PTP-PEST controls motility through regulation of Rac1
Bibliographic record
Abstract
The cytoplasmic protein tyrosine phosphatase, PTP-PEST, associates with the focal adhesion proteins p130cas and paxillin and has recently been implicated in cell migration. In this study, we investigated the mechanism by which PTP-PEST regulates this phenomenon. We find that PTP-PEST is activated in an adhesion-dependent manner and localizes to the tips of membrane protrusions in spreading fibroblasts. We show that the catalytic activity of PTP-PEST is a key determinant for its effects on motility. Overexpression of PTP-PEST, but not a catalytically inactive form, impairs haptotaxis, cell spreading and formation of membrane protrusions in CHOK1 cells. In addition, overexpression of PTP-PEST in Rat1 fibroblasts perturbs membrane ruffling and motility in response to PDGF stimulation. The expression level of PTP-PEST modulates the activity of the small GTPase, Rac1. PTP-PEST overexpression suppresses activation of Rac1 in response to both integrin-mediated adhesion or growth factor stimulation. In contrast, fibroblasts that lack PTP-PEST expression show enhanced Rac1 activity. Co-expression of constitutively active Rac1 with PTP-PEST overcomes the inhibition of cell spreading and migration indicating that PTP-PEST acts by antagonizing Rac1 activation. Our data suggest a model in which PTP-PEST is activated by integrins and localized to regions where it can control motile events at the leading edge through inhibition of the small GTPase Rac1.
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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".