Discrete regulation of b-catenin-mediated transcription governs identity of intestinal epithelial stem cells
Borrelli, C.; Valenta, T.; Handler, K.; Velez, K.; Moro, G.; Lafzi, A.; de Vargas Roditi, L.; Hausmann, G.; Moor, A. E.; Basler, K.
Show abstract
The homeostasis of the gut epithelium relies upon continuous renewal and proliferation of crypt-resident intestinal epithelial stem cells (IESCs). Wnt/{beta}-catenin signaling is required for IESC maintenance, however, it remains unclear how this pathway selectively governs the identity and proliferative decisions of IESCs. Here, we demonstrate that C-terminally-recruited transcriptional co-factors of {beta}-catenin act as all-or-nothing regulators of Wnt-target gene expression. Blocking their interactions with {beta}-catenin rapidly induces loss of IESCs and intestinal homeostasis. Conversely, N-terminally recruited co-factors fine-tune {beta}-catenins transcriptional output to ensure proper self-renewal and proliferative behaviour of IESCs. Impairment of N-terminal interactions triggers transient hyperproliferation of IESCs, eventually resulting in exhaustion of the self-renewing stem cell pool. IESC mis-differentiation, accompanied by intrinsic and extrinsic stress signalling results in a process resembling aberrant "villisation" of intestinal crypts. Our data suggest that IESC-specific Wnt/{beta}-catenin output requires discrete regulation of transcription by transcriptional co-factors.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Epithelial zonation along the mouse and human small intestine defines five discrete metabolic domains 99%
- Release of Notch activity coordinated by IL-1β signalling confers differentiation plasticity of airway progenitors via Fosl2 during alveolar regeneration 98%
- A biomechanical switch regulates the transition towards homeostasis in esophageal epithelium 98%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.