Salmonella enterica serovar Typhi siderophore production is elevated and Fur inactivation causes cell filamentation and attenuation in macrophages
Bibliographic record
Abstract
Salmonella enterica serovars Typhi and Typhimurium are two closely related bacteria causing different types of infection in humans. Iron acquisition is considered essential for virulence. Siderophores are important iron chelators and production of enterobactin and salmochelins by these serovars was quantified. Overall, Salmonella Typhi produced higher levels of siderophores than Salmonella Typhimurium. The role of the global regulator Fur, involved in iron homeostasis, present and conserved in both these serovars, was then investigated. Deletion of the fur gene led to distinct phenotypes in these serovars. Defective growth in iron-rich and iron-limiting conditions and formation of filamentous cells was only observed in the S. Typhi fur mutant. Furthermore, Fur was required for optimal motility in both serovars, but motility was more reduced for the fur mutant of S. Typhi compared to S. Typhimurium. During interaction with human-cultured macrophages, Fur was more important for S. Typhi, as the fur mutant had severe defects in uptake and survival. Globally, these results demonstrate that Fur differentially affects the physiology and the virulence phenotypes of the two strains and is more critical for S. Typhi growth, morphology, motility and interaction with host cells than it is for S. Typhimurium.
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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".