Tubular ER Associates With Diacylglycerol-Rich Structures During Lipid Droplet Consumption
Bibliographic record
Abstract
Growth resumption from stationary phase in Saccharomyces cerevisiae, is characterized by lipid droplet (LD) consumption and channeling of lipid precursors towards synthesis of membranes. We have previously determined that triacylglycerol lipolysis contributes to a pool of diacylglycerol (DAG) associated with the yeast vacuole that is enriched in structures that are in close proximity to LDs. In this study we have monitored these structures using a DAG sensor fused to GFP during isolation of LDs. A unique fraction containing the DAG sensor, with low presence of LDs, was identified. Membranes enriched in the DAG probe were obtained by immunoaffinity purification using a GFP nanobody, and the associated proteome was investigated by mass spectrometry. It was determined this LD-associated fraction was enriched in proteins known to shape the tubular endoplasmic reticulum (ER) like Yop1, Sey1, Rtn1 and Rtn2. Consistently, cells lacking three of these proteins (rtn1Δ rtn2Δ yop1Δ) exhibited delayed LD consumption, larger LDs and abnormal LD distribution. In addition, the triple mutant displayed aberrant localization of the DAG sensor after 5 hours of growth resumption from stationary phase. Manipulation of DAG levels by overexpression of the DAG kinase Dgk1, impacted localization of the DAG probe and affected fitness of the triple mutant. Altogether these results link LD consumption to tubular ER expansion as a gateway of lipid precursors that otherwise accumulate in vacuolar associated membranes or other internal compartments. Furthermore, conversion of DAG to phosphatidic acid (PA) in the absence of a functional tubular ER was toxic to cells, suggesting the ratio of PA to DAG is critical to allow growth progression.
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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".