Changes in Gene Expression by Trabecular Meshwork Cells in Response to Mechanical Stretching

Abstract

purpose. Trabecular meshwork (TM) cells appear to sense changes in intraocular pressure (IOP) as mechanical stretching. In response, they make homeostatic corrections in the aqueous humor outflow resistance, partially by increasing extracellular matrix (ECM) turnover initiated by the matrix metalloproteinases. To understand this homeostatic adjustment process further, studies were conducted to evaluate changes in TM gene expression that occur in response to mechanical stretching.

methods. Porcine TM cells were subjected to sustained mechanical stretching, and RNA was isolated after 12, 24, or 48 hours. Changes in gene expression were evaluated with microarrays containing approximately 8000 cDNAs. Select mRNA changes were then compared by quantitative reverse transcription–polymerase chain reaction (qRT-PCR). Western immunoblots were used to determine whether some of these changes were associated with changes in protein levels.

results. On the microarrays, 126 genes were significantly upregulated, and 29 genes were significantly downregulated at one or more time points, according to very conservative statistical and biological criteria. Of the genes that changed, several ECM regulatory genes, cytoskeletal-regulatory genes, signal-transduction genes, and stress-response genes were notable. These included several proteoglycans and matricellular ECM proteins composed of common repetitive binding domains. The results of analysis of mRNA changes in more than 20 selected genes by qRT-PCR supported the findings in the microarray analysis. Western immunoblots of several proteins demonstrated protein level changes associated with changes in the level of mRNA.

conclusions. The expression of a variety of TM genes is significantly affected by mechanical stretching. These include several ECM proteins that contain multiple binding sites and may serve organizational roles in the TM. Several proteins that could contribute to the homeostatic modification of aqueous humor outflow resistance are also upregulated or downregulated.

The mechanisms that provide normal IOP homeostasis are only partially understood. A relatively effective homeostatic mechanism must exist, because only approximately 2% to 5% of people exhibit pathologic elevations in IOP with subsequent optic nerve damage, even at advanced ages. ^{1 2} We have hypothesized that TM cells can adjust outflow resistance over a timescale of hours to days by modulating trabecular ECM turnover and subsequent biosynthetic replacement. ^{3 4 5 6} Manipulation of the trabecular activity of a family of ECM turnover enzymes, the matrix metalloproteinases (MMPs), reversibly modulates outflow facility. ⁷ Inhibition of the endogenous ECM turnover, which is initiated by these MMPs, increases the outflow resistance. Therefore, ongoing ECM turnover must be necessary for homeostatic maintenance of the IOP. In addition, laser trabeculoplasty, a common treatment for glaucoma, appears to owe its efficacy to producing relatively sustained trabecular MMP elevations, particularly within the juxtacanalicular region of the meshwork. ^{8 9 10}  

Much of the aqueous humor outflow resistance appears to reside within the deepest portion of the TM. ¹¹ Consequently, this resistance is functionally stretched like a diaphragm across Schlemm’s canal. Alterations in the outflow resistance that are sufficient to affect IOP change the degree of stretching and distortion of the juxtacanalicular TM. A likely sensing mechanism in TM cells, indicating that an increase or decrease in outflow resistance is needed, is that of alterations in mechanical tension or stretching. This sensing could be mediated and transduced by integrin–ECM or similar types of interactions. ^{12 13} We and others have found that trabecular cells can sense changes in IOP and mechanical stretching and produce several distinctive responses. ^{14 15 16 17 18 19 20 21 22 23 24} In support of our overall hypothesis of IOP homeostasis, trabecular cells respond to pressure elevations in perfused organ culture or to mechanical stretching in cell culture by increasing MMP-2 (gelatinase A) and MMP-14 (membrane-type-1-MMP) activity or levels, while dramatically reducing levels of their primary tissue inhibitor, TIMP-2. ¹⁴ Increased trabecular MMP activity results in reduced outflow resistance ⁷ and thus should restore IOP to normal levels. Therefore, the components of a self-contained trabecular IOP homeostasis mechanism are present and functional. In perfused anterior segment organ culture, increased flow rates produce initial elevations of IOP, which return to normal over several days, even with sustained increases in perfusion rate. ^{14 23}  

An important component of this putative IOP homeostasis mechanism is the nature of the changes in the ECM that adjust the outflow resistance. The ECM turnover process is initiated by secretion/activation of the MMPs, which partially degrades select ECM proteins. This phase is followed by the removal of proteolytic ECM fragments, presumably facilitated by TM cell endocytosis. New materials must then be synthesized by TM cells to replace degraded ECM components. To adjust the outflow resistance, changes in the amount, composition, or organization of this ECM are likely to be instituted. This process must occur within the active pathway of aqueous humor outflow without allowing excessive structural disorganization. To begin unraveling the details of this complex process, microarray analysis of TM gene expression changes occurring after sustained mechanical stretching were conducted. 

Materials and Methods

Porcine eyes were obtained from Carlton Packing (Carlton, OR); proteinase inhibitor cocktail, phenylmethylsulfonyl fluoride (PMSF), dithiothreitol (DTT), and horseradish peroxidase-conjugated secondary antibodies from Sigma-Aldrich (St. Louis, MO); a DNA quantitation reagent (PicoGreen) from Molecular Probes (Eugene, OR); fibronectin antibody from Transduction Laboratories-BD Biosciences (San Diego, CA); tenascin C antibody from Santa Cruz Biotechnology (Santa Cruz, CA); Dulbecco’s modified Eagle’s medium (DMEM), antibiotics, and antimycotics from Invitrogen-Gibco (Grand Island, NY); fetal bovine serum from HyClone (Logan, UT); chemiluminescence detection kits (Super Signal) from Pierce (Rockford, IL); Falcon cell culture inserts (PET track-etched 3-μm pore membranes in six-well format) from BD Biosciences (Franklin Lakes, NJ); and RNA extraction kits (RNeasy) from Ambion (Austin, TX). 

TM Cell Culture, Mechanical Stretching, Treatments, and Extractions

Porcine TM cells were cultured as previously described. ^{5 25 26 27} By passages 3 to 5, cells were plated at a density of approximately 90% confluence onto cell culture insert membranes in six-well culture plates. ^{14 28} When cells were densely confluent, 3 to 5 days later, they were placed in serum-free medium for 24 hours before and during stretching experiments. To apply mechanical stretch/distortion, a smooth, 5.25-mm glass bead was placed in the dish beneath the center of the insert membrane. A weight was then applied to the lid of the plate, which forced the insert down onto the bead. ^{14 28} This process created a defined upward distortion of the membrane, which increased the surface area and produced mechanical stretching of the cells and their ECM. More than 20 different porcine cell lines, each comprising cells from 10 to 20 eyes, were studied. DNA analysis (PicoGreen; Molecular Probes) was conducted in parallel wells in some studies, to estimate cell density. Because the differences between wells were always less than 10%, the analysis was not conducted in all studies. At the indicated times after initiation of stretching, medium was collected and stored in aliquots frozen at −20°C until use. For cellular or ECM protein analysis, membranes were immediately rinsed with ice-cold phosphate-buffered saline and the cells lysed with a modified RIPA buffer ^{29 30 31} (2 mM EDTA, 2 mM EGTA, 1% NP-40, 0.5% sodium deoxycholate, 0.1% sodium dodecyl sulfate [SDS], 2 mM DTT, 1 mM PMSF, proteinase inhibitor cocktail, and 50 mM Tris [pH 7.5]) on ice. For RNA analysis, the membranes were cut from the inserts after stretching and placed in denaturation buffer (RNeasy kit; Ambion). They were then vortexed and the lysate removed. The remaining steps were as described in the kit protocol, and total RNA was processed according the manufacturer’s instructions. The extracted RNA was subjected to DNase treatment with 20 units of RNase-free DNase (Promega, Madison, WI) for 20 minutes. This was followed by two phenol-chloroform extraction steps to obtain high-quality RNA with an A260/A280 optical density ratio of 1.8 to 2.0. 

Gene Chip Microarray

From each control or stretch sample, 9 μg of total purified RNA was provided to the Oregon Health and Science University Spotted Microarray Core (OHSU SMC) for processing (http://www.ohsu.edu/gmsr/smc/index.shtml). The stretch or the nonstretch control RNA was labeled by reverse transcription using either fluorescein-modified or biotinylated nucleotides and an oligo-dT primer. These labeled probes were mixed and hybridized to the spotted chips at 65°C for 16 hours (M-series LifterSlips; Erie Scientific, Portsmouth, NH) in a deep well hybridization chamber (TeleChem, Sunnyvale, CA). Hybridized arrays were then probed with Tyramide signal amplification (TSA) kits (PerkinElmer, Boston, MA), with horseradish peroxidase-conjugated anti-fluorescein antibody or streptavidin. Slides were developed with Cy3- and Cy5-tyramine and scanned (ScanArray 4000 XL with ScanArray Express software; Perkin-Elmer). 

The two types of OHSU SMC microarray chips that were used had duplicate separated spottings of approximately 5700 or 8400 human cDNA clones per slide. The data presented herein are from the 8400 chips, but very similar results were obtained earlier with the 5700 chips. The libraries used were prepared by the IMAGE consortium ³² and distributed in sequence-verified form by Invitrogen (Carlsbad, CA). Amplified PCR products were printed onto microarray slides (UltraGAPS; Corning Costar, Corning, NY) using microarray printing pins (TeleChem 16 CMP-3) and an array printer (Cartesian PixSys 5500 XL; Genomic Solutions, Irvine, CA). Twenty-three plant genes (Arabidopsis thaliana) spotted twice per chip, were used for standard reference providing both a positive and a negative control. In addition, 176 spots were left blank on each chip to provide another type of negative control. Scanned images were analyzed by computer (ImaGene; BioDiscovery, Marina del Rey, CA) to determine relative fluorescence intensity for each label; to identify spot locations, shapes, sizes, and anomalies; and to determine spot-specific background intensity for each label. At each of the three time points (12, 24, and 48 hours), three totally independent experiments were conducted. Each sample from each experiment was analyzed on two separate identical microchips. On each chip, each of the 8400 genes was spotted twice in separate regions. Consequently, at each of the three time points, there were 12 separate stretch and control data pairs for each gene. 

Microarray spot fluorescence intensities for control and stretch samples with associated background values were then analyzed separately at each of the three time points. To determine statistical significance, the data from each chip with the duplicate spot values were separated into half chips, with one stretch and one control value and their respective specific backgrounds for each of the approximately 8400 cDNAs. The stretch and control data from each half-chip were then corrected for background and normalized via Lowess ³³ (GeneSpring software; Silicon Genetics, Redwood City, CA). These normalized fluorescence intensities were then combined into a single parallel data set for each time point, to identify those genes that achieved statistical significance using significance analysis of microarrays (SAM). ³⁴ Twelve normalized stretch and 12 normalized control fluorescence intensities for each gene at each time point were thus used to determine which changes were statistically significant. The number of permutations was set at 1000; the analysis was in a paired format; and the nearest number imputer was set to 10 in the SAM software (http://www.stat.stanford.edu/∼tibs/SAM/ provided in the public domain by Stanford University, Stanford, CA). The false-discovery rate Δ parameter was then adjusted to produce a median value of less than 0.5 falsely significant genes from the complete set. A separate evaluation was conducted by using two criteria to determine which gene changes achieved biological significance. To do this, all 12 of the stretch and control fluorescence spot intensity pairs with their associated backgrounds were combined into a single long data set. They were corrected for background and then normalized via Lowess (GeneSpring; Silicon Genetics), as though they were replicates on one large microchip. These data were then filtered to select genes that exhibited at least a 1.5-fold average increase or at least a 50% average decrease. These were then further filtered to eliminate genes expressed at low levels both before and after mechanical stretching. Spots with average normalized fluorescence intensities below 300 for both control and stretch, after the background was subtracted, were eliminated. This lower expression threshold was selected because it was more than 2 standard deviations above the average specific background on these chips. The subset of genes that passed all three of these selection criteria (i.e., exhibited both statistical and biological significance for at least one time point) was retained. 

Quantitative RT-PCR

Quantitative RT-PCR was performed (LightCycler and one-step Lightcycler-RNA amplification Kit, SYBR Green I; Roche Diagnostics, Indianapolis, IN). ³⁵ Primer pairs were designed in adjacent exons so that amplification of potential traces of contaminating genomic DNA would be easily identified. After the RT cycle (55°C, 10 minutes), 40 PCR cycles (94°C, 30 seconds; 50°C [primer dependent], 10 seconds; and 72°C, 14 seconds) were used. Fluorescence was acquired at the end of each extension step, and a melting curve was obtained at the end of each run. In a few cases in which multiple peaks were observed in the melting curve, the fluorescence was acquired in a separate step after each cycle at a temperature above the melting temperature of the additional nonspecific peak. After the PCR, products were analyzed on gels to verify band sizes and purity. In some cases, the product was also sequenced. Data were analyzed by the system software (LightCycler; Roche Diagnostics), by using a 10-point dilution standard curve and the crossing-point method to determine the relative template concentration of samples. Because fibronectin exhibits alternative splicing, several additional primers were designed to determine which splice forms were expressed. Twenty genes were evaluated by qRT-PCR, including several that increased, several that decreased, and several that did not show any change on the microarrays at any time after stretching. 

Western Immunoblots

Western immunoblots, transferred electrophoretically from standard SDS-PAGE gels to nitrocellulose or PVDF membranes, were probed with the indicated primary antibodies. Detection used the appropriate secondary antibodies with conjugated horseradish peroxidase and chemiluminescence according to the manufacturer’s instructions (SuperSignal; Pierce) ^{5 14 31 36} Autoradiographs were scanned and relative band density analyzed ³⁷ with a densitometry program (UVP, Upland, CA). For both the qRT-PCR and the Western immunoblot data, Student’s t-test or Mann-Whitney ranked sum analysis was used to determine significance, when comparing treatment results. All experiments presented were repeated at least three times, and typical gels were selected for presentation. 

Results

Normalization and Significance

When the microarray data sets were normalized by Lowess after the backgrounds were subtracted, flat and well-centered ratio-intensity (R-I) curves ³³ were obtained. Figure 1shows a typical R-I curve for the SMC8400 chip and 24-hour data. At each time point, a few hundred genes achieved statistically significant changes, when analyzed by SAM ³⁴ in each 12 × 12 stretch–control data set. As the Δ parameter decreased incrementally, a lower plateau was reached at approximately a median number of 0.5 falsely significant genes per data set. Additional increments reduced the number of genes without reducing the false-discovery rate. Therefore, the highest number of genes that achieved this false-discovery rate was accepted. Further filtering of this group for biological significance, in terms of expression level in the TM and magnitude of changes with mechanical stretch, gave 126 genes that achieved a 1.5-fold or larger increase and 29 genes that achieved a 50% or greater decrease at one or more of the three time points. Analysis of the results from the SMC5700 chips showed good agreement for the genes common to both arrays (data not shown). The OHSU SMC microarray facility also conducted a detailed data analysis in which somewhat different specific normalization and significance testing approaches were used. Their lists of changed genes were very similar to those we obtained, as detailed earlier. 

Filtering the data from all three time points, after subtraction of the local background and normalization via Lowess but with no other restrictions, simply requiring the mean expression levels to reach a lower threshold level of greater than 300 relative fluorescence units, produced a group of well over 3000 genes that are clearly expressed at significant levels by TM cells. 

Effects of Mechanical Stretch on Specific TM Gene Expression

Twenty-seven transcripts that code for ECM molecules or for molecules integrally involved in ECM regulation or in cell adhesion were upregulated, and two were downregulated, according to the stringent statistical and biological criteria described earlier (Table 1) . Several were elevated at all three time points, but most showed significant increases at only one or two time points. Several of those that did not reach the significance criteria were nonetheless clearly affected. As an example, fibronectin 1 was elevated at 24 hours based on our statistical significance criteria, but only 1.33-fold, and thus is labeled NS (not significant) in Table 1at this time point. 

Transcript levels for 42 genes involved in cytoskeletal function or in a variety of other forms of cellular regulation were increased, and 9 were decreased at one or more of the three time points (Table 2) . Transcript levels of 20 genes that are involved in transcription or translation were increased, and levels of 13 genes were decreased at one or more time points (Table 3) . Thirty-seven genes involved in cellular stress responses, cellular metabolism, or other cellular processes were upregulated, and five were downregulated at one or more time points (Table 4) . 

Effects of Mechanical Stretching on TM Genes Associated with Primary Open-Angle Glaucoma

We also looked specifically in the microarray data for changes in genes that have been identified as active in primary open-angle glaucoma, (i.e., myocilin/TIGR, optineurin and WDR36) ^{38 39 40} and for genes that reside in some of the chromosomal regions to which glaucoma loci have been mapped. Myocilin/TIGR (GLC1A) was not represented on this microarray, although it has been shown to be elevated in the TM early after mechanical stretch or elevated IOP. ^{18 21 23} Optineurin (GLC1E) and WDR36 (GLC1G) were both represented on our microarray. However, neither showed significant changes in expression with mechanical stretch at any of the three time points. Although positive relative fluorescence was observed for both transcripts, neither was expressed at sufficiently high levels in the TM under our culture conditions, with or without stretch to reach the very stringent expression level cutoff that we used as part of our biological significance criteria. 

The chromosomal location of each gene that reached both statistical and biological significance in our studies is included in the last columns in Tables 1 2 3 and 4 . Analysis of the actual chromosomal location of each possibly relevant gene relative to the markers used to map these glaucoma loci as localized on the most recent human chromosomal maps, showed that most of the changed genes in Tables 1 2 3 and 4are not actually within any of the mapped glaucoma loci. A summary of changed genes that are located within several mapped loci is shown in Table 5 . None were within the GLC1B, GLC1C, GLC1D, GLC1F, or GLC1G loci. ^{40 41 42 43 44} Several changed genes were identified in some of the other loci that have been mapped but not named, as indicated in Table 5 . ^{45 46 47}  

Alternative Analyses of Genes Affected by Mechanical Stretch in Microarrays

Quantitative RT-PCR was used to evaluate mRNA levels at all three time points of 20 of the genes that were elevated, decreased, or unaffected by stretch in the microarray analysis. Several examples (i.e., metallothionein 1R, tenascin C, MMP-15, SPARC and mimecan transcript levels measured by microarray and qRT-PCR) are compared at select times after stretching in Figure 2 . Some of the other genes for which mRNA levels were compared by qRT-PCR, included MMP-2, MMP-14, and TIMP-2, which were not changed (data not shown). These also showed good agreement between the two methods. Although the exact changes (x-fold) were seldom identical when the microarray and qRT-PCR were compared, all showed similar responses to stretching by both methods. 

The fibronectin microarray results were also compared with results from qRT-PCR and from Western immunoblots at 24 hours after stretching (Fig. 3) . The microarray values for fibronectin at 24 hours showed a 1.33-fold increase (Fig. 3C) . Although this reached the level of high statistical significance by SAM, it did not achieve the cutoff filter level of a >1.5-fold increase and is listed as NS in Table 1 . The results of the comparison of stretch and control cells evaluated by qRT-PCR (Fig. 3D)and by Western immunoblot (Figs. 3A 3B)show similar or larger increases in mRNA and protein levels. 

Several other sets of fibronectin PCR primers were used to look for possible changes in mRNA splicing with stretch (Fig. 4) . One pair of primers, one in the 12th and one in the 14th fibronectin type III domains, were used to look for the presence of the 13th type III domain, EIIIA (Fig. 4) . Only the smaller (337-bp) PCR product in which this domain was spliced out was detectable in stretched (S) and in nonstretched control (C) TM cells. A primer pair was made in the seventh and ninth fibronectin type III domains to look at splicing of the eighth type III domain, EIIIB. Although at least 90% of the transcripts had EIIIB spliced out and gave the 406-bp PCR product, approximately 10% of the transcripts gave the 678-bp PCR product with the EIIIB domain spliced in. This ratio did not change significantly with stretching. In the fibronectin variable region within the 17th type III domain, often referred to as the connecting segment (IIICS) domain, both variant (V)1 and V3 are often alternatively spliced. We made a pair of primers in the 16th type III domain matched with one in the V2 domain to look for the V1 domain, and a pair of primers in the V2 domain matched to one in the 18th type III domain to look for the V3 domain. The V2 domain is present in all the known splice variants containing either of the other variable domains. Stretched cells expressed exclusively a splice variant that included V1 and V3, giving, respectively, the 294- and the 264-bp PCR products. Nonstretched control TM cells, however, expressed approximately 70% of transcripts containing V1, V2, and V3 and 30% containing V2 but without V1 and V3—that is, they gave PCR products of only 219 and 171 bp, respectively. When splice variants were evaluated at the other two time points (i.e., at 12 and 48 hours; data not shown), the same patterns noted at 24 hours were observed. 

Western immunoblots at 24 and 48 hours showed tenascin C increases (Fig. 5)that are compatible with the microarray data (Table 1)and with the qRT-PCR data (Fig. 2) . Western immunoblots on several other proteins (data not shown), also showed expression patterns compatible with the microarray data. 

Discussion

Only 155 of approximately 8000 genes met our very stringent biological and statistical significance criteria for change in mRNA levels with stretching at one or more time points (Tables 1 2 3 4) . This number is likely to be an underestimate of the total number of affected genes, but the confidence that these genes changed expression levels in a biologically significant manner is high. Our selection criteria, requiring an increase of at least 1.5-fold or a decrease of 50%, seems to provide a reasonable compromise between including changes that are not really of biological significance and excluding changes that are. Requiring either the control or the stretched cellular expression levels to be several standard deviations above the subtracted background also seems reasonable, but is somewhat arbitrary. The biological relevance of the absolute abundance of a transcript, as roughly approximated by the relative fluorescence levels on the microarray and of a given x-fold change in mRNA levels is most certainly very gene specific and highly dependent on the specific cellular context. Additional variables like translational efficiency, protein half-life, posttranslational modifications, and the functional and biological efficiency of each protein molecule further complicate selection of these criteria. 

The 8000 genes on this microarray represent approximately 25% of the human genome. Although it seems possible that a few of the porcine probe sequences do not hybridize with high affinity to the human cDNAs spotted on the microarrays, this number is probably small. Because human and porcine sequences are generally similar, microarray hybridization conditions are of only moderate stringency, and both the labeled porcine probes and the spotted human cDNAs are several hundred base pairs in length, lack of cross-species hybridization should be minimal in these studies. This selected subset of 126 increased and 29 decreased mRNAs should provide useful insights into this homeostatic process. 

The genes that were changed by stretching displayed varied temporal patterns, with some changing at only one time point and others at two or all three points. One gene, IGF-binding protein 4 proteinase, was elevated 1.5-fold at 12 hours, not significantly changed at 24 hours, and significantly decreased (to 0.54-fold) at 48 hours. This temporal variation in gene expression is not surprising and suggests that the TM cell response to stretching is both complex and intricately coordinated. The distribution of the changes suggests a bias favoring only a few gene functional groups. Genes involved in ECM, cytoskeleton, or stress responses or in their regulation comprised a disproportionately large fraction of those we identified. The genes in this microarray are biased toward genes with known functions and include a wide representation of genes involved in most major biological processes. A fairly predictable and significant number of genes involved in transcription, transcriptional regulation, translation, or overall cellular regulation were significantly affected by stretching. Perhaps not too surprisingly, few genes involved in apoptosis, cellular proliferation, most aspects of cellular metabolism, or most other major cellular functions were affected. Stretching is presumably a normal homeostatic adjustment signal requiring only a moderate and focused response from these cells. 

In the current literature, microarray and cDNA library studies of human TM cells subjected to elevated pressures in perfused organ culture are somewhat comparable to our results. ^{22 24 48} The TM cells in these studies, which mostly involved experimental conditions different from ours, were probably responding to mechanical stretching that is functionally somewhat similar to the process we used. Matrix Gla protein, several metallothioneins, alpha B crystallin, alpha tubulin, transgelin, chaperonin-containing TCP1, and periostin were among the genes showing similar changes. Because of the very complex structural organization of the cells and the ECM within the TM in vivo, the relative degree to which different TM cells are exposed to stretching and distortion with increasing IOP is difficult to predict. It seems probable that each TM cell will experience different degrees of stretching and distortion with elevated IOP. In our cell culture stretch model, more uniformity is likely to be attained. However, different regions of the membranes in our model may also experience different degrees of stretch/distortion. We estimate that many of the cells in our model are experiencing degrees and types of stretching and distortion that are similar to that of many of the cells in the TM in vivo. However, it is very clear that additional detailed biophysical analysis of the TM is needed to clarify this contention. 

In terms of our working hypothesis of IOP homeostasis, the changes in ECM or ECM-related genes listed in Table 1are of particular interest. In addition to the initiation of ECM turnover by the concerted action of MMP-2, TIMP2, and MMP-14, ^{14 28} subsequent biosynthetic replacement of the degraded ECM components is likely to be an integral aspect of the homeostatic IOP adjustment. This probably entails modifying the composition or organization of the ECM to change the outflow resistance and thus modulate IOP. One group of ECM genes that are affected by stretching includes: NELL2, tenascin C, SPARC, fibronectin, laminin γ1 chain, and collagen XIV. A common feature of this group is that they are all modular matricellular ECM proteins composed of numerous repeat domains containing motifs, such as EGF-like, calcium-binding EGF-like, thrombospondin 1, fibronectin type III, von Willebrand factor C, heparin-binding or integrin-binding RGD motif. ^{49 50 51 52 53 54 55 56 57 58 59 60} Domains of these types commonly serve as specific binding cassettes for protein–protein, protein–glycosaminoglycan, or protein–cell interactions and function in ECM and tissue structure and organization. Their elevation during stretching is likely to be involved in maintaining and facilitating the tissue and ECM reorganization associated with the ECM turnover process initiated by the MMPs. Because they bind glycosaminoglycans (GAGs) and proteoglycans, which are thought to provide at least a portion of the outflow resistance, ^{3 4 61} they could also directly affect outflow by changing resistance component orientation. 

The increase in fibronectin levels and the splicing changes, which increase the fraction of the protein that contains V1 and V3 domains, are intriguing. Perfusion of anterior segment organ cultures with the second heparin binding (Hep II) fragment of fibronectin—the 14th to 16th type III domains as indicated in Figure 4 —reversibly increases outflow facility. ⁵⁷ In another tissue, it has been shown that alternative splicing of the V1 and V3 domains affect several specific biological activities of the adjacent Hep II fragment without affecting other activities. ⁵⁶ Fibronectin has an RGDS cell-binding site in the 11th type III domain that binds to α5β1 integrins (Fig. 4) . An α4β1 integrin-binding site is found in the distal portion of the Hep II region. In the alternatively spliced variable regions of IIICS, V1 contains an LDV and V3 contains an REDV, both of which are also α4β1 integrin-binding motifs. ^{62 63} Thus, TM cells switch from a mix of splice variants, with and without these two sites, to exclusively expressing the form that contains these two additional cell-binding motifs. In addition, the V2 domain of fibronectin contains a GAG-binding site, and these splice variants may impact binding to CD44 and syndecan 2 (both discussed later). Although we did not see changes in fibronectin EIIIA or EIIIB exon splicing with stretching, we detected very low levels of EIIIB in both stretched and control cells. A previous report did not detect any of either of these exons in serum-free control TM cells, although both were detected after TGF-β2 or serum treatment. ⁶⁴  

Of interest, laminin γ1 was increased 1.5-fold at 12 hours, but α2, α4, α5, β1, and the laminin receptor 1 were totally unaffected at all three time points. The laminins are a central component of cellular basement membranes, acting as scaffolds for the recruitment of other ECM components. ⁶⁵ Because laminins 1 to 15 are different heterotrimeric combinations of the α1 to 5, β1 to 4, and γ1 to 3 subunits, an increase in γ1 may reflect a partial shift from one laminin form to another, ⁵⁸ at a time when the ECM is undergoing remodeling and change. The γ1-subunit of laminin is also involved in binding to nidogen and in polymer formation. ⁶⁶ Although the primary cell-binding sites on laminin are in the laminin α-subunit, cell-binding sites have been identified on the γ1 subunit of laminin. ^{67 68 69} Based on relative fluorescence intensities in our microarrays, the α2 subunit was expressed at low to negligible levels, β1 only at moderately low levels; but α4 and α5, γ1, and laminin receptor 1 were all expressed at relatively high levels by the TM. 

A second group of ECM genes that changed expression with stretching includes several proteoglycans, some of which may serve a direct role in outflow resistance. ^{3 4 6 61} Chondroitin sulfate proteoglycan 4, fibromodulin, biglycan, syndecan 2, and the part-time proteoglycan and hyaluronan GAG receptor, CD44, increased with stretching, whereas mimecan decreased. Presumably, one likely way to adjust the outflow resistance in response to mechanical stretching would be to adjust the proteoglycan/GAG levels or composition in the TM’s ECM. Although it is tempting to speculate on the molecular mode by which increasing one or more of these proteoglycans or of decreasing mimecan, could decrease the outflow resistance, more information is needed to understand the process. Changes in the GAG side chains are also probable modifiers of the outflow resistance. 

The increase in CD44, the hyaluronan receptor, is very likely to be important in this process. A relationship between hyaluronan levels and the trabecular outflow resistance is generally accepted. ⁷⁰ Several recent studies have demonstrated the involvement of CD44 in TM cellular function and have provided hypotheses explaining relationships with the outflow resistance. ^{71 72} CD44 is also integrally involved and interactive with MMP-2 and -14, ^{73 74 75} both of which are upregulated at the translational but not the transcriptional level in TM cells by mechanical stretching. ^{14 28} CD44 exists in forms, with and without GAG side chains, and the form with chondroitin–dermatan sulfates binds to collagen XIV, which is also increased with stretching. 

Syndecan 2, a transmembrane heparan sulfate proteoglycan, ^{76 77} was upregulated at 24 hours (Table 1) . It interacts with α5β1 integrin in cellular signaling and with the Hep II, V1, and V2 regions of fibronectin. This upregulation also affects cytoskeletal organization in an ezrin-dependent step via Rho A GTPase activation. ^{78 79} Syndecan 2 is phosphorylated on two C-terminal tyrosines by the kinase domain of EphB2 receptors as a step in signaling to the cytoskeleton. ⁷⁷ Although EphB2 levels were not upregulated, its ligand, ephrin-B2, was upregulated by stretching. Thus, several proteins that have important interactions with each other are changed, further increasing the relevance of this process. CD44 also contains a cytoplasmic ezrin-binding domain, linking it to this same signaling system and to the Rho A-Rho kinase–mediated cytoskeletal regulation. ^{80 81 82 83} Therefore, the syndecan 2, ephrin-B2, and CD44 upregulation by stretching may be closely linked in maintaining the TM’s ECM and may be involved in, among other events, the Rho A–cytoskeletal modulatory changes, which also occurred with mechanical stretching of TM cells (Table 2) . 

The cytoskeletal changes observed (Table 2)involve components of all three filament systems—microfilaments, microtubules, and intermediate filaments—which suggests significant cross-talk between systems. ⁸⁴ Early cytoskeletal changes after mechanical stretching of TM cells have been reported, ¹⁵ and sustained responses and long-term differences can be expected. Agents that manipulate the TM cell cytoskeleton have been shown to affect outflow facility. ^{85 86 87 88 89} Whether the cytoskeletal changes are a direct cause or an effect of the ECM changes and outflow resistance adjustments remains unclear. 

Several other intriguing gene expression changes are notable, such as increases in the chemokines, metallothionines, and metastasis-associated protein 1. The magnitude of some of these changes suggests important, if only partially understood, regulatory processes. Several metallothionein mRNAs increase from low or negligible levels to quite high levels, increasing between 20- to more than 100-fold at one time point. Functions of these genes in other tissues include heavy metal, particularly zinc, detoxification ⁹⁰ and homeostasis. ⁹¹ This suggests that TM cells are responding to elevated or released zinc or to oxidative stress in association with the stretching. ⁹² A zinc transporter and several other stress genes are also induced. The several chemokine ligand increases and the large metastasis-associated 1 increases are similarly intriguing and similarly enigmatic. 

Although the number of genes with expression levels that are significantly changed by mechanical stretch is not large, the potential involvement of many of them in maintaining and adjusting the TM’s ECM and putatively the outflow resistance is likely. Understanding this complex process that appears to be responsible for maintaining IOP homeostasis clearly requires additional studies focused on the function of these proteins in outflow pathway biology. 

 Supported by National Institutes of Health Grants EY003279, EY008247, and EY010572 and by grants from the Glaucoma Research Foundation (San Francisco, CA), Research to Prevent Blindness, and Alcon Labs (Fort Worth, TX).

 Submitted for publication January 21, 2005; revised April 11, 2005; accepted April 22, 2005.

 Disclosure: V. Vittal, None; A. Rose, None; K.E. Gregory, None; M.J. Kelley, None; T.S. Acott, Alcon Labs (F)

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Figure 1.

 

Typical R-I plot after Lowess normalization. All the 24-hour stretch and control data from the SMC8400 chip, which included three completely separate experiments with two chips for each experiment and with two spots per chip for each gene (approximately 192,000 data points after individual local background subtractions), were subjected to Lowess normalization in the software (GeneSpring; Silicon Genetics, Redwood City, CA). The means of these normalized stretch and control data were then plotted, as indicated on the axes.

Table 1.

 

Genes Involved in ECM, ECM Regulation, or Cell Adhesion

x-Fold (Stretch/Control)					Rel Flu Intensity	Gene Name, Characteristics or Functions	GenBank ID	Location
12 h	24 h	48 h
7.165	NS*	NS	815	NEL-like 2; NELL2; ECM protein	NM_006159	12p13.11-q13.12
2.59	1.924	1.5	10535	Tenascin C (hexabrachion)	NM_002160	9q33
1.68	1.964	2.417	14907	SPARC, secreted protein, acidic, cys-rich (osteonectin)	NM_003118	5q31.3-q32
1.502	NS	1.5	17450	Fibronectin 1	NM_054034	2q34
1.621	NS	NS	1222	Laminin, gamma 1 (formerly LAMB2)	NM_002293	1q31
2.365	NS	NS	8591	Collagen 1 alpha 2	NM_000089	7q22.1
NS	1.59	NS	10759	Collagen V alpha 1	NM_000093	9q34.3-q34.3
3.252	NS	NS	4630	Collagen XIV alpha 1	NM_021110	8q23
1.769	NS	NS	12409	Chondroitin sulfate proteoglycan 4	NM_001897	15q23
1.62	1.718	1.646	14499	Fibromodulin, small Leu-rich proteoglycan	NM_002023	1q32
1.613	NS	1.5	15045	Biglycan, small Leu-rich proteoglycan	NM_001711	Xq28
NS	1.82	NS	10516	CD44, hyaluronan receptor	NM_000610	11p13
NS	1.514	NS	9803	Syndecan 2, transmembrane heparan sulfate proteoglycan	NM_002998	8q22-q23
NS	1.57	NS	1517	Ephrin-B2, EphB receptor ligand	NM_004093	13q33
1.63	NS	NS	737	Mucin 2; hypothetical protein DRAPC1	NM_002457	11p15.5
2.684	NS	NS	6881	Matrix metalloproteinase 15	NM_002428	16q13-q21
1.525	NS	NS	1529	Matrix metalloproteinase 16	NM_005941	8q21
NS	2.139	NS	1658	Plasminogen activator, urokinase	NM_002658	10q24
2.412	1.525	1.5	8797	Plasminogen activator inhibitor type 1B	NM_006216	16q12.2
1.818	NS	NS	5045	Plasminogen activator inhibitor type 1A	NM_033011	8p12
9.527	NS	NS	631	Growth differentiation factor 15; TGF beta/BMP family	NM_004864	19p13.1-q13.2
3.719	NS	3.053	5076	Endoglin; TGF beta receptor complex protein	NM_000118	9q33-q34.1
NS	1.925	NS	5323	Latent TGF beta binding protein 2	NM_000428	14q24
2.525	2.544	NS	9356	Matrix Gla protein; matrix calcification regulator	NM_000900	12p13.1-p12.3
NS	1.75	NS	11553	CTGF, connective tissue growth factor	NM_001901	6q23.1
2.26	NS	NS	8074	Melanoma cell adhesion molecule, MUC 18, CD146	NM_006500	11q23.3
NS	1.69	NS	2443	VCAM1, vascular cell adhesion molecule 1	NM_001078	1p32-p31
NS	0.497	NS	30855	Mimecan, osteoglycin, osteoinductive proteoglycan	NM_014057	9p22
0.488	NS	NS	4130	Periostin, osteoblast specific factor 2, integrin ligand	NM_006475	13q13.3

 Rel Flu Intensity, relative fluorescence intensity.

*  NS indicates that it did not reach the cut-off level for both statistical and biological significance.

Table 2.

 

Genes Involved in the Cytoskeleton or in Cytoskeletal, and Other Cellular Regulation

x-Fold (Stretch/Control)					Rel Flu Intensity	Gene Name, Characteristics, or Functions	GenBank ID	Location
12 h	24 h	48 h
52.76	48.1	NS*	562	Metastasis-associated 1; histone deacylase complex	NM_004689	14q32.3
2.688	4.807	1.69	4233	Dynamin family of large GTP-binding/GTPase	NM_002462	21q22.3
2.025	1.806	NS	8244	Transgelin 2, SM22, calponin cytoskeletal domain	NM_003564	1q21-q25
1.646	NS	NS	13862	Transgelin 3, neuronal calponin, and SM22-like with EF-hand	NM_013259	3q13.2
NS	1.818	NS	2973	Keratin 10	NM_000421	17q21
3.87	4.01	1.7	4828	Vimentin, intermediate filament protein	NM_003380	10p13
2.533	1.813	1.5	9945	Tubulin, alpha 1	NM_006000	2q35
1.835	NS	NS	13397	Beta 5 tubulin	NM_178014	6p21.33
1.61	NS	NS	21937	Actin, gamma 2, smooth muscle, enteric	NM_001615	2p13.1
NS	1.556	NS	1438	BCR-related gene, RhoGAP/RhoGEP, Rho/Rac activator	NM_021962	17p13.3
NS	1.69	NS	22000	RabGAP/TBC, EVI5, ecotropic viral integration site 5	NM_005665	1p22
NS	1.621	NS	4891	Rho/rac guanine exchange factor (GEF) 2	NM_004723	1q21-q22
1.663	NS	NS	8080	RAB6A, Ras family GTPase, retrograde Golgi to ER	NM_002869	11q13.3
1.951	NS	NS	3775	Rho GDP dissociation inhibitor (GDI) beta	NM_001175	12p12.3
NS	1.554	NS	3510	G1 to S phase transition 2, peptide chain release factor	NM_018094	Xp11.23-p11.21
NS	1.532	NS	6893	FER1L3, myoferlin, Ca-mediated membrane fusion	NM_013451	10q24
NS	1.682	NS	4146	Pro-rich coiled-coil, enabled homolog (Drosophila)	NM_018212	1q42.12
5.45	7.437	2.26	1751	Dihydrodiol dehydrogenase 1: prostaglandin redox	NM_001353	10p15-p14
5.4	NS	NS	2216	Sjögren syndrome antigen B (autoantigen La)	NM_003142	2q31.1
5.07	NS	NS	1311	Chemokine (C-C motif) ligand 2 (MCP1)	NM_002982	17q11.2-q21.1
4.37	11.55	NS	5484	Chemokine (C-C motif) ligand 7 (MCP3)	NM_006273	17q11.2-q12
3.714	6.243	NS	6219	Chemokine (C-C motif) ligand 13 (MCP4)	NM_005408	17q11.2
3.228	1.67	NS	2557	Chemokine (C-C motif) ligand 11b (eotaxin-1)	NM_002986	17q21.1-q21.2
NS	2.126	NS	1594	Angiopoietin-like 4, epithelial cell apoptosis inhibitor	NM_016109	19p13.2
NS	1.709	NS	3761	TNF alpha-induced protein 2	NM_006291	14q32.32
2.812	NS	NS	6781	Receptor type protein tyrosine phosphatase-N	NM_002846	2q35
NS	1.556	NS	931	Lyn, Src Tyr kinase family; v-yes-1 Yamaguchi related	NM_002350	8q13
4.925	NS	NS	4969	Tyrosylprotein sulfotransferase 2	NM_003595	22q12.1
1.867	1.67	NS	5305	SH2-B (phospho Tyr; PH domain, SH3/SH2 adaptor)	NM_015503	16p11.2
1.844	NS	NS	2508	PDGF receptor alpha	NM_006206	4q12
2.626	NS	NS	8489	EGF receptor related, EGF activating proteinase	NM_022450	16p13.3
2.488	NS	NS	6934	Insulin-like growth factor-binding protein 2	NM_000597	2q33-q34
2.157	NS	NS	4976	Erythropoietin receptor (tyrosine phosphorylated)	NM_000121	19p13.3-p13.2
1.676	NS	NS	272	Hypothetical protein with phospho-Tyr binding domain	NM_017933	2q36.3
2.015	NS	NS	350	dsRNA binding protein with WW pro-rich bind domain	NM_022720	22q11.2
1.91	2.846	1.5	13799	Immediate early response 3, stretch NF kappa B like	NM_003897	6p21.33
3.259	1.847	NS	2076	Sterol carrier protein 2, PI transfer and distribution	NM_002979	1p32
1.793	NS	NS	1291	Proteasome (macropain) activator subunit 2 (PA28 beta)	NM_002818	14q11.2
1.581	1.594	NS	15831	Cathepsin B, lysosomal Cys proteinase	NM_001908	8p22
1.592	NS	NS	15996	Cathepsin D, lysosomal aspartyl proteinase	NM_001909	11p15.5
1.58	NS	NS	722	Prostate proliferative shutoff associated protein	NM_015032	13q12.3
1.516	NS	0.54	2572	Pregnancy-associated protein A, IGFBP4 Zn proteinase	NM_002581	9q33.2
NS	0.47	NS	359	Rho-GTPase activating protein 10	NM_020824	10p12.1
NS	0.486	NS	2134	SOCS box-containing WD repeat protein SWiP-1	NM_015626	17q11.1
NS	0.468	NS	474	Chemokine (C-X-C motif) ligand 12	NM_199168	10q11.1
NS	0.413	0.41	7373	14-3-3 zeta/delta, PKC and monooxygenase activator	NM_003406	8q23.1
0.481	NS	NS	13332	ANK, inorganic pyrophosphate transport regulator	NM_054027	5p15.1
0.468	NS	NS	1245	NGF receptor (TNFRSF16) associated protein 1, adaptor	NM_014380	Xq22.2
0.467	NS	NS	1295	Replication protein A2, DNA damage repair and tumor suppressor	NM_002946	1p35
0.426	NS	NS	15390	Platelet-derived growth factor receptor-like (extracellular)	NM_006207	8p22-p21.3

 Abbreviations are as defined in Table 1 .

Table 3.

 

Genes Involved in Transcription or Translation Regulation Affected by Mechanical Stretch

x-Fold (Stretch/Control)					Rel Flu Intensity	Gene Name, Characteristics, or Functions	GenBank ID	Location
12 h	24 h	48 h
2.41	2.152	NS*	5724	Jun B transcription factor	NM_002229	19p13.2
NS	2.118	NS	2541	Interferon regulatory factor 1, transcriptional repressor	NM_002198	5q31.1
NS	1.816	NS	1521	NF kappa B, 1 (p105)	NM_003998	4q24
NS	1.598	NS	19320	Zinc finger protein 26 (KOX 20) transcriptional regulator	NM_019591	12q24.33
NS	1.597	NS	15296	Zinc finger protein 205, transcriptional regulator	NM_003456	16p13.3
NS	1.521	NS	16161	Zinc finger protein 585B (41-like) transcription regulator	NM_152279	19q13.12
1.735	NS	NS	14076	Zinc finger protein 36, C3H type transcription regulator	NM_003407	19q13.1
1.703	NS	NS	13487	Zinc finger protein 184, Kruppel-like transcription factor	NM_007149	6p21.3
5.068	NS	NS	517	Nuclear factor (erythroid-derived 2); NF-E2	NM_006163	12q13
2.498	NS	NS	1141	Interferon-stimulated ubiquitin-like transcription factor	NM_005101	1p36.33
2.23	NS	NS	924	Chromobox homolog 5 (CBX5), HP1 alpha homolog	NM_012117	12q13.13
2.061	NS	NS	752	HOX 12, pre-B-cell leukemia transcription factor 2	NM_002586	6p21.3
2.017	2.268	1.511	11353	Forkhead box F1 (FOXF1), FREAC-1 transcription factor	NM_001451	16q24
1.773	NS	NS	15716	C-terminal binding protein, transcriptional corepressor	NM_001328	4p16
1.769	NS	NS	332	Sterol regulatory element-binding transcription factor 2	NM_004599	22q13
1.67	1.78	NS	1429	Pirin, iron-binding nuclear NFI/CTF1 interacting protein	NM_003662	Xp22.2
1.826	NS	NS	14672	mRNA cleavage and polyadenylation-specific factor 6	NM_007007	12q15
1.592	NS	NS	3397	KIAA1404 protein, helicase family, transcription factor	NM_021035	20q13.13
1.877	1.72	1.5	13638	Ubiquitin and ribosomal protein S27a, c-term extension	NM_002945	2p16
1.545	NS	NS	14877	Eukaryotic translation elongation factor 2	NM_001961	19pter-p12
NS	0.491	NS	1425	OVN6-2, zinc finger protein 24 (KOX 17)	NM_006965	18q12
NS	0.448	NS	9374	PBX1, homeobox gene, transcription factor	NM_002585	1q23
NS	0.473	NS	7706	Sp3 transcription factor	NM_003111	2q31
NS	0.442	NS	1631	Histone H3 methyltransferase, SET domain protein 7 (SET7)	NM_030648	4q28
0.451	NS	NS	1291	Early growth response 1 (ERG1) transcription factor	NM_001964	5q31.1
0.425	NS	0.37	2069	Transcription factor 4, beta catenin interacting protein	NM_003199	18q21.1
NS	NS	0.5	3104	RNA polymerase II A	NM_000937	17p13.1
NS	0.451	0.411	782	Cyclophilin A, peptidyl-prolyl cis-trans isomerase	NM_021130	7p13-p11.2
NS	0.38	NS	492	EIF-3, subunit 6 interacting protein	NM_016091	22q
NS	0.289	NS	1416	EIF-2B	NM_003908	20pter-p12
NS	0.327	0.37	3617	CGI-90 protein	NM_016033	8q21.3
0.5	NS	NS	3511	Musashi homolog 2, heterogeneous nuclear RNP	NM_138962	1q23.2
0.493	NS	NS	9157	Transcript release factor for paused polymerase I	NM_012232	17q21.2

 Abbreviations are as defined in Table 1 .

Table 4.

 

Genes Involved in Stress, Metabolism and Other Processes That Are Affected by Mechanical Stretching

x-Fold (Stretch/Control)					Rel Flu Intensity	Gene Name, Characteristics, or Functions	GenBank ID	Location
12 h	24 h	48 h
114.23	82	48.51	354	Metallothionein 1G	NM_005950	16q13
106.98	80.9	41.498	361	Metallothionein 1R, F, (1L, II)	AF348998	16q12.2
98.44	90.25	22.991	408	Metallothionein 1H	NM_005951	16q13
92.14	75.93	31.466	439	Metallothionein 1X (1L)	NM_005952	16q13
89.77	77.95	40.699	511	Metallothionein 1B	NM_005947	16q13
3.341	NS*	NS	518	Superoxide dismutase 2, mitochondrial	NM_000636	6q25.3
2.579	NS	NS	825	Cytochrome P4501B1 (CYP1B1; GLC3A)	NM_000104	2p21
NS	2.535	NS	3813	Glutathione peroxidase 2 (gastrointestinal)	NM_002083	14q24.1
NS	1.615	NS	24808	Crystallin, alpha B	NM_001885	11q22.3-q
1.743	NS	NS	13894	Peroxiredoxin 2, mitochondrial protein	NM_181738	19p13.2
NS	1.754	NS	20217	Legumain, Asp-specific Cys endopeptidase	NM_005606	14q32.1
NS	1.739	NS	1806	ATP-dependent 26S proteosome regulatory subunit	NM_152747	7p15.1
NS	1.721	1.66	4354	Ubiquitin ligase, atrogin-1, F-box atrophy protein 32	NM_058229	8q24.13
NS	1.634	NS	2836	BACE2, membrane-associated Asp proteinase	NM_012105	21q22.3
4.0172	NS	NS	312	Amino acid/polyamine transporter, family II	NM_017728	17q25.1
2.93	2.881	NS	1589	Zinc transporter, solute carrier family 30 A1	NM_021194	1q32-q41
1.529	NS	NS	1384	Potassium voltage-gated channel, shaker-related 1	NM_000217	12p13
NS	NS	2	2583	Stearoyl-CoA desaturase (delta-9-desaturase)	NM_005063	10q23-q24
NS	NS	1.532	8780	SRY-box 5; protein-O-mannosyltransferase 1	NM_007171	9q34.1
NS	1.713	NS	338	Delta aminolevulinate synthase 1	NM_000688	3p21.1
NS	1.624	NS	2404	HesB-like domain; inorganic ion transport and metabolism	NM_030940	9q21.33
NS	1.586	NS	3277	Mitochondrial proteolipid	NM_004894	14q32.33
NS	1.548	NS	2834	Isopentenyl- or farnesyl-diphosphate delta isomerase	NM_004508	10p15.3
2.33	1.616	NS	11655	Phosphogluconate dehydrogenase	NM_002631	1p36.3-p36.13
2.3	1.601	NS	2715	Glucan (1,4-alpha-), branching enzyme 1	NM_000158	3p12.3
2.048	1.995	NS	1055	S-adenosylhomocysteine hydrolase	NM_000687	20cen-q13.1
2.042	NS	NS	12863	Aldolase C, fructose-bisphosphate	NM_005165	17cen-q12
2.002	2.601	1.904	755	Stearoyl-CoA desaturase (delta-9-desaturase)	NM_005063	10q23-q24
1.849	NS	NS	12468	Lactate dehydrogenase A	NM_005566	11p15.4
1.576	NS	NS	1193	Phosphoribosylaminoimidazole carboxylase	NM_006452	4pter-q21
1.374	NS	NS	1156	CTP synthase	NM_001905	1p34.1
1.765	NS	1.5	3259	Complement component 1q gamma	NM_172369	1p36.11
9.849	NS	NS	1587	Natural killer cell group 7 transmembrane protein	NM_005601	19q13.41
5.635	NS	NS	4370	PQ domain protein, probable electron transporter	NM_025078	18q23
2.66	NS	NS	1771	Timora, 10 transmembrane domain leu zipper protein	XM_371891	7p14.3-p14.2
1.566	NS	NS	8114	Pro-rich with poly Leu/Ile and Glu domains	NM_014745	16q24.3
1.564	NS	NS	923	Hypothetical protein RP4-622L5	NM_019118	1p36.11-p34.2
NS	0.484	NS	14188	Chaperonin-containing TCP1, subunit 4 (delta)	NM_006430	2p15
0.474	NS	NS	429	Transcription elongation factor A (SII)-like 4	NM_024863	Xq22.2
0.489	NS	NS	635	Methylmalonyl CoA epimerase	NM_032601	2p13.3
NS	0.413	NS	688	Ribosomal protein L11	NM_000975	1p36.1-p35
0.468	NS	NS	2281	EST	R99690	4q12

 Abbreviations are as defined in Table 1 .

Table 5.

 

Stretch-Modified Genes and Mapped Primary Open-Angle Glaucoma Loci

Gene	Location	Markers	GenBank ID or Name
GLC1A	1q	NA	Myocilin/TIGR (not on this microarray but increased dramatically)
GLC1B	2cen-q13	D2S2161-D2S2264	None changed
GLC1C	3q21-q24	D3S3637-D3S3694	None changed
GLC1D	8q23	D8S1830-D8S592	None changed
GLC1E	10p14	NA	Optineurin (very low expression; 0.9, 0.8 & 1.2 fold at 12, 24 & 72 hr)
GLC1F	7q35-q36	D7S2442-D7S483	None changed
GLC1G	5q22-q23	D5S2084-D5S492	WDR36 (very low expression; 1.0, 1.48 & 1.65 fold at 12, 24 & 72 hr)
Other	14q11-12	D14S261-D14S121	NM_002818;
Other	9q22	D9S152-D9S1825	NM_002160; NM_002581; NM_030940
Other	20p12	D20S194-D20S911	NM_003908
Other	2q	D2S2188-D2S2178	NM_003142; NM_003111
Other	10p	D10S1477-D10S601	NM_003380; NM_020824

Figure 2.

 

Comparison of typical microarray and qRT-PCR analysis. Log base 2 plot of the ratio of stretch to control responses as analyzed by microarray compared with qRT-PCR is shown for several genes at the indicated time points. The positions of the cutoff points used for the microarray studies (a decrease to 50% or a 1.5-fold increase) are shown by the vertical lines and are labeled above the lines for reference.

Figure 3.

 

Effects of mechanical stretching on fibronectin mRNA and protein levels. Cells were stretched for 24 hours and cellular protein or total RNA extracted and analyzed. (A) Relative band density of scans of Western immunoblots from three separate experiments. The mean ± SD with paired t-test significance is shown. (B) A typical image of the Western immunoblot bands. (C) All 36 stretch and control data pairs from seven separate experiments at the 24-hour time point from all the SMC5700 and SMC8400 microarray chips were compared. The mean relative spot fluorescence intensities with standard deviations and significance from paired t-test are shown. The microarray stretch/control ratio at this time point was ∼1.3. (D) The results from 18 qRT-PCRs from two separate experiments with six different primer sets are shown with mean, standard deviations, and significance from paired t-test, as indicated.

Figure 4.

 

Effects of mechanical stretching on fibronectin mRNA splice variants. Cells were stretched for 24 hours and total RNA extracted and analyzed by RT-PCR, with several PCR primer sets. A diagram is shown with the domain structure of fibronectin 1 including the alternatively spliced exons EIIIB, EIIIA, and III CS containing variant regions V1, V2, and V3 as indicated. The position of PCR primers and full-length product sizes are indicated above the respective splice variants. The size of the exon variably spliced is shown below each exon. Agarose gel with ethidium bromide-stained PCR products from cells that were stretched (S) or controls (C) for 24 hours are shown, with markers as indicated. The position of the predicted bands, with (+) and without (−) the indicated spliced domains, are shown next to each gel.

Figure 5.

 

Comparison of tenascin C protein levels after 24 and 48 hours of stretching. Extracted protein was subjected to Western immunoblot analysis to determine tenascin C levels. The relative density of the tenascin C band on Western immunoblots is compared. Replicate numbers (n) from three separate experiments and significance (P) levels from paired t-tests are shown.