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1 JCM Accepted Manuscript Posted Online 2 November 2016 J. Clin. Microbiol. doi: /jcm Copyright 2016, American Society for Microbiology. All Rights Reserved Identification of Molds by MALDI-TOF Mass Spectrometry Maurizio Sanguinetti, a Brunella Posteraro b Institute of Microbiology, Università Cattolica del Sacro Cuore, Rome, Italy a ; Institute of Public Health (Section of Hygiene), Università Cattolica del Sacro Cuore, Rome, Italy b #Address correspondence to Maurizio Sanguinetti, maurizio.sanguinetti@unicatt.it The authors declare no conflict of interest. Downloaded from on November 12, 2018 by guest 1

2 ABSTRACT Despite to lesser extent than the diagnostic bacteriology, MALDI-TOF MS has recently revolutionized the diagnostic mycology workflow. With regards to filamentous fungi (or molds), the precise recognition of pathogenic species is important for rapid diagnosis and appropriate treatment, especially in invasive diseases. This review summarizes the current experience with MALDI-TOF MS-based identification of common and uncommon mold species, belonging to Aspergillus, Fusarium, Mucorales, dimorphic fungi, and dermatophytes. This experience clearly shows that MALDI-TOF MS holds promise as a fast and accurate identification tool, particularly with common species or typical strains of filamentous fungi. Downloaded from on November 12, 2018 by guest 2

3 INTRODUCTION Invasive mold infections continue to occur among immunocompromised patients, particularly those receiving hematopoietic stem cell or solid organ transplantation (1), and are associated with increased healthcare costs (2). Beyond Aspergillus species that remain a major cause of invasive disease, other molds (or filamentous fungi) such as the ascomycetes Fusarium and Scedosporium species, and the mucoromycotina (Rhizopus, Mucor, and Lichtheimia corymbifera) species have emerged as causes of life-threatening infections (3). The species level identification of invasive molds is important because it is widely accepted that rapid diagnosis of infection coupled with the timely onset of appropriate antifungal therapy are key determinants of disease outcome (1). In addition, other clinically relevant filamentous fungi as dermatophytes deserve consideration for emerging diagnostic technologies (4) because phenotypic identification of these fungi is particularly challenging. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has recently revolutionized the diagnostic mycology workflow (5, 6) and, albeit to lesser extent than the diagnostic bacteriology, is gradually replacing conventional identification methods. Four different MALDI-TOF MS bench-top platforms are now commercialized for the routine identification of fungi in clinical microbiology laboratories. Together with the Andromas (Andromas SAS, Paris, France) and the Axima@Saramis (Shimadzu/AnagnosTec, Duisburg, Germany), the Bruker Biotyper (Bruker Daltonics, Bremen, Germany) and Vitek MS (biomérieux, Marcy l Étoile, France) systems are currently employed in Europe (5, 6), whereas only the last two systems are approved by the US Food and Drug Administration for clinical diagnostic use (albeit limited to bacteria and yeasts). In particular, the Bruker Daltonics instrument provides its own solution (i.e., MALDI Biotyper) which is comprised of software and database, whereas the Vitek MS system integrates the SARAMIS (Spectral Archiving and Microbial Identification System) database (i.e., an open database made by AnagnosTec) with its own closed database (7). The Biotyper software 3

4 generates (log)score values ranging from 0 to 3, with scores of 2 and 1.7 recommended for species-level or genus-level identifications, respectively, whereas a score (confidence) value of 60% is recommended for species-level identification using the Vitek MS software. Despite differing with regards to sample preparation, spectra preprocessing, and in silico identification algorithms, all these systems appear to be reliable tools for mold identification (8). KEY ISSUES FOR ROUTINE MALDI-TOF MS ANALYSIS OF MOLDS: SAMPLE PREPARATION, REFERENCE DATABASE, AND INTERPRETIVE CUTOFFS Unlike the yeasts, MALDI-TOF MS based identification of molds has been limited over the last years, mainly due to the requirement of extended sample preparation to achieve good-quality mass spectra. To this end, in the absence of comparative studies on molds, it is thought that better identification scores are obtainable from extracted protein suspensions rather than from the direct colony deposition. In particular, direct identification of molds by means of a basic sample preparation, such as an intact cell (IC; also termed whole cell ) mass spectrometry (ICMS) method, may be hampered by the presence of more robust cell wall (usually based on glucans and chitin) in fungi, contrary to bacteria. Therefore, studies using an IC approach, in which a single colony is smeared and covered by an acidic organic matrix solution directly onto a MALDI target plate, are outnumbered by studies using a cell lysis (CL) approach, in which an ethanol-formic acid procedure, starting from either agar or broth culture conditions, allows complete protein extraction (6). Of these approaches, IC (which can include a short on-target extraction with formic acid) is recommended for use with the Andromas and SARAMIS systems, whereas CL (which includes an extraction step with acetonitrile, thereby referred to as complete extraction ) is recommended for use with the Bruker Biotyper and Vitek MS systems. It should be noted that the sample preparation method advocated by biomérieux for molds has changed over the past five years, moving from an IC approach toward a CL approach. Otherwise, to minimize the effect of growth conditions on the production of uniform mycelium by fungi, Bruker Daltonics launched, in 2012, an additional 4

5 spectral library, the Filamentous Fungi Library 1.0, that was constructed using 24(48) hour-old liquid cultures for complete protein extraction. This library is separate from the general (Bruker Biotyper) library and represents the first commercial database of Bruker Daltonics for the identification of molds grown in liquid media. Interestingly, among the studies that since 2011 reported the MALDI Biotyper use for clinical laboratory diagnostics (reviewed in reference 8), only one study utilized liquid cultivation coupled with ethanol-formic acid extraction for sample preparation (9), whereas only another study (10) simply pretreated the sample by mixing fungal material (mycelium and/or conidia) with distilled water. This situation is consistent with the attempts done by several research groups, including ours, to simplify pre-analytical processes, in order to avoid the clinical (i.e., delayed turnaround time) and laboratory (i.e., prolonged working time) consequences with using liquid mold cultures. It is clear that the risk of aerosols and contamination is greater with extensive handling of molds grown on agar than in broth. However, irrespective of which method is adopted in the routine setting, the use of a biosafety cabinet during sample processing can help to prevent potential infections for the personnel working near a mycology laboratory. Overall, across the aforementioned studies, the performance of MALDI-TOF MS in mold identification was satisfactory, with rates of correct identification ranging from 72.0% (only one study) to 98.8% (reviewed in reference 8). Also, across the studies aimed to identify Aspergillus species using the Andromas (one study) and Vitek MS (two studies) MALDI systems databases (reviewed in reference 8), correct identification rates of 98.4% and 81.8 to 100% were obtained, respectively, using a fast formic acid extraction (the Andromas study) and direct deposition or complete extraction (the Vitek MS studies). More recently, using the Bruker Biotyper software in conjunction with Filamentous Fungi Library 1.0, but without liquid culture-based sample preparation, a confident MALDI-TOF MS identification (cutoff value of >1.7) was shown for 91.6% (44/48) of mold isolates tested by Riat et al. (11). A similar study was later conducted by 5

6 Sleiman et al. who used a mechanical lysis followed by complete extraction of molds grown on solid media (12), and an Australian database for the identification of 28 Aspergillus, Scedosporium, and Fusarium species (13). This in-house database, combined with the Bruker Filamentous Fungi Library 1.0, outperforms the Bruker library alone in terms of correct species identification rates (Aspergillus, 93% versus 69%; Fusarium, 84% versus 42%; and Scedosporium, 94% versus 18%, respectively). As stated previously, reference databases and the database query methods (i.e., comparing and subsequent scoring the similarity of an unknown spectrum to each database reference spectrum) may directly affect the performance of MALDI-TOF MS fungal identification (8). While the reference database provided with each commercial MALDI-TOF MS platform may not be sufficient for routine analyses (see below, for specific examples), some authors noticed that increasing the number of mass spectra obtained from distinct subcultures of strains included in the reference spectrum library (i.e., the number of reference entries) would improve the accuracy of MALDI TOF MS-based mold identification. The most clinically comprehensive mold databases developed recently by Lau et al. (12), Gautier et al. (14), and Becker et al. (15) contained, respectively, 152, 347, and 472 fungal species. Notably, the second, in the order, of these in-house databases was constructed with four spectra for 708 isolates each, to encompass 2,832 reference spectra in total (14). The Lau et al. s database, known as the NIH (National Institutes of Health, Bethesda, MD) mold database, yielded species level identification for 88.9% (370/421) of clinical isolates tested, whereas the Bruker Biotyper library alone (version _ ) identified only 3 of 421 isolates (12). The Gautier et al. s database allowed species level identification for 98.8% (1,094/1,107) of clinical isolates corresponding to 107 distinct species (14). Finally, the Becker et al. s database enabled the identification of 95.4% (372/390) of clinical isolates at the species level, whereas challenging the isolates spectra against the Bruker Biotyper library resulted in a specieslevel identification rate of <65% (15). However, several isolates were still misidentified or not 6

7 identified, essentially because they belonged to species that were insufficiently or not represented in the databases (12, 14, 15). Also, identification exclusively at the genus level was achieved for 18 (4.3%) and 11 (0.9%) of isolates, respectively, in two studies (12, 14). In the meantime, a homemade library for MALDI-TOF MS identification of dermatophytes was used in conjunction with the Bruker Biotyper library (version 3.0, which contained 3,995 unique reference spectra) to allow 93.0% and 59.6% of 171 clinical isolates to be identified at the genus and species levels, respectively (16); in another study, using the SARAMIS system, SuperSpectra were created for the MALDI-TOF MS identification of dermatophytes, which resulted in 95.8% of 141 clinical isolates correctly identified at the species level (17). To our knowledge, except for the NIH database, none of these in-house databases is so far publicly available, whereas the aforementioned library by Sleiman et al. is portable across diagnostic laboratories within Australia. The species coverage of MALDI reference database may represent the Achilles heel of each MALDI-TOF MS system available nowadays. Based on a procedure previously proposed by Cassagne et al. (18) but only using in-house databases for molds (in combination with the Bruker Biotyper library), studies have shown that MALDI-TOF MS could be reliable to identify any species of clinically relevant mold, including the cryptic Aspergillus species (14, 15, 19). However, these studies applied a lower species cutoff (mostly 1.7 [value accepted for genus assignment]) to increase identification rates. Similarly, using the Bruker Filamentous Fungi Library 1.0, identification rates were significantly increased by reducing the species cutoff from 2.0 (value accepted for species assignment) to 1.7, but, unfortunately, this occurred with species from the genera Penicillium, Fusarium, and Aspergillus which were those covered by the highest number of reference entries (9). This suggests that low spectral quality rather than a low database coverage could potentially explain for low scores (<2.0), although further studies are necessary to clarify these issues. In a very large evaluation study, 319 mold isolates from 43 different genera, recovered from different clinical specimens, were analyzed using an updated VITEK MS database, the VITEK 7

8 MS version 3.0 library, which contains unique species from 31 different genera of filamentous fungi (20). The MALDI-TOF MS system was able to correctly identify 66.8% (213/319) of isolates and 76.8% (245/319) of isolates after additional SARAMIS analysis. In particular, 98.9% (93/94) of isolates of two common Aspergillus species (A. fumigatus and A. flavus) were correctly identified; in contrast, only 65% (17/26) of isolates of Fusarium species were identified. Of 319 isolates tested, 71 (20.3%) remained unidentified; of these, 69 were absent from the database. Only 3 (0.9%) isolates, including 2 Aspergillus amoenus isolates and 1 Aspergillus calidoustus isolate were misidentified by MALDI-TOF MS (20). By a head-to-head comparison of Bruker Biotyper and VITEK MS carried out on a large collection of microorganisms, including filamentous fungi, at a public health reference laboratory in Québec (Canada), it was found that only 17 of 71 isolates tested were referenced in both systems databases, with 43 being present in the Bruker Biotyper and 20 in the Vitek MS (21). Thus, when present in their respective database, 76.7% (33/43) and 50.0% (10/20) of isolates could be correctly identified (to both species and genus levels) with the Bruker Biotyper and Vitek MS, respectively; only one misidentification was obtained (1 Fusarium proliferatum misidentified as Fusarium oxysporum) with the Vitek MS system, whereas there was no misidentification with the Bruker Biotyper system. When absent from their respective database, 12 misidentifications (mainly to genus level) were obtained with the Vitek MS system, as opposed to none with Bruker Biotyper system (21). EXAMPLES OF MOLD IDENTIFICATION BY MALDI-TOF MS Overall, current experience with MALDI-TOF MS identification suggests its usefulness in identifying a variety of human fungal pathogens, examples of which are reviewed below. These examples clearly show the recent efforts done by clinical laboratory scientists to enhance the MALDI-TOF MS identification capacity for clinical diagnostic purposes. Table 1 summarizes the main findings of the studies included in this section, which specifically address key points such as accurate identification of cryptic or closely-related species, identification of nonsporulating or 8

9 poorly sporulating organisms (e.g., dermatophytes), and rapid identification of clinically significant organisms such as dimorphs or emerging fungi. Remarkably, all the studies used the ethanol-formic acid extraction method before the MALDI-TOF MS analysis of their mold samples. i) Aspergillus species. Identification of Aspergillus species, particularly uncommon, cryptic, or morphologically undistinguishable species, by MALDI-TOF MS may be a valid alternative to DNA sequence-based identification (22). The last is time-expensive because it involves the analysis of β- tubulin (bena, tub-2) and calmodulin (cam) as a secondary genetic marker (the first being the internal transcribed spacer [ITS] region). However, only 6 and 3 of A. flavus strains (8 clinical isolates and 1 reference strain) analyzed by Tam et al. were correctly identified using the SARAMIS (Vitek MS RUO system) and Vitek MS (Vitek MS IVD system) databases, respectively; in contrast, none of the strains of Aspergillus nomius (2 clinical isolates and 1 reference strain) and Aspergillus tamarii (1 clinical isolate and 1 reference strain) was correctly identified by MALDI- TOF MS (23). Later, using the Bruker Biotyper database (OC version 3.1, updated in January 2016) amended with an in-house fungal database to expand the number of identifiable Aspergillus species, Masih et al. reported successful MALDI-TOF MS identification results (score value of 2.0) for 97.7% of 45 clinically significant Aspergillus isolates (24). The isolates belonged to 23 rare Aspergillus species, of which only 8 present in the current Bruker Biotyper database, that were enclosed in 12 sections (mainly Circumdati, Nidulantes, Flavi, Terrei, Versicolores, Aspergillus, and Nigri). Interestingly, two cryptic Aspergillus species, A. pallidofulvus (section Circumdati) and A. egyptiacus (section Usti), were isolated for first time from clinical specimens. Also, whereas 1 of 3 A. pallidofulvus isolates exhibited reduced susceptibility to amphotericin B and azoles, it was found that 38% of the rare Aspergillus isolates was resistant to at least one antifungal agent tested (24). ii) Fusarium species. Due to the presence of many cryptic (or phylogenetically closely related) species or some atypical isolates (i.e., lacking specific morphological traits in culture), conventional 9

10 identification of clinical isolates from Fusarium species complexes is particularly difficult. Triest et al. developed a user-friendly identification approach relying upon an in-house database, which was constructed with the spectra from 289 validated strains belonging to 40 Fusarium species (25). For 19 species represented by more than one strain, it was found that, using the MALDI Biotyper 3.0 software and a score value of 2.0 as the cutoff for identification, 82.8% of MALDI-TOF MS-based identifications were correct at the species level, 3% were correct at the species complex level, and the remaining 14.2% were not reliable. As expected, lowering the cutoff value (from 2.0 to 1.4) resulted in an overall rate of 91.0% correct species-level identifications and 5.6% correct species complex-level identifications. Interestingly, the success rate of correct identifications increased to even 97.0% when some Fusarium species complexes were taken as a whole; thus, MALDI-TOF MS identification would have failed with only 4 Fusarium (1 F. incarnatum, 1 F. equiseti, 1 F. sporotrichioides, and 1 F. sacchari) strains in that study (25). In support of this, the results of antifungal susceptibility testing performed on the study s isolates indicated that discriminating between Fusarium species complexes may be unnecessary between members of the same species complex (25). iii) Rhizopus/Lichtheimia species. Previous reports on the MALDI-TOF MS-based identification of Mucorales have focused only on the genus Lichtheimia (26), which is the second (after Rhizopus) most common causative agent of mucormycosis in Europe. Thus, studies related to Rhizopus species remained neglected so far, despite the fact that the identification of Rhizopus microsporus and Rhizopus arrhizus (previously known as Rhizopus oryzae), of which are known the antifungal drug susceptibility profiles, may be important for the treatment of mucormycosis. Dolatabadi et al. recently utilized MALDI-TOF MS to identify R. arrhizus, with its two varieties, arrhizus and delemar, and R. microsporus (27). MALDI-TOF MS identifications were compared with those derived by multilocus sequence typing (MLST; using ITS, ACT, and TEF gene markers). Using the MALDI Biotyper 3.0 software, a main spectrum (MSP) library was constructed with 38 Rhizopus 10

11 strains (25 R. arrhizus and 13 R. microsporus), that was subsequently challenged with the set of strains to confirm correct identity of MSPs at the species level. Thus, a hierarchical cluster analysis was performed using the 38 MSPs of the in-house Rhizopus library and the MSPs selected from the Bruker Filamentous Fungi Library 1.0 (16 MSPs for Rhizopus, 6 MSPs for Mucor, 2 MSPs for Rhizomucor, and 11 MSPs for Lichtheimia). The resultant dendrogram showed a clustering similar to the MLST phylogeny; in addition, the two varieties of R. arrhizus could be separated into the dendrogram, suggesting that MALDI-TOF MS may contribute to clarify the taxonomy of these filamentous fungi (27). iv) Penicillium marneffei. Because of the overall inexperience in identifying dimorphic fungi, diagnosis of penicilliosis, mainly caused by P. marneffei, can be challenging for many clinical laboratories. Anyhow, demonstration of the mycelial-to-yeast conversion, that is necessary for definitive identification of the fungus, takes approximately two weeks, thereby delaying diagnosis and treatment. To our knowledge, a specific study focusing on the use of MALDI-TOF MS for identification of P. marneffei appeared in the literature only very recently (28). In that study, spectra from mold and yeast cultures of 60 (59 clinical and 1 reference) strains of P. marneffei were analyzed with MALDI Biotyper 3.0 software against the Bruker database (BDAL version and Filamentous Fungi Library 1.0), with or without inclusion of additional spectra from P. marneffei strains selected from the set of test strains. None of the 60 strains, either grown in mold or yeast phase, could be correctly identified (using a score of 2.0 as cutoff) with the original Bruker database (P. marneffei was not present in either Bruker general library or Bruker Filamentous Fungi Library 1.0). As expected, using the expanded database, that included spectra from 21 (20 clinical and 1 reference) strains grown in mold and/or yeast phase, all the remaining 39 strains grown in mold, yeast, or both phases were correctly identified at the species level with score >2.0 (28). These findings agree with those of a previous study by Chen et al., that evaluated the performance of MALDI Bruker Biotyper system on the identification of 50 mold clinical isolates, including 28 11

12 genetically well-characterized P. marneffei (29). As none of 28 isolates were identified as P. marneffei by MALDI Biotyper system, the authors included 4 (NTUH-1124, NTUH-3370, NTUH- 7204, and NTUH-9736) of 28 P. marneffei isolates, that were randomly selected from each of four clusters of a principal component analysis dendrogram generated with MALDI Biotyper mass spectra of the 28 isolates. Thus, the best rate (82.1%) of accurate identification as P. marneffei (score value of 2.0) was found using newly created database by MALDI Biotyper system for the NTUH-3370 isolate (29). For 22 non-p. marneffei isolates of the study (12 Paecilomyces species, 6 Fusarium solani, 3 Rhizopus species, and 1 Pseudoallescheria boydii), the score values were of <1.7 (indicating no identification) for all, except for 1 F. solani, isolates, and none of these isolates could be correctly identified with the lowered cutoff value of 1.4, as proposed previously (25). v) Paecilomyces species. Paecilomyces species have become important human pathogens, with P. variotii and P. lilacinus being primarily implicated in invasive diseases. Recently, it was argued that P. variotii represents a complex of species, comprising P. variotii sensu stricto and other Paecilomyces species such as P. formosus, P. divaricatus, P. brunneolus, and P. dactylethromorphus. As with other molds mentioned above, similarities among members of the P. variotii species complex as well as to some Rasamsonia and Hamigera species may complicate the morphological identification of these fungi. In a study, Barker et al. reported that, despite observing unique MALDI-TOF mass spectrum profiles for Paecilomyces, Purpureocillium, Rasamsonia, and Hamigera species, none of the 77 clinical isolates identified morphologically as P. variotii, P. lilacinus (now designed as Purpureocillium lilacinus), and Paecilomyces spp. could be identified using the original Bruker Biotyper database (version 3.0) alone (30). Then, a 92.2% (71/77) agreement was found between molecular (i.e., multilocus DNA sequencing of ITS1 and ITS2, D1/D2 regions, and part of the β-tubulin gene) and MALDI-TOF MS methods only when the Bruker Biotyper database was supplemented with eight type strains. These included additional organisms known to morphologically resemble P. variotii but not present in the Biotyper spectral 12

13 library. Five isolates (1 P. formosus, 2 P. dactylethromorphus, 1 Paecilomyces sp., and 1 Hamigera sp.) could not be identified by MALDI-TOF MS, suggesting that identification of P. variotii-like organisms might be only confined to DNA sequence-based methods (30). vi) Dermatophytes. As reviewed by Cassagne et al. (8), studies published until 2014 have shown overall rates (95.8% to 99.3%) of successful MALDI-TOF MS-based identification for dermatophyte (i.e., Epidermophyton, Microsporum, and Trichophyton) species (31; also see 8 and references therein). As expected, all these studies established their own reference dermatophyte database. In one study, De Respinis et al., using a combination of organism inactivation and protein extraction, developed a sample preparation protocol that allowed to obtain rapid, reliable, and reproducible mass spectra from fungal material grown on solid media (i.e., material derived from primary cultures of skin, nails, or hairs) (31). Then, expansion of the Vitek MS V2.0.0 fungal knowledge base was made using 134 well-characterized strains from 17 dermatophyte species, for an overall 1,130 dermatophyte mass spectra that gave an estimated identification performance of 98.4%. Finally, the expanded database was challenged with 131 clinical isolates of dermatophytes belonging to 13 taxa. For 10 taxa, the rate of correct identifications was 100%, including Trichophyton erinacei (1 isolate) and Trichophyton terrestre (1 isolate); in contrast, only 15 of 19 (78.9%) African Trichophyton rubrum (also called Trichophyton soudanense) isolates were correctly identified (this rate was clearly lower than that of T. rubrum sensu stricto isolates [100%]), with several isolates being misidentified as Trichophyton violaceum, demonstrating the close relationship of these two taxa (31). Later, in another study, the Bruker Biotyper database was supplemented with additional mass spectra from 24 (13 reference [U.K. NEQAS] and 11 clinical) morphologically and/or molecularly (i.e., by ITS DNA sequencing) characterized strains of 13 different species (32). Together with dermatophyte species already existing in the original database (i.e., Epidermophyton floccosum, Microsporum canis, Microsporum gypseum, T. rubrum, Trichophyton interdigitale, Trichophyton mentagrophytes, and T. tonsurans), the newly added 13

14 species included three Microsporum species (M. fulvum, M. persicolor, and M. audouinii) and three Trichophyton species (T. erinacei, T. violaceum, and T. soudanense). It was noted that only the mass spectral profiles of T. interdigitale and T. mentagrophytes were almost indistinguishable from each other. To validate the implemented database, 64 new clinical dermatophyte isolates were tested and their identification results were compared with those obtained before database implementation (i.e., here reported within parentheses). All 64 isolates were correctly identified (score value, >2.0 for 47 isolates; score value, for the remaining 17 isolates) with the implemented database, including the M. audouinii isolate (misidentified as M. canis), 2 T. violaceum isolates (not reliably identified; score value <1.7), 1 T. tonsurans isolate (misidentified as T. rubrum), 3 T. rubrum isolates (two misidentified as T. tonsurans and one not reliably identified), 2 T. soudanense (one misidentified as T. rubrum and one not reliably identified), and 1 M. persicolor (not reliably identified). As expected, with regards to T. mentagrophytes/t. interdigitale isolates (19 and 2, respectively; not distinguished by their ITS sequence), all but 2 isolates were misidentified as T. tonsurans; 1 of the 2 isolates was misidentified as M. gypseum and the other 1 had not reliable identification (32). A more recent evaluation of the Bruker Biotyper system s performance showed that MALDI-TOF MS provided correct genus-level and species-level identifications in 96.8% (122/126) and 87.9% (113/126) of dermatophyte isolates, respectively, using a supplemented database (the MALDI Biotyper Support Library, i.e., created by adding spectra from 10 reference dermatophyte strains) and with lowered score values (33). Expectedly, correct genus-level and species-level identifications of 51.6% and 13.5% were found when MALDI-TOF MS analyses were done by using the original database (MALDI Biotyper Library, MBL version ) and manufacturer-recommended score values (33). MOLD IDENTIFICATION BY MALDI-TOF MS: IS IT REALLY A HISTORY OF SUCCESS? 14

15 Over the last 5 years, accumulated experience clearly shows that MALDI-TOF MS holds promise as an accurate mold identification tool, particularly with common filamentous fungal pathogens. Conventional phenotypic methods to identify filamentous fungi are relatively inexpensive but have a turnaround time of several days because of the time taken for fungal growth, which in certain groups of fungi (e.g., dermatophytes) can be very long. As a result, initial antifungal therapy of infection is empirical and appropriate therapy may be delayed if antifungal resistance is not suspected. Turnaround time has been reduced by the introduction of MALDI-TOF MS instruments in the clinical laboratory routine, although these continue to rely on fungal cultures. In this context, the MALDI-TOF MS technology is also being exploited to analyze patient specimens directly, completely bypassing the need for fungal growth (5). In the meantime, rapid and accurate identification of fungi can be achieved directly from positive blood cultures. In a pilot study (34), using an in-house protein extraction protocol, the diagnosis of fungemia due to F. solani (2 cases) and Fusarium verticillioides (1 case) was made by using MALDI-TOF Vitek MS system in a research-use-only (RUO) mode (i.e., by SARAMIS). All fungemias were breakthrough infection cases related to immunocompromised or critically ill patients. Unfortunately, none of the patients with F. solani fungemia could benefit from MALDI-TOF MS-guided targeted antifungal therapy, contrary to the other fungemia cases, including those due to F. verticillioides and yeast-like fungi, described in that study (34). A major limitation of MALDI-TOF MS for mold identification is still the breadth of commercially available databases. This limitation has hampered widespread implementation of MALDI-TOF MS in the clinical laboratory for the identification of filamentous fungi. Not surprisingly, as shown by all the studies here summarized, high MALDI-TOF MS-based identification rates are obtained only when using in-house reference spectra databases. Therefore, a common highlight of these studies is the need for expanded databases, which was apparent, though not exclusively, for rare, emerging, or endemic mycoses agents. In this sense, one could argue that the value of MALDI for molds is only 15

16 for the more difficult organisms, although MALDI databases for these organisms may be limited. For this reason, it would be necessary to continuously update the mold reference database, by enriching it with fungal strains/species derived from routine specimen cultures that are not (or not well) represented in the database. It was also apparent that inconclusive MALDI-TOF MS identification results are often due to differences between the procedures for the reference database construction and those for the test s isolate mass spectrum obtainment. The construction of expanded MALDI-TOF MS databases is labor-consuming, requires mycological skills, and is hindered by the fact that the in vitro device (IVD) versions of the commercialized MALDI-TOF MS systems do not enable the implementation of databases. Otherwise, in those environments not subject to regulatory body (i.e., FDA) restrictions, the practice of expansion/improvement of a RUO database (i.e., Biotyper or SARAMIS) should be confined to reference laboratories. Thus, while this practice will be a huge benefit for those laboratories with large collections of clinical isolates, it should be mandatory that an identification strategy is expanded and validated with new isolates/species and analyzed through other databases. In this context, efforts are needed to develop on-line available reference spectra databases that could be interrogated similarly to sequence databases like NCBI GenBank. Molecular methods (e.g., DNA sequencing) are currently the gold standard for the identification of fungi at the species level. Although these methods can provide accurate results, they are expensive and require specialized equipment or expertise, and are not commonly available in clinical laboratories. In the present review, findings from the 10 studies (23 25, and 27 33) shown in Table 1 indicate that, before MALDI-TOF MS testing, only one study identified the isolates via conventional phenotypical analyses (33), whereas almost all the remaining studies also sequenced all their isolates, and in two studies only molecular biology analyses were undertaken on the isolates (27, 28). This supports the idea that the overall high accuracy of MALDI-TOF MS-based mold identification shown in these studies might not be overestimated. It is worth noting that A. flavus, 16

17 the second leading cause of human aspergillosis, is not separable from Aspergillus oryzae by means of molecular biology techniques, whereas the closely related species T. mentagrophytes and T. interdigitale are not separable by means of ITS sequence analysis. By contrast, MALDI-TOF MS seems to be more powerful in resolving discrimination between these species (10, 32), as well as to distinguish clinically relevant from irrelevant species of Lichtheimia (26). However, as the MALDI- TOF MS-based identification should be consistent with the aspect of the organism in culture, a relatively mature growth must be achieved before the identification is certain. Thus, for those organisms that do not grow rapidly, the role of MALDI-TOF MS in time savings for mold identification could be questioned. In conclusion, we are sure that MALDI-TOF MS has contributed to improve the laboratory diagnosis of filamentous fungal infections in terms of rapidity and accuracy of identification in the last few years. As fast and precise recognition of a fungal pathogen can result in significant benefit for optimal patient treatment, MALDI-TOF MS-based identification should be integrated in antifungal stewardship strategies. Future studies are required to estimate the real impact of MALDI- TOF MS identification results on the clinical and therapeutic management of mold diseases. In the meantime, further improvements of the reference fungal databases are needed to explore in real time the evolving diversity of mold species recovered from clinical specimens. It is also desired that additional applications for MALDI-TOF MS-based fungal disease diagnosis (i.e., antifungal susceptibility/resistance detection and fungal strain typing) are potentiated in the near future. In summary, progresses in these areas will aid to enhance and diversify the clinical diagnostic usefulness of MALDI-TOF MS. 17

18 REFERENCES 1. Brown GD, Denning DW, Gow NA, Levitz SM, Netea MG, White TC Hidden killers: human fungal infections. Sci Transl Med 4:165rv Ananda-Rajah MR, Cheng A, Morrissey CO, Spelman T, Dooley M, Neville AM, Slavin M Attributable hospital cost and antifungal treatment of invasive fungal diseases in high-risk hematology patients: an economic modeling approach. Antimicrob Agents Chemother 55: Miceli MH, Lee SA Emerging moulds: epidemiological trends and antifungal resistance. Mycoses 54:e Buchan BW, Ledeboer NA Emerging technologies for the clinical microbiology laboratory. Clin Microbiol Rev 27: Clark AE, Kaleta EJ, Arora A, Wolk DM Matrix-assisted laser desorption ionization-time of flight mass spectrometry: a fundamental shift in the routine practice of clinical microbiology. Clin Microbiol Rev 26: Posteraro B, De Carolis E, Vella A, Sanguinetti M MALDI-TOF mass spectrometry in the clinical mycology laboratory: identification of fungi and beyond. Expert Rev Proteomics 10: Emonet S, Shah HN, Cherkaoui A, Schrenzel J Application and use of various mass spectrometry methods in clinical microbiology. Clin Microbiol Infect 16: Cassagne C, Normand AC, L'Ollivier C, Ranque S, Piarroux R Performance of MALDI-TOF MS platforms for fungal identification. Mycoses 59: Schulthess B, Ledermann R, Mouttet F, Zbinden A, Bloemberg GV, Böttger EC, Hombach M Use of the Bruker MALDI Biotyper for identification of molds in the clinical mycology laboratory. J Clin Microbiol 52:

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21 gene sequencing, metabolic fingerprinting, and matrix-assisted laser desorption ionizationtime of flight mass spectrometry. J Clin Microbiol 52: Masih A, Singh PK, Kathuria S, Agarwal K, Meis JF, Chowdhary A Clinically significant rare Aspergillus species in a referral chest hospital, Delhi, India: molecular and MALDI TOF identification and their antifungal susceptibility profiles. J Clin Microbiol 54: Triest D, Stubbe D, De Cremer K, Piérard D, Normand AC, Piarroux R, Detandt M, Hendrickx M Use of matrix-assisted laser desorption ionization-time of flight mass spectrometry for identification of molds of the Fusarium genus. J Clin Microbiol 53: Schrödl W, Heydel T, Schwartze VU, Hoffmann K, Grosse-Herrenthey A, Walther G, Alastruey-Izquierdo A, Rodriguez-Tudela JL, Olias P, Jacobsen ID, de Hoog GS, Voigt K Direct analysis and identification of pathogenic Lichtheimia species by matrixassisted laser desorption ionization-time of flight analyzer-mediated mass spectrometry. J Clin Microbiol 50: Dolatabadi S, Kolecka A, Versteeg M, de Hoog SG, Boekhout T Differentiation of clinically relevant Mucorales Rhizopus microsporus and R. arrhizus by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). J Med Microbiol 64: Lau SK, Lam CS, Ngan AH, Chow WN, Wu AK, Tsang DN, Tse CW, Que TL, Tang BS, Woo PC Matrix-assisted laser desorption ionization time-of-flight mass spectrometry for rapid identification of mold and yeast cultures of Penicillium marneffei. BMC Microbiol 16: Chen YS, Liu YH, Teng SH, Liao CH, Hung CC, Sheng WH, Teng LJ, Hsueh PR Evaluation of the matrix-assisted laser desorption/ionization time-of-flight mass 21

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23 Biosketch Author 1 Maurizio Sanguinetti, M.D., is currently full professor of Microbiology at the Università Cattolica del Sacro Cuore (UCSC) of Rome, Italy. He is director of the Institute of Microbiology and head of the Clinical Microbiology Laboratory of the UCSC Hospital A. Gemelli. He has a major interest in new diagnostic methods as a huge breakthrough for rapid identification of bacteria and fungi, as well as in new diagnostic algorithms as a means of optimizing the combined use of conventional and molecular laboratory tests. He is also interested in general microbiology and especially in studying molecular mechanisms underpinning the microbial pathogenesis and the antimicrobial drug resistance. Author 2 Brunella Posteraro, Ph.D., received her degree in biological sciences from the Università La Sapienza of Rome, Italy, and doctorate in general and clinical microbiology from the Università Cattolica del Sacro Cuore (UCSC) of Rome, Italy. She is currently associate professor of Microbiology at the Institute of Public Health (Section of Hygiene) of the UCSC. She was worked extensively in the clinical microbiology laboratory, with special interest in the development and evaluation of molecular tests for the diagnosis and characterization of fungal infections. Her current research interests are directed toward understanding the molecular mechanisms leading to antifungal resistance of yeast and filamentous fungal species. 23

24 TABLE 1 Studies evaluating the performance of MALDI-TOF MS for species identification of clinically relevant molds a MALDI system b Genus/group Species (no.) studied Acceptance criteria for ID c Isolates with ID result/total isolates Accuracy (%) Comparator identifiable with the indicated DB d method(s) e Vitek MS Aspergillus A. flavus 60% 3/9 Vitek MS IVD 33.0 MB, MO 23 6/9 SARAMIS 66.0 A. nomius 60% 0/3 Vitek MS IVD 0.0 MB, MO 0/3 SARAMIS 0.0 A. tamarii 60% 0/2 Vitek MS IVD 0.0 MB, MO 0/2 SARAMIS 0.0 Bruker Daltonics Aspergillus Aspergillus spp. (23) f /21 Biotyper 95.2 MB, MO 24 24/24 In-house 100 Bruker Daltonics Fusarium Fusarium spp. (19) g /268 In-house 82.8 MB, MO 25 Bruker Daltonics Rhizopus R. arrhizus NR 25/25 In-house 100 MB 27 R. microsporus NR 13/13 In-house 100 MB Bruker Daltonics Penicillium P. marneffei /39 In-house 100 MB 28 Bruker Daltonics Penicillium P. marneffei /28 In-house (NTUH-3370) 82.1 MB, MO 29 Paecilomyces Paecilomyces spp. (3) 2.0 0/12 Biotyper (general library and Filamentous Fungi Library 1.0) Fusarium Fusarium solani 2.0 1/6 Biotyper (general library and Filamentous Fungi Library 1.0) Rhizopus Rhizopus spp. (3) 2.0 0/3 Biotyper (general library and Filamentous Fungi Library 1.0) 0.0 MB, MO 16.6 MB, MO 0.0 MB, MO Bruker Daltonics Paecilomyces Paecilomyces spp. (4) 2.0, /71 Biotyper original library 94.3 MB, MO 30 Reference

25 supplemented Vitek MS Dermatophytes Trichophyton spp. (7), 60% 125/131 In-house Vitek MS knowledge 95.4 MB, MO 31 Arthroderma benhamiae, Microsporum spp. (4), Epidermophyton floccosum base Bruker Daltonics Dermatophytes Trichophyton spp. (6), >2.0, /64 In-house 100 MB, MO 32 Microsporum spp. (4), Epidermophyton floccosum Bruker Daltonics Dermatophytes Trichophyton spp. (7), /126 Biotyper original library 13.5 MO 33 Microsporum spp. (3), Epidermophyton floccosum < /126 Biotyper original library supplemented 89.7 Abbreviations: DB, database; ID, identification; MB, molecular biology; MO, morphology; MS, mass spectrometry; NR, not reported. a Data obtained from published articles selected for this review. b Prior to MALDI-TOF MS analysis, samples were prepared using the complete protein extraction method, as recommended by both the systems vendors. c In-house DBs are self-made spectral libraries that were initially constructed and validated, and then challenged alone or in combination with the respective system s commercial database. Otherwise, DBs were supplemented with spectral entries corresponding to species not (or not well) represented in the original DBs. d The values reported indicate confidence or score values used as ID cutoffs with the Vitek MS and Bruker Daltonics systems, respectively. e To assess the rate of correct IDs by MALDI-TOF MS, results were compared with IDs obtained by MB (i.e., DNA sequencing of single or multiple gene regions) and/or MO methods. Discrepancies between MALDI-TOF MS ID results and MO ID results were resolved by MB analyses; if the last results confirmed those of MALDI-TOF MS, the isolates were considered correctly identified by MALDI-TOF MS, regardless of the MO identification results. f Among the Aspergillus species included in the study, only rare species were considered for review purpose.