The DOI matches its Crossref record; 47 of the 48 references it cites were found in a registry or an index.
Intestinal Epithelial Cell Toll-like Receptor 5 Regulates the Intestinal Microbiota to Prevent Low-Grade Inflammation and Metabolic Syndrome in Mice
Open accessAbstract
Background & aims Mice lacking the receptor Toll-like receptor 5 (TLR5-null mice), which recognizes flagellin, have an altered intestinal microbiota composition compared with wild-type mice; they develop low-grade inflammation and metabolic syndrome and are prone to colitis. The relative roles of intestinal epithelial cell (IEC) vs dendritic cell (DC) TLR5 in mediating these phenotypes are not clear; modification of intestinal microbiota composition has been reported to reflect animal husbandry practices rather than loss of TLR5. We generated mice with specific disruption of Tlr5 in IECs or DCs by using a breeding scheme that allows comparison with cohoused siblings as controls.Methods We generated C57BL/6 mice with LoxP sites flanking Tlr5. These mice were crossed with mice expressing Cre recombinase, regulated by the villin or CD11c promoters, to generate mice that lacked expression of TLR5 by IECs (TLR5(ΔIEC)) or DCs (TLR5(ΔDC)), respectively. Tlr5(fl/fl) siblings were used as controls. On weaning, mice were housed by sex and genotype or by sex only (genotypes cohoused). Mice were examined for basal phenotypes, including microbiota composition; we also analyzed responses to pathobiont challenge, administration of dextran sodium sulfate, and high-fat diets.Results Similar to previous findings from TLR5-null mice, TLR5(ΔIEC) mice had low-grade inflammation (mild splenomegaly, shortened colons, and increased fecal levels of lipocalin 2), metabolic syndrome, and an inability to clear pathobionts and were prone to developing colitis compared with their sibling controls under both housing conditions. Development of this inflammation in the TLR5(ΔIEC) mice was eliminated by administration of antibiotics and associated with alterations in localization of microbiota and levels of fecal lipopolysaccharide and flagellin. The composition of the microbiota clustered more closely according to genotype than housing. Loss of TLR5 from DCs did not associate with development of inflammation-associated phenotypes or alterations in the composition of the microbiota but resulted in complete loss of flagellin-induced production of interleukin-22.Conclusions In mice, flagellin activation of TLR5 on DCs leads to production of interleukin-22. Expression of TLR5 on IECs regulates the composition and localization of the intestinal microbiota, preventing diseases associated with intestinal inflammation.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“It was demonstrated in numerous reports from Dr Gewirtz’s group that expression and activation of TLR5 on IECs regulates the composition and localization of microbiota and prevents disease associated intestinal inflammation.165, 166, 167, 168”
From Regulation of Intestinal Barrier Function by Microbial Metabolites (2021) · cites this paper as [165]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
1 retracted
Gut Microbiota Is a Key Modulator of Insulin Resistance in TLR 2 Knockout Mice
Caricilli, A. M., Picardi, P. K., de Abreu, L. L., Ueno, M., Prada, P. O., Ropelle, E. R., Hirabara, S. M., Castoldi, Â., Moraes‐Vieira, P. M., Câmara, N. O. S., et al. (2011) · PLoS Biology · doi:10.1371/journal.pbio.1001212 · Cited by 285
RetractedQIIME allows analysis of high-throughput community sequencing data
Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., Fierer, N., Peña, A. G., Goodrich, J. K., Gordon, J. I., et al. (2010) · Nature Methods · doi:10.1038/nmeth.f.303 · Cited by 34,887
Self-citationSearch and clustering orders of magnitude faster than BLAST
Edgar, R. C. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq461 · Cited by 21,098
Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms
Caporaso, J. G., Lauber, C. L., Walters, W. A., Berg-Lyons, D., Huntley, J., Fierer, N., Owens, S. M., Betley, J., Fraser, L., Bauer, M., et al. (2012) · The ISME Journal · doi:10.1038/ismej.2012.8 · Cited by 8,839
UniFrac: a New Phylogenetic Method for Comparing Microbial Communities
Lozupone, C., & Knight, R. (2005) · Applied and Environmental Microbiology · doi:10.1128/aem.71.12.8228-8235.2005 · Cited by 8,227
FastTree: Computing Large Minimum Evolution Trees with Profiles instead of a Distance Matrix
Price, M. N., Dehal, P. S., & Arkin, A. P. (2009) · Molecular Biology and Evolution · doi:10.1093/molbev/msp077 · Cited by 5,602
McDonald, D. T., Price, M. N., Goodrich, J. K., Nawrocki, E. P., DeSantis, T. Z., Probst, A. J., Andersen, G. L., Knight, R. D., & Hugenholtz, P. (2011) · The ISME Journal · doi:10.1038/ismej.2011.139 · Cited by 5,144
Meyer, F., Paarmann, D., D'Souza, M., Olson, R., Glass, E., Kubal, M., Paczian, T., Rodriguez, A., Stevens, R. L., Wilke, A., et al. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-386 · Cited by 3,565
Diagnosis of multiple cancer types by shrunken centroids of gene expression
Tibshirani, R. J., Hastie, T. J., Narasimhan, B., & Chu, G. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.082099299 · Cited by 2,931
The inner of the two Muc2 mucin-dependent mucus layers in colon is devoid of bacteria
Johansson, M. E. V., Phillipson, M., Petersson, J., Velcich, A., Holm, L., & Hansson, G. C. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0803124105 · Cited by 2,200
Research works printed but not linked: 6
- Uematsu, 2006, Detection of pathogenic intestinal bacteria by Toll-like receptor 5 on intestinal CD11c+ lamina propria cells, Nat Immunol, 7, 868, 10.1038/ni1362 · DOI
- Vijay-Kumar, 2010, Metabolic syndrome and altered gut microbiota in mice lacking Toll-like receptor 5, Science, 328, 228, 10.1126/science.1179721 · DOI · Paper page
- Chassaing, 2012, Fecal lipocalin 2, a sensitive and broadly dynamic non-invasive biomarker for intestinal inflammation, PLoS One, 7, e44328, 10.1371/journal.pone.0044328 · DOI
- Carvalho, 2012, Cytosolic flagellin receptor NLRC4 protects mice against mucosal and systemic challenges, Mucosal Immunol, 5, 288, 10.1038/mi.2012.8 · DOI
- Chassaing, 2014, AIEC pathobiont instigates chronic colitis in susceptible hosts by altering microbiota composition, Gut, 63, 1069, 10.1136/gutjnl-2013-304909 · DOI
- Carvalho, 2012, Transient inability to manage proteobacteria promotes chronic gut inflammation in TLR5-deficient mice, Cell Host Microbe, 12, 139, 10.1016/j.chom.2012.07.004 · DOI · Paper page
Cited by
Sorted by citations
Dietary emulsifiers impact the mouse gut microbiota promoting colitis and metabolic syndrome
Chassaing, B., Koren, O., Goodrich, J. K., Poole, A. C., Srinivasan, S., Ley, R. E., & Gewirtz, A. T. (2015) · Nature · doi:10.1038/nature14232 · Cited by 2,055
Self-citationHuman gut microbiome: Hopes, threats and promises
Cani, P. D. (2018) · Gut · doi:10.1136/gutjnl-2018-316723 · Cited by 1,386
Regulation of Intestinal Barrier Function by Microbial Metabolites
Ghosh, S., Whitley, C. S., Haribabu, B., & Jala, V. R. (2021) · Cellular and Molecular Gastroenterology and Hepatology · doi:10.1016/j.jcmgh.2021.02.007 · Cited by 835
Gut Microbiota as a Trigger for Metabolic Inflammation in Obesity and Type 2 Diabetes
Scheithauer, T. P. M., Rampanelli, E., Nieuwdorp, M., Vallance, B. A., Verchere, C. B., van Raalte, D. H., & Herrema, H. (2020) · Frontiers in Immunology · doi:10.3389/fimmu.2020.571731 · Cited by 715
Zou, J., Chassaing, B., Singh, V., Pellizzon, M., Ricci, M. R., Flythe, M. D. D., Kumar, M. V., & Gewirtz, A. T. (2017) · Cell Host & Microbe · doi:10.1016/j.chom.2017.11.003 · Cited by 570
Metadata
- Authors
- Chassaing, B., Ley, R. E., & Gewirtz, A. T.
- Affiliations
- Cornell University (US)
- Georgia State University (US)
- Corresponding author
- Gewirtz, Andrew T.
- Venue
- Gastroenterology
- Publisher
- Elsevier BV
- Published
- 2014-12
- Volume
- 147
- Issue
- 6
- Pages
- 1363-1377.e17
- ISSN
- 0016-5085 (ISSN-L)
- PMC
- PMC4253564
- OpenAlex
- W2090488505
- Cited by
- 326
- References
- 48
- Citations by year
- 2026: 20 · 2025: 25 · 2024: 38 · 2023: 31 · 2022: 29 · 2021: 39 · 2020: 33 · 2019: 28 · 2018: 23 · 2017: 23 · 2016: 17 · 2015: 18 · 2014: 2
- FWCI
- 8.19
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Gastroenterology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (DK083890, DK099071)
- Crohn's and Colitis Foundation of America (DK083890, DK099071)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Life Sciences › Immunology and Microbiology › Immunology › Immune Response and Inflammation
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Adipokines, Inflammation, and Metabolic Diseases
- Keywords
- TLR5, intestinal epithelial cells, dendritic cells, gut microbiota, flagellin, low-grade inflammation, metabolic syndrome, colitis, IL-22, lipopolysaccharide, pathobionts, DSS-induced colitis, high-fat diet, antibiotic therapy, cohousing, host-microbe interactions
- MeSH terms
- Animals, Colitis, Enteritis, Female, Flagellin, Intestinal Mucosa, Male, Mice, Inbred C57BL, Signal Transduction, Mice, Knockout, Metabolic Syndrome, Toll-Like Receptor 4, Toll-Like Receptor 5, 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.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review