Comparison of MALDI-TOF MS instruments and databases for the identification of uncommon yeasts, <i>Aspergillus</i> spp. and rare filamentous fungi

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-ToF-MS) is key for fungal identification nowadays. We present here the largest comparison of MALDI-ToF-MS instruments and databases focusing on rare yeasts and molds identification, challenging the existing instruments and both commercial and academic databases. The strains were collected in Saint Louis Hospital (Paris) and identified using bar-code sequencing. We showed that commercial databases are efficient for the identification of the main fungal species tested, whereas the academic database outperforms them for the identification of cryptic species.

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Publication Details

Journal
Journal of Clinical Microbiology
Published
2025-05-15
DOI
https://doi.org/10.1128/jcm.01612-24
Citations
3
Primary Topic
Bacterial Identification and Susceptibility Testing
Type
article
Field-Weighted Citation Impact
3.96
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article

Comparison of MALDI-TOF MS instruments and databases for the identification of uncommon yeasts, Aspergillus spp. and rare filamentous fungi

Marc Lemaire, Renaud Piarroux, J. Bui, Anne‐Cécile Normand et al.
3 citations
Journal of Clinical Microbiology
Bacterial Identification and Susceptibility Testing
3.96
article

Comparison of MALDI-TOF MS instruments and databases for the identification of uncommon yeasts, Aspergillus spp. and rare filamentous fungi

Marc Lemaire, Renaud Piarroux, J. Bui, Anne‐Cécile Normand, Sarah Dellière, Théo Ghelfenstein-Ferreira, Alexandre Alanio, Élodie Da Silva, Véronique Charlier, Samia Hamane, Marion Dutkiewicz, Maéva Garros
article en
3 citations

Abstract

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-ToF-MS) is key for fungal identification nowadays. We present here the largest comparison of MALDI-ToF-MS instruments and databases focusing on rare yeasts and molds identification, challenging the existing instruments and both commercial and academic databases. The strains were collected in Saint Louis Hospital (Paris) and identified using bar-code sequencing. We showed that commercial databases are efficient for the identification of the main fungal species tested, whereas the academic database outperforms them for the identification of cryptic species.

Journal of Clinical MicrobiologyVol. 63(6)
Institut Pasteur (FR), Université Paris Cité (FR), Sorbonne Université (FR), Pitié-Salpêtrière Hospital (FR), Hôpital Saint-Louis (FR)
Openalex Percentile: Top 6%
Bacterial Identification and Susceptibility Testing
3.96
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Comparison of MALDI-TOF MS instruments and databases for the identification of uncommon yeasts, <i>Aspergillus</i> spp. and rare filamentous fungi — Marc Lemaire, Renaud Piarroux, et al. · Journal of Clinical Microbiology (2025) | TGRS Research Map | TGRS