study of HIV-1 latency and thus providing the opportunity to compare the transcriptome profile of latently- and reactivated HIV-1 infected cells to gain insights into differentially expressed genes, which might contribute to HIV-1 latency.

Keywords: HIV-1 latency reversal agents; latently HIV-1 infected primary CD4+ T cells; pooled data-analysis; pooled data-analysis differentially expressed genes (pdaDEGs); primary CD4+ T cell models of HIV-1 latency; reactivated HIV-1 infected primary CD4+ T cells; transcriptome profile.