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Transcript of Microarray analysis of adipocytes treated with protease ...€¦ · Web view] and lipid...
Title: Microarray analysis reveals altered lipid and glucose metabolism genes in differentiated,
ritonavir-treated 3T3-L1 adipocytes
Running title: Microarray analysis of ritonavir-treated 3T3-L1 adipocytes
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Abstract
Objective: HIV lipodystrophy is characterised by abnormal adipose tissue distribution and metabolism,
as a result of altered adipocyte function and gene expression. The protease inhibitor ritonavir is
associated with the development of lipodystrophy. Quantifying changes in adipogenic gene expression
in the presence of ritonavir may help to identify therapeutic targets for HIV lipodystrophy.
Methods: Affymetrix Mouse Genome 430 2.0 oligonucleotide microarray was used to investigate gene
expression in 3T3-L1 adipocytes treated with 20 μmol/l ritonavir or vehicle control (ethanol). Pparg,
Adipoq and Retn expression were validated by real time RT-PCR. Transcriptional signalling through
PPAR-γ was investigated using a DNA-binding ELISA. Changes in adipocyte function were
investigated through secreted adiponectin quantification using ELISA and Oil Red O staining for
triglyceride storage.
Results: Expression of 389 genes was altered by more than 5-fold in the presence of ritonavir (all P <
0.001). Gene ontology analysis revealed down-regulation of genes responsible for adipocyte
triglyceride accumulation including complement factor D (Cfd; 238.42-fold), Cidec (73.75-fold) and
Pparg (5.63-fold). Genes involved in glucose transport were also down-regulated including Adipoq
(24.42-fold) and Glut4 (13.36-fold). PPAR-γ regulatory genes Cebpa (11.33-fold) and liver-X-receptor
α (Nr1h3) were down-regulated. Changes in Pparg and Adipoq were confirmed by RT-PCR. PPAR-γ
binding to its nuclear consensus site, adiponectin secretion and triglyceride accumulation were all
reduced by ritonavir.
Conclusion: Ritonavir had a significant effect on expression of genes involved in adipocyte
differentiation, lipid accumulation and glucose metabolism. Down-regulation of Pparg may be
mediated by changes in Cebpa, Lcn2 and Nr1h3.
Keywords: adipocyte; HIV lipodystrophy; microarray; PPAR-gamma; protease inhibitor; resistin;
ritonavir
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1. INTRODUCTION
Abnormalities of body fat distribution and metabolism are reported to occur in up to 83 % of HIV
patients receiving antiretroviral therapy [1] and collectively these abnormalities are referred to as the
HIV-associated lipodystrophy syndrome (HALS) [2]. The extent to which different antiretroviral drugs
(ARVs) induce these abnormalities varies greatly between and within the drug classes. Protease
inhibitors (PI) are known to cause central fat accumulation and insulin resistance [3], while nucleoside
reverse transcriptase inhibitors (NRTI) have been associated with the development of lipoatrophy (LA)
of the face and extremities [4]. In contrast, nucleotide reverse transcriptase inhibitor (NtRTI)-based
regimens have been shown to be beneficial in improving LA [5], highlighting the fact that not all ARVs
are equal in their effects on adipose tissue.
Disruption of adipogenic processes plays a key role in the pathogenesis of HALS [6]. ARVs have been
shown to induce adipocyte dysfunction by inhibiting differentiation and adipogenesis [7], increasing
lipolysis [8] and increasing pro-inflammatory cytokine secretion [9]. Caron et al [6] suggest that ARV-
induced down-regulation of peroxisome proliferator-activated receptor (PPAR)-γ contributes to
adipocyte dysfunction in HALS. Data on the effect of ARVs on PPAR-γ are inconsistent; some studies
have shown ARVs to down-regulate PPAR-γ in vitro [10, 11] and in adipose tissue biopsy samples
from HALS patients [12], while other in vitro studies show no effect [7, 13, 14]. Microarray analysis of
samples from 3T3-L1 pre-adipocytes exposed to ARV has previously been carried out by two groups
and validated using RT-PCR. A detailed study by Pacenti et al [15] identified 1091 genes differentially
altered by NRTI and PI (not RTV) alone or in combination. PPAR-γ was among the genes significantly
down-regulated, which was confirmed by RT-PCR. Similarly, Adler-Wailes et al [13] showed
significant PPAR-γ down-regulation in adipocytes using microarray, but this was not confirmed by RT-
PCR. PPAR-γ target genes such as adiponectin are also down-regulated by ARVs [16]. The use of
synthetic PPAR-γ ligand rosiglitazone has been shown to enhance PPAR-γ and target gene expression
in adipose tissue of HALS patients [17] and to improve LA [18], which provides further support for the
role of PPAR-γ in HALS.
Ritonavir (RTV), from the PI class, is routinely used as a pharmacoenhancer of other antiretroviral
drugs and is listed by the World Health Organisation as an essential medicine required for a basic
health system [19]. The use of RTV as a boosting agent is due to its ability to inhibit cytochrome P450-
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3A4, thereby increasing circulating concentrations of other PIs [20]. Physiological concentrations of
RTV have been found to range from 0.84 μmol/l to 21.9 μmol/l [21]. The benefits of
pharmacoenhancement using RTV are marred to some extent by its interaction with other drugs, as
well as its side-effects. RTV has been shown to cause increased triglyceride hydrolysis and fatty acid
efflux in adipocytes [22] and LA in mice [23].
We investigated the effect of RTV on gene expression using microarray analysis and validated the
findings for Pparg and Adipoq using RT-PCR in 3T3-L1 cells, which are widely used for the study of
adipogenesis. We also investigated effects on nuclear binding of PPAR-γ and functionality of
adipocytes through adiponectin secretion and triglyceride storage.
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2. MATERIALS AND METHODS
2.1. Cell culture and treatment
3T3-L1 pre-adipocytes were maintained in DMEM-F12 (Invitrogen Life Technologies, Paisley, UK),
supplemented with 10% FBS (Sigma Aldrich, Poole, UK), 8 μg/ml pantothenate (MP Biomedicals
Europe, London, UK), 8 μg/ml biotin, 200 mM glutamine, 10,000 U/ml penicillin, 10 μg/l streptomycin
(all Sigma Aldrich) and 10 mg/l MycoKill AB mycoplasma antibiotic (PAA Laboratories Ltd., Yeovil,
UK) at 37°C with 5% CO2. Pre-adipocytes were grown to near confluence for 5 days and a further two
days to initiate growth arrest. Pre-adipocytes were induced to differentiate using an adipogenic cocktail
of 1 μg/ml insulin (Sigma Aldrich, Poole, UK), 0.5 mM 3-isobutyl-1-methylxanthine (IBMX;
Cambridge Bioscience, Cambridge, UK) and 0.25 μmol/l dexamethasone (Sigma Aldrich) for two days.
Subsequently, the medium was removed and replaced with adipogenic medium supplemented with 1
μg/ml insulin and near Cmax concentrations of 20 μmol/l RTV (VWR, Lutterworth, UK) or vehicle
control ethanol (0.1% v/v) for 5 days. Medium was changed every second day thereafter until the
adipocytes were fully differentiated after the 5 days, as determined by light microscopy. Cells were
exposed to treatments for a total of five days. Cell viability was confirmed prior to experimental work
using the MTS CellTiter 96 Aqueous One Solution assay (Promega, Southampton, UK). Quadruplicate
cell cultures were performed for each experimental condition.
2.2. RNA extraction and preparation
Total RNA was extracted from adipocytes after 5 days of exposure to antiretroviral drug or control
using the RNeasy Mini Kit according to manufacturer’s instructions (Qiagen, Manchester, UK).
Briefly, cells were lysed and homogenised using a highly denaturing guanidine-thiocyanate-containing
buffer. Ethanol was added to provide appropriate binding conditions and the sample was then applied
to an RNeasy Mini spin column. Total RNA binds to the membrane and contaminants were efficiently
washed away. RNA was eluted in 50 μl nuclease-free water. Total RNA (1 μg) was extracted from
adipocytes after 5 days of exposure to antiretroviral drug or control using the RNeasy Mini Kit
(Qiagen) as per manufacturer’s instructions. RNA was quantified using the NanoDrop® 1000 3.7.1
(Thermo Scientific, Wilmington, USA).
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2.3. Microarray hybridisation and data analysis
RNA samples were pooled to minimise individual variation as a source of gene-expression variance
(one pool representing the four control-treated cells and one representing the four RTV-treated cells).
500 ng of each of the two pooled samples in 5 μl nuclease-free water was used in the reactions. The
MessageAmp™ Premier RNA Amplification kit (Invitrogen Life Technologies) was used for cDNA
synthesis using ArrayScript™ reverse transcriptase. cDNA was then used in an in-vitro transcription
(IVT) reaction to synthesise biotin-modified amplified RNA (aRNA) according to the manufacturer’s
protocol. After synthesis, the biotin-modified aRNA was purified to remove enzymes, salts and
unincorporated nucleotides using the same kit. The concentration of aRNA was determined using the
NanoDrop® spectrophotometer (Thermo Scientific). Biotinylated aRNA was fragmented prior to
hybridisation using the 5X Array Fragmentation Buffer supplied with the MessageAmp™ Kit.
The aRNA sample was then evaluated using the Agilent®2100 Bioanalyser instrument (Agilent
Technologies Inc., Santa Clara, USA) and RNA 6000 Nano Kit loaded with 300 ng of aRNA per well.
The fragmented aRNA had a distribution of 35-200 nucleotides with a peak at approximately 100-200
nucleotides. 11 μg of aRNA were hybridised onto the Affymetrix Mouse Genome 430 2.0 Array Kit
(Affymetrix, High Wycombe, UK). The arrays were subsequently washed, stained and scanned on the
Fluidics Station 400 and the GeneArray Scanner (Agilent Technologies, Inc.) according to the
manufacturer’s protocol.
The Robust Multi-array Average approach was used to analyse the data using quantile normalisation
and the average change in expression was determined for each gene using the formula =IF(‘ratio
value’<1, -1/’ratio value’, ‘ratio value’) where the ratio value is ratio of treatment/control. A two-fold
change relative to control (signal log ratio ≥ 1.0 or ≤ -1.0) was selected as the threshold to define
differentially expressed genes. Altered gene lists were imported into MetaCore™ pathway analysis
software (GeneGo, Thomson Reuters, New York) where differentially expressed genes were classified
into functionally-related gene clusters.
MetaCore™ pathway analysis software was used (GeneGo, Thomason Reuters) to generate a list of
relevant gene ontology (GO) terms describing genes affected by RTV in terms of their biological
function. We input 389 Affymetrix probe identifications showing a difference of greater than 5-fold
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between RTV-treated cells and controls. A P value was generated based on the number of interactions
each gene has within the pathway. A false discovery rate (FDR) of 1 was selected to identify all objects
with at least one connection with the dataset.
2.4. Analysis of gene expression by real-time RT-PCR
cDNA was generated by reverse transcription using the High Capacity RNA-to-cDNA kit (Invitrogen
Life Technologies) as per manufacturer’s instructions. Real-time RT-PCR was used to measure PPAR-
γ, adiponectin, resistin and endogenous housekeeping control hypoxanthine-guanine
phosphoribosyltransferase (Hprt) gene expression using TaqMan® Gene Expression Assays
(Invitrogen Life Technologies). Data were analysed using the 2 -ΔΔCT method for target gene expression
normalised to control.
2.5. Nuclear PPAR-γ activation
A nuclear extract kit (Active Motif Europe, Rixensart, Belgium) was used for the extraction of nuclear
proteins from adipocytes after 5 days of exposure to antiretroviral drug or control as per manufacturer’s
protocol. Protein concentration was determined using the Bradford assay as per manufacturer’s
instructions (Sigma Aldrich). 10 μg of nuclear extract was used in a TransAM™ PPAR-γ transcription
factor assay (Active Motif Europe, Rixensart, Belgium) to investigate PPAR-γ nuclear binding to the
peroxisome proliferator response element (PPRE) as per manufacturer’s instructions. Absorbance was
measured on the Synergy HT-1 spectrophotometer (Biotek, Potton, UK) at 450 nm with a reference
wavelength of 655 nm.
2.6. ELISA
Adiponectin concentration in cell culture media was determined after 5 days of exposure to
antiretroviral drug or control. Cell supernatants were collected, centrifuged at 12,000 rpm for 10
minutes, aliquoted and stored at -20°C. Adiponectin concentration in supernatants was determined
using the DuoSet® ELISA Development kit as per manufacturer’s protocol (R&D Systems Inc.,
Abingdon, UK).
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2.7. Oil Red O staining
Oil Red O (ORO) staining (Sigma Aldrich) was used to determine the effect of treatments on adipocyte
triglyceride (TG) accumulation after 5 days of exposure to antiretroviral drug or control. Briefly, cells
were fixed with 10% formalin (VWR) for 1 h, rinsed with 60% isopropanol (Fisher Scientific,
Loughborough, UK) and stained with 60% ORO working solution prepared in isopropanol for 10
minutes. After washing with distilled water, the ORO was eluted using 100% isopropanol and the
optical density of the solution measured at 540 nm using the Synergy HT-1 spectrophotometer
(Biotek). Photographs of cell morphology were taken with a DXM 1200 Digital Camera (Nikon,
Kingston Upon Thames, UK) and a Lucia G Image-Processing System (version 4.61; Nikon).
2.8. Statistical analysis
Statistical analyses were performed using SPSS software (version 20; IBM, Hampshire, UK). Data for
RT-PCR, ELISA and DNA binding ELISA were analysed using independent samples t-tests to
compare treatment (ritonavir) with control (ethanol). Differences were considered significant if P <
0.05. Data are expressed as the mean ± standard error of the mean (SEM).
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3. RESULTS
3.1. Gene expression analysis
3.1.1. Microarray
All probe sets which produced an “absent” or “no change” signal compared with control were removed.
Of the remaining probes, those with greater than a 5-fold change compared with control were selected
in order to minimise background noise and isolate only significantly altered genes. These probes
represented 389 gene transcripts with altered expression, of which 84 (22 %) were up regulated and 304
(78 %) were down regulated. A full list of the 389 probe sets with altered expression compared with
control is available online (Supplementary Table 1). Of these 389 probe sets, 316 represent unique
genes with altered expression compared with control. A list of these 316 probe sets and their associated
fold changes is available online (Supplementary Table 2). There were 69 gene transcripts with
expression increased by 5.0-fold or more in RTV-treated cells compared with controls and 234 gene
transcripts with expression decreased by 5.0-fold or more. Table 1 presents gene transcripts in this list
which were also identified within the two top Gene Ontology processes affected by RTV.
3.1.2. Gene ontology
The main GO processes affected by RTV are listed in Figure 1 (all P < 0.001). Brown and white fat
cell differentiation were two of the top GO processes affected by RTV. Network objects (genes) within
these two main GO processes are listed in Table 1 with their corresponding fold changes.
3.1.3. Genes involved in adipocyte lipid and glucose metabolism
A number of gene transcripts with well-established roles in adipocyte differentiation and triglyceride
storage were altered in response to RTV treatment. Two were transcription factors involved in
regulating adipogenesis: PPAR-γ (-5.63-fold) and C/EBPα (-11.33-fold). PPAR-γ target gene
adiponectin was also down-regulated by RTV (24.4-fold). Other down-regulated adipogenic gene
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transcripts included resistin (Retn; -95.17-fold), fibronectin (Fn1; -9.33-fold), integrin alpha chain
alpha 6 (Itga6; -8.12-fold), lipin (-6.55-fold) and cell division cycle 20 (Cdc20; -5.80-fold).
RTV down-regulated transcript levels of genes involved in lipid homeostasis: steroyl-CoA desaturase
(Scd; -19.84-fold), liver-X-receptor alpha (Nr1h3; -7.08-fold), cluster of differentiation 36 (Cd36; -
9.04-fold), fatty acid binding protein 4 (Fabp4; -6.20-fold), cell death-inducing DFFA-like effector c
(Cidec; -73.75-fold), complement factor D (Cfd; -238.42-fold), beta 3 adrenergic receptor (Adrb3; -
36.03-fold), inhibin beta B (Ihbb; -44.18-fold) and lipocalin 2 (Lcn2; -18.70-fold). Transcript levels of
adipocyte glucose metabolism genes phosphodiesterase 3 (Pde3b; -10.31-fold) and glucose transporter
type 4 (Glut4; -13.36) were also down-regulated by RTV. Other functional and lipid metabolism gene
transcripts down-regulated by RTV included Shp1 (-5.83-fold), adipose triglyceride lipase (Pnpla2; -
5.49-fold),
In addition, transcript levels of a number of adipocyte genes were up-regulated in response to RTV
treatment including inhibitor of DNA binding 2 (Id2; 10.44-fold), interleukin-6 (Il6; 10.39-fold) and
PPAR-γ coactivator 1a (Ppargc1a; 5.09-fold). Gene transcripts involved in cell structure (alpha-actin-
2; 5.81-fold), macrophage development (Csf1; 5.78-fold) and thrombolysis (Plat; 5.37-fold) were also
up-regulated.
3.1.4. Investigation of PPAR-γ, adiponectin and resistin expression using RT-PCR
To confirm the microarray findings, mRNA expression of PPAR-γ, adiponectin and resistin was
investigated by RT-PCR. RTV significantly down-regulated Pparg mRNA expression (P = 0.002;
Figure 2) and Adipoq mRNA expression compared with control (P = 0.001; Figure 3). No significant
difference was observed in Retn mRNA expression in RTV-treated cells compared with control (P =
0.331; Figure 4).
3.2. PPAR-γ nuclear binding
In order to further investigate the mechanisms underlying Pparg down-regulation, we investigated the
effect of RTV on PPAR-γ binding to its nuclear response element, PPRE. Nuclear PPAR-γ binding to
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the immobilised consensus site was significantly reduced in cells exposed to RTV during
differentiation (P = 0.002; Figure 5).
3.3. Adiponectin protein secretion
Adiponectin protein secretion was investigated using ELISA to determine whether the effect of RTV
on gene expression was also mirrored by findings at the protein level. Adiponectin protein secretion
was also significantly decreased by RTV compared with control (P < 0.001; Figure 6).
3.4. Phenotypic changes in RTV-treated adipocytes
Adipocyte function was investigated by measuring TG accumulation in 3T3-L1 adipocytes treated with
RTV or vehicle control (ethanol). RTV significantly decreased TG accumulation (29 %) in
differentiated adipocytes (P = 0.001; Figure 7). ORO stained images show reduced TG accumulation
in RTV-treated adipocytes compared with vehicle control (Figure 8).
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4. DISCUSSION
In this study, we investigated global gene expression in adipocytes treated with RTV in order to
determine its contribution to adipocyte dysfunction and lipodystrophy. We identified 389 probe sets
representing 316 unique gene transcripts with expression levels altered more than 5-fold. Gene
ontology analysis identified brown and white fat cell differentiation as two key GO terms affected.
Transcript levels for a number of genes involved in adipocyte lipid and glucose metabolism within
these main GO processes were altered by RTV.
ARV-induced adipocyte dysfunction contributes to the development of lipodystrophy in HIV and is
thought to be mediated by alterations in the expression of PPAR-γ [6], a key adipogenic transcription
factor [24]. PPAR-γ was down-regulated by RTV in microarray analysis in this study. This finding was
confirmed by RT-PCR. Furthermore, when we investigated nuclear PPAR-γ binding to its gene
response element PPRE, we found a significant reduction in binding in response to RTV, which
suggests that PPAR-γ activation is inhibited by RTV. Our results substantiate previous reports for
PPAR-γ gene and protein expression in vitro [10, 11, 25]. Furthermore, an earlier microarray study of
3T3-L1 adipocytes treated with ARVs has shown altered PPAR-γ expression in response to treatment
with NRTI and PI, although RTV was not used in this study [15]. Differences in ARVs used certainly
account differences between our work and that of Pacenti and colleagues. Moreover, Pacenti et al
analysed samples over several days of pre-adipocyte differentiation (day 0, 3, 6, 10), while we
examined gene expression in differentiated adipocytes at one time point only. Similarly, in another
study, Adler-Wailes et al [13] investigated the effect of 10 µM RTV and found that PPAR-γ was down-
regulated in microarray, although no change was observed in subsequent RT-PCR analysis. The higher
concentration of RTV used in our study (20 µM) may have induced changes in PPAR-γ expression
detected by RT-PCR, which were not observed by Adler-Wailes et al. Moreover, statistical analysis
differed between studies: in the current study we expressed data in terms of fold change difference of
RTV-treated cells compared with control; Adler-Wailes et al used a linear regression model to
determine the effect of RTV over time and Pacenti et al used a ratio of adipocyte/pre-adipocyte gene
expression at day 3 or day 10. Other studies show mixed results for PPAR-γ expression in response to
RTV; some studies show no change in expression [7, 14], while others show a significant down-
regulation [10, 11, 25]. Given the role of PPAR-γ in adipogenesis, it is plausible that down-regulation
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of PPAR-γ leading to reduced adipogenesis may be responsible for the reduction in TG accumulation
observed in RTV-treated cells in this study.
The mechanisms underlying PPAR-γ down-regulation by antiretroviral drugs are not well understood.
There is some evidence to suggest that antiretroviral drugs alter the expression of genes upstream of
PPAR-γ including sterol regulatory element binding protein-1 (SREBP1) [26], extracellular signal
regulated kinase 1/2 and Akt/ protein kinase B [27, 28]. In this study, microarray analysis revealed
down-regulation of Nr1h3, the gene encoding liver-X-receptor α. During adipocyte differentiation,
insulin induces the expression of Nr1h3, which enhances SREBP1 expression, resulting in
transcriptional activation of PPAR-γ [29]. Down-regulation of Nr1h3 in this study may provide one
possible mechanism for the observed effect of RTV on PPAR-γ. C/EBPα is another essential
adipogenic transcription factor which induces PPAR-γ expression early in the differentiation process
(reviewed by [30]). The importance of C/EBPα is highlighted by the fact that adipocytes from Cebpa
knock-out mice do not accumulate lipid [31]. Cebpa was down-regulated by RTV in the current study,
which confirms findings from other studies using both NRTI and PI classes [21, 25]. Down-regulation
of Cebpa could be suggested to contribute to the reduction in PPAR-γ gene expression. PPAR-γ
expression is also regulated by lipocalin (Lcn2), an important adipokine involved in lipid metabolism,
body fat regulation and insulin resistance [32]. Lipocalin knockout mice demonstrate reduced de-novo
lipogenesis in adipose tissue [32], while serum lipocalin is reduced in HIV-infected individuals, but
increases significantly with the use of antiretroviral drugs [33]. Thus, down-regulation of lipocalin in
the current study may be another mechanism underlying the reduction in PPAR-γ expression, as well as
the reduction in triglyceride accumulation observed using Oil Red O stain. Inhibitor of DNA binding
(Id2) is increased during adipocyte differentiation and acts upstream of PPAR-γ to enhance its
expression [34]. Gene transcripts for Id2 were up-regulated in our study in response to RTV, which has
also been observed in obese mice and humans [34]. However, this was not reflected in the expression
levels of PPAR-γ observed in this study. Overall, the effect of ARVs on the expression of genes
upstream of PPAR-γ, including Nr1h3, Cebpa and Lcn2, may contribute to PPAR-γ down-regulation
by RTV.
A number of genes involved in lipid metabolism were down-regulated by RTV in this study including
Lipin (Lpin1). This mirrors findings from in vivo studies where lipid expression is decreased in HIV-
infected patients with lipodystrophy compared with those without lipodystrophy. Moreover, increased
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lipin expression was found to be associated with maintenance of greater fat mass and reduced cytokine
expression in lipoatrophy [35]. Lipin acts with PPARs as a coactivator of nuclear transcription to alter
the expression of other lipid metabolism genes [36]. Adipose triglyceride lipase is recognised for its
important role in adipocyte lipolysis [37], and was down-regulated by RTV in the current study. This
contrasts with the work of Adler-Wailes et al who showed increased expression of the gene in 3T3-L1
adipocytes treated for 14 days with 10 μmol/l RTV [22]. Differences may have resulted from a longer
exposure of adipocytes to RTV in the study of Adler-Wailes et al.
In the current study, transcript levels for a number of glucose metabolism genes within the two main
pathways were altered by RTV. The effect of RTV on glucose metabolism and insulin signalling has
previously been demonstrated [14, 38]. Adiponectin is an insulin-sensitising adipokine induced during
adipocyte differentiation [39] which was down-regulated -24.42-fold by RTV. This finding was
confirmed by data from RT-PCR and ELISA, which showed a significant reduction in adiponectin
expression and protein secretion. A number of other studies have demonstrated effects for PI (RTV,
amprenavir, atazanavir and abacavir) on adiponectin mRNA expression [13, 16] including two groups
who used the same 20 μmol/l concentration of RTV [7, 14]. The precise mechanism underlying
adiponectin inhibition is unclear. PPAR-γ has been suggested to play a role in the transcriptional
activation of the adiponectin gene via a PPRE in the adiponectin promoter [40]. Thus, down-regulation
of adiponectin secretion in RTV-treated adipocytes in this study may be mediated by PPAR-γ.
Furthermore, adiponectin gene transcripts were negatively regulated by pro-inflammatory cytokines
such as IL-6 and TNF-α [41] and in our study, IL-6 was up-regulated 10.39-fold in RTV-treated cells.
Therefore, it is possible that increased IL-6 expression in RTV-treated cells may contribute to the
inhibition of adiponectin expression.
Resistin is an adipokine shown to modulate adipogenesis, glucose uptake [42] and lipid metabolism
[43] in non-ARV-treated adipocytes. This finding is supported by evidence from mice where resistin
knockdown suppresses lipid production and activates fatty acid β-oxidation [43]. To the best of our
knowledge, the current study is the first to demonstrate down-regulation of resistin mRNA expression
(-95.17-fold) in vitro in response to RTV. Resistin expression in the context of HIV has previously
been investigated and patients with HALS have been shown to have higher plasma resistin levels than
uninfected controls [44]. In contrast, others have found no association between serum resistin and fat
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redistribution, insulin resistance or metabolic profile [45, 46]. Our findings are novel and highlight the
need for future studies focusing on resistin in HALS.
In addition to its inhibitory effect on gene transcripts, RTV also up-regulated a number of gene
transcripts within the white and brown adipose tissue gene networks. We observed an increase in IL-6
transcript levels in this study, which has previously been demonstrated in 3T3-F442A adipocytes [47]
and a number of studies in SGBS adipocytes [7, 14] and primary human adipocytes [16]. This effect
may be partly explained by the increased transcriptional expression of beta-3 adrenergic receptor
(Adrb3) (+36-fold) observed in this study; activation of the beta-3 adrenergic receptor has been linked
to increased expression of inflammatory genes, including IL-6 [48]. Increased IL-6 expression may
contribute to the reduction in adiponectin expression observed in this study, as a result of the negative
feedback loop that exists between IL-6 and adiponectin [49]. IL-6 has been suggested to play a role in
insulin resistance by blocking insulin signalling in adipocytes [50]. Increased IL-6 has been
demonstrated in subcutaneous adipose tissue from patients with HALS [51] and may mediate insulin
resistance in these patients. HIV/HAART-associated lipoatrophy is associated with adipose tissue
fibrosis [52]. Alpha actin 2 (Acta2) is a marker of adipose tissue fibrosis and was increased in this
study. This has been demonstrated previously in microarray analysis by Pacenti et al [15] and suggests
that RTV may play a role in increasing adipose tissue fibrosis. In patients with HIV lipodystrophy,
increased PAI-1 has been demonstrated, particularly in subcutaneous adipose tissue [53]. Although
PAI-1 was not one of the main genes altered in our study, we did observe an increase in mRNA
expression of Plat. Plat is responsible for the formation of plasmin, a fibrinolytic enzyme, from
plasminogen, a process which is inhibited by PAI-1. The increase in mRNA expression of Plat in our
study highlights the potential detrimental effect of RTV on haemostasis.
The current study has some limitations which warrant mentioning. Experiments were conducted in
murine 3T3-L1 adipocytes; therefore, the potential to translate the results to human adipocytes and
even further to humans is limited. However, our data provide further support for the significant
detrimental effects of RTV in vitro. Secondly, we investigated the effects of RTV at a concentration of
20μmol/l only. In vivo, levels of circulating ARVs are not sustained i.e. levels peak and trough.
Furthermore, protein binding, blood flow and drug transporters may also play a key role in drug
distribution, which will affect circulating ARV concentrations. However, in this study we show that
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RTV, which is routinely used as a boosting agent to increase the plasma concentrations of other PI [54],
appears to have a profound effect on adipocyte function and differentiation.
5. CONCLUSION
In this study, we focused on adipocyte differentiation pathways and demonstrated detrimental effects of
RTV on transcript levels of genes involved in adipogenesis, lipid and glucose metabolism, as well as
lipolysis. We hypothesize that down-regulation of PPAR-γ negatively affects adipogenesis and target
genes involved in adipocyte lipid and glucose metabolism. The net result is an adipocyte which is
inefficient in storing triglyceride and with increased susceptibility to lipolysis. Results of this study
suggest that RTV-induced down-regulation of C/EBPα, LXR-α and lipocalin genes may play an
important role in PPAR-γ down-regulation. Future studies should investigate the role of other genes
identified in the microarray which were affected by RTV, but not fully explored in this study. It seems
clear that down-regulation of PPAR-γ is central to the development of adipocyte dysfunction, which is
likely to contribute to the HIV/HAART-associated lipodystrophy. PPAR-γ is a transcription factor of
interest and may represent a suitable target to combat ARV-induced adipocyte dysfunction as it is
believed to be ligated by a number of dietary long chain polyunsaturated fatty acids and their
derivatives – including conjugated linoleic acids from dairy produce and omega-3 fatty acids from fish
oil.
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CONFLICT OF INTEREST
This research was supported by a grant from the Nutricia Research Foundation. The main author
received a PhD scholarship from King’s College London Graduate School. The work outlined in this
article, in addition to other work, contributed to a chapter of the main author’s PhD thesis.
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SUPPORTING MATERIAL
Supplementary Table 1 provides a full list of gene transcripts altered by ritonavir.
Supplementary Table 2 provides a list of the unique gene transcripts altered by ritonavir.
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FIGURES AND TABLES
Brown fat cell differentiation
Fat cell differentiation
Single-organism developmental process
Developmental process
System development
Single-multicellular organism process
Multicellular organismal development
Multicellular organismal process
Positive regulation of biological process
Anatomical structure development
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4
Figure 1 Gene Ontology processes affected by RTV. Significant representation in Gene Ontology 389 probes indicated a change in gene expression between RTV and control cells. These genes were categorised according to the gene ontology processes they formed part of. The Gene Ontology Terms significantly represented are shown. The length of each bar is proportional to the ratio of the number of genes altered compared with the total number of genes in the GO network. P < 0.001 for all Gene Ontologies shown.
Table 1 Network objects within the main gene ontology processes affected by RTV
Down-regulated genes
Probe identification Gene name Gene symbol Fold change
1417867_at Complement factor D Cfd 238.42
1449182_at Resistin§ Retn 95.17
1452260_at Cell death-inducing DFFA-like effector c Cidec 73.75
1426858_at Inhibin beta B Inhbb 44.18
1455918_at Beta-3 adrenergic receptor Adrb3 36.03
1422651_at Adiponectin Adipoq 24.40
1415965_at Steroyl CoA desaturase-1 Scd-1 19.84
1427747_a_at Lipocalin 2 Lcn2 18.70
1415959_at Glucose transporter type 4 Glut4 13.36
1418982_at CCAAT-enhancer binding protein alpha Cebpa 11.33
1422340_a_at Actin Actin 11.26
1433694_at Phosphodiesterase 3 Pde3b 10.31
1437218_at Fibronectin Fn1 9.33
1423166_at Cluster of differentiation 36 Cd36 9.04
1422444_at Integrin alpha 6 Itga6 8.12
1450444_a_at Liver-X-receptor-alpha Nr1h3 7.08
1428014_at Histone H4 H4 7.09
1417290_at Leucine-rich alpha-2- glycoprotein Lrg 6.58
1418288_at Lipin§ Lpin1 6.55
1424155_at Fatty acid binding protein Fabp4 6.20
1417812_a_at Laminin, beta 3 Lamb3 5.90
1460188_at Src homology 2–containing protein tyrosine phosphatase Shp1 5.83
1439377_x_at Cell division cycle 20 homolog Cdc20 5.80
1420715_a_at Peroxisome proliferator-activated receptor -γ Pparg 5.63
1428143_a_at Adipose triglyceride lipase Pnpla2 5.49
Up-regulated genes
Probe identification Gene name Gene symbol Fold change
1435176_a_at Inhibitor of DNA binding 2 Id2 10.44
1450297_at Interleukin-6 Il6 10.39
1416454_s_at Alpha-actin-2 Acta2 5.81
1460220_a_at Colony stimulating factor 1 Csf1 5.78
1415806_at Tissue plasminogen activator Plat 5.37
1456395_at Pparg coactivator 1 alpha Ppargc1a 5.09
1450781_at High mobility group protein AT-hook 2 Hmga2 5.04
Network objects from adipocyte-related GO processes as shown in Figure 1. §Object appears in the white, but not brown, adipocyte differentiation network only. All other genes are common to both pathways. Fold change is the change in expression in RTV-treated compared with control cells. The full set of gene transcripts and unique probe sets with expression altered >5-fold can be found in the supplementary online tables.
Control RTV0
0.2
0.4
0.6
0.8
1
1.2 PPAR-γ mRNA expression
Treatments
Fold
tran
scri
ptio
n re
lativ
e to
con
trol
, Hpr
t
*
Figure 2 Pparg mRNA transcription. Adipocytes were treated with vehicle control (ethanol) or 20
μmol/l RTV and expression of PPAR-γ mRNA was measured on day 5 relative to Hprt housekeeping
gene by RT-PCR. Results represent mean ± SEM of quadruplicate cell cultures. *Significantly different
(P < 0.05) from control cells.
Control RTV0
0.2
0.4
0.6
0.8
1
1.2
Adiponectin mRNA expression
Treatments
Fold
tran
scri
ptio
n re
lativ
e to
con
trol
*
Figure 3 Adipoq mRNA transcription. Adipocytes were treated with vehicle control (ethanol) or 20
μmol/l RTV and expression of Adipoq mRNA was measured on day 5 relative to Hprt housekeeping
gene by RT-PCR. Results represent mean ± SEM of quadruplicate cell cultures. *Significantly different
(P < 0.05) from control cells.
Figure 4 Retn mRNA transcription. Adipocytes were treated with vehicle control (ethanol) or 20 μmol/l RTV
and expression of Retn mRNA was measured on day 5 relative to Hprt housekeeping gene by RT-PCR. Results
represent mean ± SEM of quadruplicate cell cultures.
Control RTV0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
Resistin mRNA expression
Treatments
Fold
tran
scri
ptio
n re
lativ
e to
con
trol
, Hpr
t
Control RTV0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5PPAR-γ nuclear binding
Treatments
PPR
E b
indi
ng (O
D 4
50 n
m)
*
Figure 5 PPAR-γ nuclear binding. Nuclear proteins were extracted on day 5 from adipocytes treated
with vehicle control or 20 μmol/l RTV and nuclear PPAR-γ consensus site binding was measured.
Results represent mean ± SEM of quadruplicate cell cultures. *Significantly different (P < 0.05) from
control cells.
Control RTV0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
Adiponectin protein secretion
Treatments
Adi
pone
ctin
con
cent
ratio
n (n
g/m
l)
*
Figure 6 Adiponectin protein secretion. Adipocytes were treated with vehicle control or 20 μmol/l
RTV. Supernatants were collected from adipocytes on day 5 and used to quantify adiponectin secretion.
Results represent mean ± SEM of quadruplicate cell cultures. *Significantly different (P < 0.05) from
control cells.
Control RTV0
0.2
0.4
0.6
0.8
1
1.2Triglyceride accumulation
Treatment
Rel
ativ
e tr
igly
ceri
de a
ccum
ulat
ion
*
Figure 7 Effect of RTV on TG accumulation. Adipocytes were treated with vehicle control or 20
μmol/l RTV and stained at day 5 with ORO to quantify lipid content, which was measured
spectrophotometrically at 540 nm. Results represent mean ± SEM of quadruplicate cell cultures.
*Significantly different (P < 0.05) from control cells.
A
B
Figure 8 Oil Red O stained adipocytes. Adipocytes were treated with (A) vehicle control or (B) 20
μmol/l RTV and stained at day 5 with ORO to visualise lipid content. Black arrows indicate cells with
lipid droplets and lipid vesicles (magnification is at 40x).
50 µm
50 µm
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