Ultra-high-resolution mass spectrometry for identification of closely related dermatophytes with different clinical predilections

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Abstract

In the present study, an innovative top-down liquid chromatographytandem mass spectrometry (LC-MS/MS) method for the identification of clinically relevant fungi is tested using a model set of dermatophyte strains. The methodology characterizes intact proteins derived from Trichophyton species, which are used as parameters of differentiation. To test its resolving power compared to that of traditional Sanger sequencing and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF), 24 strains of closely related dermatophytes, Trichophyton rubrum, T. Violaceum, T. Tonsurans, T. Equinum, and T. Interdigitale, were subjected to this new approach. Using MS/MS and different deconvolution algorithms, we identified hundreds of individual proteins, with a subpopulation of these used as strain-or species-specific markers. Three species, i.e., T. Rubrum, T. Violaceum, and T. Interdigitale, were identified correctly down to the species level. Moreover, all isolates associated with these three species were identified correctly down to the strain level. In the T. Tonsurans-equinum complex, eight out of 12 strains showed nearly identical proteomes, indicating an unresolved taxonomic conflict already apparent from previous phylogenetic data. In this case, it was determined with high probability that only a single species can be present. Our study successfully demonstrates applicability of the mass spectrometric approach to identify clinically relevant filamentous fungi. Here, we present the first proof-of-principle study employing the mentioned technology to differentiate microbial pathogens. The ability to differentiate fungi at the strain level sets the stage to improve patient outcomes, such as early detection of strains that carry resistance to antifungals.

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Dukik, K., Freeke, J., Jamalian, A., Van Den Ende, B. G., Yip, P., Stephenson, J. L., … Stielow, J. B. (2018). Ultra-high-resolution mass spectrometry for identification of closely related dermatophytes with different clinical predilections. Journal of Clinical Microbiology, 56(7). https://doi.org/10.1128/JCM.00102-18

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