Viruses | Free Full-Text | A Canadian Survey of Research on HIV-1 Latency—Where Are We Now and Where Are We Heading?

Viruses | Free Full-Text | A Canadian Survey of Research on HIV-1 Latency—Where Are We Now and Where Are We Heading?

3. Host and Viral Factors in Latency Establishment

The ways in which HIV-1 establishes latency remain topics of investigation and intense scientific discussion. The consensus is that the establishment of the HIV-1 latent reservoir occurs early during infection [5]. For example, a patient who initiated cART ten days post-HIV-1 exposure still experienced viral rebound following cART cessation, even after two years of treatment and having an undetectable viral load [11]. Studies in nonhuman primates (NHP) showed that latently infected cells were established in less than 72 h [27,28]. Additional evidence comes from post-exposure prophylaxis (PEP). The increased failure of PEP directly correlates with the time taken before starting cART [29,30,31]. Most government health agencies suggest taking PEP drugs within 72 h after potential exposure, and the reason comes from the evidence that, in the context of mucosal exposure, the virus takes up to 72 h to reach the lymph nodes [32].
Other factors that account for a productive infection are the cells’ inner function and activation status. For example, naïve CD4+ T cells are resistant to HIV-1 infection, while activated CD4+ T cells are more susceptible [33,34]. As part of the inherent immune response, T cells become activated upon infection. When activated cells die, only long-lived memory CD4+ T cells remain, representing the main HIV-1 latent reservoir (see Donahue et al., 2013 [35], and Dufour et al., 2020 [5] for details). Therefore, a key question is “at what point is latency established in CD4+ T cells?”. T cells may become infected upon cell activation, achieving latency when these cells turn into a memory phenotype. Another possibility can be that activated cells become infected during the transitioning from activated to the long-lived, quiescent memory phenotype [5]. Evidence from in vitro studies has shown that targeting specific molecules associated with certain cellular phenotypes can affect the number of cells that harbor latent HIV-1. Evans et al. showed that blocking the programmed cell death protein 1 (PD-1), an immune checkpoint associated with T cell activation/exhaustion, before HIV-1 infection decreased the number of latently infected cells [36]. Fromentin et al. complemented this observation as they observed that HIV-1 reactivation was enhanced when blocking PD-1. The engagement of PD-1 with its ligand (PD-L1) inhibits viral expression and impairs the T cell receptor (TCR)-induced HIV-1 reactivation in latently infected cells. Moreover, blocking PD-1 signaling with the monoclonal antibody pembrolizumab enhanced HIV-1 production in combination with bryostatin, without increasing T cell activation [37]. Additionally, they found that PD-1 expression is higher in latently infected CD4+ T cells in patients undergoing cART [37], suggesting that the PD-1 pathway can be involved in establishing and maintaining HIV-1 latency. However, other factors, aside from CD4+ T cell activation status, influence the susceptibility of cells. Casuso et al. showed that HIV-1 preferentially infects highly dividing CD4+ T cells, independent of their activation status [38]. Moreover, blocking specific metabolic pathways, such as glycolysis, dampens HIV-1 infection, leading to cell death, and can further affect the size of the latent reservoir [38].
Another aspect of the T cell profile that influences the establishment of latency is the subtype of CD4+ T helper (Th) cells [6]. Cleret-buhot et al. showed that the proportion of latency is higher in Th17 cells compared with Th1 cells. They identified MAPK3K4 and the tyrosine-protein phosphatase non-receptor type 13 (PTPN13) in Th17 cells as possible factors in latency establishment, as the downregulation of these proteins decreased HIV-1 DNA integration [39]. In addition, Kulpa et al. demonstrated that, after latency-reversing agents (LRA) stimulation, TCM differentiated into TEM, the latter identified as one of the main HIV-1 reservoirs [40]. By ex vivo and in vitro approaches, Kulpa et al. also showed the association between the response to LRAs and the transcriptional pathways related to T cell differentiation, the acquisition of effector function, and the cell cycle [40]. In the natural course of an infection, TCM cells are reactivated upon antigen stimulation, acquiring a TEM phenotype [41]; however, it is not clear how that might happen in the context of latent HIV-1 infection.
Aside from host factors, viral factors also play a role in the latency establishment. Omondi et al. demonstrated a correlation between the HIV-1 protein Nef subtypes and the HIV-1 immune evasion and reservoir size. They showed that some Nef subtypes are more efficient than others in driving HIV-1 escape from the immune system, which positively correlates with the reservoir size, underscoring the fact that viral proteins can also influence the establishment of latency [42].

4. Molecular Mechanism of HIV-1 Latency

HIV-1 latency is complex, and what occurs at a cellular level is not any different. From virus binding to host receptors (e.g., CD4), to the regulation of proviral DNA transcription, every step of the virus replication can be modulated to influence the state of HIV-1 latency (Figure 1). In addition to the classical role of the HIV-1 envelope protein in viral entry, the gp120 portion also has different roles. For example, when recognizing CD4 in an infected cell, HIV-1 gene expression is downregulated, presumably by modulating the HIV-1 long terminal repeat (LTR) [43]. In contrast, gp120 can also bind to the α4β7 receptor, promoting CD4+ T cell activation and proliferation, resulting in HIV-1 expression [44]. In addition to CD4, other receptors have been implicated in the regulation of the HIV-1 LTR activity. For example, CD45 counteracts the phorbol 12-myristate 13-acetate (PMA)-induced HIV-1 reactivation [45] and the engagement of CD43 [46] or exposure to virions expressing B7.2 induced the activation of HIV-1 LTR [47]. These examples illustrate how HIV-1 proteins modulate latency due to the low levels of virus expression in reservoirs.
Following HIV-1 fusion to the plasma membrane, the capsid is released into the cytoplasm. The viral RNA is reverse transcribed to double-stranded DNA and, along with the integrase and host proteins, forms the pre-integration complex (PIC), allowing the integration of the proviral DNA into the host genome [48]. The process of HIV-1 translocation to the nucleus involves the nuclear pore complex, which works as a barrier to regulate nucleocytoplasmic transport under physiological conditions [49]. Several viruses, including HIV-1, usurp this complex to promote nuclear translocation [49]. Most events preceding integration are related to the restriction of HIV-1 translocation. However, pre-integration latency may also occur in which the PIC remains intact but only upon reactivation is the viral DNA integrated [50] (Figure 1). Therefore, when considering HIV-1 latency, it is also important to consider the possibility of pre-integration events that contribute to the reservoir.
Along with the PIC, several host proteins assist in its interaction with the host chromatin. Perhaps the most studied is lens epithelium-derived growth factor (or LEDGF/p75), which binds to the viral integrase, licensing the PIC toward transcriptionally active sites [51,52,53]. Moreover, the viral integrase can be regulated by post-translational modifications, such as acetylation, that increase the integrase activity [54,55]. Another important modification is the SUMOylation, which consists of the addition of SUMO (small ubiquitin-like modifier) groups to lysine residues in target proteins. SUMOylation is important for the integrase function early in the replication cycle and operates independently of the binding to LEDGF/p75. Zheng et al. described how SUMOylated proteins can interact with each other through specific SUMO-interacting motifs (SIM), including the HIV-1 integrase [56]. The HIV-1 integrase has three SIMs (M1-M3). Mutations in the M2 and M3 motifs impaired nuclear translocation, as well as reduced binding to LEDGF/p75 [56]. Interestingly, the binding to Ku70, a nuclear protein involved in DNA repair, was enhanced in the M2 and M3 SIM mutants. The infection with a virus containing SIM mutations exhibited s nuclear translocation of the PIC [56]. Although this phenotype can not be precisely associated with LEDGF/p75 or Ku70, it is clear that SUMOylation of the HIV-1 integrase plays an important role in the PIC nuclear translocation (Figure 1).
Of note, previous work from Zheng et al. showed that LEDGF/p75 is dispensable for interaction between the HIV-1 integrase and the host chromatin. They observed that by mutating the C-terminal domain of the integrase, which binds to LEDGF/p75, the integrase maintained the ability to bind to the host chromatin and further integrate the viral DNA. However, two introduced mutations (EH170,171AA) in integrase failed to bind LEDGF/p75 but induced low levels of viral replication, suggesting that LEDGF/p75 has another important function in HIV-1 replication [57]. Although the result from this study seems contradictory to what has been previously shown, it does not necessarily invalidate previous findings as the authors did not evaluate the efficiency of integration or the integration site—thus, it remains unclear whether the mutations, specifically EH170,171AA, reduced overall integration of vDNA or led the PIC to transcriptionally inactive sites.
During nuclear translocation of the PIC, the nucleoporins Nup153, Nup98, transportin-3, and RanBP2/Nup358 play key roles [49]. Moreover, nucleoporins have additional roles once the PIC enters the nucleus. Ao et al. showed that Nup62 interacts with the HIV-1 integrase and chromatin, but that its depletion does not affect nuclear translocation of integrase. However, this reduced the binding of the integrase to chromatin and the levels of integrated vDNA, suggesting that Nup62 plays a role in the integration of viral DNA [58]. Other host factors that interact with the HIV-1 integrase and influence its activity are the histone deacetylases (HDAC), playing important roles in the establishment of HIV-1 latency. Ran et al. identified HDAC10 as a host factor that reduces viral gene expression, which is downregulated during the course of the infection. In addition, HDAC10 interacts with the integrase, and its depletion increased the levels of integrated viral DNA, independent of the integrase acetylation status [59] (Figure 1).
Latency reversal involves the expression of the integrated HIV-1 genome, which is driven by a single promoter located at the 5′ LTR. In short, the HIV-1 LTR is located between the nucleosomes nuc-0 and nuc-1. Sequentially, from 3′ to 5′, it comprises a canonical TATA box with an enhancer box (E-box), as well as binding sites for the transcription factors SP-1, NF-κB, and USF-1. Further details on the binding sites, cis and trans elements are extensively reviewed in Delannoy et al. [60].
Despite the cis elements being related to the canonical transcription factors driving the HIV-1 LTR (e.g., NF-κB, NFAT), other elements have been identified as important in regulating HIV-1 expression. Ras-responsive region binding factor-1 (RBF-1) and -2 (RBF-2) are factors required for HIV-1 expression as they bind to Ras-responsive binding elements (RBEs) found in the HIV-1 proviral DNA [61]. Initially, RBF-1 was found to bind to the ets-like motifs within the Ras-responsive binding element 2 (RBE2). RBF-2 was characterized as a complex containing USF-1/USF-2 and the general transcription factor II-I (TFII-I), which cooperatively binds to RBE1 within an E-box element adjacent to the TATA box and to RBE3 upstream the NF-κB binding sites [61,62,63]. By itself, USF-1 is associated with transcriptional activation [64], and when found in the RBF-2 complex, it suppressed transcription due to the recruitment of HDAC3 [65]. In parallel, Malcolm et al. highlighted the implications of RBF-2 in the regulation of the HIV-1 LTR activity, by demonstrating that both, TCR- and PMA-, but not TNF-α-induced HIV-1 expression through RBF-2 and the Ras/MAPK signaling [65,66]. A single T-A substitution at the 3′ of RBE3 weakened the binding of TFII-I, which impaired PMA-induced virus expression and the binding of RBF-2 to the HIV-1 LTR [65]. Although these findings appear contradictory, there is likely a balance between activation and repression based on structural changes and binding factors on the LTR (For example, RBF-2), although the exact mechanism remains unclear [65,66] (Figure 1). Further investigations in RBF-2 found that the tripartite motif protein 24 (TRIM24) acted as a cofactor of RBF-2 in the induction of transcriptional elongation of the HIV-1 provirus [67]. Horvath et al. found through siRNA assays that TRIM24 bound to TFII-I and assisted in inducing HIV-1 LTR activity. Moreover, they found that TRIM24 was important for recruiting the cyclin-dependent kinase 9 (CDK9) to promote elongation. In parallel, the depletion of TRIM24 favored the establishment of latency upon HIV-1 infection in Jurkat T cells [67]. Last, the transcription factor Yin Yang 1 (YY1) is a factor previously shown to bind downstream to the TATA box (−16 to +27) and to repress HIV-1 transcription [68]. Later, YY1 was shown to bind RBE3 in unstimulated conditions, while in PMA-induced conditions, YY1 dissociated from the HIV-1 LTR. Furthermore, YY1 recruited HDAC1 and promoted viral silencing during HIV-1 infection [69].
Among the other transcription factors that are important for HIV-1 expression, the CCAAT/enhancer-binding proteins (C/EBP) have three binding sites on the HIV-1 LTR [70]. Dumais et al. showed that prostaglandin-E2 increased cyclic adenosine monophosphate (cAMP) levels, which leads to the formation of a heterodimeric complex of C/EBP-β and the cAMP-response element-binding protein (CREB). This complex interacts with the proximal binding site in the HIV-1 LTR, to induce virus expression [71]. A recent study from Canchi et al. showed that the overall expression of C/EBP-β is increased in the brain of patients with HIV-1-associated neurocognitive disorders (HAND), in postmortem frontal cortex tissue. They demonstrated that C/EBP-β expression is modulated by the viral protein Tat and that C/EBP-β levels are reduced in neurons and increased in astrocytes compared with samples from PLWH with no cognitive disorders [72]. They associated their observations with the role of C/EBP-β in regulating inflammation, metabolism, and autophagy in astrocytes, suggesting that C/EBP-β plays a role in the development of HAND due to neuroinflammation.
The importance of NF-κB and the nuclear factor of activated T cells (NFAT) in inducing HIV-1 transcription is widely characterized. The regulation of the HIV-1 LTR is the endpoint that results from a cascade of protein activation. Despite the classical stimulus that leads to NF-κB- and NFAT-induced HIV-1 expression through protein kinase C (PKC) activation, or TCR engagement, respectively, there are other less studied pathways. Ryckman et al. found that the expression of S100A8, S100A9, and S100A12, known as myeloid-related proteins (MRPs), induced viral expression by activating NF-κB, eliciting a response through the enhancer region of HIV-1 LTR in J1.1 cells, a human T cell line latently infected with HIV-1 [73]. Additionally, Dahal et al. showed the relevance of the SR RNA-binding proteins. They demonstrated that the knockdown of the SR-RBP CLK1 increased HIV-1 promoter activity and enhanced the response to LRAs by increasing HIV-1 reactivation, while depletion of CLK2 suppressed it. In addition, by inhibiting CLK1 and CLK2, but not CLK3, they observed a suppression of HIV-1 gene expression [74], suggesting that CLK proteins regulate latency at different steps.
Importantly, the HIV-1 genome codes the transactivation of transcription (Tat), a critical regulatory protein responsible for binding to the trans-activation response element (TAR) in the nascent viral RNA to drive transcription elongation [75]. Several reports demonstrate that the regulation of Tat is essential to drive efficient HIV-1 expression [75,76]. Xie et al. showed that Tat methylation, mediated by the protein arginine N-methyltransferase 6 (PRMT6), affects Tat’s ability to recruit CDK9—a master regulator of RNA transcription—to impair HIV-1 transcriptional elongation [76]. Importantly, Tat is a regulatory protein that prevents the establishment of latency [77], as exogenous Tat, from another source/virus, can reactivate HIV-1 latently infected cells [35,77]. Despite that, Tat binding to TAR is essential, and additional evidence shows that other components in the HIV-1 promoter also contribute to successful Tat-induced virus expression. For example, Wilhelm et al. identified the GTGC sequence, flanking the TATA box in HIV-1 LTR, as essential for the recruitment of transcriptional factors to the PIC [78].
The full-length HIV-1 RNA is processed co-transcriptionally by the host splicing machinery to generate multiple RNA species that will be translated to produce Gag, Gag-Pol, Envelope, accessory, and regulatory proteins. Wong et al. showed that cardiotonic steroids (CS) play a role in HIV-1 RNA splicing, restricting HIV-1 expression through its interaction with the Na+/K+ ATPse [79]. They observed that CS led to an over-spliced HIV-1 RNA and nuclear retention, thereby reducing Gag synthesis from the full-length viral RNA. In addition to mRNA splicing, another way to regulate mRNA translation is via the activity of microRNAs (miRNA) [79]. Ouellet et al. demonstrated that the TAR RNA can be used as a template to generate microRNAs, identifying two miRNAs that regulate HIV-1 gene expression [80]. On the other hand, Pardons et al. determined that the host microRNA miR125b contributes to the maintenance of latency in resting CD4+ T cells, while this role was attributed to miR155 in effector memory CD4+ T cells, highlighting that latency regulation may vary between CD4+ T cell subtypes [80,81].
Our group has reported on the control of viral RNA processing and trafficking [82,83,84,85,86,87,88] and their possible impact on HIV-1 latency [85]. We identified that HIV-1 hijacks the Up frameshift 1 (UPF1) protein to increase the stability of the viral genomic RNA [82,85]. UPF1 has been implicated in RNA surveillance as it targets mRNAs for degradation through the nonsense-mediated mRNA decay (NMD) pathway, by forming a complex with other host cofactors, such as UPF2, UPF3a, SMG1, and SMG6 [89]. UPF1-mediated viral RNA stability is dependent on the binding to UPF2, suggesting that the role of UPF1 is independent of its primary role in the NMD pathway [82] (Figure 1). In addition, the overexpression of UPF1 increased the reactivation of the HIV-1 provirus in a latent T-cell model system. Furthermore, in the same model, overexpression of either SMG6 or UPF2 downregulated HIV-1 reactivation [85]. In both cases, binding to UPF1 was required. Noteworthy, the co-overexpression of UPF1 and UPF2 is sufficient to rescue HIV-1 expression, suggesting that UPF1 fine-tunes viral genomic RNA stability, contributing directly to the maintenance of HIV-1 latency. The nucleoporin Nup62, present in the nuclear pore complex (NPC), is involved in the integration of the viral DNA [58] and participates in the nucleocytoplasmic export of the HIV-1 viral mRNA [90]. Ajamian et al. identified that UPF1 associates with Nup62 to mediate viral RNA nucleocytoplasmic export [83]. UPF1-mediated viral RNA nuclear export depends on Exportin-1 (also known as CRM1), which is consistent with the observation that UPF1 co-immunoprecipitates with Rev, CRM1, DDX3, and Nup62 in the context of HIV-1 infection [83]. Moreover, while UPF1 is required to bind UPF2 to degrade mRNA through NMD, in the context of HIV-1, the binding of UPF2 to UPF1 impairs viral RNA nuclear export [91]. As mentioned above, UPF1 regulation of the viral RNA affects the ability of infected cells to be reactivated [85], so the regulation of viral RNA nuclear export harbors similar considerations in controlling HIV-1 expression and can also play a role in the maintenance of latency.

5. Targeting of HIV-1 Latent Reservoirs

A definitive cure against HIV-1 will require targeting all latently infected cells, with the final aim of stopping cART without the concern of viral rebound. The HIV-1 reservoir is present at a low frequency (0.000001% of the T cell population), but it is represented by a long-lived pool of cells, with an estimated half-life of 44 months [3]. In Canada, several studies were carried out to decipher which are the HIV-1 reservoirs. These studies concur that the reservoir is highly diverse, represented by different cell subtypes residing in several tissues. Initial research suggested that the HIV-1 reservoir was present only in resting memory CD4+ T cells. Current research demonstrates that several T cell subsets harbor an integrated provirus, contributing to the size of the HIV-1 reservoir. An extensive review of how different CD4+ T cell subsets contribute to HIV-1 persistence can be found in Fromentin et al. [6]. In their other work to identify cellular markers that are expressed by latently infected CD4+ T cells from patients under cART, Fromentin et al. demonstrated that cells that harbor proviral DNA have a higher frequency of the immune checkpoint markers, PD-1, TIGIT, and LAG-3, in combination or alone [92]. Although these markers were not specific to HIV-1 infected cells, further research to identify a specific cell marker may represent a valuable tool to target the HIV-1 reservoir.
Chomont et al. identified that TCM and transitional memory T cell (TTM) CD4+ T cells represent major HIV-1 reservoirs, suggesting that cell self-renewal and proliferation play a role in viral persistence [17]. Interestingly, they observed that these two T cell subtypes defined two different reservoirs. TCM are the main reservoir in patients with suppressed viral load and their CD4+ T cell counts are normal. TCM do not markedly proliferate and are long-lasting. In contrast, the HIV-1 reservoir is found in TTM in viremic patients with low CD4+ T cell counts, which are cells in constant proliferation due to persistent activation of the immune system [17]. Gantner et al. complemented the observations by demonstrating that the persistent HIV-1 reservoir in TCM is due to clonal expansion, suggesting that the reservoir observed in other subtypes is derived from the progeny of TCM after antigen-driven expansion [93]. Of note, both studies suggest that early adhesion to cART impacts the HIV-1 reservoir size, which goes hand in hand with more recent work from Massanella et al. This group recruited participants and grouped them based on the time of cART initiation after infection—less than 30 days, between 31 to 90 days, or greater than 90 days—and determined the pool of latently infected cells before and up to four years after cART initiation [94]. They observed that the HIV-1 reservoir in people who initiated cART the earliest was smaller compared with the other groups, thus suggesting that early detection and adhesion to cART plays a role in the size of the reservoir [94]. Importantly, different T cell subtypes also respond differently to treatments. Sannier et al. evaluated the effect of different LRAs in reactivating the integrated provirus in different T cell subtypes [95]. All the evaluated memory T cell subtypes efficiently reversed latency, but marked differences were observed depending on the specific LRA and the subtype of memory T cells. They observed that the TEM subtype re-established HIV-1 protein synthesis, while the other memory subtypes showed a latency reversal mainly at the level of transcription, supporting that the HIV-1 reservoir is influenced by cell-intrinsic factors [95].
The HIV-1 reservoir is present in multiple tissues, encompassing the lymph nodes, GALT, CNS, spleen, lungs, liver, and bone marrow [20,96,97]. If cART is interrupted, HIV-1 can be reactivated from all of these sites, turning anatomical features into a key point to consider in future treatments (reviewed in detail by Costiniuk et al. [98]). The GALT harbors abundantly infected CD4+ T cells and macrophages [99]. Importantly, a significant T cell depletion after HIV-1 infection occurs in the GALT, which recovers slowly, even after restoring the CD4+ T cell levels due to strict adherence to cART [100]. The GALT is proposed as a “hideout” for HIV-1, as cART penetration is lower when compared with circulating cells [101]. Another site described as an HIV-1 reservoir is the lungs. Costiniuk et al. evaluated the presence of HIV-1 CD4+ T cells from pulmonary mucosa, obtained from bronchoalveolar lavage from infected adults under suppressive cART [102]. They found that proviral DNA is 13-fold higher in T cells from lung mucosa compared with the matched blood samples. They also observed that TEM were the most abundant T cell subtype in the lungs from PLWH and concluded that the pulmonary mucosa represents an important tissue in establishing the HIV-1 reservoir, even under cART [102]. HIV-1 is also detected in the CNS as early as a week after primary infection, triggering an immune response and neuroinflammation [103,104]. Research suggests that HIV-1 crosses the blood–brain barrier by traveling within infected T cells and macrophages, but there is not enough evidence to strongly support this hypothesis, as most of it comes from postmortem samples. The CNS is still understudied, mainly due to the difficulty of accessing human samples that are not postmortem, with several conclusions being drawn from studies in animal models or in vitro cell culture [105]. Importantly, HIV-1 requires adaptation to effectively establish a reservoir in the CNS as brain-derived HIV-1 isolates are less dependent on CD4 levels at the cell membranes for entry, which has been proposed to be related to macrophage infection (microglia), which are more abundant than T cells in the CNS [106,107]. In addition to microglia, astrocytes of the CNS are latently infected by HIV-1. Barat et al. demonstrated that astrocytes are relevant to HIV-1 infection as proliferative astrocytes are readily infected when compared with non-proliferative astrocytes [108]. When they evaluated provirus reactivation in astrocytes, none of the evaluated LRAs were able to reverse latency, suggesting that astrocytes might not constitute an HIV-1 reservoir but produce low levels of viral proteins, which can contribute to the neurological disorders seen in PLWH [108]. In conclusion, HIV-1 persists and establishes a reservoir in different anatomical sites within the human body, posing a challenge to eradicating HIV-1, as each tissue has different kinetics for drug uptake and unique cellular factors that support or impede viral persistence.

6. Determination of the HIV-1 Reservoir Size

There are several methodologies to evaluate the percentage of latently infected cells or the percentage of HIV-1 reactivated cells obtained from blood samples from PLWH. Initial approaches were PCR-based assays, in which the integrated provirus was detected using specific primers against the HIV-1 LTR regions [109,110,111,112]. Unfortunately, even when these approaches provide quick and easy-to-interpret answers, they do overestimate the size of the reservoir due to the detection of defective proviruses [109,113]. To partially overcome this issue, the quantification of only replication-competent viruses was carried out by the quantitative outgrowth assay (QVOA) [114,115] or the Tat/Rev-induced limiting dilution assay (TILDA) [116]. The first methodology consists of CD4+ T cells isolation from PLWH and further reactivation of HIV-1, followed by co-culture with noninfected CD4+ T cells to allow HIV-1 spread. The readout is infectious units per million (IUPM) of CD4+ T cells, determined by the quantification of viral release by p24 ELISA or RT-qPCR [115,117]. The second methodology is based on the fact that the viral RNAs that code for the viral proteins Tat and Rev are present at low levels in latently infected cells. Their expression is high in HIV-replicating cells, using the presence of these mRNAs as a readout for viral reactivation [118,119,120]. To do this, CD4+ T cells are isolated from PLWH and then treated to induce HIV-1 reactivation. Later, samples are subjected to qRT-PCR to determine the abundance of tat and rev RNAs [116]. Although both techniques provide an idea of the reservoir size, there are limitations to consider. QVOA is an expensive and time-consuming technique, requiring between 10 and 15 days and large amounts of blood (~150 mL) to be carried out. It also relies on a single round of reactivation with a specific LRA, which does not reactivate all proviruses, underestimating the reservoir size [121]. TILDA is a faster technique, requiring only two days and 10 mL of blood, making it a useful technique in clinical research. However, TILDA still overestimates the reservoir size as it detects defective proviruses that still code for tat and rev viral RNAs [113,121]. In addition, none of the mentioned techniques can distinguish between different subsets of CD4+ T cells as they are all based on bulk-isolated cells.
More recently, a flow cytometry-based approach, with several contributions from Canadian researchers, has been developed to evaluate the HIV-1 reservoir size and, also, to determine which subset of cells are more prone to be latently infected [122,123,124,125]. Ivan Sadowski’s team attempted to study HIV-1 latency by flow cytometry using a double-labeled HIV-1-coding vector termed Red-Green HIV-1 (RGH). RGH allows the detection of HIV-1 by GFP expression as well as integration into the host genome by mCherry expression under the control of the constitutively expressed cytomegalovirus promoter. This allows the distinction between latently (GFP/mCherry+) and productively (GFP+/mCherry+) HIV-1 infected cells [122]. Dahabieh et al. infected Jurkat T cells with RGH to understand whether latency is established early after infection or during later timepoints. They observed latently infected cells as early as two days post-infection, with no apparent increase in their proportion seven days after. They also confirmed that the RGH vector can infect activated primary CD4+ T cells from healthy donors, resulting in approximately 1% of cells latently infected on day six post-infection [122]. Finally, they showed that the latency established by the RGH vector can be reversed with commonly used LRA, supporting the double-labeled vector as a useful tool to study latency in vitro using flow cytometry [122]. Importantly, they observed a significant population of primary CD4+ T cells as GFP+/mCherry, suggesting viral expression with no vector integration into the host genome. The authors attribute this to the silencing of the cytomegalovirus promoter due to T cell activation [122,126,127], proposing a future version with a constitutive promoter derived from a host gene instead of a viral sequence.
One of the main problems of HIV-1 detection by flow cytometry is that anti-HIV-1 antibodies have a high signal-to-noise ratio, preventing a reliable detection of HIV-1+ cells. This situation is overcome by FISH-Flow, a technique that integrates flow cytometry with fluorescence in situ hybridization (FISH), allowing the detection of RNA at a single-cell level [128,129]. Daniel Kaufmann’s group validated this technique for HIV-1 using samples from PLWH and a set of probes targeting the viral gag and pol mRNAs, along with an antibody against the HIV-1 Gag protein [125]. By FISH-Flow, the sensitivity of HIV-1 detection was improved significantly, detecting one thousand HIV-1+ cells per 106 cells, compared with one HIV-1+ cell per 106 when using single detection of viral mRNA or Gag [125]. In this work, Baxter et al. also characterized the subset of CD4+ T cells where HIV-1 was predominant. They determined that memory CD4+ T cells (central CD45RA/CD27+, and effector CD45RA/CD27), isolated from the blood of PLWH during viremia, were the most frequently HIV-1 infected cells. In addition, these cells presented increased levels of exhaustion markers CTLA-4, PD-1, and TIGIT [125], consistent with previous publications [112,113,114,115]. Finally, they evaluated differences in CD4+ T cells between viremic and aviremic patients. They observed that memory CD4+ T cells carried most of the HIV-1 mRNA+/Gag+ cells in both groups, with viremic and aviremic patients having higher TCM and TEM proportions, respectively. In addition, they observed that the ability to reactivate HIV-1 with different LRAs shifts between the subtypes of memory T cells, even if the LRAs belong to the same class. For example, HIV-1 was reactivated from TEM cells by bryostatin, but not by ingenol, while TCM exhibited poor HIV-1 reactivation by bryostatin [125]. However, even when the FISH-Flow methodology proved to be a reliable and improved technique over previous methods, one of its major drawbacks is the requirement of a large number of cells (at least 1 × 107 CD4+ T cells per patient). A detailed protocol for the HIV-1 FISH-Flow is publicly available [124].
Nicolas Chomont’s group developed a simplified version of flow cytometry by using a combination of anti-HIV-1 antibodies instead of mRNA probes, as detecting HIV-1 by at least two different antibodies should reduce the number of false positive events [123]. In this work, Pardons et al. targeted two different epitopes of the HIV-1 capsid protein, using the antibodies KC57 and 28B7. They isolated and activated CD4+ T cells from the blood of PLWH under viremic or aviremic conditions. As expected, they observed an increase in double-positive events in viremic patients compared with aviremic patients, which increased in both groups when treated with PMA/ionomycin [123]. Then, they determined which subset of CD4+ T cells was preferentially infected with HIV-1. They observed that effector memory CD4+ T cells (CD45RA) were the main T cell subset infected with HIV-1, supporting previous observations [125]. Then, they compared CD4+ T cell phenotypes between viremic and aviremic patients. In aviremic patients, double-positive HIV-1 cells were present in the effector (CD45RA/CCR7/CD27) and transition (CD45RA/CCR7/CD27+) memory CD4+ T cells. In viremic patients, HIV-1 was found in TCM (CD45RA/CCR7+/CD27+) and Th17 cells (CCR4+/CXCR3/CCR6+) [123], the latter reported as highly permissive to HIV-1 infection [115,116]. The authors also observed that HIV-1 infected cells also expressed high levels of the α4β1 integrin receptor in the blood samples from both viremic and aviremic individuals. This integrin drives the migration of cells toward the inflamed CNS and to the bone marrow, supporting their identity as an HIV-1 reservoir [123]. The flow cytometry approach to measure the HIV-1 reservoir has proven to be as sensitive as the QVOA or TILDA assays, detecting one double-positive event every 106 CD4+ T cells, with an improved R2 when combining the two antibodies to detect HIV-1. Importantly, this approach reduces by half the number of cells required per patient and requires less time to be carried out in comparison to the FISH-Flow approach, underscoring the usefulness of this tool to phenotype and understand the HIV-1 reservoir [123].

7. Therapeutic Strategies

Strategies to target HIV-1 from latently infected cells have been evaluated thoroughly by research teams in Canada (Table 1). In 2015, Zhu et al. determined the efficiency of targeting different portions of the HIV-1 provirus by CRISPR/Cas9 [130]. This system utilizes short nucleotide sequences (termed guide RNAs) to recognize the complementary DNA and cleave it, generating double-stranded DNA breaks that, after repair, cause insertions or deletions at the target site [131,132]. Zhu et al. evaluated the inactivation of the integrated HIV-1 provirus in J-Lat 10.6 cells, a T-cell line model used to study HIV-1 latency [133]. They designed ten different guide RNAs, targeting conserved sequences present at the HIV-1 LTR, the polymerase (pol), or the regulator of expression of viral proteins (rev) segments within the HIV-1 genome. Following transfection, they stimulated HIV-1 expression by adding TNF-α and then measuring HIV-1 reactivation by quantifying viral release into the supernatant [130]. All guide RNAs reduced the amount of viral release, with a guide RNA targeting the second exon of Rev as the most effective, proving in vitro the feasibility of targeting and inactivating the HIV-1 reservoir by CRISPR/Cas9 [130].
Dr. Jonathan Angel and his group developed a strategy to target HIV-1 latently infected cells based on their previous research. Initially, they showed that latently infected cells exhibited an impaired IFN response [134], followed by the fact that the oncolytic virus, Maraba virus (MG1), targets IFN-I-defective tumors in vivo with minimal toxicity [135,136]. Considering this, they evaluated the use of MG1 to target HIV-1 latently infected cells by infecting the promonocytic cell lines U937 and U1 with different multiplicity of infections (MOI) of MG1 (U1 being a U937-derivative cell line where the HIV-1 provirus has been integrated) [137]. They observed that using an MOI of 0.005, 80% of U1 cells were infected with MG1, while only 20% of the U937 cells became infected. Consequently, cell survival was 60% in MG1-infected U1 cells, while no significant cell death was observed in infected U937 cells [137]. Based on this, they evaluated the feasibility of the MG1 strategy in CD4+ T cells isolated from healthy donors, followed by HIV-1 infection. Three days after infection, they proceeded to infect the cells with MG1 and to determine the size of the HIV-1 reservoir. In agreement with their previous results, MG1 infection decreased the amount of detected HIV-1 provirus and viral release from infected CD4+ T cells after latency reversal with phytohemagglutinin (PHA) and IL-2, suggesting that MG1 can be a feasible therapy to target HIV-1 latently infected cells. However, they required an MG1 MOI of 10 to observe significant differences [137].
More recently, Mann et al. evaluated a polyvalent virus-like particle formulation, designated activator vector (ACT-VEC), as an anti-HIV-1 vaccine that will reactivate the latent HIV-1 provirus [138]. The formulated vaccine was developed by cloning the full-length sequence of the HIV-1 provirus from the serum of five PLWH before cART initiation [139]. The five genomes were cloned into vectors and engineered to produce non-replicative HIV-1 virus particles. Later, monocytes were isolated from a group of nine PLWH, under cART since the early stages of infection, to further pulse monocyte-derived dendritic cells with the ACT-VEC formulation. Pulsed dendritic cells were exposed to purified autologous CD4+ T cells ex vivo to evaluate levels of HIV-1 reactivation [138]. An ACT-VEC pulse induced a significantly higher reactivation compared with PMA/ionomycin treatment, a common combination used to reverse latency in vitro [140]. Importantly, they observed that the released ACT-VEC-derived viruses did not show a significant genetic diversity, supporting the use of the ACT-VEC formulation as a vaccine candidate that will target CD4+ T cells expressing HIV-specific TCRs [138].
In addition to the targeting strategies of the latent HIV-1 reservoir, the development of latency-modifying agents is an important therapeutic research axis. These agents comprise LRA, the “shock and kill” approach [141], and latency-promoting agents (LPAs), commonly associated with the “Block and Lock” approach [142], both associated with two HIV-1 curative strategies. There are significant and ongoing efforts in Canadian laboratories to screen and find LRA or LPA compounds. A spotlight of these investigations is the compounds derived from natural sources, like marine sponges, other invertebrates, and microorganisms [143,144]. Thirteen LRAs and one LPA were identified in various screenings. In addition, eight were found to reactivate HIV-1 in screening the libraries: kinase inhibitor library [145], DIVERSet [146], and pANAPL (pan-African natural product library) [147]. All these compounds acted through different mechanisms to modulate viral expression (Table 1).

Table 1.
Overview of screenings for latency modifying agents.

Table 1.
Overview of screenings for latency modifying agents.

First Author
Compounds Mechanism Methodology/Comments Source from Screening Ref
Latency-Reversal Agents (LRA)
Wang, 2016 Sesterpenoid alotaketal C, D, and E.
Ansellone A
PKC activation Screened in J-lat 9.2 A total of 9 compounds extracted Marine sponge- Phorbas sp. [143]
Wang, 2022 Ansellone J
Phorone C
PKC activation Screened in J-lat 9.2 A total of 5 compounds extracted Marine sponge- Phorbas sp. [144]
Ao, 2016 PKC412 Activation of NF-κB signaling pathway Screened in ACH2 cells Small molecules library
(ChemBridge) and kinase inhibitor library (BML-2832-0100)
Hashemi, 2016 PH01, PH02, PH03, PH04, and PH05 N.E. *
iκB degradation (PH02 only)
Jurkat cells infected with HIV-luciferase reporter virus 180.000 small molecules from 3 libraries (CCBN, LCGC and DIVERSet) [146]
Richard, 2018 Psammaplin A, Apllysiatoxin, Debromoaplysiatoxin HDACi
PKC Activation
J-lat 8.4 and 10.6; PBMCs from PLWH Marine invertebrates and microorganisms. Library from R.J.A lab $ [148]
Richard, 2020 Knipholone anthrone
Tat deacetylation or influence on the PKA pathway J-lat 9.2 and PBMCs from PLWH pANAPL A total of 216 screened compounds [147]
Fortin, 2000 bis-peroxo-
vanadium (bpV) PTP inhibitors
Constant NFAT activation Jurkat cells and PBMCs from health donors NA * [149]
Hovarth, 2023 IACS-9571 Increase binding of TRIM24 to HIV-1 LTR Jurkat cells expressing mHIV-luc and Hek293T NA * [150]
Chaetocin Reduced H2K9 methylation Jurkat cells infected with HIV-luciferase reporter virus NA * [151]
T007090 Inhibition of PPARy Isolated CD4+T cells differentiated into Th17 in vitro and CD4+ T memory cells from PLWH NA * [152]
Latency-Promoting Agents (LPA)
Tietjen, 2018 Bengamide A NF-κB signaling CEM CD4+T cells A total of 252 screened compounds from marine invertebrates [153]
Flavopiridol CDK9 inhibitors Flavanoids [154]
Other Approaches
Zhu, 2015 CRISPR/Cas9 HIV-1 silencing with gRNAs for pol and rev J-lat 10.6 reactivated with TNF-α and quantified viral release in the supernatant NA * [130]
MG1—Maraba Virus Killing of latent infected cells Latent infected derived U937 macrophages and primary CD4+T cells infected in vitro NA * [137]
Mann, 2020 ACT-VEC—polyvalent virus B-clade derived Reactivation of latent HIV Ex vivo exposure of primary latent infected CD4+T cells from PLWH to ACT-VEC NA * [138]

8. Clinical Trails

According to Health Canada, there are 74 clinical trials related to HIV-1 (website:; accessed on 13 January 2023). Of them, only four evaluate a treatment to reduce the reservoir size in PLWH. In 2006, Routy et al. carried out a clinical trial [155,156] based on the evidence that chromatin remodeling plays a role in HIV-1 latency [157]. They performed an open-label, randomized clinical trial to evaluate the effect of Valproic acid (VPA) in combination with cART on the HIV-1 reservoir size as VPA is a histone deacetylase inhibitor. They determined the reactivation of the HIV-1 provirus after 16 or 48 weeks of daily administration of 1000 mg of VPA plus cART. The study included 42 PLWH, all with suppressed viral load for at least a year and a CD4+ T cell count of at least 200 cells/mm3. They observed a decline in the number of latently infected cells after 16 weeks of VPA+cART treatment, but there were no statistical differences compared with control conditions (cART-only) or with 48 weeks of co-treatment [156] (NCT00289952).
The recombinant growth hormone has been a treatment to improve immune function and CD4+ T cell reconstitution in PLWH under cART [158]. In 2017, a proof-of-concept study evaluated the effect of the recombinant human growth hormone (rhGH) on the size of the HIV-1 reservoir (NCT03091374). They assessed if the combinatory treatment of cART and rhGH can improve PLWH CD4+ T cell function and reduce HIV-1 reservoir size. They co-treated 22 PLWH with 3 mg/day of rhGH on top of cART for 24 weeks, followed by half the dose of rhGH for 24 additional weeks. All patients achieved viral suppression for at least two years and a CD4+ T cell count of at least 350 cells/mm3. Up to date, no results regarding the treatment efficacy have been released.
PLWH under prolonged cART can develop metabolic complications that contribute to persistent immune activation related to a low CD4+/CD8+ T cell ratio [159]. T cell immunometabolism regulates cell proliferation [160]; therefore, improving this can enhance T cell function and control the size of the HIV-1 reservoir [161,162]. Trautmann et al. showed that HIV-1-specific CD8+ T cells have an altered metabolic state related to immune activation and exhaustion [163]. In 2018, Routy et al. set up a clinical trial to evaluate metformin as an immunometabolic agent, combined with cART, to reduce the HIV-1 reservoir in PLWH [31]. Metformin, a well-tolerated drug commonly used to treat type II diabetes [164], inhibits mTOR signaling by activating the AMP-activated protein kinase (AMPK) pathway, promoting autophagy and improving CD4+ T cell counts in diabetic PLWH under cART [161,162].; They recruited 22 nondiabetic PLWH with suppressed viral load for at least three years and a CD4+/CD8+ T cell ratio below 0.7. They treated them with 500 mg of metformin plus cART for 12 weeks, followed by an additional 12 weeks of only cART. The study aimed to evaluate and compare the reservoir size and CD4+/CD8+ T cell ratio at the baseline, as well as 12 and 24 weeks after co-treatment initiation (NCT02659306). Unfortunately, metformin treatment did not decrease the amount of integrated HIV-1 DNA or the reservoir size measured by TILDA in CD4+ T cells from peripheral blood mononuclear cells (PBMCs), even though 8/13 study participants showed a reduction in the HIV-1 RNA/DNA ratios [165].
Last, a previous study reported that the simian immunodeficiency virus (SIV) preferentially infected CD4+ T cells that express the α4β7 integrin receptor on their surface. This receptor is a lymphocytic homing receptor that is involved in cell trafficking to the GALT, a site where HIV-1 leads to a severe depletion of CD4+ T cells during acute infection [166,167]. Byrareddy et al. observed that targeting CD4+ T cells with a monoclonal antibody against α4β7 (Vedolizumab) improved viral remission and decreased the viral load in the GALT of SIV-infected macaques during two years [166]. In 2020, McGuinty et al. developed a pilot study to assess the translation of this treatment with Vedolizumab in PLWH [168]. They enrolled 12 patients under suppressive cART for at least two years and a CD4+ T cell count of at least 500 cells/mm3. Subjects were divided into three groups and treated with a low, middle, or high dose of Vedolizumab (75 mg, 150 mg, and 300 mg, respectively), administered once a month for five months, followed by seven months of no treatment. Two months after the first administration, subjects might stop cART and proceed only with the administration of Vedolizumab (NCT03147859). Samples might be collected at the baseline and at the fifth and thirteenth month after treatment initiation to assess HIV-1 viral load and measure the reservoir size in GALT. No results from this clinical trial are available at the time of publication.

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