Protocadherin-1 binds to SMAD3 and suppresses TGF-β1-induced gene transcription
Bibliographic record
Abstract
Genetic studies have identified Protocadherin-1 (PCDH1) and Mothers against decapentaplegic homolog-3 (SMAD3) as susceptibility genes for asthma. PCDH1 is expressed in bronchial epithelial cells and has been found to interact with SMAD3 in yeast two-hybrid (Y2H) overexpression assays. Here, we test whether PCDH1 and SMAD3 interact at endogenous protein levels in bronchial epithelial cells and evaluate the consequences thereof for transforming growth factor-β1 (TGF-β1)-induced gene transcription. We performed Y2H screens and coimmunoprecipitation (co-IP) experiments of PCDH1 and SMAD3 in HEK293T and 16HBE14o(-) (16HBE) cell lines. Activity of a SMAD3-driven luciferase reporter gene in response to TGF-β1 was measured in BEAS-2B cells transfected with PCDH1 and in 16HBE cells transfected with PCDH1-small-interfering RNA (siRNA). TGF-β1-induced gene expression was quantified in BEAS-2B clones overexpressing PCDH1 and in human primary bronchial epithelial cells (PBECs) transfected with PCDH1-siRNA. We confirm PCDH1 and SMAD3 interactions by Y2H and by co-IP in HEK293T cells overexpressing both proteins, and at endogenous protein levels in 16HBE cells. TGF-β-induced activation of a SMAD3-driven reporter was reduced by exogenous PCDH1 in BEAS2B cells, whereas it was increased by siRNA-mediated knockdown of endogenous PCDH1 in 16HBE cells. Overexpression of PCDH1 suppressed expression of TGF-β target genes in BEAS-2B cells, whereas knockdown of PCDH1 in human PBECs increased TGF-β-induced gene expression. In conclusion, we demonstrate that PCDH1 binds to SMAD3 and regulates its activation by TGF-β signaling in bronchial epithelial cells. We propose that PCDH1 and SMAD3 act in a single pathway in asthma susceptibility that affects sensitivity of the airway epithelium to TGF-β.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".