High Affinity Iron Acquisition Systems Facilitate but Are Not Essential for Colonization of Chickens by Salmonella Enteritidis
Bibliographic record
Abstract
The roles of TonB mediated Fe3+(ferric iron) uptake via enterobactin (involving biosynthesis genesentABCDEF) and Fe2+(ferrous iron) uptake through the FeoABC transporter are poorly defined in the context of chicken-Salmonellainteractions. Both uptake systems are believed to be the major contributors of iron supply in theSalmonellalife cycle. Current evidence suggests that these iron uptake systems play a major role in pathogenesis in mammals and as such, they represent promising antibacterial targets with therapeutic potential. We investigated the role of these iron uptake mechanisms regarding the ability ofSalmonellaEnteritidis (SEn) strains to colonize in a chicken infection model. Further we constructed a bioluminescent reporter to sense iron limitation during gastrointestinal colonization ofSalmonellain chicken viaex vivoimaging. Our data indicated that there is some redundancy between the ferric and ferrous iron uptake mechanisms regarding iron acquisition during SEn pathogenesis in chicken. We believe that this redundancy of iron acquisition in the host reservoir may be the consequence of adaptation to unique avian environments, and thus warrants further investigation. To our knowledge, this the first report providing direct evidence that both enterobactin synthesis and FeoABC mediated iron uptake contribute to the virulence of SEn in chickens.
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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".