Population genomics of Candida albicans reveals genetic footprints that allow the prediction of antifungal resistance

Curated resistance resources like FungAMR can accurately identify genomic markers predictive of antifungal resistance in Candida albicans, but coverage is incomplete across azoles and echinocandins.

• Why it matters: Rapid detection of fungal drug resistance is urgent, yet the predictive value of whole-genome sequencing for resistance has not been thoroughly tested.
• What they did: The study integrated more than 1000 Candida albicans genomes with resistance phenotypes to six antifungals, using Genome Wide Association Studies and machine learning with curated resistance mutations and variant effect predictors.
• The result: Curated mutations were found in 56 to 74% of isolates with reduced azole susceptibility and 57 to 90% with reduced echinocandin susceptibility; prediction accuracy declined without matching genetic backgrounds and was lower for resistance than for drug-susceptible strains.