Serotyping of Streptococcus pneumoniae Based on Capsular Genes Polymorphisms
Bibliographic record
Abstract
Streptococcus pneumoniae serotype epidemiology is essential since serotype replacement is a concern when introducing new polysaccharide-conjugate vaccines. A novel PCR-based automated microarray assay was developed to assist in the tracking of the serotypes. Autolysin, pneumolysin and eight genes located in the capsular operon were amplified using multiplex PCR. This step was followed by a tagged fluorescent primer extension step targeting serotype-specific polymorphisms. The tagged primers were then hybridized to a microarray. Results were exported to an expert system to identify capsular serotypes. The assay was validated on 166 cultured S. pneumoniae samples from 63 different serotypes as determined by the Quellung method. We show that typing only 12 polymorphisms located in the capsular operon allows the identification at the serotype level of 22 serotypes and the assignation of 24 other serotypes to a subgroup of serotypes. Overall, 126 samples (75.9%) were correctly serotyped, 14 were assigned to a member of the same serogroup, 8 rare serotypes were erroneously serotyped, and 18 gave negative serotyping results. Most of the discrepancies involved rare serotypes or serotypes that are difficult to discriminate using a DNA-based approach, for example 6A and 6B. The assay was also tested on clinical specimens including 43 cerebrospinal fluid samples from patients with meningitis and 59 nasopharyngeal aspirates from bacterial pneumonia patients. Overall, 89% of specimens positive for pneumolysin were serotyped, demonstrating that this method does not require culture to serotype clinical specimens. The assay showed no cross-reactivity for 24 relevant bacterial species found in these types of samples. The limit of detection for serotyping and S. pneumoniae detection was 100 genome equivalent per reaction. This automated assay is amenable to clinical testing and does not require any culturing of the samples. The assay will be useful for the evaluation of serotype prevalence changes after new conjugate vaccines introduction.
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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) | 0.001 | 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".