Defining REV-ERBα’s ligand-mediated transcriptional mechanisms in TH17 cells 2535

Abstract Description TH17 cells are a subset of CD4+ T cells that mediate autoimmune and chronic inflammatory pathology. We have demonstrated that REV-ERBα, a member of the nuclear receptor superfamily of ligand-regulated transcription factors, acts as a critical repressor of this cell type. In line with this finding, REV-ERB agonism has been shown to ameliorate disease in several mouse models of chronic inflammation. Much work has been done to identify the target genes of REV-ERBα across multiple tissues. However, little is known about the transcriptional machinery driving its function. Our goal is to identify key proteins that drive REV-ERBα-mediated gene repression in pathogenic TH17 cells and further understand how ligands modulate this process. Therefore, we have performed miniTurboID proximity labeling and subsequent proteomic analysis to capture the REV-ERBα interactome in TH17 cells. Comparison of the REV-ERBα interactome induced by the presence and absence of endogenous ligand binding will provide insight into the transcriptional complexes that mediate REV-ERBα activity and the role of ligands in their formation. Ultimately, these efforts will bolster our understanding of REV-ERB and TH17 biology and inform the development of focused therapeutics for TH17-mediated autoimmune and chronic inflammatory diseases. Funding Sources Supported by NIH R01 DK135300 Topic Categories Immune Response Regulation: Molecular Mechanisms (IRM)

Authors

Institutions

Publication Details

Journal
The Journal of Immunology
Published
2025-11-01
DOI
https://doi.org/10.1093/jimmun/vkaf283.441
Primary Topic
Psoriasis: Treatment and Pathogenesis
Type
article
Field-Weighted Citation Impact
0.00

Funders

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

Defining REV-ERBα’s ligand-mediated transcriptional mechanisms in TH17 cells 2535

Sarah A. Mosure, Laura A. Solt, Bin-Bin Schell
The Journal of Immunology
Psoriasis: Treatment and Pathogenesis
article

Defining REV-ERBα’s ligand-mediated transcriptional mechanisms in TH17 cells 2535

Sarah A. Mosure, Laura A. Solt, Bin-Bin Schell
article en

Abstract

Abstract Description TH17 cells are a subset of CD4+ T cells that mediate autoimmune and chronic inflammatory pathology. We have demonstrated that REV-ERBα, a member of the nuclear receptor superfamily of ligand-regulated transcription factors, acts as a critical repressor of this cell type. In line with this finding, REV-ERB agonism has been shown to ameliorate disease in several mouse models of chronic inflammation. Much work has been done to identify the target genes of REV-ERBα across multiple tissues. However, little is known about the transcriptional machinery driving its function. Our goal is to identify key proteins that drive REV-ERBα-mediated gene repression in pathogenic TH17 cells and further understand how ligands modulate this process. Therefore, we have performed miniTurboID proximity labeling and subsequent proteomic analysis to capture the REV-ERBα interactome in TH17 cells. Comparison of the REV-ERBα interactome induced by the presence and absence of endogenous ligand binding will provide insight into the transcriptional complexes that mediate REV-ERBα activity and the role of ligands in their formation. Ultimately, these efforts will bolster our understanding of REV-ERB and TH17 biology and inform the development of focused therapeutics for TH17-mediated autoimmune and chronic inflammatory diseases. Funding Sources Supported by NIH R01 DK135300 Topic Categories Immune Response Regulation: Molecular Mechanisms (IRM)

The Journal of ImmunologyVol. 214(Supplement_1)
Scripps Research Institute (US), Scripps Institution of Oceanography (US), Scripps (United States) (US)
Alex's Lemonade Stand Foundation for Childhood Cancer, American Lebanese Syrian Associated Charities, National Institutes of Health, National Center for Advancing Translational Sciences
Openalex Percentile: Top 61%
Psoriasis: Treatment and Pathogenesis
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.