The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Longitudinal study of murine microbiota activity and interactions with the host during acute inflammation and recovery
Open accessAbstract
Although alterations in gut microbiota composition during acute colitis have been repeatedly observed, associated functional changes and the recovery from dysbiosis received little attention. In this study, we investigated structure and function of the gut microbiota during acute inflammation and recovery in a dextran sodium sulfate (DSS)-colitis mouse model using metatranscriptomics, bacterial 16S rRNA gene amplicon sequencing and monitoring of selected host markers. Parallel to an increase of host markers of inflammation during acute colitis, we observed relative abundance shifts and alterations in phylotype composition of the dominant bacterial orders Clostridiales and Bacteroidales, and an increase of the low abundant Enterobacteriales, Deferribacterales, Verrucomicrobiales and Erysipelotrichales. During recovery, the microbiota began to resume, but did not reach its original composition until the end of the experiment. Microbial gene expression was more resilient to disturbance, with pre-perturbation-type transcript profiles appearing quickly after acute colitis. The decrease of Clostridiales during inflammation correlated with a reduction of transcripts related to butyrate formation, suggesting a disturbance in host-microbe signalling and mucosal nutrient provision. The impact of acute inflammation on the Clostridiales was also characterized by a significant downregulation of their flagellin-encoding genes. In contrast, the abundance of members of the Bacteroidales increased along with an increase in transcripts related to mucin degradation. We propose that acute inflammation triggered a selective reaction of the immune system against flagella of commensals and temporarily altered murine microbiota composition and functions relevant for the host. Despite changes in specific interactions, the host–microbiota homeostasis revealed a remarkable ability for recovery.
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.
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
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
FLASH: fast length adjustment of short reads to improve genome assemblies
Magoč, T., & Salzberg, S. L. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr507 · Cited by 15,366
Host-gut microbiota metabolic interactions
Nicholson, J. K., Holmes, E., Kinross, J., Burcelin, R., Gibson, G., Jia, W., & Pettersson, S. (2012) · Science · doi:10.1126/science.1223813 · Cited by 4,760
Induction of Colonic Regulatory T Cells by Indigenous Clostridium Species
Atarashi, K., Tanoue, T., Shima, T., Imaoka, A., Kuwahara, T., Momose, Y., Cheng, G., Yamasaki, S., Saito, T., Ohba, Y., et al. (2011) · Science · doi:10.1126/science.1198469 · Cited by 3,752
Reducing the Effects of PCR Amplification and Sequencing Artifacts on 16S rRNA-Based Studies
Schloss, P. D., Gevers, D., & Westcott, S. L. (2011) · PLoS ONE · doi:10.1371/journal.pone.0027310 · Cited by 2,112
Metabolic Syndrome and Altered Gut Microbiota in Mice Lacking Toll-Like Receptor 5
Vijay-Kumar, M., Aitken, J. D., Carvalho, F. A., Cullender, T. C., Mwangi, S., Srinivasan, S., Sitaraman, S. V., Knight, R., Ley, R. E., & Gewirtz, A. T. (2010) · Science · doi:10.1126/science.1179721 · Cited by 2,068
Png, C. W., Lindén, S. K., Gilshenan, K. S., Zoetendal, E. G., McSweeney, C. S., Sly, L. I., McGuckin, M. A., & Florin, T. H. J. (2010) · American Journal of Gastroenterology · doi:10.1038/ajg.2010.281 · Cited by 1,364 · cited 2×
“, 2007), as well as changes in mucus degrader activity (Png et al., 2010).”
BackgroundBacterial flagellin is a dominant antigen in Crohn disease
Lodes, M. J., Cong, Y., Elson, C. O., Mohamath, R., Landers, C. J., Targan, S. R., Fort, M., & Hershberg, R. M. (2004) · Journal of Clinical Investigation · doi:10.1172/jci200420295 · Cited by 802
Integrated Metagenomics/Metaproteomics Reveals Human Host-Microbiota Signatures of Crohn's Disease
Erickson, A. R., Cantarel, B. L., Lamendella, R., Darzi, Y., Mongodin, E. F., Pan, C., Shah, M., Halfvarson, J., Tysk, C., Henrissat, B., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0049138 · Cited by 395
Bacteria Penetrate the Inner Mucus Layer before Inflammation in the Dextran Sulfate Colitis Model
Johansson, M. E. V., Gustafsson, J. K., Sjöberg, K. E., Petersson, J., Holm, L., Sjövall, H., & Hansson, G. C. (2010) · PLoS ONE · doi:10.1371/journal.pone.0012238 · Cited by 368
Cited by
Gut biogeography of the bacterial microbiota
Donaldson, G. P., Lee, S. M., & Mazmanian, S. K. (2016) · Nature Reviews Microbiology · doi:10.1038/nrmicro3552 · Cited by 2,535
Deciphering microbial interactions and detecting keystone species with co-occurrence networks
Berry, D., & Widder, S. (2014) · Frontiers in Microbiology · doi:10.3389/fmicb.2014.00219 · Cited by 1,756
Self-citationEmerging Pathogenic Links Between Microbiota and the Gut-Lung Axis
Budden, K. F., Gellatly, S. L., Wood, D. L. A., Cooper, M. A., Morrison, M., Hugenholtz, P., & Hansbro, P. M. (2017) · Nature Reviews Microbiology · doi:10.1038/nrmicro.2016.142 · Cited by 1,606
The resilience of the intestinal microbiota influences health and disease
Sommer, F., Anderson, J. M., Bharti, R., Raes, J., & Rosenstiel, P. (2017) · Nature Reviews Microbiology · doi:10.1038/nrmicro.2017.58 · Cited by 1,058
Microbial network disturbances in relapsing refractory Crohn’s disease
Swiss IBD Cohort Investigators, Yilmaz, B., Juillerat, P., Øyås, O., Ramon, C., Bravo, F. D., Franc, Y., Fournier, N., Michetti, P., Mueller, C., et al. (2019) · Nature Medicine · doi:10.1038/s41591-018-0308-z · Cited by 428
Metadata
- Authors
- Schwab, C., Berry, D., Rauch, I., Rennisch, I., Ramesmayer, J., Hainzl, E., Heider, S., Decker, T., Kenner, L., Müller, M., Strobl, B., Wagner, M., Schleper, C., Loy, A., & Urich, T.
- Venue
- The ISME Journal
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-01-09
- Volume
- 8
- Issue
- 5
- Pages
- 1101-1114
- ISSN
- 1751-7362 (ISSN-L)
- 1751-7370
- OpenAlex
- W1994243307
- Cited by
- 193
- References
- 12
- FWCI
- 7.91
- Type
- journal article
- Language
- en
- Open access
- hybrid
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Longitudinal study of murine microbiota activity and interactions with the host during acute inflammation and recovery. https://app.cochat.ai/papers/10.1038/ismej.2013.223
- The paper
- Schwab, C., Berry, D., Rauch, I., Rennisch, I., Ramesmayer, J., Hainzl, E., Heider, S., Decker, T., Kenner, L., Müller, M., Strobl, B., Wagner, M., Schleper, C., Loy, A., & Urich, T. (2014). Longitudinal study of murine microbiota activity and interactions with the host during acute inflammation and recovery. The ISME Journal. https://doi.org/10.1038/ismej.2013.223
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.