Unveiling IRF4-steered regulation of context-dependent effector programs in CD4+ T cells under Th17- and Treg-skewing conditions

The transcription factor interferon regulatory factor 4 (IRF4) is crucial for the fate determination of pro-inflammatory T helper (Th) 17 and the functionally opposing group of immunomodulatory regulatory T (Treg) cells. However, the molecular mechanisms of how IRF4 steers diverse transcriptional programs in Th17 and Treg cells are far from being definitive. Here, we integrated data derived from affinity-purification and full mass-spectrometry-based proteome analysis with chromatin immunoprecipitation sequencing. This allowed the characterization of subtype-specific molecular programs and the identification of IRF4 interactors in the Th17/Treg context. Our data reveal that IRF4-interacting transcription factors are recruited to IRF composite elements for the regulation of cell-type-specific transcriptional programs as exemplarily demonstrated for FLI1, which, in cooperation with IRF4, promotes Th17-specific gene expression. FLI1 inhibition markedly impaired Th17 differentiation. The present "omics" dataset provides a valuable resource for studying IRF4-mediated gene regulatory programs in pro- and anti-inflammatory immune responses.

Authors

Institutions

Publication Details

Journal
Cell Reports
Published
2025-03-01
DOI
https://doi.org/10.1016/j.celrep.2025.115407
Citations
2
Primary Topic
Immune Cell Function and Interaction
Type
article
Field-Weighted Citation Impact
1.59

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Unveiling IRF4-steered regulation of context-dependent effector programs in CD4+ T cells under Th17- and Treg-skewing conditions

Miguel A. Andrade‐Navarro, Ute Distler, Anna Gabele, Beatrice Wasser et al.
2 citations
Cell Reports
Immune Cell Function and Interaction
1.59
article

Unveiling IRF4-steered regulation of context-dependent effector programs in CD4+ T cells under Th17- and Treg-skewing conditions

Miguel A. Andrade‐Navarro, Ute Distler, Anna Gabele, Beatrice Wasser, Tobias Bopp, Gregory S. Harms, Krishnaraj Rajalingam, Stefan Bittner, Kathrin Luise Braband, Maximilian Sprang, Niels A. W. Lemmermann, Katja Luck, Sarah Dietzen, Stefan Tenzer, Mert Cihan, David Gómez-Zepeda, Tanja Ziesmann, Karolina Romaniuk, Michael Delacher, Katrin Pape, Georg Bündgen, Matthias Klein, M Welzel, Assel Nurbekova, Maxim Emelianov
article en
2 citations

Abstract

The transcription factor interferon regulatory factor 4 (IRF4) is crucial for the fate determination of pro-inflammatory T helper (Th) 17 and the functionally opposing group of immunomodulatory regulatory T (Treg) cells. However, the molecular mechanisms of how IRF4 steers diverse transcriptional programs in Th17 and Treg cells are far from being definitive. Here, we integrated data derived from affinity-purification and full mass-spectrometry-based proteome analysis with chromatin immunoprecipitation sequencing. This allowed the characterization of subtype-specific molecular programs and the identification of IRF4 interactors in the Th17/Treg context. Our data reveal that IRF4-interacting transcription factors are recruited to IRF composite elements for the regulation of cell-type-specific transcriptional programs as exemplarily demonstrated for FLI1, which, in cooperation with IRF4, promotes Th17-specific gene expression. FLI1 inhibition markedly impaired Th17 differentiation. The present "omics" dataset provides a valuable resource for studying IRF4-mediated gene regulatory programs in pro- and anti-inflammatory immune responses.

Cell ReportsVol. 44(3)
University of Bonn (DE), German Cancer Research Center (DE), Johannes Gutenberg University Mainz (DE), Heidelberg University (DE), University Hospital Heidelberg (DE), University Medical Center of the Johannes Gutenberg University Mainz (DE), Helmholtz Institute Mainz (DE), Novo Nordisk (Germany) (DE), DKFZ-ZMBH Alliance (DE), Institute of Molecular Biology (DE)
Deutsche Forschungsgemeinschaft
Zero hunger
Openalex Percentile: Top 19%
Immune Cell Function and Interaction
1.59
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.