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Abstract

Recent advances highlight a pivotal role for cellular metabolism in programming immune responses. Here, we demonstrate that cell-autonomous generation of nicotinamide adenine dinucleotide (NAD+) via the kynurenine pathway (KP) regulates macrophage immune function in aging and inflammation. Isotope tracer studies revealed that macrophage NAD+ derives substantially from KP metabolism of tryptophan. Genetic or pharmacological blockade of de novo NAD+ synthesis depleted NAD+, suppressed mitochondrial NAD+-dependent signaling and respiration, and impaired phagocytosis and resolution of inflammation. Innate immune challenge triggered upstream KP activation but paradoxically suppressed cell-autonomous NAD+ synthesis by limiting the conversion of downstream quinolinate to NAD+, a profile recapitulated in aging macrophages. Increasing de novo NAD+ generation in immune-challenged or aged macrophages restored oxidative phosphorylation and homeostatic immune responses. Thus, KP-derived NAD+ operates as a metabolic switch to specify macrophage effector responses. Breakdown of de novo NAD+ synthesis may underlie declining NAD+ levels and rising innate immune dysfunction in aging and age-associated diseases.

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The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

This work was supported by grant no. RO1AG048232 (K.I.A.), grant no. RF1AG058047 (K.I.A.), grant no. 1P50 AG047366 (K.I.A.), Bright Focus (K.I.A.), The Paul and Daisy Soros Fellowship for New Americans (P.S.M.), the Gerald J. Lieberman Fellowship (P.S.M.), grant no. DP1DK113643 (L.L. and J.D.R.), grant no. 5U54DK10255603 (K.C., B.A.L., and M.P.S.), grant no. 5R01CA188055 (C.D. and R.M.), R37 AA11147 MERIT (A.J. and D.M.R.), the Takeda Pharmaceuticals’ Science Frontier Fund (D.M.R.), and grant no. 5T32HL094274 (M.C. and D.B.). The authors would like to thank L. Alexandrova at the Stanford University Mass Spectrometry Core, J. Perrino at the Stanford Microscopy Facility (supported by NIH grant no. 1S10RR02678001), and the Stanford Human Immune Monitoring Center. 

Author information

Affiliations

  1. Department of Neurology & Neurological Sciences, Stanford School of Medicine, Stanford, CA, USA

    • Paras S. Minhas
    • , Peter K. Moon
    • , Siddhita Mhatre
    • , Qian Wang
    •  & Katrin I. Andreasson

  2. Neurosciences Graduate Program, Stanford University, Stanford, CA, USA

    • Paras S. Minhas

  3. Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA

    • Ling Liu
    •  & Joshua D. Rabinowitz

  4. Department of Chemistry, Princeton University, Princeton, NJ, USA

    • Ling Liu
    •  & Joshua D. Rabinowitz

  5. Department of Chemical and Systems Biology, Stanford University, Stanford, CA, USA

    • Amit U. Joshi
    •  & Daria Mochly-Rosen

  6. Department of Hematology, Stanford School of Medicine, Stanford, CA, USA

    • Christopher Dove
    •  & Ravindra Majeti

  7. Department of Genetics, Stanford School of Medicine, Stanford, CA, USA

    • Kevin Contrepois
    • , Brittany A. Lee
    •  & Michael P. Snyder

  8. Department of Pediatrics, Stanford School of Medicine, Stanford, CA, USA

    • Michael Coronado
    •  & Daniel Bernstein

  9. Mitchell Cancer Institute, University of South Alabama, Mobile, AL, USA

    • Marie Migaud

  10. Stanford Neuroscience Institute, Stanford University, Stanford, CA, USA

    • Katrin I. Andreasson

  11. Stanford Immunology Program, Stanford University, Stanford, CA, USA

    • Katrin I. Andreasson

Contributions

P.S.M., L.L., P.K.M., A.U.J., C.D., S.M., Q.W., M.C., D.B., D.M.R., and R.M. designed and performed the experiments and analyzed the data and M.M. provided advice. K.C., B.A.L., and M.P.S. performed untargeted metabolomics and analyzed the data. L.L. and J.D.R. performed targeted metabolomics and quantification of isotope labeling. P.S.M. and K.I.A. conceived and supervised the project, designed the experiments, interpreted the data, and wrote the manuscript.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Katrin I. Andreasson.

Integrated supplementary information

  1. Supplementary Figure 1 Effects of the NAMPT inhibitor FK866 and KYN supplementation.

    HuMDMs were treated with either vehicle or FK866 (10 μM, 20 h) and were supplemented with either vehicle or KYN (25 μM, 20 h). a, Representative western blot of NAD+ synthetic enzymes NMNAT1 and NADS and NAMPT; n = 3 per group, shown as mean ± S.E. with protein levels normalized to β-actin; non-significance determined by Student’s two-tailed t test. b, Administration of NMN to FK866-treated huMDMs restores NAD+ levels, as measured by LC/MS; n = 6 per group, represented as mean ± S.E., two-way ANOVA: effects of NMN and FK866, P < 0.0001 with Tukey post hoc test: ****P < 0.0001. c, LC/MS measurements of QA, NaMN, NaAD; n = 6 per group, represented as mean ± S.E.; two-way ANOVA, for QA effect of KYN, P < 0.0001; for NaMN, effects of KYN and FK866, P < 0.0001; for NaAD, effects of KYN and FK866, P < 0.001; Tukey post hoc tests: ***P = 0.0001 QA: veh-veh versus KYN-veh; ***P = 0.0002 QA: veh-FK866 versus KYB-FK866; ****P < 0.0001 NaMN: veh-veh versus KYN-veh; ####P < 0.0001 KYN-veh versus KYN-FK866; ***P = 0.0002 NaAD: veh-veh versus KYN-veh; ###P = 0.0002 NaAD: KYN-veh versus KYN-FK866. d, Reaction mechanism for isotope labeling of KYN to generate M+2 de novo NAD+.

  2. Supplementary Figure 2 Effects of the NAMPT inhibitor FK866 and KYN supplementation.

    a, Diagram of the site of action of 1MT and phthalic acid (PTH), selective inhibitors of IDO1 and QPRT, respectively. b, Representative flow cytometry plot from three independent experiments of cells treated for 20 h with either vehicle, 1MT (200 μM), or pthalic acid (PTH, 500 μM) stained with propidium iodide (n = 25,000–30,000 cells per group). c, Gating strategy for huMDMs. d–h, HuMDMs were treated with the IDO1 inhibitor 1MT (200 μM, 20 h). d, LC/MS measurement of NAD+; n = 3 biologically independent samples per group, shown as mean ± S.E.; *P = 0.0233 by Student’s two-tailed t test. e, Representative trace from three independent experiments for effect of 1MT on OCR, n = 10 biologically independent samples/group, shown mean ± S.E. f, Effects of 1MT on basal respiration, maximal respiration, and spare respiratory capacity; n = 3 biologically independent samples per group, shown as mean ± S.E.; ***P = 0.0004 for basal respiration, ***P = 0.0006 for maximal respiration, and **P = 0.0087 for spare respiratory capacity by Student’s two-tailed t test. g, Effect of 1MT on ECAR; n = 3 biologically independent samples/group, mean ± S.E.; *P = 0.0411 by Student’s two-tailed t test. h, Peritoneal macrophages from WT and Ido1–/– mice were supplemented with either vehicle or 25 μM KYN for 20 h and assayed for spare respiratory capacity and maximal respiration; n = 6 biologically independent samples per WT group and n = 9 biologically independent samples per Ido1–/– group, represented as mean ± S.E.; two-way ANOVA, effect of genotype P < 0.0001 for both, effect of KYN P < 0.05 and P < 0.0001 for spare respiratory capacity and max respiration, respectively; Tukey post hoc ***P = 0.0001, *P = 0.0200, and ****P < 0.0001. i, Permeabilized macrophages from WT and Ido1–/– mice were stimulated with complex-specific substrates, including pyruvate + malate for assessing complex I, succinate + rotenone for complex II, duroquinol for complex III, and TMPD + ascorbate for complex IV. Data are represented as mean ± S.E.; n = 8 biologically independent samples per group; ****P < 0.0001 by Student’s two-tailed t test.

  3. Supplementary Figure 3 Untargeted metabolomic profiling of WT and Ido1–/– macrophages.

    a, Hierarchical clustering of validated and significantly altered metabolites (q < 0.05) are represented. Ido1–/– macrophages show disrupted amino acid metabolism and lipid metabolism and increased glycolysis (n = 8 mice per group, two-tailed parametric Welch’s T-test with multiple-hypothesis q-value correction. FDR < 0.05 was considered significant). b, MBROLE enrichment analysis of untargeted metabolomics from comparison of Ido1–/– versus WT macrophages (n = 8 per genotype).

  4. Supplementary Figure 4 Inhibition of QPRT disrupts oxidative phosphorylation and cellular metabolism.

    a–e, HuMDMs were treated with vehicle or the QPRT inhibitor phthalic acid (PTH; 500 μM, 20 h). a, LC/MS of NAD+ with PTH treatment; n = 3 biologically independent samples per group, shown as mean ± S.E.; **P = 0.0048 by Student’s two-tailed t test. b, Representative trace of PTH-treated huMDMs. c, Basal respiration, maximal respiration, and spare respiratory capacity in PTH-treated huMDMs; n = 4 biologically independent samples per group, shown as mean ± S.E; Basal respiration: **P = 0.0023; maximal respiration **P = 0.0019; spare respiratory capacity: **P = 0.0089; all by Student’s two-tailed t test. d, ECAR in PTH-treated huMDMs; n = 3 biologically independent samples per group, *P < 0.05. e, Hierarchical clustering of targeted metabolomics for glycolysis, pentose phosphate pathway, and citric acid cycle metabolites of huMDMs treated with PTH (500 μM, 20 h; n = 3 biologically independent samples per group). f, Targeted metabolomics from e with PTH-treated huMDMs reveals an upregulation of lactate, the pentose phosphate pathway and proinflammatory TCA intermediates (in red), similar to changes seen in Qprt–/– macrophages. g, Metabolism of 13C[TRP] to NAD+ yields M+6–labeled NAD+.

  5. Supplementary Figure 5 Effects of de novo NAD+ synthesis on macrophage polarization.

    a, Representative histograms of three independent experiments for surface markers in huMDMs stimulated with LPS and phthalic acid (PTH). b, Complex I inhibitors rotenone and piericidin A (500 nM, 20 h) in huMDMs mimic the effect of QPRT inhibition (n = 3 biologically independent samples per group, three independent flow experiments, represented as mean ± S.E.; **P < 0.01, ***P < 0.001. ****P < 0.0001 by Student’s two-tailed t test). c, Hierarchical clustering of immune factors in huMDMs treated with either vehicle or piericidin A (500 nM, 20 h). d, Quantification of c. Significantly regulated immune factors in huMDMs stimulated with PTH and/or LPS, n = 3 biologically independent samples per group, represented as mean ± S.E.

  6. Supplementary Figure 6 Effect of LPS on OXPHOS, the KP, and complex activities.

    a, Macrophages from WT and Ido1–/– mice supplemented ± NAD+ (2 mM) and assayed for Sirt3 steady-state kinetics (n = 4 biologically independent samples/group, mean ± S.E.; ****P < 0.0001 by linear regression analysis; curved thin lines denote 95% CI). b, Macrophages from huMDMs treated ± phthalic acid (PTH) (500 μM, 20 h) were supplemented ± NAD+ (2 mM) and assayed for Sirt3 steady-state kinetics (n = 4 biologically independent samples per group, represented as mean ± S.E.; ****P < 0.0001 by linear regression analysis; curved thin lines denote 95% CI). c, Quantitative immunoblot of Sirt3 levels in huMDMs ± PTH (500 μM, 20 h), normalized to actin (n = 6 biologically independent samples per group, represented as mean ± S.E.; non-significance determined by Student’s two-tailed t test). d, OCR trace for huMDMs treated with either LPS (100 ng/mL) or vehicle for 20 h. e, Basal respiration in huMDMs following LPS (n = 5 biologically independent samples per veh group, n = 6 biologically independent samples per LPS group, represented as mean ± S.E.; **P < 0.01 by Student’s two-tailed t test). f, ECAR in huMDMs (n = 9 biologically independent samples/group, mean ± S.E.; ****P < 0.0001 by Student’s two-tailed t test). g, Changes in KP enzyme levels by quantitative western analysis are observed by 4 h after LPS challenge in huMDMs (n = 8 biologically independent samples per veh group, n = 9 biologically independent samples per LPS group, represented as mean ± S.E.; **P < 0.01 and *P < 0.05 by Student’s two-tailed t test). h, Increases in KP metabolites are observed by 4 h after LPS challenge in huMDMs (n = 5 biologically independent samples per group, represented as mean ± S.E.; ****P < 0.0001, ***P < 0.001, **P < 0.01, and *P < 0.05 by Student’s two-tailed t test). i, Permeabilized huMDMs ± LPS (100 ng/mL) were stimulated with complex-specific substrates, including pyruvate + malate for assessing complex I, succinate + rotenone for complex II, duroquinol for complex III, and TMPD + ascorbate for complex IV (n = 8 biologically independent samples per group, represented as mean ± S.E.; ****P < 0.0001 by Student’s two-tailed t test). j, OCR trace for huMDMs transfected with either GFP control vector or QPRT vector, stimulated with LPS (100 ng/mL) and assayed at 20 h (n = 6 biologically independent samples per group, represented as mean ± S.E.). k, Maximal respiration and spare respiratory capacity of control- and QPRT-transfected huMDMs ± LPS (n = 6 biologically independent samples per group, represented as mean ± S.E.; two-way ANOVA, effect of QPRT P < 0.0001 and P < 0.01 for maximal respiration and spare respiratory capacity, respectively; effect of LPS P < 0.01 for maximal respiration; Tukey post hoc test: *P < 0.05, **P < 0.01, ****P < 0.0001).

  7. Supplementary Figure 7 Overexpression of QPRT rescues metabolic changes induced by LPS in huMDMs.

    Untargeted metabolomics analysis was carried out on huMDMs ± LPS transfected with either GFP control vector or QPRT vector. a, Hierarchical clustering of significant validated metabolites is shown (q < 0.05 by Student’s two-tailed t test with FDR correction for multiple hypotheses; see Methods). Hierarchical clustering reveals rescue of altered amino acid, fatty acid, nucleotide, and glucose metabolism with QPRT overexpression in LPS-stimulated huMDMs (n = 6 biologically independent samples per the con + LPS and con + veh groups, n = 4 biologically independent samples per group for all others). b, Principal-component analysis of a; untargeted metabolomics shows separation of LPS-treated control huMDMs from the QPRT + veh, QPRT + LPS, and con + veh groups (n = 6 biologically independent samples per the con + LPS and con + veh groups, n = 4 biologically independent samples per group for all others). c, Enrichment of KEGG pathways (n = 6 biologically independent samples per the con + LPS and con + veh groups, n = 4 biologically independent samples per group for all others).

  8. Supplementary Figure 8 Effect of increased de novo NAD+ on immune factor generation in LPS-stimulated macrophages.

    HuMDMs transfected with either GFP control vector or QPRT vector were stimulated with LPS for 20 h. a, Representative BN-PAGE from three independent experiments. b, Permeabilized huMDMs ± LPS were stimulated with complex-specific substrates (n = 8 biologically independent samples per group, represented as mean ± S.E.; ****P < 0.0001 by Student’s two-tailed t test). c, Representative immunoblot from two independent experiments of SOD2, Ac-SOD2, and COXIV loading control. d, Comparison of proinflammatory (in red) and anti-inflammatory (in green) factors that are upregulated and downregulated by QPRT inhibition with phthalic acid (PTH) versus QPRT overexpression under basal conditions (left) and LPS-stimulated conditions (right). Note the similarity of subsets of the pro- and anti-inflammatory factors and reciprocal regulation in control versus experimental conditions. e, Representative immune factors regulated by QPRT overexpression in huMDMs ± LPS (n = 3 biologically independent samples per group, represented as mean ± S.E.).

  9. Supplementary Figure 9 De novo NAD+ synthesis regulates mitochondrial respiration and polarization state in aged macrophages.

    Young and aged huMDMs were derived from human subjects ≤35 and ≥65 years old, respectively. a, qPCR of the telomere length of young versus aged macrophages (n = 3 biologically independent samples per group, mean ± S.E.; **P = 0.0046 by Student’s two-tailed t test). b, Representative immunoblots from three independent experiments for all KP enzymes demonstrates loss of QPRT expression in aged macrophages as compared to young macrophages. c, Mean fluorescence intensities (MFI) increase for proinflammatory markers CD86 and CD64 and decrease for anti-inflammatory markers CD206 and CD23 in aged versus young huMDMs ± LPS; n = 3 biologically independents samples per group, represented as mean ± S.E.; two-way ANOVA: effects of age and LPS, P < 0.0001 for all four surface markers; Tukey post hoc test ****P < 0.0001. d–i, Young and aged huMDMs were transfected with either control vector (con) or QPRT vector (QPRT). d, Top, representative immunoblot from two independent experiments of huMDMs derived from young and aged subjects transfected with control or QPRT vectors. Bottom, quantification of changes in QPRT protein levels; n = 3 biologically independent samples/group, mean ± S.E.; two-way ANOVA, effects of age and QPRT P < 0.0001; Tukey post hoc test ****P < 0.0001. e, QPRT overexpression increases metabolism of QA to NAD+ and restores NAD+ levels in aged macrophages to those of young huMDMs; n = 3 biologically independent samples per group, represented as mean ± S.E.; two-way ANOVA, effect of age and QPRT for QA, P < 0.0001; two-way ANOVA, effect of age and QPRT for NAD+, P < 0.01; Tukey post hoc test ****P < 0.0001. f, OCR trace for young and aged control or QPRT-expressing huMDMs; n = 3 biologically independent samples per group, mean ± s.d. g, Basal respiration and ECAR in aged control and QPRT-expressing huMDMs; n = 2 biologically independent samples per con group, n = 3 biologically independent samples per QPRT-OE group, mean ± s.d.; *P = 0.034 and ***P = 0.0001 by Student’s two-tailed t test. h, Top, representative BN-PAGE of complex II activity in young and aged huMDMs transfected with either control or QPRT vectors. Bottom, quantification of complex II activity; n = 6 biologically independent samples per group, mean ± S.E.; two-way ANOVA, effect of age and QPRT, P < 0.0001; Tukey post-hoc test, ****P < 0.0001. i, Left, representative 2D SDS immunoblot from two independent experiments of complex II in young and aged huMDMs ±, assayed for acetyl-lysine immunoreactivity. Right, quantification of acyl-lysines in complex II; n = 6 biologically independent samples/group, mean ± S.E.; two-way ANOVA, effects of age and QPRT, P < 0.0001; Tukey post hoc test ****P < 0.0001. j, MFI of huMDMs treated with the complex II inhibitor dimethyl malonate (DMM, 1 mM, 20 h); n = 3 biologically independent samples/group, mean ± S.E.; CD86 **P = 0.0083, CD64 ***P = 0.0003, CD206 ***P = 0.0005, CD23 **P = 0.0022 by Student’s two-tailed t test. k, Cytokine/chemokine profiles of culture medium from huMDMs stimulated with DMM (1 mM, 20 h). l, Representative histograms from three independent experiments of young and aged huMDMs supplemented with NMN (10 μM, 20 h).

  10. Supplementary Figure 10 Mitochondrial respiration decreases in aged mouse macrophages.

    Primary peritoneal macrophages from young (3 month) and aged (16–20 month) mice were examined for mitochondrial respiration, complex activity, and mitochondrial sirtuin steady-state kinetics. a, Real-time changes in OCR in young versus aged primary macrophages (n = 10 biologically independent samples per group). b, Quantification of basal respiration and extracellular acidification rate (ECAR); n = 10 biologically independent samples per group, represented as mean ± S.E.; ****P < 0.0001 by Student’s two-tailed t test. c, Left, representative BN-PAGE from three independent experiments of complex activities in young versus aged mouse primary macrophages. Right, quantification demonstrates reduced complex I and complex II activities, n = 6 biologically independent samples per group, represented as mean ± S.E.; ****P < 0.0001 by Student’s two-tailed t test. d, Young and aged mouse macrophages were assayed for mitochondrial Sirt3 steady-state kinetics; n = 4 biologically independent samples per group, represented as mean ± S.E.; ****P < 0.0001 by linear regression analysis; curved thin lines denote 95% CI.

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