The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
Nlrp6- and ASC-Dependent Inflammasomes Do Not Shape the Commensal Gut Microbiota Composition
Open accessAbstract
The gut microbiota regulate susceptibility to multiple human diseases. The Nlrp6-ASC inflammasome is widely regarded as a hallmark host innate immune axis that shapes the gut microbiota composition. This notion stems from studies reporting dysbiosis in mice lacking these inflammasome components when compared with non-littermate wild-type animals. Here, we describe microbial analyses in inflammasome-deficient mice while minimizing non-genetic confounders using littermate-controlled Nlrp6-deficient mice and ex-germ-free littermate-controlled ASC-deficient mice that were all allowed to shape their gut microbiota naturally after birth. Careful microbial phylogenetic analyses of these cohorts failed to reveal regulation of the gut microbiota composition by the Nlrp6- and ASC-dependent inflammasomes. Our results obtained in two geographically separated animal facilities dismiss a generalizable impact of Nlrp6- and ASC-dependent inflammasomes on the composition of the commensal gut microbiota and highlight the necessity for littermate-controlled experimental design in assessing the influence of host immunity on gut microbial ecology.
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
“In fact, in different facilities, mice lacking ASC, NLRP6 (199), or NLRP3 (200) fail to show any detectable differences in the composition of their fecal flora compared to wild-type controlled littermates (199), either co-housed or individually housed, contrary to what has been described in other facilities (194).”
From The gut-brain axis: how microbiota and host inflammasome influence brain physiology and pathology (2020) · cites this paper as [199]
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
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400
QIIME 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
Cutadapt removes adapter sequences from high-throughput sequencing reads
Martin, M. (2011) · EMBnet.journal · doi:10.14806/ej.17.1.200 · Cited by 33,889
The SILVA ribosomal RNA gene database project: improved data processing and web-based tools
Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P., Peplies, J., & Glöckner, F. O. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1219 · Cited by 33,055
Search and clustering orders of magnitude faster than BLAST
Edgar, R. C. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq461 · Cited by 21,098
Naive Bayesian Classifier for Rapid Assignment of rRNA Sequences into the New Bacterial Taxonomy
Wang, Q., Garrity, G. M., Tiedje, J. M., & Cole, J. R. (2007) · Applied and Environmental Microbiology · doi:10.1128/aem.00062-07 · Cited by 20,145
UCHIME improves sensitivity and speed of chimera detection
Edgar, R. C., Haas, B. J., Clemente, J. C., Quince, C., & Knight, R. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr381 · Cited by 15,114
Klindworth, A., Pruesse, E., Schweer, T., Peplies, J., Quast, C., Horn, M., & Glöckner, F. O. (2013) · Nucleic Acids Research · doi:10.1093/nar/gks808 · Cited by 8,850
Dysfunction of the intestinal microbiome in inflammatory bowel disease and treatment
Morgan, X. C., Tickle, T. L., Sokol, H., Gevers, D., Devaney, K. L., Ward, D. V., Reyes, J. A., Shah, S. A., LeLeiko, N., Snapper, S. B., et al. (2012) · Genome Biology · doi:10.1186/gb-2012-13-9-r79 · Cited by 2,713
Cited by
Sorted by citations
Inflammasome activation and regulation: toward a better understanding of complex mechanisms
Zheng, D., Liwinski, T., & Elinav, E. (2020) · Cell Discovery · doi:10.1038/s41421-020-0167-x · Cited by 1,078
The gut-brain axis: how microbiota and host inflammasome influence brain physiology and pathology
Rutsch, A., Kantsjö, J. B., & Ronchi, F. (2020) · Frontiers in Immunology · doi:10.3389/fimmu.2020.604179 · Cited by 821
Self-citationGut 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
Diverging inflammasome signals in tumorigenesis and potential targeting
Karki, R., & Kanneganti, T. (2019) · Nature reviews. Cancer · doi:10.1038/s41568-019-0123-y · Cited by 650
The influence of the microbiome on respiratory health
Wypych, T. P., Wickramasinghe, L. C., & Marsland, B. J. (2019) · Nature Immunology · doi:10.1038/s41590-019-0451-9 · Cited by 611
Metadata
- Authors
- Mamantopoulos, M., Ronchi, F., Van Hauwermeiren, F., Vieira-Silva, S., Yilmaz, B., Martens, L., Saeys, Y., Drexler, S. K., Yazdi, A. S., Raes, J., Lamkanfi, M., McCoy, K. D., & Wullaert, A.
- Affiliations
- Ghent University (BE)
- University of Bern (CH)
- University of Basel (CH)
- University of Tübingen (DE)
- VIB-KU Leuven Center for Microbiology (BE)
- Corresponding author
- McCoy, Kathy D.
- Wullaert, Andy
- ORCID
- Venue
- Immunity
- Publisher
- Elsevier BV
- Published
- 2017-08
- Volume
- 47
- Issue
- 2
- Pages
- 339-348.e4
- ISSN
- 1074-7613 (ISSN-L)
- OpenAlex
- W2742175177
- Cited by
- 181
- References
- 39
- Citations by year
- 2026: 4 · 2025: 14 · 2024: 18 · 2023: 14 · 2022: 17 · 2021: 15 · 2020: 28 · 2019: 33 · 2018: 28 · 2017: 9
- FWCI
- 10.94
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Immunity (publishedVersion)
- PubMed (publishedVersion)
- Ghent University Academic Bibliography (Ghent University) (submittedVersion)
- BORIS (University Library Bern) (submittedVersion)
- Digital Access to Libraries (submittedVersion, other-oa)
- Lirias (submittedVersion)
- Funders
- SNSF (SNSF310030_134902, PMPDP3_145453)
- European Research Council (FP/2007-2013, 281785, 281600, 683144)
- Marie Heim-Vögtlin fellowship
- ECCO (Odysseus grant G.0C49.13N)
- Fund for Scientific Research-Flanders
- Ghent University Concerted Research Actions (BOF14/GOA/013)
- Baillet Latour Medical Research Grant
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Inflammasome and immune disorders
- Life Sciences › Immunology and Microbiology › Immunology › Immune Response and Inflammation
- Keywords
- NLRP6, ASC, inflammasome, gut microbiota composition, commensal microbiota, host innate immunity, dysbiosis, germ-free mice, host-microbe interactions
- MeSH terms
- Genetic Background, Gastrointestinal Microbiome, Animals, Bacteria, Cells, Cultured, Colitis, Female, Immunity, Innate, Mice, Inbred C57BL, Receptors, Cell Surface, RNA, Ribosomal, 16S, Sodium Dodecyl Sulfate, Mice, Knockout, Apoptosis Regulatory Proteins, Mice, CARD Signaling Adaptor Proteins, Inflammasomes, Microbiota, Dysbiosis
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