Diacylglycerol Kinase ζ Regulates Actin Cytoskeleton Reorganization through Dissociation of Rac1 from RhoGDI
Bibliographic record
Abstract
Activation of Rac1 GTPase signaling is stimulated by phosphorylation and release of RhoGDI by the effector p21-activated kinase 1 (PAK1), but it is unclear what initiates this potential feed-forward mechanism for regulation of Rac activity. Phosphatidic acid (PA), which is produced from the lipid second messenger diacylglycerol (DAG) by the action of DAG kinases (DGKs), is known to activate PAK1. Here, we investigated whether PA produced by DGKzeta initiates RhoGDI release and Rac1 activation. In DGKzeta-deficient fibroblasts PAK1 phosphorylation and Rac1-RhoGDI dissociation were attenuated, leading to reduced Rac1 activation after platelet-derived growth factor stimulation. The cells were defective in Rac1-regulated behaviors, including lamellipodia formation, membrane ruffling, migration, and spreading. Wild-type DGKzeta, but not a kinase-dead mutant, or addition of exogenous PA rescued Rac activation. DGKzeta stably associated with PAK1 and RhoGDI, suggesting these proteins form a complex that functions as a Rac1-selective RhoGDI dissociation factor. These results define a pathway that links diacylglycerol, DGKzeta, and PA to the activation of Rac1: the PA generated by DGKzeta activates PAK1, which dissociates RhoGDI from Rac1 leading to changes in actin dynamics that facilitate the changes necessary for cell motility.
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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 | 0.001 |
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".