Identification and Characterization of Moesin-, PIP2-Mediated Solid Particle Phagocytosis

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2018-08-09 Identification and Characterization of Moesin-, PIP2-mediated Solid Particle Phagocytosis

Tu, Zhongyuan

Tu. Z. (2018). Identification and Characterization of Moesin-, PIP2-mediated Solid Particle Phagocytosis (Unpublished doctoral thesis). University of Calgary, Calgary, AB. doi:10.11575/PRISM/32804 http://hdl.handle.net/1880/107622 doctoral thesis

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Identification and Characterization of Moesin-, PIP2-mediated Solid Particle Phagocytosis

Zhongyuan Tu

A THESIS

SUBMITTED TO THE FACULTY OF GRADUATE STUDIES

IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE

DEGREE OF DOCTOR OF PHILOSOPHY

GRADUATE PROGRAM IN MICROBIOLOGY AND INFECTIOUS DISEASES

CALGARY, ALBERTA

AUGUST, 2018

Phagocytosis is the defining feature of professional phagocytes of the innate immune system. This function is typically carried out by phagocytic receptors on the cell surface. These receptors can mediate binding and engulfment of solid particles. However, these phagocytic receptors have evolved very recently in history comparing to phagocytosis as a conserved cellular function. This suggests a primordial form of phagocytosis might exist. Years ago, our laboratory uncovered an expected phagocytic mechanism that solid particle can bind to membrane lipids on phagocytes to trigger lipid sorting. Consequently, this can lead to phagocytosis akin to FcγR-based phagocytosis regarding its dependence on Immunoreceptor

Tyrosine-based Activation Motif (ITAM), Src-family kinases, Syk, and phosphoinositide 3- kinase (PI3K).

Based on these findings, we proposed a hypothetical mechanism for solid particle phagocytosis termed “Signaling Equivalent Platform” (SEP). In short, membrane engagement with solid structures, either via ligand/receptor binding or merely being stabilized by an approaching solid surface will lead to a shared downstream pathway with the same dependence on ITAM and Syk. Both modes of phagocytosis are equivalent for its activation by solid structures. However, the identity of the ITAM-containing molecule and the exact involvement of lipid during solid particle phagocytosis under SEP is still unclear.

This thesis serves to strengthen the idea of SEP by identifying the ITAM-containing molecule and further characterizing the involvement of the ITAM-containing molecule and lipids during solid particle phagocytosis.

We used a generic ITAM sequence as a probe and identified moesin as the ITAM- containing molecule from the mouse genome. We further demonstrated that a solid structure

ii binding to the cell surface leads to autonomous accumulation of phosphatidylinositol 4, 5- bisphosphate (PIP2) to the site of contact, which attracts moesin, a conserved structural linker, to the plasma membrane. Moreover, Moesin, via its ITAM, is sufficient to activate phagocytic programming including Syk and downstream signaling that is virtually identical to that initiated by Fcγ receptors.

Bioinformatic analysis suggested that this moesin-mediated signaling predates modern

Fcγ and immune receptors. This thesis, therefore, reveals an evolutionarily conserved moesin-,

PIP2-mediated signaling platform for the evolutionarily conserved phagocytosis that provides essential components for modern ITAM-based signaling cascades.

iii Preface

This thesis is original, unpublished, independent work by the author, Zhongyuan Tu. The author would like to take this opportunity to lay out how this thesis is written.

Chapter 1 provides the background for the entire thesis. It is structured in a funnel shape such that the broadest topic is introduced first. The topics discussed will progressively get narrower and eventually the topic at issue is introduced and discussed at last. As the topics narrows, descriptions become more detailed. This technique was first introduced to me by Dr.

Mark McDermott, Professor Emeritus and a top-notch graduate educator at McMaster

University, and has been useful ever since.

Chapter 2 concerns the material and methods used in this thesis. I structured the methods sections according to their purpose. Specific to this thesis, section 2.4.2 presents the topic of microscopy. This section can be read independent of other parts of the thesis and intends to serve as a practical guide on how to perform good microscopy for junior graduate students in need.

This part is written in consultation with Dr. Tie Xia.

Chapter 3 to 5 contains all results of this thesis. There are two major flows when writing these chapters. The vertical flow is the results section. In it, results are presented in logical order and conclusions are made. Results are from the interpretation of data. Therefore, prudence and appropriate caution should be exercised. The horizontal flow is the discussion section. It is like a replay of a football game in which each move are highlighted and analyzed. In it, vertically flowed results are horizontally discussed, and critically examined. Also, new topics are introduced if necessary to facilitate discussion. For example, in Section 4.3, membrane domains were introduced to provide context for results discussion. Also, in section 5.3, the idea of

“effective engagement” was put forward in an attempt to explain the results further. The

iv discussion points were identified from, but not limited to, the previous discussion with committee members, discussions among colleagues and comments from reviewers of the manuscript submitted. Critical thinking and the defense elements of a thesis should be reflected in these sections. The entire writing process on the discussion sections can be described as playing a chess game against the most critical version of oneself because one must contemplate all possibilities and weigh strengths and weakness of alternative scenarios all the time. In other words, one must think hard. It is both a taxing and intellectually stimulating experience. Of special note, it is my personal view that weakness of results should be acknowledged upfront instead of looking the other way in the hope of forcing specific narratives, especially with thesis writing. The truth may be uncomfortable, inconvenient, but it shall set you free. The Chief

Justice of the Supreme Court of United States, John G Roberts Jr, stated on multiple occasions that the Court appreciates when an attorney acknowledges the weak points of their argument because the Court understands the topics brought before the Supreme Court are hard, and there are merits for each side of the argument. This is true for law, and this is true for science. Because the questions investigated in a Ph.D. thesis usually involves many unknowns and are limited by current techniques, it is helpful to exercise candor and then discuss possibilities and solutions.

Chapter 6 is the final chapter serving as the grand finale of the thesis. Results are summarized, and a model is proposed. This model is further examined in the Future Directions section for possible ways to improve this model. For example, in Section 6.2, how phagocytic signaling occurs is discussed fundamentally, and previously discussed concepts of membrane domain, “effective engagement”, checks and balances between ITAM and ITIM are fitted into this grand discussion to help better understand our work and to improve the model in the future.

In a way, this chapter can serve as a prequel to a future thesis.

v Acknowledgements

The official completion of this thesis will mark the end of the early part of my life as a scientist. Looking back, this is a long and winding road with success and much more failures as the natural progression in science. I am privileged to meet and sometimes travel alongside some of the kindest, wittiest human beings I know on this road. This section of the thesis serves to express my deepest gratitude towards these people.

First and foremost, I thank my supervisor Dr. Yan Shi for giving me such a unique opportunity to develop my graduate research and to mature as a human being. It is my firm belief that the critical thinking and interpersonal skills I have developed during my graduate studies will benefit me for the rest of my life.

Next, I thank my committee members Drs Robin Yates and Matthias Amrein for carefully guiding me through my graduate studies. It is evident to me that I gained experience points and leveled up every time coming out of a committee meeting or a candidacy exam. I believe any student is fortunate to have you as their supervisors.

I would also like to thank Dr. Tie Xia for being a personal friend and my go-to guy for imaging-related problems. Being nice is sometimes a very overrated and murky virtue as it can be misjudged. However, I would still want to make it to the record that Tie Xia is a genuinely nice person. One can always count on him for personal advice, imaging expertise, and recommendation for vegan restaurants.

The newly-minted Dr. Libing Mu is critical for developing and finishing this thesis. The fact that we have gone through this together means everything. Therefore, nothing more can be said.

vi I would also like to acknowledge Jiahua Chen, Hua Rong, Yifei Zhang, Xiaoting Wang for their companionship while they are in Canada. I enjoyed every meal they shared with me and every conversion we had.

I would like to thank the administrative staffs. Those include our lab manager Melanie

Stenner and administrative assistant Florence Yang. They made my life as a graduate student much easier by doing their job exceptionally well.

I would also like to acknowledge all the other lab members at Tsinghua University.

I would like to thank Ning Kang for her quick wit. The street smarts she exhibits always amazes me.

I would like to thank Hong Zhang for being another Mel in Tsinghua.

Special thanks also go to Dingka Song, Dan Tong, Junchen Meng, Rui Yan, Yunzhou

Fan, Xiaojie Ma, Jianjian Li, Fei Shu and Hefei Ruan. Together they maintained a very enjoyable atmosphere.

Because I am fortunate enough to be surrounded by all these wonderful people for the past years of my life, even an eternal pessimist like me has come to believe that there is still light at the end of the tunnel. I just have to follow through and walk through that door when the time arrives.

vii Dedication

This thesis is dedicated to my beloved Emma, a courageous ALS fighter.

viii

Table of Contents

Abstract ...... ii Preface...... iv Acknowledgements ...... vi Dedication ...... viii Table of Contents ...... ix List of Tables ...... xiii List of Figures and Videos ...... xiv List of Symbols, Abbreviations and Nomenclature ...... xviii Epigraph ...... xxii

CHAPTER ONE: INTRODUCTION ...... 1 1.1 Innate Immunity ...... 1 1.2 Phagocytes ...... 1 1.2.1 Macrophages ...... 2 1.2.2 Dendritic Cells ...... 4 1.3 Immune Receptors on Phagocytes ...... 5 1.3.1 Phagocytic Receptors ...... 7 1.3.1.1 Opsonic Receptors ...... 7 1.3.1.2 Non-opsonic Receptors ...... 14 1.3.2 Toll-like Receptors ...... 18 1.3.2.1 Structure, Location, and Specificities of TLRs ...... 18 1.3.2.2 TLR Signaling ...... 21 1.3.3 Other Receptors and Intracellular Sensors ...... 23 1.4 Phagocytosis ...... 23 1.4.1 Overview ...... 23 1.4.2 FcγR -mediated Phagocytosis ...... 25 1.4.2.1 Src Family Kinase ...... 25 1.4.2.2 Syk ...... 26 1.4.2.3 Small GTPases ...... 27 1.4.2.4 Phosphoinositides and Related Enzymes ...... 29 1.4.2.5 Actin Cytoskeleton ...... 32 1.4.2.6 Summary of FcγR-mediated Phagocytosis ...... 33 1.4.3 CR3-mediated Phagocytosis ...... 35 1.4.3.1 Inside-out Signaling for CR3 ...... 35 1.4.3.2 Outside-in Signaling for CR3 ...... 36 1.4.3.3 Rho GTPase Activation During CR3-mediated Phagocytosis ...... 36 1.4.3.4 Summary of CR3-mediated Phagocytosis ...... 37 1.4.4 Phagocytosis of Non-Biological Particles ...... 39 1.4.4.1 Silica Crystals ...... 39 1.4.4.2 Cholesterol Crystals ...... 40 1.4.4.3 MSU Crystals ...... 41 1.4.4.4 Alum Crystals ...... 42 1.4.4.5 Contribution to the Understanding of Solid Particle Phagocytosis by Our Laboratory ...... 44 ix 1.4.5 Signal Integration during Phagocytosis ...... 47 1.4.5.1 Cooperation between FcγR and CR3 Signals ...... 47 1.4.5.2 Counteractions between ITAM-based Activating Signals and ITIM-based Inhibitory Signals ...... 48 1.5 Aims of this Study ...... 51 1.5.1 Overarching Hypothesis ...... 51 1.5.2 Specific Aims ...... 51 1.5.2.1 What is the ITAM-containing molecule required for solid particle phagocytosis? ...... 51 1.5.2.2 What is the lipid species sorted at the site of contact during solid particle phagocytosis? ...... 52 1.5.2.3 What are the requirements and characteristics of solid particle phagocytosis? Is it evolutionarily conserved? ...... 52

CHAPTER TWO: MATERIAL AND METHODS ...... 54 2.1 Reagents ...... 54 2.1.1 Antibodies ...... 54 2.1.1.1 Primary Antibodies ...... 54 2.1.1.2 Secondary Antibodies ...... 54 2.1.2 Inhibitors ...... 55 2.1.3 Plasmids ...... 55 2.1.4 Transfection and Transduction Reagents ...... 55 2.1.5 Fluorescent Labels ...... 56 2.1.5.1 Fluorescently-labeled Lipids ...... 56 2.1.5.2 Other Labels ...... 56 2.1.6 Miscellaneous ...... 56 2.2 Cell Culture ...... 57 2.2.1 Cells ...... 57 2.2.2 Culture Conditions ...... 58 2.2.3 Transfection and Transduction ...... 58 2.2.3.1 Transient Transfection for Overexpression ...... 58 2.2.3.2 Stable Transfection for Overexpression ...... 59 2.2.3.3 Transient Transfection of siRNA to Knockdown Gene Expression ...... 59 2.2.3.4 Stable Transduction of shRNA to Knock Down Gene Expression ...... 61 2.3 Molecular Biology ...... 61 2.3.1 Real-time PCR ...... 61 2.3.2 Western Blotting ...... 62 2.3.3 Co-immunoprecipitation ...... 63 2.4 Fluorescence Microscopy ...... 63 2.4.1 Immunofluorescence ...... 63 2.4.2 Microscopy ...... 64 2.4.2.1 General Considerations for Performing Good Microscopy ...... 64 2.4.2.2 Summary ...... 75 2.4.3 Different Microscopy Modalities used for this Thesis ...... 76 2.4.3.1 Widefield Microscopy ...... 76 2.4.3.2 Confocal Microscopy ...... 76 2.4.3.3 Structured Illumination Microscopy ...... 77 x 2.4.4 Image Processing and Analysis ...... 78 2.4.4.1 Deconvolution and PSF ...... 78 2.4.4.2 Other Image Processing Methods ...... 79 2.5 Phagocytosis ...... 80 2.5.1 Preparation of Solid Particles ...... 80 2.5.1.1 Surface Coating of Proteins to Polystyrene Beads ...... 80 2.5.1.2 Making Uniform Polystyrene Beads with Tunable Rigidity ...... 80 2.5.2 Phagocytosis Assay ...... 82 2.6 Contact-related Assays ...... 83 2.6.1 Lipid Sorting Analysis on Live Cells with Beads ...... 83 2.6.2 Lipid Sorting Analysis on GPMVs with PDMS Micropatterns ...... 84 2.6.2.1 Micropatterns Design ...... 84 2.6.2.2 Fabrication and Preparation of PDMS Patterns ...... 87 2.6.2.3 Generation, Modification, and Labeling of GPMVs ...... 89 2.6.3 Lipid Sorting Analysis on Live Cells with PDMS Micropatterns ...... 89 2.6.3.1 Generalized Polarization ...... 89 2.7 In Silico Analysis ...... 90 2.7.1 ITAM Screening ...... 90 2.7.2 Phylogenetic Analysis ...... 90 2.8 Statistical Analysis ...... 91

CHAPTER THREE: THE ROLE OF MOESIN IN SOLID PARTICLE PHAGOCYTOSIS ...... 93 3.1 Introduction and Aim ...... 93 3.1.1 Introduction ...... 93 3.1.2 Aim ...... 93 3.2 Results ...... 94 3.2.1 Moesin is the ITAM-containing Molecule for Solid Particle Phagocytosis ....94 3.2.2 FERM Domain of Moesin is Sufficient to Induce Solid Particle-Triggered Signaling ...... 108 3.3 Discussion ...... 116

CHAPTER FOUR: THE ROLE OF PIP2 IN SOLID PARTICLE PHAGOCYTOSIS ..122 4.1 Introduction and Aim ...... 122 4.1.1 Introduction ...... 122 4.1.2 Aim ...... 125 4.2 Results ...... 125 4.2.1 PIP2 Sorting is Required for Solid Particle Phagocytosis ...... 125 4.2.2 PIP2 Sorting by Solid Structures is Autonomous ...... 136 4.2.2.1 Possible Triggers for PIP2 Sorting ...... 143 4.3 Discussion ...... 148

CHAPTER FIVE: CHARACTERIZATION OF MOESIN-, PIP2 -MEDIATED SOLID PARTICLE PHAGOCYTOSIS AND ITS PLACE IN EVOLUTION ...... 158 5.1 Introduction and Aim ...... 158 5.1.1 Introduction ...... 158 5.1.2 Aim ...... 160

xi 5.2 Results ...... 160 5.2.1 Sufficient Level of Particle/Surface Binding and ITAM Availability are Prerequisites for Successful Phagocytosis ...... 160 5.2.2 Comparison of Moesin-, PIP2-mediated Phagocytosis with FcγR-mediated Phagocytosis ...... 166 5.2.3 Moesin Contributes to Scavenger Receptor-mediated phagocytosis ...... 172 5.2.4 Moesin-, PIP2-mediated Phagocytosis is Evolutionarily Conserved ...... 173 5.3 Discussion ...... 177

CHAPTER SIX: SUMMARY AND FUTURE DIRECTIONS ...... 189 6.1 Summary ...... 189 6.2 Future Directions ...... 192 6.2.1 Spatiotemporal Regulation of Phagocytic Signaling ...... 192 6.2.2 Refinements for Moesin-, PIP2-mediated Solid Particle Phagocytosis ...... 196 6.2.3 Significance and Applications ...... 203

REFERENCES ...... 205

ITAM-CONTAINING PROTEINS IN PHAGOCYTOSIS ...... 229

INDUCTION OF PHAGOCYTOSIS BY CHIMERIC PHAGOCYTIC RECEPTORS ...... 234

PHYLOGENIC TREES OF KEY PHAGOCYTIC MOLECULES ...... 236

COPYRIGHT PERMISSION ...... 240 D.1. Permission for Figures 1.1, 1.4 and 1.5 from Elsevier Limited ...... 240 D.2. Permission for Figure 1.2 from Springer Nature ...... 243 D.3. Permission for Figure 1.3 from Cambridge University Press ...... 246 D.4. Permission for Figures 1.6, 1.7, 1.10 and 4.1 from Annual Reviews ...... 248 D.5. Permission for Figures 1.8 and 1.9 under Creative Commons Attribution License (CC BY) ...... 253 D.5.1. Frontiers Open Access ...... 253 D.5.2. SpringerOpen ...... 254

xii List of Tables

Table 2.1 SiRNA Sequences for Transient Gene Knockdown ...... 60

Table 2.2 Primers for RT-PCR ...... 62

Table 2.3 Basic Parameters Defining the Size, Spacing, and Alignment of Designed Micropatterns...... 87

Table 3.1 Top 25 Hits of Highly Expressed ITAM-containing Proteins in Mouse Genome...... 95

Table A.1 List of ITAM-containing Proteins Ranked by Expression Levels in Phagocytes ..... 229

xiii List of Figures and Videos

Figure 1.1 Structure and Functions of Different Types of Fcγ Receptors in Human ...... 8

Figure 1.2 Mechanism of ITAM Activation ...... 10

Figure 1.3 Domain Architecture of the different Classes of Scavenger Receptors ...... 16

Figure 1.4 Structure, Location, and Specificities of TLRs in Human...... 20

Figure 1.5 Signaling Pathways and Functions of TLRs ...... 22

Figure 1.6 Fcγ receptor-mediated Phagocytic Signaling...... 34

Figure 1.7 CR3-mediated Phagocytic Signaling ...... 38

Figure 1.8 The Recognition of Solid Particles on the Macrophage Surface...... 43

Figure 1.9 Signaling Equivalent Platform ...... 46

Figure 1.10 Immunoreceptor tyrosine-based inhibition motif (ITIM)-bearing FcγRIIB- mediated Inhibitory Signaling...... 49

Figure 2.1 Fluorescent Protein Properties...... 71

Figure 2.2 Schematic of Phagocytosis Assay ...... 83

Figure 2.3 Schematic of Fluorescence Imaging of Bead/Cell Contact ...... 84

Figure 2.4 Micropatterns Design with Basic Topological Structures, Sizes, Spacing, and Alignments...... 85

Figure 2.5 Schematic of PDMS Micropatterns Preparation ...... 88

Figure 3.1 Transient Knockdown Efficiency of Candidate ITAM-containing Genes in DC2.4 Cells...... 97

Figure 3.2 Phagocytosis Efficiency of DC2.4 Cells with Transient Knockdown of Candidate ITAM-containing Genes...... 98

Figure 3.3 Phagocytosis of Polystyrene Beads is Impaired in Stable Moesin Knockdown DC2.4 Cells...... 100

Figure 3.4 Schematic Drawing of Basic Structure of Moesin, Radixin, and Ezrin...... 102

Figure 3.5 Gene Expression Profile of ERM Family Proteins in Cell Lines and Tissues...... 102

Figure 3.6 Phagocytosis Efficiency of Polystyrene Beads by Ezrin and Radixin...... 104

xiv Figure 3.7 Disparate Accumulation Profiles of ERM Proteins around the Bead-surrounding Membranes...... 105

Figure 3.8 Indirect Evidence of Moesin Activation Triggered by Polystyrene Beads ...... 107

Figure 3.9 The Role of Moesin ITAM in Phagocytosis of Polystyrene Beads...... 109

Figure 3.10 Moesin Interacts with Syk via its FERM Domain in vitro ...... 111

Figure 3.11 Syk Activation induced by Solid Particle Engagement to Cell Surface...... 113

Figure 3.12 Kinetics of Downstream Signaling Activation following Solid Particle Engagement...... 115

Figure 3.13 Preferential Accumulation of Moesin around Silica Crystals ...... 119

Figure 3.14 Preferential Accumulation of Moesin around MSU Crystals...... 120

Figure 4.1 Spatiotemporal Distribution of Phospholipoids During Phagocytosis ...... 124

Figure 4.2 Accumulation of PIP2 around the Membrane Engaged with Polystyrene Beads ..... 126

Figure 4.3 Preferential Sorting of PIP2 into Cell Membrane in Contact with Beads ...... 131

Figure 4.4 Quantitative Analysis of PIP2 and Moesin Accumulation around a naked 6µm Polystyrene Bead ...... 134

Figure 4.5 Sequestration of membrane PIP2 Leads to Impairment of Phagocytosis of Solid Particles ...... 135

Figure 4.6 Quantitative Analysis of PIP2 Accumulation around a naked 6µm Polystyrene Bead in RAW264.7 and HEK293T Cells ...... 137

Figure 4.7 SEM images of PDMS micropatterns...... 141

Figure 4.8 Preferential Sorting of PIP2 into GPMV Membrane in Contact with Beads...... 142

Figure 4.9 PIP2 Sorting on GPMV Membranes in Contact with PDMS Micropatterns ...... 143

Figure 4.10 Specific Sorting of PIP2 on GPMV Membranes in Contact with Each Other ...... 145

Figure 4.11 Correlation between Efficiency of Solid Particles and Particle Rigidity ...... 147

Figure 4.12 Preferential Sorting of PIP2 into Highly Ordered Membranes on RAW264.7 Cells Engaged with PDMS Micropatterns ...... 156

Figure 5.1 Moesin/Syk Overexpression Failed to Induce Phagocytosis in COS-1 Cells ...... 163

Figure 5.2 Schematic Drawing of a Series of CD4-EGFP Chimeric Sequences...... 164

xv Figure 5.3 Strong Particle/Surface Binding Can Induce Phagocytosis in Certain Non- phagocytic Cells ...... 165

Figure 5.4 Partial Restoration of Phagocytosis in Moesin Knockdown DC2.4 Cells Induced by Strong Particle/Surface Binding Requires ITAM of Moesin on Chimeric Receptors ... 166

Figure 5.5 Moesin-mediated Phagocytosis and FcγR-mediated Phagocytosis are Independent of Each Other ...... 167

Figure 5.6 Moesin-mediated Phagocytosis and FcγR-mediated Phagocytosis Share Downstream Signals ...... 168

Figure 5.7 Comparison of Phagocytosis Efficiency between Moesin-mediated Phagocytosis and FcγR-mediated Phagocytosis with Beads of Different Sizes ...... 170

Figure 5.8 Comparison of the Number of Particles, Volume and Surface Area Internalized between Moesin-mediated Phagocytosis and FcγR-mediated Phagocytosis with Beads of Different Sizes of Different Sizes ...... 171

Figure 5.9 Moesin might be Involved in Scavenger Receptor-mediated Phagocytosis ...... 173

Figure 5.10 Moesin Function in Solid Particle Phagocytosis is Conserved among Species ...... 174

Figure 5.11 Potential Evolutionary Implications of Moesin-, -PIP2-mediated Signaling in Modern Immune Receptor-mediated Phagocytosis...... 177

Figure 6.1 Signaling Equivalent Platform Revisited: Moesin-, PIP2-mediated Phagocytosis ... 191

Figure 6.2 Potential Refinements for Moesin-, PIP2-mediated Solid Particle Phagocytosis ..... 202

Figure B. 1 Induction of Phagocytosis in COS-1 and Moesin-KD DC2.4 Cells with ICAM-1- ITAM Chimera ...... 234

Figure B. 2 Induction of Phagocytosis in COS-1 and Moesin-KD DC2.4 Cells with CD8a- ITAM Chimera ...... 235

Figure C. 1 Phylogenetic tree of moesin proteins family based on maximum likelihood...... 236

Figure C. 2 Phylogenetic tree of FcγR common γ chain and FcγRII family proteins based on maximum likelihood...... 237

Figure C. 3 Phylogenetic tree of PI3K catalytic subunit proteins family based on maximum likelihood...... 238

Figure C. 4 Phylogenetic tree of Syk/ZAP-70 proteins family based on maximum likelihood. 239

xvi

Video 3.1 3D-reconstructed Phagocytic Cup with Moesin and Actin ...... 106

Video 4.1 3D-reconstructed Phagocytic Cup with PIP2 and Actin ...... 127

Video 4.2 Dynamics Change of PIP2 Activation during Solid Particle Phagocytosis ...... 129

Video 4.3 Dynamics of PIP2 and Moesin Accumulation around Solid Particles ...... 133

Video 4.4 Dynamics of PIP2 Accumulation around Solid Particles in RAW264.7 Cells ...... 138

Video 4.5 Dynamics of PIP2 Accumulation around Solid Particles in HEK293T Cells ...... 139

xvii

List of Symbols, Abbreviations and Nomenclature

3D Three-dimensional AcLDL Acetylated LDL AFM Atomic force microscopy AKT/PKB Protein kinase B ANOVA Analysis of variance APC Antigen-presenting cells ARF ADP-ribosylation factor ARNO ARF nucleotide-binding site opener ATP Adenosine triphosphate BCR B cell receptor BMDM Bone marrow-derived macrophage BSA Bovine serum albumin CCD Charge-coupled device CD Cluster of differentiation C-ERMAD C-terminal ERM actin-binding domain C-laurdan 6-dodecanoyl-2-[N-methyl-N-(carboxymethyl)amino]naphthalene CLIP-170 Cytoplasmic Linker Protein-170 CLR C-type lectin receptor CR Complement receptor CRAC Cholesterol recognition amino acid consensus CRISPR Clustered regularly interspaced short palindromic repeats Cyto D Cytochalasin D DAG Diacylglycerol DC Dendritic cell Dectin DC-associated C-type lectin DNA Deoxyribonucleic acid dsRNA double-stranded RNA EDTA Ethylenediaminetetraacetic acid EGFP Enhanced green fluorescent protein EM Electron microscopy EMCCD Electron multiplying charge-coupled device ER Endoplasmic reticulum ERK Extracellular signal–regulated kinases

xviii FACS Flow-activated cell sorting Fc Fragment crystallizable FcRn Neonatal Fc receptor FcγR Fcγ receptor FDC Follicular dendritic cell FERM Band 4.1, ezrin, radixin, moesin

FKBP FK506 binding protein FN Fibronectin FRB FKBP-rapamycin binding GAP GTPase-activating protein GBD GTPase binding domain GDP Guanosine-5'-diphosphate GEF Guanine nucleotide exchange factor GP Generalized polarization GPMV Giant plasma membrane vesicle GTP Guanosine-5'-triphosphate ICAM-1 Intercellular adhesion molecule 1 IFN Interferon

IgG Immunoglobulin G IL Interleukin IP3 Inositol-3,4,5-trisphosphate IRF3 Interferon regulatory factor 3 ITAM Immunoreceptor tyrosine-based activation motif ITIM Immunoreceptor tyrosine-based inhibition motif IVIG Intravenous immunoglobulin KD Knockdown KIR Killer cell Immunoglobulin-like Receptors LCI Live cell imaging LCM L-cell conditioned medium LDL Low density lipoprotein LPS Lipopolysaccharide LTA Lipoteichoic acid

MARCKS Myristoylated alanine-rich C kinase substrate MARCO Macrophage receptor with collagenous structure MHC Major histocompatibility class MSU Monosodium urate MyD88 Myeloid differentiation primary response 88 MβCD Methyl-β-cyclodextrin

xix NA Numeric aperture NF-κB Nuclear factor kappa-light-chain-enhancer of activated B cells NK Natural killer

NLR NOD-like receptor NLR NOD-like receptor NOD Nucleotide-binding oligomerization domain NP Nanoparticle oxLDL oxidized LDL PA Phosphatidic acid PAMP Pathogen-associated molecular patterns PBS Phosphate-buffered saline PC Phosphatidylcholine PDMS Poly-dimethylsiloxane PE Phosphatidylethanolamine PFA Paraformaldehyde PFS Perfect focus system PH Pleckstrin homology PI3K Phosphatidylinositol-4,5-bisphosphate 3-kinase PI4K Phosphatidylinositol 4-kinase

PIP2 Phosphatidylinositol-4,5-bisphosphate PIP3 Phosphatidylinositol-3,4,5-trisphosphate PIP5K Phosphatidylinositol 4-phosphate 5-kinase PKC Protein kinase C PLCγ Phosphoinositide phospholipase C γ PLD Phospholipase D PLGA Poly(d,l-lactic-co-glycolic acid) PMA Phorbol-12 myristate-12-acetate PMMA poly (methyl methacrylate) PMT Photomultiplier tube PRR Pattern recognition receptor PS Phosphatidylserine PSF Point spread function PSGL-1 P-selectin glycoprotein ligand-1 Qdot Quantum dot QE Quantum efficiency RBC Red blood cells RNA Ribonucleic acid

xx ROCK Rho kinase ROI Region of interest ROS Reactive oxygen species RT-PCR Real-time polymerase chain reaction SDCM Spinning-disk confocal microscopy SDS-PAGE Sodium dodecyl sulfate polyacrylamide gel electrophoresis SEM Standard error of the mean SEP Signaling Equivalent Platform SFK Src-family kinase SH2 Src homology 2 SHIP SH2 domain-containing inositol 5-phosphatase SHP Src homology 2 domain-containing protein tyrosine phosphatase shRNA small hairpin RNA phosphatase SIM Structured illumination microscopy siRNA small interfering RNA SLP-76 Src homology 2 domain-containing leukocyte phosphoprotein of 76 SM SphingomyelinkD SNR Signal-to-noise ratio SPT Single particle tracking SR Scavenger receptor SR-A Scavenger receptor A SR-B1 Scavenger receptor B1 ssRNA single-stranded RNA STED Stimulated emission depletion Syk Spleen tyrosine kinase Symbol Definition TCR T cell receptor TIM T cell immunoglobulin mucin TIR Toll/IL-1 receptor TIRFM Total internal reflection fluorescence microscope TLR Toll-like receptor TRIF TIR domain-containing adaptor inducing interferon (IFN)-β VCA Verprolin-homology and cofilin-like and acidic region WASP Wiskott–Aldrich syndrome protein WAVE WASP-family verprolin-homologous protein WT Wildtype ZAP70 Zeta-chain-associated protein kinase 70

xxi Epigraph

Don’t EVER tell me what I CAN’T do! EVER!

—John Locke, “Lost”, 2004

xxii

Chapter One: Introduction

1.1 Innate Immunity

The innate immune system is the first line of defense against invading pathogens. Such defense mechanisms are usually quick because they exist even before infection takes place. It is a non-specific form of immune defense against danger (Murphy, 2014).

There are several layers of defense to the innate immune systems. First, as pathogens attempt to enter the human body, they encounter physical and chemical defense at epithelial barriers. Colonization of local tissue can only happen if epithelial barriers are breached. Next, pathogens will encounter sentinel innate immune cells at the site of infection. These include tissue-resident macrophage and dendritic cells (DCs), neutrophils, mast cells, natural killer (NK) cells and innate lymphoid cells. These cells function to control and eliminate infections. These cells also stimulate adaptive immune response to induce further control and elimination. Innate immune cells are also recruited to the site of infection to recognize, ingest and destroy pathogens during inflammation. Also, soluble proteins, such as complement proteins, can target pathogens for destruction by phagocytes via opsonization (Abbas et al., 2017).

The destruction of pathogens occurs via engulfment of microbial particles. The innate immune cells that can perform such function are together referred to as phagocytes (Abbas et al.,

2017).

1.2 Phagocytes

Phagocytes are generally categorized into professional phagocytes and non-professional phagocytes based on their efficiency of phagocytosis (Gordon, 2016; Rabinovitch, 1995).

Professional phagocytes include macrophages, DCs, monocytes neutrophils, osteoclasts and eosinophils owning to their highly efficient phagocytic activity in myeloid leukocytes (Gordon,

2016; Rabinovitch, 1995). On the other hand, non-professional phagocytes include fibroblast, endothelial cells, and epithelial cells have been shown to perform phagocytosis on certain particles (Gao et al., 2013; Grinnell, 1984; Hall et al., 1994; Monks et al., 2005; Nogueira et al.,

2011; Vann and Proctor, 1990). These cells are mostly facultative phagocytes (Gordon, 2016).

For example, epithelial cells are capable of phagocytosis during development and other pathological scenario but not in other situations (Flannagan et al., 2012; Freeman and Grinstein,

2016; Gordon, 2016). Also, fibroblast, sometimes referred to as “working-class phagocytes”, can clear apoptotic cells via specific integrin-mediated pathways, and such clearance is usually slow

(Williams-Herman and Werb, 1999). In contrast, both macrophages and DCs can phagocytose a variety of particles at high efficiency, thus considered the archetypical phagocytes, arguably alongside neutrophils (Silva and Correia-Neves, 2012). Therefore, the discussion in the remainder of this section will specifically focus on macrophages and DCs, as they were being used extensively in this thesis to study solid particle phagocytosis.

1.2.1 Macrophages

Macrophages are immune cells of myeloid lineage. They are migratory cells deriving from precursors in bone marrows or specific tissues and are found in all human tissues and play a crucial role in host defense (Ginhoux and Guilliams, 2016; Gordon and Taylor, 2005).

Historically, macrophages in different tissues have different names; for instance, microglial cells in the neural tissue and Kupffer cells in the liver. These tissue-resident macrophages form the

mononuclear phagocyte system together with monocytes and DCs to act as the first line of immune defense against pathogens (Hume, 2008; Hume et al., 2002; Jenkins and Hume, 2014).

Macrophages are mainly involved in engulfing and killing invading microorganisms and other insoluble material, initiating the innate immune responses and, subsequently, helping to orchestrate adaptive immune responses (Abbas et al., 2017). For example, in the case of pathogen invasion, macrophages bind and ingest the pathogen. Ingested pathogens are found within a membrane-enclosed vesicle called the phagosome, which is a specialized endocytic vacuole. In macrophages, there are intracellular vesicles that contain enzymes and toxic peroxides that are detrimental to the pathogens called lysosomes (Xu and Ren, 2015). The pathogen-containing phagosome fuses with one or more lysosomes to form a phagolysosome

(Botelho and Grinstein, 2011). Consequently, pathogens are destroyed by the lysosomal contents released into the phagolysosome (Murphy, 2014).

In addition to recognizing and destroying pathogens, macrophages also play a homeostatic role by removing apoptotic cells from the human body. It is estimated that 360 billion senescent red blood cells are cleared by macrophages daily (Bratosin et al. 1998).

Moreover, macrophages promote tissue repair by stimulating angiogenesis and fibrosis (Wynn and Vannella, 2016).

Another important function of macrophages includes cytokine and chemokine production during inflammation, which activates or helps recruit other immune cells to fight infection

(Arango Duque and Descoteaux, 2014). For example, microbial-activated macrophages can secrete several different cytokines that act on endothelial cells lining blood vessels to enhance the recruitment of more monocytes and other leukocytes from the blood into sites of infections

(Kim and Luster, 2015), thus forming a positive feedback loop to amplify the protective response against pathogens.

Additionally, like dendritic cells, macrophages can also function as antigen-presenting cells (APCs) to display antigens to T cells, albeit less efficiently (Unanue, 1984).

1.2.2 Dendritic Cells

Like macrophage, DCs are also derived from bone marrow or tissue progenitor cells

(Merad et al., 2013). They are defined in the textbook as tissue resident and circulating cells that sense the presence of microbes and initiate innate immune reactions and capture microbial proteins for display to T cells to initiate adaptive immune responses (Abbas et al., 2017).

Therefore, they are professional APCs. Despite this monomodal, thus poor, definition, the phagocytosis capability of DCs is never overlooked, as DC has been shown to recognize and ingest numerous biological and non-biological particles efficiently (Savina and Amigorena,

2007). Such efficient recognition and uptake are due to the expression of numerous receptors and their locations in tissues. It is important to recognize that both macrophage and DCs have a certain level of plasticity (Das et al., 2015; Raes et al.; van de Ven et al., 2013). Therefore, discussion of macrophage and DC function is meaningless without providing information on their location and microenvironment, as cellular programs can be altered significantly under the influence of the milieu (Ito et al., 2005; Pulendran et al., 2008). Nevertheless, the fact that DCs can efficiently function as both an APC and a phagocyte puts it in a unique place in immunity to serve as a bridging link between innate and adaptive immune systems (Malissen et al., 2014).

Besides phagocytosis and antigen presentation, DC can also produce cytokine and chemokine during inflammation to promote recruitment of additional immune cells from the blood (Turner et al., 2014). Plasmacytoid DC, a specific type of DC, can secrete type I interferon, and other cytokines and chemokines, to induce an antiviral state in cells during viral infection (Megjugorac et al.; Tezuka et al., 2011).

1.3 Immune Receptors on Phagocytes

There are two major functions carried out by phagocytes: recognition and destruction of invading foreign pathogens and clearance of endogenous cellular debris and apoptotic cells

(Gordon 2002). Phagocytes, such as macrophages and DCs, can recognize pathogens via immune receptors. Thus, it is vital for phagocytes to discriminate between self and non-self. It is proposed that cell surface receptors with broad specificity are essential during this process

(Janeway and Medzhitov 2002). These receptors of innate immunity are specific for structures that are common to groups of related microbes and do not distinguish subtle differences between microbes (Janeway and Medzhitov 2002).

Unlike the adaptive immune system, the innate immune system is a universal and ancient form of host defense against infection. While the adaptive immune system uses a virtually unlimited number of B and T cell receptors via somatic recombination, innate immune recognition relies on a limited number of germline-encoded receptors that evolved to recognize conserved microbial products called pathogen-associated molecular patterns (PAMPs) (Janeway and Medzhitov 2002). These receptors are termed pattern recognition receptors (PRRs) (Janeway

and Medzhitov 2002). Recognition of PAMPs allows the immune system to distinguish non-self or modified-self from self. PRRs are localized to the cell surface or are intracellular and are capable of recognizing a variety of ligands including lipopolysaccharides, proteins, and double- stranded RNA (Takeuchi and Akira, 2010).

The most considerable number and variety of PRRs are found on phagocytes, mainly macrophages and DCs. This is because both cells are most capable of recognizing, ingesting and eventually destructing pathogens. The principal types of PRRs found on phagocytes are Toll-like

Receptors (TLRs), Scavenger Receptors (SRs), C-type Lectin Receptors (CLRs) and cytosolic

NOD-like Receptors (NLRs) (Takeuchi and Akira, 2010).

It is worth noting that SRs and CLRs can also be classified as phagocytic receptors, and more specifically, non-opsonic receptors, because they can facilitate phagocytosis in an opsonin- independent manner (Ofek et al., 1995).

On the contrary, Fcγ Receptors (FcγRs) and Complement Receptors (CRs), are opsonic receptors for they participate in opsonic-phagocytosis (Gordon, 2016). The opsonins recognized by FcγRs and CRs are Immunoglobulin G (IgG) and complements, respectively. These receptors receive overwhelming attention in current research on phagocytosis.

In this section, we will discuss the structure and function of some significant PRRs and phagocytic receptors.

1.3.1 Phagocytic Receptors

1.3.1.1 Opsonic Receptors

Opsonins are named after the Greek word opson (ὄψον) for “relish” or “dressing”

(Delves et al., 2011). Thus, major opsonins, such as IgG antibodies and iC3b, can coat microbial surfaces to promote phagocytosis by binding to their cognate receptors, FcγRs and CRs, respectively (Winkelstein, 1973). Such coating enhances the affinity of binding between microbial particle and phagocyte cell surface. Consequently, opsonization leads to better phagocytosis efficiency. Typical opsonic receptors FcγRs and CRs are discussed below.

1.3.1.1.1 Fcγ Receptors

Fc receptors are expressed on leukocytes, including phagocytes such as macrophages and

DCs. They bind to the constant regions of different classes of antibodies with different affinity to promote phagocytosis (Hogarth, 2015).

Among these Fc receptors, FcγR is important for its role in opsonic phagocytosis. It binds to heavy chains of IgG and can be classified into several different types based on their affinity for different subclasses of IgG antibodies (Figure 1.1) (Nimmerjahn and Ravetch, 2008).

Figure 1.1 Structure and Functions of Different Types of Fcγ Receptors in Human Schematic models of the different human Fc receptors illustrate the Fc-binding α chains and the signaling subunits. FcγRIII-B is a glycophosphatidylinositol (GPI) anchored membrane protein with no known signaling functions. FcγRIIA and IIC are structurally similar low-affinity activating receptors with slightly different patterns of expression. Note that although FcγRIIA/C and FcγRIIB are both designated CD32, they are different proteins with distinct functions (see text). The neonatal FcR (FcRn) resembles class I major histocompatibility complex (MHC) molecules structurally but does not have a peptide-binding cleft. Reprint with copyright permission from Elsevier Limited (Abbas et al., 2017).

1.3.1.1.1.1 FcγRI

FcγRI bind to IgG1 and IgG3 with high affinity (Chenoweth et al., 2015). It is expressed on macrophages and neutrophils. It consists an α chain with three extracellular Ig-like domains for IgG binding. This α chain is associated with a homodimer linked via a disulfide bond named

Fcγ chain. It is noteworthy that the same Fcγ chain is also utilized by FcγRIII. The cytoplasmic tail of Fcγ chain contains an immunoreceptor tyrosine-based activation motif (ITAM) responsible for activation of downstream protein tyrosine kinases. The following section discusses the structure and function of ITAM.

1.3.1.1.1.1.1 Immunoreceptor Tyrosine-based Activation Motif

ITAMs are short peptide sequences with two tyrosine residues that are 6 to 12 amino acids apart [Tyr-X-X-(Leu/Ile)-X(6-12)-Tyr-X-X-(Leu/Ile)] (Mocsai et al., 2010). It can be associated with a receptor indirectly on the cytoplasmic tail of an adaptor protein, as in the case of FcγRI, or found directly within the cytoplasmic tail of the ligand binding receptor, as in the case of FcγRIIA. Following receptor ligation, such as IgG/FcγR binding, both tyrosine residues in the ITAM are phosphorylated, mainly by members of Src-family kinase (SFK). The phosphorylated ITAM serve as a dock to recruit spleen tyrosine kinase (Syk) via binding to its

Src Homology 2 (SH2) domains, in the case of FcγR and B cell receptor (BCR) activation

(Mocsai et al., 2010). Alternatively, Zeta-chain-Associated Protein kinase 70 (ZAP70) is recruited to phosphorylated ITAMs in the case of T cell receptor (TCR) activation (Mocsai et al.,

2010). The recruitment of Syk triggers downstream signaling, such as opsonic-phagocytic signaling in the case of FcγR activation (Figure 1.2).

Figure 1.2 Mechanism of ITAM Activation ITAMs are short peptide sequences with two tyrosine residues that are 6 to 12 amino acids apart [Tyr-X-X-(Leu/Ile)-X(6-12)-Tyr-X-X-(Leu/Ile)]. It can be associated with a receptor indirectly on the cytoplasmic tail of an adaptor protein, as in the case of FcγRI, or found directly within the cytoplasmic tail of the ligand binding receptor. Following receptor ligation, such as IgG/ FcγR binding, both tyrosine residues in the ITAM are phosphorylated, mainly by members so Src family kinase (SFK). The phosphorylated ITAM serve as a dock to recruit Syk via binding to its Src Homology SH2 domains, in the case of FcγR and BCR activation. Alternatively, ZAP70 is recruited to phosphorylated ITAMs in the case of TCR activation. The recruitment of Syk triggers downstream signaling, such as opsonic-phagocytic signaling in the case of FcγR activation. (Reprint with copyright permission from Springer Nature (Mocsai et al., 2010)

1.3.1.1.1.2 FcγRII

Unlike FcγRI, all three isoforms of FcγRII bind to IgG1 and IgG3 with low affinity. It is mainly expressed on macrophages, dendritic cells, and neutrophils, and the expression level differs among different isoforms (Nimmerjahn and Ravetch, 2008). Structurally, all isoforms share a similar extracellular domain with two Ig-like domains. This means the binding affinity to

IgG is similar among isoforms (Nimmerjahn and Ravetch, 2008). In contrast, they differ in

cytoplasmic tails. Specifically, FcγRIIA and FcγRIIC contain ITAMs, thus serving as activating receptors (Qiao et al., 2015). In comparison, FcγRIIB contains immunoreceptor tyrosine-based inhibition motif (ITIM), thus functioning as an inhibitory receptor (White et al., 2014). It is mainly expressed on myeloid cells and B cells. Refer to Section 1.4.5.2 for importance and functions of ITIM and FcγRIIB. It is noteworthy that FcγRIIA is uniquely expressed in human while FcγRIIB expresses in both human and mouse (Nimmerjahn and Ravetch, 2008).

1.3.1.1.1.3 FcγRIII

Like FcγRII, FcγRIII binds IgG1 and IgG3 with low affinity (Perussia and Ravetch,

1991). It consists of two isoforms, FcγRIIIA and FcγRIIIB. FcγRIIIA is structurally similar to

FcγRI and functions as an activating receptor via ITAM activation. It is mainly expressed on NK cells, macrophages and DCs (Nimmerjahn and Ravetch, 2008). FcγRIIIB is a poorly understood, and it is not involved in immune activation or phagocytosis (Nimmerjahn and Ravetch, 2008).

1.3.1.1.1.4 FcRn

Although not involved in phagocytosis, FcRn is a fascinating molecule worth mentioning. FcRn is called neonatal Fc receptor due to its involvement in the transport IgG from maternal circulation to the fetus (Roopenian and Akilesh, 2007). Structurally, it highly resembles

Major histocompatibility (MHC) class I molecule (Pyzik et al., 2015). It is mainly expressed on macrophages and endothelial cells (Roopenian and Akilesh, 2007). It binds to IgG in acidic endosomes, unlike surface binding for other Fcγ receptors. The FcRn- bound IgG is sequestered in acidic endosome instead of being targeted for destruction. Consequently, IgG-FcRn complexes are sorted into recycling endosome and transported to the cell surface, where IgG is

released at neutral pH. Thus, IgG returns to circulation (Pyzik et al., 2015). This mechanism is important for long half-life of IgG. Importantly, in therapeutics, fusion proteins with Fc portion of human IgG are created to prolong the half-lives of recombinant proteins (Kuo and Aveson,

2011). Also, FcRn plays a role in mucosal immunity by mediating IgG transport into mucosal secretions via transcytosis (Kobayashi et al., 2002; Tzaban et al., 2009).

1.3.1.1.2 Complement Receptors

The complement system is an important effector mechanism in both humoral immunity and innate immunity (Holers, 2014). For example, C3b, a key product of complement pathway, besides its function to initiate later steps of complement activation, can also serve as an opsonin, which deposited on the microbial cell surface via a covalent thioester linkage to proteins or polysaccharides, for recognition by CRs and eventually engulf and eliminate microbes (Holers,

2014). There are many types of CRs. They differ in expression, structure, and function (Holers,

2014). We will discuss four major types of CRs that are relatively well-studied.

1.3.1.1.2.1 CR1

CR1, or the type 1 complement receptor, has a high affinity for C3b and C4b. It functions mainly to promote phagocytosis of C3b- and C4b-coated particles and clearance of immune complexes from the circulation via phagocytosis (Krych-Goldberg and Atkinson, 2001). It is expressed on macrophages, DCs, and other cells. Structurally, CR1 consists a single chain with a large extracellular domain for ligand binding and a short cytoplasmic tail (Krych-Goldberg and

Atkinson, 2001). The binding of C3b- or C4b-coated particles to CR1 can also work in concert with FcγR to transduces signals that activate the microbicidal mechanisms of the phagocytes.

This is achieved by simultaneous engagement of C3b- and IgG-coated microbial particle to CR1 and FcγR expressed on phagocytes (Abbas et al., 2017; Flannagan et al., 2012).

1.3.1.1.2.2 CR2

CR2, or the type 2 complement receptor, does not directly participate in phagocytosis.

Instead, it functions to stimulate humoral immune responses by enhancing B cell activation by antigen and by promoting the trapping of antigen-antibody complexes in germinal centers

(Hannan, 2016). Because of such unique functions, CR2 is mainly found on B lymphocytes, follicular DCs (FDCs), and some epithelial cells. It binds to proteolytic products of C3b, namely

C3d, C3dg, and iC3b. For example, on FDCs, CR2 serves to trap iC3b-, C3d-, and C3dg-coated antigen-antibody complexes in germinal centers (Carroll, 1998).

1.3.1.1.2.3 CR3

CR3, or the type 3 complement receptor, is a significant complement receptor for phagocytosis (van Lookeren Campagne et al., 2007). It is an integrin, a heterodimeric receptor consists of an α and a β subunit by nature (Dupuy and Caron, 2008; Harburger and Calderwood,

2009), called αMβ2 or Mac-1 (Flannagan et al., 2012). Structurally, it is a heterodimer with αM chain non-covalently linked to its β2 chain. It binds iC3b with high affinity when activated to its extended conformation (Dustin, 2016). It is mainly expressed on neutrophils, macrophages, DC2, and NK cells (Dustin, 2016). On phagocytes, CR3 functions to promote phagocytosis of iC3b- opsonized microbes. It is interesting to note that CR3 can also mediate non-opsonic phagocytosis by directly binding to bacteria surface. As an integrin by design, it also binds to ICAM-1

(intercellular adhesion molecule 1) on endothelial cells to promote attachment and adhesion, thus contributing to the recruitment of leukocyte during inflammation (Landis et al., 1994).

1.3.1.1.2.4 CR4

CR4, or the type 4 complement receptor, is also an integrin called αXβ2. Structurally, it is a heterodimer with αX chain non-covalently linked to a β2 chain. It also binds iC3b like CR3, and the function of CR4 is similar to that of CR3 (Lukácsi et al., 2017). It is interesting to note that, integrin αX chain, also known as CD11c, is used as a marker for DCs for its abundant expression on this cell type (Merad et al., 2013).

1.3.1.1.3 Other opsonic receptors

Another integrin, α5β1, can be regarded as opsonic receptors for their ability to bind fibronectin (FN) and vitronectin. It has been reported that retinal pigment epithelial cells can phagocytose FN-coated beads (Zhao et al., 1999). However, little is known about how α5β1 mediates phagocytosis on macrophages and DCs.

1.3.1.2 Non-opsonic Receptors

Non-opsonic receptors are the phagocytic receptors that can directly bind to microbial particle surface to mediate phagocytosis (Gordon, 2016; Mukhopadhyay and Gordon, 2004). A few typical non-opsonic receptors are described below.

1.3.1.2.1 Scavenger receptors

In 1979, Brown and Goldstein made the initial observation that the resident mouse peritoneal macrophages were capable of taking up acetylated LDL (AcLDL) with 20 times higher the affinity than low density lipoprotein (LDL) (Goldstein et al. 1979). They termed the

AcLDL binding receptors macrophage scavenger receptors for their role in scavenging modified

LDL (Brown and Goldstein 1979). Since then, rapid progress had been made in discovering the physiological role of macrophage scavenger receptors in health and diseases. Work by Steinberg demonstrated that oxidized LDL is recognized by macrophage scavenger receptors and lipid- laden macrophages, or the “foam” cells, are formed (Quinn et al. 1987). This is thought to be the major cause of atherosclerosis (Steinberg and Witztum 2010). Later, researchers were able to clone and better define the classes of scavenger receptors. Scavenger receptor A was the first receptor cloned (Kodama et al. 1988) and followed by many other classes of scavenger receptors. The scavenger receptors are grouped into eight classes: A, B, C, D, E, F, G, and H, based on their structure (Krieger 1997). Figure 1.3 shows the domain architecture of these receptors. These receptors have broad ligand specificities that recognize a variety of ligands like lipopolysaccharide (LPS), lipoteichoic acid (LTA), apoptotic cells, microbial and viral products and polyanionic ligands in addition to recognizing modified lipoproteins (Plüddemann et al.

2007). Therefore, scavenger receptors are types of pattern recognition receptors. Some

Scavenger receptors (e.g., MARCO and SR-A) are expressed primarily on macrophages and dendritic cells, whereas others (e.g.SCARA3, 4 and 5) have a broader range of expression and are found on epithelial and endothelial cells (reviewed in Pluddemann et al. 2006; Pluddemann et al. 2007). Scavenger receptors play important roles in host defense and homeostasis due to

their broad ligand specificity. They contribute to macrophage functions such as endocytosis and phagocytosis (Platt and Gordon 2001).

Figure 1.3 Domain Architecture of the different Classes of Scavenger Receptors Scavenger receptors are divided into eight classes and are structurally very diverse. The domains are indicated in the key. Reprint with copyright permission from Cambridge University Press (Pluddemann et al., 2006).

1.3.1.2.2 C-Type Lectin Receptors

CLRs recognize carbohydrates PAMPs on the surface of microbes to facilitate phagocytosis and cytokine secretion during inflammation (Hoving et al., 2014). A few well- studied CLRs are described below. 16

1.3.1.2.2.1 Mannose Receptor

Mannose receptors bind to d-mannose, 1-fucose and N-acetyl-d-glucosamine on microbial surfaces. It is most abundantly expressed on macrophages. Structurally, it has a large extracellular domain for ligand binding and a very short cytoplasmic tail with limited signaling potential. This means that mannose receptors are primarily involved in initial binding, but not subsequent internalization, of non-opsonic phagocytosis (Martinez-Pomares, 2012).

1.3.1.2.2.2 Dectin

DC-associated C-type lectins, or Dectins, are mainly expressed on macrophages and DCs.

They are mainly involved in antifungal immunity (Herre et al., 2004). For example, Dectin-1 can bind to β-glucan, a major cell wall component of fungi. Also, Dectin-2 and Mincle can bind to high-mannose oligosaccharides on the hyphal form of fungus (Graham and Brown, 2009).

Unlike mannose receptors, Dectins contain ITAMs in its cytoplasmic tail, therefore capable of activating downstream tyrosine kinases and phagocytic signals (Underhill and Goodridge, 2012).

Also, pro-inflammatory signals, such as NF-κB-related signals, are also activated following

Dectins binding to the fungal or bacterial surface (Kingeter and Lin, 2012).

1.3.1.2.2.3 Langerin

Langerin is another CLR involved in phagocytosis (Valladeau et al., 2000). It binds to terminal mannose on microbial surfaces. It is primarily expressed on dendritic cells at epithelial barriers, such as Langerhans cells. It is unclear about the downstream signals induced by

Langerin.

1.3.1.2.3 Phosphatidylserine Receptors

Besides pathogens, phagocytes, mainly macrophages, also maintain homeostasis by recognizing and ingesting apoptotic bodies from tissues. The recognition of apoptotic bodies is achieved by receptors on the surface of macrophages (Flannagan et al., 2012).

Phosphatidylserine (PS), is a distinguishing marker for apoptotic cells. In healthy cells, PS is mostly restricted to the inner leaflet of plasma membrane, thus inaccessible for any receptor.

During cell death, PS is flipped to the outer leaflet of the plasma membrane to be recognized by phosphatidylserine receptors (Kay et al., 2012). These receptors include T cell immunoglobulin mucin (TIM), BAI1 and Stabilin-2 (Flannagan et al., 2014) .

1.3.2 Toll-like Receptors

As introduced at the beginning of this section, TLRs are the major PRRs expressed on macrophages and DCs via recognition of a variety of PAMPs.

1.3.2.1 Structure, Location, and Specificities of TLRs

In human, there are nine different TLRs (Figure 1.4) (Gay and Gangloff, 2007).

Structurally, TLR monomer is a type I transmembrane glycoprotein with leucine-rich repeats and cysteine-rich motifs in the extracellular domain and a Toll/IL-1 receptor (TIR) domain in its cytoplasmic tails. TIR domain is critical for TLR signaling whereas the multiple extracellular leucine-rich repeat motif is responsible for specificity to PAMP and they vary between TLRs (Gay and Gangloff, 2007). Also, leucine-rich domain is involved in dimerization

of TLRs following ligand binding. This further expands the specificities of TLRs via different heterodimer combination (Botos et al., 2011).

TLRs are found either on the cell surface or endosomal/Endoplasmic reticulum (ER) membranes. Specifically, TLR 1,2,4,5 and 6 are expressed on the cell surface while TLR 3,7,8 and 9 are intracellular. It should be noted that locations of TLRs coincide with the types of pathogens and the possible sub-cellular location of their PAMPs (Chaturvedi and Pierce, 2009).

For example, TLR 3,7 and 8 can recognize different forms of microbial RNAs, such as single- stranded RNA and double-stranded RNA (Jensen and Thomsen, 2012). This RNA per se are not unique to pathogens. However, their location in endosome is. This is because after pathogens are ingested, the likely cellular compartment to find its remaining RNA is the endosome in macrophages, DCs, and neutrophils. In contrast, surface-expressed TLRs usually recognize components of pathogens at their surface. For example, TLR4 and TLR2 can recognize components of bacterial cell walls such as LPS and LTA, respectively (Dessing et al.; Lu et al.,

2008; Park and Lee, 2013).

Figure 1.4 Structure, Location, and Specificities of TLRs in Human. Note that some TLRs are expressed on the cell surface and others in endosomes. TLRs may form homodimers or heterodimers. TIR, Toll/IL-1 receptor; LPS, lipopolysaccharide; dsRNA, double- stranded RNA; ssRNA, single-stranded RNA. Reprint with copyright permission from Elsevier Limited (Abbas et al., 2017).

1.3.2.2 TLR Signaling

Upon ligand binding, TLRs further activate downstream signals via adaptors and transcription factors to induce gene expression for inflammation and antiviral immunity (Figure

1.5) (Kawasaki and Kawai, 2014).

Specifically, TLR1,2,5 and 6 dimerization can be induced by binding to bacterial PAMPs on the cell surface. This leads to the activation and binding of adaptor protein Myeloid differentiation primary response 88, or simple MyD88. MyD88 will induce NF-κB activation and subsequent translocation to the nucleus to turn on expression of inflammatory genes, including cytokine, chemokines, adhesion molecule and costimulatory molecules (Vidya et al., 2018).

Consequently, an acute pro-inflammatory response is induced alongside stimulation of adaptive immunity (Vidya et al., 2018). On the other hand, viral dsRNA in endosome can bind to TLR3 to induce activation via an adaptor protein named TIR domain-containing adaptor inducing interferon (IFN)-β, or simply TRIF (Akira and Takeda, 2004). Transcription factor Interferon regulatory factor 3, or IRF3, can be activated by TRIF to induce an antiviral state by secreting type I IFNs (Kawasaki and Kawai, 2014). It is noteworthy that there is a different combination of usage for adaptors and transcription factors for each TLRs (Kawasaki and Kawai, 2014; Kumar et al., 2011).

Figure 1.5 Signaling Pathways and Functions of TLRs TLRs 1, 2, 5, and 6 use the adaptor protein MyD88 and activate the transcription factors NF-κB and AP-1. TLR3 uses the adaptor protein TRIF and activates the IRF3 and IRF7 transcription factors. TLR4 can activate both pathways. TLRs 7 and 9 in the endosome use MyD88 and activate both NF-κB and IRF7. IFN, interferon; IRFs, interferon regulatory factors; NF-κB, nuclear factor kappa B. Reprint with copyright permission from Elsevier Limited (Abbas et al., 2017).

1.3.3 Other Receptors and Intracellular Sensors

In addition to the cell surface and endosomal/ER membrane presence of PRRs, other sensor and receptors can be found in the cytosol to recognize cytosolic PAMPs and danger- associated molecular patterns (DAMPs) to promote inflammation, in both health and disease.

NOD-like receptors (NLRs) are such cytosolic receptors. Of interest, NLRP can sense a plethora of stimulations such as extracellular Adenosine triphosphate (ATP), silica crystals, monosodium urate (MSU) (He et al., 2016). NLRP3, alongside adaptor ASC and pro-caspase-1, forms a protein complex called inflammasome. Triggered by the stimulation mentioned above, inflammasome is activated, and pro-caspase-1 is released into caspase 1, its active form, to cleave the pre-formed pro-IL1β into IL1β, thus causing inflammation (Jo et al., 2016).

There are also other cytosolic DNA sensors. They sense bacterial or viral DNA to induce anti-bacterial or antiviral immunity (Paludan and Bowie, 2013).

1.4 Phagocytosis

1.4.1 Overview

The major feature of a phagocyte, such as the macrophage, is its ability to bind and internalize particles such as bacterial pathogens, apoptotic cells, and environmental particles. In fact, “phagocyte” was coined by the Russian zoologist Ilya Metchnikoff, who collected a minute, transparent starfish larva and pierced it with a thorn from a rose. In response, tiny amoeboid cells covered the thorn in an attempt to ingest the invading menace. He hypothesized that these cells with phagocytic ability were capable of ingestion and might play a key role in host defense and

tissue homeostasis (Tauber, 2003). Phagocytosis is a process by which macrophages ingest particles with a nominal diameter of more than 0.5μm. When the particle size is below 0.5μm, the process is regarded as endocytosis. Bacteria, apoptotic cells, cell debris and environmental dust, are all members of this category (Gordon, 2016). During phagocytosis, internalization is initiated by specific cell surface receptors interacting with their cognate ligand on the particles.

The particles are then internalized after actin has polymerized at the site of receptor binding

(Huynh et al., 2007). Actin is then shed from the phagosome, and the phagosome matures as the pH drops to form the phagolysosome. Consequently, pathogens are destroyed in the phagolysosome (Aderem and Underhill, 1999; Botelho and Grinstein, 2011; Groves et al., 2008).

The initial binding of invading pathogen or dangerous particles are mainly carried out by two types of receptors: 1) PRRs including TLRs, CLRs and scavenger receptors. They recognize specific components of invading pathogens like polysaccharides (mannose receptors) and, lipopolysaccharides (LPS) on gram-negative bacteria (TLR4) (Aderem and Ulevitch, 2000), and oxidized low-density lipoprotein (oxLDL) (SRs) (Wang et al., 2010), and engulf pathogens without opsonin (Pluddemann et al., 2009). 2) opsonic receptors such as complement receptors and Fcγ Receptors (FcγRs) (Greenberg and Grinstein, 2002). IgGs specifically bind to their targets whereas complement fragments C3b and iC3b bind non-specifically to the surface of foreign structures (Abbas et al., 2017). The modes of phagocytic uptake are different between

FcγR- and complement-mediated phagocytosis (Flannagan et al., 2012). During FcγR-mediated phagocytosis, membrane actively zippers around its target particle to form a phagocytic cup; this process depends on Cdc42 (Tollis et al., 2010). In contrast, during complement-mediated phagocytosis, particles sink into the cell without pseudopods extension, which is characteristic of

FcR-mediated phagocytosis and is independent of Cdc42 (Flannagan et al., 2012). In addition to

opsonic phagocytosis of solid particles, mostly biological particles by FcγR, non-opsonic phagocytosis of non-biologically particles has gained some interests in recent years (Nakayama,

2018). Later parts of this section will discuss the possible mechanism for phagocytosis of non- biological particles.

1.4.2 FcγR -mediated Phagocytosis

FcγR-mediated phagocytosis is the prototypical receptor-mediated phagocytosis. In general, FcγR-mediated phagocytosis is an intricate mechanism that involves the spatial and temporal coordination of membrane remodeling, receptor clustering, kinase activation and reorganization of cortical actins (Flannagan et al., 2012). We will focus our attention on FcγR

IIA which contains an intracellular ITAM directly at its cytoplasmic domain for this discussion.

1.4.2.1 Src Family Kinase

As FcγR crosslinks with IgG-opsonized particles, two tyrosine residues in the ITAM domain is phosphorylated by SFKs, Lyn, Hck, and Fgr. Lyn-/-, Hck-/- and Fgr-/- triple knockout macrophages displayed little ITAM phosphorylation coupled with delayed actin phagocytic cup formation (Fitzer-Attas et al., 2000). Also, the macrophages with Hck−/− Fgr−/− double knockout displayed normal FcγR phagocytosis, while the Lyn−/− single mutant mice showed a delay in Syk phosphorylation (Fitzer-Attas et al., 2000; Hunter et al., 1993). Therefore, it is important to note that SFK members have some functional redundancy in FcγR-mediated phagocytosis.

1.4.2.2 Syk

Phosphorylated tyrosine residues in the ITAM domain serve as a docking station for SH2 domains of Syk (Kiefer et al., 1998; Kimura et al., 1996; Law et al., 1996). Two loss-of-function studies have shown that Syk recruitment is indispensable for FcγR-mediated phagocytosis. First,

Inhibition with Syk antisense nucleotides resulted in inhibition of phagocytosis (Matsuda et al.,

1996). Second, Syk -/- macrophages were incapable of phagocytosing IgG-coated beads (Crowley et al., 1997). It was demonstrated that pharmacological disruption of SFK could affect recruitment of Syk during FcγR-mediated phagocytosis (Kimura et al., 1996). On the other hand, the importance of Syk in FcγR-mediated phagocytosis is also demonstrated by gain-of-function studies. First, it was demonstrated that binding of IgG-opsonized particles to FcγRIIIA could lead to more Syk phosphorylation (Darby et al., 1994). Second, overexpression of Syk in FcγR- transfected COS-1 cells can significantly enhance its phagocytic efficiency of IgG-opsonized particles (Indik et al., 1995). Physical binding of Syk to ITAM has been demonstrated with immunoprecipitation studies (Darby et al., 1994).

Docking of Syk to phosphorylated tyrosine residues of ITAM activates downstream effectors via phosphorylation, including its activation via phosphorylation by SFK (Mocsai et al.,

2010). Phosphorylated Syk serves as a docking station for the SH2 domain of p85 subunit of phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K), thus activating its catalytic subunit p110 following its binding to p85 (Chacko et al., 1996). Phosphatidylinositol-4,5-bisphosphate (PIP2) at the D3-position of the inositol ring is then phosphorylated by PI3K. As a result, PIP2 is modified to phosphatidylinositol-3,4,5-trisphosphate (PIP3) (Scott et al., 2005).

Besides PI3K, Syk also has other interacting partners. It has been demonstrated that Syk recruit other downstream molecules including Vav, Grb2 and PLCγ via direct association with

adaptor protein Src homology 2 domain-containing leukocyte phosphoprotein of 76 kD (SLP-76) during phagocytosis (Chen et al., 2013; Mocsai et al., 2010).

1.4.2.3 Small GTPases

F-actin polymerization following solid particle binding at the site of contact has long been demonstrated (Castellano et al., 2001; Diakonova et al., 2002). It drives the formation of pseudopods and their extension. Small GTPases are known regulators of F-actin in phagocytosis, adhesion, and migration, which all involves frequent actin rearrangement (Castellano et al.,

2001). It was demonstrated that Cdc42 and Rac1, two small GTPases, are involved in the creation of filopodia and lamellipodia, respectively (Ridley et al., 1992). In comparison, RhoA, another small GTPase, is involved in the formation of actin-myosin filaments where cytoskeleton is at a relative ‘resting state’ (Hackam et al., 1997).

Small GTPases, in general, serve as molecular switches to turn on or off signals (Manser,

2002). When they are GTP bound, they are active. By contrast, small GTPases are inactive when they are bound to GDP. Activation of small GTPase is facilitated by interaction with guanine nucleotide exchange factors (GEFs). GEFs substitute the GDP bound to GTPases for GTP for activation (Cherfils and Chardin, 1999). In comparison, inactivation is achieved with the help of

GTPase-activating proteins (GAPs). GAPs mediated GTP hydrolysis to inactivate Small

GTPases (Santy and Casanova, 2002).

Rho family GTPases and ADP-ribosylation factor (ARF) family GTPases are implicated in FcγR-mediated phagocytosis (Bos et al., 2007) and will be discussed below.

1.4.2.3.1 Rho family GTPases

The major Rho family GTPase involved in FcγR-mediated phagocytosis are Cdc42 and

Rac1 (Massol et al., 1998).

Microscopy analysis revealed the differential spatiotemporal distribution of Cdc42 and

Rac1 during FcγR-mediated phagocytosis. Cdc42 was found to accumulate at the leading edge of extending pseudopods early in phagocytosis whereas Rac1 is enriched at all places of the phagocytic cup and peaked during closure of phagosome (Hoppe and Swanson, 2004).

Loss-of-function studies have shown the necessity of Rho family GTPase for FcγR- mediated phagocytosis. First, macrophages expressed with dominant negative mutants of Cdc42 displayed diminished phagocytosis efficiency of IgG-opsonized particles (Caron and Hall, 1998).

Second, small hairpin RNA (shRNA) knockdown of Cdc42 impaired the ability of macrophage to internalize, but not to bind, IgG-opsonized solid particles (Park and Cox, 2009). In the same study, they also found that pseudopod extension and Wiskott–Aldrich syndrome protein

(WASP/N-WASP), which contributes toward F-actin polymerization, are blocked with the

Ccd42 knockdown (Park and Cox, 2009).

The GEF of Rac1, Vav mediate its activation. It has been demonstrated that Vav can be recruited to the site of contact in FcγR-expressing COS-1 cells (Patel et al., 2002). It was also found that Rac-1 does not regulate Cdc42 (Patel et al., 2002). Vav contains an SH2 domain, thus can directly bind to Syk (Deckert et al., 1996). Further, it also contains a pleckstrin homology

(PH) domain specific for PIP3, a product of PI3K following activation. Therefore, Vav can also function at the phagocytic cup to recruit PIP3 (Han et al., 1998).

1.4.2.3.2 ARF family GTPase

The ADP-ribosylation factor (ARF) family of GTPases also contributes to FcγR- mediated phagocytosis. Two members, ARF1 and ARF6, have been studied in FcγR-mediated phagocytosis.

Similar to that of Cdc42 and Rac-1, live cell microscopy also revealed that ARF6 is more enriched at the growing tips of pseudopods and promotes pseudopod extension whereas ARF1 remains functional through the phagocytic cup (Beemiller et al., 2006). This dynamic is disrupted when cells are treated with LY294002, a PI3K inhibitor. Therefore, it was suggested that PI3K is crucial in modulating ARF GTPase activity (Beemiller et al., 2006).

ARF6 can also activate phosphatidylinositol 4-phosphate 5-kinase (PIP5K) enzyme to generate more PIP2 at the membrane (Boronenkov and Anderson, 1995; Honda et al., 1999).

PIP2 is a substrate for PI3K, therefore, feeding ARF6 back into the control of PI3K on its activity.

1.4.2.4 Phosphoinositides and Related Enzymes

Lipids play a pivotal role in phagocytosis (Botelho et al., 2004; Flannagan et al., 2012;

Yeung et al., 2006). Among them, PIP2 and PIP3 are most extensively studied for FcγR- mediated phagocytosis (Flannagan et al., 2012). One of the general features of these phosphoinositides is that they cause the build-up of negative charge on the inner leaflet of the plasma membrane. As a result, cationic proteins, such as Rac1, PIP5K, and SFKs can be attracted to the membrane (Yeung et al., 2006). We will discuss the specific involvement of these phosphoinositides and related enzymes in FcγR-mediated phagocytosis.

1.4.2.4.1 PI (4,5) P2

During FcγR-mediated phagocytosis, PIP5K is recruited to the inner leaflet and activated via various involvement of Rac1, ARF6 and phosphatidic acid (PA), which is the hydrolytic product of phosphatidylcholine (PC) catalyzed by Phospholipase D (PLD) (Beemiller et al.,

2006; Botelho et al., 2000; Corrotte et al., 2006; Honda et al., 1999). This recruitment will lead to PIP2 enrichment at the site of contact. Specifically, at the leading edge of pseudopod and early in phagocytosis, PIP2 works in concert with Cdc42 to promote F-actin polymerization via

Arp2/3 complex (Higgs and Pollard, 2000; Rohatgi et al., 2000). At later stages of phagocytosis,

PIP2 disappears from the phagocytic cup, followed by the breakdown of the F-actin network underneath. The disappearance of PIP2 can be accounted for by the actions of phosphoinositide phospholipase C γ (PLCγ) and PI3K (Scott et al., 2005). Specifically, PLCγ cleaves PIP2 into diacylglycerol (DAG) and inositol-3,4,5-trisphosphate (IP3) (Botelho et al., 2000). DAG further activates protein kinase Cε (PKCε), an effector of phagocytosis (Larsen et al., 2000). In addition,

DAG recruits and activates RasGRPs, GEFs for Ras and Raf1. In turn, Ras is activated and promote inflammation via ERK (Botelho et al., 2009). The function of PI3K is introduced in the following section.

1.4.2.4.2 Phosphoinositide 3-Kinase and PI (3,4,5) P3

PI3K is an essential molecule for phagocytosis as it is involved in pseudopod extension and phagosome closure (Cox et al., 1999). Structurally, it contains a p85 regulatory subunit and a p110 catalytic subunit (Wymann and Pirola, 1998). It is the p110 subunit that phosphorylates

PIP2 at the D3 position of the inositol ring, thus converting it to PIP3. It has been shown that

PI3K can physically associate with Syk in mouse macrophages incubated with IgG-opsonized

particles, likely via its SH2 domain on the p85 regulatory subunit (Moon et al., 2005). It is worth noting that the SH2 containing inositol 5-polyphosphatase 1 (SHIP1) can be recruited to the

ITIM motif on FcγRIIB via binding of its SH2 domain to dephosphorylate PIP3 to counteract

PI3K signal (Nakamura et al., 2002).

PI3K activation during FcγR-mediated phagocytosis induces the recruitment of protein kinase B (AKT/PKB). This recruitment is caused by the increased concentration of PIP3 and binding of AKT/PKB to PIP3 via its PH domain, which has a high affinity for PIP3 but not PIP2

(Chan et al., 1999; Toker and Cantley, 1997). Vav and ARF nucleotide-binding site opener

(ARNO), two PH domain-containing GEFs, are also recruited to bind to PIP3. They function to activate Rac1 and AFR6, respectively (Cohen et al., 2007; Han et al., 1998). Myosin X, which is proposed to mediate pseudopod extension, is also recruited to interact with PIP3 (Araki, 2006).

1.4.2.4.3 Protein Kinase C

DAG, hydrolytic product of PIP2, activates PKC family proteins (Allen and Aderem,

1995b). PKC proteins are serine/threonine kinases (Larsen et al., 2000). They activate a downstream effector named myristoylated alanine-rich C kinase substrate (MARCKS). In resting state, MARCKS primarily functions to crosslink F-actin and tether actin network to the plasma membrane. During FcγR-mediated phagocytosis, PKC phosphorylates MARCKS to release it from the membrane, therefore untether F-actin from the membrane (Allen and Aderem, 1995a;

Larsen et al., 2000). This causes increased mobility of FcγR to allow for lateral clustering to efficiently initiate phagocytic signaling (Hartwig et al., 1992).

1.4.2.5 Actin Cytoskeleton

One significant consequence of all the phagocytic signaling events described above during FcγR-mediated phagocytosis is the reorganization of actin cytoskeleton (Flannagan et al.,

2012). This is directly achieved by F-actin nucleation promoting proteins WASP and WASP- family verprolin-homologous protein (WAVE) (Blanchoin et al., 2000; Machesky and Insall,

1998). Clinically, it has been demonstrated that patients with a loss-of-function mutation in

WASP are defective in FcγR-mediated phagocytosis of human IgG-opsonized Escherichia coli

(Lorenzi et al., 2000; Rengan et al., 2000).

Structurally, WASP contains a GTPase binding domain (GBD) in N-terminal regions and a verprolin-homology and cofilin-like and acidic region (VCA) adjacent to its catalytic C- terminal regions. In resting state, WASP is inactive due to the interaction between GBD and

VCA (Higgs and Pollard, 2000). Activation of WASP is achieved via binding of active GTP- bound Cdc42 and PIP2 to its GBD, thus making its catalytic regions accessible. WASP, in turn, binds to Arp2/3 via its VCA region to activate Arp2/3 (Higgs and Pollard, 2000; Rohatgi et al.,

2000). Knockdown studies with shRNA have shown that actin assembly is impaired in mouse macrophages with deficient WASP expression (Park and Cox, 2009). Arp2/3 directly binds to F- actin to promote nucleation and de novo polymerization on previously formed actin filament and forming a branch with a 70° angle from the original actin filament (Stradal and Scita, 2006;

Svitkina, 2012). Also, Arp2/3 also contributes to F-actin bundling and crosslinking during FcγR- mediated phagocytosis (May et al., 2000).

1.4.2.6 Summary of FcγR-mediated Phagocytosis

To briefly summarize, during FcγR-mediated phagocytosis, IgG-opsonized particles bind to Fcγ receptors on the surface of macrophages. Receptor cross-linking activates Src-family kinase to bind and phosphorylate ITAM of the Fcγ receptor. Phosphorylated tyrosine residues in the ITAM serve as docking stations for Syk, which in turn binds and activates PI3K. Other effectors such as small GTPases and PKC are also activated. In addition to enzymes, phosphoinositides such as PIP2 and PIP3 also transduce essential signals. Consequently, these signals lead to actin polymerization via Arp2/3 binding and activation (Figure 1.6).

Figure 1.6 Fcγ receptor-mediated Phagocytic Signaling. Aggregated receptors trigger activation of tyrosine kinases (orange), including Src-family kinases (SFKs), followed by recruitment of adaptor proteins (green). The resulting signaling platforms activate multiple lipid-modification enzymes (blue) and guanine nucleotide exchange factors (lavender) for small GTPases (brown). Nucleation-promoting factors (purple) activate the actin nucleation complex Arp2/3 (red), which in turn elicits actin polymerization that drives pseudopod extension. Abbreviations: DAG, diacylglycerol; ITAM, immunoreceptor tyrosine- based activation motif; LAT, linker of activated T cells; PA, phosphatidic acid; PC, phosphatidylcholine; PI3K, phosphatidylinositol 3-kinase; PI(3,4)P2, phosphatidylinositol-3,4- bisphosphate; PI(3,4,5)P3, phosphatidylinositol-3,4,5-trisphosphate; PI(4,5)P2, phosphatidylinositol-4,5-bisphosphate; PKC, protein kinase C; PLC, phospholipase C; PLD, phospholipase D; SHIP, Src homology 2 domain–containing inositol 5’-phosphatase; Syk, spleen tyrosine kinase; WASP, Wiskott-Aldrich syndrome protein. Reprint with copyright permission from Annual Reviews (Flannagan et al., 2012).

1.4.3 CR3-mediated Phagocytosis

CR3-mediated phagocytosis is another important form of opsonic phagocytosis.

Mechanistically, it shares many common signals with FcγR-mediated phagocytosis previously described (Flannagan et al., 2012). In this section, we will emphasize some differences between

CR3-mediated phagocytosis and FcγR-mediated phagocytosis.

As discussed in section 1.3.1.1.2.3, CR3 is an integrin. In general, integrin receptor signaling involves two steps. During resting state, integrins are at a bent conformation in which the binding affinity for their ligands is low. Therefore, first, the cell must signal from within to activate integrin. This is called ‘inside-out’ signaling. Activated integrins are in an extended conformation with high affinity for ligands. Second, ligands bind to activated integrins to initiate signaling that consequently lead to rearrangement of F-actin cytoskeleton. This process is called

‘outside-in’ signaling (Harburger and Calderwood, 2009). The next sections will focus on the

CR3-specific aspects of these processes during phagocytosis.

1.4.3.1 Inside-out Signaling for CR3

The necessity of inside-out signaling for efficient phagocytosis of iC3b opsonized particles was demonstrated with deficiency to engulf iC3b-opsonized particles by macrophages without stimulation (Wright and Griffin, 1985). This is due to the low-affinity state of inactive

CR3 (Ehlers, 2000). This stimulation can come in many forms such as laminin, fibronectin and inflammatory cytokines (Pommier et al., 1983; Wright and Griffin, 1985). Experimentally, it was shown that phorbol-12 myristate-12-acetate (PMA) could provide stimulations for CR3 inside- out signaling. Specifically, PMA activates PKC, which in turn phosphorylates serine residues on

the β chain of CR3 in macrophages (Chatila et al., 1989). Rap1 GTPase was also shown to transduce CR3 inside-out signals, as PMA-stimulated macrophages were shown to be deficient in iC3b-opsonized RBCs uptake when a dominant negative construct for Rap1 is expressed

(Caron et al., 2000).

1.4.3.2 Outside-in Signaling for CR3

Unlike FcγR, CR3 does not have ITAMs or seem to associate with ITAM when CR3- mediated phagocytosis was first studied (Flannagan et al., 2012). It was shown that CR3- mediated phagocytosis is unaltered when macrophages were treated with tyrosine kinase inhibitor (Allen and Aderem, 1996). Furthermore, it was shown that CR3-mediated phagocytosis is normal in Syk -/- deficient mouse (Kiefer et al., 1998). Later, other groups have shown that Syk phosphorylation is required for CR3-mediated phagocytosis (Shi et al., 2006). Further, it was also demonstrated that iC3b-opsonized phagocytosis is impaired when Syk function is blocked

(Shi et al., 2006; Tohyama and Yamamura, 2006). These conflicting reports have made it difficult to establish a firm signaling mechanism like FcγR-mediated phagocytosis. In recent years, it has been shown that Syk can bind to the phosphorylated ITAM on DAP12 or FcγR- associated γ chain (Mocsai et al., 2010). Therefore, it seems probable that Syk is activated during

CR3-mediated phagocytosis by associating itself with ITAM-containing adaptor proteins via its

SH2 domain to help transduce phagocytic signals (Mocsai et al., 2010).

1.4.3.3 Rho GTPase Activation During CR3-mediated Phagocytosis

Like FcγR-mediated phagocytosis, Rho GTPases are important effector proteins in CR3- mediated phagocytosis. Specifically, in CR3-mediated phagocytosis, RhoA is shown to be

activated during phagocytosis of iC3b-opsonized RBCs by macrophages. Unlike FcγR-mediated phagocytosis, Rac1 and Cdc42 are not involved in CR3-mediated phagocytosis (Caron and Hall,

1998; May et al., 2000). CR3 recruits RhoA to the threonine motif located in its cytoplasmic tail of β2 chain. The likely GEF for RhoA is Vav (Caron and Hall, 1998).

Two pathways have been demonstrated in which RhoA can promotes actin polymerization (Caron and Hall, 1998). First, RhoA directly activates Rho kinase (ROCK).

ROCK, in turn, phosphorylates myosin II via its light chain. As a result, the Arp2/3 complex is activated to promote F-actin rearrangement and assembly. It has been shown that F-actin polymerization is reduced when ROCK activity is disrupted by inhibitors or expression of dominant negative mutants (Olazabal et al., 2002).

Alternatively, RhoA can activate mammalian diaphanous-related formin (mDia) to promote F-actin assembly and polymerization (Colucci-Guyon et al., 2005). The mDia formin is recruited by a microtubule-associated protein, Cytoplasmic Linker Protein-170 (CLIP-170)

(Lewkowicz et al., 2008). It is worth noting that, unlike Arp2/3, mDia functions to increase F- actin length without branching (Colucci-Guyon et al., 2005; Lewkowicz et al., 2008).

1.4.3.4 Summary of CR3-mediated Phagocytosis

To summarize, during CR3-mediated phagocytosis, CR3 is first activated via inside-out signal to reach a high-affinity state for ligand binding. Next, the outside-in signaling is triggered by binding of iC3b-opsonized particles to CR3. ITAM-containing adaptor proteins are likely involved in the activation and Syk is recruited to the ITAM. RhoA is activated by CR3 to promote actin polymerization through Arp2/3 and mDia.

Figure 1.7 CR3-mediated Phagocytic Signaling

Binding of iC3b-opsonized particles to αMβ2 integrins activates RhoA in a tyrosine kinase- independent manner or, possibly, via the spleen tyrosine kinase (Syk) kinase pathway, involving recruitment of the immunoreceptor tyrosine-based activation motif (ITAM)-bearing DAP12 and Fc receptor γ chain. RhoA stimulates the activity of the serine/threonine kinase Rho kinase (ROCK), which activates myosin II by phosphorylation of its light chain. Myosin II seemingly participates in the recruitment of Arp2/3, which nucleates actin polymerization. RhoA also activates the actin nucleator mDia, which is recruited to the phagocytic cup in a CLIP-170- dependent manner. Reprint with copyright permission from Annual Reviews (Flannagan et al., 2012).

1.4.4 Phagocytosis of Non-Biological Particles

Besides biological particles, such as bacteria, other solid particles can be taken up by phagocytes. These non-biological particles include crystals and nanomaterials with particle size over 500 nm in diameter (Nakayama, 2018). Because the surfaces of non-biological particles are less likely opsonized by antibodies or complement proteins and lack the PAMPs recognizable by typical phagocytic receptors (See Section 1.3.1), they rely on other mechanisms of phagocytosis, typically with help from non-opsonic receptors, for recognition and internalization (Figure 1.8).

Our understanding of phagocytosis of non-biological particles is still rudimentary and fragmented. The following sections will discuss the phagocytic mechanisms of selected non- biological particles that are extensively studied and better understood.

1.4.4.1 Silica Crystals

Silica, a component of sand and rocks, is known to cause lung fibrosis and cancer

(Brown, 2009). They are usually contained in dust and air pollutants and inhaled into lung to interact with alveolar macrophages (Pozzi et al., 2003). Silica particles are rapidly internalized by alveolar macrophages, and further inflammation and cell death ensued (Costantini et al.,

2011; Hamilton et al., 2008). There has not been a defined mechanism delineating the internalization of silica particles but only a few pieces of evidence. First, class A scavenger receptors SR-A1 and MARCO are shown to mediate silica phagocytosis as demonstrated by the impaired phagocytosis of silica particles and reduction of subsequent inflammation in knockout mice (Thakur et al., 2008, 2009). Also, class B scavenger receptors SR-B1 and CD36 are shown to bind to silica particles and contribute to the chronic inflammation of lungs induced by silica

particles (Wang et al., 2009). Third, Gilberti and colleagues have demonstrated that, following initial engulfment, Rac1 and RhoA GTPase are activated, which consequently leads to F-actin accumulation at the particle attachment site (Gilberti et al., 2008). They also demonstrated that phagocytosis of silica particles is sensitive to disruptions by inhibitors of tyrosine kinase, actin polymerization, and phosphatidylinositol, which are like the classical FcγR-mediated phagocytosis described in Section 1.4.2. Interestingly, they also showed that, unlike classical phagocytosis, microtubules are required in the early steps of phagocytosis during attachment

(Gilberti and Knecht, 2014).

Taken together, silica particle phagocytosis involves bindings of particles to class A and class B scavenger receptors. This will lead to an internalization mechanism similar to that of the

FcγR-mediated phagocytosis except that microtubules are required at the initial steps. It is important to point out the fact that, despite all the evidence described above suggesting the importance of scavenger receptors in silica phagocytosis, scavenger receptors have very short cytoplasmic tails that lack any apparent signaling motif involved in phagocytic signaling

(Greaves and Gordon, 2009), it is still unclear what initiates phagocytic signaling after receptor binding. Thus, it is likely that scavenger receptors can serve as tethering molecules for initial particle binding and attachment. Therefore, they may function as co-receptors to unidentified receptors or surface molecules, which possesses the necessary signaling motifs, such as ITAM, in their cytoplasmic tails.

1.4.4.2 Cholesterol Crystals

Accumulation of cholesterols can result in the formation of crystals. They can be engulfed by macrophages in atherosclerotic lesions, and this leads to inflammation (Tall and

Yvan-Charvet, 2015). A few investigations have been conducted to study the mechanism of recognition and phagocytosis of cholesterol particles. First, researchers have shown that cholesterol crystals can activate complement proteins C5a and C5aR. This leads to the activation of extracellular signal–regulated kinases (ERKs) and NF-κB pathways which then leads to the upregulation of CR3, and this contributes to cholesterol phagocytosis (Kolev et al., 2014; Vogt et al., 1985). However, it is still unclear as to how cholesterol crystals can be internalized since it is not opsonized with iC3b, a ligand for CR3 that is upregulated by cholesterol crystals (Samstad et al., 2014). Second, Clec4e, a C-type lectin, has been shown to directly bind to cholesterol crystals via a cholesterol recognition amino acid consensus (CRAC) motif in its extracellular domain. This binding can lead to activation of proinflammatory signals associated with FcR common γ chains (Kiyotake et al., 2015). However, no experimental evidence suggests that cholesterol crystals are phagocytosed by cells via the FcγR-dependent mechanism. Moreover, this binding is only found in human but not mouse (Kiyotake et al., 2015).

To summarize, cholesterol crystals can lead to upregulation of phagocytic receptor CR3, and in human, are shown to bind to Clec4 directly. However, it remains to be seen if and how any phagocytic receptor can directly mediate binding and internalization of cholesterol crystals.

1.4.4.3 MSU Crystals

Uric acid is released by dying cells and can cause inflammation (Shi et al., 2010).

Saturation of uric acid will lead to the formation of monosodium urate crystals. MSU crystals are implicated in the pathogenesis of gouty arthritis (Shi et al., 2010). Like cholesterol crystals, MSU crystals can also activate complement pathways (Giclas et al., 1979; Hasselbacher, 1979).

Specifically, it was reported that MSU crystals could activate C5a. C5a binds to C5aR to activate

pro-inflammatory signals in human monocytes. However, the same research also confirmed that

C5aR does not facilitate phagocytosis of MSU crystals (An et al., 2014). Further, FcγRIII has been shown to directly bind to MSU crystals to activate downstream Syk signalizing, albeit only in neutrophils. Again, despite the activation of Syk and association with FcR common γ chain upon direct engagement of MSU crystals with FcγRIII, researchers failed to show that FcγRIII mediates internalization of MSU crystals (Barabé et al., 1998). In macrophages and DCs, our group has shown that direct engagement of MSU crystals to the membrane is sufficient to induce downstream phagocytic signaling (Ng et al., 2008). Refer to Section 1.4.4.5 for details regarding our previous research findings and proposed models.

It is worth noting here that Clec12a, a C-type lectin, has been reported to direct engage

MSU (Neumann et al., 2014). Since Clec12a contains an ITIM in its cytoplasmic domain, it functions as an inhibitory receptor during phagocytosis. Mechanistically, ITIM attracts phosphatases to remove phosphate groups on activated ITAMs, thus counteracting the activating effect of Syk. In fact, enhanced inflammation was observed in Clec12-deficient mice treated with

MSU (Neumann et al., 2014). Such check-and-balance between ITAM-kinase signaling and

ITIM-phosphatase signaling is a recurrent scheme not only in phagocytic signaling but also in general immune signaling. This scheme represents a fundamental integrated signaling mechanism of immune activation and regulation. Refer to Section 1.4.5.2 for an in-depth discussion on this topic.

1.4.4.4 Alum Crystals

Alum is an inorganic adjuvant. Phagocytosis of alum crystals will lead to the activation of NLRP3 inflammasomes (Eisenbarth et al., 2008; Hornung et al., 2008). To date, no apparent

receptors were reported to mediate phagocytosis of alum crystals. Instead, our laboratory has shown that, like MSU, alum can directly bind to membrane lipids. Ligation of alums crystals and membrane lipids is sufficient to induce ITAM-based phagocytic signaling marked by the activation of Syk and PI3K (Flach et al., 2011).

Figure 1.8 The Recognition of Solid Particles on the Macrophage Surface. Macrophages recognize and internalize crystals and nanoparticles through cell-surface receptors and membrane cholesterol. Silica particles are recognized by SR-A1, MARCO, SR-B1, and CD36. Alum, poly(methyl methacrylate) (PMMA), and monosodium urate (MSU) crystals bind directly to membrane cholesterol to be internalized. MSU and cholesterol crystals activate complement pathways. Soluble oxidized low-density lipoprotein (oxLDL) is internalized by CD36 and then crystallized in phagosomes. P2X7R does not cause lysosomal damage. In addition to these, many unknown pathways of phagocytosis remain to be identified. Signals 1 corresponds to NF-κB-dependent pro-inflammatory signals. Signal 2 corresponds to phagocytic signals involves Syk and PI3K. Reprint with copyright permission under Creative Commons Attribution License (CC BY) from Nakayama, 2018.

1.4.4.5 Contribution to the Understanding of Solid Particle Phagocytosis by Our Laboratory

Our laboratory has been attempting to understand how solid particles can be recognized and internalized by phagocytes. The following sections detail our findings and summarize a proposed mechanism based on our findings.

1.4.4.5.1 Previous Studies on Particle Phagocytosis

As discussed in Section 1.4.4.3 and 1.4.4.4, it is still unclear if any phagocytic receptor can mediate binding and subsequent internalization of solid particles altogether. Meanwhile, our group showed in 2008 that recognition of solid structures such as MSU depends on lipids, but not protein receptors on the cell membrane (Flach et al., 2011; Ng et al., 2008). This claim was substantiated by the following experimental evidence. First, when observing immune activation at the single cell level with atomic force microscopy (AFM), we were able to detect binding force between MSU crystals and cell surface within 30 seconds of initial contact. The magnitude of such force, roughly around 200 pN, is similar to that of a receptor and ligand binding.

Furthermore, we found that crystal phagocytosis via direct membrane engagement is dependent on phosphorylation of ITAM and Syk, which is identical to that of FcR-mediated phagocytosis.

For example, a delayed binding force in DCs was observed with Lyn-/-, Hck-/- and Fgr-/- triple knockout mice, which is in parallel with the delayed ITAM phosphorylation. Moreover, membrane binding force between crystals and plasma membrane dropped to a basal level in Syk

-/- knockout DCs (Ng et al., 2008). However, we were not able to identify the ITAM-bearing surface receptor or adaptor responsible for crystal phagocytosis, as a binding force between MSU crystals and cell membrane remained the same for the FcγR-/-, DAP12 -/- double knockout mice and wildtype controls. This finding was also later confirmed with alum crystals (Flach et al.,

2011). Taken together, these results have provided compelling evidence that phagocytes membrane can directly engage crystals during phagocytosis equivalent to a ligand-receptor interaction.

Second, when we treated cells with Pronase to digest and denature proteins on the cell surface, the strength of binding force between MSU and cell surface and subsequent activation remain intact (Ng et al., 2008). Specifically, when we disrupt cholesterol in the membrane with methyl-β-cyclodextrin (MβCD), binding force dropped to the basal level (Ng et al., 2008). This suggests that cholesterol might directly engage crystals during phagocytosis. We further confirmed this finding in our study with alum in 2011 (Flach et al., 2011) ; When we detect binding force between MSU/alum crystals and synthetic lipid bilayers, we found bilayers from cholesterol and other supporting lipids exhibited more significant interaction with crystals compared to control bilayers. Moreover, the same mechanism involves direct binding of membrane cholesterol was demonstrated for poly(methyl methacrylate) (PMMA) microspheres with a collaborating group in 2011 (Malik et al., 2011). To summarize, these results suggested that membrane cholesterol is responsible for non-specific ligation of solid particles, such as

MSU, alum and PMMA, to cells membranes during phagocytosis. In addition, since cholesterol is a vital component of lipid raft, they suggested that the potential involvement of lipid raft in solid particle phagocytosis. Refer to Section 4.3 for description and discussion on lipid rafts.

1.4.4.5.2 Signaling Equivalent Platform: A Hypothetical Mechanism for Particle Phagocytosis

Based on the findings described in Section 1.4.4.5.1, in 2012, Drs. Yan Shi and Wajahat

Mehal together proposed a hypothetical mechanism for solid particle phagocytosis termed

“Signaling Equivalent Platform” (Figure 1.9) (Shi, 2012).

In it, they proposed that, when membrane is engaged with solid structures, either via ligand/receptor binding or merely being stabilized by an approaching solid surface, rafts and associated proteins are sorted to high density for signaling, such sorting will lead to a shared downstream pathway with the same dependence on ITAM and Syk. In this regard, the two modes of phagocytosis are equivalent for its activation by solid structures (Shi, 2012).

Figure 1.9 Signaling Equivalent Platform A hypothetical mechanism of lipid sorting by topological reasoning: free state of lipid rafts are enriched with proteins of signaling potential, such as ITAM containing receptors. These domains are admixed with other non-raft lipids and are randomly dispersed. Packing cholesterol and sphingolipids continuously may produce a flat planar surface. However, it does not happen as it is energetically unfavorable. Upon binding of a receptor/ligand, or being stabilized by an approaching solid surface, phase separation will cluster these two lipids and drive out other species. Thus, the lipid rafts and their associated proteins are sorted to high density for signaling. To a phagocyte, the left and the right are equivalent for its activation. ITAM, immunoreceptor tyrosine-based activation motif. Reprint with copyright permission under Creative Commons Attribution License (CC BY) from Shi, 2012.

1.4.5 Signal Integration during Phagocytosis

Although different types of phagocytosis were discussed individually for better clarification, one should be mindful that, in cells, different types of phagocytic signaling occur concurrently (Freeman and Grinstein, 2014). Therefore, cooperation between pathways can be expected. On the other hand, activation without control is dangerous, the control in immune receptor signaling is put in place by ITIM-based phosphatase activities on various kinases and on

ITAM itself. Such counteraction deserves some attention. Although not discussed, it should be noted that PRRs such as TLRs also crosstalk with other phagocytic receptors (Amiel et al., 2009;

Hajishengallis and Lambris, 2011). Such signal integration, whether cooperative or counteractive, functions to fine-tune the outcome of signaling and immune response.

1.4.5.1 Cooperation between FcγR and CR3 Signals

Microscopy studies have revealed that FcγR binding to IgG-opsonized particles can promote enrichment of CR3 at the same phagocytic cup. Specifically, it was found that FcγR can provide inside-out signaling for CR3 activation (Poo et al., 1995; Zhou et al., 2001). When FcγR is crosslinked, SFK and PLCγ are recruited to the cell surface. PKC is activated downstream to phosphorylated MARCKS (Section 1.4.2.4.3) (Zhou and Li, 2000). The release of MARCKS will free CR3 from its attachment to the underneath F-actin cytoskeleton. The freed CR3s undergo lateral clustering and are found to accumulate at the FcγR-enriched phagocytic cup

(Jongstra-Bilen et al., 2003).

Furthermore, co-localization of FcγR with CR3 can enhance CR3 signals because

FcγR functions to provide a pool of available ITAMs near CR3. This was experimentally

demonstrated by the inability of FcγR lacing functional ITAM to enhance CR3 signaling (Huang et al., 2011).

1.4.5.2 Counteractions between ITAM-based Activating Signals and ITIM-based Inhibitory Signals

Regulatory mechanisms usually balance immune activation (Abbas et al., 2017).

Specifically, regarding ITAM-based immune receptor activation, phosphatases downstream of

ITIM are responsible for counteracting activating signals (Figure 1.10) (Flannagan et al., 2012).

If the inhibitory signals are insufficient spatiotemporally, the net result is immune activation, as is the case of the initial phase of most immune receptor activation. On the other hand, if inhibitory signals exceed the activating signals spatiotemporally, the net result is inhibition, as demonstrated with the inhibitory signaling in B cells (Sármay et al., 1996). Also, during homeostasis, activating signals and inhibitory signals can co-exist in dynamic equilibrium, the net results are no apparent activation, but cells remain sensitive to the change that can shift the equilibrium either way (Billadeau and Leibson, 2002). This idea of dynamic equilibrium of immune signals will be explored further in Section 6.2 to advance the concept further when the findings of this thesis is combined with other concepts and recent development in phagocytosis research.

Mechanistically, following ITIM-bearing receptor clustering by ligand binding, the ITIM is phosphorylated. It then recruits the SH2 domain-containing protein tyrosine phosphatase

(SHP) and SH2 domain-containing inositol 5-phosphatase (SHIP) to inhibit PI3K-dependent signaling by hydrolyzing PIP3 into PIP2. SHP inhibits upstream FcγR-mediated signaling at

multiple levels by dephosphorylating the ITAM of stimulatory receptors, as well as activation sites on SFKs, Syk, Vav, and PI3K (Flannagan et al., 2012).

Figure 1.10 Immunoreceptor tyrosine-based inhibition motif (ITIM)-bearing FcγRIIB- mediated Inhibitory Signaling. Upon receptor aggregation, the ITIM of FcγRIIB is monotyrosine-phosphorylated and recruits the phosphatases SHP and Src homology 2 domain–containing inositol 5’-phosphatase (SHIP). The inositol 5-phosphatase SHIP inhibits phosphatidylinositol 3-kinase (PI3K)-dependent signaling by hydrolyzing phosphatidylinositol-3,4,5-trisphosphate [PI(3,4,5)P3] into phosphatidylinositol-3,4-bisphosphate [PI(3,4)P2]. The tyrosine phosphatase SHP inhibits upstream FcγR-mediated signaling at multiple levels by dephosphorylating the ITAM of stimulatory receptors, as well as activation sites on Src-family kinases (SFKs), spleen tyrosine kinase (Syk), Vav, and PI3K (faded regions). Abbreviations: ITAM, immunoreceptor tyrosine- based activation motif; LAT, a linker of activated T cells. Reprint with copyright permission from Annual Reviews (Flannagan et al., 2012).

Such counteraction of ITIM-mediate inhibitory signals to ITAM-mediated activating signals is a recurrent theme in immunology, and its application is beyond phagocytic signaling.

Paragraphs below discuss some of these scenarios at different stages of immunity and in therapy.

Intravenous immunoglobulins (IVIGs) are used in the treatment of patients with autoimmune conditions, in which ITAM-induced activating signals is beyond health levels. It

can upregulate expression of FcγRIIB to induce inhibitory signals in B cells, macrophages and

DCs to reduce antibody production and to dampen inflammation (Aloulou et al., 2012).

NK cells express ITAM-containing activating receptors, such as CD16, alongside ITIM- containing inhibiting receptors like Killer cell Immunoglobulin-like Receptors (KIRs) (Long,

2008). The life or death of a cell engaged with NK cells are decided by the integration of the signals (Abbas et al., 2017). When an NK cell engages with a normal cell, both activating and inhibitory receptors bind to the normal cell to receive signals. Such engagement will keep the normal cell alive as the integrated signal do not reach the threshold for activation. It is important to note that inhibitory receptors engage with self class I MHC, which is downregulated in the virus-infected cells. Therefore, engagement of NK cell with a virus-infected cell leads to NK activation and killing. This is because inhibitory receptors do not bind to sufficient amount of self class I MHC to induce enough inhibitory signal to counteract the activating signal.

Therefore, the integrated signal passes the threshold for activation to allow for NK cell activation and killing (Long, 2008).

Antibody feedback is a phenomenon in which secreted IgG antibody can bind to B cell to downregulate further antibody production. IgG achieves this by forming immune complexes with antigen and then simultaneously binding to membrane Ig via antigen and binding to FcγRIIB via its Fc portion. This crosslinking brings ITIM-bearing FcγRIIB to the proximity of kinases activity. Specifically, downstream SHIP was recruited to convert PIP3 back to PIP2.

Consequently, the integrated signal is not above the activating threshold anymore. Therefore production of antibodies in response to an antigen is halted (Heyman, 2003).

1.5 Aims of this Study

As discussed in Section 1.4.4.5.2, we proposed a hypothetical mechanism for solid particle phagocytosis. The hypothesis is stated below.

1.5.1 Overarching Hypothesis

During conserved solid particle phagocytosis, solid particles can directly engage cell membrane. This engagement will cause lipid sorting and enrichment of ITAM-containing molecules at the site of contact which consequently leads to phagocytosis.

Therefore, this thesis aims to address the following major questions stated below.

1.5.2 Specific Aims

1.5.2.1 What is the ITAM-containing molecule required for solid particle phagocytosis?

To identify the ITAM-containing molecules required for solid particle phagocytosis, we generated a library of ITAM-containing molecule and ranked them according to their expression levels in phagocytes. Next, we selected top candidates and knocked them down in DC2.4, a phagocytic cell line. These knockdown cells were subjected to phagocytosis assay (Section

2.5.2) to determine if phagocytosis is impaired with gene knockdown. Once identified, we employed microscopy to determine the subcellular localization of this ITAM-containing molecule. Also, immunoprecipitation of this ITAM-containing molecule to Syk is also performed to determine the physical association during solid particle phagocytosis. This ITAM- containing molecule was determined to be moesin.

1.5.2.2 What is the lipid species sorted at the site of contact during solid particle phagocytosis?

The identity of the lipids was first proposed based on the findings detailed in Chapter 3 and previous literature on phagocytosis discussed in Section 1.4. The temporal and spatial distribution of lipids following engagement of solid particles was investigated via microscopy.

Autonomous sorting of lipids via contact was also investigated by microscopy with fluorescently labeled Giant Plasma Membrane Vesicles (GPMVs) and micropatterns. Finally, sequestration of lipids was performed with drugs to establish the necessity for such lipids during phagocytosis at the functional level as measured by phagocytosis assay. The lipid responsible for solid particle phagocytosis was determined to be PI(4,5)P2.

1.5.2.3 What are the requirements and characteristics of solid particle phagocytosis? Is it evolutionarily conserved?

First, we sought to determine the minimally essential requirements for solid particle phagocytosis via overexpression of chimeric receptors with CD4 extracellular domain and moesin ITAM in its cytoplasmic domain, in non-phagocytic cell lines to induce phagocytosis of solid particles. Next, we characterized the signaling mechanism of solid particle phagocytosis with pharmacological inhibitors/western blotting. Further, we compared the mechanism of solid particle phagocytosis with FcγR-mediated phagocytosis to determine the efficiency of phagocytosis. In addition, the involvement of the ITAM-containing molecule in SR-mediate phagocytosis was also inquired with macrophages derived from SR knockout mice and with moesin-KD DC2.4 cells. Finally, to assess the evolutionary conservation of particle phagocytosis, reconstitution studies on phagocytosis was performed with evolutionarily earlier versions of the ITAM-containing proteins. We also used bioinformatic methods and tools to

construct phylogenetic trees to determine the origin of crucial phagocytosis molecules from the solid phagocytic pathway and FcγR-phagocytic pathway, thus enabling a direct comparison to establish that solid particle phagocytosis is evolutionarily conserved.

Chapter Two: Material and Methods

2.1 Reagents

2.1.1 Antibodies

2.1.1.1 Primary Antibodies

Anti-Moesin (ab151542), anti-Ezrin (ab4069), anti-Radixin (ab52495), anti-phospho-

ERM (ab76247) were purchased from Abcam. Anti-phospho-Syk (2710), anti-phospho-PI3

Kinase P85/P55 (4228), anti-Syk (2712), anti-phospho-Erk1/2 (8544, 9101), anti-Erk1/2 (9102), anti-phospho-Akt (9271), anti-Akt (9272), anti-phospho-P38 (9211), anti-P38 (9212), anti- rabbit-IgG (7074), anti-mouse-IgG (7076) were purchased from CST. Anti-PI3 Kinase P85 (06-

195) and anti-phospho-tyrosine (05-321) were purchased from Merck. Anti-GAPDH (BE0023) was purchased from EASYBIO. Anti-Myc (M20002) and anti-Flag (M20008) were purchased from Abmart. Mouse monoclonal anti-BSA antibody (SAB200688) was purchased from Sigma

Aldrich.

2.1.1.2 Secondary Antibodies

2.1.1.2.1 Secondary Antibodies for Immunoblotting

Horseradish Peroxidase (HRP)-conjugated goat anti-rabbit IgG (111-035-003), and HRP- conjugated goat anti-mouse IgG (115-035-003) were purchased from Jackson ImmunoResearch

Laboratories.

2.1.1.2.2 Secondary Antibodies for Microscopy

Alexa Fluor 488-conjugated goat anti-rabbit IgG (A11008) and Alexa Fluor 488- conjugated goat anti-mouse IgG (A11029) were purchased from ThermoFisher. 54

2.1.2 Inhibitors

Piceatannol (527948), Syk Inhibitor (574711), Syk Inhibitor IV, BAY 61-3606 HCL

(574714), R406 (5.05819.0001), Wortmannin (681676) and LY294002 (440204) were purchased from Calbiochem.

2.1.3 Plasmids

PLCδ-PH-GFP (35142), PLCδ-PH-mCherry (36075) and Lifeact-TdTomato (54528) vectors are purchased from Addgene. Lifeact-EGFP (60112) was purchased from Ibidi. Full- length moesin and truncated moesin were constructed by cloning indicated fragments from mouse cDNA into pCAG-IRES-Neo vector (Tokuzawa et al., 2003) fused with a C-terminal

EGFP. CD4-ITAM-EGFP, CD4-EGFP were constructed by cloning mouse CD4 with or without a C-terminal ITAM from moesin, followed by an EGFP fragment. Flag-tagged full-length moesin and truncations were constructed by cloning the fragments into pcDNA3.1 fused with an

N-terminal Flag tag. 6Myc-tagged Syk was constructed by cloning mouse Syk into pCS2 with an

N-terminal 6x Myc tag. All mutated forms were generated via site-directed mutagenesis and confirmed by DNA sequencing.

2.1.4 Transfection and Transduction Reagents

Lipofectamine 2000 (11668019) was purchased from ThermoFisher. XFect (631318) was purchased from Clontech. FuGene HD (E2311) was purchased from Promega. INTERFERin siRNA transfection reagent (409-10) was purchased from PolyPlus. MISSION® lentiviral packaging mix (SHP001) were purchased from Sigma Aldrich.

2.1.5 Fluorescent Labels

2.1.5.1 Fluorescently-labeled Lipids

Bodipy FL-PI (4,5) P2 (C-45F6) were purchased from Echelon Biosciences. TopFluor

TMR-PC (810180C) and TopFluor TMR-PE (810241C) were purchased from Avanti Lipids.

2.1.5.2 Other Labels

Alexa Fluor 594 phalloidin (A12381), Alexa Fluor 488 phalloidin (A12379), Alexa Fluor

594-conjugated Streptavidin (S11227) and Alexa Fluor 405-conjugated Streptavidin (S32351) were purchased from ThermoFisher.

2.1.6 Miscellaneous

Polystyrene microspheres (19822) were purchased from Polysciences. Styrene and 55% w/w divinylbenzene (DVB) were purchased from Dongda Chemical Engineering Group Co.

Poly (vinyl alcohol) (PVA-217) was purchased from Kuraray (Japan). Benzoyl peroxide (BPO) was purchased from Beijing Chemical Reagents Company. Fast Membrane Emulsifier

(FM0210/500M) and microporous membrane were provided by Senhui Microsphere Tech

(Suzhou) Co., Ltd. Geneticin (10131027), Carestream Health X-Omat LS film (05-728-45),

NeutrAvidin (31000), EZ-Link Sulfo-NHS-LC-biotin kit (21327) and ProlongGold (P36975) mounting media were purchased from ThermoFisher. Anti-Flag M2 affinity gel (A2220), RIPA buffer (R0278) and uric acid (U2625) were purchased from Sigma-Aldrich. Protein A/G-Agarose

(A10001) were purchased from Abmart. DPBS (14190-144) and 0.25% Trypsin-EDTA

(25200056) were purchased from Gibco. An aqueous solution of 16% paraformaldehyde (PFA)

(15710) and 12 mm diameter 1-1/2 Micro Coverglasses (72230-01) were purchased from

Electron Microscopy Sciences. Bovine Serum Albumin (BSA) (ALB001.500) was purchase

from Bioshop. Biotin-BSA (A8549), Tween-20 (P9416), Triton X-100 (93443) and

SYLGARD® 184 (761036) were purchased from Sigma Aldrich. VWR Micro Slides (48382-

173) was purchased from VWR International. Maleylated BSA (MalBSA) was a gift from Dr.

Dawn M.E. Bowdish. Immun-Blot PVDF membrane (1620177) was purchased from Bio-Rad.

The ECL Western Blotting detection system (RPN2134) was purchased from GE Healthcare.

TransStart® Green qPCR SuperMix (AQ101) was purchased from Transgen Biotech.

2.2 Cell Culture

2.2.1 Cells

DC2.4 (CVCL_J409) and RAW264.7 (ATCC: TIB-71) cells were cultured in complete

RPMI-1640 medium supplemented with 10% (v/v) fetal bovine serum (FBS), 10 nM HEPES,

1% (v/v) Penicillin-Streptomycin and 0.05 mM 2-Mercaptoethanol. COS-1(ATCC: CRL-1650),

COS-7(ATCC: CRL-1651), HEK293T (ATCC: CRL-3216) and NIH-3T3(ATCC: CRL-1658) cells were cultured in DMEM containing 10% FBS and 1% (v/v) Penicillin-Streptomycin.

SR-A1-/- SR-A6 -/- double knockout (DKO) bone marrow from C57BL/6 mice was a gift from Dr. Dawn M.E. Bowdish of McMaster University. We cultured DKO and wildtype (WT) bone marrows in complete RPMI-1640 media containing 25% of L-cell conditioned medium

(LCM) to derive bone marrow-derived macrophages (BMDMs). BMDMs were harvested on day seven after the initial LCM addition for subsequent experiments.

2.2.2 Culture Conditions

Cells were incubated at 37 °C in a 5% CO2, 95% humidity incubator. Cells were detached by incubation with 0.25% Trypsin EDTA at 37 °C for 5 minutes following a brief but gentle washing step with DPBS. We routinely sub-cultured cells at 1:5 and only cells with low passage numbers (p<5) were used in all the experiments.

2.2.3 Transfection and Transduction

We employed transfection and transduction methods to overexpress or knockdown our gene of interest or knockdown (KD) in cells to study their roles in phagocytosis. Below are the specific methods.

2.2.3.1 Transient Transfection for Overexpression

2.2.3.1.1 General Transfection

Plasmid DNA transfection of easy-to-transfect cell lines was performed using

Lipofectamine 2000 as per manufacturer's protocol. Briefly, cells were seeded into tissue culture plates at an optimized density to reach 70% confluency the next day. The following day, cells were transfected with 3 L Lipofectamine 2000 per 1 g of DNA mixed in Opti-MEM. Cells were incubated with fresh media 5 hours after transfection and were used for analysis 24 hours after transfection.

2.2.3.1.2 Cell-type Specific Transfection

2.2.3.1.2.1 RAW264.7-specific Transfection

Transfection of RAW264.7 cells was performed using XFect as per manufacturer's protocol. Typically, RAW 264.7 cells were seeded into 24 well tissue culture plates at a density

of 1 x 105 cells/well in 0.5 mL complete media to reach 70% confluency the next day. The following day, cells were transfected with a mixture of 0.3 L XFect polymers and 1 g plasmid

DNA in 100 L Opti-MEM at 25 L mixture per well. Cells were incubated with fresh media 5 hours after transfection and were used for analysis 24 hours after transfection.

2.2.3.1.2.2 DC2.4-specific Transfection

Transfection of DC2.4 cells was performed with FuGene HD as per manufacturer's protocol with optimization to increase transfection efficiency and enhance cell survival after transfection. Typically, DC2.4 cells were seeded into 24 well tissue culture plates at a density of

3 x 105 cells/well in 0.5 mL complete media to reach 70% confluency the next day. The following day, cells were transfected with a mixture of 5 L FuGene HD and 1 g plasmid DNA mixture in Opti-MEM at 50 L per well. Cells were incubated with fresh media 5 hours after transfection and were used for analysis 24 hours after transfection.

2.2.3.2 Stable Transfection for Overexpression

Twenty-four hours after transfection (Section 2.2.3.1.2.2), DC2.4 cells expressing Flag-

Syk-EGFP were incubated with G418 (600 μg/ml), stable clones were picked according to their

EGFP expression after two weeks of selection.

2.2.3.3 Transient Transfection of siRNA to Knockdown Gene Expression

INTERFERin siRNA transfection reagent was used to transfect siRNA. For a typical 24- well plate format, cells were seeded into each well at a density of 1 x 105 cells/well in 0.5 mL complete media to reach 70% confluency the next day. The following day, cells were

transfected with a mixture of 0.6 pM siRNA duplexes and 2 L INTERFERin in 100 L Opti-

MEM per well. Cells were incubated with fresh media 5 hours after transfection and were used for analysis 24 hours after transfection. The table below (Table 2.1) shows the sequences of siRNAs used for transient transfection.

Gene Sequence

Csf1r GCUCUUUCUGAACCGUGUAAA

CCUACUCAGUUGCCCUACAAU

CCAUGGUGAAUGGUAGGGAAU

Fcer1g CCUACUCUACUGUCGACUCAA

CAGCUCUGCUAUAUCCUGGAU

UGAGACUCUGAAGCAUGAGAA

Hmox1 GCCGAGAAUGCUGAGUUCA

ACAGUGGCAGUGGGAAUUUAU

AGCCACACAGCACUAUGUAAA

Lcp1 GCUUUGAUGAGUUUAUCAA

GCCAAGUAGCUUCUGCUAUAA

CGAUGGCAUAGUUCUUUGUA

Msn GGACGAGACAAAUACAAGACCCUGC

GGAGCGUGCUCUCCUGGAA

CGGUCCUGUUGGCUUCUUA

Ndrg1 AACUCAUUCCUGGAAACAAA

CCUGGAAACAAACUUCUGUUU

CCUACGCUAAUGCGGUAUUAA

Tyrobp CCAAGAUGCGACUGUUCUU

GGUGUUGACUCUGCUGAUU

GGGACCCGGAAACAACACA

Table 2.1 SiRNA Sequences for Transient Gene Knockdown

2.2.3.4 Stable Transduction of shRNA to Knock Down Gene Expression

2.2.3.4.1 Lentiviral Packaging

Lentiviral particles producing moesin, ezrin, radixin and negative control shRNAs were packaged as per manufacturer’s instructions. HEK293T cells were seeded onto a 100 mm culture dish at a density of 1×106 cells per dish in 10 mL complete DMEM. The following day, the cells were transfected with a 182 µL cocktail mix of 26 µg lentiviral packaging mix and 2.6 µg gene- specific transfer vectors alongside 16 µL FuGene HD transfection reagent diluted in Opti-MEM.

Old media were replaced with pre-warmed fresh media 16 hours post-transfection. Viral particles were harvested twice at 48 and 72 hours post-transfection and they can be stored at -70 °C for future use.

2.2.3.4.2 Viral Transduction and Selection of Cells

DC2.4 cells were infected with lentivirus packaged by moesin, ezrin, radixin and negative control shRNAs. Forty-eight hours post-infection, cells were cultured in complete

RPMI containing puromycin (1 μg/ml) and cells were cultured in fresh medium every two days.

One week after the initial addition of puromycin, single clones were picked, and the knockdown efficiency at the protein level was evaluated via western blotting.

2.3 Molecular Biology

2.3.1 Real-time PCR

Real-time PCR (RT-PCR or quantitative PCR, qPCR) was performed as per the instructions of TransStart® Green qPCR SuperMix protocol to check expression levels of genes.

The table below shows the sequences of primers used for real-time PCR (Table 2.2).

Sense Antisense

Msn 5’-TCCCAGTTGGAAATGGCTCG-3’ 5’-GCTCTGCCACATGAGGTGTA-3’

Ezr 5’-ACAGCAGTTGGAAACCG-3’ 5’-GGCCTCCAGACGTTCAG-3’

Rdx 5’- CTCTTACCACAGCGTGTTTTGG-3’ 5’-TTCCCTTAGCATCCCTCTGTGT-3’

Merlin 5’-CATACCGAGCTTCGACATTAT-3’ 5’-CTTGCTCTTCTCCATGTACTC-3’

Frmd4a 5’-CAACGAGAACCGCATCAA-3’ 5’-GTCTTCGCTGGCGATATTT-3’

Frmd4b 5’-GGGACCACGTTCAAGTTAG-3’ 5’-CAACCAGCTTCTGCTGTAT-3’

Csf1r 5’-CATGGCCTTCCTTGCTTCTAA-3’ 5’-TGCCGTAGGACCACACATCA-3’

Fcer1g 5’-ATATCCTGGATGCTGTCCTG-3’ 5’-TCTCATATGTCTCCTGGCTC-3’

Hmox1 5’-GAATCGAGCAGAACCAGCCT-3’ 5’-CTCAGCATTCTCGGCTTGGA-3’

Lcp1 5’-ACTGAGAATTCAAGTCTGTCACCT-3’ 5’-AGCTGATGTATCCGTTGCCA-3’

Ndrg1 5’-CCTCAACGACATGAACCCGA-3’ 5’-TGCAAAGTGACAGTGTGGGT-3’

Tyrobp 5’-GAAGGGACCCGGAAACAACA-3’ 5’-CTGATGGGCATAGAGTGGGC-3’

Table 2.2 Primers for RT-PCR

2.3.2 Western Blotting

For each sample, 107 cells were lysed with RIPA buffer. Total proteins were subjected to sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). Following SDS-

PAGE, proteins were transferred to Immun-Blot PVDF membrane from gels at 100 Volts for 60 min in western blot transfer buffer (30 g/l Tris, 14.4 g/l glycine, 20% methanol in H2O) (Towbin et al. 1979). The membrane was then blocked at 4 oC in blocking buffer (4% fat-free milk powder, 0.1% Tween in TBS) for one hour and then incubated overnight in blocking buffer containing indicated primary antibodies with dilutions ranging from 1:200 to 1:1000. The

membrane was washed three times in 0.1% Tween in TBS, before incubation with HRP- conjugated anti-rabbit/mouse secondary antibodies (dilution 1: 100,000) for another hour.

Finally, the membrane was washed three times in 0.1% Tween in PBS and developed using the

ECL Western Blotting detection system onto Carestream Health X-Omat LS film.

2.3.3 Co-immunoprecipitation

For co-immunoprecipitation, the antibodies against one protein in the protein complexes were incubated with Protein A-Sepharose beads for 1 hour at room temperature. This is followed by further incubation with cell lysates from 1×107 cells for 4 hours at 4℃. Immunocomplexes were washed four times with RIPA buffer and eluted from Protein A-Sepharose beads with SDS in SDS-PAGE loading buffer via boiling at 95 oC for 5 minutes before resolved by Western

Blotting (Section 2.3.2). Other interacting partners in the protein complexes were probed with specific antibodies against those proteins.

2.4 Fluorescence Microscopy

2.4.1 Immunofluorescence

Typically, cells were seeded onto microscopy coverslips of 12 mm in diameters pre- loaded onto each well of a 24-well tissue culture plate at 1x 105 cells per well in complete media overnight. For immunofluorescence staining, cells were fixed with 4% paraformaldehyde (PFA) for 10 minutes at room temperature followed by three repeated washes with PBST (PBS with

0.1% v/v Tween-20) for a total of 15 minutes. Next, unless otherwise indicated, cells were permeabilized with 0.1% Triton-X100 for 3 minutes at room temperature. After being rewashed

3 times with PBST, cells were blocked with 5% (w/v) bovine serum albumin (BSA) in PBS for 1

hour at room temperature to minimize non-specific binding of antibodies. After blocking, cells were incubated with primary antibodies at 4°C overnight. The next day, cells were rewashed for three times and incubated with fluorescently-labeled secondary antibodies (Section 2.1.1.2.2) at

1:2000 dilution and fluorescently-labeled phalloidin (Section 2.1.5.2) at 1:200 dilution at 37°C for 30 minutes. Finally, cells were mounted with 7 µL ProlongGold mounting media for each coverslip to microscopy slides and cured for 24 hours before subjected to fluorescence microscopy.

2.4.2 Microscopy

The discussion within this section is confined to fluorescence-based light microscopy due to the overwhelming involvement of light microscopy and limited utilization of other microscopic methods like Electron Microscopy (EM) and AFM during the development of this thesis.

2.4.2.1 General Considerations for Performing Good Microscopy

2.4.2.1.1 Preamble

This section serves as a brief and practical guide for performing good microscopy, and it is based primarily on the author’s practical experience with microscopy. For a good understanding on different microscopic methods with an in-depth explanation regarding underlying theories with technical details, I refer readers to the review paper by Fisher and colleagues (Fischer et al., 2011). Also, the Handbook of Biological Confocal Microscopy

(Pawley and Masters, 2008) is a generally acclaimed and detailed technical resource for microscopic imaging. Finally, websites created by microscopy manufacturers Nikon and

Olympus both provide excellent JAVA-based interactive tutorials on different aspects of microscopy. Specifically, I refer readers to the Microscopy Resource Center

(http://olympus.magnet.fsu.edu/) by Olympus with Florida State University and MicroscopyU

(https://www.microscopyu.com/tutorials) by Nikon.

A perfect microscopic method would produce images of high spatial and temporal resolutions from any given sample. However, in practice, such microscope does not exist at least in a generally applicable, universally accessible manner. Therefore, one must first decide the degree of trade-off between the spatial and temporal information collected and whether that information is sufficient to answer the biological questions.

2.4.2.1.2 Fluorescence Microscopy: A Simple Overview

It is helpful to lay out the big picture of fluorescence imaging in simplistic terms before further discussion as the readers can refer to this section to track where along the microscopy process does any specific discussion concern in the following sections. During fluorescence imaging, fluorophores are raised to an excited state with a lamp or laser first. Next, photons are emitted from the fluorophores while they return to their ground state. A portion of the emitted photons can enter the objective lens and are focused towards a detector. When a photon strikes a detector, it has a chance to be registered as a hit, and this is determined by the quantum efficiency (See Section 2.4.2.1.3.1) of a detector. Such hit will cause the release of an electron.

Finally, the charges are quantified as pixel values after a fixed time period. Therefore, on the fluorescence images, higher pixel values correspond to more photons, which originates from the fluorophores and later focused towards the detector, collected for such pixel (Bankhead, 2014).

2.4.2.1.3 Main Properties Concerning Microscopy

Three important properties should be considered when choosing the suitable microscope: sensitivity, speed, and phototoxicity (Thorn, 2016).

2.4.2.1.3.1 Sensitivity

First, sensitivity determines how much information in the form of light can be collected by a microscope for a given fluorophore after excitation. This is influenced by choice of objectives and detectors used. For example, microscopes are generally equipped with array detectors such as Charge-Coupled Device (CCD) and Electron Multiplying CCD (EMCCD) cameras or with point detectors such as Photomultiplier Tube (PMT) (Pawley and Masters,

2008). These detectors provide different levels of sensitivity depending on specific applications.

Therefore, it is advisable to consult the manufacturer's specifications. One critical property of the detectors regarding sensitivity is quantum efficiency (QE), it is defined as the probability of generating of a photoelectron from an incident photon by a detector (Pawley and Masters, 2008).

Thus, QE determines the devices’ photoelectric sensitivity to light. Also, the higher the numeric aperture (NA) of an objective, the more light can be collected (Pawley and Masters, 2008).

Higher NA also leads to better lateral (rxy) and axial (rz) resolution, as the resolutions are

2 theorized to be rxy = 0.61λ/NA and rz = 2λn/NA , respectively, as defined by Rayleigh Criterion

(Pawley and Masters, 2008), where n is the refractive index of the objective lens immersion medium and λ is the emission wavelength. Spatial resolution is important because it measures how close two structures can be before they become indistinguishable. By Rayleigh Criterion, two equally bright spots are said to be resolved if they are separated by the distance calculated from rxy and rz. It is important to note the effective lateral and axial resolutions vary from one

imaging system to another due to inherent differences in Point Spread Function (PSF) and noise alongside other factors (Pawley and Masters, 2008). PSF is a very important concept in microscopy. Refer to Section 2.4.3 for a simple introduction to this concept. Nevertheless, it is sufficient to know that NA has a much more significant impact on axial resolution than lateral resolution. To get better resolving power to enable optical sectioning for 3D reconstruction of fluorescence microscopy images, higher NA is required.

2.4.2.1.3.2 Speed

Second, speed determines how fast a microscope can capture an image. Thus, higher speed of an imaging system corresponds to less acquisition time and, consequently, better temporal resolution. The spatial resolution provided by an imaging system should be evaluated case by case with considerations on temporal resolution and photobleaching. For example, during confocal microscopy, one can increase the laser power to reduce the acquisition time.

However, this is done at risk with the samples being photobleached very quickly. In very general terms, widefield microscope equipped with CCD or EMCCD cameras tend to capture the same image faster than a confocal or multiphoton microscope with a PMT detector because cameras capture the entire field as one single frame while PMT detectors scan the field point-by-point. To improve the speed of confocal microscopy, one can select a relatively small region of interest

(ROI) and only scan for that region. This can significantly reduce the time for image acquisition.

This is particularly useful when the location of cell or structure of interest is known. For example, when we image phagocytosis in action, only cells with beads attached are of interest.

Further, using an array of pinholes, Spinning-Disk Confocal Microscopy (SDCM) can improve

temporal resolution while maintaining the same optical sectioning capability of a traditional confocal microscope (Fischer et al., 2011).

2.4.2.1.3.3 Phototoxicity

Third, phototoxic effects and the severity of photobleaching vary among different microscopic methods depending on the type and, more importantly, the power of illuminating light. For example, a laser with a shorter wavelength is more phototoxic than a laser with longer wavelength with the same laser power output. This is more of an issue for live cell microscopy than for fixed cells. During live cell microscopy, excessive exposure to light can cause the irreversible destruction of fluorescent proteins and reactive oxygen species (ROS) produced from such process can further cause damage to a cell via oxidative stress. Also, it is widely known that illumination from UV (405 nm) laser can cause DNA damage in a cell by inducing crosslinking and formation of thymine dimers (Martinez-Fernandez et al., 2017). Those damages can consequently induce cell death via apoptosis (Lee et al., 2013). This can be visually observed during live cell imaging under suboptimal conditions. Cells will display membrane blebs when exposed to excessive amount of light. Therefore, it is crucial to experimentally determine if the power of light and the time of illumination is tolerable for one’s sample. One can experimentally determine the actual power hitting the sample with a power density meter placed directly above

(in the case of an inverted microscope) the objective lens in place of the sample. In our laboratory, we use a handheld PM100 Digital Power and Energy Meter Console from Thorlabs to determine power density when troubleshooting photobleaching issues.

2.4.2.1.3.4 Concerns about Sensitivity, Speed, and Phototoxicity during Sample Preparation

Although the above paragraphs discussed how to choose the right microscope with an acceptable level of sensitivity, speed, and phototoxicity from the hardware perspective, attempts should also be made to improve these properties by choosing a good fluorophore during sample preparation. For example, choosing a brighter fluorophore will benefit both sensitivity and speed as more light can be collected compared to a dimmer fluorophore. Specifically, brightness is given as n×ε×φ, where n is the number of fluorophores per molecule, ε is the extinction coefficient of the fluorophore and φ is the quantum yield of the dye (Pawley and Masters, 2008).

Extinction coefficient measures the light-absorbing capacity of a dye. Therefore, fluorophores with higher extinction coefficient are preferred as more light can be absorbed. On the other hand, quantum yield measures the fluorescing capability of a dye as it is the ratio between the number of fluorescence photons emitted and the number of photons absorbed (Pawley and Masters,

2008). In addition, the emission wavelength of a fluorophore is also an important factor.

Detectors on different microscopes will have different spectral sensitivity, meaning that QE (see

Paragraph 4 of this section) is different for different wavelength. Therefore, it is ideal to match the emission spectra of a fluorophore to the spectral sensitivities of a given detector to maximize detection. Some systems also offer a spectral detection mode in which signals are collected over the entire spectrum, and a series of images are generated for visual comparison of fluorescence intensities. This is an elegant solution which helps to determine the best range of wavelength to collect signals from. For fluorescent proteins, these parameters can be found at http://www.fpvis.org/FP.html when choosing a dye with good brightness properties and good photostability. The figure below shows the comparison of the brightness against the photostability of a fluorophore for all fluorescent proteins curated in the database. For example,

tdTomato, a red dye that is extremely bright but not very photostable, is suitable for rapidly- developing processes such as phagocytosis (typically finishes within 5 minutes since initial contact), as it can provide high temporal resolution and adequate spatial resolution. On the other hand, mStable, a far-red dye that is extremely photostable (almost 10 folds higher than tdTomato) but very dim (less than 8% of the brightness of tdTomato), is suitable for less rapidly changing process such as cell division, as it enables imaging over an extended period of time

(e.g., overnight). Also, to prevent photobleaching and phototoxicity during live cell imaging, we avoid using fluorescent proteins with excitation wavelength around the UV range, to begin with.

Further, Prolong Live Antifade Reagent (P36974) and Live Cell Imaging Solution (A14291DJ) from ThermoFisher were used during live cell imaging to prevent photobleaching as the reagents presumably contain oxygen scavengers to prevent irreversible oxidation and eventually destruction of fluorescent proteins (Bogdanov et al., 2009).

Fluorophores are not only limited to fluorescent proteins (Specht et al., 2017). If cells are fixed, then the temporal resolution is no longer a concern. Organic dyes are typically used as they are bright and stable. Alexa Fluor and DyLight series organic dyes are two excellent sources. Also, quantum dots (Qdots), made from nanoscale semiconducting materials, are far brighter and more stable than organic dyes. They are preferred in applications such as single particle tracking (SPT) for their superior brightness and photostability (Shen et al., 2017).

Figure 2.1 Fluorescent Protein Properties.

2.4.2.1.4 Signal-to-Noise Ratio

Ultimately, a good fluorescent microscopic image is one that balances temporal and spatial resolutions while maintaining a high signal-to-noise ratio (SNR) (Pawley and Masters,

2008). SNR is important because it directly measures the contrast of an image, and contrast plays into resolution. For example, when SNR is low, the noise is high. Thus, the necessary distance

(refer to paragraph 4 of this section for the definition of spatial resolution) to resolve two points in an image is increased (Bankhead, 2014). This means the spatial resolution is decreased when

SNR is low. SNR is expressed as S/N, where S is the signal detected by a detector and N is the total noise (Pawley and Masters, 2008).

2.4.2.1.4.1 Signal

The signal is expressed as I×QE×T, where I (photons/second) is the input light level, QE

(electrons/photon) is quantum efficiency as discussed in the fourth paragraph of this section, and

T (second) is the integration time. Therefore, strategies to increase signals can include increasing light input, choosing a more sensitive detector and increasing integration time via decreasing scanning speed when working with a point detector or increasing exposure time when working with an array detector (Pawley and Masters, 2008). It is worth noting here that increasing integration time to improve SNR is one example of the many trade-offs in microscopy in which temporal resolution is sacrificed for better SNR. We will also see other trade-offs in the following discussions.

2.4.2.1.4.2 Noise

On the other hand, there are two major types of noise associated with microscopy. These include signal noise and camera noise. Signal noise, also called photon noise or shot noise, is the inherent and the most important noise. It represents random fluctuation in the signal. This fluctuation, or statistical variation, is the result of the particle nature of light and the stochastic fluctuation in photon arrival times at the detector, and it follows a Poisson distribution in a signal-dependent manner. It is equivalent to the square-root of the signal at the local pixel.

Therefore, SNR can be simply reduced by increasing the signal itself. One can imagine there will be some trade-offs between spatial resolution and phototoxicity to find the sweet spot for SNR.

Camera noise can be further divided into readout noise and dark noise. Readout noise represents the errors as the chip is read. It originates from the inaccuracies in quantifying the number of photons being detected. Such noise follows a Gaussian distribution in a signal-independent

manner (Pawley and Masters, 2008). In other words, readout noise is constant for every pixel across the image, and it will not accumulate over time. Therefore, readout noise can be reduced by reading the chips more slowly. Thus, again, one can imagine there has to be trade-offs between temporal resolution and SNR. Dark noise, sometimes called thermal noise, arises from statistical variations in the number of electrons, but not photoelectrons, thermally generated within the detectors regardless the presence of photons (Pawley and Masters, 2008). Thus, one can image such noise can build up over time following generation of heat from device during imaging. Therefore, one can reduce dark signal by cooling the chip to reduce heat.

2.4.2.1.4.3 Methods for Improving SNR

Practically speaking, SNR can be improved at different stages of microscopy. First, if applicable, when building a microscope, a detector with high QE and a cooling system should be considered to increase signal and decrease dark noise. However, the cost can be prohibitive.

Second, during sample preparation, staining should be optimized to make samples as bright as possible. Also, the photostability of fluorophores should be considered. Together, they help increase signals and minimize the effect of photon noise. Third, during acquisition, excitation intensity can be increased to enable collection of more photons to increase signal. However, saturation should be avoided, and phototoxicity is another concern. To alleviate concerns with saturation and phototoxicity, repeated registration of the same field with lower excitation intensity are performed. This helps reduce the effect of phototoxicity as small doses of less intense light are less harmful to fluorophores than more intense light in one big dose for the same amount of radiation. Such accumulation of multiple scans of the same field combined with image averaging can help optimize SNR. As an extra consideration for confocal microscopy, the

optimal size of pinhole should be determined to reach the best SNR possible. The default setting is usually a good starting point (Kakade et al., 2016). Fourth, post-acquisition, 3D deconvolution can be used to improve the SNR of an image. Images presented in this thesis, are all z-stacked images except for the SIM images were 3D deconvolved to improve SNR. 2D deconvolution is also performed for time-lapse, non-z-stacked images to improve SNR. One should bear in mind that 2D deconvolution is more of a “cleanup” method and the improvement on images are marginal compared to 3D deconvolution. See Section 2.4.3 for description deconvolution and how it relates to PSF.

2.4.2.1.5 Other Practical Concerns for Microscopy

Other practical concerns include accessibility, ease-of-use, cost, and focal drift during live cell imaging. In fact, accessibility to microscopes should be first determined. During this thesis, the most frequently used microscopes are the ones housed in our own laboratory, as human factors are minimized compared to working with a core facility. Also, easy-of-use varies between different imaging systems. Practice and a few non-costly mistakes can help overcome this. Further, the cost to build/purchase and maintain a microscope in-house or an hourly rate to use a microscope in a core facility should be considered if budget is concerned. For example, detectors are costly part of a microscope. A detector with a cooling system to reduce dark noise is usually much more expensive than a detector without a cooling system. Thus, one must determine if the added extra cost to improve SNR is justified. This can be done by requesting a demo from the manufacturer to determine for oneself if the new detector is really needed.

Finally, for live cells, samples can drift out of focus during time-lapse imaging due to turbulence in heat or other imperfections relating to the mechanical setup of a microscope. This is called

focal drift. This can be circumvented via the use of commercial heat stage. The Olympus IX-73 microscope and Nikon A1R microscope used in this thesis are both equipped with commercial customized thermal stages from Tokai Hit. The heat stages are usually turned on and used 30 minutes after the temperature of the stage becomes stable. In addition, some microscopes can correct such drift at the hardware level. Perfect Focus System (PFS) from Nikon is one such solution.

2.4.2.2 Summary

To summarize Section 2.4.2, a good fluorescent microscopic image is one that balances resolution and contrast. The resolution includes temporal and spatial resolutions while contrast is characterized by SNR. Three major properties are concerned for fluorescence microscopy: sensitivity, speed, and phototoxicity. Among them, sensitivity impacts spatial resolution while speed determines temporal resolution. Phototoxicity and photobleaching affect both spatial and temporal resolution. Moreover, SNR characterizes the quality of measurement and the ultimate performance of an imaging system. It can be influenced by sensitivity, speed, and phototoxicity.

Trade-offs must be made when balancing spatial resolution, temporal resolution, and SNR when manipulating sensitivity, speed and phototoxicity properties. Therefore, it is critically important to establish from the beginning of an experiment or even project what constitutes an acceptable image. Perhaps the lyrics from the song You Can’t Always Get What You Want from The Rolling

Stones best summarize microscopy: You can't always get what you want. But if you try sometimes, you might find. You get what you need.

The sections below discuss the usage of different microscopy methods for this thesis.

The parameters mentioned in these sections for different microscopy methods was optimized experimentally so that the images with good resolution and SNR could be obtained.

2.4.3 Different Microscopy Modalities used for this Thesis

2.4.3.1 Widefield Microscopy

We employed widefield microscopy to collect images for phagocytosis assay (Section

2.5.2) for fixed cells because it provides enough spatial resolution. Also, time-lapse microscopy was performed on cells to study the process of phagocytosis. Widefield microscopy was chosen because they provide better temporal resolution besides easy accessibility. Image acquisition was performed with an Olympus IX-73 microscope in our laboratory located at the University of

Calgary or a home-built microscope in our laboratory located at Tsinghua University. Oil- immersion Olympus UplanFLZ Objective 100X with 1.0 zoom, NA=1.31, pixel size=108 nm, Z stack distance= 0.5 µm, image size = 2048*2048 pixels. Camera exposure time varies from 40 ms to 600 ms depending on the brightness and photostability of fluorescence dyes.

2.4.3.2 Confocal Microscopy

We employed confocal microscopy to collect images from lipid sorting analysis with solid particles (Section 2.6.1) for fixed cells or solid patterns (Section 2.6.2) for GPMVs. Image acquisition was performed with Nikon A1R +, a scanning confocal system in Live Cell Imaging

(LCI) facility located at the Snyder Institute of University of Calgary. We choose the Nikon

A1R+ confocal microscope for two main reasons. First, for these experiments, the better spatial

resolution is favored for further quantification and possible 3D reconstruction. Second, we have experimentally determined that the Nikon A1R+ be the best system that protects our sample from photobleaching since the fluorophore available to us for these experiments suffers from photostability issues with widefield microscopes. This is important because it allowed imaging of entire z-stack to enable optical sectioning. Oil-immersion Nikon Plan Apochromat λ Objective

60X with 1.0 zoom, NA=1.40, pixel size=60 nm, Z stack distance=0.3 µm, image size=1024*1024 pixels at 250 Hz scanning speed with 2-line averaging while maintaining the pinhole at the default size of 35.76 µm. Laser power varies between 0.5%-30% of the maximum output for any given channel depending on the brightness and photostability of fluorophores.

2.4.3.3 Structured Illumination Microscopy

Structured illumination microscopy (SIM) was performed on and ELYRA-coupled Carl

Zeiss LSM780 microscope to capture super-resolution images for experiments involves phagocytic cups. We chose this method because the higher spatial resolution is needed to enable

3D reconstruction to reveal the fine detail regarding the spatial arrangement of molecules at the phagocytic cup. The grid size was used in the default setting recommended by the vendor, and the number of rotations was 5. Dr. Pascal Detampel acquired images with my input due to restricted accessibility by external personnel. Plan Apochromat DIC M27 Oil-immersion Carl

Zeiss Objective 63X with 1.6 zoom, NA=1.40, pixel size=40nm, Z stack distance=0.11 µm, image size=2048*2048 pixels. Laser power varies between 0.5%-15% of the maximum output for any given channel. Camera exposure time was set at 50 ms to 100 ms depending on the brightness and photostability of fluorophores.

2.4.4 Image Processing and Analysis

For a better understanding of the principles and applications of digital image processing, I strongly recommend the book Analyzing fluorescence microscopy images with ImageJ by Dr.

Peter Bankhead, which is accessible at goo.gl/egHSwq free of charge. I adhered to all the principles of digital image processing laid out in his book during image processing and analysis.

For example, quantification of fluorescent intensities was completed only on raw images while processed images with better SNR can be used for display (Bankhead, 2014).

2.4.4.1 Deconvolution and PSF

Images from Olympus IX-73 microscope were deconvolved with CellSens software with known PSF calculated by Olympus. Images from the home-built TIRFM were collected with

MicroManager and processed in FIJI (Fiji Is Just ImageJ) before they can be deconvolved with

Autoquant X with blind PSF estimation from collected data. FIJI is an ImageJ variant with many powerful plugins. Confocal images were processed and deconvolved with Nikon NIS Elements software with known PSF from Nikon. SIM images were processed first with Zen software for calculation and channel alignment. Further deconvolution is not necessary for super-resolution images as SNR is high enough after initial processing with the Zen software.

This paragraph seeks to give a simple explanation of what PSF is and its importance relating to deconvolution (Pawley and Masters, 2008). Our molecules of interest are typically labeled with fluorescent probes such as proteins or organic dyes ranging from 0.5 nm-10 nm in diameter. These fluorescent probes are small enough to behave as point sources of light. Thanks to the wave nature of the light, when the light is emitted from a point source, it will form a diffraction pattern that spreads across multiple pixels as opposed to a single pixel. In 3D space,

light from a single point spreads into a larger volume and is dependent on specific optical systems. Such large volume is known as the PSF. PSF is a mathematical function that describes how light, from a single point, spread into a large volume on an optical system. In other words,

PSF describes the distribution of light from the point source for a given optical system. Due to the property of light in which light emitted from a single point cannot be focused back to a single pixel on an image, raw images acquired on any diffraction-limited optical system is said to be blurred. Blurring can be described mathematically by a process called convolution. Therefore, deconvolution represents a method of deblurring in which deblurred images are calculated from raw images with known or estimated PSF. Therefore, it is essential to know or be able to estimate PSF for deconvolution. PSF is usually known for a commercial system as previously determined by manufacturers. Deconvolution is usually faster with known PSFs. On the other hand, PSF can be estimated by fitting PSF into input images through iterations. Such blind deconvolution usually takes a longer time (Krishnamurthi et al., 1995).

2.4.4.2 Other Image Processing Methods

Line profile analysis was done with Autoquant X or FIJI. A line is drawn across an ROI, and pixel values were quantified and presented along with the line. This method is performed to determine the difference in concentrations for our molecule of interest as probed by fluorescent proteins or organic dyes at different space. Kymograph analysis and all fluorescence intensities were measured with FIJI. Briefly, a line is drawn across an ROI, and pixel values were quantified and presented along with the time axis. This method is performed to determine the change in the concentrations for our molecule of interest as probed by fluorescent proteins or organic dyes over time at given space. 3D reconstruction of fluorescence images was done with

Imaris 7.2.3. Briefly, an ROI, such as a phagocytic cup, was chosen and 3D surfaces were rendered by the software according to their original pixel values with other inputs. This method is performed to determine the spatial arrangement of different molecules of interest as probed by fluorescent proteins or organic dyes.

2.5 Phagocytosis

2.5.1 Preparation of Solid Particles

2.5.1.1 Surface Coating of Proteins to Polystyrene Beads

Proteins were coated on polystyrene beads per technical data sheet 238E from

Polysciences. Briefly, 0.5 ml of the stock beads were washed with 0.1 M borate buffer (pH=8.5) three times before incubation with 400 µg proteins overnight at room temperature with gentle end-to-end mixing. Next, beads were washed with PBS buffer three times after being centrifuged for 10 mins. Finally, beads were resuspended in 1 ml PBS buffer and stored at 4°C.

To coat the surface of beads with biotin, 0.5 ml of the stock beads were incubated with

200µ g biotin-BSA. To coat the surface of beads with IgG, beads were coated with 200 µg BSA and then with 200 µg mouse anti-BSA IgG to expose the Fc fragment.

2.5.1.2 Making Uniform Polystyrene Beads with Tunable Rigidity

Premix membrane emulsification technique and FMEM-500M equipment were used to prepare oil in water emulsion. Different percentages of the crosslinking agent were used to tune the polystyrene microparticle rigidity. In a typical process, 9 g styrene as monomers, 0.43 g

BPO as initiator (4.3 wt. % of total monomers), and 1 g DVB or other dosages (10-90% w/w of total monomers) were commingled together and used as the oil phase. Deionized water (150 ml)

containing 1% w/w PVA was used as water phase. The oil phase and water phase were mixed by low-speed stirring and poured into the premix silos. Next, this coarse emulsion was extruded through the microporous membrane under a nitrogen gas pressure. The preliminarily emulsified emulsion was extruded through the same membrane as coarse emulsion in the next pass. We obtained the final emulsion after repeating the above process for three times. Such emulsion was transferred to a four-neck glass separator flask equipped with a semicircular anchor type blade, a condenser, and a nitrogen inlet nozzle. The emulsion was bubbled with nitrogen gas for one hr.

Then, the nozzle was lifted, and the temperature was increased to 70 oC in small increments. The polymerization was carried out for 20 hours under nitrogen atmosphere. At this stage, the preparation contains a mixture of single microparticles varying in size from 1 µm to 9 µm and unreacted chemicals. This preparation was washed with hot water then ethanol for four times to eliminate unreacted chemicals to minimize potential toxic effects from manufactured polystyrene beads. Finally, beads of uniform size around 3 µm among different rigidity levels were obtained via flow-activated cell sorting (FACS) with PolySciences 3 µm as the positive control for size selection.

2.5.1.2.1 Characterization of Rigidity via Nanoindentation

We probed the rigidity of single polystyrene microparticles with different degrees of cross-linking with an atomic force microscope (Veeco BioScope Catalyst, USA). Briefly, the microparticles or bead solution diluted with ethanol was dipped on the surface of a clean glass substrate. These beads adhered to glass surface primarily due to the capillary force. The topography of the surface was first scanned in tapping mode with a stiff probe (Veeco TESPA, spring constant 20-80 N/m, resonant frequency 230-320 kHz) and the location of individual

beads were then identified for force-indentation displacement probing. The force applied for indentation ranged from 100 -1500 nN. The observed indentation depth was less than 10 nm, about 0.3% of the size of beads. The same beads were probed three times, and at least 12 beads were investigated for each sample. The rigidity (Young’s modulus) of these beads was obtained through indentation analysis based on Herzt model with a Poisson ratio of 0.33 for bulk polystyrene using the native Veeco analyzing software.

2.5.2 Phagocytosis Assay

Cells were seeded into 24 well plates at 105 cells/well the night before the experiment.

Biotin-BSA-coated beads resuspended in Opti-MEM at 1:1000 (v/v) were centrifuged to the bottom of the dish at 930 g for three mins at 4°C. For typical 3 µm beads, this theoretically corresponds to roughly five beads per cell on average. Cells were chilled on ice for five mins before being moved into a 37°C, 5% CO2 incubator to synchronize phagocytosis. Cells were incubated with beads for indicated durations. Cells were then moved from the incubator and washed with PBS buffer once before 4% PFA fixation for 10 minutes. After fixation, cells were directly labeled with 1:200 Alexa Fluor405-Streptavidin for 30 minutes on ice without permeabilization, thus differentiating uninternalized (with fluorescent label) beads from internalized (without fluorescent label) beads (Figure 2.2a). Next, samples were examined with microscopy under brightfield and fluorescent channel. For each cell, the number of cell- associated beads was counted with brightfield as nall whereas the number of positively stained beads were counted with the fluorescent channel as nout (Figure 2.2b). Therefore, the phagocytic efficiency for each bead is calculated as: Beads internalized (%) = (nall - nout) / nall. For each technical repeat, at least 50 cells were counted to obtain summary statistics.

(a) (b)

Figure 2.2 Schematic of Phagocytosis Assay (a) Cells were directly labeled without permeabilization, thus differentiating uninternalized (with a fluorescent label) beads from internalized (without fluorescent label) beads. (b) Samples were examined with microscopy under brightfield (left) and fluorescent (right) channel. For each cell, the number of cell-associated beads was counted with brightfield as nall whereas the number of positively stained beads were counted with the fluorescent channel as nout (Figure 2.2b). Therefore, the phagocytic efficiency for each bead is calculated as: Beads internalized (%) = (nall - nout) / nall. For each technical repeat, at least 50 cells were counted to obtain summary statistics.

2.6 Contact-related Assays

2.6.1 Lipid Sorting Analysis on Live Cells with Beads

Cells are grown on glass-bottom FluoroDish at 37 °C in a 5% CO2 humidified chamber and loaded onto microscopy stage following transfection of PLCδ-PH-GFP or TopFluor TMR-

PC and TopFluor TMR-PE to fluorescently visualize lipids. Next, we delivered a naked 6µm polystyrene bead glued to an AFM cantilever by Epoxy to a cell surface with 1nN constant force.

Finally, fluorescence images of cells in contact with beads were recorded for analysis (Figure

2.3).

Figure 2.3 Schematic of Fluorescence Imaging of Bead/Cell Contact A 6µm polystyrene bead is glued to an AFM cantilever by Epoxy. The cell is cultured on a glass- bottom dish ready for imaging. AFM cantilever with bead approaches the bead at a constant force of 1 nN until it touches the cell. Fluorescence images were then recorded.

2.6.2 Lipid Sorting Analysis on GPMVs with PDMS Micropatterns

2.6.2.1 Micropatterns Design

Micropatterns were designed in AutoCAD 2017. Several considerations were given when designing such micropatterns. First, basic topological structures such as triangle, square, circle, cross and strait were chosen as the basic structural units of micropatterns to study the potential impact of shapes on phagocytosis. Second, micropatterns with different sizes, spacing, and alignment were designed to potentially study for the effect of size on phagocytosis (Table

2.3). Overall, a total of 64 1mm*1mm squares with a unique pattern, size, spacing and alignment as 8*8 squares and fit into a 1cm*1cm square for subsequent fabrication (Figure 2.4).

Figure 2.4 Micropatterns Design with Basic Topological Structures, Sizes, Spacing, and Alignments. This graph shows the entire design and layout of micropatterns with different basic topological structures, sizes, spacing, and alignment. This design consists of a total number of 64 1mm*1mm squares with the defined pattern, size, spacing, and alignment fit into a 1cm*1cm square for subsequent fabrication. A full-resolution design can be accessed at https://goo.gl/ywnHm2.

C Parameters (µm) 1 2 3 4 5 6 7 8 R 1 Diameter 3 3 N/A N/A N/A N/A N/A N/A

Within-sample horizontal 3 3 2.1213 2.1213 2.5981 3 5.6569 3 distance Within-sample vertical 3 3 2.1213 2.1213 2.25 998 5.6569 998 distance Between-sample horizontal 1.5 4.5 1.0607 3.1816 1.299 3 3.3431 6 distance Between-sample vertical 1.5 9.9405 1.0607 7.1086 1.6471 N/A 3.3431 N/A distance 2 Diameter 3 3 N/A N/A N/A N/A N/A N/A

Within-sample horizontal 3 3 2.1213 2.1213 2.5981 2.5981 5.6569 5.6569 distance Within-sample vertical 3 3 2.1213 2.1213 2.25 2.25 5.6569 5.6569 distance Between-sample horizontal 4.5 4.5 3.1816 1.0607 3.8972 1.9019 9.3431 3.3431 distance Between-sample vertical 4.5 7.7763 3.1816 3.4026 4.2453 5.5078 9.3431 9.8431 distance 3 Diameter 3 3 N/A N/A N/A N/A N/A N/A

Within-sample horizontal 3 3 2.1213 2.1213 2.5981 5 5.6569 5 distance Within-sample vertical 3 3 2.1213 2.1213 2.25 998 5.6569 998 distance Between-sample horizontal 3 6 2.1213 4.2426 2.598 5 6.3431 10 distance Between-sample vertical 3 12.5882 2.1213 8.9365 2.9461 N/A 6.3431 N/A distance 4 Diameter 3 3 N/A N/A N/A N/A N/A N/A

Within-sample horizontal 3 3 2.1213 2.1213 2.5981 2.5981 5.6569 5.6569 distance Within-sample vertical 3 3 2.1213 2.1213 2.25 2.25 5.6569 5.6569 distance Between-sample horizontal 6 6 4.2426 2.1213 5.1962 3.4019 12.3431 6.3431 distance Between-sample vertical 6 10.3841 4.2426 5.1993 5.5443 8.08 12.3431 15.0931 distance 5 Diameter 6 6 N/A N/A N/A N/A N/A N/A

Within-sample horizontal 6 6 4.2426 4.2426 5.1962 8 8.4853 8 distance Within-sample vertical 6 6 4.2426 4.2426 4.5 998 8.4853 998 distance Between-sample horizontal 3 9 2.1213 6.3639 2.5385 8 3.5147 16 distance Between-sample vertical 3 19.8493 2.1213 14.0761 3.2348 N/A 3.5147 N/A distance 6 Diameter 6 6 N/A N/A N/A N/A N/A N/A

Within-sample horizontal 6 6 4.2426 4.2426 5.1962 5.1962 8.4853 8.4853 distance Within-sample vertical 6 6 4.2426 4.2426 4.5 4.5 8.4853 8.4853 distance Between-sample horizontal 9 9 6.3639 6.3639 7.7943 3.8038 15.5147 3.5147 distance Between-sample vertical 9 15.5 6.3639 6.747 8.4905 11.0787 15.5147 11.5147 distance 7 Diameter 6 6 N/A N/A N/A N/A N/A N/A

Within-sample horizontal 6 6 4.2426 4.2426 5.1962 10 8.4853 10 distance

Within-sample vertical 6 6 4.2426 4.2426 4.5 998 8.4853 998 distance Between-sample horizontal 6 12 4.2426 8.4852 5.1168 10 9.5147 20 distance Between-sample vertical 6 25.3142 4.2426 18.0085 5.813 N/A 9.5147 N/A distance 8 Diameter 6 6 N/A N/A N/A N/A N/A N/A

Within-sample horizontal 6 6 4.2426 4.2426 5.1962 5.1962 8.4853 8.4853 distance Within-sample vertical 6 6 4.2426 4.2426 4.5 4.5 8.4853 8.4853 distance Between-sample horizontal 12 12 8.4852 8.4852 10.3924 6.8038 21.5147 9.5147 distance Between-sample vertical 12 20 8.4852 10.4998 11.0886 16.08 21.5147 22.7225 distance

Table 2.3 Basic Parameters Defining the Size, Spacing, and Alignment of Designed Micropatterns. This table provides the complete list of parameters defining the size, spacing, and alignment of micropatterns in each 1mm*1mm square corresponding to the layout shown in Figure 2.4. For each of the 64 1mm*1mm squares, diameter alongside within-sample horizontal/vertical distance helps define the rough size of the individual micropattern whereas between-sample horizontal/vertical distance helps define the spacing and alignment of individual micropattern. Specifically, within-sample distances measure the maximum distance of an individual micropattern both vertically and horizontally. On the other hand, between-sample distances measure the distance between two immediate neighboring micropatterns both vertically and horizontally. The designation of R and C indicates Row and Column of this table, respectively.

2.6.2.2 Fabrication and Preparation of PDMS Patterns

Micropatterned array was fabricated with conventional semiconductor microfabrication and soft lithography. Briefly, a fused silica photomask carrying the designed micropatterns described in 2.6.2.1 was first made through a photolithography process (Beijing Zhongke

Shengze Technology Development Co., Ltd.). The Si micropatterned mold was then fabricated by high-resolution photolithography and dry etching techniques (Department of

Microelectronics, Peking University).

Next, poly-dimethylsiloxane (PDMS) micropatterned array was generated by replica molding. Briefly, PDMS and the curing agent (SYLGARD® 184) were combined in a 3:1 ratio

and mixed thoroughly using a pipette for 15 mins. PDMS mixture was degassed for 1 hour under vacuum. A thin layer of degassed PDMS mixture was cast onto the chlorotrimethylsilane

(MACKLIM)-coated resist master by spinning at 1000 rpm for 1 min. After overnight incubation at 60°C, hardened patterns (1 cm x 1 cm) were peeled off and stored at room temperature (Figure

2.5). To prepare for GPMV/pattern contact experiment, patterns were pre-coated with

NeutrAvidin and stored at -20°C.

Figure 2.5 Schematic of PDMS Micropatterns Preparation This schematic shows the preparation of PDMS micropatterns. A mixture of PDMS and curing agent was poured into a previously manufactured Si mold to form a thin layer. After overnight incubation at 60°C, hardened micropatterns were peeled off and loaded onto glass coverslips and stored at -20°C for future experiments.

2.6.2.3 Generation, Modification, and Labeling of GPMVs

We made GPMVs according to the protocol published by Sezgin et al. (Sezgin et al.,

2012) with modifications. First, cells were first cultured in a 35-mm culture dish overnight to reach 70% confluency. Before vesiculation, cell surface was biotinylated with an EZ-Link Sulfo-

NHS-LC-biotin kit. This step is a modification of the original protocol to provide extra adherence of GMPV to PDMS patterns coated with NeutrAvidin.

Next, biotinylated cells were washed twice with 1 ml PBS and then incubated with 1 ml freshly prepared 25 mM PFA/2 mM DTT in PBS at 37°C for 60 mins. GPMVs were concentrated by leaving the GPMVs suspension in a 1.5 ml Eppendorf tube for 30 mins.

Finally, GPMVs were labeled with Bodipy FL-PIP2, TopFluor TMR-PC, and TopFluor

TMR-PE at 1:50 dilution on ice for 40 mins. Labeled, biotinylated GPMVs were then incubated with NeutrAvidin-coated PDMS micropatterns for 30 mins at room temperature before they were examined with Nikon A1R+ confocal microscope.

2.6.3 Lipid Sorting Analysis on Live Cells with PDMS Micropatterns

2.6.3.1 Generalized Polarization

For GP analysis, cells were excited at 405 nm, and images were recorded with 450nm and 525 nm for ordered and disordered membranes, respectively. GP images were calculated via radiometric imaging methods detailed in Owens et al. 10. Specifically, GP= (I450-

G×I525)/(I450-G×I525), where the sensitivity correction factor G was experimentally determined using a solution 10 µM c-laurdan in DMSO following a procedure described previously (Kim et al., 2007). C-laurdan was a gift from Chang-Chun Ling at the Department of

Chemistry of the University of Calgary.

2.7 In Silico Analysis

2.7.1 ITAM Screening

An ITAM sequence Tyr-X-X-(Leu/Ile)-X(6-12)-Tyr-X-X-(Leu/Ile) was used as the probe to search against the online database of PROSITE (http://prosite.expasy.org/scanprosite/). This resulted in a list of ITAM-containing proteins. Next, these proteins were sorted by expression level according to 3 previous RNA-Seq studies in NCBI GEO Database (GSE62704:

GSM1531752, GSM1531768 for BMDC; GSE63199: GSM1543756, GSM1543757,

GSM1543758, GSM1543759 for BMDM; GSE52320: GSM1263072 for RAW264.7) in descending orders. Further, the ITAM-containing proteins which are highly expressed in

BMDMs, BMDCs and RAW264.7 cells were analyzed further. The expression score is calculated and normalized with the expression level of β-Actin as 100. The functions of these proteins were annotated based on the information provided in UniProt (http://www.uniprot.org/).

2.7.2 Phylogenetic Analysis

We selected key phagocytic proteins to study the evolution of phagocytosis. Specifically, the amino acid sequences (RefSeq) of low affinity immunoglobulin gamma Fc region receptor II

(Fcgr2), Fc ε receptor γ subunit (Fcer1g), moesin, Syk/ZAP70 and phosphatidylinositol 3-kinase

(PI3K) catalytic subunit (NP_001129691.1, NP_004097.1, NP_002435.1, NP_003168.2 and

NP_002638.2, respectively) in Homo sapiens were used as probes to find their orthologues from the model organism database by NCBI protein BLAST (https://blast.ncbi.nlm.nih.gov/). While leaving all the other settings at their default values, the top RefSeq hits of each species were selected to perform multiple sequence alignment and construct phylogenetic trees. The maximum likelihood phylogenetic reconstruction of the amino acid matrices was performed using the

PhyML 3.0 web server (http://www.atgc-montpellier.fr/phyml/) (Guindon et al., 2010). The amino acid substitution models were selected using the Akaike Information Criterion by the

SMS (Lefort et al., 2017) integrated into PhyML 3.0 web server. Each tree searching was performed using ten times of random starting tree and SPR algorithm. The branch supports were calculated using one hundred bootstrap samples.

To present the relative evolutionary rates of proteins among different groups of organisms, a time axis was shown along with the phylogenetic tree in the unit of million years before present, while y-axis displayed a number of substitutions per site compared to the amino acid sequence of the homologs in H. sapiens. Therefore, the slopes of branches might suggest amino acid substitution rates, indicating how rapidly a particular protein evolves. The species divergence times were used to represent the divergence time between orthologous amino acid sequences, and they were from the estimated time derived from previous studies in the

TIMETREE website (http://www.timetree.org/) (Hedges et al., 2006; Hedges et al., 2015; Kumar and Hedges, 2011; Kumar et al., 2017). In the phylogeny of paralogous ZAP70 and Syk, the tree root age was calculated by amino acid substitution rates on both ZAP70 and Syk clades respectively based on the molecular clock.

2.8 Statistical Analysis

GraphPad Prism 7 (GraphPad Software) was used to generate graphs and to perform statistical analysis unless otherwise indicated. The significance level of all statistical tests was set at 0.05. Tests results were considered not significant when p≥0.05 (ns), significant when

0.01≤p<0.05 (*), very significant when 0.001≤p<0.01 (**) and extremely significant when

0.0001≤p<0.001 (***) or when p<0.0001 (****). An unpaired, two-tailed Student’s t-test was

conducted to compare two samples. When comparing multiple samples, one-way analysis of variance (ANOVA) models was used followed by post-hoc Scheffé test with STATA 14

(StataCorp LLC). For correlation analysis, non-parametric Spearman correlation analysis was performed, and the resulting Spearman's rank correlation coefficient r and p-value were reported.

For bar graphs or scatter plots, data were presented as mean ± standard error of the mean (SEM).

Chapter Three: The Role of Moesin in Solid Particle Phagocytosis

3.1 Introduction and Aim

3.1.1 Introduction

We have previously uncovered a phagocytic mechanism of solid particles in which Syk kinase and basal ITAM phosphorylation are required for MSU and alum binding and activation(Flach et al., 2011; Ng et al., 2008). However, the specific ITAM-containing molecules responsible for solid particle phagocytosis remained unknown. Experimentally, we found that recruitment and activation of Syk, a well-defined kinase for ITAM in immune signaling of phagocytes, to the site of contact is required for particle phagocytosis. This suggests that an

ITAM-containing molecule must be involved in solid particle phagocytosis. However, we failed an initial attempt to identify this molecule as we investigate some most apparent targets.

Specifically, we found that the typical ITAM-containing molecules such as FcγR and DAP12 that are previously demonstrated to play a role in phagocytosis were not necessary for such solid particle phagocytosis (Flach et al., 2011; Ng et al., 2008).

It is worth noting here that solid particle phagocytosis in this thesis explicitly refers to the non-opsonic phagocytic mechanism we reported and described in Section 1.4.4.5.

3.1.2 Aim

This chapter aims to identify the ITAM-containing molecule in solid particle phagocytosis.

3.2 Results

3.2.1 Moesin is the ITAM-containing Molecule for Solid Particle Phagocytosis

To find the ITAM-containing molecules required for receptor-independent phagocytosis, we generated a library of ITAM-containing molecule in mouse genome in silico. Typically, the amino acids sequence of ITAM is defined as YXX(L/I)X6-8YXX(L/I), where X denotes any amino acid (Monroe, 2006). To make such library inclusive, we plan to use the sequence

YXX(L/I)X6-12YXX(L/I) with a more extended linker region as the template and searched all combinations of such sequences against PROSITE, an online database of protein domains, families and functional site (Sigrist et al., 2009). All the positive hits returned from this search will make up the ITAM-containing molecule library. This search resulted in a library of 1085

ITAM-containing molecule. Gene symbols and gene IDs were recorded (Figure A-1). These hits were ranked according to their expression scores normalized to β-Actin expression, and the top

25 ITAM-containing molecules were listed for further investigations (Table 3.1). Of the 25 top hits, 18 were excluded for further analysis due to their unlikely involvement in phagocytosis. The reason for disqualification was stated in the note column of Table 3.1.

Therefore, we narrowed our search down to 7 candidate genes: Fcer1g, Tyrobp, Lcp1,

Hmox1, Csf1r, Ndrg1, and Msn.

Rank Gene Symbol Score ITAM Sequence X(n) Note ITAM sequence in 1 Itm2b 56.16 extracellular/luminal domain 2 Fcer1g* 38.70 YTGLNTRSQETYETL 7

3 Tyrobp* 32.01 YQELQGQRPEVYSDL 7

4 Npc2 24.71 Secretory Protein

5 Lcp1 22.33 YSDLSDALVIFQLYEKI 9

6 Rps3 15.16 40S ribosomal protein

ITAM sequence in transmembrane 7 Slc6a6 9.63 domain 8 Hmox1 9.63 YTALEEEIERNKQNPVYAPL 12

9 Csf1r 8.61 YGILLWEIFSLGLNPYPGI 11

ITAM sequence in the extracellular 10 Cd36 8.51 domain ITAM sequence in 11 Atp1a1 7.96 extracellular/transmembrane domain 12 Ndrg1 7.94 YHDIGMNHKTCYNPL 7

ITAM sequence in 13 Slc11a1 6.59 extracellular/transmembrane domain 14 Msn* 6.49 YLKIAQDLEMYGVNYFSI 10

ITAM sequence in Myosin motor 15 Myh9 6.10 domain 16 Actr2 5.86 ITAM sequence at ATP binding site 17 Rpl7 5.42 60S ribosomal protein ITAM sequence at the Cdc42 binding 18 Iqgap1 5.15 region 19 Ctsc 4.96 Lysosome localization 20 Rps25 4.76 40S ribosomal protein ITAM sequence in 21 Cd81 4.39 extracellular/transmembrane domain 22 Degs1 4.14 Mitochondrial localization

23 Glud1 4.09 Mitochondrial localization

24 Rpl7a 3.87 60S ribosomal protein

25 Atp6v1e1 3.86 Subunit of Vacuolar ATPase

Table 3.1 Top 25 Hits of Highly Expressed ITAM-containing Proteins in Mouse Genome. For those analyzed further, or of substantial relevance to phagocytosis, the corresponding rows are colored green and their ITAM sequences are listed. For those not pursued further, notes were provided at the first column to the right to state the reasons for such exclusion. The score is calculated and normalized with the expression level of β-Actin as 100. * denotes genes with reported functional ITAM motifs. The green rows represent the seven candidate genes identified for further investigation.

Next, we attempted to transiently knockdown expression of the seven remaining genes in

DC2.4, a phagocytic cell line used in previous research on particle phagocytosis, to determine at the functional level if phagocytosis is indeed impaired. Knockdown efficiency was preliminarily determined by RT-PCR at gene expression (mRNA) level. Among the seven transient knockdown cells, Hmox1 and Csfl1r knockdown cells exhibited less than 50% knockdown efficiency. Moreover, these knockdown cells showed significant morphological changes from

WT DC2.4, rendering them unsuitable for subsequent functional analysis. Therefore, Hmox1 and

Csfl1r were not investigated further. In comparison, Fcer1g, Tyrobp, Lcp1, Ndrg1 and Msn knockdown cells all displayed more than 60% knockdown efficiency and healthy morphology

(Figure 3.1). Therefore, these knockdown DC2.4 cells were assessed further for their phagocytosis ability with a quantitative phagocytosis assay (Section 2.5.2).

Figure 3.1 Transient Knockdown Efficiency of Candidate ITAM-containing Genes in DC2.4 Cells. The ratios of mRNA levels over GAPDH with gene-specific siRNA or control siRNA transfection are shown. N=3. For all figure legends involving repeats, “n” denotes the number of technical repeats in each group and “N” denotes the number of independent biological repeats. Csf1r encodes colony stimulating factor 1 receptor, which is involved in cell growth, proliferation and differentiation (Stanley and Chitu, 2014). Hmox1 encodes heme oxygenase 1, which is involved in heme catabolism (Choi and Alam, 1996). Fcer1g encodes high affinity immunoglobulin epsilon receptor subunit gamma, which is involved in IgE-mediated immune signaling in allergy (Sakurai et al., 2004). Tyrobp encodes DAP12, which is involved in immune cell activation (Turnbull and Colonna, 2007). Lcp1 encodes Plastin-2, which is involved in leukocyte activation via actin bundling (Shinomiya, 2012). Ndrg1 encodes N-myc downstream- regulated gene 1, which is involved in hormone responses, cell growth, and differentiation (Song and Cao, 2013). Msn encodes moesin, which is involved in organization of the cell cortex (Fehon et al., 2010).

Phagocytosis of DC2.4 cells was evaluated via a quantitative phagocytosis assay. This assay is a fluorescence microscopy-based method developed in-house to test the phagocytic ability of cells. Briefly, 3µm, biotin-BSA-coated polystyrene beads are incubated with cells at

37°C, 5% CO2 for 40 minutes. Cells are then fixed with 4% PFA and labeled with Alexa Fluor conjugated-Streptavidin without permeabilization, thus differentiating uninternalized (with fluorescent label) beads from internalized (without fluorescent label) beads. Phagocytosis efficiency was expressed as the percentage of beads internalized per cell averaged over at least

50 cells (Section 2.5.2).

For the remaining five candidate genes in which their expression was significantly knocked down, Msn and Lcp1 DC2.4 knockdown cells showed the most significant reduction in phagocytic efficiency at ~45% reduction (Figure 3.2) while reduction at the gene expression level remained similar at 30-40% (Figure 3.1). However, Lcp1 encodes Plastin-2, and Plastin-2 is cytosolic with no membrane binding ability (Lin et al., 1988) as opposed to moesin encoded by

Msn, we chose to focus our further investigations on moesin solely.

Figure 3.2 Phagocytosis Efficiency of DC2.4 Cells with Transient Knockdown of Candidate ITAM-containing Genes. Data were presented as mean±s.e.m, n=200, from a total of N = 4 independent experiments.

We cloned stable moesin-KD DC2.4 cells with shRNA method (Section 2.2.3.4) and the knockdown efficiency was confirmed with western blotting (Figure 3.3a) and immunofluorescence microscopy (Figure 3.3b) that stable knockdown of moesin in DC 2.4 cells was indeed successful. In the most successful cases, signals for moesin was barely detectable with western blotting and immunofluorescence microscopy while control cells display strong positive signals. Next, the stable moesin knockdown cells were tested by phagocytosis assay. We observed roughly 70% decrease in phagocytosis (Figure 3.3c). This is an even more dramatic decrease than transient moesin knockdown DC2.4. This can be explained by the more thorough elimination of moesin in stable clones. Interestingly, we also observed a reduced surface binding to silica crystals of stable moesin knockdown DC2.4 cells compared to control cells as measured by Atomic Force Microscopy-based Single Cell Force Spectroscopy (AFM-SCFS) (Figure 3.3d).

Overall, the above results suggest that moesin is a likely candidate of the ITAM-containing molecule for solid particle phagocytosis.

(a) (b)

Figure 3.3 Phagocytosis of Polystyrene Beads is Impaired in Stable Moesin Knockdown DC2.4 Cells. (a) Moesin shRNA-transfected DC2.4 cell single clones were immunoblotted with antibodies against moesin, and GAPDH. This experiment was completed by Libing Mu. (b) Immunofluorescence staining of wildtype and stable moesin knockdown DC2.4. (c) Phagocytosis efficiency of the clones with high KD efficiency indicated with red dots in (a) n=50, N=3. (d) AFM force measurement of moesin-KD DC2.4 in contact with silica crystals. n=190, N=3. This experiment was completed by Jiahuan Chen.

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Moesin is a member of ERM family protein including two other paralogs named ezrin and radixin in vertebrates (Bretscher et al., 2002). These proteins share an N-terminal Band 4.1, ezrin, radixin, moesin (FERM) domain that binds the plasma membrane followed by an α-helical linker region and a C-terminal ERM actin-binding domain (C-ERMAD) that can interact with F- actin. At resting state, FERM domain interacts with the C-ERMAD domain via a reversible head-to-tail interaction to mask F-actin-binding site and membrane association, thus rendering the entire protein inactive in the cytosol (Fiévet et al., 2007). To achieve an active state, FERM binding with PIP2 at the plasma membrane is required to lift the restricted access to the actin- binding site at C-ERMAD (Fievet et al., 2004). Also, phosphorylation of a threonine residue

(T567 in ezrin, T564 in radixin and T558 in moesin) within C-ERMAD domain is needed for such activation (Nakamura et al., 1995; Simons et al., 1998). Notably, ezrin, moesin, and radixin all share an almost identical ITAM-like sequence within their FERM domains (Figure 3.4).

However, we only successfully identified moesin, but not ezrin or radixin, as the likely candidate for ITAM-containing molecules responsible for solid particle phagocytosis. We wonder if this can be attributed to the difference in expression in phagocytes. RT-PCR results showed moesin is the most highly expressed among ERM and other FERM-containing proteins in typical phagocytes like BMDCs, BMDMs, DC2.4 and RAW264.7 (Figure 3.5a). Further, a search in the online gene expression database BioGPS (Wu et al., 2016) confirmed moesin as the most highly expressed proteins among ERM proteins in phagocytes (Figure 3.5b). The above results indicate that moesin might be the only member of ERM family protein involved in solid particle phagocytosis due to its abundance in phagocytes.

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Figure 3.4 Schematic Drawing of Basic Structure of Moesin, Radixin, and Ezrin. Function domains and sequences of ITAM motif are shown. The degree of homology of each domain compared to moesin is also displayed.

(a) (b)

Figure 3.5 Gene Expression Profile of ERM Family Proteins in Cell Lines and Tissues. (a) Absolute quantification PCR of ERM family members at mRNA level for different cell types. n=3, N=3 (b) Relative expression levels of three ERM proteins, revealed by the indicated probes from BioGPS (http://biogps.org) database, in mouse phagocytes and tissues.

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To confirm that moesin is the only ERM family member required for solid particle phagocytosis. We also cloned ezrin and radixin knockdown DC2.4 cells and found no significant loss in phagocytosis capacity compared to moesin knockdown DC2.4 cells (Figure 3.6). A closer examination revealed that moesin is the only protein preferentially accumulated on the membrane surrounding a latex bead among ERM family proteins when RAW264.7 cells were stained with actin by phalloidin and antibodies against specific ERM proteins (Figure 3.7).

Because the samples were examined with super-resolution microscopy, this enabled us to delineate the spatial arrangement of solid particle in the form of a latex bead, moesin, and actin.

Three-dimensional (3D) reconstruction of a phagocytic cup was performed on super-resolution images (Video 3.1). The reconstructed model revealed that the bead is wrapped by an inner layer of moesin followed by an outer layer of actin. Also, a thick layer of cortical actin support was also observed at the base of this phagocytic cup. This spatial arrangement pattern agrees with the basic signaling mechanism of any phagocytosis in which actin is finally activated following earlier signaling events at the site of contact. Further, we found with immunofluorescence microscopy that phosphorylated ERM proteins were enriched in actin-rich phagocytic cups

(Figure 3.8). Because moesin is far more abundant in RAW264.7 cells than ezrin and radixin, it is sensible to conclude that the majority of phosphorylated ERM is phosphorylated moesin.

Therefore, we can conclude that moesin is phosphorylated at the site of contact following membrane engagement of solid particle with the cell surface. It is worth noting here that anti- phosphorylated ERM antibody is used for this experiment because there is no antibody specifically binds to phosphorylated moesin, understandably so due to the highly homologous nature of ERM proteins. More specifically, these proteins share the same phosphorylated residues and surrounding amino acid sequences. Therefore the epitope is near identical for

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phosphorylated ERM family proteins (Fehon et al., 2010). Taken together, these results

indirectly suggested that moesin is activated at the membrane surrounding a bead. Overall, on the

functional level, moesin is identified as the ITAM-containing molecule required for solid particle

phagocytosis.

(a) (b)

Figure 3.6 Phagocytosis Efficiency of Polystyrene Beads by Ezrin and Radixin. Multiple clones of stable ezrin (a) and radixin (b) knockdown DC2.4 cells were immunoblotted with specific monoclonal antibodies to confirm the efficiency of knockdown at the protein level. The clones with high KD efficiency used in the phagocytosis assay was indicated with red dots. Thses experiments were completed by Libing Mu. Phagocytosis efficiency is tested for stable ezrin (c) and radixin (d) knockdown DC2.4 cells. Comparisons were made to the empty vector control (lower). n=50, N=3.

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(a) (b)

Figure 3.7 Disparate Accumulation Profiles of ERM Proteins around the Bead- surrounding Membranes. (a) Moesin, ezrin, and radixin (green) were visualized with antibodies along with actin cytoskeleton (phalloidin) on RAW 264.7 cells incubated with 3 μm polystyrene beads at 37°C for 15 min. SIM was performed to obtain the fluorescence images. Scale bars, 5μm. (b) Line profiles are corresponding to fluorescence intensities of the respective ERM molecules and actin on an imaginary line across the indicated phagocytic cups. N=6.

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Video 3.1 3D-reconstructed Phagocytic Cup with Moesin and Actin This montage shows a 3D reconstructed phagocytic cup of 3µm in diameter viewed from nine different angles. The phagocytic cup is reconstructed from super-resolution image shown in Figure 3.7. Actin is colored solid red while moesin is colored translucent green. The complete video can be accessed at goo.gl/z2YWWn .

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(a) (b)

Figure 3.8 Indirect Evidence of Moesin Activation Triggered by Polystyrene Beads (a) Phospho-ERM (green) were visualized with anti-pERM antibodies alongside actin cytoskeleton by SIM on RAW 264.7 cells incubated with 3 μm naked polystyrene beads at 37°C for 15 min. (b) Line profiles corresponding to fluorescence intensities of pERM and actin were generated across the indicated phagocytic cups. N=4. Scale bars, 5μm.

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3.2.2 FERM Domain of Moesin is Sufficient to Induce Solid Particle-Triggered Signaling

In the previous section, we have identified moesin as the ITAM containing molecule.

Also, we found that moesin is activated at the site of contact during phagocytosis.

Next, we sought to determine if the ITAM-containing FERM domain of moesin is involved in solid particle phagocytosis. It is essential to confirm this as we have shown with

FcγR and DAP12 that not all ITAM-containing proteins that are highly expressed in phagocyte and previously implicated in other phagocytic mechanisms can mediate solid particle phagocytosis. To achieve this, we rescued moesin-KD DC 2.4 cells with Full-length moesin alongside ITAM-dead moesin, FERM-only moesin and FERM ITAM-dead moesin (Figure

3.9a). We found that Full-length moesin and FERM-only moesin could fully restore phagocytosis in moesin KD DC2.4 cells. In contrast, both ITAM-dead moesin mutants failed to restore phagocytosis (Figure 3.9b). These results indicate that FERM domain of moesin is sufficient to mediate solid phagocytosis and that the ITAM sequence within the FERM domain is necessary for this process.

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(a)

(b)

Figure 3.9 The Role of Moesin ITAM in Phagocytosis of Polystyrene Beads (a) Schematic drawings of EGFP-linked full-length moesin and three other mutants concerning ITAM. (b) Stable moesin knockdown DC2.4 cells, as in Figure 3.3, were rescued with full-length and mutants moesin as depicted in Figure 3.9a by transient overexpression. Empty vector control for transfection and Cyto D control for phagocytosis efficiency were included. n≥71 for each group. N=3.

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Syk is an established downstream tyrosine kinase in phagocytes (Tohyama and

Yamamura, 2009). Specifically, Syk is shown to be recruited to the membrane and activated via direct engagement of its two SH2 domains with phosphor-ITAMs in immune receptor signaling.

Since we have shown that moesin ITAM is phosphorylated and is responsible for solid particle phagocytosis, we wonder if Syk is activated following membrane engagement of solid particles.

First, we demonstrated in vitro that moesin physically binds to Syk via its ITAM- containing-FERM domain. This conclusion is based on the immunoprecipitation experiments with cells co-transfected with Syk and different domains of moesin. We found that FERM domain of moesin specifically binds to Syk (Figure 3.10). It is worth noting here that full-length moesin did not show an appreciable level of binding even though FERM domain is contained.

This is because, without stimulation from solid particles or other upstream activating signals, the full-length moesin is in its inactive state with FERM domain masked by C-ERMAD domain, thus making the ITAM inaccessible for Syk (Fehon et al., 2010). This implies that moesin recruitment and activation at the site of contact during particle phagocytosis is a precondition for

Syk recruitment and binding.

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(a)

(b) (c)

Figure 3.10 Moesin Interacts with Syk via its FERM Domain in vitro (a) Schematic drawings of moesin and the three truncated moesin fragments containing FERM domain, the linker region (Linker), and C-terminal moesin-ERMAD. Cell lysates from COS-1 cells transfected with (b) Myc-Syk and Flag-moesin full-length and associated truncation mutants or (c) Flag-Syk and associated Myc-moesin and truncation mutants were subjected to IP with anti-FLAG M2 beads. Cells were treated with 1µM Na3VO4 to preserve phosphorylation for 1 hour before harvesting. N=5. These experiments were completed by Libing Mu.

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Next, we sought to determine if Syk can be physically associated with moesin following solid particle binding to phagocytes and if such physical association of Syk to moesin will lead to its phosphorylation. First, we showed that Syk is indeed physically associated with moesin in

DC2.4 cells following treatment with MSU (Figure 3.11a) with immunoprecipitation.

Temporally, we found the level of phosphorylation of tyrosine residue was significantly increased when moesin is overexpressed in cells treated with MSU (Figure 3.11b). Such accumulation of phosphorylation of tyrosine is positively correlated to the time of MSU engagement to DC2.4 cells. Spatially, we demonstrated with fluorescence microscopy that phosphorylated Syk in enriched at the site of contact (Figure 3.11c). We observed much higher fluorescence signals of phosphorylated Syk around a bead (upper) that is tightly enclosed by the membrane than another bead (lower), not in close contact with the membrane of RAW264.7 cells. Moreover, when a bead (middle) is wholly internalized, fluorescence signal for phosphorylated Syk also diminished. This suggests that activation of Syk is most prominent during the onset of phagocytosis when solid particles are actively engaged with cell membranes.

This also coincides with the spatiotemporal activation profile of moesin, as these two molecules sit close along the signaling chain and are also physically associated when activated during phagocytosis.

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(a) (b)

(c)

Figure 3.11 Syk Activation induced by Solid Particle Engagement to Cell Surface. (a) Co-immunoprecipitation of Syk and Moesin in DC2.4 cell treated with (MSU) or without (UT) MSU. (b) Kinetics of tyrosine phosphorylation of Flag-tagged Syk transiently transfected into DC 2.4 cells following treatment with 200 µg/mL MSU crystals with indicated time. N=5 The above experiments were completed by Libing Mu. (c) RAW264.7 cells were incubated with biotin-BSA beads at 37 ℃ for 15 minutes in the presence of 1µM Na3VO4 to preserve phosphorylation before they were fixed with 4% PFA without permeabilization. Beads are stained positive for AF594-streptavidin (Red) if not internalized. Phosphorylated Syk was labeled by primary anti-pSyk antibody followed by AF488-conjugated (green) secondary antibody.

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Finally, we determined the activation profile of some signaling molecules downstream of

Syk (Figure 3.12). DC2.4 cells were incubated with MSU crystals, silica crystals and polystyrene beads at 37℃ for indicated time before investigated with Western blotting for signal activation.

In general, most of these downstream signaling molecules can be activated by all the solid particles tested. However, the magnitude and kinetics of activation differ. For example, following membrane ligation with MSU crystals, robust activation was observed for Akt, ERK, and p38 as early as 10 minutes. In contrast, neither silica nor polystyrene bead can reach the same magnitude of activation as MSU even after 30 minutes. Notably, no activation at all was observed for polystyrene beads on p38 activation. This activation profile corresponds to the inherent properties of each solid particles, as MSU and silica are known to induce pro- inflammatory signaling while polystyrene beads are not (Nakayama, 2018). Regarding phagocytosis signaling, each of the three solid particles can induce activation of ERM proteins, mostly moesin, very rapidly. Overall, we showed that downstream signals could be activated by various solid particles following membrane engagement and activation of moesin and Syk.

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Figure 3.12 Kinetics of Downstream Signaling Activation following Solid Particle Engagement. DC2.4 cells were incubated with 200mg/l MSU crystals, 200mg/ml silica crystals and 0.01% (v/v) polystyrene beads at 37℃ for indicated time. Cells were then lysed and probed with specific antibodies to investigate the activation of signaling molecules via Western blotting. These experiments were completed by Libing Mu.

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3.3 Discussion

This chapter aims to identify the ITAM-containing molecule responsible for solid particle phagocytosis.

First, we established in silico a library of ITAM-containing molecule and ranked them according to their expression levels in phagocytes. Next, we selected top candidates and transiently knocked down their gene expression in DC2.4, a phagocytic cell line. These knockdown cells were subjected to further evaluation by phagocytosis assay. Among those top candidates, we observed the most significant reduction of particle phagocytosis with Lcp1 and

Msn knockdown. It is noteworthy that, although we did not choose to further pursue Lcp1 for its role in solid particle phagocytosis, Lcp1 is nevertheless an interesting target for further investigations.

Individual clones of stably knockdown DC2.4 cells were used to confirm moesin as a likely candidate for solid particle phagocytosis. The use of individual stable clones with shRNA integration for moesin knockdown was before CRISPR (Clustered Regularly Interspaced Short

Palindromic Repeats)-Cas9 technology becomes a routine laboratory technique for gene knockout (Bauer et al., 2015). In retrospect, one could argue that we could have generated moesin knockout cells and select individual clones to reach total elimination of expression of moesin in DC2.4 cells due to high targeting efficiency of the CRISPR-Cas9 system, and to carry out subsequent functional studies. On the surface, this may sound appealing. However, major caveats exist. CRISPR-Cas9 system can have off-target effects. This occurs as Cas9 can tolerate up to 5 base mismatches within the protospacer region or a single base difference in the protospacer adjacent motif sequence (Zhang et al., 2015). Off-target mutations are generally more difficult to detect, requiring whole-genome sequencing to rule them out entirely. Therefore,

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each clone must be tested individually, and, in theory, we can never be confident we have obtained the correct clone unless a whole-genome sequencing is performed. One might argue this is also a problem for our shRNA-based method, and it is true. Nevertheless, we showed with multiple clones used in multiple experiments that at the functional level the knockdown cells were suitable enough for subsequent studies. Moreover, we showed with Western blotting that our stable knockdown efficiency is high enough to the point that no band was detectable. Also, an initial attempt to a knockout with the CRISPR-Cas9 system was made, and the cells became extremely nonadherent to glass or plastic surface of culture dishes. Thus, the added benefit of knockout over knockdown is negated. Therefore, a shRNA-based knockdown method is most suitable for this thesis.

Next, we used microscopy to determine the subcellular localization of moesin. We found that moesin preferentially accumulated around the membrane engaged with naked polystyrene beads. One might raise a question regarding whether polystyrene beads is representative of all solid particles. The simple answer to this question is no, as we demonstrated that kinetics and magnitude of signal activation following moesin and Syk phosphorylation is different for MSU, silica and polystyrene beads already (Figure 3.12). Moreover, this is due to the diverse physical and chemical properties associated with each type of solid particles (Beningo and Wang, 2002;

Champion and Mitragotri, 2006). Nevertheless, the justification for using polystyrene beads to study solid particle phagocytosis should be discussed. First and foremost, we did confirm that moesin accumulation around the site of contact is similar for MSU, silica and polystyrene beads

(Figure 3.13 and 3.14). Combined with the finding that ERM proteins are rapidly phosphorylated following incubation with all three solid particles (Figure 3.12), we are confident that the downstream signaling pathway regarding phagocytosis should be similar, although the timing

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and strength of signals may differ. However, as can be seen from the brightfield images in Figure

3.13 and 3.14, silica and MSU crystals are irregular in shape and size. This proved to be challenging for further experiments for three reasons: 1) Undefined shape and size makes it difficult to quantify the phagocytosis efficiency. 2) For studies involves touching a single solid particle with the cell membrane, lack of uniformity will make the results between each repeat hard to interpret as size and shape can be viewed as confounding variables. 3) During fluorescence microscopy, it is sometimes difficult to visually distinguish a small crystal from the cellular feature. Based on the above disadvantages stated above, it was decided to use polystyrene beads as they are incredibly homogenous in size and shape. Also, adsorption of their surface with biotin-BSA enabled us to quantify the uptake of beads via labeling with Alexa

Fluor-conjugated Streptavidin (Section 2.5.2). It worth noting here one could argue that biotin-

BSA-coated beads and even naked beads can bind to scavenger receptors as opposed to the lack of involvement of any apparent receptor found with MSU and alum crystals (Kanno et al., 2007).

This is likely caused by the difference in the surface chemistry between naked beads, biotin-

BSA-enshrouding beads and crystals. While this claim is possible, we want to remind the reader that this is the trade-off we consciously make to continue this study when no better alternative was presented. Therefore, data should be interpreted and sometimes extrapolated with great caution.

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(a) (b)

Figure 3.13 Preferential Accumulation of Moesin around Silica Crystals (a) Bone marrow-derived macrophages were incubated with 200 µg/mL silica crystals at 37 ℃ for 15 minutes before they were fixed with 4% PFA. Cells were stained with AF594-phalloidin (Red) and with primary anti-moesin antibody followed by AF488-conjugated (green) secondary antibody to visualize actin and moesin, respectively. (b) Heat map of fluorescence signals of moesin is displayed to provide visual confirmation regarding the recruitment of moesin around silica crystals.

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(a) (b)

Figure 3.14 Preferential Accumulation of Moesin around MSU Crystals (a) Bone marrow-derived macrophages were incubated with 200 µg/mL silica crystals at 37 ℃ for 15 minutes before they were fixed with 4% PFA. Cells were stained with AF594-phalloidin (Red) and with primary anti-moesin antibody followed by AF488-conjugated (green) secondary antibody to visualize actin and moesin, respectively. (b) Heat map of fluorescence signals of moesin is displayed to provide visual confirmation regarding the recruitment of moesin around MSU crystals.

Further, we determined that the ITAM-containing FERM domain is sufficient to induce solid particle phagocytosis. One important implication of this conclusion is that the C-terminal actin-binding domain of moesin is dispensable for solid particle phagocytosis. This is a novel finding because moesin is generally regarded as a passive structural linker between the plasma membrane and cortical actin (Mangeat et al., 1999). Recent reports suggested that moesin can also interact with CD93, P-selectin glycoprotein ligand-1 (PSGL-1), and is coalesced within immunological synapse in leukocytes, all in an Syk-dependent manner (Ilani et al., 2007;

Urzainqui et al., 2002; Zhang et al., 2005). This implicates the role of moesin ITAM in immune

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signaling. Although the formation of immunological synapses and phagocytic cups are similar in many regards (Niedergang et al., 2016), the involvement of moesin in phagocytosis was rarely investigated. Here, we have shown in this chapter that moesin is an active signaling molecule in solid particle phagocytosis by acting as a signaling platform for binding of Syk via its SH2 domains.

To establish that FERM domain of moesin is sufficient for solid particle phagocytosis, we performed rescue studies with ITAM-dead constructs moesin-YF and FERM-YF in moesin knockdown DC2.4 cells. We found that the efficiency of phagocytosis of polystyrene beads was similar to that of the negative vector control. Besides deficiency in phagocytosis in those rescued

DC2.4 cells, we found that morphology of ITAM-dead rescued cells differs from other experimental groups. Cells round up 24 hours after transfection compared to the control cells, and the loss of dendrites and filopodia were also observed (Data not shown). Also, when culturing these cells, we found that they are less adherent than those ITAM rescued DC 2.4 cells as they come off the plates relatively quickly, although cells are still healthy. The loss of adherence is intriguing as cell adhesion, and phagocytosis share many common pathways

(Dupuy and Caron, 2008). Anecdotally, adhesion is often referred to as “frustrated phagocytosis” despite many differences between phagocytosis and adhesion. Therefore, it is of interest to determine if moesin, especially its FERM domain, is involved in signaling pathways concerning adhesion.

In summary, in this chapter, we identified moesin as the ITAM-containing molecule responsible for solid particle phagocytosis. Specifically, the FERM domain of moesin is sufficient to trigger downstream phagocytic signaling. These signaling events include the physical binding of Syk to moesin, activation of Syk and other downstream molecules.

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Chapter Four: The Role of PIP2 in Solid Particle Phagocytosis

4.1 Introduction and Aim

4.1.1 Introduction

Another piece of the puzzle to the proposed Signaling Equivalent Platform (Section

1.4.4.5.2) model is what lipid species are sorted following solid particle engagement to the membrane to induce downstream phagocytic signaling. We approached this question from three different angles.

First, we have previously demonstrated that cholesterol at its physiological orientation and to some extent sphingomyelin (SM) binds to MSU and alum crystals with high affinity

(Flach et al., 2011; Ng et al., 2008). Subsequent lipid sorting activates an abortive phagocytic response that leads to antigen uptake. However, these findings were based on assays developed to test binding strength between lipids and crystals. The direct involvement of individual lipids in particle phagocytosis has not been investigated. Moreover, we were not able to show that cholesterol and SM indirectly induce downstream phagocytic signaling. Since these lipids are usually enriched in lipid rafts, we could only suggest that the binding of cholesterol and SM to solid particles like MSU and alum might be indicative of a general involvement of lipid rafts instead of directly triggering downstream signaling.

Second, it is well established that PIP2 is involvement in FcγR-mediated phagocytosis, and its hydrolysis directs actin remodeling (Botelho et al., 2000, 2004; Scott et al., 2005). At resting state, PIP2 is present in substantial amounts in the inner leaflet of the plasma membrane of phagocytes (Flannagan et al., 2012). Following engagement of IgG-opsonized particles to the cell membrane of phagocytes, a transient increase PIP2 concentration is transiently increased at the site of contact, and this is followed by its depletion from the base of the phagocytic cup. The

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local synthesis of PIP2 is caused by the phosphorylation of PIP5K on phosphatidylinositol 4- kinase (PI4K). While PIP2 concentration decreased from the base of the phagocytic cup, it continues to accumulate at the pseudopods actively wrapping the IgG-opsonized particle until the phagosome is completely sealed. Transient increase in PIP2 is followed by an abrupt decrease and a concomitant increase in PIP3 concentration. This local PIP2 to PIP3 conversion is facilitated by the kinase activity of PI3K via the addition of a phosphate group at the third position of the inositol ring of PIP2. Syk recruits PI3K via Gab2. PIP3 generated from PI3K activity can stabilize Gab2, thus feeding into a positive feedback loop (Gu et al., 2003). Also, the loss of PIP2 can be caused by its hydrolysis into DAG and IP3 via PLCγ (Botelho et al.,

2000). PLCγ is also recruited by Syk to the membrane and bind to PIP2 via its PH domain.

Hydrolytic product DAG further recruit PKC to promote phagocytosis (Cheeseman et al.,

2006). To summarize, PIP2 is a critically important signaling lipid in FcγR-mediated solid particle phagocytosis. Whether or how PIP2 can contribute to non-opsonic solid particle phagocytosis remained unknown. Therefore, it is of great interest to investigate whether PIP2 sorting at the membrane is responsible for solid particle phagocytosis.

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Figure 4.1 Spatiotemporal Distribution of Phospholipoids During Phagocytosis At resting state, phosphatidylinositol-4,5-bisphosphate [PI(4,5)P2] is present in substantial amounts in the inner leaflet of the plasma membrane of phagocytes. Following engagement of IgG-opsonized particles to the cell membrane of phagocytes, a transient increase PIP2 concentration is transiently increased at the site of contact, and this is followed by its depletion from the base of the phagocytic cup. The local synthesis of PIP2 is caused by the phosphorylation of PIP5K on PI4K. While PIP2 concentration decreased from the base of the phagocytic cup, it continues to accumulate at the pseudopods actively wrapping the IgG- opsonized particle until the phagosome is completely sealed. Reprint with copyright permission from Annual Reviews (Flannagan et al., 2012).

Third, in Chapter 3, moesin was identified as a mediator of solid particle phagocytosis via binding of its FERM domain to Syk. It is also established in the literature that ERM protein recruitment to membrane requires PIP2. For example, when PLCδ hydrolyzes PIP2, ERM proteins, including moesin, are released from lymphocyte membrane (Hao et al., 2009). The decrease in PIP2 concentration will lead to dephosphorylation of ERM proteins. This

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consequently leads to the inactivation of ERM proteins (Hao et al., 2009). Also, analysis from structural biology revealed that the FERM domain of moesin contains key residues Lys63 and

Lys278 for PIP2 binding (Hamada et al., 2000). It also demonstrated that in vitro when mutating either lysine residues to asparagine, PIP2 binding to moesin is lost. The loss of binding in these mutants consequently translate into impaired activation of moesin (Ben-Aissa et al., 2012). To date, little focus was put on the roles of PIP2 regarding moesin activation in phagocytes.

Notably, no study addresses this problem in any form of phagocytosis.

Taken together, we believe is it of substantial interest to test if and how PIP2 is sorted in solid particle phagocytosis to induce downstream signaling.

4.1.2 Aim

This chapter aims to identify the lipid species, possibly PIP2, sorted in moesin-mediated solid particle phagocytosis. Further, we aim to investigate the mechanism of action of such lipid in moesin-mediated solid particle phagocytosis.

4.2 Results

4.2.1 PIP2 Sorting is Required for Solid Particle Phagocytosis

First, fluorescence microscopy of PH-PLCδ-GFP-expressing RAW264.7 cells stained with phalloidin pre-incubated with naked 3µm polystyrene beads revealed that PIP2 were enriched in the site of contact similar to what has been observed with FcγR (Flannagan et al.,

2012). Specifically, line profile analysis showed paralleled accumulation of PIP2 and actin cytoskeleton at the membrane surrounding a bead (Figure 4.2). Further, 3D reconstruction of a

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phagocytic cup was performed on super-resolution images (Video 4.1). The reconstructed model revealed that the bead is wrapped by an inner layer of moesin followed by an outer layer of actin.

This spatial arrangement pattern is similar to that of moesin and actin described in Video 3.1.

This suggests that PIP2 sorting can be induced by solid particles engaged with the cell membrane.

Figure 4.2 Accumulation of PIP2 around the Membrane Engaged with Polystyrene Beads PIP2 (green) was visualized with PH-PLCδ-GFP alongside actin cytoskeleton by SIM on RAW 264.7 cells incubated with 3μm naked polystyrene beads at 37°C for 15 mins. Line profiles corresponding to fluorescence intensities of PIP2 and actin were generated across the indicated phagocytic cups. N=5. Scale bars, 5µm.

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Video 4.1 3D-reconstructed Phagocytic Cup with PIP2 and Actin This montage shows a 3D reconstructed phagocytic cup of 3µm in diameter viewed from nine different angles. The phagocytic cup is reconstructed from super-resolution image shown in Figure 4.2. Actin is colored solid red while PIP2 is colored translucent green. The complete video can be accessed at https://goo.gl/mFGhDp.

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In addition to investigating spatial arrangement of PIP2 triggered by solid particles in fine details with super-resolution microscopy, spatiotemporal distribution of PIP2 during phagocytosis of solid particles were also investigated to gain a better understanding of the dynamics of PIP2 sorting. RAW264.7 cells were co-transfected with PH-PLCδ-GFP and

LifeAct-tdTomato to visualize PIP2 and actin in live cells. LifeAct is based on the first 17 residues of Actin-binding Protein 140, or ABP140, in Saccharomyces cerevisiae. ABP140 is a non-essential 140kDa actin-binding protein shown to cross-links F-actin in vitro and to co- localize to actin fibers in vivo (Riedl et al., 2008). It has been shown that LifeAct does not interfere with actin dynamics in vivo or in vitro (Riedl et al., 2008). Therefore, it is suitable for live-cell imaging.

During initial contact of the bead to the plasma membrane, PIP2 accumulates at the base of a phagocytic cup. As phagocytosis progresses, PIP2 and actin starts to accumulate around more in the membrane, likely at the extending pseudopods, in contact with the bead. At later stages of phagocytosis, PIP2 accumulation disappeared alongside actin in most areas of cell membrane enclosing the bead except for the top area presumably undergoing phagosome sealing.

When the entire bead is completed engulfed by the cell, PIP2 disappeared completely. Typically, the entire internalization process takes 5 minutes or less from meaningful initial contact to eventual engulfment. Moreover, the dynamics of actin parallels that of PIP2. The dynamic is exceptionally similar to FcγR-mediated phagocytosis demonstrated with IgG-coated sheep red blood cells (RBCs) of similar size regarding the spatiotemporal distribution of PIP2 and actin and the total time needed for complete engulfment from initial signal activation (Henry et al.,

2004; Scott et al., 2005).

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Taken together, we conclude that PIP2 is sorted following membrane engagement with solid particles. It appears that the accumulation of PIP2 is the strongest in membrane actively sensing the particle, such as the leading edge of the extending pseudopods.

(a)

(b)

(c)

Video 4.2 Dynamics Change of PIP2 Activation during Solid Particle Phagocytosis PH-PLCδ-GFP and LifeAct-tdTomato were co-expressed in RAW 264.7 cells. Cells were incubated with naked 3µm polystyrene beads at 37 °C for 40 minutes. Images were taken at a 5s interval for 40 minutes. The image above displays the spatial distribution of PIP2 and actin around the beads at different stages of phagocytosis before phagosome sealing. The bead of interest was indicated with ‘*’ in yellow. (a) During initial contact of the bead to the plasma membrane, PIP2 and actin accumulate at the base of a phagocytic cup. (b) As phagocytosis progresses, PIP2 and actin start to accumulate around more in the membrane in contact with the bead. (c) At later stages of phagocytosis, PIP2 accumulation disappeared alongside actin in most areas of cell membrane enclosing the bead except for the top area. N=3. Scale bar, 5μm. The complete video can be accessed at goo.gl/e5qee1.

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Next, we investigate whether the PIP2 sorting triggered by membrane engagement to solid particles is a specific phenomenon. This is important because one may argue that PIP2 accumulation we saw was a passive phenomenon in which lipids deposited to the area of contact and move away when contact resolved. If this were true, then we would expect to observe unselective sorting of other membrane lipids following solid particle binding.

For this, we tested lipid sorting profile of PC and phosphatidylethanolamine (PE) alongside PIP2. PC and PE are chosen based on their abundance in the lipid bilayer. We incubated PH-GFP-expressing RAW264.7 cells, and RAW 264.7 cells stained with TopFluor

TMR-PC and TopFluor TMR-PE, with 3µm biotin-BSA-coated polystyrene beads to investigate lipid sorting. We found that only PIP2, but not PC or PE, is preferentially accumulated at the membrane with bead engagement (Figure 4.3). Specifically, when we compare fluorescence signal in the membrane with bead contact against membrane without bead contact, only PIP2 displayed an elevated signal. The preferential accumulation of PIP2 is also evident in pseudopods wrapping around the beads.

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Figure 4.3 Preferential Sorting of PIP2 into Cell Membrane in Contact with Beads Figure 4.2.2 PIP2 (green), PC (red) and PE (red) were visualized with PH-GFP, TopFluor TMR- PC or TopFluor TMR-PE on RAW 264.7 cells incubated with 3μm biotin-BSA-coated polystyrene beads as in Figure 4.2. External beads were stained with Alexa Flor 405-conjugated streptavidin (blue). Line profiles corresponding to fluorescence intensities of labeled lipids were generated across the cell to enable comparison of intensities between the contact region and non- contact regions. N=3. Scale bars, 5µm.

We found in Chapter 3 that solid particle engagement of cell membrane can induce accumulation of moesin to the site of contact. In the above section, we showed that PIP2 is preferentially sorted to the site of contact on membrane engaged with solid particles. Also, it is established in the literature that moesin can bind to PIP2 via its FERM domain (Ben-Aissa et al.,

2012). Therefore, we sought to investigate the relationship between PIP2 and moesin by examining their accumulation dynamics in response to the same solid particle trigger.

For this, a ‘frustrated phagocytosis’ experimental model was introduced (Section 2.6.1).

Briefly, cells are grown on glass-bottom FluoroDish at 37 °C in a 5% CO2 humidified chamber

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and loaded onto microscopy stage following co-transfection of PLCδ-PH-mCherry and moesin-

EGFP to fluorescently visualize PIP2 and moesin, respectively. Next, we delivered a naked 6µm polystyrene bead glued to an AFM cantilever by Epoxy to a cell surface with constant force at 1 nN. Finally, fluorescence images of cells in contact with beads were recorded at indicated intervals for analysis (Figure 2.1).

We found that the localization of moesin mostly traces PIP2. PIP2 and moesin begin to enrich around that site of contact since the onset of engagement with the bead. At around 270 seconds, PIP2 and moesin seem to stabilize around the bead and the fluorescent intensity further increase until plateaued around 400 seconds (Video 4.3). This is further confirmed when we quantitatively analyzed the dynamics of PIP2 and moesin distribution around the 6µm polystyrene bead (Figure 4.4). When the fluorescence signals between the bead-engaged membrane and non-engaged membrane were compared, we found that the fluorescent intensity increased over time for both PIP2 and moesin at the site of contact, judged from the kymograph and kinetics graph. On the other hand, fluorescence signals for PIP2 and moesin for non-engaged membrane suffered slight decrease over time, possibly due to the need of the cell to concentrate

PIP2, and by association moesin, to the site of contact for such frustrated phagocytosis because the cell was constantly trying to engulf the particle by enriching PIP2.

In summary, we have established an association between PIP2 and moesin during solid particle phagocytosis. Combined with existing literature, we suggest that PIP2 sorting can lead to moesin activation and accumulation at the site of contact. Refer to discussion in Section 4.3 on how to strengthen this claim and definitively establish the causal link between PIP2 and moesin.

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Video 4.3 Dynamics of PIP2 and Moesin Accumulation around Solid Particles Fluorescence images of moesin-EGFP and PLCδ -PH-mCherry-expressing RAW264.7 cells at 37 °C in contact with a naked polystyrene bead (indicated with “*”) glued to an AFM cantilever at indicated time points. The complete video is accessible at https://goo.gl/6nmjMT.

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Figure 4.4 Quantitative Analysis of PIP2 and Moesin Accumulation around a naked 6µm Polystyrene Bead PLCδ -PH-mCherry and moesin-EGFP were co-expressed in RAW 264.7 cells. A 3μm polystyrene bead was used to make contact with the cell surface at 37°C. Images were taken at a 6s interval for 500 s. Localization of PIP2 and moesin at the site of contact (indicated with “*”) was examined with kymographs generated from the indicated line. The normalized fluorescence is defined as the ratio of the fluorescence intensity PLCδ -PH-mCherry, which probes PIP2 or moesin-EGFP at the site of contact over non-contact regions on the cell membrane (right). N=3. Scale bar, 5μm.

Finally, to fundamentally establish the necessity of PIP2 for phagocytosis, we confirmed with phagocytosis assay that, when PIP2 was sequestered with Geneticin, which was reported to chelate PIP2 via competitive binding at 1:1 molar ratio (Gabev et al., 1989; Nawaz et al., 2009), at an inhibitory concentration of 10 mM (Figure 4.5a and Figure 4.5b), phagocytosis of naked

3µm polystyrene beads was impaired (Figure 4.5c).

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(a)

(b) (c)

Figure 4.5 Sequestration of membrane PIP2 Leads to Impairment of Phagocytosis of Solid Particles (a) Distribution of PLCδ -PH-GFP in RAW264.7 cells following incubation with 10 mM Geneticin at indicated time points. The video can be accessed at https://goo.gl/aUH2DJ. (b) The efficiency of PIP2 sequestration was determined by treating stable PH-GFP-expressing RAW264.7 cells with 0 (video accessible at https://goo.gl/HNv6Z6), 1(video accessible at https://goo.gl/3t4n3W) or 10 mM Geneticin and counting the different types of PLCδ -PH-GFP subcellular localization. Cells were categorized into three different phenotypes. None: no visible sequestration of PIP2, thus PLCδ-PH-GFP is membrane-localized, Partial: Some PIP2 sequestration, thus PLCδ -PH-GFP shows increased presence in the cytosol while with significant retention in the plasma membrane. Complete: PIP2 is completely sequestrated, thus no visible retention of PLCδ-PH-GFP in the membrane but only cytosol localization. (c) Phagocytosis efficiency was examined for both RAW 264.7 and DC 2.4 cells in the presence of 0, 1 and 10mM Geneticin with incubation of 3µm biotin-BSA-coated beads at 37 °C for 40 minutes following initial treatment of Geneticin for 10 minutes. n=50, N=4.

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Taken together, in Section 4.2.1, we have demonstrated that, for solid particle phagocytosis, PIP2 is a major lipid species enriched in the sites of contact with solid particles and is necessary for eventual internalization. Also, we suggest that PIP2 aggregation at the site of contact likely causes downstream enrichment of moesin.

4.2.2 PIP2 Sorting by Solid Structures is Autonomous

We have established that PIP2 can accumulate at the site of contact following membrane engagement to solid particles. In other words, a localized pool of PIP2 is formed at the site of contact. Therefore, it is of interest to investigate the upstream trigger of such localized PIP2 concentration.

When comparing the PIP2 clustering profile between a phagocytic cell line, RAW 264.7, and a non-phagocytic cell line, HEK 293T, we observed similar spatiotemporal patterns of PIP2 accumulation (Figure 4.6). This implies that regardless of whether a cell is phagocytic

(RAW264.7, Video 4.4) or not (HEK293T, Video 4.5), the redistribution of PIP2 could occur.

Kymograph analysis showed sustained accumulation of PIP2 at the site of contact until the beads are pulled away from the site of contact. Statistical analysis of over ten cells, for each cell type, in touch with a bead revealed that only PIP2 could redistribute to the site of contact at the plasma membrane, showing a ~3-fold increase of fluorescence intensity at the site of contact over the remaining non-contact region of the plasma membrane. The level of PC and PE remained similar at the site of contact compared to the remaining non-contact region of the cell (Figure 4.6).

Therefore, we found, when in contact with a polystyrene bead at a constant force, PIP2, but not PC or PE, on the cell membrane redistributed itself to the site of contact. More

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importantly, such PIP2 aggregation at the site of contact is independent of phagocytic signaling apparatus, including moesin.

(a) (b)

Figure 4.6 Quantitative Analysis of PIP2 Accumulation around a naked 6µm Polystyrene Bead in RAW264.7 and HEK293T Cells (a) PLCδ -PH-GFP -expressing RAW 264.7 or HEK 293T cells at 37°C were touched with a single 3 μm polystyrene bead and were recorded with a 6 s interval for 900 s and 1,200 s, respectively. Polarized distribution of PIP2 upon touching at the site of contact (indicated with “*”) on cell membrane was examined with kymograph. (b)The normalized fluorescence of PIP2, PC, and PE was calculated for RAW 264.7 and HEK 293T cells (right). n≥10, N=3. Scale bars, 5µm.

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Video 4.4 Dynamics of PIP2 Accumulation around Solid Particles in RAW264.7 Cells Fluorescence images of PLCδ -PH-GFP-expressing RAW264.7 cells at 37 °C in contact with a naked polystyrene bead (indicated with “*”) glued to an AFM cantilever at indicated time points. The complete video is accessible at https://goo.gl/hW3MM8.

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Video 4.5 Dynamics of PIP2 Accumulation around Solid Particles in HEK293T Cells Fluorescence images of PLCδ -PH-GFP-expressing HEK293T cells at 37 °C in contact with a naked polystyrene bead (indicated with “*”) glued to an AFM cantilever at indicated time points. The complete video is accessible at https://goo.gl/mmtWGz.

Since we have shown that downstream phagocytic signals are dispensable for the local concentration of PIP2 at the site of contact, we wonder if PIP2 sorting at the plasma membrane is an autonomous phenomenon in response to physical engagement of solid particles to the plasma membrane.

To test this hypothesis, we first created a system devoid of any enzymatic activity or protein structures but with viable plasma membrane containing native compositions.

Specifically, we generated surface-biotinylated GPMVs from RAW264.7 cells or HEK293T 139

cells and labeled them with fluorescent PIP2, PC or PE (Sezgin et al., 2012). Second,

NeutrAvidin-coated circular, rectangular and triangular micropatterns with a nominal diameter of

3μm and spacing of 3μm to 6μm were made from polydimethylsiloxane (PDMS) to provide solid structures with defined shapes (Figure 4.7) for biotinylated GMPV anchorage. Next, we incubated biotinylated GPMVs labeled with fluorescent PIP2, PC or PE with NeutrAvidin-coated

PDMS micropatterns and recorded the fluorescent intensity changes of lipids.

Specifically, fluorescent intensities of labeled-lipids in regions in contact with a pattern were compared against the regions without contact, as demonstrated in Figure 4.8b, to determine if there is a redistribution of lipids following solid structure contract. We found that PIP2, but not

PC or PE, showed a ~ 3-fold increase in the contact regions regardless of the shape of micropatterns (Figure 4.8c). Furthermore, when we viewed the fluorescence signals of BODIPY

FL-PIP2 from the side, the membrane in contact with both the triangle-shaped pattern and square-shaped pattern appeared to be thicker and brighter than rest of the membrane (Figure 4.9).

This suggests the active accumulation of PIP2 into the site of contact. Since all enzyme activities were abolished in GPMVs, these results suggest that PIP2 sorting in response to physical contact of a solid pattern does not require any downstream cellular activities. This means simple physical contact at the plasma membrane is sufficient to trigger PIP2 sorting, and such sorting appears to be independent of cell type or target shape tested in this experiment.

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Figure 4.7 SEM images of PDMS micropatterns.

The magnification is 2000 (top-left), 5000 (top-right), 5000 (bottom-left) and 10000 (bottom- right). The images were acquired by imaging core facility at Tsinghua University from the provided samples.

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(a)

(b) (c)

Figure 4.8 Preferential Sorting of PIP2 into GPMV Membrane in Contact with Beads. (a) Biotinylated-GPMVs were labeled with BODIPY FL-PIP2, TopFluor-TMR PC or PE and incubated with PDMS triangular and rectangular patterns coated with NeutrAvidin. Images were taken when GPMVs were settled onto a specific pattern. (c) The pattern-contact region of GMPV was defined as the contact region and its apical surface was defined as the non-contact regions for measurement. (b) Fold changes, defined as the ratio of fluorescence intensity of a given lipid at the pattern contacting regions over non-contacting regions, were measured for all shapes with or without 10 mM NaN3. n≥30, N=5. Scale bars, 5µm.

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(a) (b)

Figure 4.9 PIP2 Sorting on GPMV Membranes in Contact with PDMS Micropatterns (a) Orthogonal views of BODIPY FL-PIP2 signals with a GMPV in contact with a triangle- shaped PDMS micropattern. The complete video depicting the entire volume can be accessed at https://goo.gl/nTi7s6. (b) Orthogonal views of BODIPY FL-PIP2 signals with a GMPV in contact with a square-shaped PDMS micropattern. The complete video depicting the entire volume can be accessed at https://goo.gl/mwzZ7E. Scale bars, 3µm.

4.2.2.1 Possible Triggers for PIP2 Sorting

In the previous section, we have demonstrated that the physical engagement of solid structures of solid particles can serve as a trigger for PIP2 sorting. Next, we explored some physical properties and attempted to determine if they are relevant to PIP2 sorting.

First, it was reported that PIP2 clustering correlates with membrane curvature change from molecular simulation studies on complex lipid bilayers. Therefore, we investigated whether

PIP2 sorting involves membrane curvature change. For this, we examined the contacting region of two joining GPMVs and compared the fluorescence signals of labeled-lipids in the contact region against the rest of the membrane. We found that, in the contacting region where the

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curvature of membrane changed due to slight contact, PIP2, but not PC or PE, showed significant enrichment (Figure 4.10a). It is important to note that the enrichment of PIP2 here is not merely additive like PC and PE. Instead, a synergistic accumulation of PIP2 was observed, as we found more than two-fold increased of PIP2 compared to the additive amount (Figure 4.10b). The results indicated that the membrane curvature change induced by gentle contact could account for PIP2 sorting. However, it should be noted that whether the curvature per se directly cause

PIP2 sorting is still unclear.

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(a) (b)

Figure 4.10 Specific Sorting of PIP2 on GPMV Membranes in Contact with Each Other (a) GPMVs labeled with BODIPY FL-PIP2 (top), TopFluor-TMR PC (middle) or PE (bottom) and were imaged when two GPMVs were in contact with each other. Line profiles corresponding to fluorescence intensities of labeled lipids were generated across the membrane in contact and two other non-contact ends to enable comparison of intensities between the contact region and non-contact regions for display here. (b) Fold changes, defined as the ratio of fluorescence intensity of a given lipid at the pattern contacting regions over non-contacting regions, were measured for all lipid species. n≥20, N=4.

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The next physical property we aimed to investigate is particle stiffness. We chose to focus on particle stiffness because it was shown that it could affect the dynamics of FcγR- mediated phagocytosis (Beningo and Wang, 2002; Wells, 2008). To do this, we first synthesized a series of polystyrene microparticles with varying degrees of stiffness by manipulating the degree of cross-linking (from 10% to 90%), and their stiffness was determined individually by

AFM based-nanoindentation (Figure 4.11a). Next, we test the ability of RAW264.7 to internalize these beads. We found that phagocytosis was more efficient when beads were more rigid. Specifically, when the Young’s Modulus of beads falls below ~2.5GPa, phagocytosis efficiency is drastically reduced (Figure 4.11b). Non-parametric correlation analysis resulted in a

Spearman coefficient r=1 (p=0.0083), indicating that stiffness of phagocytic target is indeed positively correlated with phagocytic efficiency (Figure 4.11c). Whether PIP2 sorting is changed with particle stiffness remains to be determined.

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(a) (b)

(c)

Figure 4.11 Correlation between Efficiency of Solid Particles and Particle Rigidity (a)Polystyrene beads with different degrees of cross-linking on glass surfaces were subjected to force-indentation displacement probing with a stiff probe. Forces ranging from 100 to 1,500 nN were applied to a single bead, and indentation depth was recorded for each probing. The values of stiffness (Young's Modulus) were obtained via indentation analysis with Veeco software. n≥ 12, N =3. (b) RAW 264.7 cells were incubated with 3µm, biotin-BSA-labeled polystyrene beads with varying degrees of cross-linking for 90 mins at 37 °C. The efficiency of phagocytosis was analyzed as per phagocytosis assay. n=50, N=4. (c) Correlation analysis of Stiffness (Figure 4.2.13) and Phagocytosis efficiency (Figure 4.2.14) by the non-parametric method. Spearman’s rank correlation coefficient r=1. p=0.0083<0.05.

To summarize, in section 4.2.2, we have established that PIP2 can autonomously sort into the site of contact at the initiation of the moesin-mediated solid particle phagocytosis. Such PIP2 sorting is triggered by physical contact of the solid particle to the plasma membrane, and membrane curvature, and possibly particle stiffness, might serve as such triggers.

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4.3 Discussion

This chapter aims to identify the lipid species, possibly PIP2, sorted in moesin-mediated solid particle phagocytosis and to investigate the mechanism of action of such lipid in moesin- mediated solid particle phagocytosis.

First, we demonstrated separately with super-resolution microscopy and live-cell imaging that PIP2 is preferentially sorted into the site of contact in response to membrane engagement with solid particles. One might propose that it would be more convincing to demonstrate this with super-resolution microscopy with live cells. In fact, we attempted this with a DeltaVision

OMX SR imaging system. This commercial system is advertised to super-resolve live cells with

3D SIM thus allowing for dynamic super-resolution live-cell imaging. We failed in numerous attempts as we found our fluorophores quickly photobleached with this system even after optimization. This means we could not obtain images with both high spatial and temporal resolution on this system. Since there was also no better alternative for the fluorophore, we ultimately concluded that such method was not achievable with our samples. However, this method itself is valid and might be applicable to other samples.

Of interest was the discovery that the dynamics of PIP2 redistribution around the phagocytic target is similar to that of FcγR-mediated phagocytosis. This suggests that, besides the use of different ITAM-containing molecules, these two pathways likely share a plethora of signaling molecules.

Biotin-BSA coated beads were used instead naked beads for the need to stain for external beads. One could question the interchangeable use of these beads. Refer to Section 3.3 for an extended discussion on this matter. Here, I would like to suggest that the preferential sorting of

PIP2 seem to be similar for biotin-BSA and naked polystyrene beads. This was demonstrated by

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the similar PIP2 accumulation patterns observed in Figure 4.4 and 4.6. The use of biotin-BSA- coated beads is only specific for this experiment as it was needed to determine if the beads were internalized.

Next, we adopted a “frustrated phagocytosis” model to study the redistribution of PIP2 and moesin in live cells. We found that moesin accumulation on membranes mostly traces the sorting of PIP2 following engagement of naked polystyrene beads to the cell membrane. Based on this, and combined with existing literature, we suggested that PIP2 sorting can lead to moesin activation and accumulation at the site of contact. However, several improvements can be made to strengthen this link. Most critically, it is beneficial to establish that PIP2 binds to moesin following solid particle engagement with the membrane. First, the physical binding of PIP2 to moesin remained to be demonstrated. This is typically achieved by incubating model membranes such as large unilamellar vesicles (LUVs) containing defined lipid compositions like BODIPY-

FL-PIP2 with purified protein followed by co-sedimentation assays (Blin et al., 2008). It is worth noting, however, that other groups have demonstrated the physical binding moesin to PIP2, although not in the context of phagocytosis (Ben-Aissa et al., 2012; Hao et al., 2009; Yonemura et al., 1998).

We have also demonstrated the necessity of PIP2 for solid particle phagocytosis via the use of PIP2 chelator Geneticin. PIP2 depletion can also be achieved via a more elegant, and most importantly, more specific method (Suh et al., 2006). Briefly, FK506 Binding Protein (FKBP)-

Ins54p, Lyn11-FKBP-Rapamycin Binding (FRB) domain, alongside PIP2 sensor PH-PLCδ-GFP are overexpressed in a cell line. During resting state, FRB-Lyn11 is anchored to the plasma membrane via myristoylation and palmitoylation sequence in Lyn11. Ins54p, a PIP2 specific phosphatase, is localized in the cytosol. Following addition of rapamycin, Ins54p is recruited to

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the membrane. Rapamycin serves to bridge FRB and FKBP to form a stable signaling complex.

PIP2 is hydrolyzed by the phosphatase activity of Ins54p. This is evidenced by the shedding of

PIP2 sensor PH-PLCδ-GFP from the plasma membrane to the cytosol, which is the same as the results shown in (Figure 4.5a). Despite the superior feature of this PIP2 depletion system, we failed to establish such system in any phagocytes. This is mainly due to the challenge associated with overexpressing and maintaining expression for three different proteins in phagocytic cells.

We were able to establish this in easy-to-transfect cell lines such as HEK293T. However,

HEK293T was not usable since it is not phagocytic, as quantitative measurement of the efficiency of phagocytosis in RAW264.7 cells or other phagocytes was needed.

As we showed that a localized pool of PIP2 is formed at the site of contact, we wonder what the upstream triggers cause such localized PIP2 concentration. Primarily, there are two mechanisms for local PIP2 concentration: PIP2 release from sequestration and PIP2 association with membrane rafts.

First, we discuss the possibility of PIP2 release from sequestration. During resting state, some PIP2 molecules are attracted to MARCKS on the plasma membrane. MARCKS is a ubiquitously expressed protein, and it contains a cluster of basic residues known as basic effector domain. One MARCKS protein can bind to three tetravalent acidic PIP2 molecules via its basic effector domain via electrostatic interactions. Consequently, MARCKS proteins can sequester a pool of PIP2 which is available for release to signal (Gambhir et al., 2004).

The pool of sequestered PIP2 is made available for signaling, and for detection by PH-

PLCδ-GFP in experiments, by disruption of electrostatic interactions between PIP2 and

MARCKS. First, PKC phosphorylation of MARCKS can disrupt the electrostatic interaction. It was reported that phosphorylation of serine residues in the basic effector domain cause a reduced

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electrostatic attraction for the membrane. This leads to the translocation of MARCKS to the cytoplasm. Second, Calcium-calmodulin interacts directly with the basic residues of the effector domain. This also allows the translocation of MARCKS from the membrane. Consequently, the release of MARCKS leads to the formation of a localized pool of PIP2 for signaling (Gambhir et al., 2004).

We have demonstrated first with HEK293T membranes in contact with a bead that PIP2 sorting can still occur (Figure 4.6), thus suggested that phagocytic machinery, including moesin, is not required for PIP2 sorting at the plasma membrane. Furthermore, we have demonstrated with GPMVs, which is devoid of any enzymatic activities, in contact with solid micropatterns that PIP2 is preferentially sorted into the site of contact in an autonomous manner (Figure 4.8).

Therefore, MARCKS release from the membrane, which requires enzymatic activities from signals either feeding into PKC or Calcium-calmodulin (Hartwig et al., 1992), is not the most likely option to explain the formation of the localized pool of PIP2.

Another possibility for local PIP2 concentration is the association of PIP2 with membrane rafts. We note that this thesis is not focused on membrane rafts, and it falls outside our areas of expertise, but it is an important concept that warrants some discussion. Therefore, I aim to describe it in simple terms enough to facilitate further discussions. For more comprehensive views and details on membrane rafts, I refer readers to works by Dr. Kai Simons and associates (Lingwood and Simons, 2010).

In general, membrane rafts serve as signaling platforms. They act to increase the kinetics of signaling by concentrating substrates and enzymes together in the same membrane microenvironment. Membrane rafts are heterogeneous, ranging from nanoclusters that are 10 nm in size and contain only a few protein molecules to nanodomain complexes that are tens of

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nanometers in diameter, and even bigger microdomains (Lingwood and Simons, 2010).

Immunological synapse in stimulated lymphocytes and raft-enriched adhesion complexes are examples of such microdomains (Dustin, 2002). These raft microdomains are usually formed when smaller nanodomains with distinct compositions coalesce following receptor crosslinking.

For example, it was reported that spatial rafts coalesce after FcγR crosslinking and it is independent of Src family kinase activation (Kono et al., 2002). Consequently, the formation of microdomains from the coalescence of nanodomains allows for spatial confinement of otherwise spatially-segregated molecules to initiate signaling.

Lipid rafts can be defined by the high degree of lipid order, which is caused by the presence of high concentrations of cholesterol, sphingomyelin and saturated phospholipids with long acyl chains (Coskun and Simons, 2010). Membrane order is an indicator of how tightly lipids are packed within specific membrane microenvironment. Because rafts are usually concentrated with cholesterol and other lipids and proteins with propensities to tightly pack with each other, membrane orders are usually high in rafts and low in non-raft membrane domains.

Membrane packing order can be measured by Generalized Polarization (GP) values from c-laurdan-based radiometric imaging (Gaus et al., 2003). C-laurdan, or 6-dodecanoyl-2-[N- methyl-N-(carboxymethyl)amino]naphthalene, is a lipophilic dye capable of partitioning into plasma membrane. When c-laurdan is excited at the 405 nm, its emission spectrum peaks at

~450 nm when in ordered membrane domains, and redshifts to 525 nm when in disordered, or fluid, membrane domains (Kim et al., 2007). Cell membrane or model membranes are incubated with c-laurdan, and the intensity of two emission channels is simultaneously recorded. The emission ratio, also termed Generalized Polarization (Yu et al., 1996), gives a quantitative measure of membrane lipid order. Therefore, higher GP values usually indicate higher membrane

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order, which translates into potential presence of membrane rafts. However, it should be noted here that, rather than detecting individual lipid rafts, GP values from c-laurdan microscopy reveal the overall membrane order. Thus, no information can be inferred regarding the size of membrane rafts.

To preliminarily test whether local PIP2 concentration is caused by its association with membrane rafts, we performed c-laurdan microscopy followed by GP analysis described above.

Briefly, PH-PLCδ-mCherry-expressing RAW264.7 cells were cultured on PDMS micropatterns are incubated with 1 µM c-laurdan. For GP analysis, cells were excited at 405 nm, and images were recorded with 450nm and 525 nm for ordered and disordered membranes, respectively. GP images were calculated via radiometric imaging methods (Owen et al., 2011). Also, mCherry signals were also collected at the same time to assess PIP2 sorting. TopFluor-TMR PC and PE were also used as controls for other lipid species.

We found that PIP2 sorting around the contact regions on the membrane with PDMS micropatterns coincides with ordered membranes (Figure 4.12a). Moreover, GP analysis revealed that GP values were exceptionally high at the regions where PIP2 were sorted in contact with PDMS micropatterns. Further analysis revealed that PIP2, but not PE or PC, is sorted into highly ordered (defined as GP> 0.5) membranes. Taken together, these results suggest that PIP2 are specifically sorted into highly ordered membrane following engagement with solid structures.

Therefore, it is likely that membrane rafts, indicated by high membrane orders, is involved with

PIP2 sorting. Cautions should be taken to extrapolate this data further. For example, these results do not establish that membrane rafts directly cause PIP2 sorting even though common sense based on current literature seems to suggest so. Therefore, it would of interest to determine if

PIP2 interacts with any raft lipids or protein. I refer readers to section 6.2.2 for further discussion

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on the potential involvement of lipid rafts in moesin-mediated solid particle phagocytosis. For this chapter, it suffices to acknowledge that rafts might be involved in PIP2 sorting. In addition, section 6.2.1 will focus on discussion of the implication for signaling at the fundamental level for such association.

It should be cautioned here that the use of a fluorescent lipid label, such as c-laurdan, can alter membrane behavior. Therefore, label-free imaging technique can be used to study membrane domains. In particular, AFM can be used to measure membrane domains and associated change induced by triggers in model membranes (Lin et al., 2007). For this study, since visualization of proteins in live cell was required, light-based microscopy was favored.

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Figure 4.12 Preferential Sorting of PIP2 into Highly Ordered Membranes on RAW264.7 Cells Engaged with PDMS Micropatterns (a) PH-PLCδ-mCherry-expressing RAW264.7 cells were cultured on PDMS micropatterns (indicated with yellow ‘*’) are incubated with one µM c-laurdan. TopFluor-TMR PC and PE were used as controls for other lipid species. For GP analysis, cells were excited at 405 nm, and images were recorded with 450nm and 525 nm for ordered (blue) and disordered (green) membranes, respectively. Also, mCherry signals were also collected at the same time to assess PIP2 sorting (red). GP images were calculated via radiometric imaging methods detailed in Owens 2011. Specifically, GP= (I450-G×I525)/(I450-G×I525), where G is experimentally determined using a solution 10 µM c-laurdan in DMSO following a procedure described previously. (Kim) G is the sensitivity correction factor for the two different wavelengths. The purpose of its introduction is to ensure GP values are directly comparable between samples. Scale bars, 5µm (b) The number of micropattern-induced membrane with high membrane orders (GP>0.5) and lipid accumulation were counted for every individual cell. Comparisons were made between different lipid species. n≥38, N=3.

Caution should be noted here regarding PIP2 accumulation and interpretation of related results. First, although we have demonstrated with GPMVs that PIP2 can accumulate at the site of contact, PIP2 synthesis and turnover is likely still involved in such accumulation in live cells.

Second, the identify of PIP2 used in our in vitro studies should be further scrutinized.

Specifically, PIP2 exists as many different species even for a single PI(4,5)P2 class depending on the composition of acyl chains as they vary in different tissues for any given organism. The most common form of PI(4,5)P2 typically contains a saturated stearic acyl chain and an unsaturated arachidonic acyl chain (Sun et al., 2013). However, the PI(4,5)P2 used in GPMV-related studies are synthetic PIP2 which contains two saturated acyl chains. This help explain why PIP2 are sorted into the site of contact on GMPVs as lipids with saturated acyl chains tend to be partitioned into membrane rafts because they can induce tight packing, thus promoting the formation of ordered membranes (van Meer et al., 2008). The identity of the exact PI(4,5)P2 species remains to be determined in relation to moesin-mediated solid particle phagocytosis.

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Third, throughout this thesis, we used PC and PE as control lipids for PIP2-related studies. It should be noted here that both PC and PE are zwitterionic with a net charge of 0, whereas PIP2 is negatively charged (van Meer et al., 2008). Therefore, is might be helpful to charge match PIP2 with PS, which is also negatively charged, as a control lipid species.

Our results also suggested membrane curvature as a trigger for PIP2 sorting. It is unclear if curvature change itself can cause PIP2 sorting or it is merely an intermediated induced by contacting force. Moreover, whether curvature change can cause coalescence of membrane rafts remains to be investigated.

Also, despite that we showed that efficiency of solid particle phagocytosis increases with particle rigidity, it remains to be studied if PIP2 sorting depends on particle rigidity.It can be investigated by touching cells with synthesized polystyrene beads with varying degrees of stiffness and determine if kinetics of PIP2 accumulation is different on GPMVs. In addition,

PDMS micropatterns used in GPMV-related studies are generally softer than polystyrene beads.

Therefore, it is of interest to determine if the mechanism of PIP2 accumulation differ between these two materials.

In summary, in this chapter, we showed that PIP2 is preferentially sorted into the site of contact following engagement of membrane with solid structures. Moreover, we showed that such sorting is sufficiently triggered by physical contact. Specifically, we suggested that membrane rafts and curvature may serve as such triggers.

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Chapter Five: Characterization of Moesin-, PIP2 -mediated Solid Particle Phagocytosis and its Place in Evolution

5.1 Introduction and Aim

5.1.1 Introduction

In Chapter 3 and 4, we have established that solid particle phagocytosis is moesin- dependent and that PIP2 sorting at the plasma membrane is triggered by solid particles engagement with the membrane is an autonomous manner. We aim to further characterize the mechanism for this solid particle phagocytosis.

We have established that upon particle engagement at the plasma membrane, PIP2 autonomously sorted into the site of contact during moesin-, PIP2-mediated solid particle phagocytosis, which consequently leads to phagocytosis of naked polystyrene beads. In those models, a streptavidin/biotin interaction was provided for particle/membrane engagement. We wondered if such phagocytic mechanism can be universally applied to any other particle/membrane interaction. In other words, we have shown that surface engagement alone is sufficient to trigger PIP2 sorting and phagocytosis in phagocytic cells via recruitment of moesin

ITAM to the cell surface. If this hypothesis is indeed correct, one would expect phagocytosis to be induced in non-phagocytic cells at certain levels when the requirements for sufficient particle/surface binding and ITAM availability are met. This is important because of one major outstanding issue for the mechanism of moesin-, PIP2-mediated solid particle phagocytosis is the involvement, or the lack of involvement of surface receptors. We have previously demonstrated with MSU and alum crystals that this solid particle phagocytosis does not seem to require the involvement of surface receptors (Flach et al., 2011; Ng et al., 2008). Assuming there is no involvement of receptors, what is the trigger in moesin-, PIP2- mediated phagocytosis that is

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equivalent to specific receptor-ligand binding found in FcγR-mediated phagocytosis? Regarding the idea of Signaling Equivalent Platform introduced in Section 1.5.4.5.2, is solid particle binding to membrane truly equivalent to ligand/receptor binding? Hence, it is beneficial to investigate the minimally essential requirement for solid particle phagocytosis with a particular focus on the requirement of particle/surface binding.

Also, it is of interest to comparing moesin-, PIP2-mediated solid particle phagocytosis with other mechanisms of phagocytosis.

First, FcγR-mediated phagocytosis is well-studied. It is established that PIP2 involved in

FcγR-mediated phagocytosis similar to what we found in Chapter 4. Also, Syk and PI3K are critical players for FcγR-mediated phagocytosis. Therefore, it is of interest to directly compare phagocytosis efficiency and signaling between two modes of phagocytosis.

Second, scavenger receptor is another group of surface receptor we focus on. They are non-opsonic phagocytic receptors lacking any apparent signaling motif like ITAM in their short cytoplasmic tails (Bowdish and Gordon, 2009). However, they can internalize a variety of particles, including silica crystals, polystyrene beads and Streptococcus pneumoniae (Arredouani et al., 2005; Kanno et al., 2007; Novakowski et al., 2016). Analysis of the signaling pathways required for macrophage scavenger receptor-mediated phagocytosis indicated that tyrosine phosphorylation, ERK, PI3K and Cdc42 activation, which are all found with moesin-mediated solid particle phagocytosis, were all required for SR-mediated phagocytosis (Sulahian et al.,

2008). Also, SRs were generally viewed as co-receptors (Bowdish et al., 2009), meaning the possibility of ITAM involvement during SR-mediated phagocytosis should not be excluded.

Therefore, we wonder if moesin can serve as an ITAM signaling platform during SR-mediated phagocytosis.

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Lastly, we aim to investigate phagocytosis from an evolution standpoint. It has been known for a long time that, Amoeba Proteus, a single-celled eukaryotic organism, can efficiently take up solid particles such as polystyrene beads (Sobczak et al., 2008). Amoeba has long been here on earth before human start to synthesize polystyrene beads. This means that the phagocytic mechanism built into amoeba could not have co-evolved with beads. Also, none of the modern- day phagocytic receptors is present in amoeba (Shi, 2012; Yutin et al., 2009). Therefore, the phagocytic mechanism used by amoeba could be very conserved. We wonder if moesin-, PIP2- mediated phagocytosis, which also appears not to utilize any receptors, represents a primordial form of phagocytosis compared to modern day phagocytosis exemplified by FcγR-mediated phagocytosis. In other words, we want to investigate if such mechanism is evolutionarily conserved.

5.1.2 Aim

This chapter aims to characterize the moesin-, PIP2-mediated solid particle phagocytosis and to determine if such mechanism is evolutionarily conserved.

5.2 Results

5.2.1 Sufficient Level of Particle/Surface Binding and ITAM Availability are Prerequisites for Successful Phagocytosis

It has been shown that overexpression of FcRIIa alone in COS-1 cells can induce phagocytosis of IgG-coated particles (Indik et al., 1995). Here, FcRIIa serves two principal purposes. First, it allows binding with IgG via its extracellular domain. Second, it provides a pool of immediately available ITAM in its cytoplasmic tail.

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We have shown that, for moesin-, PIP2-mediated solid particle phagocytosis, ITAM of moesin is required for phagocytosis. Also, we found that surface ligation of solid particles to the cell membrane is sufficient to cause PIP2 sorting and moesin accumulation to the site of contact.

Therefore, we first attempt to induce phagocytosis in COS-1 cells with overexpression of moesin

ITAM with Syk supplemented to enhance phagocytosis.

To our dismay, the results showed that overexpression of moesin and Syk can not induce significant phagocytosis of biotin-coated beads, unlike FcγRIIa does with IgG-coated beads.

Even when we overexpress the constitutively active form of moesin, phagocytosis was kept at the basal level (Figure 5.1).

Since there is no reason to doubt that moesin is expressed to provide a pool of ITAM, one possibility for such failure is that the degree of engagement was not strong enough between the

COS-1 cell membrane and biotin-coated polystyrene beads. On the other hand, the successful induction of phagocytosis with FcRIIa overexpression must indicate that the binding of IgG- coated beads and FcRIIa is sufficiently strong to trigger downstream phagocytic events.

To test such possibility, we created fluorescently tagged chimera with full-length CD4 linked with moesin ITAM and necessary control chimera, as depicted in Figure 5.2. This will allow strong binding of ITAM-bearing CD4 to anti-CD4 coated polystyrene beads, as the strength of binding between CD4 and anti-CD4 is comparable to that of FcRIIa and IgG binding, presumably. Refer to Section 5.3 for more discussion on this comparison. Also, we expect the moesin ITAM linked with CD4 act as a pool of membrane ITAM for signaling. The chimeras were transiently overexpressed in non-phagocytic COS-1, COS-7, HEK293T and NIH

3T3 cells, and phagocytosis efficiency was measured with biotin-BSA-coated polystyrene beads.

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We successfully induced phagocytosis not only in COS-1 cells but also in COS-7 cells.

This was demonstrated by the observation that both COS-1 and COS-2 overexpressing CD4-

ITAM chimera displayed a significant level of increase in phagocytosis efficiency, similar to that of FcγRIIa. Surprisingly, we found that overexpression of ITAM dead mutant, CD4-IYAM-YF, in COS-1 and COS-7 cells can also induce phagocytosis, to similar levels of their wildtype

ITAM counterparts (Figure 5.3a, upper). This may seem counterintuitive at first, however, we later realized that endogenous expression of ERM proteins, including moesin, in these cell lines could serve as pools for ITAM to overcome the effects of ITAM dead mutation. Indeed, we detected ERM protein expressions in COS-1 and COS-7 cells (Figure 5.3b).

On the other hand, HEK293T and NIH3T3 were generally unresponsive to the attempt to induce phagocytosis by chimeras, or by FcγRIIa (Figure 5.3a, lower). We found ERM protein expression level is significantly lower in HEK293T and NIH3T3 cells compared to COS-1 and

COS-7 cells (Figure 5.3b). However, this does not explain the general failure to induce phagocytosis, especially by FcγRIIa. Therefore, HEK293T and NIH3T3 must lack some critical components of phagocytic machinery. Refer to Section 5.3 for more discussion on this.

Taken together, these results suggest that, in the presence of endogenous moesin, strong surface ligation itself was sufficient to trigger phagocytosis.

Further, when the same set of chimeras were overexpressed in moesin knockdown DC2.4 cells, only wildtype CD4-ITAM, but not mutant CD4-ITAM-YF, can partially restore phagocytosis (Figure 5.4) to about 75% of the original capacity. This likely suggests that the remaining expression of ERM is the moesin knockdown DC2.4 cells was not enough to mask the effects of ITAM-dead mutation to reinstate phagocytosis in CD4-ITAM-YF transfected cells.

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Therefore, in moesin knockdown DC2.4 cells, restoration of phagocytosis is critically dependent on the provision of wildtype ITAM on the chimeric receptors.

Overall, results from this section collectively indicate that strong surface ligation of solid particles to the cell membrane, either through receptor/particle interaction or lipid/particle interaction, can signal via moesin ITAM domain either recruited to the cell membrane or built into the cytoplasmic domain of a receptor. In short, sufficient particle/membrane binding and

ITAM availability are prerequisites for successful phagocytosis. Thus, we have demonstrated the equivalency between particle/surface binding and particle/receptor binding for solid particle phagocytosis.

Figure 5.1 Moesin/Syk Overexpression Failed to Induce Phagocytosis in COS-1 Cells COS-1 cells were overexpressed with EGPF-tagged wildtype moesin or its constitutively active mutant T558D, and mCherry tagged Syk. FcRIIA-EGFP was also expressed alone as a positive control. These cells were tested for their phagocytosis efficiency with IgG-coated beads or biotin-BSA-coated beads. N=3, n=40.

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Figure 5.2 Schematic Drawing of a Series of CD4-EGFP Chimeric Sequences. For CD4-ITAM chimeric protein, the N-terminal full-length CD4 is linked with a GSGGSG at its C-terminus to ITAM sequence YLKIAQDLEMYGVNYFSI from moesin. This ITAM sequence is linked with EGFP via the same GSGGSG linker at its C-terminus (top). For CD4- ITAM-YF mutant, tyrosine residues in the moesin ITAM sequence are mutated to phenylalanine (middle). For control, full-length CD4 is directly linked with EGFP at its C-terminus.

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(a)

(b)

Figure 5.3 Strong Particle/Surface Binding Can Induce Phagocytosis in Certain Non- phagocytic Cells (a) COS-1, COS-7, HEK293T and NIH3T3 cells were overexpressed with the CD4-EGFP chimera indicated in Figure 5.2 by transient overexpression. Empty vector negative control and FcRIIa positive control for phagocytosis efficiency were also shown. Cells expressing CD4- EGFP chimera and control were incubated with anti-CD4-coated beads while cells expressing FcγRIIa and control were incubated with IgG-coated beads, and phagocytosis efficiency was measured. n=50, N=3. (b) ERM expression in COS-1, COS-7, HEK293T and NIH3T3 cells. An equal volume of cell lysate from an equal number of cells was loaded for Western blotting probed by the anti-ERM antibody, and GAPDH was used as loading control. This experiment was completed by Libing Mu. 165

Figure 5.4 Partial Restoration of Phagocytosis in Moesin Knockdown DC2.4 Cells Induced by Strong Particle/Surface Binding Requires ITAM of Moesin on Chimeric Receptors Moesin knockdown DC2.4 or control cells were overexpressed with chimera indicated in Figure 5.2. Cells were incubated with anti-CD4-coated beads, and phagocytosis efficiency was measured. n=50, N=3.

5.2.2 Comparison of Moesin-, PIP2-mediated Phagocytosis with FcγR-mediated Phagocytosis

First, we compared the phagocytic efficiency of PIP2-, moesin-mediated phagocytosis with FcγR-mediated phagocytosis. We incubated 3µm, IgG-coated polystyrene beads with moesin knockdown and control DC2.4 cells and determined that there was no difference in

FcγR-mediated phagocytosis (Figure 5.5b). In contrast, uptake of biotin-BSA-coated polystyrene beads via moesin-, PIP2-mediated phagocytosis was significantly impaired as expected (Figure

5.5a). This suggests that moesin, which possibly serves as an ancient form of ITAM-containing molecule in solid particle phagocytosis, is no longer required for FcγR-mediated phagocytosis. In other words, moesin-mediated phagocytosis and FcγR-mediated phagocytosis are independent of

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each other. Also, it is evident that FcγR-mediated phagocytosis of IgG-coated polystyrene beads is much more efficient than moesin-mediated uptake of biotin-BSA-coated polystyrene beads in moesin knockdown DC2.4 cells, as FcγR-mediated phagocytosis quickly reached a plateau of around 90% internalization at around 15 minutes’ incubation time comparing to the 45 minutes’ time taken via moesin-, PIP2-mediated phagocytosis.

(a) (b)

Figure 5.5 Moesin-mediated Phagocytosis and FcγR-mediated Phagocytosis are Independent of Each Other The efficiency of moesin-mediated (a) and FcγR-mediated (b) phagocytosis was measured with 3µm biotin-BSA-coated beads or IgG-coated beads in moesin knockdown or control DC2.4 cells at indicated time points at 37 °C for 40 minutes. n=50, N =3.

Next, we compared moesin-, PIP2-mediated phagocytic pathway with the FcγR-mediated phagocytic pathway. First, we used R406, LY294002, and ML141 to specifically inhibit Syk,

PI3K, and Cdc42, respectively, alongside DMSO as vehicle control on RAW264.7 cells incubated with biotin-BSA- or IgG-coated beads. We found phagocytosis was significantly impaired when Syk, PI3K or Cdc42 were inhibited in cells incubated with either biotin-BSA- or

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IgG-coated beads. This suggests that core components of FcγR-mediated phagocytosis, such as

Syk, PI3K, and Cdc42, are all required for moesin-, PIP2-mediated phagocytosis (Figure 5.6a).

In addition, Western blotting analysis revealed that phosphorylation levels of Akt and Erk1/2 in moesin knockdown DC2.4 cells treated with IgG-coated beads were increased similarly to control DC2.4 cells treated with biotin-BSA-coated beads (Figure 5.6b). This suggests that downstream signaling activation, such as Akt and ERK is similar between moesin-, PIP2- mediated phagocytosis and FcγR-mediated phagocytosis.

(a) (b)

Figure 5.6 Moesin-mediated Phagocytosis and FcγR-mediated Phagocytosis Share Downstream Signals (a) Phagocytosis assays were performed on RAW 264.7 cells in the presence of R406, LY294002 and ML141, specific inhibitors for Syk, PI3K, and Cdc42, respectively. Biotin-BSA- coated beads and IgG-coated beads were used separately to establish a comparison between two phagocytic pathways. n=50, N=4. (b) Moesin knockdown and control DC2.4 cells were treated with IgG-labeled or biotin-labeled beads, respectively, for indicated times. Total cell lysates were immunoblotted with specific antibodies against p-Akt, Akt, p-Erk1/2, Erk1/2 and moesin. This experiment was completed by Libing Mu.

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Finally, we incubated 1,3 and 6µm IgG- or biotin-BSA-coated polystyrene beads with

RAW264.7 cells to compare the phagocytosis efficiency between moesin-, PIP2-mediated phagocytosis and FcγR-mediated phagocytosis with beads of different sizes. We found that IgG- coated beads (Figure 5.7a) were internalized more rapidly than biotin-BSA-coated beads ((Figure

5.7b). Specifically, internalization of IgG-coated beads by RAW264.7 cells all reached over 60% for all sizes at 15 minutes whereas biotin-BSA-coated beads were only internalized at a basal level of 20% after 15 minutes (Figure 5.7a). FcγR-mediated phagocytosis seems to plateau around 15 minutes of incubation. In contrast, moesin-mediated phagocytosis of biotin-BSA beads seem to reach its maxima after 45 minutes, but only for 3µm beads. It is unclear if internalization of 1µm beads is plateaued. The most pronounced difference was observed with

6µm beads. FcγR-mediated phagocytosis of 6µm beads was significantly higher than moesin- mediated phagocytosis for every time point reported. This difference was less striking but still significant for smaller beads. In general, FcγR-mediated phagocytosis is more efficient than moesin-mediated phagocytosis regardless of particle size. Moesin-, PIP2-mediated phagocytosis becomes much less effective than FcγR-mediated phagocytosis when particle size increases.

Refer to section 5.3 for further discussion.

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(a) (b)

Figure 5.7 Comparison of Phagocytosis Efficiency between Moesin-mediated Phagocytosis and FcγR-mediated Phagocytosis with Beads of Different Sizes Impact of particle size on the efficiency of (a) moesin-mediated t and (b) FcγR-mediated phagocytosis was measured via phagocytosis assay at indicated time points with 1, 3 and 6μm biotin-BSA- or IgG-coated polystyrene beads, respectively, in RAW 264.7 cells. n=50, N=4.

Further, we focused on the comparison between moesin-mediated phagocytosis and

FcγR-mediated phagocytosis with beads of different sizes phagocytosis at 45 minutes and found that IgG coating promoted small (1µm) bead internalization regarding the number of uptakes

(Figure 5.8a). Calculated results revealed that volume (Figure 5.8b) and surface area (Figure

5.8b) of IgG-coated beads were internalized much more significantly than biotin-BSA-coated beads. This confirmed again that moesin-, PIP2-mediated phagocytosis is not highly capable of phagocytosing bigger beads. This is likely caused by the stronger binding between FcγR and

IgG-coated polystyrene beads than biotin-coated polystyrene beads and cell surface. Refer to section 5.3 for further explanations.

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(a)

(b) (c)

Phagocytosis assays were performed with 1, 3, 4.5 and 6μm biotin-BSA-coated (red line) or IgG- coated (black line) polystyrene beads on RAW264.7 cells. The numbers of beads (a) internalized per cell on average were counted for each condition. Volume (b) and surface area (c) internalized by RAW264.7 cells were calculated from the following formula. Volume=4/3πr3, and Surface Area=4πr2. n=50, N=4.

Overall, we have demonstrated that moesin-mediated phagocytosis shares downstream signals with FcγR-mediated phagocytosis. Also, FcγR-mediated phagocytosis is much more efficient than moesin-mediated phagocytosis. Specifically, FcγR-phagocytosis is more rapid and capable when the size of the target is bigger.

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5.2.3 Moesin Contributes to Scavenger Receptor-mediated phagocytosis

Finally, we investigated if moesin is involved in SR-mediated phagocytosis. First, we coated 3µm polystyrene beads with MalBSA (maleylated-BSA, a ligand for SR-A6/SR-A1, previously known as MARCO/SR-A) (Takata et al., 1989). Next, we used BMDM from SR-A6 -

/- /SR-A1 -/- double knockout mice to test if MalBSA-coated beads are relatively specific for SR- mediated phagocytosis. We incubated MalBSA or BSA-coated beads with BMDM from SR-A6 -

/- /SR-A1 -/- DKOs. We found that only MalBSA-coated beads internalization was impaired compared BSA-coated beads (Figure 5.9a). Finally, we incubated MalBSA-coated beads with moesin knockdown or control DC2.4 cells to test if moesin deficiency would impair SR- mediated phagocytosis. We showed that, when moesin expression was knocked down in DC2.4 cells, internalization of MalBSA-coated beads was significantly impaired (Figure 5.9b). Taken together, we showed that moesin is somewhat involved in SR-mediated phagocytosis.

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(a)

(b)

Figure 5.9 Moesin might be Involved in Scavenger Receptor-mediated Phagocytosis (a) Phagocytosis assay performed on C57BL/6 WT and SR-A6-/- SR-AI-/- BMDM with MalBSA, an SR-A6 ligand, and BSA-coated beads at 37 °C for 40 minutes. n=50, N=3. (b) Phagocytosis assay was performed on moesin knockdown and control DC 2.4 cells with MalBSA, and BSA- coated beads at 37 °C for 40 minutes. n=50, N=3.

5.2.4 Moesin-, PIP2-mediated Phagocytosis is Evolutionarily Conserved

To investigate if this phagocytic mechanism is evolutionarily conserved. We first cloned moesin from earlier species like Caenorhabditis elegans, Drosophila melanogaster, and Danio rerio (Figure 5.10a). We then expressed these proteins in moesin knockdown DC2.4 cells to

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determine if phagocytosis can be restored. Indeed, moesin cloned from all earlier species successfully restored phagocytosis of biotin-BSA-coated beads (Figure 5.10b). This indicates that moesin-mediated solid particle phagocytosis is likely conserved in those species.

(a) (b)

Figure 5.10 Moesin Function in Solid Particle Phagocytosis is Conserved among Species

(a) Schematic of Moesin proteins in Mus musculus (Mm), Danio rerio (Dr), Drosophila melanogaster (Dm) and Caenorhabditis elegans (Ce), identified by NCBI Blast search. Functional domains and sequences of ITAM motif are shown. (b) Moesin knockdown DC2.4 cells were rescued with moesin from earlier species by transient overexpression. Vector transfection of the knockdown and wildtype DC2.4 cells were also shown. n=50, N=3.

The bioinformatic analysis displayed below and in Appendix C was conducted by Libing

Mu with inputs from Lin Miao. The author of this thesis included the data for the sake of completeness of the story. Refer to Appendix C for phylogenic trees.

Next, we built the maximum likelihood phylogenetic trees of the amino acid matrix for moesin (Figure C.1), FcR common γ chain and FcγRII (Figure C.2), PI3K catalytic subunit

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(Figure C.3) and Syk/ZAP-70 (Figure C.4), using the PhyML 3.0 web server (Guindon et al.,

2010). We found that, for moesin, the evolutionary lineages furthest away from H. sapiens by

BLAST were D. melanogaster and C. elegans. They diverged from the vertebrates at about 797 million years ago (Figure 5.11 and C.1). Thus, the hypothetic origin of moesin was determined to be approximately 797 million years ago. On the other hand, the common origin of Syk from the search was determined to be 435 million years ago (Figure 5.11 and C.4). Further analysis revealed that the emergence times of common ancestors of the PI3K catalytic subunit, and of Syk and its analog ZAP70 were 1.496 and 1.032~0.757 billion years ago, respectively (Figure 5.11,

C.3 and C.4). Additionally, we found the origin of Fc common γ chain by BLAST was also around 435 million years ago, although its function is not clear (Figure 5.11 and C.2a). This time point is critical since the RAG transposon invasion into the immunoglobulin (Ig) superfamily of the vertebrate genome occurred about 600 million years ago (Thompson, 1995). This directly implicates the emergence of diversification of IgG and immune receptors, which involved in opsonic phagocytosis such as FcγR-mediated phagocytosis, to about 600 million years ago. This time point is later than the estimated emergence of moesin, which was 797 million years ago.

Finally, we found the coalescent time of the FcγR II family proteins to be only 90 million years ago (Figure 5.11 and C.2b). This suggests that the Fc portion of FcγR emerged much later in evolution.

To summarize, with phylogenetic analysis, we found that moesin-based phagocytosis is evolutionarily conserved. Later during evolution after RAG transposon invasion, which gives rise to specificity, a more effective form of phagocytosis, FcγR-mediated phagocytosis, took over the workload, probably due to its diverse specificity and high binding affinity.

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Figure 5.11 Potential Evolutionary Implications of Moesin-, -PIP2-mediated Signaling in Modern Immune Receptor-mediated Phagocytosis. Phylogenetic trees of Fc γ receptor II family proteins (Fcgr2), Fc ε receptor γ subunit (Fcer1g), Moesin, Syk family proteins (ZAP-70 and Syk) and PI3 kinase catalytic subunit (PI3K). The abbreviations of proteins are labeled on the right side of trees. On top of the figure, the time axis is shown in the unit of million years. For each tree, the time axis is shown on the bottom and is aligned to the time axis on the top. The species divergence times from published studies are used. For each tree, the vertical axis on the left shows the number of substitutions per site compared to the amino acid sequence of the homolog in Homo sapiens, so the slope of each branch represents amino acid substitution rate. The gray column indicates the time interval of two rounds of whole- genome duplication (WGD) during the evolution of common ancestors of chordates (1R) and vertebrates (2R). The dark gray bar on top of the figure indicates the time interval of the emergence of RAG1 and RAG2 (not the RAG invasion itself).

5.3 Discussion

In this chapter, we aim to characterize moesin-, PIP2-mediated solid particle phagocytosis and to determine if such mechanism is evolutionarily conserved.

We sought to define some essential components for moesin-, PIP2-mediated solid particle phagocytosis.

First, we demonstrated that simple overexpression of moesin and Syk in non-phagocytic

COS-1 cells failed to induce phagocytosis, unlike FcγIIA. Since ITAM availability was unlikely to be questioned, we, therefore, speculated that binding of biotin-BSA-coated beads with the

COS-1 membrane is not as strong as FcγR-IgG binding. Specifically, the binding of beads to

COS-1 membrane must fall below a critical threshold, causing failure to signal. The more significant implication for this issue is that binding strength might dictate whether downstream signaling can occur. The next two paragraphs present my view on the role of particle/membrane engagement during phagocytosis.

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In the event of successful signaling, solid particles first bind to the plasma membrane with substantial force beyond critical threshold. The direct binding partners for solid particles can be specific receptors, such as FcγIIA for IgG-opsonized particles, or certain lipid species, such as cholesterol for MSU crystals. Some receptors and lipid species are enriched in nanodomains, such as FcγIIA and cholesterol. Refer to section 4.3 for the role of membrane domains in signaling. The beyond-the-threshold binding will immobilize membrane domain- associated signaling molecules like Fc FcγIIA and cholesterol and eventually lead to coalescence of nanodomains into microdomains. This is marked by PIP2 sorting and recruitment of ITAM- containing proteins including moesin. Consequently, increased phosphorylation and recruitment of other signaling molecules will lead to successful internalization. In this model, successful phagocytosis is caused by strong initial binding of a particle to membrane domain-associated protein or lipid. Such engagement is meaningful, therefore, we term it “effective engagement”.

In contrast, ineffective engagement means weak binding between particle and membrane. Such binding is not sufficient to stabilize membrane domain-associated signaling molecule and will not cause significant coalescence of nanodomains into microdomains. Therefore, no PIP2 sorting and moesin recruitment can happen. The results of such ineffective engagement are the failure to internalize solid particles.

It is likely that the threshold for activation is different for each particle/membrane interaction since the binding strength is different for different interactions, and stronger binding help increases the probability of signal activation. Therefore, one can imagine a transitional state in which the engagement is effective for eventual signal activation, but the time taken to reach the activation threshold varies. In other words, multiple thresholds may exit for phagocytic activation, and each threshold is reached when enough binding force is met and might be marked

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by appearance larger membrane domains coalesced from smaller ones. In fact, when we re- examine the experiment in Figure 4.6, newfound meaning might be revealed from previously unrecognized subtle differences in the kinetics of PIP2 accumulation at the site of contact. For

RAW264.7 cell membrane in contact with a naked polystyrene bead at a constant force of 1 nN,

PIP2 level at the site of contact plateaued relatively quickly, about 200 seconds since the initial engagement. In contrast, for HEK293T cell membrane, a prolonged delay for PIP2 plateau was observed, at about 800 seconds since the initial engagement. Moreover, at least one stagnant phase of PIP2 accumulation was observed between 500 to 700 seconds, matching the speculation on the multi-threshold effect of signal activation. This likely means that the binding between polystyrene beads and the phagocytic membrane is stronger than the non-phagocytic membrane.

Thus beads dwell on the phagocytic membrane less to reach full activation, hence effective engagement.

Upon examination of literature, there is no known study explicitly published on the binding strength between FcγIIA and IgG used in this thesis. Instead, the closest substitute is the pair of FcγR and Rituximab. Rituximab is a recombinant monoclonal anti-CD20 antibody with

IgG1 Fc fragment. By using AFM, one group reported that the FcγR–rituximab binding force was 65 ± 38 pN between rituximab-functionalized AFM tip and FcγR-expressing NK cells isolated from a cancer patient (Li et al., 2014). Another study showed that the mean force was 58 pN between rituximab-functionalized AFM tip and FcγR-expressing RAW264.7 cells (Li et al.,

2013). It should be noted that binding force reported in the literature from AFM studies should be taken with a grain of salt, as those studies are performed by different groups with different samples and different experimental setting, therefore the reported values are not standardized for direct comparison and interpretation. Nevertheless, these values can provide a rough estimate of

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the order of magnitude of binding. It appears the binding between FcγIIA and IgG is around the order of 100 pN.

On the other hand, little information was available regarding the binding between polystyrene beads and any lipid bilayers. Therefore, it is of interest to this thesis to determine the binding force between polystyrene beads and different cell membrane and model membrane to determine the force of binding. Specifically, since we suggested that the binding between the bead and COS-1 are not sufficient enough to induce phagocytic signaling, it would be interesting to know is binding force significantly differ between bead/COS-1 membrane and bead/RAW264.7 membrane. Moreover, if they do differ, does that imply that the membrane content is different between COS-1 and RAW264.7 cells? For example, does RAW264.7 membrane contain specific raft-associated lipids for polystyrene bead binding? This investigation is important as it contributes to the discussion on what makes a phagocyte different from a non- phagocyte. Specifically, since we have demonstrated with MSU crystals, which can induce PIP2 sorting and moesin aggregation, that it can bind to cholesterol between 50-200 pN (Ng et al.,

2008), the binding between cholesterol and polystyrene bead should be investigated. If sufficient binding between cholesterol and polystyrene beads can be demonstrated, it would be of further interest to determine if RAW264.7 contains more cholesterol-enriched nanodomains than

HEK293T.

Recall that we have shown in Chapter 4 that beads in touch with either RAW264.7 and

HEK293T at a constant force of 1nN can induce PIP2 sorting. If phagocytic signaling is critically dependent on the strength of particle/membrane binding as we suggested, it would be of interest to determine if PIP2 sorting disappears below certain force threshold. Preliminary evidence does

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suggest that PIP2 would fail to aggregate at the site of contact when the force is below 10 pN

(Data not shown).

Recent studies on immune receptor signaling can shed some lights on our “Effective

Engagement” model. BCR complex is similar to FcγR signaling-wise. It contains an extracellular domain with antigen binding site and an intracellular ITAM motifs on Igα and Igβ heterodimer

(Abbas et al., 2017). It was reported that signal activation of BCR, indicated by BCR clustering and Syk phosphorylation, is positively dependent on the mechanical forces (Wan et al., 2015).

Specific, it was reported that the force threshold required for IgG-BCR is below 12 pN, and it is much lower than the threshold for IgM-BCR, which is above 43 pN and exhibits multi-threshold effects for activation. The lowered threshold, thus higher sensitivity of IgG-BCR is likely caused by the stronger binding of antigen to IgG-BCR than IgM-BCR after class switching. Moreover, the same group found that the volume of BCR microcluster is dependent on the mechanical force as well (Wan et al., 2015). This could be indicative that stronger force can cause coalescence of membrane domains. It was also revealed in a follow-up study that the positive charges in the cytoplasmic tail can interact with PIP2, and PIP2 is preferentially enriched in the immunological synapse of IgG-BCR (Wan et al., 2018). They found that the enrichment of PIP2 is responsible for the lowered force threshold for activation. However, the researchers fall short at explaining why PIP2 help lower the threshold. One possible explanation is that BCR linked PIP2 can anchor to the cytoskeleton via ERM proteins, thus immobilizing BCR from inside. Therefore, the force required for activation is lowered. Refer to Section 6.2.2 for more discussion on the role of PIP2 and actin in signal activation and how it fits into this thesis.

To make up for the requirement for strong binding, we created fluorescently tagged chimera with full-length CD4 linked with ITAM sequence from to allow strong binding of

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ITAM-bearing CD4 to anti-CD4 coated polystyrene beads. The CD4 and anti-CD4 pair is chosen as their binding strength is similar in the order of magnitude to that of FcRIIA and IgG binding.

It was reported that the mean binding force between anti-CD4 antibody-functionalized AFM tip and CD4-mica is 79.72 ± 59.36 pN (Chen et al., 2011).

We found that, when the requirement of strong binding is met, phagocytosis can be induced in not only COS-1 cells but also COS-7 cells. Another observation was that we could not induce phagocytosis in HEK293T and NIH3T3 cells, even with FcRIIA. Besides the low expression of ERM proteins, we suspect HEK293T and NIH3T3 lack key signaling molecules of phagocytosis. Acting on the principle of parsimony, the most likely candidate is Syk. Therefore, it would be interesting to test if Syk expression differs between these cell lines.

We also argued that sufficient endogenous ERM can act as a pool of ITAM in place of the cytoplasmic ITAM in COS-1 and COS-7 cells. This argument can be further strengthened by further elimination or reduction of ERM protein expression in COS-1 and COS-7 cells. If our argument holds, then one would expect to find the failure to induce phagocytosis with the CD4-

ITAM-YF mutant. In parallel, we did find that only wildtype CD4-ITAM can induce phagocytosis in moesin knockdown DC2.4 cells. Therefore, in this case, it would further strengthen the argument by determining if ERM proteins expression levels are sufficiently low to act as a pool for ITAM. This is likely the case as we shown in Chapter 3 that moesin is barely detectable by Western blotting in this stable knockdown clone (Figure 3.3a) and ezrin and radixin expression was very low in DC2.4 cells (Figure 3.5a). Also, we noted that the induction of phagocytosis by wildtype CD4-ITAM is partial compared to the positive control. It is helpful to determine if the amount of ITAM overexpressed with the chimera is less than the endogenous

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ITAM from moesin in wildtype cells. This can be conveniently achieved by comparing them at mRNA levels via qPCR.

Nevertheless, the idea that phagocytosis can be induced by a chimeric receptor with extracellular domain of a non-phagocytic receptor coupled with intracellular moesin ITAM is very interesting. We have demonstrated this idea with a CD4-ITAM chimera. In addition, we have created two similar system, specifically ICAM-1-ITAM and CD8a-ITAM, and successfully induced phagocytosis in COS-1 and moesin knockdown DC2.4 cells (Figure B.1 and B.2).

Therefore, the usage of chimeric molecules to induce phagocytosis in cells is likely not confined to CD4. Refer to Appendix B for the results. This simple idea stemming from very basic research holds therapeutic potential. Refer to section 6.2.3 for more discussion on this topic.

Next, we compared moesin-, PIP2-mediated phagocytosis with FcγR-mediated phagocytosis to better understand moesin-, PIP2-mediated solid particle phagocytosis.

We showed that moesin-mediated phagocytosis and FcγR-mediated phagocytosis shares a plethora of downstream signaling molecules. These include Syk, PI3K, Cdc42, Akt, and ERK.

Moreover, the kinetics of activation are similar between two pathways following activation by polystyrene beads. Since the downstream signaling is similar between these two pathways, it is likely that any difference observed between two pathways stems from the difference in initial engagement of bead with the membrane, as the strength of binding and engagement of receptors is likely different between IgG-coated beads/DC2.4 cell membrane and biotin-BSA-coated beads/DC2.4 membrane.

The most striking differences observed between moesin-, PIP2-mediated phagocytosis and FcγR-mediated phagocytosis are the high efficiency of phagocytosis for FcγR-mediated

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phagocytosis and the apparent inability to internalize large particles by moesin-mediated phagocytosis.

We found that FcγR mediated phagocytosis quickly plateaued following 15 minutes of incubation while moesin-mediated phagocytosis only reached 20% phagocytosis efficiency within the same time. This striking difference is likely caused by the difference of particle/surface binding between IgG-coated bead/FcγR-expressing cell membrane and biotin- coated bead/cell membrane (cognate binding partner unspecified), and it is best explained under the idea of “effective engagement” discussed in the following paragraphs.

It should be noted that it has not been experimentally demonstrated that binding between

IgG and FcγR is significantly stronger than biotin-coated or naked bead surface to the unidentified lipid or protein components of the membrane. The discussion below operates on the assumption that IgG/FcγR binding is stronger than biotin-coated or naked beading to the membrane.

During FcγR-mediated phagocytosis, IgG-coated bead first contacts the cell membrane with binding to FcγR, likely raft-associated, with high strength. This will lead to immobilization and spatial confinement of FcγR, recruitment of PIP2 and other signaling molecules like Src- family kinase will carry out the initial signaling. PIP2 may also lower the threshold for further engagement by linking itself to the cortical actin cytoskeleton. Eventually, this will lead to coalescence of smaller membrane domains into bigger membranes domains, and phagocytic signals are amplified. This consequently will lead to internalization of the IgG-coated bead.

Because the initial binding is strong, the time to reach effective engagement is less than that of moesin-, PIP2-mediated phagocytosis. This translates into less time each IgG-coated bead dwell on the cell membrane than a biotin-coated bead or even naked bead. The net result is that the

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average time taken from initial contact of the bead eventual engulfment is much shortened for the IgG-coated bead. Therefore, within the same time, the total number of IgG-coated bead taken up by the cell is higher. One crucial distinction should be made here. The major difference in time here concerns the time of initial engagement to effective engagement, marked by the appearance of PIP2 clustering at the base of a phagocytic cup. Once the effective engagement is made, the time taken for FcγR-coated beads to be completely internalized is very similar to that of biotin-coated beads. We have demonstrated in chapter 4 (Video 4.2) that the average time taken to internalize a naked bead from initial PIP2 clustering at the base of the phagocytic cup to eventual phagosomal sealing is around 5 minutes, which is similar to the time to internalize IgG- coated beads (Flannagan et al., 2012). In other words, the time cell spends to sense the naked or biotin-coated solid particles is longer than FcγR, as IgG-coating quickly commits the cell to phagocytose by multivalent crosslinking with receptors. It would be interesting to confirm with population statistics if the dwell time from initial contact to effective engagement is longer for naked or biotin-coated beads than IgG-coated beads.

The same principle can be applied to discuss the inability of RAW264 cells to internalized big (e.g., 6 µm) biotin-coated polystyrene beads. First, we compare internalization of the bigger biotin-coated bead with smaller biotin-coated beads. Since the phagocytosis efficiency was much higher for smaller beads, we can infer that the time taken, on average, from initial engagement to effective engagement for a smaller bead is shorter than the time taken for the bigger bead. Therefore, the threshold for activation may be lower for smaller beads than bigger beads. However, it is still unclear whether such lowered threshold is caused by the difference in binding between smaller and bigger beads to the cell membrane or caused by greater curvature, bigger beads supposedly have flatter base at the site of the contact. It would be interesting to

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experimentally determine the causal factor for such different requirement of the threshold for a different size. Second, when the coating of beads is switched from biotin-BSA to IgG, phagocytosis efficiency for bigger beads drastically improves. This likely suggests that strong binding between IgG/FcγR lower the previously non-permissive, high threshold to a lower level.

Again, it would be interesting to define such threshold for future studies.

It should be noted here that there might be other fundamental explanations for the large difference in kinetics and particle size observed between FcγR- and moesin-mediated phagocytosis. For example, actin remodelling machinery and exocytosis of membrane could be less efficient for moesin-mediated phagocytosis. Therefore, it might be of interest to determine is specific components of theses processes are different between two phagocytic pathways.

Moreover, it has been suggested that PI3K are critical for internalization of large particles by by terminating actin assembly through Rac/Cdc42 GTPase-activating proteins for FcγR-mediated phagocytosis (Schlam et al., 2015). Therefore, it is of special interest to investigate whether such mechanism is defective in moesin-, PIP2-mediated phagocytosis.

We also inquired the involvement of moesin in SR-mediated phagocytosis. We found that moesin may be somewhat required for SR-mediated phagocytosis. It should be noted here that even though MalBSA was used as a ligand for MARCO and SR-A in this study and we demonstrated some specificity with double knockout cells, other scavenger receptors might also bind to MalBSA-coated beads simply due to the ligand promiscuity associated with scavenger receptors (Platt and Gordon, 1998).

Nevertheless, this finding can help explain how SR can signal. Class A SRs, such as

MARCO and SR-A contains a very short cytoplasmic tail with no known signaling motif related to phagocytosis. However, it has been demonstrated many times they can serve as a co-receptor

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for solid particles, such as silica (Hamilton et al., 2008; Thakur et al., 2009). Therefore, this study suggests that moesin may act as the ITAM-containing molecule for SR-mediated phagocytosis. It remains to be demonstrated as to how SRs are linked to moesin. Besides this apparent link, the process of SR-mediated phagocytosis is also clear within the framework of effective engagement. During phagocytosis of specific solid particles, SRs participate by non- specifically binding to the particle surface possibly through electrostatic interactions via its extracellular domain. This binding could lower the threshold for activation, thus promoting effective engagement. Moesin might be recruited downstream to promote signaling. It is unclear whether PIP2 is clustered during FcγR mediated phagocytosis, or if it is relevant at all. It would be of interest to overexpress an SR chimera with ITAM linked to the cytoplasmic domain to determine if phagocytosis can be induced in non-phagocytic cells such as COS-1.

Finally, we determined that moesin-mediated phagocytosis in evolutionarily conserved.

We found in vitro that overexpression of moesin from earlier species in moesin knockdown

DC2.4 cells can rescue moesin-mediate phagocytosis. It is interesting to note that it appears that the rescue efficiency increases when the origin of moesin is closer to Mus musculus. However, it is unknown whether this interpretation is meaningful as the phagocytosis assay might not be sensitive enough.

FcγR-mediated phagocytosis represents the most sophisticated, highly specific form of phagocytosis (Zhang et al., 2010). In other words, they serve as an “adaptive” form of phagocytosis. We wonder if moesin-, PIP2-mediated phagocytosis represents an “innate” form of phagocytosis. With phylogenetic analysis, we showed that despite that moesin-mediated and

FcγR-mediated phagocytosis shared common downstream signaling molecules such as Syk and

PI3K; they differ in their emergence during evolution. More specifically, we found that moesin

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emerged at around 797 million years ago before RAG transposon invasion (~600 million years ago), while FcγR emerged roughly 100 million years later than RAG transposon invasion. This supports the idea that moesin-, PIP2-mediated, solid particle phagocytosis is more evolutionarily conserved, less efficient than FcγR-mediated phagocytosis.

Some more delicate analysis should be performed, if possible, to further this narrative.

First, CR3, another type of opsonic receptor shall be investigated for its place in evolution. CR3 is less specific than FcγR in the sense that it binds to iC3b which non-specifically coat bacteria membranes with covalent linkage. Further, the evolution of ITAM-containing molecules shall be investigated beyond ERM family members to determine the involvement of ITAM in various forms of phagocytosis.

In summary, in this chapter, we showed strong particle/surface binding, ITAM availability are prerequisites for successful phagocytosis in phagocytes. In this regard, moesin-,

PIP2-mediated solid particle phagocytosis, and FcγR-mediated phagocytosis is similar. More equivalency between two phagocytic pathways was demonstrated by the shared downstream signaling. However, we found that moesin-, PIP2-mediated phagocytosis is much less efficient than FcγR-mediated phagocytosis, especially for big beads. This is likely a result of the weak surface binding between the bead and cell membrane. Finally, we demonstrated in vitro and in silico that moesin-mediated phagocytosis is conserved.

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Chapter Six: Summary and Future Directions

6.1 Summary

In this thesis, we have identified and characterized an evolutionarily conserved mechanism of solid particle phagocytosis.

First, in Chapter 3, we identified moesin as the ITAM-containing molecule responsible for solid particle phagocytosis. Specifically, the FERM domain of moesin is sufficient to trigger downstream phagocytic signaling. These signaling events include the physical binding of Syk to moesin, activation of Syk and other downstream molecules.

Further, in Chapter 4, we showed that PIP2 is preferentially sorted into the site of contact following engagement of membrane with solid structures. Moreover, we showed that this sorting is sufficiently triggered by physical contact.

Finally, in Chapter 5, we showed strong particle/surface binding, and ITAM availability are prerequisites for successful phagocytosis in phagocytes. In this regard, moesin-, PIP2- mediated solid particle phagocytosis, and FcγR -mediated phagocytosis share similarities. More equivalency between two phagocytic pathways was demonstrated by the shared downstream signaling. However, we found that moesin-mediated phagocytosis is much less efficient than

FcγR -mediated phagocytosis, especially for big beads. This is likely a result of the weak surface binding between the bead and cell membrane. Finally, we demonstrated in vitro and silico that moesin-, PIP2-mediated phagocytosis is conserved.

Taken together, we have identified an evolutionarily conserved phagocytic signaling pathway similar to the classical FcγR -mediated phagocytosis. A model is proposed based on the findings reported and discussed in Chapter 3,4 and 5.

For modern receptor-mediated phagocytosis, such as FcγR -mediated phagocytosis, IgG-

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opsonized particles engage with Fc receptors on the cell surface, this induces membrane curvature change and sorting of PIP2 at the site of contact. ITAM of FcγR becomes phosphorylated. Binding of Syk via its SH2 domain to phosphorylated ITAM of FcγR ensued.

This consequently leads to downstream phagocytic signaling and actin polymerization.

On the other hand, for conserved solid particle phagocytosis, solid particles are first engaged with the plasma membrane, it also induces membrane accumulation of PIP2 at the site of contact. This leads to recruitment and activation of moesin to the plasma membrane This includes the phosphorylation of ITAM tyrosine residues in FERM domain by SFK. Binding of

Syk via its SH2 domain to phosphorylated ITAM of moesin ensued. This consequently leads to downstream phagocytic signaling and actin polymerization. This process is similar to FcγR regarding PIP2 clustering, ITAM usage, Syk recruitment and downstream signaling (Figure 6.1).

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Figure 6.1 Signaling Equivalent Platform Revisited: Moesin-, PIP2-mediated Phagocytosis A scheme of potential model how FcγR and PIP2 redistribution-based mechanisms can share the entire signaling cascade downstream of ITAM for phagocytosis. Left: For modern receptor- mediated phagocytosis such as FcγR -mediated phagocytosis. IgG-opsonized particles engage with Fc receptors on the cell surface, this induces accumulation of PIP2 at the site of contact. ITAM of FcγR becomes phosphorylated. Binding of Syk via its SH2 domain to phosphorylated ITAM of FcγR ensued, which consequently leads to downstream phagocytic signaling and actin polymerization. Right: For conserved solid particle phagocytosis, solid particles are first engaged with the plasma membrane, it also induces membrane curvature change and sorting of PIP2 at the site of contact. This leads to recruitment and activation of moesin to the plasma membrane, including the phosphorylation of ITAM residues in FERM domain. Binding of Syk via its SH2 domain to phosphorylated ITAM of moesin ensued, which consequently leads to downstream phagocytic signaling and actin polymerization. This process is similar to FcγR regarding PIP2 clustering, ITAM usage, Syk recruitment and downstream signaling. A video depicting the dynamic process of this model can be accessed at https://goo.gl/TmKu3X.

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6.2 Future Directions

Although the idea of ‘Signaling Equivalent Platform’ discussed in section 1.4.4.5.2 is undoubtedly strengthened by the study of this thesis, further improvements should be made to make this model even more robust. Specifically, the model presented above is still a very crude view on how phagocytic signaling is initiated, especially about the events transpires on the membrane upstream of ITAM phosphorylation. Therefore, the discussion below will focus on addressing these outstanding issues. For this, we will first establish a fundamental framework of phagocytic signaling, and by extension immune receptor signaling with a focus on the spatiotemporal regulation of signaling molecules. We will integrate the concepts introduced in previous chapters to establish this framework. These concepts include:

(a) Counteractions between ITAM-based activating signals and ITIM-based inhibitory

signals introduced in Section 1.5.5.2.

(b) Coalescence of membrane domains introduced in Section 3.3.

Once the framework is established, we will apply it to out our proposed model (Figure

6.1) for refinement with a comparison to FcγR-mediated phagocytosis, when necessary.

6.2.1 Spatiotemporal Regulation of Phagocytic Signaling

Since we have demonstrated that ITAM downstream signaling is similar between moesin-, PIP2-mediated solid particle phagocytosis and FcγR -mediated phagocytosis, we focus our discussion on the initiation of phagocytosis. Specifically, we will discuss the events from the initial particle engagement up until the point of ITAM phosphorylation. This framework, however, will be built from bottom up for better, structured reasoning. It is noteworthy that the

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discussion below is speculative in nature with some support from published data. Nevertheless, it aims to paint a better picture for future work, and it remains to be proven true or false by future experiments.

At resting state, ITAM at the membrane could undergo low-level activation and inhibition from kinase and phosphatase activities, respectively (Monroe, 2006). The kinases include Syk and Src-family kinases while phosphatases include and SHP, CD45, and CD148

(Freeman and Grinstein, 2014). These kinases and phosphatases activities counteract each other in a dynamic equilibrium. Because there is no signal input, or trigger, from upstream, the net result at resting state likely produces no meaningful downstream signals.

To produce net activating signals or inhibitory signals, the equilibrium describes above must be shifted to either direction in response to upstream triggers. Since the net result during phagocytosis, following particle/membrane engagement, is activating signaling. This means the equilibrium must have shifted towards activation. Specifically, this means that the intensity of kinase activities on ITAM is increased whereas the intensity of phosphatase activities on ITAM might be decreased. Furthermore, the equilibrium must shift beyond a certain threshold to produce a meaningful activation signal, thus leading to recruitment and activation of downstream molecules. Net ITAM phosphorylation and clustering initiates signaling pathways that lead to activation, proliferation, and differentiation or phagocytosis (Billadeau and Leibson, 2002;

Mocsai et al., 2010). To achieve this shift in equilibrium towards net phosphorylation, the concentration of ITAM-proximal kinases via spatial confinement and exclusion of phosphatases from ITAM- or kinase-enriched regions are desired.

The concentration of ITAM-proximal kinases is the natural results of ITAM aggregation by logical deduction. It is suggested that a common feature of ITAM-containing non-catalytic

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immune receptors is the requirement for their coalescence to signal (Dushek et al., 2012).

Therefore, we must ask how ITAM can be aggregated. Specifically, what are the mechanisms that cause reduced mobility, spatial confinement and eventual aggregation of ITAM-containing molecules?

The most popular mechanism is the coalescence of membrane rafts. It has been reported that FcγR crosslinking to multivalent ligands is sufficient to cause spatial raft coalescence, and it is independent of downstream Src kinase activation (Kono et al., 2002). Further, it was found that palmitoylation of FcγRIIA is necessary for its localization to the rafts (Barnes et al., 2006;

García-García et al., 2007). It was also hypothesized that spatial raft coalescence precedes intracellular signaling and that it provides membrane domains for the downstream kinases, such as Lyn, transactivation (Kono et al., 2002). It should be noted here that due to technical challenges, no study has definitively demonstrated that nanodomains containing FcγR can physically coalesce to form microdomains for subsequent signaling. Refer to Section 6.2.2 on the discussion of such technical challenges and potential solutions.

The less popular mechanism is the spatial confinement of receptors by transmembrane protein “pickets” and underlying membrane-cytoskeleton “fence” together know as “Picket

Fence Model” (Kusumi et al., 2012). In this model, the diffusion of molecules around immobilized transmembrane pickets is slower due to the hydrodynamic-friction-like-effect at the surface of such pickets. This effect could propagate over distances equivalent to multiple diameters of picket proteins, thus forming a diffusion barrier. When such diffusion barriers are aligned along the membrane-skeleton fence, they form effective boundaries to confine signaling molecules (Kusumi et al., 2005). However, pickets proposed in this model are such elusive targets for any scientist. Even though this idea has been proposed for over 20 years, examples of

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such pickets are scarce. Specifically, no reports have been found for such pickets involving activation of phagocytic signaling that fit Kusumi’s definition.

The barrier function of specific transmembrane proteins is nevertheless interesting because it might be involved in phosphatase exclusion from ITAM-enriched regions, another event that occurs when the dynamic equilibrium shifts towards activating signals during phagocytic and immune signaling. It has long been known that phosphatase, such as CD45 and

CD148, are excluded from the phagocytic cups (Goodridge et al., 2011). Similarly, in lymphocytes, phosphatases are displaced to the peripheral of the site contact following ligand binding to BCR and TCR at the immunological synapse (Dustin, 2012; Dustin and Groves,

2012). Recently, a study has found that integrin can function as a picket to drive phosphatase, such as CD45, out of the phagocytic cup where FcγR is clustered (Freeman, 2016).

We have now established that concentration of ITAM-containing proteins and exclusion of phosphatases can be caused by raft coalescence and barrier function of membrane pickets, the focus is then shifted to how membrane raft coalescence or barrier function is triggered.

Raft coalescence can be triggered by multivalent ligand binding, synapse formation and protein oligomerization. Specifically, solid particles can serve a relatively immobile surface with affinity to a particular component of a nanodomain (Lingwood and Simons, 2010). For example,

IgG-opsonized particles can be bound by many nanodomains via FcγR-IgG binding (Kono et al.,

2002). Such multivalent binding eventually promotes the coalescence of smaller nanodomains into larger, functional microdomains for effective signaling. Therefore, the nature of particle binding to nanodomain is important for raft coalescence, and effective engagement will lead to a shift of equilibrium to activating signals, hence effective signaling. On the other hand, membrane

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pickets have been shown to bind to multiple ligands displayed on the solid target. Such binding help stabilizes phagocytic synapse and eventually drives out phosphates (Ostrowski et al., 2016).

In summary, the discussion above establishes a fundamental framework for signaling. In it, solid particles first bind to a raft-associated molecule on nanodomains via effective engagement. Alternatively, membrane pickets can engage with solid particle surface. Such binding will trigger coalescence of nanodomains into functional microdomains, or stabilization of membrane pickets to form a diffusion barrier, respectively. As a result, ITAM-containing molecules are spatially confined, thus concentrated at the site of contact. Meanwhile, phosphatases that negatively regulates ITAM-mediated signaling can be excluded from the same site of contact. As a result, the dynamic equilibrium between kinase and phosphatase activities is shifted toward generating more activating signals. When the activating signals pass certain thresholds, effective activation occurred, and downstream molecules are recruited and activated.

6.2.2 Refinements for Moesin-, PIP2-mediated Solid Particle Phagocytosis

In this section, the framework established in Section 6.2.1 will be applied specifically to moesin-, PIP2-mediated solid particle phagocytosis to identify outstanding issues for future investigations (Figure 6.2).

First, solid particles engage with a membrane with certain affinity. More specifically, it is likely that a raft-associated molecule binds to the solid particle surface non-specifically at a possibly low affinity. The binding could be influenced by property of solid particles including shape, size, stiffness and surface chemistry. On the other hand, the raft-associated molecule that binds to solid particle surface is mostly unknown. We have demonstrated that cholesterol, a raft component, can bind to MSU surface with good affinity (Ng et al., 2008). However, it is

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unknown what the identity of such raft-associated molecule to naked or biotin-BSA-coated polystyrene particles, the predominant model particles used in this thesis, is. Therefore, it is helpful to elucidate the identity of polystyrene-binding, raft-associated molecule.

This molecule can be lipids in nature. If this is the case, membrane content from a phagocytic cup may be extracted for lipidome analysis for such identification.

This molecule can also be protein in nature, of interests are scavenger receptors and integrins. These receptors are known for their ligand promiscuity, and they have been demonstrated to bind to the polystyrene surface (Kanno et al., 2007; Platt and Gordon, 1998;

Underwood et al., 1993). Binding of integrin to polystyrene particle in theory can promote stabilization of integrin and its function as membrane pickets to exclude phosphatases from the site of contact. It might be helpful to determine with AFM with proper control, such as FcγR to determine if there is a binding affinity between SR and integrin to the polystyrene surface. If it is the case, we should further determine if these proteins are raft-associated, likely via super- resolution microscopy. Also, if it is true that SR and integrin can bind to polystyrene surface, we should investigate if integrin is stabilized by bead binding by comparing the diffusion patterns of individual integrin molecules with and without bead binding. This is usually achieved by single- particle tracking (SPT) analysis with TIRFM (Freeman et al., 2016; Jin et al., 2007; Kusumi et al., 1993). This can be challenging since it requires both expertise in microscopy and coding literacy, only a handful of laboratories in the world have mastered such combination. If it is determined that integrin can function as a membrane picket, we should next determine if phosphatases such as CD45 and CD148 are indeed excluded from the site of contact, this can be achieved with total internal reflection fluorescence microscope (TIRFM) combined with

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frustrated phagocytosis model (Jaumouillé et al., 2014; Jongstra-Bilen et al., 2003; Ostrowski et al., 2016).

Next, we should carefully investigate how the ITAM-containing moesin is concentrated on the membrane. The membrane rafts theory suggests that the solid particle engage the membrane is a sufficiently effective manner. It is likely that many nanodomains engage solid particle surface via multi-valent binding. Such binding will enable coalescence of smaller nanodomains into bigger, functional microdomains. It is of interest to first determine if PIP2 resides in nanodomains and later sorted into microdomains following engagement of solid particles. Membrane rafts have been proposed to be involved phagocytosis (Magenau et al.,

2011). Moreover, it has been reported that actin polymerization is triggered by PIP2 synthesis in sphingolipid and cholesterol-rich raft domains (Rozelle et al., 2000). In addition, a study has shown that lipid raft-like domains, determined by laurdan microscopy, exist on phagosomes

(Gaus et al., 2003). Further, perturbation with MβCD to deplete cholesterol led to the dissolution of such raft-like domains (Gaus et al., 2003). Therefore, lipid raft coalescence might be involved in phagocytosis.

It is extremely challenging to observe this coalescence of nanodomains to microdomains on live cell membranes. The previously mentioned c-laurdan microscopy in Section 4.3 is only useful in determining the order of membrane in live cells because the c-laurdan can only be used with diffraction-limited microscopes such as two-photon microscopes and confocal microscopes due to its limited photostability. The resolution is not high enough to resolve individual nanodomains. On the other hand, AFM can be used to resolve of membrane rafts. It has been successfully used to demonstrated that distinct domains exist on micrometer and nanometer scales on model membranes (Chavan et al., 2015). However, its use is limited by its unsuitability

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for live cell imaging. Currently, the most promising solution to study membrane domains coalescence and to resolve individual domains is to perform super-resolution imaging techniques, such as Stimulated Emission Depletion (STED) microscopy with probes for lipid

(Klymchenko and Kreder, 2014). STED can resolve structures with size below 20 nm (Blom and

Widengren, 2017). Therefore, in theory, live cell microscopy with STED can help determine the process of raft coalescence during phagocytotic. However, several caveats exist. First, to visualize membrane domains, a fluorescent probe for membrane rafts must be used. It is possible that it can alter the behavior of membrane rafts. Second, it is unknown if such probe exists for super-resolution microscopy since the requirement for photostability is a major concern

(Klymchenko and Kreder, 2014). Third, coalescence of membrane rafts is very rapid, likely on a timescale of milliseconds (de Wit et al., 2015) seconds. It is unknown if such dynamic process can be captured while enough spatial resolution is maintained to resolve individual rafts.

If a method to observe coalescence of membrane domains can be established, it would also be interesting to determine the effect of size on raft coalescence. We observed in Section 4.2 that moesin-mediated phagocytosis is not efficient when the particle is big. By contrast, FcγR - mediated phagocytosis is capable of efficiently internalizing beads with the bigger size. It is possible that phagocytosis of bigger particles, but not smaller ones, may be dependent on the large-scale coalescence of membrane rafts.

It is also unknown if PIP2 could interact with any particle-binding, raft-associated proteins or lipids. Therefore, this possibility should be investigated.

An alternative theory for concentrating moesin is the involvement of membrane pickets.

Since there is no known study available favoring this possibility, this option is not likely considered for future studies. Also, we show that in GMPV, a model plasma membrane in which

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the cortical actin is collapsed (not experimentally determined), PIP2 sorting can occur. Since pickets typically require linkage to cortical actin for stabilization, the possibility of picket involvement in moesin-mediated phagocytosis is low.

Another potentially vital aspect of ITAM-based phagocytic activation is the exclusion of phosphatases from phagocytic cups. It has been shown that integrin can function as membrane pickets to form diffusion barrier to exclude CD45 and CD148 from the site of contact where

FcγR is clustered (Freeman et al., 2016). Moreover, FERM domain has been shown to bind to integrin α5β1 to promote motility in endothelial cells (Vitorino et al., 2015). It seems possible that FERM domain of moesin can bind to integrin to promote phosphatase exclusion. However, such theory is currently being contested. A very recent study have shown that CD45 exclusion during FcγR-mediated phagocytosis can occur in an integrin-independent manner. Rather, such exclusion depends on the size of antigen on the surface of target particles (Bakalar et al., 2018).

They argued that the previous reports by Freeman et al. suggesting an integrin-dependent mechanism for CD45 exclusion during FcγR-mediated phagocytosis had used a layer of immobilized antibodies on a surface that limits the density of FcγRs that can accumulate at a given point on the membrane. Such model is flawed as the accumulation of FcγR are limited when the antigens are not freely diffusible, unlike natural cases observed with cell-surface tumor antigens such as CD20 and Her2 (Bakalar et al., 2018; Freeman et al., 2016) Therefore, the role of integrin to act as membrane pickets to exclude phosphatases during moesin-, PIP2-mediated solid particle phagocytosis is highly debatable. Coupled with our own observation that PIP2 can still cluster in GMPV in which any protein, including, is likely not active, it is highly improbable that integrin is involved in moesin-, PIP2-mediated solid particle phagocytosis. Thus, one may first test if phosphatase exclusion can be observed with moesin-, PIP2-mediated solid particle

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phagocytosis. Next, if phosphatase exclusion can be observed, one may determine the mechanism for such exclusion. Since there is likely no involvement of specific antigens for moesin-, PIP2-mediated solid particle phagocytosis, the mechanism of antigen sized-dependent phosphatase exclusion might not be a probable candidate. In short, the existence or the identity of such membrane pickets for moesin-, PIP2-mediated solid particle phagocytosis remains a mystery.

Finally, as a side note, we will discuss the use of more evolutionarily conserved organisms to study this mechanism. We initially attempted to use Amoeba proteus to study phagocytosis since we found it can engulf polystyrene beads efficiently. Later, we stopped pursuing this model as we realized this organism is not amenable to genetic manipulation such as protein knockdown. However, other cells can be used. For example, S2 cells, a macrophage-like cell in Drosophila, may be a potentially useful cell to study phagocytosis.

In conclusion, this thesis identified an evolutionarily conserved mechanism of solid particle phagocytosis involves moesin. For future work, it is helpful to determine if solid particle/membrane engagement can induce coalescence of membrane rafts or stabilization of membrane pickets to promote signaling. The nature and strength of binding between various solid particles and membrane should be determined after the identity of the molecules responsible for binding to solid particles is revealed.

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Figure 6.2 Potential Refinements for Moesin-, PIP2-mediated Solid Particle Phagocytosis A scheme of potential refinements for moesin-, PIP2-mediated solid particle phagocytosis for Future Directions. Solid particles with different physicochemical properties can bind to nanodomains via multi-valent binding. Smaller nanodomains coalesce into bigger microdomains in which PIP2 and moesin clustered. Kinase activities are increased from this clustering, and signal activation occur when a certain threshold of phosphorylation is reached. On the other hand, membrane pickets can bind to solid particle surface for stabilization to form a diffusion barrier. It may be further stabilized via binding to the FERM domain of moesin or other proteins to cortical actin. Stabilized, immobilized membrane pickets function as diffusion barriers to exclude phosphatases, such as CD45 and CD148 from the site of contact where PIP2 and moesin clusters. Exclusion of phosphatases will increase the net phosphorylation thus promoting activation. Potential points of interest are marked with ‘?’ for future investigations.

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6.2.3 Significance and Applications

Phagocytosis, and by extension immune receptor signaling, is essential to our understanding of how immune system works in disease and health. By understanding the signaling mechanism of solid particle phagocytosis, it is possible to engineer solid particles with unique properties to modulate immune signaling in cells for therapy (Moon et al., 2012).

First, particles can be designed to function as antigen-presenting cells to induce T cell activation (Steenblock and Fahmy, 2008). This is advantageous because such treatment can be targeted, and surface interactions can be controlled from the particle.

Second, particles can be designed to function as a drug delivery system (Moon et al.,

2012). It has been demonstrated that STAT3 siRNA/PEI and PEI-StA polyplexes physically encapsulated in poly(d,l-lactic-co-glycolic acid) (PLGA) nanoparticles (NP) can successfully knock down STAT3, a transcription factor known to be activated by tumor derived factors in

DC, gene expression in DC without cytotoxic effect induced solely by polyplexes in vivo and in vitro. (Alshamsan et al., 2010). The development of solid particle to deliver immunomodulatory drugs is potentially helpful as such delivery is targeted and cytotoxic effects can be minimized with optimization (Moon et al., 2012).

Moreover, solid particles can be engineered to function as vaccines to activate antigen presenting cells by carrying molecular adjuvants (Jewell et al., 2011; Reddy et al., 2007). Recall that alum is a solid particle that functions as an adjuvant in vaccines to boost immunity. It has been demonstrated in vivo that PLGA particles carrying antigen and LPS conferred protection on nearly all vaccinated animals against a live challenge of West Nile virus (Demento et al., 2009).

On the other hand, engineering can be done at the cellular side. Specifically, phagocytosis can be induced in cells via overexpression of chimeric molecules for therapeutic use. Very

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recently, a proof-of-principle study demonstrated in vitro that murine macrophages overexpressed with chimeric receptor containing extracellular regions of tumor antigen-specific antibodies and intracellular region of ITAM-containing FcγR or Megf10 can bind and engulf silica beads coated with the same tumor antigens or even live tumor expressing the same antigen on the cell surface (Morrissey et al., 2018). Further, co-culture of such macrophages with tumors could reduced the cancer cell number by 40% (Morrissey et al., 2018). It remains to be tested whether in vivo such engineered cells can work to eliminate tumors.

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228

ITAM-CONTAINING PROTEINS IN PHAGOCYTOSIS

Table A.1 List of ITAM-containing Proteins Ranked by Expression Levels in Phagocytes

Score Gene Symbol Score Gene Symbol Score Gene Symbol Score Gene Symbol 56.15614 Itm2b 3.08232 Dad1 1.70283 Polr2a 1.16924 Nub1 38.69960 Fcer1g 3.06498 Psme1 1.69114 Stt3a 1.15113 Fdps 32.01277 Tyrobp 2.93642 Mfge8 1.67444 Eprs 1.10337 Tm6sf1 24.70679 Npc2 2.93302 Lrrc47 1.67413 Spg21 1.09647 Renbp 22.33209 Lcp1 2.91987 Cltc 1.66172 Psme2 1.09021 Sf3a3 15.16300 Rps3 2.90799 Sdcbp 1.62330 Myo1g 1.08351 Cpsf3 9.63464 Slc6A6 2.89862 Snx8 1.55499 Scarb1 1.08264 Elmo1 9.63402 Hmox1 2.87903 Rps10 1.54789 Lmo2 1.07894 Acp5 8.61086 Csf1r 2.76382 Ndufc2 1.53371 Slc37a2 1.07766 Atp6V0a1 8.50650 Cd36 2.75414 Tbc1d13 1.50618 Nacc1 1.07224 Lmf2 7.96065 Atp1a1 2.58908 Tfrc 1.49755 Myo9b 1.06315 Slc12a7 7.93785 Ndrg1 2.56275 Sf3B1 1.43639 B4galt1 1.05595 Pes1 6.59205 Slc11a1 2.41615 Lrpap1 1.43385 Prdx2 1.05060 Cnp 6.48514 Msn 2.32843 Dync1h1 1.41921 Rdx 1.05026 Cd274 6.09836 Myh9 2.28088 Plxna1 1.41255 Trim27 1.03637 Agpat5 5.86133 Actr2 2.19869 Copa 1.40995 Vps33a 1.02684 Pgs1 5.42347 Rpl7 2.19356 Esyt1 1.40805 Olfm1 1.01433 Smg5 5.15248 Iqgap1 2.19079 Plec 1.38548 Sel1l 1.00450 Bcl6 4.96170 Ctsc 2.18807 Aoah 1.38479 Tpra1 0.99930 Ubap2L 4.75938 Rps25 2.18155 Anapc5 1.37557 Mgat4b 0.99635 Gpr137B 4.39447 Cd81 2.13025 Clptm1L 1.36931 Atp1a3 0.98892 Tmem205 4.13897 Degs1 2.12783 Rasa4 1.35911 Prpf8 0.97717 Ptpn23 4.08823 Glud1 1.99307 Bri3 1.34004 Ndufv3 0.97096 Fzr1 3.86812 Rpl7a 1.98558 Amfr 1.32742 Nsun2 0.96118 Myo5A 3.85504 Atp6v1e1 1.95195 Glb1 1.30503 Iars 0.95973 Fam134A 3.83566 Pla2g7 1.92907 Atf5 1.28051 Pkn1 0.95127 Psen2 3.80461 Cct7 1.91393 Dock2 1.27921 Bub1b 0.94156 Myo1c 3.77740 Fyb 1.88221 Cyfip1 1.27688 Elovl1 0.94025 Prkag1 3.74364 Ctsa 1.88024 Znfx1 1.26525 Slc35a4 0.93076 Metap1 3.67304 Junb 1.87379 Tmem86a 1.26376 Tbc1d2b 0.90974 Farsb 3.40835 Clptm1 1.83467 Cpd 1.22618 Paf1 0.89264 Abcd1 3.37653 Nhp2 1.82547 Fnip2 1.22025 Ldlr 0.88623 Psme3 3.35022 Rcc2 1.77750 Gnpda1 1.21860 Apobec1 0.88502 Pold1 3.15043 Adcy7 1.72577 Tlr1 1.21798 Mtmr6 0.87404 Tmem206

Scores (blue cells) were normalized against β-actin expression level and presented as percentage values for each protein (yellow cells).

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Table A.1 List of ITAM-containing Proteins Ranked by Expression Levels in Phagocytes (Cont’d)

Score Gene Symbol Score Gene Symbol Score Gene Symbol Score Gene Symbol 0.86380 Necap1 0.64834 Rmnd5b 0.50743 Tmx3 0.41944 Vhl 0.86185 Ogdh 0.64119 Ppp1R12a 0.50612 Nipsnap3b 0.41897 Slc7A11 0.85791 Atp13a3 0.64061 Ube3b 0.50325 Atrx 0.41734 Ebpl 0.85644 Psmd11 0.63627 Tmem9b 0.50286 Usp47 0.41729 Tubgcp3 0.85405 B3Galnt1 0.63169 Skiv2L2 0.50088 Utp20 0.41151 Sfswap 0.85240 Slc29A1 0.62151 Fbxo38 0.50051 Smarca5 0.41060 Ccnf 0.84294 Dennd5a 0.62098 Mcoln1 0.49574 Ube3c 0.40970 Ints7 0.84193 Atp5h 0.61877 Atp6v0a2 0.49514 Rptor 0.40936 Cstf1 0.83290 Tsg101 0.61745 Sec11a 0.49497 Appbp2 0.40784 Phip 0.83060 Usp19 0.61666 Kctd13 0.49217 Tpp2 0.40556 Ppip5K2 0.82775 Iqgap2 0.61292 Rasal3 0.49070 Ezr 0.40501 Mfsd6 0.81330 Fads2 0.61044 Usp8 0.48526 Cdk11b 0.40453 Ctr9 0.81064 Ndufs6 0.61038 Faf2 0.48294 Man1a2 0.40407 Edem3 0.79625 Naa15 0.60941 Ipo13 0.48108 Haus4 0.39757 Alox5 0.79010 Abca7 0.60872 Panx1 0.48043 Gnpat 0.39288 Dmxl1 0.78634 Jagn1 0.60589 Dexi 0.47701 Zcchc6 0.39278 Slc7A6 0.78621 Cd79B 0.59257 Mocos 0.47662 Frmd4b 0.39242 Trpm7 0.78423 Secisbp2L 0.59107 Nob1 0.47455 Hells 0.39097 Myo1h 0.78066 Trappc10 0.59107 Dennd4b 0.47422 Phf10 0.39027 Senp2 0.77447 Map3k12 0.58860 Vps36 0.47221 Gpr84 0.38944 Slc12a6 0.77384 Gtpbp4 0.58166 Ifi204 0.47118 Plekhm2 0.38371 Pdgfb 0.77343 Uba5 0.57813 Ankrd17 0.46807 Mtmr2 0.38181 Exoc6 0.76749 Gclc 0.57423 Ipo4 0.46648 Rnf145 0.37920 St6galnac4 0.76037 Psmd12 0.57124 Ppp3cb 0.46548 Ccnk 0.37648 Zzef1 0.75178 Smc3 0.57078 Actr8 0.46476 Aurka 0.37335 Atm 0.74493 Csnk2A1 0.56881 Fam134c 0.46105 Naa25 0.37267 Nup133 0.73473 Zdhhc5 0.56532 Rnf139 0.45807 Nrm 0.37142 Pptc7 0.73216 Atad2 0.56164 Mtr 0.45604 Plekhm3 0.37049 Exoc4 0.72946 Stk38 0.55525 Tlr4 0.45580 Tbc1d9 0.37034 Rhot1 0.72534 Htra2 0.55503 Trak1 0.45188 Cyfip2 0.36950 Dicer1 0.72502 Fam162a 0.55116 Wdr13 0.44958 Prpf38a 0.36700 Slc35c1 0.71970 Slc7A7 0.55072 Jmjd1c 0.44739 Mettl9 0.36278 Ptcd1 0.71241 Nf2 0.54666 Ttc7b 0.44440 Lactb 0.36229 Polrmt 0.69551 Ctnnd1 0.53826 Slc12A4 0.44228 Ahctf1 0.36131 Dnajb9 0.69492 Ppp3ca 0.53438 Mycbp2 0.44204 Opa1 0.35864 Ubr2 0.68626 Zc3Hav1 0.52486 Snx27 0.44173 Cog8 0.35826 Adcy3 0.68340 Nbeal2 0.51671 Ugcg 0.44132 Vps52 0.35786 Abcb6 0.68004 Cog7 0.51653 Aqr 0.43855 Crnkl1 0.35701 Tspyl2 0.66200 Me2 0.51646 Mbtps1 0.43679 Sqrdl 0.35649 Mon2 0.65863 Aurkb 0.51638 Ncor1 0.43327 Bet1 0.35602 Ipo11 0.65218 Hp1Bp3 0.51036 Hdac3 0.42916 Pigu 0.35578 Hsph1 0.64898 Man2a1 0.50933 Sesn2 0.42117 Ino80c 0.35472 Nlrx1

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Table A.1 List of ITAM-containing Proteins Ranked by Expression Levels in Phagocytes (Cont’d)

Score Gene Symbol Score Gene Symbol Score Gene Symbol Score Gene Symbol 0.35155 Pole 0.27293 Tdrd7 0.22123 Pls3 0.16937 Dip2a 0.34970 Tmem5 0.27079 Adck1 0.21914 Lin54 0.16804 Frmd4a 0.34313 Fbxo21 0.27038 Zswim6 0.21894 Zfyve27 0.16779 Tmem184c 0.34283 Fnip1 0.26817 Gpr18 0.21846 Galt 0.16706 Zfp292 0.34183 Exoc1 0.26784 Sugp2 0.21727 Lrba 0.16447 Mlh1 0.34176 Prim1 0.26662 Sgms1 0.21723 Cd109 0.16401 Cysltr1 0.34036 Csnk2a2 0.26535 Mcoln3 0.21595 Zbtb4 0.16164 Zswim7 0.33895 Dock11 0.26529 Tmem63b 0.21500 Slc25a36 0.16115 Urgcp 0.33714 Clasp2 0.26363 Ercc2 0.21378 Snx25 0.15893 Trim65 0.33466 Gbe1 0.26097 Kntc1 0.21281 Pcmtd1 0.15824 Depdc5 0.33317 Cdc23 0.26057 Ino80 0.21185 Atr 0.15812 Ints8 0.32925 Usp34 0.26002 Stam2 0.21107 Ctsf 0.15795 Klf9 0.32890 Trrap 0.25799 Pfkfb4 0.21015 As3mt 0.15681 Snupn 0.32642 Slc25a30 0.25727 Samd9l 0.20728 Inpp5e 0.15350 Ncoa7 0.32545 Map2k7 0.25687 Aspm 0.20641 Tcp11l2 0.15343 Dclre1A 0.32487 Ccr1 0.25677 Itpr1 0.20601 B3gnt3 0.15289 Abcd4 0.32362 Ncor2 0.25663 B4galt3 0.20357 Exoc6b 0.14925 Ccdc88A 0.32017 Tmem101 0.25506 Tiparp 0.20259 Melk 0.14792 Pex10 0.32013 Prkra 0.25403 Nhlrc2 0.20212 Pgap1 0.14701 Kptn 0.31821 Ttc27 0.25380 Naa35 0.20044 Itpr2 0.14383 Pdcd4 0.31547 Shcbp1 0.25322 Lmbrd2 0.20029 Paox 0.14381 Vps8 0.31336 Itga9 0.25305 Phkb 0.19942 Flad1 0.14371 Cmtm8 0.31328 Phka2 0.25086 Enpp2 0.19831 Tbc1d25 0.14308 Prkdc 0.31323 Nprl2 0.25038 Casp8ap2 0.19777 Dock1 0.14289 Snrk 0.31174 Arfrp1 0.25026 Trnt1 0.19736 Mboat1 0.14138 Dennd2c 0.31151 Dhx29 0.25007 Lyst 0.19334 Brwd1 0.13831 Dopey1 0.30690 Crls1 0.24950 Fbxo31 0.19289 Fbxo7 0.13774 Pigb 0.30538 Trappc9 0.24777 Flt3 0.19198 Aldh7a1 0.13514 St7l 0.30203 Ubap2 0.24198 Gys1 0.19172 Agtpbp1 0.13463 Als2 0.30187 Ralgapb 0.24034 Nln 0.19021 Arid5b 0.13454 Adcy6 0.29997 Acad9 0.23954 Znhit6 0.18943 Tsen54 0.13413 Bsn 0.29923 Nol11 0.23882 Tmem128 0.18531 Cecr5 0.13381 Bcor 0.28724 Abhd13 0.23728 Myo9a 0.18121 Zmym4 0.13371 Spire1 0.28678 Gamt 0.23277 Gpr137 0.18054 Mga 0.13106 Kifap3 0.28305 Dock5 0.23108 Cfh 0.17917 Lrrc8a 0.13038 Stk38l 0.28086 Slc25A19 0.22927 Vill 0.17805 Gne 0.12931 Gpcpd1 0.27994 Mgat4a 0.22648 Gtf2E1 0.17731 Cars2 0.12672 Zbtb33 0.27604 Tsku 0.22611 Ubr1 0.17408 Fam172a 0.12634 Stam 0.27546 Mcoln2 0.22524 Anxa11 0.17288 Scd1 0.12579 Cnr2 0.27487 Myo10 0.22383 Entpd7 0.17261 Oasl1 0.12395 Rad18 0.27383 Tapt1 0.22298 Dip2B 0.17077 P2ry14 0.12106 Fntb 0.27367 Ptprm 0.22281 Angel2 0.17039 Ctc1 0.12059 Ctps2

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Table A.1 List of ITAM-containing Proteins Ranked by Expression Levels in Phagocytes (Cont’d)

Score Gene Symbol Score Gene Symbol Score Gene Symbol Score Gene Symbol 0.12009 Plxna2 0.08109 Plekhh3 0.03835 Trim16 0.01342 Sh2d7 0.11919 Gnpda2 0.08090 Mapkbp1 0.03774 Rora 0.01335 Zfp14 0.11909 Grk5 0.08034 Dzip3 0.03774 B4galt4 0.01297 Zdhhc23 0.11892 Ppip5k1 0.08019 Ficd 0.03747 Baiap3 0.01222 Rap1gap 0.11782 Ocrl 0.07991 Exog 0.03629 Satb2 0.01196 Abca5 0.11741 Cenpi 0.07913 Spns3 0.03516 Myo1b 0.01173 Tspan7 0.11711 Zcchc11 0.07803 Arv1 0.03312 Rasgrf2 0.01162 Mpp4 0.11528 Ighmbp2 0.07570 Ccr3 0.03276 Naip7 0.01152 Caprin2 0.11123 Pigv 0.07461 Serpinf1 0.03102 Plekhh2 0.01125 Hey1 0.11109 Naip5 0.07328 Rnf217 0.03071 Per2 0.01115 Rasgrf1 0.11071 Cdc14b 0.07319 Cacna1a 0.03041 Tmem63c 0.01113 Cd96 0.11050 Me1 0.07146 Pex11a 0.03033 Wdr19 0.01063 Arhgap32 0.11022 Dsn1 0.07133 Zfhx4 0.02999 Ccdc80 0.01055 Ptpn3 0.11007 Dtwd1 0.07124 Mag 0.02939 Ttc30b 0.01044 Slc17a7 0.10923 Atp10d 0.06856 Grasp 0.02924 Dpy19l3 0.00983 Chst1 0.10777 Jmy 0.06694 Brwd3 0.02692 Tlr11 0.00973 Sema4g 0.10656 P2ry1 0.06248 Emp2 0.02584 Slc25a14 0.00937 Aldh5a1 0.10612 Rcor3 0.06117 Abcd2 0.02464 Tuba8 0.00890 Xkrx 0.10474 Dock4 0.06001 Pex1 0.02449 Best1 0.00877 St6galnac2 0.10468 Ttc39b 0.05965 Cdc14A 0.02431 Slc22a15 0.00855 Nup210l 0.10408 Mtrf1 0.05405 Tmem216 0.02369 Epm2a 0.00839 Catsperg1 0.10240 Tmem143 0.05330 Ptch1 0.02345 Ttc30A1 0.00820 Npas4 0.10226 Dpp4 0.05223 Mtmr7 0.02304 Dennd5b 0.00817 Pdgfrb 0.10029 Clec16a 0.04951 Cenpk 0.02241 Cd79a 0.00803 Ctsw 0.09946 Alg6 0.04888 Cacna1f 0.02169 Plvap 0.00782 Nat1 0.09935 Ppp3cc 0.04770 B3Gnt7 0.02085 Osbpl10 0.00759 Gpr3 0.09745 Slc25a33 0.04702 Naip6 0.02053 Slc25a42 0.00747 Flt1 0.09714 Rdh10 0.04668 Amigo1 0.01986 Ablim1 0.00740 B4galnt3 0.09574 Gstk1 0.04547 Lamb2 0.01925 Ttc26 0.00714 Atp8b5 0.09436 Wwox 0.04545 Wdr35 0.01923 Pfkfb1 0.00712 Npas2 0.09421 Mfsd8 0.04503 Myh7b 0.01900 Clstn3 0.00703 Abca6 0.09333 Hlcs 0.04117 Paqr9 0.01889 Tssk4 0.00693 Ank1 0.09304 Ganc 0.04069 Timp3 0.01851 Hrh2 0.00691 Slc12a5 0.09107 Fancm 0.04059 Mansc1 0.01728 Gpr34 0.00690 Sema3c 0.09063 Myo1d 0.04038 Dock6 0.01663 Ly75 0.00635 Col12a1 0.09025 Slc16a7 0.04021 Kdr 0.01586 Cysltr2 0.00625 Ms4a2 0.09010 Rap1gap2 0.04010 Cacna1d 0.01546 Hectd2 0.00615 Nid1 0.08900 Tanc2 0.03998 Pdcd1lg2 0.01498 Myh10 0.00608 Ptpru 0.08878 Tmcc3 0.03936 Vnn3 0.01456 Cd247 0.00601 Fam3b 0.08786 Trib3 0.03924 Ahi1 0.01427 Espnl 0.00595 Atp1a4 0.08648 Lrrc8b 0.03843 Ptgfrn 0.01395 Cdnf 0.00594 Tie1 0.08164 Dync2h1 0.03841 Cmbl 0.01354 Lrig3 0.00562 Nsun7

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Table A.1 List of ITAM-containing Proteins Ranked by Expression Levels in Phagocytes (Cont’d)

Score Gene Symbol Score Gene Symbol Score Gene Symbol Score Gene Symbol 0.00554 Myh11 0.00335 Cacna1s 0.00203 Cpne5 0.00077 Elfn2 0.00551 Kcnq2 0.00332 Catsperg2 0.00198 Oxgr1 0.00052 Cpne9 0.00535 Efcab9 0.00331 Tsnaxip1 0.00197 Serpind1 0.00051 Tspan18 0.00528 Myh3 0.00328 Krt24 0.00196 Rasl12 0.00046 Unc93a 0.00528 Ptprd 0.00319 Slc16a4 0.00196 Plce1 0.00041 Elfn1 0.00527 Arnt2 0.00318 Prkg1 0.00194 Ano9 0.00041 Ttll2 0.00526 Fat3 0.00314 Ppp4r4 0.00193 Itih4 0.00037 Nbea 0.00524 Prdm11 0.00314 C1ql3 0.00191 Pigr 0.00037 Krt222 0.00523 C1ql4 0.00312 Myo1a 0.00191 Ttn 0.00034 Pamr1 0.00521 Enkur 0.00312 Kalrn 0.00191 Fbxl13 0.00033 Best3 0.00505 Slc7a13 0.00311 Kctd19 0.00190 Clgn 0.00032 Rlbp1 0.00504 Rapgefl1 0.00306 Lrguk 0.00190 Tspan11 0.00031 Ccdc87 0.00501 Slitrk4 0.00306 Has3 0.00190 Kcnd3 0.00031 Svop 0.00501 Cacna1b 0.00304 Gpr182 0.00189 Tmem145 0.00024 Myh14 0.00447 Dock3 0.00302 B3gnt6 0.00189 Trank1 0.00022 Fgd5 0.00419 Me3 0.00288 Ptprk 0.00189 Atp6v0a4 0.00021 Gif 0.00417 Angpt1 0.00288 Map3k13 0.00188 Myh4 0.00018 Gabrr1 0.00409 Adamts13 0.00288 Kif26b 0.00188 Myo5b 0.00014 Cndp1 0.00409 Folh1 0.00286 Best2 0.00188 Htr5b 0.00013 Myh7 0.00407 Gja8 0.00285 Fap 0.00187 Ptchd3 0.00013 Scn8a 0.00406 Dsp 0.00284 Cdk15 0.00186 Myh1 0.00012 Tdrd9 0.00404 Glb1l2 0.00274 Ddah1 0.00185 Unc13c 0.00012 Nrxn1 0.00398 Nmbr 0.00265 Ttll7 0.00185 Scn5a 0.00011 F2Rl1 0.00395 Slc16a14 0.00264 Cdh23 0.00185 Fras1 0.00010 D7Ertd443E 0.00385 Greb1l 0.00259 Igsf10 0.00184 Slc45a1 0.00009 Tmem130 0.00384 Lrrc19 0.00255 Phex 0.00183 Pls1 0.00008 Aox3 0.00383 Sema6a 0.00249 Cd3e 0.00183 Adrb3 0.00008 Cacna1c 0.00381 Cd3d 0.00248 Naalad2 0.00183 Capn13 0.00008 Otop3 0.00378 Bdkrb2 0.00238 Adam32 0.00183 Cyp4a12a 0.00008 Clstn2 0.00376 Clmn 0.00235 Cd3g 0.00183 Gabrb3 0.00007 Pde1a 0.00374 Efcab5 0.00230 Prss38 0.00183 Mgat5b 0.00007 Clip4 0.00367 Adcy10 0.00224 Pcdh18 0.00183 Nrxn3 0.00006 Smarca1 0.00367 Klb 0.00220 Scn4a 0.00183 Otc 0.00004 Tex11 0.00366 Efs 0.00219 Slc2A4 0.00168 Popdc2 0.00004 Grid2ip 0.00366 Enpp3 0.00216 Kcnk3 0.00167 Trpm6 0.00003 Grm5 0.00366 Gabrb1 0.00216 Plxnb1 0.00157 B3Galt2 0.00003 Kcnma1 0.00357 Trim43c 0.00216 Hhip 0.00122 Gpr39 0.00003 Mboat4 0.00356 Greb1 0.00215 Glis1 0.00098 C1ql1 0.00002 Esrrb 0.00352 Gpr61 0.00207 Lrrc17 0.00093 Atp8a2 0.00002 Krt19 0.00352 Atp1a2 0.00205 Cacna1e 0.00088 Slc17a8 0.00002 Stox1 0.00347 Tecta 0.00204 Ccr4 0.00086 Fat4 0.00002 Tmem30c 0.00336 Gcgr 0.00203 Myh6 0.00083 Nek10

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INDUCTION OF PHAGOCYTOSIS BY CHIMERIC PHAGOCYTIC

RECEPTORS

(a) (b)

Figure B. 1 Induction of Phagocytosis in COS-1 and Moesin-KD DC2.4 Cells with ICAM-1- ITAM Chimera (a) Cos-1 cells were transfected with ICAM-1, ICAM-1-ITAM chimeric molecule or empty vector control by transient overexpression, and phagocytosis assay was performed using anti- ICAM-1 coated beads. (b) Moesin-KD DC2.4 cells were transfected with ICAM-1, ICAM-1- ITAM chimeric molecule or empty vector control by transient overexpression, and phagocytosis assay was performed using anti-ICAM-1 coated beads. Non-specific shRNA (NS) transfected cells were also used as the control for Moesin KD.

234

(a) (b)

Figure B. 2 Induction of Phagocytosis in COS-1 and Moesin-KD DC2.4 Cells with CD8a- ITAM Chimera (a) Cos-1 cells were transfected with CD8a, CD8a-ITAM chimeric molecule or empty vector control by transient overexpression, and phagocytosis assay was performed using anti-CD8a- coated beads. (b) Moesin-KD DC2.4 cells were transfected with CD8a, CD8a-ITAM chimeric molecule or empty vector control by transient overexpression, and phagocytosis assay was performed using anti-ICAM-1 coated beads. Non-specific shRNA (NS) transfected cells were also used as the control for Moesin KD.

235

PHYLOGENIC TREES OF KEY PHAGOCYTIC MOLECULES

Figure C. 1 Phylogenetic tree of moesin proteins family based on maximum likelihood.

Numbers above branches represent bootstrap support in percentage from 100 replicates, and values less than 50 are not shown. Numbers below branches show branch lengths in the unit of the number of substitutions per site. The scale bar is in the unit of substitutions per site. This analysis is performed by Libing Mu with inputs from Lin Miao.

236

(a)

(b)

Figure C. 2 Phylogenetic tree of FcγR common γ chain and FcγRII family proteins based on maximum likelihood. Phylogenetic trees of (a) FcγR common γ chain and (b) FcγRII family proteins are displayed. Numbers above branches represent bootstrap support in percentage from 100 replicates, and values less than 50 are not shown. Numbers below branches show branch lengths in the unit of the number of substitutions per site. The scale bar is in the unit of substitutions per site. This analysis is performed by Libing Mu with inputs from Lin Miao.

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Figure C. 3 Phylogenetic tree of PI3K catalytic subunit proteins family based on maximum likelihood.

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Figure C. 4 Phylogenetic tree of Syk/ZAP-70 proteins family based on maximum likelihood.

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In submitting an article to any of the journals published by SpringerOpen I certify that:

1. I am authorized by my co-authors to enter into these arrangements. 2. I warrant, on behalf of myself and my co-authors, that: o the article is original, has not been formally published in any other peer- reviewed journal, is not under consideration by any other journal and does not infringe any existing copyright or any other third party rights; o I am/we are the sole author(s) of the article and have full authority to enter into this agreement and in granting rights to Springer are not in breach of any other obligation; o the article contains nothing that is unlawful, libellous, or which would, if published, constitute a breach of contract or of confidence or of commitment given to secrecy; o I/we have taken due care to ensure the integrity of the article. To my/our - and currently accepted scientific - knowledge all statements contained in it purporting to be facts are true and any formula or instruction contained in the article will not, if followed accurately, cause any injury, illness or damage to the user. 3. I, and all co-authors, agree that the article, if editorially accepted for publication, shall be licensed under the Creative Commons Attribution License 4.0. If the law requires that the article be published in the public domain, I/we will notify Springer at the time of submission, and in such cases the article shall be released under the Creative Commons 1.0 Public Domain Dedication waiver. For the avoidance of doubt it is stated that sections 1 and 2 of this license agreement shall apply and prevail regardless of whether the article is published under Creative Commons Attribution License 4.0 or the Creative Commons 1.0 Public Domain Dedication waiver. 4. I, and all co-authors, agree that, if the article is editorially accepted for publication in Chemistry Central Journal, Chemical and Biological Technologies in Agriculture, Geochemical Transactions, Heritage Science, Journal of Cheminformatics, or Sustainable Chemical Processes, data included in the article shall be made available under the Creative Commons 1.0 Public Domain Dedication waiver, unless otherwise stated. For the avoidance of doubt it is stated that sections 1, 2, and 3 of this license agreement shall apply and prevail. [End of SpringerOpen’s license agreement] ______

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Explanatory notes regarding SpringerOpen’s license agreement

As an aid to our authors, the following paragraphs provide some brief explanations concerning the Creative Commons licenses that apply to the articles published in SpringerOpen -published journals and the rationale for why we have chosen these licenses.

The Creative Commons Attribution License (CC BY), of which CC BY 4.0 is the most recent version, was developed to facilitate open access as defined in the founding documents of the movement, such as the 2003 Berlin Declaration. Open access content has to be freely available online, and through licensing their work under CC BY authors grant users the right to unrestricted dissemination and re-use of the work, with only the one provison that proper attribution is given to authors.

This liberal licensing is best suited to facilitate the transfer and growth of scientific knowledge. The Open Access Scholarly Publishers Association (OASPA) therefore strongly recommends the use of CC BY for the open access publication of research literature, and many research funders worldwide either recommend or mandate that research they have supported be published under CC BY. Examples for such policies include funders as diverse as the Wellcome Trust, the Australian Governments, the European Commission’s Horizon 2020 framework programme, or the Bill & Melinda Gates Foundation.

The Creative Commons Attribution License 4.0 provides the following summary (where ‘you’ equals ‘the user’):

You are free to:

• Share — copy and redistribute the material in any medium or format • Adapt — remix, transform, and build upon the material for any purpose, even commercially. The licensor cannot revoke these freedoms as long as you follow the license terms

Under the following terms:

• Attribution— you must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. • No additional restrictions—you may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

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Notices You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation. No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.

Please note: For the terms set in italics in the summary above further details are provided on the Creative Commons web page from which the summary is taken (http://creativecommons.org/licenses/by/4.0/).

As specified in clause 4 of the Springer Open license agreement shown above, a small number of SpringerOpen journals use the Creative Commons 1.0 Public Domain Dedication waiver (CC0 or CC zero) for data published within articles. This open data policy follows the same logic, facilitating maximum benefit and the widest possible reuse of knowledge. It is also the case that in some jurisdictions copyright does not apply to data. CC0 waives all potential copyrights, to the extent legally possible, as well as the attribution requirement. The waiver applies to data, not to the presentation of data. If, for instance, a table or figure displaying research data is reproduced, CC BY and the requirement to attribute applies. Increasingly, however, new insights are possible through the use of big data techniques, such as data mining, that harness the entire corpus of digital data. In such cases attribution is often technically infeasible due to the sheer mass of the data mined, making CC0 the most suitable licensing tool for research outputs generated from such innovative techniques.

It is important to differentiate between legal requirements and community norms. It is first and foremost a community norm, not a law, that within the scientific community attribution mostly takes the form of citation. It is also a community norm that researchers are expected to refer to their sources, which usually takes the form of citation. Across all cases of research reuse (including data, code, etc), community norms will apply as is appropriate for the situation: researchers will cite their sources where it is feasible, regardless of the applicable license. CC0 therefore covers those instances that lie beyond long-established community norms. The overall effect, then, of CC0 for data is to enable further use, without any loss of citations. For further explanations, please refer to BioMed Central’s Open Data page.

The Creative Commons 1.0 Public Domain Dedication waiver provides the following summary:

No copyright The person who associated a work with this deed has dedicated the work to the public domain by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighbouring rights, to the extent allowed by law.

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You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other information below.

Other information

• In no way are the patent or trademark rights of any person affected by CC0, nor are the rights that other persons may have in the work or in how the work is used, such as publicity or privacy rights. • Unless expressly stated otherwise, the person who associated a work with this deed makes no warranties about the work, and disclaims liability for all uses of the work, to the fullest extent permitted by applicable law. • When using or citing the work, you should not imply endorsement by the author or the affirmer. Please note: for the terms set in italics in the summary above further details are provided on the Creative Commons web page from which the summary is taken (http://creativecommons.org/publicdomain/zero/1.0/).

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