Lipid Rafts of Platelet Membrane As Therapeutic Target: Role of « Omics »

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UNIVERSITE BOURGOGNE- FRANCHE COMTE

ECOLE DOCTORALE « ENVIRONNEMENTS-SANTE »

Année 2017

THESE

Pour obtenir le grade de

Docteur de l’Université de Franche-Comté

Spécialité : Sciences de la Vie et de la Santé Pharmacologie fondamentale ; Pharmacologie clinique ; Addictologie

Présentée et soutenue publiquement

Le 5 Mai 2017

Par

Vahideh RABANI

Lipid rafts of platelet membrane as therapeutic target: Role of « Omics »

Directeur de thèse : Pr Siamak DAVANI

Mme Ségolène Gambert, Maitre de Conférences, Université de Bourgogne - Franche-Comté Examinateur Mr Jean-Luc Cracowski, Professeur à l’Université de Grenoble-Alpes Rapporteur Mr Nicolas Meneveau, Professeur à l’Université de Bourgogne - Franche-Comté Examinateur Mr Siamak Davani, Professeur à l’Université de Bourgogne - Franche-Comté Directeur de thèse Mr Frédéric Deschaseaux, Chargé de Recherche CNRS, Université Toulouse III Rapporteur Mr Zoubir Djerada, Maitre de Conférences, Université de Reims Champagn-Ardennes Examinateur

Acknowledgment

This thesis was founded by “Conseil régional de Franche-Comté” and “Fédération Française de

Cardiologie”.

This thesis was conducted in EA3920, university of Bourgogne Franche-Comté, Besançon, France.

I would like to thank reporters Dr. Frédéric Deschaseaux and Prof. Jean-Luc Cracowski and jury members who accept kindly to evaluate this thesis Dr. Ségolène Gambert, Prof. Nicolas Meneveau,

Prof. Siamak Davani and Dr. Zoubir Djerada.

In addition, I owe a massive debt of gratitude to Prof. Nicolas Meneveau, for all his helps and supports, for accept me in his clinical research team where I learned so much, for his encouragement and his nice smile when he listened to my projects.

I need to thank Prof. Siamak Davani, however, there is no word in any languages to help me to express my gratitude to him and to his enormous humanity, to his unlimited patience to show the way, unconditional helps and supports, to his thrust on me, to his generosity to give me wings to fly, to his presence in each minute of work, to his precious mentorship in science as well as morality and ethics.

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I am really grateful to have this chance to know you and to work with you Damien Montange. You have remarkably accomplished role of “co-encadrement” in my thesis. Thank you for your sincer kindnesses and your presence in laboratory, in calculation, in finding hard solution and in all other difficult situations. Without you and your help this thesis would not be started. I feel myself lucky to know you and work with you. Thank you for your great heart, your nobility and your solidarity.

I want that you know how much I appreciate your help, how much I am thankful to you Fiona

Ecarnot, for all your supports, helps and all the magic that you do in this 4 years of thesis from editing my English to your hints in preparation for a voyages and articles. Thank you for being my good friend and helping me to overcome the most complicated administrative processes of the world.

I need thank Benoit Vallat, for his help in teaching and troubleshooting in analysis of proteomics.

I want thank, Barbara Dehecq, Celin Viennet, Marion Tissot and EA3181 who have always supported me by providing materials, and Celine Elie-Caille, for her help in AFM microscopy.

I owe an endless appreciation to Prof. Bernard Payrastre and his research team, Jennifer Seris and

Jean Marie Xureb, who accept me in his laboratory and share with me his knowledge as well as his equipments.

I need to thank Prof. Christophe Ramsayer, for share with me his knowledge in lipid rafts.

I want thank my friends for their presence, their warm smile, their support and coulouring my life during this thesis: Armand, Shima, Reza, Gerard, Mari Jo, Jöelle, Marie Petite Jean, Amanda Wang,

Youssef Lboutoun and Hervé Reissy.

I owe my whole life to my parents, who showed me the value of study, who maked me see other things in life and changed my point of view to see new things.

My love AMIR and AFRA: Your exictance is the reason of my each breath, is my strongest motivation to stand up and is my principal goal, the best method, the most valued result and the most precious conclusion for my life. Without your sacrifices nor me neither this thesis could survives.

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Abstract

Platelets are blood cells at the crossroads of both haemostasis and thrombosis. The majority of platelet functions depend on their membrane, which contains numerous, ordered lipid microdomains named lipid rafts. These microdomains play a pivotal role in all phases of platelet-mediated haemostasis. Lipid rafts are a prerequisite for the functioning of receptors in charge of platelet activation and signal transduction. The role of platelets in thrombotic diseases is crucial, and underpins the continue research interest in antiplatelet therapy.

In this context, we aimed to study the lipid rafts of platelet membranes as the principal assembly place of known receptors, and likely also other, unknown elements that participate in the thrombotic function of platelets, with a view to proposing new therapeutic targets.

We used lipidomics and proteomics as well as immunoblot analysis to identify lipid rafts and investigate the organization of lipid rafts in resting, stimulated and antiplatelet-treated platelets. Detergents, ultracentrifugation and sucrose gradients were used mainly for membrane fractionation and isolation of lipid rafts.

The main findings of our work are: 1) Development of a framework or guidelines for platelet lipid raft investigation; 2) Presentation of a global profile of the lipid and protein composition of platelet lipid rafts; 3) Demonstration of the impact of activators and inhibitors on the reorganization of platelet lipid rafts; and 4) Suggestion for potential new therapeutic targets by proteomics analysis through interactive network analyzing of coagulation factor XIII (FXIII) and Vasodilator-Stimulated Phosphoprotein (VASP).

Our results show that lipid rafts have potential as new therapeutic targets in pharmacological research in antiplatelets. “Omics” studies are important to expand our knowledge in this field.

Table of content

Abstract ...... i

List of Figures ...... 6

List of Tables ...... 8

Abbreviations ...... 9

1. General introduction ...... 12

1.1 Platelet function in hemostasis ...... 12

1.1.1 First wave of hemostasis: Platelet activation and secretion ...... 13

1.1.2 Platelet Aggregation ...... 16

1.1.3 Second Wave of hemostasis: Platelet-mediated coagulation ...... 17

1.2 Platelet membrane and its role in hemostasis and thrombosis...... 18

1.3 Platelets in atherothrombotic disease ...... 20

1.4 Current antiplatelet therapies ...... 20

1.5 Future antiplatelet therapies and research of new therapeutic targets ...... 22

1.6 New methods for new therapeutic targets in antiplatelet therapy ...... 23

1.6.1 Proteomics of platelets ...... 24

1.6.2 Lipidomics of platelets ...... 29

1.7 Objectives and outlines ...... 33

Submitted Article: New biomarkers and new therapeutic targets in cardiovascular disease by

Omics” ...... 36

2. Lipid raft in platelet membrane: identification, isolation and their lipid and protein profile .. 58 3

2.1 Platelet membrane ...... 58

2.1.1 Characterization of membrane organization: Lipid raft vs. fluid mosaic model ...... 58

2.1.2 Lipid raft in platelet: Function and their role in signaling transduction ...... 63

Published Article: Comparative Lipidomics and proteomics analysis of platelet lipid rafts using

different detergents ...... 68

2.1.3 Supplementary data ...... 79

3. Antiplatelet drugs and platelet membrane ...... 86

3.1 Antiplatelet drugs and lipid raft ...... 88

Submitted article: Impact of ticagrelor on P2Y1 and P2Y12 localization and on cholesterol

levels in platelet plasma membrane ...... 94

Abstract: impact of antiplatelet drugs on cholesterol level of platelet lipid raft ...... 109

Abstract: PAR-1 localization through re-organization of lipid rafts in thrombin-activated and

Vorapaxar-treated platelets ...... 113

3.1.1 Supplementary Data ...... 116

4. Proteomics analysis of platelet membrane and system biology...... 120

4.1 Network analysis ...... 121

4.1.1 Protein interaction network in platelets ...... 123

4.1.2 Functional protein network analysis to find good hits ...... 124

4.1.3 Functinal protein interactive network in lipid raft of platelet ...... 124

Published Article: Functional network analysis of FXIII in lipid raft of platelet ...... 126

Abstract: Functional protein network of GSK3B in lipid raft of platelet ...... 133

Abstract: Functional protein network analysis of VASP in lipid raft of platelet ...... 137

4.1.4 Suplementary data ...... 140

5. Discussion ...... 146

6. Conclusion ...... 152

7. Perspectives ...... 153

7.1 Investigation on cause of cholesterol loss after manipulation ...... 153

7.2 Impact of vorapaxar and thrombin on PAR-1 localisation on platelet lipid raft ...... 155

7.3 Quantitative proteomics analysis ...... 158

7.4 VASP and lipid raft ...... 158

7.5 Lipidomics and lipid raft modelisation ...... 159

8. References ...... 160

List of Figures

Figure 1: Hemostasis waves. 14

Figure 2: Principal platelet activators and their receptors. 16

Figure 3: Blood coagulation. 17

Figure 4: FXIII needs to be localized on lipid raft to properly do its function in clot retraction. 19

Figure 5 : All current antiplatelet therapies with their corresponding pathways. 22

Figure 6 : Proteins and proteomics in platelet research. 25

Figure 7 : Example of the workflow of a platelet proteomics study. 29

Figure 8 : An illustration of lipidomics analysis by Slatter et al 2016. 32

Figure 9: The Fluid—Mosaic Membrane Model of biological membrane structure, as originally proposed in 1972. 59

Figure 10 : Lipid raft concept: plasma membrane is containing organized microdomain. 60

Figure 11 : Graphical abstract for methodology of investigation on “Comparative lipidomics and proteomics analysis of platelet lipid rafts using different detergents”. 69

Figure 12 : Anticoagulant in the sampling time has no effect on lipid raft extraction 79

Figure 13 : Conventional gradient is more effective for lipid raft extraction of platelets. 80

Figure 14: Lipid and protein contents of platelets membrane extracted by ultrasonication. 81

Figure 15 : Visualization of platelet lipid raft on naked mica. 83

Figure 16 : Visualization of non-raft part of platelets membrane on naked mica. 84

Figure 17 : Intraction of aspirin and lipid rafts. 88

Figure 18 : Impact of anti-platelets drugs on lipid raft of plasma membrane. 111

Figure 19 : Vorapaxar treated and thrombin activated platelets showed different cholesterol and protein profiles. 114

Figure 20: Impact of principal activators on lipid raft of plasma membrane. 116

Figure 21 : Aspirin treated and arachidonic acid activated paletlets showed different lipid raft organisation. 117

Figure 22 : Platelet activation by collagen and treatment with tirofiban change cholesterol distribution on platelet membrane. 118

Figure 23 : Lipid profile change after activation by epinephrine or treatment by dipyridamole. 119

Figure 24 : Different level of network analysis. 123

Figure 25 : Interactive network of proteins around GSK3β on lipid raft of platelets. 134

Figure 26 : Identification of lipid raft of platelet’s membrane by lipidomics and dot blot. 138

Figure 27 : All proteins of lipid raft of platelets with their interactions 140

Figure 28 : Confidence interactive network of VASP 141

Figure 29 : Interactive network of VASP base on molecular actions. 143

Figure 30: Expression of caspase family in platelets activated and treated by drugs. 154

Figure 31 : Localization of PAR-1 on platelet membrane. 156

Figure 32 : PAR-1 in resting platelets treated by different dose of vorapaxar. 157

List of Tables

Table 1: Proteomics studies on platelets in physiological and pathophysiological conditions ...... 26

Table 2 : Mean of cholesterol concentration in cholesterol rich raft and non-raft microdomain of platelet plasma membran after incubation with antiplatelets drugs...... 110

Table 3: Proteins with activation or inhibition type of interaction to GSK3β with theirs probability scores...... 135

Table 4 : Full name of interactive proteins with VASP in plasma membrane of platelet presented in this table...... 144

Abbreviations

AA Arachidonic acid

ACTB Actin B

ACTR3 ARP3 actin-related protein 3 homolog

ADP adenosine diphosphate

AFM Atomic Forced microscopy

ALB Albumin

ANXA5 annexin A5

ApoE Apolipoprotein E

CCR6 C-C Motif Chemokine Receptor 6 CDC42 cell division cycle 42 CFL1 Cofilin 1 cGMP cyclic guanosine monophosphate (cGMP)

COX-1 cyclooxygenase-1 cPLA2α cytosolic phospholipase A2a CTAD sodium citrate, Theophylline, Adenosine, Dipyridamole

CTTN Cortactin

DIAPH1 Diaphanous Related Formin 1

DNM2 Dynamin 2

DPYSL2 dihydropyrimidinase-like 2

DRM Detergent Resistance Membrane

FXIII Facor 13 of coagulation

FYB Fyn-binding protein

FYN protein-tyrosine kinase oncogene family

GP Glycoprotein GSK3β Glycogen synthase kinase 3 beta GSN gelsolin GRB2 growth factor receptor-bound protein 2

HMG-CoA hydroxy-3-methylglutaryl-CoA

HSP90AB1 heat shock protein 90kDa alpha HUPO Human Proteome Organization HUPO ILK integrin-linked kinase

ITGA Integrin A

ITGB Integrin B

LASP1 LIM and SH3 protein 1

LCP2 Lymphocyte Cytosolic Protein 2

LDL low-density lipoprotein

Ld liquid-disordered Lo liquid-ordered LPP1 lipid phosphate phosphatase 1

MAPK mitogen-activated protein kinase 1; Serine/threonine kinase

MBCD methyl-β-cyclodextrin

MSN Moesin

MYLK Myosin Light Chain Kinase

NSAID nonsteroidal anti-inflammatory drug

NAP1L1 nucleosome assembly protein 1-like 1

PAR Protease-activated receptor

PDE5A Phosphodiesterase 5A

PFN1 profilin 1 PC Phosphatidyl-cholin PS phosphatidylserine

PLEK Pleksterin

PPM1A protein phosphatase, Mg2+/Mn2+ dependent, 1A

PPM1F protein phosphatase, Mg2+/Mn2+ dependent, 1F PPIs protein-protein interactions PRP platelet-rich plasma P2Ys/ P2Xs purinergic receptors

RAC1 ras-related C3 botulinum toxin substrate, 10

RDX rodoxin

RRAS related RAS viral (r-ras) oncogene homolog SM sphingomyelin SRC Proto-oncogene tyrosine-protein kinase Src

TLN1 Talin 1 TGFB1I1 transforming growth factor beta 1 induced transcript 1 protein UBC Ubiquitin

1. General introduction

1.1 Platelet function in hemostasis

Platelets are small anucleate blood cells generated from megakaryocytes in the bone marrow and cleared in the reticuloendothelial system. Key role of platelets in human body is hemostasis and thrombosis. Beside these roles there are evidences confirme that platelets are multipurpose cells involved in many other pathophysiological processes such as innate and adaptive immune responses, atherosclerosis, angiogenesis, lymphatic vessel development, liver regeneration and tumor metastasis (1).

Physiological role of hemostasis is to stop bleeding at the site of an injury while in other circulation network blood flows normally. The endothelium of blood vessels has an anticoagulant surface which guaranty blood fluid state. In case of blood vessel damage, some molecules of the sub endothelial matrix of entdothelium are exposed to the blood.

These elements are able to initiate formation of a blood clot. In this case, platelets are rapidly captured by subendothelial matrix proteins, such as collagen and von Willebrand factor (VWF), respectively, via the collagen receptors glycoprotein (GP) VI, α2β1-integrin and the glycoprotein receptor complex GPIb/V/IX. This interaction between platelets and subendothelial ligands induces a multistep process signaling networks of hemostasis.

Although this process take seconds but it is highly regulated and it remains at site of injury.

Hemostasis categorized to two steps; primary hemostasis involves platelet activation and aggregation, secondary hemostasis involves coagulation, deposition of insoluble fibrin and clot retraction (2).

Recent studies indicate that hemostasis occurs in three waves (Fig. 1):

1. Protein wave, that is the deposition of plasma proteins as fibronectin in site of

hemostasis

2. First wave: Platelet adhesion, activation, aggregation and secretion

3. Second Wave: Blood coagulation, which is initiated by the intrinsic or extrinsic

coagulation cascades

Platelets contribute to all three waves of hemostasis and are central players in this critical physiological process to prevent bleeding. These three waves consider also as waves of thrombus formation in pathological conditions such as acute coronary syndromes (Fig. 1) (1).

1.1.1 First wave of hemostasis: Platelet activation and secretion

Encountered to a vessel injury, platelets first change shape, then aggregate, and finally release their secretory granules. During activation some signaling events occur independent of type of agonist stimulation such as an increase in cytosolic calcium and an induction of tyrosine phosphorylation of many cytosolic proteins (3). These events continue to make an integrin-mediated firm adhesion, spreading and exocytosis of platelet granules releasing their elements to amplify platelet activation via autocrine mechanisms and to capture and activate additional platelets from the blood stream.

Figure 1: Hemostasis waves.

Hemostasis occurs in three waves. During the protein wave, plasma proteins are deposited at the site of the injury. Deposition of these proteins results in platelets accumulation. During the first wave platelets become activated and start to secret their granules and other secretory elements. These changes are followed by deposition of fibrinogen and its change to fibrin which is known as the second wave of hemostasis (4).

1.1.1.1 Principal Platelet activators

There are so many literature on signal transduction and pathways intermediating platelet activation and aggregation which could find in these references (5–10). Elaborating these pathways is beyond of objectives of this thesis. Here, we briefly introduce principal activators of platelets and their receptors (Fig. 2).

 Collagen is the first and one of the strongest platelet agonist. Its receptors are GP VI

and integrin α2β1. It makes an adhesive complex by vWF and GP Ib-IX-V (11).

 ADP (adenosine diphosphate) secreted from the dense-bodies (δ-granules) is one of

the major platelet feedback agonist amplifying platelet activation via the G protein-

coupled purine receptors P2Y1 and P2Y12. These receptors activate platelets by using

Gαq and Gαi protein signaling pathways. Gαs pathways also used by epinephrine

known as adrenaline for platelet activation. Epinephrine secret from dense granules

can activate platelets or reinforce their activation (12–14).

 Thromboxane A2 (TXA2) is generated in the cytoplasm of platelet from

cyclooxygenase activity (COX-1) and act in a feedback manner. This molecule

released during platelet activation to signal via G protein coupled TP receptors (TPα

and TPβ) (15–17). Residual thromboxane synthesis could cooperate with

epinephrine to induce platelet aggregation (18). Arachidonic acid (AA), a fatty acid, is

a potent platelet activator which after oxygenation uses also the cyclooxygenase

pathway to induces platelet activation (19).

 Thrombin is a strong platelet agonist and feedback activator via signaling through

GPIb and G protein coupled protease activated receptors (PAR) 1 and 4 downstream

signaling. PAR-1 is activated by subnanomolar concentrations of thrombin, while

PAR-4 requires higher concentration of the same agonist to be fully activated(20).

Figure 2: Principal platelet activators and their receptors.

1.1.2 Platelet Aggregation

Platelet aggregation is platelet_to_platelet adhesion and is the result of receptor αIIbβ3- integrin (GPIIb/ IIIa) activation via receptor-mediated inside-out signaling. Activated αIIbβ3- integrin in its “open” conformation can bind to plasma fibrinogen which cross-links two

αIIbβ3-integrin molecules on different platelets and prepare platelet aggregation accompany by additional enhancement of platelet activation via outside-in signaling. Only strong agonist as collagen or thrombin or high concentrations of weak agonists, such as ADP or TXA2 can maintain the active conformation of the αIIbβ3-integrin and therefore induce the switch from reversible to irreversible platelet aggregation (21). Platelet aggregation forms thrombus (22).

1.1.3 Second Wave of hemostasis: Platelet-mediated coagulation

Stimulated platelets stabilize thrombus through fibrin formation and clot retraction during blood coagulation (11). Only strong platelet agonists such as collagen and thrombin (via thrombin-factor XI feedback loop) induce a procoagulant platelet surface leading to explosive generation of thrombin (the central coagulation protease) which is able to cleave fibrinogen to sticky fibrin (23,24). Platelet-derived cofactor V and factor XIII secreted from the α-granules (25) also play pivotal roles in platelet-based coagulation. Blood coagulation composed of intrinsic and extrinsic pathways are illustrated in figure 3.

Figure 3: Blood coagulation.

In this phase of hemostasis, factors of coagulation and thrombin make an insoluble clot by cleaving fibrinogen to fibrin and make a network of fibrin around the accumulated platelets (26).

1.2 Platelet membrane and its role in hemostasis and thrombosis

All receptors of principal activators of platelet are located on its membrane. As platelets do not have nucleus and rapidly react to stimulus, their membrane and its proteins cunduct the majority of platelet functions.

It is well established that distribution of lipids in membrane is elaborately organized (27).

This organization of platelet membrane discovered and studied through parts of membrane which are known as “detergent resistant membrane (DRM)” (28). These parts contain a fine structure which is known as lipid raft (See chapter 2 for a more detailed description).

Generally, these parts are defined as cholesterol and sphingomyelin riched microdomains of membrane (29). Lipid rafts play a crucial role in signaling by theirs clustering result in increasing the local concentration of signaling molecules and facilitate the generation of signals (30). Lipid rafts play a role in nearly all phases of hemostasis and thrombosis from initial adhesion at site of injury to release of procoagulant microvesicles (30). For exemple, when activated by collagen, GP Ib-IX-V and GP VI/Fcγ complexes need to be localized in lipid rafts to be functional (31).

Thrombin activates PAR-1 by cleaving a peptide bond (Arg41-Ser42) in the receptor’s extracellular domain. This cleavage discloses a new N-terminus of the receptor referred to as a tethered ligand. This “new tail” of the receptor interacts with a distinct domain of the cleaved receptor and, ultimately, causes its activation (20). It has been demonstrated that lipid raft localization of PAR-1 affects presentation of its exodomain for interaction with coagulation proteases in endothelial cells (32). Involvement of lipid rafts in multiple signal transductions mediated by two isoforms of thromboxane A₂ receptor is confirmed (33). An

important proportion of TXA2 receptor (40%) is colocalise at lipid rafts (34). It is also shown that the ability of Gαi to potentiate ADP-mediated platelet aggregation is highly dependent upon its localization to lipid rafts (14).

In coagulation process, lipid rafts are also needed. It is established that intrinsic pathway of coagulation cascade assembles mostly on platelet rafts (30). Recently,Kasahra et al showed how FXIII localization on raft relates to its activation (Fig. 4) (35).

Figure 4: FXIII needs to be colocalized on lipid raft to properly do its function in clot retraction (36).

Following platelet activation, platelet surface phosphatidylserine (PS) should be externalized to harbor the coagulation factors and markedly potentiate thrombin generation (i.e. cell- based thrombin generation) and blood coagulation. This externalization is a raft depended process (4).

1.3 Platelets in atherothrombotic disease

In natural conditions, the two phases of hemostasis occur simultaneously and are mechanistically related to each other. These mechanisms are tightly regulated and even a minor dysregulation can results in pathologic situations such as bleeding (e.g. β3 integrin deficiency in Glanzmann thrombasthenia) or thrombosis (2).

In addition to theses dysregulations, atherosclerotic plaque rupture can cause arterial thrombosis. In this site platelet form pathogenic, occlusive thrombi which may lead to uncontrolled vessel occlusion, resulting in life-threatening consequences (e.g. unstable angina, myocardial infarction and ischemic stroke). As a result, attenuating platelet activation appears to be a valuable strategy in effectively controlling pathological thrombosis and first-line therapeutic strategies in ACSs (37,38).

1.4 Current antiplatelet therapies

Antiplatelet therapy constitutes the cornerstone in the management of patients with acute coronary syndromes and generally high-risk patients with atherothrombosis (39). These therapies based on known activation pathway of platelets as; 1) cyclo-oxygenase (COX)-1 mediated thromboxane A2 (TXA2) synthesis and activation via the TXA2 receptor; 2) adenosine diphosphate (ADP) via P2Y12 receptor; and 3) thrombin via the protease activated receptor (PAR)-1 (20).

Platelet inhibitors have been introduced to clinic by application of basic methods of cellular and molecular biology according to the study of activation pathways and approachs of inhibition/antagonization of platelet receptors (40).

Current antiplatelets mainly aim to 1) inhibit thromboxane A2 synthesis, which inhibits platelet activation (e.g. aspirin) (41) 2) antagonize the function of platelet P2Y12 receptors,

(e.g. clopidogrel, prasugrel, and ticagrelor) (10) 3)inhibit platelet integrin αIIbβ3 activity, which inhibits platelet aggregation, (e.g. abciximab, eptifibatide, and tirofiban) (42) 4) inhibit phosphodiesterase enzymes that normally break down cAMP (increasing cellular cAMP levels and blocking the platelet aggregation response to ADP) (e.g. dipyridamole) and/or cGMP (43) 5) antagonize PAR-1 and PAR -4 receptors (e.g. vorapaxar and atopaxar) (5) (Fig.

5).

Figure 5 : All current antiplatelet therapies with their corresponding pathways.

Name of molecules are showed in black, green, red and purple correspond to FDA-approved, phase III, phase II or preclinical development status, respectively (44).

1.5 Future antiplatelet therapies and research of new therapeutic targets

Although current antiplatelet therapies showed effectiveness in preventing atherothrombotic events, a significant number of patients continue to develop thrombotic events despite receiving suitable treatment. Therefore there is a concern about finding new molecules as platelet activation inhibitors with better preventive properties without increasing the risk of bleeding (45). This necessity arises from : weak/poor inhibition of platelet function, excessive bleeding, thrombocytopenia, unexpected platelet activation (44) or, unresponsiveness of some patient to them. For example, dual antiplatelet therapy with 22

P2Y12 antagonists and aspirin is a key treatment for patients with acute coronary syndrome

(10,46,47). Nonetheless, in spite of receiving this treatment some patients continue to suffer from recurrent thrombotic events (48,49). In this case, either patients are non-responsive to this drug or these thrombotic events are result of platelet activation and aggregation occurring independently of ADP or thromboxane A2 receptor-mediated signaling pathways.

In this context, finding safer and more effective antiplatelets, new methods for new therapeutic targets is suitable.

1.6 New methods for new therapeutic targets in antiplatelet therapy

Given that the platelet is an enucleated cell, the role of nucleus and genome in platelet’s functionality is negligible. Consequently, proteins and lipids of platelets regulate the most part of functional pathways of platelets and participate in its activation and aggregation.

Study of these two categories of biomolecules is absolutely necessary in platelet research.

There are some obstacles in platelet research such as intolerance of platelets to manipulation or their small size which make them incompatible to most of ordinary imaging technics. For example, these obstacles have greatly delayed the identification of major platelet receptor for ADP, the P2Y12 receptor, which was first described in 2001 (50), whereas it is more than a century that platelets are known as key player in hemostasis (51).

Today, despite to the considerable progresses in our understanding of platelet biology using classical methodologies, there is still a growing need for studying and understanding platelet prteins and lipids, more deeply. Today we need studies concerning all proteins and lipids of platelets by the mean of whole proteome and lipidome. These objectives are not inaccessible anymore with new technical approaches as proteomics and lipidomics. Although

even several years after Omics revolution, our knowledge of platelet proteomics and lipidomics is way behind of all other blood cells. Fortunaly recent advances in these techniques can facilitate high throughput investigation of platelets to provide prerequisite knowledge to investigate novel therapeutic targets.

1.6.1 Proteomics of platelets

As reviewed above, membrane proteins of platelet are crucial for platelet functions (Fig. 6).

These proteins include all important receptors on surface of platelet which are responsible of platelet function through precise pathway and all other protein categories as enzymes, transporters, structural and adhesion (52). Platelet proteomics research is a young field but improve rapidly, due to new developments in proteomics instrumentation, notably, in mass spectrometry. Platelets proteomics study can tell us about quantitative changes of platelet proteins (if results come from a quantitative proteomics study), post-translational modifications (in case of using stable isotope labeling strategies (53)), protein-protein interactions and, protein localization (54).

One important question in platelet proteomics research is to decode the complex processes underlying platelet function, mainly by identifying novel proteins in platelet proteome and investigate functional changes of the platelet proteome in normal and pathologic states (55).

So far, several efforts have been made to shed a light on the correlations between platelet proteome and its functioning. Table 1 provides a non exhaustive overview of them.

Figure 6 : Proteins and proteomics in platelet research.

A) An overview of some protein classes of platelet. The rate of abundancy is represented by color. B) Current and potential future applications of proteomics in platelet research (54).

Table 1: Proteomics studies on platelets in physiological and pathophysiological conditions (non exhaustive). Proteomics study Results objective Whole platelet Burkhart et al (56) 4000 proteins were defined proteome Klockenbusch et al Whole platelet 2477 proteins were defined (57) proteome Whole platelet Lee et al (58) 5423 proteins were defined proteome Whole platelet Boyanova et al (59) 5000 proteins were defined proteome 84 protein spots differentially regulated between both conditions platelets play Comparing platelet differential role in various diseases releasate composition in Velez et al (60) through the secretion of different subsets thrombin and collagen of granule proteins and microvesicles stimulated platelets following a predominant activation of certain receptors Compare proteome of intracoronary versus upregulation of platelet activation Velez et al (61) peripheral arterial blood biomarkers at the culprit site platelets in patient proteomic profiles of Significant increase in : PAC-I binding, Cevik et al (62) platelets from acute Gp2b/3a activation and Ca2+ secretion ischemic stroke patients Platelet proteomics in Upregulation of chaperones like HSP70, thalassemia to find why protein disulfide isomerase; oxidative Karmakar et al (63) different degree of stress proteins like peroxiredoxin2, pathophysiological superoxide dismutase1 , translation severity initiation factor 5a

Proteome of young -1036 proteins was defined Thiele et al (64) platelets -54 as biomarker of young platelets Platelets supernatant Dzieciatkowska et al proteome in transfused 503 distinct proteins were detected (65) recipients

Proteomics study Results objective Lewandrewski et al platelet’s membrane 1282 proteins were defined (66) Rabani et al (67) Platelet’s lipid raft 248 proteins were defined Szklanna et al (68) Platelets DRM 141 proteins were defined Adult peripheral /cord Longo et al (69) 751/760 proteins were defined blood Proteome of alpha activation via PAR 1 or PAR 4 don’t effect Van Holten et al (70) granule on alpha granule proteome Proteome of alpha Zufferey et al (71) granule Differences in proteins which participate Compare children in tissue and organ development, cell Cini et al (72) platelet proteomics proliferation regulation and angiogenesis profile with adult processes Platelet proteomics Yip et al (73) analysis in children metallopeptidase inhibitor 1 (TIMP1) is Shah et al (74) Platelet glycoproteome highly modified by aspirin and correlated by hyper reactivity of platelet in vitro Comparative proteomics Identification of 6 biomarker of this Zhang et al (75) analysis in immune pathology thrombocytopenia Compare platelet proteomic changes in S100A8 is present in the platelets of heart Raphael et al (76) platelets from heart failure subjects failure subjects Platelet proteomic 500 proteins was defined where 83 of Cevik et al (62) profile of patient with these proteins were found to be acute ischemic stroke significant -Distinct protein signatures when Quantitative proteomics stimulated by different physiological Milioli et al (77) analysis of platelet- agonists derived microparticles -3383 proteins, of which 428 membrane and 131 soluble proteins

Proteomics study Results objective Platelet derived Capriotti et al (78) 603 proteins were defined microparticle proteome -Different expression of Galectin-3 Microparticle proteome Binding Protein, [Gal3BP], and Alpha-2 Ramacciotti et al (79) after deep venous macroglobulin [A2M] thrombosis -Showed inhibition of fibrinolysis and hemostatic in plug formation Platelet proteome in Providing a list of alternative Baumgartner et al health donner and normalisation candidates for accurate (80) patient with biomarker quantification, the most neurological disorder reliable one : 14-3-3 gamma

On the whole, results of studies recapitulated in table 1, confirmed that proteomics is a promising field of study for both fundamental and clinical platelet research. Despite to its strength in providning a more comprehensive insight into platelet proteins and their role in platelet function, proteomics result must be validated by other technices to be considered as credible therapeutic targets (Fig. 7). However with technological progressions and ameliorations, actually, a new generation of high-resolution high-sensitivity mass spectrometers are able to analyze proteins with levels of specificity and/or sensitivity that otherwise was not possible by classical methods such as immunoassay-based thechnics (81).

Figure 7 : Example of the workflow of a platelet proteomics study (82).

1.6.2 Lipidomics of platelets

In recent years, new generation mass spectrometry analysis of lipids (termed “lipidomics”) has begun to change our understanding of how these molecules participate in key cellular processes (83).

Lipidomics methods usually target known families of lipids using mass spectrometry. There are some attempts to bioinformatics tools to “mine” different mass spectrometry datasets.

Previously it was suggested that mammalian cells contain 100 000–500 000 possible lipids, but experimental attempts to prove this still lacking (84,85).

Lipids are diverse families of biomolecules that perform essential structural, functional and signaling roles in platelets. Enzymes and signal transduction pathways tightly control their formation and metabolism, and their dysregulation leads to significant defects in platelet function. Platelet activation is associated with significant changes to membrane lipids, and formation of diverse bioactive lipids that play essential roles in hemostasis (83).

Responsiveness of platelet to shear stress changed after exogenous lipid moiety exposure to platelet membrane (86).

Considering lipids and their role in platelet and cardiovascular diseases, two aspects could be considered: platelet lipids means the lipids which construct membrane and other lipid residual which play a role in signaling pathway and plasma lipid profile like LDL and HDL.

Plasma lipid profile is a very sensitive marker for risk stratification and dyslipidemia is a key factor in cardiovascular diseases. Here in this thesis, we are only focusing on a subgroup of the first category of platetlet’s lipids, i.e. lipids that are present in platelet cellular membrane. However plasmatic lipids are also known to act on platelet function. For example platelets have receptors for both native (n) and oxidative (ox) LDL. LDL binding to its receptor on platelet surface, ApoE, make platelet more sensitive to its agonist mediated by p38 and MAPK pathway (87). A recent study shows an association between plasmatic lipid profile and platelet indices (88).

A lipidomics study on platelet in patient with ovarian cancer showed that lipid profile of platelets in patient with this pathology change to procoagulant profile (89). The study

suggests that 2 classes of lipids (higher phosphatidylinositol and lower lysophosphatidylcholine) change in platelets and platelet-derived microparticles isolated from ovarian cancer patients. They showed that platelets from patients expressed less lipid phosphate phosphatase 1 (LPP1), a key enzyme in phospholipid biosynthesis pathways, than normal platelets (89). This reduction might correlate with changes in the platelet lipid profile from varian cancer patients. This study is an example how lipidomics study can help us toward prognostic biomarker and may be a potential candidate for new drugs.

Duvernay et al. 2015 studied platelet PAR-1 & PAR-4 signaling pathway by profiling glycerophospholipid (GPL) mass. They confirmed phosphatidylinositol as a major substrate of cPLA2α. They suggested a novel eicosanoid production in response to platelet activation concerning PAR-4 and GPVI mediated (90).

Slatter et al. 2016 performed a comprehensive lipidomic study on resting and activated platelet (84). Moreover, by characterization of about 200 oxidized species they showed that remodeling of the membrane via phospholipase activity provides energy substrates for respiration. These findings suggest a direct link between innate immunity and mitochondrial bioenergetics in human platelets. They also show that low-dose aspirin supplementation profoundly affects the platelet lipidome (84) (Fig. 8).

Figure 8 : An illustration of lipidomics analysis by Slatter et al 2016 (84).

Conducting lipidomics and protemics studies, Peinimaeki-Roemer et al. showed that platelet extracellular vesicle could share the same origin with platelet granules and their function may overlap with these granules (91). Overall, the lipidomics of platelets is poorly investigated and most of studies which use lipidomics of platelets, utilize it as a tool for studying lipid rafts (see chapter 2 for more detailes).

1.7 Objectives and outlines

As it discussed in the former sections, a growing body of evidence suggests that lipid rafts play a very important role in platelet functions. Nonetheless little is known about their characteristics, their lipids and proteins compostion and their implication in antiplatelet efficacy. The main aim of this thesis was to investigate lipid raft microdomain of platelets and their potential to be therapeutic targets. In order to achieve this goal we followed these steps:

1. Identification and characterization of platelet lipid rafts by:

a) The development of a suitable method for isolation and fractionation of

plasma membrane of platelets by comparing different tools to isolate lipid

raft.

b) The study of platelet membrane organization by Omics studies to prepare a

comparable basis for our further investigations.

c) A better definition for platelet’s raft based on lipids and proteins distribution

of plasma membrane.

2. Impact study of platelet activators and theirs antagonists/inhibitors on reorganization

of lipid rafts by the examination of:

a) The organization and reorganization of lipid rafts after activation by its

principal activators

b) The modification of lipid raft in platelet incubated only by anti-platelets

drugs 33

c) The efficiency and impact of antagonists/inhibitors on platelet activated by

corresponding signaling pathway to antagonists/inhibitors

3. Research of new potential therapeutic targets by proteomics analysis by

bioinformatics investigation:

a) Realization of a data base of platelet lipid rafts’ proteins

b) Presentation of some good hits as potential candidates for therapeutic targets

In the second chapter we first reviewed all current debates around lipid rafts and lipid rafts of platelets and then we develop a framework for choosing best compatible method for platelet lipid raft isolation. We also present a global schema of lipid and protein composition of lipid raft by lipidomics and proteomics analysis of non-stimulated platelets.

In the third chapter, we investigate the impact of platelet activation via principal activation pathway on organization of lipid raft. These findings follow by examining the impact of inhibitors of these pathways on lipid raft organization. Finally we do experiment on activated platelets previously treated by inhibitors.

In the fourth chapter, by proteomics analysis of non-stimulated and stimulated platelets we try to find new therapeutic target. We present our results on functional protein interactive network of three proteins: FXIII, GSK3B and VASP.

In final chapters of the thesis, we discuss and synthesize the interconnection between our results, and discuss their implications in current and the future platelet research. At the end,

we provide a short list of questions and future directions which in our point of view may be of crucial importance in the field of platelet research.

Our findings are presented in individual chapters but they are interconnected. Each chapter contains published or submitted articles and some abstracts presented in international or national congresses.

Submitted Article

New biomarkers and new therapeutic targets

in cardiovascular disease by “Omics”

New biomarkers and new therapeutic targets in cardiovascular disease by “Omics”

Vahideh Rabani and Siamak Davani 1EA 3920 – Univ. Bourgogne-Franche Comté, Besançon, France 2Laboratoire de Pharmacologie Clinique et Toxicologie, CHU de Besançon, France

Short title: New biomarker and therapeutic target in cardiovascular diseases

Keywords: Biomarker, therapeutic target, genomics, proteomics, lipidomics

Corresponding author: Siamak Davani, MD, PhD Laboratoire de Pharmacologie Clinique et Toxicologie, CHU Besançon 1, Bld Fleming, 25000 Besançon, France [email protected]

Abstract

Cardiovascular diseases are among the leading causes of morbidity and mortality. Despite scientific and technical progress in risk prediction, diagnostics, prognostication and therapy of cardiovascular pathologies, new biomarkers and therapeutic targets remain the subject of intense research to reduce the burden of these diseases. High throughput analyses, termed “omics”, are a promising avenue of research. These recently developed technical fields have revolutionized biological and medical research in a very short time. By their interdisciplinary nature, these new methods have already provided a wide vision of cell and tissue pathways and functions. Here, we review how these methods can help to discover new biomarkers and therapeutic targets in cardiovascular diseases.

Introduction

Biomarkers are molecules implicated in the mechanisms of a pathology, or that can provide information about the severity of a disease or sensitivity to specific therapy. In cardiovascular diseases, many events remain unpredictable, and to avoid them, we need more accurate, stable, easily detectable, specific and sensitive biomarkers to improve the diagnosis and prognosis of these pathologies (1). Evidently, biological functions must be studied at system levels. The most important tools in system biology studies are collectively termed “Omics”. Combining “Omics” data with other markers, like imaging, statistical analyses, epidemiology, and clinical biochemistry, will help to achieve a better understanding of pathophysiological issues underlying cardiovascular diseases (2). The shift towards the wider use of omics tools in cardiovascular diseases has rapidly gained ground in recent years, due to the application of these techniques to improve our understanding of the molecular mechanisms involved in multifactorial diseases. For example, in 2005, approximately 500 articles were published relating to omics techniques in of cardiovascular-related fields, compared to 6500 published articles in 2015 (Google scholar, search for key words “Omics” and “cardiovascular”) (3). In this review, we focus on these high-throughput analytical techniques termed “Omics”, and provide an overview of their utility in discovering new molecules as targets or markers in cardiovascular disease.

Genomics as a starting point

“Omics” are technologies that make it possible to measure, compare or identify hundreds of molecules within a single sample, in a very short time, with a big field of view. These interdisciplinary fields of study, which call on knowledge in biochemistry, biophysics, mathematics, informatics and biology, have helped to elucidate some pathophysiological issues in diseases over the past decade (Fig. 1 ) (4). Genomics has had a significant impact on current knowledge of diseases and biological mechanisms. Inherited diseases or many childhood disorders and rare diseases have become known thanks to genomics studies. According to a report by O'Donnell et al, the main goals of genomics in cardiovascular diseases are to elucidate biological mechanisms, and using this knowledge, to personalize medicine, and shed light on rare diseases and inherited heart diseases (4). The discovery of mutations affecting the low-density lipoprotein (LDL) receptor, leading to new LDL cholesterol–lowering therapies was one such remarkable application (5). Currently, several loci are known to be associated with myocardial infarction and coronary artery disease (4,6). For example, ABO and ADAMTS7 are reportedly associated with coronary atherosclerosis (7), CNNM2 with high blood pressure and the APOA5 gene cluster with elevated levels of triglycerides and cholesterol (8). Gene discoveries have reinforced existing evidence regarding interactions in a number of commonly used cardiovascular drugs; this field of research is sometimes termed pharmacogenomics. For example, variants 39

in CYP2C9 and VKORC1 are implicated in 40% of response variation to warfarin (9). Variations in the cytochrome P-450 enzyme, CYP2C19 is a major factor responsible for non- responsiveness to clopidogrel (10), while variation in the β1-adrenergic–receptor gene, ADRB1, alters response to beta-blockade in heart failure, and a variant in SLC01B1 is associated with statin-related myopathy (11,12). In 2015, CardioGenBase proposed a database of major cardiovascular disease-associated research articles (13) (http://www.cardiogenbase.com/index.php). They collected all gene/proteins related to Major CardioVascular Diseases (MCVDs) published in the literature (Fig. 2). The number of genes proposed for each pathology confirmed that there are huge amounts of data on genomics of cardiovascular diseases, and today, it is necessary to analyze them systematically. For example, one of the important steps to successful translation of genomics innovation from the laboratory to the clinic relates to the association of a genotype to a phenotype in the population. This can be achieved by a combination of genomics and proteomics, or both, with a clinical phenotype. It is important to consider that a single gene can produce different proteins, which in turn can be subjected to different post-translational modifications. Therefore genes can provide concrete information about organisms (16). Genomics with whole genome sequencing prepares a basis for other omics branches, such as proteomics and lipidomics (14,15,17,18). In this order, “gene ontology” and “gene annotation” are the principal tools for proteomics data analyses. “Gene annotation” can tell us about the localization and activity of any gene and its product; in other words, it can provide a link between a sequenced gene and its biological function (19).

Proteomics: the current center of attention

Proteomics is based on mass spectrometry (MS), which measures the molecular mass of charged molecules such as proteins or peptides. In this method, proteins or protein fragments are separated according to their physico-chemical properties and their charges. The ratio of mass-to-charge ratios (m/z) is compared to current databases to help protein identification and analyses (20). Proteomics is a constantly and rapidly evolving science and utilizes different MS procedures, but reviewing proteomic techniques is beyond the aim of this review and may be found in references (18,21–24). The main goal of proteomics in the search for new biomarkers of cardiovascular disease is to provide a precise and individual risk profile, available in routine practice, and to provide a specific and sensitive proteomic approach to detect early signs of pathology. To achieve these goals, we need to dispose of comprehensive protein datasets in physiological and pathological conditions (1) and to combine proteomics results with clinical phenotypes, metabolite changes, and genetic haplotype information (25). This combination could also cover genotype–phenotype association (26), which is an important aspect in the validation of a new biomarker, and for phenotype prediction in population studies (27). The correlation between genotype and phenotype can prepare a guideline to develop treatment based on genetic testing (28). 40

Most proteomics studies in cardiovascular disease have been performed on plasma from patients. Despite the advantage of the availability of sample resources, plasma proteomics is controversial, because of its complexity and dynamics. On the other hand, it is difficult to detect low-abundance proteins in plasma because of the high concentrations of other proteins (the 20 most abundant proteins represent 99.9% of total plasma protein, like albumin) (29,30). Regardless of these difficulties in plasma proteomics, new candidate biomarkers based on proteomics study on low-abundance plasma proteins have been described. For example, in acute decompensated heart failure (ADHF), bioinformatics analysis of the expression of 103 differential proteins resulted in the identification of quiescin Q6 sulfhydryl oxidase 1 (QSOX-1) as the most promising candidate protein to identify patients with ADHF (31). The main activity of QSOX-1 has previously been described as protein folding, production of extracellular matrix, redox regulation, and protection from apoptosis, angiogenesis, and cell differentiation (32). Mebazaa et al showed in a series of animal model and human studies, that the expression of QSOX1, specifically in the left ventricle and left atrium, corresponds to the degree of pressure overload and hypertrophy and subsequent development of ADHF (31). Upregulation of myocardial QSOX1 expression was seen only in ADHF, and not in patients with acute dyspnea of non-cardiac origin or in patients with stable compensated heart failure. The diagnostic performance of QSOX1 alone was as same as Brain Natriuretic Protein (BNP) and N-terminal proBNP (NT-proBNP) in the entire study population, and showed a significant additional diagnostic value when combined with BNP (31,33). One of the most important adverse cardiovascular events is thrombosis. Research on new biomarkers and potential targets for thrombotic events, to enable risk stratification could focus on plasma, circulating cells or thrombus tissue. Information from these studies has the potential to propose a prothrombic state and represent a link between genotype, environment and disease phenotype (34). Ramaiola et al studied the proteomics profile of thrombus in in-stent thrombosis (IST) and showed a higher content of structure-related proteins such as gelsolin, actin cytoplasmic 1, tropomyosin, and myosin, without changes in fibrin(ogen)-related products. They observed that proteins with enzymatic activity (peroxiredoxin-2, flavin reductase, carbonic anhydrase 1, and alpha enolase) were reduced (35). Alonso-Orgaz and coworkers described 108 proteins in human coronary thrombus in patients with ST-segment elevation acute coronary syndrome (STE- ACS). They showed a positive correlation between 5 proteins (fermitin homolog 3, thrombospondin-1, myosin-9, beta parvin and ras-related protein Rap-1b) and CD41, pointing out the importance of focal adhesion pathway activation in platelets participating in thrombus formation (36). Proteomics analysis has also shown that in patients with ST-elevation myocardial infarction, culprit site-derived plasma but not systemic plasma enhanced proteolytic activity towards pigment epithelium-derived factor (PDEF). This proteomics study of coronary thrombus aspirates indicated that PEDF processing is associated with coronary plaque rupture (37). Other sources of information for proteomics are platelets and monocytes involved in thrombosis and atherosclerosis (16). A study in the proteome of circulating monocytes in patients with non–STE-ACS (38), showed 17 proteins whose expression was altered, as compared with expression in subjects with stable coronary artery disease. Among the proteins showing abnormal expression, levels of antiatherogenic proteins, such as 41

paraoxonase I and HSP70, and anti-inflammatory proteins, such as protein disulfide isomerase were decreased. In contrast, there was overexpression of mature cathepsin D, with pro-atherogenic effects, and enolase I, involved in macrophage transformation into foam cells. Other studies in the same context confirm that, in NSTE-ACS patients, atorvastatin 80 mg/day normalizes expression of HSP70, paraoxonase I, annexin I—which has anti-inflammatory properties—and annexin II—involved in spontaneous fibrinolysis (39). It has previously been shown that cathepsin D and HSP70 are biomarkers of atherosclerotic lesions (40). Other cell sources for thrombosis proteomics studies are platelets. Platelets do not have any nucleus and therefore, they are controlled by their proteins (41). They are upstream of the thrombus formation cascade and can be found in atheromatous plaque (42). There are some proteins like the Dok and RGS families and novel receptors, including CLEC-2 and G6b-B, which were discovered by proteomics analysis in platelets. Analysis of the platelet proteome provides information to identify proteins involved in discrete surface platelet function such as platelet adhesion, activation, aggregation, and secretion. A proteomics study on platelets from patients with ACS, compared with stable patients, showed that levels of proteins involved in cytoskeleton formation (F-actin capping, β- tubulin, α-tubulin isotypes 1 and 2, vinculin, vimentin, and two Ras-related protein Rab-7 isotypes), glycolytic reactions (glyceraldehyde-3-phosphate dehydrogenase, lactate dehydrogenase and two pyruvate kinase isotypes), and redox balance (manganese-SOD) were reduced in ACS patients. Proteins associated with cell survival, such as the β subunit of the proteasome 1 were also decreased in platelets of patients with ACS compared to stable patients (43). Another study with similar objectives, comparing protein patterns of platelets from patients with stable or acute coronary atherosclerosis, identified six differentially expressed proteins; two involved in energy metabolism (2-ketoglutarate dehydrogenase [OGDH], and lactate dehydrogenase [LDH]), three associated with the cytoskeleton-based processes (γ-actin, 1B Coronin and Pleckstrin) and one involved in protein degradation (proteasome subunit type 8) (1,44). Some proteomics studies on platelets in cardiovascular diseases are summarized in Table 1.

Table 1: Proteomics study on platelets in cardiovascular diseases. Proteomics study Results Velez et al(45) Compare proteome of upregulation of platelet activation intracoronary versus biomarkers at the culprit site peripheral arterial blood platelets in patient Van Holten et al(46) Proteome of alpha activation via PAR 1 or PAR 4 does not granule affect alpha granule proteome Cini et al(47) Compare platelet Differences in proteins which participate proteomics profile of in tissue and organ development, cell children with those of proliferation regulation and angiogenesis adults processes Shah et al(48) platelet glycoproteome metallopeptidase inhibitor 1 (TIMP1) is highly modified by aspirin and correlated with hyper reactivity of platelets in vitro Raphael et al (49) compare platelet S100A8 is present in the platelets of heart proteomic changes in failure subjects platelets from heart failure subjects Cevik et al (50) Platelet proteomic 500 proteins defined, 83 of these proteins profile of patients with were found to be significant acute ischemic stroke Milioli et al (51) Quantitative proteomics distinct protein signatures when analysis of platelet- stimulated by different physiological derived microparticles agonists 3383 proteins, of which 428 membrane and 131 soluble proteins

Most pivotal platelet proteins are situated on its membrane, because platelet activation and aggregation usually require surface contact with the surrounding tissue. Therefore, special interest focuses on this contacting region, and hence on the subproteome of the platelet plasma membrane (52–54). In a proteomics study by Lewandrowski and Burkhart, more than 4000 proteins on the plasma membrane of platelets were identified. In the last decade, the introduction of lipid rafts and microdomains as an action platform in membranes has changed our vision of the plasma membrane (55). A cumulating body of evidence suggests that lipid–protein and lipid–lipid interactions in the plasma membrane limit the mobility of membrane proteins and interfere in their localization. Lipid rafts are about 10–200 nm in lipid-ordered microdomains enriched with sphingomyelin, glycosphingolipids, and

cholesterol (56, 57). It is now established that some platelet proteins, such as P2Y12(58) and FXIII (59) need to be on lipid rafts to be functional. Using different bioinformatics analysis tools, such as network analyzing could bring new concepts regarding existing data. In our recent study on coagulation FXIII, we showed that its interactive protein network changes after activation of platelets. We showed that FXIII interacts with cytoskeletal proteins such as actin, only after activation of platelets (60). These kinds of interactions also can be considered as therapeutic targets (61–63). In 2015, the American Heart Association (AHA) released a scientific statement on the transformative impact of proteomics on cardiovascular health and disease, in which they summarized the progress that has been made over the last 20 years in proteomics analysis in cardiovascular diseases (64). This comprehensive review provided a guideline for the use of next-generation proteomics for future scientific discovery in the basic research laboratory and clinical settings. Globally, proteomics is a promising tool to discover earlier and cheaper new biomarkers and therapeutic targets. However, these biomarkers need biological verification and validation to be considered as a true biomarkers or therapeutic targets. With improving proteomics techniques and procedures, and with the completion of the repository map of human proteins (85% complete to date) by the Human Proteome Organization (https://hupo.org/) (65), it is possible that this precious method will rapidly move from bench to bedside.

Lipidomics: beyond plasma lipid profile

Another branch of omics in lipid related diseases (66), which is of potential value in research of biomarker or therapeutic targets is lipidomics. Lipidomics is considered as a sub-branch of metabolomics (67). Metabolites are chemical elements whose alteration during metabolism can serve as signatures of biochemical activity. Since most metabolites are lipids (phospholipids, glycerophospholipids, and sphingolipids) (67) and lipids play a crucial role in most cardiovascular diseases, we focus on lipidomics in this review. Lipidomics is able to quantify hundreds of lipids species in a single sample with various structural and functional roles (68). This information improves our understanding of cardiovascular diseases at a level of detail not manageable with classical analytical methods. These technologies are able to identify different lipid compositions; like sphingomyelin and phosphatidylcholine (56), different concentrations of molecular lipid species like phosphatidylcholine 18:0/18:1. In addition, in a single sample, they can characterize lipid structure by determination for example of the place of a double bond in a lipid molecule like phosphatidylcholine 16:0/18:1 n9 (69). Furthermore, lipidomics can identify lipid cellular distribution and provide information about their biochemical interactions and dynamics (70). This type of lipid data is valuable in cardiovascular research. In this regard, Holčapek et al clustered three groups of people (healthy volunteers, obese people and cardiovascular patients) and performed lipidomics 44

analysis of plasma, erythrocytes and lipoprotein fractions (71). They showed that the two most upregulated lipids in cardiovascular patient groups were 1,3-DG (diacylglycerols) 32:1 and 1,3-DG 34:1, while the most downregulated species were sphingomyelin 34:2 and 1,3- DG 32:0 (71). Other attempts at cardiovascular risk prediction using lipidomics have revealed a different lipid profile in HIV-positive patients in favor of cardiovascular diseases. Total of 74 lipid species were identified, and 8 lipid classes were significantly associated with future cardiovascular events in HIV-positive subjects (72). Bellis et al combined genomics and lipidomics and showed that human plasma lipidome is heritable. They showed a correlation between the lipid component of plasma and polygenes that involve in cardiovascular risk (73). For example, in calcific coronary artery disease (CAD) there is a significant association between single-nucleotide polymorphism and lipid levels, however these relations cannot predict the severity of CAD (74). The lipid profile of patients with calcific coronary artery disease revealed phosphatidylcholine moieties, with 18-carbon decreased and 20:4 increased (75). These two lipids have previously been proposed as indicators of disturbed inflammation homeostasis (76). The levels of these two lipid species and sphingomyelin dysregulation, which is implicated in cell apoptosis, have been proposed as a biomarker of calcific coronary artery disease. However, lipid measurements must be over the long term (57). It is noteworthy that previously, tenascin-X protein was shown to be greatly decreased and alpha-2-HS-glycoprotein increased in calcific aortic valves compared with adjacent normal valve tissues (77). This is an example of how the combination of knowledge from different sources can yield a concrete result for decoding disease. In a comparative study of lipidomics profiles of human atherosclerotic plaques, 150 species of lipids were identified in plaque, and their interactions as well as differences between plaque lipid expression and control arteries were demonstrated (78) (Fig 3). Another important application of lipidomics is in cell membrane research. For example; combining lipidomics and genomics showed that membrane lipids are highly co-regulated. One study revealed a conserved circular lipid network reflecting membrane lipid metabolism, subcellular localization, and adaptation mechanisms (79). Lipidomics provided a good tool for identification of plasma membrane fractions and characterization of these microdomains (Fig.4) by establishing the ratio of cholesterol/sphingomyelin in lipid raft microdomains (56,80,81). These microdomains are the focus of attention in membrane biological research and are implicated in cardiovascular diseases through their participation in platelet activation (58,59), monocyte membrane reorganization (82) and in the mechanisms mediating drug effects (41,63) . Considering all these aspect of functionality of lipidomics in cardiovascular diseases, we can consider this technique as a very good tool in cardiovascular research toward new biomarkers and therapeutic targets.

Conclusion Omics are important tools for the identification of new biomarkers and therapeutic targets in cardiovascular diseases. These methods provide a basis from which to study a biological system. However, this field of research remains young and needs more investigation of the accuracy and applications of the omics techniques. Nonetheless Omics can provide precise idea information about what gene, protein or lipid is valuable for investigation, as well as potentially validating new biomarkers or targets. Omics will help to strengthen evidence, and improve understanding both rapidly and reliably in multifactorial pathologies. Systematic analysis of already exciting Omics data is necessary and helpful to identify populations at risk, provide reliable risk stratification and establish molecular signatures of pathologic conditions.

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Figure 1: Genomics, proteomics and lipidomics are promising methods in system biology in cardiovascular research. As an example, FXIII (factor 13 of coagulation), can be analyzed at gene level with genomics databases, and shows how many genes correspond to a protein network known as cardiovascular related genes. In addition, it can be studied at the level of proteins, by proteomics analyses, showing which proteins FXIII interacts with, when it is on the lipid rafts of platelet. Furthermore, lipidomics analysis can inform about lipid structure and composition (here, only different phosphatidylcholines) of plasma membrane rafts, where FXIII is localized in case of activation, as compared to non-raft parts.

Figure 2: Number of genes proposed to have an association with different MCVDs in literatures based on CardioGeneBase data base.

Figure 3: Some of lipid species identified in Human Atherosclerotic Plaques.

Figure 4: Lipidomics demonstrated variation in lipid species present in raft and non-raft part of platelet membrane.

2. Lipid raft in platelet membrane: identification, isolation and their lipid and

protein profile

2.1 Platelet membrane

Platelets can be activated by chemical or mechanical stimuli (92). Both of them intermediated by plasma membrane of platelets. Therefore, membrane of platelet is the most important part of platelet in pharmacological research focusing on antiplatelet therapy. There are long debates on characterization of plasma membrane organisation.

2.1.1 Characterization of membrane organization: Lipid raft vs. fluid mosaic model

In 1972 the classic Singer–Nicolson fluid mosaic model of the cell membrane was presented to describe the lipid bilayer as a neutral two-dimensional solvent in which proteins diffuse freely and they are dispersed and individually embedded in a more or less randomly organized fluid lipid bilayer (93). This model has strongly influenced our view on structural and dynamical aspects of biological membrane for years. However this concept has changed by researchers who bring new concept of a membrane well organized in different domain around years. Most of membrane researcher shifted to this new aspect of membrane, but

Nicolson claimed recently that “The Fluid—Mosaic Model of Membrane Structure: is still relevant to understanding the structure, function and dynamics of biological membranes after more than 40 years” (94) (Fig. 9).

Figure 9: The Fluid—Mosaic Membrane Model of biological membrane structure, as originally proposed in 1972. They proposed this model of cell membrane focused only on protein and lipid bilayer and no other structure associated with membrane (93,94).

This membrane concept has been modified substantially since Simon Kai introduced for first time the new aspect in cell membrane structure(27).

In 1986, Simons and Van Meer showed that in tight junction of epithelial cells there are difference in lipid composition of exoplasmic leaflet and cytoplasmic leaflet (95). These findings in this thematic proposed a heterogeneity in lipid composition to make different domain in plasma membrane. In 1997, Simons et al proposed the lipid raft theory (27) (Fig.

10), where glycosphingolipids form detergent-resistant membranes (DRMs) enriched in cholesterol and glycosylphosphatidylinositol (GPI)-anchored proteins in cold non-ionic detergents such as Triton. It is proposed that these rafts operate as platforms for the attachment of proteins when membranes are moved around inside the cell and during signal

transduction (27). This theory is based on the dynamic clustering of sphingolipids and cholesterol to form rafts that move with in fluid bilayer.

Figure 10 : Lipid raft concept: plasma membrane is containing organized microdomain.

Definition of lipid raft still is debating. These micro-domains change their properties in different studies. Inconsistencies in lipid raft isolation procedures, type, concentration and duration of incubation, make results difficult to compare, and may contribute to some controversy in the field (67).

Some of inconstancies in raft definition and isolation are related to different points of view of scientists who are working on this concept. Studying membrane raft is on boundary of two disciplines, biophysics and cellular biology. In each discipline scientists have focused on the membrane composition but, evidently, from different points of view. The biologists are more concentrated on the role and its function in biological pathways, whereas biophysicists are more interested in the exact composition and mathematical simulation of the behavior of this composition. Nevertheless the membrane research needs to a closer collaboration of

both disciplines by focusing on both physical and biological aspects to provide us a through understanding of lipid rafts (96).

There are also some degrees of inconsistency in the terminology of plasma membrane studies, for example in description of membrane lateral heterogeneity which have been used to describe lipid asymmetry. This concept has also been considered as a basic requirement for the function of biological membranes. This asymmetry is a fundamental prerequisite of several cellular processes, where maintaining this asymmetry throughout the life-span of the cell is of vital importance for the proper functioning of the cell. This process is energetically demanding and cells invest considerable amounts of energy to generate and maintain asymmetric lipid distribution (97).

In addition to rafts, other domains have also been described at the plasma membrane of eukaryotes: caveolae (98) and tetraspanin-rich domains (99). Caveolae are defined as an invaginations of the plasma membrane and are especially abundant in endothelial cells and adipocytes (100). Tetraspanins are structural proteins bearing four transmembrane domains, which control the formation of membrane tubules. They can oligomerize and recruit various proteins to establish functional domains (101). All these domains share similarities with lipid raft such as small size, instability and governance by the liquid-ordered (Lo)/liquid- disordered (Ld) phase partitioning.

Therefore, despite to intense debates, several lipid domains have been shown in the literature but, their classification is still lacking. It is proposed at 2016 to distinguish two classes of lipid domains based on the following distinct features: (i) size (20–100 nm vs

> 200 nm); (ii) stability (second vs min); and (iii) lipid enrichment (sphingomyelin and

cholesterol vs several compositions, not restricted to sphingomyelin and cholesterol). From the biological point of view, it seems that cholesterol is the most important element of lipid rafts as it is believed to help to stabilize the raft through hydrophobic binding to the other components (102). Whether these two types of domains can coexist within the same plasma membrane or whether some micro-domains result from the clustering of small rafts under appropriate conditions are key open questions that must be addressed regarding biomechanical and biophysical properties of cell plasma membranes. In addition, in order to clarify whether lipid domains can be generalized or not in biological membranes, it is crucial to use appropriate tools in combination with innovative imaging technologies and simple well-characterized cell models (103).

The lipid composition of raft renders them insoluble in non-ionic detergents. This is why they are called Detergent Resistance Membrane (DRM). They are part of these micro-domains

(104) which can be isolated from other soluble parts of membrane by sucrose gradient and based on their buoyant density (isopycnic ultracentrifugation). Despite of all debates, isolation and the study of lipid raft in DRM remains the most useful starting point for defining membrane subdomains, including lipid raft (105). Methodology of DRM isolation is also partially responsible for ongoing debates on identification of DRM or rafts. Historically, lipid rafts have been isolated by their low density and insolubility in cold non-ionic detergents such as Triton X100 (106,107). This separation relies highly on the preparation procedure, in particular the type of detergent, its concentration and the duration of incubation (108). A wide variety of procedures has been used to isolate lipid raft fractions.

These include the use of different detergents such as NP-40, octylglucoside, CHAPS, Lubrol

WX, Brij 35 and Triton X-100 in different concentrations (109). Other reason for contradiction is that lipid domains have often been reported under non-physiological conditions; 4°C or for example after cholesterol extraction by methyl-β-cyclodextrin (MBCD)

(110).

2.1.2 Lipid raft in platelet: Function and their role in signaling transduction

First report on platelet lipid raft was released by Dorahy (111). He showed that in resting platelets, there is caveolin-negative; CD36-rich microdomains could implicate in platelet activation. In human platelet plasma membrane, there is a relatively high amount of sphingomyelin suggesting a lipid composition in favor of lipid raft formation in these cells

(112).

The platelet plasma membrane presents an interesting thermally sensitive system. Human platelets are very susceptible to chilling, activating when the temperature falls below 20 °C

(113,114). During cold-induced platelets activation, a reversible process occurs as lipid rafts cluster into larger aggregates (3). This limitation represents a crucial issue in terms of storage of platelets in blood banks. Recent work attempting to explain cold-induced activation in platelets has shown that DiI-C18:0 becomes in homogeneously distributed in the platelet plasma membrane below 24 °C (3). This uneven distribution of DiI-C18:0 suggests the generation of macroscopic lipid phase separation during cooling. However, above 24 °C, an even distribution of the dye is observed. This reversibility suggests that domain formation is thermotropically driven, since biochemical signaling would be expected to induce non reversible aggregation. Since human platelets membrane contain a low cholesterol content around 15 mol% (only membrane with less than 20 mol% cholesterol

have access to compositional region of macroscopic domains) (115), they can form macroscopic domain (116). For this reason, the platelet presents an interesting opportunity to compare with the model system phase diagrams. In this model system the outer leaflet enters the macroscopic domain region only at the lower temperature (117).

It was shown that platelet lipid rafts play a role in Gp-VI and FcRIIa mediated platelet activation signaling pathways (118). It is proposed that this pathway need lipid raft for clustering all subunits of this pathway may be as same as other immune receptor that they are usually multisubunit receptor pathways (119,120). It is suggested that Gp-IX-V complex are located on lipid rafts of platelets (112). Raft parts would be concentrated in platelet filopodia in correlation with CD63 and c-Src (121). Recent study showed that clot retraction which is mediated by factor XIII-dependent fibrin-αIIbβ3-myosin axis in platelet sphingomyelin-rich membrane rafts (35). Moscardo et al. confirmed that human platelet response to thromboxane A2 receptor agonist depended on the integrity of lipid rafts (34).

Raft domains of platelets contain a variety of proteins, among which CD9, CD36, Flotillin- 1

(reggie 2) and Flotillin-2 (reggie 1) are considered as raft marker proteins (109,122–125).

They act as platforms for the assembly of membrane receptors and are involved in signal transduction cascades, ion channel function, intracellular membrane trafficking and apoptosis (109,122).

Since lipid rafts supposed to be implicated in cell signaling, protein components of this especial part of membrane has a great value to investigate. There are several works on proteomics of lipid raft. For example lipid raft of prostasomes (126), internal organ like mitochondria and endoplasmic reticulume (127), in ovarian cancer cells (128), breast cancer

(129), B cells (130), T cell (131), in Fragile X Mental Retardation Protein (132). In these studies the results of proteomics showed enrichment in proteins corresponding to function of that cells or organelle.

Recently “RaftProt: mammalian lipid raft proteome database” was introduced (133).

RaftProt is a database of mammalian lipid raft-associated proteins as reported in high- throughput mass spectrometry studies. http://lipid-raft-database.di.uq.edu.au/. This work confirms how it is important to have a clear and more detailed vision on lipid raft protein profile.

Study of Larive et al on proteomics of platelet lipid raft proteomics in our knowledge is the only proteomics study on lipid raft of platelet (134). They have showed, by proteomics analysis, for the first time the recruitment and enrichment of proteins in platelet rafts under a mechanical constraint. They also showed that if rafts destruct by MBCD, proteins would not accumulate in lipid rafts (134).

Therefore our study on protein profile of platelet lipid raft isolated by different detergents provided important information about protein profile of platelet lipid rafts.

2.1.2.1 Lipid raft of platelet: Isolation, lipid and protein profiles

As mentioned, for isolation of lipid rafts utilizing detergent is still one of the best methods.

Membrane protein studies also have advanced significantly over the past few years due to application of detergents.

In this work, we first aimed to establish a standard method for isolation of lipid raft of platelet based on their size and density by isopynic ultracentrifugation in sucrose gradient

and secondly by quantifying cholesterol and sphingomyelin amounts (Fig. 11). There is a favorable interaction between SM and Ch and there is strong evidence that they are colocalized in cell membrane (135), therefore from the first step we have investigated pieces of platelet membrane which have isolated in equilibrium density gradient ultracentrifugation with density around 1.08 g/cc which found in interface of sucrose 35% and 5% (106,136) which contain protein marker of lipid raft as flotillin 1and 2 and CD36.

In second step, we confirmed the following definition by lipidomics analysis and immunoblot studies in platelet lipid raft: cholesterol, sphingomyelin enriched microdomain, which are positive for three raft marker: Flotillin 1, Flotillin 2 and CD36. To choose this definition we based on different definitions reported in literature which we have reviewed in previous paragraphs.

In the third step, we have compered lipid and protein profiles of rafts obtained using different detergents and based on these results we choosed the most compatible and the least harsh detergent.

It is well established that the choice of detergent is usually conducted to be suited for the purification of a special membrane protein. Therefore, an experiemental fine tuning of the methodology is necessary mainly for determining the detergent that stabilizes a membrane protein or a memebrane part better than others. Therefore, we selected three non-ionic detergents with different physicochemical characteristics to compare their impact on isolated raft’s lipid and protein profile in platelet membrane (see below). Choosing the most suitable detergent has a great importance for our study as there are not gold rules for

detergent selection. Based on different characters of detergents, they can show different compatibilities to isolate raft and proteins.

Details of methods and results are elaborated in following peer-reviewed article published at

“Platelets” and one abstract presented in “SFPT”, (Société Française de Pharmacologie et de

Thérapeutique) 2015, Caen, France.

Detergents which their impact on raft isolation have been investigated:

Brij™ 35: a nonionic polyoxyethylene surfactant which most frequently used as a component of cell lysis buffers or a surfactant in various HPLC applications.

Triton X-100: a nonionic surfactant that has a hydrophilic polyethylene oxide chain and an aromatic hydrocarbon lipophilic or hydrophobic group. The hydrocarbon group is a 4--phenyl group.

Lubrol WX: a nonionic detergent with ethylene oxide condensate of fatty alcohols; cetyl- stearyl ether.

To obtain these results and made our choice on isolation by detergent we have tested other method as ultra-sonication for membrane fractionation and different kind of sucrose gradients as conventional and modified one also. Furthermore to investigate morphological features of platelet’s raft, we have tried to visualized membrane fraction by Atomic forced microscopy (AFM). The results of these pre-hypothesis are presented in supplementary data at the end of chapter.

Published Article

Comparative Lipidomics and proteomics analysis of platelet lipid rafts using

different detergents

Figure 11 : Graphical abstract for methodology of investigation on “Comparative lipidomics and proteomics analysis of platelet lipid rafts using different detergents”.

2.1.3 Supplementary data

2.1.3.1 Anticoagulant has no effect on lipid raft extraction

Cholesterol analysis on lipid raft fractions showed no difference between tube containing sodium citrate only and the tube contained sodium citrate, Theophylline, Adenosine,

Dipyridamole (CTAD) (Fig. 12). This result confirmed that the tested anticoagulants have no effect on lipid raft extraction.

Fractions

Figure 12 : Anticoagulant in the sampling time has no effect on lipid raft extraction

Cholesterol distribution in lipid raft fractions after using different anticoagulants in the time of sampling were meseaured, cholesterol distribution showed no difference. Lubrol WX 1% lysed platelets. Fractions 1-2-3 = 5%, fractions 4-5-6-7-8=35% and fractions 9-10-11-12= 45% sucrose in MBS.

2.1.3.2 Conventional gradient is more effective for lipid raft extraction of platelets

To choose the most convenient sucrose gradient, we compare conventional (4 ml 45%, 5 ml

35%, 3 ml 5%) and modified gradient (4 ml 45%, 3 ml 35%, 4 ml 20%, and 1 ml 5%). Based on cholesterol analysis, our results showed 4 fractions containing lipid rafts with conventional 79

gradient and only 1 with modified gradient (Fig. 13). Since, we need a high amount of samples; the conventional gradient is more suitable for further proteomics analysis.

Figure 13 : Conventional gradient is more effective for lipid raft extraction of platelets.

Quantifying fraction’s cholesterol level in conventional and modified gradient of Lubrol WX 1% lysed platelets ▪1-2-3 = 5%, 4-5-6-7-8=35% and 9-10-11-12= 45% sucrose in MBS. ∆ 1=5%, 2-3-4-5=20%, 6-7-8=35% and 9-10-11-12= 45% sucrose in MBS

2.1.3.3 Ultrasonication vs. detergent

To compare lipid raft isolated by detergents and ultra-sonication, PRP were sonicated at high rate (5 min 30s in puls 30s, on 10s, off/ amplitude maximal output 70%) and law rate (1min and 30 s/ puls 15s, on and 1s, off/ amplitude maximal output 70%) on ice. Obtained lysate

followed the same procedure of ultracentrifugation as detergent lysed PRP (Fig. 14 A and B).

Proteins of interest were investigated by dot blot on obtained fractions (Fig. 14 C).

Figure 14: Lipid and protein contents of platelets membrane extracted by ultrasonication.

Fractions: 1-2-3 corresponding to 5% sucrose, 4-5-6-7-8 = 35% sucrose and 9-10-11-12 = 45% sucrose. Cholesterol (Ch ▪), Phosphatidyl-cholin (PC ∆) and sphingomyelin (SM ●) concentrations in each fraction are represented as percentage to their total quantity in the 12 fractions (n=2). A) Ultrasonication in high rate B) Ultrasonication in law rate C) Dot blot analysis after fractionation by ultrasonication.

2.1.3.4 Visualization of raft and non-raft micro-domain in sucrose fraction by Atomic

Forced microscopy (AFM)

We have chosen fraction 3 as represent of raft (Fig. 15) and fraction 10 as represent of non- raft fractions (Fig. 16). These two fractions were analyzed by AFM microscopy on liquid to compare raft and non-raft fraction.

On naked mica with a freshly cleaved substrate, pieces of membrane were fused spontaneously and a membrane patch was performed (in contact and tapping phase.)

First of all on naked mica freshly cleaved, laser alignment was done on cantilever in H2O, then surface of naked mica were scanned in H2O. 200µl of fraction 3 were put on mica and microscopy has been done in contact and in tapping. Microscopy on fraction 10 was performed in same manner.

Figure 15 : Visualization of platelet lipid raft on naked mica.

A) Naked mica in H2O. B) Fraction 3 on naked mica. C) On a profile of 2 um of distance we have observed 2 object 300 to 500 nm in diameter. D) These objects of 300_500 nm present height of 10 nm, their surface were not planar. E) In this picture you can see one object with two different height in its body one about 5-7 nm and other more than 7 nm.

Figure 16 : Visualization of non-raft part of platelets membrane on naked mica. Fraction 10 of fractionated platelets visualized on naked mica. There is no any object on naked mica. The height of this thin layer is 1 nm.

Therefore based on this preliminary test on AFM we have observed pieces of membrane presented in raft fractions. This study needs to be repeated to be reliable. We have done the same analysis on same fractions but freeze ones and we did not obtain same results. It

suggested that freeze/ thaw of fractions disrupt the object (eventually rafts) in sucrose fraction.

2.1.3.5 Non-raft protein markers we have found serotransferin (P02787) in non-raft fraction in proteomics data as well as

Integrin b1 as Bodin et al (124) introduce as non-raft marker in platelet.

3. Antiplatelet drugs and platelet membrane

Cell membrane is the first biological barrier encounter by drugs. Drugs must either effect on membrane or must pass across membranes to reach an intracellular target or to be excreted from the cell. The interaction drug-membrane leads to changes in lipid and protein composition of membrane and consequently its fluidity and/or permeability (137). This interaction can impact the bioavailability of a drug, its mechanism of action or explain its toxicity. We know that membrane – drug interactions alter the physicochemical properties of membranes and influence the drug partitition within the membrane (137). Alteration in physicochemical properties can result in toxicity by modifying performance of cell and function of membrane receptors or proteins in charge of signal transduction (138).

Efficiency of drugs to interact with the membranes is one of the most important pharmacological features of drugs biological activity. Membrane contains lipid and proteins, therefore knowing type of interaction on membrane-drug is also important. However it seems that principal target of drugs are proteins and regulation of their activities, but it is necessary to know in what manner drugs interact with membrane’s lipids. Indeed, structural changes in the lipid phase resulting structural defects and consequently disturb membrane function and indirectly modulate membrane proteins and impact efficiacy of drug (139).

Recently, in filed of drug-membrane research, lipid rafts are in the hotline of pharmacological investigations because of their important role in signal transduction.

Allen et al (140) proposed that psychopharmacological drugs could accumulate in these microdomains. Enrichment of these drugs in lipid rafts may have an effect on neurotransmitter receptor signaling like the allosteric modulation of ligand-gated ion

channels involving to the psychopharmacological effects (140). In another example,

Edelfosine, an anti-cancer drug, accumulates in lipid rafts in yeast and mediates its cytotoxic activity by affecting raft protein composition and reorganization of lipid rafts (141).

Furthermore, it is shown that some biological amphiphiles such as many anti-inflammatory agents induce a wide-ranging reorganization of the plasma membrane nanostructure. They stabilizes cholesterol-dependent nanoclusters (142).

Aspirin, with amphiphiles features, is one of the most used and most known antiplatelet agents. Aspirin was reported to partitition into lipid bilayers and position itself in the lipid head group region (143–145). Alsop et al. suggested that aspirin is able to directly interact with model lipid membranes and oppose the molecular level organization induced by cholesterol (Fig. 17)(146). Aspirin was also shown to be able to dissolve cholesterol plaque

(143). Previous study indicated that platelets which showed resistance to aspirin were associated with increased in their membrane cholesterol (147).

Figure 17 : Intraction of aspirin and lipid rafts (146).

3.1 Antiplatelet drugs and lipid raft

Decisive role of platelet membrane composition and fluidity in platelet cell function is evident (83,148). Most of activation pathways of palelet are dependent to lipid rafts

(31,35,149–152). Current antiplatelets drugs aim to inhibit or antagonize these pathways.

Mechanisms of implication of lipid raft in activation of platelets via some of these activation pathways have been studied. There is a gap in manner that lipid raft are implicated in inhibition/antagonization of pathways by drugs. If the antiplatelet drugs in addition of their effect on receptor inhibition/antagonization, have any impact on lipid rafts or not has an influential effect on antiplatelet research. Therefore, understanding how antiplatelet agents interact with lipid bilayer membrane of platelet can open a new horizon in this field.

In this chapter we have focused on effect of antiplatelet drugs and their corresponding activators on lipid raft organization of platelets. We have choosen 5 pairs of these inhibitors/antagonists and their activators:

1) Aspirin which inhibits COX-1 activity (41) and its activator arachidonic acid (AA) (19).

2) Ticagrelor which antagonize the function of platelet P2Y12 receptors (10) and ADP its

direct activator. Epinephrine use the same pathway for activating platelets (12–14).

3) Tirofiban inhibitor of platelet integrin αIIbβ3 activity (42) and its activator collagen

(11).

4) Vorapaxar antagoniste of PAR-1 receptors (5) and its activator thrombin (20).

5) Dipyridamole inhibits phosphodiesterase (43) we did not examine the activator of

this pathway.

To study the impact of platelet activators and theirs antagonists/inhibitors on reorganization of lipid rafts first we have investigate the organization and reorganization of lipid rafts in platelets treated by all these drugs and their activators distinctly. Impact of these elements on level of cholesterol of lipid rafts guided us to choose two pair of them for further investigation; ticagrelor and ADP, vorapaxar and thrombin. In this step we have investigated the impact of activation on platelets treated by corresponding antagonists on lipid raft organization.

By the way preliminary results of other pairs are presented in supplementary data.

Organization and re-organization of lipid raft of platelet were studied by lipidomics and immunoblot was used to study the localization of proteins. Details of methods and results 89

are presented in following article and in two abstracts presented in “ESC”, (European society of cardiology) 2016, Rome, Italy.

We have reviewd breifly, in first chapter, platelets activators used here and in next paragraphs we present concisely studied drugs.

 Aspirin

Aspirin stays as a cornerstone of cardiovascular disease prevention since late 1980s and it is one of the most commonly used drugs in the world (153). Aspirin, acetylsalicylic acid, is a nonsteroidal anti-inflammatory drug (NSAID) that has a wide range of pharmacologic effects.

Aspirin inhibits cyclooxygenase 1 and 2 (COX-1 or 2) non-selectively and leads to anti- inflammatory, antipyretic and platelet inhibitory effects (154) (155). The primary mechanism of action of aspirin is to irreversibly acetylate the serine-529 residue of cyclooxygenase

(COX)-1 in platelets (39,156–158). Low dose of aspirin preferentially inactivates COX-1, which leads to the inhibition of arachidonic acid conversion to prostaglandin G2 and the production of thromboxane A2 (TXA2). Studies have shown that a single dose of 325 mg aspirin inhibits most of COX-1 activity in platelets (159). Aspirin has a very short circulating half–life approximately 20 minutes (160) .

 Ticagrelor

Ticagrelor is the first reversible P2Y12 receptor antagonist and belong to the new cyclopentyl-triazolopyrimidine class. These agents block adenosine diphosphate (ADP)- induced platelet aggregation (150,151). Ticagrelor exhibits potent, rapid, and reversible binding. Its half-life values are 4 min for binding and 14 min for unbinding. The rapid on/off

receptor kinetics of ticagrelor indicate that its inhibitory effect closely reflects levels of drug exposure (163). Ticagrelor binds to the P2Y12 receptor at a site distinct from the ADP- binding site and appears to inhibit ADP-induced receptor signaling in a noncompetitive manner (162). There is no evidence on whether this molecule interacts with lipid raft and if it makes some changes in its compositions.

 Tirofiban

Tirofiban- a synthetic nonpeptide tyrosine derivative - is a glycoprotein (GP) IIb/IIIa reversible antagonist. This is a small molecule (0.495 kDa). It has a rapid onset and often used in conjunction with heparin (164,165). In high risk patient with unstable atherosclerosis plaque tirofiban administration decrease cell adhesion molecules level consequently it can avoid thrombosis (166).

Tirofiban has a high specificity for the GPIIb/IIIa receptor. After binding to receptor it make a conformation on receptor differed from the resting conformation. It has been proved that tirofiban had little or no effect on GpIIb/IIIa secondary or tertiary structure but acts on

GpIIb/IIIa quaternary structure (167). This conformational modulation of GPIIb/IIIa may consider as mechanism by which tirofiban inhibit platelet activation in spite of receptor recruitment. This conformational change can result in exposure of a ligand-induced binding site (epitopes) which can bind directly either to the antibody or to the glycoprotein receptor antagonist–antibody complex. Tirofiban reported to cause occasional thrombocytopenia.

This effect can explained by reaction of tirofiban with GpIIb/IIIa antagonist-coated platelets and cause their destruction (168,169). There is no evidence on whether this molecule interacts with lipid raft and if it makes some changes in its compositions.

 Dipyridamole

Dipyridamole is a platelet inhibitor with antithromboctic effects. It is a cyclic guanosine monophosphate (cGMP)-dependent phosphodiesterase and adenosine carrier inhibitor

(170,171). It blocks reabsorption of adenosine by cells and increases interstitial adenosine concentrations(172,173). In this way dipyridamole stimulates adenylyl cyclase in platelets, end in elevation of cAMP and consequently prevention of platelet aggregation (174).

Dipyridamole is a weak inhibitor of three cGMP-hydrolyzing PDEs (PDE5, PDE10, and PDE11)

(175). It has established that PDE2 and PDE10 are localized in lipid raft (176). It was shown that hydrophobic drugs such as dipyridamole can make lipid/drug-enriched raft domains. In this way they may lead to chaining of cholesterols or drugs inside the bilayer. It shows that this drug can increase membrane fluidity(177). In the other hand dipyridamole showed some anti-lipid features. There are some hypothesis for mechanism of action of dipyridamole on lipids: 1) reduces the uptake of plasma lipid by reducing the number or functional capacity of low-density-lipoprotein (LDL) receptors (178); 2) inhibition of cholesterol synthesis in smooth muscle cells (179); 3) reduce severely liver 3-hydroxy-3-methylglutaryl-CoA (HMG-

CoA) reductase activity (180). It has been shown also that complex of platelet-dipyridamole affect physical properties of interaction surface of platelets (181).

 Vorapaxar

Vorapaxar (SCH530348) is a PAR-1 inhibitor which inhibit the cellular actions of thrombin via a selective antagonism of PAR-1 (20). Vorapaxar is a synthetic tricyclic 3-phenylpyridine

structurally similar to himbacine, a natural antimuscarinic agent isolated from the barks of

Galbulimima baccata (182).

Vorapaxar produce potent, selective, and reversible PAR-1 antagonism. This molecule, a first-in-class PAR-1 inhibitor, is orally active with rapid absorption and high bioavailability

(>90%) after oral administration (20). Vorapaxar is a new molecule and there is no evidence on its effect on lipid rafts.

Submitted article

Impact of ticagrelor on P2Y1 and P2Y12 localization and on cholesterol

levels in platelet plasma membrane

Impact of ticagrelor on P2Y1 and P2Y12 localization and on cholesterol levels in platelet plasma membrane

Vahideh Rabani1, Damien Montange1,2, Nicolas Meneveau1,3, Siamak Davani1,2

1EA 3920 – Univ. Bourgogne-Franche Comté, Besançon, France

2Laboratoire de Pharmacologie Clinique et Toxicologie, CHU de Besançon, France

3Service de Cardiologie, CHU de Besançon, France

Short title: Impact of ticagrelor on platelet membrane Keywords: Ticagrelor; ADP; Cholesterol; Lipid rafts; Platelets

Corresponding author: Siamak Davani, MD, PhD Laboratoire de Pharmacologie Clinique et Toxicologie, CHU Besançon 3, Boulevard Fleming, 25000 Besançon, France [email protected]

Abstract:

Ticagrelor is an antiplatelet agent that inhibits platelet activation via P2Y12 antagonism. There are several studies showing that P2Y12 need lipid rafts to be activated, but there are few data about how ticagrelor impacts lipid raft organization. Therefore, we aimed to investigate how ticagrelor could impact the distribution of cholesterol and consequently alter the organization of lipid rafts on platelet plasma membranes. We identified cholesterol-enriched raft fractions in platelet membranes by quantification of their cholesterol levels. Modifications in cholesterol and protein profiles (Flotillin 1, Flotillin 2, CD36, P2Y1 and P2Y12) were studied in platelets stimulated by ADP, treated by ticagrelor, or both. In ADP-stimulated and ticagrelor-treated groups, we found a decreased level of cholesterol in raft fractions of platelet plasma membrane compared to the control group. In addition, the peak of cholesterol in different experimental groups changed its localization on membrane fractions. In the control group it was situated on fraction 2, while in ADP stimulated platelets it was located in fractions 3 to 5, and in fraction 4 in ticagrelor treated group. The proteins studied also showed changes in their level of expression and localization in fractions of plasma membrane. Cholesterol levels of plasma membranes have a direct role in the organization of platelet membranes and could be modified by stimulation or drug treatment. Since ticagrelor and ADP both changed lipid composition and protein profile, investigating the lipid and protein composition of platelet membranes is of considerable importance as a focus for further research in anti-platelet management.

Introduction Ticagrelor, a cyclopentyl-triazolo-pyrimidine, and a selective and reversible P2Y12 receptor antagonist, is used in the treatment of acute coronary syndromes and after coronary stent implantation (1–4). ADP is one of the most established platelet stimuli, and it induces multiple platelet responses and potentiates platelet aggregation via G protein-coupled P2Y1 and P2Y12 receptors (5). Cholesterol-enriched domains, or lipid rafts, plays a crucial role in the function of platelets, since the lipid rafts have a role in the amplification or attenuation of G-protein signaling (7, 8). Equally, lipid raft integrity is required for the P2Y1 and P2Y12 signaling pathway, and numerous studies have shown that clopidogrel, another P2Y12 receptor antagonist, inhibits this pathway by partitioning out this receptor from the lipid raft (7–11). Although it is clear that P2Y12 needs the lipid raft to be activated, there is a paucity of data on how stimulation by ADP, and inhibition of this pathway by ticagrelor could impact on the distribution of cholesterol and consequently alter the organization of lipid rafts on platelet plasma membranes. In this study, we aimed to investigate the effect of ticagrelor and ADP on lipid raft composition by studying their impact on cholesterol distribution and P2Y1 and P2Y12 localization in platelet lipid rafts.

Material and methods

Experimental groups To investigate the impact of ticagrelor on the organization of cholesterol in the platelet membrane, we defined 5 experimental groups: i) control group; ii) platelets stimulated by ADP; iii) platelets treated by ticagrelor; iv) platelets treated by ticagrelor and then stimulated by ADP (ticagrelor + ADP); v) platelets incubated by Methyl-β-cyclodextrin (MBCD) and stimulated by ADP (MBCD + ADP). MBCD was used to deplete cholesterol in the platelet membrane.

Raft isolation and cholesterol dosage Isolation of lipid rafts was performed as previously described (12). Briefly, platelet pools were obtained from healthy donors from the French Blood Transfusion Center (Etablissement Français du Sang Bourgogne Franche-Comté, Besançon, France). A total of 2×1010 platelets were used in each experiment. Platelets were stimulated by ADP (Bio/Data corporation, Horsham, USA) 200µM and 5 mM CaCl2 for 10 min. Cells were incubated by ticagrelor (C4242, ALSACHIM, Illkirch, France) 4µM or MBCD (C4555, Sigma-Aldrich, Saint Louis USA) 2% for 30 min with shaking at 37°C. Samples were homogenized by Dounce homogenizer on ice in MBS buffer (25 mM MES, 150 mM NaCl, pH 6.5) containing Triton X100 1% (w/v) concentration. Lysate in a 45% sucrose solution was overlaid with a sucrose gradient (5% to 35%) in 8 ml of MBS buffer and was centrifuged for 20 hours at 34000 RPM at 4°C in Sorvall WX with a swinging rotor TH-641 (Thermo Scientific France, Villebon sur 97

Yvette, France). Twelve sucrose fractions (fraction 1 to 12) were collected from the top to bottom of the tube. Cholesterol concentration was determined based on the Folch method (13) and utilizing gas chromatography/mass spectrometry (GC-MS) (14). This experiment was repeated 3 times.

Immunoblot assay Protein markers of lipid rafts (CD36, Flotillin 1 and Flotillin2) and presence of P2Y1 and P2Y12 were evaluated by immunoblot assay. Rabbit polyclonal anti-P2Y1 (ab85896) and anti- P2Y12 (ab180366) and monoclonal anti-Flotillin-1(ab411927), anti-CD36 (ab133625) and anti-Flotillin-2 (ab181988) (Abcam, Paris, France) were used for immunoblot analysis. Protein levels in each fraction were quantified by BCA Protein Assay (Thermo Scientific France, Villebon sur Yvette, France). 3 microliters of each sample, containing the same quantity of proteins, were put on nitrocellulose membrane directly. After blocking non- specific binding sites for 1 h with BSA 5% in TBS-Tween (TBS with 0.1% Tween 20), membranes were incubated by primary antibodies, horseradish peroxidase conjugated goat anti rabbit IgG H&L (ab6721) (Abcam, Paris, France) were used as secondary antibodies.

Statistical analysis Data are expressed as mean ± SEM. Significant differences among experimental groups were determined by one way ANOVA and the Tukey test. A p-value <0.05 was considered significant. Before performing ANOVA, normality of data was tested by the Shapiro-Wilk test. All tests were performed using SigmaPlot software version 12 (Systat Software Inc., San Jose, CA, USA).

Results Cholesterol profile in experimental groups Analysis of cholesterol concentrations showed that the profile of cholesterol distribution on fractionated membranes changed in the experimental groups. The peak of cholesterol intensity in the control group was in fraction 2; in platelets stimulated by ADP, the peak was observed in fractions 3, 4 and 5; in platelets treated by ticagrelor in fraction 4; and in ticagrelor + ADP platelets, in fraction 2 with a mini peak in fraction. In the MBCD + ADP group, we found a mini-peak in fraction 2 (Fig 1A to 5A). Compared to the control group, the peak of cholesterol shifted to other fractions in the ADP and ticagrelor groups.

Level of cholesterol on raft and non-raft fractions of plasma membrane in experimental groups Sucrose fractions were obtained after ultracentrifugation of platelet lysate. Levels of cholesterol and presence of protein markers of lipid rafts were examined in these fractions. 98

The first four fractions found in the interface of sucrose 35% and 5% (Fig 1A), which contained protein markers of lipid rafts (namely Flotillin 1 and Flotillin 2 and CD36) were defined as raft fractions (Fig 1B). The remaining fractions (5-12) were considered as non-raft fractions.

We studied the impact of different treatments on raft cholesterol levels by comparing the sum total of cholesterol present in the fractions considered as rafts and non-rafts. In platelets stimulated by ADP, we observed a significant difference in the amount of cholesterol in raft fractions compared to controls (478.60 ±55.82 vs. 982.55±7.10nmol/mL p<0.001) (Fig 6A). We observed a significant difference in the amount of cholesterol in fractions containing rafts in platelets incubated by ticagrelor vs the control group (339.30±12.78 vs. 982.55±7.10 nmol/mL, p<0.001). Lipid rafts of platelets that were treated by ticagrelor and stimulated by ADP had a significantly lower level of cholesterol than the control group (522.42± 85.8 vs. 982.55±7.10 nmol/mL, p<0.001). The decrease in cholesterol level in raft fractions was significant (212.25±2.94 vs. 982.55±7.10 nmol/mL p<0.001) compared to the control group in platelets stimulated by ADP after depletion of cholesterol by MBCD (Fig 6A). There was no significant difference in the level of cholesterol in fractions considered as non-rafts in all groups (Fig 6B).

Lipid raft markers, P2Y1 and P2Y12 presence and localization in fractions Considering protein markers of lipid rafts, we observed that activation by ADP changed the localization and expression of Flotillin 1, Flotillin 2 and CD36 compared to the control group (Fig 1B). Although ADP stimulated platelets were positive for Flotillin 1, Flotillin 2 and CD36, the localization and the intensity of these proteins were different from controls (fractions 3, 4 and 5 in ADP stimulated vs. fractions 1, 2 and 3 in controls)(Fig 2B). In platelets treated by ticagrelor, expression of Flotillin 1, Flotillin 2 and CD36 was weak (Fig 3B). In the ticagrelor + ADP group, the expression trend of these proteins was more similar to that of the control group than ADP stimulated platelets (Fig 4B). In the MBCD + ADP group, CD36 expression was completely lost (Fig 5B). We also examined the localization of P2Y1 and P2Y12 in the experimental groups. Dot blot analysis of these two proteins showed that in resting platelets, they localized in non-raft fractions (Fig 1B), whereas after stimulation by ADP, P2Y1 was found strongly in fraction 5, and both P2Y1 and P2Y12 lost their strong expression in non-raft fractions (Fig 2 B). In platelets treated by ticagrelor, we observed weaker signaling in non-raft fractions compared to ADP stimulated platelets and control groups. The ticagrelor-treated group showed a very weak positivity of these two proteins in raft fractions. The trend of P2Y1 and P2Y12 presence was similar to that of the group stimulated by ADP, but unlike the control group (Fig 3B). 99

In the ticagrelor + ADP group, presence of P2Y1 and P2Y12 followed the same trend as in the group stimulated by ADP alone, although the signals were weaker than ADP stimulation alone (Fig 4B). In MBCD + ADP platelets, despite ADP stimulation, we did not observe any signal of presence of P2Y1 and P2Y12 in raft fractions and the protein profile was similar to that of the control group, but at a weaker level (Fig5B).

Discussion Our study shows that treatment with ticagrelor and stimulation by ADP could induce a change in the distribution of cholesterol in plasma membranes of platelets. The presence and strength of expression of Flotillin1, Flotillin2 and CD36 changed after activation by ADP, after ticagrelor treatment and after cholesterol depletion by MBCD. These changes confirmed that these lipid raft markers are localized in parts of the membrane enriched in cholesterol. This finding is in line with previous studies regarding their localization on cholesterol-enriched micro domains of membrane (15–17). In addition, this finding confirms our previous study (12) showing that the strength of expression of raft protein markers is related to the level of cholesterol. Comparing raft organization of ADP-stimulated platelets to the control group, we found that the cholesterol peak in fraction 2 disappear in favour of fractions 3, 4 and 5, showing the impact of ADP in cholesterol distribution. In addition, raft markers showed weaker expression in fraction 2 compared to controls, and were present in fractions 3 to 5. In the control group, P2Y1 and P2Y12 were found in non-raft fractions. After ADP stimulation, they were expressed in raft fractions 3 and fraction 5. This suggests that fraction 5 could be considered as a fraction containing rafts, whereas rafts were found only in fractions 1-4 in the control group. Taken together, these results confirm that ADP stimulation reorganizes raft membranes in platelets. The decrease in the level of cholesterol in raft fractions after stimulation by ADP is in line with the findings of Heijnen et al. (18), who showed cholesterol accumulation in the filopodia of activated platelets, and microparticle formation via blebbing in filopodia of platelets (19–21). We could assume that platelets lose cholesterol via release of microparticles from the plasma membrane. This hypothesis is reinforced by the findings of Del Conde et al showing that vesicle release might be a raft-dependent process (22). These assumptions are also coherent with the results of Biro et al, who showed that lipid rafts are present in platelet-derived microparticles, but the lipid composition of the microparticles is different depending on the platelet antagonist used (23). This is coherent with our finding of different levels of cholesterol in lipid rafts, and different distribution of cholesterol depending on the treatment. In the ticagrelor group compared to controls, we found that treatment by a P2Y12 antagonist decreased and shifted the peak of cholesterol to fraction 4. Surprisingly, in platelets treated by ticagrelor, raft markers were absent in all fractions compared to other groups. Conversely, ADP stimulation after ticagrelor treatment reversed this condition to a profile similar to that of the control group. It has been suggested that ticagrelor does not

100

dock to the agonist-bound P2Y12 and requires a mediated model of the P2Y12. Ticagrelor reversibly binds to extracellular regions of P2Y12 (24). Given the reversibility of this interaction, it is possible that ticagrelor does not make a vital change to the position of P2Y12 or the lipid composition of the membrane by itself. Serebruany et al suggest that the cyclic nature of the interaction between ticagrelor and PY12 can cause cell damage (25) and changes in the plasma membrane’s natural physical properties. Presumably, the plasma membrane may lose its cholesterol and consequently its membrane asymmetry, which is the signature of lipid raft presence. Despite the importance of these results, the lack of empirical and experimental evidence showing the underlying mechanisms of the impact of ticagrelor on platelet membrane restricts our ability to further discuss these results. Expression of P2Y1 and P2Y12 in raft fractions showed differences between experimental groups. These proteins were absent in raft fractions of the control group, but it seems that ADP and ticagrelor promote their presence in rafts and in cholesterol-increased fractions. Therefore, beside the stimulation or treatment, perhaps they need a threshold level of cholesterol in the raft part of the membrane to be able to stay in the raft, and below that level, they cannot remain in the rafts. We observed that after depletion of cholesterol, even stimulation by ADP could not bring these proteins to the raft fractions. Therefore, patterns of their presence after depletion of cholesterol were similar to the control group. In this regard, it has previously been shown that cholesterol homeostasis is critical for normal receptor function (26).

Conclusion

Taken together, our results show that ticagrelor and ADP changed the level of cholesterol in plasma membranes. These changes might be considered as a reorganization of cholesterol and/or re-distribution of this lipid through the membrane. Our findings also show that maintenance of certain proteins requires the presence of cholesterol, and redistribution of cholesterol may alter their localization. These findings warrant further investigation, in particular to identify the underlying mechanism, but they are an important basis for future research, providing new insights into pharmacological aspects of platelet membrane organization after anti-platelet therapy.

Acknowledgements This work was supported by “Conseil Regional de Franche-Comté”. We thank Mrs Fiona Ecarnot for her critical reading of this manuscript. We are really grateful for technical support of Lipidomic Analytical platform of Dijon.

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23. Biro E, AkkermanJWN, Hoek FJ, Gorter G, Pronk LM, Sturk A, et al. The phospholipid composition and cholesterol content of platelet-derived microparticles: a comparison with platelet membrane fractions. J ThrombHaemost.déc 2005;3(12):2754‑63.

24. Paoletta S, Sabbadin D, von Kügelgen I, Hinz S, Katritch V, Hoffmann K, et al. Modeling ligand recognition at the P2Y12 receptor in light of X-ray structural information. J Comput Aided Mol Des. août 2015;29(8):737‑56.

25. Serebruany VL. Viewpoint: reversible nature of platelet binding causing transfusion-related acute lung injury (TRALI) syndrome may explain dyspnea after ticagrelor and elinogrel. ThrombHaemost. déc 2012;108(6):1024‑7. 103

26. Ibrahim S, McCartney A, Markosyan N, Smyth EM. HeterodimerizationWith the Prostacyclin Receptor Triggers Thromboxane Receptor Relocation to Lipid Rafts. ArteriosclerThrombVasc Biol. 1 janv 2013;33(1):60‑6.

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Figure legends Figures 1A, 2A, 3A, 4A, 5A: Cholesterol content (Ch ▪) of platelet membranes of different experimental groups: Control (1A), stimulated by ADP (2A), treated by ticagrelor (3A), treated by ticagrelor plus stimulation by ADP (4A), and cholesterol-depleted then stimulated by ADP (5A). Fractions: 1-2-3 corresponding to 5% sucrose, 4-5-6-7-8 corresponding to 35% sucrose and 9-10-11-12 corresponding to 45% sucrose. ADP: adenosine diphosphate, MBCD: Methyl-β-cyclodextrin

Figures 1B, 2B, 3B, 4B, 5B: Results of dot blot analysis for specific marker proteins of lipid rafts (Flotillin- 1,Flotillin-2 and CD36) and P2Y1 and P2Y12 in all fractions. Each graph is representative of three different experiments (n=3).

Figure 6: Distribution of cholesterol in A) raft and B) non-raft of experimental groups. Error bars represent standard error of three measurements of three different experiments. (n=3) *= p value<0.001

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Abstract: impact of antiplatelet drugs on cholesterol level of platelet lipid raft

Poster presentation, ESC, Rome, 2016

Impact of antiplatelet drugs on cholesterol level of platelet lipid rafts

Vahideh Rabani, Damien Montange, Siamak Davani

Background: Cholesterol (Ch)-rich rafts play a crucial role in platelet activation signaling pathways. Several antiplatelet medications target the membrane proteins of platelets. Most of these pathways are dependent on Ch-rich raft. We aimed to investigate impact of five principal antiplatelet agents on Ch arrangement in Ch-rich raft of platelet plasma membranes. Methods: Platelets were obtained from healthy donors from the French blood transfusion center. Platelets were incubated in MBS buffer solution containing: Acetylsalicylic acid 100 µM, Dipyridamole 50 µM, Tirofiban 60 nM, Ticagrelor 4 µM and Vorapaxar 100nM for 30 min at 37°C in shaking. Platelet membranes were fractionated using Triton X100 1%. Platelets without drugs were considered as a control. Ch-rich rafts were identified by lipidomics analysis and immunoblot staining of markers (Flotillins and CD 36). Levels of Ch in raft and non-raft fractions were compared. Results: Cholesterol level was determined in Ch-rich rafts. Compared to control platelets, Ch levels in platelets treated by antiplatelet drugs were significantly lower in Ch-rich raft fractions. No difference was found between non-raft fractions in all groups (Fig. 18). Acetylsalicylic acid, Dipyridamole, Tirofiban and Ticagrelor reduced the level of Ch in Ch-rich raft fractions. Vorapaxar had no impact on Ch levels in the plasma membrane of platelets.

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Avarage cholesterol concentrations of raft fractions have been summarized in table 2. Conclusion: Antiplatelet drugs change the reorganization of Ch-rich rafts in plasma membranes of platelets.

Table 2 : Mean of cholesterol concentration in cholesterol rich raft and non-raft microdomain of platelet plasma membran after incubation with antiplatelets drugs. Experimental groups Ch-rich raft ±SEM Non-raft ±SEM Acetylsalicylic acid 357,049368 17,1326588 197,794406 49,2439777

Dipyridamole 179,886076 62,44241 247,833391 28,843973

Tirofiban 207,962462 74,8413674 394,972585 50,12

Ticagrelor 305,693542 47,5303696 265,3711 31,1146386

Vorapaxar 601,949791 60,5489 269,628254 61,0204

Control 982,550455 5,29248291 244,302882 49,4008133

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Figure 18 : Impact of anti-platelets drugs on lipid raft of plasma membrane.

Up) representative picture of the gradient obtained after centrifugation. Light refractive band, characteristic of lipid rafts in the low-density fractions of the gradient, showed deifferent morphology after different treatments. Down) Cholesterol level changed in raft and non-raft fraction of plasma membrane after drug treatments.

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Abstract: PAR-1 localization through re-organization of lipid rafts in thrombin-

activated and Vorapaxar-treated platelets

Poster presentation, ESC, Rome, 2016

PAR-1 localization through re-organization of lipid rafts in thrombin-activated and

Vorapaxar-treated platelets

Vahideh Rabani, Damien Montange, Siamak Davani

Background: Vorapaxar is a new protease-activated receptor-1 (PAR1) antagonist. It has been demonstrated that lipid raft (LR) localization plays a pivotal role in presenting the PAR- 1 exodomain for interaction with coagulation proteases. Thrombin will delocalize or alter the membrane organization to make the catalytic domain of PAR-1 accessible for protease. We aimed to investigate if Vorapaxar could alter the cholesterol-rich raft organization, and if this reorganization changed the localization of PAR-1 on the platelet membrane. Methods: Platelets were obtained from healthy donors from French Blood Transfusion Center. Platelets were incubated with either Thrombin (0.5u/ml), or Vorapaxar (100nM), or both, or neither (control group). Platelet membranes were fractionated using Triton X100 1%. LRs were identified by lipidomics analysis and immunoblot staining of markers (Flotillins and CD 36). Localization of PAR-1 and 4 was verified by same techniques in plasma membrane fractions. Results: Lipid rafts were identified based on their concentrations of Cholesterol (Ch) and sphingomyelin (SM). Stimulation with thrombin changed the organization of the membrane. These alterations were less pronounced on platelets previously treated by Vorapaxar. Dot blot analysis showed that in the control group, Par-1 presented in fractions considered as non-rafts, with very low presence in the first raft fraction (Fig. 19). Conclusion: Localization of PAR-1 on the platelet membrane changes in the presence of Vorapaxar and/or thrombin. It is established that thrombin activates PAR-1 by cleaving a peptide bond (Arg41-Ser42) in the receptor’s extracellular domain. This cleavage discloses a new N-terminus of the receptor referred to as a tethered ligand. This “new tail” of the receptor interacts with a distinct domain of the cleaved receptor and, ultimately, causes its activation (21). It has been demonstrated that lipid raft (LR) localization plays a pivotal role in presenting the PAR-1 exodomain for interaction with coagulation proteases in endothelial

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cells(32). Therefore we can consider that thrombin will delocalize or alter the membrane organization to make the catalytic domain of PAR-1 accessible for protease.

Figure 19 : Vorapaxar treated and thrombin activated platelets showed different cholesterol and protein profiles.

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3.1.1 Supplementary Data

Figure 20: Impact of principal activators on lipid raft of plasma membrane.

Up) representative picture of the gradient obtained after centrifugation. Light refractive band, characteristic of lipid rafts in low-density fractions of the gradient, showed deifferent morphology after different treatments. Down) Cholesterol level changed in raft and non-raft fractions of plasma membrane after activation through different antagonist.

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3.1.1.1 Aspirin vs. arachidonic acid

To investigate the impact of aspirin and activation of platelets by Arachidonic Acid (AA), we have incubated heathy platelet with AA 5 mg/ml and acetylsalicylic acid (aspirin) 100 µM as previously described in previous parts of this chapter.

Plasma membrane of platelet activated by AA, showed a reduction in cholesterol level in raft fractions vs control group (493.74±20.26 vs. 982.55±7.10 p<0.001) (Fig. 20).

There were no significant difference in fractions considering as non-raft after activation by

AA and treatment with aspirin at the level of cholesterol.

It seems that both treatment (activation and inhibition) cause loss of cholesterol in plasma membrane of platelet. This lost followed by decrease in expression strength of lipid raft protein markers as Flotillin 1 and 2 and CD36 after treatments comparing to control (Fig. 21).

Figure 21 : Aspirin treated and arachidonic acid activated paletlets showed different lipid raft organisation.

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3.1.1.2 Collagen vs. tirofiban

To investigate the impact of activation of platelets with collagen and tirofiban, we have incubated healthy platelet with 1.9 mg/ml collagen and tirofiban 60 nM.

Treatment by tirofiban and activation by collagen change organization of lipid raft (Fig.22).

In platelets activated by collagen we observed increase in cholesterol amount comparing to control group (1107.01±17.04 vs. 982.55±7.10) (Fig.20).

There were no significant differences in fractions considering as non-raft fraction after activation by collagen.

Figure 22 : Platelet activation by collagen and treatment with tirofiban change cholesterol distribution on platelet membrane.

3.1.1.3 Dipyridamole, epinephrine

To investigate the impact of activation of platelets with epinephrine and effect of dipyridamole on organization of lipid raft of platelet, we have incubated healthy platelet we have activated platelet by epinephrine 1mM or incubated by dipyridamole 50 µM.

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Treatment by dipyridamole and activation by epinephrine change organization of lipid raft

(Fig.23).

In platelets activated by epinephrine we observed decrease in cholesterol amount comparing to control group (346.02±39.66 vs. 982.55±7.10) (Fig.20).

Figure 23 : Lipid profile change after activation by epinephrine or treatment by dipyridamole.

In each experiment, in addition to control group we had groups of shams with platelets incubated in buffer of activators and drugs with same duration of incubation. None of these groups showed significant differences with control groups in level of lipid and proteins.

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4. Proteomics analysis of platelet membrane and system biology

For decades we believed in “one-gene/one-enzyme/one-function” framed by Beadle and

Tatum (Beadle and Tatum, 1941) (183), or one protein bring one substrate to one product.

Omics revolution which showed complexity of biology by myriads of molecules in one sample revealed that biological functions cannot be understood by investigating a single gene or protein. It confirmed that biological functions are a property of the biological system and must be studied at system levels.

It is nothworthy to be mentioned that bioinformatics has a central role in system biology.

Bioinformatics provided expand variety of tools from analysis protein expression patterns in two-dimensional gels (184) to identify and quantify proteins based on mass spectrometry and other chemical data. In proteomics field most of developed tools are available on the

Internet through the World Wide Web, and can be accessed through the ExPASy proteomics server (www.expasy.ch/tools/). System biology in level of proteomics will progress rapidly if all the data generated in proteomics projects store in annotated and curated databases. This storage result in integration of theoretical and experimental biological data with large-scale proteomics projects (185) as Human Proteome Organization (https://hupo.org/) (186).

System biology is a branch of science which use different level of information to understand how biological system are operational (187). System contains dynamic components which interact with each other. In order to understand the mechanism of its function we need modeling the system. We must consider that the complexity of systems is depending on number of components and level of system (Fig.23). In this context, properties of a system

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araise from interactions of its components and probably whole interactions are more than the sum of components. Biological systems and cellular networks are governed by specific laws and principles and understanding of them will be essential for a deeper comprehension of biology (188).

4.1 Network analysis

One of the models of study in system biology is “network”. Network is a mathematical structure which reduces complexity of a system by “simplifying” the system and summarizes it as components (nodes) and interactions (edges) between them. It seems that in this simplifying process functional richness of node will be lost but sometimes this simplification results to new discoveries. This node can be proteins or other macromolecules. The edge is physical, biochemical and functional interactions. These interaction or edges can be computed by bioinformatics analysis. In network analysis we try to provide maps of interaction as unbiased as possible (188). This analysis let us modeling molecular interactions in detail at the scale of whole cells or in our study in scale of platelet plasma membrane. Normally data used as foundation in a network is provided by:

1) Already existing data available in the literature, for example an experimental or

original article which proved physical or biochemical interactions between our

molecules in our data sets

2) computational predictions based on available “orthogonal” (statistically

independent) information such as sequence similarities, gene-order conservation, co-

presence and co-absence of genes in completely sequenced genomes and protein

structural information (189)

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3) Using unbiased high throughput experimental mapping strategies applied at the

scale of whole genomes or proteomes (190).

Literature-curated data present the advantage of using already available information and already proved experimentally, but they are limited and they lack of systematization.

Computational predictions are fast and efficient but they can be imperfect because they use indirect information. The best approach is high throughput data try to describe unbiased, systematic, and well-controlled data. They are still incomplete but in few years we can have highly reliable, comprehensive protein-protein interaction and gene regulatory network maps for human(191). Therefore all accessible sources were used to provide as much as data about molecule under investigation. Then the reliability of these data will compute by bioinformatics tools. There are progressive statistical analysis use in determine how each interaction is reliable. In these mathematical calculation number of physical protein pair

(completeness), probability of whether interactions can and cannot be detected by a particular assay (assay sensitivity), the fraction of all detectable interactions found by a single implementation of any interaction assay (sampling sensitivity) and the proportion of true biophysical interactors (precision) will considered. These calculations give a quantitative idea of accuracy of a particular interaction network (191). There are several level of network

(Fig. 24 ) and protein interaction network is becoming one of the major objectives of system biology (192).

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Figure 24 : Different level of network analysis (188).

4.1.1 Protein interaction network in platelets

Both clinical and basic researchers have great interest in understanding platelet physiology by untangling the complex network of cellular signaling. This holds promise for better diagnostics, monitoring and therapy as well as identifying potential novel drug targets and development of novel antithrombotic strategies (193). During last decade many proteomics studies have done on platelets which have been reviewed in first chapter and the review article. These studies provided massive data bases which extracting information from them need a special knowledge and tools. Boyanova et al. in 2012, introduced a comprehensive human platelet repository (PlateletWeb) for systems biologic analysis of platelets (59). This comprehensive source gather result of proteome and transcriptome studies on platelet and can be a helpful tool for network analysis of platelet proteins. Although plateletWeb prepared for platelet studies but it still needs to be completed.

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4.1.2 Functional protein network analysis to find good hits

Searching new therapeutic target on platelet, we have focused on proteomics analysis.

Proteins are the “executive core” of cellular events and alterations in their behavior cause thousands of pathologies. Proteins are the major class of drug targets (194). Recently it is demonstrated that protein-protein interactions (PPIs) can be targeted by small molecules with a specificity and selectivity. These small molecules considered as new generation of drugs and consequently PPI became a new therapeutic target (192,195,196). Considering PPI as target, we first need to find good Hits. Hits are proteins in network which show an interesting type of interaction with high percentage of occurring. To this aim protein network of a system can help us to find good hits. For example the contribution of several platelet receptors and their ligands has been highlighted in thrombus formation. Although fibrinogen has been known for years as essential for platelet aggregation, recent studies demonstrated that fibrinogen-independent platelet aggregation occurs in both gene deficient animals and human patients under physiological and pathological conditions (197).

This suggests that there are other unconsidered molecule(s) may also play a role in these processes. Identification and characterization of these molecules and their interactions could help to find good hits toward development of new therapies thrombotic diseases.

4.1.3 Functional protein interactive network in lipid raft of platelet

Lipid rafts provide a platform which prepares a place for landing proteins with a proper topography resulting in a successful interaction between them. Lipid rafts proteins actively use protein-protein interaction to accumulate signaling proteins on these microdomains

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(198). Lipid raft attracts signaling proteins and membrane skeletal association and allows these proteins to move numerous to new locations (151). In platelet, protein markers of lipid raft Flotillin 1 and Flotilin 2 are highly conserved membrane proteins which are structurally and functionally related. They are heterooligomer and they form molecular scaffolds in cholesterol-rich membrane microdomains beside play roles in membrane receptor clustering

(199).

In this part of the thesis, we aimed to study the proteome of this restricted part of membrane to understand which proteins are found in raft or non-raft part of platelet in resting and activation condition. In best of our knowledge the first report of proteomics of platelets lipid raft provided in this thesis. Network analysis of three proteins with important role in platelet function described below. Results of these analyses are presented in one article published in Platelets and some abstracts presented in American Heart Association,

European Society of Cardiology and SFPT.

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Published Article

Functional network analysis of FXIII in lipid raft of platelet

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Abstract: Functional protein network of GSK3B in lipid raft of platelet

Poster presentation, SFPT, Nancy, 2016

Activation/ inhibition network protein of Glycogen synthase kinase 3 beta

(GSK3B) in platelets lipid rafts

Vahideh Rabani, Damien Montange, Siamak Davani

Background: One of the classical enzymes regulated downstream of class I PI3Ks and Akt is Glycogen synthase kinase 3 beta (GSK3β) which is active in resting cells. Study with pharmacological inhibitors and genetic approaches was shown that GSK3β negatively regulate platelet functions and thrombosis. Means; inhibition of GSK3β is necessary for full platelet responses after activation by different agonists. Furtheremore, the PI3Kβ/PDK1/Akt/ GSK3β pathway plays an important role in platelet activation and thrombus growth and stability at high shear stress. A number of GSK3β’s activators and inhibitors have been suggested in different models but no one has been characterized in platelets yet. Therefore the aim of this study is to propose some new candidates as activator or inhibitor for GSK3β by sorting based on co-localization with this protein on lipid rafts of platelets. Methods: Lipid raft of platelets were isolated by using lubrol WX 0.05% (w/v) and sucrose gradient. After ultracentrifugation, sucrose fractions were sampled. Lipidomic analysis was performed in order to identify the fractions enriched in cholesterol and sphingomyelin (lipid rafts). These fractions were selected for further proteomic analyses. Network of associated proteins was drown by STRING and Reactom data bases. Results: Sucrose fractions containing platelet lipid rafts were identified as (Figure 25A). In these fractions, we observed a group of proteins associated with GSK3β on lipid raft of platelets isolated by lubrol WX (Figure 25B). Only proteins with proposed interaction of activation or inhibition to GSK3β were choosed. These proteins listed below: cell division cycle 42 (CDC42), dihydropyrimidinase-like 2 (DPYSL2), growth factor receptor- bound protein 2 (GRB2), heat shock protein 90kDa alpha(HSP90AB1), integrin-linked kinase (ILK), mitogen-activated protein kinase 1; Serine/threonine kinase (MAPK1), nucleosome assembly protein 1-like 1(NAP1L1), protein phosphatase, Mg2+/Mn2+ dependent, 1A(PPM1A), protein phosphatase, Mg2+/Mn2+ dependent, 1F(PPM1F ), ras-related C3 botulinum toxin substrate(RAC1), ras-related C3 botulinum toxin substrate 2(RAC2), ras

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homolog family member A (RHOA ), related RAS viral (r-ras) oncogene homolog (RRAS), transforming growth factor beta 1 induced transcript 1 protein (TGFB1I1). Among all these proteins DPYSL2 showed the strongest activation effect on GSK3β. Conclusion: We could identify candidate’s proteins that could activate or inhibit GSK3β in lipid raft. These results could provide further insight into the clinical target of pathways through by this molecule.

Figure 25 : Interactive network of proteins around GSK3β on lipid raft of platelets.

A) Identification of raft parts B) Interactive protein network of GSK3β in raft parts.

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Table 3: Proteins with activation or inhibition type of interaction to GSK3β with theirs probability scores.

Table 1: Interactive network of GSK3β in raft of platelets Activation inhibition

CDC42 cell division cycle 42 0.113 0.113

DPYSL2 dihydropyrimidinase-like 2 0.800 -

GRB2 growth factor receptor-bound protein 2 0.149 -

HSP90AB1 heat shock protein 90kDa alpha 0.096 -

ILK integrin-linked kinase 0.110 0.110

MAPK1 mitogen-activated protein kinase 1; Serine/threonine kinase 0.194 0.194

NAP1L1 nucleosome assembly protein 1-like 1 0109 0.109

PPM1A protein phosphatase. Mg2+/Mn2+ dependent 0.109 0.109

RAC1 ras-related C3 botulinum toxin substrate 0.113 0.113

RAC2 ras-related C3 botulinum toxin substrate 2 0.113 0.113

RHOA ras homolog family member A 0.113 0.113

r-ras oncogene homolog 0.113 0.113

TGFB1I1 transforming growth factor beta 1 induced transcript 1 protein 0.73 -

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Abstract: Functional protein network analysis of VASP in lipid raft of platelet

Poster presentation, SFPT, Nancy/ ESC, Rome / AHA, new Orleans, 2016

Protein network of VASP in lipid raft of platelets.

Vahideh Rabani, Damien Montange, Nicolas Meneveau, Siamak Davani

Background: VAsodilator-Stimulated Phosphoprotein (VASP) represents a very sensitive marker of platelet responsiveness to ADP receptor (P2Y12) inhibitors (clopidogrel, prasugrel or ticagrelor). VASP is involved in down-regulation of platelet adhesion to the vascular wall under both physiologic and pathophysiologic conditions. After platelet stimulation, VASP is colocalized with F-actin on Detergent Resistant Membrane (DRM) but the whole macromolecular protein network involved in this activity is not well known. Therefore, the aim of this study was to investigate interactive proteins with VASP on DRM of platelets. Methods: Lipid rafts of human platelets were isolated using Triton X100 1% (w/v) and sucrose gradient. After ultracentrifugation, sucrose fractions were sampled. Lipidomics analysis was performed to identify fractions enriched in cholesterol and sphingomyelin (considered as DRM). These enriched fractions were selected for further proteomic analyses. Post analysis of proteomics results was performed to recognize interactive network and participating protein pathways around VASP. Results: Sucrose fractions containing platelet DRMs were identified as shown in Figure 26. In these fractions, we identified potential proteins interacting with VASP (Fig. 29). Some of the interactions were already confirmed experimentally in Homo Sapiens such as CDC42 and Zyxin (interaction: activation); Vinculin, WAS (Wiskott-Aldrich syndrome effector protein), Ubiquintin and YWHAZ (tyrosine 3-monooxygenase / tryptophan 5-monooxygenase activation protein) (interaction: binding) and GSN (gelsolin) (interaction: inhibition). The association between VASP and others proteins as FYN, FYB, PFN1 (profilin 1), LASP1 (LIM and SH3 protein 1) and SRC were shown experimentally in other species (with their putative homologs). Others proteins in this network are potential candidates for platelet study in order to identify their role in this network and the nature of their relationship with VASP. Conclusion: We identified proteins associated with VASP in DRM fractions containing rafts of platelet membranes. This could provide further insight into the clinical target of pathways through this molecule.

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Figure 26 : Identification of lipid raft of platelet’s membrane by lipidomics and dot blot.

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4.1.4 Suplementary data

4.1.4.1 Network analysis: step by step

Figure 27 showed first network from proteomics data set of platelet’s lipid raft with 335 nodes

(proteins) and 2799 edges (interaction of proteins).

Figure 27 : All proteins of lipid raft of platelets with their interactions

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Figure 28 : Confidence interactive network of VASP

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Among all these proteins, we focused only on VASP and all the other proteins that have an intraction with VASP. Analysis was performed based on confidence interaction. There are different types of interactions, for example, interactions from calculated databases are shown in blue, Interactions previously shown experimentally are shown in purple while gene neighborhood is shown in green, and so on (Fig. 28 ).

To be more clear see the figure of interaction between VASP and FYB below:

FYB stands for Fyn-binding protein, and there are 3 types of interaction between FYB and VASP namely from experimental data, associated in curated data bases, and they mentioned together in publications cited in pubmed.

Experimental/Biochemical Data: score 0.570

Association in Curated Databases: score 0.900

Co-Mentioned in PubMed Abstracts: score 0.502

In next step to find good hits we have analyzed this interaction by molecular action based analysis

(Fig. 29).

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Figure 29 : Interactive network of VASP base on molecular actions.

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Table 4 : Full name of interactive proteins with VASP in plasma membrane of platelet presented in this table.

ACTB actin, beta ACTR3 ARP3 actin-related protein 3 homolog ALB albumin ANXA5 annexin A5 CDC42 cell division cycle 42 CFL1 cofiline 1 CTTN cortactin DIAPH1 diaphanous homolog 1 DNM2 dynamin 2 FYB FYN binding protein FYN tyrosine-protein kinase FYN GSN gelsolin ITGA2 integrin, alpha 2 ITGA2B integrin, alpha 2b (platelet glycoprotein IIb of IIb/IIIa complex, antigen CD41) ITGA6 integrin, alpha 6 ITGB1 integrin, beta 1 LASP1 LIM and SH3 protein 1 LCP2 lymphocyte cytosolic protein 2 MSN moesin MYLK myosin light chain kinase PDE5A phosphodiesterase 5A, cGMP-specific PFN1 profilin 1 PLEK Plekestrin RDX radixin SRC v-src sarcoma TLN1 talin 1 UBC ubiquitin C UTRN utrophin VASP vasodilator-stimulated phosphoprotein VCL vinculin VWF von Willebrand factor WAS Wiskott-Aldrich syndrome; Effector protein for Rho-type GTPases WASF2 WAS protein family, member 2 YWHAZ tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, zeta polypeptide ZYX zyxin

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We analysed the interactive network to understand all the possible types of interaction between each protein and VASP, such as activation, inhibition and so on.

These results help us to find some good hits and valuable interaction that warrants more careful study as a target.

To summarize this network, we found the following major interactions:

 VASP activation was already confirmed experimentally in Homo Sapiens with CDC42 and

Zyxin.

 VASP inhibition was already confirmed experimentally in Homo Sapiens with GSN (gelsolin).

In our opinion, these three interactions are good hits and really valuable to be studied because they affect the function of VASP.

Association between VASP and some of other proteins in this network has been shown experimentally in other species. These proteins are: FYB / Vinculin/ WAS (Wiskott-Aldrich syndrome effector protein)/ Ubiquintin / YWHAZ (tyrosine 3-monooxygenase / tryptophan 5-monooxygenase activation protein) / PFN1 (profilin 1) / LASP1 (LIM and SH3 protein 1) and SRC.

Therefore, other proteins in this network are potential candidates for platelet study in order to identify their role in this network and the nature of their relationship with VASP.

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5. Discussion

Lipid rafts are a prerequisite for the functioning of many of receptors in charge of platelet activation and signal transduction participating in, almost, all phases of platelet-mediated haemostasis and thrombosis (14,30,31,35,112,119,124,149–151,200,201). Consequently their roles in thrombotic diseases are undeniable and make them a high potential therapeutic target in antiplatelet therapy.

This goal was achieved by addressing these primary aims:

1. Identification and characterization of platelet lipid raft

a. Proposing a standard method for isolation of lipid raft by comparing different

tools for isolation

b. Characterization of lipid raft via lipid and protein profile of them

c. Finding the best definition of raft in platelet

2. Investigation on lipid raft organization in case of :

a. Activation by principal and known activation signaling pathway and their

receptors

b. Inhibition/antagonization of these receptor by known anti platelets drugs

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c. Incubation with inhibitors/antagnists and activation by corresponding

activators

3. Expand our knowledge on proteome of lipid raft bioinformatically

a. Preparing a data base of platelet lipid rafts’ proteins

b. Introducing good hits as new candidates for therapeutic targets

After the first chapter consecrate to some generality, the second chapter was dedicated to the study of lipid raft isolation tools. In this chapter, we have compared the impact of three different detergents on lipid and protein profiles of rafts and non-rafts based on lipidomics and proteomics analysis in order to propose a valid and effective technique to isolate lipid rafts from platelet membrane. A growing body of evidence supports the importance of choosing an appropriate detergent for the study of lipid rafts (108,202–205). In this regard, our lipidomics results showed the presence of lipid rafts enriched in cholesterol and sphingomyelin within sucrose 5% fractions only by using Brij35, Lubrol WX and Triton X100

1%. In contrast, the use of the same detergents at 0.05% could not produce the same results. These results suggest that the concentration of detergent is crucial in isolating lipid rafts. Similar results were obtained by Garner et al. on the lipid bilayer with Triton X100 and

Lubrol WX at different concentrations (205). Moreover, we obtained greater enrichment of lipid rafts in Ch/PC and SM/PC using Triton X100 and Lubrol WX 1%. It is evident that the physical and chemical nature of the detergent has an impact on the solubilization procedure of plasma membrane by detergents (205,206).

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We also provide evidence that shows how different isolation processes could affect localization of studied proteins. Lewandrowski et al. have produced a rather complete liste of platelet membrane proteins by enriching plasma membrane using 2-phase aqueous partitioning systems (66). Comparison of our dataset with them showed that 359 proteins were present only in our study and 819 proteins only in theirs. These differences could be explained by different methods which have been utilized in these two studies or simply, using detergents might have had solubilized membrane proteins. However, our findings revealed 359 new proteins to be added to the existing body of literature. We observed that the total number of proteins identified by at least two peptides was greater when we used

Triton X100 1%, Lubrol WX 0.05% and 1% to lyse the platelets. These findings are in agreement with the concept of “Detergent selectivities” developed by Schuck et al. regarding the ability of different detergents to enrich different subsets of membrane proteins, cholesterol, and sphingomyelin over glycerophospolipids such as phosphatidylcholine (204). Among all the detergents we tested, Triton X100 1% seems to be the most suitable for lipid raft isolation. Nevertheless, our findings suggest that, depending on the objective of the study on lipid rafts, choosing a compatible detergent at a suitable concentration is of paramount importance, particularly if an investigation of the association between specific proteins and lipid rafts is planned. Consequently, in our further studies on

FXIII we chose Lubrol WX, 0.05% as FXIII extraction showed compatibility with this detergent.

This part of this thesis can be considered as a model study which is capable to enlighten many discrepancies in this field and bring new insight into platelets lipid raft studies. We evaluated lipidomics (Cholesterol, Sphingomyelin and phosphatidylcholine) profile accompanied by proteomics profile of the same sub domains. 148

In third chapter of thesis we have investigated the impact of activation and drug administration on organization of lipid raft of platelets.

We observed that activation by different platelet activators except collagen decreased level of cholesterol of lipid raft as well as antiplatelets tested here except vorapaxar. Cholesterol distribution profile also changed beside level of expression of proteins on lipid raft.

Increase in amount of cholesterol after activation by collagen could be a concequence of

“merging” internal membranes and granules by plasma membrane. It has been shown that lipid rafts can be found in compartments of cells, such as Golgi apparatus, which participate in protein transport towards plasma membrane (207). This hypothesis is supported by evidence provided in our previous works (208), reporting the presence of proteins of Golgi apparatus and endoplasmic reticulum in proteomics data obtained in raft and non-raft parts of plasma membrane of platelet. In other words, the cholesterol increased in lipid rafts after platelet activation by collagen, can, at least partially, be explained by “merging” Golgie apparatus and endoplasimic reticulum. Nevertheless, this hypothesis needs to be further explored by experimental studies.

Conversly, other activators (thrombin, ADP, AA and epinephrine) reduce the quantity of cholesterol in lipid rafts which seems to be contradictory to activation by collagen.

For instance, it might happen due to release of microparticles and granules because lipid rafts also can be found on these particles which its composition may change in terms of the platelet activator (209).

Decrease of cholesterol in lipid raft is also observed after antiplatelet drugs (Aspirin, dipyridamole, tirofiban, ticagrelor and vorapaxar) administration but not with vorapaxar. 149

Releasing granules and microparticles might not be applicable here, because these mechanisms are happened after activation and antiplatelet drugs are supposed to inhibit platelet activation. It has been proposed that binding and unbinding cycle of ticagrelor to

P2Y12 causes cell damage that subsequently, can cause platelet destruction probably by apoptosis (210). This phenomenon has been shown with aspirin (211) and tirofiban

(168,169). Overally, based on these evidences, this cholesterol reduction after drug administration might be related to reduction of platelets life span. In other words, drug administration increases the mortality rate of platlets which is usally programed to be conducted through an apoptotic event (212,213). It has already been suggested that beginning the apoptotic phase is associated with elimination of plasma membrane cholesterol (214,215) as it showed that apoptotic cells lose their liquid ordered phase of their plasma membrane maintained by cholesterol (216). Other hypothetical mechanism for the reduction of cholesterol quantity after drug administration could be the internalization of receptors with some part of membrane in endocytosis vacuole (217). However, both hypotheses should be studied more carefuly (Detailes in prespective chapter).

In the final chapter of the present thesis, we have focused on proteomics analysis of platelet lipid raft. Based on high throughput studies, we showed new proteins interacting with elements of activation and coagulation of platelets. We have investigated interactive network of FXIII in resting and stimulated platelets and we have presented a set of proteins interacting with FXIII on lipid raft in these two different conditions (218). Our results suggest that key “platelet activation” proteins are further associated to the raft domain. In contrast to them, on the non-raft domains, we rather observed accumulation of proteins involved in

150

“regulation of cytoskeleton actin” before and after activation by thrombin. After activation of platelet, a decrease in the quantity of the plasma membrane proteins was observed. This latter event could be explained by secretion of proteins and granules out of platelet after activation, as after activation, we could find more proteins in supernatant of stimulated platelets (219,220). Although after activating platelets we found fewer proteins interacting with FXIII-A1 of the raft domain, these remaing proteins participate in more “clot retraction” reactions. This finding supports lipid raft membrane specialization, in addition to its other functions, as a signaling platform and dynamic structure involved in platelet activation (112).

We have shown that FXIII interact with actin only after activation and only in the raft part.

Previously it was shown that FXIII needs either SM riched microdomain for clot retraction

(35) or to externalize their cytoplasmic pool of FXIII-A(221). Interaction of FXIII with pleckestrin (222), FGA(F2) (223,224), FG, FN(225) and HSP27 (226) have been proven experimentally.Therefore, further investigation of other proteins in networks of FXIII-A1 , in activated and non activated platelets, and their interaction with FXIII-A1 could enhance our knowledge on this process.

Putting to gether all results suggests that lipid rafts are submitted to a rearrangement after any kind of treatments (activation or drug administration) on platelets membrane and there is an analogy between these rearrangements in lipid and protein content of membrane.

These rearrangements should be studied more profoundly as they have strong potential to provided efficient therapeutic targets (see perspectives).

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6. Conclusion

The research outcomes presented in this thesis have contributed to the current understanding of some of the least known platelet membrane microdomain called lipid raft.

We tried to shed light on debated definition of them and their lipid and protein profiles. We have showed that lipid raft of platelet deserve to be investigated seriously in pharmacological research to find new therapeutic target particularly in antiplatelet therapy.

Our result revealed that the number of new proteins in plasma membrane of platelets is enourmous. Some of these proteins are previously and separately investigated but rarely computed as a system. Our bioinformatical computation on lipid rafts brings new ideas in field of searching therapeutic target in antiplatelet therapy by focusing on platelet lipid raft.

In addition we have shown that research on pharmacological aspects of platelet’s lipid raft is feasible in spite of all controversary debate in definition of raft and with all limitation in high throughput studies and with highly sensitive nature of platelets.

Another interesting result of this study is the impact of antiplatelets on lipid raft and their effect on the organization of platelet membrane.

Finally, our results showed that lipid raft could be considered as potential target in pharmacological research and omics studies are important and indispensable to push foreward border of knowledge in this field.

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7. Perspectives

7.1 Investigation on cause of cholesterol loss after manipulation

To investigate if loss of cholesterol after manipulation of platelets is related to apoptosis or not we have done Western Blot analysis of caspase 3, 8 and 9 on whole platelet lysate in different treated platelets. These results are far from to confirm apoptosis of platelet after treatment but merit to be presented here (Fig. 30) as our early future lines of study.

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Figure 30: Expression of caspase family in platelets activated and treated by drugs. Different pattern in caspase family expression have been observed after ADP, AA activation and aspirin, ticagrelor incubation and in platelet incubated first by ticagrelor or aspirin and then activated by corresponding activators.

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7.2 Impact of vorapaxar and thrombin on PAR-1 localisation on platelet lipid raft

Among all drugs tested on cholesterol level of lipid raft, only voapaxar maintain cholesterol distribution near to control group. In fact we are really curious about the mechanism of vorapaxar and thrombin on membrane of platelet and their impact on PAR-1 localisation on membrane. Answer to this question defines one of our promising perspectives and made us to set a collaboration with laboratory of Prof. Bernard PAYRASTRE at Toulouse (UMR 1048

I2MC “Production et function plaquettaires, signalization et phosphoinositides”). Following images are our preliminary image of PAR-1 localisation on lipid raft of platelets (Fig. 31 and

32).

These preliminary results showed that 1) there is a colocalisation between PAR-1 and rafts in activated platelet. 2) Level of expression of PAR-1 on platelet membrane augmount with increase of vorapaxar dosage.

155

Figure 31 : Localization of PAR-1 on platelet membrane. A) Resting platelets B) Activated paletelet by TRAP (Thrombin Receptor-Activating Peptide) C) cholesterol depleted platelet activated by TRAP Anti PAR-1-Alexa 488. Cholera toxine- Alexa 594

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Figure 32 : PAR-1 in resting platelets treated by different dose of vorapaxar. A) without vorapaxar B) treated by 73.5 ng/ml C) 735 ng/ml D)2,2µg/ml vorapaxar

157

7.3 Quantitative proteomics analysis

To validate proteins proposed as good hits for therapeutic target we need to repeat our proteomics experiments. We have done already a semi-quantative analysis of proteomics data before and after stimulation by thrombin. Results of this analysis showed us that there are some protein like CXCL7, CALX, GPIBB, FGG, GPIX will expressed more after activation.

There are some proteins that only observed after activation: ATP5A1, CD 47, PGRMC 1

(membrane association progesterone receptor), NNT (NADP transhydrogenase mitochondrial). There are proteins which their expressions reduced after activation as CLIC-

1 (choloride intracellular channel protein 1). Giving exact fold change which can help us to propose new target or validate good hits need repetition and new proteomics analysis.

Therefore repeating these analyses by different activator and different antiplatelet drugs would be a promising way to discover new molecules which play key role in platelet activation and coagulation.

7.4 VASP and lipid raft

Given all attention were received to our results on VASP in deifferent congresses, we decided to study the impact of ticagrelor, prasugrel and clopidogrel on localization and on interactive protein network of VASP and P2Y12 membrane’s lipid raft.

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7.5 Lipidomics and lipid raft modelisation

Lipidomics help us in this thesis in definition of lipid raft and there is still potential in our lipidomics results to be explored. Lipidomics is a very young branch of omics and especially in platelet. We have started collaboration with Prof. Christophe Ramseyer (Laboratoire

Chrono-environnement, UMR CNRS 6249, UBFC-Université Bourgogne Franche Comté) who is specialist in lipid domain modelisation and lipidomics analysis. Deepen our knowledge on lipid composition of lipid raft and modelisation virtually of these parts in platelet can improve pharmacological vision of these microdomains. These new knowledge and methods visualise these domains by softwares based on concentration and behaiviour of different type of lipids in lipid raft.

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