Selective BCL-XL Antagonists Eliminate Infected Cells from a Primary Cell Model of HIV Latency but not from Ex Vivo Reservoirs

HIV persists, despite antiviral immune responses and effective antiretroviral therapy, in viral reservoirs that seed rebound viremia if therapy is interrupted. Previously, we showed that the BCL-2 protein contributes to HIV persistence by conferring a survival advantage to reservoir-harboring cells. Here, we demonstrate that many of the BCL-2 family members are overexpressed in HIV-infected CD4+ T-cells, indicating increased tension between pro-apoptotic and pro-survival family members – as well as raising the possibility that the inhibition of pro-survival members may disproportionately affect the survival of HIV-infected cells. Based on these results, we chose to further study BCL2L1 (encoding the protein BCL-XL), due to its consistent overexpression and the availability of selective antagonists. Infection of primary CD4+ T-cells with either a clinical isolate, a CCR5-tropic strain, or a CXCR4-tropic strain of HIV resulted in increased BCL-XL protein expression; and treatment with two selective BCL-XL antagonists, A-1155463 and A-1551852, led to disproportionate cell death compared to uninfected CD4+ T-cells. In a primary cell model of latency, both BCL-XL antagonists drove significant reductions in total HIV DNA and in infectious cell frequencies both alone and in combination with the latency reversing agent bryostatin-1, with little off-target cytotoxicity. However, these antagonists, with or without bryostatin-1, or in combination with the highly potent latency reversing agent combination PMA + ionomycin, failed to reduce total HIV DNA and infectious reservoirs in ex vivo CD4+ T-cells from ART-suppressed donors. Our results add to growing evidence that bonafide reservoir-harboring cells are resistant to multiple “kick and kill” modalities - relative to latency models - and uncover BCL-XL antagonists as a facile approach to probing mechanistic underpinnings. We also interpret our results as encouraging of further exploration of BCL-XL antagonists for cure, where combination approaches may unlock the ability to eliminate ex vivo reservoirs.


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HIV persists, despite antiviral immune responses and effective antiretroviral therapy, in 24 viral reservoirs that seed rebound viremia if therapy is interrupted. Previously, we showed 25 that the BCL-2 protein contributes to HIV persistence by conferring a survival advantage 26 to reservoir-harboring cells. Here, we demonstrate that many of the BCL-2 family  bryostatin-1, with little off-target cytotoxicity. However, these antagonists, with or without 39 bryostatin-1, or in combination with the highly potent latency reversing agent combination 40 PMA + ionomycin, failed to reduce total HIV DNA and infectious reservoirs in ex vivo CD4 + 41 T-cells from ART-suppressed donors. Our results add to growing evidence that bonafide 42 reservoir-harboring cells are resistant to multiple "kick and kill" modalities -relative to 43 latency models -and uncover BCL-XL antagonists as a facile approach to probing 44 mechanistic underpinnings. We also interpret our results as encouraging of further

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Although antiretroviral therapy (ART) durably suppresses HIV replication, it cannot 50 eradicate persisting infected cells with integrated HIV proviruses. These cells comprise a 51 'viral reservoir' which seeds viral rebound when ART is interrupted, with the best 52 characterized reservoir being formed in CD4 + T-cells [1]. An important mechanism of 53 persistence is the maintenance of viral latency, particularly in resting memory CD4 + T-54 cells, which prevents death from viral cytopathic effects as well as recognition and 55 elimination by immune effectors, such as cytotoxic T-lymphocytes (CTLs) [2][3][4]. More 56 recent work has additionally uncovered mechanisms by which reservoir-harboring cells 57 may survive both viral-or immune-mediated cytopathicity, with the pro-survival factor BCL-58 2 implicated in both of these scenarios [5]. With respect to viral cytopathicity, one 59 mechanism of death is through cleavage of the host protein procaspase 8 by HIV protease 60 to generate Casp8p41, which drives apoptosis [6]. BCL-2 is able to antagonize this 61 pathway by binding to Casp8p41, and preventing cell death in BCL-2 high cells [7]. With 62 respect to immune-mediated cytopathicity, our group recently made a series of 63 observations which led us to conclude that BCL-2 comprises one mechanism by which 64 HIV reservoir-harboring cells resist elimination by CTL: i) BCL-2 high CD4 + T-cells [22,23]. Also acting to promote apoptosis, the pro-survival BCL-2 homologs BCL-XL and 99 Bfl1/A1 have been reported to be suppressed by HIV Vpu [24]. On the pro-survival side of 100 the interaction, the pro-apoptotic homolog BAD has been shown to be inactivated by HIV

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However, when we applied the same strategies to 'natural' HIV reservoirs in ex vivo CD4 + 125 T-cells from ARV-treated donors, we observed that none of these treatments were 126 sufficient to reduce reservoir sizes. Our study thus identifies BCL-XL overexpression as a 127 survival mechanism that can be targeted in productive-infection to promote death of the

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HIV-infected primary CD4 + T-cells were predominately characterized by overexpression 156 of the BCL-2 family, representing both pro-survival and pro-apoptotic members.

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The above experiment utilized total CD4 + T-cells and thus contained cells of 158 diverse phenotypes and functional profiles. We next extended these results to an 159 analogous experiment using a more homogeneous pool of cells with a central memory 160 (TCM) phenotype, given that these cells are a major cellular reservoir of HIV [31]. TCM were 161 generated by the in vitro priming of naïve CD4 + T-cells, using the methodology of the well-162 characterized cultured TCM model of HIV latency [32,33]. With this more homogeneous 163 cell population, we again observed a general pattern of overexpression of BCL-2 family 164 genes in HIV-infected vs uninfected cells, including the pro-apoptotic members PMAIP1, 165 BMF, and BAK1, and the pro-survival members BCL2, BCL2A1 and BCL2L1 (Fig. 1C).

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As with total CD4 + T-cells, we observed significant underexpression of the pro-survival

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In an initial experiment using model cells generated from an HIV-negative donor, bryostatin-1 alone (3.17-fold and 3.57-fold, respectively), however did not reduce HIV DNA 242 relative to BCL-XL antagonists alone (Fig. 3B). In this initial experiment, treatment with A-243 1331852 was observed to drive a significant reduction in IUPM when used alone (4.52-244 fold, p<0.0001, Fig. 3C). A-1155463 alone also showed a 1.65-fold reduction in IUPM, but 245 this was not statistically significant. Significant reductions in IUPM were also observed in 246 treatments with each of the BCL-XL antagonists + bryostatin-1 (p<0.01), where A-1155463 247 + bryostatin-1 showed a 3.59-fold decrease and A-1331852 + bryostatin-1 showed a 3.90-248 fold decrease relative to bryostatin-1 alone, although these reductions were smaller in 249 magnitude than that observed with ABT-199, which showed a 21.18-fold decrease relative 250 to bryostain-1 alone (Fig. 3C). Thus, these data suggest that both the BCL-XL antagonists 251 were able to reduce the frequency of latently HIV-infected cells generated from an HIV-252 negative donor, either alone or in combination with bryostatin-1.

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To account for potential differences in CD4 + T-cell function from HIV-negative vs  either of the BCL-XL antagonists, used alone or in combination with bryostatin-1. The only significant differences that we observed were increases in IUPM following treatment with 298 bryostatin-1 (p<0.001, Fig. 4B), which we have also reported previously [8]. Thus, this 299 initial experiment with ex vivo CD4 + T-cells from a single donor showed a general lack of 300 reduction in HIV-infected cell frequencies following treatment with BCL-XL antagonists.

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We extended these results by performing HIVE assays with ex vivo resting CD4 + 302 T-cells from 6 long-term ART-suppressed HIV-positive donors ( Table 1). Across this study 303 population, we observed a lack of significant differences in either HIV DNA or IUPM when 304 comparing untreated conditions to treatment with any of the BCL-X L antagonists tested 305 either alone or in combination with bryostatin-1 (Fig. 4C-F), while the increase in IUPM 306 observed with bryostatin-1 treatment in Fig. 4B was found to be consistent across this 307 population (Fig. 4D & F). Additionally, we also tested the same concept in combination 308 with a more potent LRA, PMA and ionomycin, and consistently observed the same lack 309 of effects for the BCL-XL antagonists. Again, we were not able to observe a significant

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Total CD4 + T-cells or T CM CD4 + cells were activated and infected as described above.

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When the infection rate went over 10%, cells were collected and stained with antibodies 456 against human-CD3, CD4, CD8, and p24, with a fixable live/dead dye staining, and then 457 sorted by flow cytometry (SONY9000) directly into 15mL collection tubes for HIV+ (p24 + ) 458 and HIV-(p24 -) cells (Fig. 1A). Total RNA was immediately extracted using the miRNeasy 459 FFPE Kit (Qiagen), and RNA quality and concentration was determined by Agilent

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Following the overnight culture, a small aliquot of cells was mixed with CountBrightTM 511 absolute counting beads and viability dye to obtain a count of total, live CD4 + T-cells by 512 flow cytometry. This viable cell count was used to determine cell numbers for ddPCR and 513 QVOA plating strategies (Fig. 3A).

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HIVE assays with ex vivo resting CD4 + T cells from long-term ART-suppressed donors 516 were set up same as described above, without "cultured TCM" primary cell latency   Table 2; Droplets were prepared using the QX200 Droplet Generator (Bio-Rad) 524 following the manufacturer's instructions. Sealed plates were cycled using the following 525 program: 95°C for 10 min; 40 cycles of 94°C for 30 s, 60°C for 1 min; and 98°C for 10 min.

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Reactions were analyzed using the QX200 Droplet Reader and number of template 527 molecule per μl of starting material was estimated using the Quantalife ddPCR software.

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All subjects were adults, and gave written informed consent prior to their participation.