efficient identification of malassezia yeasts by matrix-assisted laser desorption ionization-time of...

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Article type : Original Article

Efficient identification of Malassezia yeasts by matrix-assisted laser desorption ionization-

time of flight mass spectrometry (MALDI-TOF MS)

A. Kolecka1, K. Khayhan1,2, M. Arabatzis3, A. Velegraki3, M. Kostrzewa4, A. Andersson5, A.

Scheynius5, C. Cafarchia6, R. Iatta6, M.T. Montagna7, S. Youngchim8, F.J. Cabañes9, P.

Hoopman1, B. Kraak1, M. Groenewald1, T. Boekhout1,10,11

Running title: MALDI-TOF/MS identification of Malassezia spp.

1CBS-KNAW, Fungal Biodiversity Centre, Utrecht, the Netherlands.

2Department of Microbiology and Parasitology, Faculty of Medical Sciences, University of

Phayao, Phayao, Thailand.

This article is protected by copyright. All rights reserved.

3Research Mycology Laboratory (K.A. 70/3/6915), Microbiology Department, Medical School

of University of Athens, Athens, Greece.

4Bioanalytical Development, Bruker Daltonics GmbH, Bremen, Germany.

5Karolinska Institutet, Translational Immunology Unit, Department of Medicine Solna,

Stockholm, Sweden.

6Department of Veterinary Medicine, Aldo Moro University of Bari, Valenzano, Bari, Italy.

7Department of Biomedical Science and Human Oncology, Section of Hygiene, Aldo Moro

University of Bari, Bari, Italy.

8Department of Microbiology, Faculty of Medicine, Chiang Mai University, Chiang Mai,

Thailand.

9Department of Animal Health and Anatomy, Universitat Autònoma de Barcelona, Bellaterra,

Barcelona, Spain.

10Department of Internal Medicine and Infectious Diseases, University Medical Center, Utrecht,

the Netherlands.

11Department of Dermatology, Shanghai Key Laboratory of Molecular Medical Mycology,

Second Military Medical University, Changzheng Hospital, Institute of Dermatology and

Medical Mycology, Shanghai, People's Republic of China.

Corresponding author: Teun Boekhout, Department of Yeast Research, CBS-KNAW Fungal

Biodiversity Centre, Uppsalalaan 8, 3584CT Utrecht, The Netherlands.


Tel. +31 30 2122 600, Fax. +31 30 2512 097

e-mail: [email protected]

Statement of all funding sources that supported the work:

This publication was made possible by a NPRP grant 5-298-3-086 from the Qatar National

Research Fund (a member of the Qatar Foundation) to Teun Boekhout. The statements herein are

solely the responsibility of the authors. Anna Kolecka received a travel grant from the Walter

Gams non-profit foundation Studienstiftung Mykologische Systematik und Ökologie to attend

the 5th FEBS Advanced Lecture Course Human Fungal Pathogens: Molecular Mechanisms of

Host-Pathogen Interactions and Virulence, May 25-31, 2013, La Colle sur Loup, France

(Kolecka et al., abstract C12) where this work was partially presented.

Any conflict of interest:

Markus Kostrzewa is an employee of Bruker Daltonics GmbH (Bremen, Germany), the

manufacturer of the MALDI Biotyper system, which was used for this study. Bruker Daltonics

GmbH did not influence the design of the study. All other authors do not report conflicts of

interest. All authors contributed to the content and the writing of this manuscript.


What’s already known about this topic?

• Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-

TOF MS) has been developed for the rapid identification of microorganisms and proved

to be a robust tool for the recognition of bacterial species.

• Recently, it was shown that MALDI-TOF MS provided reliable identifications of yeasts

and filamentous fungi.

• Identification of Malassezia isolates by routine methods remains laborious and results in

a relative high number of errorneous results.

What does this study add?

• A database of reference mass spectra resulting in efficient and correct identification of all

Malassezia species by MALDI-TOF MS in a short turnaround time.

• MALDI-TOF MS results were consistent with those obtained by sequence analyses.

• The method may efficiently demonstrate the involvement of different Malassezia species

in skin diseases.

• Application of MALDI-TOF MS for the identification of Malassezia isolates is of clinical

importance as fast and reliable identification will result in early application of treatment.


Abstract

Background: Infections caused by Malassezia yeasts are most likely underdiagnosed, because

fatty acid supplementation is needed for growth. Rapid identification of Malassezia species is

essential for appropriate treatment of Malassezia related skin-infections, fungemia and

nosocomial outbreaks in neonates, children and adults and can be live saving for those patients.

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS)

was reported as a rapid and reliable diagnostic tool to identify clinically important yeasts, but so

far no data have been reported on identification of Malassezia isolates with this technique.

Objectives: To create an extensive database of main mass spectra (MSPs) that will allow quick

identification of Malassezia species by MALDI-TOF MS.

Methods: An in-house library of 113 MSPs was created from 48 reference strains from the CBS-

KNAW yeast collection. The in-house library was challenged with two test sets of Malassezia

strains, namely 165 reference strains from the CBS collection and 338 isolates collected in

Greece, Italy, Sweden, and Thailand.

Results: MALDI-TOF MS allowed correct identification of all 14 Malassezia spp. MALDI-TOF

MS results were concordant with those of sequence analyses of the internal transcribed spacers

(ITS1/ITS2) and the D1/D2 domains of the large subunit (LSU) of the ribosomal DNA (rDNA).

Conclusions: Implementation of the MALDI-TOF MS system as a routine identification tool

will contribute to correct identification of Malassezia yeasts with a minimal effort and in a short

turnaround time which is specifically important for the rapid identification of Malassezia in skin

diseases and nosocomial outbreaks.

Key words: lipophilic yeasts, mass spectrometry, identification, skin, nosocomial outbreak


Introduction

Malassezia yeasts are anamorphic basidiomycetes and 14 species of this monophyletic genus are

presently known (1). Findley et al. (2) revealed the presence of eleven Malassezia species as part

of the human skin microbiome. Five species are mainly known from animal skin (i.e. M. caprae,

M. cuniculi, M. equina, M. nana, M. pachydermatis), but can also occur on humans (1, 3).

Depending on the host immune condition, Malassezia yeasts can be a skin-related commensal or

an opportunistic fungal pathogen (3, 4). They occur on healthy and diseased skin of humans and

warm-blooded animals and may be involved in catheter related infections of neonates and adults.

The occurrence of Malassezia species on skin is due to their ability to adapt to dermal

physiological properties (2, 5, 6). Malassezia species are known as etiological agents of skin

diseases, such as pityriasis (tinea) versicolor, folliculitis, seborrheic dermatitis (including

dandruff), and have been associated with several dermal conditions, such as atopic dermatitis,

and psoriasis (1, 4, 7-11). Malassezia species can cause invasive and systemic infections in

neonatal and paediatric patients as well as in adult individuals whose immune system is

suppressed or compromised that usually receive lipid supplementation via central venous

catheters (CVC) (12-19). Malassezia furfur is most commonly found in conjunction with

nosocomial outbreaks in neonatal intensive care units (20, 21), but outbreaks due to M.

pachydermatis and M. sympodialis can occur as well (16, 20, 22, 23). Early onset of antifungal

treatment for these patients is hampered due to difficult diagnostics of Malassezia yeasts and,

consequently, these infections are most likely underdiagnosed.

Before the introduction of molecular methods the identification of Malassezia spp. was usually

based on biochemical characteristics that involve many days, are not always reliable, and have an

error rate of 14 % (1, 3, 24). Additionally, the routine laboratories most commonly use non-lipid


supplemented media, like Sabouraud glucose agar (SGA) to differentiate yeasts, but for the

isolation, enumeration and identification of Malassezia spp. complex and specialized media

should be used (e.g. modified Dixon’s agar, mDA or modified Leeming & Notman agar, MLNA)

(1).

The culture-based conventional identification methods usually provide ambiguous results of

differentiation between Malassezia spp., and thus application of molecular techniques has

resulted in continuous revision of this genus (11). PCR- and sequence-based methods have been

applied to detect and identify Malassezia spp. Restriction fragment length polymorphism (RFLP)

and amplified fragment length polymorphism (AFLP) analyses of rDNA have also been used

(25-29). Non-invasive methods to detect Malassezia species directly from the infected skin

included terminal fragment length polymorphism and real-time PCR (27, 30-33). Sequence

analyses of universal barcoding markers, such as ITS and the D1/D2 regions of the rDNA,

became also the “gold standard” for accurate identification of Malassezia spp. (24, 34, 35) and

allowed recognition of new species (24, 34, 36-38). Pyrosequencing identified 11 Malassezia

species (39). In contrast to the culture-based methods, molecular techniques that involve DNA

can confirm the presence of dead or at least metabolically inert cells of Malassezia on the skin

(11).

Recently, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-

TOF MS) became the state-of-the-art procedure in medical microbiology diagnostics. This

method allows identification of closely related species and subspecies of yeasts with high

resolution (40-44). Many studies showed rapid and reliable identification of microorganisms,

including bacteria and fungi, in clinical microbiological laboratories by this method (45-57).

While the high discriminatory power of species identification by MALDI-TOF MS is certainly


true for pure cultures, the method cannot be applied directly to identify clinical skin samples.

However, it was recently reported, that MALDI-TOF MS was applied on positive blood cultures

without the need for prior culturing and this resulted in reliable identification of Candida spp.

causing bloodstream infection within 30 min (58). Here, we provide evidence that MALDI-TOF

MS is highly suitable to detect, identify and discriminate between all 14 described Malassezia

spp. regardless on the culture media used. Results obtained from the MALDI-TOF MS-based

identification system were compared and validated with isolates from human clinical and

veterinary origins, namely healthy and diseased skin as well as bloodstream isolates.

Material and methods

Strains and culture conditions

Two sets of Malassezia strains representing all 14 species were selected (Table 1-2). The first set

contained 165 type and reference strains from the Yeast Collection of the CBS Fungal

Biodiversity Centre (CBS-KNAW, www.cbs.knaw.nl/collection) (i.e. reference set, Table 1,

Table S1). The second set (i.e. the clinical set, Table 2) consisted of 338 clinical isolates obtained

from four countries, including isolates from infected skin and blood of neonates (Greece),

isolates from the skin of patients with seborrheic dermatitis, atopic dermatitis and from healthy

individuals of which 58 isolates were previously identified as M. sympodialis (5) (Sweden), and

isolates from a nosocomial outbreak among neonates, isolated from their skin, urine, and blood

as well as from CVC and incubators of the ward (Italy). All these isolates were identified at the

genus level by routine methods used in the respective laboratories. The isolates from Thailand

were from the skin of healthy individuals and two isolates from patients with pityriasis

versicolor. The clinical set was complemented by 17 veterinary isolates that were identified in


Italy; 3 came from Brazil and 14 from Italy (59, 60). Validation of these strains at the species

level was achieved by rDNA sequence analysis of ITS and/or D1/D2 for veterinary isolates from

Italy (60) and part of the clinical isolates from Sweden (5), and rDNA sequence analysis of ITS

(GenBank acc. No KC464507; KC464508) and PCR-RFLP for the isolates from Greece (27).

Italian clinical isolates were validated by rDNA sequencing of ITS and D1/D2 in this study. The

Thai sub-set was used without further molecular validation as the results of MALDI-TOF MS

and ITS/D1/D2 sequencing identifications of isolates from the other origins were concordant.

All cultures grew on MLNA plates at 30 oC (1). Prior to MALDI-TOF MS identification, all

Malassezia spp. were re-cultured on mDA plates and cultivated at 30 °C (1). After 24h sufficient

growth was observed for M. pachydermatis and M. furfur, 48-72h were necessary to get

sufficient biomass of M. globosa, M. equina, M. sympodialis, M. slooffiae, M. nana, M. obtusa,

M. caprae, M. yamatoensis, M. dermatis and M. japonica, whereas the slow growing strains of

M. restricta and M. cuniculi needed seven up to 14 days to grow. A set of nine strains of M.

pachydermatis (L2, L9, CBS 1879NT, CBS 1885, CBS 4165, CBS 6534, CBS 6535, CBS

6535_2008, CBS 6537) was sub-cultured on SGA, mDA and MLNA plates and incubated for

24h at 30 oC. Origin and isolation site of L2 and L9 M. pachydermatis strains were previously

described by Theelen et al. (61).

Sequence analyses

DNA extractions were performed from strains grown on mDA plates according to the protocol of

Bolano et al. (62) and ITS and D1/D2 regions of the rDNA were analysed as reported by Gupta

et al. (24). The sequence alignments and consensus sequences were processed as described

previously (44).


MALDI-TOF MS - sample preparation and identification runs

Sample preparation was carried out using the ethanol/formic acid (EtOH/FA) protein extraction

method, according to the Bruker Daltonics GmbH protocol (56). Once sufficient growth of the

tested strains was detected on mDA (additionally on MLNA and SGA for M. pachydermatis),

two loops of yeast biomass (1 µL volume, sterile inoculation loop, Greiner bio-one) were

resuspended in 300 µL of milliQ water followed by 900 µL of absolute ethanol. The volume of

FA used for optimising ranged between 5–30 µL. However, for most of the tested samples and

depending on their hydrophobicity a volume of 10-20 µL of FA was found to be optimal and an

equal volume of acetonitrile (ACN) was added later. The volume of FA used was dependent on

the pellet size and the incubation time was important due to the hydrophobic nature of the cells.

The crude protein extract was used for two purposes: i) to generate Main mass SPectra (MSPs) to

be stored as an entry in the CBS-KNAW in-house library, and ii) for identification runs operated

by flex control version 3.3.108.0 and measured by the MALDI Biotyper RTC software 3.0

(Bruker, Germany).

The strains from the reference and clinical sets were measured and identified by MALDI

Biotyper RTC software 3.0 (Bruker, Germany) by using a 96-spot polished steel target plate

(Bruker, Germany) and Bacterial Test Standard (BTS, Bruker, Germany) as a positive control, as

described by (44). MALDI-TOF MS identification results were achieved automatically as the

log-score values: secure species identification (>2.0), secure genus identification (1.7-2.0) and

not reliable identification (<1.7, NRI). Strains with low scores (<1.7, NRI) and no peaks found

(NPF) were repeated. The identification was considered correct if at least one spot from the

duplicates gave a reliable identification with score >1.7.


CBS-KNAW in-house library

The CBS-KNAW in-house database contained 113 reference MSPs (Fig. 1) from 48 strains,

including type and reference strains covering all 14 Malassezia species (Table S1). These MSPs

were generated using the MALDI Biotyper Automation Control software version 3.0 (Bruker,

Germany). Additionally, ethanol extracts of 39 strains of Malassezia spp. cultivated on MLNA

and mDA were sent to Bruker Daltonics (Bremen, Germany) for creation of MSPs according to

the manufacturer’s standard operating procedures (SOPs). For identification runs CBS in-house

database was used simultaneously with the Bruker Daltonics commercial database (BDAL).

Results

Effect of growth media

Nine strains of M. pachydermatis growing on SGA, mDA and MLNA plates were identified

using the BDAL database alone and in combination with CBS in-house database. Results showed

that when the BDAL database was applied, only five out of nine (5/9) strains on MLNA and

mDA were identified as M. pachydermatis with a log-score >2.0 and three with scores (2.0-1.7).

When growing on SGA, seven (7/9) strains had log-scores >2.0 and one a score (2.0-1.7). One

strain had NRI (<1.7) when grew on SGA, mDA, and NPF on MLNA. Using the CBS in-house

database, irrespective of the media used, eight strains were correctly identified with scores >2.0

and one strain had a score (2.0-1.7) on SGA and mDA, and the same strain had NPF on MLNA.

We recommend the use of mDA plates because oil residues may be transferred from the surface

of MLNA plates together with the yeast biomass, which makes it difficult to dry and measure on

the spots on the target plate.


MALDI-TOF MS based identification of reference CBS-KNAW strains

Identification by MALDI-TOF MS of 165 reference Malassezia strains from CBS resulted in

accurate recognition at the genus and species level for all strains with different log-score values

(Table 1) and was concordant with ITS and D1/D2 sequences of rDNA. One hundred and forty

strains (84.8%) had log-score values >2.0 and 25 strains (15.2%) had values (2.0-1.7) for at least

on one spot from duplicates (Table 1). Strains of M. caprae (n= 3), M. cuniculi (n=1), M. equina

(n=3), M. japonica (n=3), M. nana (n=6), M. sympodialis (n=10) and M. yamatoensis (n=2) were

correctly identified with log-score values >2.0. For other species, namely M. dermatis, M. furfur,

M. globosa, M. obtusa, M. pachydermatis M. restricta, M. slooffiae, 112 strains were correctly

identified with log-score values >2.0 and 25 strains with scores (2.0-1.7).

For 19/165 Malassezia strains identifications provided by MALDI-TOF MS (with log-scores

>2.0 either 2.0-1.7) did not match with the primary identifications given by CBS-KNAW

collection. These initially discrepant data underwent validation by sequencing analyses of the

ITS and D1/D2 regions of the rDNA. The final results confirmed that the MALDI-TOF MS

identifications were correct and consistent with the sequencing results. Thus, nine strains initially

thought to represent M. globosa turned out to be M. furfur, four M. restricta turned out to be M.

slooffiae, from two M. furfur strains one turned out to be M. japonica and one M. pachydermatis,

one M. slooffiae turned out to be M. furfur, and from three M. sympodialis strains one turned out

to be M. furfur, M. nana and M. pachydermatis, respectively.

Identification of clinical isolates by MALDI-TOF MS and ITS/D1-D2 validation

In total, 338 clinical isolates of Malassezia spp. were examined (Table 2). No major errors were

observed in identifications provided by MALDI-TOF MS, as the correct identification at the


genus level was accomplished for all tested isolates and these were concordant with ITS and

D1/D2 validation. Based on the MALDI-TOF MS results, the sub-set of validated clinical

isolates (n=206, 100%) comprised M. dermatis (n=1), M. furfur (n=94), M. globosa (n=20), M.

pachydermatis (n=15), M. slooffiae (n=2), and M. sympodialis (n=74). Identification at the

species level was accomplished for all isolates; 193 isolates (93.7%) with log-score value >2.0,

for 10 isolates (4.8%) with log-scores (2.0-1.7) and three isolates (1.5%) were correctly

identified with log-scores <1.7 (Table 3). These three isolates were veterinary M. pachydermatis

strains from Italy (CD9, CD14, CD69). Three veterinary isolates from Italy (CD864, CD865,

CD866) were identified as M. furfur with log-score values >2.0 which was in concordance to ITS

and D1/D2 rDNA sequence data (60) and clustering of MSPs (Fig. 1).

Because of the robust identification of the above set of reference and clinical isolates, a set of

132 clinical isolates from Thailand was identified by MALDI-TOF MS only. MALDI-TOF MS

identification resulted in correct genus recognition for all isolates (100%). Identification at the

species level was detected with log-scores >2.0 for 128 isolates (96.9%), with log-scores (2.0-

1.7) for three isolates (2.3%) and one isolate (0.8%) matched with M. globosa with NRI score

1.7>value>1.6 (Table 3). Based on the MALDI-TOF MS identifications the Thai set comprised

M. dermatis (n=15), M. furfur (n=39), M. globosa (n=1), M. japonica (n=2), M. slooffiae (n=6),

and M. sympodialis (n=69) (Table 2). This set was used to determine the number of runs needed

to accomplish identification at the species level. The cumulative percentage of correct

identification scores obtained during successive runs showed that during the first run a correct

species match with reliable identification results (log-scores >2.0 and log-scores 2.0-1.7) was

achieved for 92.4% of tested isolates (n=122), which after the second run increased to 94.7%


(n=125). Four runs were needed to achieve species identification for 98.5% of tested isolates,

and one isolate remained identified with log-scores <1.7 (1.5%) only.

Discussion

Isolation and identification of Malassezia spp. from clinical specimens remains a problem due to

the lipid-dependent nature of these yeasts and differences in growth rates between species (1, 4).

Phenotypic identification of Malassezia strains involves the use of morphological and

physiological characteristics. Although these methods are cheap and easy to use, they remain

laborious and results turned out to be not very reliable when interpreted by personnel with a

limited expertise in diagnostic mycology. Also, Malassezia spp. misidentification rates were

reported. Makimura and colleagues (63) confirmed that 27 out of 46 clinical isolates of

Malassezia were misidentified, i.e. an error rate of 59%. Other studies employing AFLP and

rDNA sequencing analyses revealed approximately 14% misidentified Malassezia isolates by

traditional methods (24, 64).

Next to the rDNA sequence-based species identification, successful applications of MALDI-TOF

MS to identify pathogenic yeasts have been reported (43, 44, 64-67). So far Malassezia spp.

were insufficiently represented in the commercially available reference database BDAL that

contained hitherto only two MSPs, namely one for M. furfur (DSM 6170) and one for M.

pachydermatis (VML, no strain number provided). Therefore, a CBS in-house database of 113

MSPs of all 14 Malassezia spp. was created and results showed that MALDI-TOF MS was

capable to reliably identify and discriminate between all known Malassezia spp. (Fig. 1).

Technical variation and reproducibility of measurements were tested by using the same strains


that were used to create the database (Table 1). No effect of different media was observed when

applied to nine strains of M. pachydermatis. Identification rates increased from as low as 55.6%

(mDA, MLNA) with the original BDAL database with two entries only to 89% when using the

new CBS in-house database. Different media did not influence the identification results as the

species remained separate from each other (Fig. 2). Cluster analysis of MSPs generated for type

and reference strains revealed species-specific clusters (Fig. 2). M. nana, however, showed two

clusters (Fig. S1). The top cluster links together MSPs of three M. nana strains isolated from ear

of cows in Brazil, viz. CBS 9558, CBS 9559, and CBS 9560 (37), and the bottom one contains

two strains from cat; namely CBS 9557T from Japan (37) and CBS 8334 from UK. Interestingly,

Cabañes and colleagues proposed that M. nana may represent a genetically and taxonomically

heterogenous complex (68), which is corroborated here by MALDI-TOF MS.

Performance of the CBS-KNAW in-house database was challenged by testing a set of clinical

isolates. Importantly, all tested strains were identified at the genus level and for most of the

tested strains (98.2%) designation at the species level was achieved with high accuracy as only 4

out of 338 (1.2%) tested clinical isolates were identified with not reliable log-scores <1.7 (Table

3). Importantly, not only the log-scores >2.0 but also those of value (2.0-1.7) gave identifications

that were concordant at the species level with ITS and/or D1/D2 sequencing data. Thus we

suggest that the cut-off value for correct species identification of Malassezia isolates may be

lowered to log-scores >1.7, as it was already suggested for other yeasts (44, 53). Major errors

defined as incorrect genus ID were never observed with log-scores >1.7 and minor errors, viz.

misidentification at the species level, were not found either.

To conclude, MALDI-TOF MS identification of Malassezia isolates facilitates accurate species

identification. MALDI-TOF MS is a robust identification system for Malassezia isolates if an


extended database is used. The mass spectra generated per strain are a unique fingerprint and

therefore MALDI-TOF MS is ideal for species discrimination but may also have potential for

strain typing. This, however, needs to be further explored. It remains to be seen whether skin

scrapings contain sufficient biomass to allow direct examination by MALDI-TOF MS. Hsieh et

al. (69) showed that 106 of bacterial cells were sufficient to gain correct identifications with log-

scores >2.0 while 102-104 always gave log-scores <1.7. Furthermore, mixed skin infections are

difficult to deal with as well.

Once a culture (or cultures) is available from a clinical skin sample or blood, the correct

management of neonates and other individuals suffering from Malassezia related infections will

be strongly improved with the MALDI-TOF MS based identification of Malassezia isolates, due

to its accuracy and speed. Also the epidemiological connection between the skin microbiota and

Malassezia-related sepsis remains to be investigated. Finally, MALDI-TOF MS can also be used

for quality control of Malassezia culture, as it generates results consistent with rDNA sequencing

data in a short time.

Acknowledgements

Technical support and useful insights related to ITS/D1-D2 sequencing from Bart Theelen (CBS-

KNAW) is highly acknowledged. We also appreciate the assistance of Luuk van Haren (CBS-

KNAW) and we would like to thank Dr. Gustav Wikberg (Karolinska University Hospital,

Stockholm, Sweden) for collecting clinical samples used in this study.


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Figures

Figure 1. Cluster analysis of 113 MALDI-TOF Main mass Spectra’s (MSPs) of strains

belonging to 14 Malassezia species that were used to create the CBS-KNAW in-house database.

Detailed information on CBS strains selected for MSPs creations can be found in Supplementary

Table S1. The MSPs were obtained from strains growing on mDa and MLNA and were created

by CBS-KNAW (as manual entries) and Bruker laboratories. Additionally, the MSPs of three

atypical M. furfur isolates of veterinary origin from Italy (CD864, CD865, CD866) were


included. Distance level of subdivision is displayed in relative units. n-number of MSPs created

per species

Figure 2. Cluster analysis of 32 MALDI-TOF Main mass Spectra’s (MSPs) of CBS type

strains of 14 Malassezia species. These strains were validated by sequencing of the

D1/D2 and ITS of regions. Distance level of subdivision is displayed in relative units. The

media used (mDA or MLNA) did not influence species separation. MSPs were created by

Bruker Daltonics and those made in-house by CBS-KNAW (as manual entries) are

marked with superscript (*).

Tables

Table 1. The MALDI-TOF MS identification score results of 165 reference strains belonging to

14 Malassezia species from the CBS-KNAW yeast collection.

M.

yam

atoe

nsis

2 0 0 0 0 0 0 0 0 0 2

M.

sym

podi

alis

7 2 0 1 0 0 0 0 0 0 10

M.

sloo

ffia

e

6 0 0 1 4 0 1 0 0 0 12

M.

rest

rict

a

1 0 0 0 1 0 1 0 0 0 3


M.

pach

yder

mat

is

17

1 0 7 4 4 1 0 0 0 34

M.

obtu

sa

1 0 0 0 1 0 0 0 0 0 2

M.

nana

3 1 0 2 0 0 0 0 0 0 6

M.

japo

nica

3 0 0 0 0 0 0 0 0 0 3

M.

glob

osa

8 0 0 1 0 0 2 0 0 0 11

M.

furf

ur

59

2 0 6 4 0 1 0 0 0 72

M.

equi

na

2 1 0 0 0 0 0 0 0 0 3

M.

derm

atis

2 0 0 0 0 0 1 0 0 0 3

M.

cuni

culi

1 0 0 0 0 0 0 0 0 0 1

M.

capr

ae

3 0 0 0 0 0 0 0 0 0 3

CB

S-K

NA

W

refe

renc

e se

t n(

%)

115

(69.

7)

7 (4

.2)

0 18

(10.

9)

14

(8.5

)

4 (2

.4)

7 (4

.2)

0 0 0 165

(100

)

Spot

2

(sco

re)

>2.0

2.0-

1.7

NR

I (<

1.7)

NP

F

2.0-

1.7

NR

I (<

1.7)

NP

F

NR

I (<

1.7)

NP

F

NP

F

tota

l no

. of

stra

ins

Spot

1

(sco

re)

>2.0

>2.0

>2.0

>2.0

2.0-

1.7

2.0-

1.7

2.0-

1.7

NR

I (<

1.7)

NR

I (<

1.7)

NP

F


Table 2. Clinical isolates studied. This list indicates the country of origin of the isolates used

for the validation of CBS-KNAW Malassezia in-house database.

Malassezia spp. Clinical isolates Italy

(n=76)

Veterinary isolates Italy

(n=17)

Clinical isolates Sweden

(n=95)

Clinical isolates Greece

(n=18)

Clinical isolates Thailand

(n=132)*

M. dermatis 0 0 1 0 15

M. furfur 76 3 0 15 39

M. globosa 0 0 20 0 1

M. japonica 0 0 0 0 2

M. pachydermatis 0 14 0 1 0

M. slooffiae 0 0 2 0 6

M. sympodialis 0 0 72 2 69

*this set was used without sequencing validation


Table 3. MALDI-TOF MS identification results of Malassezia species from previously validated

and non-validated subsets of clinical isolates.

Score (log values) Validated clinical isolates from Greece,

Italy and Sweden (n = 206)

Non-validated clinical isolates from Thailand

(n = 132)

Spot 1 Spot 2 Number of correct ID (%)

Number of correct ID (%)

>2.0 >2.0 141 (68.4) 115 (87.1) >2.0 2.0-1.7 8 (3.9) 2 (1.5) >2.0 NRI (<1.7) 1 (0.5) 0

>2.0 NPF 43 (20.9) 11 (8.3) 2.0-1.7 2.0-1.7 6 (2.9) 0

2.0-1.7 NRI (<1.7) 1 (0.5) 1 (0.8)

2.0-1.7 NPF 3 (1.5) 2 (1.5) NRI (<1.7) NRI (<1.7) 3 (1.5) 1 (0.8)

NRI (<1.7) NPF 0 0 NPF NPF 0 0

total 206 (100) 132 (100)

ID – identification, NRI – not reliable ID, NPF – no peaks found

efficient identification of malassezia yeasts by matrix-assisted laser desorption ionization-time of...

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