- Email: [email protected]
Flow rate calibration to determine cell-derived microparticles and homogeneity of blood components
Accepted Manuscript Title: Flow rate calibration to determine cell-derived microparticles and homogeneity of blood components Author: Egarit Noulsri Surada Lerdwana Kulvara Kittisares Attakorn Palasuwan Duangdao Palasuwan PII: DOI: Reference:
S1473-0502(17)30144-1 http://dx.doi.org/doi:10.1016/j.transci.2017.07.016 TRASCI 2209
To appear in: Received date: Revised date: Accepted date:
22-5-2017 3-7-2017 12-7-2017
Please cite this article as: Noulsri E, Lerdwana S, Kittisares K, Palasuwan A, Palasuwan D, Flow rate calibration to determine cell-derived microparticles and homogeneity of blood components. Transfusion and Apheresis Science (2017), http://dx.doi.org/10.1016/j.transci.2017.07.016 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
1 Flow rate calibration to determine cell-derived microparticles and homogeneity of blood components Egarit Noulsri1*, Surada Lerdwana2, Kulvara Kittisares3, Attakorn Palasuwan4, Duangdao Palasuwan4* 1
Research Division, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok,
Department of Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol
cr
2
ip t
Thailand
University, Bangkok, Thailand
Department of Transfusion Medicine, Faculty of Medicine Siriraj Hospital, Mahidol
us
3
University, Bangkok, Thailand
Department of Clinical Microscopy, Faculty of Allied Health Science, Chulalongkorn
an
4
University, Bangkok, Thailand
M
*Correspondence to Egarit Noulsri, Ph.D.
Ac ce pt e
Thailand 10700
d
Research Division, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok,
Tel.: +66-2-419-2795
Fax.: +66-2-411-0175
E-mail: [email protected] or
Duangdao (Nantakomol) Palasuwan, Ph.D.
Department of Clinical Microscopy, Faculty of Allied Health Science, Chulalongkorn University, Bangkok, Thailand 10330 Tel.: +66-2-218-1086 (ext.335) Fax.: +66-2-218-3771 E-mail: [email protected]
Page 1 of 23
2 Running title: Flow rate calibration for MP counting Keywords: cell-derived microparticle; flow rate calibration; platelet concentrate; packed red blood cell; transfusion
4
Number of table:
0
cr
Number of figure:
us
19
Ac ce pt e
d
M
an
Number of page:
ip t
Total word count: 4,190
Page 2 of 23
3 Abstract Background: Cell-derived microparticles (MPs) are currently of great interest to screening transfusion donors and blood components. However, the current approach to counting MPs is not affordable for routine laboratory use due to its high cost.
ip t
Aim: The current study aimed to investigate the potential use of flow-rate calibration for counting MPs in whole blood, packed red blood cells (PRBCs), and platelet concentrates
cr
(PCs).
us
Methods: The accuracy of flow-rate calibration was investigated by comparing the platelet
an
counts of an automated counter and a flow-rate calibrator. The concentration of MPs and their origins in whole blood (n = 100), PRBCs (n = 100), and PCs (n = 92) were determined
the blood components.
M
using a FACSCalibur. The MPs’ fold-changes were calculated to assess the homogeneity of
d
Results: Comparing the platelet counts conducted by automated counting and flow-rate
Ac ce pt e
calibration showed an r2 of 0.6 (y = 0.69x + 97,620). The CVs of the within-run and betweenrun variations of flow-rate calibration were 8.2% and 12.1%, respectively. The Bland-Altman plot showed a mean bias of -31,142 platelets/µL. MP enumeration revealed both the difference in MP levels and their origins in whole blood, PRBCs, and PCs. Screening the blood components demonstrated high heterogeneity of the MP levels in PCs when compared to whole blood and PRBCs.
Conclusions: The results of the present study suggest the accuracy and precision of flow-rate calibration for enumerating MPs. This flow-rate approach is affordable for assessing the homogeneity of MPs in blood components in routine laboratory practice.
Page 3 of 23
4 Introduction Cell-derived microparticles (MPs) are small particles with an average size of 0.1 1 µm. Upon activation or when undergoing apoptosis, cells release MPs through regulated molecular mechanisms. These MPs can originate from platelets (PMPs), red blood cells
ip t
(RMPs), leukocytes (LMPs), or endothelials (EMPs). Increased levels of MPs have been documented in several pathological circumstances. In the last few years, MP assessment has
cr
attracted increased attention in the field of transfusion medicine [1-3]. A number of studies
us
have demonstrated the association between increased MPs and complications in transfusion recipients [4]. Furthermore, differences in the levels of MPs or their heterogeneity in blood
an
products may affect the therapeutic efficiency and quality of prepared blood components [5].
practice.
M
Considering this, screening MPs in blood components is suggested in routine laboratory
d
Several approaches have been developed to quantify MP concentrations in biological
Ac ce pt e
specimens. An automated instrument for counting MPs has been evaluated recently [2]; however, this instrument is not yet available in several countries. In contrast, flow cytometry is a widely used approach for determining MPs [6]. This approach also enables quantifying the MPs per microliter by comparing to a known number of reference microbeads. Despite being highly accurate, use of this bead-based flow-cytometry approach is limited by the relatively high cost of commercial counting beads. To overcome this limitation, affordable approaches are needed. Calibration based on flow rate is a flow-cytometry approach used to determine cell concentration. This approach is based on the assumption that flow-rate calibrated through the flow cytometer remains unchanged [7]. Given this constant flow rate, the volume of the sample acquired in a specific time can be calculated using referent microbeads with a known concentration. This enables calculation of the concentration of cells per microliter by dividing the events counted in the same time by the previously calculated
Page 4 of 23
5 volume [8]. This flow-rate calibration offers several advantages with respect to sample manipulation and the cost of testing. For clinical application, flow-rate calibration has been used to enumerate CD4 T-lymphocytes and cell-derived MPs [9, 10]. However, no study has investigated its potential use for screening the quality of blood components.
ip t
The present study aimed to assess the accuracy and precision of flow-rate calibration for enumerating MPs and to apply this approach to determine the homogeneity of the MPs in
cr
blood components. The study’s results are applicable to the routine screening of transfusion
us
donors and blood components in general laboratories, especially in resource-limited
Ac ce pt e
d
M
an
countries.
Page 5 of 23
6 Materials and Methods Materials Annexin V conjugated with fluorescein isothiocyanate (Annexin V-FITC), CD41a conjugated with allophycocyanin (CD41a-APC), CD235a conjugated with phycoerythrin (CD235a-PE),
ip t
CD45 conjugated with peridinin chlorophyll (CD45-PerCP), and 10 × annexin-V binding buffer were purchased from ImmunoTools (Gladiolenweg, Friesoythe, Germany).
cr
CountBright™ absolute counting beads were obtained from Invitrogen (Carlsbad, CA, USA).
us
SPHERO™ Blank Calibration (1.09 µm) was purchased from Spherotech Inc. (Libertyville, IL, USA). FACSflow sheath fluid was from Bacton Dickinson (BD Bioscience; San Jose,
an
CA, USA).
M
Transfusion donors, sample collection, and complete blood count analysis This study was approved by the Institutional Review Board of Siriraj Hospital, Mahidol
d
University School of Medicine, Bangkok, Thailand (IRB no.240/2558). Written consent of
Ac ce pt e
donors was obtained after the procedure was explained in detail, including the time it would take and its possible hazards and benefits. After informed consent was obtained, blood samples were collected and processed using a standard procedure at the Department of Transfusion Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University. The whole blood samples were drawn into blood-collection tubes containing 3.2% sodium citrate (Greiner Bio-One GmbH; Kremsmünster, Austria) and then subjected to complete blood-count determination using a Siemens ADVIA 2120i hematology analyzer (Siemens Healthcare Diagnostics; Erlangen, Germany). The instrument was routinely calibrated as recommended by the manufacturer. Preparation of the blood components
Page 6 of 23
7 The whole blood from donor was collected into triple bags blood collecting systems (JMS Triple Blood Bag, CPD-SAGM solution; JMS Pte Ltd, Singapore). These systems included a 450 ml collecting bag containing 63 ml of CPD, a 400 ml bag containing 100 ml of SAGM red cell preservative solution and a 400 ml bag for 5 day platelet storage. All whole blood
ip t
units were stored at room temperature (22 ± 2°C) for up to 8 hours before preparation of the blood components. The whole blood units were centrifuged at 3100×g (Heraeus™
cr
Cryofuge™ 6000i; Thermo Electron LED GmbH, Langenselbold, Germany) for 5 minutes at
us
22 ± 2°C. Following, the units were separated into packed red cells (PRBCs) and platelet rich plasma (PRP) using a manual extractor. The PRP was then transferred into a 400 ml bag for
an
platelet storage. After centrifugation at 3800×g for 5 minutes at 22 ± 2°C, platelet poor plasma (PPP) and platelet concentrate (PC) were then separated. One hundreds milliliters of
M
SAGM was added into the PRBC units then stored at 4 ± 2 °C. The plasma units were transferred into a 400 ml bag then rapid frozen to -30°C using a shock freezer (TPSU 40,
d
Thalheimer; Ellwangen, Germany or MBF 12, Dometic; Hosingen, Luxembourg) and stored
Ac ce pt e
at -30 ± 10°C. The PC units were left stationary for 1 hour and then stored at 22 ± 2°C in a platelet incubator (PC3200i Helmer; Noblesville, IN). Sample staining and flow cytometry analysis of platelets and MPs The samples were first diluted 1:100 with phosphate-buffered saline (PBS). Then, 5 microliters of the diluted samples were transferred to other polystyrene tubes containing 3 µL of annexin V-FITC, 5 µL of CD41-APC, 5 µL of CD235a-PE, 5 µL of CD45-PerCP, and 20 µL of 1x annexin-V binding buffer. After 15 min of incubation in the dark at room temperature, 300 µL of 1x annexin-V buffer was added to the tube. The stained samples were analyzed in a FACSCalibur flow cytometer (BD; San Jose, CA, USA) equipped with dual 75mW blue lasers (488 nm) and 40-mW red lasers (640 nm).
Page 7 of 23
8 Prior to the study, CaliBRITE™ Beads with FACSComp™ software (BD; San Jose, CA, USA) were used to optimize and calibrate the instrument. The forward scatter (FSC), side scatter (SSC), and fluorescent intensity parameters were set as logarithmic scale. The threshold was set at FSC to exclude debris and signal noise. To determine the platelet counts,
ip t
first, the FSC vs. SSC dot-plot was used to identify the platelet population. Then, the SSC vs. CD41a dot-plot was used to determine the events of the platelets (Figure 1A). To determine
cr
the MPs, the MP gate was established according to 1-µm standard beads (Figure 1B). The
us
annexin V vs. SSC dot plot was used to identify MPs positive for annexin V (Ann+ MPs). Then, events of RMPs, PMPs, and LMPs of these previously gated Ann+ MPs were
an
determined on the histogram plots of CD235a-PE, CD41a-APC, and CD45-PerCP, respectively. The concentrations of cells and MPs per microliter were determined using flow-
d
Heterogeneity of the blood products
M
rate calibration, as described previously [11].
Ac ce pt e
To determine the heterogeneity of the blood components, the averages of the total levels of MPs, RMPs, and PMPs were calculated. Then, the fold-change of each blood component was determined by dividing each individual measurement by the average for that component, and then each fold-change was plotted on the histogram. The measurements having fold-changes of more than 1 and 2 were identified, and those having more than a 2-fold change between the blood products were compared. Statistical analysis
The data were analyzed and graphed using GraphPad Prism version 5.01 (GraphPad; San Diego, CA, USA). Results were expressed as mean, standard deviation (SD), and coefficient of variation (CV). The normality of the data was assessed using a Kolmogorov-Smirnov test. Linear regression and a Bland-Altman plot were used to determine the relationship and the
Page 8 of 23
9 bias between the two methods, respectively. A Mann-Whitney U-test was used to compare
Ac ce pt e
d
M
an
us
cr
ip t
differences between groups. A p value < 0.05 was considered statistically significant.
Page 9 of 23
10 Results Accuracy and precision of flow-rate calibration for enumerating cell concentration To determine the linearity of the flow-rate calibration, the whole blood was diluted 1:10, 1:100, 1:1000, 1:10000, and 1:100000 with PBS. The diluted samples were analyzed for
ip t
number of platelets using both flow-rate calibration and automated counting. The results from each method were compared with the expected measurement. The results showed that the
cr
linearity of the flow-rate was between 2,486 and 226,000 platelets/µL. The linearity of the
us
automated hematology cell counter was between 22,600 and 260,000 platelets/µL.
an
To assess the accuracy of flow-rate calibration, 100 blood samples were analyzed for platelet counts using both flow-rate calibration and automated counting. The results showed that the
M
correlation coefficient was 0.6 and the linear regression equation was y = 0.69x + 97,620 (Figure 2A). The Bland-Altman plot demonstrated a mean bias of -31,142 platelets/µL and a
Ac ce pt e
d
limit of agreement of from -105,462 platelets/µL to +43,176 platelets/µL (Figure 2B). A further experiment was conducted to determine measurement precision. For the within-run variation, 10 replicates of counting bead were determined for the concentration. The data demonstrated a CV of 8.2%. For the between-run variation, 5 replications of counting bead were determined consecutively for 5 days. The results showed a CV of 12.1%. Collectively, these data suggested the accuracy and precision of flow-rate calibration for determining cell concentration.
Quantification of MPs and their origin in whole blood, PRBCs, and PCs First, we optimized the flow-cytometry analysis of MPs. Platelet-rich plasma samples were prepared by centrifugation and then incubated with calcium-ionophore A23187 at a final concentration of 10 µM at 37°C. After 30 min, the samples were analyzed by a flow
Page 10 of 23
11 cytometer. The results showed a five-fold increase in the PMP level of the A123187-treated PRP compared to the level in the control, suggesting that the flow-cytometry gating strategy was optimized for further MP analysis. The next experiment was conducted to determine the levels of MPs in whole blood and blood
ip t
components. Figure 3 shows the number of total MPs, RMPs, PMPs, and LMPs in whole
cr
blood (n = 100), PRBCs (n = 100), and PCs (n = 92).
us
In the whole blood samples, the concentration of total MPs was 26,647 ± 12,277 particles/µL; 11,643-86,667 particles/µL. The number of RMPs (11,749 ± 3,817 particles/µL; 4,990-
an
24,360 particles/µL) was slightly higher than that of PMPs (10,380 ± 4,239 particles/µL;
particles/µL; 1-1,206 particles/µL).
M
2,842-27,907 particles/µL). The LMPs showed the lowest concentration (304 ± 356
d
In the PRBCs, the total number of MPs was 29,349 ± 11,817 particles/µL; 12,808-107,169
Ac ce pt e
particles/µL. The RMP concentration (18,226 ± 6,172 particles/µL; 7,714-42,004 particles/µL) was significantly higher than the PMP (6,741 ± 3,328 particles/µL; 2,33027,907 particles/µL) and LMP (340 ± 360 particles/µL; 1-2,014 particles/µL) concentrations.
In the PCs, the MP total was 39,692 ± 27,368 particles/µL; 16,304-139,153 particles/µL. Further characterization of the origin revealed that the PMP concentration (15,292 ± 8,124 particles/µL; 2,773-56,324 particles/µL) was higher than the RMP (9,535 ± 2,974 particles/µL; 4,819-22,017 particles/µL) and LMP (326 ± 373 particles/µL; 1-1,943 particles/µL) concentrations. Taken together, these data suggest the differences in MP concentrations and their origins in various blood components. Homogeneity of MP levels in whole blood, PRBCs, and PCs
Page 11 of 23
12 The next experiment was conducted to determine the potential use of flow-rate calibration to assess the homogeneity of blood components. Figure 4 shows the fold-changes of the total levels of MPs, RMPs, and PMPs in whole blood, PRBCs, and PCs. For the whole blood samples, 67 measurements of total MPs showed fold-changes of less
ip t
than 1 (Figure 4A), and 4 measurements showed fold-changes greater than 2. For the RMPs, 57 measurements showed fold-changes of less than 1, and 2 measurements showed fold-
cr
changes greater than 2. For the PMPs, 58 measurements showed fold-changes of less than 1,
us
and 3 measurements showed fold-changes greater than 2.
an
For the PRBCs, the frequency plot showed 61 measurements of the total MPs with foldchanges of less than 1 (Figure 4B) and 2 measurements with fold-changes greater than 2. For
M
the RMPs, 50 measurements showed fold-changes of less than 1, and 2 measurements showed fold-changes greater than 2. The frequency plot of PMPs showed 56 measurements
d
with fold-changes of less than 1 and 2 measurements with fold-changes greater than 2.
Ac ce pt e
For the PCs, further analysis showed 77 measurements of the total MPs with fold-changes of less than 1 (Figure 4C) and 10 measurements with fold-changes greater than 2. Of these 10 measurements, 3 had fold-changes greater than 3. For the RMPs, 22 measurements showed fold-changes of less than 1. In addition, 14 and 5 measurements showed fold-changes greater than 2 and 3, respectively. Further analysis of the PMPs showed 66 measurements with foldchanges of less than 1 and 5 measurements with fold-changes greater than 2. The high number of PC measurements having fold-changes greater than 2 and 3 suggests high heterogeneity of MP levels in the PCs compared to those in the whole blood and PRBCs.
Page 12 of 23
13 Discussion Interest in quantifying the MPs in blood components for use as a potential biomarker is increasing [1-3]. Therefore, it is necessary to develop an alternative methodology that is affordable, accurate, and reliable for use in routine laboratory practice. The present
ip t
investigation validated flow-rate calibration as a method for enumerating MPs when screening blood donors. In addition, it highlighted the effects of this approach on quantifying
cr
MPs in various blood components.
us
The results of the present study suggest that flow-rate calibration is highly accurate and precise when enumerating cells and particles. This suggestion was supported by the dilution
an
experiment, which showed good correlation between the expected platelet count and the platelet count measured using flow-rate calibration. In addition, the CVs of the within-run
M
and between-run variations of the approach were less than 10% and 15%, respectively. These
d
results correlated with those of previous investigations demonstrating the high precision and
Ac ce pt e
accuracy of flow cytometry based on flow rate for enumerating CD4+ T-lymphocytes and MPs [8, 9, 12]. Apart from its accuracy and precision, flow-rate calibration has other advantages that make it suitable for use in routine laboratory practice. One of the most important advantages is its affordability. Flow-rate calibration obviates the need to add counting beads to each sample. Therefore, it can be used to screen a number of samples at lower cost than bead-based flow cytometry. Another advantage is the availability of flow cytometers, which are now commonly used in laboratories in many countries. For example, Thailand has 120 flow cytometers in hospitals and laboratories nationwide [13]. The method of counting MPs based on flow rate can be applied in a general laboratory without additional instruments. Despite the advantages of flow-rate calibration for MP counting, several points must be considered. The principle of flow-rate calibration is based on the assumption that the flow cytometer used in the study shows a constant flow rate. Instability of the flow
Page 13 of 23
14 cytometer’s flow rate results in the inaccuracy of the MP count. To avoid this error, it is necessary to monitor the count rate vs. the time. Recently, the effects of swarm and coincidence detection on MP quantitation have been proposed [14]. The swarm effect may occur if the flow rate is set too high, leading to inaccuracy in MP enumeration. To avoid
ip t
swarm detection, dilution experiments should be performed to determine whether the number of MPs decreases in proportion to the dilution. Another point to be considered is coincidence.
cr
This problem occurs when the concentration is too high, resulting in a low incidence of
us
double-stained particles. Therefore, to identify the coincidence effect, only single-stained beads should be used.
an
Further experiments screening the MPs in whole blood from donors suggested less variability in the MP levels. This suggestion was supported by the finding that only 2% of the
M
measurements showed fold-changes in the levels of total MPs, RMPs, and PMPs that were
d
greater than 2. In addition, the unprocessed whole blood samples showed no differences in
Ac ce pt e
the levels of RMPs and PMPs. Recent studies have suggested that variability in donors is associated with increased MP levels in transfused blood [14, 15]. This variability could be caused by underlying diseases in donors. This hypothesis is supported by previous studies showing a high prevalence of donors with thalassemia and deficiencies in glucose 6 phosphate dehydrogenase [16-18]. These diseases include pathogenicity in red blood cells and oxidative status, resulting in increased MPs in the blood circulation. Increased MPs in blood products derived from these donors might contribute to complications in transfusion recipients. Even with lessened variability, routine screening donors’ MPs might be necessary to reduce transfusion complications in recipients that are associated with increased MP levels. Compared to whole blood and PRBCs, PCs showed a higher frequency of fold-changes greater than 2 in the total MPs, RMPs, and PMPs, suggesting higher heterogeneity of the MPs in PCs. Such heterogeneity in blood components has been attributed to multiple factors,
Page 14 of 23
15 including procedures for preparing blood components and storage lesion [19, 20]. In addition, studies have suggested that this heterogeneity in blood components affects their therapeutic efficiency [2]. Hence, it may be necessary to categorize blood components to isolate those with high MP levels for specific use and management. For example, blood components with
ip t
high MP levels might be selected for patients with bleeding tendencies. Considering the increased ability of MPs to activate coagulation, such a practice might reduce the number of
cr
units needed to correct transfusion recipients’ bleeding problems. This management strategy
complications associated with multiple-unit transfusions.
us
might help increase the therapeutic efficiency of transfusion blood products and reduce the
an
In summary, the results of the present study demonstrated the potential uses of flow cytometry based on flow rate to enumerate MP concentrations in various blood products. In
M
addition, the results demonstrated the potential for using this approach in routine laboratory
d
practice to screen MP levels in both whole blood samples from transfusion donors and blood
Ac ce pt e
components. Routine screening for MP concentration can be important to increasing therapeutic efficiency and reducing transfusion complications associated with MPs.
Page 15 of 23
16 Figure legends Figure 1. Flow cytometry gating strategy for enumerating platelets and MPs. (A) First, the platelets are identified on the FSC vs. SSC dot-plot. Then, the events of the platelets positive for CD41a from the previous gated population are determined on the CD41a vs. SSC
ip t
dot-plot. (B) The MPs gate is defined on the FSC vs. SSC dot-plot. The events of the annexin V positive MPs or total MPs are determined on the annexin V vs. SSC dot-plot. The events of
cr
the RMPs, PMPs, and LMPs of the annexin V positive MPs are determined on the histogram
us
plot of CD235a, CD41a, and CD45.
Figure 2. Comparison of platelet counts conducted by automated counter and flow-rate
an
calibration. (A) Linear regression analysis of the platelet counts obtained from the flow cytometer on the x-axis and automated cell counter on the y-axis. The plot also indicates the
M
r2 and the linear regression equation. (B) The Bland-Altman plot shows the bias between the
Ac ce pt e
FRC: flow-rate calibration.
d
platelet counts conducted using the two methods. The mean bias and the LOA are indicated.
Figure 3. Levels of MPs and their origin in whole blood and blood components. Bar plots represent the number of the total MPs, RMPs, PMPs, and LMPs in (A) whole blood, (B) packed red blood cells, and (C) platelet concentrate. * indicates significant differences between groups at p < 0.0001. Error bars present mean±s.d Figure 4. Homogeneity of the MPs in whole blood and blood components. The frequency plots demonstrate the fold-changes of the total MPs, RMPs, and PMPs in (A) whole blood, (B) packed red blood cells, and (C) platelet concentrate.
Page 16 of 23
17 Acknowledgments This research was supported by the National Research University Project, Office of Higher Education Commission (NRU59-010-HR). Authors thank the Faculty of Medicine, Siriraj
Ac ce pt e
d
M
an
us
cr
ip t
Hospital, Mahidol University for supporting the research project.
Page 17 of 23
18 References
Ac ce pt e
d
M
an
us
cr
ip t
[1] Burnouf T, Chou ML, Goubran H, Cognasse F, Garraud O, Seghatchian J. An overview of the role of microparticles/microvesicles in blood components: Are they clinically beneficial or harmful? Transfusion and apheresis science : official journal of the World Apheresis Association : official journal of the European Society for Haemapheresis. 2015;53:137-45. [2] Kanzler P, Mahoney A, Leitner G, Witt V, Maurer-Spurej E. Microparticle detection to guide platelet management for the reduction of platelet refractoriness in children - A study proposal. Transfusion and apheresis science : official journal of the World Apheresis Association : official journal of the European Society for Haemapheresis. 2016. [3] Noulsri E, Udomwinijsilp P, Lerdwana S, Chongkolwatana V, Permpikul P. Differences in levels of platelet-derived microparticles in platelet components prepared using the platelet rich plasma, buffy coat, and apheresis procedures. Transfusion and apheresis science : official journal of the World Apheresis Association : official journal of the European Society for Haemapheresis. 2017;56:135-40. [4] Jy W, Ricci M, Shariatmadar S, Gomez-Marin O, Horstman LH, Ahn YS. Microparticles in stored red blood cells as potential mediators of transfusion complications. Transfusion. 2011;51:886-93. [5] Kriebardis AG, Antonelou MH, Georgatzakou HT, Tzounakas VL, Stamoulis KE, Papassideri IS. Microparticles variability in fresh frozen plasma: preparation protocol and storage time effects. Blood transfusion = Trasfusione del sangue. 2016;14:228-37. [6] Poncelet P, Robert S, Bailly N, Garnache-Ottou F, Bouriche T, Devalet B, et al. Tips and tricks for flow cytometry-based analysis and counting of microparticles. Transfusion and apheresis science : official journal of the World Apheresis Association : official journal of the European Society for Haemapheresis. 2015;53:110-26. [7] Bergeron M, Lustyik G, Phaneuf S, Ding T, Nicholson JK, Janossy G, et al. Stability of currently used cytometers facilitates the identification of pipetting errors and their volumetric operation: "time" can tell all. Cytometry Part B, Clinical cytometry. 2003;52:37-9. [8] Storie I, Sawle A, Goodfellow K, Whitby L, Granger V, Reilly JT, et al. Flow rate calibration I: a novel approach for performing absolute cell counts. Cytometry Part B, Clinical cytometry. 2003;55:1-7. [9] Pattanapanyasat K, Chimma P, Sratongno P, Lerdwana S. CD4+ T-lymphocyte enumeration with a flow-rate based method in three flow cytometers with different years in service. Cytometry Part B, Clinical cytometry. 2008;74:310-8. [10] Nantakomol D, Chimma P, Day NP, Dondorp AM, Combes V, Krudsood S, et al. Quantitation of cell-derived microparticles in plasma using flow rate based calibration. The Southeast Asian journal of tropical medicine and public health. 2008;39:146-53. [11] Walker CL, Whitby L, Granger V, Storie I, Reilly JT, Barnett D. Flow rate calibration. III. The use of stabilized biostandards to calibrate the flow rate and calculate absolute CD4+ T-cell counts. Cytometry Part B, Clinical cytometry. 2006;70:154-62. [12] Nielsen MH, Beck-Nielsen H, Andersen MN, Handberg A. A flow cytometric method for characterization of circulating cell-derived microparticles in plasma. Journal of extracellular vesicles. 2014;3. [13] Noulsri E, Lerdwana S, Pattanapanyasat K. Long-term external quality assessment program for CD4+ T-lymphocyte enumeration in Thailand. Accreditation and Quality Assurance. 2016;21:367-75.
Page 18 of 23
19
Ac ce pt e
d
M
an
us
cr
ip t
[14] Chandler WL. Measurement of microvesicle levels in human blood using flow cytometry. Cytometry Part B, Clinical cytometry. 2016;90:326-36. [15] Simak J, Gelderman MP. Cell membrane microparticles in blood and blood products: potentially pathogenic agents and diagnostic markers. Transfusion medicine reviews. 2006;20:1-26. [16] Kriebardis A, Antonelou M, Stamoulis K, Papassideri I. Cell-derived microparticles in stored blood products: innocent-bystanders or effective mediators of post-transfusion reactions? Blood transfusion = Trasfusione del sangue. 2012;10 Suppl 2:s25-38. [17] Alabdulaali MK, Alayed KM, Alshaikh AF, Almashhadani SA. Prevalence of glucose-6phosphate dehydrogenase deficiency and sickle cell trait among blood donors in Riyadh. Asian journal of transfusion science. 2010;4:31-3. [18] Francis RO, Jhang JS, Pham HP, Hod EA, Zimring JC, Spitalnik SL. Glucose-6phosphate dehydrogenase deficiency in transfusion medicine: the unknown risks. Vox sanguinis. 2013;105:271-82. [19] Maffi D, Pasquino MT, Mandarino L, Tortora P, Girelli G, Meo D, et al. Glucose-6phosphate dehydrogenase deficiency in Italian blood donors: prevalence and molecular defect characterization. Vox sanguinis. 2014;106:227-33. [20] Ayers L, Kohler M, Harrison P, Sargent I, Dragovic R, Schaap M, et al. Measurement of circulating cell-derived microparticles by flow cytometry: sources of variability within the assay. Thrombosis research. 2011;127:370-7. [21] Yuana Y, Bertina RM, Osanto S. Pre-analytical and analytical issues in the analysis of blood microparticles. Thrombosis and haemostasis. 2011;105:396-408.
Page 19 of 23
Page 20 of 23
ed
ce pt
Ac M an
c
us
ed pt ce Ac
Page 21 of 23
ed pt ce Ac
Page 22 of 23
Page 23 of 23
pt e
ce
Ac d
M
an
cr
us
i
S1473-0502(17)30144-1 http://dx.doi.org/doi:10.1016/j.transci.2017.07.016 TRASCI 2209
To appear in: Received date: Revised date: Accepted date:
22-5-2017 3-7-2017 12-7-2017
Please cite this article as: Noulsri E, Lerdwana S, Kittisares K, Palasuwan A, Palasuwan D, Flow rate calibration to determine cell-derived microparticles and homogeneity of blood components. Transfusion and Apheresis Science (2017), http://dx.doi.org/10.1016/j.transci.2017.07.016 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
1 Flow rate calibration to determine cell-derived microparticles and homogeneity of blood components Egarit Noulsri1*, Surada Lerdwana2, Kulvara Kittisares3, Attakorn Palasuwan4, Duangdao Palasuwan4* 1
Research Division, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok,
Department of Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol
cr
2
ip t
Thailand
University, Bangkok, Thailand
Department of Transfusion Medicine, Faculty of Medicine Siriraj Hospital, Mahidol
us
3
University, Bangkok, Thailand
Department of Clinical Microscopy, Faculty of Allied Health Science, Chulalongkorn
an
4
University, Bangkok, Thailand
M
*Correspondence to Egarit Noulsri, Ph.D.
Ac ce pt e
Thailand 10700
d
Research Division, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok,
Tel.: +66-2-419-2795
Fax.: +66-2-411-0175
E-mail: [email protected] or
Duangdao (Nantakomol) Palasuwan, Ph.D.
Department of Clinical Microscopy, Faculty of Allied Health Science, Chulalongkorn University, Bangkok, Thailand 10330 Tel.: +66-2-218-1086 (ext.335) Fax.: +66-2-218-3771 E-mail: [email protected]
Page 1 of 23
2 Running title: Flow rate calibration for MP counting Keywords: cell-derived microparticle; flow rate calibration; platelet concentrate; packed red blood cell; transfusion
4
Number of table:
0
cr
Number of figure:
us
19
Ac ce pt e
d
M
an
Number of page:
ip t
Total word count: 4,190
Page 2 of 23
3 Abstract Background: Cell-derived microparticles (MPs) are currently of great interest to screening transfusion donors and blood components. However, the current approach to counting MPs is not affordable for routine laboratory use due to its high cost.
ip t
Aim: The current study aimed to investigate the potential use of flow-rate calibration for counting MPs in whole blood, packed red blood cells (PRBCs), and platelet concentrates
cr
(PCs).
us
Methods: The accuracy of flow-rate calibration was investigated by comparing the platelet
an
counts of an automated counter and a flow-rate calibrator. The concentration of MPs and their origins in whole blood (n = 100), PRBCs (n = 100), and PCs (n = 92) were determined
the blood components.
M
using a FACSCalibur. The MPs’ fold-changes were calculated to assess the homogeneity of
d
Results: Comparing the platelet counts conducted by automated counting and flow-rate
Ac ce pt e
calibration showed an r2 of 0.6 (y = 0.69x + 97,620). The CVs of the within-run and betweenrun variations of flow-rate calibration were 8.2% and 12.1%, respectively. The Bland-Altman plot showed a mean bias of -31,142 platelets/µL. MP enumeration revealed both the difference in MP levels and their origins in whole blood, PRBCs, and PCs. Screening the blood components demonstrated high heterogeneity of the MP levels in PCs when compared to whole blood and PRBCs.
Conclusions: The results of the present study suggest the accuracy and precision of flow-rate calibration for enumerating MPs. This flow-rate approach is affordable for assessing the homogeneity of MPs in blood components in routine laboratory practice.
Page 3 of 23
4 Introduction Cell-derived microparticles (MPs) are small particles with an average size of 0.1 1 µm. Upon activation or when undergoing apoptosis, cells release MPs through regulated molecular mechanisms. These MPs can originate from platelets (PMPs), red blood cells
ip t
(RMPs), leukocytes (LMPs), or endothelials (EMPs). Increased levels of MPs have been documented in several pathological circumstances. In the last few years, MP assessment has
cr
attracted increased attention in the field of transfusion medicine [1-3]. A number of studies
us
have demonstrated the association between increased MPs and complications in transfusion recipients [4]. Furthermore, differences in the levels of MPs or their heterogeneity in blood
an
products may affect the therapeutic efficiency and quality of prepared blood components [5].
practice.
M
Considering this, screening MPs in blood components is suggested in routine laboratory
d
Several approaches have been developed to quantify MP concentrations in biological
Ac ce pt e
specimens. An automated instrument for counting MPs has been evaluated recently [2]; however, this instrument is not yet available in several countries. In contrast, flow cytometry is a widely used approach for determining MPs [6]. This approach also enables quantifying the MPs per microliter by comparing to a known number of reference microbeads. Despite being highly accurate, use of this bead-based flow-cytometry approach is limited by the relatively high cost of commercial counting beads. To overcome this limitation, affordable approaches are needed. Calibration based on flow rate is a flow-cytometry approach used to determine cell concentration. This approach is based on the assumption that flow-rate calibrated through the flow cytometer remains unchanged [7]. Given this constant flow rate, the volume of the sample acquired in a specific time can be calculated using referent microbeads with a known concentration. This enables calculation of the concentration of cells per microliter by dividing the events counted in the same time by the previously calculated
Page 4 of 23
5 volume [8]. This flow-rate calibration offers several advantages with respect to sample manipulation and the cost of testing. For clinical application, flow-rate calibration has been used to enumerate CD4 T-lymphocytes and cell-derived MPs [9, 10]. However, no study has investigated its potential use for screening the quality of blood components.
ip t
The present study aimed to assess the accuracy and precision of flow-rate calibration for enumerating MPs and to apply this approach to determine the homogeneity of the MPs in
cr
blood components. The study’s results are applicable to the routine screening of transfusion
us
donors and blood components in general laboratories, especially in resource-limited
Ac ce pt e
d
M
an
countries.
Page 5 of 23
6 Materials and Methods Materials Annexin V conjugated with fluorescein isothiocyanate (Annexin V-FITC), CD41a conjugated with allophycocyanin (CD41a-APC), CD235a conjugated with phycoerythrin (CD235a-PE),
ip t
CD45 conjugated with peridinin chlorophyll (CD45-PerCP), and 10 × annexin-V binding buffer were purchased from ImmunoTools (Gladiolenweg, Friesoythe, Germany).
cr
CountBright™ absolute counting beads were obtained from Invitrogen (Carlsbad, CA, USA).
us
SPHERO™ Blank Calibration (1.09 µm) was purchased from Spherotech Inc. (Libertyville, IL, USA). FACSflow sheath fluid was from Bacton Dickinson (BD Bioscience; San Jose,
an
CA, USA).
M
Transfusion donors, sample collection, and complete blood count analysis This study was approved by the Institutional Review Board of Siriraj Hospital, Mahidol
d
University School of Medicine, Bangkok, Thailand (IRB no.240/2558). Written consent of
Ac ce pt e
donors was obtained after the procedure was explained in detail, including the time it would take and its possible hazards and benefits. After informed consent was obtained, blood samples were collected and processed using a standard procedure at the Department of Transfusion Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University. The whole blood samples were drawn into blood-collection tubes containing 3.2% sodium citrate (Greiner Bio-One GmbH; Kremsmünster, Austria) and then subjected to complete blood-count determination using a Siemens ADVIA 2120i hematology analyzer (Siemens Healthcare Diagnostics; Erlangen, Germany). The instrument was routinely calibrated as recommended by the manufacturer. Preparation of the blood components
Page 6 of 23
7 The whole blood from donor was collected into triple bags blood collecting systems (JMS Triple Blood Bag, CPD-SAGM solution; JMS Pte Ltd, Singapore). These systems included a 450 ml collecting bag containing 63 ml of CPD, a 400 ml bag containing 100 ml of SAGM red cell preservative solution and a 400 ml bag for 5 day platelet storage. All whole blood
ip t
units were stored at room temperature (22 ± 2°C) for up to 8 hours before preparation of the blood components. The whole blood units were centrifuged at 3100×g (Heraeus™
cr
Cryofuge™ 6000i; Thermo Electron LED GmbH, Langenselbold, Germany) for 5 minutes at
us
22 ± 2°C. Following, the units were separated into packed red cells (PRBCs) and platelet rich plasma (PRP) using a manual extractor. The PRP was then transferred into a 400 ml bag for
an
platelet storage. After centrifugation at 3800×g for 5 minutes at 22 ± 2°C, platelet poor plasma (PPP) and platelet concentrate (PC) were then separated. One hundreds milliliters of
M
SAGM was added into the PRBC units then stored at 4 ± 2 °C. The plasma units were transferred into a 400 ml bag then rapid frozen to -30°C using a shock freezer (TPSU 40,
d
Thalheimer; Ellwangen, Germany or MBF 12, Dometic; Hosingen, Luxembourg) and stored
Ac ce pt e
at -30 ± 10°C. The PC units were left stationary for 1 hour and then stored at 22 ± 2°C in a platelet incubator (PC3200i Helmer; Noblesville, IN). Sample staining and flow cytometry analysis of platelets and MPs The samples were first diluted 1:100 with phosphate-buffered saline (PBS). Then, 5 microliters of the diluted samples were transferred to other polystyrene tubes containing 3 µL of annexin V-FITC, 5 µL of CD41-APC, 5 µL of CD235a-PE, 5 µL of CD45-PerCP, and 20 µL of 1x annexin-V binding buffer. After 15 min of incubation in the dark at room temperature, 300 µL of 1x annexin-V buffer was added to the tube. The stained samples were analyzed in a FACSCalibur flow cytometer (BD; San Jose, CA, USA) equipped with dual 75mW blue lasers (488 nm) and 40-mW red lasers (640 nm).
Page 7 of 23
8 Prior to the study, CaliBRITE™ Beads with FACSComp™ software (BD; San Jose, CA, USA) were used to optimize and calibrate the instrument. The forward scatter (FSC), side scatter (SSC), and fluorescent intensity parameters were set as logarithmic scale. The threshold was set at FSC to exclude debris and signal noise. To determine the platelet counts,
ip t
first, the FSC vs. SSC dot-plot was used to identify the platelet population. Then, the SSC vs. CD41a dot-plot was used to determine the events of the platelets (Figure 1A). To determine
cr
the MPs, the MP gate was established according to 1-µm standard beads (Figure 1B). The
us
annexin V vs. SSC dot plot was used to identify MPs positive for annexin V (Ann+ MPs). Then, events of RMPs, PMPs, and LMPs of these previously gated Ann+ MPs were
an
determined on the histogram plots of CD235a-PE, CD41a-APC, and CD45-PerCP, respectively. The concentrations of cells and MPs per microliter were determined using flow-
d
Heterogeneity of the blood products
M
rate calibration, as described previously [11].
Ac ce pt e
To determine the heterogeneity of the blood components, the averages of the total levels of MPs, RMPs, and PMPs were calculated. Then, the fold-change of each blood component was determined by dividing each individual measurement by the average for that component, and then each fold-change was plotted on the histogram. The measurements having fold-changes of more than 1 and 2 were identified, and those having more than a 2-fold change between the blood products were compared. Statistical analysis
The data were analyzed and graphed using GraphPad Prism version 5.01 (GraphPad; San Diego, CA, USA). Results were expressed as mean, standard deviation (SD), and coefficient of variation (CV). The normality of the data was assessed using a Kolmogorov-Smirnov test. Linear regression and a Bland-Altman plot were used to determine the relationship and the
Page 8 of 23
9 bias between the two methods, respectively. A Mann-Whitney U-test was used to compare
Ac ce pt e
d
M
an
us
cr
ip t
differences between groups. A p value < 0.05 was considered statistically significant.
Page 9 of 23
10 Results Accuracy and precision of flow-rate calibration for enumerating cell concentration To determine the linearity of the flow-rate calibration, the whole blood was diluted 1:10, 1:100, 1:1000, 1:10000, and 1:100000 with PBS. The diluted samples were analyzed for
ip t
number of platelets using both flow-rate calibration and automated counting. The results from each method were compared with the expected measurement. The results showed that the
cr
linearity of the flow-rate was between 2,486 and 226,000 platelets/µL. The linearity of the
us
automated hematology cell counter was between 22,600 and 260,000 platelets/µL.
an
To assess the accuracy of flow-rate calibration, 100 blood samples were analyzed for platelet counts using both flow-rate calibration and automated counting. The results showed that the
M
correlation coefficient was 0.6 and the linear regression equation was y = 0.69x + 97,620 (Figure 2A). The Bland-Altman plot demonstrated a mean bias of -31,142 platelets/µL and a
Ac ce pt e
d
limit of agreement of from -105,462 platelets/µL to +43,176 platelets/µL (Figure 2B). A further experiment was conducted to determine measurement precision. For the within-run variation, 10 replicates of counting bead were determined for the concentration. The data demonstrated a CV of 8.2%. For the between-run variation, 5 replications of counting bead were determined consecutively for 5 days. The results showed a CV of 12.1%. Collectively, these data suggested the accuracy and precision of flow-rate calibration for determining cell concentration.
Quantification of MPs and their origin in whole blood, PRBCs, and PCs First, we optimized the flow-cytometry analysis of MPs. Platelet-rich plasma samples were prepared by centrifugation and then incubated with calcium-ionophore A23187 at a final concentration of 10 µM at 37°C. After 30 min, the samples were analyzed by a flow
Page 10 of 23
11 cytometer. The results showed a five-fold increase in the PMP level of the A123187-treated PRP compared to the level in the control, suggesting that the flow-cytometry gating strategy was optimized for further MP analysis. The next experiment was conducted to determine the levels of MPs in whole blood and blood
ip t
components. Figure 3 shows the number of total MPs, RMPs, PMPs, and LMPs in whole
cr
blood (n = 100), PRBCs (n = 100), and PCs (n = 92).
us
In the whole blood samples, the concentration of total MPs was 26,647 ± 12,277 particles/µL; 11,643-86,667 particles/µL. The number of RMPs (11,749 ± 3,817 particles/µL; 4,990-
an
24,360 particles/µL) was slightly higher than that of PMPs (10,380 ± 4,239 particles/µL;
particles/µL; 1-1,206 particles/µL).
M
2,842-27,907 particles/µL). The LMPs showed the lowest concentration (304 ± 356
d
In the PRBCs, the total number of MPs was 29,349 ± 11,817 particles/µL; 12,808-107,169
Ac ce pt e
particles/µL. The RMP concentration (18,226 ± 6,172 particles/µL; 7,714-42,004 particles/µL) was significantly higher than the PMP (6,741 ± 3,328 particles/µL; 2,33027,907 particles/µL) and LMP (340 ± 360 particles/µL; 1-2,014 particles/µL) concentrations.
In the PCs, the MP total was 39,692 ± 27,368 particles/µL; 16,304-139,153 particles/µL. Further characterization of the origin revealed that the PMP concentration (15,292 ± 8,124 particles/µL; 2,773-56,324 particles/µL) was higher than the RMP (9,535 ± 2,974 particles/µL; 4,819-22,017 particles/µL) and LMP (326 ± 373 particles/µL; 1-1,943 particles/µL) concentrations. Taken together, these data suggest the differences in MP concentrations and their origins in various blood components. Homogeneity of MP levels in whole blood, PRBCs, and PCs
Page 11 of 23
12 The next experiment was conducted to determine the potential use of flow-rate calibration to assess the homogeneity of blood components. Figure 4 shows the fold-changes of the total levels of MPs, RMPs, and PMPs in whole blood, PRBCs, and PCs. For the whole blood samples, 67 measurements of total MPs showed fold-changes of less
ip t
than 1 (Figure 4A), and 4 measurements showed fold-changes greater than 2. For the RMPs, 57 measurements showed fold-changes of less than 1, and 2 measurements showed fold-
cr
changes greater than 2. For the PMPs, 58 measurements showed fold-changes of less than 1,
us
and 3 measurements showed fold-changes greater than 2.
an
For the PRBCs, the frequency plot showed 61 measurements of the total MPs with foldchanges of less than 1 (Figure 4B) and 2 measurements with fold-changes greater than 2. For
M
the RMPs, 50 measurements showed fold-changes of less than 1, and 2 measurements showed fold-changes greater than 2. The frequency plot of PMPs showed 56 measurements
d
with fold-changes of less than 1 and 2 measurements with fold-changes greater than 2.
Ac ce pt e
For the PCs, further analysis showed 77 measurements of the total MPs with fold-changes of less than 1 (Figure 4C) and 10 measurements with fold-changes greater than 2. Of these 10 measurements, 3 had fold-changes greater than 3. For the RMPs, 22 measurements showed fold-changes of less than 1. In addition, 14 and 5 measurements showed fold-changes greater than 2 and 3, respectively. Further analysis of the PMPs showed 66 measurements with foldchanges of less than 1 and 5 measurements with fold-changes greater than 2. The high number of PC measurements having fold-changes greater than 2 and 3 suggests high heterogeneity of MP levels in the PCs compared to those in the whole blood and PRBCs.
Page 12 of 23
13 Discussion Interest in quantifying the MPs in blood components for use as a potential biomarker is increasing [1-3]. Therefore, it is necessary to develop an alternative methodology that is affordable, accurate, and reliable for use in routine laboratory practice. The present
ip t
investigation validated flow-rate calibration as a method for enumerating MPs when screening blood donors. In addition, it highlighted the effects of this approach on quantifying
cr
MPs in various blood components.
us
The results of the present study suggest that flow-rate calibration is highly accurate and precise when enumerating cells and particles. This suggestion was supported by the dilution
an
experiment, which showed good correlation between the expected platelet count and the platelet count measured using flow-rate calibration. In addition, the CVs of the within-run
M
and between-run variations of the approach were less than 10% and 15%, respectively. These
d
results correlated with those of previous investigations demonstrating the high precision and
Ac ce pt e
accuracy of flow cytometry based on flow rate for enumerating CD4+ T-lymphocytes and MPs [8, 9, 12]. Apart from its accuracy and precision, flow-rate calibration has other advantages that make it suitable for use in routine laboratory practice. One of the most important advantages is its affordability. Flow-rate calibration obviates the need to add counting beads to each sample. Therefore, it can be used to screen a number of samples at lower cost than bead-based flow cytometry. Another advantage is the availability of flow cytometers, which are now commonly used in laboratories in many countries. For example, Thailand has 120 flow cytometers in hospitals and laboratories nationwide [13]. The method of counting MPs based on flow rate can be applied in a general laboratory without additional instruments. Despite the advantages of flow-rate calibration for MP counting, several points must be considered. The principle of flow-rate calibration is based on the assumption that the flow cytometer used in the study shows a constant flow rate. Instability of the flow
Page 13 of 23
14 cytometer’s flow rate results in the inaccuracy of the MP count. To avoid this error, it is necessary to monitor the count rate vs. the time. Recently, the effects of swarm and coincidence detection on MP quantitation have been proposed [14]. The swarm effect may occur if the flow rate is set too high, leading to inaccuracy in MP enumeration. To avoid
ip t
swarm detection, dilution experiments should be performed to determine whether the number of MPs decreases in proportion to the dilution. Another point to be considered is coincidence.
cr
This problem occurs when the concentration is too high, resulting in a low incidence of
us
double-stained particles. Therefore, to identify the coincidence effect, only single-stained beads should be used.
an
Further experiments screening the MPs in whole blood from donors suggested less variability in the MP levels. This suggestion was supported by the finding that only 2% of the
M
measurements showed fold-changes in the levels of total MPs, RMPs, and PMPs that were
d
greater than 2. In addition, the unprocessed whole blood samples showed no differences in
Ac ce pt e
the levels of RMPs and PMPs. Recent studies have suggested that variability in donors is associated with increased MP levels in transfused blood [14, 15]. This variability could be caused by underlying diseases in donors. This hypothesis is supported by previous studies showing a high prevalence of donors with thalassemia and deficiencies in glucose 6 phosphate dehydrogenase [16-18]. These diseases include pathogenicity in red blood cells and oxidative status, resulting in increased MPs in the blood circulation. Increased MPs in blood products derived from these donors might contribute to complications in transfusion recipients. Even with lessened variability, routine screening donors’ MPs might be necessary to reduce transfusion complications in recipients that are associated with increased MP levels. Compared to whole blood and PRBCs, PCs showed a higher frequency of fold-changes greater than 2 in the total MPs, RMPs, and PMPs, suggesting higher heterogeneity of the MPs in PCs. Such heterogeneity in blood components has been attributed to multiple factors,
Page 14 of 23
15 including procedures for preparing blood components and storage lesion [19, 20]. In addition, studies have suggested that this heterogeneity in blood components affects their therapeutic efficiency [2]. Hence, it may be necessary to categorize blood components to isolate those with high MP levels for specific use and management. For example, blood components with
ip t
high MP levels might be selected for patients with bleeding tendencies. Considering the increased ability of MPs to activate coagulation, such a practice might reduce the number of
cr
units needed to correct transfusion recipients’ bleeding problems. This management strategy
complications associated with multiple-unit transfusions.
us
might help increase the therapeutic efficiency of transfusion blood products and reduce the
an
In summary, the results of the present study demonstrated the potential uses of flow cytometry based on flow rate to enumerate MP concentrations in various blood products. In
M
addition, the results demonstrated the potential for using this approach in routine laboratory
d
practice to screen MP levels in both whole blood samples from transfusion donors and blood
Ac ce pt e
components. Routine screening for MP concentration can be important to increasing therapeutic efficiency and reducing transfusion complications associated with MPs.
Page 15 of 23
16 Figure legends Figure 1. Flow cytometry gating strategy for enumerating platelets and MPs. (A) First, the platelets are identified on the FSC vs. SSC dot-plot. Then, the events of the platelets positive for CD41a from the previous gated population are determined on the CD41a vs. SSC
ip t
dot-plot. (B) The MPs gate is defined on the FSC vs. SSC dot-plot. The events of the annexin V positive MPs or total MPs are determined on the annexin V vs. SSC dot-plot. The events of
cr
the RMPs, PMPs, and LMPs of the annexin V positive MPs are determined on the histogram
us
plot of CD235a, CD41a, and CD45.
Figure 2. Comparison of platelet counts conducted by automated counter and flow-rate
an
calibration. (A) Linear regression analysis of the platelet counts obtained from the flow cytometer on the x-axis and automated cell counter on the y-axis. The plot also indicates the
M
r2 and the linear regression equation. (B) The Bland-Altman plot shows the bias between the
Ac ce pt e
FRC: flow-rate calibration.
d
platelet counts conducted using the two methods. The mean bias and the LOA are indicated.
Figure 3. Levels of MPs and their origin in whole blood and blood components. Bar plots represent the number of the total MPs, RMPs, PMPs, and LMPs in (A) whole blood, (B) packed red blood cells, and (C) platelet concentrate. * indicates significant differences between groups at p < 0.0001. Error bars present mean±s.d Figure 4. Homogeneity of the MPs in whole blood and blood components. The frequency plots demonstrate the fold-changes of the total MPs, RMPs, and PMPs in (A) whole blood, (B) packed red blood cells, and (C) platelet concentrate.
Page 16 of 23
17 Acknowledgments This research was supported by the National Research University Project, Office of Higher Education Commission (NRU59-010-HR). Authors thank the Faculty of Medicine, Siriraj
Ac ce pt e
d
M
an
us
cr
ip t
Hospital, Mahidol University for supporting the research project.
Page 17 of 23
18 References
Ac ce pt e
d
M
an
us
cr
ip t
[1] Burnouf T, Chou ML, Goubran H, Cognasse F, Garraud O, Seghatchian J. An overview of the role of microparticles/microvesicles in blood components: Are they clinically beneficial or harmful? Transfusion and apheresis science : official journal of the World Apheresis Association : official journal of the European Society for Haemapheresis. 2015;53:137-45. [2] Kanzler P, Mahoney A, Leitner G, Witt V, Maurer-Spurej E. Microparticle detection to guide platelet management for the reduction of platelet refractoriness in children - A study proposal. Transfusion and apheresis science : official journal of the World Apheresis Association : official journal of the European Society for Haemapheresis. 2016. [3] Noulsri E, Udomwinijsilp P, Lerdwana S, Chongkolwatana V, Permpikul P. Differences in levels of platelet-derived microparticles in platelet components prepared using the platelet rich plasma, buffy coat, and apheresis procedures. Transfusion and apheresis science : official journal of the World Apheresis Association : official journal of the European Society for Haemapheresis. 2017;56:135-40. [4] Jy W, Ricci M, Shariatmadar S, Gomez-Marin O, Horstman LH, Ahn YS. Microparticles in stored red blood cells as potential mediators of transfusion complications. Transfusion. 2011;51:886-93. [5] Kriebardis AG, Antonelou MH, Georgatzakou HT, Tzounakas VL, Stamoulis KE, Papassideri IS. Microparticles variability in fresh frozen plasma: preparation protocol and storage time effects. Blood transfusion = Trasfusione del sangue. 2016;14:228-37. [6] Poncelet P, Robert S, Bailly N, Garnache-Ottou F, Bouriche T, Devalet B, et al. Tips and tricks for flow cytometry-based analysis and counting of microparticles. Transfusion and apheresis science : official journal of the World Apheresis Association : official journal of the European Society for Haemapheresis. 2015;53:110-26. [7] Bergeron M, Lustyik G, Phaneuf S, Ding T, Nicholson JK, Janossy G, et al. Stability of currently used cytometers facilitates the identification of pipetting errors and their volumetric operation: "time" can tell all. Cytometry Part B, Clinical cytometry. 2003;52:37-9. [8] Storie I, Sawle A, Goodfellow K, Whitby L, Granger V, Reilly JT, et al. Flow rate calibration I: a novel approach for performing absolute cell counts. Cytometry Part B, Clinical cytometry. 2003;55:1-7. [9] Pattanapanyasat K, Chimma P, Sratongno P, Lerdwana S. CD4+ T-lymphocyte enumeration with a flow-rate based method in three flow cytometers with different years in service. Cytometry Part B, Clinical cytometry. 2008;74:310-8. [10] Nantakomol D, Chimma P, Day NP, Dondorp AM, Combes V, Krudsood S, et al. Quantitation of cell-derived microparticles in plasma using flow rate based calibration. The Southeast Asian journal of tropical medicine and public health. 2008;39:146-53. [11] Walker CL, Whitby L, Granger V, Storie I, Reilly JT, Barnett D. Flow rate calibration. III. The use of stabilized biostandards to calibrate the flow rate and calculate absolute CD4+ T-cell counts. Cytometry Part B, Clinical cytometry. 2006;70:154-62. [12] Nielsen MH, Beck-Nielsen H, Andersen MN, Handberg A. A flow cytometric method for characterization of circulating cell-derived microparticles in plasma. Journal of extracellular vesicles. 2014;3. [13] Noulsri E, Lerdwana S, Pattanapanyasat K. Long-term external quality assessment program for CD4+ T-lymphocyte enumeration in Thailand. Accreditation and Quality Assurance. 2016;21:367-75.
Page 18 of 23
19
Ac ce pt e
d
M
an
us
cr
ip t
[14] Chandler WL. Measurement of microvesicle levels in human blood using flow cytometry. Cytometry Part B, Clinical cytometry. 2016;90:326-36. [15] Simak J, Gelderman MP. Cell membrane microparticles in blood and blood products: potentially pathogenic agents and diagnostic markers. Transfusion medicine reviews. 2006;20:1-26. [16] Kriebardis A, Antonelou M, Stamoulis K, Papassideri I. Cell-derived microparticles in stored blood products: innocent-bystanders or effective mediators of post-transfusion reactions? Blood transfusion = Trasfusione del sangue. 2012;10 Suppl 2:s25-38. [17] Alabdulaali MK, Alayed KM, Alshaikh AF, Almashhadani SA. Prevalence of glucose-6phosphate dehydrogenase deficiency and sickle cell trait among blood donors in Riyadh. Asian journal of transfusion science. 2010;4:31-3. [18] Francis RO, Jhang JS, Pham HP, Hod EA, Zimring JC, Spitalnik SL. Glucose-6phosphate dehydrogenase deficiency in transfusion medicine: the unknown risks. Vox sanguinis. 2013;105:271-82. [19] Maffi D, Pasquino MT, Mandarino L, Tortora P, Girelli G, Meo D, et al. Glucose-6phosphate dehydrogenase deficiency in Italian blood donors: prevalence and molecular defect characterization. Vox sanguinis. 2014;106:227-33. [20] Ayers L, Kohler M, Harrison P, Sargent I, Dragovic R, Schaap M, et al. Measurement of circulating cell-derived microparticles by flow cytometry: sources of variability within the assay. Thrombosis research. 2011;127:370-7. [21] Yuana Y, Bertina RM, Osanto S. Pre-analytical and analytical issues in the analysis of blood microparticles. Thrombosis and haemostasis. 2011;105:396-408.
Page 19 of 23
Page 20 of 23
ed
ce pt
Ac M an
c
us
ed pt ce Ac
Page 21 of 23
ed pt ce Ac
Page 22 of 23
Page 23 of 23
pt e
ce
Ac d
M
an
cr
us
i