Sequencing and Detection of Two Missense Variants at Chromosome 7 as Potential Azole Resistance Markers in Saccharomyces Cerevisiae
Bibliographic record
Abstract
Introduction: Widespread practices of over-prescribing antibiotic, antiviral, and antifungal drugs have sparked concern over the risk of antimicrobial resistance arising in bacterial, viral, and fungal pathogens. This risk threatens to jeopardize the efficacy of many drugs being prescribed today for said infections. Azoles are a major class of antifungal drugs, presenting the need for research efforts on mechanisms of azole resistance. My objective was to perform the genomic sequencing and variant profiling of a Baker’s Yeast (Saccharomyces cerevisiae) strain that displays resistance phenotype when plated with Clotrimazole, a type of azole antifungal. Methods: Through short-read genomic sequencing and subsequent variant calling, putative antifungal resistance genotypes were elucidated in a clotrimazole-resistant yeast strain. Results: Variant calls at the PDR1 and ERG25 loci reveal two potential Clotrimazole-resistance genotypes. Discussion: These variants are both missense mutations involving a single-nucleotide change to the reference genomic loci in question. Although PDR1 variants are putative markers of azole resistance in yeast, the emergence of a novel ERG25 variant that may contribute to this phenotype has not yet been. Conclusion: Follow-up experiments will need to include induced missense mutations at the ERG25 loci and selection assays to confirm that the described variants described here indeed constitute azole resistance. Establishing a knowledgebase of resistance marker genes and putative resistance variants for model organisms such as Saccharomyces cerevisiae can guide investigations into orthologous proteins in other species that may become responsible for future antifungal-resistant infections.
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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) | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| 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".