Viscoelasticity and structure of blood clots generated in-vitro by rheometry: A comparison between human,horse,rat,and camel

Abstract

BACKGROUND:

Although the coagulation system is evolutionary well preserved, profound species differences exist in viscoelastic as well as in common laboratory tests of coagulation.

OBJECTIVE:

Evaluating differences in clot formation and material characterisation of clots of four mammalian species on macro-, micro- and nanoscales by the means of rheometry, scanning electron microscopy (SEM) and small angle x-ray scattering (SAXS).

METHODS:

Blood samples were collected from healthy human volunteers, laboratory rats (HL/LE inbred strain), warmblood horses and dromedary camels. Clot formation was observed by oscillating shear rheometry until plateau formation of the shear storage modulus G’, at which point selected clots were prepared for scanning electron microscopy. SEM images were analysed for fibre diameter and fractal dimension. Additionally, scattering profiles for plasma and whole blood samples were obtained with SAXS.

RESULTS:

Viscoelasticity of clots showed great interspecies variation: clots of rats and horses exhibited shorter clotting times and higher G’ plateau values, when compared to human clots. Camel clots showed unique clotting characteristics with no G’ plateau formation in the timeframe observed. Less differentiating features were found with SEM and SAXS, although the rat fibre network appears to be more convoluted and dense, which resulted in a higher fractal dimension.

CONCLUSION:

Clotting kinetic differs between the species, which is not only of clinical interest, but could also be an important finding for animal models of blood coagulation.

Keywords

Blood coagulation rheometry ROTEM SEM SAXS comparative hemorheology

1 Background

As a reaction to injury or in various pathological states blood has the capability to change its state and transform from a viscoelastic liquid into a viscoelastic solid. Adequate control of coagulation is key to the fitness of organisms, as both, hypo- and hypercoaguable states are deleterious to its health: Thromboembolic events like myocardial infarction, stroke, venous thrombosis and pulmonary embolism are among the major causes of morbidity and mortality world wide [1, 2]. Many hypocoaguable states are iatrogenic: possible reasons include the use of antithrombotic and anticoagulant drugs [3] or so-called trauma coagulopathy, which is a condition caused by massive blood loss with consecutive fluid replenishment, occurring either intraoperatively or after accidental trauma [4]. Hereditary conditions like haemophilia or the lack of other coagulation factors also can lead to serious bleeding events [5].

Quintessential to clot formation is the enzymatic conversion of fibrinogen into fibrin monomers and its subsequent spontaneous polymerisation. Red blood cells (RBC) and thrombocytes are incorporated into the growing network, the end result of which is capable to impede blood flow. Fibrinogen conversion is however only the last step in a complicated cascade involving various pro- and anticoagulatory plasmatic serine proteases and their cofactors, which are traditionally divided into extrinsic and intrinsic pathways, a paradigm which shifted in the last years towards the cell based model of coagulation [6].

Laboratory assessment of the coagulation system is commonly performed by measuring activated partial thromboplastin time and prothrombin time. Both tests measure onset of coagulation after addition of substances, which selectively activate either intrinsic or extrinsic pathways. Concentration and enzymatic activity of individual clotting factors can also be assessed. However, biochemical assays only evaluate specific aspects of the clotting cascade. Relevant for the physiological and pathological roles of blood clots are their physical properties on a macroscale. These can be assessed by viscoelastic testing methods, e.g. ROTEM^®, which is used in human and veterinary medicine [7, 8]. A possible, research-oriented alternative to ROTEM^® is oscillating shear rheometry. With this method, blood samples are sheared in the rheometers measurement geometry at constant shear amplitude and frequency. The advantage over the classical ROTEM^® test is the possibility to choose the deformation amplitude as needed to minimize the influence of the applied mechanical strain on the clot formation process and the resulting fibre architecture. Generally spoken, clot formation is the polymerisation of fibrin fibres out of fibrin monomers, and the increase of material “stiffness” with time can be measured. As a result of applied strain, the stress inside the material increases with time, which is translated into so-called viscoelastic moduli. The shear storage modulus G’ can be interpreted as elastic component of the materials viscoelasticity and represents the “stiffness”, while loss modulus G” accounts for the viscous component or basically represents the fluid properties of the material. It follows that during clot formation G’ increases, while G” decreases [9].

A well-established method for investigation of biological macromolecular systems on nanometer scale are small angle scattering (SAS) methods like Small Angle X-ray (SAXS) and small angle neutron scatterings techniques, which give information about size, shape, surface-to-volume ratio, distribution and polydispersity of molecules in solution. [10] Due to its robustness, SAS methods were employed to characterise e.g. diameter of fibrin clots [11], as well as the nanostructure of fibrin [12], or to monitor structural changes upon deformation [13]. Due to hardware configuration, only very small systems can be investigated: For our in-house set-up the limit is 1000 Å, but up to 1μm are possible when using sophisticated synchrotron configurations.

Here we report the macro-, micro- and nanoscale properties of coagulating whole blood drawn from four different mammalian species (human, horse, rat and camel), applying oscillating shear rheometry, scanning electron microscopy (SEM) and SAXS respectively.

Blood of different species shows pronounced differences in fluidity. This is due to differences in erythrocyte number, size, shape, and deformability, but the most important role is played by red blood cell (RBC) aggregation tendency [14], which can also modify tissue perfusion [15, 16]. Blood clotting seems to be less diverse, which could be indicative of its evolutionary importance. Genes encoding coagulation factors are shared among all jawed vertebrates and evolved over 430 million years ago from a suggested primitive coagulation system [17]. However, comparative studies applying ROTEM^® have revealed species appearing to be more procoagulant (rat, pig, rabbit [18], cynomologous monkeys [19]), while other animals (sheep [18], cat [20], horse [21], baboon [22]) exhibit a clotting profile comparable to that of humans [23]. Of special interest is the camel, which lives in hot and dry environments and experiences dehydration, sometimes followed by rapid rehydration. In one study, camels appeared to be more procoagulant than humans [24], the authors hypothesise this finding to be an adaptive mechanism in order to minimise fluid loss.

Cross species comparative studies are a classical approach to investigate physiological processes. Here, the selected species should help us understand the relationship between blood components and their importance for the clot formation process without the need to artificially modify blood samples. As such, we only used unaltered blood. Additionally, animal models involve the investigation of disease mechanisms [25, 26] or therapeutic approaches [27]. Comparative data can be potentially of use to interpret and refine those models.

2 Methods

2.1 Sample collection

After obtaining informed consent and with approval of the ethical review committee of the Medical University of Vienna (EK No. 1371/2015), venous whole blood was collected from nine male volunteers (20–25 years old, healthy and with no intake of any medication for the last 7 days) from the anticubital vein using a 21 gauge butterfly needle and a Vacuette blood collection system (Greiner Bio-One GmbH, Kremsmünster, Austria), containing 3.8% sodium citrate for anticoagulation. Blood was stored at ambient temperature and processed after maximum of 4 hours.

Whole blood was withdrawn from 11 female rats of the HL/LE inbred strain, which has been bred since 1983 at the Medical University of Vienna. Excess blood volumes of control animals (GZ BMWFW-66.009/0112-WF/V/3b/2015) were used at project termination. The animals received general anesthesia by 100 mg/kg Ketamine and 10 mg/kg Xylazine i.p., and blood was collected by cardiac puncture using a 18G needle mounted on a 5 mL syringe. Blood was immediately transferred into citrated tubes (3.8 % sodium citrate, Greiner Bio-One GmbH; Kremsmünster, Austria) and tests were started thereafter with a maximum delay of 2 hours.

Whole blood was withdrawn from 1 male and 5 female warmblood horses by puncturing the jugulary vein using a 21G butterfly needle and the Vacuette blood collection system as described before. Ethical approval number is as follows: BMWFW-66.009/0230-WF/V/3b/2017.

Blood from dromedary camels was withdrawn on the campus of the Camel Research Center, Dubai, VAE from the jugulary vein of 8 female, clinically healthy dromedaries, using a 21G needle. Samples were immediately anticoagulated as described above. Approvance of an ethical review committee is not needed, since blood was collected for clinical reasons. One male Bactrian camel was used for the SAXS measurements. Ethical approval number for the blood withdrawal is: BMWFW-66.009/0230-WF/V/3b/2017.

2.2 Rheometry

The rheometer Physica MCR 302 (Anton Paar, Graz, Austria) was used. The measurement geometry (gap height 1 mm, 25 mm plate-plate geometry, stainless steel with profiled surfaces) was filled with 0.58 mL citrated whole blood after recalcification with 0.38μL 0.2 M Ca^2 +. Time sweeps were conducted at constant oscillation frequency f = 1.5 Hz and deformation amplitude γ= 0.001. The change of storage modulus G’ was monitored by the operator and the measurement was ended after visual detection of the storage modulus plateau. In case of the camel, measurements were ended after 4300 seconds, as no plateau formation was observed.

2.3 ROTEM^®

ROTEM^® measurements were conducted according to the manufacturers specifications using the ROTEM^® Delta (TEM International, Munich, Germany) in NATEM mode at 37 °C for 1 hour. Samples were recalcified with 0.2 M Ca2+ using the built-in auto-pipette.

2.4 SEM

Representative blood clots were analysed using a Quanta 250 FEG SEM (Thermo Fisher Scientific, Waltham, MA, USA). After in-vitro clot formation in the rheometer gap and detection of the G’ plateau, samples were rinsed three times with phosphate buffered saline while still adhering to the plate, and fixated thereafter in situ in 2.5 % glutaraldehyde. After one hour of fixation they were carefully removed from the plate, rinsed three times in distilled water, followed by stepwise dehydration in ethanol-water solutions (30, 50, 70, 90, and 98% ethanol). Samples were incubated in each ethanol-water solution for 10 minutes each, and finally stored in 98% ethanol until essayed. For SEM, they were mounted on an aluminium stub using a double-sided carbon sticker, dried in a vacuum oven for 30 minutes at 40 °C and coated with a thin gold layer using a Scancoat Six (Edwards, Burgess Hill, UK). The SEM was operated under high vacuum conditions and with variable voltages between 5 and 20 kV. The secondary electron detector was used to generate the micrographs.

2.5 Analysis of the SEM images

As proof-of-concept, semi-automated analysis of SEM images was performed in order to gain information on fibre diameter distribution and fractal dimension. Fibres from the original SEM images were manually extracted using image editor software. The remaining analysis was implemented in Mathematica 11 (see Fig. 3): Images were binarized and then fitted by using an algorithm with locally maximal circles. Each circle was set to touch three or more white points within the image. The diameter of the circles was then recalculated from pixels to the length scale (in nm) using the inset from the SEM image and finally plotted as a histogram. Additionally, fractal dimensions of the fibre network were also determined using a box counting algorithm.

2.6 SAXS

SAXS measurements were performed using the Small Angle X-ray diffraction instrument PSAXS System S/Max 3000 (Rigaku, Tokyo, Japan) equipped with a MM002+ microfocus source (Cu-Kα) and a Triton200 detector.

One citrated whole blood sample of each species human, rat, and camel (horse samples were not available at that time) was prepared for SAXS: Plasma aliquots were separated from whole blood after centrifugation at 1500 U/min for 5 minutes in a Rotanta/RPC centrifuge (Hettich, Tuttlingen, Germany). Citrated samples were used without further modification to obtain the reference signals for unclotted plasma. For clotted samples clotting was induced as described above for rheometry. Both, citrate-anticoagulated and recalcified plasma samples were introduced into 1.5 mm capillaries. Clotting was assumed to be complete after 1 h, at which point the SAXS measurement was started for 4 h in vacuum. Collected 2D scattering images were background subtracted, radially averaged and normalized to a unit to facilitate comparisons between samples. An effective distance of 250 Å in real space was reached.

2.7 Statistics

Statistical analysis of rheometrical values and data visualisation was performed using R version 3.4.2 [28]. Data analysis of SAXS measurements was performed using Mathematica 11 (Wolfram Research, Inc., Champaign, IL, USA) with ATSAS [29] and GNOM [30] packages.

3 Results

3.1 Viscoelastic tests

Shear storage modulus G’ increased significantly after a typical initial lag phase, which can be referred to as clotting time. Since it was not possible to accurately detect the gel point, we defined clotting time as the time until G’ reached 10 Pa (CT-rheo). Formation of a final composite network was assumed as soon as G’ reached a plateau, with G’max indicating the final stiffness of the blood clot and G’max-t indicating the time until G’max was obtained. G’max-t was not obtained for camels, as no plateau formation was observed. Results are shown in Fig. 1 and Table 2. Haematological parameters of the species investigated are presented in Table 1, as well as the most common parameters (CT, CFT, MCF and also MCF-t) obtained by ROTEM^® in Table 3.

Fig.1

Average G’ development of different species.

Table 1

Haematological parameters of the animals investigated

		Human		Horse		Rat		Camel
		Mean	SD	Mean	SD	Mean	SD	Mean	SD
Erythrocytes	10¹²/l	4.92	0.29	7.97	0.89	7.75	0.53	8.81	0.65
Haemoglobin	g/dl	14.59	0.70	13.65	1.02	13.75	0.94	12.43	1.13
Haematocrit	l/l	0.43	0.02	0.38	0.03	0.42	0.03	0.26	0.02
Leukocytes	10⁹/l	6.59	1.64	5.73	0.68	2.15	0.45	8.80	1.63
Platelets	10⁹/l	282	84	121	32	983	107	286	62
MCV	fl	86.72	2.71	48.21	2.51	54.34	2.34	29.90	1.54
MCH	pg	29.71	0.90	17.20	0.82	17.75	0.80	14.10	0.57
MCHC	g/dl	34.26	0.49	35.65	0.29	32.69	0.82	47.18	1.05

Table 2

Species differences of parameters obtained by rheology. Clotting time was defined operationally as time point where G’> = 10 Pa. No G’ plateau formation was observed in camels, as such G’max represents G’ after 2 h and G’max-t cannot be provided

	n	Clotting time (s)		G’max (Pa)		G’max-t (s)
	n	Mean	SD	Mean	SD	Mean	SD
Human	9	618	115	282	27	2832	366
Horse	6	456	67	403	66	2363	422
Rat	11	246	67	673	65	2363	336
Camel	8	684	254	476	38	–	–

Table 3

Species differences of coagulation parameters obtained by ROTEM in NATEM mode. MCF-t of camel clots is not provided because clot formation was not complete at the end of the measurement period (1 h)

	n	CT (s)		CFT (s)		MCF (mm)		MCF-t (s)
	n	Mean	SD	Mean	SD	Mean	SD	Mean	SD
Human	9	957	131	360	60	48	5	2191	118
Horse	3	588	131	160	39	55	3	1613	93
Rat	11	297	60	73	23	65	4	1976	170
Camel	7	751	123	518	164	41	6	–	–

No significant correlations were found between clot kinetic parameters determined by rheometry and ROTEM for each species (e.g. by testing CT-rheo vs. CT-ROTEM^®, or G’max vs. MCF, or G’max-t vs. MCF-t). Comparison of mean clotting times (CT-rheo vs. CT-ROTEM^®) using two sided t-tests showed significant differences: t = –5.975, p < 0.001 for humans, t = –2.394, p = 0.044 for horses and t = –2.271, p = 0.035 for rats. No significant difference of clotting times was found for camels. Times until maximum clot strength (G’max-t vs. MCF-t) were also compared using two sided t-tests and showed significant differences for humans (t = 5.111, p < 0.001), horses (t = 4.269, p = 0.007) and rats (t = 3.420, p = 0.004). It thus seems as if clotting is detected earlier by rheometry than by ROTEM^® and maximum clot formation is detected later.

3.2 SEM

Microscopical examination of the samples revealed a fibrous network incorporating erythrocytes and thrombocytes (Fig. 2A-D). Whereas human, horse and camel samples exhibit comparable structures, the rat fibrous network appears to be more convoluted with smaller pore sizes and higher fibre density. Additionally, both fibre and erythrocyte diameters appear to be much smaller than in the other animals. Horse blood clots feature a large number of echinocytes.

Fig.2

SEM pictures of the fibrin network from human (A), horse (B), rat (C) and camel (D) at 15000×magnification.

Fibre diameters ranged between 50–150 nm in the human sample, 200–350 nm in the horse, 75–250 nm in the rat, and 50–200 nm in the camel clots. fractal dimensions of the fibre network was 1.70 for human, 1.65 for horse, 1.73 for camel, and 1.94 for rat clots. Note that a fractal dimension of 2 would correspond to a space-filling 2D image and a fractal dimension of 1 would correspond to a line.

Fig.3

Fibres from the original SEM image (A) were manually extracted and binarised (B) to reveal the internal fiber network. Binarised images were then fitted in Mathematica using an algorithm with locally maximal circles, so that they touch three or more white points within image (C). The diameter of the circles was then recalculated from pixels to nm using the inset from SEM image and plotted as a histogram (D).

3.3 SAXS

Due to the complexity and polydispersity of blood, modelling the SAXS signal from the samples’ data was greatly hindered. Therefore, qualitative analysis and comparison of the scattering profiles were performed only for plasma samples (see Fig. 4).

Fig.4

Comparison of scattering profiles for human, rat, and camel for plasma (A) and clotted plasma (B). Scattering profile intensities were normalized to a unit for easier comparison between species.

Visual comparison of the scattering profiles reveals that SAXS scattering signals exhibit similar characteristics within the tested species, suggesting similarities in the structural composition of those samples on the probed nanometer scale between 30 to 400 Å. The broad shoulders positioned at 0.07 Å^-1 present for all plasma signals indicate the presence of structures of approximately 44 Å in diameter with a wide polydispersity of the size. A more informative comparison was performed by fitting parts of scattering profiles (see Table 4). The initial slope of the signal gives information about dimensionality of the analysed system, while the slope of the decay to zero reveals information about the so called Porod constant, which refers to surface roughness of the system (see Fig. 5). Presence of peaks or shoulders in the signal provides insight into the so-called radius of gyration (Rg) of the structures of the system (see Fig. 6). Radius of gyration was determined in reciprocal space using following formula:

$I (q) = I (0) e^{(\frac{q^{2} {Rg}^{2}}{3})}$ (1)

q is the scattering vector defined as 4π sin(θ)/λ, where θ is the angel between incident X-ray beam and the center of the detector and λ is the wavelength of the used X-rays (1.54 Å), I(q) stands for measured intensity, I(0) is the extrapolated zero angle intensity and Rg is the radius of gyration [31].

Scattering profiles were also recalculated to real space using indirect Fourier transform to calculate the radius of gyration from the real space and maximal diameter of the scatterer D_max: $I (q) = 4 π \int p (r) \frac{sin (qr)}{qr} qr$ (2)

D_max is the estimated maximal diameter of the scatterer and p(r) is the pair distribution function that describes the paired-set of all distances between points within an analyzed object (see Fig. 7).

The radius of gyration was then calculated using following formula: ${Rg}^{2} = \frac{\int r^{2} p (r) dr}{2 \int p (r) dr}$ (3)

Unlike the previous approach for estimating the radius of gyration, this one uses the whole scattering curve and is therefore more reliable and often used as a cross-check (see Table 5).

Fig.5

Explanations of Porod exponents.

Fig.6

Radius of gyration describes distribution of the components of an object around a point mass. It gives an approximate of size of scattering system.

Fig.7

Plotted pair distribution function.

Table 4

Comparison of fitting parameters for human, rat and camel plasma and blood related samples. Rg (radius of gyration)

	Human		Rat		Camel
	Plasma	Clotted plasma	Plasma	Clotted plasma	Plasma	Clotted plasma
Initial slope	0.5	0.6	0.6	0.6	0.6	0.9
Rg (Å)	25.1	25.7	26.5	27.9	25.9	25.1
Porod	3.8	3.8	3.1	3.7	3.7	3.4

Table 5

Comparison of radius of gyration in reciprocal and real space for tested plasma samples with the estimate of accuracy

	Human		Rat		Camel
	Plasma	Plasma clotted	Plasma	Plasma clotted	Plasma	Plasma clotted
Angular	0.0275 to	0.0267 to	0.0267 to	0.0267 to	0.0334 to	0.0335 to
range (1/Å)	0.2640	0.2270	0.2270	0.2270	0.2633	0.2566
Reciprocal space	25.8	26.5	27.8	28.7	25.9	26.2
Rg (Å)
D max (Å)	66.3	87.5	83.8	88.0	80.0	79.5
Real space	25.7	26.5	27.7	28.7	25.9	26.2
Rg (Å)
Total	69.0%	73.6%	78.8%	71.9%	61.6%	91.6%
estimate

4 Discussion

Comparative studies are a valuable approach in physiology when structure-functional relationships are the matter of interest. In this study, we were able to show distinct differences in clot formation between rats, camels, and horses in comparison to human. The species included were chosen due to their wide differences in blood properties: For instance, horse RBCs show pronounced aggregability, which leads to remarkable shear thinning and thixotropy of blood, whereas camel RBCs are known to not form Rouleaux structures at all. Shear thinning in camelid blood is therefore reduced and RBC sedimentation rate – and hence thixotropy – is very low. These two species are contrasting in terms of RBC aggregability and magnitude of blood shear thinning, whereas human blood fluidity is in between [32].

Platelet count and plasma fibrinogen concentration of horse and camel are broadly similar and comparable to human, however, platelet function may be different since it reflects a species-like manner. Platelet counts of rats are however so high, that platelets cannot be regarded as tracer elements for the suspension, which could by the way be the reason for the good suspension stability of rat blood. Whole blood viscosity in rats is even higher than in horses, although RBC aggregability is minute [32]. Due to the high number of platelets, coagulating blood of rats could mimic a hypercoaguable state in humans and we were specifically interested in the morphology of such clots.

The use of shear rheometry in the investigation of coagulation is a well-established method in research, but not common in clinical practice. Blood clotting is essentially a complex polymerisation process and, as such, can be compared to the curing of polymers, which show similar characteristics when investigated by shear rheometry. Key to coagulation is the plasmatic protein fibrinogen, a dimer consisting out of three pairs of polypeptide chains (Aα, Bβ, γ). During coagulation, fibrinopeptides A and B are separated off proteolytically by thrombin. The resulting monomeric fibrin forms small oligomers spontaneously. Initially short, the oligomers grow longitudinally and form two-stranded chains of fibrin molecules. Those so-called protofibrils aggregate laterally to make up fibres, which are subject to crosslinking by factor XIII [33].

Species differences in the viscoelastic properties of whole blood clots could possibly originate in altered structural composition of fibrinogen. While beta and gamma chains are relatively conserved [34], the alpha chain, especially the α-C region, differs greatly between rats and humans [35, 36]. As it was pointed out recently by Falvo et al., the structure α-C could explain differences in fibre extensibility between differences species [37]. α-C is implicated in lateral aggregation of protofibrils and it was demonstrated that genetically modified fibrin lacking α-C showed decreased stiffness [38]. However, how inter-species structural alterations in fibrinogen sequence effect physical properties is not fully known.

Physical clot properties are also dependent on network characteristics (e.g. fibre diameter, branching characteristics or porosity). Most importantly, higher fibrinogen concentrations are correlated with thicker fibres and increased network density in the final clot. Additionally, changes in pH, Ca^2 +, temperature, thrombin or factor XIII concentrations change the clot morphology and, hence, the clot stiffness [39, 40]. A highly branched fibre network, composed of fibres with intermediate thicknesses, should display the strongest network assembly [41]. Aside from temperature, we did not control for plasmatic factors, and as such, values obtained represent the physiological state of the animals studied.

Species differences of clot stiffness can also be effected by erythrocyte and thrombocyte concentrations [42]. Increasing haematocrit of human blood beyond 10 % lowers final clot stiffness, as network pore size is increased by incorporation of erythrocytes [43], and the material is weakened through this effect. Contact of RBCs to fibres on the clot surface seems to be more loose than platelet-clot interactions, although receptors for fibrinogen binding exist on the surface of human RBCs [44], and erythrocytes within the clot are known to be wrapped around by fibres tightly and are thus heavily deformed [45]. The force for clot compression is generated by thrombocytes, which are bound directly to the fibrinogen and its products via the GP IIb/IIIa receptor. Physiologically, this mechanism is thought to be important due to re-enabling blood flow past the thrombus site. In terms of clot viscoelasticity, platelet concentration is related to the final clot stiffness, and it was hypothesised that platelets play an important role for the rapid rise of the clot stiffness [46] after the initial lag phase.

The combined effects of fibre network properties, with incorporated erythrocytes and platelets, on the shear elastic modulus of the final clot can be seen in the rat: Not only are rat RBCs smaller in volume than human RBCs and thus occupy less space within the clot, thrombocyte concentration is increased approximately 10-fold, compared to humans. SEM imaging revealed a distinct morphology of rat clots, showing a highly convoluted network with small pores, which is reflected by a higher fractal dimension. The increased clot stiffness shown by us is therefore not surprising and indeed, it is known that rats are more procoaguable than humans: Siller-Matula et al. reported that rats exhibit shortened clotting times, increased clot formation rate and higher maximum clot firmness by using ROTEM [18]. We support the argument of other authors that the use of rats as model organisms of human coagulation disorders is not appropriate [47]. This may also be of specific interest in toxicological testing.

The role of platelets for the development of clot stiffness could also explain the unique clotting characteristics of camels: camel platelets are less sensitive to common activating substances [48] and we used only calcium to activate the coagulation process. Surprisingly to us, camels showed slow clot formation rate and exhibited no tendency to form a G’ plateau even after 70 minutes. This finding is supported by the ROTEM^® diagrams, which also show pin restraint slowly rising until the end of the measurement period, which was set at 60 minutes, was reached. While this suggests incomplete clot formation, no gross structural deficits were found upon examination with SEM.

To our best knowledge, we are first in reporting the viscoelastic properties of camel clots, although camelid plasmatic coagulation was recently studied. Small but significant shortenings of prothrombin time and activated partial thromboplastin time were found [24, 49], and the authors suggested that a quick coagulation is required in camels in order to minimize fluid loss in case of a trauma. However, conventional clotting times are not directly comparable to clotting time obtained by viscoelastic tests [50]. Although the coagulation system of the camel is commonly described as being procoagulatory, our findings do not confirm this statement. Our clotting time (defined as time until G’ equals 10 Pa) was retarded in comparison to human values. In the present study, sample drying prevented us from performing the measurements over a longer duration, which is what we suggest to do in order to gain more insight into camel blood clot formation.

Several authors investigated the equine coagulation system using viscoelastic testing devices [21, 51, 52], but no study applying rheometry is known to us. Clotting time by ROTEM^® was previously determined as about 490 seconds without the use of a clotting activator [21], which corresponds well to the clotting times obtained by us. Fibre diameter measured via SEM image analysis is also in agreement with previously published data, where it is given as range between 11–250 nm [53].

A unique morphological feature of equine clots was the presence of echinocytes (Fig. 2B). Echinocytes are commonly seen in blood smears of healthy horses after strenuous exercise, or may occur during intestinal disease [54]. Generally, the red cell membrane shows a species-specific lipid and protein composition [15]. Rising RBC quantities typically decrease clot stiffness as described above. But hypothetically, RBCs might also contribute to mechanical clot strength through their elastic modulus if red cell compression by the fibrin fibre network is assured to result in a compacted clot. Horse erythrocytes are known to be rather inflexible compared to many other mammalian species [55], which could originate from the absence of membrane proteins like protein bands 4.2, 6, and 8 [56]. Higher RBC membrane stiffness in horses could thereby add to the overall clot stiffness, especially as horses feature a higher RBC membrane per red cell ratio due to smaller RBCs in comparison to humans, at similar haematocrit values. This also applies to camels, another species known to have rigid RBCs. The elliptic camelid RBC membranes are even fortified to withstand the high osmotic fluctuations in blood plasma during dehydration and rapid rehydration. Clots of both animal species displayed higher elastic shear modulus compared to human clots.

Surprisingly, no correlation between rheometry and ROTEM^® was observed in this study, but sample sizes were very small as we did not aim at comparing those devices. However, we found differences in clotting and plateau times between rheometry and ROTEM^®. If this finding indicates a higher sensitivity of rheometry must be thoroughly elaborated by further studies, and the value of this finding in clinical settings is completely unclear, as yet.

Key to this study was the use of native, unaltered blood samples to reflect the physiological differences of the species investigated. We therefore did not control for differences in cell counts and fibrinogen concentration by design, as any sample manipulation can influence the clotting behaviour and the process of clot formation by activation and degranulation of platelets during centrifugation. For instance, in our preliminary studies with human blood samples, we observed artificial reductions in the platelet count through centrifugation of the blood sample at 800 U/min. One limitation in this study is the small sample size, however differences between the animals in terms of viscoelastic properties are clearly seen, whereas SEM and SAXS show less dissimilarities.

Since the visual examination of clot features is a biased approach by design, we also attempted semi-automated analysis in order to detect fibre diameter distribution as well as fractal dimension (df). While fully automated analysis of pure fibrin networks is possible [57], the presence of RBCs and platelet aggregates makes analysis of whole blood clots non-trivial. SEM pictures were therefore edited manually to define fibres and cells and the remaining algorithm was conducted automatically. This manual selection of fibres and cells remains a source of bias, especially due to the high depth of focus of SEM. Fibres seen are possible distributed over several image planes, which affect their apparent size.

Corresponding to visual analysis, calculated fibre diameters of human, horse and camel were comparable, whereas rats showed decreased fibre diameter. Human fibre diameter corresponded to values obtained recently from whole blood clots of healthy females [58]. SAXS analysis of pure fibrin clots by Weigandt et al. revealed fibre diameters of about 85 nm [13], which is somewhat smaller than in our calculations.

Fractal dimension (df) as a parameter of blood clot structure was proposed recently [59] as new biomarker of clot microstructure. In healthy humans, df of clots at the gel point lies in a narrow range of 1.74 (±0.07). Its rise is associated with prothrombotic conditions, for instance in acute myocardial infarction [60], ischaemic stroke [61] or due to malignant disease [62]. In this study, we calculated df of fully in-vitro developed clots and found similar values. Although one might expect that df changes continuously over the time course of clotting from the gel point to the G’ plateau, clot microstructure is rather fixed at the gel point. Since this primary structure fairly acts as a template for the subsequent fibrin mesh [60], it is therefore not surprising that our df values are in agreement with the values determined by others at the gel point.

Scattering methods are useful tools in structural characterization of complex materials, as samples are probed under its native conditions, and hence the occurrence of artefacts due to e.g. sample pre-treatment is reduced. SAXS scattering profiles can be analysed for obtaining e.g. size estimates of scattering structures also can easily be used to compare similar samples.

The scattering profiles of the clotted versus the unclotted plasma samples look quite similar. This would imply that the clotting process does not affect the shape of the sample on the nanoscale. However, the maximal sizes of features that could be resolved with our SAXS configuration are around 400 Å, which is well below the reported fibre diameter of approximately 800 Å and the fibre diameter range we determined using SEM image analysis.

It further seems as if, on the tested scale and irrespectively of the sample type, the samples consist of objects with dimensionality values between 0 and 1 (between sphere and fiber) at a given length scale between 30 and 400 Å. In the range of 35 to 75 Å the intensity decreases as a function of P/q^–r, where r is the Porod exponent and equals 4 for smooth structures and is between 3 and 4 for volume fractals. The Porod exponent observed in this study is between 3.1 and 3.8. In human plasma samples, it seems as if the fractal dimension in the Porod region is not affected by clotting. The behaviour of camel samples resembles the characteristics of human scattering profiles suggesting similar complexity of fibre network and also not much change due to clotting. Rat samples, however, are characterized by a lower Porod exponent value (3.1), in particular in the non-clotted state, suggesting its structure on the nanometer scale might be more complex and rough. Upon clotting the Porod exponent reaches similar values to human and camel plasma, although SEM visualisation (see Fig. 2C) and rheometry suggest a more complex clot structure.

All tested plasma samples feature shoulders at similar positions of the scattering profile, thus radius of gyration (Rg) for those samples is similar – around 25 Å, indicating the presence of objects with a few nanometer in diameter in the internal structure of a fibre. The measurement of radius of gyration was cross-checked in real space as well. Rg values obtained using this approach are more reliable as the fitting routine uses the whole scattering profile and not only the shoulder part, however they proved to be similar. The validity of this approach is also rated with high called total estimate – a criterion that compares the actual value with its ideal one, indicating high plausibility of the results. For this evaluation, though, a few points from low q data was excluded. This implies that there is a bigger scatterer present in the samples, affecting the scattering profiles we collected. Structure of this bigger scatterer could not be resolved with current SAXS configuration. From the shape of the pair distribution one could also conclude that the maximal averaged diameter of the scatterer within plasma is around 80 Å and that the averaged shape is ball-like as indicated by Gaussian-like distribution of the values.

All above hints that we were not able to resolve the fibre formation with the used SAXS set-up. Especially the sharp peak at the position q = 0.0282 Å^–1 (223 Å in real space) reported by Yeromonahos et al. (12) to be longitudinal periodicity of the nanostructure of the fibres [12] is not present in our plasma spectra. A possible explanation for that is the fact that Yeromonahos et al. worked on the pure mixture of fibrinogen and thrombin, whereas we analysed the whole plasma solution, which is mainly composed of albumins and globulins (55 % and 38 % of total serum content respectively), whereas fibrinogen accounts for only 7 % of total serum protein content. Both albumins and globulins are globular proteins with the radius of gyration of ca. 29 Å [63, 64] and 39.5 Å respectively [65, 66] and since together they account for over 90 % of total protein content in serum they might simply cover the signal of fibrinogen (Rg of 158 Å – calculated from the crystal structure PDB: 3GHG using FoXS server [67]) or fibrin. That would also explain minute influence of plasma coagulation on resulting scattering profiles as well as not pronounce differences between tested animals as the structures of both albumins and globulins is conserved within mammals [68]. To visualise the differences in the fibrin structure between different species a configuration allowing measurements of longer distances will be employed for further investigations.

In conclusion, clotting profiles obtained by rheometry show profound differences between the species investigated. In case of the rat, we were also able to demonstrate remarkable structural differences on the clot network level as determined by SEM. Rats have a highly procoagulant haemostatic system and are thus probably not accurate model organisms for coagulation studies targeted at humans. Regarding horses and camels, further studies are necessary to track how composition of blood alters clot architecture. Analysing clots at nanoscale using SAXS requires a sophisticated experimental setup and will be subject of further studies.

Footnotes

Acknowledgments

We are grateful to Dr. Monika Seltenhammer for providing us horse blood samples. We also thank Julian A. Skidmore to allow us use the camel blood samples for the viscoelastic testing, and Noemi Frisina for performing SAXS measurements of the camel plasma sample. Additionally, we would like to thank Philipp Siedlaczek for help with SEM imaging.

This study was presented at the 1st Hemorheology Days in Puchberg, Austria, July 19-21 2017.

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Viscoelasticity and structure of blood clots generated in-vitro by rheometry: A comparison between human,horse,rat,and camel

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSION:

Keywords

1 Background

2 Methods

2.1 Sample collection

2.2 Rheometry

2.3 ROTEM®

2.4 SEM

2.5 Analysis of the SEM images

2.6 SAXS

2.7 Statistics

3 Results

3.1 Viscoelastic tests

Footnotes

Acknowledgments

References

2.3 ROTEM^®