Genome-Wide Analysis of Sterol-Lipid Storage and Trafficking in <i>Saccharomyces cerevisiae</i>
Bibliographic record
Abstract
The pandemic of lipid-related disease necessitates a determination of how cholesterol and other lipids are transported and stored within cells. The first step in this determination is the identification of the genes involved in these transport and storage processes. Using genome-wide screens, we identified 56 yeast (Saccharomyces cerevisiae) genes involved in sterol-lipid biosynthesis, intracellular trafficking, and/or neutral-lipid storage. Direct biochemical and cytological examination of mutant cells revealed an unanticipated link between secretory protein glycosylation and triacylglycerol (TAG)/steryl ester (SE) synthesis for the storage of lipids. Together with the analysis of other deletion mutants, these results suggested at least two distinct events for the biogenesis of lipid storage particles: a step affecting neutral-lipid synthesis, generating the lipid core of storage particles, and another step for particle assembly. In addition to the lipid storage mutants, we identified mutations that affect the localization of unesterified sterols, which are normally concentrated in the plasma membrane. These findings implicated phospholipase C and the protein phosphatase Ptc1p in the regulation of sterol distribution within cells. This study identified novel sterol-related genes that define several distinct processes maintaining sterol homeostasis.
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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".