Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

PARK7/DJ-1 promotes pyruvate dehydrogenase activity and maintains Treg homeostasis during ageing

Abstract

Pyruvate dehydrogenase (PDH) is the gatekeeper enzyme of the tricarboxylic acid (TCA) cycle. Here we show that the deglycase DJ-1 (encoded by PARK7, a key familial Parkinson’s disease gene) is a pacemaker regulating PDH activity in CD4+ regulatory T cells (Treg cells). DJ-1 binds to PDHE1-β (PDHB), inhibiting phosphorylation of PDHE1-α (PDHA), thus promoting PDH activity and oxidative phosphorylation (OXPHOS). Park7 (Dj-1) deletion impairs Treg survival starting in young mice and reduces Treg homeostatic proliferation and cellularity only in aged mice. This leads to increased severity in aged mice during the remission of experimental autoimmune encephalomyelitis (EAE). Dj-1 deletion also compromises differentiation of inducible Treg cells especially in aged mice, and the impairment occurs via regulation of PDHB. These findings provide unforeseen insight into the complicated regulatory machinery of the PDH complex. As Treg homeostasis is dysregulated in many complex diseases, the DJ-1–PDHB axis represents a potential target to maintain or re-establish Treg homeostasis.

Your institute does not have access to this article

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Fig. 1: Dj-1 deletion compromises Treg cellularity in aged mice.
Fig. 2: Dj-1 ablation compromises nTreg survival in young mice but does not affect thymic Treg development.
Fig. 3: Dj-1 deletion impairs Treg homeostatic proliferation and activation pathways in aged mice.
Fig. 4: DJ-1 promotes PDH activity selectively in human resting nTreg cells.
Fig. 5: Dj-1 deletion compromises PDH activity in murine resting nTreg cells.
Fig. 6: Dj-1 deletion impairs OXPHOS selectively in nTreg cells.
Fig. 7: Dj-1 deletion impairs iTreg differentiation.
Fig. 8: Dj-1 deletion inhibits iTreg differentiation via PDHB.

Data availability

The microarray data have been deposited in the NCBI Gene Expression Omnibus under the accession number GSE115269. The proteomic mass spectrometry data (https://doi.org/doi:10.25345/C5437F) of the co-IP analysis have been deposited in ProteomeXchange via MassIVE under the identifier PXD016610. Source data are provided with this paper.

References

  1. Smeitink, J., van den Heuvel, L. & DiMauro, S. The genetics and pathology of oxidative phosphorylation. Nat. Rev. Genet. 2, 342–352 (2001).

    CAS  Article  PubMed  Google Scholar 

  2. O’Neill, L. A., Kishton, R. J. & Rathmell, J. A guide to immunometabolism for immunologists. Nat. Rev. Immunol. 16, 553–565 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Abou-Sleiman, P. M., Muqit, M. M. & Wood, N. W. Expanding insights of mitochondrial dysfunction in Parkinson’s disease. Nat. Rev. Neurosci. 7, 207–219 (2006).

    CAS  Article  PubMed  Google Scholar 

  4. Mizuno, Y. et al. Deficiencies in complex I subunits of the respiratory chain in Parkinson’s disease. Biochem. Biophys. Res. Commun. 163, 1450–1455 (1989).

    CAS  Article  PubMed  Google Scholar 

  5. Schapira, A. H. et al. Mitochondrial complex I deficiency in Parkinson’s disease. J. Neurochem. 54, 823–827 (1990).

    CAS  Article  PubMed  Google Scholar 

  6. González-Rodríguez, P. et al. Disruption of mitochondrial complex I induces progressive parkinsonism. Nature 599, 650–656 (2021).

    Article  CAS  PubMed  Google Scholar 

  7. Bonifati, V. et al. Mutations in the DJ-1 gene associated with autosomal recessive early-onset parkinsonism. Science 299, 256–259 (2003).

    CAS  Article  PubMed  Google Scholar 

  8. Hayashi, T. et al. DJ-1 binds to mitochondrial complex I and maintains its activity. Biochem. Biophys. Res. Commun. 390, 667–672 (2009).

    CAS  Article  PubMed  Google Scholar 

  9. Irrcher, I. et al. Loss of the Parkinson’s disease-linked gene DJ-1 perturbs mitochondrial dynamics. Hum. Mol. Genet. 19, 3734–3746 (2010).

    CAS  Article  PubMed  Google Scholar 

  10. Krebiehl, G. et al. Reduced basal autophagy and impaired mitochondrial dynamics due to loss of Parkinson’s disease-associated protein DJ-1. PLoS ONE 5, e9367 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Hao, L. Y., Giasson, B. I. & Bonini, N. M. DJ-1 is critical for mitochondrial function and rescues PINK1 loss of function. Proc. Natl Acad. Sci. USA 107, 9747–9752 (2010).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  12. Burbulla, L. F. et al. Dopamine oxidation mediates mitochondrial and lysosomal dysfunction in Parkinson’s disease. Science 357, 1255–1261 (2017).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  13. Ariga, H. et al. Neuroprotective function of DJ-1 in Parkinson’s disease. Oxid. Med. Cell. Longev. 2013, 683920 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Pisetsky, D. S. The role of mitochondria in immune-mediated disease: the dangers of a split personality. Arthritis Res. Ther. 18, 169 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Mosley, R. L., Hutter-Saunders, J. A., Stone, D. K. & Gendelman, H. E. Inflammation and adaptive immunity in Parkinson’s disease. Cold Spring Harb. Perspect. Med. 2, a009381 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Waak, J. et al. Regulation of astrocyte inflammatory responses by the Parkinson’s disease-associated gene DJ-1. FASEB J. 23, 2478–2489 (2009).

    CAS  Article  PubMed  Google Scholar 

  17. Kim, J. H. et al. DJ-1 facilitates the interaction between STAT1 and its phosphatase, SHP-1, in brain microglia and astrocytes: a novel anti-inflammatory function of DJ-1. Neurobiol. Dis. 60, 1–10 (2013).

    CAS  Article  PubMed  Google Scholar 

  18. Amatullah, H. et al. DJ-1/PARK7 impairs bacterial clearance in sepsis. Am. J. Respir. Crit. Care Med. 195, 889–905 (2017).

    CAS  Article  PubMed  Google Scholar 

  19. Liu, W. et al. Park7 interacts with p47phox to direct NADPH oxidase-dependent ROS production and protect against sepsis. Cell Res. 25, 691–706 (2015).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  20. Singh, Y. et al. Differential effect of DJ-1/PARK7 on development of natural and induced regulatory T cells. Sci. Rep. 5, 17723 (2015).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  21. Sakaguchi, S., Miyara, M., Costantino, C. M. & Hafler, D. A. FOXP3+ regulatory T cells in the human immune system. Nat. Rev. Immunol. 10, 490–500 (2010).

    CAS  Article  PubMed  Google Scholar 

  22. Reeve, A., Simcox, E. & Turnbull, D. Ageing and Parkinson’s disease: why is advancing age the biggest risk factor? Ageing Res. Rev. 14, 19–30 (2014).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  23. He, F. et al. PLAU inferred from a correlation network is critical for suppressor function of regulatory T cells. Mol. Syst. Biol. 8, 624 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Bras, J., Guerreiro, R. & Hardy, J. SnapShot: genetics of Parkinson’s disease. Cell 160, 570 (2015).

    CAS  Article  PubMed  Google Scholar 

  25. Gillis, J. & Pavlidis, P. The role of indirect connections in gene networks in predicting function. Bioinformatics 27, 1860–1866 (2011).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  26. Pham, T. T. et al. DJ-1-deficient mice show less TH-positive neurons in the ventral tegmental area and exhibit non-motoric behavioural impairments. Genes Brain Behav. 9, 305–317 (2010).

    CAS  Article  PubMed  Google Scholar 

  27. Jagger, A., Shimojima, Y., Goronzy, J. J. & Weyand, C. M. Regulatory T cells and the immune aging process: a mini-review. Gerontology 60, 130–137 (2014).

    CAS  Article  PubMed  Google Scholar 

  28. Zeng, N. et al. DJ-1 depletion prevents immunoaging in T-cell compartments. EMBO Rep. 23, e53302 (2022).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  29. Kohm, A. P., Carpentier, P. A., Anger, H. A. & Miller, S. D. Cutting edge: CD4+CD25+ regulatory T cells suppress antigen-specific autoreactive immune responses and central nervous system inflammation during active experimental autoimmune encephalomyelitis. J. Immunol. 169, 4712–4716 (2002).

    CAS  Article  PubMed  Google Scholar 

  30. Mak, T. W. et al. Glutathione primes T cell metabolism for inflammation. Immunity 46, 675–689 (2017).

    CAS  Article  PubMed  Google Scholar 

  31. Gray, D. H. et al. Developmental kinetics, turnover, and stimulatory capacity of thymic epithelial cells. Blood 108, 3777–3785 (2006).

    CAS  Article  PubMed  Google Scholar 

  32. Zemmour, D. et al. Single-cell gene expression reveals a landscape of regulatory T cell phenotypes shaped by the TCR. Nat. Immunol. 19, 291–301 (2018).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  33. Xu, J. et al. The Parkinson’s disease-associated DJ-1 protein is a transcriptional co-activator that protects against neuronal apoptosis. Hum. Mol. Genet. 14, 1231–1241 (2005).

    CAS  Article  PubMed  Google Scholar 

  34. Holling, T. M., Schooten, E. & van Den Elsen, P. J. Function and regulation of MHC class II molecules in T-lymphocytes: of mice and men. Hum. Immunol. 65, 282–290 (2004).

    CAS  Article  PubMed  Google Scholar 

  35. van der Brug, M. P. et al. RNA binding activity of the recessive parkinsonism protein DJ-1 supports involvement in multiple cellular pathways. Proc. Natl Acad. Sci. USA 105, 10244–10249 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Weyand, C. M., Goronzy, J. & Fathman, C. G. Modulation of CD4 by antigenic activation. J. Immunol. 138, 1351–1354 (1987).

    CAS  PubMed  Google Scholar 

  37. Vandenbon, A. et al. Immuno-Navigator, a batch-corrected coexpression database, reveals cell type-specific gene networks in the immune system. Proc. Natl Acad. Sci. USA 113, E2393–E2402 (2016).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  38. Patel, M. S. & Roche, T. E. Molecular biology and biochemistry of pyruvate dehydrogenase complexes. FASEB J. 4, 3224–3233 (1990).

    CAS  Article  PubMed  Google Scholar 

  39. Desdin-Mico, G. et al. T cells with dysfunctional mitochondria induce multimorbidity and premature senescence. Science 368, 1371–1376 (2020).

    CAS  Article  PubMed  Google Scholar 

  40. Wang, R. & Green, D. R. Metabolic checkpoints in activated T cells. Nat. Immunol. 13, 907–915 (2012).

    Google Scholar 

  41. Zhou, Z. H., McCarthy, D. B., O’Connor, C. M., Reed, L. J. & Stoops, J. K. The remarkable structural and functional organization of the eukaryotic pyruvate dehydrogenase complexes. Proc. Natl Acad. Sci. USA 98, 14802–14807 (2001).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  42. Zachar, Z. et al. Non-redox-active lipoate derivates disrupt cancer cell mitochondrial metabolism and are potent anticancer agents in vivo. J. Mol. Med. 89, 1137–1148 (2011).

    CAS  Article  PubMed  Google Scholar 

  43. Polansky, J. K. et al. DNA methylation controls Foxp3 gene expression. Eur. J. Immunol. 38, 1654–1663 (2008).

    CAS  Article  PubMed  Google Scholar 

  44. Benayoun, B. A., Pollina, E. A. & Brunet, A. Epigenetic regulation of ageing: linking environmental inputs to genomic stability. Nat. Rev. Mol. Cell Biol. 16, 593–610 (2015).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  45. 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 

  46. Richard, A. J., Hang, H. & Stephens, J. M. Pyruvate dehydrogenase complex (PDC) subunits moonlight as interaction partners of phosphorylated STAT5 in adipocytes and adipose tissue. J. Biol. Chem. 292, 19733–19742 (2017).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  47. Patel, K. P., O’Brien, T. W., Subramony, S. H., Shuster, J. & Stacpoole, P. W. The spectrum of pyruvate dehydrogenase complex deficiency: clinical, biochemical and genetic features in 371 patients. Mol. Genet. Metab. 106, 385–394 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  48. Olahova, M. et al. Biallelic mutations in ATP5F1D, which encodes a subunit of ATP synthase, cause a metabolic disorder. Am. J. Hum. Genet. 102, 494–504 (2018).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  49. Probst-Kepper, M. et al. GARP: a key receptor controlling FOXP3 in human regulatory T cells. J. Cell. Mol. Med. 13, 3343–3357 (2009).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  50. Tyanova, S. et al. The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat. Methods 13, 731–740 (2016).

    CAS  Article  PubMed  Google Scholar 

Download references

Acknowledgements

This work was supported by the Luxembourg National Research Fund (FNR) CORE programme (CORE/14/BM/8231540/GeDES), the Luxembourg–RIKEN bilateral programme ‘TregBar’, ‘NEXTIMMUNE’ (PRIDE/11012546) and ‘CRiTiCS’ DTU (to F.Q.H.); individual Aide à la Formation Recherche grants to E.D. (PHD-2014-1/7603621) and N.Z. (PHD-2015-1/9989160); and other PhD position grants to C.M.C. (PRIDE/2015/10907093) and D.G.F. (through the Luxembourg–RIKEN bilateral programme (2015/11228353, ‘TregBar’)) through the group of F.Q.H. The work was also supported by the DFG (grant WU 164/5-1) to W.W. and by the German Federal Ministry of Education and Research (BMBF) through the Integrated Network MitoPD (grant 031A430E to W.W. and D.M.V.W.). J.M. is supported by FNR ATTRACT (A18/BM/11809970). D.B. is supported by FNR ATTRACT (A14/BM/7632103) and FNR CORE grants (C21/BM/15796788 and C18/BM/12691266). R.K. is supported by the FNR NCER-PD and PEARL programme (FNR/P13/6682797). We also thank the Luxembourg Centre for Systems Biomedicine Metabolomics Platform for providing technical and analytical support and acknowledge the EMBL Genomics Core Facility (Heidelberg, V. Benes) for their microarray analysis. We thank A. Daujeumont, N. Ouzren, T. Li, O. Boyd, N. Bonjean, C. Davril, S. Köglsberger, J. Walter, X. Dong, S. Badeke and F. Fack for their expert technical support. We acknowledge M.P. Dufresne (Liege, Belgium) for allowing us to access their irradiator and N. Malvaus from the Luxembourg Red Cross for providing buffy coats and leukopaks.

Author information

Authors and Affiliations

Authors

Contributions

E.D. and N.Z. designed and performed major parts of the human- and mouse-related experiments, respectively. N.Z. analysed mouse-related data. C.M.C. performed and analysed human-, patient- and mouse-related experiments. N.P. and C.L.L. performed and analysed metabolome-related experiments. J.M. and M.B. performed and supervised 13C tracing experiments and data analysis. D.G.F. and S.D. performed parts of primary human T cell-related experiments. G.G.G. and J.C.S. contributed to Seahorse assays. M.P.M. and J.D.T. contributed to epigenetic analysis. M.A.G. and J.R. performed and analysed proteomic experiments. H.K., M.G. and D.B. performed EAE-related experiments. C.G. supervised FCM-related experiments. A.B., S.F., O.D., D.C. and C.L. performed and/or supervised parts of mouse-related experiments. D.M.V.W. performed part of the EAE experiments. W.W., R.K., R.B. and M.O. provided insights and supervised parts of the experiments. R.B. and M.O. revised the manuscript. F.Q.H. conceived and directed the project and wrote the manuscript.

Corresponding author

Correspondence to Feng Q. Hefeng.

Ethics declarations

Competing interests

F.Q.H., R.B. and E.D. once filed a patent on some of the related data.

Peer review

Peer review information

Nature Metabolism thanks Ulf Beier, Alexander Eggel and the other, anonymous, reviewers for their contribution to the peer review of this work. Primary handling editors: Alfredo Gimenez-Cassina and George Caputa, in collaboration with the Nature Metabolism team.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 DJ-1 is highly expressed in human Tregs and connected with well-known Treg genes in Treg specific-correlation network.

a, Mean transcription expression of the known PD genes measured in the first 6hrs of anti-CD3-/-CD28/IL-2 stimulation assessed by our published high-time-resolution (an interval of 20min) time-series transcriptome (with 19 time points)23. Treg1 and Treg2 (or Teff1 and Teff2) represent two independently repeated HTR time-series experiments for Tregs (or Teffs). DJ-1 is highlighted by red rectangle. b, PARK7/DJ-1 subnetwork extracted from the constructed human Treg-specific correlation network. Each oval represents one gene. A selection of known key Treg genes were highlighted in red. Each line between DJ-1 and the other genes represents a correlation-based functional linkage.

Extended Data Fig. 2 Characterization of highly purified human nTregs.

a, Characterization of highly purified human nTregs (CD4+CD25highCD127low). Representative FCM plots of FOXP3, CD127, Helios, and CD25 on human Tregs relative Teffs (all the markers were not stained in the same panel). ‘TregThu’ is a golden standard of isolated human Tregs50. The protein expression of LRRC32 (GARP) was measured after 3-day stimulation by irradiated EBV-transformed B cells. b, Representative ImageStream plot of GZMB expression in unstimulated Tregs or Teffs. c, Representative In-vitro proliferation assay of human Teffs suppressed by human Tregs at different ratios, in co-culture with irradiated EBV-B cells for 5 days. Only living CD4 T cells were gated for analysis. Results represent 7-10 (a-c) independent experiments (from different heathy donors).

Extended Data Fig. 3 Dj-1 deletion does not compromise suppressor function of individual Tregs.

a, b, In-vitro suppression assay of Dj-1-/- or Dj-1+/+ Tregs isolated from aged (a) or young (b) mice in co-culture with Tconv and irradiated feeder cells in the presence of anti-CD3 for 3.5 days. Percentages of dividing cells from the total population (the total population indicates the gated DAPI-negative and CD4+, CFSE-labelled Tconv) are presented on the plots. c, Frequency of CTLA4-expressing cells among CD4+FOXP3+ Treg cells (left) and Geometric mean (Geo mean, MFI) of CTLA4 among CD4+FOXP3+ Tregs from spleen (Sp) and lymph nodes (LN) from Dj-1-/- and Dj-1+/+ WT littermates [for the frequency, n=that in d and e; for CTLA4 MFI measurement in aged mice (aged KO, n=3; WT, n=5 sp; KO, n=3 LN; WT, n=4 LN; of note, for comparability, the CTLA4 MFI results were not pooled from different batches; for CTLA4 MFI measurement in young mice, n=that in d and e]. *P=0.0500. d, e, Geometric mean (MFI) of FOXP3 (d) or CD25 (e) expression among CD4+FOXP3+ Tregs. Young or aged murine results are marked in each panel (young KO, n=5; young WT, n=5; aged KO, n=8; aged WT, n=6; aged data pooled from 2 independent experiments). **P=0.00581 (d); **P=0.00654 and **P=0.00946 (e). Results represent three (a, b) and four (c, d, e) independent experiments. Data are mean ± s.d. P values are determined by two-tailed Student’s t-test. ns, not significant, *P<=0.05, **P<=0.01 and ***P<=0.001.

Source data

Extended Data Fig. 4 BM models show that Treg cellularity is also regulated in a hematopoietic-extrinsic and host micro-environmental aging-dependent manner.

a, Gating strategy used to identify FOXP3+ cells among CD4 T cells developed from CD45.1 Dj-1 WT- and CD45.2 Dj-1 KO-origin cells in bone marrow (BM) chimeras. b, Percentages of FOXP3+ cells among living CD4+ cells originated from CD45.1 or CD45.2 BM cells transplanted from young donors (left panel, n=5). Representative histogram overlay of FOXP3 expression among living CD4 T cells derived from CD45.2 Dj-1 KO or CD45.1 Dj-1 WT BM cells (right panel). **P=0.00131. c, Percentages of FOXP3+ cells among living CD4+ cells originated from CD45.1 Dj-1 WT or CD45.2 Dj-1 KO BM cells transplanted from aged donors and reconstituted in young Dj-1 KO (n=4) or WT recipients (n=5). **P=0.00113 and ***P=0.000106. Results represent two (b, c) independent experiments. Data are mean ± s.d. P values are determined by paired two-tailed Student’s t-test. ns, not significant, *P<=0.05, **P<=0.01 and ***P<=0.001.

Source data

Extended Data Fig. 5 Treg-specific correlation between Dj-1 and Pdhb.

a, mRNA expression of Park7/Dj-1 is highly correlated with Pdhb only in murine Tregs but not in other analyzed CD4 T-cell subsets. 1416526_a_at and 1416090_at are the probeset IDs measuring Park7 and Pdhb in Affymetric microarrays, respectively. The number (n) of microarray samples used for correlation analysis is 240, 51, 35 and 47 from CD4 Tregs, Th1, Th2 and Tmem (memory CD4 T cells), respectively. The R value corresponds to Pearson correlation coefficient and the associated P-value is from two-tailed test (Prism). Ns, non-significant and otherwise, P value is provided for the corresponding cell type. For the details, refer to the database (from Sakaguchi’s lab): https://sysimm.ifrec.osaka-u.ac.jp/immuno-navigator/?o=10090&probe1=1416526_a_at&probe2=1416090_at&cell=5.

Source data

Extended Data Fig. 6 Expression analysis of the genes encoding PDH complex and the PDH regulatory machinery in nTregs of aged mice.

a, mRNA expression of the genes (Pdks) encoding PDH kinases and the genes (Pdps) encoding pyruvate dehydrogenase phosphatases in Tregs freshly isolated from aged Dj-1 KO and age- and gender-matched WT littermates (n=3/group). **P=0.00420, *P=0.0348, and *P=0.0362. b, mRNA expression of the genes encoding several PDH complex subunits in Tregs freshly isolated from aged Dj-1 KO and WT littermates. Results are the summary of the microarray datasets (from 3 mice each group). Data are mean± s.d. P values are determined by two-tailed Student’s t-test. ns or unlabeled, not significant, *P<=0.05, **P<=0.01 and ***P<=0.001.

Source data

Extended Data Fig. 7 PDH inhibition compromises nTreg proliferation but not lineage stability.

a, b, c, Cell proliferation [as labelled by CTV] (a), cell survival as measured by live/dead staining among CD4+ cells (b) or histogram overlay of FOXP3 expression (c) in isolated nTregs stimulated for three days treated with the indicated concentration of a PDH inhibitor (CPI-613) or control vehicle or without stimulation (gray). Results represent at least three independent experiments.

Extended Data Fig. 8 Age-dependent loss of methylation in Foxp3 TSDR in naïve CD4 cells.

a, upper panel: Methylation analysis of isolated naïve CD4+ T cells (CD4 Tn) from DJ-1 KO or WT mice for Foxp3 TSDR (Regulatory T-Cell-Specific Demethylated Region). Individual values for CpG positions 6-12 are shown as individual data points. lower panel: Heatmap displays mean methylation per CpG position in 5% intervals. **P=0.0095 and ***P=3.2E-05. b, upper panel: Methylation analysis of isolated CD4 Tn from DJ-1 KO or WT mice for the Foxp3 promoter region. Individual values for CpG positions 1-5 are shown as individual data points. Lower panel: Heatmap displays mean methylation per CpG position in 10% intervals. Results represent 2-4 independent experiments (young KO n= 7; young WT n= 7; aged KO n= 2; aged WT n= 4; all males). Boxplots show 25th and 75th percentiles around the median. Whiskers correspond to 1.5× IQR (interquantile range). Horizontal bars show Holm-adjusted P values after two-sided Wilcox test. Of note, since Foxp3 is an X-linked gene, to avoid observing x-inactivation-related methylation alteration, we focused on males here.

Source data

Extended Data Fig. 9 PDH inhibition also compromises iTreg differentiation in naïve CD4 T cells isolated from aged mice.

a, Representative FCM plots of FOXP3 expression among living CD4 T cells differentiated from naïve CD4 T cells (CD4 Tn) treated with different doses of CPI-613 or control vehicle without (upper panel) or with 10U/ml of recombinant IL-2 (lower panel). The CD4 Tn were isolated from very old DJ-1 WT mice (~105-wk-old). b, Percentages of FOXP3+ cells (left panel) or Ki67+ cells (right panel) among living CD4 T cells following iTreg differentiation with different doses of CPI-613 or control vehicles with or without exogenous IL-2 for three days (n=3 mice). Middle panel, Percentages of living cells among total CD4 T cells following iTreg differentiation. Of note, a PE instead of APC fluorochrome (the latter was used in other experiments) was used to analyze FOXP3 expression in the experiments of this figure. *P=0.0387, **P=0.00157 and ***P=0.000845 (left panel); *P=0.0206, *P=0.0130 and **P=0.00130 (middle panel); *P=0.0183 and **P=0.00312 (right panel). Results represent two (a, b) independent experiments. Data are mean ± s.d. P values are determined by two-tailed Student’s t-test. ns, not significant, *P<=0.05, **P<=0.01 and ***P<=0.001.

Source data

Supplementary information

Supplementary Information

Supplementary Tables 1–6 and Fig. 1

Reporting Summary

Source data

Source Data Fig. 1

Statistical source data for Fig. 1.

Source Data Fig. 2

Statistical source data for Fig. 2.

Source Data Fig. 3

Statistical source data for Fig. 3.

Source Data Fig. 4

Statistical source data for Fig. 4.

Source Data Fig. 4

Unprocessed western blots for Fig. 4a,i,j.

Source Data Fig. 5

Statistical source data for Fig. 5.

Source Data Fig. 5

Unprocessed western blots for Fig. 5a–e.

Source Data Fig. 6

Statistical source data for Fig. 6.

Source Data Fig. 7

Statistical source data for Fig. 7.

Source Data Fig. 8

Statistical source data for Fig. 8.

Source Data Extended Data Fig. 3

Statistical source data for Extended Data Fig. 3.

Source Data Extended Data Fig. 4

Statistical source data for Extended Data Fig. 4.

Source Data Extended Data Fig. 5

Statistical source data for Extended Data Fig. 5.

Source Data Extended Data Fig. 6

Statistical source data for Extended Data Fig. 6.

Source Data Extended Data Fig. 8

Statistical source data for Extended Data Fig. 8.

Source Data Extended Data Fig. 9

Statistical source data for Extended Data Fig. 9.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Danileviciute, E., Zeng, N., Capelle, C.M. et al. PARK7/DJ-1 promotes pyruvate dehydrogenase activity and maintains Treg homeostasis during ageing. Nat Metab 4, 589–607 (2022). https://doi.org/10.1038/s42255-022-00576-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s42255-022-00576-y

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing