Campylobacter jejuni ferric–enterobactin receptor CfrA is TonB3 dependent and mediates iron acquisition from structurally different catechol siderophores
Bibliographic record
Abstract
Campylobacter jejuni NCTC11168 does not produce any endogenous siderophores of its own yet requires the CfrA enterobactin transporter for in vivo colonization. In addition, the genome of C. jejuni NCTC11168 contains three distinct TonB energy transduction systems, named TonB1, TonB2, and TonB3, that have not been tested for their role in siderophore uptake or their functional redundancy. We demonstrate that C. jejuni NCTC11168 transports ferric-enterobactin in an energy dependent manner that requires TonB3 for full activity with TonB1 showing partial functional redundancy. Moreover C. jejuni NCTC11168 can utilize a wide variety of structurally different catechol siderophores as sole iron sources during growth. This growth is solely dependent on the CfrA enterobactin transporter and highlights the wide range of substrates that this transporter can recognize. TonB3 is also required for growth on most catechol siderophores. Furthermore, either TonB1 or TonB3 is sufficient for growth on hemin or hemoglobin as a sole iron source demonstrating functional redundancy between TonB1 and TonB3. In vivo colonization assays with isogenic deletion mutants revealed that both TonB1 and TonB3 are required for chick colonization with TonB2 dispensable in this model. These results further highlight the importance of iron transport for efficient C. jejuni colonization.
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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 | 0.001 |
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".