Srf1 Is a Novel Regulator of Phospholipase D Activity and Is Essential to Buffer the Toxic Effects of C16:0 Platelet Activating Factor
Bibliographic record
Abstract
During Alzheimer's Disease, sustained exposure to amyloid-β₄₂ oligomers perturbs metabolism of ether-linked glycerophospholipids defined by a saturated 16 carbon chain at the sn-1 position. The intraneuronal accumulation of 1-O-hexadecyl-2-acetyl-sn-glycerophosphocholine (C16:0 PAF), but not its immediate precursor 1-O-hexadecyl-sn-glycerophosphocholine (C16:0 lyso-PAF), participates in signaling tau hyperphosphorylation and compromises neuronal viability. As C16:0 PAF is a naturally occurring lipid involved in cellular signaling, it is likely that mechanisms exist to protect cells against its toxic effects. Here, we utilized a chemical genomic approach to identify key processes specific for regulating the sensitivity of Saccharomyces cerevisiae to alkyacylglycerophosphocholines elevated in Alzheimer's Disease. We identified ten deletion mutants that were hypersensitive to C16:0 PAF and five deletion mutants that were hypersensitive to C16:0 lyso-PAF. Deletion of YDL133w, a previously uncharacterized gene which we have renamed SRF1 (Spo14 Regulatory Factor 1), resulted in the greatest differential sensitivity to C16:0 PAF over C16:0 lyso-PAF. We demonstrate that Srf1 physically interacts with Spo14, yeast phospholipase D (PLD), and is essential for PLD catalytic activity in mitotic cells. Though C16:0 PAF treatment does not impact hydrolysis of phosphatidylcholine in yeast, C16:0 PAF does promote delocalization of GFP-Spo14 and phosphatidic acid from the cell periphery. Furthermore, we demonstrate that, similar to yeast cells, PLD activity is required to protect mammalian neural cells from C16:0 PAF. Together, these findings implicate PLD as a potential neuroprotective target capable of ameliorating disruptions in lipid metabolism in response to accumulating oligomeric amyloid-β₄₂.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".