Oxidative stress-induced modifications of histidyl-tRNA synthetase affect its tRNA aminoacylation activity but not its immunoreactivity
Bibliographic record
Abstract
The aminoacyl-tRNA synthetases are ubiquitously expressed enzymes that catalyze the esterification of amino acids to their cognate tRNAs. Autoantibodies against several aminoacyl-tRNA synthetases are found in autoimmune polymyositis and dermatomyositis patients. Because necrosis is often found in skeletal muscle biopsies of these patients, we hypothesized that cell-death-induced protein modifications may help in breaking immunological tolerance. Since cell death is associated with oxidative stress, the effect of oxidative stress on the main myositis-specific autoantibody target Jo-1 (histidyl-tRNA synthetase; HisRS) was studied in detail. The exposure of Jurkat cells to hydrogen peroxide resulted in the detection of several oxidized methionines and one oxidized tryptophan residue in the HisRS protein, as demonstrated by mass spectrometry. Unexpectedly, the tRNA aminoacylation activity of HisRS appeared to be increased upon oxidative modification. The analysis of myositis patient sera did not lead to the detection of autoantibodies that are specifically reactive with the modified HisRS protein. The results of this study demonstrate that the Jo-1/HisRS autoantigen is modified under oxidative stress conditions. The consequences of these modifications for the function of HisRS and its autoantigenicity are discussed.
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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".