Diacylglycerol kinase zeta regulates Rac1-mediated remodeling of the actin cytoskeleton
Bibliographic record
Abstract
The lipid second messengers diacylglycerol (DAG) and phosphatidic acid (PA) regulate the activity and localization of actin reorganizing proteins that participate in cellular shape changes underlying important biological processes. DAG kinases (DGKs) phosphorylate DAG to yield PA, thereby attenuating the activity of DAG-activated proteins and stimulating proteins that respond to PA. Using cell biological and biochemical approaches, I explored the hypothesis that DGKzeta regulates actin cytoskeleton remodeling in mammalian cells by associating with and promoting the activity of the Rho GTPase Rac1 and the Rac1-activated kinase PAK1. I found that DGKzeta forms a complex with both proteins, and that PA from DGKzeta promotes the release of Rac1 from its inhibitor RhoGDI, triggering Rac1 activation. DGKzeta also regulates the localization and activity of PAK1. Furthermore, the ability of DGKzeta to promote Rac1 activity appears to underlie important physiological processes requiring the restructuring of the actin cytoskeleton such as cell migration, neurite outgrowth, and myoblast fusion. Localization of signaling complexes to specific cellular domains is required for complex changes in cell morphology. Because subcellular localization is critical for DGKzeta function, I investigated the molecular mechanisms underlying its targeting to different cellular compartments. I found that both PKC-mediated phosphorylation of the MARCKS domain and binding of the C-terminus to syntrophins regulate DGKzeta recruitment to the plasma membrane. Collectively, my results define a molecular mechanism that regulates the recruitment of DGKzeta to the membrane and that couples changes in DAG and PA to the activation of PAK1 and Rac1. These findings have uncovered a novel role for DGKzeta in actin cytoskeleton organization.
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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) | 0.001 | 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".