Insulin-secreting beta cells play an essential role in maintaining physiological blood glucose levels, and their dysfunction leads to the development of diabetes. To elucidate the signalling events regulating insulin secretion, we applied a recently developed phosphoproteomics workflow. We quantified the time-resolved phosphoproteome of murine pancreatic cells following their exposure to glucose and in combination with small molecule compounds that promote insulin secretion. The quantitative phosphoproteome of 30,000 sites clustered into three main groups in concordance with the modulation of the three key kinases: PKA, PKC and CK2A. A high-resolution time course revealed key novel regulatory sites, revealing the importance of methyltransferase DNMT3A phosphorylation in the glucose response. Remarkably a significant proportion of these novel regulatory sites is significantly downregulated in diabetic islets. Control of insulin secretion is embedded in an unexpectedly broad and complex range of cellular functions, which are perturbed by drugs in multiple ways.
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.
Platelets are critical for haemostasis and blood clotting. However, since under normal circumstances blood should flow without clotting, its function is regulated via a complex interplay of activating and inhibiting signal transduction pathways. Understanding this network is crucial for treatment of cardiovascular and bleeding diseases. Detailed protein interaction and phosphorylation data are explored to establish a simplified Boolean model of the central platelet cascades. We implemented the model by means of CellNetAnalyzer and showed how different signalling events coalesce into a fully activated system state. Furthermore, we examined the networks' inherent threshold behaviour using the semi-quantitative modelling software SQUAD. Finally, predictions are verified monitoring phosphorylations which mark different activation phases as modelled. The model can also be applied to simulate different pharmacological conditions as they modify node activity (aspirin, clopidogrel, milrinon, iloprost, combination) and is available for further studies. It agrees well with observations. Activatory pathways are diversified to cope with complex environmental conditions. Platelet activation needs several activation steps to integrate over different network subsets, as they are formed by the interplay of activating kinases, calcium mobilization, and the inhibiting cAMP-PKA system. System stability analysis shows two phases: a sub-threshold behaviour, characterized by integration over different activatory and inhibitory conditions, and a beyond threshold phase, represented by competition and shutting down of counter-regulatory pathways. The integrin network and Akt-protein are critical for stable effector response. Dynamic threshold-analysis reveals a dependency of the relative activating input strength necessary to irreversibly engage the system from the absolute inhibitory signal strength.
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