Mechano-transduction And Transcription Networks In Vascular Cells Base On Proteomics

Vascular remodeling is the crucial pathological process during manydiseases such as hypertension and artherosclerosis. Studies have shownthat mechanical stress played an important role in the onset anddevolopment of vascular remodeling. It is significant to explore themolecular mechanism of the vascular remodeling and discover the keybiomarker and drug targets for the pathological research and clinicaltreatment of artherosclerosis.Using two dimensional electrophoresis (2-DE) and massspectrometry,43differentially expressed proteins between vasculartissues cultured under between normal (15dyn/cm2) and low (5dyn/cm2)shear stress were identified. Gene ontology and IPA were used to analyzethe functions and signal pathways of the above defferencially epressedproteins, and4probable signal networks related to shear stress wereinfered. Lamin A, LOX, Rack1, Rab28, etc were found as newmechano-sensitive proteins, whose expression and mechanism in themechano-induced vascular remodeling had not been reported. Then, theshear stress was exerted to the co-cultured vascular smooth muscle cells (VSMCs) and endothelial cells (ECs) by flow chamber system. Westernblotting was used to detect the expression of Lamin A and LOX underdifferent shear stress, and the result show that low shear stress inhabitedthe expression of Lamin A and increase the expression of LOX in ECsand VSMCs. Afterwards, RNA interference and recombination proteinwere used to verified some key nodes and edges related to Lamin A andLox in the predicted network.Phosphorylation/dephosphorylation cycling is one of the mostimportant modifications that regulate the activation of signal molecules.Therefore, in the following research, the time series profiles ofphosphorated proteins and the coresponding phosphorylated sites inVSMCs subjected to cyclic strain were investigated by stable isotopelabelling amino acid in cell culture (SILAC), chromatogram and massspectrometry. Then, the clustering, function and pathway analysis wereapplied to analyze the expression model, GO functions, signal pathwaysand phosphorylated network of the differential expressed phosphorylatedproteins in different time points. The results discovered new signalpathway which maybe participated in the mechano-transduction, andsuggested that cytoskeleton may directly sense mechanical stress,regulate many binding protein, and regulate cell function. It offered a newdirection of the research of mechano-sensor which transferredextracellular mechanical stress into intracellular biochemical signal. In order to further analyze the above proteomic data, discover morevaluable mechano-transduction network, especially the information oftranscription factors which regulate gene expression, we investigated newmethods, applied from large-scale microarray data, and used it to discovertranscriptionalnetwork based on the above proteomic data. First, weintroduced the averaged three-way mutual information (AMI3) andnetwork assisted regression algorithm, a new approach which could infertranscriptional network from large-scale microarray. The algorithm wasverified by E.coli and S.cerevisiae and human B cell data. Then, applyingthe AMI3and network assisted regression algorithm, the transcriptionalnetwork of human umbilical vein ECs was constructed, and thetranscriptional combined with signal transduction network in ECs werealso constructed based on the microarray and2-DE data of vascular cellsstimulated by low shear stress. This network, including both signaltransduction to transcriptional regulation, systematically describedmechano-transduction process of vascular cells.Furthermore, the graphlet interaction was introduced andcardiovascular disease genes were predicted. Our study found that thegraphlet interaction between disease genes and normal genes weresignificantly different. Accordingly, new score was calculated based onthe graphlet interaction to identify disease genes. Leave-one-outcross-validation was applied to evaluate the performance based on known disease genes in OMIM database. Compared with random walk andEndeavour, graphlet interaction obtained higher precision and stability.Using this method,12new cardiovascular diseases genes, such as NOS2and VEGFR1, were predicted.In summary, using proteomic analysis combined with computationalmethods, we constructed signal transduction and gene regulatory networkof vascular cells respond to mechanical stress, discovered new moleculeswhich were probable participated in mechano-transduction. Usingmolecular and biological experiments, part of the predicted molecules andthe regulatory relation were verified. This study provided new researchapproaches and direction for investigating the molecular mechanism ofvascular remodeling induced by mechanical stress, and suggestedpotential biomarker for diagnosis and treatment of cardiovasculardiseases including atherosclerosis.