The Emergence of Invasive Streptococcus pneumoniae Serotype 24F in Lebanon: Complete Genome Sequencing Reveals High Virulence and Antimicrobial Resistance Characteristics
Bibliographic record
Abstract
Background Invasive pneumococcal disease (IPD) remains a global health problem. IPD incidence has significantly decreased by the use of pneumococcal conjugate vaccines (PCV). Nevertheless, non-PCV serotypes remain a matter of concern. Eight Streptococcus pneumoniae serotype 24F isolates, belonging to a non-PCV serotype, were detected through the Lebanese Inter-Hospital Pneumococcal Surveillance Program. The aim of the study is to characterize phenotypic and genomic features of the 24F isolates in Lebanon. Methods WGS using long reads sequencing (PacBio) was performed to produce complete circular genomes and to determine clonality, antimicrobial resistance and virulence determinants. Results The sequencing results yielded eight closed circular genomes. Three multilocus sequence typing (MLST) types were identified (ST11618, ST14184, ST15253). Both MLST and WGS analyses revealed that these isolates from Lebanon were genetically homogenous belonging to clonal complex CC230 and clustered closely with isolates originating from Canada, United States of America, United Kingdom and Iceland. Their penicillin binding protein profiles correlated with both β-lactam susceptibility patterns and MLST types. Moreover, the isolates harbored the macrolide and tetracycline resistance genes and showed a similar virulence gene profile. To our knowledge, this study represents the first report of complete phenotypic and genomic characterization of the emerging Streptococcus pneumoniae, serotype 24F, in the Middle East and North Africa region.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".