SMAD4, a mediator of TGF-β signaling, plays an important role in T cells to prevent inflammatory bowel disease (IBD). However, the precise mechanisms underlying this control remain elusive. Using both genetic and epigenetic approaches, we revealed an unexpected mechanism by which SMAD4 prevents naive CD8+ T cells from becoming pathogenic for the gut. Prior to the engagement of the TGF-β receptor, SMAD4 restrains the epigenetic, transcriptional, and functional landscape of the TGF-β signature in naive CD8+ T cells. Mechanistically, prior to TGF-β signaling, SMAD4 binds to promoters and enhancers of several TGF-β target genes, and by regulating histone deacetylation, suppresses their expression. Consequently, regardless of a TGF-β signal, SMAD4 limits the expression of TGF-β negative feedback loop genes, such as Smad7 and Ski, and likely conditions CD8+ T cells for the immunoregulatory effects of TGF-β. In addition, SMAD4 ablation conferred naive CD8+ T cells with both a superior survival capacity, by enhancing their response to IL-7, as well as an enhanced capacity to be retained within the intestinal epithelium, by promoting the expression of Itgae, which encodes the integrin CD103. Accumulation, epithelial retention, and escape from TGF-β control elicited chronic microbiota-driven CD8+ T cell activation in the gut. Hence, in a TGF-β–independent manner, SMAD4 imprints a program that preconditions naive CD8+ T cell fate, preventing IBD.
Ramdane Igalouzene, Hector Hernandez-Vargas, Nicolas Benech, Alexandre Guyennon, David Bauché, Célia Barrachina, Emeric Dubois, Julien C. Marie, Saïdi M’Homa Soudja
Usage data is cumulative from May 2024 through May 2025.
Usage | JCI | PMC |
---|---|---|
Text version | 1,333 | 256 |
171 | 74 | |
Figure | 592 | 3 |
Table | 83 | 0 |
Supplemental data | 63 | 4 |
Citation downloads | 76 | 0 |
Totals | 2,318 | 337 |
Total Views | 2,655 |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.