First Step on the Way to Identify Dermatophytes Using Odour Fingerprints

Abstract

The clinical diagnosis of dermatophytosis and identification of dermatophytes face challenges due to reliance on culture-based methods. Rapid, cost-effective detection techniques for volatile organic compounds (VOCs) have been developed for other microorganisms, but their application to dermatophytes is limited. This study explores using VOCs as diagnostic markers for dermatophytes. We compared VOC profiles across different dermatophyte taxa using solid-phase microextraction (SPME) and advanced analytical methods: gas chromatography-mass spectrometry (GC-MS) and comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GC×GC-TOFMS). We analyzed 47 dermatophyte strains from 15 taxa grown on sheep wool, including clinically significant species. Additionally, we examined phylogenetic relationships among the strains to correlate genetic relatedness with metabolite production. Our results showed that GC×GC-TOFMS offered superior resolution but similar differentiation of VOC profiles compared to GC-MS. VOC spectra allowed reliable distinction of taxonomic units at the species level and below, however, these distinctions showed only a slight correlation with phylogenetic data. We identified pan-dermatophyte and species- or strain-specific VOC profiles, indicating their potential for rapid, non-invasive detection of dermatophyte infections, including epidemic strains. These patterns could enable future taxa-specific identification. Our study highlights the potential of VOCs as tools for dermatophyte taxonomy and diagnosis.

Keywords: Dermatophytes; Gas chromatography-mass spectrometry; Metabolite profiles; Volatile organic compounds.

Fig. 1

Overview of the features detected by gas chromatography-mass spectrometry (GC–MS) in all the dermatophyte and non-dermatophyte species, based on the presence/absence of a feature across the strains of the particular species

Fig. 2

Comparison of dendrograms based on sequence markers (a) and VOCs spectra (b) of dermatophytes. Maximum likelihood multilocus (ITS, tubb, and tef1-α) tree (a). The ex-type strains are designated with a superscripted T. Hierarchical clustering analysis on VOCs spectra analysed by gas chromatography-mass spectrometry (GC–MS) (b). Three biological replicates per each strain were studied

Fig. 3

Demonstration of separation of emerging dermatophyte populations (marked with a darker colour) based on VOCs production. It showcases the identification of epidemic strains of T. benhamiae var. luteum within other taxa in the T. benhamiae clade (a), and drug-resistant isolates of T. mentagrophytes var. indotineae and T. rubrum within strains of their respective species (b). Hierarchical clustering analysis of strains measured by gas chromatography-mass spectrometry (GC–MS). Three biological replicates (a–c) per each strain were studied

Fig. 4

Comparison of the two approaches used in the study by comparing principal component analysis of the data measured on strains of T. benhamiae var. luteum, T. mentagrophytes, and T. erinacei by gas chromatography-mass spectrometry (GC–MS) (a), and by multidimensional gas chromatography with time-of-flight mass spectrometry (GC×GC–TOFMS) before (b), and after the feature selection (c)

Fig. 5

Overview of the top 40 features detected from solid-phase microextraction (SPME) followed by multidimensional gas chromatography with time-of-flight mass spectrometry (GC×GC-TOFMS) analysis of the strains of T. benhamiae var. luteum, T. mentagrophytes, and T. erinacei