Skip to main content

Advertisement

SpringerLink
Log in

Obesidomics: contribution of adipose tissue secretome analysis to obesity research

  • Review
  • Published:
Endocrine Aims and scope Submit manuscript

Abstract

Obesity is presently reaching pandemic proportions and it is becoming a major health concern in developed and developing countries due to its comorbidities like type II diabetes, cardiovascular pathologies, and some cancers. The discovery of the adipose tissue role as an endocrine gland able to secrete adipokines that affects whole-body energy homeostasis has become a key break-through toward a better molecular understanding of obesity. Among the known adipokines involved in the regulation of energy metabolism very few have been clearly seen as central regulators of insulin sensitivity, metabolism, and energy homeostasis. Thus, the discovery and characterization of new adipocyte-derived factors is still in progress. Proteomics technology has emerged as a useful tool to analyze adipose tissue secretion (secretome) dynamics giving a wider picture into the molecular events that control body weight. Besides the identification of new secreted proteins, the advantage of using this approach is the possibility to detect post-translational modifications and protein interactions that generally cannot be predicted by genome studies. In this review, we summarize the recent efforts to identify new bioactive adipokines by proteomics especially in pathological situations such as obesity.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. L. Qi, Y.A. Cho, Gene-environment interaction and obesity. Nutr. Rev. 66, 684–694 (2008)

    Article  PubMed  Google Scholar 

  2. D.H. Bessesen, Update on obesity. J. Clin. Endocrinol. Metab. 93, 2027–2034 (2008)

    Article  PubMed  CAS  Google Scholar 

  3. D.M. Mutch, K. Clément, Unraveling the genetics of human obesity. PLoS Genet. 2, e188 (2006)

    Article  PubMed  Google Scholar 

  4. M. Seip, O. Trygstad, Generalized lipodystrophy, congenital and acquired (lipoatrophy). Acta Paediatr. Suppl. 413, 2–28 (1996)

    Article  PubMed  CAS  Google Scholar 

  5. J. Moitra, M.M. Mason, M. Olive, D. Krylov, O. Gavrilova, B. Marcus-Samuels, L. Feigenbaum, E. Lee, T. Aoyama, M. Eckhaus, M.L. Reitman, C. Vinson, Life without white fat: a transgenic mouse. Genes Dev. 12, 3168–3181 (1998)

    Article  PubMed  CAS  Google Scholar 

  6. B. Antuna-Puente, B. Feve, S. Fellahi, J.-P. Bastard, Adipokines: the missing link between insulin resistance and obesity. Diabetes Metab. 34, 2–11 (2008)

    Article  PubMed  CAS  Google Scholar 

  7. H. Hauner, Secretory factors from human adipose tissue and their functional role. The Proc. Nutr. Soc. 64, 163–169 (2005)

    Article  CAS  Google Scholar 

  8. N. Halberg, I. Wernstedt-Asterholm, and P.E. Scherer, The adipocyte as an endocrine cell. Endocrinol. Metab. Clin. North. Am. 37, 753–68, x–xi (2008)

    Google Scholar 

  9. L. Hutley, J.B. Prins, Fat as an endocrine organ: relationship to the metabolic syndrome. Am. J. Med. Sci. 330, 280–289 (2005)

    Article  PubMed  Google Scholar 

  10. K. Brochu-Gaudreau, C. Rehfeldt, R. Blouin, V. Bordignon, B.D. Murphy, M.F. Palin, Adiponectin action from head to toe. Endocrine 37, 11–32 (2010)

    Article  PubMed  CAS  Google Scholar 

  11. M. Blüher, Vaspin in obesity and diabetes: pathophysiological and clinical significance. Endocrine (2011) (in press)

  12. I. Castan-Laurell, C. Dray, C. Attané, T. Duparc, C. Knauf, P. Valet, Apelin, diabetes, and obesity. Endocrine 40, 1–9 (2011)

    Article  PubMed  CAS  Google Scholar 

  13. M. Tyers, M. Mann, From genomics to proteomics. Nature 422, 193–197 (2003)

    Article  PubMed  CAS  Google Scholar 

  14. M.P. Pavlou, E.P. Diamandis, The cancer cell secretome: a good source for discovering biomarkers? J. Proteomics. 73, 1896–1906 (2010)

    Article  PubMed  CAS  Google Scholar 

  15. M.P. et al. Lodish G, Berk A, Zipursky SL. Mol. Cell Biol. New York (1999)

  16. H. Skalnikova, J. Motlik, S.J. Gadher, H. Kovarova, Mapping of the secretome of primary isolates of mammalian cells, stem cells and derived cell lines. Proteomics 11, 691–708 (2011)

    Article  PubMed  CAS  Google Scholar 

  17. C. van Vliet, E.C. Thomas, A. Merino-Trigo, R.D. Teasdale, P.A. Gleeson, Intracellular sorting and transport of proteins. Prog. Biophys. Mol. Biol. 83, 1–45 (2003)

    Article  PubMed  Google Scholar 

  18. W. Nickel, C. Rabouille, Mechanisms of regulated unconventional protein secretion. Natl. Rev. Mol. Cell. Biol. 10, 148–155 (2009)

    Article  CAS  Google Scholar 

  19. N. Aoki, S. Jin-no, Y. Nakagawa, N. Asai, E. Arakawa, N. Tamura, T. Tamura, T. Matsuda, Identification and characterization of microvesicles secreted by 3T3-L1 adipocytes: redox- and hormone-dependent induction of milk fat globule-epidermal growth factor 8-associated microvesicles. Endocrinology 148, 3850–3862 (2007)

    Article  PubMed  CAS  Google Scholar 

  20. J.D. Bendtsen, L.J. Jensen, N. Blom, G. Von Heijne, S. Brunak, Protein Eng. Des. Sel. 17, 349–356 (2004)

    Article  PubMed  CAS  Google Scholar 

  21. J.D. Bendtsen, H. Nielsen, G. von Heijne, S. Brunak, Improved prediction of signal peptides: SignalP 3.0. J. Mol. Biol. 340, 783–795 (2004)

    Article  PubMed  Google Scholar 

  22. M. Bodén and J. Hawkins, Prediction of subcellular localization using sequence-biased recurrent networks. Bioinformatics (Oxford, England) 21, 2279–2286 (2005)

    Google Scholar 

  23. O. Emanuelsson, H. Nielsen, S. Brunak, G. von Heijne, Predicting subcellular localization of proteins based on their N-terminal amino acid sequence. J. Mol. Biol. 300, 1005–1016 (2000)

    Article  PubMed  CAS  Google Scholar 

  24. S.-H. Chiou, C.-Y. Wu, Clinical proteomics: current status, challenges, and future perspectives. Kaohsiung J. Med. Sci. 27, 1–14 (2011)

    Article  PubMed  Google Scholar 

  25. G. Alvarez-Llamas, E. Szalowska, M.P. de Vries, D. Weening, K. Landman, A. Hoek, B.H.R. Wolffenbuttel, H. Roelofsen, R.J. Vonk, Characterization of the human visceral adipose tissue secretome. Mol. Cell Proteomics 6, 589–600 (2007)

    Article  PubMed  CAS  Google Scholar 

  26. X. Chen, S. Hess, Adipose proteome analysis: focus on mediators of insulin resistance. Expert Rev. Proteomics 5, 827–839 (2008)

    Article  PubMed  CAS  Google Scholar 

  27. J.C. Sanchez, D. Chiappe, V. Converset, C. Hoogland, P.A. Binz, S. Paesano, R.D. Appel, S. Wang, M. Sennitt, A. Nolan, M.A. Cawthorne, D.F. Hochstrasser, The mouse SWISS-2D PAGE database: a tool for proteomics study of diabetes and obesity. Proteomics 1, 136–163 (2001)

    Article  PubMed  CAS  Google Scholar 

  28. S. Yang, C.-M., Huang, Recent advances in protein profiling of tissues and tissue fluids. Expert Rev. Proteomics. 4, 515–529 (2007)

    Google Scholar 

  29. M. Pardo, R.A. Dwek, N. Zitzmann, Proteomics in uveal melanoma research: opportunities and challenges in biomarker discovery. Expert Rev. Proteomics 4, 273–286 (2007)

    Article  PubMed  CAS  Google Scholar 

  30. P. Wang, E. Mariman, J. Keijer, F. Bouwman, J.-P. Noben, J. Robben, J. Renes, Profiling of the secreted proteins during 3T3-L1 adipocyte differentiation leads to the identification of novel adipokines. Cell. Mol. Life Sci. 61, 2405–2417 (2004)

    PubMed  CAS  Google Scholar 

  31. I.A. Brewis, P. Brennan, Proteomics technologies for the global identification and quantification of proteins. Adv. Protein Chem. Struct. Biol. 80, 1–44 (2010)

    Article  PubMed  CAS  Google Scholar 

  32. H. Roelofsen, M. Dijkstra, D. Weening, M.P. de Vries, A. Hoek, R.J. Vonk, Comparison of isotope-labeled amino acid incorporation rates (CILAIR) provides a quantitative method to study tissue secretomes. Mol. Cell Proteomics 8, 316–324 (2009)

    PubMed  CAS  Google Scholar 

  33. X. Chen, D. Hunt, S.W. Cushman, S. Hess, Proteomic characterization of thiazolidinedione regulation of obese adipose secretome in Zucker obese rats. Proteomics Clin. Appl. 3, 1099–1111 (2009)

    Article  PubMed  CAS  Google Scholar 

  34. X. Chen, S.W. Cushman, L.K. Pannell, S. Hess, Quantitative proteomic analysis of the secretory proteins from rat adipose cells using a 2D liquid chromatography-MS/MS approach. J. Proteome Res. 4, 570–577 (2005)

    Article  PubMed  CAS  Google Scholar 

  35. S. Famulla, D. Lamers, S. Hartwig, W. Passlack, A. Horrighs, A. Cramer, S. Lehr, H. Sell, J. Eckel, Pigment epithelium-derived factor (PEDF) is one of the most abundant proteins secreted by human adipocytes and induces insulin resistance and inflammatory signaling in muscle and fat cells. Int. J. Obes. 35, 762–772 (2011)

    Article  CAS  Google Scholar 

  36. D. Lamers, S. Famulla, N. Wronkowitz, S. Hartwig, S. Lehr, D.M. Ouwens, K. Eckardt, J.M. Kaufman, M. Ryden, S. Müller, F.-G. Hanisch, J. Ruige, P. Arner, H. Sell, J. Eckel, Dipeptidyl peptidase 4 is a novel adipokine potentially linking obesity to the metabolic syndrome. Diabetes 60, 1917–1925 (2011)

    Article  PubMed  CAS  Google Scholar 

  37. S. Zvonic, M. Lefevre, G. Kilroy, Z.E. Floyd, J.P. DeLany, I. Kheterpal, A. Gravois, R. Dow, A. White, X. Wu, J.M. Gimble, Secretome of primary cultures of human adipose-derived stem cells: modulation of serpins by adipogenesis. Mol. Cell Proteomics 6, 18–28 (2007)

    PubMed  CAS  Google Scholar 

  38. M.J. Lee, J. Kim, M.Y. Kim, Y.-S. Bae, S.H. Ryu, T.G. Lee, J.H. Kim, Proteomic analysis of tumor necrosis factor-alpha-induced secretome of human adipose tissue-derived mesenchymal stem cells. J. Proteome Res. 9, 1754–1762 (2010)

    Article  PubMed  CAS  Google Scholar 

  39. D.M. Mutch, C. Rouault, M. Keophiphath, D. Lacasa, K. Clément, Using gene expression to predict the secretome of differentiating human preadipocytes. Int. J. Obes. 33, 354–363 (2009)

    Article  CAS  Google Scholar 

  40. C. Chiellini, O. Cochet, L. Negroni, M. Samson, M. Poggi, G. Ailhaud, M.-C. Alessi, C. Dani, E.-Z. Amri, Characterization of human mesenchymal stem cell secretome at early steps of adipocyte and osteoblast differentiation. BMC Mol. Biol. 9, 26 (2008)

    Article  PubMed  Google Scholar 

  41. H. Molina, Y. Yang, T. Ruch, J.-W. Kim, P. Mortensen, T. Otto, A. Nalli, Q.-Q. Tang, M.D. Lane, R. Chaerkady, A. Pandey, Temporal profiling of the adipocyte proteome during differentiation using a five-plex SILAC based strategy. J. Proteome Res. 8, 48–58 (2009)

    Article  PubMed  CAS  Google Scholar 

  42. J. Zhong, S.A. Krawczyk, R. Chaerkady, H. Huang, R. Goel, J.S. Bader, G.W. Wong, B.E. Corkey, A. Pandey, Temporal profiling of the secretome during adipogenesis in humans. J. Proteome Res. 9, 5228–5238 (2010)

    Article  PubMed  CAS  Google Scholar 

  43. J. Kim, Y.S. Choi, S. Lim, K. Yea, J.H. Yoon, D.-J. Jun, S.H. Ha, J.-W. Kim, J.H. Kim, P.-G. Suh, S.H. Ryu, T.G. Lee, Comparative analysis of the secretory proteome of human adipose stromal vascular fraction cells during adipogenesis. Proteomics 10, 394–405 (2010)

    Article  PubMed  CAS  Google Scholar 

  44. N. Billon, M.C. Monteiro, C. Dani, Developmental origin of adipocytes: new insights into a pending question. Biol. Cell 100, 563–575 (2008)

    Article  PubMed  CAS  Google Scholar 

  45. M. Toyoda, Y. Matsubara, K. Lin, K. Sugimachi, M. Furue, Characterization and comparison of adipose tissue-derived cells from human subcutaneous and omental adipose tissues. Cell Biochem. Funct. 27, 440–447 (2009)

    Article  PubMed  CAS  Google Scholar 

  46. A.W.B. Joe, L. Yi, Y. Even, A.W. Vogl, F.M.V. Rossi, Depot-specific differences in adipogenic progenitor abundance and proliferative response to high-fat diet. Stem cells. 27, 2563–2570 (2009)

    Article  PubMed  CAS  Google Scholar 

  47. S. Santosa, M.D. Jensen, Why are we shaped differently, and why does it matter? Am. J. Physiol. Endocrinol. Metab 295, E531–E535 (2008)

    Article  PubMed  CAS  Google Scholar 

  48. M.M. Ibrahim, Subcutaneous and visceral adipose tissue: structural and functional differences. Obes. Rev. 11, 11–18 (2010)

    Article  PubMed  Google Scholar 

  49. P. Arner, Regional adipocity in man. J. Endocrinol. 155, 191–192 (1997)

    Article  PubMed  CAS  Google Scholar 

  50. J.R. Peinado, Y. Jimenez-Gomez, M.R. Pulido, M. Ortega-Bellido, C. Diaz-Lopez, F.J. Padillo, J. Lopez-Miranda, R. Vazquez-Martínez, M.M. Malagón, The stromal-vascular fraction of adipose tissue contributes to major differences between subcutaneous and visceral fat depots. Proteomics 10, 3356–3366 (2010)

    Article  PubMed  CAS  Google Scholar 

  51. R. Pérez-Pérez, F.J. Ortega-Delgado, E. García-Santos, J.A. López, E. Camafeita, W. Ricart, J.-M. Fernández-Real, B. Peral, Differential proteomics of omental and subcutaneous adipose tissue reflects their unalike biochemical and metabolic properties. J. Proteome Res. 8, 1682–1693 (2009)

    Article  PubMed  Google Scholar 

  52. S.L. Hocking, L.E. Wu, M. Guilhaus, D.J. Chisholm, D.E. James, Intrinsic depot-specific differences in the secretome of adipose tissue, preadipocytes, and adipose tissue-derived microvascular endothelial cells. Diabetes. 59, 3008–3016 (2010)

    Article  PubMed  CAS  Google Scholar 

  53. R. Ross, L. Léger, D. Morris, J. de Guise, R. Guardo, Quantification of adipose tissue by MRI: relationship with anthropometric variables. J. Appl. Physiol. 72, 787–795 (1992)

    PubMed  CAS  Google Scholar 

  54. A. Roca-Rivada, J. Alonso, O. Al-Massadi, C. Castelao, J.R. Peinado, L.M. Seoane, F.F. Casanueva, M. Pardo, Secretome analysis of rat adipose tissues shows location-specific roles for each depot type. J. Proteomics 74, 1068–1079 (2011)

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

This study has been funded by Instituto de Salud Carlos III (ISCIII: Ministerio de Ciencia e Innovación de España): FIS PI0/00537 (FEDER co-financing); FIS PS09/02075; CP08/00216; Xunta de Galicia 10PXIB918273PR. A.R–R is funded by CIBER FisiopatologíaObesidad y Nutrición (CB06/03); M.P. is a Miguel Servet Fellow (Instituto de Salud Carlos III/SERGAS).L.M.Seoane is a ISCIII/SERGAS Researcher.

Author information

Authors and Affiliations

  1. Grupo Obesidómica, Laboratorio de Endocrinología Molecular y Celular, Instituto de Investigación Sanitaria de Santiago de Compostela, Complexo Hospitalario Universitario de Santiago (CHUS/SERGAS), Santiago de Compostela, Spain

    Maria Pardo & Arturo Roca-Rivada

  2. Grupo Fisiopatología Endocrina, Laboratorio de Endocrinología Molecular y Celular, Instituto de Investigación Sanitaria de Santiago de Compostela, Complexo Hospitalario Universitario de Santiago (CHUS/SERGAS), Santiago de Compostela, Spain

    Luisa Maria Seoane

  3. CIBER Fisiopatología Obesidad y Nutrición (CB06/03), Instituto de Salud Carlos III, C/Sinesio Delgado, 4, Spain

    Maria Pardo, Arturo Roca-Rivada, Luisa Maria Seoane & Felipe F. Casanueva

  4. Departamento de Medicina, Universidade de Santiago de Compostela, Santiago de Compostela, Spain

    Felipe F. Casanueva

Authors
  1. Maria Pardo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Arturo Roca-Rivada
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Luisa Maria Seoane
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Felipe F. Casanueva
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Maria Pardo or Felipe F. Casanueva.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Pardo, M., Roca-Rivada, A., Seoane, L.M. et al. Obesidomics: contribution of adipose tissue secretome analysis to obesity research. Endocrine 41, 374–383 (2012). https://doi.org/10.1007/s12020-012-9617-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12020-012-9617-z

Keywords

Search

Navigation