Discrimination of Clinical and Food-Derived Candida Strains Using Biotyping and Molecular Typing Approaches

TL;DR

This study compares different methods to distinguish between Candida strains from clinical and food sources, finding that ITS sequencing and karyotyping are the most accurate.

Contribution

The study introduces the use of ITS sequencing and karyotyping as highly discriminatory methods for Candida strain typing.

Findings

ITS sequencing and karyotyping achieved a discrimination index of 1.000, the highest among tested methods.

Biotyping misclassified 64.3% of isolates compared to ITS sequencing.

Lower discrimination indices may reflect method limitations, not true genetic relatedness.

Abstract

Identification and differentiation of Candida spp. yeasts, especially clinically relevant isolates, is of high importance with respect to their origin, pathogenic potential, colonization pattern, and resistance to antimycotics. Currently, numerous typing methods with varying or unknown discriminatory power are used. This study evaluated the utility of five methods—biotyping using the API system, ITS1 and ITS4 sequence analysis, ITS region polymorphism, multiplex PCR of ITS1, ITS3, and ITS4 regions, and karyotyping—for typing 42 strains differing in origin (24 clinical and 18 food-borne). The highest discriminatory power was obtained for ITS sequencing and karyotyping, both yielding a discrimination index of 1.000. The discrimination indices for other methods ranged from 0.957 for genotyping based on ITS region polymorphism to 0.997 for multiplex PCR-genotyping. Although biotyping showed relatively high discriminatory potential, its use led to misclassification of 64.3% of isolates compared to ITS sequencing. These findings emphasize the importance of applying a typing method with a discrimination index of 1.000 to ensure accurate interpretation of strain-relatedness and origin. Methods with lower indices may reflect methodological limitations rather than actual genetic relatedness. Determining the discrimination index is therefore essential when selecting appropriate tools for yeast typing, particularly in clinical and epidemiological contexts.

Figures