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Lactate limits CNS autoimmunity by stabilizing HIF-1α in dendritic cells

Nature volume 620, pages 881–889 (2023)Cite this article

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Abstract

Dendritic cells (DCs) have a role in the development and activation of self-reactive pathogenic T cells1,2. Genetic variants that are associated with the function of DCs have been linked to autoimmune disorders3,4, and DCs are therefore attractive therapeutic targets for such diseases. However, developing DC-targeted therapies for autoimmunity requires identification of the mechanisms that regulate DC function. Here, using single-cell and bulk transcriptional and metabolic analyses in combination with cell-specific gene perturbation studies, we identify a regulatory loop of negative feedback that operates in DCs to limit immunopathology. Specifically, we find that lactate, produced by activated DCs and other immune cells, boosts the expression of NDUFA4L2 through a mechanism mediated by hypoxia-inducible factor 1α (HIF-1α). NDUFA4L2 limits the production of mitochondrial reactive oxygen species that activate XBP1-driven transcriptional modules in DCs that are involved in the control of pathogenic autoimmune T cells. We also engineer a probiotic that produces lactate and suppresses T cell autoimmunity through the activation of HIF-1α–NDUFA4L2 signalling in DCs. In summary, we identify an immunometabolic pathway that regulates DC function, and develop a synthetic probiotic for its therapeutic activation.

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Fig. 1: Activation of HIF-1α by lactate inhibits the pro-inflammatory activities of DCs.
Fig. 2: HIF-1α-induced NDUFA4L2 limits the production of mtROS.
Fig. 3: L-LA limits the mtROS-driven activation of XBP1 in DCs.
Fig. 4: Activating HIF-1α–NDUFA4L2 with engineered probiotics ameliorates EAE.

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Data availability

All raw and processed deep -sequencing data have been deposited at the Gene Expression Omnibus (GEO) with accession code GSE188504.

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Acknowledgements

This work was supported by grants NS102807, ES02530, ES029136 and AI126880 from the National Institutes of Health (NIH); RG4111A1 and JF2161-A-5 from the National Multiple Sclerosis Society; RSG-14-198-01-LIB from the American Cancer Society; and PA-160408459 from the International Progressive MS Alliance (to F.J.Q.). C.M.P. was supported by a fellowship from FAPESP BEPE (2019/13731-0) and by the Herbert R. & Jeanne C. Mayer Foundation; G.F.L. received support from a grant from the Swedish Research Council (2021-06735); C.G.-V. was supported by an Alfonso Martin Escudero Foundation postdoctoral fellowship and by a postdoctoral fellowship (ALTF 610-2017) from the European Molecular Biology Organization; C.-C.C. received support from a postdoctoral research abroad program (104-2917-I-564-024) from the Ministry of Science and Technology, Taiwan; C.M.R.-G. was supported by a predoctoral F.P.U. fellowship from the Ministry of Economy and Competitiveness and by the European Union FEDERER program; M.A.W. was supported by NIH (1K99NS114111, F32NS101790 and T32CA207201), the Program in Interdisciplinary Neuroscience and the Women’s Brain Initiative at Brigham and Women’s Hospital; T.I. was supported by an EMBO postdoctoral fellowship (ALTF: 1009–2021) and H.-G.L. was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2021R1A6A3A14039088). We thank L. Glimcher and J. R. Cubillos Ruiz for sharing ItgaxCreXbp1flox mice; S. McSorley for providing the S. typhimurium strain; H. Xu and M. Lehtinen for providing training on CSF extraction; all members of the F.J.Q. laboratory for advice and discussions; R. Krishnan for technical assistance with flow cytometry studies; and the NeuroTechnology Studio at Brigham and Women’s Hospital for providing access to Seahorse instruments.

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Authors and Affiliations

  1. Ann Romney Center for Neurologic Diseases, Harvard Medical School, Brigham and Women’s Hospital, Boston, MA, USA

    Liliana M. Sanmarco, Joseph M. Rone, Carolina M. Polonio, Gonzalo Fernandez Lahore, Federico Giovannoni, Kylynne Ferrara, Cristina Gutierrez-Vazquez, Agustin Plasencia, Camilo Faust Akl, Payal Nanda, Evelin S. Heck, Zhaorong Li, Hong-Gyun Lee, Chun-Cheih Chao, Claudia M. Rejano-Gordillo, Pedro H. Fonseca-Castro, Tomer Illouz, Mathias Linnerbauer, Jessica E. Kenison, Rocky M. Barilla, Daniel Farrenkopf, Nikolas A. Stevens, Gavin Piester, Elizabeth N. Chung, Vijay K. Kuchroo, Michael A. Wheeler, Roni Nowarski & Francisco J. Quintana

  2. Evergrande Center for Immunologic Diseases, Harvard Medical School, Brigham and Women’s Hospital, Boston, MA, USA

    Joseph M. Rone, Gonzalo Fernandez Lahore, Rocky M. Barilla, Vijay K. Kuchroo & Roni Nowarski

  3. Synlogic Therapeutics, Cambridge, MA, USA

    Ning Li, Anna Sokolovska, David Hava & Jose M. Lora

  4. Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Lucas Dailey, Michael A. Wheeler, Clary Clish & Francisco J. Quintana

  5. Centro de Biología Molecular Severo Ochoa UAM-CSIC, Universidad Autónoma de Madrid, Madrid, Spain

    Eduardo Balsa

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Contributions

L.M.S., J.M.R., C.M.P., G.F.L., F.G., K.F., C.G.-V., N.L., A.S., A.P., C.F.A., P.N., E.S.H., H.-G.L., C.-C.C., C.M.R.-G., P.H.F.-C., M.L., J.E.K., R.M.B., D.F., G.P., E.N.C., N.A.S. and L.D. performed in vitro and in vivo experiments, FACS and genomic experiments. L.M.S., Z.L. and M.A.W. performed bioinformatic analyses. T.I. performed unbiased quantification of histology samples. J.M.R., C.C., V.K.K. and R.N. contributed reagents. L.M.S., N.L., D.H., A.S., J.M.L. and F.J.Q. designed and generated engineered probiotics. L.M.S., E.B. and F.J.Q. discussed and interpreted findings and wrote the manuscript with input from the other co-authors. F.J.Q. designed and supervised the study and edited the manuscript.

Corresponding author

Correspondence to Francisco J. Quintana.

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Competing interests

N.L., A.S., D.H. and J.M.L. were employees of Synlogic Therapeutics during some of this study. The remaining authors declare no competing interests.

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Nature thanks Greg Delgoffe, Lawrence Steinman and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Fig. 1 Analysis of HIF-1Itgax mice during EAE.

a, Uniform manifold approximation and projection (UMAP) displaying CNS DCs analysed by scRNA-seq during EAE. b, GSEA of hypoxia activation in DC subsets (cDC1, cDC2 and pDC) from scRNA-seq dataset53. c,d, Representative dot plot (c) and flow cytometry analysis (d) of HIF-1α expression in splenic cDC1s (CD8+CD11b−), cDC2s (CD8−CD11b−) and pDCs (B220+) 25 days after EAE induction in WT mice (n = 5 mice per group). e, Gating strategy used to analyse CD4+ T cells in the CNS of mice subjected to EAE. f, IFNγ+, IFNγ+IL-17+ CD4+ T cells in spleens of WT (n = 5) and HIF-1αItgax (n = 4) mice subjected to EAE. g,h, Cytokine production (20 μg/mL MOG33–55) (g) and proliferative recall response to ex vivo MOG35–55 restimulation (h) of splenocytes isolated from mice from (f (n = 3 for WT IFNγ, n = 4 for HIF-1αItgax IFNγ, IL-17 and WT GM-CSF, n = 5 otherwise). i, Absolute number of DCs in CNS from WT and HIF-1αItgax mice (n = 5 mice per group). j–l, Heat map (j), IPA (k) and GSEA analysis (l) of RNA-seq of DCs isolated from the CNS of WT or HIF-1αItgax mice subjected to EAE. Statistical analysis was performed using unpaired Student’s t-test for f and g and two-way ANOVA followed by Šídák’s multiple comparisons test for h. Data shown as mean ± s.e.m.

Source data

Extended Data Fig. 2 Effects of HIF-1α in DCs.

a, mRNA expression of shown genes in BMDCs isolated from WT mice treated with either vehicle or LPS and subjected to normoxia or hypoxia (n = 3 per group) b, mRNA expression of shown genes in BMDCs isolated from WT mice treated with LPS and ML228, DFX, or after Vhl knockdown (siVhl) (n = 3-for Il1b after LPS, Il12a and Tnf for siVhl, n = 4 otherwise). c, Vhl expression in siVhl-treated BMDCs from b (n = 3 for siNT, n = 4 for siVhl). d, Ifng and Il17a expression in 2D2+ CD4+ T cells co-cultured with WT BMDCs pre-stimulated with LPS and ML228, DFX or siVhl (n = 4 per group). e,f, HIF-1α MFI (e) and frequency of viable cells (f) of BMDCs following LPS stimulation and subjected to normoxia or hypoxia (n = 6 for viability after hypoxia, n = 4 otherwise). g,h, Experimental design (g) and S. thyphimurium CFU quantification (h) in caecum from WT (n = 4) and HIF-1αItgax (n = 5) mice 14 days after infection. i,j, S2W1 Tetramer-specific (i) and IFNγ+ and IL-17+ (j) CD4+ T cells in colon from mice from h. Statistical analysis was performed using one-way ANOVA with Tukey’s, Dunnett’s or Šídák’s post-hoc test for selected multiple comparisons for a,b,d–f, or unpaired Student’s t-test for c, h-j. Data shown as mean ± s.e.m.

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Extended Data Fig. 3 Effects of HIF-1α activation by L-LA on DCs.

a,b, Representative histogram (a) and MFI (b) of HIF-1α expression in BMDCs isolated from WT mice and treated with vehicle, LPS, L-LA, or both LPS and L-LA (n = 3 for vehicle, n = 4 otherwise). c, HIF-1α luciferase activity in BMDCs isolated from FVB.129S6-Gt(ROSA)26Sortm2(HIF1A/luc)Kael/J mice and treated with L-LA (n = 5 per group). d, Hif1a expression in BMDCs treated with vehicle or LPS (n = 3 per group). e, L-LA production of WT mouse BMDCs treated with vehicle or LPS and subjected to normoxia or hypoxia conditions (n = 4 per group). f, mRNA expression of shown genes in WT mouse BMDCs treated with vehicle or LPS and varying concentrations of L-LA (n = 4 for Il1b LPS+LA 0.1mM, Il23a LPS+LA 0.1, 1 and 10 mM and Tnf LPS+LA 1mM, n = 4 otherwise). g, mRNA expression of shown genes in human DCs after HIF1A knockdown (siHIF1A) or control (siNT) treated with LPS and L-LA or D-LA (n = 3 per group). h–j, mRNA expression of shown genes in WT mouse BMDCs after Slc16a1 knockdown (siSlc16a1) or control (siNT) (h,i) or treatment with the MCT1-antagonist AZD3965 (j) treated LPS and L-LA (n = 3 per group). Statistical analysis was performed using one-way ANOVA with Tukey’s, Šídák’s or Holm-Šídák’s post-hoc test for selected multiple comparisons for b,e–h,j, or unpaired Student’s t-test for c,d,i. Data shown as mean ± s.e.m.

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Extended Data Fig. 4 Effects of HIF-1α activation by D-LA on DCs.

a, mRNA expression of shown genes in splenic DCs isolated from WT or HIF-1αItgax mice stimulated with LPS or LPS and L-LA (n = 3–4 per group). b,c, mRNA expression of Hif1a (b) or HIF1A (c) after knockdown in mouse BMDCs (b) and human DCs (c) (n = 4 for siHif1 in BMDCs, n = 3 otherwise). d, Absolute numbers of HIF-1α+ DCs following treatment with D-LA or LPS with D-LA (n = 3 for media and LPS+D-LA 1 mM, n = 4 otherwise). e, mRNA expression of shown genes in splenic DCs from WT mice after LPS treatment with or without D-LA (1mM) treatment for 6h (n = 7 for Il12a in LPS treatment, n = 3 for Il23a in LPS and LPS+D-LA and Tnf in LPS, n = 4 otherwise). f, Ifng and Il17a expression in 2D2+ CD4+ T cells co-cultured DCs pre-treated with LPS or LPS and D-LA (1mM) (n = 3 for LPS-treated cells, n = 4 otherwise). Statistical analysis was performed using one-way ANOVA with Tukey’s, Šídák’s or Dunnett’s post-hoc test for selected multiple comparisons for a and d, or unpaired Student’s t-test for b,c,e,f. Data shown as mean ± s.e.m.

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Extended Data Fig. 5 Effects of HIF-1α on DC metabolism.

a, ECAR in BMDCs isolated from WT or HIF-1αItgax mice after glucose, oligomycin and 2-DG treatment (n = 10 WT and 20 HIF-1α KO replicate wells). b, Glycolysis and glycolytic capacity in WT and HIF-1αItgax BMDCs from a (n = 10 WT and 17 HIF-1α KO replicate wells). c, 2-NBDG uptake and Slc2a1 expression in BMDCs isolated from WT and HIF-1αItgax mice and stimulated with LPS (n = 4–6 per group). d, Transactivation of Ndufa4l2 promoter in Ndufa4l2-luciferase transfected DC2.4 cells treated with L-LA or LPS for 24 h (n = 3 per group). e, OCR in BMDCs isolated from WT or HIF-1αItgax mice and transfected with either an empty or Ndufa4l2-overexpression plasmid (n = 6 for WT, n = 5 otherwise). f, Ndufa4l2 expression after transfection with Ndufa4l2-oxerexpression plasmid or silencing with siRNA (n = 3 per group). g, mRNA expression of shown genes in WT mouse BMDCs after Ndufa4l2 knockdown (siNdufa4l2) or controls (siNT) stimulated with LPS and treated with or without D-LA for 6 h (n = 5 for Il23a siNT LPS + D-LA, n = 6 otherwise). Statistical analysis was performed using unpaired Student’s t-test for b,c,f and one-way ANOVA with Šídák’s or Holm-Šídák’s post-hoc test for selected multiple comparisons for d,e,g. Data shown as mean ± s.e.m.

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Extended Data Fig. 6 Incorporation of L-LA into TCA intermediates.

a, mRNA expression of shown genes in BMDCs isolated from WT mice and stimulated with LPS and mitoPQ or L-LA for 6 h (n = 3–4 per group). b, mRNA expression of shown genes in BMDCs isolated from WT mice and treated with mitoPQ for 6 h (n = 4–5 per group). c, 13C incorporation into TCA intermediates in BMDCs isolated from WT mice and treated with uniformly labelled 13C-lactate (L-LA*), L-LA or LPS for 1 h (n = 3 per group). d, Pyruvate intracellular levels in WT BMDCs after treatment with LPS, L-LA or D-LA for 1 h (n = 4 per group). e,f, mtROS production (e) and mRNA expression of shown genes (f) in WT BMDCs pre-treated with LDH-inhibitor oxamate, L-LA or LPS (n = 3–4 per group). g, mRNA expression of shown genes in splenic DCs isolated from WT or HIF-1αItgax mice then treated with LPS or pyruvate for 6 h (n = 3–4 per group). Statistical analysis was performed using one-way ANOVA with Tukey’s, Šídák’s or Dunnett’s post-hoc test for selected multiple comparisons for a,e–g and unpaired Student’s t-test for b. Data shown as mean ± s.e.m.

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Extended Data Fig. 7 Control of DCs by XBP1.

a,b, sXbp1/Xbp1 mRNA ratio in BMDCs isolated from WT mice and treated with LPS or LPS+D-LA (a) and LPS, mitoPQ or mitoTempo (MitoTP) (b) for 6 h (n = 4 per group). c,d, XBP1 recruitment to the Il1b, Il6 and Il23a promoters in WT BMDCs treated with LPS and mitoPQ (c) or LPS and ML228 (d) for 6h. e, Total numbers of IFNγ+ and IL-17+ CD4+ splenic T cells in WT (n = 3–4) and Xbp1Itgax (n = 4) mice 30 days after EAE induction. f,g, Heat map (f) and IPA (g) in CNS DCs from WT (n = 4) and Xbp1Itgax (n = 5) mice 30 days after EAE induction. Statistical analysis was performed using unpaired Student’s t-test for a,c-e and one-way ANOVA with Šídák’s post-hoc test for selected multiple comparisons for b. Data shown as mean ± s.e.m.

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Extended Data Fig. 8 Effect of lactate on EAE.

a, EAE development of mice after vehicle injection (n = 9), intraperitoneal (ip) (n = 10), nasal, or intravenous (iv) (n = 5 per group) L-LA or D-LA administration. b, IFNγ+, IFNγ+IL-17+ and IL-17+ CD4+ T cells in CNS isolated from mice from a 28 days after EAE induction (n = 3–4 per group). c–f, Heat map (c), GSEA (d) and IPA (e,f) analysis of RNA-seq of splenic DCs isolated from mice treated with vehicle, L-LA (e) and D-LA (f) 28 days after EAE induction. Statistical analysis was performed using two-way ANOVA for a and one-way ANOVA with Dunnett’s post-hoc test for selected multiple comparisons for b. Data shown as mean ± s.e.m.

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Extended Data Fig. 9 EcNLac characterization.

a, L-LA and D-LA concentration in plasma taken from naive and peak EAE WT mice (n = 5 per group). b, Schematic depicting the genome sequencing of EcNLac and parental EcN strains. c, Schematic for the plasmid used to induce ldhA expression in the EcNLac engineered strain. d, EcNGFP reporter strain. e, GFP expression in EcNGFP after activation at 37C. f,g, D-LA concentration in plasma (f) and colon tissue (g) after EcNLac or EcN administration (n = 5–9 mice per group). h, D-LA concentration in CSF and CNS lysate from naive (n = 4–5) and EAE (n = 3) WT mice after EcNLac administration, shown relative to D-LA concentration levels in EcN-treated mice. i, Percentage of HIF-1α+ DCs out of total DCs isolated from small intestine and colon tissue from EcN (n = 3–5) or EcNLac (n = 3–4) treated mice. j,k, Heat map (j) and GSEA (k) analysis of RNA-seq of DCs isolated from the small intestine of EcN (n = 3) or EcNLac (n = 4) treated mice. l,m, EcNLac CFUs in blood isolated from naive and peak EAE mice treated with EcNLac daily for a week (l) and EcNGFP in blood 1, 4 and 24 h after oral gavage (m). Small intestine CFU levels are shown as positive controls (n = 4–5 per group). n, Experimental design to assess the effect of EcNLac daily or weekly administration on EAE disease course. Statistical analysis was performed using two-way ANOVA with Šídák’s post-hoc test for e,f, and one-way ANOVA with Dunnett’s post-hoc test for selected multiple comparisons for i. Data shown as mean ± s.e.m.

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Extended Data Fig. 10 Effects of EcNLac on EAE and S. thyphimurium infection.

a, Splenic IFNγ+ and IL-17+CD4+ T cells isolated 20 days after EAE induction from WT mice treated with EcN (n = 5–6) or EcNLac (n = 5) and HIF-1αItgax mice treated with EcN (n = 3) or EcNLac (n = 3). b,c, Proliferative recall response to ex vivo MOG35–55 restimulation (b) and cytokine production (20 μg ml−1 MOG33–55) (c) of splenocytes isolated 20 days after EAE induction from WT mice dosed daily with EcN (n = 4–8) or EcNLac (n = 3–8). d–g, EAE development (d), IFNγ+ and IL-17+CD4+ T cells in CNS (e) and spleen (f), and splenocyte proliferation recall response (g) to ex vivo MOG35–55 restimulation of WT mice treated weekly with EcN (n = 4–5) or EcNLac (n = 4–5). h, CFUs in liver and caecum from WT mice infected with S. thyphimurium after daily or weekly administration of EcN (n = 5) or EcNLac (n = 4–5). i–k, Percentage of S2W1 tetramer+ out of total CD4 T cells in colon (i), and liver (j) and representative S2W1 tetramer staining of CD4 T cells in liver (k) in mice from h. l,m, HIF-1α MFI in neutrophils, monocytes and T cells (l), and number of HIF-1α+ DCs (m) in small intestine as a result of daily EcN (n = 5–8) or EcNLac (n = 5) treatment of WT mice for one week. Statistical analysis was performed using one-way ANOVA with Dunnett’s post-hoc test for selected multiple comparisons for a, two-way ANOVA followed by Šídák’s multiple comparisons test for b,d,g and unpaired Student’s t-test for c,e,f,m. Data shown as mean ± s.e.m.

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Sanmarco, L.M., Rone, J.M., Polonio, C.M. et al. Lactate limits CNS autoimmunity by stabilizing HIF-1α in dendritic cells. Nature 620, 881–889 (2023). https://doi.org/10.1038/s41586-023-06409-6

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