The Campylobacter jejuni Ferric Uptake Regulator Promotes Acid Survival and Cross-Protection against Oxidative Stress
Bibliographic record
Abstract
Campylobacter jejuni is a prevalent cause of bacterial gastroenteritis in humans worldwide. The mechanisms by which C. jejuni survives stomach acidity remain undefined. In the present study, we demonstrated that the C. jejuni ferric uptake regulator (Fur) plays an important role in C. jejuni acid survival and acid-induced cross-protection against oxidative stress. A C. jejuni Δfur mutant was more sensitive to acid than the wild-type strain. Profiling of the acid stimulon of the C. jejuni Δfur mutant allowed us to uncover Fur-regulated genes under acidic conditions. In particular, Fur was found to upregulate genes involved in flagellar and cell envelope biogenesis upon acid stress, and mutants with deletions of these genes were found to be defective in surviving acid stress. Interestingly, prior acid exposure of C. jejuni cross-protected against oxidative stress in a catalase (KatA)- and Fur-dependent manner. Western blotting and reverse transcription-quantitative PCR revealed increased expression of KatA upon acid stress. Electrophoretic mobility shift assays (EMSAs) demonstrated that the binding affinity between Fur and the katA promoter is reduced in vitro under conditions of low pH, rationalizing the higher levels of expression of katA under acidic conditions. Strikingly, the Δfur mutant exhibited reduced virulence in both human epithelial cells and the Galleria mellonella infection model. Altogether, this is the first study showing that, in addition to its role in iron metabolism, Fur is an important regulator of C. jejuni acid responses and this function cross-protects against oxidative stress. Moreover, our results clearly demonstrate Fur's important role in C. jejuni pathogenesis.
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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".