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- MATERIALS AND METHODS
- LITERATURE CITED
It is clear that some finite amount of platelets will be analyzed/sorted along with leukocytes isolated from peripheral blood unless proper precautions are taken to exclude them. This is not a trivial matter because platelets have been shown to be transcriptionally active (1) and may express genes (mRNA) and proteins normally associated with peripheral blood leukocytes. In fact, transcript profiling of platelets by microarray has demonstrated the presence of numerous “leukocyte gene” transcripts (2). Reports also describe platelet expression of leukocytic immunomodulatory proteins such as CD154 (3), chemokine receptors (4), and inflammatory cytokines (5). The first problem this presents is that platelets directly associated with cells of interest can confound immunophenotyping results, as platelets can be directly associated with other blood-derived cells by coincidence, specific- or nonspecific-binding during flow cytometric analysis. This could lead to an instance where a cell population is purported to express a protein that it does not, but that in fact is expressed by associated platelets or platelet fragments (6). In addition, like monocytes and polymorphonuclear leukoctyes, platelets express Fc receptors capable of binding IgG (7) and therefore have potential to be nonspecifically labeled with monoclonal antibodies of this isotype. Therefore, platelet-associated cells need to be resolved and, perhaps, excluded from analysis/sorting in the same manner that other cell aggregates are excluded. The second issue is specific to sorting applications and is more insidious. Free platelets falling below instrument threshold, typically based on a laser scatter parameter, are unaccounted for, will be sorted along with cells of interest, and will go completely undetected. In addition to expressing genes and producing cytokines common to leukocytes, platelets can affect leukocyte functions, such as cytokine secretion and adhesion molecule expression, by direct cell–cell contact (8, 9). Therefore, if platelets are sorted along with cells of interest, this can potentially affect experimental results obtained from sorted cells where leukocyte function or gene expression analyses are performed.
Given that there are several explanations for platelet contamination, all must be addressed to obtain the best results. First, coincidence occurs when two, or more, cells reach the interrogation point (i.e. laser intercept) at nearly the same instant. Coincidence will be most problematic in samples where the ratio of platelets to nonplatelets is high. High cell concentrations (5–10 × 108 cells/mL) often used during high speed sorting can also increase coincidence frequency. Simple depletion of platelets or enrichment of target cells will be helpful to reduce coincidence. As described in Materials and Methods, during wash steps platelets were centrifuged at a gravitational force multiple 10 times (1,200g) that of leukocytes. In fact, platelets do not pellet well at 120g and this alone serves to deplete platelets in lysed whole blood preparations. This phenomenon can also be exploited after differential centrifugation of granulocytes, wherein platelets are retained with granulocytes in the same density gradient band. Multiple wash steps can greatly reduce the number of platelets in a sample. Second, there is always potential for nonspecific adherence of platelets to target cells. The addition of protein, such as bovine serum albumin (BSA), to the wash/stain buffer is commonly used to aid in reduction of nonspecific protein adhesion (e.g. nonspecific antibody binding, cell aggregation) and may therefore aid in reduction of nonspecific binding of platelets to other cells. However, it appears unlikely that this is the major source of platelet contamination and therefore BSA was not used in the current study.
The third cause of platelet contamination defined, and seemingly the most problematic, is specific leukocyte–platelet adhesion wherein the activation or proadhesive status of platelets and leukocytes contribute to the formation of platelet–leukocyte aggregates. These interactions are more difficult to attenuate than nonspecific aggregation and therefore require that great care is taken to minimize activation/priming of platelets and leukocytes. To this end, it is important that proper venipuncture technique is practiced to minimize shear stress and vessel trauma. Shear stress and release of tissue factor from the puncture site can lead to platelet activation and/or initiation of the clotting cascade, as can insufficient anticoagulant in the collection apparatus. The current study employed 10% w/v disodium EDTA as anticoagulant, but many other anticoagulants are available and may be superior depending on experimental design and endpoints measured. The effects of anticoagulants on platelets, leukocytes, and other relevant experimental parameters have been discussed elsewhere (10–14).
Results demonstrated that platelet–leukocyte aggregates were more prevalent in samples prepared by lysis of RBCs versus differential centrifugation (Table 2). This could be partly due to activation of platelets by red cell lysis, a phenomenon that has been reported previously (15). There is also a body of evidence that indicates that temperatures below normal human body temperature, in some reports by even a few degrees Celsius, can lead to platelet priming, activation, degranulation, and/or hypersensitivity to shear stress (16–19). Other factors that can influence platelet activation and may therefore have bearing on platelet contamination of leukocyte preparations include discarding a portion of the blood collected, time elapsed before analysis, centrifugation, fixation (or lack thereof), and storage conditions of blood before sample preparation (15, 20). Nevertheless, leukoctye–platelet interactions do occur in vivo (21, 22) and may persist ex vivo, and therefore, a small number of aggregates may be observed regardless of steps taken to minimize this.
When sorting, the three sources of platelet contamination described earlier must be addressed in addition to a fourth, free platelets. Because of their small size, platelets produce a forward laser scatter signal well below leukocytes, and likely below forward scatter threshold value, when using instrument settings typical of leukocyte analysis. Conventional wisdom dictates that events on a dot plot of forward versus side laser scatter that appear below the lymphocyte cluster are “unlysed red cells, dead cells, or cellular debris.” However, use of anti-CD42d demonstrated that the majority of these low scatter events are in fact platelets (Fig. 1). Consequently, if these events are below threshold, not only will they be sorted along with cells of interest but also the operator will be unaware of their existence. This is true even if a phenotypic marker such as anti-CD42d is used to identify platelets. The practice of raising the (forward laser scatter) threshold value to ignore events below lymphocytes may be acceptable for analysis if these events truly are of no interest. However, this is a misguided approach for dealing with unwanted cellular events in sorting applications; adjusting the instrument to ignore these events does not remove them from the sample. It is at least as important to resolve all contaminating cells as it is to resolve target cells to obtain a high purity postsort sample. If platelet contamination in various forms is not addressed, platelets will undoubtedly be present in sorted fractions, resulting in potentially misleading data. First, free platelets that are below threshold and sorted along with cells of interest may become visible upon reanalysis of the sorted sample due to formation of platelet aggregates or association with other cells upon reanalysis, for instance. This result would likely be misinterpreted as poor sorter performance. Also, as alluded to earlier, platelets present in postsort samples can directly or indirectly impact cell function and gene expression analyses. Even though the RNA content of platelets is small compared to leukocytes, the contribution from platelets can be significant if they are abundant or if using a technique that is sensitive enough to detect low copy number genes (e.g. TaqMan®).
Sorter setup and optimization are critical for resolution of free platelets from noise in both forward and side laser scatter channels. The following discussion is specific to a digitally enhanced FACSVantage (DiVa) sorter, but may also be applicable to other sorters with similar capabilities. The normal approach of using a single threshold parameter (forward laser scatter) and displaying laser scatter (forward and side) on a linear scale does not work well when trying to minimize platelet contamination from sorts. A dual threshold of forward and side laser scatter is recommended. Displaying forward scatter on a logarithmic scale is necessary to truly resolve platelets and leukocytes simultaneously and ensure that platelets are above threshold, but makes it difficult to resolve individual leukocyte subsets. Unfortunately, this is unavoidable with current instrument configuration and display capabilities. Replacing the forward scatter diode with a photomultiplier tube may improve dynamic range and will be investigated. Displaying both scatter parameters on a logarithmic scale is helpful when trying to resolve platelets from RBCs (Fig. 3) and the majority of leukocytes should be off scale at the high end. If threshold values are too low (≤500), electronic noise may overlap the platelet laser scatter signals when sorting logic is engaged as was the case with the instrument used for this study (Figs. 2f–2j). This can be resolved by increasing both the voltage to the scatter detectors and the dual-scatter threshold values.
Numerous examples of how platelets can confound data interpretation from leukocytes have been provided but analysis/sorting experiments involving other blood-derived cells can also be impacted. In fact, platelet contamination can also perturb data collected from hematopoietic stem cells, RBCs, circulating endothelial cells (CECs), and endothelial progenitor cells (EPCs) for similar reasons. For instance, (human) platelets express the hematopoietic stem cell antigen CD34 (23). Platelet-endothelial cell adhesion molecule (PECAM), also known as CD31, is expressed on platelets as well as leukocyte subsets (24), hematopoietic progenitors (25, 26), and stem cells (27). The type B scavenger receptor (CD36) is identical to human platelet GPIV (28) and is also expressed on leukocyte subsets, endothelium, and RBCs (29). Furthermore, as was the case with leukocytes, platelets can specifically adhere to endothelial cells resulting in modulation of function (30, 31) and platelet–CEC aggregates may be encountered during flow cytometric analysis. Therefore, it is deemed especially important to resolve and exclude platelets when sorting rare blood cell populations such as hematopoietic stem cells/progenitors and CECs/EPCs.
Given their small size and potentially large number in leukocyte preparations, it is difficult to completely ablate platelet contamination, but following the suggestions given herein will greatly reduce the extent to which they impact experiments with blood-derived cells. Minimally, platelet activation/aggregation/clotting should be avoided; free platelets should be resolved above threshold, a platelet immunophenotypic maker should be included, and postsort analysis should be performed. There are many antiplatelet antibodies available for humans and rodents. Note that calcium-chelating anticoagulants (e.g. EDTA, sodium citrate, etc.) may impede the binding of certain anti-bodies or dissociate surface glycoproteins, leading to poor immunostaining of platelets. Investigators should confirm that blood processing does not interfere with antibody reporters. Anti-CD42d worked well with rat blood under the conditions described in this article.
In the past, platelets were regarded merely as anucleate particles necessary for hemostasis. In the current context they are described as “contamination” and mostly a nuisance. But platelets are now regarded as complex multifunctional cells with immunomodulatory capabilities (3, 32) and a peer-reviewed scientific journal bears their name. Even though flow cytometric analysis of platelets and leukocytes are commonplace, combination analyses are not. This is true despite the fact that analyses specific for leukocyte–platelet aggregates have been described (21, 22, 33, 34) as informative of platelet activation status and data suggests that platelet-associated leukocytes may represent a functionally distinct subclass (35). Therefore, it seems that platelet–leukocyte interaction should be of interest to platelet researchers and traditional immunologists alike. Perhaps it is time for platelets to be included in routine immunophenotypic/flow cytometric analysis of blood preparations. At the very least, platelets should be resolved to ensure that they are not influencing experimental results from other blood-derived cells of interest.