Publication:
Optimizing filamentous fungi identification by MALDI-TOF MS: a comparative analysis of key factors

dc.contributor.coauthorOzmen-Capin, Busra Betul
dc.contributor.coauthorWhite, John
dc.contributor.coauthorSerra, Chiara
dc.contributor.coauthorAhmed, Sultan
dc.contributor.coauthorBotero-Kleiven, Silvia
dc.contributor.coauthorÖzenci, Volkan
dc.contributor.departmentSchool of Medicine
dc.contributor.kuauthorDoğan, Özlem
dc.contributor.schoolcollegeinstituteSCHOOL OF MEDICINE
dc.date.accessioned2025-12-31T08:23:05Z
dc.date.available2025-12-31
dc.date.issued2025
dc.description.abstractPurpose: The identification of filamentous fungi in clinical microbiology laboratories remains a challenging task. Although matrix-assisted laser desorption/ionization–time of flight mass spectrometry (MALDI-TOF MS) has revolutionized microbial diagnostics by enabling rapid and accurate species-level identification, its application to molds is still evolving. This study aims to evaluate the performance of two Bruker MALDI-TOF MS systems, Sirius One and Microflex 3.1, for the identification of filamentous fungi using different extraction protocols and database configurations. Method: A total of 68 filamentous fungal isolates, including clinically significant species, were analyzed. Fungal cultures were processed under standardized conditions using two protein extraction methods: a detailed in-tube extraction with ethanol, formic acid, and acetonitrile, and a direct on-plate extraction. Spectra were acquired using both Sirius One and Microflex 3.1 systems, and identifications were performed using manufacturer-provided databases and the MSI-2.0 database. Results: The Sirius One system outperformed Microflex 3.1, achieving a 92.6% correct identification rate with the MSI-2 database compared to 70.6% for Microflex (p < 0.01). When using manufacturer-provided databases, identification rates were lower: 51.5% for Sirius One and 41.2% for Microflex. Notably, the on-plate extraction method performed comparably to the in-tube method, achieving 94.1% accuracy with Sirius One and the MSI-2 database. Conclusion: The combination of the Sirius One system, MSI-2.0 database, and on-plate extraction method provides a highly effective and time-efficient workflow for the identification of filamentous fungi in routine clinical diagnostics, reaching 94.1% accuracy. This approach is recommended for implementation in clinical mycology laboratories, though further optimization of manufacturer-supplied databases remains necessary. © The Author(s) 2025.
dc.description.fulltextYes
dc.description.harvestedfromManual
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.indexedbyPubMed
dc.description.publisherscopeInternational
dc.description.readpublishN/A
dc.description.sponsoredbyTubitakEuN/A
dc.description.sponsorshipKarolinska Institute
dc.identifier.doi10.1007/s10096-025-05316-0
dc.identifier.eissn1435-4373
dc.identifier.embargoNo
dc.identifier.issn0934-9723
dc.identifier.pubmed41145750
dc.identifier.quartileQ2
dc.identifier.scopus2-s2.0-105019936988
dc.identifier.urihttps://doi.org/10.1007/s10096-025-05316-0
dc.identifier.urihttps://hdl.handle.net/20.500.14288/31694
dc.identifier.wos001603013400001
dc.keywordsBruker biotyper
dc.keywordsFilamentous fungi
dc.keywordsMALDI-TOF MS
dc.keywordsMSI-2 database
dc.keywordsMicroflex
dc.keywordsSirius one
dc.language.isoeng
dc.relation.affiliationKoç University
dc.relation.collectionKoç University Institutional Repository
dc.relation.ispartofEuropean Journal of Clinical Microbiology and Infectious Diseases
dc.relation.openaccessYes
dc.rightsCC BY-NC-ND (Attribution-NonCommercial-NoDerivs)
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectInfectious Diseases
dc.subjectMicrobiology
dc.titleOptimizing filamentous fungi identification by MALDI-TOF MS: a comparative analysis of key factors
dc.typeJournal Article
dspace.entity.typePublication
person.familyNameDoğan
person.givenNameÖzlem
relation.isOrgUnitOfPublicationd02929e1-2a70-44f0-ae17-7819f587bedd
relation.isOrgUnitOfPublication.latestForDiscoveryd02929e1-2a70-44f0-ae17-7819f587bedd
relation.isParentOrgUnitOfPublication17f2dc8e-6e54-4fa8-b5e0-d6415123a93e
relation.isParentOrgUnitOfPublication.latestForDiscovery17f2dc8e-6e54-4fa8-b5e0-d6415123a93e

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