Genomic analysis of group A <i>Streptococcus</i> isolated during a correctional facility outbreak of MRSA in 2004
Bibliographic record
Abstract
BACKGROUND: In 2004–2005, an outbreak of impetigo occurred at a correctional facility during a sentinel outbreak of methicillin- resistant Staphylococcus aureus (MRSA) in Alberta, Canada. Next-generation sequencing (NGS) was used to characterize the group A Streptococcus (GAS) isolates and evaluate whether genomic biomarkers could distinguish between those recovered alone and those co-isolated with S. aureus. METHODS: Superficial wound swabs collected from all adults with impetigo during this outbreak were cultured using standard methods. NGS was used to characterize and compare all of the GAS and S. aureus genomes. RESULTS: Fifty-three adults were culture positive for GAS, with a subset of specimens also positive for MRSA ( n = 5) or methicillin-sensitive S. aureus ( n = 3). Seventeen additional MRSA isolates from this facility from the same time frame (no GAS co-isolates) were also included. All 78 bacterial genomes were analyzed for the presence of known virulence factors, plasmids, and antimicrobial resistance (AMR) genes. Among the GAS isolates were 12 emm types, the most common being 41.2 ( n = 27; 51%). GAS genomes were phylogenetically compared with local and public datasets of invasive and non-invasive isolates. GAS genomes had diverse profiles for virulence factors, plasmids, and AMR genes. Pangenome analysis did not identify horizontally transferred genes in the co-infection versus single infections. CONCLUSIONS: GAS recovered from invasive and non-invasive sources were not genetically distinguishable. Virulence factors, plasmids, and AMR profiles grouped by emm type, and no genetic changes were identified that predict co-infection or horizontal gene transfer between GAS and S. aureus.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".