FORUM EKSPERTÓW
A nanoscale resolution assay of flow-induced platelet microaggregation

Background

Platelets are blood elements that play a crucial role in vascular haemostasis. In response to vascular damage, platelets interact with subendothelial proteins, resulting in a haemostatic plug. Plasma and subendothelium proteins including fibrinogen, collagen, and von Willebrand factor (vWF) mediate platelet adhesion and aggregation by engaging with platelet receptor proteins. GPIb, the vWF binding subunit of the GPIb/V/IX receptor, mediates mainly platelet adhesion to the endothelium [1, 2]. Platelets then change shape through reorganization of the cytoskeleton, leading to the generation of mediators such as thromboxane A2 (TXA2) [3], adenosine diphosphate (ADP) [4] and matrix metalloproteinase-2 (MMP-2) [5] that recruit more platelets to the aggregate. The GPIIb/IIIa receptor is essential for this process, since it allows fibrinogen binding to the receptors of adjacent platelets [6].

Over the past 50 years various methods have been used to study platelet aggregation. O’Brien first reported the use of a strong hand lens with powerful cross illumination to monitor platelet aggregation [7]. Later, Born developed a simple spectrophotometer device (light aggregometer) that recorded changes in light transmission in response to aggregation induced by agonists in stirred platelets [8].

The method had a profound effect on platelet aggregation research and similar devices based on measurement of light scattering or electrical impedance [9] are routinely used worldwide. However, these instruments do not detect the initial aggregation process which is characterized by the formation of microaggregates. Platelet function measurements using vessel wall damage- and flow-mimicking devices such as cone and plate analyser, platelet function analyser 100, coaxial cylinder couette or annular and parallel perfusion chambers have limited sensitivity and specificity and do not correlate well with the light aggregometer, which still remains the “gold standard” of platelet function testing [10-15].

In order to overcome these problems we have used a Quartz Crystal Microbalance with Dissipation (QCM-D). The principle of analysis of QCM is based on the resonance frequency f of a quartz crystal induced by applying an alternating electric field across the crystal. An increase in mass bound to the quartz surface causes the crystal’s oscillation frequency f to decrease (negative f shift) and it has been shown that for rigid, evenly distributed, and sufficiently thin adsorbed layers f is proportional to the mass. In this way, the QCM operates as a very sensitive balance and the mass can be calculated with nanogram sensitivity [16]. Changes in f as a result of platelet adhesion on quartz crystals have been reported previously by Matsuda [17] and Kawakami [18] using a custom-made QCM. However, when a soft or thick layer is bound to the crystal there is a high dissipation D shift and the damping or D of the crystal’s oscillation reveals the film’s softness (viscoelasticity). In this particular case the mass can be underestimated by measuring only f. Therefore, the combined information from changes in f and D is superior to f measurements alone [19, 20]. Using a QCM-D both parameters can be monitored simultaneously in real time and the formation of thin films (nm) of biological materials such as proteins or cells can be characterized by measuring both f and D [21, 22].

We used a commercially available QCM-D to design a novel method to measure in real time platelet microaggregation under low flow conditions.

Materials and methods

Reagents

All reagents were purchased from Sigma-Aldrich (Dublin, Ireland) unless otherwise indicated.

Blood collection and platelet isolation

Blood was collected from healthy volunteers who had not taken any drugs known to affect platelet function for at least 14 days prior to the study. Platelet-rich plasma (PRP) was prepared from blood as previously described [23] and diluted with PBS at final concentrations from 50,000 to 210,000 platelets µL­–1. Platelet-poor plasma (PPP) was used as a control for protein plasma deposition.

Quartz Crystal Microbalance

with Dissipation

The QCM-D from Q-Sense (Q-SenseTM E4 system, Q-Sense AB, Sweden) has four temperature and flow-controlled modules set up in parallel configuration. The heart of the system is a quartz crystal sensor that is placed in a chamber inside the module. Samples are perfused using a peristaltic microflow system (ISMATEC, IMS 935).

For the study of platelet aggregation, polystyrene-coated (PC) quartz crystals were used as sensors following coating with fibrinogen. Fibrinogen-uncoated PC-quartz crystals were used as controls. For fibrinogen coating sensors were placed in fibrinogen dissolved in phosphate buffered saline (PBS) (100 µg mL–1) for one hour at room temperature. Sensors were mounted on the flow chamber and PRP (50,000; 100,000; 150,000 and 210,000 platelets µL–1) was perfused through the device at 37°C and platelet aggregation was monitored in real time by the acquisition Q-Sense software (QSoft401) and measured as f and D.

To study the effects of increasing concentrations of platelets, PPP and PRP (100,000; 150,000 and 210,000 platelets µL–1) were perfused at 50 and 100 µL min–1 for up to 60 minutes and the concentration-response curves were generated.

To analyse the effects of flow rates and platelet con-centrations on shear stress, PRP (210,000 platelets µL–1) was perfused through the system at a fixed flow rate (10, 20, 50 and 100 µL min–1) for 30 minutes and platelet aggregation was monitored and measured as changes in f and D.

Phase-contrast microscopy

The formation of platelet aggregates on the crystal surface was studied using a Zeiss microscope (Axiovert 200M, UK). First, PPP and PRP suspensions were perfused on fibrinogen-coated PC-quartz crystals for 30 minutes through the device. The crystals were then taken for phase-contrast microscopy using a 20x objective. Photomicrographs were captured using a digital camera and Zeiss software (Axiovision 4.7).

Confocal microscopy

For the study of activated platelets PRP was perfused on fibrinogen-coated PC-quartz crystals for 30 minutes. Afterwards, crystals were placed in a 24-well plate and washed three times with PBS. Each sample was then treated with fluorescein isothiocyanate (FITC) conjugated PAC-1 (BD Biosciences, UK/Ireland) (150 µL) for 30 minutes in the dark. Platelets were then fixed with 2% formaldehyde for 30 minutes at room temperature and permeabilized with 0.1% triton for 3 minutes. Finally, samples were stained with phalloidin actin (Invitrogen, USA) (1 : 200 dilution) for 1 hour at room temperature, and mounted on a glass slide with mounting medium. For the study of resting platelets, platelets were treated in suspension and mounted on a glass slide. In both cases confocal images were taken using a 63x oil immersion objective, with a numerical aperture of 1.4, on a Zeiss LSM 510 Meta system (UK). The samples were excited using 488 nm and 561 nm and emission filters of band-pass 505-550 nm and long-pass 575 nm, respectively.

Atomic force microscopy

For the atomic force microscopy (AFM) imaging PRP was perfused on fibrinogen-coated PC-quartz crystals for 30 minutes.

Afterwards, samples were fixed using 2.5% glutaral-dehyde for 30 minutes at 37°C. Platelets were then dehydrated through ascending grades of ethanol (60% for 20 minutes, 80% for 20 minutes, 90% for 20 minutes and finally 100% for 30 minutes repeated once). Thereafter, crystals were mounted onto microscope slides facing upwards. The crystal-on-slide was mounted onto the microscope and clipped down to ensure no movement during acquisition. Images were then taken using an Ntegra Spectra (NT-MDT, Russia) AFM/Raman system. Imaging was carried out in dry-phase, semi-contact AFM with a silicon-nitride tip (NSG10, Golden silicon probes). The resonance frequency of the tip was found to be 280 KHz. Height AFM images, 70 µm x 70 µm scans, were taken five times for each sample, around the central area of the crystal, at 0.55 Hz. Image analysis was carried out on the height images using the Nova software (filter Fit Lines-X was used followed by subtract plane and finally grain analysis).

Flow cytometry

In order to analyse receptor expression on the surface of individual platelets and to minimize platelet activation caused by sample preparation procedures, no stirring or vortexing steps were used. The abundance of P-selectin on the surface of platelets after perfusion of PRP through the system, in the presence or absence of thrombin receptor-activating peptide (TRAP 25 µmol L–1) was measured by flow cytometry as previously described [24]. Resting platelets were used as a control. After collection samples were incubated in the dark for 5 minutes at room temperature in the presence of saturating concentrations (10 µg mL–1) of P-selectin (CD62P-APC from BD Biosciences, UK/Ireland). Following incubation, samples were diluted in FACS Flow fluid and analysed within 5 minutes using a BD FACSArray (BD Biosciences, Oxford, UK). The instrument was set up to measure the size (forward scatter), granularity (side scatter) and cell fluorescence. A two-dimensional analysis gate of forward and side scatter was drawn in order to include single platelets and exclude platelet aggregates and microparticles. Antibody binding was measured by analysing individual platelets for fluorescence.

The mean fluorescence intensity was determined after correction for cell autofluorescence. For each sample, the fluorescence was analysed using a logarithmic scale. Fluorescence histograms were obtained for 10,000 individual events. Data were analysed using BD FACSArray system software 1.0.3.

Rheology

The platelet aggregation rheology study was carried out based on the dimensions of the module chamber and assu-

ming laminar flow along the crystal active measurement area. The volume ric flow rate Q injected through the peristaltic pumping system was considered incrementally fixed at 10, 20,50 and 100 µL min–1. Shear rates and shear stresses on different platelet concentrations were calculated based on the PRP rheological changes at the same conditions where the experiments were performed, at 37°C. The mean velocity within the chamber during each experiment was calculated as vmean = Q/(w•h), where Q is the flow rate, w is the width and h the height of the chamber inside the module.

The shear rate  in the middle of the crystal sensing area was calculated by  =  vmean/h, where density was calculated based on the mass for the volume used. The shear stress  was given by the formula  = • vmean /h, where  is the dynamic viscosity. The dynamic viscosity of PRP preparations (at final concentrations of 100,000; 150,000 and 210,000 platelets µL–1) was measured using a vibro-viscosimeter (SV-10 sine wave SV-10, A&D, USA). Prostacyclin (100 ng mL–1) was added to each sample prior to measurement to inhibit platelet aggregation during the acquisition.

Q-Tools analysis using Voigt-based viscoelastic model

Assuming the deposition of a homogeneous layer across the crystal, it is possible, using the analysing Q-Tools software (Q-Sense AB, Sweden), to perform modelling of the raw data from the Q-Sense software (QSoft401) and calculate the layer thickness and accumulation of mass. Changes in f and D induced by deposition of platelets and plasma proteins were measured simultaneously at the 3rd, 5th and 7th overtones and modelled to calculate the thickness of the layer and estimate the mass deposited on the crystal surface.

Statistics

Results are expressed as f and D (from the 3rd overtone) or as percentage of aggregation (where the values for 210,000 platelets µL–1 on fibrinogen-coated PC-quartz crystals were considered as 100% of aggregation) of at least three independent experiments. All means are reported with standard deviation. Data were analysed using GraphPad Prism 5 software. One-way analyses of variance, repeated measures ANOVA and Dunnett’s or Tukey-Kramer’s multiple comparisons post test were performed, where appropriate. Statistical significance was considered when P < 0.05.

Results

Perfusion of sensor crystals

with platelets leads to aggregation

The perfusion of physiological concentrations of plate-

lets (210,000 platelets µL–1) on PC-quartz crystals induced a decrease in f and an increase in D, indicating the deposition of platelets on the sensor surface (Fig. 1).

The effects of different concentrations of platelets perfused on fibrinogen-coated and fibrinogen-uncoated PC-quartz crystals at a flow rate of 50 and 100 µL min–1 were investigated. Platelet-poor plasma and increased concentrations of platelets were perfused across the sensors for up to 60 minutes. Perfusion of PRP across fibrinogen-coated sensors led to a concentration-dependent decrease in f and increase in D when compared to PPP (Fig. 2A). These effects were confirmed by phase-contrast microscopy that showed the presence of platelet aggregates on the surface of crystals (Fig. 2B). Furthermore, a cytoskeleton reorganisation, activation of GPIIb/IIIa and the formation of pseudonucleus and pseudopodia were detected by confocal and AFM (Fig. 3 and Fig. 4). The perfusion of fibrinogen-uncoated PC-quartz crystals also led to platelet aggregation. However, these effects were lower when compared to fibrinogen-coated PC-quartz crystals. When traces recorded for fibrinogen-uncoated and fibrinogen-coated PC-quartz crystals were analysed and compared at 50 and 100 µL min–1 and after 15, 30, 45 and 60 minutes of perfusion of PRP, significant differences were found after perfusion of physiological concentrations of platelets at 100 µL min–1 for 30 minutes (repeated measures ANOVA,

n = 3, Pf and PD < 0.0001, Tukey’s Multiple Comparison Test,

P < 0.05 coated vs uncoated) (Fig. 5). Perfusion of fibrinogen-coated PC-quartz crystals with PRP at 50,000 platelets µL–1 also led to a decrease in f and increase in D (Fig. 6).

Platelets not associated with the sensor surface were not activated, as shown by low abundance of P selectin on the platelet surface in perfusate measured by flow cytometry. However, these platelets could be activated in the presence of soluble agonists such as TRAP (repeated measures of ANOVA, n = 3, P < 0.001 vs control) (Fig. 7).

Rheology

The influence of flow rates and platelet concentrations on platelet aggregation and shear stress inside the perfusion chamber within the crystal active measurement area was also studied. The perfusion of PRP (210,000 platelets µL–1) at 10, 20, 50 and 100 µL min–1 resulted in a significant decrease in f and increase in D with maximal effect at 50 and 100 µL min–1 (One-way ANOVA; n = 3; Pf = 0.0003; PD = 0.0008; Tukey’s Multiple Comparison Test, P < 0.01 vs 10 µL min–1). The effect of bulk shear stress on platelet aggregation was calculated for incremental flow rates (10, 20, 50 and 100 µL min–1) and increased concentrations of platelets (100,000; 150,000 and 210,000 platelets µL–1) at 37°C, ranging between 0.2 and 4.0 dyne cm–2 (Fig. 8, Table I).

Q-Tools analysis using Voigt-based viscoelastic model

Considerable differences in the fitting depending on the donor and the experimental conditions were found using the Q-Tools software. AFM imaging was performed on samples where the modelling was applied and the image analysis on the height images was carried out to evaluate the accuracy of the Q Tools modelling. The average heights for the platelet aggregates calculated by AFM and the ones obtained using the Voigt-based model by the Q-Tools software are shown in Table II.

Discussion

The main objective of our work was to characterize low flow-induced platelet microaggregation using a nanoscale resolution device, QCM-D. We used PRP for these experiments as the use of whole blood would necessitate constant mixing of platelet samples to be perfused over a long period of time (up to 60 minutes) and this could result in platelet activation.

Since nanoscale devices have great sensitivity and measure deposition of mass in nanograms, the first question was whether sensor crystals (PC-quartz crystal) coated with fibrinogen could provide a platelet activating surface and induce platelet aggregation; and secondly, whether using this system, the flow rate and shear stress could influence platelet microaggregation.

Polystyrene-coated quartz crystals were coated with fibrinogen, a plasma protein, which is both necessary and sufficient for platelet interactions leading to adhesion and aggregation. In fact, an early feature of platelet activation by different agonists is exposure of specific glycoprotein receptors, particularly GPIIb/IIIa, to which fibrinogen binds with high affinity [25]. In fact, patients suffering from fibrinogen disorders have long bleeding times [26]. In addition, fibrinogen is adsorbed on biomaterial surfaces in much higher quantity than other adhesion proteins and it is known to be well adsorbed on polystyrene [27]. Perfusion of fibrinogen-coated sensors with PRP led, as monitored in real time by the device, to reduced f and increased D, and therefore accumulation of mass on the sensor surface in a platelet concentration-dependent manner confirmed by phase-contrast microscopy.

However, perfusion of fibrinogen-uncoated crystals with PRP led to reduced aggregation, supporting the hypothesis that fibrinogen plays an important role facilitating platelet adhesion and aggregation on the surface of sensor crystals. When confocal microscopy was performed on fibrinogen-coated PC-quartz crystals after perfusion of PRP, platelet cytoskeleton reorganization (visualized by anti-actin antibody) and the presence of activated GPIIb/IIIa receptors (stained with PAC-1 antibody) on the platelet membrane surface were shown. Furthermore, nanometre scale imaging analysis by AFM showed fried-egg-like platelets with budding granules and extended pseudopodia, that clearly indicated platelet activation [28]. Our results are consistent with previous studies which have shown that adhesion of platelets to materials coated with fibrinogen can lead to platelet activation [29, 30]. It is not surprising that fibrinogen-uncoated PC-crystals induced platelet aggregation. It is well known that platelet aggregation takes place when blood is exposed to foreign surfaces, and this phenomenon underpins the thromboembolic complications associated with the use of different prosthetic devices [31]. Interestingly, sensor-induced platelet activation and microaggregate formation are detected even for very low concentrations of platelets and limited to the platelet population in direct contact with the sensor surface. Other platelets flowing through a 40 µL flow chamber are not activated, as shown by the flow cytometry analysis of platelet P-selectin.

The use of a nanoscale resolution device enabled us to study and quantify the onset of platelet microaggregation and subsequent phenomena under conditions of low shear stress (< 4 dyne cm–2).

Under situations of low shear stress, bound fibrinogen promotes platelets to adhere firmly via platelet GPIIb/IIIa receptors [32]. In fact, when fibrinogen-coated sensors were perfused with PRP, platelet microaggregation was demonstrated by phase-contrast microscopy and AFM and increased expression of activated GPIIb/IIIa receptors was shown by immunofluorescence microscopy. Previous studies adopted well-established and well-characterised models to carry out ex vivo measurements [15, 33]. These are based on large volume (mL min–1), high shear rate

(> 1000 s–1) and high shear stress (> 100 dyne cm–2) models. With recent advances in nanotechnology it is now possible to custom-design microfluidics systems which can perform high-throughput screening of multiple antiplatelet agents with low shear stresses requiring only a few microlitres

of blood [34].

Nanotechnology, therefore, offers a unique scalability in the model validation of shear-dependant platelet microaggregation. The instrument used in our study is a commercially available research device equipped with only four flow chambers, making it less suitable for high-throughput screening.

However, this device allows real-time, ex vivo, high-sen-

sitivity and precise measurements of platelet micro-aggregation that can be easily supplemented by direct imaging of platelet aggregates on the sensor crystals using standard phase-contrast microscopy, highly advanced confocal imaging, AFM or scanning electron microscopy (SEM). In a previous study QCM-D was used to follow platelet morphological changes by SEM focusing on the platelet primary adhesion process on a mix of fibronectin and albumin deposited on silica crystals [35]. Weber et al. [36] have investigated the binding kinetics of GPIIb/IIIa to polymer-adsorbed fibrinogen using QCM-D, correlating the results with platelet adhesion to the polymer surfaces by SEM. However, the work presented here is part of a PhD thesis performed in our lab where the QCM-D was used for the first time to characterize platelet microaggregation under flow conditions with nanoscale resolution [37]. In fact, the presence of platelet microaggregates deposited on the sensor surface was detected in real time by the device and demonstrated by direct imaging of the sensor crystals by AFM.

The linear Sauerbrey equation has been widely used to quantify the mass as an increase in the mass bound to the sensor causes the crystal’s oscillation f to decrease. However, the Sauerbrey equation does not apply in situations where the mass bound to the sensor surface behaves as a complex viscoelastic layer. Previous studies on cell adhesion using QCM have demonstrated that cells attached to the sensor surface produce significant variability in f shifts and do not behave as elastic masses. In fact, in cellular adsorption applications, the f and Sauerbrey relationship underestimate the adsorbed mass of cells and the D parameter becomes essential to fully characterize the adsorption of a viscoelastic cellular structure [20, 21]. Interestingly, the inapplicability of the Sauerbrey equation has been demonstrated in a study with platelets where the f response produced by binding human platelets to collagen was compared to the calculated mass bound using 51Cr radiolabelling of platelets. The mass value estimated by the Sauerbrey equation was found to be 200 times less than the actual bound mass based on the radiolabelled measurements [38]. If the adsorbed layer is homogeneous across the crystal, it is also theoretically possible to estimate the mass using a Voigt-based viscoelastic model included in the Q-Tools software combining and fitting both f and D [39]. However, in our experiments the distribution of the platelet aggregates (not always uniform through the sensor surface, as shown by phase-contrast and AFM), and the complexity in the viscoelastic structure of the platelet aggregate layer, make the software unsuitable for the measurement of mass. Therefore f and D values are used to quantify the changes in platelet aggregation.

The sensitivity limits of the system allow for platelet measurement within the sensor area which is almost 1000 times larger than a platelet. Although the adhesion of platelets to the substrate was expected to increase the shear stress as the channel size becomes reduced, an aggregate had an average height measured by AFM that accounted for only 0.5% reduction of the total chamber depth, facilitating on the other hand the instrument’s precise measurements. In addition, the detection of platelet activation measured by flow cytometry only after perfusion of PRP in the presence of agonist demonstrates that this method mimics the platelet behaviour at microvasculature level where platelets become activated just in the place of injury. Real-time measurements at very low concentrations of platelets (50,000 µL–1) also point to the ability of this device to quantify platelet function in low platelet concentration samples such as from patients with thrombocytopenia.

In conclusion, we have shown that platelet micro-aggregates are formed on fibrinogen-coated surfaces under low shear stress and this deposition can be quantified with great sensitivity by QCM-D. Thus, platelet microaggregate biology and physiology can be effectively studied using nanoscale resolution devices.

Acknowledgments

We are grateful to Paul Jurasz, John Booth, Alan Gaffney and Carsten Ehrhardt for helpful discussions and to Esther Rufino for technical help. The work was supported by a Science Foundation Ireland (SFI) PI grant to MWR and an SFI-RFP grant to CM. CM is an SFI Stokes Lecturer.

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