Protein Tyrosine Nitration of Aldolase in Mast Cells: A Plausible Pathway in Nitric Oxide-Mediated Regulation of Mast Cell Function
Bibliographic record
Abstract
NO is a short-lived free radical that plays a critical role in the regulation of cellular signaling. Mast cell (MC)-derived NO and exogenous NO regulate MC activities, including the inhibition of MC degranulation. At a molecular level, NO acts to modify protein structure and function through several mechanisms, including protein tyrosine nitration. To begin to elucidate the molecular mechanisms underlying the effects of NO in MCs, we investigated protein tyrosine nitration in human MC lines HMC-1 and LAD2 treated with the NO donor S-nitrosoglutathione. Using two-dimensional gel Western blot analysis with an anti-nitrotyrosine Ab, together with mass spectrometry, we identified aldolase A, an enzyme of the glycolytic pathway, as a target for tyrosine nitration in MCs. The nitration of aldolase A was associated with a reduction in the maximum velocity of aldolase in HMC-1 and LAD2. Nuclear magnetic resonance analysis showed that despite these changes in the activity of a critical enzyme in glycolysis, there was no significant change in total cellular ATP content, although the AMP/ATP ratio was altered. Elevated levels of lactate and pyruvate suggested that S-nitrosoglutathione treatment enhanced glycolysis. Reduced aldolase activity was associated with increased intracellular levels of its substrate, fructose 1,6-bisphosphate. Interestingly, fructose 1,6-bisphosphate inhibited IgE-mediated MC degranulation in LAD2 cells. Thus, for the first time we report evidence of protein tyrosine nitration in human MC lines and identify aldolase A as a prominent target. This posttranslational nitration of aldolase A may be an important pathway that regulates MC phenotype and function.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".