Evaluating and improving Vitek MS for identification of clinically relevant

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1 JCM Accepted Manuscript Posted Online 24 May 2017 J. Clin. Microbiol. doi: /jcm Copyright 2017 American Society for Microbiology. All Rights Reserved Evaluating and improving Vitek MS for identification of clinically relevant species of Trichosporon and the close-related genera Cutaneotrichosporon and Apiotrichum João N. de Almeida Júnior 1,2 ; Viviane M. Favero Gimenes 1 ; Elaine C. Francisco 3, Lumena P. Machado Siqueira 2 ; Renato K. Gonçalves de Almeida 1 ; Juliette Guitard 4 ; Christophe Hennequin 4,* ; Arnaldo Lopes Colombo 3,* ; Gil Benard 2,* ; Flavia Rossi 1,*. 1 Central Laboratory Division (LIM03), Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil. 2 Laboratory of Mycology (LIM 53), Instituto de Medicina Tropical de São Paulo, Universidade de São Paulo, São Paulo, Brazil. 3 Laboratório Especial de Micologia, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, Brazil. 4 AP-HP, Hôpital St Antoine, Service de Parasitologie-Mycologie, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, Inserm UMR 1135, CNRS ERL 8255; Centre d Immunologie et des Maladies Infectieuses (CIMI-Paris), 91 Bd de l hôpital, F-75013, Paris, France * Senior authors contributed equally to this work. Running title: Vitek MS and identification of Trichosporon species Key words: Trichosporon, Cutaneotrichosporon, Apiotrichum, Vitek MS, MALDI-TOF mass spectrometry Corresponding author: João Nobrega de Almeida Júnior. Mailing address: Laboratorio de Microbiologia, DLC, PAMB, Instituto Central. Av. Dr. Enéas de Carvalho Aguiar, Cerqueira César / São Paulo Brazil. Fax: Telephone: / jnaj99@gmail.com. 26 1

2 Abstract: Trichosporon species are relevant etiologic agents of hospital-acquired infections. High mortality rates are attributed to Trichosporon deep-seated infections in immunocompromised individuals, being fast and accurate species identification relevant for hasting the best-targeted therapy. Recently, Trichosporon taxonomy has been re-assessed and three genera have been proposed for the pathogenic species: Trichosporon, Cutaneotrichosporon and Apiotrichum. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) has replaced old phenotypic methods for microorganism s identification in clinical laboratories, but spectral profile databases have to be evaluated and improved for optimal species identification performance. Vitek MS (biomérieux) is one of the commercial available MALDI-TOF MS platforms for pathogen identification and its spectral profile databases remain poorly evaluated for Trichosporon, Cutaneotrichosporon and Apiotrichum species identification. We herein evaluated and improved Vitek MS for the identification of the main clinical relevant species of Trichosporon, Cutaneotrichosporon and Apiotrichum using a large set of strains and isolates belonging to different yeast collections of Brazil and France

3 Introduction: Opportunistic non-candida yeasts, including Trichosporon spp., are emerging pathogens of deep-seated infections in the context of immunodepression and/or invasive procedures (1, 2). In addition, outbreaks of catheter-related fungemia by these pathogens have been described in neonatal intensive care units (3). Based on molecular phylogenetic analysis, Trichosporon pathogenic species were initially subdivided into three clades: clade Porosum, which included the species Trichosporon asahii, Trichosporon inkin, Trichosporon coremiiforme, Trichosporon asteroides, Trichosporon faecale, Trichosporon ovoides, Trichosporon japonicum, and Trichosporon lactis; clade Cutaneum, which included the species Trichosporum mucoides, Trichosporon dermatis, Trichosporon debeurmannianum, Trichosporon jirovecii and Trichosporon cutaneum; clade gracile/brassicae, which included the species Trichosporon mycotoxinivorans, Trichosporon montevideense, Trichosporon domesticum, and Trichosporon loubieri (4). Among these pathogenic species, T. asahii, T. asteroides, T. faecale, T. inkin, T. coremiiforme, C. dermatis, and A. mycotoxinivorans are the main species related to deep-seated infections (2, 4). Recently, based on multiple gene sequence analysis, Trichosporon taxonomy has been re-assessed and new genera has been proposed for the monophyletic clades, which includes Trichosporon, Cutaneotrichosporon and Apiotrichum for the pathogenic species (5). These genera are intrinsically resistant to echinocandins and resistance to other antifungal classes has been described (2, 4). Moreover, distinct inter-species antifungal susceptibility profile, virulence and pathogenicity have been suggested (2, 6). Thus, not only genus but also species correct identification of these opportunistic pathogens is recommended for optimal clinical management and/or for epidemiological purposes. 3

4 Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) has emerged as a useful technique for rapid and precise pathogen identification in clinical laboratories (7). Recent studies analyzing the performance of MALDI-TOF MS for identification of more than 1000 yeast isolates (>95% Candida) describe successful species identification ranging from 95 to 98% when compared to DNA-based gold-standard techniques (8, 9). However, the performance of MALDI- TOF MS for identification of non-candida species is suboptimal, and wellconstructed in-house spectral profiles databases are required to achieve better performance (8, 10). Likewise, studies that evaluated MALDI-TOF MS for identification of clinically relevant species of Trichosporon, Cutaneotrichosporon and Apiotrichum using the Bruker s instrument showed that it required upgrade of the spectral profile library (e.g. Biotyper) to achieve optimal species identification performance (10, 11). In this work, we evaluated the Vitek MS instrument (biomérieux, Marcy- L Etoile, France) and its associated databases for the identification of Trichosporon, Cutaneotrichosporon and Apiotrichum clinically relevant species, and also constructed and validated an in-house spectral profile database for better identification of these pathogens

5 Material and Methods Fungal organisms A total of 15 CBS-KNAW reference strains and 93 non-replicate clinical isolates (blood, urine, stools, skin and respiratory tract) from Brazilian (University of São Paulo, Federal University of São Paulo) and French collections (Hôpital Saint- Antoine, Paris) were analyzed. Trichosporon spp., Cutaneotrichosporon spp. and Apiotrichum spp. were represented by 76, 20, 12 organisms, respectively. For all these organisms, species identification was carried out by sequence analysis of the IGS1 or D1/D2 domain of the 26S region of the ribosomal DNA with primers and amplification parameters that were previously described (12, 13). Sample preparation for MALDI-TOF MS analysis Strains and isolates maintained as frozen stocks at -80 C in yeast-extract peptone dextrose medium were subcultured on Sabouraud s dextrose agar (SDA) plates and incubated for 48 h at 30 C before MALDI-TOF MS analysis. Due to the dry and rough morphology of some Trichosporon isolates, homogenous smearing of colonies on target plate was troublesome and a standard protein extraction protocol with ethanol and formic acid was used for all analysis. In brief, one loop of yeast biomass was transferred into a 1.5 ml tube (Eppendorf) containing 300 µl of purified water and mixed thoroughly. Subsequently, 900 µl of absolute ethanol was added to each tube and mixed for 1 minute. The samples were centrifuged for 2 minutes at rpm and the supernatant was removed. The pellet was dried at room temperature and 50 µl of formic acid (70%) was added. In addition, an equivalent volume of acetonitrile was added and the mix was centrifuged for 2 minutes at rpm. Finally, 1μl of the clear supernatant was spotted in quadruplicate onto a disposable 5

6 MALDI target slide composed of a polypropylene carrier with a stainless steel layer (biomérieux). After air-drying, each spot was overlaid with 1µl of α-cyano-4- hydroxycinnamic acid (HCCA) matrix (biomérieux). MALDI-TOF MS analysis by biomérieux IVD and RUO databases Measurements were performed on a Vitek MS instrument (biomérieux) equipped with both In Vitro Diagnostic (IVD) and Research Use Only (RUO, SARAMIS ) databases (biomérieux). For the IVD analysis, spectra were obtained using the Vitek MS automation control and Myla software (biomérieux) with the manufacturer's suggested settings. For each acquisition group, a standard (Escherichia coli ATCC 8739) was included to calibrate the instrument and validate the run. The spectra were analyzed by the Vitek MS v3.2 IVD database (biomérieux). The software compares the spectrum obtained to the expected spectrum of each organism or organism group (e.g. bacteria or fungi) and high confidence level identification was considered when single species showed a probability of ID 60%. For the RUO analysis, spectra were generated using the Launchpad v2.8 software (biomérieux) and compared to the SARAMIS v.4.13 database (biomérieux). Peak matches that yield identification results with confidence values exceeding 75% are reported. For both IVD and RUO results, we considered accurate identification if the correct species was mentioned despite the report of Trichosporon for the new genera Cutaneotrichosporon and Apiotrichum.. Organisms that were initially not identified or misidentified were reanalyzed another two times to check the repeatability and reproducibility of these results. Construction of an in-house SuperSpectrum library for upgrading the RUO database For SuperSpectra construction, mass spectra of 32 organisms, representing all the 6

7 species investigated in this study, were imported into the SARAMIS Premium software package (biomérieux) (Table 1). Then, 10 high-quality mass spectra replicates of a given species from a single or two organisms ( 120 masses, 70 similarity) were selected to create a species-specific SuperSpectrum with the SARAMIS Premium SuperSpectrum tool (biomérieux) according to the manufacturer s instructions. The specificity of the potential biomarker masses was determined by comparison against the whole SARAMIS spectral archive (biomérieux), and a SuperSpectrum with 40 masses had to have at least 20 speciesspecific biomarkers. The RUO spectral profile database were upgraded with the addition of 22 in-house SuperSpectra, including three for the species T. asahii, T. inkin, and T. asteroides, two for the species C. dermatis, and one for the species T. faecale, T. ovoides, T. coremiiforme, T. lactis, C. mucoides, C. jirovecii, C. debeurmannianum, A. domesticum, A. montevideense, A. mycotoxinivorans, and A. loubieri (Table 01). Finally, the original SuperSpectra from the SARAMIS v.4.13 database (biomérieux) related to misidentifications were inactivated, and the upgraded database with the in-house SuperSpectra was challenged for identification of all strains and isolates. Organisms that were initially not identified or misidentified were reanalyzed another two times to check the repeatability and reproducibility of these results

8 Results The IVD database reported correct species ID for 73.6%, 5%, and 0% of Trichosporon, Cutaneotrichosporon, and Apiotrichum organisms, respectively. All organisms belonging to the species T. faecale, T. coremiiforme, T. japonicum, T. lactis, C. jirovecii, C. debeurmannianum, A. montevideense, A. mycotoxinorans, A. domesticum, and A. loubieri lacked identification. All 12 C. dermatis organisms were consistently misidentified as C. mucoides. One isolate of C. jirovecii and one isolate of A. montevideense were misidentified as Candida valida (confidence level of 50%) and Candida albicans (confidence level of 95.4%), respectively, but all results of the subsequent repeat analyses came out as no identification. Two T. inkin isolates were initially misidentified as T. ovoides (confidence levels of 50 and 99.8%), but correct species assignment was achieved after repeat analyses. The RUO database reported correct species ID for 68.4%, 5% and 0% of Trichosporon, Cutaneotrichosporon, and Apiotrichum organisms, respectively. All organisms belonging to the species T. ovoides, T. faecale, T. japonicum, C. jirovecii, C. debeurmannianum, A. montevideense, A. mycotoxinorans and A. domesticum lacked identification. Among three organisms of T. coremiiforme, two had correct genus identification, despite being misclassified as T. asahii with a confidence level of 80-90%, even after repeated analysis. C. dermatis organisms were consistently misclassified as C. cutaneum/mucoides or had identification restricted to the genus level. The SuperSpectra Trichosporon_asahii_1_ and Trichosporon_cutaneum/mucoides_1_ from the original RUO database were inactivated since they were related to misidentifications of T. coremiiforme and C. dermatis, respectively. The upgraded RUO database improved the identification of 8

9 species already represented in the original databases, such as T. inkin and T. asteroides. In addition, mass spectra of Trichosporon faecale, T. coremiiforme, T. ovoides, T. lactis, T. japonicum, C. dermatis, C. jirovecii, C. debeurmannianum, A. mycotoxinivorans, A. montevideense, A. loubieri and A. domesticum had correct species assignment (without misidentifications) by our in-house SuperSpectrum library. The performance of the IVD, the original and upgraded RUO databases for Trichosporon, Cutaneotrichosporon and Apiotrichum species identification is summarized in Table 2. Details of the misidentifications observed for IVD and RUO databases are provided in Table

10 Discussion Despite the good performance for the identification of some relevant species, such as T. asahii, T. asteroides and T. inkin, we showed that the current IVD database from the Vitek MS needs improvement for identification of other relevant species of the genus Trichosporon, and also for the species of the genera Cutaneotrichosporon and Apiotrichum. Furthermore, despite being a rare event, we found genus misidentifications when Cutaneotrichosporon and Apiotrichum isolates were analyzed. Thus, while improvement of the current IVD database of Vitek MS by the manufacturer is pending, we advise Vitek MS users not to abandon traditional phenotypic methods (e.g macro- and micromorphology, hydrolysis of urea) to report an unidentified basidiomycetous yeast, a surrogate marker of echinocandin resistance, while final identification is carried out by a reference laboratory through sequence analysis of the IGS1 or D1/D2 domain of the 26S region of the ribosomal DNA. The RUO database (SARAMIS ) has proven to be an auxiliary tool when the IVD database fails to provide correct Candida species identification (14). On the contrary, in the case of Trichosporon, Cutaneotrichosporon and Apiotrichum species, the RUO database appeared ineffective for a most sensitive identification of those species. Only the addition of in-house SuperSpectra and exclusion of the manufacturer s SuperSpectra, which was related to misidentifications of T. coremiiforme and C. dermatis isolates, were necessary to optimize its performance. Indeed, the identification of C. dermatis has gained relevance since this species was recently related to pan-azole resistance (15). However, like conventional phenotypic method such as Vitek2, Vitek MS and its IVD and RUO databases misidentified all C. dermatis isolates as C. mucoides (16). Despite being genetically close-related 10

11 species, we were able to construct species-specific SuperSpectra of both C. dermatis and C. mucoides, achieving 100% correct species ID for both species in the validation step of our in-house database. The SARAMIS Premium SuperSpectrum tool (biomérieux) has shown to be a useful tool to create species-specific spectral profiles since it compares the biomarkers with the whole SARAMIS spectral archive during the SuperSpectrum construction process (17). A. mycotoxinivorans (former Trichosporon mycotoxinivorans) is now considered a relevant pathogen for patients with cystic fibrosis (18). Moreover, this microorganism has been related to deep-seated infections in immunocompromised patients with invasive disposals in India (19). The use of Bruker s MALDI-TOF MS as a reliable tool for A. mycotoxinivorans species identification has helped to strengthen the epidemiologic link of T. mycotoxinivorans to cystic fibrosis (20, 21). Thus, it appears that inclusion of the species in the database used for clinical diagnosis is now mandatory. In conclusion, Vitek MS databases show good performance for the identification of common relevant species of Trichosporon such as T. asahii, T. inkin, T. asteroides. However, Vitek MS consistently misidentifies C. dermatis as C. mucoides and other Trichosporon, Cutaneotrichosporon and Apiotrichum clinical relevant species remains neglected by the current IVD and RUO databases. The inhouse database built with well-identified organisms of clinically relevant Trichosporon, Cutaneotrichosporon and Apiotrichum species outperformed the current IVD and RUO spectral profile databases. SARAMIS Premium allowed the construction of species-specific SuperSpectra that can differentiate close-related species of Trichosporon, Cutaneotrichosporon and Apiotrichum

12 Acknowledgments We would like to thank Adriana L. Motta and Maria Isabel Cunha for the excellent technical assistance. The Trichosporon, Cutaneotrichosporon and Apiotrichum SuperSpectra produced in this work are freely available by contacting the corresponding author. This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. The work of ALC has a grant from National Counsil of Technological and Scientific Development (CNPQ /2015-8)

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15 Diaz MR, Fell JW High-Throughput Detection of Pathogenic Yeasts of the Genus Trichosporon. J Clin Microbiol 42: Chao Q-T, Lee T-F, Teng S-H, Peng L-Y, Chen P-H, Teng L-J, Hsueh P-R Comparison of the accuracy of two conventional phenotypic methods and two MALDI-TOF MS systems with that of DNA sequencing analysis for correctly identifying clinically encountered yeasts. PloS One 9:e Oliveira dos Santos C, Zijlstra JG, Porte RJ, Kampinga GA, van Diepeningen AD, Sinha B, Bathoorn E Emerging pan-resistance in Trichosporon species: a case report. BMC Infect Dis 16: De Figueiredo DSY, de Almeida JN, Motta AL, Castro E Silva DM, Szeszs MW, Del Negro GMB Evaluation of VITEK 2 for discriminating Trichosporon species: misidentification of Trichosporon non-t. asahii. Diagn Microbiol Infect Dis 80: Stephan R, Ziegler D, Pflüger V, Vogel G, Lehner A Rapid genus- and species-specific identification of Cronobacter spp. by matrix-assisted laser desorption ionization-time of flight mass spectrometry. J Clin Microbiol 48: Hickey PW, Sutton DA, Fothergill AW, Rinaldi MG, Wickes BL, Schmidt HJ, Walsh TJ Trichosporon mycotoxinivorans, a novel respiratory pathogen in patients with cystic fibrosis. J Clin Microbiol 47: Dabas Y, Xess I, Kale P Molecular and antifungal susceptibility study on trichosporonemia and emergence of Trichosporon mycotoxinivorans as a bloodstream pathogen. Med Mycol. pii: myw

16 Shah AV, McColley SA, Weil D, Zheng X Trichosporon mycotoxinivorans infection in patients with cystic fibrosis. J Clin Microbiol 52: Goldenberger D, Hinić V, Prince SS, Tamm M, Balestra A-M, Hohler D, Frei R A case report of a cystic fibrosis patient with repeated isolation of Trichosporon mycotoxinivorans identified by a novel short-extraction method. BMC Infect Dis

17 392 Table 1. Organisms used to construct the in-house SuperSpectra library Strain name Species (In-house SuperSpectrum No.) NCBI access number CBS2479 Trichosporon asahii (01) EU CBS2530 T. asahii (01) EU HCFMUSP- T. asahii (02) KX TA01 HCFMUSP- T. asahii (03) KX TA02 HCFMUSP- T. inkin (01) KY DLC03 HCFMUSP- T. inkin (01) KY DLC06 HCFMUSP- T. inkin (02) KY DLC11 HCFMUSP- T. inkin (03) KY DLC15 CBS4828 Trichosporon faecale (01) KM L8339 T. faecale (01) KM CBS2482 Trichosporon coremiiforme AB (01) L9178 T. coremiiforme (01) KX LEMI53 Trichosporon asteroides KY (01) LEMI54 T. asteroides (01) KM LEMI55 T. asteroides (02) EU LEMI53 T. asteroides (03) KY CBS8641 Trichosporon japonicum AF (01) CBS7556 Trichosporon ovoides (01) AB CBS9051 Trichosporon lactis (01) AJ CBS2043 Cutaneotrichosporon AY dermatis (01) HCFMUSP- C. dermatis (01) KY DLC10 F0801 C. dermatis (02) KY CBS7625 Cutaneotrichosporon AB mucoides (01) CBS6864 Cutaneotrichosporon AB jirovecii (01) F2601 C. jirovecii (01) KY HCFMUSP- Cutaneotrichosporon KY DLC101 debeurmannianum (01) CBS9756 Apiotrichum KX mycotoxinivorans (01) CBS10094 A. mycotoxinivorans (01) KX

18 CBS7719 Apiotrichum loubieri (01) KY CBS8605 Apiotrichum montevideense KY (01) F0501 A. montevideense (01) KY CBS8280 Apiotrichum domesticum (01) JN

19 Table 2. Performance of Vitek MS according to the different databases for the identification of Trichosporon, Cutaneotrichosporon and Apiotrichum clinically relevant species. Species (No.) IVD database Original RUO database Upgraded RUO database Correct Correct Correct % confidence % confidence % confidence species ID* species ID species ID level level level (%) (%) (%) Trichosporon species (n=76) 56 (73.6) (68.4) (100) Trichosporon asahii (n= 26) 26 (100) (100) (100) Trichosporon inkin (n= 21) 19 (90.4) (76.1) (100) 99.9 Trichosporon faecale (n= 13) # 0 (0) - 0 (0) - 13 (100) Trichosporon asteroides (n= 10) 10 (100) (100) (100) Trichosporon coremiiforme (n= 3) 0 (0) - 0 (0) - 3 (100) 99.9 Trichosporon ovoides (n=1) 1 (100) (0) - 1 (100) 99.9 Trichosporon lactis (n=1) 0 (0) - 0 (0) - 1 (100) 99.9 Trichosporon japonicum (n=1) 0 (0) - 0 (0) - 1 (100) 99.9 Cutaneotrichosporon species (n=20) 1 (5) (5) (100) Cutaneotrichosporon dermatis (n=12) 0 (0) - 0 (0) - 12 (100) Cutaneotrichosporon jirovecii (n= 4) ## 0 (0) - 0 (0) - 4 (100) Cutaneotrichosporon mucoides (n=1) 1 (100) (100) (100) 99.9 Cutaneotrichosporon debeurmannianum (n=3) 0 (0) - 0 (0) - 3 (100) 99.9 Apiotrichum species (n=11) 0 (0) - 0 (0) - 11 (100) Trichosporon mycotoxinivorans (n= 5) 0 (0) - 0 (0) - 5 (100) 99.9 Trichosporon montevideense (n= 4) ** 0 (0) - 0 (0) - 4 (100) Trichosporon loubieri (n= 1) 0 (0) - 0 (0) - 1 (100) 99.9 Trichosporon domesticum (n=1) 0 (0) - 0 (0) - 1 (100)

20 * ID= identification; # one isolate had identification to genus level by the RUO database; one isolate misidentified as Trichosporon asahii by the RUO database; All isolates misidentified as Trichosporon mucoides by the IVD database, while eight isolates were misidentified as Trichosporon cutaneum/mucoides and four were classified as Trichosporon sp. by the RUO database; ## one isolate misidentified as Candida valida by the IVD database (confidence level 50%); ** one isolate misidentified as Candida albicans by the IVD database (confidence level 95.4%)

21 410 Table 3. Misidentifications produced by the IVD and RUO databases. IVD database Species Misidentification Persistant Spectral profile related to (mis-id*/tested organisms) (confidence level ID) Mis-ID** misidentification Trichosporon inkin (2/21) # Trichosporon ovoides ( %) No Not accessible Cutaneotrichosporum dermatis Trichosporon mucoides (99.9%) Yes Not accessible (12/12) Cutaneotrichum jirovecii (1/4) Candida valida (50%) No Not accessible Apiotrichum montevideense (1/5) Candida albicans (95.4%) No Not accessible RUO database Species Misidentification Persistant Spectral profile related to (mis-id/tested organisms) (confidence level id.) Mis-ID** misidentification Trichosporon coremiiforme (2/3) Trichosporon asahii (80-90%) Yes Trichosporon_asahii_1_ C. dermatis (12/12) Trichosporon cutaneum/mucoides Yes Trichosporon_cutaneum/mucoides_1_ 21

22 ( %) 411 * ID= identification; **after repeated analysis; # species included in the database 22