A comparative analysis of the bistability switch for platelet aggregation by logic ODE based dynamical modeling.

A kinetic description of the fragile equilibrium in thrombozytes regulating blood flow would be an important basis for rational medical interventions. Challenges for such a model include regulation by a complex bistability switch that determines the transition from reversible to irreversible aggregation and sparse data on the kinetics. A so far scarcely applied technique is given by the derivation of ordinary differential equations from Boolean expressions, which are called logic ODEs. We employ a combination of light-scattering based thrombocyte aggregation data, western blot and calcium measurements to compare three different ODE approaches regarding their suitability to achieve a data-consistent model of the switch. Our analysis reveals the standardized qualitative dynamical system approach (SQUAD) to be a better choice than classical mass action formalisms. Furthermore, we analyze the dynamical properties of the platelet aggregation threshold as a basis for medical interventions such as novel platelet aggregation inhibitors.

[1]  Ursula Klingmüller,et al.  Structural and practical identifiability analysis of partially observed dynamical models by exploiting the profile likelihood , 2009, Bioinform..

[2]  Thomas Dandekar,et al.  Time-resolved in silico modeling of fine-tuned cAMP signaling in platelets: feedback loops, titrated phosphorylations and pharmacological modulation , 2011, BMC Systems Biology.

[3]  Deepak L. Bhatt,et al.  Clinical Aspects of Platelet Inhibitors and Thrombus Formation , 2007, Circulation research.

[4]  J. Timmer,et al.  A Boolean view separates platelet activatory and inhibitory signalling as verified by phosphorylation monitoring including threshold behaviour and integrin modulation. , 2013, Molecular bioSystems.

[5]  Z. Ruggeri,et al.  Activation of Platelet Function Through G Protein–Coupled Receptors Platelets As Immune Cells: Bridging Inflammation and Cardiovascular Disease In Vivo Thrombus Formation in Murine Models Clinical Aspects of Platelet Inhibitors and Thrombus Formation Adhesion Mechanisms in Platelet Function , 2007 .

[6]  C. Gachet P2 receptors, platelet function and pharmacological implications , 2008, Thrombosis and Haemostasis.

[7]  U. Walter,et al.  Low angle light scattering analysis: a novel quantitative method for functional characterization of human and murine platelet receptors , 2011, Clinical chemistry and laboratory medicine.

[8]  Carol S. Woodward,et al.  Enabling New Flexibility in the SUNDIALS Suite of Nonlinear and Differential/Algebraic Equation Solvers , 2020, ACM Trans. Math. Softw..

[9]  Steffen Klamt,et al.  Transforming Boolean models to continuous models: methodology and application to T-cell receptor signaling , 2009, BMC Systems Biology.

[10]  U. Walter,et al.  Phosphorylation of CalDAG‐GEFI by protein kinase A prevents Rap1b activation , 2013, Journal of thrombosis and haemostasis : JTH.

[11]  H. Hamm,et al.  Mathematical model of PAR1-mediated activation of human platelets. , 2011, Molecular bioSystems.

[12]  J. Timmer,et al.  Dynamical modelling of prostaglandin signalling in platelets reveals individual receptor contributions and feedback properties. , 2013, Molecular bioSystems.

[13]  Manash S. Chatterjee,et al.  A molecular signaling model of platelet phosphoinositide and calcium regulation during homeostasis and P2Y1 activation. , 2008, Blood.

[14]  Jens Timmer,et al.  Dynamical modeling and multi-experiment fitting with PottersWheel , 2008, Bioinform..

[15]  Ioannis Xenarios,et al.  A method for the generation of standardized qualitative dynamical systems of regulatory networks , 2005, Theoretical Biology and Medical Modelling.

[16]  Thomas F. Coleman,et al.  An Interior Trust Region Approach for Nonlinear Minimization Subject to Bounds , 1993, SIAM J. Optim..