Post-Transcriptional Modulation of αENaC mRNA in Alveolar Epithelial Cells: Involvement of its 3’ Untranslated Region
Bibliographic record
Abstract
BACKGROUND/AIMS: The epithelial sodium channel (ENaC) expressed in alveolar epithelial cells plays a major role in lung liquid clearance at birth and lung edema resorption in adulthood. We showed previously that αENaC mRNA expression is downregulated in part via posttranscriptional regulation of mRNA stability. In the present work, the role of the αENaC 3' untranslated region (3'UTR) in the regulation of mRNA stability was studied further. METHODS: Quantitative reverse transcription PCR (qRT-PCR) was performed to investigate the expression of αENaC in alveolar epithelial cells. The role of the αENaC 3'UTR was evaluated through sequential deletions. RNA affinity chromatography and mass spectrometry were achieved to investigate the nature of the proteins that could bind this sequence. The function of these proteins was assessed through knockdown and overexpression in vitro. RESULTS: First, we found that αENaC mRNA half-life was much shorter than expected when using a transcriptionally controlled plasmid expression system compared to Actinomycin D treatment. Sequential deletions of the αENaC 3'UTR revealed that the αENaC 3'UTR plays an important role in the modulation of αENaC mRNA stability, and that there is a complex stabilizing and destabilizing interplay between different regions of the 3'UTR that modulate this process. Finally, we identified RNA-binding proteins that interact with the αENaC 3'UTR and showed that Dhx36 and Tial1 are involved in the decrease in αENaC mRNA stability via the proximal region of its 3'UTR. CONCLUSION: Taken together, these findings indicate that the αENaC 3'UTR plays an important role in modulating transcript levels, and Dhx36 and Tial1 seem to be involved in posttranscriptional regulation of αENaC expression in alveolar epithelial cells.
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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) | 0.001 | 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".