Active Stabilization of Human Endothelial Nitric Oxide Synthase mRNA by hnRNP E1 Protects against Antisense RNA and MicroRNAs
Bibliographic record
Abstract
Human endothelial nitric oxide synthase (eNOS) mRNA is highly stable in endothelial cells (ECs). Posttranscriptional regulation of eNOS mRNA stability is an important component of eNOS regulation, especially under hypoxic conditions. Here, we show that the human eNOS 3' untranslated region (3' UTR) contains multiple, evolutionarily conserved pyrimidine (C and CU)-rich sequence elements that are both necessary and sufficient for mRNA stabilization. Importantly, RNA immunoprecipitations and RNA electrophoretic mobility shift assays (EMSAs) revealed the formation of heterogeneous nuclear ribonucleoprotein E1 (hnRNP E1)-containing RNP complexes at these 3'-UTR elements. Knockdown of hnRNP E1 decreased eNOS mRNA half-life, mRNA levels, and protein expression. Significantly, these stabilizing RNP complexes protect eNOS mRNA from the inhibitory effects of its antisense transcript sONE and 3'-UTR-targeting small interfering RNAs (siRNAs), as well as microRNAs, specifically, hsa-miR-765, which targets eNOS mRNA stability determinants. Hypoxia disrupts hnRNP E1/eNOS 3'-UTR interactions via increased Akt-mediated serine phosphorylation (including serine 43) and increased nuclear localization of hnRNP E1. These mechanisms account, at least in part, for the decrease in eNOS mRNA stability under hypoxic conditions. Thus, the stabilization of human eNOS mRNA by hnRNP E1-containing RNP complexes serves as a key protective mechanism against the posttranscriptional inhibitory effects of antisense RNA and microRNAs under basal conditions but is disrupted under hypoxic conditions.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".