Interactions between the PDZ domains of Bazooka (Par-3) and phosphatidic acid: in vitro characterization and role in epithelial development
Bibliographic record
Abstract
Bazooka (Par-3) is a conserved polarity regulator that organizes molecular networks in a wide range of cell types. In epithelia, it functions as a plasma membrane landmark to organize the apical domain. Bazooka is a scaffold protein that interacts with proteins through its three PDZ (postsynaptic density 95, discs large, zonula occludens-1) domains and other regions. In addition, Bazooka has been shown to interact with phosphoinositides. Here we show that the Bazooka PDZ domains interact with the negatively charged phospholipid phosphatidic acid immobilized on solid substrates or in liposomes. The interaction requires multiple PDZ domains, and conserved patches of positively charged amino acid residues appear to mediate the interaction. Increasing or decreasing levels of diacylglycerol kinase or phospholipase D-enzymes that produce phosphatidic acid-reveal a role for phosphatidic acid in Bazooka embryonic epithelial activity but not its localization. Mutating residues implicated in phosphatidic acid binding revealed a possible role in Bazooka localization and function. These data implicate a closer connection between Bazooka and membrane lipids than previously recognized. Bazooka polarity landmarks may be conglomerates of proteins and plasma membrane lipids that modify each other's activities for an integrated effect on cell polarity.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".