effects of m-csf and adherence on human monocyte - ag-rehli.de

Effects of M-CSF and Adherence on Human Monocyte to Macrophage

Differentiation

Diplomarbeit

Naturwissenschaftliche Fakultät III

Biologie und Vorklinische Medizin

Universität Regensburg

Vorgelegt von

Thomas Gross

2010

Table of Contents

1

TTaabbllee ooff CCoonntteennttss

Table of Contents ................................................................................. 1

Deutsche Zusammenfassung .............................................................. 4

1 Introduction .................................................................................... 6

1.1 The Mononuclear Phagocyte System (MPS) .............................. 6

1.1.1 Classification of Human Monocytes ....................................................... 8

1.2 The Role of M-CSF and Its Receptor CSF-1R ............................ 8

1.3 Effects of M-CSF on Monocyte Differentiation .......................... 11

1.3.1 In vitro Results ..................................................................................... 11

1.3.2 In vivo Results ...................................................................................... 11

1.4 Effects of Adhesion on Monocyte Differentiation ...................... 12

1.5 Transcription Factors Involved in Monocyte Differentiation ....... 14

1.6 M-CSF, Adherence and Human Monocyte to Macrophage

Differentiation ........................................................................... 15

2 Aim of the Study ........................................................................... 16

3 Material and Equipment ............................................................... 17

3.1 Equipment ................................................................................ 17

3.2 Consumables ........................................................................... 18

3.3 Chemicals ................................................................................ 18

3.4 Enzymes, Kits and Products for Molecular Biology ................... 18

3.5 Antibodies ................................................................................ 19

3.6 Molecular Weight Standards .................................................... 19

3.7 Software/Bioinformatics ............................................................ 19

3.8 Oligonucleotides ....................................................................... 20

Table of Contents

2

4 Methods ........................................................................................ 21

4.1 General Cell Culture Methods .................................................. 21

4.1.1 Isolation of Monocytes Through Counter Current Elutriation ............... 21

4.1.2 Monocyte Culture Conditions ............................................................... 22

4.1.2.1 Adherently Cultured Macrophages ................................................... 23

4.1.2.2 Non-Adherently Cultured Macrophages ........................................... 23

4.1.3 Determination of Total Cell Number and Vitality .................................. 23

4.2 Preparation and Analysis of RNA ............................................. 24

4.2.1 Cell Harvest and Total RNA Isolation ................................................... 24

4.2.2 Formaldehyde Agarose Gel (1%) ......................................................... 24

4.2.3 Reverse Transcription (RT) .................................................................. 25

4.2.4 Quantitative Real Time PCR (RT-qPCR) ............................................. 26

4.2.5 Primer Design ...................................................................................... 27

4.3 Whole Genome Expression Analysis ........................................ 28

4.3.1 Microarray Handling ............................................................................. 28

4.3.1.1 Labeling Reaction ............................................................................. 28

4.3.1.2 Microarray Hybridization ................................................................... 29

4.3.2 Data Analysis Using GeneSpring Software .......................................... 30

4.4 Hypergeometric Optimization of Motif EnRichment (HOMER) .. 30

4.5 Preparation and Analysis of Protein ......................................... 31

4.5.1 Cell Harvest and Sample Preparation .................................................. 31

4.5.1.1 Preparation of Whole Cell Extracts ................................................... 31

4.5.1.2 Preparation of Nuclear/Cytoplasm Extracts ...................................... 32

4.5.2 Discontinuous Sodium-Dodecyl-Sulfate-Polyacrylamide-Gel-Electrophoresis (SDS-PAGE) ............................................................... 33

4.5.3 Western Blotting (semi-dry technique) ................................................. 35

4.5.4 Immunostaining of Protein Blots .......................................................... 36

4.5.5 ECL Detection of Proteins .................................................................... 36

5 Results .......................................................................................... 37

5.1 Preliminary Work ...................................................................... 37

5.2 Generation of Adherent and Non-Adherent Macrophages ........ 37

Table of Contents

3

5.3 mRNA Expression in Adherent and Non-Adherent Macrophages .

................................................................................................. 38

5.4 Comparison of Global Gene Expression Profiles between

Adherent and Non-Adherent Macrophages .............................. 43

5.4.1 Global mRNA Expression Analysis ...................................................... 43

5.4.2 Promoter Motif Analysis ....................................................................... 45

5.5 Adherent Macrophages Display Elevated Expression of SRF

Target Genes ........................................................................... 46

5.6 In silico Analysis of Putative SRF and FLI1 Binding Sites ......... 50

5.7 Western blot Analysis of SRF and FLI1 Protein Expression ..... 51

5.7.1 Analysis of FLI1 Protein Expression .................................................... 51

5.7.2 Analysis of SRF Protein Expression .................................................... 52

6 Discussion .................................................................................... 55

6.1 Adherence-Dependent Human Monocyte to Macrophage

Differentiation ........................................................................... 55

6.2 SRF and Macrophage Adherence ............................................ 57

6.3 Outlook ..................................................................................... 62

7 Summary ....................................................................................... 63

8 References .................................................................................... 64

Abbreviations ..................................................................................... 70

Danksagungen .................................................................................... 72

Eidesstaatliche Erklärung .................................................................. 73

Deutsche Zusammenfassung

4

DDeeuuttsscchhee ZZuussaammmmeennffaassssuunngg

Durch die Aktivierung von Signaltransduktionskaskaden kann das Verhalten einer

Zelle verändert werden. Zu den Faktoren, die intrazelluläre Kaskaden anschalten,

zählen unter Anderem Chemokine, Komponenten der extrazellulären Matrix sowie

Wachstumsfaktoren. Der Wachstumsfaktor Macrophage Colony Stimulating Factor

(M-CSF) bindet an den Rezeptor CSF-1R und aktiviert auf diese Weise intrazelluläre

Signalkaskaden, die das Überleben und die Differenzierung von Makrophagen

beeinflussen. Aus diesem Grund wird M-CSF allgemein als wichtiger Überlebens-

und Differenzierungsfaktor für Makrophagen angesehen. Dabei stammen jedoch die

meisten Daten, die diese Annahme stützen, aus dem Maussystem. Ein interessanter

Befund der Vorarbeiten, die in unserem Labor durchgeführt wurden, war, dass die

Differenzierung von humanen Monozyten unter Adhärenzbedingungen unabhängig

von M-CSF verläuft. Die mit dem spezifischen Inhibitor (GW2580) des M-CSF

Rezeptors behandelten Monozyten zeigten im Laufe der Differenzierung nur eine

geringfügig erhöhte Apoptoserate und exprimierten die Makrophagen spezifischen

Gene CHIT1 und CHIL3 genauso wie unbehandelte Makrophagen. Außerdem gehen

nicht-adhärent kultivierte Makrophagen ohne M-CSF innerhalb weniger Tage

komplett in Apoptose über. Deswegen gehen wir davon aus, dass Adhärenz im

humanen System als Überlebens- und Differenzierungsstimulus ausreicht.

Das Ziel dieser Arbeit war es, diese interessanten Beobachtungen weiter zu

verfolgen, und dabei die Effekte von M-CSF und Adhärenz auf humane

Makrophagen genauer zu studieren. Hierfür wurden Makrophagen unter adhärenten

sowie nicht-adhärenten Bedingungen für einen Zeitraum von sieben Tagen kultiviert.

Adhärent kultivierte Makrophagen wurden gleich nach dem Aussäen in parallelen

Ansätzen mit M-CSF, GW2580 beziehungsweise DMSO (als Kontrolle für GW2580,

da GW2580 in DMSO gelöst wurde) behandelt. Es wurden zu unterschiedlichen

Zeitpunkten der Differenzierung Zellen geerntet und entsprechend den weiteren

Experimenten präpariert. Dabei wurden die verschieden stimulierten

Makrophagenkulturen vor allem auf der Ebene des Transkriptoms untersucht.

Die genomweite Analyse eines Zeitverlaufs lieferte Hinweise darauf, dass die

Genexpression im Laufe der Differenzierung unter nicht-adhärenten Bedingungen im

Allgemeinen verzögert reguliert wird. Zudem wiesen die Expressionsprofile von

Deutsche Zusammenfassung

5

M-CSF beziehungsweise GW2580 kultivierten Makrophagen wenig bis gar keine

Unterschiede auf. Diese Ergebnisse unterstützen unsere Annahme, dass Adährenz

im humanen System als Überlebens- und Differenzierungsstimulus ausreicht.

De novo Analysen der Promotorstrukturen lieferten die Sequenzmotive für Klasse I

ETS Faktoren, STAT/ISRE, und den Serum Response Faktor (SRF). Western Blot

Analysen zeigten, dass die 67 kDA Isoform von SRF (SRF-FL) in adhärenten

Makrophagen stärker angereichert war als in nicht-adhärenten Makrophagen. Durch

die Analyse der Microarray-Daten konnte festgestellt werden, dass im Laufe der

Makrophagen-Differenzierung bekannte Zielgene des SRF unter adhärenten

Bedingungen deutlich stärker hochreguliert werden als unter nicht-adhärenten

Bedingungen.

Zusammenfassend deuten die Ergebnisse der vorliegenden Arbeit darauf hin, dass

SRF im Rahmen der Adhärenz abhängigen Makrophagendifferenzierung eine

wichtige Rolle spielen könnte.

Introduction

6

11 IInnttrroodduuccttiioonn

11..11 TThhee MMoonnoonnuucclleeaarr PPhhaaggooccyyttee SSyysstteemm ((MMPPSS))

In the 1880s, Elie Metchnikoff described phagocytes in invertebrates as well as in

vertebrates, indicating that phagocytosis, carried out by macrophages and

neutrophils, is not only used to scavenge apoptotic cells, but is also an important host

defence mechanism of innate immunity (Chang 2009). Based on the observation that

macrophages and endothelial cells are both capable of phagocytosis, K.A.L. Aschoff

developed the idea of the „reticuloendothelial system‟ (RES) in the late 19th and early

20th centuries (Chang 2009). However, later investigations pointed out that

endothelial cells are not phagocytes.

As monoblasts, pro-monocytes, monocytes and macrophages have similar

morphological, cytochemical and functional characteristics, they were recognized as

a cell family called mononuclear phagocytes. These findings defined the basis of the

concept of the „mononuclear phagocyte system‟ (MPS), which was postulated by van

Furth in 1969 (van Furth et al. 1982).

Circulating CD14+ monocytes account for 5 to 10% of peripheral blood leukocytes in

humans and represent the key members of the MPS. Monocytes have the capacity to

differentiate into various immune cells, including macrophages, dendritic cells and

osteoclasts (Seta and Kuwana 2007). The remarkable heterogeneity of macrophages

is related to their origin, phenotype, tissue localization, proliferative potential, and

function (Taylor and Gordon 2010). Table 1-1 lists the different macrophage subtypes

in various tissues.

Introduction

7

Tissue Cell

Bone marrow

Monoblasts

Promonocytes

Monocytes

Macrophages

Peripheral blood Monocytes

Liver Kupffer cells

Lung Alveolar macrophages

Connective tissue Histiocytes

Spleen

Red Pulp Macrophages Lymph node

Thymus

Bone Osteoclasts

Synovium

Type A Cells Mucosa-associated lymphoid tissue

Gastrointestinal tract

Central nervous system Microglia

Skin Histiocytes/Langerhans cells

Serous cavities Pleura/Peritoneal Macrophages

Inflammatory tissues Epitheloid cells

Exudative macrophages

Granuloma Multinucleated giant cells

Table 1-1: Mononclear phagocytes in different tissues (Ross and Auger, 2002)

In the classical sense, peripheral macrophages are replenished by circulating blood

monocytes rather than by local cell division. However, recent findings state that at

least a small percentage of cell renewal is carried out by local cell division under

steady state conditions (Tacke and Randolph 2006). Several researchers object the

usefulness of the MPS as there might be as many different macrophage subtypes as

markers applied for their description (Hume 2006). In addition, they argue that all

macrophages can change as a consequence of their microenvironment by

continuously adapting their functional pattern in response to the progressive

inflammatory response (Stout et al. 2005). Thus, revision of the model of the MPS

might be necessary.

Introduction

8

1.1.1 Classification of Human Monocytes

Human peripheral blood monocytes are an inhomogeneous population as they differ

in phenotype and function. In humans, three subsets of monocytes could be

described defined by their phenotype and cytokine production.

CD14+CD16- monocytes represent 80% to 90% of blood monocytes, express high

levels of the chemokine receptor CCR2 and low levels of CX3CR1. They produce

interleukin-10 (IL-10) rather than tumor necrosis factor (TNF) and IL-1 in response to

lipopolysaccharide (LPS) in vitro (Serbina et al. 2008).

CD16+ monocytes are classified as proinflammatory cells, express high levels of

CX3CR1 and low levels of CCR2 (Geissmann et al. 2003; Weber et al. 2000); , and

in general have been described to be responsible for the production of TNF in

response to LPS stimulation (Ziegler-Heitbrock 2000). However, it could be

demonstrated that CD16+ monocytes are composed of at least two populations with

remarkably distinct functions (Grage-Griebenow et al. 2001). Monocytes expressing

CD16 and CD14 (CD14+CD16+) do also express the fragment, crystallizable (Fc)

receptors CD64 and CD32, produce TNF and IL-1 in response to LPS and have

phagocytic activity (Grage-Griebenow et al. 2001). In contrast, monocytes expressing

CD16 but very low levels of CD14 (CD14dimCD16+) do not express CD64 and CD32,

are poorly phagocytic and lack the production of TNF or IL-1 in response to LPS

(Skrzeczyńska-Moncznik et al. 2008).

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The development of blood monocytes is dependent on a cytokine known as the

Macrophage Colony Stimulating Factor (M-CSF). M-CSF is a disulfide linked

homodimeric growth factor that acts on cells of the mononuclear phagocytic system,

including monocytes, macrophages, dendritic cells and osteoclasts. Regarding

monocytes and macrophages, M-CSF is known to control proliferation of monocytes

and their progenitors (Clanchy et al. 2006), to regulate monocytic survival and to

support the differentiation of monocytes to macrophages (Irvine et al. 2009).

Macrophages can be polarized by the micro-environment to mount specific M1 or M2

functional programs (Mantovani et al. 2002). M1-type macrophages are 'classically

Introduction

9

activated' macrophages that respond to interferon-γ (IFNγ) by releasing pro-

inflammatory cytokines, such as IL-12 and IL-23, and that are involved in the T helper

1 (Th1)-cell-mediated immune resolution of infection (Gordon 2003).

M2-type macrophages are 'alternatively activated' macrophages that respond to Th2-

type cytokines, such as IL-4 and IL-13, and are involved in fibrosis, tissue repair and

humoral immunity (Mantovani et al. 2002). M-CSF is constitutively present in vivo (2 -

30 ng/ml in normal human serum) (Irvine et al. 2009) and favors an M2-polarized

phenotype during human monocyte to macrophage differentiation (Martinez et al.

2006) Thus, the M2-polarized phenotype is likely to predominate under homeostatic

conditions.

Human macrophages produce three biologically active isoforms of M-CSF:

A secreted glycoprotein, a cell-surface glycoprotein and a secreted proteoglycan,

which either circulates or is anchored to the extracellular matrix (ECM). During

human monocyte to macrophage differentiation all three M-CSF isoforms are

upregulated (Bonafé et al. 2005). It is known from mouse experiments that M-CSF

regulates several functions of mature macrophages like chemotaxis, adherence or

antimicrobial responses. In human mature macrophages, M-CSF regulates

cholesterol biosynthesis and lipid metabolism and favors a proatherogenic

environment (Irvine et al. 2009). M-CSF is often considered as a pro-tumor cytokine

enhancing growth and aggressiveness of several tumor types by stimulating tumor

infiltrating macrophages to produce angiogenic growth factors, proteases that

facilitate tumor metastases and immunosuppressive molecules (Biswas et al. 2008).

All known effects of M-CSF are mediated by the cell surface receptor CSF-1R, which

is expressed in progenitor and mature cells of the MPS. CSF-1R is also known to be

expressed in cells of the deciduas and placental trophoblast (Irvine et al. 2009). The

CSF-1R is a type III tyrosine kinase receptor encoded by the proto-oncogene c-fms

(Sherr et al. 1985), and is closely related to the c-Kit receptor. The receptor is

comprised of an extracellular ligand binding domain joined through a single

membrane-spanning helix to an intracellular protein tyrosine kinase domain. The

extracellular ligand binding domain is composed of five immunoglobulin-like loops.

Binding of the homodimeric M-CSF to the receptor‟s extracellular ligand binding

domain induces non-covalent dimerization of the CSF-1R, activation of the receptor‟s

kinase and a first wave of receptor tyrosine phosphorylation. After covalent

dimerization and a second wave of tyrosine phosphorylation, specific tyrosine

Introduction

10

residues in the cytoplasmic domain will be phosphorylated allowing various linker

proteins to bind and activate multiple intracellular signal transduction pathways.

Amongst others, the phosphatidylinositol-3 kinase (PI3K) pathway mediates

macrophage survival. Along with the sarcoma (src)/Proline-rich and Ca2+-activated

tyrosine kinase (Pyk2) pathway, the PI3K pathway influences macrophage adhesion

and motility through the Rho family of GTPases. The extracellular signal-regulated

kinase (ERK) mitogen-activated protein kinase (MAPK) pathway Raf/MEK/ERK

promotes cellular proliferation and activation (Pixley and Stanley 2004) (Figure 1-1).

Figure 1-1: Signaling pathways regulated by CSF-1R (Pixley and Stanley 2004)

In general, triggering this phosphorylation cascade increases gene transcription and

protein translation and induces cytoskeletal remodeling, leading to the survival,

proliferation and differentiation of target cells (Yeung and Stanley 2003). Following

activation of CSF-1R with M-CSF, the ligand-receptor complex is rapidly internalized,

gets ubiquitinated and lysosomaly degraded (Pixley and Stanley 2004). The rate of

reappearance of the receptor at the cell surface limits biological responses to M-CSF

(Fowles et al. 2000).

Introduction

11

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1.3.1 In vitro Results

As human macrophages are difficult to obtain from human donors in sufficient

amounts, it is necessary to generate them in vitro from peripheral blood monocytes

for further analyses. Studying human monocytes in vitro, Becker and colleagues

recognized that adhesion is an important factor for survival and differentiation of

monocytes (Becker et al. 1987). This observation led to the assumption that

biochemical factors present in human serum must be crucial for monocyte

maturation. Soon M-CSF was revealed as one critical factor for monocyte survival, as

treatment of adherent cultures with human serum in presence of anti-M-CSF

antibodies inhibited monocyte maturation (Andreesen et al. 1990). Monocyte survival

is dependent on the type of material used for culturing monocytes in vitro. Monocytes

survived in serum free cultures when they were able to firmly adhere to plastic, as

firm adhesion on plastic allows monocytes to produce autocrine survival factors like

M-CSF and TNF (Haskill et al. 1988). On hydrophobic teflon foils, monocytes do not

adhere as firlmy as on plastic; the semi-adherent teflon grown monocytes required

exogenous M-CSF in order to be rescued from apoptosis in serum free medium.

Irrespective of the type of surface coating, monocyte survival was never

accompanied by differentiation under serum free conditions (Andreesen et al. 1990).

Komuro et al. stated that macrophages need continuous M-CSF as its removal

results in apoptosis and that M-CSF itself induces the production of survival and

differentiation factors (Komuro et al. 2005). Thus, M-CSF was found to be obligatory

for monocyte survival and differentiation. However, M-CSF alone is not sufficient to

replace human serum, and it could be shown that human erythrocyte catalase, which

is a component of human serum, enhances monocyte survival in the absence of M-

CSF (Komuro et al. 2005).

1.3.2 In vivo Results

Mice being homozygous for an inactivating mutation of the M-CSF encoding gene

(Csf1op/Csf1op) or being deficient for the CSF-1 receptor (Csf1r-/Csf1r-) showed

Introduction

12

reduced numbers of almost all tissue macrophage populations and have diminished

response to inflammatory challenge. Diminished macrophage counts in Csf1op/op-

mice could be restored by a daily intracutaneous injection of M-CSF (Stanley et al.

1997; Chitu and Stanley 2006) or by using M-CSF transgenes for the different

isoforms (Dai et al. 2004; Nandi et al. 2006) . These findings highlight the importance

of M-CSF in the murine system.

11..44 EEffffeeccttss ooff AAddhheessiioonn oonn MMoonnooccyyttee DDiiffffeerreennttiiaattiioonn

A hematopoietic stem cell (HSC) in the bone marrow may differentiate to a common

lymphoid progenitor (CLP) and a common myeloid progenitor (CMP). The CMP

mediates the generation of precursors of erythrocytes, granulocytes and monocytes

and is followed by the granulocyte-monocyte precursor (GMP) that still has the ability

to differentiate into granulocytes and monocytes. Finally, a monoblast differentiates

under the influence of the granulocyte-monocyte colony-stimulating factor (GM-CSF)

and M-CSF after the premonocyte state to monocytes (Figure 1-2).

Figure 1-2: Hematopoietic stem cell differentiation (Mancarelli et al. 2010 - modified)

Introduction

13

Monocytes leave the bone marrow, enter the blood and circulate before they adhere

to the endothelium of blood vessels and transmigrate into the surrounding tissue.

Adhesion involves an initial selectin-glycoprotein interaction resulting in monocyte

rolling, succeeded by the activation of monocyte integrins via chemokines, which

allows a firm integrin-protein adhesion. After cell polarization, monocytes are able to

migrate by diapedesis between epithelial cells into the subendothelial ECM (Imhof

and Aurrand-Lions 2004).

It seems likely that monocytes enter the tissues randomly and retain a certain

plasticity to react to the local biochemical micro-environment rather than exhibiting

multiple but distinct populations (Stout and Suttles 2004). After entering the tissue,

monocytes become soon indistinguishable from resident macrophages (Hume 2006).

The micro-environment is defined by stromal and lymphoid cells, the ECM and

soluble factors. Cell-cell and cell-substrate interactions are viewed as important

events influencing a broad range of cellular characteristics (Shi and Simon 2006).

Thus, cell–cell and cell–matrix contacts are supposed to have an impact on the

differentiation of monocytes.

Monocyte adhesion is followed by integrin ligation resulting in an „outside-in‟ integrin

signaling causing phosphorylation of tyrosine residues of certain intracellular

proteins, namely ERK, p38 and the c-Jun N-terminal kinase (JNK). Tyrosine

phosphorylation subsequently leads to the activation of transcription, stabilization of

the produced mRNA and organization of the cytoskeleton (Mondal et al. 2000).

Currently it is not known to what extent this signaling cascade influences the

differentiation of monocytes. However, several groups demonstrated the role of

transcription factors targeted by integrin engagement. For instance, down-regulation

of the expression of the transcription factor forkhead box P1 (Foxp1) is critical for

monocyte differentiation in vitro (Shi and Simon 2006) and in vivo, because Foxp1

represses the transcription of the CSF-1R; furthermore, transgenic mice

overexpressing human Foxp1 exhibited reduced macrophage accumulation and

survival (Shi et al. 2008). This underlines the importance of the CSF-1R for monocyte

maturation. Apart from this, it could be unveiled, that JNK and M-CSF are able to

interact, suggesting a synergic effect of adhesion and M-CSF on monocyte to

macrophage differentiation (Himes et al. 2006).

Introduction

14

11..55 TTrraannssccrriippttiioonn FFaaccttoorrss IInnvvoollvveedd iinn MMoonnooccyyttee

DDiiffffeerreennttiiaattiioonn

The specification of hematopoietic cells is governed by the coordinated action of

several transcription factors regulating the expression of myeloid-specific genes.

Amongst the numerous transcription factors being involved, PU.1 plays a central role

as it controls several cell fate decisions along the myelo-monocytic pathway. PU.1 is

a member of the Ets family of transcription factors and is known to be essential in the

development of myeloid lineages (Rosmarin et al. 2005). Its inhibitory interaction with

the GATA binding protein GATA-1 shuts down the megakaryocytic/erythroid

pathway. Repression of GATA-2 blocks mast cell development (Walsh et al. 2002).

At the stage of the granulocyte/macrophage progenitors, PU.1 drives monocytic

differentiation by antagonizing C/EBPα, a transcription factor required for granulocytic

development; C/EBPα is a member of the CCAAT enhancer-binding proteins

(C/EBPs) (Zhang et al. 1996). PU.1 can be considered as some kind of master

transcription factor regulating the expression of the CSF-1R gene c-fms during

hematopoiesis (Chang 2009). Expression of c-fms is controlled by its promoter and

the c-fms intron regulatory element FIRE. Transcriptional activation of c-fms occurs in

two stages. In the stage of the hematopoietic stem cell, PU.1 binds to the c-fms

promoter at low levels. In the stage of committed macrophage progenitor cells, the

promoter and FIRE are fully occupied by PU.1, causing the binding of a number of

transcription factors (e.g. early growth response protein 2 (EGR-2), C/EBPs, runt-

related transcription factor 1 (RUNX1) and SP1) to FIRE through chromatin

remodeling, which leads to the high-level expression of CSF-1R mRNA and CSF-1R

proteins (Krysinska et al. 2007).

Apart from PU.1, a batch of other transcription factors is known to be involved in

monocyte to macrophage differentiation. For instance, RUNX1 physically associates

with C/EBPα while binding to the c-fms promoter (Zhang et al. 1996). MafB is

responsible for the up-regulation of macrophage-related transcription factors (Gemelli

et al. 2008). The interferon regulatory factor 8/interferon consensus sequence-

binding protein (IRF-8/ICSBP) induce the expression of target genes, such as

cathepsin C and cystatin C, during early stages of macrophage differenation by

binding to a cis element that also binds PU.1 (Tamura et al. 2005). C/EBPβ and PU.1

are considered to regulate gene expression during late stages of monocyte to

Introduction

15

macrophage differentiation. This could be indicated by their recruitment to the

promoter of the CHIT1-gene, whose expression correlates with late macrophage

differentiation (Pham et al. 2007). The forkhead transcription factor Foxp1 is a

transcriptional repressor of the CSF-1R and is regulated by integrin engagement.

Down-regulation of the expression of Foxp1 is critical for monocyte differentiation

(Shi and Simon 2006; Shi et al. 2008).

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MMaaccrroopphhaaggee DDiiffffeerreennttiiaattiioonn

The action of transcription factors can be modified by signal transduction pathways

triggered by several factors, including cytokines, chemokines and components of the

ECM. The secretion of the cytokine M-CSF can be induced by monocyte adhesion

(Becker et al. 1987; Haskill et al. 1988). M-CSF mediates its effects through CSF-1R

and is known to be important for monocytic survival and differentiation (Pixley and

Stanley 2004; Irvine et al. 2009), but most data supporting the importance of M-CSF

for monocyte to macrophage differentiation are based on the murine system (Brugger

et al. 1991; Pixley and Stanley 2004). However, in humans, adherence by its own

could be sufficient for survival and differentiation of monocytes. Preliminary work in

our laboratory demonstrated that adherent macrophages treated with the CSF-1R-

specific inhibitor GW2580 expressed the macrophage-specific genes CHIT1 and

CHI3L1 similar to untreated macrophages. In the absence of M-CSF, non-adherently

cultured macrophages underwent apoptosis within 3 days of culture. Apoptosis was

inhibited by adding exogenous M-CSF at the beginning of the culture period.

Compared to untreated adherent macrophages, adherently cultured and with

GW2580 treated macrophages showed only a slightly higher rate of apoptosis in the

process of differentiation (Pham et al. 2007). These findings suggest that autocrine

M-CSF plays a minor role for survival and differentiation of adherently cultured

human macrophages.

Aim of the Study

16

22 AAiimm ooff tthhee SSttuuddyy

Based on the results of preliminary work, the aim of this study was to elucidate the

effects of M-CSF and adherence on the differentiation of human peripheral blood

monocytes to macrophages in detail. Adherent and non-adherent monocytes were

cultured over a time window of seven days. By analyzing gene expression in

adherent monocytes treated with DMSO, M-CSF and GW2580 respectively, and in

non-adherent monocytes treated with M-CSF, transient differences in gene

expression levels should be detectable. The comparison of expression profiles of

differently cultivated macrophages should reveal which genes are regulated by

adherence, M-CSF or both during the process of differentiation. A de novo motif

search algorithm in target gene promoters possibly delivers sequence motifs for

transcription factors that could play a role during adherence-dependent monocyte to

macrophage differentiation. Transcription factors will be further analyzed by Western

blot. These experiments should contribute to the understanding of M-CSF and

adherence in their role in the process of differentiation of human macrophages.

Material and Equipment

17

33 MMaatteerriiaall aanndd EEqquuiippmmeenntt

33..11 EEqquuiippmmeenntt

Autoclave Technomara, Fernwald, Germany

Biofuge fresco Heraeus, Osterode, Germany

Camera Polaroid, Cambridge, USA

Densitometer Molecular Dynamics, Krefeld, Germany

Electrophoresis equipment Biometra, Göttingen, Germany

Fast-blot-apparatus Biometra, Göttingen, Germany

Film-development machine Agfa, Köln, Germany

Heat sealer Fermant 400 Josten & Kettenbaum, Bensberg, Germany

Heatblock Stuart Scientific, Staffordshire, UK

Incubators Heraeus, Hanau, Germany

Laminar air flow cabinet Lamin Air HA 2472 Heraeus, Osterode, Germany

Megafuge 3,0 R Heraeus, Osterode, Germany

Microarray hybridization chambers SureHyb Agilent Technologies, Böblingen, Germany

Microarray hybridization oven w/rotator Agilent Technologies, Böblingen, Germany

Microarray scanner; 5 micron resolution Agilent Technologies, Böblingen, Germany

Microarray slide holder Agilent Technologies, Böblingen, Germany

Microscopes Zeiss, Jena, Germany

Multifuge 3S-R Heraeus, Osterode, Germany

Multipipettor Multipette plus Eppendorf, Hamburg, Germany

NanoDrop PeqLab, Erlangen, Germany

Neubauer hemocytometer Carl Roth, Karlsruhe, Germany

PCR-Thermocycler PTC-200 MJ-Research/Biometra, Oldendorf, Germany

pH-Meter Knick, Berlin, Germany

Picofuge Heraeus, Osterode, Germany

Power supplies Biometra, Göttingen, Germany

Realplex Mastercycler epGradient S Eppendorf, Hamburg, Germany

Sorvall RC 6 plus Thermo Fisher Scientific, Hudson, USA

Speed Vac Christ, Osterode, Germany

Thermomixer Eppendorf, Hamburg, Germany

Typhoon 9200 Molecular Dynamics, Krefeld, Germany

Water purification system Millipore, Eschborn, Germany

Universal turning device Greiner Bio-One, Frickenhausen, Germany


18

33..22 CCoonnssuummaabblleess

Cell culture flasks and pipettes Costar, Cambridge, USA

Centrifuge tubes (15, 50, 200, 250 ml) Falcon, Heidelberg, Germany

Heat sealing films Eppendorf, Hamburg, Germany

Micro test tubes (0.5, 1.5, 2 ml) Eppendorf, Hamburg, Germany

Microarray gasket slides Agilent Technologies, Santa Clara, USA

Microarray slides, 4x44K format Agilent Technologies, Santa Clara, USA

PCR plate Twin.tec 96 well Eppendorf, Hamburg, Germany

PVDF transfer membrane Millipore, Eschborn, Germany

Syringes and needles Becton Dickinson, Heidelberg, Germany

Sterile combitips for Eppendorf multipette Eppendorf, Hamburg, Germany

Sterile micropore filters Millipore, Eschborn, Germany

Sterile plastic pipettes Costar, Cambridge, USA

Sterile plastic petri dishes, 100x15mm Falcon, Heidelberg, Germany

Sterile plastic roller bottles Falcon, Heidelberg, Germany

Teflon foils Heraeus, Hanau, Germany

Whatmann paper Biometra, Göttingen, Germany

X-ray films (ECL, Amersham) GE Healthcare, München, Germany

33..33 CChheemmiiccaallss

All chemicals were purchased from Sigma (Deisendorf, Germany) or Merck

(Darmstadt, Germany) unless otherwise mentioned.

33..44 EEnnzzyymmeess,, KKiittss aanndd PPrroodduuccttss ffoorr MMoolleeccuullaarr BBiioollooggyy

Aprotinin Roche, Mannheim, Germany

Bestatin Roche, Mannheim, Germany

BSA Sigma, Deisenhofen, Germany

Chymostatin Roche, Mannheim, Germany

DTT Invitrogen, Darmstadt, Germany

E-64 Roche, Mannheim, Germany

GW2580 Merck, Darmstadt, Germany

Gene Expression Hybridization Kit Agilent, Waldbronn, Germany

Leupeptin Roche, Mannheim, Germany


19

Low RNA Linear Amp Kit PLUS, One-Color Agilent, Waldbronn, Germany

M-CSF, human recombinant R&D Systems, Minneapolis, USA

Nonidet P40 Roche, Mannheim, Germany

Pepstatin Roche, Mannheim, Germany

QuantiTect SYBR Green Qiagen, Hilden, Germany

RNA Spike-In Kit, One-Color Agilent, Waldbronn, Germany

RNeasy Mini Kit Qiagen, Hilden, Germany

RNase-Free DNase Set Qiagen, Hilden, Germany

Transcriptor High Fidelity cDNA Synthesis Kit Roche, Mannheim, Germany

Western Blotting Detection Reagent (ECL, Amersham) GE Healthcare, München, Germany

33..55 AAnnttiibbooddiieess

ß-Actin rabbit, polyclonal Sigma, Deisenhofen, Germany

FLI1 (C-19)x rabbit, polyclonal Santa Cruz, Heidelberg, Germany

GABPα (C-20) goat, polyclonal Santa Cruz, Heidelberg, Germany

GABPβ1/2 (N-20)x goat, polyclonal Santa Cruz, Heidelberg, Germany

Goat Anti-rabbit IgG HRP conjugate rabbit, polyclonal Dako, Hamburg, Germany

Phospho-SRF[Ser103] rabbit, polyclonal NEB, Frankfurt, Germany

Rabbit Anit-goat IgG HRP conjugate goat,polyclonal Dako, Hamburg, Germany

SRF (G-20)x rabbit, polyclonal Santa Cruz, Heidelberg, Germany

33..66 MMoolleeccuullaarr WWeeiigghhtt SSttaannddaarrddss

Kaleidoscope Precision Plus Protein Standard Bio-Rad Laboratories, Hercules, Canada

Kaleidoscope Prestained Standards Bio-Rad Laboratories, Hercules, Canada

Novex Sharp Prestained Protein Standard Invitrogen, Darmstadt, Germany

33..77 SSooffttwwaarree//BBiiooiinnffoorrmmaattiiccss

Agilent Feature Extraction Software Agilent, Waldbronn, Germany

Agilent Scan Control Software Agilent, Waldbronn, Germany

BLAT http://genome.brc.mcw.edu

GeneRunner version 3.05 Hastings Software

GeneSpring GX11.0.1 Agilent, Waldbronn, Germany

HOMER http://biowhat.ucsd.edu/homer/

MATInspector Genomatix Software, Germany

Microsoft Excel 2003/2007


20

Perlprimer version 1.1.19

PubMed www.ncbi.nlm.nih.gov/entrez

USCS Genome Browser www.genome.ucsc.edu

33..88 OOlliiggoonnuucclleeoottiiddeess

CCL2_fwd 5-GCGAGCTATAGAAGAATCACCAGCA-3

CCL2_rev 5-CATGGAATCCTGAACCCACTTCTG-3

CCL22_fwd 5-CGTGATTACGTCCGTTACCGTC-3

CCL22_rev 5-ATCGGCACAGATCTCCTTATCCC-3

CCL7_fwd 5-GCACTTCTGTGTCTGCTGCTC-3

CCL7_rev 5-TGGTGGTCCTTCTGTAGCTCTC-3

CHI3L1_ fwd 5-AAGGTCACCATTGACAGCAGC-3

CHI3L1 _rev 5-CCTCAACATGTACCCCACAGC-3

CXCL10_fwd 5-GTACCTGCATCAGCATTAGTAATCAACC-3

CXCL10_rev 5-TGGATTCAGACATCTCTTCTCACCC-3

CXCL5_fwd 5-GATCAGTAATCTGCAAGTGTTCGCC-3

CXCL5_rev 5-CAAGACAAATTTCCTTCCCGTTCTTCAG-3

CXCR4_fwd 5-ACCTCTACAGCAGTGTCCTCATCC-3

CXCR4_rev 5-TCCAGACGCCAACATAGACCAC-3

DHCR7_fwd 5-CCCAACATTCCCAAAGCCAAGAG-3

DHCR7_rev 5-TAGGAAGATGACGCTCGCCAG-3

DUSP5_fwd 5-AGAGCCCTCATCAGCCAGTG-3

DUSP5_rev 5-CATGGTAGGCACTTCCAAGGTAGAG-3

EGR1_fwd 5-AGCAGCACCTTCAACCCTCAG-3

EGR1_rev 5-CCAGCACCTTCTCGTTGTTCAG-3

EGR2_fwd 5-CCATCTTTCCCAATGCCGAACTG-3

EGR2_rev 5-CCAGTCATGTCAATGTTGATCATGCC-3

EGR3_fwd 5-CAACTGCCTGACAATCTGTACCC-3

EGR3_rev 5-GGTTGGGCTTCTCGTTGGTC-3

IFI44_fwd 5-TCGAAGGGAGTTGGTAAACGC-3

IFI44_rev 5-GGACCTCACAGGCTCACATCTC-3

MAPK13_fwd 5-TTGGGCTCCTGGATGTCTTCAC-3

MAPK13_rev 5-GGTACTGGATCTTCTCCTCACTGAACTC-3

MMP19_fwd 5-GAAGAAGAGACAGAGCTGCCCAC-3

MMP19_rev 5-CTGCATCCAGGTTAGGTTCTACCC-3

PPARγ_fwd 5-GGGCGATCTTGACAGGAAAGAC-3

PPARγ_rev 5-CCACCTCTTTGCTCTGCTCCT-3

TFPI_fwd 5-GCCTGCTGCTTAATCTTGCCC-3

TFPI_rev 5-CCATCATCCGCCTTGAATGCAC-3

Methods

21

44 MMeetthhooddss

Unless otherwise mentioned, all methods were based on protocols described in

„Current protocols of Molecular Biology‟ (Ausubel 1988) and in the „Molecular cloning

laboratory manual‟ (Sambrook 2001).

44..11 GGeenneerraall CCeellll CCuullttuurree MMeetthhooddss

All cells for long term and for short term culturing were incubated in an incubator

(Hareus) at a constant temperature of 37°C, with a 95% humidity and 5% CO2

concentration. For washing and harvesting, cells were centrifuged using the general

cell program: 8 min, 300×g, 4°C.

4.1.1 Isolation of Monocytes Through Counter Current Elutriation

Peripheral blood mononuclear cells (PB-MNCs) were separated by leukapheresis of

healthy donors, followed by density gradient centrifugation over Ficoll/Hypaque.

Monocytes were then isolated from MNCs by counter current centrifugal elutriation.

Elutriation was performed in a J6M-E centrifuge equipped with a JE 5.0 elutriation

rotor and a 50 ml flow chamber (Beckmann, Germany). After sterilizing the system

with 6% H2O2 for 20min, the system was washed with phosphate buffered saline

(PBS) two times. Following calibration at 2500 rpm and 4°C with Hanks balanced salt

solution (BSS), MNCs were loaded at a flow rate of 52 ml/min. Fractions were

collected and the flow through rate was sequentially increased according to Table

4-1.

Methods

22

Fraction Volume (ml) Flow rate (ml/min) Main cell type contained

Ia 1000 52 platelets

Ib 1000 57

B- and T- lymphocytes, Natural Killer (NK) cells

IIa 1000 64

IIb 500 74

IIc 400 82

IId 400 92

III 800 130 monocytes

Table 4-1. Elutriation parameters and cell types

Monocytes represent the largest cells within the MNCs and are therefore mainly

obtained in the last fraction. Monocytes were >85% pure as determined by

morphology and CD14 antigen expression. Low amounts of monocytes may be also

detected in the IId fraction. Monocytes (fraction III) were centrifuged (8 min, 300×g,

4°C), resuspended in RPMI culture medium and counted. Monocyte yields were

donor dependent, typically between 10-20% of total MNCs. Supernatants of

monocyte cultures were routinely collected and analysed for the presence of IL-6

which was usually low, indicating that monocytes were not activated before or during

elutriation.

4.1.2 Monocyte Culture Conditions

In order to generate macrophages in vitro, 1×106 monocytes/ml were cultured in

RPMI 1640, routinely supplemented with 2% AB-serum, L-glutamine (2 mM), sodium

pyruvate (1 mM), antibiotics (50 U/ml penicillin and 50 µg/ml streptomycin), 2 ml

vitamins, non essential amino acids and 50 µM ß-mercaptoethanol unless otherwise

mentioned. Media supplements were purchased from Gibco and Biochrome (L-

glutamine) respectively. Cells were cultured at 37°C, 5% CO2 and with 95% relative

humidity in an incubator.

Morphology of macrophages was examined microscopically.

Methods

23

4.1.2.1 Adherently Cultured Macrophages

For RNA isolation adherent macrophages were cultured on plastic petri dishes over a

time window of seven days. At the beginning of the culture period, cells were treated

with recombinant human (rh) M-CSF (100 ng/ml), GW2580 (10 µM) and DMSO (10

µl/10 ml), respectively, in parallel approaches. GW2580 was solved in DMSO; thus,

DMSO served as vehicle control for GW2580.

For preparation of whole cell and nuclear/cytoplasm extract, adherent macrophages

were cultured on teflon foils over a time window of 18 hours (h).

4.1.2.2 Non-Adherently Cultured Macrophages

Non-adherent macrophages were cultured over a time window of seven days (RNA

isolation) or 18 h (preparation of whole cell and nuclear/cytoplasm extract) in a

continuously rotating (12 U/min) flask (250 ml centrifuge tube, Falcon) with a vented

cab (Costar), using a universal turning device (Greiner Bio-One). Cells were treated

with rh M-CSF (100 ng/ml) at the beginning of the culture period.

4.1.3 Determination of Total Cell Number and Vitality

Required materials: Trypan blue solution: 0.2% (w/v) trypan blue in 0.9% NaCl-solution

The total number of cells and their vitality was determined microscopically using vital

staining with trypan blue (TP). The cell suspension was diluted with the TP-solution.

Dead cells are stained dark blue with TP and are clearly distinguishable from living

cells in the microscope, as living cells exclude TP actively. Using a Neubauer

hemocytometer the number of living cells within a large corner square was counted

and the concentration of viable cells was then calculated using the following

equation:

Methods

24

Number of viable cells/ml: C = N×D×104

N = average of unstained cells per corner square (1 mm² containing 16 sub-squares)

D = dilution factor

44..22 PPrreeppaarraattiioonn aanndd AAnnaallyyssiiss ooff RRNNAA

4.2.1 Cell Harvest and Total RNA Isolation

Adherent and non-adherent macrophages were harvested after different time points

(4 h, 18 h, 42 h, 162 h) in culture. Adherent cells were washed once with PBS,

scraped, and lysed with buffer RLT supplemented with ß-mercaptoethanol (ß-ME) by

using a syringe and a 0.9 mm needle. Non-adherent cells were washed with PBS,

centrifuged and lysed. Total RNA was isolated using the Qiagen RNeasy Mini Kit

following the manufacturer‟s manual. To remove potential DNA contamination,

DNase digestion with the RNase-Free DNase Set (Qiagen, Germany) was embedded

in the protocol. RNA concentration was then determined with the NanoDrop

spectrophotometer and quality was assessed by agarose gel electrophoresis.

4.2.2 Formaldehyde Agarose Gel (1%)

Required Buffers: (Stated weight-% or molarities refer to the end concentrations)

MOPS (20×): 0.4 M 42 g MOPS/NaOH, pH 7.0

100 mM 4.1 g NaOAc

20 mM 3.7 g EDTA

Add H2ODEPC to 500 ml, store in the dark

Methods

25

RNA loading buffer: 50% 10 ml Formamide, deionised

2.2 M 3.5 ml Formaldehyde (37%)

1x 1 ml MOPS (20×)

0.4% 0.8 ml Bromophenol blue (1% in H2O)

1% 0.2 g Ficoll 400, Pharmacia; dissolve in 2 ml H2O

Add H2ODEPC to 20 ml, store in 1 ml aliquots at -20°C

Add 5 µl/ml Ethidium bromide (10 mg/ml) before use

Agarose 0.3 g 0.5 g 2 g 2.5 g

H2ODEPC 22.8 ml 38 ml 153 ml 190 ml

MOPS (20x) 1.5 ml 2.5 ml 10 ml 19.5 ml

After cooling down to 60°C - 55°C, add

Formaldehyde 5.28 ml 8.8 ml 35 ml 44 ml

Table 4-2. RNA agarose gel mixture

According to the required total amount (Table 4-2), the agarose was dissolved in

MOPS/H2ODEPC by heating in a microwave oven and cooled to 60°C. Formaldehyde

was added while stirring the solution under a fume hood and the gel was cast,

mounted in an electrophoresis tank and overlaid with 1× MOPS as electrophoresis

buffer. RNA samples were heated to 37°C for 30 min to control RNase contamination

and placed on ice afterwards. Samples were subsequently diluted with four volumes

RNA loading buffer (1:4), denatured for 20 min at 65°C and briefly incubated on ice.

Following centrifugation, the samples were loaded into the gel slots. Gels were run at

40-60 volts.

4.2.3 Reverse Transcription (RT)

To quantify mRNA transcripts of genes, total RNA was reverse transcribed to

complementary DNA (cDNA) using the Transkriptor High Fidelity cDNA Synthesis Kit

(Roche, Germany) following the manufacturer‟s manual.

Methods

26

Reaction setup:

Template-primer mix: 1 µg total RNA

Add H2OUSB to 10.4 µl

Add 1 µl Anchored oligo (dT)18 Primer

Master mix: 4 µl Transcriptase Reaction Buffer (5x)

0.5 µl Protector RNase Inhibitor

2 µl dNTP-Mix

1 µl DTT

1.1 µl Transcriptor High Fidelity Reverse Transcriptase

The template-primer mixture was denatured by heating for 10 min at 65°C, then was

immediately cooled on ice, and 8.6 µl Master mix were added per reaction. The

reaction was incubated for 30 min at 45°C, and the reverse transcriptase was

inactivated by heating to 85°C for 5 min. The reaction was stopped by placing the

tubes on ice. The resulting cDNA was then diluted 1:5 and quantified with specific

primers by quantitative Real time PCR (RT-qPCR) (see section 4.2.4).

4.2.4 Quantitative Real Time PCR (RT-qPCR)

In general, the polymerase chain reaction (PCR) allows in vitro synthesis of large

amounts of DNA by primed, sequence-specific polymerization of nucleotide

triphosphates, catalyzed by DNA polymerase. Quantitative real-time PCR (RT-qPCR)

was used for quantification of cDNA after reverse transcription (see section 4.2.3).

PCR reactions were performed using the QuantiFast SYBR Green Kit from Qiagen in

a 96 well format adapted to the Eppendorf Realplex Mastercycler EpGradient S

(Eppendorf, Hamburg, Germany) (Table 4-3 and Table 4-4: RT-qPCR conditions).

Specific primers amplify small regions of the fragment of interest, and the relative

amount of amplified DNA was measured through the emission of light by the SYBR

green dye, when it intercalated in double stranded DNA.

Methods

27

Component Volume Final concentration

2 x SYBR Green mix

(QuantiFast, Qiagen) 5 μl 1 x

H2O 2 μl

10 µM Primer_forward 0.5 μl 0.5 μM

10 µM Primer_reverse 0.5 μl 0.5 μM

Template DNA 2 µl

Table 4-3. Basic RT-qPCR conditions

Cycle step Temp. Time Number of cycles

Initial Melting 95°C 5 min 1

Melting 95°C 8 s

45 Combined Annealing and Extension 60°C 20 s

Melting 95°C 15 s 1

Combined Annealing and Extension 60°C 15 s

Melting Curve 10-20 min

95°C 15 s

Table 4-4. Thermocycler RT-qPCR program

To calculate amplification efficiency, a dilution series (1:10; 1:20, 1:50; 1:100) of a

suitable cDNA-containing sample was additionally measured for each primer pair.

Realplex software automatically calculated DNA amounts based on the generated

slope and intercept. Specific amplification was controlled by melting-curve analysis

and data were imported and processed in Microsoft Excel 2003 or 2007, respectively.

All samples were measured in duplicates and normalized to the ACTB housekeeper-

gene, dividing mean Sybr-green values by the corresponding ACTB values.

4.2.5 Primer Design

Unless otherwise mentioned sequences for generating primer were extracted using

the UCSC Genome Browser. In general, primers were designed with PerlPrimer

Software and controlled using in-silico PCR and BLAT functions of the UCSC

Genome Browser. Following settings were used to design primer:

Methods

28

Primer Tm: 65-68°C

Primer length: 20-28 bp

Amplicon size: 80-150 bp

Primers comprised sequences of different exons, except primers for CXCR4, EGR-3

and TFPI. Primers were purchased from Metabion.

44..33 WWhhoollee GGeennoommee EExxpprreessssiioonn AAnnaallyyssiiss

Total RNA preparations from three different human donors were used to globally

analyse gene expression patterns on Whole Human Genome Expression arrays

(4x44K, Agilent).

4.3.1 Microarray Handling

Labeling of high quality RNA, hybridization and scanning were performed using the

Agilent Gene Expression system according to the manufacturer‟s instructions.

4.3.1.1 Labeling Reaction

200 ng to 1000 ng high quality RNA were amplified and cyanine 3-CTP labeled using

the one color Low RNA Input Linear Amplification Kit from Agilent in order to

generate fluorescent cRNA (complementary RNA). The method uses T7 RNA

polymerase, which simultaneously amplifies the target material and incorporates

cyanine 3-CTP. In brief, the appropriate amount of total RNA was mixed with the

designated volume of the Agilent one color Spike-In-Mix dilution together with the T7

Promoter primer. Template and primer were denatured at 65°C for 10 min. Next, the

reaction was placed on ice for 5 min. After adding the cDNA Master Mix, which

contains the MMLV Reverse Transcriptase for reverse transcription of total RNA, the

samples were incubated at 40°C for 2 h. Afterwards the reaction was heated to 65°C

for 15 min in order to disrupt possible secondary structures. Samples were put on ice

immediately for 5 min and the Transcription Master Mix was added. It contains the

already mentioned T7 RNA Polymerase and the cyanine 3 labeled CTP. Samples

Methods

29

were incubated at 40°C for 2 h. The labeled and amplified cRNA was purified using

Qiagen‟s RNeasy mini spin columns. Labeling efficiency was controlled using the

NanoDrop spectrophotometer. Thus it was possible to determine yield and specific

activity of each reaction.

4.3.1.2 Microarray Hybridization

1.65 µg labeled cRNA with a specific activity of more than 9.0 pmol Cy3 per µg cRNA

were fragmented and hybridized on Whole Human Genome Expressionarrays

(4×44K, Agilent). The Fragmentation Mix was prepared as follows:

Component Volume/Mass

Labelled, linearly amplified cRNA 1.65 μg

Agilent Blocking Agent (10x) 11 μl

Nuclease free water Add to 52.8 μl

Fragmentation Buffer (25x) 2.2 μl

Samples were incubated at 60°C for exactly 30 minutes in order to fragment RNA.

Afterwards, the fragmentation was stopped by adding of 2x Hybridization buffer.

The final hybridization mixture for the 4x44K (4 arrays/slide) Whole Human Genome

microarrays were prepared as follows:

Component Volume

cRNA from Fragmentation Mix 55 μl

Agilent Hybridization Buffer (2x) (2xGE, HI-RPM)

55 μl

The sample was spun down and kept on ice until loading onto an array, which was

performed as soon as possible. Hybridization on microarray slides (Agilent) was then

carried out at 65°C for 17 h using an Agilent SureHyb chamber and an Agilent

hybridization oven. After 17 hours of hybridization at 65°C, slides were washed in

Gene Expression Wash Buffer I (Agilent) at room temperature for one minute and in

Gene Expression Wash Buffer II (Agilent, prewarmed to 37°C) for an additional

minute. Afterwards slides were dried and incubated in acetonitrile for 30 seconds.

Images were scanned immediately using a DNA microarray scanner (Agilent), and

processed with Feature Extraction Software 9.5.1 (Agilent) using default parameters

(protocol GE1-v5_95_Feb_97) to obtain background subtracted and spatially

derended, processed signal intensities.

Methods

30

4.3.2 Data Analysis Using GeneSpring Software

For further analysis, text files resulting from Feature Extraction were imported to

GeneSpring GX 11.0.1 software (Agilent) in order to compare gene expression

profiles between various differentiation time points and conditions.

First, probes showing large variations either between donors or among each other

(if more than one probe for one gene is available) were excluded. Data for a given

gene were normalized to the median expression level of that gene across all

samples.

Generally, only more than 6 fold signal changes were defined as gene induction or

repression. The gene list was reduced to significantly regulated genes using a fold

change with a cut off of 5.0, and using One-way ANOVA (p-value < 0.05).

Hierarchical cluster analysis was used to identify genes with similar expression

profiles and to reveal common functions of significantly regulated genes. Using a fold

change with a cut off of 2.0, custom lists were created by pairing expression profiles

of the differently treated macrophages at the given time points with each other and

with freshly isolated monocytes. Those custom lists display genes that are up- or

down-regulated respectively in one condition compared to another condition at

identical time points. Custom lists were used as target sets for de novo motif search

performed with a de novo motif discovery algorithm called HOMER (see section 4.4).

Processed data was imported into Microsoft Office Excel 2007 for further analysis.

In order to validate microarray data, several genes were selected and verified by RT-

qPCR (see section 4.2.4)

44..44 HHyyppeerrggeeoommeettrriicc OOppttiimmiizzaattiioonn ooff MMoottiiff EEnnRRiicchhmmeenntt

((HHOOMMEERR))

HOMER is a de novo motif discovery algorithm that was used to identify sequences

that are enriched in promoters of up-regulated genes in adherent or in non-adherent

macrophages. HOMER looks for motifs with differential enrichment between two sets

of sequences. The program was used to find motifs of a length of 8, 10 and 12 bp,

respectively, from -300 bp to +50 bp realtive to the transcription start site (TSS) that

were overrepresented in the promoters of a target set (list of genes that were up- or

Methods

31

down-regulated, respectively, in one condition compared to another condition at

identical time points) relative to the promoters of a background set (default promoter

set of human genes that are not regulated). In each case sequences were matched

for their CpG content to avoid bias from CpG islands. Motifs were found by first

exhaustively checking the enrichment of simple motifs, then refining promising

candidates into accurate probability matrices.

44..55 PPrreeppaarraattiioonn aanndd AAnnaallyyssiiss ooff PPrrootteeiinn

4.5.1 Cell Harvest and Sample Preparation

Adherent cells were harvested at different time points (4 h, 18 h) in culture.

Therefore, after removing non-adherent macrophages by washing the cells with PBS

at room temperature, adherent macrophages were cooled by adding PBS at 4°C and

subsequently detached by carefully “juddering” the teflon foils (Andreesen et al.

1983). After harvesting, cells were centrifuged, and the pellet was resuspended in

PBS at 4°C before counting. Non-adherent cells were harvested at time points 4 h

and 18 h in culture by centrifugation. The pellet was resuspended in PBS at 4°C, and

cells were counted. Adherent and non-adherent cells were washed with PBS at 4°C.

The supernatant was removed, the pellet resuspended in 1-1.5 ml PBS at 4°C and

transferred to an Eppendorf cup.

Whole cell and nuclear/cytoplasm extracts were prepared in order to detect specific

proteins in a given sample by western blotting technique.

4.5.1.1 Preparation of Whole Cell Extracts

Cells were washed 4 min at 4°C with 3500 rpm. After removing the supernatant, the

pellet was resuspended in 1 ml PBS. Cells were centrifuged 4 min at 4°C with 3500

rpm. The supernatant was removed completely and 100 µl SDS sample buffer (2x)

were added. Samples were immediately denatured at 95°C and were shaked for 10

min with 600 rpm. Afterwards, samples were vortexed at maximum speed for 1 min

and aliquoted in 2 x 50 µl. Samples were stored at -20°C.

Methods

32

4.5.1.2 Preparation of Nuclear/Cytoplasm Extracts

Required Buffers:

Cytoplasmic extraction buffer (CEB): 10 mM Tris pH 7.9

60 mM KCl

1 mM EDTA

Pre-equilibration buffer: Lysis buffer: Final conc.

EDTA pH 8.0 1.5 mM

DTT 1 mM

EGTA 1 mM

ß-Glycerophosphate 50 mM

Sodium-Flouride 50 mM

Sodium-Pyrophosphate 25 mM

Sodium-Orthovanadate 1 mM

Leupeptin 2 µg/ml

Pepstatin A 2 µg/ml

Aprotinin 2 µg/ml

Pre-equilibration buffer and lysis buffer always had to be made fresh. The required

amount of lysis buffer, and thus also pre-equilibration buffer, was adjusted according

to the applied number of cells (150 µl lysis buffer/10x106 cells).

Cells were washed 5 min at 4°C to -9°C with 3500 rpm. After removing the

supernatant, the pellet was resuspended in 500 µl pre-equilibration buffer. Cells were

centrifuged for 4 min at 4°C to -9°C with 3500 rpm and the supernatant was removed

completely. Afterwards the pellet was resuspended in 150 µl lysis buffer/10x106 cells.

For lysis, cells were incubated on ice for 10 min. In order to separate nuclei and

cytoplasm the lysed cells were centrifuged for 4 min at 4°C to -9°C with 3500 rpm,

and pellet (nuclei) and supernatant (cytoplasm) were devided transferring the

supernatant into a fresh Eppendorf cup. Protein samples were stored at -20°C.

Directly before loading onto the gel, samples were diluted by adding the same

amount of SDS sample buffer (2x). Afterwards, samples were once denatured by

boiling for 5 min at 95°C shaking with 600 rpm.

Final conc.

NP 40 0.4%

Chymostatin 100 µg/ml

Bestatin 10 µg/ml

E64 3 µg/ml

1.10 phenanthroline 1 mM

Methods

33

4.5.2 Discontinuous Sodium-Dodecyl-Sulfate-Polyacrylamide-Gel-

Electrophoresis (SDS-PAGE)

Protein samples were separated electrophoretically by using a discontinuous gel

system composed of stacking and separating gel layers that differ in salt and

acrylamide (AA) concentration.

Required Buffers and Solutions: (Stated weight-% or molarities refer to the end concentrations)

Acrylamide (30%): 146 g Acrylamide (MW 71.1)

4.0 g BIS (MW 154.2)

5.0 g PDA (MW 194.2)

Add ddH2O to 500 ml

Separating gel buffer: 1.5 M 90.83 g Tris/HCl pH 8.8

Add ddH2O to 500 ml

Stacking gel buffer: 0.5 M 30 g Tris/HCl pH 6.8

Add ddH2O to 500 ml

SDS stock solution: 10% 10 g SDS

Add ddH2O to 100 ml

Tris buffer: 1.25 M 13 g Tris/HCl pH 6.8

Add ddH2O to 100 ml

SDS sample buffer (2 x): 20% 10 ml Glycerin

125mM 5 ml Tris buffer

4% 2 g SDS

10% 5 ml 2-Mercaptoethanol

0.02% 10 mg Bromphenolblue

Add ddH2O to 50 ml

APS (10%): 100 mg Ammonium persulfate

Add ddH2O to 1 ml

Methods

34

Laemmli buffer (5×): 40 mM 15 g Tris

0.95 M 21 g Glycine

0.5% 15 g SDS

Add ddH2O to 3000 ml

Gel Stock Solutions Separating Gel Stacking Gel

7.5% 10% 12% 15% 5%

Stacking Gel Buffer - - - - 2.5 ml

Separating Gel Buffer 2.5 ml 2.5 ml 2.5 ml 2.5 ml -

SDS (10%) 0.1 ml 0.1 ml 0.1 ml 0.1 ml 0.1 ml

AA (30%) 2.5 ml 3.3 ml 4.0 ml 5.0 ml 1.665 ml

Distil water 4.9 ml 4.1 ml 3.4 ml 2.4 ml 5.735 ml

Table 4-5. SDS-PAGE stock solutions

Stock solutions Separating Gel Stacking Gel

Stock solutions 6 ml 3 ml

TEMED 6 µl 3 µl

APS (10%) 50 µl 40 µl

Table 4-6. SDS-PAGE gel mixture

According to the designated concentration (Table 4-5 & Table 4-6), the separating

gel was prepared the day before electrophoresis and overlaid with water-saturated

isobutanol until it was polymerized. Isobutanol was exchanged by separating gel

buffer diluted 1:3 with water and the gel was stored overnight at 4°C. The following

day, the stacking gel was poured on top of the separating gel, and the comb was

inserted immediately. After polymerization, the gel was mounted in the

electrophoresis tank, which was filled with 1×Laemmli buffer. Protein samples were

loaded and the gel was run with 60 volts until the sample buffer bands reached the

surface of the stacking gel. Next, the voltage was increased to 120-140 volts and the

gel was run for 2-4h (Shapiro et al. 1967; Laemmli et al. 1970). Proteins were

resolved through the separating gel according to their size.

Methods

35

4.5.3 Western Blotting (semi-dry technique)

Required buffers:

(Stated weight-% or molarities refer to the end concentrations)

Buffer A: 0.3 M 36.3 g Tris, pH 10.4

20% 200 ml Methanol


Buffer B: 25 mM 3.03g Tris, pH 10.4

20% 200 ml Methanol


Buffer C 4 mM 36.3 g ε-amino-n-caproic acid, pH 7.6

20% 200 ml Methanol


After separation by SDS-PAGE, proteins were blotted electrophoretically onto a

polyvinylidene fluoride (PVDF) membrane (Immobilon-P, Millipore) using a three-

buffer semi-dry system (Towbin et al. 1979) and visualized by immunostaining using

specific antibodies and the ECL detection kit. The membrane was cut to gel size,

moistened first with methanol followed with buffer B and placed on top of three

Whatman3MM filter papers soaked with buffer A (bottom, on the anode), followed by

three Whatman3MM filter papers soaked with buffer B. The SDS-PAGE gel was then

removed from the glass plates, immersed in buffer B and placed on top of the

membrane. Another three Whatman 3MM filter papers soaked with buffer C were

placed on top of the gel followed by the cathode. Air bubbles in between the layers

had to be avoided. Protein transfer was conducted for 45 min at 0.8 mA/cm2 gel

surface area.

Table 4-7. Preparation of blotting sandwich

Cathode

3x Whatmann paper in buffer C

SDS gel

Membrane

3x Whatmann paper in buffer B

3x Whatmann paper in buffer A

Anode

Methods

36

4.5.4 Immunostaining of Protein Blots

Required buffers and solutions:

(Stated weight-% or molarities refer to the end concentrations)

TBS (10x): 100 mM 45.8 g Tris /HCl, pH 7.4

1.5 M 175.5 g NaCl


TBST: TBS (1x) + 0.1% Tween20 100 ml TBS (10x)

1ml Tween20


Milk powder solution: 5% 5 g milk powder

100 ml TBST

BSA: 5% 5 g BSA

100 ml TBST

Blotted membranes were blocked with 5% milk in TBST for 1h and washed three

times for 6 min with TBST if the primary antibody was diluted in BSA. Incubation with

the primary antibody was carried out at 4 C overnight. After washing three times 6

min with TBST, the membrane was incubated for 1h with a horseradish-peroxidase

(HRP)-coupled secondary antibody, detecting the isotype of the first antibody. Three

washing steps of 3x 6 min preceded the visualization of bound antibody using the

ECL detection kit.

4.5.5 ECL Detection of Proteins

In the ECL detection the peroxidase coupled to the secondary antibody catalyzes the

oxidation of luminol. The resulting chemiluminescence signal was detected on an

autoradiography film (HyperfilmTM ECL, Amersham). Blots were exposed to the

autoradiography film for 5 sec to 30 min or longer depending on the signal intensity.

Results

37

55 RReessuullttss

55..11 PPrreelliimmiinnaarryy WWoorrkk

Preliminary work in our laboratory showed that human peripheral blood monocytes

differentiated independently of M-CSF when cultured adherently. Adherent

monocytes treated with the CSF-1R-specific inhibitor GW2580 underwent apoptosis

at a slightly higher rate than adherent untreated macrophages. In addition, GW2580-

treated macrophages expressed the macrophage-specific genes CHIT1 and CHI3L1

similar to untreated macrophages (Pham et al. 2007). CHIT1 and CHI3L1 are both

genes whose expression correlates with late macrophage differentiation (Boot et al.

1995; Rehli et al. 2003). By analyzing the transcriptome of differently treated

macrophages over a time course, the aim of this study was to examine the effects of

M-CSF and adherence on human monocyte to macrophage differentiation.

55..22 GGeenneerraattiioonn ooff AAddhheerreenntt aanndd NNoonn--AAddhheerreenntt

MMaaccrroopphhaaggeess

In order to investigate the impact of adherence and M-CSF on the process of

differentiation, human monocytes were treated with DMSO, GW2580, and

exogenous M-CSF, respectively, directly after seeding on petri-dishes. Monocytes

were cultured on plastic petri-dishes to generate adherent macrophages. On plastic,

monocytes are able to adhere firmly and produce autocrine M-CSF (Haskill et al.

1988). GW2580 is a selective inhibitor of CSF-1R, blocking its kinase activity by

competitive inhibition of ATP binding to the tyrosine kinase receptor. Thus, GW2580

inhibits the M-CSF mediated activation of signal transduction pathways (Conway et

al. 2005) that are, amongst others, involved in survival and differentiation. As

GW2580 was dissolved in DMSO, macrophages treated with DMSO served as

vehicle control. In a parallel approach, monocytes were cultured non-adherently

using a continuously rotating turning device, which inhibits adhesion to the plastic

Results

38

container. As non-adherently cultured monocytes need exogenous M-CSF in order to

survive, M-CSF was added at the beginning of the culture period.

Figure 5-1: Cell culture setup

Since monocytes probably show a great donor dependent variability in mRNA

expression, differently treated adherent macrophages and non-adherent

macrophages were prepared in parallel cultures from five independent donors.

55..33 mmRRNNAA EExxpprreessssiioonn iinn AAddhheerreenntt aanndd NNoonn--AAddhheerreenntt

MMaaccrroopphhaaggeess

Gene expression profiles change during human monocyte to macrophage

differentiation and, potentially, also in dependence on treatment. Irvine and

colleagues previously studied the impact of M-CSF in human monocyte-derived

macrophages (HMDM). HMDM were differentiated in medium containing recombinant

human (rh) M-CSF on tissue culture plastic. On day 5 after seeding, HMDM were

supplemented with fresh medium, harvested and replated on day 6 and used on day

7 for further analyses prior to expression analysis using microarray approach. HMDM

were M-CSF starved overnight prior to stimulation with rh M-CSF for 6 h. They were

able to identify novel genes regulated by M-CSF in mature human macrophages.

According to their results, CXCR4 expression is down-regulated while expression of

CCL2, CCL7, CXCL10 and DHCR7 is upregulated in mature HMDM after stimulation

of M-CSF for 6h (Irvine et al. 2009).

Based on the previous publication by Irvine et al. CCL2, CCL7, CXCL10, DHCR7 and

CXCR4 were selected for RT-qPCR to analyze for differentiation or treatment related

Results

39

effects on gene expression. For this purpose, cells were harvested at different time

points (4 h, 18 h, 42 h, 162 h) during monocyte to macrophage differentiation. Total

RNA from five independent donors was isolated using the Qiagen RNeasy Mini Kit.

RNA concentration was determined using the NanoDrop spectrophotometer. Integrity

of RNA was assessed by agarose gel electrophoresis. Using RT-qPCR, a time

course of mRNA expression of these genes was analyzed revealing donor

dependent variabilities. However, donors 1, 2 and 5 generally displayed comparable

mRNA expression profiles. Thus, these 3 donors were selected for genome-wide

expression analyses of the effects of M-CSF, adherence or both in the process of

monocyte to macrophage differentiation using microarray approach (Figure 5-2,

Figure 5-3 and Figure 5-4).

Results

40

Figure 5-2, Panel A and B: mRNA expression profile of the human genes

CCL2 and CCL7 in 5 donors RT-qPCR for (A) CCL2 and (B) CCL7 expression at the indicated differentiation time points of adherent macrophages treated with DMSO, M-CSF and GW2580, respectively, and of non-adherent macrophages (NonAdh). DMSO serves as vehicle control for GW2580. Results were normalized to ACTB expression and recalculated in relation to the expression values of sample DMSO 4 h in order to adjust donor dependent variabilities. Values are means ± SD obtained from two technical replicates.

Results

41

Figure 5-3, Panel A and B: mRNA expression profile of the human genes

CXCL10 and CXCR4 in 5 donors RT-qPCR for (A) CXCL10 and (B) CXCR4 expression at the indicated differentiation time points of adherent macrophages treated with DMSO, M-CSF and GW2580, respectively, and of non-adherent macrophages (NonAdh). DMSO serves as vehicle control for GW2580. Results were normalized to ACTB expression and recalculated in relation to the expression values of sample MN 0 h in order to adjust donor dependent variabilities. Values are means ± SD obtained from two technical replicates.

Results

42

Figure 5-4: mRNA expression profile of the human DHCR7 gene in 5 donors RT-qPCR for DHCR7 expression at the indicated differentiation time points of adherent macrophages treated with DMSO, M-CSF and GW2580, respectively, and of non-adherent macrophages (NonAdh). DMSO serves as vehicle control for GW2580. Results were normalized to ACTB expression and recalculated in relation to the expression values of sample MN 0 h in order to adjust donor dependent variabilities. Values are means ± SD obtained from two technical replicates.

Results

43

55..44 CCoommppaarriissoonn ooff GGlloobbaall GGeennee EExxpprreessssiioonn PPrrooffiilleess

bbeettwweeeenn AAddhheerreenntt aanndd NNoonn--AAddhheerreenntt MMaaccrroopphhaaggeess

5.4.1 Global mRNA Expression Analysis

Genome-wide expression analyses were performed to identify groups of genes that

are regulated by M-CSF, adherence or both in the process of monocyte to

macrophage differentiation, and thus may play an important role for monocyte

differentiation. For this purpose, total RNA of donors 1, 2 and 5 was used for

microarray analyses. These three donors showed less variation in terms of

expression profiles and therefore were selected for global mRNA expression

analysis. Signal intensity raw data generated by Agilent Feature Extraction software

were analyzed with GeneSpring GX 11.0.1 in order to compare gene expression

profiles between various differentiation time points and conditions. Values of all three

independent donors were averaged for each time point. Canditate genes were further

reduced to significantly differentially expressed genes using a fold change cut off of

5.0 prior to One-way ANOVA analysis (p-value < 0.05) (see section 4.3.2).

Figure 6-5 illustrates expression differences of significantly regulated genes in

differently treated macrophages at time points 4 h, 18 h and 162 h during monocyte

to macrophage differentiation. Signal intensities were normalized to expression data

of freshly isolated monocytes to reduce donor dependent variability. In general,

expression levels of adherent macrophages treated either with DMSO, M-CSF or

GW2580 displayed little to no differences. However, mRNA expression differed

between all adherent macrophages (represented as DMSO, M-CSF and GW2580)

and non-adherent macrophages at all indicated time points in the course of

differentiation. Adherent macrophages showed clusters comprising significantly up-

or down-regulated genes. By comparison, in non-adherently cultured macrophages,

gene expression generally seemed to be less strongly regulated. However, gene

expression levels of non-adherent macrophages converged to expression levels of

adherent macrophages in the course of differentiaton, suggesting a delayed

regulation in macrophages if cultured under non-adherent conditions (Figure 5-5).

Results

44

Figure 5-5: Hierarchical clustering of treatments and time points Color-coded expression levels of candidate genes with significant up- or down-regulation (fold change >5). Blue, white and red represent low, medium and high expression, respectively. The tree on the left represents genes with similar expression patterns. Three independent donors were averaged before further analyses. DMSO, MCSF and GW2580 indicate gene-expression in adherently cultured but differently treated macrophages; Nadh indicates gene-expression in non-adherent macrophages.

Results

45

5.4.2 Promoter Motif Analysis

Co-regulated genes are supposed to share similarities in their regulatory

mechanisms. Thus, promoter regions of these genes may contain common sequence

motifs representing binding sites for transcription factors. The identification of

transcription factors could advert to pathways that might be involved in M-CSF or

adherence induced survival and differentiation of monocytes. Hence, Hypergeometric

Optimization of Motif EnRichment (HOMER), a de novo motif discovery algorithm,

was used to identify sequences that are enriched in promoters of up-regulated genes

in adherent or in non-adherent macrophages (see section 4.4). This algorithm only

determines enriched motifs within gene promoters and does not account for other

regulatory elements. The sequence motif for the serum response factor (SRF) was

significantly enriched in promoter sequences of genes up-regulated after 4h in M-

CSF-treated adherent macrophages compared to non-adherent macrophages

(Figure 5-6, panel A). SRF is a member of the MADS box superfamily of

transcription factors and regulates the activity of several immediate-early genes, like

for EGR-1 and EGR-2, and thereby contributes to apoptosis, cell-growth and cell

differentiation (Chai and Tarnawski 2002). Another motif was enriched in promoter

sequences of genes up-regulated in adherent, M-CSF treated macrophages as well

as in non-adherent macrophages at the time points 4 h and 18 h compared to freshly

isolated monocytes (MN 0 h). This motif, here termed as for FLI (Figure 5-6, panel

B), actually represents the consensus binding site of class I ETS factors (Wei et al.

2010). As one representative, FLI1 was further analyzed. The STAT/ISRE motif was

enriched in promoter sequences of genes upregulated in non-adherent macrophages

compared to adherent macrophages at the time points 4 h, 18 h and 162 h (Figure 5-

6, panel C). However, transcription factors that are able to bind to the interferon

stimulated response element (ISRE) were not further analyzed.

Results

46

Figure 5-6: Promoter Motif Analysis Enriched sequence motifs are shown in the top line for each transcription factor. Published consensus sites are shown below the enriched motifs. p-Values represent the enrichment of the appropriate motif contained in the promoter sequence of genes that were (A) up-regulated in adherent macrophages when compared to non-adherent macrophages, (B) up-regulated in adherent and non-adherent macrophages when compared to freshly isolated monocytes, (C) up-regulated in non-adherent macrophages when compared to adherent macrophages at the indicated time points.

55..55 AAddhheerreenntt MMaaccrroopphhaaggeess DDiissppllaayy EElleevvaatteedd EExxpprreessssiioonn ooff

SSRRFF TTaarrggeett GGeenneess

Upon de novo motif search, gene expression data were further analyzed on the basis

of significantly enriched motifs. For candidate genes, expression profiles of adherent

macrophages (adherent MAC + M-CSF) were compared with non-adherent

macrophages (NonAdh MAC) (time points 4 h, 18 h and 162 h). In addition,

expression profiles of adherent MAC + M-CSF and NonAdh MAC, respectively, were

compared with freshly isolated monocytes (MN 0 h) (time points 4 h, 18 h and 162 h).

Results

47

Expression levels of candidate genes selected on the basis of the SRF motif are

demonstrated in Figure 5-7, panel A.

SRF binds to SREs in the promoter of EGR-1 and EGR-2 (Chai and Tarnawski

2002). Chromatin immunoprecipitation (ChIP) assays experimentally verified SRF

binding upstream of DUSP5 (Tullai et al. 2004). In addition, CCL22 was selected as

one gene that is not known to be targeted by SRF. CCL22 is known to be highly

expressed in mature macrophages (Fantuzzi et al. 2003).

Adherent MAC + M-CSF displayed elevated expression levels of EGR-1, EGR-2 and

DUSP5 at 4 h; afterwards expression decreased. In the case of CCL22, expression

seemed to increase continuously during the culture period of adherent MAC + M-

CSF. In contrast, NonAdh MAC showed reduced expression of these genes at

almost all examined time points (Figure 5-7, panel A).

Expression levels of candidate genes selected on the basis of the Class I ETS factor

motif are shown in Figure 5-7, panel B.

In adherent MAC + M-CSF, expression of MMP19, which is preferentially expressed

by monocytes (Bar-Or et al. 2003), was increased after 4h of culture and was still

higher expressed at the 18 h time point, compared to its expression in NonAdh MAC.

During the seven day period of culturing, the expression level of MAPK13 appeared

to be increasingly up-regulated in adherent MAC + M-CSF as well as in NonAdh

MAC, reaching the maximum of expression at 162 h of culturing. To some extent

NonAdh MAC showed a lower expression of MAPK13 (Figure 5-7, panel B).

However, differences in MAPK13 expression between adherent MAC + M-CSF and

NonAdh MAC were not striking, and thus this gene served as control for the

validation of expression array data by RT-qPCR.

Results

48

Figure 5-7: Expression levels of indicated genes in adherent and non-adherent macrophages (A) Relative expression levels of candidate genes with SRF motif in promoter sequences. (B) Relative expression levels of candidate genes with Class I ETS factor motif in promoter sequences. Expression levels of indicated genes were normalized to the median of the expression level of the corresponding candidate gene across all samples.

Since microarray data studies implicate several false positive data points, these

results need to be confirmed by other methods. For this purpose, expression profiles

of EGR-1, EGR-2, DUSP5, CCL22, MMP19 and MAPK13 were verified using RT-

qPCR (see section 4.2.4). As demonstated in Figure 5-8, data of both approaches

were consistent. EGR-1 showed highest expression levels at 4 h and 18 h of

monocyte differentiation. EGR-2 expression levels were already up-regulated at 4 h,

slightly increased at 18 h and afterwards decreased. DUSP5-expression was high at

4 h, and then decreased rapidly. The expression of CCL22 increased continuously

during the culture period (Figure 5-8). Significant differences in expression between

adherent MAC + M-CSF and NonAdh MAC were calculated using paired t-test

(Figure 5-8) and point out that in non-adherently cultured macrophages, gene

expression in general seems to be less strongly regulated. Expression profiles

Results

49

between adherent MAC + M-CSF and adherent MAC + GW2580, which is the CSF-

1R inhibitor, displayed only marginal differences. These findings indicate that

adherence induced monocyte to macrophage differentiation proceeds mainly

independently of M-CSF, thus emphasizing the assumption, that adherence by its

own seems to be sufficient for the survival and differentiation of human monocytes.

Figure 5-8: mRNA expression profiles of genes in adherent and non-adherent macrophages Validation of mRNA microarray experiments using RT-qPCR. Data were normalized to ACTB expression and have been recalculated in relation to monocytes (MN; 0 h). Values are means ±SD obtained from five independent experiments. Asterisks denote significant differences in mRNA expression between adherent MAC + M-CSF and NonAdh MAC, calculated by using paired t-test: p<0.001*** (highly significant); p<0.01** (very significant); p< 0.05* (significant); p>0,05 (not significant). Freshly isolated MN were cultured adherently and treated either with DMSO (vehicle control), GW2580 or M-CSF for the indicated time points directly after seeding. Freshly isolated MN were also cultured non-adherently for 4 h, 18 h and 162h respectively.

Results

50

55..66 IInn ssiilliiccoo AAnnaallyyssiiss ooff PPuuttaattiivvee SSRRFF aanndd FFLLII11 BBiinnddiinngg

SSiitteess

To determine putative SRF and FLI1 binding sites upstream of the transcription start

sites (TSS) of EGR-1, EGR-2, DUSP5, CCL22, MMP19 and MAPK13, 1 kb

sequences upstream of the TSS were obtained from the USCS Genome Browser.

Cis-regulatory elements are widely distributed throughout mammalian genomes. In

many cases however, these elements are present within the proximal promoter a few

hundred to a couple of thousand bases upstream of the TSS. A 1 kb window

upstream of the TSS should be sufficient to account for most of the cis-regulatory

elements occurring within proximal promoter regions.

The 1 kb sequence of of each gene was then analyzed using MATInspector‟s Matrix

Family Library (version 8.2) of transcription factor binding sites. The vertebrate group

of this library represents binding site descriptions of 5747 transcription factors. The

positions of the core sequences of the predicted binding sites relative to the TSS

were determined with the help of GeneRunner software. Computationally predicted

binding sites for SRF and FLI1 are shown in Figure 5-9.

Figure 5-9: Putative binding sites of SRF and FLI1 upstream of the TSS of candidate regions Schematic representation of architectures from SRF or FLI1 containing proximal promoter regions of indicated genes. Arrows mark the TSS, ovals and diamonds mark the respective motifs. Positions of binding sites relative to the TSS were determined computationally using MATInspector and GeneRunner software.

Results

51

55..77 WWeesstteerrnn bblloott AAnnaallyyssiiss ooff SSRRFF aanndd FFLLII11 PPrrootteeiinn

EExxpprreessssiioonn

Western blot analyses were performed in order to examine if protein levels of SRF

and FLI1 change in the process of monocyte differentiation in dependence on

adherence. Monocytes were cultured adherently on teflon foils. Teflon foils were

used in order to be able to harvest high numbers of cells and to count the cells for

loading equal numbers onto the SDS gel. Non-adherent macrophages were

generated using roller bottles and a continuously rotating turning device. In both

cases monocytes were cultured, over a period of 18 hours. Whole cell extracts were

prepared from freshly isolated monocytes (MN 0 h), as well as from adherent and

non-adherent macrophages at time points 4 h (Adh 4 h) and 18 h (Adh 18 h, NonAdh

18 h). As high numbers of cells were difficult to obtain after 4 h in culture, changes in

protein levels were focused on the 18 h time point. After separation by SDS-PAGE,

proteins were blotted onto a PVDF membrane. Membranes were probed using

specific antibodies against SRF and FLI1. Proteins were detected using a

horseradish-peroxidase (HRP)-coupled secondary antibody, which catalyses a

chemiluminescent reaction. The resulting chemiluminescence signal was detected on

an autoradiography film.

5.7.1 Analysis of FLI1 Protein Expression

FLI1 mRNA encodes two isoforms (51 kDa and 48 kDa), that are synthesized by

alternative translation initiation of the same FLI1 mRNA transcript (Truong and Ben-

David 2000). Protein levels of donor 2 were decreased in adherent macrophages at 4

h (Adh 4 h) of differentiation in comparison to freshly isolated monocytes (MN 0 h).

Although protein degradation cannot be excluded, protein levels of donor 2 were

consistent with the relative mRNA expression of FLI1 during monocyte differentiation.

However, protein levels were comparable at 0 h and 18 h of culture. Furthermore,

mRNA expression levels did not differ significantly between adherent and non-

adherent macrophages (Figure 5-10).

Results

52

Figure 5-10: Western blot analysis of FLI1 protein expression FLI1 protein levels from 2 independent donors are shown on top. Whole cell extracts were prepared from freshly isolated monocytes (MN 0 h) as well as from adherent (Adh) macrophages at time points 4 h (only one donor) and 18 h after seeding. Western blots were performed using a FLI1 specific antibody. Known FLI1 isoforms are indicated by size. ß-Actin antibody was used to asses for equal loading of samples. mRNA expression levels of the FLI1 gene obtained from whole genome analysis are shown below. mRNA expression levels of FLI1 were normalized to the median of its expression level across all samples.

5.7.2 Analysis of SRF Protein Expression

Alternative splicing of SRF generates at least four mRNA isoforms, the full-length

mRNA form (SRF-FL) comprising all seven exons, SRF-Δ5 lacking exon 5, SRF-Δ4,5

lacking exons 4 and 5 as well as SRF-Δ3,4,5 lacking exons 3,4 and 5. (Davis et al.

2002). On the protein level, expression of a 67 kDa and a 57 kDa SRF protein,

corresponding to SRF-FL and SRF-Δ5 respectively, were found in cell extracts of

divers human and mouse cell lines (Belaguli et al. 1999; Kemp and Metcalfe 2000).

The 67 kDa SRF protein (SRF-FL) was detected in lysates of human primary

keratinocytes (Koegel et al. 2009). Davis et al. demonstrated the translation of all four

mRNA transcripts in adult human cardiac myocytes with protein sizes about 67 kDa

(SRF-FL), 57 kDa (SRF-Δ5), 52 kDa (SRF-Δ4,5) and 40 kDa (SRF-Δ3,4,5)

respectively (Davis et al. 2002).

Results

53

In this study, Western blot analyses using a SRF specific antibody revealed

numerous protein bands including some bands that likely represent artifacts formed

during sample preparation or appearing as a result of protein degradation or

unspecific binding of the SRF antibody. However, bands with approximate sizes of 67

kDa, 57 kDa, 52 kDa and 40 kDa were detected, probably corresponding to the

isoforms SRF-FL, SRF-Δ5, SRF-Δ4,5 and SRF-Δ3,4,5. In general, SRF protein levels

were increased after 18 hours of monocyte to macrophage differentiation. All three

donors showed similar expression patterns of SRF, despite donor dependent

variations in protein levels. Interestingly, the full-length isoform of approximately 67

kDa was especially increased in whole cell extracts of adherent macrophages

(Figure 5-11). Figure 5-11 also displays that the relative expression of the SRF gene

does not correspond to the detected differences in SRF-FL protein levels between

adherent and non-adherent macrophages. SRF mRNA levels did not significantly

differ between adherent MAC + M-CSF and NonAdh MAC. These findings suggest

that adherence dependent mechanisms influence SRF expression, possibly resulting

in augmented stability of the 67 kDa isoform of the serum response factor in

adherently cultured macrophages.

Results

54

Figure 5-11: Western blot analysis of SRF protein expression SRF protein levels from 3 independent donors are shown on top. Whole cell extracts were prepared from freshly isolated monocytes (MN 0 h) as well as from non-adherent (NonAdh) and adherent (Adh) macrophages 18 h after seeding. Western blots were performed using a SRF specific antibody. Known SRF isoforms are indicated by size. Asterisk indicates a band of unknown size, which is possibly unspecific. ß-Actin antibody was used to asses for equal loading of samples. mRNA expression levels of the SRF gene obtained from whole genome analysis are shown below. mRNA expression levels of SRF were normalized to the median of its expression level across all samples.

Discussion

55

66 DDiissccuussssiioonn

66..11 AAddhheerreennccee--DDeeppeennddeenntt HHuummaann MMoonnooccyyttee ttoo

MMaaccrroopphhaaggee DDiiffffeerreennttiiaattiioonn

M-CSF and its receptor CSF-1R are important players in the process of monocyte to

macrophage differentiation. The binding of M-CSF to CSF-1R results in the

phosphorylation of specific tyrosine residues in the receptor‟s cytoplasmic domain

followed by the activation of multiple intracellular signal transduction pathways

(Pixley and Stanley 2004). By this means, M-CSF regulates monocyte survival and

differentiation of myeloid progenitor cells to monocytes and, ultimately, tissue

macrophages (Irvine et al. 2009). Most data supporting M-CSF as an essential

cytokine for monocyte to macrophage differentiation are based on the murine system

(Brugger et al. 1991; Pixley and Stanley 2004). However, in humans, the situation

might differ. As a result of preliminary work in our laboratory, it was demonstrated

that human monocytes differentiated independently of M-CSF when cultured under

adherent conditions (Pham et al. 2007). Thus, our group proposes that adherence is

sufficient for the survival and differentiation of human monoyctes.

Yet, several studies argue for a role of M-CSF in human monocyte to macrophage

differentiation, postulating that M-CSF is an important factor in the events leading to

macrophage differentiation. For instance, in vitro experiments demonstrated that

monocytes are able to produce autocrine M-CSF when they adhere to plastic

surfaces (Becker et al. 1987; Haskill et al. 1988). M-CSF was the only cytokine

produced by adherent monocytes and macrophages in the absence of any stimulus

(Scheibenbogen and Andreesen 1991). In addition, it was found that human

macrophages required the continuous presence of M-CSF in order to survive, and

that M-CSF itself induces the production of survival and differentiation factors

(Komuro et al. 2005). On the transcriptome level, Horiguchi and colleagues were first

to report the detection of M-CSF transcripts in human peripheral blood monocytes

(Horiguchi et al. 1986). Liu et al examined a high level expression of M-CSF during

early stages of human monocyte to macrophage differentiation, proposing that M-

CSF is capable of promoting macrophage differentiation (Liu et al. 2008).

Discussion

56

Taken together, these findings document M-CSF as an important factor for survival

and differentiation of human monocytes.

However, little is known about adherence-dependent monocyte to macrophage

differentiation which might also proceed independent of the actions of autocrine M-

CSF. To study the impact of adherence and M-CSF, respectively, freshly isolated

human peripheral blood monocytes were treated with DMSO, M-CSF and the CSF-

1R specific inhibitor GW2580 (Conway et al. 2005), and were cultured under

adherent conditions. In a parallel approach, non-adherent macrophages were

generated using roller bottles and a continuously rotating universal turning device.

Global mRNA expression analyses revealed a large number of significantly up- or

down-regulated genes in adherent macrophages while non-adherently cultured

macrophages displayed less changes in gene expression during the early culture

phase. Gene expression levels of non-adherent macrophages often converged to

expression levels of adherent macrophages in the course of differentiation,

suggesting a delayed regulation of gene expression in macrophages if cultured under

non-adherent conditions. Thus, loss of adherence might be responsible for the

delayed gene expression in non-adherent macrophages. In turn, adherence can be

suggested as a critical component maintaining monocyte survival and promoting

monocyte to macrophage differentiation.

GW2580 inhibits M-CSF mediated activation of signal transduction pathways by

blocking the receptor‟s kinase activity (Conway et al. 2005). Expression profiles

between adherent macrophages treated with M-CSF and adherent ones treated with

GW2580 showed little to no differences in mRNA expression levels, indicating that

adherence-dependent monocyte to macrophage differentiation probably proceeds

mainly independently of M-CSF.

Recently, IL-34, a previously undescribed ligand, was found to be an alternative

functional ligand for CSF-1R. IL-34 stimulates monocyte viability and promotes the

formation of the colony-forming unit-macrophage (CFU-M), a macrophage progenitor

(Lin et al. 2008). This means that other factors are able to bind to CSF-1R and

contribute to M-CSF-independent monocyte to macrophage differentiation. In turn, it

might be speculated that M-CSF also binds to other receptors, which have not been

considered yet, and mediate its effects on monocyte survival and differentiation

independently of CSF-1R. Thus, M-CSF might contribute to survival and

Discussion

57

differentiation in GW2580-treated monocytes. However, currently there is no

evidence for a CSF-1R independent role of M-CSF.

Taken together, these findings suggest that adhesion is not an absolute, but at least

a sufficient condition for monocyte survival and differentiation. Nevertheless, a minor

role of autocrine M-CSF in adherently differentiating macrophages can‟t be ruled out.

66..22 SSRRFF aanndd MMaaccrroopphhaaggee AAddhheerreennccee

Promoter motif analysis revealed the sequence motifs for class I ETS factors,

STAT/ISRE and SRF. Recent research revealed that the ETS-domain DNA-binding

specificities cluster into four major classes. The class I of ETS factors comprises 15

ETS transcription factors, for example, FLI1, GABPA, ETS1 and 2, ETV 1-4 and

ELK1 (Wei et al. 2010).

STAT1 and STAT2 are able to combine with the IRF-9 protein to form the

transcription factor ISGF-3, which binds to the ISRE, and induces transcription of

IFN-α-induced genes (ISGs) (Gerber and Pober 2008).

The only motif that was attributed to a single transcription factor was the consensus

binding site for SRF. This motif was significantly enriched in promoter sequences of

genes up-regulated after 4 h in M-CSF-treated adherent macrophages compared to

non-adherent macrophages.

SRF is a member of the MADS box family of transcription factors. The MADS box is a

highly conserved domain among eukaryotes and stands for MCM-1 from yeast,

Agamous and Deficiens from plants and SRF from animals. It comprises a DNA

binding domain, a dimerization domain and an interface for protein-protein

interactions (Figure 6-1). The transactivation domain is located in the C-terminal

region of SRF and contains several phosphorylation sites that signal the recruitment

of SRF-associated factors (Chai and Tarnawski 2002; Miano 2003).

Figure 6-1: Schematic representation of the MADS box (Iyer et al. 2006) Schematic representation of the MADS box functional regions. The αI-helix is involved in protein-DNA interaction. The αII-helix is involved in protein-protein interactions. Both β-sheets are involved in SRF dimerization.

Discussion

58

SRF is broadly expressed and regulates various target genes in brain, muscle and

other tissues (Wang et al. 2001). Known SRF target genes are characterized by the

presence of single or multiple copies of the SRF binding element (SRE). SREs are

specified by a CC(A/T)6GG core sequence, also known as the CArG-box. SRF binds

as a homodimer to CarG boxes (Figure 6-2) in the promoters of immediate-early

genes (IEGs) such as C-FOS, EGR-1 and EGR-2, neuronal genes such as NURR11

and NURR77, cytoskeletal genes such as ACTB and VCL, and several muscle-

specific genes (Miano 2003; Chai and Tarnawski 2002).

Figure 6-2: Schematic crystal structure of the SRF MADS box binding a CarG box

(Iyer et al. 2006) SRF binds as a homodimer. One SRF monomer is shown in blue, the other one in red.

By regulating expression of these genes, SRF controls cell growth and differentiation

as well as neuronal functions and muscle development. SRF itself contains two CarG

boxes in its promoter region and thus is a regulator of its own promoter activity (Davis

et al. 2002).

It is estimated that over half of all human genes are alternatively spliced (Kan et al.

2005). Several groups reported the generation of at least four SRF mRNA isoforms

by alternative splicing of the primary RNA transcript (Kemp and Metcalfe 2000; Davis

et al. 2002; Zhang et al. 2007). The human SRF gene encompasses seven exons

spanning about 11kb of DNA on chromosome 6p21 (Miano 2003). The full-length

mRNA form (SRF-FL) comprises all seven exons. SRF-Δ5 lacks exon 5, SRF-Δ4,5

lacks exons 4 and 5 while SRF-Δ3,4,5 lacks exons 3,4 and 5 (Davis et al. 2002). In

addition, it was shown that SRF mRNA isoforms are expressed in a tissue-specific

manner (Kemp and Metcalfe 2000). The balance of SRF isoform transcripts as well

as of the corresponding proteins plays an important role in the regulation of SRF

target genes, including SRF itself. It was demonstrated that SRF-Δ3,4,5 protein was

able to bind to SREs and repressed the SRF gene promoter (Zhang et al. 2007).

Discussion

59

Davis et al. observed a significant reduction in SRF-FL protein expression in parallel

with increased levels of the SRF-Δ4,5 isoform (Davis et al. 2002).

We showed that the full-length isoform of approximately 67 kDa was especially

increased in whole cell extracts of adherent macrophages. In view of the mentioned

findings, it could be speculated that SRF-Δ3,4,5 and SRF-Δ4,5 regulate expression

of full length SRF in an autocrine manner, resulting in less strongly SRF-FL

expression in non-adherently cultured macrophages compared to adherent

macrophages. However, this implicates an increase in SRF-Δ3,4,5 and SRF-Δ4,5

protein levels, which was not observed.

The ubiquitin-proteasome pathway plays an important role in the regulation of

proteins with a short half-life, such as the cyclins acting during the cell cycle or

transcription factors (Guinez et al. 2008). It has been speculated that proteins could

be protected against proteasomal degradation by O-linked N-acetylglucosaminylation

(O-GlcNAc) (Han and Kudlow 1997; Zhang et al. 2003) . Evidence exists that SRF is

a target of O-GlcNAc modification (Reason et al. 1992).

Adherence could be responsible for activating processes that lead to O-GlcNAc

modifications of SRF-FL protein resulting in its greater stability and protection against

proteasomal degradation.

Thus, according to these results, it may be speculated that adherence-dependent

mechanisms influence SRF-FL stability at the posttranscriptional or posttranslational

level.

The identification of the consensus SRF motif in adherence-induced genes in

macrophages prompted us to search for known SRF targets that were not induced in

non-adherent macrophages. Analysis of our microarray data revealed that adherent

macrophages show increased expression levels of EGR-1, EGR-2 and DUSP5 in the

course of monocyte to macrophage differentiation.

EGR-1 and EGR-2 are known SRF target genes (Chai and Tarnawski 2002). SRF

binding upstream of DUSP5 has been verified by Tullai and colleagues using ChIP

(Tullai et al. 2004). Thus, it was expected that the computational prediction for SRF

binding sites reveals one or more SREs upstream of the TSS of these genes.

EGR-1 is involved in cell growth, apoptosis and mitogenesis (Thiel and Cibelli 2002).

Moreover, it is speculated that EGR-1 may play an essential role in cell differentiation

along the monocyte lineage (Shafarenko et al. 2005). Kharbanda et al reported EGR-

2 up-regulation during macrophage differentiation (Kharbanda et al. 1991). Recently,

Discussion

60

transient DUSP5 induction at early stages of macrophage differentiation was

demonstrated (Grasset et al. 2010).

Taken into account that EGR-1, EGR-2 and DUSP5 are direct targets of SRF

containing SREs in their promoter regions (Chai and Tarnawski 2002; Tullai et al.

2004) and are associated with monocyte to macrophage differentiation (Shafarenko

et al. 2005; Kharbanda et al. 1991; Grasset et al. 2010), it can be suggested that

SRF dependent regulation of these genes plays an important role in adherence

dependent monocyte to macrophage differentiation.

In addition to EGR-1, EGR-2 and DUSP5, we chose CCL22 as a candidate gene that

is not reported to be targeted by SRF. CCL22 is known to be highly expressed in

mature macrophages (Fantuzzi et al. 2003). We could examine that the expression of

CCL22 increased continuously during the culture period. Our in silico analysis of SRF

binding sites within a 1 kb window upstream of the TSS revealed one putative SRE.

However, whether CCL22 is a direct or indirect target of SRF remains to be

elucidated.

Evidence exists that abnormalities in cell spreading, adhesion and migration are

related to SRF deficiencies. Recently, Koegel et al. demonstrated that keratinocytes

express the transcription factor SRF and that reduction of SRF expression in these

cells is responsible for adhesion defects. They examined that adherence of human

primary keratinocytes to the culture dish was significantly reduced in cells treated

with siRNA against SRF (Koegel et al. 2009). Thus, they reasoned that impaired cell

spreading and adhesion defects in SRF siRNA treated primary keratinocytes were a

direct consequence of the loss of SRF.

These findings are consistent with the previously described role of SRF in the

organization of focal adhesion assembly in embryonic stem (ES) cells (Schratt et al.

2002). SRF-deficient ES cells displayed a significantly reduced expression of a

variety of focal adhesion (FA) proteins, for example ß1-Integrin, Talin and Vinculin

(Schratt et al. 2002). FA proteins are large, dynamic protein complexes that function

as signal transducers, which inform the cell about the condition of the ECM, thus

affecting cell behavior. Together with integrins, FAs link the ECM to the actin

cytoskeleton (Chen 2003; Rivera et al. 1993). Therefore it was suggested that their

reduced expression in SRF-deficient ES cells might be responsible for impairments in

spreading, substrate adhesion, and cell migration (Schratt et al. 2002).

Discussion

61

Cell-cell and cell-substrate interactions are viewed as important events influencing a

broad range of cellular characteristics and are supposed to have an impact on the

differentiation of monocytes (Shi and Simon 2006; Shi et al. 2008). Considering SRF

dependent adhesion defects in primary keratinocytes (Koegel et al. 2009) and

reduced expression of FA proteins in SRF-deficient ES cells (Schratt et al. 2002), our

studies suggest SRF as a transcription factor that may play an important role in the

course of adherence-dependent monocyte to macrophage differentiation.

Signaling molecules, for example cytokines, growth factors or ECM components, are

able to activate signal transduction pathways resulting in the modification of

regulatory molecules, such as transcription factors, which in turn induce or repress

the transcription of certain genes.

SRF target genes can be regulated by the interaction of SRF with other transcription

factors. SRF accessory factors comprise the ternary complex factors (TCFs), which

belong to the Ets family of transcription factors. TCFs include the proteins Elk-1, Sap-

1 as well as Net. TCFs act through their binding to ETS motifs adjoining the CarG

boxes of some IEGs. In combination with TCFs, SRF controls proliferation and

apoptotic regulation (Muehlich et al. 2008). SRF-containing transcription factor

complexes are targets of multiple intracellular cascades including cascades of the

MAP kinase network and Rho-dependent signaling (Alberti et al. 2005). TCF-

dependent SRF mediated transcriptional activation involves the Ras/Raf/MEK/ERK

pathway. Activation of this pathway by extracellular stimuli results in the

phosphorylation of a TCF followed by its binding to an ETS motif adjacent to a SRE,

ultimately regulating gene expression by the interaction of TCF with SRF (Chai and

Tarnawski 2002). Other MAP kinases like JNK and p38/RK can be activated through

small GTPases such as Rac and Cdc42 and phosphorylate TCFs (Wasylyk et al.

1998).

The activation of pathways involving the MAP kinases ERK, p38 and JNK,

respectively, can be triggered through integrin engagement caused by monocyte

adhesion (Mondal et al. 2000). Elk-1 is a member of the class I ETS transcription

factors (Wei et al. 2010), and our promoter motif analysis delivered the consensus

binding site of class I ETS factors. Thus, phosphorylation of TCFs through ERK, p38

or JNK might be induced by monocyte adhesion subsequently leading to the

activation of transcription via TCF containing SRF transcription factor complexes.

Discussion

62

66..33 OOuuttllooookk

This study indicates that the transcription factor SRF may play a role during

adherence-dependent monocyte to macrophage differentiation.

However, the functional relevance of these findings remains to be demonstrated. A

first approach may be to identify SRF targets by chromatin immunoprecipitation

(ChIP). ChIP is a method to determine the binding of a certain protein to a specific

DNA sequence. ChIP-sequencing may allow the identification of global binding sites

for SRF. Another way to study the function of SRF may be the knockdown of its

expression in monocytes by siRNAs to analyze the impact of SRF deficiency on

adherence-dependent monocyte to macrophage differentiation.

In addition, a possible role of TCFs in the regulation of SRF dependent gene

expression could be indicated by eletromobility shift assays.

Summary

63

77 SSuummmmaarryy

Signaling molecules like cytokines, growth factors or ECM components are able to

activate signal transduction pathways resulting in the modification of regulatory

molecules, such as transcription factors, and thus modulate cell behavior. The

cytokine M-CSF mediates its effects through CSF-1R and is known to be important

for monocytic survival and differentiation. However, preliminary work in our laboratory

demonstrated that human monocytes differentiated independently of M-CSF when

cultured under adherent conditions. Therefore our group proposes that adherence is

sufficient for the survival and differentiation of human monoyctes.

The aim of this study was to elucidate the effects of M-CSF and adherence on the

differentiation of human peripheral blood monocytes to macrophages in detail.

Adherent and non-adherent monocytes were cultured over a time window of seven

days. Global mRNA expression analyses of differently treated adherent

macrophages and non-adherent macrophages suggest a delayed regulation of gene

expression in macrophages if cultured under non-adherent conditions. Expression

profiles between adherent macrophages treated with M-CSF and adherent ones

treated with GW2580 showed little to no differences in mRNA expression levels.

These findings support the idea that adherence-dependent monocyte to macrophage

differentiation proceeds mainly independently of M-CSF. A de novo motif search

algorithm in target gene promoters delivered the sequence motif for the transcription

factor SRF. Western blot analysis with an SRF specific antibody showed that the full-

length isoform of approximately 67 kDa was especially increased in whole cell

extracts of adherent macrophages. Microarray data analysis revealed that adherent

macrophages show increased expression levels of known SRF target genes in the

course of monocyte to macrophage differentiation.

Taken together, our studies suggest SRF as a transcription factor that may play an

important role in the course of adherence-dependent monocyte to macrophage

differentiation.

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Abbreviations

70

AAbbbbrreevviiaattiioonnss

ANOVA Analysis of variance

APS ammonium persulfate

BSA bovine serum albumin

BSS balanced salt solution

C/EBP CCAAT enhancer-binding protein

CFU-M colony-forming unit-macrophage

ChIP chromatin immunoprecipitation

CLP common lymphoid progenitor

CMP common myeloid progenitor

CSF-1R macrophage colony stimulating factor receptor

DEPC diethylpyrocarbonate

DMSO dimethyl sulfoxide

DTT dithiothreitol

ECM extracellular matrix

EGR-2 early growth response protein 2

ERK extracellular signal-regulated kinase

ES cell embryonic stem cell

FA focal adhesion

Foxp1 forkhead box P1

GM-CSF granulocyte-monocyte colony-stimulating factor

GMP granulocyte-monocyte precursor

GW2580 5-(3-methoxy-4-((4-methoxybenzyl)oxy)benzyl)pyrimidine-2,4-

diamine

HMDM human monocyte-derived macrophages

HOMER hypergeometric optimization of motif enrichment

HRP horseradish-peroxidase

HSC hematopoietic stem cell

IEG immediate-early gene

IFNγ interferon-γ

IL interleukin

IRF-8/ICSBP interferon regulatory factor 8/interferon consensus sequence-

binding protein

ISGF3 Interferon stimulated gene factor 3

ISRE interferon stimulated response element

JNK c-Jun N-terminal kinase

kb kilo bases

kDa kilo dalton

LPS lypopolysaccharide

MAC macrophage

MAPK mitogen-activated protein kinase

M-CSF macrophage colony stimulating factor

Abbreviations

71

MN monocyte

MOPS 3-(N-morpholino)propanesulfonic acid

MPS mononuclear phagocyte system

NK natural killer cells

O-GlcNAc O-linked N-acetylglucosaminylation

PB-MNC peripheral blood mononuclear cell

PBS phosphate buffered saline

PCR polymerase chain reaction

PI3K phosphatidylinositol-3 kinase

PVDF polyvinylidene

RES reticuloendothelial system

RT reverse transcription

RUNX1 runt-related transcription factor 1

SDS-PAGE sodium-dodecyl-sulfate-polyacrylamide-gel-electrophoresis

siRNA small interfering RNA

SRE SRF binding element

SRF serum response factor

ß-ME ß-mercaptoethanol

TBS tris buffered saline

TCF ternary complex factor

TEMED tetramethylethylenediamine

Th1 T helper 1 cell

Th2 T helper 2 cell

TNF tumor necrosis factor

TP trypan blue

Tris tris(hydroxymethyl)aminomethane

TSS transcription start site

Danksagungen

72

DDaannkkssaagguunnggeenn

Ich möchte mich bei Herrn Prof. Dr. Reinhard Andreesen für seine großzügige Unterstützung

und die Ermöglichung dieser Diplomarbeit herzlich bedanken.

Desweiteren gilt mein Dank Prof. Dr. Gernot Längst für die Bereitschaft, diese Arbeit als

Erstgutachter zu betreuen.

Ich möchte mich insbesondere auch bei Prof. Dr. Michael Rehli für die interessante

Themenstellung sowie Betreuung meiner Arbeit bedanken. Ich habe mich vom ersten

Moment an sehr wohl in seiner Arbeitsgruppe gefühlt. Seine Ruhe, Geduld sowie

Anregungen und Ratschläge haben mir bei der Fertigstellung dieser Arbeit stets

weitergeholfen und mir neue Einblicke in die Thematik ermöglicht.

Ein besonderes Dankeschön gilt Hang, die mir alle Methoden beigebracht hat, mit Rat und

Tat zur Stelle war und immer ein offenes Ohr für meine Fragen hatte. Mit ihrer Erfahrung hat

sie mir so über manche Tücken des Laboralltags hinweggeholfen.

Hang, thank you very much.

Ebenso möchte ich allen noch nicht erwähnten im Team der AG Rehli sowie auch der

gesamten AG Kreutz und allen, die sich sonst noch im Carrerasbau tummeln, für ihre Hilfe

und Unterstützung, auflockernden Gespräche und gemeinsames Lammentieren falls mal

wieder etwas nicht funktioniert hat, und die gemeinsamen Aktivitäten und Unternehmungen

jenseits des Laboralltags danken.

Im Einzelnen geht mein Dank an…

Lucia für ihre Unterstützung und Hilfe im Umgang mit der Zellkultur;

Maja und Chris für die Ratschläge beim zu Papier bringen dieser Arbeit;

Julia für unterhaltsame Diskussionen sowie gute und hilfreiche Tipps;

Dagmar, Claudia und Ireen für die angenehme Atmosphäre und guten Zuspruch;

Kaste für die gemeinsamen Männerabende mit Eddy;

Alice, Gabi, Katrin, Monika, Bernadette, Sabine, Isabell, Julia, Martina und Sandra für die

nette Gesellschaft im Büro und den Labors des Carrerasbau.

Schließlich möchte ich mich bei meiner Familie bedanken, die stets an mich geglaubt hat

und immer für mich da ist. Ohne ihre Unterstützung hätte ich es nie so weit gebracht.

Eidesstaatliche Erklärung

73

EEiiddeessssttaaaattlliicchhee EErrkklläärruunngg

Hiermit erkläre ich, dass ich die am heutigen Tag eingereichte Arbeit selbstständig

verfasst und ausschließlich die angegebenen Quellen und Hilfsmittel verwendet

habe.

Regensburg, den ……………………. ………………………………………….

Thomas Gross

effects of m-csf and adherence on human monocyte - ag-rehli.de

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