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
Affiliations
- Céline Cruciani-Guglielmacci
- Unité de Biologie Fonctionnelle et Adaptative, Sorbonne Paris Cité, CNRS UMR 8251, Université Paris Diderot, Paris, France
- Lara Bellini
- Unité de Biologie Fonctionnelle et Adaptative, Sorbonne Paris Cité, CNRS UMR 8251, Université Paris Diderot, Paris, France
- Jessica Denom
- Unité de Biologie Fonctionnelle et Adaptative, Sorbonne Paris Cité, CNRS UMR 8251, Université Paris Diderot, Paris, France
- Masaya Oshima
- INSERM U1016, Université Paris-Descartes, Institut Cochin, Paris, France
- Neïké Fernandez
- Unité de Biologie Fonctionnelle et Adaptative, Sorbonne Paris Cité, CNRS UMR 8251, Université Paris Diderot, Paris, France
- Priscilla Normandie-Levi
- Unité de Biologie Fonctionnelle et Adaptative, Sorbonne Paris Cité, CNRS UMR 8251, Université Paris Diderot, Paris, France
- Xavier P. Berney
- Centre for Integrative Genomics, University of Lausanne, 1015 Lausanne, Switzerland
- Nadim Kassis
- Unité de Biologie Fonctionnelle et Adaptative, Sorbonne Paris Cité, CNRS UMR 8251, Université Paris Diderot, Paris, France
- Claude Rouch
- Unité de Biologie Fonctionnelle et Adaptative, Sorbonne Paris Cité, CNRS UMR 8251, Université Paris Diderot, Paris, France
- Julien Dairou
- Unité de Biologie Fonctionnelle et Adaptative, Sorbonne Paris Cité, CNRS UMR 8251, Université Paris Diderot, Paris, France
- Tracy Gorman
- Discovery Sciences, Innovative Medicines & Early Development Biotech Unit, AstraZeneca, Cambridge Science Park, Milton Road, Cambridge CB4 0WG, UK
- David M. Smith
- Discovery Sciences, Innovative Medicines & Early Development Biotech Unit, AstraZeneca, Cambridge Science Park, Milton Road, Cambridge CB4 0WG, UK
- Anna Marley
- Discovery Sciences, Innovative Medicines & Early Development Biotech Unit, AstraZeneca, Cambridge Science Park, Milton Road, Cambridge CB4 0WG, UK
- Robin Liechti
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
- Dmitry Kuznetsov
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
- Leonore Wigger
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
- Frédéric Burdet
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
- Anne-Laure Lefèvre
- Recherche de Découverte, PIT Métabolisme, IdRS, 11 rue des Moulineaux, 92150 Suresnes, France
- Isabelle Wehrle
- Recherche de Découverte, PIT Métabolisme, IdRS, 11 rue des Moulineaux, 92150 Suresnes, France
- Ingo Uphues
- Boehringer Ingelheim Pharma GmbH & Co, KG 88400 Biberach, Germany
- Tobias Hildebrandt
- Boehringer Ingelheim Pharma GmbH & Co, KG 88400 Biberach, Germany
- Werner Rust
- Boehringer Ingelheim Pharma GmbH & Co, KG 88400 Biberach, Germany
- Catherine Bernard
- Recherche de Découverte, PIT Métabolisme, IdRS, 11 rue des Moulineaux, 92150 Suresnes, France
- Alain Ktorza
- Recherche de Découverte, PIT Métabolisme, IdRS, 11 rue des Moulineaux, 92150 Suresnes, France
- Guy A. Rutter
- Section of Cell Biology and Functional Genomics, Department of Medicine, Imperial College London, London W120NN, UK
- Raphael Scharfmann
- INSERM U1016, Université Paris-Descartes, Institut Cochin, Paris, France
- Ioannis Xenarios
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
- Hervé Le Stunff
- Unité de Biologie Fonctionnelle et Adaptative, Sorbonne Paris Cité, CNRS UMR 8251, Université Paris Diderot, Paris, France; I2BC – UMR 9198 Université Paris Sud, Gif sur Yvette, France
- Bernard Thorens
- Centre for Integrative Genomics, University of Lausanne, 1015 Lausanne, Switzerland
- Christophe Magnan
- Unité de Biologie Fonctionnelle et Adaptative, Sorbonne Paris Cité, CNRS UMR 8251, Université Paris Diderot, Paris, France; Corresponding author.
- Mark Ibberson
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland; Corresponding author. Vital-IT Group, SIB Swiss Institute of Bioinformatics, Genopode Building, University of Lausanne, Quartier Sorge, 1015 Lausanne, Switzerland.
- Journal volume & issue
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Vol. 6,
no. 4
pp. 340 – 351
Abstract
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