Protein <i>S</i> -Bacillithiolation Functions in Thiol Protection and Redox Regulation of the Glyceraldehyde-3-Phosphate Dehydrogenase Gap in <i>Staphylococcus aureus</i> Under Hypochlorite Stress
Bibliographic record
Abstract
Aims: Bacillithiol (BSH) is the major low-molecular-weight thiol of the human pathogen Staphylococcus aureus. In this study, we used OxICAT and Voronoi redox treemaps to quantify hypochlorite-sensitive protein thiols in S. aureus USA300 and analyzed the role of BSH in protein S-bacillithiolation. Results: The OxICAT analyses enabled the quantification of 228 Cys residues in the redox proteome of S. aureus USA300. Hypochlorite stress resulted in >10% increased oxidation of 58 Cys residues (25.4%) in the thiol redox proteome. Among the highly oxidized sodium hypochlorite (NaOCl)-sensitive proteins are five S-bacillithiolated proteins (Gap, AldA, GuaB, RpmJ, and PpaC). The glyceraldehyde-3-phosphate (G3P) dehydrogenase Gap represents the most abundant S-bacillithiolated protein contributing 4% to the total Cys proteome. The active site Cys151 of Gap was very sensitive to overoxidation and irreversible inactivation by hydrogen peroxide (H2O2) or NaOCl in vitro. Treatment with H2O2 or NaOCl in the presence of BSH resulted in reversible Gap inactivation due to S-bacillithiolation, which could be regenerated by the bacilliredoxin Brx (SAUSA300_1321) in vitro. Molecular docking was used to model the S-bacillithiolated Gap active site, suggesting that formation of the BSH mixed disulfide does not require major structural changes. Conclusion and Innovation: Using OxICAT analyses, we identified 58 novel NaOCl-sensitive proteins in the pathogen S. aureus that could play protective roles against the host immune defense and include the glycolytic Gap as major target for S-bacillithiolation. S-bacillithiolation of Gap did not require structural changes, but efficiently functions in redox regulation and protection of the active site against irreversible overoxidation in S. aureus. Antioxid. Redox Signal. 28, 410–430.
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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".