Jason H. Haga

Directional shear flow and Rho activation prevent the endothelial cell apoptosis induced by micropatterned anisotropic geometry

To study the roles of anisotropic cell morphology and directionality of mechanical force in apoptosis, the spreading of human umbilical vein endothelial cells (HUVECs) was constrained by growing on micropatterned (MP) strips of fibronectin (FN, 20 μg/cm2) with widths of 15, 30, and 60 μm on silicone membrane. Cells on 30- and 60-μm strips, like cells on a nonpatterned (NP) surface coated with FN, showed clear actin stress fibers with anchoring spots of phosphorylated focal adhesion kinase (p-FAK) and no significant apoptosis. On 15-μm strips, cells had few stress fibers, no p-FAK, and significant apoptosis. After seeding for 12 h, the cells were subjected to pulsatile shear stress (12 ± 4 dyn/cm2) parallel or perpendicular to MP strips, or kept under static condition. Parallel flow caused cell elongation with enhanced stress fibers and p-FAK, and a reduction in apoptosis, but perpendicular flow did not. The Rho inhibitory C3 exoenzyme abolished the effects of parallel flow. RhoV14, the constitutively active Rho, enhanced stress fibers and p-FAK, and prevented apoptosis of HUVECs on 15-μm strips under static condition. RhoV14 also reduced cell apoptosis under both parallel and perpendicular flows. Our results indicate that cell apoptosis can be modulated by changes in ECM micropatterning, anisotropic cell morphology, and mechanical forces. These extracellular microenvironment factors affect cell survival through alterations in Rho GTPase activity, stress fiber organization, and FAK phosphorylation.

Roles of MAP kinases in the regulation of bone matrix gene expressions in human osteoblasts by oscillatory fluid flow

We investigated the effects of oscillatory flow in regulating the gene expressions of type I collagen (COL1, the main component of human bone tissues) and osteopontin (OPN, the key gene for calcium deposition) in human osteoblast‐like (MG‐63) cells, and the roles of mitogen‐activated protein kinases (MAPKs) in this regulation. The cells were subjected to oscillatory flow (0.5 ± 4 dyn/cm2) or kept under static condition for various time periods (15 min, 30 min, 1 h, 2 h, 4 h, 8 h, and 16 h). Oscillatory flow caused significant up‐regulations of both COL1 and OPN gene expressions over the 16 h of study, and a transient activation of MAPKs was starting at 15 min and declining to basal level in 2 h. The flow‐induction of COL1 was blocked by an ERK inhibitor (PD98059) and reduced by a JNK inhibitor (SP600125), whereas that of OPN was abolished by PD98059. Analysis of the cis‐elements in the COL1 and OPN promoters suggests the involvement of transacting factors Elk‐1 and AP‐1 in the transcription regulation. The ERK inhibitor (PD98059) blocked Elk‐1 phosphorylation, as well as COL1 and OPN gene expression. The JNK inhibitor (SP600125) abolished c‐jun phosphorylation and COL1 expression. These results suggest that the flow‐induction of OPN was mediated through the ERK‐Elk1‐OPN pathway, and that COL1 was regulated by both the ERK‐Elk1‐COL1 and JNK‐c‐JUN‐COL1 pathway. J. Cell. Biochem. 98: 632–641, 2006.

DNA microarray study on gene expression profiles in co-cultured endothelial and smooth muscle cells in response to 4- and 24-h shear stress

Shear stress, a major hemodynamic force acting on the vessel wall, plays an important role in physiological processes such as cell growth, differentiation, remodelling, metabolism, morphology, and gene expression. We investigated the effect of shear stress on gene expression profiles in co-cultured vascular endothelial cells (ECs) and smooth muscle cells (SMCs). Human aortic ECs were cultured as a confluent monolayer on top of confluent human aortic SMCs, and the EC side of the co-culture was exposed to a laminar shear stress of 12 dyn/cm2 for 4 or 24 h. After shearing, the ECs and SMCs were separated and RNA was extracted from the cells. The RNA samples were labelled and hybridized with cDNA array slides that contained 8694 genes. Statistical analysis showed that shear stress caused the differential expression (p ≤ 0.05) of a total of 1151 genes in ECs and SMCs. In the co-cultured ECs, shear stress caused the up-regulation of 403 genes and down-regulation of 470. In the co-cultured SMCs, shear stress caused the up-regulation of 152 genes and down-regulation of 126 genes. These results provide new information on the gene expression profile and its potential functional consequences in co-cultured ECs and SMCs exposed to a physiological level of laminar shear stress. Although the effects of shear stress on gene expression in monocultured and co-cultured EC are generally similar, the response of some genes to shear stress is opposite between these two types of culture (e.g., ICAM-1 is up-regulated in monoculture and down-regulated in co-culture), which strongly indicates that EC–SMC interactions affect EC responses to shear stress.

PRAGMA-ENT: An International SDN testbed for cyberinfrastructure in the Pacific Rim: PRAGMA-ENT: An International SDN testbed for cyberinfrastructure in the Pacific Rim

The Pacific Rim Application and Grid Middleware Assembly (PRAGMA) is an international community of researchers that actively collaborate to address problems and challenges of common interest in eScience. The PRAGMA Experimental Network Testbed (PRAGMA‐ENT) was established with the goal of constructing an international software‐defined network (SDN) testbed to offer the necessary networking support to the PRAGMA cyberinfrastructure. PRAGMA‐ENT is isolated, and PRAGMA researchers have complete freedom to access network resources to develop, experiment, and evaluate new ideas without the concerns of interfering with production networks.

Identification of a Specific Inhibitor for the Dual-Specificity Enzyme SSH-2 via Docking Experiments on the Grid

The slingshot-2 (SSH-2) protein plays a significant role in different cell functions such as growth and movement. SSH-2 is a phosphatase protein that belongs to a unique class of enzymes called dual specificity phosphatases (DSP) that target the phosphothreonine and phosphotyrosine residues of mitogen-activated protein (MAP) kinases, which regulate cell growth. Because of this, it is of great interest to find specific inhibitors of DSPs such as SSH-2. Implementing an in silico platform to screen a sizable pool of chemical compounds against SSH-2 on the grid environment with the molecular docking software DOCK 6, several chemical compounds have been identified as potential inhibitors of SSH-2 activity. The issues of performing routine virtual screenings on the grid and possible improvements are also presented. The most promising inhibitor determined from standard and AMBER DOCK screenings was 2-amino-3-phosphonooxy-propanoic acid, which will be verified with wet bench testing.

Virtual Screening for SHP-2 Specific Inhibitors Using Grid Computing

SHP-2 is a protein tyrosine phosphatase (PTP) that plays an important role in many cellular functions such as development, growth, and death; thus SHP-2 has been hypothesized to play an important role in various diseases such as diabetes, neurodegeneration, and cancer. The importance of the individual roles of different PTPs is not well understood and this is complicated by the lack of specific inhibitors. In this study, we have utilized the multi-institutional PRAGMA Grid computation resources to virtually screen the ZINC 7 database using virtual docking software DOCK 6.2. Preliminary results suggest several SHP-2 specific inhibitors that can be further tested and validated under laboratory conditions. Complications during these multiple, virtual screenings on the grid as well as potential improvements are also discussed. These findings have future clinical significance in the creation of new drug therapies for the treatment of different diseases.

Bringing flexibility to virtual screening for enzymatic inhibitors on the grid

Virtual screening has become an important part of the drug discovery process. Grid computing facilitates this process by providing shared computational resources across different international institutions to run computationally intensive, scientific applications without the need for a centralized supercomputer. This study designed and implemented a flexible, scalable platform to perform a large virtual screening experiment on the PRAGMA grid testbed using the molecular docking simulation software DOCK 5.4. Using Opal OP to wrap DOCK as a grid service and PERL for data manipulation purposes, the ldquodruglikerdquo subset of the ZINC database, which contains 2,066,906 compounds, was successfully screened against the catalytic site of a protein tyrosine phosphatase. The screening required 11.56 days laboratory time and utilized 200 processors over 7 clusters. A ranked list of the best binding compounds to the phosphatase was generated and is currently being tested in biological applications for their efficacy and specificity.

Pulsatile equibiaxial stretch inhibits thrombin-induced RhoA and NF-κB activation

This study investigated interactions between the effects of mechanical stretch and thrombin on RhoA activation in rat aortic smooth muscle cells (RASMC). Equibiaxial, pulsatile stretch, or thrombin produced a significant increase in RhoA activation. Surprisingly, in combination, 30 min of stretch inhibited the ability of thrombin to activate RhoA. NO donors and 8-bromo-cGMP significantly inhibited thrombin-induced RhoA activation. Interestingly, the nitric oxide synthase (NOS) inhibitor L-NAME increased basal RhoA activity, suggesting that NOS activity exerts a tonic inhibition on RhoA. Stretching RASMC increases nitrite production, consistent with the idea that NO contributes to the inhibitory effects of stretch. Thrombin stimulates MAP kinase and NF-kappaB pathways through Rho and these responses were blocked by 8-bromo-cGMP or stretch and restored by L-NAME. These data suggest that stretch, acting through NO and cGMP, can prevent the ability of thrombin to stimulate Rho signaling pathways that contribute to pathophysiological proliferative and inflammatory responses.

Protein Structure Modeling in a Grid Computing Environment

Advances in sequencing technology have resulted in an exponential increase in the availability of protein sequence information. In order to fully utilize information, it is important to translate the primary sequences into high-resolution tertiary protein structures. MODELLER is a leading homology modeling method that produces high quality protein structures. In this study, the function of MODELLER was expanded by configuring and deploying it on a parallel grid computing platform using a custom four-step workflow. The workflow consisted of template selection through a protein BLAST algorithm, target-template protein sequence alignment, distribution of model generation jobs among the compute clusters, and final protein model optimization. To test the validity of this workflow, we used the Dual Specificity Phosphatase (DSP) protein family, which shares high homology among each other. Comparison of the DSP member SSH-2 with its model counterpart revealed a minimal 1.3% difference in output energy scores. Furthermore, the Dali Pair wise Comparison Program demonstrated a 98% match among amino acid features and a Z-score of 26.6 indicating very significant similarities between the model and actual protein structure. After confirming the accuracy of our workflow, we generated 23 previously unknown DSP family protein structure models. Over 40,000 models were generated 30 times faster than conventional computing. Virtual receptor-ligand screening results of modeled protein DSP21 were compared with two known structures that had either higher or lower structural homology to DSP21. There was a significant difference (p!0.001) between the average ligand ranking discrepancy of a more homologous protein pair and a less homologous protein pair, suggesting that the protein models generated were sufficiently accurate for virtual screening. These results demonstrate the accuracy and usability of a grid-enabled MODELLER program and the increased efficiency of processing protein structure models. This workflow will help increase the speed of future drug development pipelines.