HIV-1 Vpr drives a tissue residency-like phenotype during selective infection of resting memory T cells

Summary HIV-1 replicates in CD4+ T cells, leading to AIDS. Determining how HIV-1 shapes its niche to create a permissive environment is central to informing efforts to limit pathogenesis, disturb reservoirs, and achieve a cure. A key roadblock in understanding HIV-T cell interactions is the requirement to activate T cells in vitro to make them permissive to infection. This dramatically alters T cell biology and virus-host interactions. Here we show that HIV-1 cell-to-cell spread permits efficient, productive infection of resting memory T cells without prior activation. Strikingly, we find that HIV-1 infection primes resting T cells to gain characteristics of tissue-resident memory T cells (TRM), including upregulating key surface markers and the transcription factor Blimp-1 and inducing a transcriptional program overlapping the core TRM transcriptional signature. This reprogramming is driven by Vpr and requires Vpr packaging into virions and manipulation of STAT5. Thus, HIV-1 reprograms resting T cells, with implications for viral replication and persistence.


Introduction 20
Resting primary CD4+ T cells cannot be efficiently infected by cell-free HIV-1 virions in vitro and 21 require robust mitogenic stimulation to support viral replication 1-3 . This has led to the notion that T 22 cell activation is necessary for HIV-1 replication and that resting T cells are not permissive for HIV-23 1 infection. However, mitogenic T cell activation in vitro results in wide-spread phenotypic and 24 functional reprogramming which dominates changes to gene and protein expression 4-6 , concealing 25 and altering authentic virus-host interactions. This presents a significant challenge for understanding 26 the cellular response to HIV-1 infection and the consequences of the virus-host interaction for HIV-27 1 replication and persistence. While it is clear HIV-1 efficiently infects and replicates in activated T 28 cells, the outcomes of the virus-host interaction with resting T cells has been reported to be cell 29 death 7 or latency 8 . However, previous data demonstrating that HIV-1 cell-to-cell spread is highly-30 efficient and drives widespread changes in protein phosphorylation status in both infected and target 31 cells 9-13 suggested that cell-to-cell spread may overcome the barrier to productive infection of resting 32 T cells. Here, we comprehensively show for the first time that HIV-1 exploits cell-to-cell spread to 33 efficiently infect resting memory CD4+ T cells and have used this to uncover a hithertho unknown 34 consequence of HIV-1 infection for T cell reprogramming driven by the accessory protein Vpr. 35

Results 37
To test whether cell-to-cell spread allows for productive infection of resting T cells, HIV-1 infected 38 Jurkat T cells (Fig. 1a) or primary CD4+ T cells (Fig. 1b) were co-cultured with uninfected resting 39 Fig. 1a-e). We confirmed that CD4+ T cells isolated from peripheral 40 blood display a resting phenotype by staining for Ki67, CD69, HLA-DR and MCM2. (Extended data 41 Fig. 1c-e). Infection of resting target cells in the absence of mitogenic or cytokine activation was 42 measured. Direct co-culture of infected and uninfected cells resulted in significant levels of HIV-1 43 cells also upregulated the TRM marker CXCR6 21 during HIV-1 infection, (Fig. 2g,h and Extended data 100 Fig. 3k,n), as well as increasing the population of CD69+ve cells co-expressing CD49a, PD-1 and 101 CD101 that are also associated with the core TRM signature 21 (Fig. 2i,j and Extended data Fig. 3l). 102

CD4+ T cells (Extended data
As expected for TRMs, we saw no upregulation of CX3CR1 expression (Extended data Fig. 3o) and 103 no transcriptional upregulation of S1PR1 or KLF2 mRNA (Extended data Fig. 5i). Critically, induction 104 of TRM-associated markers did not occur in uninfected Gag-ve bystander cells (Fig. 2k and Extended 105 data Fig.3m,n). By contrast to CD8+ TRM cells, CD103 was barely detectable and not upregulated 106 (Extended data Fig.3p,q), consistent with the observation of limited CD103 expression on CD4+ T 107 cells 21 . Induction of CD69 expression was also concomitant with upregulation of the T RM -associated 108 transcription factor Blimp-1 28-30 (Fig. 2l,m). Similar upregulation of TRM-associated markers were also 109 observed when unstimulated CD4+ T cells from tonsil (Fig. 2n,o) or mediastinal lymph nodes (Fig. 110 2p,q) were infected with HIV-1 via cell-to-cell spread and exposed to IL7 (Fig. 2o,q), demonstrating 111 that induction of TRM-like phenotype also occurs in tissue-derived T cells following HIV-1 infection. 112 Taken together, these data suggest that HIV-1 infection of resting memory CD4+ T cells 113 reprogrammes cells by upregulating expression of TRM-associated marker proteins, and thus induces 114 a phenotype characteristic of tissue residency. 115 HIV-1 expresses four accessory proteins, Vif, Vpu, Vpr and Nef which directly and indirectly 116 manipulate host cell factors to facilitate efficient viral replication in vivo and drive pathogenesis 31 . Co-117

culture of resting target T cells with donor T cells infected with HIV-1 accessory protein mutants 118
showed that deletion of Vpr (HIV-1 ΔVpr) resulted in a complete abrogation of the TRM-like phenotype 119 as evidenced by a lack of CD69 upregulation, and no detection of the CD69+/CXCR6+/CD49a+ 120 triple-positive T RM -like memory population (Fig. 3a,b,d, Extended data Fig.4 and 5a-e). By contrast, 121 deletion of Vpu or Nef did not affect HIV-1 induction of T RM -markers on infected resting T cells (Fig.  122 3a,b, Extended data Fig. 4 and Fig. 5a-e). HIV-1 ΔVif could not be tested because Vif is required to 123 antagonise APOBEC3-mediated viral restriction and allow infection 32 . HIV-1 Vpr is not required for 124 infection of T cells in vitro 33,34 and concordantly, loss of TRM-marker protein induction was not due to 125 lack of infection of target cells by HIV-1 ΔVpr virus, nor reduced Gag expression ( Fig. 3c and  126 Extended data Fig. 5f-h). Critically, Vpr was also required for induction of CD69 expression observed 127 at the mRNA level, as well as induction of CXCR6 and Blimp1 (PRDM1) mRNA (Fig. 3e). As 128 expected, there was no upregulation of S1PR1 or KLF2 mRNA by either HIV-1 WT or ΔVpr virus 129 (Extended data Fig.5i), consistent with their suppression under conditions of TRM induction 21 . HIV-1 130 dependent upregulation of CD69 surface expression was inhibited by Ruxolitinib treatment (Fig. 2d) 131 in a Vpr-dependent manner (Extended data Fig. 5j). Furthermore, HIV-1 infection downregulated the 132 IL7 receptor alpha-subunit (CD127) from the cell surface (Extended data Fig 5k) and transcriptionally 133 (fold change=0.693, adjusted p-value=5.89E-08, Supplementary table 1), indicative of activation of 134 this pathway 35 by HIV-1. This was accompanied by a significant increase in the intracellular levels of 135 phosphorylated transcription factor STAT5 (Extended data Fig. 5j and k). These data are consistent 136 with Vpr manipulating cellular signalling pathways to drive induction of a TRM-like phenotype in 137 response to IL7. Vpr-dependent TRM-like induction was also accompanied by spontaneous 138 production of IFN by infected CD4+ memory T cells (Fig. 3f), in line with the increased capacity of 139 TRM to produce this cytokine 21,36 . Notably, Vpr-mediated induction of a TRM-like phenotype was not 140 inhibited by the integrase inhibitor Raltegravir (Fig. 3g, h) that potently suppressed HIV-1 integration 141 into resting memory CD4+ T cells infected by cell-to-cell spread (Fig. 3i), demonstrating that the TRM-142 like phenotype does not require integration. Of note, the presence of integrated provirus in resting 143 CD4+ T cells (less than or equal to 1 provirus per cell Fig. 3i) further supports the observation that 144 cell-to-cell spread results in resting CD4+ T cell infection (Fig. 1). Collectively, these data identify 145 Vpr as the viral determinant required for upregulation of TRM-associated proteins on HIV-1 infected 146 resting CD4+ T cells. 147 Vpr is a multifunctional protein that is packaged into viral particles and is present during the 148 early stages of infection where it plays an important, but as yet poorly-defined role in HIV-1 149 pathogenesis. Amongst the best-defined functions of Vpr are its ability to a) bind the Cul4A-DDB1 150 (DCAF1) complex (leading to an interaction with the ubiquitinylation and proteasomal machinery); b) 151 induce G2/M cell-cycle arrest and; c) drive apoptosis in infected cells [37][38][39][40][41] . We abrogated these 152 functions individually by introducing the mutations Q65R, S79A or R80A into Vpr in the context of 153 virus and confirmed that each Vpr mutant is packaged into virions (Fig. 3j). Co-culture of resting 154 memory target T cells with HIV-1+ T cells infected with different Vpr mutants revealed that the Vpr 155 mutants S79A or R80A (inhibits cell cycle arrest) behaved similarly to WT virus and did not induce 156 CD69 and CXCR6 upregulation ( Fig. 3k-m). By contrast, Q65R (that is most closely associated with 157 loss of DCAF1 binding) was unable to induce a TRM-like phenotype following infection of target cells, 158 behaving like ΔVpr virus in these experiments ( Fig. 3k-m). 159 Next we performed transcriptional profiling by RNA-Seq analysis of flow-sorted cells infected 160 with HIV-1 WT or ΔVpr virus by cell-to-cell spread. Figure 4 shows that HIV-1 infection induced 161 widespread changes to gene expression in resting memory T cells when compared to uninfected 162 cells (232 differentially expressed genes (DEG), fold change >1.2, adjusted p-value<0.01) (Fig. 4). 163 Hierarchial clustering and principal component analysis revealed that the gene expression patterns 164 in response to HIV-1 WT infection were clearly distinct from those induced following infection with 165 ΔVpr virus (Fig. 4 a- Fig. 4e). In fact, much of the transcriptional response to 169 HIV-1 infection was regulated by Vpr, as evidenced by changes in DEG in the presence and absence 170 of Vpr (Fig. 4f). The requirement for Vpr in driving many of the changes to DEG was also observed 171 in response to IL7 (Fig. 4d, Supplementary table 2 and 4, and Extended data Fig. 6a). Consistent 172 with Vpr manipulating the T cell response to HIV-1 infection (Supplementary table 5  and 8). This was further evidenced by Upstream Regulator analysis that showed significant 178 enrichment for genes associated with cytokine signalling and transcriptional regulators that were 179 again largely Vpr-dependent ( Fig. 4j and k, and Extended data Fig. 6). Taken together, these data 180 reveal that HIV-1 induces dramatic reprogramming during infection of resting memory CD4+ T cells 181 that is driven largely by Vpr. 182 Tissue residency of T cells has been associated with a 31-gene core transcriptional 183 signature 21 . We took advantage of this dataset and our RNAseq analysis to determine whether this 184 core TRM signature was enriched in our transcriptome of HIV-1 infected resting memory T cells. 185 Hierarchical clustering of our data, compared to the core signature of TRM cells (CD69+ve T cells 186 isolated from human lung and spleen) 21 from Kumar et al, showed that HIV-1 infected memory T 187 cells exposed to IL7 grouped distinctly and clustered with CD69+ve TRM cells (Fig. 5a, 188 Supplementary table 9) distinct from non-TRM T cells (CD69-ve T cells isolated from tissue and blood 189 from Kumar et al). We further corroborated this finding by calculating a TRM enrichment score based 190 on the published core transcriptional signature, which showed that HIV-1 infected resting memory T 191 cells (both +/-IL7) harbour a higher TRM signature score, significanly different from non-TRM T cells, 192 approximating more closely to that of bona fide TRM cells (Fig. 5b). Critically, this was 193 with mock and ΔVpr infected cells showing an enrichment score that was not statistically different to 194 non-TRM. Taken together, these data demonstrate that HIV-1 induces both a phenotypic and 195 transcriptional TRM-like signature in resting T cells via the accessory protein Vpr. 196 197 Discussion 198 Our discovery that resting CD4+ T cells can be productively infected by cell-to-cell spread, allowing 199 for viral integration, replication and dissemination, transforms our ability to determine how T cells 200 respond to and suppport HIV-1 replication without confounding activation-induced changes. 201 Recently, it has been reported that cell-to-cell spread can also facilitate latent infection of resting T 202 cells without productive infection 8 . Together, these two studies highlight the distinct advantages of 203 co-culture models (that do not require mitogenic, experimental stimulation of T cells to drive infection) 204 to study native HIV-1-host cell interactions and the cellular response to infection. 205 Here we have employed our co-culture model to show that HIV-1 infection of resting memory 206 T cells induces a TRM-like phenotype evidenced by upregulation and co-expression of TRM-associated 207 markers on infected cells and induction of a core T RM transcriptional signature. HIV-1 establishes 208 cellular and tissue reservoirs (both active and latent) that ultimately prevent cure with antiretroviral 209 therapy. Importantly, TRM cells are long-lived and are thought to be largely confined to tissue 42 210 providing an alternate model for a tissue-associated reservoir driven by the virus itself. Our results 211 suggest that HIV-1 persistence and the establishment of tissue reservoirs may be driven, in part, 212 through direct viral induction of a TRM-like phenotype via transcriptional reprogramming. Recently, 213 TRM in cervical tissue were found to be preferentially infected by HIV-1 and can harbour an HIV-1 214 reservoir in vivo 43 . The relative contribution of pre-existing versus HIV-1 induced TRM cells to viral 215 reservoirs and their relative abundance in different anatomical compartments in vivo remains to be 216 quantified, but we expect TRM cells harbouring virus to be important contributors to viral persistence. 217 In light of these findings it is possible that HIV-1 infected cells circulating in peripheral blood may in 218 fact represent cells that have failed to become part of the tissue reservoir, leading to an 219 underestimation of the true viral burden. Having shown that HIV-1 infection of resting T cells by cell-220 to-cell spread results in productive infection, we hypothesise that induction of a TRM-like phenotype 221 in infected cells may also play additional roles in establishing and maintaining viral reservoirs by 222 sequestering infected cells in tissue sites where susceptible target T cells are in abundance, thus 223 supporting localised viral replication. Indeed we have shown that infected resting memory T cells 224 support spreading infection to disseminate virus. Given the importance of TRM cells as a population 225 that are increasingly recognised to be critical in providing localised immunity and 226 immunosurveillance 20,30 , future work should focus on understanding the contribution of HIV-1 227 induced TRM-like cells in pathogenesis and persistence. 228 It is now emerging that committed TRM precursors, imprinted with the capacity to become 229 mature TRM pre-exist in blood and that when exposed to the appropriate cues in tissues or ex vivo 230 can become tissue-resident 22,23 . Thus the ontogeny, derivation and maintenance of T RM cells 231 appears more complex that initially appreciated. Our discovery that HIV-1 induces a T RM -like 232 phenotype in CD4+ T cells provides an opportunity to gain new understanding of mechanisms behind 233

CD4+ TRM induction and maintainance. 234
We found that HIV-1 infection of resting memory T cells was associated with striking 235 transcriptional reprograming that was licenced by Vpr, thus identifting a novel function for this 236 enigmatic HIV accessory protein. Notably, HIV-1 induction of a TRM-like phenotype via Vpr was 237 accompanied by induction of a TRM transcriptional signature that aligned closely with a published 238 core TRM signature 21 . Vpr-deletion not only abolished induction of this TRM signature, but also many 239

HIV-1 induced changes to gene expression following infection of resting T cells. This is in keeping 240
with wide-spread proteome remodelling by Vpr in activated T cells 44 , but suggests that these 241 changes may be driven in part by a hitherto unappreciated role for Vpr in modulating the host cell 242 gene expression profile. Whether this reflects wide-spread epigenetic changes mediated by Vpr or 243 manipulation of key upstream regulators remains to be determined. Our data show HIV-1 Vpr 244 modulates T cell responsiveness to external stimuli by manipulation of immune signalling pathways, 245 including innate and inflammatory responses. This is particularly intriguing and suggests HIV-1 246 manipulates immune signalling pathways to benefit the virus, in this case by priming resting memory 247 T cells for TRM-like induction. Vpr-mediated induction of TRM-like phenotype was dependent on 248 residue Q65 and Vpr is reported to drive wide-spread remodelling of the cellular proteome via its 249 recruitment of DCAF1 through Q65 44 . Whether this requirement for Q65 in induction of a TRM-like 250 phenotype is DCAF1-dependent or not remains unclear because DCAF1 knockdown in primary T 251 cells made cells hyper-responsive to HIV-1 induced cell death (Extended data Fig. 7). Thus we 252 cannot at present formally exclude other functions of Vpr Q65 in the process of TRM-induction. 253 Notably, a rare case of laboratory-derived infection with Vpr-defective HIV-1 was 254 characterised by markedly delayed seroconversion, suppressed viremia and normal CD4+ T cell 255 counts 45 , consistent with reduced pathogenesis and failure to establish and maintain a significantly 256 large tissue reservoir. We envisage therapeutic targeting of Vpr to manipulate persistence and 257 pathogenesis. In order to achieve an HIV-1 cure it is essential to understand the nature and

Plasmids and virus production 396
The HIV-1 clone pNL4.3 was obtained from the CFAR, NIBSC (cat# 2006 All virus stocks were produced by plasmid transfection of HEK 293T cells with Fugene 6 (Promega). 412 Supernatants were harvested at 48h and 72h, filtered, DNase treated, purified and concentrated by 413 ultracentrifugation through a 25% sucrose cushion and resuspended in RPMI1640 with 10% FBS. 414 Viral titres were determined by measuring reverse transcriptase activity by SG-PERT assay 51 . 415

Flow cytometry and FACS 449
For flow cytometry analysis, cells were washed in PBS and stained with fixable Zombie UV 450 Live/Dead dye, Aqua Live/Dead dye or NIR Live/Dead dye (Biolegend) for 5 min at 37C. Excess 451 stain was quenched with FBS-complemented RPMI. When tonsil and lymph node lymphocytes were 452 used, Live/Dead staining was quenched using human AB serum (Sigma) in RPMI. Cell surface 453 staining was performed in PBS, complemented with 20% Super Bright Staining Buffer 454 (ThermoFisher) when appropriate, at 4C for 30min. Unbound antibody was washed off thoroughly 455 and cells were fixed with 4% FA or PFA before intracellular staining. For intracellular detection of 456 IFN in infected target CD4+ T cells after 72h of cell-to-cell spread, cells were treated throughout the 457 co-culture with IL7 and Brefeldin A (Biolegend) treated for 6h before surface staining and fixation. Gag core antigen (FH190-1-1, Beckman Coulter; PE, FITC). All samples were acquired on either an 473 BD Fortessa X20 or LSR II using BD FACSDiva software and analyzed using FlowJo v10 (Tree 474 Star). FACS sorting was performed with a BD FACSAria III or BD FACSAria IIu Cell Sorter. Cells 475 were either lysed immediately in RLT lysis buffer (Qiagen) with 1% β-mercaptoethanol (Sigma) and 476 stored at -80C for later RNA extraction or resuspended in RPMI supplemented with 20% FBS and 477 10IU/ml IL2 and used immediately. 478

Quantification of HIV-1 integration 489
To quantify integration of HIV-1 in resting T cells, nested Alu-gag quantitative PCR was performed 490 as previously described 53 . Briefly, DNA was isolated from FACS sorted infected resting CD4+ 491 memory T cells after 72h of cell-to-cell spread using the Qiagen Blood Mini Kit. 492 Integrated DNA was pre-amplified using 100nM Alu fw primer, 600nM HIV-1 Gag rv primer, 0.2mM 493 dNTP, 1U Phusion Hot Start Flex (Promega), and 45ng DNA in 50μl reactions. Cycling conditions 494 were: 94˚C for 30s, followed by 40 cycles of 94˚C for 10s, 55˚C for 30s, and 70˚C for 2.5min. For 495 quantitation of HIV-1 integration, a second round real-time quantitative PCR was performed using 496 the pre-amplified DNA. These samples were run alongside a standard curve of known dilutions of 497 CEM cells containing integrated HIV-1 DNA. Reactions contained 0.25μM of RU5 fw and rv primers, 498 and 0.2μM probes, 1x Qiagen Multiplex Mastermix, and 10μl pre-amplified DNA. Cyclin conditions 499 were: 95˚C for 15min, followed by 50 cycles of 94˚C for 60s and 60˚C for 60s. 2LTR circles were 500 measured by quantitative PCR 54 . Reactions contained 150ng DNA, 10μ 2LTR fw and rv primers, 501 10μM probe and 1x TaqMan Gene Expression Master Mix (ThermoFisher). Cycling conditions were: 502 95˚C for 15min, followed by 50 cycles of 95˚C for 15s and 60˚C for 90s. Reactions were performed 503 using 7500 Real-Time PCR System (Applied Biosystems). The following primers and probes were 504 Technologies) and fragment analysis using the D1000 High Sensitivity assay on the 4200 543 Tapestation (Agilent Technologies). 544

RNA
sequencing data was quality assessed using FASTQC 545 (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) before and after low-quality and 546 adapter trimming using Trimmomatic 55 . Filtered reads were then pseudo-mapped using Kallisto 56 to 547 the transcriptome available in Ensembl v.101 (http://aug2020.archive.ensembl.org/index.html). Per-548 transcript counts were imported and aggregated per gene using the TXimport R package 57 . The 549 DESeq2 package 58 was used for data normalisation, outlier detection and differential gene TPM values <0.001 were adjusted to 0.001 as a lower limit of detection. These data were aligned to 563 the transcriptomic data from the present study using gene symbol in an integrated Log2 transformed 564 data matrix and subjected to batch correction by study using Combat 62 . Expression of selected genes 565 previously identified to be up and downregulated in TRM 21 were used to cluster the samples in both 566 studies using 1-Spearman rank correlation with average linkage in ClustVis 60 . A transcriptional 567 signature score for TRM was derived from the difference between the sum of up and down-regulated 568 genes in TRM in the previously published signature. This score was used to evaluate the relative 569 similarity of each transcriptome data set in the present project to TRM and non-TRM data. 570 571 572

Statistical analysis 573
Statistical analysis was performed using GraphPad Prism. Normally distributed data was analysed 574 for statistical significance by two-tailed t-tests (when comparing two groups) or one-way ANOVA 575 with Bonferroni or Dunnett's post-test (when comparing more than two groups). Data show the mean 576 +/-the S.E.M with significance shown on the figures. Where appropriate, the median+IQR is shown 577 and Kruskall-Wallis test was used to compare groups. Significance levels were defined as *, P < 578 0.05; **, P < 0.01 and ***, P < 0.001. Mol. Ther. 15, 1947Ther. 15, -1954Ther. 15, (2007.