Proteomic analysis reveals the direct recruitment of intrinsically disordered regions to stress granules in <i>S. cerevisiae</i>
Bibliographic record
Abstract
Stress granules (SGs) are stress-induced membraneless condensates that store non-translating mRNA and stalled translation initiation complexes. Although metazoan SGs are dynamic compartments where proteins can rapidly exchange with their surroundings, yeast SGs seem largely static. To gain a better understanding of yeast SGs, we identified proteins that sediment after heat shock using mass spectrometry. Proteins that sediment upon heat shock are biased toward a subset of abundant proteins that are significantly enriched in intrinsically disordered regions (IDRs). Heat-induced SG localization of over 80 proteins were confirmed using microscopy, including 32 proteins not previously known to localize to SGs. We found that several IDRs were sufficient to mediate SG recruitment. Moreover, the dynamic exchange of IDRs can be observed using fluorescence recovery after photobleaching, whereas other components remain immobile. Lastly, we showed that the IDR of the Ubp3 deubiquitinase was critical for yeast SG formation. This work shows that IDRs can be sufficient for SG incorporation, can remain dynamic in vitrified SGs, and can play an important role in cellular compartmentalization upon stress.This article has an associated First Person interview with the first author of the paper.
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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) | 0.000 | 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".