MALDI-TOF mass spectrometry for rapid identification of clinical fungal isolates based on ribosomal protein biomarkers

Journal of Microbiological Methods 109 (2015) 93–105

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Journal of Microbiological Methods

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MALDI-TOF mass spectrometry for rapid identification of clinical fungalisolates based on ribosomal protein biomarkers

Ashutosh Panda a, Anup K. Ghosh b, Bijay R.Mirdha a,⁎, Immaculata Xess a, Saikat Paul b, Jyotish C. Samantaray a,Alagiri Srinivasan a, Shehla Khalil a, Neha Rastogi a, Yubhisha Dabas a

a Department of Microbiology, All India Institute of Medical Sciences, New Delhi 110029, Indiab Department of Medical Microbiology, Post Graduate Institute, Chandigarh 160012, India

⁎ Corresponding author.E-mail address: [email protected] (B.R. Mirdh

http://dx.doi.org/10.1016/j.mimet.2014.12.0140167-7012/© 2014 Elsevier B.V. All rights reserved.

a b s t r a c t

Article history:Received 20 August 2014Received in revised form 18 December 2014Accepted 18 December 2014Available online 23 December 2014

Keywords:Matrix assisted laser desorption ionization-time of flight mass spectrometryFungal isolatesRapidIdentification

This study aimed to evaluate the identification of clinical fungal isolates (yeast and molds) by protein profilingusing Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF/MS). A total of125 clinical fungal culture isolates (yeast and filamentous fungi) were collected. The test set included 88 yeastisolates (Candida albicans, Candida glabrata, Candida guilliermondii, Candida kefyr, Candida krusei, Candidaparapsilosis, Candida rugosa, Candida tropicalis and Cryptococcus neoformans) and 37 isolates of molds(Alternaria spp., Aspergillus flavus, Aspergillus fumigatus, Aspergillus niger, Cunninghamella spp., Histoplasmacapsulatum,Microsporum gypseum,Microsporum nanum, Rhizomucor spp. and Trichophyton spp.). The correlationbetweenMALDI TOFMS and conventional identification for all these 125 fungal isolates included in the studywas87.2% at the species level and 90.4% at the genus level.MALDI TOFMS results revealed that the correlation in yeast(n= 88) identification was 100% both at the genus and species levels whereas, the correlation inmold (n= 37)identification was more heterogeneous i.e. 10.81% isolates had correct identification up to the genus level, 56.7%isolates had correct identification both at the genus and species levels, whereas 32.42% isolateswere deemedNotReliable Identification (NRI). But,with themodification in sample preparation protocol formolds, therewas a sig-nificant improvement in identification. 86.4% isolates had correct identification till the genus and species levelswhereas, only 2.7% isolates had Not Reliable Identification. In conclusion, this study demonstrates that MALDI-TOF MS could be a possible alternative to conventional techniques both for the identification and differentiationof clinical fungal isolates. However, the main limitation of this technique is that MS identification could be moreprecise only if the reference spectrum of the fungal species is available in the database.

© 2014 Elsevier B.V. All rights reserved.

1. Introduction

Fungal infections are of major concern especially in the immuno-compromised individuals as well as in immunocompetent hosts. Theseinfections could be both from exogenous and endogenous sources andare often seen in patients with hematological malignancies, transplantrecipients and HIV/AIDS. The most common endogenous opportunisticfungal infection is caused by Candida spp., whereas predominant exog-enous fungal infections could be due to Cryptococcus neoformans, Asper-gillus spp. and zygomycetes. Identification of fungal pathogens usingconventional phenotypic methods is often subjective, time-consumingand may sometimes be inconclusive especially for unusual yeasts, der-matophytes and molds. There is advent of pre-emptive therapy basedonly on clinical observation which at times leads to unnecessary useof antifungal agents causing toxicity in the patients. This imparts theneed of rapid and simple techniques for the identification of fungal

a).

species to optimize appropriate antifungal treatment for the specificinfection.

For rapid identification there are commercially available methodswhich are based on the biochemical characteristics of the isolates likechromogenic agar media (CHROM Agar), biochemical and enzymaticcard panels, e.g., the API ID 20C, API ID 32C, and automated system foridentification and characterization and antifungal susceptibility testingi.e. Vitek ID YST systems (bioMérieux, Nürtingen, Germany). However,there are inherent disadvantageswith these techniques including limit-ed database and often reported misidentification (Coignard et al., 2004;Massonet et al., 2004).

In recent times, the identification of microbial species using proteo-mic approach is becoming popular as an alternative to chromatographicand even DNA-dependent methods. One of such methods is matrixassisted laser desorption ionization-time of flight mass spectrometry(MALDI TOF MS); this technique is based upon the detection of highlyabundant proteins in a mass range of 2–20 kDa by calculating theirmass (m) to charge (z),m/z values. Thus, a typical spectrum (MS finger-print) is generated for each microorganism which matched with the

Table 1Correlation between conventional and MALDI-TOF MS identification of yeasts.

Conventional identification(Number of isolates) (n = 88)

MALDI TOF MS identification

NRIa Genus levelb Species levelc Discrepancy

Candida albicans (19) – – 19 (100%) NilCandida glabrata (12) – – 12 (100%) NilCandida guilliermondii (4) – – 4 (100%) NilCandida kefyr (9) – – 9 (100%) NilCandida krusei (7) – – 7 (100%) NilCandida parapsilosis (8) – – 8 (100%) NilCandida rugosa (2) – – 2 (100%) NilCandida tropicalis (14) – – 14 (100%) NilCryptococcus neoformans (13) – – 13 (100%) Nil

Note: NRI— Not Reliable Identification.a MALDI-TOF score b 1.7.b MALDI-TOF score ≥ 1.7.c MALDI-TOF score ≥ 2.0.

Table 3Correlation between conventional andMALDI-TOFMS identification ofmoldswith normalextraction protocol.

Conventional identification(Number of isolates)(n = 37)

MALDI TOF MS identification

NRIa Genuslevelb

Species levelc Discrepancy

Alternaria spp. (1) – – 1 (100%)A. alternata

–

Aspergillus flavus (8) – – 8 (100%) –

Aspergillus fumigatus (10) – 1 (10%) 9 (90%) –

Aspergillus niger (4) – – 4 (100%) –

Cunninghamella spp. (1) – – 1 (100%)C. bertholletiae

–

Histoplasma capsulatum (1) 1 (100%) – – –

Microsporum gypseum (2) – – 2 (100%) –

Microsporum nanum (2) – – 2 (100%) –

Rhizomucor spp. (1) – – 1 (100%)R. pusillus

–

Trichophyton mentagrophytes(4)

– – 4 (100%) –

Trichophyton tonsurans (3) – 3 (100%) – –

Total n = 1 n = 4 n = 32

Note: NRI— Not Reliable Identification.a MALDI-TOF score b 1.7.b MALDI-TOF score ≥ 1.7.c MALDI-TOF score ≥ 2.0.

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reference spectra and thereby providing identification of the organism(Panda et al., 2013). The MALDI-TOF MS is being commonly used forthe identification of various microorganisms such as Gram positive bac-teria (Bizzini and Greub, 2010; Steensels et al., 2011; Barbuddhe et al.,2008; Bernardo et al., 2002; Friedrichs et al., 2007; Grosse-Herrentheyet al., 2008; Moura et al., 2008; Ryzhov et al., 2000; Schulthess et al.,2013) and Enterobacteriaceae (Conway et al., 2001; McElvaniaTekippe et al., 2013), as well as for the identification of nonfermentingbacteria (Degand et al., 2008; Mellmann et al., 2008, 2009; Minanet al., 2009) and mycobacteria (Panda et al., 2013; Lefmann et al.,2004; Pignone et al., 2006; Hettick et al., 2006; Shitikov et al., 2012; ElKhechine et al., 2011; Saleeb et al., 2011; Lotz et al., 2010). Many fungalgenera of different filamentous fungi including most dermatophytes(Epidermophyton, Trichophyton and Microsporum) (Erhard et al., 2008;Nenoff et al., 2013; Packeu et al., 2013) and zygomycetes (Rhizopus,Mucor, Rhizomucor, Cunninghamella and Lichtheimia) have beenestablished and various clinical yeast isolates (Candida spp., andCryptococcus spp.) (Cassagne et al., 2011; Wang et al., 2014; Schrödlet al., 2012) have also been successfully identified by MALDI-TOFMS. Other fungal genera such as Aspergillus (Cassagne et al., 2011;Lau et al., 2013), Fusarium (Marchetti-Deschmann et al., 2012) andPenicillium (Hettick et al., 2008; Posch et al., 2013) have also been re-ported to be identified successfully by MALDI-TOF MS. Although thereare many reports on fungal identification from western world, thereare very few reports from developing nations where identification andcharacterization of the fungal isolates are done following proteomic ap-proach (Lau et al., 2013; Marklein et al., 2009; Qian et al., 2008; Blattelet al., 2013).

Table 2Correlation between conventional and MALDI-TOF MS identification of molds with normal ext

Conventional identification(Number of isolates) (n = 37)

MALDI TOF MS identification

NRIa G

Alternaria spp. (1) – 1Aspergillus flavus (8) – –

Aspergillus fumigates (10) 1 (10%) 1Aspergillus niger (4) 1 (25%) –

Cunninghamella spp. (1) 1 (100%) –

Histoplasma capsulatum (1) 1 (100%) –

Microsporum gypseum (2) 2 (100%) –

Microsporum nanum (2) 2 (100%) –

Rhizomucor spp. (1) 1 (100%) –

Trichophyton mentagrophytes (4) 2 (50%) –

Trichophyton tonsurans (3) 1 (33.3%) 2Total n = 12 n

Note: NRI— Not Reliable Identification.a MALDI-TOF score b 1.7.b MALDI-TOF score ≥ 1.7.c MALDI-TOF score ≥ 2.0.

In the present study, we attempt to evaluate the applicability ofMALDI-TOF MS for the identification of clinical fungal isolates (yeastsand filamentous fungi). Furthermore, an attempt was made to enhancethe identification protocols for clinically important molds. The proteo-mic approach for identification was further compared/ correlated withconventional and morphological identifications.

2. Material and methods

In the present study, a total of 125 fungal isolates were collectedfromdifferent clinical samples (blood, urine, pus, biopsy, swab, cerebro-spinal fluid, respiratory tract and wound specimens). All these clinicalsamples were processed using conventional mycological techniquesand biochemical characterizationwas done for identification. These iso-lates were simultaneously identified by MALDI-TOF MS and the resultswere compared.

The following available ATCC reference strains such as Candidaalbicans ATCC 10231; Candida krusei ATCC 6258; Candida parapsilosisATCC 22019; Candida guilliermondii ATCC 6260; Candida kefyrATCC 204093; C. neoformans ATCC 14151; C. neoformans ATCC

raction protocol.

enus levelb Species levelc Discrepancy

(100%) – –

8 (100%) –

(10%) 8 (80%) –

3 (75%) –

– –

– –

– –

– –

– –

2 (50%) –

(66.66%) – –

= 4 n = 21

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14116; and Candida glabrata ATCC 15126 were used as controls in thisstudy.

2.1. Examination of clinical samples using conventional technique

Examinations of clinical specimenswere carried out using directmi-croscopy i.e. Gram's stain, India ink preparation and 10% potassium hy-droxide (KOH) mount. Culture was done on Sabouraud's dextrose agar(SDA) [Himedia Laboratories, Mumbai, India] containing gentamicin.

a) Candida albicans

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Fig. 1.MALDI-TOF MS mass spectra of yeasts: Candida albicans (a), Candida glabrata (b), Candidrugosa (g), Candida tropicalis (h), Cryptococcus neoformans (i).

Yeasts were identified by using Germ Tube test, morphological featureson Corn Meal Agar, urease production, sensitivity to cycloheximide andreduction of dye on Triphenyl Tetrazolium Chloride (TTC medium) andCHROM Agar. Carbohydrate Fermentation Test and Carbohydrate As-similation Testwere performed for genus differentiation and speciation.

Molds were identified on the basis of their growth on SDA and wereconfirmed by examining features microscopically. They were furthersubcultured on Potato Dextrose Agar (PDA) for better sporulation andwere incubated at different temperatures (25 °C and 37 °C).

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a guilliermondii (c), Candida kefyr (d), Candida krusei (e), Candida parapsilosis (f), Candida

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Fig. 1 (continued).

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2.2. Sample preparation for MALDI-TOF MS

Ethanol/formic acid extraction procedure was followed according tothe manufacturer's instruction (Bruker Daltonik GmbH, Bremen, andGermany). Briefly, clinical isolates were transferred into the 1.5 mlscrew cap extraction tube with an inoculation loop or pipette tip andweremixed thoroughly in 300 μl of double distilledwater. Absolute eth-anol (0.9ml)was added, the contents of the tubeswere carefullymixed,the tubeswere then centrifuged at 13,000×g for 2min; the supernatantwas discarded and the pellet was air dried. Approximately 10 μl of the

pellet was mixed thoroughly with 50 μl of formic acid (70%), before ad-dition of an equivalent volume of Acetonitrile. The mixture was centri-fuged at 13,000 ×g for 2 min, and 1 μl of the supernatant was placedonto a ground steel MALDI target plate. This was allowed to dry atroom temperature. Subsequently, each sample was overlaid with 1 μlof matrix solution, which consisted of a saturated solution of α-cyano-4 hydroxy-cinnamic acid (HCCA) in 50% Acetonitrile and 2.5%trifluoroacetic acid (final concentration: 10 mg HCCA/ml) and air-dried at room temperature. TheMALDI-TOFMS target was subsequent-ly introduced into the MALDI-TOF mass spectrometer for automated

e) Candida krusei

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f) Candida parapsilosis

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Fig. 1 (continued).

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measurement and data interpretation. For identification of yeasts andmolds, all the sampleswere blinded andwere run in duplicates. Individ-uals performing a particular test for identification were unaware of theresults obtained from the other.

2.2.1. Modified sample preparation protocol for mold identification byMALDI-TOF MS

The sample preparation protocol wasmodified and standardized formolds. Briefly, 30 ml glass screw cap tubes containing Sabouraud

dextrose broth were inoculated with mold and placed on a rotospin(Tarsons #3070) and incubated overnight or until enough biologicalmaterial is observed. The growth was then centrifuged at 4000 rpmfor 10min to settle down the filamentous fungi sediment to the bottomof the tube. 1.5 ml of the sediment was further taken in a 2 mlmicrocentrifuge tube and centrifuged for 10min at 13,000 rpm. The su-pernatant was discarded carefully and 1ml of distilled water was addedto the pellet and vortexed for 1min, followed by repeatedwashing for 2times. The pellet thus obtainedwas further processed by ethanol/formic

g) Candida rugosa

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h) Candida tropicalis

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Fig. 1 (continued).

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acid extraction procedure and mechanical rupture of the growth withglass beads (Sigma #G8772) as mentioned above.

2.3. Instrumentation

All the samples were analyzed using a microflex LT MALDI-TOF MSinstrument (Bruker Daltonik GmbH, Bremen, Germany). The spectrawere recorded in the linear positive mode at a laser frequency of20 Hz within a mass range of 2 to 20 kDa. Various parameter settings

for microflex instrument were as follows i.e. ion source 1 at 20 kV, ionsource 2 at 18.5 kV, lens at 8.5 kV, pulsed ion extraction of 250 ns andno gating.

2.4. Instrument calibration

Freshly prepared Bruker Bacterial Test Standard Escherichia coli(#255343) (Bruker Daltonik GmbH, Bremen, Germany) was used asthe reference strain for the calibration and instrument parameter

i) Cryptococcus neoformans

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Fig. 1 (continued).

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optimization as instructed by the manufacturer. MALDI Biotyper Cali-bration Procedure was followed according to the manufacturer's in-structions. Briefly, right flexControl method was used and one sumspectrum was measured at the desorption level of the laser energyusing inbuilt AutoXmethod. The software generally has the ability to se-lect the calibration peaks in the range of ±300 ppm automatically andto perform calibration. Once the calibration is achieved, the calibrationvalues are saved and further applied to the measurement of clinical ex-perimental strains.

2.5. Data processing

Initial manual/visual estimation of the mass spectra was per-formed using the FlexAnalysis 2.4 software (Bruker Daltonik GmbH,Germany). For automated data analysis, raw spectra were processedusing the MALDI Biotyper 3.1 software (Bruker Daltonik GmbH,Germany)with default settings. The smoothing, normalization, baselinesubtraction and peak picking were carried out by the software, therebycreating a list of the most significant peaks of a spectrum (m/z valueswith a given intensity). The generated peak lists derived from thefungal MALDI-TOF profile mass spectra were compared with eachentry of the MALDI Biotyper database. An updated database fromthe manufacturer (Bruker Daltonik GmbH, Germany) for fungalstrains was used for the analysis. There are currently more than(five hundred for fungus) six thousand (total) references, using thestandard parameters of the pattern-matching algorithms. These algo-rithms have different mathematical approaches that have alreadybeen described (Arnold and Reilly, 1998; Jarman et al., 2000; Pinedaet al., 2000). The results of the pattern-matching process wereexpressed as log (score) values, computed by comparison of the peaklist for an unknown isolate with the reference main spectral patternMSP in the database. The log (score) value ranged from 0 to 3, a log(score) value ≥1.7 is indicative of a close relationship (i.e., at thegenus level) and a log (score) value ≥2.0 is the set threshold for amatch at the species level.

2.6. Criteria for identification and discrepant analysis

When routine conventional identification and MALDI-TOF MS hadexactly the same identification to the species level, the identificationwas considered final. Inaccurate identification at the genus level wasconsidered as a major error.

3. Result

In this study, a total of 125 clinical fungal culture isolates (yeast andfilamentous fungi) and 9 ATCC controls were analyzed using MALDI-TOFMS. It was found that all the 9 ATCC reference strainswere correctlyidentified byMALDI TOFMSwith a log (score) values of N2.30 indicativeof ‘highly probable species identification’. Upon comparing and analyz-ing both the MS fingerprint patterns obtained from 125 isolates withthat from the conventional tests, it was observed that the correlationin yeast (n = 88) identification was extremely high (100%) both atthe genus and species levels (Table. 1). On the other hand, the correla-tion in mold identification was more heterogeneous when the normalextraction procedure was followed as that of yeast (Table 2). Amongthe total 37 mold isolates, only 12 (32.42%) isolates were deemed“Not Reliable Identification (NRI)”, whereas 4 (10.81%) isolates had cor-rect identification up to the genus level and the rest 21 (56.7%) isolatesup to both the genus and species levels.

Our modified protocol for sample preparation has significantly im-proved the identification of molds by MALDI-TOF MS (Table 3).Among the total 37 mold isolates, only one isolate (2.7%) was deemedNRI, whereas 4 (10.8%) isolates had correct identification up to thegenus level only and the rest 32 (86.4%) isolates had correct identifica-tion till the genus and species levels.

The correlation betweenMALDI-TOFMS and conventional identifica-tion for all 125 fungal isolates included in the study was 96%((88 + 32) / 125) at the species level and 99.2% ((88 + 32 + 4) / 125)at the genus level. Only 2.7% isolates (1/125) had NRI when comparedto conventional methods of identification. The spectral processing

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results have shown that there are signature peaks for a particular species(Figs. 1 & 2).

4. Discussion

Diagnosis of fungal infections is often plagued with ambiguity and itis a time consuming process requiring 2–4 weeks for culture positivity,therebydelayingdefinitive therapeutic intervention. For rapid diagnosisand successful disease management there is a need for development of

a) Alternaria alternata

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Fig. 2.MALDI-TOF MS mass spectra of molds: Alternaria alternata (a), Aspergillus flavus (b), Aspgypseum (f), Microsporum nanum (f), Rhizomucor pusillus (g), Trichophyton mentagrophytes (h)

rapid and reliable identification techniques.Molecular techniques avail-able for the early diagnosis of fungal infections are very specific and lesstime consuming. However, these techniques are largely restricted to re-search and reference laboratories. Sophisticated technique such asMALDI-TOF MS has recently been used as a useful and reliable alterna-tive for the identification of a wide array of bacterial species (Bizziniand Greub, 2010; Steensels et al., 2011; Barbuddhe et al., 2008;Bernardo et al., 2002; Friedrichs et al., 2007; Grosse-Herrenthey et al.,2008; Moura et al., 2008; Ryzhov et al., 2000; Schulthess et al., 2013;

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ergillus fumigatus (c), Aspergillus niger (d), Cunninghamella bertholletiae (e),Microsporum.

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Fig. 2 (continued).

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Conway et al., 2001;McElvania Tekippe et al., 2013; Degand et al., 2008;Mellmann et al., 2008, 2009; Minan et al., 2009; Lefmann et al., 2004;Pignone et al., 2006; Hettick et al., 2006; Shitikov et al., 2012; ElKhechine et al., 2011; Saleeb et al., 2011; Lotz et al., 2010). However,only few studies have assessed the performance of MALDI-TOF MS-based identification under routine laboratory conditions for the fungalisolates (Panda et al., 2013; Marklein et al., 2009; Iriart et al., 2012;Ferreira et al., 2013; Posteraro et al., 2013). In our study, MALDI-TOFMS could accurately identify all the ATCC controls in duplicate. The

results obtained from our study suggest that the identification of differ-ent yeast and mold species is possible using MALDI-TOF MS. Since ourstudy was a blinded one with the samples being processed and run induplicate, the reproducibility of the instrumentwas tested andwas sub-sequently found to be consistent for all the samples. The MALDI MSmass spectral patternswere also reproducible for the isolates belongingto the same genus and species.

In the present study a total of 125 fungal isolates were evaluated.Among these 125 isolates 88 isolates were yeast and the rest 37 isolates

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Fig. 2 (continued).

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were molds. Identification by MALDI-TOF MS for the yeast isolatesyielded a valid score for all the 88 isolates till the species level withthe log score value ≥2.0. The accuracy for identification of yeast usingMALDI TOF MS was 100% up to the species level. MALDI-TOF MS per-formed well for medically important yeast identification; similar con-clusion has been reached by various other studies (Ferreira et al.,2013; Posteraro et al., 2013; Chalupová et al., 2014). The identificationof yeast using MALDI TOFMS allows high reliability with low time con-sumption, and avoids the use of biochemical identification systems andthe chromogenic agar media.

For identification of molds by MALDI TOF MS two strategies werefollowed, initially the identification was done by the same procedureas that of yeast identification. The results obtained by this procedureyielded a valid score for only 21 (56.75%) isolates out of total 37 isolatestill the species level, with the log score value of≥2.0. Among the rest 16isolates, 4 isolates yielded a valid log score value of ≥1.7 indicative of aclose relationship at the genus level and 12 isolates yielded a log scorevalue of b1.7 indicating Not Reliable Identification (NRI). Out of twelve(n= 12) isolates which were deemed NRI byMALDI TOF MS, 5 isolates(1 isolate each of Cunninghamella spp., Histoplasma capsulatum and

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Rhizomucor spp. and 2 isolates of Microsporum nanum) were deemedNRI status due to the non-availability of the MSP in the database. Suchtaxonomical discordances can be easily corrected by an update of thedatabase. The accuracy for identification of molds using MALDI TOFMS was 56.7% at the species level and 67.56% at the genus level. Thisheterogeneity can be associated with the complex protein profile ofmolds and the variation of the protein profiles with the age of the cul-ture (Ferreira et al., 2013).

The identification of molds by MALDI-TOF MS was significantly im-provedwhen followed by the secondmodified protocol andwith an up-date of the database by the manufacturer. This protocol reduced theeffects of culture conditions and aided in the production of a uniformmycelium. This method yielded the valid score of ≥2.0 at the specieslevel for 32 isolates of total 37 mold isolates, only one isolate(Histoplasma capsulatum) was deemed NRI, due to the non-availabilityof the peak in the database. Studies on MALDI-TOF MS performance

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concerning dermatophytes are limited (Erhard et al., 2008; Gautieret al., 2014). One of such studies has indicated a low level of identifica-tion by MALDI TOF MS for mold isolates and has advocated improvingthe extraction protocol (Ferreira et al., 2013). The results obtained inthis study have shown that with the improvement of the extractionand sample preparation protocol a good accuracy in case of mold iden-tification can also be achieved.

On carrying out an extensive analysis of the MALDI TOF MS finger-prints, a consistent spectral pattern among all the isolates at the specieslevel was observed. Since a majority of the protein signals lie between 2and 13 kDa, it could imply that a significant portion of the signals werederived from the ribosomal proteins that range from 2000 to 20,000 Da(Panda et al., 2013; Maier and Kostrzewa, 2007). Within the observedmass range, a few unique signals were conserved among the isolate ofsame species (Figs. 1 & 2). Such conclusions have been reported byothers (Panda et al., 2013; Mellmann et al., 2008; Minan et al., 2009;Lefmann et al., 2004).

The identification using MALDI TOF MS method based on the ribo-somal protein biomarkers could analyze samples rapidly within mi-nutes after culture positivity. The time taken from extraction toidentification of a single sample takes approximately 23 min (Table 4),but batch processing reduced the time taken for the identification ofeach sample and thereby facilitated high throughput outcome. In addi-tion to this, low running cost, non-requirement of high technical exper-tise and the simple extraction procedure provide MALDI-TOF MS an

Table 4Time kinetics for MALDI-TOF MS.

Workflow Duration per sample

Extraction 8 minApplication on plate 1 minDrying 5 minApplication matrix 1 minDrying 5 minRead into system 2 minTime to result 35 sTotal 22.35 min

edge over the othermethods for identification. Nonetheless the applica-bility must be carefully performed. Our observations have shown thatapplication of too much material reduces the quality of the result. Fur-thermore, care should be taken when the sample is being overlaidwith the matrix solution to not to induce a liquid smear betweenspots, which may result in cross contamination.

In conclusion, our study demonstrated that MALDI-TOFMS could bea possible feasible alternative diagnostic tool for rapid and accurateidentification and differentiation of fungal isolates. The accuracy foridentification of yeast is very high, when compared to molds. Improve-ment in the extractionmethodsmay possibly improve the identificationof molds using MALDI TOF MS.

Conflicts of interest

None of the authors have any conflicts of interest.

Acknowledgments

We would like to acknowledge Mr. Rajesh Vashisht at BrukerDaltonik Pvt. Ltd. for all his technical assistance; Dr. ArunalokeChakrabarti at Post Graduate Institute, Chandigarh, India, for his invalu-able support and guidance. We would further like to extent our thanksto the authorities at All India Institute of Medical Sciences (AIIMS), NewDelhi, India for providing us with the financial support for this study.

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