The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Metabolic adaptation to a high-fat diet is associated with a change in the gut microbiota
Open accessAbstract
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
An obesity-associated gut microbiome with increased capacity for energy harvest
Turnbaugh, P. J., Ley, R. E., Mahowald, M. A., Magrini, V., Mardis, E. R., & Gordon, J. I. (2006) · Nature · doi:10.1038/nature05414 · Cited by 12,444
Inflammation and metabolic disorders
Hotamisligil, G. S. (2006) · Nature · doi:10.1038/nature05485 · Cited by 9,199
Human gut microbes associated with obesity
Ley, R. E., Turnbaugh, P. J., Klein, S., & Gordon, J. I. (2006) · Nature · doi:10.1038/4441022a · Cited by 8,785
The gut microbiota as an environmental factor that regulates fat storage
Bäckhed, F., Ding, H., Wang, T., Hooper, L. V., Koh, G. Y., Nagy, A., Semenkovich, C. F., & Gordon, J. I. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0407076101 · Cited by 6,245
Obesity alters gut microbial ecology
Ley, R. E., Bäckhed, F., Turnbaugh, P., Lozupone, C. A., Knight, R. D., & Gordon, J. I. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0504978102 · Cited by 6,176
Cani, P. D., Bibiloni, R., Knauf, C., Waget, A., Neyrinck, A. M., Delzenne, N. M., & Burcelin, R. (2008) · Diabetes · doi:10.2337/db07-1403 · Cited by 4,819
Self-citationInflammation and insulin resistance
Shoelson, S. E. (2006) · Journal of Clinical Investigation · doi:10.1172/jci29069 · Cited by 4,769
Mechanisms underlying the resistance to diet-induced obesity in germ-free mice
Bäckhed, F., Manchester, J. K., Semenkovich, C. F., & Gordon, J. I. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0605374104 · Cited by 2,615
Ivanov, I. I., Frutos, R. D. L., Manel, N., Yoshinaga, K., Rifkin, D. B., Sartor, R. B., Finlay, B. B., & Littman, D. R. (2008) · Cell Host & Microbe · doi:10.1016/j.chom.2008.09.009 · Cited by 1,770
Samuel, B. S., Shaito, A., Motoike, T., Rey, F. E., Backhed, F., Manchester, J. K., Hammer, R. E., Williams, S. C., Crowley, J., Yanagisawa, M., et al. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0808567105 · Cited by 1,564
Gut microbiota modulation with norfloxacin and ampicillin enhances glucose tolerance in mice
Membrez, M., Blancher, F., Jaquet, M., Bibiloni, R., Cani, P. D., Burcelin, R. G., Corthesy, I., Macé, K., & Chou, C. J. (2008) · The FASEB Journal · doi:10.1096/fj.07-102723 · Cited by 493
Self-citationLuminal Cathepsin G and Protease-Activated Receptor 4
Dabek, M., Ferrier, L., Roka, R., Gecse, K., Annahazi, A., Moreau, J., Escourrou, J., Cartier, C., Chaumaz, G., Leveque, M., et al. (2009) · The American Journal of Pathology · doi:10.2353/ajpath.2009.080986 · Cited by 73
Cited by
Host-gut microbiota metabolic interactions
Nicholson, J. K., Holmes, E., Kinross, J., Burcelin, R., Gibson, G., Jia, W., & Pettersson, S. (2012) · Science · doi:10.1126/science.1223813 · Cited by 4,760
Self-citationYou are what you eat: Diet, health and the gut microbiota
Zmora, N., Suez, J., & Elinav, E. (2019) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/s41575-018-0061-2 · Cited by 1,792
Intestinal permeability – a new target for disease prevention and therapy
Bischoff, S. C., Barbara, G., Buurman, W., Ockhuizen, T., Schulzke, J.-D., Serino, M., Tilg, H., Watson, A., & Wells, J. M. (2014) · BMC Gastroenterology · doi:10.1186/s12876-014-0189-7 · Cited by 1,755
Self-citationThe gut-liver axis and the intersection with the microbiome
Tripathi, A., Debelius, J., Brenner, D. A., Karin, M., Loomba, R., Schnabl, B., & Knight, R. (2018) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/s41575-018-0011-z · Cited by 1,480
How informative is the mouse for human gut microbiota research?
Nguyen, T. L. A., Vieira-Silva, S., Liston, A., & Raes, J. (2015) · Disease Models & Mechanisms · doi:10.1242/dmm.017400 · Cited by 1,334
“microbiota composition and metabolic adaptations in mice on highfat diets (Serino et al., 2012).”
Background
Metadata
- Authors
- Serino, M., Luche, E., Gres, S., Baylac, A., Bergé, M., Cenac, C., Waget, A., Klopp, P., Iacovoni, J., Klopp, C., Mariette, J., Bouchez, O., Lluch, J., Ouarné, F., Monsan, P., Valet, P., Roques, C., Amar, J., Bouloumié, A., Théodorou, V., & Burcelin, R.
- Venue
- Gut
- Publisher
- BMJ
- Published
- 2011-11-22
- Volume
- 61
- Issue
- 4
- Pages
- 543-553
- ISSN
- 0017-5749 (ISSN-L)
- 1468-3288
- OpenAlex
- W2109392327
- Cited by
- 615
- References
- 12
- FWCI
- 11.40
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
