Proteomics applied to the study of platelet-related diseases: Aiding the discovery of novel platelet biomarkers and drug targets

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www.elsevier.com/locate/jprot

Review

Proteomics applied to the study of platelet-related diseases: Aiding the discovery of novel platelet biomarkers and drug targets☆ Andrés F. Parguiña, Isaac Rosa, Ángel García⁎ Department of Pharmacology, and Center for Research in Molecular Medicine and Chronic Diseases (CIMUS), Universidade de Santiago de Compostela, Santiago de Compostela, Spain

AR TIC LE I N FO Available online 8 May 2012

ABS TR ACT Platelets play a fundamental role in hemostasis. Because they do not have a nucleus, proteomics is an ideal way to approach their biochemistry. Platelet proteomics is still a

Keywords:

young field that emerged a decade ago. Initial platelet proteomic research focused on

Platelets

general proteome mapping followed by the exploration of sub-cellular compartments, the

Clinical proteomics

membrane proteome, and signaling pathways. The initial studies were later completed with the analysis of the platelet releasate and microparticle proteome. The success of these studies led to the application of platelet proteomics to the study of several pathologies where platelets play a fundamental role. Those include platelet-related disorders, such as storage pool disease, gray platelet syndrome, and Quebec platelet disorder; diseases where unwanted platelet activation is highly relevant, such as thrombosis and cardiovascular disease; and other diseases, such as cystic fibrosis, uremia, or Alzheimer's disease. In the present review article, we revise the most relevant proteomic studies on platelet-related diseases carried out to date, paying special attention to sample preparation requirements for platelet clinical proteomic studies. This article is part of a Special Issue entitled: Integrated omics. © 2012 Elsevier B.V. All rights reserved.

Contents 1. 2. 3.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sample preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Platelet proteomics in disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

276 276 277

Abbreviations: ACS, Acute Coronary Syndrome; AD, Alzheimer's Disease; ARB, Angiotensin II Receptor Blocker; ASA, Acetyl Salicylic Acid; CAD, Coronary Artery Disease; CF, Cystic Fibrosis; GPS, Gray Platelet Syndrome; MI, Myocardial Infarction; MK, Megakaryocyte; NSTE, Non-ST Segment Elevation; PD, Parkinson's Disease; PRP, Platelet Rich Plasma; QPD, Quebec Platelet Disorder; RBC, Red Blood Cell; SA, Stable Angina; SCAD, Stable Coronary Artery Disease; SPD, Storage Pool Disease; STE, ST Segment Elevation; uPA, Urinary Plasminogen Activator; WBC, White Blood Cell. ☆ This article is part of a Special Issue entitled: Integrated omics. ⁎ Corresponding author at: Centro de Investigación en Medicina Molecular y Enfermedades Crónicas (CIMUS), Universidade de Santiago de Compostela; Avda de Barcelona s/n, 15782 Santiago de Compostela, Spain. Tel.: +34 881 815429; fax: +34 881 815403. E-mail address: [email protected] (Á. García). 1874-3919/$ – see front matter © 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.jprot.2012.04.043

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3.1. 3.2. 3.3.

Arterial thrombosis and cardiovascular diseases Uremia . . . . . . . . . . . . . . . . . . . . . . . Storage pool disease . . . . . . . . . . . . . . . 3.3.1. Gray platelet syndrome . . . . . . . . . . 3.3.2. Quebec platelet disorder . . . . . . . . . 3.3.3. δ-Storage pool disease . . . . . . . . . . 3.4. Cystic fibrosis . . . . . . . . . . . . . . . . . . . 3.5. Neurodegenerative diseases . . . . . . . . . . . 4. Future perspective . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . .

1.

Introduction

Platelets are small anucleate cell fragments that circulate in the blood. They average approximately 2–3 μm in diameter and have a discoid shape while in resting state. Platelets are produced and released into the bloodstream by precursor megakaryocytes (MKs) in the bone marrow [1] and have a life span of 7–10 days [2]. They drift with the circulation reacting to different stimuli and playing a crucial role in maintaining vascular integrity and regulating hemostasis. Their purpose and functions were thought to be well established thirty years ago. However, platelets proved not so simple and they keep showing unsuspected and important functions in other fundamental biological processes like inflammation, immunity and cancer [3]. Under normal conditions, platelets circulate in the blood as quiescent disks. But, when the endothelium of a blood vessel is damaged, platelets adhere to various extracellular matrix components, such as collagen or Von Willebrand Factor, and experience potent activation and shape change. From a pathological point of view, unwanted platelet activation is related to several pathologies, such as thrombosis and cardiovascular disease. Platelet research is thriving and their intricacies are being investigated from different perspectives [4]. One of these approaches is the analysis of the cellular machinery that gives platelets their abilities, i.e. the proteins. Among the numerous tools that are used to analyze the proteome, mass spectrometry (MS) is the most important one [5]. During the last decades, MS advances in protein identification and quantification spurred the growth of proteomics and facilitated its application to many different areas of research, including platelet research [6]. Platelet lack of a nucleus, and therefore of DNA, hampers their study with many traditional molecular biology techniques. Therefore, the analysis of their proteome seems like a perfect way to unravel their molecular complexities. MS is able to identify very low quantities of proteins in complex mixtures, so it qualifies as a perfect approach to study the protein composition of platelets. During the last decade, the study of platelets and their functions using proteomics has been popularized. Most of the work performed has been recently compiled in a review by Zufferey et al. [6]. The first studies aimed to complete the entire mapping of the platelet proteome either in basal state [7–9] or in activated platelets [10,11] and paved the way for the development of the field. Soon, the realization of the complexities of such massive undertaking changed the aim to the

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study of specific platelet compartments or sub-proteomes; the secretome [12] or the platelet membrane proteome [13]. The field has steadily improved and recent studies show that platelet proteomics constitutes an important tool to dissect the role of platelets in different pathologies [14,15]. In this review we aim to compile all the studies performed using platelet proteomic techniques in a clinical environment with a special emphasis in one of the key steps for a successful proteomic study, sample preparation.

2.

Sample preparation

In any proteomic study it is essential to have a robust but simple method to prepare the samples that are going to be analyzed [16]. This becomes of critical importance when dealing with complex samples where the biological variation is unavoidable. Platelets are not an exception and special care must be given to minimize the technical variation among specimens. The main problem with platelets is that, when they are taken away from their physiological environment, they are prone to suffer activation due to different stimuli like shear stress and agonists, produced during blood withdrawal, or centrifugation steps and platelet washing during their laboratory manipulation [17]. Careful thought should be given to the preparation of platelets for proteomic analysis as the conditions employed can have a profound impact in the final results. There are several aspects to be considered when a platelet clinical proteomic study is designed. Firstly, it is the selection of test subjects and how their personal background might affect the platelet proteome. There are many factors that can influence the platelet protein content and that should be taken into consideration when the samples are selected. Firstly, it is highly desirable to attain a tight relationship between the clinicians that obtain the samples and the researchers. Patients need to be defined according to strict clinical and/or laboratory criteria to avoid the arising of mixed populations, which may cause confusing or misinterpreted results. It is also important to control the kind of medications the donors are taking because they may have important effects in platelet function [18]. Special attention must be paid to the use of antiplatelet agents like aspirin, clopidogrel and integrin αIIbβ3 inhibitors, as they influence platelets directly and would alter the results in great measure. Another factor to consider is how the blood is

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withdrawn from patients and controls. The recommended parameters are as follow: use a 21-gauge needle, and a light and controlled tourniquet to extract blood from the median cubital vein; discard the first 2 mL of blood; and collect the subsequent blood in citrate tubes or, as reported recently, in tubes containing a mixture of citrate, theophylline, adenosine, and dipyridamole [17]. Several other parameters need to be supervised to avoid spontaneous platelet activation and aggregation. Working temperature should be always around 20–25 °C as extreme changes can activate platelets. The pH of the buffer employed to isolate platelets should be monitored and it is usually lowered to around 6.6 with acid-citrate-dextrose, under which condition, aggregation does not occur. Moreover, when platelets are concentrated spontaneous activation events might be caused by platelet–platelet interactions; therefore, when isolated, their concentration should not be over 109 platelets/ mL. It is also very important to minimize contamination of the platelet preparation with other blood components like plasma proteins and other blood cells to ensure that a “clean” proteome is analyzed. Contamination can be minimized by taking the upper third of the platelet-rich plasma (PRP) and, when sample availability is not a limitation, using leukocyte removal filters [8]. Only by using strict quality control standards it is possible to achieve this to a reasonable level. In order to separate platelets from plasma, two types of methods can be used, one based on centrifugations and the other on gel-filtration. The first, and harsher, involves the pelleting of platelets and resuspension in appropriate buffers. Several rounds of centrifugation are performed and they might produce artifacts if not controlled. Ideally, one should monitor platelet activation markers in every step of the platelet preparation procedure. This is strongly recommended when the first samples are analyzed in a particular study, and can be performed in several ways like analyzing changes in cell shape or platelet surface receptor expression. The use of inhibitors like prostacyclin (final concentration 1 μM) is recommended to avoid activation during centrifugation. The first centrifugation step of the blood produces a two-phase solution with a red blood cell (RBC) pellet which constitutes 40–80% of the total volume, a layer of white blood cells (WBCs), and a superior phase of PRP. It is worth mentioning that when working with clinical samples there is usually a limitation in sample availability and the use of leukocyte removal filters is discouraged as they can produce losses of up to 25% of the platelets [19]. There is no standardized protocol and different groups use a wide array of methods with different settings to avoid the risk of PRP contamination with WBCs [7,20,21]. In our experience, blood centrifugation at 200 g during 20 min produces a clear layer of WBC that is easily avoided when pipetting the PRP and results in a highly pure platelet population [22]. Nevertheless, it is important not to pipette the fraction of PRP closer to the WBC layer because even if very small relative numbers of RBCs or WBCs were found in the platelet preparation they could have an important impact in the final result. The second method of obtaining platelets is by gel-filtration; this method is far gentler and platelets are generally more responsive to agonists, but it has a major disadvantage as it does not allow concentration of platelets. When platelets are isolated, it is necessary to disrupt them for further proteomic analysis. Several options exist depending

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on the downstream process. Hypotonic buffers such as NP-40, Triton X-100 or SDS are often used; lysis in liquid nitrogen is another option. It is important to use protease and phosphatase inhibitors during this step because the intracellular proteases and phosphatases are still active and might be altering the proteome map. We have obtained good results when using a protease inhibitor cocktail containing the following inhibitors (final concentrations are indicated): aprotinin (10 μg/mL), pepstatin (1 μg/mL), leupeptin (10 μg/mL), and AEBSF (40 μg/mL). A commercial cocktail from Sigma is also a good option [9]. Regarding a phosphatase inhibitor cocktail, we recommend the following one (final concentrations indicated): sodium orthovanadate (1 mM), sodium fluoride (0.1 mM) and benzamidine (1 mM). Another method commonly used to concentrate and purify platelet proteins is by precipitation from a suspension of washed or gel-filtered platelets. Protein precipitation with 20% trichloroacetic acid (TCA) in acetone is a good option [22].

3.

Platelet proteomics in disease

The application of proteomic technologies to the analysis of platelets in a clinical environment is starting to take off (Fig. 1). Proteomics can be a helpful tool in the search for biomarkers, in the diagnosis of rare platelet disorders or in the dissection of molecular mechanisms that underlie a specific condition. One of the studies which initiated the field of platelet proteomics in clinical research was performed in 2008 and focused in the most obvious role of platelets, their involvement in arterial thrombosis [23]. Several other studies have followed the trend with different experimental designs, patient samples and techniques, making thrombotic and cardiovascular problems one of the main focuses of platelet clinical proteomic research. Nevertheless, research has not only been performed in this field but in other platelet-related diseases as well. In this section we will review the different platelet clinical proteomic studies carried out to date according to the pathology they focused on.

3.1.

Arterial thrombosis and cardiovascular diseases

Cardiovascular diseases are the leading cause of death worldwide [24]. They comprise a series of pathologies involving the heart or blood vessels that usually have similar causes, mechanisms, and treatments. Atherosclerosis is one of the main reasons why cardiovascular problems arise and platelets play a fundamental role in the formation, development and rupture of the atherosclerotic plaque and subsequent arterial thrombus formation [25]. As a result, antiplatelet therapies are widely used in primary and secondary prevention of myocardial infarction (MI), stroke and other cardiovascular events [26]. Platelet proteomics has been recently applied to cardiovascular and arterial thrombosis diseases (Table 1). The first study was performed by Arias-Salgado and colleagues in 2008 and focused on patients with arterial thrombosis, primarily with ischemic stroke [23]. They used a traditional proteomic technique, twodimensional gel electrophoresis (2-DE), for protein separation. In the first dimension they used 13 cm immobilized pH gradient (IPG) strips with a non-lineal range of pH 3–10 and for the second dimension they employed 10% SDS polyacrilamide gels (SDSPAGE). As it happens in all platelet proteomic studies, MS was the

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Venipuncture Blood centrifugation

Organelle sucrose gradient fractionation Platelet function analysis

1D-PAGE

2-DE

SDS-PAGE

2D-DIGE

nUPLC

LC

LCQ-IT MALDI-TOF/TOF

LTQ-IT Q-TOF

Blood extraction and platelet isolation

Sample preparation and/or classification

Protein separation

Mass Spectrometry analysis FT-ICR

1D/fluorescent and 2D Western blot Enzyme activity assays

Results Validation

Immunoelectron microscopy

Fig. 1 – Schematic workflow displaying the different proteomic techniques applied to platelet research in a clinical environment.

technique of choice for protein identification. The platelet proteome of arterial thrombosis patients (n=29) and healthy donors (n=24) was compared. Most of the differences detected between groups were related to cytoskeletal changes which supported the idea of preactivated platelets in thrombotic diseases [27,28]. The most interesting result of their study was the stable decrease of three proteins in platelets from patients (ILK, aldolase and GAPDH). These differences were constant regardless of the type of vascular pathology (the patient group included both peripheral thrombosis and ischemic stroke subjects) or treatment, and were only related to the period of time elapsed from the acute thrombotic episode and the time the blood specimens were collected. Besides the above results, the study also detected four proteins increased in the platelets from patients (actin-binding, p57, NMMHC-A, PK and PGK) [23]. Our group in Santiago de Compostela is applying 2-DE-based proteomics to the search of novel platelet biomarkers and drug targets in acute coronary syndromes (ACSs). ACSs encompass unstable angina, non-ST segment elevation (NSTE) MI, and ST segment elevation MI (STEMI). We recently performed two consecutive studies analyzing the platelet proteome of NSTEMI (n=18) and STEMI (n=11) patients compared to a group of sex, age and treatment matched stable coronary artery disease (SCAD) controls (n=10 and n=15, respectively). Blood samples were taken in less than 12 h following the initiation of the acute event and platelets were isolated immediately afterwards. We separated platelet proteins using large 2D gels; 24-cm pH 4–7 IPG strips for the first dimension, and 10% SDS-PAGE gel for the second. After gel staining with Sypro Ruby, and differential image

analysis, the differentially regulated protein features were identified using MS (MALDI-TOF/TOF). In the first study we found 40 differentially regulated proteins, corresponding to 22 open ready frames (ORFs) [29]. Major groups of proteins identified corresponded to cytoskeletal, signaling and proteins either secreted or involved in vesicles or secretory trafficking pathway. The study highlights proteins involved in αIIbβ3 and GPVI signaling as differentially regulated in NSTEMI. Results related to signaling proteins, such as ILK or Src, and secreted proteins, such as SPARC, were validated by 1D and 2D western blotting. In the second study, we compared the platelet proteome of STEMI patients to that of an SCAD group control. In this case, the results followed a similar trend but somewhat acuter [30]. We found 56 differences between groups (Fig. 2A), corresponding to 42 ORFs, and the main functional groups represented were the same as in the NSTEMI study. The higher number of differences in the STEMI study is not surprising bearing in mind that an STEMI event is more severe than a NSTEMI and also that the samples were collected closer to the initiation of the event. The number of unique proteins altered in both studies suggests cases of posttranslational modifications and/or natural proteolysis. As in the NSTEMI study, many proteins were connected in a functional network where the integrin and actin cytoskeleton signaling pathways were highlighted (Fig. 2B). Since there were also several differentially regulated proteins involved in GPVI signaling, we decided to further explore the involvement of this pathway in ACSs by studying platelets from an independent cohort of patients. In this case, platelets were activated with the GPVI specific agonist collagen-related peptide (CRP) in the presence of inhibitors of secondary mediators to ensure that the changes in

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Table 1 – Main findings from studies analyzing platelet proteome changes in arterial thrombosis and cardiovascular diseases. Authors

Clinical samples

Main findings

Arias-Salgado et al. [23]

Platelets from arterial thrombosis patients and healthy controls

Banfi et al. [31]

Platelets from coronary artery disease patients (NSTEMI, stable angina) and healthy controls

López-Farré et al. [32]

Platelets from acute coronary syndrome patients and stable coronary ischemic disease patients

Parguiña et al. [29]

Platelets from NSTEMI patients and stable coronary artery disease patients

Parguiña et al. [30]

Platelets from STEMI patients and stable coronary artery disease and healthy controls

Mateos-Cáceres et al. [35]

Platelets from aspirin-resistant and aspirinsensitive patients

Volpi et al. [38]

Platelets from stable coronary artery disease patients

Sacristán et al. [18]

Platelets from hypertensive patients

Cytoskeletal changes. Validation of differences in ILK, GAPDH and PK. Alterations disappeared in the long term. Cytoskeletal changes. Validation of differences in Coronin-1B, PSB8 and pleckstrin. Upregulation of proteins involved in platelet energy metabolism. Alterations might be produced at MK level. Reduction in cytoskeleton and antioxidant stressrelated proteins. Validation of differences in manganese superoxide dismutase, glutathione-Stransferase, fructose-1,6-bisphosphate aldolase and triosephosphate isomerase activities. Alterations might be produced at MK level. Changes in cytoskeleton, signaling, and secreted or involved in secretory trafficking pathway proteins. Involvement of GPVI and αIIbβ3 signaling pathways. Validation of differences in Src, ILK and SPARC. Platelets are pre-activated in acute patients. Changes in cytoskeleton, signaling, and secreted or involved in secretory trafficking pathway proteins. GPVI is up-regulated in STEMI patients. Validations of differences related to the adapter CrkL and the active form of the tyrosine kinase Src (both upregulated in acute patients). Platelets are preactivated in acute patients. Cytoskeletal and energy metabolism changes. Their results indicate a higher apoptotic state in ASA-resistant platelets. Cytoskeletal and energy metabolism changes. Validations of differences in SNAP, STIP-1 and Profilin-1. Clopidogrel inhibits exocytosis and cytoskeleton-related processes of platelets. Olmesartan medoxomil decreased the levels of gelsolin precursor isotype 4 and increased the levels of several others, including some antioxidant isotypes. Alterations might be produced at MK level.

NSTEMI = non-ST segment elevation myocardial infarction. STEMI = ST segment elevation myocardial infarction. MK= Megakaryocyte. ASA = Acetyl Salicylic Acid.

the proteome were specifically due to GPVI signaling. Platelets from STEMI patients were compared to SCAD and healthy controls. Results showed that GPVI signaling is upregulated in acute patients, both in basal and CRP-activated platelets. This highlights the potential of this pathway as an anti-platelet drug target in ACS. Furthermore, we also demonstrated that the active form of the kinase Src (phosphorylated in Tyr418) was upregulated in platelets from STEMI patients (Fig. 2C). Src family kinases play a major role in these signaling cascades, especially in the case of the collagen receptors GPVI, receptor αIIbβ1 and the fibrinogen receptor αIIbβ3. The upregulation of the active form of Src in STEMI patients suggests a primary role for those pathways in the acute event. In both studies we performed a follow-up analysis and could see that the number of differences decreased with time indicating that they were due to the acute event and reinforcing the idea of platelet activation during the event. In 2010, the same year of publication of our NSTEMI study, Banfi and colleagues compared the platelet proteome profile of a

group of Coronary Artery Disease (CAD) patients (n=26), composed by 14 NSTEMI subjects and 12 stable angina (SA) patients, to the platelet proteome of healthy controls (n=10). The techniques employed were 2-DE (pH 3–10, 17 cm) and MS (LTQ-IT). They detected six altered proteins including proteins related to energy metabolism (LDH, OGDH), cytoskeleton processes (lambda actin, coronin 1B, pleckstrin) and protein degradation (PSB8). Their results are in agreement with ours as they suggest events of cytoskeletal remodeling, platelet activation (pleckstrin phosphorylation) and proteolytic activity (lambdaactin) in platelets of cardiovascular patients. They also propose that platelets from patients suffer from higher energy metabolism and relate the differences between patients and healthy controls to the chronic and evolving atherosclerotic process [31]. In another recent study, López Farré and colleagues compared the platelet proteome of 16 ACS patients and 26 CAD controls using 2-DE (18 cm, pH 3–10) and MS (MALDI-TOF/TOF) [32]. They found that platelets from ACS patients have reduced

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A

200

Mr (kDa)

15 4

B

pI

C

7

Whole Cell Lysates Basal

CRP

IB: pTyr

IB: Src-pY418

IB: GAPDH

Fig. 2 – Representative results from the analysis of platelets from STEMI patients [30]. A) High-resolution 2-DE based proteome profile of platelets from STEMI patients. Differentially regulated features, after comparing the platelet proteome of STEMI patients (n = 11) and matched SCAD controls (n = 15), are highlighted. B) Top canonical pathways identified by Ingenuity Pathways Analysis software (Ingenuity Systems, CA) when working with the full set of differentially regulated proteins between STEMI and SCAD groups. C) GPVI signaling is upregulated in platelets from STEMI patients. Western blot analysis of pTyr (4G10 monoclonal antibody), Src-pTyr418, and GAPDH protein expression levels in basal and collagen-related peptide (CRP)-activated platelets from STEMI patients (n = 6) and SCAD (n = 6) and healthy (n = 6) controls. Equal amounts of proteins corresponding to each of the six patients per group were pooled for each study point and loaded in different lanes in a 4–12% NuPAGE Bis–Tris gel for protein separation before western blotting.

expression of proteins involved in platelet cytoskeleton, glycolysis pathway, and cellular-related antioxidant system, compared to CAD platelets. A diminished antioxidant system

in ACS platelets might predispose them to an easier activation, in fact it has been speculated that the decreased antioxidant system in platelets during an ACS is unable to

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prevent platelet activation by oxygen free radicals [33]. Moreover, the decreased quantities of several proteins in ACS patients could not be attributed to platelets with a higher tendency to secretion because many of these proteins were non-stored platelet proteins. Accordingly, the authors hypothesize that MK might produce “bewildered” platelets, with altered protein content, days before the onset of the ACS [32]. There are several drug treatments for MI, one that is routinely used in clinical practice is the administration of Acetyl Salicylic Acid (ASA) to inhibit platelet activation in patients admitted to hospital with suspected ACS [34]. However, there is a subgroup of patients that do not respond well to the treatment showing inadequate platelet inhibition by ASA. Several mechanisms have been suggested to be involved in this resistance, including genetic reasons, platelet heterogeneity, non compliance, etc.… but the phenomenon is still not well understood. With that in mind, Mateos Cáceres et al. used a platelet functionality test to separate 51 stable coronary ischemic patients in two groups, namely ASA-resistant (n= 25) or ASA-sensitive (n= 26), and then they used 2-DE (18 cm, pH 3–10 or pH 4–7) and MS (MALDI-TOF/TOF) to compare their platelet proteome [35]. They found three proteins downregulated in ASAresistant patients related to cytoskeleton (gelsolin precursor types 2 and 3, F-actin capping). These proteins are involved in the control of assembly and disassembly of actin filaments, essential for platelet shape change from quiescent discoid to active expanded [36]. They could also see alterations in proteins involved in energetic metabolism and more precisely, they demonstrated a reduced expression of glutathione Stransferase and disulfide isomerase isotype 1 in ASAresistant patients, which may indicate that these platelets have a reduced protection against oxygen free radicals and could be more easily activated [35]. Their results, taken as a whole, might indicate a higher apoptotic state in ASAresistant platelets [35]. Clopidogrel is another antiplatelet agent routinely used for the management of ACS. It limits platelet activation by inhibiting the ADP receptor P2Y12 and its use is especially encouraged when performing coronary angioplasty procedures [37]. Recently, Volpi and colleagues decided to study the platelet proteome of patients who underwent clopidogrel treatment and elective percutaneous coronary intervention (PCI) in order to shed light over the molecular mechanisms that regulate platelet reactivity in that context [38]. Their study made use of 2-DE (18 cm, pH 3–10) to compare the platelet proteome of 20 patients with SCAD at three time points; before coronary angiography, 12 h after administration of 600 mg of clopidogrel and 24 h after PCI. Twenty four differences were detected among the three different time points and 18 could be identified using MS (MALDI-TOF/TOF). The proteins identified included several altered energy metabolism enzymes and proteins related to cytoskeleton-based processes, which may indicate platelet activation. The alterations of proteins like SNAP, STIP-1 and Profilin-1 were confirmed using western blotting. Their results suggest the expected effects of clopidogrel over platelets, like controlling their enhanced activation in SCAD or stopping their exocytosis processes [38]. Hypertension, a closely related cardiovascular problem, is a major risk factor for cardiovascular events. Research has been performed in the field to complete a comparative analysis of the

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platelet proteome of moderate hypertensive patients before and after treatment with an angiotensin II receptor blocker (ARB) called Olmesartan medoxomil [18]. ARBs have been recognized in several trials as having beneficial effects in cardiovascular morbidity and mortality but there is also an interest to see if they provide additional benefits over other antihypertensive drugs. Platelets from hypertensive patients have a tendency to aggregate and also present a basal state of pre-activation [39]. In this regard, some ARBs have demonstrated to inhibit human platelet activation in vitro [40]. Sacristán and colleagues used 2-DE (pH 3–10 or pH 4–7) and MALDITOF/TOF to detect the differences between 13 patients with moderate hypertension who were randomized to have a six month drug treatment or not. They observed that the treatment with Olmesartan medoxomil indeed significantly decreased systolic blood pressure, total cholesterol and LDLcholesterol plasma levels and proteinuria in moderate essential hypertensive patients with non-controlled blood pressure [18]. Also, they demonstrated an effect not previously reported in other ARBs, that is, the drug altered the levels of some platelet proteins. Specifically, the drug decreased the levels of gelsolin precursor isotype 4, which could indicate a reduction in platelet activation and increased levels of several other proteins, including some antioxidant isotypes, which suggest a reduced antioxidative requirement of platelets in treated patients [18]. Another recent study in this context, although not in humans, focused on platelets from rats with induced hypertension [41]. Hypertension was induced in cyp1a1ren-2 transgenic rats by feeding indole-3-carbinol (I3C) and in Fischer 344 rats by subcutaneously infusing angiotensin II (ANG II). The effects produced over the rat's platelets were consistent and reversible. After 14 days of the induction the authors compared the platelet proteome of hypertensive rats (I3C, n = 10 and ANG II, n = 7) with that of their corresponding control group composed of normotensive rats after placebo treatment (n = 10 and n = 7). The proteomic technique chosen for the analysis was 2D-DIGE (pH 4–7) and it allowed the detection of 66 altered proteins in feeding I3C rats and 157 in ANG II infused rats. There was a coincidence between both models in 45 spots, which were identified by MS (MALDI-TOF/ TOF and FT-ICR) and contained mostly cytoskeletal protein fragments. This protein degradation might indicate that ANG II-dependent hypertension could produce an accelerated aging of platelets. Interestingly, the authors also found that the same proteome changes, but in the opposite direction, were produced by repeated blood withdrawals, which certainly promote the generation of new platelets. Changes in the proteome were found to be reversible with time so the altered proteins might prove useful in the development of biomarkers to monitor blood pressure therapy [41].

3.2.

Uremia

Uremia is a condition where there is an accumulation of waste products in the blood due to kidney failure. Patients suffering from this disorder develop an acquired platelet dysfunction that results in bleeding complications [42]. Platelets from these patients display biochemical and structural irregularities, suffer from impaired platelet-vessel wall interaction and are also

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affected by the surrounding uremic plasma. Presently, the nature of this platelet dysfunction remains unclear so the analysis of protein changes happening in the diseased platelets could shed some light about its pathogenesis. The first proteomic analysis performed in uremic platelets was carried out by Walkowiak and colleagues in 2007 [20]. In this preliminary study they used 2-DE (IPG strips pH 3–10, 11 cm and ExcelGels 12.5%) to separate the platelet proteins of uremic patients (both dialyzed (n= 9) and nondialyzed (n= 9)) and healthy controls (n= 9). The authors only detected differences in the number of proteins between groups and did not perform quantitative measurements. They found that the proteome of patients is significantly changed, most noticeably in dialyzed samples, when compared to the control group. A massive array of low molecular weight proteins appeared in dialyzed samples and it might be related to the contact suffered by platelets with artificial substances during dialysis [20]. In 2010 another study expanded the analysis of uremic platelets by analyzing nondialyzed samples of uremic patients (n= 15) according to their platelet functional state [43]. After dividing the pool of patients using the platelet function test PFA-100 in normal (n= 7) and dysfunctional (n= 8), they used 2-DE (pH 3–10, 10% SDS) and MALDI-TOF/TOF to detect differences between groups. They found altered proteins related to cytoskeleton, cell interaction, energy metabolism and oxidative stress. Specifically, they detected actin interacting protein-1 isotype 1 as downregulated in dysfunctional uremic platelets, which correlates with the already known abnormal cytoskeletal assembly in uremic platelets [44]. Integrin IIb, part of the receptor αIIbβ3, was also altered, being upregulated in dysfunctional platelets. Several antioxidant-related proteins were found to be upregulated, which correlates with the reported fact that oxidative stress is increased in uremic patients [45].

3.3.

Storage pool disease

Defects on secretion or storage pool disease (SPD, OMIM %185050) is a heterogeneous collection of inherited disorders that include some well-characterized examples of intracellular defects. SPDs can affect α-granules, δ-granules or both [46]. Here we review some examples of how platelet proteomics can be used to compare the platelet proteome of patients suffering SPDs with matched controls, characterize the platelet defects caused by them or even help in the diagnosis of undefined SPDs.

3.3.1.

Gray platelet syndrome

Gray platelet syndrome (GPS) is a rare inherited disorder characterized by mild to moderate thrombocytopenia with bleeding tendency and a marked decrease or absence of platelet αgranules and of the proteins contained in them. These proteins are either synthesized in MKs or endocytosed from plasma. Their functions range from promoting platelet aggregation to regulate cell proliferation and angiogenesis depending on the local environment [47]. The condition is caused by homozygous or compound heterozygous mutation in the NBEAL2 gene and produces enlarged gray platelets that contain the so-called ghost granules, which do not store their corresponding proteins (OMIM #139090). In 2007 Maynard et al. first used a linear sucrose gradient method to isolate α-granules from healthy donors for proteomic

analysis [48]. Proteins were separated by SDS-PAGE (4–12% Novex Tris-glycine gel) and identified by LC–MS/MS (LTQ NSIIon Trap). In this way, 219 proteins were identified, 39 known to be from α-granules, 50 that were part of the releasate, and 44 potential new α-granule proteins. Three years later the same authors applied the same method to analyze the platelet proteome of one GPS patient and compare it to healthy α-granules [49]. The final list of identifications included 586 proteins and some of them were validated using immuno-electron microscopy. They found that soluble, biosynthetic cargo proteins were severely reduced or undetected in GPS platelets, whereas the packaging of soluble, endocytic cargo proteins was only moderately affected [49]. Their results support the idea of ghost granules in GPS, and their MS method – based on normalized peptide hits and controlled false discovery rate – proved useful to study α-granules. Recently, in a multidisciplinary study with a similar approach, i.e. sucrose-gradient subcellular fractionation of platelets and MS, Gunay-Aygun and colleagues localized the protein product of the gene responsible for GPS, NBEAL2, in the dense tubular system (endoplasmatic reticulum) of platelets [50]. This study constitutes a good example of how proteomics can be integrated, as part of a complex technology platform to yield relevant data for platelet biology.

3.3.2.

Quebec platelet disorder

Another disorder that affects α-granules is Quebec Platelet Disorder (QPD). QPD is an autosomal dominant bleeding disorder due to a gain-of-function defect in fibrinolysis. It is caused by heterozygous tandem duplication of the urinary plasminogen activator (uPA) gene on chromosome 10q24. The hallmark of the disorder is markedly increased uPA levels within platelets, which causes intraplatelet plasmin generation and secondary degradation of α-granule proteins although αgranule ultrastructure is preserved (OMIM #601709). In 2008, Maurer-Spurej and colleagues used proteomics to diagnose QPD in a family with a history of bleeding problems [51]. The patients had been previously diagnosed with an undefined SPD. The different symptoms and alterations were not consistent with any particular disorder and several observations were inconsistent with QPD. Consequently, a new tool was required to investigate the platelet defect. Maurer-Spurej et al. compared the platelet proteome of four members of the same family with that of two control healthy donors. Platelet proteins were separated in 20 cm 12% 1D-SDS-PAGE gels and stained with Sypro Ruby. Bands were processed for LC–MS/MS analysis. The analysis could exclude primary platelet defects like Glanzmann's thrombasthenia, Bernard–Soulier syndrome, GPS and δ-storage pool disease. Three α-granule proteins were decreased in platelets from the patients, namely, fibrinogen, multimerin and thrombospondin-1 compared to control platelets. These results, together with the normal levels of plasma fibrinogen and the normal morphology of patient platelets were suggestive of QPD. The authors then decided to use immunoblotting of platelet lysates to confirm it. By measuring the levels of uPA they found that it was consistently increased in all patients' platelets which supported the hypothesis of QPD diagnostic [51]. This report is a great example of an unexploited application of proteomics: the ability to aid in the diagnosis of platelet-related disorders.

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3.3.3.

δ-Storage pool disease

Dense bodies or δ-granules are the repository sites for molecules such as ADP, ATP and serotonin. The disorders affecting these granules produce a deficiency in secretion-dependent aggregation. The molecular basis for the defect is unexplained but may relate to granule formation or the packaging of their contents. In a recent study the platelet proteome and secretome of eight patients with clinical bleeding problems were compared to that of healthy subjects [52]. Patients presented reduced, but not absent, number of platelet δ-granules and impaired secretion upon activation with weak agonists. The researchers aimed to unravel the molecular mechanisms at the basis of the heterogeneous platelet secretion defect [52]. Their experimental design made use of biological and technical replicates, and combined Difference Gel Electrophoresis (DIGE) [53] and MS (MALDI-TOF/TOF) for proteomic analysis. Comparison between patient and control gels revealed that 60 and 14 protein spots varied in the technical and biological studies, respectively, and six unique proteins were found to have an altered expression in both experimental designs, namely, vinculin, talin-1, transgrelin-2, fibrinogen, coronin and neutral AB glucosidase. The final number of uniquely identified proteins modified in platelets was 44, all of which had been previously identified in the platelet releasate. Many of the proteins identified were related to the cytoskeleton. The authors checked, using a real-time PCR cytoskeleton kit, if the differentially expressed proteins were a result of overall cytoskeletal membrane disorganization or an underlying defect in one or more genes that regulate the cytoskeleton [52]. They found two upregulated genes (ARHGDIB and ARPC2) whose corresponding proteins were also altered in the proteomic study. Their results suggest that the cytoskeleton plays an important role in SPDs; however, there is an important factor to consider: the residual presence of secreted microparticles after platelet activation.

3.4.

Cystic fibrosis

Another genetic disease is cystic fibrosis (CF), a multi-organ disorder that affects the intestinal glands, biliary tree, bronchial glands, sweat glands and the male and female reproductive systems. CF is caused by a mutation in the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) gene that encodes for a chloride ion channel required to regulate the components of sweat, digestive juices and mucus. The first study using proteomics of platelets in CF patients has been performed by Pieroni and colleagues last year [15]. This research group had previously published the first proof of CFTR expression in human platelets [54]. Analyzing the platelet proteome in the context of CF is interesting because platelets seem to have an important role in the disease as seen in previous studies that indicated an increase in circulating activated platelets and platelet–leukocyte complexes in CF patients [55,56]. The proteomic analysis encompassed two complementary approaches that compared the platelet proteome of CF patients (n= 6) to the platelet proteome of healthy controls (n= 9). The first approach made use of nano Ultra Performance Liquid Chromatography–MSE (nUPLC–MSE) and yielded 65 differentially expressed proteins between groups. The second approach consisted of 2-DE (pH 3–10) and MALDI-

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TOF/TOF, which identified 58 differences. There was an overlap between approaches of only four proteins (namely vinculin, hemoglobin subunit α, ras suppresor protein 1 and zyxin), which emphasizes the need of combining different proteomic techniques to get the maximum amount of information about the study matter. Taken as a whole, the results of this study strongly suggest that platelets in CF patients express a proinflammatory phenotype [15].

3.5.

Neurodegenerative diseases

Platelet proteomics has been recently applied to the study of neurodegenerative diseases, specifically, Alzheimer's (AD) and Parkinson's disease (PD). These conditions are associated with a decline of cognitive functions. Today, they represent an important health issue in older people due to increased life expectancy. Therefore, there is an important need to identify diagnostic and prognostic biomarkers for the early detection and treatment of these conditions [14]. AD is known to produce platelet alterations at several levels, from increased membrane fluidity and cytoskeletal abnormalities to an increase in oxidative stress and abnormal cytoplasmatic calcium influxes [14]. Zellner and co-workers used 2D-DIGE (pH 6–9, 24 cm) and MS (LC–MS/MS) to compare the platelet proteome of AD (n= 34) and PD (n= 15) patients to their corresponding matched controls. After strict criteria for the detection of differentially regulated proteins, only one spot was found to be significantly upregulated in the AD patient group. The protein contained in the spot was identified as monoamine oxidase-B (Mao-B). MaoB is an enzyme that catalyzes the breakdown of the neurotransmitter dopamine, it is involved in the pathophysiology of AD and PD and its increase in the brain is associated with AD. This protein was not altered in PD patients compared to their control group. The results of Mao-B were confirmed using fluorescence-based 1D (used to verify changes in protein levels) and 2D western blotting (used to confirm the identity of Mao-B). MAO-B mRNA also showed significantly higher expression levels in AD patients whereas no changes were observed in PD patients compared to corresponding controls. Mao-B platelet activity was also assessed in a subgroup of AD patients and controls and was found to be increased in the former. This study, with the aid of platelet proteomics, shows for the first time that in addition to elevated enzyme activity, also the MaoB protein and mRNA expression levels were increased in platelets from AD patients [14].

4.

Future perspective

During the last four years clinical proteomics has been applied to the study of platelet-related diseases in an attempt to identify novel platelet biomarkers and drug targets (Table 2). Although the initial data are promising, platelet clinical proteomics faces various challenges, some of them related to the experimental design: difficulty in obtaining enough platelet protein to run technical replicates, or difficulty in obtaining a sufficient number of biological replicates. Moreover, a careful and well defined experimental design should take into consideration the number of samples per group needed to detect a change with a certain degree of confidence; this issue, together

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Table 2 – List of proteomic studies performed on platelets in a clinical environment. Authors Arias-Salgado et al. [23] Banfi et al. [31]

López-Farré et al. [32]

Parguiña et al. [29]

Parguiña et al. [30]

Mateos-Cáceres et al. [35] Volpi et al. [38] Sacristán et al. [18] Maynard et al. [49]

Gunay-Aygun et al. [50] Maurer-Spurej et al. [51]

Di Michele et al. [52] Marques et al. [43] Walkowiak et al. [20] Pieroni et al. [15] Zellner et al. [14]

Clinical samples Platelets from arterial thrombosis patients and healthy controls Platelets from coronary artery disease patients (NSTEMI, stable angina) and healthy controls Platelets from acute coronary syndrome patients and stable coronary ischemic disease patients Platelets from NSTEMI patients and stable coronary artery disease patients Platelets from STEMI patients and stable coronary artery disease and healthy controls Platelets from aspirin-resistant and aspirin-sensitive patients Platelets from stable coronary artery disease patients Platelets from hypertensive patients Platelet alpha-granules from a Gray Platelet Syndrome patient and a healthy control Platelets from Gray Platelet Syndrome patients Platelets from four members of a family with bleeding disorders and healthy controls Platelet releasate from patients with bleeding problems Platelets from uremic patients with normal and altered functionality Platelets from dialyzed/non-dialyzed uremic patients and healthy controls Platelets from cystic fibrosis patients and healthy controls Platelets from Alzheimer's and Parkinson's patients and healthy controls

Proteomic approach

validation method

2-DE MALDI-TOF/TOF 2-DE LCQ-IT

Western blot Western blot and enzyme activity assays

2-DE MALDI-TOF/TOF

Western blot and enzyme activity assays

2-DE MALDI-TOF/TOF

1D and 2D-based western blot

2-DE MALDI-TOF/TOF

1D and 2D-based western blot

2-DE MALDI-TOF/TOF 2-DE MALDI-TOF/TOF 2-DE MALDI-TOF/TOF 1D-PAGE/LC LTQ-IT

Western blot and enzyme activity assays 1D and 2D-based western blot – Immunoelectron microscopy

Sucrose gradient fractionation/LC LTQ-IT SDS-PAGE/LC Q-TOF

–

2D-DIGE MALDI-TOF/TOF 2-DE MALDI-TOF/TOF 2-DE

Western blot

2-DE/nUPLC MALDI-TOF/TOF and Q/TOF 2D-DIGE/LC LTQ-IT

Western blot

– – – 1D-fluorescent, 2D-based western blot and enzyme activity assays

NSTEMI = Non-ST segment elevation myocardial infarction. STEMI = ST segment elevation myocardial infarction.

with an adequate statistic analysis and validation strategy, is of great importance to avoid reporting of false positives [57]. Technical improvements in proteomics technology are making quantitative analyses more feasible each day, without the need of high amounts of starting biological material, which is of great importance for clinical studies. The challenges are real and should be addressed; nevertheless, platelet proteomics will continue to be applied to the study of platelet-related diseases with the aim of improving their diagnosis and treatment.

Acknowledgments The authors would like to acknowledge the support given by the Spanish Ministry of Economy and Competitiveness (MINECO) [grant No. SAF2010-22151, co-funded by the European Regional Development Fund (ERDF)], the Galician Government

(Consellería de Educación, Xunta de Galicia, Spain) [grant No. INCITE09PXIB203145PR], and the Fundación Mutua Madrileña (Spain). AG is a Ramón y Cajal Research fellow (MINECO), and AFP a FPI pre-doctoral fellow (MINECO).

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