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Foxp3 and Toll-like receptor signaling balance Treg cell anabolic metabolism for suppression

Nature Immunology volume 17, pages 1459–1466 (2016)Cite this article

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Abstract

CD4+ effector T cells (Teff cells) and regulatory T cells (Treg cells) undergo metabolic reprogramming to support proliferation and immunological function. Although signaling via the lipid kinase PI(3)K (phosphatidylinositol-3-OH kinase), the serine-threonine kinase Akt and the metabolic checkpoint kinase complex mTORC1 induces both expression of the glucose transporter Glut1 and aerobic glycolysis for Teff cell proliferation and inflammatory function, the mechanisms that regulate Treg cell metabolism and function remain unclear. We found that Toll-like receptor (TLR) signals that promote Treg cell proliferation increased PI(3)K-Akt-mTORC1 signaling, glycolysis and expression of Glut1. However, TLR-induced mTORC1 signaling also impaired Treg cell suppressive capacity. Conversely, the transcription factor Foxp3 opposed PI(3)K-Akt-mTORC1 signaling to diminish glycolysis and anabolic metabolism while increasing oxidative and catabolic metabolism. Notably, Glut1 expression was sufficient to increase the number of Treg cells, but it reduced their suppressive capacity and Foxp3 expression. Thus, inflammatory signals and Foxp3 balance mTORC1 signaling and glucose metabolism to control the proliferation and suppressive function of Treg cells.

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Figure 1: Treg cell proliferation is associated with increased glycolysis and anabolic signaling.
Figure 2: Signaling via TLR1 and TLR2 drives Treg cell glycolysis and proliferation, yet reduces suppressive capacity.
Figure 3: Foxp3 reduces aerobic glycolysis and promotes mitochondrial oxidative metabolism.
Figure 4: Foxp3 expression is sufficient to suppress glycolysis and promote oxidative metabolism.
Figure 5: Glut1 expression increases the number and size of Treg cells but reduces their suppressive capacity.
Figure 6: Increased glucose uptake impairs the suppressive ability of Treg cells.

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Acknowledgements

We thank members of the Rathmell and Wells laboratories for discussions, and the Immunological Genome Project. Supported by the Crohn's and Colitis Foundation of America (Senior Research Grant to J.C.R.), the Alliance for Lupus Research (J.C.R.), the US National Institutes of Health (R01HL 108006 and R01105550DK to J.C.R.; P01HL018646 to L.A.T. and J.C.R.; F31CA183529 to R.J.K.; R00CA168997 to J.W.L.; and R01AI070807 and P01AI073489 to A.D.W.), and the German Research Foundation (Deutsche Forschungsgemeinschaft; P.J.S.).

Author information

Author notes

  1. Valerie A Gerriets and Rigel J Kishton: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Pharmacology and Cancer Biology, Duke University, Durham, North Carolina, USA

    Valerie A Gerriets, Rigel J Kishton, Marc O Johnson, Sivan Cohen, Amanda G Nichols & Jason W Locasale

  2. Department of Pathology, Microbiology, and Immunology, Vanderbilt Center for Immunobiology, Vanderbilt University, Nashville, Tennessee, USA

    Marc O Johnson, Peter J Siska & Jeffrey C Rathmell

  3. Department of Toxicology and Cancer Biology and Markey Cancer Center, Center for Environmental and Systems Biochemistry, University of Kentucky, Lexington, Kentucky, USA

    Marc O Warmoes

  4. Department of Medicine, Division of Hematology and Oncology, Vanderbilt University Medical Center, Nashville, Tennessee, USA

    Aguirre A de Cubas

  5. Division of Pediatric Endocrinology and Diabetes, Duke University, Durham, North Carolina, USA

    Nancie J MacIver

  6. Massachusetts General Hospital, Center for Transplantation Sciences, Boston, Massachusetts, USA

    Laurence A Turka

  7. Department of Pathology and Laboratory Medicine, The Children's Hospital of Philadelphia and the Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA

    Andrew D Wells

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Contributions

V.A.G., R.J.K., A.D.W. and J.C.R. designed the study, interpreted data and wrote the manuscript. V.A.G. and R.J.K. performed most of the experiments. M.O.J., S.C. and P.J.S. performed experiments to analyze Foxp3 regulation of metabolism. A.G.N. assisted V.A.G. and R.J.K. and maintained animals that were essential for the study. M.O.W. performed mass spectrometry. A.A.d.C. analyzed RNAseq data. J.W.L. assisted in metabolomics analysis. N.J.M. and L.A.T. assisted with data analysis and interpretation. A.D.W. performed microarray analysis.

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Correspondence to Jeffrey C Rathmell.

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Integrated supplementary information

Supplementary Figure 1 Treg cell metabolism is regulated by Foxp3 and inflammatory signals.

(a) CD4+Foxp3+ T cells and CD4+Foxp3- T cells were analyzed by flow cytometry for Ki67 expression levels. (b-c) CD4+CD25- T cells were isolated from the spleens of WT mice, polarized under Treg skewing conditions for 5 days and treated with vehicle (H2O) or 5 μg/mL Pam3CSK4 for the final 24 hrs. Cells were re-isolated by magnetic separation and analyzed for (b) forward scatter (FSC) and (c) glycolytic capacity using the Seahorse Extracellular Flux Analyzer. (d) Gene ontology analysis using PANTHER of pathways altered by Foxp3 deletion using gene expression data published by Williams and Rudensky (Nat. Immunol 8:277). (e-f) Primary murine CD4+CD25- T cells were activated and transduced with control or Foxp3 expressing retrovirus and (e) analyzed by chromatin immunoprecipitation-sequencing showing Foxp3 associated sites in the pyruvate dehydrogenase kinase 3 (PDK3) and PIK3cg loci or (f) analyzed by QPCR for expression of PDK3 mRNA. Data are representative of biological triplicate experiments (a-b, e-f), two independent experiments (c), or an analysis of previously published datasets with biological duplicates (d). Means and standard deviations are shown, * p<0.05.

Supplementary Figure 2 Foxp3 expression in non–T cell lineage inhibits anabolic growth signaling and gene expression.

a-e. Three individual clones of control and Foxp3-ER expressing FL5.12 cells were treated with 4OHT to activate Foxp3 and examined for (a-b) the expression of metabolic and related proteins, (c) select glycolytic gene expression by QPCR or (d-e) were extracted and analyzed using high-resolution LC-QE-MS. (d) A heat map with relative levels of metabolites using unsupervised hierarchical clustering or (e) select metabolite levels are shown. Data are representative of three independent experiments (a-b) or an analysis of three independent clones (c-e). (a-b) Gel bands are quantified, * p<0.05, **p<0.005.

Supplementary Figure 3 Constitutive Akt expression increases the number and frequency of Treg cells but diminishes suppressive function.

a-b. CD4+CD25- T cells were isolated from the spleens of control and mAkt-Tg mice and polarized under Treg skewing conditions. Cells were examined for (a) glucose uptake and (b) ROS levels as measured by DCFDA. c-i. Foxp3+ tTreg from the spleen of control and mAkt-Tg mice were examined for (c) tTreg number, (d) percentage and (e) cell size determined by forward scatter and were measured by flow cytometry. (f) CD25, (g) ICOS, (h) CD69 and (i) CD62L protein expression in CD4+Foxp3+ control and mAkt-Tg cells were measured by flow cytometry. (j) CD4+CD25- T cells were isolated from the spleens of control and mAkt-Tg mice and were polarized under Treg skewing conditions to measure inhibition of effector T cell (Teff) proliferation in an in vitro suppression assay. Data are representative of two independent experiments (a, b), three independent experiments (c, d, f-i), four independent experiments (e), or two experiments (f, j). Means and standard deviations are shown, * p<0.05.

Supplementary Figure 4 Transgenic expression of Glut1 results in altered metabolic and immune phenotypes in Treg cells.

a-d. CD4+CD25- T cells were isolated from the spleens of control and Glut1-Tg mice and polarized under Treg skewing conditions. Cells were examined for (a) Glut1 expression levels by immunoblot, (b) glucose uptake, (c) ROS production as measured by DCFDA and (d) ECAR and OCR levels were measured using the Seahorse Extracellular Flux Analyzer before and after the addition of the specified inhibitors. e-f. CD4+Foxp3+ T cells from the spleens of control and Glut1-Tg mice were examined for expression of (e) CD25 and (f) Helios proteins. Data are representative of three independent experiments (a-b, d, e) or compiled data from three independent experiments (c, f). Means and standard deviations are shown, * p<0.05.

Supplementary Figure 5 Transgenic Glut1 expression alters the immunological phenotype of Treg cells.

a-f. CD4+CD25- T cells were isolated from the spleens of control and Glut1-Tg mice and polarized under Treg skewing conditions. Skewed cells were analyzed for (a) Foxp3 expression by flow cytometry, (b) cell size by FSC analysis, (c) CD25 and (d) ICOS protein expression by flow cytometry. (e) RNA expression levels of a panel of immunosuppressive related genes by QPCR and (f) percentage of IFNγ and IL-2 producing CD4+Foxp3+ cells by flow cytometry are shown. Data are representative of three independent experiments (a-d) or the average of six biological replicates (e) or four biological replicates (f). Means and standard deviations are shown, * p<0.05.

Supplementary Figure 6 Transgenic expression of Glut1 diminishes the suppressive ability of Treg cells in vitro and in vivo.

a. CD4+CD25- T cells were isolated from the spleens of control and Glut1-Tg mice and polarized under Treg skewing conditions. Control and Glut1-Tg Treg were functionally examined in an in vitro suppression assay to measure inhibition of effector T cells (Teff) proliferation and the Teff division index was calculated by Flowjo flow cytometry analysis software. b-d. RAG1-/- mice were injected with naïve effector (CD4+CD25-CD45RBhi) T cells to induce colitis. After weight loss indicated active disease was apparent, control or Glut1-Tg CD4+CD25+CD45RBlo Treg were sorted and analyzed by flow cytometry to assess sorted Treg. (b) The expression of CD25 and CD45Rb and (c) Foxp3 protein of sorted rescue Treg are shown. (d) At the termination of the experiment Foxp3 levels were assessed on CD4+ gated T cells in the spleens of recipient animals. (e) Thy1.1 naïve effector (CD4+CD25-CD45RBhi) T cells were adoptively transferred into RAG1-/- mice to initiate IBD. Thy1.2 control or Glut1-tg tTreg (CD4+CD25+CD45RBlo) T cells were sorted and injected after disease was apparent Foxp3 levels were then assessed by flow cytometry on adoptively transferred Thy1.1 effectors and Thy1.2 CD4 control and Glut1-tg Treg from mesenteric lymph nodes and spleens. Data are the result of three independent experiments (a), representative of three independent experiments (b) or is representative of two independent experiments with at least 5 mice per group (c, d). Means and standard deviations are shown, * p<0.05. (f) Model of our findings. Our findings show that Treg are metabolically heterogeneous and depend on activating and inflammatory signals as well as Foxp3 itself to coordinate metabolism. In the presence of inflammatory stimuli, such as TLR ligands, Treg increase mTORC1 signaling, Glut1, and glycolysis, which results in increased cell growth and proliferation. Suppressive capacity, however, can be impaired. As inflammatory signals are reduced, Foxp3 can tilt the balance away from mTORC1 signaling to favor oxidative metabolism that lowers proliferative ability but enhances suppression to promote inflammatory resolution. Metabolic transitions are critical in this process as increased Glut1 expression is sufficient to promote Treg growth while reducing suppression and stability.

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Gerriets, V., Kishton, R., Johnson, M. et al. Foxp3 and Toll-like receptor signaling balance Treg cell anabolic metabolism for suppression. Nat Immunol 17, 1459–1466 (2016). https://doi.org/10.1038/ni.3577

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