R

ESEARCH

A

RTICLE

Proteomics of drug resistance in Candida glabrata
biofilms

C. Jayampath Seneviratne

1

, Yu Wang

2

, Lijian Jin

1

, Y. Abiko

3

and Lakshman P. Samaranayake

1

1

Oral Biosciences, Faculty of Dentistry, The University of Hong Kong, Hong Kong

2

Department of Pharmacology and Pharmacy, The University of Hong Kong, Hong Kong

3

Biochemistry and Molecular Biology, Nihon University School of Dentistry at Matsudo, Chiba, Japan

Received: August 21, 2009

Revised: December 15, 2009

Accepted: December 20, 2009

Candida glabrata is a fungal pathogen that causes a variety of mucosal and systemic infections
among compromised patient populations with higher mortality rates. Previous studies have
shown that biofilm mode of the growth of the fungus is highly resistant to antifungal agents
compared with the free-floating or planktonic mode of growth. Therefore, in the present
study, we used 2-D DIGE to evaluate the differential proteomic profiles of C. glabrata under
planktonic and biofilm modes of growth. Candida glabrata biofilms were developed on
polystyrene surfaces and age-matched planktonic cultures were obtained in parallel. Initially,
biofilm architecture, viability, and antifungal susceptibility were evaluated. Differentially
expressed proteins more than 1.5-fold in DIGE analysis were subjected to MS/MS. The
transcriptomic regulation of these biomarkers was evaluated by quantitative real-time PCR.
Candida glabrata biofilms were highly resistant to the antifungals and biocides compared with
the planktonic mode of growth. Candida glabrata biofilm proteome when compared with its
planktonic proteome showed upregulation of stress response proteins, while glycolysis
enzymes were downregulated. Similar trend could be observed at transcriptomic level. In
conclusion, C. glabrata biofilms possess higher amount of stress response proteins, which
may potentially contribute to the higher antifungal resistance seen in C. glabrata biofilms.

Keywords:
2-D DIGE / Biofilm / Candida glabrata / Microbiology / Stress response

1

Introduction

Candida glabrata has emerged as a major pathogen among
compromised patient groups such as HIV/AIDS patients,
transplant recipients, and patients receiving chemotherapy
[1–3]. Candida glabrata infections rank second to those of
Candida albicans among all forms of candidiasis [4], and C.

glabrata infections have the highest mortality rate among
infections due to non-albicans Candida species. The repor-
ted mortality associated with C. glabrata candidemia is
approximately 50% among cancer patients and as high as
100% among bone marrow transplant patients [4].

Candida infections primarily begin with adherence and

colonization on an artificial or a biotic host surface. This
process leads to the formation of surface-attached commu-
nities known as biofilms, which are structured communities
of microorganisms that are encased in a matrix of exopoly-
meric substances. Biofilms of microorganisms display
unique characteristics that confer a survival advantage over
their planktonic or free-floating counterparts [5]. Formation
of biofilms is the predominant mode of growth of micro-
organisms in nature, and it is estimated that at least 65% of
all microbial infections are related to biofilms [6]. Previous
studies have shown that biofilm-forming ability is a major
virulence attribute of C. glabrata, and a major contributing
factor is higher antifungal resistance [7–10]. Candida

Abbreviations: CLSM, confocal laser scanning microscopy; MIC,
minimum inhibitory concentration; SEM, scanning electron
microscopy; Q-RT-PCR, quantitative–real-time PCR; XTT, tetra-
zolium salt 2,3-bis(2-methoxy-4-nitro-5-sulfophenyl)-5-[(pheny-
lamino)carbonyl]-2H-tetrazolium hydroxide; YNB, yeast nitrogen
base medium

Correspondence: Professor Lakshman P. Samaranayake, Oral
Biosciences, Faculty of Dentistry, The University of Hong Kong,
Prince Philip Dental Hospital, 34 Hospital Road, Hong Kong
E-mail: [e-mail]
Fax: [phone]

&

2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

www.proteomics-journal.com

1444

Proteomics 2010, 10, 1444–1454

DOI 10.1002/pmic.200900611

glabrata possesses both innate and acquired resistance
against antifungal drugs due to its ability to modify ergo-
sterol biosynthesis, mitochondrial function, or antifungal
efflux, and higher antifungal resistance within biofilms
makes C. glabrata biofilms even more difficult to manage.

The molecular mechanisms underpinning drug resistance

of C. glabrata within biofilms are still elusive but need to be
understood to allow the development of new management
strategies against C. glabrata infections. One can utilize the
‘‘hypothesis-free’’ system biology tools of ‘‘proteomics,
genomics, and bioinformatics’’ to investigate the molecular
machinery of the biofilm mode of the growth of C. glabrata
and hence can propose a possible mechanism of higher
antifungal resistance. So far, only a few studies have explored
the proteome of C. glabrata [11, 12], and there appear to be no
studies on C. glabrata biofilms. In a previous study, we
performed a comparative proteomic analysis on the plank-
tonic and biofilm modes of C. albicans [13]. We found that
C. albicans biofilms are associated with increased anti-oxida-
tive capacities, which we hypothesized are associated with
higher antifungal resistance during the biofilm growth.
Therefore, the aim of this study was to compare the proteome
of planktonic and biofilm modes of C. glabrata to explore the
mechanisms that might contribute to the virulence of this
organism. Furthermore, we compared the differential
proteomic expression of C. glabrata with those of C. albicans
from our previous study in an attempt to obtain a wider view
of higher antifungal resistance in Candida biofilms.

2

Materials and methods

2.1

Organisms and growth conditions

We used two C. glabrata strains: a reference laboratory strain
of C. glabrata ATCC 90030 from the archival collection of the
Oral Biosciences Laboratory of the Faculty of Dentistry, and
a wild-type strain C. glabrata Cg-5, which has been
previously characterized [9]. The identity of the yeast isolates
was confirmed using the commercially available API32C
identification system (bioMe

´rieux, Marcy l’Etoile, France).

Candida glabrata strains were subcultured on Sabouraud’s
dextrose agar (Gibco, Paisley, UK) and maintained at 41C
during the experimental period. The purity of the cultures
was confirmed periodically by Gram staining and the germ-
tube test.

2.2

Preparation of standard yeast cell suspension

Candida were grown in Sabouraud’s dextrose agar at 371C
for 18 h and then inoculated in yeast nitrogen base medium
(YNB, Difco, USA) supplemented with 50 mM glucose [14].
After overnight culture in a rotary shaker at 75 rpm, yeast
cells were harvested in the late exponential growth phase
and washed twice with 20 mL of PBS (pH 7.2, 0.1 M).

2.3

Biofilm formation

Yeast cells were resuspended in YNB supplemented with
100 mM glucose and adjusted to a cell density of 1.0  10

7

cells/mL to achieve optimal biofilm formation [14, 15].
Candida glabrata biofilms were formed in wells of polystyrene
culture plates (Iwaki, Tokyo, Japan) as previously described
[16]. For the antifungal susceptibility assays, 100 mL of the
1.0  10

7

cells/mL cell suspension was placed in each well of

96-well plates. For all other experiments, 1 mL of cell
suspension was placed in each well of 12-well plates. As
negative controls, some wells received no Candida suspen-
sion. Plates were first incubated at 371C in a shaker at 75 rpm
for 1.5 h to allow yeast to adhere to the well surface. The
medium was then removed by aspiration, each well was
washed with 1 mL of PBS to remove non-adherent cells, and
2 mL of YNB with 100 mM glucose was pipetted into each
well. Plates were then incubated at 371C with shaking for
48 h. For the proteomics and transcriptomic analyses, age-
matched planktonic cultures in test tubes were prepared in
parallel and incubated in an orbital shaker at 371C.

2.4

Antifungal susceptibility of planktonic and
biofilm modes of C. glabrata

Antifungal susceptibility testing was performed on both
planktonic and biofilm samples of C. glabrata. Four anti-
fungal drugs commonly used to treat oropharyngeal and
systemic candidiasis were selected for the study: caspo-
fungin (Merck, USA), which is a relatively new echino-
candin; nystatin, a polyene (Sigma, USA); amphotericin B, a
polyene (Sigma); and ketoconazole, an azole (Sigma). The
antifungal agents were prepared as previously described
[17].

For the planktonic samples of C. glabrata, the minimum

inhibitory concentration (MIC) of each drug was determined
according to the relevant protocol of the Clinical and
Laboratory Standards Institute [18]. Antifungal susceptibility
for C. glabrata biofilms was performed using standard XTT
reduction assay, as described previously [16, 19]. In brief,
after 48 h of biofilm formation, the medium was removed
and biofilms were washed with 100 mL PBS to remove non-
adherent cells. The stock solutions of drug were diluted with
RPMI 1640, supplemented with 2% glucose to obtain drug
concentrations ranging from 100 to 0.1 mg/mL for caspo-
fungin, 240 to 0.225 mg/mL for amphotericin B, and 64 to
0.125 mg/mL for nystatin and ketoconazole. After 100 mL of
drug solution had been added to each well, plates were
incubated at 371C for 24 h and the metabolic activity of
fungal cells was determined by the XTT assay. The MIC
for drug activity against Candida biofilms was defined as
the lowest drug concentration that reduced the optical
density in XTT readings by 50% compared with the drug-
free control. Each experiment was repeated three times
with four replicates.

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2.5

Oxidative stress tolerance of planktonic and
biofilm modes of C. glabrata

Oxidative stress tolerance of the planktonic and biofilm
modes of C. glabrata was evaluated using two clinical
biocides: NaOCl and H

2

O

2

. The MICs of these two biocides

in planktonic and biofilm modes of C. glabrata were deter-
mined with the relevant protocol of the Clinical and
Laboratory Standards Institute and the XTT reduction assay,
respectively.

2.6

Scanning electron microscopy and confocal
scanning laser microscopy

Candida biofilms were developed for 48 h on polystyrene
discs under similar conditions as described above and
processed for scanning electron microscopy (SEM) and
confocal scanning laser microscopy (CLSM), as described
previously [13]. The topographic features of the biofilm were
visualized by SEM (XL30CP; Philips) in high-vacuum mode
at 10 kV, and images were processed for display with
Photoshop software (Adobe Systems, Mountain View, CA,
USA). For CLSM imaging, Candida biofilms were gently
washed twice with PBS and stained with SYTO-9 and
propidium iodide stains in the Live/Dead BacLight Viability
kit (Molecular Probes, Eugene, OR, USA). Biofilms were
incubated with the two stains for 20 min in the dark at 301C
before the CLSM. Subsequently, images of the stained
biofilms were captured using a CLSM imaging system
(FLUOVIEW FV 1000; Olympus, Tokyo, Japan).

2.7

Proteomic experiments

The C. glabrata Cg-5 isolate was selected for comparative
proteomic studies using an optimized protein extraction
method that had been used previously for proteomic studies
of C. albicans biofilms [13]. Briefly, cell pellets were resus-
pended in 500 mL of b-mercaptoethanol buffer [20] and an
equal volume of 0.5-mm diameter glass beads. Cells were
mechanically disrupted by seven cycles of shaking in a
Vortex Genie-1 mixer (Scientific Industries, USA) for 30 s
followed by 3 min of cooling on ice. Cell extracts were
centrifuged for 13 200 rpm for 15 min and the supernatant
was quantified for protein content by the Bradford assay
(Bio-Rad, Hercules, CA, USA).

2.8

2-D DIGE

2-D DIGE was performed as previously described [21]. All
2-D DIGE reagents and equipment for isoelectric focusing
(including IPGphor, Immobiline DryStrip kit, Immobiline
Drystrips (18 cm, pH 4–7 linear gradient), IPG buffer, and
the Ettan DALT system) were purchased from GE Health-

care, USA. Sequencing-grade trypsin was from Promega
(Madison, WI, USA).

For sample labeling, 50 mg of the lysate was labeled with

400 pmol of cyanine dyes, Cy3 or Cy5, according to standard
protocols. Cy2 was used to label the internal standard, which
comprised equal amounts of proteins from all samples. The
labeling was terminated by the addition of 1 mL of 10 mM
lysine. The labeled samples were then randomly mixed to
allow every gel to contain 50 mg each of Cy2-labeled internal
standard and Cy3- or Cy5-labeled samples. The labeled
samples were randomly mixed to allow every gel to contain
50 mg each of Cy2-labeled internal standard and Cy3- and
Cy5-labeled samples. For the first dimension separation, the
labeling mixture was applied to three Immobiline DryStrips
(18 cm, pH 4–7 linear) by cup loading with a total running
time of 55 kV/h of the IEF. The second dimension was
carried out with three 12.5% SDS-PAGE gels, and gel
images were subsequently acquired at the recommended
wavelengths by using a Typhoon 9410 high-performance gel
and blot imager (GE Healthcare). In total, nine images with
good separation qualities were analyzed using DeCyder
differential in-gel analysis and biological variation analysis
software programs (GE Healthcare). For analysis, a gel with
the most detected protein spots was chosen as the master
image, against which spots of all the other gel images were
matched. The internal standards (Cy-2 images) were inclu-
ded in the analysis procedure to eliminate technical varia-
tion. Highly reproducible protein spots that up- or
downregulated greater than 1.5-fold between planktonic
versus biofilm proteomes with a Student’s t-test p-value of
less than 0.05 were considered for MS identification.

2.9

MS

For protein identification, the cyanine dye-labeled gels were
subsequently stained with modified silver staining, as
described previously [22]. Differentially expressed spots were
selected after DeCyder analysis of the DIGE images and
were excised from the gels. In-gel trypsin digestion was
performed manually according to a previously described
protocol [23]. The peptides were extracted from the gel
pieces, concentrated, and desalted with the ZipTip kit
(Millipore, USA), and 1 mL of each sample was mixed with
1 mL of matrix solution containing 0.01 g/mL CHCA for MS
analysis in a Voyager-DE STR MALDI-TOF MS system and
an ABI 4800 MALDI-TOF/TOF MS/MS (Applied Biosys-
tems, Foster City, CA, USA).

Peptide mass lists and peptide fragment sequences were

generated for protein identification using Data Explorer
software version 4.9 and 4000 series Explorer

TM

software V

3.5, respectively. For MS analysis, laser intensity of 2500 was
used and eight sub-spectra with 50 shots each were acquired
for each sample spot. Calmix 1 and 2 (Applied Biosystems)
were used for external calibration with mass tolerance of
100 ppm. Keratin and trypsin autodigestion peaks were

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excluded. Peak filtering was from 800 to 4000 Da with S/N
filter 410 for database searching. For MS/MS analysis, laser
intensity of 3100 was used. The precursor tolerance was
0.2 Da and the MS/MS precursor resolution was set at 350.
Twenty-five sub-spectra with the total of 2500 shots were
acquired for each sample spot with metastable suppressor
on. Mass tolerance of fragment ion was 0.1 Da.

2.10

Database search

An in-house MASCOT v2.1 (Matrix Science) searching
engine

(http://www.matrixscience.com/search_form_se-

lect.html) was used to identify candidate proteins against the
NCBInr database (Fungi, protein entries 467215). These
candidates were subsequently clarified with the C. glabrata
genome database (www.genolevures.org). The criteria
used in the search were as follows: modifications including
Cys as S-carbamidomethyl derivate and Met as oxidized
methionine, one missed cleavage site, pI 3–0, and a protein
mass range from 10 to 500 kDa [21]. For protein identifica-
tion from both MS and MS/MS, probability scores were
taken to be significant if the p-value was

o0.05. For all

significant identifications, both protein and total ion scores
were above or equal to the 95% confidence interval. To
assign putative molecular functions for identified C. glabrata
proteins, we searched the following bioinformatics data-
bases: Saccharomyces cerevisiae genomic database (www.
yeastgenome.org/), C. albicans genomic databases (www.
candidagenome.org and http://www.broad.mit.edu/annota-
tion/fgi/), and the MIPS database (http://mips.gsf.de/
genre/proj/yeast/index.jsp).

2.11

Isolation of total RNA, cDNA synthesis, and
quantitative real-time PCR

Total RNA was extracted from both C. glabrata Cg-5 and
ATCC planktonic and biofilm samples, as described
previously [24]. Briefly, the SV Total RNA isolation kit
(Promega) was used according to the manufacturer’s
instructions, and RNA purity and integrity were quantified
in a NanoDrop ND-1000 spectrophotometer (NanoDrop
Technologies). Gel electrophoresis was also performed to
verify intact RNA. cDNA was synthesized by RT-PCR at
431C for 90 min in a 20-mL reaction volume containing 1 mg
of total RNA, 1 mL (200 U) of Superscript II (Gibco-BRL),
0.5 mg of oligo dT-primer, first-strand buffer, 10 mM DTT,
and 1 mM dNTPs. A control reaction was performed without
reverse transcriptase for all the isolates to verify the absence
of genomic DNA contamination.

Quantitative real-time PCR (Q-RT-PCR) was used to

evaluate gene expression levels of the proteins that had
shown significant up- or downregulation at transcriptomic
level. Tests were carried out in duplicate in at least three
separate experiments. Q-RT-PCR was carried out with the

ABI PRISM 7900HT sequence detection system using Syber
Green (SYBR Green PCR master mix; Applied Biosystems).
The primers (Sigma) are listed in Table 1. Prior to the
experiment, several housekeeping genes were tested for
their stability across the samples. URA3 was selected as the
most stable candidate and therefore used for normalization.
Each 20-mL PCR reaction contained 10 mL SYBR, 1 mL of
cDNA, 2 mL of primer mix, and 7 mL of double-distilled
water. Step 1 took place at 501C for 2 min, step 2 at 951C for
10 min, and step 3 at 951C for 15 s and 601C for 1 min for 40
cycles. Melting curve analysis and gel electrophoresis was
performed to confirm specificity of the product. Relative
transcriptomic expressions of the selected genes were
analyzed using DDCt Pfaffl method taking their PCR effi-
ciencies into account [25].

3

Results

3.1

Antifungal susceptibility and oxidative stress
tolerance of planktonic and biofilm modes

Antifungal susceptibility testing of the planktonic and
biofilm modes of C. glabrata showed that Candida biofilms
are considerably more resistant to antifungals than their
planktonic counterparts, irrespective of the class of the
antifungal (Table 2). Moreover, C. glabrata biofilms were
less susceptible to the clinical biocides (Table 2). Hence, it
seemed that C. glabrata biofilms were more tolerant to the
oxidative stress than its planktonic counterparts.

3.2

Microscopy of C. glabrata biofilms

Both SEM and CLSM images showed mature biofilm
architecture in C. glabrata biofilms by 48 h. Multilayered
C. glabrata biofilms were composed of blastospores

Table 1. Primer sequences of the selected genes for transcript-

omic analysis using Q-RT-PCR

Gene

Primer sequence

URA3 F

5

0

-GGGCTTTGACTGGCTAATAATGAC-3

0

URA3 R

5

0

-CCAAGTGCATCGCCTTTATCA-3

0

PEP4 F

5

0

-AAGAAGGAAAAATTGACCAAGGAA-3

0

PEP4 R

5

0

-GCCTTCTCATATTGACTCACGTACTT-3

0

HSP12 F

5

0

-TGAATCCTACGCAGACACTGCTA-3

0

HSP12 R

5

0

-CGGCATCGTTCAACTTGGA-3

0

TRX1 F

5

0

-CGAAAAGTTCGCTGCTGAATACT-3

0

TRX1 R

5

0

-TCTGGCAACTCGTCGACATC-3

0

FBA1 F

5

0

-CCAGCTTACGGTATCCCAGTTG-3

0

FBA1 R

5

0

-TACCATCGTACCATGGCAATAGC-3

0

ENO1 F

5

0

-GTGTCATGGTTTCCCACAGATCT-3

0

ENO1 R

5

0

-AGTTCTCAAACCGACGACCAA-3

0

GPM1 F

5

0

-GCTGACTCCCCATACTCTCAAAA-3

0

GPM1 R

5

0

-TCAATGACCAAAGCCAAAGATTC-3

0

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embedded in thick extracellular matrix in both SEM and
CLSM images (Supporting Information Figs. 1 and 2).

3.3

2-D DIGE profiles of C. glabrata biofilms

As shown in the representative images (Figs. 1A and B),
protein spots were evenly distributed across the 4–7 pI range
in the first dimension and between 15 and 160 kDa after
12.5% SDS-PAGE in the second dimension. Approximately
900 spots were detected in each image by DeCyder DIA
image analysis. Comparison of the differentially expressed
proteins in the biofilm and planktonic modes of C. glabrata
using the DeCyder software revealed that there were 17
upregulated and 7 downregulated protein spots (1.5 times or
more) (Fig. 1C). These protein spots were examined further
by MS/MS analysis.

3.4

Tandem mass spectrometric identification of
differentially expressed proteins

MS and MS/MS were used to study the 17 upregulated and
7 downregulated proteins in C. glabrata biofilms (Fig. 1B,
Table 3). To avoid confusion regarding the identity of the
proteins, nomenclatures of the proteins were retrieved from
four relevant bioinformatics databases (Table 3). Although
C. glabrata falls in a similar genus to C. albicans, it exhibits
substantial differences in its structure and biological prop-
erties. Furthermore, in the taxonomic lineage, C. glabrata is
closer to S. cerevisiae non-pathogenic yeast. Therefore,

considering the availability of annotated information and
evolutionary proximity of C. glabrata and S. cerevisiae, iden-
tified proteins were named according to the S. cerevisiae
database (www.yeastgenome.org).

Biological data mining with bioinformatics databases

revealed that the studied proteins belonged to several func-
tional

categories,

including

stress-response

proteins,

enzymes related to carbohydrate metabolism, and trans-
porters (Table 3). Among the upregulated protein biomar-
kers were a number of stress-response proteins such as heat
shock protein-12 (Hsp12p), cytoplasmic thioredoxin iso-
enzyme (Trx1p), alkyl hydroperoxide reductase (Ahp1p),
vacuolar aspartyl protease (Pep4p), aldehyde dehydrogenase
(Ald2p), and alcohol dehydrogenase isoenzyme III (Adh3p).
Among the downregulated proteins were several biomarkers
corresponding to key enzymes involved in glycolysis. These
included fructose-1,6-bisphosphate aldolase (Fba1p), glycer-
aldehyde-3-phosphate dehydrogenase (Thd3p), phosphogly-
cerate mutase (Gpm1p), enolase (Eno1p), and alcohol
dehydrogenase (Adh1p). On the contrary, transaldolase,
which belongs to the non-oxidative branch of pentose
phosphate pathway, was identified among the upregulated
proteins.

Some of the proteins, such as enolase (Eno1p), transal-

dolase (Tal1p), fructose-1,6-bisphosphate aldolase (Fba1p),
alcohol dehydrogenase (Adh1p), and glyceraldehyde-3-
phosphate dehydrogenase (Tdh3p) had different isoforms
with a slightly different M

r

and pI (Fig. 1B, Table 2). These

results suggest that these biofilm-related proteins were
subjected to posttranslational modifications, which may
result in different functional assembly of the isoforms.

3.5

Transcriptomic analysis by Q-RT-PCR

To evaluate the relative transcriptomic expression of the
up- and downregulated proteins, Q-RT-PCR was carried
out using SyberGreen assay (SYBR Green PCR master
mix; Applied Biosystems) for both C. glabrata Cg-5 and
C. glabrata ATCC strains, which we have previously shown
to be comparable biofilm formers [26]. The transcriptomic
level of all the selected genes in both the species showed
similar trends to those in the proteomic analyses. For
instance, HSP12, PEP4, and TRX1 were upregulated,
whereas ENO1, FBA1, and GPM1 were downregulated at
the transcriptomic level, thereby corroborating proteomic
findings (Fig. 2).

4

Discussion

Candida glabrata is the second most prevalent fungal
pathogen in humans after C. albicans. As compromised host
populations have been growing worldwide, the prevalence of
C. glabrata infections, particularly of systemic origin, has
also been increasing in the recent years [4]. Biofilm-forming

Table 2. Antifungal and clinical biocide susceptibility of plankto-

nic and biofilm modes of C. glabrata

Minimum inhibitory concentration

C. glabrata
strain

Planktonic
mode

Biofilm
mode

Antifungal
Caspofungin

ATCC

0.2

100

Cg5

0.8

4100

Amphotericin B

ATCC

0.23

16

Cg5

0.93

32

Nystatin

ATCC

2

16

Cg5

4

32

Ketoconazole

ATCC

0.125

464

Cg5

0.25

464

5-FC

ATCC

0.8

4420

Cg5

1.6

4420

Biocide
NaOCl

ATCC

0.01%

0.30%

Cg5

0.01%

0.30%

H

2

O

2

ATCC

0.02%

2.10%

Cg5

0.02%

4.30%

MIC is indicated as mg/mL for antifungals and as a percentage
(%) for biocides.

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ability is known to be a major virulence attribute of
Candida species including C. glabrata. In the present study,
C. glabrata biofilms were much more resistant to four
clinically used antifungal agents than their planktonic
counterparts. Moreover, C. glabrata biofilms were more
tolerant than planktonic cells to the oxidative stress gener-
ated by two clinically used biocides. These results agree with
those of previous studies on C. glabrata biofilms [7, 27].
Hypothesized mechanisms to explain the higher antifungal
traits seen in the biofilm mode of Candida include robust
biofilm architecture, decreased metabolic activity, altered
gene expression, extracellular matrix, presence of ‘‘persister
cells’’, and higher anti-oxidative capacities [28–31]. However,
the exact mechanism by which fungi acquire higher resis-
tance in the biofilm mode of growth is yet to be elucidated.

Cellular imaging obtained by SEM and CLSM showed

that C. glabrata biofilms are exclusively composed of
blastospores that are devoid of hyphal cells, in contrast to
C. albicans biofilms, which show a predominance of hyphae.
Hence, the architecture of the C. glabrata biofilms is
distinctly different from that of C. albicans biofilms, as we
have observed previously [13]. Nevertheless, C. glabrata

biofilms are highly resistant to antifungal agents, as are
C. albicans biofilms [16]. Thus, it is tempting to speculate
that a common mechanism exists in the biofilm mode of
Candida that confers higher antifungal resistance. Exploring
the molecular mechanisms of biofilm growth of these
Candida species may help in the understanding of the
generic and specific pathways pertaining to higher anti-
fungal resistance, but there appear to be no studies in the
literature on the proteomic profiles of C. glabrata biofilms.
Limited data on biofilms of other Candida species suggest
that protein profiles are differentially expressed in proteome
of biofilms and planktonic cultures [20, 32–34].

Unlike traditional 2-DE, 2-D DIGE offers increased

capacity for spot matching and accurate quantitative analysis
of multiple groups of samples with relative ease. Therefore,
2-D DIGE technology was used in the present study to
examine differential protein expression between the two
growth modes of Candida. The 24 spots that were up- or
downregulated by more than 1.5 times were identified by
both peptide mass fingerprinting and peptide fragment
sequencing (Table 3). Pathway analysis of the protein
changes suggested a downregulation of the glycolytic

Figure 1. 2-D DIGE images (overlay (A) and silver stained (B)) of biofilm proteome of C. glabrata. (A) Protein lysates (50 mg) labeled with
Cy3, Cy5, or Cy2 (for internal control) were mixed and separated using pH 4–7 isoelectric focusing strips in the first dimension and 12.5%
SDS-PAGE in the second dimension. (B) Annotated spots are those found to be up- or downregulated at equal or over 1.5-folds between
biofilm and planktonic experimental groups. These proteins were subsequently identified by MS/MS (Table 3). (C) Three-dimenional
images of differentially expressed proteins of planktonic and biofilm 2-D DIGE gels analyzed by DeCyder software.

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pathway. At the same time, several proteins in the biofilm
that were associated with stress response were upregulated.
Transcriptomic regulations of identified protein biomarkers
evaluated by Q-RT-PCR in both C. glabrata reference and
wild-type strains corroborated our proteomic findings.
Hence, expression patterns of both mRNA and protein
showed similar trends.

In previous studies, upregulated proteins in C. glabrata

biofilms that were associated with stress responses (Hsp12p,
Trx1p, Ahp1p, Pep4p, and Ald2p) were shown to play an
important roles in the stress responses of yeast [35–38]. We
previously found that oxidative stress-response proteins
were upregulated in C. albicans biofilms and suggested that
these anti-oxidant biomarkers may contribute to the higher
antifungal resistance of C. albicans biofilms [13]. Therefore,
it is important to establish the functional roles of identified
biomarkers in the C. glabrata biofilm proteome and compare
them with those in C. albicans.

One of the upregulated stress-response proteins in the

C. glabrata biofilm proteome is Trx1p, a component of the
oxidative stress defenses of the yeast. The thioredoxin redox
system, which includes Trx1p, is able to protect cells from
reactive oxygen species and plays a key role in defending the
cell against stress, particularly oxidative stress, thereby
maintaining a reduced environment within the cell [38, 39].
This molecule is also upregulated in the C. albicans biofilm
proteome [13]. Hence, it is tempting to speculate that Trx1p
is a part of an oxidative stress-response pathway that, in
turn, plays a role in the biofilm mode of growth of Candida.
Another upregulated oxidative stress-response protein in
C. glabrata biofilms, Ahp1p, has been found to be upregu-

lated during stress conditions in a wide range of micro-
organisms [37, 40], including C. albicans [13]. Taken
together, the results on protein biomarkers imply the exis-
tence of a common pathway in the biofilm mode of both
C. glabrata and C. albicans species that confers higher anti-
oxidative capacity, regardless of architectural and morpho-
logical dissimilarities.

The C. glabrata biofilm proteome also showed differential

expression of other stress-response proteins – for instance,
Hsp12p, which is induced by various forms of stress,
including heat shock, oxidative stress, and osmotic stress
[41]. Previous studies have shown that Hsp12p is an
important stress-response protein in other fungal species
such as S. cerevisiae [35, 37, 38]. Intriguingly, HSP12 gene
has also been shown to be upregulated in azole antifungal
resistance of C. albicans [42]. Cytoplasmic aldehyde dehy-
drogenase (Ald2p) is another stress-response protein that we
found to be upregulated in C. glabrata biofilms. Under stress
conditions, Ald2p, together with Ald3p, removes the accu-
mulated toxic metabolite acetaldehyde by converting it to
acetyl Co-A. Hence, Ald2p is an important enzyme in the
yeast stress response [43].

When cells are exposed to stress conditions, particularly

those inducing oxidative stress, molecules such as nucleic
acids, lipids, proteins, and carbohydrates become oxidized,
and the accumulated oxidized versions need to be removed
fairly efficiently. Therefore, protein degradation, in addition
to repair, plays a key housekeeping role in eliminating
oxidized proteins which is mediated by vacuolar proteinases.
The protein Pep4p is vital for vacuolar proteinase activity
and enables fungi to survive under conditions of oxidative
stress [44]. In the present study, Pep4p was upregulated in
C. glabrata biofilms, again consistent with the major role
played by oxidative stress-response mechanisms in the
biofilm mode of Candida growth.

The findings of this study indicate that glycolysis and

hence energy production is downregulated in the biofilm
mode of growth. Several glycolytic enzymes, including
Fba1p, Tdh3p, Gpm1p, and Eno1p, were downregulated in
C. glabrata biofilms compared with planktonic cultures.
Fba1p catalyzes the hydrolysis of fructose-1,6-bisphosphate
into

glyceraldehyde-3-phosphate

and

dihydroxyacetone

phosphate, Tdh3p catalyzes the phosphorylation of glycer-
aldehyde-3-phosphate into 1,3-bisphosphoglycerate, Gpm1p
catalyzes the conversion of 3-phosphoglycerate into 2-phos-
phoglycerate, and Eno1p catalyzes the conversion of
2-phosphoglycerate to phosphoenolpyruvate. The limited
available genomic and proteomic studies on Candida
biofilms agree with the notion that metabolic activity
decreases as biofilms mature [45]. The development of a
biofilm community into a three-dimensional multilayered
structure leads to the deprivation of nutrients to the bottom
layers. It can be surmised that cells across the biofilm
exhibit differential metabolic activity: while the bottom
layers are in a state of quiescence, metabolic activity of
middle and top layers may still be in an active state. Indeed,

Figure 2. Transcriptomic analyses of the selected genes that
were up- or downregulated at the protein level using Q-RT-PCR.
Note the transcriptomic expression of TRX1 of Cg5 was
approximately similar between planktonic and biofilm modes
(log

10

0.004

70.001).

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Candida biofilms have been found to contain heterogeneous
cells with variable metabolic activity [46, 47]. Reduced
metabolic activity may reflect energy and nutrient conser-
vation to avoid stress inducers, as well as activation of the

glyoxylate pathway, which is important in producing cell-
wall carbohydrates and exopolymeric substances [48].

The protein Atp2p, which was upregulated in C. glabrata

biofilms in this study, has been shown to be upregulated

Table 3. Differentially expressed proteins identified by MS/MS

Spot
no.

Protein
name

Identifier

Gene
Cg

Gene
Sac

Gene
Ca

Unique
peptide

Sequence
coverage
(%)

Biofilm/
Planktonic

Factor

289

Cytoplasmic aldehyde

dehydrogenases

gi|50287753 CAGL0F07777g

ALD2

ALD4

26

50

Up

1.9

379

b subunit of the F1 sector of

mitochondrial ATP
synthase

gi|50288781 CAGL0H00506g ATP2

ATP2

20

46

Up

2.2

436

Enolase/phosphopyruvate

hydratase

gi|50289857 CAGL0I02486g

ENO1

ENO1

22

53

Up

2

511

Golgi vesicle protein of

unknown function

gi|50292761 CAGL0L00891g

GVP36

orf19.1236

14

55

Up

1.7

550

Adenosine kinase

gi|50285923 CAGL0C04983g ADO1

ADO1

12

39

Up

1.9

566

Transaldolase

gi|50285355 CAGL0B03069g TAL1

TAL1

10

30

Up

1.7

575

Transaldolase

gi|50285355 CAGL0B03069g TAL1

TAL1

12

43

Up

1.7

554

Glyceraldehyde-3-

phosphate
dehydrogenase

gi|50288681 CAGL0G09383g TDH3

TDH3

16

62

Up

1.6

743

Protein component of the

small (40S) ribosomal
subunit

gi|50292587 CAGL0K11748g RPS11B orf19.4149.1

9

51

Up

1.5

760

Alkyl hydroperoxide

reductase

gi|50294878 CAGL0M11704g AHP1

AHP1

7

45

Up

1.5

762

Peptidyl-prolyl cis-trans

isomerase

gi|50288871 CAGL0H01529g CPR5

CYP5

3

16

Up

1.6

793

Vacuolar aspartyl protease

(proteinase A)

gi|50294061 CAGL0M02211g PEP4

APR1.

4’

12

Up

7.2

799

Heat shock protein-12

gi|50290911 CAGL0J04202g

HSP12

HSP12

11

84

Up

2.3

801

Peptidyl-prolyl cis-trans

isomerase

gi|50292417 CAGL0K09724g FPR1

RBP1

9

67

Up

1.5

803

Alcohol dehydrogenase

isoenzyme III

gi|68476713 CAGL0I07843g

ADH3

ADH2

6

27

Up

2.4

804

Cytoplasmic thioredoxin

isoenzyme

gi|50291653 CAGL0K00803g TRX1

TRX1

8

88

Up

1.5

805

Cytoplasmic thioredoxin

isoenzyme

gi|50291653 CAGL0K00803g TRX1

TRX1

4

56

Up

2.2

478

Enolase/phosphopyruvate

hydratase

gi|50289857 CAGL0I02486g

ENO1

ENO1

20

49

Down

1.6

509

Fructose-1,6-bisphosphate

aldolase

gi|50292893 CAGL0L02497g

FBA1

FBA1

19

63

Down

2.2

513

Fructose-1,6-bisphosphate

aldolase

gi|50292893 CAGL0L02497g

FBA1

FBA1

17

54

Down

2

526

Alcohol dehydrogenase

gi|50290317 CAGL0I07843g

ADH1

ADH2

14

59

Down

1.5

529

Alcohol dehydrogenase

gi|50290317 CAGL0I07843g

ADH1

ADH2

14

59

Down

1.7

598

Glyceraldehyde-3-

phosphate
dehydrogenase

gi|50290597 CAGL0J00451g

TDH3

TDH3

13

53

Down

1.8

713

Tetrameric

phosphoglycerate
mutase

gi|50287073 CAGL0E06358g

GPM1

GPM1

22

64

Down

1.7

Proteins were named according to the S. cerevisiae genomic database (www.yeastgenome.org), or C. glabrata genomic database
(www.genolevures.org). To avoid confusion in nomenclature, gene names according to NCBInr_200705 FASTA (Identifier), C. glabrata
genomic database (Gene Cg), S. cerevisiae genomic database (Gene Sac), and C. albicans genomic database (Gene Ca)
(www.candidagenome.org) databases are also provided.

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during pseudohyphal growth of C. albicans. Furthermore,
via links with Efg1p, Cph1p, and Tec1p, Atp2p may be
connected to downstream signaling events of the MAP
kinase pathway, which is important for biofilm formation,
stress response, and virulence [49, 50]. However, it is note-
worthy that C. glabrata does not produce true hyphal forms.
In our previous study on C. albicans biofilm proteome,
which used the same methodology as in this study, a
number of upregulated biomarkers were associated with
hyphal proteins, including Sti1p, Ald5p, Cit1p, Mdh1p,
Mcr1p, Egd1p, Ynk1p, and Cyp1p [13]. These protein
biomarkers were not present in the C. glabrata proteome,
suggesting that species-specific molecular mechanisms may
operate in Candida biofilms to preserve morphological and
architectural variability of different species. These findings
validate our methodology to explore the proteomics of
Candida biofilms.

Many studies suggest that Candida in the biofilm mode

possesses higher antifungal resistance than in the plank-
tonic mode. However, the exact molecular mechanism
behind this phenomenon has yet to be described. In the
present study, we have shown that changes in expression
profiles of various stress-response proteins are associated
with the biofilm mode of growth. Cannon et al. suggested
that drug resistance of Candida is in fact a mechanism to
cope with stress [51]. Therefore, it is conceivable that the
biofilm mode of growth, stress response, and antifungal
resistance of Candida may all have a generic link that ulti-
mately helps the fungi to survive in a hostile environment.
From the evidence so far furnished from proteomic studies
of C. albicans and C. glabrata biofilms, we hypothesize that
antifungal resistance is not a primary trait of the biofilm, but
a ‘‘bonus trait’’ that Candida acquires through its stress
response, which represents its integral arsenal to combat
and survive in a wide range of habitats. Further experiments
are needed to explore the potential of this new insight to
devise more efficient antifungal strategies that will bring
clinical and other translational benefits.

We thank Alan Wong, Lawrence Luk, and Priscilla Leung for

technical assistance and Dr. Trevor Lane for editorial assistance.
This work was supported by the Hong Kong Research Grants
Council, RGC no. HKU 7624/06M.

The authors have declared no conflict of interest.

5

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