Protein ligands mediate the CRM1-dependent export of HuR in response to heat shock
Post-publication record
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Bibliographic record
Abstract
AU-rich elements (AREs) located in the 3' UTRs of the messenger RNAs (mRNAs) of many mammalian early response genes promote rapid mRNA turnover. HuR, an RRM-containing RNA-binding protein, specifically interacts with AREs, stabilizing these mRNAs. HuR is primarily nucleoplasmic, but shuttles between the nucleus and the cytoplasm via a domain called HNS located between RRM2 and RRM3. We recently showed that HuR interacts with two protein ligands, pp32 and APRIL, which are also shuttling proteins, but rely on NES domains recognized by CRM1 for export. Here we show that heat shock induces increased association of HuR with pp32 and APRIL through protein-protein interactions and that these ligands partially colocalize with HuR in cytoplasmic foci. HuR associations with the hnRNP complex also increase, but through RNA links. CRM1 coimmunoprecipitates with HuR only after heat shock, and nuclear export of HuR becomes sensitive to leptomycin B, an inhibitor of CRM1. Export after heat shock requires the same domains of HuR (HNS and RRM3) that are essential for binding pp32 and APRIL. In situ hybridization and coimmunoprecipitation experiments show that LMB treatment blocks both hsp70 mRNA nuclear export and its cytoplasmic interaction with HuR after heat shock. Together, our results argue that upon heat shock, HuR switches its export pathway to that of its ligands pp32 and APRIL, which involves the nuclear export factor CRM1. HuR and its ligands may be instrumental in the nuclear export of heat-shock mRNAs.
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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 | 0.001 |
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".