7SL RNA and signal recognition particle orchestrate a global cellular response to acute thermal stress
Bibliographic record
Abstract
Non-coding 7SL RNA is an ancestor to mammalian Alu and B1 SINE RNAs and is thought to function exclusively within the Signal Recognition Particle (SRP), aiding in the translocation of secretory proteins into the endoplasmic reticulum for export. Here, we discover a function of 7SL/SRP unrelated to protein secretion. Under acute heat shock, 7SL and SRP together selectively arrest cellular transcription and translation machineries during early response to stress. Under thermal stress, 7SL is upregulated, accumulates in the nucleus, and binds to target genes repressed by heat shock. Concurrently, in the cytosol, SRP binds to ribosomes and inhibits new protein synthesis. Translational suppression occurs independently of the signal peptide and is abrogated by depleting SRP. Translation inhibition extends to the mitochondria, as nuclear-encoded genes with mitochondrial functions are enriched among SRP targets. Thus, apart from its role in protein export, 7SL/SRP orchestrates a global response to acute stress that encompasses the nucleus, cytosol, and mitochondria across transcription and translation. 7SL is traditionally thought to function within the SRP to aid in protein translocation into the ER. Here, the authors show that under acute heat shock, it selectively arrests cellular transcription and translation, independent of the signal peptide.
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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".