Dissecting components of the <i>Campylobacter jejuni fetMP-fetABCDEF</i> gene cluster in iron scavenging
Bibliographic record
Abstract
ABSTRACT Campylobacter jejuni is a leading cause of bacterial gastroenteritis worldwide. Acute infection can be antecedent to highly debilitating long-term sequelae. Expression of iron acquisition systems is vital for C. jejuni to survive the low iron availability within the human gut. The C. jejuni fetMP-fetABCDEF gene cluster is known to be upregulated during human infection and under iron limitation. While FetM and FetP have been functionally linked to iron transport in prior work, here we assess the contribution by each of the downstream genes ( fetABCDEF ) to C. jejuni growth during both iron-depleted and iron-replete conditions. Significant growth impairment was observed upon disruption of fetA , fetB, fetC , and fetD , suggesting a role in iron acquisition for each encoded protein. FetA expression was modulated by iron-availability but not dependent on the presence of FetB, FetC, FetD, FetE or FetF. Functions of the putative thioredoxins FetE and FetF were redundant in iron scavenging, requiring a double deletion (Δ fetEF ) to exhibit a growth defect. C. jejuni FetE was expressed and the structure solved to 1.50 Å, revealing structural similarity to thiol-disulfide oxidases. Functional characterization in biochemical assays showed that FetE reduced insulin at a slower rate than E. coli Trx and that together, FetEF promoted substrate oxidation in cell extracts, suggesting that FetE (and presumably FetF) are oxidoreductases that can mediate oxidation in vivo . This study advances our understanding of the contributions by the fetMP-fetABCDEF gene cluster to virulence at a genetic and functional level, providing foundational knowledge towards mitigating C. jejuni -related morbidity and mortality.
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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".