Cited by 19Gut microbiota and healthGastrointestinal motility and disordersMicrobial Metabolites in Food Biotechnology

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In vitro microbiota model recapitulates and predicts individualised sensitivity to dietary emulsifier

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Rytter, Héloïse, Naimi, Sabrine, Wu, Gary, Lewis, Jim, Duquesnoy, Maeva, Vigué, Lucile, Tenaillon, Olivier, Belda, Eugeni, Vazquez-Gomez, Marta, Touly, Nina, Arnone, Djésia, Hao, Fuhua, Ley, Ruth E, Clément, Karine, Peyrin-Biroulet, Laurent, Patterson, Andrew D, Gewirtz, Andrew T, Chassaing, Benoit·2025·Gut

Abstract

Background: Non-absorbed dietary emulsifiers, including carboxymethylcellulose (CMC), directly disturb intestinal microbiota, thereby promoting chronic intestinal inflammation in mice. A randomised controlled-feeding study (Functional Research on Emulsifiers in Humans, FRESH) found that CMC also detrimentally impacts intestinal microbiota in some, but not all, healthy individuals. Objectives: This study aimed to establish an approach for predicting an individual’s sensitivity to dietary emulsifiers via their baseline microbiota. Design: We evaluated the ability of an in vitro microbiota model (MiniBioReactor Arrray, MBRA) to reproduce and predict an individual donor’s sensitivity to emulsifiers. Metagenomes were analysed to identify signatures of emulsifier sensitivity. Results: Exposure of human microbiotas, maintained in the MBRA, to CMC recapitulated the differential CMC sensitivity previously observed in FRESH subjects. Furthermore, select FRESH control subjects (ie, not fed CMC) had microbiotas that were highly perturbed by CMC exposure in the MBRA model. CMC-induced microbiota perturbability was associated with a baseline metagenomic signature, suggesting the possibility of using one’s metagenome to predict sensitivity to dietary emulsifiers. Transplant of human microbiotas that the MBRA model deemed CMC-sensitive, but not those deemed insensitive, into IL-10 −/− germfree mice resulted in overt colitis following CMC feeding. Conclusion: These results suggest that an individual’s sensitivity to emulsifier is a consequence of, and can thus be predicted by, examining their baseline microbiota, paving the way to microbiota-based personalised nutrition.

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  1. 10.1038/nri2710 · DOI
  2. 10.1172/JCI72330 · DOI
  3. 10.1111/jgh.16043 · DOI
  4. 10.1016/j.trim.2023.101835 · DOI
  5. 10.1016/S0140-6736(17)32448-0 · DOI · Paper page
  6. 10.1093/ecco-jcc/jjac167 · DOI
  7. 10.1053/j.gastro.2019.06.027 · DOI
  8. 10.1111/apt.15045 · DOI
  9. Marion-Letellier, 2019, Inflammatory Bowel Diseases and Food Additives: To Add Fuel on the Flames!, Nutrients, 11, 10.3390/nu11051111 · DOI
  10. 10.1016/j.ypmed.2019.05.004 · DOI
  11. Naimi, 2021, Direct impact of commonly used dietary emulsifiers on human gut microbiota, Microbiome, 9, 10.1186/s40168-020-00996-6 · DOI
  12. Chassaing, 2017, Colonic Microbiota Encroachment Correlates With Dysglycemia in Humans, Cell Mol Gastroenterol Hepatol, 4, 205, 10.1016/j.jcmgh.2017.04.001 · DOI
  13. 10.1128/IAI.01341-08 · DOI
  14. 10.1053/j.gastro.2021.11.006 · DOI · Paper page
  15. Daniel, 2024, Human Intestinal Microbiome Determines Individualized Inflammatory Response to Dietary Emulsifier Carboxymethylcellulose Consumption, Cell Mol Gastroenterol Hepatol, 17, 315, 10.1016/j.jcmgh.2023.11.001 · DOI · Paper page
  16. Auchtung, 2015, Cultivation of stable, reproducible microbial communities from different fecal donors using minibioreactor arrays (MBRAs), Microbiome, 3, 10.1186/s40168-015-0106-5 · DOI
  17. 10.1007/978-1-4939-6361-4_18 · DOI
  18. Schneeberger, 2015, Akkermansia muciniphila inversely correlates with the onset of inflammation, altered adipose tissue metabolism and metabolic disorders during obesity in mice, Sci Rep, 5, 10.1038/srep16643 · DOI · Paper page
  19. 10.1136/gutjnl-2014-308778 · DOI · Paper page
  20. 10.1038/s41575-022-00631-9 · DOI · Paper page
  21. Cao, 2014, Association between Faecalibacterium prausnitzii Reduction and Inflammatory Bowel Disease: A Meta-Analysis and Systematic Review of the Literature, Gastroenterol Res Pract, 2014, 872725, 10.1155/2014/872725 · DOI
  22. 10.1016/j.mib.2013.06.003 · DOI
  23. 10.1136/gutjnl-2012-303207 · DOI · Paper page
  24. Chassaing, 2018, Mice harboring pathobiont-free microbiota do not develop intestinal inflammation that normally results from an innate immune deficiency, PLoS One, 13, 10.1371/journal.pone.0195310 · DOI
  25. 10.1038/s41586-020-2269-x · DOI
  26. 10.1053/j.gastro.2019.04.021 · DOI
  27. 10.1016/j.cgh.2020.04.006 · DOI
  28. 10.1097/MIB.0000000000000110 · DOI
  29. Hobson, 2022, MiniBioReactor Array (MBRA) in vitro gut model: a reliable system to study microbiota-dependent response to antibiotic treatment, JAC Antimicrob Resist, 4, 10.1093/jacamr/dlac077 · DOI
  30. Hobson, 2022, A Microbiota-Dependent Response to Anticancer Treatment in an In Vitro Human Microbiota Model: A Pilot Study With Hydroxycarbamide and Daunorubicin, Front Cell Infect Microbiol, 12, 10.3389/fcimb.2022.886447 · DOI
  31. Sellem, 2024, Food additive emulsifiers and cancer risk: Results from the French prospective NutriNet-Santé cohort, PLoS Med, 21, 10.1371/journal.pmed.1004338 · DOI
  32. 10.1016/S2213-8587(24)00086-X · DOI
  33. Sellem, 2023, Food additive emulsifiers and risk of cardiovascular disease in the NutriNet-Santé cohort: prospective cohort study, BMJ, 382, 10.1136/bmj-2023-076058 · DOI
  34. Iizuka, 2022, Is the Use of Artificial Sweeteners Beneficial for Patients with Diabetes Mellitus? The Advantages and Disadvantages of Artificial Sweeteners, Nutrients, 14, 10.3390/nu14214446 · DOI
  35. 10.1016/j.bbrc.2024.150798 · DOI
  36. Palmnäs, 2014, Low-dose aspartame consumption differentially affects gut microbiota-host metabolic interactions in the diet-induced obese rat, PLoS One, 9, 10.1371/journal.pone.0109841 · DOI
  37. 10.1016/j.cell.2022.07.016 · DOI · Paper page
  38. Bonazzi, 2024, Individualized microbiotas dictate the impact of dietary fiber on colitis sensitivity, Microbiome, 12, 10.1186/s40168-023-01724-6 · DOI
  39. 10.1038/ismej.2012.8 · DOI · Paper page
  40. 10.4056/aigs.1443528 · DOI
  41. 10.1038/s41587-019-0209-9 · DOI · Paper page
  42. 10.1038/nmeth.3869 · DOI · Paper page
  43. 10.1038/ismej.2011.139 · DOI
  44. 10.1039/c2an35392j · DOI
  45. 10.1021/pr2011507 · DOI
  46. 10.1089/cmb.2017.0096 · DOI
  47. Inam, 2022, Impact of Antibiotics on the Lung Microbiome and Lung Function in Children With Cystic Fibrosis 1 Year After Hospitalization for an Initial Pulmonary Exacerbation, Open Forum Infect Dis, 9, 10.1093/ofid/ofac466 · DOI
  48. 10.1177/0023677214544728 · DOI
  49. 10.1172/JCI200522996 · DOI
  50. Chassaing, 2012, Fecal lipocalin 2, a sensitive and broadly dynamic non-invasive biomarker for intestinal inflammation, PLoS One, 7, 10.1371/journal.pone.0044328 · DOI
  51. 10.1007/978-1-61779-513-8_13 · DOI

Metadata

Authors
Rytter, H., Naimi, S., Wu, G., Lewis, J., Duquesnoy, M., Vigué, L., Tenaillon, O., Belda, E., Vazquez-Gomez, M., Touly, N., Arnone, D., Hao, F., Ley, R. E., Clément, K., Peyrin-Biroulet, L., Patterson, A. D., Gewirtz, A. T., & Chassaing, B.
Affiliations
  • Centre National de la Recherche Scientifique (FR)
  • University of Pennsylvania (US)
  • Microbiome-Host Interactions, INSERM U1306, CNRS UMR6047, Institut Pasteur, Université Paris Cité, Paris, France
  • Inserm (FR)
  • Inserm, Nutrition and Obesities: Systemic Approaches Research Unit, NutriOmics, Sorbonne University, Paris, France
  • Pennsylvania State University (US)
  • Max Planck Institute for Biology (DE)
  • INFINY Institute, Nancy University Hospital, Vandœuvre-lès-Nancy, France
  • Georgia State University (US)
Venue
Gut
Publisher
BMJ
Published
2025-01-27
Volume
74
Issue
5
Pages
761-774
ISSN
  • 0017-5749 (ISSN-L)
  • 1468-3288
OpenAlex
W4406870625
Cited by
19
References
7
Citations by year
2026: 12 · 2025: 7
FWCI
5.71
Type
journal article
Language
en
Open access
Locations
  • Gut (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • HAL (submittedVersion, cc-by)
Funders
  • EMULBIONT (ANR-21-CE15-0042-01)
  • Paris Région – DIM One Health-DOH 2.0
  • European Research Council
  • INSERM
  • DREAM (ANR-20-PAMR-0002)
  • the Kenneth Rainin Foundation, ANR (ANR-21-CE15-0042-01)
  • European Union (804135, ERC-2018-StG)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Health Sciences › Medicine › Gastroenterology › Gastrointestinal motility and disorders
  • Health Sciences › Nursing › Nutrition and Dietetics › Microbial Metabolites in Food Biotechnology
Keywords
food emulsifiers, carboxymethyl cellulose, gut microbiota, microbiota transplantation, colitis, personalized nutrition, chronic intestinal inflammation
MeSH terms
Gastrointestinal Microbiome, Animals, Carboxymethylcellulose Sodium, Female, Humans, Male, Interleukin-10, Emulsifying Agents, Mice

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