Comparative genomics of ST5 and ST30 methicillin-resistant Staphylococcus aureus sequential isolates recovered from paediatric patients with cystic fibrosis
Bibliographic record
Abstract
Staphylococcus aureus chronic airway infection in patients with cystic fibrosis (CF) allows this pathogen to adapt over time in response to different selection pressures. We have previously shown that the main sequence types related to community-acquired methicillin-resistant S. aureus (MRSA) infections in Argentina – ST5 and ST30 – are also frequently isolated from the sputum of patients with CF, but in these patients they usually display multi-drug antimicrobial resistance. In this study, we sequenced the genomes of MRSA from four paediatric CF patients with the goal of identifying mutations among sequential isolates, especially those possibly related to antimicrobial resistance and virulence, which might contribute to the adaptation of the pathogen in the airways of patients with CF. Our results revealed genetic differences in sequential MRSA strains isolated from patients with CF in both their core and accessory genomes. Although the genetic adaptation of S. aureus was distinct in different hosts, we detected independent mutations in thyA, htrA, rpsJ and gyrA – which are known to have crucial roles in S. aureus virulence and antimicrobial resistance – in isolates recovered from multiple patients. Moreover, we identified allelic variants that were detected in all of the isolates recovered after a certain time point; these non-synonymous mutations were in genes associated with antimicrobial resistance, virulence, iron scavenging and oxidative stress resistance. In conclusion, our results provide evidence of genetic variability among sequential MRSA isolates that could be implicated in the adaptation of these strains during chronic CF airway infection.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".