Microbiota imbalance induced by dietary sugar disrupts immune-mediated protection from metabolic syndrome
Open accessAbstract
How intestinal microbes regulate metabolic syndrome is incompletely understood. We show that intestinal microbiota protects against development of obesity, metabolic syndrome, and pre-diabetic phenotypes by inducing commensal-specific Th17 cells. High-fat, high-sugar diet promoted metabolic disease by depleting Th17-inducing microbes, and recovery of commensal Th17 cells restored protection. Microbiota-induced Th17 cells afforded protection by regulating lipid absorption across intestinal epithelium in an IL-17-dependent manner. Diet-induced loss of protective Th17 cells was mediated by the presence of sugar. Eliminating sugar from high-fat diets protected mice from obesity and metabolic syndrome in a manner dependent on commensal-specific Th17 cells. Sugar and ILC3 promoted outgrowth of Faecalibaculum rodentium that displaced Th17-inducing microbiota. These results define dietary and microbiota factors posing risk for metabolic syndrome. They also define a microbiota-dependent mechanism for immuno-pathogenicity of dietary sugar and highlight an elaborate interaction between diet, microbiota, and intestinal immunity in regulation of metabolic disorders.
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Unhealthy dietary interventions, such as high-fat, high-sugar, and high-salt interventions, negatively impact the gut microbiome and induce intestinal inflammation by impairing TH17 cell functions.
“Unhealthy dietary interventions, such as high-fat, high-sugar, and high-salt interventions, have been shown to negatively impact the gut microbiome and induce intestinal inflammation by impairing TH17 cell functions.698–700”
From Microbiota–gut–brain axis and its therapeutic applications in neurodegenerative diseases (2024) · cites this paper as [700]
CD5L is selectively expressed by non-pathogenic in vitro Th17 cells and inhibits their acquisition of a pathogenic phenotype.
“CD5 antigen-like (CD5L), a regulator of lipid metabolism, was selectively expressed by Th17 cells differentiated in vitro under non-pathogenic conditions, and was shown to inhibit Th17 cells to attain a pathogenic Th17 cell phenotype”
From TH17 cell heterogeneity and its role in tissue inflammation (2023) · cites this paper as [57]
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Kennedy, D. J., & Kashyap, S. R. (2011) · Metabolic Syndrome and Related Disorders · doi:10.1089/met.2011.0003 · Cited by 50 · see citing works
Yang, J., Park, K., & Cho, S. (2018) · Journal of Biological Chemistry · doi:10.1074/jbc.ra118.002405 · Cited by 48 · see citing works
Deregulated Lipid Sensing by Intestinal CD36 in Diet-Induced Hyperinsulinemic Obese Mouse Model
Buttet, M., Poirier, H., Traynard, V., Kévin, G., Tran, T. T. T., Sundaresan, S., Besnard, P., Abumrad, N. A., & Niot, I. (2016) · PLoS ONE · doi:10.1371/journal.pone.0145626 · Cited by 45 · see citing works
Barros, M. T. (2001) · Revista do Instituto de Medicina Tropical de São Paulo · doi:10.1590/s0036-46652001000600016 · Cited by 5 · see citing works
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Microbiota–gut–brain axis and its therapeutic applications in neurodegenerative diseases
Loh, J. S., Mak, W. Q., Tan, L. K. S., Ng, C. X., Chan, H. H., Yeow, S. H., Foo, J. B., Ong, Y. S., How, C. W., & Khaw, K. Y. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-01743-1 · Cited by 1,193 · see citing works
TH17 cell heterogeneity and its role in tissue inflammation
Schnell, A., Littman, D. R., & Kuchroo, V. K. (2023) · Nature Immunology · doi:10.1038/s41590-022-01387-9 · Cited by 286 · see citing works
The gut microbiome in Alzheimer’s disease: what we know and what remains to be explored
Chandra, S., Sisodia, S. S., & Vassar, R. J. (2023) · Molecular Neurodegeneration · doi:10.1186/s13024-023-00595-7 · Cited by 278 · see citing works
Microbiota in inflammatory bowel disease: mechanisms of disease and therapeutic opportunities
Iliev, I. D., Ananthakrishnan, A. N., & Guo, C.-J. (2025) · Nature Reviews Microbiology · doi:10.1038/s41579-025-01163-0 · Cited by 249 · see citing works
Short-term dietary changes can result in mucosal and systemic immune depression
Siracusa, F., Schaltenberg, N., Kumar, Y., Lesker, T. R., Steglich, B., Liwinski, T., Cortesi, F., Frommann, L., Diercks, B.-P., Bönisch, F., et al. (2023) · Nature Immunology · doi:10.1038/s41590-023-01587-x · Cited by 64 · see citing works
Interleukin-17 as a key player in neuroimmunometabolism
Douglas, A., Stevens, B., & Lynch, L. (2023) · Nature Metabolism · doi:10.1038/s42255-023-00846-3 · Cited by 49 · see citing works
Song, Z., Chen, J., Ji, Y., Yang, Q., Chen, Y., Wang, F., & Wu, Z. (2023) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2023.124650 · Cited by 34 · see citing works
- Authors
- Kawano, Y., Edwards, M., Huang, Y., Bilate, A. M., Araujo, L. P., Tanoue, T., Atarashi, K., Ladinsky, M. S., Reiner, S. L., Wang, H. H., Mucida, D., Honda, K., & Ivanov, I. I.
- Affiliations
- Columbia University (US)
- Rockefeller University (US)
- Keio University (JP)
- California Institute of Technology (US)
- Columbia University Irving Medical Center (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Ivanov, Ivaylo I.
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2022-09
- Volume
- 185
- Issue
- 19
- Pages
- 3501-3519.e20
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC9556172
- OpenAlex
- W4293462145
- Cited by
- 349
- References
- 84
- Citations by year
- 2026: 72 · 2025: 106 · 2024: 82 · 2023: 77 · 2022: 12
- FWCI
- 22.59
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 401 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- CaltechAUTHORS (California Institute of Technology) (submittedVersion)
- Funders
- Japan Society for the Promotion of Science (20H05627)
- National Human Genome Research Institute (RM1HG009490)
- National Institute of Allergy and Infectious Diseases (U01AI163069, R01AI144808, R21AI146817, R56AI076458, R01AI132403)
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK118044, R01DK113375, R01DK093674, R01DK098378, P30DK132710)
- National Institute of Biomedical Imaging and Bioengineering (R01EB031935)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Health Sciences › Medicine › Epidemiology › Adipokines, Inflammation, and Metabolic Diseases
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diet, Metabolism, and Disease
- Keywords
- gut microbiota, dietary sugar, metabolic syndrome, obesity, Th17 cells, IL-17, fat absorption, high-fat high-sugar diet, ILC3, Faecalibaculum rodentium, commensal bacteria, intestinal immunity, prediabetes
- MeSH terms
- Dietary Sugars, Animals, Intestinal Mucosa, Lipids, Mice, Inbred C57BL, Obesity, Interleukin-17, Metabolic Syndrome, Mice, Th17 Cells, Diet, High-Fat, Microbiota
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.
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