Multi-locus sequence typing and phylogenetics of Cryptococcus neoformans AD hybrids
Bibliographic record
Abstract
Hybrid AD strains of the human pathogenic Cryptococcus neoformans species complex have been reported from many parts of the world. However, their origin, diversity, and evolution are incompletely understood. In this study, we analyzed 102 AD hybrid strains representing 21 countries on five continents. For each strain, we obtained its mating type and its allelic sequences at each of the seven loci that have been used for genotyping haploid serotypes A and D strains of the species complex by the Cryptococcus research community. Our results showed that most AD hybrids exhibited loss of heterozygosity at one or more of the seven analyzed loci. Phylogenetic and population genetic analyses of the allelic sequences revealed multiple origins of the hybrids within each continent, dating back to one million years ago in Africa and up to the present in other continents. We found evidence for clonal reproduction and long-distance dispersal of these hybrids in nature. Comparisons with the global haploid serotypes A and D strains identified new alleles and new haploid multi-locus genotypes in AD hybrids, consistent with the presence of yet-to-be discovered genetic diversity in haploid populations of this species complex in nature. Together, our results indicate that AD hybrids can be effectively genotyped using the same multi-locus sequencing type approach as that established for serotypes A and D strains. Our comparisons of the AD hybrids among each other as well as with the global haploid serotypes A and D strains revealed novel genetic diversity as well as evidence for multiple origins and dynamic evolution of these hybrids in nature.
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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 | 0.000 | 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".