Role of Ion Channels and Activation State in

Regulation of Podosomes, Migration and

Invasion, and Phagocytosis in Microglia

by

Tamjeed Ahmed Siddiqui

A thesis submitted in conformity with the requirements

for the degree of Doctor of Philosophy

Graduate Department of Physiology

University of Toronto

© Copyright 2016 by Tamjeed Ahmed Siddiqui

ii

Role of Ion Channels and Activation State in Regulation

of Podosomes, Migration and Invasion, and

Phagocytosis in Microglia

Tamjeed Ahmed Siddiqui

Doctor of Philosophy

Graduate Department of Physiology

University of Toronto

2016

Abstract

Microglia are resident immune cells and professional phagocytes of the CNS. They

rapidly respond to injury and disease and can assume a spectrum of activation states with

pro-inflammatory (M1) or anti-inflammatory (M2) being at the extreme ends. It is

important to understand how microglial activation states affect their migration and

phagocytosis, crucial functions after injury. However, the mechanisms that regulate these

phenotypes are not well characterized. As well, the cytokine profile after injury or disease

is changing yet little is known about the molecular and functional consequences. We

hypothesized that the microglial phenotype is different in each activation state, with ion

channels regulating specific microglia functions. Rat microglia cultures were stimulated

with IFN-γ plus TNF-α ("I + T"; M1 activation), interleukin-4 (M2a/alternative

activation), and interleukin-10 (M2c/acquired deactivation). I report that IL-4- and IL-10-

treated cells differentially express podosomes but migrate and invade much better.

Further, based on enrichment of KCa2.3/SK3 Ca2+-activated potassium channels in

microglial podosomes, we predicted that it regulates migration and invasion.

Surprisingly, of three KCa2.3 inhibitors (apamin, tamapin, NS8593), only NS8593

iii

abrogated the increased migration and invasion of IL-4 and IL-10-treated microglia. This

discrepancy was explained by the observed block of TRPM7 currents by NS8593. We

conclude that TRPM7 (not KCa2.3) contributes to the enhanced ability of microglia to

migrate and invade under anti-inflammatory states. Next, we assessed: (i) gene

expression changes reflecting microglial activation and inflammatory states, and

receptors and enzymes related to phagocytosis and ROS production; (ii) myelin

phagocytosis and production of ROS; and (iii) expression and contributions of several ion

channels that are considered potential targets for regulating microglial behavior. M1

stimulation increased pro-inflammatory genes, phagocytosis, and ROS. M2a stimulation

increased anti-inflammatory genes and ROS production. Myelin phagocytosis enhanced

the M1 profile and dampened the M2a profile, and both phagocytosis and ROS

production were dependent on NOX enzymes, Kir2.1 and CRAC channels. Importantly,

microglia showed some capacity for re-polarization between M1 and M2a states, based

on gene expression changes, myelin phagocytosis, and ROS production. Together, these

results characterize two major reactive phenotypes observed after injury, and elucidate

regulatory roles of ion channels for specific microglia functions.

iv

Acknowledgements I would like to begin by expressing my gratitude to my supervisor, Dr Lyanne C

Schlichter. Over the past six-plus years, she took me under wings to teach me how to

critically analyze findings and perform thought experiments, to “sit with my cells”, that

became a valuable tool in my various projects. I used to be a terrible writer but have

improved a lot, all thanks to Dr Schlichter. She has been incredibly patient with me,

taking the time to teach me writing skills and make me understand the importance of

writing as a medium to communicate my ideas and work. Her support, dedication,

enthusiasm and advice among many other attributes made working with her an

educational and fun experience. Her guidance and supervision, enabled me to evolve into

a better person and mature into a better scientist. I would also like to thank Dr Schlichter

for all the hard work and time she invests into writing grants that provide funding for us

and the lab. She was also available as a confidant to hear my personal issues for which I

am truly grateful. I know I was not the easiest student to work with and I cannot express

in words how thankful I am for the opportunity to work with Dr Schlichter, but I hope I

am able to make her proud as a graduate student that she trained.

I extend thanks to my committee members, Dr James Eubanks and Dr Shannon

Dunn as well as other faculty members including Dr Peter Pennefather, for their time to

attend meetings and helpful suggestions. Their comments and suggestions provided

valuable support in furthering my work. I am also grateful to my examiners for taking

time to read my thesis and attend my examination meeting.

Special thanks to my work family at the lab, past and current. Dr Starlee Lively

for “lively” discussions inside and outside lab meetings, reading and editing reports (so

many corrections!), and being an amazing adviser for various facets of research and life.

Thanks to Dr Roger Ferreira and Raymond Wong for being my go to guys for “sparking”

my electrophysiology knowledge; Dr Jayalakshmi Caliaperumal (Jaya) for discussing and

v

sharing ideas regarding my work. Thank you to Michael Joseph and Doris Lam for

constantly listening in on my annoying discussions/arguments with a smile on their face

and never complaining. As well, Stanley lab members Sabiha Gardezi (G-unit), Robert

Chen, Fiona Wong, Arup Nath, Britney, Qi Li. All of you are amazing people that have

more “culture” than my microglia cultures.

Much thanks to Xiaoping Zhu and Frank Vidic. Xiaoping is the tireless force that

managed the lab from behind the scenes to make sure everyone is taken care of. Xiaoping

was the first person to make me comfortable in the lab when I started as a graduate

student and she made a promise that she would not retire until I graduate. She lied. But I

hold no resentment because of the amazing person that she is and friendship that she

provided when she was at work, with her infectious smile, always on my right hand side.

We still miss you. I would also like to thank Frank Vidic for providing technical support

and responding to the oddest requests that is hard to describe yet he understood. Both

Xiaoping and Frank are one of the most dedicated people I have had the pleasure to meet

and work with.

I wanted to thank the administrative staff at UHN and University of Toronto,

Rosalie Pang, Colleen Shea, Julie Wan and Leanne Da Costa, for all the help and support.

I owe a lifetime of gratitude and love to my parents for their sacrifice and trust to

send their teenage son off to Toronto to ensure I received the best education. My mother,

who provides endless love to the family, taught me that through hard work anything can

be achieved and to never give up. My father, who has always been patient and

understanding, taught me that through honesty, perseverance and tenacity, nothing is

impossible. They continue to be my role models and are the architects of my personality.

Thanks to both my brothers as well for always being there, enjoying the good times and

rescuing me from the bad times.

vi

To my in-laws, Suresh, Velvili and Geththn, I cannot thank you all enough for

providing amazing dedication, care and support so that my life is comfortable and stress-

less. For making me feel important and strengthening my spirits when I needed it so

many times through my research career. To the love of my life, my wife Kiruththiga

Sures. You endured so much from me through the years, from listening to me ramble on

about my failed experiments to reading papers in the middle of the night with the lights

on or sleeping at odd hours not by your side and making keyboard sounds as I write my

reports. No matter the hardship, you always reminded me of the positive aspects in

everything and stuck by me, motivating and encouraging me. You were also there to

celebrate my accomplishments. To make them more special than even I could imagine.

You were always the better person between the two of us. I may not have had the

opportunity to show you my appreciation but I now have a lifetime to return the favor and

say thank you for being my companion, my best friend, my love, my soul mate, my wife,

my angel. NVBI!

vii

Table of Contents

Abstract

Acknowledgements

Table of contents

List of Tables

List of Figures

Abbreviations

Publications

Chapter 1. General Introduction

1.1. Organization of this thesis

1.2. Microglia: Immune cells of the CNS

1.3. Microglia and neuroinflammation

1.4. Microglia activation

1.5. Inducing microglia activation in vitro

1.5.1. Pro-inflammatory or M1 cytokines

1.5.2. Anti-inflammatory or M2a cytokines

1.5.3. Acquired deactivation or M2c cytokines

1.6. Myelin phagocytosis

1.6.1.1. Phagocytosis-related receptors

1.6.1.2. Phagocytosis and respiratory burst

1.6.1.3. Phagocytosis and the microglial activation state

1.7. Migration and podosomes

1.8. Ion channels in microglia

1.8.1.1. Ca2+-permeable channels

1.8.1.2. Kv1.3 and Kir2.1 channels

1.8.1.3. Ca2+-activated K+ channels

1.9. Project rationales and Hypotheses

Project 1. To assess the contribution of Ca2+-activated K+ channels to

podosomes, migration and invasion

Project 2. To evaluate relationships between microglial activation

states, myelin phagocytosis and respiratory burst, and contributions of

ion channels

viii

Chapter 2. General Methods

2.1 Microglia cell cultures

2.2. Chemicals and antibodies

2.3. Immunocytochemistry (ICC)

2.4. Nanostring and qRT-PCR

2.5. Patch clamp electrophysiology

2.6. Transmigration and invasion assays

2.7. Myelin phagocytosis and ROS production

2.8. Statistical Analysis

Chapter 3. Expression and Contributions of TRPM7 and KCa2.3/SK3 Channels to

the Increased Migration and Invasion of Microglia in Anti-Inflammatory Activation

States

3.1. Introduction

3.2. Results

3.3. Discussion

Chapter 4. Complex molecular and functional outcomes of single versus sequential

cytokine stimulation of rat microglia

4.1. Introduction

4.2. Results

4.3. Discussion

4.4. Conclusions

Chapter 5. General Discussion

5.1. Microglia activation and white matter damage

5.2. Microglia polarization in ischemic core

5.3. Microglia polarization in peri-infarct

5.4. Potential therapeutic strategies

5.5. Microglia polarization in ICH

5.6. Ion channel regulation of microglia behaviour

5.7. Proposed model

Chapter 6. Conclusions

Chapter 7. Future Directions

Chapter 8. References

ix

List of Tables

Table 1. Target sequences for NanoString nCounter analysis in Chapter 3…………33

Table 2. Target sequences for NanoString nCounter analysis in Chapter 4…………35

x

List of Figures

Figure 3.1. NanoString analysis of expression changes for selected genes in response to

IL-4- and IL-10-treatment ..……………………………………………………………..44

Figure 3.2. Effect of microglial activation state and selected channel inhibitors on

podosome (podonut) expression ………………………………………………………...49

Figure 3.3. Migration of primary rat microglia is affected by the activation state, and by

KCa2.3 and TRPM7 inhibitors ……………………………………………………….....52

Figure 3.4. KCNN3 expression and KCa2.3 current inhibition by NS8593 in microglia in

differing activation states………………………………………………………………...56

Figure 3.5. NS8593 and AA-861 inhibit the TRPM7 current in primary rat microglia and

MLS-9 microglial cells ……………………………………………………………….....61

Figure 3.6. Mg2+-dependence of TRPM7 current block by NS8593 …………………..64

Figure 3.7. Effects of IL-4- and IL-10-treatment on TRPM7 expression, current and

block by NS8593 in primary rat microglia ………………………………………...........66

Figure. 4.1. Effects of microglial activation state and exposure to myelin on

inflammatory gene expression ….……………………………………………………….77

Figure. 4.2. Effects of microglial activation state on expression of phagocytosis-related

molecules, phagocytosis, and ROS production ………………………………………….81

Figure. 4.3. Expression of ROS-related molecules and contribution of NOX enzymes to

myelin phagocytosis and ROS production ……………………………………………....86

Figure. 4.4. Repolarizing the inflammatory profile of microglia using sequential cytokine

addition …………………………………………………………………………….........89

Figure. 4.5. Sequential cytokine addition affects expression of phagocytosis-related

molecules ……...………….............................................................................................92

Figure. 4.6. Sequential cytokine addition affects expression of ROS-associated genes

……..........................................................................................................................……94

Figure. 4.7. Sequential cytokine addition affects myelin phagocytosis and NOX-

mediated ROS production ……………………………………………………………….97

Figure. 4.8. Transcript expression of K+ channels and SOCE-related genes is affected by

the microglial activation state and myelin phagocytosis ...…………………………….101

Figure. 4.9. Roles of K+ and CRAC channels in myelin phagocytosis and ROS

production ......................................................................................................................104

xi

Abbreviations

CD: Cluster of differentiation

CNS: Central nervous system

CR3: Complement receptor 3

CRAC: Calcium release activated calcium

DAG: Diacylglycerol

DCF: Dichlorodihydrofluorescein

DiI: 1,1'-dioctadecyl-3,3,3',3'-tetramethylindocarbocyanine

ECM: Extracellular matrix

FBS: Fetal bovine serum

HEPES: 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid

IFN-γ: Interferon gamma

IL: Interleukin

IP3: Inositol trisphosphate

LAMP-1: Lysosome-associated membrane glycoprotein

LPS: Lipopolysaccharide

MEM: Minimum essential medium

MTMR6: Myotubularin related protein 6

NADPH: Nicotinamide adenine dinucleotide phosphate

NOX: NADPH oxidase

PI3K: Phosphoinositide-3-kinase

PIP2: Phosphotidylinositol bisphosphate

PLC: Phospholipase C

PMA: Phorbol myristate acetate

RB: Respiratory burst

RNA: Ribonucleic acid

ROS: Reactive oxygen species

RT-PCR: Reverse transcription-polymerase chain reaction

SIRPα: Signal regulatory protein alpha

SOCE: Store operated calcium entry

SR-A: Scavenger receptor-A

STIM: Stromal interaction molecule

TIM-3: T-cell immunoglobulin and mucin-domain containing 3

TNF-α: Tumor necrosis factor alpha

TREM2: Triggering receptor expressed on myeloid cells 2

xii

Publications Siddiqui TA, Lively S, Schlichter LC. Complex molecular and functional outcomes of

single versus sequential cytokine stimulation of rat microglia. J Neuroinflammation.

2016 Mar 24;13(1):66.

Siddiqui T, Lively S, Ferreira R, Wong R, Schlichter LC. Expression and contributions

of TRPM7 and KCa2.3/SK3 channels to the increased migration and invasion of

microglia in anti-inflammatory activation states. PLoS One. 2014 Aug

22;9(8):e106087.

Siddiqui TA, Lively S, Vincent C, Schlichter LC. Regulation of podosome formation,

microglial migration and invasion by Ca(2+)-signaling molecules expressed in

podosomes. J Neuroinflammation. 2012 Nov 17;9:250.

Vincent C, Siddiqui TA, Schlichter LC. Podosomes in migrating microglia:

componentsand matrix degradation. J Neuroinflammation. 2012 Aug 8;9:190.

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Chapter 1. General Introduction

1.1. Organization of this thesis

This thesis is based on the work contained in two published papers (Siddiqui et al., 2014;

Siddiqui et al., 2016). Accordingly, Chapters 3 and 4 have been taken whole from their

respective manuscripts. The general introduction provides background knowledge

regarding microglia biology, specifically activation, migration, phagocytosis and ion

channels. It is to serve as a foundation for the brief introductions found in Chapters 3 and

4. These chapters will contain a brief Introduction followed by all of the Results and

Discussion from the original paper. Then a General Discussion will address the most

salient findings from the thesis in light of the literature that will culminate in a proposed

model to help understand the findings in a cohesive manner. The last section will

highlight some limitations of the aforementioned studies and suggest future investigations

for furthering knowledge regarding microglia physiology and neuroinflammation.

1.2. Microglia: Immune cells of the CNS

Microglia represent 5 to 20% of the total glial cell population in the CNS (Kaur et al.,

2010). Understanding the origins of microglia is important to appreciate the specialized

functions they play in the CNS. Microglia are a unique population among mononuclear

myeloid cells. In the early stages of embryonic development, mouse microglia precursor

cells have been shown to originate from yolk sac erythromyeloid precursors that migrate

away from the sac and invade the developing CNS (Biber et al., 2016; Ginhoux et al.,

2010; Kierdorf et al., 2013; Schulz et al., 2012). This was a remarkable finding,

considering the yolk sac is an extra-embryonic tissue that develops early in pregnancy as

part of primitive hematopoiesis. The precursor cells then proliferate and migrate to

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different regions of the brain to differentiate into microglial cells. Post-natally, microglia

reside in an immune privileged environment due to the blood brain barrier (BBB) that

separates the brain anatomically and physiologically, strictly regulating substances that

cross the barrier (Alberts, 2008). In fact, the microglial population in the healthy brain is

considered to be self-sustained. It does not require replenishment from systemic immune

precursor cells and there is no contribution of bone marrow components to the microglial

population (Ajami et al., 2007; Mildner et al., 2007; Schulz et al., 2012). Essentially,

microglia exist in a specialized environment without interacting with blood throughout a

healthy lifespan, unlike most other tissue resident macrophages. With time, as microglia

populate various areas of the brain, they lose their migration capacity and differentiate to

enter a ‘quiescent’ state. The cells constantly survey their surrounding environment with

the help of highly motile processes that contact various cell types, including astrocytes

and neurons, sampling via pinocytosis (Davalos et al., 2005; Kaur et al., 2010;

Nimmerjahn et al., 2005). Besides microglial surveillance, groups have shown that they

play a critical role in CNS development by producing trophic factors, such as insulin-like

growth factor-1 (Ueno et al., 2013), by supporting synaptogenesis (Roumier et al., 2004;

Zhan et al., 2014), neurogenesis (Butovsky et al., 2006; Choi et al., 2008; Walton et al.,

2006), aiding in tissue vascularization (Checchin et al., 2006; Fantin et al., 2010) and

neuronal axon guidance (Herbomel et al., 2001; Rochefort et al., 2002; Verney et al.,

2010), and clearing apoptotic cells via phagocytosis (Cunningham et al., 2013; Marin-

Teva et al., 2004). Additionally, microglia maintain homeostasis by directly interacting

with synaptic termini, dendritic spines, astrocytic processes, and synaptic clefts, to aid in

supporting synaptic connections and monitoring synaptic activity (Chung et al., 2015;

Tremblay et al., 2010; Wake et al., 2009). Depending on the activity, microglia can also

prune non-functional synapses, which can in turn modulate neuronal networks (Li et al.,

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2012; Paolicelli et al., 2011) and influence learning and memory (Parkhurst et al., 2013).

In a transgenic mouse model that results in a significantly reduced microglia population,

the brain exhibits increased neuron and astrocyte populations but reduced

oligodendrocyte numbers relative to wild type mice (Erblich et al., 2011).

1.3. Microglia and neuroinflammation

Injury to the CNS can be generally classified into two categories: traumatic acute injury

(e.g., stroke, physical injury) or slowly evolving chronic injury (e.g. infection, multiple

sclerosis). Because our research group primarily studies microglial response after stroke

in vivo, the focus of this thesis will be on acute injury to the brain. Acute injury causes

extensive tissue damage and necrotic cell death that produces cell debris and releases

intracellular substances like ATP into the brain parenchyma (Doll et al., 2014; Melani et

al., 2005). These are the primary events that initiate the neuroinflammation process, along

with disruption of the blood brain barrier (BBB), edema, and excitotoxicity (Doll et al.,

2014; Gaetz, 2004; Shoichet et al., 2008). Some aspects of the inflammation process

involve production of cytotoxic reactive radicals, and alterations in gene expression and

cell signalling that induce pro-inflammatory and anti-inflammatory responses. The initial

events and evolution of neuroinflammation lead to a secondary response that results in

damage to neural tissue, demyelination, and formation of a glial scar that is considered to

be inhibitory to regeneration (Shoichet et al., 2008). As part of the pro-inflammatory

response, there are increased levels of inflammatory cytokines (e.g. TNF-α, IL-1β) in the

early phases of injury, such as stroke, that persist for hours to days (Lambertsen et al.,

2012). Expression of anti-inflammatory cytokines (e.g. IL-4, IL-10, TGFβ) also increases

in the early phases of stroke injury (Doll et al., 2014; Doyle et al., 2010; Kim et al., 2000;

Krupinski et al., 1996; Li et al., 2001). Microglia are considered to be one of the major

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sources of the aforementioned cytokines. Microglia play a crucial role in shaping the

neuroinflammatory response. As resident immune cells of the brain, they possess a wide

array of receptors that aid in homeostasis and detection of pathological stimuli (Hickman

et al., 2013). As a response to injury stimuli, microglia undergo a complex transformation

process from the non-activated “quiescent” state to “activated”. Once activated, microglia

exhibit various phenotypes; e.g., proliferation, migration, phagocytosis, production of

interleukins, cytokines and reactive oxygen species (Hanisch and Kettenmann, 2007;

Kaushal et al., 2007; Kettenmann et al., 2011; Schlichter et al., 2010), which will be

discussed further below.

1.4. Microglia activation

Considering the versatile nature of microglial cells, it is not surprising that there is

growing evidence of microglial involvement in most, if not all, neuropathologies (Block

et al., 2007; Colton, 2009; Davoust et al., 2008; Graeber, 2010; Hanisch and Kettenmann,

2007; Kaur et al., 2010; Kreutzberg, 1996; Streit, 2005). In the healthy brain, “resting”

microglia have a ramified morphology with a small somata and many thin processes

extending in various directions (Biber et al., 2016; Kettenmann et al., 2011). The

processes are highly motile and survey the local microenvironment of the brain (Davalos

et al., 2005; Nimmerjahn et al., 2005). Microglial activation in response to damage results

in well-known morphological changes, characterized by retraction of the processes, and

hypertrophy of the cell body to adopt a more amoeboid-like morphology (Kreutzberg,

1996; Schlichter et al., 2010). Enhanced expression of CD11b (CR3/MAC-1), Iba1

(AIF1) and CD68 (ED-1) are commonly used markers to identify activated microglia in

vivo (Ito et al., 2001; Morrison and Filosa, 2013). In addition to these changes, microglial

activation can be simply categorized into two extremes depending on the injury context

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and activation state, i.e., pro-inflammatory and anti-inflammatory states. The pro-

inflammatory or M1 activation state is associated with exacerbation of tissue damage by

producing noxious factors like IL-1β, TNF-α, ROS, iNOS-mediated NO, and MMPs

(Gibson et al., 2005; Gottschall et al., 1995; Lambertsen et al., 2009; Ritzel et al., 2015a;

Starossom et al., 2012). Anti-inflammatory or M2 activation states are associated with

tissue repair and protecting the brain against injury (Cherry et al., 2014; Colton, 2009;

Franco and Fernandez-Suarez, 2015; Hanisch, 2013). To curb inflammation, M2

microglia produce neurotrophic factors, such as IGF-1 (Lai and Todd, 2006) and BDNF

(Elkabes et al., 1996), and anti-inflammatory cytokines, such as TGFβ (Lehrmann et al.,

1998; Wiessner et al., 1993) and IL-10 (de Bilbao et al., 2009). After experimental stroke,

down-regulating general microglial activation reduced the infarct size (Weng and Kriz,

2007; Yrjanheikki et al., 1998) and induced potential neurogenesis for beneficial

behavioural outcomes (Liu et al., 2007). When assessing microglia polarization after

injury, some studies have reported that M2 markers were up-regulated before M1

markers after ischemic stroke (Hu et al., 2012; Perego et al., 2011; Suenaga et al., 2015)

and traumatic brain injury (Wang et al., 2013). Conversely, M1 markers were up-

regulated before M2 markers after intracerebral hemorrhage (Wan et al., 2016; Yang et

al., 2016) and after cuprizone-induced demyelination (Miron et al., 2013). Although these

studies suggest that microglia can repolarize between activation states, they did not

discriminate microglia from infiltrating macrophages. Macrophages that infiltrate the

brain after injury cannot be distinguished from activated, rounded up microglia

morphologically, and cell-specific markers are controversial. Consequently, pure

microglia cultures are a valuable tool to test the hypothesis that microglia can repolarize

between activation states. Therapeutic strategies to influence microglial activation state

usually propose blanket treatments that promote the anti-inflammatory state and/or inhibit

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the pro-inflammatory state. However, there is evidence that both pro- and anti-

inflammatory responses can play a role in tissue repair (Yong and Marks, 2010). Findings

presented in this thesis will further support this possibility and illustrate the complex

biology of neuroinflammation.

1.5. Inducing microglia activation in vitro

Microglia can be stimulated into different activation states in vitro. Pro-inflammatory, or

M1 activation, is characterized by expression of pro-inflammatory molecules, such as

inducible nitric oxide synthase (iNOS), interleukin 1β (IL-1β), and cyclooxygenase-2

(COX-2) (Franco and Fernandez-Suarez, 2015). It is typically induced by adding

lipopolysaccharide (LPS), a component of gram negative bacteria cell walls. However,

this stimulation model reflects CNS bacterial infection rather than acute damage, such as

stroke. Instead, we use a combination of interferon-gamma (IFN-γ) and tumor necrosis

factor-alpha (TNF-α) to induce M1 activation (see Fig 4.1). M2 activation can be divided

into M2a, M2b and M2c sub-categories. This thesis will focus on M2a and M2c. M2a

activation, or alternative activation, is characterized by expression of mannose receptor 1

(MRC1/CD206) and the chemokine, CCL22 (Franco and Fernandez-Suarez, 2015).

Interleukin-4 (IL-4) is the most common cytokine used to evoke an M2a response. M2c

activation, or acquired deactivation, can be induced by interleukin 10 (IL-10) but there is

some evidence that the evoked gene changes more closely resemble an M1 profile (Chhor

et al., 2013). It is important to note that all polarizing treatments used in the Schlichter

lab are physiologically relevant cytokines that are produced after acute damage, such as

stroke. In addition, our in vitro studies at the molecular level show that our microglia

cultures have low expression of inflammatory molecules, including iNOS, IL-1β, TNF-α,

MRC1, and CD163, indicating that they are relatively quiescent (Lively and Schlichter,

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2013; Siddiqui et al., 2014; Sivagnanam et al., 2010). The distinction between M1 and

M2 is a simplification and represents the extreme states of what is likely a continuum in

vivo. More likely is that, during neuropathology, dynamic changes in the CNS cytokine

environment evoke both extremes and intermediate states of microglial activation.

1.5.1. Pro-inflammatory or M1 cytokines

Interferon-gamma (IFN-γ) is a type II interferon that can bind to a receptor complex

consisting of IFN-γ receptors type 1 and 2 (IFNR1 and IFNR2), and initiate signalling via

the Janus family kinases, Jak1/2 (Schroder et al., 2004). A downstream effector of the

activated Jak kinases is the transcription factor, STAT1, which, in its phosphorylated

form, can translocate to the nucleus to modulate gene expression that is usually

associated with promoting inflammation and antagonizing proliferation (Meraz et al.,

1996; Schindler et al., 2007). Although IFN-γ production was originally attributed to

helper T lymphocytes, it is now known that other immune cells can produce this

cytokine, including B cells, macrophages and microglia (Schroder et al., 2004). IFN-γ has

diverse effects on microglia. It can be anti-proliferative, and can induce antigen

presentation, apoptosis, production of reactive oxygen and nitrogen species, and

leukocyte attraction (Schroder et al., 2004). In vivo after ischemic stroke, various brain

cells contribute to production of IFN-γ, including astrocytes, macrophages, and microglia

(Hurn et al., 2007; Lambertsen et al., 2004; Lau and Yu, 2001; Yilmaz et al., 2006). It

can be released early after injury and orchestrate the ensuing neuro-inflammatory

response (Shohami et al., 1999). Knockout mouse studies suggest that IFN-γ exacerbates

ischemic injury (Lambertsen et al., 2004; Yilmaz et al., 2006).

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Tumor necrosis factor-alpha (TNF-α) is produced initially as a transmembrane protein

that can be cleaved by the matrix metalloprotease, TNF-α-converting enzyme (TACE), to

release soluble TNF-α (Olmos and Llado, 2014); both transmembrane and soluble TNF-α

can bind to TNF-α receptor 1 (TNFR1) or receptor 2 (TNFR2). TNFR1 contains an

intracellular death domain that binds to adaptor proteins recruited following ligand-

receptor binding, and activates nuclear factor-κB (NF-κB), p38 mitogen-activated protein

kinase (p38 MAPK), and activator protein 1 (AP-1), which mediate transcription of

inflammation-related genes (Carpentier et al., 1998; Chen and Goeddel, 2002;

Hallenbeck, 2002). TNF-α can bind to TNFR1 receptor with low affinity and can have

deleterious effects including cytotoxicity of oligodendrocytes, Schwann cells, and

primary neurons (Boyle et al., 2005; Perry et al., 1998; Selmaj and Raine, 1988). Several

studies have reported beneficial impacts of deleting TNFR1 or injecting an anti-TNFα

antibody in infection and CNS injury models (Bermpohl et al., 2007; Grau et al., 1987;

Iosif et al., 2006; Martin-Villalba et al., 2001). On the other hand, TNF-α can bind with

higher affinity to TNFR2 to mediate cytoprotective or homeostatic functions (Barna et

al., 1990; Cheng et al., 1994; Davidson et al., 1996; Liu et al., 1998; Shen et al., 1997).

Interestingly, TNFR2 preferentially binds to transmembrane TNF-α (Horiuchi et al.,

2010) Overall then, effects of TNF-α depend on the receptor type, and concentration of

soluble versus transmembrane TNF-α.

TNF-α levels increase after an acute injury like stroke (Gregersen et al., 2000; Haddad et

al., 2006; Lively and Schlichter, 2012) or traumatic brain injury (Shohami et al., 1994;

Taupin et al., 1993). Within the brain, microglia are major producers of TNF-α during

neuroinflammation (Hanisch, 2002; Kuno et al., 2005; Welser-Alves and Milner, 2013),

although neurons, astrocytes, and endothelial cells can also produce it (Buttini et al.,

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1996; Gregersen et al., 2000; Hofman et al., 1989; Lee et al., 1993; Liu et al., 1994;

Medana et al., 1997; Sawada et al., 1990; Seilhean et al., 1997; Uno et al., 1997). In vitro

and in vivo, TNF-α is produced in response to LPS, β-amyloid peptide (Aβ), IFN-γ, and

ATP (Hide et al., 2000; Meda et al., 1995; Sawada et al., 1989; Si et al., 2000; Yates et

al., 1999). In microglia, TNF-α expression can not only be induced by IFN-γ (Nguyen

and Benveniste, 2002) but the two cytokines can synergize to up-regulate iNOS

expression in mouse microglia (Mir et al., 2009; Mir et al., 2008). As well, TNF-α can

further potentiate TNF-α production in a positive feedback manner (Kuno et al., 2005).

Excess TNF-α levels cause cytotoxic effects, such as damaging oligodendrocytes (Selmaj

et al., 1991) and neurons (Sriram et al., 2002), and attenuating neurogenesis (Butovsky et

al., 2006); and several studies that disrupted TNF-α production or signalling showed

protection (Bermpohl et al., 2007; Meistrell et al., 1997; Nawashiro et al., 1997; Tobinick

et al., 2012; Yang et al., 2010).

Based on the literature and findings from the Schlichter lab, we selected the pro-

inflammatory cytokines, IFN-γ and TNF-α, to induce a pro-inflammatory or M1

activation state.

1.5.2. Anti-inflammatory or M2a cytokines

Interleukin-4 (IL-4) is primarily produced by mast cells, Th2 lymphocytes, eosinophils,

and basophils. Recently, IL-4 expression was found only in primary neuronal cultures

and not astrocytes, microglia or oligodendrocytes (Zhao et al., 2015). The effect of IL-4

signalling is mediated through the IL-4R α-chain (IL-4Rα). Upon binding to its ligand,

IL-4Rα can homodimerize with the γ-chain or heterodimerize with the IL-13Rα receptor.

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Upon activation, the homodimer receptor complex signals through Jak1 and Jak3, while

the heterodimer signals through Jak1 and Tyk2. Both signalling cascades regulate gene

transcription by phosphorylating and activating the transcription factor, STAT6, which

then dimerizes and translocates to the cell nucleus. A protective role of IL-4 was shown

in co-cultures of neurons and LPS-activated microglia, where inhibition of pro-

inflammatory cytokines such as TNF-α and nitric oxide was seen (Butovsky et al., 2006;

Chao et al., 1993). IL-4 treated microglia supported oligodendrogenesis in neural

progenitor cell co-cultures (Butovsky et al., 2006), and this could help in remyelination

after white matter damage. In an ischemic stroke model in mice, IL-4 expression was up-

regulated in the lesion (Zhao et al., 2015). IL-4 knockout mice had larger lesions and

worse inflammation than wildtype mice, and exogenous IL-4 injection in IL-4 KO mice

reduced most of the detrimental symptoms (Xiong et al., 2011), which illustrates its role

in limiting damage after injury. Furthermore, IL-4 injection improved functional recovery

after stroke in mice (Zhao et al., 2015). IL-4 has been suggested as a therapeutic agent in

studies that model neurological diseases, such as Alzheimer’s disease (Lyons et al., 2007)

and multiple sclerosis (Ponomarev et al., 2007), in addition to aforementioned stroke

studies (Xiong et al., 2011; Zhao et al., 2015).

1.5.3. Acquired deactivation or M2c cytokines

Interleukin-10 (IL-10) is considered an important anti-inflammatory cytokine (Sawada et

al., 1999). It binds to two receptors, IL-10R1 and IL-10R2, to activate intracellular

pathways involving Jak-STAT signalling (Ouyang et al., 2011). IL-10 receptors associate

with Jak1 and Tyk2 kinases that, when activated, promote translocation of the STAT3

transcription factor into the nucleus to affect gene expression. STAT3 is believed to

facilitate expression of anti-apoptotic and pro-survival genes (Schindler et al., 2007).

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Although STAT3 is the key downstream transcription factor, IL-10 can also involve

STAT1 (Meraz et al., 1996; Wehinger et al., 1996), perhaps modulating genes involved

in both pro- and anti-inflammatory responses. IL-10R is apparently expressed in

microglial cells around white matter tracts (Hulshof et al., 2002).

Microglia can express IL-10 after LPS stimulation in vitro or LPS injection in vivo

(Ledeboer et al., 2002; Park et al., 2007). Increased IL-10 expression was also observed

after stroke (Fouda et al., 2013; Lively and Schlichter, 2012) and traumatic brain injury

(Kamm et al., 2006). IL-10 is believed to reduce damage after brain injury. For instance,

IL-10 knockout mice exhibited larger necrotic areas after ischemic stroke compared to

wild type mice (Grilli et al., 2000), and IL-10 injection reduced the size of brain lesions

(Spera et al., 1998). Conversely, there are suggestions that IL-10 might impair wound

healing (Werner and Grose, 2003) and induce an M1-like inflammatory profile (Chhor et

al., 2013). Together, the published data suggest conflicting roles of IL-10 in

neuroinflammation.

1.6. Myelin phagocytosis

Microglia are considered professional phagocytes of the CNS. During brain development,

they clear apoptotic cell debris (Cunningham et al., 2013; Marin-Teva et al., 2004), and

in the healthy brain, they prune synaptic connections to refine neural circuits for

efficiency (Li et al., 2012; Paolicelli et al., 2011). However, the most well characterized

aspect of microglia phagocytic function is in the context of damage. There is direct

evidence in vivo that microglia can engulf dying/damaged neurons (Morsch et al., 2015).

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Acute injuries to the brain generate tissue debris. Debris removal by microglia

phagocytosis is considered beneficial for subsequent tissue repair (Neumann et al., 2009),

and phagocytic microglia can also release neurotrophic factors (Derecki et al., 2012;

Hosmane et al., 2012; Sierra et al., 2013; Tanaka et al., 2009). Myelin debris, which is

generated when there is white matter damage (Pantoni et al., 1996), inhibits axonal

sprouting (Gitik et al., 2011) and reduces oligodendrocyte differentiation, which delays

remyelination and repair (Kotter et al., 2005). Microglia can internalize myelin debris

(Williams et al., 1994) and to a greater degree than macrophages (Durafourt et al., 2012).

Improper myelin clearance due to a deficiency in CX3CR1 receptors on microglia

inhibited remyelination (Lampron et al., 2015). Thus, rapid removal of myelin is

important for establishing an environment beneficial for axon regeneration.

In a transient ischemic stroke model, the Schlichter lab demonstrated that

microglia/macrophages selectively infiltrate damaged myelin bundles (Moxon-Emre and

Schlichter, 2010). This was particularly interesting when comparing remyelination after

damage in young versus old animals. Younger animals were more effective in removing

myelin debris and in reparative remyelination; whereas, older animals had reduced

remyelination because of inefficient removal of myelin debris (Dubois-Dalcq et al., 2005;

Kotter et al., 2005; Neumann et al., 2009; Shields et al., 1999). Furthermore, in a model

of focal white matter demyelination, aged animals had delayed remyelination that was

attributed to impaired clearance of inhibitory myelin debris (Kotter et al., 2006; Ruckh et

al., 2012).

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1.6.1 Phagocytosis-related receptors

The process of phagocytosis can be divided into three stages: (i) receptor-mediated

recognition of a particle of interest; (ii) formation of a phagocytic cup around the particle

by extension of membrane, which involves cell volume changes and cytoskeleton

remodeling; and (iii) ingestion of the particle into a specialized organelle, the phagosome

(Sierra et al., 2013). Ligand recognition initiates an orchestrated progression of multiple

intracellular signalling mechanisms and cross-talk, which influences the actin

cytoskeleton to initiate phagocytosis (Freeman and Grinstein, 2014), and in which

intracellular Ca2+ signalling plays a pivotal role (Brechard and Tschirhart, 2008; Nunes

and Demaurex, 2010).

Microglia express an array of receptors involved in recognition and phagocytosis of

targets, including bacteria, apoptotic cell bodies, cell debris, and misfolded protein.

Receptors identified as involved in myelin phagocytosis include CR3, SRA and Fcγ

receptors (Smith, 2001). There is new evidence that the CX3CR1 receptor might also aid

in myelin clearance (Lampron et al., 2015).

Scavenger Receptor A (SRA/CD204) is considered a pattern recognition receptor that

recognizes a broad range of ligands, including bacterial cell wall components, beta-

amyloid particles, and apoptotic cells (Kelley et al., 2014). SRA is expressed in many cell

types, including macrophages and microglia. SRA expression was up-regulated in an

ischemic stroke model, and SRA depletion reduced the infarct size and improved

neurological function (Xu et al., 2012). This protective phenotype was associated with

reduced expression of M1 markers, like TNF-α, and increased expression of M2 markers,

like CD206. Similarly, in an ischemia-reperfusion model, SRA-KO mice had reduced

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infarct size and inflammatory response (Lu et al., 2010). This suggests that SRA

exacerbates brain injury by skewing the inflammatory response towards pro-

inflammation.

Complement receptor 3 (CR3; Mac-1; CD11b-CD18; αMβ2) is a common cell marker for

microglia and macrophages, and its expression is increased in activated cells after CNS

injury (Fu et al., 2014; Kettenmann et al., 2011; Schlichter et al., 2014; Taylor and

Sansing, 2013). CR3 is considered an opsonic receptor because it recognizes cells that are

tagged (opsonized) with the complement protein, C3b. Neurons that are opsonized by

C3b are phagocytosed by microglia (Linnartz et al., 2010; Schafer et al., 2012). Although

opsonization is not obligatory for CR3-mediated phagocytosis (e.g., of myelin),

complement mediated phagocytosis is more efficient (Rotshenker, 2003). Interestingly,

the CR3 receptor complex can both inhibit and augment myelin phagocytosis, depending

on its structure; i.e., αM augments phagocytosis while β2 inhibits it (Reichert et al., 2001).

Pro-inflammatory stimulation can enhance the ligand binding efficiency of CR3 receptor

(Caron et al., 2000).

Fcγ receptors are another class of opsonic receptors, which are well-characterized in the

phagocytosis literature. There are three isoforms: FcγRI, FcγRII, and FcγIII (Flannagan et

al., 2012), all of which recognize the Fc portion of immunoglobulin G (IgG) antibodies.

Hence, FcγR-mediated phagocytosis exclusively involves opsonized particles. The

cytosolic domain of most, but not all, FcγRs contains a signalling motif, called an

‘immunoreceptor tyrosine based activation motif’ (ITAM), which facilitates

phagocytosis. ITAM-containing receptors include FcγRIa and FcγRIIIa (CD16).

However, not all FcγRs stimulate phagocytosis, and the cytosolic portion of FcγRIIB

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(CD32) contains an ‘immunoreceptor tyrosine-based inhibition motif’ (ITIM), which

inhibits phagocytosis (Flannagan et al., 2012). Many studies use antibodies that recognize

both CD16 and 32 to label microglia/macrophages and indicate that they are in an M1

activation state (David, 2014; Hu et al., 2012) but opposite effects on phagocytosis might

be expected.

1.6.2. Phagocytosis and respiratory burst

Myelin phagocytosis induces a respiratory burst (RB) in microglia that generates reactive

oxygen species (ROS) (Williams et al., 1994), mediated by NOX enzyme activity (Liu et

al., 2006). The NOX family consists of NOX1-5, DUOX1 and DUOX2 (Bedard and

Krause, 2007; Brandes et al., 2014). These enzymes are responsible for production of

ROS in phagocytes, including microglia (Bedard and Krause, 2007; Brandes et al., 2014).

ROS can be cytotoxic because it can irreversibly damage DNA, lipids, and proteins.

Microglia express NOX1, NOX2 and NOX4, while NOX3 was not detected (Harrigan et

al., 2008). Among the subtypes, NOX2 is well-studied, and is largely responsible for the

phagocytosis-induced ROS production (respiratory burst) of microglia (Bedard and

Krause, 2007; Brandes et al., 2014) as well as other phagocytes (Flannagan et al., 2012).

NOX2 activation in microglia contributes to neuroinflammation and induces neuron

death under pathologic conditions (Jiang et al., 2015; Qin et al., 2013). It is important to

note that, under normal conditions, cells use ROS as a second messenger to modulate

signalling pathways (Bedard and Krause, 2007). For example, ROS signalling is required

for neuronal signalling, memory, and central homeostasis (Jiang et al., 2015 ). However,

over-production of ROS during RB causes oxidative stress to bystander cells and cell

death (Bedard and Krause, 2007; Brandes et al., 2014; Zhang et al., 2014).

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1.6.3 Phagocytosis and the microglial activation state

Microglia phagocytosis depends on receptor expression on the cell surface, and

phagocytosis specificity for a substrate depends on the receptor. In addition, particle

internalization depends on receptor dynamics and cellular expression levels. Hence, the

microglia phagocytosis capacity for a substrate depends on the type and level of receptor

expressed. It should be noted that many studies use plastic beads or other inorganic

materials to study microglia phagocytosis. However, one should be cautious about

conclusions of these studies because they do not represent physiologically relevant

substrates.

Regarding myelin phagocytosis, a couple of studies showed that microglia phagocytosis

depends on their activation state; however, the results were conflicting. LPS M1 activated

rat microglia exhibited increased phagocytosis of myelin (Smith et al., 1998). One study

showed that IL-4 stimulated M2 microglia had increased myelin phagocytosis (Durafourt

et al., 2012) but another showed no change (Smith et al., 1998). M2c-activation of rat

microglia with IL-10 increased myelin phagocytosis (Smith et al., 1998). Myelin is said

to induce an anti-inflammatory effect in microglia (Kroner et al., 2014; Liu et al., 2006)

but it was not known whether myelin phagocytosis affects induced activation states.

Lastly, it was not known how sequentially exposing microglia to M1- versus M2-

inducing cytokines affects their activation state, phagocytic capacity or RB. One focus of

my thesis is to evaluate the relationship between myelin phagocytosis, activation state,

and respiratory burst in microglia. In addition, I will assess the regulatory role of ion

channels in phagocytosis and respiratory burst.

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1.7. Migration and podosomes

Microglia migration to the site of injury is a crucial early response to most forms of CNS

injury. Microglia are highly dynamic in the mature CNS, constantly reshaping their

processes (Davalos et al., 2005; Li et al., 2012; Nimmerjahn et al., 2005; Tay et al., 2016;

Tremblay et al., 2010), even after death as observed in mice (Dibaj et al., 2010). Several

studies have focused on elucidating mechanisms regulating microglial cell migration and

process motility (Tremblay et al., 2011). Purinergic signalling via metabotropic P2Y12

receptors facilitate microglial process extension to laser injury in vivo (Davalos et al.,

2005; Haynes et al., 2006) as well as process remodeling in retinal explants (Fontainhas

et al., 2011). In damaged tissue, purinergic signalling could be activated by release of

ATP or UTP from necrotic cells into the brain parenchyma. These molecules are well-

established chemoattractants for microglia (Ferreira and Schlichter, 2013; Honda et al.,

2001), and have been used in the Schlichter lab. In vivo and ex vivo studies showed that

microglia acquire a migratory phenotype after activation due to injury (Carbonell et al.,

2005; Lee et al., 2008; Sieger et al., 2012). When studying how the microglial activation

state affects migration capacity, several reports showed that LPS-stimulated pro-

inflammatory microglia have markedly reduced migration (abd-el-Basset and Fedoroff,

1995; Broderick et al., 2000; De Simone et al., 2010). The Schlichter lab validated that

observation, and reported the novel findings that LPS-induced M1 microglia have

reduced invasion through Matrigel (basement membrane analog), and that IL-4

stimulated M2 microglia have markedly increased migration and invasion capacities

(Lively and Schlichter, 2013). That study showed that the changes in invasion capacity

depend on activity of different matrix degrading enzymes.

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For cells to traverse through tissue requires remodeling of the local extracellular matrix

(ECM). ECM surrounds cells, serves as “glue” that allows cells to adhere for anchorage,

and provides additional support to keep the cells bound together. Matrix degrading

enzymes, such as matrix metalloproteinases (MMPs), aid in ECM remodeling, and some

MMPs are up-regulated after brain injury (Heo et al., 1999; Romanic et al., 1998;

Wasserman et al., 2007). Migrating cells must also form new adhesions to substrate to

provide traction and mechanical force for locomotion (Alberts, 2008). Adhesion and

anchorage primarily depend on a class of molecules called integrins. Expressed on cell

surfaces, they comprise αβ heterodimers and are receptors for ECM molecules. Microglia

express various integrins, and activation stimuli change integrin expression (Milner and

Campbell, 2003). The Schlichter lab first reported (Vincent et al., 2012) the surprising

discovery that microglia can spontaneously express podosomes in vitro. These

microscopic structures contribute to both matrix remodeling and traction (Linder et al.,

2011; Murphy and Courtneidge, 2011). Podosomes are protrusive, adhesive, F-actin-rich

microscopic structures constitutively expressed in cultured monocytic-lineage cells; e.g.

osteoclasts (Marchisio et al., 1984) and macrophages (Amato et al., 1983). Podosome

structures have also been discovered in 3D cultures of macrophages in vitro (Cougoule et

al., 2010; Rottiers et al., 2009). They exhibit features such as: (i) integrin-mediated

attachment to ECM to provide anchorage and traction; (ii) fast turnover to allow for quick

assembly and disassembly (maturation process) during fast migration; and (iii) matrix

degrading enzymes that facilitate localized ECM degradation for invasion. Microglial

podosomes organize into large donut-shaped superstructures that we have termed

‘podonuts’. The Schlichter lab showed that podosomes can degrade the ECM molecule,

fibronectin; i.e., microglia express podosomes that have degradation functionality.

Further characterization showed that disrupting these structures decreased microglia

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migration and invasion (Siddiqui et al., 2012). Because microglia migration and invasion

depend on podosomes and the cell activation state, we hypothesized that expression of

podosomes correlates with the microglial activation state. Understanding how the

activation state is related to migration phenotype and associated regulatory mechanisms

could aid in developing therapeutic measures that target microglia and brain

inflammation.

1.8. Ion channels in microglia

Cell migration is the result of a complex interplay comprising adhesion at leading edge,

detachment at trailing edge, and matrix remodeling, and intracellular signalling pathways

that regulate cytoskeletal rearrangements (e.g. protein tyrosine kinases) (Alberts, 2008;

Ridley et al., 2003). Ion channels also play an important role in cell migration by

influencing the actin cytoskeleton and cell volume changes (Schwab et al., 2012).

Microglia express a wide variety of ion channels that include H+ channels, Na+ channels,

Ca2+-release-activated Ca2+ channels, Cl− channels, K+ channels and non-selective cation

channels from the TRP family (Echeverry et al., 2016; Eder, 2005; Stebbing et al., 2015).

In microglia, ion channels regulate many functions and hence have been proposed as

therapeutic targets in neurological diseases (Skaper, 2011). The focus of this thesis will

be on three K+ channels (Kv1.3, SK3, SK4), store-operated Ca2+-release-activated Ca2+

channels, and the non-selective cation channel, TRPM7.

1.8.1. Ca2+-permeable channels

CNS expression of the calcium-permeable, non-selective cation channel, Transient

Receptor Potential Melastatin 7 (TRPM7) was first discovered in the Schlichter lab, who

found it in microglia (Jiang et al., 2003). This channel is strongly outward rectifying at

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depolarized membrane potentials (Kerschbaum et al., 2003); however, under

physiological conditions, it predominantly carries the divalent cations, Ca2+ and Mg2+

(Penner and Fleig, 2007). TRPM7 channels are unique in having a functional C-terminal

serine/threonine protein kinase domain, and it is sometimes referred to as a “chanzyme”

(Visser et al., 2014). TRPM7 channels are regulated by a number of factors that include

PLC signalling and PIP2 levels, mechanical stretch of the membrane, growth factors

(Abed and Moreau, 2009; Wei et al., 2009), pH (Jiang et al., 2005; Li et al., 2007), and

ROS (Aarts et al., 2003). Functionally, the channel plays an important role in cellular

magnesium homeostasis, proliferation, and migration (Fleig and Chubanov, 2014; Visser

et al., 2014). However, in microglia, very little is known regarding TRPM7 channel

regulation, function or expression in different activation states. The Schlichter lab

reported that TRPM7 channels are constitutively active, and the current density is

modulated through tyrosine phosphorylation (Jiang et al., 2003). Further characterization

showed that Src tyrosine kinase contributes to channel function. Many microglia

functions involve Ca2+ signalling, including migration, proliferation, phagocytosis, and

the production of nitric oxide, cytokines, chemokines and interleukins (Farber and

Kettenmann, 2006). TRPM7 is a calcium-permeable channel, and its activation might

thus be important for microglial functions and requires further investigation. Studying

TRPM7 by inhibiting its expression or function is difficult because it is essential for

embryonic development, and its global deletion in mice results in embryonic lethality (Jin

et al., 2008; Ryazanova et al., 2010). Furthermore, there is no commercially available

selective inhibitor to target TRPM7, even though a selective blocker was developed in

2011 (Zierler et al., 2011).

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The Schlichter lab first showed that store-operated Ca2+ entry (SOCE) supplies

intracellular Ca2+ in microglia via Orai1/CRAC channels (Ohana et al., 2009). CRAC

channels are comprised of pore-forming Orai1 subunit and the ER-resident Ca2+-sensor

STIM1 molecule (Soboloff et al., 2012), which together form an inward-rectifying,

highly selective Ca2+ channel (Prakriya and Lewis, 2015). CRAC channels are considered

to be store-operated because they are activated by signals that deplete ER luminal Ca2+.

For example, CRAC can be activated by P2Y6 receptor simulation or other G protein-

coupled metabotropic receptors (Heo et al., 2015; Koizumi et al., 2007; Michaelis et al.,

2015). Rodent microglia express mRNA for Orai1, Orai2, Orai3, STIM1 and STIM2

(Heo et al., 2015; Michaelis et al., 2015; Ohana et al., 2009). All three Orai homologs

produce Ca2+-selective store-operated channels with differing biophysical characteristics

but Orai1 is the best characterized.

In rat microglia, we found that podosomes co-localize with Orai1 molecules (Siddiqui et

al., 2012). Inhibition of Orai1/CRAC channels with BTP2 reduced podosome expression,

which, in turn, attenuated microglia migration and invasion. There are few reports

regarding changes in Ca2+ signalling and expression of relevant Ca2+-signalling

molecules in specific microglial activation states; and the results are somewhat

inconsistent. Murine microglia activated with LPS (M1 activation) had increased

expression of STIM1 and unchanged Orai1 and Orai3 in one study (Heo et al., 2015), but

reduced STIM1 and Orai3 and unchanged Orai1 and STIM2 in another (Michaelis et al.,

2015). While Orai1 expression was not changed in either study, SOCE was reduced. For

rat microglia, we recently found that the CRAC-mediated Ca2+ rise was ~50% lower after

IL-4 treatment (M2a activation) but not affected by IL-10 treatment (M2c activation)

(Lam and Schlichter, 2015). More recent evidence suggests that Ca2+ entry via SOCE

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facilitates cytokine secretion, as well as UDP-induced phagocytosis and chemotaxis (Heo

et al., 2015; Michaelis et al., 2015). Because other Ca2+-permeable channels in microglia

are non-selective (Echeverry et al., 2016; Kettenmann et al., 2011; Stebbing et al., 2015),

CRAC channels are important in providing a highly selective route for Ca2+ influx to

modulate cellular signalling and functions. Thus, it was important to further study the

relationship between CRAC channels and microglia in different activation states, and this

was part of my thesis work.

1.8.2. Kv1.3 and Kir2.1 channels

K+ channels are the most studied channels in microglia. The two first-characterized K+

channels were the outward-rectifier, voltage-gated Kv1.3 channel and inward-rectifier

Kir2.1 channel (Richardson and Hossain, 2013). Kir2.1 channels are thought to maintain

a hyperpolarized membrane potential (Hibino et al., 2010), and both channels can

produce membrane potential oscillations in rat microglia (Newell and Schlichter, 2005),

while Kv1.3 channels hyperpolarizes the membrane potential. Kv1.3 expression is up-

regulated in LPS-activated microglia (Fordyce et al., 2005; Schilling and Eder, 2007).

Results on Kir2.1 expression are inconsistent, with pro-inflammatory stimuli increasing it

in murine microglia (Boucsein et al., 2003; Draheim et al., 1999; Prinz et al., 1999) but

decreasing it in rat microglia (Norenberg et al., 1992; Schlichter et al., 1996; Visentin et

al., 1995). More recently, the Schlichter lab found that the anti-inflammatory stimuli, IL-

4 and IL-10, did not change the Kir2.1 current in rat microglia (Lam and Schlichter,

2015).

In vivo, Alzheimer's patients exhibited increased expression of Kv1.3 in microglia

(Rangaraju et al., 2015), while in the MCAO stroke model, Kir2.1 and Kv1.3 currents

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were detected in isolated mouse microglia (Chen et al., 2015c). These channels can

regulate various microglia functions. Both Kir2.1 and Kv1.3 are associated with

microglial proliferation (Kotecha and Schlichter, 1999; Lam and Schlichter, 2015;

Pannasch et al., 2006; Schlichter et al., 1996). The Schlichter lab found that, in rat

microglia, blocking Kv1.3 channels with agitoxin-2 reduced the respiratory burst

(Fordyce et al., 2005; Khanna et al., 2001), and that blocking Kir2.1 with ML133

increased proliferation, reduced migration, and influenced the Ca2+ dynamics (Lam and

Schlichter, 2015).

1.8.3. Ca2+-activated K+ channels

The Ca2+-activated K+ channels, SK1-SK4 are gated by Ca2+-calmodulin (CaM) and are

sensitive to changes in the intracellular Ca2+ concentration. Microglia express SK3 and

SK4, little SK1, and negligible SK2 (Kaushal et al., 2007; Schlichter et al., 2010). SK

channels link changes in intracellular calcium to changes in membrane potential

(Pedarzani and Stocker, 2008). In non-excitable cells, like microglia, SK channels have

the potential role of maintaining the driving force for Ca2+ influx by hyperpolarizing the

cell membrane (Kaushal et al., 2007; Potier et al., 2006; Schlichter et al., 2010). KCa2.3

expression increased in LPS-activated rat microglia, and blocking KCa2.3 channels with

apamin or tamapin reduced microglial activation and NO production, which is neurotoxic

(Schlichter et al., 2010). KCa2.3 channels likely maintain an electrical driving force for

Ca2+ entry, perhaps through Orai1/CRAC channels (Schlichter et al., 2010). In vivo,

KCa2.3 channels were prominently expressed on the surface of activated

microglia/macrophages in rat models of hemorrhagic or ischemic strokes (Schlichter et

al., 2010).

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Several groups, including ours, have shown that KCa3.1 channels contribute to microglial

activation and microglia-mediated neurotoxicity (Chen et al., 2011; Kaushal et al., 2007;

Maezawa et al., 2012). KCa3.1 channels also play a key role in cell migration (Schwab et

al., 2012), and KCa3.1 expression increased in IL-4 stimulated, anti-inflammatory rat

microglia, which show increased migration (Ferreira et al., 2014). KCa3.1 inhibition with

clotrimazole or the more selective blocker, TRAM-34, reduced microglia migration

(Ferreira et al., 2014; Schilling et al., 2004). In vivo, mouse microglia isolated from the

infarcted area after MCAO had larger KCa3.1 currents than microglia from non-infarcted

control brains (Chen et al., 2015c). When KCa3.1 was deleted or blocked with TRAM-

34, the animals had smaller infarcts, as well as reduced microglia/macrophage activation,

and pro-inflammatory and anti-inflammatory cytokine production.

1.9. Project rationales and hypotheses

The Schlichter lab has been studying microglia physiology for two decades. A major

aspect of the studies involves culturing primary rat microglial cells. The isolation

protocol produces a >99% purity of microglia (Kaushal et al., 2007; Ohana et al., 2009;

Sivagnanam et al., 2010), and the lab has shown (based on mRNA expression and

functional assays) that our culturing methods result in microglia being in a relatively

resting, but migratory state (Sivagnanam et al., 2010; Vincent et al., 2012). We do our

studies in primary microglia cells rather than cell lines, unlike many other labs, because

they more closely reflect in vivo microglia. For my research project, to induce different

activation states, cultured microglia were treated with: (i) tumor necrosis factor alpha

(TNFα) and interferon gamma (IFNγ) to induce classical activation, (ii) interleukin-4 (IL-

4) to induce alternative activation, or (iii) interleukin-10 (IL-10) to induce a deactivated

state. IFN-γ and TNF-α are pro-inflammatory cytokines that are released by microglia,

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damaged cells and infiltrating macrophages at the site of injury after events such as stroke

or trauma (Kettenmann et al., 2011; Lively and Schlichter, 2012). We avoid using

lipopolysaccharide (LPS), which is commonly used to induce classical activation

(Hanisch and Kettenmann, 2007; Kettenmann et al., 2011), and is derived from cell walls

of Gram-negative bacteria. While effective and convenient, LPS treatment does not

represent acute brain injury but rather models bacterial infection of the brain.

Project 1. To assess the contribution of Ca2+-activated K+ channels to

podosomes, migration and invasion

The Schlichter lab (another MSc student and I) discovered that microglia in vitro

spontaneously express podosomes (Vincent et al., 2012). In a second study (Siddiqui et

al., 2012), we reported novel findings regarding podosomes: (i) podosomes required Ca2+

influx through podosome-associated CRAC channels, (ii) podosomes play a role in

microglia migration and invasion, and (iii) novel podosome components, including Ca2+-

activated SK3 and CRAC (Orai1+STIM1) channels. The Schlichter lab also found that

microglial migration and invasion depends on their activation state (Lively and

Schlichter, 2013). Migration and invasion were significantly reduced in pro-inflammatory

M1 microglia but markedly higher in anti-inflammatory M2a microglia and was

dependent on activity of matrix degrading enzymes including MMPs that are known to

associate with podosomes. [To date, no other lab has investigated the relationship

between microglia podosomes, migration and invasion.] We hypothesized that M2-

activated microglia would have increased podosome expression to account for their

increased migration and invasion capacity, and that KCa2.3 channels would regulate

podosome expression to influence microglia migration and invasion.

- 26 -

Project 2. To evaluate relationships between microglial activation states,

myelin phagocytosis and respiratory burst, and contributions of ion

channels

In characterizing white matter damage after transient ischemic stroke in rats, the

Schlichter lab found that axonal damage, which occurs over a period of 7 days, correlated

with accumulation of activated microglia/macrophages. Furthermore, axon bundles that

contained damaged myelin were infiltrated by phagocytic microglia/macrophages while

undamaged bundles were not (Moxon-Emre and Schlichter, 2010). Microglia can

phagocytose myelin debris and produce excess ROS, and limited studies suggested that

their phagocytic capacity depends on their activation state (Smith et al., 1998). However,

that study and others used a single stimulus to evoke one activation state; whereas, in

vivo studies show that microglia/macrophage polarization after injury changes between

M1 and M2 (Hu et al., 2012; Miron et al., 2013; Perego et al., 2011; Suenaga et al., 2015;

Wan et al., 2016; Wang et al., 2013; Yang et al., 2016). Probing microglia-specific

functions in vivo is very difficult because they cannot be easily distinguished from

infiltrating macrophages. Hence, to study microglia responses, I applied several

activation paradigms, with or without myelin debris. Little is known about regulatory

mechanisms that modulate myelin phagocytosis in microglia, and our lab is especially

interested in roles of several ion channels. Previously, our lab found that Cl- channels can

influence E. Coli phagocytosis by microglia (Ducharme et al., 2007), and recently,

CRAC channels were found to facilitate phagocytosis of beads but required UDP

stimulation (Heo et al., 2015; Michaelis et al., 2015). I tested the hypothesis that several

ion channels contribute to myelin phagocytosis and respiratory burst.

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Chapter 2. General Methods

2.1 Microglia cell cultures

Giulian and Baker (1986) (Giulian and Baker, 1986) were the first to develop isolation

and culturing protocols for microglia. The Schlichter lab published its first microglia

paper in 1996, and since then has refined the protocol such that after isolation, neonatal

rat microglia remain in a relatively resting state, as judged by very low expression of

many inflammatory mediators (Liu et al., 2013; Lively and Schlichter, 2013; Sivagnanam

et al., 2010). Isolation of rat microglia was done by either Xiaoping Zhu or Raymond

Wong following standard protocols as described previously (Ferreira et al., 2014; Lively

and Schlichter, 2013; Ohana et al., 2009; Siddiqui et al., 2012; Sivagnanam et al., 2010).

Briefly, primary microglia cultures were derived from 1 to 2 day old Sprague-Dawley rat

pups. After removing the meninges, the brain was dissected and mashed through a

stainless steel sieve in Minimum Essential Medium (MEM; Invitrogen, Burlington,

Canada), and then centrifuged at 1000 g for 10 min. The supernatant was removed and

the pellet was re-suspended in MEM supplemented with 10% fetal bovine serum (FBS;

Wisent, St-Bruno, Canada) and 0.05 mg/ml gentamycin (Invitrogen), and plated on flasks

to maintain at 37ºC, 5% CO2 atmosphere. After 48 hr, cellular debris, non-adherent cells

and supernatant were removed and fresh medium was added. The mixed cell cultures

were then maintained for another 5 to 6 days. Microglial suspensions were then obtained

by shaking the mixed cultures on an orbital shaker for 3-4 hours in 37ºC at 60 to 65 rpm.

The suspension containing microglial cells was then centrifuged for 10 min at 1000 g and

the cell pellet was re-suspended in MEM supplemented with 2% FBS and 100 µM

gentamycin. Microglia were seeded onto 96-well tissue culture plates at 7–8 × 104

cells/well (for phagocytosis and ROS assays), 7–8 × 104 cells/15 mm coverslip (for

- 28 -

fluorescence microscopy), and >105 cells/coverslip (for mRNA collection)., incubated in

the 2% FBS supplemented MEM at 37ºC, 5% CO2, and used within 24 to 48 hr.

The MLS-9 cell line was derived in our laboratory after treating primary rat microglia

with colony-stimulating factor-1 for several weeks (Zhou et al., 1998). Cells were thawed

and cultured for several days in medium (MEM, 10% FBS, 100 µM gentamycin), and

then harvested in phosphate buffered saline (PBS) containing 0.25% trypsin and 1 mM

EDTA, washed with MEM, centrifuged (300×g, 10 min) and re-suspended in culture

medium. There are several advantages of using MLS-9 cells for studying KCa and

TRPM7 currents. They lack two interfering K+ currents – inward-rectifier (Kir2.1) and

Kv1.3 (Newell and Schlichter, 2005; Schlichter et al., 1996) – and they have large

KCa2.3 (Liu et al., 2013) and TRPM7 currents (see Chapter 3).

2.2. Chemicals and antibodies

To induce different activation states, microglia were exposed to recombinant rat

cytokines (R&D Systems Inc., Minneapolis, MN). A classical (M1) state was induced by

20 ng/mL IFN-γ plus 50 ng/mL TNF-α (for 24 h): a treatment we refer to as “I + T”.

Alternative activation (M2a) was induced by 20 ng/mL IL-4 (for 24 h). Acquired

deactivation (M2c) was induced with 20 ng/mL IL-10 (for 24 h). All cytokines from

R&D Systems Inc., Minneapolis, MN. Stock solutions were made in sterile PBS with 0.3

% bovine serum albumin and stored at –20 °C. For sequential cytokine additions, the first

treatment (IL-4 or I + T) was applied for 2 h, and then, the second (IL-4, I + T, IL-10) was

added for an additional 22 h without washing. Several channel inhibitors were used to

assess contributions of ion channels. Kv1.3 was blocked with agitoxin-2 (AgTx; IC50=0.2

nM) (Kotecha and Schlichter, 1999) (Sigma-Aldrich, Oakville, ON, Canada) as before

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(Cayabyab et al., 2000; Newell and Schlichter, 2005). CRAC channels were blocked with

N-[4-[3,5-bis(trifluoromethyl)-1H-pyrazol-1-yl]phenyl]-4-methyl-1,2,3-thiadiazole-5-

carboxamide (BTP2; IC50=10-500 nM; (Prakriya and Lewis) (EMD Millipore, San

Diego, CA). We previously showed that 10 μM BTP2 blocks Ca2+ signalling through

CRAC (Ferreira and Schlichter, 2013; Lam and Schlichter, 2015). Kir2.1 was blocked

with N-[(4-methoxyphenyl)methyl]-1-naphthalene-methanamine hydrochloride (ML133;

IC50=3.5 µM) (Tocris Bioscience, MO) as in our recent study (Lam and Schlichter,

2015). KCa3.1 (also known as IK1, SK4) was blocked with 1-[(2-chlorophenyl)

diphenylmethyl]-1H-pyrazole (TRAM-34; IC50=20 nM) (Pedarzani and Stocker, 2008)

(Sigma) as before (Ferreira et al., 2014; Ferreira and Schlichter, 2013; Wong and

Schlichter, 2014). Apamin (Sigma) is a well-known pore blocker of KCa2.3 channels

(and KCa2.1 and 2.2) at higher doses (IC50 = 4 nM) but only KCa2.1 and 2.2 at lower

doses (IC50 = 704 pM and 27 pM, respectively)(Pedarzani and Stocker, 2008). Similarly,

tamapin (Alamone Labs, Jerusalem, Israel) is a potent pore blocker of KCa2.3 (and

KCa2.2) channels at higher concentrations (IC50 = 1.7 nM) but only KCa2.2 at lower

concentrations (IC50 = 24 pM) (Pedarzani and Stocker, 2008). NS8593 (Sigma-Aldrich)

was developed as a negative gating modulator (inhibitor) of KCa2.1, KCa2.2 and KCa2.3

channels, and is effective at sub-micromolar levels with physiologically relevant

intracellular Ca2+ concentrations (Strobaek et al., 2006). However, NS8593 was found to

block cloned TRPM7 channels (Chubanov et al., 2012). AA-861 (Sigma) is a 5-

lipooxygenase inhibitor that was reported to effectively inhibit TRPM7 channels (Chen et

al., 2010). Stock solutions were prepared in sterile double distilled water (agitoxin-2,

apamin, tamapin), ethanol (AA-861), or DMSO (TRAM-34, ML133, BTP2). For all

channel inhibitors, aliquots were stored at −20°C.

- 30 -

2.3. Immunocytochemistry (ICC)

Cover slips bearing microglia were fixed in 4% paraformaldehyde (PFA) (Electron

Microscopy Sciences, Hatfield, PA) in PBS for 10 to 15 min at room temperature, and

then permeabilized for 5 min with 0.2% Triton X-100. To block non-specific staining,

cells were incubated in blocking solution (4% donkey serum in PBS; Jackson

Immunoresearch, West Grove, PA) for 1 hr at room temperature. The blocking solution

was replaced and the cells were then incubated overnight at 4ºC with a primary antibody

in blocking solution. After another 1 hr of blocking, a secondary donkey antibody in

blocking solution (conjugated to Dylight 488 or Dylight 594; 1:250; Jackson

Immunoresearch) was added to label the corresponding primary antibody, and incubated

for 1 hr at room temperature in the dark. F-actin was visualized by incubating cells with

Alexa 488-conjugated phalloidin (1:50 in block solution, Invitrogen) for 15 min at room

temperature in the dark. Cell nuclei were stained by incubating with 4',6-diamidino-2-

phenylindole (DAPI; 1:3000 in PBS) for 5 min. Cover slips were mounted on glass slides

with mounting medium (Dako, Glostrup, Denmark) for viewing using epifluorescence

widefield microscopy. Negative controls were prepared for each ICC preparation using

the aforementioned protocol, except that primary antibodies were omitted. Before use,

antibodies in blocking solution were centrifuged at 10,000 rpm for 10 min to remove any

aggregates that might bind non-specifically and introduce artefacts.

Microglia were imaged with a Zeiss Axioplan 2 widefield epifluorescence microscope

(Zeiss, Toronto, ON) equipped with a Zeiss Axiocam HR digital camera.

- 31 -

2.4. Nanostring and qRT-PCR

Gene expression studies using nanostring or qRT-PCR were performed by Starlee Lively

or Xiaoping Zhu, respectively. Total RNA was extracted using TRIzol reagent

(Invitrogen), and an RNeasy Mini Kit (QIAGEN, Mississauga, ON, Canada), as in our

recent studies (Liu et al., 2013; Lively and Schlichter, 2013; Sivagnanam et al., 2010).

RNA samples were stored at –80ºC. Multiplexed gene expression analysis (NanoString

nCounter™). This high-throughput method was used to analyze molecular markers of

microglial activation, matrix degrading enzymes, phagocyte-related receptors and other

molecules of particular interest (e.g., the KCNN3/KCa2.3 channel). Each gene (Tables 1

and 2) was recognized by a probe set (consisting of a capture probe and a reporter probe)

that was designed and synthesized by NanoString nCounter™ technologies. Extracted

RNA (200 ng) was sent to the Princess Margaret Genomics Centre

(http://www.pmgenomics.ca; Toronto, Canada), where the sample purity was assessed

(using Nanodrop 1000) before conducting the assay (hybridization, detection, scanning)

according to the manufacturer’s instructions. Background subtraction and normalization

of RNA counts were conducted using NanoString nCounter™ digital analyzer software

(http://www.nanostring.com/support/ncounter/). Gene expression was normalized to the

housekeeping gene, hypoxanthine guanine phosphoribosyl transferase (HPRT1) for

Chapter 3 or three housekeeping genes: hypoxanthine guanine phosphoribosyl transferase

1 (HPRT1), β-glucuronidase (GusB), and 60S ribosomal protein L32 (Rpl32) for Chapter

4. Quantitative real-time reverse-transcriptase polymerase chain reaction (qRT-PCR).

RNA samples were reverse transcribed using SuperScript II reverse transcriptase,

according to the manufacturer’s instructions (Invitrogen). The following primers for

TRPM7 and the housekeeping gene, HPRT1, were designed using ‘Primer3Output’

(http://bioinfo.ut.ee/primer3-0.4.0). TRPM7: forward (5’- AGGGCAGTGGTTTGCTGT-

- 32 -

3’) and reverse (5’- CAGGGCCAAAAACCATGT-3’). HPRT1: forward (5’-

CAGTACAGCCCCAAAATGGT-3’) and reverse (5’-

CAAGGGCATATCCAACAACA-3’). cDNA was amplified using an ABI PRISM 7700

Sequence Detection System (PE Biosystems, Foster City, CA, USA) as follows: 50°C for

2 min, 95°C for 10 min, 40 cycles at 95°C for 15 sec, and 60°C for 60 sec; followed by a

dissociation step (95°C for 15 sec, 60°C for 15 sec, 95°C for 15 sec). ‘No-template’ and

‘no-amplification’ controls were included for both genes, and single peaks on the melting

curves confirmed the specific amplification of each gene. The threshold cycle (CT) for

TRPM7 was normalized to that of HPRT1 before analyzing and comparing gene

expression.

- 33 -

Table 1. Target sequences for NanoString nCounter analysis in Chapter 3.

Gene Genbank Accession

Target Sequence

Arg1 NM_017134.2 ACGGGAAGGTAATCATAAGCCAGAGACTGACTACCTTAAACCACCGAAATAAATGTGAATACATCGCATAAAAGTCATCTGGGGCATCACAGCAAACCGA

Ctsb NM_022597.2 GTCTGGGAAAAACCTGCTTTTTTGTTGTAGGTGCCACGTAACCCTGTCAGTTTAACAAGGAATGACCGTGCCAATAAACCAATTCTCCCTCTGCTTGAAA

Ctsd NM_134334.2 GACACTGTGTCGGTTCCATGTAAGTCAGACTTAGGAGGTATCAAGGTGGAGAAACAGATCTTTGGGGAAGCCACCAAGCAGCCTGGAGTCGTATTCATCG

Ctsk NM_031560.2 AGCAGGCTGGAGGACTAAGGTGACCTTCCCAAGCCCCTGTCTTCTATATACACCAGTGCAGATTTCAGTCTTCCACTGAGATGCACAAATCTATTCATGA

CtsL1 NM_013156.1 GTGGGGCCTATTTCTGTTGCCATGGATGCAAGCCATCCGTCTCTCCAGTTCTATAGTTCAGGTATCTACTATGAACCCAACTGTAGCAGCAAGGACCTCG

Ctss NM_017320.1 GATTGCTCAACCGAAGAAAAGTACGGGAATAAAGGCTGCGGGGGTGGCTTCATGACCGAAGCTTTCCAGTACATCATCGATACGAGCATCGACTCAGAAG

Itgam/CD11b

NM_012711.1 CATCCCTTCCTTCAACAGTAAAGAAATATTCAACGTCACCCTCCAGGGCAATCTGCTATTTGACTGGTACATCGAGACTTCTCATGACCACCTCCTGCTT

CD163 NM_001107887.1 AGTTTCCTCAAGAGGAGAGGTCTTGATACATCAAGTTCAGTACCAAGAGATGGATTCGAAGACGGATGATCTGGACTTGCTGAAATCCTCGGGTTGGCAT

c-myc NM_012603.2 ACCGAGGAAAACGACAAGAGGCGGACACACAACGTCTTGGAACGTCAGAGGAGAAACGAGCTGAAGCGTAGCTTTTTTGCCCTGCGCGACCAGATCCCTG

CD68/ ED1

NM_001031638.1 CTCTCATTCCCTTACGGACAGCTTACCTTTGGATTCAAACAGGACCGACATCAGAGCCACAGTACAGTCTACCTTAACTACATGGCAGTGGAATACAATG

Hpse NM_022605.1 CTTGAATGGACGAGTTGCGACCAAAGAAGATTTTCTGAGCTCTGATGTCCTGGACACTTTTATCCTATCTGTGCAAAAAATTCTGAAGGTGACTAAGGAG

HO-1/ Hsp32

NM_012580.2 CTAGTTCATCCCAGACACCGCTCCTGCGATGGGTCCTCACACTCAGTTTCCTGTTGGCGACCGTGGCAGTGGGAATTTATGCCATGTAAATGCAGTGTTG

Il1b NM_031512.1 TGCACTGCAGGCTTCGAGATGAACAACAAAAATGCCTCGTGCTGTCTGACCCATGTGAGCTGAAAGCTCTCCACCTCAATGGACAGAACATAAGCCAACA

Il1rn/ Il1ra

NM_022194.2 TCATTGCTGGGTACTTACAAGGACCAAATACCAAACTAGAAGAAAAGATAGACATGGTGCCTATTGACTTTCGGAATGTGTTCTTGGGCATCCACGGGGG

Il6 NM_012589.1 GGAACAGCTATGAAGTTTCTCTCCGCAAGAGACTTCCAGCCAGTTGCCTTCTTGGGACTGATGTTGTTGACAGCCACTGCCTTCCCTACTTCACAAGTCC

Nos2/ iNOS

NM_012611.2 ACGGGACACAGTGTCGCTGGTTTGAAACTTCTCAGCCACCTTGGTGAGGGGACTGGACTTTTAGAGACGCTTCTGAGGTTCCTCAGGCTTGGGTCTTGTT

Mmp2 NM_031054.2 CTTTTTTGTGCCCAAAGAAAGGTGCTGACCGTATCCCTCCCAGGTGCTACTTTCTCCCGCCCACCCAAGGGGATGCTTGGATATTCACAATGCAGCCCTC

Mmp9 NM_031055.1 TGCGTCGGGCGCTGCTCCAACTGCTGTATAAATATTAAGGTATTCAGTTACTCCTACTGGAAGGTATTATGTAACCATTTCTCTCTTACATCGGAGGACA

- 34 -

Mmp12 NM_053963.1 AGGCACAAACCTGTTCCTTGTTGCTGTTCATGAGCTTGGCCATTCCTTGGGGCTGCGGCATTCCAATAATCCAAAATCAATAATGTACCCTACCTACAGA

Mmp14 NM_031056.1 GTTCCAGATAAGTTTGGGACTGAGATCAAGGCCAATGTTCGGAGGAAGCGCTATGCCATTCAGGGCCTCAAGTGGCAGCATAATGAGATCACTTTCTGCA

Mrc1 NM_001106123.1 CTTTGGAATCAAGGGCACAGAGCTATATTTTAACTATGGCAACAGGCAAGAAAAGAATATCAAGCTTTACAAAGGTTCCGGTTTGTGGAGCAGATGGAAG

Nfe2l2/Nrf2

NM_031789.1 ATACAACAAAAAAAGAAGTACCTGTGAGTCCTGGTCATCAAAAAGTCCCATTCACAAAAGACAAACATTCAAGCCGATTAGAGGCTCATCTCACAAGAGA

Stat6 NM_001044250.1 GTGGTTTGATGGTGTCCTGGACCTCACTAAACGCTGTCTTCGGAGCTACTGGTCAGATCGGCTGATCATCGGCTTTATCAGTAAGCAATATGTCACTAGC

Tgfb1 NM_021578.2 CGCCTGCAGAGATTCAAGTCAACTGTGGAGCAACACGTAGAACTCTACCAGAAATATAGCAACAATTCCTGGCGTTACCTTGGTAACCGGCTGCTGACCC

Timp1 NM_053819.1 CATCGAGACCACCTTATACCAGCGTTATGAGATCAAGATGACTAAGATGCTCAAAGGATTCGACGCTGTGGGAAATGCCACAGGTTTCCGGTTCGCCTAC

Tlr2 NM_198769.2 TTTACAAACCCTTAGGGTAGGAAATGTTGACACTTTCAGTGAGATAAGGAGAATAGATTTTGCTGGGCTGACCTCTCTCAACGAACTTGAAATTCAGGTA

Tlr4 NM_019178.1 GTCAGTGTGCTTGTGGTAGCCACTGTAGCATTTCTGATATACCACTTCTATTTTCACCTGATACTTATTGCTGGCTGTAAAAAGTACAGCAGAGGAGAAA

Tnf NM_012675.2 GGTGATCGGTCCCAACAAGGAGGAGAAGTTCCCAAATGGGCTCCCTCTCATCAGTTCCATGGCCCAGACCCTCACACTCAGATCATCTTCTCAAAACTCG

- 35 -

Table 2. Target sequences for NanoString nCounter analysis in Chapter 4.

Gene Genbank Accession

Target sequence

Aif1 (Iba1)

NM_017196.2 ATCGATATTATGTCCTTGAAGCGAATGCTGGAGAAACTTGGGGTTCCCAAGACCCATCTAGAGCTGAAGAAATTAATTAGAGAGGTGTCCAGTGGCTCCG

Ccl22 NM_057203.1 TACATCCGTCACCCTCTGCCACCACGTTTCGTGAAGGAGTTCTACTGGACCTCAAAGTCCTGCCGCAAGCCTGGCGTCGTTTTGATAACCATCAAGAACC

Cd11b (Itgam)

NM_012711.1 CATCCCTTCCTTCAACAGTAAAGAAATATTCAACGTCACCCTCCAGGGCAATCTGCTATTTGACTGGTACATCGAGACTTCTCATGACCACCTCCTGCTT

Cd68 (ED1)

NM_001031638.1 CTCTCATTCCCTTACGGACAGCTTACCTTTGGATTCAAACAGGACCGACATCAGAGCCACAGTACAGTCTACCTTAACTACATGGCAGTGGAATACAATG

Cd163 NM_001107887.1 CCTCTGTAATTTGCTCAGGAAACCAATCGCATACACTGTTGCCATGTAGTTCATCATCTTCGGTCCAAACAACAAGTTCTACCATTGCAAAGGACAGTGA

C1r XM_001061611.1 ACAAAGACCTTATGGGTTATGTCAGCGGCTTCGGGATAACAGAAGATAAAATAGCTTTTAATCTCAGGTTTGTCCGTCTGCCCATAGCCGATCGAGAGGC

Cybb (Nox2)

NM_023965.1 CAGTACCAAAGTTTGCCGGAAACCCTCCTATGACTTGGAAATGGATCGTGGGTCCCATGTTCCTGTATCTGTGTGAGAGGCTGGTGCGGTTTTGGCGATC

Ptgs2 (COX-2)

NM_017232.3 TTCGGAGGAGAAGTGGGTTTTAGGATCATCAACACTGCCTCAATTCAGTCTCTCATCTGCAATAATGTGAAAGGGTGTCCCTTTGCCTCTTTCAATGTGC

Cx3cr1 NM_133534.1 ATGTGCAAGCTCACGACTGCTTTCTTCTTCATTGGCTTCTTTGGGGGCATATTCTTCATCACCGTCATCAGCATCGACCGGTACCTCGCCATCGTCCTGG

FcγR1a NM_001100836.1 TGATGGATCATACTGGTGCGAGGTAGCCACGGAGGACGGCCGTGTCCTTAAGCGCAGCACCAAGTTGGAGCTATTTGGTCCCCAGTCATCAGATCCTGTC

FcγR2b NM_175756.1 CTGGTCCAAGGAATGCTGTAGATATGAAAGAAAACATCTAGAGTCCCTTCTGTGAGTCCTGAAACCAACAGACACTACGATATTGGTTCCCAATGGTTGA

FcγR3a NM_207603.1 GACTCTTGTTTGCAATAGACACAGTGCTGTATTTCTCGGTGCAGAGGAGTCTTCAAAGTTCCGTGGCAGTCTATGAGGAACCCAAACTTCACTGGAGCAA

Gusb NM_017015.2 TCATTTGATCCTGGATGAGAAACGAAAAGAATATGTCATCGGAGAGCTCATCTGGAATTTTGCTGACTTCATGACGAACCAGTCACCACTGAGAGTAACA

Havcr2 (TIM-3)

NM_001100762.1 CGATGAAATTAAGGACTCTGGAGAAACTATCAGAACTGCTGTCCACATTGGAGTAGGCGTCTCTGCTGGGCTGGCCCTGGCACTTATTCTTGGTGTTTTA

Hprt1 NM_012583.2 AGCTTCCTCCTCAGACCGCTTTTCCCGCGAGCCGACCGGTTCTGTCATGTCGACCCTCAGTCCCAGCGTCGTGATTAGTGATGATGAACCAGGTTATGAC

Hvcn1 (Hv1)

XM_006249369.2 ACCAAGAGGATGAGCAGGTTCTTGAAGCACTTCACAGTGGTGGGGGACGACTACCACACCTGGAATGTCAACTACAAGAAGTGGGAGAACGAGGAGGATG

Il6 NM_012589.1 GGAACAGCTATGAAGTTTCTCTCCGCAAGAGACTTCCAGCCAGTTGCCTTCTTGGGACTGATGTTGTTGACAGCCACTGCCTTCCCTACTTCACAAGTCC

Kcna3 (Kv1.3)

NM_019270.3 GCCACCTTCTCCAGAAATATCATGAACCTGATAGACATTGTAGCCATCATCCCTTATTTTATTACTCTGGGCACTGAGCTGGCTGAGCGACAGGGTAATG

- 36 -

Kcnj2 (Kir2.1)

NM_017296.1 GTTCTTTGGCTGTGTGTTTTGGTTGATAGCTCTGCTCCACGGGGATCTGGATGCTTCTAAAGAGAGCAAAGCGTGTGTGTCTGAGGTCAACAGCTTCACG

Kcnn4 (KCa3.1)

NM_023021.2 TACGTCTCTACCTGGTGCCTCGCGCGGTACTTCTGCGTAGCGGGGTCCTGCTCAACGCGTCTTACCGCAGCATCGGGGCGCTCAACCAAGTCCGATTCCG

Mrc1 NM_001106123.1 CTTTGGAATCAAGGGCACAGAGCTATATTTTAACTATGGCAACAGGCAAGAAAAGAATATCAAGCTTTACAAAGGTTCCGGTTTGTGGAGCAGATGGAAG

Msr1 (SR-A)

NM_001191939.1 CACGTTCCATGACAGCATCCCTTCCTCACAACACTATAAATGGCTCCTCCGTTCAGGAGAAACTGAAGTCCTTCAAAGTTGCCCTCGTCGCTCTCTACCT

Myc NM_012603.2 ACCGAGGAAAACGACAAGAGGCGGACACACAACGTCTTGGAACGTCAGAGGAGAAACGAGCTGAAGCGTAGCTTTTTTGCCCTGCGCGACCAGATCCCTG

Ncf1 NM_053734.2 TCCATTCCCAGCATCCCATAATTGGGCTTGTCCGTGTTCCAACATCTGGGCGGAATTTCACAGCCAAAGGTCAAGAGGACTGCTGTTACGTTCAAGGTCG

Nos2 (iNOS)

NM_012611.2 ACGGGACACAGTGTCGCTGGTTTGAAACTTCTCAGCCACCTTGGTGAGGGGACTGGACTTTTAGAGACGCTTCTGAGGTTCCTCAGGCTTGGGTCTTGTT

Nox1 NM_053683.1 CCGAGAAAGAAGATTCTTGGCTAAATCCCATCCAGTCTCCAAACGTGACAGTGATGTATGCAGCATTTACCAGTATTGCTGGCCTTACTGGAGTGGTCGC

Nox4 NM_053524.1 TGTTGGACAAAAGCAAGACTCTACATATCACCTGTGGCATAACTATTTGTATTTTCTCAGGTGTGCATGTAGCTGCCCACTTGGTGAACGCCCTGAACTT

P2ry6 NM_057124.2 TGGCCCAACATGCCTGGCCCTCCAAAATTTCTATGTCAACCACAAAACTAAGACACCTGTGTTTCGGGGACTGGTCAGTTCATGCTTGTTATACCAGAAT

Orai1 NM_001013982.1 GCCTTCTCCACCGTCATCGGGACGCTGCTTTTCCTGGCCGAAGTCGTGCTGCTCTGCTGGGTGAAGTTCTTACCGCTCAAGAGGCAGGCGGGACAGCCAA

Orai3 NM_001014024.1 ACCTGTAATGTGCTTTACAGTTGGCATCCTGGGAGAGATTTTACATAGGCTCCTCAGATGAACCACTTTACACTTGGTGACTTGTGGTGGTGTGTCCCAC

Rpl32 NM_013226.2 CATCGTAGAAAGAGCAGCACAGCTGGCCATCAGAGTCACCAATCCCAACGCCAGGCTACGCAGCGAAGAGAATGAATAGATGGCTTGTGTGCCTGTTTTG

Sirpa NM_013016.2 AGGACATTCATTCTCGGGTCATCTGCGAGGTAGCCCACGTCACCTTGGAAGGACGCCCGCTTAATGGGACCGCTAACTTTTCTAACATCATCCGAGTTTC

Stim1 NM_001108496.2 TATCTATCGTGATTGGTGTGGGTGGCTGCTGGTTTGCCTATATCCAGAACCGTTACTCTAAGGAGCACATGAAGAAAATGATGAAGGATCTGGAAGGATT

Stim2 NM_001105750.2 TTCACAATTGGACGCTTGAGGATACCCTGCAGTGGTTGATAGAATTTGTTGAACTCCCACAATACGAGAAGAATTTTAGGGATAATAATGTGAAAGGAAC

Tnfa NM_012675.2 GGTGATCGGTCCCAACAAGGAGGAGAAGTTCCCAAATGGGCTCCCTCTCATCAGTTCCATGGCCCAGACCCTCACACTCAGATCATCTTCTCAAAACTCG

Trem2 NM_001106884.1 TCCGGCTGGCTGAGGAAGGGTGCCATGGAACCTCTCCACGTGTTTGTCCTGTTGCTGGTCACAGAGCTGTCCCAAGCCCTCAACACCACAGTGCTGCAGG

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2.5. Patch clamp electrophysiology

Patch clamp recordings were performed by Roger Ferreira and Raymond Wong. Primary

rat microglia and MLS-9 cells were plated on 15 mm diameter coverslips at

~7.5×104/coverslip and mounted in a model RC-25 perfusion chamber (Warner

Instruments, Hamden, CT). They were superfused with an extracellular (bath) solution

containing (in mM): 125 NaCl, 5 KCl, 1 MgCl2, 1 CaCl2, 5 glucose, and 10 HEPES,

adjusted to pH 7.4 (with NaOH). Sucrose was added to adjust the osmolarity to ~310

mOsm (measured with a freezing point-depression osmometer; Advanced Instruments,

Norwood, MA), which prevented activation of the swelling-activated Cl- current

(Schlichter et al., 2011). Bath solutions were exchanged using a gravity-driven perfusion

system flowing at 1.5–2 ml/min. All recordings were made at room temperature.

Recordings were performed in the whole-cell- or perforated-patch configuration using 7–

9 MΩ resistance pipettes pulled from thin-walled borosilicate glass (WPI, Sarasota, FL)

using a Narishige puller (Narishige Scientific, Setagaya-Ku, Tokyo). Patch-clamp data

were obtained with an Axon Multiclamp 700A amplifier (Molecular Devices, Sunnyvale,

CA). Signals were compensated on-line for capacitance and series resistance, filtered at 5

kHz, and acquired and digitized using a Digidata 1322A board with pClamp software

(ver9; Molecular Devices). Junction potentials were reduced by using agar bridges made

with bath solution, and were calculated with the utility in pClamp. After correction, all

voltages were about 5 mV more negative than shown.

TRPM7 currents were recorded in the whole-cell configuration with a pipette solution

buffered to ~20 nM free Ca2+ to preclude activation of KCa2.3 channels. Because these

channels are inhibited by high intracellular Mg2+ in microglia (Jiang et al., 2003) and

other cells (Monteilh-Zoller et al., 2003; Nadler et al., 2001), most recordings used a

- 38 -

Mg2+-free pipette solution containing (in mM): 100 K-aspartate, 40 KCl, 1 CaCl2, 2

K2ATP, 10 EGTA, 10 HEPES, pH adjusted to 7.2 with KOH, 280 mOsm/kgH2O. The

exception was for experiments testing the Mg2+-dependence of NS8593, in which case

free Mg2+ was adjusted to 75 or 300 µM by adding 1 mM or 2 mM MgCl2, respectively

to the standard pipette solution. Free Mg2+ (and Ca2+, below) concentrations were

calculated with WEBMAXC Extended software

(http://www.stanford.edu/~cpatton/webmaxc/webmaxcE.htm). KCa2.3 currents were

recorded in the perforated-patch configuration, using pipettes containing 200 µg/ml

amphotericin B (Sigma), in a similar ionic solution, but with 0.5 CaCl2 and 1 EGTA to

obtain ~120 nM free Ca2+. After a giga-ohm seal formed, amphotericin B lead to a

gradual decrease in series resistance, and experiments were begun after the resistance was

<100 MΩ.

2.6. Transmigration and invasion assays

For transmigration assays, microglia were seeded at 40,000 cells/well on the upper well

of Transwell™ filter inserts (VWR, Mississauga, ON, Canada). The filters contain 8 µm-

diameter pores that allow cell haptokinesis; i.e., random migration without an applied

chemical gradient. For invasion assays, the setup was the same, except the cells were

seeded on BioCoat Matrigel™ Invasion Chambers (BD Biosciences, Mississauga, ON,

Canada), in which the filters are coated with MatrigelTM, a basement membrane-like

ECM substance secreted by mouse sarcoma cells. Cells must degrade the Matrigel in

order to migrate to underside of the filter. One hour after seeding, MEM with 2% FBS

was added to both upper and lower wells, with or without 20 ng/ml IL-4 or IL-10. After 1

hr further incubation, a channel inhibitor was added . The chambers were then incubated

for 24 hr (37°C, 5% CO2), and the filters were fixed in 4% paraformaldehyde for 10 min

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and rinsed with PBS. Microglia that remained on the upper side of the filter were

removed by swirling a Q-tip on the filter surface. To visualize microglia that had

translocated to the underside of the filter, cells were stained with 0.3% crystal violet in

methanol solution for about 1 min, and rinsed with PBS to remove excess stain. The cells

were counted in 5 random fields/filter at 40× magnification, using an Olympus CK2

inverted microscope (Olympus, Tokyo, Japan).

2.7. Myelin phagocytosis and ROS production

Myelin was isolated by homogenizing adult rat brains (weighing 1.95–2.10 g) in iso-

osmotic buffer, followed by sucrose gradient centrifugation (Norton and Poduslo, 1973).

The myelin concentration was calculated from the total protein concentration, using the

Pierce bicinchoninic acid (BCA) assay (Thermo Fisher Scientific, Waltham, MA), and

adjusted as required. Myelin was labeled in the dark with the lipophilic dye, 1,1′-

dioctadecyl-3,3,3′,3′-tetramethyl-indocarbocyanine perchlorate (DiI) (Molecular Probes,

Burlington, ON, Canada) (1:200; ≥2 min, 37 °C), as is commonly done for phagocytosis

studies (Greenhalgh and David, 2014; Liu et al., 2006). Microglia were seeded at 7–

8 × 104 cells per 15-mm glass coverslip. They were cultured for 1–2 days without

complement proteins (Reichert et al., 2001) by using 2% heat-inactivated FBS at 37 °C, 5

% CO2, and then incubated with DiI-labeled myelin. Extracellular myelin was removed

by washing with standard bath solution (for phagocytosis and ROS assays), Trizol

reagent (for RNA isolation) or fixative (for fluorescence microscopy). The cells were

plated at the same high density, and the plate reader was configured to measure

fluorescence intensity at the bottom of the plate. At the end of every experiment, we

monitored the cell health and saw no evidence of damage, death, or obvious differences

in cell numbers.

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Myelin phagocytosis was first optimized by incubating microglia with 5, 25, or 50 μg/mL

myelin for 6 h or with 25 μg/mL myelin for 1, 3, or 6 h. Phagocytosis of DiI-labeled

myelin fragments was verified by fluorescence microscopy in microglia that were fixed

in 4% paraformaldehyde (10 min, room temperature) and stained with FITC-conjugated

tomato lectin (1:500, 15 min; Sigma-Aldrich, Oakville, ON) and the nuclear stain, 4′,6-

diamidino-2-phenylindole (DAPI; 1:3000, 5 min; Cayman Chemical, Ann Arbor,

Michigan). After washing (three times, 5 min), cells on coverslips were mounted on glass

slides with Dako mounting medium (Dako, Glostrup, Denmark) and stored in the dark at

4 °C until images were acquired with an Axioplan 2 wide-field epifluorescence

microscope equipped with an Axiocam HR digital camera (both from Zeiss, Toronto,

ON, Canada).

An earlier study of murine microglia showed that myelin debris was internalized within 1

h and accumulated in LAMP-1-positive lysosomes, presumably targeted for degradation

(Liu et al., 2006). We verified that unstimulated (control) rat microglia rapidly

phagocytose myelin fragments under the present conditions. At 25 μg/mL myelin, uptake

was substantial by 3 h, and by 6 h, DiI-labeled myelin fragments had accumulated mainly

in the perinuclear region, with a small amount in other cell regions (Fig. 4.1.A). For the

remaining study, we chose a 6 h incubation with 25 μg/mL myelin. The washing

procedure effectively removed extracellular myelin debris (Fig. 4.1.A); thus, we could

use a multi-label fluorescence plate reader to quantify myelin phagocytosis.

To quantify ROS, microglia were incubated (1 h, 37 °C, 5 % CO2) with the membrane-

permeant probe, a chloromethyl derivative of 2′,7′-dichlorodihydrofluorescein diacetate

(CM-H2DCFDA; 5 μM; Invitrogen). The probe is cleaved by intracellular esterases to

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release H2DCFDA, which is then oxidized to a fluorescent compound,

dichlorodihydrofluorescein (DCF) that remains trapped in the cells. DCF (495 nm

excitation, 525 nm emission) is a general ROS probe that is compatible with DiI-labeled

myelin (553 nm excitation, 570 nm emission), thus allowing myelin phagocytosis and

ROS production to be monitored in the same samples. Extracellular CM-H2DCFDA and

myelin fragments were removed by washing the coverslips with standard bath solution,

which contained (in mM) 125 NaCl, 5 KCl, 1 CaCl2, 1 MgCl2, 10 HEPES, and 5 D-

glucose (pH 7.4; 290–300 mOsm). As a positive control for ROS production, microglia

were occasionally stimulated for 1 h with the PKC activator, phorbol 12-myristate 13-

acetate (PMA; 100 nM, Sigma), which produced a robust DCF signal (not shown).

2.8. Statistical Analysis

Quantitative data are presented as mean ± standard error of the mean (SEM). One- or

two-way ANOVA statistical tests were performed followed by post hoc analysis as

inidicated in figure legends. Results were considered significant if p<0.05. n values,

where indicated, represent individual microglia cultures across numerous animals.

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Chapter 3. Expression and Contributions of TRPM7 and

KCa2.3/SK3 Channels to the Increased Migration and

Invasion of Microglia in Anti-Inflammatory Activation States

3.1. Introduction

Microglia rapidly respond to CNS injury and disease and can assume a spectrum of

activation states. It is important to understand how microglial activation states affect their

migration and invasion; crucial functions after injury and in the developing CNS. We

reported that LPS-treated rat microglia migrate very poorly, while IL-4-treated cells

migrate and invade much better. Microglial podosomes were found to regulate migration

and invasion. We hypothesized that IL-4 and IL-10 would differentially affect podosome

expression, gene induction, migration and invasion. Further, based on the enrichment of

the KCa2.3/SK3 Ca2+-activated potassium channel in microglial podosomes, we

predicted that it regulates migration and invasion. Rat microglia cultures were stimulated

for 24 h with IL-4 or IL-10. We found both cytokines increased migration and invasion

but only IL-10 affected podosome expression. Surprisingly, upon addition of three

KCa2.3 inhibitors (apamin, tamapin, NS8593), only NS8593 abrogated the increased

migration and invasion of IL-4 and IL-10-treated microglia (and invasion of unstimulated

microglia). Further investigation yielded a role for TRPM7 (not KCa2.3) channel to the

enhanced ability of microglia to migrate and invade when in anti-inflammatory states.

3.2. Results

Changes in gene expression indicate similarities and differences in microglial responses

to IL-4 and IL-10

Microglial cells were stimulated for 6 hr with IL-4 to induce ‘alternative’ activation or

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with IL-10 to induce ‘acquired deactivation’ (see Introduction). This early time point was

chosen to allow time for protein changes to occur and exert effects during the 24 hr

functional assays. The multiplex NanoString™ assay was used to compare mRNA

expression of 28 genes (listed in Table 1) within several categories: well-known markers

of classical activation (e.g., IL-1β, TNFα, iNOS, IL-6) and alternative activation (MRC1,

Arg1, CD163); other known immune mediators; and matrix-degrading enzymes of

relevance to microglial migration and invasion. The rapidly induced genes fell into four

groups: those induced selectively by IL-4 (Fig. 3.1A), selectively by IL-10 (Fig. 3.1B),

by both cytokines (Fig. 3.1C), or unaffected by either cytokine (not shown). Note that the

6 hr results do not rule out later changes in gene expression. The findings described

below indicate that IL-4 and IL-10 induce different expression patterns in rat microglia

despite both being considered anti-inflammatory cytokines.

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Figure 3.1. NanoString analysis of expression changes for selected genes in response

to IL-4- and IL-10-treatment.

Treating rat primary microglia for 6 hr with 20 ng/ml IL-4 or 20 ng/ml IL-10 resulted in

gene expression changes that were specific for IL-4 (A), specific for IL-10 (B), or

common to both treatments (C). mRNA expression was normalized to the housekeeping

gene, HPRT1, and shown as mean ± SEM with the number of individual cultures

indicated on each bar. [Note the differing Y-axis scales.] One-way ANOVA with Tukey's

post-hoc test revealed differences from unstimulated (control) microglia: *p<0.05,

**p<0.01, ***p<0.001. Prepared and analyzed by Starlee Lively

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(i) IL-4-specific induction. IL-4 alone increased transcript levels of 7 of the genes

examined, including four hallmark molecules of alternative activation: mannose receptor

C type 1 (MRC1), arginase 1 (Arg1), CD163, transforming growth factor-β1 (TGFβ1) by

5.5-, 2.9-, 9.8- and 2-fold, respectively. These changes are similar to our recent results

(Liu et al., 2013; Lively and Schlichter, 2013). The transcription factor, c-myc, which

polarizes human macrophages toward an alternative-activation state (Pello et al., 2012),

was increased 6.2 fold. The toll-like receptors (TLRs) exemplify differential effects of the

cytokines on gene expression. IL-4 increased TLR4 by 3.8 fold and decreased TLR2 by

77%. Among the matrix-degrading enzymes examined, only IL-4 increased cathepsin S.

(ii) IL-10- specific induction. IL-10 selectively up-regulated 7 of the genes examined.

CD11b, a subunit of complement receptor 3 that is often used to identify microglia, was

increased 1.5 fold. We examined two genes that help dampen effects of pro-inflammatory

stimuli: the IL-1 receptor antagonist (IL-1ra) and the anti-oxidant, heme oxygenase-1

(HO-1; also called Hsp32) (Foresti et al., 2013; Perrier et al., 2006): IL-1ra was increased

1.7 fold and Hsp32 by 5.4 fold. IL-10 increased expression of the pleiotropic cytokine,

IL-6, by 1.3 fold. IL-10 increased TLR2 by 1.3 fold, but had no effect on TLR4. IL-10

up-regulated the matrix-degrading enzymes, cathepsin L1 (1.8 fold) and MMP14 (2.3

fold). (iii) Induced by both IL-4 and IL-10. Six of the genes examined were up-

regulated by both IL-4 and IL-10. ED1, which is a lysosomal marker often used to

indicate microglial activation and phagocytic capacity, was increased 1.8 fold by IL-4

and 1.4-fold by IL-10. STAT6 is an important signalling molecule linked to IL-4-induced

alternative activation (reviewed in (Colton, 2009; Sica and Mantovani, 2012)): it was

increased 1.6 fold by IL-4 and 1.9 fold by IL-10. The transcription factor, nuclear factor-

erythroid 2-related factor 2 (Nrf2), regulates redox homeostasis and skews microglia

toward alternative activation (Rojo et al., 2010): it was increased 1.6 fold by IL-4 and 1.5

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fold by IL-10. The endogenous broad-specificity MMP inhibitor, TIMP metallopeptidase

inhibitor 1 (TIMP1), was increased equally (1.9 fold) by IL-4 and IL-10. IL-4 and IL-10

both increased the matrix-degrading enzymes, cathepsin B (1.6- and 1.7 fold,

respectively) and cathepsin D (1.6- and 1.5 fold, respectively). (iv) Not induced (not

shown). Neither cytokine significantly altered expression of the pro-inflammatory genes,

tumor necrosis factor-α (TNF-α) or inducible nitric oxide synthase (iNOS) at the 6 hr

time point. Among the matrix-degrading enzymes, neither cytokine altered expression of

heparanase, cathepsin K or the matrix metalloproteases, MMP2 and MMP12. Although

not reaching statistical significance (n=5 samples), IL-4-treated microglia apparently had

less IL-1 and more MMP9.

Podosome expression depends on the microglial activation state but not on KCa2.3 or

TRPM7 channels

F-actin is concentrated in the core of each podosome in microglia (Siddiqui et al., 2012;

Vincent et al., 2012) and other cells (reviewed in (Murphy and Courtneidge, 2011)), and

is thus a useful marker for quantifying the proportion of microglia bearing a podonut.

Microglia were treated for 24 hr with LPS, IL-4 or IL-10 (Fig. 3.2). At this time, most

unstimulated microglia were unipolar with a single, large fan-shaped lamellum at the

leading edge and a trailing uropod; i.e., 57% (n=9 separate cultures) in static counts of

fixed cells (Fig. 3.2A). In contrast, LPS-treated cells were amoeboid or round and flat.

Most IL-10-treated microglia were unipolar with a lamellum and a uropod (64%; n=9).

The morphology of IL-4-treated cells was more variable, but many cells were unipolar

with a lamellum that exhibited extensive membrane ruffling (43%; n=9); consistent with

our recent report (Lively and Schlichter, 2013). These were the morphologies of

microglia used for gene-expression analysis in Figure 3.1. Because LPS-treated microglia

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did not have podonuts and did not migrate during the 24 hr test period (Lively and

Schlichter, 2013), this treatment was not examined further. Podonuts were well expressed

in unstimulated, IL-4- and IL-10-treated microglia (Fig. 3.2A). The proportion of

microglia with a podonut was increased (by 2.4 fold) only in IL-10-treated cells (Fig.

3.2B).

KCa2.3 (SK3) is enriched in the core of podosomes (Siddiqui et al., 2012); therefore, we

used two KCa2.3 inhibitors to ask whether this channel regulates podosome expression.

In order to factor out culture variability, the proportion of microglia with a podonut in IL-

4- and IL-10-treated cells was normalized to its unstimulated counterpart for each culture.

Inhibiting KCa2.3 with 5 nM tamapin for 6 hr did not affect podonut expression in

unstimulated (Fig. 3.2C), IL-4-treated (Fig. 3.2D), or IL-10-treated microglia (Fig. 3.2E).

The blocker, NS8593 (7 µM, 6 hr), slightly reduced the number of microglia expressing a

podonut (by 13%; p<0.05) only in IL-10-treated microglia (Fig. 3.2E). Thus, KCa2.3

channel activity is apparently not necessary for podonut expression.

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Figure 3.2. Effect of microglial activation state and selected channel inhibitors on

podosome (podonut) expression.

A. Representative fluorescence micrographs show podonut expression in unstimulated

primary rat microglia or 24 hr after treatment with LPS (10 ng/ml), IL-4 (20 ng/ml) or IL-

10 (20 ng/ml). The arrows indicate examples of a single, large donut-shaped ring of

podosomes, which we call a ‘podonut’ in the lamellum of unipolar microglia. Cells were

stained for filamentous (F-) actin with phalloidin (green) to quantify the proportion of

cells with a podonut, and with the nuclear marker, DAPI (blue) to quantify total cell

numbers. Scale bar, 50 µm. B. Podosome (podonut) expression is affected by the

microglial activation state. The proportion of microglial cells bearing a podonut in the

lamellum (sum of 3 randomly selected fields of view at 10× magnification) was

normalized to unstimulated cells. C–E. Microglia were unstimulated or stimulated for 24

hr with 20 ng/ml IL-4 or IL-10, and then exposed for 6 hr to control medium or the

KCa2.3 inhibitors, 5 nM tamapin or 7 µM NS8593, which also inhibits TRPM7 channels

(see Results and Figs. 3.6, 3.7). All graphical data are shown as mean ± SEM with

sample size ( of individual cultures) indicated on each bar. A one-way ANOVA with

Tukey's post-hoc analysis was used to determine significant differences. *p<0.05;

***p<0.001.

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Migration of primary microglia is increased by IL-4 and IL-10 and requires TRPM7 (not

KCa2.3)

We recently found that microglia stimulated with IL-4 migrate much more than

unstimulated cells (Lively and Schlichter, 2013). Because there are some similarities in

outcomes and anti-inflammatory effects of IL-4 and IL-10, we were not surprised that

both treatments increased microglia transmigration; by 2.3 fold for IL-10 and 2.6 fold for

IL-4 (Fig. 3.3A). To assess whether KCa2.3 activity is required for this enhanced

migration, we first compared effects of three well known KCa2.3 blockers. Microglia,

unstimulated or stimulated with IL-4 or IL-10, were incubated in TranswellTM chambers

with 5 nM tamapin, 100 nM apamin or 7 µM NS8593. NS8593 was originally described

as a selective inhibitor of KCa2.x channels (Strobaek et al., 2006). Based on their known

potencies (see Methods), these concentrations should block >95% of KCa2.3 channels for

apamin (IC50=4 nM), 90% for NS8593 (IC50=0.7 M), and ~65% for tamapin (IC50=1.7

nM). Surprisingly, their effects on transmigration differed. Apamin did not inhibit

migration, regardless of the activation state (Fig. 3.3B–D), and instead, both apamin and

tamapin increased migration of unstimulated cells, while NS8593 had no effect (Fig.

3.3B). [Blocking KCa2.2 alone with 250 pM tamapin had no effect on migration,

regardless of cell activation state (data not shown)]. The most striking difference was that

NS8593 inhibited transmigration of IL-4- and IL-10-treated cells (by 50% and 68%,

respectively); restoring it to the level of unstimulated microglia. This dramatic reduction

by NS8593, but not by apamin or tamapin, indicates that NS8593 is not acting through a

block of KCa2.3 channels.

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Figure 3.3. Migration of primary rat microglia is affected by the activation state,

and by KCa2.3 and TRPM7 inhibitors.

A. Microglia in the upper well of Transwells were unstimulated or stimulated with either

20 ng/ml IL-4 or 20 ng/ml IL-10 for 24 hr. The number of cells that migrated to the

underside of the filter was then counted and normalized to control (unstimulated) cells,

indicated by the dashed line. B–D. Microglia were unstimulated or stimulated with IL-4

or IL-10 as in panel A, with or without a channel inhibitor: 100 nM apamin, 5 nM

tamapin, 7 µM NS8593 or 10 µM AA-861. E–H. IL-4 and IL-10 increase the invasion

capacity of rat microglia, and TRPM7 is involved. Microglia were plated in the upper

wells of Matrigel chambers, with or without stimulation by 20 ng/ml IL-4 or 20 ng/ml IL-

10 for 24 hr. E. Invasion of control (unstimulated) microglia was compared with IL-4-

and IL-10-treated cells. F–H. Microglia were unstimulated or stimulated with IL-4 or IL-

10 as in panel A, with or without simultaneous addition of a channel inhibitor: 100 nM

apamin, 7 µM NS8593 or 10 µM AA-861. For each stimulus, the number of cells that

had migrated or invaded was normalized to the level without a channel inhibitor. The

dashed line in all graphs indicates the level in control (unstimulated) cells. Data are

expressed as mean ± SEM with the number of individual cultures indicated on each bar.

A one-way ANOVA with Tukey's post-hoc test was used to compare results with and

without a channel inhibitor; *p<0.05, **p<0.01, ***p<0.001; or for NS8593 versus AA-

861 (†p<0.05).

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Importantly, NS8593 was recently found to block cloned TRPM7 channels expressed in

HEK cells, with an IC50 of 1.6 µM in the absence of intracellular Mg2+ (Chubanov et al.,

2012). This is similar to the IC50 for block of KCa2.3, which raises the possibility that the

effects of 7 M NS8593 were due to TRPM7 block. To further address this possibility, we

tested AA-861, which inhibits TRPM7 at 10 µM (IC50=6 µM; (Chen et al., 2010)). AA-

861 preferentially reduced migration of IL-4-treated (Fig. 3.3C) and IL-10-treated (Fig.

3.3D) microglia (by 58% and 65%, respectively), without affecting unstimulated cells

(Fig. 3.3B). These results are entirely consistent with the effects of NS8593 and further

indicate that TRPM7, rather than KCa2.3, is involved in the enhanced migration of IL-4-

and IL-10-treated microglia.

Invasion of primary microglia is increased by IL-4 and IL-10 treatment and requires

TRPM7

When seeded in the upper well of a MatrigelTM Invasion chamber, microglia must

degrade the MatrigelTM layer in order to invade to the underside of the filter. We

previously found that IL-4 increased invasion by rat microglia (Lively and Schlichter,

2013) and here, we corroborated that effect and then showed that IL-10 increased

invasion by 93% compared with unstimulated cells (Fig. 3.3E). In an earlier study

showing that NS8593 inhibited invasion of unstimulated microglia (Siddiqui et al., 2012),

we concluded that KCa2.3 channels were responsible. However, with block of TRPM7

being a possibility, we now compared NS8593 with the KCa2.x blocker, apamin, and the

TRPM7 inhibitor, AA-861. Apamin had no effect on invasion regardless of the microglial

activation state (Figs. 3.3E–H). This is consistent with the migration results (Figs. 3.3A–

D), and strongly suggests that despite the presence of KCa2.3 in podosomes, this channel

is not needed for substrate (Matrigel) degradation. In contrast, NS8593 reduced invasion

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of unstimulated, IL-4- and IL-10-treated cells to a similar degree: ~60% compared with

no channel inhibitor. The TRPM7 inhibitor, AA-861, also decreased microglia invasion:

by 57% in IL-10-treated cells and 32% in unstimulated cells. Its effect on IL-4-treated

cells did not reach statistical significance. Overall, it appears that TRMP7 is involved in

the invasion capacity of microglia. While for IL-4- and IL-10-treated cells, reduced

invasion might result from their reduced migratory capacity; this is not the full

explanation for unstimulated microglia. That is, the TRPM7 blockers reduced invasion

but not migration, and thus the channel appears to be involved in substrate degradation.

NS8593 (and not AA-861) inhibits the KCa2.3 current in microglia

As shown above, effects of NS8593 on migration of primary microglia during a 24 hr test

period depend on the cell activation state (Fig. 3.3). Results in Figure 3.4A show a lack of

correlation between activation state and expression of KCNN3, the gene encoding

KCa2.3. There were no significant differences between control (unstimulated), IL-4- or

IL-10-treated microglia at either 6 or 24 hr. Because 7 µM NS8593 had different effects

from the KCa2.3 blockers, apamin and tamapin, it was necessary to show whether this

drug concentration inhibits KCa2.3 channels in microglia under all three activation

conditions. NS8593 was originally described as a negative gating modulator that depends

on the intracellular Ca2+ concentration; i.e., with a Kd of 726 nM at 0.5 µM Ca2+ versus

∼14 µM at 10 µM Ca2+ (Strobaek et al., 2006). To correspond with NS8593 effects on

migration of intact microglia, KCa2.3 inhibition was examined using the perforated-patch

configuration to maintain normal intracellular Ca2+. Current inhibition was assessed in

both MLS-9 microglial cells and primary microglia.

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Figure 3.4. KCNN3 expression and KCa2.3 current inhibition by NS8593 in

microglia in differing activation states.

A. Expression of KCNN3 mRNA was quantified using NanoString nCounter analysis in

unstimulated primary microglia, and at 6 hr (solid bars) and 24 hr (striped bars) after

treatment with 20 ng/ml IL-4- or IL-10-treatment. B–D. NS8593 inhibits the KCa2.3

current, while AA-861 has no effect. KCa2.3 currents were recorded from MLS-9

microglial cells in the perforated-patch configuration produced by amphotericin B (200

µg/ml) in the pipette. The voltage protocol throughout was a 120 ms-long voltage ramp

from −100 to +80 mV from a holding potential of −70 mV. The bath always contained 1

µM TRAM-34 to block KCa3.1 currents. Riluzole (300 µM) was used simply as a tool to

activate the KCa2.3 current (Liu et al 2013). B. Upper panel: Representative traces show

the current evoked by riluzole with or without 7 µM NS8593. Lower panel: The

representative time course (current measured at +80 mV) illustrates KCa2.3 current

activation and its inhibition by NS8593. C. Representative currents and time course show

that no current was activated when 7 µM NS8593 was present in the bath. D. The current

is insensitive to 10 µM AA-861. Note that current activation by riluzole is readily

reversible (wash), as we previously showed (Liu et al 2013). E–G. The KCa2.3 current in

primary rat microglial cells is inhibited by 7 µM NS8593 under differing activation

states. Currents were recorded using the same patch-clamp configuration as described for

MLS-9 cells. Upper panels: Representative currents in microglia that were unstimulated

(E), or treated for 24 hr with 20 ng/mL IL-4 (F) or 20 ng/mL IL-10 (G). Lower panels: A

representative time course for each cell (current at +80 mV) shows activation by riluzole

and inhibition by NS8593. qRT-PCR performed and analyzed by Xiaoping Zhu. Patch

clamp recordings done by Roger Ferreira and Raymond Wong.

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We used riluzole (2-amino-6-(trifluoromethoxy) benzothiazole) simply as a tool to

activate KCa2.3 currents because we recently found that it reliably activates KCa2.3 (and

KCa3.1) channels in MLS-9 and primary rat microglial cells (Ferreira et al., 2014; Liu et

al., 2013). To eliminate potential contributions of KCa3.1 currents, the selective KCa3.1

blocker, 1 µM TRAM-34, was added to the bath. MLS-9 cells. As expected, riluzole

activated a KCa2.3 current in all MLS-9 cells tested (15/15; see example in Fig. 3.4B).

The mean current amplitude at +80 mV was 130±15 pA (n = 15). With voltage-clamp

ramps from −100 to +80 mV, the current was present at all voltages and reversed near the

K+ Nernst potential (about −85 mV), as previously described for whole-cell recordings

from MLS-9 cells (Liu et al., 2013). After the KCa2.3 current was activated, bath

perfusion of 7 µM NS8593 rapidly and dramatically inhibited the current in 5/5 cells

tested (example in Fig. 3.4B). With pre-addition of 7 µM NS8593 to the bath (and

TRAM-34 to block KCa3.1), no current was activated (6 cells tested; example in Fig.

3.4C). The observed efficacy of NS8593 is consistent with the reported Kd of 726 nM at

0.5 µM intracellular free Ca2+ (Strobaek et al., 2006). For completeness, we also tested

the TRPM7 inhibitor, 10 µM AA-861, which was used in the migration and invasion

assays in Figure 3.3. AA-861 had no effect on the current (4/4 cells; example shown in

Fig. 3.4D). Primary microglia. We could find no recordings of KCa2.3 currents in

primary rat microglia in the literature. Here, riluzole activated a KCa2.3 current in 1/8

unstimulated microglia (264 pA; Fig. 3.4D), 2/8 IL-4-treated microglia (529 pA, 249 pA;

smaller current shown in Fig. 3.4E), and 2/8 IL-10-treated microglia (246 pA, 81 pA;

larger current shown in Fig. 3.4F). The current was very similar to the KCa2.3 current in

MLS-9 cells (above). It was present at all voltages tested (−100 to +80 mV) and reversed

near the K+ Nernst potential, and was consistent with biophysical features of cloned

KCa2.3 channels (Kohler et al., 1996). Due to the low prevalence of current, we did not

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assess amplitudes in different activation states. In 5/5 microglia, 7 µM NS8593

dramatically inhibited the KCa2.3 current, and this occurred at the normal intracellular

free Ca2+ concentration maintained by perforated-patch recordings. Pre-treatment with

NS8593 could not be tested because KCa2.3 current activation was unreliable in primary

microglia.

NS8593 and AA-861 inhibits the TRPM7 current in microglia

Because we used 7 µM NS8593 and 10 µM AA-861 in functional studies (Figs. 3.2 and

3.3), we tested whether these drug concentrations inhibit the TRPM7 current in microglia

(Fig. 3.5). First, TRPM7 current was assessed in primary rat microglia using the whole-

cell configuration with a Mg2+-free intracellular solution because block by NS8593 was

reported to be mildly Mg2+-dependent (Chubanov et al., 2012). Moreover, we previously

found that the TRPM7 current in rat microglia spontaneously activates in Mg2+-free

conditions (Jiang et al., 2003). A holding potential of −10 mV was used to inactivate

Kv1.3 current (Newell and Schlichter, 2005). [For consistency, the same protocol was

used for MLS-9 cells (below), although they lack Kv1.3 current.] As in our earlier study

(Jiang et al., 2003), the TRPM7 current was isolated at positive potentials and was

strongly outward-rectifying, while an inward-rectifying (Kir2.1) current was present at

very negative potentials (Fig. 3.5A, B). In primary microglia, the TRPM7 current was

reduced by both NS8593 and AA-861, while the inward rectifier was not affected. In the

examples shown, the time course of the TRPM7 current shows slow, spontaneous

activation after break-in, which required more than 10 min to reach a quasi-stable

plateau. TRPM7 inhibition by 7 µM NS8593 was rapid (Fig. 3.5A), while 10 µM AA-

861 was slower (Fig. 3.5B). Similar results were seen with MLS-9 microglial cells (Fig.

3.5C, D), which were advantageous in lacking Kv1.3 and Kir2.1 currents, and having

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much larger TRPM7 currents (721±63 pA versus 334±26 pA in primary microglia; Fig.

3.5E) that activated more rapidly after break-in. Inhibition by NS8593 was readily

reversible, which is consistent with direct channel block (Chubanov et al., 2012).

[Reversibility in primary microglia was difficult to study because the TRPM7 current

activated slowly.] Interestingly, there was a similar degree of inhibition of TRPM7 by

both drugs, and in both cell types. NS8593 reduced the current by 86% and 93% in

primary microglia and MLS-9 cells, respectively (Fig. 3.5F). AA-861 reduced the current

by 94% and 90% in primary microglia and MLS-9 cells, respectively (Fig. 3.5G).

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Figure 3.5. NS8593 and AA-861 inhibit the TRPM7 current in primary rat

microglia and MLS-9 microglial cells.

TRPM7 currents were recorded in the whole-cell configuration using a Mg2+-free pipette

solution. The voltage protocol throughout was a 120 ms-long ramp from −100 to +115

mV, from a holding potential of −10 mV. Graphical data are presented as mean ± SEM

for the number of cells indicated on each bar, and were compared using an unpaired t-

test: ***p<0.001. A–D. Representative currents from primary rat microglial cells (A, B)

and MLS-9 microglial cells (C, D) with Mg2+-free intracellular solution (no MgCl2, 10

mM EGTA). Upper panels: Currents are shown with and without 7 µM NS8593 (A, C) or

10 µM AA-861 (B, D) in the bath. Lower panels: Representative time courses (current

measured at +115 mV) show current activation, and inhibition by 7 µM NS8593 (A, C)

or 10 µM AA-861 (B, D). [The reversibility of NS8593 is shown in panel C.] E.

Comparison of the TRPM7 current amplitude (measured at +115 mV) in primary

microglia and MLS-9 cells. F, G. Comparison of TRPM7 current inhibition by 7 µM

NS8593 (F) and by 10 µM AA-861 (G) in primary microglia and MLS-9 microglial cells.

Patch clamp recordings done by Roger Ferreira and Raymond Wong.

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NS8593 inhibits the TRPM7 current in microglia, with or without intracellular Mg2+, and

regardless of the microglial activation state

The previously reported TRPM7 block by NS8593 exhibited a mild dependence on

intracellular Mg2+ (IC50 = 1.6 µM without Mg2+; 5.9 µM at 300 µM Mg2+) (Chubanov et

al., 2012). In addition, high intracellular Mg2+ inhibits the TRPM7 current in microglia

(Jiang et al., 2003) and other cells (Mederos y Schnitzler et al., 2008; Park et al., 2014).

Our earlier work (Jiang et al., 2003) showed that the TRPM7 current in primary rat

microglia is dose-dependently inhibited by internal Mg2+; i.e., the current was reduced

∼25% with 75 µM internal Mg2+ and its time-dependent run-up was prevented by 2.8

mM Mg2+, a concentration that fully inhibited cloned TRPM7 channels (Nadler et al.,

2001). Normal free Mg2+ is 250–1000 µM in mammalian cells (Romani and Scarpa,

2000), and 300 µM Mg2+ was reported to reduce the efficacy of TRPM7 inhibition by

NS8593 in HEK 293 cells (Chubanov et al., 2012). Therefore, we compared the current

amplitude and NS8593 block in MLS-9 cells with 0, 75 and 300 µM intracellular Mg2+

(Fig. 3.5B, Fig. 3.6). As with Mg2+-free intracellular solution (Fig. 3.5C), the TRPM7

current activated soon after break-in with 75 or 300 µM internal Mg2+ (Fig. 3.6A, B) and

reached a quasi-stable plateau by 10 min, at which time the amplitude was measured at

+115 mV. Although there might have been a trend toward smaller currents, these levels

of Mg2+ did not significantly affect the mean amplitude (Fig. 3.6C): 819±66 pA (no

Mg2+), 704±87 pA (75 µM Mg2+; 15% reduction), and 779±80 pA (300 µM Mg2+; 5%

reduction). In subsequent experiments, 7 µM NS8593 was added >10 min after break-in.

The TRPM7 current was substantially and equally blocked at all three Mg2+

concentrations (Fig. 3.6D): by 93.4% (no Mg2+), 93.6% (75 µM Mg2+), and 96.2% (300

µM Mg2+).

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Figure 3.6. Mg2+-dependence of TRPM7 current block by NS8593.

TRPM7 currents were recorded in MLS-9 microglial cells in the whole-cell configuration

with differing free Mg2+ concentrations in the pipette solution. The voltage protocol

throughout was a 120 ms-long ramp from −100 to +115 mV, from a holding potential of

−10 mV. Graphical data are presented as mean ± SEM for the number of cells indicated

on each bar, and were compared using a one-way ANOVA. A–D. Effect of 75 µM and

300 µM intracellular free Mg2+ on TRPM7 currents and their inhibition by NS8593. In

panels A and B, upper traces are representative currents with and without 7 µM NS8593,

and the lower panels (time course of current at +115 mV) show the rapid onset and

reversibility of inhibition by NS8593. TRPM7 current amplitude (at +115 mV; panel C),

and percent inhibition by 7 µM NS8593 (panel D) are compared for 75 µM and 300 µM

intracellular free Mg2+. Patch clamp recordings done by Roger Ferreira and Raymond

Wong.

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Finally, because NS8593 abolished the enhanced migratory capacity of IL-4- and IL-10-

treated primary microglia, but not unstimulated cells (Fig. 3.3), we compared TRPM7

expression, current amplitude and block by NS8593 under the three activation conditions

(Fig. 3.7). Treating primary microglia with IL-4 (but not IL-10) modestly increased

TRPM7 expression: at 24 hr it was 1.4-fold higher (Fig. 3.7A). The TRPM7 current (Fig.

3.7B, C) and its amplitude (measured at +115 mV; Fig. 3.7D) were similar under all three

conditions; i.e., 339±31 pA in unstimulated microglia, 328±56 pA after IL-4, and 390±28

pA after IL-10. Moreover, the degree of TRPM7 block by 7 µM NS8593 was the same

(Fig. 3.7E): 85.6% in unstimulated, 87.6% after IL-4, and 89.8% after IL-10. In

summary, 7 µM NS8593 effectively blocks TRPM7 channels in rat microglia and the

MLS-9 microglial cell line at physiologically relevant intracellular Mg2+ concentrations,

and microglia that were unstimulated or treated with IL-4 or IL-10.

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Figure 3.7. Effects of IL-4- and IL-10-treatment on TRPM7 expression, current and

block by NS8593 in primary rat microglia.

A. TRPM7 mRNA expression was measured using quantitative real-time RT-PCR at 6 hr

(solid bars) and 24 hr (striped bars) in unstimulated rat microglia or after treatment with

20 ng/ml IL-4 or 20 ng/ml IL-10. Values are expressed as mean expression (normalized

to HPRT1) ± SEM, with the number of individual cultures indicated on each bar. *p<0.05

indicates the difference from time-matched control (unstimulated) cells, and was

determined using a 2-way ANOVA followed by Bonferroni post-hoc test. B–E. The

TRPM7 current and block by NS8593 were not affected by 24 hr treatment with 20 ng/ml

IL-4 or IL-10. Whole-cell recordings were performed on primary rat microglia using

Mg2+-free pipette solution. B, C. Representative currents (upper panels) in response to

120 ms-long ramps from −100 to +115 mV, from a holding potential of −10 mV. Time

course of the current (lower panels) measured at +115 mV. D, E. Summary of TRPM7

current amplitudes measured at +115 mV (D) and percent inhibition of TRPM7 currents

by 7 µM NS8593 (E). Graphical data are presented as mean ± SEM for the number of

cells indicated on each bar, and were compared using a one-way ANOVA with Tukey's

post-hoc test. qRT-PCR performed and analyzed by Xiaoping Zhu. Patch clamp

recordings done by Roger Ferreira and Raymond Wong.

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3.3. Discussion

Microglia express receptors for IL-4 and IL-10 (Harry, 2013), and stimulation with

either cytokine is thought to dampen acute CNS inflammation, facilitate removal of

debris, and aid in brain repair by up-regulating anti-inflammatory mediators and

neurotrophic factors (reviewed in (Colton, 2009; Luo and Chen, 2012)). Studies have

examined IL-4-mediated alternative activation and IL-10-mediated acquired deactivation

in vitro, often after pre-treating microglia with a classical-activating stimulus such as LPS

(Qian et al., 2006; Won et al., 2013; Zhao et al., 2006). Very few studies have directly

compared IL-4 and IL-10 treatment, and the most extensive gene expression comparison

suggests that IL-10 outcomes resemble LPS in murine microglia (Chhor et al., 2013).

Moreover, there is evidence that IL-10 can be elevated very early in models of ischemia

and intracerebral hemorrhage (Fouda et al., 2013; Wasserman et al., 2007) and that

microglia can initially undergo alternative activation and then progress to classical

activation in vivo (Hu et al., 2012).

In comparing gene induction by IL-4 and IL-10 treatment of isolated rat microglia, some

differences are expected because their signalling pathways diverge. Both cytokines can

signal through Jak1 kinase, but key downstream transcription factors are STAT6 for IL-4,

and STAT3 for IL-10 (reviewed in (Colton, 2009; Ouyang et al., 2011)). IL-4-induced

changes in gene expression have been better characterized than responses to IL-10. IL-4

up-regulates hallmark molecules of alternative activation (e.g., Arg1, MRC1) in murine

microglia (reviewed in (Colton, 2009)), and rat microglia (Liu et al., 2013; Lively and

Schlichter, 2013). Here, up-regulated genes were compared at 6 hr after IL-4- or IL-10-

treatment in rat microglia that were mainly migratory and unipolar with a lamellum and a

uropod. Some genes were specific to each cytokine treatment and some were shared. IL-4

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treatment selectively increased MRC1, Arg1, CD163, TGFβ1, c-myc, TLR4, and

decreased TLR2. IL-10 treatment selectively increased CD11b, IL-6, IL-1ra, TLR2, and

Hsp32 (heme oxygenase-1) at 6 hr, but not IL-1β or iNOS. Both cytokines up-regulated

expression of ED1, TIMP1, and the transcription factors, STAT6 and Nrf2, which

potentially contribute to the gene changes they evoked in common. Despite IL-4 and IL-

10 being considered anti-inflammatory cytokines, evidence that they can evoke different

gene expression profiles includes some IL-10 responses that are similar to pro-

inflammatory stimuli (e.g., LPS) but on a reduced scale. IL-10 up-regulated IL-1β and

iNOS by 6 hr, and by 12 hr IL-6 was also increased in murine microglia (Chhor et al.,

2013; Michelucci et al., 2009).

Microglia are migratory in the developing CNS, and while migration is limited in the

healthy adult, it is prevalent after acute CNS injury (reviewed in (Harry, 2013;

Kettenmann et al., 2011). Having observed extensive microglial relocation to the injury

site after intracerebral hemorrhage (Moxon-Emre and Schlichter, 2011; Wasserman and

Schlichter, 2008), ischemia (Moxon-Emre and Schlichter, 2010), optic nerve damage

(Kaushal et al., 2007; Koeberle and Schlichter, 2010), and spinal cord injury (Bouhy et

al., 2011), we realized that invasion through brain tissue will require ECM degradation.

Thus, it is notable that microglial migration and invasion were increased by both IL-4 and

IL-10 treatment, while migration of LPS-treated cells was decreased (Lively and

Schlichter, 2013); present study). In addition, differences were seen in expression of

ECM-degrading enzymes depending on the microglial activation state. IL-4 selectively

increased cathepsin S, IL-10 increased MMP14 and cathepsin L1, while both cytokines

increased cathepsins B and D. The IL-10 response was similar to the earlier study using

LPS, in which MMP14 and cathepsin L1 were increased (Lively and Schlichter, 2013).

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While IL-10 increased migration of neutrophils (Mashimo et al., 2008) and dendritic cells

(Lindenberg et al., 2013) invasion was not examined in those studies.

Podosomes are thought to be important for migration, invasion and ECM degradation

(Linder et al., 2011; Murphy and Courtneidge, 2011), and we previously found that

reducing podosome numbers reduced migration and invasion of unstimulated rat

microglia (Siddiqui et al., 2012). Therefore, we hypothesized that the differing migration

and invasion capacities of microglia and their dependence on ion channels would

correspond with podosome expression. Consistent with the hypothesis, LPS-treated

microglia were not migratory and had few if any podosomes; and conversely, blocking

KCa2.3 did not reduce podosome expression, migration or invasion in the other

activation states. In contrast, IL-10 increased podosome prevalence but IL-4 did not; and

while migration and invasion of IL-4 and IL-10-treated cells was substantially inhibited

by blocking TRPM7 channels, there was little to no effect on podosome expression. This

is consistent with our earlier study showing that the TRPM7 inhibitor, spermine, did not

affect podosome expression (Siddiqui et al., 2012). One possibility is that the substantial

basal level of podosomes in unstimulated microglia is sufficient to support migration and

the ECM-degradation needed for invasion.

The KCa2.3 channel is present in lamellipodia and filopodia of neural progenitor cells

(Liebau et al., 2007), facilitates migration of some cancer cells (Chantome et al., 2009;

Jelassi et al., 2011; Potier et al., 2006), and is being considered as a therapeutic target for

cancer (Potier et al., 2011). In breast cancer cells, KCa2.3 can be activated by Ca2+ influx

through Ca2+-release-activated Ca2+ (CRAC) channels, which increases migration

(Chantome et al., 2013). Having discovered that microglial podosomes are enriched in

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KCa2.3 and Orai1 (the pore-forming subunit of CRAC), and that inhibiting Ca2+ entry

reduces podosomes and migration (Siddiqui et al., 2012); we expected that blocking

KCa2.3 channels would inhibit their migration and invasion. Instead, migration of

unstimulated rat microglia was moderately increased by the blockers, apamin and

tamapin, suggesting that KCa2.3 activity is inhibitory; while these blockers had no effect

on IL-4- or IL-10-treated cells. Invasion was not affected by blocking KCa2.3 (with

apamin) under any of the three activation conditions. NS8593 reliably inhibited KCa2.3

current in microglia and MLS-9 cells, as previously reported for cloned KCa2.3 channels

(Strobaek et al., 2006). In contrast to apamin and tamapin, NS8593 reduced microglial

migration after IL-4- or IL-10-treatment and invasion under all three activation

conditions. A KCa2.3 current was detected in fewer than 25% of primary microglia; thus,

we also tested migration of MLS-9 microglial cells, which robustly expressed KCa2.3

currents (Liu et al., 2013); present study). KCa2.3 block by apamin or tamapin did not

affect MLS-9 cell migration but NS8593 did.

The discrepancy between effects of NS8593 with those of apamin or tamapin prompted

us to investigate the role of TRPM7 channels, which were recently found to be inhibited

by NS8593 (Chubanov et al., 2012). NS8593 very effectively inhibited the TRPM7

current in microglia, and functional studies indicate that the channel is important for

microglia in anti-inflammatory states. That is, both NS8593 and another TRPM7

inhibitor, AA-861 (Chen et al., 2010), reduced migration of IL-4- and IL-10-treated

microglia but not unstimulated microglia. Both TRPM7 inhibitors reduced microglial

invasion under all three activation conditions. TRPM7 is a Ca2+-permeable channel that is

ubiquitously expressed and implicated in several homeostatic cellular functions,

including divalent cation regulation, cell survival and proliferation (reviewed in (Asrar

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and Aarts, 2013; Bates-Withers et al., 2011; Park et al., 2014). In the CNS, TRPM7 was

first discovered in microglia (Jiang et al., 2003), and more recently has been proposed as

a therapeutic target to reduce neurodegeneration after stroke (Aarts and Tymianski,

2005). There is evidence that TRPM7 is involved in migration, especially in cancer cells

(reviewed in (Fiorio Pla and Gkika, 2013) and highly migratory fibroblasts (Wei et al.,

2009). TRPM7 can respond to membrane stretch and mediate localized Ca2+ entry at the

leading edge of migrating fibroblasts (Wei et al., 2009) and neuroblastoma cells (Visser

et al., 2013). It can interact with cytoskeletal components (Clark et al., 2006; Clark et al.,

2008) to modulate actomyosin contractility that is required for cell migration (Su et al.,

2006). Over-expressing TRPM7 in a neuroblastoma cell line facilitated cell adhesion and

formation of podosomes (Clark et al., 2006) and invadosomes (Visser et al., 2013), and

inhibiting TRPM7 reduced migration of activated T cells (Kuras et al., 2012). TRPM7

whole-cell currents were of similar amplitude in unstimulated microglia and after

treatment with LPS or a phorbol ester (Jiang et al., 2003), as well as IL-4 or IL-10

(present study); however, the channel is regulated by several mechanisms that might

affect the current in intact cells. These include intracellular Mg2+ (Bae and Sun, 2013;

Chubanov et al., 2012; Demeuse et al., 2006), Src tyrosine kinase (Jiang et al., 2003),

protein kinase A (Takezawa et al., 2004), phosphatidylinositol 4,5-biphosphate (PIP2)

(Runnels et al., 2002), and others (reviewed in (Penner and Fleig, 2007). It might be that

TRPM7 is preferentially activated in intact microglia to increase their migration and

invasion capacity after IL-4 or IL-10. For instance, IL-4 signalling can activate

phosphatidylinositide 3-kinase and the Src-family tyrosine kinase, Fes (Jiang et al.,

2000).

NS8593, and several other commonly used activators and inhibitors of KCa2.1–2.3

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channels are potent inhibitors of TRPM7 channels (Chubanov et al., 2012). The

overlapping pharmacological profiles emphasize the need to consider off-target effects on

TRPM7 when using these compounds in functional studies. The microglial activation

state appears to strongly influence migration and invasion. LPS-treated, classical-

activated rat microglia migrated very poorly, while IL-4-treated (alternative-activated)

cells migrated and invaded much better than unstimulated microglia, as did microglia in

an acquired deactivation state induced by IL-10. If highly migratory microglial cells are

maintained in anti-inflammatory states, this might reduce bystander damage while they

migrate in the developing CNS and to injury sites after brain damage or disease. The

present results also suggest that the selective contribution of TRPM7 to

migration/invasion of microglia in the anti-inflammatory state should be considered in

the current effort to develop TRPM7 inhibitors for CNS disorders.

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Chapter 4. Complex molecular and functional outcomes of

single versus sequential cytokine stimulation of rat microglia

4.1. Introduction

Phagocytosis is crucial during CNS development and in the healthy adult, to both

promote and maintain appropriate synaptic connections and homeostasis. After CNS

injury or disease, phagocytosis is crucial for clearing cellular debris, including

degenerated myelin after acute injury or degenerative diseases, such as multiple sclerosis.

For CNS repair to occur, myelin debris must be rapidly removed because it inhibits

differentiation of oligodendrocyte precursor cells and remyelination, and promotes

formation of membrane attack complexes that further damage myelin (Gitik et al., 2011;

Hadas et al., 2012; Sierra et al., 2013). Microglia are the ‘professional’ phagocytes of the

CNS. In vitro studies have addressed the microglial phagocytic capacity for plastic beads,

bacteria, apoptotic cells, red blood cells, and less often, myelin. Little is known about the

relationship between microglial activation states, myelin phagocytosis and ROS

production, and conversely, how myelin phagocytosis affects microglial activation states.

Furthermore, it is not known how sequentially exposing microglia to M1- versus M2-

inducing cytokines affects their activation state, phagocytic capacity or ROS production.

We hypothesized that microglial activation affects myelin phagocytosis and consequent

ROS production, and that activation can be ‘re-polarized’. We began by comparing

unstimulated, M1- and M2-activated rat microglia, quantifying myelin phagocytosis,

ROS production, and expression of inflammatory mediators and receptors/enzymes

related to phagocytosis and ROS production. Then, we examined how all these responses

were affected by applying an M1 stimulus followed by an M2 stimulus, and vice versa.

Microglia showed unique responses depending on cytokine stimulation. Finally, we show

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novel regulation of myelin phagocytosis and associated ROS production by CRAC and

Kir2.1 channels, but not Kv1.3 or SK4.

4.2. Results

Myelin phagocytosis affects the activation state of primary rat microglia

When unstimulated (control) microglia were exposed to 25 µg/mL of myelin debris for 6

h, myelin was seen mainly in the perinuclear region, with a small amount in other cell

regions (Fig. 4.1A). We then examined expression of over two dozen genes to create a

profile of microglial responses to the activating stimuli and to myelin debris. Previously,

by assessing several well-known inflammatory genes, we found that unstimulated rat

microglia were in a relatively resting state (Liu et al., 2013; Lively and Schlichter, 2013;

Sivagnanam et al., 2010). This was confirmed, based on very low expression of well-

established pro-inflammatory (M1) molecules (NOS2/iNOS, TNF-α, COX-2, IL-6), and

of some markers of ‘alternative’ (M2) activation (CD163, CCL22). Two M2-associated

molecules, c-myc and MRC1 were expressed at moderate levels, and MRC1 expression

was similar to our recent study (Ferreira et al., 2014). When unstimulated cells were

allowed to phagocytose myelin for 6 h, none of these markers changed significantly (Fig.

4.1B).

The same inflammatory markers were quantified after microglia were treated with

cytokines to evoke two different activation states; and again, after myelin phagocytosis

(Fig. 4.1B, C). Previously validated M1 markers included increased NOS2, COX-2, IL-6,

and a loss of M2a markers (Chhor et al., 2013). Here, classical (M1) activation was

evoked by 24 h treatment with a combination of IFN-γ and TNF-α (which we call ‘I+T’).

As expected, there was a dramatic increase in expression of pro-inflammatory molecules

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(NOS2, TNF-α, COX-2); IL-6 increased to a lesser degree. Conversely, IL-4 (M2a,

alternative activation) increased expression of several M2-associated molecules (MRC1,

CD163, c-myc, CCL22). Interestingly, while Iba1 expression increased in the M1 state

and decreased in the M2 state, it was robustly expressed under all conditions (Fig. 4.1C),

and is thus not strictly an activation marker.

Microglia were treated with cytokines (as above), exposed to myelin for a further 6 h, and

gene expression was again quantified. After myelin phagocytosis, M1-polarized

microglia showed increased expression of some pro-inflammatory molecules (TNF-α, IL-

6). In M2a-polarized microglia, phagocytosis decreased several genes associated with

alternative activation (MRC1, CD163, c-myc). Overall, these results suggest that myelin

can rapidly exacerbate some pro-inflammatory responses of M1-polarized microglia and

reduce M2a polarization.

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Figure. 4.1. Effects of microglial activation state and exposure to myelin on

inflammatory gene expression.

A Myelin phagocytosis. Representative images showing myelin fragments inside primary

rat microglia at 6 h after adding 25 μg/mL DiI-labeled myelin (red). Microglia were co-

labeled with tomato lectin (TL, green) and the nuclear stain, DAPI (blue). Scale bar, 10

μm. Short arrows show peri-nuclear accumulation of myelin; long arrows show myelin in

other cell regions. B, C Gene expression of inflammatory markers (B) and “ionized Ca2+

binding adapter molecule 1” (C; Iba1; also known as AIF-1). Microglia were

unstimulated (control, CTL) or stimulated for 24 h with 20 ng/mL IFN-γ and 50 ng/mL

TNF-α (I + T) or 20 ng/mL IL-4, with or without a subsequent 6-h exposure to 25 μg/mL

myelin (30 h total time after cytokine addition; plus or minus sign indicates

presence/absence of myelin). Expression of each gene is shown as normalized mRNA

counts (described in the “Methods” section). On the scatterplots, the mean ± SEM is

indicated for six different microglia cultures. Data were analyzed by two-way ANOVA

with Bonferroni’s post hoc test. The comparisons are as follows. Asterisk Between

unstimulated microglia (CTL) and cells treated with I + T or IL-4. Dagger sign CTL

versus activated cells in the presence of myelin. Number sign Effects of myelin within a

particular activation state. One symbol p < 0.05, two symbols p < 0.01, three symbols

p < 0.001. Nanostring analysis performed by Starlee Lively

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The microglial activation state affects myelin phagocytosis and expression of

phagocytosis-related molecules

It is very difficult to quantify phagocytosis in vivo, thus many studies use surrogate

phagocytosis ‘markers’ such as the glycoprotein, CD68 (ED1) (Sierra et al., 2013). Here,

we compared expression of a panel of phagocytosis-related molecules in untreated, M1-

and M2a-activated microglia (Fig. 4.2A). The molecules were chosen for the following

reasons. To phagocytose myelin in vitro, microglia primarily use the scavenger class A

receptor (SR-A), CR3 (also called αMβ2, and comprised of CD11b and CD18), and

immunoglobulin Fc gamma receptors (if anti-myelin antibodies are present) (Hadas et al.,

2012; Sierra et al., 2013; Smith, 2001). We quantified expression of SR-A, FcγRIa,

FcγRIIb, FcγRIIIa, and CD11b. FcγRIa (CD64) and FcγRIIIa (CD16) stimulate

phagocytosis; whereas, FcγRIIb (CD32) is inhibitory (Linnartz et al., 2010), as is SIRPα

(CD172a), which interacts with CD47 ligand on myelin (Gitik et al., 2011). CD68 and

CR3 are often used as general markers of microglial activation because their staining

intensity increases after CNS injury (Fu et al., 2014; Kettenmann et al., 2011; Schlichter

et al., 2014; Taylor and Sansing, 2013). C1r is an essential protease that initiates the

classical complement pathway to opsonize particles with complement proteins for

targeted phagocytosis (Sarma and Ward, 2011). Nucleotides released by damaged cells

act as ‘find-me’ signals for phagocytes, and UDP acts on metabotropic P2Y6 receptors to

facilitate phagocytosis. This receptor is up-regulated in microglia in response to dying

neurons (Fu et al., 2014; Koizumi et al., 2007). Recently, TREM2, CX3CR1 and TIM-3

have been added to the list of receptors involved in microglial phagocytosis. TREM2

senses lipid components of damaged myelin, is required for debris clearance, and is

mainly expressed on microglia (Poliani et al., 2015). In the CNS, CX3CR1 is expressed

exclusively by microglia and perivascular macrophages (Cardona et al., 2006), and is

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required for effective clearance of myelin debris (Lampron et al., 2015). TIM-3 is present

in human microglia that are specifically localized to white matter (Anderson et al., 2007).

LPS increases TIM-3 expression in murine microglia, and blocking its activity decreases

their phagocytosis of apoptotic neurons (Wang et al., 2015).

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Figure. 4.2. Effects of microglial activation state on expression of phagocytosis-

related molecules, phagocytosis, and ROS production.

A Phagocytosis-related genes. Microglia were unstimulated (control, CTL) or stimulated

for 24 h with 20 ng/mL IFN-γ + 50 ng/mL TNF-α (M1 activation state) or 20 ng/mL IL-4

(M2a state), with or without a subsequent 6-h exposure to 25 μg/mL myelin (plus or

minus sign indicates presence/absence of myelin), as in Fig. 4.1A. Values are expressed

as normalized mRNA counts (described in the “Methods” section), mean ± SEM (six

different cell cultures), and were analyzed by two-way ANOVA with Bonferroni’s post

hoc test. B. Phagocytosis of myelin fragments. Microglia were exposed for 6 h to 25

μg/mL DiI-labeled myelin, and the amount of internalized myelin was determined in

unstimulated (CTL), M1 (I + T), M2a (IL-4), and M2c (20 ng/mL IL-10)-stimulated

microglia. Results were normalized to control microglia (dashed line) to determine

activation state-dependent changes. Data are expressed as mean ± SEM (20 individual

cultures) and were analyzed by one-way ANOVA with Dunnett’s post hoc test. C.

Production of reactive oxygen species (ROS). Intracellular ROS was monitored with the

general ROS probe, dichlorofluorescein (DCF), and normalized to DCF levels in

unstimulated (CTL) microglia without myelin (dashed line). Data were analyzed by two-

way ANOVA with Bonferroni’s post hoc test (n = 19 individual cultures). The

comparisons are as follows. Asterisk Between unstimulated microglia (CTL) and cells

treated with I + T, IL-4, or IL-10. Dagger sign CTL versus different activation states in

the presence of myelin. Number sign Effects of myelin within a particular activation

state. One symbol p < 0.05, two symbols p < 0.01, three symbols p < 0.001. Nanostring

performed and analyzed by Starlee Lively.

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(i) In untreated microglia, there was substantial expression (arbitrary cutoff, >5000

mRNA counts/200 ng RNA) of several stimulatory receptors (CD11b, SR-A, FcγRIa,

FcγRIIIa, CD68, TREM2), and the inhibitory receptors, FcγRIIb and SIRPα (Fig. 4.2A).

There was lower expression of C1r, P2Y6, CX3CR1 and TIM-3. (ii) Following I+T (M1)

treatment, three stimulatory receptors increased (C1r, FcγRIIIa, TIM-3) and the

inhibitory receptor, SIRPα, decreased. While this might mean that M1 cells have a higher

phagocytic capacity for a wider range of targets, there were concomitant decreases in the

stimulatory receptors, SR-A, FcγRIa, CD68, TREM2 and CX3CR1. (iii) After IL-4

treatment (M2a state), there were decreases in several stimulatory receptors (CD11b, SR-

A, FcγRIa, CD68, TREM2) and an increase in the inhibitory receptor, FcγRIIb,

suggesting a reduced phagocytic capacity. However, P2Y6 increased and the inhibitory

receptor, SIRPα decreased. Surprisingly, both M1 and M2a activation decreased SR-A,

FcγRIa, CD68, TREM2, and SIRPα.

The complex changes in expression of phagocytosis-related receptors made predictions

difficult. Thus, it was important to next assess whether myelin phagocytosis was affected

by the activation state and conversely, whether myelin affected receptor expression. (i) In

unstimulated microglia, many receptors were unaffected by myelin (CD11b, SR-A,

FcγRIa, FcγRIIb, FcγRIIIa, C1r, TREM2) or slightly decreased (CD68, SIRPα).

However, there were increases in three receptors not known to mediate myelin

phagocytosis: P2Y6, CX3CR1 and TIM-3. (ii) In I+T-treated cells, myelin increased the

stimulatory receptors, P2Y6 and TIM-3, and to a lesser extent, FcγRIIIa and C1r. None

were decreased. (iii) In IL-4-treated cells, myelin increased P2Y6 and CX3CR1, and

although CD68 was slightly decreased, its mRNA counts remained very high.

Interestingly, P2Y6 increased under all three activation states. Overall, effects of myelin

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were modest. (iv) Phagocytosis was unchanged by IL-4 and increased ~20% by I+T (Fig.

4.2B). Here, we also tested IL-10 to represent an M2c phenotype that is thought to

resolve pro-inflammatory states (reviewed in (Colton, 2009; Franco and Fernandez-

Suarez, 2015). We did not examine the molecular profile after IL-10 alone, mainly

because the markers are less clear and some overlap with M1 markers (Chhor et al.,

2013); however the IL-10-evoked increase in phagocytosis was similar to I+T. These

small differences in phagocytosis are very unlikely to account for large differences in

gene expression after exposure to myelin (Fig. 4.2A).

The microglial activation state affects production of reactive oxygen species (ROS) and

expression of ROS-related molecules

Phagocytosis is often accompanied by a considerable ROS production. Thus, we next

compared ROS production in unstimulated (control) microglia and after I+T, IL-4 or IL-

10, with and without myelin phagocytosis (Fig. 4.2C). Without myelin, ROS production

increased in M1 (I+T) and M2a (IL-4) states. Myelin phagocytosis further increased ROS

production in all activation states.

Based on these changes in ROS production, we examined expression of several

molecules related to ROS production. NADPH oxidase enzymes (NOX1–5) are

homologs of NOX2/gp91phox; the catalytic subunit that is present in cell membranes

(Cheng et al., 2001). It was previously reported that primary rat microglia express NOX1,

NOX2 and NOX4, while NOX3 was not detected (Harrigan et al., 2008), and our results

corroborate this (we did not examine NOX3). NOX2 is well-studied, and is largely

responsible for the phagocytosis-induced ROS production (respiratory burst) of microglia

(Bedard and Krause, 2007; Brandes et al., 2014) and other phagocytes (Flannagan et al.,

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2012). Activation of NOX2 at the plasma membrane requires phosphorylation of the

accessory subunit, Ncf1 (neutrophil cytosolic factor 1/p47phox) (Clark et al., 1990; El-

Benna et al., 2009).

NOX2 and Ncf1 were highly expressed in unstimulated rat microglia, increased in M1-

activated cells, and decreased in the M2a state (Fig. 4.3A). Myelin phagocytosis had

minor effects, slightly decreasing NOX2 in the M1 state only. Our results are consistent

with an earlier study of IFN-γ-stimulated microglia showing that myelin phagocytosis

increased ROS production without affecting Ncf1 transcription (Liu et al., 2006). NOX4

is unique in several respects. Its contribution is regulated by transcription without

accessory subunits (Martyn et al., 2006; Serrander et al., 2007), and it is located in

membranes of the ER, nuclear envelope, and mitochondria (Nayernia et al., 2014). We

found that NOX4 expression was extremely low in unstimulated rat microglia, and

increased slightly in the M1 state only. NOX1 can contribute to production of both ROS

and reactive nitrogen species (Cheret et al., 2008), and both are involved in eradicating

pathogens (Flannagan et al., 2012). We found that NOX1 expression was always very

low, was further decreased after I+T or IL-4 treatment, and was not affected by myelin

phagocytosis. Thus, it seems most likely that NOX2 was responsible for the observed

changes in ROS production (Fig. 4.2). The voltage-gated proton channel, Hv1, was also

examined because it can facilitate ROS production by allowing H+ efflux as charge

compensation for NOX-generated electrons (DeCoursey, 2013; Ramsey et al., 2009).

Hv1 was moderately expressed in unstimulated microglia, and increased in the M1 state.

Overall, only the M1 stimulus increased known facilitators of ROS production in

microglia. Myelin phagocytosis further increased Hv1 in unstimulated and M1-activated

cells.

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Figure. 4.3. Expression of ROS-related molecules and contribution of NOX enzymes

to myelin phagocytosis and ROS production.

A. Expression of ROS-related molecules. Rat microglia were stimulated with cytokines

for 24 h with or without a subsequent 6-h exposure to myelin (plus or minus sign

indicates presence/absence of myelin), as in Figs. 4.1a and 4.2a. B. Effect of NOX

inhibition on phagocytosis of myelin fragments. The activation treatments, assay, and

normalization of data were the same as Fig. 4.2B, but now comparing the pan-NOX

inhibitor, 5 μM VAS2870. C. Effect of NOX inhibition on ROS levels in microglia that

were treated as in Fig. 2b. As above, ROS levels were normalized to unstimulated

microglia without myelin (dashed line), data are expressed as mean ± SEM (n = 6

individual cultures), and results were analyzed by two-way ANOVA with Bonferroni’s

post hoc test. The comparisons are as follows: asterisk unstimulated (CTL) versus

different activation states in the absence of myelin, dagger sign unstimulated (CTL)

versus different activation states in the presence of myelin, number sign effects of myelin

(A) or VAS2870 (B,C) within a particular activation state. One symbol p < 0.05, two

symbols p < 0.01, three symbols p < 0.001. Nanostring performed and analyzed by Starlee

Lively.

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We then used the pan-NOX inhibitor, VAS2870 (Wind et al., 2010) to assess overall

contributions of NOX enzymes. The drug was non-toxic. In control cells and in all three

activation states, VAS2870 decreased phagocytosis to below the level of unstimulated

microglia (Fig. 4.3B). Exposure to myelin always increased ROS production (as in Fig.

4.2C), and this was essentially abolished by VAS2870 in all three activated states (Fig.

4.3C). [Statistical comparisons of phagocytosis in different activation states were shown

in Fig. 4.2.]

Attempting to repolarize microglia using sequential cytokine stimulation

To model a changing inflammatory environment, such as can occur after CNS injury (see

Introduction), we used sequential addition of cytokines that induce M1 then M2

activation, and vice versa. The same panel of inflammatory, phagocytosis-related and

oxidative stress-related genes was assessed as in Figures 4.1–3. (i) Microglia were

stimulated with IL-4 followed by I+T, which we refer to as an ‘M2a→M1’ stimulus

paradigm (Fig. 4.4A). Several changes were consistent with I+T skewing (re-polarizing)

them toward an M1 state. Two M2 markers (MRC1, CD163) were dramatically reduced

(to control levels), and three pro-inflammatory mediators (NOS2, TNF-, COX2) were

higher than with IL-4 alone. The cells were not fully re-polarized to M1, as some pro-

inflammatory genes remained lower than with I+T alone: NOS2/iNOS (a 3.6 fold

increase vs 1,444 fold), Iba1 (0.6 vs 1.8 fold), TNF-α (0.8 vs 4.3 fold), and COX-2 (7.1

vs 25.9 fold). Not all genes were affected. The changes in IL-6 and CCL22 were not

different from IL-4 alone. While c-myc was increased in the M2a→M1 stimulus

paradigm, the change was small (3.6 vs 2.5 fold). (ii) In the reverse paradigm, the cells

were first stimulated with I+T, followed by IL-4 or IL-10 (Fig. 4.4B). Secondary IL-4

treatment (M1→M2a paradigm) generally dampened the M1-response and further

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skewed microglia toward an anti-inflammatory M2a state relative to I+T alone. That is,

IL-4 prevented induction of Iba1 and down-regulated several pro-inflammatory

molecules; NOS2 (5.9 vs 1,444 fold), TNF-α (1.0 vs 4.3 fold), IL-6 (1.1 vs 3.1 fold). It

also increased expression of some M2-associated molecules; CCL22 (151 vs 2.1 fold), c-

myc (3.5 vs 0.2 fold), MRC1 (0.9 vs 0.03 fold). Overall, some re-polarization of the

activation state was evident between M1 and M2a. In contrast, secondary IL-10 treatment

(M1→M2c paradigm) failed to reverse any I+T-induced changes, and instead, it

increased expression of NOS2.

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Figure. 4.4. Repolarizing the inflammatory profile of microglia using sequential

cytokine addition.

A. “M2a→M1” stimulus paradigm. Microglia were treated with 20 ng/mL IL-4 for 2 h

followed by 20 ng/mL IFN-γ + 50 ng/mL TNF-α (I + T) for 22 h. B. “M1→M2” stimulus

paradigm. Microglia were treated with I + T for 2 h followed by either IL-4

(“M1→M2a”) or 20 ng/mL IL-10 (“M1→M2c”) for 22 h. Data are expressed as mRNA

counts in 200 ng total RNA (mean ± SEM, n = 6 individual cultures) and were analyzed

by one-way ANOVA with Tukey’s post hoc test. The dashed lines indicate expression

levels in unstimulated (control) microglia. (Some lines are too low to see.) The

comparisons are as follows: asterisk differences from control microglia, number sign

effects of a secondary stimulus on the first stimulus. One symbol p < 0.05, two symbols

p < 0.01, three symbols p < 0.001. Nanostring performed and analyzed by Starlee Lively.

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Next, we examined the same phagocytosis-related (Fig. 4.5) and ROS-related molecules

(Fig. 4.6) as in Figures 4.2 and 4.3. (i) In the M2a→M1 stimulus paradigm (Fig. 4.5A),

there was a dampened response compared with IL-4 alone. Eight out of 12 phagocytosis-

related receptors decreased, including 6 stimulatory receptors (CD11b, SR-A, CD68,

TREM2, CX3CR1, TIM-3) and 2 inhibitory receptors (FcγRIIb, SIRPα). Three

stimulatory receptors were unchanged (FcγRIa, FcγRIIIa, C1r), and only P2Y6 increased.

For ROS-related molecules, Ncf1 increased but the others generally decreased (Fig.

4.6A). (ii) In the M1→M2a paradigm (Fig. 4.5B), compared with I+T alone, there was a

dampened response of several stimulatory receptors (CD11b, FcγRIIIa, CD68, C1r, TIM-

3), the inhibitory receptor, SIRPα, and all ROS-related genes (Fig. 4.6B). Genes that were

unchanged were the stimulatory receptors, SR-A, FcγRIa and TREM2, and the inhibitory

receptor, FcγRIIb. Again, only P2Y6 was increased. (iii) The M1→M2c paradigm did not

dampen responses compared with I+T alone, except for a small decrease in Ncf1 (Figs.

4.5B, 4.6B). Instead, there were increases in 5/17 phagocytosis- and ROS-related

molecules: NOX4, the stimulatory receptors, CD11b, FcγRIIIa and TIM-3, and the

inhibitory receptor, SIRPα. Together, these results indicate substantial repolarization in

the M2a→M1 and M1→M2a paradigms but not the M1→M2c paradigm.

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Figure. 4.5. Sequential cytokine addition affects expression of phagocytosis-related

molecules.

A. M2a→M1 paradigm. Microglia were treated with 20 ng/mL IL-4 for 2 h followed by

20 ng/mL IFN-γ + 50 ng/mL TNF-α (I + T) for 22 h. B. M1→M2 paradigm. Microglia

were treated with I + T for 2 h followed by either IL-4 (M1→M2a) or 20 ng/mL IL-10

(M1→M2c) for 22 h. Data are expressed as mRNA counts in 200 ng total RNA

(mean ± SEM, n = 6 individual cultures) and were analyzed by one-way ANOVA with

Tukey’s post hoc test. The dashed lines indicate expression levels in unstimulated

(control) microglia. The comparisons are as follows: asterisk differences from control

microglia, number sign effects of the second stimulus on the first stimulus. One symbol

p < 0.05, two symbols p < 0.01, three symbols p < 0.001. Nanostring performed and

analyzed by Starlee Lively.

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Figure. 4.6. Sequential cytokine addition affects expression of ROS-associated genes.

A. M2a→M1. Microglia were treated with 20 ng/mL IL-4 for 2 h followed by 20 ng/mL

IFN-γ + 50 ng/mL TNF-α (I + T) for 22 h. B. M1→M2. Microglia were treated with I + T

for 2 h followed by either IL-4 (M1→M2a) or 20 ng/mL IL-10 (M1→M2c) for 22 h.

Data are expressed as mRNA counts in 200 ng total RNA (mean ± SEM, n = 6 individual

cultures) and were analyzed by one-way ANOVA with Tukey’s post hoc test. The dashed

lines indicate expression levels in unstimulated (control) microglia. The comparisons are

as follows: asterisk differences from control microglia, number sign effects of a

secondary stimulus on the first stimulus. One symbol p < 0.05, two symbols p < 0.01,

three symbols p < 0.001. Nanostring performed and analyzed by Starlee Lively.

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The observed changes in expression of phagocytosis- and ROS-related genes led us to

directly examine myelin phagocytosis and ROS production following sequential

treatments with M2 and M1-stimuli. (i) M2→M1: When IL-4 (M2a) or IL-10 (M2c)

treated microglia were subsequently treated with I+T; both phagocytosis and ROS

production increased compared with IL-4 or IL-10 alone (Fig. 4.7A), which suggests

some re-polarization occurred. (ii) M1→M2: In the reverse paradigm (I+T, then IL-4 or

IL-10), phagocytosis was slightly increased by IL-4 (M1→M2a) but not by IL-10

(M1→M2c). ROS production was unchanged compared with I+T alone (Fig. 4.7B). (iii)

Myelin effects: Without myelin, I+T increased ROS and subsequently adding IL-4 or IL-

10 had no further effect; whereas, adding I+T after IL-4 or IL-10 increased ROS

production. Adding myelin always increased ROS production compared with control

cells (no treatment, no myelin). In the presence of myelin, there was some functional re-

polarization from M2a/c→M1 (increased phagocytosis and ROS production). In contrast,

compared with I+T alone; ROS production was not altered by M1→M2a (which slightly

increased phagocytosis) nor M1→M2c (which did not).

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Figure. 4.7. Sequential cytokine addition affects myelin phagocytosis and NOX-

mediated ROS production.

Data are presented as mean ± SEM; n = 12 (A, B), n = 6 (C). Data were normalized to

unstimulated (CTL) microglia (indicated by dashed lines) in the presence of myelin (for

phagocytosis) or without myelin (for ROS production). A. M2→M1. Microglia were first

stimulated with 20 ng/mL IL-4 (M2a) or 20 ng/mL IL-10 (M2c) for 2 h and then with 20

ng/mL IFN-γ + 50 ng/mL TNF-α (I + T; M1) for an additional 22 h. B. M1→M2. I + T

was added for 2 h, followed by IL-4 (M1→M2a) or IL-10 (M1→M2c) for a further 22 h.

For A and B, DiI-labeled myelin (25 μg/mL) was added to cultures 24 h after adding the

first cytokine, and both phagocytosis and intracellular ROS levels were assessed 6 h later

(as in Figs. 4.2B,C and 4.3B,C). C. Effect of NOX inhibition on myelin phagocytosis and

ROS production in microglia that were stimulated as in a and b. Microglia were

incubated with 25 μg/mL myelin for 6 h, with or without the pan-NOX inhibitor, 5 μM

VAS2870. Results were analyzed by a one-way ANOVA (for phagocytosis in a) or a

two-way ANOVA (for ROS and phagocytosis in C) with Bonferroni’s post hoc test. The

comparisons are as follows. Asterisk Differences from unstimulated (CTL) microglia.

Dagger sign CTL versus different activation states in the presence of myelin. Number

sign Differences within (or among) different activation states. Double dagger sign Effects

of myelin (A, B) or VAS2870 (C) within or between activation states. One symbol

p < 0.05, two symbols p < 0.01, three symbols p < 0.001

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NOX enzymes were involved in both myelin phagocytosis and ROS production under

almost all conditions (Fig. 4.7C). That is, the NOX inhibitor, VAS2870, decreased

myelin phagocytosis under all conditions, and decreased ROS production in all

stimulated cells (but not in control cells).

Expression of K+ and CRAC channels, and their contributions to myelin phagocytosis

and ROS production

Rat microglia express several K+ channels, including KCa3.1, Kv1.3 and Kir2.1; as well

as store-operated Ca2+ entry (SOCE) channels. Pore-forming Orai1 and accessory STIM1

subunits form Ca2+-release activated Ca2+ (CRAC) channels, while Orai3 and STIM2 are

also involved in SOCE (Soboloff et al., 2012). We first examined whether expression of

these channels differs in M1 and M2 microglial activation states and whether it is altered

by myelin phagocytosis (Fig. 4.8A). (i) In unstimulated (control) cells, the only change

evoked by myelin was an increase in Kv1.3 expression. (ii) I+T (M1) stimulation

increased expression of all the genes examined (except Orai1); i.e., KCa3.1 (1.8 fold),

Kv1.3 (2.3 fold), Kir2.1 (5.2 fold), Orai3 (2.2 fold), STIM1 (2.2 fold) and STIM2 (1.2

fold) (Fig. 4.8A). In I+T treated cells, myelin phagocytosis increased expression of

KCa3.1, Kv1.3, Orai1 and Orai3. (iii) IL-4 (M2a) stimulation increased expression of

KCa3.1 (2.1 fold) and Kv1.3 (1.6 fold) and decreased STIM2 (by 26%). It did not affect

Kir2.1, Orai1, Orai3 or STIM1. Myelin phagocytosis did not alter any of these genes. (iv)

In the M2a→M1 paradigm (IL-4 then I+T; Fig. 4.8B), all the genes decreased to the

control level or lower, except Kir2.1. (v) In the M1→M2a paradigm (I+T then IL-4; Fig.

4.8C), all the genes (except Orai1) decreased compared with I+T, and were then at or

below the control level. (vi) In the M1→M2c paradigm (I+T then IL-10; Fig. 4.8C), IL-

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10 did not exert the same effects as IL-4. KCa3.1 was slightly elevated compared with

I+T but no other genes were affected.

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Figure. 4.8. Transcript expression of K+ channels and SOCE-related genes is

affected by the microglial activation state and myelin phagocytosis.

A. Single cytokines with or without myelin. Microglia were stimulated for 24 h with 20

ng/mL IFN-γ + 50 ng/mL TNF-α (I + T) or 20 ng/mL IL-4, and then treated with 25

μg/mL myelin for 6 h. B. M2a→M1 paradigm. Microglia were treated with 20 ng/mL IL-

4 for 2 h followed by I + T for 22 h. C. M1→M2 paradigm. Cells were treated with I + T

for 2 h followed by IL-4 (M1→M2a) or 20 ng/mL IL-10 (M1→M2c) for 22 h. All data

are expressed as mRNA counts in 200 ng total RNA (mean ± SEM) for six individual

cultures. Data were analyzed by one-way ANOVA with Tukey’s post hoc test. The

dashed lines in B and C indicate expression levels in unstimulated (control) microglia.

Comparisons are as follows: asterisk differences from control microglia, dagger sign CTL

versus different activation states in the presence of myelin, number sign effects of myelin

within a particular activation state (A) or effects of a second stimulus on the first stimulus

(B and C). One symbol p < 0.05, two symbols p < 0.01, three symbols p < 0.001.

Nanostring performed and analyzed by Starlee Lively.

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A panel of ion-channel blockers was used to assess their involvement in myelin

phagocytosis and ROS production. Blocking KCa3.1 (Fig. 4.9A) or Kv1.3 (Fig. 4.9B) did

not alter myelin phagocytosis or ROS production under any activation state tested.

Blocking Kir2.1 had no effect on control cells (Fig. 4.9C) but it abolished the increase in

phagocytosis under all activation paradigms. Most striking was that whenever I+T was

present, Kir2.1 block reduced the myelin-induced increases in ROS production. CRAC

channel inhibition greatly decreased myelin phagocytosis under all activation paradigms

(Fig. 4.9D). ROS production was also reduced, except in control and IL-10-treated cells,

where the CRAC blocker showed a trend toward a decrease that did not reach statistical

significance. However, the myelin-stimulated ROS component was relatively small under

these conditions and there was less likelihood of seeing a blocker effect. There appear to

be multiple components of total ROS production: a background component (without

myelin) and one that was stimulated by myelin phagocytosis under all conditions (Fig.

4.2C), as well as a component that was not reduced by the NOX inhibitor (Fig. 4.3C). In

principle, channel blockers could reduce ROS by affecting any component. Overall,

expression of all four ion channels was affected by the activation state, but only Kir2.1

and CRAC channels were involved in myelin phagocytosis and the consequent

respiratory burst.

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Figure. 4.9. Roles of K+ and CRAC channels in myelin phagocytosis and ROS

production.

Microglia were stimulated for 24 h (as in Fig. 4.8), and then a channel blocker was added

with or without myelin for a further 6 h. The panels show single stimuli, as well as

M2a→M1 (left), M2c→M1 (middle), and both M1→M2a and M1→M2c (right). A.

KCa3.1 inhibition using 1 μM TRAM-34. B. Kv1.3 inhibition using 5 nM Agitoxin-2

(AgTx-2). C. Kir2.1 inhibition using 20 μM ML133. D. CRAC inhibition using 10 μM

BTP2. Graphical data are expressed as mean ± SEM (n = 6 individual cultures) and were

analyzed by a two-way ANOVA with Bonferroni’s post hoc test. The dashed lines

indicate levels in unstimulated microglia with myelin. Comparisons are as follows:

asterisk differences from control microglia, dagger sign CTL versus activation states in

the presence of a channel inhibitor, number sign effect of a second stimulus on activated

microglia, double dagger sign effect of a channel inhibitor within treatment group. One

symbol p < 0.05, two symbols p < 0.01, three symbols p < 0.001

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4.3. Discussion

This study used gene profiling and functional analyses to examine relationships between

microglial activation states, myelin phagocytosis and ROS production, and the role of

selected ion channels in these processes. Because the treatments and outcomes examined

were complex, for clarity in comparing with previous studies, the salient findings will be

discussed under four topics: 1) outcomes of single stimuli used to polarize microglia to

different activation states; 2) effects of myelin phagocytosis on their activation state; 3)

attempts to re-polarize microglial activation; and 4) expression and contributions of the

ion channels in different activation states.

Effects of single stimuli

The first step was to validate the procedures used to stimulate primary rat microglia. In

agreement with well-known markers (Cherry et al., 2014; Colton, 2009; Franco and

Fernandez-Suarez, 2015; Hanisch, 2013), we found that IFN-γ combined with TNF-α

(I+T) induced a pro-inflammatory M1-like state; while IL-4 induced an anti-

inflammatory (M2a) state. Thus, the cytokine concentrations we used were effective in

changing the molecular inflammatory profile, as measured at 24 h.

It is expected that phagocytosis by activated microglia will depend on the target, whether

it is opsonized, and which phagocytosis-related receptors are engaged. For instance, in

the damaged CNS, if extravasation of complement or antibodies occurs, this can engage

CR3 and Fc receptors, respectively. Furthermore, under in vitro conditions, if

complement is present (i.e., if serum in not heat-inactivated) this can greatly promote

myelin phagocytosis (Reichert et al., 2001). We previously showed that unstimulated rat

microglia can phagocytose polymer beads, yeast, and E. coli bacteria (Ducharme et al.,

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2007; Newell and Schlichter, 2005; Sivagnanam et al., 2010), and that E. coli

phagocytosis was robustly increased by LPS and IFN-, separately or in combination

(Sivagnanam et al., 2010). Here, untreated rat microglia robustly phagocytosed myelin,

and this was modestly increased by I+T (M1) and IL-10 (M2c), but not by IL-4 (M2a).

Our results are entirely consistent with an earlier study of rat microglia, in which

stimulation with mouse recombinant IFN-γ, TNF-α or IL-10 (note species mismatch)

increased myelin phagocytosis, but IL-4 did not (Smith et al., 1998). In contrast, IL-4 or

IL-13 stimulation increased phagocytosis of myelin by human microglia (Durafourt et al.,

2012) and of apoptotic cells by rat microglia (Zhao et al., 2015).

We next asked whether there were changes in expression of specific phagocytosis-related

receptors in different activation states. (i) For M1 stimulation, previous reports are

inconsistent, and possibly species dependent. Some changes seen in rat microglia are

expected to increase their phagocytic capacity. Our earlier study found that LPS

increased FcγRIa and FcγRIIIa, while phagocytosis of E. coli increased CR3 and SR-A

(Sivagnanam et al., 2010). The stimulatory phagocytic receptor, FcγRIIIa, is often used

as an M1 marker (Hu et al., 2012; Miron et al., 2013). We found that I+T (M1) increased

FcγRIIIa, as well as TIM-3, which promotes phagocytosis of apoptotic neurons (Wang et

al., 2015). Other changes might dampen the phagocytic capacity but again, there are

possible species differences; e.g., LPS reduced FcγRIIIa in murine microglia (Chhor et

al., 2013). The TREM2 receptor aids in target internalization by microglia (Hsieh et al.,

2009; Takahashi et al., 2005). We found that I+T dramatically decreased TREM2 in rat

microglia; however, LPS increased it in murine microglia (Schmid et al., 2002).

Fractalkine (CX3CL1) is an important chemotactic signal released by apoptotic cells

(Noda et al., 2011) but in rat microglia, LPS decreased its receptor, CX3CR1 (Boddeke et

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al., 1999), as did I+T in the present study. Based on the changes we observed with M1

stimulation (and lack of changes in FcRIIb, CD11b, P2Y6) we suggest that the most likely

contributors to increased myelin phagocytosis were the reduced inhibitory SIRPα signal,

and a known increase in the ability of CR3 to bind targets under pro-inflammatory

conditions (Freeman and Grinstein, 2014). Despite the increase in FcγRIIIa, it is not

likely involved. It binds to the Fc component of antibodies but antibody-mediated

opsonization of the myelin debris should not occur because the culture medium contained

heat-inactivated serum. (ii) For M2 stimulation, published data on phagocytosis-related

receptors are very limited and, again, there might be species differences. For rat

microglia, we found that IL-4 treatment (M2a) increased expression of the inhibitory

receptor, FcγRIIb, and substantially decreased CD11b, SR-A, CD68 and TREM2 (no

changes in SIRPα, TIM-3). For murine microglia, IL-4 did not change FcγRIIb (CD32)

expression (Chhor et al., 2013). Surprisingly, CD68 expression decreased in both M1 and

M2a microglia, and after myelin phagocytosis by unstimulated cells. CD68 is commonly

used to identify activated, phagocytic microglia (Fu et al., 2014; Kettenmann et al., 2011;

Schlichter et al., 2014; Taylor and Sansing, 2013). Together, these results suggest that

changes in receptor expression are not reliable predictors of the degree of myelin

phagocytosis. Instead protein levels and modulation might be more important. For

instance, CR3 can potentiate or inhibit myelin phagocytosis depending on its

conformation (Reichert et al., 2001). Although the changes we observed suggest a less

phagocytic phenotype in the M2a state, myelin phagocytosis was comparable to untreated

microglia. Of course, effects on phagocytosis of other targets after CNS damage (e.g.,

apoptotic neurons, cell debris, infiltrating blood cells) might differ by involving different

receptors.

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Phagocytosis is associated with elevated NOX-mediated ROS production to help kill

engulfed pathogens (Bedard and Krause, 2007; Brandes et al., 2014). It was previously

reported that untreated rat microglia robustly express the NOX2 isoform, with much

lower NOX1 and NOX4 levels, and undetectable NOX3 (Harrigan et al., 2008). Our

results confirm this pattern and extend it to the M1 and M2a states. (i) Increased ROS

production is a hallmark of M1 activation (reviewed in (Hanisch, 2013), and we found

that it was increased in I+T-treated microglia. NOX2 was likely responsible because

expression of both NOX2 and its regulatory subunit, Ncf1, were increased to very high

levels; while NOX1 and NOX4 remained at very low levels. (ii) IL-4 slightly increased

ROS production while IL-10 had no effect, and this is consistent with our recent report

(Ferreira et al., 2015). IL-4 decreased expression of NOX2 and did not change Ncf1;

however, both remained at moderate levels and could account for the ROS production.

Effects of myelin phagocytosis

There is some evidence that myelin phagocytosis can affect the M1 activation state.

Effects are potentially time dependent, and negative self-regulation might protect the

cells from “overeating” during extended exposures to targets (Hadas et al., 2012). When

murine microglia were stimulated with IFN-γ or LPS, a short exposure to myelin (≤6 h)

exacerbated the pro-inflammatory response (Liu et al., 2006), while longer exposures

(16–24 h) dampened this response (Kroner et al., 2014; Liu et al., 2006). Using the short

exposure time (6 h), which was sufficient for optimal myelin uptake (see Methods); we

found little effect on the molecular profile of unstimulated rat microglia, measured at 24

h. In contrast, myelin increased expression of pro-inflammatory cytokines in M1 (I+T-

treated) rat microglia. This is consistent with the previous short-exposure study (Liu et

al., 2006). In IL-4-treated cells, myelin reduced several M2a-associated molecules. These

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results suggest that myelin can skew activated rat microglia toward a pro-inflammatory

state.

Because levels of phagocytosis-related receptors were not well predicted by the

microglial activation state (above); it was important to ask whether they were altered by

exposure to myelin debris. In unstimulated microglia, myelin slightly decreased SIRPα

and considerably increased CX3CR1 and P2Y6, which are all expected to promote

phagocytosis, especially of apoptotic cells. (i) In I+T-treated (M1) cells, myelin did not

alter expression of receptors known to be involved in myelin phagocytosis (CD11b, SR-

A, TREM2, CX3CR1, SIRPα). Instead, it increased P2Y6, FcγRIIIa, C1r and TIM-3, and

slightly decreased FcRIIb; changes that could promote phagocytosis of other targets. (ii)

In IL-4-treated (M2a) cells, myelin greatly increased CX3CR1, and slightly increased

P2Y6. CD68 was slightly decreased and CD11b or SR-A were unchanged. Interestingly,

CX3CR1 (Arnoux and Audinat, 2015) and P2Y6 (Fu et al., 2014) promote microglial

migration toward damaged cells, and we previously found that M2a-activated rat

microglia migrate better (Lively and Schlichter, 2013). Thus, exposure to myelin debris

might further potentiate the migratory capacity of M2a-activated microglia.

Myelin phagocytosis increases ROS production by unstimulated microglia (Liu et al.,

2006; Smith et al., 1998). We confirmed this and showed that the myelin-evoked ROS

production required NOX activity under all activation conditions tested (I+T, IL-4, IL-

10). Myelin did not affect expression of NOX enzymes, but it increased expression of the

proton channel, Hv1, which could contribute to the increased ROS production seen in

unstimulated and M1-activated cells. Moreover, myelin binding to Mac1 (CD11b) can

activate NOX2 and promote ROS generation (Chen et al., 2015a). Interestingly,

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inhibiting NOX activity reduced myelin phagocytosis under all activation conditions

tested. While we do not know the mechanism, an earlier study of rat macrophages

suggested that NOX-mediated ROS production promotes signalling mechanisms involved

in myelin phagocytosis (van der Goes et al., 1998).

Sequential cytokine stimulation

After acute CNS injury, the inflammatory milieu changes over time (Hanisch and

Kettenmann, 2007; Prinz and Priller, 2014). However, whether microglial activation

states are functionally plastic is poorly understood. It is important to determine if, once

polarized, they can respond to new signals. Based on the few studies that have addressed

time-dependent changes in the overall inflammatory state in vivo, the outcome might

depend on the type of injury. In the cuprizone-induced demyelination model, an overall

M1 state gave way to an M2a phenotype at the time of re-myelination (Miron et al.,

2013). In the first week after intracerebral hemorrhage, we observed concurrent elevation

of pro- and anti-inflammatory mediators (Lively and Schlichter, 2012; Wasserman et al.,

2007). However, after cerebral ischemia or traumatic brain injury, murine microglia

exhibited an early M2 state, followed by M1 (Hu et al., 2012; Wang et al., 2013). An in

vitro study of rat microglia found that adding IL-4 (M2a) before LPS (M1) decreased

expression of the M1-associated molecules, COX-2, iNOS, and TNF-α compared with

LPS alone (Kitamura et al., 2000). Similarly, in mixed rat glial cell cultures, simultaneous

addition of LPS and IL-4 (or IL-10; M2c) reduced IL-6, TNF-α, and NO production,

compared with LPS alone (Ledeboer et al., 2000). Both studies assessed pro-

inflammatory mediators only. For murine microglia, when LPS was followed by IL-4,

NOS2 and COX-2 expression decreased, while CD206 and Arg1 (M2a markers)

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increased compared with LPS alone (Chhor et al., 2013; Fenn et al., 2012). The present

study greatly extends these previous reports.

We examined effects of sequential addition of M1- and M2-inducing cytokines on: the

inflammatory profile, expression of phagocytosis-related receptors and ROS-related

molecules, and on myelin phagocytosis and consequent ROS production. We employed

four sequential treatment paradigms that address the possibility that the cytokine profile

changes after injury or disease. The most convincing re-polarization of the inflammatory

state was between I+T and IL-4 treatments, applied in both sequences. (i) M1→M2a

paradigm. In I+T-primed microglia, adding IL-4 dampened the pro-inflammatory profile

(NOS2, TNF-, IL-6, COX-2) and increased M2a markers (MRC1, c-myc, CCL22). This

is entirely consistent with previous studies using LPS and IL-4 (cited above). The

relationship of phagocytosis and ROS production to expression of receptors and enzymes

phagocytosis- and ROS-related molecules was complicated and sometimes, unexpected.

Although myelin phagocytosis was increased, several phagocytosis-promoting receptors

decreased (CD11b, FcγRIIIa, CD68, C1r, TIM-3), compared with I+T alone. Among the

inhibitory receptors, SIRPα decreased and FcRIIb was unchanged. Thus, the decrease in

SIRP might have promoted phagocytosis. Despite the lack of change in ROS production,

ROS-related molecules decreased (NOX enzymes, Ncf1, Hv1), suggesting that the

remaining levels were sufficient. (ii) M2a→M1. In IL-4-treated cells, adding I+T

skewed them toward an M1 profile. There was increased expression of most pro-

inflammatory molecules (NOS2, TNF-, COX-2), decreases in some M2 markers (MRC1,

CD163), and increased myelin phagocytosis and ROS production. The outcome might

depend on the exact stimulus paradigm and target type. For instance, we observed some

changes in receptor expression that are expected to promote phagocytosis: an increase in

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P2Y6 and decreases in the inhibitory receptors, FcRIIb and SIRPα. Most phagocytosis-

promoting receptors decreased, particularly CD11b, TREM2, CD68, TIM-3 and

CX3CR1. (iii) M1→M2c. In I+T-primed cells, adding IL-10 did not resolve the pro-

inflammatory state and, surprisingly, it increased iNOS/NOS2 expression. While

expression of several phagocytosis-related receptors increased (CD11b, FcγRIIIa, TIM-

3), SIRPα increased slightly, while phagocytosis and ROS production were unchanged.

(iv) M2c→M1. In IL-10-treated cells, adding I+T increased myelin phagocytosis and

ROS production (gene changes were not examined, as explained above).

Overall, our results show malleability in re-polarization of rat microglia between M1 and

M2a states. Their qualitative ability to respond to a new incoming signal was preserved

but their quantitative response was often reduced. The amount of re-polarization could

well depend on the experimental paradigm (cytokine concentrations, time course). For

instance, although we did not observe resolution of M1 activation by IL-10, it is possible

that the time course of treatment or monitoring was not optimal. In future, in vivo spatial

and temporal changes in the cytokine environment will need to be examined in each

damage/disease model, to further examine the re-polarization capacity of microglia.

Expression and contributions of ion channels

Ion channels regulate numerous processes in cells that are relevant to phagocytosis,

including cell volume, Ca2+ signalling, and cytoskeletal re-organization (Schwab et al.,

2012). Microglia express a surprisingly large array of ion channels, some of which are

involved in proliferation, migration, and Ca2+ signalling (reviewed in (Kettenmann et al.,

2011; Stebbing et al., 2015). Very little is known about roles of channels in phagocytosis

by microglia; particularly in different activation states. We previously found that Cl-

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channels regulate phagocytosis of E. coli by rat microglia (Ducharme et al., 2007).

Phagocytosis is a Ca2+-dependent process that involves store-operated Ca2+ entry (SOCE)

(Heo et al., 2015; Michaelis et al., 2015). The Ca2+ release activated Ca2+ (CRAC)

channel is apparently the major SOCE pathway in rat microglia (Ferreira and Schlichter,

2013; Lam and Schlichter, 2015; Ohana et al., 2009; Siddiqui et al., 2012). Interestingly,

CRAC can be activated by P2Y6 and other G protein-coupled metabotropic receptors, and

we found that phagocytosis of myelin debris increased P2Y6 expression under all

activation states examined. We then focused on CRAC and three K+ channels (KCa3.1,

Kir2.1, Kv1.3) that are thought or known to regulate Ca2+ entry. In rat microglia, KCa3.1

and Kir2.1 regulate CRAC-mediated Ca2+ influx (Ferreira et al., 2014; Ferreira and

Schlichter, 2013; Lam and Schlichter, 2015), and Kv1.3 is involved in ROS production

(Fordyce et al., 2005; Khanna et al., 2001). CRAC channels are comprised of a pore-

forming Orai1 subunit and a Ca2+-sensing STIM1 subunit (Soboloff et al., 2012). While

other subunits are considered less important, SOCE in murine microglia might also

involve STIM2 (Michaelis et al., 2015), and Orai3 activity can also be regulated by STIM

proteins (Soboloff et al., 2012). Rodent microglia express mRNA for Orai1, Orai3,

STIM1 and STIM2 (Heo et al., 2015; Michaelis et al., 2015; Ohana et al., 2009). In

murine microglia, Orai1, STIM1 and STIM2 contribute to SOCE and phagocytosis (Heo

et al., 2015; Michaelis et al., 2015). There are few reports regarding changes in Ca2+

signalling and expression of relevant Ca2+-signalling molecules in specific activation

states; and the results are somewhat inconsistent. For murine microglia, LPS (M1)

increased STIM1 without affecting Orai1 or Orai3 in one study (Heo et al., 2015), but

reduced STIM1 and Orai3 without affecting Orai1 or STIM2 in another (Michaelis et al.,

2015). Orai1 expression was not changed in either study but SOCE was reduced. The

Ca2+ entry pathway was not determined. An earlier study of murine microglia reported

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that LPS rapidly elevated basal Ca2+ and reduced the UTP-induced rise (Hoffmann et al.,

2003). For human microglia, M1 stimulation (GM-CSF+LPS+IFN-γ) did not affect the

Ca2+ response to ADP; whereas, M2 activation (M-CSF+IL-4+IL-13) increased it and

this was attributed to increased P2Y12 receptor expression (Moore et al., 2015). For rat

microglia, we recently found that the CRAC-mediated Ca2+ rise was ~50% lower after

IL-4 treatment (M2a) but not affected by IL-10 (M2c) (Lam and Schlichter, 2015).

In unstimulated rat microglia, myelin affected expression of Kv1.3 only (increased) but

channel expression was strongly affected by the microglial activation state. (i) I+T-

treated (M1) cells had increased expression of Kv1.3, KCa3.1, Kir2.1, STIM1, STIM2

and Orai3. Myelin phagocytosis increased Kv1.3, KCa3.1, Orai1 and Orai3. The high

STIM expression and increase in Orai1, the pore forming subunit of CRAC, should

facilitate Ca2+ signalling. (ii) IL-4-treated (M2a) cells had increased Kv1.3 and KCa3.1

compared with control cells. Myelin had no further effects. No Orai or STIM molecules

increased but STIM2 decreased slightly. Thus, the previously observed decrease in

CRAC signalling (Lam and Schlichter, 2015) is not readily explained by Orai or STIM

expression. (iii) Sequential cytokine addition had complex effects on channel expression.

M1→M2a: Compared with I+T stimulation alone, subsequent IL-4 addition reduced

KCa3.1, Kv1.3, Kir2.1, Orai3, STIM1 and STIM2. M2a→M1: Compared with IL-4

alone, subsequent I+T addition decreased expression of KCa3.1, Kv1.3, Orai3, STIM1

and STIM2, but not Kir2.1. M1→M2c: Compared with I+T alone, subsequent addition

of IL-10 only changed KCa3.1, which was increased. Overall, with respect to ion

channels, rat microglia showed considerable re-polarization between M1 and M2a states,

while IL-10 was ineffective.

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The use of selective channel blockers showed that CRAC was important for phagocytosis

under all activation conditions examined, while myelin phagocytosis and ROS production

by activated microglia were both dependent on Kir2.1 (but not Kv1.3 or KCa3.1). What

could account for a lack of contribution of Kv1.3 and KCa3.1 when, in principle, all

routes of K+ flux can control the membrane potential of cells? The simplest possibility is

that, despite substantial transcript expression, Kv1.3 and KCa3.1 were not active during

myelin phagocytosis. We propose a scenario in which Kv1.3 and KCa3.1 are inhibited,

while Kir2.1 and CRAC are facilitated. All three K+ channels are post-translationally

regulated by signalling molecules downstream of the phagocytosis receptors, CR3 and

SR-A. CR3 signalling activates Src family tyrosine kinases, phosphoinositide-3-kinase

(PI3K) and phospholipase C (PLC) (Freeman and Grinstein, 2014; Neher et al., 2012).

Kv1.3 is strongly inhibited by activated Src in rat microglia (Cayabyab et al., 2000).

Lipid phosphatases localize to phagosome cups (see reviews (Flannagan et al., 2012;

Freeman and Grinstein, 2014), and the lipid phosphatase, myotubularin-related protein 6

(MTMR6) regulates macropinocytosis (Maekawa et al., 2014), which uses similar

machinery to phagocytosis (Levin et al., 2015). KCa3.1 is strongly inhibited by MTMR6

(Srivastava et al., 2005). How might Kir2.1 and CRAC channel activity be promoted?

Both CR3 and SR-A signalling involve PLC (Hsu et al., 2001) and PI3K (Todt et al.,

2008). PI3K generates PIP2, which stabilizes the open configuration of Kir2.1 channels

(Hibino et al., 2010). PLC activity generates diacylglycerol (DAG) and inositol

triphosphate (IP3), which depletes ER calcium stores and activates CRAC (Flannagan et

al., 2012). In addition, DAG activates protein kinase C, which can stimulate NOX

enzymes and increase ROS production (Brandes et al., 2014).

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4.4. Conclusions

Experimental strategies for treating acute CNS injury increasingly address inflammation,

often targeting pro- or anti-inflammatory states in a generalized manner. Some preclinical

studies target innate immune cells (microglia, macrophages, neutrophils) more

selectively, but it is crucial to investigate potential targets in different cell activation

states. Further specificity in target selection will be necessary because some products and

functions can be either detrimental or beneficial, as is the case for phagocytosis. In CNS

disease and injury states where white matter is damaged, efficient re-myelination requires

that microglia remove myelin debris from affected axons. Therefore, treatment strategies

should preserve microglial phagocytosis while reducing harmful inflammatory responses.

Here, we investigated numerous molecular and functional changes in rat microglia

skewed to different M1 and M2 activation states. Our results illustrate several complex

outcomes that should be considered in pursuing strategies to target microglia. For

instance, the M1 state increased phagocytosis of myelin debris, which could aid in tissue

repair, but NOX-mediated ROS production was also increased, which might damage

bystander cells. Myelin phagocytosis exacerbated M1 activation, decreased M2

activation, and evoked more NOX-mediated ROS production, suggesting a positive-

feedback network that might increase damage. Using sequential cytokine addition to

model changing activation cues after acute CNS injury, we asked whether microglia can

be re-polarized from one activation state to another. Qualitative molecular re-polarization

was seen between M1 and M2a states with the paradigms used, which supports attempts

to re-program the inflammatory response in vivo. Moreover, because both M1→M2 and

M2→M1 paradigms increased myelin phagocytosis, it might be possible to maintain

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efficient debris clearance while therapeutically altering inflammatory mediators to a less

toxic mix.

Ion channels are increasingly proposed as molecular targets for controlling CNS

inflammation. This study contributes information about channel expression and

functional contributions that should be taken into account. While Kv1.3 and KCa3.1

expression were affected by the microglial activation state, neither channel contributed to

myelin phagocytosis. Thus, Kv1.3 and KCa3.1 blockers might be useful for reducing

inflammation without preventing beneficial debris clearance. On the other hand, Kir2.1

and CRAC channels facilitated myelin phagocytosis in all activated states, suggesting

that stimulating their activity might aid in debris clearance. However, our results also

suggest that facilitating these channels will also increase ROS production whenever an

M1 stimulus is present, and this could damage bystander cells.

This study greatly extends our knowledge by examining effects of single-versus-

sequential addition of M1- and M2-inducing cytokines. Results on myelin phagocytosis

and consequent ROS production are most relevant to diseases involving white-matter

damage, such as spinal cord injury, stroke, hemorrhage, brain trauma, MS and ALS.

However, results concerning the inflammatory profile, expression of phagocytosis-related

receptors, ROS-related molecules and ion channels, will be broadly applicable to CNS

injury and disease.

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Chapter 5. General Discussion

When I began my research in the Schlichter lab, the group had published numerous

papers showing novel regulatory roles of ion channels in specific microglia functions in

vitro. In vivo, the lab had performed extensive characterization studies comparing grey

matter and white matter neuroinflammation in young and aged rats in both ischemic and

intracerebral hemorrhagic stroke injury models. Along with other groups, Schlichter lab

showed that microglia exhibit marked enrichment to sites of injury, presumably through

migration; however, very little was known in terms of mechanisms that facilitated this

microglial phenotype. A surprising discovery was made that resting microglia can form

unique microscopic structures called podosomes. Microglial podosome expression was

found to be dependent on Ca2+, which in turn affected microglia migration and invasion.

Soon after, the activation state was also found to influence microglia migration and

invasion. The activation state was also known to affect myelin phagocytosis. When

assessing microglia responses in white matter damage, the Schlichter lab showed that

ED1-positive microglia (common phagocytic marker) selectively infiltrate damaged

myelin bundles but the activation state of these microglia was not characterized.

Considering our interest in ion channel regulation of specific microglia functions, the

purpose of this thesis was to assess: (i) the relationship between microglia activation

state, migration and invasion, as well as the role of ion channels, and (ii) the relationship

between microglia activation state, myelin phagocytosis and ROS production, as well as

role of ion channels. I showed that SK3 and TRPM7 channels differentially regulate

microglia migration and invasion depending on the activation state. The extent of myelin

phagocytosis was also shown to be dependent on the activation state. To support the

notion that ion channels regulate specific microglia functions, Kir2.1 and CRAC channels

were found to play an important role in myelin phagocytosis but Kv1.3 and SK4 channels

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did not. Importantly, we utilized high throughput assays to profile microglia cells, and

presented substantial evidence to support the hypothesis that microglia can repolarize

between activation states to a certain extent. The results presented in this thesis provide

an extensive insight into ion channel regulation of two major functions of activated

microglia after CNS injury, migration and phagocytosis. Thus, the knowledge will prove

useful when devising therapeutic strategies by taking into account responses of microglia,

which are major players in shaping CNS neuroinflammation.

5.1. Microglia activation and white matter damage

In the healthy brain, microglia are highly motile but not migratory (Davalos et al., 2005;

Li et al., 2012; Nimmerjahn et al., 2005). In this resting state, microglia perform a

number of homeostatic functions. As primary surveyors of brain health, any perturbation

in their environment from normal elicits a response. The extent of the response is

dependent on severity and location in the brain. For example, damage induced at the

single cell level induced microglia to respond rapidly and remove the damaged cell by

phagocytosis without initiating an inflammatory response (Morsch et al., 2015); a so

called immunologically- silent response. Initial microglia response is believed to limit

propagation of damage. This was demonstrated using two-photon live imaging, which

showed that where focal laser induced injury caused elicited microglia in proximity to

rapidly extend their processes toward the injury site (Davalos et al., 2005; Haynes et al.,

2006; Nimmerjahn et al., 2005). However, a larger, acute injury will result in extensive

cell death at the site of injury. Delayed clearance and prolonged exposure to injury-

associated molecules causes continued dysfunction and promotes degeneration. This kind

of damage will elicit a more pronounced neuroinflammatory response in microglia.

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Microglia respond to the damaged environment by undergoing activation, which results

in exhibition of many responsive phenotypes, such as migration toward the injury site and

phagocytosis of debris from damaged cells (Hanisch and Kettenmann, 2007; Kaushal et

al., 2007; Kettenmann et al., 2011; Moxon-Emre and Schlichter, 2010; Taylor and

Sansing, 2013; Wasserman and Schlichter, 2008). In white matter tissues, we found that

ischemic injury induced myelin damage in the core within 24 h (Moxon-Emre and

Schlichter, 2010), and damage progressed outward toward the peri-infarcted area for at

least 7 days. Myelin forming cells, oligodendrocytes, have a high metabolic rate (Amaral

et al., 2016; Funfschilling et al., 2012; Saher et al., 2005) and contain low levels of anti-

oxidants, making them vulnerable to oxidative damage by pro-oxidants (Thorburne and

Juurlink, 1996) or metabolic distress, which can be caused by ischemic stroke. The

resultant death of oligodendrocytes would lead to deposition of myelin debris. As

mentioned before, myelin debris inhibits differentiation of oligodendrocytes and inhibits

axonal growth. Microglia are primarily responsible for the clearance of myelin debris, as

they are well equipped to phagocytose damaged and degenerating tissue, process

phagocytic material more efficiently, and show prolonged viability. Infiltrating

macrophages, on the other hand, are more prone to apoptotic or necrotic death that

contributes to dead cell debris, and this further exacerbates damage (Greenhalgh and

David, 2014; Schilling et al., 2005). Myelin phagocytosis is dependent on the microglia

activation state (Smith et al., 1998). The cytokine profile at the injury site starts to change

after injury, including increased levels of TNF-α, IL-4, IL-1β, IL-10 (Lambertsen et al.,

2012; Lively and Schlichter, 2012). Depending on cytokine levels, microglia can be

stimulated into either a pro-inflammatory activation state that can exacerbate damage, or

anti-inflammatory states that are associated with tissue repair. Hence, the evolution of the

neural injury response involves a dynamic interplay between microglial responses that

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promote repair and regeneration and those of damage. However, there are only a few

studies that investigate microglia polarization in vivo after damage.

5.2. Microglia polarization in the ischemic core

When assessing microglia populations and polarization dynamics in vivo, most studies

done in ischemic stroke injury models show differential patterns, depending on the

location within the injury (Taylor and Sansing, 2013). The core represents an area of

extensive cell death due to little to no blood flow that causes irreversible damage. In a 90-

minute transient ischemia model, Iba1-positive cells are apparent in the ischemic core as

early as 3.5 hours after reperfusion. By the 48 hour time point, Iba1-positive cells have

dramatically increased in the core (Ito et al., 2001). In another transient ischemia model

using endothelin-1, Iba1-positive cells showed significantly increased numbers in the

ischemic core by 3 days and peaked at 7 days (Moxon-Emre and Schlichter, 2010).

Another study using a permanent ischemia model showed that CD11b-positive cells

increased by 6 hours in the ischemic core, and this was maintained until the 7 day time

point (Perego et al., 2011). Iba1 and CD11b are commonly used cell markers that label

both microglia and macrophages. Perego and colleagues also characterized microglia

polarization in the ischemic core, and showed that expression of the M2 markers, Ym1

and CD206/MRC1, was increased within 24 h in the ischemic core. In agreement,

findings from two other studies showed a similar pattern in CD206 levels in the ischemic

core, with an increasing trend until day 5 and then decreasing at days 14 and 35 (Hu et

al., 2012; Suenaga et al., 2015). The latter studies also characterized M1 polarization

using CD16/32 (Fcγ receptors) as an M1 marker to illustrate a substantial increase

starting at day 5 and peak at 14 days after injury. These studies show that the cells that

migrate into the infarct core are M2 microglia/macrophages. However around 7 days

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post-injury, M1 microglia/macrophage numbers start to increase, and those levels are

maintained for up to 14 days. This would support the notion that the initial microglia

response to injury is to protect and prevent the spread of damage. However, because the

studies lacked the ability to differentiate microglia cells from infiltrating macrophages,

the change in polarization pattern could not be attributed to one or the other cell type.

In vitro microglia cultures provide a vital tool to test whether microglia can repolarize

and how that influences microglial functions. In this thesis, I assessed the microglia

repolarization capacity using physiologically relevant cytokines. Microglia exhibited

dramatic repolarization between M1 and M2a activation states. In contrast, IL-10

showed no effect in repolarizing markers. In fact, IL-10 further up-regulated expression

of neurotoxic iNOS and NOX4, which were already high in I+T stimulated M1

microglia.

Microglia in the M2 activation state showed an enhanced migration and invasion capacity

(Lively and Schlichter, 2013; Siddiqui et al., 2014). This supports the observation that

microglia cells that appear first at the site of injury are in an M2 activation state when

they encounter myelin debris being generated in the ischemic core from damaged myelin.

The CD206 M2 marker was used to show that M2 microglia infiltrate into the ischemic

core first, and CD206 was specifically up-regulated with IL-4 stimulation. This coincides

with injured neurons in the peri-infarct region up-regulating expression of IL-4 from 3

hours until 1 day after ischemic injury (Zhao et al., 2015). Perhaps microglia cells

migrating from regions distal to the core are stimulated by IL-4 before infiltrating the

injury site, resulting in up-regulation of the M2 marker, CD206. Together with the

finding that IL-4 stimulated M2 microglia show no change in myelin phagocytosis

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relative to resting microglia, this implies that microglia in the ischemic core maintain

their basal phagocytic capacity for myelin. This is consistent with observations that after

cerebral infarction, the number of phagocytic microglia did not change after it peaked at

1 day (Schilling et al., 2004). In fact, we presented the novel finding that myelin

dampened the M2 response and up-regulated CX3CR1 gene expression. CX3CR1

interacts with neuronal CX3CL1 (fractalkine) ligand to keep microglia in a quiescent state

(Arnoux and Audinat, 2015). CX3CR1 deficiency led to impaired microglia migration

(Liang et al., 2009). The up-regulation of CX3CR1 in M2 activated microglia suggests

that they are maintaining their enhanced migration phenotype and myelin phagocytic

capacity. Furthermore, the down- regulation of the M2 activation state agrees with in

vivo observations that M2 marker expression peaks early after injury but decreases at

later time points.

Microglia/macrophage polarization starts to shift toward an M1 activation state 7 days

post-injury. Of note, the marker used to label M1 cells, CD16/32, recognizes two

different Fcγ receptors. CD16/FcγIII is thought to stimulate phagocytosis, while CD32/

FcγII is considered to inhibit it (Linnartz et al., 2010). We found that the two molecules

are differentially up-regulated in M1 and M2a stimulated microglia. CD16/FcγIII was up-

regulated in M1 microglia and CD32/ FcγII was up-regulated in M2a microglia. This

would suggest that CD16/32 is not a suitable marker for M1 polarization. Microglia also

exhibit a reduced migration capacity in the M1 state (Lively and Schlichter, 2013). M1

microglia are generally considered detrimental, as they are associated with production of

ROS and nitric oxide, and secretion of pro-inflammatory cytokines (Colton, 2009;

Hanisch and Kettenmann, 2007; Kettenmann et al., 2011). However, evidence was

presented in this thesis that M1 activated microglia have an enhanced myelin phagocytic

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capacity that would aid in clearance of myelin debris. Myelin exposure also up-regulated

mRNA expression of CD16/FcγIII and TIM-3 phagocytosis-related receptors. Reducing

TIM-3 activity decreases phagocytosis of apoptotic neurons (Wang et al., 2013). Thus,

M1 microglia that are detected at later time points after injury are mostly involved in

debris clearance, including myelin and apoptotic bodies. Consistent with this, higher

TNF-α expression, with the potential to induce microglia to M1 activation, were

associated with higher phagocytic activity of microglia after ischemic stroke (Ritzel et al.,

2015b). However, M1 microglia also produce excessive ROS when ingesting myelin.

Considering that microglia migration was enhanced at an earlier time in the ischemic

core, due to microglia being M2 activated with up-regulated CX3CR1 expression, they

could be destined to die closer to the center of the ischemic core away from undamaged

tissue. This notion would agree with observations from other groups showing that

CD11b-positive cells in the ischemic core are ‘disintegrating’ (Schroeter et al., 2009;

Schroeter et al., 1999). Through evolution, microglia might have developed the ability to

sense that the ischemic core is irreversibly damaged and repair is futile. Thus, the cells

devised a mechanism that limits propagation of damage by phagocytosing as much debris

as possible as they repolarize to the M1 activation state. Then, the excess production of

ROS would likely increase oxidative stress to cytotoxic levels as cell death is limited to

the center of the injury site. In conjunction, a glial scar forms around the injury site a

week after ischemic stroke injury, and is thought to wall off lesions and prevent the

spread of damage (Lively et al., 2011; Rhodes and Fawcett, 2004). Consequently, the

surrounding peri-infarct region is protected from the fallout of damage-associated

particles at the center of the injury site, thereby increasing the probability for the stressed

tissue that is in peri-infarct region to survive and take part in tissue regeneration/repair.

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5.3. Microglia polarization in peri-infarct

There is growing support for the idea that stressed and injured tissue in the peri-infarct

region might retain plasticity and the ability to participate in the repair process (Zhao et

al., 2015). Here, compared to the core, the extent of cell death is smaller but fate of

surviving cells are at risk depending on injury severity. Over time, molecules deposited in

the core from traumatic ischemic damage can diffuse outward into the peri-infarct region

and cause more damage after the initial injury. In terms of the pattern of the

microglia/macrophage activation state compared to the ischemic core, the cells exhibited

a different trend. Microglia/macrophages showed similar increases in the CD16/32 M1

marker and the CD206 M2 marker at earlier time points up to 3 days (Hu et al., 2012).

M2 polarization showed a transient rise by day 5 that eventually falls, while M1

polarization continues increasing. In terms of microglia/macrophage population

dynamics, Iba1-positive cells increased between 3 and 5 days after 90-minute transient

ischemia-reperfusion injury (Ito et al., 2001). This is a slightly delayed response

compared with the ischemic core where Iba1-positive cells were observed within hours.

In the endothelin-1 transient ischemia model, Iba1-positive cells showed a greater

increase compared to the core by 3 days but then showed a moderate rise to day 7

(Moxon-Emre and Schlichter, 2010). Myelin damage in the peri-infarct region was

slightly delayed but axonal damage was pronounced, peaking at 3 days post-injury and

then plateauing by day 7. In contrast, the ischemic core showed delayed but continued

worsening of axonal damage from day 3 to 7. This suggests that axonal damage in the

core is progressive, while the peri-infarct region is affected at later time points. Given

that the activation state changes, and the migration and myelin phagocytosis phenotype

is similar to the ischemic core, we would predict that a similar mechanism operates in this

region. However, it is important to consider that the environment that microglia are

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exposed to in the peri-infarct region is different from the core. There are reduced

damage-associated molecules due to less cell death and debris. This includes the reduced

effect of myelin debris on dampening M2 activation. In the peri-infarct area, initial

arrival of M2 microglia would produce neurotrophic factors that support tissue repair. For

example, alternatively activated microglia can support remyelination by driving

oligodendrocyte differentiation (Miron et al., 2013). Subsequent polarization to the M1

activation state coincides with the increased axonal damage observed. M1 activated

microglia would aid in removal of inhibitory myelin debris and perhaps continue

facilitating remyelination repair initiated earlier by M2 microglia.

5.4. Potential therapeutic strategies

The inflammatory response is a subject of active debate within the neuroscience

community. While some inflammation is clearly needed to limit degeneration and address

the cellular debris resulting from CNS injury, there is active discussion on whether the

inflammatory response should be further enhanced (Correale and Villa, 2004; Lenzlinger

et al., 2001; Morganti-Kossmann et al., 2002). The general therapeutic approach of using

anti-inflammatory agents to inhibit M1 activation is naïve. This is clear from studies that

used anti-inflammatory treatments and found they were detrimental to myelin repair. For

example, in a lysolecithin-induced demyelination model, systemic treatment with the

anti-inflammatory drug, dexamethasone, significantly impaired remyelination (Triarhou

and Herndon, 1986). In another demyelination model using ethidium bromide, treatment

with the anti-inflammatory agents, methylprednisolone succinate and minocycline,

showed a similar reduction in remyelination repair (Chari et al., 2006; Li et al., 2005). On

the other hand, unregulated stimulation of pro-inflammation is also damaging. This is

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illustrated in a study where zymosan was applied to induce inflammation (Gensel et al.,

2009). Although this treatment promoted axon growth in the spinal cord, it also led to

significant cell death. This is consistent with the finding that, although M1 activated

microglia show increased myelin phagocytosis, there is also substantially increased ROS

production. Thus, elucidating mechanisms that shape neuroinflammation, and exploiting

factors involved in endogenous neuroprotection and neuro-regeneration might aid in

developing more effective treatments for traumatic CNS injury. Because of the

progressive nature of cell death following traumatic CNS injury, a sustained

neuroprotective therapy might be required to alleviate or reduce neurological disability

and render the damaged CNS more receptive to regenerative strategies. Ideal treatment

strategies will exploit and complement endogenous repair mechanisms while suppressing

inhibitory mechanisms. Alternatively, a more desired approach is one that preferentially

enhances phagocytosis and chemotaxis in microglia, but not excessive pro-inflammatory

production of ROS (Rawji et al., 2016). One such an agent could be monophosphoryl

lipid A (MPL), a modified form of LPS that does not stimulate the more pro-

inflammatory pathways downstream of its receptor, TLR4 (Mata-Haro et al., 2007). For

example, administration of MPL in an Alzheimer’s disease mouse model increased

microglial phagocytosis, reduced amyloid-β plaques and improved functional outcome

(Michaud et al., 2013). This approach of stimulating microglial phagocytosis but not pro-

inflammatory cytokine secretion would conceivably be cytoprotective. Moreover,

stimulating microglia to phagocytose inhibitory myelin debris without an excessive pro-

inflammatory cytokine response could enhance axon regeneration and remyelination.

Several groups have also examined strategies to enhance a more regulatory microglial

phenotype (Cohen et al., 2014; Yamanaka et al., 2012). Such treatments target

transcriptional regulators important in promoting a regulatory microglia phenotype, such

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as up-regulation of interferon regulatory factor-7 (IRF-7) or activation of peroxisome

proliferator-activated receptor γ (PPAR-γ) (Cohen et al., 2014; Yamanaka et al., 2012).

5.5. Microglia polarization in ICH

Only recently, research investigating microglia polarization after intracerebral

hemorrhage (ICH) has been published (Wan et al., 2016; Yang et al., 2016). Although

both these studies report changes in M1 and M2 markers, the groups only reported

overall changes in expression in the brain parenchyma, which is not specific for the

microglia/macrophage population. Wan et al (Wan et al., 2016) showed that CD16 (an

M1 marker) transiently increases 4 hours after injection of autologous blood into the

brain. CD16 expression then reduced while expression of CD206 and Ym1 (M2 markers)

increased after 1 day. The other study showed a peak increase in iNOS and TNF-α (M1

markers) at 1 day after collagenase-induced ICH injury and then the expression returned

to baseline levels by 2 weeks (Yang et al., 2016). In contrast, CD206 and Ym1

expression peaked at 1 day and stayed up-regulated for another 48 hours before declining

to baseline levels by 2 weeks. The findings from these studies are in agreement with

published work from the Schlichter lab. Characterization of the inflammation profile in

the brain after collagenase-induced ICH showed that expression of the M1 markers,

iNOS and TNF-α, increased from 6 hours to 1 day, and then is decreased by day 7

(Lively and Schlichter, 2012). The M2 markers, CD206/MRC1 and CD163, showed up-

regulatedexpression from 1 to 3 days, before decreasing by 7 days. Earlier, another study

in the lab showed that Iba1-positive cells infiltrate into the hematoma starting at 3 days,

and showed an increasing trend to 14 days (Moxon-Emre and Schlichter, 2011). In all the

aforementioned studies, the microglia polarization in the hematoma or peri-hematoma

was not characterized; however, the neuroinflammation profile after damage suggested

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that the M1 phenotype was followed by M2 polarization. Because ICH introduces blood

components, such as thrombin, heme and blood-borne cells, microglia likely respond to

both damaged brain tissue and molecules that the cells have not been exposed to

throughout their lifetime, since the BBB is sealed. A possible explanation is that

microglia might have evolved to first polarize to the M1 activation state. Myelin debris

exposure would augment the M1 response, as illustrated in this thesis, in addition to up-

regulating the phagocytosis receptors for apoptotic cells, TIM-3 and C1r. Essentially,

microglia are prioritizing removal of debris, including myelin, without the need for

migrating through tissue. With time, microglia progress to M2 polarization to perhaps

gain an enhanced migration capacity. Furthermore, work presented in this thesis showed

that repolarization from M1 to M2a enhanced phagocytosis more than M1 stimulation

alone. M2a polarization would also up-regulate CD163, an M2 marker as well as heme

scavenger receptor (Schaer et al., 2007). Together, the repolarization would further aid in

removing the hematoma and tissue debris for possible remyelination repair. This is

evident in a cuprizone-induced demyelination model, where Miron et al (Miron et al.,

2013) reported that microglia undergo a similar repolarization paradigm, and that the

subsequent switch to the M2 activation state promotes oligodendrocyte differentiation to

promote remyelination.

5.6. Ion channel regulation of microglia behaviour

Cell migration and phagocytosis involve extensive cytoskeletal rearrangement and cell

volume changes. Ion channels can influence these by regulating Ca2+ dynamics in the cell

(Schwab et al., 2012). Ca2+ is a critical second messenger molecule required for efficient

migration (Schwab et al., 2012) and phagocytosis (Brechard and Tschirhart, 2008; Nunes

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and Demaurex, 2010). Among the two cell functions, the role of ion channels has been

better studied in migration than phagocytosis.

Migrating cells tightly regulate the spatial and temporal concentrations of cytosolic Ca2+,

maintaining an ascending global gradient from front-to-rear (Wei et al., 2012). Studies

done by Wei and colleagues (Wei et al., 2009; Wei et al., 2010) in fibroblasts showed

short-lived, localized rises in cytosolic Ca2+ at the leading edge that steer cells during

migration. The authors suggest that having a low Ca2+ background at the leading edge

helps maintain a chemical driving force for Ca2+ entry through Ca2+ permeable TRPM7

channels, which initiates Ca2+ signalling cascades necessary for cell migration.

Upon the discovery of podosomes in microglia, we found that these structures aid in

microglia migration and are regulated by Ca2+ (Siddiqui et al., 2012). In addition, we

found that the Ca2+-associated molecules, Orai1 and KCa2.3 channels, also associated

with podosomes. Inhibiting Orai1/CRAC channels reduced podosome expression as well

as migration and invasion. But the function of KCa2.3 channels was not elucidated at the

time. Orai1 can form a signalling complex with KCa2.3 in tumor cells to aid in migration

(Chantome et al., 2013). Besides podosomes, microglia migration was also dependent on

the cell activation state (Lively and Schlichter, 2013). Microglia stimulated with IL-4 to

an M2a activation state showed enhanced migration and invasion capacity. In contrast,

LPS-stimulated M1 microglia showed markedly reduced migration. The Schlichter lab,

and a small number of other groups, has found that ion channels play a critical role in

various microglia functions (Ferreira et al., 2014; Kaushal et al., 2007; Khanna et al.,

2001; Siddiqui et al., 2014; Siddiqui et al., 2016; Siddiqui et al., 2012; Stebbing et al.,

2015). However, there is a lack of knowledge regarding ion channel roles in migration

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and myelin phagocytosis of activated microglia. Considering that ion channels are being

increasingly suggested as therapeutic targets in neuroinflammation, it is imperative to

understand their role in microglia.

In this thesis, the role of KCa2.3 and TRPM7 channels in microglia migration and

invasion was initially investigated. This is because KCa2.3 channels have been

implicated in the migration and metastasis of cancer cells (Chantome et al., 2009;

Gueguinou et al., 2016; Jelassi et al., 2011; Potier et al., 2006). Cancer cells utilize

KCa2.3 channels to maintain a driving force for sustained Ca2+ entry that facilitates

migration (Chantome et al., 2013). This is mediated through association with Orai1

subunits of CRAC channels. The KCa2.3-Orai1 complex forms a positive feedback that

allows for sustained Ca2+ entry. Disruption of this complex reduced Ca2+ entry and

migration. In microglia, Orai1 and KCa2.3 channels both co-localize at podosomes

(Siddiqui et al., 2012). Inhibiting Ca2+ entry via Orai1/CRAC channels resulted in

reduced podosome expression and migration. We proposed the following model:

localized Ca2+ elevation through CRAC channels activates Ca2+-dependent KCa2.3

channels. The resulting K+ efflux is expected to hyperpolarize the membrane and help

maintain a driving force for Ca2+ entry. Ca2+ entry is then expected to regulate multiple

downstream effector molecules that contribute to podosome expression and cell

migration. Using specific pharmacological blockers, apamin and tamapin, as well as

negative modulator NS8593, we found that KCa2.3 function is not required for podosome

expression. In fact, KCa2.3 block increased migration, contrary to observations made in

cancer cells. Then, why do KCa2.3 channels associate with podosomes? There is some

evidence that KCa2.3 channels can serve as adaptor molecules independent of their

channel activity. KCa2.3 channels can associate with the serine/threonine CK2 kinase

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(Bildl et al., 2004). It is possible that microglia exploit KCa2.3 expression for trafficking

purposes, but that needs to be tested. Interestingly, in the same study, the KCa2.3

negative modulator, NS8593, reduced microglia migration and invasion in M2 activated

microglia. This was surprising at the time because KCa2.3 inhibition with apamin and

tamapin had no effect. At the time, a study found that NS8593 was not selective for

KCa2.3 channels, and can inhibit TRPM7 currents (Chubanov et al., 2012). This led us to

investigate the role of TRPM7 channels in microglia migration. TRPM7 channels have

been implicated in the migration of various cell types, including vascular smooth muscle

cells (Lin et al., 2016), T cells (Kuras et al., 2012), fibroblasts (Wei et al., 2009), and

mostly in cancer cells (Chen et al., 2015b; Fiorio Pla and Gkika, 2013). However, we

found that TRPM7 plays a significant role in migration and invasion of M2 microglia.

Yet, TRPM7 expression and current was not changed in M2 activated microglia. This

would suggest that the channel activity is being regulated post-translationally. TRPM7

channels can be regulated by many factors that include pH, ROS and PIP2 (Sun et al.,

2015). In injury such as stroke, excessive ROS production contributes to progression of

brain injury (McCann and Roulston, 2013). As well, brain ischemia is associated with

tissue acidosis (Nemoto and Frinak, 1981). Both ROS and acidic pH can potentiate

TRPM7 currents (Jiang et al., 2005; Nadler et al., 2001), which might support migration

of M2 activated microglia into the ischemic core. In migrating cells, PIP2 concentrations

are higher at the leading edge, and help maintain cell polarity (Thapa and Anderson,

2012). TRPM7-mediated Ca2+ entry was also observed at the leading edge of migrating

fibroblasts (Wei et al., 2009), and decreasing TRPM7 levels resulted in impaired

migration. PIP2 supports TRPM7 activity, and its depletion rendered the channel inactive

(Runnels et al., 2002). In microglia, TRPM7 currents are constitutively active (Jiang et

al., 2003). Because microglia also show polarity in the direction of migration (Vincent et

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al., 2012), M2 activated microglia can utilize a similar PIP2-regulated mechanism to

maintain TRPM7 currents. Inhibition of TRPM7 currents has been suggested as a

therapeutic strategy after stroke (Sun et al., 2015). However, this could reduce migration

of M2 activated microglia to the site of injury where they might be involved in

preventing damage propagation. Indeed, the absence of microglia generally results in a

larger brain injury (Elmore et al., 2014; Szalay et al., 2016).

In murine macrophages, cytosolic Ca2+ levels were important for phagocytosis, as its

chelation negatively impacted phagocytic ingestion rates (Hishikawa et al., 1991;

Ichinose et al., 1995a, b). A mechanism that is associated with Ca2+ dependence of

phagocytosis involves SOCE via the STIM1-Orai1 machinery (Braun et al., 2009). These

studies investigated the role Ca2+ in Fcγ receptor-mediated phagocytosis. In microglia,

the predominant pathway for Ca2+ entry is SOCE-mediated via Orai1/CRAC channels.

Knowledge regarding the role of CRAC channels in microglia is very limited. Inhibition

of Orai1/CRAC channels in microglia resulted in reduced migration and invasion

(Siddiqui et al., 2012). The work in this thesis shows that CRAC channels significantly

facilitate myelin phagocytosis and associated ROS production regardless of the cell

activation state. As indicated earlier, myelin debris in our culture conditions is likely not

opsonized with antibodies or complement proteins. This implies that myelin phagocytosis

does not involve Fcγ receptors and/or complement-mediated augmentation via CR3

receptors. More recently, microglia isolated from mice with genetic deletion of

Orai1/CRAC channels or STIM subunits exhibited reduced UDP-stimulated phagocytosis

(Heo et al., 2015; Michaelis et al., 2015). However, the mechanism involves UDP-

mediated activation of metabotropic receptor P2Y6, which is thought to induce SOCE via

Orai1/CRAC channels (Koizumi et al., 2007). Myelin phagocytosis associated with

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CRAC channels did not require additional ligand stimulation. Ca2+ entry via CRAC

channels is regulated by Kir2.1 channels (Lam and Schlichter, 2015). Blocking Kir2.1

channels reduced Ca2+ entry through CRAC channels. In my thesis work, blocking Kir2.1

channel also significantly reduced myelin phagocytosis and ROS production. This could

be due to the influence of Kir2.1 channels on Ca2+ entry via CRAC channels or an

independent mechanism that requires further investigation. On the other hand, myelin

phagocytosis was not affected by inhibition of Kv1.3 and SK4 channels. Together, the

work in this thesis showed crucial roles for CRAC and Kir2.1 channels in myelin

phagocytosis and the associated respiratory burst. As well, it provides evidence that

microglia utilize ion channels to regulate specific functions, highlighting the complex

biological relationship between ion channels and microglia physiology.

5.7. Proposed model

I will first construct a model that builds on findings presented in this thesis, and then

speculate on the molecular basis of myelin phagocytosis in microglia cells based on the

literature.

At the macroscopic level, microglia are constantly surveying their surrounding

environment, even in the healthy brain. Under pathological conditions, microglia are

exposed to a different environment and respond accordingly by undergoing activation to

either a pro-inflammatory M1 or anti-inflammatory M2 activation state. Upon activation,

microglia exhibit different migration and invasion capacity. Podosomes in microglia were

initially shown to regulate the extent of microglia migration and invasion. However, we

now report that podosomes are sufficient, but not necessary, for these phenotypes. After

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injury to white matter, such as ischemic stroke, microglia attain an M2 activation state in

order to migrate fast towards the injury site, presumably to contain the damage by

removal of myelin debris, and to limit propagation of damage. This enhanced migration

is dependent on TRPM7 channel activity, which is supported by environmental factors,

including pH and oxidative stress. With increasing time after the acute ischemic event,

however, the biochemical environment changes as damage progresses and oxidative

stress increases due to myelin phagocytosis. Microglia show the remarkable capability to

repolarize from the M2a state to M1 state. This is associated with increased myelin

phagocytosis, due to down-regulation of SIRPα (an inhibitor of myelin phagocytosis),

increased ROS production, and reduced migration. Microglia can now more efficiently

remove inhibitory myelin debris to support remyelination repair processes, including

promoting differentiation of oligodendrocyte precursor cells. On the other hand, certain

injuries can elicit microglia to undergo repolarization from M1 to M2, like that observed

after ICH. In this scenario, microglia first prioritize removal of tissue debris without the

need to migrate. But with time, microglia would need to move to other sites to aid in

removal of noxious substances, including blood components. Thus, it makes sense that

the cells repolarize to an M2 activation state. In this repolarization paradigm, microglia

exhibit further augmented myelin phagocytosis correlated with reduced expression of

SIRPα, and migration. Although, regardless of the activation state, Kir2.1 and CRAC

channels, but not Kv1.3 and SK4 channels, play a critical role in myelin phagocytosis and

associated ROS production.

At the molecular level, microglia primarily utilize CR3 and SRA receptors to

phagocytosis myelin in vitro (Rotshenker, 2003; Smith, 2001). Of the two receptors, CR3

signalling has been studied more extensively (Freeman and Grinstein, 2014). The

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proposed model will look specifically at the signalling molecules downstream of each

receptor that could potentially regulate the ion channels found in this study to be involved

in myelin phagocytosis. Most of the studies cited are based on the microglia and

macrophage literature. In vitro, myelin can be opsonized with complement factors in

presence of non-heat-inactivated serum or remain non opsonized when serum is heat

inactivated; CR3 receptors can bind both (Reichert and Rotshenker, 2003). The

phagocytosis efficiency of CR3 receptors is higher for complement opsonized myelin.

Reichert and group showed in mouse microglia that when myelin is complement

opsonized, the CR3 contribution to myelin phagocytosis is almost 80%, while SRA

contributes to the remaining 20%. However, when myelin is non-opsonized, identical to

our culture condition using heat-inactivated serum, the CR3 contribution decreases to

about 60%. In addition, pro-inflammatory stimuli can prime CR3 receptors, and

accumulate multiple receptors spatially for more efficient binding that can increase

phagocytosis (Freeman and Grinstein, 2014). CD11b/alphaM and CD18/beta2 subunits

make up the CR3 integrin (Mac1) complex. It can activate a wide range of signalling

pathways that include RhoA GTPase, Src family kinases and Syk kinase (Gitik et al.,

2014; Gitik et al., 2010). Activation of Src kinases would negatively regulate Kv1.3

function in microglia (Cayabyab et al., 2000). Although RhoA activity negatively

regulates Kir2.1 (Muessel et al., 2013), the Gitik group suggested that in microglia, RhoA

is primarily located in the perinuclear region, away from the cell periphery where

phagocytic cups are forming (Gitik et al., 2010). Myelin activation of CR3 could also

activate other kinases, including FAK, PI3K, PLC and PKC, possibly involving Syk (see

reviews (Linnartz and Neumann, 2013; Neher et al., 2012). PI3K in turn would generate

PIP2 and PIP3 and influence actin dynamics; all known to be required for phagosome cup

formation (see reviews (Flannagan et al., 2012; Freeman and Grinstein, 2014). PIP2

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stabilizes the open conformation of Kir2.1 channels, allowing the influx/efflux of K+ ions

depending on the membrane potential (Hibino et al., 2010). PIP2 also serves as a substrate

for PLC to generate soluble IP3 (Flannagan et al., 2012) that leads to emptying of ER

Ca2+ stores, and CRAC channel activation in microglia (Ohana et al., 2009). As a

regulatory mechanism, lipid phosphatases localize to phagosome cups (see reviews

(Flannagan et al., 2012; Freeman and Grinstein, 2014) that can include MTMR6. In C.

elegans, a similar regulatory mechanism occurs during macropinocytosis (similar to

mammalian phagocytosis) (Maekawa et al., 2014); where MTMR6 localized to the

forming micropinosome. MTMR6 inhibits SK4 channel activity (Srivastava et al., 2005).

Additionally, PKC activation, mediated via CR3 or DAG (breakdown product of PLC

activity on PIPs), could also inhibit SK4 channel activity (Wulf and Schwab, 2002), and

at the same time induce ROS formation via Nox enzymes (Brandes et al., 2014). In fact,

PIP breakdown is needed to close the phagosome cup (see reviews (Flannagan et al.,

2012; Freeman and Grinstein, 2014). During phagosome closing and maturation, the

required depletion of PIP2 would reduce the Kir2.1 open conformation, and not provide

the substrate for formation of IP3, leading to CRAC channel inactivity. Finally, CR3

signalling requires MLCK activity in microglia (Gitik et al., 2010), a kinase involved in

cell contractile machinery possibly to engulf trapped particles into the cell.

The other phagocytic receptor that contributes to myelin phagocytosis in vitro is SRA

(CD204/MSR1). The distinction in SRA signalling compared to CR3 signalling is

important to consider when comparing the contribution of each receptor to myelin

phagocytosis in different activation states. In MS, SRA up-regulation was correlated with

MS lesion formation in microglia, macrophages and astrocytes (Hendrickx et al., 2013).

Little is known about the SRA downstream signalling mechanism but recent work is

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shedding some light into the matter. Initial investigations in macrophages showed

involvement of PKC and PLC signalling (Hsu et al., 2001). Further investigation showed

that SRA lacks enzymatic activity but might signal by associating with Mer tyrosine

kinase (MerTK) (Todt et al., 2008). Recently, MerTK was shown to be involved in

myelin phagocytosis in human microglia (Healy et al., 2016). In fact, MerTK expression

was associated with microglia phagocytosis, and MerTK inhibition attenuated myelin

phagocytosis. In the BV-2 microglia cell line, MerTK signalling required Rac and PI3K

signalling molecules (Grommes et al., 2008). A clear distinction here is that, unlike CR3

that depends on RhoA signalling only and not Cdc42 or Rac in microglia, SRA signalling

does not require RhoA activity (Gitik et al., 2010) but instead signals through Rac. In

fact, Rac activity is believed to be antagonistic to RhoA activity (Freeman and Grinstein,

2014). This would imply that the negative regulatory role of RhoA for Kir2.1 is not

present. Instead, PIP2 (generated by PI3K in addition to PIP3) is the only known positive

modulator of Kir2.1 that will be present under SRA signalling. Furthermore, similar to

CR3 signalling, PLC would cleave PIP2/3 to generate IP3 and DAG to activate CRAC

channels and PKC, respectively. PKC activation would inhibit SK4 channels but, in

conjunction with Rac signalling, would activate Nox enzyme activity to generate ROS

(Brandes et al., 2014). SRA signalling in microglia requires MLCK activity (Gitik et al.,

2010), a common mechanism suggested for CR3 signalling to pull in and engulf the

target particle, myelin.

Of the two receptors, the expression of CR3 mostly remains higher than SRA in this

study. This would suggest that CR3 is the primary phagocytic receptor, and the prevalent

signalling pathway operating to regulate myelin phagocytosis in microglia. It is, however,

important to keep in mind that the expression of the phagocytosis inhibitory receptor,

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SIRPα, changes depending on the microglia activation state. SIRPα signals via SHP1 and

SHP2 tyrosine phosphatases that prevent the activation phosphorylation signals of CR3

(see review (Linnartz and Neumann, 2013). There is no knowledge of its regulatory role

in SRA receptors. In general, I+T stimulation down-regulated this receptor, which would

imply a reduction in inhibitory signal. In addition, the general lack of change in CR3

expression in I+T stimulated microglia would explain why M1 activated microglia

exhibit increased myelin phagocytosis.

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Chapter 6. Conclusions

The first goal of this thesis was to assess contributions of Ca2+-regulated K+ channels to

podosomes, migration and invasion. I report the novel finding that podosome expression

is not dependent on KCa2.3 function or the microglial activation state. This suggested

that podosomes are sufficient but not required for microglia migration. KCa2.3 channels,

however, do negatively regulate microglia migration. M2 activated microglia showed no

change in KCa2.3 gene expression or currents based on patch clamp electrophysiology. A

surprising discovery was the involvement of TRPM7 channels in this study. These

channels were found to selectively contribute to the migration and invasion capacity of

M2 activated microglia. No change was found in TRPM7 mRNA expression in M2

activated microglia. As well, TRPM7 currents showed no change. This suggests that a

post-translational regulatory mechanism likely modulates its activity in M2 activated

microglia. Lastly, we showed that the negative gating modulator of KCa2.3 channels,

NS8593, is an effective inhibitor of TRPM7 channels in microglia. The inhibitory effect

was not dependent on the microglia activation state.

My next goal involved evaluating the relationship between microglia activation state,

myelin phagocytosis, respiratory burst, and ion channel contributions. I present the novel

finding that 6 h myelin exposure augments the M1 response and dampens the M2

response. Resting microglia, however, showed no observable change in activation state

after exposure to myelin. I+T induced an M1 activation state in microglia that increased

myelin phagocytosis. IL-10 stimulated microglia also showed increased myelin

phagocytosis. IL-4 stimulated M2a microglia showed a basal phagocytic capacity, similar

to unstimulated microglia. Myelin evoked a robust respiratory burst response that was

dependent on NOX activation. Based on expression levels, we believe it is the NOX2

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isoform. Hence, antioxidant therapy might inhibit beneficial aspects of myelin

phagocytosis. We presented the exciting finding that microglia can repolarize between

M1 and M2a states. IL-10, thought to be a deactivation cytokine, showed no observable

repolarization in microglia. This might be due to the experimental setup and might

require further investigation. In repolarization paradigms, M1 stimulation augmented

myelin phagocytosis and ROS production regardless of the sequence of cytokine

stimulation. Again, these responses were dependent on NOX activity. Lastly, Kir2.1 and

CRAC channels play an important role in myelin phagocytosis and associated ROS

production. Kv1.3 and SK4 channels showed no observable effect. This supports the idea

that microglia ion channels regulate specific microglia functions.

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Chapter 7. Future Directions

With the discovery that the microglia activation state regulates myelin phagocytosis in

vitro, some important questions are raised. While I studied most of the activation states

that can be induced in vitro, I did not test TGFβ stimulation. It is considered a potent

deactivator of microglial cells and would be of interest to test its repolarization capacity

in M1 and M2 activated microglia. In addition, we found that gene expression changes

for phagocytosis-related receptors did not always help explain functional changes

observed in microglia. Performing protein expression studies (e.g., flow cytometry,

western blots) to complement gene expression studies would help in obtaining a more

detailed understanding of regulatory molecules that modulate specific microglia

functions. Furthermore, given the extensive library of genes we studied, it might aid in

identifying receptors involved in myelin phagocytosis that are unknown. The recent

finding that MerTK plays a role in myelin phagocytosis (Healy et al., 2016) supports the

model I proposed in my thesis. This provides impetus to test the various signalling

molecules in my model to gain a better fundamental understanding of effector molecules

that regulate myelin phagocytosis. This could be done using pharmacological tools that

modulate activity of proteins of interest.

With the development of techniques that help discern microglia from other immune cells

involved in neuroinflammation, I propose we study the activation state of microglia in

ischemic and ICH stroke models. Specifically, how does the microglia polarization state

change over time after damage? What is the location of specific activated microglia in

injury? For microglia that enter damaged bundles, do they show internalized myelin

particles? What activation state are they in? Due to increased oxidative stress from

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infiltrating macrophages, I would hypothesize that the microglia are in a M1 activation

state in damaged myelin bundles to help clear myelin debris and promote remyelination.

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