Non-selective regulation of peroxide and superoxide resistance genes by PerR in Campylobacter jejuni
Bibliographic record
Abstract
Campylobacter jejuni is an important foodborne pathogen. The molecular mechanisms for the regulation of oxidative stress resistance have not yet been understood fully in this bacterium. In this study, we investigated how PerR (peroxide stress regulator) modulates the transcriptional regulation of both peroxide and superoxide resistance genes in C. jejuni, particularly under oxidative stress conditions. The transcriptional levels of ahpC, katA, and sodB were substantially increased by aeration and oxidant exposure. Interestingly, a perR mutation completely abrogated the transcriptional response of ahpC, katA and sodB to oxidants. Furthermore, we demonstrated that perR transcription was reduced by aeration and oxidant exposure. In contrast to the unique role of PerR homologs in peroxide stress regulation in other bacteria, C. jejuni PerR directly regulates the transcription of sodB, the most important gene in superoxide defense, as evidenced by the alteration of sodB transcription by the perR mutation and direct binding of rPerR to the sodB promoter. In addition, we also observed notable morphological changes in C. jejuni from spiral rods to cocoid morphology under aerobic conditions. Based on the intracellular ATP levels, C. jejuni entered a viable-but-non-culturable (VBNC) state under aerobic conditions. These findings clearly demonstrate that C. jejuni possesses a unique regulatory mechanism of oxidative stress defense that does not specifically distinguish between peroxide and superoxide defense, and PerR plays a pivotal role in this non-selective regulation of oxidative stress resistance in C. jejuni.
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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".