Phosphorylation of the glycerol 3‐phosphate acyltransferase Gpt2 regulates the timing of TAG mobilization upon growth resumption
Bibliographic record
Abstract
Glycerol‐3‐phosphate acyltransferases (GPATs) catalyze the first step of glycerol‐3‐phosphate acylation at the sn‐1 position producing lyso‐phosphatidic acid. This is the committed and rate limiting step in de‐novo synthesis of phosphatidic acid, the key intermediate in the glycerophospholipids and triacylglycerols (TAG) biosynthetic pathways. Two GPATs have been identified in S cerevisiae , Gpt2 and Sct1. Gpt2 (but not Sct1) becomes essential when cells are grown with oleic acid as the only carbon source. While oleic acid induced large accumulation of lipid droplets (LDs) in wild‐type cells, cells lacking GPT2 failed to accumulate these storage compartments of TAG and other neutral lipids. This lead to a growth defect and significant reduction of cell viability. We were intrigued by the fact that the intracellular distribution of Gpt2 and its phosphorylation status changed under these growth conditions compared to growth on glucose. We identified several phosphoresidues in Gpt2 by mass spectrometry analysis, localized to a serine rich region in the carboxy‐terminus of the protein. To investigate the role of phosphorylation in the regulation of Gpt2, the phosphorylation status of the protein was manipulated by introducing Ser to Ala or to Asp mutations in the GPT2 locus. Importantly, all phosphorylation mutants were expressed at physiological levels and could support life in the absence of Sct1, indicating these mutants are functional. During characterization studies of these mutants, we have discovered that changes in the phosphorylation status of Gpt2 affect its ER distribution, with the protein concentrating at points of contact with lipid droplets in actively growing cells. Staining of neutral lipids with BODIPY™ 493/503 or Nile red, indicated that specific serine to alanine mutations result in larger lipid droplets compare to those in wild type cells. We determined that this phenotype was indeed accompanied by a significant increase in TAG levels, mostly notorious during exponential growth. The differences in LD size and TAG accumulation became milder during stationary phase. SDS‐PAGE analysis of wild type Gpt2 indicated that the phosphorylation pattern of the protein changes in stationary phase, with the appearance of a faster migrating band that resembles that observed for the S to A mutants. Interestingly, this second band vanishes upon growth resumption, coinciding with TAG mobilization and lipolysis. Microscopy inspection of S to A phosphomutant strains showed a clear delay in LD size reduction up to 5 hours after resuspension of 5‐days stationary phase cells in fresh medium. This was also accompanied by a delay in TAG consumption. These results highlight the role of Gpt2 in coordinating synthesis and glycerolipid turnover in response to nutrients. Altogether, it appears that phosphorylation regulates Gpt2 interaction with lipid droplets, allowing TAG mobilization upon growth resumption from a quiescent state. Support or Funding Information This work has been financially supported by NSERC (to V.Z. and B.S.) and the Austrian Science Fund (FWF; Project P21251 to K.A.)
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".