Genetic Adaptation of <i>Pseudomonas aeruginosa</i> to the Airways of Cystic Fibrosis Patients Is Catalyzed by Hypermutation
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Bibliographic record
Abstract
In previous work (E. E. Smith, D. G. Buckley, Z. Wu, C. Saenphimmachack, L. R. Hoffman, D. A. D'Argenio, S. I. Miller, B. W. Ramsey, D. P. Speert, S. M. Moskowitz, J. L. Burns, R. Kaul, and M. V. Olson, Proc. Natl. Acad. Sci. USA 103:8487-8492, 2006) it was shown that Pseudomonas aeruginosa undergoes intense genetic adaptation during chronic respiratory infection (CRI) in cystic fibrosis (CF) patients. We used the same collection of isolates to explore the role of hypermutation in this process, since one of the hallmarks of CRI is the high prevalence of DNA mismatch repair (MMR) system-deficient mutator strains. The presence of mutations in 34 genes (many of them positively linked to adaptation in CF patients) in the study collection of 90 P. aeruginosa isolates obtained longitudinally from 29 CF patients was not homogeneous; on the contrary, mutations were significantly concentrated in the mutator lineages, which represented 17% of the isolates (87% MMR deficient). While sequential nonmutator lineages acquired a median of only 0.25 mutation per year of infection, mutator lineages accumulated more than 3 mutations per year. On the whole-genome scale, data for the first fully sequenced late CF isolate, which was also shown to be an MMR-deficient mutator, also support these findings. Moreover, for the first time the predicted amplification of mutator populations due to hitchhiking with adaptive mutations in the course of natural human infections is clearly documented. Interestingly, increased accumulation of mutations in mutator lineages was not a consequence of overrepresentation of mutations in genes involved in antimicrobial resistance, the only adaptive trait linked so far to hypermutation in CF patients, demonstrating that hypermutation also plays a major role in P. aeruginosa genome evolution and adaptation during CRI.
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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 | 0.000 | 0.001 |
| 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