mTOR coordinates transcriptional programs and mitochondrial metabolism of activated Treg subsets to protect tissue homeostasis

Chapman, Nicole M.; Zeng, Hu; Nguyen, Thanh-Long M.; Wang, Yanyan; Vogel, Peter; Dhungana, Yogesh; Liu, Xiaojing; Neale, Geoffrey; Locasale, Jason W.; Chi, Hongbo

doi:10.1038/s41467-018-04392-5

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Published: 29 May 2018

mTOR coordinates transcriptional programs and mitochondrial metabolism of activated T_reg subsets to protect tissue homeostasis

Nature Communications volume 9, Article number: 2095 (2018) Cite this article

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Abstract

Regulatory T (T_reg) cells derived from the thymus (tT_reg) and periphery (pT_reg) have central and distinct functions in immunosuppression, but mechanisms for the generation and activation of T_reg subsets in vivo are unclear. Here, we show that mechanistic target of rapamycin (mTOR) unexpectedly supports the homeostasis and functional activation of tT_reg and pT_reg cells. mTOR signaling is crucial for programming activated T_reg-cell function to protect immune tolerance and tissue homeostasis. T_reg-specific deletion of mTOR drives spontaneous effector T-cell activation and inflammation in barrier tissues and is associated with reduction in both thymic-derived effector T_reg (eT_reg) and pT_reg cells. Mechanistically, mTOR functions downstream of antigenic signals to drive IRF4 expression and mitochondrial metabolism, and accordingly, deletion of mitochondrial transcription factor A (Tfam) severely impairs T_reg-cell suppressive function and eT_reg-cell generation. Collectively, our results show that mTOR coordinates transcriptional and metabolic programs in activated T_reg subsets to mediate tissue homeostasis.

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Introduction

Regulatory T (T_reg) cells expressing the transcription factor Foxp3 suppress conventional T-cell responses to establish self-tolerance, prevent autoimmunity, and maintain tissue homeostasis^1,2. Foxp3 deficiency eliminates T_reg-cell development and function, leading to autoimmune diseases characterized by excessive T helper 1 (T_H1), T_H2, or T_H17 responses, and germinal center (GC) B-cell reactions driven by T follicular helper (T_FH) cells^3,4,5. Thymic-derived T_reg (tT_reg) cells exit the thymus and populate peripheral tissues, where resting T_reg cells [also called central T_reg (cT_reg) cells] are activated in response to antigen and inflammatory cues^6,7,8,9. These activation signals increase effector molecule expression and induce transcription factors that define the selective suppressive functions and tissue localization of activated T_reg cells [also known as effector T_reg (eT_reg) cells]^{5,10,11,12,13,14,15}. Peripherally-derived T_reg (pT_reg) cells are a developmentally distinct population of activated T_reg cells that arises from the naive CD4⁺ T-cell pool and inhibit T_H2 or T_H17 responses at mucosal sites^{6,16,17,18,19}. The transcription factor interferon regulatory factor 4 (IRF4) is expressed in both eT_reg and pT_reg cells in vivo and is an essential positive regulator of their homeostasis and function^{7,15,17,20,21,22}. IRF4 expression and function are induced by TCR signals in T_reg cells by incompletely understood mechanisms^7,8,22.

Metabolic rewiring is important for T-cell fate decisions, but the metabolic programs regulating T_reg-cell activation and specialization remain uncertain²³. The activation of the mechanistic target of rapamycin (mTOR) induces metabolic reprogramming necessary for conventional T-cell activation and differentiation^23,24. In contrast, mTOR appears to antagonize T_reg-cell differentiation and expansion in vitro and suppressive activity in vivo^23,25,26. Mechanistically, inhibition of mTOR upregulates fatty acid oxidation, which supports mitochondrial respiration important for T_reg-cell differentiation, proliferation, and survival in vitro^27,28. Moreover, low levels of mTOR activation are needed to prevent excessive glycolysis that can impair T_reg-cell survival and lineage stability²³. Although the prevailing model is that mTOR activation hinders T_reg-cell function, T_reg cells have higher basal levels of mTORC1 activation than conventional T cells^29,30, which is essential for T_reg-cell function in vivo³⁰. Thus, mTOR-dependent metabolic programming might have context-dependent roles in different T_reg-subsets or under distinct physiological conditions.

Here, we show that mTOR orchestrates activation-induced transcriptional and metabolic signatures that are essential for T_reg-cell activation and function. We find that either acute or chronic inhibition of mTOR disrupts T_reg-cell suppressive activity and leads to uncontrolled conventional T-cell activation. In line with this observation, mucosal CD4⁺ T-cell responses, including T_H2 responses, are increased when T_reg cells lose mTOR, associated with a loss of eT_reg and pT_reg cells in mucosal sites. Mechanistically, mTOR mediates T_reg-cell activation and suppressive activity by promoting IRF4 expression and mitochondrial metabolism. Indeed, disruption of mitochondrial metabolism severely impairs the suppressive function of activated T_reg cells and their homeostasis in tissues. Collectively, our results show that mTOR controls peripheral tolerance by integrating transcriptional and metabolic programs critical for the homeostasis and suppressive activity of activated T_reg cells.

Results

mTOR promotes activated T_reg-cell suppressive activity

T_reg cells activated in vivo have enhanced suppressive activity critical for immune homeostasis^7,8,31,32, yet the molecular events controlling T_reg-cell activation remain to be fully defined. To identify pathways associated with increased suppressive function of T_reg cells, we mined a published dataset of activated T_reg cells isolated from diphtheria toxin (DT)-treated Foxp3^DTR mice (DTR, diphtheria toxin receptor)³². Gene set enrichment analysis (GSEA) revealed that the hallmark mTORC1 and PI3K-Akt-mTOR signaling pathways were among the most significantly (false discovery rate, FDR < 0.05) upregulated gene sets in activated vs. resting T_reg cells (Fig. 1a). Thus, increased T_reg-cell suppressive activity is correlated with enhanced mTOR signaling. To rigorously test the function of mTOR for the suppressive activity of activated T_reg cells, we activated T_reg cells in vitro in the presence or absence of the mTOR inhibitor, PP242. We found that acute inhibition of mTOR diminished the ability of activated T_reg cells to suppress conventional T-cell proliferation (Fig. 1b) and to express the immunosuppressive molecule CTLA4 (Fig. 1c), indicating a kinase-dependent function of mTOR in T_reg-cell function. Accordingly, the suppressive activity of T_reg cells isolated from Cd4^CreMtor^fl/fl mice was dampened (Fig. 1d). Thus, mTOR is essential for the suppressive function of T_reg cells in vitro.

To establish a role for mTOR in T_reg-cell function in vivo, we generated female Foxp3^Cre/DTRMtor^fl/fl mosaic mice. These mice express a floxed Mtor allele²⁴, whose expression can be deleted by Cre recombinase driven under the Foxp3 promoter (denoted as Foxp3^Cre)³³, resulting in the deletion of mTOR within T_reg cells after they have expressed Foxp3. Acute depletion of DTR-expressing T_reg cells with DT forces the remaining Foxp3^Cre-expressing T_reg cells to become activated, expand, and control immune homeostasis in adult mice³⁴. Upon DT treatment, Foxp3^Cre/DTRMtor^fl/fl mosaic mice, but not their respective Foxp3^Cre/DTRMtor^{+/+ or +/fl} controls, developed inflammation associated with increased organ size and cell number, especially peripheral lymph nodes (Fig. 1e). Further, there were increased frequencies of CD44^hiCD62L^lo effector/memory CD4⁺ in the peripheral lymph nodes (Fig. 1f). After DT treatment, Foxp3^Cre/DTRMtor^fl/fl mice had a profound enrichment for IL-4-producing and small but significant increase in IL-17A-producing, but not IFN-γ-producing, CD4⁺ T cells in the spleen (Fig. 1g, h). Similar observations were found in peripheral lymph nodes (Fig. 1g). Therefore, mTOR signaling is essential for the suppressive function of activated T_reg cells, and its acute deletion in T_reg cells leads to loss of immune homeostasis and the activation of T_H2, and to a lesser extent, T_H17 cells.

T_reg cells require mTOR to prevent spontaneous autoimmunity

To determine the effects of long-term deletion of Mtor on T_reg-cell suppressive function in vivo, we next generated mice bearing a conditional deletion of Mtor within all committed Foxp3⁺ T_reg cells (denoted as Foxp3^CreMtor^fl/fl mice). As anticipated, Mtor was efficiently deleted within Foxp3-YFP⁺ T_reg cells from Foxp3^CreMtor^fl/fl mice (Supplementary Fig. 1a). In contrast to their littermate controls that remained healthy, Foxp3^CreMtor^fl/fl mice developed an early-onset lymphoproliferative and autoimmune disease, indicated by reduced body size and hunched posture, enlargement of peripheral lymphoid organs, and extensive lymphocyte and/or myeloid cell infiltration in multiple organs, such as the skin and lung (Fig. 2a–c). This disease ultimately led to the early death of Foxp3^CreMtor^fl/fl mice (Fig. 2d). These mice had reduced frequencies of CD44^loCD62L^hi naive CD4⁺ and CD8⁺ T cells and increased frequencies of CD44^hiCD62L^lo effector/memory phenotype CD4⁺ and CD8⁺ T cells (Fig. 2e). There were also significant increases in IFN-γ-, IL-4-, IL-10-, IL-13-, and IL-17A-producing CD4⁺ T cells and IFN-γ-producing CD8⁺ T cells in mice with mTOR-deficient T_reg cells (Fig. 2f and Supplementary Fig. 1b). Foxp3^CreMtor^fl/fl mice had 5–10-fold and 10–15-fold increases in the frequencies of cells producing T_H2- or T_H17-associated cytokines, respectively, while IFN-γ-producing cells were increased by ~5-fold (Supplementary Fig. 1c). Within T_reg cells, the frequency of IFN-γ-producing cells was also increased in Foxp3^CreMtor^fl/fl mice (Supplementary Fig. 1d). We also found that the frequencies and total numbers of PD-1⁺CXCR5⁺ T_FH cells (Fig. 2g) and CD95⁺GL7⁺ GC B cells (Fig. 2h) were increased in Foxp3^CreMtor^fl/fl mice. We, therefore, performed immunohistochemistry analysis of GCs, B cells, and T cells in whole tissue sections. This analysis revealed that PNA⁺ cells were diffusely distributed in extrafollicular regions, while T and B cells were markedly increased, in mesenteric lymph nodes (Supplementary Fig. 1e). Foxp3^CreRptor^fl/fl mice, which have impaired mTORC1 signaling³⁰, also had elevated T_FH and GC B-cell responses (Supplementary Fig. 1f), indicating that mTORC1 is essential for the T_reg-cell-mediated suppression of spontaneous GC reactions. To determine if T_FH cells produce elevated levels of IL-4 and/or IL-21 to promote GC reactions^35,36, we isolated CD4⁺Foxp3-YFP⁻CD44^hiCXCR5⁻PD-1⁻ non-T_FH cells and CD4⁺Foxp3-YFP⁻CD44^hiCXCR5⁺PD-1⁺ T_FH cells from Foxp3^CreMtor^fl/fl mice and their littermate controls, and measured the expression of Il4 and Il21. T_FH cells from Foxp3^CreMtor^fl/fl mice had increased expression of Il4, but not Il21, while non-T_FH cells had increased expression of both Il4 and Il21 (Supplementary Fig. 1g, h). Thus, constitutive depletion of mTOR revealed its essential role for T_reg cell-mediated suppression of conventional T-cell responses in vivo.

mTOR supports T_reg-cell suppression of mucosal T_H2 responses

T_reg cells regulate T-cell responses important for tissue homeostasis, especially at barrier surfaces like the lung, intestines, and skin^1,2. We found that in the lung of Foxp3^CreMtor^fl/fl mice, there were respective 5–10-fold and 10–15-fold increases of IL-4- and IL-13-producing CD4⁺ T cells, while the increases in T_H1 and T_H17 responses were less pronounced (2–3-fold increased) (Fig. 3a and Supplementary Fig. 2a). T_H2 and T_H17 responses were also more elevated than T_H1 responses in the colon lamina propria (Fig. 3b). Because we found a consistent increase of T_H2 cytokines in both the lung and colon lamina propria and acute deletion of mTOR led to a profound increase of T_H2 responses (Fig. 1h), we next performed comprehensive immunohistochemistry analyses of multiple organs in Foxp3^CreMtor^fl/fl mice. Elevated T_H2 responses are associated with an accumulation of eosinophils, alternatively activated M2 macrophages, and neutrophils in target tissues¹⁶. Indeed, MBP⁺ eosinophils were increased in the lung (Fig. 3c), as well as the dermis of the skin (Supplementary Fig. 2b) of mice-bearing mTOR-deficient T_reg cells. Additionally, CD163⁺ macrophages were expanded, including Ym1⁺ M2 macrophages present in the alveolar space and interstitium of the lung (Fig. 3d). Increased M2 macrophage activation was also evident in the skin (Supplementary Fig. 2c). We also observed an increase of cells positive for iNOS2, which primarily stains for neutrophils, in the lung (Fig. 3e) and skin (Supplementary Fig. 2d). T_H2 inflammation is also associated with the accumulation of mucosal mast cells (MMCs) in the intestines³⁷. Foxp3^CreMtor^fl/fl mice had an increase of MCPT1⁺ interepithelial MMCs and MCPT4⁺ lamina propria MMCs in the large and small intestines (Fig. 3f). Altogether, these results underscore an important role for mTOR in mediating T_reg-cell-dependent suppression of effector T-cell responses, especially T_H2-associated events, within mucosal tissues.

mTOR enforces mucosal tT_reg- and pT_reg-cell homeostasis

Recent work shows that tT_reg cells present in tissues exhibit T_H2-biased gene signatures and express transcription factors essential for the suppression of T_H2 responses^12,38,39. Additionally, the absence of pT_reg cells drives elevated T_H2 responses in mucosal tissues^16,17,18. Therefore, we hypothesized that reduced abundance of tT_reg and/or pT_reg cells might account for increased T_H2 responses in the lung and colon of Foxp3^CreMtor^fl/fl mice. Neuropilin-1 (Nrp1) and Helios are expressed at higher levels in tT_reg than pT_reg cells^40,41. We found that there was a significant decrease in the frequency of Nrp1⁺ tT_reg and Nrp1⁻ pT_reg cells in the lung of Foxp3^CreMtor^fl/fl mice (Fig. 4a). Helios staining revealed a similar reduction in tT_reg and pT_reg cells in the lung of Foxp3^CreMtor^fl/fl mice (Fig. 4b). We tested if these effects were cell-intrinsic by adoptively transferring an equal ratio of CD45.1⁺ wild-type bone marrow cells and CD45.2⁺ Foxp3^CreMtor^+/fl or Foxp3^CreMtor^fl/fl bone marrow cells into irradiated Rag1^–/–-recipient mice. This inflammation-free system confirmed that the reduction of these lung T_reg-cell populations was cell-intrinsic (Fig. 4c). We next examined pT_reg and tT_reg cell populations in the colon lamina propria of Foxp3^CreMtor^fl/fl mice by staining for either Helios or RORγt, a transcription factor selectively enriched in pT_reg cells isolated from the intestines^17,19. Similar to our observations in the lung, pT_reg cells, as well as Helios⁺ or RORγt^– tT_reg cells, were reduced in the colon lamina propria of Foxp3^CreMtor^fl/fl mice (Fig. 4d, e). The reduction of RORγt⁺ pT_reg cells may also contribute to the increased T_H17 cell activation in the colon lamina propria of Foxp3^CreMtor^fl/fl mice (Fig. 3b)¹⁹. Analysis of Helios⁺ and Helios⁻ T_reg-cell populations in the colon lamina propria from mixed bone marrow chimeras verified cell-intrinsic effects (Fig. 4f). Altogether, these results indicate that the accumulation of mucosal tissue tT_reg and pT_reg cells is disrupted in the absence of mTOR.

To determine the role for mTOR in pT_reg-cell maintenance in vivo, we purified naive Foxp3-YFP⁻CD4⁺ T cells from either Foxp3^CreMtor^+/fl or Foxp3^CreMtor^fl/fl mice and adoptively transferred these cells into Rag1^–/– mice (Fig. 4g). In this system, naive T cells can acquire Foxp3 expression⁴², and the concomitant expression of the Cre transgene induces Mtor deletion in pT_reg cells generated in vivo. The frequency and number of mTOR-deficient pT_reg cells were reduced in mesenteric lymph nodes (Fig. 4h), while the numbers of donor-derived total CD4⁺ T cells were comparable (Fig. 4i). These results indicate that mTOR promotes the maintenance of pT_reg cells in vivo.

Activated T_reg cells express GATA3, which is required to suppress T_H2 responses^{1,2,11,12,16,38}. Therefore, we next examined if mTOR regulates GATA3 expression in activated T_reg cells. We established an in vitro system where T_reg cells from wild-type mice were stimulated with anti-CD3 and anti-CD28 antibodies in the presence of TGF-β and IL-6 to mimic the environmental signals at mucosal sites^1,2,12. As expected, compared with IL-2 stimulation, IL-4 strongly upregulated GATA3 expression under these conditions¹². However, IL-4-induced GATA3 upregulation was diminished upon inhibition of mTOR activity (Fig. 4j). The frequency of GATA3⁺ T_reg cells was also significantly reduced in the colon lamina propria (Fig. 4k), a site where these cells are enriched under steady state^11,12. These in vitro and in vivo results highlight the requirement of mTOR signaling for GATA3 expression in T_reg cells.

mTOR promotes eT_reg-cell generation

After thymic development, peripheral cT_reg cells undergo antigen and inflammation-driven activation and differentiate into eT_reg cells that are enriched in tissues, including the lung and colon lamina propria^{1,2,7,8,21,22}. Although eT_reg cells are crucial for immune homeostasis, the molecular requirements driving their activation and function are still poorly defined. Our above data indicated that mTOR-deficient tT_reg cells were reduced in the lung and colon. Moreover, unbiased GSEA showed that mTORC1 signaling was enriched in CD44^hiCD62L^lo eT_reg cells compared to CD44^loCD62L^hi cT_reg cells (Fig. 5a). Given these results, we next tested whether mTOR regulates eT_reg-cell generation. Because T_reg cells isolated from inflammatory environments could undergo secondary phenotypic changes, we analyzed cell-intrinsic effects of mTOR deficiency in cT_reg and eT_reg cells isolated from healthy, female mosaic mice (designated as Foxp3^Cre/+). There was an increase in the frequency but not number of Foxp3-YFP⁺CD44^loCD62L^hi cT_reg cells and a reduction in the frequency and number of Foxp3-YFP⁺CD44^hiCD62L^lo eT_reg cells in the spleen of Foxp3^Cre/+Mtor^fl/fl mosaic mice (Fig. 5b). We also confirmed the reduction of eT_reg cells in the spleen of mixed bone marrow chimeras (Supplementary Fig. 3a). Consistent with elevated mTORC1 signaling in eT_reg cells (Fig. 5a), the frequency and number of eT_reg cells were reduced in the absence of Rptor (Supplementary Fig. 3b). The number of KLRG1⁺ T_reg cells was also reduced in absence of mTOR, consistent with a reduction of eT_reg cells (Fig. 5c and Supplementary Fig. 3c)⁹. The expression of CD25, a marker expressed at higher levels on cT_reg cells than eT_reg cells⁹, was increased on mTOR-deficient T_reg cells (Fig. 5d and Supplementary Fig. 3d). Moreover, eT_reg-cell-associated molecules like ICOS and CTLA4 were expressed at lower levels in the absence of mTOR, while the expression of TIGIT or Foxp3 was equivalent between the control and mTOR-deficient T_reg cells (Fig. 5d and Supplementary Fig. 3d)^1,2,9. Activated T_reg cells also differentiate into specialized or tissue-resident T_reg-cell populations, including CXCR5⁺PD1⁺Foxp3⁺ T_FR cells that express Bcl6^5,10,13. Both T_FR cells and Bcl6 expression were reduced in the absence of mTOR (Fig. 5e and Supplementary Fig. 3e). Consistent with our earlier analysis of mixed bone marrow chimeras, there was nearly a complete loss of colon T_reg cells in Foxp3^CreMtor^fl/fl mosaic mice (Fig. 5f). Thus, mTOR is essential for maintaining eT_reg cells in vivo.

Mechanistically, the loss of eT_reg cells in the absence of mTOR could be due to defective survival or reduced activation-induced differentiation. To test the former, we analyzed the expression of active caspase-3 in control and mTOR-deficient T_reg cells isolated from mixed bone marrow chimeras and found normal survival of mTOR-deficient T_reg cells (Fig. 5g). Also, the frequency of 7AAD⁺ cells was similar or reduced in purified CD44^loCD62L^hi cT_reg cells activated in the presence of the mTOR inhibitors (Supplementary Fig. 3f), further indicating that mTOR is not essential for cell survival.

To test the role of mTOR in activation-induced differentiation, we purified CD44^loCD62L^hi cT_reg cells from wild-type mice and activated them for 3 days in the presence or absence of the mTOR inhibitors, Torin 1 and PP242⁴³. We found that cT_reg cells differentiation into CD44^hiCD62L^lo eT_reg-like cells was impaired by mTOR inhibition (Fig. 5h). Similarly, the frequency of mTOR-deficient T_reg cells in the spleen and peripheral lymph nodes of DT-treated Foxp3^Cre/DTRMtor^fl/fl mice was reduced relative to the controls (Supplementary Fig. 3g, left panel), but total numbers of T_reg cells were not significantly different (Supplementary Fig. 3g, right panel), likely due to the increased organ size (Fig. 1e). Thus, mTOR-deficient T_reg cells also fail to appropriately respond to activation-induced signals in vivo. We also investigated if these regulatory pathways applied to human cells. In the presence of the mTOR inhibitors, activated human CD45RA^hiCD45RO^lo naive T_reg cells had impaired upregulation of CD25 and FOXP3 (Fig. 5i), which are expressed more abundantly in human CD45RA^loCD45RO^hi activated T_reg cells than naive T_reg cells⁴⁴. Thus, mTOR activity represents an evolutionarily conserved pathway for driving eT_reg-cell generation.

mTOR links activation signals to IRF4 upregulation

IRF4 is induced by TCR signals to promote eT_reg-cell differentiation and regulates T_reg-cell-mediated suppression of T_H2 responses in vivo^7,8,15,21,22. To determine if mTOR induces IRF4 expression upon activation, we purified control and mTOR-deficient cT_reg cells and activated them for 24 and 48 h before analyzing IRF4 expression by flow cytometry. IRF4 expression was reduced at 24 and 48 h after activation (Fig. 6a). Acute mTOR inhibition with Torin 1 or PP242 also significantly reduced activation-induced upregulation of IRF4 in cT_reg cells (Fig. 6b). Mechanistically, mTOR controls IRF4 expression at the post-transcriptional level, because cT_reg cells activated in the presence of the mTOR inhibitors for 24 or 48 h had increased Irf4 expression compared to the internal controls (Fig. 6c). To show that the ~20–30% reduction of IRF4 expression was biologically important, we analyzed gene expression profiles in cT_reg cells activated in the presence or absence of Torin 1 or PP242. Among the genes that were consistently altered by both inhibitors were 124 IRF4 target genes, including Ccr8 and Eea1^8,15,21,22 (Fig. 6d). Also, the loss of IRF4 expression likely accounted for the impairment of mTOR-deficient T_reg cells to express ICOS (Fig. 5d and Supplementary Fig. 3d), which is induced by IRF4-dependent mechanisms to drive eT_reg-cell differentiation in vivo^9,15. Altogether, these data indicate that mTOR promotes eT_reg-cell differentiation, in part, by modulating IRF4 expression, which also helps explain how T_H2 responses become elevated in Foxp3^CreMtor^fl/fl mice.

mTOR orchestrates mitochondrial metabolism in T_reg cells

Metabolism is a crucial determinant of T_reg-cell biology²³, but the mechanisms controlling metabolic rewiring required for the function of activated T_reg cells are not clear. GSEA showed that cT_reg cells upregulated mTORC1 signaling and several metabolic pathways, including glycolysis, upon activation (Supplementary Fig. 4a), while mTOR inhibitor-treated cT_reg cells had a significant downregulation of genes in the glycolytic pathway (Fig. 6e and Supplementary Table 1), including Hk2 (Fig. 6d). Because IRF4 also promotes metabolic reprograming of conventional CD4⁺ and CD8⁺ T cells⁴⁵, we determined if mTOR signals via IRF4 to regulate T_reg-cell metabolism. We performed functional enrichment analysis of IRF4 targets that were differentially expressed in cT_reg cells activated in the presence of mTOR inhibitors (Fig. 6d). This analysis revealed enrichments for glycolytic and nucleotide metabolism and upstream regulators of these pathways, including Myc and mTORC1^30,46,47 (Fig. 6f). Thus, the mTOR-IRF4 axis supports the upregulation of glycolytic and nucleotide metabolism during cT_reg-cell activation.

Besides glycolysis, cT_reg cells upregulated genes in the oxidative phosphorylation pathway in an mTOR-dependent manner (Fig. 7a and Supplementary Table 1). Indeed, 366 mitochondrial genes (identified from the MitoCarta 2.0 database⁴⁸) were differentially expressed in activated cT_reg cells (vs. unstimulated cells), and 158 of these genes were mTOR targets (Fig. 7b). Twenty-one mitochondrial genes were putative IRF4 gene targets (based on IRF4 ChIP-seq analysis²²), but only six of these genes were induced upon cT_reg-cell activation. Only one of these IRF4 targets (Mrps28) was upregulated in an mTOR-dependent manner during cT_reg-cell activation (Fig. 7b). These data, combined with the functional enrichment analysis above, suggest that mTOR promotes mitochondrial gene expression in a largely IRF4-independent manner. To further test the effects of mTOR on the metabolic pathways, we performed metabolomics profiling using high-resolution mass spectrometry on resting and activated T_reg cells. We found that 54 metabolites were differentially expressed between T_reg cells activated in the presence of Torin 1 vs. DMSO (Fig. 7c). For instance, the expression of the TCA cycle intermediates isocitrate/citrate, malate, and succinate and the electron acceptor NAD⁺ were significantly decreased in T_reg cells activated in the presence of Torin 1 (Fig. 7c). Unbiased metabolite set enrichment analysis (MSEA) revealed that activated T_reg cells significantly upregulated metabolic pathways associated with mitochondria-dependent energy production and the biosynthesis of proteins and nucleotides, such as the citric acid cycle, the mitochondrial electron transport chain, and pyrimidine biosynthesis⁴⁹ (Supplementary Fig. 4b). The upregulation of these mitochondria-related metabolic pathways was impaired when T_reg cells were activated in the presence of Torin 1 (Fig. 7d). Consistent with this observation, T_reg cells activated in the presence of Torin 1 had lower mitochondrial membrane potential (TMRM), whereas mitochondria number as indicated by Mitotracker staining was comparable (Fig. 7e). Thus, mTOR links activation signals to IRF4-dependent and -independent transcriptional programs to induce metabolic reprogramming during T_reg-cell activation.

Tfam is essential for eT_reg-cell homeostasis and function

We next genetically defined the importance of mitochondrial metabolism in T_reg-cell function in vivo. We conditionally deleted mitochondrial transcription factor A (Tfam), a nuclear-encoded transcription factor essential for efficient electron transport chain activity^50,51, in T_reg cells by breeding Foxp3^Cre transgenic mice with mice-bearing floxed alleles for Tfam⁵¹. Tfam-deficient T_reg cells isolated from Foxp3^Cre/+Tfam^fl/fl mosaic mice had comparable mitochondrial content but less mitochondria-derived reactive oxygen species (ROS) (Fig. 8a), consistent with reduced mitochondrial respiratory chain function. We found that Tfam is critical for T_reg-cell function, as Foxp3^CreTfam^fl/fl mice developed a severe inflammatory disease associated with smaller body size, skin inflammation, alopecia (Fig. 8b), early lethality (Fig. 8c), and enlargement of the peripheral lymph nodes (Fig. 8d). Further, there were increased effector/memory T cells (Fig. 8e) and significantly enhanced IFN-γ-producing CD8⁺ T cell and T_H1, T_H2, and T_H17-cell activation (Fig. 8f) in diseased mice-bearing Tfam-deficient T_reg cells. Tfam-deficient T_reg cells also had a propensity for increased IFN-γ production (Supplementary Fig. 5a). Moreover, the frequency and number of T_FH cells were increased (Fig. 8g). Only the frequency, not the number, of GC B cells was increased, likely due to a reduction of total B220⁺ B cells in Foxp3^CreTfam^fl/fl mice (Fig. 8h and Supplementary Fig. 5b). Thus, Tfam deficiency in T_reg cells leads to altered immune homeostasis and development of autoimmunity.

We next analyzed T_reg-cell populations in mixed bone marrow chimeras to determine the cell-intrinsic role of Tfam-dependent mitochondrial metabolism in eT_reg-cell accumulation and homeostasis. There was a reduction in the frequency and number of CD44^hiCD62L^lo eT_reg cells (Fig. 8i) and KLRG1⁺ T_reg cells (Fig. 8j) in the absence of Tfam. Further, Tfam-deficient T_reg cells had reduced expression of ICOS and CTLA4 (Fig. 8k), but not Foxp3 (Supplementary Fig. 5c). However, unlike mTOR-deficient T_reg cells, CD25 expression was not increased on Tfam-deficient T_reg cells (Supplementary Fig. 5c), and TIGIT expression was reduced (Fig. 8k). Tfam deficiency also reduced T_FR-cell generation and Bcl6 expression (Fig. 8l). Further, there was a cell-intrinsic reduction of Tfam-deficient T_reg cells within the colon lamina propria and the lung (Fig. 8m, n). Collectively, these results indicate that Tfam-dependent mitochondrial metabolism is critical for the function and homeostasis of activated T_reg cells in vivo.

Discussion

Activated tT_reg and pT_reg cells are crucial for peripheral T-cell tolerance and tissue homeostasis. Here, we show that activated T_reg-cell populations have increased mTOR signaling necessary for T_reg-cell activation and tissue T_reg-cell homeostasis. Mechanistically, mTOR tunes IRF4-dependent transcriptional programming and mitochondrial metabolism. In the absence of mTOR, activated tT_reg and pT_reg cells are severely decreased in mucosal tissues, associated with excessive T_H2, and to a lesser extent T_H1 and T_H17 responses, and disrupted tissue homeostasis. Further, the homeostasis and suppressive activity of activated T_reg cells is impaired by the loss of mitochondrial metabolism and consequently leads to autoimmunity (Supplementary Fig. 5d). Thus, our data identify and establish a critical mTOR-dependent metabolic node that regulates the homeostasis and suppressive function of activated T_reg cells in vivo.

TCR-dependent signals coupled with co-stimulation and inflammatory cues drive T_reg-cell activation and differentiation into specialized or tissue-resident T_reg-cell subsets^{1,2,7,8,9,21,22}. Several transcriptional programs are essential for the differentiation and function of activated T_reg cells^{7,20,21,22,43,52,53}. However, the upstream signaling pathways driving eT_reg-cell homeostasis are unknown. Here, we show that activation signals through mTOR are required for T_reg-cell activation and function, thereby establishing the first kinase pathway, to our knowledge, that links TCR signals and transcriptional programs necessary for T_reg-cell activation. Mechanistically, mTOR promotes the expression of IRF4 and GATA3, transcription factors that are essential for T_reg-cell-dependent suppression of T_H2 responses^7,11,12,15. Moreover, IRF4 also enforces eT_reg-cell differentiation and pT_reg-cell homeostasis to limit mucosal T_H2 responses^{16,17,20,21,22}. Therefore, by promoting the expression of IRF4 and GATA3, mTOR maintains activated T_reg-cell populations that facilitate tissue homeostasis. The mTOR-dependent induction of IRF4 expression in cT_reg cells was not transcriptionally regulated, and, in conventional CD4⁺ T cells⁵⁴, occurs independently of the mTOR-4EBP1 translation axis. Therefore, mTOR likely regulates IRF4 expression at the post-translational level, such as via SUMOlyation⁵⁵. A key question that remains is, why are mucosal tissues more sensitive to the upregulation of T_H2 responses than secondary lymphoid organs in mice-bearing mTOR-deficient T_reg cells? One possibility is that these sites are enriched for activated tT_reg- and pT_reg-cell populations and hence their loss more readily increases T_H2 responses at these sites than in the peripheral lymphoid organs^1,2,56. Further, recent work shows that tissue T_reg cells express high levels of ST2 (IL-33 receptor)^38,39, which induces GATA3 activation that biases T_reg cells toward the T_H2 suppressive program³⁹. Thus, mTOR deficiency and other conditions that decrease GATA3 expression will impair this feed forward loop and disrupt T_H2-like T_reg-cell suppressive responses.

Metabolic reprogramming contributes to cell fate decisions. However, the metabolic programs promoting the homeostasis and function of activated T_reg cells are not completely understood²³. Despite the previous work suggesting an inhibitory role of mTOR for mitochondrial oxidative metabolism in induced T_reg cells in vitro²⁷, we show here that mitochondrial metabolism is highly induced during T_reg-cell activation in an mTOR-dependent manner, and is essential for activated T_reg-cell function and tissue homeostasis in vivo. Indeed, T_reg-specific deletion of Tfam impairs T_reg-cell function, leading to the hyperactivation of conventional T cells and autoimmunity. Mechanistically, mitochondrial metabolism could affect eT_reg-cell proliferation or survival within tissues as has been reported in vitro^27,28. Of note, Raptor-deficient T_reg cells have reduced mitochondria-related gene expression³⁰, and Foxp3^CreTfam^fl/fl and Foxp3^CreRptor^fl/fl mice have similar elevations in activated T-cell responses, disease pathologies, and survival kinetics³⁰. Additionally, deficiency of Tfam and Raptor impairs T_FR cell accumulation⁵⁷. Thus, our data suggest a key role for Raptor-mTORC1-induced mitochondrial metabolism in establishing the fate and function of activated T_reg cells in different microenvironments.

T_reg cells must adapt to different environmental cues to acquire unique suppressive functions, and the appropriate balance of mTOR and metabolic signaling appears to be linked to this process. Inactivation of mTORC1 alone or combined with mTORC2 disrupts T_reg-cell suppressive activity³⁰; however, whether mTORC1-independent functions of Raptor⁵⁸ or Raptor/Rictor-independent mTOR complexes play roles in T_reg-cell biology remained unclear. Our results here suggest that mTOR does act through Raptor and Rictor to promote T_reg-cell function. Compared to Raptor deficiency alone, loss of mTOR or Raptor and Rictor in T_reg cells leads to similar extensions in lifespan³⁰, which may be due to more limited tissue damage, such as in the intestines. The balance of mTORC1- and/or mTORC2-induced metabolic programs may also tune T_reg-cell suppression of effector T-cell responses. For instance, Raptor-deficient T_reg cells have increased mTORC2-Akt activity³⁰, which can upregulate glycolysis at the expense of mitochondrial metabolism and lead to inappropriate suppression of T_H1 and T_FH responses^59,60,61. Despite being dispensable for T_reg-cell suppressive activity^30,61, mTORC2 can promote T_reg-cell trafficking to sites of inflammation and non-lymphoid tissues via upregulating glycolysis or suppressing Foxo1 activity^43,62. Thus, gain of mTORC1 and concomitant loss of mTORC2 activity could reduce T_reg-cell trafficking to T_H1 and T_H17 inflammatory sites^63,64,65. mTOR may also promote trafficking to sites of T_H2 inflammation by modulating Ccr8 expression and/or CCL22/CCR4-induced chemotaxis^62,66. We, therefore, propose that T_reg-cell function is finely tuned by graded nature of mTOR signaling and metabolic programs, which are likely influenced by local environmental signals. This tunable nature of mTOR signaling in T_reg cells may offer a therapeutic strategy to modulate T_reg-cell responses to selectively alter the conventional T-cell responses in autoimmunity, infectious diseases, and cancer.

Methods

Mice

C57BL/6, CD45.1⁺, Cd4^Cre, Foxp3^DTR, Rag1^–/–, Mtor^fl, and Tfam^fl mice were purchased from The Jackson Laboratory. Foxp3^Cre mice, from Dr. Alexander Rudensky, have been described previously³³. All genetic models used in this study were on the C57BL/6 background, and both male and female mice were used for quantification and analysis, except for histological analysis where only male mice were used. Mice were generally 4–6-weeks-old unless otherwise indicated. The number of animals in each group are provided in the figures and/or figure legends. All mice were kept in specific pathogen-free conditions within the Animal Resource Center at St. Jude Children’s Research Hospital. The animal protocols were approved by the Institutional Animal Care and Use Committee of St. Jude Children’s Research Hospital. Mixed bone marrow chimeras were generated by adoptive transfer of CD45.1⁺ bone marrow cells mixed 1:1 with CD45.2⁺ bone marrow cells from Foxp3^CreMtor^+/fl or Foxp3^CreMtor^fl/fl mice into sub-lethally irradiated Rag1^–/– mice as described³⁰. For the pT_reg cell in vivo maintenance model, CD4⁺Foxp3-YFP⁻CD44^loCD62L^hi naive T cells from the spleens and peripheral lymph nodes of Foxp3^CreMtor^+/fl or Foxp3^CreMtor^fl/fl mice were purified on a Synergy or Reflection fluorescence activated cell sorter (Sony Biotechnology). Then, 0.75 × 10⁶ cells were transferred via retroorbital injection into sex-matched Rag1^–/– mice. The presence of Foxp3-YFP⁺ T_reg cells was evaluated in the mesenteric lymph nodes 4 weeks later⁴². Foxp3^Cre/DTR mosaic mice were treated with DT (50 μg kg⁻¹) i.p. three times per week, for a total of four injections. The mice were euthanized, and tissues were harvested for flow cytometry analysis 11 days following the first DT treatment. Sample sizes were chosen based upon previous data generated within the laboratory and were selected to maximize the chance of uncovering statistically significant differences of the mean. No animals were excluded from analysis.

Flow cytometry

Lymphocytes were harvested form the peripheral lymphoid tissues by manual disruption or the colon lamina propria as previously described^30,67. For surface marker analyses, cells were stained in PBS containing 2% (wt/vol) BSA and the appropriate antibodies. The following fluorescent-conjugate-labeled antibodies, purchased from various commercial sources (Biolegend, BD Biosciences, Thermo Fisher Scientific, and Sony Biotechnology), were used: anti-CD4 (clone RM4-5), anti-CD8 (clone 53-6.7), anti-B220 (clone RA3-6B2), anti-CD62L (clone MEL-14), anti-CD44 (clone IM7), anti-CD95 (clone Jo2), anti-GL7 (clone GL-7), anti-CD279 (PD-1) (Clone J43), and anti-TCRβ (clone H57-597) antibodies. Biotin-conjugated anti-CXCR5 antibody (clone 2G8) and PE-labeled streptavidin from BD Biosciences were used for T_FH cell staining. Intracellular staining was performed using the Foxp3/Transcription Factor Staining buffers (Cat #00-5523-00, Thermo Fisher Scientific) per the manufacturer’s instructions. The following antibodies were used: anti-CD152 (CTLA4) (clone UC10-4B9), anti-Foxp3 (clone NRRF-30), anti-RORγt (clone B2D), anti-GATA3 (clone TWAJ), anti-IRF4 (clone 3E4), anti-Helios (clone 22F6), anti-IL-4 (clone 11B11), anti-IL-10 (clone JES5-16E3), anti-IL-13 (clone eBio13A), anti-IFN-γ (clone XMG1.2), anti-IL-17A (clone TC11-18H10.1), anti-human CD25 (clone BC96), anti-human CD45RA (clone HI100), anti-human CD45RO (clone UCHL1), anti-human CD4 (clone A161A1), and anti-human FOXP3 (clone 236 A/E7). For intracellular cytokine staining, total splenocytes were stimulated for 4–5 h with phrobol 12-myristate 13-acetate (PMA) and ionomycin in the presence of monensin (BD Biosciences). Surface and intracellular staining was then performed as above. For active caspase-3 staining, surface molecules were stained before cells were fixed, permeabilized, and stained for intracellular active caspase-3 using the BD Biosciences active caspase-3 apoptosis kit per the manufacturer’s instructions (Cat # 550914). Staining for mitochondrial dyes (MitoSOX, TMRM, and Mitotracker Deep Red; Thermo Fisher Scientific) was performed as previously described³⁰.

Histology and immunohistochemistry

Tissues were fixed in 10% (vol/vol) neutral buffered formalin solution, embedded in paraffin, section, and stained with hematoxylin and eosin. Blinded samples were analyzed by an experienced pathologist (P.V.) for the presence of lesions indicative of autoimmune disease. For the identification of ieMMCs or lpMMCs, tissue sections from the small intestines and large intestines were respectively stained with primary rat anti-MCPT1 monoclonal antibody (Cat # 14-55303-82, Thermo Fisher Scientific) or goat anti-MCPT4 antibody (LS-B5958, LifeSpan Biosciences) as described previously³⁷. GCs were identified by staining with anti-CD3 antibody and peanut agglutinin as described⁶¹.

In vitro T_reg-cell suppression assays

For analysis of T_reg-cell suppression in vitro, CD4⁺CD25^hi T_reg cells or CD4⁺Foxp3-YFP⁺ T_reg cells, isolated from the lymphoid organs of the respective Cd4^Cre- or Foxp3^Cre-expressing mice, were co-cultured with naive CD4⁺ T cells and irradiated splenocytes as antigen presenting cells as previously described³⁰. For suppression assays using in vitro activated T_reg cells, CD25^hi T_reg cells were sorted from the lymphoid organs of C57BL/6 mice, resuspended in complete Click’s medium containing IL-2 (200 U ml⁻¹), and activated using anti-CD3 (10 μg ml⁻¹) and anti-CD28 (10 μg ml⁻¹) antibodies for 3 days in the presence of PP242 (500 nM, Tocris Bioscience) or vehicle control. The live cells were then isolated using Lymphocyte Separation medium and co-cultured with naive CD4⁺ T cells and irradiated splenocytes for 3 days, and the incorporation of [³H]-thymidine was assessed as described³⁰.

T_reg-cell cultures

CD4⁺Foxp3-YFP⁺CD44^loCD62L^hi cT_reg cells were purified and activated with anti-CD3 and anti-CD28 antibodies in the presence of recombinant IL-2 for various times in the presence of vehicle, Torin 1 (50 nM) or PP242 (500 nM) before total RNA was harvested using the Qiagen RNeasy micro kit per the manufacturer’s instructions. Alternatively, cT_reg cells were stimulated as above for 1–3 days and analyzed by flow cytometry as previously described⁴³. For analysis of GATA3 protein expression, CD4⁺CD25⁺ T_reg cells were isolated from the mesenteric lymph nodes using the CD25⁺ T_reg-cell enrichment kit (Miltenyi). The cells were then activated with anti-CD3 (5 μg ml⁻¹) and anti-CD28 (5 μg ml⁻¹) antibodies for 3 days in the presence of various stimuli and/or Torin 1 (50 nM) as indicated in the figure: TGF-β (2 ng ml⁻¹), IL-2 (200 U ml⁻¹), IL-4 (20 ng ml⁻¹), IL-6 (20 ng ml⁻¹), and butyrate (125 μM). The expression of GATA3 in Foxp3⁺ T_reg cells was assessed by flow cytometry.

Human T_reg-cell cultures

All human studies were in compliance with the Declaration of Helsinki. Blood donors were recruited by the Blood Donor Center at St. Jude Children’s Research Hospital, where they provided written consent for their discarded blood products to be used for research. This consent form has been reviewed and approved by the Institutional Review Board at St. Jude Children’s Research Hospital. We were provided with apheresis rings containing peripheral blood mononuclear cells (PBMCs) isolated from de-identified donors. Human CD4⁺CD25⁺CD45RA⁺CD45RO⁻ naive T_reg cells were purified from these human PBMCs, and activated with anti-CD3 (clone OKT3, 5 μg ml⁻¹) and anti-CD28 (clone CD28.2, 5 μg ml⁻¹) for 3 days in the presence of IL-2 and mTOR inhibitors as above. The expression of human CD25 and human FOXP3 was then analyzed by flow cytometry.

Metabolomics

CD4⁺CD25^hi T_reg cells, isolated from lymphoid organs of C57BL/6 mice, were purified and resuspended in complete Click’s medium. Then, 1.3 × 10⁶ T_reg cells were treated with medium alone or immobilized anti-CD3 antibody (10 μg ml⁻¹) and anti-CD28 antibody (10 μg ml⁻¹) for 16 h in the presence Torin 1 (50 nM) or vehicle control. Intracellular metabolites, isolated using methanol extraction of two technical replicates, were analyzed using the Ultimate 3000 UHPLC (Dionex) coupled to Q Exactive Plus-Mass spectrometer (QE-MS, Thermo Fisher Scientific) for metabolite profiling. Detailed methods were previously described⁶⁸, except that mobile phase A was replaced with water containing 5 mM ammonium acetate (pH 6.8). Differentially expressed metabolites were identified by Limma (Bioconductor) and the Benjamini-Hochberg method was used to estimate the false discover rate (FDR). MetaboAnalyst was used to analyze range-scale data and provide KEGG pathway analysis of significantly altered metabolic pathways (log₂ = 0.5) (www.metaboanalyst.ca/)⁴⁹.

Gene expression analysis

For mTOR deletion efficiency in T_reg cells, quantitative real-time PCR analysis was performed using Mtor Taqman probes (Thermo Fisher Scientific, Cat #4351372). For detection of Il4 and Il21, CD4⁺Foxp3-YFP^–CD44^hiCXCR5^–PD-1⁻ non-T_FH cells or CD4⁺Foxp3-YFP^–CD44^hiCXCR5⁺PD-1⁺ T_FH cells were stimulated for 4 h using plate bound anti-CD3 (5 μg ml⁻¹) and anti-CD28 (5 μg ml⁻¹) antibodies. Quantitative real-time PCR analysis was performed using SyBR Green Real-Time PCR Master Mix (Thermo Fisher Scientific) and primers for Il4 (Forward 5’-GGTCTCAACCCCCAGCTAGT-3’; Reverse 5’-GCCGATGATCTCTCTCAAGTGAT-3’) and Il21 (Forward 5’-GGACCCTTGTCTGTCTGGTAG-3’; Reverse 5’-TGTGGAGCTGATAGAAGTTCAGG-3’). For microarray analysis, RNA samples from unstimulated cT_reg cells or cT_reg cells activated in the presence of vehicle, Torin 1, or PP242 for 20 h as indicated above were analyzed with the GeneChip Mouse Gene 2.0 ST Array (Thermo Fisher Scientific). Differentially expressed transcripts in biological triplicate samples were identified by ANOVA (Partek Genomics Suite version 6.5), and the Benjamini-Hochberg method was used to estimate the FDR.

GSEA of hallmark pathways in resting vs. activated T_reg cells from these microarray samples or published datasets (GSE55753³² or GSE61077⁷) was performed as previously described³⁰. IRF4 targets were identified from ChIP-seq data²² deposited in GSE98263 and compared against genes that were differentially expressed in activated cT_reg cells treated with or without mTOR inhibitors as above. IRF4 target genes that were differentially expressed in activated cT_reg cells treated with mTOR inhibitors were subjected to functional enrichment analysis of metabolism-related pathways, where significance was determined using the Fisher exact test and Benjamini-Hochberg method (FDR < 0.05).

Statistics

The results in graphs represent the mean ± s.e.m., with the numbers of mice per group and number of experimental replicates indicated in each figure legend. The P-values were calculated with unpaired, two-tailed Student’s t-test assuming equal variance (GraphPad Prism software), where *P < 0.05; **P < 0.01; ***P < 0.001. No specific randomization methods were used in these studies. Investigators were not blinded to samples except where indicated for histological and immunohistochemical analysis.

Data availability

Microarray data that support the findings of this study have been deposited in the Gene Expression Omnibus with the primary accession code GSE104130. Other data are available from the corresponding author upon request.

References

Li, M. O. & Rudensky, A. Y. T cell receptor signalling in the control of regulatory T cell differentiation and function. Nat. Rev. Immunol. 16, 220–233 (2016).
Article PubMed PubMed Central CAS Google Scholar
Ohkura, N., Kitagawa, Y. & Sakaguchi, S. Development and maintenance of regulatory T cells. Immunity 38, 414–423 (2013).
Article PubMed CAS Google Scholar
Fontenot, J. D., Gavin, M. A. & Rudensky, A. Y. Foxp3 programs the development and function of CD4+CD25+regulatory T cells. Nat. Immunol. 4, 330–336 (2003).
Article PubMed CAS Google Scholar
Hori, S., Nomura, T. & Sakaguchi, S. Control of regulatory T cell development by the transcription factor Foxp3. Science 299, 1057–1061 (2003).
Article ADS PubMed CAS Google Scholar
Chung, Y. et al. Follicular regulatory T cells expressing Foxp3 and Bcl-6 suppress germinal center reactions. Nat. Med. 17, 983–988 (2011).
Article ADS PubMed PubMed Central CAS Google Scholar
Abbas, A. K. et al. Regulatory T cells: recommendations to simplify the nomenclature. Nat. Immunol. 14, 307–308 (2013).
Article PubMed CAS Google Scholar
Levine, A. G., Arvey, A., Jin, W. & Rudensky, A. Y. Continuous requirement for the TCR in regulatory T cell function. Nat. Immunol. 15, 1070–1078 (2014).
Article PubMed PubMed Central CAS Google Scholar
Vahl, J. C. et al. Continuous T cell receptor signals maintain a functional regulatory T cell pool. Immunity 41, 722–736 (2014).
Article PubMed CAS Google Scholar
Smigiel, K. S. et al. CCR7 provides localized access to IL-2 and defines homeostatically distinct regulatory T cell subsets. J. Exp. Med. 211, 121–136 (2014).
Article PubMed PubMed Central CAS Google Scholar
Linterman, M. A. et al. Foxp3+follicular regulatory T cells control the germinal center response. Nat. Med. 17, 975–982 (2011).
Article PubMed PubMed Central CAS Google Scholar
Rudra, D. et al. Transcription factor Foxp3 and its protein partners form a complex regulatory network. Nat. Immunol. 13, 1010–1019 (2012).
Article PubMed PubMed Central CAS Google Scholar
Wohlfert, E. A. et al. GATA3 controls Foxp3(+) regulatory T cell fate during inflammation in mice. J. Clin. Invest. 121, 4503–4515 (2011).
Article PubMed PubMed Central CAS Google Scholar
Wollenberg, I. et al. Regulation of the germinal center reaction by Foxp3+follicular regulatory T cells. J. Immunol. 187, 4553–4560 (2011).
Article PubMed CAS Google Scholar
Yu, F., Sharma, S., Edwards, J., Feigenbaum, L. & Zhu, J. Dynamic expression of transcription factors T-bet and GATA-3 by regulatory T cells maintains immunotolerance. Nat. Immunol. 16, 197–206 (2015).
Article PubMed CAS Google Scholar
Zheng, Y. et al. Regulatory T-cell suppressor program co-opts transcription factor IRF4 to control T(H)2 responses. Nature 458, 351–356 (2009).
Article ADS PubMed PubMed Central CAS Google Scholar
Josefowicz, S. Z. et al. Extrathymically generated regulatory T cells control mucosal TH2 inflammation. Nature 482, 395–399 (2012).
Article ADS PubMed PubMed Central CAS Google Scholar
Ohnmacht, C. et al. MUCOSAL IMMUNOLOGY. The microbiota regulates type 2 immunity through RORgammat(+) T cells. Science 349, 989–993 (2015).
Article ADS PubMed CAS Google Scholar
Wu, C. et al. The transcription factor musculin promotes the unidirectional development of peripheral Treg cells by suppressing the TH2 transcriptional program. Nat. Immunol. 18, 344–353 (2017).
Article PubMed PubMed Central CAS Google Scholar
Sefik, E. et al. MUCOSAL IMMUNOLOGY. Individual intestinal symbionts induce a distinct population of RORgamma(+) regulatory T cells. Science 349, 993–997 (2015).
Article ADS PubMed PubMed Central CAS Google Scholar
Dias, S. et al. Effector regulatory T cell differentiation and immune homeostasis depend on the transcription factor Myb. Immunity 46, 78–91 (2017).
Article PubMed CAS Google Scholar
Cretney, E. et al. The transcription factors Blimp-1 and IRF4 jointly control the differentiation and function of effector regulatory T cells. Nat. Immunol. 12, 304–311 (2011).
Article PubMed CAS Google Scholar
Vasanthakumar, A. et al. The TNF receptor superfamily-NF-kappaB axis is critical to maintain effector regulatory T cells in lymphoid and non-lymphoid tissues. Cell Rep. 20, 2906–2920 (2017).
Article PubMed CAS Google Scholar
Newton, R., Priyadharshini, B. & Turka, L. A. Immunometabolism of regulatory T cells. Nat. Immunol. 17, 618–625 (2016).
Article PubMed PubMed Central CAS Google Scholar
Saxton, R. A. & Sabatini, D. M. mTOR signaling in growth, metabolism, and disease. Cell 168, 960–976 (2017).
Article PubMed PubMed Central CAS Google Scholar
Delgoffe, G. M. et al. The mTOR kinase differentially regulates effector and regulatory T cell lineage commitment. Immunity 30, 832–844 (2009).
Article PubMed PubMed Central CAS Google Scholar
Battaglia, M., Stabilini, A. & Roncarolo, M. G. Rapamycin selectively expands CD4+CD25+FoxP3+regulatory T cells. Blood 105, 4743–4748 (2005).
Article PubMed CAS Google Scholar
Michalek, R. D. et al. Cutting edge: distinct glycolytic and lipid oxidative metabolic programs are essential for effector and regulatory CD4+T cell subsets. J. Immunol. 186, 3299–3303 (2011).
Article PubMed PubMed Central CAS Google Scholar
Gerriets, V. A. et al. Metabolic programming and PDHK1 control CD4+T cell subsets and inflammation. J. Clin. Invest. 125, 194–207 (2015).
Article PubMed Google Scholar
Procaccini, C. et al. An oscillatory switch in mTOR kinase activity sets regulatory T cell responsiveness. Immunity 33, 929–941 (2010).
Article PubMed PubMed Central CAS Google Scholar
Zeng, H. et al. mTORC1 couples immune signals and metabolic programming to establish T(reg)-cell function. Nature 499, 485–490 (2013).
Article ADS PubMed PubMed Central CAS Google Scholar
Kim, J. M., Rasmussen, J. P. & Rudensky, A. Y. Regulatory T cells prevent catastrophic autoimmunity throughout the lifespan of mice. Nat. Immunol. 8, 191–197 (2007).
Article PubMed CAS Google Scholar
Arvey, A. et al. Inflammation-induced repression of chromatin bound by the transcription factor Foxp3 in regulatory T cells. Nat. Immunol. 15, 580–587 (2014).
Article PubMed PubMed Central CAS Google Scholar
Rubtsov, Y. P. et al. Regulatory T cell-derived interleukin-10 limits inflammation at environmental interfaces. Immunity 28, 546–558 (2008).
Article PubMed CAS Google Scholar
DuPage, M. et al. The chromatin-modifying enzyme Ezh2 is critical for the maintenance of regulatory T cell identity after activation. Immunity 42, 227–238 (2015).
Article PubMed PubMed Central CAS Google Scholar
Weinstein, J. S. et al. TFH cells progressively differentiate to regulate the germinal center response. Nat. Immunol. 17, 1197–1205 (2016).
Article PubMed PubMed Central CAS Google Scholar
Reinhardt, R. L., Liang, H. E. & Locksley, R. M. Cytokine-secreting follicular T cells shape the antibody repertoire. Nat. Immunol. 10, 385–393 (2009).
Article PubMed PubMed Central CAS Google Scholar
Vogel, P. et al. Globule leukocytes and other mast cells in the mouse intestine. Vet. Pathol. 55, 76-97 (2018).
Article PubMed Google Scholar
Delacher, M. et al. Genome-wide DNA-methylation landscape defines specialization of regulatory T cells in tissues. Nat. Immunol. 18, 1160-1172 (2017).
Article PubMed PubMed Central CAS Google Scholar
Schiering, C. et al. The alarmin IL-33 promotes regulatory T-cell function in the intestine. Nature 513, 564–568 (2014).
Article ADS PubMed PubMed Central CAS Google Scholar
Yadav, M. et al. Neuropilin-1 distinguishes natural and inducible regulatory T cells among regulatory T cell subsets in vivo. J. Exp. Med. 209, 1713–1722 (2012). S1711-1719.
Article PubMed PubMed Central CAS Google Scholar
Thornton, A. M. et al. Expression of Helios, an Ikaros transcription factor family member, differentiates thymic-derived from peripherally induced Foxp3+ T regulatory cells. J. Immunol. 184, 3433–3441 (2010).
Article PubMed PubMed Central CAS Google Scholar
Liu, G., Yang, K., Burns, S., Shrestha, S. & Chi, H. The S1P(1)-mTOR axis directs the reciprocal differentiation of T(H)1 and T(reg) cells. Nat. Immunol. 11, 1047–1056 (2010).
Article PubMed PubMed Central CAS Google Scholar
Luo, C. T., Liao, W., Dadi, S., Toure, A. & Li, M. O. Graded Foxo1 activity in Treg cells differentiates tumour immunity from spontaneous autoimmunity. Nature 529, 532–536 (2016).
Article ADS PubMed PubMed Central CAS Google Scholar
Miyara, M. et al. Functional delineation and differentiation dynamics of human CD4+ T cells expressing the FoxP3 transcription factor. Immunity 30, 899–911 (2009).
Article PubMed CAS Google Scholar
Man, K. et al. The transcription factor IRF4 is essential for TCR affinity-mediated metabolic programming and clonal expansion of T cells. Nat. Immunol. 14, 1155–1165 (2013).
Article PubMed CAS Google Scholar
Yang, K. et al. T cell exit from quiescence and differentiation into Th2 cells depend on Raptor-mTORC1-mediated metabolic reprogramming. Immunity 39, 1043–1056 (2013).
Article PubMed PubMed Central CAS Google Scholar
Wang, R. et al. The transcription factor Myc controls metabolic reprogramming upon T lymphocyte activation. Immunity 35, 871–882 (2011).
Article PubMed PubMed Central CAS Google Scholar
Calvo, S. E., Clauser, K. R. & Mootha, V. K. MitoCarta2.0: an updated inventory of mammalian mitochondrial proteins. Nucl. Acids Res. 44, D1251–D1257 (2016).
Article PubMed CAS Google Scholar
Xia, J. & Wishart, D. S. MetPA: a web-based metabolomics tool for pathway analysis and visualization. Bioinformatics 26, 2342–2344 (2010).
Article PubMed CAS Google Scholar
Larsson, N. G. et al. Mitochondrial transcription factor A is necessary for mtDNA maintenance and embryogenesis in mice. Nat. Genet. 18, 231–236 (1998).
Article PubMed CAS Google Scholar
Baixauli, F. et al. Mitochondrial respiration controls lysosomal function during inflammatory T cell responses. Cell Metab. 22, 485–498 (2015).
Article PubMed PubMed Central CAS Google Scholar
Grinberg-Bleyer, Y. et al. NF-κB c-rel is crucial for the regulatory T cell immune checkpoint in. Cancer Cell. 170, 1096–1108.e1013 (2017).
CAS Google Scholar
Oh, H. et al. An NF-kappaB transcription-factor-dependent lineage-specific transcriptional program promotes regulatory T cell identity and function. Immunity 47, 450–465 e455 (2017).
Article PubMed CAS PubMed Central Google Scholar
Yi, W. et al. The mTORC1-4E-BP-eIF4E axis controls de novo Bcl6 protein synthesis in T cells and systemic autoimmunity. Nat. Commun. 8, 254 (2017).
Article ADS PubMed PubMed Central CAS Google Scholar
Ding, X. et al. Protein SUMOylation is required for regulatory T cell expansion and function. Cell Rep. 16, 1055–1066 (2016).
Article PubMed CAS Google Scholar
Tian, L. et al. Foxp3(+) regulatory T cells exert asymmetric control over murine helper responses by inducing Th2 cell apoptosis. Blood 118, 1845–1853 (2011).
Article PubMed PubMed Central CAS Google Scholar
Xu, L. et al. The kinase mTORC1 promotes the generation and suppressive function of follicular regulatory T cells. Immunity 47, 538–551 e535 (2017).
Article PubMed CAS Google Scholar
Kim, K. et al. mTORC1-independent Raptor prevents hepatic steatosis by stabilizing PHLPP2. Nat. Commun. 7, 10255 (2016).
Article ADS PubMed PubMed Central CAS Google Scholar
Gerriets, V. A. et al. Foxp3 and Toll-like receptor signaling balance Treg cell anabolic metabolism for suppression. Nat. Immunol. 17, 1459–1466 (2016).
Article PubMed PubMed Central CAS Google Scholar
Huynh, A. et al. Control of PI(3) kinase in Treg cells maintains homeostasis and lineage stability. Nat. Immunol. 16, 188–196 (2015).
Article PubMed PubMed Central CAS Google Scholar
Shrestha, S. et al. Treg cells require the phosphatase PTEN to restrain TH1 and TFH cell responses. Nat. Immunol. 16, 178–187 (2015).
Article PubMed PubMed Central CAS Google Scholar
Kishore, M. et al. Regulatory T cell migration is dependent on glucokinase-mediated glycolysis. Immunity 47, 875–889 e810 (2017).
Article PubMed PubMed Central CAS Google Scholar
Apostolidis, S. A. et al. Phosphatase PP2A is requisite for the function of regulatory T cells. Nat. Immunol. 17, 556–564 (2016).
Article PubMed PubMed Central CAS Google Scholar
Park, Y. et al. TSC1 regulates the balance between effector and regulatory T cells. J. Clin. Invest. 123, 5165–5178 (2013).
Article PubMed PubMed Central CAS Google Scholar
Wei, J. et al. Autophagy enforces functional integrity of regulatory T cells by coupling environmental cues and metabolic homeostasis. Nat. Immunol. 17, 277–285 (2016).
Article PubMed PubMed Central CAS Google Scholar
Soler, D. et al. CCR8 expression identifies CD4 memory T cells enriched for FOXP3+ regulatory and Th2 effector lymphocytes. J. Immunol. 177, 6940–6951 (2006).
Article PubMed CAS Google Scholar
Hall, J. A. et al. Essential role for retinoic acid in the promotion of CD4(+) T cell effector responses via retinoic acid receptor alpha. Immunity 34, 435–447 (2011).
Article MathSciNet PubMed PubMed Central CAS Google Scholar
Liu, X., Ser, Z. & Locasale, J. W. Development and quantitative evaluation of a high-resolution metabolomics technology. Anal. Chem. 86, 2175–2184 (2014).
Article PubMed PubMed Central CAS Google Scholar

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Acknowledgements

We acknowledge Dr. Yongqiang Feng for critical reading of the manuscript, Dr. Alexander Rudensky for Foxp3^Cre mice, the St. Jude Immunology FACS core facility for cell sorting, and C. Cloer, M. Hendren, A. KC, B. Rhode, and S. Rankin for animal colony maintenance and technical assistance. This work was supported by The Hartwell Foundation Biomedical Research Fellowship (to N.M.C.) and by NIH AI105887, AI101407, CA176624, NS064599, and CA221290 (to H.C.).

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Department of Immunology, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, MS 351, Memphis, TN, 38105, USA
Nicole M. Chapman, Hu Zeng, Thanh-Long M. Nguyen, Yanyan Wang, Yogesh Dhungana & Hongbo Chi
Department of Pathology, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, MS 250, Memphis, TN, 38105, USA
Peter Vogel
Department of Pharmacology & Cancer Biology, Duke University School of Medicine, Levine Science Research Center C266, Box 3813, Durham, NC, 27710, USA
Xiaojing Liu & Jason W. Locasale
Hartwell Center for Bioinformatics and Biotechnology, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, MS 312, Memphis, TN, 38105, USA
Geoffrey Neale

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Nicole M. Chapman
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Hu Zeng
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Thanh-Long M. Nguyen
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Yanyan Wang
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Peter Vogel
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Yogesh Dhungana
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Xiaojing Liu
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Geoffrey Neale
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Hongbo Chi
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Contributions

N.M.C. designed, performed, and analyzed experiments and wrote the manuscript; H.Z., T.M.N. and Y.W. designed, performed, and analyzed experiments; P.V. performed immunohistochemistry analysis and provided histopathology scoring; X.L. and J.W.L. performed metabolomics analysis; Y.D. and G.N. performed bioinformatics analysis; H.C. designed experiments, edited the manuscript, and provided overall direction.

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Correspondence to Hongbo Chi.

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Chapman, N.M., Zeng, H., Nguyen, TL.M. et al. mTOR coordinates transcriptional programs and mitochondrial metabolism of activated T_reg subsets to protect tissue homeostasis. Nat Commun 9, 2095 (2018). https://doi.org/10.1038/s41467-018-04392-5

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Received: 10 September 2017
Accepted: 26 April 2018
Published: 29 May 2018
DOI: https://doi.org/10.1038/s41467-018-04392-5

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