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Resting memory CD4+ T cells are the largest reservoir of persistent infection in HIV-1-positive subjects. They harbor dormant, stably integrated virus despite suppressive antiretroviral therapy, posing an obstacle to a cure. Surface markers that identify latently infected cells remain unknown. Microarray analyses comparing resting latently infected and uninfected CD4+ T cells generated in vitro showed profound differences in the expression of gene programs related to transcriptional and posttranscriptional regulation, cell proliferation, survival, cycle progression, and basic metabolism, suggesting that multiple biochemical and metabolic blocks contribute to preventing viral production in latently infected cells. We identified 33 transcripts encoding cell surface markers that are differentially expressed between latently infected and uninfected cells. Quantitative reverse transcriptase PCR (RT-QPCR) and flow cytometry analyses confirmed that the surface marker CD2 was expressed at higher levels on latently infected cells. To validate this result in vivo, we sorted resting memory CD4+ T cells expressing high and low surface levels of CD2 from six HIV-1-infected subjects successfully treated with antiretroviral drugs for at least 3 years. Resting memory CD4+ CD2high T cells from all subjects harbored higher HIV-1 DNA copy numbers than all other CD4+ T cell subsets. Moreover, after ex vivo viral reactivation, robust viral RNA production was detected only from resting memory CD4+ CD2high T cells but not from other cell subsets. Altogether, these results show that a high CD2 expression level is a hallmark of latently infected resting memory CD4+ T cells in vivo.
Current antiretroviral therapy (ART) is ineffective at eradicating human immunodeficiency virus type 1 (HIV-1) infection. Low-level viremia (<50 copies/ml) is often detected with ultrasensitive assays in patients on suppressive ART (1); occasional bursts of viral replication (“blips”) occur (2, 3), and eventually, viremia rebounds after ART interruption in all but exceptional cases (4).
HIV-1 establishes persistent infection in a number of cell types at different anatomical compartments via different mechanisms (reviewed in references 5, 6, 7, 8, and 9). Latent reservoirs harbor stably integrated HIV-1 DNA in the absence of viral particle production, are refractory to antiretroviral drugs, and are invisible to immune surveillance. The largest latent reservoir consists of resting memory CD4+ T cells, with a major contribution from central and transitional memory CD4+ T cells (10).
Numerous factors, such as the quiescent nature of resting memory CD4+ T cells, the site of viral integration, and many others, contribute to the establishment and maintenance of HIV-1 latency. Some of these mechanisms are currently being exploited to flush the latent provirus from its reservoirs in the absence of T cell activation (5, 11–13) by combining latency-reversing agents (LRAs) that reactivate latent proviruses, causing the demise of the infected cell, with highly active ART (HAART) intensification, which prevents infection of new target cells. While this approach presents potential pitfalls (the fraction of replication-competent latent proviruses that can be reactivated with LRAs [A. Cillo, M. Sobolewski, J. Coffin, and J. Mellors, presented at the 20th Conference on Retroviruses and Opportunistic Infections, Atlanta, GA, 2013; Y. C. Ho, L. Shan, J. Wang, N. Hosmane, J. Blankson, and R. Siliciano, presented at the 20th Conference on Retroviruses and Opportunistic Infections, Atlanta, GA, 2013], the fraction of latently infected CD4+ T cells that survives after viral reactivation , incomplete efficacy of HAART in sanctuary sites [15–17], and the impact of LRAs on reservoirs other than CD4+ T cells and on other latent viruses [18, 19]), reactivation of latent reservoirs merits further investigation. Nevertheless, there is also a need to develop alternative therapeutic approaches to eliminate or reduce the number of latently infected cells. The identification of cell surface biomarkers would provide an impetus in that direction. Indeed, uniquely or differentially expressed surface molecules could be used to isolate a partially purified subpopulation of latently infected cells for further characterization. Moreover, they could provide new therapeutic targets for the elimination of latently infected cells even in the absence of viral reactivation. To gain insight into the cellular mechanisms contributing to viral 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 (20) to study the expression profile of latently infected CD4+ T cells by microarray analysis. The results that we report in this study point to new mechanisms for the establishment and maintenance of latency in CD4+ T cells that could be exploited for exploring novel therapies aimed at targeting this reservoir. In addition, this survey identified a panel of genes encoding cell surface molecules that were differentially expressed in latently infected versus uninfected cells, which may have diagnostic as well as therapeutic implications. Among the markers identified in our study, CD2 was particularly interesting because of its know therapeutic applications (21–31). Sorting of resting memory CD4+ T cells expressing high levels of the CD2 receptor from HIV-1-infected subjects on suppressive ART allowed a significant enrichment of latently infected cells able to produce robust levels of viral particles following ex vivo reactivation. Therefore, the studies presented below demonstrate that high levels of CD2 expression identify latently infected resting memory CD4+ T cells in virally suppressed HIV-1-infected subjects.
All of the subjects provided their informed written consent to participate in the study. Peripheral blood mononuclear cells (PBMCs) of 4 HIV-1-negative donors (donors 3, 111, 112, and 113) were obtained with signed informed consent, after approval of the Institutional Review Board of the University of Maryland, Baltimore. PBMCs of 6 HIV-1-seropositive subjects (subjects ST045, ST101, ST102, ST104, ST109, and ST113) with undetectable viremia on suppressive ART for at least 3 years were obtained with signed informed consent and approved by the Institutional Review Board at Martin Memorial Health Systems (Stuart, FL).
The model for generation of latently infected CD4+ T cells in vitro was described previously (20), except for the modifications described in the supplemental material.
Procedures for sorting of in vitro-generated latently infected cells, total RNA isolation, and microarray analysis are described in the supplemental material and were described previously (32).
Total RNA was isolated as described above, and cDNA was generated by using the high-capacity RNA-to-cDNA kit (Applied Biosystems). Quantitative real-time PCRs (QPCRs) were performed in triplicate on a Bio-Rad IQ5 instrument by using TaqMan gene expression assays (Applied Biosystems) (see Table S4 in the supplemental material), according to the manufacturer's instructions. Expression levels were compared to the levels of MED19, since it did not show differential expression in the microarray.
Surface expression of CD2, CD6, and CD130 was analyzed on CD4+ T cell cultures latently infected with HIV-1 carrying a green fluorescent protein (GFP) reporter gene in place of Nef (pNL4-3-GFP). Further details are available in the supplemental material.
We obtained PBMCs from 5 HIV-1-seropositive subjects with undetectable viremia who were on suppressive ART for at least 3 years (see Table S3 in the supplemental material). CD4+ T cells were enriched from PBMCs by negative selection. Quantification of total HIV-1 DNA was performed with 300,000 cells of each subset by using ultrasensitive HIV-1 DNA PCR assays (sensitivity, 1 copy), as previously described (10). For viral reactivation, naive CD4+ T cells and resting memory CD4+ T cells expressing high or low levels of CD2 (5 × 105 cells per subset) were stimulated with anti-CD3/CD28 Dynabeads for 6 days in the presence of antiretrovirals (180 nM zidovudine [AZT], 100 nM efavirenz [EFV], and 200 nM raltegravir [RALT]) to prevent new rounds of infection. We then used ultrasensitive reverse transcriptase PCR (RT-PCR) (detection limit, 1 HIV-1 RNA copy) to quantify HIV-1 RNA copies in supernatants. Finally, the percentages of naive, central memory, transitional memory, effector memory, and terminally differentiated cells were determined by flow cytometry by gating on total CD4+ T cells and on the subset of CD4+ T cells expressing high and low levels of CD2. Further details for all these procedures are provided in the supplemental material.
Complete results from this comparative host gene expression profiling analysis can be found at the public Gene Expression Omnibus (GEO) database under accession number GSE40550.
Latently infected cells were generated in vitro from CD4+ T cells of 4 HIV-1-negative donors (donors 3, 111, 112, and 113) according to our previously described model (20), with the modifications shown in Fig. S1A in the supplemental material and described in Materials and Methods. After infection and expansion, cells were allowed to rest for 1 week, which allowed them to achieve cell quiescence, as shown by the lack of the activation markers HLA-DR, CD69, and Ki67 (see Fig. S1B in the supplemental material).
We have previously shown that the HIV-1 p24gag antigen synthesized during productive infection persists in the cytoplasm of infected cells for several days and slowly declines during the latency phase (20). Detection of p24gag in the cytoplasm of latently infected cells does not reflect new rounds of viral infection or de novo synthesis, in that the addition of AZT or cycloheximide does not affect the slope of p24gag decay (20). Moreover, RT activity was detectable in culture supernatants of cells from two different donors at the peak of infection, but it was undetectable after 1 week of rest, indicating that by that time, active viral production had ceased (see Fig. S1C in the supplemental material). Therefore, we exploited cytoplasmic p24gag to sort latently infected from uninfected cells from the same initial cell culture by flow cytometry, as we described recently (32). As cytoplasmic p24gag declines over time, the frequency of p24gag-negative latently infected cells sorting with, and thus contaminating, the truly HIV-1-negative population grows as a function of the length of the resting phase. We circumvented this potential pitfall by employing a resting phase of 1 week, since this was shown to be sufficient to obtain quiescent, latently infected cells (see above).
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 (20). 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, as described previously (20), in Materials and Methods, and in Fig. 1A. RNA quality diagnostics did not reveal any artifacts (20).
Complete results from this comparative host gene expression profiling analysis can be found in Table S1 in the supplemental material and at the public GEO database (accession number GSE40550). A total of 533 genes were upregulated in latently infected cells, while 342 genes were downregulated (false discovery rate [FDR], <5%). Of particular interest are a panel of genes downmodulated in latently infected cells that could contribute to halt HIV-1 transcription due to their involvement in cellular metabolism, chromosome organization, gene expression, cell activation, proliferation, survival, and cell cycle progression (Fig. 1B).
Some of the factors known to have a role in HIV-1 infection and latency were also deregulated in latently infected cells. Thus, the mRNA of the chromatin-remodeling enzyme responsible for transcription repression, histone deacetylase 1 (HDAC1) (33), and the natural antiviral factor apolipoprotein B mRNA-editing, enzyme-catalytic, polypeptide-like 3G (APOBEC3G) (34) were up- and downregulated, respectively, in latently infected compared to uninfected cells. We also found reduced expression levels of a number of transcripts that might potentially impact entry into or maintenance of HIV-1 latency: mRNAs for several eukaryotic initiation-of-translation factors (EIFs), 1AX, 2A, 4A1, 4B, 4G2, and 5A (required for Rev function ); CCND2 and CCND3 (involved in G1 progression and G1/S transition in human T cells ); and MYST4 (a histone methyltransferase involved in chromatin condensation ) were expressed at lower levels in latently infected than in uninfected cells.
Finally, a number of transcripts involved in various steps of the virus life cycle were also found to be differentially modulated when latently infected cells were compared to uninfected cells from the same culture. For instance, we found that the transcripts of the HIV-1-suppressive factors CCL4/MIP-1β and CCL5/RANTES were downregulated in latently infected cells. However, mRNAs of the HIV-1 receptor CD4 and coreceptor CXCR4 genes were upregulated in these cells. Transcripts of factors involved in RNA splicing (PRPF4B, SFRS16, and SFRS17A) were upregulated in latently infected cells, whereas factors mediating nuclear import of Rev (IPO5/RANBP5  and IPO7 ) and Tat (NUP93 and NUP153 ) were downmodulated in these cells.
The results of our microarray analysis also revealed deregulated expression of many genes in Gene Ontology (GO) categories such as nucleic acid, protein, and lipid metabolic processes; RNA processing; posttranscriptional regulation; posttranslational protein modifications; protein localization; and nucleocytoplasmic transport. Moreover, genes involved in vesicle transport, endocytosis, and membrane invagination were also differently regulated in latently infected cells. Data for additional enrichment analyses, including the updated analysis of functional annotation (AFA), can be found at the GEO database (accession number GSE40550).
In relation to proliferation or survival, both pro- and antiapoptotic factors were found to be up- and downmodulated in latently infected cells. Thus, based on these results, it is difficult to ascertain whether latent infection confers a cell survival benefit.
To validate our data set, we performed real-time RT-PCR with total RNA from latently infected and uninfected cells from 2 donors for 15 genes identified in the microarray analysis. The results obtained by quantitative RT-PCR (RT-QPCR) for all the genes were in accordance with the differential expression found by microarray analyses: 5 out of 5 genes were upregulated (Fig. 2A), and 10 out of 10 were downregulated (Fig. 2B).
We found that 89 transcripts for membrane-associated proteins were differentially expressed (56 up- and 33 downregulated) in latently infected compared to uninfected CD4+ T cells generated in vitro (see Table S2 in the supplemental material). Among these 89 transcripts, 33 encode cell surface markers belonging to the cluster-of-differentiation (CD) protocol, including 20 genes upregulated and 13 downregulated in latently infected CD4+ T cells (Table 1). We used RT-QPCR to validate differential expression of 10 upregulated and 3 downregulated transcripts with total RNA from cells generated with our in vitro latency model. As shown in Fig. 3A and andB,B, all 13 genes (except CD6 with RNA from donor 112) were validated in samples from two donors. Next, we decided to confirm whether some of these receptors were also deregulated at the protein level by flow cytometry. We focused on surface molecules that were upregulated, since they may have more therapeutic and diagnostic potential, and we selected three receptors expressed at high (CD2), intermediate (CD6), and low (CD130/IL6RB) levels on CD4+ T cells. We used our in vitro model to generate cultures latently infected with full-length, replication-competent HIV-1 expressing GFP, which facilitates flow cytometry analysis. As GFP, like HIV-1 p24gag, persists in the cytoplasm of infected cells for several days during the latency phase (see Fig. S2 in the supplemental material), we measured the expression levels of these three markers on latently infected and uninfected cells by gating on the GFP-positive (GFP+) and GFP-negative (GFP−) fractions, respectively. The results were validated by using latently infected cultures generated using our in vitro model of HIV-1 latency. As shown in Fig. 3C, surface expression levels of all three receptors were higher on latently infected than on uninfected cells.
Next, we sought to determine whether the cell surface markers identified through the microarray analysis described above could be used to identify latently infected cells in vivo. As the differential expression level of the CD2 receptor between latently infected and uninfected cells in vitro was higher than those of CD6 and CD130 (Fig. 3C), we chose to perform our studies with clinical samples using CD2 first. Thus, we obtained a large number of PBMCs (5 × 109 to 15 × 109 cells) through leukapheresis from six HIV-1-seropositive subjects with undetectable viremia and who were on suppressive ART for at least 3 years (see Table S3 in the supplemental material). We enriched CD4+ T cells by negative selection, and we stained these cells with fluorochrome-conjugated antibodies to CD3, CD4, HLA-DR, CD45RA, and CD2, as described in Materials and Methods. After gating on the live-cell population, we sorted naive CD4+ T cells (CD3+ CD4+ CD45RA+), activated memory CD4+ T cells (CD3+ CD4+ HLA-DR+ CD45RA−), and resting memory CD4+ T cells (CD3+ CD4+ HLA-DR− CD45RA−) that fell within the 20th highest and lowest percentiles of CD2 fluorescence (CD2high and CD2low, respectively) (Fig. 4A). First, we measured the copies of HIV-1 DNA in the 4 sorted cell subsets, using CD4+ T cells as controls. We found that resting memory CD4+ CD2high T cells from all six subjects harbored higher HIV-1 DNA copy numbers than the other cell subsets (Fig. 4B). The median of the enrichment of HIV-1 DNA copies in the CD4+ CD2high subset compared to total CD4+ T cells was 5.7-fold (range, 3- to 10.8-fold; P = 0.013) (Fig. 4B).
Next, we measured viral RNA production following in vitro reactivation of resting memory CD4+ CD2high, resting memory CD4+ CD2low, and naive CD3+ CD4+ CD45RA+ T cells. Sorted cells from 3 of the 6 subjects analyzed as described above (subjects ST101, ST104, and ST113) were stimulated with anti-CD3/CD28 Dynabeads for 6 days in the presence of antiretrovirals to prevent new rounds of infection. We then used ultrasensitive RT-PCR to quantify HIV-1 RNA copies in culture supernatants after pelleting of viral particles by ultracentrifugation. We detected robust levels of viral RNA production in the culture medium of resting memory CD4+ CD2high T cells, whereas little or no viral particles were detected in the supernatants of resting memory CD4+ CD2low and naive CD4+ T cells (Fig. 4C). Thus, these results indicate that a high expression level of the surface receptor CD2 identifies resting memory CD4+ T cells harboring replication-competent HIV-1 in peripheral blood of virally suppressed patients.
Finally, we used flow cytometry to determine the frequencies of all major cell differentiation subsets (naive, central memory, transitional memory, effector memory, and terminally differentiated) within the total CD4+ T cell, CD4+ CD2low, and CD4+ CD2high populations of 5 out of 6 subjects as described above. As shown in Fig. 5, the CD4+ CD2high population was markedly enriched in cells displaying a memory phenotype. Thus, these results are in line with a previous study showing that integrated HIV-1 is found primarily within central (CD45RA− CCR7+ CD27+), transitional (CD45RA− CCR7− CD27+), and effector (CD45RA− CCR7− CD27−) memory CD4+ T cells (10).
Several limitations hinder the study of HIV-1 latency with clinical samples, including the lack of distinctive surface markers for latently infected cells, the low frequency of latently infected resting memory CD4+ T cells in ART patients, and the fact that clinical samples allow studying only reactivation from latency but not the mechanisms underlying its establishment. These reasons have compelled several groups to develop in vitro models to generate and study proviral latency in resting CD4+ T cells (20, 41–50; reviewed in reference 9).
The model developed in our laboratory (20) recapitulates the activation of primary CD4+ T cells via T cell receptor (TCR) engagement, infection with HIV-1, and return back to quiescence through a resting phase in the presence of low levels of interleukin-7 (IL-7). Our model is amenable to providing new insights into the nature of latency and identifying new biomarkers and therapeutic targets. The modifications of our original model that we adopted in the current study for the purpose of isolating latently infected cells—most notably a shortened resting phase—did not affect our ability to generate truly quiescent latently infected cells, as shown by the lack of surface and intracellular activation markers (HLA-DR, CD69, and Ki67) and by the absence of RT activity in the culture supernatants. The choice of using RT activity as a measure of viral latency was dictated by the evidence that cell-associated viral RNA can be detected in latently infected resting memory CD4+ T cells of HIV-1-infected subjects under effective antiretroviral therapy (11, 51), and therefore, this parameter might not provide a stringent measure of latency. This result underscores the role of low doses of IL-7 in the establishment of immunological memory in CD4+ T cells (52–54). We have previously shown that the HIV-1 antigen p24gag produced during active viral replication persists in the cytoplasm of infected cells for several days, even during latent infection, which allows us to distinguish latently infected CD4+ T cells from their uninfected counterparts (20). Thus, we took advantage of this marker to perform, for the first time, comparative genomic profiling of primary latently infected resting memory CD4+ T cells versus their uninfected counterparts sorted from the same culture. Previous studies were carried out with latently infected cell lines (55–57), but no studies using primary CD4+ T cells have been reported. Krishnan et al. showed altered expression levels of genes encoding components of the proteasome, histone deacetylases, and transcription factors in the chronically infected cell lines ACH-2, J1.1, and U1 compared to the parental uninfected cell lines A3.01, Jurkat, and U937 (56). The same data set was used later on to identify several networks at the latent stage, including an enrichment of proteins associated with HIV-1 replication, apoptosis, and cell growth regulation (58). Since latently infected cells cannot be distinguished from uninfected cells in vivo, only a comparative study of resting memory CD4+ T cells from viremic and aviremic subjects has been done so far (59).
Our microarray analysis indicates that latently infected resting memory CD4+ T cells have a very different gene expression profile than uninfected cells. It should be noted that because of the temporal course of our experimental design, it is unclear whether the genes identified in our screen are related to entry into latency, maintenance of latency, or both. Resolving this issue will require a more accurate follow-up study. The affected gene ontology not only covers pathways related to transcriptional and posttranscriptional regulation, as described previously (13, 60), but also illustrates more profound changes affecting cell proliferation, cell cycle progression, as well as basic cellular functions such as nucleic acid, lipid, carbohydrate, and amino acid metabolic processes. Altogether, these changes may contribute to the establishment of a cellular environment that is conducive to cell quiescence and viral latency. Recent ex vivo studies suggested that a single treatment with current LRAs induces viral reactivation in only a small percentage of latently infected cells (Cillo et al., presented at the 20th Conference on Retroviruses and Opportunistic Infections; Ho et al., presented at the 20th Conference on Retroviruses and Opportunistic Infections). Furthermore, recent in vivo studies showed that administration of a single dose and multiple doses of the HDAC inhibitor vorinostat led to transient increases in acetylation of histone H3 and in HIV-1 gag cell-associated RNA copy numbers. Therefore, treatment with vorinostat also affects the transcription activity of the HIV-1 long terminal repeat (LTR) in vivo. However, this effect was not paralleled by a spike in viremia (11; J. Elliott, A. Solomon, F. Wightman, M. Smith, S. Palmer, M. Prince, J. Watson, J. Hoy, J. McMahon, and S. R. Lewin, presented at the 20th Conference on Retroviruses and Opportunistic Infections, Atlanta, GA, 2013). A possible interpretation of these results may be that an increase in the level of cell-associated viral RNA following exposure to LRAs did not lead to viral production by latently infected cells. The results of our microarray analysis may suggest that latently infected cells lack the proper biochemical machinery required to support viral production despite higher intracellular levels of viral RNA. The use of concomitant LRAs targeting different transcription blocks was clearly shown to be more effective than single-agent approaches in vitro (43, 61). Moreover, it is conceivable that targeting of more downstream steps, including some of the ones identified in this study, may lead to more sustained viral production, especially in more refractory latent reservoirs.
The establishment of HIV-1 latency has been portrayed largely as a passive process. In other words, HIV-1 expression is shut down—and consequently, latency is achieved—as part of the process by which the host cell returns to quiescence. However, it is plausible that viral proteins expressed during productive infection of activated CD4+ T cells could play an active role by deregulating gene programs within the host cell so as to generate a cellular environment conducive to cell quiescence and viral latency. Indeed, our microarray study indicated that in latently infected cells, gene programs were modulated in a way that is consistent with cell quiescence, cell survival, transcription silencing, and evasion of the immune system. Since HIV-1 proteins have a profound effect on many host cell functions that are relevant to its life cycle (55, 58, 62–69), it is conceivable that they might also affect cell functions relevant to latency. On the other hand, it is possible to speculate that a subset of CD4+ T cells with a gene expression profile similar to the one emerging from our microarray analysis already preexists in peripheral blood of healthy individuals, so that upon HIV-1 infection, it provides an ideal environment for the establishment of latency.
Our microarray analysis found that the expressions of transcripts encoding a number of cell surface markers were deregulated in latently infected CD4+ T cells. This finding is of particular relevance since specific surface biomarkers to distinguish these cells have not yet been identified. Of these, CD2 was selected for validation in clinical samples, using peripheral blood of aviremic HIV-1-infected subjects under suppressive antiretroviral therapy for at least 3 years. Selection based on high expression levels of this CD2 receptor allowed strong ex vivo enrichment of a bona fide latent reservoir of resting memory CD4+ T cells. In all subjects analyzed, this CD2high population was shown to contain higher copy numbers of HIV-1 DNA and to give rise to more robust viral production upon reactivation than total resting memory CD4+ T cells. On the other hand, our data also show that the majority of CD2high cells are not infected. Moreover, we detected HIV-1 sequences in the CD2low subset of 5/6 subjects as well as HIV-1 RNA in the culture supernatant of CD2low cells of 1/3 subjects following ex vivo reactivation. Therefore, expression of high CD2 levels does not fully capture the latent reservoir, and while it represents a useful tool for future research, it is a limited one. The identification of new markers remains a high priority, and the list of transcripts identified in our microarray study might represent a valid starting point.
Two lines of evidence provide a possible basis for the identification of CD2high as a biomarker of bona fide latently infected CD4+ T cells. Indeed, binding of CD2 to its ligand, CD58/LFA-3, facilitates T cell interactions with antigen-presenting cells and perhaps enhances virus transmission. Additionally, LFA-3 is found on the membrane of HIV-1 virions and has been proposed to mediate viral targeting to particular tissues and specific cell types (70). Thus, cells overexpressing CD2 might bind HIV-1 and become infected more readily.
CD2 might represent a potential target for the elimination of latently infected CD4+ T cells. Whereas some anti-CD2 antibodies induce T cell proliferation (71) and viral transcription in PBMCs and resting CD4+ T cells (72, 73), binding of certain epitopes on CD2 induces T cell death via antibody-dependent cellular cytotoxicity (ADCC) induced by NK cells and activated monocytes. For instance, alefacept, a fusion protein composed of the first extracellular domain of human LFA-3 fused to the hinge, CH2, and CH3 domains of human IgG1, as well as rat IgG2b monoclonal antibody LO-CD2a/BTI-322 inhibit T cell proliferation and induce NK cell-mediated death of T cell memory subsets (74, 75). LO-CD2a/BTI-322 and its humanized version (siplizumab; MEDI-507) have been used for the treatment of acute kidney transplant rejection (22, 26, 28, 30), acute graft-versus-host disease (GVHD) (21, 24, 29), and psoriasis (23) and is being tested for the treatment of T cell malignancies (25, 27, 31). In addition, alefacept is FDA approved to kill memory T cells expressing higher levels of CD2 for the treatment of chronic psoriasis (76, 77). These studies suggest the possibility of targeting CD2 for the depletion of latently infected CD4+ T cells in HIV-1 infection. Although CD2 is also expressed on uninfected T and NK cells, the FDA has approved targeting of receptors such as CD20 for cell depletion in autoimmune diseases and cancer, despite the fact that CD20 is also expressed on normal B and T cells (78, 79).
Besides CD2, our microarray study found other interesting receptors that, on the basis of their known function and signaling pathways, could be explored to target or deplete this latent reservoir (Table 1). For example, engagement of the tumor necrosis factor (TNF) receptors CD262, CD270, and APO-3, found upregulated in our microarray in latently infected resting CD4+ T cells, triggers caspase activation and apoptosis (80, 81). In addition, two receptors listed in Table 1 are known to trigger cell death through the p38 mitogen-activated protein kinase (MAPK) pathway. Thus, antibodies to CD70, a TNF family member (80, 82), trigger death of malignant cells (83). Also, it is well documented that CXCR4 mediates p38 MAPK-dependent cell death in HIV-1 infection (84, 85). In addition, we found differential expressions of transcripts encoding cell surface activation markers such as CD38, CD69, and CD154/CD40L. This result is intriguing because our flow cytometry analysis showed that CD69 is not expressed on the cell surface after 1 week of a resting phase, and it further underscores the need to validate microarray results at the protein level.
In summary, microarray analysis using HIV-1 latently infected resting memory CD4+ T cells generated with our in vitro model points toward possible new pathways of latency beyond transcription that could be explored as new therapeutic targets aimed at eradicating this reservoir. 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 in-depth molecular studies, for monitoring the size of the latent reservoir in the clinical setting, as well as for the development of novel therapeutic strategies aimed at eradicating HIV-1. Among them, CD2 has proven to allow efficient enrichment of latently infected resting memory CD4+ T cells ex vivo.
This work was supported by National Institutes of Health grant AI084711 (F.R.). L.M. was also supported by NIH-NCI grant P30CA006973.
Published ahead of print 12 June 2013
Supplemental material for this article may be found at http://dx.doi.org/10.1128/JVI.01297-13.