The carrier Msn5p/Kap142p promotes nuclear export of the hsp70 Ssa4p and relocates in response to stress
Bibliographic record
Abstract
Cytoplasmic hsp70s like yeast Ssa4p shuttle between nucleus and cytoplasm under normal growth conditions but accumulate in nuclei upon stress. This nuclear accumulation is only transient, and Ssa4p relocates to the cytoplasm when cells recover. We show here that Ssa4p nuclear export is independent of Xpol/Crm1 and identify the importin-beta family member Msn5p/Kap142p as the exporter for Ssa4p. In growing cells and in vitro, Msn5p and Ssa4p generate genuine export complexes that require Ran/Gsp1p-GTP. Furthermore, nucleoporin Nup82p, which plays a role in Msn5p-mediated transport, is necessary for efficient export of Ssa4p. In living cells, stress not only regulates Ssa4p localization, but also controls the distribution of Msn5p. Msn5p is concentrated in nuclei of unstressed cells, but appears in the cytoplasm upon exposure to ethanol, heat, starvation or severe oxidative stress. In addition, growth on non-fermentable carbon sources relocates a portion of Msn5p to the cytoplasm and leads to a partial nuclear accumulation of Ssa4p. Taken together, growth and stress conditions that localize the transporter Msn5p to the cytoplasm also induce the nuclear accumulation of its cargo Ssa4p.
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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".