Angiocrine polyamine production regulates adiposity (original) (raw)

Data availability

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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  3. Amaia Zabala-Letona
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  4. Anabel Martinez-Romero
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  5. Judith Llena
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  6. Daniel Beiroa
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  7. Leonor Gouveia
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  8. Iñigo Chivite
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  9. Sebastián Zagmutt
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  10. Pau Gama-Perez
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  11. Oscar Osorio-Conles
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  12. Laia Muixi
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  13. Ainara Martinez-Gonzalez
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  14. Sandra D. Castillo
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  15. Natalia Martín-Martín
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  16. Pau Castel
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  17. Lorea Valcarcel-Jimenez
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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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  22. Laura Herrero
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  23. Rui Benedito
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  24. Pablo Garcia-Roves
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  25. Josep Vidal
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  26. Paul Cohen
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  27. Rubén Nogueiras
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  28. Marc Claret
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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 toMariona Graupera.

Ethics declarations

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.

Peer review

Peer review information

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

Additional information

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

Extended data

Extended Data Fig. 1 Validation of Pten deletion in _Pten_iΔEC 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 _Ribotag_iHAEC mice (eWAT n = 3, BAT, muscle and liver n = 2). (b) Representative images of flat-mounted eWAT from 5-week-old control _Ribotag_iHAEC 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 _Ribotag_iHAEC and _Pten_iΔEC_- Ribotag_iHAEC 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 Pten iΔEC mice (n = 6), (e) lung-EC obtained from control (n = 6) and Pten iΔEC mice (n = 6), (f) muscle-EC obtained from control (n = 4) and Pten iΔEC mice (n = 5) and (g) BAT-EC obtained from control (n = 3) and Pten iΔEC 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).

Source data

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 Pten iΔEC mice at 12 weeks of age (control n = 8, Pten iΔEC n = 6). (b and c) Body composition analysis of control and Pten iΔEC mice at 14 weeks (control n = 7, Pten iΔEC n = 5) by MRI. (d and e) Gene expression analysis of fibrosis markers in whole tissue extracts from (d) eWAT (control n = 4, Pten iΔEC n = 6) and (e) iWAT (control n = 5, Pten iΔEC n = 6) from control and Pten iΔEC 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 Pten iΔEC 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, Pten iΔEC n = 4) and (h) iWAT (control n = 4, Pten iΔEC n = 5) from control and Pten iΔEC 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 Pten iΔEC mice. (k) Levels of leptin in serum of control and Pten iΔEC mice at 14 weeks of age (control n = 5, Pten iΔEC 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 Pten iΔEC 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 Pten iΔEC 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 Pten iΔEC mice at 12 weeks of age (brain n = 8, muscle, liver and heart control n = 4, Pten iΔEC 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 Pten iΔEC 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 Pten iΔEC (n = 9) mice at 12 weeks of age. (e) Representative images of CD31 (white) and Ter119 (red) stained sections of control and Pten iΔEC eWAT at 12 weeks of age. (h) Representative hematoxylin and eosin staining of BAT sections from control and Pten iΔEC 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 Pten iΔEC mice at 14 and 19 weeks of age. (c) eWAT pad weight at 14 (control n = 15, Pten iΔEC n = 16) and 19 (control n = 13, Pten iΔEC n = 10) weeks of age, (d) Quantification of adipocyte area of eWAT at 14 (control n = 8, Pten iΔEC n = 10) and 19 (control n = 7, Pten iΔEC n = 8) weeks of age, (e) iWAT pad weight at 14 (control n = 14, Pten iΔEC n = 16) and 19 (control n = 13, Pten iΔEC n = 10) weeks of age from control and Pten iΔEC mice. (f) Tissue weight in control and Pten iΔEC mice at 14 weeks of age (n = 11). (g) Confocal images of eWAT whole-mount staining with IB4 (red) from control and Pten iΔEC mice at 14 and 19 weeks of age. (h) Quantification of IB4-positive area in eWAT depots from control and Pten iΔEC mice at 14 (n = 6 per group) and 19 weeks of age (n = 7 per group). (j) Representative images of eWAT from control and Pten iΔEC mice at 5 and 12 weeks of age. (k) eWAT pad weight in control and Pten iΔEC mice at 5 (control n = 9, Pten iΔEC n = 10) and 12 (control n = 7, Pten iΔEC n = 5) weeks of age. (l) Quantification of adipocyte area of eWAT from control and Pten iΔEC mice at 5 (n = 4) and 12 (n = 4) weeks of age. (m) iWAT pad weight in control and Pten iΔEC mice at 5 (control n = 9, Pten iΔEC n = 10) and 12 (control n = 7, Pten iΔEC n = 5) weeks of age. (n) Tissue weight in control and Pten iΔEC mice at 12 weeks of age (control n = 7, Pten iΔEC n = 5). (o) Confocal images of eWAT whole-mount staining with IB4 (red) from control and Pten iΔEC mice at 5 and 12 weeks of age. (p) Quantification of IB4-positive area in eWAT depots from control and Pten iΔEC mice at 5 and 12 weeks of age (control n = 7, Pten iΔEC 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 _Ribotag_iHAEC 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 Pten iΔEC mice exposed to HFD for 10 weeks (control n = 9, Pten iΔEC n = 4). (b) Insulin tolerance test (ITT) performed in control and Pten iΔEC mice fed with HFD for 10 weeks (control n = 13, Pten iΔEC n = 10). Bars to the right show AUC quantification of blood glucose monitoring during ITT (control n = 13, Pten iΔEC n = 10). (c) Basal insulin levels and (d) HOMA-IR index in control and Pten iΔEC mice fed with HFD for 10 weeks (control n = 6, Pten iΔEC n = 4). (e) Masson trichrome fibrosis staining in eWAT and iWAT sections from control and Pten iΔEC mice exposed to HFD for 10 weeks. (f) Gene expression analysis of fibrosis markers in whole tissue extracts from eWAT (control n = 7, Pten iΔEC n = 4) from control and Pten iΔEC mice exposed to HFD for 10 weeks. (g) Tissue weight in control and Pten iΔEC mice exposed to HFD for 34 weeks (control n = 9, Pten iΔEC n = 8). (h) ITT performed in control and Pten iΔEC mice fed with HFD for 30 weeks (control n = 10, Pten iΔEC 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 Pten iΔEC mice fed with HFD for 34 weeks (control n = 9, Pten iΔEC n = 8). (k) Masson trichrome fibrosis staining in eWAT and iWAT sections from control and Pten iΔEC 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 _Ribotag_iHAEC n = 5, Pten iΔEC _- Ribotag_iHAEC n = 4), (b) muscle (control Ribotag iHAEC n = 5, Pten iΔEC - Ribotag iHAEC n = 5), (c) and liver (control Ribotag iHAEC n = 5, Pten iΔEC n = 4) from control Ribotag iHAEC and Pten iΔEC - Ribotag iHAEC mice at 5 weeks of age. (d) Glucose uptake measurement in control and Pten iΔEC endothelial cells (control n = 6, Pten iΔEC n = 8). (e and f) In vitro expression analysis of (e) lipid catabolic genes and (f) Cd36 by qPCR in control and Pten iΔEC lung-derived primary endothelial cells (lung-EC) (control n = 4, Pten iΔEC n = 6). (g) Fatty Acid β-Oxidation (FAO) in lung-EC from control and Pten iΔEC mice (n = 8 per group). (h) OCR in control and Pten iΔEC lung-EC in lipid-enriched medium. (i) Bars show OCR quantification from control and Pten iΔEC lung-EC in lipid-enriched medium (control n = 8, Pten iΔEC n = 10). (j) Tissue weight in control and Pten iΔEC mice treated with vehicle or etomoxir for 5 weeks (control - vehicle n = 15, control - etomoxir n = 9, Pten iΔEC - vehicle n = 11, Pten iΔEC - etomoxir n = 10). (k) Representative images of IB4 stained blood vessels (red) in flat-mounted eWAT from control, Pten iΔEC, Pten _iΔEC_-Pgc1β iΔEC and Pgc1β iΔEC mice at 10 weeks of age. (l) Quantification of IB4 positive area in eWAT from control, Pten iΔEC, Pten iΔEC_-Pgc1β iΔEC and Pgc1β iΔEC mice at 10 weeks of age (control n = 9, Pten iΔEC n = 6, Pten iΔEC_-Pgc1β_iΔEC n = 8, Pgc1β_iΔEC n = 5). (m) eWAT pad weight of control Pten iΔEC, Pten _iΔEC_-Pgc1β iΔEC and Pgc1β iΔEC mice at 10 weeks of age (control n = 18, Pten iΔEC n = 5, Pten iΔEC - Pgc1β iΔEC n = 10, Pgc1β iΔEC 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 Pten iΔEC eWAT explant experiment. eWAT from 5 weeks of age control and Pten iΔEC 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 Pten iΔEC 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, Pten iΔEC n = 6) and (e) eWAT (control n = 8, Pten iΔEC 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) _Amd_1 mRNA expression levels analysed by qPCR normalized by mL32 gene expression in eWAT endothelium from control Ribotag iHAEC and Pten iΔEC - Ribotag iHAEC (control Ribotag iHAEC n = 7, Pten iΔEC - Ribotag iHAEC n = 8). (l) Western blot analysis of Amd1, S6K (phosphorylated and total) in adipose-derived primary endothelial cells from Pten iΔEC 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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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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