1 Gene Therapy Research Department, Berlex Biosciences, Richmond, California 94804
2 Drexel University, Philadelphia, Pennsylvania 19104
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ABSTRACT |
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shear stress; disturbed flow; microarray; atherosclerosis; endothelium
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INTRODUCTION |
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In this study we used cDNA microarrays and subtractive cloning methods to analyze changes in steady-state mRNA levels in cultured HAEC exposed to either DF or high-shear steady LF. This comprehensive and unbiased analysis demonstrated significant differences in the gene expression pattern exhibited by HAEC exposed to the two distinct flow patterns and allowed the identification for the first time of a collection of "proatherogenic" genes not reported so far to be regulated by flow/shear stress.
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MATERIALS AND METHODS |
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Flow apparatus.
The design of the DF chamber has been described in detail previously (9, 25, 27, 5053). It consists of a circular chamber (6.5 cm diameter, height of 1.5 cm) into which media enters from a round entrance port and then exits through a round orifice opposite to the entrance port. Flow of media through the chamber (100 ml/min) is driven by a peristaltic pump together with upstream and downstream reservoirs, which serve to generate a pulsatile flow with a sinusoidal pattern. The flow field in the chamber has been extensively characterized with high spatial (<100 µm) and temporal (10 ms) resolution (9, 25, 5053). Nunc-Thermanox coverslips (13 mm diameter) were placed into the wells of 24-well plates, coated with human fibronectin, and then seeded with 50,000 cells/well of HAEC. Approximately 48 h after reaching confluence, the coverslips were transferred either into another 24-well plate with fresh media (static controls) or glued into depressions in the surface of the flow chamber using 20 µl of biological glue solution (42), which consisted of a mixture of thrombin and fibrinogen, such that the coverslips are flush with the surface of the chamber. The small quantity of thrombin in the glue (0.5 U/coverslip) was not sufficient to upregulate VCAM-1 mRNA expression as determined by TaqMan quantitative RT-PCR (Q-RT-PCR) (data not shown). Three of the coverslips (positions 1, 3, and 5) are located along the "jet stream" between the entrance and the exit of the flow, while coverslips in locations 2 and 4 are located in the areas of "recirculating eddies" which mimic some of the flow conditions in the areas of atherosclerotic predilection (27, 53). All the experiments reported here were performed with cells pooled from locations 2 and 4 in the chamber which experienced shear forces of <0.01 dyn/cm2 and are located in the region of the chamber exposed to recirculating eddies. A detailed description of the hemodynamic conditions in this chamber, including numerical analyses of the flow fields (including the spatial distribution of peak mean flow velocities and calculation of shear stresses) in the areas of the recirculating eddies, are described by Samet and Lelkes (51). Photographs of the flow chamber with the location of the coverslips can be found in Lelkes et al. (27). A parallel plate chamber was used to generate steady LF as described (53). Briefly, HAEC were plated on fibronectin-coated single-well tissue culture chamber slides (Nunc). Forty-eight hours after reaching confluence, the cell-lined tissue culture slides were placed into a depression in the bottom half of the chamber. A Teflon gasket was used to create a 0.5-mm space above the cells when the top half of the chamber was attached. Media was circulated through the chamber at 100 ml/min by a peristaltic pump via upstream and downstream reservoirs, resulting in a wall shear stress calculated as 13 dyn/cm2. The upstream reservoir was left open to the atmosphere to dampen the pulsatility of the pump, thereby generating steady LF. The height of the chambers was adjusted to create the necessary hydrostatic pressure, and the flow rate through the chamber was calibrated using an in-line flow meter. The media used for all flow experiments was the same as that used to culture the cells, except that the amount of FBS was reduced to 5% (cells were adapted to the lower serum concentration for 24 h prior to initiating the flow experiments). The flow apparatus was placed inside a tissue culture incubator (5% CO2, 37°C) for the entire course of the experiment (up to 24 h). Media was changed on the static control cells when the flow experiment was started.
RNA isolation.
At the end of a flow experiment, the HAEC-lined coverslips were removed from the chamber and placed in 12-well plates containing media from the flow system. Microscopic examination showed that the monolayers remained intact in all of the flow experiments. The HAEC-lined coverslips were then washed once with PBS and lysed with Trizol reagent (Life Technologies). RNA was extracted from the lysate according to the manufacturers instructions and then treated with 1 unit of RNase-free DNase I (Promega) per 20 µg of RNA in 1x transcription buffer (Ambion) at 37°C for 30 min to remove traces of contaminating genomic DNA. The RNA was recovered by extraction with phenol/chloroform/isoamyl alcohol and ethanol precipitation, dissolved in water and quantitated by measuring the absorbance at 260 nm. Alternatively, RNA was extracted using the RNeasy kit (Qiagen) and treated with DNase I on the column prior to elution with water. The quality of every RNA sample was determined by denaturing 250 ng with formamide followed by electrophoresis on a nondenaturing agarose gel. RNA with distinct 18s and 28s rRNA bands with no smearing was considered to be undegraded and suitable for further analysis. The lysate from coverslips in locations 2 and 4 were pooled from 35 independent flow experiments to generate the RNA used in array hybridizations and Q-RT-PCR.
Tumor necrosis factor- treatment of HAEC.
HAEC were plated on 10-cm tissue culture plates, allowed to reach confluence, then exposed to a final concentration of 10 ng/ml human recombinant tumor necrosis factor- (TNF
, Calbiochem) for 3 or 20 h. Control cells were treated in parallel with vehicle (BSA). After washing once with PBS, total RNA was extracted using the RNeasy kit (Qiagen) and treated with DNase I on the purification column.
Atlas arrays.
Three micrograms of total RNA was converted to 32P-labeled cDNA using a mixture of primers specific to the set of genes on each array according the manufacturers instructions (Clontech). This has the advantage of generating a relatively uncomplex hybridization probe containing cDNA from only the limited set of 588 genes on the array, thereby reducing nonspecific cross-hybridization, which can lead to false positives. Labeled cDNA was denatured, prehybridized in solution to human Cot1/2 DNA and then hybridized to the array in ExpressHyb hybridization solution (Clontech) containing 0.1 mg/ml of denatured herring sperm DNA at 68°C overnight. The arrays used were the human I array (catalog no. 7740-1) and the human cardiovascular array (catalog no. 7734-1), both of which contain cDNA fragments representing 588 unique human genes and 9 housekeeping genes, each spotted in duplicate. After extensive washing under stringent conditions (68°C in 0.1x SSC) the arrays were exposed to a storage phosphor autoradiography screen (Fujifilm Medical Systems) which were subsequently scanned on a Storm PhosphorImager (Molecular Dynamics). The resulting image files were imported into Array Vision (Imaging Research) image analysis software to locate and quantify spot intensities and perform background subtraction. The signal intensity was calculated as the mean pixel value minus a local regional background and reported for each spot on the array. The resulting intensity values were exported to GepView a proprietary array analysis program developed at Berlex for identification of differentially expressed genes. The signal intensities were normalized to the mean signal intensity of all the spots on the array. Duplicate spots of each cDNA were averaged. To compare two arrays (2 conditions), the fold changes and differences of the corresponding normalized signal intensities were first calculated. The differences were standardized by calculation of a z score = [(IB on array 1 - IB on array 2)/SdID_ALL], where IB is the mean, normalized intensity value for a given gene, and SdID_ALL is the standard deviation of the signal intensity differences of all of the genes on the array. The z score is a measure of the statistical significance of the difference in signal intensity of a given gene on the two arrays compared with the average difference for all of the genes on the array. Differentially expressed genes with significant fold changes were identified by setting two thresholds, one for fold changes (2-fold) and one for z score (0.3), and taking the set of genes above both thresholds. It was determined empirically that using a z score threshold of 0.3 eliminates most of the false positives with both intensity values close to background and ratios greater than 2 due to division by low intensity values. The probes for all Atlas array hybridizations were synthesized from RNA that was pooled from at least three independent flow experiments. For the 24-h DF experiments, two hybridizations were performed each with probe derived from different pooled RNA samples, and the mean fold change for each gene that showed significant fold change over static was calculated. A comparison of the fold changes from these two hybridizations showed that more than 70% of the changes were consistent. For the other experimental conditions, single-array hybridizations were performed. For a given RNA sample, the data generated from the human I and cardiovascular Atlas arrays were combined. For those genes that were differentially expressed and present on both types of arrays, the average of the fold change on the two arrays was calculated. The differences in expression between DF and LF at the two time points were calculated from the respective fold change to static as follows. If the fold change to static was positive in both LF and DF or negative in both LF and DF, then the fold change in DF was divided by the fold change in LF, and the reciprocal was taken as required. When the fold change to static was positive for DF and negative for LF or vice versa, then the fold changes were multiplied, taking the sign of the fold change in DF.
Subtraction cloning.
One microgram total RNA from HAEC exposed for 24 h to either DF or to LF was converted into cDNA using the SMART cDNA synthesis kit (Clontech). The resulting cDNA was amplified by 17 cycles of long-distance PCR according the PCR-Select subtraction cloning protocol (Clontech). This limited number of cycles was carefully optimized to provide sufficient amplified cDNA without over-amplification. After purification the cDNA was digested with RsaI, ligated to special adapters according to the PCR Select protocol, and the PCR-based subtraction procedure was then performed (DF minus LF). Semi-quantitative PCR analysis of the subtracted cDNA demonstrated that the abundance of cDNA for the housekeeping genes glyceraldehyde-3-phosphate dehydrogenase (GAPDH), -tubulin, and ribosomal protein S9 was substantially reduced compared with unsubtracted cDNA, whereas that of VCAM-1 and monocyte chemotactic protein 1 (MCP-1) was substantially increased. The subtracted cDNA was cloned into the T/A cloning vector pCR2.1TOPO (Invitrogen), and white colonies (containing inserts) were picked at random and grown up in 96-well plates to which glycerol was added to create master stocks of the clones. Sequence analysis of randomly selected clones revealed that several clones were very abundant in the library. To avoid sequencing these clones repeatedly, the library was screened by hybridization with labeled cDNA representing these genes before being analyzed for differential expression under flow. For generating arrays, the cDNA inserts of selected clones were amplified by PCR using primers flanking the insert. The yield of amplified cDNA was checked by electrophoresis on agarose gels prior to spotting onto arrays. VCAM-1 cDNA fragments for spotting on arrays were generated by RT-PCR using human VCAM-1-specific primers (5' GAAGGATGCGGGAGTATATGA 3', 5' GACATAGATGGGCATTTCTTT 3'), and negative control cDNA was generated by PCR amplification of the inserts of plasmids containing the human testis-specific protein (GenBank accession no. X52128) and human semenogelin (accession no. XM_009525). Amplified cDNA was denatured with 0.3 M NaOH, spotted on nylon membranes (Schleicher and Schuell), neutralized with 0.5 M Tris, pH 7.5, then cross-linked with UV irradiation. Hybridization of these cDNA arrays with 32P-labeled cDNA probes was performed according to the instructions in the PCR-Select Differential Screening kit (Clontech). This method uses oligonucleotides complementary to the common primer sequences found in all of the arrayed cDNA clones to prevent nonspecific hybridization to the identical sequences present in the labeled cDNA probe. To prepare the hybridization probe, cDNA was synthesized from 0.6 µg of total RNA extracted from HAEC exposed for 24 h to DF, LF, or no flow (static), or from HAEC under static conditions exposed to TNF
or vehicle control for 2 and 21 h using the SMART cDNA synthesis protocol (Clontech). This cDNA was subjected to the minimum number of PCR cycles needed to make sufficient cDNA for labeling (9 cycles of long-distance PCR were used). After purification, half of this minimally amplified cDNA was labeled with 32P using random primers and Klenow enzyme. 32P was incorporated equally into the probes which were subsequently hybridized to identical filter arrays of cDNA inserts that had been prepared as described above. In addition to clones from the subtraction library, these filters contained cDNA fragments from VCAM-1 as a positive control, the two testis-specific genes as negative controls, and seven housekeeping genes (GAPDH, GenBank accession no. X01677; 23 kDa highly basic protein, X56932; ribosomal protein S9, U14971; phospholipase A2, M86400;
-tubulin, K00558; HLA class I histocompatibility antigen C-4
-chain, M11886; and ribosomal protein S19, M81757). The filters were washed at high stringency (0.2x SSC, 68°C) and imaged on a Storm PhosphorImager (Molecular Dynamics). Signal intensities for each spot were determined as described above for Atlas arrays, except that the signal on the testes-specific cDNA fragments (which was essentially identical to the signal on blank areas of the membrane) was used for background subtraction. For comparing one array to another, the signal intensities were normalized to the mean signal of the seven housekeeping genes instead of normalizing to all genes because of the large number of genes showing increases in DF compared with static or LF. Normalized intensity values were used to calculate fold changes between the three flow conditions (DF vs. LF, DF vs. static, and LF vs. static). When the signal intensity of a given spot was less than twice the average background, that gene was considered to be not detectable under that condition. When expression was not detectable under any of the three flow conditions, that clone was eliminated from further analysis. For those clones whose expression was not detectable under one or two conditions, the intensity value in those conditions was artificially set to twofold over background before calculating the fold change. Hybridizations were performed once using probes derived from RNA that was pooled from at least three independent flow experiments. To confirm this data, arrays containing a subset of the genes were probed in the same way using probes derived from RNA pooled from two independent DF experiments on a different strain of HAEC purchased from Clonetics. In total, some 700 cDNA clones from the forward subtraction library (DF minus LF) were screened for differential expression under flow.
Assays for DNA synthesis.
Following exposure to DF or LF, HAEC were incubated for an additional 4 h with 1 µCi [3H]thymidine. After three washes with ice-cold PBS, the cells were lysed on ice for 10 min with 10% trichloroacetic acid (TCA). The lysate was transferred into microcentrifuge tubes, centrifuged for 5 min at 10,000 g, and the pellet was resuspended in 10% SDS. Radioactivity in the TCA-insoluble pellet was determined in a liquid scintillation counter. For determining bromodeoxyuridine (BrdU) incorporation, we used a commercially available kit (Zymed). Briefly, following 24-h exposure to flow conditions, HAEC were transferred to 24-well plates, incubated for an additional 24 h with the BrdU labeling reagent, and subsequently processed according to the manufacturers instructions. The coverslips were then mounted on microscope slides, and bright-field images were acquired from three random fields at a magnification of x125. The number of BrdU-stained nuclei was evaluated by computer-aided image analysis (Image-Pro). A total of three independent experiments were performed, each in duplicate. The significance of differences between the groups was determined using unpaired Students t-test.
Monocyte adhesion assay.
HAEC-lined coverslips (static controls, treated for 5 h with 10 ng/ml TNF, or exposed to DF for 5 h) were placed into 24-well plates. To each well, 1 ml of MCDB131 medium containing 10% FBS and 5 x 105 monocytic U937 cells (ATCC CRL-1593.2) was added, and the monocytes were allowed to adhere for 30 min at 37°C, 5% CO2. To investigate the role of VCAM-1 in monocyte adhesion, some of the monolayers were preincubated for 2 h with saturating concentrations of a neutralizing anti-VCAM-1 antibody (11.5 µg/ml) followed by two washes with PBS, prior to addition of the monocytes. At the end of the experiments, nonadhered monocytes were removed by three washes with PBS, and the cells were fixed for 15 min with 3.7% paraformaldehyde. Subsequently, monocytes adhesion was evaluated microscopically. For each experimental condition, three random phase-contrast microscopic images per well, captured with a high-resolution camera (series 68; Dage-MTI, Michigan City, IN) connected to an inverted microscope (Diaphot, Nikon, Tokyo, Japan) through a x10 objective were projected onto a video monitor. Adhered monocytes per field (0.2 mm2) were counted manually on the screen. A total of three independent experiments were performed, each in duplicate. The significance of differences between the groups was determined by ANOVA followed by the Tukey comparison.
Quantitative real-time RT-PCR.
To quantitate the mRNA levels of selected genes, the following sets of primers and probes were used. All primer probe sets were designed using the ABI Primer Express software and the sequence of the relevant human mRNA from GenBank. All probes were labeled at the 5' end with 6-carboxyfluorescein (6-FAM) and contained the quencher dye 6-carboxy-N,N,N,N-tetramethylrhodamine (TAMRA) at the 3' end. VCAM-1: F primer CATGGAATTCGAACCCAAACA, R primer GACCAAGACGGTTGTATCTCTGG; probe AGGCAGAGTACGCAAACACTTTATGTCAATGTTG; E-selectin: F primer CAGTGCACAGCCTTGTCCAA, R primer CCCATAACGGAAACTGCCA, probe CCCGAGCGAGGCTACATGAATTGTCTT; p57kip2: F primer CGGCGATCAAGAAGCTGTC, R primer CGACGACTTCTCAGGCGC, probe TCTGATCTCCGATTTCTTCGCCAAGC; p55CDC: F primer CCGGAAGACCTGCCGTT, R primer TCGGATTTCAGGCGCATC, probe CATTCCTTCCCTGCCAGACCGTATCC; HSP70: F primer TACTCCGACAACCAACCCG, R primer TGTCTTTCGTCATGGCCCTC, probe CGCCCTCGTACACCTGGATCAGCA; glycoprotein IIIa (gpIIIa): F primer CCATTCTGCTCATTGGCCTT, R primer TCGGTCGTGGATGGTGATG, probe CCGCCCTGCTCATCTGGAAACTCC; Jagged-2: F primer TTACTGTGATTGCATCCCGG, R primer CTGACACTGCCCGCGAC, probe AGGGCATCAACTGCCATATCAACGTCAA; and thrombospondin-1 (TSP-1): F primer GCATCTACTTGCTTCAGTTGGGA, R primer CAGAGATGGCCTCACAATAGCAC, probe CCATTCCACTCTGCCTTTGTCACAGAGC. The primers and probes for human GAPDH were purchased from Applied Biosystems. Total RNA samples were converted to cDNA using a reverse transcription kit (Applied Biosystems) and random hexamer oligonucleotides as the primer in a 50-µl reaction containing 100 ng of total RNA. Aliquots of the cDNA were assayed in triplicate by real-time quantitative PCR using TaqMan reagents from Applied Biosystems on an ABI Prism 7700 sequence detection instrument. A standard curve consisting of serial dilutions of cDNA prepared from RNA extracted from untreated HAEC was run with every assay and used to calculate the quantity of a given mRNA in the unknown samples. The standard curves for all the primer/ probe sets used were linear over at least 3 logs with correlation coefficients of 0.98 or greater and slopes of between -3.3 and -3.7. The variability between triplicate assays of the same cDNA sample was typically less than 5%. The quantity of a given mRNA was normalized by dividing it by the quantity of GAPDH mRNA in that cDNA sample.
Semi-quantitative RT-PCR for MCP-1.
A one-step RT-PCR reaction was performed on 50 ng of total RNA from HAEC exposed to static or LF conditions for 24 h using an RT-PCR kit from Epicenter Technologies according to the manufacturers instructions and the following primers: F primer, TCTGCCGCCCTTCTGTGC; R primer, TCGGAGTTTGGGTTTGCTTGTC. [-32P]dCTP was included in each reaction to label the PCR product. Aliquots of the PCR reaction were removed after 20, 25, 30, and 35 cycles and fractionated on 6% acrylamide-urea gels. The amount of specific PCR product at the different cycles was quantitated on a Storm PhosphorImager. The data were normalized to the quantity of 23-kDa highly basic protein mRNA in the same RNA sample as determined by the same RT-PCR assay run in parallel using the following primers: F primer, CGCAAGCGGATGAACACCAAC; R primer, GCCAGGCGCCCCAGATAGG. The lowest cycle number (cycle 25) at which a significant signal (at least 1 x 105 counts) for MCP-1 was detectable was used to calculate the fold change between the static and LF samples.
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RESULTS |
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Several genes with known roles in cell cycle control were modulated by DF or LF (Fig. 2, nos. 2226). We observed a significant upregulation in LF compared with static of the mRNA for the cyclin-dependent kinase (CDK) inhibitor p57kip2, which was confirmed by Q-RT-PCR (Table 2). The tyrosine kinase wee1Hu was also upregulated in LF exposed cells compared with cells under static conditions, but unchanged by DF compared with static. Both of these proteins can function to block cell cycle progression. The upregulation of the growth arrest and DNA damage inducible protein 153 (GADD 153) by LF is consistent with an inhibition of cell cycle progression under high-shear conditions. Cyclin B1 and p55CDC were downregulated by DF but were not affected by LF, suggesting that DF also has an effect upon cell cycle. The downregulation of p55CDC by DF was confirmed by Q-RT-PCR (Table 2).
Several apoptosis-related genes were altered by DF or LF (Fig. 2, nos. 2734), including a relative decrease of TSP-1 expression under LF conditions, which was confirmed by Q-RT-PCR (Table 2). At the 24 h time point, we also observed a decrease in p53 mRNA levels in HAEC exposed to LF compared with static conditions. A significant increase in the expression of the mRNAs for the heat shock proteins HSP70, -40, and -47 (Fig. 2, nos. 3537) was observed under LF at the late time point, with little or no change under DF. The increase of HSP70 mRNA levels by LF was confirmed by Q-RT-PCR (Table 2).
There appears to be a coordinated reduction of integrin expression under LF (Fig. 2, nos. 3844) and, therefore, a relative increase under DF. These changes include the two subunits of the fibronectin receptor (5, ß1), as well as integrins-
3, -
6, -
m, and -
v and VE-cadherin. A number of genes involved in thrombosis or fibrinolysis were regulated by either DF or LF (nos. 5459 in Fig. 2). Among these are gpIIIa and the thrombin receptor, both of which were downregulated by LF. The downregulation of gpIIIa by LF was confirmed by Q-RT-PCR (Table 2). We also found that the mRNAs for endothelin 1 and endothelin converting enzyme 1 (nos. 61 and 62, respectively, in Fig. 2) were downregulated by LF. The levels of mRNA encoding a number of proteins involved in regulating oxidative status were modulated by flow (Fig. 2, nos. 6467). Both SOD-1 and SOD-2 were downregulated in DF compared with LF at 24 h, whereas glutathione S-transferase exhibited a relative increase in DF compared with LF. The matrix metalloproteinase (MMP)-14 and MMP-7 were downregulated by LF at 24 h, whereas MMP-1 and MMP-8 were increased by LF at the same time point (Fig. 2, nos. 6871).
The mRNA level of several signaling molecules were affected by the different flow conditions (Fig. 2, nos. 7281). For example, bone morphogenic protein 4 (BMP4) and Smad1, both of which are components of the transforming growth factor-ß (TGFß) signaling pathway, were downregulated by DF at the late time point. In addition, various protein kinases were modulated by the different flow conditions at one or both time points. For example, the tyrosine kinase receptor RET and the tyrosine kinase RYK were downregulated by LF. We also observed significant changes in the mRNA levels of several transcription factors (Fig. 2, nos. 8289), including relative increases of Hox-11 and Hox-7 and relative decreases in b-myb, Fra-1, and egr1 in DF compared with LF. Among the growth factors surveyed on these arrays, only three showed significant changes under flow (Fig. 2, nos. 9092). The mRNA levels of several receptors were altered by flow; for example, the platelet-derived growth factor (PDGF) receptor -chain was downregulated by DF, and slightly increased by LF but only at the early time point. The mRNA for two cytochrome P-450 enzymes (Fig. 2, nos. 100 and 101) was increased by both DF and LF at 24 h, such that the net change was only a small increase in DF compared with LF. A number of additional genes (Fig. 2, nos. 102111) were modulated by the different flow conditions, but their relevance to flow modulated EC biology has yet to be established.
Subtraction cloning combined with cDNA array analysis identifies additional flow-regulated genes.
cDNA arrays are limited to the set of genes present on the array. To overcome this limitation, we utilized subtraction cloning to enrich for cDNA clones representing mRNA species more abundant in HAEC exposed to DF than in HAEC exposed to LF. By subtracting LF mRNA from DF mRNA we expected to capture genes upregulated by DF and also genes downregulated by LF. cDNA clones representing TSP-1, endothelial specific molecule 1 (ESM-1), VCAM-1, and plasminogen activator inhibitor 1 (PAI-1) were abundant in the subtraction library, representing 17%, 2.7%, 2.5%, and 2.1% of the library, respectively. cDNA clones from this library were screened for differential expression in HAEC exposed to DF, LF, or static conditions for 24 h using membrane-based cDNA arrays, and the results are presented in Fig. 3 as fold change compared with static.
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Gene expression profile induced by TNF is distinct from that induced by DF.
To investigate the possible role of nuclear factor B (NF-
B) activation in gene regulation under DF conditions, we also surveyed gene expression changes induced in HAEC exposed to 10 ng/ml TNF
, a well-characterized activator of the NF-
B pathway (30). Microarray analysis indicated distinct differences in the response of HAEC to TNF
and DF (data not shown). We therefore used Q-RT-PCR to measure changes in the mRNA levels of selected genes induced by 24-h exposure to TNF
and compared this to the response to 24-h exposure to DF (Table 2). As expected, E-selectin and VCAM-1 were upregulated by TNF
, and these genes were also upregulated by DF. However, while VCAM-1 mRNA was upregulated more than 70-fold by TNF
, DF induced a much smaller 3.5-fold upregulation of this mRNA. Similarly, we observed large differences in the magnitude of upregulation of E-selectin mRNA by TNF
and DF (10-fold vs. 90-fold, respectively). Although the mRNA level of p55CDC was slightly upregulated by TNF
(2.5-fold), it was strongly downregulated by DF (21-fold). Similarly, HSP70 and Jagged-2 were regulated in opposite directions by TNF
and DF.
Effect of DF and LF on DNA synthesis in HAEC.
The gene expression profile of HAEC exposed to LF predicts a reduction in cell proliferation under this flow condition compared with HAEC kept under static conditions. To analyze the functional consequences predicted by the differential gene expression profile, we assessed DNA synthesis in HAEC exposed for 24 h to DF, LF, or static conditions by measuring [3H]thymidine and BrdU incorporation. The results (Fig. 4) demonstrate a statistically significant 25% decrease in [3H]thymidine incorporation and a 44% reduction in the number of BrdU-positive nuclei in cells exposed to LF compared with static controls. In contrast, exposure of HAEC to DF resulted in a significant 60% increase in [3H]thymidine incorporation and a 225% increase in the number of BrdU-positive nuclei compared with HAEC under static conditions (Fig. 4).
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DISCUSSION |
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Cultured EC are no longer exposed to hemodynamic forces, specifically high-shear LF, a key stimulus that is required to maintain their physiological state. Most published data on the effects of flow on EC function and gene expression comes from a comparison of high-shear LF vs. static conditions. We have attempted to obtain a more relevant picture of the gene expression changes induced in EC by "pathological" flow conditions by comparing the changes in mRNA levels induced by DF and steady high-shear LF using microarrays and subtraction cloning. To date, no microarray-based analysis comparing the gene expression changes induced in vascular EC by high-shear LF and low-shear non-unidirectional or disturbed flow (or other conditions similar to DF) has been reported. Subtraction cloning proved to be an effective way to identify flow-regulated genes, as only 5 of the 32 genes discovered with this approach were also identified using arrays of preselected genes. To confirm the microarray data, we used Q-RT-PCR to measure the relative expression of nine selected genes in HAEC exposed for 24 h to DF, LF, and static conditions (Table 2). The results from this analysis agreed well with the array data in terms of both the directions of the change and, for most of the genes, the magnitude of the change. The genes we selected for Q-RT-PCR cover the most relevant functional classes with respect to the effect of DF and LF upon EC, for example, the class of genes involved in cell adhesion (VCAM-1, E-selectin), inflammation (MCP-1), proliferation (p57kip2), apoptosis (TSP-1, Jagged-2, HSP70), and thrombosis (gpIIIa).
Our results demonstrate that DF and LF induce distinct patterns of gene expression. The genes that were regulated by hemodynamic forces could be grouped into nine classes according to their response to exposure to DF and LF for 24 h (Table 3). Although genes downregulated by LF but unaffected by DF (class III) constituted the largest group (50 genes), the finding that 49 genes were regulated by DF (16 in class I, 10 in class II, and 23 in classes VIX) demonstrates that DF is more than simply the absence of LF. The fact that the DF-induced gene expression pattern is significantly different from that seen under static conditions indicates that although DF represents very low shear stress values, the coexistence of other variables (e.g., pulsatile non-unidirectional, nonsteady flow), is sufficient to induce a biological response in EC. In total, more than 130 genes were regulated by DF or LF at either the early or late time points. To the best of our knowledge, flow regulation of the mRNA levels of not more than 22 of these genes has been reported previously, including the recent microarray-based analyses of HUVEC (12, 34) and HAEC (7). Of particular interest are the class I genes (Table 3; Fig. 3) that were upregulated by DF and downregulated by LF. These genes exhibit the largest difference in expression between DF (that is, similar to conditions that exist at areas of the arterial circulation predilected for atherosclerosis) and LF (that is, similar to conditions that exist at atheroprotected areas). This class contains genes with clearly defined roles in atherosclerosis, such as VCAM-1, E-selectin, and MCP-1, as well as genes of known function whose involvement in atherosclerosis has yet to be proven, such as TSP-1. There are also genes in class I, such as KIAA0487 and 24775 mRNA, for which a function remains to be identified. The finding that one set of genes can respond to both DF and LF, albeit in different directions, while others respond only to DF or only to LF suggests that distinct signaling pathways are responsible for the response to these two stimuli.
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In most cases the expression data presented here for genes known to be regulated by flow/shear stress are in agreement with published data. For example, earlier reports of the downregulation of the thrombin receptor (41), endothelin-1 (54), endothelin converting enzyme-1 (32), and MCP-1 (55) by high-shear LF are consistent with the microarray data presented here. The upregulation of VCAM-1, ICAM-1, and E-selectin by DF is consistent with a previous report showing upregulation of these genes by oscillatory flow, another model of low shear stress (6). However, in contrast to the sustained upregulation of VCAM-1 mRNA by DF, oscillatory flow induced a transient upregulation of VCAM-1 mRNA that peaked at 4 h and declined to baseline by 24 h (6). For several genes the pattern of flow regulation we observed differs from earlier reports. For example, upregulation of ICAM-1 by high-shear LF has been described using HUVEC (37), whereas we observed a downregulation of this gene after 24 h of LF. Similarly, SOD-2 was shown to be upregulated in HUVEC exposed to laminar shear stress (LSS) for up to 6 h (58), whereas we found SOD-2 unchanged by LF but downregulated by DF at 24 h. Urbich et al. (61) found that the mRNA for integrins-5 and -ß1 were increased in HUVEC by exposure to LF, whereas we observed a decrease in the mRNA levels for these genes in HAEC under LF. We surmise that some of these discrepancies may be due to differences in the cell type, flow model, or time point analyzed.
The mRNA levels of several cell adhesion molecules (E-selectin, VCAM-1, ICAM-1, sialophorin, CD44, ICAM-2, PECAM, and MUC18) exhibited a relative increase in expression under DF compared with LF conditions (Fig. 2, nos. 18). The importance of VCAM-1 in early atherosclerosis is well established (10), presumably via the ability of this molecule to promote extravasation of monocytes. Our finding that additional adhesion molecules are upregulated under DF compared with LF suggests that these may also play a role in the interaction of the endothelium with inflammatory cells at predilected areas. For example, sialophorin or CD43 (Fig. 2, no. 1) is a member of the sialomucin family, which act as scaffold molecules to present selectin carbohydrate ligands, thereby increasing the strength of the interactions between leukocytes and EC (23). The relevance of our model was strengthened by the finding that exposure of HAEC to DF resulted in increased monocyte adherence (Fig. 5). The ability of a neutralizing antibody to VCAM-1 to partially block this increased monocyte adhesion supports the concept that the observed changes in cell adhesion molecule gene expression have functional consequences.
The largest functional group of flow-regulated genes comprises mediators of inflammation (Fig. 2, nos. 921; Fig. 3, nos. 15 and 26). According to the literature published to date, only one of these genes, MCP-1, has previously been shown to be regulated by flow (55). The finding that the mRNAs for additional proinflammatory molecules (CDC27L receptor, NAP3, mip2, receptors for IL-2, -3, -9, CD72, IL-6, IL-8, RP1, and HuMig) are present at higher levels in DF relative to LF (mostly due to the downregulation by LF) suggests that exposing EC to DF could contribute to the persistent state of low level inflammation characteristic of atherosclerosis-prone regions (49).
Both the Atlas arrays and Q-RT-PCR revealed that the mRNA for p57kip2 was significantly increased in HAEC exposed to LF for 24 h. High levels of p57kip2 would be expected to block cell cycle progression at the G1-S transition by binding to and inhibiting the activity of CDKs such as CDK2 and CDK4 (24, 33). The LF-induced upregulation of the mRNA for wee1Hu (Fig. 2, no. 25), which is a negative regulator of p34CDC2 (59), would also be expected to inhibit cell cycle progression, but at the G2 checkpoint. These results show that in our experiments LF induced the expression of two cell cycle regulators capable of blocking cell cycle progression at both the G1 to S and G2 to M transitions. The anti-proliferative effect of high-shear steady LF on EC is well established, and upregulation of the CDK inhibitor p21cip1 by LF has been demonstrated in both HUVEC and bovine aortic EC (BAEC) (1, 29). A careful examination of our Atlas array data showed that the signal for p21cip1 mRNA was increased in LF compared with static at 24 h, but because of the low signal intensity this difference did not meet the criteria for significance. Consistent with previous reports and the gene expression data presented here, we showed a statistically significant decrease in DNA synthesis in HAEC exposed to LF (Fig. 4). The mRNA levels of p57kip2 and wee1Hu were unchanged in DF conditions compared with static and therefore were relatively lower in DF than under LF conditions. This suggests that like static cells, DF exposed cells may have lost the cell cycle block conferred by the increased expression of these genes under LF conditions and therefore may exhibit a proliferative phenotype. In our model the rate of DNA synthesis in HAEC exposed to DF was increased compared with cells under static conditions. Previously, Davies et al. (11), using a model of turbulent flow that generates different hemodynamic conditions to those used in our studies, reported an increase in the number of [3H]thymidine-labeled nuclei in BAEC exposed to low- or high-shear turbulent flow.
Several genes that have been shown to modulate apoptosis and/or angiogenesis were regulated by flow (Fig. 2, nos. 2737; Fig. 3, nos. 3 and 18). The levels of TSP-1 mRNA were upregulated by DF and downregulated by LF (Fig. 3, no. 3; Table 2). TSP-1 is a pleiotropic molecule, but one of its functions in EC is to block angiogenesis by activating apoptosis (18, 43). The mRNA for p53 was downregulated by LF compared with static but unchanged by DF and therefore relatively higher in DF compared with LF. p53 responds to a variety of stimuli, including DNA damage, and this can result in the induction of apoptosis. A coordinated upregulation of HSPs (HSP70, -40, and -47) was detected after 24-h exposure to LF (Fig. 2, nos. 3537; Table 2). A number of the HSPs including HSP70 are anti-apoptotic due at least in part to their ability to inhibit formation of the apoptosome complex (5). Jagged-2, a ligand for the receptor notch, and potential anti-angiogenic molecule (63) was upregulated by DF and also downregulated by LF (Fig. 3, no. 18 and Table 2). Thus our results demonstrate flow-induced changes in the mRNA levels of several genes (TSP-1, p53, HSPs, and Jagged-2) all of which are consistent with increased apoptosis under DF conditions. The combination of increased apoptotic rate and increased proliferation rate under DF conditions might lead to increased EC turnover that could result in focal denudation of the blood vessel thereby exposing the procoagulant surface beneath.
The relative increase in mRNA levels of endothelin 1 and endothelin converting enzyme 1 in DF compared with LF conditions (Fig. 2, nos. 61 and 62) would be predicted to result in endothelium-mediated vasoconstriction under conditions of DF. The relative increase in expression of the thrombin receptor (Fig. 2, no. 54; Fig. 3, no. 32) and PAI-1 (Fig. 3, no. 12) in DF compared with LF is predicted to cause a shift to a procoagulant state under DF. Although a decrease in PAI-1 mRNA in HUVEC exposed to shear stress has been reported (20), we extend this observation by demonstrating not only the downregulation under LF but also upregulation by DF such that the net change is more than 10-fold. Increased PAI-1 at sites exposed to DF would be expected to reduce the potential for clot lysis. The level of the mRNA for gpIIIa, one of the subunits of the gpIIbIIIa complex, an important receptor for activated platelets, was reduced under LF compared with static cells (Fig. 2, no. 55; Table 2), which might reduce the capacity to bind activated platelets, leading to reduced platelet deposition in arterial areas exposed to high-shear LF.
Several genes involved in signaling, including two members of the TGFß family of signaling molecules (BMP4 and Smad1), protein kinases (e.g., RYK, RET, FAST, and MAPK6), and the ligand Dickkopf-2 (Dkk2) were regulated by either DF or LF. This suggests that exposure to flow may alter the capacity of EC to respond to various stimuli.
In summary, these data demonstrate that DF is not simply the absence of LF but in fact represents a distinct biomechanical stimulus that has a profound impact upon the gene expression profile of human aortic EC in culture. Microarray and subtraction cloning analysis revealed regulation of genes hitherto unknown to be flow regulated. Q-RT-PCR analysis confirmed the data obtained from the microarrays. For some of the genes whose expression was altered by DF or LF, corresponding changes in EC function (monocyte adhesion and DNA synthesis) could be demonstrated. The upregulation of VCAM-1 and increased monocyte adhesion to EC exposed to DF was similar to EC in vivo at atherosclerosis-prone regions, confirming the relevance of our model system for in vivo conditions. Many of the genes upregulated by DF are potentially proatherogenic. In addition, we identified genes whose regulation by LF would be predicted to be anti-atherogenic. Thus it is likely that the presence of low-shear non-unidirectional, nonsteady, pulsatile flow (DF) together with the absence of LF at predilected areas may predispose the endothelium to the development of atherosclerosis. Although the described studies lead to important new observations, they represent findings in a model system. The relevance of the gene expression changes detected in these in vitro models to gene expression differences at atherosclerosis-prone sites in vivo must be studied in the future.
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ACKNOWLEDGMENTS |
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This study was supported in part by an American Heart Association Grant-in-Aid (to P. I. Lelkes).
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FOOTNOTES |
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Address for reprint requests and other correspondence: A. R. Brooks, Berlex Biosciences, 15049 San Pablo Ave., Richmond, CA 94804 (E-mail: alan_brooks{at}berlex.com).
10.1152/physiolgenomics.00075.2001.
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