Dietary emulsifiers impact the mouse gut microbiota promoting colitis and metabolic syndrome

  • Nature volume 519, pages 9296 (05 March 2015)
  • doi:10.1038/nature14232
  • Download Citation


The intestinal tract is inhabited by a large and diverse community of microbes collectively referred to as the gut microbiota. While the gut microbiota provides important benefits to its host, especially in metabolism and immune development, disturbance of the microbiota–host relationship is associated with numerous chronic inflammatory diseases, including inflammatory bowel disease and the group of obesity-associated diseases collectively referred to as metabolic syndrome. A primary means by which the intestine is protected from its microbiota is via multi-layered mucus structures that cover the intestinal surface, thereby allowing the vast majority of gut bacteria to be kept at a safe distance from epithelial cells that line the intestine1. Thus, agents that disrupt mucus–bacterial interactions might have the potential to promote diseases associated with gut inflammation. Consequently, it has been hypothesized that emulsifiers, detergent-like molecules that are a ubiquitous component of processed foods and that can increase bacterial translocation across epithelia in vitro2, might be promoting the increase in inflammatory bowel disease observed since the mid-twentieth century3. Here we report that, in mice, relatively low concentrations of two commonly used emulsifiers, namely carboxymethylcellulose and polysorbate-80, induced low-grade inflammation and obesity/metabolic syndrome in wild-type hosts and promoted robust colitis in mice predisposed to this disorder. Emulsifier-induced metabolic syndrome was associated with microbiota encroachment, altered species composition and increased pro-inflammatory potential. Use of germ-free mice and faecal transplants indicated that such changes in microbiota were necessary and sufficient for both low-grade inflammation and metabolic syndrome. These results support the emerging concept that perturbed host–microbiota interactions resulting in low-grade inflammation can promote adiposity and its associated metabolic effects. Moreover, they suggest that the broad use of emulsifying agents might be contributing to an increased societal incidence of obesity/metabolic syndrome and other chronic inflammatory diseases.

  • Subscribe to Nature for full access:



Additional access options:

Already a subscriber?  Log in  now or  Register  for online access.


Primary accessions

European Nucleotide Archive

Data deposits

Sequencing data are deposited in the European Nucleotide Archive under accession number PRJEB8035.


  1. 1.

    et al. The inner of the two Muc2 mucin-dependent mucus layers in colon is devoid of bacteria. Proc. Natl Acad. Sci. USA 105, 15064–15069 (2008)

  2. 2.

    et al. Translocation of Crohn’s disease Escherichia coli across M-cells: contrasting effects of soluble plant fibres and emulsifiers. Gut 59, 1331–1339 (2010)

  3. 3.

    , & Mucosal flora in Crohn’s disease and ulcerative colitis - an overview. J. Physiol. Pharmacol. 60 (Suppl 6). 61–71 (2009)

  4. 4.

    Food Safety Commission [of Japan]. Evaluation Report of Food Additives (Polysorbates 20, 60, 65 and 80) (2007) [transl.]

  5. 5.

    Toxicology and Carcinogenesis Studies of Polysorbate 80 (CAS No. 9005–65–6) in F344/N Rats and B6C3F1 Mice (Feed Studies). Natl. Toxicol. Program Tech. Rep. Ser. 415, 1–225 (1992)

  6. 6.

    et al. Bacterial overgrowth and inflammation of small intestine after carboxymethylcellulose ingestion in genetically susceptible mice. Inflamm. Bowel Dis. 15, 359–364 (2009)

  7. 7.

    , , , & Interleukin-10-deficient mice develop chronic enterocolitis. Cell 75, 263–274 (1993)

  8. 8.

    et al. Deletion of TLR5 results in spontaneous colitis in mice. J. Clin. Invest. 117, 3909–3921 (2007)

  9. 9.

    et al. Familial transmission rather than defective innate immunity shapes the distinct intestinal microbiota of TLR-deficient mice. J. Exp. Med. 209, 1445–1456 (2012)

  10. 10.

    , & Intestinal epithelial cell Toll-like receptor 5 regulates the intestinal microbiota to prevent low-grade inflammation and metabolic syndrome in mice. Gastroenterology 147, 1363–1377 (2014)

  11. 11.

    & Preservation of mucus in histological sections, immunostaining of mucins in fixed tissue, and localization of bacteria with FISH. Methods Mol. Biol. 842, 229–235 (2012)

  12. 12.

    & UniFrac: a new phylogenetic method for comparing microbial communities. Appl. Environ. Microbiol. 71, 8228–8235 (2005)

  13. 13.

    , , , & Host-bacterial mutualism in the human intestine. Science 307, 1915–1920 (2005)

  14. 14.

    et al. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 444, 1027–1031 (2006)

  15. 15.

    et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464, 59–65 (2010)

  16. 16.

    et al. Mucolytic bacteria with increased prevalence in IBD mucosa augment in vitro utilization of mucin by other bacteria. Am. J. Gastroenterol. 105, 2420–2428 (2010)

  17. 17.

    et al. Intestinal inflammation targets cancer-inducing activity of the microbiota. Science 338, 120–123 (2012)

  18. 18.

    et al. Transient inability to manage proteobacteria promotes chronic gut inflammation in TLR5-deficient mice. Cell Host Microbe 12, 139–152 (2012)

  19. 19.

    , , & IBD-what role do Proteobacteria play? Nature Rev. Gastroenterol. Hepatol. 9, 219–230 (2012)

  20. 20.

    et al. Altering the intestinal microbiota during a critical developmental window has lasting metabolic consequences. Cell 158, 705–721 (2014)

  21. 21.

    , , , & AIEC pathobiont instigates chronic colitis in susceptible hosts by altering microbiota composition. Gut 63, 1069–1080 (2014)

  22. 22.

    et al. Detectable serum flagellin and lipopolysaccharide and upregulated anti-flagellin and lipopolysaccharide immunoglobulins in human short bowel syndrome. Am. J. Physiol. Regul. Integr. Comp. Physiol. 294, R402–R410 (2008)

  23. 23.

    et al. Fecal lipocalin 2, a sensitive and broadly dynamic non-invasive biomarker for intestinal inflammation. PLoS ONE 7, e44328 (2012)

  24. 24.

    et al. Dietary-fat-induced taurocholic acid promotes pathobiont expansion and colitis in Il10−/− mice. Nature 487, 104–108 (2012)

  25. 25.

    et al. Helicobacter hepaticus triggers colitis in specific-pathogen-free interleukin-10 (IL-10)-deficient mice through an IL-12- and gamma interferon-dependent mechanism. Infect. Immun. 66, 5157–5166 (1998)

  26. 26.

    & Inflammatory mechanisms in obesity. Annu. Rev. Immunol. 29, 415–445 (2011)

  27. 27.

    et al. Metabolic syndrome and altered gut microbiota in mice lacking Toll-like receptor 5. Science 328, 228–231 (2010)

  28. 28.

    et al. Divergent metabolic adaptations to intestinal parasitic nematode infection in mice susceptible or resistant to obesity. Gastroenterology 133, 1979–1988 (2007)

  29. 29.

    et al. Commensal microbe-derived butyrate induces the differentiation of colonic regulatory T cells. Nature 504, 446–450 (2013)

  30. 30.

    et al. Artificial sweeteners induce glucose intolerance by altering the gut microbiota. Nature 514, 181–186 (2014)

  31. 31.

    et al. Detection of pathogenic intestinal bacteria by Toll-like receptor 5 on intestinal CD11c+ lamina propria cells. Nature Immunol. 7, 868–874 (2006)

  32. 32.

    et al. Adherent-invasive Escherichia coli induce claudin-2 expression and barrier defect in CEABAC10 mice and Crohn’s disease patients. Inflamm. Bowel Dis. 18, 294–304 (2012)

  33. 33.

    et al. Targeted deletion of metalloproteinase 9 attenuates experimental colitis in mice: central role of epithelial-derived MMP. Gastroenterology 129, 1991–2008 (2005)

  34. 34.

    et al. Toll-like receptor 9-induced type I IFN protects mice from experimental colitis. J. Clin. Invest. 115, 695–702 (2005)

  35. 35.

    et al. Elevated flagellin-specific immunoglobulins in Crohn’s disease. Am. J. Physiol. Gastrointest. Liver Physiol. 288, G403–G406 (2005)

  36. 36.

    et al. A core gut microbiome in obese and lean twins. Nature 457, 480–484 (2009)

  37. 37.

    et al. The Earth Microbiome Project: Meeting report of the “1 EMP meeting on sample selection and acquisition” at Argonne National Laboratory October 6 2010. Stand. Genomic Sci. 3, 249–253 (2010)

  38. 38.

    et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 6, 1621–1624 (2012)

  39. 39.

    et al. QIIME allows analysis of high-throughput community sequencing data. Nature Methods 7, 335–336 (2010)

  40. 40.

    Comparison of sequencing utility programs. Open Bioinformatics J. 7, 1–8 (2013)

  41. 41.

    Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460–2461 (2010)

  42. 42.

    et al. An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. ISME J. 6, 610–618 (2012)

  43. 43.

    , & FastTree: computing large minimum evolution trees with profiles instead of a distance matrix. Mol. Biol. Evol. 26, 1641–1650 (2009)

  44. 44.

    , & UniFrac–an online tool for comparing microbial community diversity in a phylogenetic context. BMC Bioinformatics 7, 371 (2006)

  45. 45.

    , , & Diagnosis of multiple cancer types by shrunken centroids of gene expression. Proc. Natl Acad. Sci. USA 99, 6567–6572 (2002)

Download references


This work was supported by NIH grant DK099071 and DK083890. B.C. is a recipient of the Research Fellowship award from the Crohn’s and Colitis Foundation of America (CCFA). We thank B. Zhang, L. Etienne-Mesmin, H. Q. Tran and E. Viennois for technical assistance.

Author information


  1. Center for Inflammation, Immunity and Infection, Institute for Biomedical Sciences, Georgia State University, Atlanta, Georgia 30303, USA

    • Benoit Chassaing
    •  & Andrew T. Gewirtz
  2. Faculty of Medicine, Bar Ilan University, Safed, 13115, Israel

    • Omry Koren
  3. Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York 14853, USA

    • Julia K. Goodrich
    • , Angela C. Poole
    •  & Ruth E. Ley
  4. Digestive Diseases Division, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia 30322, USA

    • Shanthi Srinivasan


  1. Search for Benoit Chassaing in:

  2. Search for Omry Koren in:

  3. Search for Julia K. Goodrich in:

  4. Search for Angela C. Poole in:

  5. Search for Shanthi Srinivasan in:

  6. Search for Ruth E. Ley in:

  7. Search for Andrew T. Gewirtz in:


B.C. and A.T.G. conceived the project, designed the experiments, interpreted the results, and wrote the manuscript. B.C. performed all experiments and analysis with advice and guidance from O.K., J.K.G., and A.C.P. S.S. and R.E.L. guided experimental design and data interpretation.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Andrew T. Gewirtz.

Extended data

Supplementary information

PDF files

  1. 1.

    Supplementary Table 1

    This table contains analysis of taxonomic abundances at the phyla, class, order and family level. WT, IL10-/- and TLR5-/- mice were exposed to drinking water containing CMC or P80 (1.0%) for 12 weeks. Microbiota composition was analyzed. Taxonomic abundances were analyzed at different levels (phyla, class, order and family). All the significantly altered groups upon emulsifier exposure are highlighted in bold. p-values were calculated using a 2-tailed t-test.

  2. 2.

    Supplementary Table 2

    This table shows OTUs statistically different between water-treated group and emulsifier-treated group. WT, IL10-/- and TLR5-/- mice were exposed to drinking water containing CMC or P80 (1.0%) for 12 weeks. Microbiota composition was analyzed. Table lists all OTUs found to be statistically different between water-treated group and emulsifier-treated groups. All OTUs that were previously described to have mucolytic properties are highlighted in purple. p-values were calculated using a 2-tailed t-test.

  3. 3.

    Supplementary Table 3

    This table contains prevalence analysis of the OTUs found to be related to Helicobacter genus. WT, IL10-/- and TLR5-/- mice were exposed to drinking water containing CMC or P80 (1.0%) for 12 weeks. Microbiota composition was analyzed. Prevalence of the OTUs 470487, 2729098, 102480 and 3319464 (Greengenes Prok_MSA IDs), assigned to belong to the Helicobacter genus, were analyzed. p-values were calculated using a 2-tailed t-test.


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.