Genome-Wide Identification of Francisella tularensis Virulence Determinants
Bibliographic record
Abstract
Francisella tularensis is a gram-negative pathogen that causes life-threatening infections in humans and has potential for use as a biological weapon. The genetic basis of the F. tularensis virulence is poorly understood. This study screened a total of 3,936 transposon mutants of the live vaccine strain for infection in a mouse model of respiratory tularemia by signature-tagged mutagenesis. We identified 341 mutants attenuated for infection in the lungs. The transposon disruptions were mapped to 95 different genes, virtually all of which are also present in the genomes of other F. tularensis strains, including human pathogenic F. tularensis strain Schu S4. A small subset of these attenuated mutants carried insertions in the genes encoding previously known virulence factors, but the majority of the identified genes have not been previously linked to F. tularensis virulence. Among these are genes encoding putative membrane proteins, proteins associated with stress responses, metabolic proteins, transporter proteins, and proteins with unknown functions. Several attenuated mutants contained disruptions in a putative capsule locus which partially resembles the poly-γ-glutamate capsule biosynthesis locus of Bacillus anthracis, the anthrax agent. Deletional mutation analysis confirmed that this locus is essential for F. tularensis virulence.
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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) | 0.000 | 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 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".