Published on

  • Be the first to comment

  • Be the first to like this


  1. 1. Atherosclerosis is the build-up of plaque on the endothelial monolayer of vascular tissues resulting from physiologic injuries. The endothelial monolayer supplies the signal transduction interface for blood-borne mechanical and chemical stimuli. Endothelial signalling is regulated by hemodynamic forces, one of which is shear stress. Here we have applied a computational systems biology approach in order to investigate, elucidate and be able to predict the molecular shear stress response in endothelial cells. <ul><li>Endothelial cells: </li></ul><ul><ul><li>Monolayer between blood and arterial wall </li></ul></ul><ul><ul><li>Cell function regulated by physical forces </li></ul></ul>We have developed a continuous mechanistic model of 245 ordinary differential equations resolving in total the dynamics of more than 700 molecular reactions under fluid flow induced shear stress. The systems of equations is assembled by translating all biochemical interactions into ODEs by following definition: is described by Incorporating all existing knowledge into the model still fails to match published experimental results. There is still interactions and responses to stimuli that we do not understand. Focal adhesion kinase acts downstream of integrin receptors, however its activation seems to be much faster than the one of integrins. Fluid Shear stress Smooth Muscle cell Endothelial cells Fibroblast Intimal Layer Medial Layer Adventitial Layer Compressive stress Circumferential stress RAS C3G Graf Crk P P CAS GAP P FAK Vin PAX Rac SRC Dock180 Rap1 Vav1 SOS CSK Grb2 Fibronectin Integrin β chain Integrin α chain Focal complex PIPKiγ661 Talin <ul><li>Modulators of signalling: </li></ul><ul><ul><li>Focal complex formation </li></ul></ul><ul><ul><li>Engagement of Rho GTPases </li></ul></ul>2. Fatty Streak 3. Vulnerable Plaque 4. Advanced/ Unstable lesion/ plaque Rupture 1. Healthy <ul><ul><li>Pathogenesis of atherosclerosis </li></ul></ul>FAK- p PTP_PEST Paxillin-p Talin Fn Available pool of cytosolic paxillin-Fak v23, v33 v24, v34 v25, v35 v26, v36 v28, v38 v27, v37 v29, v39 v30, v40 v31, v41 v32, v42 Talin Fn Talin Fn FAK- p PTP_PEST Talin Fn Talin Fn Talin Fn Paxillin FAK Paxillin Paxillin-p Talin Fn FAK Paxillin SRC RPTPaP CSK SRC-p FAK p Paxillin p Talin FAK p Paxillin p Talin SRC Talin Talin Paxillin p FAK p SRC SRC-p PTPSrc V61 v62 v63, v68 v64, v69 v65 V66, v70 v67, v71 Fn Fn Fn Fn DAG PKCi PKC-Ca PKC-Ca-DAG PKCa basal PKCa GRB2 RPTPa RPTPaP degradation GRB2 RPTPa v44 v45 v46 v47, v54 PTPX1 v50, v51, v53 v52 v48, v49 synthesis v43 Shear Stress Calpain i Calpain a Calpastatin TalinInt TalinClv Calpain a Calpastatin Calpain a TalinInt Caex Ca++ v1 v2 v3 v4 degradation production degradation IKKi IKKaa IKKi PKCa v55, v56, v57 v58, v59, v60 NL-PLS, VIP CA PCA Clustering <ul><li>So far 7 published time-dependent experimental measurements of molecules have been matched: avb3, FAK, SRC, CAS, PKC, CRK and intracellular calcium dynamics. </li></ul><ul><li>FAK dynamics from the model initially failed to match published results. We predicted that FAK activation is indirectly affected by deformation of avb3. Reports have agreed with our hypothesis. Giannone et al , 2004. Has not been validated yet. </li></ul><ul><li>We predict that Src kinase is a modulator of negative feedback for focal complex formation by phosphorylation of integrin receptors and reduction of their affinity reaction rates for downstream targets. Scientific evidence supports our prediction. Frame MC, 2004 </li></ul>Reactions of Calcium, Calpain, Talin, Integrins, FAK, paxillin, Src, RPTPa and PKC An overview of the modelling approach. The process beings with the definition of the model system and end when predictions from the model match experimental data. Define Model System Collect Parameters Model Parameter Estimation Experimental Data (literature & in-house) Data Fitting Analysis Experimental approach Data Simulation Predictions Match No ? Yes ? Modelling approach – steps for formulation and validation Shear stress response in endothelial cells and disease Analyzing the dynamics of molecular interactions Hypotheses formed and following tests – an example Results and further analysis under work Model description – Interaction between molecules Fn Fn RAP1 Talin Resting ~85% Pre-active (Talin bound) Active ~10% Talin FAK SRC CAS CRK C3G Ca++ A deformation model is created to explain deviations of the model from experimental measurements. Simulations are run to test the influence of the new additions to the model. PECAM1 Further multivariate statistical and sensitivity analyses of simulation results are in process. Clustering, PCA, PLS and contribution analysis are sued to identify the molecular components and parameters that influence most the overall dynamic signature of the model. Pathway modules can also be identified according to their pattern of dynamic behaviour . After modifications the model predicts accurately the concentration of species (Integrins and FAK( both at steady state and after application of shear stress). Calcium dynamics. Biphasic character predicted. Mathematical modelling of the shear stress molecular response in endothelial cells Kostas Lykostratis, Marketa Zvelebil, Anne J Ridley Song Li et al , 1997 Tzima et al ,2001 Integrins Steady state – NO shear stress Applied shear stress (12dyn/cm ) 2 Basal Level, 10% of total Rap1 contribution ?? Activation boost after 5 minutes.…Why ?..How? FAK- p Paxillin-p FAK Paxillin