Detection and differentiation of causative organisms of onychomycosis in an ex vivo nail model by means of Raman spectroscopy.

BACKGROUND: Onychomycosis is worldwide the most prevalent infection of the nail. It is mainly caused by the dermatophytes Trichophyton rubrum and Trichophyton mentagrophytes and to a lesser extent Trichophyton tonsurans. The yeast Candida albicans and the mould Scopulariopsis brevicaulis can also cause onychomycosis. Management of these nail conditions may require appropriate treatment methods and therefore the identification of the causative species can be of importance. However, the determination of agents causing onychomycosis is still not optimal. OBJECTIVES: To detect and differentiate causative organisms of onychomycosis in an ex vivo nail model by means of Raman spectroscopy. The work focusses is on the discriminative power of Raman spectroscopy for detection of differences between T. rubrum, T. mentagrophytus and T. tonsurans on human nail and distinguishing these dermatophytic from the non-dermatophytic species S. brevicaulis and C. albicans. METHODS: Raman spectra (200/sample) were taken from 50-µm human nail slices infected with T. rubrum, T. mentagrophytus, T. tonsurans, S. brevicaulis or C. albicans using a 2500 High-Performance Raman Module and 785-nm diode laser. Processed spectra were analysed by sorting the correlation matrix and presented as dendrogram and heat map. Raman spectra from suspended dermatophytic microconidia were taken for mutual comparisons. RESULTS: Spectral differences between the dermatophytes T. rubrum, T. mentagrophytus and T. tonsurans (635-795, 840-894, 1018-1112, 1206-1372, 1566-1700/cm) and the non-dermatophytes S. brevicaulis and C. albicans (442-610, 692-758, 866-914, 1020-1100, 1138-1380,1492-1602/cm) growing on nail were confirmed by clustering correlation showing two main clusters. Dissimilarities between tested dermatophytes were also found with T. rubrum being most different. Raman spectra of the dermatophytic microconidia varied over the whole tested 400-1800/cm range. CONCLUSION: Important dermatophytic and non-dermatophytic agents of onychomycosis growing on ex vivo human nail can be distinguished specifically and non-invasively by Raman spectroscopy.

Proof of principle for successful characterization of methicillin-resistant coagulase-negative staphylococci isolated from skin by use of Raman spectroscopy and pulsed-field gel electrophoresis.

Coagulase-negative staphylococci (CNS) are among the most frequently isolated bacterial species in clinical microbiology, and most CNS-related infections are hospital acquired. Distinguishing between these frequently multiple-antibiotic-resistant isolates is important for both treatment and transmission control. In this study we used isolates of methicillin-resistant coagulase-negative staphylococci (MR-CNS) that were selected from a large surveillance study of the direct spread of MR-CNS. This strain collection was used to evaluate (i) Raman spectroscopy as a typing tool for MR-CNS isolates and (ii) diversity between colonies with identical and different morphologies. Reproducibility was high, with 215 of 216 (99.5%) of the replicate samples for 72 isolates ending up in the same cluster. The concordance with pulsed-field gel electrophoresis (PFGE)-based clusters was 94.4%. We also confirm that the skin of patients can be colonized with multiple MR-CNS types at the same time. Morphological differences between colonies from a single patient sample correlated with differences in Raman and PFGE types. Some morphologically indistinguishable colonies revealed different Raman and PFGE types. This indicates that multiple MR-CNS colonies should be examined to obtain a complete insight into the prevalence of different types and to be able to perform an accurate transmission analysis. Here we show that Raman spectroscopy is a reproducible typing system for MR-CNS isolates. It is a tool for screening variability within a collection of isolates. Because of the high throughput, it enables the analysis of multiple colonies per patient, which will enhance the quality of clinical and epidemiological studies.