Pab1 acetylation at K131 decreases stress granule formation in Saccharomyces cerevisiae
Bibliographic record
Abstract
Under environmental stress, such as glucose deprivation, cells form stress granules-the accumulation of cytoplasmic aggregates of repressed translational initiation complexes, proteins, and stalled mRNAs. Recent research implicates stress granules in various diseases, such as neurodegenerative diseases, but the exact regulators responsible for the assembly and disassembly of stress granules are unknown. An important aspect of stress granule formation is the presence of posttranslational modifications on core proteins. One of those modifications is lysine acetylation, which is regulated by either a lysine acetyltransferase or a lysine deacetylase enzyme. This work deciphers the impact of lysine acetylation on an essential protein found in Saccharomyces cerevisiae stress granules, poly(A)-binding protein (Pab1). We demonstrated that an acetylation mimic of the lysine residue in position 131 reduces stress granule formation upon glucose deprivation and other stressors such as ethanol, raffinose, and vanillin. We present genetic evidence that the enzyme Rpd3 is the primary candidate for the deacetylation of Pab1-K131. Further, our electromobility shift assay studies suggest that the acetylation of Pab1-K131 negatively impacts poly(A) RNA binding. Due to the conserved nature of stress granules, therapeutics targeting the activity of lysine acetyltransferases and lysine deacetylase enzymes may be a promising route to modulate stress granule dynamics in the disease state.
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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) | 0.002 | 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".