# Epithelial Cell Gene Expression Induced by  IntracellularStaphylococcus aureus

Authors: Xianglu Li; William G. Fusco; Keun S. Seo; Kenneth W. Bayles; Erin E. Mosley; Mark A. McGuire; Gregory A. Bohach
Journal: International Journal of Microbiology
 (2009)

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## Abstract

HEp-2 cell monolayers were cocultured with intracellularStaphylococcus aureus, and changes in gene expression were profiled using DNA microarrays. Intracellular S. aureus affected genes involved in cellular stress responses, signal transduction, inflammation, apoptosis, fibrosis, and cholesterol biosynthesis. Transcription of stress response and signal transduction-related genes including atf3, sgk, map2k1, map2k3, arhb, and arhe was increased.  In addition, elevated transcription of proinflammatory genes was observed for  tnfa, il1b, il6, il8, cxcl1, ccl20, cox2, and pai1. Genes involved in proapoptosis and fibrosis were also affected at transcriptional level by intracellular  S. aureus. Notably, intracellular  S. aureus induced strong transcriptional down-regulation of several cholesterol biosynthesis genes. These results suggest that epithelial cells respond to intracellular S. aureus by inducing genes affecting immunity and in repairing damage caused by the organism, and are consistent with the possibility that the organism exploits an intracellular environment to subvert host immunity and promote colonization.


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## Body

## 1. Introduction

Staphylococcus aureus (S. aureus), a nosocomial or community-acquired
pathogen that colonizes much of the healthy population [1], is an important cause of
skin infections, pneumonia, septicemia, endocarditis, osteomyelitis,
folliculitis, mastitis, and other infections.  The organism also causes
toxigenic illnesses such as food poisoning and toxic shock syndrome [2].  Infections caused by S. aureus may be refractory to therapy and become chronic or recur,
despite acceptable  therapy [3–6].Several studies
showed thatS. aureus can become
internalized by nonprofessional phagocytes [7–9]; α5β1 integrin is necessary for fibronectin-mediated S. aureus internalization
involving staphylococcal fibronectin-binding proteins [10, 11]. Internalization may provide several benefits to S. aureus. It has been proposed that
intracellular S. aureus evades
exposure to antibiotics [3] and host immunity. It also provides an intracellular
milieu which leads to the formation of small-colony variants with decreased
metabolic activity and increased antibiotic resistance [12].Microarray
technology has helped elucidate pathogen-host cell interactions and profile the
effects on epithelial cells by organisms including, but not limited to,Yersinia
enterocolitica [13], Salmonella dublin
[14], Shigella flexneri [15], Bordetella pertussis
[16], Mycobacterium tuberculosis
[17], Pseudomonas aeruginosa
[18], Listeria monocytogenes
[19], Streptococcus pyogenes
[20], and S. aureus
[21, 22].  Although the internalization of S. aureus by nonprofessional phagocytes
is well documented [5, 7–9, 23–25], the cellular response to
intracellular S. aureus has only been
partially elucidated [3, 26], focusing mainly on apoptosis
[27–33].  The present study assessed global changes in
gene expression over an 8-hour time period in epithelial cell monolayers
induced by intracellular S. aureus.  The data demonstrated that cultured
epithelial cells respond to intracellular S.
aureus by inducing several classes of genes that could influence the
outcome of colonization or infection by this organism in vivo.


## 2. Materials and Methods

### 2.1. Cultures

HEp-2 cells [34] were
purchased from the American Type Culture
Collection (ATCC).  Routine maintenance
was conducted using complete growth medium (CGM) [10]. S. aureus RN6390
[32, 33, 35] provided by A. Cheung
(Dartmouth Medical School) was used to infect HEp-2 cells using established
techniques described previously [8, 32, 33, 36].  Briefly,
bacteria from 16-hour Todd Hewitt broth cultures were washed
three times with phosphate buffered saline (PBS), and resuspended in invasion
medium (IM; CGM lacking antibiotics and FBS) to make
stocks with approximately 109 colony-forming units
(CFU) mL−1.  Bacterial stocks were diluted 10-fold in
fresh IM; 500 μL of the
cell suspension well−1 were used to infect each HEp-2 culture at a
multiplicity of infection (MOI) of 10.
The cocultures were centrifuged immediately to synchronize monolayer
infections and incubated at 37°C for 10 minutes to allow internalization, after
10 minutes, the IM was rapidly replaced with fresh medium containing gentamicin
(100μgmL−1) to kill noninternalized bacteria.  Thereafter, the cocultures were incubated (up
to 8 hours following S. aureus exposure) and analyzed at various times
following exposure to S. aureus as
described below.For growth rate
analyses, cells from 16-hourS. aureus RN6390 TH broth cultures (above)
were pelleted, washed three times with PBS, and diluted with PBS to 105 CFU mL−1.  A 100 μL aliquot
was inoculated into 10 mL of TH broth or IM, with or without FBS (without
antibiotics).  Cultures were incubated
with vigorous shaking up to 8 hours. CFU concentrations were
determined by a standard plate count method.


### 2.2. RNA Isolation and Purification

HEp-2 cells were
harvested at 2, 4, 6, or 8 hours following addition of bacteria.  RNA was isolated using TRIZOL (Invitrogen)
according to the manufacturer’s instructions and further purified with RNAeasy
MinElute Cleanup Kits (Qiagen).  RNA
samples, quantified using a NanoDrop ND-1000
spectrophotometer (Nanodrop Technologies)
and showing OD260:OD280 ratios >1.95
were used for subsequent experiments.


### 2.3. Microarray Methods and Data Analysis

MWG Human 30K microarrays
(MWG) were used according to the manufacturer’s
instructions.  cDNA was
synthesized using the BD Atlas PowerScript Fluorescent Labeling Kit (BD) with
oligo(dT)12-18 primer (Invitrogen).
CyDye Post-Labeling Reactive Dyes (Amersham) were used to fluorescently
label the cDNA (Cy3 for cDNA from uninfected cells and Cy5 for cDNA from S. aureus infected cells).  Unincorporated dye was removed from labeled
cDNA with CHROMA SPIN+TE-30 columns (Clontech).
Labeled cDNA was dissolved in salt-based hybridization buffer (MWG),
incubated at 95°C (3 minutes), chilled on ice, and hybridized to the microarray
chips in the dark for 16–24 hours at 42°C
with slow rocking.  Arrays were washed
and scanned with an Axon 4000A dual channel microarray scanner (Axon) to
generate multi-TIFF images which were processed with GenePix Pro 6.0 software
(Molecular Devices).


### 2.4. Quantitative Real-Time PCR (QRT-PCR)

QRT-PCR was used
to validate selected microarray data.
cDNA was synthesized from 1μg
of RNA using Superscript Π Reverse Transcriptase (Invitrogen).  Primers
(Table 1), designed using Primer
Express 2.0 software (PE Applied Biosystems), were purchased from Integrated
DNA Technologies (IDT).  Data were analyzed as described previously [37].  The threshold cycle (CT) was calculated as the cycle number at which the  ΔRn crossed the
baseline.  Data were normalized by
calculating   ΔCT
[CT of target
−CT of the internal control
(β-actin)].  Normalized   ΔCT
data from S. aureus infected HEp-2
cells were compared to data from uninfected HEp-2 cells by calculating     ΔΔCT [ΔCT
of S. aureus infected HEp-2 cells −ΔCT  of uninfected HEp-2 cells].  Each experiment was conducted thrice for
validation, and the mean value is reported.Table 1
DNA primers
used for QRT-PCR experiments.
GeneForward
primers (5′-3′)Reverse
primers (5′-3′)atf3GATGTCCTCTGCGCTGGAATCCTCGGCTTTTGTGATGGAc-fosGCCCTTTGATGACTTCCTGTTCGGAGCGGGCTGTCTCAGAc-junGCAAAGATGGAAACGACCTTCTGCTCTCGGACGGGAGGAAjunBCTACACGACTACAAACTCCTGAAACCCCCCAGGCGCTTTGAGAsgkGTGCCTGGGAGCTGTCTTGTGCTGTGTTTCGGCTATAAAAAGGarhbTCCCAATGTGCCCATCATCATGCGGGCCAGCTCTGTmap2k3CCCTACATGGCCCCTGAGATCCAGACGTCGGACTTGACAIl1bCGAATCTCCGACCACCACTACTCCATGGCCACAACAACTGAtnfaCCTGGTATGAGCCCATCTATCTGTAGTCGGGCCGATTGATCTCIl6AGCCGCCCCACACAGATCGAGGATGTACCGAATTTGTTTIl8CTGGCCGTGGCTCTCTTGCTTGGCAAAACTGCACCTTCAccl20TCCTGGCTGCTTTGATGTCAAAAGTTGCTTGCTGCTTCTGATTcxcl1AACATCCAAAGTGTGAACGTGAAGAGTGTGGCTATGACTTCGGTTTIl10CTTGTCTGAGATGATCCAGTTTTACCTCCTTGATGTCTGGGTCTTGGTTptgs2GGAAGCCTTCTCTAACCTCTCCTATTAGGGAGTCGGGCAATCATCadmGGATGTCGCGTCGGAGTTTTGCTGGACATCCGCAGTTCdkk1AAGTACCAGACCATTGACAACTACCAGGGACTAGCGCAGTACTCATCAGTigfbp1CCATCTGATGGCCCCTTCTCCTTCGAGCCATCATAGGTACTGcasp9AGGACATGCTGGCTTCGTTTTTCTAGGGTTGGCTTCGACAAtgfb1CCTGGCGATACCTCAGCAACCGGTGACATCAAAAGATAACCAthbs1TCCGCAAAGTGACTGAAGAGAATGAACTCCGTTGTGATAGCATAGGcyr61GGTGGAGTTGACGAGAAACAATGAGGGAGCCGCTTCAGTGAhmgcrCCCAGTTGTGCGTCTTCCATGCGAACCCTTCAGATGTTTCsqleCGCCCTCTTCTCGGATATTCTCCGAGCTGCTCCTTATTTTCTGdhcr7AGCCGCCCAGCTCTATACCTTTATGGCAGAAGTCAGGGAGAGAldlrGATGAAGTTGGCTGCGTTAATGTCGCCGCTGTGACACTTGAactbCGTTGCTATCCAGGCTATGCTTCACCGGAGTCCATCACGAT


### 2.5. Cholesterol Analyses

HEp-2 cells were
dislodged with TrypLE Express (Gibco) and collected by centrifugation.  Lipids were extracted with chloroform and
methanol [38], analyzed and quantified by
gas chromatography/mass spectrometry (GC-MS 6890N; Agilent Technologies) and reported as μg/105 cells. Each
experiment was conducted at least three times.


### 2.6. Flow Cytometry

Prior to
infection,S. aureus was labeled with
0.5 μM 5- (and-6)-carboxyfluorescein
diacetate,  succinimidyl ester (CFSE) (Invitrogen) for 10 minutes at 37°C.  CFSE-stained S. aureus
was washed three times with PBS and used to
infect HEp-2 cells as described above.
After coculturing for 10 minutes,
cells were washed and incubated (15 minutes, 37°C) with S. aureus
specific  antibody ab37644 (Abcam), followed by goat antimouse IgG conjugated with
Cy5 (Southern Biotech) to quantify extracellular bacteria.  In parallel experiments to quantify
extracellular bacteria, infected monolayers were treated with lysostaphin for 2 hours resulting in loss of the CFSE
signal.  Confirmation of the
effectiveness of lysostaphin treatment was accomplished by treatment with
Cy5-conjugated antibody as described above.
Cells were harvested and analyzed with a FACSAria flow cytometer (BD),
equipped with FACSDiva software (BD).


### 2.7. Statistical Analyses

GeneSpring version
7.2 (Silicon Genetics) was used to analyze microarray data.  For each time point, data from 3–5 separate
replicated experiments were obtained and analyzed by 2-way ANOVA (P  <
.05) to determine their validity, followed by Benjamini and Hochberg false
discovery rate correction for each data set [39].  Correction for spot intensity variations
among arrays was performed by intensity-dependent normalization and subtraction
of background based on negative controls.
Normalized mean values were determined for all data points.  Microarray data were reported as increased or
decreased expression (>1.0 or <1.0, resp.) by dividing the mean
Cy5 value (infected HEp-2 cells) by the mean Cy3 value (uninfected HEp-2 cells)
for each time point.


## 2.1. Cultures

HEp-2 cells [34] were
purchased from the American Type Culture
Collection (ATCC).  Routine maintenance
was conducted using complete growth medium (CGM) [10]. S. aureus RN6390
[32, 33, 35] provided by A. Cheung
(Dartmouth Medical School) was used to infect HEp-2 cells using established
techniques described previously [8, 32, 33, 36].  Briefly,
bacteria from 16-hour Todd Hewitt broth cultures were washed
three times with phosphate buffered saline (PBS), and resuspended in invasion
medium (IM; CGM lacking antibiotics and FBS) to make
stocks with approximately 109 colony-forming units
(CFU) mL−1.  Bacterial stocks were diluted 10-fold in
fresh IM; 500 μL of the
cell suspension well−1 were used to infect each HEp-2 culture at a
multiplicity of infection (MOI) of 10.
The cocultures were centrifuged immediately to synchronize monolayer
infections and incubated at 37°C for 10 minutes to allow internalization, after
10 minutes, the IM was rapidly replaced with fresh medium containing gentamicin
(100μgmL−1) to kill noninternalized bacteria.  Thereafter, the cocultures were incubated (up
to 8 hours following S. aureus exposure) and analyzed at various times
following exposure to S. aureus as
described below.For growth rate
analyses, cells from 16-hourS. aureus RN6390 TH broth cultures (above)
were pelleted, washed three times with PBS, and diluted with PBS to 105 CFU mL−1.  A 100 μL aliquot
was inoculated into 10 mL of TH broth or IM, with or without FBS (without
antibiotics).  Cultures were incubated
with vigorous shaking up to 8 hours. CFU concentrations were
determined by a standard plate count method.


## 2.2. RNA Isolation and Purification

HEp-2 cells were
harvested at 2, 4, 6, or 8 hours following addition of bacteria.  RNA was isolated using TRIZOL (Invitrogen)
according to the manufacturer’s instructions and further purified with RNAeasy
MinElute Cleanup Kits (Qiagen).  RNA
samples, quantified using a NanoDrop ND-1000
spectrophotometer (Nanodrop Technologies)
and showing OD260:OD280 ratios >1.95
were used for subsequent experiments.


## 2.3. Microarray Methods and Data Analysis

MWG Human 30K microarrays
(MWG) were used according to the manufacturer’s
instructions.  cDNA was
synthesized using the BD Atlas PowerScript Fluorescent Labeling Kit (BD) with
oligo(dT)12-18 primer (Invitrogen).
CyDye Post-Labeling Reactive Dyes (Amersham) were used to fluorescently
label the cDNA (Cy3 for cDNA from uninfected cells and Cy5 for cDNA from S. aureus infected cells).  Unincorporated dye was removed from labeled
cDNA with CHROMA SPIN+TE-30 columns (Clontech).
Labeled cDNA was dissolved in salt-based hybridization buffer (MWG),
incubated at 95°C (3 minutes), chilled on ice, and hybridized to the microarray
chips in the dark for 16–24 hours at 42°C
with slow rocking.  Arrays were washed
and scanned with an Axon 4000A dual channel microarray scanner (Axon) to
generate multi-TIFF images which were processed with GenePix Pro 6.0 software
(Molecular Devices).


## 2.4. Quantitative Real-Time PCR (QRT-PCR)

QRT-PCR was used
to validate selected microarray data.
cDNA was synthesized from 1μg
of RNA using Superscript Π Reverse Transcriptase (Invitrogen).  Primers
(Table 1), designed using Primer
Express 2.0 software (PE Applied Biosystems), were purchased from Integrated
DNA Technologies (IDT).  Data were analyzed as described previously [37].  The threshold cycle (CT) was calculated as the cycle number at which the  ΔRn crossed the
baseline.  Data were normalized by
calculating   ΔCT
[CT of target
−CT of the internal control
(β-actin)].  Normalized   ΔCT
data from S. aureus infected HEp-2
cells were compared to data from uninfected HEp-2 cells by calculating     ΔΔCT [ΔCT
of S. aureus infected HEp-2 cells −ΔCT  of uninfected HEp-2 cells].  Each experiment was conducted thrice for
validation, and the mean value is reported.Table 1
DNA primers
used for QRT-PCR experiments.
GeneForward
primers (5′-3′)Reverse
primers (5′-3′)atf3GATGTCCTCTGCGCTGGAATCCTCGGCTTTTGTGATGGAc-fosGCCCTTTGATGACTTCCTGTTCGGAGCGGGCTGTCTCAGAc-junGCAAAGATGGAAACGACCTTCTGCTCTCGGACGGGAGGAAjunBCTACACGACTACAAACTCCTGAAACCCCCCAGGCGCTTTGAGAsgkGTGCCTGGGAGCTGTCTTGTGCTGTGTTTCGGCTATAAAAAGGarhbTCCCAATGTGCCCATCATCATGCGGGCCAGCTCTGTmap2k3CCCTACATGGCCCCTGAGATCCAGACGTCGGACTTGACAIl1bCGAATCTCCGACCACCACTACTCCATGGCCACAACAACTGAtnfaCCTGGTATGAGCCCATCTATCTGTAGTCGGGCCGATTGATCTCIl6AGCCGCCCCACACAGATCGAGGATGTACCGAATTTGTTTIl8CTGGCCGTGGCTCTCTTGCTTGGCAAAACTGCACCTTCAccl20TCCTGGCTGCTTTGATGTCAAAAGTTGCTTGCTGCTTCTGATTcxcl1AACATCCAAAGTGTGAACGTGAAGAGTGTGGCTATGACTTCGGTTTIl10CTTGTCTGAGATGATCCAGTTTTACCTCCTTGATGTCTGGGTCTTGGTTptgs2GGAAGCCTTCTCTAACCTCTCCTATTAGGGAGTCGGGCAATCATCadmGGATGTCGCGTCGGAGTTTTGCTGGACATCCGCAGTTCdkk1AAGTACCAGACCATTGACAACTACCAGGGACTAGCGCAGTACTCATCAGTigfbp1CCATCTGATGGCCCCTTCTCCTTCGAGCCATCATAGGTACTGcasp9AGGACATGCTGGCTTCGTTTTTCTAGGGTTGGCTTCGACAAtgfb1CCTGGCGATACCTCAGCAACCGGTGACATCAAAAGATAACCAthbs1TCCGCAAAGTGACTGAAGAGAATGAACTCCGTTGTGATAGCATAGGcyr61GGTGGAGTTGACGAGAAACAATGAGGGAGCCGCTTCAGTGAhmgcrCCCAGTTGTGCGTCTTCCATGCGAACCCTTCAGATGTTTCsqleCGCCCTCTTCTCGGATATTCTCCGAGCTGCTCCTTATTTTCTGdhcr7AGCCGCCCAGCTCTATACCTTTATGGCAGAAGTCAGGGAGAGAldlrGATGAAGTTGGCTGCGTTAATGTCGCCGCTGTGACACTTGAactbCGTTGCTATCCAGGCTATGCTTCACCGGAGTCCATCACGAT


## 2.5. Cholesterol Analyses

HEp-2 cells were
dislodged with TrypLE Express (Gibco) and collected by centrifugation.  Lipids were extracted with chloroform and
methanol [38], analyzed and quantified by
gas chromatography/mass spectrometry (GC-MS 6890N; Agilent Technologies) and reported as μg/105 cells. Each
experiment was conducted at least three times.


## 2.6. Flow Cytometry

Prior to
infection,S. aureus was labeled with
0.5 μM 5- (and-6)-carboxyfluorescein
diacetate,  succinimidyl ester (CFSE) (Invitrogen) for 10 minutes at 37°C.  CFSE-stained S. aureus
was washed three times with PBS and used to
infect HEp-2 cells as described above.
After coculturing for 10 minutes,
cells were washed and incubated (15 minutes, 37°C) with S. aureus
specific  antibody ab37644 (Abcam), followed by goat antimouse IgG conjugated with
Cy5 (Southern Biotech) to quantify extracellular bacteria.  In parallel experiments to quantify
extracellular bacteria, infected monolayers were treated with lysostaphin for 2 hours resulting in loss of the CFSE
signal.  Confirmation of the
effectiveness of lysostaphin treatment was accomplished by treatment with
Cy5-conjugated antibody as described above.
Cells were harvested and analyzed with a FACSAria flow cytometer (BD),
equipped with FACSDiva software (BD).


## 2.7. Statistical Analyses

GeneSpring version
7.2 (Silicon Genetics) was used to analyze microarray data.  For each time point, data from 3–5 separate
replicated experiments were obtained and analyzed by 2-way ANOVA (P  <
.05) to determine their validity, followed by Benjamini and Hochberg false
discovery rate correction for each data set [39].  Correction for spot intensity variations
among arrays was performed by intensity-dependent normalization and subtraction
of background based on negative controls.
Normalized mean values were determined for all data points.  Microarray data were reported as increased or
decreased expression (>1.0 or <1.0, resp.) by dividing the mean
Cy5 value (infected HEp-2 cells) by the mean Cy3 value (uninfected HEp-2 cells)
for each time point.


## 3. Results and Discussion

### 3.1. Experimental Model

As this study was
designed to assess the effects of internalizedS. aureus on the HEp-2 pharyngeal epithelial cell line, the
influences of extracellular bacteria or their exotoxins produced prior to
internalization of S. aureus were
minimized by (1) thoroughly washing the inocula; (2) treating cocultures with gentamicin
after a very short (10 minutes) extracellular bacterial exposure; (3)
conducting the extracellular exposure period in a medium that does not support
extracellular growth.  Specifically,
unlike control cultures in TH broth which supported robust growth, S. aureus RN6390 cultured in IM did not
grow, even when incubated for periods of time much longer than the 10 minutes
used to infect cells (Figure 1). Furthermore, IM supplemented with FBS
supported moderate growth, indicating that a lack of growth in IM alone was not
due to inhibitory components.Figure 1
Growth analysis
ofS. aureus RN6390. To assess
growth, S. aureus RN6390
was inoculated into different media (TH broth, IM, or IM
supplemented with FBS). CFUs
were determined hourly by a standard
plate count method up to 8 hours, and represented as the mean ± SEM of data
acquired from three experiments.Considering the short exposure of HEp-2
cells to extracellularS. aureus, it was of interest to quantify the
percentage of infected HEp-2 cells containing intracellular bacteria.  This was accomplished by differential
staining of intracellular and extracellular bacteria and by monitoring
intracellular CFSE-stained S.
aureus following lysostaphin treatment to remove extracellular
bacteria.  As shown in Figure 2(a), a 10-minute-exposure
resulted in monolayers in which approximately 57.0% of the HEp-2 cells
contained cell-associated S.aureus (extracellular and/or intracellular), while approximately 39.0% of HEp-2 cells
were associated with extracellular bacteria (Figure 2(b)).  Lysostaphin treatment which removed nearly
all extracellular bacteria (Figure 2(d)) revealed that approximately 43.2% of
the HEp-2 cells had intracellular S. aureus (Figure 2(c)).Assessment ofS. aureus RN6390 internalization using
flow cytometry. Dotted lines indicate the uninfected HEp-2 cell control, and
solid lines indicate HEp-2 cells infected with CFSE-labeled S. aureus ((a)
and (c)) or infected with CFSE-labeled S.
aureus followed by labeling Cy5-conjugated mAb specific for S. aureus ((b)
and (d)). In panels (a) and (b), HEp-2 cells were infected with CFSE-labeled S. aureus without treatment with
lysostaphin. CFSE signal represents HEp-2 cells infected with extracellular
and/or intracellular S. aureus (a).
Cy5 signal represents HEp-2 cells infected with extracellular S. aureus  only (b). In panels (c) and
(d), HEp-2 cells were infected with CFSE-labeled S. aureus followed by the treatment with lysostaphin which degrades
staphylococcal cell wall causing a loss of CFSE signal by extracellular S. aureus. CFSE signal represents HEp-2
cells infected with intracellular S.
aureus only (c). This was confirmed by showing the loss of Cy5 signal in
panel (d). Data shown are from a representative experiment which was conducted
three times.
(a)(b)(c)(d)


### 3.2. Microarray and QRT-PCR Data Analysis

IntracellularS.
aureus altered expression of several classes of HEp-2 genes.  Genes with statistically validated altered
transcription levels >1.50-fold (increase or decrease) at any of the four-time-points
in microarrays are listed in Table 2.  To
avoid potential pitfalls associated with amplification of mRNA such as inferior
reducibility, mRNA was not amplified in this study.  The microarray data shown here represented
true transcription levels.  Although we
suspect that relatively low mRNA levels resulted in microarray data for some
samples which were not
statistically significant (P  > .05), data for selected genes of interest were validated by QRT-PCR
(summarized in Table 3).  Data not shown
in Table 2 resulted from signal intensities <50 which were too low to
quantify.Table 2
Microarray analysis of gene expression changes in infected HEp-2 cell
monolayers.
CategoryGeneFold
change (P value)2 h4 h6 h8 hStress responseatf37.89  (.024)1.53  (.113)2.00  (.041)0.85 (.189)c-fos2.59  (.052)1.21 (.072)0.911 (.302)0.843 (.287)fosB2.29  (.009)1.14 (.605)0.95 (.919)1.10 (.101)c-jun1.88  (.011)1.40 (.094)0.77 (.064)1.27 (.035)junB1.98  (.007)1.16 (.015)1.22 (.015)1.03 (.407)sgk4.17  (.018)2.16  (.005)1.84  (.178)2.13  (.066)Signal transductionmap2k11.23 (.835)1.52 (.025)1.80  (.030)2.86 (.041)arhe2.61 (.005)2.31 (.060)1.26 (.370)1.70 (.085)arhb2.21 (.044)2.18 (.004)1.78  (.065)1.60 (.022)ack-10.67 (.061)0.56 (.081)0.39  (.004)0.51 (.026)map2k31.98  (.014)2.41 (.003)1.96  (.127)2.33 (.052)Proinflammatory responsecox23.32 (.012)2.71 (.088)1.29 (.065)2.55 (.064)Cell proliferation and
proapoptosisdkk12.17  (.026)7.11 (.001)3.23  (.012)4.52 (.055)klf42.33  (.001)1.78  (.134)1.61  (.008)1.61 (.104)klf62.51 (.019)1.50  (.064)1.52  (.046)1.62  (.090)Igfbp12.54 (.062)4.32  (.001)2.13  (.086)11.10  (.030)Igfbp30.77 (.664)1.80  (.051)3.65  (.003)2.23  (.088)casp91.95  (.015)1.57  (.021)0.54 (.617)0.78 (.666)bnip31.25 (.073)1.64  (.034)2.86  (.002)2.47  (.041)nur776.17  (.038)1.28 (.181)0.78 (.114)0.87 (.235)Profibrotictgfbr21.47 (.011)1.67 (.083)2.09 (.008)2.10  (.010)v-erb-b0.96 (.608)1.67 (.055)1.96 (.005)2.11  (.007)itga50.88 (.768)2.19 (.037)2.12 (.033)3.20  (.030)thbs11.28 (.112)2.93 (.001)2.54  (.024)2.44  (.209)pai12.45 (.006)1.80  (.040)1.27 (.089)1.32 (.136)pai2ND2.09  (.015)4.43 (.001)4.13  (.013)cyr614.43 (.007)3.24  (.001)2.33  (.152)1.61 (.249)ctgf6.78 (.026)2.13  (.141)NDNDnov1.46 (.301)1.98  (.059)2.05  (.002)2.15  (.006)Cholesterol synthesissc4mol0.81 (.367)0.32 (.001)0.36  (.001)0.31 (.001)hmgcr1.11 (.700)0.30 (.002)0.21  (.001)0.36 (.016)hsd17b70.74 (.189)0.50 (.001)0.30 (.006)0.31 (.014)idi11.00 (.979)0.53 (.018)0.33 (.004)0.31 (.151)sqle0.90 (.397)0.50 (.007)0.26 (.001)0.31 (.008)sc5dl0.90 (.358)0.45 (.017)0.23 (.008)0.35 (.064)fdft10.96 (.551)0.59 (.002)0.29 (.001)0.26 (.010)dhcr70.95 (.527)0.63 (.010)0.51 (.016)0.39 (.014)insig10.69 (.338)0.20 (.001)0.26 (.001)0.41  (.014)acas2ND0.58 (.080)0.27 (.001)0.37  (.024)ldlr1.09 (.048)0.41 (.002)0.54 (.017)0.68 (.114)ND:
Not determined. Data not shown due to low signal intensity
(<50).Table 3
Validation of selected genes by QRT-PCR.
CategoryGeneFold
change (P value)2 h4 h6 h8 hStress responseatf315.45 (.001)4.46 (.005)1.38 (.004)1.97 (.027)c-fos4.55 (.001)1.32 (.005)1.47 (.001)1.86 (.001)c-jun2.93 (.001)1.26 (.001)1.77 (.001)2.91 (.001)junb3.60 (.001)1.26 (.001)1.37 (.008)2.29 (.004)sgk3.36 (.001)1.20 (.001)1.87 (.001)2.02 (.001)Signal transductionarhb2.61 (.002)1.80 (.001)2.17 (.001)1.71 (.019)map2k31.57 (.001)1.89 (.013)2.04 (.005)2.12 (.001)Proinflammatory responseil1b3.64 (.001)1.58 (.007)2.02 (.001)1.47 (.002)tnfa3.36 (.001)1.30 (.009)2.21 (.001)1.43 (.001)il62.65 (.001)1.87 (.001)2.96 (.001)1.55 (.004)ccl206.29 (.001)5.07 (.002)4.53 (.001)1.82 (.001)cxcl13.82 (.001)2.41 (.001)2.87 (.001)3.05 (.050)cox24.16 (.001)3.69 (.001)3.96 (.001)2.95 (.011)Cell proliferation and Proapoptosisdkk13.43 (.001)6.90 (.001)4.31 (.001)2.28 (.001)igfbp13.50 (.001)6.82 (.045)4.20 (.010)9.89 (.001)casp92.74 (.001)1.34 (.005)1.42 (.004)1.13 (.021)Profibrotictgfb11.55 (.002)1.20 (.023)1.71 (.001)2.66 (.001)thbs11.83 (.001)4.55 (.001)4.12 (.002)4.09 (.001)cyr613.31 (.001)4.01 (.002)2.28 (.016)2.44 (.001)Cholesterol synthesishmgcr1.25 (.025)0.17 (.001)0.15 (.001)0.17 (.001)sqle1.00 (.005)0.30 (.001)0.14 (.001)0.15 (.001)dhcr71.17 (.050)0.50 (.001)0.27 (.001)0.16 (.001)ldlr1.57 (.010)0.09 (.001)0.12 (.001)0.23 (.001)


### 3.3. Stress Response

The
adaptor-related protein complex 1 (AP-1) comprises JUN, FOS, and activating
transcription factor (ATF) proteins; it regulates a variety of activities
including proliferation, apoptosis, and inflammation in response to stress
signals, cytokines, growth factors, and microbial infections [40, 41].  Internalization of S. aureus induced a rapid
(7.89-fold) increase in atf3 mRNA levels at 2 hours
postinfection that rapidly declined thereafter, as measured by microarray
analysis (Table 2).  QRT-PCR analysis
yielded consistent findings (Table 3).
Other AP-1 genes, such as c-fos, fosB, c-jun, and junB,
were up-regulated as measured by microarray and/or QRT-PCR analysis, albeit
less dramatically at 2 hours.  Another
stress response gene, sgk, encoding
serum and glucocorticoid-induced protein kinase (SGK) [42], was up-regulated maximally
at 2 hours (Tables 2 and 3).  SGK is
involved in epithelial sodium transport, and is induced in epithelial cells in
response to environmental stimuli and stress [42].


### 3.4. Signal Transduction

IntracellularS. aureus also affected genes involved
in several mitogen-activated protein kinase (MAPK) pathways.  MAPK kinase 1 (map2k1) mRNA levels
gradually increased and reached a maximum level at 8 hours
(Table 2), MAPK kinase
1 activates downstream extracellular signal-regulated protein kinases (ERKs) in
the Ras-Raf-MEK-ERK pathway.  Two Ras
homolog genes, arhe and arhb, were generally up-regulated >1.50-fold throughout the 8-hour-infection
(Tables 2 and 3), whereas, the Ras inhibitor gene, ack-1, was down-regulated
(Table 2).  Thus, up-regulation of map2k1, arhe, and arhb, and
down-regulation of the inhibitor ack-1 are consistent with activation of Ras-ERK pathway.  Ras proteins are important for cytoskeleton
reorganization [43, 44], coinciding with bacterial uptake and intracellular movement.  Transcription of another MAPK gene (map2k3), a dual-specific kinase that
phosphorylates MAPK14 (p38), was up-regulated >1.50-fold at all four-time-points
(Tables 2 and 3).  P38 pathway plays an important role in
regulating proinflammatory gene expression including tnfa, il1b, and cox2
[43, 44].Staphylococcal
activation of the ERK and P38 pathways in epithelial cells has also been
observed in previous studies [45–47].  Activation of ERK and P38 pathways, in
epithelial cells, was also seen in other intracellular pathogen infections such
as Helicobacter pylori [48] and Salmonella enterica
[49].


### 3.5. Proinflammatory Response

Intracellular
bacteria frequently up-regulate several proinflammatory cytokine genes (tnfa, il1b, and il6) and
chemokine genes (il8, ccl20, and cxcl1)
[15, 49, 50].  Due to the low transcriptional activity of il1b, tnfa, il6, cxcl1, and ccl20 in uninfected HEp2-cells, accurate comparison of these genes
was not obtained with microarray analysis.
QRT-PCR analysis demonstrated that transcription of il1b, tnfa, il6, cxcl1, and ccl20 genes was
up-regulated (Table 3),
although only small to moderate increases were observed, compared to previous
study [22].  This finding is likely due to differences in
types of host cells and in S. aureus strains, and also due to the fact that we investigated only the effects of
intracellular staphylococci.  For
example, human umbilical endothelial cells infected with a clinical S. aureus isolate, were induced
expression of several proinflammatory cytokines/chemokines with similar fold changes to our
study at transcriptional level.
However, it did not induce expression of either tnfa, or ilb, which was different from our study
[26]. Similarly, vaginal
epithelial cells cocultured simultaneously with intracellular and extracellular S. aureus MNSM, producing toxic shock
syndrome toxin-1, for 3 hours showed increases in the transcription of il8, cxcl1,
and ccl20 (11.3-fold, 17.1-fold and
207.9-fold, resp.) which were much stronger than our results [22].Cyclooxygenase-2 gene  (cox2), an inducible form of the cyclooxygenase-1 gene
(cox1), was up-regulated at all
four-time-points in this study (Tables 2 and 3).  As an immediate early response gene that is
responsible for prostanoid biosynthesis involved in proinflammation, cox2 is expressed in epithelial cells,
macrophages, fibroblasts, and vascular endothelial cells [51].  COX2 is
induced by IL-1β [52] and lipoteichoic acid from S. aureus
[53].  Up-regulation of cox2 transcription was also associated with infection of epithelial
cells by gram-negative bacteria: Y. enterocolitica
[13] and  S. flexneri M90T, probably via LPS
[15].  The  induction
of cox2 expression  is not significantly in vaginal epithelial cell
cultures infected (intracellular plus extracellular) with the superantigen
producing strain S. aureus MNSM
(see above) [22], further emphasizing the potentially different  effects caused by various S. aureus strains, as well as the systems employed to measure their effects.


### 3.6. Cell Proliferation and Proapoptosis

IntracellularS. aureus RN6390 affected transcription
of several proapoptotic genes.
Dickkopf-1 (dkk1), was
up-regulated >2.00-fold at all time points examined (Tables 2 and
3).  Krüppel-like factors 4 and 6 genes (klf4 and klf6) were up-regulated
>2.00-fold at 2 hours postinfection (Table 2).  Microarray data showed the gene for caspase-9
(casp9) up-regulated ~2.00-fold at 2 hours
(Table 2), and this result
was confirmed by QRT-PCR (Table 3).  The
gene (bnip3) encoding Bcl2/adenovirus
E1B 19kDa interacting protein 3, a mitochondrial proapoptotic protein, was
up-regulated >2.00-fold at both 6 hours and 8 hours
(Table 2).  Two insulin-like growth factor binding
protein genes (igfbp1 and igfbp3) were up-regulated >1.50-fold at 4 hours, 6 hours, and 8 hours
postinfection (Tables 2 and
3).  The NR4A1 receptor gene
(nur77), which encodes a transcription
factor that exhibits proapoptotic properties in T cells [54], was up-regulated ~6-fold at 2 hours
(Table 2).  These findings were similar to several
studies demonstrating that the infection of epithelial cells
[8, 28, 32, 33], endothelial cells
[29, 30, 55, 56], and osteoblasts
[3, 57, 58]
with S. aureus can lead to
apoptosis.  Previous work in our lab had
shown the involvement of host caspases 3 and 8 in S. aureus-induced apoptosis
[32] and the requirement of the S. aureus virulence gene regulator agr in the induction of epithelial cell
apoptosis [33].


### 3.7. Profibrotic Gene Transcription in HEp-2 Cells

TGFβ1 is a key
protein involved in many cell functions including fibrosis formation,
regulation of cell cycle, apoptosis, and matrix remodeling [59].  QRT-PCR
indicated that tgfβ1 was
up-regulated by intracellular S. aureus
(Table 3). Intracellular S. aureus also induced transcription of several genes related to
TGFβ1, especially in regard to
fibrosis formation (Tables 2 and 3). In microarray experiments, transforming
growth factor beta receptor 2 gene (tgfβr2)
and epidermal growth factor receptor (EGFR)
gene (v-erb-b) were up-regulated >1.5-fold after 4 hours
(Table 2).
Integrin α5 gene (itga5) was gradually up-regulated after 2-hour-infection
(Table 2).  The gene (thbs1) encoding
thrombospondin 1 was up-regulated ~3.00-fold at 4 hours and 2.54-fold at 6 hours in microarray
experiments (Table 2), and similarly, with QRT-PCR
(Table 3).Plasminogen
activator inhibitor 1 and 2 genes (pai1, pai2) were up-regulated in
microarray experiments (Table 2).
Studies have shown that TGFβ1 induces plasminogen activator inhibitor 1
(PAI1) expression and demonstrated the
requirement for EGFR in this process [60–62].  Both PAI1 and PAI2 are inhibitors of the
fibrinolysis system, acting to block the activity of tissue plasminogen
activator and urokinase, and preventing the conversion of plasminogen to
plasmin.  Plasmin is a serine protease
that degrades fibrin clots as well as extracellular matrix components.  Thus, up-regulation of pai1 and pai2 may reduce extracellular matrix degradation.The CCN
(Cysteine-rich 61, Connective tissue growth factor, and Nephroblastoma
overexpressed) family members are cysteine-rich and functionally diverse
proteins that are involved in mitosis, apoptosis, adhesion, extracellular
matrix production, angiogenesis, and tumor growth [63].  Three genes belonging to the CCN family were
up-regulated.  Two of those, cyr61 and ctgf, were significantly up-regulated at early time points
(Table 2
and 3).  The third CCN gene, nov, was significantly up-regulated after 4 hours at transcriptional level
(Table 2).  An increased
transcription of cyr61 and ctgf genes has been shown during epithelial cell infection with Y. enterocolitica
[13], S. flexneri
[15], and B. pertussis [16].
CYR61, CTGF, and NOV have the capability to bind both fibronectin and α5β1 integrin, similar to IGFBP1 and
IGFBP3 [64–68], and are implicated in wound healing [68].  Taken
together, up-regulation of these profibrotic genes indicates that intracellular S. aureus might affect the extracellular matrix by
stimulating fibrosis and aiding
in repair of the damage caused
by S. aureus infection.


### 3.8. Cholesterol Biosynthesis

IntracellularS. aureus caused down-regulated
expression of cholesterol biosynthesis enzyme genes, including sterol-c4-methyl
oxidase-like (sc4mol),
3-hydroxy-3-methylglutaryl-coenzyme A reductase (hmgcr), hydroxysteroid (17β) dehydrogenase 7
(hsd17b7), isopentenyl-diphosphate delta isomerase (idi1), squalene monooxygenase (sqle), sterol c5-desaturase-like (sc5dl), farnesyl-disphosphate
famesyltransferase 1 (fdft1), and
7-dehydrocholesterol reductase (dhcr7).  Genes involved in regulation of cholesterol
synthesis were also down-regulated.  Insulin-induced
gene 1 (insig1), encoding a membrane
endoplasmic reticulum protein, was down-regulated (0.20-fold at 4 hours,
0.26-fold at 6 hours, and 0.41-fold at 8 hours)
(Table 2).  Acetyl CoA
synthetase gene (acas2) and low-density lipoprotein receptor gene (ldlr) were also transcriptionally
down-regulated (Table 2).  QRT-PCR data
confirmed the down-regulation of hmgcr, sqle, dhcr7, and ldlr
(Table 3).  Cholesterol quantification with GC-MS
also showed that host cells displayed
a corresponding decreased cholesterol synthesis after a challenge with
intracellular S. aureus (Table 4).
Garner et al. showed an essential
role for cholesterol in the uptake of S.
typhimurium into HeLa cells, demonstrating that the removal of cholesterol
caused a greater than 90%
decrease in bacterial uptake [69].  Thus, a reduction in cholesterol may be a response to limit the
internalization of S. aureus.  In addition, a decrease in cholesterol levels
could limit the effects of S. aureus exotoxins on the host cell membrane. S.
aureus alpha toxin, along with other pore-forming toxins from Streptococcus and Clostridium species, showed reduced activity when cholesterol levels
in lipid membranes were decreased [70, 71].  A recent study showed that the golden S. aureus pigment, staphyloxanthin, is
synthesized with the same substrates used for cholesterol biosynthesis by host
cells [72].  It is unclear at present whether
the effect on cholesterol biosynthesis is related to this finding; however, it
is conceivable that this effect might represent a host response to affect
production of this staphylococcal virulence factor.Table 4
Cholesterol
quantification [(μg/105 cells)  ± SD]  in uninfected
and infected HEp-2 cell
monolayers.
Cell
typeIncubation time (h)2468Unchallenged HEp-2 cell75.82±2.9969.78±5.3164.94±5.0055.91±4.78Challenged HEp-2 cell58.43±3.7351.92±2.8750.74±5.2243.38±3.36% cholesterol reduction22.9125.6021.8722.41P value.005.050.045.026In summary, this
study demonstrates that several classes of genes in HEp-2 cells undergo changes
in transcriptional expression in response to intracellularS. aureus.  We
observed that, in the first few hours of intracellular infection, epithelial
cells can respond to intracellular S. aureus quickly by inducing early
stress response (AP-1 complex) and MAPK pathways (Ras, P38), which consequently
stimulate broader responses
such as proinflammatory response, apoptosis, and fibrosis.  Our data support the belief that the role of epithelial cells in innate
immunity is not simply that of a physical barrier against invading pathogens,
but it is also actively
involved in the induction of more complex host defense mechanisms.  Another possibility is that, as a successful
pathogen, intracellular S. aureus might lead to host gene
expression that facilitates its
intracellular survival.  This is
consistent with induction of Ras-related cytoskeleton reorganization and the fibrosis process.  Our results are also consistent with,
although not definitive of, a delicate balance between effects which benefit
the host and those which are more beneficial to S. aureus.  Finally, this
study showed that intracellular S. aureus suppressed cholesterol synthesis in epithelial cells.  The consequence of this
suppression on the pathogenesis of S.
aureus is not clearly presented but might be related to recent observations regarding staphylococcal
pigment production.


## 3.1. Experimental Model

As this study was
designed to assess the effects of internalizedS. aureus on the HEp-2 pharyngeal epithelial cell line, the
influences of extracellular bacteria or their exotoxins produced prior to
internalization of S. aureus were
minimized by (1) thoroughly washing the inocula; (2) treating cocultures with gentamicin
after a very short (10 minutes) extracellular bacterial exposure; (3)
conducting the extracellular exposure period in a medium that does not support
extracellular growth.  Specifically,
unlike control cultures in TH broth which supported robust growth, S. aureus RN6390 cultured in IM did not
grow, even when incubated for periods of time much longer than the 10 minutes
used to infect cells (Figure 1). Furthermore, IM supplemented with FBS
supported moderate growth, indicating that a lack of growth in IM alone was not
due to inhibitory components.Figure 1
Growth analysis
ofS. aureus RN6390. To assess
growth, S. aureus RN6390
was inoculated into different media (TH broth, IM, or IM
supplemented with FBS). CFUs
were determined hourly by a standard
plate count method up to 8 hours, and represented as the mean ± SEM of data
acquired from three experiments.Considering the short exposure of HEp-2
cells to extracellularS. aureus, it was of interest to quantify the
percentage of infected HEp-2 cells containing intracellular bacteria.  This was accomplished by differential
staining of intracellular and extracellular bacteria and by monitoring
intracellular CFSE-stained S.
aureus following lysostaphin treatment to remove extracellular
bacteria.  As shown in Figure 2(a), a 10-minute-exposure
resulted in monolayers in which approximately 57.0% of the HEp-2 cells
contained cell-associated S.aureus (extracellular and/or intracellular), while approximately 39.0% of HEp-2 cells
were associated with extracellular bacteria (Figure 2(b)).  Lysostaphin treatment which removed nearly
all extracellular bacteria (Figure 2(d)) revealed that approximately 43.2% of
the HEp-2 cells had intracellular S. aureus (Figure 2(c)).Assessment ofS. aureus RN6390 internalization using
flow cytometry. Dotted lines indicate the uninfected HEp-2 cell control, and
solid lines indicate HEp-2 cells infected with CFSE-labeled S. aureus ((a)
and (c)) or infected with CFSE-labeled S.
aureus followed by labeling Cy5-conjugated mAb specific for S. aureus ((b)
and (d)). In panels (a) and (b), HEp-2 cells were infected with CFSE-labeled S. aureus without treatment with
lysostaphin. CFSE signal represents HEp-2 cells infected with extracellular
and/or intracellular S. aureus (a).
Cy5 signal represents HEp-2 cells infected with extracellular S. aureus  only (b). In panels (c) and
(d), HEp-2 cells were infected with CFSE-labeled S. aureus followed by the treatment with lysostaphin which degrades
staphylococcal cell wall causing a loss of CFSE signal by extracellular S. aureus. CFSE signal represents HEp-2
cells infected with intracellular S.
aureus only (c). This was confirmed by showing the loss of Cy5 signal in
panel (d). Data shown are from a representative experiment which was conducted
three times.
(a)(b)(c)(d)


## 3.2. Microarray and QRT-PCR Data Analysis

IntracellularS.
aureus altered expression of several classes of HEp-2 genes.  Genes with statistically validated altered
transcription levels >1.50-fold (increase or decrease) at any of the four-time-points
in microarrays are listed in Table 2.  To
avoid potential pitfalls associated with amplification of mRNA such as inferior
reducibility, mRNA was not amplified in this study.  The microarray data shown here represented
true transcription levels.  Although we
suspect that relatively low mRNA levels resulted in microarray data for some
samples which were not
statistically significant (P  > .05), data for selected genes of interest were validated by QRT-PCR
(summarized in Table 3).  Data not shown
in Table 2 resulted from signal intensities <50 which were too low to
quantify.Table 2
Microarray analysis of gene expression changes in infected HEp-2 cell
monolayers.
CategoryGeneFold
change (P value)2 h4 h6 h8 hStress responseatf37.89  (.024)1.53  (.113)2.00  (.041)0.85 (.189)c-fos2.59  (.052)1.21 (.072)0.911 (.302)0.843 (.287)fosB2.29  (.009)1.14 (.605)0.95 (.919)1.10 (.101)c-jun1.88  (.011)1.40 (.094)0.77 (.064)1.27 (.035)junB1.98  (.007)1.16 (.015)1.22 (.015)1.03 (.407)sgk4.17  (.018)2.16  (.005)1.84  (.178)2.13  (.066)Signal transductionmap2k11.23 (.835)1.52 (.025)1.80  (.030)2.86 (.041)arhe2.61 (.005)2.31 (.060)1.26 (.370)1.70 (.085)arhb2.21 (.044)2.18 (.004)1.78  (.065)1.60 (.022)ack-10.67 (.061)0.56 (.081)0.39  (.004)0.51 (.026)map2k31.98  (.014)2.41 (.003)1.96  (.127)2.33 (.052)Proinflammatory responsecox23.32 (.012)2.71 (.088)1.29 (.065)2.55 (.064)Cell proliferation and
proapoptosisdkk12.17  (.026)7.11 (.001)3.23  (.012)4.52 (.055)klf42.33  (.001)1.78  (.134)1.61  (.008)1.61 (.104)klf62.51 (.019)1.50  (.064)1.52  (.046)1.62  (.090)Igfbp12.54 (.062)4.32  (.001)2.13  (.086)11.10  (.030)Igfbp30.77 (.664)1.80  (.051)3.65  (.003)2.23  (.088)casp91.95  (.015)1.57  (.021)0.54 (.617)0.78 (.666)bnip31.25 (.073)1.64  (.034)2.86  (.002)2.47  (.041)nur776.17  (.038)1.28 (.181)0.78 (.114)0.87 (.235)Profibrotictgfbr21.47 (.011)1.67 (.083)2.09 (.008)2.10  (.010)v-erb-b0.96 (.608)1.67 (.055)1.96 (.005)2.11  (.007)itga50.88 (.768)2.19 (.037)2.12 (.033)3.20  (.030)thbs11.28 (.112)2.93 (.001)2.54  (.024)2.44  (.209)pai12.45 (.006)1.80  (.040)1.27 (.089)1.32 (.136)pai2ND2.09  (.015)4.43 (.001)4.13  (.013)cyr614.43 (.007)3.24  (.001)2.33  (.152)1.61 (.249)ctgf6.78 (.026)2.13  (.141)NDNDnov1.46 (.301)1.98  (.059)2.05  (.002)2.15  (.006)Cholesterol synthesissc4mol0.81 (.367)0.32 (.001)0.36  (.001)0.31 (.001)hmgcr1.11 (.700)0.30 (.002)0.21  (.001)0.36 (.016)hsd17b70.74 (.189)0.50 (.001)0.30 (.006)0.31 (.014)idi11.00 (.979)0.53 (.018)0.33 (.004)0.31 (.151)sqle0.90 (.397)0.50 (.007)0.26 (.001)0.31 (.008)sc5dl0.90 (.358)0.45 (.017)0.23 (.008)0.35 (.064)fdft10.96 (.551)0.59 (.002)0.29 (.001)0.26 (.010)dhcr70.95 (.527)0.63 (.010)0.51 (.016)0.39 (.014)insig10.69 (.338)0.20 (.001)0.26 (.001)0.41  (.014)acas2ND0.58 (.080)0.27 (.001)0.37  (.024)ldlr1.09 (.048)0.41 (.002)0.54 (.017)0.68 (.114)ND:
Not determined. Data not shown due to low signal intensity
(<50).Table 3
Validation of selected genes by QRT-PCR.
CategoryGeneFold
change (P value)2 h4 h6 h8 hStress responseatf315.45 (.001)4.46 (.005)1.38 (.004)1.97 (.027)c-fos4.55 (.001)1.32 (.005)1.47 (.001)1.86 (.001)c-jun2.93 (.001)1.26 (.001)1.77 (.001)2.91 (.001)junb3.60 (.001)1.26 (.001)1.37 (.008)2.29 (.004)sgk3.36 (.001)1.20 (.001)1.87 (.001)2.02 (.001)Signal transductionarhb2.61 (.002)1.80 (.001)2.17 (.001)1.71 (.019)map2k31.57 (.001)1.89 (.013)2.04 (.005)2.12 (.001)Proinflammatory responseil1b3.64 (.001)1.58 (.007)2.02 (.001)1.47 (.002)tnfa3.36 (.001)1.30 (.009)2.21 (.001)1.43 (.001)il62.65 (.001)1.87 (.001)2.96 (.001)1.55 (.004)ccl206.29 (.001)5.07 (.002)4.53 (.001)1.82 (.001)cxcl13.82 (.001)2.41 (.001)2.87 (.001)3.05 (.050)cox24.16 (.001)3.69 (.001)3.96 (.001)2.95 (.011)Cell proliferation and Proapoptosisdkk13.43 (.001)6.90 (.001)4.31 (.001)2.28 (.001)igfbp13.50 (.001)6.82 (.045)4.20 (.010)9.89 (.001)casp92.74 (.001)1.34 (.005)1.42 (.004)1.13 (.021)Profibrotictgfb11.55 (.002)1.20 (.023)1.71 (.001)2.66 (.001)thbs11.83 (.001)4.55 (.001)4.12 (.002)4.09 (.001)cyr613.31 (.001)4.01 (.002)2.28 (.016)2.44 (.001)Cholesterol synthesishmgcr1.25 (.025)0.17 (.001)0.15 (.001)0.17 (.001)sqle1.00 (.005)0.30 (.001)0.14 (.001)0.15 (.001)dhcr71.17 (.050)0.50 (.001)0.27 (.001)0.16 (.001)ldlr1.57 (.010)0.09 (.001)0.12 (.001)0.23 (.001)


## 3.3. Stress Response

The
adaptor-related protein complex 1 (AP-1) comprises JUN, FOS, and activating
transcription factor (ATF) proteins; it regulates a variety of activities
including proliferation, apoptosis, and inflammation in response to stress
signals, cytokines, growth factors, and microbial infections [40, 41].  Internalization of S. aureus induced a rapid
(7.89-fold) increase in atf3 mRNA levels at 2 hours
postinfection that rapidly declined thereafter, as measured by microarray
analysis (Table 2).  QRT-PCR analysis
yielded consistent findings (Table 3).
Other AP-1 genes, such as c-fos, fosB, c-jun, and junB,
were up-regulated as measured by microarray and/or QRT-PCR analysis, albeit
less dramatically at 2 hours.  Another
stress response gene, sgk, encoding
serum and glucocorticoid-induced protein kinase (SGK) [42], was up-regulated maximally
at 2 hours (Tables 2 and 3).  SGK is
involved in epithelial sodium transport, and is induced in epithelial cells in
response to environmental stimuli and stress [42].


## 3.4. Signal Transduction

IntracellularS. aureus also affected genes involved
in several mitogen-activated protein kinase (MAPK) pathways.  MAPK kinase 1 (map2k1) mRNA levels
gradually increased and reached a maximum level at 8 hours
(Table 2), MAPK kinase
1 activates downstream extracellular signal-regulated protein kinases (ERKs) in
the Ras-Raf-MEK-ERK pathway.  Two Ras
homolog genes, arhe and arhb, were generally up-regulated >1.50-fold throughout the 8-hour-infection
(Tables 2 and 3), whereas, the Ras inhibitor gene, ack-1, was down-regulated
(Table 2).  Thus, up-regulation of map2k1, arhe, and arhb, and
down-regulation of the inhibitor ack-1 are consistent with activation of Ras-ERK pathway.  Ras proteins are important for cytoskeleton
reorganization [43, 44], coinciding with bacterial uptake and intracellular movement.  Transcription of another MAPK gene (map2k3), a dual-specific kinase that
phosphorylates MAPK14 (p38), was up-regulated >1.50-fold at all four-time-points
(Tables 2 and 3).  P38 pathway plays an important role in
regulating proinflammatory gene expression including tnfa, il1b, and cox2
[43, 44].Staphylococcal
activation of the ERK and P38 pathways in epithelial cells has also been
observed in previous studies [45–47].  Activation of ERK and P38 pathways, in
epithelial cells, was also seen in other intracellular pathogen infections such
as Helicobacter pylori [48] and Salmonella enterica
[49].


## 3.5. Proinflammatory Response

Intracellular
bacteria frequently up-regulate several proinflammatory cytokine genes (tnfa, il1b, and il6) and
chemokine genes (il8, ccl20, and cxcl1)
[15, 49, 50].  Due to the low transcriptional activity of il1b, tnfa, il6, cxcl1, and ccl20 in uninfected HEp2-cells, accurate comparison of these genes
was not obtained with microarray analysis.
QRT-PCR analysis demonstrated that transcription of il1b, tnfa, il6, cxcl1, and ccl20 genes was
up-regulated (Table 3),
although only small to moderate increases were observed, compared to previous
study [22].  This finding is likely due to differences in
types of host cells and in S. aureus strains, and also due to the fact that we investigated only the effects of
intracellular staphylococci.  For
example, human umbilical endothelial cells infected with a clinical S. aureus isolate, were induced
expression of several proinflammatory cytokines/chemokines with similar fold changes to our
study at transcriptional level.
However, it did not induce expression of either tnfa, or ilb, which was different from our study
[26]. Similarly, vaginal
epithelial cells cocultured simultaneously with intracellular and extracellular S. aureus MNSM, producing toxic shock
syndrome toxin-1, for 3 hours showed increases in the transcription of il8, cxcl1,
and ccl20 (11.3-fold, 17.1-fold and
207.9-fold, resp.) which were much stronger than our results [22].Cyclooxygenase-2 gene  (cox2), an inducible form of the cyclooxygenase-1 gene
(cox1), was up-regulated at all
four-time-points in this study (Tables 2 and 3).  As an immediate early response gene that is
responsible for prostanoid biosynthesis involved in proinflammation, cox2 is expressed in epithelial cells,
macrophages, fibroblasts, and vascular endothelial cells [51].  COX2 is
induced by IL-1β [52] and lipoteichoic acid from S. aureus
[53].  Up-regulation of cox2 transcription was also associated with infection of epithelial
cells by gram-negative bacteria: Y. enterocolitica
[13] and  S. flexneri M90T, probably via LPS
[15].  The  induction
of cox2 expression  is not significantly in vaginal epithelial cell
cultures infected (intracellular plus extracellular) with the superantigen
producing strain S. aureus MNSM
(see above) [22], further emphasizing the potentially different  effects caused by various S. aureus strains, as well as the systems employed to measure their effects.


## 3.6. Cell Proliferation and Proapoptosis

IntracellularS. aureus RN6390 affected transcription
of several proapoptotic genes.
Dickkopf-1 (dkk1), was
up-regulated >2.00-fold at all time points examined (Tables 2 and
3).  Krüppel-like factors 4 and 6 genes (klf4 and klf6) were up-regulated
>2.00-fold at 2 hours postinfection (Table 2).  Microarray data showed the gene for caspase-9
(casp9) up-regulated ~2.00-fold at 2 hours
(Table 2), and this result
was confirmed by QRT-PCR (Table 3).  The
gene (bnip3) encoding Bcl2/adenovirus
E1B 19kDa interacting protein 3, a mitochondrial proapoptotic protein, was
up-regulated >2.00-fold at both 6 hours and 8 hours
(Table 2).  Two insulin-like growth factor binding
protein genes (igfbp1 and igfbp3) were up-regulated >1.50-fold at 4 hours, 6 hours, and 8 hours
postinfection (Tables 2 and
3).  The NR4A1 receptor gene
(nur77), which encodes a transcription
factor that exhibits proapoptotic properties in T cells [54], was up-regulated ~6-fold at 2 hours
(Table 2).  These findings were similar to several
studies demonstrating that the infection of epithelial cells
[8, 28, 32, 33], endothelial cells
[29, 30, 55, 56], and osteoblasts
[3, 57, 58]
with S. aureus can lead to
apoptosis.  Previous work in our lab had
shown the involvement of host caspases 3 and 8 in S. aureus-induced apoptosis
[32] and the requirement of the S. aureus virulence gene regulator agr in the induction of epithelial cell
apoptosis [33].


## 3.7. Profibrotic Gene Transcription in HEp-2 Cells

TGFβ1 is a key
protein involved in many cell functions including fibrosis formation,
regulation of cell cycle, apoptosis, and matrix remodeling [59].  QRT-PCR
indicated that tgfβ1 was
up-regulated by intracellular S. aureus
(Table 3). Intracellular S. aureus also induced transcription of several genes related to
TGFβ1, especially in regard to
fibrosis formation (Tables 2 and 3). In microarray experiments, transforming
growth factor beta receptor 2 gene (tgfβr2)
and epidermal growth factor receptor (EGFR)
gene (v-erb-b) were up-regulated >1.5-fold after 4 hours
(Table 2).
Integrin α5 gene (itga5) was gradually up-regulated after 2-hour-infection
(Table 2).  The gene (thbs1) encoding
thrombospondin 1 was up-regulated ~3.00-fold at 4 hours and 2.54-fold at 6 hours in microarray
experiments (Table 2), and similarly, with QRT-PCR
(Table 3).Plasminogen
activator inhibitor 1 and 2 genes (pai1, pai2) were up-regulated in
microarray experiments (Table 2).
Studies have shown that TGFβ1 induces plasminogen activator inhibitor 1
(PAI1) expression and demonstrated the
requirement for EGFR in this process [60–62].  Both PAI1 and PAI2 are inhibitors of the
fibrinolysis system, acting to block the activity of tissue plasminogen
activator and urokinase, and preventing the conversion of plasminogen to
plasmin.  Plasmin is a serine protease
that degrades fibrin clots as well as extracellular matrix components.  Thus, up-regulation of pai1 and pai2 may reduce extracellular matrix degradation.The CCN
(Cysteine-rich 61, Connective tissue growth factor, and Nephroblastoma
overexpressed) family members are cysteine-rich and functionally diverse
proteins that are involved in mitosis, apoptosis, adhesion, extracellular
matrix production, angiogenesis, and tumor growth [63].  Three genes belonging to the CCN family were
up-regulated.  Two of those, cyr61 and ctgf, were significantly up-regulated at early time points
(Table 2
and 3).  The third CCN gene, nov, was significantly up-regulated after 4 hours at transcriptional level
(Table 2).  An increased
transcription of cyr61 and ctgf genes has been shown during epithelial cell infection with Y. enterocolitica
[13], S. flexneri
[15], and B. pertussis [16].
CYR61, CTGF, and NOV have the capability to bind both fibronectin and α5β1 integrin, similar to IGFBP1 and
IGFBP3 [64–68], and are implicated in wound healing [68].  Taken
together, up-regulation of these profibrotic genes indicates that intracellular S. aureus might affect the extracellular matrix by
stimulating fibrosis and aiding
in repair of the damage caused
by S. aureus infection.


## 3.8. Cholesterol Biosynthesis

IntracellularS. aureus caused down-regulated
expression of cholesterol biosynthesis enzyme genes, including sterol-c4-methyl
oxidase-like (sc4mol),
3-hydroxy-3-methylglutaryl-coenzyme A reductase (hmgcr), hydroxysteroid (17β) dehydrogenase 7
(hsd17b7), isopentenyl-diphosphate delta isomerase (idi1), squalene monooxygenase (sqle), sterol c5-desaturase-like (sc5dl), farnesyl-disphosphate
famesyltransferase 1 (fdft1), and
7-dehydrocholesterol reductase (dhcr7).  Genes involved in regulation of cholesterol
synthesis were also down-regulated.  Insulin-induced
gene 1 (insig1), encoding a membrane
endoplasmic reticulum protein, was down-regulated (0.20-fold at 4 hours,
0.26-fold at 6 hours, and 0.41-fold at 8 hours)
(Table 2).  Acetyl CoA
synthetase gene (acas2) and low-density lipoprotein receptor gene (ldlr) were also transcriptionally
down-regulated (Table 2).  QRT-PCR data
confirmed the down-regulation of hmgcr, sqle, dhcr7, and ldlr
(Table 3).  Cholesterol quantification with GC-MS
also showed that host cells displayed
a corresponding decreased cholesterol synthesis after a challenge with
intracellular S. aureus (Table 4).
Garner et al. showed an essential
role for cholesterol in the uptake of S.
typhimurium into HeLa cells, demonstrating that the removal of cholesterol
caused a greater than 90%
decrease in bacterial uptake [69].  Thus, a reduction in cholesterol may be a response to limit the
internalization of S. aureus.  In addition, a decrease in cholesterol levels
could limit the effects of S. aureus exotoxins on the host cell membrane. S.
aureus alpha toxin, along with other pore-forming toxins from Streptococcus and Clostridium species, showed reduced activity when cholesterol levels
in lipid membranes were decreased [70, 71].  A recent study showed that the golden S. aureus pigment, staphyloxanthin, is
synthesized with the same substrates used for cholesterol biosynthesis by host
cells [72].  It is unclear at present whether
the effect on cholesterol biosynthesis is related to this finding; however, it
is conceivable that this effect might represent a host response to affect
production of this staphylococcal virulence factor.Table 4
Cholesterol
quantification [(μg/105 cells)  ± SD]  in uninfected
and infected HEp-2 cell
monolayers.
Cell
typeIncubation time (h)2468Unchallenged HEp-2 cell75.82±2.9969.78±5.3164.94±5.0055.91±4.78Challenged HEp-2 cell58.43±3.7351.92±2.8750.74±5.2243.38±3.36% cholesterol reduction22.9125.6021.8722.41P value.005.050.045.026In summary, this
study demonstrates that several classes of genes in HEp-2 cells undergo changes
in transcriptional expression in response to intracellularS. aureus.  We
observed that, in the first few hours of intracellular infection, epithelial
cells can respond to intracellular S. aureus quickly by inducing early
stress response (AP-1 complex) and MAPK pathways (Ras, P38), which consequently
stimulate broader responses
such as proinflammatory response, apoptosis, and fibrosis.  Our data support the belief that the role of epithelial cells in innate
immunity is not simply that of a physical barrier against invading pathogens,
but it is also actively
involved in the induction of more complex host defense mechanisms.  Another possibility is that, as a successful
pathogen, intracellular S. aureus might lead to host gene
expression that facilitates its
intracellular survival.  This is
consistent with induction of Ras-related cytoskeleton reorganization and the fibrosis process.  Our results are also consistent with,
although not definitive of, a delicate balance between effects which benefit
the host and those which are more beneficial to S. aureus.  Finally, this
study showed that intracellular S. aureus suppressed cholesterol synthesis in epithelial cells.  The consequence of this
suppression on the pathogenesis of S.
aureus is not clearly presented but might be related to recent observations regarding staphylococcal
pigment production.



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*Source: 753278-2009-02-03.xml*