Stress‐mediated inhibition of the classical nuclear protein import pathway and nuclear accumulation of the small GTPase Gsp1p
Bibliographic record
Abstract
Stress modifies all aspects of cellular physiology, including the targeting of macromolecules to the nucleus. To determine how distinct types of stress affect classical nuclear protein import, we followed the distribution of NLS-GFP, a reporter protein containing a classical nuclear localization sequence (NLS) fused to green fluorescent protein GFP. Nuclear accumulation of NLS-GFP requires import to be constitutively active; inhibition of import redistributes NLS-GFP throughout the nucleus and cytoplasm. In the yeast Saccharomyces cerevisiae, starvation, heat shock, ethanol and hydrogen peroxide rapidly inhibited classical nuclear import, whereas osmotic stress had no effect. To define the mechanisms underlying the inhibition of classical nuclear import, we located soluble components of the nuclear transport apparatus. Failure to accumulate NLS-GFP in the nucleus always correlated with a redistribution of the small GTPase Gsp1p. Whereas predominantly nuclear under normal conditions, Gsp1p equilibrated between nucleus and cytoplasm in cells exposed to starvation, heat, ethanol or hydrogen peroxide. Furthermore, analysis of yeast strains carrying mutations in different nuclear transport factors demonstrated a role for NTF2, PRP20 and MOG1 in establishing a Gsp1p gradient, as conditional lethal alleles of NTF2 and PRP20 or a deletion of MOG1 prevented Gsp1p nuclear accumulation. On the basis of these results, we now propose that certain types of stress release Gsp1p from its nuclear anchors, thereby promoting a collapse of the nucleocytoplasmic Gsp1p gradient and inhibiting classical nuclear protein import.
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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) | 0.001 | 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".