Discovery of a <i>Streptococcus pneumoniae</i> serotype 33F capsular polysaccharide locus that lacks <i>wcjE</i> and contains a <i>wcyO</i> pseudogene
Bibliographic record
Abstract
Abstract Objectives As part of large on-going vaccine impact studies in Fiji and Mongolia, we identified 25/2750 (0.9%) of nasopharyngeal swabs by microarray that were positive for Streptococcus pneumoniae contained pneumococci with a divergent 33F capsular polysaccharide locus (designated ‘33F-1’). We investigated the 33F-1 capsular polysaccharide locus to better understand the genetic variation and its potential impact on serotyping results. Methods Whole genome sequencing was conducted on ten 33F-1 pneumococcal isolates. Initially, sequence reads were used for molecular serotyping by PneumoCaT. Phenotypic typing of 33F-1 isolates was then performed using the Quellung reaction and latex agglutination. Genome assemblies were used in phylogenetic analyses of each gene in the capsular locus to investigate genetic divergence. Results All ten pneumococcal isolates with the 33F-1 cps locus typed as 33F by Quellung and latex agglutination. Unlike the reference 33F capsule locus sequence, DNA microarray and PneumoCaT analyses found that 33F-1 pneumococci lack the wcjE gene, and instead contain wcyO with a frameshift mutation. Phylogenetic analyses found the wzg, wzh, wzd, wze, wchA, wciG and glf genes in the 33F-1 cps locus had higher DNA sequence similarity to homologues from other serotypes than to the 33F reference sequence. Conclusions We have discovered a novel genetic variant of serotype 33F, which lacks wcjE and contains a wcyO pseudogene. This finding adds to the understanding of molecular epidemiology of pneumococcal serotype diversity, which is poorly understood in low and middle-income countries.
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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 | 0.000 | 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) | 0.001 | 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".