Molecular Evaluation of the mRNA Expression of the ERG11 , ERG3 , CgCDR1 , and CgSNQ2 Genes Linked to Fluconazole Resistance in Candida glabrata in a Colombian Population

• Published in: Journal of fungi (Basel) Vol. 10; no. 7; p. 509
• Main Authors: Cárdenas Parra, Leidy Yurany, Rojas Rodríguez, Ana Elisa, Pérez Cárdenas, Jorge Enrique, Pérez-Agudelo, Juan Manuel
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.07.2024
• Subjects: Analysis; Antifungal agents; Candida glabrata; Classification; Drug dosages; Enzymes; ERG3 gene; Fluconazole; fungal drug resistance; Fungi; Gene expression; Genes; Genetic aspects; Genetic engineering; Infections; Messenger RNA; molecular docking simulation; multivariate analysis; Mutation; Population studies; reverse transcriptase polymerase chain reaction; Sterols; Yeast; Colombia; Spain; United States > US; reverse transcriptase polymerase chain reaction; fluconazole; Candida glabrata; fungal drug resistance; molecular docking simulation; multivariate analysis
• ISSN: 2309-608X; 2309-608X
• DOI: 10.3390/jof10070509

The study of genes associated with fluconazole resistance, from a molecular perspective, increases the understanding of the phenomenon with a view to its clinical applicability. We sought to establish the predictive molecular profile of fluconazole resistance in by analyzing the , , , and genes. Expression was quantified using RT-qPCR. Metrics were obtained through molecular docking and Fisher discriminant functions. Additionally, a predictive classification was made against the susceptibility of to fluconazole. The relative expression of the , , and genes was higher in the fluconazole-resistant strains than in the fluconazole-susceptible, dose-dependent strains. The gene with the highest relative expression in the fluconazole-exposed strains was , and in both the resistant and susceptible, dose-dependent strains exposed to fluconazole, this was also the case. The molecular docking model generated a median number of contacts between fluconazole and that was lower than the median number of contacts between fluconazole and , - , and - . The predicted classification through the multivariate model for fluconazole susceptibility achieved an accuracy of 73.5%. The resistant strains had significant expression levels of genes encoding efflux pumps and the gene. Molecular analysis makes the identification of a low affinity between fluconazole and its pharmacological target possible, which may explain the lower intrinsic susceptibility of the fungus to fluconazole.