16 Vascular redox signalling and protein oxidation: focus on palmitoylation of NADPH oxidase 5 (Nox5) as a potential posttranslational regulatory process
Bibliographic record
Abstract
NOX5 is a significant source of reactive oxygen species (ROS), which controls vascular tone and blood pressure, making it an interesting drug target for hypertension. Understanding the regulatory mechanisms of Nox5 is a high priority. We, therefore, investigate how palmitoylation as a posttranslational modification regulates Nox5 trafficking, localization and function. We engineered HEK cells stably expressing tetracycline-inducible wild-type and mutant (C338/342A) YFP-tagged Nox5. The substantial level of palmitoylation observed in the WT was abolished in the mutant Nox5. Confocal microscopy analysis indicated that Nox5 was predominantly localised in the ER, as previously reported. A small population of Nox5 also localises at the cell surface membrane. Membrane labelling and purification with biotinylation reagents revealed no significant difference in surface abundance between the WT and mutant Nox5. We evaluated Nox5 activity using the ROS sensor L-012 and detected no ROS in the absence of tetracycline. However, in tetracycline-treated cells, ROS were only detected following stimulation of cells with Nox5 agonists (400nM PMA and 1uM Ionomycin). The greater ROS generation observed in WT than in mutant cells indicates that palmitoylation enhances Nox5 activity. Next, using TurboID-mediated proximity labelling and mass spectroscopy, we identified Nox5 interaction partners, including palmitoylating (zDHHC5), depalmitoylating (APT2) enzymes and previously proven interactors. Evidence herein suggests that palmitoylation controls Nox5 activity but not its subcellular distribution. Further experiments will investigate the importance of identified palmitoylation enzymes, the effect of palmitoylation on Nox5 activity (and localization), and the downstream functional consequence of Nox5 palmitoylation in VSMC growth, migration, contraction, and inflammation.
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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) | 0.002 | 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".