ArticleFrontiers in cellular and infection microbiology2022
How Yeast Antifungal Resistance Gene Analysis Is Essential to Validate Antifungal Susceptibility Testing Systems.
Article in Frontiers in cellular and infection microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Phenotypical Differences at the Physiological and Clinical Level between Two Genetically Closely RelatedJournal of fungi (Basel, Switzerland) · 2024Article
- Candidiasis and Other Emerging Yeasts.Current fungal infection reports · 2023Review
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Authors and funding
4 authors.
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Abstract
Objectives: The antifungal susceptibility testing (AFST) of yeast pathogen alerts clinicians about the potential emergence of resistance. In this study, we compared two commercial microdilution AFST methods: Sensititre YeastOne read visually (YO) and MICRONAUT-AM read visually (MN) or spectrophotometrically (MNV), interpreted with Clinical and Laboratory Standards Institute and European Committee on Antimicrobial Susceptibility Testing criteria, respectively. Methods: Overall, 97 strains from 19 yeast species were measured for nine antifungal drugs including a total of 873 observations. First, the minimal inhibitory concentration (MIC) was compared between YO and MNV, and between MNV and MN, either directly or by assigning them to five susceptibility categories. Those categories were based on the number of MIC dilutions around the breakpoint or epidemiological cut-off reference values (ECOFFs or ECVs). Second, YO and MNV methods were evaluated for their ability to detect the elevation of MICs due to mutation in antifungal resistance genes, thanks to pairs or triplets of isogenic strains isolated from a single patient along a treatment previously analyzed for antifungal resistance gene mutations. Reproducibility measurement was evaluated, thanks to three quality control (QC) strains. Results: YO and MNV direct MIC comparisons obtained a global agreement of 67%. Performing susceptibility category comparisons, only 22% and 49% of the MICs could be assigned to categories using breakpoints and ECOFFs/ECVs, respectively, and 40% could not be assigned due to the lack of criteria in both consortia. The YO and MN susceptibility categories gave accuracies as low as 50%, revealing the difficulty to implement this method of comparison. In contrast, using the antifungal resistance gene sequences as a gold standard, we demonstrated that both methods (YO and MN) were equally able to detect the acquisition of resistance in the Conclusion: This study demonstrates the valuable use of both commercial microdilution AFST methods to detect antifungal resistance due to point mutations in antifungal resistance genes. We highlighted the difficulty to conduct conclusive analyses without antifungal gene sequence data as a gold standard. Indeed, MIC comparisons taking into account the consortia criteria of interpretation remain difficult even after the effort of harmonization.
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