Manash S. Chatterjee

Determination of surface tissue factor thresholds that trigger coagulation at venous and arterial shear rates: amplification of 100 fM circulating tissue factor requires flow

Protein microarrays presenting spots of collagen and lipidated tissue factor (TF) allowed a determination of the critical surface concentration of TF required to trigger coagulation under flow. Whole blood supplemented with corn trypsin inhibitor (to inhibit factor XIIa) was perfused over microarrays for 5 minutes. Immunofluorescence staining of platelet glycoprotein GPIbalpha and fibrin(ogen) revealed a critical TF concentration (EC50) of 3.6, 8.4, and 10.2 molecules-TF/microm2 at wall shear rates of 100, 500, and 1000 s(-1), respectively. For collagen arrays where only the center lane of spots (in the direction of flow) contained TF, a downstream distance of 14 mm was required for the thrombus to widen enough to reach across a 300-micrometer gap to the adjacent TF-free lanes of collagen spots, in agreement with numerical simulation. To investigate the effect of low levels of circulating TF, whole blood (+/-100 fM added TF) was tested under static and flow conditions. After 5 minutes, the addition of 100 fM TF to whole blood had negligible effect under static conditions, but caused a 2.5-fold increase in fibrin formation under flow. This report defines the threshold concentrations of surface TF required to trigger coagulation under flow.

Systems Biology of Coagulation Initiation: Kinetics of Thrombin Generation in Resting and Activated Human Blood

Blood function defines bleeding and clotting risks and dictates approaches for clinical intervention. Independent of adding exogenous tissue factor (TF), human blood treated in vitro with corn trypsin inhibitor (CTI, to block Factor XIIa) will generate thrombin after an initiation time (Ti) of 1 to 2 hours (depending on donor), while activation of platelets with the GPVI-activator convulxin reduces Ti to ∼20 minutes. Since current kinetic models fail to generate thrombin in the absence of added TF, we implemented a Platelet-Plasma ODE model accounting for: the Hockin-Mann protease reaction network, thrombin-dependent display of platelet phosphatidylserine, VIIa function on activated platelets, XIIa and XIa generation and function, competitive thrombin substrates (fluorogenic detector and fibrinogen), and thrombin consumption during fibrin polymerization. The kinetic model consisting of 76 ordinary differential equations (76 species, 57 reactions, 105 kinetic parameters) predicted the clotting of resting and convulxin-activated human blood as well as predicted Ti of human blood under 50 different initial conditions that titrated increasing levels of TF, Xa, Va, XIa, IXa, and VIIa. Experiments with combined anti-XI and anti-XII antibodies prevented thrombin production, demonstrating that a leak of XIIa past saturating amounts of CTI (and not “blood-borne TF” alone) was responsible for in vitro initiation without added TF. Clotting was not blocked by antibodies used individually against TF, VII/VIIa, P-selectin, GPIb, protein disulfide isomerase, cathepsin G, nor blocked by the ribosome inhibitor puromycin, the Clk1 kinase inhibitor Tg003, or inhibited VIIa (VIIai). This is the first model to predict the observed behavior of CTI-treated human blood, either resting or stimulated with platelet activators. CTI-treated human blood will clot in vitro due to the combined activity of XIIa and XIa, a process enhanced by platelet activators and which proceeds in the absence of any evidence for kinetically significant blood borne tissue factor.

Multiscale prediction of patient-specific platelet function under flow

During thrombotic or hemostatic episodes, platelets bind collagen and release ADP and thromboxane A(2), recruiting additional platelets to a growing deposit that distorts the flow field. Prediction of clotting function under hemodynamic conditions for a patients platelet phenotype remains a challenge. A platelet signaling phenotype was obtained for 3 healthy donors using pairwise agonist scanning, in which calcium dye-loaded platelets were exposed to pairwise combinations of ADP, U46619, and convulxin to activate the P2Y(1)/P2Y(12), TP, and GPVI receptors, respectively, with and without the prostacyclin receptor agonist iloprost. A neural network model was trained on each donors pairwise agonist scanning experiment and then embedded into a multiscale Monte Carlo simulation of donor-specific platelet deposition under flow. The simulations were compared directly with microfluidic experiments of whole blood flowing over collagen at 200 and 1000/s wall shear rate. The simulations predicted the ranked order of drug sensitivity for indomethacin, aspirin, MRS-2179 (a P2Y(1) inhibitor), and iloprost. Consistent with measurement and simulation, one donor displayed larger clots and another presented with indomethacin resistance (revealing a novel heterozygote TP-V241G mutation). In silico representations of a subjects platelet phenotype allowed prediction of blood function under flow, essential for identifying patient-specific risks, drug responses, and novel genotypes.

Pairwise agonist scanning predicts cellular signaling responses to combinatorial stimuli.

Prediction of cellular response to multiple stimuli is central to evaluating patient-specific clinical status and to basic understanding of cell biology. Cross-talk between signaling pathways cannot be predicted by studying them in isolation and the combinatorial complexity of multiple agonists acting together prohibits an exhaustive exploration of the complete experimental space. Here we describe pairwise agonist scanning (PAS), a strategy that trains a neural network model based on measurements of cellular responses to individual and all pairwise combinations of input signals. We apply PAS to predict calcium signaling responses of human platelets in EDTA-treated plasma to six different agonists (ADP, convulxin, U46619, SFLLRN, AYPGKF and PGE2) at three concentrations (0.1, 1 and 10 × EC50). The model predicted responses to sequentially added agonists, to ternary combinations of agonists and to 45 different combinations of four to six agonists (R = 0.88). Furthermore, we use PAS to distinguish between the phenotypic responses of platelets from ten donors. Training neural networks with pairs of stimuli across the dose-response regime represents an efficient approach for predicting complex signal integration in a patient-specific disease milieu.Patient-specific prediction of cellular response to multiple stimuli is central to evaluating clinical risk, disease progression, and response to therapy. We deployed Pairwise Agonist Scanning (PAS) to measure calcium signaling of human platelets in EDTA-treated plasma exposed to 6 different agonists (at 0.1, 1, and 10×EC50) used individually or in 135 pairwise combinations. With 154 traces, we trained a neural network (NN) model to accurately predict the entire 6-dimensional response to ADP, convulxin, U46619, SFLLRN, AYPGKF, and PGE2. The NN successfully predicted calcium responses to sequential agonist additions, all ternary combinations of [ADP]+[convulxin]+[SFLLRN] (R=0.88), and 45 different combinations of 4 to 6 agonists (R=0.88). Furthermore, PAS provided 135 pairwise synergy values that allowed a unique phenotypic scoring and differentiation of 10 donors. Training of NNs with pairs of stimuli across the dose-response regime represents a highly efficient approach to predict integration of multiple, complex signals in a patient-specific disease milieu.

A molecular signaling model of platelet phosphoinositide and calcium regulation during homeostasis and P2Y1 activation

To quantify how various molecular mechanisms are integrated to maintain platelet homeostasis and allow responsiveness to adenosine diphosphate (ADP), we developed a computational model of the human platelet. Existing kinetic information for 77 reactions, 132 fixed kinetic rate constants, and 70 species was combined with electrochemical calculations, measurements of platelet ultrastructure, novel experimental results, and published single-cell data. The model accurately predicted: (1) steady-state resting concentrations for intracellular calcium, inositol 1,4,5-trisphosphate, diacylglycerol, phosphatidic acid, phosphatidylinositol, phosphatidylinositol phosphate, and phosphatidylinositol 4,5-bisphosphate; (2) transient increases in intracellular calcium, inositol 1,4,5-trisphosphate, and G(q)-GTP in response to ADP; and (3) the volume of the platelet dense tubular system. A more stringent test of the model involved stochastic simulation of individual platelets, which display an asynchronous calcium spiking behavior in response to ADP. Simulations accurately reproduced the broad frequency distribution of measured spiking events and demonstrated that asynchronous spiking was a consequence of stochastic fluctuations resulting from the small volume of the platelet. The model also provided insights into possible mechanisms of negative-feedback signaling, the relative potency of platelet agonists, and cell-to-cell variation across platelet populations. This integrative approach to platelet biology offers a novel and complementary strategy to traditional reductionist methods.

Endothelial cell specific adhesion molecule (ESAM) localizes to platelet–platelet contacts and regulates thrombus formation in vivo

Summary.  Background: In resting platelets, endothelial cell specific adhesion molecule (ESAM) is located in alpha granules, increasing its cell surface expression following platelet activation. However, the function of ESAM on platelets is unknown. Objective: To determine whether ESAM has a role in thrombus formation. Methods and results: We found that following platelet activation ESAM localizes to the junctions between adjacent platelets, suggesting a role for this protein in contact‐dependent events that regulate thrombus formation. To test this hypothesis we examined the effect of ESAM deletion on platelet function. In vivo, ESAM−/− mice achieved more stable hemostasis than wild‐type mice following tail transection, and developed larger thrombi following laser injury of cremaster muscle arterioles. In vitro, ESAM−/− platelets aggregated at lower concentrations of G protein‐dependent agonists than wild‐type platelets, and were more resistant to disaggregation. In contrast, agonist‐induced calcium mobilization, αIIbβ3 activation, alpha‐granule secretion and platelet spreading, were normal in ESAM‐deficient platelets. To understand the molecular mechanism by which ESAM regulates platelet activity, we utilized a PDZ domain array to identify the scaffold protein NHERF‐1 as an ESAM binding protein, and further demonstrated that it associates with ESAM in both resting and activated platelets. Conclusions: These findings support a model in which ESAM localizes to platelet contacts following platelet activation in order to limit thrombus growth and stability so that the optimal hemostatic response occurs following vascular injury.

RGS/Gi2α interactions modulate platelet accumulation and thrombus formation at sites of vascular injury

Although much is known about extrinsic regulators of platelet function such as nitric oxide and prostaglandin I(2) (PGI(2)), considerably less is known about intrinsic mechanisms that prevent overly robust platelet activation after vascular injury. Here we provide the first evidence that regulators of G-protein signaling (RGS) proteins serve this role in platelets, using mice with a G184S substitution in G(i2α) that blocks RGS/G(i2) interactions to examine the consequences of lifting constraints on G(i2)-dependent signaling without altering receptor:effector coupling. The results show that the G(i2α)(G184S) allele enhances platelet aggregation in vitro and increases platelet accumulation after vascular injury when expressed either as a global knock-in or limited to hematopoietic cells. Biochemical studies show that these changes occur in concert with an attenuated rise in cyclic adenosine monophosphate levels in response to prostacyclin and a substantial increase in basal Akt activation. In contrast, basal cyclic adenosine monophosphate (cAMP) levels, agonist-stimulated increases in [Ca(++)](i), Rap1 activation, and α-granule secretion were unaffected. Collectively, these observations (1) demonstrate an active role for RGS proteins in regulating platelet responsiveness, (2) show that this occurs in a pathway-selective manner, and (3) suggest that RGS proteins help to prevent unwarranted platelet activation as well as limiting the magnitude of the normal hemostatic response.

Systems biology of platelet-vessel wall interactions.

Blood systems biology seeks to quantify outside-in signaling as platelets respond to numerous external stimuli, typically under flow conditions. Platelets can activate via GPVI collagen receptor and numerous G-protein coupled receptors (GPCRs) responsive to ADP, thromboxane, thrombin, and prostacyclin. A bottom-up ODE approach allowed prediction of platelet calcium and phosphoinositides following P2Y1 activation with ADP, either for a population average or single cell stochastic behavior. The homeostasis assumption (i.e., a resting platelet stays resting until activated) was particularly useful in finding global steady states for these large metabolic networks. Alternatively, a top-down approach involving Pairwise Agonist Scanning (PAS) allowed large data sets of measured calcium mobilization to predict an individuals platelet responses. The data was used to train neural network (NN) models of signaling to predict patient-specific responses to combinatorial stimulation. A kinetic description of platelet signaling then allows prediction of inside-out activation of platelets as they experience the complex biochemical milieu at the site of thrombosis. Multiscale lattice kinetic Monte Carlo (LKMC) utilizes these detailed descriptions of platelet signaling under flow conditions where released soluble species are solved by finite element method and the flow field around the growing thrombus is updated using computational fluid dynamics or lattice Boltzmann method. Since hemodynamic effects are included in a multiscale approach, thrombosis can then be predicted under arterial and venous thrombotic conditions for various anatomical geometries. Such systems biology approaches accommodate the effect of anti-platelet pharmacological intervention where COX1 pathways or ADP signaling are modulated in a patient-specific manner.