Antisense to human CD39 dysregulates immune metabolism in inflammatory bowel disease

Abstract

Defective CD39 levels contribute to an imbalance between Tregs and Th17 effectors in inflammatory bowel disease (IBD). CD39 initiates an ATP hydrolysis cascade that culminates with the generation of adenosine, an immune metabolite that is key to tissue homeostasis. Human CD39 is regulated by an endogenous antisense RNA (CD39-AS) that is markedly elevated in IBD Tregs and Th17 cells. In this study, we investigated how CD39-AS affects the function of Tregs and Th17 cells in healthy subjects and IBD patients. We report that CD39-AS RNA is present in two main splice variants that are specifically expressed by Tregs or Th17 cells. Blockade of CD39-AS via self-delivering oligonucleotides targeting the splice variant expressed in Tregs results in a decrease of glucose transport and glycolysis and in enhanced Treg function and stability in IBD. In Th17 cells, silencing of CD39-AS limits oxidative responses and ameliorates mitochondrial health. These metabolic effects are also noted in a model of experimental colitis in humanized mice, along with reduced disease activity. Thus, in vivo administration of oligonucleotides targeting the Treg or Th17 cell CD39-AS variant limits disease activity, decreases the expression of GLUT1 and improves mitochondrial health in gut-derived CD4 lymphocytes. Mechanistically, activation of HIF-1α and STAT3 results in the upregulation of CD39-AS in IBD cells. In conclusion, CD39-AS is an important modulator of Treg and Th17 cell metabolism. Interference with this antisense RNA, or the factors favoring its upregulation, might contain inflammation and halt disease progression in IBD by restoring immune metabolism and Treg functional stability.

INTRODUCTION

In inflammatory bowel disease (IBD), imbalance between regulatory T cells (Tregs), a lymphocyte subset central to immune homeostasis, and T effector cells (Teffs) is favored by dysfunctional CD39, an ectonucleotidase that plays a central role in the maintenance of immune tolerance [1-3]. CD39 hydrolyzes adenosine triphosphate (ATP) and adenosine diphosphate (ADP) into adenosine monophosphate (AMP), which is subsequently converted into immunosuppressive adenosine by the ectoenzyme CD73 [2, 3]. CD39 is highly expressed on endothelial cells and immune cells, including Tregs [4], where it contributes to suppressive function through the pericellular generation of adenosine, and on a subset of effector Th17 cells, where it imparts regulatory properties and limits pathogenic potential [5, 6].

CD39 can be regulated at the genetic level via single nucleotide polymorphisms in noncoding regions of the gene that are correlated with CD39 mRNA expression [7]. CD39 is also regulated at the transcriptional level through the activation of aryl hydrocarbon receptor (AhR), a transcription factor that mediates toxin responses and modulates adaptive immunity; through alterations in oxygen levels and hypoxia inducible factor 1 alpha (HIF-1α), which in the context of chronic inflammation negatively regulates CD39 in Th17 cells [8]; and through signal transducer and activator of transcription 3 (STAT3) via IL-6 [9]. We have recently shown that CD39 can also be regulated at the posttranscriptional level by an endogenous antisense RNA (CD39 antisense, CD39-AS), with multiple splice variants originated several kilobases downstream of the CD39 gene on human chromosome 10 (long arm) [10]. CD39-AS RNA is upregulated in both Tregs and Th17 cells obtained from the peripheral blood and lamina propria (LP) of Crohn’s disease patients [10]. CD39-AS is located mainly in the cell nucleus, where it interacts with nuclear proteins such as nucleolin and heterogeneous ribonuclear protein A1, the blockade of which restores CD39 levels in Tregs and Th17 cells of patients with Crohn’s disease [10].

Long noncoding RNAs (lncRNAs) are known to regulate multiple biological functions, including the p53-mediated response to DNA damage [11], cytokine expression [12], inflammation [13, 14] and cell metabolism, including glucose metabolism [15], cholesterol biosynthesis [16] and cell signaling [17, 18]. How CD39-AS RNA modulates the function of Tregs and Th17 cells remains untested. Furthermore, the factors involved in its upregulation in IBD-derived cells are unclear.

Here we show that CD39-AS RNA modulates the metabolic function of Tregs and Th17 cells, with blockade of the antisense limiting glucose transport and glycolytic capacity in Tregs and restraining oxidative responses in Th17 cells. These phenomena are noted in vitro in cells obtained from controls and IBD patients, in which antisense silencing results in stabilization of the Treg phenotype and improved suppression, and in a mouse model of experimental colitis in NOD/scid/gamma humanized mice. The transcription of CD39-AS RNA is differentially modulated in healthy individuals and IBD patients, as hypoxia and HIF-1α favor antisense upregulation in Tregs from both groups, whereas STAT3 activation leads to antisense upregulation in Th17 cells from IBD patients.

RESULTS

Silencing of CD39-AS RNA controls Treg glucose metabolism

To determine how CD39-AS RNA impacts cell function, we initially tested the effects of this long noncoding RNA on cell transcriptome. To this end, we exposed Jurkat cells that we previously showed to express high levels of CD39-AS RNA [10] to self-delivering AUMsilence antisense oligonucleotides (AUMsilence ASOs, AUM LifeTech, Philadelphia, PA) that specifically target the ENST0000045278.5 ENTPD1-AS1-209 variant (v1, CD39-ASv1) according to Harshe et al. [10]), which is highly expressed in Jurkat cells [10]. Bulk RNA-seq carried out following treatment with CD39-ASv1-ASO indicated that blockade of CD39-AS RNA resulted in differential expression of 4129 genes. Silencing of CD39-AS downregulated 1368 genes, including CCNE2, encoding cyclin E2, which plays a role in the G1/S phase of the cell cycle; ABCB10, encoding a transporter belonging to the MDR/TAP subfamily of drug transporters; and ASS1, encoding arginine succinate synthase, which is involved in the urea cycle (Fig. 1A and Supplementary Table 1). Treatment of Jurkat cells with CD39-ASv1-ASO resulted in the upregulation of 2761 genes, including PLEC, encoding plectin, a crosslinking element of the cytoskeleton; AHNAK, encoding a negative regulator of cell growth; and COL7A1, encoding a protein involved in collagen formation (Fig. 1A and Supplementary Table 1). Kegg pathway and gene set enrichment analysis (GSEA) identified “tryptophan metabolism”, “metabolism of xenobiotics by cytochrome P450” and “TGF beta signaling pathway” as some of the gene sets mostly enriched in Jurkat cells treated with CD39-ASv1-ASO (Fig. 1B, C); these data suggest a role for CD39-AS RNA in the modulation of cell metabolic functions.

Fig. 1.

Silencing of CD39-AS RNA results in enrichment of metabolic gene sets in Jurkat cells. Jurkat cells were subjected to bulk RNA-seq after exposure to scrambled-ASO (scr) or CD39-ASv1-ASO for 72 h. A Volcano plot showing upregulated (red) and downregulated (blue) genes in CD39-AS-ASO-treated Jurkat cells compared with those treated with scrambled-ASO. The X- and Y-axes correspond to the log2-fold change and −log₁₀(p value), respectively (n = 3). B KEGG gene sets enriched in Jurkat cells treated with CD39-ASv1-ASO compared with those treated with scrambled-ASO. Positively enriched gene sets are indicated on the right; negatively enriched gene sets are indicated on the left. C GSEA plots showing that the KEGG Tryptophan Metabolism, KEGG Metabolism of Xenobiotics by Cytochrome P450 and KEGG TGF Beta Signaling Pathway gene sets are enriched in CD39-ASv1-ASO-treated Jurkat cells. Gene sets enriched at a nominal p value of <0.05 and a false discovery rate (FDR) of <25% were considered significant

CD39-AS RNA expression is more elevated in Tregs and Th17 cells than in other T-cell subsets [10]. We therefore tested the effects of its silencing on the metabolic gene profiles of Tregs and Th17 cells obtained from the peripheral blood of healthy subjects using the NanoString nCounter Metabolic Pathways Panel (Nano-String, Seattle, WA) as a more targeted transcriptomic approach. Changes in metabolic genes were examined in the presence of ASO to scrambled RNA or the CD39-ASv1 variant in Tregs, having shown more effective downregulation of the antisense in Tregs treated with CD39-ASv1-ASO (Supplementary Fig. 1A).

We noted downregulation of genes involved in glucose transport (SLC2A1, which encodes GLUT1) and glycolysis (HK2) in Tregs treated with CD39-ASv1-ASO compared with Tregs exposed to scrambled-ASO (Fig. 2A, Supplementary Fig. 1B, C and Supplementary Table 2). These effects resulting from antisense blockade were also noted upon CD39 silencing (Supplementary Fig. 1B, C), ruling out the possibility that decreases in SLC2A1 and HK2 could result from CD39 upregulation due to antisense silencing, as shown previously [10]. GSEA revealed that CD39-ASv1 silencing in Tregs was negatively correlated with genes associated with glucose transport (Fig. 2B).

Fig. 2.

Silencing of CD39-AS RNA inhibits glucose metabolism in Tregs. Tregs obtained from the peripheral blood of healthy subjects were exposed to scrambled-ASO (scr) or CD39-ASv1-ASO for 72 h. Differences in metabolic gene expression were evaluated via NanoString using the nCounter Metabolic Pathways Panel. A Volcano plot showing upregulated (red) and downregulated (blue) genes in CD39-AS-ASO-treated Treg cells compared with scrambled-ASO-treated cells. The X- and Y-axes correspond to the log2-fold change and −log₁₀ (p value), respectively. The experiment was run in triplicate and repeated independently three times. B GSEA plot showing that the NanoString glucose transport gene set was negatively enriched in CD39-ASv1-ASO-treated Tregs compared with scr-treated Tregs. C Uptake of glucose by scr- and CD39-ASv1-ASO-treated Tregs was determined using the Glucose Uptake-glo Assay. Line graphs represent the relative light units (RLUs) of Tregs obtained from the peripheral blood of n = 9 healthy subjects (HS) and n = 7 inflammatory bowel disease (IBD) patients and from the lamina propria of colon biopsies or resections collected from n = 6 IBD patients (4 active and 2 inactive); *p ≤ 0.05 (two-sided paired t test). D, E The extracellular acidification rate (ECAR) of peripheral blood Tregs exposed to scr- or CD39-ASv1-ASO was determined via Seahorse. Mean ± SEM ECAR of scr- and CD39-ASv1-ASO-treated Tregs from n = 7 HS and seven IBD patients; *p ≤ 0.05 (two-sided paired t test). F Line graphs showing the glycolytic capacity of scr- and CD39-ASv1-ASO-treated Tregs obtained from the peripheral blood of n = 7 HS and n = 7 IBD patients; *p ≤ 0.05 (two-sided paired t test). G Treg proliferation was determined using the Cell Titer 96^® Aqueous One Solution Cell Proliferation Assay. Line graphs representing the absorbance at 490 (A₄₉₀) nm of scr- and CD39-ASv1-ASO-treated Tregs obtained from the peripheral blood of n = 5 HS and n = 9 IBD patients; *p ≤ 0.05 (two-sided paired t test). H Treg ectoenzymatic activity was determined by malachite green assay after cell exposure to ATP. Line graphs showing μM phosphate in the culture supernatant of scr- and CD39-ASv1-ASO-treated Tregs obtained from the peripheral blood of n = 8 HS and n = 6 IBD patients and from the lamina propria of colon biopsies or resections collected from n = 4 IBD patients (2 active and 2 inactive); *p ≤ 0.05, **p ≤ 0.01 (two-sided paired t test). I Percentage inhibition of CD4⁺CD25⁻ cell proliferation by peripheral blood Tregs exposed to scr- or CD39-ASv1-ASO in n = 8 HS and n = 8 IBD patients; *p ≤ 0.05 (two-sided paired t test)

The effects of CD39-ASv1 silencing were subsequently tested at the functional level in Tregs obtained from healthy subjects and IBD patients. In this analysis, cells obtained from both Crohn’s disease patients and ulcerative colitis patients were included, as the antisense was upregulated in the Tregs of patients from both groups (Supplementary Fig. 2A). Silencing of CD39-ASv1 resulted in decreased glucose uptake in Tregs obtained from the peripheral blood of controls, IBD patients, and from the LPs of IBD patients (Fig. 2C). Treatment with fasentin, a specific inhibitor of the glucose transporter GLUT1, increased the ability of Tregs to suppress, even in the presence of high glucose concentrations (Supplementary Fig. 1D). In contrast, exposure to insulin, which activates glucose transport, resulted in decreased Treg suppression in both controls and IBD patients (Supplementary Fig. 1E).

Importantly, in IBD, the percentage inhibition of glucose uptake was inversely correlated with C-reactive protein (CRP) levels (Supplementary Fig. 2B).

In both controls and patients, the silencing of CD39-ASv1 in Tregs limited the extracellular acidification rate (ECAR), glycolytic capacity (Fig. 2D-F) and cell proliferation (Fig. 2G).

The regulation of glucose metabolism following antisense blockade was accompanied by increased ectoenzymatic activity, as reflected by heightened free phosphate concentrations in the culture supernatants of control and IBD Tregs (Fig. 2H); and ameliorated the suppression of CD4⁺CD25⁻ cell proliferation by IBD Tregs (Fig. 2I).

Since in chronic inflammatory and autoimmune conditions Tregs have a high propensity to acquire proinflammatory features and convert into effector cells when exposed to an inflammatory challenge, we tested whether the silencing of CD39-ASv1 could limit this phenomenon. After the addition of CD39-ASv1-ASO, Tregs were exposed to IL-6 and IL-1β [19, 20]. In IBD, exposure to CD39-ASv1-ASO boosted the frequency of FOXP3⁺ cells among Tregs exposed to IL-6 and IL-1β (Fig. 3A). Exposure to a proinflammatory challenge resulted in a marked increase in the proportion of RORC⁺ and IL-17⁺ lymphocytes that were reduced to baseline levels in the presence of CD39-ASv1-ASO (Fig. 3B, C). No significant changes in the proportions of FOXP3⁺, RORC⁺, IL-17⁺ and IFNγ⁺ cells were noted in the Tregs of healthy subjects or in the proportion of IFNγ⁺ cells among IBD Tregs following exposure to proinflammatory challenge in the absence or presence of CD39-ASv1-ASO (Fig. 3A-D).

Fig. 3.

Blockade of CD39-AS RNA stabilizes Tregs in IBD. Treg functional phenotype was tested in the presence of a proinflammatory challenge consisting of IL-6 and IL-1β in scrambled-ASO (scr)- and CD39-ASv1-ASO-treated Tregs obtained from the peripheral blood of HS and IBD patients. Mean ± SEM frequency of A FOXP3⁺, B RORC⁺, C IL-17⁺, and D IFNγ⁺ Tregs exposed to scr-, CD39-ASv1-ASO, scr- + IL-6/IL-1β and CD39-ASv1-ASO + IL-6/IL-1β (HS, n = 5; IBD, n = 5). *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001 (one-way ANOVA followed by Tukey’s multiple comparisons test)

The effects of antisense blockade on glucose metabolism, ectoenzymatic activity, suppressive function and plasticity after proinflammatory challenge were comparable in the Tregs of patients with Crohn’s disease and those with ulcerative colitis.

Overall, these data show that CD39-AS impacts glucose metabolism and boosts ectoenzymatic activity in healthy subject and IBD Tregs and that antisense silencing enhances the suppression and stability of Tregs in IBD. These findings suggest that this lncRNA might play an important role in the control of immune regulation.

Blockade of CD39-AS modulates oxidative responses in Th17 cells

Changes in metabolic pathway gene expression were evaluated following the exposure of Th17 cells to scrambled-ASO or CD39-AS-ASO specifically targeting the ENST00000414006.2 ENTPD1-AS1-201 v2 (CD39-ASv2) variant, with initial experiments showing marked antisense inhibition in Th17 cells treated with CD39-AS-ASO specific for this variant (CD39-ASv2-ASO) (Supplementary Fig. 3A). Blockade of the antisense in Th17 cells resulted in decreased levels of proline-rich 5 (PRR5), encoding a proline-rich protein that is part of the mammalian target of rapamycin complex 2 (mTORC2), and increased levels of ERCC6 (Fig. 4A, Supplementary Fig. 3B, C and Supplementary Table 3), encoding a Cockayne syndrome B (CSB) protein, which has ATPase activity and is involved in DNA damage and the control of oxidative responses [21]. The silencing of CD39-ASv2 induced gene expression changes that were persistent in the presence of CD39 silencing (Supplementary Fig. 3B, C), indicating that these effects are likely due to antisense blockade and not to the resulting CD39 upregulation [10].

Fig. 4.

Silencing of CD39-AS RNA limits oxidative responses in Th17 cells. Th17 cells obtained from the peripheral blood of healthy subjects were exposed to scrambled-ASO (scr) or CD39-ASv2-ASO for 72 h. Differences in metabolic gene expression were evaluated via NanoString using the nCounter Metabolic Pathways Panel. A Volcano plot showing upregulated (red) and downregulated (blue) genes in CD39-ASv2-ASO-treated Th17 cells compared with scrambled-ASO-treated cells. The X- and Y-axes correspond to the log2-fold change and −log₁₀(p value), respectively. The experiment was run in triplicate and repeated independently three times. B, C The oxygen consumption rate (OCR) of peripheral blood Th17 cells exposed to scr- or CD39-ASv2-ASO was determined via Seahorse. Mean ± SEM OCR in scr- and CD39-ASv2-ASO-treated Th17 cells from n = 7 HS and n = 6 IBD patients; *p ≤ 0.05, **p ≤ 0.01 (two-sided paired t test). Line graphs showing D maximum respiration and E spare respiratory capacity of scr- and CD39-ASv2-ASO-treated Th17 cells obtained from the peripheral blood of n = 7 HS and n = 6 IBD patients; *p ≤ 0.05 (two-sided paired t test). F–H Line graphs representing the JC-1 red/green ratio in scr- and CD39-ASv2-ASO-treated Th17 cells obtained from the peripheral blood of n = 8 HS patients and n = 5 IBD patients and from the lamina propria of colon biopsies or resections collected from n = 8 IBD patients (4 active and 4 inactive); *p ≤ 0.05, **p ≤ 0.01 (two-sided paired t test). Representative histograms of red (PE, representing “aggregates”) and green (FITC, representing “monomers”) fluorescence in Th17 cells exposed to scr-, carbonyl cyanide m-chlorophenyl hydrazone (CCCP) or CD39-ASv2-ASO

The effects of CD39-ASv2-ASO treatment were tested at the functional level in Th17 cells obtained from healthy subjects and IBD patients. Th17 cells from patients with Crohn’s disease and ulcerative colitis were included, as CD39-AS RNA was upregulated in Th17 cells obtained from both groups (Supplementary Fig. 4A). Silencing of antisense decreased IL-17A and IL-22 levels (Supplementary Fig. 5A, B) and limited the oxygen consumption rate (OCR), maximum respiration and spare respiratory capacity (i.e., the difference between basal ATP production and maximal activity) in Th17 cells obtained from the peripheral blood of controls and IBD patients (Fig. 4B-E); these data further corroborate the transcriptome analysis and suggest a role for the antisense in the regulation of oxidative responses, mitochondrial activity and health. In IBD Th17 cells, the percentage inhibition of maximum respiration was inversely correlated with CRP levels (Supplementary Fig. 4B). Blockade of CD39-ASv2 limited mitochondrial depolarization, as reflected by an increased red/green fluorescence ratio on JC-1 staining, with red fluorescence (aggregates) representing “healthy mitochondria” and being associated with high mitochondrial membrane potential; and with green fluorescence (monomers) representing “unhealthy mitochondria” and being associated with low mitochondrial membrane potential. This was noted in peripheral blood Th17 cells from healthy subjects (Fig. 4F) and IBD patients (Fig. 4G), in whom a comparable pattern was present when Th17 cells from the LP were analyzed (Fig. 4H). Control of oxidative responses upon exposure to CD39-ASv2-ASO resulted in limited ROS mitochondrial production in healthy subjects and IBD Th17 cells (Supplementary Fig. 6).

Overall, these data indicate that blockade of CD39-AS impacts Th17 cell metabolism by decreasing oxidative responses and enhancing mitochondrial fitness.

Silencing of CD39-AS modulates metabolic function and clinical outcome in experimental colitis

The metabolic effects of CD39-AS silencing were also evaluated in a well-established model of experimental colitis in NOD/scid/gamma mice reconstituted with human CD4 cells expressing CD39-AS RNA, as we previously reported [10]. NOD/scid/gamma immunodeficient mice were repopulated with CD39-AS⁺ CD4⁺ cells obtained from one healthy blood donor and tested for CD4⁺ T-cell reconstitution after 3 weeks. As we reported previously, reconstituted mice were sensitized with trinitrobenzene sulfonic acid (TNBS) and, one week later, administered TNBS intrarectally, treated with scrambled-ASO, CD39-ASv1-ASO or CD39-ASv2-ASO and sacrificed 72 h later (Fig. 5A). Compared with scrambled-ASO-treated mice, those treated with CD39-ASv1-ASO or CD39-ASv2-ASO presented a lower disease activity index (DAI) (Fig. 5B), increased colon length (Fig. 5C), a reduced histology score (Fig. 5D) and decreased infiltration of CD3⁺ lymphocytes (Supplementary Fig. 7A). In mice treated with CD39-ASv1-ASO, there was a decrease in the frequency of GLUT1⁺ cells among CD4 lymphocytes isolated from the LP (Fig. 5E), whereas in mice administered CD39-ASv2-ASO, an increase in the JC-1 Red/Green ratio was noted in CD4⁺ lymphocytes obtained from the intraepithelial (IEL) and LP compartments (Fig. 5F). While no differences in the proportions of CD3⁺CD4⁺, CD4⁺CD25^highFOXP3⁺ and CD4⁺IL-17A⁺ lymphocytes were noted between scrambled-ASO- and CD39-ASO-treated mice in all the compartments tested (Supplementary Fig. 7B-D), the levels of CD39 were greater in the MLN and IEL Tregs of mice exposed to CD39-ASv1-ASO (Supplementary Fig. 8A); and in the MLN CD4⁺IL-17A⁺ cells of mice treated with CD39-ASv2-ASO (Supplementary Fig. 8B).

Fig. 5.

Blockade of CD39-AS RNA limits glucose transport and oxidative responses in experimental colitis in NOD/scid/gamma humanized mice. A NOD/scid/gamma female recipients were reconstituted with CD39-AS⁺ CD4 lymphocytes, obtained from one healthy volunteer. After three weeks, mice were checked for human chimerism, and those displaying more than 10% human chimerism were initially sensitized to TNBS and, after seven days, administered TNBS intrarectally. At the same time of TNBS administration, mice were treated with a single injection of scrambled-ASO (scr), CD39-ASv1-ASO or CD39-ASv2-ASO and sacrificed 72 h later. Mean ± SEM (B) disease activity index (DAI) and C colon length in recipients treated with scrambled-ASO (scr, n = 5), CD39-ASv1-ASO (n = 5) or CD39-ASv2-ASO (n = 5). D Mean ± SEM histology score at the harvest in mice treated with scr-, CD39-ASv1-ASO or CD39-ASv2-ASO. Hematoxylin and eosin (H&E) and anti-human CD3 staining of colon sections (original magnification ×20, scale bar 100 μm). *p ≤ 0.05, **p ≤ 0.01 (one-way ANOVA followed by Tukey’s multiple comparisons test). Mean ± SEM (E) frequency of Glut1⁺ cells within CD4 lymphocytes and F JC-1 red/green ratio of CD4⁺ cells isolated from the spleen, mesenteric lymph node (MLN), intraepithelial (IEL) and lamina propria (LP) of mice treated with scr-, CD39-ASv1-ASO or CD39-ASv2-ASO. Representative histograms of Glut1, red PE (representing “aggregates”) and green FITC (representing “monomers”) fluorescence of CD4⁺ cells isolated from the spleen, MLN, IEL and LP are shown. *p ≤ 0.05, **p ≤ 0.01 (unpaired t test)

Collectively, these data show that the beneficial properties of CD39-AS silencing might be linked to the control of glucose metabolism and to the limitation of oxidative responses.

CD39-AS is differentially regulated in healthy individuals and patients with IBD

To determine the factors involved in the upregulation of CD39-AS RNA in IBD-derived cells, we initially conducted bioinformatic analysis of the CD39-ASv1 (i.e., ENTPD1-AS1-209) and CD39-ASv2 (i.e., ENTPD1-AS1-201) promoter regions using JASPAR and identified several predicted binding sites for transcription factors such as HIF-1α, which is upregulated during chronic inflammatory conditions [8, 22]; STAT3, which regulates CD39 via IL-6; and the tumor suppressor Krüppel-like factor 6 (KLF6) (see Supplementary notes for HIF-1α, STAT3 and KLF6 binding sites). Silencing of HIF-1α resulted in decreased levels of CD39-AS in Tregs from healthy subjects and IBD patients (Fig. 6A). No changes in CD39-AS RNA levels were noted after silencing STAT3 and KLF6 in healthy subjects and IBD Tregs (Fig. 6B, C).

Fig. 6.

CD39-AS RNA is differentially modulated in healthy control and IBD derived cells. By performing bioinformatic analysis of the promoter of CD39-AS, we identified HIF-1α, STAT3 and KLF6 as transcription factors with high binding scores. Mean ± SEM CD39-AS RNA levels after Treg or Th17 cells were exposed to scrambled (scr), HIF-1α (A, D), STAT3 (B, E), or KLF6 (C, F) siRNA ( Tregs: HS, n = 6–8; IBD, n = 5; Th17 cells: HS, n = 6–9; IBD, n = 4). Blockade of HIF-1α results in decreased antisense levels in Tregs from both HS and IBD patients, whereas silencing of STAT3 results in decreased antisense levels in Th17 cells obtained from IBD patients. Mean ± SEM CD39-AS RNA levels after exposure of Tregs (G) to normoxic or hypoxic (2% O₂) conditions (HS, n = 5; IBD, n = 5). H Mean ± SEM CD39-AS RNA levels after Th17 cells were exposed to vehicle or the STAT3 inducer ML-115 (HS, n = 5; IBD, n = 5). *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001 (paired t test)

In Th17 cells, silencing STAT3 resulted in decreased CD39-AS levels in IBD (Fig. 6E), whereas no changes in antisense levels were noted after silencing HIF-1α and KLF6 in Th17 cells from controls and IBD patients (Fig. 6D, F). These findings were subsequently validated in additional culture experiments in which Tregs were exposed to hypoxia and Th17 cells were treated with ML-115, which induces STAT3. Exposure of Tregs to hypoxia boosted CD39-AS RNA levels in Tregs from both healthy subjects and IBD patients (Fig. 6G), whereas treatment with ML-115 increased CD39-AS RNA levels in IBD-derived Th17 cells (Fig. 6H).

These data further corroborate the role of HIF-1α and STAT3 in the upregulation of CD39-AS.

DISCUSSION

We show that CD39-AS RNA is an important immunomodulator that impacts the metabolism of Tregs and Th17 cells, along with their fitness, function and phenotypic stability. Blockade of CD39-AS RNA limits glucose transport and glycolysis in Tregs while inhibiting oxidative responses and enhancing mitochondrial health in Th17 cells.

Our data indicate that CD39-AS RNA regulates genes associated with cell metabolism, as noted in Jurkat cells, and then further confirmed in Tregs and Th17 cells. Blockade of antisense in Tregs results in the control of genes linked to glucose metabolism, and these findings are corroborated at the functional level, with decreases in glucose uptake and glycolytic capacity noted. Our results rule out that these effects could derive from high levels of CD39, which is involved in the control of glucose metabolism, and its deficiency has been associated with high lactate levels and heightened expression of glycolytic genes [23, 24]. In this context, our data revealed that the downregulation of genes linked to glucose metabolism was achieved independently of CD39, as gene expression changes were still noted when Tregs were concomitantly exposed to CD39 siRNA. Regulation of glucose metabolism by lncRNAs was previously proposed by Zhang and colleagues in the context of cancer [15]. In this study, lncRNA-MIF, a c-myc-activated lncRNA, was found to suppress aerobic glycolysis by promoting Fbxw7-mediated c-myc degradation [15]. In our experimental setting, blockade of CD39-AS resulted in limitations in glucose metabolism and associated pathways, which are important determinants of cell inflammatory status and function. Controlling glucose uptake and glycolysis might be relevant for restoring the functionality of Tregs through the modulation of their metabolism. The finding that blockade of glucose transport is key to Treg function was supported by increased suppression following Treg treatment with fasentin and decreased suppression following Treg exposure to insulin. A decrease in Treg suppressive function following treatment with insulin was previously noted by Han et al., who proposed that insulin inhibitory effects on Treg suppression are linked to AKT activation and reduced production of IL-10 [25]. Future studies should aim to measure the levels of CD39-AS RNA and the effects these might have on the function of Tregs isolated from IBD patients concomitantly suffering from type 2 diabetes, which is characterized by a reduced response to insulin and insulin resistance.

In IBD, silencing of antisense enhances Treg suppression, likely as a result of decreased glucose metabolism, improved ectoenzymatic activity and a stabilized phenotype. In healthy subjects, a lack of increase in Treg suppression following exposure to CD39-AS oligos might derive from low baseline levels of antisense [10]. The reduced Treg cell proliferation noted upon CD39-AS-ASO treatment might result from a decrease in glycolysis, as suggested by previous work [26], or from high concentrations of adenosine, which limits Treg activation [27] while increasing CD39 levels and suppressive function [6].

Control of cell metabolism by CD39-AS was also evident in Th17 cells, where blockade of the antisense resulted in increased expression of ERCC6, which encodes the CSB protein, which has known ATP-induced ATPase activity and is involved in DNA excision repair and in the control of oxidative responses [21]. As for Tregs, this effect appeared to be independent of CD39, which was also observed when CD39-ASv2-ASO was added in the presence of CD39 silencing. The inhibition of oxidative responses was confirmed at the functional level, with a reduced OCR, maximum respiration and spare respiratory capacity, which are important measures of mitochondrial function. These findings were corroborated by the results showing ameliorated mitochondrial health in Th17 cells following exposure to antisense blockade, as reflected by an increase in the aggregate/monomer ratio via flow cytometry.

Whether CD39-AS RNA alters cell metabolism through transcriptional regulation or through the control of the mRNA levels of metabolic genes needs further investigation. In turn, the effects of altered metabolic changes caused by CD39-AS modulation of the CD39 locus and of the transcription factors upregulated during chronic inflammation also require additional testing.

The metabolic changes linked to CD39-AS might be particularly relevant for Tregs and Th17 cells in Crohn’s disease and ulcerative colitis patients, where the antisense is upregulated. As blockade of antisense limits glycolysis and glucose transport in Tregs and modulates mitochondrial function in Th17 cells, treatment strategies based on interference with this lncRNA should be considered to restore Treg suppression and adenosine production along with reduced oxidative responses in Th17 cells. The finding that levels of CRP, a marker of inflammation, are inversely correlated with the extent of glycolytic activity or maximum respiration inhibition implies that significant beneficial effects could be attained by this form of treatment in IBD. The salutary effects noted in mice reconstituted with human CD4 cells expressing the antisense further support the beneficial properties of CD39-AS silencing via ASO. It is unclear whether the metabolic effects noted following CD39-AS-ASO treatment could be reversed. Our data indicate that treatment with CD39-ASv1-ASO stabilizes IBD Tregs in a proinflammatory milieu, a phenomenon that, by favoring the maintenance of immune homeostasis, could also protract the beneficial effects of CD39-AS-ASO on cells and tissues.

CD39-AS RNA is differentially regulated in Tregs and Th17 cells of healthy individuals and IBD patients. Among the factors with high predicted binding to the CD39-AS promoter, HIF-1α appears to play an important role in the transcriptional induction of CD39-AS in the Tregs of healthy subjects and IBD patients. HIF-1α can be induced during protracted inflammation and has been previously shown to impact Tr1 cell differentiation as well as the response of Th17 cells to AhR activation [8, 28, 29]. Thus, HIF-1α could indirectly lead to CD39 regulation either through the inhibition of AhR, as we previously reported [8, 22], or through the induction of CD39-AS, as reported in the current manuscript.

When evaluating Th17 cells, we noted that blockade of STAT3, a transcription factor involved in the early development of Th17 cells, downregulates CD39-AS in IBD. In previous work, STAT3 was found to induce CD39 through IL-6 in murine Th17 cells [9], suggesting a different role of this transcription factor in mice and humans. Alternatively, STAT3 might concomitantly induce CD39 and CD39-AS, therefore being involved in their mutual regulation. Future investigations should focus on defining these interactions.

In conclusion, we have shown that CD39-AS RNA has important effects on Treg and Th17 cell biological functions through the modulation of their metabolism. Silencing of antisense variants limits oxidative responses and improves mitochondrial health in Th17 cells while controlling glucose metabolism in Tregs. These effects are important in IBD, where blockade of antisense stabilizes Treg phenotype and function and is of clinical benefit in experimental colitis. Strategies based on the blockade of CD39-AS, or the factors involved in its induction, might have favorable effects in containing inflammation and disease progression in IBD.

MATERIALS AND METHODS

Jurkat cell line

The Jurkat human cell line was obtained from the American Type Culture Collection (ATCC, Manassas, VA) and maintained at 37 °C and 5% CO₂ in RPMI 1640 medium supplemented with 2 mM L-glutamine, 100 IU/ml penicillin, 100 mg/ml streptomycin, 1% nonessential amino acids and 10% FBS (Gibco, Thermo Fisher Scientific, Waltham, MA).

Subjects

Peripheral blood mononuclear cells (PBMCs) and lamina propria mononuclear cells (LPMCs) were isolated from 60 IBD patients, 27 with Crohn’s disease (13 females; 14 males) and 33 with ulcerative colitis (20 females; 13 males). Patients were recruited from the IBD Center, Gastroenterology Division at Beth Israel Deaconess Medical Center (BIDMC), Boston, MA. Twenty-seven patients (11 with Crohn’s disease; 16 with ulcerative colitis) had active disease. At the time of sample collection, 23 patients with Crohn’s disease and 32 with ulcerative colitis were receiving treatment. For 28 patients (10 with Crohn’s disease and 18 with ulcerative colitis), the drug regimens included more than one drug. Supplementary Tables 4 and 5 include the demographic and clinical data of the IBD patients included in this study. PBMCs were also obtained from 30 age- and sex-matched healthy blood donors (Blood Donor Center at Children’s Hospital, Boston and BIDMC). Studies on human samples received IRB approval (protocol 2021P000347) from the Committee on Clinical Investigations, BIDMC. Written informed consent was obtained from all participants prior to inclusion in this study.

Cell isolation and polarization

PBMCs were obtained via density gradient centrifugation on Ficoll–Paque (GE Healthcare Life Sciences, Pittsburgh, PA) [5, 10]. LPMCs were obtained from freshly biopsied colonic tissue or from colon resections of 8 patients with IBD. In 2 patients, tissue biopsies were collected from both inflamed and noninflamed areas (three to four 2–5 mm samples per biopsied area). LPMCs were obtained via our previous protocols [5, 6]. Briefly, biopsied or resected tissue was washed with 1 × PBS, cut into small sections and incubated in Ca²⁺⁻ and Mg²⁺-free HBSS containing 4 mM EDTA and 1 mM dithiothreitol at 37 °C for 15 min. After removing the epithelia by discarding the supernatants and repeating the procedure three times, the tissue was minced further and resuspended in RPMI 1640 (Gibco, Thermo Fisher Scientific, Waltham, MA) containing 10% fetal bovine serum (FBS), 400 U/ml collagenase D and 0.01 mg/ml DNAse I. Following incubation at 37 °C for 1.5 h with pipetting every 30 min, the digested tissue was filtered and centrifuged at 1500 rpm for 7 min, after which the cells were collected. The viability of the PBMCs and LPMCs was verified by trypan blue exclusion and exceeded 98%.

Tregs and Th17 cells were purified as CD4⁺CD25^+/high CD127^−/low (Tregs) and CXCR3⁻CCR6⁺ cells (Th17) via immunomagnetic beads (CD4⁺CD25⁺CD127^dim/− Regulatory T-Cell Isolation Kit II, Miltenyi Biotec, San Diego, CA) or enrichment beads (Miltenyi Biotec) (purity higher than 92% in all cases). In some experiments, Tregs and Th17 cells were polarized from total CD4 T cells obtained from PBMCs and LPMCs via negative selection (Miltenyi Biotec) (purity equal to or greater than 92%). After resuspension in RPMI 1640 supplemented with 10% FBS, CD4⁺ T cells were exposed to Treg- or Th17-polarizing conditions for five days. These combinations consisted of TGF-β (10 ng/ml), IL-2 (100 ng/ml) and Dynabeads Human T Activator CD3/CD28 for T-cell expansion (Thermo Fisher Scientific) at a bead/cell ratio of 1/2 for Tregs and of IL-6 (50 ng/ml), IL-1β (25 ng/ml), TGF-β (3 ng/ml) and Dynabeads Human T Activator CD3/CD28 at a bead/cell ratio of 1/50 for Th17 cells. After 5 days, the Treg and Th17 cell phenotypes were validated via FACS analysis (Supplementary Fig. 9a, b). All cytokines were purchased from Peprotech (Thermo Fisher Scientific).

In additional experiments, Tregs treated with scrambled-ASO or CD39-AS-ASO were subjected to a proinflammatory challenge consisting of IL-6 (0.04 μg/ml) and IL-1β (0.01 μg/ml) [19, 20] for the last 36 h of culture. The frequencies of FOXP3⁺, RORC⁺, IL-17⁺ and IFNγ⁺ cells among Tregs were measured via flow cytometry (see below).

Cell culture and inhibition studies

Jurkat, Treg and Th17 cells were treated with CD39-AS-ASOs or scrambled-ASO at 10 μM, as we previously reported [10]. Cells were cultured for 72 h at 37 °C and 5% CO₂. CD39-AS inhibition was tested by qPCR, as previously described [10]. CD39-AS-ASOs are specific to either CD39-ASv1 or the CD39-AS1v2 variant. In additional experiments, Treg and Th17 cells were exposed to CD39, HIF-1α, STAT3 and KLF6 Silencer Select siRNAs (Thermo Fisher Scientific). Cells were resuspended in Opti-MEM (Thermo Fisher Scientific) and seeded at 1–1.5 × 10⁵/well in 96-well plates [10]. CD39, HIF-1α and STAT3-specific siRNAs were used at a final concentration of 1 pmol/well; KLF6 siRNA was used at 2 pmol/well and added to Tregs and Th17 cells for the last fourteen hours of culture. A negative control siRNA (scrambled siRNA, Thermo Fisher Scientific) was used. CD39, HIF-1α, STAT3 and KLF6 silencing was verified via qPCR via gene-specific primers following reverse transcription.

Bulk RNA-seq: RNA extraction and library preparation

Bulk RNA-seq was performed on RNA isolated from three replicates each of scrambled ASO- and CD39-ASv1-ASO-treated Jurkat cells. A total of 1 × 10⁶ Jurkat cells were used per sample. Total RNA was extracted from frozen cell pellets via a Qiagen RNeasy Plus Mini Kit following the manufacturer’s instructions (Qiagen, Germantown, MD). Total RNA samples were quantified via a Qubit 2.0 fluorometer (Life Technologies, Carlsbad, CA, USA), and RNA integrity was checked via an Agilent TapeStation 4200 (Agilent Technologies, Palo Alto, CA, USA). The RNA sequencing libraries were prepared via the NEBNext Ultra II RNA Library Prep Kit for Illumina according to the manufacturer’s instructions (NEB, Ipswich, MA, USA). Briefly, mRNAs were initially enriched with Oligod(T) beads. The enriched mRNAs were fragmented for 15 min at 94 °C. First-strand and second-strand cDNA were subsequently synthesized. The cDNA fragments were end repaired and adenylated at the 3’ ends, and universal adapters were ligated to the cDNA fragments, followed by index addition and library enrichment via PCR with limited cycles.

The sequencing library was validated on an Agilent TapeStation (Agilent Technologies) and quantified by using a Qubit 2.0 fluorometer as well as by quantitative PCR (KAPA Biosystems, Wilmington, MA, USA). The sequencing libraries were multiplexed and clustered onto a flow cell on the Illumina NovaSeq instrument according to the manufacturer’s instructions. The samples were sequenced via a 2 × 150 bp paired-end (PE) configuration. Image analysis and base calling were conducted via NovaSeq Control Software. The raw sequence data (.bcl files) generated from Illumina NovaSeq were converted into fastq files and demultiplexed via Illumina bcl2fastq 2.20 software. One mismatch was allowed for index sequence identification.

NanoString assay

Total RNA was obtained from peripheral blood Tregs and Th17 cells treated with scrambled ASO, CD39-ASv1-ASO (Tregs) or CD39-ASv2-ASO (Th17 cells) via the RNeasy Mini Kit (Qiagen) according to the manufacturer’s instructions. The RNA concentration was determined via Nanodrop, while the integrity was verified via an Agilent Bioanalyzer. Samples with DV200 values greater than 70% were used in subsequent steps. NanoString profiling was performed via the nCounter Human Metabolic Pathways Panel (NanoString Technologies, Seattle, WA). A total of 140 ng of total RNA was used as input for hybridization reactions containing reporter and capture probes, as per the manufacturer’s instructions. As we previously reported [30, 31], RNA samples were hybridized at 65 °C for 24 h and subsequently processed, and each sample was analyzed in a single nCounter cartridge lane. The posthybridization process was carried out in an nCounter MAX Analysis System (NanoString Technologies).

Glucose uptake assay

Glucose uptake by Tregs was determined via the Glucose Uptake-Glo Assay (cat. # J1341; Promega, Madison, WI). Cells were seeded at 2 × 10⁵/well and subsequently exposed to scrambled-ASO or CD39-ASv1-ASO for 72 h. At the end of the culture period and after washing with 1 × PBS, 1 mM 2-deoxyglucose was added to the cultures. After 10 min of incubation at room temperature, Stop and Neutralization buffers were added, followed by the addition of 2-deoxyglucose-6-phosphate detection reagent. Luminescence was recorded after 1 h of incubation at room temperature via an Infinite^® M Plex multimode microplate reader from Tecan, with attenuation set to “Auto” and an integration time of 1000 milliseconds. The relevant light units were recorded for each well. Control wells containing no cells were used to adjust the raw values for background luminescence before further analysis.

Malachite green assay

Free phosphate concentration was measured using the Malachite Green Phosphate Assay Kit (cat. # MAK3087; Sigma Aldrich, St. Louis, MO). Scrambled-ASO- and CD39-ASv1-ASO-treated Treg cells were washed with 500 μl of saline solution, transferred to 96-well plates at 2 × 10⁵/200 μl/well and subsequently exposed to 10 μM ATP at room temperature for 15 min. After centrifugation, 80 μl of the supernatant was collected from each sample and transferred to a 96-well transparent flat bottom plate. After the addition of 20 μl of working reagent per sample, plates were gently tapped to favor reagent mixing, covered with foil and incubated at room temperature for 30 min. The absorbance was then measured via an Infinite^® M Plex multimode microplate reader from Tecan at a wavelength of 620 nm.

Seahorse

Peripheral blood-derived Tregs and Th17 cells were assayed on an XF^e96 Extracellular Flux Analyzer (Seahorse Bioscience, North Billerica, MA) at 4 × 10⁵/well. The ECAR and OCR were determined via the Seahorse XF Glycolysis Stress Kit (Seahorse Bioscience) and the XF Cell Mito Stress. XF glycolysis stress included three sequential injections of D-glucose, oligomycin and 2-deoxy-glucose, as previously reported [32]. The XF Cell Mito Stress included sequential injections of oligomycin (part A), carbonyl cyanide 4-(trifluoromethoxy) phenyl hydrazone (part B), and a mixture of rotenone and actinomycin A (part C). Measurements of glycolytic capacity for XF glycolysis stress, maximum respiration and spare respiratory capacity for XF cell Mito Stress were also obtained.

Cell proliferation and suppression assay

The ability of scrambled-ASO- and CD39-ASv1-ASO-treated Treg cells to proliferate was tested after 72 h of culture in the presence of the Dynabeads Human T Activator CD3/CD28 for T-cell expansion (Thermo Fisher Scientific) at a bead/cell ratio of 1/2. Proliferation was assessed using the Cell Titer 96^® Aqueous One Solution Cell Proliferation Assay (cat # G3582, Promega) according to the manufacturer’s suggested protocol. Briefly, 20 μl of Cell Titer Aqueous One Solution Reagent was added to each well, in which cells were seeded at 1 × 10⁶ per ml in 100 μl of culture medium. After one hour of incubation at 37 °C and 5% CO₂ in the dark, the absorbance was recorded. The absorbance was measured on an Infinite^® M Plex multimode microplate reader from Tecan at a wavelength of 490 nm. Readings were taken in triplicate. The values were normalized by subtracting the background absorbance, the geometric mean of wells containing medium with no cells, from the raw values. Geometric means were derived from each sample for both treated and untreated Tregs on the basis of the triplicate values recorded before the fold change between classes was determined.

The ability of Tregs to suppress the proliferation of CD4⁺CD25⁻ cells was assessed in coculture experiments, in which scrambled-ASO- and CD39-ASv1-ASO-treated Tregs were added at a 1/8 ratio to autologous CD4⁺CD25⁻ target cells, which were also isolated via immunomagnetic beads (Miltenyi Biotec). Parallel cultures of CD4⁺CD25⁻ cells without Tregs were conducted under identical conditions. Responder cells were activated with IL-2 (100 ng/ml) and the human T activator CD3/CD28 (bead/cell ratio of 1/2). After 72 h of coculture, proliferation was assessed using Cell Titer 96^® Aqueous One Solution Cell Proliferation Assay (Promega), as indicated above. In an additional set of experiments, the ability of Tregs to suppress CD4⁺CD25⁻ cell proliferation was tested in the presence of DMEM high glucose pyruvate medium (Thermo Fisher Scientific) in the absence or presence of fasentin (a GLUT1 inhibitor) (Millipore Sigma) at 25 μM for 24 h [33]. The ability of Tregs to suppress was also tested in the presence of insulin (Tocris Biotechne, Minneapolis, MN), which was used at 10 ng/ml for 24 h [34].

qRT–PCR

The expression of human CD39-AS, CD39, SLC2A1, HK2, PRR5, ERCC6, HIF-1α, STAT3 and KLF6 was determined via qPCR. Total RNA was extracted from 3–5 × 10⁶ Treg and Th17 cells via TRizol Reagent (Thermo Fisher Scientific), and mRNA was reverse transcribed via an iScript cDNA synthesis kit (BioRad Laboratories, Hercules, CA) according to the manufacturer’s instructions. Samples were run on a Step One Plus Real-Time PCR System (Applied Biosystems, Foster City, CA), and the results were analyzed by matched software and expressed as relative quantification. Relative gene expression was determined after normalization to β actin or GAPDH. The CD39-AS, CD39, HIF-1α and KLF6 primer sequences are reported in Supplementary Table 6. PrimeTime qPCR primers for the detection of human ERCC6, HK2, PRR5, SLC2A1 STAT3, β actin and GAPDH were predesigned by and purchased from Integrated DNA Technologies (Coralville, IA).

Live cell imaging

Live-cell imaging was performed to assess the presence of active mitochondria, live cells, and reactive oxygen species in Th17 cells exposed to scrambled-ASO or CD39-ASv2-ASO. Cells were transferred to Eppendorf tubes and then washed with 1 × PBS with 1% FBS before being resuspended in a final volume of 1 ml. A total of 100 μl of 1 μM MitoTracker Green FM (Cell Signaling Technology, cat. # 9074), 2 μl of 2.5 mM CellROX Deep Red (Thermo Fisher, cat. # C10422), and 50 μl of NucBlue Live ReadyProbe (Thermo Fisher R37605) were added to each sample, followed by a 30-min incubation at 37 °C and 5% CO₂. Positive controls consisted of cells treated with 100 μM carbonyl cyanide 3-chlorophenylhydrazone (CCCP) at the time of staining. Cells were then washed three times with 1 × PBS and centrifuged for 5 min at 1500 rpm between each wash. Finally, cells were resuspended in 100 μl of 1 × PBS, transferred to a Costar opaque black 96-well clear bottom plate, and imaged on an ECHO Revolve (ECHO, Lake Zurich, IL) at 10 × magnification via the FITC, PE, and Cy5 fluorescent channels.

Flow cytometry

The phenotypes of polarized Tregs and Th17 cells were validated by flow cytometry. Cells were stained with FITC, APC, Pe-Cy7, Pacific Blue (PB), PerCP-Cy5.5, PE, and Brilliant Violet 605 (BV605) anti-human antibodies against CD4 (clone # A161A1), CD127 (clone # A01905), and CCR6 (clone G034E3), all from Biolegend (San Diego, CA), CD25 (clone # M-A251, BD Pharmingen, Franklin Lakes, NJ), and IL-23R (clone # FAB1400IF, R&D Systems, Minneapolis, MN). The expression of RORC, FOXP3, IL-17A, IL-22 and IFNγ was measured using the eBioscience FOXP3/Transcription Factor Staining Set (Thermo Fisher Scientific) according to the manufacturer’s instructions. Following fixation and permeabilization, cells were stained with APC-conjugated anti-human RORC (clone # AFKJS-9, Thermo Fisher Scientific), APC-conjugated anti-human FOXP3 (clone # PCH101, Thermo Fisher Scientific), BV605-conjugated anti-human IL-17A (clone # BL168, Biolegend), PE-Cyanine 7 (PE-Cy7)-conjugated anti-human IL-22 (clone # 22URTI, Thermo Fisher Scientific) and Alexa Fluor 700-conjugated anti-human IFNγ (clone # B27, BD Pharmingen) antibodies. Cells were acquired on a Cytoflex Lx flow cytometer (Beckman Coulter, Pasadena, CA) and analyzed via FlowJo 2 software (version 10, TreeStar, Ashland, OR). Fluorescence compensation was adjusted based on fluorescence-minus-one (FMO) method.

JC-1 staining

Th17 cells were resuspended in warm cell culture medium at 1 × 10⁶ cells/ml. JC-1 mitochondrial membrane potential indicator dye was added at 2 μM, and cells were incubated at 37 °C and 5% CO₂ for 20 min. An aliquot of cells exposed to 100 μM CCCP for 5 min at 37 °C and 5% CO₂ served as a positive experimental control. Samples were then washed following the addition of 2 ml of warm 1 × PBS and centrifuged for five minutes at 25 °C and 400 × g. After resuspension in 1 × PBS, cells were analyzed by FACS within four hours. Fluorescence was measured using FITC and PE channels.

Induction and assessment of colitis

Colitis was induced in NOD/scid/gamma mice preemptively reconstituted with CD39-AS⁺ CD4⁺ cells obtained from one healthy blood donor via TNBS, as we previously reported [10, 30]. Six-week-old male and female NOD/scid/gamma mice were purchased from the Jackson Laboratory (Bar Harbor, ME) and kept under pathogen-free conditions between 21 °C and 23 °C, with a 12:12 h dark/light cycle and a relative humidity between 45 and 55%. Mice received 2–3 × 10⁶ CD4 T cells that were tested for CD39-AS expression by qPCR, as we previously reported [10, 30]. Three weeks after CD4 T-cell transfer, mice were bled and checked for human chimerism. Those mice showing more than 10% human chimerism (75% of the mice originally transferred) were sensitized to TNBS at 2.5 mg in 50% ethanol, as previously reported [10, 35]. After seven days, mice were anesthetized and subsequently administered a single enema of 0.25 mg of TNBS in 50% ethanol in a total volume of 50 μl [35]. At the time of TNBS administration, mice received a single injection of scrambled-ASO, CD39-ASv1-ASO or CD39-ASv2-ASO. As previously described, CD39-AS-ASOs were administered at 5.4 mg/kg i.p. [10]. After the induction of colitis, weight and stool were assessed and recorded daily until harvest, 72 h after the intrarectal TNBS administration. The DAI was calculated on the basis of body weight loss, presence of gross blood, and stool consistency. On the day of harvest, colons were dissected, and their length was measured from the ileocecal junction to the anal verge. The histology score was calculated via hematoxylin and eosin (H&E) staining. Lymphocytes were collected from the spleen, MLN, IEL and LP for subsequent flow cytometry analysis. Dead cells were excluded via the use of 7-aminoactinomycin D (7-AAD) viability staining solution (BioLegend) and single-cell gating. Staining was carried out using Brilliant Violet 785 anti-human CD3 (clone # OKT3, Biolegend), FITC anti-human CD4 (clone # OKT4, Biolegend), PE-Cy7 anti-human CD25 (clone # M-A251, BD Pharmingen), PE anti-human CD39 (clone # A1, Biolegend) and Alexa Fluor 647 anti-human GLUT1 (cat. # 566580, BD Biosciences, Franklin Lakes, NJ) antibodies. The expression of RORC, FOXP3 and IL-17A was determined using the eBioscience FOXP3/Transcription Factor Staining Buffer Set upon staining with PB anti-human FOXP3 (clone # 206D, Biolegend), APC anti-human RORC (clone # AFKJS-9, Thermo Fisher Scientific) and BV605 anti-human IL-17A (clone # BL168, Biolegend). Separate cell aliquots were subjected to JC-1 staining, as indicated above.

The animal protocol was approved by the Animal Care and Use Committee at BIDMC (protocol 049-2021).

Immunohistochemistry

Paraffin-embedded colonic tissue was subjected to antigen retrieval [36]. 6 μm tissue sections were stained with hematoxylin and eosin, and the histology score was calculated as previously reported [5]. Sections were also incubated overnight at 4 °C with polyclonal rabbit anti-human CD3 (cat. # A045229-2; Agilent Dako, Santa Clara, CA) at 1/70. After blocking endogenous peroxidase with 3% H₂O₂, sections were incubated with goat anti-rabbit secondary antibody (Vector Laboratories, Burlingame, CA) at 1/1000 for one hour at room temperature. After treatment with Vectastain Elite ABC kit (Vector Laboratories), sections were examined via light microscopy.

Statistics

Bulk RNA-seq (Jurkat cells).

After confirming the quality of the raw data, sequence reads were trimmed to remove possible adapter sequences and nucleotides of poor quality. The trimmed reads were mapped to the reference genome available on ENSEMBL using the STAR aligner v.2.5.2b. BAM files were generated as a result of this step. Unique gene hit counts were calculated by using feature Counts from the Subread package v.1.5.2. Only unique reads that fell within exon regions were counted. After the extraction of gene hit counts, a gene hit count table was used for downstream differential expression analysis. Using DESeq2, a comparison of gene expression between the groups of samples was performed. The Wald test was used to generate p values and log2-fold changes. Genes with adjusted p values < 0.05 and absolute log2-fold changes >0.25 were considered differentially expressed genes for each comparison.

Volcano plots were generated via the “ggplot2” package in R Studio (version 2023.06.2+561) [37, 38], and display all measured genes [39]. Genes considered differentially expressed are color coded by expression value, with negatively expressed genes represented by blue, positively expressed genes represented by red, and genes that showed no significant change in expression are represented by black. Only differentially expressed genes with a p value < 0.000001 were labeled on the volcano plot via the “ggrepel” package [40] due to the large number of differentially expressed genes that met the p value threshold of <0.05.

NanoString data analysis (Tregs and Th17 cells).

The raw data were imported to ROSALIND via the NanoString nSolver^® protocol for data normalization to generate normalization factors.

Differential expression between two groups of samples was calculated using the Generalized Linear Model for count data (NanoString). The model assumes a negative binomial distribution and utilizes the raw data and estimates of noise and dispersion across all samples in the experiment to calculate the fold change and p value for each gene. P values were adjusted to account for multiple testing via the Benjamini–Hochberg false discovery rate (FDR) method. NanoString nCounter gene expression counts were processed via ROSALIND to generate normalized gene expression counts, log2-fold change values, and p values. Genes were considered differentially expressed if they exhibited an absolute log2-fold change greater than 0 with a p value < 0.05.

Volcano plots were generated as indicated above. Only differentially expressed genes with a p value < 0.05 were labeled on the volcano plot via the “ggrepel” package.

RNA samples from cells treated with scrambled-ASO or CD39-ASO were run in triplicate, and experiments were repeated independently three times.

GSEA

Jurkat cells:

Normalized counts were obtained from Azenta Life Sciences, as were log2-fold changes and p values generated by DESeq2 via the Wald test. KEGG gene sets and pathways were used to perform GSEA using the Broad Institute’s GSEA software [41-43]. Parameters were set to rank genes by the weighted ratio of classes on the phenotype permutation. Gene sets enriched at a nominal p value of <0.05 and an FDR of <25% were considered significant. Figures representing the enriched gene sets were produced in R using the “clusterProfiler” [44, 45] and “enrichPlot” packages. The gene sets were ranked in descending order by FDR and color coded by p value. The gene sets that were shown to be positively correlated with the CD39-ASv1-ASO-treated Jurkat class presented the greatest changes in gene expression between untreated and treated cells.

Tregs and Th17 cells:

Normalized gene expression counts, log2-fold changes, and p values were obtained from ROSALIND. NanoString gene sets and pathways were used to perform GSEA on the normalized counts using the Broad Institute’s GSEA software. The parameters used included ranking by weighted Log2 ratio of classes on the gene set permutation. Gene sets enriched at a nominal p value of <0.05 and/or FDR of <25% were considered significant. Figures representing the enriched gene sets were produced as indicated above.

All other results presented throughout the manuscript are expressed as mean ± SEM unless otherwise stated. The normality of the variable distribution was assessed via the Kolmogorov–Smirnov goodness-of-fit test. Comparisons were performed via parametric (paired or unpaired Student’s t test) or nonparametric (Mann–Whitney test) tests according to the data distribution (two-sided). One-way ANOVA, followed by Tukey’s multiple comparisons test, was used when more than two sets of data were compared. Correlations were determined via Pearson correlation coefficient. p ≤ 0.05 was considered significant. Statistical analysis was performed using GraphPad Prism, version 9.2.0 (GraphPad software, San Diego, CA).

Supplementary Material

Supplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41423-025-01295-6.