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      Validation of a New Web Application for Identification of Fungi by Use of Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry

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          ABSTRACT

          Matrix-assisted laser desorption ionization–time of flight (MALDI-TOF) mass spectrometry has emerged as a reliable technique to identify molds involved in human diseases, including dermatophytes, provided that exhaustive reference databases are available. This study assessed an online identification application based on original algorithms and an extensive in-house reference database comprising 11,851 spectra (938 fungal species and 246 fungal genera). Validation criteria were established using an initial panel of 422 molds, including dermatophytes, previously identified via DNA sequencing (126 species). The application was further assessed using a separate panel of 501 cultured clinical isolates (88 mold taxa including dermatophytes) derived from five hospital laboratories. A total of 438 (87.35%) isolates were correctly identified at the species level, while 26 (5.22%) were assigned to the correct genus but the wrong species and 37 (7.43%) were not identified, since the defined threshold of 20 was not reached. The use of the Bruker Daltonics database included in the MALDI Biotyper software resulted in a much higher rate of unidentified isolates (39.76 and 74.30% using the score thresholds 1.7 and 2.0, respectively). Moreover, the identification delay of the online application remained compatible with real-time online queries (0.15 s per spectrum), and the application was faster than identifications using the MALDI Biotyper software. This is the first study to assess an online identification system based on MALDI-TOF spectrum analysis. We have successfully applied this approach to identify molds, including dermatophytes, for which diversity is insufficiently represented in commercial databases. This free-access application is available to medical mycologists to improve fungal identification.

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          High-throughput identification of bacteria and yeast by matrix-assisted laser desorption ionization-time of flight mass spectrometry in conventional medical microbiology laboratories.

          Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is suitable for high-throughput and rapid diagnostics at low costs and can be considered an alternative for conventional biochemical and molecular identification systems in a conventional microbiological laboratory. First, we evaluated MALDI-TOF MS using 327 clinical isolates previously cultured from patient materials and identified by conventional techniques (Vitek-II, API, and biochemical tests). Discrepancies were analyzed by molecular analysis of the 16S genes. Of 327 isolates, 95.1% were identified correctly to genus level, and 85.6% were identified to species level by MALDI-TOF MS. Second, we performed a prospective validation study, including 980 clinical isolates of bacteria and yeasts. Overall performance of MALDI-TOF MS was significantly better than conventional biochemical systems for correct species identification (92.2% and 83.1%, respectively) and produced fewer incorrect genus identifications (0.1% and 1.6%, respectively). Correct species identification by MALDI-TOF MS was observed in 97.7% of Enterobacteriaceae, 92% of nonfermentative Gram-negative bacteria, 94.3% of staphylococci, 84.8% of streptococci, 84% of a miscellaneous group (mainly Haemophilus, Actinobacillus, Cardiobacterium, Eikenella, and Kingella [HACEK]), and 85.2% of yeasts. MALDI-TOF MS had significantly better performance than conventional methods for species identification of staphylococci and genus identification of bacteria belonging to HACEK group. Misidentifications by MALDI-TOF MS were clearly associated with an absence of sufficient spectra from suitable reference strains in the MALDI-TOF MS database. We conclude that MALDI-TOF MS can be implemented easily for routine identification of bacteria (except for pneumococci and viridans streptococci) and yeasts in a medical microbiological laboratory.
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            Mould Routine Identification in the Clinical Laboratory by Matrix-Assisted Laser Desorption Ionization Time-Of-Flight Mass Spectrometry

            Background MALDI-TOF MS recently emerged as a valuable identification tool for bacteria and yeasts and revolutionized the daily clinical laboratory routine. But it has not been established for routine mould identification. This study aimed to validate a standardized procedure for MALDI-TOF MS-based mould identification in clinical laboratory. Materials and Methods First, pre-extraction and extraction procedures were optimized. With this standardized procedure, a 143 mould strains reference spectra library was built. Then, the mould isolates cultured from sequential clinical samples were prospectively subjected to this MALDI-TOF MS based-identification assay. MALDI-TOF MS-based identification was considered correct if it was concordant with the phenotypic identification; otherwise, the gold standard was DNA sequence comparison-based identification. Results The optimized procedure comprised a culture on sabouraud-gentamicin-chloramphenicol agar followed by a chemical extraction of the fungal colonies with formic acid and acetonitril. The identification was done using a reference database built with references from at least four culture replicates. For five months, 197 clinical isolates were analyzed; 20 were excluded because they were not identified at the species level. MALDI-TOF MS-based approach correctly identified 87% (154/177) of the isolates analyzed in a routine clinical laboratory activity. It failed in 12% (21/177), whose species were not represented in the reference library. MALDI-TOF MS-based identification was correct in 154 out of the remaining 156 isolates. One Beauveria bassiana was not identified and one Rhizopus oryzae was misidentified as Mucor circinelloides. Conclusions This work's seminal finding is that a standardized procedure can also be used for MALDI-TOF MS-based identification of a wide array of clinically relevant mould species. It thus makes it possible to identify moulds in the routine clinical laboratory setting and opens new avenues for the development of an integrated MALDI-TOF MS-based solution for the identification of any clinically relevant microorganism.
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              Development of a clinically comprehensive database and a simple procedure for identification of molds from solid media by matrix-assisted laser desorption ionization-time of flight mass spectrometry.

              Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is a powerful tool for the rapid and highly accurate identification of clinical pathogens but has not been utilized extensively in clinical mycology due to challenges in developing an effective protein extraction method and the limited databases available. Here, we developed an alternate extraction procedure and constructed a highly stringent database comprising 294 individual isolates representing 76 genera and 152 species. To our knowledge, this is the most comprehensive clinically relevant mold database developed to date. When challenged with 421 blinded clinical isolates from our institution, by use of the BioTyper software, accurate species-level (score of ≥ 2.0) and genus-level (score of ≥ 1.7) identifications were obtained for 370 (88.9%) and 18 (4.3%) isolates, respectively. No isolates were misidentified. Of the 33 isolates (7.8%) for which there was no identification (score of <1.7), 25 were basidiomycetes not associated with clinical disease and 8 were Penicillium species that were not represented in the database. Our library clearly outperformed the manufacturer's database that was obtained with the instrument, which identified only 3 (0.7%) and 26 (6.2%) isolates at species and genus levels, respectively. Identification was not affected by different culture conditions. Implementation into our routine workflow has revolutionized our mycology laboratory efficiency, with improved accuracy and decreased time for mold identification, eliminating reliance on traditional phenotypic features.
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                Author and article information

                Journal
                Journal of Clinical Microbiology
                J. Clin. Microbiol.
                American Society for Microbiology
                0095-1137
                1098-660X
                August 23 2017
                September 2017
                September 2017
                June 21 2017
                : 55
                : 9
                : 2661-2670
                Article
                10.1128/JCM.00263-17
                5648703
                28637907
                407ab410-ffce-4102-8196-6941e5482272
                © 2017
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