Rodriguez-Temporal David, Adrados Daniel, Alastruey-Izquierdo Ana, Alkorta Miriam, Candela Ana, Canut Andrés, Castro Carmen, Cilla Carlos Gustavo, de Dios Caballero Juan, Ercibengoa María, Fernández Marina, Fradejas Isabel, Fraile Oscar, Goyanes María José, Gutiérrez Ainhoa, López José Israel, López Concha, López-Calleja Ana Isabel, López-Medrano Ramiro, Muñoz Patricia, Ortega Adriana María, Oviaño Marina, Peman Javier, Rodríguez-Mayo María, Ruiz Alba, Tristancho Alexander, Rodríguez-Sánchez Belén
Clinical Microbiology and Infectious Diseases Department, Instituto de Investigación Sanitaria Gregorio Marañón, Hospital General Universitario Gregorio Marañón, 28007 Madrid, Spain.
Microbiology Department, Complejo Hospitalario Insular-Las Palmas, 35016 Las Palmas de Gran Canaria, Spain.
J Fungi (Basel). 2025 May 5;11(5):356. doi: 10.3390/jof11050356.
The identification of filamentous fungi by matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) represents a challenge due to their complex taxonomy and the lack of comprehensive databases. The aim of this study was to evaluate the current status of available MALDI-TOF MS databases for the identification of dermatophytes, including commercial, in-house, and web-based databases. We collected 289 dermatophyte strains from different centers and analyzed them using four databases and a combination of them. The combination of commercial and in-house databases was shown to improve the identification rate and accuracy at the species level. For , the concordance among all databases was above 90.0%. For the group, correct identification at the species level ranged from 30.0 to 78.9%, depending on the database, and showed very low agreement among them. The addition of the novel species to our in-house database resulted in the successful identification of this species. On the other hand, and were the species most frequently misidentified by MALDI-TOF MS. Through deep spectra analysis of both species, up to 29 protein peaks were found to be suitable for their differentiation, demonstrating the potential of peak analysis in differentiating closely related species. In conclusion, improvements of the databases with new strains resulted in increased identification accuracy at the species level. This, combined with peak analysis, could improve the overall identification of dermatophytes by MALDI-TOF MS in clinical laboratories.
由于丝状真菌复杂的分类学以及缺乏全面的数据库，利用基质辅助激光解吸/电离飞行时间质谱（MALDI-TOF MS）鉴定丝状真菌是一项挑战。本研究的目的是评估用于鉴定皮肤癣菌的现有MALDI-TOF MS数据库的现状，包括商业数据库、内部数据库和基于网络的数据库。我们从不同中心收集了289株皮肤癣菌菌株，并使用四个数据库及其组合对它们进行分析。结果表明，商业数据库和内部数据库的组合提高了物种水平的鉴定率和准确性。总体而言，所有数据库之间的一致性高于90.0%。对于[具体某组]，根据数据库的不同，物种水平的正确鉴定率在30.0%至78.9%之间，且各数据库之间的一致性非常低。将新物种[具体物种名]添加到我们的内部数据库后，成功鉴定出了该物种。另一方面，[具体物种名1]和[具体物种名2]是MALDI-TOF MS最常误鉴定的物种。通过对这两个物种的深度光谱分析，发现多达29个蛋白峰适合用于区分它们，这表明峰分析在区分密切相关物种方面具有潜力。总之，用新菌株改进数据库可提高物种水平的鉴定准确性。这与峰分析相结合，可以提高临床实验室中通过MALDI-TOF MS对皮肤癣菌的整体鉴定能力。
