Real-time PCR assays for genotyping of Cryptococcus gattii in North America
Bibliographic record
Abstract
BACKGROUND: Cryptococcus gattii has been the cause of an ongoing outbreak starting in 1999 on Vancouver Island, British Columbia and spreading to mainland Canada and the US Pacific Northwest. In the course of the outbreak, C. gattii has been identified outside of its previously documented climate, habitat, and host disease. Genotyping of C. gattii is essential to understand the ecological and geographical expansion of this emerging pathogen. METHODS: We developed and validated a mismatch amplification mutation assay (MAMA) real-time PCR panel for genotyping C. gattii molecular types VGI-VGIV and VGII subtypes a,b,c. Subtype assays were designed based on whole-genome sequence of 20 C. gattii strains. Publically available multilocus sequence typing (MLST) data from a study of 202 strains was used for the molecular type (VGI-VGIV) assay design. All assays were validated across DNA from 112 strains of diverse international origin and sample types, including animal, environmental and human. RESULTS: Validation revealed each assay on the panel is 100% sensitive, specific and concordant with MLST. The assay panel can detect down to 0.5 picograms of template DNA. CONCLUSIONS: The (MAMA) real-time PCR panel for C. gattii accurately typed a collection of 112 diverse strains and demonstrated high sensitivity. This is a time and cost efficient method of genotyping C. gattii best suited for application in large-scale epidemiological studies.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".