TCF-4 Mediates Cell Type-specific Regulation of Proglucagon Gene Expression by β-Catenin and Glycogen Synthase Kinase-3β
Bibliographic record
Abstract
The proglucagon gene (glu) encodes glucagon, expressed in pancreatic islets, and the insulinotropic hormone GLP-1, expressed in the intestines. These two hormones exert critical and opposite effects on blood glucose homeostasis. An intriguing question that remains to be answered is whether and how glu gene expression is regulated in a cell type-specific manner. We reported previously that the glu gene promoter in gut endocrine cell lines was stimulated by beta-catenin, the major effector of the Wnt signaling pathway, whereas glu mRNA expression and GLP-1 synthesis were activated via inhibition of glycogen synthase kinase-3beta, the major negative modulator of the Wnt pathway (Ni, Z., Anini, Y., Fang, X., Mills, G. B., Brubaker, P. L., & Jin, T. (2003) J. Biol. Chem. 278, 1380-1387). We now show that beta-catenin and the glycogen synthase kinase-3beta inhibitor lithium do not activate glu mRNA or glu promoter expression in pancreatic cell lines. In the intestinal GLUTag cell line, but not in the pancreatic InR1-G9 cell line, the glu promoter G2 enhancer-element was activated by lithium treatment via a TCF-binding motif. TCF-4 is abundantly expressed in the gut but not in pancreatic islets. Furthermore, both TCF-4 and beta-catenin bind to the glu gene promoter, as detected by chromatin immunoprecipitation. Finally, stable introduction of dominant-negative TCF-4 into the GLUTag cell line repressed basal glu mRNA expression and abolished the effect of lithium on glu mRNA expression and GLP-1 synthesis. We have therefore identified a unique mechanism that regulates glu expression in gut endocrine cells only. Tissue-specific expression of TCF factors thus may play a role in the diversity of the Wnt pathway.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".