The DOI matches its Crossref record; 83 of the 83 references it cites were found in a registry or an index.
A bacterial bile acid metabolite modulates Treg activity through the nuclear hormone receptor NR4A1
Open accessPublished version of a preprint
Abstract
Bile acids act as signaling molecules that regulate immune homeostasis, including the differentiation of CD4+ T cells into distinct T cell subsets. The bile acid metabolite isoallolithocholic acid (isoalloLCA) enhances the differentiation of anti-inflammatory regulatory T cells (T reg cells) by facilitating the formation of a permissive chromatin structure in the promoter region of the transcription factor forkhead box P3 (Foxp3). Here, we identify gut bacteria that synthesize isoalloLCA from 3-oxolithocholic acid and uncover a gene cluster responsible for the conversion in members of the abundant human gut bacterial phylum Bacteroidetes. We also show that the nuclear hormone receptor NR4A1 is required for the effect of isoalloLCA on T reg cells. Moreover, the levels of isoalloLCA and its biosynthetic genes are significantly reduced in patients with inflammatory bowel diseases, suggesting that isoalloLCA and its bacterial producers may play a critical role in maintaining immune homeostasis in humans.
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?
The cited source says what the claim attributes to it.
In the citing paper
“Because NUR77 was shown to be required for isoalloLCA–induced FOXP3 expression in CD4+ T cells (32),”
From Bile acid synthesis impedes tumor-specific T cell responses during liver cancer (2025) · cites this paper as [32]
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
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106
The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400
limma powers differential expression analyses for RNA-sequencing and microarray studies
Ritchie, M. E., Phipson, B., Wu, D., Hu, Y., Law, C. W., Shi, W., & Smyth, G. K. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv007 · Cited by 40,458
clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters
Yu, G., Wang, L.-G., Han, Y., & He, Q.-Y. (2012) · OMICS: A Journal of Integrative Biology · doi:10.1089/omi.2011.0118 · Cited by 36,259
BLAST+: architecture and applications
Camacho, C., Coulouris, G., Avagyan, V., Ma, N., Papadopoulos, J., Bealer, K., & Madden, T. L. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-421 · Cited by 22,074
HTSeq—a Python framework to work with high-throughput sequencing data
Anders, S., Pyl, P. T., & Huber, W. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btu638 · Cited by 21,464
Model-based Analysis of ChIP-Seq (MACS)
Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-9-r137 · Cited by 18,386
Self-citationRobinson, J. T., Thorvaldsdóttir, H., Winckler, W., Guttman, M., Lander, E. S., Getz, G., & Mesirov, J. P. (2011) · Nature Biotechnology · doi:10.1038/nbt.1754 · Cited by 15,390
Heinz, S., Benner, C., Spann, N., Bertolino, E., Lin, Y. C., Laslo, P., Cheng, J. X., Murre, C., Singh, H., & Glass, C. K. (2010) · Molecular Cell · doi:10.1016/j.molcel.2010.05.004 · Cited by 13,382
Cited by
Sorted by citations
Small molecule metabolites: discovery of biomarkers and therapeutic targets
Qiu, S., Cai, Y., Yao, H., Lin, C., Xie, Y., Tang, S., & Zhang, A. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01399-3 · Cited by 993
Gut microbiota-derived bile acids in intestinal immunity, inflammation, and tumorigenesis
Cai, J., Sun, L., & Gonzalez, F. J. (2022) · Cell Host & Microbe · doi:10.1016/j.chom.2022.02.004 · Cited by 892
Novel bile acid biosynthetic pathways are enriched in the microbiome of centenarians
Sato, Y., Atarashi, K., Plichta, D. R., Arai, Y., Sasajima, S., Kearney, S. M., Suda, W., Takeshita, K., Sasaki, T., Okamoto, S., et al. (2021) · Nature · doi:10.1038/s41586-021-03832-5 · Cited by 632
Gut-Microbiota-Derived Metabolites Maintain Gut and Systemic Immune Homeostasis
Wang, J., Zhu, N., Su, L., Gao, Y., & Yang, R. (2023) · Cells · doi:10.3390/cells12050793 · Cited by 649
Bile acid metabolism and signaling, the microbiota, and metabolic disease
Cai, J., Rimal, B., Jiang, C., Chiang, J. Y. L., & Patterson, A. D. (2022) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2022.108238 · Cited by 529
Metadata
- Authors
- Li, W., Hang, S., Fang, Y., Bae, S., Zhang, Y., Zhang, M., Wang, G., McCurry, M. D., Bae, M., Paik, D., Franzosa, E. A., Rastinejad, F., Huttenhower, C., Yao, L., Devlin, A. S., & Huh, J. R.
- Affiliations
- Harvard University (US)
- Broad Institute (US)
- University of Oxford (GB)
- Brigham and Women's Hospital (US)
- Corresponding author
- Yao, Lina
- Devlin, A. Sloan
- Huh, Jun R.
- ORCID
- Venue
- Cell Host & Microbe
- Publisher
- Elsevier BV
- Published
- 2021-09
- Volume
- 29
- Issue
- 9
- Pages
- 1366-1377.e9
- ISSN
- 1931-3128 (ISSN-L)
- PMC
- PMC9064000
- OpenAlex
- W3193797930
- Cited by
- 306
- References
- 81
- Citations by year
- 2026: 70 · 2025: 74 · 2024: 68 · 2023: 40 · 2022: 48 · 2021: 6
- FWCI
- 12.70
- 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, 373 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 Host & Microbe (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (R01 DK110559, MIRA R35 GM128618)
- Harvard Medical School
- Seres Therapeutics
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Health Sciences › Medicine › Oncology › Drug Transport and Resistance Mechanisms
- Keywords
- bile acid metabolites, regulatory T cells, Foxp3, Nur77, nuclear receptors, gut microbiota, Bacteroidetes, inflammatory bowel disease, immune homeostasis, CD4+ T cell differentiation, chromatin structure
- MeSH terms
- Bile Acids and Salts, Cell Differentiation, Chromatin, Multigene Family, Humans, Phenanthrenes, Promoter Regions, Genetic, Inflammatory Bowel Diseases, Signal Transduction, T-Lymphocyte Subsets, Bacteroidetes, T-Lymphocytes, Regulatory, Forkhead Transcription Factors, Nuclear Receptor Subfamily 4, Group A, Member 1
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