The 58-Kilodalton Major Virulence Factor of <i>Francisella tularensis</i> Is Required for Efficient Utilization of Iron
Bibliographic record
Abstract
We investigated the role of the 58-kDa FTT0918 protein in the iron metabolism of Francisella tularensis. The phenotypes of SCHU S4, a prototypic strain of F. tularensis subsp. tularensis, and the Delta FTT0918 and Delta fslA isogenic mutants were analyzed. The gene product missing in the Delta fslA mutant is responsible for synthesis of a siderophore. When grown in broth with various iron concentrations, the two deletion mutants generally reached lower maximal densities than SCHU S4. The Delta FTT0918 mutant, but not the Delta fslA mutant, upregulated the genes of the F. tularensis siderophore locus (fsl) operon even at high iron concentrations. A chrome azurol sulfonate plate assay confirmed siderophore production by all strains except the Delta fslA strain. In a cross-feeding experiment using medium devoid of free iron, SCHU S4 promoted growth of the Delta fslA strain but not of the Delta FTT0918 strain. The sensitivity of SCHU S4 and the Delta FTT0918 and Delta fslA strains to streptonigrin demonstrated that the Delta FTT0918 strain contained a smaller free intracellular iron pool and that the Delta fslA strain contained a larger one than SCHU S4. In contrast to the marked attenuation of the Delta FTT0918 strain, the Delta fslA strain was as virulent as SCHU S4 in a mouse model. Altogether, the data demonstrate that the FTT0918 protein is required for F. tularensis to utilize iron bound to siderophores and that it likely has a role also in siderophore-independent iron acquisition. We suggest that the FTT0918 protein be designated Fe utilization protein A, FupA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".