Microarray analysis of human vascular smooth muscle cell responses to bacterial lipopolysaccharide.

Microarray analysis of human vascular smooth muscle cell responses to bacterial lipopolysaccharide.

Article Type:	Report
Subject:	Vascular smooth muscle (Health aspects) Microbial polysaccharides (Health aspects) DNA microarrays (Research) Polymerase chain reaction (Methods) Atherosclerosis (Research) Muscle cells (Health aspects) RNA (Health aspects)
Authors:	Minta, Joe James Yun, J. Der, Sandy Rana, Shikha
Pub Date:	04/01/2007
Publication:	Name: American Journal of Immunology Publisher: Science Publications Audience: Professional Format: Magazine/Journal Subject: Biological sciences Copyright: COPYRIGHT 2007 Science Publications ISSN: 1553-619X
Issue:	Date: April, 2007 Source Volume: 3 Source Issue: 2
Topic:	Event Code: 310 Science & research
Geographic:	Geographic Scope: Canada Geographic Code: 1CANA Canada

Accession Number:	182406510
Full Text:	Abstract: Accumulating evidence suggest a causal role of bacterial and viral infections in atherogenesis. Bacterial lipopolysaccharide (LPS) has been shown to stimulate resting vascular smooth muscle cells (SMC) with the production of inflammatory cytokines and modulation of quiescent cells to the proliferative and synthetic phenotype. To comprehensively identify biologically important genes associated with LPS-induced SMC phenotype modulation, we compared the transcriptomes of quiescent human coronary artery SMC and cells treated with LPS for 4 and 22 h. The SMCs responded robustly to LPS treatment by the differential regulation of several genes involved in chromatin remodeling, transcription regulation, translation, signal transduction, metabolism, host defense, cell proliferation, apoptosis, matrix formation, adhesion and motility and suggest that the induction of clusters of genes involved in cell proliferation, migration and ECM production may be the main force that drives the LPS-induced phenotypic modulation of SMC rather than the differential expression of a single gene or a few genes. An interesting observation was the early and dramatic induction of four tightly clustered interferon-induced genes with tetratricopeptide repeats (IFIT1, 2, 4, 5). siRNA knock-down of IFIT1 in SMC was found to be associated with a remarkable up-regulation of TP53, CDKN1A and FOS, suggesting that IFIT1 may play a role in cell proliferation. Our data provide a comprehensive list of genes involved in LPS biology and underscore the important role of LPS in SMC activation and phenotype modulation which is a pivotal event in the onset of atherogenesis. Key words: Vascular smooth muscle cells, lipopolysaccharide, transcriptome, microarray, quantitative PCR, siRNA, IFIT1 INTRODUCTION Atherosclerosis is a complex, chronic inflammatory disease of the arterial vessel wall manifested at predilected locations of the vasculature [1]. It is initiated by multiple local and systemic risk factors (including mechanical shear stress due to hemodynamic changes, hypercholesterolemia, hypertension, high plasma levels of inflammatory markers, etc.) which induce endothelial dysfunction and vascular injury [1]. The disease is characterized by complex interactions between a variety of lipids, mononuclear phagocytes and their soluble mediators in the intima and by intimal hyperplasia. The accumulation of excess cholesterol and cholesteryl esters by macrophages at these sites results in the formation of foam cells that are the hallmarks of early fatty streak lesions and atheroma development [1,2]. Accumulating evidence suggests that chronic viral or bacterial infections, particularly infections with the ubiquitous gram-negative respiratory pathogen, Chlamydia pneumoniae, may be an additional risk factor that may initiate and/or promote atherosclerosis. Patients with acute myocardial infarction and coronary artery disease have been reported to have significantly higher titers of antibodies against C. pneumoniae compared to healthy controls and C. pneumoniae has been localized to the intima of vascular smooth muscle cells (SMCs) in many atherosclerotic lesions [3,4]. C. pneumoniae has been shown to infect and multiply within macrophages, endothelial cells and SMCs [3] and C. pneumoniae and Chlamydial lipopolysaccharide (LPS) have been reported to induce the release of inflammatory cytokines from mononuclear cells, endothelial cells and SMCs [5,6] and to stimulate oxidation of low-density lipoprotein and formation of macrophage foam cells [7,8]. Failure of coronary artery bridge grafts or restenosis has been associated with chronic inflammation induced by LPS [9,10]. Systemic inflammatory responses induced by LPS have been shown to increase neointimal formation after ballon injury and stent implantation and the induced proliferation of SMCs may play a key role in atherogenesis [11]. LPS is a complex glycolipid component of the gram-negative bacterial cell wall composed of a hydrophilic polysaccharide and a hydrophobic Lipid A moiety [12]. The interaction of serum LPS-binding protein (LBP) with LPS facilitates the binding of the lipid A moiety to CD14, a 55 kDa glycoprotein present as a soluble factor (sCD14) or as a glycosylphosphatidylinositol (GPI)-anchored membrane protein [13,14,15]. This complex, which also contains MD-2, interacts with Toll-like receptor 4 (TLR4) which mediates the cellular activation by LPS. TLR4 signaling induces the activation of NFkB and MAPK pathways and proliferation of SMCs [16,17,18,19,20,21]. Recently, Engelmann et al. [22,23] have reported that repeated perivascular administration of LPS or inoculation of Chlamydophila pneumoniae into rabbits induce formation of atheromatous lesions in vivo. The ability of VSMCs in the media of arteries to undergo phenotype modulation from the quiescent and contractile state to the proliferative, migratory and synthetic phenotype that elaborates extracellular matrix underlies their crucial role in the development and progression of vascular pathology such as atherosclerosis and restenosis. Phenotype modulation involves a cascade of events in which different genes are turned on or off in a regulated manner. Thus to gain further insight into the molecular events associated with LPS-mediated activation of SMCs, we have analyzed the transcriptomes of quiescent and LPS-treated human coronary artery SMCs using oligonucleotide microarray analysis. Our results show that the transcriptional effects of LPS on SMCs were particularly far-reaching and many genes that are involved in various biological mechanisms such as chromatin remodeling, transcriptional regulation, translation, signal transduction, metabolism, innate and adaptive immune responses, cell proliferation, apoptosis, matrix formation, cell adhesion and motility, were regulated in a coordinated fashion. The LPS effect appeared to be mediated via the transcriptional induction of proinflammatory cytokines and growth factors and these in turn initiated multiple signal transduction pathways that induced transcriptional activation of genes that are effectors of cell proliferation, migration and extracellular matrix formation. The data presented is thus in agreement with accumulating evidence that LPS may be a risk factor that initiates and/or promotes atherosclerosis. MATERIALS AND METHODS Smooth muscle cell culture and reagents: Human coronary artery SMCs (Clonetics, Walkersville, MD) were cultured in SMC basal medium (SmBM) containing SmBM-3 growth supplements [FBS (5%), bovine insulin (50 ng [mL.sup.-1]), human recombinant (hr)-EGF (5.0 ng [mL.sup.-1]), hr-FGF-B (20 ng [m.sup.L-1]) and GA-1000 (Gentamicin, Amphotericin B)] supplied by BioWhittaker Inc. Walkersville, MD. SMCs were characterized by their typical hill and valley growth pattern, by staining with anti-SM-[alpha]-actin antibody (Dako Diagnostics) and by the lack of staining of Factor VIII related antigen, an endothelial cell marker, using anti-factor VIII antibody (Dako Diagnostics). SMCs at passage 4 were seeded in growth supplemented SmBM-3 medium for 24 h and the medium was replaced with basal mediun containing 0.5% FBS for 48 h to induce quiescence before treated with LPS (E. coli 055.B5, Sigma/Aldrich, St. Louis, MO). Human AB serum was purchased from Sigma/Aldrich, St. Louis, MO. For siRNA experiments, human aorta SMCs (ATCC, Manassas, VA) were cultured in growth supplemented F12K medium according to the instructions of the supplier. RNA isolation and gene expression profiling: Total RNA was extracted from cells using TRIzol reagent (Invitrogen Life Technologies, Inc. Burlington, ON) and contaminating chromosomal DNA was removed using Rnasefree DNase Message Clean Kit (GenHunter Corp., Nashville, TN). The integrity of RNA preparations was assured by comparing the intensities of 28 S and 18 S rRNA bands on 1% formamidealdehyde agarose gel. mRNA was isolated from the total RNA using Oligotex according to the manufacturer's instructions (Qiagen Inc., Mississauga, ON). Biotinylated complementary RNA (cRNA) samples for chip hybridization were prepared according to protocols supplied by Affymetrix (Affymetrix, Santa Clara, CA) and then hybridized to HG-U133A oligonucleotide array Gene Chip (Affymetrix, Santa Clara, CA) following the manufacturer's protocol. The arrays were washed, stained with streptavidin-phycoerythrin and scanned. Data files were analyzed using Affymetrix GeneChip[R] Operating Software (GCOS) version 1.0 (Affymetrix, Santa Clara, CA). Gene cluster analysis: Gene expression pattern analysis was performed using GENESIS ver. 1.3.0. Raw expression values of differentially regulated genes (above signal log ratio of 1.0) from microarray analysis were adjusted with log 2 transform data and 'median centre genes, and clustered I nto 40 groups using k-mean clustering according to the method of Eisen et al. [24] Groups with similar gene expression pattern were combined together to generate three gene expression patterns: up-regulated at both 4 and 22 h, upregulated only at 4 h and down-regulated only at 4 h. Quantitative real-time PCR: Quantitative real-time PCR was performed with an ABI Prism 7900HT Sequence Analyzer using the manufacturer's recommended protocol (Perkin-Elmer Applied Biosystems, Foster City, CA) to validate differential expression of selected genes. Two different primer sets were designed for each investigated gene using Primer Express version 2.0 (Perkin-Elmer Applied Biosystems, Foster City, CA). Each reactions was run in triplicates in 10 [micro]L volumes containing 4 [micro]L of diluted first strand cDNA template, 5 [micro]L of SYBR Green PCR Master Mix, 0.1 [micro]L (50 [micro]M) of each forward and reverse primers and 0.8 [micrp]L [H.sub.2]O. Samples were incubated at 95 [degrees]C for 3 min to activate Taq polymerase and 40 cycles were performed at 95 [degrees]C for 10 sec, at 65 [degrees]C for 15 sec and at 70 oC for 20 sec. A standard curve of each primer set was generated using human tonsil genomic DNA [25]. Sequences for the primers used in this study are available on request. siRNA preparation and transfection: Cell cultures at 60-80% confluence were transfected with custom designed and synthesized IFIT1-specific siRNA primers (Sense: GGC UGU CCG UUU AAA UCC A; Antisense: UGG AUU UAA GCG GAC AGC C) using RNAi Human/Mouse Control Kit and instructions supplied by Qiagen. siRNA (30 [micro]L of 20 [micro]M solution), RNAiFect (22.5 [micro]L) and buffer EC-R buffer (70 [micro]L) were mixed together and incubated for 15 min at room temperature to allow formation of tranfection complexes. The complexes were then added drop-wise onto the cells in the fresh medium. A scrambled nonsilencing siRNA that has no known homology with mammalian genes was used to control for non-specific silencing effects. RT-PCR: RT-PCR was performed using the Superscript first strand synthesis system (Invitrogen), Hotstart Taq Master Mix Kit (Qiagen) and gene specific primers designed from published cDNA sequences. IFIT1 forward primer (5'TCAGAATTCGGATCCATGAGTGAAATTCGTA AG3') and reverse primer (5'CAAGCTTGCCTGCAGTTAAATGGAAAGTCGC AG 3') amplifies a 1.5 kb cDNA fragment. GAPDH forward primer (5'CCACCCAGAAGACTGTGGAT3') and reverse primer (5'CCCCTCTTCAAGGGGTCTAC3') amplifies a 600 bp cDNA fragment. PCR amplification was initiated with a hot start at 95[degrees]C for 15 min followed by 35 cycles of denaturation at 94[degrees]C for 3 min, annealing at 56 [degrees]C for 1 min and extension at 72[degrees]C for 3 min and ended with an extension phase at 72 [degrees]C for 10 min. PCR products were collected and analyzed by electrophoresis on 1% agarose gel to determine the levels of IFIT1 and GAPDH. RESULTS AND DISCUSSION Effect of LPS on the proliferation of SMC: In order to access the effect of LPS on SMC proliferation, quiescent SMCs in microtiter plates were stimulated with LPS (100 ng [mL.sup.-1]) in the presence of 0.5% FBS or 5% AB serum as source of sCD14 [26]. The culture media were replaced at day 2 and the cells were detached at day 5 and counted. The mean and standard error of the mean were determined for three experiments, each performed in quadruplicates. LPS stimulated SMC proliferation as determined by the increase in cell number over a 5 day culture period Fig. 1. The increase in cell number in cultures containing 0.5% FBS or 5% AB serum, were comparable. In the presence of 0.5% FBS and 100 ng [mL.sup.-1] LPS, SMC proliferation was increased 2.4 fold relative to cells in basal medium containing 0.5% FBS alone and SMC proliferation in medium containing 5% AB serum and 100 ng [mL.sup.-1] LPS was 5.1 fold greater than in the presence of AB serum alone. Our results on the mitogenic effect of LPS on SMCs is in agreement with earlier reports [27, 28]. Microarray analysis of differential gene expression in LPS-treated SMCs: Confluent SMCs cultures were synchronized to quiescence by incubation for 48 h in SmBM+0.5% FBS. To obtain a global profile of the transcriptional changes induced by LPS, we examined the gene expression responses of human coronary artery SMCs stimulated with 5% AB serum alone or AB serum containing LPS (100 ng [mL.sup.-1]) for 4 and 22 h using Affymetrix oligonucleotide arrays (HGU133A). Of the 18,400 transcripts (14,500 well-characterized genes) present on the chips, 1015 and 3749 genes (including ests and redundant gene probes) were found to be differentially regulated by LPS at 4 and 22 h, respectively. 469 genes were induced and 546 were suppressed at 4 h and 2526 were induced and 1223 were suppressed at 22 h. [FIGURE 1 OMITTED] Quantitative real-time pcr validation of results of gene array analysis: To validate the gene array results, the expression of 13 regulated genes was analyzed using reverse transcription followed by quantitative real-time PCR. The expression levels of human GAPDH and beta-2-microglobulin were used as internal housekeeping gene controls to normalize technical variability between samples. The expression of 9 genes was shown to correlate well in microarray and real-time PCR whereas the magnitudes of differential expression were somewhat different for 4 genes (data now shown). Overall, the real-time PCR data was more sensitive than the microarray data. Scatter plot analysis: Scatter plots of log-transformed expression values from microarray analysis for pairwise comparisons of AB serum+LPS treated SMCs (ordinate) versus the control cells treated with AB serum alone (abscissa) for 4 and 22 h were used to display the regulated genes (Fig. 2). The data points along the diagonal represent genes expressed at comparable levels in both sets whereas those that lie off the diagonal represent genes differentially expressed between the samples identified by the two axes. The data indicate that the number of regulated genes increased with time. Also, whereas the number of induced and repressed genes at 4 h was comparable, the number of induced genes at 22 h was much greater than that of the suppressed genes. The plots confirmed that LPS induced and suppressed a greater numbers of genes at 22 h compared to 4 h (Fig. 2A and B). Scatter plot analysis of SMC treated with AB serum for 4 and 22 h shows that AB serum induces regulation of genes (Fig. 2C). This effect was more pronounced at 4 h and appeared to subside by 22 h. Comparison of the scatter plots of SMC treated with AB+LPS for 4 and 22 h showed that the magnitude of expression appeared to be similar for most genes. This suggests that the robust induction of genes in LPS 22 h compared to AB 22 h may be due to the prolonged and sustained activation of genes by LPS which compensates for the diminished AB serum effect at 22 h (Fig. 2D). Profile of down-regulated genes: Since it is possible that the SMC genes that were down-regulated by LPS may be implicated in the maintenance of the quiescent phenotype, we have displayed in Tables 1A and 1B the induction and functional profiles of the top 10 SMC genes down-regulated by LPS treatment at 4 and 22 h. Two transcripts with the greatest fold decrease in expression in 4 h were albumin and cannabinoid receptor 1 (CNR1). Albumin is the serum carrier protein that plays an important role in stabilizing extracellular fluid volume and is known to be down-regulated during acute inflammation. CNR1 is a G-coupled receptor in brain and some peripheral tissues that recognize plant derived cannabinoids (marijuana) as well as endogenous lipid-like mediators (such as arachidonyl ethanolamide [anandamide] and 2-arachidonyl glycerol) that are potent modulators of neurobehavioral functions [29]. CNR1 and its endogenous ligands have role in regulating cerebral arterial tone and reactivity by modulating influx of calcium through Ltype calcium channels. Todate, the role of CNRs in SMC phenotype modulation is unknown. Among the down-regulated genes were two prostanoid receptors, PTGDR and PTGER4, a transcription-related gene (HCAP-G), two structural-related genes (D2LIC, PPFIA3), a chloride transporter (CLCN3) and negative regulators of cell proliferation and apoptosis (GW112 [30], INHBE [31]). [FIGURE 2 OMITTED] The expression of the top 10 down-regulated genes at 4 h had returned to near normal levels at 22 h and thus the profile of the genes repressed at 22 h was different from the genes repressed at 4 h (Table 1). Three of the top 10 genes that were most highly down-regulated in 22 h were signal transduction-related genes (KRAS2, PAK1IP1, SH3BP2). This group also contained genes involved in various functions such as transcription repression (HDAC4), ribosome macromolecular assembly (RPS10), cytochrome c oxidase respiratory chain complex (COX5), glycine metabolism (GCSH), actin polymerization and cell adhesion to extracellular matrix (ITGB5) and two hypothetical genes (C6orf79, KIAA0507). Profile of up-regulated genes: SMC genes upregulated by LPS treatment may be associated with antibacterial or anti-viral activity and inflammation and/or the induction of the proliferative, migratory and synthetic phenotype. The top 10 up-regulated genes in SMC treated with LPS for 4 h were mostly LPS-, interferon-, TNF- or IL1-inducible proinflammatory and antiviral genes that participate in host defense (Table 2). The level of expression of many of the genes up-regulated at 4 h was found to have subsided by 22 h. The gene that was most highly up-regulated in 4 h LPS-stimulated SMCs was IFIT1. It has been suggested that IFIT1 is an anti-viral protein; however, its exact mechanism of action is at present unclear [32]. IFIT1 has recently been reported to bind to Rho guanine nucleotide exchange factor 10 [33] and also to block the interaction between eukaryotic translation initiation factors, eIF2 and eIF3 and thereby regulate translation initiation and protein synthesis [34]. IFIT4 which is a member of IFIT1 family of closely linked genes was also highly up-regulated [35]. Other genes encoding antiviral proteins that were highly induced in 4 h include MX1, cig5 and MDA5. Pro-inflammatory cytokines and chemokines known to be induced in response to bacterial and viral infections (CCL3, CCL20) were upregulated in 4 h LPS-stimulated SMCs. Some of the cytokine up-regulated genes may not be directly involved in defense response and these include USP18 (deubiquitinating protease)[36] and SAMHD1 (implicated in shifting dendritic cells from antigen uptake and processing phenotype to the antigen presentation phenotype)[37]. Two cytokine inducible genes of unknown functions (IFIT4, IFI44) were also upregulated at 4 h. The overall profile of the top 10 genes regulated in 4 h LPS-stimulated SMC is reminiscent of the induction of acute inflammation and a proliferative response. In contrast with the profile of the genes induced by LPS in 4 h, most of the genes up-regulated in 22 h were probably not the direct result of cytokine activity but rather the effects of induction or activation of transcription factors. The top 10 over-expressed genes were predominantly involved in transcriptional activation, extracellular matrix formation and cell proliferation. LOXL2, a copper-dependent enzyme that initiates cross-linking of collagens and elastin [38], had the greatest expression among the top 10 highly up-regulated genes in 22 h LPS-treated SMCs (Table 2). Recently a direct link has been established between LOXL2 and SNAIL, a transcription factor that represses E-cadherin expression, in inducing epithelial-mesenchymal cell transitions and carcinoma progression [39]. Thus there is a possibility that the up-regulated expression of LOXL2 in LPS treated SMC may be associated with the induction of the proliferative response. Several genes involved in extracellular matrix formation (COL6A2, EMILIN1, PLEC1) were also highly up-regulated. The other genes in the 22 h top 10 up-regulated category include genes involved in transcription regulation or chromatin modification (POLR2E, MAZ, BTBD2), IFN-inducible genes (IFI27), tetracyclin transporter-like protein (TETRAN) and the hypothetical C1orf29 gene. Functional characterization of the LPS regulated genes: In order to discover the classes of genes that were involved in LPS-mediated SMC activation, we applied a signal log ratio cut-off of > [+ or -] 1.0, eliminated all redundant probes that had less significant statistical values for each gene and categorized the remaining 1541 differentially regulated genes into functional groups/subgroups based on gene annotation information from Affymetrix database. Genes of unknown or miscellaneous functions were grouped together as Others. As shown in Figure 3, differential expression of genes belonging to functional categories such as transcription and chromatin remodeling, translation, signal transduction, host defense, proliferation, apoptosis, metabolism, ubiquitination, transporters and structural proteins indicates a robust SMC response to LPS treatment. The complete tables of the functional categories of LPS regulated SMC genes are available on request Table 3. A detailed discussion of all regulated genes is beyond the scope of this report and instead we focus on the specific sets of genes that are involved in host defense, transcription and chromatin remodeling, signal transduction, proliferation, apoptosis and cytoskeleton and matrix formation which we believe drive SMC phenotype modulation. Host defense: Treatment of SMC with LPS induced the expression of several ligands and receptors of C-C and C-X-C chemokines and interleukins. Although the changes in the expression of various interferon subtypes were not deemed significant when analyzed using GCOS version 1.0, several interferon-inducible genes (IFIT1, IFIT2, IFIT4, IFI27, STIP1, G1P2, G1P3, IFI44, IFI35, OAS1-3, MX1), granulocyte colony stimulating factor 3 (CSF3), neutrophil chemokines, IL8, CCL20, CCL3, CXCL3, CXCL10 and MIF were highly expressed. Other inflammatory and immune-related genes such as the toll-interacting protein (TOLLIP) [40] and antiviral proteins (OAS1, 2, 3) were more up-regulated at 22 h compared to 4 h. Serine proteinase inhibitor (SERPINB2) was induced possibly to protect the SMCs from excessive inflammation. Taken together, the results suggest that LPS induces SMCs to express inflammatory cytokines, chemokines and cell surface receptors that could induce chemotactic attraction of hematopoietic cells, neutrophils and mononuclear cells which contribute to inflammatory and immune responses. This is consistent with the well known function of LPS as a potent activator of inflammation and immune response. Transcription and chromatin remodeling: LPS regulated the expression of many transcription factors and molecules involved in chromatin remodeling. The most highly up-regulated transcription-related gene was RNA polymerase II polypeptide E (POLR2E), a component of the multisubunit eukaryotic DNA-dependent RNA polymerase II complex [41]. Several other components of the POLR2 holoenzyme were up-regulated. These include DNA polymerases (PDIP46, POLD4), core promoter binding proteins (COPEB, TAF13), initiator binding protein (GTF2I) and transcription complex subunit 3 (CNOT3). Parathymosin (PTMS) and chromodomain helicase DNA binding proteins (CHD1L) and several nucleosomal histones (H1FX, HIST1H4H, HISTH2BE, HIST2H2AA) were highly up-regulated in LPS-treated cells. Particularly PTMS affects the interaction of linker histone H1 which is the major factor that stabilizes higher order chromatin structure with nucleosomes and thereby modulates the action of chromatin-remodeling enzymes [42]. Zinc finger protein transcriptional regulators (NAKAP95 and MAZ) and members of NFkB family (NFKB2, RELA) were induced at 22 h. IRF7 (a regulatory factor of viral/interferon inducible genes) and a member of the STAT family of transcription activators (STAT 6) were induced at 22 h. These results are in agreement with previous reports of activation of the JAK-STAT signaling pathway in LPS treated cells. The above compendium of LPS-mediated differential expression of several chromatin remodeling genes and transcription regulators have profound effects on gene expression in LPS treated SMCs and subsequently on inflammation, proliferation, apoptosis, ECM production, cell adhesion and cell migration responses and the modulation of the quiescent cells to the activated SMC phenotype. Signal transduction: Several genes involved in a variety of signal transduction pathways were up-regulated in SMCs following treatment with LPS for 22 h. The Ras/Rho/CDC42 signaling pathway was activated as judged by the increase in the expression of genes encoding Rho guanine nucleotide exchange factors and dissociation inhibitors (ARHGEF16, ARHGDIA), G-protein coupled receptors (GPR, GPR51, GPR161, MUC20) and GTP-binding proteins of the Ras superfamily (GNB2, GPS1, DRG2, RABAC1, RAB3GAP, RAC2). Plexin B1 (PLXNB1) was the second highest induced gene in this category. PLXNB1 has been reported to mediate Sema4D-induced repulsive axon guidance signaling by acting as a GTPase activating protein for R-Ras, a member of the Ras superfamily of small GTP-binding proteins, which plays a key role in cell adhesion by activating integrins and promoting cell migration and neurite outgrowth [43, 44]. The transforming growth factor signaling pathway was recruited as judged by the induction of TGFB1, TGFBR2, LTBP3 and BMPR2. Binding of TGFB or BMPs to cognate type II receptors leads to the phosphorylation of the type I subunit by the constitutively active serine-threonine kinase type II receptor. Phosphorylated receptor I is an active kinase that subsequently phosphorylates and propagates intracellular downstream signals, including Smad proteins and mitogen-activated protein kinases [45, 46]. By the regulation of TGF inducible genes, the TGFB signaling pathway may mediate regulatory effects on a multitude of cellular processes in the LPS-treated SMCs including proliferation, differentiation, migration and extracellular matrix accumulation [47]. LPS also stimulated the expression of several transcriptional activators. The NF-kB subunits NFKB2 (p49/p100) and RELA (p65) as well as a putative NFkB activating protein (FLJ20241) and an inhibitor of inducible I-kappa B-kinase epsilon (IKBKE) were up-regulated and their activation suggests NFkB pathway signaling [48]. The MAPK pathway was activated in LPS-treated SMCs as judged by the increased expression of MAPK enzymes [48] (MAP2K2, MAPKAPK2). The phosphatidylinositol-3-kinase (PI3K) signaling pathway was also activated as judged by the increased expression of PIK4CB and protein kinase isotypes (PRKCD, PRKCL2). Proliferation: Several growth factor genes (including VEGF, NRG1, NGFB) and growth factor receptor genes (e.g. FGFR1, MET, PDAP1) were induced by LPS at 22 h. In mammals, the progression through the cell cycle is regulated by the association of cyclins and their cyclin-dependent kinase (CDK) partners. Activity of these cyclin/cyclin-dependent kinase complexes is inhibited by the action of cyclin-dependent kinase inhibitors (CDKIs) that bind to these complexes and thereby inhibit progression through the restriction points of the cell cycle and cellular proliferation. Treatment of SMCs with LPS for 22 h resulted in up-regulation of several cell cycle-dependent genes (CCNL2, CDC2L2, CDC37, CDK5, CDK10), cell cycle regulatory genes (BUB1, human DOC-1R, NF2, FZR1, WISP1) and regulators of proliferation (MAD1L1, TMPO, CAPNS1, ANAPC5, NOTCH2). In contrast, negative regulators of growth such as cell cycle arrest genes including HCAP-G (mitosis-related chromosome condensation protein G), MAD1L1 (a G1 to S cell cycle checkpoint protein) and several cyclin-dependent kinase inhibitors (CKS2, p27, p21, p18, p16) were repressed at 4 h. These results are consistent with the pro-proliferative effect of LPS on SMCs. Apoptosis: Six anti-apoptotic genes (BIRC3, RIG-I, BCL2A1, TNFAIP2, TNFSF7, TNFSF10) and 3 proapoptotic genes (HSXIAPAF1, MDA5, TARSH) were up-regulated within 4 h of LPS treatment whereas GW112 were repressed at 4 h. Pro-apoptotic genes such as BAX, RIPK1, TP53I11, BAD, DAPK3, PRF1, MCL1, SH3GLB2, SNCA and TNFRSF10D were induced at 22 h and HSXIAPAF1 was induced at both 4 and 22 h. Structural proteins: The changes in expression levels of structural genes occurred predominantly at 22 h. Among the up-regulated genes, extracellular matrix collagen 6A2, 6A1, 1A1 and 4A2 were greatly increased. The different types of collagens i) may be associated with laminin, entactin and heparan sulfate proteoglycans to form the sheet-like basement membranes that separate epithelium from connective tissue or ii) may be components of microfibrillar structures in many tissues that localize close to cells where they may provide an anchoring function and may be involved in cell migration, differentiation and embryonic development. Several non-collagenous ECM components were also up-regulated. LOXL2, a copper-dependent enzyme that initiates cross-linking of collagens and elastin, was among the highly up-regulated structural genes in 22 h LPS-treated SMCs (Table 1B). Genes encoding microfibril associated proteins (EMILIN1, THBS3) and heparin sulfate proteoglycans of basement membranes (HSPG2, BGN, SDC1, SDC4) were also up-regulated at 22 h. These proteins may play a role in cell adhesion, cell morphology, intracellular communication and anchorage of SMC to elastic lamellae. The expression of several genes encoding cytoplasmic cytoskeletal proteins involved in actin reorganization (PLEC1, TUBB, GSN, NF2, VIL2, FLNA, ARPC4, TAGLN2, MYO1B, NRP2, TMOD3) were up-regulated after 22 h of LPS stimulation. These cytoskeletal proteins are central to the modulation of cell shape, adhesion, migration and the organization of cell surface structures. Cell adhesion is an essential requirement for cell migration and morphogenesis during development. Genes encoding integral membrane proteins localized at focal adhesions and cell-cell junctions, such as VIL2, ASTN2, CLDN1, CLDN11, ITGB3, SCAM-1, ZYX, PCDHGC3, THY1, CD151, ICAM1 were up-regulated at 22 h in LPS stimulated SMCs. These proteins regulate a variety of cellular events, including cell adhesion, spreading and migration, cell proliferation and differentiation and anchorage dependence of signal transduction that may lead to cell proliferation, migration or transformation and metastasis [49,50,51]. Secretory metalloproteinases (such as MMP14, ADAM17) which are Zn(2+)-binding endopeptidases that degrade various components of the extracellular matrix such as collagens, pro-collagens and hyaluronan binding proteoglycans and probably facilitate SMC migration were over-expressed in LPS stimulated SMC. Studies using the candidate gene approach has shown that bacterial lipopolysaccharide induces differential induction of the expression of several VSMC genes that encode cytokines (IL-1 [52], IL-6 [53], TNF-alpha [54], IFN [55]), chemokines (MCP-1 [56], IP-10 [57], IL-8, MIP-2 [58]), enzymes involved in prostanoid synthesis (PLA2 [59], COX-2 [60]), adhesion molecules (VCAM-1 [61], E-selectin [62], ICAM-1 [63]), LPS-binding proteins (LBP [64], CD14 [65], TLR4 [17]), human antigen [R.sup.16] (an RNA-binding protein involved in LPS cell activation effects), adrenomedullin [66], heme oxygenase-1 [67], low-density lipoprotein receptor-1 (LOX-1) [68], complement components and regulators (C3, C4, DAF, MCP, CD59 [69]), iNOS [70] and NO production [71], endothelin-receptor A and B [72], antiviral cytomegalovirus inducible gene 5 (viperin) [73], tissue factor and urokinase-type plasminogen activator (u-PA) [74]. LPS has also been shown to mediate some of its effects by the regulation of cytokines [55], activation of NADPH oxidase [17] and MAPK [17,75] and NFKB [70] signaling pathways. The data reported in this study is in agreement with most of these findings and also provides a comprehensive list of genes that have thus far not been implicated in LPS biology. Clustering analysis of genes displaying similar expression: Differentially regulated genes were grouped according to their expression patterns following treatment with AB (4 h), AB+LPS (4 h), AB (22 h) and AB+LPS (22 h) to determine if a correlation exists between gene function and expression pattern in response to LPS stimulation. Gene expression pattern analysis was performed using GENESIS ver. 1.3.0. Raw expression values of all differentially regulated genes (above signal log ratio of 1.0) from microarray analysis were adjusted with 'log 2 transform data' and 'median centre genes' and clustered into 40 groups using k-mean clustering. We focused on regulation at 4 h because we reasoned that this early time period may better represent direct signaling effect of LPS on gene transcription. Clusters with similar gene expression pattern were combined together to generate 3 groups: up-regulated at both 4 and 22 h, up-regulated at 4 h and down-regulated at 4 h. Detailed results of clustering analysis are available on request. The majority of 83 genes up-regulated at both 4 and 22 h are IFN- or TNF-inducible genes (IFI-15K, IFIT1, IFN p78, IFNAI27, IFNR2, ISTF3, IFNIP44, IFIT4, OAS1-3, IRF7, TNFSF7, 10, TNFAIP2, etc.) or cytokine/chemokine genes (CCL3, CXCL3, CSF3, CXCL10, CCL8, IL8, etc.) associated with the inflammatory response. This observation re-emphasizes the important role of LPS in the regulation of SMC activation and phenotype modulation and the initiation and/or augmentation of inflammation in cardiovascular diseases. Fourteen out of 41 genes in the 4 h up-regulated group belong to a subgroup containing growth factors (FGF2, BMP2, LIM), cytokines (IL-1b, IL-15) and cytokine-induced genes (IFIT5, VCAM1, TNFAIP6, IKKa, CC2, CC7, CXC11, OASL, SOD2). The 4 h down-regulated gene group (116 genes) contained genes that mediate diverse biological functions such as chromosomal modification, signal transduction, growth and differentiation, metabolism, translation, and nuclear transport. siRNA knockdown of IFIT1: Since IFIT1 was an early response gene that was most dramatically induced by LPS, we hypothesized that it may have an important role in the early events of the activation and proliferation of SMCs. Thus to gain insight into the biological significance of IFIT1 in LPS-induced SMCs, we knocked down IFIT1 transcripts using small interference RNA and then compared the expression of candidate genes in knock-down cells with wild type cells using real-time PCR. Human aortic SMCs (T/G HA-VSMC) were transfected with scrambled siRNA or IFIT1 siRNA as described and IFIT1 expression was assessed using semi-quantitative RT-PCR. Aliquots of the amplification mixtures were collected after 25, 30 and 35 cycles and analyzed by 1% agarose gel electrophoresis. IFIT1 expression was almost completely suppressed by siRNA relative to scrambled siRNA control (data not shown). To gain further insight into the biological functions of IFIT1, the effect of IFIT1 knock-down on the expression of 14 different candidate genes such as IFIT1, IFIT4, FOS, B2M, cytokines (TNF, TGF[beta]), adhesion molecules (ICAM1, VCAM), cell cycle progression/control (CCND1, p53, p15, p16, p21, p27) was analyzed. The expression of each gene in IFIT1 knock-down (KD) SMCs was calculated relative to the expression level in control cells treated with the scrambled siRNA, which was taken as 100%. The expression of IFIT1 in SMC IFIT1 knock-down SMCs was reduced to 8% and interestingly the expression of the closely linked paralogous gene, IFIT4, was also coordinately down-regulated to 35% (Fig. 4A). The expression of TGF[beta], ICAM1, VCAM, p15, p16, p27 and B2M was not significantly affected by IFIT1 KD. While TNF was moderately down-regulated to 65% (Fig. 4A), IFIT1 knock-down resulted in a remarkable up-regulation of FOS (8 fold), TP53 (11 fold), CDKN1A/p21 (866 fold) (Fig. 4B). The human c-fos oncogene heterodimerizes with c-jun to form the immediate-early transcription factor AP-1 that stimulates the transcription of genes containing AP-1 regulatory elements [76]. The tumor suppressor protein, TP53, which is undetectable or present in low levels in resting cells but is generally found in increasing amounts in proliferating non-transformed and transformed cells, is up-regulated in response to stress signals, DNA damage and is transcriptionally induced by IFNA/B through ISGF3 [77]. It has been proposed that TP53 binds as a tetramer to a p53-binding site and activates the transcription of downstream target genes that induce apoptosis or cell cycle arrest and/or invasion [78,79]. The cyclin-dependent kinase inhibitor, CDKN1A/p21, participates in the regulation of the G2 checkpoint of the cell cycle and probably serves as the effector of TP53 cell cycle control [76]. The up-regulation of these genes in IFIT1 knock-down cells suggests that IFIT1 may be implicated in the regulation of the expression of the above genes during SMC proliferation. [FIGURE 4 OMITTED] CONCLUSION In this study, LPS was found to have a profound effect on SMC gene expression profile and the induction of many genes involved in cellular transcription, translation, signal transduction and metabolism indicates the activated state of SMC. This global change in genetic profile may be the main force that drives the LPS-induced phenotypic transition of SMC rather than the differential expression of a single gene or a few genes. The induction of genes involved in cell proliferation, adhesion, motility and matrix formation suggests that LPS mediated SMC transition from the quiescent to proliferative, synthetic and migratory phenotype. Many genes associated with apoptosis, both pro- and anti-, were also differentially regulated by LPS suggesting that the balance in cell survival and death was somehow tilted although the direction is not clear. 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Yun, (1) Sandy Der and (1) Shikha Rana (1) Department of Laboratory Medicine and Pathobiology, Faculty of Medicine (2) Applied Molecular Oncology, Ontario Cancer Institute/University Health Network, Toronto, Ontario, Canada Corresponding Author: Joe Minta, Department of Laboratory Medicine and Pathobiology, 1 King's College Circle, Medical Sciences Building Room 6211, Faculty of Medicine, University of Toronto, Toronto, ON Canada M5S1A8, Tel: 416-946-0316 Table 1: Ten SMC genes highly down-regulated by LPS treatment at 4 h (A) and 22 h (B). (All numbers are expressed as signal log ratio.) Symbol LPS 4h LPS 22h Gene CNR1 -3.5 1.3 cannabinoid receptor 1 (brain) ALB -3.2 0 albumin HCAP-G -3.1 -1.1 chromosome condensation protein G GW112 -3.1 0.1 differentially expressed in hematopoietic lineages PTGDR -2.9 0.1 prostaglandin D2 receptor (DP) CLCN3 -1.8 0.5 chloride channel 3 INHBE -1.7 -0.4 activin beta E D2LIC -1.6 -0.9 dynein 2 light intermediate chain PTGER4 -1.6 -0.6 prostaglandin E receptor 4 (subtype EP4) PPFIA3 -1.4 -1.9 protein tyrosine phosphatase, receptor type, f polypeptide (PTPRF), interacting protein (liprin), alpha 3 KRAS2 -0.2 -3.3 v-Ki-ras2 Kirsten rat sarcoma 2 viral oncogene homolog KIAA0507 0.3 -2.4 Homo sapiens mRNA, chromosome 1 specific transcript KIAA0507. HDAC4 0.3 -2.2 histone deacetylase 4 COMA -0.2 -2.1 cytochrome c oxidase subunit Va PAKIIPI -0.1 -2.1 PAKI interacting protein 1 ITGB5 0.3 -2 integrin, beta 5 SH3BP2 2.1 -2 SH3-domain binding protein 2 GCSH -0.2 -1.9 Homo sapiens transcribed sequence with strong similarity to protein pir:GCHUH (H.sapiens) GCHUH glycine cleavage system protein H precursor--human C6orf79 0.1 -1.9 chromosome 6 open reading frame 79 RPS10 0.3 -1.9 ribosomal protein S10 Table 2. Ten SMC genes highly up-regulated by LPS treatment at 4 h (A) and 22 h (B). (All numbers are expressed as signal log ratio.) Symbol LPS 4h LPS 22h Gene IFITI 7.3 5 interferon-induced protein with tetratricopeptide repeats 1 USP18 4.3 5 ubiquitin specific protease 18 SAMHDI 3.9 3.1 SAM domain and HD domain 1 cig5 3.8 0.9 viperin MX1 3.7 3.8 myxovirus (influenza virus) resistance 1, interferon- inducible protein p78 (mouse) MDA5 3.7 1.9 melanoma differentiation associated protein-5 IFIT4 3.6 1.6 interferon-induced protein with tetratricopeptide repeats 4 CCL3 3.6 1.3 chemokine (C-C motif) ligand 3 CCL20 3.4 4.3 chemokine (C-C motif) ligand 20 IFI44 3.4 2.6 interferon-induced protein 44 LOXL2 0.1 7 lysyl oxidase-like 2 POLR2E 0 6.8 polymerase (RNA)11(DNA directed) polypeptide E, 25kDa CIorf29 3.1 6.2 chromosome 1 open reading frame 29 COL6A2 -0.1 6.1 collagen, type VI, alpha 2 IFI27 2.4 5.7 interferon, alpha-inducible protein 27 TETRAN -0.5 5.7 tetracycline transporter-like protein EMILINI -0.7 5.7 elastin microfibril interfacer 1 MAZ 0.2 5.6 MYC-associated zinc finger protein (purine-binding transcription factor) PLECI -0.4 5.4 plectin 1, intermediate filament binding protein 500kDa BTBD2 0 5.3 BTB (POZ) domain containing 2 Table 3. VSMC genes regulated by LPS treatment at 4 and 22 h. (Gene expressions are shown in signal log ratio.) A. Genes involved in host defense Probe Set ID Gene IFN Inducible 202411_at interferon, alpha-inducible protein 27 203153_at interferon-induced protein with tetratricopeptide repeats 1 212009_s_at stress-induced-phosphoprotein 1 (Hsp70/Hsp90-organizing protein) 205483_s_at interferon, alpha-inducible protein (clone IFI-15K) 202086_at myxovirus (influenza virus) resistance 1, interferon-inducible protein p78 (mouse) 204972_at 2'-5'-oligoadenylate synthetase 2, 69/71kDa 205552_s_at 2',5'-oligoadenylate synthetase 1, 40/46kDa 217502_at interferon-induced protein with tetratricopeptide repeats 2 218400_at 2'-5'-oligoadenylate synthetase 3, 100kDa 204415_at interferon, alpha-inducible protein (clone IFI-6-16) 214453_s_at interferon-induced protein 44 209417_s_at interferon-induced protein 35 204747_at interferon-induced protein with tetratricopeptide repeats 4 Innate Immunity and Inflammation 205476_at chemokine (C-C motif) ligand 20 204614_at serine (or cysteine) proteinase inhibitor, clade B (ovalbumin), member 2 217871_s_at macrophage migration inhibitory factor (glycosylation-inhibiting factor) 217930_s_at toll interacting protein 211506 s at interleukin 8 207442_at colony stimulating factor 3 (granulocyte) 205114_s_at chemokine (C-C motif) ligand 3 204533_at chemokine (C-X-C motif) ligand 10 207850_at chemokine (C-X-C motif) ligand 3 B. Genes involved transcription and chromatin remodeling Chromatin Remodeling 207824_s_at MYC-associated zinc finger protein (purine-binding transcription factor) 218045_x_at parathymosin 218064_s_at neighbor of A-kinase anchoring protein 95 204805_s_at Hl histone family, member X 208180_s_at histone 1, H4h 207645_s_at chromodomain helicase DNA binding protein 1-like 208527_x_at histone 1, H2be 214290_s_at histone 2, H2aa Transcription Regulation 209636_at nuclear factor of kappa light polypeptide gene enhancer in B-cells 2 (p49/p100) 209878_s_at v-rel reticuloendotheliosis viral oncogene homolog A, nuclear factor of kappa light polypeptide gene enhancer in B-cells 3, p65 (avian) 201332_s_at signal transducer and activator of transcription 6, interleukin-4 induced 208436_s_at interferon regulatory factor 7 Basal TF 213887_s_at polymerase (RNA)11(DNA directed) polypeptide E, 25kDa 203239_s_at CCR4-NOT transcription complex, subunit 3 215357_s_at polymerase delta interacting protein 46 202996_at polymerase (DNA-directed), delta 4 208960_s_at core promoter element binding protein 205966_at TAF13 RNA polymerase 11, TATA box binding protein (TBP)-associated factor, 18kDa TAF13 210892_s_at general transcription factor II, i C. Genes involved signal transduction MAPK 213490_s_at mitogen-activated protein kinase kinase 2 215050_x_at mitogen-activated protein kinase-activated protein kinase 2 RAS 209991_x_at G protein-coupled receptor 51 215807_s_at plexin B1 207419_s_at ras-related C3 botulinum toxin substrate 2 (rho family, small GTP binding protein Rac2) 4.4 217782_s_at G protein pathway suppressor 1 203267_s_at developmentally regulated GTP binding protein 2 208009_s_at Rho guanine exchange factor (GEF) 16 201167_x_at Rho GDP dissociation inhibitor (GDI) alpha 206971_at G protein--coupled receptor 161 203136_at Rab acceptor 1 (prenylated) 215249_at mucin 20 212932_at RAB3 GTPase-ACTIVATING PROTEIN 206673_at putative G protein coupled receptor 200852_x_at guanine nucleotide binding protein (G protein), beta polypeptide 2 P13K 210969_at protein kinase C-like 2 202545_at protein kinase C, delta 210417_s_at phosphatidylinositol 4-kinase, catalytic, beta polypeptide NFkB 58994_at putative NFkB activating protein 214398_s_at inhibitor of kappa light polypeptide gene enhancer in B-cells, kinase epsilon TGFB Related 203085_s_at transforming growth factor, beta 1 (Camurati-Engelmann disease) 209920_at bone morphogenetic protein receptor, type 11(serine/threonine kinase) D. Genes involved proliferation Cell Cycle 221427_s_at cyclin L2 204247_s_at cyclin-dependent kinase 5 204857_at MADI mitotic arrest deficient-like 1 (yeast) 211017_s_at neurofibromin 2 (bilateral acoustic neuroma) 209754_s_at thymopoietin 207428_x_at cell division cycle 2-like 2 203252_at tumor suppressor deleted in oral cancer-related 1 209414_at Fzrl protein 210622_x_at cyclin-dependent kinase (CDC2-like) 10 209953_s_at CDC37 cell division cycle 37 homolog (S. cerevisiae) 208721_s_at anaphase promoting complex subunit 5 216277_at BUB1 budding uninhibited by benzimidazoles 1 homolog (yeast) 209112_at cyclin-dependent kinase inhibitor 1B (p27, Kipl) 204170_s_at CDC28 protein kinase regulatory subunit 2 202284_s_at cyclin-dependent kinase inhibitor 1A (p21, CipI) 204159_at cyclin-dependent kinase inhibitor 2C (p18, inhibits CDK4) 207039_at cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) GF and Angiogenesis 219922_s_at latent transforming growth factor beta binding protein 3 207334_s_at transforming growth factor, beta receptor II (70/80kDa) 208231_at neuregulin 1 206796_at WNTI inducible signaling pathway protein 1 206814_at nerve growth factor, beta polypeptide 210513_s_at vascular endothelial growth factor 210973_s_at fibroblast growth factor receptor 1 (fins-related tyrosine kinase 2, Pfeiffer syndrome) 213807_x_at met proto-oncogene (hepatocyte growth factor receptor) 202290_at PDGFA associated protein 1 Differentiation 210756_s_at Notch homolog 2 (Drosophila) Others 200001_at calpain, small subunit 1 218663_at chromosome condensation protein G E. Genes involved in apoptosis Pro-apoptotic 211833_s_at BCL2-associated X protein 214667_s_at tumor protein p53 inducible protein 11 209941_at receptor (TNFRSF)-interacting serine-threonine kinase 1 1861_at BCL2-antagonist of cell death 206133_at XIAP associated factor-1 203890_s_at death-associated protein kinase 3 214617_at perforin 1 (pore forming protein) 219209_at melanoma differentiation associated protein-5 220518_at target of Nesh-SH3 Anti-apoptotic 200796_s_at myeloid cell leukemia sequence 1 (BCL2-related) 210538_s_at baculoviral IAP repeat-containing 3 218813_s_at SH3-domain GRB2-like endophilin B2 211546_x_at synuclein, alpha (non A4 component of amyloid precursor) 218943_s_at DEAD/H (Asp-Glu-Ala-Asp/His) box polypeptide 202510_s_at tumor necrosis factor, alpha-induced protein 2 205681_at BCL2-related protein Al 212768_s_at differentially expressed in hematopoietic lineages TNF Related 210654_at tumor necrosis factor receptor superfamily, member 10d, decoy with truncated death domain 206508_at tumor necrosis factor (ligand) superfamily, member 7 202688_at tumor necrosis factor (ligand) superfamily, member 10 F. Genes involved in structural proteins ECM 202997_s_at lysyl oxidase-like 2 209156_s_at collagen, type VI, alpha 2 204163_at elastin microfibril interfacer 1 217430_x_at collagen, type I, alpha 1 212091_s_at collagen, type VI, alpha 1 211966_t collagen, type IV, alpha 2 201654_s_at heparan sulfate proteoglycan 2 (perlecan) 201262_s_at biglycan 202827_s at matrix metalloproteinase 14 (membrane-inserted) 201286_at syndecan 1 209561_at thrombospondin 3 205746_s_at a disintegrin and metalloproteinase domain 17 (tumor necrosis factor, alpha, converting enzyme) Cytoskeleton 216971_s_at plectin 1, intermediate filament binding protein 500kDa 209372_x_at tubulin, beta polypeptide 214040_s_at gelsolin (amyloidosis, Finnish type) 214752_x_at filamin A, alpha (actin binding protein 280) 217817_at actin related protein 2/3 complex, subunit 4, 20kDa 210978_s_at transgelin 2 215074_at myosin 113 220800_s_at tropomodulin 3 (ubiquitous) Adhesion and Migration 217234_s_at villin 2 (ezrin) 218182_s_at claudin 1 209693_at astrotactin 2 204627_s_at integrin, beta 3 (platelet glycoprotein IIIa, antigen CD61) 207788_s_at vinexin beta (SH3-containing adaptor molecule-1) 200808_s_at zyxin 202071_at syndecan 4 (amphiglycan, ryudocan) 210841_s_at neuropilin 2 215836_s_at protocadherin gamma subfamily C, 3 206908_s_at claudin 11 (oligodendrocyte transmembrane protein) 202638_s_at intercellular adhesion molecule 1 (CD54), human rhinovirus receptor 204306_s_at CD151 antigen 208850_s_at Thy-1 cell surface antigen Probe Set ID Symbol 4h 22h IFN Inducible 202411_at IFI27 2.4 5.7 203153_at IFITI 7.3 5 212009_s_at STIP1 -0.1 4.6 205483_s_at GIP2 2.3 3.9 202086_at MX1 3.7 3.8 204972_at OAS2 1.8 2.9 205552_s_at OAS1 2.5 2.8 217502_at IFIT2 2.3 2.8 218400_at OAS3 1.1 2.8 204415_at GIP3 1.3 2.7 214453_s_at IFI44 3.4 2.6 209417_s_at IFI35 0.6 2 204747_at IFIT4 3.6 1.6 Innate Immunity and Inflammation 205476_at CCL20 3.4 4.3 204614_at SERPINB2 1.3 3.2 217871_s_at MIF -0.1 2.9 217930_s_at TOLLIP 0.1 2.8 211506 s at IL8 1.9 2.6 207442_at CSF3 2.6 1.6 205114_s_at CCL3 3.6 1.3 204533_at CXCL10 2.6 0.9 207850_at CXCL3 2.5 0.2 B. Genes involved in Chromatin Remodeling 207824_s_at MAZ 0.2 5.6 218045_x_at PTMS -0.1 4.9 218064_s_at NAKAP95 -0.3 4.9 204805_s_at HIFX -1.1 4 208180_s_at HISTIH4H 1.5 3 207645_s_at CHDIL 0.3 3 208527_x_at HISTIH2BE -0.1 2.4 214290_s_at HIST2H2AA 0.0 2.3 Transcription Regulation 209636_at NFKB2 0.7 4 209878_s_at RELA 0.4 3.9 201332_s_at STAT6 0.4 3 208436_s_at IRF7 1.5 2.5 Basal TF 213887_s_at POLR2E 0.0 6.8 203239_s_at CNOT3 -0.2 4.1 215357_s_at PDIP46 0.3 3.6 202996_at POLD4 0.0 3.5 208960_s_at COPEB 0.6 2.6 205966_at 0.0 2.6 210892_s_at GTF2I -0.2 2.2 C. Genes involved in MAPK 213490_s_at MAP2K2 0.2 4 215050_x_at MAPKAPK2 0.0 3.2 RAS 209991_x_at GPR51 -0.6 5.2 215807_s_at PLXNB1 0.0 4.9 207419_s_at RAC2 0.5 4.4 217782_s_at GPS1 -0.3 3.9 203267_s_at DRG2 -0.1 3.7 208009_s_at ARHGEF16 0.1 3.4 201167_x_at ARHGDIA 0.8 3.2 206971_at GPR161 0.5 3.1 203136_at RABAC1 0.1 2.7 215249_at MUC20 0.1 2.2 212932_at RAB3GAP -0.3 2.1 206673_at GPR -0.1 2 200852_x_at GNB2 -0.4 2 P13K 210969_at PRKCL2 0.3 3.9 202545_at PRKCD -1.8 3.8 210417_s_at PIK4CB -0.2 2.2 NFkB 58994_at FU20241 -0.2 2.7 214398_s_at IKBKE 0.2 2.3 TGFB Related 203085_s_at TGFB1 -0.3 3.3 209920_at BMPR2 -0.4 2 D. Genes involved in Cell Cycle 221427_s_at CCNL2 0.0 5.1 204247_s_at CDK5 -0.6 4.3 204857_at MADIL1 -0.8 3.7 211017_s_at NF2 -0.4 3.5 209754_s_at TMPO 0.1 3.1 207428_x_at CDC2L2 -0.4 2.8 203252_at DOC-1R 0.0 2.7 209414_at FZR1 0.5 2.4 210622_x_at CDK10 0.2 2.4 209953_s_at CDC37 -0.4 2.4 208721_s_at ANAPC5 -0.2 2.3 216277_at BUB1 1.4 2 209112_at CDKNIB -1.2 -0.7 204170_s_at CKS2 -0.2 -1 202284_s_at CDKNIA -0.3 -1 204159_at CDKN2C -0.7 -1 207039_at CDKN2A -0.1 -1.6 GF and Angiogenesis 219922_s_at LTBP3 -0.5 4.5 207334_s_at TGFBR2 0.6 4 208231_at NRG1 -0.1 2.9 206796_at WISP1 -0.3 2.9 206814_at NGFB 0.8 2.6 210513_s_at VEGF 0.4 2.6 210973_s_at FGFR1 0.3 2.2 213807_x_at MET 0.9 2 202290_at PDAP1 0.2 2 Differentiation 210756_s_at NOTCH2 0.6 2 Others 200001_at CAPNS1 -0.2 2.7 218663_at HCAP-G -3.1 -1.1 E. Genes involved in apoptosis Pro-apoptotic 211833_s_at BAX -0.2 4.1 214667_s_at TP53I11 0.6 3.8 209941_at RIPK1 -0.1 3.6 1861_at BAD 0.1 3.2 206133_at HSXIAPAF1 1.2 2.4 203890_s_at DAPK3 -0.1 2 214617_at PRF1 -0.6 2 219209_at MDA5 3.7 1.9 220518_at TARSH 2.0 0.8 Anti-apoptotic 200796_s_at MCL1 0.7 5 210538_s_at BIRC3 2.7 4.9 218813_s_at SH3GLB2 0 2.9 211546_x_at SNCA 0.8 2 218943_s_at RIG-1 3.4 1.6 202510_s_at TNFAIP2 2.6 1.2 205681_at BCL2A1 2.6 0.6 212768_s_at GW112 -3.1 0.1 TNF Related 210654_at TNFRSF10D 0.3 4.1 206508_at TNFSF7 2.9 1.2 202688_at TNFSF10 2.1 -0.3 F. Genes involved ECM 202997_s_at LOXL2 0.1 7 209156_s_at COL6A2 -0.1 6.1 204163_at EMILIN1 -0.7 5.7 217430_x_at COLIA1 0.5 5.1 212091_s_at COL6A1 0.2 4.7 211966_t COL4A2 0.0 4.7 201654_s_at HSPG2 0.6 4.5 201262_s_at BGN 0.7 4.4 202827_s at MMP14 0.7 4.3 201286_at SDC1 0.1 3.4 209561_at THBS3 -0.1 2.6 205746_s_at ADAM17 0.1 Cytoskeleton 216971_s_at PLEC1 -0.4 5.4 209372_x_at TUBB 0.0 4.3 214040_s_at GSN 0.2 4.2 214752_x_at FLNA -0.3 3.3 217817_at ARPC4 -0.2 3.2 210978_s_at TAGLN2 0.2 3.1 215074_at MYOIB -1.3 3 220800_s_at TMOD3 0.0 2.1 Adhesion and Migration 217234_s_at VIL2 -0.1 3.9 218182_s_at CLDN1 1.1 2.7 209693_at ASTN2 -0.7 2.7 204627_s_at ITGB3 0.2 2.6 207788_s_at SCAM-1 0.4 2.5 200808_s_at ZYX -0.1 2.4 202071_at SDC4 1.0 2.3 210841_s_at NRP2 0.6 2.2 215836_s_at PCDHGC3 0.3 2.1 206908_s_at CLDN11 0.3 2.1 202638_s_at ICAMI 1.7 2 204306_s_at CD151 0 2 208850_s_at THYI 0 2 Fig. 3: Functional categories of LPS-regulated VSMC genes. We applied a signal log ratio cutoff of >+1.0 to all the genes that were differentially regulated by LPS treatment by 4 h and 22 h and all redundant probes that had less significant statistical values for each gene were also eliminated. Then the remaining 1541 differentially regulated genes were categorized into functional groups/subgroups based on gene annotation information from Affymetrix database. Genes of unknown or miscellaneous functions were grouped together as Others. Distribution of LPS regulated genes into functional groups Transporters 163, 11% Translation/Protein Biosynthesis 75, 5% Transcription/ Chromatin remodeling 178, 11% Structural proteins 127, 8% Signal transduction 125, 8% Proliferation 107, 7% Pro/Antiapoptosis 57, 4% Others 363, 24% Metabolism 211, 13% Host defense 104, 7% Ubiquitination 34, 2% Note: Table made from pie chart.
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