Phosphofructokinase P fine-tunes T regulatory cell metabolism, function, and stability in systemic autoimmunity

Abstract

Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by defective regulatory T (T_reg) cells. Here, we demonstrate that a T cell–specific deletion of calcium/calmodulin-dependent protein kinase 4 (CaMK4) improves disease in B6.lpr lupus-prone mice and expands T_reg cells. Mechanistically, CaMK4 phosphorylates the glycolysis rate-limiting enzyme 6-phosphofructokinase, platelet type (PFKP) and promotes aerobic glycolysis, while its end product fructose-1,6-biphosphate suppresses oxidative metabolism. In T_reg cells, a CRISPR-Cas9–enabled Pfkp deletion recapitulated the metabolism of Camk4^−/− T_reg cells and improved their function and stability in vitro and in vivo. In SLE CD4⁺ T cells, PFKP enzymatic activity correlated with SLE disease activity and pharmacologic inhibition of CaMK4-normalized PFKP activity, leading to enhanced T_reg cell function. In conclusion, we provide molecular insights in the defective metabolism and function of T_reg cells in SLE and identify PFKP as a target to fine-tune T_reg cell metabolism and thereby restore their function.

In autoimmunity, phosphofructokinase P rewires T_reg cell metabolism, leading to impaired immunosuppressive function and stability.

INTRODUCTION

Systemic lupus erythematosus (SLE) is an autoimmune disease that involves all organ systems and affects young women (1). Despite available treatments, SLE is responsible for substantial morbidity and mortality worldwide (2). Current treatment relies on the use of immunosuppressive drugs that control the immune dysregulation at the price of increased risk of infections and cardiovascular disease, which represent the main causes of morbidity and mortality in SLE (3).

In recent years, the study of immune cell metabolism has transformed our understanding of immunobiology and autoimmune diseases. Different cellular subsets, classically identified using surface or intracellular markers, are characterized by distinct metabolic profiles, which also adapt on the basis of the immune cell activation status and localization (4). SLE CD4⁺ T cells are characterized by an increased glycolytic metabolism and dysregulated oxidative phosphorylation (5). Normalization of T cell metabolism using the glycolysis inhibitor 2-deoxyglucose and the adenosine monophosphate (AMP)–activated kinase (AMPK) agonist metformin reverses the T cell–aberrant phenotype in vitro and improves lupus-like disease in mice (5). Furthermore, a recent proof-of-concept clinical trial of metformin in patients with SLE yielded encouraging results (6).

Among the proposed therapeutic strategies for SLE, reinforcing the regulatory T (T_reg) cell compartment is particularly attractive (7) because the T_reg cell compartment has consistently been described as quantitatively reduced (8, 9) and/or functionally impaired (10, 11). The mechanisms that drive T_reg cell dysfunction in SLE are multifactorial and involve systemic inflammation, altered T cell signaling (7), and platelet–T_reg cell interaction (12). During the past two decades, our team has studied the role of the calcium/calmodulin-dependent protein kinase 4 (CaMK4), a serine/threonine kinase (13). CaMK4 activity is regulated by intracellular calcium levels, which are higher in human SLE T cells compared to healthy donors (HDs) because of aberrant TCR signaling (14, 15). Consequently, SLE T cells are characterized by an increased CaMK4 activity (16), and Camk4 global knockdown improves induced and spontaneous autoimmunity in mice (17). CaMK4 inhibition enhanced mouse T_reg cell differentiation and function in vitro, impaired T helper 17 (T_H17) cell differentiation, and increased interleukin-2 (IL-2) production by conventional T cells (18). Recent data suggest that CaMK4 controls several aspects of immune cell metabolism. Studies from our team identified that CaMK4 advances aerobic glycolysis and promotes T_H17 cell differentiation by controlling the activity of pyruvate kinase M2 (19). However, the exact mechanisms whereby CaMK4 negatively affects T_reg cell function are still unknown.

Here, we present evidence that the rate-limiting glycolysis enzyme 6-phosphofructokinase (PFK) platelet-type (PFKP) activity is controlled through serine phosphorylation by CaMK4. We demonstrate that, in parallel to the control of the glycolytic pathway, PFKP, through its end product fructose-1,6-biphosphate (F-1,6P), controls oxidative phosphorylation in an opposite manner. Furthermore, the modulation of T_reg cell metabolism using a CRISPR-Cas9 Pfkp deletion led to enhanced T_reg cell function and stability in in vitro and in vivo systems. At the translational level, we demonstrate increased PFKP activity in SLE CD4⁺ T cells that, when corrected, improves T_reg cell activity. Our studies bring forward PFKP as a target molecule to control T_reg cell function.

RESULTS

T cell–specific CaMK4 deficiency expands the T_reg cell compartment and ameliorates disease in lupus-prone mice

CaMK4-deficient MRL/lpr^fas show improved lupus-like features (18), but because CaMK4 is expressed in other cells, including podocytes (20), the contribution of CaMK4 deficiency in T cells in the expression of pathology is unclear. To address this question, we crossed B6.lpr mice with B6.Camk4^fl/fl mice expressing the Cre recombinase only in T cells (B6.lpr.Camk4^fl/fl.dlck-Cre), leading to depletion of CaMK4 in T cells (fig. S1A). Camk4^fl/fl.dlck-Cre mice had decreased cervical lymph node volume, as well as spleen size, weight, and cellularity, compared to Camk4^fl/fl littermates (Fig. 1, A to C). Because both conventional T (T_conv) cells and T_reg cells express CaMK4 (fig. S1B), we studied these subpopulations in B6.lpr mice. The percentage of IL-17A–producing CD4⁺ T cells was decreased in the spleen (P < 0.05) but not in the peripheral blood of the Camk4^fl/fl.dlck-Cre mice (Fig. 1D and fig. S1C, gating), while the percentage of interferon-γ (IFN-γ)–producing CD4⁺ T cells remained unchanged (fig. S1, C and D). Conversely, Camk4^fl/fl.dlck-Cre mice were characterized by an expanded T_reg cell compartment in the spleen and the peripheral blood compared to CaMK4-sufficient littermates (P < 0.01 for both comparisons; Fig. 1E and fig. S1E, gating). CaMK4 deficiency in T cells led to decreased double-negative T cell in the blood, the spleen, and the kidney of B6.lpr mice (fig. S1, F and G). Furthermore, serum double-stranded DNA (dsDNA) antibody levels were significantly decreased in mice with CaMK4-deficient T cells as compared to CaMK4-sufficient littermates (P < 0.01; Fig. 1F). At the organ level, B6.lpr mice with CaMK4-deficient T cells were characterized by decreased proteinuria (Fig. 1G) and improved kidney glomerular (Fig. 1I) and perivascular pathology scores (Fig. 1J). Collectively, these results indicate that a T cell–specific CaMK4 deficiency in B6.lpr mice results in the improvement of hallmark features of lupus-like disease with a simultaneous expansion of the T_reg cell compartment.

Fig. 1. T cell–specific CaMK4 deficiency expands the T_reg cell compartment and ameliorates disease in lupus-prone mice.

Thirty-two–week-old C57Bl/6.lpr mice with (B6.lpr.Camk4^fl/fl.dlckCre, blue; n = 5) or without (C5B6.lpr.Camk4^fl/fl, red; n = 7) T cell–specific CaMK4 knockout were studied. Data are from two independent experiments. (A) Representative pictures of the spleen and cervical lymph node. (B and C) Spleen weight (B) and cellularity (C) at week 32. (D and E) Percentage of IL-17A⁺–producing cells (D) and CD25⁺FoxP3⁺ (T_reg) (E) cells among CD4⁺ T cells in the spleen and the peripheral blood of the mice. (F) Serum dsDNA antibodies were measured using enzyme-linked immunosorbent assay (ELISA). (G) Results from urine strip measuring proteinuria [results ranging from absent (0) to ++++ (4)]. (H) Representative periodic acid Schiff (PAS) staining of kidney tissues. (I and J) Glomeruli (I) and tubular pathology scores (J) were evaluated. Each point indicates the result from one mouse; bars represent means ± SEM. ns, not significant; *P < 0.05; **P < 0.01 using bilateral Student’s t test.

CaMK4 affects the glycolytic and oxidative metabolism of inducible T_reg cells

In accordance with previous findings that CaMK4 is expressed in T_reg cells and affects their differentiation (18, 21), we found that CaMK4 deficiency enhanced murine in vitro inducible T_reg (iT_reg) cell differentiation (Fig. 2A) and Forkhead Box P3 (FoxP3) expression (fig. S2A). Conversely, the transfection of a CaMK4 overexpression (CaMK4-OE) vector suppressed iT_reg cell differentiation and FoxP3 expression (P < 0.01; Fig. 2B and fig. S2B). To evaluate the impact of CaMK4 on the iT_reg cell metabolic profile, we conducted real-time metabolic studies of iT_reg cells at 8, 24, and 72 hours of differentiation using a Seahorse XF analyzer. We found that Camk4^−/− T cells were characterized by decreased extracellular acidification rate (glycolytic activity) at all time points of iT_reg cell differentiation (Fig. 2C). In contrast, oxidative metabolism assessed by the oxygen consumption rate was increased in Camk4^−/− iT_reg cells at the 24- and 72-hour time points (Fig. 2, D and E). Similar results were found when comparing wild-type and Camk4^−/− conventional (nondifferentiating) CD4⁺ T cells (fig. S2, C and D). Consistent with these findings, Camk4^−/− iT_reg cells were characterized by increased levels of mitochondrial reactive oxygen species (mtROS) (P < 0.01; Fig. 2F) and mitochondrial DNA content (Fig. 2G). Collectively, these results suggest that during iT_reg cell differentiation, CaMK4 affects the glycolytic and mitochondrial cellular metabolism and negatively affects iT_reg differentiation.

Fig. 2. CaMK4 affects T cell glycolytic and oxidative metabolism during T_reg cell differentiation.

(A) CD62L⁺CD4⁺ T cells were isolated from the spleen of C57Bl/6 or Camk4^−/− mice and differentiated to iT_reg cells. The percentage of CD25⁺FoxP3⁺ iT_reg cells was evaluated using flow cytometry at day 3. Representative cytometry results (left) and the cumulative results (right; n = 4) are shown. (B) CD62L⁺CD4⁺ T cells of C57Bl/6 mice were differentiated to iT_reg cells and transfected at day 2 of culture with an empty vector or a CaMK4-OE vector. iT_reg cell differentiation was evaluated at day 3 using flow cytometry on viable transfected (GFP⁺) cells (n = 4). (C and D) CD62L⁺CD4⁺ T cells were isolated from the spleen of C57Bl/6 or Camk4^−/− mice were differentiated to iT_reg cells. Representative results of Seahorse XFe glycolysis stress test (C) or mitochondrial stress test (D) at 8, 24, or 72 hours. ECAR, extracellular acidification rate; 2-DG, 2-deoxyglucose; OCR, oxygen consumption rate. (E) Cumulative results of the basal respiration rate (left), the adenosine triphosphate (ATP)–linked respiration rate (middle), and the maximal respiration rate (right) at 8, 24, and 72 hours of wild-type (WT) and Camk4^−/− (KO) iT_reg cells (n = 3 independent experiments per time point with three technical replicates each). (F) WT and Camk4^−/− (KO) iT_reg cells were stained with MitoSOX (2 μM) and evaluated using flow cytometry. Representative (left) and cumulative data (right) of MitoSOX mean fluorescence intensity (MFI) are shown (n = 3 biological replicates per time point). (G) Total DNA from iT_reg from WT and Camk4^−/− mice were extracted, and a quantitative polymerase chain reaction (qPCR) was conducted using NADH dehydrogenase subunit 1 gene (ND1) probe to evaluate mitochondrial DNA (mtDNA). MtDNA copies per cell were calculated by the formula 2^−ΔCt. *P < 0.05 and **P < 0.01 using unpaired bilateral Student’s t test (A, F, and G) or paired bilateral Student’s t test (B and E).

CaMK4 posttranslationally controls the activity of the rate-limiting enzyme PFKP

To investigate how CaMK4 affects the iT_reg cell metabolic profile during differentiation, we conducted a comprehensive metabolomic analysis. At early steps of iT_reg cell differentiation (8 hours), the classical glycolysis pathway was enriched (P < 0.05), while the pentose phosphate pathway was not (fig. S3A). Close evaluation of the glycolysis metabolites of the Camk4^−/− iT_reg cells differentiated for 8 hours showed that fructose-6-phosphate (F-6P) was increased, while F-1,6P was decreased (Fig. 3, A and B). The dysbalanced levels of the two metabolites suggested that the activity of PFK, the rate-limiting glycolysis enzyme catalyzing the transformation of F-6P to F-1,6P, is impaired in CaMK4-deficient T_reg cells (Fig. 3B). PFK has three isoforms in humans and mice: PFKP, PFK liver-type (PFKL), and PFK muscle-type (PFKM). Because we found that in mouse iT_reg cells, PFKP was expressed at levels 10 to 100 times higher compared to PFKM and PFKL (Fig. 3C), we focused on the PFKP isoform. The expression of PFKP was similar between wild-type and Camk4^−/− iT_reg cells at the mRNA and the protein levels (Fig. 3, D and E). However, Camk4^−/− iT_reg cells had significantly decreased PFK enzymatic activity compared to wild-type counterparts (P < 0.01; Fig. 3F). Conversely, transfection of iT_reg cells with a CaMK4-OE vector led to increased PFK activity (P < 0.01; Fig. 3G). Collectively, these results suggest that CaMK4 enhances T_reg cell glycolysis by controlling PFKP enzymatic activity at a posttranslational level.

Fig. 3. CaMK4 controls the activity of the rate-limiting glycolysis enzyme PFKP at a posttranslational level.

(A) The metabolites from WT or Camk4^−/− T cells after 8 hours of differentiation under iT_reg cell–polarizing conditions were extracted and semiquantitatively measured using liquid chromatography–mass spectrometry (LC-MS; n = 3 biological replicates per genotype). Heatmap showing the average normalized level of metabolites from the glycolysis, pentose phosphate pathway, and the cell energy balance from three biological replicates. *P < 0.10, **P < 0.05, and ***P < 0.01 using multiple unpaired Student’s t test with single pooled variance. (B) Metabolites from the glycolysis pathway are shown in a color reflecting their relative level in each genotype: increased in Camk4^−/− (red, P < 0.10), decreased in Camk4^−/− (blue, P < 0.10), or unchanged (black). (C) The relative expression of the three PFK isoforms were measured gene using reverse transcription qPCR (RT-qPCR) in WT and Camk4^−/− iT_reg cells (n = 3). Expressions of PFK isoforms are relative to the housekeeping gene. (D) PFKP expression was compared between WT and Camk4^−/− iT_reg cells using the ΔΔCt method (n = 5). (E) Western blot of WT and Camk4^−/− iTreg cells showing PFKP and β-actin (left) and cumulative densitometry results (right; n = 4). (F) PFK enzymatic activity of WT and Camk4^−/− iT_reg cell lysates was measured using a colorimetric assay (n = 5). (G) PFK enzymatic activity was measured in the lysates of Camk4^−/− iT_reg cells transfected with either an empty vector or a CaMK4-OE vector (n = 5). *P < 0.05 and **P < 0.01 using unpaired bilateral Student’s t test. ****P < 0.0001 using one-way ANOVA with Holm-Sidak’s correction.

CaMK4 phosphorylates serine-539 of PFKP and affects iT_reg cell differentiation

Previously published mass spectrometry data suggested that CaMK4 may physically interact with PFKP (19). To confirm this, we transfected Camk4^−/− T cells with a FLAG-tagged CaMK4-OE vector. We subsequently immunoprecipitated the CaMK4 protein using a FLAG antibody and were able to detect PFKP by immunoblotting (Fig. 4A), confirming physical interaction. Because CaMK4 is a serine/threonine kinase, we hypothesized that CaMK4 may phosphorylate serine residues on PFKP. To address this, we immunoprecipitated PFKP from protein lysates of wild-type or Camk4^−/− iT_reg cells. After blotting the precipitate, while the signal for PFKP (86 kDA) was similar in both conditions (Fig. 4B, bottom), the signal for phosphoserine at 86 kDA was decreased in lysates from Camk4^−/− cells (Fig. 4B, top), suggesting that CaMK4 affects the phosphorylation of PFKP serine residues. To further substantiate this hypothesis, we conducted a phosphoproteomics study of the PFKP immunoprecipitates from wild-type and Camk4^−/− iT_reg cells. We identified that two serine residues (S162 and S539) were phosphorylated in wild-type, but not in Camk4^−/−, cells (Fig. 4C; full phosphoproteomics results available in the Supplementary Materials). Serine-539 (S540 in humans) is a highly conserved amino acid among mammals including humans and may harbor an N-acetylglucosamine (GlcNAc) residue that negatively affects PFKP activity (22). Furthermore, amino acids 537 to 541 of PFKP represent the binding site of fructose-2,6-biphosphate, an allosteric activator of PFKP (23), reinforcing the importance of this site as a modulator of the PFKP enzymatic activity. To evaluate the potential impact of these phosphorylated serine residues on T_reg cell biology, we conducted a site-directed mutagenesis of a PFKP-OE vector. We substituted serine-162 or serine-539 with an alanine residue that cannot be phosphorylated (S162A-OE and S539A-OE, respectively), thus blocking the potential impact of CaMK4 on PFKP. While the transfection of PKFP and PFKP-S162A-OE vector resulted in a reduction in iT_reg cell differentiation and FoxP3 expression, the PFKP-S539A-OE vector did not (Fig. 4D and fig. S4A). Furthermore, compared to PFKP-OE–transfected iT_reg cells, PFKP-S539A-OE–transfected iT_reg cells demonstrated lower glycolysis and higher Oxidative phosphorylation (OXPHOS) (fig. S4, B and D), recapitulating the differences observed between wild-type and Camk4^−/− T cells (Fig. 2, C and D). These results suggest that serine-539 phosphorylation is responsible for CaMK4/PFKP effect on the T_reg cell biology. Collectively, CaMK4 physically interacts with PFKP and phosphorylates serine residue 539, thereby affecting PFKP activity and iT_reg cell metabolism and differentiation.

Fig. 4. CaMK4 phosphorylates serine-539 of PFKP and affects iT_reg cell differentiation.

(A) CD62L⁺ CD4⁺ T cells from Camk4^−/− mice were differentiated in iT_reg cells and transfected with FLAG-tagged CaMK4-OE vector on day 2. At day 3, proteins were extracted from cell lysate and immunoprecipitated with an anti-FLAG antibody. Western blot showing CaMK4 and PFKP. IgG, immunoglobulin G; IB, ImmunoBlot. (B) Cell lysates from WT and Camk4^−/− iT_reg cells were immunoprecipitated with a PFKP antibody. Western blot of the immunoprecipitates revealing phospho-serine residues (top) and PFKP (bottom). (C) Schematic of the phosphosproteomics experiment. Cell lysates from WT and Camk4^−/− iT_reg cells were immunoprecipitated with a PFKP antibody and migrated on a NuPAGE bis-tris gel. The band corresponding to PFKP was cut and processed by LC-MS to identify phosphorylated residues on PFKP. Data are from two independent experiments. (D) Site-directed mutagenesis was conducted on a PFKP-OE vector to substitute S162 or S539 by an alanine residue (PFKP S162A and PFKP S539A, respectively). CD62L⁺ CD4⁺ T cells from C57Bl/6.FoxP3.Gfp mice were transfected at day 2 of culture with an empty vector or a PFKP-OE vector, and iT_reg cell differentiation was measured at day 3 on DsRed⁺ (transfected) viable cells using flow cytometry. Representative of cell differentiation (left) and cumulative data of three independent experiments (right). **P < 0.01 and ***P < 0.001 using one-way ANOVA test with Holm-Sidak’s correction.

The CaMK4/PFKP axis affects iT_reg cell metabolic rheostat and differentiation through PFKP end product F-1,6P

We have shown that Camk4^−/− iT_reg cells are characterized by enhanced oxidative metabolism and mitochondrial DNA content after 24 hours of differentiation (Fig. 2, D and E). Furthermore, metabolomic studies of iT_reg cells showed that metabolites from the tricyclic acid cycle were enriched at 24 hours of differentiation (fig. S5, A and B). To understand the mechanism underlying the impact of CaMK4 on oxidative phosphorylation, we studied the phosphorylation (i.e., activation) status of kinases known to control the metabolic rheostat. We found that Camk4^−/− iT_reg cells were characterized by increased phosphorylation of AMPK, a master regulator of the oxidative metabolism (Fig. 5A), and reduced molecular target of rapamycin (mTOR) pathway activation, as assessed by decreased phospho-p70S6K levels (fig. S5C). Conversely, the transfection of iT_reg cells with a CaMK4-OE vector resulted in reduced AMPK phosphorylation (Fig. 5B). PFKP catalyzes the glycolysis rate-limiting step of F-6P conversion to F-1,6P. F-1,6P was demonstrated to inhibit AMPK phosphorylation in fibroblast cell lines, thereby regulating the metabolic cellular rheostat (24). Because F-1,6P levels were decreased in Camk4^−/− iT_reg cells (Fig. 2, A and B), we hypothesized that the impact of CaMK4 on the mitochondrial metabolism is mediated by reduced F-1,6P levels driving increased AMPK phosphorylation. To evaluate this hypothesis, we differentiated Camk4^−/− iT_reg cells together with the glycolysis intermediates F-6P or F-1,6P. We found that the PFKP end product F-1,6P, but not its precursor F-6P, reduced AMPK phosphorylation (Fig. 5C), mtROS levels (Fig. 5D), and cellular mitochondrial DNA content (Fig. 5E). Furthermore, F-1,6P reduced Camk4^−/− iT_reg cell differentiation to the same level of wild-type (P < 0.001; Fig. 5F) and blunted FoxP3 expression (fig. S5D). Glycolysis metabolites or selected amino acids did not affect CaMK4 activation nor CamK4 and PFKP expression (fig. S5, E and F). Collectively, these results suggest that Camk4^−/− fine-tunes iT_reg cell oxidative metabolism by affecting the AMPK/mTOR metabolic rheostat through the PFKP end product, F-1,6P, thereby affecting iT_reg cell differentiation.

Fig. 5. The CaMK4/PFKP axis affects iT_reg cell metabolic rheostat and differentiation through PFKP end product F-1,6P.

(A) iT_reg cells were differentiated from WT or Camk4^−/− CD62L⁺ CD4⁺ T cells. After 24 hours of differentiation, protein lysates were extracted, and Western blot was conducted. The left panel shows the stained membrane, and the right panel indicates the dosimetry measurement of Thr¹⁷²-phosphorylated AMPK (n = 5). (B) iT_reg cells were differentiated from Camk4^−/− CD62L⁺ CD4⁺ T cells and transfected with an empty vector or a CaMK4-OE vector. Representative Western blot of iT_reg cell lysates at 24 hours after transfection. (C to F) iT_reg cells were differentiated from Camk4^−/− CD62L⁺ CD4⁺ T cells with 1 mM F-1,6P or F-6P. (C) AMPK phosphorylation status (n = 4). (D) Mean fluorescence intensity of MitoSOX among living cells (n = 4). (E) Mitochondrial content was measured using qPCR (n = 4). (F) Percentage of CD25⁺FoxP3^hi iT_reg cells at day 3 of differentiation. *P < 0.05, **P < 0.01, and ***P < 0.001 using unpaired Student’s t test (B), paired one-way ANOVA with Holm-Sidak’s correction (C to E), or unpaired one-way ANOVA with Holm-Sidak’s correction (F).

CRISPR-Cas9–mediated PFKP knockdown alters the metabolism and enhances iT_reg cell differentiation and function in vitro

To confirm the importance of PFKP in T_reg cell biology, we silenced PFKP by transfecting CRISPR-Cas9–expressing T cells with single guide RNA (sgRNA) targeting the Pfkp gene. Transfection of Pfkp target sgRNA led to marked reduction of PFKP expression (Fig. 6A), as well as cellular PFK activity and extracellular acidification rate (i.e., glycolysis; Fig. 6, B and C) compared to control sgRNA. In addition, PFKP knockdown led to increased AMPK phosphorylation (Fig. 6D), mtROS (Fig. 6E), and cellular oxygen consumption rates (Fig. 6F). The impact of these metabolic changes translated to enhanced iT_reg cell differentiation upon PFKP knockdown (P < 0.01; Fig. 6G), as well as increased FoxP3 expression (fig. S6A). To evaluate the impact of PFKP modulation on T_reg cell functions, we conducted in vitro immunosuppression assay with control or Pfkp target sgRNA-transfected iT_reg cells. The silencing of PFKP in iT_reg cells led to enhanced in vitro immunosuppressive capacity (Fig. 6H). Collectively, these results demonstrate that PFKP fine-tunes the glycolytic and oxidative metabolisms of T_reg cells and thereby affects their differentiation and suppressive function in vitro.

Fig. 6. CRISPR-Cas9–mediated PFKP knockdown alters the metabolism of iT_reg cells and affects their in vitro immunosuppressive function.

CD62L⁺ CD4⁺ T cells from CRISPR-Cas9–expressing mice were differentiated into iT_reg cells and transfected at day 1 with control or Pfkp target sgRNAs. (A) Western blot showing PFKP expression in iT_reg cell lysates. (B) Phosphofructokinase activity of T_reg cell lysates (n = 3). (C) Representative of a Seahorse glycolysis stress test of control (red) or Pfkp target (blue) iT_reg cells. (D) Representative Western blot (left) and cumulative densitometry result (right; n = 4) showing phospho-AMPK and total AMPK in control and PFKP target iT_reg cells. (E) Mean florescence intensity of MitoSOX marker in control and Pfkp target iT_reg cells (n = 3). (F) Representative of a Seahorse mitochondrial stress test of control (red) and Pfkp target (blue) iT_reg cells. (G) Percentage of CD25⁺ FoxP3⁺ among control and Pfkp target iT_reg cells was measured using flow cytometry at day 3 of differentiation. Representative flow plot (left) and cumulative results (right) are shown (n = 4). (H) Control or Pfkp target iT_reg cells were cocultured for 3 days with CellTrace Violet–stained T_conv cells (T_reg/T_conv cells, ratio of 1:1 to 1:4) and antigen-presenting cells together with CD3/CD28 stimulation. Representative proliferation of T_conv cells under different coculture ratio (left) and cumulative results of iT_reg cell immunosuppression activity (right; n = 3 independent experiments of three replicates each). Each dot represents the value of one biological replicate, and bars indicate means and SEM. *P < 0.05, **P < 0.01, and ***P < 0.001 using unpaired bilateral Student’s t test.

CRISPR-Cas9–mediated PFKP knockdown improves T_reg cell function and stability in vivo

To gain further insight on the impact of PFKP modulation on T_reg cell function in vivo, we transferred 4 × 10⁶ syngeneic CD45RB^high CD4⁺ T_conv cells ± 5 × 10⁵ control or Pfkp target sgRNA-transfected iT_reg cells to C57BL/6.Rag1^−/− mice to induce inflammatory colitis (Fig. 7A). Without iT_reg cell transfer, the mice developed severe colitis leading to massive weight loss within 7 weeks mandating euthanasia (purple line; Fig. 7B). The transfer of iT_reg cells blunted the weight loss and the colitis severity, with Pfkp target–transfected iT_reg cells showing the best efficiency (blue line; Fig. 7, B and C). Transferred iT_reg cells constitutively expressed green fluorescent protein (GFP), allowing the lineage tracking of these cells. The proportion of CD25⁺FoxP3⁺ cells among splenic and mesenteric lymph node GFP⁺ CD4⁺ T cells was higher in the mice transferred with PFKP-deficient iT_reg cells (Fig. 7D), suggesting higher stability of the PFKP-deficient iT_reg cells. Similarly, transferred PFKP-deficient iT_reg cells expressed lower levels of IL-17A compared to control iT_reg cells (Fig. 7E). To further investigate whether PFKP deficiency improved T_reg cell stability, we cultured control or PFKP-deficient iT_reg cells for 24 hours under T_H17-differentiating conditions. We found that PFKP-deficient iT_reg cells retained higher FoxP3 expression (fig. S7, A and B) while expressing lower levels of IL17A RNA (fig. S7C). Furthermore, these differences translated in higher immunosuppressive functions in vitro (fig. S7D). To evaluate whether these differences were associated with a different methylation profile in the FoxP3 conserved noncoding sequences (CNS), we evaluated CpG methylation in control and PFKP-deficient iT_reg cells cultured under T_H17 conditions (fig. S7E). The CpG methylation profile was similar in the T_reg-specific demethylation region and in the proximal promoter of FoxP3, while it was decreased in evolutionary conserved region 3 located in the upstream enhancer in the PFKP-deficient iT_reg cells (fig. S7F). However, the biological relevance of these differences is unknown. Collectively, these results demonstrate that the modulation of PFKP in iT_reg cells improves their immunosuppressive capacity in vivo and their stability in an inflammatory environment.

Fig. 7. PFKP modulation improves the iT_reg cell in vivo function and stability in the adoptive transfer colitis model.

(A) Design of the in vivo experiment. Cas9-GFP expressing CD62L⁺ CD4⁺ T cells were transfected with control of Pfkp target sgRNA and differentiated into iT_reg cells. CD45RB^hi CD4⁺ T (T_conv) cells were sorted using fluorescence-activated cell sorting (FACS) from CD4⁺ T cells presorted from the splenocytes of C57Bl/6 mice. T cell–deficient RAG1^−/− mice were transferred with 4 × 10⁶ T_conv and 5 × 10⁵ iT_reg. Data are from three independent experiments of two to three mice per condition. (B) Weight of mice transferred with T_conv cells only (purple, n = 4), T_conv and control iT_reg cells (red, n = 8), or T_conv and Pfkp target iT_reg cells (blue, n = 8). (C) Representative colon pathology of RAG1^−/− mice at the end of the adoptive transfer experiment. Scale bars, 100 μm. (D) After sacrifice, the percentage of CD25⁺FoxP3⁺ T_reg cells was evaluated among initially transferred iT_reg identified as GFP⁺ CD4⁺ T cells, in the spleen and in mesenteric lymph nodes (mLNs; n = 8). (E) After sacrifice, the percentage of IL-17A–expressing cells was evaluated among initially transferred iT_reg identified as GFP⁺ CD4⁺ T cells, in the spleen and in mLNs (n = 8). (B) Points indicate the mean of the group, and bars show SEM. **P < 0.01 and ***P < 0.001 using two-way ANOVA with Holm-Sidak’s correction. (E and F) Each point indicates a biological replicate, and bars show means and SEM. ***P < 0.001 using one-way ANOVA test with Holm-Sidak’s correction.

CaMK4 regulates PFKP activity in CD4⁺ T cells from patients with SLE and impairs human T_reg function

To evaluate the translational value of our findings, we first confirmed that PFKP was the main PFK expressed in CD4⁺ T cells from HDs and patients with SLE (Fig. 8A). Furthermore, sorted primary human T_conv and T_reg cells expressed similar mRNA levels of PFKP and minimal levels of PFKM and PFKL (fig. S7A). In accordance with our data in mice and with previous reports of increased CaMK4 activity in SLE T cells (16), especially in patients with high disease activity (25), we found that human CD4⁺ T cells were characterized by increased PFK activity compared to age- and sex-matched HDs (P < 0.01; Fig. 8B). Moreover, the PFK activity of CD4⁺ T cells from patients with SLE correlated significantly with the SLE disease activity index (SLEDAI; r = 0.579, P < 0.005; Fig. 8C). Supporting the role of CaMK4 as a driver of PFKP activity in SLE CD4⁺ T cells, the culture of SLE CD4⁺ T cells with the CaMK4 inhibitor KN93 led to a significant decrease in PFK activity (P < 0.01; Fig. 8D), to similar levels as compared with HD CD4⁺ T cells (fig. S7B). To confirm that CaMK4 may increase PFKP enzymatic activity in healthy CD4⁺ T cells, we stimulated HD CD4⁺ T cells with ionomycin to induce CaMK4 activation (fig. S8D), which resulted in an increase in cellular PFK activity (fig. S8E). Similar to our findings with SLE CD4⁺ T cells, treatment of healthy CD4⁺ T cells with KN93 prevented the increase of PFK activity mediated by CamK4 activation.

Fig. 8. CaMK4 regulates PFKP activity in SLE CD4⁺ T cells and impairs human T_reg cell immunosuppressive functions.

(A) RT-qPCR of the three PKF isoforms in CD4⁺ T cells of HDs (n = 6) and CD4⁺ T cells of patients with SLE (n = 6). (B) PFK activity was measured from the lysate of CD4⁺ T cells cultured during 24 hours with CD3/CD28 activation. Samples from HDs (n = 11) and patients with SLE (n = 22). (C) Spearman correlation of the CD4⁺ T cell PFK activity and the SLEDAI (n = 22).The delimited gray area indicates the 95% confidence interval of the linear regression. (D) PFK activity was measured from the lysate of CD4⁺ T cells cultured during 24 hours with CD3/CD28 activation with or without KN93 (10 μM; n = 22). (E and F) Immunosuppressive assay were conducted by sorting T_conv and T_reg cells using FACS from HD. T_conv cells stained with CellTrace Violet proliferation marker were cultured either alone (upper panel) or with T_reg cells at a 1:1 ratio (bottom), with CD3/CD28 activation ± KN93 (10 μM). Cells were stained for viability, and proliferation was assessed using flow cytometry at day 7. (E) Representative results of T_conv cells proliferation. (F) The percentage of immunosuppression was calculated by comparing T_reg/T_conv cell proliferation to T_conv cell proliferation from the corresponding condition (n = 4 biological replicates). Each point represents one donor, and lines and bars indicate means and SEM. **P < 0.01 using nonparametric Mann-Whitney test (B), nonparametric Wilcoxon test (D), or unpaired two-tailed Student’s t test (F). ****P < 0.0001 using paired one-way ANOVA with Holm-Sidak’s correction. DMSO, dimethyl sulfoxide.

Last, to evaluate whether the decrease of PFKP activity through CaMK4 inhibition translated in enhanced human T_reg cell function, we conducted in vitro immunosuppression assay using freshly sorted HD T_reg cells (fig. S7D). While KN93 did not affect T_conv cell proliferation compared to the solvent dimethyl sulfoxide (Fig. 8E, top), KN93 led to improved T_reg cell–mediated suppression (P < 0.01; Fig. 8F). Collectively, these results suggest that in human CD4⁺ T cells, CaMK4 controls PFKP activity and is responsible for impaired T_reg cell immunosuppressive functions.

DISCUSSION

In the current study, we demonstrate that the rate-limiting enzyme PFKP fine-tunes T_reg cell metabolism and that its activity is controlled by CaMK4. Using immunoprecipitation and phosphoproteomics studies, we showed that CaMK4 binds and phosphorylates PFKP, most likely on the serine-539 residue, thereby mediating its effect on T_reg cells. S539 residue has been linked to the enzymatic regulation of PFKP either through GlcNacetylation, which inhibits PFKP activity (22), or through the binding of fructose-2,6-biphosphate, an allosteric activator of PFKP (23). We have linked decreased PFKP activity of CaMK4-deficient T_reg cells to increased activation of the AMPK axis, a master regulator of the mitochondrial metabolism, through reduced levels of the PFKP end product F-1,6P, which is a potent inhibitor of AMPK (26).

As a result, CaMK4-deficient iT_reg cells displayed enhanced mitochondrial respiration, increased mitochondrial content, and impaired mTOR signaling. Outside its effect on AMPK, CaMK4 may also negatively affect oxidative metabolism by promoting mitophagy through its effect on the PTEN-induced putative kinase 1 (PINK1)/PARKIN axis (27). In accordance with an increased mitochondrial content and enhanced oxidative metabolism, CaMK4-deficient iT_reg cells were characterized by increased levels of mtROS. While ROS are often considered as pathogenic intermediates (28), their effect on T_reg cell may be beneficial through the stabilization of Nuclear factor of activated T-cells (NFAT), which in turn stabilizes FoxP3 expression through a direct interaction with its CNS2 region (29, 30). However, very high levels of mtROS from damaged mitochondria may lead to DNA damage and T_reg cell death in autoimmunity (31), emphasizing the importance of a tight regulation of mtROS in T_reg cells.

Close links exist between T_reg cell metabolism and their regulatory program. The transcription factor FoxP3, which is the main driver of the T_reg cell regulatory program, promotes mitochondrial metabolism and fatty acid oxidation (32, 33). The reverse link also exists because the metabolic modulation of T_reg cells affects their differentiation, stability, and immunosuppressive functions (34). Although glycolysis is necessary during T_reg cell proliferation (35) and migration (36), T_reg cell immunosuppressive properties rely on their mitochondrial metabolism (33, 37). In accordance with these findings, we found that the modulation of glycolysis in T_reg cells using a CRISPR-Cas9–mediated Pfkp knockdown enhanced mitochondrial oxidative metabolism of and ultimately led to improved T_reg cell function and stability in vitro and in an in vivo model of adoptive transfer colitis. Because PFKP knockdown in iT_reg cells recapitulated the metabolism of Camk4^−/− iT_reg, we hypothesize that PFKP enzymatic modulation represents a major mechanism underlying the effect of CaMK4 on T_reg cells metabolism. Other studies from our group have shown the importance of CaMK4 in the differentiation of other T cell subsets, such as the proinflammatory T_H17 cells (17). In the B6.lpr lupus-like mouse, we found that a T cell–specific Camk4 deletion led to increased circulating and splenic T_reg cells, while T_H17 cells were decreased (Fig. 1, D and E). This finding is concordant with a previous report showing that a CaMK4 inhibitor (KN93) or somatic Camk4 deletion expanded the T_reg cell compartment in the MRL/lpr mouse (18, 21). However, the use of CD4-tagged nanolipogel loaded with KN93 in MRL/lpr mice led to clinical improvement without affecting the splenic T_reg and T_H17 compartment (38). This discrepancy may be explained by the lower levels of inhibition of CaMK4 with nanolipogels compared to genetic deletion (dose effect) or by the fact that nanolipogels mainly affect circulating CD4⁺ T cells (mature), while genetic deletion was effective early during T cell differentiation (time effect).

Enzymes involved in immunometabolism and their end products represent attractive therapeutic targets in autoimmune diseases. Current SLE pharmacopeia relies on nonspecific antiproliferative and immunosuppressive drugs, or more recently, on anticytokine biologics. These therapeutic strategies have limited clinical value either because of the redundancy of the immune signaling when blocking one single cytokine axis or because of the side effect of immunosuppressive drugs such as infections, which rank among the first causes of mortality in SLE (3). Modulation of the metabolism of immune cells allows the targeting of a broad range of cells without total disruption of their function, which may come with better safety profile. Recently, the well-tolerated AMPK agonist metformin was shown to have beneficial clinical effects in a proof-of-concept clinical study in SLE (6). Drugs that affect immunometabolism through other mechanisms (e.g., PPAR agonists) have also shown promising results in inflammatory disease animal models (39). Our current study identifies PFKP as a potential therapeutic target in autoimmunity as it impairs T_reg cell function and stability. Furthermore, our results in humans suggest that targeting PFKP activity through CaMK4 inhibition improves T_reg cell immunosuppressive function and may therefore represent a promising adjuvant therapy in SLE. Targeting the glucose metabolism through PFKP offers several advantages. First, PFKP modulation does not affect cellular entry of glucose, which remains crucial for cellular proliferation and the production of nucleotides via the pentose phosphate pathway (40). Second, because PFKP is a rate-limiting enzyme, the modulation of its activity affects downstream metabolites, including F-1,6P that we and the others have demonstrated to affect the metabolic rheostat through the AMPK/mTOR axis (24). Last, the targeting of the PFKP isoform limits off-target impact outside the immune system, especially in highly glycolytic organs such as the liver and the muscle, which mainly express PFKL and PFKM, respectively (41). However, the central nervous system and the heart highly express PFKP inhibition of which could have unwanted effects. In this regard, inhibition of CaMK4 would lead to more physiological inhibition of PFKP and parallel suppression of T_H17 cells (17). However, since CaMK4 is also expressed in the central nervous system, inhibitors that do not cross the blood-brain barrier should be developed.

In conclusion, we describe a new mechanism whereby CaMK4 fine-tunes T_reg cell metabolism through the phosphorylation of the glycolysis rate-limiting enzyme PFKP, thereby affecting T_reg cell function and stability in inflammatory diseases. These results identify the CaMK4/PFKP axis as a potential therapeutic target in autoimmunity, able to correct T_reg cell dysfunction, which characterizes patients with SLE.

MATERIALS AND METHODS

Study design

The aim of this study was to evaluate how CaMK4 affects cellular metabolism of T_reg cells and therefore affects their differentiation, stability, and function in human SLE. Cellular metabolism was assessed using Seahorse XFE, metabolomics studies, and cytometry (ROS quantification). We conducted phosphoproteomics study [liquid chromatography–mass spectrometry (LC-MS)] to identify that PFKP was phosphorylated by CaMK4. We then used in vitro and in vivo experiments to evaluate the importance of PFKP and CaMK4 in T_reg cell biology and in autoimmunity. Our animal protocol was approved by the Beth Israel Deaconess Medical Center institutional animal care and use committee (approvals 088-2015 and 063-2021). Patients with SLE and HDs gave informed and written consent and provided peripheral blood for research purposes. Our human research protocol was approved by the Beth Israel Deaconess Medical Center Institutional Review Board (2006-000298).

Human samples

Adult patients diagnosed with SLE according to the ACR/EULAR 2019 classification criteria and followed at the Beth Israel Deaconess Medical Center (BIDMC) rheumatology outpatient clinic were offered to participate to the study. HDs were recruited by the rheumatology outpatient clinic. For human immunosuppressive assays, leukocytes from healthy blood donors were retrieved using apheresis leukoreduction by the Blood Donor Center (Boston Children Hospital). CD4⁺ T cells were isolated using Ficoll gradient separation of heparinized whole blood preincubated with a RosetteSep human CD4⁺ T cell enrichment kit (STEMCELL Technologies).

Mice

All the mice were housed in the pathogen-free Animal Resource Facility from Beth Israel Deaconess Medical Center (Center for Life Science). C57BL/6 (B6), B6.129X1-Camk4^tm1Tch/J (Camk4^−/−, strain 004994), C57BL/6.Foxp3^IRES-GFP (Foxp3-Gfp, strain 006769), B6J.129(Cg)-Gt(ROSA)26Sortm1.1(CAG-cas9*,-EGFP)Fezh/J (Cas9.Gfp, strain) mice, B6.MRL-Fas^lpr/J (B6.lpr; strain 000482) mice, and B6.129S7-Rag1^tm1Mom/J (Rag1^−/−; strain 002216) mice were purchased from the Jackson Laboratory. Camk4^fl/fl.dlck-Cre mice were maintained in our in-house colony and crossed with the B6.MRL-Fas^lpr/J. All mice were housed in specific pathogen–free condition at the Beth Israel Deaconess Medical Center mouse facility [Center for Life Science (CLS) site]. Adoptive transfer colitis model was conducted by retro-orbital injection of 4 × 10⁶ of flow cytometry–sorted CD45RB^hi CD4⁺ T cells (from C57Bl/6 mice) ± 5 × 10⁵ iT_reg cells (from C57Bl/6.Cas9-Gfp) to 8-week-old Rag1^−/− mice. At the end of experiment, spleens and cervical or mesenteric lymph nodes were retrieved to conduct cytometry. The colon (colitis model) or the kidney (B6.lpr model) were placed in a cassette, fixated in formalin 10% for 24 hours, and embedded in paraffin for cutting followed by periodic acid Schiff or hematoxylin and eosin coloration. The kidney pathology was evaluated by an experienced pathologist (M.G.T) blinded to the mouse genotype. Glomerular pathology and perivascular infiltration were scored from 0 to 3 (3 indicating more severe disease) as described previously (42).

T cell culture and in vitro T_reg cell differentiation

Murine CD62L⁺ CD4⁺ T cells were magnetically sorted from freshly isolated splenocytes using a Miltenyi CD62L⁺ CD4⁺ T cell sorting kit according to the manufacturer’s instructions. Naive CD4⁺ T cells (3 × 10⁵) were cultured on with RPMI 1640 medium supplemented with 10% fetal bovine serum, penicillin/streptomycin, and β-mercaptoethanol in a 48-well plate precoated with goat anti-hamster cross-linking antibody. To obtain iT_reg cells in vitro, the medium was supplemented with anti-CD3 (0.25 μg/ml, 145-2C11; BioLegend, San Diego, CA), anti-CD28 (0.5 μg/ml, 37.51; BioXcell, Lebanon, NH), IL-2 (20 ng/ml; R&D Systems), transforming growth factor–β1 (TGF-β1; 1.0 ng/ml; R&D Systems), anti–IFN-γ (10 μg/ml; BioXcell), and anti–IL-4 (10 μg/ml; BioXcell). To evaluate iT_reg stability, day 3–differentiated iT_reg cells were cultured 24 hours with T_H17-differentiating conditions: anti-CD3 (0.25 μg/ml), anti-CD28 (0.5 μg/ml), IL-6 (3 ng/ml; R&D Systems), TGF-β1 (0.3 ng/ml), anti–IFN-γ (10 μg/ml), and anti–IL-4 (10 μg/ml).

Transfection

For overexpression experiments, the transfection of 15 μg of the vector (listed in table S3) was conducted using the Amaxa Mouse T Cell Nucleofector Kit with the X-001 program (Lonza, Basel, Switzerland) following the manufacturer’s instructions. Electroporation was conducted on day 2 of differentiation, and the transfected cells were evaluated at day 3 using flow cytometry and gating on viable transfected (GFP⁺ or DsRed⁺) cells. For CRISPR-Cas9 gene knockdown experiments, 50 pmol of each targeting sgRNA was transfected in CAS9-expressing cells at day 1 of differentiation using the X-001 program.

Site-directed mutagenesis

Site-directed mutagenesis of PFKP-OE vector was conducted using a Q5 site-directed mutagenesis kit (New England Biolabs, Ipswich, MA) following the manufacturer’s instructions. The primers used for mutagenesis were designed using the New England Biolabs mutagenesis primer design online tool (table S3). After mutagenesis, the products were Sanger-sequenced (Azenta, Chelmsford USA) to verify correct mutagenesis.

FoxP3 promoter methylation study

Genomic DNA was extracted from 10⁶ iT_reg cells using a Qiamp DNA mini kit (Qiagen) according to the manufacturer’s instructions. Genomic DNA (500 ng to 1 μg) was converted using an Epitect Fast bisulfite conversion kit (Qiagen) according to the manufacturer’s instructions. Bisulfite-treated DNA (500 ng) was submitted to EpigenDx (Hopkinton MA, USA) for amplification and next-generation sequencing.

Flow cytometry and cell sorting

Surface staining was conducted in phosphate-buffered saline (PBS) for 15 min at room temperature. Intracellular staining was conducted by fixing cells with Cytofix/Cytoperm buffer (15 min, +4°C) and then staining with the antibody in Perm/wash buffer overnight at +4°C (BD Biosciences, Franklin Lakes, NJ, USA). For cytokine evaluation, the cells were stimulated in complete RPMI 1640 medium with phorbol myristate acetate (500 ng/ml; Sigma-Aldrich, St. Louis, MI, USA), ionomycine (1.4 μg/ml; Sigma-Aldrich), and GolgiStop (BD Biosciences). Zombie Aqua and Zombie ultraviolet fixable viability markers (BioLegend) were used to gate on living cells. Flow cytometry acquisition was conducted with Cytoflex (Beckman Coulter, Brea, CA) and cell sorting using FACSAria (BD). For cell sorting, the purity of the sorted population was over 95%. Flow cytometry analysis was conducted using FlowJo software (BD Biosciences).

Enzyme-linked immunosorbent assay

dsDNA antibody levels were measured using a homemade enzyme-linked immunosorbent assay as previously described (43). Briefly, sera were diluted 1:50 with 1% PBS bovine serum albumin and incubated at room temperature with shaking for 2 hours on 96-well plates precoated with l-lysin (0.05 mg/ml) for 2 hours at room temperature, then coated with Calf thymus DNA (0.1 mg/ml, Sigma-Aldrich), +4°C overnight. Standard was made using serial dilution of the serum of one 16-week-old MRL/lpr mouse. After washing, the wells were incubated with an alkaline phosphatase–conjugated goat anti-mouse immunoglobulin G antibody (1:5000; Jackson ImmunoResearch) for 1 hour, and colorimetric reaction was provoked by adding diethanolamine substrate buffer (Thermo Fisher Scientific) and PNPP (p-Nitrophenyl Phosphate)-phosphatase substrate (Sigma-Aldrich) and read at 405 nm. The results are expressed as units per volume.

Metabolic assays and metabolomics study

Glycolysis stress test and mitochondrial stress test were conducted using a Seahorse XF HS mini device (Agilent). A total of 2 × 10⁵ cells per well were plated on an XFp culture miniplate precoated with Celltak (Corning). The assay was conducted following the manufacturer’s instructions.

Cellular phosphofructokinase 1 enzymatic activity was measured using the PKF assay (Abcam) from cell lysates of murine or human CD4⁺ T cell. The cell lysates were prepared using 100 μl of assay buffer, snap-frozen in liquid nitrogen, and stored at −80°C until further processing. Protein concentration of the cell lysate was measured using Coomassie protein assay (Sigma-Aldrich) conducted in triplicate. The assay was conducted following the manufacturer’s instructions, and the results are expressed as nanomole of enzymatic reaction per minute per microgram of input protein.

For the metabolomics study, the medium of differentiating iT_reg cells was replaced by a new medium 2 hours before metabolite extraction. Cells were retrieved in a Falcon tube, and metabolites were extracted using 80% prechilled methanol mixed with molecular biology–grade water and incubated at −80°C for 15 min. Cell debris was pelleted, and the supernatant containing metabolites was dried using a Speedvac device. The pellets containing the metabolite were resuspended in 20 μl of LC-MS–grade water and processed by the BIDMC LC-MS platform (https://bidmcmassspec.org/). The procedure was conducted with biological triplicates, and the results were analyzed using the metaboanalyst platform (www.metaboanalyst.ca).

Western blotting

Cell lysates were loaded on NuPAGE 4 to 12% Bis-Tris Gel (Thermo Fisher Scientific) and subsequently transferred to a nitrocellulose membrane. After blocking with 6% skimmed milk, the membrane was incubated with a primary and then a secondary antibody (list in table S2). Bands were revealed using the ECL System (Cytiva, Marlborough, MA) and detected with ChemiDoc XRS+ (Bio-Rad, Hercules, CA USA). The images were analyzed for densitometry using the Image Lab software (Bio-Rad).

Immunoprecipitation and phosphoproteomics

Cell lysates were precipitated using the Dynabeads Protein G Immunoprecipitation Kit (Thermo Fisher Scientific) with an anti-FLAG or an anti-PFKP antibody (table S2) following the manufacturer’s instructions. The immunoprecipitated protein was migrated on an NuPAGE 4 to 12% Bis-Tris Gel for Western blot (as described above). For the phosphoproteomics study, gel band containing PFKP (80 to 90 kDa) was identified using Coomasie Blue staining SimplyBlue Safestain (Thermo Fisher Scientific) and cut for subsequent phosphoproteomics analysis (BIDMC LC-MS platform; https://bidmcmassspec.org/).

RNA isolation and quantitative polymerase chain reaction

RNA was isolated using TRIzol reagent (Sigma-Aldrich), and complementary DNA (cDNA) was obtained using RNA to cDNA EcoDry tubes (Takara, Mountain View, CA, USA) following the manufacturer’s instructions. The quantitative polymerase chain reaction was conducted with TaqMan probes (see list in table S3), Taqman reaction buffer, and cDNA, according to the manufacturer’s instructions, with a LightCycler 480 device (Roche). Relative gene expression was calculated using the ΔCt method with TATA-box Binding Protein (TBP) as the housekeeper gene.

Immunosuppressive assay

For mouse immunosuppression assay, 5 × 10⁴ magnetically sorted CD4⁺ T cells (Miltenyi) stained with CellTrace Violet (5 μM; Thermo Fisher Scientific) were cocultured with iT_reg cells (ratio of 1:1 to 1:4) together with 10⁵ antigen-presenting cells (splenocytes treated with mitomycin C) under CD3-activating condition (5 μg/ml)/CD28-activating condition (3 μg/ml). After 3 days of culture, the proliferation of CD4⁺ T cells was assessed using CellTrace Violet dilution and FlowJo V10 (Ashland, OR, USA) proliferation module.

For human immunosuppression assay, FACSAria-sorted 5 × 10⁴ T_reg (CD25⁺CD127⁻CD4⁺) cells were cocultured at 1:1 ratio with T_conv (CD25⁻CD127⁺CD4⁺) cells stained with CellTrace Violet (5 μM) in a CD3-coated (5 μg/ml) 96-well plate together with soluble anti-CD28 (5 μg/ml; BioXcell). After 7 days of culture, the proliferation of CD4⁺ T cells was assessed using CellTrace Violet dilution and FlowJo V10 (Ashland, OR, USA) proliferation module.

Statistical analysis

Statistical analysis was conducted using GraphPad Prism Version 9. In figures, points show individual data points, bars represent the mean, and error bars indicate SEM. Quantitative data were compared between two groups using Student’s two-tailed t test or one-way analysis of variance (ANOVA) with Holm-Sidak’s correction for multiple analysis when comparing more than two groups, unless indicated otherwise. Correlation was computed using the nonparametric Spearman correlation test. In figures, statistical results are indicated as follows: not significant (ns), P ≥ 0.05; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

Supplementary Materials

This PDF file includes:

Figs. S1 to S8

Tables S1 to S3

Other Supplementary Material for this manuscript includes the following:

Data files S1 to S4

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