Molecular Metabolism (Apr 2017)

Molecular phenotyping of multiple mouse strains under metabolic challenge uncovers a role for Elovl2 in glucose-induced insulin secretion

  • Céline Cruciani-Guglielmacci,
  • Lara Bellini,
  • Jessica Denom,
  • Masaya Oshima,
  • Neïké Fernandez,
  • Priscilla Normandie-Levi,
  • Xavier P. Berney,
  • Nadim Kassis,
  • Claude Rouch,
  • Julien Dairou,
  • Tracy Gorman,
  • David M. Smith,
  • Anna Marley,
  • Robin Liechti,
  • Dmitry Kuznetsov,
  • Leonore Wigger,
  • Frédéric Burdet,
  • Anne-Laure Lefèvre,
  • Isabelle Wehrle,
  • Ingo Uphues,
  • Tobias Hildebrandt,
  • Werner Rust,
  • Catherine Bernard,
  • Alain Ktorza,
  • Guy A. Rutter,
  • Raphael Scharfmann,
  • Ioannis Xenarios,
  • Hervé Le Stunff,
  • Bernard Thorens,
  • Christophe Magnan,
  • Mark Ibberson

Journal volume & issue
Vol. 6, no. 4
pp. 340 – 351

Abstract

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Objective: In type 2 diabetes (T2D), pancreatic β cells become progressively dysfunctional, leading to a decline in insulin secretion over time. In this study, we aimed to identify key genes involved in pancreatic beta cell dysfunction by analyzing multiple mouse strains in parallel under metabolic stress. Methods: Male mice from six commonly used non-diabetic mouse strains were fed a high fat or regular chow diet for three months. Pancreatic islets were extracted and phenotypic measurements were recorded at 2 days, 10 days, 30 days, and 90 days to assess diabetes progression. RNA-Seq was performed on islet tissue at each time-point and integrated with the phenotypic data in a network-based analysis. Results: A module of co-expressed genes was selected for further investigation as it showed the strongest correlation to insulin secretion and oral glucose tolerance phenotypes. One of the predicted network hub genes was Elovl2, encoding Elongase of very long chain fatty acids 2. Elovl2 silencing decreased glucose-stimulated insulin secretion in mouse and human β cell lines. Conclusion: Our results suggest a role for Elovl2 in ensuring normal insulin secretory responses to glucose. Moreover, the large comprehensive dataset and integrative network-based approach provides a new resource to dissect the molecular etiology of β cell failure under metabolic stress. Keywords: Diabetes, Pancreas, Beta cell dysfunction, Network analysis, Molecular phenotyping, Metabolic stress