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Angiocrine polyamine production regulates adiposity

Nature Metabolism volume 4, pages 327–343 (2022)Cite this article

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Abstract

Reciprocal interactions between endothelial cells (ECs) and adipocytes are fundamental to maintain white adipose tissue (WAT) homeostasis, as illustrated by the activation of angiogenesis upon WAT expansion, a process that is impaired in obesity. However, the molecular mechanisms underlying the crosstalk between ECs and adipocytes remain poorly understood. Here, we show that local production of polyamines in ECs stimulates adipocyte lipolysis and regulates WAT homeostasis in mice. We promote enhanced cell-autonomous angiogenesis by deleting Pten in the murine endothelium. Endothelial Pten loss leads to a WAT-selective phenotype, characterized by reduced body weight and adiposity in pathophysiological conditions. This phenotype stems from enhanced fatty acid β-oxidation in ECs concomitant with a paracrine lipolytic action on adipocytes, accounting for reduced adiposity. Combined analysis of murine models, isolated ECs and human specimens reveals that WAT lipolysis is mediated by mTORC1-dependent production of polyamines by ECs. Our results indicate that angiocrine metabolic signals are important for WAT homeostasis and organismal metabolism.

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Fig. 1: PteniΔEC mice show reduced adiposity.
Fig. 2: High vascular content and enhanced EC proliferation in PteniΔEC WAT.
Fig. 3: PteniΔEC mice are resistant to diet-induced obesity.
Fig. 4: Pten loss in ECs correlates with enhanced lipids mobilization from WAT.
Fig. 5: Lipid oxidation is essential for Pten-null EC proliferation.
Fig. 6: Endothelial-derived polyamines stimulate lipolysis.
Fig. 7: Polyamines fine-tune β-ADR-dependent lipolysis.
Fig. 8: Pharmacological modulation of Amd1 regulates adiposity.

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Image source data and Excel files of all data presented in graphs within the figures and extended data figures have been supplied in Source Data files. Separate files for each figure have been supplied.

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Acknowledgements

We thank members of the Endothelial Pathobiology and Microenvironment Group for helpful discussions. We thank the CERCA Program/Generalitat de Catalunya and the Josep Carreras Foundation for institutional support. The research leading to these results has received funding from la Fundación BBVA (Ayuda Fundacion BBVA a Equipos de Investigación Científica 2019, PR19BIOMET0061) and from SAF2017-82072-ERC from Ministerio de Ciencia, Innovación y Universidades (MCIU) (Spain). The laboratory of M.G. is also supported by the research grants SAF2017-89116R-P (FEDER/EU) co-funded by European Regional Developmental Fund (ERDF), a Way to Build Europe and PID2020-116184RB-I00 from MCEI; by the Catalan Government through the project 2017-SGR; PTEN Research Foundation (BRR-17-001); La Caixa Foundation (HR19-00120 and HR21-00046); by la Asociación Española contra el Cancer-Grupos Traslacionales (GCTRA18006CARR, also to A.C.); European Foundation for the Study of Diabetes/Lilly research grant, also to M.C.); and by the People Programme (Marie Curie Actions; grant agreement 317250) of the European Union’s Seventh Framework Programme FP7/2007-2013 and the Marie Skłodowska-Curie (grant agreement 675392) of the European Union’s Horizon 2020 research. The laboratory of A.C. is supported by the Basque Department of Industry, Tourism and Trade (Elkartek) and the department of education (IKERTALDE IT1106-16), the MCIU (PID2019-108787RB-I00 (FEDER/EU); Severo Ochoa Excellence Accreditation SEV-2016-0644; Excellence Networks SAF2016-81975-REDT), La Caixa Foundation (ID 100010434), under the agreement LCF/PR/HR17, the Vencer el Cancer foundation and the European Research Council (ERC) (consolidator grant 819242). CIBERONC was co-funded with FEDER funds and funded by Instituto de Salud Carlos III (ISCIII). The laboratory of M.C. is supported by the ERC under the European Union’s Horizon 2020 research and innovation programme (grant agreement 725004) and CERCA Programme/Generalitat de Catalunya (M.C.). The laboratory of D.S. is supported by research grants from MINECO (SAF2017-83813-C3-1-R, also to L.H., cofounded by the ERDF), CIBEROBN (CB06/03/0001), Government of Catalonia (2017SGR278) and Fundació La Marató de TV3 (201627-30). The laboratory of R.N. is supported by FEDER/Ministerio de Ciencia, Innovación y Universidades-Agencia Estatal de Investigación (RTI2018-099413-B-I00 and and RED2018-102379-T), Xunta de Galicia (2016-PG057 and 2020-PG015), ERC under the European Union’s Horizon 2020 research and innovation programme (grant agreement 810331), Fundación BBVA, Fundacion Atresmedia and CIBEROBN, which is an initiative of the ISCIII of Spain, which is supported by FEDER funds. The laboratory of J.A.V. is supported by research grants from MICINN (RTI2018-099250-B100) and by La Caixa Foundation (ID 100010434, LCF/PR/HR17/52150009). P.M.G.-R. is supported by ISCIII grant PI15/00701 cofinanced by the ERDF, A Way to Build Europe. Personal support was from Marie Curie ITN Actions (E.M.), Juan de la Cierva (IJCI-2015-23455, P.V.), CONICYT fellowship from Chile (S.Z.), Vetenskapsradet (Swedish Research Council, 2018-06591, L.G.) and NCI K99/R00 Pathway to Independence Award (K99CA245122, P. Castel).

Author information

Author notes

  1. These authors jointly supervised this work: Arkaitz Carracedo, Mariona Graupera.

Authors and Affiliations

  1. Endothelial Pathobiology and Microenviroment Group, Josep Carreras Leukaemia Research Institute (IJC), Badalona, Barcelona, Spain

    Erika Monelli, Pilar Villacampa, Anabel Martinez-Romero, Judith Llena, Leonor Gouveia, Laia Muixi, Sandra D. Castillo & Mariona Graupera

  2. Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance (BRTA), Bizkaia Technology Park, Derio, Spain

    Amaia Zabala-Letona, Ainara Martinez-Gonzalez, Natalia Martín-Martín, Lorea Valcarcel-Jimenez, Sonia Fernandez-Ruiz & Arkaitz Carracedo

  3. Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Instituto de Salud Carlos III, Madrid, Spain

    Amaia Zabala-Letona, Natalia Martín-Martín, Arkaitz Carracedo & Mariona Graupera

  4. CIMUS, University of Santiago de Compostela-Instituto de Investigación Sanitaria, Santiago de Compostela, Spain

    Daniel Beiroa & Rubén Nogueiras

  5. Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain

    Daniel Beiroa, Dolors Serra, Laura Herrero, Pablo Garcia-Roves & Rubén Nogueiras

  6. Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden

    Leonor Gouveia

  7. Neuronal Control of Metabolism Laboratory, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain

    Iñigo Chivite & Marc Claret

  8. Department of Biochemistry and Physiology, School of Pharmacy and Food Sciences, Institut de Biomedicina de la Universitat de Barcelona (IBUB), Universitat de Barcelona, Barcelona, Spain

    Sebastián Zagmutt, Dolors Serra & Laura Herrero

  9. Department of Physiological Sciences, Faculty of Medicine and Health Sciences, University of Barcelona and Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain

    Pau Gama-Perez & Pablo Garcia-Roves

  10. Department of Endocrinology, IDIBAPS, Hospital Clinic, University of Barcelona, Barcelona, Spain

    Oscar Osorio-Conles & Josep Vidal

  11. Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain

    Oscar Osorio-Conles, Josep A. Villena, Josep Vidal & Marc Claret

  12. Traslational prostate cancer Research lab, CIC bioGUNE-Basurto, Biocruces Bizkaia Health Research Institute, Barakaldo, Spain

    Natalia Martín-Martín & Arkaitz Carracedo

  13. Department of Biochemistry and Molecular Pharmacology, New York University Grossman School of Medicine, New York, NY, USA

    Pau Castel

  14. Molecular Genetics of Angiogenesis Group, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain

    Irene Garcia-Gonzalez & Rui Benedito

  15. Laboratory of Metabolism and Obesity, Vall d’Hebron-Institut de Recerca, Universitat Autònoma de Barcelona, Barcelona, Spain

    Josep A. Villena

  16. Laboratory of Molecular Metabolism, The Rockefeller University, New York, NY, USA

    Paul Cohen

  17. Galician Agency of Investigation, Xunta de Galicia, La Coruña, Spain

    Rubén Nogueiras

  18. Biochemistry and Molecular Biology Department, University of the Basque Country (UPV/EHU), Bilbao, Spain

    Arkaitz Carracedo

  19. Ikerbasque; Basque Foundation for Science, Bilbao, Spain

    Arkaitz Carracedo

Authors
  1. Erika Monelli
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  2. Pilar Villacampa
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  18. Irene Garcia-Gonzalez
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  19. Josep A. Villena
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  20. Sonia Fernandez-Ruiz
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  21. Dolors Serra
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  26. Paul Cohen
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  27. Rubén Nogueiras
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  29. Arkaitz Carracedo
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  30. Mariona Graupera
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Contributions

E.M., M.C., A.C. and M.G. conceived the project. E.M., P.V., L.G., A.Z.-L., A.M.-R., J.L.L., D.B., L.G., I.C., S.Z., P.G.-P. O.O.-C., L.M., A.M.-G., S.D.C., N.M.-M, P. Castel, L.V.-J., I.G.-G. and S.F.-R. performed experiments and analyzed data with the supervision of J.V., D.S., L.H., R.B., P.G.-R., R.N., P. Cohen, M.C., A.C. and M.G. E.M., P.V., L.G., S.D.C., A.C. and M.G. wrote the manuscript and designed the Figures. L.H., D.B., R.N., P.G.-R., M.C., A.C. and M.G. provided funding.

Corresponding author

Correspondence to Mariona Graupera.

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Competing interests

M.G. has a research agreement with Merck and Venthera. None of those have a relationship with adipose tissue vasculature. The remaining authors declare no competing interests.

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Nature Metabolism thanks the anonymous reviewers for their contribution to the peer review of this work. Primary handling editor: Christoph Schmitt.

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Extended data

Extended Data Fig. 1 Validation of Pten deletion in PteniΔEC mice.

a) Enrichment ratios of expression of VE-cadherin (Cdh5) and tissue-specific gene in endothelial cell-specific mRNA preparations from eWAT, BAT, muscle and liver after ribosome immunoprecipitation from RibotagiHAEC mice (eWAT n = 3, BAT, muscle and liver n = 2). (b) Representative images of flat-mounted eWAT from 5-week-old control RibotagiHAEC mice stained with HA (white), ICAM2 (green) and isolectin (IB4) (blue). White islets show high magnification of selected regions shown below. (c) Quantification of Pten mRNA levels in WAT, BAT liver and muscle endothelium from RibotagiHAEC and PteniΔEC- RibotagiHAEC at 5 weeks of age (n = 6 per group). (d-g) Western blot analysis of Pten expression in (d) adipose-EC obtained from control (n = 5) and PteniΔEC mice (n = 6), (e) lung-EC obtained from control (n = 6) and PteniΔEC mice (n = 6), (f) muscle-EC obtained from control (n = 4) and PteniΔEC mice (n = 5) and (g) BAT-EC obtained from control (n = 3) and PteniΔEC mice (n = 6). Data represent mean ± SEM (error bars). Samples represent biological replicates. Statistical analysis was performed by the two-sided Mann-Whitney test (Extended Data Fig. 1c).

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Extended Data Fig. 2 Endothelial Pten loss leads to reduced fat mass, and it is not associated with fibrosis, altered differentiation or cell death.

(a) Tissue weight in control and PteniΔEC mice at 12 weeks of age (control n = 8, PteniΔEC n = 6). (b and c) Body composition analysis of control and PteniΔEC mice at 14 weeks (control n = 7, PteniΔEC n = 5) by MRI. (d and e) Gene expression analysis of fibrosis markers in whole tissue extracts from (d) eWAT (control n = 4, PteniΔEC n = 6) and (e) iWAT (control n = 5, PteniΔEC n = 6) from control and PteniΔEC mice at 12 weeks of age. (f) Representative microscopic images showing in vitro adipocyte differentiation from preadipocytes (contained in the stromal vascular fraction (SVF) obtained from iWAT depots from 6-week-old control and PteniΔEC mice. A representative image of cultured SVF prior to differentiation is shown to the left. (g and h) Gene expression analysis of adipocyte differentiation markers in whole tissue extracts from (g) eWAT (control n = 5, PteniΔEC n = 4) and (h) iWAT (control n = 4, PteniΔEC n = 5) from control and PteniΔEC mice at 12 weeks of age. (i and j) Representative confocal images of (i) eWAT and (j) iWAT sections stained with cleaved caspase-3 (red) and DAPI (white) from 12-week-old control and PteniΔEC mice. (k) Levels of leptin in serum of control and PteniΔEC mice at 14 weeks of age (control n = 5, PteniΔEC n = 4). Data represent mean ± SEM (error bars). Samples represent biological replicates. Statistical analysis was performed by the two-sided Mann-Whitney test (Extended Data Fig. 2b, c, d, e, g, k).

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Extended Data Fig. 3 Molecular and histological vascular characterization in several tissues of control and PteniΔEC mice.

(a) Representative images of CD31-stained blood vessels (white) in sections from brain, muscle, liver and heart and IB4-stained blood vessels (white) in cryosections of BAT and from control (upper panels) and PteniΔEC mice (lower panels) at 12 weeks of age. (b) Quantification of vessel density expressed as percentage of total area in brain, muscle, liver, heart, and BAT sections from control and PteniΔEC mice at 12 weeks of age (brain n = 8, muscle, liver and heart control n = 4, PteniΔEC n = 3, BAT n = 4). (c) Gene expression analysis of endothelial markers Pecam1 (left graph) and Cdh5 (right graph) in whole tissue extracts from control and PteniΔEC mice at 5 weeks of age (BAT n = 5, muscle n = 4, liver n = 8, heart n = 4, lung n = 9, intestine n = 5, eWAT=5, iWAT=5). (d) VegfA gene expression analysis in whole tissue extracts from eWAT and iWAT from control (n = 5) and PteniΔEC (n = 9) mice at 12 weeks of age. (e) Representative images of CD31 (white) and Ter119 (red) stained sections of control and PteniΔEC eWAT at 12 weeks of age. (h) Representative hematoxylin and eosin staining of BAT sections from control and PteniΔEC mice at 12 weeks of age. Data represent mean ± SEM (error bars). Samples represent biological replicates. Statistical analysis was performed by the two-sided Mann-Whitney test (Extended Data Fig. 3b, c, d).

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Extended Data Fig. 4 In vivo characterization upon endothelial Pten loss.

(a,i) Scheme illustrating the experimental protocol. (b) Representative images of eWAT from control and PteniΔEC mice at 14 and 19 weeks of age. (c) eWAT pad weight at 14 (control n = 15, PteniΔEC n = 16) and 19 (control n = 13, PteniΔEC n = 10) weeks of age, (d) Quantification of adipocyte area of eWAT at 14 (control n = 8, PteniΔEC n = 10) and 19 (control n = 7, PteniΔEC n = 8) weeks of age, (e) iWAT pad weight at 14 (control n = 14, PteniΔEC n = 16) and 19 (control n = 13, PteniΔEC n = 10) weeks of age from control and PteniΔEC mice. (f) Tissue weight in control and PteniΔEC mice at 14 weeks of age (n = 11). (g) Confocal images of eWAT whole-mount staining with IB4 (red) from control and PteniΔEC mice at 14 and 19 weeks of age. (h) Quantification of IB4-positive area in eWAT depots from control and PteniΔEC mice at 14 (n = 6 per group) and 19 weeks of age (n = 7 per group). (j) Representative images of eWAT from control and PteniΔEC mice at 5 and 12 weeks of age. (k) eWAT pad weight in control and PteniΔEC mice at 5 (control n = 9, PteniΔEC n = 10) and 12 (control n = 7, PteniΔEC n = 5) weeks of age. (l) Quantification of adipocyte area of eWAT from control and PteniΔEC mice at 5 (n = 4) and 12 (n = 4) weeks of age. (m) iWAT pad weight in control and PteniΔEC mice at 5 (control n = 9, PteniΔEC n = 10) and 12 (control n = 7, PteniΔEC n = 5) weeks of age. (n) Tissue weight in control and PteniΔEC mice at 12 weeks of age (control n = 7, PteniΔEC n = 5). (o) Confocal images of eWAT whole-mount staining with IB4 (red) from control and PteniΔEC mice at 5 and 12 weeks of age. (p) Quantification of IB4-positive area in eWAT depots from control and PteniΔEC mice at 5 and 12 weeks of age (control n = 7, PteniΔEC n = 5). Data represent mean ± SEM (error bars). Samples represent biological replicates. Statistical analysis was performed by the two-sided Mann-Whitney test (Extended Data Fig. 4c, d, e, f, h, k, l, m, n, p).

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Extended Data Fig. 5 Low endothelial Pten expression correlates with high vascular content in mouse and human white adipose tissue.

(a) Representative confocal images of wild-type eWAT whole-mount staining with IB4 (red) after 12 weeks of chow diet or HFD. (b) Quantification of IB4 positive area in eWAT from wild-type mice exposed to chow diet or HFD for 12 weeks (chow diet n = 4, HFD n = 5). (c) In vivo Pten mRNA expression levels in adipose endothelial cells from wild-type RibotagiHAEC mice after exposure to chow diet or HFD for 12 weeks (chow diet n = 5, HFD n = 4). (d) Representative confocal images of visceral adipose tissue (VAT) whole-mount stained with CD31 (red) from non-obese and patients with obesity. (e) Quantification of vessel branches in VAT whole-mount stained with CD31 from non-obese and patients with obesity (non-obese n = 6, obese n = 10). (f) Pten mRNA expression levels in VAT tissue extracts from non-obese and patients with obesity (non-obese n = 5, obese n = 6). Data represent mean ± SEM (error bars). Samples represent biological replicates. Statistical analysis was performed by the two-sided Mann-Whitney test (Extended Data Fig. 5b, c, e, f).

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Extended Data Fig. 6 Low endothelial Pten expression correlates with improved glucose systemic metabolism in mice.

(a) Tissue weight in control and PteniΔEC mice exposed to HFD for 10 weeks (control n = 9, PteniΔEC n = 4). (b) Insulin tolerance test (ITT) performed in control and PteniΔEC mice fed with HFD for 10 weeks (control n = 13, PteniΔEC n = 10). Bars to the right show AUC quantification of blood glucose monitoring during ITT (control n = 13, PteniΔEC n = 10). (c) Basal insulin levels and (d) HOMA-IR index in control and PteniΔEC mice fed with HFD for 10 weeks (control n = 6, PteniΔEC n = 4). (e) Masson trichrome fibrosis staining in eWAT and iWAT sections from control and PteniΔEC mice exposed to HFD for 10 weeks. (f) Gene expression analysis of fibrosis markers in whole tissue extracts from eWAT (control n = 7, PteniΔEC n = 4) from control and PteniΔEC mice exposed to HFD for 10 weeks. (g) Tissue weight in control and PteniΔEC mice exposed to HFD for 34 weeks (control n = 9, PteniΔEC n = 8). (h) ITT performed in control and PteniΔEC mice fed with HFD for 30 weeks (control n = 10, PteniΔEC n = 9). Bars to the right show AUC quantification of blood glucose monitoring during ITT. (i) Basal insulin levels and (j) HOMA-IR index in control and PteniΔEC mice fed with HFD for 34 weeks (control n = 9, PteniΔEC n = 8). (k) Masson trichrome fibrosis staining in eWAT and iWAT sections from control and PteniΔEC mice exposed to HFD for 34 weeks. Data represent mean ± SEM (error bars). Samples represent biological replicates. Statistical analysis was performed by the two-sided Mann-Whitney test (Extended Data Fig. 6a, c, d, f, i, j) and 2-way ANOVA with Bonferroni correction (Extended Data Fig. 6b, h).

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Extended Data Fig. 7 Pten-null ECs proliferation depends on lipid oxidation.

(a-c) Endothelial expression of lipid catabolic genes analysed by qPCR and normalized by mL32 gene expression in (a) BAT (control RibotagiHAEC n = 5, PteniΔEC- RibotagiHAEC n = 4), (b) muscle (control RibotagiHAEC n = 5, PteniΔEC- RibotagiHAEC n = 5), (c) and liver (control RibotagiHAEC n = 5, PteniΔEC n = 4) from control RibotagiHAEC and PteniΔEC- RibotagiHAEC mice at 5 weeks of age. (d) Glucose uptake measurement in control and PteniΔEC endothelial cells (control n = 6, PteniΔEC n = 8). (e and f) In vitro expression analysis of (e) lipid catabolic genes and (f) Cd36 by qPCR in control and PteniΔEC lung-derived primary endothelial cells (lung-EC) (control n = 4, PteniΔEC n = 6). (g) Fatty Acid β-Oxidation (FAO) in lung-EC from control and PteniΔEC mice (n = 8 per group). (h) OCR in control and PteniΔEC lung-EC in lipid-enriched medium. (i) Bars show OCR quantification from control and PteniΔEC lung-EC in lipid-enriched medium (control n = 8, PteniΔEC n = 10). (j) Tissue weight in control and PteniΔEC mice treated with vehicle or etomoxir for 5 weeks (control - vehicle n = 15, control - etomoxir n = 9, PteniΔEC - vehicle n = 11, PteniΔEC - etomoxir n = 10). (k) Representative images of IB4 stained blood vessels (red) in flat-mounted eWAT from control, PteniΔEC, PteniΔEC-Pgc1βiΔEC and Pgc1βiΔEC mice at 10 weeks of age. (l) Quantification of IB4 positive area in eWAT from control, PteniΔEC, PteniΔEC-Pgc1βiΔEC and Pgc1βiΔEC mice at 10 weeks of age (control n = 9, PteniΔEC n = 6, PteniΔEC-Pgc1βiΔEC n = 8, Pgc1βiΔEC n = 5). (m) eWAT pad weight of control PteniΔEC, PteniΔEC-Pgc1βiΔEC and Pgc1βiΔEC mice at 10 weeks of age (control n = 18, PteniΔEC n = 5, PteniΔEC - Pgc1βiΔEC n = 10, Pgc1βiΔEC n = 10). Data represent mean ± SEM (error bars). Samples represent biological replicates. All statistical analysis was performed by the two-sided Mann-Whitney test (Extended Data Fig. 7a, b, c, d, e, f, e, i, j) and one-way ANOVA with Bonferroni correction (Extended Data Fig. 7l, m).

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Extended Data Fig. 8 Loss of endothelial Pten results in increased polyamine levels.

(a) Schematic representation of control and PteniΔEC eWAT explant experiment. eWAT from 5 weeks of age control and PteniΔEC mice were cut in ~25 mg pieces, placed in 500ul of DMEM low glucose + 0,5% FFA free BSA, and incubated for the indicated time points. (b) Experimental design of conditioned media collection and fractioning. A 3 kDa cut off filter retained the protein and vesicle fraction, whereas the metabolite-rich fraction was collected as the flow-through. The lipolytic effect of both fractions was tested on eWAT explants of wild-type mice. (c) Label-free 13C fraction of metabolites related to polyamines biosynthesis in adipose-ECs from control and PteniΔEC mice (n = 6 per group) from Fig. 6g. MET: Methionine; SAM: S-Adenosylmethionine; dcSAM: Decarboxylated S-adenosylmethionine; MTA: 5´ Methylthioadenosine. Data represent mean ± SEM (error bars). Statistical analysis was performed by t-test (Extended Data Fig. 8c).

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Extended Data Fig. 9 Loss of endothelial Pten results in increased label-free polyamine levels.

(a, b) Schematic representation of the polyamine metabolic pathway and expression of the indicated metabolites in (d) adipose endothelial cells (control n = 6, PteniΔEC n = 6) and (e) eWAT (control n = 8, PteniΔEC n = 7) measured by LCMS. Data represent mean ± SEM (error bars). Statistical analysis was performed by t-test (Extended Data Fig. 9a,b).

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Extended Data Fig. 10 Spermidine supplementation in mice exposed to HFD ameliorates glucose systemic metabolism.

(a, b) Positive control of lipolysis in (a) WAT tissue explants and (b) primary adipocytes. (c) Positive control of cAMP production in primary adipocytes. (d) Epinephrine and norepinephrine level in control eWAT measured by LCMS (n = 5). Data represent mean ± SEM (error bars). (e) Tissue weight of wild-type mice fed with HFD and treated with vehicle or spermidine for 6 weeks (vehicle n = 9, spermidine n = 10). (f) GTT performed in wild-type fed with HFD and treated with vehicle or spermidine for 6 weeks (vehicle n = 9, spermidine n = 7). (g) AUC quantification of blood glucose monitoring during GTT. (h) Food intake measurement in wild-type mice fed with HFD and treated with vehicle or spermidine for 6 weeks (n = 7). (i) Body weight curve of wild-type mice fed with HFD and treated with vehicle or spermidine with pair-feeding conditions after week 10. PF, Pair feeding applied to control mice (n = 7). (j) Body weight at sacrifice values of chow and HFD wild-type mice used for experiments represented in Fig. 7k (n = 12 per group). (k) Amd1 mRNA expression levels analysed by qPCR normalized by mL32 gene expression in eWAT endothelium from control RibotagiHAEC and PteniΔEC- RibotagiHAEC (control RibotagiHAEC n = 7, PteniΔEC- RibotagiHAEC n = 8). (l) Western blot analysis of Amd1, S6K (phosphorylated and total) in adipose-derived primary endothelial cells from PteniΔEC mice after treatment with vehicle (DMSO) or mTOR inhibitor (rapamycin, 1 μm) (n = 6). Red arrowhead shows residual phosphorylated Akt signal. (c) Quantification of Amd1 signal obtained in immunoblots showed in (m) (vehicle n = 6, rapamycin n = 5). Data represent mean ± SEM (error bars). Samples represent biological replicates. Statistical analysis was performed by the two-sided Mann-Whitney test (Extended Data Fig. 10a, b, c, e, g, h, j, m) and ANOVA with Bonferroni correction (Extended Data Fig. 10f, i).

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Supplementary information

Supplementary Information

This file contains four sets of data: (1) List of reagents; (2) List of primers; (3) List of antibodies; and (4) Information about the human cohorts.

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Monelli, E., Villacampa, P., Zabala-Letona, A. et al. Angiocrine polyamine production regulates adiposity. Nat Metab 4, 327–343 (2022). https://doi.org/10.1038/s42255-022-00544-6

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