JCM Accepted Manuscript Posted Online 5 November 207 J. Clin. Microbiol. doi:0.28/jcm.03537 Copyright 207 American Society for Microbiology. All Rights Reserved. MultiCenter Evaluation of the VITEK MS v3.0 System for the Identification of Filamentous Fungi 2 3 4 5 6 7 8 9 0 2 3 4 5 6 Jenna Rychert, #, E. Sue Slechta, Adam P. Barker 2, Edwin Miranda 3, N. Esther Babady 3, YiWei Tang 3, 5, Connie Gibas 4, Nathan Wiederhold 4, DeAnna Sutton 4, Kimberly E. Hanson 2 ARUP Laboratories, Salt Lake City, UT, USA; 2 University of Utah, Salt Lake City, UT, USA; 3 Memorial Sloan Kettering Cancer Center, New York, NY, USA; 4 University of Texas Health Science Center, San Antonio, San Antonio, TX, USA; 5 Weill Medical College of Cornell University, New York, NY, USA Running Head: Identification of Mold Using VITEK MS v3.0 #Address correspondence to Jenna Rychert, Jennifer.Rychert@aruplab.com Deceased.
7 Abstract 8 9 20 2 22 23 24 25 26 27 28 29 30 3 32 33 34 35 Invasive fungal infections are an important cause of morbidity and mortality affecting primarily immunocompromised patients. While fungal identification to the species level is critical to providing appropriate therapy, it can be slow, laborious, and often relies on subjective morphologic criteria. The use of MALDITOF mass spectrometry has the potential to speed up and improve the accuracy of identification. In this multicenter study, we evaluated the accuracy of the VITEK MS v3.0 system in identifying,60 clinical mold isolates as compared to identification by DNA sequence analysis and supported by morphologic and phenotypic testing. Among the 59 isolates representing organisms in the v3.0 database, 9% (n=387) were correctly identified to the species level. An additional 27 isolates (2%) were correctly identified to the genus level. Fifteen isolates were incorrectly identified, either due to a single incorrect identification (n=3) or multiple identifications from different genera (n=2). In those cases, when a single identification was provided that was not correct, the misidentification was within the same genus. The VITEK MS v3.0 was unable to identify 9 (6%) isolates, despite repeat testing. These isolates were distributed among all the genera. When considering all isolates tested, even those that were not represented in the database, the VITEK MS v3.0 provided a single correct identification 98% of the time. These findings demonstrate that the VITEK MS v3.0 system is highly accurate for the identification of common molds encountered in the clinical mycology laboratory. 36 37 2
38 Introduction 39 40 4 42 43 44 45 46 47 48 49 50 5 52 53 54 55 56 57 58 Species level identification is critical for the evaluation and management of fungal infections. Mold identification has traditionally been based on subjective assessments of the macroscopic and microscopic appearance of organisms grown in culture. This is problematic given that species that may be morphologically similar can be genetically distinct, pathologically different, and may have different antifungal susceptibility profiles. Furthermore, consistent and accurate results are dependent on highly skilled clinical mycologists that have undergone substantial training. DNA sequencing is widely accepted as the reference method for fungal identification. However, accurate specieslevel identification often requires sequencing of multiple gene targets, can be expensive, and may not be readily available in the routine clinical setting. Matrixassisted laser desorption ionization time of flight mass spectrometry (MALDITOF MS) has potential clinical utility for species level identification of molds, just as it does for bacteria and yeasts (6). Recent studies suggest that successful identification of molds using mass spectrometry depends on the availability of a diverse and wellcurated database (77). Unlike the previous version, the newest version (v3.0) of the database that is included with the VITEK MS system (biomérieux, Inc., Durham, NC) includes 79 medically relevant mold species. Each species is represented by 222 unique isolates with 75% represented by four or more isolates (D. Pincus, personal communication). Database spectra were generated by testing each isolate under several growth conditions, including several media types and multiple incubation times, using multiple instruments, and several different operators. The end result is a collection of 3
59 60 6 over 20 reference spectra per species. In the present study, we evaluated the accuracy of the VITEK MS v3.0 system for identification of clinically relevant molds in comparison to DNA sequence analysis supported by morphologic and phenotypic testing. 62 63 64 65 66 67 68 69 70 7 72 73 74 75 76 77 78 79 Results Clinical isolates. A total of,59 unique mold isolates, representing organisms that are included in the VITEK MS v3.0 database, were tested over the course of the study. These isolates included 26 genera and 5 species. As shown in Table, the VITEK MS v3.0 provided a single identification that was correct to the species level for,387 (9%) of the isolates tested. An additional 27 (2%) isolates were correctly identified at the genus level (Table 2). Correct genus level identifications were instances where the VITEK MS v3.0 reported multiple species within the same genus, and this matched the genus identification provided by the reference method. As shown in Table 3, 5 isolates were misidentified (%), either as a result of a single incorrect identification (3 isolates) or reporting of multiple genera (2 isolates). All single species incorrect identifications were accurate at the genus level. In addition, results with multiple genera always included the correct specieslevel identification. Given that sequencing cannot always discriminate between phylogenetically similar organisms, we verified that these reference results were accurate using maximum parsimony and Bayesian analyses (Supplemental Data). In all cases, the reference result provided in Table 3 was fully supported by these additional analyses. A total of 79 isolates (5%) had to undergo repeat testing in order to obtain the final result (Table 4). A minority of these (9 of 79, %) produced spectra of 4
80 8 82 83 84 85 86 87 88 89 90 9 92 93 94 95 96 97 insufficient quality, leading to the result of No Identification. For 50 of the isolates, a correct identification was made after respotting the original extract. The other 29 isolates required reextraction to get the correct identification. A result of No identification was obtained for 9 (6%) isolates despite repeat testing. Eightytwo isolates representing organisms not included in the VITEK MS v3.0 database were also tested (Table 5). In the majority of cases (60/82; 73%), the VITEK MS v3.0 gave a result of No identification. The remaining 27% (22 of 82) were provided with a single identification that was incorrect. These misidentifications represent % of the total isolates tested (22 of 60).The majority (20 of 22) of these misidentified isolates were still within the correct genus. Clinical isolate results by organism group Dimorphic fungi. The VITEK MS v3.0 accurately identified 4 of the 4 dimorphic fungi that were tested. This included 40 isolates of Blastomyces dermititidis, 38 isolates of Coccioides immitis/posadasii, 32 isolates of Histoplasma capsulatum, and 3 isolates of Sporothrix schenkii complex. Three Coccidiodes immitis/posadasii and one Histoplasma capsulatum had to be respotted after an initial result of No identification in order to obtain the final correct identification. 98 5
99 00 0 02 03 04 05 06 07 08 09 0 2 3 4 5 6 7 8 9 Mucorales. Of the 8 Mucorales isolates tested, 0 (86%) were accurately identified to the specieslevel. Accuracy was highest for Lictheimia corymbifera (29/3, 94%), followed closely by members of the Rhizopus microsporus complex (26/29, 90%). There was a single Rhizopus microsporus that was misidentified as Rhizopus arrhizus. Seven Mucor racemosus and three Rhizopus microsporus underwent repeat testing after an initial result of No identification. A correct identification was made by respotting the original extract in all of these cases. Sixteen Mucorales isolates (4%) could not be identified despite repeat testing; the majority of these were Mucor racemosus or Rhizopus arrhizus species complex. Aspergillus. Aspergillus species were one of the largest groups of organisms included in the study. The majority of Aspergillus isolates tested (305/329, 93%) were correctly identified to the species level. Twentythree (7%) Aspergillus isolates were not identified. Repeat testing was performed on 6 isolates that were initially not identified, including 7 that needed to be respotted and 9 that needed to be reextracted. The VITEK MS v3.0 was least accurate for obtaining a species level identification for A. versicolor. One A. versicolor isolate was identified at the genus level and an additional eight could not be identified, despite repeat testing. Dematiaceous fungi. A total of 325 dematiaceous fungi were tested; 295 (9%) of these were correctly identified to the specieslevel. Of note, all 4 Scedosporium apiospermum, 32 Scedosporium prolificans, and 3 Exophiala dermatitidis were correctly identified. Eleven of the dematiaceous fungal isolates required repeat testing due to a failure to be identified on the first 6
20 2 22 23 24 25 26 27 28 29 30 3 32 33 34 35 36 37 38 39 40 analysis. Five of these were correctly identified after respotting the initial extract and another five were correctly identified after spotting a new extract. There was one Scedosporium boydii (formerly Pseudallescheria boydii) isolate that was misidentified after repeat testing of a new extract as Scedosporium apiospermum. Note that these organisms were previously considered to be the sexual (teleomorph) and asexual (anamorph) forms of one another, respectively, but are now recognized as separate species (8). There was also a Cladophialophora bantiana isolate in which the VITEK MS v3.0 gave a split result of Cladophialophora bantiana and Candida colliculosa. In all, the system failed to identify 28 (9%) of the dematiaceous fungi tested. Of these, six (five E. rostratum and one C. spicifera) had spectra of insufficient quality on all repeat testing which led to the result of No Identification. Dermatophytes. The majority of the dermatophytes (246/29, 85%) were correctly identified to the specieslevel. Trichophyton species were particularly problematic, with 2 isolates incorrectly identified. Eleven of these were a single incorrect identification within the Trichophyton genus. The result for the remaining isolate was a split identification that included T. violaceum, Candida lambica, and Fusarium oxysporum complex. There were no Trichophyton isolates for which the VITEK MS v3.0 ultimately provided a result of No identification, however, 2 needed repeat testing in order to obtain the final correct result. There were seven Microsporum or Epidermophyton isolates that could not be identified by VITEK MS v3.0, with an additional 5 that required repeat testing after failing to be identified on the first analysis. E. floccosum was the only organism in this group for which repeat testing was the result of poor 7
4 42 quality spectra. For each of the three isolates of this organism that underwent repeat testing, lack of a quality spectra was the reason repeat testing was required. 43 44 45 46 47 48 49 50 5 52 53 54 55 56 57 58 Other Potential Pathogens. Among the other 36 potentially pathogenic molds tested, 299 (95%) were correctly identified to the species level. Among these were six isolates that were respotted and five isolates that were reextracted in order to get the final correct result after failing to be identified on the first analysis. No molds within this category were misidentified or identified only to the genus level. Seventeen of the isolates were not identified despite repeat testing. Challenge Set. In addition to the isolates obtained during the course of clinical work, a panel of 50 wellcharacterized isolates representing 6 genera and 27 species included in the VITEK MS v3.0 database were run at each of the three clinical laboratories. As shown in Table 6, 4 of the 50 (94%) challenge isolates were correctly identified to the species level. There were no misidentifications, but nine isolates could not be identified despite repeat testing. The VITEK MS v3.0 failed to identify two isolates in each of two laboratories and five isolates in the other laboratory. Specifically, an isolate of Rhizopus arrhizus was not identified at two of the three laboratories and an Aspergillus versicolor was not identified at any of the three laboratories. 59 8
60 6 62 63 64 65 66 67 68 69 70 7 72 73 74 75 76 77 78 79 80 Reproducibility. Reproducibility testing produced a single correct identification to the species level for 298 of the 300 (>99%) isolates in the reproducibility panel. In two instances, Purpureocillium lilacinum was not identified, once at site three and once at site one. There was also a single instance where Aspergillus fumigatus was not identified on the initial run at site three, but upon repeat testing of the same extract, the correct result to the species level was obtained. There were no misidentifications of any organism at any site. There also were no differences in organism identification by site, operator, reagent kit, or day. Given that the VITEK MS v3.0 failed to identify Purpureocillium lilacinum but no other organism, there may be organismspecific factors that contribute to a failure to identify a specific isolate. Discussion The US Food and Drug Administration (FDA) recently cleared the VITEK MS v3.0 system for the identification of 79 filamentous fungi. Identification of molds using this system requires sample preparation that is not necessary for the identification of bacteria and yeast. In particular, the sample is inactivated in ethanol and protein extraction is performed in a tube prior to deposition on the target slide. Testing can be performed within 28 days of visible growth on rapidly growing molds and within 525 days for slow growing molds. Thus, the VITEK MS v3.0 system, with its commercially available reagents, standardized SOP, and robust database that allows for flexibility in incubation time, should make identification of commonly encountered molds feasible for many clinical laboratories. 9
8 82 83 84 85 86 87 88 89 90 9 92 93 94 95 96 97 98 99 200 20 202 This study confirms the excellent accuracy and reproducibility of the VITEK MS v3.0 system for the identification of common molds to the genus or species level. Despite organism group specific limitations, when a single identification was provided it was correct 98% of the time. The system was especially good at identifying dimorphic fungi (00% accuracy), but somewhat less effective for dermatophytes, with only 85% of these isolates correctly identified to the species level. This was primarily due to a genus level identification or a misidentification between Trichophyton violaceum and Trichophyton rubrum and similar issues with Trichophyton species of Arthroderma benhamiae including T. verrucosum, T. interdigitale, and T. erinacei. In all these cases, the VITEK MS v3.0 result was a genetically similar species to the reference identification. Other MALDITOF MS studies have also noted difficulty in discriminating some Trichophyton species, especially T. violaceum and T. rubrum due to their high degree of homology (9, 20). This issue can sometimes be resolved by adding more spectral libraries for these organisms into the database; however, this is not always the case (7). Future database updates may want to take this into consideration. Relative to other groups, organisms in the order Mucorales were the most likely to produce a result of No identification even with repeat testing (4%). This was most pronounced for M. racemosus and R. arrhizus. While several studies have evaluated the accuracy of MALDITOF MS for identifying members of the Mucorales, these species are not well represented in the literature, so it is difficult to determine whether this is a common problem (8, 0,, 3, 223). Poorer performance for either the dermatophytes or the Mucorales is unlikely to be due to differences in the age of the culture at time of testing. While fungal protein profiles may change as incubation time 0
203 204 205 206 207 208 209 20 2 22 23 24 25 26 27 28 29 220 22 222 progresses, this has been accounted for in the VITEK MS v3.0 database. Several dematiaceous fungi could not be identified as a result of poor quality spectra. Initial studies suggested that darkly pigmented fungi may be difficult to identify by MALDITOF MS (24); however, more recent work has shown that this is not necessarily the case (8, 2527). Multiple studies have previously evaluated the accuracy of MALDITOF MS for identifying molds (7, 8, 07, 9, 20, 23, 28, 29). The strength of this study is the large number of organisms tested across a variety of clinical laboratories using a standardized procedure and instrumentation. A limitation is that the study primarily focused on molds more commonly encountered in the clinical mycology laboratory and those contained in the VITEK MS v3.0 database. Among the isolates that were tested that were not represented in the database, the majority was given the most appropriate result of No Identification. The misidentifications for organisms not represented in the database represent % of all of the isolates tested. Further, they were all correct at the genus level and the misidentification at the species level is unlikely to impact initial antifungal therapy. Performance of the system in clinical practice will ultimately depend on the epidemiology of organisms encountered in any individual clinical setting. For example, the spectrum of organisms identified in a reference setting or cancer center, may be more diverse than is seen in a community hospital. Using a customized database that is more comprehensive may make sense for some laboratories; however, creation of an expanded database with more rare organisms requires additional time, expertise, and quality control. 223
224 225 226 227 228 229 230 23 232 233 234 235 236 237 238 239 240 24 In summary, the VITEK MS v3.0 system is highly accurate for the identification of commonly encountered molds in the clinical mycology laboratory. With this technology, it may now be feasible for more clinical laboratories to accurately identify a range of filamentous fungi to the specieslevel. Materials and Methods Study Sites. VITEK MS v3.0 system test performance was evaluated at three clinical laboratories within the United States (ARUP Laboratories, Salt Lake City, UT; University of Texas Health Science Center, San Antonio, TX; and Memorial Sloan Kettering Cancer Center, New York, NY). Prior to initiation of testing, operators at each site were trained on the testing protocol, isolate and target slide preparation, and result review per the manufacturer s instructions. Prior to testing study samples, each operator was required to analyze a panel of five molds in duplicate (Aspergillus fumigatus, Fusarium proliferatum, Purpureocillium lilacinum, Lecythophora hoffmanii, and Penicillium chrysogenum). Testing could begin once they were able to achieve at least 90% agreement between duplicate samples and 95% correct identifications. This study was approved by the human subjects committees at the respective sites, when deemed necessary by their institutional review boards. 242 243 Mold Isolates. Each study site was responsible for testing approximately 0 clinical isolates per species of a predefined list of organisms (Table ), with preference given to fresh isolates 2
244 245 246 247 248 249 250 25 252 253 254 255 256 257 258 259 260 26 262 263 obtained during the course of clinical work. In the event that a site was unable to obtain 0 fresh isolates, additional frozen isolates obtained from a culture collection or provided by the study sponsor were permitted. In additional to the clinical isolates, each site also tested a challenge set consisting of 50 wellcharacterized strains. The identity of the organisms within the challenge set was blinded to the operators performing the testing. Cultures were incubated under standard conditions at 30 C and tested within 28 days of visible growth for rapidly growing molds or 525 days for slow growing molds. Cultures were grown on potato dextrose agar, Sabouraud dextrose agar, or Sabouraud dextrose agar with gentamicin and chloramphenicol. These culture conditions were identical to the conditions used to build the v3.0 Knowledgebase. Frozen isolates were required to undergo subculture twice prior to testing. Sample Preparation for MALDITOF Analysis. Sample preparation was performed according to the manufacturer s instructions using the VITEK MS Mould Reagent Kit (biomérieux, Durham, NC). Approximately cm 2 of mold was inactivated in 900 µl of 70% ethanol followed by centrifugation at 4,000 g for 2 minutes. Ethanol was removed and protein extraction was performed by resuspending the pellet in 40 µl of 70% formic acid and 40 µl of acetonitrile. After centrifugation again at 4,000 g for 2 min, µl of the supernatant was spotted on the target slide, allowed to dry, and overlaid with µl of a saturated solution of alphacyano4 3
264 265 hydroxycinnamic acid matrix in 50% acetonitrile plus 2.5% trifluoroacetic acid (VITEK MSCHCA; biomérieux, Inc.). 266 267 268 269 270 27 272 273 274 275 276 277 278 279 280 28 For instrument calibration, an Escherichia coli reference strain (ATCC 8739) was transferred to designated wells on the target slide using a.0 µl loop, overlaid with.0 µl of VITEK MSCHCA matrix, and air dried. Positive (Aspergillus brasiliensis; ATCC 6404) and negative (reagents alone) controls were analyzed on each day of testing. Organism Identification using the VITEK MS v3.0 System. The VITEK MS v3.0 system includes an OEM (original equipment manufacturer)labeled Shimadzu AXIMA Assurance mass spectrometer linked to a reference database as previously described (2). In those instances when a result of No identification was obtained, repeat testing of a single spot was performed using the same extract. If a result of No identification was obtained again, a new sample extract was prepared and tested on a single spot. If identification was still not made, a result of No Identification was used as the final result. In cases where multiple genera were reported, a new extract was prepared and tested on a single spot. The result obtained upon repeat testing was used as the final result. 282 283 Organism Identification by DNA Sequencing. All study isolates were sent to a centralized laboratory (Fungus Testing Laboratory, University of Texas Health Science Center, San Antonio, 4
284 285 286 287 288 289 290 29 292 293 294 295 296 297 298 299 300 30 TX) for DNA sequencebased identification combined with morphologic/phenotypic characteristics. DNA sequence analysis was performed after PCR amplification and sequencing of isolatespecific targets (ITS/ITS2 and D/D2 regions of rrna, tubulin, calmodulin, actin, glyceraldehyde3phosphate dehydrogenase, RNA polymerase II subunits RPB & RPB2, and/or translation elongation factor genes) (30). BLASTn analysis of the DNA sequences was conducted using publically available databases, including GenBank, CBS KNAW, and FusariumDB. DNA sequence identification results were confirmed by morphologic/phenotypic analysis. In the event of a discrepancy or lowdiscrimination result, or when discordant results were obtained using this method, supplemental sequencing of a different gene target and/or phenotypic testing was performed. Analysis. The VITEK MS v3.0 result was considered accurate to the species level if a single identification was given and it matched the identification obtained by sequencing. It was considered correct to the genus level if multiple identifications, all from the same genus, were reported and this matched the genus obtained by sequencing. It was considered incorrect, if a single identification was given that did not match (at some taxonomic level) the result obtained by sequencing or when multiple identifications of different genera were reported. 302 303 304 Reproducibility testing. Reproducibility testing was performed by two operators at each clinical laboratory. A panel of five organisms (Aspergillus fumigatus, Fusarium proliferatum, Purpureocillium lilacinum, Lecythophora hoffmannii, and Penicillium chrysogenum) was tested 5
305 306 307 308 309 30 3 32 33 34 35 36 37 38 39 320 32 in duplicate on two runs daily for five days. The identity of each organism was blinded to the operators. Testing was performed using three different lots of reagents. The position of each organism on the target slide was predetermined and tested sequentially on one slide and randomized on a second slide. Sample preparation, organism identification on the VITEK MS v3.0, and result analysis was performed as described above. Acknowledgements We thank Tracy McMillen, Pam Foster, Janet Hindler, Romney Humphries, Stephen Jenkins, Doris Ortez, Michael Pfaller, Tonya Snyder, Charles Stratton, and Susan WuButler for technical assistance and/or clinical isolate provision. This study was performed as part of an FDA trial of the VITEK MS v3.0 system and was funded by the device manufacturer (biomérieux, Inc., Durham, NC) under research agreements of SK203773 (Memorial Sloan Kettering Cancer Center). The analysis of the data presented herein was performed by the study authors without influence by the device manufacturer. This study was supported in part by an NIH/NCI Cancer Center Support Grant P30 (CA008748). 322 6
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Dematiaceous (n=325) Dermatophytes (n=29) Dimorphs (n=4) Mucorales (n=8) 44 Tables 442 443 Table. Accuracy of VITEK MS v3.0 Compared to Sequencing for Clinical Isolates Included in the Database Reference Identification Mucor racemosus complex (n=30) Rhizopus arrhizus complex (n=28) Rhizopus microsporus complex (n=29) Lichtheimia corymbifera (n=3) Correct to Species 24 (80) 22 (79) 26 (90) 29 (94) VITEK MS Identification (%) Correct to Genus Incorrect Results (3) No ID 6 (20) 6 (2) 2 (7) 2 (6) Total 0 (86) (<) 6 (4) Blastomyces dermatitidis (n=40) Coccidioides immitis/posadasii (n=38) Histoplasma capsulatum (n=32) Sporothrix schenckii complex (n=3) 40 (00) 38 (00) 32 (00) 3 (00) Total 4 (00) Arthroderma benhamiae (n=) Microsporum audouinii (n=33) Microsporum canis (n=3) Microsporum gypseum (n=35) Epidermophyton floccosum (n=3) Trichophyton mentagrophytes complex Trichophyton interdigitale (n=30) Trichophyton rubrum (n=3) Trichophyton tonsurans (n=33) Trichophyton verrucosum (n=3) Trichophyton violaceum (n=34) (n=) (00) 30 (9) 30 (97) 32 (9) 30 (97) (00) 29 (97) 3 (00) 30 (9) 8 (58) 4 (4) (3) (3) (3) 9 (29) 4 (4) 2 (6) 4 (3) 6 (8) 2 (6) (3) 3 (9) 2 (3) Total 246 (85) 26 (9) 2 (4) 7 (2) Alternaria alternata (n=32) Curvularia hawaiiensis (n=26) Curvularia spicifera (n=35) Exserohilum rostratum (n=35) Exophiala dermatitidis (n=3) Exophiala xenobiotica (n=32) Scedosporium boydii (n=32) Scedosporium apiospermum (n=4) Scedosporium prolificans (n=32) Cladophialophora bantiana (n=29) 30 (94) 25 (96) 34(97) 9 (54) 3 (00) 25 (78) 30 (94) 4 (00) 32 (00) 28 (97) (3) (3) 2 (6) (4) 2 (3) 6 3 (46) 7 (22) (3) Total 295 (9) 2 (<) 28 (9) 23
Other potential pathogens (n=36) Aspergillus species (n=328) 444 445 446 447 448 Aspergillus brasiliensis (n=3) Aspergillus calidoustus (n=33) Aspergillus flavus/oryzae (n=33) Aspergillus fumigatus (n=32) Aspergillus lentulus (n=30) Aspergillus nidulans (n=33) Aspergillus niger complex (n=37) Aspergillus sydowii (n=30) Aspergillus terreus complex (n=34) Aspergillus unguis (4) Aspergillus versicolor (n=3) 29 (94) 29 (88) 33 (00) 32 (00) 30 (00) 32 (97) 32 (87) 30 (97) 32 (94) 4 (00) 22 (7) (3) 2 (7) 4 (2) (3) 5 (4) (3) 2 (6) 8 (26) Total 305 (93) (<) 23 (7) Fusarium oxysporum complex (n=3) Fusarium proliferatum (n=30) Fusarium solani complex (n=39) Paecilomyces variotii (n=30) Penicillium chrysogenum (n=30) Penicillium citrinum (n=) Rasamsonia argillacea (n=34) Acremonium sclerotigenum (n=30) Lecythophora hoffmannii (n=30) Sarocladium kiliense (n=30) Purpureocillium lilacinum (n=3) 30 (97) 30 (00) 33 (85) 30 (00) 30 (00) (00) 29 (85) 30 (00) 27 (90) 30 (00) 29 (94) (3) 6 (5) 5 (5) 3 (0) 2 (6) Total 299 (95) 7 (5) Total Molds (n=59) 387 (9) 27 (2) 5 () 9 (6) Not included in FDA claim 2 No identification due to spectra of insufficient quality on all repeat testing 3 For five of 6 isolates, no identification due to spectra of insufficient quality on all repeat testing 24
449 Table 2. Correct Identifications to the Genus Level for Clinical Isolates Included in the v3.0 Database 450 45 452 453 Reference Result VITEK MS Result (number of results) Aspergillus versicolor Aspergillus versicolor, Aspergillus sydowii () Microsporum audouinii Microsporum canis, Microsporum audouinii () Trichophyton interdigitale Trichophyton tonsurans, Trichophyton interdigitale () Trichophyton tonsurans Trichophyton tonsurans, Trichophyton interdigitale () Trichophyton verrucosum Trichophyton verrucosum, Trichophyton erinacei (5) Trichophyton verrucosum, Trichophyton erinacei, Arthroderma benhamiae () Trichophyton verrucosum, Arthroderma benhamiae (2) Trichophyton erinacei, Arthroderma benhamiae () Trichophyton violaceum Trichophyton rubrum, Trichophyton violaceum (4) Arthroderma benhamiae is the telemorph of Trichophyton mentagrophytes Downloaded from http://jcm.asm.org/ on December 3, 208 by guest 25
Multiple Genera Single Identification 454 Table 3. Incorrect Identifications for Clinical Isolates Included in the v3.0 Database Reference Identification VITEK MS Identification (number of results) Rhizopus microsporus Rhizopus arrhizus () 455 456 457 458 459 460 Trichophyton tonsurans Trichophyton interdigitale (2) Trichophyton verrucosum Trichophyton interdigitale (3) Trichophyton verrucosum Trichophyton erinacei () Trichophyton violaceum Trichophyton rubrum (5) Scedosporium boydii 2 Scedosporium apiospermum () Cladophialophora bantiana Cladophialophora bantiana, Candida colliculosa () Trichophyton violaceum Trichophyton violaceum, Candida lambica, Fusarium oxysporum complex () For additional analysis regarding the reference identification, see Supplemental Data. 2 The anamorph of Scedosporium apiospermum was previously named Pseudallescheria boydii, but it is now considered a separate species. 26
Other potential pathogens (n=36) Aspergillus species (n=328) Dematiaceous (n=325) Dermatophytes (n=29) Dimorphs (n=4) Mucorales (n=8) 46 Table 4. Results of Repeat Testing Reference Identification Respot Correct ID VITEK MS Identification (%) Reextract Correct ID Reextract MisID Mucor racemosus complex (n=30) Rhizopus microsporus complex (29) 7 (23) 3 (0) Total 0 (8) Coccidioides immitis/posadasii (n=38) Histoplasma capsulatum (n=32) 3 (8) (3) Total 4 (3) Epidermophyton floccosum (n=3) Microsporum audouinii (n=33) Microsporum canis (n=3) Microsporum gypseum (n=35) Trichophyton interdigitale (n=30) Trichophyton rubrum (n=3) Trichophyton verrucosum (n=3) Trichophyton violaceum (n=34) Total 8 (6) 9 (3) Alternaria alternata (n=32) Curvularia hawaiiensis (n=26) Exophiala dermatitidis (n=3) Exserohilum rostratum (n=35) Scedosporium boydii (n=32) Scedosporium apiospermum (n=4) 7 3 2 3 2 2 Total 5 (2) 5 (2) (<) Aspergillus calidoustus (n=33) Aspergillus flavus/oryzae (n=33) Aspergillus nidulans (n=33) Aspergillus niger complex (n=37) Aspergillus sydowii (n=30) Aspergillus terreus complex (n=34) Aspergillus versicolor (n=3) Total 7 (2) 9 (3) Fusarium solani complex (n=35) Lecythophora hoffmannii (n=30) Paecilomyces variotii (n=30) Penicillium chrysogenum (n=30) Purpureocillium lilacinum (n=3) Rasamsonia argillacea (n=34) Sarocladium kiliense (n=30) Total 6 (2) 5 (2) 2 2 2 5 2 0 2 2 2 2 462 Total Molds (n=59) 50 (3) 28 (2) () 27
No Identification (n=60) Incorrect Identification (n=22) 463 Table 5. Organisms not included in the v3.0 Database 464 465 466 VITEK MS Identification Reference Identification (number of results) Aspergillus flavus/oryzae Aspergillus nomius () Aspergillus nidulans Aspergillus delacroxii (3) Aspergillus quadrilineatus (3) Emericella variecolor () Aspergillus versicolor Aspergillus amoenus (2) Aspergillus fructus () Candida kefyr/parapsilosis Cladophialophora boppii () Curvularia hawaiiensis Curvularia senegalensis () Curvularia spicifera Curvularia lunata () Curvularia pseudolunata () Fusarium chlamydosporum complex Fusarium incarnatumequiseti species complex () Fusarium oxysporum complex Fusarium nygamai () Fusarium proliferatum Fusarium fujikuroi (2) Mucor velutinosus Mucor circinelloides f. janssenii () Penicillium chrysogenum Penicillium rubens (2) No Identification Alternaria species () Aspergillus creber (2), Aspergillus jensenii (5), Aspergillus nomius (), Aspergillus section usti (), Aspergillus striatus/cleistominutus (), Aspergillus tabacinus (), Aspergillus tamarii () Chaetomium species () Cladophialophora carrionii (), Cladophialophora minourae (2) Cladosporium cladosporioides (), Cladosporium halotolerans (), Cladosporium sphaerospermum () Coprinellus xanthothrix () Curvularia aeria (2), Curvularia hominis (2), Curvularia lunata (), Curvularia pseudolunata (2), Curvularia species () Exophiala bergeri (), Exophiala oligosperma () Fusarium brachygibbosum (), Fusarium dimerum (2), Fusarium incarnatumequiseti species complex (), Fusarium lactis (), Fusarium lichenicola (), Fusarium sp. in Fusarium fujikuroi spp. Complex (), Fusarium sublutinans (), Fusarium verticillioides () Lichtheimia ramose (3), Lichtheimia ramose/corymbifera (2) Mucor circinelloides (), Mucor plumbeus () Paecilomyces formosus (2) Penicillium copticola (), Penicillium crustosum (2), Penicillium decumbens (), Penicillium janthinellum (), Penicillium paneum (), Penicillium polonicum (), Penicillium sizovae () Rhinocladiella similis () Sarocladium bifurcatum () Trichophyton soudanense () 28
467 468 Table 6. Accuracy of VITEK MS v3.0 Compared to Sequencing for the Challenge Set 469 470 VITEK MS Identification (%) Reference Identification Correct to Species Correct to Genus Incorrect No ID Alternaria alternata (n=3) 3 (00%) Aspergillus flavus/oryzae (n=2) 2 (00%) Aspergillus fumigatus (n=9) 9 (00%) Aspergillus lentulus (n=3) 3 (00%) Aspergillus nidulans (n=3) 3 (00%) Aspergillus niger complex (n=3) 3 (00%) Aspergillus sydowii (n=6) 6 (00%) Aspergillus terreus complex (n=6) 6 (00%) Aspergillus versicolor (n=6) 2 (33%) 4 (67%) Curvularia spicifera (n=3) 3 (00%) Epidermophyton floccosum (n=3) 3 (00%) Exophiala xenobiotica (n=3) 3 (00%) Fusarium oxysporum complex (n=9) 9 (00%) Fusarium solani complex (n=6) 6 (00%) Lecythophora hoffmannii (n=3) 3 (00%) Lichtheimia corymbifera (n=3) 3 (00%) Paecilomyces variotii complex (n=6) 6 (00%) Penicillium chrysogenum (n=2) 2 (00%) Purpureocillium lilacinum (n=6) 5 (83%) (7%) Rhizopus arrhizus complex (n=6) 3 (50%) 3 (50%) Rhizopus microsporus complex (n=3) 2 (66%) (33%) Sarocladium kiliense (n=3) 3 (00%) Scedosporium apiospermum (n=6) 6 (00%) Scedosporium boydii (n=6) 6 (00%) Scedosporium prolificans (n=3) 3 (00%) Trichophyton interdigitale (n=6) 6 (00%) Trichophyton rubrum (n=3) 3 (00%) Total in Challenge Set (n=50) 4 (94%) 9 (6%) 29