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Fgr kinase is required for proinflammatory macrophage activation during diet-induced obesity

Nature Metabolism volume 2, pages 974–988 (2020)Cite this article

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Abstract

Proinflammatory macrophages are key in the development of obesity. In addition, reactive oxygen species (ROS), which activate the Fgr tyrosine kinase, also contribute to obesity. Here we show that ablation of Fgr impairs proinflammatory macrophage polarization while preventing high-fat diet (HFD)-induced obesity in mice. Systemic ablation of Fgr increases lipolysis and liver fatty acid oxidation, thereby avoiding steatosis. Knockout of Fgr in bone marrow (BM)-derived cells is sufficient to protect against insulin resistance and liver steatosis following HFD feeding, while the transfer of Fgr-expressing BM-derived cells reverts protection from HFD feeding in Fgr-deficient hosts. Scavenging of mitochondrial peroxides is sufficient to prevent Fgr activation in BM-derived cells and HFD-induced obesity. Moreover, Fgr expression is higher in proinflammatory macrophages and correlates with obesity traits in both mice and humans. Thus, our findings reveal the mitochondrial ROS–Fgr kinase as a key regulatory axis in proinflammatory adipose tissue macrophage activation, diet-induced obesity, insulin resistance and liver steatosis.

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Fig. 1: Lack of Fgr prevents proinflammatory M1-like polarization of BMDMs.
Fig. 2: Lack of Fgr prevents AT-CM polarization of BMDMs.
Fig. 3: Fgr-deficient mice are protected against HFD-induced obesity.
Fig. 4: Lack of Fgr prevents liver steatosis through increased FAO in a HFD.
Fig. 5: Lack of Fgr in BM-derived cells protects from HFD-induced liver steatosis.
Fig. 6: Loss of Fgr in immune cells prevents proinflammatory WAT macrophage infiltration.
Fig. 7: ROS scavenging in the immune cells recapitulates Fgr KO phenotype.
Fig. 8: Fgr expression in obese mice and humans.

Data availability

The data that support the findings of this study are available from the corresponding author upon request. Accession codes to public repositories are GSE64770 for HMDP HF/HS adipose tissue, GSE38705 for HMDP macrophages and GSE70353 for human METSIM study. HMDP and METSIM data are also available at https://systems.genetics.ucla.edu/. Source data are provided with this paper.

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Acknowledgements

We thank C. Lowell for the kind gift of the Fgr−/− mice; M. Murphy for the kind gift of MitoQ; M. Cueva and R. Álvarez for mouse work; A. Molina-Iracheta and R. Doohan for histology; and A.J. Brownstein, A. Divakaruni and A. Jones for macrophage work. We thank the individuals who participated in the METSIM study. The METSIM study was supported by grants from the Academy of Finland (no. 321428), Sigrid Juselius Foundation, Finnish Foundation for Cardiovascular Research, Centre of Excellence of Cardiovascular and Metabolic Diseases and the Academy of Finland (to M.L.). Work in the laboratory of J.A.E. is funded by the CNIC and a grant by Ministerio de Ciencia, Innovación e Universidades (MICINN), Agencia Estatal de Investigación (AEI) and Fondo Europeo de Desarrollo Regional (FEDER; SAF2015-65633-R and RTI2018-099357-B-I00), the EU (UE0/MCA317433), the Biomedical Research Networking Center on Frailty and Healthy Ageing (CIBERFES-ISCiii) and the HFSP agency (RGP0016/2018). Work in the laboratory of D.S. is funded by the CNIC; the European Research Council (ERC-2016-Consolidator Grant 725091); the European Commission (635122-PROCROP H2020); MICINN, AEI and FEDER (SAF2016-79040-R and PID2019-108157RB); Comunidad de Madrid (B2017/BMD-3733 Immunothercan-CM); FIS-Instituto de Salud Carlos III, MICINN and FEDER (RD16/0015/0018-REEM); the Acteria Foundation; Atresmedia (Constantes y Vitales prize); and Fundació La Marató de TV3 (201723). Work in the laboratory of O.S.S. is funded by National Institutes of Health (NIH; R01 DK099618-05, R01 CA232056-01, R21AG060456-01 and R21 AG063373-01) and the American Diabetes Association (1-19-IBS-049). Work in laboratory of A.J.L. was supported by NIH-PO1HL028481 and NIH-R01DK117850 (A.J.L.). Work in the laboratory of M.L. was funded by the Academy of Finland. Work in the laboratory of J.P.B. was funded by Spanish Ministry of Science, Innovation and Universities (MCINU/FEDER; grants SAF2016-78114-R and RED2018‐102576‐T), Instituto de Salud Carlos III (CB16/10/00282), Junta de Castilla y León (Escalera de Excelencia CLU-2017-03), Ayudas Equipos Investigación Biomedicina 2017 Fundación BBVA and Fundación Ramón Areces. The CNIC is supported by the Instituto de Salud Carlos III (ISCIII), MICINN and the Pro CNIC Foundation and is a Severo Ochoa Center of Excellence (SEV-2015-0505). K.C.K. is funded by NIH-K99 DK120875 and AHA Fellowship 18POST33990256. S.I. is funded by RYC-2016-19463 and RTI2018-094484-B-I00. The funders had no role in the study design, data collection and interpretation, nor the decision to submit the work for publication.

Author information

Author notes

  1. These authors contributed equally: Rebeca Acín-Pérez, Salvador Iborra.

Authors and Affiliations

  1. Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain

    Rebeca Acín-Pérez, Salvador Iborra, Yolanda Martí-Mateos, Ruth Conde-Garrosa, Mª del Mar Muñoz, Raquel Martínez de Mena, Concepción Jiménez, David Sancho & José Antonio Enríquez

  2. Metabolism Theme, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA

    Rebeca Acín-Pérez, Anton Petcherski & Orian S. Shirihai

  3. Department of Immunology, Ophthalmology and ENT, School of Medicine, Universidad Complutense, Madrid, Spain

    Salvador Iborra & Emma C. L. Cook

  4. Department of Medicine, Division of Cardiology, University of California, Los Angeles, Los Angeles, CA, USA

    Karthickeyan Chella Krishnan & Aldon J. Lusis

  5. Institute of Functional Biology and Genomics, University of Salamanca, CSIC, Salamanca, Spain

    Juan Pedro Bolaños

  6. Institute of Biomedical Research of Salamanca, University Hospital of Salamanca, University of Salamanca, CSIC, Salamanca, Spain

    Juan Pedro Bolaños

  7. Centro de Investigación Biomédica en Red sobre Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain

    Juan Pedro Bolaños & José Antonio Enríquez

  8. Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland

    Markku Laakso

  9. Department of Microbiology, Immunology and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, USA

    Aldon J. Lusis

  10. Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA

    Aldon J. Lusis

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  1. Rebeca Acín-Pérez
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Contributions

Conceptualization: R.A-P., S.I., C.J., D.S. and J.A.E.; Methodology: R.A-P., S.I., A.P., M.M.M. and R.M.d.M.; Validation: R.A-P., S.I., R.C.-G., A.P., M.M.M., R.M.d.M. and K.C.K. Investigation; R.A-P., S.I., E.C.L.C, A.P., M.M.M., E.C.L.C., R.M.d.M. and Y.M.-M.; Writing of original draft: R.A-P., S.I., D.S. and J.A.E.; Writing of the review and editing: R.A-P., S.I., A.P., C.J., O.S.S., D.S. and J.A.E.; Funding acquisition: S.I., O.S.S., D.S. and J.A.E.; Resources: M.L., J.P.B., A.J.L., O.S.S., D.S. and J.A.E; and supervision: R.A-P., S.I., C.J., D.S. and J.A.E.

Corresponding authors

Correspondence to David Sancho or José Antonio Enríquez.

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Extended data

Extended Data Fig. 1 Activation of Fgr is necessary for M1-like macrophage polarization.

a, BMDM from WT and FgrKO mice untreated or treated with LPS + IFNγ were analyzed by flow cytometry for NO2, IL12p40, TNFα, CD86 and CD40 (n = 6). b-c, Measure of H2O2 (b) and superoxide (c) in WT BMDM treated under the conditions indicated (n = 11). d, Pyruvate-malate and (e) succinate driven respiration in isolated liver mitochondria in the indicated treatments (n = 6). f, Maximal respiratory capacity of mitochondrial complex I, II and IV in isolated liver mitochondria in the indicated treatments (n = 6). g, BMDM from WT and FgrKO mice untreated or treated with xanthine/xanthine oxidase (X/XO), LPS, the combination of both or adipose conditioned media (AT) were analyzed by flow cytometry for NOS2, MHC-II, NOS2 and CD86. WT, n = 6 for all conditions but 33% AT where n = 3, FgrKO, n = 3. Representative unnormalized seahorse profile of oxygen consumption of BMDM from WT and FgrKO mice treated with LPS+ IFNγ for 16 h (overnight, o/n, h) or 4 h (i) (n = 7 for untreated or n = 4 for treated). Representative unnormalized oxygen consumption analysis of IFNγ primed (pIFNγ) BMDM from WT (left panels) and FgrKO (right panels) treated with (j) LPS, (k) LPS plus NPA and (l) LPS plus NAC at the start of the SeaHorse assay (n = 3). m, Complex II immunocapture and phosphorylation analysis by western blot of SDHA in WT BMDM untreated or treated with LPS+ IFNγ for 4hrs. (a,g) *, P <0.05; **, P <0.01; ***, P <0.001; ****, P <0.0001. 2-way ANOVA and Tukey post-hoc test was used. Each point represents a biological replicate. Data are the mean ± SEM.

Source data

Extended Data Fig. 2 Fgr-deficient mice are protected against high fat diet induced obesity.

a, Absolute weight of WT and Fgr KO mice in NNT WT or KO background fed in high fat diet (HFD) for 8 weeks (in NNTWT background, n = 11; in NNTKO background n = 26). b, Insulin (upper panel) and c-peptide (bottom panel) levels after glucose injection (insulin release assay) in WT (solid circles) and FgrKO (open triangles) mice in NNTWT or NNTKO background fed high fat diet. (In b for insulin levels: in NNT WT background, n = 7; in NNTKO background n≥18: for c-peptide levels, n = 7). c-d, Water (c) and food (d) intake by mice assessed in metabolic cages for 48 hours. e, O2 consumption (VO2), (f) CO2 production (VCO2), and (g) energy expenditure (EE) measured in mice in metabolic cages for 48 hours (n = 6). Each point represents a biological replicate. Data are the mean ± SEM.

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Extended Data Fig. 3 Fgr-deficient mice have normal glucose metabolism in standard diet.

a, Weight gain (left panel) and absolute weight (right panel) of WT and Fgr KO mice in NNT WT or KO background fed in standard diet (SD) for 8 weeks (in NNT WT background, n≥12; in NNT KO background n≥8). b-c, Glucose (GTT, b) and insulin tolerance test (ITT, c) in mice fed in SD for 10 weeks (in NNT WT background, n≥14; in NNT KO background n≥8). d, Basal insulin (upper panel) and c-peptide (bottom panel) levels in WT and FgrKO mice in NNTWT or NNTKO background fed HFD for 8–10 weeks. e-f, Fold induction (e) and absolute levels (f) of insulin (upper panel) and c-peptide (bottom panel) amount compared to basal level after glucose injection (insulin release assay) in WT (solid circles) and FgrKO (open triangles) mice in NNTWT or NNTKO background fed high fat diet. (In e-f for insulin levels: in NNT WT background, n≥12; in NNT KO background n≥13: for c-peptide levels, n≥7). g-i, Food and water intake (g), O2 consumption (VO2) and CO2 production (VCO2) (h), and respiratory quotient (RQ) and energy expenditure (EE) (i) measured in mice in SD after being in metabolic cage analysis for 48 hours. g-i, Top panels represent values normalized by body weight. Bottom panels represent values unnormalized (n≥7). Signification assessed by unpaired t-test. *, P <0.05; **, P <0.01; ***, P <0.001; ****, P <0.0001. Each point represents a biological replicate. Data are the mean ± SEM.

Source data

Extended Data Fig. 4 Lipid profile and liver fatty acid oxidation is normal in mice lacking Fgr.

a, Representative H&E staining of WAT paraffin sections of the indicated genotypes in SD. Scale bars corresponds to 500 µm. b, Representative ORO staining of OCT liver sections of the indicated genotypes in SD. Scale bars corresponds to 100 µm. c, Quantification of ORO staining performed as in b). d, Serum lipid profile for triglycerides (upper panel), HDL (middle panel) and total cholesterol (bottom panel) in WT and Fgr KO mice in NNT WT or KO background fed in SD for 8 weeks (in NNT WT background, n≥12; in NNT KO background n≥9). e, Enzymatic activities of citrate synthase (CS, upper panel), short chain 3-hydroxyacyl CoA dehydrogenase (SCHA) versus CS (middle panel) and isocitrate dehydrogenase (ISDH) versus CS (bottom panel) in the different mouse genotypes in SD measured by spectrophotometry (n≥10). f, Ketone bodies (KB, upper panel), Glucose (middle panel), and protein (bottom panel) concentration in urine in the indicated mouse genotypes in SD (for glucose and protein, n≥8, for KB, n≥14). Signification assessed by t-test *, P <0.05; **, P <0.01; ***; P <0.001. Each point represents a biological replicate. Data are the mean ± SEM.

Source data

Extended Data Fig. 5 BM transplantation weight under high fat diet.

a, Weight over time in mice under high fat diet after BM transplantation of the indicated genotypes (n = 16). b, Analysis of OCR non normalized by cell counts in WAT infiltrated macrophages isolated from mice fed high fat diet, using glucose oxidation (GO: glucose plus pyruvate plus glutamine) or fatty acid oxidation or (FAO: palmitoyl-CoA + carnitine) as substrates in the assay media (n = 3). c, Weight over time in WT mice under high fat diet with and without NAC supplementation in the drinking water (n = 10). d, Weight over time in mito-catalase (mCAT) BM grafted mice under high fat diet (n = 9). One-way ANOVA with Sidak correction for multiple comparisons. *, P <0.05; **, P <0.01; ***, P <0.001; ****, P <0.0001. Each point represents a biological replicate. Data are the mean ± SEM.

Source data

Extended Data Fig. 6 Loss of Fgr prevents proinflammatory WAT macrophage infiltration induced by HFD.

a, Representative flow cytometry dot plots of WAT-infiltrated CD11c+ (M1-like, left panel), CD206+ (M2-like) and inflammatory double negative (right panel) macrophages form WT and Fgr-deficient (NNTKO in both cases) mice fed with standard diet (SD) or high-fat diet (HFD). b, Analysis of total amount of WAT-infiltrated inflammatory CD11c+ and double negative macrophages on HFD fed mice in WT and FgrKO mice. c, d, Representative flow cytometry histograms (c) and quantification (d) of iNOS expression in the indicated ATM populations. e, f, Representative flow cytometry histograms (c) and quantification (d) of MerTK expression in the indicated ATM populations. One-way ANOVA with Sidak correction for multiple comparisons. **, P <0.01; ****, P <0.0001. Each point represents a biological replicate. Data are the mean ± SEM.

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Acín-Pérez, R., Iborra, S., Martí-Mateos, Y. et al. Fgr kinase is required for proinflammatory macrophage activation during diet-induced obesity. Nat Metab 2, 974–988 (2020). https://doi.org/10.1038/s42255-020-00273-8

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  • DOI: https://doi.org/10.1038/s42255-020-00273-8

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