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J

OURNAL OF

C

LINICAL

M

ICROBIOLOGY

, Nov. 2007, p. 3743–3753

Vol. 45, No. 11

0095-1137/07/$08.00

0

doi:10.1128/JCM.00942-07

Copyright © 2007, American Society for Microbiology. All Rights Reserved.

DNA Microarray-Based Detection and Identification of Fungal

Pathogens in Clinical Samples from Neutropenic Patients

Birgit Spiess, Wolfgang Seifarth, Margit Hummel,* Oliver Frank, Alice Fabarius, Chun Zheng,

Handan Mo

¨rz, Ru

¨diger Hehlmann, and Dieter Buchheidt

III. Medizinische Universita

¨tsklinik, Medizinische Fakulta

¨t Mannheim der Universita

¨t Heidelberg, 68305 Mannheim, Germany

Received 7 May 2007/Returned for modification 28 June 2007/Accepted 18 August 2007

The increasing incidence of invasive fungal infections (IFI) in immunocompromised patients emphasizes the

need to improve diagnostic tools. We established a DNA microarray to detect and identify DNA from 14 fungal

pathogens (

Aspergillus fumigatus

,

Aspergillus flavus

,

Aspergillus terreus

,

Candida albicans

,

Candida dubliniensis

,

Candida glabrata

,

Candida lusitaniae

,

Candida tropicalis

,

Fusarium oxysporum

,

Fusarium solani

,

Mucor racemosus

,

Rhizopus microsporus

,

Scedosporium prolificans

, and

Trichosporon asahii

) in blood, bronchoalveolar lavage, and

tissue samples from high-risk patients. The assay combines multiplex PCR and consecutive DNA microarray

hybridization. PCR primers and capture probes were derived from unique sequences of the 18S, 5.8S, and

internal transcribed spacer 1 regions of the fungal rRNA genes. Hybridization with genomic DNA of fungal

species resulted in species-specific hybridization patterns. By testing clinical samples from 46 neutropenic

patients with proven, probable, or possible IFI or without IFI, we detected

A. flavus

,

A. fumigatus

,

C. albicans

,

C. dubliniensis

,

C. glabrata

,

F. oxysporum

,

F. solani

,

R. microsporus

,

S. prolificans

, and

T. asahii

. For 22 of 22

patients (5 without IFI and 17 with possible IFI), negative diagnostic results corresponded with negative

microarray data. For 11 patients with proven (

n

4), probable (

n

2), and possible IFI (

n

5), data for

results positive by microarray were validated by other diagnostic findings. For 11 of 11 patients with possible

IFI, the microarray results provided additional information. For two patients with proven and probable

invasive aspergillosis, respectively, microarray results were negative. The assay detected genomic DNA from 14

fungal pathogens from the clinical samples, pointing to a high significance for improving the diagnosis of IFI.

Systemic fungal infections are increasing and cause severe

morbidity and high mortality rates for immunocompromised

patients, especially patients with acute leukemia after intensive

chemotherapy or allogeneic stem cell transplantation. Besides

the increasing incidence, the epidemiology of invasive fungal

infections (IFI) is changing, and during the last decade, both

uncommon and resistant fungal pathogens, e.g.,

Zygomycetes

,

Candida krusei

, or

Aspergillus terreus

, emerged (3, 4, 7, 22,

25, 26).

Concerning the outcome of patients with IFI, early

initi-ation of antifungal treatment is crucial; since conventional

microbiological diagnostic procedures are time-consuming

and lack sensitivity and/or specificity, antifungal therapy—in

most cases—is started empirically or preemptively based on

surrogate marker findings (serologic tests and computed

tomography of the chest) (11, 12, 24).

In recent years, molecular diagnostic tools, such as PCR, have

been established for early detection of fungal pathogens

(espe-cially

Aspergillus

and

Candida

species) in clinical samples (5, 6, 10,

14, 18, 19, 21, 27, 29, 30) by sensitive and specific methods.

To facilitate early diagnosis of IFI caused by common and

less common clinically relevant fungi, we established a sensitive

and specific DNA microarray combining multiplex PCR and

consecutive DNA chip hybridization to detect fungal genomic

DNA in clinical samples and we evaluated this assay by testing

blood, bronchoalveolar lavage (BAL), and tissue samples from

neutropenic patients at high risk for invasive fungal infections.

MATERIALS AND METHODS

Strains and growth conditions.Fungal test strains were obtained from the Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH, Braun-schweig, Germany, from the Centraalbureau voor Schimmelcultures, Utrecht, The Netherlands, or from the Institute for Medical Microbiology and Hygiene, Universita¨tsklinikum Mannheim, University of Heidelberg, Germany.

DNA extraction.Prior to DNA extraction, fungal cultures were grown in Sabouraud agar for 72 h at 30°C. DNA extraction from fungal cultures was performed (29) with the QIAGEN DNeasy plant mini kit (QIAGEN, Hilden, Germany) as described previously. DNA from bacterial cultures was obtained from the Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH, Braunschweig.

DNA extraction both for blood and BAL samples was performed according to a protocol described previously (29). Tissue samples were processed additionally in liquid nitrogen for disruption.

Primers for multiplex PCRs.The first multiplex primer mix was for amplifi-cation of the internal transcribed spacer 1 (ITS1) regions of fungal rRNA genes. Nine sense primers derived from the highly conserved 18S and three antisense primers from the highly conserved 5.8S regions of the rRNA genes were selected (Table 1). The first primer mix also contained a primer pair selected from the ITS1 region of the human rRNA gene as a positive control. All antisense primers were 5⬘modified with carbocyanine 3 (Cy3) fluorochrome. Therefore, the am-plification products were Cy3 labeled at the 5⬘ends.

The second multiplex primer set was used for a separate PCR as an internal standard for the quality of DNA and as a positive and a negative control for the hybridization reaction. The primer mix contained primers for human housekeep-ing genes correspondhousekeep-ing to glucose-6-phosphate dehydrogenase (G6PD), human ribosomal protein 19 (RPL19), and two plant-specific genes (Arabidopsis thaliana ribosomal protein L23a [AtrpL23a] andA. thalianaactin 2 [ACT2]) as negative controls.

The melting temperatures of the primers and possible secondary structures were calculated with Oligo software (Oligo 6.0; MedProbe AS, Oslo, Norway).

* Corresponding author. Mailing address: III. Medizinische

Universi-ta

¨tsklinik, Medizinische Fakulta

¨t Mannheim der Universita

¨t Heidelberg,

Theodor-Kutzer-Ufer 1-3, D-68167 Mannheim, Germany. Phone:

49-621-383-4115. Fax: 49-621-383-4201. E-mail: margit.hummel@med3

.ma.uni-heidelberg.de.

Published ahead of print on 22 August 2007.

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Design of capture probes and microarray preparation.The fungal oligonu-cleotide probes and two positive control oligonuoligonu-cleotides from human DNA were designed from the ITS1 sequences available in the GenBank database (www.ncbi.nlm.nih.gov/). Sequence alignments were performed using the Geno-matix DiAlign (www.genoGeno-matix.de/cgi-bin/dialign/dialign.pl). By comparing the sequences of the ITS1 regions, oligonucleotides were generated from regions with a high level of variability between the different fungal species. One to three capture probes of various lengths (22 to 70 bases) per fungal species and two human ITS1 oligonucleotides as positive controls were designed (24 and 55 bases). As additional positive controls, we designed four capture probes (26 to 55 bases) based on the human glucose-6-phosphate dehydrogenase (G6PD) gene and two oligonucleotides (26 and 55 bases) based on the human ribosomal protein L19 (RPL19) gene.

Two plant capture probes of 55 bases from theA. thalianagenesAtrpL23aand ACT2served as negative controls.

The ITS1 region ofCandida parapsilosis, the third yeast responsible for can-didemia, showed a high level of homology and cross-reactivity to otherCandida species so it was not included.

To predict the potential cross-reactivities of the capture probes, additional database searches were performed by using the BLASTN program (www.ncbi .nlm.nih.gov/). Sequences of the capture probes and sequence sources used for primers and capture probes design are given in Table 2.

All oligonucleotides had a C12 spacer and were NH2modified at their 5⬘ends

for covalent coupling.

The synthetic oligonucleotides were diluted to 100␮M in 3⫻SSC (1⫻SSC is 0.15 M NaCl plus 0.015 M sodium citrate). Microarrays were prepared and treated as described previously (28). The microarray design is shown in Fig. 1.

For hybridization data redundancy, two replicates were spotted onto the same slide.

PCR, labeling, and chip hybridization.Cy3-labeled DNA probes were synthe-sized by PCR in a total volume of 50␮l containing 2␮l template DNA (1 pg to 5 ng fungal DNA, 200 ng human DNA), 3 mM MgCl2, 0.25 mM of each

deoxynucleoside triphosphate, 1 U of Taq polymerase (Invitrogen GmbH, Karlsruhe, Germany), and 200 pmol primer mixtures.

For amplification of the ITS1 regions and human housekeeping/A.thaliana control genes, two separate PCRs under the same reaction conditions were carried out. Amplification was performed in a DNA thermal cycler (Mastercy-cler; Eppendorf AG, Hamburg, Germany) and started with 2 min of initial denaturation at 94°C, followed by 45 cycles of DNA denaturation at 94°C for 30 s, primer annealing at 56°C for 1 min, elongation at 72°C for 3 min, and a final extension step at 72°C for 10 min. Before microarray hybridization, the Cy3-labeled DNA was ethanol precipitated, air dried, and redissolved in 23␮l hy-bridization buffer containing 3.0⫻ SSC, 0.5% sodium dodecyl sulfate, 50% formamide, and 50 mM sodium phosphate buffer, pH 7.4.

Hybridization was performed under standardized conditions described else-where (28).

[image:2.585.43.539.88.444.2]

Chip evaluation. Hybridized glass slides were scanned with an Affymetrix GMS 418 array scanner (Affymetrix) by using the recommended settings for Cy3 fluorochrome. High-resolution images (10␮m/pixel) were saved in the TIF file format (16-bit) and further evaluated by the ImaGene 4.0 software tool package (BioDiscovery, Inc., Los Angeles, CA). The original signal and the signals of the two replicates from one hybridization were evaluated separately. The mean values and standard deviations were calculated. After background subtraction for each signal, false color mapping (BMP file format, 24-bit) was used to display

TABLE 1. Composition of fungal and human ITS1 genes, housekeeping genes, and

Arabidopsis thaliana

-specific primer sets used for

amplification of the hybridization probes

Primer namea Orientation 5⬘

Modified Nucleotide sequence (5⬘–3⬘) Targeted organism(s)

Fungal rRNA genes

ITS1-s1

Sense

CCTGCGGAAGGATCATTACC

A. flavus

,

A. fumigatus

,

A. terreus

,

C. albicans

, and

C. tropicalis

ITS1-s2

Sense

CTGCGAATGGCTCATTAAATC

C. glabrata

ITS1-s3

Sense

CAGCGGAGGGATCATTACC

F. oxysporum

ITS1-s4

Sense

CTGCGGAGGGATCATTACC

F. solani

ITS1-s5

Sense

GTGAACCTGCGGAAGGATC

M. racemosus

ITS1-s6

Sense

GTGAACCTGCGGAAGGTTC

R. microsporus

ITS1-s7

Sense

GTGAACCTGCGGAAGGATC

C. lusitaniae

and

C. dubliniensis

ITS1-s8

Sense

GTGAACCAGCGGAGGGATC

S. prolificans

ITS1-s9

Sense

GTGAACCTGCGGAAGGATC

T. asahii

ITS1-as1OP

Antisense

Cy3

CCAAGAGATCCATTGTTGAAAG

A. flavus

,

A. terreus

, and

R. microsporus

ITS1-as2OP

Antisense

Cy3

CAAGAGATCCGTTGTTGAAAG

A. fumigatus

,

C. albicans

,

C. dubliniensis

,

C. lusitaniae

,

C. tropicalis

,

F. oxysporum

,

F. solani

,

M. racemosus

,

S. prolificans

, and

T. asahii

ITS1-as3OP

Antisense

Cy3

AGGCCATGCGATTCGAAAAG

C. glabrata

Human rRNA genes

HumITS1-sA

Sense

CCTCCCCGTGGTGTGAAAC

HumITS1-asB

Antisense

Cy3

GTTCTTCATCGACGCACGAGC

Arabidopsis thaliana

genes

ACT2-s1

Sense

TGTATAATTGATTCAGAATC

ACT2-as1

Antisense

Cy3

CTCCGTTTTTTTAGTGGTTAAC

AtrpL23a-s1

Sense

AAAGGCTGTGAAGTCTGGTC

AtrpL23a-as1

Antisense

Cy3

GGAGTAGCGCTGATTTTTGG

Human housekeeping

genes

G6PD-sA

Sense

AATCAGGTGTCACCCTGG

G6PD-asBOP

Antisense

Cy3

CAGGTAGAGCCGGGATGATC

RPL19-sA

Sense

AGGTGAAGGGGAATGTGTTC

RPL19-asBOP

Antisense

Cy3

CAACTAACCTCTAGTCCCTAC

a

s, sense; as, antisense; Hum, human.

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TABLE 2. Capture probe sequences derived from the ITS1 regions of the corresponding organisms and sequence sources

Organism Probe namea Length (bases) Probe sequence (5–3)b Dot code Accession no.

C. albicans Calb1Sc 21 AACTTGTCACACCAGATTATTACT A2 AJ551313

C. dubliniensis Cdub1Sc 23 AACTTGTCACGAGATTATTTTTA A3 AJ865083

C. dubliniensis Cdubl2 55 AAACTTACAACCAAATTTTTTATAAACTTGTCACGAG

ATATTTTTAATAGTCAA

A4

C. lusitaniae Clusi1 55 AAAAATACATTACACATTGTTTTTGCGAACAAAAAA

ATAAATTTTTTTATTCGAA

A5 AF172262

C. lusitaniae Clusi2 68 AAAAATACATTACACATTGTTTTTGCGAACAAAAAA

ATAAATTTTTTTATTCGAATTTCTTAATATCA

A6

C. glabrata Cglab1 70 GATAGTTCCTTTACTACATGGTATAACTGTGGTAATT

CTAGAGCTAANTCATGCTTAAAATCTCGACCTC

A7 M60311

C. glabrata Cglab2 55 AAGAGATGTATTTATTAGATAAAAAATCAATGTCTT

CGGACTTTTTGATGATTCA

A8

C. glabrata Cglab3 55 GATAGTTCCTTTACTACATGGTATAACTGTGGTAATT

CTAGAGCTAAATCATGCT

A9

C. tropicalis Ctrop1 55 GTGTTTTTTATTGAACAAATTTCTTTGGTGGCGGGAG

CAATCCTACCACCAGAGG

A10 AF321539

C. tropicalis Ctrop2 70 GTGTTTTTTATTGAACAAATTTCTTTGGTGGCGGGAG

CAATCCTACCACCAGAGGTTATAACTAAACCAA

A11

R. microsporusvar. rhizopodiformis

Rmicr1 70 ACTAATGTATTGGCACTTTACTGGGATTTACTTCTCA GTATTGTTTGCTTCTATACTGTGAACCTCTGGC

B1 AY243958

R. microsporusvar. rhizopodiformis

Rmicr2 55 GATTACCTTTCTTCCTTTGGGAAGGAAGGTGCCTGG TACCCTTTACCATATACCA

B2

R. microsporusvar. rhizopodiformis

Rmicr3 55 TACTGGGATTTACTTCTCAGTATTGTTTGCTTCTATA CTGTGAACCTCTGGCGAT

B3

R. microsporusvar. rhizopodiformis

Rmicr4 55 ACTAATGTATTGGCACTTTACTGGGATTTACTTCTCA GTATTGTTTGCTTCTATACTGTGAACCTCTGGC

B4

R. microsporusvar. rhizopodiformis

Rmicr5 55 ACTAATGTATTGGCACTTTACTGGGATTTACTTCTCA GTATTGTTTGCTTCTATA

B5

F. oxysporum Foxys1 70 CCGAGTTTACAACTCCCAAACCCCTGTGAACATACC

ACTTGTTGCCTCGGCGGATCAGCCCGCTCCCGGT

B9 X94173

F. oxysporum Foxys2 55 CAGCCCGCTCCCGGTAAAACGGGACGGCCCGCCAG

AGGACCCCTAAACTCTGTTT

B10

F. solani Fsola1 55 CCGAGTTATACAACTCATCAACCCTGTGAACATACCT

AAAACGTTGCTTCGGCGG

B11 AJ608989

F. solani Fsola2 55 CCTAAAACGTTGCTTCGGCGGGAACAGACGGCCCTG

TAACAACGGGCCGCCCCCG

B12

M. racemosus Mrace1 55 AAATAATCAATAATTTTGGCTTGTCCATCATTATCTA

TTTACTGTGAAACGTATT

C1 AJ271061

M. racemosus Mrace2 70 TGTTCCACTGCTATAAGGATAGGCAGCGGAAATGTT

AACCGAGTCATAATCAAGCTTAGGCTTGGTATCC

C2

S. prolificans Sprol1 55 TGTTCTGTTGCCTCGGCGGGGAGGAAGACCCCTTAA

AAAGCCCAGCCCCCGCCGG

C3 AY228120

S. prolificans Sprol2 24 GAGGAAGACCCCTTAAAAAGCCCA C4

T. asahii Tasah1 55 TCGAGTATTTTTACAAACAATGTGTAATGAACGTCG

TTTTATTATAACAAAATAA

C5 AF322110

T. asahii Tasah2 30 ACAATGTGTAATGAACGTCGTTTTATTATA C6

A. flavus Aflav1 55 GGGCCCGCGCCCGCCGGAGACACCACGAACTCTGTC

TGATCTAGTGAAGTCTGAG

C7 L76747

A. flavus Aflav2 27 CACCACGAACTCTGTCTGATCTAGTGA C8

A. terreus Aterr1 55 GTTGCTTCGGCGGGCCCGCCAGCGTTGCTGGCCGCC

GGGGGGCGACTCGCCCCCG

C9 AY373871

A. terreus Aterr2 27 AGCGTTGCTGGCCGCCGGGGGGCGACT C10

A. fumigatus Afumi1 55 GGGCCCGCGCCCGCCGAAGACCCCAACATGAACGCT

GTTCTGAAAGTATGCAGTC

C11 AY373851

A. fumigatus Afumi2 28 CCCCAACATGAACGCTGTTCTGAAAGTA C12

M. racemosus Mrace3 55 TGGTATCCTATTATTATTTACCAAAAGAATTCAGAAT

TAATATTGTAACATAGAC

D2

Human

Positive controls HumITS1_1 24 AGCGCCCTCGCCAAATCGACCTCG D3 U13369 HumITS1_2 55 CCTCCCGGTGCGTCGTCGGGAGCGCCCTCGCCAAAT

CGACCTCGTACGACTCTTA

D4

A.thaliana

Negative controls Atrpl23aA 55 AAGCCTTCAAGAAGAAGGACAAAAAGATTAGGACC AAGGTCACCTTCCACAGGCC

D5 AF034694

ACT2A 55 TTGACGAGTTCGGATGTAGTAGTAGCCATTATTTAA TGTACATACTAATCGTGAA

D6 U41998

Human

Positive controls RPL19_1 55 ACAAGCGGATTCTCATGGAACACATCCACAAGCTGA AGGCAGACAAGGCCCGCAA

D7 AC004408

RPL19_2 26 CACATCCACAAGCTGAAGGCAGACAA D8 G6PD-2_1 55 CTTCCATCAGTCGGATACACACATATTCATCATCATG

GGTGCATCGGTGAGTATC

D9 X55448

G6PD-2_2 28 CAGTCGGATACACACATATTCATCATCA D10 G6PD-1_1 55 CCCTGAGCCGGACCCAGGTGTGCGGGATCCTGCGG

GAAGAGCTTTTCCAGGGCGA

D11

G6PD-1_2 26 TGCGGGATCCTGCGGGAAGAGCTTTT D12

a

Names of the fungal capture probes are derived from the first letter of genus name and the first four letters of the species name and are consecutively numbered. Hum, human.

b

All capture probes have a C12 spacer and a NH2linker at the 5⬘ends.

c

Capture probe sequences are from Leinberger et al. (20).

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resultant images as shown in Fig. 2. Dots with at least twice the signal intensities of the background intensities were evaluated as positive signals. Background intensities were calculated by the ImaGene 4.0 program.

Patients.Blood, BAL, and tissue samples from a total of 46 immunocompro-mised neutropenic patients with mainly hematological malignancies were further processed for diagnostic purposes after the patients gave informed consent. Primary diseases were acute myeloid leukemia (AML) (n⫽21), acute lympho-blastic leukemia (ALL) (n⫽7), non-Hodgkin’s lymphoma (NHL) (n⫽11), myelodysplastic syndromes (MDS) (n⫽2), severe aplastic anemia (n⫽1), osteomyelofibrosis (n⫽1), metastatic rhabdomyosarcoma (n⫽1), medulloblas-toma (n⫽1), and metastatic germ cell tumor (n⫽1).

For clinical evaluation, we investigated 91 samples (66 blood samples, 18 BAL samples, and 7 tissue samples) from 46 neutropenic patients with proven (n⫽5), probable (n⫽3), or possible (n⫽33) IFI, according to the European Organi-zation for Research and Treatment of Cancer/Mycoses Study Group (EORTC/ MSG) 2002 criteria (1). For five patients, there was no evidence of IFI.

Clinical samples.Blood samples were obtained by venipuncture under sterile conditions in a sterile vessel to a final concentration of 1.6 mg EDTA per ml blood. The sample volume was 5 to 7 ml.

BAL was performed as described previously (29), and BAL samples were obtained in a sterile vessel without conservation medium. The mean sample volume was 10 ml.

Tissue samples were obtained by needle biopsies (liver and kidney) or surgical procedures (other samples) under sterile conditions.

RESULTS

The multiplex PCR for amplification of the ITS1 regions

(137 to 245 bp) of the 14 fungal pathogens showed different

sensitivity thresholds for the genomic DNAs of the fungal

species (Table 3). Even large amounts of genomic bacterial

DNAs (5 ng) used as negative controls (

Enterococcus faecalis

DSM 2570,

Escherichia coli

DSM 787,

Klebsiella pneumoniae

DSM 4617,

Proteus mirabilis

DSM 788,

Pseudomonas

aerugi-nosa

DSM 50071,

Staphylococcus aureus

DSM 799, and

Strep-tococcus pneumoniae

DSM 20566) were not amplified in the

ITS1 multiplex PCR and did not give any signals after

hybrid-ization to the fungal DNA microarray. The genomic DNA of

Penicillium notatum

, a fungal organism that we did not aim to

detect, was amplified by PCR and gave hybridization signals

with one of three capture probes of

Candida glabrata

and one

of two capture probes of

Scedosporium prolificans

.

Addition-ally, for a human, ITS1-specific, 226-bp fragment, few

nonspe-cific amplification products were visible when large amounts of

human genomic DNA (200 ng) were used in the ITS1

multi-plex PCR. After the hybridization of the human PCR products

to the DNA microarray, there was no cross-reactivity between

human DNA and fungal capture probes detected. There were

also no cross-reactivities between any fungal or human PCR

products and the two spotted

A. thaliana

negative control

oli-gonucleotides. Hybridization with two Cy3-labeled

oligonucle-otides (50

M), which were complementary to the two spotted

A. thaliana

capture probes, resulted in intense signals (data not

shown).

The fungal and human capture probes were located on the

glass microarray as shown schematically in Fig. 1. To establish

the fungal DNA chip, 5-ng amounts of each of 14 genomic

fungal DNAs were amplified separately by ITS1 multiplex

PCR and the products were then hybridized. Every fungal

organism showed a specific hybridization pattern after

evalu-ation of the hybridizevalu-ation signals (Fig. 2A). Details about the

correlation of the hybridization patterns and the fungal

organ-isms are described in Table 4. In spite of single

cross-reactiv-ities, each species has a unique signature hybridization pattern.

Different hybridization conditions were tested and

com-pared. The best hybridization results and an appropriate ratio

between specific binding, signal intensity, and cross-reactivity

were achieved by using the following hybridization and

wash-ing conditions: hybridization at 42°C uswash-ing 50% formamide for

12 h following a washing step for 10 min in 1

, 0.5

, and 0.1

SSC at room temperature, respectively.

For

Candida tropicalis

,

Fusarium oxysporum

, and

Rhizopus

microsporus

DNA, the detection limit of the array is above the

detection limit of the hybridization preceding fungal ITS1

PCR. Additional serial 10-fold dilutions of the three DNAs

were used to determine the detection threshold of the array.

The ITS1 PCR detection limits were 1 pg for

C. tropicalis

, 10 pg

for

F. oxysporum

, and 8 pg for

R. microsporus

, and the

detec-FIG. 1. Schematic composition of glass microarray and grid location of fungal, human, and

A. thaliana

-specific oligonucleotides (capture

probes). Grid locators (A1, A12, and D1 for Cy3) represented by a spotted Cy3-labeled arbitrary oligonucleotide are depicted as black boxes.

Names of the fungal capture probes are derived from the first letter of the genus name and the first four letters of the species name and are

numbered consecutively as follows: Calb1S (20),

Candida albicans

; Cdub1S (20) and Cdubl,

Candida dubliniensis

; Clusi,

Candida lusitaniae

; Cglab,

Candida glabrata

; Ctrop,

Candida tropicalis

; Rmicr,

Rhizopus microsporus

; Foxys,

Fusarium oxysporum

; Fsola,

Fusarium solani

; Mrace,

Mucor

racemosus

; Sprol,

Scedosporium prolificans

; Tasah,

Trichosporon asahii

; Aflav,

Aspergillus flavus

; Aterr,

Aspergillus terreus

; and Afumi,

Aspergillus

fumigatus

.

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tion limits of the array were 300 pg DNA for

C. tropicalis

, 500

pg for

F. oxysporum

, and 300 pg for

R. microsporus

.

For the other fungal species, the detection threshold of the

ITS1 PCR marked the detection limit of the array (Table 3).

Two hundred nanograms of genomic DNA directly from

sam-ples of patients with known or predicted IFI were used in the

ITS1 fungal multiplex PCR and in positive and negative control

PCRs. The template of the PCR was composed of a mix of human

DNA and potentially present fungal DNA. The PCR products

were used for hybridization to the DNA microarray.

The results of microarray investigations of blood, BAL,

and tissue samples from 46 neutropenic

immunocompro-mised patients are given in Table 5. Microarray results were

compared to culture, histopathology, imaging, serologic,

and clinical findings, according to the EORTC/MSG 2002

criteria for invasive fungal infections, and to

Aspergillus

-specific nested PCR (29) results, in summary demonstrating

the feasibility of this tool.

For 22 of 22 patients (5 without IFI and 17 with possible

IFI), negative conventional diagnostic results corresponded

FIG. 2. (A) Typical hybridization patterns using 5 ng genomic DNA of the different fungal species, presented by false color mapping. Glass

microarrays were probed with Cy3-labeled DNA fragments amplified separately with the primer mixture for the fungal ITS1 PCR. (B)

Hybrid-ization patterns using 200 ng human DNA mixed with potential fungal DNA from clinical samples amplified separately with the primer mixture

for the fungal and human ITS1 regions and for human housekeeping/

A. thaliana

genes and combined for hybridization. Fungus-specific signals are

indicated by arrows. For assignment of the hybridization signals, compare Fig. 2B with Fig. 1 and Tables 4 and 5.

V

OL

. 45, 2007

FUNGAL DETECTION BY MICROARRAY TECHNOLOGY

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with negative microarray data. For eight patients with proven

(

n

5) or probable (

n

3) IFI, results for four or two patients

were confirmed by microarray testing, respectively. For

pa-tients with possible IFI (

n

5), positive microarray data were

validated by other diagnostic findings. For 11 of 11 patients

with possible IFI, the microarray results provided additional

information about fungal pathogens. For one patient with

proven invasive aspergillosis (determined from a brain abscess

sample), DNA microarray results from blood samples were

negative under antifungal conditions; for one patient with

probable invasive aspergillosis, DNA microarray results from a

BAL aliquot were negative; this patient also received

antifun-gal treatment.

Genomic DNA and specific hybridization patterns of

Can-dida albicans

,

Candida dubliniensis

,

Candida glabrata

,

Aspergil-lus fumigatus

,

Aspergillus flavus

,

Fusarium solani

,

Rhizopus

microsporus

,

Scedosporium prolificans

, and

Trichosporon asahii

were detected. One fungal pathogen was identified in 11

pa-tients with IFI, and two or more fungal pathogens were

like-wise identified in 11 patients with IFI.

We also compared microarray findings to the results of a

previously described and clinically validated

Aspergillus

-specific

nested PCR assay (6, 29). For one patient, the

Aspergillus

nested PCR assay was positive for

Aspergillus

DNA, whereas

the DNA microarray results were negative. For three patients,

the

Aspergillus

PCR results for blood and tissue samples were

positive, whereas the DNA microarray results were negative

for

Aspergillus

DNA but positive for additional fungal species

(

C. albicans

,

C. dubliniensis

, and

C. glabrata

). Differences

be-tween nested

Aspergillus

PCR (29) findings and the microarray

results are caused by the higher sensitivity of the nested PCR

assay for

Aspergillus

DNA. For five patients, positive

Aspergil-lus

PCR findings were in line with positive DNA microarray

results for

Aspergillus

DNA.

Three representative hybridizations of DNA from a total

of 46 patients (Table 5) isolated from clinical samples are

shown in Fig. 2B. For the blood sample from patient 3,

hybridization resulted in distinct hybridization signals for all

three

C. glabrata

capture probes without any

cross-reactivi-ties. A corresponding blood culture was positive for

Candida

[image:6.585.43.283.88.243.2]

species that could not be further differentiated. A second

TABLE 4. Hybridization patterns for the 14 fungal species

Fungal species

Hybridization signal (dot code)

Signature hybridization

patterna

C. albicans

A2

Calb1S (20)

A4

Cdubl2

C. dubliniensis

A3

Cdub1S (20)

A4

Cdubl2

A8

Cglab2

C. lusitaniae

A4

Cdubl2

A5

Clusi1

A6

Clusi2

A8

Cglab2

C3

Sprol1

C5

Tasah1

D7

RPL19_1

C. glabrata

A7

Cglab1

A8

Cglab2

A9

Cglab3

D7

RPL19_1

C. tropicalis

A9

Cglab2

A11

Ctrop2

D7

RPL19_1

R. microsporus

var.

A3

Cdub1S

rhizopodiformis

A7

Cglab1

A8

Cglab2

A11

Ctrop2

B2

Rmicr2

D7

RPL19_1

F. oxysporum

B9

Foxys1

B10

Foxys2

D7

RPL19_1

F. solani

B11

Fsola1

C11

Afumi1

D7

RPL19_1

M. racemosus

D2

Mrace3

S. prolificans

C3

Sprol1

D3

HumITS1_2

D7

RPL19_1

T. asahii

A8

Cglab2

C5

Tasah1

C6

Tasah2

D7

RPL19_1

A. flavus

A7

Cglab1

A8

Cglab2

B9

Foxys1

B10

Foxys2

C7

Aflav1

D3

HumITS1_2

A. terreus

C9

Aterr1

C10

Aterr2

C11

Afumi1

D7

RPL19_s1

A. fumigatus

C11

Afumi1

aNames of the fungal capture probes are derived from the first letter of the genus

name and the first four letters of the species name and are consecutively numbered. Specific capture probes are marked in bold letters. The unique signature hybridiza-tion pattern for each organism is shown in column 3. Hum, human.

TABLE 3. Lowest detectable amount of DNA from fungal strains

by PCR

Fungal strain or samplea DNA amt

(pg)

Aspergillus flavus

DSM 1959... 20

Aspergillus fumigatus

DSM 819 ... 50

Aspergillus terreus

DSM 826 ... 10

Candida albicans

DSM 11949 ... 1

Candida dubliniensis

DSM 75921 ... 1

Candida glabrata

DSM 11226 ... 1

Candida lusitaniae

, CS ... 1

Candida tropicalis

DSM 1346... 1

Fusarium oxysporum

DSM 12646 ... 10

Fusarium solani

DSM 1164 ...100

Mucor racemosus

DSM 62760... 10

Rhizopus microsporus

var.

rhizopodiformis

DSM 2196... 8

Scedosporium prolificans

CBS 100390... 50

Trichosporon asahii

, CS... 10

aCS, clinical sample.

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[image:7.585.50.549.90.710.2]

TABLE 5. Results from patient blood, BAL, and tissue samples

a

Patient Sample Diagnosis Diagnostic significanceb

Result(s) from diagnostic

work-up DNA microarray result(s)

c

Nested PCR resultd

1 BAL ALL Proven Culture positive for aspergillosis Positive forA. flavus, A. fumigatus,F. oxysporum, andF. solani

2 Blood AML Proven Histology positive, culture negative

Positive forA. flavusand

C. tropicalis

3 Blood AML Proven Culture positive forCandida, histology positive

Positive forC. glabrata

3A Brain abscess Positive forC. glabrata

3B Spleen abscess Positive forC. glabrataand

S. prolificans

3C Spleen tissue Positive forS. prolificans

4 Blood AML Proven Candidasepsis, blood culture positive forC. albicans

Positive forC. dubliniensis

5 BAL OMF, HSCT Probable Positive forAspergillusAg (galactomannan)

Positive forC. glabrata,A. flavus, andF. oxysporum

6 Blood ALL Probable Positive forAspergillusAg (galactomannan)

Positive forC. tropicalis

Positive LI Positive forC. glabrata, A. flavus, A. fumigatus, andT. asahii

6A BAL Positive forC. glabrataand

T. asahii

6B Blood Positive forC. glabrata

6C Blood Negative ⫺

7 Blood AML Possible PCR positive forCandida Positive forC. dubliniensisand

C. glabrata

7A Blood Positive forC. glabrata (⫹)

7B Spleen Positive forC. dubliniensisand

C. glabrata

7C Needle biopsy, kidney

Positive forC. dubliniensisand C.glabrata

(⫹) 8 Blood Germ cell tumor Possible Serology positive forCandida,e

negative forCandidaAg, negative forAspergillusAg (galactomannan)

Positive forC. tropicalisand

C. glabrata

9 Blood ALL Possible Positive forAspergillusAg Positive forA. flavus

10 Blood ALL Possible Negative forAspergillusAg (galactomannan), positive hepatic nodule

Positive forC. tropicalis (⫹)

10A Blood Positive forC. tropicalis (⫹)

10B Blood Positive forC. tropicalis

10C Blood Negative (⫹)

11 Blood AML Possible Positive LI Negative ⫹

11A Blood Positive forA. fumigatus

12 Blood Plasmocytoma No IFI Negative LI Negative ⫺

13 Blood Mantle cell lymphoma

No IFI Positive forMycobacterium tuberculosis

Negative ⫺

13A BAL Negative ⫺

14 BAL AML No IFI Negative ⫺

15 BAL MDS No IFI No microbiological proof Negative ⫺

16 Blood AML No IFI Negative forAspergillusAg (galactomannan), fungal culture negative

Negative ⫺

16A Blood Negative ⫺

16B Blood Negative ⫺

17 Blood AML Possible Positive LI, negative for AspergillusAg (galactomannan)

Negative ⫺

17A Blood Negative ⫺

17B Blood Negative ⫺

18 Blood AML Possible Positive LI Negative ⫺

18A Blood Negative ⫹

18B Blood Negative ⫺

19 BAL AML Possible No microbiological proof Negative ⫺

20 Blood CLL Possible Histology negative Negative ⫺

20A BAL Negative ⫺

21 BAL MDS Possible Negative forAspergillusAg (galactomannan), positive LI

Negative ⫺

22 Blood AML Possible Negative forAspergillusAg (galactomannan), blood culture negative, BAL negative forAspergillusAg (galactomannan), negative for CandidaAg

Negative ⫺

23 Blood AML Possible Positive LI, negative for AspergillusAg (galactomannan)

Negative ⫺

23A Blood Negative ⫺

Continued on following page

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example (patient 1) shows the hybridization results using

DNA from a BAL sample. A blood culture from this patient

identified

A. fumigatus

. The hybridization gave positive

sig-nals for

A. flavus

,

A. fumigatus

,

F. oxysporum

, and

F. solani

.

The third example (patient 5) showed signals with the

C.

glabrata

capture probes and the

A. flavus

probe.

Addition-ally, the sample was positive by

Aspergillus

antigen testing

[image:8.585.47.545.80.625.2]

(galactomannan enzyme-linked immunosorbent assay). The

TABLE 5—

Continued

Patient Sample Diagnosis Diagnostic significanceb

Result(s) from diagnostic

work-up DNA microarray result(s)

c

Nested PCR resultd

24 BAL CLL Possible Positive LI Negative ⫺

25 Blood AML Possible Negative LI Negative ⫺

25A Blood Negative ⫺

26 BAL Hairy cell leukemia

Possible Fungal culture negative Negative ⫺ 27 Blood AML Possible Negative forAspergillusAg

(galactomannan)

Negative ⫺

27A Blood Negative ⫺

27B Blood Negative ⫺

28 Blood AML Possible Positive for LI, negative for AspergillusAg

(galactomannan)

Negative ⫺

28A Blood Negative ⫺

28B Blood Negative ⫺

28C Blood Negative ⫺

28D Blood Negative ⫺

28E Blood Negative ⫺

29 Blood AML Possible Negative forAspergillusAg (galactomannan)

Negative ⫺

29A Blood Negative ⫺

29B Blood Negative ⫺

29C Blood Negative ⫺

30 Blood AML Possible Positive LI Negative ⫺

30A Blood Negative ⫺

30B Blood Negative ⫺

30C Blood Negative ⫺

31 Blood AML relapse Possible Positive LI, negative for AspergillusAg (galactomannan)

Negative ⫺

31A Blood Negative ⫺

31B Blood Negative

32 Blood AML Possible Positive LI Negative ⫺

32A Blood Negative ⫹

32C Blood Negative ⫺

33 BAL ALL Possible Negative forAspergillusAg (galactomannan)

Negative ⫺

34 Blood Multiple myeloma Possible No microbiological proof Positive forC. glabrataand

C. tropicalis ⫹

35 Blood SAA Possible Negative ⫹

35A Blood Positive forC. tropicalis

36 BAL Mantle cell lymphoma

Possible No microbiological proof Positive forC. albicans ⫺ 37 BAL ALL, mucositis Possible No microbiological proof Positive forC. glabrataand

C. tropicalis

38 Blood ALL Possible No microbiological proof Positive forR. microsporus

39 Liver biopsy Rhabdomyosarcoma Possible No microbiological proof Positive forC. glabrata

40 Liver biopsy Medulloblastoma Possible No microbiological proof Positive forC. tropicalisand S. prolificans

41 Liver biopsy B-NHL Possible Negative forAspergillusAg (galactomannan), fungal culture negative, positive hepatic nodule

Positive forC. glabrata

41A Blood Negative ⫺

42 Blood Lymphoma Possible Negative forAspergillusAg (galactomannan), fungal culture negative

Positive forC. glabrata

42A BAL Positive forC. glabrataand

C. tropicalis

43 BAL AML Possible Positive LI, CT positive Positive forC. glabrata

44 BAL T-NHL Possible Positive LI Positive forC. glabrata

45 Blood NHL Proven Aspergillosis, histology from brain abscess

Negative ⫹

45A Blood Negative ⫺

45B Blood Negative (⫹)

46 BAL B-CLL Probable Positive forAspergillusAg (galactomannan)

Negative ⫺

a

, negative;⫹, positive; (⫹), weakly positive; Ag, antigen; CLL, chronic lymphocytic leukemia; CT, computed tomography scan of the chest; HSCT, hematologic stem cell transplantation; LI, lung infiltrate; OMF, osteomyelofibrosis; SAA, severe aplastic anemia.

b

See reference 1.

c

Results from three capture probe replicates.

d

The nested PCR assay is specific forAspergillusspecies. See reference 29.

e

Status after fungal sepsis.

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result of the nested PCR assay for

Aspergillus

species was

negative for this patient.

Hybridization of the DNA from a blood sample of a healthy

volunteer did not give any signal with the fungal capture

probes.

DISCUSSION

In immunocompromised patients, the spectrum of clinically

relevant fungal pathogens causing systemic infections with

con-siderable morbidity and high mortality rates is changing (25).

Therefore, we set out to establish a rapid, specific, and

sensi-tive molecular method to detect and identify the most

emerg-ing fungal pathogens (26) from noncultured clinical samples in

one assay.

Our DNA microarray is able to detect clinically relevant

fungal pathogens at low detection thresholds. Results using

clinical samples from immunocompromised patients with

he-matological malignancies show the usefulness of the

microar-ray in the clinical context. The benefit of the fungal microarmicroar-ray

is the potential to detect the most important 14 fungal

patho-gens in a specific IFI high-risk setting with one test; due to

feasibility concerns, other fungi were not included. In view of

the changing spectrum of emerging clinically relevant fungal

pathogens causing IFI and the advent of novel antifungals, this

new diagnostic approach meets urgent clinical needs, at least

concerning the group of patients treated for hematological

malignancies.

For our assay, sensitive and specific detection and

identifi-cation of the fungal pathogens were achieved by designing

primer pairs complementary to the highly conserved 18S and

5.8S regions of the fungal rRNA genes and oligonucleotide

capture probes complementary to the more variable ITS1

re-gions which enabled a differentiation of fungal species (13, 14,

15, 16, 20). As part of the rRNA genes, the ITS1 regions were

chosen as targets because they are present in numerous copies

in the fungal genome. The design of the primer pairs from

highly conserved regions of a multicopy gene lead to a high

sensitivity of the PCR and to an amplification of the target

sequences with only a few primer combinations. Reasons for

the different detection thresholds of ITS1 PCR for the fungal

DNAs could be different primer binding capacities and

possi-ble secondary structures of single primers. The existence of two

to three oligonucleotides per fungal organism (2) resulted in

species-specific hybridization patterns.

As a proof of principle and for clinical validation,

hybridiza-tion of DNA of blood, BAL, and tissue samples from a total of

46 patients demonstrated the applicability and feasibility of our

diagnostic assay (Table 5).

For 22 patients, negative microarray data were confirmed by

negative conventional diagnostic results. On the other hand,

positive microarray data were confirmed by other diagnostic

results for 11 patients with proven (

n

4), probable (

n

2),

or possible (

n

5) IFI.

For 11 of 11 patients with possible IFI, the group of patients

with the highest diagnostic uncertainty, the microarray results

provided additional information about the pathogens, which

were mainly

Candida

species. Among the clinical samples of

this patient group were five BAL samples positive for

Candida

species; from a clinical point of view, the detection of

Candida

species in BAL is not accepted as proof for IFI. The rate of

sample contamination with

Candida

species is still unclear.

For one patient with proven invasive aspergillosis

(deter-mined from a brain abscess sample), DNA microarray results

from blood samples were negative and possibly caused by

in-tensive antifungal treatment (18); for one patient with

proba-ble invasive aspergillosis, DNA microarray results from a BAL

aliquot were also negative under antifungal treatment and/or

due to a nonrepresentative sample.

Genomic DNA and specific hybridization patterns of

Can-dida albicans

,

Candida dubliniensis

,

Candida glabrata

,

Aspergil-lus fumigatus

,

Aspergillus flavus

,

Fusarium solani

,

Rhizopus

mi-crosporus

,

Scedosporium prolificans

, and

Trichosporon asahii

were detected. One fungal pathogen was identified in 11

pa-tients with IFI, and two or more fungal pathogens were

like-wise identified in 11 patients with IFI. The microarray findings

of these patients show the potential of the assay to detect more

than one fungal organism as a cause of infection in the same

patient. From a clinical point of view, our knowledge about

fungal infections caused by multiple pathogens is small.

Comparing results of the microarray analysis to the

As-pergillus

-specific nested PCR assay, positive

Aspergillus

PCR

findings for five patients were in line with positive DNA

microarray results for

Aspergillus

DNA. For one patient, the

Aspergillus

nested PCR assay was positive, whereas the DNA

microarray results were negative. For three patients,

As-pergillus

PCR results from blood and tissue samples were

positive, whereas the DNA microarray results were negative

for

Aspergillus

DNA but positive for additional fungal

spe-cies (

C. albicans

,

C. dubliniensis

, and

C. glabrata

).

Differ-ences between nested

Aspergillus

PCR (29) findings and the

microarray results are caused by the higher sensitivity of the

nested PCR assay for

Aspergillus

DNA; generally, nested

PCR assays are more sensitive than multiplex PCRs because

of an additional partial amplification of the PCR product in

the second step.

Three other groups previously described the application

of the DNA microarray technology for the detection of

fungal pathogens from cultured clinical isolates. In the study

of Hsiao et al. (16), the capture probes were designed

against the ITS1 and ITS2 regions of the fungal rRNA genes

of filamentous fungi but not of yeasts. The group

deter-mined the detection threshold of the assay by using two

serially diluted fungal DNA samples for all pathogens. In

contrast, our assay defined different species-specific

detec-tion thresholds of both PCR and microarray hybridizadetec-tion

for all 14 fungal species. The second study describing the

detection of fungal pathogens from cultured clinical isolates

was published by Leinberger et al. (20). In this study,

cap-ture probes complementary to the ITS1 and ITS2 regions of

the fungal rRNA genes were spotted on epoxy-coated glass

slides. This DNA microarray contained capture probes from

12

Candida

and

Aspergillus

species, but not from other

clin-ically relevant fungal pathogens. Although universal fungal

primers exist (31), we decided to design primer pairs

ampli-fying the ITS1 regions only, because of the good binding

capacity of shorter DNA fragments of up to 300 bases

dur-ing hybridization, leaddur-ing to a high sensitivity of the assay.

In the study by Leinberger et al., the question of PCR and

hybridization detection thresholds was not addressed. In

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contrast, we focused our interest on a high sensitivity for our

assay because we were investigating noncultured clinical

samples containing only small amounts of fungal DNA.

Huang et al. (17) described another application of the DNA

microarray technology that uses capture probes from the

fungal ITS2 regions of the rRNA genes to identify

patho-genic fungi from standard strains and cultured clinical

iso-lates. The detection of the fungal DNA was carried out

using isolates and additionally spiked blood samples of 16

patients by negative culture, microscopy, or PCR. Their

DNA microarray contains capture probes of 20 fungal

spe-cies. Other pathogens are less relevant than

Candida

,

As-pergillus

, and

Mucor

species for the clinical investigation of

immunocompromised patients with hematologic

malignan-cies.

In addition to those of DNA chip technology tests, the

results of a small number of multifungal PCR-based assays

for the detection and identification of fungal pathogens in

clinical samples have been published (8–10, 14, 19, 21, 27).

These assays cover a different spectrum of targeted fungal

organisms using diverse methodical detection procedures

after an initial PCR step, in order to answer distinct clinical

questions. However, a molecular diagnosis gold standard of

IFI has not yet been defined.

The established multifungal DNA microarray detects

clinically relevant fungal pathogens specifically and at low

detection thresholds from noncultured clinical samples,

de-tecting different fungal pathogens with one test. In view of

the changing spectrum of clinically relevant and emerging

fungal pathogens causing IFI, this new diagnostic approach

meets urgent clinical needs, at least concerning the high-risk

group of patients with hematologic malignancies. This

eval-uation by a prospective multicenter study, testing blood,

BAL, and tissue samples from immunocompromised

pa-tients, especially patients with acute leukemia, and,

compar-ing microarray results with findcompar-ings from conventional

diag-nostic studies, is ongoing.

ACKNOWLEDGMENTS

This work was supported by a grant of the Deutsche Krebshilfe/Dr.

Mildred Scheel Stiftung fu

¨r Krebsforschung (project number 70-3255

Bu 1).

We are indebted to H. Hof, C. Mosbach, and A. Dietz, Institute of

Clinical Microbiology and Hygiene, University Hospital of Mannheim,

for excellent microbiological support.

REFERENCES

1.Ascioglu, S., J. H. Rex, B. de Pauw, J. E. Bennett, J. Bille, F. Crokaert, D. W. Denning, J. P. Donnelly, J. E. Edwards, Z. Erjavec, D. Fiere, O. Lortholary, J. Maertens, J. F. Meis, T. F. Patterson, J. Ritter, D. Selleslag, P. M. Shah, D. A. Stevens, and T. J. Walsh.2002. Defining opportunistic invasive fungal infections in immunocompromised patients with cancer and hematopoi-etic stem cell transplants: an international consensus. Clin. Infect. Dis.

34:7–14.

2.Behr, T., C. Koob, M. Schedl, A. Mehlen, H. Meier, D. Knopp, E. Frahm, U. Obst, K. Schleifer, R. Niessner, and W. Ludwig.2000. A nested array of rRNA targeted probes for the detection and identification of enterococci by reverse hybridization. Syst. Appl. Microbiol.23:563–572.

3.Bethge, W. A., M. Schmalzing, G. Stuhler, U. Schumacher, S. M. Krober, M. Horger, H. Einsele, L. Kanz, and H. Hebart.2005. Mucormycoses in patients with hematologic malignancies: an emerging fungal infection. Haemato-logica90:ECR22.

4.Bille, J., O. Marchetti, and T. Calandra.2005. Changing face of health-care associated fungal infections. Curr. Opin. Infect. Dis.18:314–319. 5.Buchheidt, D., M. Hummel, D. Schleiermacher, B. Spiess, and R. Hehlmann.

2004. Current molecular diagnostic approaches to systemic infections with

aspergillus species in patients with hematological malignancies. Leuk. Lym-phoma45:463–468.

6.Buchheidt, D., and M. Hummel.2005.Aspergilluspolymerase chain reaction (PCR) diagnosis. Med. Mycol.43:139–145.

7.Castagnola, E., S. Cesaro, M. Giacchino, S. Livadiotti, F. Tucci, G. Zanazzo, D. Caselli, I. Caviglia, S. Parodi, R. Rondelli, P. E. Cornelli, R. Mura, N. Santoro, G. Russo, R. De Santis, S. Buffardi, C. Viscoli, R. Haupt, and M. R. Rossi.2006. Fungal infections in children with cancer: a prospective, multi-center surveillance study. Pediatr. Infect. Dis. J.25:634–639.

8.Diaz, M. R., and J. W. Fell.2004. High-throughput detection of pathogenic yeasts of the genusTrichosporon. J. Clin. Microbiol.42:3696–3706. 9.Diaz, M. R., T. Boekhout, B. Theelen, M. Bovers, F. J. Cabanes, and J. W.

Fell.2006. Microcoding and flow cytometry as a high-throughput fungal identification system forMalasseziaspecies. J. Med. Microbiol.55:1197– 1209.

10.Einsele, H., H. Hebart, G. Roller, J. Lo¨ffler, I. Rothenhofer, C. A. Mu¨ller, R. A. Bowden, J. van Burik, D. Engelhard, L. Kanz, and U. Schumacher.

1997. Detection and identification of fungal pathogens in blood by using molecular probes. J. Clin. Microbiol.35:1353–1360.

11.Girmenia, C., M. Nucci, and P. Martino.2001. Clinical significance of As-pergillusfungaemia in patients with haematological malignancies and inva-sive aspergillosis. Br. J. Haematol.114:93–98.

12.Guiot, H. F., W. E. Fibbe, and J. W. van’t Wout.1994. Risk factors for fungal infection in patients with malignant hematologic disorders: implications for empirical therapy and prophylaxis. Clin. Infect. Dis.18:525–532. 13.Healy, M., K. Reece, D. Walton, J. Huong, K. Shah, and D. P. Kontoyiannis.

2004. Identification to the species level and differentiation between strains of Aspergillusclinical isolates by automated repetitive-sequence-based PCR. J. Clin. Microbiol.42:4016–4024.

14.Hendolin, P. H., L. Paulin, P. Koukila-Kahkola, V. J. Anttila, H. Malmberg, M. Richardson, and J. Ylikoski.2000. Panfungal PCR and multiplex liquid hybridization for detection of fungi in tissue specimens. J. Clin. Microbiol.

38:4186–4192.

15.Henry, T., P. C. Iwen, and S. H. Hinrichs.2000. Identification ofAspergillus species using internal transcribed spacer regions 1 and 2. J. Clin. Microbiol.

38:1510–1515.

16.Hsiao, C. R., L. Huang, J. P. Bouchara, R. Barton, H. C. Li, and T. C. Chang.

2005. Identification of medically important molds by an oligonucleotide array. J. Clin. Microbiol.43:3760–3768.

17.Huang, A., J. W. Li, Z. Q. Shen, X. W. Wang, and M. Jin.2006. High-throughput identification of clinical pathogenic fungi by hybridization to an oligonucleotide microarray. J. Clin. Microbiol.44:3299–3305.

18.Lass-Flo¨rl, C., E. Gunsilius, G. Gastl, H. Bonatti, M. C. Freund, A. Gschwendter, G. Kropshofer, M. P. Dietrich, and A. Petzer.2004. Diag-nosing invasive aspergillosis during antifungal therapy by PCR analysis of blood samples. J. Clin. Microbiol.42:4154–4157.

19.Lau, A., S. Chen, T. Sorell, D. Carter, R. Malik, P. Martin, and C. Halliday.

2007. Development and clinical application of a panfungal PCR assay to detect and identify fungal DNA in tissue specimens. J. Clin. Microbiol.

45:380–385.

20.Leinberger, D. M., U. Schumacher, I. B. Autenrieth, and T. T. Bachmann.

2005. Development of a DNA microarray for detection and identification of fungal pathogens involved in invasive mycoses. J. Clin. Microbiol.43:4943– 4953.

21.Loeffler, J., N. Henke, H. Hebart, D. Schmidt, L. Hagmeyer, U. Schumacher, and H. Einsele.2000. Quantification of fungal DNA by using fluorescence resonance energy transfer and the Light Cycler system. J. Clin. Microbiol.

38:586–590.

22.Marchetti, O., J. Bille, U. Fluckiger, P. Eggimann, C. Ruef, J. Garbino, T. Calandra, M. P. Glauser, M. G. Tauber, and D. Pittet.2004. Epidemiology of candidemia in Swiss tertiary care hospitals: secular trends, 1991–2000. Clin. Infect. Dis.38:311–320.

23. Reference deleted.

24.Martino, R., and C. Viscoli.2006. Empirical antifungal therapy in patients with neutropenia and persistent or recurrent fever of unknown origin. Br. J. Haematol.132:138–154.

25.Maschmeyer, G.2006. The changing epidemiology of invasive fungal infec-tions: new threats. Int. J. Antimicrob. Agents27:3–6.

26.Pfaller, M. A., and D. J. Diekema.2004. Rare and emerging opportunistic fungal pathogens: concern for resistance beyondCandida albicansand As-pergillus fumigatus. J. Clin. Microbiol.42:4419–4431.

27.Schabereiter-Gurtner, C., B. Selitsch, M. L. Rotter, A. M. Hirschl, and B. Willinger.2007. Development of novel real-time PCR assays for detection and differentiation of eleven medically importantAspergillusandCandida species in clinical specimens. J. Clin. Microbiol.45:906–914.

28.Seifarth, W., B. Spiess, U. Zeilfelder, C. Speth, R. Hehlmann, and C. Leib-Mo¨sch.2003. Assessment of retroviral activity using a universal retrovirus chip. J. Virol. Methods112:79–91.

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29.Skladny, H., D. Buchheidt, C. Baust, F. Krieg-Schneider, W. Seifarth, C. Leib-Mo¨sch, and R. Hehlmann.1999. Specific detection ofAspergillus spe-cies in blood and bronchoalveolar lavage samples of immunocompromised patients by two-step PCR. J. Clin. Microbiol.37:3865–3871.

30.Spiess, B., D. Buchheidt, C. Baust, H. Skladny, W. Seifarth, U. Zeilfelder, C. Leib-Mo¨sch, H. Mo¨rz, and R. Hehlmann.2003. Development of a Light-Cycler PCR assay for detection and quantification ofAspergillus fumigatus

DNA in clinical samples from neutropenic patients. J. Clin. Microbiol.41:

1811–1818.

31.White, T. J., T. Bruns, S. Lee, and J. Taylor.1990. Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics, p. 315–322.InM. Innis, J. Gelfand, J. Sninsky, and T. White (ed.), PCR protocols: a guide to methods and application. Academic Press, Inc., San Diego, CA.

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Figure

TABLE 1. Composition of fungal and human ITS1 genes, housekeeping genes, and Arabidopsis thaliana-specific primer sets used foramplification of the hybridization probes
TABLE 2. Capture probe sequences derived from the ITS1 regions of the corresponding organisms and sequence sources
FIG. 1. Schematic composition of glass microarray and grid location of fungal, human, and A
FIG. 2. (A) Typical hybridization patterns using 5 ng genomic DNA of the different fungal species, presented by false color mapping
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References

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