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Alterations in gut microbiota associated with a cafeteria diet and the physiological consequences in the host



Gut microbiota have been described as key factors in the pathophysiology of obesity and different components of metabolic syndrome (MetS). The cafeteria diet (CAF)-fed rat is a preclinical model that reproduces most of the alterations found in human MetS by simulating a palatable human unbalanced diet. Our objective was to assess the effects of CAF on gut microbiota and their associations with different components of MetS in Wistar rats.


Animals were fed a standard diet or CAF for 12 weeks. A partial least square-based methodology was used to reveal associations between gut microbiota, characterized by 16S ribosomal DNA gene sequencing, and biochemical, nutritional and physiological parameters.


CAF feeding resulted in obesity, dyslipidemia, insulin resistance and hepatic steatosis. These changes were accompanied by a significant decrease in gut bacterial diversity, decreased Firmicutes and an increase in Actinobacteria and Proteobacteria abundances, which were concomitant with increased endotoxemia. Associations of different genera with the intake of lipids and carbohydrates were opposed from those associated with the intake of fiber. Changes in gut microbiota were also associated with the different physiological effects of CAF, mainly increased adiposity and altered levels of plasma leptin and glycerol, consistent with altered adipose tissue metabolism. Also hepatic lipid accretion was associated with changes in microbiota, highlighting the relevance of gut microbiota homeostasis in the adipose–liver axis.


Overall, our results suggest that CAF feeding has a profound impact on the gut microbiome and, in turn, that these changes may be associated with important features of MetS.

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  1. 1

    Hildrum B, Mykletun A, Hole T, Midthjell K, Dahl AA . Age-specific prevalence of the metabolic syndrome defined by the International Diabetes Federation and the National Cholesterol Education Program: the Norwegian HUNT 2 study. BMC Public Health 2007; 7: 220.

    Article  Google Scholar 

  2. 2

    Eckel RH, KGMM Alberti, Grundy SM, Zimmet PZ . The metabolic syndrome. Lancet 2005; 365: 1415–1428.

    CAS  Article  Google Scholar 

  3. 3

    Wong SK, Chin K-Y, Suhaimi FH, Fairus A, Ima-Nirwana S, Alberti K et al. Animal models of metabolic syndrome: a review. Nutr Metab (Lond) 2016; 13: 65.

    Article  Google Scholar 

  4. 4

    Panchal SK, Brown L, Panchal SK, Brown L . Rodent models for metabolic syndrome research. J Biomed Biotechnol 2011; 2011: 351982.

    Article  Google Scholar 

  5. 5

    Gomez-Smith M, Karthikeyan S, Jeffers MS, Janik R, Thomason LA, Stefanovic B et al. A physiological characterization of the cafeteria diet model of metabolic syndrome in the rat. Physiol Behav 2016; 167: 382–391.

    CAS  Article  Google Scholar 

  6. 6

    Sampey BP, Vanhoose AM, Winfield HM, Freemerman AJ, Muehlbauer MJ, Fueger PT et al. Cafeteria diet is a robust model of human metabolic syndrome with liver and adipose inflammation: comparison to high-fat diet. Obesity 2011; 19: 1109–1117.

    CAS  Article  Google Scholar 

  7. 7

    de Macedo IC, de Freitas JS, da Silva Torres IL . The influence of palatable diets in reward system activation: a mini review. Adv Pharmacol Sci 2016; 2016: 7238679.

    PubMed  PubMed Central  Google Scholar 

  8. 8

    Saper CB, Chou TC, Elmquist JK . The need to feed: homeostatic and hedonic control of eating. Neuron 2002; 36: 199–211.

    CAS  Article  Google Scholar 

  9. 9

    Estadella D, Oyama LM, Dâmaso AR, Ribeiro EB, Oller Do Nascimento CM . Effect of palatable hyperlipidic diet on lipid metabolism of sedentary and exercised rats. Nutrition 2004; 20: 218–224.

    CAS  Article  Google Scholar 

  10. 10

    Cigarroa I, Lalanza JF, Caimari A, del Bas JM, Capdevila L, Arola L et al. Treadmill intervention attenuates the cafeteria diet-induced impairment of stress-coping strategies in young adult female rats. PLoS ONE 2016; 11: e0153687.

    Article  Google Scholar 

  11. 11

    Lalanza JF, Caimari A, Del Bas JM, Torregrosa D, Cigarroa I, Pallàs M et al. Effects of a post-weaning cafeteria diet in young rats: metabolic syndrome, reduced activity and low anxiety-like behaviour. PLoS One 2014; 9: e85049.

    Article  Google Scholar 

  12. 12

    Sonnenburg JL, Bäckhed F . Diet–microbiota interactions as moderators of human metabolism. Nature 2016; 535: 56–64.

    CAS  Article  Google Scholar 

  13. 13

    Sonnenburg ED, Smits SA, Tikhonov M, Higginbottom SK, Wingreen NS, Sonnenburg JL . Diet-induced extinctions in the gut microbiota compound over generations. Nature 2016; 529: 212–215.

    CAS  Article  Google Scholar 

  14. 14

    Fischbach MA, Sonnenburg JL . Eating for two: how metabolism establishes interspecies interactions in the gut. Cell Host Microbe 2011; 10: 336–347.

    CAS  Article  Google Scholar 

  15. 15

    De Filippo C, Cavalieri D, Paola M, Di, Ramazzotti M, Poullet JB, Massart S et al. Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proc Natl Acad Sci U S A 2010; 107: 14691.

    CAS  Article  Google Scholar 

  16. 16

    Cotillard A, Kennedy SP, Kong LC, Prifti E, Pons N, Le Chatelier E et al. Dietary intervention impact on gut microbial gene richness. Nature 2013; 500: 585–588.

    CAS  Article  Google Scholar 

  17. 17

    Clarke SF, Murphy EF, Nilaweera K, Ross PR, Shanahan F, O’Toole PW et al. The gut microbiota and its relationship to diet and obesity: new insights. Gut Microbes 2012; 3: 186–202.

    Article  Google Scholar 

  18. 18

    Clarke SF, Murphy EF, O’Sullivan O, Ross RP, O’Toole PW, Shanahan F et al. Targeting the microbiota to address diet-induced obesity: a time dependent challenge. PLoS ONE 2013; 8: e65790.

    CAS  Article  Google Scholar 

  19. 19

    Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, Duncan A, Ley RE et al. A core gut microbiome in obese and lean twins. Nature 2009; 457: 480–484.

    CAS  Article  Google Scholar 

  20. 20

    DiBaise JK, Frank DN, Mathur R . Impact of the gut microbiota on the development of obesity: current concepts. Am J Gastroenterol Suppl 2012; 1: 22–27.

    CAS  Article  Google Scholar 

  21. 21

    Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI . An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 2006; 444: 1027–1031.

    Article  Google Scholar 

  22. 22

    Walters WA, Xu Z, Knight R . Meta-analyses of human gut microbes associated with obesity and IBD. FEBS Lett 2014; 588: 4223–4233.

    CAS  Article  Google Scholar 

  23. 23

    Caimari A, Del Bas JM, Crescenti A, Arola L . Low doses of grape seed procyanidins reduce adiposity and improve the plasma lipid profile in hamsters. Int J Obes 2013; 37: 576–583.

    CAS  Article  Google Scholar 

  24. 24

    Prabhakar PV, Reddy UA, Singh SP, Balasubramanyam A, Rahman MF, Indu Kumari S et al. Oxidative stress induced by aluminum oxide nanomaterials after acute oral treatment in Wistar rats. J Appl Toxicol 2012; 32: 436–445.

    CAS  Article  Google Scholar 

  25. 25

    Rodríguez-Sureda V, Peinado-Onsurbe J . A procedure for measuring triacylglyceride and cholesterol content using a small amount of tissue. Anal Biochem 2005; 343: 277–282.

    Article  Google Scholar 

  26. 26

    Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods 2010; 7: 335–336.

    CAS  Article  Google Scholar 

  27. 27

    Lê Cao K-A, Rohart F, Gonzalez I, Dejean S mixOmics: Omics Data Integration Project. R Packag version 611 2016.

  28. 28

    Lê Cao K-A, Martin PGP, Robert-Granié C, Besse P . Sparse canonical methods for biological data integration: application to a cross-platform study. BMC Bioinformatics 2009; 10: 34.

    Article  Google Scholar 

  29. 29

    Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 2003; 13: 2498–2504.

    CAS  Article  Google Scholar 

  30. 30

    González I, Cao K-AL, Davis MJ, Déjean S . Visualising associations between paired ‘omics’ data sets. BioData Min 2012; 5: 19.

    Article  Google Scholar 

  31. 31

    Fox J . The R commander: a basic-statistics graphical user interface to R. J Stat Softw 2005; 14: 1–42.

    Google Scholar 

  32. 32

    Le Chatelier E, Nielsen T, Qin J, Prifti E, Hildebrand F, Falony G et al. Richness of human gut microbiome correlates with metabolic markers. Nature 2013; 500: 541–546.

    CAS  Article  Google Scholar 

  33. 33

    Fernandes J, Su W, Rahat-Rozenbloom S, Wolever TMS, Comelli EM . Adiposity, gut microbiota and faecal short chain fatty acids are linked in adult humans. Nutr Diabetes 2014; 4: e121.

    CAS  Article  Google Scholar 

  34. 34

    Schwiertz A, Taras D, Schäfer K, Beijer S, Bos NA, Donus C et al. Microbiota and SCFA in lean and overweight healthy subjects. Obesity (Silver Spring) 2010; 18: 190–195.

    Article  Google Scholar 

  35. 35

    Lecomte V, Kaakoush NO, Maloney CA, Raipuria M, Huinao KD, Mitchell HM et al. Changes in gut microbiota in rats fed a high fat diet correlate with obesity-associated metabolic parameters. PLoS ONE 2015; 10: e0126931.

    Article  Google Scholar 

  36. 36

    Minemura M, Shimizu Y . Gut microbiota and liver diseases. World J Gastroenterol 2015; 21: 1691–1702.

    CAS  Article  Google Scholar 

  37. 37

    Million M, Lagier J-C, Yahav D, Paul M . Gut bacterial microbiota and obesity. Clin Microbiol Infect 2013; 19: 305–313.

    CAS  Article  Google Scholar 

  38. 38

    Cani PD, Neyrinck AM, Fava F, Knauf C, Burcelin RG, Tuohy KM et al. Selective increases of bifidobacteria in gut microflora improve high-fat-diet-induced diabetes in mice through a mechanism associated with endotoxaemia. Diabetologia 2007; 50: 2374–2383.

    CAS  Article  Google Scholar 

  39. 39

    Dewulf EM, Cani PD, Claus SP, Fuentes S, Puylaert PGB, Neyrinck AM et al. Insight into the prebiotic concept: lessons from an exploratory, double blind intervention study with inulin-type fructans in obese women. Gut 2013; 62: 1112–1121.

    CAS  Article  Google Scholar 

  40. 40

    Machado MV, Cortez-Pinto H . Diet, microbiota, obesity, and NAFLD: a dangerous quartet. Int J Mol Sci 2016; 17: 1–20.

    Google Scholar 

  41. 41

    Llorente C, Schnabl B . The gut microbiota and liver disease. C Cell Mol Gastroenterol Hepatol 2015; 1: 275–284.

    Article  Google Scholar 

  42. 42

    Shin N-R, Whon TW, Bae J-W, Woese CR, Fox GE, Lauber CL et al. Proteobacteria: microbial signature of dysbiosis in gut microbiota. Trends Biotechnol 2015; 33: 496–503.

    CAS  Article  Google Scholar 

  43. 43

    Frirdich E, Whitfield C . Lipopolysaccharide inner core oligosaccharide structure and outer membrane stability in human pathogens belonging to the Enterobacteriaceae. J Endotoxin Res 2005; 11: 133–144.

    CAS  PubMed  Google Scholar 

  44. 44

    Cani PD, Bibiloni R, Knauf C, Waget A, Neyrinck AM, Delzenne NM et al. Changes in gut microbiota control metabolic endotoxemia-induced inflammation in high-fat diet-induced obesity and diabetes in mice. Diabetes 2008; 57: 1470–1481.

    CAS  Article  Google Scholar 

  45. 45

    Cani PD, Amar J, Iglesias MA, Poggi M, Knauf C, Bastelica D et al. Metabolic endotoxemia initiates obesity and insulin resistance. Diabetes 2007; 56: 1761–1772.

    CAS  Article  Google Scholar 

  46. 46

    Everard A, Lazarevic V, Gaïa N, Johansson M, Ståhlman M, Backhed F et al. Microbiome of prebiotic-treated mice reveals novel targets involved in host response during obesity. ISME J 2014; 8: 2116–2130.

    CAS  Article  Google Scholar 

  47. 47

    Walker A, Pfitzner B, Neschen S, Kahle M, Harir M, Lucio M et al. Distinct signatures of host–microbial meta-metabolome and gut microbiome in two C57BL/6 strains under high-fat diet. ISME J 2014; 8: 2380–2396.

    CAS  Article  Google Scholar 

  48. 48

    Geurts L, Lazarevic V, Derrien M, Everard A, Van Roye M, Knauf C et al. Altered gut microbiota and endocannabinoid system tone in obese and diabetic leptin-resistant mice: impact on apelin regulation in adipose tissue. Front Microbiol 2011; 2: 149.

    CAS  Article  Google Scholar 

  49. 49

    Pfalzer AC, Nesbeth P-DC, Parnell LD, Iyer LK, Liu Z, Kane AV et al. Diet- and genetically-induced obesity differentially affect the fecal microbiome and metabolome in Apc1638N mice. PLoS ONE 2015; 10: e0135758.

    Article  Google Scholar 

  50. 50

    Ramakrishna BS . Role of the gut microbiota in human nutrition and metabolism. J Gastroenterol Hepatol 2013; 28: 9–17.

    CAS  Article  Google Scholar 

  51. 51

    Canfora EE, Jocken JW, Blaak EE . Short-chain fatty acids in control of body weight and insulin sensitivity. Nat Rev Endocrinol 2015; 11: 577–591.

    CAS  Article  Google Scholar 

  52. 52

    den Besten G, Bleeker A, Gerding A, van Eunen K, Havinga R, van Dijk TH et al. Short-chain fatty acids protect against high-fat diet-induced obesity via a PPARγ-dependent switch from lipogenesis to fat oxidation. Diabetes 2015; 64: 2398–2408.

    CAS  Article  Google Scholar 

  53. 53

    Vrieze A, Van Nood E, Holleman F, Salojärvi J, Kootte RS, Bartelsman JFWM et al. Transfer of intestinal microbiota from lean donors increases insulin sensitivity in individuals with metabolic syndrome. Gastroenterology 2012; 143: 913–916.e7.

    CAS  Article  Google Scholar 

  54. 54

    VAUGHAN M . The production and release of glycerol by adipose tissue incubated in vitro. J Biol Chem 1962; 237: 3354–3358.

    CAS  PubMed  Google Scholar 

  55. 55

    Nurjhan N, Consoli A, Gerich J . Increased lipolysis and its consequences on gluconeogenesis in non-insulin-dependent diabetes mellitus. J Clin Invest 1992; 89: 169–175.

    CAS  Article  Google Scholar 

  56. 56

    Loomba R, Seguritan V, Li W, Long T, Klitgord N, Bhatt A et al. Gut microbiome-based metagenomic signature for non-invasive detection of advanced fibrosis in human nonalcoholic fatty liver disease. Cell Metab 2017; 25: 1054–1062.e5.

    CAS  Article  Google Scholar 

  57. 57

    Virtue S, Vidal-Puig A . Adipose tissue expandability, lipotoxicity and the metabolic syndrome—an allostatic perspective. Biochim Biophys Acta 2010; 1801: 338–349.

    CAS  Article  Google Scholar 

  58. 58

    Fabbrini E, Sullivan S, Klein S . Obesity and nonalcoholic fatty liver disease: biochemical, metabolic, and clinical implications. Hepatology 2010; 51: 679–689.

    CAS  Article  Google Scholar 

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Funding for the present research was provided by ACC1Ó (TECCT11-1-0012). We gratefully acknowledge the assistance of the laboratory technicians Silvia Pijuan, Yaiza Tobajas, Iris Triguero, Gertruda Chomiciute and Beatriz Millán.

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Correspondence to J M del Bas.

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del Bas, J., Guirro, M., Boqué, N. et al. Alterations in gut microbiota associated with a cafeteria diet and the physiological consequences in the host. Int J Obes 42, 746–754 (2018).

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