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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.
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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
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).”
BackgroundCurrent Understanding of Dysbiosis in Disease in Human and Animal Models
DeGruttola, A. K., Low, D., Mizoguchi, A., & Mizoguchi, E. (2016) · Inflammatory Bowel Diseases · doi:10.1097/mib.0000000000000750 · Cited by 1,122
Intestinal microbiota determines development of non-alcoholic fatty liver disease in mice
Le Roy, T., Llopis, M., Lepage, P., Bruneau, A., Rabot, S., Bevilacqua, C., Martin, P., Philippe, C., Walker, F., Bado, A., et al. (2013) · Gut · doi:10.1136/gutjnl-2012-303816 · Cited by 1,001
Towards a more comprehensive concept for prebiotics
Bindels, L. B., Delzenne, N. M., Cani, P. D., & Walter, J. (2015) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/nrgastro.2015.47 · Cited by 914
De Angelis, M., Piccolo, M., Vannini, L., Siragusa, S., De Giacomo, A., Serrazzanetti, D. I., Cristofori, F., Guerzoni, M. E., Gobbetti, M., & Francavilla, R. (2013) · PLoS ONE · doi:10.1371/journal.pone.0076993 · Cited by 887
Microbiota and diabetes: an evolving relationship
Tilg, H., & Moschen, A. R. (2014) · Gut · doi:10.1136/gutjnl-2014-306928 · Cited by 853
Schneeberger, M., Everard, A., Gómez-Valadés, A. G., Matamoros, S., Ramírez, S., Delzenne, N. M., Gomis, R., Claret, M., & Cani, P. D. (2015) · Scientific Reports · doi:10.1038/srep16643 · Cited by 798
Molecular phenomics and metagenomics of hepatic steatosis in non-diabetic obese women
Hoyles, L., Fernández-Real, J.-M., Federici, M., Serino, M., Abbott, J., Charpentier, J., Heymes, C., Luque, J. L., Anthony, E., Barton, R. H., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0061-3 · Cited by 720
Self-citationMichielan, A., & D’Incà, R. (2015) · Mediators of Inflammation · doi:10.1155/2015/628157 · Cited by 709
Wan, Y., Wang, F., Yuan, J., Li, J., Jiang, D., Zhang, J., Li, H., Wang, R., Tang, J., Huang, T., et al. (2019) · Gut · doi:10.1136/gutjnl-2018-317609 · Cited by 598
Impact of Diet-Modulated Butyrate Production on Intestinal Barrier Function and Inflammation
Bach Knudsen, K. E., Lærke, H. N., Hedemann, M. S., Nielsen, T. S., Ingerslev, A. K., Gundelund Nielsen, D. S., Theil, P. K., Purup, S., Hald, S., Schioldan, A. G., et al. (2018) · Nutrients · doi:10.3390/nu10101499 · Cited by 572
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Patterson, E., Ryan, P. M., Cryan, J. F., Dinan, T. G., Ross, R. P., Fitzgerald, G. F., & Stanton, C. (2016) · Postgraduate Medical Journal · doi:10.1136/postgradmedj-2015-133285 · Cited by 552
Functions of Gut Microbiota Metabolites, Current Status and Future Perspectives
Liu, J., Tan, Y., Cheng, H., Zhang, D., Feng, W., & Peng, C. (2022) · Aging and disease · doi:10.14336/ad.2022.0104 · Cited by 529
Gut microbiota composition and activity in relation to host metabolic phenotype and disease risk
Holmes, E., Li, J. V., Marchesi, J. R., & Nicholson, J. K. (2012) · Cell Metabolism · doi:10.1016/j.cmet.2012.10.007 · Cited by 490
Metabolically healthy versus metabolically unhealthy obesity
Iacobini, C., Pugliese, G., Blasetti Fantauzzi, C., Federici, M., & Menini, S. (2019) · Metabolism · doi:10.1016/j.metabol.2018.11.009 · Cited by 453
A Consideration of Biomarkers to be Used for Evaluation of Inflammation in Human Nutritional Studies
Calder, P. C., Ahluwalia, N., Albers, R., Bosco, N., Bourdet-Sicard, R., Haller, D., Holgate, S. T., Jönsson, L. S., Latulippe, M. E., Marcos, A., et al. (2013) · British Journal of Nutrition · doi:10.1017/s0007114512005119 · Cited by 425
Tremellen, K., & Pearce, K. (2012) · Medical Hypotheses · doi:10.1016/j.mehy.2012.04.016 · Cited by 359
A critical review on the impacts of β-glucans on gut microbiota and human health
Jayachandran, M., Chen, J., Chung, S. S. M., & Xu, B. (2018) · The Journal of Nutritional Biochemistry · doi:10.1016/j.jnutbio.2018.06.010 · Cited by 333
Benedict, C., Vogel, H., Jonas, W., Woting, A., Blaut, M., Schürmann, A., & Cedernaes, J. (2016) · Molecular Metabolism · doi:10.1016/j.molmet.2016.10.003 · Cited by 324
“high- or high-sugar diets, which are known to impact not only glucose metabolism but also the gut microbiome [75].”
BackgroundKellow, N. J., Coughlan, M. T., & Reid, C. M. (2014) · British Journal of Nutrition · doi:10.1017/s0007114513003607 · Cited by 307
Microbiota regulation of the mammalian gut-brain axis
Burokas, A., Moloney, R. D., Dinan, T. G., & Cryan, J. F. (2015) · Advances in applied microbiology · doi:10.1016/bs.aambs.2015.02.001 · Cited by 300
A selective gut bacterial bile salt hydrolase alters host metabolism
Yao, L., Seaton, S. C., Ndousse-Fetter, S., Adhikari, A. A., DiBenedetto, N., Mina, A. I., Banks, A. S., Bry, L., & Devlin, A. S. (2018) · eLife · doi:10.7554/elife.37182 · Cited by 274
Probiotics modulate gut microbiota and improve insulin sensitivity in DIO mice
Bagarolli, R. A., Tobar, N., Oliveira, A. G., Araújo, T. G., Carvalho, B. M., Rocha, G. Z., Vecina, J. F., Calisto, K., Guadagnini, D., Prada, P. O., et al. (2017) · The Journal of Nutritional Biochemistry · doi:10.1016/j.jnutbio.2017.08.006 · Cited by 266
Lelouvier, B., Servant, F., Païssé, S., Brunet, A., Benyahya, S., Serino, M., Valle, C., Ortiz, M. R., Puig, J., Courtney, M., et al. (2016) · Hepatology · doi:10.1002/hep.28829 · Cited by 242
Self-citationCian, R., Drago, S., De Medina, F., & Martínez-Augustin, O. (2015) · Marine Drugs · doi:10.3390/md13085358 · Cited by 238
Yoo, S., Kim, Y., Park, D., Jung, U., Jeon, S., Ahn, Y., Huh, C., McGregor, R., & Choi, M. S. (2013) · Obesity · doi:10.1002/oby.20428 · Cited by 230
The “psychomicrobiotic”: targeting microbiota in major psychiatric disorders: a systematic review
Fond, G., Boukouaci, W., Chevalier, G., Regnault, A., Eberl, G., Hamdani, N., Dickerson, F., Macgregor, A., Boyer, L., Dargel, A., et al. (2015) · Pathologie Biologie · doi:10.1016/j.patbio.2014.10.003 · Cited by 219
Diet, inflammation and the gut microbiome: mechanisms for obesity-associated cognitive impairment
Leigh, S.-J., & Morris, M. J. (2020) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2020.165767 · Cited by 221
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Jeffery, I., & O'Toole, P. (2013) · Nutrients · doi:10.3390/nu5010234 · Cited by 199
Toubal, A., Kiaf, B., Beaudoin, L., Cagninacci, L., Rhimi, M., Fruchet, B., da Silva, J., Corbett, A. J., Simoni, Y., Lantz, O., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-17307-0 · Cited by 165
Impact of dietary fats on brain functions
Chianese, R., Coccurello, R., Viggiano, A., Scafuro, M., Fiore, M., Coppola, G., Operto, F. F., Fasano, S., Laye, S., Pierantoni, R., et al. (2018) · Current Neuropharmacology · doi:10.2174/1570159x15666171017102547 · Cited by 159
Dumas, M.-E., Rothwell, A. R., Hoyles, L., Aranias, T., Chilloux, J., Calderari, S., Noll, E. M., Péan, N., Boulangé, C. L., Blancher, C., et al. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.06.039 · Cited by 114
“…the isogenic mouse population model with a pharmaco-metabonomic approach, phenotypic heterogeneity in absence of genetic variation can be directly predicted by specific microbial-host co-metabolites, which could not be inferred through 16 s rRNA phylogenetic analysis (Serino et al., 2012).”
BackgroundMethodInfluentialLinks between Dietary Protein Sources, the Gut Microbiota, and Obesity
Madsen, L., Myrmel, L. S., Fjære, E., Liaset, B., & Kristiansen, K. (2017) · Frontiers in Physiology · doi:10.3389/fphys.2017.01047 · Cited by 110
Moreno‐Navarrete, J. M., Serino, M., Blasco‐Baque, V., Azalbert, V., Barton, R. H., Cardellini, M., Latorre, J., Ortega, F., Sabater‐Masdeu, M., Burcelin, R., et al. (2018) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.201700721 · Cited by 106
Self-citationFar from the eyes, close to the heart: dysbiosis of gut microbiota and cardiovascular consequences
Serino, M., Blasco-Baque, V., Nicolas, S., & Burcelin, R. (2014) · Current Cardiology Reports · doi:10.1007/s11886-014-0540-1 · Cited by 93
Self-citationSexual dimorphism of cardiometabolic dysfunction: Gut microbiome in the play?
Cross, T.-W. L., Kasahara, K., & Rey, F. E. (2018) · Molecular Metabolism · doi:10.1016/j.molmet.2018.05.016 · Cited by 87
Monk, J. M., Lepp, D., Wu, W., Pauls, K. P., Robinson, L. E., & Power, K. A. (2017) · The Journal of Nutritional Biochemistry · doi:10.1016/j.jnutbio.2017.08.002 · Cited by 85
Gut microbiota, fatty liver disease, and hepatocellular carcinoma
Chu, H., Williams, B., & Schnabl, B. (2018) · Liver Research · doi:10.1016/j.livres.2017.11.005 · Cited by 84
Publisher Correction: The 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/s41575-018-0031-8 · Cited by 70
Foucault, A.-S., Even, P., Lafont, R., Dioh, W., Veillet, S., Tomé, D., Huneau, J.-F., Hermier, D., & Quignard-Boulangé, A. (2014) · Physiology & Behavior · doi:10.1016/j.physbeh.2014.02.002 · Cited by 68
Dhillon, J., Li, Z., & Ortiz, R. M. (2019) · Current Developments in Nutrition · doi:10.1093/cdn/nzz079 · Cited by 69
Crescenzo, R., Mazzoli, A., Di Luccia, B., Bianco, F., Cancelliere, R., Cigliano, L., Liverini, G., Baccigalupi, L., & Iossa, S. (2017) · Food & Nutrition Research · doi:10.1080/16546628.2017.1331657 · Cited by 63
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Liso, M., De Santis, S., Verna, G., Dicarlo, M., Calasso, M., Santino, A., Gigante, I., Eri, R., Raveenthiraraj, S., Sobolewski, A., et al. (2020) · Inflammatory Bowel Diseases · doi:10.1093/ibd/izz279 · Cited by 57
Reichelt, A. C., Loughman, A., Bernard, A., Raipuria, M., Abbott, K. N., Dachtler, J., Van, T. T. H., & Moore, R. J. (2020) · Nutritional Neuroscience · doi:10.1080/1028415x.2018.1537169 · Cited by 49
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
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