A Validated Regulatory Network for Th17 Cell Specification
Open accessAbstract
Th17 cells have critical roles in mucosal defense and are major contributors to inflammatory disease. Their differentiation requires the nuclear hormone receptor RORγt working with multiple other essential transcription factors (TFs). We have used an iterative systems approach, combining genome-wide TF occupancy, expression profiling of TF mutants, and expression time series to delineate the Th17 global transcriptional regulatory network. We find that cooperatively bound BATF and IRF4 contribute to initial chromatin accessibility and, with STAT3, initiate a transcriptional program that is then globally tuned by the lineage-specifying TF RORγt, which plays a focal deterministic role at key loci. Integration of multiple data sets allowed inference of an accurate predictive model that we computationally and experimentally validated, identifying multiple new Th17 regulators, including Fosl2, a key determinant of cellular plasticity. This interconnected network can be used to investigate new therapeutic approaches to manipulate Th17 functions in the setting of inflammatory disease.
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Multiple studies have described an important pathogenic function of GM-CSF in neuroinflammation.
“Multiple studies have described an important pathogenic function of GM-CSF in neuroinflammation.”
From TH17 cell heterogeneity and its role in tissue inflammation (2023) · cites this paper as [36]
GM-CSF+ T cells co-express a great variety of other cytokines including IL-2, IL-3, IL-4, IL-6, IL-13, IL-17A, IL-22, IFNγ, and TNF.
“This conclusion is further supported by the findings that GM-CSF+ T cells co-express a great variety of other cytokines including IL-2, IL-3, IL-4, IL-6, IL-13, IL-17A, IL-22, IFNγ, and TNF [33, 36, 76, 175].”
From TH17 cell heterogeneity and its role in tissue inflammation (2023) · cites this paper as [36]
Genes affected by positive or negative regulators significantly overlap with genes bound by key CD4+ transcription factors Foxp3, Batf, Irf4, and ROR-γt.
“The genes affected by either positive or negative regulators also significantly overlap with those bound by key CD4+ transcription factors (e.g., Foxp326,27, Batf, Irf4, and ROR-γt28,29, Xiao et al., unpublished data).”
From Dynamic regulatory network controlling TH17 cell differentiation (2013) · cites this paper as [29]
The core Th17 network from Ciofani et al. significantly overlaps with the authors' computationally inferred model.
“Reassuringly, their core Th17 network significantly overlaps with our computationally inferred model (Supplementary Fig. 14).”
From Dynamic regulatory network controlling TH17 cell differentiation (2013) · cites this paper as [29]
The results suggest a model in which Tsc22d3 acts as a transcriptional repressor that competes with Th17-positive regulators for binding sites.
“This suggests a model where Tsc22d3 exerts its Th17-negative function as a transcriptional repressor that competes with Th17 positive regulators over binding sites, analogous to previous findings in CD4+ regulation29,43.”
From Dynamic regulatory network controlling TH17 cell differentiation (2013) · cites this paper as [29]
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- Authors
- Ciofani, M., Madar, A., Galan, C., Sellars, M., Mace, K., Pauli, F., Agarwal, A., Huang, W., Parkurst, C. N., Muratet, M., Newberry, K. M., Meadows, S., Greenfield, A., Yang, Y., Jain, P., Kirigin, F. K., Birchmeier, C., Wagner, E. F., Murphy, K. M., Myers, R. M., Bonneau, R., & Littman, D. R.
- Affiliations
- New York University (US)
- Courant Institute of Mathematical Sciences (US)
- HudsonAlpha Institute for Biotechnology (US)
- Max Delbrück Center (DE)
- Spanish National Cancer Research Centre (ES)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Bonneau, Richard
- Littman, Dan R.
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2012-10
- Volume
- 151
- Issue
- 2
- Pages
- 289-303
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC3503487
- OpenAlex
- W2021340905
- Cited by
- 1,160
- References
- 83
- Citations by year
- 2026: 45 · 2025: 63 · 2024: 86 · 2023: 91 · 2022: 74 · 2021: 108 · 2020: 91 · 2019: 86 · 2018: 84 · 2017: 87 · 2016: 93 · 2015: 102 · 2014: 89 · 2013: 59 · 2012: 2
- FWCI
- 34.70
- Type
- journal article
- Language
- en
- Update notices
- erratum (2025-10-16)
- 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, 390 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 (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Leukemia and Lymphoma Society
- National Institutes of Health (PN2 EY016586, RC1 AI087266, IU54CA143907-01, RC4 AI092765)
- Cancer Research Institute
- Crohn's and Colitis Foundation of America
- Arthritis National Research Foundation
- National Science Foundation (IOS-1126971)
- Topics
- Life Sciences › Immunology and Microbiology › Immunology › Psoriasis: Treatment and Pathogenesis
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Keywords
- Th17 cell differentiation, transcriptional regulatory networks, RORγt, BATF, IRF4, STAT3, chromatin accessibility, transcription factor occupancy, FOSL2, cellular plasticity, inflammatory diseases, mucosal immunity, transcription factor mutants
- MeSH terms
- Interferon Regulatory Factor-4, Animals, Cell Differentiation, Encephalomyelitis, Autoimmune, Experimental, Humans, Molecular Sequence Data, Mice, Knockout, Interferon Regulatory Factors, Basic-Leucine Zipper Transcription Factors, Mice, Fos-Related Antigen-2, Gene Regulatory Networks, Genome-Wide Association Study, Nuclear Receptor Subfamily 1, Group F, Member 3, Th17 Cells
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.
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