Exploring the Targets of Reactive Oxygen Species and Defense against Oxidative Stress in <i>Campylobacter jejuni</i> Using a Multiomics Approach
Bibliographic record
Abstract
Campylobacter jejuni is a major cause of human gastroenteritis. Pathogenesis depends on survival in reactive oxygen species (ROS) that are produced endogenously and by host phagocytes and microbiota. Label-based proteomics by LC-MS/MS quantified 1347 proteins (83.0% of the predicted proteome) in response to hydrogen peroxide (10 μM/0.5 mM) and superoxide-inducing paraquat (PQ; 2 μM/10 μM). Antioxidants including catalase (KatA) and alkylhydroperoxide reductase (AhpC), were induced, consistent with the oxidative stress response. Changes to nutrient transporters (SdaC/PutP/LctP) correlated with the intracellular abundance of substrates (serine/proline/lactate). ROS significantly elevated the abundance of the outer membrane protein Cj1170c, and Δ cj 1170c bacteria were compromised for survival in H 2 O 2 and under osmotic stress. PQ induced intracellular accumulation of threonine and homoserine, while Δ cj1170c bacteria were depleted of these metabolites. ROS targets cysteine thiols that can be irreversibly modified to sulfinic and sulfonic (SO 2 H/SO 3 H) acids. We identified 1334 Cys-SO 2 H/SO 3 H-modified peptides (867 sites in 495 proteins) using SCX negative and HILIC positive selection coupled to LC-MS/MS. Many sites were modified without exogenous H 2 O 2, suggesting that C. jejuni maintains an oxidative intracellular environment potentially related to microaerophilicity. Fe–S clusters were the primary targets of ROS. ROS trigger molecular remodeling associated with in-host growth, while overoxidizable Cys sites provide targets for redox-based antimicrobials.
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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".