Phosphatidylserine dictates the assembly and dynamics of caveolae in the plasma membrane
Bibliographic record
Abstract
Caveolae are bulb-shaped nanodomains of the plasma membrane that are enriched in cholesterol and sphingolipids. They have many physiological functions, including endocytic transport, mechanosensing, and regulation of membrane and lipid transport. Caveola formation relies on integral membrane proteins termed caveolins (Cavs) and the cavin family of peripheral proteins. Both protein families bind anionic phospholipids, but the precise roles of these lipids are unknown. Here, we studied the effects of phosphatidylserine (PtdSer), phosphatidylinositol 4-phosphate (PtdIns4P), and phosphatidylinositol 4,5-bisphosphate (PtdIns(4,5)P 2 ) on caveolar formation and dynamics. Using live-cell, single-particle tracking of GFP-labeled Cav1 and ultrastructural analyses, we compared the effect of PtdSer disruption or phosphoinositide depletion with caveola disassembly caused by cavin1 loss. We found that PtdSer plays a crucial role in both caveola formation and stability. Sequestration or depletion of PtdSer decreased the number of detectable Cav1-GFP puncta and the number of caveolae visualized by electron microscopy. Under PtdSer-limiting conditions, the co-localization of Cav1 and cavin1 was diminished, and cavin1 degradation was increased. Using rapamycin-recruitable phosphatases, we also found that the acute depletion of PtdIns4P and PtdIns(4,5)P 2 has minimal impact on caveola assembly but results in decreased lateral confinement. Finally, we show in a model of phospholipid scrambling, a feature of apoptotic cells, that caveola stability is acutely affected by the scrambling. We conclude that the predominant plasmalemmal anionic lipid PtdSer is essential for proper Cav clustering, caveola formation, and caveola dynamics and that membrane scrambling can perturb caveolar stability.
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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".