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Senescent cells promote tissue NAD+ decline during ageing via the activation of CD38+ macrophages

Nature Metabolism volume 2, pages 1265–1283 (2020)Cite this article

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An Author Correction to this article was published on 10 December 2020

This article has been updated

Abstract

Declining tissue nicotinamide adenine dinucleotide (NAD) levels are linked to ageing and its associated diseases. However, the mechanism for this decline is unclear. Here, we show that pro-inflammatory M1-like macrophages, but not naive or M2 macrophages, accumulate in metabolic tissues, including visceral white adipose tissue and liver, during ageing and acute responses to inflammation. These M1-like macrophages express high levels of the NAD-consuming enzyme CD38 and have enhanced CD38-dependent NADase activity, thereby reducing tissue NAD levels. We also find that senescent cells progressively accumulate in visceral white adipose tissue and liver during ageing and that inflammatory cytokines secreted by senescent cells (the senescence-associated secretory phenotype, SASP) induce macrophages to proliferate and express CD38. These results uncover a new causal link among resident tissue macrophages, cellular senescence and tissue NAD decline during ageing and offer novel therapeutic opportunities to maintain NAD levels during ageing.

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Fig. 1: M1 macrophages are characterized by increased NADase activity.
Fig. 2: The NAM-salvage pathway controls NAD levels to regulate macrophage activation and polarization.
Fig. 3: High NADase activity in M1 macrophages is CD38 dependent.
Fig. 4: NAD decline during ageing is associated with increased CD38+ tissue-resident macrophages in eWAT.
Fig. 5: Cytokines secreted by senescent cells promote macrophage CD38 expression and proliferation.
Fig. 6: CD38+ Kupffer cells accumulate in the livers of ageing mice.
Fig. 7: Acute and chronic LPS treatment causes a CD38-dependent decrease in tissue NAD levels.
Fig. 8: Proposed model for how ageing-related inflammation enhances NAD degradation.

Data availability

For proteomics data, all files are uploaded to the Center for Computational Mass Spectrometry, and can be downloaded using the following link ftp://massive.ucsd.edu/MSV000083726 (MassIVE ID number: MSV000083726). Data uploads include protein identification and quantification details, spectral library and FASTA file used for analysis. Tabula Muris Senis database is accessible at this link: https://tabula-muris-senis.ds.czbiohub.org. All other data that support the findings of this study are available from the corresponding author upon request. Source data are provided with this paper.

Code availability

Coding used in image analysis is available upon request. Source data are provided with this paper.

Change history

  • 10 December 2020

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Acknowledgements

This project was supported by NIH grant R24DK085610 (E.V.), Gladstone Institute intramural funds (E.V.) and Buck Institute intramural funds (E.V. and J.C.). A.J.C. is a recipient of the UC President’s Postdoctoral Fellowship at UCSF and was supported by NIH training grant T32AG000266 (Buck Institute). A.K. was supported by the SENS Research Foundation and NIH grant R01AG051729 (J.C.). B.S. and N.B. were supported by NIH grant U01AG060906 (B.S., principal investigator) and NIH Shared Instrumentation Grant 1S10OD016281 (Buck Institute). M.S.S. and C.B. were supported by NIH grant R01HL147545 and the Roy J. Carver Trust to C.B. We thank M. Walter for help with imaging cells, and P. Dighe for help optimizing Seahorse assay conditions. We thank R. Camarda, V. Byles and D. Powell for reviewing the manuscript and helpful discussions.

Author information

Author notes

  1. Kyong-Oh Shin

    Present address: Department of Food Science and Nutrition, Hallym University, Chuncheon, Republic of Korea

  2. Charles Brenner

    Present address: Department of Diabetes & Cancer Metabolism, City of Hope National Medical Center, Duarte, CA, USA

  3. These authors contributed equally: Abhijit Kale, Rosalba Perrone.

Authors and Affiliations

  1. Buck Institute for Research on Aging, Novato, CA, USA

    Anthony J. Covarrubias, Abhijit Kale, Rosalba Perrone, Jose Alberto Lopez-Dominguez, Herbert G. Kasler, Indra Heckenbach, Ryan Kwok, Christopher D. Wiley, Hoi-Shan Wong, Eddy Gibbs, Nathan Basisty, Qiuxia Wu, Ik-Jung Kim, Elena Silva, Kaitlyn Vitangcol, Rebeccah Riley, Birgit Schilling, John Newman, Judith Campisi & Eric Verdin

  2. UCSF Department of Medicine, San Francisco, CA, USA

    Anthony J. Covarrubias, John Newman & Eric Verdin

  3. Chan Zuckerberg Biohub, San Francisco, CA, USA

    Angela Oliveira Pisco & Stephen R. Quake

  4. Department of Biochemistry, Carver College of Medicine, University of Iowa, Iowa City, IA, USA

    Mark S. Schmidt & Charles Brenner

  5. Department of Cellular and Molecular Medicine, University of Copenhagen, Copenhagen, Denmark

    Indra Heckenbach & Morten Scheibye-Knudsen

  6. Division of Gastroenterology, Hepatology and Endoscopy, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Shankar S. Iyer

  7. College of Pharmacy, Chungbuk National University, Cheongju, Republic of Korea

    Kyong-Oh Shin & Yong-Moon Lee

  8. Department of Biochemistry and Molecular Genetics, Northwestern University, Chicago, IL, USA

    Issam Ben-Sahra

  9. Gladstone Institutes, Virology and Immunology, San Francisco, CA, USA

    Melanie Ott

  10. Immunology and Molecular Genetics, Kawasaki Medical School, Kurashiki, Japan

    Katsuhiko Ishihara

  11. Department of Bioengineering, Stanford University, Stanford, CA, USA

    Stephen R. Quake

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  1. Anthony J. Covarrubias
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Contributions

Conceptualization, A.J.C. and E.V.; Methodology, A.J.C. and E.V.; Investigation, A.J.C. (all experiments), A.K. (In vivo experiments, senescent-cell experiments, proteomics and flow cytometry), R.P. (NADase assays and flow cytometry), J.A.L.-D. (in vivo experiments), A.O.P. (single-cell RNA-seq analysis), H.G.K. (flow cytometry), M.S.S. (LC–MS), I.H. (IF imaging and analysis), R.K. (in vivo experiments, IF imaging and analysis), C.D.W (in vivo experiments), H.-S.W. (Seahorse assay), E.G. (Seahorse assay), S.S.I. (RNA analysis), N.B. (proteomics), Q.W. (IF imaging and analysis), I.-J.K. (in vitro experiments), E.S. (in vivo experiments), K.V. (in vivo experiments), K.-O.S. (LC–MS), Y.-M.L. (LC–MS), R.R. (In vivo experiments), I.-B.S. (LC–MS), M.O. (animal housing), B.S. (proteomics), M.S.-K. (IF imaging and analysis), K.I. (provided Cd157 KO and Cd38/Cd157 DKO bone marrow), S.R.Q. (single-cell RNA-seq analysis), J.N. (provided ageing mice), C.B. (LC–MS), J.C. (senescent-cell experiments); writing—original draft, A.J.C. and E.V.; writing—review and editing, all authors; supervision, E.V.; funding acquisition, see Acknowledgements.

Corresponding author

Correspondence to Eric Verdin.

Ethics declarations

Competing interests

All authors have reviewed and approved the manuscript. C.B. is the inventor of intellectual property on the nutritional and therapeutic uses of NR, serves as chief scientific advisor of and holds stock in ChromaDex. E.V. is a scientific cofounder of NAPA Therapeutics. A.J.C., R.P., Q.W., E.S. and K.V. received partial salary support from NAPA Therapeutics. J.C. is a scientific cofounder of Unity Biotechnology. The other authors declare no competing interests.

Additional information

Peer review information Primary Handling Editor: Pooja Jha.

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

Extended data

Extended Data Fig. 1 CD38 expression in human M1 macrophages and analysis of the de novo NAD pathway in BMDMs.

a, mRNA levels of CD38 in human peripheral blood monocytes (PBMC)-derived macrophages treated with recombinant human IL-4 (M2) or LPS (M1) for 18 hours. Representative data from one of three patient samples. (n = 4 independent biological experiments) b, Immunofluorescence of human PBMC derived macrophages stimulated as described above using an anti-human CD38 antibody (Green) and nuclei with DAPI (Blue). Scale bars represents 10μm. Analyzed in PBMCs derived from one patient. c, NADase activity in human PBMC-derived macrophages treated with recombinant human IL-4 (M2) or LPS (M1) for 18 hours. Shown is the mean of two separate experiments from different donors with 2 replicates each. d, Schematic of the de novo NAD synthesis pathway. e, mRNA levels of de novo NAD synthesis pathway enzymes. f, Quantification of tryptophan metabolites measured by LC-MS in M0, M2 and M1 mouse BMDMs activated for 24 hours. ND=not detected. Data shows the mean ± SEM n=3 independent experiments except in A and B. Statistical significance indicated as *P<0.05, **P<0.01, and ***P<0.001; two-sided Student’s t-test.

Source data

Extended Data Fig. 2 Analysis of the role of the NAM-salvage pathway and sirtuins in macrophage activation and polarization.

a, NAD levels quantified by LC-MS in M0, M1 and M2 BMDMs pre-treated or not with 50 nM FK866 and NR for 6 hours prior to stimulation with LPS for an additional 6 hours or IL-4 for 16 hours. b, mRNA levels of M2 genes in BMDMs pre-treated or not with FK866 and NR for 6 hours prior to stimulation with IL-4 for 16 hours. All statistical comparisons are relative to M2 + FK866. c, mRNA levels of M1 genes in BMDMs pre-treated or not with FK866 and NR for 6 hours prior to stimulation with LPS for 6 hours. All statistical comparisons are relative to M1 + FK866. d, Western analysis of Nampt Fl/Fl CreER and Nampt Fl/Fl BMDMs treated with 1 ug/ml tamoxifen. e, mRNA levels of M2 genes in Nampt Fl/Fl CreER and Nampt Fl/Fl BMDMs treated with IL-4 for 16 hours. f, mRNA levels of M1 genes in Nampt Fl/Fl CreER and Nampt Fl/Fl BMDMs treated with LPS for 6 hours. g, mRNA levels of M2 genes in WT BMDMs pretreated with the indicated concentration of the sirtuin inhibitors Ex527 and AGK2 for 30 minutes prior to stimulation with IL-4 for 16 hours. All statistical comparisons are relative to M2. h, mRNA levels of M1 genes in WT BMDMs pretreated with the indicated concentration of the sirtuin inhibitors Ex527 and AGK2 for 30 minutes prior to stimulation with LPS for 6 hours. All statistical comparisons are relative to M1. Data show the mean ± SEM. (n=3 independent experiments). Statistical significance defined as *P<0.05, **P<0.01, and ***P<0.001; two-sided Student’s t-test.

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Extended Data Fig. 3 Heightended NADase activity in M1 macrophages is CD38 dependent and PARP1 independent.

a, Flow cytometry results comparing CD38 surface staining in naive (M0) WT and Cd38 KO BMDMs or BMDMs treated with IL-4 (M2) and LPS (M1) for 16 hours. b-c, NADase activity measured with non-cell permeable εNAD in intact M0, M2, and M1 WT and Cd38 KO BMDMs activated for 16 hours relative to cell number (B) and protein content (C). d, mRNA levels of Cd157 in M0 and M1 WT and Cd38 KO BMDMs treated for 16 hours. e, LC-MS quantification of NR in M0 and M1 WT and Cd38 KO BMDMs treated for 16 hours. f, mRNA levels of anti-oxidant genes in WT and Cd38 KO BMDMs treated with IL-4 (M2) and LPS (M1) for the indicated intervals. g, Western analysis of PARP activity (PARylation) and DNA damage (γH2AX) in WT and Cd38 KO BMDMs treated with IL-4 (M2) and LPS (M1) for the indicated intervals compared to WT MO macrophage treated with 1 mM H2O2 for 10 minutes. h, Western analysis of PARP activity (PARylation) and DNA damage (γH2AX) in WT and Cd38 KO BMDMs treated with IL-4 (M2) and LPS (M1) for 8 hours prior to treatment with 1 mM H2O2 for 10 minutes. Data show the mean ± SEM. (n= at least 3 independent experiments). Statistical significance indicated as *P<0.05, **P<0.01, and ***P<0.001; two-sided Student’s t-test. Unless noted with a bar, statistical comparisons are relative to the appropriate MO WT or Cd38 KO sample of the same genotype.

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Extended Data Fig. 4 CD38+ resident macrophages accumulate in ageing adipose tissue.

a, LC-MS quantification of NAD in eWAT from WT young male mice (6 month) n=7 mice/group, Cd38 KO young male mice (3 month) n=5 mice/group, WT old male mice (25 month) n=10 mice/group, and Cd38 KO old male mice (26 month) n=5 mice/group. NAD concentrations are shown as pmol/mg of tissue. (same WT data from Fig. 4a). b, mRNA levels of Il-1α and IL-10 in eWAT from 6 and 25 month-old WT male mice. (WT young male mice (6 month) n=7 mice/group, WT old male mice (25 month) n=9 mice/group) c, Western analysis of adipose tissue from young (3 Month) and old (19 month) WT male mice to detect PARP activity (PARylation) and DNA damage (γH2AX). Each lane represents one mouse (young n=4 mice/group, old n=4 mice/group). d, mRNA levels of Cd38 in visceral adipose tissue, the stromal vascular fraction, and adipocyte fraction from young (3 month) and old (19 month) WT male mice. (young n=4 mice/group, old n=4 mice/group). e, Flow cytometry gating strategy to identify CD45+ immune cells from the stromal vascular fraction of eWAT. Cells were first gated on forward scatter (FSCA) vs side scatter (SSCA) to discard cell debris and dead or dying cells. Next FSCH (height) vs FSCA (Area) was used to select single cells. Single cells were then gated for auto-fluorescent using the Empty(E) BV421 vs BV711 channels (not used as antibody fluorophores) to discard cells that showed auto-fluorescence in these channels. Then CD45+ cells were selected and analyzed for CD38 and macrophage markers. Flow cytometry gating strategy to identify resident and non-resident macrophages from the stromal vascular fraction of eWAT, showing representative flow plots and histograms for the indicated ages of mice. f, Flow cytometry quantification of CD38- (low) resident macrophages, CD38- non-resident macrophages, and CD38+ (high) non-macrophage immune cells from eWAT of WT male mice for the ages shown. (2 months n=6 mice/group, 6 months n=5 mice/group, 12 months n=5 mice/group, 18 months n=5 mice/group, 25+ months n=7 mice/group) For in vivo experiments, data from individual mice are shown. Statistical significance indicated as *P<0.05, **P<0.01, and ***P<0.001; two-sided Student’s t-test.

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Extended Data Fig. 5 Senescent cell burden is causally linked to increased macrophage CD38 expression.

a, mRNA levels of Il-1α, Cxcl1, and IL-10 in eWAT from 6 month-old WT male mice i.p. injected with Doxo or PBS. (PBS n=8 mice/group, Doxo n=7 mice/group) b, Quantification of CD38-low resident macrophages, and CD38-low non-resident macrophages from eWAT of 6 month-old WT male mice injected with Doxo or PBS. (PBS n=8 mice/group, Doxo n=8 mice/group). c, CD38 mRNA levels in WT and Cd38 KO BMDMs co-cultured (10:1) with non-senescent control mouse dermal fibroblasts (CTRL-MDF) or irradiated senescent MDF (Sen(IR)-MDF) for 24 hours. (n=4 independent biological experiments per condition) d, mRNA levels of Cd38 in WT BMDMs treated with the indicated DAMPs for 16 hours. (n=3 independent biological experiments per condition) e, mRNA levels of inflammatory genes in CTRL-MDF and Sen(IR)-MDF. (n=4 independent biological experiments per condition) f, mRNA levels of Cd38 in BMDMs treated with the indicated concentrations (ng/ml) of recombinant mouse cytokines for 24 hours. (n=3 independent biological experiments per condition) g, Heatmap of significantly upregulated proteins identified by mass spectrometry in conditioned media from CTRL-MDF and Sen(IR)-MDF. (n=4–6 independent biological experiments per condition). For in vivo experiments, data from individual mice are shown. Data show the mean ± SEM. (n= at least 3 independent experiments). Statistical significance indicated as *P<0.05, **P<0.01, and ***P<0.001; two-sided Student’s t-test.

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Extended Data Fig. 6 Single-cell RNA sequencing analysis of inflammatory, NAD consuming, and biosynthetic genes in ageing hepatocytes and liver endothelial cells.

a, Dot-plot and heatmap of the indicated genes in liver hepatocytes based on age. Logarithmic axes, base-10. b, Dot-plot and heatmap of the indicated genes in liver endothelial cells based on age. Logarithmic axes, base-10.

Extended Data Fig. 7 LPS promotes tissue NAD decline via CD38.

a, Representative gating for the splenic leukocyte populations quantified in Fig. 7c, d and Extended Data Fig. 7a. Left six panels show gating for identification of B cells and different myeloid cells, as indicated, as well as gating for CD38-positive cells in all populations. Right six panels show gating for T cell subsets, as indicated. Red arrows indicate sequential gating, pointing from parent plots towards child plots. b, Quantification of immune cell populations and CD38+ immune cells in the spleen of 3 month-old WT male mice i.p. injected with PBS or LPS for 4 weeks, and analyzed by flow cytometry. (PBS n=10 mice/group, LPS n=9 mice/group) c, Western analysis of CD38, CD157, CD68, and NAMPT in eWAT of 3 month-old WT male mice injected with PBS or LPS for 4 weeks and Image J quantification of CD38 protein levels relative to NAMPT. Each lane represents one mouse (PBS n=4 mice/group, LPS n=5 mice/group) d, mRNA levels of NAD consuming enzymes in eWAT from 3 month-old WT male mice injected with PBS or LPS for 4 weeks. (PBS n=4 mice/group, LPS n=5 mice/group) e, mRNA levels of the indicated genes in whole eWAT from 4 month-old WT and Cd38 KO male mice injected with PBS or LPS for 12 hours. (n=10 mice/group) f, Western analysis of eWAT from 4 month-old WT and Cd38 KO male mice injected with PBS or LPS for 12 hours (n=3 mice/group). g, LC-MS quantification of NAD-related metabolites in eWAT from 4 month-old WT and Cd38 KO male mice IP injected with PBS or LPS for 12 hours. (n=10 mice/group) h, LC-MS quantification of NAD-related metabolites in liver from 4 month-old WT and Cd38 KO male mice IP injected with PBS or LPS for 12 hours. (n=10 mice/group) Data from individual mice are shown for in vivo experiments. Data show the mean ± SEM. Statistical significance indicated as *P<0.05, **P<0.01, and ***P<0.001; two-sided Student’s t-test except for 7 g and 7 h one-tailed t-test was used.

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Covarrubias, A.J., Kale, A., Perrone, R. et al. Senescent cells promote tissue NAD+ decline during ageing via the activation of CD38+ macrophages. Nat Metab 2, 1265–1283 (2020). https://doi.org/10.1038/s42255-020-00305-3

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