A modified cysteinyl-labeling assay reveals reversible oxidation of protein tyrosine phosphatases in angiomyolipoma cells
Bibliographic record
Abstract
The production of reactive oxygen species (ROS) exerts an additional tier of control over tyrosine phosphorylation-dependent signal transduction by transiently inhibiting the catalytic activity of specific protein tyrosine phosphatases (PTPs). Hence, the ability to detect reversible oxidation of PTPs in vivo is critical to understanding the complex biological role of ROS in the control of cellular signaling. Here, we describe an assay for identifying those PTPs that are reversibly oxidized in vivo, which utilizes the unique chemistry of the invariant catalytic Cys residue in labeling the active site with biotinylated small molecules under mildly acidic conditions. We have applied this cysteinyl-labeling assay to the study of platelet-derived growth factor (PDGF) receptor signaling in an angiomyolipoma cell model. Doing so has allowed us to detect reversible oxidation of several proteins in response to sustained PDGF stimulation. As in other cell systems, we have observed the reversible oxidation of the classical PTP SHP2 and the tumor suppressor phosphatase PTEN in response to PDGF stimulation. Furthermore, we detected reversible oxidation of members of two other subclasses of PTPs, the receptor PTP LAR and the dual-specificity phosphatase MKP1. These data demonstrate the broad selectivity of the assay, allowing us to detect representatives of all of the major subgroups of the PTP superfamily. We anticipate that this cysteinyl-labeling enrichment strategy can be applied broadly to study reversible oxidation as a mechanism of harnessing PTP catalytic activity in a variety of signaling pathways.
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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 | 0.000 |
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".