Role of microRNA in microglial phenotype - ULisboa · 2018. 3. 29. · Publications The studies included in this thesis were presented in the following publications: Oral presentations

UNIVERSIDADE DE LISBOA

FACULDADE DE FARMÁCIA

Role of microRNA in microglial phenotype

during the progression of Alzheimer’s disease

Mafalda Aurélio Monteiro

Dissertação

MESTRADO EM CIÊNCIAS BIOFARMACÊUTICAS

2016

UNIVERSIDADE DE LISBOA

FACULDADE DE FARMÁCIA

Role of microRNA in microglial phenotype during

the progression of Alzheimer’s disease

Mafalda Aurélio Monteiro

Dissertação orientada por:

Professora Doutora Adelaide Fernandes

Professora Doutora Dora Brites

MESTRADO EM CIÊNCIAS BIOFARMACÊUTICAS

2016

The studies presented in this thesis were performed at the Neuron-Glia Biology in Health and

Disease research group, at the Research Institute for Medicines (iMed.ULisboa), Faculty of

Pharmacy, Universidade de Lisboa, under the supervision of Adelaide Fernandes, Ph.D and

Dora Brites, Ph.D

This work was funded by EXPL/NEU-NMC/1003/2013 grant from FCT to Adelaide

Fernandes and FCT grant UID/DTP/04138/2013 to iMed.ULisboa.

Publications

The studies included in this thesis were presented in the following publications:

Oral presentations

Monteiro M, Brites D, Fernandes A. Role of microRNA in microglia phenotype during the

progression of Alzheimer’s disease. VIII Cycle of Scienceshops – Alzheimer’s disease. 2015.

Lisbon, Portugal

Poster communications

Monteiro M, Caldeira C, Brites D, Fernandes A. Human microglia phenotype and microRNA

profile change over time under Amyloid-beta-enriched conditions. 7th Postgraduate

iMed.ULisboa Students Meeting. 2015, Lisbon, Portugal

Monteiro M, Caldeira C, Brites D, Fernandes A. Human microglia phenotype changes in the

presence of Amyloid-beta expressing neuroblastoma cells. XIV Meeting of the Portuguese

Society for Neurosciences. 2015. Póvoa de Varzim, Portugal

À minha avó.

Agradecimentos

Gostaria de começar por agradecer à Prof.ª Dr.ª Dora Brites por me ter dado a

oportunidade de me juntar ao grupo Neuron-Glia Biology in Health and Disease para realizar

esta tese, mesmo com a condicionante de ser trabalhadora-estudante e, por isso, não poder

participar em muitas das atividades do grupo. Agradeço também pelo apoio que me deu

aquando da candidatura a bolsas, não só pelas cartas de recomendação mas também pelas

dicas que, estou certa, me serão sempre úteis a nível profissional.

Tenho também muito a agradecer à Adelaide, pois sem o seu apoio esta tese nunca

teria sido feita. Um muito obrigada por me ter dado a oportunidade, desde os projetos do 1º

ano do CBF, de trabalhar e aprender consigo. Obrigada por toda a dedicação e paciência,

mesmo quando as coisas não correram tão bem ou tive dificuldade em cumprir prazos...É,

sem dúvida, um exemplo no mundo da ciência não só por todos os conhecimentos que tem

mas também por saber transmiti-los.

Agradeço a todos os que fazem parte do grupo, sem exceção, por me terem acolhido e

ajudado nas muitas vezes em que precisei. Obrigada ao Pedro Dionísio por toda a ajuda

que me deu durante o CBF, mas também pela companhia no CPM quando as horas já iam

avançadas.

Não posso deixar de agradecer o companheirismo da equipa da farmácia de Tercena, e

em particular à Dr.ª Martine por ter permitido que eu conciliasse o meu trabalho com a

realização do CBF.

Ao meu pai agradeço todo o apoio que me deu ao longo do tempo do mestrado,

principalmente quando tive de fazer um esforço maior para cumprir deadlines. Á minha irmã

Catarina, obrigada por teres participado ativamente nesta tese ao ajudares-me com as

imagens. À Patrícia, desculpa tantas vezes ter-te usado como “caixote do lixo emocional”

mas, acredita, foste uma grande ajuda para mim ao longo deste percurso, obrigada! Fica

aqui uma última palavra à minha mãe que, mesmo estando tão longe, tenho a certeza que

esteve sempre a olhar por mim...

A toda a minha família, obrigada por tudo! E a ti, avó Especiosa, uma palavra especial

por todo o carinho que sempre me deste. Espero que esta tese sirva para que outras

pessoas cheguem à tua idade, 103 aninhos, com a mesma qualidade de vida.

Não podia deixar de agradecer às minhas amigas “galinhas” por me terem

acompanhado ao longo desta jornada.

Por último, uma palavra, e só mesmo uma palavra a ti, João: OBRIGADA!

Role of microRNA in microglial phenotype during the progression of Alzheimer’s disease

i

Table of Contents

Abbreviations ........................................................................................................... vii

Abstract .................................................................................................................... ix

Resumo ................................................................................................................... xi

I. INTRODUCTION ...................................................................................................... 1

1. Alzheimer’s disease......................................................................................... 1

1.1. Diagnostic and treatment ................................................................................. 1

1.2. Pathogenesis .................................................................................................. 2

1.2.1. Amyloid β-peptide and neurofibrillary tangles .................................................. 2

1.2.2. Neuroinflammation .......................................................................................... 5

2. Microglia: the key players in neuroinflammation .............................................. 6

2.1. Microglial regulation and functions ................................................................... 6

2.2. Microglial phenotypic diversity ......................................................................... 7

2.3. Microglia in the aged brain............................................................................... 9

2.4. Microglial deregulation in Alzheimer’s disease................................................. 11

3. MicroRNAs: biogenesis and functions ............................................................. 13

3.1. Inflammation-related microRNAs in microglia .................................................. 14

3.1.1. MiR-124 ........................................................................................................... 14

3.1.2. MiR-155 ........................................................................................................... 15

3.1.3. MiR-146a ......................................................................................................... 16

3.2. MicroRNA profile in Alzheimer’s disease ......................................................... 18

3.3. Deregulation of microglial microRNAs in Alzheimer’s disease ......................... 20

4. Human versus rodent microglia ....................................................................... 21

4.1. The human CHME3 microglial cell line ............................................................ 22

5. Aims ................................................................................................................ 22

II. MATERIALS AND METHODS ................................................................................. 23

1. Cell culture and treatment................................................................................ 23

2. Protein extraction and western blot analysis .................................................... 24

3. Enzyme-Linked Immunosorbent Assay (ELISA) .............................................. 25

4. Total RNA extraction, reverse transcription and semi-quantitative RealTime

Polymerase Chain Reaction (qRT-PCR) ......................................................................... 26

5. Evaluation of microglial phagocytic ability ........................................................ 27

6. Senescence-associated β-galactosidase assay .............................................. 28

7. Statistical analysis ........................................................................................... 28

III. RESULTS ................................................................................................................ 29

ii

1. APP expression and Aβ secretion in neuroblastoma cells ............................... 29

2. The presence of CHME3 microglia does not alter APP expression in

neuroblastoma cells but reduces sAPPα, sAPPβ and Aβ1-40 levels in co-culture media ... 31

3. Human CHME3 microglial expression of inflammation-related miRNAs and their

targets is mainly altered in the presence of SH-SY5Y APP695 Swe cells ........................ 33

4. The expression of pro-inflammatory cytokines in CHME3 microglia is markedly

induced when co-cultured with SH-SY5Y APP695 Swe cells .......................................... 36

5. The expression of CHME3 microglial immune markers is reversed when co-

cultured with SH-SY5Y APP695 or SH-SY5Y APP695 Swe cells .................................... 38

6. The expression of anti-inflammatory markers in CHME3 microglia is markedly

induced when co-cultured with SH-SY5Y APP695 Swe cells, with TGF-β exception ....... 39

7. CHME3 microglia co-cultured with SH-SY5Y APP695 Swe cells preserve their

phagocytic capacity for longer periods ............................................................................. 40

8. CHME3 microglia show increased SA-β-gal activity when co-cultured with SH-

SY5Y APP695 Swe cells ................................................................................................. 42

IV. DISCUSSION ........................................................................................................... 45

V. REFERENCES ......................................................................................................... 55


iii

Figure Index

I. INTRODUCTION

Figure I.1 | Metabolism of the amyloid precursor protein (APP) and representation of the

Swedish mutation.. ................................................................................................................ 4

Figure I.2 | Microglial phenotypes in the healthy (M0, M1, M2a, M2b and M2c) and aged

(dystrophic and primed) brain.. .............................................................................................11

Figure I.3 | Regulation of inflammation and immunity by miR-124, miR-155 and miR-146a.. 18

II. MATERIALS AND METHODS

Figure II.1 | Schematic representation of the experimental design ........................................ 24

III. RESULTS

Figure III.1 | APP expression, and sAPPα, sAPPβ and Aβ secretion by neuroblastoma cells..

.............................................................................................................................................30

Figure III.2 | Presence of CHME3 microglia does not alter APP expression in neuroblastoma

cells but reduces sAPPα, sAPPβ and Aβ1-40 in co-culture media.. ........................................32

Figure III.3 | Expression of miR-124 gradually increases in CHME3 microglia when co-

cultured with SH-SY5Y APP695 Swe cells, whereas the mRNA expression of C/EBP-α

decays over time.. ................................................................................................................33

Figure III.4 | Expression of miR-155 peaks in CHME3 microglia when co-cultured with SH-

SY5Y APP695 Swe cells with a subsequent reduction, whereas the mRNA expression of

SOCS1 increases in a time-dependent manner. No evident changes are observed for

C/EBP-β mRNA expression.. ................................................................................................35

Figure III.5 | Expression of miR-146a increases in CHME3 microglia when co-cultured with

SH-SY5Y APP695 Swe cells decreasing over time. Conversely, whereas mRNA expression

of IRAK1 progressively increases, the mRNA expression of TRAF6 does not show any

significant variation along time.. ............................................................................................36

iv

Figure III.6 | CHME3 microglial mRNA expression of the pro-inflammatory cytokines TNF-α,

IL-6 and IL-1β is enhanced over time when co-cultured with SH-SY5Y APP695 Swe cells.. 37

Figure III.7 | CHME3 microglial mRNA expression of iNOS is rapidly induced when co-

cultured with SH-SY5Y APP695 Swe cells whereas MHC class II mRNA expression is slowly

enhanced.. ...........................................................................................................................39

Figure III.8 | mRNA expression of the anti-inflammatory markers Arginase 1 and IL-10 is

rapidly induced in CHME3 microglia when co-cultured with SH-SY5Y APP695 Swe cells and

progressively enhances, though TGF-β mRNA expression does not show a gradual variation

pattern.. ................................................................................................................................40

Figure III.9 | Average of phagocytosed beads per CHME3 microglial cell tends to reduce in all

co-culture systems, though CHME3 microglia co-cultured with SH-SY5Y APP695 Swe cells

retain their capacity to uptake increased number of beads along time in co-culture.. ............41

Figure III.10 | CHME3 microglia co-cultured with SH-SY5Y APP695 Swe cells show

increased levels of senescence-associated β-galactosidase (SA-β-gal) activity along time in

co-culture.. ...........................................................................................................................43

IV. DISCUSSION

Figure IV.1 | Human CHME3 microglia shift from a pro-inflammatory to a more anti-

inflammatory/regulatory phenotype when co-cultured with SH-SY5Y APP695 Swe cells.. ....54


v

Index of Tables

I. INTRODUCTION

Table I.1 | Expression of miR-124, miR-155 and miR-146a in samples of Alzheimer’s disease

(AD) patients, in vivo and in vitro AD models, and evidence of their role in the regulation of

microglia in AD.. ...................................................................................................................21


Table II.1 | Sequences used as primers for detection of mRNA expression in CHME3

microglia ...............................................................................................................................26

Table II.2 | Target sequences of predesigned primers used for detection of miRNAs

expression in CHME3 microglia ............................................................................................27


vii

Abbreviations

AB/AM Antibiotic antimycotic

AD Alzheimer’s disease

AICD Amyloid precursor protein intracellular domain

APP Amyloid precursor protein

Arg1 Arginase 1

Aβ Amyloid β-peptide

Aβ1-40/1-42 40/42 residues length Amyloid β-peptide

BACE1 β-site amyloid precursor protein cleaving enzyme 1

BDNF Brain-derived neurotrophic factor

C/EBP-α CCAAT/enhancer-binding protein α

CD206 Mannose receptor

CFH Complement factor H

CNS Central nervous system

CREB Cyclic AMP response element-binding

CSF Cerebrospinal fluid

CSF-1 Colony stimulating factor 1

CTF C-terminal fragment

DMEM Dulbecco’s Modified Eagle’s Medium

ECF Extracellular fluid

ECM Extracellular matrix

ELISA Enzyme-Linked Immunosorbent Assay

EOFAD Early onset familial Alzheimer’s disease

FBS Fetal bovine serum

FIZZ1 Resistin-like α

GM-CSF Granulocyte macrophage colony stimulating factor

HAG Human astroglial

HLA-DR Human leucocyte antigen

HMG Human microglial

HNG Human neuron-glial

h-tau Hyperphosphorylated tau

IFN-γ Interferon γ

IL Interleukin

iNOS Inducible nitric oxide synthase

IRAK1 Interleukin-1 receptor-associated kinase 1

viii

IRF Interferon regulatory factor

JAK Janus kinase

L-glu L-glutamine

LPS Lipopolysaccharide

MAPK Mitogen-activated protein kinase

M-CSF Macrophage colony stimulating factor

MHC class II Major histocompatibility complex class II

miRNA/miR MicroRNA

NFTs Neurofibrillary tangles

NF-κB Nuclear factor κB

NO Nitric oxide

qRT-PCR Semi-quantitative RealTime Polymerase Chain Reaction

RA Retinoic acid

ROS Reactive oxygen species

RPMI Roswell Park Memorial Institute

sAPP Soluble amyloid precursor protein

SA-β-gal Senescence-associated β-galactosidase

SOCS1 Suppressor of cytokine signaling 1

STAT Signal transducer and activators of transcription

Swe Swedish

TGF-β Transforming growth factor β

TLR Toll-like receptor

TNF-α Tumor necrosis factor α

TRAF6 Tumor necrosis factor receptor-associated factor 6

TREM2 Triggering receptor expressed on myeloid cells 2

T-TBS Tween 20 (0.1%)-Tris buffered saline

Ym1 Chitinase 3-like-3


ix

Abstract

Alzheimer’s disease (AD) is the most prevalent form of dementia and its impact in

society has been aggravating throughout years. Due to its progressive nature and lack of

marked treatment benefits, many efforts have been done to unveil AD pathogenesis seeking

for novel therapeutic targets or biomarkers.

Current view on AD pathogenesis attributes significant importance to neuroinflammation,

where microglia play a pivotal role. Under normal conditions, microglia exhibit a

quiescent/vigilant state and perform the brain surveillance. After an injury, microglia initiate

the immune defense of the brain and acquire a pro-inflammatory or anti-inflammatory

phenotype depending on stimuli. After the inflammation resolution, the brain homeostasis is

restored. Various conditions such as the presence of amyloid β-peptide (Aβ) and aging can

deregulate microglial response, though it remains unclear how microglial deregulation affect

the course of AD. Furthermore, it was established that some microRNAs (miRNAs or miRs)

that are known to promote microglial quiescence (miR-124) or regulate microglial activation

states (miR-155 and miR-146a) are deregulated in AD. However, it has not been established

whether the deregulation of these miRNAs can influence microglial phenotype and response

in AD, particularly concerning human microglia.

With this work, we proposed to analyze the temporal response of human CHME3

microglia when co-cultured with two Aβ-expressing human neuroblastoma cells, SH-SY5Y

APP695 or SH-SY5Y APP695 Swe cells. We assessed microglia for miRNAs (miR-124, miR-

155 and miR-146a) and their targets, as well as for pro-inflammatory (IL-1β, IL-6 and TNF-α),

anti-inflammatory (TGFβ, IL-10 and Arginase 1) and immune (iNOS and MHC class II)

markers, and additionally for phagocytic capacity and senescence.

We found that when CHME3 microglia are co-cultured with SH-SY5Y APP695 Swe cells

they exhibit a more pronounced response than when co-cultured with other neuroblastoma

cells. Indeed, in the presence of SH-SY5Y APP695 Swe cells CHME3 microglia initially

exhibit a miR-124low/miR-155high/miR-146ahigh profile like activated cells but gradually switch

to a miR-124high/miR-155low/miR-146alow profile typical of a gradual shift towards an

alternative activated/deactivated phenotype that ultimately give rise to quiescent cells. The

pro-inflammatory markers are robustly expressed in microglia during the whole time, but the

expression of the anti-inflammatory markers is gradually enhanced suggesting an

immunoregulatory response. With regards to immunity, microglia rapidly express the innate

immune marker iNOS followed by a later induction of the adaptive immune marker MHC

class II.

x

Altogether, we demonstrated that the CHME3 / SH-SY5Y APP695 Swe co-culture is the

most adequate in vitro AD model to study human microglial response and possibly to assay

new microglia-targeted therapeutic strategies.

Keywords: Human microglia, Alzheimer’s disease, miR-124, miR-155, miR-146a, phenotype


xi

Resumo

A doença de Alzheimer (AD) é a forma de demência com maior prevalência no mundo e

o seu impacto na sociedade tem vindo a agravar-se ao longo dos anos. Dada a sua

natureza progressiva, mas também devido à falta de eficácia dos medicamentos utilizados

atualmente na prática clínica, têm sido feitos vários estudos na tentativa de desvendar os

mecanismos patogénicos da AD com o objetivo de descobrir novos biomarcadores ou alvos

terapêuticos que permitam melhorar o diagnóstico da doença e atrasar a sua progressão.

Atualmente sabe-se que a neuroinflamação tem um papel importante na patogénese da

AD, pelo que a microglia se destaca dada a sua relevância como reguladora da

neuroinflamação. Em condições normais, as células da microglia apresentam um estado

quiescente, vigiando a homeostase cerebral. Quando ocorre um dano, a microglia

rapidamente inicia a resposta imunitária por forma a neutralizá-lo e proteger o cérebro,

adquirindo um fenótipo pro-inflamatório ou anti-inflamatório dependendo do estímulo. Após a

resolução da inflamação, as células da microglia voltam ao estado quiescente/vigilante

permitindo que a homeostase do cérebro seja reposta. Sabe-se também que em algumas

situações tais como na presença de agregados proteicos do péptido β amiloide (Aβ) – que é

originado a partir do seu precursor, APP –, mas também durante o próprio envelhecimento,

as funções e resposta da microglia estão alteradas. Porém, não foi ainda esclarecido como

é que a desregulação das células da microglia devida a esses estímulos pode afetar o curso

da AD.

Por outro lado, há certos microRNAs (miRs) reconhecidos pela sua capacidade de

modular a expressão de genes que afetam os fenótipos da microglia, nomeadamente o miR-

124, o miR-155 e o miR-146a. Enquanto que o miR-124 é expresso maioritariamente nas

células da microglia no estado vigilante, sendo responsável pela sua manutenção, o miR-

155 e o miR-146a regulam a expressão de genes envolvidos em vias de sinalização que

levam à ativação celular. Vários estudos demonstram que a expressão destes microRNAs

está desregulada na AD baseando-se não só em amostras de doentes mas também em

diferentes modelos animais da AD. Contudo, não foi ainda esclarecido de que forma essa

desregulação pode afetar a resposta e o fenótipo da microglia, nomeadamente no que diz

respeito às células humanas.

Com este trabalho, pretendemos explorar a resposta da linha de microglia humana

CHME3 quando em co-culturas com linhas de neuroblastoma humano que expressam Aβ,

sendo estas as células SH-SY5Y APP695 ou SH-SY5Y APP695 Swe. As primeiras são

células que expressam a isoforma 695 da APP, e as outras são células que expressam uma

forma da APP mutante originada pela mutação Sueca (Swe). A análise da resposta da

xii

microglia foi feita com base na determinação da expressão de microRNAs (miR-124, miR-

155 e miR-146a) e respetivos genes alvo, assim como marcadores de fenótipo pro-

inflamatório (IL-1β, IL-6 and TNF-α) e anti-inflamatório (TGFβ, IL-10 and Arginase 1) e

marcadores de resposta típica imunitária (iNOS and MHC class II). Adicionalmente,

avaliámos a capacidade fagocítica da microglia e senescência, que estão associados às

funções da microglia na AD.

Os nossos resultados demonstram que a linha de microglia humana CHME3 tem uma

resposta particularmente alterada na presença das células SH-SY5Y APP695 Swe face à

co-cultura com a outra linha de neuroblastoma, possivelmente pela maior acumulação de

Aβ1-40 detetada nessa situação. Nesse modelo, observámos que a microglia inicialmente

apresenta níveis elevados do miR-155 e do miR-146a e níveis reduzidos do miR-124,

semelhante às células ativadas. Com o decorrer do tempo ocorre um aumento gradual da

expressão do miR-124 em detrimento da expressão do miR-155 e do miR-146a, o que

sugere que a microglia progressivamente adquire um fenótipo de ativação alternativo, ou

desativação, que terminará num retorno ao estado de vigilância. Durante todo o tempo de

co-cultura verificámos que a microglia expressa marcadores pro-inflamatórios, em paralelo

com um aumento gradual da expressão dos marcadores anti-inflamatórios sugerindo que a

microglia progressivamente desenvolve uma resposta imunorreguladora. Por outro lado,

observámos que a resposta imunitária inata da microglia foi rapidamente induzida neste

modelo, demonstrada pelo pico imediato da expressão da iNOS, enquanto que a resposta

imunitária adaptativa foi induzida mais tardiamente, traduzida pelo aumento gradual da

expressão do MHC class II.

Deste modo, demonstrámos que as co-culturas compostas pela linha de microglia

CHME3 e pelas células SH-SY5Y APP695 Swe são o modelo in vitro da AD mais adequado

para estudar a resposta da microglia humana e possivelmente utilizar em ensaios de

avaliação de novos agentes terapêuticos que tenham como alvo a microglia.

Palavras chave: Microglia humana, doença de Alzheimer, miR-124, miR-155, miR-146a,

fenótipo


1

I. INTRODUCTION

1. Alzheimer’s disease

Alzheimer’s disease (AD) is a progressive, non-reversible neurodegenerative disorder

that consists in the most common form of dementia by accounting for 50-70% of all

diagnosed cases. In 2015, dementia was estimated to affect more than 46 million people

worldwide, which is predicted to double every 20 years causing a huge economic impact in

health care (Prince et al. 2015).

The global prevalence of AD increases with life expectancy affecting more than one-

third elderly over 85 years old. Following advanced age, family history is the second major

risk factor for AD whereas the presence of specific genetic mutations correlate with

enhanced susceptibility to develop rare early onset familial AD (EOFAD) (45-65 years old) or

most commonly late onset AD (> 65 years old) (Reitz and Mayeux 2014, Tanzi 2012).

Additional non-genetic factors that can predispose to the development of sporadic AD

include some pathological conditions such as the incidence of traumatic brain injury,

cerebrovascular disease and diabetes, and lifestyle aspects such as inadequate diet and

lack of physical and intellectual activity (Reitz and Mayeux 2014).

1.1. Diagnostic and treatment

Initial symptoms of AD include episodic loss of memory characterized by difficulty in

storing and retrieving new information, termed mild cognitive impairment. During the course

of AD, patients progressively evidence memory and cognitive decline, while behavioral

impairment can occur in later AD stages (Reitz and Mayeux 2014). Accordingly, cerebral

damage in early AD is most prominent in areas responsible for the formation and retrieval of

memories such as the entorhinal cortex and hippocampus, though it progressively spreads to

the remaining cortical regions. In parallel, the cholinergic neurons in the basal forebrain are

also commonly injured in AD (Braak and Braak 1991, 1995).

I. Introduction

2

There are no medicines available to prevent AD onset, and the only pharmacologic

options approved are limited to patients ranging from moderate to severe AD stages such as

the cholinesterase inhibitors donepezil, galantamine and rivastigmine, and the N-methyl-D-

aspartate receptor antagonist memantine. These medicines provide some symptomatic

benefits by ameliorating neurologic activity, though they have modest impact on AD

progression as they fail to modify the pathologic process (Kumar et al. 2015). On the other

hand, the lack of reliable biomarkers remains an obstacle for the determination of AD risk, as

well as for establishing AD diagnosis and prognosis. Current approaches for AD diagnosis

include a combination of cognitive and memory tests with brain imaging techniques such as

Positron Emission Tomography, which allows determining the hippocampus volume or

detecting the presence of amyloid plaques when using the Pittsburgh Compound-B. These

are accurate methods for AD diagnosis, though they are not routinely used in clinical practice

for AD stratification (Reitz and Mayeux 2014).

Therefore, innovative biomarkers are critically required contributing to early AD detection

and pharmacologic intervention. Furthermore, unveiling the pathogenesis of AD is essential

to identify novel mechanisms and targets with potential to originate alternative therapeutic

strategies to delay AD progression.

1.2. Pathogenesis

The two major hallmarks of the AD brain consist in the presence of extracellular amyloid

β-peptide (Aβ)-containing senile plaques and intraneuronal deposition of neurofibrillary

tangles (NFTs) composed by hyperphosphorylated tau (h-tau). Since AD is a multifarious

disorder, other events cannot be dissociated from the neurodegenerative process in

particular neuroinflammation.

1.2.1. Amyloid β-peptide and neurofibrillary tangles

Aβ is a small (~ 4 kDa) peptide which is originated from the cleavage of the amyloid

precursor protein (APP), a transmembrane glycoprotein that is ubiquitously expressed in

mammalian tissues. Following protein synthesis, APP is modified by glycosylation leading to

the formation of immature APP, that is predominantly N-glycosylated, and mature APP, that

is N- and O-glycosylated. There are three major isoforms of APP each containing 770, 751 or

695 amino acids, the APP770, APP751 and APP695 respectively, the last being the most

predominant in neurons.


3

APP can be processed through two pathways, the prevalent non-amyloidogenic or the

alternative amyloidogenic pathway (Figure I.1). In the non-amyloidogenic pathway, APP is

cleaved by α-secretase within the Aβ region generating the C-terminal fragment α (CTF-α)

and sAPPα, a large soluble N-terminal ectodomain that is secreted. The CTF-α is further

cleaved by γ-secretase, an enzymatic complex composed by presenilin 1 and 2, nicastrin,

anterior pharynx defective and presenilin enhancer 2, producing the p3 fragment and an APP

intracellular domain (AICD). In the amyloidogenic pathway, APP is primarily cleaved by β-

secretase (also denominated β-site APP cleaving enzyme 1, BACE1) resulting in the release

of sAPPβ and formation of CTF-β. The CTF-β is further cleaved by γ-secretase generating

an AICD and the Aβ monomer. The main form of Aβ produced is 40 residues length (Aβ1-40),

although there is a small proportion of Aβ that is 42 residues length (Aβ1-42), the most prone

to self-aggregate. Aβ aggregation states range from soluble oligomers to insoluble fibrils, the

last being the main component of the senile plaques that typically deposit in the AD brain

(O'Brien and Wong 2011).

The toxicity of extracellular Aβ oligomers and senile plaques mainly relies on their ability

to trigger neuroinflammation (Heppner et al. 2015, Meraz-Rios et al. 2013, Shadfar et al.

2015). On the other hand, intraneuronal accumulation of Aβ oligomers, either produced

intracellularly or reuptaken from the extracellular environment, also play a role in AD

pathogenesis by facilitating the formation of h-tau, disrupting calcium homeostasis and

causing synaptic, proteasome and mitochondrial impairment, thus compromising overall

neuronal function leading to cell death (Cavallucci et al. 2012, LaFerla et al. 2007). The

imbalance between Aβ production and clearance that result in exacerbated accumulation of

Aβ in different assembly states supports the “amyloidogenic cascade hypothesis” of AD

pathogenesis (O'Brien and Wong 2011).

Mutations in the APP gene as well as in genes encoding presenilin 1 and presenilin 2,

the PSEN1 and PSEN2 genes respectively, are known to modify the APP metabolism

towards Aβ generation. These mutations mostly predispose to the incidence of EOFAD,

which represents approximately 5% of all diagnosed AD cases. On the other hand, the major

genetic risk factor to develop late onset AD is the presence of the ε4 allele of the

apolipoprotein E gene, which correlates with deficits in Aβ clearance (Tanzi 2012). Recent

genome-wide association study analysis of sporadic AD cases identified variants in genes

encoding innate immune molecules including the triggering receptor expressed on myeloid

cells 2 (TREM2) (Guerreiro et al. 2013, Jonsson et al. 2013) and the myeloid cell-surface

antigen CD33 (Naj et al. 2011), thereby supporting the involvement of phagocytes namely

microglia, the brain phagocytic cells, in AD pathogenesis.

The Swedish (Swe) mutation, which was first described in 1992, is a specific

modification in the APP gene that correlates with EOFAD (Mullan et al. 1992). This mutation

I. Introduction

4

is characterized by a double amino acid KMNL change in the N-terminal of the APP β-

secretase cleavage site (codons 595 and 596 in APP695), making APP a preferable

substrate for β-secretase. The consequence of the Swe mutation is the enhancement of the

amyloidogenic processing of APP leading to the secretion of exacerbated amounts of Aβ

forms and abnormal intracellular Aβ accumulation (Citron et al. 1992, Martin et al. 1995)

(Figure I.1).

Figure I.1 | Metabolism of the amyloid precursor protein (APP) and representation of the Swedish mutation. Most APP is processed through the non-amyloidogenic pathway, whereas cleavage by α-secretase generates sAPPα, that is secreted, and C-terminal fragment α (CTF-α), which is secondly cleaved by γ-secretase originating the p3 fragment and an APP intracellular domain (AICD). In the amyloidogenic pathway, APP is cleaved by β-secretase resulting in the production of sAPPβ, that is secreted, and CTF-β, which is further cleaved by γ-secretase leading to the generation of the amyloid β-peptide (Aβ). Once formed, Aβ aggregates towards higher complex molecules ranging from oligomers to fibrils, the main components of the senile plaques. All these Aβ assembly states are found in the AD brain and contribute to AD pathogenesis. The Swedish mutation consists in a specific variant of the APP gene defined by a double amino acid KMNL change in the β-secretase cleavage site, making APP a preferable substrate for β-secretase. This mutation results in enhanced APP processing through the amyloidogenic pathway and consequent production of increased amounts of Aβ forms.

The other hallmark of AD is the accumulation of NFTs. The microtubule-associated

protein tau is responsible for the maintenance of the axonal structure by stabilizing the

microtubules, affecting axonal transport of vesicles. There are six tau isoforms ranging from

352 to 441 amino acids in the adult brain deriving from alternative splicing, all containing a

high number of phosphorylation sites. The presence of genetic mutations and covalent

modifications of tau, as well as external events including Aβ-mediated toxicity, oxidative

stress and inflammation, have been postulated to trigger tau hyperphosphorylation and

consequent dissociation from the microtubules. Once tau disengaged, microtubules undergo

conformational changes that promote h-tau aggregation into NFTs which compromise

microtubule polymerization and consequently axonal transport leading to synaptic

dysfunction and neurodegeneration (Ballatore et al. 2007).


5

1.2.2. Neuroinflammation

The involvement of inflammation in AD pathogenesis is assumed for more than two

decades, primarily supported by studies reporting the presence of pro-inflammatory

chemokines and cytokines including interleukin (IL)-1 and IL-6 in the brain, plasma and

cerebrospinal fluid (CSF) of AD patients (Bauer et al. 1991, Blum-Degen et al. 1995, Griffin

et al. 1989). Previous data also postulated that glial activation was a late event in AD,

suggested by the presence of activated microglia and astrocytes in the vicinity of senile

plaques (Dickson et al. 1988, Itagaki et al. 1989).

However, it is now established that the neuroinflammatory response in AD is not

exclusively attributed to the presence of exacerbated amounts of pro-inflammatory and

oxidative species, as deregulated anti-inflammatory mediators are also found in the brain and

circulation of AD individuals (Colton et al. 2006, Cribbs et al. 2012, Sudduth et al. 2013,

Swardfager et al. 2010). Furthermore, current view on AD pathogenesis sustain that glial

activation is not exclusively a consequence of plaque deposition but can preclude Aβ

accumulation, for instance due to the incidence of genetic mutations or due to local/systemic

inflammation. Upon activation, microglia and in a lower fashion astrocytes secrete a wide

range of molecules such as glutamate, cytokines, chemokines, reactive oxygen species

(ROS), nitric oxide (NO), complement factors and byproducts of cyclooxygenase 2 (e.g.

prostaglandins) that can directly promote neuronal apoptosis, or cause marked functional

and structural neuronal impairment leading to death. Besides neurons, the oligodendrocytes

can also be compromised in AD which in turn supports neurodegeneration. Glial activation

can also promote tau phosphorylation and enhance Aβ burden either by supporting APP

amyloidogenic processing or due to inefficient Aβ degradation. In turn, the presence of Aβ in

different assembly states interacts with glia enhancing the neuroinflammatory response,

culminating in a vicious pathological cycle driving AD pathogenesis (Heppner et al. 2015,

Meraz-Rios et al. 2013, Shadfar et al. 2015).

Besides glia, other cells such as brain endothelial cells, infiltrating T lymphocytes,

macrophages and monocytes can also support neuroinflammation in AD. However, along

with astrocytes, these cells might have reduced participation in AD pathogenesis compared

with microglia, since microglia are fundamental for the regulation of neuroinflammation and

maintenance of the brain homeostasis.

I. Introduction

6

2. Microglia: the key players in neuroinflammation

Microglia are the brain-resident myeloid cells that arise during the first wave of

hematopoiesis in yolk sac blood islands (Ginhoux et al. 2010, Mizutani et al. 2012). Microglial

differentiation from myeloid progenitors is particularly driven by the granulocyte macrophage

colony stimulating factor (GM-CSF) and the macrophage colony stimulating factor (M-CSF),

as well as the transcription factors CCAAT/enhancer-binding protein α (C/EBP-α) and PU.1

(Ponomarev et al. 2013).

Microglia are highly dynamic and multipurpose cells, playing fundamental role in the

maintenance of the brain homeostasis. One of the most important functions of microglia

involves their ability to participate in both innate and adaptive immunity, since microglia

produce inflammatory/oxidative agents, have phagocytic capacity and perform antigen

presentation. Microglia are also responsible for the clearance of neurotransmitters and

debris, as well as extracellular matrix (ECM) remodeling and immunoregulation which are

important in the resolution phase of inflammation (Boche et al. 2013).

2.1. Microglial regulation and functions

Microglial regulation is dependent on their interaction with the whole brain

microenvironment where the neuron-microglial crosstalk emerges as the most relevant axis.

This communication involves neuronal secretion of molecules, commonly termed signals,

that are recognized by specific receptors on microglial surface and regulate their activity and

functions.

Under normal conditions, neurons secrete colony stimulating factor 1 (CSF-1) and IL-34

that act as “survival” signals upon binding the CSF-1 receptor on microglial surface,

supporting microglial development and survival. Furthermore, neurons secrete “resting”

signals mainly CD200 and CX3CL1 (also termed fractalkine) that bind the respective targets

CD200R and CX3CR1 (Brown and Neher 2014, Kierdorf and Prinz 2013). These signals are

particularly important for microglia to remain in their quiescent/vigilant state (M0 phenotype),

in which cells are extensively ramified (Figure I.2). Quiescent/vigilant microglia are

characterized by low levels of expression of typical markers of activated cells including

antigen-presenting proteins (CD45, CD80, CD86 and major histocompatibility complex class

II, MHC class II) and integrins (CD11c). Due to this phenotypic profile, quiescent microglia

were firstly thought to be “nonactivated” cells, though they are currently assumed to perform

the brain surveillance. Indeed, M0 microglia are characterized by the expression of anti-

inflammatory cytokines including IL-10 and IL-4, and molecules that are required for tissue

repair such as resistin-like α (FIZZ1) and chitinase 3-like-3 lectin (Ym1, Chi3l3 in humans)


7

resembling alternative activated cells (Ponomarev et al. 2007). Moreover, M0 microglia are

important for sustaining normal neuronal development and functions as they secrete

transforming growth factor β (TGF-β), insulin growth factor 1 and brain-derived neurotrophic

factor (BDNF) (Boche et al. 2013, Ponomarev et al. 2013) (Figure I.2).

After a brain injury, neurons secrete “help” signals that drive microglial migration towards

damaged tissues, and “eat me” or “do not eat me” signals that respectively stimulate or

inhibit neuronal phagocytosis. These signals are recognized through the respective receptors

on microglial surface including cytokine/chemokine receptors and pattern recognition

receptors such as toll-like receptors (TLRs), scavenger receptors, CD33 and TREM2 (Brown

and Neher 2014, Kierdorf and Prinz 2013). These receptors are differently expressed in

microglia in accordance to their phenotype upon activation, which in turn exhibit a wide

spectrum of possibilities depending on stimuli.

2.2. Microglial phenotypic diversity

Distinct molecules were shown to induce microglial polarization towards classic

activated (M1), alternative activated (M2a), type II alternative activated (M2b) or acquired

deactivated (M2c) phenotype, whereas microglial morphology is shifted from ramified to

amoeboid (Ponomarev et al. 2013, Walker and Lue 2015) (Figure I.2).

Microglial classic activation associate with strong pro-inflammatory, cytotoxic and

immune response to pathogen-associated molecular patterns or damage-associated

molecular patterns. These agents are interferon γ (IFN-γ), GM-CSF, tumor necrosis factor α

(TNF-α) and lipopolysaccharide (LPS). After these molecules bind to the respective receptors

on microglial surface (IFNR, GM-CSFR, TNFR and TLR4) they promote the activation of

signaling pathways including Janus kinase/signal transducer and activators of transcription 1-

4 (JAK/STAT1-4), IFN regulatory factors (IRFs), p38 and JNK mitogen-activated protein

kinase (MAPK) and nuclear factor κB (NF-κB) (Freilich et al. 2013). This leads to the

transcription of pro-inflammatory genes such as cyclooxygenase 2, TNF-α, IL-1β, IL-6, IL-12

and IL-23. Functionally, classic activated microglia exhibit phagocytic ability due to the

expression of the scavenger receptor CD68 and Fc receptors, which mediate phagocytosis

of molecules that have been opsonized with antibodies. M1 microglia are fundamental in the

innate immune response by typically expressing inducible nitric oxide synthase (iNOS),

which metabolizes arginine towards NO. Together with the secretion of ROS,

metalloproteinases and collagenases, the production of NO contributes for tissue

degradation (Colton 2009). Besides participation in innate immunity, M1 microglia participate

in the adaptive immune response by expressing CD40, CD45, CD80, CD86 which mediate T

I. Introduction

8

cell activation. Furthermore, they are often characterized by overexpression of MHC class

II/human leucocyte antigen (HLA-DR), though some data report that MHC class II is not

exclusively expressed by amoeboid/activated microglia (Michell-Robinson et al. 2015,

Ponomarev et al. 2013, Walker and Lue 2015).

On the other hand, the presence of any of M2 microglial phenotypes correlates with anti-

inflammatory events. Alternative microglial activation towards the M2a phenotype is induced

by IL-4 and IL-13, and is particularly important for protecting the brain against parasites. IL-4-

mediated activation of microglia involves several transcriptional networks such as STAT6.

Concomitantly, IL-4 stimulation inhibits the expression of STAT1-4 and IRF3 genes involved

in classic microglial activation (Freilich et al. 2013) and the M1-related markers CD45 and

NO (Ponomarev et al. 2007). M2a microglia are particularly characterized by increased levels

of IL-1 receptor antagonist and mannose receptor (CD206). Moreover, they overexpress

arginase 1 (Arg1), which competes with iNOS for arginine required for the formation of

collagen (Colton 2009). Along with FIZZ1 and Ym1, upregulation of Arg1 correlates with

ECM reconstruction and protection. Moreover, M2a microglia secrete the anti-inflammatory

cytokines TGF-β, IL-10, IL-4 and IL-13 which are important for immunosuppression (Cherry

et al. 2014, Michell-Robinson et al. 2015, Ponomarev et al. 2013, Walker and Lue 2015).

When microglia are exposed to immune complexes and LPS, they acquire the

immunoregulatory M2b (or type II) phenotype which represents a lower alternative activated

state as a result of its mixed M1/M2a profile. M2b microglia are essential for clearing away

ROS and NO released during M1 activation, protecting the brain against LPS insult. The

polarization of myeloid cells towards the M2b phenotype requires two signals, firstly involving

the binding of ligands through the Fcγ receptor and secondly through TLR4. The resulting

M2b phenotype is characterized by the release of pro-inflammatory (IL-1β, TNF-α and IL-6)

simultaneously with anti-inflammatory (IL-10 and IL-4) cytokines. However, M2b microglia

secrete low levels of IL-12, which can be used to differentiate M1 and M2b microglia. In

addition, M2b cells express MHC class II, CD80 and CD86, making them prone to participate

in adaptive immunity (Cherry et al. 2014, Michell-Robinson et al. 2015, Ponomarev et al.

2013, Walker and Lue 2015).

Finally, stimulation with either glucocorticoids or TGF-β and IL-10 induces microglial

deactivation towards the M2c phenotype. M2c microglia exhibit some markers of M2a and

M2b cells including FIZZ1, TGF-β, IL-10, Arg1 and CD206, though they are particularly

distinguished from them by the expression of the scavenger receptor CD163. Functionally,

M2c microglia are mainly important for immunosuppression and debris scavenging (Cherry et

al. 2014, Michell-Robinson et al. 2015, Ponomarev et al. 2013, Walker and Lue 2015).

Besides M0, M1, M2a, M2b and M2c microglial phenotypic markers and functions have

been quite well described in the healthy brain, due to microglial plasticity some of their


9

characteristics might overlap, and novel phenotypes may arise making it difficult to assess

microglia under pathological conditions (Walker and Lue 2015). Furthermore, once studying

AD, additional age-related phenotypes should be taken into account.

2.3. Microglia in the aged brain

It is accepted that aging induces marked changes in microglia culminating in

overwhelming dysfunction, but it has not been established whether aged microglia become

over-activated upon stimulation or degenerate and lack their ability to respond as a

consequence of cellular senescence (Figure I.2).

Some reports demonstrated that a range of pro-inflammatory and immune markers are

aberrantly expressed in the brain of healthy elderly (Cribbs et al. 2012, Schuitemaker et al.

2012). These observations support the hypothesis of several authors who argue that

microglia are primed in the aged brain, thereby developing exacerbated and prolonged

neuroinflammatory response after stimulation (Norden and Godbout 2013, Perry V. H. et al.

2010, van Gool et al. 2010). In elderly, microglial activation during sepsis was associated

with enhanced detrimental behavioral outcome (Lemstra et al. 2007). After peripheral LPS

administration in aged mice, microglia were shown to produce exaggerated amounts of pro-

inflammatory and reactive species (Chen et al. 2008, Godbout et al. 2005). In similar study

conditions, it was demonstrated that microglia lack their ability to respond to the M2a

mediator IL-4, failing to recover from LPS stimulation due to lack of Arg1 (Fenn et al. 2012,

Fenn et al. 2014). Failure in polarizing aged microglia towards the M2a phenotype might

provide an explanation for the presence of reduced levels of IL-4 in the brain of aged mice

which in turn impacts in neuronal synaptic function (Nolan et al. 2005). These data suggest

that microglial dysfunction in the aged brain occurs as a consequence of their primed

response upon pro-inflammatory stimulation concomitantly with irresponsiveness to anti-

inflammatory stimulation, leading to the generation of uncontrolled inflammatory and

oxidative stress in the brain increasing the vulnerability to neurodegeneration.

Streit and his collaborators identified, in brain samples of elderly, a population of

microglia with specific characteristics which was reported as dystrophic/senescent microglia

(Streit et al. 2004). Phenotypically, dystrophic microglia might be misinterpreted due to the

expression of HLA-DR (Streit et al. 2004) as it is also expressed in functional human young

microglia (Broderick et al. 2000, Melief et al. 2012). Morphologically, dystrophic microglia are

distinct from ramified and amoeboid cells by exhibiting condensed nucleus, fragmented

cytoplasmic processes (cytorrhexis), deramification and spheroidal/bulbous swellings. All

these features have been attributed to progressive telomere shortening and decreased

I. Introduction

10

telomerase activity which can lead to replicative cellular senescence (Flanary and Streit

2004, 2005, Flanary et al. 2007), culminating in accidental microglial death manifested by

remarkable cytorrhexis (Streit 2002, 2005, Streit and Xue 2009, Streit et al. 2004). Senescent

microglia exhibit irreversible dysfunction that includes self-renewal inability, reduced vitality

as well as motility and phagocytic impairment. This compromises the brain homeostasis

predisposing to the development of age-related neurodegenerative disorders, particularly AD

(Streit 2005, 2006).

Dystrophic microglia are thought to be spontaneously seen only in the aged human

brain and not in rodents as a consequence of lifestyle and environmental factors that

contribute to microglial senescence throughout life (Streit and Xue 2012, 2013, Streit et al.

2014). However, studies of primary murine microglia obtained from old mice (Njie et al. 2012,

Sierra et al. 2007), or neonatal mice followed by prolonged in vitro culture as performed in

our laboratory (Caldeira et al. 2014), demonstrated that aged microglia acquire properties of

senescent cells including alterations in morphology, phenotypic profile and inability to

respond appropriately to stimuli. Altogether, these findings support that a wide range of

microglial phenotypes probably co-exist in the aged brain, playing different roles in

neurodegeneration.


11

Figure I.2 | Microglial phenotypes in the healthy (M0, M1, M2a, M2b and M2c) and aged (dystrophic and primed) brain. In the normal brain, neurons release several “resting” signals including CX3CL1 and CD200 inducing microglia to remain quiescent/vigilant (M0). In turn, M0 microglia excrete insulin growth factor 1 (IGF-1), brain-derived neurotrophic factor (BDNF) and transforming growth factor β (TGF-β) that are important for supporting normal neuronal development and functions. During brain surveillance, stimuli such as lipopolysaccharide (LPS) or interferon γ (IFN-γ) can induce microglial cytotoxic/classic activation (M1). In this state, microglia express increased levels of toll-like receptors (TLRs) and immune markers (e.g. major histocompatibility complex class II, MHC class II), while secrete pro-inflammatory mediators (e.g. interleukin (IL)-6, IL-1β, tumor necrosis factor α, TNF-α) and reactive species due to the enhanced expression of inducible nitric oxide synthase (iNOS). On the other hand, stimulation of microglia with IL-4/IL-13, LPS/immunocomplexes or IL-10/TGF-β/glucocorticoids trigger microglial alternative activation (M2a), less alternative activation (M2b) or acquired deactivation (M2c), respectively. M2a microglia are important for the generation of an anti-inflammatory environment by secreting anti-inflammatory cytokines (TGF-β), and for the extracellular matrix (ECM) repair by exhibiting increased levels of arginase 1 (Arg1). The expression of IL-1 receptor antagonist (IL-1Ra) is considered a key biomarker for M2a microglia, whereas they antagonize the synthesis of pro-inflammatory markers. M2b microglia are immunoregulatory cells by exhibiting a mixed M1/M2a phenotype characterized by pro-inflammatory (IL-6, IL-1β, TNF-α) and anti-inflammatory (IL-10) markers. Finally, M2c microglia are important in the resolution phase of inflammation particularly for debris scavenging and immunoregulation, as they are characterized by enhanced levels of CD163, IL-10 and TGF-β. Additional microglial phenotypes have been proposed to populate the aged brain possibly playing a role in neurodegeneration: dystrophic/senescent microglia, which are characterized by condensed nucleus and swelling formation, concomitantly with irresponsiveness to stimuli and lack of neuronal supportive functions; and primed microglia, which are over-responsive to stimuli, especially systemic infection, leading to the generation of exacerbated and prolonged neuroinflammation.

2.4. Microglial deregulation in Alzheimer’s disease

As stated above, neuroinflammation is currently assumed to participate in AD

pathogenesis by sustaining the accumulation of exacerbated amount of Aβ and NFTs in the

AD brain. Since microglia play a pivotal role in the regulation of neuroinflammation, it is

widely accepted that the whole neurodegenerative process might depend on microglial

functionality, which can be affected by several environmental and genetic factors that

ultimately can drive irreversible microglial impairment (Heneka et al. 2014, Heppner et al.

2015, Mosher and Wyss-Coray 2014, Prokop et al. 2013).

I. Introduction

12

Under normal conditions, quiescent microglia (M0) promptly recognize distinct stimuli

that trigger microglial pro-inflammatory (M1) or anti-inflammatory (M2) response. Microglia

are appropriately induced to proliferate, secrete cytokines, chemokines and oxidative

species, undergo chemotaxis or phagocytosis to protect the healthy neurons against

injurious agents. Following the resolution phase of inflammation, microglial cells return to

their quiescent/vigilant state thereby restoring the brain homeostasis.

In AD, the presence of pathological protein aggregates particularly Aβ, alterations in the

central nervous system (CNS) (e.g. trauma), the incidence of systemic or local inflammatory

disorders and/or mutations in specific genes can support microglial deregulation by affecting

their phagocytic ability and motility, as well as cytokine production (Heppner et al. 2015,

Prokop et al. 2013). The M1 and M2a/M2b/M2c microglial activation states are quite well

characterized based on their surface markers, products secreted and functions in normal

conditions, though it has not been yet understood whether the presence of these microglial

phenotypes individually affect the course of AD. Besides classic activated microglia typically

correlate with cytotoxic features, numerous studies performed in transgenic AD mouse

models demonstrate that the presence of microglia exhibiting M1-related markers might have

beneficial effects by reducing Aβ pathology (Varnum and Ikezu 2012, Wilcock 2012). On the

other hand, the presence of M2 microglia is not exclusively attributed to microglial protective

functions in AD, as M2 microglial phenotypic markers are found in the brain both in early and

late AD stages (Sudduth et al. 2013). Moreover, studies of transgenic AD mouse models

provide controversial data regarding the role of M2a, M2b and M2c microglia controlling Aβ

pathology (Varnum and Ikezu 2012, Wilcock 2012). For instance, it was recently

demonstrated that the accumulation of IL-10, a major anti-inflammatory cytokine, might

inhibits microglial ability to clear Aβ (Michaud and Rivest 2015). On the other hand, it has

been highly discussed whether mutations in genes encoding TREM2 and CD33, which are

considered markers of M2 microglia (Walker and Lue 2015), affect microglial ability to uptake

Aβ in AD (Heppner et al. 2015, Prokop et al. 2013).

Besides it is still debatable whether M1 and M2 microglial phenotypes play detrimental

or protective roles in AD, it seems clear that the use of inflammation modulator treatments,

including non-steroidal anti-inflammatory drugs and glucocorticoids, should be carefully

considered as they can deregulate microglial activation towards harmful phenotypes when

microglia are still functional (Meraz-Rios et al. 2013). However, chronic exposure to Aβ,

cytokines and chemokines can drive microglial dysfunction towards primed activation states,

where microglia respond exaggeratedly to stimuli generating strong pro-inflammatory

environment. As abovementioned, the presence of primed microglia in the aged brain is

particularly deleterious in both humans and mice (Godbout et al. 2005, Lemstra et al. 2007),

possibly predisposing to the development of AD. At this time, therapeutic interventions


13

should be aimed at the restoration of normal microglial function before microglia come in

senescence, an irreversible state of microglial dysfunction/dystrophy. Streit and his

colleagues have been proposing an alternative perspective on AD pathogenesis centered in

microglial dysfunction, as they found that microglial dystrophy is enhanced in the brain of

individuals with increased Aβ load compared with Aβ-free controls (Flanary et al. 2007).

Moreover, they reported that dystrophic microglia co-localize with both Aβ deposits and tau-

composing structures in the brain of AD patients (Streit et al. 2009), suggesting not only that

Aβ induces microglial senescence rather than activation, but also that the presence of

dystrophic microglia prompts tau pathology. On the other hand, they claim that some factors

including lifestyle, diet, physical and mental activities, as well as exposure to drugs and

pollutants are relevant for driving microglial senescence, supporting the idea that microglial

dystrophy and AD can occur spontaneously only in humans (Streit and Xue 2012, 2013,

Streit et al. 2014).

In summary, it seems clear that microglia are deregulated in AD, and that distinct

functional and/or dysfunctional phenotypes may co-exist playing different roles in the AD

brain. However, more attention should be focused on identifying relationships between

microglial phenotypes and events in AD, particularly using brain tissues and cells of human

origin.

3. MicroRNAs: biogenesis and functions

MicroRNAs (miRNAs or miRs) are small single-stranded RNAs that are endogenously

expressed in diverse species and cells. Besides being non-coding, miRNAs regulate the

expression of specific genes at the post-transcriptional level blocking protein synthesis.

MiRNAs can be originated through two different pathways depending on the primary

genomic loci: the canonical and non-canonical pathways. In the canonical pathway, the RNA

polymerase II mediates miRNA gene transcription to pri-miRNA, a large stem-loop hairpin

structure. Then, the pri-miRNA is asymmetrically cleaved in the nucleus towards the

generation of a pre-miRNA, mediated by an enzymatic complex containing Drosha, an

RNAse III endonuclease, and DiGeorge syndrome critical region gene 8. In the non-

canonical pathway, the miRNA precursor, named mirtrons, are directly spliced from the

intronic sequences of transcribed genes forming a lariat structure which is de-branched to

form the pre-miRNA hairpin structure. The processed pre-miRNA either obtained through the

canonical or non-canonical pathways is then exported to the cytoplasm by Exportin-

5/RanGTP where it is cleaved by another RNAse III endonuclease (Dicer), losing the stem-

loop of the precursor to produce a double-stranding miRNA molecule. Then, the functional

I. Introduction

14

strand associates with Argonaute proteins 1-4 in order to originate a RNA-induced silencing

complex, while the complementary strand, usually denoted as miRNA*, is rapidly degraded.

Finally, RISC can recognize and bind to complementary seed sequences in the 3’

untranslated region of target mRNAs, resulting in their degradation and consequent

repression of the translation process (Bartel 2004, Winter et al. 2009).

Several miRNAs have been implicated in many important biological processes including

cell development, proliferation, differentiation, inflammation and immunity. Hence,

understanding the role of miRNAs in the regulation of genes involved in microglial

neuroinflammatory response is fundamental to assess microglial profile and functions in

pathological conditions.

3.1. Inflammation-related microRNAs in microglia

Several miRNAs have been so far identified to be likely involved in the regulation of

microglial functions (Michell-Robinson et al. 2015). With regards to neuroinflammation,

numerous studies support that the miR-124, miR-155 and miR-146a play a pivotal role in the

regulation of microglial phenotype by promoting microglial quiescence (miR-124), or by

driving microglial inflammatory and immune response (miR-155 and miR-146a) (Ponomarev

et al. 2013).

3.1.1. MiR-124

The miR-124 is a brain-enriched miRNA, whereas it is particularly expressed in neurons

(Jovicic et al. 2013). During the CNS development, the expression of miR-124 is important

for supporting neuronal differentiation and maturation (Makeyev et al. 2007, Visvanathan et

al. 2007) and regulate axonal and dendritic branching (Franke et al. 2012). Moreover, it can

also disinhibit neurite outgrowth in an inflammatory environment (Hartmann et al. 2015).

In microglia, C/EBP-α is established as one of the main targets of miR-124. C/EBP-α

was reported to be expressed in low levels in quiescent microglia, though it is upregulated

upon microglial activation (Walton et al. 1998). Furthermore, C/EBP-α and its downstream

target PU.1 play an important role driving the development of myeloid cells both in the first

and second waves of hematopoiesis. Upon miR-124 inhibition of C/EBP-α/PU.1,

differentiation of macrophages to adult microglia was shown to be favored in detriment of

monocytes proliferation (Ponomarev et al. 2011).

The miR-124 was found to be crucial for maintaining microglial quiescence, as miR-124

inhibition of C/EBP-α reduces the expression of CD45, MHC class II and F4/80, iNOS and


15

TNF-α, all involved in microglial pro-inflammatory and immune response, while enhances the

expression of the anti-inflammatory agents FIZZ1, Arg1 and TGF-β (Ponomarev et al. 2011)

(Figure I.3). In a mice model of chronic pain, intrathecal administration of miR-124 was

shown to normalize the M1/M2 phenotypic markers ratio after an inflammatory insult, which

might has beneficial effects in disease (Willemen et al. 2012). On the other hand, during

experimental autoimmune encephalomyelitis, peripheral administration of miR-124 was

shown to promote systemic deactivation of macrophages (Ponomarev et al. 2011). These

data suggest that miR-124 not only contributes to maintain the MHC class IIlow/CD45low profile

of quiescent microglia, but might also has an immunoregulatory role by promoting cell

deactivation while enhance the expression of anti-inflammatory agents. When macrophages

reach the brain, they are possibly deactivated due to direct transfer of miR-124 from miR-

124+ neurons through exosomal shuttle vesicles (Ponomarev et al. 2013). Since microglial

expression of miR-124 does not require neither IL-4/IL-13 receptors, typically activated when

microglia are polarized towards the M2a phenotype, nor STAT6 signaling (Veremeyko et al.

2013), it is also reasonable that miR-124+ neurons, rather than IL-4, regulate the levels of

miR-124 in quiescent microglia, besides IL-4 is highly expressed in the normal CNS

(Ponomarev et al. 2007). On the other hand, when quiescent microglia are stimulated with IL-

4 towards the alternative activated state, the levels of miR-124 decay (Freilich et al. 2013).

Recently, it was demonstrated that the TNF receptor-associated factor 6 (TRAF6) is a

direct target of miR-124 (Qiu et al. 2015) providing alternative mechanisms for miR-124-

mediated immunosuppression in microglia.

3.1.2. MiR-155

The miR-155 is considered a pro-inflammatory miRNA, as its expression is upregulated

in response to LPS, TNF-α or IFN but downregulated in response to anti-inflammatory

cytokines such as IL-10 and TGF-β in myeloid cells (McCoy et al. 2010, O'Connell et al.

2007, Tili et al. 2007).

In murine microglia, LPS was shown to induce miR-155 upregulation as a result of the

activation of many inflammatory transcription factors including NF-κB, c-Jun, STAT1-4, and

IRF1, IRF3, IRF7 and IRF8 (Freilich et al. 2013). In murine N9 microglial cell line, miR-155

overexpression was reported to directly inhibit the expression of suppressor of cytokine

signaling 1 (SOCS1), a key repressor of NF-κB and JAK/STAT1 signaling pathways.

Targeting SOCS1 induces the upregulation of several M1 markers including IL-1β, IFN-γ,

iNOS, IL-6 and TNF-α, potentiating pro-inflammatory and immune microglial response

(Cardoso et al. 2012) which can have detrimental impact on neurogenesis (Woodbury et al.

I. Introduction

16

2015) (Figure I.3). On the other hand, the expression of SOCS1 can be restored upon miR-

155 suppression (Kim et al. 2014).

Besides supporting classic microglial activation, upregulation of miR-155 was shown to

inhibit the STAT6 anti-inflammatory signaling pathway in microglia (Freilich et al. 2013) and

macrophages (Martinez-Nunez et al. 2011). Additionally, miR-155 was reported to inhibit

microglial alternative activation by repressing c-Maf, a transcription factor that regulates the

anti-inflammatory response in myeloid cells (Su et al. 2014). In murine and human myeloid

cells, miR-155 was also shown to directly repress C/EBP-β (He et al. 2009, Worm et al.

2009), a transcription factor that regulates the expression of several anti-inflammatory genes

including IL-10, Arg1, IL-13 receptor α1 and CD206 (Ruffell et al. 2009). C/EBP-β can be

positively regulated by the transcriptional activity of cyclic AMP response element-binding

(CREB) via TLR4-p38 MAPK (Ananieva et al. 2008, El Kasmi et al. 2008), or STAT6 via IL-4

receptor-JAK (Albina et al. 2005), and it is particularly important for sustaining

immunosuppression and tissue repair (Figure I.3).

Overexpression of miR-155 was also reported to occur in brain sections and microglia of

aged mice compared with samples of adult counterparts (Fenn et al. 2013), suggesting that

deregulated expression of miR-155 in elderly potentially provide favorable conditions to the

development of inflammation-related neurodegenerative disorders.

3.1.3. MiR-146a

Like miR-124, the miR-146a is also considered a brain-enriched miRNA though it is

rather expressed in microglia than in neurons (Jovicic et al. 2013).

The miR-146a is upregulated in myeloid cells in response to TNF-α, IL-1β or LPS,

through the activation of NF-κB (Li Y. Y. et al. 2011c, Lukiw 2012, Perry M. M. et al. 2008).

However, upregulation of miR-146a negatively regulates NF-κB by targeting two components

of the TLR signaling pathway, the IL-1R-associated kinase 1 (IRAK1) and TRAF6 (Taganov

et al. 2006). Inhibition of IRAK1 and TRAF6 blocks TLR signaling by reducing

phosphorylation and degradation of the inhibitor of κB, which consequently blocks the

translocation of the NF-κB to the nucleus. As a consequence, miR-146a promotes abrogation

of NF-κB-mediated transcription of several pro-inflammatory genes such as IL-1β, IFN-γ,

iNOS, IL-6 and TNF-α, attenuating both the immune and inflammatory responses. Due to the

inhibition of NF-κB transcriptional activity, miR-146a also generates a negative feedback on

its own expression, as well as on the expression of miR-155 (Rusca and Monticelli 2011)

(Figure I.3). In primary young murine macrophages, lack of miR-146a expression was shown

to result in loss of immunological tolerance and exacerbated pro-inflammatory response to


17

LPS, generating harmful uncontrolled chronic inflammation (Boldin et al. 2011). Altogether,

these data suggest that miR-146a overexpression acts like an inflammatory break while

triggers the resolution of inflammation.

However, some studies evoked that miR-146a overexpression in the brain potentiates

inflammation rather than constraints. Like other NF-κB-sensitive miRNAs, upregulation of

miR-146a was found to inversely correlate with the expression of the complement factor H

(CFH), an important repressor of the innate immune response and inflammatory signaling

(Lukiw et al. 2008). These findings were validated in human neuron-glial (HNG) co-cultures,

human astroglial (HAG) and human microglial (HMG) cells, whereas TNF-α-induced miR-

146a coupled with CFH and IRAK1 repression (Li Y. Y. et al. 2011b). In HAG cells, it was

also shown that miR-146a inhibition of IRAK1 resulted in compensatory NF-κB-mediated

upregulation of IRAK2 (Cui et al. 2010), suggesting that IRAK2 can drive an alternative

mechanism for NF-κB activation after miR-146a overexpression. Nevertheless, IRAK2 was

reported to be repressed by miR-146a in murine macrophages (Hou et al. 2009), as well as

in human astrocytes (Iyer et al. 2012) and in CHME3 microglia (Sharma et al. 2015),

suppressing NF-κB activation and inflammation. These data support the controversy

regarding the role of miR-146a in the regulation of inflammation and immunity, especially

concerning the brain.

On the other hand, miR-146a is considered a marker of cellular senescence (Olivieri et

al. 2013a, Olivieri et al. 2013b). A recent study performed in our laboratory reported that,

when primary neonatal murine microglia are cultured in vitro for long time, they acquire a

miR-146a-enriched profile and decreased levels of miR-124 and miR-155, which together

with other markers is indicative of microglial senescence and loss of function (Caldeira et al.

2014). Interestingly however, studies performed in primary cells and brain tissues obtained

from aged mice demonstrated that miR-146a is overexpressed in macrophages and brain

tissues but not in microglia (Fenn et al. 2013, Jiang et al. 2012, Li N. et al. 2011a). Age-

related NF-κB activation can be one of the reasons for the upregulation of miR-146a in

elderly (Ye and Johnson 2001), which in turn might limit senescence-associated

inflammation by inhibiting the expression of pro-inflammatory cytokines (Bhaumik et al. 2009,

Jiang et al. 2012).

I. Introduction

18

Figure I.3 | Regulation of inflammation and immunity by miR-124, miR-155 and miR-146a. The miR-124 is an important mediator of microglial quiescence by directly targeting CCAAT/enhancer-binding protein α (C/EBP-α), consequently affecting the C/EBP-α/PU.1 pathway. On the one hand, inhibition of C/EBP-α reduces microglial proliferation while increases differentiation. On the other hand, miR-124 represses C/EBP-α transcriptional activity suppressing the expression of several cell surface molecules that are important for mediating microglial immunity, including major histocompatibility complex class II (MHC class II) and CD45. The miR-155 directly targets the suppressor of cytokine signaling 1 (SOCS1), an inhibitor of two important signaling pathways that are activated after microglial recognition of pro-inflammatory cytokines (e.g. interleukin (IL)-6 and interferon γ, IFN-γ) or lipopolysaccharide (LPS) via toll-like receptor 4 (TLR4): Janus kinase/signal transducer and activators of transcription 1 (JAK/STAT1) and nuclear factor κB (NF-κB). By targeting SOCS1, miR-155 promotes classic activation of microglia which is characterized by the expression of several pro-inflammatory and immune markers sustaining both cytotoxic and immune response. In addition, the miR-155 targets C/EBP-β which mediates the transcription of anti-inflammatory agents such as Arginase 1, IL-10, IL-13 receptor α1 (IL-13Rα1) and mannose receptor (CD206) required for immunoregulation and wound healing. C/EBP-β-mediated transcription of anti-inflammatory genes can in turn be regulated through TLR4-p38 mitogen-activated protein kinase (MAPK) or IL-4 signaling. Besides controversy, the miR-146a is considered an inflammatory break as it targets two transducers involved in NF-κB signaling that are downstream of TLR4, the IL-1R-associated kinase 1 (IRAK1) and tumor necrosis factor receptor-associated factor 6 (TRAF6). Once miR-146a targets IRAK1 and TRAF6, it inhibits the phosphorylation and degradation of the inhibitor of κB (IκB) blocking the translocation of NF-κB to the nucleus. As a consequence, miR-146a overexpression reduces NF-κB-mediated transcription of pro-inflammatory and immune markers while negatively regulate its own expression. Furthermore, miR-146a might also negatively regulate the expression of miR-155 through the inhibition of its transcription by NF-κB, or c-Jun via TLR4-JNK MAPK signaling pathway.

3.2. MicroRNA profile in Alzheimer’s disease

The miR-124, miR-155 and miR-146a have proven to be crucial in the regulation of

microglia in the healthy brain, though their profile and role in AD are still unclear.

Several studies performed in hippocampal brain samples of AD patients ranging from

early to severe disease stages demonstrated that miR-124 is downregulated (Lau et al.

2013, Lukiw 2007, Wang et al. 2011). Downregulation of miR-124 in AD might induce

neuronal impairment by supporting Aβ generation through the regulation of APP splicing

(Smith P. et al. 2011), or due to the upregulation of its direct target BACE1, as demonstrated

in Aβ1-42-treated PC12 pheochromocytoma cells and rat hippocampal neurons (Fang et al.

2012).


19

In contrast to miR-124, the miR-155 was reported to be overexpressed in circulating

fluids and cells of AD individuals including CSF, extracellular fluid (ECF) (Alexandrov et al.

2012, Lukiw et al. 2012), peripheral blood mononuclear cells (Schipper et al. 2007) and

blood-derived monocytes (Guedes et al. 2016). In Aβ42-stressed HNG co-cultures, miR-155

overexpression was found to negatively correlate with CFH (Lukiw et al. 2012) suggesting

that miR-155 prompts AD-related inflammation. These findings were corroborated by data

obtained from 3xTg AD mice brain, whereas miR-155 overexpression, concomitantly with

SOCS1 downregulation, was correlated with the generation of strong inflammatory

environment preceding the deposition of senile plaques (Guedes et al. 2014).

Several studies performed in cortical and hippocampal brain samples of AD patients

ranging from early to severe disease stages showed that miR-146a is overexpressed in both

brain regions during the whole course of AD (Cui et al. 2010, Lau et al. 2013, Li Y. Y. et al.

2011c, Lukiw et al. 2008). Another study reported that miR-146a overexpression occurs only

in the hippocampus of early AD individuals but not in later stages, suggesting that miR-146a

elevation mostly contribute to early AD events (Muller et al. 2014). Interestingly, miR-146a

upregulation in the brain might be specific of AD and not related with other pathologies such

as amyotrophic lateral sclerosis, Parkinson’s disease or schizophrenia (Sethi and Lukiw

2009).

Controversial results regarding miR-146a expression in the CSF, ECF and plasma are

also found, since some authors detected miR-146a upregulation (Alexandrov et al. 2012,

Lukiw et al. 2012) while others detected miR-146a downregulation, suggesting that miR-146a

upregulation in AD might occur only in the brain (Kiko et al. 2014). Another report

corroborated that miR-146a is downregulated in the CSF of AD patients, and identified the

presence of blood-derived cells in the CSF as a possible confounding criteria for the

detection of miR-146a upregulation in other studies (Muller et al. 2014). Interestingly

however, a recent analysis corroborated that miR-146a is upregulated in CSF samples free

of blood contaminations of AD patients (Denk et al. 2015).

Stimulation of human brain cells with Aβ42 and pro-inflammatory cytokines was also

shown to result in the miR-146a upregulation, while affecting the expression of important

regulators of inflammation and immunity (Cui et al. 2010, Li Y. Y. et al. 2011b, Lukiw et al.

2008, Lukiw et al. 2012). For instance, miR-146a overexpression in Aβ42-stressed human

neuronal and HMG cells, as well as in HNG co-cultures, was found to repress CFH

expression (Li Y. Y. et al. 2011b, Lukiw et al. 2008, Lukiw et al. 2012). Since these findings

were validated in the human AD brain (Lukiw et al. 2008), they support the hypothesis that

overexpression of miR-146a might potentiate inflammation in AD. On the other hand, the

presence of enhanced levels of miR-146a in Aβ42-stressed HAG cells and in the brain of AD

patients was found to correlate with decreased levels of its direct target IRAK1 but increased

I. Introduction

20

levels of IRAK2 (Cui et al. 2010, Li Y. Y. et al. 2011b), suggesting that elevation of IRAK2

following miR-146a inhibition of IRAK1 might represent an alternative pathway for miR-146a

to potentiate inflammation in AD. Furthermore, miR-146a overexpression in HNG co-cultures

was shown to repress TSPAN12 under Aβ42 exposure (Li Y. Y. et al. 2011b). Since

TSPAN12 regulates α-secretase activity (Xu et al. 2009), miR-146a inhibition of TSPAN12 is

suggestive of induction of APP amyloidogenic cleavage. Moreover, abundance of miR-146a

in the brain of two AD mouse models, Tg2576 and 5xFAD mice, was found to correlate with

increased senile plaque deposition and synaptic pathology (Li Y. Y. et al. 2011c). These data

demonstrate that miR-146a can play different roles in AD either by regulating inflammation or

influencing Aβ pathology.

In summary, although available data demonstrate that miR-124 might be downregulated

while miR-155 might be upregulated in AD, there is much more controversy in classifying the

expression of miR-146a. Still, most data support that it might be upregulated in AD (Table

I.1).

3.3. Deregulation of microglial microRNAs in Alzheimer’s disease

As we stated above, balanced expression of miR-124, miR-155 and miR-146a is

fundamental to fine-tune microglial phenotype sustaining the brain homeostasis. Hence,

aberrant expression of these miRNAs might probably enhance microglial deleterious

behavior in detriment of their supportive functions, which likely impact in AD initiation and

progression. In our knowledge, there are very few studies devoted to the assessment of

microglial regulation by miRNAs in AD, and there are only available data concerning miR-155

and miR-146a.

In Aβ42-stressed HMG cells, elevation of miR-146a was shown to repress CFH (Li Y. Y.

et al. 2011b). This might represent one of the mechanisms by which miR-146a

overexpression sustains exacerbated microglial neuroinflammatory response in AD.

However, additional efforts are required in order to understand whether microglial miR-146a

deregulation in AD affects the expression of other targets that are important for the regulation

of microglial inflammatory and immune response, namely IRAK1 and TRAF6.

In N9 murine microglia exposed to Aβ fibrils, c-Jun overexpression was found to occur

concomitantly with miR-155 upregulation. These findings corroborate that c-Jun

transcriptional activity early in the brain of 3xTg AD mice might be responsible for miR-155

overexpression as well as microglial activation. In turn, miR-155-mediated microglial

activation might prompt the generation of a strong inflammatory environment favorable to the

deposition of senile plaques (Guedes et al. 2014).


21

Several reports have been performed in order to assess the expression of miR-124,

miR-155 and miR-146a in the brain and circulating fluids/cells of AD individuals, and also to

clarify the role of these three miRNAs in AD pathology using AD transgenic mice and cellular

models. However, there are very few data regarding the role of miR-155 and miR-146a in the

regulation of microglia in AD, and none concerning miR-124 (Table I.1), which emphasizes

the need of additional efforts in this context.

Table I.1 | Expression of miR-124, miR-155 and miR-146a in samples of Alzheimer’s disease (AD) patients, in vivo and in vitro AD models, and evidence of their role in the regulation of microglia in AD. Legend: ↑, increased in; ↓, decreased in; Aβ, amyloid β-peptide; BDM, blood-derived monocytes; CFH, complement factor H; CSF, cerebrospinal fluid; ECF, extracellular fluid; HAG, human astroglial; HMG, human microglial; HN, human neuronal; HNG, human neuron-glial; PBMC, peripheral blood mononuclear cells; SOCS1, suppressor of cytokine signaling 1. References: 1 (Lau et al. 2013, Lukiw 2007, Wang et al. 2011); 2 (Fang et al. 2012); 3 (Alexandrov et al. 2012, Lukiw et al. 2012); 4 (Schipper et al. 2007); 5 (Guedes et al. 2016); 6 (Lukiw et al. 2012); 7 (Guedes et al. 2014); 8 (Cui et al. 2010, Lau et al. 2013, Li Y. Y. et al. 2011b, Lukiw et al. 2008, Sethi and Lukiw 2009); 9 (Alexandrov et al. 2012, Lukiw et al. 2012, Denk et al. 2015); 10 (Li Y. Y. et al. 2011c, Lukiw et al. 2008, Lukiw et al. 2012); 11 (Li Y. Y. et al. 2011b); 12 (Muller et al. 2014); 13 (Kiko et al. 2014, Muller et al. 2014); 14 (Li Y. Y. et al. 2011c).

microRNA Expression in AD Regulation of microglia in AD

miR-124 ↓ Human brain1

↓ Aβ1-42-stressed PC12 cells and primary rat

neurons2

(Not reported in literature)

miR-155 ↑ Human CSF, ECF3, PBMC

4 and BDM

5

↑ Aβ42-stressed HNG co-cultures6

↑ 3xTg AD mice brain7

↑ in Aβ fibrils-stressed N9 microglia

due to c-Jun activation, and causes

↓ SOCS17

miR-146a ↑ Human brain8, CSF and ECF

9

↑ Aβ42-stressed HNG co-cultures, HN and

HAG cells10

↑ Tg2576 and 5xFAD AD mice brain11

↓ Human brain12

, CSF and plasma13

↑ in Aβ42-stressed HMG cells

causes ↓ CFH14

4. Human versus rodent microglia

The vast majority of data of microglial phenotype and functions available in literature

were obtained from primary microglia or cell lines of rodents, particularly mice. Due to their

accessibility, mice have been widely used as a source of microglia to perform studies in

different contexts such as health, aging or pathologies including AD, whereas several

transgenic AD mouse models were performed (Elder et al. 2010). However, there are several

interspecies differences that should be taken into account when considering the extrapolation

of data from murine microglia to human counterparts. This includes differences in distribution

(Lawson et al. 1990, Mittelbronn et al. 2001), proliferation, response to stimuli and

phenotypic markers (Cherry et al. 2014, Smith A. M. and Dragunow 2014, Walker and Lue

I. Introduction

22

2015). As so, human cell lines should be considered to explore a typical human disorder that

lacks its complete representativity in a rodent model.

4.1. The human CHME3 microglial cell line

CHME3 was the first microglial cell line of human origin, having been generated in 1995.

This cell line was obtained from immortalization of primary embryonic microglia by

transfection with a plasmid containing the cDNA encoding for the simian virus 40 (SV40)

large T antigen, promoting the continuous and fast proliferation of cells due to the

abolishment of their anti-tumor defense. As a result, CHME3 microglia are an homogeneous

cell population which can be cultured in significant quantities, while retained the

characteristics of their primary cell counterparts (Janabi et al. 1995). Hence, CHME3

microglia represent an appropriate in vitro model to study human microglial properties and

functions avoiding the use of human primary microglia, which availability is extremely limited.

Furthermore, since CHME3 microglia can support subsequent transfections (Janabi et al.

1995), they also provide an useful tool to study microglial gene regulation. Indeed, this cell

line has already been used to perform microglial miRNAs regulation upon viral infection

(Sharma et al. 2015), and for studies of microglial neuroinflammation and neuroprotection in

AD-like conditions (Hjorth et al. 2010, Hjorth et al. 2013, Lindberg et al. 2005).

5. Aims

The main goal of the present thesis was to assess human CHME3 microglial responses

in terms of miRNA expression and phenotypic markers when co-cultured with human SH-

SY5Y neuroblastoma cells expressing Aβ as in vitro models recapitulating some AD-related

pathological processes.

Firstly, we intended to characterize the in vitro AD models by comparing CHME3

microglia plus mock-transfected SH-SY5Y cells (control) with SH-SY5Y cells overexpressing

wild-type APP695 (SH-SY5Y APP695) or APP695 harboring the Swedish mutation (SH-

SY5Y APP695 Swe) based on the analysis of intracellular APP and extracellular sAPPα,

sAPPβ, Aβ1-40 and Aβ1-42 levels.

Secondly, we aimed to assess human CHME3 microglia for the expression of

inflammation-related miRNAs (miR-124, miR-155 and miR-146a) and respective targets, as

well as typical phenotypic and immune markers. Additionally, we further proposed to analyze

microglial specific functions associated with AD, namely the phagocytic capacity and its

eventual association to an increased prevalence of senescent cells.


23


1. Cell culture and treatment

Human CHME3 microglial cells, a gift from Professor Marc Tardieu, were routinely

cultured in T75 in Roswell Park Memorial Institute (RPMI) medium supplemented with 10%

fetal bovine serum (FBS), 2% antibiotic antimycotic (AB/AM) (Sigma-Aldrich, St. Louis, MO,

USA) and 1% L-glutamine (L-glu) (Sigma-Aldrich).

Human neuroblastoma SH-SY5Y, SH-SY5Y APP695 and SH-SY5Y APP695 Swe cells,

a gift from Professor Anthony Turner, were routinely cultured in T75 in Dulbecco’s Modified

Eagle’s Medium (DMEM) (Gibco™, Thermo Fisher Scientific, Waltham, MA, USA)

supplemented with 10% FBS and 2% AB/AM. All cell lines were cultured in a humidified

atmosphere containing 5% CO2 at 37ºC.

For neuronal differentiation , SH-SY5Y, SH-SY5Y APP695 and SH-SY5Y APP695 Swe

neuroblastoma cells were seeded in 12-well plates coated with poly-d-lysine/laminin at a final

concentration of 5x104 cells per well (day 0). After 24h (day 1), retinoic acid (RA) (Sigma-

Aldrich) was added at a final concentration 10 µM in culture medium and maintained for 7

days (until day 8). RA-containing culture medium was changed every 2 days.

Three days before finishing the RA treatment of neuroblastoma cells (day 5), CHME3

microglial cells were seeded in 12-well plates at a final concentration of 5x104 cells per well

onto HCl-washed coverslips containing 3-4 paraffin dots. CHME3 microglia were maintained

in RPMI medium supplemented with 10% FBS, 2% AB/AM and 1% L-glu for 48h (until day

7), when both neuroblastoma and CHME3 cell culture media were changed to FBS-free

media.

On day 8, CHME3 cells seeded onto paraffin dots-containing coverslips were placed on

top of RA-differentiated SH-SY5Y, SH-SY5Y APP695 or SH-SY5Y APP695 Swe cells in

order to perform CHME3 / SH-SY5Y, CHME3 / SH-SY5Y APP695 and CHME3 / SH-SY5Y

APP695 Swe co-cultures (0h). All co-cultures were maintained for 24h, 48h and 72h (days 9-

II. Materials and Methods

24

11) in RPMI medium with 1% L-glu and 2% AB/AM. At each time point, both neuroblastoma

and CHME3 cells were harvested, and culture media was collected for analysis (Figure II.1).

Figure II.1 | Schematic representation of the experimental design

2. Protein extraction and western blot analysis

To determine the content of secreted proteins, aliquots of 1,800 µL of SH-SY5Y, SH-

SY5Y APP695 and SH-SY5Y APP695 Swe cells culture media were collected before co-

culturing (0h), corresponding to 24h of pure culture maintenance, and 24h, 48h and 72h after

co-culturing with CHME3 microglia. Total proteins were precipitated by adding 10%

trichloroacetic acid in acetone, followed by 2-4 washing cycles with acetone containing 20

mM Dithiothreitol and centrifugation at 15,000 g for 10 min. The protein pellet was dissolved

in buffer containing 8M urea, 1% SDS (1:1) and proteases inhibitor (1:25) followed by

sonication and centrifugation at 3,200 g for 10 min.

To determine neuroblastoma intracellular protein content, before co-culturing (0h), and

24h, 48h and 72h after co-culturing with CHME3, SH-SY5Y, SH-SY5Y APP695 and SH-

SY5Y APP695 Swe cells were harvested in ~50 µL ice-cold Cell lysis buffer (Cell Signaling)

containing 1 nM PMSF followed by sonication and centrifugation at 10,000 g for 5 min. Total

protein concentrations in the supernatant were measured using the Bradford method with


25

Bio-Rad’s Protein Assay Reagent (Bio-Rad Laboratories, Hercules, CA, USA), according

with manufacturer instructions.

Protein samples from neuroblastoma cell lysates and culture media precipitates were

separated on a Tris-Tricine gel. All protein samples were then transferred to nitrocellulose

membranes (Amersham Biosciences, Little Chalfont, UK) and incubated in blocking buffer

[Tween 20 (0.1%)-Tris buffered saline, T-TBS, and 5% (w/v) non-fat dried milk] at room

temperature for 1 hour. After blocking, membranes were incubated at 4ºC overnight with the

primary antibody diluted in T-TBS and 5% Bovine Serum Albumin. Membranes of

neuroblastoma cell lysates were incubated with 6E10 antibody (mouse, 1:200, BioLegend,

San Diego, CA, USA, SIG-39320) to detect APP, and membranes of culture media

precipitates were also incubated with 6E10 antibody to detect sAPPα and with an anti-wild-

type-sAPPβ antibody (rabbit, 1:50, IBL, Aramachi, Takasaki-Shi, Gunma, Japan, 18957).

After washing with T-TBS, membranes were incubated at room temperature for 1 hour with

the correspondent secondary antibody diluted in blocking buffer [horseradish-peroxidase-

conjugated anti-mouse or anti-rabbit (1:2000, Santa Cruz Biotechnology, Dallas, TX, USA,

sc-2032 or sc-2004)]. After washing membranes with T-TBS, chemiluminescent detection

was performed with WesternBright™ Sirius (Advansta Inc, Menlo Park, CA, USA) and bands

were visualized in Chemidoc from Bio-Rad Laboratories. The relative intensities of protein

bands were analyzed using the Image Lab analysis software (Bio-Rad Laboratories) and

normalized to total protein bands detected following staining with AmidoBlack® (Sigma-

Aldrich).

For reprobing, membranes were incubated with stripping buffer (62.5 mM Tris and 100

mM β-Mercaptoethanol and 2% SDS) at 50ºC for 30 min. After washing with T-TBS,

membranes were blocked and sequentially incubated with the next primary and respective

secondary antibody as described above.

3. Enzyme-Linked Immunosorbent Assay (ELISA)

Determination of Aβ1-40 and Aβ1-42 released by neuroblastoma cells to culture media was

performed by ELISA using Human Amyloidβ (1-40) Assay Kit (IBL, 27713) and Human

Amyloidβ (1-42) Assay Kit (IBL, 27711), respectively, in accordance with the manufacturer’s

guidelines. Colorimetric reaction was measured at 450 nm in a Bio-Rad microplate

absorbance spectrophotometer (Bio-Rad Laboratories).


26

4. Total RNA extraction, reverse transcription and semi-quantitative RealTime

Polymerase Chain Reaction (qRT-PCR)

To determine CHME3 microglial gene expression, before co-culturing (0h), and 24h, 48h

and 72h after co-cultures total RNA was isolated from microglia using the TRIzol® reagent

method in accordance with the manufacturer’s guidelines (Invitrogen, Carlsbad, CA, USA)

and RNA concentration was quantified using the NanoDrop ND-100 Spectrophotometer

(NanoDrop Technologies, Wilmington, DE, USA). Aliquots of 150-400 ng of total RNA were

reversely transcribed using the SensiFAST cDNA Synthesis Kit (Bioline, Taunton, MA, USA),

under manufacturer’s instructions. Semi quantitative (q)RT-PCR was performed on a 7300

RealTime PCR System (Applied Biosystems, Foster City, CA, USA) using a SensiFAST

SYBR® Hi-Rox Kit (Bioline), under optimized conditions: 50ºC for 2 min, 95ºC for 2 min

followed by 40 cycles at 95ºC for 5 s and 62ºC for 30 s. In order to verify the specificity of the

amplification, a melt-curve analysis was performed immediately after the amplification

protocol (95ºC for 15 s, followed by 60ºC for 30 s and 95ºC for 15 s). The PCR was

performed in 96-well plates with each sample performed in duplicate, and a non-template

control was included for each gene. Glyceraldehyde 3-phosphate dehydrogenase (GAPDH)

was used as endogenous control, and fold change was calculated vs. basal CHME3

microglial expression at 0h. The sequences used as primers are listed in Table II.1.

Table II.1 | Sequences used as primers for detection of mRNA expression in CHME3 microglia

Gene Forward primer (5’-3’) Reverse primer (5’-3’)

Arg1 TGGAAACTTGCATGGACA AAGTCCGAAACAAGCCAA

CEBP-α CAAAGCCAAGAAGTCGGTGGACAA TCATTGTGACTGGTCAACTCCAGC

CEBP-β CACAGCGACGACTGCAAGATCC CTTGAACAAGTTCCGCAGGGTC

GAPDH CGCTCTCTGCTCCTCCTGTT CCATGGTGTCTGAGCGATGT

IL-10 CCTGGAGGAGGTGATGCCCCA CCTGCTCCACGGCCTTGCTC

IL-1β GGGCCTCAAGGAAAAGAATC TTCTGCTTGAGAGGTGCTGA

IL-6 ATGAACTCCTTCTCCACAAGC GTTTTCTGCCAGTGCCTGTTTG

iNOS TCCGAGGCAAACAGCACATTCA GGGTTGGGGGTGTGGTGATGT

IRAK1 CTGGAAGGCAGAAAAGTTGG TGTGACTCACGGCTGAACAC

MHC class II AGGGATTGCGCAAAAGCA TCACCTCCATGTGCCTTACAGA

SOCS1 TCCGTTCGCACGCCGATTAC TCAAATCTGGAAGGGGAAGG

TGF-β TGCGCTTGAGATCTTCAAA GGGCTAGTCGCACAGAACT

TNF-α AACCTCCTCTCTGCCATC ATGTTCGTCCTCCTCACA

TRAF6 CCTTTGGCAAATGTCATCTGTG CTCTGCATCTTTTCATGGCAAC


27

For miRNA analysis, before co-culturing (0h), and 24h, 48h and 72h after co-cultures

total RNA was extracted from CHME3 cells and quantified as described above. cDNA

synthesis for miRNA quantification was performed with the Universal cDNA Synthesis Kit

(Exiqon, Woburn, MA, USA) using 100 ng total RNA according to the following protocol: 42ºC

for 60 min followed by heat-inactivation of the reverse transcriptase at 95ºC for 5 min. The

miRCURY LNA™ Universal RT microRNA PCR Kit (Exiqon) was used in combination with

predesigned primers to specific target sequences (Exiqon) (Table II.2). The reaction

conditions consisted of polymerase activation/denaturation and well-factor determination at

95ºC for 10 min, followed by 50 amplification cycles at 95ºC for 10 s and 60ºC for 1 min

(ramp-rate 1.6ºC/s). The PCR was performed in 96-well plates with each sample performed

in duplicate, and a non-template control was included for each analysis. The miRNA fold

change vs. basal CHME3 microglial expression at 0h was determined by the Pfaffl method.

Table II.2 | Target sequences of predesigned primers used for detection of miRNAs expression in CHME3 microglia

Gene Target sequence

hsa-miR-124-3p UAAGGCACGCGGUGAAUGCC

hsa-miR-146a-5p UGAGAACUGAAUUCCAUGGGUU

mmu-miR-155-5p UUAAUGCUAAUUGUGAUAGGGGU

SNORD110 (Reference gene)

5. Evaluation of microglial phagocytic ability

To evaluate microglial phagocytic capacity, CHME3 cells were incubated for 75 min at

37ºC with 0.0025% (v/v) 1 µm fluorescent latex beads (SigmaChemical Co., St.Louis, MO,

USA) at 24h, 48h and 72h post co-culturing with neuroblastoma cells and then fixed with 4%

(w/v) paraformaldehyde in phosphate-buffer saline. Microglial nuclei were stained with

Hoechst dye, and fluorescence was visualized using an AxioCam HRm camera adapted to

an AxioSkope® microscope (Zeiss, Oberkochen, Germany). Bright field images were

captured to visualize microglial cytoplasm and assure that beads were within the cell body.

At least, 10 random microscopic fields were acquired per sample. The number of ingested

beads per cell was counted. Results are presented as mean number of ingested beads per

cell (± SEM) and as percentage of cells that phagocytosed < 5, 6-10 or > 10 beads.


28

6. Senescence-associated β-galactosidase assay

CHME3 microglial senescence was evaluated by determining the activity of senescence-

associated β-galactosidase (SA-β-gal) using the Cellular senescence assay kit (Millipore,

Billerica, MA, USA), according to the manufacturer instructions. Microglial nuclei were

counterstained with hematoxylin. Bright field microscopy images of at least 10 random

microscopic fields were acquired per sample. The number of turquoise stained microglia (SA-

β-gal-positive cells) was counted, and results are presented as percentage of senescent cells

(± SEM).

7. Statistical analysis

Results are presented as mean ± SEM. Differences between groups were determined

by one-way or two-way ANOVA using GraphPad PRISM 5.0 (GraphPad Software Inc., San

Diego, CA, USA) as appropriate, followed by multiple comparisons Bonferroni post hoc

correction. p values less than 0.05 were considered statistically significant.


29

III. RESULTS

1. APP expression and Aβ secretion in neuroblastoma cells

First, we decided to evaluate the expression of APP and the secretion of Aβ by

neuroblastoma cell lines SH-SY5Y, SH-SY5Y APP695 and SH-SY5Y APP695 Swe during

24h in order to assure the validity of our system, and also to assure that human CHME3

microglia would be exposed to different levels of these proteins. We observed that both SH-

SY5Y APP695 and SH-SY5Y APP695 Swe cells express APP with increased signal than

SH-SY5Y cells, demonstrated by the difference of intensity of bands obtained in western blot

analysis of neuroblastoma cell lysates using the 6E10 antibody. Moreover, we observed that

both SH-SY5Y APP695 and SH-SY5Y APP695 Swe cells express mature and immature

APP695, confirmed by the presence of a double-band patter immediately below 130 kDa

which shows mature and immature APP differently modified by glycosylation, whereas SH-

SY5Y cells express a single-band pattern corresponding to mature APP695 (Figure III.1A,

upper panel). Curiously, when analyzing the protein content in neuroblastoma cell culture

media, we observed that SH-SY5Y APP695 and SH-SY5Y APP695 Swe cells secrete

sAPPα predominantly with the same molecular weight that intracellular immature APP695,

whereas SH-SY5Y cells release sAPPα with increased molecular weight similarly to

intracellular mature APP695 (Figure III.1A, median panel). Once testing for sAPPβ, we only

detected bands in samples of SH-SY5Y APP695 cell culture medium and not in samples of

SH-SY5Y APP695 Swe cell culture medium (Figure III.1A, bottom panel). The absence of

bands may be explained by the lack of reactivity of the antibody to the sAPPβ fragment

obtained from cells harboring the Swe mutation, since this mutation alters the epitope region

that is recognized by this antibody.

Given these results, we then explored the amounts of secreted Aβ by ELISA. We

observed that both SH-SY5Y APP695 and SH-SY5Y APP695 Swe cells secreted

significantly increased levels of Aβ1-40 to culture media when compared with SH-SY5Y cells

(289 and 330 pg/mL from SH-SY5Y APP695 and SH-SY5Y APP695 Swe cells vs. 26 pg/mL

III. Results

30

from SH-SY5Y cells) (Figure III.1B). We also evaluated the released Aβ1-42 in the culture

media of those cells but observed a much lower secretion, below 20 pg/mL, and no

significant differences between the distinct neuroblastoma cell lines (Figure III.1C). Overall,

we observed that both SH-SY5Y APP695 and SH-SY5Y APP695 Swe cells express and

secrete higher amounts of APP then SH-SY5Y cells, resulting in increased accumulation of

Aβ1-40 in culture media.

Figure III.1 | APP expression, and sAPPα, sAPPβ and Aβ secretion by neuroblastoma cells. APP was detected in SH-SY5Y, SH-SY5Y APP695 and SH-SY5Y APP695 Swe cell lysates by western blot using the 6E10 antibody; sAPPα and sAPPβ were detected in SH-SY5Y, SH-SY5Y APP695 and SH-SY5Y APP695 Swe cell culture media by western blot using the 6E10 antibody and an anti-wild-type-sAPPβ antibody, respectively (A). Aβ1-40 (B) and Aβ1-42 (C) were detected in SH-SY5Y, SH-SY5Y APP695 and SH-SY5Y APP695 Swe cell culture media using appropriate ELISA kits. Results are mean ± SEM (n = 2-3 per group). * p < 0.05 and ** p < 0.01 vs. SH-SY5Y cells.


31

2. The presence of CHME3 microglia does not alter APP expression in

neuroblastoma cells but reduces sAPPα, sAPPβ and Aβ1-40 levels in co-

culture media

Next, we evaluated how the expression of APP and the secretion of Aβ by

neuroblastoma cells could be differently modulated by the presence of human CHME3

microglia in the co-culture system. We found that the single-band pattern of APP expression

in SH-SY5Y cells, as well as the two-band pattern of APP expression in SH-SY5Y APP695

and SH-SY5Y APP695 Swe cells were retained, although slight differences of APP signal

were observed along time (Figure III.2A, upper panel).

On the contrary, when looking at sAPP, we found a marked reduction in sAPPα signal in

co-culture media 24h post co-culturing neuroblastoma cells with CHME3 microglia

independently on the neuroblastoma cell line (Figure III.2A, median panel). With the

increase of the co-culturing period, we observed an accumulation of sAPPα, represented by

increased signal in a time-dependent manner namely for CHME3 / SH-SY5Y APP695 and

CHME3 / SH-SY5Y APP695 Swe co-culture systems. Once testing for sAPPβ, we could only

detect the same pattern of accumulation in the CHME3 / SH-SY5Y APP695 co-culture

system (Figure III.2A, bottom panel), suggesting once again that only SH-SY5Y APP695

and SH-SY5Y APP695 Swe cells are secreting this sAPP form but we may not detect the

protein upon the Swe mutation.

Interestingly, when we evaluated secreted Aβ1-40, we observed that the levels of this

peptide in CHME3 / SH-SY5Y APP695 and CHME3 / SH-SY5Y APP695 Swe co-culture

media significantly diminished at 24h when compared with isolated neuroblastoma cell

culture media (p < 0.01). Curiously, with the increase of co-culturing time, we observed a

higher and significant accumulation of Aβ1-40 in CHME3 / SH-SY5Y APP695 Swe co-culture

medium when compared with CHME3 / SH-SY5Y or CHME3 / SH-SY5Y APP695 co-culture

media (Figure III.2B). We found that the levels of Aβ1-42 in media of neuroblastoma cells also

tended to decline in the presence of CHME3 microglia, namely in the first 24h when

compared with media from isolated neuroblastoma cells, though the secretion of this peptide

is much lower than Aβ1-40 in this co-culture systems (Figure III.2C).

These results suggest that microglia may be clearing the release of sAPP and Aβ from

co-culture media, at least in the initial time periods, but may be losing their ability to do so for

longer time periods. Curiously, these set up allow us to observe that there is a higher

accumulation of Aβ1-40 in CHME3 / SH-SY5Y APP695 Swe co-culture media, which

corroborates previous findings suggesting that SH-SY5Y APP695 Swe cells secrete

increased levels of Aβ compared with SH-SY5Y APP695 cells (Jamsa et al. 2011). As so, we

may assure that human CHME3 microglial cells were exposed to distinct amounts of Aβ

III. Results

32

when in the presence of these two different neuroblastoma cell lines, suggesting that these

co-culture systems represent suitable in vitro models of AD using human cell lines to

evaluate microglial response.

Figure III.2 | Presence of CHME3 microglia does not alter APP expression in neuroblastoma cells but reduces sAPPα, sAPPβ and Aβ1-40 in co-culture media. After co-culturing CHME3 microglia with neuroblastoma cells, APP was detected in SH-SY5Y, SH-SY5Y APP695 and SH-SY5Y APP695 Swe cell lysates by western blot using the 6E10 antibody; sAPPα and sAPPβ were detected in CHME3 / SH-SY5Y, CHME3 / SH-SY5Y APP695 and CHME3 / SH-SY5Y APP695 Swe co-culture media by western blot using the 6E10 antibody and an anti-wild-type-sAPPβ antibody, respectively (A). Aβ1-40 (B) and Aβ1-42 (C) were detected in CHME3 / SH-SY5Y, CHME3 / SH-SY5Y APP695 and CHME3 / SH-SY5Y APP695 Swe co-culture media using appropriate ELISA kits. Results are mean ± SEM (n = 2-3 per group). * p < 0.05 and ** p < 0.01 vs. SH-SY5Y cells. † p < 0.05 vs. SH-SY5Y APP695 cells.


33

3. Human CHME3 microglial expression of inflammation-related miRNAs and

their targets is mainly altered in the presence of SH-SY5Y APP695 Swe cells

Having characterized our in vitro AD models, we next assessed how human CHME3

microglia could differently express miRNAs related to an inflammatory response and

microglial phenotype. While miR-124 was correlated with microglial quiescence, miR-155

was established to support microglial pro-inflammatory and immune response. The role of

miR-146a in the regulation of neuroinflammation is more debatable, though several data

demonstrate that it is important for triggering the resolution phase of inflammation

(Ponomarev et al. 2013).

The CHME3 microglial cells isolated from CHME3 / SH-SY5Y APP695 Swe co-culture

showed a time-dependent enhancement of miR-124 expression (p < 0.05). While there was a

slight decrease of miR-124 levels during the first 24h, after 48h they raised peaking at 72h

when compared with CHME3 microglia isolated either from CHME3 / SH-SY5Y or CHME3 /

SH-SY5Y APP695 co-cultures (0.4-fold vs. 0.02- or 0.05-fold, respectively, p < 0.01) (Figure

III.3A).

As expected and in contrast to miR-124, the mRNA expression of its target C/EBP-α in

CHME3 microglia isolated from CHME3 / SH-SY5Y APP695 Swe co-culture showed a time-

dependent decline (p < 0.01). Microglial C/EBP-α mRNA levels peaked 24h after co-culturing

CHME3 with SH-SY5Y APP695 Swe cells when compared with microglia isolated either from

CHME3 / SH-SY5Y or CHME3 / SH-SY5Y APP695 co-cultures (4.3-fold vs. 2.0- or 0.5-fold,

respectively, p < 0.01), rapidly decreasing thereafter (Figure III.3B).

Figure III.3 | Expression of miR-124 gradually increases in CHME3 microglia when co-cultured with SH-SY5Y APP695 Swe cells, whereas the mRNA expression of C/EBP-α decays over time. CHME3 microglial levels of miR-124 (A) and C/EBP-α mRNA (B) upon co-culture with SH-SY5Y, SH-SY5Y APP695 or SH-SY5Y APP695 Swe cells for 24h, 48h and 72h were analyzed by qRT-PCR. Results are mean of fold change vs. basal CHME3 microglial expression ± SEM (n = 3-5 per group). * p < 0.05 and ** p < 0.01 vs. SH-SY5Y cells. †† p < 0.01 vs. SH-SY5Y APP695 cells.

III. Results

34

In opposition, the expression of miR-155 in CHME3 microglia isolated from CHME3 /

SH-SY5Y APP695 Swe co-culture rapidly peaked after 24h when compared with microglia

either isolated from CHME3 / SH-SY5Y or CHME3 / SH-SY5Y APP695 co-cultures (1.9-fold

vs. 0.7- or 0.3-fold, respectively, p < 0.01), decreasing afterwards. On contrary, the

expression of miR-155 in CHME3 microglia co-cultured with SH-SY5Y APP695 cells showed

a tendency to increase along time (Figure III.4A).

As expected, the mRNA expression of the miR-155 target SOCS1 in CHME3 microglia

isolated from CHME3 / SH-SY5Y APP695 Swe co-culture enhanced in a time-dependent

manner (p < 0.01). Interestingly, SOCS1 mRNA expression in CHME3 microglia was

markedly increased right after 24h of co-culturing with SH-SY5Y APP695 Swe cells when

compared with microglia isolated from CHME3 / SH-SY5Y or CHME3 / SH-SY5Y APP695

co-cultures (6.6-fold vs. 1.3- or 0.7-fold, respectively, p < 0.01), and further increased this

different response for later time points (8.8-fold vs. 0.8- or 0.8-fold at 48h, 12.9-fold vs. 1.0-

or 1.9-fold at 72h, p < 0.01) (Figure III.4B).

On the other hand, when we analyzed the mRNA expression of other known target of

miR-155, the C/EBP-β, there were no significant changes along time, just a tendency to

decrease in CHME3 microglia co-cultured with SH-SY5Y APP695 Swe cells. Curiously, the

mRNA expression of C/EBP-β showed a tendency to increase in CHME3 microglia co-

cultured with SH-SY5Y APP695 cells (Figure III.4C). These results showing that C/EBP-β

mRNA expression profile is similar to miR-155 suggest that, in our co-culture system, C/EBP-

β may not be the main target of miR-155.


35

Figure III.4 | Expression of miR-155 peaks in CHME3 microglia when co-cultured with SH-SY5Y APP695 Swe cells with a subsequent reduction, whereas the mRNA expression of SOCS1 increases in a time-dependent manner. No evident changes are observed for C/EBP-β mRNA expression. CHME3 microglial levels of miR-155 (A), SOCS1 (B) and C/EBP-β mRNAs (C) upon co-culture with SH-SY5Y, SH-SY5Y APP695 or SH-SY5Y APP695 Swe cells for 24h, 48h and 72h were analyzed by qRT-PCR. Results are mean of fold change vs. basal CHME3 microglia expression ± SEM (n = 3-5 per group). ** p < 0.01 vs. SH-SY5Y cells. † p < 0.05 and †† p < 0.01 vs. SH-SY5Y APP695 cells.

In agreement with miR-155, CHME3 microglial miR-146a expression peaked 24h after

co-culturing with SH-SY5Y APP695 Swe cells compared with SH-SY5Y APP695 cells (0.9-

fold vs. 0.4-fold, p < 0.01) decreasing afterwards in a time-dependent manner (p < 0.01)

(Figure III.5A). The decrease of miR-146a expression along time was also observed for

CHME3 microglial cells co-cultured with SH-SY5Y or SH-SY5Y APP695 cells but in a much

lower magnitude.

Next, we evaluated the expression of specific miR-146a targets. As expected, the

mRNA expression of IRAK1 in microglia isolated from CHME3 / SH-SY5Y APP695 Swe co-

culture demonstrated an inverse variation compared with miR-146a. Indeed, there was a

time-dependent increase of IRAK1 mRNA expression (p < 0.05) that was significantly higher

vs. CHME3 / SH-SY5Y or CHME3 / SH-SY5Y APP695 co-cultures at 48h and 72h (1.4-fold

vs. 0.5- or 0.6-fold at 48h, p < 0.05, and 2.4-fold vs. 0.8- or 0.6-fold at 72h, p < 0.01,

respectively) (Figure III.5B).

On the other hand, the mRNA expression of the other miR-146a target, the TRAF6,

increased earlier right at 24h peaking at 48h in CHME3 microglia co-cultured with SH-SY5Y

APP695 Swe cells, where it was significantly higher than that of microglia isolated either from

CHME3 / SH-SY5Y or CHME3 / SH-SY5Y APP695 co-cultures (2.0-fold vs. 0.8- or 0.9-fold,

respectively, p < 0.05), maintaining thereafter levels similar to the other co-culture systems

(Figure III.5C).

III. Results

36

Figure III.5 | Expression of miR-146a increases in CHME3 microglia when co-cultured with SH-SY5Y APP695 Swe cells decreasing over time. Conversely, whereas mRNA expression of IRAK1 progressively increases, the mRNA expression of TRAF6 does not show any significant variation along time. CHME3 microglial levels of miR-146a (A), IRAK1 (B) and TRAF6 mRNAs (C) upon co-culture with SH-SY5Y, SH-SY5Y APP695 or SH-SY5Y APP695 Swe cells for 24h, 48h and 72h were analyzed by qRT-PCR. Results are mean of fold change vs. basal CHME3 microglia expression ± SEM (n = 3-5 per group). * p < 0.05 and ** p < 0.01 vs. SH-SY5Y cells. † p < 0.05 and †† p < 0.01 vs. SH-SY5Y APP695 cells.

Overall, our results showed that CHME3 microglia co-cultured with SH-SY5Y APP695

Swe cells respond with a rapid expression of miR-155 and miR-146a that is reduced along

time, in opposition to a time-dependent increase of miR-124, suggesting a progressive

shifting of microglial phenotype.

4. The expression of pro-inflammatory cytokines in CHME3 microglia is

markedly induced when co-cultured with SH-SY5Y APP695 Swe cells

Given the previous results showing an early expression of miR-155 and miR-146a

followed by a later increase of miR-124 expression, we then decided to evaluate the

inflammatory response of microglia (Figure III.6). We first observed that the mRNA

expression of all the pro-inflammatory cytokines TNF-α, IL-1β and IL-6 had a marked time-

dependent increase in CHME3 microglia co-cultured with SH-SY5Y APP695 Swe cells (p <

0.01).

In particular, TNF-α mRNA expression was significantly higher in CHME3 microglia co-

cultured with either SH-SY5Y APP695 or SH-SY5Y APP695 Swe cells compared with

microglia co-cultured with SH-SY5Y cells (0.8- or 0.9-fold vs. 0.4-fold, respectively, p < 0.05)

at 24h. However, this increment was only further enhanced and significant for later time


37

points in CHME3 microglia co-cultured with SH-SY5Y APP695 Swe cells when compared

with SH-SY5Y or SH-SY5Y APP695 cells (1.2-fold vs. 0.7- or 0.7-fold at 48h, and 1.4-fold vs.

0.9- or 1.0-fold at 72h, respectively, p < 0.05) (Figure III.6A).

On the other hand, we observed that only the co-culture with SH-SY5Y APP695 Swe

cells induced a later increase of IL-6 mRNA expression in CHME3 microglia following 48h

when compared with co-cultures with SH-SY5Y APP695 cells (2.7-fold vs. 1.0-fold, p < 0.05),

which further enhanced at 72h when compared with co-cultures with SH-SY5Y or SH-SY5Y

APP695 cells (9.9-fold vs. 0.5- or 0.6-fold, respectively, p < 0.01) (Figure III.6B).

Curiously, when we analyzed the mRNA expression of IL-1β in CHME3 microglia, we

observed that 24h after co-culturing with either SH-SY5Y APP695 or SH-SY5Y APP695 Swe

cells microglial mRNA expression of IL-1β was significantly reduced than in CHME3 / SH-

SY5Y co-culture (3.5- or 2.1-fold vs. 6.2-fold, respectively, p < 0.01). Inversely, at 48h after

co-culturing CHME3 microglia with SH-SY5Y APP695 or SH-SY5Y APP695 Swe cells, the

mRNA expression of IL-1β increased when compared with CHME3 / SH-SY5Y co-culture

(9.3- or 3.6-fold vs. 0.9-fold, respectively, p < 0.01). However, the IL-1β mRNA expression

was only further enhanced at 72h in CHME3 microglia co-cultured with SH-SY5Y APP695

Swe cells when compared with SH-SY5Y or SH-SY5Y APP695 cells (23.0-fold vs. 0.8- or

1.1-fold, respectively, p < 0.01) (Figure III.6C).

Figure III.6 | CHME3 microglial mRNA expression of the pro-inflammatory cytokines TNF-α, IL-6 and IL-1β is enhanced over time when co-cultured with SH-SY5Y APP695 Swe cells. CHME3 microglial levels of TNF-α (A), IL-6 (B) and IL-1β mRNAs (C) upon co-culture with SH-SY5Y, SH-SY5Y APP695 or SH-SY5Y APP695 Swe cells for 24h, 48h and 72h were analyzed by qRT-PCR. Results are mean of fold change vs. basal CHME3 microglial expression ± SEM (n = 3-5 per group). * p < 0.05 and ** p < 0.01 vs. SH-SY5Y cells. † p < 0.05 and †† p < 0.01 vs. SH-SY5Y APP695 cells.

III. Results

38

5. The expression of CHME3 microglial immune markers is reversed when co-

cultured with SH-SY5Y APP695 or SH-SY5Y APP695 Swe cells

We next decided to evaluate additional markers of microglial reactivity that are usually

associated with their innate/adaptive immune response and reported to be altered in distinct

microglial phenotypes (Colton 2009).

First, we evaluated iNOS mRNA expression (Figure III.7A) and we observed that at 24h

CHME3 microglia co-cultured with SH-SY5Y APP695 Swe cells showed a marked increase

in the expression of this molecule when compared with microglia co-cultured with SH-SY5Y

or SH-SY5Y APP695 cells (3.0-fold vs. 0.7- or 0.5-fold, respectively, p < 0.01). The iNOS

mRNA expression decreased with time in co-culture although it was still significantly higher

than in microglia isolated from CHME3 / SH-SY5Y co-culture at 72h (1.7-fold vs. 0.3-fold, p <

0.01). Curiously, in CHME3 / SH-SY5Y APP695 co-culture, microglial mRNA expression of

iNOS showed an inversed profile significantly increasing with time when compared with

CHME3 / SH-SY5Y co-culture (1.2-fold vs. 0.6-fold at 48h, p < 0.05, and 2.1-fold vs. 0.3-fold

at 72h, p < 0.01) to similar levels of that in microglia isolated from CHME3 / SH-SY5Y

APP695 Swe co-cultures at 72h.

On the other hand, the response of CHME3 microglial cells to the presence of SH-SY5Y

APP695 Swe cells regarding MHC class II mRNA expression showed a less pronounced

enhancement that increased throughout co-culturing time, reaching a maximum effect at 72h

when compared with CHME3 / SH-SY5Y or CHME3 / SH-SY5Y APP695 co-cultures (2.1-fold

vs. 0.4- or 0.5-fold, respectively, p < 0.01). Interestingly, CHME3 microglia when co-cultured

with SH-SY5Y APP695 cells showed an initial increase of MHC class II mRNA expression

when compared with CHME3 / SH-SY5Y co-culture (1.4-fold vs. 0.7-fold at 24h, p < 0.01)

decreasing afterwards (Figure III.7B).

Based on these results, it seems that CHME3 microglia co-cultured with SH-SY5Y

APP695 Swe cells respond more rapidly and in a higher magnitude than those co-cultured

with SH-SY5Y APP695 cells in terms of innate immune response, possibly given the higher

amount of Aβ1-40 observed for early time points in media of CHME3 / SH-SY5Y APP695 Swe

co-cultures.


39

Figure III.7 | CHME3 microglial mRNA expression of iNOS is rapidly induced when co-cultured with SH-SY5Y APP695 Swe cells whereas MHC class II mRNA expression is slowly enhanced. CHME3 microglial levels of iNOS (A) and MHC class II mRNAs (B) upon co-culture with SH-SY5Y, SH-SY5Y APP695 or SH-SY5Y APP695 Swe cells for 24h, 48h and 72h were analyzed by qRT-PCR. Results are mean of fold change vs. basal CHME3 microglial expression ± SEM (n = 3-5 per group). * p < 0.05 and ** p < 0.01 vs. SH-SY5Y cells. † p < 0.05 and †† p < 0.01 vs. SH-SY5Y APP695 cells.

6. The expression of anti-inflammatory markers in CHME3 microglia is

markedly induced when co-cultured with SH-SY5Y APP695 Swe cells, with

TGF-β exception

Given the inflammatory data and since we observed a marked increase of miR-124

expression along time in co-culture, we next wanted to evaluate how the presence of

different neuroblastoma cells could affect CHME3 microglial expression of anti-inflammatory

markers, typically associated with alternative activated/acquired deactivated microglial

phenotypes.

Co-culturing of CHME3 microglia with SH-SY5Y APP695 Swe cells induced a marked

microglial mRNA expression of Arginase 1 right at 24h when compared with CHME3 / SH-

SY5Y or CHME3 / SH-SY5Y APP695 co-cultures (2.5-fold vs. 1.2- or 0.7-fold, respectively, p

< 0.01) that was maintained throughout co-culturing time (2.9-fold vs. 1.4- or 1.6-fold at 48h,

and 2.8-fold vs. 1.7- or 1.9-fold, respectively, p < 0.05) (Figure III.8A).

Similarly, the mRNA expression of IL-10 raised significantly in CHME3 microglia co-

cultured with SH-SY5Y APP695 Swe cells at 24h when compared with CHME3 microglia

isolated from CHME3 / SH-SY5Y or CHME3 / SH-SY5Y APP695 co-cultures (3.3-fold vs.

1.0- or 1.4-fold, respectively, p < 0.01) and further increased at later time points (3.8-fold vs.

1.0- or 1.6-fold at 48h, and 5.5-fold vs. 1.1- or 2.0-fold at 72h, respectively, p < 0.01) (Figure

III.8B).

Conversely, the mRNA expression of TGF-β in microglia did not show significant

changes between the different co-culture systems at 24h and 48h, while at 72h there was a

rise in CHME3 microglial cells co-cultured with SH-SY5Y APP695 or SH-SY5Y APP695 Swe

cells when compared with microglia isolated from CHME3 / SH-SY5Y co-culture (1.4- or 1.2-

fold vs. 0.8-fold, respectively, p < 0.01) (Figure III.8C).

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40

These results indicate that there is an increased expression of anti-inflammatory

markers in CHME3 microglia along time when co-cultured with SH-SY5Y APP695 Swe cells.

Figure III.8 | mRNA expression of the anti-inflammatory markers Arginase 1 and IL-10 is rapidly induced in CHME3 microglia when co-cultured with SH-SY5Y APP695 Swe cells and progressively enhances, though TGF-β mRNA expression does not show a gradual variation pattern. CHME3 microglial levels of Arginase 1 (A), IL-10 (B) and TGF-β mRNAs (C) upon co-culture with SH-SY5Y, SH-SY5Y APP695 or SH-SY5Y APP695 Swe cells for 24h, 48h and 72h were analyzed by qRT-PCR. Results are mean of fold change vs. basal CHME3 microglial expression ± SEM (n = 3-5 per group). * p < 0.05 and ** p < 0.01 vs. SH-SY5Y cells. † p < 0.05 and †† p < 0.01 vs. SH-SY5Y APP695 cells.

7. CHME3 microglia co-cultured with SH-SY5Y APP695 Swe cells preserve

their phagocytic capacity for longer periods

Once testing for microglial phagocytic capacity, we observed that CHME3 microglial

cells tended to ingest a reduced number of beads over time independently on the co-culture

system (Figure III.9B). We also found that the vast majority (> 90%) of CHME3 microglial

cells isolated from either CHME3 / SH-SY5Y, CHME3 / SH-SY5Y APP695 or CHME3 / SH-

SY5Y APP695 Swe co-cultures are able to ingest less than 5 beads (p < 0.01 vs. more

beads) (Figures III.9C-E). The remaining 10% of CHME3 microglial cells predominantly

ingested 6-10 beads at 24h in all co-culture systems and very few cells were shown to

uptake more than 10 beads in such conditions. Interestingly, in longer time periods only

CHME3 microglia co-cultured with SH-SY5Y APP695 Swe cells were able to retain their

ability to phagocyte more than 6 beads, namely at 48h (p < 0.05 vs. CHME3 / SH-SY5Y co-

culture) whereas microglia co-cultured with SH-SY5Y or SH-SY5Y APP695 failed to

phagocyte this amount of beads (Figures III.9C-E). Our data suggest that CHME3 microglial


41

phagocytic capacity is more sustained in the presence of SH-SY5Y APP695 Swe cells than

in the other co-culture systems.

Figure III.9 | Average of phagocytosed beads per CHME3 microglial cell tends to decrease in all co-culture systems, though CHME3 microglia co-cultured with SH-SY5Y APP695 Swe cells retain their capacity to uptake increased number of beads along time in co-culture. CHME3 microglia were co-cultured with SH-SY5Y, SH-SY5Y APP695 or SH-SY5Y APP695 Swe cells for 24h, 48h and 72h and then exposed to green fluorescent beads to measure their phagocytic capacity. Microglial nuclei were stained with Hoechst dye (DAPI), and bright field images were captured to visualize microglial cytoplasm. Arrows represent ingested beads. Images represent CHME3 microglia co-cultured with SH-SY5Y cells for 48h (A). Number of phagocytosed beads per cell (B), and number of CHME3 microglia phagocytosing < 5, 6-10 and > 10 beads upon co-culture with SH-SY5Y (C), SH-SY5Y APP695 (D) or SH-SY5Y APP695 Swe cells (E) was counted. Results are mean ± SEM (n = 2-3 per group). The percentage of microglial cells that phagocytize < 5 beads is significantly higher than the percentage of cells that phagocytize more than 6 beads in all co-cultures and time points (p < 0.01). * p < 0.05 vs. SH-SY5Y cells. Scale bar equals 25 µm.

III. Results

42

8. CHME3 microglia show increased SA-β-gal activity when co-cultured with

SH-SY5Y APP695 Swe cells

Lastly, and since in our previous data we have reported that microglial exposure to Aβ

oligomers enhances microglial senescence (personal communication), we decided to

additionally evaluate this parameter in our co-culture systems.

Our first observation was that the percentage of SA-β-gal-positive cells in the whole

CHME3 microglial population considering the three co-culture systems and the three time

points analyzed never reached 10%, indicating a reduced induction of senescence in these

models (Figure III.10B). Nevertheless, we observed that while CHME3 microglia co-cultured

with SH-SY5Y or SH-SY5Y APP695 cells showed reduced senescence that decayed

throughout time, CHME3 / SH-SY5Y APP695 Swe co-culture always showed increased

levels of SA-β-gal-positive cells that became significant for longer time periods when

compared with CHME3 / SH-SY5Y or CHME3 / SH-SY5Y APP695 co-cultures (5.5-fold vs.

1.8- or 1.6-fold at 48h, p < 0.05, and 8.5-fold vs. 2.9- or 3.9-fold at 72h, p < 0.01,

respectively).

Our data demonstrate that CHME3 microglial SA-β-gal activity is slightly higher and

retained when co-cultured with SH-SY5Y APP695 Swe cells over time.


43

Figure III.10 | CHME3 microglia co-cultured with SH-SY5Y APP695 Swe cells show increased levels of senescence-associated β-galactosidase (SA-β-gal) activity along time in co-culture. CHME3 microglia were co-cultured with SH-SY5Y, SH-SY5Y APP695 or SH-SY5Y APP695 Swe cells for 24h, 48h and 72h and then tested for SA-β-gal activity using a commercial kit. Arrows represent SA-β-gal-positive CHME3 microglia. Image represents CHME3 microglia co-cultured with SH-SY5Y APP695 cells for 48h (A). SA-β-gal-positive cells were counted (B). Results are mean ± SEM (n = 2-3 per group). * p < 0.05 and ** p < 0.01 vs. SH-SY5Y cells. † p < 0.05 and †† p < 0.01 vs. SH-SY5Y APP695 cells. Scale bar equals 50 µm.


45

IV. DISCUSSION

AD is currently one of the most critical public health problems considering both its social

and economic impact. This evidence has been motivating most researchers to develop

studies to unveil AD pathogenesis, whereas neuroinflammation emerges as a promising

source of targets in order to generate novel therapies and/or improve AD diagnosis.

Microglia are pivotal cells in the regulation of neuroinflammation in the healthy brain,

though their role in AD is still not well clarified. Most efforts devoted to study microglia in AD

are performed with cells from animal origin usually provided from transgenic AD mouse

models, and there is huge controversy regarding the extrapolation of data from murine to

human microglial cells. Furthermore, considering the importance of miRNAs regulating

microglia in health, very few studies have been done in order to investigate the role of

miRNAs regulating microglia in AD.

In the present study, we used the CHME3 microglial cell line to explore the response of

human microglia in two AD cellular models, particularly focusing on changes in microglial

miRNA profile and phenotype. The two AD models herein performed were composed by SH-

SY5Y cells overexpressing wild-type APP695 or APP695 bearing the Swe mutation. These

cells are clones of the human SH-SY5Y neuroblastoma cell line, one of the most commonly

used model for studying neurodegeneration as cells can be induced to resemble human

neurons upon differentiation with RA and/or growth factors such as BDNF (Agholme et al.

2010, Constantinescu et al. 2007, Jamsa et al. 2004). Both SH-SY5Y APP695 and SH-SY5Y

APP695 Swe cells are considered useful for evaluating endogenous Aβ toxicity avoiding cell

incubation with exogenous Aβ, giving rise to suitable models for studying AD pathogenesis

and therapy in vitro (Ma and Zhang 2009).

Before assessing microglia, we analyzed neuroblastoma cells for intracellular APP and

extracellular sAPPα, sAPPβ, Aβ1-40 and Aβ1-42 expression. This initial analysis aimed at

characterizing SH-SY5Y APP695 and SH-SY5Y APP695 Swe cells improving our knowledge

on the environment generated within the AD models. We observed that SH-SY5Y APP695

and SH-SY5Y APP695 Swe cells endogenously express increased levels of APP than SH-

IV. Discussion

46

SY5Y cells, and also both the mature and immature APP695 isoforms whereas SH-SY5Y

cells express only mature APP695, the most glycosylated and thus the heaviest APP695

isoform. Our analysis confirmed previous studies that reported similar patterns of APP

detection in undifferentiated SH-SY5Y, SH-SY5Y APP695 and SH-SY5Y APP695 Swe cell

lysates using the same antibody (Belyaev et al. 2010). We then sought to analyze

extracellular expression of products resulting from non-amyloidogenic (sAPPα) and

amyloidogenic (sAPPβ, Aβ1-40 and Aβ1-42) cleavage of APP. We observed that all

neuroblastoma cells secrete sAPPα to media, whereas we detected slightly weaker sAPPα

signal in SH-SY5Y APP695 Swe than in SH-SY5Y APP695 cell culture medium. This

evidence corroborate previous studies in which undifferentiated SH-SY5Y APP695 cells were

reported to excrete increased levels of sAPPα than undifferentiated SH-SY5Y APP695 Swe

cells (Belyaev et al. 2010, Tomasselli et al. 2003). Once testing for Aβ1-40 and Aβ1-42 media

content, we found that SH-SY5Y APP695 and SH-SY5Y APP695 Swe cells significantly

secrete Aβ1-40 but not Aβ1-42 to media. It was previously reported in several studies that both

undifferentiated SH-SY5Y APP695 and SH-SY5Y APP695 Swe cells secrete higher levels of

Aβ1-40 than Aβ1-42 (Belyaev et al. 2010, Jamsa et al. 2011, Oules et al. 2012) which supports

our findings. On the other hand, we observed that SH-SY5Y APP695 Swe cells did not

secrete higher amounts of Aβ1-40 and Aβ1-42 than SH-SY5Y APP695 cells when cultured

alone for 24h (indicated as 0h or basal levels). In this regard, previous studies showed

contradictory data, whereas some authors demonstrate that SH-SY5Y APP695 Swe cells

secrete higher levels of Aβ1-40 and Aβ1-42 than SH-SY5Y APP695 cells (Belyaev et al. 2010,

Jamsa et al. 2011), others reported no differences among cells (Oules et al. 2012). Indeed,

this difference between SH-SY5Y APP695 Swe and SH-SY5Y APP695 cells would be

predictable since the presence of the Swe mutation enhances the affinity of APP to β-

secretase over 50-fold compared with wild-type APP, enhancing APP amyloidogenic

processing toward the generation of Aβ (Tomasselli et al. 2003). Based on the same

premise, we wondered that sAPPβ expression would also be enhanced in media of SH-

SY5Y APP695 Swe cells. However, we could only detect sAPPβ in media samples of SH-

SY5Y APP695 cells due to a lack of the antibody reactivity to sAPPβ secreted by SH-SY5Y

APP695 Swe cells. We believe that sAPPβ was undetectable in SH-SY5Y APP695 Swe cell

culture media due to a change in the amino acid sequence recognized by the anti-sAPPβ

antibody herein used from SEVKM to SEVNL induced by the Swe mutation, blocking the

recognition of the protein by the antibody. Taken together, our results demonstrated that SH-

SY5Y APP695 and SH-SY5Y APP695 Swe cells were not significantly different neither in

intracellular APP expression nor extracellular Aβ1-40 and Aβ1-42 levels when cultured alone for

24h. SH-SY5Y APP695 cells seem to secrete slightly increased levels of sAPPα than SH-

SY5Y APP695 Swe cells, and we could not infer on differences in sAPPβ secretion.


47

However, when we next assessed the expression of intracellular APP and extracellular

sAPPα, sAPPβ, Aβ1-40 and Aβ1-42 on neuroblastoma cells co-cultured with CHME3 microglia

from 24h to 72h, we observed marked differences between SH-SY5Y APP695 and SH-SY5Y

APP695 Swe cells.

While there were no changes in APP expression in these neuroblastoma cells, the levels

of sAPPα were reduced in the presence of CHME3 microglia, namely at 24h and

accumulated afterwards. The same pattern was observed for sAPPβ in culture media of SH-

SY5Y APP695 cells. Concerning the evaluation of Aβ peptide, we found that at 24h Aβ1-40

and with a slightly variation also Aβ1-42 levels were reduced in CHME3 / SH-SY5Y APP695

and CHME3 / SH-SY5Y APP695 Swe co-culture media. Most attractively, once cells were

co-cultured for longer time periods, we observed that Aβ1-40 tendentiously accumulated in

media essentially in CHME3 / SH-SY5Y APP695 co-culture and significantly in CHME3 / SH-

SY5Y APP695 Swe co-culture. These results confirm that SH-SY5Y APP695 Swe cells

elicits a higher accumulation of extracellular Aβ1-40 than SH-SY5Y APP695 cells for longer

time periods, which may justify the different response of CHME3 microglia in the presence of

these cell lines. It is accepted that microglia participate in Aβ degradation through

intracellular mechanisms involving phagocytosis, or extracellular mechanisms involving the

secretion of proteases such as metalloproteinases (Lee and Landreth 2010). It has been

widely reported that microglial cells interact with Aβ among different assembly states, and

also that this interaction induces an extensive variability of microglial responses that might

affect microglial-mediated Aβ clearance (Heppner et al. 2015). Furthermore, previous data

showed that murine microglia actively respond under exposure to sAPPα and sAPPβ

treatment (Bodles and Barger 2005, Ikezu et al. 2003). These data suggest that, in our AD

models, microglia might interact with sAPPα, sAPPβ, Aβ1-40 and Aβ1-42 contributing to early

protein clearance. Since APP production in neuroblastoma cells seem to be preserved during

the whole time of co-culture, we believe that progressive protein accumulation in CHME3 /

neuroblastoma co-culture media may indicate a higher production of these species

associated with an increased microglial inability to uptake and/or degrade these proteins at

the extracellular level for long periods. This effect is markedly observed for Aβ1-40

accumulation in CHME3 / SH-SY5Y APP695 Swe co-culture media.

Overall, our analysis of CHME3 microglial response in the two AD models showed that

SH-SY5Y APP695 Swe cells further deregulate microglial profile than SH-SY5Y APP695

cells over time, particularly concerning the expression of miRNAs as well as phenotypic and

immune markers.

The miR-124, miR-155 and miR-146a are established to play a fundamental role in the

regulation of microglial neuroinflammatory response in the healthy brain by targeting specific

molecules involved in key signaling pathways (Ponomarev et al. 2013). As summarized in

IV. Discussion

48

Table I.1, several data provided from samples of AD patients, cellular models and transgenic

animals demonstrate that miR-124, miR-155 and miR-146a are aberrantly expressed in AD.

However, very few reports were devoted to evaluate whereas miRNAs deregulation in AD

affected microglia. In our study, we showed that microglia initially exhibited a miR-124low/miR-

155high/miR-146ahigh profile that gradually switched to a miR-124high/miR-155low/miR-146alow

profile in the presence of SH-SY5Y APP695 Swe cells. Additionally, we found that

progressive upregulation of miR-124 was associated with downregulation of C/EBP-α mRNA.

Our findings corroborate studies of Ponomarev and colleagues who reported that C/EBP-α

mRNA is directly repressed by miR-124 in murine microglia, promoting cellular quiescence

mediated by downregulation of immune markers concomitantly with upregulation of anti-

inflammatory agents (Ponomarev et al. 2011). Conversely, the miR-155 was found to support

microglial activation by directly targeting SOCS1 mRNA in murine microglia, contributing to

reverse SOCS1-mediated repression of JAK/STAT1 and NF-κB signaling pathways and

subsequently enhance the transcription of pro-inflammatory and immune genes (Cardoso et

al. 2012). The expression of miR-155 was found to be upregulated in N9 murine microglia

under exposure to Aβ fibrils, and miR-155 overexpression and consequent SOCS1

downregulation was shown to support the generation of detrimental neuroinflammatory

environment in the brain of 3xTg AD mice (Guedes et al. 2014). In addition, miR-155 was

reported to target C/EBP-β mRNA in murine and human myeloid cells, consequently

repressing C/EBP-β-mediated transcription of anti-inflammatory agents (He et al. 2009,

Worm et al. 2009). In our CHME3 / SH-SY5Y APP695 Swe co-culture, we found that gradual

microglial miR-155 decrease inversely associated with SOCS1 mRNA increase, though

SOCS1 mRNA was overexpressed when compared with the other co-culture systems. On

the other hand, we did not observe inverse correlation between miR-155 and C/EBP-β

mRNA expression in microglia, suggesting that in our experimental model C/EBP-β may not

be a preferential target of miR-155.

The role of miR-146a in the regulation of inflammation and immunity has been more

debatable, particularly involving direct repression of IRAK1 and TRAF6. In human astrocytes,

miR-146a inhibition of IRAK1 was found to sustain IRAK2-mediated NF-κB activation

promoting a neuroinflammatory response (Cui et al. 2010). However, miR-146a

overexpression upon viral infection was reported to repress NF-κB activation and

neuroinflammatory response by directly targeting IRAK1 and TRAF6 mRNA in CHME3

microglia (Sharma et al. 2015). Our results in CHME3 / SH-SY5Y APP695 Swe co-cultures

showed that microglial mRNA expression of IRAK1 was progressively enhanced in

opposition to miR-146a decay. Conversely, microglial TRAF6 mRNA expression was

elevated at 24h, slightly increased at 48h and decreased at 72h. We suppose that TRAF6


49

mRNA decay at 72h might occur as a consequence of miR-124 overexpression, since miR-

124 was also reported to directly target TRAF6 mRNA in murine microglia (Qiu et al. 2015).

Based on those evidences, we believe that in the presence of SH-SY5Y APP695 Swe

cells, CHME3 microglia show a rapid pro-inflammatory response typical of classic activated

cells followed by a transition to a more alternative activated/deactivated phenotype to resolve

the damage and return to their quiescent/vigilant state.

To verify our hypothesis, we assessed the expression of a range of pro-inflammatory

(IL-6, IL-1β and TNF-α), immune (iNOS and MHC class II) and anti-inflammatory (IL-10,

Arginase 1 and TGF-β) markers in CHME3 microglia. All these markers are typically found in

microglial cells undertaking different phenotypic profiles, and several data support that they

are aberrantly expressed in the AD brain (Colton et al. 2006, Cribbs et al. 2012, Sudduth et

al. 2013). IL-6, IL-1β and TNF-α are three pro-inflammatory cytokines commonly expressed

by classic activated microglia (Ponomarev et al. 2013, Walker and Lue 2015). Besides

increased levels of these cytokines correlate with cytotoxic events, it remains debatable

whether microglial upregulation of IL-6, IL-1β and TNF-α contributes to Aβ accumulation or

clearance (Meraz-Rios et al. 2013). We found that TNF-α mRNA was overexpressed in

microglia during the whole time of co-culture with SH-SY5Y APP695 Swe cells, whereas IL-6

and IL-1β mRNA levels were initially reduced but progressively reached significant increased

values. Since TNF-α mRNA fast upregulation occurred simultaneously with Aβ1-40 drop in

media of both AD models, and IL-6 and IL-1β mRNA expression raised over time

concomitantly with Aβ1-40 accumulation in CHME3 / SH-SY5Y APP695 Swe co-culture media,

we suppose that only TNF-α may be correlated with microglial-mediated Aβ1-40 clearance,

while chronic expression of such pro-inflammatory cytokines might support Aβ1-40

accumulation. CHME3 microglia are known to spontaneously express IL-6 (Janabi et al.

1995), though it was shown that IL-6 is overexpressed in CHME3 microglia under exposure

to Aβ1-40 (Lindberg et al. 2005). These data provide possible explanation for our results since

CHME3 microglia co-cultured with SH-SY5Y APP695 Swe cells for 24h showed no

difference in IL-6 mRNA expression compared with microglia co-cultured with SH-SY5Y

cells, when Aβ1-40 levels were reduced. However, in the presence of SH-SY5Y APP695 Swe

cells for longer periods IL-6 mRNA overexpression in CHME3 microglia might be sustained

by Aβ1-40 accumulation in media. On the other hand, we observed that gradual upregulation

of IL-6, IL-1β and TNF-α mRNAs occurred in parallel with miR-146a downregulation and

concomitant upregulation of its targets IRAK1 and TRAF6 mRNAs. As stated above, the

miR-146a repression of IRAK1 and TRAF6 was found to repress NF-κB signaling required

for supporting CHME3 microglial neuroinflammatory response (Sharma et al. 2015). In our

model, we believe that under microglial miR-146a depletion, overexpression of TRAF6 and

IRAK1 mRNAs can activate NF-κB towards the transcription of pro-inflammatory genes

IV. Discussion

50

namely IL-6, IL-1β and TNF-α. However, since miR-155 was found to induce the expression

of these cytokines through SOCS1 repression in murine microglia (Cardoso et al. 2012), we

believe that SOCS1 mRNA overexpression in parallel with miR-155 downregulation might

negatively affect the expression of IL-6, IL-1β and TNF-α. This is an effect that would

potentially be observed if cells were co-cultured for longer than 72h.

Concerning the immune markers, we observed that iNOS and MHC class II mRNAs

expression exhibit opposite variation patterns in CHME3 microglia in the presence of SH-

SY5Y APP695 or SH-SY5Y APP695 Swe cells over time. The expression of iNOS is mostly

involved in innate immune response of classic activated microglia by producing NO, which

has cytotoxic effects (Colton 2009). Interestingly, we found that microglial iNOS mRNA

expression was rapidly upregulated in the presence of SH-SY5Y APP695 Swe cells but more

slowly in the presence of SH-SY5Y APP695 cells, suggesting that microglial innate immune

response is promptly activated in CHME3 / SH-SY5Y APP695 Swe co-culture rather than in

CHME3 / SH-SY5Y APP695 co-culture. After strong upregulation at 24h, we believe that

microglial iNOS mRNA expression was not retained under exposure to SH-SY5Y APP695

Swe cells over time due to SOCS1 mRNA overexpression, which might have an inhibitory

effect in the transcription of the iNOS gene similarly to pro-inflammatory genes (Cardoso et

al. 2012). A previous study showed that CHME3 microglia that uptake Aβ1-42 predominantly

overexpress iNOS and exhibit pro-inflammatory markers resembling classic activated cells

(Hjorth et al. 2010). Since we observed marked microglial iNOS mRNA overexpression at

24h when Aβ levels were reduced in CHME3 / SH-SY5Y APP695 Swe co-culture media, we

suppose that iNOS expression might correlate with microglial-mediated Aβ uptake in this

time point. Early overexpression of iNOS mRNA in microglia suggests that the production of

NO is augmented, which in turn might contribute to further generate an oxidative stressed

environment favorable to Aβ accumulation in accordance to previous reports (Meraz-Rios et

al. 2013). On the other hand, MHC class II/HLA-DR correlate with microglial participation in

adaptive immunity, though it is debatable whether it is a marker of amoeboid/activated or

ramified/quiescent microglia (Walker and Lue 2015). CHME3 microglia do not spontaneously

express the MHC class II immune marker (Janabi et al. 1995). Interestingly however, we

found that both SH-SY5Y APP695 and SH-SY5Y APP695 Swe cells induce MHC class II

mRNA expression in CHME3 microglia. We believe that progressive microglial MHC class II

mRNA overexpression in CHME3 / SH-SY5Y APP695 Swe co-culture might be a late

response to strong overexpression of C/EBP-α mRNA at 24h, as C/EBP-α is involved in the

transcription of the MHC class II gene in murine microglia (Ponomarev et al. 2011).

Next, we thought to analyze CHME3 microglial expression of the anti-inflammatory

markers Arginase 1, IL-10 and TGF-β which are characteristic of alternative activated and

deactivated microglia (Walker and Lue 2015). Arginase 1 is a typical marker of alternative


51

activated murine microglia though there is some controversy regarding its expression in

humans (Cherry et al. 2014). Functionally, Arginase 1 competes with NOS for their common

substrate arginine, triggering its conversion in collagen that is important for the ECM

reconstruction during the resolution phase of inflammation (Colton 2009). On the other hand,

IL-10 and TGF-β are mainly expressed in microglia upon acquired deactivation playing an

important immunoregulatory role by counteracting pro-inflammatory cytokine induction

(Colton 2009). In CHME3 / SH-SY5Y APP695 Swe co-culture, we found that Arginase 1 and

IL-10 mRNAs expression was upregulated during the whole co-culture time, but TGF-β

mRNA was overexpressed only at 72h when compared with the other co-culture systems.

Interestingly, our findings not only demonstrated that Arginase 1 mRNA is expressed in

human microglia but also that it is progressively upregulated in the presence of SH-SY5Y

APP695 Swe cells in contrast with iNOS mRNA downregulation. This evidence suggests that

Arginase 1 might counteract iNOS activity towards the formation of collagen required for

tissue repair. On the other hand, we suppose that microglial IL-10 and lastly TGF-β mRNAs

upregulation occurs to suppress IL-6, IL-1β and TNF-α mRNAs induction in the presence of

SH-SY5Y APP695 Swe cells. In murine microglia, miR-124 overexpression was shown to

correlate with induction of IL-10, TGF-β and Arginase 1 (Ponomarev et al. 2011), thus we

believe that miR-124 overexpression along time might also be associated with the rising

expression of these anti-inflammatory cytokines in our AD model composed by CHME3 / SH-

SY5Y APP695 Swe cells. Interestingly, it was recently demonstrated that the presence of

increased levels of IL-10 in the brain of transgenic AD mouse models was associated with

decreased microglial ability to clear Aβ (Michaud and Rivest 2015). This evidence provides a

possible explanation for our observations of microglial IL-10 mRNA upregulation

concomitantly with Aβ accumulation in CHME3 / SH-SY5Y APP695 Swe co-culture media.

Taken together, our findings demonstrate that microglia exhibit a robust pro-inflammatory

phenotype in the presence of SH-SY5Y APP695 Swe cells over time which tends to be

counterbalanced by the increment expression of anti-inflammatory/regulatory agents.

Simultaneously, microglial adaptive immune marker MHC class II is upregulated in detriment

of the innate immune marker iNOS.

In addition to miRNA profile and phenotypic analysis, we intended to evaluate CHME3

microglial phagocytic capacity. We found that neither exposure to SH-SY5Y APP695 nor SH-

SY5Y APP695 Swe cells significantly affected the number of ingested beads per microglial

cell in average. Moreover, we found that the vast majority (> 90%) of microglial cells uptake

less than 5 beads independently on the co-culture system or time point analyzed, and

tendentiously the number of microglia which phagocytized more than 6 beads decreased

over time. Interestingly however, we found that in the presence of SH-SY5Y APP695 Swe

cells a small population of microglia retained their ability to uptake more than 6 beads at 48h.

IV. Discussion

52

Taken together, our findings demonstrate that besides CHME3 microglia showed limited

capacity to ingest beads, their phagocytic ability is only longer preserved in the presence of

SH-SY5Y APP695 Swe cells. We believe that progressive decline in CHME3 microglial

phagocytic capacity might occur as a consequence of miR-124 upregulation, since this

miRNA was shown to repress microglial phagocytosis of apoptotic cells during development

in a zebrafish model (Svahn et al. 2015). CHME3 microglia are recognized to show little

capacity to uptake zymosan particles (Janabi et al. 1995) but are able to uptake Aβ1-42

particularly after IFN-γ stimulation (Hjorth et al. 2010). This suggests that, in our AD models,

CHME3 microglial phagocytic capacity towards Aβ may be saturating microglial phagocytic

ability towards added beads, but additional efforts are required to verify this hypothesis.

Finally, we analyzed CHME3 microglial senescence regarding SA-β-gal activity. Cellular

senescence is considered a marker of aging which is characterized by irreversible cell cycle

arrest and detrimental dysfunction, accompanied by morphological alterations (Kuilman et al.

2010). According to Streit and his collaborators, the presence of senescent microglia in the

human brain is an upmost trigger for AD initiation and subsequently drives AD progression

(Streit et al. 2014). In our co-culture models, we found that the percentage of SA-β-gal-

positive CHME3 microglia never reached 10% of the total microglial population

independently on the co-culture system or time point analyzed. After 48h and 72h, we

observed that the percentage of SA-β-gal positive cells tendentiously decayed in the

presence of SH-SY5Y or SH-SY5Y APP695 cells, though it remained close to 10% in the

presence of SH-SY5Y APP695 Swe cells. Since senescence is an irreversible feature, we

believe that the percentage of SA-β-gal-positive microglia decay in the presence of SH-SY5Y

or SH-SY5Y APP695 cells may be a consequence of decreased viability of these cells that

are removed to the culture media. Furthermore, based on our findings for miRNAs,

phenotypic and immune markers demonstrating microglial activity, it was not surprising that

the percentage of senescent/dysfunctional cells in CHME3/ SH-SY5Y APP695 Swe co-

culture was reduced. A previous report demonstrated that large T antigen-immortalized

human cell lines exhibit none or low SA-β-gal activity (Dimri et al. 1995). Since CHME3

microglia were immortalized employing a similar method (Janabi et al. 1995), we believe that

this provides a probable explanation for our results comprising low percentage of SA-β-gal-

positive CHME3 microglia. Additional determinations could be done in future studies of

CHME3 microglia improving knowledge on CHME3 microglial senescence such as

assessment of proliferative and morphological changes, and deregulation of cell cycle

inhibitors (Kuilman et al. 2010). A recent study from our laboratory showed that primary

murine microglia aged in vitro acquire a senescent phenotype based on their altered

morphology, reduced NF-κB activation, migratory inability and increased SA-β-gal activity

(Caldeira et al. 2014). Recent data also showed that exposure of young primary microglia to


53

Aβ leads to more than 60% of SA-β-gal-positive cells, suggesting that Aβ may enhance

microglial senescence (personal communication). Indeed, here we showed that CHME3

microglia co-cultured with SH-SY5Y APP695 Swe cells still maintain an increased number of

SA-β-gal-positive cells when compared with the other co-culture systems, corroborating our

previous data. On the other hand, it was also shown that senescent murine microglia exhibit

miR-146a overexpression but reduced expression of miR-155 (Caldeira et al. 2014).

However, in CHME3 / SH-SY5Y APP695 Swe co-cultures we observed that microglial miR-

146a and miR-155 expression varied in the same direction and not oppositely to each other,

suggesting that miR-146a rather regulates neuroinflammation in this AD model than acts as

a microglial senescence biomarker.

Concluding Remarks

In summary, our studies provided evidence that the presence of SH-SY5Y APP695 Swe

cells markedly induce human CHME3 microglial deregulation over time, and demonstrated

that CHME3 / SH-SY5Y APP695 Swe co-culture represents the most suitable in vitro model

to assess human microglial changes in an AD-like environment. We demonstrated that under

Aβ1-40-reduced levels, human microglia exhibit a miR-124low/miR-155high/miR-146ahigh profile

that subsequently switch to a miR-124high/miR-155low/miR-146alow profile concomitantly with

Aβ1-40 accumulation. This miRNA profile transition was accompanied by changes in the

expression of some miRNAs targets that are recognized to regulate microglial immune and

inflammatory response. In this AD model, we found that human microglia were characterized

by robust pro-inflammatory response as evidenced by overexpression of IL-6, IL-1β and

TNF-α mRNAs, but progressively acquire anti-inflammatory and regulatory properties, as

evidenced by gradual overexpression of Arginase 1, IL-10 and TGF-β mRNA levels. Along

with microglial miRNA profile transition, our results for phenotypic markers demonstrate that

microglia are rapidly polarized towards an activated/pro-inflammatory phenotype but later

change to an anti-inflammatory phenotype with the rising expression of regulatory markers

associated with M2 cells prevalence. Subsequently, microglia might gradually return to their

quiescent state as a consequence of miR-124 upregulation, in which some cells retain the

expression of the M2 markers. Furthermore, human microglia also exhibit rapid ability to

initiate innate immune responses demonstrated by early iNOS mRNA overexpression, as

well as slow ability to participate in the adaptive immune response as evidenced by

progressive MHC class II mRNA upregulation (Figure IV. 1).

IV. Discussion

54

Figure IV.1 | Human CHME3 microglial cells with a pro-inflammatory profile acquire a more anti-inflammatory/regulatory phenotype when co-cultured with SH-SY5Y APP695 Swe cells. In the presence of SH-SY5Y APP695 Swe cells, CHME3 microglia initially exhibit a miR-124

low/miR-155

high/miR-146a

high profile and promptly initiate the

innate immune response as evidenced by rapid iNOS mRNA upregulation. Once cells are co-cultured for longer time periods, CHME3 microglia progressively acquire a miR-124

high/miR-155

low/miR-146a

low profile and are probably more prone to participate

in the adaptive immunity, as evidenced by slow MHC class II mRNA upregulation. During the whole co-culture duration, microglia exhibited a robust pro-inflammatory response characterized by increased levels of TNF-α, IL-6 and IL-1β mRNAs, though progressively develop an anti-inflammatory/regulatory response as demonstrated by the increased expression of Arginase 1, IL-10 and TGF-β mRNAs, which is likely supported by miR-124 upregulation. These microglial changes were accompanied by a progressive increment of Aβ1-40 levels in CHME3 / SH-SY5Y APP695 Swe co-culture media.

As a final note, we consider that our findings in CHME3 / SH-SY5Y APP695 Swe co-

cultures provide a meaningful baseline to further studies aimed at using miRNA-based

technologies to modulate CHME3 microglia. Indeed, a previous study showed that miR-155

ablation in SOD1 mice, a model of amyotrophic lateral sclerosis, restored microglial

functionality and ameliorated disease symptoms (Butovsky et al. 2015). Based on this report,

one could expect that targeting microglial miRNA profile could be a powerful therapeutic

strategy in the treatment of AD. Hence, we believe that our AD cellular model offers suitable

in vitro conditions to perform CHME3 microglial miRNAs regulation and further assess how

the resulting phenotype is able to promote neuroprotection instead of neurodegeneration.


55

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Role of microRNA in microglial phenotype - ULisboa · 2018. 3. 29. · Publications The studies included in this thesis were presented in the following publications: Oral presentations