key: cord-0274607-7w2zxoxw
authors: Shytaj, Iart Luca; Procopio, Francesco Andrea; Tarek, Mohammad; Carlon-Andres, Irene; Tang, Hsin-Yao; Goldman, Aaron R.; Munshi, MohamedHusen; Forcato, Mattia; Leskov, Konstantin; Ye, Fengchun; Lucic, Bojana; Cruz, Nicolly; Singh, Amit; Bicciato, Silvio; Padilla-Parra, Sergi; Lusic, Marina; Diaz, Ricardo Sobhie; Alvarez-Carbonell, David; Savarino, Andrea
title: Glycolysis downregulation is a hallmark of HIV-1 latency and sensitizes infected cells to oxidative stress
date: 2020-12-31
journal: bioRxiv
DOI: 10.1101/2020.12.30.424810
sha: d7b7da663c749a59ece101ae3d26fa2a5113daa4
doc_id: 274607
cord_uid: 7w2zxoxw

HIV-1 infects lymphoid and myeloid cells, which can harbor a latent proviral reservoir responsible for maintaining lifelong infection. Glycolytic metabolism has been identified as a determinant of susceptibility to HIV-1 infection, but its role in the development and maintenance of HIV-1 latency has not been elucidated. By combining transcriptomic, proteomic and metabolomic analysis, we here show that transition to latent HIV-1 infection downregulates glycolysis, while viral reactivation by conventional stimuli reverts this effect. Decreased glycolytic output in latently infected cells is associated with downregulation of NAD+/NADH. Consequently, infected cells rely on the parallel pentose phosphate pathway and its main product, the antioxidant NADPH, fueling antioxidant pathways maintaining HIV-1 latency. Of note, blocking NADPH downstream effectors, thioredoxin and glutathione, favors HIV-1 reactivation from latency in lymphoid and myeloid cellular models. This provides a “shock and kill effect” decreasing proviral DNA in cells from people-living-with-HIV/AIDS. Overall, our data show that downmodulation of glycolysis is a metabolic signature of HIV-1 latency that can be exploited to target latently infected cells with eradication strategies.

Decades after its outbreak, the HIV/AIDS pandemic remains one of the main causes of morbidity and mortality of humankind, leading to almost one million victims per year (source: UNAIDS). Moreover, due to the severe medical and economic crisis caused by Coronavirus Disease 2019 , adherence to and availability of antiretroviral therapies (ART) is decreasing in areas where HIV/AIDS prevalence is particularly high (Jiang et al, 2020; Jewell et al, 2020) . This worsening of the death toll highlights the fragility of current therapeutic approaches, based on lifelong ART administration. Therefore, a cure for HIV/AIDS is an unmet medical need of growing importance for people-livingwith-HIV/AIDS (PLWH). The quest for a cure is hampered by persistence of transcriptionally silent proviruses within latently infected cells, which render these cells hard to discriminate from their uninfected counterparts (Finzi et al, 1999) . Latent HIV-1 DNA can be mainly found in viral reservoirs such as CD4 + T-cells (Van Lint et al, 2013) , however myeloid cells (in particular microglia) can also contribute to persistence of the infection during ART (Sattentau & Stevenson, 2016) . Pinpointing molecular features to allow selective targeting of latently HIV-1 infected cells would represent a significant, and perhaps decisive, step in the quest for an HIV/AIDS cure.

A possible approach to reach this goal is the investigation of the metabolic pathways exploited by the retrovirus to actively replicate and enter a latent state. In this regard, it is interesting to point out that the cells more susceptible to HIV-1 infection are characterized by an increased glycolytic rate (Valle-Casuso et al, 2019) . Cellular activation, leading to increased glycolysis, is necessary for active HIV-1 replication; of note, in CD4 + T-cells and monocytes of HIV-1 infected individuals, glucose consumption is increased and the expression of the glucose transporter GLUT-1 is upregulated (Palmer et al, 2014a (Palmer et al, , 2014b .

Conversely, reports on the effect of HIV-1 infection on glycolysis have been sparse and, in some respects, conflicting. Starting from the 1990s, studies have shown that cells infected with HIV-1 display decreased levels of NAD + , an important substrate of glycolytic reactions (Murray et al, 1995) , and that supplementation of the NAD + precursor nicotinamide influences viability of productively HIV-1 infected cells (Savarino et al, 1996) . Moreover, after ART implementation, PLWH showed to be more susceptible to hyperglycemia than the general population (Dubé et al, 1997) . On the other hand, upregulated glucose metabolism was reported to favor apoptosis of infected CD4 + T-cells (Hegedus et al, 2014) . Although these combined sets of data strongly support a role of active glycolysis in determining susceptibility to HIV-1 infection as well as an altered glucose metabolism in PLWH, the role of glycolysis in viral latency, and therefore in possible curing strategies, has as yet remained unclear.

The importance of understanding the relationship between cell metabolism and the infection is emphasized by the possible first long-term remission of HIV-1 without bone marrow transplantation (Abstract Supplement Oral Abstracts from the 23rd International AIDS Conference 2020). This individual had been treated with a combination of intensified ART and the NAD + precursor nicotinamide, thus suggesting a possible contribution of glycolysis regulation in the therapeutic result obtained. The anecdotal character of this case, however, renders difficult the drawing of definitive conclusions.

Indirect evidence of an interplay between glycolysis and HIV-1 latency can also be drawn by the dysregulation of redox pathways, which are intertwined with glycolytic metabolism in several cell types and pathological conditions (Locasale & Cantley, 2011; Kondoh et al, 2007) . This interconnection might be relevant, as we recently showed that HIV-1 infection leads to enhancement of antioxidant defenses in primary CD4 + T-cells (Shytaj et al, 2020) . HIV-1 infection causes an initial oxidative stress (Daussy et al, 2020) , which then leads to the nuclear translocation of the master antioxidant transcription factor Nrf2. This translocation in turn induces transcription of several proteins involved in antioxidant response, including glucose 6-phosphate dehydrogenase (G6PDH), which diverts glucose 6-phosphate from the glycolytic pathway to the pentose cycle, responsible for production of the antioxidant NADPH.

Therefore, elucidating the specific glycolysis/redox state interconnection during HIV-1 infection would be of pivotal importance for understanding the molecular events which lead infected cells to either die or establish a latent infection.

Herein, we combine transcriptomic, proteomic, and metabolomic datasets, including single cell analyses, to show that, during transition to HIV-1 latency, glycolysis is downregulated. In line with this, our results show that latently infected cells able to undergo HIV-1 reactivation are also characterized by prompter reactivation of glycolysis. Moreover, we show that downregulation of glycolysis in latently infected cells is accompanied by higher reliance on the antioxidant thioredoxin (Trx) and glutathione (GSH) systems for cell survival. Our results highlight the possibility to exploit glycolytic imbalances induced by HIV-1 infection for the elimination of retrovirally infected cells. This result may improve our knowledge of pathways that can be targeted by strategies aimed at eradicating HIV/AIDS.

To study transcriptomic profiles upon infection, we used microarray and RNA-Seq data sets generated in primary CD4 + T-cells infected with HIV-1 pNL4-3 . The cellular model employed is based on longitudinal sample collection to cover different time points, from early HIV-1 infection [day 3 post-infection (p.i.)] to peak retroviral replication (days 7-9 p.i.) and latency/survival of infected cells (day 14 p.i.). The detailed features and validations of this cellular model have been described previously elsewhere (Shytaj et al, 2020) .

Microarray results highlighted significant downregulation of the glycolytic pathway in infected cell cultures, which was independently evidenced by Gene Set Enrichment Analysis [GSEA; (Subramanian et al, 2005) ] either using a customized gene set comprising enzymes involved in human glycolysis (henceforth, HUMAN-GLYCOLYSIS) or using the Reactome or Biocarta databases ( Figure 1A ;

Additional file 1). Entrance of the infected cells into a hypometabolic state was also shown by downregulation of glycolysis-independent transcriptional and translational pathways, although downregulation of these pathways did not reach the same level of convergence among the databases examined as compared to the glycolytic pathway (Additional file 1). Moreover, among the pathways more heavily perturbed by HIV-1 infection, there was the interferon pathway (Additional file 1), as expected, and pathways associated with both apoptosis and cell cycle, in line with the fact that, in an HIV-1 infected cell cultures, some cells succumb to infection and others survive developing a proviral latent state.

We then analyzed in detail the glycolytic enzymes of the pathway HUMAN-GLYCOLYSIS ( Figure 1B ). The glycolytic enzymes characterized by significantly downregulated transcription upon infection were hexokinase 2 (HK2), glucose 6-phosphate isomerase (GPI), phosphofructokinase liver type (PFKL), aldolase fructose-bisphosphate C (ALDOC), triosephosphate isomerase 1 (TPI1) and enolase 2 (ENO2), thus suggesting a broad downregulation of the glycolytic pathway ( Figure 1B ). In particular, the highly significant downregulation of GPI suggests a glycolysis-specific effect, as this enzyme commits metabolites to the glycolytic, rather than to the alternative pentose-phosphate pathway.

To expand these analyses, we explored an RNA-Seq dataset derived from the same primary CD4 + T-cell model, which was previously published elsewhere (Shytaj et al, 2020) . In this dataset, the number of donors and time points was higher, allowing the study of the expression of glycolytic enzymes during each infection stage ( Figure 1C ). In line with the microarray results, differential gene expression analysis of RNA-Seq data (DESeq2) (Love et al, 2014) highlighted significant downregulation of glycolysis in infected cells cultures, which was initiated at peak HIV-1 replication (7-9 days p.i.) and persisted after retroviral replication had ceased (14 days p.i.) ( Figure 1C ). As seen in microarray analysis, enzyme transcriptional downregulation covered all main steps of glycolysis, and the RNA-Seq data set further suggested that various isoforms, in particular of PFK, might contribute differently to glycolysis downregulation during productive or latent infection [PFK-platelet (P); adjusted p value = 0.04 at 7 days p.i. PFK-muscle (M); adjusted p value = 0.04 at 14 days p.i. respectively]. Finally, analysis of a previously published proteomic dataset of the same CD4 + T-cell model (Shytaj et al, 2020) further corroborated the downregulating effect of HIV-1 on glycolysis, confirming significant downmodulation of GPI, PGK1 and TPI1 (Additional file 2).

Overall, these data show that HIV-1 infection during its transition to latency is associated with downregulated expression of glycolytic enzymes, in particular those catalyzing the early steps of glycolysis.

The aforementioned results prove that glycolysis downregulation is initiated during productive infection and accompanies HIV-1 latency establishment. We then proceeded to specifically investigate the transcriptional regulation of the HUMAN-GLYCOLYSIS pathway upon the reverse process, i.e. reactivation from latency.

To this aim, we first analyzed two single cell RNA-Seq (scRNA-Seq) datasets independently published by the groups of Ciuffi and Nussenzweig, respectively (Golumbeanu et al, 2018; Cohn et al, 2018) . In the first dataset, primary CD4 + T-cells infected with pseudotyped HIV-1-GFP/VSVG had been sorted according to GFP expression and allowed to revert to latency (Golumbeanu et al, 2018) . Latently infected cells had then been either left untreated or subjected to HIV-1 reactivation by strong (α-CD3/CD28 antibodies) or weak stimuli [suberoyl anilide hydroxamic acid (SAHA)]. Eventually, the transcriptomic profile was analyzed by scRNA-Seq (Golumbeanu et al, 2018) . Using principal component analysis, the authors identified two cell clusters, which were less (cluster 1) or more (cluster 2) susceptible to HIV-1 reactivation (Golumbeanu et al, 2018) . We analyzed the expression of the enzymes of the glycolytic pathway in both clusters and found that glycolytic enzymes were downregulated in cells of cluster 1 ( Figure 1D ). Interestingly, this relative downregulation, already visible in basal conditions, was maintained upon treatment with either anti-CD3/CD28 antibodies or SAHA ( Figure 1D ). Moreover, GPI expression was lower in the cell subpopulation less responsive to HIV-1 reactivation as compared to the more susceptible cell subpopulation ( Figure 1E When infected cells were compared to their uninfected counterparts incubated under similar conditions, results showed a clear pattern of GPI downregulation being more significant in latent than in productive infection and accompanied by a more pronounced downregulation of the early glycolytic enzymes in the former (Additional File 3). Finally, sc-RNA-Seq profiling of HC69 cells highlighted a significantly positive correlation between baseline HIV-1 expression and key glycolytic enzymes, including GPI, in the subset of cells in which proviral transcription was detectable ( Figure 1G ,H). Conversely, treatment with dexamethasone (DEXA), which is a known glycolysis inhibitor (Ma et al, 2013) , decreased both the proportion of HC69 cells expressing the transcripts of the glycolytic pathway and the baseline percentage of cells expressing HIV-1 transcripts (Additional file 4).

Taken together, these results show that low expression of early glycolytic enzymes, in particular GPI, is associated with HIV-1 latency maintenance, and that at least partial restoration of glycolysis is required for latency disruption. Metabolite enrichment analysis showed significant changes in the glycolysis/gluconeogenesis pathway in both latently and productively infected cells as compared to their uninfected counterparts ( Figure 2C ,D).

We then proceeded to analyze the glycolytic metabolites separately.

Results from latently infected cells showed significantly decreased levels of the metabolite produced by PFK, i.e. fructose 1,6 bisphosphate ( Figure 2E ). Since the PFK enzyme acts immediately downstream of GPI, downregulation of fructose 1,6 bisphosphate is in line with the reduced expression of GPI in latently infected cells, as shown by both RNA-Seq and scRNA-Seq analysis ( Figure 1 ). There was also a trend towards reduction of glyceraldehyde 3-phosphate, a product of ALDO, the enzyme acting immediately downstream of PFK ( Figure 2E ). These results, again, support the view that latently infected cells are characterized by a block in the early glycolytic steps.

Instead, the pattern observed in cells reactivated from latency, as compared to uninfected (C20) cells subjected to the same HIV-1 reactivating stimulus, showed a less clear impairment of glucose metabolism, with parameters indicative of glycolysis downregulation (a relative paucity of the initial glycolytic metabolites) and parameters indicative of glucose consumption (significantly decreased Dglucose levels and decreased ADP levels) ( Figure 2F ).

We then explored the connection between decreased glycolytic metabolism and other, intertwined, metabolic pathways highlighted by the aforementioned enrichment analysis ( Figure Network analysis supports the view that these cells rely on glutamate metabolism as an alternative source of pyruvate for fueling ADP utilization through the Krebs cycle ( Figure 2H ).

Among the most significantly enriched pathways, we further considered metabolism of antioxidants (Additional file 5), due to its well described interconnection with glycolysis and NAD + , via the pentose pathway (Grant, 2008) , and its relevance in the establishment and maintenance of HIV-1 latency (Shytaj et al, 2020; Benhar et al, 2016) . Network analysis revealed a likely connection between NADH decrease and redox pathways in latently infected cells ( Figure 2G ). Accordingly, increased levels of oxidized glutathione, consistent with higher oxidative stress upon infection, as previously described (Shytaj et al, 2020) , were associated with a decrease not only in NADH but also in its precursor NAD + . The HIV-1related NAD + consumption was also associated with altered nicotinamide metabolism (Additional files 5,6) and with a trend towards increased expression of proteins consuming NAD + /NADH ( Figure 2G ).

Among the most up-or downregulated transcripts (> 1 or < -1 Log 2 fold) involved in this pathway were G6PD and PARP2 in latent infection, the former being the enzyme initiating the pentose phosphate pathway and the latter being a NAD + -consuming enzyme involved in repair of oxidative-stress induced DNA damage (Chevanne et al, 2007 ) ( Figure 2G ). Moreover, productively, but not latently, infected cells were characterized by higher levels of sirtuin (SIRT)1 and 3, which are known to favor HIV-1 replication (Pagans et al, 2005) and to counteract mitochondrial oxidative stress, respectively (Singh et al, 2018) ( Figure 2G ). Productively infected cells also displayed decreased expression of CD38, an ectoenzyme responsible for hydrolysis of extracellular NAD + and intracellular recycling of its components, ADPribose and nicotinamide (Savarino et al, 2000) ( Figure 2G ).

Overall, these data show that early glycolytic metabolites are downregulated in both latently and productively HIV-1 infected cells, as compared to uninfected cells. Moreover, the results indicate that HIV-1 infection diverts metabolism from glycolysis to the pentose cycle, as further described below.

The data so far presented suggest that glycolysis is downregulated in latently HIV-1 infected cells to divert glucose 6-phosphate to the pentose cycle. In this regard, the standard balance between the two pathways would be altered by NAD + paucity ( Figures 2E-G) , as NAD + is not only a main cofactor for glycolytic enzymes, but also a precursor of the main pentose cycle cofactor NADP + (Xiao et al, 2018) . As diversion to the pentose phosphate pathway leads to regeneration of the antioxidant NADPH, we tested whether blocking the downstream effectors of NADPH could induce HIV-1 escape from latency and exploit NADH paucity to reduce the ability of infected cells to survive oxidative stress.

For this purpose, we chose the drugs auranofin (AF) and buthionine sulfoximine (BSO), which by inhibiting thioredoxin (Trx) and glutathione (GSH) regeneration, respectively (Benhar et al. 2016) , can block the antioxidant/pro-latency effect of NADPH. These drugs were also preferred because of their translational potential, due to their clinical (separately) and pre-clinical (combined) testing as antireservoir compounds in PLWH and macaques infected with the simian immunodeficiency virus (SIV) (Diaz et al, 2019; Benhar et al, 2016) . As expected, at the concentrations chosen for the reactivation experiments, the two drugs were able to synergistically increase oxidative stress in a previously described reporter model which allows measuring GSH potential in live cells (Bhaskar et al, 2015) (Additional File 7). When we analyzed HIV-1 production in a number of proviral latency models, we found that AF/BSO favored proviral reactivation, at different efficiencies, in both lymphoid and myeloid models ( Figure 3A , Additional Files 8, 9) .

Moreover, when cell viability was analyzed, results showed that combined inhibition of Trx and GSH led to the preferential killing of HIV-1 infected cells as compared to their uninfected counterparts ( Figure   3B ), although specific leukemia/lymphoma cell lines were highly sensitive to AF and BSO treatment irrespective of HIV-1 infection, in line with the previously described sensitivity of such neoplasias to these drugs (Benhar et al, 2016; Fiskus et al, 2014) .

We finally tested the combination of AF and BSO in primary cells derived from PLWH under ART.

Analysis of metabolic profiles of this primary cell model showed significant enrichment of the pentose cycle upon treatment with both AF and BSO as compared to cells treated with BSO only (Additional file 10). These effects were not detectable when cells treated with AF-only were compared to cells treated with BSO, thus supporting the specificity of the drug combination. Both results are in line with the well-known compensation of GSH inhibition by the Trx system (Benhar et al, 2016) , thus confirming that only the combination of both drugs can lead to a sustained pro-oxidant effect. Finally, we tested the therapeutic potential of AF and BSO on CD4 + T-cells of PLWH receiving ART. As, in these ex-vivo samples, direct and precise analysis of cell viability (infected vs. control) was not possible due to the low frequency of HIV-1-infected cells, we indirectly tested the selective survival/elimination of HIV-1 infected cells by measuring the frequency of the integrated proviral DNA in cells sorted for viability after treatment.

Results showed that, despite only minor effects on HIV-1 reactivation as measured by Tat/rev Induced Limiting Dilution Assay [TILDA (Procopio et al, 2015) ] (Additional file 11), proviral HIV-1 DNA was significantly lower in cell cultures that had received both AF and BSO ( Figure 3C ). Of note, cells from two of the donors showed loss of integrated proviral DNA signal after AF/BSO treatment.

Overall, these data show that glycolysis downregulation and increased reliance on the pentose cycle in latently HIV-1 infected cells can be exploited by pro-oxidant drugs targeting Trx and GSH to induce HIV-1 reactivation and/or mortality of infected cells.

The results of the present study identify downregulation of glycolytic activity as a determinant of the transition from productive to latent HIV-1 infection, an effect that is reversed upon proviral reactivation.

Our data show that it is HIV-1 infection per se that paves the way towards glycolysis downregulation, since productively HIV-1-infected cells display glycolytic profiles intermediate between those of uninfected and latently infected cells. Of note, HIV-1-associated downregulation of glycolysis was shown to occur mainly due to downmodulation of glycolysis-initiating enzymes (e.g. GPI) and paucity of precursors of the energetic products of glycolysis.

Our findings complement previous studies showing that the cell subsets most susceptible to HIV-1 infection are those displaying higher glycolytic activity and that this metabolic state supports HIV-1 replication (Valle-Casuso et al, 2019; Hegedus et al, 2014) . The present study was instead aimed at a longer follow up, comprising transition to proviral latency from productive infection and proviral reactivation from latency. The overall evidence points toward a model where progressive downregulation of glycolysis is associated with gradual dampening of retroviral replication, perhaps selecting those cells that can survive the productive phase and undergo latent infection. The fact that latently infected cells undergo a metabolic transition, is further corroborated by our results showing that conventional HIV-1 reactivation stimuli can preferentially enhance glycolysis upon reversion to productive infection ( Figure   4 ).

One study that reached a partially different conclusion from ours is the work of Castellano et al. which analyzed a time course of macrophages infected in vitro with HIV-1 (Castellano et al, 2019) . This study concluded that glycolysis might not be impaired in latently infected macrophages, although it pinpointed that these cells rely on glycolysis-independent energy sources such as glutamate. The authors based their conclusions on the analysis of the acidification capability (a byproduct of glycolysis). Our report, however, shows decreased production of lactate at the single cell level, which may have been missed using a cell culture containing HIV-1 infected cells surrounded by a majority of uninfected bystander cells. On the other hand, our report confirms that, when glycolysis is downregulated, glutamate becomes a readily alternative source for pyruvate in latently infected cells, so as to maintain sufficient levels of OXPHOS-derived ATP production compatible with cell survival. In this regard, another study analyzed a panel of 186 different metabolites in plasma of PLWH and highlighted glutamate was one out of the 6 metabolites that was unequivocally elevated among PLWH as compared to uninfected control individuals (Scarpelini et al, 2016) .

Our analysis of the glycolytic pathway at a single cell resolution may reconcile our conclusions with previous results obtained studying the metabolism of PLWH. In this regard, Palmer et al. showed that glycolysis is upregulated in PLWH, independently of ART (Palmer et al, 2014a (Palmer et al, , 2014b . As the percentage of infected cells in vivo is relatively low, this effect could be attributed to chronic immune hyperactivation (Deeks et al, 2004) , rather than to retroviral replication per se. In line with a possible contribution of bystander effects to the in-vivo observations, the data sets analyzed in the present work clearly showed transcriptional downregulation of the glycolysis pathway in single cells characterized by a deep latency state.

A hallmark of HIV-1 infection identified by our metabolomic analysis is the consumption of nicotinamide, which is a NAD + precursor. This molecule is also necessary for synthesis of NADP + , the precursor of the antioxidant NADPH, which is the main pentose cycle product. Therefore, nicotinamide consumption may contribute to divert metabolism from glycolysis to the pentose cycle, consistent with a model where glycolysis favors HIV-1 replication while the pentose cycle favors HIV-1 latency as well as antioxidant defenses. The latter phenomenon is in line with the previously described upregulation of antioxidant responses in latently HIV-1 infected cells (Shytaj et al, 2020) . Moreover, oxidative stress immediately following HIV-1 infection was shown to induce increased transcription of G6PDH (Shytaj et al. 2020) , therefore further validating the diversion of glucose 6-phosphate to the pentose cycle.

Moreover, these observations may shed new light on the previously reported contribution of nicotinamide to proviral escape from latency (Samer et al, 2020) and viability of HIV-1-infected cells (Savarino et al, 1997) .

Our data also show that reinforcing glycolysis downmodulation through pro-oxidant drugs acting downstream of NADPH may lead to the selective elimination of infected cells. In particular, NADPH acts as a cofactor for the regeneration of the two most important antioxidant defenses, Trx and GSH (Benhar et al, 2016; Miller et al, 2018) . In line with this, dual inhibition of the Trx and GSH pathways might induce a vicious cycle: on one side, subtracting metabolites to glycolysis and readdressing them to the antioxidant defense-generating pentose cycle, and on the other side blocking the downstream antioxidant effects of the pentose cycle (Figure 4) . In this regard, an interesting parallel can be drawn with neoplastic cells, as previous studies showed increased susceptibility to the cytotoxic effects of combined Trx and GSH pathway inhibition in lung cancer cells with pharmacologically inhibited glycolysis (Fath et al, 2011; Li et al, 2015) . Indeed, while our study privileged the use of a dual drug combination to decrease the likelihood of non-specific toxicity, it is tempting to speculate that including an inhibitor of glycolysis could enhance the effects observed on latently infected cells. Interestingly, the use of one such inhibitor A possible limitation of our study is that it focused mainly on glycolysis as the energy-producing pathway. In this regard, another major source of NADH is the Krebs cycle (Wu et al, 2015; Viña et al, 2016) , which intervenes downstream of glycolysis. We believe that the complexity of these phenomena will require stepwise analysis. Future work might shed light on the regulation of the Krebs cycle during latent HIV-1 infection and thus provide a more complete and integrated picture of the metabolic alterations induced by HIV-1 infection.

The translational relevance of our findings resides in the fact that the drugs selected to inhibit the Trx and GSH pathways could become a useful tool for inducing a "shock-and-kill" effect, helping to purge the latently infected cells (Deeks, 2012) . Indeed, the drugs used in the present work (AF and BSO) had already shown the potential to decrease the viral reservoir in macaques and PLWH (Shytaj et al, 2015; Diaz et al, 2019) . A similar effect was observed in macaques treated with another prooxidant compound and Trx pathway inhibitor, i.e. arsenic trioxide (Yang et al, 2019) . One characteristic of these strategies was not only the elimination of latently infected cells in vivo but also the enhancement of anti-HIV-1 cell mediated immunity (Shytaj et al, 2015) . In light of the results of the present study, this immune enhancement could be interpreted as a consequence of the "shock" effect against viral latency provided by the combined inhibition of the Trx and GSH pathways. Future studies will be required to test this hypothesis and to understand the potential interplay between oxidative stress and cell-mediated immunity in the context of HIV-1 infection. Overall these results highlight glycolysis downregulation as a distinctive metabolic feature of latently HIV-1 infected cells which can be exploited to target latent reservoirs.

The following cell lines or primary cells were used as models of productive or latent HIV-1 infection: 1) Carbonell et al, 2017) , c) primary CD4 + T-cells from healthy donors infected with HIV-1 in vitro (Shytaj et al, 2020) and d) primary CD4 + T-cells from PLWH with viral loads stably suppressed by ART; 2) myeloid cells: a) the THP-1 monocytic cell line, b) the U937 and U1

(latently HIV-1 infected) promonocytic cell lines, c) primary human monocyte derived macrophages (Shytaj et al, 2013) , d) human immortalized microglia (hµglia) clone C20 (uninfected) and clone HC69 were cultured using RPMI + 10% fetal bovine serum (FBS) and plated at 0.25-0.5 X 10 6 cells/mL as previously described (Shytaj et al, 2020) .

Latently HIV-1 infected Th17 cells were generated as previously described (Dobrowolski et al, 2019; Garcia-Mesa et al, 2017) . Briefly, naive CD4 + T cells were isolated using a RoboSep CD4 + Naïve T cell negative selection kit (STEMCELL Technologies Inc., Vancouver, British Columbia, Canada), and 2 X 10 6 cells were resuspended in 10 mL RPMI medium and stimulated with 10 µg/mL concanavalin A (ConA) (EMD Millipore, Billerica, MA, USA) in the presence of subset-specific cytokines. Cells were cultured for 72 h at 37°C, followed by addition of 10 mL of fresh medium, additional 10 µg/mL ConA, polarization cocktail cytokines, and 120 IU/mL of IL-2. After 6 days, cells were washed and resuspended in RPMI medium supplemented with the growth cytokines IL-23 (50 ng/mL) and IL-2 (60 IU/mL). Cells were then infected in a 24-well plate using VSV glycoproteinpseudotyped virus expressing CD8 and GFP at a multiplicity of infection (MOI) of 2 at a cellular concentration of 5 X 10 6 cells per mL, in the presence of cell subset cytokines. Cells were spinoculated at 2,000 × g for 1.5 h at room temperature and then placed in an incubator overnight. Cells were adjusted to 1 × 10 6 per mL in the presence of cell subset-appropriate growth cytokines. After 48 h, infection efficiency was determined by GFP expression and infected cells were isolated using RoboSep mouse CD8a positive selection kit II (STEMCELL Technologies Inc., Vancouver, British Columbia, Canada). Cells (50 X 10 6 per mL) were pre-incubated with 50 µL/mL of antibody cocktail from the kit and 40 µL/mL of magnetic beads and diluted into 2.5 mL RoboSep buffer. Positive cells were recovered by magnetic bead separation, suspended in 1 mL of medium, and vortexed to release the cells and beads from the tube wall.

HIV-1 infection were isolated from total blood of healthy individuals using the RosetteSep™ Human CD4 + T Cell Enrichment Cocktail (STEMCELL Technologies Inc., Vancouver, British Columbia, Canada) as previously described (Shytaj et al, 2020) and according to the manufacturer's instructions. The blood was obtained through the Heidelberg University Hospital Blood Bank following approval by the local ethics committee. To induce activation before HIV-1 infection Dynabeads® Human T Activator CD3/CD28 was added to cells for 72 h. Cells were then mock-infected or infected using 2ng p24 of HIV 1 pNL4 3 /10 6 cells. Mock-infected and HIV-1 infected cells were then cultured for two weeks in RPMI + 20% FBS with 10 ng/mL IL 2 at a density of 0.5-2 X 10 6 /mL. At 3,7,9 and 14 days post-infection 1 X 10 6 cells were pelleted and used for RNA extraction and transcriptomic analysis (microarray and RNA-Seq) as previously described (Shytaj et al, 2020) . for at least 12 months. Culture conditions and HIV-1 reactivation experiments were conducted as described in (Procopio et al, 2015) .

For producing latently HIV-1 infected THP-1 (ATCC number: TIB-202) cell cultures, uninfected cells were cultured on a 6-well plate at a density of 1 × 10 6 cells per well in RPMI growth medium containing 10% FBS, 1% penicillin/streptomycin, and 50 nM of 2-mercaptoethanol. Infection with a HIV-1-GFP virus was carried out by spinoculation, as described in . Positively selected cells were placed in RPMI medium with cell type-specific growth cytokines at 1 X 10 6 in upright flasks and allowed to expand for a week prior to treatments. During all assays suspension cells were cultured at a density of 1 X 10 6 cells per mL, in 96-well plates in a volume of 100 µL.

Monocytic cell lines U937 and U1 (harbouring the latent HIV-1 provirus) were cultured in RPMI + 10%

FBS. Cells were stably transduced to express the Grx1-roGFP2 biosensors in cytoplasm as described previously (Bhaskar et al, 2015) .

The procedure used to generate hµglia/HIV HC69 from C20 was previously described in ( HIV-1 pseudovirus bearing Gag-mCherry was produced as described previously (Coomer et al, 2020) .

Briefly, Lenti-XTM 293T cells were transfected at 60-70% confluency with a mix of pR8ΔEnv, pcRev, NL4-3 Gag-mCherry Δ Env and with or without JR-FL Env, at a 2:1:3:3 ratio, using GeneJuice 

Total cellular RNA was extracted using the InviTrap® Spin Universal RNA Mini Kit (Stratec Biomedical, Germany) according to the manufacturers' instructions and as previously described (Shytaj et al, 2020) . RNA concentration was assessed using a P-class P 300 NanoPhotometer (Implen GmbH, Munich, Germany).

Primary CD4 ++ T-cells infected with HIV-1 or mock-infected were subjected to microarray and RNA-Seq using 500 ng of total RNA that was quality checked for integrity via Bioanalyzer. Microarray was performed using the HumanHT-12 beadchip (Illumina, Inc., 5200 Illumina Way San Diego, CA 92122 USA) and scanned using an iScan array scanner. Data extraction was done for all beads individually, and outliers were removed when the absolute difference to the median was greater than 2.5 times MAD (2.5

Hampelís method). Raw data are available at GSE163405.

Bead-level microarray raw data were converted to expression values using the lumi R package for quality control, variance stabilization, normalization, and gene annotation (Du et al, 2008) . Briefly, raw data and control probes were loaded in R using the lumiR and addControlData2lumi functions. Raw signals were background corrected, estimating the background based on the control probe information with the bgAdjust method of the lumiB function. Background corrected data were then processed with the variance-stabilizing transformation (VST) of the lumiT function to stabilize the variance and were finally normalized using the quantile normalization implemented in lumiN. Gene expression data were annotated using the R package illuminaHumanv4.db that contains the mappings between Illumina identifiers and gene descriptions.

To identify the impact of HIV-1 infection on gene expression, we compared the expression levels of

Microarray (Tusher et al, 2001) algorithm coded in the same R package. In SAM, we estimated the percentage of false-positive predictions (i.e., false discovery rate, FDR) with 100 permutations and selected as differentially expressed those genes with an FDR q-value ≤ 0.05.

Over-representation analysis was performed using Gene Set Enrichment Analysis (Subramanian et al, 2005 ) and using the gene sets of the Biocarta and Reactome collections from the Broad Institute Molecular Signatures Database (http://software.broadinstitute.org/gsea/msigdb) as well as a customized gene set derived from AmiGO (see section "Glycolysis pathway" below). GSEA software (http://www.broadinstitute.org/gsea/index.jsp) was applied on Log 2 expression data of cells infected with HIV-1 or matched mock-infected controls. Gene sets were considered significantly enriched at FDR < 5% when using Signal2Noise as metric and 1,000 permutations of gene sets.

Differential expression of genes in RNA-Seq datasets was analyzed using the DESeq2 package (Love et al, 2014) . The datasets used were retrieved from (Shytaj et al, 2020 ) (GSE127468) for CD4 + T-cells and from (Garcia-Mesa et al, 2017) (SRP075430) for uninfected (C20) and HIV-1 infected (HC69) microglia.

Heatmaps were generated using the Morpheus tool (https://software.broadinstitute.org/morpheus). 

Proteomic analysis of CD4 + T-cells infected in vitro with HIV-1 or mock-infected was retrieved from (Shytaj et al, 2020 by Despite Data-independent Acquisition (DIA) processing raw data with Spectronaut Pulsar X (version 11) using default and previously described parameters (Shytaj et al, 2020) . Heatmaps were generated using the Morpheus tool (https://software.broadinstitute.org/morpheus).

Metabolomic analysis was performed as described previously (Li et al, 2020) . Briefly, polar metabolites were extracted from cells using a cold extraction solution containing 80% methanol and 20% water. Two types of analyses were conducted. One set was run undiluted (1x), while the other set was concentrated 5fold before analysis (5x For pathway analysis, Human Metabolome Database (HMBD) (Wishart, 2020) IDs of the metabolites differentially expressed between the conditions compared were submitted to the MetaboAnalyst platform.

Comparisons were analyzed by Student's t-test using Holm's correction for multiple comparisons, so as to generate a q-value. The library 'Homo sapiens (human)' of the Human Metabolome Database was used for pathway analysis. For network generation, metabolite data were integrated with the RNA-Seq data of the same microglia model (described in its dedicated methods section). As input data, KEGG IDs, p-values and Log 2 fold changes were used for the selected compounds (metabolites and gene transcripts). In order to analyze a correlation network of the compounds in shared pathways, MetScape (Gao et al, 2010) , an app implemented in Java and integrated with Cytoscape (version 3.5.1), was used.

Except for a priori analysis ( 

Cell viability upon treatment with auranofin and/or BSO was measured using the CellTiter 96 ® Non Radioactive Cell Proliferation Assay (MTT) (Promega; Madison, WI, USA) according to the manufacturer's instructions, as described in (Shytaj et al, 2020) . Absorbance values were measured using an Infinite 200 PRO (Tecan, Männedorf, Switzerland) plate reader. After blank subtraction, absorbance values were normalized using matched untreated controls.

To measure GFP expression in J-Lat 9.2 cells, 500 × 10 5 cells were fixed with 4% PFA in PBS, washed twice with PBS and resuspended in the FACS buffer. GFP fluorescence was measured using a BD 

Intracellular redox potential measurements in U1 cells were done as described earlier (Bhaskar et al, 2015) . Briefly, the ratio-metric response of cells expressing the Grx1-roGFP2 sensor was obtained by measuring excitation at 405 and 488 nm at a fixed emission (510/10 nm) using a FACS Verse Flow cytometer (Becton Dickinson, Franklin Lakes, NJ, USA).

HIV-1 expression (Gag-p24) in U1 cells was measured by qPCR as described previously (Bhaskar et al, 2015 To measure integrated HIV-1 DNA in live CD4 + T-cells of PLWH, Alu-HIV PCR was performed as described in (Chomont et al, 2009 ). HIV-1 reactivation in the same cell types was measured by Tat/rev Induced Limiting Dilution Assay as described in (Procopio et al, 2015) .

Statistical analysis of in-silico data is described in the respective Methods subchapters. HIV-1 reactivation and cell viability data were analyzed by parametric (i.e. one or two way ANOVA tests) or nonparametric (i.e. Friedman test). Parametric testing was adopted when normality could be hypothesized (sample size ≤ 3) or restored through an appropriate transformation (e.g. tangent in the case of Figure 3B ).

Data sets characterized by sample size > 3 which did not pass the normality tests (D´Agostino & Pearson or Shapiro-Wilk) and for which a transformation was not applicable were analyzed by non-parametric tests. For both parametric and non-parametric tests, post-test comparisons were used to compare specific groups as described in the Figure captions. Analyses were performed using GraphPad Prism (GraphPad Software, San Diego, CA, USA). FOXK2  HK1  HK2  HK3  GCK  GPI  PFKL  PFKM  PFKP  ALDOA  ALDOB  ALDOC  ADPGK  TPI1  GAPDH  GAPDHS   PGK1  PGK2  BPGM  PGAM1  PGAM2  PGM2L1  ENO1  ENO2  ENO3  PKLR 

Abstract Supplement Oral Abstracts from the 23rd International AIDS Conference

Toll-like receptor 3 activation selectively reverses HIV latency in microglial cells

Cross-talk between microglia and neurons regulates HIV latency

Administration of vorinostat disrupts HIV-1 latency in patients on antiretroviral therapy

Dual targeting of the thioredoxin and glutathione systems in cancer and HIV

Measuring glutathione redox potential of HIV-1-infected macrophages

HIV infection and latency induce a unique metabolic signature in human macrophages

Oxidative DNA damage repair and parp 1 and parp 2 expression in Epstein-Barr virusimmortalized B lymphocyte cells from young subjects, old subjects, and centenarians

HIV reservoir size and persistence are driven by T cell survival and homeostatic proliferation

Where does HIV hide? A focus on the central nervous system

Clonal CD4 T cells in the HIV-1 latent reservoir display a distinct gene profile upon reactivation

Single-cell glycolytic activity regulates membrane tension and HIV-1 fusion

HIV-1 Env induces pexophagy and an oxidative stress leading to uninfected CD4 T cell death

Shock and kill

Immune activation set point during early HIV infection predicts subsequent CD4+ T-cell changes independent of viral load

Potential impact of the antirheumatic agent auranofin on proviral HIV-1 DNA in individuals under intensified antiretroviral therapy: Results from a randomised clinical trial

Entry of Polarized Effector Cells into Quiescence Forces HIV Latency

Protease inhibitor-associated hyperglycaemia

lumi: a pipeline for processing Illumina microarray

Enhancement of carboplatin-mediated lung cancer cell killing by simultaneous disruption of glutathione and thioredoxin metabolism

Latent infection of CD4+ T cells provides a mechanism for lifelong persistence of HIV-1, even in patients on effective combination therapy

Auranofin induces lethal oxidative and endoplasmic reticulum stress and exerts potent preclinical activity against chronic lymphocytic leukemia

Metscape: a Cytoscape plug-in for visualizing and interpreting metabolomic data in the context of human metabolic networks

Immortalization of primary microglia: a new platform to study HIV regulation in the central nervous system

Single-Cell RNA-Seq Reveals Transcriptional Heterogeneity in Latent and Reactivated HIV-Infected Cells

Metabolic reconfiguration is a regulated response to oxidative stress

HIV-1 pathogenicity and virion production are dependent on the metabolic phenotype of activated CD4+ T cells

Potential effects of disruption to HIV programmes in sub-Saharan Africa caused by COVID-19: results from multiple mathematical models

Maintaining HIV care during the COVID-19 pandemic

Protection from oxidative stress by enhanced glycolysis; a possible mechanism of cellular immortalization

The mitophagy effector FUNDC1 controls mitochondrial reprogramming and cellular plasticity in cancer cells

Combined inhibition of glycolysis, the pentose cycle, and thioredoxin metabolism selectively increases cytotoxicity and oxidative stress in human breast and prostate cancer

HIV-1 infection of microglial cells in a reconstituted humanized mouse model and identification of compounds that selectively reverse HIV latency

Metabolic Flux and the Regulation of Mammalian Cell Growth

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets

Switch of glycolysis to gluconeogenesis by dexamethasone for treatment of hepatocarcinoma

NADPH-dependent and -independent disulfide reductase systems

HIV infection decreases intracellular nicotinamide adenine dinucleotide

SIRT1 regulates HIV transcription via Tat deacetylation

Glucose transporter 1-expressing proinflammatory monocytes are elevated in combination antiretroviral therapy-treated and untreated HIV+ subjects

Increased glucose metabolic activity is associated with CD4+ T-cell activation and depletion during chronic HIV infection

A Novel Assay to Measure the Magnitude of the Inducible Viral Reservoir in HIV-infected Individuals

Nicotinamide activates latent HIV-1 ex vivo in ART suppressed individuals, revealing higher potency than the association of two methyltransferase inhibitors, chaetocin and BIX01294

A genetically encoded FRET lactate sensor and its use to detect the Warburg effect in single cancer cells

Macrophages and HIV-1: An Unhealthy Constellation

Role of CD38 in HIV-1 infection: an epiphenomenon of T-cell activation or an active player in virus/host interactions

Apoptotic DNA fragmentation, and its in vitro prevention by nicotinamide, in lymphocytes from HIV-1-seropositive patients and in HIV-1-infected MT-4 cells

Investigation of the potential role of membrane CD38 in protection against cell death induced by HIV-1

Plasma Metabolomics Biosignature According to HIV Stage of Infection, Pace of Disease Progression, Viremia Level and Immunological Response to Treatment

Investigational treatment suspension and enhanced cell-mediated immunity at rebound followed by drug-free remission of simian AIDS

Alterations of redox and iron metabolism accompany the development of HIV latency

Two-Year Follow-Up of Macaques Developing Intermittent Control of the Human Immunodeficiency Virus Homolog Simian Immunodeficiency Virus SIVmac251 in the Chronic Phase of Infection

The Role of Sirtuins in Antioxidant and Redox Signaling

Comprehensive Integration of Single-Cell Data

Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles

Significance analysis of microarrays applied to the ionizing radiation response

Cellular Metabolism Is a Major Determinant of HIV-1 Reservoir Seeding in CD4 T Cells and Offers an Opportunity to Tackle Infection

HIV-1 transcription and latency: an update

Role of NAD /NADH redox ratio in cell metabolism

Metabolomic Data Exploration and Analysis with the Human Metabolome Database

Krebs cycle metabolon formation: metabolite concentration gradient enhanced compartmentation of sequential enzymes

MetaboAnalyst: a web server for metabolomic data analysis and interpretation

NAD(H) and NADP(H) Redox Couples and Cellular Energy Metabolism

Arsenic Trioxide Impacts Viral Latency and Delays Viral Rebound after Termination of ART in Chronically SIV-Infected Macaques

A.Sa is the inventor of a patent covering the use of auranofin and buthionine sulfoximine for treatment of HIV/AIDS. (Tusher et al, 2001) ] and Deseq2 for RNA-Seq data (Love et al, 2014) . Panels D-F) scRNA-Seq of the expression of the entire glycolytic pathway or of glucose phosphate isomerase only (GPI) in primary CD4 + T-cells infected in vitro (D,E) or CD4 + T-cells of PLWH (F). In panels D,E, cells were infected with VSVG-HIV-1-GFP and sorted for viral expression as detailed in (Golumbeanu et al, 2018) . Following latency establishment, cells were left untreated or HIV-1 expression was reactivated through suberoyl anilide hydroxamic acid (SAHA) or α -CD3-CD28 engagement. Clusters 1 and 2 were identified by principal component analysis as described in (Golumbeanu et al, 2018) . In panel F, CD4 + T-cells were isolated from total blood of PLWH under ART as described in (Cohn et al, 2018) . Viral expression was reactivated by treatment with phytohemagglutinin (PHA) and cells were sorted using antibodies against Env and Gag. Sorted cells were then subjected to scRNA-Seq analysis. The expression level of the HUMAN-GLYCOLYSIS pathway in Panel D was calculated as the average expression of genes comprising the gene list; expression levels in cluster 1 and 2 were compared using Wilcoxon rank sum test. For panels E-F significance of GPI differential expression level between clusters (E) or between control and Env + Gag + conditions (F) was assessed by Wilcoxon rank sum test encoded in FindMarkers Seurat R function. Panels G,H) Correlation of combined HIV-1 expression and the expression of the entire glycolytic pathway (G) or GPI only (H) in sc-RNA-Seq profiling of untreated HC69 microglial cells. Data were analyzed by Spearman's correlation coefficients. ** p< 0.01, *** p< 0.001; *** p< 0.0001. Table ( LUT). Calibration color bar shows values from 2.1 to 2.5 ns. Scale bar = 10 µm. Panel B) Box and whisker plot showing results from individual TZM-bl cells from 3 independent experiments. Total number of cells analyzed per condition is indicated above each box. Results were analyzed using one-way ANOVA and Sidak post-hoc test **** : p < 0.0001. Panels C,D) Metabolite enrichment analysis in latently (C) and productively (D) infected microglial cells as compared to their uninfected counterparts. The top enriched pathways were ordered according to p values obtained with Q statistic for metabolic datasets performed with Globaltest (MetaboAnalyst) (Xia et al, 2009) . Panels E,F) Heatmap of glycolytic metabolites in HC69 latently infected cells (E) or HC69-TNF cells with HIV-1 reactivated (F) as compared to their uninfected counterparts. Data are displayed as Log 2 fold change expression. P values were calculated by Student's ttest while the Benjamini-Hochberg false discovery rate was used to account for multiple testing and calculate q values. Panels G,H) Network analysis of metabolites and genes associated with NAD + /NADH (G) and ADP (H) pathways. Genes differentially expressed are derived from the RNA-Seq analysis shown in Additional file 3. Hexagons represent metabolites, circles represent genes and the figure legend describes the differentiation pattern of nodes. Networks were built using Cytoscape software (http://www.cytoscape.org) using Metscape plugin (http://metscape.ncibi.org/tryplugin.html) (Gao et al, 2010) . , or a combination of the two. The characteristics of the different models adopted are detailed in the Material and Methods section. Each data point represents a mean from at least two independent experiments conducted in the different models. Replicates of all experiments for each cell model are shown in Additional Files 8, 9 and 11, except for the data of monocyte-derived macrophages which were retrieved from (Shytaj et al, 2013) . Panel C. Levels of integrated HIV-1 DNA following treatment for 48 h with AF and/or BSO in CD4 + T-cells derived from PLWH under suppressive antiretroviral therapy. Live cells were sorted after treatment, and integrated DNA was measured by Alu-PCR. The latency reactivating agent SAHA was used as a reference compound (Archin et al, 2012) . Data were analyzed by nonparametric Friedman´s test followed by Dunn's post-test (A,C) or two-way ANOVA followed by Tukey's post-test (B). Solid lines represent the means. * p< 0.05, ** p< 0.01, *** p< 0.001. . During productive HIV-1 infection, glycolysis is downregulated, a process which is in part compensated by enhancement of the parallel pentose phosphate pathway. Latent HIV-1 infection can ensue either spontaneously, leading to further glycolysis downregulation, or be induced by agents such as dexamethasone (DEXA), which can directly inhibit glycolysis. During latency, the pentose phosphate pathway remains active and fuels, through NADPH activity, regeneration of the two main antioxidant molecules, i.e. Trx and GSH. Reversion to a productively infected state is accompanied by partial reactivation of the glycolytic pathway. Blocking Trx and GSH inhibits downstream effects of NADPH without restoring glycolytic activity, thus favoring death of latently infected cells. TrxR = thioredoxin reductase; GCLC = Glutamate-cysteine ligase; GSSG = oxidized GSH.

Primary CD4 + T-cells were isolated from total blood of healthy individuals, activated for 72 h with α -CD3-CD28 beads and infected with HIV-1 pNL4-3 or mock-infected. Both infected and mockinfected cells were cultured for two weeks to model different infection stages as described in (Shytaj et al, 2020) . On days 7, 9 and 14 post-infection, HIV-1 infected and mock-infected cells were subjected to microarray analysis. Data from different time points were pooled for the analysis. Significantly enriched pathways in HIV-1 infected and mock-infected cells were identified by Gene Set Enrichment Analysis [GSEA (Subramanian et al, 2005) ]. Number of donors = 2.

Heatmap of the expression of the glycolytic pathway in HIV-1 infected vs mock-infected cells. Cells were activated for 72 h with α -CD3-CD28 beads and infected with HIV-1 pNL4-3 or mock-infected. Both infected and mockinfected cells were cultured for two weeks to model different infection stages as described in (Shytaj et al, 2020) . On days 3, 7, 9 and 14 post-infection, HIV-1 infected and mock-infected cells were subjected to proteomic analysis (Shytaj et al, 2020) . Data were analyzed by Student's t-test after pooling the different time points. Additional Files 5 and 6. List of metabolic pathways enriched in latently (Additional file 5) and productively (Additional file 6) infected microglial cells. Microglial cells were subjected to metabolomic analysis under four conditions: uninfected (C20), uninfected and activated (C20-TNF), latently HIV-1 infected (HC69) and reactivated HIV-1 infection (HC69-TNF). Each infected condition was compared to its uninfected counterpart. The analysis was performed using MetaboAnalyst (Xia et al. 2009 ). Additional File 7. Auranofin (AF) and buthionine sulfoximine (BSO) co-treatment induces synergistic oxidative stress in U1 cells. U1 cells expressing the redox sensor Grx1-roGFP2 (Bhaskar et al, 2015) were exposed to various combinations of AF and/or BSO and the roGFP2 ratio (405/488 nm) was measured 24 h post-treatment. Fold change was calculated by dividing the roGFP2 ratios under treated conditions with the untreated cells. Data (mean ± SD of three experiments) were analyzed by One Way ANOVA followed by Tukey's post-test (only comparisons between matching drug dosages are shown for simplicity´s sake). * p< 0.05, **** p< 0.0001.

Culturing conditions for each cell type are detailed in the Materials and Methods section. Cells were left untreated or treated with AF (500 nM), BSO (250 μ M), or a combination of the two. Treatment duration was 48 h except for Jurkat/J-lat 9.2, Th17 and U937/U1 cells that were treated for 24 h. HIV-1 expression was determined by FACS (Th17, J-Lat9.2, HC69 microglia, iGM microglia, THP-1) or qPCR (U1). Data are expressed as mean ± SD of three replicates and were analyzed by One-Way ANOVA followed by Tukey's post-test (A) or Two-Way ANOVA followed by Sidak´s post-test (B). * p< 0.05, ** p< 0.01, *** p< 0.001, **** p< 0.0001.

Peripheral blood mononuclear cells (PBMC), isolated from total blood of PLWH, were treated with auranofin AF (500 nM), BSO (250 μ M) or a combination of the two, for 24 h. PBMC donors were selected from PLWH enrolled in trial NCT02961829 (Diaz et al, 2019) . Cells were subjected to metabolomic analysis and the top enriched pathways were ordered according to p values obtained with Q statistic for metabolic datasets performed with Globaltest (MetaboAnalyst) (Xia et al, 2009 ). Number of donors = 6.Additional File 11. HIV-1 reactivation in CD4 + T-cells of PLWH under ART following treatment with auranofin (AF) and buthionine sulfoximine (BSO). CD4 + T-cells were isolated from total blood of PLWH under suppressive ART and left untreated or treated with AF (500 nM), BSO (250 μ M) or a combination of the two for 48 h. Viral reactivation was measured by Tat/rev Induced Limiting Dilution Assay [TILDA (CD4 + T-cells of PLWH)] (Procopio et al, 2015) . Data are expressed as medians and interquartile ranges.