Systematic analysis of membrane contact sites in <i>Saccharomyces cerevisiae</i> uncovers modulators of cellular lipid distribution
Bibliographic record
Abstract
Abstract Actively maintained close appositions, or contact sites, between organelle membranes, enable the efficient transfer of biomolecules between the various cellular compartments. Several such sites have been described together with their tethering machinery. Despite these advances we are still far from a comprehensive understanding of the function and regulation of most contact sites. To systematically characterize the proteome of contact sites and support the discovery of new tethers and functional molecules, we established a high throughput screening approach in Saccharomyces cerevisiae based on co-localization imaging. We imaged split fluorescence reporters for six different contact sites, two of which have never been studied before, on the background of 1165 strains expressing a mCherry-tagged yeast protein that have a cellular punctate distribution (a hallmark of contact sites). By scoring both co-localization events and effects on reporter size and abundance, we discovered over 100 new potential contact site residents and effectors in yeast. Focusing on several of the newly identified residents, we identified one set of hits as previously unrecognized homologs to Vps13 and Atg2. These proteins share their lipid transport domain, thus expanding this family of lipid transporters. Analysis of another candidate, Ypr097w, which we now call Lec1 ( L ipid-droplet E rgosterol C ortex 1), revealed that this previously uncharacterized protein dynamically shifts between lipid droplets and the cell cortex, and plays a role in regulation of ergosterol distribution in the cell.
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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".