Platelets react rapidly to a range of stimuli. This paper describes a real-time flow cytometry-based platelet function assay and a newly developed bespoke open-source software (Kinetx) to enable quantitative kinetic measurements of platelet granule release, fibrinogen binding, and intracellular calcium flux.
Platelets react rapidly to vascular injury and undergo activation in response to a range of stimuli to limit blood loss. Many platelet function tests measure endpoint responses after a defined time period and not the rate of platelet activation. However, the rate at which platelets convert extracellular stimuli into a functional response is an essential factor in determining how efficiently they can respond to injury, bind to a forming thrombus, and signal to recruit other platelets. This paper describes a flow cytometry-based platelet function assay that enables simultaneous data acquisition and sample stimulation and utilizes newly developed bespoke open-source software (Kinetx) to enable quantitative kinetic measurements of platelet granule release, fibrinogen binding, and intracellular calcium flux. Kinetix was developed in R so that users can alter parameters such as degree of smoothing, identification of outlying data points, or time scales. To aid users unfamiliar with the R environment, Kinetix analysis of data can be performed by a single command. Together, this allows real-time platelet activation metrics, such as rate, acceleration, time to peak-rate, time to peak-calcium, and qualitative shape changes, to be accurately and reproducibly measured and categorized. Kinetic measurements of platelet activation give a unique insight into platelets’ behavior during the first stages of activation and may provide a method of predicting the recruitment of platelets into a forming thrombus.
Platelets play a central role in hemostasis and generate a rapid and multifaceted response to vascular injury1,2. Current platelet function tests measure various aspects of platelet reactivity, representative of their hemostatic actions in vivo. Traditionally, platelet function has been assessed using endpoint assays that measure fibrinogen binding, granule release, or platelet aggregation in platelets stimulated for long enough to achieve maximal activation3,4. These tests do not take into account the time taken for platelets to convert extracellular stimuli to intracellular signals and calcium flux and subsequently degranulate and bind to the growing thrombus. Blood flows at a shear rate of up to 20 dynes/cm3 in veins and 80 dynes/cm3 in large arteries5, emphasizing the need for platelets to counteract this rapid rate of flow by detecting, processing, and responding to extracellular stimuli rapidly to bind into a forming thrombus and support its ongoing growth.
The rate of platelet activation can vary independently of the maximum extent of platelet activation. Integrin-linked kinase (ILK) is a protein involved in regulating β1 and β3 integrins in platelets6,7. Inhibition or specific deletion of ILK in vivo demonstrated that the rate, but not the maximal extent of platelet activation, was affected in the absence of functional ILK8. Differences between the rate of aggregation and maximum level of aggregation were also identified in mice deficient in CALDAG GEFI9,10, a signaling molecule involved in the regulation of inside-out signaling via RAP111.
These findings demonstrate that platelet rate and maximal activation levels can be autonomous and that measurements of maximal activation may not be descriptive of platelet behavior up to this point. These differences in the time taken for platelets to become activated may profoundly affect their initial binding to the growing thrombus, impacting the architecture and overall size of the thrombus. These variations between platelet rate and maximal activation highlight the need for an assay to accurately measure the rate of platelet activation and can be used to detect variances within the population.
This paper describes a method that accurately measures platelet activation and calcium flux in real-time and calculates a range of metrics, including the rate at which platelets become activated and the time taken for platelets to reach the maximum rate of activation and maximum calcium flux. These kinetic measurements of platelet activation give a better insight into the behavior of platelets during the first stages of thrombus formation and provide a method for predicting how quickly platelets can be recruited into a forming thrombus.
The rate at which platelets detect, process, and respond to activating stimuli may be an essential determinant for thrombus formation. Previous studies have found that inhibition of signaling elements that impact the rate, but not the final extent of platelet activation, results in the formation of unstable thrombi8. Many platelet function assays measure the extent of platelet activation and aggregation in response to different conditions and treatments; however, these do not consider the rate at which platelets become activated and the time taken for this complex process to occur3,4. The innovative flow cytometry-based assays developed here reproducibly monitor platelet activation over time and translate this into a range of metrics to calculate the maximum rate of platelet activation and the time taken for platelets to reach this maximum rate and become fully activated.
The data presented highlights the real-time assay's capacity to identify variations between different responses to agonist type and concentration and between individuals. Many previous reports have shown that platelet reactivity is highly variable between normal individuals15,16, indicating that the rate of platelet activation may also vary significantly within the population. Data from this study demonstrates that the rate of degranulation and fibrinogen binding to platelets appears to be even more variable than the maximum levels of platelet activation. This shows that real-time flow cytometry can also be utilized as a valuable and reliable tool to identify variances in platelet rate in the population and detect the effects of different inhibitory or pro-activatory agents on platelet rate as an additional means of measuring platelet function.
When platelet function is measured using endpoint assays, comparisons can be made on the extent of fibrinogen binding or granule release between different agonists. The loess curves comparing fibrinogen binding over the first 5 min of platelet activation demonstrate the ability of the real-time assay to tease out more detail in the differences in platelet activation kinetics that single endpoint assays cannot measure.
The data collected from the real-time assay demonstrates that the speed at which fibrinogen binds to platelets follows a slightly different pattern, depending on the activating pathway (Figure 3). In order to accurately assess platelet activation kinetics, it is essential to use a non-pressurized flow cytometer that enables simultaneous data acquisition and sample stimulation. It is also essential that the agonists are added rapidly to ensure near-instantaneous and complete mixing of agonist and platelets. Stimulation with thrombin ADP and epinephrine produces a similar curve representing a rapid initiation of signaling in response to receptor sensitization resulting in fibrinogen binding to platelets at a quick and steady rate. In contrast, platelets stimulated by CRP-XL are initially very slow to bind fibrinogen following initial receptor sensitization; however, the rate of fibrinogen binding is then rapidly increased after this initial delay. Platelet stimulation with U46619, a mimetic of TXA2, results in a quick initial rate of fibrinogen binding, which decreases rapidly to a very slow rate leading to only a slight and steady increase in fibrinogen binding over time.
Kinetx was designed to be open-source, reproducible, and easy to implement in order to get around problems with proprietary software, such as cost and inflexibility. As such, it needed to be developed with software that was non-propriety. R was chosen as it is widely used by biologists, easy to install, cost-free, and open-source. This open-source environment allows users proficient in R to alter parameters such as degree of smoothing, identification of outlying data points, or time scales. However, to aid researchers who are unfamiliar with R Kinetix was also developed so that analysis can be performed via a single command (either kinetxProcess or kinetxProcessCalcium, depending on the data being analyzed). The Kinetix software demonstrated here can calculate a range of metrics, including values for the maximum levels, rate, and acceleration of fibrinogen binding or P-selectin exposure and the time points at which these maximums occur. The kinetics of platelet activation in response to different stimulatory pathways can be more accurately compared using these numbers.
Comparisons between different agonist stimulations in the maximum levels of fibrinogen binding and the rates of fibrinogen binding to platelets are good examples of where the rate of platelet activation can vary independently of maximum binding. Comparing maximum fibrinogen binding after 5 min of stimulation with 0.04 µM ADP (3.85 LogFU) and 0.04 µg/mL CRP-XL (3.70 LogFU), both agonists have resulted in a similar amount of bound fibrinogen (Figure 5A). The maximum rates of fibrinogen binding show an even more minor difference (0.04 µM ADP – 0.0050 LogFU/minute; 0.04 µg/mL CRP-XL – 0.0054 LogFU/min), indicating that the overall rate of fibrinogen binding is similar between these two stimulations (Figure 5B). However, when the lag time of platelet activation is compared, there is a clear difference showing CRP-XL (117 s to maximum rate) accelerating at a much slower rate than ADP (47 s to maximum rate) (Figure 5C). Thus, it becomes clear that ADP stimulation results in a much faster initial response (P < 0.001) when compared to CRP-XL. When observed together, these measurements of platelet kinetics in response to two different agonists describe a rapid initial response to ADP stimulation which accelerates slowly and remains at a steady rate. In contrast, CRP-XL stimulation results in a slow initial rate of activation, which accelerates rapidly at a much later time, eventually leading to a similar overall rate and levels of fibrinogen binding as ADP. These differences between the maximum levels, rate, and acceleration of fibrinogen binding demonstrate that a number of parameters are involved in measuring how quickly platelets become activated. The real-time assay and Kinetx analysis can measure and compare these parameters, describe the time taken from receptor sensitization to the platelet response, and compare this between different signaling pathways.
Increasing agonist concentration does not have a significant effect on the rate of fibrinogen binding to platelets. However, the time taken to reach the maximum rate of fibrinogen binding decreases as agonist concentration increases, suggesting that platelets bind fibrinogen at a steady rate and receptor saturation plays a more prominent role in how quickly platelets bind fibrinogen.
The calcium flux assay and analysis described is a quick and easy to perform calcium assay that can be incorporated as extra samples in the real-time assay allowing for the analysis of calcium and platelet fibrinogen binding and P-selectin in the same run of samples. The bespoke analysis package provides an in-depth assessment of calcium flux kinetics, including the shape of the response, maximum response, and time to maximum response. These parameters can then be compared for variation between donors and in response to various pharmaceutical agents. Calcium flux in platelet has been previously studied in platelets using a variety of flow cytometry-based assays17,18,19. Aliotta et al.14, describe an elegant assay capable of analyzing the kinetics of multiple intracellular ions. The calcium assay presented here builds upon these previously published assays by including the analysis package allowing greater flexibility, a more in-depth exploration of the data with the benefit of high-throughput analysis for multiple donors in a short timeframe.
Previous studies have demonstrated that the inhibition or absence of certain signaling molecules results in an altered platelet activation rate, which directly translates to thrombus formation8,9. In the past, platelet activation kinetics could be measured by flow cytometry over a number of fixed time points which can then be used to calculate and compare, for example, the rate of GPIIbIIIa externalization in response to different agonists20. The real-time assay and Kinetx analysis described in this paper provide a simple, freely available, and accurate method for measuring both rate and endpoint of platelet activation from resting platelets. This is likely important in identifying physiologically relevant variations in platelet function that may be missed when only endpoint readings are measured.
The authors have nothing to disclose.
This project was supported by the British Heart Foundation (PG/16/36/31967, RG/20/7/34866, and RG/15/2/31224).
9,11-Dideoxy-11α,9α-epoxymethanoprostaglandin F2α – U46619 | Sigma-Aldrich, Poole, UK | D8174-1MG | |
Accuri C6 flow cytometer with BD Csampler | Beckton Dickinson, UK | 660517 + 660519 | |
Adenosine diphosphate | Sigma-Aldrich, Poole, UK | A2754-1G | |
APC-labelled anti-P-selectin (CD62p) | BD Biosciences, UK | 550888 | |
Corning polypropylene 96-well round-bottomed, non-treated microtitre plate | Sigma-Aldrich, Poole, UK | CLS3879-50EA | |
Cross-linked collagen related peptide (CRP-XL) | CambCol, UK | ||
Epinephrine | Sigma-Aldrich, Poole, UK | E4375-1G | |
FITC-labelled anti-fibrinogen antibody | Dako, Agilent Technologies, UK | F011102-2 | |
Fluo-4 Direct dye | Thermo-Fisher Scientific | F10472 | |
Gel loading tips | Starlab, UK | I1022-0600 | |
Gly-Pro-Arg-Pro peptide | Sigma-Aldrich, Poole, UK | G1895-5MG | |
Thrombin | Sigma-Aldrich, Poole, UK | SRE0003-10KU | |
Thrombin receptor activator peptide 6 (TRAP-6) | Bachem, St Helens, UK | H-2936.0005 | |
Vacuette 9NC coagulation 3.2 % trisodium citrate (0.109 mol/L) | Greiner Bio-one LTD, Stonehouse, UK | 454327 |
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