Project description:Background: The cellular reservoir of latent HIV infection remains the main barrier to cure this virus. Elimination of this reservoir would be possible, if molecular identity of latently infected cells were fully elucidated. Biomarkers proposed previously were able to capture only a relatively small fraction of all reservoir cells. In the present study, we set out to conduct comprehensive molecular profiling, at the protein and RNA levels, of CD4+ T cells latently infected with HIV in vitro, using liquid chromatography-mass spectrometry (LC-MS) and RNA sequencing (RNA-Seq), respectively. Protein-based methods such as quantitative proteomic profiling using LC-MS may be more beneficial due to direct transferability of results to antibody-based approaches to capture latently infected cells. Integrated analysis of proteomic and transcriptomic data adds a level of validation and increases confidence in identified biomarkers. Flow cytometry and integrated HIV DNA assay were further used to enrich for latently infected cells with antibodies against selected biomarker proteins. Results: Using quantitative proteomics, we identified a total of 10,886 proteins (peptide level FDR < 0.05), of which 673 were up- and 780 down-regulated in latently infected compared to mock-infected cells in vitro (p < 0.05). Among these proteins, 21 were dysregulated at the RNA level in the same direction. Pathway analysis identified p53, mTOR, Wnt and NOTCH signaling, demonstrating that our in vitro model reflects known mechanisms of latency establishment and maintenance. Comparison of identified proteins with other proteomics studies revealed that identified molecular signatures of latency depend on technology and cell types used; however, a subset of proteins were identified both in the present, and at least one other study. Antibodies against selected protein markers, CEACAM1 and PLXNB2, could enrich for latently infected cells from mixed cell population 3-10 fold (5.8 fold average, p < 0.001). Conclusion: Two new molecules, CEACAM1 and PLXNB2, were identified as biomarkers for HIV latency. However, the level of enrichment for latently infected cells compared to biomarkers proposed previously was not improved. These results are consistent with the idea that each proposed biomarker defines only a subset of latently infected cells, and that a combined biomarker will be required to capture or target the latent HIV reservoir represented by different cell types.

Project description:Suppressive HAART does not eradicate HIV-1 and viral DNA persists as a stably integrated form in the absence of viral particle production. As a consequence, latent reservoirs are refractory to antiretroviral drugs and invisible to immune surveillance. The largest latent reservoir consists of resting memory CD4+ T cells. These cells can resume viral infection when activated through antigen recognition, causing bursts of viremia (blips). Current therapies targeting latent HIV-1 have focused primarily on the M-bM-^@M-^\shock and killM-bM-^@M-^] approach, which employs M-bM-^@M-^\anti-latencyM-bM-^@M-^] drugs M-bM-^@M-^S most notably histone deacetylase (HDAC) inhibitors M-bM-^@M-^S to reactivate and flush latent provirus from its cellular reservoirs in the absence of global T cell activation. This approach is predicated on the notions that viral reactivation will lead to the demise of the infected cell, and that HAART will prevent spreading of the infection. On the contrary, recent evidence indicates that latently infected CD4+ T cells of HIV-1 patients on HAART survive in vitro viral reactivation with the HDAC inhibitor, SAHA, even when co-cultured with autologous CD8+ cytotoxic T lymphocytes (CTL). Moreover, it remains to be addressed the impact of anti-latency drugs on viral reservoirs undergoing low-level ongoing replication, inherently more resistant to the cytopathic effects of HIV-1 and residing in anatomical sites hard to reach for some antiretroviral drugs (e.g. macrophages). As a consequence, there is a need to develop alternative therapeutic approaches aimed at eliminating or decreasing the latent reservoir. Progress in that direction has been hindered by the lack of biomarkers uniquely or differentially expressed on latently infected compared to their uninfected counterparts. To gain insight into the cellular mechanisms that take place in the context of latency, and with the goal of identifying distinctive markers that distinguish latently infected CD4+ T cells, we have used an in vitro model developed in our laboratory to study the expression profile of latently infected CD4+ T cells by microarray analysis. We have used a culture system, previously established in our laboratory, to generate and isolate quiescent latently infected CD4+ T cells in vitro. In this in vitro HIV-1 latency model, CD4+ T cells are activated, infected with full length, replication competent HIV-1, and then returned to quiescence in the presence of IL-7, yielding a culture of quiescent latently infected and uninfected cells. We showed that HIV-1 p24gag expressed during viral replication persists in the cytoplasm of latently infected cells for several days before being degraded. Therefore, we exploited the presence of cytoplasmic p24gag to sort latently infected from uninfected cells by FACS from the same initial cell culture. Total RNA was isolated from sorted latently infected and uninfected cells generated from CD4+ T cells of four different donors. Paired RNA samples from infected and uninfected cells were labeled with Cy3 and Cy5 to allow dual-color competitive hybridization. Moreover, to control for the dye bias in our experiments, we implemented a dye swap protocol (reciprocal labeling) for paired RNA samples from 2 donors. Samples were analyzed by dual-color competitive hybridization on the Agilent whole human genome microarrays (41,000 unique probes). This is the first comparative genomic profiling of primary latently infected resting memory CD4+ T cells versus their uninfected counterparts sorted from the same culture. Microarray analyses performed in this study revealed profound differences between latently infected and uninfected cells. Of relevance are genes involved, not only in previously described pathways related with transcriptional and post-transcriptional regulation, but affecting proliferation, survival, cell cycle progression and cell metabolism. This could explain why latently infected cells have been resistant to reactivation with current anti-latency approaches. Thus, targeting of more downstream steps, such as the ones identified in this study, may be able to enhance viral flushing from refractory latent reservoirs. In addition, we identified a panel of surface makers differentially expressed in latently infected cells, which seem worth investigating for their potential use as biomarkers. Indeed, they might allow the enrichment of this latent reservoir for molecular in depth studies, for monitoring the size of the latent reservoir in the clinical setting, as well as for the development of new therapeutic strategies aimed at eradicating this reservoir.

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