SIR telomere silencing depends on nuclear envelope lipids and modulates sensitivity to a lysolipid drug
Bibliographic record
Abstract
Abstract The nuclear envelope (NE) is important in maintaining genome organization. The role of lipids in the communication between the NE and telomere silencing was investigated, including how changes in lipid composition impact gene expression and overall nuclear architecture. For this purpose, yeast cells were treated with the non-metabolizable lysophosphatidylcholine analog edelfosine, known to accumulate at the perinuclear endoplasmic reticulum. Edelfosine treatment induced NE deformation and disrupted telomere clustering but not anchoring. In addition, the association of Sir4 at telomeres measured by ChIP decreased. RNA-seq analysis showed altered expression of Sir-dependent genes located at sub-telomeric (0-10 kb) regions, which was consistent with Sir4 dispersion. Transcriptomic analysis revealed that two lipid metabolic circuits were activated in response to edelfosine, one mediated by the membrane sensing transcription factors, Spt23/Mga2, and the other by a transcriptional repressor, Opi1. Activation of these combined transcriptional programs resulted in higher levels of unsaturated fatty acids and the formation of nuclear lipid droplets. Interestingly, cells lacking Sir proteins displayed resistance to unsaturated fatty acids and edelfosine, and this phenotype was connected to Rap1. GRAPHICAL ABSTRACT Summary The nuclear envelope (NE) is important for nuclear organization. This study shows that changes in NE lipid composition from lysolipid treatment decreases Sir4 association with telomeres, their clustering at NE, and triggers lipid-specific transcriptional circuits regulated by membrane-sensing factors.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".