Comparison of Francisella tularensis genomes reveals evolutionary events associated with the emergence of human pathogenic strains
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Francisella tularensis subspecies tularensis and holarctica are pathogenic to humans, whereas the two other subspecies, novicida and mediasiatica, rarely cause disease. To uncover the factors that allow subspecies tularensis and holarctica to be pathogenic to humans, we compared their genome sequences with the genome sequence of Francisella tularensis subspecies novicida U112, which is nonpathogenic to humans. RESULTS: Comparison of the genomes of human pathogenic Francisella strains with the genome of U112 identifies genes specific to the human pathogenic strains and reveals pseudogenes that previously were unidentified. In addition, this analysis provides a coarse chronology of the evolutionary events that took place during the emergence of the human pathogenic strains. Genomic rearrangements at the level of insertion sequences (IS elements), point mutations, and small indels took place in the human pathogenic strains during and after differentiation from the nonpathogenic strain, resulting in gene inactivation. CONCLUSION: The chronology of events suggests a substantial role for genetic drift in the formation of pseudogenes in Francisella genomes. Mutations that occurred early in the evolution, however, might have been fixed in the population either because of evolutionary bottlenecks or because they were pathoadaptive (beneficial in the context of infection). Because the structure of Francisella genomes is similar to that of the genomes of other emerging or highly pathogenic bacteria, this evolutionary scenario may be shared by pathogens from other species.
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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 | 0.001 | 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 it