Header

UZH-Logo

Maintenance Infos

Matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry using the Vitek MS system for rapid and accurate identification of dermatophytes on solid cultures


De Respinis, Sophie; Monnin, Valérie; Girard, Victoria; Welker, Martin; Arsac, Maud; Cellière, Béatrice; Durand, Géraldine; Bosshard, Philipp P; Farina, Claudio; Passera, Marco; Van Belkum, Alex; Petrini, Orlando; Tonolla, Mauro (2014). Matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry using the Vitek MS system for rapid and accurate identification of dermatophytes on solid cultures. Journal of Clinical Microbiology, 52(12):4286-4292.

Abstract

The objective of this research was to extend the Vitek MS fungal knowledge base version 2.0.0 to allow the robust identification of clinically relevant dermatophytes, using a variety of strains, incubation times, and growth conditions. First, we established a quick and reliable method for sample preparation to obtain a reliable and reproducible identification independently of the growth conditions. The Vitek MS V2.0.0 fungal knowledge base was then expanded using 134 well-characterized strains belonging to 17 species in the genera Epidermophyton, Microsporum, and Trichophyton. Cluster analysis based on mass spectrum similarity indicated good species discrimination independently of the culture conditions. We achieved a good separation of the subpopulations of the Trichophyton anamorph of Arthroderma benhamiae and of anthropophilic and zoophilic strains of Trichophyton interdigitale. Overall, the 1,130 mass spectra obtained for dermatophytes gave an estimated identification performance of 98.4%. The expanded fungal knowledge base was then validated using 131 clinical isolates of dermatophytes belonging to 13 taxa. For 8 taxa all strains were correctly identified, and for 3 the rate of successful identification was >90%; 75% (6/8) of the M. gypseum strains were correctly identified, whereas only 47% (18/38) of the African T. rubrum population (also called T. soudanense) were recognized accurately, with a large quantity of strains misidentified as T. violaceum, demonstrating the close relationship of these two taxa. The method of sample preparation was fast and efficient and the expanded Vitek MS fungal knowledge base reliable and robust, allowing reproducible dermatophyte identifications in the routine laboratory.

Abstract

The objective of this research was to extend the Vitek MS fungal knowledge base version 2.0.0 to allow the robust identification of clinically relevant dermatophytes, using a variety of strains, incubation times, and growth conditions. First, we established a quick and reliable method for sample preparation to obtain a reliable and reproducible identification independently of the growth conditions. The Vitek MS V2.0.0 fungal knowledge base was then expanded using 134 well-characterized strains belonging to 17 species in the genera Epidermophyton, Microsporum, and Trichophyton. Cluster analysis based on mass spectrum similarity indicated good species discrimination independently of the culture conditions. We achieved a good separation of the subpopulations of the Trichophyton anamorph of Arthroderma benhamiae and of anthropophilic and zoophilic strains of Trichophyton interdigitale. Overall, the 1,130 mass spectra obtained for dermatophytes gave an estimated identification performance of 98.4%. The expanded fungal knowledge base was then validated using 131 clinical isolates of dermatophytes belonging to 13 taxa. For 8 taxa all strains were correctly identified, and for 3 the rate of successful identification was >90%; 75% (6/8) of the M. gypseum strains were correctly identified, whereas only 47% (18/38) of the African T. rubrum population (also called T. soudanense) were recognized accurately, with a large quantity of strains misidentified as T. violaceum, demonstrating the close relationship of these two taxa. The method of sample preparation was fast and efficient and the expanded Vitek MS fungal knowledge base reliable and robust, allowing reproducible dermatophyte identifications in the routine laboratory.

Statistics

Citations

10 citations in Web of Science®
10 citations in Scopus®
Google Scholar™

Altmetrics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Dermatology Clinic
Dewey Decimal Classification:610 Medicine & health
Date:December 2014
Deposited On:12 Feb 2015 15:19
Last Modified:05 Apr 2016 19:06
Publisher:American Society for Microbiology
ISSN:0095-1137
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1128/JCM.02199-14
PubMed ID:25297329

Download

Full text not available from this repository.
View at publisher

TrendTerms

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.

Author Collaborations