Étude du potentiel inflammatoire et immunitaire des vésicules

© Geneviève Marcoux, 2021

Étude du potentiel inflammatoire et immunitaire des vésicules extracellulaires dérivées des plaquettes

Thèse

Geneviève Marcoux

Doctorat en microbiologie-immunologie

Philosophiæ doctor (Ph. D.)

Québec, Canada

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Résumé

Les plaquettes sont très abondantes dans le sang où elles ont un rôle dans

l'hémostase, l’inflammation et l’immunité. Activées, elles vont subir un changement

de conformation qui permet la libération de nombreuses molécules effectrices ainsi

que la production de vésicules extracellulaires (EV). Les EV sont formées par le

bourgeonnement de la plaquette et emportent une partie de son contenu, incluant

des acides nucléiques, des protéines de surface et des organelles. Hétérogène, le

contenu diversifié des EV de plaquettes suggère qu’elles peuvent exercer de

nombreuses fonctions.

Dans le cadre de cette thèse, nous nous sommes d’abord intéressés à l’utilisation

de l’algorithme SPADE couplé à la cytométrie en flux pour améliorer la détection

d’EV et mieux apprécier leur hétérogénéité dans des concentrés plaquettaires (PC)

servant à la transfusion. Nous avons aussi évalué l’utilisation de cette approche pour

le développement de biomarqueurs dans le cadre de l’analyse d’EV dans le liquide

synovial de patients arthritiques. Cette étude a révélé que l’utilisation d’algorithmes

couplés à la cytométrie en flux tels que SPADE pourrait faciliter la compréhension

des fonctions des EV et le développement de leur étude comme biomarqueurs.

Nous nous sommes ensuite intéressés à une première sous-catégorie d’EV de

plaquettes, celles qui contiennent des mitochondries (mito+EV). Nous avons émis

l'hypothèse que ces mito+EV représentent un réservoir d'ADN mitochondrial, signal

de danger (motifs moléculaires associés aux dommages, DAMP) reconnu et présent

dans de nombreuses conditions inflammatoires, et qu’elles pourraient être

impliquées dans les réactions transfusionnelles. Nous avons observé que les

mito+EV étaient plus abondantes dans les PC impliqués dans des réactions

transfusionnelles et qu’elles corrèlent significativement avec l’ADN mitochondrial.

Comme la majorité de l’ADN mitochondrial est encapsulée dans des EV, cette étude

suggère que les EV peuvent être un biomarqueur utile pour la prédiction du risque

potentiel de réactions transfusionnelles, bien que des investigations soient

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nécessaires pour déterminer s'il existe un rôle pathogène causal du DAMP

mitochondrial encapsulé dans les EV par opposition à l'ADN mitochondrial en

solution.

Nous nous sommes enfin intéressés à une seconde sous-catégorie d’EV de

plaquettes, celles qui contiennent du protéasome. Les plaquettes contiennent un

protéasome actif et présentent des antigènes par l'intermédiaire du complexe majeur

d’histocompatibilité de classe I (CMH I) ce qui leur confère une fonction dans

l’immunité adaptative. Étant donné qu’il n’a jamais été examiné si le protéasome est

également transféré dans les EV de plaquettes auparavant, nous avons émis

l'hypothèse qu'une machinerie fonctionnelle pour l'apprêtement et la présentation de

l'antigène est transférée aux EV de plaquettes. En utilisant une combinaison

d'analyses moléculaires et fonctionnelles, nous avons montré la présence d'un

protéasome 20S actif dans diverses conditions où les plaquettes sont activées, ainsi

que du CMH I et des molécules de coactivation des lymphocytes. L’incubation d’EV

de plaquettes avec l’ovalbumine (OVA) a mis en évidence, par l'activation et la

prolifération des lymphocytes T CD8+ spécifiques de l'antigène OVA, qu’elles

peuvent apprêter et présenter efficacement l’antigène. Ces résultats suggèrent que

les EV de plaquettes contribuent à l'immunité adaptative.

Dans l’ensemble, nous avons montré que les EV de plaquettes ont un rôle dans

l’inflammation et l’immunité avec leur contenu en mitochondries et en protéasome.

Elles sont hétérogènes et peuvent être utilisées comme biomarqueurs dans

différents contextes.

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Abstract

Platelets are very abundant in the blood where they play a role in hemostasis,

inflammation and immunity. Activated, platelets will undergo a change of

conformation which allows the release of numerous effector molecules as well as

the production of extracellular vesicles (EVs). EVs are formed by the budding of the

platelet and bring some of its contents, including nucleic acids, surface proteins and

organelles. Heterogeneous, the diverse content of platelet EVs suggests that they

can perform many functions. As part of this thesis, we first looked at the use of the

SPADE algorithm coupled with flow cytometry to improve the detection of EVs and

allow a better appreciation of their heterogeneity in platelet concentrates (PC) used

for transfusion. We also evaluated the use of this approach for the development of

biomarkers in the analysis of EVs in the synovial fluid of arthritis patients. This study

revealed that the use of algorithms such as SPADE coupled with flow cytometry

could facilitate the understanding of the functions of EVs and the development of

their studies as biomarkers. We then looked at a first subcategory of platelet EV,

those that contain mitochondria (mito+EVs). We hypothesized that these mito+EVs

represent a reservoir of mitochondrial DNA, a damage-associated molecular pattern

(DAMP) recognized and present in many inflammatory conditions, and that they

could be involved in transfusion reactions. We observed that mito+EVs were more

abundant in PCs involved in transfusion reactions and that they correlate significantly

with mitochondrial DNA. As the majority of mitochondrial DNA is encapsulated in

EVs, this study suggests that EVs may be a useful biomarker for predicting the

potential risk of transfusion reactions, although further investigation is needed to

determine if there is a pathogenic role of mitochondrial DAMP encapsulated in EVs

as opposed to mitochondrial DNA in solution.

We finally focused on a second subcategory of platelet EVs, those that contain

proteasome. Platelets contain an active proteasome and present antigens through

the major histocompatibility complex I (MHC I), which gives them an important

function in adaptive immunity. Whether the proteasome is also transferred into the

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platelet EVs has never been examined. We hypothesized that a functioning

machinery for the processing and presentation of the antigen is transferred to the

platelet EVs. Using a combination of molecular and functional assays, we have

demonstrated the presence of an active 20 S proteasome under various conditions

where platelets are activated, as well as MHC I and lymphocyte coactivation

molecules. Demonstrated by activation and proliferation of ovalbumin (OVA) antigen

specific CD8 + T lymphocytes, EVs from platelets incubated with OVA can efficiently

prepare and present antigen. These results suggest that platelet EVs contribute to

adaptive immunity.

Overall, we have shown that platelet EVs have a role in inflammation and immunity

with their mitochondria and proteasome content. They are heterogeneous and can

be used as biomarkers in different contexts.

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Table des matières

Résumé ........................................................................................................................................ ii

Abstract ...................................................................................................................................... iv

Table des matières ................................................................................................................. vi

Liste des figures ..................................................................................................................... ix

Liste des tableaux .................................................................................................................. xi

Liste des abréviations ......................................................................................................... xii

Remerciements ..................................................................................................................... xvi

Avant-propos ........................................................................................................................ xvii

Introduction ............................................................................................................................... 1 1.1 Les plaquettes ................................................................................................................................. 1

1.1.1 Description générale ............................................................................................................................1 1.1.2 À l’origine des plaquettes : les mégacaryocytes ...................................................................3 1.1.3 Rôles des plaquettes dans l’hémostase ....................................................................................5

1.1.3.1 Coagulation ........................................................................................................................................................... 5 1.1.3.2 Transfusion de plaquettes .............................................................................................................................. 7 1.1.3.3 Transfusion de plaquettes : les risques associés .................................................................................. 8 1.1.3.4 Les risques infectieux ....................................................................................................................................... 8 1.1.3.5 Les risques non infectieux .............................................................................................................................. 9 1.1.3.6 Facteurs connus à ce jour ............................................................................................................................ 10

1.1.4 Rôles des plaquettes et des mégacaryocytes dans l’immunité .................................. 11 1.1.4.1 Notions d’immunologie ................................................................................................................................ 12 1.1.4.2 Les plaquettes dans l’inflammation et l’immunité innée .............................................................. 20 1.1.4.3 Les mégakaryocytes dans l’immunité innée ....................................................................................... 24 1.1.4.4 Support des cellules de l’immunité adaptative par les plaquettes ............................................ 25 1.1.4.5 Apprêtement et présentation de l'antigène par les plaquettes .................................................. 27 1.1.4.6 Apprêtement et présentation de l'antigène par les mégacaryocytes....................................... 31

1.2 Les vésicules extracellulaires ................................................................................................ 34 1.2.1 Description générale et mécanisme de formation ............................................................. 34 1.2.2 Isolation et détection des vésicules extracellulaires. ....................................................... 37 1.2.3 Diversité des vésicules extracellulaires .................................................................................. 38 1.2.4 Organelles contenues dans les vésicules extracellulaires ............................................ 39

1.2.4.1 La mitochondrie ............................................................................................................................................... 39 1.2.4.2 Le protéasome .................................................................................................................................................. 41

1.2.5 Les vésicules extracellulaires de plaquettes ........................................................................ 41 1.3 Objectifs ........................................................................................................................................... 43

Chapitre 1: Revealing the diversity of extracellular vesicles using high-dimensional flow cytometry analyses. ........................................................................ 45

2.1 Résumé ............................................................................................................................................ 45 2.2 Abstract ............................................................................................................................................ 47 2.3 Introduction .................................................................................................................................... 48 2.4 Methods ........................................................................................................................................... 51 2.5 Results .............................................................................................................................................. 55 2.6 Discussion ...................................................................................................................................... 63

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2.7 References ...................................................................................................................................... 66 2.8 Figures and legends ................................................................................................................... 72 2.8 Supplementary figures and legends ................................................................................... 79 2.9 Supplementary tables ................................................................................................................ 83

Chapitre 2: Platelet-derived extracellular vesicles convey mitochondrial DAMPs in platelet concentrates and their levels are associated with adverse reactions. .................................................................................................................................. 85

3.1 Résumé ............................................................................................................................................ 85 3.2 Abstract ........................................................................................................................................... 87 3.3 Introduction .................................................................................................................................... 88 3.4 Methods ........................................................................................................................................... 92 3.5 Results ............................................................................................................................................. 96 3.6 Discussion ................................................................................................................................... 100 3.7 References ................................................................................................................................... 104 3.8 Figures and legends ................................................................................................................ 111 3.9 Tables ............................................................................................................................................ 116 3.10 Supplementary methods ..................................................................................................... 120 3.11 Supplementary tables .......................................................................................................... 122 3.12 Supplementary references ................................................................................................. 129

Chapitre 3: Platelet-derived extracellular vesicles contain an active proteasome involved in protein processing for antigen presentation via class I major histocompatibility molecules ........................................................................ 130

4.1 Résumé ......................................................................................................................................... 130 4.2 Abstract ........................................................................................................................................ 133 4.3 Introduction ................................................................................................................................. 134 4.4 Methods ........................................................................................................................................ 136 4.5 Results .......................................................................................................................................... 138 4.6 Discussion ................................................................................................................................... 145 4.7 References ................................................................................................................................... 149 4.8 Figures and legends ................................................................................................................ 155 4.9 Supplementary methods ....................................................................................................... 166 4.10 Supplementary figures ........................................................................................................ 173 4.11 Supplementary references ................................................................................................. 175

Discussion ............................................................................................................................ 176 5.1 Mise en contexte ....................................................................................................................... 176 5.2 Résumé des découvertes et discussion ........................................................................ 177

Conclusion ............................................................................................................................ 185

Bibliographie ........................................................................................................................ 186

Annexe I: Mitochondrial damage-associated molecular patterns in blood transfusion products ........................................................................................................ 212

Abstract ................................................................................................................................................ 213 Mitochondria and inflammation ................................................................................................. 214 Mitochondrial release..................................................................................................................... 216 Extracellular mitochondria and adverse reactions ........................................................... 218 Extracellular mitochondria as a biomarker .......................................................................... 220 Summary ............................................................................................................................................. 221

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Acknowledgements ......................................................................................................................... 222 References .......................................................................................................................................... 223

Annexe II: Role of platelets and megakaryocytes in adaptive immunity .... 226 Abstract ................................................................................................................................................ 227 Introduction ........................................................................................................................................ 228 Platelet-leukocyte Interactions and Implications for Adaptive Immunity ................ 230 Antigen Processing and Presentation by Platelets........................................................... 232 Antigen Processing and Presentation by Megakaryocytes........................................... 236 Platelets Response to Antibodies ............................................................................................ 238 Conclusion and Perspectives ..................................................................................................... 245 References .......................................................................................................................................... 247

Annexe III: Platelets release pathogenic serotonin and return to circulation after immune complex-mediated sequestration ................................................... 256

Abstract ................................................................................................................................................ 258 Introduction ........................................................................................................................................ 259 Results .................................................................................................................................................. 261 Discussion .......................................................................................................................................... 278 Materials and Methods ................................................................................................................... 283 Acknowledgments ........................................................................................................................... 287 References .......................................................................................................................................... 288

Annexe IV: Autoantibodies in Systemic Lupus Erythematosus Target Mitochondrial RNA ............................................................................................................. 291

Abstract ................................................................................................................................................ 292 Introduction ........................................................................................................................................ 293 Materials and Methods ................................................................................................................... 297 Results .................................................................................................................................................. 303 Discussion .......................................................................................................................................... 313 References .......................................................................................................................................... 318

Annexe V: Anti-mitochondrial autoantibodies in systemic lupus erythematosus and their association with disease manifestations ............. 323

Abstract ................................................................................................................................................ 324 Introduction ........................................................................................................................................ 325 Results .................................................................................................................................................. 330 Discussion .......................................................................................................................................... 341 Material and Methods ..................................................................................................................... 345 Acknowledgements ......................................................................................................................... 357 References .......................................................................................................................................... 358

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Liste des figures

Introduction Figure 1: Cascade de coagulation .......................................................................... 6 Figure 2: Vue générale de la cascade du complément ........................................ 13 Figure 3: Les sites de liaison du CMH I au CD8 et du CMH II au CD4 ................. 15 Figure 4: Structure du protéasome et de l’immunoprotéasome ............................ 17 Figure 5: Apprêtement du peptide et présentation par le CMH I .......................... 19 Figure 6: Les plaquettes soutiennent les cellules de l’immunité adaptative et présentent l’antigène ............................................................................................. 31 Figure 7: Les mégacaryocytes sont des cellules immunitaires ............................. 33 Figure 8: Échelle de taille des vésicules extracellulaire ........................................ 35 Figure 9: DAMPs dérivés de la mitochondrie ....................................................... 40 Chapitre 1 Figure 1. Characterization of extracellular vesicles .............................................. 72 Figure 2. Detection of platelet EV subpopulations by hs-FCM ............................. 73 Figure 3. SPADE analysis of human blood cells and EVs .................................... 75 Figure 4. SPADE tree to assess EVs in cellular perturbations ............................. 76 Figure 5. SPADE overlapping panels for EV diversity in plasma .......................... 77 Figure 6. SPADE and EV-based biomarkers in disease ....................................... 78 Supplementary Figure 1. Detection of red blood cell subpopulations by hs-FCM ... .............................................................................................................................. 79 Supplementary Figure 2. Protein content in cells and EVs from plasma, platelets and RBCs .............................................................................................................. 81 Supplementary Figure 3. Initial gating before performing SPADE analysis ........ 82 Chapitre 2 Figure 1. Assessment of platelet EV subpopulation by high-sensitivity flow cytometry............................................................................................................. 111 Figure 2. Platelet EV subpopulation levels are higher in platelet concentrates involved in adverse transfusion reaction ............................................................. 113 Figure 3. The majority of the mitochondrial DNA in platelet concentrates is present in EVs .................................................................................................................. 114 Figure 4. Levels of soluble CD62P, but not soluble CD40L, correlate with mitochondria containing platelet EVs .................................................................. 115

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Chapitre 3 Figure 1. Platelets and PEVs contain proteasome .............................................. 155 Figure 2. Identification of proteasome-containing PEVs under physiological and pathological conditions ........................................................................................ 157 Figure 3. Platelets and PEVs load and process OVA onto MHC-I ...................... 158 Figure 4. PEVs in blood circulation can reach lymphoid organs and circulate in lymph ................................................................................................................... 159 Figure 5. Platelet and PEVs with loaded OVA peptide express activation and co-stimulatory molecules .......................................................................................... 161 Figure 6. PEVs can induce antigen-specific T cell activation and cytokine production through antigen presentation ............................................................................... 163 Figure 7. PEVs loaded with native OVA process and present OVA peptide to induce antigen-specific T cell lymphoproliferation ........................................................... 164 Supplementary Figure 1. Gate design for EV analysis ............................................ ............................................................................................................................ 173 Supplementary Figure 2. Characterization of proteasome PEV diversity using a fluorescent proteasomal activity-based probe ..................................................... 174

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Liste des tableaux

Chapitre 1 Supplementary Table 1. Staining panels for the different SPADE tree ............... 83 Supplementary Table 2. Demographic and clinical characteristics of RA patients .............................................................................................................................. 84 Chapitre 2 Table 1. Optimal cut-off values for EV subtypes as determined by Youden’s method ............................................................................................................................ 116 Table 2. EV subtype associations with soluble CD40L (n=92) and soluble CD62P (n=96) in platelet concentrates ............................................................................ 117 Table 3. Quantification of mitochondrial DNA, soluble CD40L and soluble CD62P in platelet concentrates ........................................................................................... 118 Table 4. Optimal cut-off values for sCD40L and sCD62P as determined by Youden’s method (Healthy donors: n=50, reaction n=48) ................................................... 119 Supplementary Table 1. Adverse transfusion reactions associated platelet concentrates........................................................................................................ 122 Supplementary Table 2. Qualitative information of the transfusion product ...... 123 Supplementary Table 3. Quantitative information on the donors and on the platelet concentrates........................................................................................................ 124 Supplementary Table 4. Quantification of EV subtypes in platelet concentrates ............................................................................................................................ 125 Supplementary Table 5. Cubic effect of EVs on adverse reaction .................... 126 Supplementary Table 6. Predictive values of EV subtypes adjusted for the different adverse reactions ................................................................................................ 127 Supplementary Table 7. EV subtype associations with mitochondrial DNA in platelet concentrates (n= 35) ............................................................................... 128

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Liste des abréviations

ACD (Acid-citrate-dextrose)

ADN Acide désoxyribonucléique

ADP Adénosine diphosphate

AHTR Réaction hémolytique aiguë (Acute Hemolytic Transfusion Reaction)

APC Cellules présentatrice d’antigène (Antigen presenting cells)

ARN Acide ribonucléique

ATP Adénosine triphosphate

β2-MG Microglobuline β2

BAL (Bronchoalveolar lavages)

BC Couche leucoplaquettaire (Buffy-Coat)

BCR Récepteur des cellules B (B cell receptor)

CAP (Carboxy(alkylpyrrole) protein adducts)

CD40L CD40 Ligand

CD62P Sélectine P

CLR Récepteurs lectine membranaire de type C (C-type Lectin Receptor)

CMFDA (Chloromethylfluorescein diacetate)

CMH Complexe majeur d’histocompatibilité

CPS-I Carbamoyl-phosphate synthétase I

CRP-XL (Cross-linked collagen-related peptide)

DAMPs Motifs moléculaires associés aux dommages (Damage-Associated

Molecular Patterns)

DC Cellules dendritiques (Dendritic cells)

DHTR Réaction hémolytique retardée (Delayed Hemolytic Transfusion

Reaction)

ERAAP (Endoplasmic reticulum amino peptidase)

ESCRT Complexe de tri endosomal nécessaire au transport (Endosomal

Sorting Complex Required for Transport)

EV Vésicule extracellulaire (Extracellular Vesicle)

FCM (Flow cytometry)

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FNHTR Réaction fébrile non-hémolytique (Febrile Non-Hemolytic Transfusion

Reaction)

GPVI Glycoprotéine VI

HBSS (Hanks' Balanced Salt Solution)

HLA Antigènes leucocytaires humains (Human Leukocyte Antigen)

HMGB1 (High-mobility group box 1)

hs-FCM (high-sensitivity FCM)

HSP 70 (Heat shock protein 70)

IFN Interféron

Ig Immunoglobuline

IL Interleukine

ITP Thrombocytopénie immunitaire (Immune thrombocytopenia)

LPS Lipopolysaccharide

LBP Protéine liant le LPS (LPS binding protein)

Mac-1 lntégrine CD11b/CD18 (Macrophage-1 antigen)

MD-2 (Myeloid differentiation factor 2)

MIP (Macrophage Inflammatory Protein)

miRNA micro ARN

MK Mégacaryocytes (Megakaryocytes)

mRNA ARN messager

mtDNA ADN mitochondrial

MV Microvésicule

NET (Neutrophil extracellular traps)

NK Cellules tueuses naturelles (Natural killers)

NOD Nucleotide-binding Oligomerization Domain

OCS Système canaliculaire ouvert (Open Canalicular System)

ODN Oligodésoxyribonucléotides

OVA Ovalbumine

PAMP Motifs moléculaires associés aux pathogènes (Pathogen-associated

molecular patterns)

PBS (Phosphate buffered saline)

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PC Concentrés plaquettaires (Platelet Concentrates)

PDGF (Platelet Derived Growth Factor)

PEV Vésicules extracellulaires de plaquettes (platelet-derived EV)

PF4 Facteur plaquettaire 4 (Platelet factor 4)

PLC Complexe chargeant le peptide (Peptide Loading Complex)

PMA (Phorbol myristate acetate)

PRP Plasma riche en plaquettes

PS Phosphatidylsérine

PSGL1 Ligand-1 de la glycoprotéine CD62P

PVDF (Polyvinylidene difluoride)

RANTES (Regulated on Activation, Normal T Cell Expressed and Secreted)

ROS Espèces réactives d’oxygène (Reactive oxygen species)

sCD40L CD40 Ligand soluble

SLC44A2 (Solute carrier family 44 member 2)

SLE Lupus érythémateux disséminé (Systemic Lupus Erythematosus)

SPADE (Spanning-tree Progression Analysis of Density-normalized Events)

TACO Surcharge circulatoire liée à la transfusion (Transfusion Associated

Circulatory Overload)

TA-GVHD Réaction du greffon contre l’hôte (Transfusion-Associated Graft-

Versus-Host Disease)

TAP Protéines de transport associées à l’antigène (Transporters

associated with Antigen Processing)

TCR Récepteur des cellules T (T cell receptor)

TEM (Transmission Electron Microscopy)

TF Facteur tissulaire (Tissue Factor)

TGF (Transforming growth factor)

TLR Récepteurs de type Toll (Toll-like receptors)

TRALI Syndrome respiratoire aigu post-transfusionnel (Transfusion-Related

Acute Lung Injury)

Tregs Lymphocytes T régulateurs

TNF Facteur de nécrose tumorale (Tumor necrosis factor)

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VIH Virus de l’immunodéficience humaine

VHB Virus de l’hépatite B

VHC Virus de l’hépatite C

vWf Facteur von Willebrand

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Remerciements

Je tiens d'abord à remercier tout particulièrement le Dr Éric Boilard pour son

encadrement lors des sept dernières années. Merci de m’avoir encouragée à faire

une thèse à la suite de ma maitrise sur un sujet qui me passionne, pour la confiance

témoignée tout au long de mes études et pour m’avoir donné la liberté et l’autonomie

dont j’avais besoin. Merci aussi pour les multiples occasions de formations, congrès

et activités auxquelles j’ai pu assister sous sa supervision, ainsi que pour les

nombreuses activités d’équipe organisées sous son initiative.

Je remercie aussi le Dr Benoit Vingert et Marie Tamagne de m’avoir accueillie dans

leur laboratoire et de m’avoir fait une place dans leur famille. Les quelques mois

passés avec eux à Paris ont été exceptionnels et m’ont permis d’évoluer au sein

d’une dynamique de laboratoire complètement différente et de bénéficier de leur

expérience sur de nouvelles techniques et de nouvelles idées. J'aimerais également

remercier Tania Lévesque, une personne et une collègue exceptionnelle qui est

maintenant devenue une amie. J’aimerais aussi souligner Stephan, Anne, Yann,

Audrée, Julien, Andréa, Étienne, Jonathan, Anne-Claire et Vanessa sans qui la vie

au laboratoire n’aurait pas été aussi agréable. J'aimerais exprimer toute ma

reconnaissance à Isabelle Allaeys, Nathalie Cloutier et Emmanuelle Rollet-Labelle

pour leur encadrement et leur aide, ainsi que tous les autres membres de l’équipe

Boilard. Ils ont été une source importante de conseils et d'informations et des gens

avec qui il est agréable de travailler. J’inclus aussi tous les chercheurs, assistants

de recherche et étudiants de l’étage, ainsi que les membres du comité de

programme. Je remercie également la Société Canadienne du Sang, Mitacs et les

autres organismes ayant financé le projet.

Enfin, je souhaite exprimer toute ma gratitude à mes proches pour leur appui et pour

m’avoir toujours encouragé dans la poursuite de mes études. Merci aussi à mon

petit chat. Ton amour, ta confiance en moi et ton soutien m'ont permis de persévérer

et de surpasser mes objectifs personnels et professionnels.

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Avant-propos

Le Dr Éric Boilard a conçu et dirigé le projet de recherche. Il a participé à l’analyse

des données et corrigé les articles des chapitres 1, 2 et 3. Le Dr Benoit Vingert a

codirigé une partie du projet mentionné au chapitre 3 de cette thèse.

J’ai conçu et réalisé les expériences, analysé et interprété les données, réalisé les

analyses statistiques et écrit les manuscrits des articles présentés aux chapitre 2 et

4 de ce document en collaboration avec les auteurs mentionnés ci-dessous.

Concernant l’article présent au chapitre 3, j’ai participé principalement à la

conception, l’analyse et l’interprétation des expériences pour les figures 1 et 2 de

l’article et pour la rédaction du manuscrit.

L’article qui constitue le chapitre 1, intitulé Revealing the diversity of extracellular

vesicles using high-dimensional flow cytometry analyses a été publié dans le

journal Scientific Reports en 2016 :

Marcoux, G., Duchez, A. C., Cloutier, N., Provost, P., Nigrovic, P. A., Boilard, E. (2016). Revealing the diversity of extracellular vesicles using high-dimensional flow cytometry analyses. Scientific Reports. 6:35928.

L’article qui constitue le chapitre 2, intitulé Platelet-derived extracellular vesicles

convey mitochondrial DAMPs in platelet concentrates and their levels are

associated with adverse reactions a été publié dans le journal Transfusion en

2019 :

Marcoux G, Magron A, Sut C, Laroche A, Laradi S, Hamzeh-Cognasse H, Allaeys I, Cabon O, Julien AS, Garraud O, Cognasse F, Boilard E. (2019). Platelet-derived extracellular vesicles convey mitochondrial DAMPs in platelet concentrates and their levels are associated with adverse reactions. Transfusion. Apr 11. doi: 10.1111/trf.15300.

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L’article qui constitue le chapitre 3, intitulé Platelet-derived extracellular vesicles

contain an active proteasome involved in protein processing for antigen

presentation via class I major histocompatibility molecules, est présentement

en révision pour le journal Blood (BLD-2020-009957):

Marcoux, G. Laroche, A., Hasse, S., Tamagne, M., Zufferey, A., Lévesque,T., Allaeys, I., Rebetz,J. Karakeussian-Rimbaud, A., Turgeon, J., Bourgoin,S.G., Hamzeh-Cognasse, H., Cognasse, F., Kapur, R., Semple, J.W., Hébert, M.J., Pirenne, F., Overkleeft, H.S., Florea, B.I., Dieude, M., Vingert, B. and Boilard, E. (2021) Platelet-derived extracellular vesicles contain an active proteasome involved in protein processing for antigen presentation via class I major histocompatibility molecules. Blood (BLD-2020-009957)

Au cours de mon doctorat, j’ai collaboré à la rédaction de deux revues de littérature.

La première qui est intitulée Mitochondrial damage-associated molecular

patterns in blood transfusion products est présente en Annexe I :

Marcoux, G. and Boilard, E. (2017). Mitochondrial damage-associated molecular patterns in blood transfusion products. ISBT Science Series. 12(4): 501-505. La seconde, intitulée Role of platelets and megakaryocytes in adaptive immunity, a été écrite en parallèle avec l’introduction de cette thèse, est présente en Annexe II et vient d’être publiée dans le journal Platelets : Marcoux, G., Laroche, A., Romero, J.E. and Boilard, E. (2020) Role of platelets and megakaryocytes in adaptive immunity. Platelets 2020: p. 1-12. doi: 10.1080/09537104.2020.1786043

J’ai aussi collaboré significativement à différents projets qui n’apparaissent pas dans

cette thèse. Parmi ceux qui ont été publiés, j’ai notamment contribué pour le modèle

LPS et l’imagerie en microscopie deux photons dans cet article en Annexe III qui

s’est mérité le prix PNAS Cozzarelli Prize 2018:

Cloutier N, Allaeys I, Marcoux G, Machlus KR, Mailhot B, Zufferey A, Levesque T, Becker Y, Tessandier N, Melki I, Zhi H, Poirier G, Rondina MT, Italiano JE, Flamand L, McKenzie SE, Cote F, Nieswandt B, Khan WI, Flick MJ, Newman, PJ, Lacroix S, Fortin P, Boilard E. (2018). Platelets release pathogenic serotonin and return to

xix

circulation after immune complex-mediated sequestration. Proc Natl Acad Sci USA.115(7): 1550-1559.

J’ai aussi participé au projet sur l’étude des anticorps antimitochondriaux qui a mené

jusqu’à ce jour à la publication de deux articles en Annexes IV et V :

Becker Y, Marcoux G, Allaeys I, Julien A-S, Loignon R-C, Benk-Fortin H, Rollet-Labelle E, Rauch J, Fortin PR and Boilard E (2019). Autoantibodies in Systemic Lupus Erythematosus Target Mitochondrial RNA. Front. Immunol. 10:1026. doi: 10.3389/fimmu.2019.01026

Becker Y, Loignon RC, Julien AS, Marcoux G, Allaeys I, Lévesque T, Rollet-Labelle E, Benk-Fortin H, Cloutier N, Melki I, Eder L, Wagner É, Pelletier M, Hajj HE, Tremblay MÈ, Belleannée C, Hébert MJ, Dieudé M, Rauch J, Fortin PR, Boilard E. (2019). Anti-mitochondrial autoantibodies in systemic lupus erythematosus and their association with disease manifestations. Sci Rep. Mar 14;9(1):4530.

Enfin, j’ai aussi contribué à ces articles publiés depuis mon arrivée dans le

laboratoire du Dr Boilard :

Boudreau,L.H., Duchez,A.C., Cloutier,N., Soulet,D., Martin,N. Bollinger,J., Pare,A., Rousseau,M., Naika,G.S., Lévesque,T., Laflamme,C., Marcoux, G., Lambeau,G., Farndale,R.W., Pouliot,M., Hamzeh-Cognasse,H., Cognasse,F., Garraud,O., Nigrovic,P.A., Guderley,H., Lacroix,S., Thibault,L., Semple,J.W., Gelb,M.H. and Boilard,E (2014) Platelets release mitochondria serving as substrate for bactericidal group IIA-secreted phospholipase A2 to promote inflammation, Blood : 2014 Oct 2;124(14):2173-83. doi: 10.1182/blood-2014-05-573543. Marcoux, G., Duchez,A.C.,Rousseau,M., Lévesque,T., Boudreau,L.H., Thibault, L. andBoilard,E. (2016): Microparticle and mitochondrial release during extended storage of different types of platelet concentrates, Platelets, DOI: 10.1080/09537104.2016.1218455 Boudreau, L.H., G. Marcoux and E. Boilard, Platelet microparticles in transfusion

(2015). Vox Sanguinis, ISBT Science Series, 10: 305–308. doi: 10.1111/voxs.12142

1

Introduction

1.1 Les plaquettes

Giulio Bizzozero a décrit en 1882 un nouvel élément du sang ayant un rôle important

pour la thrombose et la coagulation. Maintenant connues sous le nom de

plaquettes[1], ces dernières circulent dans le sang pour une période d’environ 8 à

10 jours afin de détecter les vaisseaux endommagés[2, 3]. Il s’est écoulé près de

trente ans avant que James Homer Wright fasse la démonstration en 1910 que les

plaquettes sont dérivées des mégacaryocytes (MK-Megakaryocytes) de la moelle

osseuse[4, 5].

1.1.1 Description générale

Chez les mammifères, ces fragments anucléés de petite taille (environ 2 µm de

diamètre) sont rarement reconnus comme étant des cellules. Ne possédant pas de

noyau ni d’ADN génomique, les plaquettes héritent toutefois de l’ARN messager, de

microARN, de fragments de Golgi et de la machinerie nécessaire pour la traduction

de leurs précurseurs, ce qui leur confère la possibilité de synthétiser des

protéines[6]. De plus, le cytoplasme et des organelles telles que les granules ou les

mitochondries qui sont contenus dans la plaquette proviennent aussi des MK[6].

La membrane plasmique de la plaquette est constituée d’une bicouche de

phospholipides et possède un glycocalix qui est recouvert de glycolipides et de

glycoprotéines permettant l’interaction des plaquettes entre elles, avec les autres

cellules ou avec le milieu qui les entourent[7, 8]. Les plaquettes non activées sont

généralement lisses, mais possèdent des invaginations qui déterminent les entrées

du système canaliculaire ouvert (OCS-Open Canalicular System)[2]. Ce système

constitue une source importante de membrane mobilisable lors du changement de

conformation des plaquettes après leur activation[9] et permet l’importation ou la

sécrétion de protéines et d’autres molécules[2].

2

Le cytoplasme de plaquettes contient différents types de granules sécrétoires, dont

les granules alpha, les granules T, les granules denses, les peroxysomes et les

lysosomes. Les molécules contenues dans ces granules dérivent des MK, ou bien

sont incorporées par endocytose à partir du plasma[10]. La libération de granules

par les plaquettes est centrale pour assurer leurs diverses fonctions, que ce soit

pour l’adhésion, l’activation, l’agrégation ou la sécrétion de molécules anti-

inflammatoires et antimicrobiennes[11, 12].

Les granules alpha sont les plus abondantes[13] comptant en moyenne 50 à 80

granules par plaquettes[14]. D’une taille de 200 à 500 nm, ces granules

correspondent environ à 10% du volume de la plaquette. La surface membranaire

qui entoure les granules est équivalente à celle rendue disponible par l’OCS, ce qui

en fait aussi un réservoir important[14]. Combinées, la membrane plasmique des

granules alpha et celle de l’OCS permettent à la plaquette de multiplier de 2 à 4 fois

sa surface, lorsqu’activée[10]. Les granules alpha renferment plus de 300 protéines

dont des chimiokines (interleukine (IL)-8/CXCL8, Platelet Factor 4-PF4/CXCL4,

Regulated on Activation, Normal T Cell Expressed and Secreted-RANTES/CCL5),

des précurseurs du complément, des facteurs de coagulation, des protéines

d’adhésion et des intégrines (incluant la glycoprotéine VI (GPVI), αIIb, β3 et la

sélectine P (CD62P)), des facteurs de croissance et le complexe majeur

d’histocompatibilité (CMH) de classe I[10]. Des études ont montré que le cargo des

granules alpha est hétérogène, indiquant l’existence de sous-populations[15] dont

la libération pourrait être affectée par la force et la nature des agonistes utilisés pour

stimuler les plaquettes[16]. Les granules denses contiennent de petites molécules

comme le calcium, l’ADP (adénosine diphosphate) et l’ATP (adénosine

triphosphate), qui confèrent une apparence opaque en microscopie[6] ainsi que des

molécules telles que la sérotonine et l’histamine[11]. Des peroxysomes et des

lysosomes sont aussi présents dans le cytoplasme des plaquettes[17]. Ces derniers

libèrent des hydrolases acides dans l’environnement plaquettaire qui participent au

remodelage des thrombus et à la réponse antimicrobienne[16]. Les granules T,

3

identifiées récemment, ne contiennent pas de marqueurs typiques des autres types

de granules, mais contiennent des protéines disulfures isomérases qui catalysent le

repliement correct des peptides et le récepteur de type Toll (TLR/Toll-Like

Receptors) 9[18].

Le cytosquelette de la plaquette est constitué de trois composantes majeures, soit

la spectrine, l’actine et les microtubules, nécessaires pour le remodelage de la

plaquette et la libération de son contenu. Lorsque la plaquette est activée, elle subit

un changement de conformation important[19]. Ce processus est initié par un influx

de calcium[2] et implique le cytosquelette de la plaquette[19]. La contribution

spécifique de ces composantes a été démontrée en utilisant des molécules telles

que les cytochalasines B, D, E et le latrunculin A qui inhibent la polymérisation de

l’actine ou bien le nocodazole qui dépolymérise les microtubules[20, 21].

Même si les plaquettes ne sont pas considérées comme des cellules, elles partagent

de nombreuses caractéristiques communes. Elles possèdent des récepteurs

diversifiés lui permettant de répondre à de nombreux stimuli. Elles ont un

cytosquelette capable de se modifier rapidement lors de l’activation et des granules

sécrétoires contenant un grand éventail de molécules pouvant affecter leur

environnement. Bien qu’elles soient principalement reconnues pour leur rôle

physiologique primaire, soit l’initiation de la coagulation et la formation de thrombus

pour la prévention des saignements[22], la contribution des plaquettes dans

l’immunité innée et adaptative est de plus en plus reconnue. En effet, elles peuvent

reconnaitre et distinguer différents types de dangers (soi, non-soi, pathogènes) et

ajuster leurs réponses de façon appropriée[23].

1.1.2 À l’origine des plaquettes : les mégacaryocytes

Environ 100 milliards de plaquettes doivent être générées de façon quotidienne, par

le processus de thrombocytopoiëse afin de maintenir un compte plaquettaire normal

(150-400 x 109/litre de sang). Cette production peut être augmentée en cas de

baisse subite du compte plaquettaire, ce qui suggère une homéostasie réactive[24].

Un MK peut à lui seul libérer des milliers de plaquettes[25, 26].

4

Les MK sont de grandes cellules hétérogènes (50 à 100 µm) avec un noyau pouvant

contenir plusieurs copies de chaque chromosome (jusqu'à 128N)[27]. Leur fonction

principale est de produire et de libérer des plaquettes dans la circulation[28]. La

mégacaryocytopoïèse, qui est la production de MK dans la moelle osseuse, est

contrôlée par un processus complexe régulé principalement par la

thrombopoïétine[29]. Cette hormone est produite par le foie[30, 31] et son niveau

est inversement proportionnel au taux de plaquettes produites[32]. Sous l’action de

la thrombopoïétine et diverses autres cytokines, les cellules souches

hématopoïétiques vont se différentier lors de différents stades de maturation, soit le

progéniteur commun myéloïde, puis le progéniteur mégacaryocyte/érythrocyte pour

devenir finalement progéniteur mégacaryocytaire. C’est lors de ces étapes de

maturation que le MK va, par le processus d’endomitose[33], devenir une cellule

polyploïde ce qui permet l’augmentation de la synthèse protéique[34, 35]. La

formation d’un réseau de membranes de démarcation, l’augmentation du volume du

cytoplasme, la production de granules sécrétoires et l’expression des protéines

plaquettaires font aussi partie du processus de maturation et permettront aux

précurseurs mégacaryocytaires d’effectuer la formation des proplaquettes[36].

Un réarrangement du cytosquelette et du cytoplasme de façon à former une

succession d’extensions reliées par de ponts cytoplasmiques permet la formation

des proplaquettes[37, 38]. Ces proplaquettes, ressemblant à un collier de perles,

vont être produites jusqu’à l’utilisation complète du cytoplasme et des membranes

du MK. C’est aussi lors de ce processus que le contenu des MK incluant les

organelles est transféré aux proplaquettes[39-41]. Insérées dans les jonctions de la

paroi des vaisseaux sanguins, ces proplaquettes sont ensuite fragmentées et les

plaquettes individuelles sont libérées directement dans le courant sanguin où elles

pourront exercer leurs fonctions dans l’hémostase et dans l’immunité[42, 43].

5

1.1.3 Rôles des plaquettes dans l’hémostase

1.1.3.1 Coagulation

L’hémostase se définit comme l’arrêt de l'écoulement du sang, spontané ou

provoqué par différents moyens médicaux ou chirurgicaux. Les plaquettes et les

facteurs de coagulation permettent la formation spontanée d’un caillot et ont donc

un rôle majeur dans l’hémostase (Figure 1). À l’aide de leurs récepteurs de surface

pour le collagène sous-endothélial et le facteur von Willebrand (vWf) lié au

collagène[44], les plaquettes vont pouvoir s’activer, adhérer et agréger au site de

lésion vasculaire pour former un caillot. Étant donné la perte de l’asymétrie

membranaire, ces plaquettes activées exposent alors la phosphatidylsérine (PS) à

leur surface qui fournit un échafaudage aux complexes enzymatiques de

coagulation[45]. En parallèle, les cellules endothéliales abimées vont exposer à leur

surface le facteur tissulaire (TF-tissue factor)[44]. Le TF est ciblé par le facteur de

coagulation VII circulant dans le plasma, qui sera converti à sa forme activée

VIIa[44]. La liaison du facteur de coagulation VIIa au TF induit une cascade de

réactions impliquant les facteurs de coagulation présents dans le sang, ce qui

conduit à la génération de thrombine (voie extrinsèque)[44]. Les facteurs de

coagulation sont des protéines présentes dans le plasma sous forme de proenzymes

(zymogènes) qui doivent être clivées pour activer à leur tour la proenzyme suivante.

La thrombine va ensuite activer des plaquettes supplémentaires et permettre la

production de fibrine, tout en jouant un rôle crucial dans les phases d'amplification

et de propagation de la coagulation par l’activation des facteurs de coagulation V,

VIII et XI (voie intrinsèque), créant une boucle d’autoamplification de la génération

de thrombine. Le facteur XIII permet ensuite la formation d’un réseau de fibres de

fibrines, nécessaire pour la stabilisation des caillots[46].

6

Figure 1: Cascade de coagulation

La cascade de coagulation est composée de protéases qui sont activées par clivage

par une enzyme en amont. Les zymogènes sont marqués en orange et les

composants actifs sont indiqués en bleu et le TF en vert. Le TF exprimé sur diverses

cellules abimées initie la voie extrinsèque qui se poursuit jusqu’à la formation de

thrombine. La thrombine nouvellement formée propage la coagulation par

l’activation des facteurs de coagulation V, VIII et XI (voie intrinsèque). Cela conduit

à une augmentation de la génération de thrombine, ce qui est essentiel pour la

formation de fibrine. Le facteur XIII permet ensuite la formation de filaments de

fibrines, nécessaire pour la stabilisation des caillots. (Figure créée à l’aide de

BioRender)

7

1.1.3.2 Transfusion de plaquettes

La transfusion est une procédure médicale courante qui a pour but de substituer les

éléments du sang manquants à la suite d’une hémorragie, d’une maladie ou d’un

traitement[47-49]. La transfusion de plaquettes est utilisée plus spécifiquement pour

traiter ou prévenir les saignements en cas de thrombocytopénie ou de plaquettes

défectueuses[50]. La seule source de plaquettes viables, avant le début des années

1970, provenait de sang total frais[51]. Avec l’avancement de différentes

technologies, il est maintenant possible d’isoler les plaquettes sous forme de

concentrés plaquettaires (PC-platelet concentrate), facilitant ainsi la thérapie

transfusionnelle[52]. Ceux-ci sont préparés à partir du sang total par centrifugation

selon deux techniques distinctes par les vitesses de centrifugation, qui permettent

d’obtenir soit le plasma riche en plaquettes (PRP) ou bien la couche

leucoplaquettaire (BC-Buffy-Coat)[52-54]. Les leucocytes et les érythrocytes

résiduels sont éliminés par filtration ou centrifugation et les plaquettes sont remises

en suspension dans du plasma. Les PC peuvent aussi être préparés par aphérèse.

C’est le processus lors duquel le sang d’un donneur est mis en circulation en

système fermé à l’aide d’un cathéter dans l’appareil d’aphérèse. Les plaquettes sont

séparées des autres cellules par centrifugation afin d’être conservées, alors que les

autres composants du sang retournent au donneur par un second cathéter[55, 56].

L’aphérèse permet d’obtenir de plus grande quantité de plaquettes qu’avec un don

de sang total. La réduction du nombre de donneurs nécessaire avec la technique

d’aphérèse a l’avantage de diminuer le risque d’allo-immunisation et de transmission

de maladies au patient en comparaison des techniques de dons de sang total[57].

Outre le procédé de fabrication, de nombreux facteurs affectent la qualité des PC.

Le respect d’une période de repos avant de resuspendre les PC est important afin

de diminuer le niveau d’activation des plaquettes et d’améliorer leur morphologie[58-

62]. Les conditions d’entreposage, incluant la température, la durée et le type

d’agitation utilisé[63-71], la nature du dispositif contenant le PC[72-74] ainsi que

l’utilisation ou non d’une solution d’entreposage peuvent affecter grandement les

plaquettes[75-77].

8

Même sous des conditions optimales d’entreposage, des changements

morphologiques, structuraux et fonctionnels des plaquettes sont inévitables. Ces

altérations sont nommées lésions d’entreposage des plaquettes et sont la cause

d’une diminution progressive de la survie post-transfusion et des fonctions

hémostatiques des plaquettes[78]. Ces altérations incluent le changement des

protéines de surface des plaquettes[79-81], et la perte de la forme discoïde à la suite

d’un réarrangement du cytosquelette[82]. L’activation des plaquettes et leur

dégranulation lors de l’entreposage entrainent aussi la présence à leur surface de

CD62P et de PS[83] et l’accumulation de molécules bioactives[84]. L’entreposage

des PC entraine aussi la libération de vésicules extracellulaires (EV-extracellular

vesicle). Une section y sera consacrée.

1.1.3.3 Transfusion de plaquettes : les risques associés

Comme toute procédure médicale, les transfusions de produits sanguins présentent

certains risques pour les patients. En effet, cette procédure médicale peut mener à

la transmission de maladies infectieuses ou à des réactions transfusionnelles graves

pour le receveur. Les transfusions de plaquettes sont moins fréquentes que la

transfusion d’autres produits sanguins, mais présentent un risque supérieur[85].

1.1.3.4 Les risques infectieux

Que ce soit parce que le sang du donneur est contaminé, qu’un élément de la flore

bactérienne est introduit dans le composant sanguin lors du prélèvement ou qu’une

contamination survient lors de la préparation[86], la transfusion présente encore

aujourd’hui un risque infectieux. Le scandale du sang contaminé dans les années

1980, où la principale préoccupation concernait la transmission d’infections

virales[87], notamment du virus de l’immunodéficience humaine (VIH), de l’hépatite

B ou C (VHB ou VHC) a forcé l’instauration de mesures visant à prévenir la

transmission de maladies. L’application stricte de critères pour la détermination

d’éligibilité au don, incluant l’exclusion des pratiques sexuelles à risques, ont permis

une diminution nette de la transmission du VIH et de l’hépatite[88, 89]. Les critères

adressant les voyages à l’étranger ont aussi permis de limiter les risques de

contracter la malaria ou la maladie de Creutzfeldt-Jacob et sa variante. Une

9

sélection restrictive des donneurs de sang et l’utilisation de donneurs non rémunérés

permettent aussi de réduire les risques infectieux[90-92].

Depuis les années 1990, les efforts se sont davantage concentrés sur la réduction

de l’incidence de la contamination microbienne des produits sanguins,

principalement pour les PC qui sont conservés à température ambiante[87]. Des

procédures simples, comme la désinfection efficace de la peau au site de

prélèvement, permettent une réduction des bactéries de la flore normale jusqu’à

99%[93]. De plus, la méthode de diversion des premiers millilitres de sang a été

instaurée afin d’éviter la contamination causée par la carotte de peau pouvant se

retrouver dans 65% des cas dans l’aiguille lors de la phlébotomie[94]. Ces premiers

millilitres de sang, utilisés pour les tests de dépistage, se retrouvent maintenant dans

une poche annexe pour prévenir la contamination par la flore du donneur[95], ce qui

s’est avéré efficace pour réduire la contamination des produits sanguins[96-98].

L’introduction de nouvelles technologies pour détecter, réduire ou prévenir la

contamination qui sont maintenant appliquées couramment ont aussi permis la

réduction de ces risques infectieux[99-104].

1.1.3.5 Les risques non infectieux

L’implantation de ces nombreuses mesures préventives a mis de l’avant

l’importance des risques transfusionnels non infectieux.[105] Ceux-ci incluent la

réaction hémolytique aiguë (AHTR-Acute Hemolytic Transfusion Reaction) ou

retardée (DHTR-Delayed Hemolytic Transfusion Reaction) qui, en résultat d’une

incompatibilité entre les anticorps du donneur et les globules rouges du receveur,

entraine une destruction des globules rouges. Elle est considérée aiguë (AHTR)

quand les symptômes surviennent en moins de 24 heures suivant la transfusion ou

retardée (DHTR) s’ils surviennent entre 24 heures et trois semaines post-

transfusion[106]. Des réactions allergiques mineures, telles qu’une réaction

cutanée, ou majeures (anaphylactique) peuvent aussi être observées post-

transfusion[106]. Le mécanisme mis en cause dans ce type de réaction est une

hypersensibilité de type I due à la transfusion d’immunoglobulines (Ig) E présentes

dans le plasma[107].

10

Une surcharge circulatoire liée à la transfusion (TACO-Transfusion Associated

Circulatory Overload) peut se produire dans le cas de transfusion massive. Le cœur

étant incapable de pomper adéquatement un grand volume de produits sanguins, il

en résultera une insuffisance cardiaque et un oedème pulmonaire aigu[108]. La

thrombocytopénie immunitaire (ITP-Immune thrombocytopenia) est caractérisée par

une destruction des plaquettes du donneur et du receveur menant à une

thrombocytopénie sévère qui survient de 5 à 10 jours après la transfusion et entraine

des hémorragies pouvant être mortelles[106, 109]. Le mécanisme de destruction

des plaquettes reste inconnu, mais des antigènes plaquettaires absents des

plaquettes du receveur et présents chez le donneur semblent être en cause[109,

110]. Une réaction fébrile non hémolytique (FNHTR-Febrile Non-Hemolytic

Transfusion Reaction) est caractérisée par une élévation de température égale ou

supérieure à 1°C qui ne peut être reliée à la condition du patient ou à un autre type

de réaction transfusionnelle[106]. Une FNHTR peut être causée par plusieurs

facteurs et il existe une corrélation linéaire entre les niveaux de cytokines, la quantité

de leucocytes et la durée d’entreposage des PC conservés à 22°C[111, 112].

La réaction du greffon contre l’hôte (TA-GVHD-Transfusion-Associated Graft-

Versus-Host Disease), qui s’avère fatale dans 90% des cas, est causée par une

destruction des cellules du receveur par les lymphocytes du donneur, en cas de

différence des antigènes leucocytaires[106, 113]. Enfin, le syndrome respiratoire

aigu post-transfusionnel (TRALI-Transfusion-Related Acute Lung Injury) est

caractérisé par une détresse respiratoire aiguë, un œdème pulmonaire bilatéral et

une hypoxémie se produisant généralement dans les 2 heures suivant la

transfusion[106, 113]. Cette réaction, peu fréquente et encore mal comprise,

s’expliquerait par l’hypothèse du « Two-hit », où l’implication d’un anticorps ou d’un

médiateur soluble combiné à la condition clinique du receveur sont nécessaires pour

son développement[114, 115].

1.1.3.6 Facteurs connus à ce jour

Les réactions allergiques sont causées par des protéines plasmatiques comme l’IgA,

11

l’IgE et l’haptoglobine ainsi que certains allergènes chimiques ou alimentaires

présents dans le produit sanguin[85, 107, 116, 117]. Différents lipides bioactifs

relargués par les macrophages, les basophiles et les plaquettes, tels que certaines

lysophosphatidylcholines augmentent lors de l’entreposage des PC[118] et peuvent

activer les neutrophiles[119, 120]. Il en est de même pour de nombreuses cytokines

incluant l’IL-1α, l’IL-1β, l’IL-2, l’IL-6, IL-8/CXCL8, le Tumor Necrosis Factor (TNF),

l’interféron (IFN)-α, l’IFN-γ, le PF4/CXCL4, la β-thromboglobuline (β-TG),

RANTES/CCL5, le Macrophage Inflammatory Protein (MIP)-1α/CCL3, le

Transforming Growth Factor (TGF)-β et le Platelet Derived Growth Factor

(PDGF)[84, 111, 112, 121-129]. Le CD40 ligand (CD40L), aussi connu sous le nom

de CD154, est un médiateur pro-inflammatoire qui attire particulièrement l’attention.

Se trouvant sous forme soluble (sCD40L) ou associé aux cellules, il est entreposé

dans les granules alpha des plaquettes jusqu’à leur activation et s’accumule dans

les PC lors de l’entreposage[130-132]. Son effet activateur sur les macrophages

induit la libération de nombreuses cytokines associées aux réactions

transfusionnelles[133, 134]. Enfin, il peut y avoir production d’alloanticorps anti-

leucocytaires dirigés contre les antigènes leucocytaires humains de classes I et II

qui sont fréquemment retrouvés chez les femmes avec antécédent de grossesse ou

chez les donneurs ayant déjà été transfusés[135-137]. L’exclusion de ces derniers

aux dons a permis de réduire les risques de réactions transfusionnelles[138-140].

1.1.4 Rôles des plaquettes et des mégacaryocytes dans

l’immunité

Compte tenu du grand nombre de plaquettes dans le sang (40:1 par rapport aux

cellules immunitaires) et de leur vaste éventail de récepteurs immunitaires, la

capacité des plaquettes à soutenir les cellules immunitaires, promouvoir et participer

activement à l'immunité a fait l'objet de nombreuses investigations. Il est suggéré

que les MK et les plaquettes jouent un rôle dans la réponse immunitaire innée (révisé

en détail [2, 27, 141-144]) et dans l’immunité adaptative[145].

12

1.1.4.1 Notions d’immunologie

La capacité d'un organisme à se défendre contre des pathogènes ou des

substances étrangères nécessite la participation de deux composants du système

immunitaire : l'immunité innée et l’immunité adaptative. Les acteurs cellulaires

classiques de l’immunité innée sont les monocytes (forme immature et circulant dans

le sang), les macrophages (forme mature ayant migré dans les tissus), les

granulocytes (neutrophiles, éosinophiles et basophiles), les mastocytes et les

cellules dendritiques (DC-Dendritic Cells)[146]. L’immunité innée est la première à

se déclencher, prenant de quelques minutes à quelques heures pour détecter,

phagocyter et éliminer les micro-organismes tout en contribuant aux quatre points

cardinaux de l’inflammation (douleur, chaleur, rougeur, gonflement)[147].

Cette détection par le système immunitaire inné implique la reconnaissance de

motifs moléculaires connus sous le nom de motifs moléculaires liés aux pathogènes

ou associés aux dommages (respectivement PAMP ou DAMP)[148]. Les PAMP

sont des composants exogènes conservés parmi un large spectre de micro-

organismes et d'allergènes, tandis que les DAMP sont des signaux d'alarme

endogènes produits pendant le stress ou la mort cellulaire qui conduisent à des

réponses inflammatoires stériles[149, 150]. Les PAMP et les DAMP sont reconnus

par divers récepteurs reconnaissant des motifs structuraux répétés et comprennent

les récepteurs lectine membranaire de type C (CLR-C-type Lectin Receptor), les

TLR et les récepteurs de type NOD (Nucleotide-binding Oligomerization

Domain)[151]. La stimulation de ces récepteurs permet la sécrétion de cytokines et

de chimiokines pro-inflammatoires importantes pour le recrutement de cellules

immunitaires et l’activation du complément, pour activer directement la phagocytose

ou permettre la sécrétion de molécules nécessaires pour l’opsonisation, c’est-à-dire

la liaison de protéines au pathogène pour faciliter sa phagocytose[146, 148].

Le complément est un système de protéines plasmatiques qui entraine une réaction

en chaîne, tout comme la cascade de coagulation. Cette cascade peut être activée

par trois voies, la voie classique, la voie des lectines et la voie alternative. Ces

13

étapes précoces convergent toutes vers la formation de C3 convertase qui clive le

C3 en C3a et C3b et génère une succession de réactions de clivage menant au

recrutement des cellules inflammatoires et immunitaires, à l’opsonisation et à la

destruction des pathogènes et des cellules mortes, endommagées ou apoptotiques

(Figure 2)[152].

Figure 2: Vue générale de la cascade du complément

Elle peut être activée par trois voies, la voie classique, la voie des lectines et la voie

alternative. La voie classique est activée lorsque C1q se lie à la surface du

pathogène soit de manière directe, soit en liant la protéine C réactive ou bien en liant

un complexe antigène-anticorps. La voie des lectines est activée lors de la liaison

de lectines ou de ficolines présentes chez les phagocytes à des glucides présents

chez les pathogènes. Enfin, la voie alternative est déclenchée lors de la liaison sur

le pathogène du composant C3 activé spontanément dans le plasma. Ces étapes

précoces convergent toutes vers la formation de C3 convertase et mène au

recrutement des phagocytes, à la formation du complexe d’attaque membranaire, à

l’opsonisation et la destruction des pathogènes, des complexes immuns et des

cellules mortes, endommagées ou apoptotiques. (Figure créée à l’aide de

BioRender)

Bien qu’efficace pour éliminer la plupart des pathogènes, les réponses immunitaires

innées ne sont pas spécifiques et ne confèrent pas une immunité durable. En

14

revanche, le système immunitaire adaptatif confère une mémoire

immunologique[146]. Elle implique un processus appelé présentation antigénique

qui se produit pendant la réponse du système immunitaire inné et nécessite environ

deux semaines afin d’établir une réponse immunitaire plus forte, plus spécifique et

plus rapide à une rencontre subséquente[153].

Le système immunitaire adaptatif nécessite des acteurs supplémentaires, soit les

lymphocytes T impliqués dans la réponse immunitaire à médiation cellulaire et les

lymphocytes B, impliqués dans la réponse immunitaire humorale. À l’aide de leur

récepteur d’antigènes hautement spécifiques, respectivement le BCR (B cell

receptor) et le TCR (T cell receptor)[154], ils pourront détecter les antigènes

présentés à la surface des cellules présentatrices d’antigènes (APC-Antigen

presenting cells) qui font le pont entre l’immunité innée et adaptative[155].

Pour qu’un antigène soit reconnu par un lymphocyte T, il doit être présenté à la

surface de la cellule par les molécules du CMH, aussi connu chez l’humain sous le

nom d’antigène leucocytaire humain (HLA-Human Leukocytes Antigen), afin d’être

reconnu par le TCR[146]. Il existe deux catégories de molécules du CMH, soit les

molécules de CMH de classe I (HLA-A, -B et -C) et de classe II (HLA-DR, -DP, -DQ)

qui diffèrent par leur structure et leur distribution sur les différents types

cellulaires[156]. Le CMH I comprend une chaîne lourde liée de façon non covalente

à une chaîne légère microglobuline β2 (β2-MG) et est exprimé constitutivement par

toutes les cellules nucléées[157]. Le CMH II est composé d’une chaîne alpha et une

chaîne bêta et est exprimé sur les APC[158]. Ces protéines membranaires

possèdent un sillon extracellulaire qui permet l’insertion d’un fragment peptidique

dérivé de l’antigène et qui stabilise le complexe formé du peptide et d’une molécule

de CMH. Le CMH I a un sillon plus restrictif et lie généralement des peptides d’une

longueur de 8-10 acides aminés[159]. Le CMH II étant plus ouvert, la longueur des

peptides qu’il peut lier n’est pas restreinte, mais est généralement supérieure à 13

acides aminés[156]. En plus de la liaison entre le TCR et le CMH chargé d’un

peptide, une interaction supplémentaire avec les corécepteurs CD4 ou CD8

présents sur les lymphocytes est requise pour stabiliser l’interaction entre les deux

15

cellules et permettre une réponse efficace des lymphocytes T à l’antigène. Le CD8

reconnait spécifiquement le CMH I et le CD4 le CMH II en s’associant à une région

invariable de la molécule du CMH (Figure 3)[160].

Figure 3. Les sites de liaison du CMH I au CD8 et du CMH II au CD4

(A) Le site de liaison du CD4 dont la chaîne est représentée en orange se situe à la base du domaine β2 d'une molécule du CMH de classe II, dans la crevasse hydrophobe entre les domaines β2 (blanc) et α2 (rose). (B) La liaison du CD8, dont les deux chaînes du dimère sont représentées en violet clair et violet foncé, se lie à une molécule du CMH de classe I. La chaîne lourde de classe I est représentée en blanc et la β2-microglobuline en rose. Le site de liaison du CD8 sur la molécule du CMH de classe I se trouve dans une position similaire à celle du CD4 dans la molécule du CMH de classe II, mais la liaison du CD8 implique également la base des domaines α1 et α2. (Traduite du Janeway’s immunology 8e édition)[152].

16

Les lymphocytes T exprimant le CD4 (effecteurs) reconnaissent des antigènes

extracellulaires liés aux molécules du CMH II et activent d’autres cellules

immunitaires incluant les lymphocytes B[161]. Les lymphocytes B vont ensuite

entrainer la production d’anticorps nécessaire pour la neutralisation ou

l’opsonisation de l’antigène et l’activation du complément. Les lymphocytes T

exprimant le CD8 (cytotoxiques) vont reconnaitre des APC présentant des antigènes

du cytosol (pathogènes intracellulaires et tumeurs) liés aux molécules du CMH I et

mener à la destruction de la cellule infectée ou cancéreuse[161]. Certaines APC

peuvent aussi présenter des antigènes extracellulaires aux lymphocytes T CD8+

(restreints au CMH I) lors d’un processus appelé présentation croisée ou l’antigène

est capturé par endocytose ou phagocytose puis dégradé par des protéases dans

une vacuole[161].

Les peptides présentés par le CMH I ne pourraient l’être sans avoir été

préalablement apprêtés par le protéasome, l’une des deux voies principales de

dégradation des protéines intracellulaires qui existent chez les eucaryotes avec la

voie vacuolaire qui est impliquée dans la présentation croisée[160, 162-164]. Le

protéasome est une protéase multicatalytique de haut poids moléculaire

principalement connu pour sa fonction dans le maintien de l'hémostase des

protéines cellulaires et l’élimination des protéines mal repliées ou marquées

d’ubiquitine[165, 166]. Il est aussi impliqué dans d’autres fonctions cellulaires, telles

que la différenciation cellulaire, la progression du cycle cellulaire, la transcription, la

réponse au stress oxydatif et l'apoptose[162, 164]. Le protéasome est délimité du

reste de la cellule par sa structure fermée qui forme un espace compartimenté

analogue à la lumière d'une organelle[167]. Étant une structure spécialisée contenue

dans le cytoplasme qui a une fonction spécifique, nous allons considérer le

protéasome comme une organelle.

Le complexe central, nommé protéasome 20S, est formé de quatre anneaux

superposés comprenant chacune 7 sous-unités différentes pour un total de 28 sous-

unités distinctes (Figure 4)[168]. Les anneaux aux extrémités sont composés de

17

sous-unités α et les anneaux du centre sont composés des sous-unités β incluant

les sous-unités catalytiques β1 (activité de type caspase), β2 (type trypsine) et β5

(type chymotrypsine)[168, 169]. Ces différentes activités permettent au protéasome

20S de dégrader n’importe quel type de protéines en peptides d’une longueur de 3

à 15 acides aminés[163, 170]. Ce complexe central peut être associé avec le

régulateur 19S, qui contient la sous-unité ATPase permettant l’ouverture des

anneaux α, pour former le protéasome 26S[168]. Le 19S est important pour la

reconnaissance des protéines ubiquitinylées et permet leur linéarisation pour

l’insertion dans le complexe central[163]. Le protéasome 20S peut aussi s’associer

au régulateur 11S pour former l’immunoprotéasome, dans lequel les sous-unités

catalytiques β1, β2 et β5 sont remplacées par leurs homologues β1i, β2i et β5i[168].

Il est impliqué dans la génération de peptides améliorés pour la présentation

antigénique du CMH I[171].

Figure 4. Structure du protéasome et de l’immunoprotéasome

Le cœur du protéasome standard 20S est composé de 28 sous-unités non identiques qui sont disposées en quatre anneaux; deux composés de sept sous-unités α et deux composés de sept sous-unités β. Les sous-unités (β1, β2 et β5) sont catalytiquement actives (centre). Le protéasome 20S peut s’associer à deux régulateurs 19S pour former le protéasome 26S (à gauche). Le protéasome peut aussi s’associer au régulateur 11S pour former l’immunoprotéasome, qui contient trois sous-unités catalytiquement actives différentes (β1i, β2i et β5i). (Tirée de Klockenbusch et al[168].)

18

En effet, l’immunoprotéasome présente une activité de type caspase réduite et une

activité de type trypsine et chymotrypsine renforcée en comparaison du protéasome

standard, ce qui génère des peptides de nature hydrophobe ou basique ayant une

plus grande affinité avec la poche de liaison aux peptides du CMH I[163, 172-175].

Exprimé constitutivement dans les cellules immunitaires des tissus lymphoïdes tels

que la rate, le thymus et les ganglions lymphatiques, l’immunoprotéasome peut

aussi être induit dans les autres cellules en présence d’IFN γ et de TNF[162, 176].

En effet, la libération de cytokines proinflammatoires libérées par les cellules de

l’immunité innée contribue à la substitution du protéasome standard par

l’immunoprotéasome dans les tissus inflammés, en plus d’induire la surexpression

d’autres protéines liées à la présentation antigénique dont le CMH I et les protéines

de transport associées à l’antigène (TAP-Transporters associated with Antigen

Processing)[177]. Les sous-unités catalytiques de l’immunoprotéasome influencent

aussi la sélection des lymphocytes T en modulant le répertoire de TCR; les peptides

apprêtés en absence de l’une ou l’autre des sous-unités vont avoir des séquences

différentes qui peuvent mener à une réponse moindre ou même absente des

lymphocytes T cytotoxiques[178-180]. L’utilisation d’inhibiteurs sélectifs de

l’immunoprotéasome dans les dernières années à aussi mis en évidence sa

contribution dans les maladies auto-immunes, dans divers syndromes auto-

inflammatoires, dans le cancer et dans le rejet de greffe[181-184].

Les peptides, une fois clivés par le protéasome, sont ensuite transférés par le

transporteur TAP (composé des protéines TAP1 et TAP2) dans la lumière du

réticulum endoplasmique[185]. C’est à cet endroit qu’ils seront apprêtés davantage

au besoin par les aminopeptidases ERAAP (Endoplasmic reticulum amino

peptidase )1 et 2 et qu’ils vont s’associer au CMH I à l’aide du complexe chargeant

le peptide (PLC-peptide loading complex)[164]. Le PLC est composé des

chaperones tapasine, calnexine, calréticuline et la protéine disulfure isomérase

ERp57 qui aident au chargement et à la stabilisation du peptide dans le sillon du

CMH I en plus de vérifier la qualité du complexe formé[185]. Enfin le complexe CMH

19

I-peptide est exporté à travers le Golgi puis exposé à la surface de la cellule pour

être détecté par les lymphocytes T CD8+[164]. (Figure 5)

Figure 5: Apprêtement du peptide et présentation par le CMH I

Une chaine de CMH I nouvellement synthétisée se lie temporairement à la calnexine

dans le réticulum endoplasmique (RE) jusqu’à ce que ce complexe se lie à la β2-

microglobuline (β2-MG). Une fois stabilisé, le complexe partiellement replié se

dissocie ensuite de la calnexine, pour se lier à la tapasine, au transporteur TAP et

aux chaperonnes ERp57 et la calréticuline pour former le complexe de chargement

peptidique. Le protéasome, situé dans le cytosol, génère des peptides qui sont

transportés dans la lumière du RE par le transporteur TAP. La liaison d'un peptide

au CMH I achève le repliement de la molécule du CMH I et lui permet de se libérer

du complexe de chargement peptidique et de quitter le RE pour être exposé à la

surface cellulaire. L’interaction avec les lymphocytes T CD8+ pour la présentation

antigénique pourra alors se produire. (Figure créée à l’aide de BioRender)

20

1.1.4.2 Les plaquettes dans l’inflammation et l’immunité innée

Le rôle des plaquettes n'est pas limité à la réponse hémostatique. Les plaquettes

sont capables de phagocytose, mécanisme inné conservé des thrombocytes

(l’équivalent nucléé des plaquettes chez les vertébrés inférieurs), et cette activité

permettant de capturer des pathogènes s’effectue grâce à l’OCS[186-189]. Parmi

les premières cellules recrutées à l’endothélium inflammé ou endommagé, les

plaquettes expriment également un ensemble de récepteurs qui leur permettent de

détecter et d’éliminer les pathogènes directement ou en activant d’autres cellules

immunitaires[2, 143, 190].

Les plaquettes expriment de nombreux membres de la famille des TLR. Les TLR 1

à 10 ainsi que leurs voies de signalisation, molécules adaptatrices et facteurs de

transcription ont été identifiés chez l’humain et sont tous exprimés par les

plaquettes[191]. Ces TLR permettent à la plaquette de jouer un rôle critique dans

l’immunité innée par la reconnaissance de PAMP et de DAMP. Fait intéressant,

l’expression des différents TLR est plus élevée chez les plaquettes des femmes et

est associée avec l’expression de CD62P[191]. Les TLR 1-2-4-5-6 et 10 sont

présents à la surface de la cellule et les TLR 3-7-8 et 9 sont localisés dans les

endosomes et dans les granules T pour le TLR 9[18, 192]. En plus de leur

localisation cellulaire, les TLR peuvent aussi être classés en fonction des

pathogènes qu’ils ciblent. Le TLR 10 n’a pas encore de fonction connue et ne sera

pas décrit davantage. Les TLR 1 à 6 reconnaissent principalement des molécules

composant les bactéries, les mycètes (les TLR 2,4 et 6), les parasites et parfois des

composants structuraux des virus (TLR 2 et 4)[192]. Les acides nucléiques des

pathogènes sont aussi reconnus par des TLR, soit le TLR 3 pour l’ARN double brins,

les TLR 7 et 8 pour l’ARN simple brin et le TLR 9 pour l’ADN double brins[192]. Étant

donné qu’un modèle murin d’injection de lipopolysaccharide (LPS), ligand majeur du

TLR 4, a été utilisé lors de ma thèse, et que l’ADN mitochondrial (mtDNA-

mitochondrial DNA), ligand du TLR 9, est un sujet récurrent dans les prochains

chapitres, ces deux TLR seront décrits plus en détail.

21

Le TLR 4 reconnaît le LPS, un composant majeur de la paroi des bactéries Gram-

négatives[193]. La liaison du LPS par le TLR 4 n’est pas directe, elle implique deux

protéines plasmatiques accessoires, la protéine liant le LPS (LBP-LPS binding

protein), et le CD14. Le CD14 est présent à la surface des cellules, mais pas à la

surface des plaquettes, c’est donc sa forme soluble (sCD14) présente dans le sang

qui permet l’interaction avec deux complexes TLR 4-MD-2 (myeloid differentiation

factor 2) et qui entraine leur dimérisation[193, 194]. Les plaquettes humaines

peuvent discerner diverses isoformes de LPS bactérien via le TLR 4, entrainant des

profils de sécrétion de cytokines distincts et une réponse modulée en fonction des

différentes espèces de pathogènes[195, 196]. L’effet du LPS sur les plaquettes est

controversé et semble être affecté par le mode d’isolation et de préparation des

plaquettes[197]. Il pourrait augmenter l’activation des plaquettes par divers

agonistes ou promouvoir directement leur activation et entrainer la production

d’EV[196, 198-201]. Les plaquettes, en contact avec le LPS, seraient importantes

dans la production du TNF-α[202], de TF[203] et de sCD40L[204] en plus

d’augmenter la phagocytose des plaquettes qui sont liées à des auto-anticorps[205].

La stimulation du TLR 4 peut entrainer une thrombocytopénie ainsi que

l’accumulation de plaquettes aux poumons[198]. Les plaquettes, une fois leurs TLR

4 activés, se lient aussi aux neutrophiles pour augmenter la sécrétion de peptides

antimicrobiens et la production de NET (neutrophil extracellular traps) par ces

derniers, ce qui permet de piéger les pathogènes[206, 207]. En plus du LPS,

d’autres ligands incluant des motifs viraux et des DAMPs sont reconnus par le TLR

4, tels que les histones[208], l’hyaluronane soluble, la bêta-défensine 2, la protéine

HMGB1 (high-mobility group box 1)[209], HSP 70 (heat shock protein 70)[210],

S100A8/A9[211] et les pentaglucosides de Candida albicans[212].

Le TLR 9, exprimé par les plaquettes humaines et murines, reconnaît les motifs

d'ADN 2´-désoxyribo (cytidine-phosphate guanosine) non méthylés, communément

appelés motifs CpG. Ces motifs sont retrouvés dans l'ADN bactérien et viral, mais

aussi dans l’ADN mitochondrial[213]. L’ARNm du TLR 9 est exprimé chez les MK

matures et est régulé à la hausse durant la production de proplaquettes[18]. Les

22

plaquettes non activées expriment une quantité basale importante de TLR 9 à leur

surface. Celle-ci peut être augmentée chez l’humain en cas de stimulation avec de

la trombine, du collagène de type IV, de l’ADP, du PMA (phorbol myristate acetate)

et du CRP-XL (cross-linked collagen-related peptide)[18]. Ceci suggère d’une part

que le TLR 9 existe également dans les compartiments intracellulaires, mais d’autre

part que son expression est régulée différentiellement en fonction des espèces

puisque ce n’est pas le cas chez la souris[202]. Des oligodéoxyribonucléotides

(ODN) synthétiques contenant des motifs CpG nonméthylés sont généralement

utilisés comme agonistes pour activer le TLR 9. Lorsque les plaquettes sont

stimulées avec des ODN, elles séquestrent ces derniers ce qui favorise

l’augmentation de TLR 9 et de CD62P à leur surface[18]. Il a été montré que

l’activation de la voie TLR 9 augmente le risque de thromboses et d’accidents

cardiovasculaires[214]. En plus de reconnaitre les motifs CpG, le TLR 9 détecte

aussi des ligands endogènes altérés lors de conditions physiopathologiques

associées au stress oxydatif ou aux infections[215]. Ces protéines générées lors du

stress oxydatif sont groupées sous le terme CAP (carboxy(alkylpyrrole) protein

adducts) et sont fréquemment retrouvées dans les tumeurs, les plaies cicatrisantes

ou des maladies comme le diabète ou l’athérosclérose[215].

En plus d’exprimer différents TLR, les plaquettes humaines expriment des

récepteurs Fc pour les Ig A (IgA), E (IgE) et G (IgG), soit respectivement le

FcαRI[216], le FcεRI et FcεRII[217-219], et le FcγRIIA[220]. Les récepteurs FcαRI

et FcγRIIA sont absents chez la souris[221, 222], mais un modèle de souris

transgénique exprimant le FcγRIIA humain a été développé pour étudier le rôle de

ce récepteur[222]. L’activation du récepteur FcαRI des plaquettes par des IgA,

immunoglobulines participantes à l’immunité des muqueuses, entraine la production

de cytokines proinflammatoires (incluant l’IL-1β) et de TF qui sont critiques pour la

pathogenèse de plusieurs maladies inflammatoires et pour la thrombose[216]. La

stimulation des plaquettes via les récepteurs FcεRI et FcεRII, induit la libération de

sérotonine et de RANTES/CCL5, appuyant le rôle des plaquettes dans

l’inflammation allergique et la défense contre les parasites[217-219]. Le FcγRIIA est

23

lui aussi impliqué dans la thrombose et dans la pathogenèse de certaines maladies

auto-immunes[223], car il est important pour l’activation des plaquettes par le

vWf[224] et l'élimination des complexes immuns contenant des IgG circulants[225].

L’activation du FcγRIIA plaquettaire induit l’activation d’intégrines dont αIIbβ3 (le

complexe GPIIb-IIIa dont l’expression est unique aux plaquettes et induit leur

aggrégation), l’aggrégation des plaquettes, la sécrétion du contenu des granules, la

génération d’espèces réactives d’oxygène (ROS-reactive oxygen species), et

l’augmentation d’expression de surface de CD62P[226-232]. Cette cascade

d’évènements peut mener à un choc systémique tel qu’observé lors d’injection de

complexes immuns dans les souris transgéniques[233-236]. La présence du

FcγRIIA sur la plaquette permet aussi l’internalisation de bactéries opsonisées ou

leur élimination par la libération de molécules antimicrobiennes comme le

PF4/CXCL4[228, 237-239]. Il est aussi important pour le rôle des plaquettes dans la

lutte contre les infections virales, parasitaires et fongiques[240-249].

Évidemment l’ensemble des récepteurs de plaquette est vaste et ne se limite pas

uniquement aux TLR et aux récepteurs Fc. Elles expriment notamment six intégrines

différentes (α2β1, α5β1, α6β1, αLβ2, αIIbβ3, et ανβ3) importantes pour l’adhésion

cellulaire et leur activation. Elles possèdent aussi les récepteurs pour de nombreux

agonistes dont la thrombine[250], l’ADP[251], des prostaglandines[252-256], des

lipides[257-259] et des chimokines[260]. Une fois activées, les plaquettes vont

libérer de nombreuses molécules pouvant permettre l’interaction avec d’autres

cellules immunitaires, induire l’inflammation ou sa résolution, l’angiogenèse,

l’apoptose et/ou détruire les pathogènes[261].

Différentes molécules participent aux interactions entre les plaquettes et les cellules

immunitaires. Les plaquettes interagissent via CD62P ou la glycoprotéine Ib, avec

le ligand-1 de la glycoprotéine CD62P (PSGL-1) et l'intégrine CD11b/CD18 (Mac-1)

trouvés sur les leucocytes[262, 263]. Ces interactions déclenchent l’activation des

leucocytes et l’expression d’intégrines nécessaire pour l’adhésion aux parois des

vaisseaux sanguins[264]. Le dépôt de RANTES/CCL5 et de PF4/CXCL4 par les

24

plaquettes sur les cellules endothéliales aux sites d’inflammation favorise aussi

l’adhésion ferme et la transmigration des leucocytes vers les tissus inflammés,

endommagés et/ou infectés[265]. La forme activée du récepteur plaquettaire au

fibrinogène, le récepteur αIIbβ3, peut aussi se lier à SLC44A2 (solute carrier family

44 member 2) ainsi que Mac-1 sur le neutrophile. Cette interaction entraine la

production de cytokines pro-inflammatoires dont l’IL-1b, l’IL-8/CXCL8 et la libération

de sérotonine, ce qui a pour effet d’augmenter la perméabilité des cellules

endothéliales, de causer une vasodilatation et des fuites vasculaires[266, 267]. Les

différents médiateurs relargués par les plaquettes favorisent aussi l’activation des

neutrophiles et leur activité bactéricide, notamment en promouvant la production de

ROS[207, 268, 269], en augmentant l’activité phagocytaire et leur capacité à

produire des NET, soit des filets formés de chromatine décondensée chargée

d'enzymes protéolytiques et d'autres molécules antibactériennes expulsés des

neutrophiles activés[270, 271]. Il a été démontré que les NET favorisent l’activation,

la dégranulation et l’aggrégation des plaquettes, créant ainsi une boucle

d’amplification[272, 273]. En plus d’avoir un rôle dans la défense antimicrobienne,

les NET sont aussi générés lors d’une réponse à un stimulus non

conventionnel[274]. La formation non sollicitée ou un défaut dans l’élimination des

NET peut entrainer de l’inflammation et une surexposition à des auto-antigènes, ce

qui entraine des dommages tissulaires et facilite le développement de l’auto-

immunité[275-278].

1.1.4.3 Les mégakaryocytes dans l’immunité innée

Les mégakaryocytes expriment de nombreux récepteurs immunitaires y compris les

TLR 1 à 6 (l'ARNm du TLR 5 a été identifié dans les mégakaryocytes pulmonaires)

et le TLR 9 lors de la production de proplaquettes[18]. Le TLR 4 est notamment

impliqué dans la régulation de la production de plaquettes. Elles expriment aussi les

récepteurs d’immunoglobulines (FcRγIIA et FcεRI pour les mégakaryocytes

humains et FcγRI sur une sous-population de mégakaryocytes murins) et des

molécules co-stimulatrices, telles que le CD40L[27]. Les MK de la niche médullaire

sont en contact avec des cellules souches hémopoïétiques. Par sécrétion de

25

plusieurs molécules comme la thrombopoïétine, PF4/CXCL4 ou TGF-β, ils sont ainsi

capables de réguler la quiescence ou la prolifération des cellules souches

hématopoïétiques[242, 243]. Non seulement ils communiquent avec d'autres

cellules via ces molécules, mais les mégakaryocytes sont également capables

d'empéripolèse, un phénomène dynamique où elles engloutissent les neutrophiles

et où il se produit un échange membranaire[279].

1.1.4.4 Support des cellules de l’immunité adaptative par les plaquettes

Pendant l'immunité adaptative, les plaquettes peuvent soutenir les APC classiques

à travers plusieurs molécules (résumé en Figure 6, panneau de gauche). Par

exemple, le PF4/CXCL4, une chimiokine produite en abondance par les plaquettes

activées, inhibe la prolifération des lymphocytes T humains activés et la libération

des cytokines qu’ils produisent[280]. Le PF4/CXCL4 peut également influencer la

fonction et la différenciation des DC, conduisant à des DC différenciées qui sont

capables d'internaliser l'antigène, mais qui ne peuvent l’apprêter

adéquatement[281]. La protéine CD62P est emmagasinée dans des granules α et

libérée lors de l'activation plaquettaire. Cette protéine joue un rôle dans le

recrutement des lymphocytes aux sites d'inflammation[282, 283]. La contribution de

CD62P dans l'immunité adaptative implique également une présentation croisée

augmentée par les DC. En effet, les plaquettes modulent la maturation des DC

dérivées de monocytes par des interactions directes entre CD62P et PSGL1. En

effet, les DC générées par la co-incubation avec CD62P sont plus efficaces que les

DC dérivées à partir de cytokines pour générer une immunité tumeur-spécifique des

lymphocytes T[284]. La sérotonine n’est pas synthétisée par les plaquettes, mais

capturée et emmagasinée via leur transporteur de sérotonine dans les granules

denses plaquettaires[285]. Cette molécule est capable de favoriser le recrutement

des lymphocytes T CD4+ et CD8+ [286, 287] et d’affecter la différenciation des DC.

Les DC traitées à la sérotonine montrent une expression réduite des molécules co-

stimulatrices et une production accrue d'IL-10, diminuant leur capacité d’activer les

lymphocytes T[288].

26

Alors que le CD40L est localisé de manière intracellulaire dans les plaquettes

inactivées, les plaquettes activées arborent le CD40L à leur surface, ce qui leur

permet d'interagir avec les cellules porteuses de CD40 telles que les autres

plaquettes ou les cellules endothéliales, en plus des lymphocytes et des DC. Il a été

démontré que le CD40L dérivé des plaquettes induit la différenciation des

monocytes en DC et leur maturation, en plus de réguler positivement l’expression

de leurs molécules costimulatrices[289-291]. Cette fonction du CD40L plaquettaire

peut être très pertinente pour le lupus érythémateux systémique (SLE-Systemic

Lupus Erythematosus), maladie auto-immune dans laquelle les plaquettes se sont

révélées capables d'induire la différenciation des DC et la libération d'IFN, favorisant

ainsi la sécrétion d'anticorps par les lymphocytes B[292]. Une description plus

détaillée des interactions plaquettaires via le CD40L dans l'immunité adaptative a

déjà été étudiée en détail dans plusieurs revues[293-296]. Les plaquettes exprimant

le CD40L ont également été identifiées dans différentes pathologies où elles activent

directement l'endothélium[297] ou bien elles contribuent au recrutement de

neutrophiles et de lymphocytes T à l'endothélium endommagé, plus particulièrement

dans l'intima et dans les plaques dans l'athérosclérose[298]. Ainsi, conformément

aux investigations in vivo et in vitro qui ont révélé un rôle du CD40L plaquettaire

dans la commutation isotypique des lymphocytes B et dans l'augmentation de la

fonction des lymphocytes T CD8+ durant l'infection, ces multiples études suggèrent

que les plaquettes, via le CD40L, peuvent avoir un impact sur les lymphocytes et les

DC dans les étapes clés de l'immunité adaptative[299].

Les plaquettes sont également importantes dans l'induction de la tolérance

immunitaire, car leur déplétion réduit la fréquence des lymphocytes T régulateurs

(Tregs) Foxp3+ dans la peau inflammée et dans les ganglions lymphatiques

drainants[300]. Elles sont considérées comme protectives, car elles augmentent

l'activation des lymphocytes T régulateurs CD4+ et elles produisent aussi du TGF-β,

un régulateur reconnu de la fonction des lymphocytes T CD8+[301, 302].

27

1.1.4.5 Apprêtement et présentation de l'antigène par les plaquettes

Le protéasome a été purifié de la fraction cytosolique des plaquettes humaines pour

la première fois au début des années 90[303, 304]. Depuis, la présence de toutes

les sous-unités catalytiquement actives du protéasome 20S dans les plaquettes

humaines a été confirmée, incluant les sous-unités composant

l'immunoprotéasome[168]. Toutes ces composantes peuvent s'assembler pour

obtenir un immunoprotéasome constitutivement actif dans les plaquettes, même en

l’absence de stimulation par l’IFN[168]. De plus, il a été montré que l’activité du

protéasome des plaquettes est régulée positivement lors de septicémie

bactérienne[305].

La pertinence de cet organite dans les plaquettes n'est pas encore entièrement

comprise étant donné la faible production de protéines par les plaquettes, mais

certaines fonctions clés ont été identifiées et examinées récemment[306]. Le

protéasome est nécessaire pour la production de plaquettes par les MK[307, 308],

pour limiter la durée de vie des plaquettes[309], pour leur activation[310, 311]

(contesté par Koessler et al.[312]), et pour la libération d’EV[313]. Ces résultats sont

d'une importance clinique, car le bortézomib, un inhibiteur du protéasome utilisé

pour traiter les patients atteints de lymphome multiple, induirait une

thrombocytopénie[307, 308].

Une autre fonction du protéasome est d'hydrolyser les protéines en petits peptides.

Ce processus est d'une importance critique pour le chargement des peptides dans

le CMH de classe I et pour la présentation antigénique aux cellules T CD8+ dans

l'immunité adaptative. On trouve des molécules de CMH I sur les plaquettes murines

et humaines[314, 315], mais une large proportion (70 à 80%) s'est avérée provenir

de l’adsorption de CMH I circulant dans le plasma[316]. Non seulement les

plaquettes peuvent l’adsorber, elles sont également capables de transférer leur

CMH de classe I à la surface des cellules tumorales, ce qui leur confère un

phénotype normal[317]. En enrobant les cellules tumorales, les plaquettes

interfèrent avec la capacité des cellules tueuses naturelles (NK-Natural Killers) à

28

reconnaitre les cellules nocives auxquelles il manque le CMH I. Les tumeurs

cachées échappent ainsi à la reconnaissance des cellules NK, empêchant la

cytotoxicité et la production d'IFN γ[317]. Ce rôle insidieux du CMH I plaquettaire

permet la croissance des tumeurs et l'établissement du cancer.

En plus du CMH I et de la β2-MG, une chaperone moléculaire pour le complexe du

CMH I, la spectrométrie de masse a permis de caractériser le protéome des granules

α des plaquettes et d’identifier 45 protéines liées à la voie « d’apprêtement et

présentation de l'antigène »[318]. Parmi ces protéines, les auteurs ont identifié les

protéines TAP1 et TAP2 (antigen peptide transporter 1 and 2), qui permettent la

translocation du peptide traité dans le réticulum endoplasmique plaquettaire avant

leur chargement sur le CMH I[318]. Les composants du PLC (ERp57, calréticuline,

calnexine et tapasine), ainsi que les molécules costimulatrices des cellules T, dont

le CD40, ICOSL et CD86 (cette dernière chez l'homme uniquement)[318, 319] se

trouvent dans les plaquettes, ce qui suggère que les plaquettes contiennent toute la

machinerie pour l’apprêtement et la présentation des antigènes aux lymphocytes T.

Alors que la plupart des molécules ont été identifiées dans les compartiments

intracellulaires, leur présence à la surface des plaquettes est nécessaire à la

formation de synapses immunologiques avec les lymphocytes T. Une analyse par

microscopie confocale a révélé que les protéines CMH I, β2-MG, TAP1 et TAP2

pouvaient être localisées à la surface des plaquettes activées par la thrombine,

indiquant leur sécrétion lors de l'activation[318]. De plus, les nouvelles plaquettes

présentent des quantités plus grandes de CMH I sur leur membrane plasmique que

les plaquettes plus anciennes chez les souris, ce qui suggère que l'expression de

surface du CMH I est modulée tout au long de la durée de vie des plaquettes[320].

L'activation des plaquettes lors d’une infection peut également conduire à

l'expression du CMH I sur la membrane plasmique. En effet, chez les plaquettes

murines le CMH I est augmenté en cas d'infection par Plasmodium berghei et le

virus de la dengue[319, 321].

29

Les travaux par Chapman et al. ont montré la capacité des plaquettes à apprêter et

à présenter des antigènes aux lymphocytes T[319]. Les auteurs, en chargeant les

plaquettes avec la protéine ovalbumine (OVA) ont confirmés qu’elles possédaient la

machinerie nécessaire pour transformer efficacement l'OVA en peptides, y compris

la séquence peptidique antigénique SIINFEKL. Cette séquence, si elle est présentée

par les molécules du CMH I, peut être reconnue par le TCR exprimé par toutes les

cellules T chez les souris transgéniques OT-1. En utilisant des approches in vitro et

in vivo, ils ont montré que les plaquettes pouvaient en effet présenter l'antigène de

l'OVA via le CMH I aux lymphocytes T et, étant donné l'expression de molécules

costimulatrices par les plaquettes, pouvaient stimuler l’activation et la production

d'IL-2 des lymphocytes T[319]. Ces résultats indiquent une utilisation potentielle des

plaquettes dans un vaccin à base de cellules. Cette hypothèse a été testée avec un

véritable pathogène, Plasmodium berghei, parasite responsable du paludisme. En

utilisant le parasite Plasmodium berghei transgénique pour les acides aminés C-

terminaux 150-368 d'OVA (Pba-OVA), il a été montré que les plaquettes, via leur

CMH I, sont capables de charger et de présenter des antigènes dérivés de PbA-

OVA pour générer des lymphocytes T protecteurs[319]. L'ensemble de ces

expériences montrent que les plaquettes sont capables d’apprêter et de présenter

l'antigène.

Bien que les plaquettes puissent internaliser d'autres agents pathogènes que

Plasmodium berghei, tels que le virus de la dengue, le virus de la grippe et le VIH

par phagocytose ou endocytose[240, 243, 322, 323], elles augmentent également

l’élimination bactérienne chez les souris septicémiques[208]. Non seulement elles

sont capables de tuer directement des agents pathogènes comme C. albicans[324],

les plaquettes favorisent aussi l'interaction entre des agents pathogènes comme le

virus de l'hépatite B[325], L. monocytogenes ou d'autres bactéries Gram positifs

avec des cellules présentatrices d’antigènes professionnelles[326], soit en se liant

au pathogène et en le conduisant aux DCs, soit en recrutant les cellules

immunitaires au site d'infection et en modulant leur réponse. Un rôle pour le CD40L

plaquettaire a également été mis en évidence dans le contexte d’infections

30

bactériennes et virales. L'infection par le virus de la dengue chez l'homme augmente

l'expression de CD40L à la membrane plaquettaire et induit la sécrétion de

sCD40L[321]. Le CD40L dérivé des plaquettes améliore également l'absorption et

la destruction de Staphylococcus aureus par les DC grâce à l’augmentation de

l’expression du CD80 et la production accrue du TNF-α et des cytokines pro-

inflammatoires IL-12 et IL-6[327].

Un autre groupe de recherche a montré que le CD40L dérivé des plaquettes

améliorait la réponse des lymphocytes T CD8+ spécifiques de l'OVA et augmentait

l’élimination d'une Listeria monocytogenes transgénique pour le peptide OVA[328].

Le rôle des plaquettes dans la présentation antigénique a été montré depuis peu

(voir Figure 6, panneau de droite). Il reste cependant à déterminer si les antigènes

microbiens transformés peuvent être présentés par les molécules du CMH I des

plaquettes activées pour jouer un rôle dans l'immunité adaptative contre ces agents

pathogènes.

31

Figure 6: Les plaquettes soutiennent les cellules de l’immunité adaptative et présentent l’antigène

(Panneau de gauche) Les plaquettes soutiennent la présentation antigénique à travers plusieurs molécules telles que la sérotonine, le TGF-β et le PF4/CXCL4. Elles sont capables de reconnaître les agents pathogènes directement via des récepteurs de type Toll (TLR) ou leurs récepteurs d'immunoglobulines (FcR). De plus, les plaquettes expriment CD40L, CLEC-2 et CD62P, ce qui peut favoriser l'interaction et l'activation des lymphocytes T, B et les DC. Les plaquettes produisent également des vésicules extracellulaires (EV). (Panneau de droite) Les plaquettes participent directement à l’apprêtement et à la présentation de l'antigène. Le CMH I et CD62P se trouvant dans les granules alpha des plaquettes sont exposés à la surface après activation. Le protéasome est fonctionnel dans les plaquettes et joue de nombreux rôles dans les fonctions plaquettaires, incluant l’apprêtement. Les molécules impliquées dans la présentation de l'antigène, telles que TAP 1 et TAP 2 et celles du complexe de chargement peptidique sont présentes dans les plaquettes. Les peptides apprêtés par le protéasome sont chargés sur des molécules du CMH I par le complexe de chargement peptidique et présentés à la surface des plaquettes aux lymphocytes T CD8+. (Figure créée à l’aide de BioRender)

1.1.4.6 Apprêtement et présentation de l'antigène par les mégacaryocytes

Contrairement aux plaquettes qui n'expriment pas les molécules du CMH II (excepté

de façon transitoire lors d’ITP)[329-331], les progéniteurs précoces des MK, dérivés

32

des cellules souches hématopoïétiques humaines, expriment le CMH II. Ces MK

jouent des rôles qui rappellent celui des APC. Il a été montré que ces MK soutiennent

l'activation des lymphocytes T et augmentent la prolifération des Th17, des Th1 et

des cellules doubles positives Th17/Th1 lorsqu'ils sont incubés en présence de

lymphocytes de sujets normaux ou de patients atteints de SLE[332]. Les

progéniteurs de MK sont aussi efficaces pour monter une réponse immunitaire

contre le pathogène opportuniste Candida albicans, suggérant ainsi que la

mobilisation des cellules souches hématopoïétiques peut conduire à la génération

d'une population de MK avec des fonctions immunitaires[333]. Classiquement, les

molécules du CMH II présentent des peptides dérivés de pathogènes

extracellulaires via les endosomes, qui est un site d'entrée pour les virus. Il est connu

que le virus de la dengue peut se développer dans les progéniteurs de MK et les MK

matures peuvent générer une immunité antivirale qui implique des molécules d'IFN

en réponse au virus de la dengue ainsi qu'au virus de l’influenza[334]. Il reste à

établir, cependant, si les MK peuvent traiter et présenter des peptides viraux dans

le contexte d'une infection virale[335]. Les MK peuvent aussi être localisés dans les

poumons et, selon des études de transcriptome, ces derniers présentent un

phénotype de cellules immunitaires (cytokines et voies de signalisation activées)

contrairement aux MK de la moelle osseuse[336]. Comme les MK pulmonaires ont

un accès privilégié aux pathogènes de l'air tels que le virus de l’influenza ainsi qu'aux

allergènes, ils pourraient être en mesure de contribuer à la présentation antigénique

dans cet organe. Non seulement les mégacaryocytes des poumons ont une

expression de gènes similaire aux APC, mais ce phénotype est plastique et dépend

de l’environnement tissulaire comme il a été montré lors du transfert de

mégacaryocytes de la moelle osseuse dans les poumons[337]. Ces derniers

acquièrent une expression augmentée du CMH II dans l’environnement pulmonaire,

tout comme lorsqu’ils sont stimulés avec des PAMP tels que le LPS[337]. Cet article,

publié tout récemment, a aussi mis en évidence que les mégacaryocytes des

poumons peuvent internaliser, apprêter et présenter l’antigène via le CMH II aux

lymphocytes T CD4+[337].

33

Alors que l'expression du CMH II est perdue dans les MK matures de la moelle

osseuse, des études ont confirmé que le CMH I et la machinerie nécessaire pour

apprêter et présenter l'antigène y sont maintenus. De plus, les MK expriment CD80

et CD86, des molécules de co-stimulation des lymphocytes[338]. En utilisant à la

fois des approches in vitro et in vivo dans le modèle OVA de présentation de

l'antigène, il a été montré que les MK pouvaient internaliser et apprêter l'OVA en son

peptide antigénique (SIINFEKL) et le présenter aux lymphocytes T, favorisant ainsi

leur prolifération[338]. D'importance clinique, les MK pourraient présenter des

peptides endogènes (le CD61 présent chez les MK) pour activer les cellules T CD8+

spécifiques de CD61 et ainsi médier l’ITP in vivo (Figure 7)[338].

Figure 7: Les mégacaryocytes sont des cellules immunitaires

Les MK expriment les TLR 1 à 6, les récepteurs d'immunoglobulines (FcRγIIA, FcεRI ou FcγRI) et la molécule co-stimulatrice CD40L. Les premiers progéniteurs de MK

34

expriment également le CMH II qui est important pour soutenir l'activation des cellules T et l'expansion des cellules T auxiliaires. Les MK contiennent du protéasome, expriment le CMH I et les molécules co-stimulatrices CD80 et CD86. Ces dernières leur permettent d’apprêter et de présenter l'antigène et de déclencher l'activation des lymphocytes T CD8+ et leur lymphoprolifération. Les MK sont capables d'emperipolèse et produisent les plaquettes et des vésicules extracellulaires (EV). (Figure créée à l’aide de BioRender) En raison de leur abondance dans le sang et les poumons, les plaquettes et les MK

sont idéalement positionnés pour réagir rapidement à un antigène et le présenter

aux lymphocytes. Un résumé de leurs rôles dans l’immunité innée et adaptative est

présenté en Figures 6 et 7. Toutefois, les plaquettes et les MK ne peuvent pas

atteindre les organes lymphoïdes en circulant à travers la lymphe comme le ferait

un leucocyte. Les plaquettes peuvent interagir directement avec les lymphocytes de

la rate ou les organes lymphoïdes secondaires et tertiaires par le biais des veinules

postcapillaires. Les plaquettes activées libèrent aussi des EV qui apportent avec

elles du contenu de la plaquette et qui pourraient être impliquées dans cette

interaction.

1.2 Les vésicules extracellulaires

1.2.1 Description générale et mécanisme de formation

Les EV sont des éléments sphériques de petite taille, composées de cytosol et d’une

membrane lipidique dont le contenu est enrichi en cholestérol, sphingomyélines, PS

et glycosphingolipides[339]. Les EV sont produites lors de l’activation ou de

l’apoptose de tout type cellulaire confondu, incluant les cellules procaryotes et

eucaryotes d’organismes unicellulaires ou pluricellulaires[340], et diffèrent en

fonction de leur taille, de leur contenu, de leur composition et de leur processus de

formation. Elles sont retrouvées dans tous les liquides biologiques ainsi que dans le

surnageant de culture cellulaire. Les EV ont de nombreux rôles, notamment pour

l’élimination de déchets cellulaires, la communication intracellulaire, l’hémostase, le

développement et l’inflammation[341-345].

35

Certaines EV sont associées à des pathologies et peuvent servir de biomarqueur

comme dans les fluides de patients atteints de maladies auto-immunes[346, 347].

Leur implication dans la progression de certaines maladies est également étudiée.

Par exemple, les EV de plaquettes et de cellules endothéliales sont plus abondantes

chez les patients atteints du syndrome anti-phospholipides[348]. Les EV de

plaquettes jouent aussi un rôle dans l’arthrite, où elles sont présentes abondamment

dans le liquide synovial des patients, et chez les patients atteints de SLE[349, 350].

En plus de présenter un intérêt comme source de biopsie liquide, les EV offrent aussi

un potentiel thérapeutique. Des études récentes s’intéressent à l’utilisation d’EV

pour effectuer du transport de médicament à des sites spécifiques dans l’organisme

ou bien à leur utilisation pour le développement de vaccins dans des maladies auto-

immunes[351-353].

Classées en trois groupes, soit les exosomes, les microvésicules (MV) et les corps

apoptotiques, les EVs ont des caractéristiques et des fonctions distinctes (Figure

8)[345].

Figure 8: Échelle de taille des vésicules extracellulaires Tirée de György, B. et al[354]. Taille respective des cellules et des différentes vésicules extracellulaires en comparaison avec d’autres éléments connus.

36

Issus de la fragmentation de cellules en apoptose, les corps apoptotiques ont une

taille comprise entre 1 et 5 μm, chevauchant celle des plaquettes[354]. Les

exosomes, qui sont formés par l’exocytose des corps multivésiculaires (MVB). Le

mécanisme de formation des MVB est dirigé par le complexe de tri endosomal

nécessaire au transport (ESCRT-endosomal sorting complex required for transport)

et requiert la participation d’une trentaine de protéines[355]. Les MVB ainsi formés

seront libérés dans le milieu extracellulaire lors de leur fusion avec la membrane

plasmique[356]. Les exosomes ont une taille comprise entre 50 et 100 nm de

diamètre qui est similaire aux virus[354]. De façon intéressante, de nombreux virus

enveloppés, principalement ceux à ARN, sont générés en utilisant la voie

ESCRT[357]. Les exosomes peuvent aussi être formés de façon ESCRT-

indépendante[358]. Les MV, également connues sous le nom d’ectosomes ou de

microparticules, sont des structures dont la taille comprise entre 100 nm et 1 µm

chevauche celle des complexes immuns et des bactéries (Figure 8)[354, 359]. Bien

que le système ESCRT semble aussi être impliqué dans la production de MV[360,

361], une combinaison d’autres facteurs sont importants. Ceci inclut le remodelage

de la membrane et la redistribution des phospholipides dont l’externalisation de la

PS via l’activité de flippases, floppases et de scramblases[362-364]. Une

augmentation du calcium intracellulaire est aussi nécessaire pour le remodelage du

cytosquelette qui permet le bourgeonnement et la libération des MV[365]. Les EV

principalement étudiées lors de cette thèse entrent dans la catégorie des MV et

seront décrites plus en détail.

Étant donné l’augmentation rapide de la recherche sur les EV dans les dernières

années, une société nommée ISEV (International Society for Extracellular Vesicles)

qui regroupe des scientifiques ayant une expertise dans le domaine a été fondée en

2011 dans le but d’améliorer, d’uniformiser et d’encadrer la recherche sur les EV.

Trois ans plus tard, l’ISEV a publié un article de référence indiquant les exigences

expérimentales minimales pour la définition des EV et de leurs fonctions[366]. Ces

exigences ont été révisées en 2018[367], et des recommandations entourant le

prélèvement, le transport et l’entreposage des EV ont été décrites en 2019[368]. Des

37

bases de données telles que ExoCarta (http://www.exocarta.org), EVpedia

(http://www.evpedia.info) et Vesiclepedia (http://www.microvesicles.org) concernant

les exosomes ou les EV ont aussi été créées[369-371].

1.2.2 Isolation et détection des vésicules extracellulaires.

L’isolation des EV pour leur caractérisation peut s’avérer complexe et présente de

nombreux obstacles. Non seulement, le milieu duquel sont extraites les EV contient

de nombreux contaminants tels que des acides nucléiques, des lipoprotéines, des

agrégats protéiques et des complexes immuns[354, 366, 372], mais une séparation

stricte entre les exosomes et les MV basée sur la taille ou par leur mécanisme de

formation n’est pas possible à ce jour et il n’existe pas de consensus sur les

marqueurs spécifiques à utiliser pour discriminer les deux populations[373]. Les

méthodes actuellement utilisées pour l’isolation incluent la centrifugation,

l’ultracentrifugation par gradient de densité, la chromatographie d’exclusion de

taille[372] et l’utilisation de trousses commerciales qui combinent plusieurs

approches[366].

Les EV peuvent être étudiées et caractérisées de nombreuses façons, notamment

par l’utilisation de marqueurs pour différentier les EV entre elles pour l’origine

cellulaire par exemple. Elles peuvent aussi être analysées par mesure de la diffusion

dynamique de la lumière (mouvement brownien), par analyse de suivi des

nanoparticules, par la mesure d’impédance, par immunobavardage de type

Western, ou des analyses protéomiques globales utilisant la spectrométrie de

masse[366, 374]. D’autres techniques qui permettent d’étudier les EV de façon

individuelle et qualitative sont la microscopie à fluorescence et la vidéomicroscopie

(pour les EV de grande tailles)[375, 376], ainsi que la microscopie électronique, la

microscopie à force atomique et la cytométrie en flux[377]. Étant donné la complexité

et le temps nécessaire pour l’analyse par microscopie, la cytométrie en flux est

l'approche la plus largement utilisée (70-75% des cas) pour la détection des EV et

présente l’avantage d’être quantitative en plus de permettre l’utilisation de plusieurs

marqueurs[378, 379]. Les cytomètres conventionnels, initialement développés pour

38

l’analyse de cellules offrent une faible résolution pour les EV de taille inférieure à 0,5

µm[380]. Cette différence de taille a un impact majeur pour l’analyse par cytométrie

si l’on considère qu’une cellule fait en moyenne 100 fois le diamètre d’une EV et

donc 10 000 fois sa surface[381]. Heureusement des cytomètres de haute sensibilité

ont été développés et offrent une résolution suffisante pour différentier les sous-

types de EV, incluant ceux qui contiennent des organelles[382, 383]. Cette approche

sera la principale utilisée pour l’analyse des EV de plaquettes.

De nombreux critères doivent être respectés pour une bonne caractérisation des EV

par cytométrie en flux afin de respecter les recommandations de l’ISEV.[367] Les

informations concernant la collection, l’isolation et l’entreposage des EV doivent être

présente dans le manuscrit avec toutes les étapes du marquage. Une description

détaillée des réactifs utilisés et du cytomètre (type de cytomètre, lasers utilisés,

seuils (treshold) et intensité, débit, etc.) est aussi exigé. Des contrôles de marquage

incluant l’analyse du tampon, des échantillons non marqués, des simples

marquages et l’utilisation d’isotype sont demandés. La nature membranaire des EV

doit être confirmée par un traitement à l’aide d’un détergent tel que le Triton X-100.

Des dilutions en série doivent être faites afin de démontrer l’absence de coïncidence

lors de l’analyse et de la quantification des EV. Enfin des détails sur la méthodologie

utilisée pour estimer la taille des EVs doivent aussi être fournis.

1.2.3 Diversité des vésicules extracellulaires

Le développement de techniques pour l’isolation et la caractérisation des EV a

permis de mieux apprécier leur diversité. En effet, les EV circulant dans le sang

peuvent provenir de différentes cellules vasculaires (plaquettes, monocytes, cellules

endothéliales, globules rouges et granulocytes). Ces EV expriment des marqueurs

de surface telles que des intégrines et transportent des acides nucléiques et des

protéines qui proviennent de la cellule mère, suggérant que ces EV pourraient avoir

une fonction distincte selon la nature de la cellule de laquelle elles proviennent et de

l’état (activé ou non)[378]. Les EV ont un rôle important pour l’hémostase et la

39

défense de l’hôte[384]. Elles ont toutefois un rôle majeur dans le développement et

la progression de nombreuses maladies comme le cancer, les maladies

cardiovasculaires, la prééclampsie, le diabète et les maladies

neurodégénératives[342, 384-387].

1.2.4 Organelles contenues dans les vésicules extracellulaires

1.2.4.1 La mitochondrie

La mitochondrie possède une membrane interne, site de la respiration cellulaire, qui

est repliée de façon à former de nombreuses invaginations et d’une membrane

externe. Elle possède son propre génome, l’ADN mitochondrial qui s’apparente a

celui de Rickettsia prowazekii[388]. Cette molécule circulaire, double-brin, est

formée de 16 569 paires de bases qui codent pour 2 ARN ribosomaux, 22 ARN de

transfert et 13 protéines[389], et qui possède des îlots CpG non méthylés[213]. La

mitochondrie joue de nombreux rôles au sein de la cellule. Elle est essentielle pour

la production d’énergie (ATP)[390], pour la synthèse d’hormones[391], pour

l’homéostasie du calcium[392, 393], et pour la régulation de la mort cellulaire

(apoptose)[394, 395].

Possédant de nombreuses caractéristiques communes avec les procaryotes, la

mitochondrie est une source importante de DAMPs (Figure 9). La mtDNA peut, via

le TLR 9, induire une réponse immunitaire dans différentes pathologies telles que le

cancer et les maladies auto-immunes[396, 397]. La présence de mtDNA est aussi

observée chez les patients gravement blessés, lors de sepsis ou de dommages aux

organes et est liée à l’évolution clinique[398-405]. Les produits sanguins, incluant

les PC, contiennent aussi de la mtDNA, qui est d’ailleurs impliquée dans le

développement de certaines réactions transfusionnelles comme le TRALI[406].

Les peptides formylés provenant de la mitochondrie s’accumulent aux sites de

dommages tissulaires. Ces derniers activent les récepteurs de peptides formylés, ce

qui induit l’accumulation de cellules pro-inflammatoires telles que les

40

neutrophiles[407, 408]. Une protéine de la chaine de transport d’électrons, le

cytochrome C, est libérée dans le milieu extracellulaire lors de l’apoptose[409]. Cette

dernière fait partie des nombreux autoantigènes ciblés dans des maladies auto-

immunes systémiques telles que l’arthrite rhumatoïde et le SLE[410, 411]. Un autre

élément de la membrane mitochondriale, les cardiolipides, sont des phospholipides

négativement chargés qui permettent l’ancrage du cytochrome C[412, 413]. Lors de

leur exposition à la surface des cellules apoptotiques, les cardiolipides sont aussi

reconnus par des autoanticorps ciblant les phospholipides[414].

Figure 9. DAMPs dérivés de la mitochondrie

La mitochondrie est une source de DAMPS qui peuvent être libérés lors de différents processus de mort cellulaire (apoptose, nécrose secondaire ou nécrose) ou d’une lésion tissulaire (section en bleu). Ces DAMPs comprennent la mtDNA, des peptides formylés, des cardiolipides, du cytochrome c, du carbamoyl-phosphate synthétase (CPS-I) et de l’ATP (section en vert). Une fois que les DAMPs sont libérés dans l'espace extracellulaire, ils peuvent stimuler la réponse innée ou adaptative (section en rose). Adaptée de Krysko et al[415].

41

1.2.4.2 Le protéasome

Du protéasome extracellulaire a été observé dans le sang pour la première fois il y

a bientôt 30 ans[416]. Connu sous le nom de protéasome circulant, sa présence est

augmentée chez les patients souffrant de maladies auto-immunes, de cancers, de

trauma et de sepsis[417]. Il n’est toutefois pas exclu que ce protéasome puisse être

relargué par les cellules. D’ailleurs, il a récemment été observé que les lymphocytes

T et les cellules souches mésenchymateuses relarguent des EV contenant du

protéasome[418, 419]. De plus, il a été démontré que le protéasome 20S est présent

et actif dans les EV dérivées de cellules endothéliales apoptotiques[169]. Non

seulement ces EV régulent la formation des structures lymphoïdes tertiaires, elles

sont aussi importantes dans la production d'auto-anticorps et le rejet de greffe après

la transplantation[169, 420]. Le transfert du protéasome dans les EV de plaquettes

est plausible étant donné sa présence dans les plaquettes et les MK, mais n’a pas

été vérifié à ce jour.

1.2.5 Les vésicules extracellulaires de plaquettes

Les EV de plaquettes représentent environ 80% des EV circulantes dans le

sang[421, 422]. Anciennement appelées poussière de plaquettes[423], elles sont

formées lors de l’activation des plaquettes par divers agonistes comme la thrombine,

le collagène et le complément[424, 425]. Elles peuvent aussi être formées en

l’absence d’activation sous contrainte de cisaillement et lors de l’entreposage dans

les PC[426-428].

Les EV de plaquettes, lors de leur genèse, peuvent apporter avec elles des

mitochondries situées à proximité de la membrane plasmique[382]. Ces EV,

présentes dans les liquides biologiques et dans les PC forment une population

hétérogène qui peut être divisée en trois catégories[382], soit les EV qui ne

contiennent pas de mitochondries, les EV qui contiennent une ou des mitochondries.

Il est aussi possible d’observer des mitochondries extracellulaires, qui ne sont pas

entourées d’une membrane de plaquette (freeMitos). L’ADN mitochondrial est aussi

42

retrouvé dans les EV[429, 430].

Il est suggéré que les EV de plaquettes jouent de nombreux rôles dans la régulation

des fonctions physiologiques et pathologiques[431]. Elles ont une activité

procoagulante en exposant la PS et elles accélèrent la génération de thrombine[426,

432-434]. Elles expriment aussi du TF qui permet l’initiation de la cascade de

coagulation in vivo[435-437]. Les EV de plaquettes ont aussi un rôle dans la

régulation de l’immunité (stimulation et suppression), où elles peuvent interagir avec

les lymphocytes T et réguler leur différenciation et leur activité régulatrices[438, 439].

De plus, elles peuvent favoriser la formation de centres germinatifs et la production

d'IgG par les lymphocytes B en fonction de leur contenu en CD40L[440, 441].

Comme les EV de plaquettes peuvent circuler dans la lymphe[442, 443], elles ont la

possibilité de transporter des molécules de l'immunité adaptative vers les organes

lymphoïdes.

Le cargo transporté par les EV de plaquettes (facteurs de croissance, protéines,

acides nucléiques, organelles, etc) leur permet aussi de jouer un rôle dans la

communication intracellulaire[354, 444]. Par l’échange d’acides nucléiques (mRNA,

miRNA et autres types d’ARN), elles peuvent réguler les cellules à des niveaux post-

transcriptionnels[445-447]. Le cargo des EV de plaquettes leur donne aussi rôle

dans l’inflammation en libérant de nombreux médiateurs pro-inflammatoires.

L’emphase de cette thèse sera sur deux organelles contenues dans les EV, soit la

mitochondrie et le protéasome.

43

1.3 Objectifs

Les plaquettes favorisent l'hémostase en jouant un rôle important dans la

coagulation, mais elles ont aussi un rôle dans l’immunité. Lors de leur activation,

elles produisent des EV dont le cargo est variable. Le but de cette étude vise d’une

part à approfondir les connaissances fondamentales sur les EV de plaquettes et

leurs rôles dans l’inflammation et l’immunité en s’attardant plus spécifiquement aux

organelles pouvant être contenues dans les EV de plaquettes. Notre hypothèse

générale est que le cargo des EV de plaquettes, plus précisément les organelles,

leur confèrent un rôle dans l’inflammation et l’immunité.

Dans le cadre de cette thèse, nous avions comme premier objectif d’évaluer

l’utilisation d’un algorithme (SPADE) couplé à la cytométrie en flux pour améliorer la

détection d’EV. Notre hypothèse est que l’utilisation de SPADE peut permettre de

mieux apprécier l’hétérogénéité des EV dans des concentrés plaquettaires (CP)

servant à la transfusion.

Un second objectif était d’évaluer si les EV de plaquettes contenant des

mitochondries pouvaient représenter un réservoir d'ADN mitochondrial, DAMP

reconnu et présent dans de nombreuses conditions inflammatoires. Notre hypothèse

est que les EV de plaquettes contenant des mitochondries peuvent être un réservoir

d’ADN mitochondrial et que cet ADN mitochondrial peut être utilisé pour évaluer le

risque d’incident transfusionnel des PC.

Un troisième objectif était de vérifier si le protéasome, ainsi qu’une machinerie

fonctionnelle pour l'apprêtement et la présentation de l'antigène sont transférés dans

les EV de plaquettes. Notre hypothèse est que les EV de plaquettes contiennent un

protéasome fonctionnel et que le protéasome confère aux EV de plaquettes un rôle

dans l’immunité.

44

Dans l’ensemble, les objectifs ont été atteints et nous avons démontré que les EV

de plaquettes ont un rôle dans l’inflammation et l’immunité avec leur contenu en

mitochondries et en protéasome.

45

Chapitre 1: Revealing the diversity of extracellular

vesicles using high-dimensional flow cytometry

analyses.

2.1 Résumé

Les vésicules extracellulaires (EV) produites par les cellules activées ou

apoptotiques sont hétérogènes et cette diversité pourrait permettre leur utilisation

comme biomarqueur. Malgré les progrès concernant l’amélioration des techniques

d’isolation et de caractérisation des EV, leur analyse par cytométrie en flux est

encore limitée concernant leur séparation du bruit de fond de l’appareil et l’analyse

de plusieurs paramètres conjoints. Nous avons appliqué l’algorithme SPADE à

l’analyse de nos EV par cytométrie en flux à haute sensibilité. Celui-ci nous a permis

d’organiser les sous-populations d’EV de plaquettes et de globules rouges et

d’apprécier leur hétérogénéité en plus de mettre en évidence des sous-types de

patients arthritiques selon la composition des EV présentes dans leur liquide

synovial. Notre étude a révélé que l’utilisation d’algorithmes couplés à la cytométrie

en flux tels que SPADE pourrait faciliter la compréhension des fonctions des EV et

le développement de leur étude comme biomarqueurs.

46

Revealing the diversity of extracellular vesicles using high-dimensional flow

cytometry analyses

Geneviève Marcoux1, Anne-Claire Duchez1, Nathalie Cloutier1, Patrick Provost1,

Peter A. Nigrovic2 & Eric Boilard1

1 Centre de Recherche du Centre Hospitalier Universitaire de Québec, Faculté de

Médecine de l’Université Laval, Département de microbiologie et immunologie,

Québec, QC, Canada, G1V 4G2

2 Centre de Recherche du Centre Hospitalier Universitaire de Québec, Faculté de

Médecine de l’Université Laval, Département de Psychiatrie et Neurosciences,

1Centre de Recherche du Centre Hospitalier Universitaire de Québec, Faculté de

Médecine de l’Université Laval, Département de microbiologie et immunologie,

Québec, QC, Canada.

2Department of Medicine, Division of Rheumatology Immunology and Allergy,

Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA.

Corresponding author:

Eric Boilard, PhD

Centre de Recherche en Rhumatologie et Immunologie

Centre de Recherche du Centre Hospitalier Universitaire de Québec

Faculté de Médecine de l’Université Laval

2705 Laurier Blvd., room T1-49

Québec, QC

Canada G1V 4G2

E-mail: [email protected]

47

2.2 Abstract

Extracellular vesicles (EV) are small membrane vesicles produced by cells upon

activation and apoptosis. EVs are heterogeneous according to their origin, mode of

release, membrane composition, organelle and biochemical content, and other

factors. Whereas it is apparent that EVs are implicated in intercellular

communication, they can also be used as biomarkers. Continuous improvements in

pre-analytical parameters and flow cytometry permit more efficient assessment of

EVs; however, methods to more objectively distinguish EVs from cells and

background, and to interpret multiple single-EV parameters are lacking. We used

spanning-tree progression analysis of density-normalized events (SPADE) as a

computational approach for the organization of EV subpopulations released by

platelets and erythrocytes. SPADE distinguished EVs, and logically organized EVs

detected by highsensitivity flow cytofluorometry based on size estimation,

granularity, mitochondrial content, and phosphatidylserine and protein receptor

surface expression. Plasma EVs were organized by hierarchy, permitting

appreciation of their heterogeneity. Furthermore, SPADE was used to analyze EVs

present in the synovial fluid of patients with inflammatory arthritis. Its algorithm

efficiently revealed subtypes of arthritic patients based on EV heterogeneity

patterns. Our study reveals that computational algorithms are useful for the analysis

of high-dimensional single EV data, thereby facilitating comprehension of EV

functions and biomarker development.

48

2.3 Introduction

Extracellular vesicles (EV) are small membrane vesicles released by cells into the

extracellular milieu. They are subdivided into three major groups, primarily based on

the process underlying their release. Exosomes are produced by exocytosis of

multivesicular bodies and have a diameter that ranges between approximately 50-

150 nm. Microvesicles (MV), also termed microparticles or ectosomes, are vesicles

of approximately 100–1000 nm in diameter generated by cytoplasmic membrane

budding and fission. Apoptotic bodies are released by apoptotic cells and generally

possess dimensions larger than 1000 nm1–3. However, it should be noted that these

definitions are still subject to change, as larger exosomes (up to 250 nm) have been

described, and apoptotic cells also release exosome-like vesicles3,4. Hence, the term

EV is increasingly utilized, as it more liberally encompasses all vesicle types

released by cells.

As EVs carrying components from donor cells can be internalized by cellular

recipients, they are implicated in intercellular communication5–7. Eukaryotic, and

prokaryotic cells produce EVs, suggesting that this mechanism is well-conserved

throughout evolution, which points to its significance. Furthermore, EVs are induced

by cell activation, and EV levels in biological fluids are altered in different

pathologies, such as cancer, rheumatic diseases, neurodegenerative disorders,

organ damage, and infectious diseases2,3,8. Hence, EVs appear to be potent

biomarkers, and their detection in blood and other biological fluids is improving with

the recent establishment of pre-analytical conditions, standardization of

quantification approaches, and development of more efficient means of detection9–

15.

EVs (more specifically MVs) have been described in the blood of healthy individuals.

They mainly comprise MVs derived from platelets and red blood cells (RBC)16–19.

Cell surface markers allow the cellular origin of MVs to be distinguished as CD41a

and CD235a are detected on the surface of platelets and RBC MVs, respectively.

49

Studies show that megakaryocytes (MK) can also generate CD41a+-MVs, and that

MVs in blood derived from MKs can be distinguished from those of platelets by

surface expression of P-selectin (CD62P), lysosomal-associated membrane protein

1 (LAMP-I) and immunoreceptor-based activation motif (ITAM) receptors16,20,21.

Thus, cell lineage markers provide useful information for determining the cellular

source of EVs.

EV heterogeneity is further complicated by the presence or absence of other

components. Phosphatidylserine (PS) exposure by EVs, which permits identification

of the latter with probes conjugated to PS-binding proteins such as annexin V and

lactadherin, can in fact appear undetectable on a substantial proportion of EVs16,22–

24. EV subpopulations may contain active proteasome, organelles (e.g.

mitochondria), and may undergo post-translational modification in disease, such as

citrullination in inflammatory arthritis4,16,23,25–27. Furthermore, EVs are decorated with

autoantibodies in autoimmune diseases such as systemic lupus erythematosus

(SLE) and rheumatoid arthritis (RA)16,23,28, and different platelet stimuli were shown

to trigger release of different EV subpopulations18,24. In summary, EVs are highly

heterogeneous, and the recognition of EV subtypes is necessary for the

comprehension of EV functions and consistent design of biomarkers.

Seminal research has established optimal pre-analytical conditions for the

preparation of samples for EV analyses12,29,30. Flow cytometry (FCM) remains the

most convenient methodology for assessment of EVs in biological fluids, especially

when a large sample number is analyzed, and when further characterization is

required using multiple markers on hundreds of thousands of EVs simultaneously.

Whereas traditional flow cytometers were not designed for the detection of such

small vesicles, the recent development of high-sensitivity FCM (hs-FCM) has greatly

improved investigators’ capabilities of analyzing EVs and developing biomarkers

based on EV heterogeneity10,12,13,15,23.

However, even with up-to-date approaches for the detection of EVs, investigators

50

are left with tremendous amounts of high-dimensional datasets that are impossible

to interpret using traditional gating on bivariate dot plots. Furthermore, with more

powerful methods of detection, distinguishing potentially relevant, but rare,

subpopulations of EVs from the generally important non-specific background is a

recognized issue12. There is currently no study that reports a means of facilitating

interpretation of flow cytofluorometric analyses of EVs. Thus, with the rapidly growing

improvements in detection technologies, and recognition of the vast heterogeneity

of EVs, the development of methods to objectively interpret multiple single-EV

parameters is urgent. Scientists implicated in the study of EVs are, of course, not

the first to face this sort of challenge. For instance, in immunology, an understanding

of the functions of discrete immune cells has evolved greatly since the discovery of

the different immune cell subtypes. It is now well-accepted that T lymphocytes are

heterogeneous and plastic, with CD4 and CD8 expression, and the identification of

several subtypes such as Th1, Th2, Th17, regulatory T cells and follicular-helper T

cells31. Moreover, dendritic cells32,33, monocytes, macrophages34 and

neutrophils35,36 are subdivided into different classes based on surface receptor

expression and density. From this perspective, traditional methods to analyze

multidimensional single-cell data are inadequate, as they are subjective and

restricted to our actual knowledge of the cellular phenotypes.

Spanning-tree progression analysis of density-normalized events (SPADE) is a

versatile computational approach that can be applied to mass and FCM data37.

SPADE does not require manual gating, which is considered more subjective37,38,

and allows the visualization of rare cell types, which would be lost or simply excluded

if they were unexpected. Also, it provides a global overview of cellular heterogeneity

by showing a continuity of phenotype, instead of clustering events in an independent

and strictly-defined population. Those features were successfully used to

characterize cell populations in different contexts37,39–43. In this present study, we

successfully used SPADE algorithms to build an EV hierarchy for the appreciation

of EV diversity in biological fluids.

51

2.4 Methods

2.4.1 Ethics

The study was approved by the medical ethics committee of CHU de Québec and

Université Laval. Methods were carried out in accordance with the approved

guidelines. Platelets and RBC were obtained from the citrated blood of healthy

human volunteers under informed consent according to a protocol approved by an

Institutional Review Board (Centre de Recherche du Centre Hospitalier Universitaire

de Québec). Synovial fluid (SF) was obtained from volunteers with rheumatoid

arthritis (RA) with approval of the ethic committee (Brigham and Women’s Hospital)

and under informed consent.

2.4.2 Platelets

Platelets were isolated after centrifugation of blood (282 x g for 10 min) at room

temperature (RT). Platelet-rich plasma (PRP) was obtained after an additional

centrifugation of the supernatant at 600 x g for 3 min at RT. The supernatant was

then centrifuged at 1,300g for 5 min at RT and the platelet-containing pellet was

resuspended in Tyrode’s buffer (pH 7.4). Platelets were counted (Cellometer

AutoM10; Nexcelom Bioscience) and adjusted to a density of 100 x 106 cells/ml in

Tyrode’s buffer (pH 7.4). For platelet EVs, platelets were stimulated with thrombin

(0.5 U/ml, Sigma) for 1 h at 37 °C after addition of 5 mM of calcium. Platelet activation

was stopped by addition of 20 mM of EDTA, and remnant platelets were removed

by centrifugation at 1,300 x g for 5 min at RT, performed twice.

2.4.3 Platelet-free plasma (PFP)

PRP from healthy volunteers was prepared as above without any stimulation and

was centrifuged at 2,500 x g for 20 min at RT. Then, the supernatant was centrifuged

twice at 3,200 x g for 5 min when platelet-free plasma (PFP) was required.

2.4.4 Red blood cells (RBCs)

Red blood cells were isolated after centrifugation of blood (282 x g for 10 min at RT).

52

Platelet-rich plasma and buffy coat fractions were eliminated to conserve the RBC

pellet. Red blood cells were counted (Cellometer AutoM10), adjusted to a density of

100 x 106 cells/mL in Tyrode’s buffer (pH 7.4) and contained less than 0.004% (n =

3) contaminating platelets. For RBC EVs, 200 μL of this preparation was added to

50 ml of distilled water (filtered through a 0.22-μm membrane) for 5 min, and 5 ml of

PBS 10X (filtered through a 0.22-μm membrane) was then added to stop the

hypotonic reaction. Remnant RBC were removed by centrifugation at 1,300 x g for

5 min at RT13.

2.4.5 Characterization of EVs

Hs-FCM approach. All the analyses were performed on a BD Canto II Special Order

Research Product (BD Biosciences) equipped with a small particle option, as

described previously13,23. The forward scatter (FSC) on this dedicated equipment is

coupled to a photomultiplier tube (PMT) with a 488 nm solid state, 100 mW output

blue laser (rather than the conventional 20 mW), and includes a 633 nm HeNe, 20

mW output red laser and a 405 nm solid state diode, 50 mW output violet laser. The

hs-FCM includes an FSC-PMT and a Fourier optical transformation unit, which

reduces the background/noise and increases the angle of diffusion, thereby

enhancing the detection of small-diameter particles.

FCM performance tracking was performed daily before all analyses using the BD

cytometer setup and tracking beads (BD Biosciences, San Jose, CA, USA). The

assigned voltage for FSC-PMT was 300 volts (V). For side scatter (SSC), the

assigned voltage was 460 V and the threshold was 200. Voltage was set to 360 V

for FITC, 450 V for PE-Cy7, 500 V for Deep Red (or APC), 500 V for PE, 500 V for

Alexa Fluor 700 (used only for the counting beads) and 305 V for V450. Acquisition

was performed at low speed (~10 μL/min) and, to remain quantitative, a known

quantity of (fluorescent) polystyrene microsphere (15-μm diameter: Polysciences,

PA, USA) was added to each tube, and a constant number of beads detected on the

basis of (auto) fluorescence was acquired for each sample throughout all the study.

Silica particles (Kisker Biotech GmbH & Co. Steinfurt, Germany) of known

53

dimensions (100 nm, 500 nm and 1 μm in diameter) were used for instrument set-

up standardization13,23. Fluorophores implicating distinct lasers were intentionally

chosen to minimise compensation. For every performed experiment, the only

necessary compensation was 5.00% for APC-V450.

Detection of platelets, RBCs and EVs by flow cytometry. Platelets and EVs were

prepared as above and 5 μL per sample was labeled in a total reaction volume of

100 μL (as indicated in Table S1) at 37 °C for 30 min. Then, the sample was diluted

by adding 400 μL of the labeling buffer prior analysis by hs-FCM. RBC-derived

samples were labeled as described above with the exception of MitoTracker, which

was omitted given the known absence of mitochondria in RBCs. For Triton or EDTA

treatment, samples (5 μL) were incubated 30 min at RT with 0.05% Triton X-100 or

50 μM EDTA (with PBS instead of Annexin V buffer for EDTA) before labeling. For

the ultracentrifugation treatment, samples were centrifuge at 100 000 g x 1 h at 20

°C to pellet EVs, and the supernatant was labeled as presented above.

Plasma EV diversity with overlapping staining panels. EVs contained in platelet-

free plasma (5 μL for 100 μL reaction) were labeled as indicated in Table S1 with the

four different cocktails (5a, b, c and d). The reaction was stopped by adding 400 μL

of the labeling buffer.

EV diversity in RA synovial fluid. Freshly obtained SF, collected without

anticoagulant, was centrifuged at 1,900 x g for 30 min at 4 °C to remove leukocytes

and then stored at − 80 °C. EVs present within the SF (5 μL for 100 μL reaction)

were labeled as indicated in Table S1 and the reaction was stopped by adding 400

μL of the labeling buffer.

Immunoblotting. Cells were pelleted at 1,300 x g for 5 min: EVs derived from

platelets and RBC and those present in plasma were centrifuged at 18,000 x g for

90 min5 and processed in lysis buffer (20 mM Tris HCl pH 7.8, 1.25 mM EDTA, 0.5%

Triton X-100, 0.5% NP-40, 120 mM NaCl, 2 mM phenylmethylsulfonyl fluoride.

54

Lysate protein content was measured using a bicinchoninic acid protein assay kit

(Fisher). Proteins (10 μg) were separated by 10% SDS-PAGE, transferred to a

polyvinylidene difluoride membrane and the candidate proteins were detected using

antibodies against platelet MV marker CD41a (Abcam used at 1/1,000), an enzyme

reportedly present in platelet MVs; 12-lipoxygenase (12LO) (Santa Cruz, used at 1

μg/ml); cytoskeleton marker β-actin (Sigma, clone AC-15 used at 1/15,000); the EV

markers, tumor susceptibility 101 (TSG101)(Abcam, clone 4A10 used at 0.1 mg/ml)

and ALG-interacting protein X (ALIX) (Santa Cruz, clone 3A9 used at 1 μg/ml); the

RBC marker CD235a (Santa Cruz, clone YTH89.1 used at 1 μg/mL); and the

mitochondrial markers, voltage-dependent anion channel (VDAC) (Cell Signaling,

used at 11.6 μg/ml) and translocase of outer mitochondrial membrane TOMM-22

(Abcam, used at 2.5 μg/ml)5,44. The PVDF membranes were incubated with

peroxidase-conjugated antibodies recognizing the primary antibodies (Jackson

ImmunoResearch, used at 0.08 μ g/ml).

Size analysis. Silica beads were diluted 1/100 in PBS 1X (filtered through a 0.22-

μm membrane) and analyzed by Zetasizer Nano S (Malvern Instruments, Ltd.,

Malvern, UK).

2.4.6 Statistical analyses

The results are presented as mean ± SEM, and were analyzed with Prism 6

(GraphPad Software, CA, USA).

2.4.7 SPADE analyses

The pre-compiled standalone version of SPADE-3 for Mac without Matlab was

downloaded at http://pengqiu.gatech.edu/software/SPADE/. FCS files were

exported from BD FACSDiva™ software (BD Bioscience) in FCS 3.0 format and

analyzed using FlowJo (FlowJo, LLC, OR, USA) software to exclude counting beads

and events with dimensions smaller than 100-nm silica beads. Specific details for

each SPADE analysis are provided within the results section.

55

2.5 Results

2.5.1 Optimization and validation of high sensitivity flow

cytofluorometric methods for the detection of EVs.

In the first set of experiments, we validated that platelets, RBC, and their daughter

EVs, were efficiently resolved by hs-FCM. EVs were not pelleted prior to hs-FCM

analyses, given the reported deleterious impact of this procedure on EV integrity45.

Furthermore, as one goal of this study was to appreciate EV diversity, we chose to

maintain the complexity of our EV preparations by avoiding exosome and MV

enrichment. Therefore, EV preparations comprised a mixture of exosomes and MVs

derived from platelets and RBC, and the hs-FCM conditions were optimally designed

to detect EVs larger than 100 nm silica beads.

Given that size is a factor of interest in these analyses, we used microspheres of

known dimensions to standardize the instrument setup. Whereas polystyrene

microspheres are frequently utilized for the determination of size, their refraction

index (1.59) differs considerably from that of membrane vesicles (1.39)13,46,47.

Hence, while size, shape, surface roughness, granularity and the angle of collection

impact light scattering, the intensity of the scattered light greatly depends on the

refraction index for particles with dimensions smaller than the wavelength of light (in

this case 488 nm). Thus, for our analyses, we used silica beads, which have a

refraction index (1.42)13,46,47 closer to that of membrane vesicles, to establish the

lower limit of the EV gate, and we included intact platelets and RBC to ensure that

they were efficiently distinguished from their respective daughter EVs.

We validated that silica microspheres ranging from 100–1000 nm in diameter (Fig.

1A) were efficiently resolved by hs-FCM (Fig. 1B). Resting platelets were as

expected larger than 1000 nm silica beads (Fig. 1C)48. To generate platelet EVs,

platelets were triggered by thrombin and remnant platelets were removed by

centrifugation. In these preparations, platelets were undetectable (Fig. 1D), and

56

platelet EVs were detected by hs-FCM (Fig. 1E), and were clearly distinguishable

from intact platelets (compared to Fig. 1C). As expected, RBC (mean diameter

between 7–8 μ m) appeared much larger than platelets in our hs-FCM analyses (Fig.

1F), and were triggered to release EVs by osmotic shock. RBCs were largely absent

from EV preparations (Fig. 1H). RBC EVs were efficiently distinguished from intact

RBC (Fig. 1H), although they displayed apparent larger dimensions than platelet

EVs in hs-FCM (compared to Fig. 1E). This observation will not be investigated

further in the present study. Thus, small EVs are detected in our hs-FCM analyses.

Fluorochrome-conjugated probes and antibodies can form submicron aggregates in

solution, which can be mistakenly interpreted as EVs by hs-FCM49. Furthermore,

multiple EVs can be detected simultaneously if present at a too elevated

concentration or analyzed at high acquisition speed, a process called coincidence

or swarm that compromises the interpretation of EV multicolor labeling47. To ensure

that genuine EVs were detected, and that no signals arose from aggregated

fluorochromes, we used an established detergent assay49,50. Under these

conditions, the membrane moiety of the EVs is dissolved by Triton X-100 treatment

while protein aggregates are left intact13,23,49,50. In addition, the specificity of PS

recognition by annexin V-conjugated fluorochromes, which is a calcium-dependent

event, was confirmed by calcium chelation using EDTA13,22. As EVs can be pelleted

by centrifugation, we also verified that no EVs were detected in fluids after

ultracentrifugation.

Platelet EVs may contain mitochondria, and can express surface CD41a and PS5,25.

Thus, platelet EVs, detected by a combination of mitochondrial dye MitoTracker,

anti-CD41a antibody and annexin V (Fig. 2A), were treated with detergent (Fig. 2B),

or EDTA (Fig. 2C). Furthermore, all the fluorescent probes were incubated with fluids

that underwent ultracentrifugation (Fig. 2D). Under these conditions, the vast

majority of EVs positive for CD41a (Fig. 2B,D,E), MitoTracker (Fig. 2B,D,F), and

annexin V (Fig. 2G), were eliminated by detergent and centrifugation. Conversely,

EDTA primarily affected annexin V labeling (Fig. 2G), with only a modest impact on

57

CD41a (Fig. 2C,E) and MitoTracker signals (Fig. 2C,F), thereby validating the

specificity of our multicolor labeling of platelet EVs and further confirming the

heterogeneity of EVs.

We next verified the absence of coincidence in our hs-FCM conditions and validated

our quantitative strategies. In the absence of coincidence, the concentration of EVs

should be reduced according to dilution factors, while the mean fluorescence

intensity should remain constant13. We confirmed the lack of coincidence, as the

concentrations of EVs positive for CD41a (Fig. 2H), MitoTracker (Fig. 2K) and

annexin V (data not shown for platelet EVs) were consistently reduced without any

impact on the mean and median fluorescence intensity (Fig. 2I,J,L,M). Using anti-

CD235a and annexin V-conjugated probes, we also confirmed the specificity of our

signals and the absence of coincidence in our flow cytofluorometric acquisitions of

RBC EVs (Figure S1).

Depending on their mechanism of release, EVs may contain distinct sets of proteins

and organelles44. Of note is that immunoblotting confirmed that our EV preparations

contained proteins reportedly present in EVs5,25,44. As expected, CD235a was

absent in EVs derived from platelets, whereas the surface protein CD41a, the

cytosolic platelet 12-LO, the cytoskeleton protein actin, the EV proteins TSG101 and

ALIX, and the mitochondrial proteins VDAC and TOMM-22 were detected in platelet

EVs. CD41a, platelet 12-LO, and mitochondrial markers were absent in RBC EVs,

whereas cytoskeleton and EV markers were detected (Figure S2). Together, these

observations confirm that our strategies are optimal for the establishment of optimal

high-dimensional dataset analyses of EVs.

2.5.2 Analysis of RBCs, platelets and their EVs using SPADE

Contrary to traditional gating analysis, where gates must be manually designed,

SPADE uses topological methods to reveal distinct populations of cells from high-

dimensional data sets37,38,43, and also equally represents rare and abundant cell

types (and potentially EVs). This is important, because rare, but biologically relevant

58

EVs, might be masked if outnumbered by background or noise; a particularly

frequent issue in FCM analyses of EVs. Events (e.g. cells, or potentially EVs here)

that share similitudes on the basis of marker expression are clustered within the

same node. Each node can be colored according to their median intensity for a given

marker expression (low to high; blue to red, respectively) and the size of the node

reflects the number of events that it contains43. Nodes that belong to the same

branch on the tree are more likely to be related to each other than nodes found on

different branches, and the length of the branches is determined automatically by

the program43. Thus, using multiple fluorescent markers, in addition to lightscatter

(FSC-PMT and SSC), it might become possible to identify groups of EVs that are

similar with respect to each measured parameter.

RBCs, platelets, and their respective EVs generated in vitro, as above (n = 3 blood

donors), were detected by hs-FCM on the basis of expression of CD41a, CD235a,

PS exposure, mitochondrial content, size (FSC-PMT) and inner complexity (SSC).

FCS files were pre-analyzed to exclude counting beads (Fig S3A) and events smaller

than 100 nm silica beads (Figs S3B and 1B). The files were used to build the SPADE

tree with the following markers: FSC-H (for cells), FSC-PMT-H, SSC-H, MitoTracker-

H, CD41a-H, CD235a-H and annexin V-H. An inverse hyperbolic sine transformation

with cofactor 150 was applied in order to scale the data, and the maximum allowable

cells/EVs in the pooled down-sampled data was set to 50,000. The outlier was set

to the 1st percentile of local densities and the target density was set such that a fixed

number of 20,000 cells would remain. The number of desired clusters was 200, as

a high EV heterogeneity was expected, and the K-means algorithm was chosen as

the clustering parameter.

Using the semi-automated annotation tool (button “Auto Suggest Annotation”), which

relies on all markers used to build the tree, a tree was automatically generated (Fig.

3A), distinguishing 10 sub-populations (namely 1–10). The first autosuggestion

revealed a strong difference in CD235a expression, size and inner complexity, and

isolated the CD235a (RBCs) high branch (1–3) from the rest of the tree. A second

59

autosuggestion highlighted a subpopulation (6) presenting high expression of

CD41a, MitoTracker, SSC, FSC and FSC-PMT, which correspond to platelets. The

three subsequent autosuggestions revealed PS-expressing EVs produced from

platelets (9–10) and from RBCs (3), which were also smaller than their mother cells.

As (1–2) subpopulations showed a homogeneous distribution for every marker

except for CD235a expression, the software suggested division of this branch into

two. Autosuggestions also distinguished mitochondria-containing EVs that did not

present RBC (CD235a−) or platelet (CD41a−) markers (subpopulation 8),and allowed

the partition of subpopulations (9–10) according to CD41a, MitoTracker and PS

expression. It is important to note that these populations were objectively identified

without any gating or prior knowledge. Only subpopulations (4) and (7) were drawn

manually, mainly because of their bright intensities in distinctive markers.

The (1–10) subpopulations were then annotated, and the SPADE tree was

interpreted. Subpopulation (1) includes cells (high intensity for FSC-PMT-H, FSC-H

and SSC-H) that were not RBCs (low expression of CD235a) or platelets (low

expression of CD41a), potentially representing a low number of contaminating

leukocytes or RBC ghosts generated by RBC activation. Subpopulation (2) contains

RBCs, which show high intensity for FSC-PMT, FSC and SSC and also high

expression of CD235a markers, but low expression of CD41a. Subpopulation (3)

contains RBC EVs with intermediate intensity for FSC-PMT, FSC and SSC, high

expression of CD235a and low expression of CD41a. All RBC EVs detected in those

samples exposed PS (high intensity for annexin V expression). With a low

expression of all 7 markers, the (5) subpopulation was annotated as background,

although it might also contain EVs left unidentified using this set of markers.

Subpopulation (6) contains platelets, which show relatively high light scatter for FSC-

PMT, FSC and SSC and expression of CD41a and MitoTracker. Subpopulation (8)

showed low expression of all markers except for MitoTracker, suggesting that they

might be naked mitochondria or mitochondria encapsulated in EVs lacking

expression of CD41a. Subpopulations (7, 9 and 10) represent platelet EVs

(intermediate CD41a expression and SSC, low CD235a expression and low light

60

scatter for FSC-PMT and FSC). Subpopulation (4) includes EVs with variable

expression levels of CD41a (low to high), with those presenting the brightest CD41a

intensity representing 1,15+/-1,99% of this subpopulation (data not shown).

Subpopulation (10) includes EVs containing mitochondria (high MitoTracker

expression), with variable exposure of PS (intermediate to high intensity annexin V

binding). More than 40 classical analyses with bivariate plots were necessary to

interpret the data (Fig. 3B–E). These observations confirm that upon treatment by

SPADE analyses, homogeneous EV subpopulations were identified, and further

highlight the complexity of analyzing high-dimensional flow cytometry data without

appropriate computerized tools.

2.5.3 Analysis of platelet response to thrombin stimulation using

SPADE

EV production is evidence of cellular activation or apoptosis. Thus, the SPADE

analysis as above was used to appreciate the platelet response to thrombin

stimulation (Fig. 4). Both resting and activated platelets were portrayed in the

constructed tree. The fold-change in subpopulation frequencies varied upon

activation (i.e. red, increase; blue, decrease), indicating that platelet EV

subpopulations (9–10), and extracellular mitochondria (8), were produced, while

platelets (6) lost their dominance. Background/debris (5) varied following the

stimulation, pointing to the generation of debris following platelet activation or the

presence of unidentified EVs using this set of markers. These observations confirm

the ability of SPADE to distinguish cell and EV populations, and to appreciate cellular

plasticity and EV biogenesis in response to stimuli.

2.5.4 Generating overlapping panels in plasma EV analyses.

SPADE also permits the integration of multiple staining using overlapping marker

panels (cocktail 5a-d in Table S1). For these experiments, we evaluated endogenous

EVs present in healthy human platelet-free plasma samples and generated a new

tree. The overlapping markers CD41a, MitoTracker, FSC-PMT and SSC, were

present in every condition, and we also included annexin V, CD62P, GPVI and

61

CLEC-2 as interchangeable markers within the tree (Fig. 5)16,20,21. FCS files were

exported and analyzed as above. The SPADE parameters were the same except for

the target densities that were fixed to 10,000 cells/EVs. Platelet-derived EVs (high

CD41a expression) were mostly located at the bottom of the tree (the lower branches

1–3), some of them expressing GPVI and CLEC-2 (branches 1,2). Of note was that

theupper part of the tree (CD41a−) also revealed high expression of GPVI and CLEC-

2 on EVs (branches 7–9). Thus, the SPADE algorithm provides analyses of high-

dimensional data that is scalable with an increasing number of markers useful for

EV analysis. Furthermore, these data demonstrate that SPADE can identify

subpopulations, like the presence of three subpopulations of platelet-derived EVs

that could have been overlooked with classical dot plot analyses.

2.5.5 SPADE for the appreciation of EVs as biomarker in disease.

Different cellular lineages contribute to EV accumulation in the synovial fluid (SF) of

RA patients. Platelet-derived EVs have been identified in RA SF5,13,25,51,52, and

present with heterogeneous dimensions and mitochondrial content (Fig. 6A). We

quantitatively identified EVs in the SF of 20 RA patients on the unique basis of 4

markers (i.e. CD41a, MitoTracker, FSC-PMT and SSC) to generate a new SPADE

tree (Fig. 6A). SPADE parameters were the same as in the first tree (Figs 3 and 4)

with the exception that 150 clusters were used instead of 200 given the reduced

number of parameters measured. Using the autosuggestion tool to objectively

identify EV subpopulations, two major subpopulations were revealed: i.e. CD41+,

MitoTracker− and CD41+, MitoTracker+ EVs. SPADE tree highlighted the great

variability between RA patients, as some EV subtypes appeared to be completely

absent (empty nodes in white) in some patients (Fig. 6B,C). These differences in EV

expression patterns did not seem to correlate with rheumatoid factor (RF) and anti-

citrullinated protein auto-antibody (anti-CCP) levels (Table S2). These data suggest

that EV pattern recognition using the objective analysis tool SPADE can highlight

differences in EV content in disease, providing a tool for the determination of potent

biomarkers in disease.

63

2.6 Discussion

The emergence of EVs as important players in intercellular communication has

opened the way to intensive research on this topic. EV levels are modulated in

certain pathologies, and studies have established the vast diversity of EVs produced

by cells, suggesting that EVs might be used as biomarkers2,7. Groups of scientists

have established the most appropriate pre-analytical conditions for the study of EVs

and for the design of modern methodologies for their fine characterization3,9–

11,13,14,17,18,26,27,29,30,48–50. Furthermore, efforts have been made in recent years to

institute a coherent nomenclature for EVs44. Not withstanding these major

improvements, it remains an obvious challenge to objectively interpret the large

quantity of high-dimensional data in EV analyses. For instance, although

fluorescence, rather than light scatter, used as trigger greatly improves EV detection,

the distinction of EVs from background in FCM is still an obstacle in complex

fluids12,13,17. Furthermore, platelets are abundant in blood and represent an important

source of EVs; however, they are frequently misinterpreted as EVs given their

relatively small dimensions11. The absence of such analytical tools for the

comprehension of EV functions prompted our study.

SPADE offers the advantage of using an encompassing panel of markers to cluster

the data, which allows the identification of rare cell types and facilitates new,

unanticipated, biological discoveries37,38. Our study shows that SPADE is a versatile

computerized tool to objectively handle hundreds of thousands of hs-FCM EV data

and to reveal unpredicted EV subtypes. Most importantly, SPADE can be utilized for

the analysis of EV data obtained with any flow cytometer, assuming that EVs are

detected correctly. Whereas there exist other algorithms (other than SPADE)

available for the interpretation of FCM data53, SPADE is among the most appropriate

to reveal rare subpopulations of events by flow cytometry37,38,43. Investigators,

however, need to compare trees from one condition to another to identify changes

in nodes between conditions, which can be challenging if FCM based biomarkers

are examined in multiple patients, for example. Future improvements to these

64

applications by engineers in the field might include high throughput tree comparison.

SPADE permitted the establishment of a tree that portrays EVs from platelets and

RBC, the two main sources of EVs reported in blood. Of interest is that SPADE

successfully recognized platelet activation based on platelet-derived EV production,

suggesting that it might be used as a tool to assess EV-based cellular perturbations.

Unanticipated subpopulations of EVs present in plasma were revealed by a second

SPADE analysis with overlapping markers. Prior studies revealed that the majority

of the platelet-derived EVs in blood in fact originate from MKs, the cells from which

platelets are produced16,20. The immunoreceptor-based activation motif (ITAM)

receptors GPVI and CLEC-2 were reported absent on the surface of platelet-derived

EVs, but were found on the surface of (MK)-derived EVs, which also express

CD41a16,20,21. Whereas SPADE might have revealed MK-derived EVs in plasma

(CD41+ GPVI+ CLEC-2+ EVs), it unexpectedly shed light on CD41−-EVs expressing

GPVI and CLEC-2. Although the functions of these EVs remain to be established,

we hypothesize that these EVs might also originate from MKs. As for any data

interpretation implicating flow cytometry, complementary approaches, such as

electron microscopy, functional assays and biochemistry, should be utilized to

confirm the actual presence of novel populations of EVs and to verify their biological

significance.

The analysis of EVs contained in bio-specimens from disease patients permits the

identification of biomarkers. With a rather simple analysis that included assessment

of CD41a and mitochondrial content in EVs from 20 patients, a third SPADE analysis

highlighted the heterogeneity that prevails in RA. The possibility to extract the

number of events in each node for all patients, similarly to the exportation of statistics

in traditional gating, allows a relatively easy comparison between patients. RA

patients with higher EV diversity were usually those with higher platelet EV

concentrations, pointing to a more important platelet contribution to the pathology in

those patients. As it is suggested that platelet EVs invade the synovial space due to

enhanced joint vascular permeability54, it might also provide information on the

65

integrity of the vasculature in these patients. RA patients have enhanced risks of

death due to cardiovascular disorders. Future studies might determine if increased

levels of EV subtypes are an indication of certain comorbidities (other than those

that were presented in Table S2) or impact response to different treatment in RA.

Furthermore, we suggest that the combination of these approaches might be used

for a qualitative and a quantitative stratification of patients suffering from

heterogeneous diseases, such as RA and potentially other rheumatic diseases. In

this study, SPADE was applied to the analysis of high-dimensional data based on

EV detection. We suggest that this approach may be utilized for the assessment of

more numerous EV markers by FCM or mass cytometry. An in-depth understanding

of EV subtypes modelled as high-dimensional point clouds will accelerate the

implementation of EV subtypes as biomarkers and will facilitate the understanding

of their role(s) in different contexts such as coagulation, inflammation, cancer, and

immunity.

66

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centrifugation induces aggregation of extracellular vesicles. J Extracell Vesicles

4, 29509, doi: 10.3402/jev.v4.29509 (2015).

46 Chandler, W. L., Yeung, W. & Tait, J. F. A new microparticle size calibration

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7836.2011.04283.x (2011).

47 van der Pol, E., van Gemert, M. J., Sturk, A., Nieuwland, R. & van Leeuwen, T.

G. Single vs. swarm detection of microparticles and exosomes by flow

cytometry. J Thromb Haemost 10, 919–930, doi: 10.1111/j.1538-

7836.2012.04683.x (2012).

48 Parida, B. K., Garrastazu, H., Aden, J. K., Cap, A. P. & McFaul, S. J. Silica

microspheres are superior to polystyrene for microvesicle analysis by flow

cytometry. Thromb Res 135, 1000–1006, doi: 10.1016/j.thromres.2015.02.011

(2015).

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49 Gyorgy, B. et al. Detection and isolation of cell-derived microparticles are

compromised by protein complexes resulting from shared biophysical

parameters. Blood 117, e39–e48, doi: 10.1182/blood-2010-09-307595 (2011).

50 Inglis, H. C. et al. Techniques to improve detection and analysis of extracellular

vesicles using flow cytometry. Cytometry A 87, 1052–1063, doi:

10.1002/cyto.a.22649 (2015).

51 Gyorgy, B. et al. Improved flow cytometric assessment reveals distinct

microvesicle (cell-derived microparticle) signatures in joint diseases. PLoS One

7, e49726, doi: 10.1371/journal.pone.0049726 (2012).

52 Boilard, E. et al. Platelets amplify inflammation in arthritis via collagen-

dependent microparticle production. Science 327, 580–583, doi:

10.1126/science.1181928 (2010).

53 Aghaeepour, N. et al. Critical assessment of automated flow cytometry data

analysis techniques. Nat Methods 10, 228–238, doi: 10.1038/nmeth.2365

(2013).

54 Cloutier, N. et al. Platelets can enhance vascular permeability. Blood 120,

1334–1343, doi: 10.1182/blood-2012-02-413047 (2012).

72

2.8 Figures and legends

Figure 1. Characterization of extracellular vesicles.

(A) Size evaluation of silica beads by nanosizer based on dynamic light scattering. (B) Design of a lower EV gate by hs-FCM based on acquisition of silica beads of various sizes (100 to 1000 nm). (C) Portrayal of non-activated platelets (PLT). (D) Remnant platelets detected in the EV fraction (after stimulation) using a cell counter and FCM (< 2%). ND: not detected. (E) EVs from preparations cleared of any remnant platelets by centrifugations were analyzed by hs-FCM. Representative of 3 different donors. (F) Portrayal of RBCs analyzed by FCM. (G) Remnant RBCs detected in the EV fraction (after stimulation) using cell counter and FCM (< 16%). ND: not detected. (H) EVs from preparations cleared of any remnant RBCs by centrifugations were analyzed by hs-FCM. Representative of 3 different donors, *P < 0.05.

73

Figure 2. Detection of platelet EV subpopulations by hs-FCM.

(A) Representative SSC-H (granularity) and FSC-PMT-H (relative size) dot plots of platelet EVs detected using MitoTracker and fluorochrome-conjugated antibodies directed against CD41a in the absence of treatment (control). (B–D) FSC-PMT/SSC portrayals of platelet EVs detected with MitoTracker and antibodies directed against CD41a after treatment with 0.05% Triton X-100 (B) 50 μ M EDTA (C) or after clearance of EVs using ultracentrifugation (centri) (D). Total MitoTracker+ EVs are presented in the orange gate (middle panel), and their relative size and granularity is displayed in the upper panel. Total CD41a+ EVs are presented in the blue gate (middle panel), and their relative size and granularity is displayed in the lower panel. Data are representative of 3 independent experiments. (E,F) Sensitivity of CD41a

74

(E) MitoTracker (F) and annexin V (G) EVs to clearance by ultracentrifugation (centri), Triton and EDTA, presented as % of untreated (Ctrl). (H–M) CD41a+ and MitoTracker+ EVs were serially diluted twice (2-fold dilution) and quantitatively analyzed by hs-FCM using counting microspheres. Their concentration (H,K), the mean of fluorescence (I,L) and the median of fluorescence (J,M), are presented. Data are presented as mean ± SEM of 3 independent experiments, *P < 0.05 compared with the control (Ctrl); NS: Non-significant; Wilcoxon test.

75

Figure 3. SPADE analysis of human blood cells and EVs. (A) SPADE tree derived from RBC, platelets and EVs from healthy human blood cells using FCS files obtained by hs-FCM analyses. Each tree is colored according to the indicated marker. Mean fluorescence intensity ranging from low (blue) to high (red) was used to identify 10 different subpopulations (1–10) described in the text. (B–E) Events from the different subpopulations identified in trees were represented by classical analysis with bivariate plots showing (B) size and granularity, (C) CD41a and MitoTracker expression, (D) annexin V and CD235a expression or (E) CD41a and annexin V expression. (B) Arrow indicates highest cellular population in FSC-PMT-H and SSC-H. Data were generated using cells and EVs from 3 independent experiments. FCS data from the independent experiments were integrated by SPADE to generate trees.

76

Figure 4. SPADE tree to assess EVs in cellular perturbations.

After stimulation of platelets with thrombin, cell frequency decrease (blue) in platelets (6) and increase (red) in platelet EVs (9–10). Red blood cell markers (CD235a) (2,3), other cells (1), and noise/background (5) were mostly unchanged. Platelet CD41a+ EVs (9,10) and extracellular mitochondria lacking CD41a+ (8, naked mitochondria) were induced (red). Data are representative of 3 independent experiments.

77

Figure 5. SPADE overlapping panels for EV diversity in plasma.

EVs present in plasma were detected by hs-FCM, and FCS files were used to build a SPADE tree. Each tree is colored according to the indicated marker intensity. Mean fluorescence intensity ranging from low (blue) to high (red) for size (FSC-PMT-H), granularity (SSC-H), fluorescent-conjugated antibodies (CD41a−H, CD62P-H, GPVI-H, CLEC-2-H), MitoTracker and annexin V. Nine subpopulations were highlighted by manual identification based on the expression of the different markers, starting from the bottom of the tree: (1) Platelet EVs, positive for every marker (high intensity shown in red); (2) Platelet EVs positive for every marker except annexin V and CLEC-2 (low intensity shown in blue); (3) platelet EVs (CD41a high) with weak expression (shown in yellow) of MitoTracker and GPVI, and negative for annexin V, CD62P and CLEC-2; (4) EVs negative for CD41a, but positive for MitoTracker, annexin V and GPVI; (5) EVs presenting high expression of CD41a with low light scattering in FSC and SSC; (6) EVs with a weak expression of CD41a, negative for all other markers; (7) EVs negative for CD41a, and positive for all other markers, including activation markers (annexin V and CD62P); (8) EVs positive for every marker and presenting higher inner complexity (SSC-H) and (9) EVs negative for CD41a and presenting higher intensity in FSC-PMT. Data are representative of 3 independent experiments.

78

Figure 6. SPADE and EV-based biomarkers in disease.

(A) Platelet-derived EVs present in synovial fluid (SF) of rheumatoid arthritis (RA) patients were detected by hs-FCM and portrayed in a SPADE tree (n = 20). Each tree is colored according to the indicated marker. Mean fluorescence intensity ranging from low (blue) to high (red) for size (FSC-PMT-H), granularity (SSC-H), fluorescent-conjugated antibodies CD41a-H and MitoTracker. (B) Representative tree of 6 RA synovial fluids with high (upper trees) or low (lower trees) EV diversity. (C) Platelet EVs containing mitochondria (CD41a+ MitoTracker+) and those not containing mitochondria (CD41a+ MitoTracker−) were detected among the 20 RA patients tested. ****P < 0.0001 between high and low EV diversity, Mann-Whitney test.

79

2.8 Supplementary figures and legends

80

Supplementary Figure 1. Detection of RBC subpopulations by hs-FCM. (A) Representative SSC-H (granularity) and FSC-PMT-H (relative size) dot plots of RBC EVs detected using annexin V and fluorochrome-conjugated antibodies directed against CD235a in the absence of treatment (control). (b–d) FSC-PMT/SSC portrayals of RBC EVs detected with fluorochrome-conjugated annexin V and fluorochrome-conjugated antibodies directed against CD235a and treated with 0.05% Triton X-100, (B) 50 μM EDTA, (C) or after clearance of EVs using ultracentrifugation (centri)(D). Total annexin V+ events are presented in the green gate (middle panel) and their relative size and granularity is displayed in the upper panel. Total CD235a+ events are presented in the blue gate (middle panel) and their relative size and granularity is displayed in the lower panel. Data are representative of 3 independent experiments. (E–F) Sensitivity of CD235a (E) and annexin V (F) EVs to clearance by ultracentrifugation (centri), Triton and EDTA, presented as % of untreated (Ctrl). (G–L) CD235a+ and annexin V+ EVs were serially diluted twice (2-fold dilution) and quantitatively analyzed by hs-FCM using counting microspheres. Their concentration (G and J), the mean of fluorescence (H and K) and the median of fluorescence (I and L), are presented. Data are presented as the mean ± SEM of 3 independent experiments, *P < 0.05 compared with the control (Ctrl); NS : Non significant ; Wilcoxon test.

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Supplementary Figure 2. Protein content in cells and EVs from plasma, platelets and RBCs. Immunoblot of CD41a, ALIX, 12-LO, TSG101, actin, CD235a, VDAC and TOMM-22 in cells (C) and EVs (EV) from platelets (PLTs), red blood cells (RBC) and plasma. Data are representative of three independent experiments. Cells (C), EVs (EV).

82

Supplementary Figure 3. Initial gating before performing SPADE analysis. (A) After the acquisition of fluorescent signals, an initial gating was performed on all data to exclude counting beads from files. (B) After bead exclusion, a gate was drawn to include events over 100 nm in diameter (based on silica beads from Fig. 1B).

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2.9 Supplementary tables

Supplementary Table 1. Staining panels for the different SPADE trees*

Figure Antibody/label Suppliers Concentration Labelling buffer

3-4

V450-conjugated anti-human CD41a

BD Bioscience, clone HIP8

1 µL

Annexin V buffer (BD Pharmingen) pre-filtered through a 0.22-µm-pore-size membrane (Fisher Scientific, ON, Canada).

PE-Cy7-conjugated anti-human CD235a

BD Pharmingen, clone HIR2

3 µL

FITC-conjugated annexin V BD Pharmingen 3 µL

MitoTracker Deep Red (APC)** Life Technologies 100 nM

5a



1 µL

Annexin V buffer pre-filtered through a 0.22-µm-pore-size

membrane

MitoTracker Green (FITC) Life Technologies 100 nM

APC-conjugated anti-human C-type lectin receptor 2 (CLEC-2)

R&D System, clone 219133

10µL

5b



1 µL


membrane


PE mouse anti-human platelet glycoprotein VI (GPVI)

BD Pharmingen, clone HY101

1 µL

5c



1 µL Annexin V buffer pre-filtered through a 0.22-µm-pore-size

membrane MitoTracker Green (FITC) Life Technologies 100 nM

APC-conjugated annexin V BD Pharmingen 3 µL

5d



1 µL


membrane


APC-conjugated anti-human CD62P

BD Pharmingen, clone AK-4

3 µL

6

PE-conjugated anti-human CD41a


1 µL PBS pre-filtered through a 0.22-

µm-pore-size membrane MitoTracker Deep Red (APC) Life Technologies 100 nM

*All stainings were performed at 37°C for 30 minutes.

** MitoTracker was omitted for the RBC-derived samples.

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Supplementary Table 2. Demographic and clinical characteristics of RA patients. Synovial fluid is from affected joint (knee). Different parameters were measure as gender, age, Rheumatoid Factor (RF), anti-cyclic citrullinated peptide (CCP), erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), CD41+MitoTracker+ EVs and CD41+ EVs.

Gender Age

(years) RF Anti-CCP ESR (mm)

CRP level (mg/L)

CD41+MitoTracker+ EVs

CD41+ EVs

N/A N/A N/A N/A N/A N/A 3751 358

F 77 2720 N/A 90 17.4 11652 1671

F 75 67 N/A 22 20.5 2214 4296

F 78 2720 N/A 71 9.0 11369 3460

F 88 2000 N/A 85 39.9 37171 4664

F 71 96 10 14 5.6 3249 27513

F 71 96 10 14 5.6 10040 35269

F N/A N/A N/A N/A N/A 27 398

F 56 25 N/A 56 35.1 318 1031

M 62 <10 1 29 5.0 7 147

F 34 205 N/A 74 4.3 191 573

M 34 <10 1 26 19.3 52 306

M 63 94 1 12 6.6 144 582

F 76 392 N/A 24 9.4 186 933

F 65 N/A N/A 3 94.7 97 623

F 65 N/A N/A 3 94.7 66 407

F 63 48 >100 25 11.6 70 1288

F 60 324 100 42 11118.6 33 747

F 59 173 >100 40 N/A 403 1152

M 59 289 N/A 10 4.1 59 1022

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Chapitre 2: Platelet-derived extracellular vesicles convey mitochondrial DAMPs in platelet concentrates and their levels are associated with adverse reactions.

3.1 Résumé Les plaquettes activées libèrent des vésicules extracellulaires (EV) pouvant contenir

des mitochondries (mito+EV). Ces EV contiennent des motif moléculaires associés

aux dommages (DAMP) comme l’ADN mitochondrial, détecté en conditions

inflammatoires et dans les concentrés plaquettaires (CP) destinés à la transfusion.

Nous avons émis l'hypothèse que les mito+EV représentent un réservoir d'ADN

mitochondrial et avons exploré ce lien dans les CP qui ont induit ou non des

réactions transfusionnelles. Non seulement les mito+EV étaient plus abondantes

dans les CP impliqués dans des réactions transfusionnelles, mais elles corrèlent

significativement avec l’ADN mitochondrial dont la majorité est encapsulée dans des

EV. Bien que notre travail implique que des investigations sont nécessaires pour

déterminer s'il existe un rôle pathogène causal du DAMP mitochondrial encapsulé

dans les EV par opposition à l'ADN mitochondrial en solution, cette étude suggère

que les EV peuvent être un biomarqueur utile pour la prédiction du risque potentiel

de réactions transfusionnelles.

86

Platelet-derived extracellular vesicles convey mitochondrial DAMPs in platelet concentrates and their levels are associated with adverse reactions Genevieve Marcoux,1,† Audrey Magron,1,† Caroline Sut,2,3 Audree Laroche,1 Sandrine Laradi,2,3 Hind Hamzeh-Cognasse,2 Isabelle Allaeys,1 Ophelie Cabon,1 Anne-Sophie Julien,4 Olivier Garraud,2 Fabrice Cognasse,2,3,† and Eric Boilard1,5,† From the 1Department of Infectious Diseases and Immunity, Centre de Recherche du CHU de Québec - Université Laval, the 4Department of Mathematics and Statistic, Université Laval, Quebec City, Québec, and the 5Canadian National Transplantation Research Program, Edmonton, Alberta, Canada; the 2Université de Lyon, UJM-Saint-Etienne, GIMAP, EA 3064 and 3Département Scientifique, Établissement Français du Sang Auvergne- Rhône-Alpes, Saint-Étienne, France. Address reprint requests to: Eric Boilard, PhD, Centre de Recherche du Centre Hospitalier Universitaire de Québec, Faculté de Médecine de l’Université Laval, 2705 Laurier Boulevard, Room T1-49, Québec, QC, Canada G1V 4G2; e-mail: eric.boilard@ crchudequebec.ulaval.ca; or Fabrice Cognasse, PhD, Etablissement Français du Sang Auvergne-Rhône-Alpes, Département Scientifique, 25 Boulevard Pasteur, 42100 Saint-Etienne, France; e-mail: fabrice. [email protected]. † Equally contributed. This work was supported by “Amis de Rémi Association” to (FC), the Etablissement Français du Sang (EFS) to (FC and EB), and in part by a foundation grant from the Canadian Institutes of Health Research (CIHR) to EB. EB is the recipient of an investigator award from CIHR. GM has an award from the Canadian Blood Services, and AM is recipient of an award from MITACS. Received for publication January 9, 2019; revision received March 6, 2019, and accepted March 10, 2019. doi:10.1111/trf.15300 © 2019 AABB TRANSFUSION 2019;00;1–12

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3.2 Abstract

BACKGROUND: Whereas platelet transfusion is a common medical procedure,

inflammation still occurs in a fraction of transfused individuals despite the absence

of any apparent infectious agents. Platelets can shed membrane vesicles, called

extracellular vesicles (EVs), some of which contain mitochondria (mito+EV). With its

content of damage-associated molecular pattern (DAMP), the mitochondrion can

stimulate the innate immune system. Mitochondrial DNA (mtDNA) is a recognized

DAMP detected in the extracellular milieu in numerous inflammatory conditions and

in platelet concentrates. We hypothesized that platelet-derived mitochondria

encapsulated in EVs may represent a reservoir of mtDNA.

STUDY DESIGN AND METHODS: Herein, we explored the implication of mito+EVs

in the occurrence of mtDNA quantified in platelet concentrate supernatants that

induced or did not induce transfusion adverse reactions.

RESULTS: We observed that EVs were abundant in platelet concentrates, and

platelet-derived mito+EVs were more abundant in platelet concentrates that induced

adverse reactions. A significant correlation (rs = 0.73; p < 0.0001) between platelet-

derived mito+EV levels and mtDNA concentrations was found. However, there was

a non-significant correlation between the levels of EVs without mitochondria and

mtDNA concentrations (rs =−0.11; p = 0.5112). The majority of the mtDNA was

encapsulated into EVs.

CONCLUSION: This study suggests that platelet derived EVs, such as those that

convey mitochondrial DAMPs, may be a useful biomarker for the prediction of

potential risk of adverse transfusion reactions. Moreover, our work implies that

investigations are necessary to determine whether there is a causal pathogenic role

of mitochondrial DAMP encapsulated in EVs as opposed to mtDNA in solution.

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3.3 Introduction

Platelet transfusion is a common medical procedure necessary for individuals with

low platelet counts or defective platelets.1 It requires the collection of platelets as

platelet concentrates and storage, usually up to 5 or 7 days depending on the country

and blood bank involved. Whereas transfusion is a lifesaving operation, it

can also generate unwanted reactions in a proportion of patients.1,2

The establishment of strict procedures to avoid the transfusion of microbial

components has greatly reduced the transmission of infections in recipients.

However, sterile inflammation and organ injury in transfused recipients still occur in

the absence of any apparent infectious agents.3 Transfusion-related acute lung

injury is the leading cause of transfusion-related death and is initiated by soluble

mediators in plasma, such as antibodies against the human leukocyte antigen on

WBCs of the recipient or lysophospholipids, and may be modulated by regulatory T

cells or the recipient gastrointestinal microbiota.4–7 Febrile nonhemolytic transfusion

reactions (FNHTRs) are more frequent; they affect approximately 1% to 5% of total

platelet transfusions and are experienced by 30% of multitransfused patients.1,8 As

transfusion of the plasma fraction (without cells or platelets) is sufficient to trigger

these reactions,9 it is suggested that mediators released by cells or platelets during

the platelet preparation or storage (commonly referred to as “storage lesion”) are

involved in adverse reactions.10

Notwithstanding the various improvements that may preserve platelet integrity

during the preparation of platelet concentrates and storage, the occurrence of

platelet activation or storage lesions may lead to release of immunomodulatory

molecules in the platelet concentrates capable of mediating leukocyte activation.1

Lipid mediators (e.g., prostaglandins, lysophospholipids), cytokines and chemokines

(e.g., IL1β, CD40L, RANTES [CCL5], platelet factor 4 [PF4]), all may play a role in

immunologic reactions.1 For example, the release of soluble CD40L (sCD40L) has

89

been described during platelet storage, and its elevated concentration is associated

with a higher occurrence of adverse reactions.11–13

Activated or apoptotic cells and platelets can also shed small (approx. 100-1000 nm

in diameter) membrane vesicles, called extracellular vesicles (EVs) that are

generally identified as microparticles in transfusion research.14,15 They harbor CD41

and CD61 markers, and a proportion of them can express and P-selectin (CD62P).

During plasma membrane budding and shedding, there is engulfment of platelet

cytoplasmic molecules into certain EVs. Molecules potentially implicated in adverse

reactions following platelet transfusion have been described in EVs.14,15 For

instance, CD40L carried by EVs from apheresis platelet concentrates activate

respiratory burst in neutrophils.16,17 Moreover, phosphatidylserine (PS), a

phospholipid implicated in the prothrombotic role of platelet-derived EVs and their

clearance,18–20 is harbored by only a fraction of them.21–23

The mitochondrion is the organelle that mediates the oxidative phosphorylation

necessary for adenosine triphosphate production.24 It also plays an important role in

cell division and apoptosis.24,25 Intriguingly, mitochondria share several features with

bacteria, such as the presence of a double membrane comprising cardiolipin,

formylated peptides, and a circular genome containing hypomethylated CpG DNA

motifs.26–29 Mitochondrial damage-associated molecular patterns (DAMPs), such as

mitochondrial DNA (mtDNA) and formylated peptides, activate toll-like receptors

(TLRs; particularly TLR9) and formyl peptide receptors, respectively.30–36

Mitochondrial DAMPs have been described in a multitude of inflammatory

conditions.37–44 Thus, if released from a damaged cell, mitochondrial DAMPs are

suggested to contribute to inflammation.45

Each platelet contains approximately four mitochondria in the cytoplasm, which have

the potential of being wrapped into EVs, thereby forming mito+EVs.21,38,46 Early

proteomic analyses have already identified certain mitochondrial proteins in platelet-

derived EVs,47 thus pointing to an EV mitochondrial content. The study by Boudreau

90

et al.38 established the presence of actual respiratory-competent mitochondria,

inside a subpopulation of EVs generated by stimulating platelets using various

stimuli or from platelet concentrates. Confirmatory studies by multiple laboratories

have further contributed to unequivocally identifying extracellular mitochondria in

platelet concentrates.46,48–50 How mitochondria are released by platelets in platelet

concentrates is not completely understood, but factors such as the methodology

used to prepare platelet concentrates (e.g., platelet-rich plasma, apheresis, and

buffy coat) and the utilization of pathogen inactivation systems have been

suggested.45,46,48–51

Quantitative polymerase chain reaction (qPCR) to assess mtDNA is a powerful

quantitative approach to indirectly measure mitochondria in the extracellular milieu.

It was used by different laboratories to determine the presence of mtDNA in platelet

concentrates, plasma or stored red blood cells used for transfusion.38,46,48,52–55 It was

determined that higher levels of mtDNA are present in platelet concentrates that

induced FNHTR in transfused individuals than in those that were transfused without

complications.38,50,52,54,55 As the experimental conditions (qPCR) to quantify mtDNA

in the extracellular milieu do not allow distinction of mtDNA in solution from the

mtDNA encapsulated in EVs, none of these studies actually provide insights into the

source of mtDNA or the potential pathogenic mechanism. Hence, whether mtDNA

plays a pathogenic role in transfusion cannot be adequately mechanistically

assessed unless it is initially determined whether it is in solution or encapsulated in

mito+EVs.

Although a contribution by EVs in adverse reactions following transfusion has been

proposed, experimental evidence in human studies supporting this concept is

scarce.1 Blood was collected from patients with side effects (urticaria, fever,

erythema, dyspnea, and hypotension) attributed to platelet transfusion, and

significantly more platelet-derived EVs were detected in the circulation of transfused

patients undergoing hematologic disease compared to nonhematologic disease.56

Others have examined platelet-derived EVs present in platelet concentrates and an

91

association with adverse reactions; levels of platelet-derived EVs did not correlate

with the occurrence of transfusion-related acute lung injury or posttransfusion

reaction with dyspnea.57

In the present study, we examined platelet-derived EVs in platelet concentrates as

a potential biomarker predictive of adverse reaction, taking into account the diversity

of EVs and their content in mitochondrial DAMP. We monitored EVs based on their

mitochondrial content and expression of CD62P and PS using flow cytometry.

Moreover, we quantified mtDNA in the same platelet concentrates, and we

determined whether there was an association between the levels of EV subtypes

and mtDNA and whether they were associated with a higher risk of FNHTR in

transfused recipients.

92

3.4 Methods

3.4.1 Preparation and storage of platelet concentrates

Single-donor apheresis platelets were collected from regular anonymized blood

donors (Regional Blood Bank, EFS Auvergne-Rhône-Alpes;

http://www.dondusang.net)13,50 who volunteered to provide blood for research

purposes and signed a consent form, approved by the ethical committees of

Etablissement Français du Sang. Platelet concentrates were identified with

barcodes, were leukoreduced to less than 106/bag and included 35% native plasma

and 65% platelet additive solution Intersol (Fenwal) or SSP+ (Macopharma). Platelet

concentrates were stored at 22°C with gentle rotation and shaking (60 rpm) for a

maximum of 5 days before being used. Platelet transfusions were conducted as part

of routine care in the university-affiliated hospital. If the transfusion induced adverse

reactions, the incident/accident declaration, strictly conformed to national protocols,

was reported to hemovigilance departments describing symptoms and forwarding

the platelet concentrate identification number. Immediately after the identification of

adverse reactions, the incriminated platelet concentrate bags were shipped back to

blood establishment for immediate processing. The platelet concentrate bag tubing

(controls and adverse reactions) was then stripped and sufficient volume samples

were recovered for the analyses.58 To generate supernatants for the EV analysis,

platelet concentrate samples were centrifuged at 402 x g, during 10 minutes at 22°C.

Supernatants were kept frozen (−80°C) until testing. Samples obtained from platelet

concentrate not associated with adverse transfusion reaction were processed in the

same conditions and were used as controls. All the data relative to the transfused

recipients were provided by the physician in charge and were identified using

barcodes to protect their anonymity, according to the French regulation. Any

information regarding the transfused patient, other than the occurrence of adverse

reaction and type of adverse reaction, are not accessible to the study given the

absence of consent from the patients and in agreement with the French regulation.

For this study, we investigated 48 platelet concentrates that were associated with

transfusion reaction (e.g., allergic reaction, FNHTR, hemodynamic trouble) for which

we had 50 matched controls according to storage duration. All the available

93

information related to platelet concentrates and transfusions are presented in Tables

S1through S3, available as supporting information in the online version of this paper.

3.4.2 Measures of soluble CD62P and CD40L in platelet concentrate

supernatants

Control platelet concentrates and platelet concentrates that resulted in adverse

reactions were shipped almost immediately to the blood establishment.

Supernatants were collected and frozen (−80°C) until assay, with a maximum of 12

hours between the occurrence of a reaction and the end of the processing. Levels

of CD40L and soluble CD62P (sCD62P) in PC supernatants were measured using

Luminex technology, according to the manufacturer’s instructions. Data were

expressed in ng/mL and adjusted to 109 platelets.

3.4.3 EV depletion using centrifugation and magnetic microspheres

Platelet concentrate supernatants were diluted five times in 0.2-μm filtered PBS. Fifty

microliters of each diluted sample was used for the following treatments.

Ultracentrifugation

Samples were centrifuged at 100,000 x g for 1 hour at 18°C to pellet all EVs, and

supernatants were used to extract nucleic acids.

CD41 depletion

Twenty-five microliters of protein G magnetic beads (EMD Millipore) were washed

and incubated for 2 hours at room temperature with 10 μg of antihuman CD41

antibody in 100 μL PBS (clone M148, NovusBio) or 10 μg of irrelevant antibody in

100 μL phosphate-buffered saline (antihuman NFATc1, clone 7A6, Santa Cruz

Biotechnology) as control. After 4 washes, beads were incubated with 50 μL of

diluted PC’s supernatant, for 2 hours at room temperature. A magnet was used to

retain magnetic beads, and the remaining samples were used to extract nucleic

acids.

94

Benzonase digestion

Samples were digested or not for 30 minutes at 37°C with a genetically engineered

endonuclease (Benzonase, Sigma- Aldrich), 100 U/mL in 40mM of Tris, 10 mM of

NaCl, 6 mM of MgCl2, 1 mM of CaCl2, pH 7.9); nuclease activity was stopped by

adding 20mM of ethylenediaminetetraacetic acid and samples were then used to

extract nucleic acids. Benzonase activity on free mtDNA was evaluated by adding

purified human mtDNA in platelet concentrate supernatant. In all conditions, mtDNA

was further quantified by real-time qPCR.

3.4.4 Statistical analyses

Descriptive statistics are presented as frequency with percentage for categorical

variables, while interquartile ranges are presented for continuous variables. Graphic

results are presented as mean±standard error of the mean. The concentrations of

EVs and soluble factors in platelet concentrates were compared between the control

and reaction groups using Mann–Whitney test. The statistical significance for

comparisons between groups for the settings of optimal flow cytometry conditions

and for the benzonase nuclease assays were determined using one-way repeated

measures-analysis of variance or paired Student’s t test. Correlations between the

variables were assessed using Spearman correlation coefficient.

Associations between the diverse types of EVs and occurrence of adverse reaction

on transfusion were studied by univariable and multivariable logistic regressions.

The latter were adjusted for sex of donor, storage duration, and the concentration of

platelets in the platelet concentrates.

Receiver operating characteristic curves were generated to assess the predictive

ability of EVs on reactions, and their area under the curve was calculated. Results

were considered positive for the different EV subtypes when their value was above

the cutoff value identified after maximizing Youden’s index. A 95% confidence

interval was obtained for the cutoff using 10,000 bootstrap samples. Performance

measures of these values (sensitivity, specificity, negative and positive predictive

95

value, accuracy, and area under the curve) are presented. Results were considered

statistically significant when the p value was less than 0.05. All statistical analyses

were done using computer software (Prism, version 6, GraphPad Software; and SAS

version 9.4, SAS Institute Inc.).

More details on detection of EV and mitochondria by flow cytometry and

quantification of mtDNA are in Appendix S1, available as supporting information in

the online version of this paper.

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3.5 Results

In this retrospective case control study, 9206 consecutive platelet concentrates were

collected, for which 140 were associated with adverse reactions. We examined 48

single donor apheresis platelet concentrates that were associated with transfusion

reaction (e.g., allergic reaction, FNHTR, hemodynamic trouble) and for which we

had 50 controls, matched on method of platelet preparation and storage duration.

None of these platelet concentrates had been analyzed previously for their mtDNA

nor the EV contents. All the transfused patients had received a single platelet

transfusion with the exclusion of other components, with the exception of four who

had also received RBC transfusion more than 16 hours before the platelet

transfusion (Tables S1 and S2). The respective information on transfused products

and the blood donors is presented in Table S3.

Flow cytometry was used to quantify the different subtypes of EVs. We first ensured

the validity of our approach and confirmed that we could detect particles as small as

100-nm silica beads (EV gate, Fig. 1A), which are also smaller than resting platelets

(Fig. 1B). We activated washed platelets in vitro using thrombin to generate EVs

(Fig. 1C) and verified that the different EV subtypes were quantified with high degree

of specificity. Events in the EV gate (Fig. 1D, upper left) were displayed to assess

the presence of mitotracker and CD41 expression in reactive platelet concentrates

(Fig. 1D, lower left). Among CD41+EVs containing mitochondria (red gate) or not

(blue gate), PS, as determined by the binding of annexin V (Fig. 1D, upper right), or

CD62P expression (Fig. 1D, lower right) were also determined for all platelet

concentrates. To assess the specificity of our EV detection method, we used several

controls schematized in Fig. 1E: Given their membrane moiety, EVs were quantified

in samples that were either treated or left untreated with detergent Triton-X100. We

confirmed that in the presence of detergent, CD41+EVs, CD41+CD62P+EVs,

CD41+PS+EVs and CD41+mito+EVs were dissolved and thereby not detected (Fig.

1E-F). Furthermore, given that EVs can be eliminated from supernatants by high-

speed centrifugation, all EV types were significantly decreased in biospecimens that

underwent ultracentrifugation (Fig. 1E-F). PS, reportedly present on the surface of a

97

subpopulation of EVs, was assessed using the PS-binding probe annexin V. As

annexin V binding to PS requires calcium ions, we confirmed the absence of

CD41+PS+EVs in the presence of the calcium chelator ethylenediaminetetraacetic

acid (Fig. 1E-G). Serial dilution of the samples led to consistent dilution of the EVs

without affecting the median and mean CD41 fluorescence intensity, further

confirming our quantitative approach (Fig. 1H and I).

The various subtypes of EVs were quantified in platelet concentrate supernatants by

a blinded operator. Our study confirms the abundance of CD41+EVs in platelet

concentrates and indicates that their levels are on average significantly higher in

samples that induced adverse reactions compared to controls (Fig. 2A). Moreover,

when the mitochondrial content and/or other markers (PS, CD62P) were taken into

account, all the EV subtypes were significantly more elevated in adverse reactions

than in controls (Fig. 2B-F and Table S4, available as supporting information in the

online version of this paper.). Cutoff values were calculated by Youden’s index for

all subtypes of CD41+EVs. We found that total number of CD41+EVs gave the best

predictive ability; hence, a concentration of 40.87 x106 CD41+EV/mL could predict

90% of the true adverse reactions (Table 1).

Despite the efforts to identify perfectly matched platelet concentrates in each group

(no reaction and reaction), small but significant differences were noticed in variables

such as storage duration and platelet levels in circulation in the blood donors, and a

near significant difference in platelet concentration present in platelet concentrates

(Table S3). Logistic regressions to predict adverse reactions showed a cubic relation

for total CD41+EVs, as well as CD41+mito+EVs and CD41+mito−EVs. When adjusting

for sex of the transfused product, storage duration of the platelet concentrates, and

the platelet concentration in platelet concentrates, the previous relationships were

still highly significant (Table S5, available as supporting information in the online

version of this paper.), further proving the robustness of the EV markers.

98

Moreover, we verified the predictive ability of EV subtypes on particular adverse

reactions using receiver operating characteristics and their area under the curve

(Table S6, available as supporting information in the online version of this paper.).

We observed that total CD41+EVs, CD41+mito−EVs and CD41+mito−PS+ EVs were

promising predictors of all adverse reactions. Mitochondria containing EVs were

poorly predictive of allergic reaction, whereas CD41+mito−CD62P+ EVs could predict

allergic and hemodynamic trouble but not the FNHTRs. Although adverse reaction

types are not necessarily exclusive, the number of incidents that implicated two

reactions types was insufficient to make further prediction analyses.

To determine whether CD41+mito+EVs could account for the mtDNA present in

platelet concentrates, the concentration of mtDNA in the same samples was

determined using a qPCR approach, and correlations with CD41+mito+EV levels

were examined. We found a strong and significant correlation between the two

markers (rs = 0.73; p < 0.0001), whereas no significant correlation was found

between CD41+mito−EVs and mtDNA (Fig. 3A-B and Table S7, available as

supporting information in the online version of this paper.). To further confirm the

involvement of EVs with mtDNA levels, EVs (of all types) were eliminated from

supernatants by ultracentrifugation. We found a near complete (98%) reduction in

mtDNA levels in EV-depleted samples (Fig. 3C). A 50% reduction in mtDNA was

determined when CD41+EVs were specifically depleted using magnetic microbeads,

which confirmed the presence of mtDNA associated with CD41+EVs (Fig. 3C). The

efficient depletion of CD41+mito+EVs with ultracentrifugation and magnetic beads

was validated by flow cytometry (Fig. 3D). Moreover, while mtDNA in platelet

concentrates was protected from DNAse, suggesting that it is encapsulated within

mito+EVs (Fig. 3E), mtDNA isolated from hepatocytes and spiked into plasma was

indeed sensitive to DNAse treatment (in those conditions, 95.9±1.9% [n = 3] of the

exogenous mtDNA was hydrolyzed) (Fig. 3F). Thus, CD41+EVs, including those

containing mitochondria (CD41+mito+EVs), are more abundant in platelet

concentrates that have induced adverse reactions and their presence explains, at

least in part, the occurrence of mtDNA. Higher levels of sCD40L have been reported

99

in adverse reactions.11–13 However, whether CD40L release occurs concomitantly

with the production of mito+CD41+EVs in platelet concentrates is as yet unknown.

We measured sCD40L in platelet concentrate supernatants and verified the

correlation with CD41+mito+EVs. We found a good correlation between the two

measurements, suggesting that they are released concomitantly (Fig. 4A and Table

2). In the same way, the occurrence of CD41+mito+EVs correlated strongly with

sCD62P, suggesting that the liberation of CD41+mito+EV and α-granule content may

occur jointly (Fig. 4B and Table 2). We also observed that both sCD40L and sCD62P

levels were higher in platelet concentrates that have induced adverse reactions (Fig.

4C-D and Table 3). Cutoff values were calculated by Youden’s index for sCD40L

and sCD62P. We found that sCD62P has a good predictive ability; however, sCD40L

measurement shows a poor sensitivity (Table 4).

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3.6 Discussion

Although platelet-derived EVs have long been incriminated as a potential player in

adverse reactions, no study has formally verified the presence of platelet-derived

EVs and their subtypes in platelet concentrates confirmed as having triggered

adverse reactions. Furthermore, the fact that platelet EVs transport mitochondria,

and the multiple studies from different investigators that indicated higher levels of

mtDNA in adverse reactions,38,46,48,52–55 prompted our examination of platelet-

derived EVs as the actual source of mtDNA in platelet concentrates. Our study

highlights the broad diversity of platelet-derived EVs and shows that platelet EVs

convey mitochondria in platelet concentrates.

Extracellular vesicles encompass exosomes, small vesicles stored in intracellular

compartments, and microparticles or microvesicles, produced by plasma membrane

budding and shedding.14 Platelets can release both exosomes and microparticles59

and in the absence of consistent markers to distinguish both types of vesicles, it is

difficult to unequivocally determine the cellular compartment from which the

microparticles have emerged.60 However, given that smaller EVs may have been

overlooked by the flow cytometry approach used herein, and given that exosomes

are not expected to contain organelles,14,60 the EVs described in the present study

mainly include microparticles shed from the plasma membrane. The exact

mechanism of mitochondria release from platelets is unclear, but rearrangement of

the cytoskeleton is implied and may involve proteins in the apoptosis cascade.38

If replicated in a larger cohort of samples, our study suggests that the quantification

of CD41+EV may be a useful approach to identify platelet concentrates at risk of

provoking adverse reactions. Moreover, we found that extracellular mitochondria,

assessed using mtDNA or mito+EVs, were also significantly elevated in adverse

reactions. Although the quantification of platelet EVs requires only a few microliters

of fluids (5 μL were used herein), which is useful in the design of potent biomarker,

it also implicates experienced investigators and sophisticated flow cytometry

equipment. Given that the levels of mtDNA and mito+EVs showed a strong

101

correlation, it suggests that the measurement of mtDNA, using a quantitative

approach such as qPCR, may more conveniently permit to indirectly assess the

number of platelet-derived EVs in platelet concentrates.

The observation that DNAse treatment did not impact mtDNA levels suggests that it

is protected within EVs. Interpretation of the data could be complicated by the

presence of PF4 in platelet concentrates, as the former also protects DNA from

hydrolysis by DNAse.61 However, the fact that mtDNA was completely eliminated

from platelet concentrate supernatants by centrifugation provided further

confirmation that most, if not all, mtDNA in platelet concentrates is in fact

encapsulated in EVs. The targeted depletion of CD41+EVs using magnetic

microspheres led to consistent but partial reduction of mtDNA in the extracellular

milieu. We hypothesize that the absence or the too low expression of CD41 on a

certain proportion of platelet-derived mito+EVs, the presence of free mitochondrial

organelles in the extracellular milieu, or the liberation of mito+EV by leukocytes

through the blood processing could explain how mtDNA was not completely

eliminated by this approach.

While the release of CD40L is suggested to occur with longer storage duration,62,63

the preparation method of the transfusion product is suggested to be the main cause

of EV and mitochondrial release.46,49 We found that mitochondrial release correlates

with sCD40L and sCD62P, suggesting that similar pathways may have led to their

liberation. Given that technical approaches (e.g., enzyme-linked immunosorbent

assay, multiplex) used to quantify sCD40L and sCD62P cannot distinguish whether

these molecules are in solution or associated with EVs, we further speculate that

similarly to mtDNA, CD40L and CD62P molecules in platelet concentrates are in fact

conveyed by platelet-derived EVs.

While associations between various EV subtypes and adverse reactions were

examined, the study design did not address causality. Whether platelet-derived EVs

play an actual role in adverse reactions remains to be established experimentally,

but they may contribute through their broad repertoire of inflammatory

102

molecules,14,15 such as sCD40L and CD62P and their interaction with their

respective counterreceptors on leukocytes, namely, CD40 or integrin β3 and

platelet-selectin glycoprotein ligand-1.56,64 As PS is also exposed on a proportion of

the mito+EVs, they may also contribute to adverse reaction through the support of

the coagulation cascade and thrombosis. With the identification of mtDNA in platelet

concentrates, prior investigations have logically focused on verifying the impact of

purified mtDNA on various cellular lineages both in vitro and in vivo.54 While these

studies are crucial for the understanding of potential mechanisms related to

transfusion-induced adverse reactions, they may not fully recapitulate the actual

pathogenesis if mtDNA is in fact typically encapsulated into EVs and not free in

solution. It is frequently suggested that mitochondrial DAMPs activate TLRs (e.g.,

TLR9) in endosomes. Thus, it remains to be established whether mitochondrial

DAMPs inside EVs actually reach endosomes to activate TLRs. As platelet EVs,

including mito+EVs, were previously found internalized by neutrophils,65 this pathway

of activation remains a promising avenue. Moreover, mtDNA has been assessed in

a multitude of inflammatory conditions, including trauma,37,44 burn injury,43 hepatitis,

cancer,66 rheumatoid arthritis,38,39 and systemic lupus erythematosus.40,41

Considering that the induction of platelet EVs is frequently observed in inflammation,

it would be interesting to consider whether their presence explains the occurrence

of mtDNA in all of these conditions.

To summarize, we demonstrated the potential of EV based biomarker research with

an appreciation of EV diversity. Transfusion is viewed as a triad of intricate

parameters: 1) the donor (physiologic and genetic characteristic, environmental—

e.g., stress, pollution, self-prescribed drugs, food intake), 2) the labile blood

component (collection, preparation/processing, storage, delivery condition, etc.),

and 3) the recipient (physiologic and genetic characteristics, pathology, etc.). All

these variables must be considered to improve outcomes. The identification of

biomarker or the identification of storage lesion and transfusion outcomes may

contribute to the improvement of storage conditions and personalized transfusion.

The EV cargo is vast, and the development of additional tools may permit the

103

distinction of a larger spectrum of EV heterogeneity for the identification of novel

potent biomarkers and an understanding of the roles of EVs in inflammation.

104

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Figure 1. Assessment of platelet EV subpopulations by high-sensitivity flow

cytometry.

112

Fig. 1. (A) Acquisition by flow cytometry (BD Canto II Special Order Research Product) of silica beads of various size (100, 500, and 1000 nm) displayed in side scatter (SSC)-H (granularity) and forward scatter (FSC)-photomultiplier tube (PMT)-H (relative size) to design the lower (100 nm) and upper (1000 nm) limits of the EV gate. (B) SSC-H and FSC-PMT-H portrayal of nonactivated platelets. (C) Remnant platelets (outside of the EV gate) and EVs (inside the gate) generated after stimulation of platelets with thrombin. (D) Representative SSC-H and FSC-PMT-H dot plots of platelet EVs from a PC supernatant implicated in transfusion reaction (upper left). EVs detected from this sample in the EV gate (in black) are displayed (lower left) according to their content in mitochondria using 100-nm MitoTracker Deep Red (MitoTracker-APC-H) and their expression of V450 fluorochrome-conjugated antibodies directed against CD41a (CD41-V450-H). All EVs expressing CD41 (with mitochondria in the red section, and no mitochondria in blue) were also analyzed for PS expression using fluorescein isothiocyanate– conjugated annexin V (upper right) or activation using phycoerythrin-conjugated CD62P (lower right). (E) Several controls were done to assess the specificity of our EV detection. (F) Sensitivity of CD41a+ EVs to clearance by 0.05% Triton X-100 (TX-100) and ultracentrifugation (Ultra), presented as % of untreated (Ctrl). Data are presented as mean±standard error of the mean (SEM) of 3 independent experiments, paired t test (**p < 0.01 and ****p < 0.0001) compared with the control (Ctrl); (G) Sensitivity of CD41a+PS+ EVs to clearance by ethylenediaminetetraacetic acid treatment presented as percentage of untreated (Ctrl). Data are presented as mean±SEM of four independent experiments, paired t test (***p < 0.001) compared with the control (Ctrl). (H, I) CD41a+EVs were serially diluted (twofold dilution) and quantitatively analyzed by flow cytometry using counting microspheres. Their concentration and the calculated dilution factor (H), the median of fluorescence (I, upper) and the mean of fluorescence (I, lower) are presented. Data are presented as mean±SEM of four independent experiments, Repeated Measures one-way ANOVA; NS, non-significant. [Color figure can be viewed at wileyonlinelibrary.com] as the mean ± SEM. Differences between day 1 and 7 were verified using t-test, *p<0.05.

113

Figure 2. Platelet EV subpopulation levels are higher in platelet concentrates

involved in adverse transfusion reaction.

Platelet-derived EVs present were analyzed by high-sensitivity flow cytometry in control platelet concentrates (PCs) (control, n=50) or PCs implied in adverse transfusion reaction (reaction, n=48). Samples were labeled with CD41-V450, MitoTracker Deep Red, and annexin V–fluorescein isothiocyanate or CD62P-PE. Samples were quantified for (A) total platelet EVs (CD41+), (B) platelet EVs expressing CD62P (CD41+CD62P+), (C) platelet EVs expressing PS (CD41+PS+), (D) platelet EVs containing mitochondria (CD41+mito+), (E) platelet EVs containing mitochondria and expressing CD62P (CD41+mito+CD62P+) and (F) platelet EVs containing mitochondria and expressing PS (CD41+mito+PS+). Data are represented as mean±SEM (***p < 0.001 and ****p < 0.0001) between control and reaction PCs, Mann–Whitney test.

114

Figure 3. The majority of the mitochondrial DNA in platelet concentrates is

present in EVs.

The level of platelet EVs (A) containing mitochondria (CD41+mito+EVs) or not (B) (CD41+mito−EVs) measured by high-sensitivity flow cytometry were compared to the amount of mtDNA measured by qPCR. Correlations between the variables were assessed using nonparametric Spearman test and considered significantly different from zero when p < 0.05. (C, D) Supernatant was harvest from platelet concentrates (PCs) after different treatment: Control supernatant without treatment (Ctrl), ultracentrifugation at 100,000 g for 1 hour at 18°C to pellet EVs (Ultra), CD41 depletion with magnetic beads (CD41-) or irrelevant antibody (IRR AB). (C) Nucleic acids were extracted for all conditions and mtDNA was quantified by qPCR. Data are presented as mean±SEM of eight independent experiments. One-way analysis of variance; NS, non-significant (**p < 0.01) compared with the control. (D) CD41+mito+EVs were also analyzed in supernatants for all conditions by high-sensitivity flow cytometry. Data are presented as mean±SEM of five independent experiments (*p < 0.05, ****p < 0.0001) compared with the control, one-way analysis of variance. (E) Samples from PCs were digested (Benzo) or not (Ctrl) with the DNAse Benzonase and then used to extract nucleic acids for mtDNA quantification by qPCR. Paired t test, n=8, *p < 0.05. (F) Benzonase activity on free mtDNA was evaluated by adding purified human mtDNA in platelet concentrate supernatant. Samples were digested (Benzo) or not (Ctrl) with Benzonase and then used to extract nucleic acids for mtDNA quantification by qPCR. Paired t test, n=3, *p < 0.05.

115

Figure 4. Levels of soluble CD62P, but not soluble CD40L, correlate with

mitochondria containing platelet EVs.

Levels of soluble CD62P, but not soluble CD40L, correlate with mitochondria containing platelet EVs. The level of mitochondria containing platelet EVs (CD41+mito+EVs) measured by high-sensitivity flow cytometry was compared to (A) the amount of soluble CD40L (sCD40L, n= 92) or (B) the amount of soluble CD62P (sCD62P, n=96) measured by enzyme-linked immunosorbent assay. Correlations between the variables were assessed using nonparametric Spearman test and considered significantly different from zero when p < 0.05. Levels of sCD40L (C) and sCD62P (D) were compared between control and reaction PCs. Data are represented as mean±SEM (**p < 0.01 and ****p < 0.0001) between control and reaction PCs, Mann–Whitney test.

116

3.9 Tables

Table 1. Optimal cut-off values for EV subtypes as determined by Youden’s

method (Healthy donors: n=50, reaction n=48)

Variable

(x 106/mL) CutPoint

BCI

Sensitivity Specificity PPV NPV Accuracy AUC P-value

Total CD41+

EVs

>=40.87 (27.67-47.08) 0.90 0.86 0.86 0.90 0.88 0.91(0.84;0.97) <.001***

CD41+mito+

EVs

>=13.67 (6.52-25.45) 0.60 0.90 0.85 0.70 0.76 0.77(0.67;0.87) <.001***

CD41+mito-

EVs

>=20.99 (18.31-41.69) 0.88 0.76 0.78 0.86 0.82 0.85(0.77;0.93) <.001***

CD41+mito+

PS+ EVs

>=12.33 (6.33-25.21) 0.65 0.86 0.82 0.72 0.76 0.78(0.69;0.87) <.001***

CD41+mito+

CD62P+

EVs

>=3.63 (1.25-3.82) 0.56 0.96 0.93 0.70 0.77 0.79(0.7;0.89) <.001***

CD41+mito-

PS+ EVs

>=39.77 (19.68-53.78) 0.73 0.88 0.85 0.77 0.81 0.85(0.77;0.93) <.001***

CD41+mito-

CD62P+

EVs

>=0.15 (0.09-0.22) 0.73 0.72 0.71 0.73 0.72 0.70(0.59;0.81) <.001***

AUC = area under the curve; BCI = Bootstrap 95% confidence interval; EVs = extracellular vesicles; NPV = negative predictive value; PPV = positive predictive value. ***p < 0.001.

117

Table 2. EV subtype associations with soluble CD40L (n=92) and soluble

CD62P (n=96) in platelet concentrates

Total

CD41+ EVs

CD41+mito

+ EVs

CD41+mito

- EVs

CD41+mito

+ PS+ EVs

CD41+mito+

CD62P+ EVs

CD41+mito

- PS+ EVs

CD41+mito-

CD62P+ EVs

sCD40L rs 0.45 0.40 0.35 0.44 0.38 0.34 0.24

p <.0001 <.0001 0.0006 <.0001 0.0002 0.0009 0.0189

sCD62P rs 0.65 0.74 0.51 0.72 0.75 0.49 0.33

p <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 0.0011

Values are presented as Spearman correlation coefficient (rs) and p-value (p). sCD40L: soluble CD40L. sCD62P: soluble CD62P.

118

Table 3. Quantification of mitochondrial DNA, soluble CD40L and soluble

CD62P in platelet concentrates

Variable Reaction n 95% CI Median Q1;Q3

mtDNA No 0 - - -

(ng/mL) Yes 35 (58256.69; 91899.04) 66539.57 (30158.54; 110482.86)

sCD40L No 44 (5882.74; 7512.58) 6583.20 (3756.10; 9326.20)

(pg/mL) Yes 48 (6974.39; 9188.29) 7812.80 (5096.50; 10792.90)

sCD62P No 48 (104.53; 134.47) 101.45 (83.80; 140.05)

(ng/mL) Yes 48 (426.64; 762.70) 444.50 (230.55; 700.55)

mtDNA = mitochondrial DNA; n = number of samples; Q1; Q3 = first and third quartiles; sCD40L = soluble CD40L; sCD62P = soluble CD62P.

119

Table 4. Optimal cut-off values for sCD40L and sCD62P as determined by

Youden’s method (Healthy donors: n=50, reaction n=48)

Variable CutPoint BCI Sensitivity Specificity PPV NPV Accuracy AUC P-value

sCD40L

(pg/mL)

>=9426 (2287-9831) 0.42 0.93 0.87 0.59 0.66 0.71(0.61;0.82) <.001***

sCD62P

(ng/mL)

>=211 (197-322) 0.81 0.94 0.93 0.83 0.88 0.92(0.86;0.98) <.001***

AUC = area under the curve; BCI = Bootstrap 95% confidence interval; NPV = negative predictive value; PPV = positive predictive value; sCD40L = soluble CD40L; sCD62P = soluble CD62P. ***p < 0.001.

120

3.10 Supplementary methods

Detection of platelet EVs and mitochondria

Samples were labeled with 100nM MitoTracker Deep Red (ThermoFisher Scientific),

which accumulates in activated mitochondria, V450 anti-human CD41a (BD

Biosciences) which targets glycoprotein IIb on platelets and platelet-derived EVs and

PE anti-CD62P (Beckman Coulter, CA, USA), which targets the activated platelets

and platelet-derived EVs or FITC-annexinV (BD Biosciences) which targets

phosphatidylserine (PS). After a 30 minutes incubation period at 37ºC, samples were

diluted with PBS pre-filtered through a 0.22µm pore size membrane (Fisher

Scientific, ON, Canada) or 1x AnnexinV-binding buffer. EVs were then analyzed by

Flow cytometry with a BD Canto II Special Order Research Product (BD

Biosciences), as described previously.[378, 448] Briefly, a forward scatter (FSC)

coupled to photomultiplier tube (PMT) was mounted on the flow cytometer and

parameters were set to allow optimal detection of silica microspheres from 100 to

1000nm. Flow cytometer performance tracking was performed daily before all

analyses. For the FSC-PMT, the assigned voltage was 300V, 450 for FITC, 435 for

PE, 500 for APC and 500 for V450. For SSC, the assigned voltage was 400V and

the threshold was 200. EV acquisition was performed at low speed (~10µl/min) and

for quantification, a known quantity of fluorescents beads (3µm diameter:

Polysciences inc., Warrington, PA, USA) was added to each tube and a constant

number of beads was acquired for each sample. Silica particles of known dimension

(100nm, 500nm and 1µm in diameter (Kisker Biotech GmbH &Co., Steinfurt,

Germany) were used to standardize FSC-PMT parameters, and EVs were defined

as being smaller than 1µm silica particles and platelets. The results were analyzed

using the software FlowJo V10.1r5 in order to identify different EV subpopulations

on the chosen parameters; namely CD41a, MitoTracker, CD62P, PS, relative size

(FSC-PMT) and granularity (SSC-H).

To assess the detection specificity, we made several controls: For Triton treatment,

samples were incubated 30 minutes at room temperature (RT) with 0.05% Triton X-

100 before labeling. For EDTA, samples were treated for 30 minutes at RT with

121

50μM EDTA (using PBS instead of Annexin V buffer as diluent). For

ultracentrifugation treatment, samples were centrifuge at 100 000g for 1 hour at 20°C

to pellet EVs, and supernatants were labeled. When washed platelets were

stimulated to produce EVs, 0.5 U/mL of thrombin (Sigma) was added for 1 hours at

37°C after addition of 5 mM of calcium.

Quantification of mtDNA

For each sample that resulted in adverse reactions, nucleic acids were extracted

from 50 μl of PC’s supernatant with the QIAamp DNA Micro extraction kit (QIAGEN,

Toronto, ON, Canada) and mtDNA was quantified by real-time quantitative PCR as

described previously.[382, 449]

122

3.11 Supplementary tables

Supplementary Table 1: Adverse transfusion reactions associated platelet

concentrates

Variable Occurrence of reaction n %

Reaction No 50 51.0

Yes 48 49.0

Reaction type* AATR 22 22.4

FNHTR 26 26.5

HT 14 14.3

*Reaction types are not mutually exclusives. AATR: atypical allergic transfusion reaction, FNHTR: Febrile nonhemolytic transfusion reaction, HT: Hemodynamic trouble

123

Supplementary Table 2: Qualitative information of the transfusion product

Variable Level n %

Transfusion alone No 54 55.1 Yes 44 44.9

Transfusion with RBCs No 94 95.9 Yes 4 4.1

Transfusion with FFP No 98 100

Sex of the donor Female 36 36.7

Male 62 63.3

RBCs: red blood cells, FFP: fresh frozen plasma

124

Supplementary Table 3: Quantitative information on the donors and on the platelet concentrates

Variable Reaction Median Q1;Q3 P-value1

Storage days No 2.87 (2.02; 3.81)

0.0011** Yes 3.00 (3.00; 4.00)

White blood cells (donor-109/L)

No 6.66 (5.46; 7.50) 0.7197

Yes 6.61 (5.55; 7.72)

Red blood cells (donor-109/L)

No 4.90 (4.58; 5.15) 0.7223

Yes 4.91 (4.66; 5.23)

Hemoglobin (donor-g/dL)

No 14.50 (13.80; 15.40) 0.7142

Yes 14.55 (13.60; 15.10)

Hematocrit (donor-%) No 43.05 (40.70; 45.50)

0.8478 Yes 42.80 (41.10; 45.15)

Mean corpuscular volume (donor)

No 88.30 (85.90; 91.40) 0.5293

Yes 88.00 (85.15; 90.90)

Mean corpuscular hemoglobin concentration (donor)

No 29.75 (28.80; 30.80) 0.5246 Yes 29.60 (28.85; 30.65)

Mean corpuscular hemoglobin (donor)

No 33.55 (33.00; 34.30) 0.6160

Yes 33.60 (32.55; 34.20)

Platelets in donor (109/L)

No 273.50 (246.00; 290.00) 0.0333*

Yes 291.50 (251.00; 322.50)

Platelets in PC (109/L) No 1304.00 (1241.00; 1396.00)

0.0507 Yes 1381.00 (1275.00; 1528.00)

Q1;Q3 : first and third quartiles. PC: platelet concentrate. *p<0.05 and **p<0.01

125

Supplementary Table 4: Quantification of EV subtypes in platelet concentrates

Variable (x 106/mL)

Occurrence of reaction 95% CI Median Q1;Q3

Total CD41+ EVs No (19.55; 40.11) 19.35 (11.52; 29.24)

Yes (82.07; 127.38) 90.62 (47.44; 135.39)

CD41+mito+ EVs No (5.12; 11.77) 4.96 (2.61; 9.81)

Yes (18.05; 27.21) 21.86 (7.72; 35.69)

CD41+mito- EVs No (14.18; 28.59) 12.47 (8.38; 19.56)

Yes (59.74; 104.46) 62.56 (31.01; 104.85)

CD41+mito+ PS+ EVs

No (5.66; 10.78) 5.50 (2.40; 9.54)

Yes (18.65; 29.91) 17.41 (7.38; 37.88)

CD41+mito+ CD62P+ EVs

No (0.78; 1.89) 0.78 (0.30; 1.39)

Yes (3.61; 6.02) 4.03 (1.36; 7.08)

CD41+mito- PS+ EVs

No (14.71; 26.23) 13.89 (7.86; 22.68)

Yes (61.57; 112.61) 62.05 (31.10; 107.11)

CD41+mito- CD62P+ EVs

No (0.11; 0.26) 0.09 (0.04; 0.21)

Yes (0.23; 0.60) 0.24 (0.10; 0.33)

n : number of samples. SD: standard deviation, CI: confidence interval. Q1;Q3 : first and third quartiles.

126

Supplementary Table 5: Cubic effect of EVs on adverse reaction

Variable Univariable model Multivariable model

Total CD41+ EVs 29.31 (<0.0001) 23.15 (<0.0001)

CD41+mito+ EVs 15.90 (0.0012) 18.28 (0.0004)

CD41+mito- EVs 27.31 (<0.0001) 24.62 (<0.0001)

Results are shown as Chi-Square statistic (p-value) for the cubic effect of each variable. Multivariable model also includes sex of the donor, storage duration and concentration of platelets.

127

Supplementary Table 6: Predictive values of EV subtypes adjusted for the different adverse reactions

Variable

AUC (95% CI)

AATR FNHTR HT

Total CD41+ EVs 0.79(0.70;0.88)*** 0.74(0.65;0.84) *** 0.85(0.77;0.93)***

CD41+mito+ EVs 0.61(0.48;0.74) 0.75(0.63;0.86)*** 0.7(0.55;0.86)*

CD41+mito- EVs 0.78(0.69;0.87)*** 0.68(0.56;0.80)** 0.84(0.75;0.93)***

CD41+mito+ PS+ EVs 0.62(0.49;0.76) 0.75(0.64;0.86)*** 0.71(0.56;0.86)**

CD41+mito+ CD62P+ EVs 0.64(0.51;0.77)* 0.74(0.62;0.86)*** 0.68(0.54;0.83)*

CD41+mito- PS+ EVs 0.79(0.70;0.89)*** 0.68(0.56;0.80)** 0.81(0.72;0.90)***

CD41+mito- CD62P+ EVs 0.66(0.55;0.78)** 0.41(0.28;0.54) 0.73(0.61;0.84)***

AATR: atypical allergic transfusion reaction, FNHTR: Febrile nonhemolytic transfusion reactions, HT: Hemodynamic trouble, AUC: area under the curve. * p < 0.05, ** p < 0.01, *** p <0.001, where p comes from the test H0: AUC = 50% vs H1: AUC ≠ 50%

128

Supplementary Table 7: EV subtype associations with mitochondrial DNA in platelet concentrates (n= 35)

Total

CD41+ EVs

CD41+mito+

EVs

CD41+mito-

EVs

CD41+mito+

PS+ EVs

CD41+mito+

CD62P+ EVs

CD41+mito-

PS+ EVs

CD41+mito-

CD62P+ EVs

rs 0.07 0.73 -0.11 0.59 0.74 -0.07 -0.14

p 0.7012 <.0001 0.5112 0.0002 <.0001 0.6706 0.4214

Values are presented as Spearman correlation coefficient (rs) and p-value (p).

129

3.12 Supplementary references

1 Rousseau, M. et al. Detection and quantification of microparticles from

different cellular lineages using flow cytometry. Evaluation of the impact of

secreted phospholipase A2 on microparticle assessment. PLoS One 10,

e0116812, doi:10.1371/journal.pone.0116812 (2015).

2 Marcoux, G. et al. Revealing the diversity of extracellular vesicles using high-

dimensional flow cytometry analyses. Sci Rep 6, 35928,

doi:10.1038/srep35928 (2016).

3 Marcoux, G. et al. Microparticle and mitochondrial release during extended

storage of different types of platelet concentrates. Platelets 28, 272-280,

doi:10.1080/09537104.2016.1218455 (2017).

4 Boudreau, L. H. et al. Platelets release mitochondria serving as substrate for

bactericidal group IIA-secreted phospholipase A2 to promote inflammation.

Blood 124, 2173-2183, doi:10.1182/blood-2014-05-573543 (2014).

130

Chapitre 3: Platelet-derived extracellular vesicles

contain an active proteasome involved in protein

processing for antigen presentation via class I

major histocompatibility molecules

4.1 Résumé

Les plaquettes sont maintenant reconnues pour leur contribution à l'immunité. Elles

contiennent un protéasome actif et présentent des antigènes par l'intermédiaire du

CMH I. Une fois activées, elles libèrent des vésicules extracellulaires (PEV) qui sont

hétérogènes, ce qui suggère qu'elles jouent diverses fonctions. Il n’a jamais été

examiné si le protéasome est emporté dans les EV de plaquettes lors de leur

formation. Nous avons émis l'hypothèse qu'une machinerie fonctionnelle

d’apprêtement et de présentation de l'antigène se retrouve dans les EV de

plaquettes lors de leur activation. En utilisant une combinaison d'analyses

moléculaires et fonctionnelles, nous avons montré la présence d'un protéasome 20S

actif dans diverses conditions ou les plaquettes sont activées, ainsi que du CMH I et

des molécules de coactivation des lymphocytes. Démontré par l'activation et la

prolifération des lymphocytes T CD8+ spécifiques de l'ovalbumine (OVA), les PEV

incubées avec l’OVA peuvent apprêter et présenter l’antigène. Ces résultats

suggèrent que les PEV contribuent à l'immunité adaptative.

131

Platelet-derived extracellular vesicles contain an active proteasome involved

in protein processing for antigen presentation via class I major

histocompatibility molecules

Genevieve Marcoux1, Audrée Laroche1, Stephan Hasse1, Marie Tamagne2,3,4, Anne

Zufferey1, Tania Lévesque1, Isabelle Allaeys1, Johan Rebetz5, Annie Karakeussian-

Rimbaud6,7, Julie Turgeon6,7, Sylvain G. Bourgoin1, Hind Hamzeh-Cognasse8,

Fabrice Cognasse8,9, Rick Kapur10, John W. Semple5, Marie-Josée Hébert6,7, France

Pirenne2,3,4, Herman S. Overkleeft11, Bogdan I. Florea11, Mélanie Dieude6,7,12, Benoit

Vingert2,3,4, Eric Boilard1,7.

1 Centre de recherche du CHU de Québec- Université Laval, Département de

microbiologie-infectiologie et d’immunologie, Centre ARThrite de l’Université Laval,

Québec, QC, Canada.

2 Univ Paris Est Creteil, INSERM, IMRB, F-94010 Creteil, France

3 Etablissement Français du Sang, Ivry sur Seine, F-94200, France

4 Laboratory of Excellence GR-Ex, Paris, France

5 Division of Hematology and Transfusion Medicine, Lund University, Lund, Sweden,

Departments of Pharmacology and Medicine, University of Toronto, Toronto,

Canada

6 Research Centre, Centre hospitalier de l'Université de Montréal (CRCHUM),

Montréal, Québec, Canada.

7 Canadian Donation and Transplantation Research Program, Edmonton, Alberta,

Canada

8 Université de Lyon, Université Jean Monnet, INSERM U1059, Saint-Etienne,

France

9 Établissement Français du Sang Auvergne-Rhône-Alpes, Saint-Etienne, France.

132

10 Sanquin Research, Department of Experimental Immunohematology, Amsterdam

and Landsteiner Laboratory, Amsterdam UMC, University of Amsterdam,

Amsterdam, the Netherlands.

11 Gorlaeus Laboratories, Leiden Institute of Chemistry and Netherlands Proteomics

Centre, Leiden, The Netherlands.

12 Département Microbiologie, Infectiologie et Immunologie, Faculté de Médecine,

Université de Montréal, Montréal, Québec, Canada.

Correspondence should be sent to:

Eric Boilard, PhD

Centre de Recherche du Centre Hospitalier Universitaire de Québec

Faculté de Médecine de l’Université Laval

2705 Laurier Blvd, room T1-49, Québec, QC, Canada G1V 4G2

[email protected]

Phone: +1 418-525-4444, extension 46175, Fax: +1 418-654-2765

Or

Benoît Vingert, PhD

Établissement Français du Sang

Institut Mondor de Recherche Biomédicale-INSERM U955,

5 rue Gustave Eiffel, 94017 Créteil, France

[email protected]

Phone: +33 1 56 72 17 40, Fax: +33 1 56 72 17 47

133

4.2 Abstract

In addition to their hemostatic role, platelets play a significant role in immunity. Once

activated, platelets release extracellular vesicles (EVs) formed by budding of their

cytoplasmic membranes. Because of their heterogeneity, platelet EVs (PEVs) are

thought to perform diverse functions. It is unknown, however, whether the

proteasome is transferred from platelets to PEVs or whether proteasomal protein

processing function is retained. We hypothesized that functional protein processing

and antigen presentation machinery is bearing by PEVs derived from activated

platelets. Using a combination of molecular and functional assays, we showed the

presence of an active 20S proteasome in PEVs. Moreover, MHC-I and lymphocyte

costimulatory molecules (CD40L and OX40L) were found in proteasome-containing

PEVs. Proteasome-containing PEVs were identified in healthy donor blood, in

platelet concentrates used for transfusion, in inflammatory conditions and in the

murine lymphatic system. Injection of PEVs into mice revealed that they could reach

lymphoid organs. The PEV proteasome could process exogenous ovalbumin (OVA)

and efficiently load its antigenic peptide onto MHC-I molecules which promoted

OVA-specific CD8+ T lymphocyte proliferation. These results suggest that PEVs

contribute to adaptive immunity through cross-presentation of antigens and have

privileged access to immune cells through the lymphatic system, a tissue location

that is inaccessible to platelets.

134

4.3 Introduction

After erythrocytes, platelets are the second most abundant lineage in blood and are

best known for their role in hemostasis1. Platelets are small fragments produced by

the large multinucleated megakaryocytes in the bone marrow. Although

approximately 100 billion platelets are produced in humans each day, most are

eliminated through the mononuclear phagocytic system in the spleen and liver

without having encountered injured endothelium.

Platelets bear receptors that permit the recruitment of immune cells and carry an

extensive set of immune and inflammatory molecules (e.g. cytokines/chemokines,

lipid mediators, hormones) that are stored in their granules or cytoplasm, or

synthesized and upregulated by mRNA translation following platelet activation.

Thus, while platelets may mount an innate immune response to injury, which is

critical to combat pathogen invasion, organ and tissue damages may also favor

platelet activation and inflammation in chronic inflammatory diseases2-8.

In contrast to innate immunity, adaptive immunity encompasses the mechanisms

underlying the specific response to pathogens. This involves lymphocytes, antigen-

presenting cells (APCs) and the production of effector cells and antibodies9-31. The

differentiation and activation of APCs are enhanced by platelet-derived molecules,

such as platelet factor 4 (PF4) and soluble CD40L, while platelet adhesion receptors

can also promote the recruitment of lymphocytes11,12,15-17.

Albeit anucleate, the platelet cytoplasm includes numerous molecules comprising

the proteasome, which are transferred from megakaryocytes to their progeny. The

proteasome is a high molecular weight cylindrical protein complex through which

unwanted or damaged proteins are degraded32,33. The central complex part, called

the 20S proteasome, is made up of twenty-eight distinct subunits34, comprising the

three catalytic subunits necessary for the degradation of proteins into peptides of

three to fifteen amino acids in length34,35. Proteasome activity in megakaryocytes is

required for platelet production36,37 and in platelets, the proteasome regulates

135

platelet lifespan38, activation39-41 and the release of PEVs42,43. The platelet

proteasome can hydrolyze proteins into smaller peptides34,44,45, thereby enabling

peptide loading onto the platelet major histocompatibility complex (MHC) class I

molecules (MHC-1)46-48. Components of the peptide loading complex are also

expressed in platelets and are found in close proximity with MHC-I during platelet

activation49,50. As platelets can efficiently form an immunological synapse with T-

lymphocytes to activate lymphocyte proliferation49,51,52, they are known to fulfill roles

in cross-presentation of antigens in adaptive immunity. In a similar manner,

megakaryocytes cross-present antigens to CD8 T-lymphocytes, thereby suggesting

that they may also play a dual role in innate and adaptive immunity48,53-55.

Extracellular vesicles, produced in abundance by platelets, are small (up to 1 µm in

diameter) membrane-bound vesicles released from the plasma membrane or

endosomal compartments of activated cells. Platelet EVs are heterogeneous in

terms of surface molecules and content (e.g. nucleic acids, lipids, transcription

factors, enzymes, mitochondria) and as such may play diverse functions beyond

hemostasis56-58. For instance, PEVs convey mitochondrial components that are

associated with inflammation and adverse transfusion reactions (ATRs)59-61. Despite

the fact that platelets are restricted to the blood circulation, PEVs can cross tissue

barriers and enter synovial fluid62,63, lymph64,65 and bone marrow66 where they can

deliver platelet-derived molecules and modulate target cells57. For instance, PEVs

promote the formation of germinal centers and the production of IgG by B-cells67,68.

They also interact with and modulate regulatory T cell differentiation and activity69,70.

Thus, PEVs may be able to transport platelet-derived molecules relevant to adaptive

immunity into lymphoid organs. However, it is unknown whether the proteasome and

the molecules necessary for antigen presentation are also transferred during the

budding of PEVs. In this study, we evaluated whether a functional protein processing

and antigen presentation machinery is transferred to PEVs by activated platelets.

136

4.4 Methods

More details are presented in supplemental methods

Labeling of murine platelets, DCs and PEVs Platelets were isolated from

C57BL/6J mice by retro-orbital puncture in 200 µL ACD (acid-citrate-dextrose),

350 µL Tyrode’s buffer pH 6.5. Whole blood was centrifuged at 600xg for 3 min and

then at 400xg for 2 min to remove red blood cells. Supernatant was spun at 1,300xg

for 5 min and the platelet-containing pellet was gently resuspended in 600 µL

Tyrode’s buffer pH 7.4. Platelets were either left nonactivated or activated with

thrombin (0.1 U/mL) after addition of 5 mM of calcium for 90 min at RT. Platelet EVs

were obtained by two rounds of centrifugation of stimulated platelets at 1,300xg for

5 min at RT. Either activated platelets, EVs or DC were pulsed with 100 µg/mL OVA

protein (Sigma-Aldrich), 200 µg/mL of OVA peptide (SIINFEKL [Invivogen, San

Diego, CA]) or left unpulsed for 4 h at RT. These conditions were either left unlabeled

for lymphoproliferation or intracellular staining experiments or labelled for hs-FCM

experiments.

Five µL of PEVs or platelet suspensions were labeled with 250 nM LWA300

proteasome probe in a total volume of 100 μl for 90 min at 30°C. Samples were then

incubated with the following antibodies for 30 min at RT prior to dilution in Annexin

V binding buffer and analysis by hs-FCM: BUV395 anti-CD41, BV650 anti-CD62p,

BV650 anti-CD62p, BV711 Annexin V, BV421 anti-OX40L, BUV737 anti-CD154 (all

BD Biosciences), PeCy7 anti-CD40, PeCy7 anti-MHC-I (AF6-88.5) and PE anti-

MHC-I bound to OVA peptide (25D1.16) (all from Biolegend).

In vitro antigen-specific CD8+ T-cell activation In vitro antigen-specific CD8+ T-

cell activation was performed using purified OVA-specific OT-1 CD8+ T cells in

combination with C57BL/6J mice platelets, EVs and DCs. Purified splenocytes were

obtained as described above.

137

For proliferation, splenocytes were stained with 5-(and 6)-carboxyfluorescein

diacetate, succinimidyl ester (CFSE, Thermo Fisher Scientific) and 3 × 105 cells in

100 µL were then stimulated for five days at 37°C in 96-well plates in the presence

of CD41+ PEVs (or platelets or DCs) pulsed with either OVA protein, OVA peptide

(SIINFEKL) or left unpulsed (ratio of 1 CD41+ PEV for 1 OT-1 cell). Cultured OT-1

cells were washed twice by centrifugation at 1,400xg for 7 min in PBS and labeled

with BUV395 mouse anti-CD3 (BD Biosciences) and PerCP-Cy5.5 mouse anti-CD8

(Biolegend) for 30 min at 4°C. Cells were washed and fixed with 150 µL PFA 1% for

analysis by hs-FCM.

For intracellular staining, 3 × 105 splenocytes were cocultured (1:1 ratio) in the

presence of CD41+ EVs (or platelets or DC) pulsed with either OVA protein, OVA

peptide (SIINFEKL) or left unpulsed. After 1-h incubation at 37°C, brefeldin A and

monensin (0.25× final concentration, Thermo Fisher Scientific) were added in the

culture media to determine the production of cytokines and the coculture was

pursued overnight. Cells were washed twice and membrane proteins were labeled

with PE anti-CD40 (Thermo Fisher Scientific), BUV395 anti-CD3, PerCP-Cy5.5 anti-

CD8, BV421 anti-CD134 (Biolegend) and aqua live/dead (Invitrogen) for 30 min at

4°C. Cells were fixed and permeabilized with a commercial kit (Thermo Fisher

Scientific) for intramembranous staining and then stained with AF647 anti-IL2 (BD

Biosciences) and AF700 IFN-γ (BD Biosciences). Cells were washed and fixed with

150 µL PFA 1% for analysis by flow cytometry.

138

4.5 Results

4.5.1 PEVs contain functional proteasome

Immunoblotting was used to confirm that PEVs released from thrombin-activated

human platelets contained the proteasome 20S α subunit (Figure 1A). Using

platelets as a positive control, we assessed proteasome function in PEVs.

Proteasome-associated caspase-like activity was detectable in both platelets and

the PEV fraction, but was undetectable in the supernatant (Figure 1B), indicating

that the catalytically active proteasome was transferred to PEVs upon their release.

Visualization of immunogold-labeled proteasome 20S α subunit by transmission

electron microscopy confirmed the presence of proteasomes in PEVs (Figure 1C).

LWA300 is a conjugate between epoxomicin, a natural inhibitor of the 20S

proteasome, and BODIPY FL fluorophore and generates an activity-based,

fluorescent, and plasma membrane-permeable inhibitor that can identify the

proteasome in cells71,71. Using LWA300, we designed assays to detect and quantify

active proteasome-containing PEVs71,72. Confocal microscopic visualization of

platelets as positive controls, and PEVs from thrombin-activated platelets labeled

with LWA300 revealed that both platelets and a subpopulation of PEVs contained

active proteasome (Figure 1D). Moreover, hs-FCM confirmed PEV heterogeneity

following platelet activation by thrombin (Figure 1E). Approximately 16.66.5% of

the larger (i.e. 500–900 nm) PEV microvesicles73, contained proteasome whereas

smaller PEV (i.e. less than 500 nm) exosomes73 had no detectable proteasome

(Figure 1E and Supplementary figure 1). The detection specificity of proteasome-

containing PEVs by hs-FCM was confirmed using a combination of controls. We

confirmed efficient competition of the LWA300 probe by unlabeled epoxomicin, and

we determined the particulate nature and membrane moiety of proteasome-

containing PEVs, as they were respectively pelleted by ultracentrifugation and

sensitive to detergent treatment (Figure 1F-G).

139

Hs-FCM was further used to characterize proteasome-containing PEVs in terms of

surface markers and mitochondrial content. Approximately half of the proteasome-

containing PEVs expressed exposed phosphatidylserine while the vast majority

expressed surface P-selectin (Supplementary figure 2A). Furthermore, 68.37.8%

of the proteasome-containing PEVs also contained mitochondria (Supplementary

figure 2A). Investigation of the mechanisms underlying release of active

proteasome positive PEVs revealed that the total number of PEVs (with and without

proteasomes) and proteasome-containing PEVs were significantly reduced in the

presence of actin inhibitors (cytochalasin B, D, E and latrunculin A) but not by the

tubulin polymerization inhibitor nocodazole (Supplementary figure 2B).

Proteasome release in PEVs was not unique to thrombin stimulation as the platelet

agonists ADP, cross-linked collagen related peptide (CRP-XL) and heat-aggregated

IgG (HA-IgG) also triggered release of proteasome-containing PEVs

(Supplementary figure 2C).

4.5.2 Identification of proteasome-containing PEVs under

physiological and pathological conditions

The presence of proteasome-containing PEVs was assessed ex vivo and in vivo

under conditions conducive to platelet activation and PEV release. A mean of 1.82

× 106 (range:1.13 × 105 to 8.11 × 106, n = 6) proteasome-containing PEVs/mL were

detected by hs-FCM in the blood of healthy individuals, pointing to their constitutive

presence under physiological conditions.

PEVs were quantified in platelet concentrates known to have caused ATRs and

compared with control concentrates that did not induce ATRs. Given the reported

increase in mitochondria-containing PEVs in ATRs59,60, we also determined the

levels of mitochondria-containing PEVs. Documented ATRs included febrile

nonhemolytic reactions, skin manifestations (e.g. itching or skin rash) and

cardiovascular events such as hypotension or tachycardia. High levels of

proteasome-containing PEVs were found in all tested platelet concentrates

(Figure 2A) but the concentrations of proteasome-containing PEVs (with or without

140

mitochondria) were not significantly elevated in platelet concentrates that induced

ATR (Figure 2A). In contrast, compared with control platelet concentrates not

associated with ATR, the concentrations of mitochondria-containing PEVs were

increased in ATR-associated concentrates, consistent with prior findings59,60. These

data reveal that proteasome-containing PEVs are an expected component in platelet

concentrates and suggest that the presence of extracellular mitochondria in PEVs,

rather than the proteasome, may indicate increased risks of ATR.

Transfusion-related acute lung injury (TRALI) is a potentially lethal adverse reaction

that can result from transfusion of platelet concentrates74. Thus, we quantified

proteasome-containing PEVs in murine bronchoalveolar lavages in an inducible

TRALI model75,76. Proteasome-containing PEVs were detected in bronchoalveolar

lavages from both TRALI and control mice (Figure 2B), however, no significant

difference was observed between the two groups (Figure 2B). This suggests that

proteasome-containing PEVs are not increased during lung inflammation in this

model.

Our in vitro investigations pointed to the high potency of immune complexes (HA-

IgG) in generating proteasome-containing PEVs (Supplementary figure 2C).

Although mice lack FcγRIIA, this is the only Fcγ receptor expressed by human

platelets that is capable of responding to immune complexes77. Recent findings

indicate that circulating immune complexes stimulate the release of mitochondria-

containing PEVs in mice expressing the FcγRIIA transgene78,79. To determine

whether the proteasome is also released under these conditions, we injected

immune complexes into FcγRIIA-expressing mice and quantified proteasome-

containing PEVs79. Compared with diluent injected control mice, there were

significantly elevated levels of proteasome-containing PEVs in plasma of mice with

immune-complexes challenge (Figure 2C). These findings confirmed that

proteasome-containing PEVs are present under various physiological and

pathological conditions.

141

4.5.3 Protein processing by proteasome-containing PEVs

In order to study proteasome function in PEVs, we investigated its ability to process

proteins into smaller peptides by assessing their successful loading into the antigen-

binding groove of MHC-I molecules. We confirmed the expression of MHC-I on

resting and thrombin-activated murine platelets and verified whether MHC-I is

maintained on PEVs. We found that washed resting platelets did not express MHC-

I on their surface (Figure 3A), however, thrombin activation led to a significant

increase in surface MHC-I expression (Figure 3A), consistent with the reported

presence of this molecule in α-granules and its release upon activation49,50,80,81. A

small proportion (1.9 0.9%) of the spontaneously released PEVs expressed MHC-

I, but this proportion significantly increased upon platelet activation with thrombin

(means of 7.7 2.1%).

To determine whether PEV MHC-I can indeed load small peptides, we pulsed PEVs

with the ovalbumin (OVA) peptide SIINFEKL and monitored its association with

MHC-I molecules using the 25D1.16 monoclonal antibody, which specifically

recognizes MHC-I/SIINFEKL complexes82. Similarly with platelets, PEVs loaded the

SIINFEKL peptide onto their MHC-I molecules (Figure 3B). Native OVA was also

efficiently processed by platelets and the SIINFEKL peptide was loaded in MHC-I

(Figure 3C), consistent with prior work49. Of interest, incubation of native OVA with

PEVs resulted in proteolysis of the former and retrieval of the SIINFEKL peptide from

MHC-I molecules expressed by the PEVs. Taken together, the data show that PEVs

can process native proteins into smaller peptides thereby enabling antigen

presentation through MHC-I.

4.5.4 Proteasome-containing PEVs can reach lymphoid organs and

circulate through the lymphatic system

Intravenously injected PEVs have a limited circulation time in human blood, ranging

from 10 min to hours depending on studies83,84. It is unclear, however, whether they

can reach lymphoid organs. Hence, fluorescently labeled PEVs were intravenously

injected into mice and their presence in spleen and lymph nodes was monitored

142

60 min post injection. Platelet EVs were no longer detectable in blood at this time

(Figure 4A) but were observed in the tested lymphoid organs (Figure 4B). Platelet

EVs can circulate through the lymphatic system, which is the main circulatory system

permitting dissemination of antigens to lymphoid organs. Moreover, the levels of

PEVs in lymph are increased in mouse models of atherosclerosis and autoimmune

inflammatory arthritis57,64,65. Using the lymph from mice, we evaluated whether PEVs

were associated with proteasome and MHC-I molecules. We found that a fraction of

the PEVs in lymph expressed MHC-I (11.2 2.2%) and contained an active

proteasome (12.0 3.9%). Remarkably, a small, but detectable proportion (1.6

0.7%) of the lymph PEVs contained both proteasome and MHC-I molecules

(Figure 4C). This finding was significant given the substantial number of PEVs in

lymph (mean of 2.5 × 107/mL in mice64).

4.5.5 Proteasome-containing PEVs express lymphocyte co-

stimulatory molecules

Efficient stimulation of adaptive immunity requires both recognition of the antigen-

MHC-I complexes by the T cell receptor (TCR) and the activity of co-stimulatory

molecules. Therefore, we evaluated whether platelets or proteasome-containing

PEVs loaded with SIINFEKL expressed co-stimulatory molecules in addition to other

known PEV markers. Compared with PEVs that had undetectable SIINFEKL

loading, both platelets and PEVs loaded with SIINFEKL (25D1.16-positive)

expressed higher levels of proteasome (Figure 5). Moreover, in contrast to

thrombin-activated platelets, where phosphatidylserine expression is increased

when loaded with SIINFEKL, both PEVs bearing SIINFEKL and those negative for

SIINFEKL expressed similar levels of phosphatidylserine (Figure 5). Furthermore,

both platelets and SIINFEKL-bearing PEVs expressed higher levels of P-selectin,

and the co-stimulatory molecules CD40L, CD40 and OX40L (Figure 5). Thus,

among the different subtypes of PEVs, those with a higher density of antigen–MHC-

I complexes show more abundant expression of lymphocyte co-stimulatory

molecules and bear a higher content of active proteasome.

143

4.5.6 Proteasome-containing PEVs can support antigen-specific T

cell activation

T cells isolated from OT-1 mice100 were co-incubated for 18 hours with PEVs that

were either pulsed or not with the SIINFEKL peptide or native OVA. Dendritic cells

and platelets were treated similarly as positive controls and for comparison

(Figure 6A). The T cells (CD3+CD8+) were then washed and the expression of

CD40, OX40, IL-2 and IFN-γ was evaluated to assess T cell activation.

Compared with DCs and platelets, PEVs could induce a significant release of IFN-γ

when pulsed with the OVA peptide, whereas native OVA led to an increase in IFN-γ

but did not reach statistical significance (Figure 6B). Moreover, DCs, and to a lesser

extent platelets and PEVs, were only capable of inducing significant CD40

expression by T lymphocytes previously pulsed with the OVA peptide (Figure 6C).

In contrast, OX40 and IL-2 expression were not induced by DCs, platelets or PEVs

under these experimental conditions (Figure 6D-6E).

Whether PEVs could stimulate T cell proliferation, a hallmark response by the

lymphocyte antigen-MHC-I complex was evaluated. T cells from OT-1 mice were

labeled with CFSE to monitor cellular division and co-incubated for 5 days with either

DCs, activated platelets or PEVs, which were either pulsed or not with either

SIINFEKL or native OVA (Figure 7A). Lymphoproliferation would be represented by

a decrease in the mean fluorescence intensity histogram, i.e. a dilution of CFSE

fluorescence. (Figure 7B-C).

As expected, we found that the proportion of lymphoproliferative cells was

significantly higher when OT-1 T lymphocytes were incubated with peptide- or native

OVA-pulsed DCs or activated platelets (Figure 7B-C). Of particular note is that PEVs

also supported T cell proliferation when pulsed with either the SIINFEKL or native

OVA (Figure 7D). In addition, when PEVs were removed from pulsed conditions by

ultracentrifugation, no proliferation was observed, confirming that the pulsed proteins

alone cannot support proliferation (Figure 7E). Furthermore, inhibition of PEV

144

proteasome by epoxomicin before pulsing with native OVA inhibited the ability of

PEV to induce T cell proliferation (Figure 7F left panel). The effect was directed

toward PEV proteasome, as addition of epoxomicin prior to peptide pulsing at the

same concentration used on DCs did not inhibit proliferation (Figure 7F right panel).

In summary, PEVs are capable of processing native proteins into smaller peptides

through their active proteasome, thereby enabling peptide loading onto MHC-I.

Platelet EVs express co-stimulatory molecules, and their interaction with positively

selected T lymphocytes promotes lymphocyte cytokine production and proliferation.

145

4.6 Discussion

Megakaryocytes and platelets are emerging as active players in innate and adaptive

immunity7,53,54. The platelet role in immunity is mainly confined to the blood

circulation, while megakaryocytes are localized in bone marrow and lungs. The latter

location potentially provides the megakaryocyte with more direct access to airborne

pathogens and allergens55,85,86. In contrast, PEVs can disseminate into organs and

tissues that are inaccessible to megakaryocytes and platelets and this may be

possibly due to their small dimensions and the presence of unique surface

molecules. In this study, we found that the proteasome and the necessary machinery

to process and present antigens to CD8+ T cells are packaged into PEVs by

platelets. Thus, PEVs may extend the immune functions played by platelets and

megakaryocytes outside the confines of the blood.

Platelet EVs are heterogeneous in terms of surface molecules and their platelet-

derived content. The presence of mitochondria within PEVs is well

documented59,60,87, but it was unknown whether other organelles were also

transferred from the platelet. The proteasome is much more abundant than

mitochondria, at around 800,000 copies per cell88 in contrast to approximately 3–7

mitochondria per platelet60. Further investigation will be necessary to determine if

the presence of multiple organelles within a single vesicle is the result of a specific

sorting mechanism, or because those vesicles are larger and may have more

storage capacity. Nonetheless, as previously shown for mitochondria-containing

PEVs, we observed that the release of proteasome-containing PEVs requires

cytoskeleton remodeling via intact actin microfilament dynamics and that a broad

array of platelet agonists induce the release of proteasome-containing PEVs60.

The presence of an extracellular proteasome has already been documented in

normal human blood, and elevated levels have been found in patients suffering from

autoimmune diseases, sepsis or trauma89. Moreover, the 20S proteasome core is

present and active within EVs derived from apoptotic endothelial cells and regulates

tertiary lymphoid structures formation, autoantibody production and graft rejection

146

following transplantation35. While some evidence supports that a circulating

extracellular proteasome may be transported by EVs, we show that EVs of platelet

origin, among the most abundant EVs in blood, do contain the proteasome.

Consistent with this, mass spectrometry analysis of the human PEV proteome

identified numerous proteasomal subunits90-92. These include subunits of the 20S

catalytic core (PSMA1, PSMA2, PSMA3, PSMA4, PSMA5, PSMA6, PSMA7,

PSMB1, PSMB2, PSMB3, PSMB4, PSMB5, PSMB6), an immunoproteasome

subunit (PSMB8), subunits of the 19S regulator (PSMC2, PSMC4, PSMC5, PSMC6,

PSMD2, PSMD3, PSMD11, PSMD13) and the 11S regulator (PSME1 and

PSME2)90-92. Thus, while proteomic data points to proteasome proteins in PEVs, the

present work unequivocally demonstrates its presence and documents for the first

time that the extracellular proteasome in PEVs is functional and can contribute to

antigen processing.

We used complementary approaches and developed a hs-FCM-based assay to

detect active proteasome at the single EV level, thereby permitting the quantification

and assessment of other molecules expressed by proteasome-containing EVs. Of

particular note the proteasome-containing PEVs also expressed MHC-I and

lymphocyte co-stimulatory molecules, which enabled lymphocyte activation,

proliferation and cytokine generation. This process is well regulated, as it strictly

implicated protein processing by the proteasome, subsequent loading onto MHC-I

molecules for recognition by CD8+ T cells. These findings demonstrate a novel and

potentially important role for PEVs in adaptive immunity. While our work suggests

that PEVs may be involved in adaptive immunity through antigen presentation, it

does not necessarily exclude that other cells may release proteasome-containing

EVs capable of playing this role. Indeed, EVs derived from DCs, B and T

lymphocytes, macrophages and NK cells can perform cross-presentation,

suggesting that they also contain the necessary antigen processing machinery93-98.

Further studies will be necessary to determine the impact and the importance of

PEVs as antigen presenting elements.

147

We identified proteasome-containing PEVs in the blood of healthy donors. As most

PEVs in blood under healthy conditions are suggested to originate from

megakaryocytes99,100, the latter may also constitutively release proteasome-

containing EVs. Moreover, we found that numerous stimuli of human platelets, as

well as the in vivo stimulation of mouse platelets by immune complexes could induce

release of proteasomes in PEVs, suggesting that proteasome release is at least

conserved in humans and mice and takes place under conditions implicating platelet

activation. Platelet potency at actively generating immunity against the Plasmodium

berghei parasite has been demonstrated49. Moreover, megakaryocytes can be

infected by Dengue virus101, and they can also ingest and phagocytose E. coli55.

Given their small size, intact microorganisms may not necessarily be present inside

PEVs, but PEVs might process cytosolic microbial proteins derived from infected

cells, such as platelets or megakaryocytes that lack the ability to disseminate through

the lymphatic system. Thus, PEVs may be implicated in immune surveillance and

might contribute to presentation of microbial antigens. Furthermore, the presence of

proteasome-containing PEVs in platelet concentrates was not associated with

increased risks of ATR or TRALI in a mouse model. It remains to be verified whether

the presentation of platelet antigens (e.g. CD41 or CD61) by PEVs from platelet

concentrates might contribute to generation of anti-platelet immunity in transfused

recipients, although this has been shown with megakaryocytes56. It is also unknown

whether the proteasome in EVs (from platelets, megakaryocytes, or other cells)

displays other functions in addition to antigen processing. Future investigations

might reveal whether the proteasome impact protein half-life in EVs.

Activated platelets release PEVs containing both mitochondria and the proteasome.

Our findings in mouse lymph revealed that proteasome-containing PEVs can

circulate in the lymphatic system, potentially explaining their accumulation in

lymphoid organs following intravenous injection. It is intriguing that these findings

contrast with mitochondria-containing PEVs, which are essentially absent from

lymph64. This privileged access to the lymphatic system by proteasome-containing

PEVs may reveal a new immune route for PEVs to reach lymphoid organs or infected

148

tissues. Our study highlights the diversity of PEVs, and supports the concept that

different subtypes of PEVs may play different roles depending on their cargo and

tissue distribution.

149

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156

Figure 1. Platelets and PEVs contain proteasome

(A) Proteasome 20S α subunit and actin in human platelet extracellular vesicles

(PEVs) and platelet (PLTs) preparations (25 μg protein per lane) were assessed by

immunoblotting. Results are representative of six distinct preparations. (B)

Proteasome function was assessed by measuring the caspase-like activity of PEVs

and platelet supernatants. Platelets were used as positive control (Gray dotted line)

using the Proteasome-Glo Caspase-like Cell-based Assay. Fifteen μg of proteins

were used per condition. Mean ± SEM, n = 7, ** P < 0.01, Mann-Whitney. (C)

Transmission Electron Microscopy (TEM) visualization of immunogold labelling of

proteasome 20S α subunit in PEVs released from thrombin-activated platelets. Data

are representative of three independent experiments. (D) Confocal microscopy

visualization of proteasome content associated with platelets (left panel) and PEVs

(right panel). Visualization of CD41, wheat germ agglutinin (WGA) to determine

plasma membrane surface, proteasome (LWA300) and merge is displayed in the

region of interest (ROI). Populations originating from dashed lines squares and

represented in ROI are triple positives (white arrowheads) or CD4- and WGA-

positive but proteasome-negative (white arrows). (E) High-sensitivity flow cytometry

(hs-FCM) analysis of resting platelets and thrombin-activated platelets. Two distinct

populations of PEVs, i.e. larger PEVs (approximately 17% of these PEVs contain

active proteasome) and smaller PEVs, not containing active proteasome. (n = 20

data are presented as mean ± SEM, ** P < 0.01, *** P < 0.001 and **** P < 0.0001,

Kruskal–Wallis). (F-G) Controls were performed to assess the specificity of PEV

detection using hs-FCM. Sensitivity of CD41+Proteasome+ PEVs to competition by

epoxomicin, ultracentrifugation (Ultracentri) or 0.05% Triton X-100 and unlabeled

samples are presented as % of untreated (Control). Data are presented as mean ±

SEM of 5 independent experiments, paired t-test ****P < 0.0001 compared with the

control.

157

Figure 2. Identification of proteasome-containing PEVs under physiological

and pathological conditions

(A) Proteasome-containing PEVs detected by hs-FCM are found in PFP from platelet

concentrates that have caused adverse transfusion reaction (ATR) in recipients and

in control concentrates that did not induce ATR. The total number of proteasome-

containing PEVs (containing or not mitochondria (mito)), proteasome+mitochondria-

PEVs or proteasome+mitochondria+PEVs does not significantly differ between

control and ATR, while proteasome- mitochondria+ PEVs are increased in ATR (no

adverse reaction group [n = 33] vs. adverse reaction group [n = 34] matched in terms

of storage duration; data are presented as mean ± SEM, NS non-significant, **** P

< 0.0001, Student t test). (B) Proteasome-containing PEVs detected by hs-FCM are

found in bronchoalveolar lavages from mice after induction of transfusion related

acute lung injury (TRALI) with 34-1-2s and AF6-88.5.5.3 antibody and in control mice

(n = 5, data are presented as mean ± SEM, NS non-significant, Student t test). (C)

Proteasome-containing PEVs are detected at significantly higher levels in mice 1

hour post i.v. injection of HA-IgG vs. control (diluent) mice. (n = 3, **P < 0.01, data

are presented as mean ± SEM, Student’s t-test)

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Figure 3. Platelets and PEVs load and process OVA onto MHC-I

(A) Thrombin-activated platelets and their PEVs express MHC-I (detected by hs-

FCM). (n = 7, data are presented as mean ± SEM, ** P < 0.01, *** P < 0.001, Mann–

Whitney). Platelets and their PEVs are able to load the SIINFEKL peptide (B) or to

process and load ovalbumin (OVA) (C) onto MHC-I. (n = 13, * P < 0.05, ** P < 0.01,

data are presented as mean ± SEM, Kruskal-Wallis test comparisons to unpulsed)

159

160

Figure 4. PEVs in blood circulation can reach lymphoid organs and circulate

in lymph

(A) One-hour post i.v. injection, CMFDA fluorescently labeled PEVs are

undetectable in blood circulation. CMFDA fluorescently labeled PEVs are easily

detected if spiked in blood as a positive control. The number of CMFDA PEVs per

µL of blood was quantified and no difference was observed between control (not

injected) and PEV-injected mice (lower left). (n = 7, data are presented as mean ±

SEM, NS non-significant, Mann–Whitney). (B) CMFDA-labeled PEVs localized in the

spleen and in lymph nodes (LN) are indicated by white arrowhead. ROI: region of

interest. Results are representative of observations made in seven mice per group.

(C) PEVs in lymph were detected by hs-FCM and expression of MHC-I and

proteasome (LWA300) was determined. +/+ double positive and −/− double negative

for MHC-I and proteasome. (n = 6, data are presented as mean ± SEM).

161

162

Figure 5. Platelets and PEVs with loaded OVA peptide express activation and

co-stimulatory molecules

(A-B) Platelets and (C-D) PEVs loaded with OVA peptide (25D1.16+) express higher

levels of proteasome, and activation and co-stimulatory molecules. (A,C) Mean

fluorescence intensity (MFI) of the different markers assessed by hs-FCM (n = 7,

data are mean ± SEM, NS non-significant, * P < 0.05, Student’s t-test). (B,D)

Representative MFI histogram of the 25D1.16 negative and positive populations for

each marker.

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Figure 6. PEVs can induce antigen-specific T cell activation and cytokine

production through antigen presentation.

(A) Schematic representation of the experimental plan. Cells and PEVs used for the

stimulation of lymphocytes assessed by intracellular cytokines staining (ICS). DC:

dendritic cells, NS: unpulsed, OVA: ovalbumin, O/N: overnight. (B-E) Expression of

receptors or cytokines by CD3+ CD8+ T cells co-incubated with either DCs, activated

platelets (PLTs) or PEVs, left unpulsed or pulsed with SIINFEKL (PP) or ovalbumin

(OVA). (B) Interferon gamma (IFN-γ) production, (C) CD40 expression, (D) OX40

expression and (E) IL-2 production (n = 6, 7 or 9; data are presented as mean ±

SEM. * P < 0.05, ** P < 0.01 Wilcoxon vs. unpulsed).

164

165

Figure 7. PEVs loaded with native OVA process and present OVA peptide to

induce antigen-specific T cell lymphoproliferation.

(A) Schematic representation of the experimental plan. DC: dendritic cells, NS:

unpulsed, OVA: ovalbumin, CFSE: Carboxyfluorescein succinimidyl ester. (B-C) Hs-

FCM dot plot (B) or histogram (C) showing CFSE fluorescence shift of CD3+ CD8+

T cells populations when co-incubated with either dendritic cells (DC), activated

platelets (PLTs) or PEVs left unpulsed or pulsed with SIINFEKL peptide (PP) or

ovalbumin (OVA) for 7 days. (D) Percentage of CD3+ CD8+ lymphoproliferative cells

after co-incubation with either DCs, PLTs or PEVs unpulsed or pulsed with PP or

OVA for 7 days. (n = 14; data are presented as mean ± SEM. NS non-significant, **

P < 0.01, *** P < 0.001, ****P < 0.0001, Friedman test followed by Dunn’s post-test

for multiple comparisons to unpulsed). (E) Percentage of CD3+ CD8+

lymphoproliferative cells after 7 days co-incubation with either PP-pulsed DCs or

supernatant (surn) depleted of PEVs by ultracentrifugation, left unpulsed or pulsed

with PP or OVA. (n=5; data are presented as mean ± SEM, ** P < 0.01, Mann-

Whitney vs. unpulsed). (F) Proportion of CD3+ CD8+ lymphoproliferative cells after 7

days co-incubation with OVA-pulsed PEVs treated or not with epoxomicin (epoxo)

for 2 hours and PP-pulsed DCs(DC + PP) treated or not with epoxomicin (epoxo). (n

= 9 for PEVs and n = 3 for DC; data are mean ± SEM, NS non-significant, ** P <

0.01, Wilcoxon).

166

4.9 Supplementary methods

Ethics The study was approved by the medical ethics committee of CHU de Québec

and Université Laval. Methods were carried out in accordance with approved

guidelines. Platelets were obtained from the citrated blood of healthy human

volunteers under informed consent according to a protocol approved by an

Institutional Review Board (Centre de Recherche du Centre Hospitalier Universitaire

de Québec). With approval from the ethics committees of Etablissement Français du

Sang, single-donor apheresis platelet concentrates were collected from healthy

anonymized volunteer blood donors (Regional Blood Bank, EFS Auvergne-Rhône-

Alpes) who gave consent for research purposes1-3.

Human platelets and EVs Platelets were isolated from healthy volunteers after

centrifugation of citrated whole blood (282xg for 10 min) at room temperature (RT).

The supernatant was centrifuged at 600xg for 3 min at RT to obtain platelet-rich

plasma (PRP). The latter was then centrifuged at 1,300xg for 5 min at RT and the

platelet-containing pellet was resuspended in Tyrode’s buffer (pH 7.4). Platelets

were counted (Cellometer AutoM10; Nexcelom Bioscience Lawrence, MA, USA),

adjusted to a density of 100 x 106 cells/mL in Tyrode’s buffer (pH 7.4) and, unless

stated in the legend, were either left nonactivated or activated with thrombin for 3 h

to obtain PEVs. In order to obtain PEVs, 5 mM calcium was added to platelets, which

were then stimulated with either thrombin (0.5 U/mL, Sigma-Aldrich), crosslinked

collagen-related peptide (CRP-XL) (1 µg/mL), ADP (20 µM, Sigma-Aldrich) or heat-

aggregated immunoglobulin G (HA-IgG) (0.5 mg/mL MP Biomedicals), for the

duration described in the corresponding legend. Platelet activation was stopped by

addition of 20 mM EDTA, and remnant platelets were removed by two rounds of

centrifugation at 1,300xg for 5 min at RT.

Characterization of proteasome-containing platelets and PEVs

Western Blot Platelet EVs and platelets were freshly prepared and centrifuged at

18,000xg for 1 h 30 min at 18°C or 1,500xg for 10 min, respectively. Pellets were

167

stored in phosphate-buffered saline (PBS) buffer containing protease inhibitor

cocktail, at −80°C until analysis (completeTM mini EDTA-free Protease Inhibitor

Cocktail, Sigma-Aldrich). Protein content was determined by Pierce BCA Protein

Assay Kit (Thermo Fisher Scientific) according to the manufacturer’s guidelines.

Protein samples were separated by 12.5% SDS-PAGE followed by transfer onto a

polyvinylidene difluoride (PVDF) membrane. After blocking in milk, proteins of

interest were detected by primary antibodies against Proteasome 20S alpha3

subunit (Novus Biologicals, Centennial, CO, USA) and actin (Abcam). The PVDF

membranes were then incubated with horseradish peroxidase-conjugated antibody

against the primary antibodies (Jackson ImmunoResearch Laboratories).

Proteasome function assay Proteasome function was assessed by measuring the

caspase-like activity of PEVs using the Proteasome-Glo Caspase-like Cell-based

Assay (Promega Corporation), according to the manufacturer’s instructions.

Platelets served as the positive control. Fifteen μg of proteins were used per

condition.

Transmission electron microscopy Freshly obtained PEVs were fixed in 2% PFA

for 30 min and stored at 4°C prior to embedding in LR White acrylic resin. Eighty-

nanometer sections were mounted on an electron microscopy (EM) grid. Colloidal

bead staining was conducted by incubating the different EM grids face down on a 15

μL-droplet on a Parafilm sheet in a humidity chamber at RT. Electron microscopy

grids were incubated in PBS-glycine 50 mM for 15 min followed by a 15-min blocking

step in PBS containing 1% OVA. The grids were labeled for 30 min with

proteasome 20S alpha 3 antibody (Novus Biological) at 1:50, followed by 20 min

with 18 nm colloidal Gold-AffiniPure Donkey anti-rabbit IgG (H+L) at 1:150 (Jackson

ImmunoResearch Laboratories). Between each incubation, the EM grids were

washed under a stream of PBS. Following labelling, the grids were stained with 3%

uranyl acetate in water for 3 min prior to visualization on a FEI Tecnai G2 Spirit

BioTWIN transmission electron microscope at 80kV.

168

Confocal microscopy Platelets or PEVs were labeled with 1 µM LWA300

(proteasome probe) for 1 h 30 min at 30°C. Labeled and unlabeled platelets or PEVs

were added to a 24-well plate at 4°C for 18 h to promote adhesion to round glass

coverslips precoated with poly-L-lysine (Sigma-Aldrich). Immunocytofluorescence

staining was performed on the coverslips after centrifugation at 2,000xg for 5 min.

After three washes with PBS, the coverslips coated with platelets or EVs were

removed from the 24-well plate processed for staining on a parafilm sheet (10 ×

20 cm) organized in a gridpattern for each step: Each coverslip was flipped over (cell

side down) in the appropriate solution droplets (100 µL) for each staining step. The

samples were first blocked with 5% FBS (fetal bovine serum), 5% horse serum,

0.05% saponin in PBS for 20 min at room temperature. The primary antibodies were

diluted in the blocking solution: Integrin alpha 2b/CD41 antibody (1:100, mouse,

Novus Biologicals) and wheat germ agglutinin (WGA) - Alexa Fluor® 594 conjugate

(1:200, Invitrogen). The coverslips were transferred into the primary antibody

droplets, protected from light and incubated overnight at 4°C. After three washes in

PBS droplets, the coverslips were incubated for 2 h at room temperature with the

secondary antibodies diluted in blocking buffer: AlexaFluor647 F(ab’)2 anti-mouse

(1:300, Jackson ImmunoResearch Laboratories). The coverslips were washed three

times and mounted onto microscope slides in DAKO fluorescent mounting medium

(Agilent Technologies). Images were acquired with a Quorum Wave FX Spinning

Disk Confocal Microscope (Borealis - Leica DMI 6000B) at 63× (LEICA HCX PL

APO 63× 1.30 glycerol objective).

High-sensitivity flow cytometry (hs-FCM) All analyses were performed on a BD

Canto II Special Order Research Product (BD Biosciences) equipped with a small

particle option, as described previously (Figures 1 to 5)4, or with 20 parameters

LSRFortessa with small particle option (BD Biosciences) (Figures 6 to 8). Hs-FCM

performance tracking was performed daily before all analyses for both cytometers

using the BD cytometer setup and tracking beads (BD Biosciences,) or BD

FACSDiva CS&T Research Beads (BD Biosciences). Flow cytometer performance

was confirmed before each assay. Acquisition was performed at low speed and

169

quantification was conducted using either fluorescent polystyrene microspheres (3

μm diameter: Polysciences) of known concentration added to each tube, or

TruCount tubes (BD Biosciences). Silica particles (Kisker Biotech GmbH & Co.

Steinfurt) of known dimensions (100 nm, 500 nm and 1 μm in diameter) were used

for instrument set-up standardization. Fluorophore compensation was optimized for

every antibody panel.

Labeling of human platelets and EVs Five µl of PEV or platelet suspension were

labeled with 250 nM LWA300 proteasome probe in a total volume of 100 μL for 1 h

30 min at 30°C. Samples were then incubated with V450 anti-human CD41a

(clone HIP8) (BD Biosciences) and/or APC anti-human CD62P (clone AK-4, BD

Biosciences), APC Annexin V for phosphatidylserine (BD Biosciences),

MitoTrackerTM Deep Red FM for mitochondria (Invitrogen) for 30 min at RT and then

diluted into 500 µL PBS and analyzed by hs-FCM. Extracellular vesicles were first

gated according to their size and inner complexity (FSC PMT-H vs. SSC-H) to

consider events between approximately 100 and 1000 nm. CD41 and proteasome

expression levels were then verified in EVs. The presence of EVs was confirmed by

several negative controls: 1) EVs were ultracentrifuged at 100,000xg for 1 h at 20°C

and the supernatant was labeled as described above; 2) EVs were lysed using

0.05% Triton X-100 for 30 min at RT, before proteasome labeling and hs-FCM

analysis. 3) In addition, functionality of the EV-associated proteasomes was

confirmed by specific inhibition by epoxomicin (2.5 µM). The latter is a non-

fluorescent competitive inhibitor of the LWA300 probe and was used prior to

LWA300 labeling. To induce EV release, platelets (after addition of 5 mM of calcium)

were treated with diluent (PBS), cytochalasin B (20 µM; Sigma-Aldrich), cytochalasin

D (1 µM; Sigma-Aldrich), cytochalasin E (4 µM; Cayman Chemical), latrunculin A (10

µM; Cayman Chemical), or nocodazole (5 µM; Cayman Chemical) for 15 min at RT

and then treated with thrombin (0.5 U/mL, 4 h at RT). Platelet activation was

terminated by addition of 20 mM EDTA, and remnant platelets were removed by two

rounds of centrifugation at 1,300xg for 5 min at RT.

170

Mice C57BL/6J, FcγRIIATGN hemizygous mice and OT-1 mice were obtained from

The Jackson Laboratory (Bar Harbor, ME, USA). Mice were housed and bred in the

research center animal facility, under pathogen-free conditions. Guidelines of the

Canadian Council on Animal Care were followed in a protocol approved by the

Animal Welfare Committee at Laval University (#2017-122-2).

Antibody-mediated murine TRALI model TRALI in mice was induced as reported

previously5-6. In brief, 18 hours prior to TRALI induction, C57BL/6 mice were injected

intraperitoneally with the monoclonal antibody GK1.5 (4.5 mg/kg) to deplete CD4+ T

cells. Mice then received a single i.v. injection of a cocktail of 34-1-2S (45 mg/kg)

and AF6-88.5.5.3 (4.5 mg/kg) in a 600 µL volume on the day of experimentation.

After 90 min, mice were anesthetized with a mixture of Ketaminol and Rompun and

exsanguinated by cardiac puncture. Bronchoalveolar lavages (BAL) were collected

by flushing the lungs three times with PBS. BAL were spun at 600xg for 5 min at RT.

The supernatant was transferred in a clean tube and spun at 1,300xg for 5 min at

RT. Supernatants were stored at −80°C until hs-FCM analysis.

Immune complex injection model HA-IgG (600 μg and 750 μg in males and

females, respectively) were i.v. injected in mice as previously reported7. Mice were

sacrificed after 1 h and blood was collected by cardiac puncture in 200 µL ACD,

350 µL Tyrode’s buffer pH 6.5. Platelet-free plasma (PFP) was prepared by two

rounds of centrifugation at 2,500xg for 15 min at RT and stored at −80°C until hs-

FCM analysis.

Lymph Lymph was collected as previously described from 18-h-fasted C57BL/6J

mice8-9. For PEV analysis, lymph was centrifuged twice at 2,500xg for 15 min to

remove all residual cells. Freshly collected lymph was used for hs-FCM analysis and

frozen (at −80°C) lymph was used for immunoblotting. Platelet EVs in 1 µL lymph

were labeled with LWA300 (250 nM). The following antibodies were added for 30 min

at RT: BV421 anti-mouse CD41 (clone MWReg30, BD Biosciences), and MHC

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Class I (H-2kb) monoclonal antibody (AF6-88.5.5.3) APC (Invitrogen). Samples were

then diluted with PBS and analyzed by hs-FCM.

Intravenous injection of PEVs PEVs were prepared from freshly isolated, washed

platelets adjusted to a density of 100 × 106 cells/mL, labeled with 1 μM 5-

chloromethylfluorescein diacetate (CMFDA, Invitrogen) for 10 min at RT and then

stimulated overnight at RT with collagen (0.5 μg/mL) after addition of

5 mM calcium10. Platelet activation was terminated by addition of 20 mM EDTA, and

remnant platelets were removed by centrifugation at 2,000xg for 10 min at RT.

Platelet EVs were then ultracentrifuged (18,000xg for 90 min at 18C), resuspended

in Tyrode’s Buffer 7.4 with 5 mM calcium and stored at −80°C. CMFDA-labelled EVs

were thawed just before injection and fluorescence and count were verified by hs-

FCM. Mice were injected i.v. with 5 × 108 CMFDA-labeled EVs in 100 µL or

equivalent volume of control (PBS / Tyrode’s buffer pH 7.4 with 5 mM calcium). After

1 h, mice were sacrificed and blood, lymph nodes (LNs) (popliteal, inguinal,

mesenteric and mandibular) and spleen were harvested and processed in the dark.

Platelet-free plasma (PFP) was prepared by centrifugation of whole blood as above

and 5 µL of PFP was fixed in 500 µL final volume of PBS 2% PFA for analysis by hs-

FCM. Spleen and pooled LNs were dissected into small pieces and incubated in

1 mL of collagenase type IV (0.4 mg/mL in HBSS 1×, Biochemical Corporation) for

90 min at 37°C in a 6-well plate. Organ disruption was completed by pipetting up and

down followed by passage through a 70 µm cell strainer with the addition of 1 mL

PBS. Cells were centrifuged at 500xg for 5 min at 4°C. Spleen pellets (but not LN

pellets) were resuspended in 1 mL of ultrapure H2O for 20 s to remove RBCs. Lysis

was stopped by the addition of 110 µL Hanks' Balanced Salt Solution (HBSS) 10×

and cells were centrifuged at 500xg for 5 min at 4°C. Spleen and LN pellets were

resuspended in PBS. One hundred µL of cell suspension were labeled with Hoechst

(Invitrogen) for 10 min at RT and fixed with 100 µL 4% PFA before cytospinning

(500xg for 3 min at RT). Cells were mounted with SlowFadeTM Gold Antifade

Mountant (Invitrogen) on microscope slides. Images were acquired with a Quorum

Wave FX Spinning Disk Confocal Microscope (Borealis - Leica DMI 6000B) at 63×

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(LEICA HCX PL APO 63× 1.30 glycerol objective). Images were processed using

Volocity software.

Dendritic cell preparation Splenocytes were obtained from C57BL/6J mice by

treating the spleen with collagenase D (400 Mandl U/mL; Roche Diagnostics) and

DNAse (50 μg/mL; Roche Diagnostics) for 30 min at 37°C as previously described11-

12. Fetal bovine serum was added and the spleen was dilacerated between two

microscope slides. The cells were then filtered through 40 µm cell strainers in

complete medium: (RPMI 1640–glutamate, 50 U/mL penicillin-streptomycin, 10 mM

HEPES, 1 mM sodium pyruvate [Thermo Fisher Scientific], and 5% SVF). Cells were

washed twice in complete medium by centrifugation at 700xg for 10 min. Dendritic

cells were enriched from splenocytes with 250 µL of the Dendritic Cell Enrichment

Set (BD Biosciences) biotinylated antibodies for 15 min at 4°C. Cells were washed

and 250 µL streptavidin beads were added for 30 min at 4°C before magnetic

separation (10 min on the magnet). Dendritic cells were counted and used

immediately.

Data analysis Hs-FCM data were analyzed using FlowJo software V.10.1 (BD

Biosciences). Statistical analyses were performed using GraphPad Prism 7.0

software (GraphPad Software). Gaussian distribution of the datasets was tested

prior to performing the statistical analysis. The test performed for each comparison

is specified in the corresponding legend, i.e. Wilcoxon, Mann–Whitney or Student’s

t-tests for 2 group comparisons and Friedman test followed by Dunn’s post-test for

multiple comparison for multi-experimental comparisons or Kruskal-Wallis. Only

relevant statistical tests are reported in the figures. Results are expressed as mean

± standard error of mean (SEM). The p-values (P) <0.05 were considered statistically

significant.

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4.10 Supplementary figures

Supplementary Fig. 1: Gate design for EV analysis (A) Gating used for the characterization of platelets, large and small platelet-derived extracellular vesicles (PEVs). (B) Silica beads of 100 nm, 500 nm and 1,000 nm of diameter used to approximate the size of the small and large EV populations.

174

Supplementary Fig. 2: Characterization of proteasome PEV diversity using a fluorescent proteasomal activity-based probe (A) Proteasome-containing PEVs co-occur with the expression of phosphatidylserine (Annexin V+, n = 7), P-selectin (n = 6) or mitochondria (n = 9). Data are presented as mean ± SEM. (B) Release of proteasome-containing (left) or not (right) PEVs from thrombin-activated platelets requires intact actin microfilament dynamics. PEV and proteasome-containing PEV release is significantly reduced following addition of actin inhibitors cytochalasin (Cyto) B, D and E and latrunculin (Lat) A, but not tubulin polymerization inhibitor (nocodazole) (n = 6 data are presented as mean ± SEM, * P < 0.05, ** P < 0.01 Wilcoxon compared to DMSO). (C) ADP, cross-linked collagen-related peptide (CRP-XL), heat-aggregated IgG (HA-IgG), and thrombin activation for 3 hours trigger the release of CD41+Proteasome+ PEVs quantified by hs-FCM (n = 5; data are presented as mean ± SEM. *P < 0.05, Wilcoxon vs. supernatant from resting platelets).

175

4.11 Supplementary references

1. Cognasse F, Aloui C, Anh Nguyen K, et al. Platelet components associated with

adverse reactions: predictive value of mitochondrial DNA relative to biological response

modifiers. Transfusion. 2016;56(2):497-504.

2. Cognasse F, Sut C, Fromont E, Laradi S, Hamzeh-Cognasse H, Garraud O. Platelet

soluble CD40-ligand level is associated with transfusion adverse reactions in a mixed

threshold-and-hit model. Blood. 2017;130(11):1380-1383.

3. Marcoux G, Magron A, Sut C, et al. Platelet-derived extracellular vesicles convey

mitochondrial DAMPs in platelet concentrates and their levels are associated with adverse

reactions. Transfusion (Paris). 2019;59(7):2403-2414.

4. Boudreau LH, Duchez AC, Cloutier N, et al. Platelets release mitochondria serving

as substrate for bactericidal group IIA-secreted phospholipase A2 to promote inflammation.

Blood. 2014;124(14):2173-2183.


against transfusion-related acute lung injury via IL-10. Blood. 2017;129(18):2557-2569.


development of murine transfusion-related acute lung injury. Blood Adv. 2018;2(13):1651-

1663.

7. Cloutier N, Allaeys I, Marcoux G, et al. Platelets release pathogenic serotonin and

return to circulation after immune complex-mediated sequestration. Proc Natl Acad Sci U S

A. 2018;115(7):E1550-E1559.

8. Milasan A, Tessandier N, Tan S, Brisson A, Boilard E, Martel C. Extracellular

vesicles are present in mouse lymph and their level differs in atherosclerosis. J Extracell

Vesicles. 2016;5:31427.

9. Tessandier N, Melki I, Cloutier N, et al. Platelets Disseminate Extracellular

Vesicles in Lymph in Rheumatoid Arthritis. Arterioscler Thromb Vasc Biol.

2020:ATVBAHA119313698.

10. Rousseau M, Belleannee C, Duchez AC, et al. Detection and quantification of

microparticles from different cellular lineages using flow cytometry. Evaluation of the

impact of secreted phospholipase A2 on microparticle assessment. PLoS One.

2015;10(1):e0116812.

11. Elayeb R, Tamagne M, Bierling P, Noizat-Pirenne F, Vingert B. Red blood cell

alloimmunization is influenced by the delay between Toll-like receptor agonist injection

and transfusion. Haematologica. 2016;101(2):209-218.

12. Elayeb R, Tamagne M, Pinheiro M, et al. Anti-CD20 Antibody Prevents Red Blood

Cell Alloimmunization in a Mouse Model. J Immunol. 2017;199(11):3771-3780.

176

Discussion

5.1 Mise en contexte

Les EV sont des vésicules membranaires de petite taille produites par tout type

cellulaire et libérées dans le milieu extracellulaire. L’émergence de leur importance

dans de nombreuses fonctions, principalement pour la communication intercellulaire

et la régulation de conditions physiologiques et pathologiques[341-343], a forcé la

mise en place et le développement de nombreux éléments afin d’améliorer la

recherche dans le domaine. Que ce soit via la création de l’ISEV et de bases de

données sur les EV ou bien via la mise en place de nombreux congrès, les

scientifiques ont contribué lors des dernières années à améliorer la qualité de la

recherche sur les EV[366, 367, 369-371]. En 2019, la dernière version des

exigences expérimentales minimales pour la définition des EV et de leurs fonctions

a été publiée[368]. Cette version est la troisième publiée depuis mon arrivée dans le

laboratoire (2013) et le début de ma thèse (fin 2015). Étant donné les efforts mis en

place dans les dernières années, notamment concernant l’institution d’une

nomenclature cohérente des EV[366], vous aurez probablement remarqué une

évolution entre les articles insérés dans ce manuscrit.

Dès le début de ma thèse, un effort constant a été déployé pour respecter les

exigences expérimentales minimales. Bien que la taille des EV que j’ai étudiées par

cytométrie en flux corresponde davantage aux microvésicules qu’aux exosomes,

nous avons toujours fait preuve de prudence dans notre nomenclature. Nous avons

évité le terme microvésicule/microparticule, n’ayant jamais visualisé la production

des vésicules par des techniques d’imagerie en temps réel ce qui est nécessaire

selon le MISEV pour confirmer leur origine[367]. Concernant la caractérisation des

EV par cytométrie en flux, les articles des trois chapitres respectent les exigences

minimales. En effet, nous avons toujours fait preuve de transparence dans notre

caractérisation des EV en donnant une description détaillée de la collection, de

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l’isolation, de l’entreposage, des protocoles de marquages et des caractéristiques

du cytomètre utilisé. Chacun des articles présente, dans ses premières figures, tous

les contrôles nécessaires pour confirmer la spécificité des marquages et la nature

membranaire des EV étudiées ainsi que leur taille et leur quantité. Non seulement

le domaine a grandement évolué, mes connaissances se sont aussi approfondies.

Cette discussion aura donc pour but de faire un résumé des découvertes, mais aussi

de prendre du recul sur les résultats publiés au cours des dernières années et de

leur impact.

Mes travaux présentés dans cette thèse portent sur diversité des EV de

plaquettes, plus précisément en ce qui concerne leur contenu en

mitochondries et en protéasome et les différentes fonctions qu’elles peuvent

exercer dans l’inflammation et l’immunité

5.2 Résumé des découvertes et discussion

Un regard neuf sur la diversité des EV

Les EV sont hétérogènes et cette diversité pourrait permettre leur utilisation comme

biomarqueur[378, 383, 450, 451]. Bien que les techniques d’isolation et de

caractérisation des EV aient été améliorées dans les dernières années, l’utilisation

de la cytométrie en flux pour leur analyse n’est toujours pas optimale. La séparation

entre les EV et le bruit de fond de l’appareil est difficile, de même que la mise en

évidence de populations rares[451]. De plus, en cherchant à étudier la diversité et

l’hétérogénéité des EVs, il est nécessaire d’utiliser plusieurs marqueurs ce qui

complique l’analyse et celle-ci peut varier considérablement entre les utilisateurs.

Comme l’interprétation des résultats était un défi important et qu’à cette époque il

n’y avait aucune étude rapportant un moyen de faciliter l'interprétation des analyses

cytofluorométriques des EV, nous avons cherché une solution. Parmi les approches

déjà utilisées pour l’analyse des cellules, nous avons sélectionné l’algorithme

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SPADE[452, 453]. Cet algorithme présentait l’avantage d’une analyse automatique,

donc non influencée par l’utilisateur[452, 454]. Il permettait également la

visualisation de populations peu abondantes et d’obtenir une vue d'ensemble de

l'hétérogénéité cellulaire en montrant une continuité du phénotype.

L’application de l’algorithme SPADE à l’analyse de nos EV par cytométrie en flux à

haute sensibilité nous a permis d’organiser les sous-populations d’EV de plaquettes

et de globules rouges et d’apprécier leur hétérogénéité. Nous avons ainsi pu

appliquer cette technique à l’analyse de la composition des EV présentes dans le

liquide synovial de patients arthritiques. Notre étude a révélé que l’utilisation

d’algorithmes couplés à la cytométrie en flux tels que SPADE pourrait faciliter la

compréhension des fonctions des EV et le développement de leur étude comme

biomarqueurs.

Avec du recul, cette combinaison entre l’utilisation d’un algorithme et l’analyse de la

diversité des EV par cytométrie en flux était innovante. Bien que l’article ait eu un

impact limité dans le domaine avec 19 citations[455-471], nous avons pu montrer

que l’hétérogénéité des EV ajoute un niveau de complexité supérieur pour l’analyse,

mais que celui-ci est nécessaire pour l’avancement des connaissances dans le

domaine. L’étude des sous-populations d’un même type d’EV, de plaquettes dans

le cas présent, a permis de stratifier des patients arthritiques. De plus, cette étude a

encouragé d’autres équipes de recherche à utiliser SPADE et des algorithmes

similaires pour étudier les EV[468, 469]. Alors qu’en 2015-2016, il était nécessaire

d’avoir des connaissances en bio-informatique pour pouvoir utiliser SPADE, cet

algorithme et d’autres sont maintenant intégrés directement dans les logiciels

d’analyse classiques de cytométrie en flux tels que FlowJo et FCS Express. Bien

que j’ai personnellement aimé apprendre des notions de bio-informatique, je crois

qu’il était nécessaire de rendre l’utilisation d’algorithmes plus accessible à tous pour

favoriser leur application. En conclusion, nous avons contribué à mettre l’emphase

sur l’importance de l’analyse de l’hétérogénéité des EV. Une meilleure

caractérisation de l’hétérogénéité des EV, basée non seulement sur leur source et

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leur taille, mais aussi sur leur cargo pourra nous permettre une meilleure

compréhension de leur rôle critique dans la physiologie et les pathologies.

dans l’inflammation…

Dans la continuité de ce projet, je me suis intéressée à la diversité du cargo contenu

dans les EV de plaquettes, notamment concernant le contenu en organelles. Notre

laboratoire a déjà montré que les EV de plaquettes, lors de leur genèse, peuvent

apporter avec elles des mitochondries fonctionnelles situées à proximité de la

membrane plasmique[382]. Ces dernières forment une population hétérogène selon

la présence ou l’absence de mitochondries[382]. Des mitochondries extracellulaires,

qui ne sont pas entourées d’une membrane de plaquette (freeMitos), ont aussi été

observées dans les liquides biologiques et les PC servant pour la transfusion[382].

L’hydrolyse de la membrane mitochondriale par la phospholipase A2 IIA entraîne

non seulement la libération de médiateurs inflammatoires[382], mais de l’ADN

mitochondrial est aussi retrouvé dans les EV et est potentiellement

inflammatoire[429, 430].

Lors de mon projet de maitrise, je m’étais intéressée à la libération des sous-

populations d’EV de plaquettes et de leur contenu en mitochondries dans les PC

préparés selon trois techniques différentes, soit le plasma riche en plaquettes, la

couche leucoplaquettaire et l’aphérèse sur une période de 7 jours. Cette étude nous

a permis de conclure que le mode de préparation, plutôt que la durée de stockage,

a un impact sur la libération des EV contenant ou non des mitochondries dans les

PC[449]. Toutefois, même après 7 jours d’entreposage, les PC étudiés dans cette

étude avaient un niveau d’ADN mitochondrial bien inférieur à la quantité détectée

dans les PC impliqués dans des réactions transfusionnelles[382, 449]. Ainsi, bien

que les EV de plaquettes semblent être impliquées dans les réactions

transfusionnelles, des études supplémentaires adressant le mécanisme de

libération de l’ADN mitochondrial dans les PC et le mécanisme d’implication des EV

étaient nécessaires.

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Comme aucune étude n'avait officiellement vérifié la présence de sous-populations

d’EV de plaquettes dans les PC impliqués dans des réactions transfusionnelles

indésirables, nous avons exploré ce lien dans les PC qui ont induit ou non des

réactions transfusionnelles. Nous avons donc émis l’hypothèse que les EV de

plaquettes contenant des mitochondries représentent un réservoir d'ADN

mitochondrial. Nous avons observé que non seulement les EV contenant des

mitochondries étaient plus abondantes dans les PC impliqués dans des réactions

transfusionnelles, mais qu’elles corrélaient significativement avec l’ADN

mitochondrial.[472] De plus, nous avons confirmé que la vaste majorité de l’ADN

mitochondrial détecté dans les PC est encapsulé dans des EV[472]. Cette étude

nécessite d’être répliquée dans une cohorte plus grande, mais elle suggère que la

quantification d’EV de plaquette pourrait être un biomarqueur potentiel pour la

prévention de réactions transfusionnelles.

La présence d’un cargo mitochondrial n’est pas unique aux vésicules de plaquettes

et sont utilisation en tant que biomarqueur est de plus en plus envisagée en dehors

du domaine transfusionnel. Par exemple, des EV contenant des DAMPS

mitochondriaux sont présentes en plus grande quantité chez les patients atteints de

la maladie de Parkinson[473, 474]. Ces EV contenant des mitochondries sont aussi

augmentées dans le plasma de patients atteints de mélanome, de cancer des

ovaires et de cancer du sein[475]. L’absence ou la diminution du cargo mitochondrial

peut aussi être indicateur de maladies. Par exemple, bien qu’une grande quantité

d’EV de plaquettes soit produite lors d’infection par le HIV, la proportion d’EV

contenant des mitochondries et leur densité est inférieure chez les malades que

chez les contrôles[476]. La diminution du contenu mitochondrial dans les EV est

aussi un marqueur potentiel pour le diagnostic des troubles du spectre autistique et

le syndrome du X fragile[477].

Bien qu’elle requiert un faible volume d’échantillon à analyser, cette approche serait

toutefois limitée étant donné qu’elle implique l’utilisation d’un cytomètre adapté à

l’analyse des EV. De plus, l’harmonisation de l’analyse des EV entre les différents

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laboratoires est complexe et nécessite d’avoir des utilisateurs expérimentés. Étant

donné la forte corrélation entre la présence d’EV de plaquettes contenant des

mitochondries et la quantité d’ADN mitochondrial dans les PC, une approche plus

simple et plus accessible serait l’utilisation de la PCR quantitative ou d’une technique

similaire pour quantifier l’ADN mitochondrial.

Cette étude suggère que les EV et leur cargo en mitochondrie peuvent être un

biomarqueur utile pour la prédiction du risque potentiel de réactions

transfusionnelles. Il reste toutefois à déterminer si l’ADN mitochondrial encapsulé

dans les EV, par opposition à l'ADN mitochondrial libre dans le plasma, est aussi

inflammatoire. Considérant que l'induction des EV de plaquettes est observée

fréquemment en conditions inflammatoires, il serait pertinent de valider si leur

présence explique aussi la présence d’ADN mitochondrial. Il faudrait donc évaluer

si l’ADN mitochondrial encapsulé a le potentiel d’activer le TLR9 in vivo aussi

efficacement que l’ADN libre. De plus, il sera important de considérer l’effet du reste

du cargo inflammatoire de la mitochondrie, tel que les cardiolipides, les ROS, l’ARN

mitochondrial[478] ou l’ATP qui sont responsables de dommages aux poumons[405]

en plus du cargo inflammatoire des EV de plaquettes.

Un modèle in vivo pertinent de réaction transfusionnel pour répondre à ces questions

serait le modèle de TRALI murin. Ce modèle a déjà été utilisé pour montrer

l’implication de plaquettes conservées plusieurs jours et d’EV libérées lors de

l’entreposage dans le développement du TRALI[479, 480]. Une continuité de ce

projet serait de continuer à décortiquer l’hétérogénéité des EV de plaquettes dans

le modèle de TRALI murin et d’évaluer leur effet dans l’initiation du TRALI et dans

les dommages aux poumons.

Un article récent a montré que l'emballage sélectif des protéines mitochondriales

dans des vésicules extracellulaires empêche la libération de DAMP

mitochondriaux[481]. Puisque la membrane vésiculaire confère une protection

contre la dégradation lors du transport[472], et que les EV de plaquettes sont

retrouvées en grande quantité dans la circulation, il serait important de considérer

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un aspect que nous avons négligé. Les EV de nombreuses sources cellulaires

peuvent être utilisées pour effectuer un transfert horizontal du contenu mitochondrial

dans le traitement de diverses maladies. Par exemple, les cellules souches

mésenchymateuses sécrètent des EV contenant des mitochondries

fonctionnelles[482]. Celles-ci peuvent transférer leurs mitochondries à d’autres

cellules telles que les cellules épithéliales du poumon, ce qui améliore leur capacité

à refermer des plaies[483], ou bien aux macrophages pour les polariser vers un

phénotype anti-inflammatoire[482, 484]. Des EV de cellules souches dérivées de

cardiomyocytes contenant des mitochondries ont aussi été utilisées pour améliorer

les fonctions cardiaques post ischémie et offrent une possibilité thérapeutique pour

les maladies cardiaques[485]. Les cellules souches neuronales peuvent aussi

transférer leurs mitochondries via la production d’EV aux phagocytes

mononucléaires dans un modèle murin de sclérose en plaques. Ce transfert à

permis de rétablir les dysfonctions mitochondriales présentes et d’améliorer l’état

clinique ce qui suggère un traitement potentiel non seulement pour la sclérose en

plaques, mais aussi pour les autres maladies neurodégénératives[486]. D’ailleurs,

les EV d’astrocytes contenant des mitochondries se sont avérées efficaces dans le

traitement de maladies telles que l’Alzheimer[487] et les accidents vasculaires

cérébraux[477]. Ces exemples sont la preuve que non seulement les EV de

plaquettes contenant des mitochondries ont un potentiel comme biomarqueur, elles

pourraient aussi être utilisées d’un point de vue thérapeutique.

…et dans l’immunité

Lors de ma thèse, j’ai eu la chance de collaborer sur un autre projet visant à mettre

en lumière la diversité du contenu en organelles des EV de plaquettes, non pas

uniquement dans un contexte d’inflammation, mais égalemment d’immunité. J’ai

initialement contribué à ce projet pour finalement l’amener à terme lors du départ de

la post-doctorante qui l’avait initié. Ceci m’a permis de m’éloigner du domaine de la

transfusion et de m’intéresser davantage au rôle immunitaire des plaquettes,

élargissant mon champ d’expertise développé pendant le doctorat.

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Les plaquettes et les mégacaryocytes contribuent à l’immunité innée et

adaptative[488]. Elles contiennent un protéasome actif et présentent des antigènes

par l'intermédiaire du CMH I[143, 318, 319, 338]. Pour ce projet, nous avons émis

l'hypothèse qu'une machinerie fonctionnelle d’apprêtement et de présentation de

l'antigène est transférée aux EV de plaquettes lors de leur activation. Nous avons

non seulement démontré la présence d'un protéasome 20S actif dans les EV de

plaquettes dans diverses conditions où les plaquettes sont activées, mais aussi

démontré que les PEV incubées avec l’OVA peuvent apprêter et présenter

efficacement l’antigène.

Les PEV ne sont pas les seuls types d'EV qui contribuent à la présentation de

l'antigène. Il a déjà été prouvé que les EV dérivées de cellules immunitaires telles

que les DC, les lymphocytes B, les lymphocytes T, les macrophages et les cellules

NK ont un rôle dans la présentation antigénique [80-85]. Tout comme nous l’avons

montré pour les plaquettes, il a été mis en évidence que les EV dérivées de cellules

NK contiennent des composants du système protéasome-ubiquitine[489] et que les

lymphocytes T exportent du protéasome via leurs vésicules, ce qui explique une

grande partie du protéasome extracellulaire observé dans de nombreuses

conditions pathologiques[418, 467]. Les cellules endothéliales libèrent aussi des EV

contenant du protéasome et ces dernières induisent la production d’autoanticorps et

accélèrent le rejet de greffe[169]. Les EV dérivées de macrophages associées aux

tumeurs, de cellules souches mésenchymateuses et d’ostéoclastes contiennent

aussi du protéasome et participent au remodelage tissulaire[419, 490, 491]. Cette

fonction de remodelage est d’ailleurs utilisée par de nombreux pathogènes tels que

Plasmodium falciparum, Acanthamoeba castellanii, Toxoplasma gondii,

Echinococcus granulosus, Leishmania, Trichuris muris, Trichomonas vaginalis et

certains champignons pour altérer la membrane cellulaire de son hôte et faciliter

l’infection[492]. Ceci est un élément supplémentaire appuyant le rôle des EV, et par

extension des plaquettes, dans la régulation de l’immunité en conditions

physiologiques ou pathologiques[493, 494]. De plus, en plus de la présentation

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antigénique, il n’est pas exclu que les EV de plaquettes puissent elle aussi participer

au rejet de greffe, à la production d’autoanticorps, à la réponse antitumorale et au

remodelage tissulaire comme c’est le cas pour les EV d’autres types cellulaires.

Il a récemment été démontré que les MK pulmonaires peuvent induire l’activation de

lymphocytes T CD4+ via le CMH II in vitro et in vivo[337]. Cet article a soulevé de

nombreuses questions. Premièrement, est-ce que les EV de plaquettes pouvant

effectuer la présentation antigénique proviennent de plaquettes strictement dérivées

des MK pulmonaires? Deuxièmement, est-ce que les plaquettes dérivées des MK

pulmonaires expriment aussi le CMH II et, par conséquent, est-ce que les EV de MK

pulmonaires et de plaquettes peuvent aussi effectuer la présentation aux

lymphocytes T CD4+ ? Mon étude s’est focalisée sur les EV de plaquettes, mais il

faudra aussi vérifier si les EV dérivées de MK sont capables d’effectuer la

présentation antigénique via le CMH I ou le CMH II en émettant l’hypothèse que la

présentation puisse même être augmentée dans les cas des EV dérivées des MK

pulmonaires.

Les EV de plaquettes ayant un accès privilégié au système lymphatique et aux

organes lymphoïdes, elles contribueraient à une fonction immunitaire

supplémentaire des plaquettes, cette fois en dehors de la circulation sanguine. Il

sera cependant nécessaire de déterminer l’impact et l’importance réelle des EV de

plaquettes en tant qu’éléments présentant l’antigène. Une autre limite de cette étude

est que le mécanisme exact d’apprêtement et de présentation de l’antigène n’est

pas connu. Ceci est d’ailleurs le cas pour la présentation antigénique par les

plaquettes et par les autres types d’EV. Un effort collectif sera nécessaire dans les

prochaines années pour mieux décortiquer et comprendre la contribution des EV

dans la présentation antigénique.

185

Conclusion

Les travaux présents dans cette thèse montrent que les plaquettes activées libèrent

à la fois des mitochondries et du protéasome. En étudiant la diversité du contenu en

organelles des EV de plaquettes en contexte inflammatoire et immunitaire, cette

étude a mis en évidence l’importance de s’intéresser à l’hétérogénéité des EV et

soutient le concept selon lequel différents sous-types de PEV peuvent jouer des

rôles différents en fonction de leur cargo.

186

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212

Annexe I: Mitochondrial damage-associated

molecular patterns in blood transfusion products

Genevieve Marcoux1,2,3 et Eric Boilard1,2,3 Affiliations

1 Axe Maladies Infectieuses et Inflammatoires, Centre de Recherche du CHU de Québec, Université Laval, Québec, QC, Canada.

2 Département de Microbiologie-infectiologie et D'immunologie and Centre ARThrite, Université Laval, Québec, QC, Canada.

3 Department of Infectious Diseases and Immunity, Centre de Recherche du CHU de Québec, Québec, QC, Canada.

213

Abstract

Mitochondria are organelles in charge of energy supply and the control of apoptosis.

Owing to their similarities with bacteria, however, extracellular mitochondria are

considered damage‐associated molecular patterns (DAMPs) capable of activating

the immune system and non‐immune cells. Studies revealed that diverse blood

products contain extracellular mitochondria, which could account for the adverse

reactions that can occur in transfusion. In this review, we discuss how mitochondrial

DAMPs can trigger inflammatory responses, we highlight conditions relevant to

transfusion during which mitochondria have been identified outside cells, and we

discuss their potential as biomarkers for the assessment of blood product quality.

214

Mitochondria and inflammation

The mitochondrion is a small organelle localized within cells that mediates the

oxidative phosphorylation necessary for ATP production1. In addition to its role in

energy supply, the mitochondrion also plays an instrumental role in the control of cell

division and apoptosis1, 2. The number of mitochondria present in different cellular

lineages is variable: there are no mitochondria in erythrocytes, approximately 4–7

mitochondria in platelets and leucocytes, and up to 2000 mitochondria in

hepatocytes1, 3. Depending on the metabolic activities necessary for cell functions,

the size of mitochondria can vary (0.5 μm to 10 μm)4, 5, with platelets presenting

smaller mitochondria, and cardiomyocytes demonstrating changes in mitochondrial

dimensions depending on their activities and hypoxia3, 6. Moreover, mitochondria are

dynamic organelles; they can divide, a process known as fission, and can merge

together, a process known as fusion7.

Studies suggest that mitochondria share with bacteria several similarities8, 9. Both

bacteria and mitochondria can consume O2 and produce CO2, express formylated

peptides10, 11 and bear a circular genome composed of hypomethylated CpG DNA

motifs12, 13. Hence, the genome of mitochondria shares significant levels of homology

with the one of Rickettsia prowatzekii, a gram‐negative alphaproteobacteria,

suggesting that they might have a common ancestor12-14. While the mitochondrion

in the cytosol contributes to activation of the inflammasome, its components can also

activate pathogen recognition receptor (PRR), thus providing distinct mechanisms

potentially leading to inflammatory responses15, 16. Reactive oxygen species (ROS)

and ATP derived from mitochondria are known triggers of inflammasomes and were

shown to activate Type I interferon regulated genes17. Its mitochondrial DNA

(mtDNA) can activate toll‐like receptors (TLR) present in endosomes whereas its

formylated peptides can activate formyl peptide receptors (Fig. 1)10, 18-20.

215

Figure 1: Mitochondria participate to inflammasome activation. Mitochondria in

the extracellular milieu are a source of diverse damage‐associated molecular

patterns such as ATP, Reactive oxygen species, N‐formyl peptides, which are

sensed through formyl peptide receptors (FPR) and mtDNA, which triggers toll‐like

receptors (TLR9) in endosomes. These mitochondrial components are able to promote of activation of the inflammasome, particularly NLRP3.

216

Mitochondrial release

Mitochondria are released from different cellular lineages in multiple conditions:

Damaged organs or tissues (e.g. liver and brain)11, 21-23, neutrophils24-26,

hepatocytes21, mast cells27, eosinophils28, T cells29 and platelets3, 30 can release

mitochondria. Extracellular mitochondria have been described in brain trauma31, in

synovial fluid of patients with rheumatoid arthritis3, 32, in systemic lupus

erythematosus25, 26, in steatohepatitis21, burn injury33 and in blood of patients at the

intensive care unit34. As parasites also expulse their mitochondria33, it points to a

well‐conserved mechanism and suggests that it might have relevance to different

biological processes yet to determine.

With their great abundance in blood, platelets are the main pool of mitochondria in

blood circulation. Thus, the presence of mitochondria in the extracellular milieu in

blood transfusion products, such as stored red blood cells, plasma and platelet

concentrates3, 35-37, is highly likely to reflect platelet activation or lesions, which might

have occurred during blood collection, blood processing, storage condition and

duration or treatment with agents (e.g. pathogen inactivation systems and platelet

additive solutions)36-40. Evidence of mitochondrial release by platelets originate from

studies on platelet extracellular vesicles, submicron vesicles released by cells on

activation or apoptosis. Extracellular vesicles produced by platelets, known as

microparticles, were revealed to contain mitochondrial peptides41, pointing to a

mitochondrial content. Whether mitochondria were actually present in microparticles

was however unknown. Studies were, therefore, undertaken to determine the impact

of platelet activation on mitochondrial release. Boudreau et al.3 showed that various

stimuli (collagen, thrombin and ionophore) could induce release of mitochondria.

Mitochondria were identified in the extracellular milieu either as naked organelle (free

mitochondria) or encapsulated within microparticles3. These structures were

quantified using flow cytometry and visualized using electron microscopy. Given that

platelets represent an important source of mitochondria in blood circulation, platelet

concentrates were searched for the presence of extracellular mitochondria.

Mitochondria, both as free organelle and inside microparticles, were found in platelet

217

concentrates prepared in blood bank conditions3. Interestingly, a simultaneous study

confirmed that mtDNA is present in various blood products, such as plasma, platelet

concentrates and stored red blood cells33. It is noteworthy to mention that the

quantification of mtDNA in extracellular milieu is an actual measure of potential

mtDNA in solution, free mitochondria and microparticle‐containing mitochondria. A

complete characterization of the extracellular mitochondria is thus needed in order

to determine the mechanism leading to mitochondrial release and to understand their

impact on other cells. Although the origin of mtDNA in these products is unknown, it

is tempting to speculate that most originate from platelets.

218

Extracellular mitochondria and adverse reactions

There are studies in which the potential contribution of extracellular mitochondria to

adverse reactions was examined. Boudreau et al. quantified mtDNA in the

extracellular milieu of platelet concentrates that has induced adverse reactions and

compared the levels within samples that were transfused without incidents3.

Interestingly, the authors confirmed that significantly higher levels of extracellular

mitochondria correlated with adverse reactions. Using a decisional tree based on an

algorithm to compare cytokine levels and mtDNA, Cognasse et al. found that mtDNA

did not correlate with levels of cytokines, suggesting that it might be an independent

risk factor40, 42. Importantly, these observations were corroborated by Yasui et al.

who further confirmed that elevated levels of mtDNA were present in platelet

concentrates that induced nonhemolytic transfusion reactions (NHTRs) in platelet

transfusion43. Moreover, levels of mtDNA present in plasma and platelet

concentrates correlate well with levels of mtDNA in serum of post‐transfusion

patients and are associated with higher risk of acute respiratory distress syndrome35,

44.

How exactly mitochondria may mediate their inflammatory role in transfusion is

unknown, but different studies on transfusion research provided mechanistic

insights. Boudreau et al. suggested that an enzyme, a secretory phospholipase A2

(sPLA2) called IIA (sPLA2‐IIA), could hydrolyse naked mitochondria, due to its

bactericidal properties, and thereby release mtDNA and lysophospholipids, which

are known triggers of transfusion related acute lung injury3, 45. Hence sPLA2‐IIA is

present in blood, in platelet concentrates, and is induced in blood in inflammatory

conditions3. Yasui et al. found that mtDNA could activate neutrophils, monocytes and

basophils43. The authors showed that when neutrophils were primed with formylated

peptides or anti‐HLA antibodies, mtDNA at concentrations found in nonhaemolytic

transfusion reactions could induce oxidative burst and Mac‐ 1 expression43.

Although studies are still needed to confirm whether or not platelet concentrates also

contain extracellular formylated peptides, mitochondrial formylated peptides were

219

found to induce neutrophil infiltration and airway contraction, further demonstrating

that extracellular mitochondria could contribute to adverse reactions through diverse

components, other than mtDNA46.

220

Extracellular mitochondria as a biomarker

What induces mitochondrial release in blood transfusion products is not clear at the

moment. Given that mtDNA is present in frozen plasma, it suggests that

mitochondria were released prior to plasma preparation. The combination of flow

cytometry and spanning‐tree progression analysis of density‐normalized events

(SPADE) as computational approach permits a better appreciation of the

heterogeneity of microparticles (i.e. cellular source, compartment origin, organelle

content and surface markers expression)47. Using flow cytometry and SPADE to

assess presence of naked organelles and mitochondria encapsulated in

microparticles, it was found that the preparation method had a significant impact on

extrusion of mitochondria and that storage duration had no or very modest effect on

release37, 38, 47. Platelets prepared using the platelet‐rich plasma method contained

more extracellular mitochondria than those prepared using apheresis and buffy coat

methods, even before storage37. Furthermore, treatments of platelets with pathogen

inactivation systems, which can induce release of microparticles39, 48, also

engendered mitochondrial release36. There is currently no study that verified whether

mitochondrial damage‐associated molecular patterns (DAMPs)16, 20 were actually

present in blood of certain blood donors, thus prior blood processing and storage.

221

Summary

Although more work is necessary to confirm whether mitochondrial DAMPs are the

actual cause of adverse reactions, the measurement of mtDNA in blood transfusion

products is a simple inexpensive approach to determine its quality. Using a

quantitative PCR, it was found that pathogen inactivation systems could cross‐link

mtDNA, thus impeding polymerase reactions when longer amplification fragments

are generated49. While these observations confirm that Intercept and Mirasol are

both capable of damaging mtDNA50, 51, the approach reported in this study49 permits

to confirm efficiency of the inactivation process. Quantitative PCR can also be

performed to assess the presence of mtDNA in the extracellular milieu. In sum,

quantification of mtDNA using PCR or assessment of extracellular mitochondria

using flow cytometry are powerful strategies to determine the quality of blood

transfusion products.

There is a growing number of studies that report mitochondrial release in

pathological conditions. Future studies are thus needed to determine whether

extracellular mitochondria are more abundant in blood of certain blood donors,

thereby explaining their presence in only a fraction of blood products. While

mitochondrial release might be part of well‐regulated mechanisms of intercellular

communication in differential biological processes, the presence of extracellular

mitochondria in blood transfusion products, however, may contribute to adverse

reactions. The assessment of extracellular mitochondria in blood transfusion

products will indicate the usefulness of this biomarker in transfusion and will

contribute to determine conditions underlying mitochondrial release.

222

Acknowledgements

The authors declare no competing financial interests. EB and GM wrote the review.

This work was supported by the Canadian Institutes of Health Research and the

Canadian Blood Services (EB). EB is the recipient of a Canadian Institutes of Health

Research new investigator award and is a Canadian National Transplant Research

Program researcher. GM is a recipient of awards from the Canadian Blood Services.

The views expressed herein do not necessarily represent the view of the federal

government.

223

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226

Annexe II: Role of platelets and megakaryocytes in

adaptive immunity

Genevieve Marcoux 1 ,2 , 3 , Audrée Laroche 1, 2 , 3 , Jenifer Espinoza Romero1 , 2 , 3

and Eric Boilard 1 , 2 ,3

Affiliations

1 Axe Maladies Infectieuses et Inflammatoires, Centre de Recherche du CHU de Québec, Université Laval , Québec, QC, Canada.

2 Département de Microbiologie-infectiologie et D'immunologie and Centre ARThrite, Université Laval , Québec, QC, Canada.

3 Department of Infectious Diseases and Immunity, Centre de Recherche du CHU de Québec , Québec, QC, Canada.

227

Abstract

The immune system is comprised of two principal interconnected components called

innate and adaptive immunity. While the innate immune system mounts a

nonspecific response that provides protection against the spread of foreign

pathogens, the adaptive immune system has developed to specifically recognize a

given pathogen and lead to immunological memory. Platelets are small fragments

produced from megakaryocytes in bone marrow and lungs. They circulate

throughout the blood to monitor the integrity of the vasculature and to prevent

bleeding. Given their large repertoire of immune receptors and inflammatory

molecules, platelets and megakaryocytes can contribute to both innate and adaptive

immunity. In adaptive immunity, platelets and megakaryocytes can process and

present antigens to lymphocytes. Moreover, platelets, via FcγRIIA, rapidly respond

to pathogens in an immune host when antibodies are present. This manuscript

reviews the reported contributions of platelets and megakaryocytes with emphasis

on antigen presentation and antibody response in adaptive immunity.

228

Introduction

The ability of an organism to defend itself against foreign substances and infectious

agents principally requires contributions from two components of the immune

system, namely innate or natural immunity and acquired, also known as adaptive,

immunity. The innate immune response implicates the recognition of well-conserved

molecular motifs, known as pathogen-associated or damage-associated molecular

patterns (respectively PAMPs or DAMPs). Pathogen-associated molecular patterns

are exogenous components conserved among a large spectrum of microorganisms

and allergens, while DAMPs, derived from host cells, are endogenous alarm signals

produced during cellular stress or death and lead to sterile inflammatory responses

[1,2]. PAMPs and DAMPs bind to cell surface receptors and intracellular sensors

known as pattern recognition receptors (PRRs), which include the Toll-like receptors

(TLRs), NOD-like receptors (NLRs), RIG-I-like receptors (RLRs), and C-type lectin-

like receptors (CLRs). Pattern recognition receptors are expressed by innate

immune cells and nonimmune cells. Innate immune responses are nonspecific and

do not confer long-lasting immunity.

In contrast, the adaptive immune system has evolved to confer immunological

memory. It involves a process called antigen presentation that occurs during the

initial response and provides a stronger and more rapid immune response to a

subsequent encounter. More advanced acquired immunity is present in vertebrates,

but microorganisms such as prokaryotes have developed acquired immune memory

that provides protection against bacteriophages through a system called CRISPR

[3,4]. The adaptive immune system requires B lymphocytes, involved in the humoral

immune response, and T lymphocytes involved in the cell-mediated immune

response. T cells are further divided into subcategories according to their receptor

repertoire and functions.

Platelets are small (2–4 µm in diameter) anucleated fragments produced by

megakaryocytes. Nearly one trillion platelets patrol the blood vessels to monitor and

maintain the integrity of the latter. Thrombus formation occurs in response to blood

229

vessel damage in order to prevent bleeding [5]. However, the role of platelets is not

restricted to the hemostatic response [6,8]. Platelets are capable of phagocytosis,

which is suggested to be a conserved innate mechanism from thrombocytes in lower

vertebrates such as birds and fish [9,11]. Platelets also express immune and

inflammatory molecules, and a set of immune receptors such as TLRs, CD40L [6]

and the Fc receptor for immunoglobulin G (IgG) IIA (FcγRIIA) [12]. Upon activation,

platelets also release extracellular vesicles (EVs) that harbor some of these platelet

components. Given the vast number of platelets in blood (40:1 ratio to immune cells)

and their extensive array of immune receptors, the capacity of platelets to support,

promote and to actively participate in immunity is the focus of numerous

investigations.

230

Platelet-leukocyte Interactions and Implications for

Adaptive Immunity

Megakaryocytes (MK) and platelets, as well as their EVs, are suggested to play a

role in the innate immune response (reviewed in [6,8,13,16]). During adaptive

immunity, platelets can support the activities of classical antigen presenting cells.

While it has been demonstrated that platelet-derived molecules (PF4, CD40L, P-

selectin, serotonin,) are capable of enhancing dendritic cell (DC) differentiation and

antigen presentation, platelets can also promote recruitment of lymphocytes to sites

of inflammation [17,25]. Different molecules participate in platelet and leukocyte

interactions. The activated form of platelet αIIbβ3, the fibrinogen receptor, can bind

the solute carrier family 44 member 2 (SLC44A2) on neutrophils, which can enhance

their activation and netosis [26]. This receptor is also likely expressed by other

cellular lineages from the bone marrow (myeloid and non-myeloid), and whether it

contributes to platelet–lymphocyte interactions remains to be established. Through

its binding to fibrinogen, αIIbβ3 also indirectly interacts with Mac-1 [27]. Platelets and

neutrophils interact through CD62P or glycoprotein Ib, found on platelets, as well as

P-selectin glycoprotein ligand-1 (PSGL-1) and integrin CD11b/CD18 (Mac-1), found

on neutrophils [28,29].

Through direct interactions of platelet P-selectin and PSGL1 expressed by

monocytes, platelets mediate DC maturation. The contribution of platelet P-selectin

also enhances antigen cross presentation by DC, as they were more potent than

cytokine-derived DC in generating tumor-specific T cell immunity [20]. The effect of

another platelet molecule, serotonin, appears to have opposite effect on DC

differentiation: The DC capacity to stimulate T cells is decreased by serotonin, as

the latter reduces expression DC co-stimulatory molecules and enhances IL-10

production [30]. Similarly, platelet factor 4 (PF4) increases the DC responsiveness

to Toll-like receptor ligands [31], reduces the processing of antigens [17]. Moreover,

platelet-derived CD40L was shown to induce monocyte differentiation into DC, DC

maturation and upregulation of costimulatory molecules [23,25]. This function of

CD40L derived by platelets may be highly relevant to autoimmune diseases, such

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as systemic lupus erythematosus in which platelets induce DC differentiation and

type-I interferon release, thereby promoting B-cell secretion of antibodies [32].

Platelets also impact lymphocyte functions. For instance, platelet interactions with

CD40 bearing cells, such as lymphocytes, via CD40L have already been covered

thoroughly in several reviews (for instance see [33,36]). In vivo and in vitro

investigations revealed a role of platelet CD40L in B cell isotype switching and the

increased CD8+ T cell function during infection [37]. Platelets expressing CD40L

were also identified in different pathologies where they directly activate the

endothelium [38], or in which they contribute in the recruitment of neutrophils and T

cells to the damaged endothelium, more particularly in the intima and in plaque

ruptures in atherosclerosis [39]. Upon activation, platelets release molecules such

as PF4, P-selectin or serotonin, which can modulate lymphocyte responses. For

example, PF4 inhibits proliferation of activated human T cells and their release of

cytokines [40]. While P-selectin expressed by platelets plays a role in the recruitment

of lymphocytes to sites of inflammation [18], the interaction of CD4+ T cells (but not

CD8+ T cells) with platelet P-selectin mediates the platelet recruitment in the liver,

where they activate the endothelium and enhance hepatocellular damage [19].

Serotonin, not synthesize by platelets but captured and stored via their serotonin

transporter in platelet dense granules [41], is also able to promote the recruitment of

CD4+ and CD8+ T cells [21,22]. With their PF4 and TGF-β content, platelets are

also involved in induction of immune tolerance as they can control the differentiation

of Th17 and the expression of Foxp3+ Tregs [42,43].

In sum, platelets and the platelet-derived molecules impact DC and both B- and T-

cells in adaptive immunity. This review, however, focuses on the role played by

platelets and megakaryocytes in antigen presentation and antibody response.

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Antigen Processing and Presentation by Platelets

The proteasome is a high molecular weight multicatalytic protease primarily known

for its function in the maintenance of cellular protein hemostasis. It was first purified

from the cytosolic fraction of human platelets in the early nineties [44,45]. The

presence of all catalytically active subunits of the standard 20 S proteasome in

human platelets has since been confirmed, including the immunoproteasome

subunit β5 [46]. It was demonstrated that all of these components could assemble

into the constitutively active standard proteasome or immunoproteasome complex

in platelets [46]. The relevance of this organelle in platelets is not yet fully

understood, but a number of key functions such as platelet production by

megakaryocytes [47,48], delimiting platelet lifespan [49], activation [50,51]

(challenged by Koessleret al [52].), upregulation of proteasome activity during

bacterial sepsis [53] and release of extracellular vesicles (EVs) [54] have been

identified (reviewed recently [55]). These findings are of clinical relevance, as

bortezomib, a proteasome inhibitor used to treat patients with multiple lymphoma,

reportedly induces thrombocytopenia [47,48].

Another function of the proteasome in adaptive immunity is to hydrolyze proteins into

smaller peptides. This process is critically important for peptide loading into the major

histocompatibility complex (MHC) class I and their subsequent antigenic

presentation to CD8+ T cells. MHC I molecules are found on both murine and human

platelets [56,57], but a large proportion (70% to 80%) was shown to be adsorbed

from circulating MHC I molecules in plasma [58]. MHC II molecule, in contrast, is

absent on normal platelets although it was identified on platelets in immune

thrombocytopenia (ITP) [59,61]. In addition, platelets are also able to transfer their

MHC class I onto the tumor cell surface, conferring the tumor cell with an apparently

normal phenotype thereby providing protection from deletion by natural killer (NK)

cells [62]. This insidious role of platelet MHC I allows tumor growth and cancer

establishment.

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In addition to MHC I and beta-2 microglobulin (B2-MG), a molecular chaperone for

the MHC I complex, mass spectrometry approaches identified 43 proteins related to

the “antigen processing and presentation” pathway within the platelet α-granule

proteome [63]. Among those proteins, the authors identified antigen peptide

transporters 1 and 2 (TAP1 and TAP2), which are involved in the translocation of

processed peptides into the platelet ER before they are loaded into MHC I molecules

[63]. Components of the peptide loading complex (Erp57, calreticulin, calnexin and

tapasin), as well as the T cell co-stimulatory molecules CD40, ICOSL and CD86 (the

latter in humans only) [63,64], are found in platelets, suggesting that platelets bear

the entire machinery concerned with antigen processing and presentation to T-cells.

While most molecules were identified in the intracellular compartment, surface

expression by platelets is necessary for the formation of immunological synapse with

T cells. Confocal microscopy analysis revealed that MHC I, B2-MG, TAP1 and TAP2

could localize on the surface of thrombin-activated platelets, pointing to their

secretion upon activation [63]. Moreover, young murine platelets displayed higher

levels of MHC I molecules on their plasma membrane than older platelets,

suggesting that MHC I surface expression is modulated throughout the platelet

lifespan [65]. Platelet activation during infection can also lead to the expression of

MHC I on the plasma membrane: both murine and human platelets increase

expression of MHC I molecules in response to infection by Plasmodium berghei [64]

and dengue virus [66].

Pioneer work by Chapman et al. unequivocally demonstrated the capacity of

platelets to process and present antigens to T-cells [64]. The authors loaded

platelets with ovalbumin (OVA) protein and confirmed that the machinery in platelets

could efficiently process OVA into peptides, including the antigenic peptide

sequence SIINFEKL, which can be recognized by the T cell receptor (TCR)

expressed by all T cells in transgenic OT-1 mice when presented by MHC I

molecules. Using both in vitro and in vivo approaches, they further demonstrated

that platelets could indeed present processed ovalbumin antigen through MHC I to

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T-cells and, given the expression of co-stimulatory molecules by platelets, could

stimulate IL-2 production by T cells and their activation [64].

While these findings point to a potential use for platelets in a cell-based vaccine, this

hypothesis was tested with an actual pathogen, Plasmodium berghei, the parasite

that causes malaria. Using a Plasmodium berghei parasite transgenic for the C-

terminal amino acids 150–368 of OVA (Pba-OVA), it was shown that platelets, via

their MHC I, are able to acquire and present PbA-OVA-derived antigens to generate

protective T cells [64]. Together, these observations demonstrate that platelets are

capable of antigen processing and presentation (Figure 1). While platelets can

internalize pathogens other than Plasmodium berghei, such as dengue virus,

influenza virus and HIV [67,70] through phagocytosis or endocytosis, they also

increase bacterial clearance in septic mice [71]. However, it remains to be

established whether processed microbial antigens can be presented by MHC I

molecules on activated platelets to fulfill a role in adaptive immunity against these

pathogens.

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Figure 1. Platelet support antigen presenting cells and present antigens. (Left panel) Platelets support antigen presentation through several molecules such as serotonin, TGF-β and platelet factor 4 (PF4). They are able to recognize pathogens directly via Toll-like receptors (TLRs) or with their set of immunoglobulin receptors (FcRs). Moreover, platelets express CD40L, CLEC-2 and P-selectin, which can promote interaction and activation of antigen presenting cells (B cells, DC) and T cells activation. Platelet also produces extracellular vesicles (EVs). (Right panel) Platelets directly participate to antigen processing and presentation. MHC I is found in α-granules of platelets with P-selectin and is exposed upon stimulation. Proteasome is functional in platelets and is playing numerous roles in platelet functions, including the processing of proteins. Molecules implicated in antigen presentation, such as TAP 1 and TAP 2 and those from the peptide loading complex (PLC), are present in platelets. Peptide processed through the proteasome are loaded onto MHC I molecules with the activity of PLC and presented at the platelet surface to CD8 + T cells.

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Antigen Processing and Presentation by Megakaryocytes

Megakaryocytes are large (50 to 100 µM) heterogeneous cells with a multilobular

nucleus that can contain several copies of each chromosome (up to 128 N).

Megakaryocytopoiesis in the bone marrow is under the control of a complex process

primarily regulated by thrombopoietin. Megakaryocytes in the bone marrow niche

are in contact with hemopoietic stem cells. By secretion of several molecules like

thrombopoietin, PF4 or TGF-β, they are thus able to regulate hemopoietic stem cells

quiescence or proliferation [72,73].

Megakaryocytes express numerous immune receptors (reviewed in [16]), including

TLR 1 through 6 (TLR 5 mRNA was identified in lung MK), Ig receptors (FcγRIIA and

FcεRI for human MKs, and FcγRI on a subpopulation of murine MKs), and co-

stimulatory molecules, such as CD40L. Moreover, neutrophils can migrate through

MKs by a mechanism known as emperipolesis, which can permit membrane

exchange between the two cellular lineages [74].

In contrast to platelets, which do not normally express MHC II molecules, early MK

progenitors derived from human hematopoietic stem cells express MHC II. These

MKs were suggested to play roles reminiscent of professional antigen presenting

cells. They have been shown to support T cell activation and to increase the

expansion of Th17, Th1, and Th17/Th1 double-positive cells when incubated in the

presence of lymphocytes from normal subjects or systemic lupus erythematosus

(SLE) patients [75]. Megakaryocyte progenitors were efficient at mounting an

immune response against the opportunistic pathogen Candida albicans, thereby

suggesting that the mobilization of hematopoietic stem cells can lead to the

generation of a certain population of MK with immune functions [76]. MHC II

molecules classically present peptides derived from extracellular pathogens

trafficking through endosomes, which is a site of virus entry. Dengue virus can grow

in MK progenitors [77], and mature MKs can generate antiviral immunity implicating

interferon molecules in the response to dengue virus as well as influenza virus.

However, it remains to be established whether MKs can process and present viral

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peptides in the context of viral infection [78]. Megakaryocytes are present in lungs

and, according to transcriptome studies, display an immune cell phenotype in

contrary to MKs in bone marrow [79]. As MKs in lungs have privileged access to

airborne pathogens such as influenza viruses in addition to allergens, lung MKs may

be able to contribute to antigen presentation in this organ.

While MHC II expression is lost in mature MKs, studies confirmed that the MHC I

molecule and the necessary machinery to uptake and process antigens are

maintained in mature MKs (Figure 2). Moreover, MKs express CD80 and CD86

lymphocyte co-stimulation molecules [80]. Using both in vitro and in vivo approaches

in the OVA model of antigen presentation, the authors demonstrated that MKs could

internalize and process ovalbumin into its antigenic peptide (SIINFEKL) and could

present it to T-cells, thereby promoting T-cell proliferation [80]. Of clinical importance

is that MKs could present endogenous MK-associated (CD61) peptides to activate

CD61-specific CD8 + T cells and mediate ITP in vivo [80].

Figure 2. Megakaryocytes are immune cells. MKs express Toll-like receptors (TLRs) 1 to 6, immunoglobulin receptors (FcRγIIA, FcεRI or FcγRI) and the co-stimulatory molecule CD40L. Early MK progenitors also express MHC II shown to support T-cell activation and T helper cell expansion. MKs possess proteasome subunit, express MHC I and the co-stimulatory molecules CD80 and CD86 allowing them to process and present antigen and trigger CD8+ T cell activation and lymphoproliferation. MKs are able to undergo emperipolesis, produce platelets and produce extracellular vesicles (EVs).

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Platelets Response to Antibodies

Fc Receptors

Fc receptors (FcRs) regulate antibody-mediated responses by binding to the

fragment crystallizable (Fc) region of immunoglobulins. Fc receptors are at the

interface between the innate and adaptative immune systems as they activate

immune cells and can promote internalization of pathogens captured by antibodies.

Fc receptors are divided according to their affinity for different immunoglobulin (Ig)

classes or subclasses, their interaction with different forms of Ig (monomeric,

aggregated, immune complexes IC) and their function (activatory/inhibitory).

According to their heterogeneity, many biological functions can be regulated by

FcRs, such as degranulation, proliferation, phagocytosis, transcytosis and

immunoglobulin recycling [81].

Both mice and humans express FcRs although many differences can be observed

with regard to expression pattern or the affinities of murine and human FcRs. For

example, humans express some FcRs that mice do not, such as FcαRI and FcγRIIA,

the specific receptors for IgA and IgG, respectively [82]. Moreover, humans possess

more IgG-binding receptors FcγR than mice [82]. Conversely, mice express FcγRIV

that has no human counterpart [83], although human FcγRIIIA and FcγRI are

suggested as functional orthologs of murine FcγRIV.

Like many other immune cells, human platelets express FcRs. It has been shown

that human platelets express four activatory FcRs: FcαRI [84], FcεRI, FcεRII [85,87],

and FcγRIIA [88]. Expressed FcRs allow platelets to interact with different

immunoglobulin classes (IgA, IgE and IgG), which further highlights the role of

platelets in the immune response. For example, platelets can be activated by IgE

(via FcεRI and FcεRII), which points to a potential role for platelets in allergic

disorders, or against parasites [85,87]. In addition, platelets contribute to thrombosis

in human inflammatory diseases and in response to infection via their receptors

FcαRI (via IgA) and FcγRIIA (via IgG) [84,88].

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The most studied platelet FcR is FcγRIIA. FcγRIIA is the sole IgG-specific FcR

expressed by platelets in humans and is thereby the most abundantly expressed

FcR in blood [89,90]. This receptor binds with low affinity to monomeric IgGs but

induces signaling when antibodies are aggregated or bound to an antigen. Immune

complexes are known to make a pathogenic contribution to autoimmune diseases

such as rheumatoid arthritis, SLE, antiphospholipid syndrome and heparin-induced

thrombocytopenia (HIT) [91].

FcγRIIA

The FcγRIIA receptor is a 40 kDa type I transmembrane protein with two extracellular

Ig-like domains: one transmembrane domain and a cytoplasmic tail [92]. Unlike the

majority of FcγRs, FcγRIIA does not require association with an FcRγ subunit for

activation. FcγRIIA possesses its own two immunoreceptor tyrosine-based

activation motif (ITAMs) domains on its cytoplasmic tail, similar to the FcRγ subunit.

Immunoreceptor tyrosine-based activation motifs are signaling motifs recognized by

their classical YxxL sequences, which possess two tyrosines that can be

phosphorylated by Src kinases after initiation of FcγRIIA activation. Phosphorylation

creates a docking site for tyrosine kinase Syk via its SH2 domains [93,94]. In

platelets, phosphatidylinositide3-kinases are phosphorylated by Syk and propagate

the intracellular signaling cascade through the phosphorylation of PLCγ2. PLCγ2

activation leads to the production of second messengers, an increase in intracellular

calcium and activation of protein kinase C [95]. As a result, platelet FcγRIIA

activation leads to granule content secretion, ROS generation, integrin activation,

upregulation of P-selectin, platelet aggregation and thrombus formation [96,101].

The P2X1 channel, which is the main calcium entry site in platelets, has been shown

to contribute to the increase in calcium after initiation of FcγRIIA activation and leads

to platelet aggregation [102].

FcγRIIA is encoded by the FCGR2A gene on chromosome 1q23.3 [103]. Two

different alleles of FcγRIIA are well studied and can be co-dominantly expressed.

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The two alleles differ by the presence of an arginine (R) or a histidine (H) at position

131 in the amino acid chain [104]. The mutation lies in the second Ig-like domain,

which provides a different binding affinity to the allelic variants. A histidine at position

131 (FcγRIIA-H131) confers a higher affinity for IgG2 than the FcγRIIA-R131 variant

[104,106]. These FcγRIIA polymorphisms have been widely studied for their roles in

susceptibility to several diseases or the severity of these diseases. For example,

FcγRIIA polymorphisms are suggested to play a role in sepsis [107], SLE [108], HIT

[109,110], sickle cell disease [111], malaria, HIV [112], Epstein-Barr virus [113],

dengue virus [114,115], systemic meningococcal infections [116] and cardiac

diseases [117]. However, an actual contribution of the different FcγRIIA

polymorphisms remains controversial and further mechanistic insights are

necessary to fully assess their contribution to disease [118,123].

Platelets and Antibody Response

Immune Complexes

Immune complexes can mediate inflammation and have been intensively studied for

their role in pathogeneses such as SLE, rheumatoid arthritis and HIT. These

pathologies are all associated with thrombotic events and, consequently, possible

involvement of platelet activation mediated by IC. Activation of FcγRIIA is initiated

following an encounter with IC and has been shown to subsequently activate αIIbβ3,

thereby leading to full platelet activation and degranulation [124,125]. The integrin

αIIbβ3 changes to its activated conformation following signaling from activated

FcγRIIA leading to positive feedback (outside-in signaling), thus initiating α- and

dense granule secretion, which is important for thrombus formation [98,125,126].

Transgenic mice expressing FcγRIIA (FcγRIIATGN) have been generated given that

this receptor is absent in mice [127]. Immune complexes induce thrombosis in the

lungs and thrombocytopenia in FcγRIIATGN mice [124,128,131]. Many studies have

also shown that following activation of FcγRIIA, transgenic mice experienced

systemic shock [124,131,133]. Shock requires the release of serotonin from dense

granules, which relies on the activation of platelet αIIbβ3 and fibrinogen binding.

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Moreover, serotonin was shown to be a mediator of IgG-dependent anaphylaxis and

to contribute to the severity of the reaction in a humanized mouse that expressed all

human FcγRs in place of all murine FcγRs [134]. However, although the systemic

shock induced by IC had a critical requirement for serotonin, the latter is dispensable

in thrombosis and thrombocytopenia observed in FcγRIIATGN mice, thus revealing

the heterogeneity of functions mediated by the activation of platelet FcγRIIA.

Heparin-induced thrombocytopenia, an immune reaction against heparin, is also

characterized by thrombocytopenia and implicates circulating IgG antibodies that

target PF4 and heparin complexes. PF4 changes its structural conformation after

binding to charged polyanions, such as those present in heparin, lipopolysaccharide

(LPS) or Gram-negative bacteria. PF4 exposes neoepitopes after conformational

change, which promotes the binding of anti-PF4/heparin antibodies (anti-PF4/P)

present in certain individuals [135]. As a result, anti-PF4/P and PF4 complexes

promote interaction with FcγRIIA. These IC in HIT stimulate platelet FcγRIIA, thereby

activating platelets to release procoagulant factors and EVs and promote platelet

clearance [136].

Bacterial Infection

PF4 binding to endogenous polyanions and the recognition of the complex by

antibodies can play a role in the protection of the host against pathogens [135].

Therefore, the clearance of platelets by anti-PF4/PF4 in HIT could be explained by

a disturbed host defense mechanism, where bacteria may be the target of anti-PF4

[137]. Antibody-opsonized bacteria also bind to FcγRIIA, possibly implicating

platelets in the combat of infections. Bacteria are widely studied for their interactions

with platelets and many differences have been observed between bacterial strains

with regard to the manner in which they bind and activate platelets. A wide range of

bacterial strains (Staphylococcus aureus, Streptococcus sanguinis, Streptococcus

gordonii, Streptococcus oralis, Streptococcus pneumoniae, Helicobacter pylori,

Escherichia coli, Streptococcus pyogenes) appears to share a common property:

they all induce platelet aggregation through an involvement with FcγRIIA

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[98,138,146]. It is suggested that prevalent antibodies in humans (thus in plasma)

recognize bacterial epitopes and thereby form IC. Hence, anti-LPS antibodies are

detected in healthy individuals and form IC in the presence of this bacterial PAMP

[124]. Mechanistically, it was established that platelet aggregation by E. coli requires

IgG and FcγRIIA, can be enhanced by αIIbβ3 engagement, involves secondary

mediators (e.g. ADP and TxA2) and complement formation [144,145]. (Figure 3)

Evidence of integrin αIIbβ3 involvement was also observed in FcγRIIA-mediated

platelet aggregation by Gram-positive bacterial strains (Staphylococcus aureus,

Streptococcus sanguinis, Streptococcus gordonii, Streptococcus oralis and

Streptococcus pneumoniae)

Figure 3. Platelet response to antibody. Platelet FcγRIIA can bind to immune complexes, which are largely studied for their contribution to autoimmune diseases. Furthermore, platelet FcγRIIA can interact with many opsonized microorganisms such as bacteria (Escherichia coli, Staphylococcus aureus, Streptococcus sanguinis, Streptococcus pneumoniae, Streptococcus pyogenes, Streptococcus gordonii, Streptococcus oralis, and Helicobacter pylori), viruses (influenza H1N1) and fungi (M. circinelloides). FcγRIIA activation triggers the phosphorylation of ITAM motifs by the Src-family kinase that form a docking site for the SH2 domain of Syk tyrosine kinase. Syk activates a phosphorylation cascade that results in LAT and PI3 K induction of the intracellular cascade to PLCγ. PLCγ activation leads to the production of DAG and IP3, which increases intracellular calcium concentration, possibly via the channel P2X1, and activates protein kinase C (PKC), respectively. Meanwhile, αIIbβ3 binding to its ligand leads to an outside-in signal that enhances Syk activation. This increase in calcium and the activation of PKC leads to the αIIbβ3 inside-out signal and to platelet degranulation.

243

It was shown that bacteria-mediated FcγRIIA activation could have a possible

negative impact on host recovery, for example, by colonization of the heart valves

by platelets aggregated with Streptococcus oralis [147]. In addition, studies

confirmed that thrombocytopenia in sepsis is associated with increased risk of

mortality [148,151]. E. coli is involved in sepsis and in other pathologies where

thrombi are detrimental, such as in the development of hemolytic uremic syndrome

(HUS). On the other hand, platelet activation may play a role in the protection against

bacteria. Platelets possess the capacity to kill bacteria in an FcγRIIA-dependent

manner through the internalization of bacteria or by release of granules containing

antimicrobial proteins [152,154]. FcγRIIA-mediated PF4 release is also implicated in

the killing capacity of opsonized bacteria by platelets [98]. Moreover, aggregation

was suggested to restrict pathogens to a site with a high concentration of

antibacterial substances implying that platelet aggregation plays a possible

protective role against infection [152].

Viral, Fungal and Parasitic Infection

Although thrombocytopenia occurs in viral, fungal and parasitic infections, only a

limited number of studies have examined the role of platelet FcγRIIA in these

scenarios [69,155,160]. H1N1 promotes platelet activation through FcγRIIA.

Activation requires the presence of antibodies against influenza virus and leads to

release of granule components and EVs [68], which could contribute to

overwhelming inflammation [68]. Thrombocytopenia was induced by influenza virus

injection into FcγRIIATGN mice, only if the mice had developed antibodies to a

previous influenza virus infection. While this observation suggests a platelet

contribution to the defense of the host against infection, platelet activation may

contribute to an exacerbated inflammation, known as a cytokine storm, which can

be lethal in influenza infection [161]. In the case of Ebola virus, FcγRIIA has been

shown to enhance the infection of a cell line after its activation by virus–antibody

complexes, it is however unknown whether the mechanism takes place in platelets

[162].

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Dengue virus has been shown to bind to FcγRIIA after the production of platelet

associated IgG, suggesting a possible role for FcγRIIA platelets in the clearance of

the viruses. Dengue virus is also able to replicate in platelets [67]. While interactions

between platelets and other viruses have been observed, the FcγRIIA contribution

was generally not verified [163].

Very little is known regarding platelet FcγRIIA in parasitic disease. It has been shown

that platelets can induce lysis of parasite digestive vacuole membrane via PF4,

which results in elimination of the parasite [164]. Thus, degranulation following

platelet activation is an important platelet function in parasitic infection, and it

remains to be determined whether this pathway is mediated via FcγRIIA.

In fungal infections, platelet FcγRIIA-mediated activation shares several similarities

with bacterial FcγRIIA activation. Mucormycete spores induce platelet aggregation

through FcγRIIA and αIIbβ3 [165]. The interaction with fungi is dependent on the

developmental stage of the fungus, and initiates the release of secondary mediators

by platelets, such as ADP and TxA2 [165]. As platelets are able to inhibit the

mucormycete germination process [166], this points to a potential role for FcγRIIA in

the protection against fungal infection.

245

Conclusion and Perspectives

Platelets and their mother cell, the megakaryocyte, can play roles in adaptive

immunity. In addition to their support of professional APC and in lymphocyte

functions, they can process and present antigens (Figures 1 and 2). Platelets bind

IC and microorganisms through FcγRIIA (Figure 3), most likely because of prevalent

antibodies against most common microorganisms even in healthy individuals.

Consistent with this, FcγRIIA is the dominant receptor activated by Zika virus if in the

presence of sera from convalescent patients infected by dengue or West Nile virus,

pointing to the formation of IC in blood of patients with preexisting antiflavivirus

immunity [167]. It is not completely understood how platelet FcγRIIA plays a role

against infections or in autoimmune diseases, but in response to antibodies, platelets

have the potential to control the proliferation of, or to kill, certain microorganisms

through the release of their vast arsenal of inflammatory molecules. It is important to

note that this activation pathway by antibodies is absent in laboratory mice given the

absence of FcγRIIA in mice and the fact that mice (1) are used at a relatively young

age, (2) are housed in overly clean environments, (3) never develop any infectious

diseases, (4) are never vaccinated, and (5) therefore may not have antibodies

against these microbes.

As a result of their abundance in blood and lungs, platelets and megakaryocytes are

ideally positioned to act as the primary responder and to convey antigens to

lymphocytes. This includes their potential response to airway-infecting viruses such

as the SARS-Cov2, which generates overwhelming inflammatory responses and

cardiovascular manifestations in certain individuals [168]. However, in contrast to

leukocytes, which can circulate through lymph to reach lymphoid organs, platelets

are not observed in lymph. They may directly interact with lymphocytes in the spleen

or secondary and tertiary lymphoid organs through high endothelial venules.

Activated platelets also release EVs. Platelet EVs are the most abundant EV in the

bloodstream, representing approximately 80% of circulating EVs [169]. Platelet EVs

are suggested to play numerous roles in regulating both physiological and

246

pathological functions [170]. Platelet EVs can interact with lymphocytes and regulate

regulatory T cell differentiation and activity [171,172]. Moreover, they can promote

the formation of germinal centers and the production of IgG by B-cells as a function

of their CD40L load [173,174]. As platelet EVs can circulate in lymph [175,176], they

may be able to transport adaptive immunity molecules to lymphoid organs through

this circulatory system. In autoimmune disease implicating IC, platelet EVs are

shown to harbor autoantigens such as non-histone nuclear protein high mobility

group box 1 (HMGB1) and citrullinated proteins (e.g. vimentin and fibrinogen) that

are the targets of prevalent antibodies in SLE and rheumatoid arthritis [177,178].

Whether FcγRIIA can remain exposed on certain platelet EVs to contribute to

dissemination of IC in these pathologies is not known. Future studies are necessary

to highlight whether platelet EVs play roles in adaptive immunity, similarly to platelets

and MK.

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Annexe III: Platelets release pathogenic serotonin

and return to circulation after immune complex-

mediated sequestration

Nathalie Cloutier 1 , Isabelle Allaeys 1 , Genevieve Marcoux 1, Kellie R Machlus 2

, Benoit Mailhot 3 , Anne Zufferey 1 , Tania Levesque 1 , Yann Becker 1 , Nicolas Tessandier 1 , Imene Melki 1 , Huiying Zhi 4 , Guy Poirier 5 , Matthew T Rondina 6

, Joseph E Italiano 2 , Louis Flamand 1 , Steven E McKenzie 7 , Francine Cote 8

, Bernhard Nieswandt 9 , Waliul I Khan 10 ,11 , Matthew J Flick12 , Peter J Newman4

, Steve Lacroix 3 , Paul R Fortin 13 , Eric Boilard14 ,15

Affiliations

1 Centre de Recherche du Centre Hospitalier Universitaire de Québec-Université Laval, Département de microbiologie et immunologie, Faculté de Médecine, Université Laval, QC, Canada G1V 4G2.

2 Division of Hematology, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115.

3 Centre de Recherche du Centre Hospitalier Universitaire de Québec-Université Laval, Département de Médecine Moléculaire, Faculté de Médecine, Université Laval, QC, Canada G1V 4G2.

4 Blood Research Institute, Milwaukee, WI 53213.

5 Centre de Recherche du Centre Hospitalier Universitaire de Québec-Université Laval, Département d'Oncologie, Faculté de Médecine, Université Laval, QC, Canada G1V 4G2.

6 Department of Internal Medicine, University of Utah, Salt Lake City, UT 84112.

7 Cardeza Foundation for Hematological Research, Thomas Jefferson University, Philadelphia, PA 19107.

8 Institut Imagine, INSERM U1163, CNRS ERL8254, Université Paris Descartes, Hôpital Necker, 75006 Paris, France.

9 Department of Experimental Biomedicine, University Hospital and Rudolf Virchow Center, 97080 Wuerzburg, Germany.

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10 Farncombe Family Digestive Health Research Institute, McMaster University, Hamilton, ON, Canada L8S 4L8.

11 Department of Pathology & Molecular Medicine, McMaster University, Hamilton, ON, Canada L8S 4L8.

12 Cancer and Blood Diseases Institute, Division of Experimental Hematology and Cancer Biology, Cincinnati Children's Hospital, Cincinnati, OH 45229.

13 Centre de recherche du Centre Hospitalier Universitaire de Québec-Université Laval, Département de médecine, Faculté de médecine, Université Laval, QC, Canada G1V 4G2.

14 Centre de Recherche du Centre Hospitalier Universitaire de Québec-Université Laval, Département de microbiologie et immunologie, Faculté de Médecine, Université Laval, QC, Canada G1V 4G2; [email protected].

15 Canadian National Transplantation Research Program, Edmonton, AB, Canada T6G 2E1.

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Abstract

There is a growing appreciation for the contribution of platelets to immunity; however,

our knowledge mostly relies on platelet functions associated with vascular injury and

the prevention of bleeding. Circulating immune complexes (ICs) contribute to both

chronic and acute inflammation in a multitude of clinical conditions. Herein, we

scrutinized platelet responses to systemic ICs in the absence of tissue and

endothelial wall injury. Platelet activation by circulating ICs through a mechanism

requiring expression of platelet Fcγ receptor IIA resulted in the induction of systemic

shock. IC-driven shock was dependent on release of serotonin from platelet-dense

granules secondary to platelet outside-in signaling by αIIbβ3 and its ligand

fibrinogen. While activated platelets sequestered in the lungs and leaky vasculature

of the blood-brain barrier, platelets also sequestered in the absence of shock in mice

lacking peripheral serotonin. Unexpectedly, platelets returned to the blood circulation

with emptied granules and were thereby ineffective at promoting subsequent

systemic shock, although they still underwent sequestration. We propose that in

response to circulating ICs, platelets are a crucial mediator of the inflammatory

response highly relevant to sepsis, viremia, and anaphylaxis. In addition, platelets

recirculate after degranulation and sequestration, demonstrating that in adaptive

immunity implicating antibody responses, activated platelets are longer lived than

anticipated and may explain platelet count fluctuations in IC-driven diseases.

259

Introduction

Platelets are best known for their involvement in hemostasis. Their abundance in

blood underlies their perfect positioning for constant surveillance of the endothelium

to ensure vascular integrity. The role of platelets, however, is not restricted to the

hemostatic response (1). Not only do platelets express a vast array of mediators

serving wound repair but they also possess immune receptors and inflammatory

molecules (1–3). Moreover, following tissue injury or infection, platelets are a central

effector in driving an inflammatory process for recruiting leukocytes, principally

neutrophils, to the affected site (4–6). The platelet contribution at an inflamed site

also includes the prevention of bleeding (7, 8), as platelets seal the breaches formed

during the extravasation of neutrophils (9).

Platelet activation occurs at the interface with the vasculature, is elicited by injury or

inflammation, and is restricted to the endothelium or tissue. However, given the great

number of platelets in blood and their extensive set of immune receptors, systemic

immune triggers can also activate platelets while in circulation (i.e., in the absence

of endothelial or tissue injury). In rheumatic diseases, such as rheumatoid arthritis

(RA), systemic lupus erythematosus (SLE), and antiphospholipid syndrome, there is

a prevalence of pathogenic antibody–antigen scaffolds, called immune complexes

(ICs), in circulation in patients (10). Anaphylactic reactions due to allergens (11, 12)

and i.v. administration of drugs, such as in heparin-induced thrombocytopenia (HIT)

(13), also implicate ICs, thereby provoking acute inflammatory responses and a rapid

drop in platelet count (thrombocytopenia). ICs can also form in blood during sepsis

and viremia, when antibodies in the immune host recognize microbial antigens or

their toxins.

The pathological link between ICs and cellular responses is mediated by members

of the Fcγ receptor (FcγR) family. The low-affinity receptor FcγRIIA is the sole FcγR

expressed by platelets in humans, and is thereby the most abundantly expressed

receptor in blood (12, 14, 15). Of note, it is the dominant receptor activated by Zika

virus if in the presence of sera from convalescent patients infected by dengue or

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West Nile virus, pointing to the formation of ICs in blood in patients with preexisting

antiflavivirus immunity (16). Moreover, diverse strains of bacteria and the influenza

virus H1N1 trigger platelet FcγRIIA activation after forming ICs in an immune host

(17, 18). In addition, studies with human platelets show that ICs from patients with

SLE also activate platelets through FcγRIIA (19). However, mice do not express

FcγRIIA, and murine platelets are completely devoid of any FcγRs (12). Thus, IC-

mediated responses in mice strongly favor leukocytes, which express other FcγRs,

while platelets play small or accessory roles in mouse models implicating ICs.

To more accurately model FcγRIIA reactions in mice, transgenic FcγRIIA

(FcγRIIATGN) mice that display FcγRIIA expression on platelets and certain

leukocytes, including monocytes and neutrophils as in humans, were developed (12,

20). Notably, stimulation of FcγRIIA in transgenic mice induces a shock response

that is reminiscent of anaphylaxis in humans, with a strong reliance on neutrophil

activity and implicating release of platelet-activating factor (PAF) (14, 21–24).

How ICs trigger systemic responses is not completely understood, as no study has

definitively determined the contribution of platelets to this response in vivo. Here, we

employed FcγRIIATGN mice to elucidate the precise mechanisms by which platelets

contribute to IC-mediated shock.

261

Results

Platelets Are Critical During the Systemic Response.

ICs injected into FcγRIIATGN mice trigger systemic shock (22–24). Although

thrombosis in the lungs and thrombocytopenia accompany systemic shock in these

mice (22, 25–27), the platelet contribution to IC-induced shock has never been

formally assessed. We used heat-aggregated (HA) IgG as an IC surrogate (28, 29),

as it permits precise investigation of the role of FcγR activation with no bias owing

to the nature of antigen specificities. HA-IgG (160 ± 7 nm in diameter) was injected

i.v. into WT mice lacking FcγRIIA (FcγRIIAnull) and FcγRIIATGN mice. Significant

temperature loss (15 min) preceded by rapid significant systemic shock (3 min) in all

of the FcγRIIATGN mice was confirmed, but it was never observed in the FcγRIIAnull

mice (Fig. 1A and Movie S1). All of the FcγRIIATGN mice collapsed, underwent

profound immobility, and lost consciousness (Fig. S1A). Mice recovered from the

shock and hypothermia within 180 min, after which no residual signs were apparent

(Fig. S1B). The occurrence of shock was dependent on the concentration of ICs

present in blood, not induced by monomeric IgG, similarly induced when murine ICs

were used, and more profound in male FcγRIIATGN mice compared with females (Fig.

S1 C–E).

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Fig. 1 Platelets are critical during the systemic response. Systemic shock (Upper) (scores defined in Materials and Methods) and temperature (Lower) were measured at the indicated time points following IC injection in FcγRIIATGN and FcγRIIAnull mice (A; n = 12); FcγRIIATGN mice preinjected with platelet-depleting antibody (PLT Ab) and isotypic control antibody (Ctrl Ab) (B; n = 8); FcγRIIATGN/β3+/+ and FcγRIIATGN/β3−/− mice (C; n = 15); bone marrow chimeric mice generated by transfer of FcγRIIATGN cells into WT (D and E; native fibrinogen), Fibγ∆5 (D), and Fibγ390-396A (E) irradiated mice (n = 6); FcγRIIATGN mice preinjected with GPIb Fab (Xia.B2) or diluent (F; n = 6); FcγRIIATGN mice pretreated with aurintricarboxylic acid (ATA) or diluent (G; n = 8); and FcγRIIATGN mice pretreated with alteplase (H; n = 4) or diluent. null, FcyRIIAnull; TGN, FcyRIIATGN. Data are mean ± SEM. **P < 0.005, ***P < 0.001, and ****P < 0.0001; repeated-measures two-way ANOVA, statistical variation between groups (A–H).

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To formally assess the contribution of platelets to the systemic shock, we depleted

platelets (>98%) before injection of ICs. Thrombocytopenic mice were completely

protected from IC-mediated systemic responses (Fig. 1B and Fig. S1F), identifying

a critical role for platelets in shock induced by circulating ICs. In platelets, efficient

αIIbβ3 signaling relies on the FcγRIIA immunoreceptor tyrosine-based activation

motif, and, accordingly, the expression of FcγRIIA by platelets enhances fibrinogen-

mediated platelet activation (30). Thus, we verified the functional association of

FcγRIIA and the αIIbβ3 receptor in vivo by comparing the response in

FcγRIIATGN/β3−/− and FcγRIIATGN/β3+/+ mice. The FcγRIIATGN/β3−/− mice were

completely resistant to IC challenge (Fig. 1C), further emphasizing the role of

platelets and pointing to the requirement of αIIbβ3 in the mechanism of IC-mediated

shock.

While αIIbβ3 may amplify FcγRIIA signaling through common kinases located in the

platelet cytoplasm, it is predominantly known as the fibrinogen receptor, which may

contribute upon binding to platelet activation (31–33). Fibrinogen also mediates

platelet–neutrophil interactions by bridging αIIbβ3 and macrophage-1 antigen (Mac-

1) (34). Hence, platelet–neutrophil aggregates formed in blood in the presence of

ICs (Fig. S2A), as well as neutrophils, were also necessary in the systemic

responses (Fig. S2B), in agreement with prior studies (23, 28). To verify the specific

role of fibrinogen, we used mutant fibrinogen chimera mice. We lethally irradiated

fibrinogenγΔ5 (FibγΔ5) and fibrinogenγ390-396A (Fibγ390-396A) mutant mice, which

express mutant fibrinogen unable to bind αIIbβ3 or Mac-1 (34, 35), respectively, and

engrafted the mice with bone marrow from FcγRIIATGN mice. After injection with ICs,

we found that fibrinogen binding to αIIbβ3 was necessary for the systemic response,

whereas bridging platelets with leukocytes through fibrinogen binding to Mac-1 was

dispensable (Fig. 1 D and E). Consistent with these data, the blockade of Mac-1 as

well as PSGL-1, the counterreceptor of platelet P-selectin on leukocytes (36), had

no effect on shock (Fig. S2C).

Like αIIbβ3, GPIb is critical in the prevention of bleeding and thrombosis, and the

ablation of the gene coding for GPIb in mice leads to severe bleeding defects (37).

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As GPIb is localized within lipid raft membrane microdomains in physical proximity

with FcγRIIA (38), we used a GPIb-blocking Fab to probe the contribution of GPIb,

and found that it is dispensable in shock mediated by ICs (Fig. 1F). Furthermore, the

pharmacological blockade of von Willebrand factor (vWF) binding to GPIb (ATA;

aurintricarboxylic acid) or administration of recombinant tissue plasminogen

activator (tPA; alteplase) to promote the lysis of any existing thrombi also had no

effect on shock (Fig. 1 G and H). These data further demonstrate that platelet

activation by circulatory ICs implicates pathways distinct from those promoting vaso-

occlusion and vascular injury.

Identification of the Shock Mediator.

Consistent with the rapid response, an increase in platelet factor 4 (PF4) and

serotonin, components stored in α- and δ-granules, respectively, was detected in

blood within 10 min (at the time of mouse collapse and before hypothermia) of the

IC trigger in FcγRIIATGN mice (Fig. 2A). We therefore hypothesized that a component

released from platelet granules may be responsible for induction of systemic shock.

Intravital microscopy of the microvasculature using two-photon microscopy revealed

significant vessel leakage and vasodilatation in response to IC injection in

FcγRIIATGN mice (Fig. 2 B and C). Vessel leakage was systematically observed in

response to IC injection in both FcγRIIATGN mice and FcγRIIAnull mice, but was

absent in FcRγ−/− mice, pointing to the role of other receptor(s) for ICs (Fig. S3A). It

was also maintained in the absence of neutrophils, further suggesting that vascular

leakage is not the key pathological feature downstream of FcγRIIA driving

IC/platelet-mediated shock (Fig. S3A).

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Fig. 2. Serotonin is the mediator of shock. (A) PF4 (Left) and serotonin (Right) concentrations were measured in platelet-free plasma prepared from blood of FcγRIIATGN mice collected 10 min after IC injection (n = 5). The baseline (measured in nonchallenged FcγRIIATGN mice) concentration is indicated using a dotted line. Dil, diluent. (B and C) Intravital microscopy reveals profound changes to the mouse ear vasculature in response to ICs. (B) Vascular leakage, evidenced by the presence of Evans Blue (magenta) outside blood vessels in the subendothelial matrix rich in collagen (blue), is represented using FcγRIIATGN. (Scale bar: 75 μm.) (C) Vasodilatation was measured prior to leakage (t = 8 min) in FcγRIIATGN, FcγRIIAnull, or FcγRIIATGN/Tph1−/− mice (n > 5 vessels per field in three mice per group). (D–G) Systemic shock (Upper) and temperature (Lower) were measured at the indicated time points following injection of serotonin (Sero) or its Dil in FcγRIIAnull mice (D; n = 6), after IC injection in FcγRIIATGN mice treated or not treated with the SSRI fluoxetine (E; n = 10), after IC injection in FcγRIIATGN/Tph1+/+ and FcγRIIATGN/Tph1−/− mice (F; n = 9), and after injection of ICs in FcγRIIATGN mice pretreated with the 5-hydroxytryptamine receptor 2 blocker ketanserin or Dil (G; n = 5). null, FcyRIIAnull; TGN, FcyRIIATGN. Data are mean ± SEM. *P < 0.05, **P < 0.005, ***P < 0.001, and ****P < 0.0001, using an unpaired t test (A); one-way ANOVA (C); and repeated-measures two-way ANOVA, statistical variation between groups (D–G).

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In stark contrast, vasodilatation was a response observed exclusively in FcγRIIATGN

mice (Fig. 2C). Identified first as a serum agent mediating vascular tone, serotonin

is a powerful vasoconstrictor when added to smooth muscle cells. However, it is a

potent vasodilator on endothelial cells (39). In the case of systemic activation in the

absence of vascular injury, and thus an intact endothelium, we hypothesized that

serotonin might be the key platelet component driving vasodilatation. This is

supported by the fact that the majority of peripheral serotonin, which represents 95%

of the total body serotonin pool, is stored in platelet δ-granules (40, 41). Platelets do

not synthesize serotonin; they utilize their serotonin transporter (SERT) to capture

circulatory serotonin, with the latter being generated by enterochromaffin cells from

the digestive tract by the enzyme tryptophan hydroxylase 1 (Tph1) (42, 43).

Consistent with our hypothesis, vasodilatation was abrogated in FcγRIIATGN/Tph1−/−

mice in response to ICs (Fig. 2C). It was also maintained in absence of neutrophils,

further confirming the direct role of peripheral serotonin in IC-induced vasodilatation

of microvessels (Fig. S3B).

Serotonin levels in plasma were back to normal 1 h postshock (Fig. S3C). To directly

verify its role in systemic shock, serotonin was injected into FcγRIIAnull mice, which

resulted in a shock response reminiscent of the responses observed in IC-injected

mice (Fig. 2D). We then used a selective serotonin reuptake inhibitor (SSRI), a SERT

blocker used as an antidepressant, to inhibit serotonin storage by platelets.

Administration of the SSRI for 3 wk to deplete the serotonin content of δ-granules

(41) revealed the important contribution of serotonin uptake in IC-mediated

inflammation: SSRI treatment nearly abolished the systemic shock response (Fig.

2E). Furthermore, FcγRIIATGN/Tph1−/− mice lacking platelet serotonin (43) showed

almost complete resistance to shock (Fig. 2F), confirming the critical role of

peripheral serotonin in IC-mediated shock. In addition, blockade of the 5-

hydroxytryptamine 2 receptor family, which is expressed in the periphery by

platelets, but also by monocytes and macrophages, dendritic cells, eosinophils, B

and T lymphocytes, endothelial cells, fibroblasts, cells from the cardiovascular

system, and neurons in the peripheral nervous system (40), was effective at reducing

shock (Fig. 2G). In support of the potential role of αIIbβ3 in degranulation, serotonin

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was not released in FcγRIIATGN/β3−/− mice after IC injection, in agreement with the

absence of shock in those mice (Fig. S3D). Key actors in the prevention of bleeding

and thrombosis, the platelet-derived mediators ADP and thromboxane A2, were

dispensable for shock (Fig. S3 E and F). In addition, neutrophil extracellular traps,

which can be present in thrombosis (44), were detected during shock according to

quantifications of circulating nucleosomes (Fig. S3G); however, the injection of

DNase did not protect mice from shock (Fig. S3H). Together, these observations

highlight the importance of platelet-derived serotonin in the systemic response to ICs

in vivo, a platelet response that is distinct from that traditionally observed in

hemostasis and thrombosis.

And the Platelet Count?

Circulating platelets were also monitored throughout the systemic response and

beyond. We observed that FcγRIIATGN mice rapidly underwent profound

thrombocytopenia (∼10% of total normal platelet count) in response to ICs, whereas

FcγRIIAnull mice presented with only very minimal or no changes in platelet counts

(Fig. 3A). In fact, thrombocytopenia occurred rapidly (<10 min), and the platelet

count gradually increased, reaching ∼20% by 60 min, and it was 50% resolved within

24 h (Fig. 3A). The occurrence of thrombocytopenia was critically dependent on the

expression of FcγRIIA and was similarly induced in males and females (Fig. S4A).

Only platelets were affected, as the levels of RBCs, monocytes, and neutrophils

were unchanged in response to ICs (Fig. S4 B–D). Thrombocytopenia was as

profound in native fibrinogen mice as in FibγΔ5 and Fibγ390-396A mice (Fig. 3B),

suggesting that fibrinogen binding was dispensable, and that thrombocytopenia only

modestly involved β3, potentially through binding to its other ligands. Conversely,

thrombocytopenia was unaltered by the inhibition of GPIb and vWF interactions, or

the blockade of thromboxane A2 synthesis and ADP (Fig. 3B). Thrombin–

antithrombin complexes and D-dimers, which are evidence of coagulation activation

and thrombus degradation, respectively, were not significantly elevated 24 h after

shock (Fig. S4 E and F), and consistent with this, the destruction of potential thrombi

by the injection of alteplase did not impact platelet count (Fig. 3B). These data further

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dissociate the platelet response in coagulation and thrombosis from IC-induced

thrombocytopenia

Fig. 3.Thrombocytopenia in response to ICs. (A and B) Blood samples were

collected at the indicated time points following IC injection, and CD41+ platelets in

whole blood were counted using a flow cytometer. (A) Platelet count was determined

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in FcγRIIATGN and FcγRIIAnull mice (n = 11). (B) Percentages of circulating platelets

10 min after IC injection compared with initial platelet count were calculated in

FcγRIIAnull mice (black) and the indicated three different groups of FcγRIIATGN mice.

Mice were pretreated with acetylsalicylic acid (ASA) (n = 4), apyrase (n = 6),

aurintricarboxylic acid (ATA) (n = 3), alteplase (n = 5), or diluent (n = 14) (all shown

in blue). FcγRIIATGN mice pretreated with GPIb Fab or control (n = 4),

FcγRIIATGN/β3+/+ or FcγRIIATGN/β3−/− mice (n = 10); FcγRIIATGN/Tph1+/+ mice; or

FcγRIIATGN/Tph1−/− mice (n = 4) are represented (all shown in purple). Bone marrow

chimeric mice generated by transfer of FcγRIIATGN cells into WT (native fibrinogen),

Fibγ∆5, and Fibγ390-396A irradiated (IRRAD) mice are represented (n = 3 per group)

(shown in green). (C and D) Mice were injected with diluent or IC, and blood was

collected 24 h later. (C) Exposition of PS and P-selectin (P-sel) was assessed on

CD41+ platelets using flow cytometry in FcγRIIATGN mice (n = 7). (D) Platelet content

of PF4 (n = 6) and serotonin (n = 5) was measured by ELISA in 106 platelets retrieved

24 h after shock. Baseline (measured in nonchallenged FcγRIIATGN mice) contents

are indicated using dotted lines. (E) PF4 and serotonin-negative cells were counted

using immunofluorescence microscopy (n = 3 different mice). Representative image

of Z-stack projections using confocal microscopy. Platelets that returned to

circulation 24 h after IC injection were used for quantification. Tubulin (red) was used

as a platelet marker. PF4 (green) and serotonin (green) were observed in less than

60% of platelets. Empty platelets (arrowheads) and platelets (arrows) are

represented. (Scale bars: 2 μm.) As a negative control, serotonin labeling was

performed on Tph1−/− platelets (Fig. S9). (F) Electron microscopy of FcγRIIATGN

platelets before IC injection (Upper) and 24 h after IC injection (Lower). Empty

platelets (arrowheads) and platelets (arrows) are represented. (Scale bars: 0.8 μm.)

(G) Systemic shock was measured in FcγRIIATGN mice injected with ICs at t = 0 and

rechallenged at t = 24 h (n = 3). (H) Plasma levels of PF4 (n = 4) and serotonin (n =

5) were determined in mice rechallenged 24 h after the first challenge with ICs.

Results were compared with the level after the first challenge (dotted lines). (I)

Platelets were purified from FcγRIIATGN mouse blood, fluorescently labeled, and

adoptively transferred i.v. in FcγRIIATGN mice. One hour later, mice were injected

with ICs, and fluorescent platelets in circulation were determined at the indicated

time points following injection of ICs (n = 10). Dil, diluent; null, FcyRIIAnull; TGN;

FcyRIIATGN. Data are mean ± SEM. **P < 0.005, ***P < 0.001, and ****P < 0.0001,

using an unpaired t test (A, D, and H); one-way ANOVA (B, C, E, and I); and

repeated-measures two-way ANOVA, statistical variation between groups (G).

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Platelet conversion to microparticles also did not explain the profound

thrombocytopenia, as microparticle levels only increased 60 min after the IC trigger

(Fig. S4G). The decrease in platelet number could also not be attributed to platelet

interaction with leukocytes, as neutrophil depletion, or blockade of Mac-1 and PSGL-

1, had no effect on thrombocytopenia (Fig. S4 H and I). Given that

FcγRIIATGN/Tph1−/− mice also underwent profound thrombocytopenia (Fig. 3B), and

that exogenous serotonin did not induce thrombocytopenia (Fig. S4J), this suggests

that serotonin serves as the effector of IC-mediated shock but is not the driver of the

resulting thrombocytopenia. Thus, although thrombocytopenia occurs concurrently

with shock, it is not causative in the mechanism of inducing the shock.

The unanticipated rapid recovery in platelet count prompted a detailed analysis of

the platelets present in blood 24 h after IC challenge. We found that platelets were

not activated or apoptotic, as evidenced by the lack of phosphatidylserine (PS) and

P-selectin on their surface (Fig. 3C). However, the platelet granule content was

markedly reduced (Fig. 3D), as ∼30% of the circulating platelets contained no

detectable serotonin or PF4 (Fig. 3E), suggesting significant degranulation. Electron

microscopy further confirmed that circulating platelets were frequently devoid of any

granules (Fig. 3F). Notably, platelets still expressed surface FcγRIIA 24 h postshock

(Fig. S5 A and B), and still underwent thrombocytopenia if challenged a second time

with ICs (Fig. S5C). This is in contrast to shock, where FcγRIIATGN mice were

resistant to shock induced by further challenges (Fig. 3G), and neither serotonin nor

PF4 was induced in the blood of these mice (Fig. 3H). Thus, we hypothesized that

platelets circulating 24 h postshock were, in fact, platelets that had already

degranulated and had undergone temporary sequestration. To verify this, we

performed fluorescent labeling of FcγRIIATGN platelets, which we adoptively

transferred into FcγRIIATGN mice. As expected, 87 ± 12% of fluorescent platelets,

which were negative for PS (Fig. S5D), rapidly became undetectable from the blood

circulation after an IC trigger. Of particular importance, 42 ± 16% of the fluorescently

labeled FcγRIIA platelets, devoid of any surface PS, were identified in blood 24 h

after shock (Fig. 3I), confirming a temporary sequestration of platelets following

FcγRIIA activation and their return to the blood circulation after degranulation.

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Localization of Sequestration Sites.

We next aimed to determine the sites of platelet sequestration in response to

FcγRIIA activation. An intravital imaging system (IVIS) provided evidence of

fluorescently labeled platelets in the lungs (Fig. 4A), but not in other locations, in

agreement with previous studies (22, 25–27). Platelet thrombi populated with

neutrophils were also evident in the lungs (Fig. 4B), although no pulmonary edema

was observed (Fig. 4C). Thrombi contribution to platelet sequestration and shock

was not significant: ablation of the β3 gene, or blockade of GPIb using Fab,

significantly reduced thrombus formation in FcγRIIATGN mice (Fig. 4D) with only a

modest or no impact on thrombocytopenia, respectively (Fig. 3B). Furthermore,

serotonin had no effect on thrombus formation, as the number of thrombi in the lungs

remained unchanged in FcγRIIATGN/Tph1−/− mice (Fig. 4D). These data identify the

lungs as the apparent major site for platelet sequestration, and highlight that

although thrombi are present in the lungs, these thrombi play no role in the

thrombocytopenia and shock mediated by ICs.

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Fig. 4.Localization of sites of sequestration. (A) Mouse platelets from whole blood of FcγRIIATGN mice were labeled in vivo before IC injection. The kidneys (Kid), spleen (Spl), liver (Liv), heart (He), lungs (Lu), and brain (Br) were harvested 10 min after IC injection, and fluorescence was measured in each organ using an IVIS to determine platelet localization (n = 3). Results were compared with FcγRIIAnull mice injected with diluent, and are presented as the percentage of fluorescence in diluent-injected FcγRIIAnull mice. (B) Lungs were collected 10 min after IC injection. Thrombi (star) and neutrophils (arrows) were examined by microscopy after hematoxylin and eosin coloration. (Magnification: 400×.) (C) FcγRIIATGN mice were injected with diluent (Dil) or ICs, and lungs were collected after 10 min. The lung wet-to-dry ratio was evaluated. (D) Number of lung thrombi per square millimeter was quantified in FcγRIIAnull (n = 4), FcγRIIATGN (n = 12), FcγRIIATGN/β3−/− (n = 7), and FcγRIIATGN/Tph1−/− (n = 3) mice, as well as in FcγRIIATGN mice pretreated with GP1b Fab antibody (n = 4). (E) Mouse platelets from FcγRIIAnull and FcγRIIATGN mice were labeled in vivo. Lungs were collected 10 min after the IC trigger, and the number of fluorescent platelets was estimated (n = 4) using a standard curve designed with known numbers of fluorescent platelets spiked into nonfluorescent control lung homogenates. Percentages were obtained by comparison with platelet count obtained before the experiment and are presented as the percentage of total platelet number in the whole-mouse body. (F) ICs were labeled with DyLight-647 anti-Human IgG (fluo ICs) before injection in mice. The Kid, Spl, Liv, He, Lu, and Br were harvested 10 min later, and fluorescence was measured in each organ using an IVIS to determine IC localization (n = 3). Results are presented as the percentage of fluo determined in FcγRIIAnull mice. (G) Two-photon intravital microscopy in brain microvasculature of FcγRIIATGN/CD41-YFP mice injected with ICs. Thrombi were observed 5 min after IC injection (arrows), whereas brain vasculature leakage occurred after 10 min. (Scale bar: 50 μm.) null, FcyRIIAnull; TGN; FcyRIIATGN. Data are mean ± SEM. *P < 0.05, **P < 0.005, ***P < 0.001, and ****P < 0.0001 using one-way ANOVA (A and D) and an unpaired t test (C, E, and F).

However, we suspected that other anatomical sites of platelet sequestration might

exist, as the IVIS approach may not permit an optimal distinction between

immobilized platelet aggregates and circulating platelets in the microvasculature,

where small platelet aggregates are to be expected. In addition, if the entire platelet

population was sequestered in the lungs, it was puzzling that none of the mice died

from the IC trigger. Using a quantitative approach to measure fluorescently labeled

CD41+ platelets, we estimated that the lungs, in fact, contained only 16% of the total

platelet load (Fig. 4E), confirming that other sites of platelet sequestration likely

existed.

The presence of platelets outside the vasculature was excluded first, as no platelets

were detected in the thoracic lymph (Fig. S6A). Furthermore, assessment using

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whole-mouse imaging of yellow fluorescent protein (YFP) in FcγRIIATGN/CD41-YFP

mice, which constitutively express YFP in CD41-expressing cells, efficiently

identified thrombi in the lungs and megakaryocytes in the bone marrow, but did not

reveal platelets outside blood vessels or in other tissues (Fig. S6B). Therefore, we

speculated that tracking ICs in mice might be a more efficient means of leading us

to platelet sequestration sites. We found that ICs not only localized to the lungs but

were also observed in the brain vasculature (Fig. 4F). Thus, the brain

microvasculature was examined using two-photon microscopy in live

FcγRIIATGN/CD41-YFP mice, with the inclusion of FcγRIIAnull/CD41-YFP mice for

comparison. We observed profound leakage of the brain vasculature in both

FcγRIIAnull and FcγRIIATGN mice when injected with ICs (Fig. 4G and Movies S2 and

S3). Of importance, in the presence of ICs, small platelet aggregates readily formed

in the leaky brain microvasculature, but only if FcγRIIA was expressed by platelets

(Fig. 4G and Movie S2). Thrombi were not detected in the microvasculature of the

kidney, liver, or spleen of FcγRIIATGN mice injected with diluent or ICs (Fig. S6C),

and two-photon microscopy of the femurs in live FcγRIIATGN/CD41-YFP mice did not

reveal any platelet aggregation in sinusoids in the bone marrow (Fig. S6D). These

data suggest that in the presence of ICs, platelets sequester in certain microvascular

beds, notably in the lungs and brain, and that this event occurs independent of

thrombosis and leakage.

Role of Platelet FcγRIIA and Serotonin in Acute Inflammatory Responses.

During microbial invasion, foreign antigens are recognized by host antibodies and

form ICs. Hence, incubation of human platelets in the presence of influenza virus or

various strains of bacteria leads to platelet activation, which strictly requires the

presence of plasma and FcγRIIA (17, 18). While these observations suggest that

motifs on pathogens contribute to the formation of ICs, whether they can trigger

platelet activation in vivo has not been established.

Antibodies against lipopolysaccharide (LPS), a common gram-negative pathogen-

associated molecular pattern (PAMP), were detected in the blood of healthy

volunteers similar to patients with septic shock due to confirmed gram-negative

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bacteria infection (Fig. 5A). In contrast to humans, mice housed in a facility with high

standards of cleanliness present no detectable anti-LPS antibodies (nonimmune

mice) (Fig. 5B). Therefore, we immunized mice with small quantities of bacterial

PAMP (LPS), which had no perceptible effect on FcγRIIAnull or FcγRIIATGN mice (Fig.

5C). FcγRIIAnull and FcγRIIATGN mice developed equivalent anti-LPS antibody levels

within 3 wk (LPS-immune mice) (Fig. 5B), and, importantly, a subsequent injection

of LPS only induced serotonin release and shock in FcγRIIATGN mice (Fig. 5 C and

D). The shock induced by LPS-containing ICs was dependent on the presence of

platelets, and was greatly diminished in the absence of peripheral serotonin or β3

gene expression (Fig. 5 E–G). Moreover, plasma serotonin levels were significantly

reduced in FcγRIIATGN/β3−/− mice after LPS injection (Fig. 5D). Thrombocytopenia

was dramatically increased in the presence of FcγRIIA expression (Fig. 5H), as in

the passive model of the IC trigger, and was also transient, as platelets with

significantly reduced PF4 and serotonin content were identified in blood when they

reappeared (Fig. 5I).

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Fig. 5.Role of the FcγRIIA/serotonin axis in acute inflammation. Endogenous antibodies directed against LPS (anti-LPS) were measured by ELISA in plasma of healthy volunteers (HV) and patients with ongoing septic shock (SS) (A; n = 11) and in FcγRIIAnull and FcγRIIATGN mice that were immunized with LPS (LPS-immune) or diluent (nonimmune) (B; n = 4). OD, optical density. (C) Systemic shock and temperature were evaluated in nonimmune (n = 4) or LPS-immune mice (n = 6) expressing or not expressing FcγRIIA. (D) Serotonin levels in plasma were determined in LPS-immune FcγRIIAnull, FcγRIIATGN, and FcγRIIATGN/β3−/− mice immediately after LPS injection (n = 5) and compared with nonimmune FcγRIIATGN mice (baseline level, indicated as a dotted line). Systemic shock and temperature were measured after LPS injection in LPS-immune FcγRIIATGN mice preinjected with platelet-depleting (PLT Ab) or control (Ctrl Ab) antibodies (E; n = 5) and in LPS-immune FcγRIIATGN/Tph1+/+ mice and FcγRIIATGN/Tph1−/− mice (F; n = 6). (G) Systemic shock was measured after LPS injection in LPS-immune FcγRIIATGN/β3+/+ mice and FcγRIIATGN/β3−/− mice (n = 4). (H) CD41+ platelets in whole blood were counted using flow cytometry at the indicated time points after injection of LPS in LPS-immune FcγRIIAnull and FcγRIIATGN mice (n = 5). (I) Platelet content in PF4 (n = 5; Left) and serotonin (n = 6; Right) were determined 48 h after LPS injection in LPS-immune FcγRIIAnull and FcγRIIATGN mice and compared with nonimmune FcγRIIATGN mouse levels (dotted lines). Dil, diluent; null, FcyRIIAnull; TGN, FcyRIIATGN. Data are mean ± SEM. **P < 0.005, ***P < 0.001, and ****P < 0.0001, using an unpaired t test (A and I); repeated-measures two-way ANOVA, statistical variation between groups (C and E–G); and one-way ANOVA (B, D, and H).

We further verified whether the same conclusions hold in viremia and in a well-

described model of active systemic anaphylaxis (23, 28, 29). The i.v. injection of

herpes simplex virus-1 (HSV-1), capable of blood dissemination in immunized

humans (45, 46), in HSV-1–immunized mice induced shock reminiscent of the

responses seen in IC-injected mice and dependent on FcγRIIA (Fig. S7A). Moreover,

BSA injection in BSA-immunized mice initiated systemic anaphylactic responses,

and a proportion of the FcγRIIATGN mice, but never the FcγRIIAnull mice, died. Modest

shock response and moderate thrombocytopenia were also observed in FcγRIIAnull

mice (Fig. S7B), possibly due to the high antigenicity of BSA and the potent

immunization protocol implicating adjuvant, consistent with other studies implicating

neutrophils and FcγRIIA-independent responses in these experimental conditions

(23, 28, 29). Of importance is that in all models, platelet FcγRIIA and serotonin were

involved in shock, while FcγRIIA was implicated in thrombocytopenia (Fig. S7 C–E).

Thus, as in our passive model of IC-mediated immune reaction, active immunization

with gram-negative PAMPs, virus, or protein antigen dominantly implicates platelet

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FcγRIIA and serotonin, and presents with transient platelet sequestration. The

mechanisms unveiled in this study are illustrated in Fig. 6.

Fig. 6.Platelets release pathogenic serotonin and return to blood circulation after IC-mediated degranulation and sequestration. Sequential events (numbered 1–6) were observed when circulating ICs encountered platelets. Platelets are abundant in blood and in humans (not in WT mice); they express FcγRIIA, a low-affinity receptor for IgG. ICs activate FcγRIIA present on platelets (1), which changes αIIbβ3 to its active conformation (2). (3) Active αIIbβ3 binds its extracellular ligand fibrinogen, which mediates outside-in signaling and granule release. In the absence of αIIbβ3, there is no granule release. It is suggested (dotted line) that serotonin engages neutrophils (4), and it is further hypothesized (dotted line) that serotonin

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induces vasodilatation through its action on endothelial cells (5). (6) Multiple manifestations are observed when ICs form in blood. Shock, characterized by loss of consciousness, immobility, shallow respiration, and hypothermia, strictly implicates platelets, αIIbβ3 binding to fibrinogen, and serotonin release. In the absence of neutrophils, serotonin is released but shock is abolished. It is surmised that neutrophils produce PAF in response to serotonin, which may contribute to shock downstream of serotonin release. Mediators of shock are indicated in the figure. Thrombocytopenia is due, at least in part, to platelet sequestration in certain vascular beds, notably in the lung and brain microvasculature. Sequestration implicates FcγRIIA but, in contrast to shock, occurs independent of serotonin and neutrophils, and only partially implicates β3. Thrombocytopenia is only transient, and platelets return to blood circulation with emptied granules. Microparticle release is observed in blood before return of platelets. Roles of different molecules in thrombocytopenia are indicated in the figure. Vasodilatation is implicating platelet-derived serotonin and is occurring independent of the presence of neutrophils. Thrombosis was characterized in lungs following IC administration. It implicates FcγRIIA and β3, and, in contrast to shock, it involves GPIb and not serotonin. These data support the notion that shock and thrombosis are independent events. Vascular leakage occurs independent of platelets and FcγRIIA. Molecules implicated in leakage are presented in the figure. NETosis, neutrophil extracellular traps; P-sel, P-selectin.

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Discussion

In this study, we examined platelet activity in IC-induced systemic inflammation in

the absence of vascular insult. We confirmed a central role for platelet activation and

identified serotonin as a critical platelet component mediating mechanisms of shock.

Albeit artificial, models utilizing ferric chloride, laser-induced injury, or injection of

cytokines or PAMP in tissue/organs (e.g., cremaster muscle, liver, lungs)–(6, 9, 47)

have provided crucial insights to key pathways implicated in inflammation. Herein,

we used HA-IgG as a surrogate model of ICs and revealed critical components in

the in vivo response to systemic ICs, which were further confirmed using active

immunization with endotoxin, virus, or a commonly used antigen in the study of

anaphylaxis. Our observations were only possible using FcγRIIATGN mice, where we

confirmed the functional association of FcγRIIA and αIIbβ3 in platelet activation, and

suggest that targeting these receptors may have clinical benefits in severe conditions

involving ICs. Conversely, other molecules (i.e., P-selectin, GPIb, ADP,

thromboxane) that classically play a dominant role in platelet activation in

thrombosis, or favor platelet and neutrophil interactions, were dispensable. The

contribution of neutrophils to the systemic response to ICs is, however, not excluded,

as neutrophils have also been previously implicated, possibly through the release of

PAF (12, 23, 28). Hence, although serotonin release was maintained in the absence

of neutrophils, shock was dramatically reduced (Figs. S2B and S8A). We thus

propose that the release of serotonin precedes the neutrophil contribution to shock,

consistent with the reported role of serotonin in neutrophil activation (48). As

vasodilation was also present in the absence of neutrophils (Fig. S3B), these data

suggest that platelets, through serotonin, orchestrate neutrophil activation and

endothelial cell functions, and that these events can occur independently (Fig. 6).

Vascular leakage is another feature systematically observed when ICs were present

in blood. Intriguingly, leakage and vasodilatation were not connected, as leakage

took place independent of FcγRIIA but vasodilation critically required FcγRIIA and

serotonin. As such, vessel permeability likely involved smaller postcapillaries

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vessels and more subtle changes in endothelial cell interactions, and was also

insufficient to induce significant edema in the lungs, although platelets and

neutrophils accumulated in great number in the lungs. In addition, leakage critically

involved IC-mediated signaling, given that it was totally absent in FcRγ−/− mice (Fig.

S3A). While neutrophils express other IgG receptors (other than FcγRIIA), they were

dispensable in the process (Fig. S3A). Therefore, leakage could be attributed to mast

cells or basophils, for instance, which also express an array of receptors, such as

FcγRI and FcγRIII, capable of responding to ICs and can mediate permeability,

potentially through histamine release (49).

Whereas serotonin is mostly known for its role in mood, anxiety, psychosis, or

memory in the central nervous system, more than 95% of total body serotonin is

present in the periphery (39). The majority of peripheral serotonin is stored in

platelets, and our observations further revealed that platelets from female mice

contain less serotonin than those from males (Fig. S8B), which may explain, in part,

the aggravated phenotype observed in male mice compared with females following

IC challenge. Moreover, although platelets in females and males expressed similar

levels of FcγRIIA, female FcγRIIATGN mice presented significantly lower platelet

counts than males, which could also partially explain the reduced shock in females

in comparison to male mice (Fig. S8 C–E). Other immune components, such as

complement C5a, are also more abundant in males than in females (50). Whether

the serotonin reservoir in platelets explains a fundamental gender-related dichotomy

in susceptibility to inflammatory responses to ICs remains to be established.

The function of serotonin in platelets is not clear; studies suggest that it is important

for the serotonylation of proteins necessary in platelet aggregation (51). However,

SSRIs are typically used by patients during the perioperative period and mice lacking

peripheral serotonin present only mild bleeding defects (43). Thus, the present study

sheds light on a major role of platelet serotonin in response to a systemic stimulus,

which occurs independent of other molecules typically implicated in the prevention

of bleeding. The advantages for an organism to release bulk serotonin in response

to systemic ICs are unclear. We can speculate that in response to a microbial

280

invasion in an immune host, it might be preferable to reduce blood flow to prevent

dissemination of the pathogen to vital organs and to facilitate its capture by

phagocytes. As serotonin also mediates organ regeneration (52), its liberation may

be pivotal to regrowth following insults caused by pathogen invasion.

Thrombocytopenia, which coincides with thrombi formation in the lungs, has been

reported to occur in FcγRIIATGN mice, and requires the expression of guanine

nucleotide exchange factor CalDAG-GEF1 and 12-lipoxygenase (22, 25–27, 53).

We showed here that the formation of thrombi or occlusion of blood vessels was not

the primary cause of shock; thrombi formed normally in FcγRIIATGN/Tph1−/− mice,

whereas shock was nearly totally abrogated in these mice. Furthermore, reduction

of thrombosis by blockade of GPIb was without effect on shock and

thrombocytopenia, thereby revealing that thrombocytopenia resulted mainly from

platelet sequestration, not thrombosis. Whereas platelets were observed in the lungs

and brain, principally in the smaller and intertwined vessels, platelets may also be

hiding in other yet-to-be-discovered vascular beds despite our careful investigations.

In thrombotic thrombocytopenic purpura, profound thrombocytopenia is explained by

the failure of ADAMTS13 to perform proteolysis of vWF attached to the endothelium

(54), a mechanism distinct from what is observed in IC-induced thrombocytopenia,

as the blockade of vWF and GPIb had no effects on thrombocytopenia in our study.

As in-depth whole-mouse imaging uniquely identified megakaryocytes and thrombi,

which comprise more stable and adherent platelets, it suggests that the majority of

the sequestered platelets were dislodged by the perfusion procedure. Therefore, we

propose that platelets might be bridged together by ICs, and that platelet–IC

scaffolds may be loosely trapped in the microvasculature.

Degranulated platelets recirculate, a finding of potential significance for elucidating

mechanisms underlying thrombocytopenia. The absence of PS at the surface

suggests that they are not procoagulant platelets, known as balloon- or zombie-like

platelets (55). How platelets return to the circulation after sequestration is unclear,

but it is reasonable to speculate that disengagement of FcγRIIA after its

desensitization by yet unknown mechanisms (e.g., unidentified immunoreceptor

281

tyrosine-based inhibitory motif-containing receptors or phosphatases) or IC

internalization by platelets (56) might release platelets from platelet–IC scaffolds and

permit their liberation from the microvasculature. FcγRIIA expression was

maintained, however, on recirculating platelets, suggesting that it might be recycled

if the internalization of ICs is implicated. Of interest is that platelets at thrombi

surfaces visualized in vascular injury models appear loosely packed and lightly

activated (57, 58), and might also return to the circulation. As platelets activated in

vitro with thrombin can also circulate after degranulation if transfused (59, 60), our

study reveals that thrombotic and immunological triggers can induce degranulation

independent of platelet elimination. These models contrast with the general belief

that platelets “have only one life,” and may not recirculate after undergoing activation

in vivo.

The insertion of human activating (FcγRIIA/IIIA/IIIB) and inhibitory (FcγRIIB) FcγR

into the equivalent murine locus confirmed the predominance of FcγRIIA in systemic

shock in the humanized mouse model (28), suggesting that our findings may well be

translatable to humans as platelets from transgenic mice and humans express

equivalent levels of FcγRIIA (18). While these approaches cannot fully recapitulate

all of the subtleties of IC-driven inflammation in humans, it is very likely that the

mechanisms revealed in our study may, at least in part, take place in disease states

such as rheumatic disease, HIT, sepsis, viremia, anaphylaxis, and adverse reactions

following i.v. IgG therapy.

PAMPs trigger innate immune responses through activation of pattern-recognition

receptors, but the recognition of PAMPs by antibodies in adaptive immunity can

modulate different responses (61). We found that LPS, a Toll-like receptor 4 (TLR-

4) trigger, dominantly implicates platelets and serotonin when involving the adaptive

immune response in mice that had been preexposed to LPS. All adult volunteers we

examined also displayed antibodies directed against the endotoxin. Interestingly,

humans lacking TLR signaling molecules are extremely susceptible to infections in

infancy and childhood, and thereafter develop significant resistance, consistent with

the prevalent role of adaptive immunity in adults (62). Sepsis susceptibility is

282

associated with FcγRIIA polymorphism (63) and is accompanied by elevated

serotonin and endothelial hyperpermeability (64), which could be attributed to

platelets. Furthermore, thrombocytopenia measured in patients with sepsis is a

strong predictor of mortality (65, 66), and our data suggest that platelets may be

sequestered through FcγRIIA activation in some patients. It is thus important to note

that most mouse models of sepsis or viral infection may be suboptimal, as they

overlook the contribution of FcγRIIA in a nonimmune host. Observations from trials

during which LPS was injected into volunteers revealed that humans responded

more promptly to small doses of LPS than mice (67), pointing to the involvement of

ICs and FcγRIIA in humans, a pathway absent in mice.

Circulating platelets presenting reduced granule content are reported in different

contexts, such as cardiovascular diseases, type-2 diabetes mellitus, preeclampsia,

autoimmune diseases, and sepsis (68–72). In patients with severe sepsis, ADP and

serotonin contents in platelets were reduced by 40% and 50%, respectively (71).

However, very little is known about the impact of in vivo platelet degranulation on

platelet life span. In chronic conditions implicating ICs, such as rheumatic diseases,

ICs constantly trigger platelet FcγRIIA, consistent with the frequent shifts in platelet

count. Hence, microthrombi are recognized in these diseases, including in the lungs,

and the platelet content of serotonin is reportedly reduced in patients with SLE and

RA by 25% and 27%, respectively (72, 73), suggesting that platelets might indeed

circulate in their degranulated form in various contexts implicating ICs (70).

Neuropsychiatric SLE is the least understood, yet the most prevalent, manifestation

of SLE (74). Our identification of localized platelet activation in the brain

microvasculature and leakage of the blood–brain barrier may thus have implications

in the important and poorly understood neurological manifestations in rheumatic

diseases.

In summary, our study reveals platelet contributions to inflammation in reactions

involving ICs. It appears that the FcγRIIA signaling and serotonin release are unique

in regard to their major role in inflammation and minor roles in the prevention of

283

bleeding, suggesting that interference in this process might be a promising avenue

for further research.

Materials and Methods

Mice.

C57BL/6J (FcγRIIAnull mice), FcγRIIATGN hemizygous mice (12, 20), and FcRγ−/−

mice were obtained from The Jackson Laboratory. FcγRIIATGN hemizygous mice

described to express human FcγRIIA on platelets, megakaryocytes, monocytes,

macrophages, neutrophils, eosinophils, basophils, mast cells, and dendritic cells (12,

20) were backcrossed to C57BL/6J more than 10 times. The β3−/− mice (30), Tph1−/−

mice (43), and CD41-YFP mice (75) were crossed with FcγRIIATGN mice to obtain

FcγRIIATGN/β3−/− (30), FcγRIIATGN/Tph1−/−, and FcγRIIATGN/CD41-YFP mice.

Chimeric mice were generated by transfer of bone marrow cells of FcγRIIATGN mice

into FcγRIIAnull (WT), Fibγ390-396A, and Fibγ∆5 irradiated mice (34, 35, 76). Guidelines

of the Canadian Council on Animal Care were followed in a protocol approved by

the Animal Welfare Committee at Laval University (2013-106-3).

HA-IgG as an IC Model.

Human IgG (IC) (MP-biological, Sigma–Aldrich and Innovative Research) were i.v.

injected (600 μg and 750 μg) in males and females, respectively. In some

experiments, human IgG was dissolved but nonaggregated (monomeric) or mouse

IgG was aggregated and injected in mice (29).

Measure of Shock.

Temperature was measured using a rectal probe thermometer at indicated time

points. Signs of apparent shock were assessed as described previously (24, 77)

using a score from 0 to 3 (24, 77). A score of 3 represents completely immobilized

and unconscious mice (mice collapse and do not react to sound or touch), a score

of 2 represents mice with impaired mobility and irregular respiration, a score of 1

corresponds to mice with slow motions and shallow respiration, and a score of 0

284

describes normal mice. In anaphylaxis experiments implicating BSA injection in

BSA-immunized FcγRIIATGN mice, death was sometimes observed. In those

exceptional cases, shock was scored as 4. Scores measured in experimental groups

were averaged and are presented as a function of time (minutes). Scores for

individual mice for key experiments are provided in SI Materials and Methods (Fig.

S1 A and F).

LPS Immunization Model.

Mice were immunized with i.v. injection of 1 mg/kg LPS (Escherichia coli 0111:B4;

Sigma–Aldrich) at days 0, 14, 28, and 42. At the first and the last immunizations,

shock and temperature were monitored for 1 h. Mouse blood was drawn by cardiac

puncture 10 min after the fourth injection and used for platelet count and ELISA.

Lungs were also collected as described below.

Flow Cytometry.

Flow cytometry was performed using a BD FACSCanto II instrument with forward

scatter coupled to a photomultiplier tube “small particles option” flow cytometer (BD

Biosciences). Platelets, platelets interacting with neutrophils, and platelet

microparticles were analyzed.

Histology.

In some experiments, organs were collected at the end of the experiment.

Intratracheal instillation with 1 mL of 4% paraformaldehyde in lungs was performed

before collection. Brain, kidneys, spleen, heart, liver, and lungs were collected and

then fixed in 4% paraformaldehyde for 24 h (lungs) or 72 h (other organs); they were

then washed and stored in PBS at 4 °C before histology. After fixation, paraffin-

embedded organs were cut into 5-μm sections and stained with hematoxylin and

eosin. Thrombi were observed on five different spots at 400× resolution, they were

counted using light microscopy (BX51; Olympus) by a blinded investigator, and the

numbers of lung thrombi per square millimeter were calculated. Neutrophils were

identified in lungs of IC-injected FcγRIIATGN mice.

285

Two-Photon Intravital Microscopy.

For in vivo imaging of the mouse brain, FcγRIIATGN/CD41-YFP mice (8–12 wk old)

were anesthetized with 1–2% isoflurane (vol/vol) and a cranial window was made to

expose the vasculature of the sensorimotor cortex. Animals were imaged 2 wk after

the surgery. Briefly, for the imaging session, the head of the mouse was restrained

using a custom-built cranial stereotaxic apparatus (David Kopf Instruments) and

placed under the microscope. For the ear imaging, mice were anesthetized and the

hair recovering the ears was gently removed using Nair, a commercial depilatory

lotion. One ear was then gently flattened and fixed on a Plexiglas bloc using MSI-

EpiDermGlu (Medisav Services). Gelseal (GE Healthcare) was applied around the

tissues to form a watertight rim, and the imaging cavities were filled with sterile HBSS

without Ca2+/Mg2+ (Thermo Fisher Scientific). Blood vessels were stained by an i.v.

injection of 0.05% Evans Blue (Sigma–Aldrich) diluted in 0.9% sterile saline. Body

temperature was kept at 37 °C during all procedures with a heating pad. Four to six

different vessels per mouse were analyzed at 1 and 8 min postinjection.

Patients with Septic Shock.

Adult (age ≥ 21 y) patients with septic shock and confirmed, gram-negative

bacteremia were included. Each patient or an authorized family member provided

written informed consent. Septic shock was defined as the presence of sepsis

(requiring evidence of systemic infection and two or more of the following:

temperature >38 °C or <36 °C; heart rate >90 beats per minute; respiratory rate >20

breaths per minute or partial pressure of carbon dioxide in arterial blood <32 mmHg;

WBC count >12,000/mL, <4,000/mL, or >10% bands) and the need for vasopressors

to maintain a systolic blood pressure >90 mmHg or within 40 mmHg of baseline

despite adequate fluid resuscitation (5, 6). For identification of gram-negative

bacteremia, blood samples were obtained from patients upon intensive care unit

(ICU) admission as part of their routine clinical care. Blood samples underwent gram

staining and culturing in a clinical pathology laboratory. Gram-negative pathogens

were identified from the gram stain and/or cultures by the clinical laboratory. Healthy,

286

fasting adult (age ≥ 21 y) control subjects provided informed consent. Following

informed consent, demographic data, physiological parameters, and laboratory data

were recorded. Plasma was harvested by centrifugation on whole blood collected in

sterile ACD vacutainer tubes. Plasma was frozen at −80 °C until used for assays. In

patients with septic shock, plasma was obtained within 48 h of ICU admission.

Study Approval.

Informed consent was obtained from all human subjects in the study. The study was

approved by the institutional review board at University of Utah.

Statistical Analysis.

Results are presented as mean ± SEM. The statistical significance for comparisons

between groups was determined using one-way ANOVA, two-way repeated-

measures ANOVA, an unpaired Student’s t test, or a Mann–Whitney U test. The

D’Agostino–Pearson test was used as a normality test. All statistical analysis was

done using Prism software package 6 (GraphPad Software).

287

Acknowledgments

We thank Isabelle Dubuc for expert technical assistance with virus preparation. This

work was supported by a foundation grant from the Canadian Institutes of Health

Research (CIHR) (to E.B.); it was also supported, in part, by NIH/National Heart,

Lung, and Blood Institute Grant 5F32HL118865 (to K.R.M.), Grant HL130054 (to

P.J.N.), and Grant R01Hl68130 (to J.E.I.); by Grant 1K01DK111515 from the

National Institutes of Diabetes and Digestive and Kidney Diseases (to K.R.M.); by a

grant from the Canadian Funds for Innovation (to G.P.); by Grant HL112311 (to

M.T.R.); by Grant HL126547 (to M.T.R.); by National Institute on Aging Grant

AG048022 (to M.T.R.), by a CIHR foundation grant (to W.I.K.); by Grant

P01HL110860 (to S.E.M.), by a CIHR operating grant (to S.L.); and by CIHR Grant

MOP 93575 (to L.F.). E.B. is the recipient of an investigator award from the CIHR.

K.R.M. and J.E.I. are American Society of Hematology Fellow Scholars. G.M. has

an award from the Canadian Blood Services, N.T. and I.M. are recipients of

fellowships from The Arthritis Society (TAS), A.Z. is a recipient of fellowships from

the TAS and CIHR, and B.M. has a fellowship from the Fondation du Centre

Hospitalier Universitaire de Quebec. This material is also the result of work

supported with resources and the use of facilities at the George E. Wahlen Veterans

Affairs Medical Center (M.T.R.). The contents do not represent the views of the US

Department of Veterans Affairs or the US Government.

288

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291

Annexe IV: Autoantibodies in Systemic Lupus

Erythematosus Target Mitochondrial RNA

Yann Becker 1, Geneviève Marcoux1, Isabelle Allaeys1 , Anne-Sophie

Julien2, Renée-Claude Loignon 3, Hadrien Benk-Fortin 1, Emmanuelle Rollet-

Labelle 1, Joyce Rauch 4, Paul R Fortin1,3,5 , Eric Boilard 1 , 5

Affiliations

1 Département de microbiologie et immunologie, Faculté de Médecine de l'Université Laval, Centre de Recherche du CHU de Québec-Université Laval, Québec City, QC, Canada.

2 Département de mathématiques et statistiques, Université Laval, Québec City, QC, Canada.

3 Division de Rhumatologie, Département de Médecine, CHU de Québec-Université Laval, Québec City, QC, Canada.

4 Division of Rheumatology, Department of Medicine, Research Institute of the McGill University Health Centre, Montreal, QC, Canada.

5 Axe maladies infectieuses et inflammatoires, Centre de Recherche du CHU de Québec-Université Laval, Québec City, QC, Canada.

292

Abstract

The mitochondrion supplies energy to the cell and regulates apoptosis. Unlike other

mammalian organelles, mitochondria are formed by binary fission and cannot be

directly produced by the cell. They contain numerous copies of a compact circular

genome that encodes RNA molecules and proteins involved in mitochondrial

oxidative phosphorylation. Whereas, mitochondrial DNA (mtDNA) activates the

innate immune system if present in the cytosol or the extracellular milieu, it is also

the target of circulating autoantibodies in systemic lupus erythematosus (SLE).

However, it is not known whether mitochondrial RNA is also recognized by

autoantibodies in SLE. In the present study, we evaluated the presence of

autoantibodies targeting mitochondrial RNA (AmtRNA) in SLE. We quantified

AmtRNA in an inducible model of murine SLE. The AmtRNA were also determined

in SLE patients and healthy volunteers. AmtRNA titers were measured in both our

induced model of murine SLE and in human SLE, and biostatistical analyses were

performed to determine whether the presence and/or levels of AmtRNA were

associated with clinical features expressed by SLE patients. Both IgG and IgM

classes of AmtRNA were increased in SLE patients (n = 86) compared to healthy

controls (n = 30) (p < 0.0001 and p = 0.0493, respectively). AmtRNA IgG levels

correlated with anti-mtDNA-IgG titers (r s = 0.54, p < 0.0001) as well as with both

IgG and IgM against β-2-glycoprotein I (anti-β2GPI; r s = 0.22, p = 0.05), and

AmtRNA-IgG antibodies were present at higher levels when patients were positive

for autoantibodies to double-stranded-genomic DNA (p < 0.0001). AmtRNA-IgG

were able to specifically discriminate SLE patients from healthy controls, and were

negatively associated with plaque formation (p = 0.04) and lupus nephritis (p = 0.03).

Conversely, AmtRNA-IgM titers correlated with those of anti-β2GPI-IgM (r s = 0.48,

p < 0.0001). AmtRNA-IgM were higher when patients were positive for anticardiolipin

antibodies (aCL-IgG: p = 0.01; aCL-IgM: p = 0.002), but AmtRNA-IgM were not

associated with any of the clinical manifestations assessed. These findings identify

mtRNA as a novel mitochondrial antigen target in SLE, and support the concept that

mitochondria may provide an important source of circulating autoantigens in SLE.

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Introduction

The mitochondrion is an intracellular organelle involved in the regulation of

numerous cellular functions, among which the best known are ATP production and

programmed cell death (1, 2). Mitochondria are considered as deriving from the

endosymbiosis of an α-synfular; proteobacterium (3, 4), providing the organelles

many bacterial features (3, 5–9).

Different cellular lineages (10–18) may extrude their mitochondria upon activation.

Extracellular mitochondria have been identified in damaged tissues (8, 18–20);

diverse inflammatory conditions (11, 12, 14, 21–24); and in the blood of critical care

patients (22). As mitochondria retained several characteristics of their ancestral

prokaryotic origin, the release of mitochondrial components onto the extracellular

milieu can activate the innate immune system (25, 26). The efflux of mtDNA is

facilitated by megapores formed in the mitochondrial membrane during apoptosis,

and detected by the cytosolic DNA sensors cGAS and stimulator of interferon genes

(STING) pathway, thereby leading to type I interferon synthesis (27). Cardiolipin, N-

formylated peptides, mtDNA, ATP and reactive oxygen species are known

mitochondrial damage-associated molecular patterns (9, 28–30). They further

activate cells through nuclear oligomerization domain-like receptors (28, 29, 31), toll-

like receptors (TLR) (e.g., TLR9 for mtDNA), or formyl peptide receptors (9, 28–31).

Systemic lupus erythematosus is an autoimmune disease characterized by the

presence of circulating immune complexes and inflammation in multiple organs and

tissues. Recent evidence point to an involvement of mtDNA, liberated by neutrophils,

in the activation of STING and type-I IFN production in SLE (11, 12). Moreover,

extracellular mtDNA can enhance leukocyte migration and degranulation (32), and

promotes the secretion of the pro-inflammatory cytokine TNF-α by plasmacytoid

dendritic cells (33). Production of autoantibodies targeting several mitochondrial

components was reported in SLE as well as in other diseases [e.g., primary biliary

cirrhosis (PBC), antiphospholipid syndrome (APS), and cardiomyopathies] (Figure

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1). Anti-mitochondrial autoantibodies recognize proteins, such as those involved in

oxidative phosphorylation, phospholipids or unidentified epitopes present in the

mitochondrial membrane. Despite the extensive literature regarding antibodies

targeting the cardiolipin (also known as the mitochondrial antigen M1) in SLE, the

anti-mitochondrial autoantibody repertoire and their antigenic targets remains mostly

uncharacterized (12, 34–37). Using intact mitochondria and mtDNA as antigens to

screen autoantibodies in SLE patients, we have shown that different sets of

autoantibodies also target the mitochondrial outer membrane and mtDNA (36).

Given the accumulating evidence for mitochondrial release during inflammatory

pathogenesis, these observations point to a role for mitochondria both in the

stimulation of the innate immune system and as a potential source of autoantigens.

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Figure 1 Anti-mitochondrial antibodies and related diseases. Several types of anti-mitochondrial antibodies (AMA) have been reported in various diseases. The epitopes targeted by AMA cover all families of biomolecules: lipids (yellow background), proteins (red hues) or nucleic acids (blue hues). However, the precise nature of some mitochondrial epitopes targeted by AMA are still unclear. (gray hues). To date, the sole mitochondrion-specific phospholipid antigen reported in both APS and SLE is cardiolipin (M1). M1 is located within the mitochondrial inner membrane (MIM) in healthy organelles, but may be displayed on the outer membrane (MOM) upon damages to the organelle. Distinct AMA against an unknown antigen (M5) were also reported in both APS and SLE. Four antigens are associated with PBC; PDC-E2 (M2, MIM), sulfite oxidase (M4, MOM), M8 (MOM), and glycogen phosphorylase (M9, MOM). These mitochondrial antigens are peptidic, with the exception of M8, whose nature remains uncharacterized. Sarcosine dehydrogenase (M7) is another immunogenic protein that is targeted by autoantibodies in patients suffering from cardiac conditions (i.e., hypertrophic or idiopathic cardiomyopathies or acute myocarditis). Two types of AMA were reported as iatrogenically induced in human patients: AMA-M3 (unknown, MOM) and AMA-M6 (monoamine oxidase B, MOM). In addition to these autoantibodies, we have reported the presence of autoantibodies targeting whole mitochondria (AwMA) in patients with SLE, APS, and PBC (with higher titers found in SLE donors). Moreover, antibodies specific to the mtDNA were specific to SLE patients. In the present study, we describe autoantibodies against mtRNA in patients with SLE and APS.

Whereas, the mitochondrion has already been described as a source of mtDNA

during inflammation (17, 21, 32), it is not known whether its important RNA content

(mtRNA) can contribute to the autoantigenic load in SLE. Despite its presence at

high copy numbers, the mitochondrial genome is very compact (38–40) During its

translation into mitochondrial messenger RNA (38), a long polycistronic transcript is

generated from each strand of mtDNA prior to undergoing processing into mtRNA

molecules. This highly regulated process is thought to occur in a particular location

in the mitochondrion, called mitochondrial RNA granules (41), and requires key RNA

processing enzymes such as the members of the FASTK family of proteins (42). The

human mitochondrial transcriptome comprises 16S ribosomal RNA molecules

(78%), transfer (13%), messenger (8%) and small non-coding antisense (1%)

mtRNA molecules. The complete mitochondria transcriptome is controlled by the

cell's energy requirements, and therefore varies greatly depending on its tissue

distribution. In the heart, 30% of the total messenger RNA molecules are of

mitochondrial origin, whereas ~5% of the total messenger RNA load in less

metabolically active cells such as leukocytes is encoded by mitochondrial genes

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(39). The important quantity of mtRNA may thus represent a major antigenic load for

the adaptive immune system upon release of mitochondria onto the extracellular

milieu.

With the accumulating evidence supporting the liberation of mitochondrial

components into the extracellular milieu in SLE (11, 12), it is crucial to identify the

various mitochondrial antigens. In the present study, we examined whether the RNA

molecules present in mitochondria are antigenic. The levels of anti-mtRNA

(AmtRNA) were measured in SLE sera, and we determined whether AmtRNA were

associated with antibodies against whole mitochondrial organelles (AwMA) and

mtDNA (AmtDNA). We also investigated the occurrence of AmtRNA in an induced

model of murine SLE. Finally, we determined whether AmtRNA were associated with

disease manifestations in patients with SLE.

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Materials and Methods

Induced Model of Murine SLE

This study was carried out in accordance with the recommendations of the Canadian

Council on Animal Care. The protocol was approved by McGill University Animal

Care Committee. C57BL/6 mice were obtained from Harlan Sprague Dawley Inc.

(Indianapolis, IN, USA) and housed in a specific-pathogen-free animal facility at the

animal facility of the Research Institute of the McGill University Health Center.

Female (10–12-weeks-old) mice were injected intravenously (i.v.) with 100 μL

human β2-GPI (20 μg) (Crystal Chem Inc., Elk Grove Village, IL, USA), followed 24

h later by a 100 μL i.v. injection of lipopolysaccharide (LPS from E.coli, serotype

O111:B4; 10 μg) (List Biological Laboratories, Campbell, CA, USA). β2-GPI and LPS

injections were repeated every 2 weeks for a total of three rounds of immunizations,

and then at 2-month intervals for the fourth and the fifth immunizations. C57BL/6

mice injected i.v. with PBS and LPS following the same schedule were used as

controls. Mice were bled 1 week after the fifth immunization and serum was kept

frozen at −70°C until testing.

Mitochondria Isolation

Mitochondria were isolated from the livers of C57BL/6 mice as previously described

(43). In brief, cells and tissues were disrupted by grinding in a glass/Teflon tissue

potter containing 12 mL ice-cold mitochondrial isolation buffer (10 mM Tris, 1 mM

EGTA, 200 mM sucrose) for each gram of liver. Debris were pelleted twice at 700 g,

for 10 min at 4°C and the supernatants were transferred to fresh tubes. Mitochondria

were further separated from other cellular fractions by three centrifugation steps

(twice at 7,000 g and once at 10,000 g, for 10 min at 4°C). Between each step,

pelleted mitochondria were re-suspended in 12 mL isolation buffer. Samples were

kept at −80°C until required for RNA isolation.

Mitochondrial RNA Isolation

Mitochondrial RNA was isolated using the Aurum™ Total RNA Mini Kit (Bio-Rad,

Hercules, CA, USA), following the manufacturer's instructions. Ribonucleic acid

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yields were quantified using a BioDrop μLITE and its proprietary software (BioDrop

Ltd., Cambridge, UK). The absence of contamination by mitochondrial DNA was

assessed by resolution of 1 μg untreated mtRNA and the same amount of RNAse

A-treated (QIAgen, 100 μg/mL) mtRNA on a 1.5% (w/v) agarose gel (Supplementary

Figure 1A). 15.09 ± 2.74 μg mtRNA were isolated for each mg of bicinchoninic acid

assay (BCA)-dosed mitochondria used (n = 3).

Enzyme-Linked Immunoassays for the Detection of Antibodies Targeting

Mitochondrial Antigens

Clear 96-well High Bind half-area flat bottom ELISA microplates (Corning, New York,

USA) were pre-coated with 100 μL per well of 1% protamine sulfate (Sigma-Aldrich)

in double-distilled water for 1 h at RT. Plates were then washed thrice with PBS and

loaded with mtRNA. Plates were coated overnight at 4°C, washed thrice and non-

specific binding was blocked for 4 h at 37°C with 100 μL per well of ELISA blocking

buffer (PBS−10% FBS−0.5% gelatin). Wells were rinsed three times with PBS and

incubated in duplicate with serum diluted (1:150 for human and 1:50 for mice) in

incubation buffer (PBS−10% FCS−0.3% gelatin). Plates were washed thrice with

PBS and incubated for 90 min at RT with either γ or μ chain-specific-alkaline

phosphatase-(AP) conjugated goat anti-human IgG or IgM (Sigma-Aldrich) for

human serum, or γ chain-specific-horseradish peroxidase (HRP)-conjugated goat

anti-mouse IgG (Sigma-Aldrich) for mice (1:1000) in secondary antibody buffer

(PBS−0.4% bovine serum albumin [BSA]). Unbound antibodies were washed thrice

with PBS. Signals from AP-conjugated antibodies were developed with para-

nitrophenol phosphate (p-NPP) for ~30 min at 37°C, and HRP-conjugated antibodies

were developed with 3,3′,5,5′-tetramethylbenzidine (TMB) at RT. The reaction was

stopped with 2 N sulfuric acid (H2SO4). Optical densities (OD) were measured at

405 nm (p-NPP) or 450 nm (HRP) on a SpectraMax 190 microplate reader

(Molecular Devices, Sunnyvale, CA, USA), using SoftMax Pro 5.4.1 (Molecular

Devices). For each experiment, blank values (i.e., wells coated with mtRNA, but

without sera) were subtracted from each measurement.

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The quantity of purified mitochondrial RNA (mtRNA) required for coating half-area

flat-bottom 96-well ELISA microplates (Corning, New York, USA) was optimized

following the aforementioned protocol, by using increasing concentrations from 0 to

1,600 ng of coating mtRNA. Pooled sera (1:150) from 6 SLE patients, who had

previously tested positive for AmtDNA and AwMA, were incubated after blocking

non-specific binding. The peak signal for optical densities at 405 nm was obtained

with 200 ng of coating mtRNA (Supplementary Figure 1B).

Ethics and Study Approval

This study was carried out in accordance with the recommendations of the Research

Ethics Board of the CHU de Québec—Université Laval with written informed consent

from all subjects. All subjects gave written informed consent in accordance with the

Declaration of Helsinki. The protocol was approved by Research Ethics Board of the

CHU de Québec—Université Laval.

Human Serum Samples

The human sera tested in this study were obtained from the Systemic Autoimmune

Rheumatic Disease (SARD) biobank and data repository (SARD-BDB) located at the

CHU de Québec-Université Laval (UL). This SARD-BDB and the specific use of the

sera for the present study were approved by the CHU de Québec-UL research ethics

board (#B13-06-1243 and #B14-08-2108, respectively). Patients with SLE met the

1982 ACR classification criteria for SLE (revised in 1997) (44, 45). A peripheral blood

sample was collected at the time of their first visit. Serum samples from 30 healthy

donors and 87 SLE patients included in the SARD-DBD cohort were used in the

present study. However, one patient had no clinical data available and was therefore

excluded for bio-statistical comparisons (i.e., n = 86 SLE donors for these tests).

Additional Serum Samples

Sera from a cohort of patients and controls from the University of Toronto Lupus

Clinic, as well as patients with primary biliary cirrhosis (PBC) from Quebec City, were

used in additional exploratory analyses to test the presence of AmtRNA in patients

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with the antiphospholipid syndrome (APS, n = 12) and PBC (n = 12). APS patients

and healthy controls, distinct from those included in the SARD-BDB (n = 43), were

originally recruited between August 2010 and October 2011, and gave consent to

allow remaining biospecimens to be used for future studies on lupus biomarkers.

This study has been reviewed and approved by the Research Ethics Board of the

University Health Network (#10-0637-BE) and of the CHU de Québec—Université

Laval (#B14-08-2108). APS patients met 1999 Sapporo criteria for the disease

(revised in 2006) (46, 47), and healthy controls were recruited if they had no known

illnesses and had no infectious symptoms at the time of the blood draw. Donors gave

a single blood sample that was linked to their anonymized clinical data. PBC patients

were positive for anti-mitochondrial antibodies and presented clinical criteria for the

disease (47, 48).

Clinical Variables Collected in SLE Patients

Sociodemographic Variables

Information was collected concerning patient's age, gender, marital status, and

ethnicity at the first visit in the SARD-BDB.

Patient Characteristics Including Exposures to Cardiovascular Risk Factors

A body mass index (BMI) was calculated and reported as underweight, normal,

overweight and obese. Hypertension and diabetes mellitus were documented as

present or absent. Smoking history was reported as non-smokers, ex-smokers or

current smokers. Female patients were considered post-menopausal in the absence

of menstruations for more than 12 continuous months.

Disease Specific Characteristics

ACR classification criteria (44, 45) were documented for each of the 11 categories

and a total score calculated (5 ± 1.28). Disease duration, lupus disease activity using

the SLE Disease Activity Index–2000 (SLEDAI-2K) (49, 50) and lupus damage using

the Systemic Lupus International Collaborating Clinics (SLICC)/ACR damage index

(SDI) (51, 52) were collected during the clinical visit matched to the blood specimen

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draw. Both the SLEDAI-2K and the SDI are reported as continuous variables and

they both have proven validity, reliability, and perform well in observational studies.

Medication Variables

Antimalarial use was defined as use of hydroxychloroquine or chloroquine at the

current visit. Steroid use was defined as prednisone use in the past year.

Clinical Outcomes

Clinically relevant lupus disease activity and damage were used as clinical outcome

in our analyses and were defined as a SLEDAI-2K of 4 or more to capture clinically

active lupus and a SDI of 1 or more to capture clinically significant damage. Other

outcome variables included arterial and venous thrombotic event ever in the past

and presence of lupus nephritis according to the presence or absence of the renal

item of the SLICC Classification criteria for SLE (53). Presence or absence of carotid

plaques, as well as average carotid-intima media thickness (CIMT) was also

documented by carotid ultrasound following a standard examination of both carotids

(standard carotid ultrasound research protocol using an Esaote MyLab Five

ultrasound machine with digital images sent for blind reading at the IMT Core

Laboratory of the Montreal Heart Institute).

Information From Clinical Laboratories

For SLE patients, an automated complete blood count was documented. The anti-

dsDNA, anticardiolipin antibodies (aCL) (IgG and IgM—laboratory cut-offs of 40 GPL

or MPL units) and anti-β2-GPI (IgG and IgM—laboratory cut-offs above the 99th

percentile of controls) were measured by ELISA. The lupus anticoagulant assay (LA)

followed international guidelines for the performance of this functional assay (54).

The above tests were performed in a clinical laboratory at CHU de Quebec-

Universite Laval as part of routine care.

Information From Research Laboratories

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In addition to the measurements provided by the clinical laboratories, our research

laboratory performed antibody assays to detect AwMA and AmtDNA, following

previously described methods (36).

Statistical Analyses

Descriptive statistics are presented as mean with standard deviation or frequency

with percentage without missing values for continuous and categorical variables,

respectively. Comparisons between groups were performed using the Student's,

Wilcoxon or Kruskal-Wallis tests depending on the nature of the variables and their

distribution. Spearman correlations were calculated to assess association between

continuous variables. Associations between AmtRNA and clinical outcomes were

studied by bivariate and multivariate logistic regressions, for dichotomous and

continuous outcomes, respectively. The latter were adjusted for gender, disease

duration, age, BMI, antimalarial medication and prednisone use. ROC curves were

generated to assess the predictive ability of AmtRNA to discriminate between SLE

and controls, and their area under the curve (AUC) was calculated. Participants'

results were considered positive for AmtRNA when their value was above the cut-off

value identified after maximizing Youden's Index. A 95% confidence interval was

obtained for the cut-off using 10,000 bootstrap samples. Performance measures are

presented with their 95% exact confidence interval. Statistical analyses were

performed with Prism 7 software (GraphPad Software Inc., La Jolla, CA, USA) and

SAS version 9.4 (SAS Institute Inc., Cary, NC, USA) and Figures were assembled

with Photoshop CS6 13.0 (Adobe Systems Inc., Mountain View, CA, USA).

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Results

We used our quantitative ELISA to assess whether AmtRNA from the IgG subclass

(AmtRNA-IgG) could be detected in an induced model of murine SLE in which the

production of circulating IgG against whole mitochondria (AwMA) and mitochondrial

DNA (AmtDNA) was previously reported (36). Antibodies against mtRNA were

significantly increased (p = 0.0005) in the sera of SLE mice compared with control

mice (Figure 2).

Figure 2 Circulating anti-mitochondrial RNA autoantibodies are detectable in sera from mice with induced SLE. Sera (1:50) from mice with induced SLE were incubated on ELISA plates coated with 200 ng murine mtRNA per well. Mice with induced SLE displayed a significant increase in serum antibodies against mtRNA in comparison to control mice. N = 4 mice per group. Data show the mean ± SD. Student's t-test. ***p < 0.001.

A cohort of 86 SLE patients (Tables 1–5) and 30 healthy controls (19 females [63.3

%], 11 males [36.7%], age: 49.33 ± 7.68 years) was studied to determine the

occurrence of AmtRNA-IgG and AmtRNA-IgM in human SLE. The proportion of male

donors in the healthy group was higher than in the SLE cohort (i.e., 36.7% vs. 16.3%

of male donors, respectively) as well as than the 1:10 male-to-female sex bias

reported in the disease. We thus verified that the anti-mitochondrial antibody titers

measured were not influenced by sex, using Wilcoxon test and found no significant

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differences (p-values between 0.14 and 0.97). Both AmtRNA-IgG and -IgM were

significantly increased in SLE patients, compared with healthy individuals (p =

0.0002 and p = 0.0493, respectively) (Figure 3; Supplementary Figure 1). In healthy

donors, AmtRNA-IgM were higher than AmtRNA-IgG levels (0.32 ± 0.24 vs. 0.16 ±

0.12), suggesting that antibodies targeting mitochondrial epitopes may be present in

healthy individuals even in the absence of any detectable pathology.

Table 1: Sociodemographic characteristics in the SARD-BDB.

Variable n Mean ± SD [or n (%)] Female 86 72 (83.7) Age (years) 86 49.41 ± 14.60 Marital status 82 Single 14 (17.1) Married 55 (67.1) Tobacco intake 83 Non-smokers 48 (57.8) Smokers 14 (16.9) Ex-smokers 21 (25.3)

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Table 5: Laboratory measurements. Variable n Mean ± SD [or n (%)] Platelets (0.10∧9/L) 86 221.63 ± 72.68 White blood cells (0.10∧9/L) 86 5.80 ± 2.06 Creatinine clearance 26 91.88 ± 21.31 AmtDNA (OD 405 nm) IgG 86 0.49 ± 0.53 IgM 86 0.45 ± 0.38 AwMA (OD 405 nm) IgG 86 0.34 ± 0.37 IgM 86 0.56 ± 0.58 AmtRNA (OD 405 nm) IgG 86 0.42 ± 0.38 IgM 86 0.52 ± 0.47 Lupus anticoagulant (LA) 61 8.69 ± 22.76 Anticardiolipin antibodies (aCL) IgG 79 11.33 ± 12.39 IgM 79 6.92 ± 13.92 Anti-β2GPI antibodies IgG 79 2.78 ± 6.59 IgM 79 3.36 ± 3.89 Anti-dsDNA antibodies 22 31.01 ± 80.40

β2GPI, β-2-glycoprotein I; AmtDNA, anti-mitochondrial DNA antibodies; AmtRNA, anti-mitochondrial RNA antibodies; AwMA, anti-whole mitochondria antibodies; OD, optical density.

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Figure 3 Antibodies targeting mitochondrial RNA (AmtRNA) are elevated in SLE patients. Two different isotypes of antibodies against mtRNA, IgG (left panel) and IgM (right panel), were assessed in SLE patients and healthy individuals included in the SARD-BDB. Both AmtRNA IgG and IgM were significantly increased in SLE patients, compared to healthy individuals (p = 0.0002 and p = 0.0493, respectively). SLE: N = 86; Healthy controls: N = 30. Data show the mean ± SD. Student's t-test. *p < 0.05; ***p < 0.001. Table 2: Clinical characteristics in the SARD-BDB. Variable n Mean ± SD [or n (%)] Disease duration 86 10.43 ± 10.69 Body mass index 86 25.55 ± 4.97 Post-menopausal 64 38 (59.4) Hypertension 86 11 (12.8) Diabetes 84 2 (2.4) Malar rash 85 19 (22.4) Discoid rash 85 12 (14.1) Photosensitivity 85 36 (42.4) Oral ulcers 85 26 (30.6) Arthritis (≥2 peripheral joints) 85 69 (81.2) Serositis 85 22 (25.9) Renal disorders 85 22 (25.9) Neurological disorders 85 4 (4.7) Hematological disorders 85 68 (80.0) Immunological disorders 85 62 (72.9) Anti-nuclear antibodies (ANA) 85 85 (100.0)

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Table 3: Outcome variables of the study.

Variable n Mean ± SD [or n (%)] SLEDAI-2K (Score) 3.24 ± 3.96 SLEDAI-2K ≥ 4 86 36 (41.9) SDI (score) 3.24 ± 3.96 SDI ≥ 0 86 36 (41.9) Thrombosis 10 (11.6) Arterial events 86 3 (3.5) Venous events 4 (4.7) Presence of plaque in the carotid 63 24 (38.1) Carotid intima-media thickness (CIMT, μm) 34 0.63 ± 0.13 Nephritis 61 14 (23.0)

SDI, lupus severity disease index; SLEDAI-2K, systemic lupus erythematosus disease activity index−2000.

Table 4: Information about medications taken by SLE patients (n = 86) in the SARD-BDB. Variable n(%) Anticoagulation/anti-platelets 13 (15.1) Antimalarial 70 (81.4) Prednisone 18 (20.9) Lipid lowering 14 (16.3) Diabetes medication 2 (2.3) LUPUS TREATMENTS Hydroxychloroquine 65 (76) Chloroquine 6 (7) Azathioprine 15 (17) Methotrexate 15 (17) Leflunomide 1 (1) Mycophenolate mofetil 11 (13) Mycophenolic acid 1 (1) Cyclophosphamide (PO or IV) 3 (4)

IV: intravenous injection; PO: per os.

In a separate exploratory analysis using donors distinct from those included in the

SARD-BDB, AmtRNA-IgG were also significantly increased in patients with APS, an

autoimmune condition often associated with SLE (p < 0.001 vs. healthy controls).

However, no differences in AmtRNA-IgG were observed between patients with PBC,

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a disease known for an adaptive immune response against mitochondrial

autoantigens, and healthy controls (p = 0.31) (Figure 4).

Figure 4 Detection of AmtRNA in two different diseases with anti-mitochondrial antibodies. Antiphospholipid syndrome (APS) and primary biliary cirrhosis (PBS) are two diseases with antibodies targeting mitochondrial antigens; cardiolipin (M1) in APS and PDC-E2 (M2), sulfite oxidase (M4), M8 (whose target is still unclear) and sarcosine dehydrogenase (M9) in PBC. Sera (1:150) from patients with APS presented a significant increase in circulating autoantibodies against mtRNA, compared to healthy individuals, whereas PBC patients had levels similar to the controls. Healthy: N = 43, APS: N = 12, PBC N = 12. Data are Mean ± SD. Kruskal-Wallis test with multiple comparisons to controls/healthy donors; Dunn's correction. ****p < 0.001.

Autoantibodies to genomic dsDNA (anti-dsDNA) and to β-2-glycoprotein I (anti-

β2GPI, IgG, and IgM) were evaluated during the clinical work-up of a patient with an

increased likelihood of SLE. We examined whether titers in AmtRNA (IgG and IgM)

and levels of anti-dsDNA or anti-β2GPI were associated with each other in the

patients, and found correlations between levels of AmtRNA-IgG and those of both

anti-β2GPI-IgG and IgM (rs = 0.22, p = 0.05). AmtRNA-IgM titers only displayed a

strong correlation with anti-β2GPI-IgM (rs = 0.48, p < 0.0001). Conversely, no

correlations were observed between AmtRNA and concentrations of anti-dsDNA

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(Table 6). We also determined whether the levels of AmtRNA correlated with IgG

and IgM antibodies targeting mitochondrial epitopes localized in diverse sub-

compartments of the organelle (36). Specifically, we measured antibodies

recognizing intact whole mitochondria (AwMA), which most likely bind epitopes

found on the outer mitochondrial membrane; aCL, which target cardiolipin, a

phospholipid located mainly within the mitochondrial inner membrane; and AmtDNA,

which recognize mitochondrial DNA. We found that AmtRNA-IgG levels correlated

with AmtDNA-IgG (rs = 0.54, p < 0.0001) and with AwMA-IgG (rs = 0.24, p = 0.03),

but not with aCL (IgG and IgM). AmtRNA-IgM concentrations correlated with

AmtDNA-IgM (rs = 0.83, p < 0.0001), AwMA-IgM (rs = 0.71, p < 0.0001), aCL-IgG

(rs = 0.27, p = 0.02), and aCL-IgM (rs = 0.57, p < 0.0001). Thus, in addition to the

newly described AmtRNA, different sets of anti-mitochondrial antibodies occur

conjointly in SLE.

Table 6: Correlations of anti-mtRNA levels, with titers of other auto-antibodies in SLE patients. AmtRNA IgG IgM AmtDNA IgG rs = 0.54 rs = 0.19 p < 0.0001 p = 0.08 IgM rs = −0.01 rs = 0.83 p = 0.92 p < 0.0001 AwMA IgG rs = 0.24 rs = 0.14 p = 0.03 p = 0.21 IgM rs = −0.03 rs = 0.71 p = 0.78 p < 0.0001 AmtRNA IgG rs = 0.16

p = 0.15 IgM rs = 0.16

p = 0.15 Anti-β2GPI antibodies IgG rs = 0.22 rs = 0.18 p = 0.05 p = 0.11 IgM rs = 0.22 rs = 0.48 p = 0.05 p < 0.0001 Anti-dsDNA antibodies rs = 0.13 rs = 0.11 p = 0.56 p = 0.62 Values are presented as Spearman correlation coefficient (rs) and p-value.

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β2GPI, β-2-glycoprotein I; aCL, anti-cardiolipin antibodies; AwMA, anti-whole mitochondria antibodies. AmtDNA, anti-mitochondrial DNA antibodies; Anti-dsDNA, antibodies against double-stranded DNA. Data in bold are statistically significant (p < 0.05).

One of the main features of SLE is the expression of numerous autoantibodies in

patients (55), some of which are known to be associated with the clinical expression

of the disease (56). We assessed whether AmtRNA are qualitatively associated with

positivity to several autoantibodies commonly found in SLE, including anti-dsDNA,

aCL, and LA. AmtRNA-IgG levels were higher in presence of anti-dsDNA antibodies

(p < 0.0001), whereas AmtRNA-IgM titers were elevated in presence of aCL-IgG and

-IgM (p = 0.01 and p = 0.002, respectively) (Table 7). Of note, circulating AmtRNA-

IgM tended (p = 0.06) to be increased in the presence of LA in SLE patients.

Table 7: Association of AmtRNA with clinically relevant SLE autoantibodies. AmtRNA IgG IgM aCL IgG (–) 0.26 ± 0.43 (–) 0.34 ± 0.40 (+) 0.42 ± 0.91 (+) 0.56 ± 0.90 p = 0.14 p = 0.01 IgM (–) 0.26 ± 0.43 (–) 0.33 ± 0.38 (+) 0.53 ± 0.95 (+) 0.86 ± 1.43 p = 0.19 p = 0.002 Lupus anticoagulant (–) 0.25 ± 0.45 (–) 0.35 ± 0.40 (+) 0.40 ± 0.67 (+) 0.57 ± 0.98 p = 0.20 p = 0.06 Anti-dsDNA antibodies (–) 0.19 ± 0.28 (–) 0.34 ± 0.41 (+) 0.70 ± 0.71 (+) 0.55 ± 0.27 p < 0.0001 p = 0.10 Values presented as median ± IQR and Wilcoxon test p-value for patient positives (+) or negatives (–) for each variable. aCL, anti-cardiolipin antibodies; AmtRNA, anti-mitochondrial RNA antibodies; Anti-dsDNA, antibodies against double-stranded DNA. Data in bold are statistically significant (p < 0.05).

We examined whether AmtRNA were associated with disease manifestations in 86

SLE patients for whom detailed clinical information were available (Table 8). Higher

levels of AmtRNA-IgG were associated with a lower occurrence of plaque in the

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carotid using a bivariate analysis [OR(95% CI) = 0.14 (0.02–0.91); p = 0.04], but this

significance was lost in the multivariate logistic regression [OR(95% CI) = 0.16

(0.01–1.81); p = 0.14]. We found no association between AmtRNA-IgG and two

clinical indices; one measuring SLE disease activity (SLEDAI-2K ≥ 4) and the other

indicating damages (SDI > 0), both by bi- and multivariate analyses. However, higher

concentrations of AmtRNA-IgG were positively associated with elevated anti-dsDNA

antibodies in both models. AmtRNA-IgG were not associated with lupus nephritis in

a bivariate analysis [OR(95% CI) = 0.17 (0.02–1.71); p = 0.13], but this association

became significant in the multivariate model [OR(95% CI) = 0.02 (0.00–0.68); p =

0.03]. In contrast, AmtRNA-IgM were not significantly associated with any of these

clinical outcomes by either the bi- or multi-variate analysis.

Table 8: Association of AmtRNA with clinical manifestations in SLE. AmtRNA IgG IgM OR (CI) p OR (CI) p Thrombotic events 1.28 (0.24;6.77) 0.77 0.93 (0.22;3.93) 0.92 [1.15 (0.17;7.87)] [0.88] [1.00 (0.18;5.61)] [1.00] Presence of plaque 0.14 (0.02–0.91) 0.04 0.83 (0.25–2.76) 0.76 [0.16 (0.01–1.81)] [0.14] [0.82 (0.23–2.91)] [0.76] SLEDAI-2K ≥ 4 2.30 (0.73–7.26) 0.16 0.86 (0.34–2.17) 0.75 [3.04 (0.78–11.77)] [0.11] [0.68 (0.25–1.88)] [0.46] SDI ≥ 0 0.95 (0.28–3.21) 0.94 0.50 (0.16–1.58) 0.24 [0.85 (0.15–4.92)] [0.85] [0.46 (0.11–1.86)] [0.28] Positivity to anti-dsDNA antibodies 34.97 (6.26–195.55) <0.0001 1.92 (0.67–5.50) 0.23 [70.60 (6.31–789.47)] [0.0005] [2.01 (0.50–8.11)] [0.33] Lupus nephritis 0.17 (0.02–1.71) 0.13 0.43 (0.08–2.30) 0.33 [0.02 (0.00–0.68)] [0.03] [0.25 (0.04–1.48)] [0.12]

Values presented as odds ratios (95% Wald Confidence Interval) and p-value from logistic regressions. In each instance, bivariate results are followed by multivariate analysis (between square brackets). Values in bold have a p-value ≤ 0.05. AmtRNA, anti-mitochondrial RNA antibodies; CI: 95% Wald Confidence Interval; OR, odds ratio; SDI, lupus severity disease index; SLEDAI-2K, SLE disease activity index−2000. Data in bold are statistically significant (p < 0.05).

Furthermore, we assessed if our conclusions were identical in patients with higher

disease activity by repeating our calculations with patients having a SLEDAI-2K

score > 6 (i.e., for 15 patients, compared to 36 with a cut-off value at a SLEDAI-2K

score ≥ 4). The associations between AmtRNA-IgG with SLEDAI-2K > 6 were

[OR(95% CI) = 2.71 (0.71–10.31)] for the bivariate logistic regression and [OR(95%

CI) = 1.99 (0.40–10.00)] for the multivariate regression model. Values for the

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associations between AmtRNA-IgM and SLEDAI-2K > 6 for bi- and multivariate

analyses were [OR(95% CI) = 0.53 (0.12–2.25)] and [OR(95% CI) = 0.37 (0.07–

1.89)], respectively. Thus, the conclusions remain the same using either SLEDAI-2K

cut-off value.

To determine whether AmtRNAs might qualify as efficient predictors of SLE, we

optimized cut-off values by Youden's method (Table 9). Calculated cut-off values

were 0.30 for AmtRNA-IgG and 0.52 for AmtRNA-IgM. Both parameters were very

specific for SLE (0.90 for IgG and 0.87 for IgM). Even though both Ig isotypes

displayed a certain lack of sensitivity [43 SLE patients (49%) positive for AmtRNA-

IgG and 33 (38%) for IgM], their positive predictive values (0.93 and 0.89) suggest

that AmtRNAs may be considered as biomarkers of interest. Importantly, of all of the

anti-mitochondrial autoantibodies measured, AmtRNA-IgG was the most potent at

discriminating SLE patients from healthy donors. In this regard, AmtRNA-IgG was

closely followed by AmtDNA-IgM. In contrast, AwMA (IgG and IgM) and AmtDNA-

IgG failed to efficiently discriminate SLE patients from healthy controls.

Table 9:Performance of cut-off values for AmtRNA, AwMA, and AmtDNA (OD 405nm). Cutpoint Sensitivity Specificity PPV NPV AUC

(95% BCI) (95% ECI) (95% ECI) (95% ECI) (95% ECI) (95% ECI) AmtRNA IgG 0.30 (0.11–0.54) 0.49 (0.38–0.60) 0.90 (0.73–0.98) 0.93 (0.82–0.99) 0.38 (0.27–0.50) 0.72 (0.62–0.82) IgM 0.52 (0.24–0.64) 0.38 (0.28–0.49) 0.87 (0.69–0.96) 0.89 (0.75–0.97) 0.33 (0.23–0.44) 0.62 (0.51–0.72) AwMA IgG 0.30 (0.12–0.44) 0.36 (0.26–0.47) 0.80 (0.61–0.92) 0.84 (0.68–0.94) 0.30 (0.21–0.42) 0.57 (0.45–0.69) IgM 0.68 (0.19–1.37) 0.24 (0.16–0.35) 0.87 (0.69–0.96) 0.84 (0.64–0.96) 0.29 (0.20–0.39) 0.48 (0.37–0.60) AmtDNA IgG 0.44 (0.22–1.25) 0.35 (0.25–0.46) 0.77 (0.58–0.90) 0.81 (0.65–0.92) 0.29 (0.19–0.40) 0.51 (0.40–0.62) IgM 0.36 (0.24–0.57) 0.51 (0.40–0.62) 0.83 (0.65–0.94) 0.90 (0.78–0.97) 0.37 (0.26–0.50) 0.65 (0.55–0.75)

Values in bold have an AUC significantly different than 50%. AmtDNA, anti-mitochondrial DNA antibodies. AmtRNA, anti-mitochondrial RNA antibodies. AUC, area under the curve. AwMA, anti-whole mitochondria antibodies. BCI, Bootstrap Confidence Interval. ECI, Exact Confidence Interval. NPV, Negative Predictive Value. OD, optical density. PPV, Positive Predictive Value. Data in bold are statistically significant (p < 0.05)

313

Discussion

Although the interplay between extracellular mitochondria and innate immunity has

been well-described, the interactions between mitochondria and the adaptive

immune system are less appreciated. Mitochondrial components are generally seen

as potential damage-associated molecular pattern (DAMP) if released by cells, but

their inflammatory potential may be different if they are also recognized by

autoantibodies. Herein, we propose mtRNA as a novel source of mitochondrial

autoantigens with high relevance to SLE.

Mitochondrial RNA is not the only mitochondrial sub-component with antigenic

potential in SLE. The first descriptions of anti-mitochondrial antibodies (AMA) were

published in the 1980's. However, the actual epitope(s) of some AMA remain

unidentified (57). Thus, AmtRNA add to the more recently appreciated AmtDNA and

AwMA (36). Adaptive autoimmunity targeting mitochondrial motifs is not unique to

SLE: a humoral immune response against mitochondrial autoantigens was reported

in various diseases, and described as 9 different types of AMA targeting distinct

epitopes (namely, M1 to M9) (36, 57). While AMA have been observed in different

contexts such as in cardiovascular diseases, iatrogenic disorders, secondary

syphilis, APS and SLE, they are best characterized in PBC (57, 58). The latter is

characterized by progressive infiltration of autoreactive lymphocytes through the

hepatic portal system (48, 59, 60). These cells display targeted autoreactivities

directed against different mitochondrial antigens specifically expressed by bile ducts

(60) such as the E2 subunit of the pyruvate dehydrogenase complex (PDC-E2, also

known as mitochondrial antigen M2) (61–64), sulfite oxidase (M4) (65), glycogen

oxidase (M9) (47, 66, 67) as well as other antigens that have not yet been described

(M8). Detection of these AMA in PBC by ELISA have a prognostic value: patients

positive for AMA-M4 and -M8 suffer from active and/or progressive forms of the

disease (68), whereas patients with only AMA-M2 and -M9 display diseases with

delayed evolutions (69) (recapitulated in Figure 1).

314

How exactly the mitochondrial antibodies are produced is not completely

understood, but mitochondrial antigens can be generated through the degradation

of old or damaged mitochondria by a specific form of autophagy known as

mitophagy. Autophagosomes containing mitochondria travel through the

endolysosomal system, leading to the degradation of its cargo and allowing the

production of mitochondrial peptides that can be processed and expressed by the

major histocompatibility complex (MHC). Both MHC-I and MHC-II have been

implicated (70), an involvement for the latter being suggested in the surveillance of

mitochondrial mutations occurring in cancer (71, 72). However, a recent study

revealed that mitochondrial antigen processing can also occur independently of

mitophagy. In this case, mitochondrial antigens are carried to endosomes by

mitochondrial-derived vesicles formed by a mechanism regulated by the proteins

PINK1 and Parkin (73, 74). Whether these mechanisms are involved in the

processing of mtRNA molecules remains to be established.

Mitochondrial RNA is a recognized trigger of TLR8, which similarly to bacterial RNA,

stimulates peripheral blood mononuclear cells (75). As the most metabolically active

cells express more mtRNA, they are more likely to contribute to mtRNA antigenic

load (39). Our study demonstrates that mtRNA is also recognized by antibodies,

suggesting that Fc receptors may be implicated in the internalization of mtRNA-IgG

complexes by endosomes, thereby favoring interactions with TLR8. Mitochondria

express various RNA species, the main one being ribosomal 16S RNA molecules

(39). However, the respective antigenicity of each mtRNA species was not assessed

in the present study. Moreover, the presence of certain nuclear messenger RNA has

been described within mitochondria (39), which could also account for the

antigenicity potential of the mitochondria. Considering the evidence for mitochondrial

release in different pathogeneses, our demonstration of the presence of antibodies

directed against mitochondrial RNA further confirms the role of mitochondria as a

source of autoantigens in autoimmunity.

315

We observed associations between the three sets of mitochondrial antibodies

(AwMA, AmtDNA, and AmtRNA), pointing to their common source. Moreover, both

AmtDNA-IgG and AmtRNA-IgG were associated with positivity for anti-dsDNA

antibodies, suggesting close relationships between auto-antibodies targeting distinct

nucleic acids.

While the IgG targeting mtRNA were significantly elevated in SLE patients, the IgG

recognizing mtDNA and whole mitochondria were not increased in these patients.

These observations contrast with our previous findings, which involved a different

cohort of patients and showed that AmtDNA and AwMA were significantly increased

in SLE (36). The patients included in our previous work were recruited by the

University of Toronto Lupus Clinic. The patients recruited in the present study

(SARD-BDB) are characterized by a shorter median duration of the disease (10 vs.

6 years) that may account for reduced organ damage as indicated by the SDI score

(median: Toronto = 1; SARD-BDB = 0) and the frequency of patients with lupus

nephritis (Toronto: 38.5%; SARD-BDB: 16.3%). These differences may reflect the

course of the disease with earlier titers of autoantibodies clearing detrimental

circulating autoantigens (i.e., in the SARD-BDB cohort) until other

pathophysiological processes such as epitope spread occur, eliciting immune

complex-mediated organ damage. Another interesting aspect is the discrepancy

between the representation of the various ethnicities included in both cohorts. The

SARD-BDB is almost exclusively composed of Caucasians (Caucasian: 97.7%,

Black: 1.2%, Other ethnicities: 1.2%), whereas the Toronto cohort includes a more

diverse ethnic panel (Caucasian: 57 %, Black: 18 %, Asian: 21%. Other: 5%). Such

differences between two groups of patients may also impact results such as the

incidence, prevalence and mortality rates (76–79). Together, these differences may

reflect upon the protective effects of AmtRNA-IgG reported in the present study.

Moreover, these elements suggest that the spectrum of anti-mitochondrial

antibodies may shift during the course of the disease.

316

The heterogeneity of the disease duration for the SLE patients included in the SARD-

BDB allows the optimization of cut-offs by Youden's method that discriminate

positive from negative samples. However, calculation of a universal cut-off requires

detection of AmtRNA in newly-diagnosed SLE patients. Additionally, associations

between AmtRNA and clinical features of the disease should be interpreted with

caution, as clinical outcomes identified might have occurred before or at the same

time than the blood draw. Verification of the temporal relationship between the

production of AmtRNA and clinical outcomes would require a study of the variation

in anti-mitochondrial antibodies titers over time and their levels at the onset of a

clinical outcome in a large prospective inception cohort.

Systemic lupus erythematosus is a highly complex disease, many aspects of which

still elude researchers (80). To date, only a limited number of biomarkers are

available (81, 82). There is an intense effort to discover new biomarkers that would

allow specific discrimination of SLE patients from both healthy individuals and those

with diseases that have clinical features close to those of SLE (83). From this

perspective, we present AmtRNA-IgG as antibodies present in SLE and APS, two

diseases that are often associated with each other. Interestingly, AmtRNA-IgG

appeared to be associated with less lupus nephritis and plaque formation in the

carotid. Together, these elements indicate that AmtRNA may have prognostic value

and help to identify patients with specific clinical profiles. Moreover, the different

associations of AmtDNA and AmtRNA with lupus nephritis (AmtDNA are positively

associated with nephritis, while AmtRNA display a negative association) may help

predict SLE patients at risk of kidney damage.

Our study highlights that expression of a broad repertoire of anti-mitochondrial

antibody subtypes (AMA; AMA-M1, AMA-M5, AwMA, AmtDNA, AmtRNA) is a major

feature of SLE, with specific targets being associated with different clinical features.

Future studies dedicated to the characterization of the mitochondrial autoantigens

recognized in SLE and their outcome on disease progression may provide useful

317

information that will ultimately help to improve diagnosis, prognosis, and stratification

of SLE patients.

318

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Annexe V: Anti-mitochondrial autoantibodies in

systemic lupus erythematosus and their

association with disease manifestations

Yann Becker,1 Renée-Claude Loignon,2 Anne-Sophie Julien,3 Geneviève Marcoux,1

Isabelle Allaeys,1 Tania Lévesque,1 Emmanuelle Rollet-Labelle,1 Hadrien Benk-Fortin,1 Nathalie Cloutier,1 Imène Melki,1 Lihi Eder,4 Éric Wagner,5 Martin Pelletier,1,6 Hassan El Hajj,7 Marie-Ève Tremblay,7 Clémence Belleannée,8 Marie-Josée Hébert,9 Mélanie Dieudé,9 Joyce Rauch,10 Paul R. Fortin,2,6 and Eric Boilard1,6

Author information 1Centre de Recherche du CHU de Québec – Université Laval, Département de microbiologie et immunologie, Faculté de Médecine de l′Université Laval, Québec, Qc Canada 2Division de Rhumatologie, Département de Médecine, CHU de Québec – Université Laval, Québec, Qc Canada 3Département de mathématiques et statistique, Université Laval, Québec, Qc Canada 4Women’s College Hospital and University of Toronto, Toronto, ON Canada 5Immunology and Histocompatibility Laboratory, Department of Medical Biology CHU de Québec - Université Laval; Department of Microbiology, Infectious Diseases and Immunology, Université Laval, Québec, Qc Canada 6Axe maladies infectieuses et inflammatoires, Centre de recherche du CHU de Québec – Université Laval, Québec, Qc Canada 7Axe Neurosciences, Centre de Recherche du CHU de Québec – Université Laval, Québec, Qc Canada 8Axe Reproduction, Santé de la mère et de l’enfant, Centre de recherche du CHU de Québec – Université Laval, Québec, Qc Canada 9Centre de recherche du CHU de Montréal, Montréal Québec, Québec, Qc Canada 10Division of Rheumatology, Department of Medicine, Research Institute of the McGill University Health Centre, Montreal, Qc H4A 3J1 Canada

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Abstract

Mitochondria are organelles that govern energy supply and control cell death.

Mitochondria also express bacterial features, such as the presence of inner

membrane cardiolipin and a circular genome rich in hypomethylated CpG motifs.

While mitochondrial extrusion by damaged organs or activated cells is thought to

trigger innate immunity, it is unclear whether extracellular mitochondria also

stimulate an adaptive immune response. We describe the development of novel

assays to detect autoantibodies specific to two distinct components of the

mitochondrion: the mitochondrial outer membrane and mitochondrial DNA.

Antibodies to these two mitochondrial constituents were increased in both human

and murine systemic lupus erythematosus (SLE), compared to controls, and were

present at higher levels than in patients with antiphospholipid syndrome or primary

biliary cirrhosis. In both bi- and multi-variate regression models, antibodies to

mitochondrial DNA, but not whole mitochondria, were associated with increased

anti-dsDNA antibodies and lupus nephritis. This study describes new and optimized

methods for the assessment of anti-mitochondrial antibodies, and demonstrates

their presence in both human and murine SLE. These findings suggest that different

mitochondrial components are immunogenic in SLE, and support the concept that

extracellular mitochondria may provide an important source of circulating

autoantigens in SLE.

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Introduction

The roles of mitochondria in bioenergetics and the control of cell proliferation or

death are well-documented1,2. Furthermore, mitochondria share several similarities

with bacteria3,4. Like bacteria, mitochondria are formed of an outer and an inner

membrane (inner contains cardiolipin)4,5, express formylated peptides6,7, and contain

a circular genome with hypomethylated DNA CpG motifs, referred to as

mitochondrial DNA (mtDNA)8,9.

Various cellular lineages are capable of extruding their mitochondria. Activated mast

cells10, T-cells11, eosinophils12, hepatocytes13, neutrophils14–16 and platelets17,18, in

addition to damaged organs or tissues7,13,19,20, release extracellular mitochondria.

Mitochondria and their components (e.g. N-formylated peptides and mtDNA) are

recognized as damage-associated molecular patterns (DAMPs), which activate the

innate immune system and elicit an inflammatory response6,21–23. Moreover, ATP

and reactive oxygen species (ROS), produced by mitochondria are triggers of the

nuclear oligomerization domain (NOD)-like receptors and contribute to

inflammasome activation21,22,24. Extracellular mitochondria have been described in

various clinical conditions, including trauma25,26, burn injury27, cancer28, rheumatoid

arthritis17,29, systemic lupus erythematosus (SLE)15,16 and transfusion adverse

reactions17,18,30,31. Their pro-inflammatory potential is generally thought to occur

through activation of Toll-like receptors (TLR), formyl peptide receptors, and

cytosolic pathogen recognition receptors, all key components of the innate immune

system6,21–24.

The adaptive immune system can also recognize mitochondria. This concept is

important, as the immune response initiated by mitochondrial DAMPs may be

different if the adaptive immune system is also implicated32,33. Different sets of anti-

mitochondrial antibodies (AMA), namely AMA-M1 to -M9, have been characterized34

(recapitulated in Table 1). The AMA-M2, -M4, -M8, and -M9 classes are well-

described in primary biliary cirrhosis (PBC)35–37, an autoimmune disease

characterized by a progressive destruction of the bile ducts due to the infiltration of

326

autoreactive T-cells38. These antibodies target distinct mitochondrial proteins notably

implicated in oxidative phosphorylation, and their differential induction depends on

disease severity or stage. Conversely, AMA-M6 autoantibodies have been described

in iatrogenic hepatitis induced by iproniazid39, while the AMA-M7 class of antibodies

targets mitochondrial epitopes, identified as sarcosine dehydrogenase and enzymes

associated with flavin adenine dinucleotide, in patients with cardiomyopathy and

myocarditis40.

Table 1: Various types of anti-mitochondrial antibodies implicated in human diseases.

Type of anti-mitochondrial

antibody:

Molecular target(s):

Localization: Associated disease(s):

Method(s) of detection:

References:

Anti-M1 Cardiolipin IMM APS, SLE, secondary syphilis

IIF, ELISAa, CFT

87

Anti-M2 2-oxoacid dehydrogenase complex

IMM PBC IIF, ELISAa, CFT

58

Anti-M3 Unknown OMM Venocuran-induced PLE

IIF, CFT 55

Anti-M4 Sulfite oxidase OMM PBC ELISAb, CFT 88

Anti-M5 Unknown OMM, IMM APS, SLE, SS, haemolytic anemia

IIF, CFT 56

Anti-M6 Monoamine oxydase B

OMM Iproniazid-induced hepatitis

IIF, ELISAb, CFT

39, 89

Anti-M7 Sarcosine dehydrogenase

IMM Cardiomyopathies ELISAa–c 90

Anti-M8 Unknown OMM PBC CFT 89

Anti-M9 Glycogen phosphorylase

OMM PBC ELISA 91, 92

aELISA performed on sub-mitochondrial particles (sonicated “crude” mitochondria). bELISA performed on purified antigen. cThe exact antigen recognized by M7 antibodies is yet to fully characterize.

APS, anti-phospholipid syndrome; CFT, complement fixation test; ELISA, enzyme-linked

immunosorbent assay; IIF, indirect immunofluorescence on rodent and/or human tissues;

IMM, inner mitochondrial membrane; OMM, outer mitochondrial membrane; PBC, primary

biliary cirrhosis; PLE, pseudolupus erythematosus; SLE, systemic lupus erythematosus; SS:

Sjögren syndrome.

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SLE is an autoimmune disease characterized by the presence of circulating antigen-

autoantibody immune complexes and inflammation in multiple organs and tissues.

In SLE, neutrophils were shown to release mtDNA through the generation of ROS,

a process leading to activation of the DNA sensor stimulator of interferon genes

(STING) and type-I IFN production15,16. Studies showed that anti-mtDNA antibodies

(AmtDNA) are induced in a subset of SLE patients, suggesting that extruded mtDNA

could be a relevant source of antigen for the anti-double stranded DNA (anti-dsDNA)

antibodies that prevail in SLE16,41,42. Clinically, anti-DNA antibodies are screened

initially by indirect immunofluorescence using human epithelial type 2 cells (HEp-2)

and enzyme immunoassay using double-stranded DNA43. Presence of anti-DNA

antibodies can also be assessed by indirect immunofluorescence using Crithidia

luciliae, an hemoflagellate parasite of blow-flies that possesses a uniquely large

mitochondrion that contains a high concentration of DNA, the kinetoplast44–46.

Another method commonly used is Farr radioimmunoassay, which involves the

precipitation of antibody-bound radiolabeled DNA and its detection with a scintillation

counter47.

Antibodies targeting mitochondrial components other than mtDNA are also found in

SLE. They include anti-cardiolipin [AMA-M1, also known as anti-cardiolipin

antibodies (ACA)], anti-60kDa heat shock protein (anti-HSP60), as well as AMA-M3

and AMA-M5 antibodies. AMA-M1 antibodies recognize cardiolipin and were

originally identified in syphilis-infected patients. Anti-cardiolipin antibodies are also

found in patients with SLE and antiphospholipid syndrome (APS), resulting in false

positive results in earlier syphilis detection assays34,48.

Interestingly, cardiolipin is a phospholipid that is found uniquely in the inner

mitochondrial membrane in eukaryotic cells. However, damaged mitochondria may

externalize their cardiolipin49, that may become accessible and induce the

development of antibodies to cardiolipin. Clinically, the presence of ACA is

associated with a greater risk of thrombotic events and thrombocytopenia50,51.

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Another mitochondrial antigen, HSP60, is a mitochondrial chaperonin implicated in

mitochondrial protein import52. Patients with SLE have antibodies against HSP6053,

and their presence (when concomitant with anti-phospholid antibodies) is associated

with vascular events54.

AMA-M3 were described in patients using a drug called venocuran who developed

a drug-induced syndrome (“pseudolupus”) with clinical manifestations of arthralgia,

fever, serositis, and lymphopenia. The immunological profile of pseudolupus is

characterized by the absence of antinuclear antibody (ANA), but the presence of

AMA-M355. The antigenic target of AMA-M3 is different than that of the other AMA

classes described in PBC55. It is resistant to trypsin and it is extracted by solvent,

pointing to its lipid nature. AMA-M3 are no longer encountered clinically since the

withdrawal of the drug venocuran.

AMA-M5 comprise another class of anti-mitochondrial antibodies identified in

patients with SLE, as well in APS, Sjögren syndrome, recurrent fetal loss, and

hemolytic anemia56. The precise antigenic target(s) of AMA-M5 is undefined, but lack

of competition by cardiolipin-containing liposomes suggests that it is distinct from the

target of AMA-M157. Indirect immunofluorescence on human or rodent tissues is

used to identify anti-M5 antibodies58. While immunofluorescence and complement

fixation test revealed that only 2% of SLE patients were positive for AMA-M5,

approximately 40% were positive by enzyme-linked immunosorbent assay

(ELISA)59. However, in the latter approach, mitochondria were only partially purified

and were sonicated, thus revealing antigenic epitopes that might not be recognized

in tissues60.

Emerging evidence supports the liberation of mitochondria by activated cells and

their potential contribution to inflammation in SLE15,16. Identification of mitochondrial

antigens recognized by autoantibodies in SLE may provide information on the roles

of extracellular mitochondria in autoimmunity and systemic inflammation. Herein, we

developed new methods to detect the presence of two distinct types of circulating

AMA: anti-whole mitochondria antibodies (AwMA) and AmtDNA. We then

329

determined their usefulness in a murine model of SLE, as well as in a cohort of SLE

patients. We evaluated these AMA in parallel with antibodies to the mitochondrial

chaperonin HSP60 (a known mitochondrial target in SLE), and determined the

associations of these autoantibodies with disease characteristics. To our knowledge,

this is the first study that examines the association of these AMA with disease

manifestations in SLE.

330

Results

Different methodologies exist for the isolation of mitochondria, and several

improvements have been introduced in recent years to enhance their purity and

quality. We used a combination of previously published protocols to obtain highly

purified mitochondria61,62. Mitochondria were isolated from mouse liver or a human

hepatocyte cell line (Hep-G2) using a combination of previously published

protocols61,62 (Fig. 1a). The Percoll gradient included in the purification protocol

eliminated contaminants from the endoplasmic reticulum and the proteasome

(Supplementary Fig. 1a)62. The purity of the mitochondrial preparations was high,

based on the extremely low content of cytosolic and nuclear proteins, and the

enrichment of three mitochondrial proteins [voltage-dependent anion channel

(VDAC), cytochrome C, and translocase of the outer membrane 22 (TOMM22)]

(Fig. 1b). The isolated mitochondria maintained their cytochrome C (Fig. 1b) and

respiratory functions, suggesting that integrity was conserved during the isolation

process (Fig. 1c).

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Figure 1 : Assessment of the mitochondrial preparations. (a) Mitochondria were isolated from either mouse liver or human Hep-G2 cell line by differential centrifugations and further purified by ultracentrifugation against Percoll gradient. Alkaline lysis was performed to retrieve mtDNA. Pure mitochondria or mtDNA were used as coating antigens in direct ELISAs. (b) Cytoplasmic (C), nuclear (N) and mitochondrial (M) markers were assessed by western blotting in murine (left) and human (right) mitochondrial preparations (25 µg protein per lane). Results are representative of three distinct preparations. Blots separated by dashed lines are non-contiguous but from same membrane. Blots separated by full lines were performed on distinct membranes; (c) Functionality of murine mitochondria was determined by measurement of the oxygen consumption rate (OCR) of 10 µg mitochondria treated successively with 2 µM rotenone, 10 mM succinate, 40 µM antimycin A and 100 µM N,N,N’,N’-Tetramethyl-p-phenylenediamine (TMPD) along with 10 mM ascorbate (Asc). (d) The hydrodynamic size of the murine mitochondria was determined using zetasizer nano ZS (n = 3, left panel) and their morphology was visualized by electron microscopy (right panel). Inner membrane (black arrowhead), outer membrane (white arrowhead), cristae (black arrow), mitochondrial matrix (white arrow) are presented (scale bar account for 500 nm); (e) Size representation of purified murine mitochondria using high sensitivity-flow cytometry. Double-positive mitochondria (Mitotracker+ TOMM22+) were used for quantification. Silica beads were used to determine 100–1000 nm size scale. Data are mean ± SD. Anti-A: antimycin A; CytC: cytochtome C; FSC: forward scatter; Mito: mitochondria PCNA: proliferating cell nuclear antigen; SSC: side scatter; Total: total starting material; TOMM22: translocase of the outer mitochondrial membrane; VDAC: voltage-dependent anion channel.

Mitochondria were homogeneous in size, with a main peak detected at 820 nm by

dynamic light scattering (Fig. 1d, left panel), and retained their canonical morphology

when observed in electron microscopy (910 ± 210 nm) (Fig. 1d, right panel). High

sensitivity flow cytometry, which permits the identification of submicron particles, was

used as a quantitative approach. We estimated that 6.6 ± 1.9 × 106 mitochondria

(Mitotracker+ TOMM22+) (or 4.33 ± 1.17 µg mitochondrial proteins) could be isolated

per mg of mouse liver (n = 6), which was sufficient to prepare approximately 400

wells in half-area 96-well microplates using one mouse liver (Fig. 1e). The yield

obtained with Hep-G2 cells was lower, as 3.5 ± 0.18 µg of mitochondrial protein were

isolated per 106 Hep-G2 cells (7.0 × ± 2.1 × 108 Hep-G2 cells were harvested for

each 175 cm2 flask at confluence), which can be used to prepare approximately two

half-area 96-well microplates.

332

The quantity of purified mitochondrial protein (12.5 µg mitochondrial protein/well)

required for coating half-area 96-well microplates ELISA plates was optimized using

increasing concentrations of mitochondria (Supplementary Fig. 1b). Wells were

saturated with phosphate buffered saline (PBS) containing fetal calf serum (FCS)

and gelatin, which proved optimal for blocking nonspecific binding of antibodies in

comparison to non-fat dry milk or bovine serum albumin (data not shown). We used

an inducible murine model of SLE to determine whether AwMA could be detected in

serum63. This model is known to produce autoantibodies to nuclear and cellular

antigens63, but the presence of AwMA has never been explored. We found high

serum levels of AwMA in this induced murine lupus model, compared to healthy

control mice (Fig. 2a).

Figure 2 : Antibodies targeting mitochondrial antigens are produced in a murine model of SLE. (a) Elevated levels of anti-whole mitochondria antibodies (AwMA) were detected by direct ELISA in sera (1:150) from an inducible murine model of systemic lupus erythematosus (SLE) compared to control mice. An isotype-matched monoclonal mouse anti-translocase of the outer mitochondrial membrane 22 (TOMM22) antibody (clone IC9-2. 4 µg/mL) was included as a positive assay control (dotted line). (Control: N = 8, SLE: N = 12, Student’s t-test); (b) Lipid peroxidation following in-vitro oxidation of the mitochondria by 500 µM tert-buthyl hydroperoxide (TBHP) was quantified by thiobarbituric reactive substances (TBARS) assay (N = 3, Wilcoxon test); (c) Protein oxidation was determined by carbonyl assay (n = 6, Wilcoxon test); (d) The effect of oxidation of mitochondrial epitopes on their recognition by serum AwMA (1:20) was assessed by direct ELISA, using either native (grey symbols) or oxidized mitochondria (black symbols) as coating antigens

333

(N = 13, two-way ANOVA with multiple comparisons; Sidak’s correction). All experiment presented in the figure were performed using mouse mitochondria. Data are mean ± SD. *p < 0.05. **p < 0.01. ***p < 0.001. ****p < 0.0001.

Reactive oxygen species are generated under inflammatory conditions, and were

reported during the release of mitochondria15,16. Thus, we assessed whether

oxidation of mitochondria could impact mitochondrial recognition by AwMA. Isolated

mitochondria were treated with increasing concentrations of the oxidant tert-butyl

hydroperoxide (TBHP), and the oxidized protein and lipid contents were confirmed

using commercial assays (Fig. 2b,c and Supplementary Fig. 2). We found that

oxidation had no or very little impact on recognition of mitochondria by SLE

antibodies (Fig. 2d) (Fold increase: 1.2 ± 0.2). The data suggest that mitochondria

are immunogenic in SLE regardless of the oxidation status of their antigens.

We next used our quantitative AwMA ELISA to screen human sera. We included 175

SLE patients and 43 healthy controls (76% female, mean age 42 ± 12) (Table 2). We

also evaluated sera from APS patients (n = 12), given the high levels of anti-

cardiolipin antibodies (AMA-M1) in APS, as well as sera from PBC patients (n = 12)

confirmed positive for AMA by indirect immunofluorescence on mouse

stomach/kidney slides (MSK).

334

Table 2: Demographics and clinical characteristics (ACR criteria) for SLE patients included in the study (n = 175). Characteristics SLE patients

Age

Range, years 20–78

Mean ± S.D, years 47 ± 15

Disease duration

Range, years 0–57

Mean ± S.D, years 18 ± 12

Gender, female, n (%) 175 (100)

Thrombotic events, n (%) 35 (20)

SLEDAI-2K ≥ 4, n (%) 57 (33)

SDI ≥ 1, n (%) 124 (71)

Increased anti-dsDNA, n (%) 59 (34)

Lupus nephritis, n (%) (n = 172) 67 (39)

Currently Prescribed Medication, n (%)

Anticoagulation or anti-platelet (n = 174) 40 (23)

Antimalarial 127 (73)

Prednisone 81 (46)

Lipid lowering 26 (15)

Diabetes medication 6 (3)

Malar rash 127 (72.6)

Discoid rash 24 (13.7)

Photosensitivity 113 (64.6)

Oral ulcers 108 (61.7)

Arthritis (≥2 peripheral joints) 151 (86.3)

Serositis 67 (38.3)

Neurologic disorder (seizure or psychosis) 24 (12.0)

Renal disorderA 100 (57.1)

eGFR (n = 160)

Range, mL/min/1.73 m2 17–121

Mean ± S.D, mL/min/1.73 m2 84.38 ± 24.70

<60 mL/min/1.73 m2, n (%) 26 (16.3)

Hematologic disorderB 155 (88.6)

Immunologic disorderC 159 (90.9)

Anti-nuclear antibodies (ANA) 170 (97.1)

American College of Rheumatology criteria (ACR) score

Range 03-Nov

Mean ± S.D 6.83 ± 1.62

A >0.5 g per day of protein in urine or cellular cast or end-stage renal disease. B Hemolytic anemia (low red blood cell count) or leukopenia (White blood cells < 4000/µl), lymphopenia (<100 000/µl) in the absence of offending drug. C Positive anti-Smith, anti-dsDNA, antiphospholipid antibody and/or false positive serological test for syphilis. eGFR: estimated glomerular filtration test.

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Given the higher yield and purity of the mitochondria isolated from mouse liver, and

the fact that mice are readily accessible in most research laboratories, we used intact

murine mitochondria as coating antigens in our assay for the detection of

autoantibodies targeting the outer mitochondrial membrane in humans. We found

that AwMA were present in all healthy controls, but at much lower levels than those

encountered in a large proportion of the SLE patients. SLE patients were more

frequently positive and at higher levels for AwMA than healthy controls. APS and

PBC patients also presented a significant increase in AwMA compared to healthy

donors but signals detected for these patients were lower than those measured in

SLE patients (Fig. 3a). As the ELISA is performed on intact mitochondria, these

results suggest that AwMA are induced in SLE, and recognize autoantigens on the

outer mitochondrial membrane that are distinct from the epitopes in APS (cardiolipin)

and PBC (pyruvate dehydrogenase complex E2-component, PDC-E2), both located

in the mitochondrial inner membrane. Consistent with this, we identified PBC

patients positive for AMA when submitochondrial particles (i.e. sonicated

mitochondria) were used as coating antigens, suggesting that certain antigens

relevant to PBC may be exposed in these conditions (Supplementary Fig. 3). Human

and murine mitochondria were also compared in our assay using sera from a subset

of SLE patients. Both sources of mitochondria (human Hep-G2 cells and mouse

liver) were similarly recognized by human AwMA (Fig. 3b), suggesting that antigenic

epitopes may be conserved across these species. Hence, mitochondria from murine,

bovine and porcine tissues are routinely used to assess AwMA in humans,

suggesting that interspecies differences play a negligible role, if any, in mitochondrial

antigenicity.

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Figure 3 : Detection of anti-mitochondrial antibodies in SLE patients and specificity of the assay. (a) Increased amounts of anti-whole mitochondria antibodies (AwMA) were detected by direct ELISA in sera (1:150) from systemic lupus erythematosus (SLE), anti-phospholipid syndrome (APS) and primary biliary cirrhosis (PBC) patients. Healthy: N = 43. SLE: N = 175. APS: N = 12, PBC: N = 12. The dotted line corresponds to the cutoff value as determined by Youden’s Index (see Table 5). Kruskal-Wallis test with multiple comparisons to healthy donors; Dunn’s correction. (b) No significant differences were detected by direct ELISA when either murine (Mm, gray symbols) or human mitochondria (Hs, black symbols) were used as coating antigens to detect AwMAs in control and SLE patient sera (1:100). Two-way ANOVA. (c) AwMA binding to coating mitochondria is inhibited in presence of mitochondria (filled circles) but not by red blood cells microparticles (filled squares). Two-way repeated measures ANOVA with multiple comparison (Dunnett’s correction) to signals detected without competitors (i.e. 100%). Experiments presented in panels 3 a and 3 c were performed using mouse mitochondria, the experiment presented in panel 3 b was performed in parallel on murine and human mitochondria. Data are mean ± SD. Not significant (ns): p > 0.05. *p < 0.05. ***p < 0.001. ****p < 0.0001. Hs: Homo sapiens; Mm: Mus musculus.

Membrane-bound vesicles in the extracellular milieu, known as extracellular vesicles

or microparticles, are proposed contributors to the antigenic load in SLE64–66. To

determine whether AwMA could also recognize microparticles derived from

membranes from cells or particles other than mitochondria, we utilized red blood cell

microparticles (RBCMP) as blood-borne microparticles devoid of mitochondria as a

competitor in our AwMA-ELISA, and compared it to extracellular mitochondria in

solution. Whereas increased concentrations of competing mitochondria decreased

AwMA binding by up to 49.84 ± 15.01%, RBCMP showed no inhibition of binding of

the SLE antibodies in our assay (Fig. 3c). While these results suggest that the

antibodies detected in the AwMA-ELISA might have a preferred substrate originating

in mitochondrial membrane, we cannot exclude the possibility that other membrane

bound microparticles or even cells may also be recognized by AwMA, given the

probable occurrence of numerous protein and non-protein antigens in mitochondria.

To determine whether mtDNA also represents an antigenic target of SLE

autoantibodies, we isolated mtDNA from crude mitochondria preparations, using

standard DNA extraction by alkaline lysis. Digestion of the mtDNA by Hae II, a

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restriction enzyme with a single restriction site on the murine mitochondrial genome

(Supplementary Fig. 4a) yielded a single fragment of 16,569 base pairs, indicating

the isolation of mtDNA with its circular conformation. As expected, digestion by Pst

I generated two fragments of 12,751 and 3818 base pairs, further confirming the

expected size of the isolated mtDNA. Moreover, we confirmed enrichment of mtDNA

relative to genomic DNA (Supplementary Fig. 4b). Up to 1.55 ± 0.35 µg mtDNA was

obtained for each mg of mitochondrial protein used. Plate adhesion of different

concentrations of mtDNA was enhanced by using plates pre-treated with protamine

sulfate, and binding specificity was increased by blocking the plates with a PBS

solution containing FCS and gelatin (Supplementary Fig. 4c). Of interest, sera from

mice with induced SLE were positive for AmtDNA, compared to control mice

(Fig. 4a). Moreover, AmtDNA was significantly increased in SLE patients, but not in

patients with APS or PBC, relative to healthy controls (Fig. 4b).

Figure 4 : Antibodies targeting mitochondrial DNA in SLE. (a) Anti-mitochondrial DNA antibodies (AmtDNA) are measured by direct ELISA in sera (1:50) from a mouse model of systemic lupus erythematosus (SLE) and control mice (Control: N = 8, SLE: N = 12, Student’s t-test). An isotype-matched monoclonal mouse anti-DNA antibody (clone 35I9 DNA, 10 µg/mL) was included as a positive assay control (dotted line). (b) Elevated levels of AmtDNA are observed in sera (1:150) from SLE but not from anti-phospholipid syndrome (APS) or primary biliary cirrhosis (PBC)

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patients. Healthy: N = 43. SLE: N = 175. APS: N = 12. PBC: N = 12. The dotted line corresponds to the cutoff value as determined by Youden’s index (see Table 5). Kruskal-Wallis test with multiple comparisons to controls/healthy donors; Dunn’s correction). All experiment presented in the figure were performed using mouse mtDNA. Data are mean ± SD. Not significant (ns): p > 0.05. ***p < 0.001. PBC: primary biliary cirrhosis.

Little is known about the association of AwMA and AmtDNA with the clinical

characteristics of SLE. We assessed whether AwMA and AmtDNA were associated

with disease manifestations in 175 SLE patients for whom detailed clinical

information was available. AwMA levels correlated with AmtDNA levels in SLE

patients (rs = 0.23, p = 0.003), but not in healthy controls (rs = 0.15, p = 0.33). In

contrast, AwMA did not correlate with antibodies against other mitochondrial

antigens (i.e. HSP60 and cardiolipin) and was not found to be associated with clinical

outcomes (Tables 3 and and4).4). Interestingly, AmtDNA was associated with both

increased anti-dsDNA antibodies (p = 0.02) and with a history of lupus nephritis

(p = 0.007), but not with any of the other clinical outcomes (Table 4). When the

duration of the disease, the age of the patients, their BMI, the use of prednisone

and/or antimalarial drugs, and circulating cholesterol LDL were taken into account,

the associations of AmtDNA with increased anti-dsDNA antibodies and lupus

nephritis remained significant in a multivariate logistic regression (p = 0.01 for both),

indicating an association between AmtDNA, and these two clinical parameters.

However, AmtDNA did not correlate with anti-dsDNA as measured by Farr assay in

the cohort, suggesting that the results measured by our AmtDNA-ELISA and those

obtained by Farr assay may not be redundant. Cut-off values were identified for

AwMA and AmtDNA (Figs 3, ,44 and Table 5). Our two ELISAs displayed high

specificities (AwMA: 0.88; AmtDNA: 0.74) and allowed us to efficiently discriminate

SLE patients from healthy donors (p < 0.001 for both AmtDNA and AwMA). Using

these values, we determined that 110 patients were positive for AmtDNA (62.86%)

and 101 patients (57.71%) were positive for AwMA.

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Table 3: Intercorrelations of anti-mtDNA, anti-whole mitochondria, anti-dsDNA and anti-cardiolipin antibodies in SLE patients (n = 175). AmtDNAA AwMAA DNA (Farr)A ACA (+/−)B

Anti-HSP60 0.07 p = 0.37

0.10 p = 0.21

0.02 p = 0.81

(+) 0.28 ± 0.52 (−) 0.52 ± 0.53 p = 0.08

AmtDNA — 0.23, p = 0.003 0.05 p = 0.46

(+) 0.33 ± 0.17 (−) 0.37 ± 0.27 p = 0.40

AwMA — — 0.10 p = 0.19

(+) 0.32 ± 0.20 (−) 0.33 ± 0.23 p = 0.51

AValues are presented as Spearman correlation coefficient and p-value. BValues presented as median ± IQR and Wilcoxon test p-value for patient positives (+) or negatives (−) for ACA. ACA: anti-cardiolipin antibodies; AwMA: anti-whole mitochondria antibodies. AmtDNA: anti-mitochondrial DNA antibodies; DNA Farr: quantification of anti-dsDNA antibodies by Farr assay; HSP60: heat-shock protein 60 KDa.

Table 4: AmtDNA and AwMA associations with clinical manifestations in SLE patients (n = 175).

Clinical Outcomes AmtDNA AwMA

OR (CI) p OR (CI) p

Thrombotic events 0.43 (0.10–1.79) 0.25 0.27 (0.04–1.99) 0.2

[0.35 (0.07–1.67)]* [0.19] [0.21 (0.02–1.82)] [0.15]

SLEDAI-2K ≥ 4 0.96 (0.37–2.51) 0.93 1.34 (0.49–3.69) 0.57

[1.01 (0.33–3.05)] [0.99] [1.08 (0.37–3.14)] [0.89]

SDI ≥ 1 0.91 (0.35–2.42) 0.86 0.85 (0.30–2.40) 0.76

[0.93 (0.32–2.68)] [0.90] [0.69 (0.23–2.09)] [0.52]

Increased anti-dsDNAA 3.34 (1.22–9.16) 0.02 1.15 (0.42–3.16) 0.79

[3.94 (1.33–11.69)] [0.01] [1.16 (0.40–3.35)] [0.79]

Lupus nephritis 4.45 (1.50–13.20) 0.007 1.06 (0.39–2.90) 0.91

[4.60 (1.41–14.99)] [0.01] [0.97 (0.34–2.73)] [0.95]

AOccurrences of patients with anti-dsDNA antibodies above the clinical threshold. AwMA: anti-whole mitochondria antibodies. AmtDNA: anti-mitochondrial DNA antibodies. SDI: lupus severity disease index. SLEDAI-2K: systemic lupus erythematosus disease activity index - 2000. OR (CI): Odds ratios (95% Wald Confidence Interval). P from logistic regressions.

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*Bivariate results (N = 175) are followed by multivariate results in square brackets (N = 169).

Table 5: Performance of cut-off values for AwMA and AmtDNA (Healthy donors: n = 43, SLE: n = 175).

Cutpoint

(OD405 nm) Sensitivity Specificity PPV NPV AUC

AwMA 0.30 (0.17–

0.32)

0.58 (0.50–

0.65)

0.88 (0.75–

0.96)

0.95 (0.89–

0.98)

0.34 (0.25–

0.43)

0.80

(0.73;0.87)

AmtDNA 0.30 (0.25–

0.45)

0.63 (0.55–

0.70)

0.74 (0.59–

0.87)

0.91 (0.84–

0.95)

0.33 (0.24–

0.43)

0.71

(0.63;0.79)

AwMA: anti-whole mitochondria antibodies. AmtDNA: anti-mitochondrial DNA antibodies. AUC: area under the curve. OD: optical density. PPV: Positive Predictive Value. NPV: Negative Predictive Value. NPP: Negative Predictive Value.

Thus, although more work is needed to explore the clinical associations of AmtDNA

and AwMA in a larger lupus population and over time, different subsets of

mitochondrial epitopes (i.e. mtDNA vs. outer membrane antigens) appear to

measure different immune responses in SLE patients and may be associated with

distinct disease characteristics.

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Discussion

Mitochondrial DAMPs are known to stimulate the innate immune response, but it is

less clear whether mitochondrial antigens stimulate an antibody response and

whether these antibodies impact the inflammatory reaction. Interestingly, in PBC, a

paradigm of true organ-specific autoimmunity, evidence points to involvement of

both innate and adaptive immunity with a specific antibody response to mitochondrial

antigens67.

Although the prevalence of AMA in SLE was reported several decades ago59, this

observation was not pursued. Our study confirms the presence of AwMA (directed

against the mitochondrial surface and not redundant with that of PBC) and AmtDNA

(directed against mtDNA) in patients with SLE. However, it remains to be established

whether AwMA are pathogenic initiators of the auto-immune process or whether they

are consequences of an a priori cell activation or injury with subsequent release of

mitochondria in the extracellular milieu. These “free mitochondria” could

subsequently become antigenic in predisposed individuals and be a marker of cell

or tissue injury. They could also be a cause of further immune activation through the

formation of circulating or in-situ immune complexes, constituting a secondary

trigger of inflammation. The recognition of mitochondria by antibodies could also

implicate Fc receptors and thus modulate a distinct immune response. For example,

the intravenous injection of mtDNA into mice failed to induce proteinuria and kidney

damage68, but the response may differ in a recipient with circulating antibodies to

mitochondria.

Epitope modification, such as oxidation, can impact its antigenicity69. Notably, there

are reports suggesting that the oxidation of mtDNA occurs during its extrusion from

cells, and that the oxidized form is pathogenic15,16. Our findings using in vitro

oxidation of the mitochondria suggest that mitochondrial epitopes, regardless of

oxidation status, are targeted by autoantibodies in SLE. However, this does not

exclude the possibility that oxidized mitochondria may be more antigenic in other

pathogenesis, such as APS, or more efficient at promoting responses if recognized

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by the innate immune system. Moreover, it is not excluded that following oxidation,

mitochondrial swelling and potential formation of pores within the mitochondrial

membrane might have revealed new antigens detected in our anti-whole

mitochondria ELISA using TBHP-treated mitochondria, but this treatment may also

have caused a release of existing antigens that could have been lost in this modified

assay, thus explaining the apparent absence of impact of oxidation of the antigenicity

of the mitochondria70. Future investigations will be needed to determine the relative

targeting of native versus oxidized forms of organelle components by immune cells.

We could not verify the role of oxidation on the recognition of mtDNA by

autoantibodies due to spontaneous oxidation of isolated mtDNA, an observation also

made by other groups despite extreme preventive measures taken to maintain the

molecules under their reduced form71. Thus, it is likely that AmtDNA and anti-dsDNA

antibodies routinely measured in clinical testing both evaluate antibodies to oxidized

DNA.

We observed that AwMA levels were more elevated in SLE than in PBC. PBC

patients, however, were positive for AMA when sonicated mitochondria were utilized

in our ELISA. These observations are consistent with the fact that pyruvate

dehydrogenase complex E2 (PDC-E2), the immunodominant epitope in PBC, is

located in the mitochondrial inner membrane. Our AwMA-ELISA measures

antibodies to epitopes on intact mitochondria, in which inner membrane epitopes

remain unavailable72. This contrasts with the sonicated mitochondria used in

previous studies on AMA in SLE59, which contained inverted membranous structures

and thus revealed antigens located in the mitochondrial inner membrane60.

Furthermore, we found that AwMA levels correlated with the levels of AmtDNA, but

not with other antibodies directed at antigens located within the inner membrane of

the organelle (e.g. cardiolipin or HSP60), pointing to the existence of mitochondrial

antigens that remain to be identified73. Our study provides simple and quantitative

assays for assessment of two types of AMA (i.e. AwMA and AmtDNA) likely specific

to SLE. Further research is required to identify the mitochondrial antigen(s) and

epitope(s) of our AMA assay in SLE.

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Our analyses of AmtDNA antibodies in human sera showed an association with anti-

dsDNA as well as with lupus nephritis, consistent with the documented associations

between anti-dsDNA antibodies detected by Farr assay and lupus nephritis74. While

dsDNA used in Farr assays is usually isolated from plasmids (i.e. E. coli) and thus

may share similarities with mtDNA (e.g. hypomethylated CpG motives, circular

tertiary structure)75, the Farr assay has been described for its specificity in the

detection of high avidity antibodies of all classes (IgG and IgM, for instance). Our

data suggest that the Farr assay probably detects AmtDNA. Consistent with this,

nuclear DNA (nDNA) efficiently competed in our AmtDNA ELISA assay

(Supplementary Fig. 5a), further pointing to a certain degree of redundancy between

anti-dsDNA and AmtDNA. When nuclear and mtDNA were treated with S1 nuclease,

which digests potential single-stranded regions, both could compete in our AmtDNA

ELISA assay (Supplementary Fig. 5b), which suggests that most of the antigenicity

of mtDNA is provided by its double-stranded conformation. There might exist subsets

of antibodies that preferentially recognize mtDNA versus genomic DNA, but there is

no evidence of their occurrence at this stage. As extracellular mtDNA is reportedly

associated with various pathologies, including trauma25,26, burn injury27, cancer28

and rheumatoid arthritis17,29, it is tempting to postulate that extruded mtDNA, beyond

its role as a pro-inflammatory signal for the innate immune system, represents a

significant antigenic load available for the formation of immune complexes.

In this study, we focused our attention on immunoglobulin (Ig) G (IgG), but the

assays can be modified easily to quantify specific IgG subclasses (e.g. IgG1, IgG2a,

IgG2b) or other isotypes (e.g. IgA and IgM), which may reveal distinct functions of

these antibodies in disease. Both AwMA and AmtDNA were detected at low levels

in healthy individuals, suggesting that these antibodies are further induced during

SLE pathogenesis. These antibodies might be part of a pool of naturally occurring

autoantibodies that are thought to contribute to the continual clearance of membrane

vesicles in the circulation76,77. Protective natural autoantibodies have been described

predominantly as IgM, but other isotypes such as IgG or IgA have also been

reported78–80. It is thus tempting to postulate that antibodies targeting mitochondrial

epitopes are present in healthy individuals and might be involved in clearance of

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extracellular mitochondria. A profound change in the balance of natural IgM and

pathogenic IgG against mitochondrial epitopes may in part explain the pathogenesis

in SLE.

While these observations require confirmation in an independent cohort of patients,

they suggest that, in SLE, the adaptive immune system recognizes mitochondrial

organelles. Furthermore, our findings suggest that clinical associations may differ

according to antibody recognition of inner (e.g., ACA) versus outer mitochondrial

(e.g., AwMA) membrane components. This leads to the postulation that

pathogenicity of these antibodies may depend on whether extracellular mitochondria

are intact or not. Evaluation of antibodies to mitochondrial components in SLE may

provide novel information on patients, such as their risk for developing nephritis. If

these findings are confirmed in a large prospective cohort of SLE patients, AwMA

and AmtDNA may prove useful in predicting disease activity and disease severity,

and in stratifying SLE patients. The quantification of mitochondrial antibodies may

thus open the way to novel directions in autoimmune disease research and may be

useful for achieving a better understanding of disease mechanisms.

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Material and Methods

Study approval Patient population

The human sera tested in this study were obtained from a University Health Network

research ethics board (REB) approved study of SLE and APS patients in Toronto as

well as from healthy controls and PBC patients recruited from CHU de Québec –

Université Laval REB approved studies in Quebec City. SLE patients had to meet

the 1982 ACR classification criteria for SLE revised in 199781,82 and APS patients

met the 1999 Sapporo criteria for APS revised in 200683,84. For SLE, consecutive

female patients from the University of Toronto Lupus Clinic (UTLC) were approached

and provided consent between August 2010 and October 2011 to be part of a study

on the role of fatty acids and cardiovascular disease in lupus. They provided one

blood specimen and had their anonymized clinical data linked to their biospecimen.

Similarly, APS patients seen at the rheumatology clinic in Toronto were approached

following a similar procedure. All remaining biospecimen could be used for future

studies on biomarkers of lupus as per the original subjects’ consent. Healthy control

volunteers were recruited as part of study on markers of inflammation if they had no

known illnesses and did not have infectious symptoms at the time of the blood draw.

Age and sex were collected at that time. PBC patients met the 2009 PBC

classification criteria, revised in 201838,85 including the positivity for anti-

mitochondrial antibodies.

Data from clinical laboratories

For SLE patients, anti-dsDNA were measured using the Farr assay (laboratory cut-

off of 30%) and the anti-cardiolipin (IgG and IgM – laboratory cut-offs of 40 GPL or

MPL units) were measured by ELISA in a clinical laboratory.

Cell culture

Hep-G2 human hepatocarcinoma cells (ATCC, Manassas, VA, USA) were cultured

at 37 °C – 5% CO2 in Eagle’s Minimum Essential Medium (EMEM) (Wisent)

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supplemented with 10% fetal bovine serum (FBS) (Wisent), non-essential amino-

acids (Wisent) and penicillin/streptomycin (Wisent).

Inducible mouse model of SLE

Recommendations of the Canadian Council on Animal Care were followed in a

protocol approved by the Animal Welfare Committee at Université Laval. C57BL/6 J

were obtained from Jackson Laboratories (Bar Harbor, ME, USA) and housed in an

Elite-Plus specific-pathogen-free animal facility at CHU de Quebec. SLE

autoantibodies were induced in these mice as previously described63. In brief, 6–8-

week-old male mice received 100 µL i.v. injections of β2GPI (20 µg) (Crystal Chem,

Downers Grove, IL, USA) followed 24 h later by a 100 µL i.v. injection of

lipopolysaccharide (LPS from E. coli, O111:B4; 10 µg) (Sigma-Aldrich, Saint-Louis,

MO, USA). These injections were repeated after 2 and 4 weeks for a total of three

rounds of immunizations and mice were bled 48 h after the third immunization.

C57BL/6 J mice injected i.v. with PBS under the same schedule were used as

controls.

Ethics

Throughout the entire study, blood samples were obtained from patients under

informed consent. All the methods presented in this study were performed in

accordance with the relevant guidelines and regulations for both human and murine

donors.

Mitochondria isolation

Mitochondria were isolated from the livers of C57BL/6 J mice following a combination

of published protocols61,62. Mice were sacrificed by cervical dislocation, the liver was

swiftly removed, the gallbladder excised, and the liver was rinsed in ice-cold PBS

(137 mM NaCl, 3 mM KCl, 19 mM Na2HPO4, 2 mM KH2PO4). The liver was then

minced and transferred to a pre-cooled glass/Teflon tissue grinder containing 12 mL

of ice-cold mitochondrial isolation buffer (10 mM Tris, 1 mM EGTA, 200 mM sucrose)

per gram of liver then ground until an homogeneous suspension was obtained. Intact

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cells and nuclei were pelleted twice at 700 g, 4 °C, 10 min. Contaminating

membranes, proteins and organelles were eliminated by two centrifugations at

7,000 g, 4 °C, 10 min followed by a centrifugation at 10,000 g, 4 °C, 10 min. The

crude mitochondrial suspension was further purified by ultracentrifugation against a

Percoll gradient (10 mM Tris, 1 mM EGTA, 30% v:v Percoll) at 95,000 g, 4 °C, 30 min.

The band containing mitochondria was collected in PBS. A similar approach was

used to isolate human mitochondria with the exception that up to 107 Hep-G2 cells

were lysed by repeated passages through a narrow-gauge needle. The commercial

kit QIAgen Qproteome (QIAgen, Hilden, Germany) was also used, following the

manufacturer’s instructions, to isolate mitochondria from Hep-G2 cells for quality

comparison by western blotting with the aforementioned protocol. Isolated

mitochondria were dosed by the bicinchoninic acid (BCA) method using BCA Protein

Assay Kit (Thermo Fisher scientific, Waltham, MA, USA). Freshly isolated

mitochondria were used in all experiments with the exception of the submitochondrial

particles preparations for which pelleted mitochondria were kept at −80 °C until

needed.

Submitochondrial particles (SMP) preparation

SMP were prepared as described elsewhere60. Briefly, frozen mitochondria were

thawed at room temperature and diluted to 10 mg of mitochondrial proteins in 10 mM

4-Morpholinepropanesulfonic acid (MOPS). Samples were then sonicated using a

Fisher Sonic Dismembrator Model 500 (Thermo Scientific) at 20% maximal output

for 20 seconds then kept on a salt-ice water bath for 10 minutes. This cycle was

repeated nine times. Samples were then centrifuged at 16,000 g, 4 °C, 10 minutes in

order to discard unbroken mitochondria and other unwanted debris. Supernatants

were collected in a fresh tube and their volumes adjusted to 2 mL in 10 mM MOPS.

Samples were then ultracentrifuged at 150,000 g, 4 °C for 45 minutes. Pelleted SMP

were resuspended in SMP buffer (225 mM mannitol, 75 mM sucrose, 10 mM

HEPES, 0.1 mM EDTA, pH 7.4) and dosed. SMP preparations were kept at −80 °C

until needed.

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Red blood cells microparticles (RBCMP) preparation

Red blood cells (RBC) were isolated from the blood of healthy human volunteers by

centrifugation at 282 g for 10 minutes at RT. Platelet-rich plasma and buffy coat were

discarded, and the RBC fraction kept. RBC were counted (Cellometer Auto M10,

Nexcelom Bioscience, Lawrence, MA, USA) and adjusted to a concentration of

5 × 108 cells/mL in Tyrode’s buffer (12 mM NaHCO3, 127 mM NaCl, 5 mM KCl,

0.5 mM NaH2PO4, 1 mM MgCl2, 5 mM Glucose, 10 mM HEPES, pH 7.4). 109 cells

were then diluted in 45 mL double-distilled water and incubated for 5 minutes. The

tonicity of the buffer was then balanced by addition of 5 ml of PBS 10X (filtered

through a 0.22-μm membrane). Remnant RBC were removed by centrifugation at

1,300 g for 5 minutes at RT and supernatant was centrifugated at 18,000 g for

90 minutes at 18 °C. RBC microparticle pellet was then suspended in 500 μl PBS.

Protein concentration was measured with BCA assay.

Western blotting

After quantification, 25 µg of sample per lane were loaded onto a 12%

polyacrylamide gel and underwent migration for 1 h 30 min at 100 V (constant

voltage). Gels were then transferred overnight onto polyvinylidene difluoride

membranes (PVDF. BioRad, Hercules, CA, USA) at 4 °C and 60 mA (constant

current). Non-specific binding sites were blocked in Tris-buffered saline (TBS)−0.1%

Tween20 containing 5% non-fat dry milk for 4 h at room temperature. Proteins of

interest were labeled overnight at 4 °C with either mouse anti-actin (Clone AC-15,

1:5,000. Sigma-Aldrich), mouse anti-tubulin (Clone DM1A, 0.2 µg/mL. Abcam,

Cambridge, UK), mouse anti-proliferating cell nuclear antigen (PCNA. Clone PC10,

1 µg/mL. Santa Cruz biotechnology, Santa Cruz, CA, USA), rabbit anti-VDAC (Clone

D73D12, 1:1,000. Cell Signaling Technology, Danvers, MA, USA), mouse anti-

TOMM22 (Clone IC9-2, 2 µg/mL. Abcam) or mouse anti-cytochrome C antibody

(Clone 7H8.2C12, 0.5 µg/mL. BD Biosciences, Franklin Lakes, NJ, USA), polyclonal

rabbit anti-proteasome 20 S (0.8 µg/mL. Abcam), polyclonal rabbit anti-GRP94

(1:2,000, Abcam) diluted in superblock (BioRad). Following a 1-h incubation with

horseradish peroxidase-conjugated anti-mouse or anti-rabbit antibody (1:10,000 in

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superblock) (Jackson Immunoresearch, West Grove, USA), signals were visualized

with Western Lightning Chemiluminescence Reagent (Perkin Elmer, Waltham, MA,

USA) on a C-DiGit membrane scanner (LI-COR biotechnology, Lincoln, NE, USA).

Total proteins isolated from starting materials (i.e. mouse liver or Hep-G2 cells) were

used as controls. Full-length blots are presented in Supplementary Fig. 6a–c.

Mitochondrial size measurement by dynamic light scattering (DLS)

The size of the isolated mitochondria was measured by DLS, using a Zetasizer Nano

ZS device (Malvern instruments, Malvern, UK) equipped with the standard 4 mW,

633 nm He-Ne laser as a light source, set at a detection angle of 173°. Experiments

were replicated three times in 1 cm length disposable UV-Cuvettes (Brand GMBH,

Wertheim, Germany) containing 100 µL of isolated murine mitochondria diluted in

PBS at a concentration of 10 µg proteins/µL. The following parameters were taken

into account upon measuring the size of the mitochondrial: refraction index of the

solvent: 1.330, viscosity of the sample: 0.8872 mPas, refraction index of the proteins:

1.45, temperature: 25 °C.

Electron microscopy

Mitochondria (108) were fixed in 3.5% acrolein for 15 min at room temperature. Fixed

samples were rinsed twice in PBS then embedded in 4% agarose. 50 µm sections

were cut using a vibratome, post-fixed in 1% osmium tetroxide for 30 minutes and

embedded in Durcupan resin. Seventy-nanometer ultrathin sections were visualized

at 80 kV using a Tecnai G2 Spirit BioTWIN (FEI, Hillsboro, OR, USA) transmission

electron microscope.

Assessment of the mitochondrial oxygen consumption

Mitochondria were resuspended in mitochondrial assay solution (MAS: 70 mM

sucrose, 220 mM mannitol, 10 mM KH2PO4, 5 mM MgCl2, 2 mM HEPES, 1 mM

EGTA and 0.2%(w/v) fatty acid-free BSA, pH 7.4 at 37 °C) and supplemented with

10 mM pyruvate, 2 mM malate and 4 μM FCCP [carbonyl cyanide 4-

(trifluoromethoxy)phenylhydrazone], pH 7.4. An equivalent of 10 μg proteins was

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seeded on XF-96 plates (Agilent, Santa Clara, CA, USA). Plates were then

centrifuged 2,000 g for 20 min at 4 °C. We visualized the distribution of mitochondria

under a bright-field microscope to ensure adherence and homogeneous repartition.

Plates were maintained at 37 °C without CO2 for approximately 40 minutes prior to

loading. Oxygen consumption rates (OCR) were measured in accordance with

manufacturer instructions (Agilent/Seahorse Bioscience). Experiments were

replicated in three wells and averaged for each experimental condition. A total of 3

measurements of oxygen consumption for each condition were made approximately

every 6 minutes under basal conditions and after sequential addition of rotenone

(2 μM), succinate (10 mM), antimycin A (40 μM) and TMPD (N,N,N′,N′-tetramethyl-

p-phenylenediamine)/Ascorbate (100 μM/10 mM). Succinate was used as the

electron donor for complex II, rotenone as a complex I inhibitor, antimycin A as a

complex III inhibitor and respiration through complex IV was measured using

TMPD/ascorbate.

High sensitivity flow cytometry

Due to their small size, mitochondria were detected by high sensitivity flow

cytometry, using a “small particle option” consisting of a forward scatter (FSC)

coupled to a photomultiplier tube (PMT) mounted on a BD FACS Canto II Special

Order Research Product (SORP, BD Biosciences). Mitochondria (0.5 µg) were

stained with 1 µg of anti-TOMM22-Atto 488 (clone IC9-2, Sigma-Aldrich) and 1 µM

of mitotracker deep red (Invitrogen, Carlsbad, CA, USA) for 30 minutes at 37 °C and

diluted with PBS to a final volume of 500 µl before flow cytometry analysis. To

quantitatively measure the number of mitochondria, we used 3 µm diameter

polystyrene microsphere (Polysciences, PA, USA). 80,000 microspheres were

added to each sample and 500 microspheres were acquired. Silica particles (Kisker

Biotech, Steinfurt, Germany) were used to determine 100–1,000 nm size scale.

Mitochondrial DNA extraction by alkaline lysis

Isolated mitochondria were pelleted at 10,000 g, 4 °C, 10 min and resuspended in

0.8 mL mtDNA isolation buffer A [50 mM Tris-HCl, 10 mM EDTA, 100 µg/mL RNAse

351

A (QIAgen), pH 7.5] for every 3 mg of mitochondrial proteins. Mitochondria were then

lyzed in one volume (v:v) mtDNA isolation buffer B (extemporaneously-prepared.

0.2 M NaOH, 1% SDS) for 3 min. on ice, under gentle agitation. mtDNA suspensions

were neutralized with one volume (v:v) mtDNA isolation buffer C (1.32 M potassium

acetate, pH 4.8 adjusted with ice-cold acetic acid) for 5 min. on ice, under gentle

agitation. Mitochondrial debris were pelleted by centrifugation for 10 minutes at

14,000 g, RT. Supernatants were transferred to fresh tubes. mtDNA was precipitated

overnight at −20 °C with 0.1 volume (v:v) potassium acetate (stock solution: 3 M

sodium acetate, pH adjusted to 5.2 with ice-cold acetic acid) and 0.7 volume (v:v)

absolute isopropanol. mtDNA was then pelleted at 14,000 g, washed thrice with

1.5 mL 70% ethanol and resuspended in DNA resuspension buffer (10 mM Tris-HCl,

10 mM EDTA, pH 8.0). Mitochondrial DNA concentration was determined by

spectrophotometry (Nanodrop 1000, Thermo Fisher Scientific).

Nuclei isolation from mouse hepatocytes

Nuclei were isolated from mouse livers using published methods86. Briefly, during

mitochondria isolation protocols, while supernatants were used for performing

mitochondria isolations, pellets from the first 700 g centrifugation were resuspended

in 10 mL of ice-cold nuclei isolation buffer A (5 mM MgCl2, 10 mM Tris–HCl, 250 mM

Sucrose. pH 7.4) and ground in a pre-cooled glass/Teflon tissue grinder. The

suspension was further disrupted by three passages through a 25 G5/8 gauge needle

followed by two passages through a 27 G ½ gauge needle. The suspension was

then filtered against a 40 µM nylon cell strainer (Thermo Fisher Scientific) and

centrifuged at 600 g, 4 °C, 10 min. Pellets were resuspended in 14 mL buffer A and

centrifuged at 600 g, 4 °C, 10 min. Pellets were then resuspended in 9 volumes of

ice-cold nuclei isolation buffer B (1 mM MgCl2, 10 mM Tris– HCl, 2.0 M sucrose. pH

7.4) and centrifuged at 16,000 g, 4 °C, 30 min. Pellets were resuspended in 200 µL

PBS and stored at −20 °C.

352

Whole-cell and nuclear DNA isolation

DNA from either 25 mg of whole mouse liver or the 200 µL or isolated nuclei were

extracted using QIAmp® DNA Mini Kit (QIAgen), following instructions from the

manufacturer. Samples were eluted in DNA resuspension buffer.

Mitochondrial DNA and nuclear DNA enrichments by qPCR

Thirty nanograms of mitochondrial DNA, nuclear DNA or the same amount of total

DNA extracted from whole mouse liver using the aforementioned protocols, were

amplified in a Rotor-Gene Q real time qPCR cycler (QIAgen) according to standard

protocols with SsoAdvanced Universal SYBR® Green Supermix (BioRad) in a 10 µL

reaction volume. Two distinct primer couples were used: one specific to

mitochondrial DNA (5′-GGAACAACCCTAGTCGAATGAA-3′/5′-

GCTAGGGCCGCGATAATAAA-3′) and the other to nuclear DNA (5′-

CCTGCTGCTTATCGTGGCTG-3′/5′-GCCAGGAGAATGAGGTGGTC-3′). The

experimental conditions were: 50 °C - 2 minutes in, 95 °C - 10 min and 40 cycles

(95 °C - 15 seconds, 60 °C - 1 minutes). Fold changes were calculated with the 2−ΔCt

method setting mean value for total liver DNA extracts as 1.

Mitochondrial DNA digestion by restriction enzymes

Purified mouse mtDNA was digested by Hae II or Pst I restriction endonucleases

(NEB, Whitby, ON, Canada) according to the manufacturer’s protocol. Digested

products (1.5 μg) were then resolved on a 0.5% (w/v) agarose gel. Images were

acquired on a Chemidoc MP gel documentation system (Bio-Rad). Full-length gel is

presented in Supplementary Fig. 6d.

S1 nuclease treatment of mitochondrial DNA and nuclear DNA

30 µg of mtDNA and nDNA were diluted in 200 µL of 1X S1-buffer and treated with

50 U S1 nuclease (Thermo Fischer Scientific) for 5 minutes at 37 °C. Reaction was

stopped by addition of 600 mM EDTA (final concentration) and incubation at 70 °C

for 10 minutes. Samples were precipitated by addition of 300 mM Sodium Acetate

(final concentration) and 2 volumes (v:v) absolute ethanol for 16 hours at −20 °C.

353

Samples were pelleted at 14,000 g, RT, 20 minutes, and washed 1 mL 70% ethanol

and resuspended in DNA resuspension buffer. For competition assays, untreated

nDNA and mtDNA followed the same treatment without addition of the enzyme.

Samples were dosed by qPCR.

Mitochondria oxidation in-vitro

Dosed mitochondria were pelleted and resuspended at a concentration of 1.5 mg of

mitochondrial proteins/mL in PBS containing 500 µM of the oxidant tertbutyl

hydroperoxide (TBHP) (Sigma-Aldrich). Mitochondria were oxidized for 1 h 30 min at

37 °C under gentle agitation then rinsed twice with ice-cold PBS. Oxidized

mitochondria were subsequently quantified by BCA.

Mitochondrial lipid oxidation

Thiobarbituric acid reactive substances (TBARS) formation was assessed, using the

TBARS Parameter Kit (R&D systems, Minneapolis, MN, USA), following the

manufacturer’s instructions. Two hundred micrograms of mitochondria were lysed,

the proteins were precipitated using trichloroacetic acid (TCA) and pelleted at

12,000 g, room temperature, 4 min. The supernatants were transferred to fresh

tubes. Samples (75 µL) were incubated with 37.5 µL of thiobarbituric acid in a 96-

well plate for 3 h at 50 °C. Absorbances were read at 532 nm on a SpectraMax 190

microplate reader (Molecular Devices, Sunnyvale, CA, USA) and TBARS

quantification was performed using a standard curve provided in the kit. Oxidized

samples were compared to control mitochondria that were incubated under the same

conditions in PBS devoid of TBHP.

Mitochondrial protein oxidation

The formation of carbonyl moieties following in-vitro mitochondrial oxidation was

measured using the Protein Carbonyl Content Assay Kit (Sigma Aldrich) following

the manufacturer’s instructions. Oxidized samples were compared to control

mitochondria that were incubated under the same conditions in PBS devoid of TBHP.

354

Detection of antibodies targeting mitochondrial epitopes by ELISA

For the detection of anti-whole mitochondrial antibodies (AwMA), murine

mitochondria were diluted (500 µg/mL) in 50 mM carbonate/bicarbonate buffer, pH

9.6 and 25 µL per well were loaded onto 96-well half-area clear flat bottom

polystyrene high-binding microplates (Corning, New York, USA). Plates were coated

for 18 h at 4 °C then blocked for 4 h at 37 °C with PBS containing 10% FBS and 0.5%

gelatin. After three washes with PBS, sera diluted 1:150 (unless otherwise specified)

in PBS-10% FBS-0.3% gelatin were incubated overnight at 4 °C in duplicate. After

three washes with PBS, plates were incubated for 1 h at room temperature with

alkaline phosphatase-(AP) conjugated goat anti-mouse or anti-human IgG (Sigma-

Aldrich) diluted 1:1,000 in PBS-0.4% bovine serum albumin (BSA). Plates were

washed thrice with PBS and developed with p-nitrophenol phosphate (p-NPP) for

~30 min at 37 °C and optical densities (OD) were read at 405 nm on a microplate

reader. The same protocol was used for the detection of autoantibodies targeting

submitochondrial particles by using 25 µL per well of SMP diluted (50 µg/mL) in

50 mM carbonate/bicarbonate buffer, pH 9.6. A similar approach was used for

human mitochondria with the following modification: plates were incubated with a

horseradish peroxidase-conjugated anti-human IgG secondary antibody (1:3,000),

peroxidase activity was revealed at room temperature for ~5 min with 3,3′,5,5′-

tetramethylbenzidine (TMB). The reaction was stopped with 2 N H2SO4 and the ODs

read at 450 nm. For the anti-mtDNA ELISA, plates were pre-coated with 1%

protamine sulfate in double-distilled water for 1 h at room temperature. Plates were

washed three times with PBS and coated overnight at 4 °C with 400 ng mtDNA in

PBS. All subsequent steps were identical to those used for AwMA-ELISAs. Blank

values (mitochondrial antigens and no sera) were substracted from measured values

for each patient. During the development of these assays, the proper coating of the

wells was tested by using isotype-matched mouse monoclonal antibodies (mAb). A

monoclonal antibody (Clone IV.3, 4 µg/mL) was used as a negative assay control in

each instance while different monoclonal antibodies were used, depending on the

coating antigens, as positive assay controls: an anti-TOMM22 mAb (Clone IC9-2,

4 µg/mL. Abcam) for intact mitochondria, an anti-DNA mAb (Clone 35I9 DNA,

355

10 µg/mL. Abcam) or an anti-Cytochrome C mAb (Clone 7H8.2C12, 5 µg/mL. BD

Biosciences).

Competition assay

AwMA-ELISAs were performed as described in the previous sections with the

following modifications: serum samples were pre-incubated in dilution buffer (1:150)

spiked with various concentrations (0.25, 1 and 3 mg/mL) of competitors (i.e.

mitochondria or red blood cells microparticles) for 3 hrs. at RT and incubated in

duplicate overnight at 4 °C. Data are presented as the percentage of signal

remaining after each competition, compared to the OD (405 nm) measured in

absence of competitors.

A similar procedure was used for AmtDNA-ELISA, using increased concentrations

(0, 3, 9 and 27 ng/µL) of competing DNA (extracted from nuclei or mitochondria, with

or without S1 nuclease treatment).

Statistics

Comparisons between groups were made using either Student’s t-test, Wilcoxon

test, Friedman or Kruskal-Wallis tests, one-way ANOVA, two-way or repeated

measures ANOVA depending on the outcome, as well as the number and type of

groups. When multiple comparisons were assessed, appropriate post-hoc correction

tests were used such as Dunn’s, Dunnett’s, Sidak’s or Bonferroni’s. Associations

between AwMA, AmtDNA and anti-HSP60 were computed with Spearman

correlations. Distribution of these antibodies according to ACA results were

compared using Wilcoxon test. Associations between AwMA or AmtDNA and clinical

outcomes were studied by bivariate and multivariate linear and logistic regressions.

Clinical outcomes studied are average intima media thickness, percent change of

the flow mediated dilatation (FMD) of the brachial artery, presence of FMD, presence

of plaque in the carotid, thrombotic event ever, white blood cells count, platelet count,

increased DNA binding by Farr assay above normal range for testing laboratory,

presence of damage according to SLICC Damage Index (SDI > 0), high activity

according to SLEDAI-2K activity score (SLEDAI ≥ 4), presence of lupus nephritis,

356

biopsy class, as well as chronicity and activity index from the biopsy. The latter were

adjusted for disease duration, age, body mass index (BMI), low-density lipoproteins

(LDL) cholesterol, antimalarial medication and prednisone. Logistic regressions are

presented with odd ratios and their 95% Wald confidence interval. Participants’

results were considered positive for AwMA and AmtDNA when their value was above

the cut-off value identified after maximizing Youden’s Index. A 95% confidence

interval was obtained for the cut-off using 10,000 bootstrap samples. Performance

measures are presented with their 95% exact confidence interval.

Software

Western blot images were acquired using Image Studio Digits 5.2 (LI-COR

biotechnology). mtDNA migration through agarose gel was imaged using Image Lab

6.0.1 (Bio-Rad). DLS studies were carried using the built-in Zetasizer 7.10 software

(Malvern Instruments). EM images were acquired with the Image Capture Software

601.384 (Advanced Microscopy Techniques Corp., Woburn, MA, USA). Flow

cytometry was performed using the BD FACSDiva™ 6.1.3 (BD Biosciences). Yields

from DNA isolations were quantified using the ND-1000 3.8.1 software (Thermo

Fisher Scientific) and qPCR were performed with RotorGene 6.1 (Corbett

Research/QIAgen). Optical densities were measured using SoftMax Pro 5.4.1

(Molecular Devices). Figures were assembled with ImageJ 1.47 (National Institutes

of Health, Rockville, MA, USA) and Photoshop CS6 13.0 (Adobe Systems Inc.,

Mountain View, CA, USA). Statistical analyses were carried with Prism 7 software

(GraphPad Software Inc., La Jolla, CA, USA) and SAS version 9.4 (SAS Institute

Inc., Cary, NC, USA).

357

Acknowledgements

This work was supported in part by an operating grant from The Arthritis Society (#

225638) (to PRF) and by a Canadian Institutes of Health Research (CIHR)

Foundation grant (EB). The authors have no competing interests. EB is recipient of

a new investigator award from the CIHR and is a Canadian National Transplant

Research Program (CNTRP) researcher. PRF is recipient of a tier 1 Canada

Research Chair on Systemic Autoimmune Rheumatic Diseases. GM is a recipient of

awards from the Canadian Blood Services. IM is recipient of a fellowship from the

Arthritis Society. CB is recipient of an award from the Fonds de Recherche en Santé

du Quebec. JR is the recipient of funding from the Division of Rheumatology and the

Department of Medicine (McGill University), and a CIHR Project Grant (PJT-

159652). The authors acknowledge Rebecca Subang for technical assistance in

preparing human healthy control samples. MET is grateful to the help of Julie-

Christine Lévesque and Nathalie Vernoux with TEM experiments. The views

expressed herein do not necessarily represent the view of the federal government.

358

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