HIV persists in long-lived infected cells that are not affected by antiretroviral treatment. These HIV reservoirs are mainly located in CD4 + T cells, but their distribution is variable in the different subsets. Susceptibility to HIV-1 increases with CD4 + T cell differentiation. We evaluated whether the metabolic programming that supports the differentiation and function of CD4 + T cells affected their susceptibility to HIV-1. We found that differences in HIV-1 susceptibility between naive and more differentiated subsets were associated with the metabolic activity of the cells. Indeed, HIV-1 selectively infected CD4 + T cells with high oxidative phosphorylation and glycolysis, independent of their activation phenotype. Moreover, partial inhibition of glycolysis (1) impaired HIV-1 infection in vitro in all CD4 + T cell subsets, (2) decreased the viability of preinfected cells, and (3) precluded HIV-1 amplification in cells from HIV-infected individuals. Our results elucidate the link between cell metabolism and HIV-1 infection and identify a vulnerability in tackling HIV reservoirs.

In the present study, we undertook the analysis of the conditions determining the intracellular susceptibility of CD4 + T cell subsets to HIV-1 infection. In particular, we analyzed whether the metabolic program is distinct according to the differentiation of CD4 + T cell subsets and whether this determines their susceptibility to HIV-1 infection. We show that cellular metabolism is a central factor driving the HIV-1 infection of CD4 + T cells and that it may be an important target for new therapies against HIV-1.

Numerous studies have demonstrated the role of cellular metabolism in T cell immunity (). Naive T cells circulate in a quiescent state, relying essentially on oxidative phosphorylation (OXPHOS). Upon T cell activation and after receiving appropriate cues (costimulation, cytokines), naive T cells undergo metabolic reprogramming, strongly increasing OXPHOS and, especially, glycolysis, to cope with the energy demands of immune function and rapid proliferation (). The biomass accumulation that accompanies enhanced cellular metabolism may provide viruses with the abundance of factors that are necessary for their replication. It is worth noting that several retroviruses have evolved to use metabolite transporters as cellular receptors. The glucose transporter 1 (GLUT) is the main receptor for HTLV-1 (); phosphate transporters PiT1 and PiT2 have been reported as surface receptors for koala retrovirus, feline leukemia virus, and murine leukemia viruses (); and the amino acid transporters ASCT1 and ASCT2 are the receptors for the feline RD-114 endogenous retrovirus (). Although HIV-1 does not use metabolite transporters as its main receptors, GLUT1 expression is necessary for the postentry steps of HIV-1 replication in CD4T cells (). Moreover, the metabolism of nucleotides is critical for HIV-1 reverse transcription ().

Combination antiretroviral treatment (cART) blocks HIV-1 replication but does not eliminate infected cells. Replication-competent HIV-1 persists in cellular reservoirs that are the origin of rapid viral rebound when treatment is interrupted (). Identifying the factors underlying the seeding and survival of HIV-infected cells is a priority in the search for an HIV cure (). CD4T cells are the major target for HIV-1 infection and are thought to constitute most of the HIV-1 reservoir. However, not all CD4T cells contribute equally to the pool of persistently infected cells during cART. The composition of CD4T cells that remain infected is mainly determined by the susceptibility of CD4T cell subsets to HIV infection, their resistance to HIV-induced apoptosis, and their life span and turnover potential (). Naive CD4T cells are highly resistant to HIV-1 infection, while HIV-1 susceptibility increases in more differentiated cell subsets (). Accordingly, there is a minimal contribution of naive CD4T cells to the HIV reservoir during cART, which is mainly restricted to the memory cell subsets (). The susceptibility of CD4T cells to HIV-1 infection depends on the relative abundance of cell factors required by the virus to complete its replication cycle and of cellular restriction factors that counteract infection (). T cell activation sharply increases the expression of HIV dependency factors and thereby cell susceptibility to HIV-1 infection (), despite the concomitant presence of some restriction factors that the virus can most often circumvent. However, responsiveness to T cell receptor (TCR) activation () and susceptibility to HIV infection are not homogeneous across or within CD4T cell subsets. This discrepancy in infection efficacy suggests that HIV-1 has adapted to infect CD4T cells with a specific cellular program (). The cellular processes orchestrating the optimal conditions for the establishment of HIV-1 infection remain unclear.

As 2-DG was able to both block infection and eliminate infected cells, we wondered whether 2-DG could block HIV spread upon activation of CD4T cells from HIV-infected individuals receiving cART. We isolated CD4T cells from six individuals receiving cART ( Table S2 ) and activated the cells with phytohemagglutinin in the absence or presence of 2-DG. In all cases, 2-DG potently blocked HIV-1 amplification, as measured by ultrasensitive analyses of p24 production ( Figure 7 D). Therefore, the need of HIV for highly glycolytic cells reveals a vulnerability that can be exploited to tackle infection.

We next studied whether the preferential establishment of HIV-1 infection in highly glycolytic cells could be used to target HIV-1 reservoirs. First, we analyzed whether suboptimal inhibition of glycolysis could selectively eliminate CD4T cells that had been preinfected in vitro. We infected CD4T cells with HIV-1-VSV and sorted infected GFPfrom noninfected GFPcells ( Figure S4 A) and cultured them in the absence or presence of 2-DG to inhibit glycolysis. The presence of 2-DG induced higher levels of cell death among infected GFPcells than among GFPcells ( Figures 7 A and 7B ), affecting all memory T cell subpopulations ( Figure 7 C).

(B) HIV-1 reactivation from CD4 + T cells from six individuals on cART upon phytohemagglutinin (PHA)/interleukin-2 stimulation in the absence (blue line/symbols) or presence (orange line/symbols) of 2-DG (5 mM) (mean and SD, n = 3 replicates). Mean p24 values in the absence or presence of 2-DG on day 14 post stimulation are shown for all six experiments (right panel; median and IQR are indicated).

(A) Cell viability in sorted preinfected GFP + (green) or noninfected GFP − (red) CD4 + T cells cultured for 48 hr in the absence or presence of 2-DG. One representative example of changes in cell viability is shown in the top panels. The relative survival of 2-DG treated cells (circles) was compared with that of nontreated cells (squares) at 24 hr and 48 hr (bottom left) and changes in the CD4 + T cell subset distribution 48 hr after the treatment of pre-infected CD4 + T cells with 2-DG when compared with the distribution in the control condition (bottom right). Median values and IQR are shown (n = 3 donors). ∗ p < 0.05; ∗∗ p < 0.01.

We then analyzed the impact of inhibition of glycolysis on the infection of CD4T cells with an R5 wild-type replication-competent virus (HIV-1 Bal). We first confirmed that the hierarchy of infection of CD4T cell subsets that we observed with VSV-G single-cycle particles (Tn < Tcm < Ttm < Tem) coincided with the hierarchy of infection when we used replication-competent HIV-1 Bal ( Figure S7 B). We found that 2-DG was also able to efficiently block infection of CD4T cells with HIV-1 Bal ( Figure 6 G), independently of whether it was added at the time of challenge or 4 hr/8 hr after challenge ( Figure S7 C). Altogether, these results show that the inhibition of metabolic activity blocked HIV-1 replication, corroborating that CD4T cell metabolism is an important determinant of HIV-1 infection.

2-DG blocked HIV-1 infection in all CD4T cell subsets, although the differences were more pronounced in more differentiated (more glycolytic) cells ( Figure 6 E). Interestingly, Etomoxir slightly reduced viral replication in Tem cells but not in other T cell subsets, which could be related to the overall highly energetic nature of these cells. We then used VSV-G pseudotyped NL4.3Δenv Duo-Fluo I particles that allow HIV-1 latently and productively infected cells to be distinguished from each other () ( Figure S7 A). Interestingly, latent infection was more prominent among Tn and Tcm CD4T cells, while productive infection was predominantly observed among Tem cells ( Figure S7 A). Overall, the presence of 2-DG significantly reduced the global number of both latently and productively infected CD4T cells ( Figure 6 F), which agreed with the need for a glycolytic environment for HIV-1 to complete the preintegration steps of its replication cycle.

The above results indicate that HIV-1 infection of CD4T cells required high levels of metabolic activity. Therefore, we analyzed whether HIV-1 replication could be blocked with metabolic inhibitors. We infected activated CD4T cells with HIV-1-VSV in the presence of increasing amounts of etomoxir, an inhibitor of fatty acid oxidation (FAO), 6-diazo-5-oxo-l-norleucine (DON), a glutamine antagonist, or 2-deoxy glucose (2-DG), a competitive inhibitor of glycolysis. Etomoxir was able to reduce HIV infection but only at high concentrations, well above the levels needed to reduce mitochondrial respiration ( Figures 6 A and S6 ). DON reduced HIV infection without inducing cell death, although the extent of the inhibition was heterogeneous. Suboptimal amounts of 2-DG (5 mM), which were enough to significantly reduce glycolysis ( Figure S6 ), decreased HIV-1 infection of CD4T cells with minimal cell toxicity ( Figure 6 A). These results suggested a higher impact of glucose and glutamine metabolism than FAO on HIV-1 replication. The role of glucose metabolism was further confirmed in different sets of experiments in which the frequency of HIV-1-infected CD4T cells was reduced when the infections were performed in conditions of glucose starvation or in the presence of UK5099, a molecule that inhibits the transport of pyruvate, an end product of glycolysis, to the mitochondria ( Figure 6 B). The presence of 2-DG impaired the accumulation of HIV-1 reverse-transcribed products over time, pointing to an early block of viral replication ( Figure 6 C). 2-DG was able to reduce infection and reverse transcript levels to a similar extent whether it was added to the culture at the time of the challenge or up to 8 hr later ( Figure 6 D), indicating that 2-DG was affecting postentry steps of viral replication. Overall, these results show that a glycolytic environment was necessary for HIV-1 to complete reverse transcription.

(G) p24 production in supernatants from CD4 + T cell cultures 3 and 7 days after infection with HIV-1 Bal in the absence (blue bars) or presence (orange bars) of 2-DG (5 mM). Means and SDs for three replicates are shown at each time point for experiments done with cells from three different donors. (A–F) Significant differences (p < 0.05) between experimental conditions are shown for each T cell subset as horizontal lines.

(F) Percentage of HIV-1 productively (left panel) or latently (right panel) infected cells 72 hr after the infection of CD4 + T cells with HIV-1DuoFluo VSV-G particles in the presence of 2-DG or etomoxir. Median and IQR values from experiments with six donors are shown.

(E) Changes in HIV-1 infection levels in CD4 + T cell subsets 72 hr after the infection of bulk CD4 + T cells in the absence or in presence of 2-DG (orange symbols) or etomoxir (beige symbols). Medians (n = 7 donors) are shown.

(D) Infection levels and number of U5-Gag copies 72 hr after challenge with HIV-1 GFP -VSV in the absence or presence of 2-DG added at the time of challenge, 4 hr or 8 hr post challenge. Values represent the relative levels of infection compared with the control condition (median and IQR, n = 3 donors).

(C) Relative number of U5-Gag copies in CD4 + T cells at 6 hr, 15 hr, or 72 hr after infection with HIV-1 GFP -VSV in the absence or presence of 2-DG. Individual values (symbols), medians, and IQRs (horizontal lines) for five different donors are shown.

(B) Infection and cell death in CD4 + T cells exposed to HIV-1 in glucose-containing medium in the absence or presence of 2-DG (5 mM) or in culture medium without glucose (starvation) (left) or in the absence or presence of UK5099 (25 μM) (right).

(A) Relative level of infection (blue bars) and cell death (purple bars) compared with the control conditions in 5-day-activated CD4 + T cells infected in the absence or presence of increasing amounts of etomoxir, DON, or 2-DG (median and IQR, n = 3 donors).

Our results suggest that HIV-1 infection is favored in the environment provided by CD4T cells with high metabolic activity levels. We analyzed whether this was due to a selective infection of CD4T cells with the highest metabolic activity levels or whether it was HIV infection that increased the metabolic activity of the cells. We activated CD4T cells and sorted Tn and Tcm cells based on their capacity to uptake high or low levels of the fluorescent glucose analog 2NBDG ( Figure S5 A), which corresponded to weakly and strongly glycolytic cells, respectively ( Figure S5 B). We infected these purified cell fractions with HIV-1-VSV. Three days after infection, infected GFPCD4T cells were only observed among highly glycolytic Tn and Tcm cells, while weakly glycolytic cells were strongly resistant to infection (65× [41×–206×], median [interquartile range—IQR] fold increase in the proportion of GFPcells in HGlu versus LGlu cell subsets, p = 0.008) ( Figure 5 ). Overall these results confirmed that, in our conditions, the high metabolic activity of infected CD4T cells was one of the causes rather than a consequence of HIV infection.

(A) Representative example of 2NBDG content after sorting (top panels) and the levels of GFP expression 72 hr after challenge in CD4 + T cell fractions exposed (HIV-1) or not (control) to the virus.

CD4 + T cells were sorted based on their differentiation status (Tn or Tcm) and their rate of 2NBDG uptake. Sorted cells were then challenged with HIV-1 GFP -VSV.

To analyze whether there was a direct link between cell metabolism and HIV-1 infection, we challenged 5-day-activated bulk CD4T cells with HIV-1-VSV, and sorted 3 days later noninfected GFPand infected GFPcells. HIV-infected CD4T cells had higher levels of basal metabolism and metabolic potential and, overall, a more energetic profile than noninfected cells ( Figures 4 A and S4 A). Although we could detect infected cells among cells with low activation levels ( Figure 4 B), we found higher proportions of GFPcells among CD4T cells expressing activation markers. We therefore evaluated whether differences in the metabolic activity of infected and noninfected CD4T cells were just a consequence of the selective infection of CD4T cells with higher activation levels. We sorted CD4T cells first based on their expression of either high or low levels of both HLA-DR and CD25 and then based on whether they were GFPor GFP Figures 4 B and S4 ). After 5 days of stimulation, the CD4T cell subsets expressed different levels of activation markers ( Figure S4 B), which were highest in Tem cells and lowest in Tn cells. This was translated to different contributions of CD4T cell subpopulations in the high- and low-activation sorted cell fractions ( Figure 4 B). Nevertheless, Tn cells were more frequently found in the GFPfraction, both in high and low-activated cell populations, whereas the GFPfraction was enriched with Tem cells. These results matched the hierarchy of infection that we observed before ( Figure 1 ) and further supported that the susceptibility of CD4T cell subsets to HIV-1 depends on the intrinsic characteristics of these cells independent of their activation status. In this regard, we found that infected GFPcells in both the high- and low-activation fractions had higher basal metabolisms (OCR and ECAR) than noninfected GFPcells ( Figure 4 C). These results demonstrated that HIV-infected CD4T cells were characterized by higher metabolic activity levels.

(C) Representative analyses of OCR and ECAR (measured as above) for each cell fraction (left) and the median and IQR basal OCR and ECAR for six (high activation) and four (low activation) donors (right).

(B) In a different set of experiments, CD4 + T cells were sorted 72 hr after HIV challenge based first on their activation levels (high activation, CD25 + /HLA-DR + or low activation, CD25-/HLA-DR − ) and then on the level of GFP expression (GFP − or GFP + cells). The gating strategy is shown on the left panels. Pie charts (right) represent the median (n = 4 donors) distribution of the CD4 + T cell subsets (determined by flow cytometry) for each sorted cell fraction as follows: high activation and GFP + , high activation and GFP − , low activation and GFP + , and low activation and GFP − (n = 4).

(A) Metabolic activity (OCR and ECAR) of sorted HIV-infected GFP + and noninfected GFP − CD4 + T cells (n = 3, median and range are shown). The bioenergetic (XF) phenotypes of GFP + and GFP − cells (right panel) were determined by the basal OCR and ECAR values. The symbols represent independent experiments (n = 3 donors).

To explore the possible association between HIV infection and cell metabolism, we determined the metabolic activity of the CD4T cell subsets at the time of infection. We used a cell flux analyzer to measure, in different conditions, the oxygen consumption rate (OCR) and the extracellular acidification rate (ECAR) as indicators of OXPHOS and glycolysis, respectively (). In the absence of activation in vitro and in agreement with their quiescent nature, all sorted CD4T cell subsets had low levels of metabolic activity ( Figure 3 A). Nonetheless, small differences between subsets were noted; basal metabolism and metabolic potential were highest in Tem cells and lowest in Tn cells, while Ttm and Tcm cells presented similar intermediate levels ( Figures 3 A and 3B). These differences were more pronounced after activation, with all memory cell subsets increasing mitochondrial function and glycolysis to different extents and with different kinetics. The highest metabolic activity was measured in Tem cells, peaking on day 3 after activation and decreasing on day 5. The metabolism of Ttm and Tcm cells increased after 3 days of activation and then remained stable in Ttm cells while continuing to increase in Tcm cells. In contrast, Tn cells showed a modest increase only in mitochondrial function and not in glycolysis and only after 5 days of activation, when their metabolism was heavily relying on OXPHOS ( Figure 3 C). Accordingly, important differences were also found between CD4T cell subsets regarding their capacity to uptake glucose and their levels of the surface expression of the GLUT1 receptor, which were lowest in Tn cells and highest in Tem cells ( Figures S3 A and S3B). The relative metabolic activity levels of the different cell subsets matched their relative susceptibility to HIV-1 infection ( Figure 1 C), and we found positive correlations between HIV infection levels and multiple metabolic functions in cells that had been activated ( Figures 3 D and S3 C). These results further point to an influence of the metabolic activity of CD4T cells on their susceptibility to HIV-1.

(D) Summary of correlations between metabolic parameters at the time of infection in NA, 3-day-activated, and 5-day-activated CD4 + T cell subsets and the percentage of infected cells 72 hr post infection. The green color indicates p < 0.05. The size of the circle represents Spearman's coefficients.

(B and C) Median and IQR basal OCR (B, left panel) and ECAR (B, right panel), and basal ECAR/OCR ratio (C) for CD4 + T cell subsets in different activation states (0d, 3d, 5d). Median values in NA Tn cells are indicated by dashed lines as a reference. Symbols represent independent experiments (n = 6). Significant differences (p < 0.05) between experimental conditions are shown for each T cell subset as horizontal lines.

(A) Median values of the metabolic variables obtained for the CD4 + T cell subsets from the six donors in the different conditions analyzed.

To determine whether a molecular program was associated with the susceptibility of CD4T cell subsets to HIV infection, we analyzed the expression of a panel of 96 genes (related to T cell activation, survival, differentiation, and function as well as known viral restriction or HIV facilitating factors; Table S1 ) in each CD4T cell subpopulation at the time of infection. Nonactivated CD4T cell subsets showed distinct transcriptional profiles that were further enhanced after activation (e.g., 34 genes and 49 genes differently expressed between CD4T cell subsets without activation and after 3 days of anti-CD3 treatment, respectively; Figure 2 A). These genes were mostly related to signal transduction and the response to stimulus, which could be related to the previously described different susceptibility to CD3 activation of the CD4T cell subsets (). The level of HIV-infected cells correlated with the expression of several genes at the time of infection in the different conditions studied ( Figures 2 B and S2 ). SAMHD1 showed a negative association with infection. In contrast, positive correlations were observed between infection levels and other antiviral factors (such as APOBEC3G or SLFN11) () as well as several genes involved in the interferon response (IFI6, IFI16, EIF2AK2, and OAS1) (). Significant positive correlations were also observed between the level of HIV infection and the gene expression levels of transcription factors (STAT3, E2F1, and PRDM1), genes that have been proposed to facilitate HIV-1 infection (RRM2, HSP90AA, CFL1, and DYNC1H1) (), and multiple genes involved in T cell metabolism (SLC2A3, SLC2A1, SLC2A5, CASP3, FAS, GAPDH, and GUSB). Taken together, these results suggest that, with the exception of SAMHD1, the antiviral restriction factors analyzed did not decisively influence the cell susceptibility to HIV-1, which is in line with the results of previous reports (). Our data indicate that metabolically active cells may offer favorable conditions for HIV infection.

(B) Spearman's correlation between the levels of gene expression at the time of HIV-1 challenge and HIV-1 infection levels 72 hr after challenge. Only significant correlations (p < 0.05) are represented in the graphs (green bars). Genes highlighted in red show the group of genes that correlated with infection levels in all conditions.

(A) Heatmaps displaying the genes differentially expressed (p < 0.05) between the CD4 + T cell subsets (Tn, Tcm, Ttm, and Tem) (n = 6 donors) in the absence of activation or after 3 or 5 days of activation with soluble anti-CD3 (i.e., at the time of HIV challenge) (green = downregulation, red = upregulation). Variables are ordered by hierarchical clustering and samples by CD4 + T cell subsets.

To study whether these differences were related to the inherent program of each CD4T cell subset, we isolated quiescent CD4Tn, Tcm, Ttm, and Tem cells (n = 6 donors; Figure S1 ) and analyzed their susceptibility to HIV-1 with or without activation. Activation enhanced the susceptibility of all CD4T cell subsets to HIV-1 infection ( Figure 1 C). However, this effect was variable according to the subset. There was a tendency for Tem cells to be more susceptible than other subsets (p = 0.06) in the absence of activation, and this difference became more pronounced after 3 days (p = 0.0004, all comparisons) or 5 days of activation (p = 0.012, Tem versus Tn and Ttm, and Tcm versus Tn and Ttm). Overall, our results recapitulated previous observations showing an inherent hierarchy in the susceptibility of CD4T cell subsets to HIV-1 infection ().

We first assessed the relative intrinsic susceptibility of primary CD4T cell subsets (naive, Tn; central memory, Tcm; transitional memory, Ttm; effector memory, Tem) to HIV-1 infection. We used single-cycle NL4.3ΔenvGFP particles pseudotyped with VSV-G envelope protein (HIV-1-VSV) to circumvent differences in the surface expression of CCR5 across CD4T cell subsets. We activated CD4T cells with soluble anti-CD3. This “suboptimal” activation protocol has allowed us to expose differences in the susceptibility to HIV-1 of CD4T cells from different individuals that were masked using more potent stimulation protocols (). Activation enhanced the susceptibility to HIV-1 without altering the relative contribution of each CD4T cell subset ( Figures 1 A and 1B ). After infection, the relative frequencies of Tn, Tcm, Ttm, and Tem cells among GFP-negative (GFP) cells were identical to that among noninfected CD4T cells ( Figure 1 B). In contrast, the composition of HIV-infected GFP-positive (GFP) cells was different from that of noninfected cells, with a significant exclusion of Tn cells and strong enrichment of Tem cells. Tcm cells were also slightly underrepresented, and Ttm cells were overrepresented among GFPCD4T cells when compared with the control condition ( Figure 1 B). These results suggested different susceptibilities to HIV-1 infection of CD4T cell subsets, with Tem cells being the most susceptible, followed by Ttm and Tcm cells, and with Tn cells being strongly resistant to infection.

(D) Medians and interquartile range (IQR) values for experiments with cells from six donors. Symbols represent the individual data points. Significant differences between experimental conditions are shown for each T cell subset as horizontal lines. The median infection level in NA Tn cells is displayed as a reference dashed line to facilitate comparison between T cell subsets.

(C) Representative example of infection levels in Tn, Tcm, Ttm, and Tem cells from a donor in the different conditions analyzed.

(B) Relative distribution of CD4 + T cell subsets in nonactivated (NA) and activated (aCD3 5d) cells before HIV challenge and in activated cells not expressing GFP (aCD3 5d GFP − ) or expressing GFP (aCD3 5d GFP + ) 72 hr post challenge. The pie charts (top) represent the median values (n = 3 donors). The bottom panels represent the fold change in the CD4 + T cell subset contribution relative to the NA condition. ∗ p < 0.05; ∗∗ p < 0.01. In a different set of experiments, sorted CD4 + T cell subsets were cultured under NA or activated conditions for 3 (3d) or 5 days (5d) and challenged with HIV-1 GFP -VSV.

(A) Representative example of the proportion of 5-day-activated CD4 + T cells expressing GFP in the absence of infection (top) or 72 hr after challenge with HIV-1 GFP -VSV (bottom).

Discussion

+ Tn, Tcm, Ttm, and Tem cells. Upon potent TCR activation, naive and memory cells have been shown to strongly upregulate their metabolism and acquire effector functions ( van der Windt et al., 2013 van der Windt G.J.

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et al. CD8 memory T cells have a bioenergetic advantage that underlies their rapid recall ability. + T cell subsets enhanced their metabolic activity but essentially maintained their distinctive metabolic programs, which matched the requirements for their expected rapid reaction to antigenic stimulation (Tem ≫ Ttm > Tcm ≫ Tn). The metabolic activity of the T cell subsets overlapped with their susceptibility to HIV-1 infection (+ T cell subsets was affected by the metabolic environment within the target cells. In this study, we performed a detailed characterization of the bioenergetics of CD4Tn, Tcm, Ttm, and Tem cells. Upon potent TCR activation, naive and memory cells have been shown to strongly upregulate their metabolism and acquire effector functions (). Here, we show important metabolic differences among the three memory cell populations studied, even in the absence of stimulation. Upon anti-CD3 activation, all CD4T cell subsets enhanced their metabolic activity but essentially maintained their distinctive metabolic programs, which matched the requirements for their expected rapid reaction to antigenic stimulation (Tem ≫ Ttm > Tcm ≫ Tn). The metabolic activity of the T cell subsets overlapped with their susceptibility to HIV-1 infection ( Figures 1 C and 3 B), supporting that the extent of HIV-1 infection in CD4T cell subsets was affected by the metabolic environment within the target cells.

+ T cell subsets, there were positive correlations between the frequencies of HIV-infected cells and the expression levels of multiple genes related to cell metabolism. Negative correlations were found between the susceptibility of CD4+ T cells to HIV-1 infection and the expression of SAMHD1, an efficient HIV-1 restriction factor that also plays an important role in the regulation of cell metabolism ( Descours et al., 2012 Descours B.

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et al. The transcription factor IRF4 is essential for TCR affinity-mediated metabolic programming and clonal expansion of T cells. Schoggins and Rice, 2011 Schoggins J.W.

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Cresswell P. Human cytomegalovirus directly induces the antiviral protein viperin to enhance infectivity. Transcript profiling at the time of infection showed that among the CD4T cell subsets, there were positive correlations between the frequencies of HIV-infected cells and the expression levels of multiple genes related to cell metabolism. Negative correlations were found between the susceptibility of CD4T cells to HIV-1 infection and the expression of SAMHD1, an efficient HIV-1 restriction factor that also plays an important role in the regulation of cell metabolism (). Surprisingly, strong positive correlations were found between the levels of HIV-infected cells and the expression of a cluster of genes related to the interferon response. Although this point was not specifically explored in the present study, increasing evidence has revealed the interrelationships between cell metabolism and the interferon response (). Some type 1 interferons might enhance glycolysis (), and interferon regulatory factors play a key role during the metabolic reprogramming that follows TCR-mediated activation of T cells (). The interaction between the interferon response and cell metabolism may somewhat explain the dichotomy between antiviral and viral-enhancing interferon-stimulated genes (). Tem cells, which were the most susceptible to HIV infection in our assay, expressed the strongest levels of several restriction factors such as SLFN11 or APOBEC3G. Our results thus indicate that HIV-1 exploits the metabolic environment that most favors the completion of its replication cycle, and this might be one of the factors underlying the adaptation of HIV-1 to evade some restriction factors.

+ T cells had higher levels of metabolic activity and metabolic potential than HIV-exposed but noninfected cells. This was not solely the consequence of the preferential infection of cells with higher activation levels; when we sorted CD4+ T cells that were matched for the expression of common activation markers, we still found that HIV-infected cells had higher metabolic activity levels than noninfected CD4+ T cells. Although there are well-established links between T cell activation and cellular metabolism, it is increasingly clear that T cell functions, including proliferation, the secretion of cytokines, and cell survival, are supported through different engagements of the various metabolic pathways ( Jones and Bianchi, 2015 Jones W.

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et al. Glut1-mediated glucose transport regulates HIV infection. + T cells expressing GLUT1 and OX40 ( Palmer et al., 2017 Palmer C.S.

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et al. Metabolically active CD4+ T cells expressing Glut1 and OX40 preferentially harbor HIV during in vitro infection. We further confirmed the association between T cell metabolism and HIV infection in a series of functional analyses. First, we showed that HIV-infected CD4T cells had higher levels of metabolic activity and metabolic potential than HIV-exposed but noninfected cells. This was not solely the consequence of the preferential infection of cells with higher activation levels; when we sorted CD4T cells that were matched for the expression of common activation markers, we still found that HIV-infected cells had higher metabolic activity levels than noninfected CD4T cells. Although there are well-established links between T cell activation and cellular metabolism, it is increasingly clear that T cell functions, including proliferation, the secretion of cytokines, and cell survival, are supported through different engagements of the various metabolic pathways (). This may explain the partial dichotomy between T cell activation and cell metabolism in HIV infection that we observed in our experiments. Additionally, we found Tn cells expressing high levels of activation markers upon anti-CD3 stimulation, but these cells remained mostly resistant to HIV-1 infection. In contrast, the frequency of infected Tn cells sharply increased when we challenged highly glycolytic Tn cells. This is in agreement with previous results showing that expression of GLUT1 is necessary for HIV-1 infection of CD4T cells () and that, in vitro, HIV preferentially infects CD4T cells expressing GLUT1 and OX40 (). Overall, our results demonstrate that cells with higher metabolic activity levels were more susceptible to HIV infection.

+ T cell metabolism. CCL5 engagement with CCR5 has been described as increasing glycolysis in T cells ( Chan et al., 2012 Chan O.

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Munger J. Stealing the keys to the kitchen: viral manipulation of the host cell metabolic network. Sanchez and Lagunoff, 2015 Sanchez E.L.

Lagunoff M. Viral activation of cellular metabolism. In our experimental conditions, we could detect virtually no infected cells when we challenged cells with low metabolic activity levels. Thus, any potential change in cell metabolism that might have been induced directly by HIV particles was not sufficient to promote infection in cells that had low metabolic activity levels at the time of viral challenge. However, it is important to note that because we were interested in understanding the factors modulating HIV infection beyond the expression of HIV receptors, we used single-cycle particles devoid of HIV envelope and pseudotyped with VSV-G in this set of experiments. It is possible that fully replication-competent viruses have a stronger effect on modulating CD4T cell metabolism. CCL5 engagement with CCR5 has been described as increasing glycolysis in T cells (), and it is possible that gp120 triggers a similar effect. Moreover, HIV infection has been shown to induce increased expression of several glucose transporters in in vitro experiments (). Overall, viruses appear to possess different mechanisms to enhance cell metabolism to favor viral replication (), and this deserves additional exploration in the context of HIV infection.

+ T cell subsets, although the effects were more pronounced in more energetic cells. Inhibition of glycolysis, including several hours after viral entry, severely reduced the accumulation of HIV reverse transcripts and impaired the establishment of both productive and latent infections. Our results thus point to critical steps early during the viral replication cycle (in particular reverse transcription) that are influenced by glycolysis, which agrees with a previous report ( Loisel-Meyer et al., 2012 Loisel-Meyer S.

Swainson L.

Craveiro M.

Oburoglu L.

Mongellaz C.

Costa C.

Martinez M.

Cosset F.-L.

Battini J.-L.

Herzenberg L.A.

et al. Glut1-mediated glucose transport regulates HIV infection. Lane and Fan, 2015 Lane A.N.

Fan T.W.M. Regulation of mammalian nucleotide metabolism and biosynthesis. + T cell subsets and strong correlations with infection levels for several genes such as TP53, ESF1, and RRM2, which play critical roles in the de novo synthesis of deoxynucleotide triphosphates (dNTPs). In particular we have recently shown that changes in the expression of RRM2 affect HIV-1 replication in macrophages and dendritic cells by modifying the pools of dNTPs ( Allouch et al., 2013 Allouch A.

David A.

Amie S.M.

Lahouassa H.

Chartier L.

Margottin-Goguet F.

Barre-Sinoussi F.

Kim B.

Saez-Cirion A.

Pancino G. p21-mediated RNR2 repression restricts HIV-1 replication in macrophages by inhibiting dNTP biosynthesis pathway. Valle-Casuso et al., 2017 Valle-Casuso J.C.

Allouch A.

David A.

Lenzi G.M.

Studdard L.

Barre-Sinoussi F.

Muller-Trutwin M.

Kim B.

Pancino G.

Saez-Cirion A. p21 restricts HIV-1 in monocyte-derived dendritic cells through the reduction of deoxynucleoside triphosphate biosynthesis and regulation of SAMHD1 antiviral activity. Mathews, 2015 Mathews C.K. Deoxyribonucleotide metabolism, mutagenesis and cancer. Hegedus et al., 2014 Hegedus A.

Kavanagh Williamson M.

Huthoff H. HIV-1 pathogenicity and virion production are dependent on the metabolic phenotype of activated CD4+ T cells. Waickman and Powell, 2012 Waickman A.T.

Powell J.D. mTOR, metabolism, and the regulation of T-cell differentiation and function. + T cells ( Besnard et al., 2016 Besnard E.

Hakre S.

Kampmann M.

Lim H.W.

Hosmane N.N.

Martin A.

Bassik M.C.

Verschueren E.

Battivelli E.

Chan J.

et al. The mTOR complex controls HIV latency. Suboptimal inhibition of glycolysis impaired HIV replication, and this was observed with single-cycle VSV-G pseudotyped particles and replication-competent HIV-1 Bal and for all CD4T cell subsets, although the effects were more pronounced in more energetic cells. Inhibition of glycolysis, including several hours after viral entry, severely reduced the accumulation of HIV reverse transcripts and impaired the establishment of both productive and latent infections. Our results thus point to critical steps early during the viral replication cycle (in particular reverse transcription) that are influenced by glycolysis, which agrees with a previous report (). Along these lines, the synthesis of deoxynucleotides, the level of which is a limiting factor for HIV reverse transcription, is very energy demanding and requires substrates that are provided by different metabolic pathways, such as the pentose phosphate pathway (PPP) that is parallel to glycolysis (). Although, unfortunately, genes involved in the PPP were not included in our gene expression panel, we found important differences between CD4T cell subsets and strong correlations with infection levels for several genes such as TP53, ESF1, and RRM2, which play critical roles in the de novo synthesis of deoxynucleotide triphosphates (dNTPs). In particular we have recently shown that changes in the expression of RRM2 affect HIV-1 replication in macrophages and dendritic cells by modifying the pools of dNTPs (). Moreover, SAMHD1, the expression levels of which were negatively correlated with infection in our analysis, is a deoxynucleoside triphosphohydrolase that contributes to the control of intracellular dNTP concentration during the cell cycle (). Our results therefore suggest that metabolically active cells offer an environment with positive synthesis (RRM2) versus degradation (SAMHD1) of dNTP pools that favors HIV-1 reverse transcription. However, other steps of the viral replication cycle may also depend on cell metabolism. The inhibition of glycolysis has been shown to decrease the production of HIV-1 particles (), and mTOR (mammalian target of rapamycin), a key regulator of cellular metabolism (), appears to be involved in the establishment of HIV-1 latency in CD4T cells ().

O'Connor et al., 2018 O'Connor R.S.

Guo L.

Ghassemi S.

Snyder N.W.

Worth A.J.

Weng L.

Kam Y.

Philipson B.

Trefely S.

Nunez-Cruz S.

et al. The CPT1a inhibitor, etomoxir induces severe oxidative stress at commonly used concentrations. Yao et al., 2018 Yao C.H.

Liu G.Y.

Wang R.

Moon S.H.

Gross R.W.

Patti G.J. Identifying off-target effects of etomoxir reveals that carnitine palmitoyltransferase I is essential for cancer cell proliferation independent of beta-oxidation. Kulkarni et al., 2017 Kulkarni M.M.

Ratcliff A.N.

Bhat M.

Alwarawrah Y.

Hughes P.

Arcos J.

Loiselle D.

Torrelles J.B.

Funderburg N.T.

Haystead T.A.

et al. Cellular fatty acid synthase is required for late stages of HIV-1 replication. + T cells. In general, the association between HIV infection and cell metabolism can be exploited to impair HIV-1 replication. In our functional experiments we mostly focused on assessing the impact of glycolysis on HIV infection. Our results showing that inhibition of pyruvate transport to the mitochondria with UK5099 blocked HIV infection suggests that glucose oxidation is important for HIV-1 infection. However, the relative contribution of aerobic versus oxidative glycolysis remains to be determined. It is likely that other metabolic functions are also important for HIV-1 infection. The inhibition of FAO with etomoxir had a limited effect on HIV replication in suboptimal conditions, mostly in Tem cells, but strongly inhibited infection at higher concentrations. However, caution is needed when interpreting results obtained with etomoxir as it has been shown to produce off-target effects at such high concentrations (). A recent report suggested that fatty acid metabolism may also participate in the late steps of viral replication (). Our results with the glutamine antagonist DON suggest that glutamine metabolism may also be necessary for the optimal infection of CD4T cells. In general, the association between HIV infection and cell metabolism can be exploited to impair HIV-1 replication.

Cell survival is another process regulated by cell metabolism that could be critically relevant for the persistence of infected cells. We found that suboptimal inhibition of glycolysis induced the selective death of cells that had been preinfected in vitro, and this affected all CD4+ T cell memory subsets. We also show here that the partial inhibition of glycolysis in CD4+ T cells from HIV-infected individuals on cART potently blocked viral reactivation and spread. Based on our results, this could be the result of a combination of both the elimination of infected cells and the blocking of new cycles of viral amplification by 2-DG. Overall, our results point to the potential modulation of cell metabolism as a strategy to combat HIV infection.

Zhao et al., 2013 Zhao Y.

Butler E.B.

Tan M. Targeting cellular metabolism to improve cancer therapeutics. + T cells could have additional implications for immune responses. We recently found that while HIV-specific CD8+ T cells from rare individuals naturally controlling HIV infection are characterized by metabolic plasticity, HIV-specific CD8+ T cells from most HIV-infected subjects heavily rely on glycolysis to exert their functions (M.A. et al., unpublished data). High levels of glucose consumption by CD4+ T cells at the sites of viral replication might severely limit glucose availability for these CD8+ T cells and impair their effector function. In addition, lactic acid, which is a product of glycolysis, inhibits effector functions in cytotoxic T cells ( Mendler et al., 2012 Mendler A.N.

Hu B.

Prinz P.U.

Kreutz M.

Gottfried E.

Noessner E. Tumor lactic acidosis suppresses CTL function by inhibition of p38 and JNK/c-Jun activation. + T cells may provide the virus with additional mechanisms to mediate immune evasion, as has also been described for tumors ( Sugiura and Rathmell, 2018 Sugiura A.

Rathmell J.C. Metabolic barriers to T cell function in tumors. + T cells more strongly than does the state of differentiation and/or activation, and cellular metabolism may be an important target for new therapies against HIV-1. Therapies targeting cellular metabolism are gaining interest in the cancer field (). Metabolic reprogramming observed in tumor cells closely resembles the metabolic profile of HIV-infected T cells that we describe here. In the context of the physiopathology of HIV infection, high glucose consumption by infected CD4T cells could have additional implications for immune responses. We recently found that while HIV-specific CD8T cells from rare individuals naturally controlling HIV infection are characterized by metabolic plasticity, HIV-specific CD8T cells from most HIV-infected subjects heavily rely on glycolysis to exert their functions (M.A. et al., unpublished data). High levels of glucose consumption by CD4T cells at the sites of viral replication might severely limit glucose availability for these CD8T cells and impair their effector function. In addition, lactic acid, which is a product of glycolysis, inhibits effector functions in cytotoxic T cells (). Therefore, the metabolic characteristics of HIV-infected CD4T cells may provide the virus with additional mechanisms to mediate immune evasion, as has also been described for tumors (). Because exploiting the host cell metabolic machinery appears to be a common strategy for invading pathogens, including viruses, bacteria, and parasites, therapies targeting cell metabolism could affect a large spectrum of infections. Obviously, cell metabolism regulates critical physiological events, including immune responses, and it is necessary to develop a better understanding of the links between cell metabolism and acute and chronic infections. Overall, our study shows that cellular metabolism is a central factor that drives the HIV-1 infection of CD4T cells more strongly than does the state of differentiation and/or activation, and cellular metabolism may be an important target for new therapies against HIV-1.