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Original article
Metabolic adaptation to a high-fat diet is associated with a change in the gut microbiota
  1. Matteo Serino1,2,
  2. Elodie Luche1,2,
  3. Sandra Gres1,2,
  4. Audrey Baylac3,
  5. Mathieu Bergé3,
  6. Claire Cenac4,
  7. Aurelie Waget1,2,
  8. Pascale Klopp1,2,
  9. Jason Iacovoni1,2,
  10. Christophe Klopp5,
  11. Jerome Mariette5,
  12. Olivier Bouchez6,
  13. Jerome Lluch6,
  14. Francoise Ouarné7,
  15. Pierre Monsan7,8,9,10,
  16. Philippe Valet1,2,
  17. Christine Roques3,
  18. Jacques Amar11,
  19. Anne Bouloumié1,2,
  20. Vassilia Théodorou4,
  21. Remy Burcelin1,2
  1. 1Institut National de la Santé et de la Recherche Médicale (INSERM), Toulouse, France
  2. 2Université Paul Sabatier (UPS), Unité Mixte de Recherche (UMR) 1048, Institut de Maladies Métaboliques et Cardiovasculaires (I2MC), Toulouse Cedex 4, France
  3. 3Université de Toulouse III, UPS, LU49, Adhésion Bactérienne et Formation de Biofilms, Toulouse Cedex 9, France
  4. 4Neuro-Gastroenterology and Nutrition Unit, UMR INRA/EI-Purpan, Toulouse Cedex 3, France
  5. 5Plateforme Bio-informatique Toulouse Genopole®, UBIA INRA, Castanet-Tolosan Cedex, France
  6. 6GENOTOUL Platform, INRA Chemin de Borde-Rouge, Auzeville, France
  7. 7Université de Toulouse III, INSA, UPS, INP, LISBP, Toulouse, France
  8. 8CNRS, UMR5504, Toulouse, France
  9. 9INRA, UMR792 Ingénierie des Systèmes Biologiques et des Procédés, Toulouse, France
  10. 10Institut Universitaire de France, Paris, France
  11. 11Rangueil Hospital, Department of Therapeutics, Toulouse, France
  1. Correspondence to Dr Remy Burcelin, Université Paul Sabatier (UPS), Unité Mixte de Recherche (UMR) 1048, Institut de Maladies Métaboliques et Cardiovasculaires (I2MC), F-31432 Toulouse Cedex 4, France; remy.burcelin{at}


Objective The gut microbiota, which is considered a causal factor in metabolic diseases as shown best in animals, is under the dual influence of the host genome and nutritional environment. This study investigated whether the gut microbiota per se, aside from changes in genetic background and diet, could sign different metabolic phenotypes in mice.

Methods The unique animal model of metabolic adaptation was used, whereby C57Bl/6 male mice fed a high-fat carbohydrate-free diet (HFD) became either diabetic (HFD diabetic, HFD-D) or resisted diabetes (HFD diabetes-resistant, HFD-DR). Pyrosequencing of the gut microbiota was carried out to profile the gut microbial community of different metabolic phenotypes. Inflammation, gut permeability, features of white adipose tissue, liver and skeletal muscle were studied. Furthermore, to modify the gut microbiota directly, an additional group of mice was given a gluco-oligosaccharide (GOS)-supplemented HFD (HFD+GOS).

Results Despite the mice having the same genetic background and nutritional status, a gut microbial profile specific to each metabolic phenotype was identified. The HFD-D gut microbial profile was associated with increased gut permeability linked to increased endotoxaemia and to a dramatic increase in cell number in the stroma vascular fraction from visceral white adipose tissue. Most of the physiological characteristics of the HFD-fed mice were modulated when gut microbiota was intentionally modified by GOS dietary fibres.

Conclusions The gut microbiota is a signature of the metabolic phenotypes independent of differences in host genetic background and diet.

  • Gut microbes pyrosequencing
  • metabolic heterogeneity
  • high-fat diet responsiveness
  • type 2 diabetes
  • bacterial translocation
  • intestinal barrier function
  • intestinal bacteria
  • bone marrow transplantation
  • diabetes mellitus
  • gastrointestinal physiology
  • diabetes mellitus
  • ANAL
  • diabetes mellitus
  • diabetes mellitus

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: and

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Supplementary materials


  • See Commentary, p 474

  • Funding This work was supported by grants from Agence Nationale pour la Recherche (ANR) to RB and collaborators (ANR-Florinflam and Transflora); in part, by the European Commission's Seventh Framework programme under grant agreement No 241913 (FLORINASH) to RB and by the Benjamin Delessert Foundation to MS.

  • Competing interests None.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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