N-terminal Acetylation Levels Are Maintained During Acetyl-CoA Deficiency in Saccharomyces cerevisiae
Bibliographic record
Abstract
N-terminal acetylation (Nt-acetylation) is a highly abundant protein modification in eukaryotes and impacts a wide range of cellular processes, including protein quality control and stress tolerance. Despite its prevalence, the mechanisms regulating Nt-acetylation are still nebulous. Here, we present the first global study of Nt-acetylation in yeast cells as they progress to stationary phase in response to nutrient starvation. Surprisingly, we found that yeast cells maintain their global Nt-acetylation levels upon nutrient depletion, despite a marked decrease in acetyl-CoA levels. We further observed two distinct sets of protein N termini that display differential and opposing Nt-acetylation behavior upon nutrient starvation, indicating a dynamic process. The first protein cluster was enriched for annotated N termini showing increased Nt-acetylation in stationary phase compared with exponential growth phase. The second protein cluster was conversely enriched for alternative nonannotated N termini ( i.e. N termini indicative of shorter N-terminal proteoforms) and, like histones, showed reduced acetylation levels in stationary phase when acetyl-CoA levels were low. Notably, the degree of Nt-acetylation of Pcl8, a negative regulator of glycogen biosynthesis and two components of the pre-ribosome complex (Rsa3 and Rpl7a) increased during starvation. Moreover, the steady-state levels of these proteins were regulated both by starvation and NatA activity. In summary, this study represents the first comprehensive analysis of metabolic regulation of Nt-acetylation and reveals that specific, rather than global, Nt-acetylation events are subject to metabolic regulation.
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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".