Investigating Caveolin-Dependent Glucocorticoid Action in Inflammation

Investigating caveolin-dependent glucocorticoid action in inflammation

A thesis submitted to the University of Manchester for the degree of M.Phil in the Faculty of Medicine and Human Sciences

2013

Anna Louise Mary Mannion-Jones

School of Medicine

Contents

I. TABLES AND FIGURES ...... 7

II. Abstract ...... 10

III. Declaration ...... 10

IV. Notice of Copyright...... 11

1 Introduction ...... 18

1.1 Inflammation ...... 18

1.1.1 The cellular inflammatory response ...... 18

1.1.2 Innate vs. adaptive immunity ...... 19

1.1.3 Chronic inflammation ...... 20

1.1.4 Autoimmune disease...... 20

1.1.5 Anti-inflammatory actions of glucocorticoids ...... 22

1.1.6 The development of synthetic glucocorticoids ...... 22

1.1.7 Side effects of glucocorticoid treatment ...... 23

1.2 The glucocorticoid receptor ...... 24

1.2.1 The structure of the glucocorticoid receptor ...... 25

1.2.2 The N-terminal domain of the glucocorticoid receptor ...... 25

1.2.3 The DNA-binding domain of the glucocorticoid receptor ...... 25

1.2.4 The ligand binding domain of the glucocorticoid receptor ...... 25

1.2.5 Post-translational modifications of the glucocorticoid receptor ...... 26

1.2.6 Glucocorticoid receptor isoforms ...... 26

1.2.7 Alternative translation start sites generates glucocorticoid receptor subtypes 27

1.3 Glucocorticoid receptor effects: Genomic signalling ...... 30

1.3.1 GR binding to DNA ...... 30

1.3.2 GR tethering to other DNA bound transcription factors...... 32

1.4 Glucocorticoid receptor effects: Non-genomic signalling ...... 34

1.4.1 The stress response ...... 34

1.4.2 Mechanisms of non-genomic signalling ...... 35

1.5 Cross talk with other signalling pathways and the relationship between genomic and non-genomic signalling mechanisms ...... 40

1.5.1 Post-translational modifications of proteins in signalling: Phosphorylation . 42

1.5.2 Other inhibitors of NF-κB inflammatory signalling ...... 43

1.6 Caveolin and caveolae ...... 43

1.6.1 Caveolin knockout mice ...... 46

1.6.2 Caveolin, NF-κB and pulmonary inflammation and fibrosis ...... 47

1.6.3 Caveolin and inflammatory pathways ...... 49

1.6.4 GR association with caveolin ...... 50

1.7 Project Outline ...... 53

1.7.1 Hypothesis ...... 54

1.7.2 Aim ...... 54

1.1.1 Major techniques to be used to investigate aims ...... 55

2 Materials and Methods ...... 59

2.1 Mammalian cell culture ...... 59

2.1.1 Cell maintenance ...... 59

2.1.2 Cryoprocessing ...... 59

2.1.3 Plating cells for experiments ...... 59

2.1.4 Treatment with Dexamethasone ...... 60

2.2 Animal housing ...... 61

2.2.1 In vivo Experimental design ...... 61

2.2.2 Animal treatment ...... 61

2.3 Plasmid preparation ...... 62

2.3.1 Miniprep ...... 63

2.3.2 Restriction Digest ...... 63

2.3.3 Maxiprep ...... 63

2.4 Transfections ...... 64

2.4.1 Plasmid transfection...... 64

2.4.2 Transfection of siRNA against Caveolin ...... 64

2.5 Western blot ...... 64

2.5.1 Extracting protein from Cells ...... 64

2.5.2 Extracting protein from fresh tissues ...... 65

2.5.3 Extracting protein from snap-frozen tissues ...... 66

2.5.4 SDS Gel Electrophoresis and transfer of proteins to membrane ...... 66

2.5.5 Protein labelling with antibodies ...... 67

2.6 Antibodies used for protein detection in Western blot and Immunofluorescence 67

2.7 Real Time Quantitative Polymerase Chain Reaction (RT-QPCR) ...... 68

2.7.1 RNA extraction from cells ...... 68

2.7.2 RNA extraction from lung tissue ...... 69

2.7.3 Setting up the Real-Time qPCR reaction ...... 70

2.7.4 Real-Time qPCR reaction Thermal Cycler ...... 70

2.7.5 Analysis of QPCR results by ΔΔCT ...... 70

2.7.6 Primer design and validation ...... 71

2.7.7 Sequences of primers used in QPCR ...... 72

2.8 Genotyping ...... 72

2.9 Live cell microscopy ...... 74

2.9.1 Analysis of GR translocation in Live Cell experiment ...... 74

2.10 Immunofluorescence in Cells ...... 74

2.10.1 Cell fixing and permeabilization ...... 74

2.10.2 Antibody labelling ...... 75

2.10.3 Imaging Immunofluorescence ...... 75

2.10.4 Phalloidin Actin stain with fluorescent FITC dexamethasone ...... 75

2.11 Immunohistochemistry in tissues ...... 77

2.11.1 FFPE (formalin fixed paraffin embedded) Tissue processing...... 77

2.11.2 Antibody labelling of tissue sections, Immunofluorescence ...... 77

2.11.3 Nuclei counterstaining ...... 78

2.11.4 Quenching of autofluorescence using UV and Sudan Black B ...... 78

2.11.5 Visualising fluorescent antibody labelling in tissues ...... 78

2.12 Bronchoalveolar lavage ...... 79

2.13 Serum Corticosterone ELISA ...... 79

2.14 Histochemistry ...... 80

2.14.1 Leishman’s Stain of CytoSpins ...... 80

2.14.2 Histochemical staining with Haematoxylin and Eosin ...... 80

2.15 Statistics...... 81

3 Results ...... 82

3.1 Verification of previous findings and Experimental optimisation of procedures to investigate GR and caveolin interaction ...... 84

3.1.1 Verification of GR signalling in A549, Matthews et al. (2008) ...... 84

3.1.2 Experimental optimisation of procedures to investigate GR and caveolin interaction ...... 85

3.1.3 Optimisation of antibodies to caveolin ...... 86

3.1.4 Transfection optimisation ...... 88

3.1.5 Caveolin-1 knockdown with siRNA ...... 90

3.1.6 Optimising Immunofluorescence to visualise Caveolin and GR in fixed Cav-1 KO and WT MEFs ...... 92

3.1.7 Quenching of autofluorescence using infrared radiation and Sudan Black B staining 97

3.2 Characterisation of Cav-1 KO and Wild Type MEF response to Glucocorticoid treatment in vitro, and Lipid raft disruption in live cell ...... 105

3.2.1 Western Blots of signalling proteins ...... 105

3.2.2 Real-time Quantitative PCR (RT-qPCR) analysis of responses to dexamethasone in vitro ...... 110

3.2.3 Live cell experiments, altering membrane fluidity and its effect on glucocorticoid receptor translocation ...... 120 5

3.3 Immunohistochemistry, visualisation of GR and Caveolin ...... 121

3.3.1 Phalloidin actin stain with fluorescent-labelled dexamethasone treatment 121

3.3.2 Immunofluorescence – dual labelling of GR and caveolin ...... 123

3.4 In vivo experiment to characterise inflammatory responses in Caveolin-1 knockout mice ...... 128

3.4.1 Genotyping ...... 128

3.4.2 Western blot ...... 128

3.4.3 Real-Time Quantitative PCR of mouse lung...... 136

3.4.4 Enzyme-linked immunosorbent assay for serum Corticosterone levels ..... 145

3.4.5 Haematoxylin and Eosin stained lung tissue sections ...... 147

4 Discussion ...... 155

4.1 In vitro characterisation of Caveolin-1 knockout MEFs, developing a robust cell model to study GR and Caveolin interactions and GR target genes reliant on Caveolin 155

4.1.1 Changes in the phosphorylation of signalling proteins in response to glucocorticoids and in the presence and absence of Caveolin ...... 156

4.1.2 Real-time quantitative PCR to establish which genes are reliant on caveolin for GR regulation ...... 158

4.1.3 Altering membrane fluidity to investigate the translocation rate of GR .... 162

4.1.4 Limitations of experimental conditions involving transfection ...... 164

4.2 In vitro to in vivo determination of Glucocorticoid Receptor and Caveolin pattering in cells and tissues ...... 166

4.2.1 Determining caveolin isoform expression patterns ...... 166

4.2.2 Determining caveolin and GR patterning in fixed MEF cells, relation to cell polarity and migration ...... 167

4.2.3 Quenching of autofluorescence in lung and liver tissue ...... 168

4.2.4 Dual-labelling of Caveolin-1 and GR in the lung in vivo ...... 168

4.3 Investigating how caveolin affects the anti-inflammatory effects of glucocorticoids in the lung using knockout mice...... 169

4.3.1 Changes in circulating corticosterone levels in vivo ...... 169 6

4.3.2 CavKO mice had higher levels of infiltrating immune cells in the airways, than WT 170

4.3.3 Phosphorylated protein changes between wild type and Cav KO lung...... 170

4.3.4 Sex differences in response to glucocorticoids and to LPS ...... 172

4.3.5 Structural differences between CavKO and WT lung ...... 172

4.4 Conclusion ...... 173

5 References ...... 175

WORD COUNT : 49,633

I. TABLES AND FIGURES Table 1- Abbreviations ...... 12 Table 2 - Antibodies ...... 68 Table 3 - Primer sequences ...... 72 Table 4 - Automated sequence of baths for rehydration of tissues for paraffin embedding 77

Figure 1-1 Major signalling pathways in T-cell activation ...... 21 Figure 1-2 Structure of the glucocorticoid receptor ...... 29 Figure 1-3 Glucocorticoid action as a transcription factor ...... 31 Figure 1-4 Signalling sequence in glucocorticoid-induced T cell apoptosis ...... 41 Figure 1-5 Structure of caveolae and lipid raft ...... 45 Figure 2-1 Experimental design for cell culture ...... 60 Figure 2-2 Experimental design for in vivo LPS challenge ...... 62 Figure 3-1 Glucocorticoid response in A549 cells ...... 84 Figure 3-2 Caveolin antibodies raised in goat, comparison in MEFs ...... 86 Figure 3-3 Caveolin antibodies, tissue comparison ...... 87 Figure 3-4 Comparison of hCav1 and Cav myc RFP transfection ...... 88 Figure 3-5 Transfection time course...... 89 Figure 3-6 siRNA against caveolin1 in A549 and MEFs ...... 90 Figure 3-7 Immunofluorescence in fixed cells, hCav1 transfection, antibodies to GR (GR8E9) and Cav1 (sc7875 sc894)...... 92 Figure 3-8 Immunofluorescence fixed cells, transfection of Cav myc RFP ...... 94 Figure 3-9 Immunofluorescence fixed cells, Cav1 (goat ab) and M20 GR ...... 96 7

Figure 3-10 Autofluorescence in mouse lung ...... 98 Figure 3-11 Quenching of Autofluorescence in mouse lung ...... 99 Figure 3-12 Quenching autofluorescence in mouse liver ...... 101 Figure 3-13 Comparison of autofluorescence quenching across different spectra ...... 103 Figure 3-14 Western blot for signalling protein phosphorylation, 10 min dexamethasone105 Figure 3-15 Confirmation of caveolin transfection ...... 106 Figure 3-16 Dexamethasone time course, immunoblot for GR phosphorylation ...... 108 Figure 3-17 Caveolin transfection confirmation for dexamethasone time course ...... 109 Figure 3-18 RT-QPCR GILZ expression ...... 110 Figure 3-19 RT-QPCR Zfand5 expression ...... 111 Figure 3-20 RT-QPCR Ptchd1 expression ...... 112 Figure 3-21 RT-QPCR MT1 expression ...... 113 Figure 3-22 RT-QPCR Stc1 expression ...... 114 Figure 3-23 RT-QPCR Cdh11 expression ...... 115 Figure 3-24 RT-QPCR Runx1t1 expression ...... 116 Figure 3-25 RT-QPCR Glul expression...... 117 Figure 3-26 RT-QPCR RpS6 expression ...... 118 Figure 3-27 Caveolin transfection confirmation for RT-QPCR ...... 119 Figure 3-28 Live cell GR translocation with disruption of lipid rafts ...... 120 Figure 3-29 Fluorescent Phalloidin actin stain and GR translocation in A549 cells ...... 122 Figure 3-30 Control sections, single antibody incubations ...... 123 Figure 3-31 Fluorescent caveolin labelling in lung ...... 124 Figure 3-32 GR labelling with Far-Red ...... 125 Figure 3-33 Colocalisation of GR and caveolin in the lung ...... 126 Figure 3-34 Genotyping ...... 128 Figure 3-35 Western blot 1, lung, Caveolin and GR ...... 129 Figure 3-36 Western blot 2, lung, p65-NFκB, phospho-NFκB, PKB/Akt and pAkt ...... 131 Figure 3-37 Western blot 3, lung, SAPK/JNK ...... 133 Figure 3-38 Western blot 4, lung, IRAK1 and Pin1 ...... 135 Figure 3-39 RT-QPCR lung GILZ expression ...... 137 Figure 3-40 RT-QPCR lung MT1 expression ...... 139 Figure 3-41 RT-QPCR lung IL-6 expression ...... 141 Figure 3-42 RT-QPCR lung CXCL1/KC expression ...... 143 Figure 3-43 ELISA for serum [CORT] ...... 145 Figure 3-44 H&E lung WT and CavKO Saline...... 147

Figure 3-45 H&E WT lung LPS ...... 148 Figure 3-46 H&E CavKO lung LPS ...... 149 Figure 3-47 H&E CavKO and WT, LPS and Dex ...... 150 Figure 3-48 Immune cells in WT lung with LPS ...... 152 Figure 3-49 Immune cells in CavKO with LPS ...... 153 Figure 3-50 H&E Lung structural comparison WT CavKO ...... 154 Figure 4-1 Immune cells in BAL fluid ...... 170

II. Abstract The University of Manchester Anna Louise Mary Mannion-Jones Degree: MPhil “Investigating caveolin-dependent glucocorticoid action in inflammation” 2013

Glucocorticoids (GC) are steroid hormones that play important physiological roles in a variety of contexts, most notably effects on metabolism and the immune system. By virtue of their potent anti-inflammatory properties, synthetic GC are in wide clinical use and remain the gold standard for treatment of inflammatory diseases including rheumatoid arthritis and asthma. However, their long term use is hindered by the development of severe side effects, including osteoporosis. Understanding how GC mediate this spectrum of effects in vivo, and identifying new points for regulation is important for rational drug design. GC mediate their cellular effects through binding and activating the glucocorticoid receptor (GR). Once activated GR mediates non- genomic (over minutes) and genomic (over hours) effects. The gene regulatory effects of GC have been widely documented in different tissues and inflammatory states, but the mechanism by which GR brings about non genomic effects are less well understood. The interaction of GR with a plasma membrane protein and regulator of kinase signalling, caveolin-1 has been identified. Caveolin is an integral membrane protein that localises to specialised lipid rafts, caveolae, acting as a protein scaffold for signalling complexes.

Caveolin may be important to tether GR at the plasma membrane and facilitate non- genomic GC actions. Here, GR-caveolin interaction was investigated in vitro using an immortalised caveolin deficient cell line and then the effect was examined in vivo using a model of pulmonary inflammation using caveolin-1 knockout mice. Although subcellular GR trafficking appeared not to be altered, there were differences in GC induced kinases and transcriptional targets in the absence of caveolin. For example, phosphorylation of p65-NF-κB was 8.4-fold lower than the change seen in WT LPS-exposed mice. MT1 showed a 10-fold increase in expression with dexamethasone in CavKO, compared to 5-fold in WT in vitro, and in vivo WT showed a greater increase in expression 16-fold over control, whereas CavKO showed a 5.8-increase over control in lung tissue. The caveolin-dependent differences in glucocorticoid targets MT1, GILZ and Glul and kinase signalling pathways may have an effect on the modulation of glucocorticoid signalling.

III. Declaration

I declare that no portion of the work referred to in the thesis has been submitted in support of an application for another degree or qualification of this or any other university or other institute of learning

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Table 1- Abbreviations

Abbreviation Explanation µg microgram µl microlitre µM micromolar A549 Adenocarcinoma human alveolar basal epithelial cell line AA Arachidonic acid ab antibody AC Adenylate cyclase ACh Acetylcholine ACTH Adrenocorticotrophic hormone AF Activation function (1 and 2), transactivation domain aka also known as Akt Signalling protein also known as PKB 2-amino-3-(5-methyl-3-oxo-1,2- oxazol-4-yl)propanoic acid, a specific agonist for AMPA glutamate AMPA receptors AP-1 Activator protein-1, transcription factor composed of Jun and Fos proteins Arg Arginine, an important amino acid, precursor to nitric oxide ATF Activating transcription factor Adenosine triphosphate, transports energy within cells, substrate for kinases and adenylate ATP cyclase AUG Start codon in protein translation, codes for methionine amino acid Ave. Mean average B cell Lymphocyte, a type of white blood cell, that mature in bone marrow BAL Bronchoalveolar lavage In PKC-induced Bcl-2 apoptosis, forms pores in the mitochondrial membrane and leads to Bax cytochrome c release Bcl-2 B-cell lymphoma 2, family of proteins that regulate apoptosis BID BH3 interacting-domain death agonist, in PKC-induced Bcl-2 apoptosis interacts with Bax Bim Bcl-2-like protein 11 BSA Bovine serum albumin C/EBP Ccaat-enhancer-binding protein, family of transcription factors CA1 neuron Subset of neurons from the hippocampus Ca2+ Calcium ion Cyclic AMP, 3'-5'-cyclic adenosine monophosphate, an intracellular messenger produced from ATP cAMP by adenlyl cyclase activation Cav Caveolin, with subtypes Cav-1, -2 and -3 Cav KO Caveolin knockout, Cav-1-/-, no expression of caveolin-1 at the cell membrane Cav myc RFP RFP-conjugated Caveolin Cav-1 Caveolin 1 protein (22kDa) CB Cannabinoid, receptor class CBP CREB-binding protein, transcription coactivator CCL5 Chemokine (C-C motif) ligand 5, aka RANTES CD14 A pattern recognition receptor, detects LPS Cdh11 Cadherin 11 Cdk Cyclin-dependent kinase cDNA Complementary DNA, single stranded, reverse transcribed from mRNA cGR Cytosolic glucocorticoid receptor, the classical GR

CHF Congestive heart failure Chol Cholesterol Cl- Chloride ion CNS Central nervous system, the brain and spinal cord

CO2 Carbon dioxide COX-2 Cyclooxygenase-2 CREB cAMP response element-binding protein, transcription factor CRH Corticotrophin releasing hormone CSS Charcoal stripped FCS, delipidated C-terminal Carboxyl-terminus of a protein or polypeptide CXCL1/KC Chemokine (C-X-C motif) ligand 1 or KC DAG Diacyl-glycerol, a signalling molecule in PKC activation DAMPs Damage-associated molecular patterns 4',6-diamidino-2-phenylindole, fluorescent nuclear stain, also the corresponding frequency DAPI channel for excitation and emission spectra on the fluorescent microscope DBD DNA-binding domain delta delta CT Comparative value in RT-qPCR for change in gene expression relative to housekeeping gene Dex Dexamethasone Dex:BSA Dexamethasome conjugated to bovine serum albumin (membrane impermeable) dH2O Distilled water DMEM Dulbecco's Modified Eagles Medium, for cell culture DMSO Dimethyl sulphoxide, solvent DNA Deoxyribonucleic acid DNase Enzymes which digest DNA dNTP Deoxyribonucleotide triphosphate, used in PCR as subtrate to expand genetic material DTT Dithiothreitol, reducing agent EC Extracellular ECL Electrochemiluminescence ECM Extracellular matrix Ethylenediaminetetraacetic acid, chelating agent, sequesters and limits the activity of metal ions EDTA in solution ELISA Enzyme linked immunosorbent assay eNOS Endothelial nitric oxide synthase ER Estrogen receptor ERK Extracellular signal regulated kinase, a MAPK EtOH Ethanol FADD Fas-associated death domain Fas Fas signalling leads to apoptosis, on binding of Fas ligand (related to TNF) to Fas receptor FCS Foetal calf serum, supports cell growth and proliferation in culture FFPE Formalin fixed paraffin embedded Fluoroscein isothiocyanate, amine-binding derivative of fluoroscein fluorescent compound, also the corresponding frequency channel for excitation and emission spectra on the fluorescent FITC microscope FKBP52 FK506-binding protein 52, a chaperone Fos FBJ (Finkel–Biskis–Jinkins) murine osteosarcoma viral oncogene homologue g gram G1/S transition In cell cycling and cell division, G1 is growth phase and S phase is DNA replication

GC Glucocorticoid GILZ Glucocorticoid-induced leucine zipper Glul Glutamate-ammonia ligase, glutamate synthetase GPCR G-protein coupled receptor G-protein Guanine nucleotide binding protein GR Glucocorticoid receptor GR8E9 Glucocorticoid receptor antibody (8E9) GRE Glucocorticoid response element Gs A G-protein GSK-3β Glycogen synthase kinase-3B, phosphorylates and inactivates glycogen synthase h hour H&E Haematoxylin and Eosin H+ Proton hCav1 human caveolin 1, vector of this protein for transfection HDAC Histone deacetylase Hedgehog, signalling pathway. Involved in embryonic development and adult stem cell Hh proliferation, such as haematopoetic cells HPA axis Hypothalamic-pituitary-adrenal axis HRP Horseradish peroxidase hsp Heat shock protein IC Intracellular ICAM Intercellular adhesion molecule IFNγ Interferon gamma IGEPAL Octylphenoxypolyethoxyethanol, non-ionic non-denaturing detergent IGF Insulin-like growth factor IGFBP Insulin-like growth factor binding protein IHC Immunohistochemistry IKK Inhibitor of kappa B kinase, IκK IL Interleukin, a group of cytokines IL1-R1 Interleukin 1 receptor 1 iNOS Inducible nitric oxide synthase

IP3 Inositol-1,4,5-trisphosphate

IP3R Inositol-trisphosphate receptor (calcium channel) IPF Idiopathic pulmonary fibrosis IRAK Interleukin-1 receptor associated kinase IκB Inhibitor of kappa B in NF-κB signalling JAK Janus kinase JNK c-Jun N-terminal kinase kDa Kilo dalton, unit of molecular mass KO Knockout l litre LB Luria-Bertani broth and agar, nutritionally rich bacterial growth medium LBD Ligand-binding domain Lck Lymphocyte-specific protein tyrosine kinase, a Src kinase LDS Lithium dodecyl sulphate, reducing agent detergent and surfactant LPS Bacterial lipopolysaccharide Lys Lysine, an amino acid, site for post-translational modification of proteins 14

M Molar, concentration M20 GR Glucocorticoid receptor antibody (M20) MAPK Mitogen-activated protein kinase MEF Mouse embryonic fibroblast mESPC Miniature excitatory post-synaptic current Met Methionine, an amino acid, also start codon for protein transcription mg milligram mGR Membrane-associated glucocorticoid receptor MHC Major histocompatability complex min minute MK MAPK-activated protein kinase MKK MAP kinase kinase or MEK or MAP2K MKKK MAP kinase kinase kinase or MEKK or MAP3K MKP-1 MAPK phosphatase-1 ml millilitre mM millimolar MMP Matrix metalloproteinase MR Mineralocorticoid receptor Messenger RNA, single stranded, conveys genetic code from DNA to translation at the ribosome mRNA into amino acid sequence MS Multiple sclerosis MT Metallothionein Mammalian target of rapamycin, serine/threonine protein kinase involved in regulation of cell mTOR growth, proliferation, motility etc. myc a transcription factor, e.g. in MAPK signalling MyD88 Myeloid differentiation factor 88 MβCD Methyl-β-cyclodextrin nAChR Nicotinic acetylcholine receptor NFAT Nuclear factor of activated T-cells NF-κB Nuclear factor kappa-light-chain-enhancer of activated B cells, key controller of DNA transcription nGRE Negative glucocorticoid response element NK cell Natural killer cells, a cytotoxic lymphocyte of the innate immune system NLS Nuclear localisation signal nM nanomolar NMDA N-Methyl-D-aspartate, a specific agonist for NMDA glutamate receptors NOS Nitric oxide synthase, inducible iNOS, epithelial eNOS NTD N-terminal domain N-terminal amino- or NH2-terminal end of protein or polypeptide, usually the start OD Optical density, a quantification of detection of protein in Western blot p203 GR GR phosphorylated at serine 203 p211 GR GR phosphorylated at serine 211 a class of stress-responsive MAPK, which include MAPK14, MAPK11, MAPK12/ERK6, and p38 MAPK MAPK13/SAPK4 p44/42 MAPK aka ERK1/2 p53 Phosphoprotein or tumour suppressor p53 protein, regulates cell cycle p65-NFkB p65 subunit of NF-kB transcription factor pAkt Phosphorylated Akt/PKB PAMPs Pathogen-associated molecular patterns 15

PAP pen Creates a hydrophobic barrier for solutions applied to IHC slides PBMC Peripheral blood mononuclear cell, e.g lymphocyte, macrophage, monocyte PBS Phosphate buffered saline PBS-X PBS with 0.3% Triton-X, non-ionic surfactant Cell line derived from a pheochromocytoma adrenal rat medulla - terminally differentiate with PC-12 nerve growth factor p-caveolin phosphorylated caveolin Period2::Luciferase, genes engineered to produce luciferase in conjuction with Per2, a circadian Per2:Luc clock gene PFA Paraformaldehyde, fixative, in solution with PBS PG Prostaglandin phosphorylated, the addition of a phosphate group, often changes the activity of a protein, as phospho- with kinases pHTGR Halo-Tag GR fusion protein PI3K Signalling enzyme, Phosphoinositide 3-kinase, in PI3K/AKT/mTOR pathway Peptidyl-prolyl cis-trans isomerase NIMA-interacting 1, an enzyme, aka peptidyl-prolyl cis/trans Pin1 isomerase (PPIase) PIP2 Phospatidylinositol-1,3-bisphosphate PI-PLC Phosphatidylinositol-specific phospholiase C PKA Protein kinase A PKB Protein kinase B also known as Akt PKC Protein kinase C PLC Phospholipase C PMA Phorbol myristate acetate, an inflammatory challenge agent, activates PKC Polymorphonuclear neutrophils, granulocytes, white blood cells or leukocytes that include PMN Neutrophils, Eosinophils and Basophils PNS Peripheral nervous system, nerves and ganglia outside the CNS PP Phosphatase Ptchd1 Patched-domain containing 1 P-TEFb Positive transcription elongation factor, cyclin-dependent kinase, regulates activity of RNA Pol II PTSD Post-traumatic stress disorder PVN Paraventricular nucleus of the hypothalamus qPCR Quantitative polymerase chain reaction, used to amplify genetic material Rac Rho-family GTPase Raf a MAP3K RANTES Regulated upon activation, Normal T cell expressed, and secreted, a chemokine aka CCL5 Ras a small GTPase, e.g. in MAPK signalling Rel A protein that makes up the NF-kB heterodimer RFP Red fluorescent protein the corresponding frequency channel for excitation and emission spectra on the fluorescent Rh-TR-PE microscope for "Red" e.g. Alexa-Fluor 546 and 594, Phalloidin RIPA Radioimunoprecipitation assay buffer, for cell lysis RNA Ribonucleic acid RNA Pol II RNA polymerase II RNase Enzymes which digest RNA RPM Revolutions per minute RPMI Roswell Park Memorial Institute medium, for cell culture RpS6 Ribosomal protein s6 RT-qPCR Real time quantitative polymerase chain reaction, a measure of gene expression RU-486 Compound that inhibits activity of GR, GR antagonist, traded as Mifepristone 16

Runt-related transcription factor 1; translocated to, 1 (cyclin D-related), aka AML1T1; CBFA2T1; CDR; ETO; MGC2796; MTG8; MTG8b; ZMYND2; acute myelogenous leukemia 1 translocation 1 protein; acute myelogenous leukemia 1 translocation 1, cyclin-D related; core-binding factor, runt domain, alpha subunit 2; translocated to, 1; cyclin D-related; eight twenty one protein; myeloid Runx1t1 translocation gene on 8q22 s second sal Saline Stress-activated protein kinases/Jun amino-terminal kinases, kinases in MAPK signalling pathway, SAPK/JNK activated by MKK4/7 SDS Sodium dodecyl sulphate, detergent used to denature proteins in gel electrophoresis Serine, an amino acid, site for post-translational modification of proteins commonly Ser phosphorylation SGK Serum- and glucocorticoid-inducible kinase shRNA Short hairpin RNA, silences gene expression via RNA interference Simv Simvastatin siRNA Short interfering RNA, interferes with gene expression, similar applications as shRNA Src Proto-oncogene tyrosine-protein kinase, when active phosphorylates tyrosine residues STAT Signal transducer and activator of transcription Stc1 Stanniocalcin-1 SUMO-1 Small ubiquitin-related modifier-1 T cell Lymphocytes that mature in the thymus TATA box Goldberg-Holness box, cis-regulatory element of a DNA sequence in the promotor region of genes TBE Tris-Borate-EDTA buffer TF Transcription factor TIRAP Toll-interleukin 1 receptor (TIR) domain containing adaptor protein TLR Toll-like receptor TNFα Tumour necrosis factor alpha TRAF TNF receptor associated factor TRE Transcription factor response element Tris Tris(hydroxymethyl)aminomethane, buffer Tween Polysorbate surfactant, Polyoxyethylene (20) sorbitan monolaurate TYK Tyrosine kinase Tyr Tyrosine, an amino acid, site for post-translational modification of proteins UV Ultraviolet radiation VEGF Vascular endothelial growth factor Veh Vehicle Signalling pathway involved in regulation of gene transcription, cell polarity, proliferation and Wnt differentiation, and embryonic development WT Wild Type xg times gravity, measure of centrifugal force Zfand5 Zinc finger, AN1-type domain 5 β-ME β-mercaptoethanol

1 Introduction

1.1 Inflammation Inflammation is a necessary reaction by the body in response to invasion of pathogens, infection or injury. The inflammatory response is initiated in response to acute tissue injury, as the first stage of achieving tissue integrity in combination with tissue formation and remodelling (Eming et al. 2007). The inflammatory phase is characterised by the five cardinal signs of dolor (pain) calor (heat), rubor (reddening), oedema (swelling), and functio laesa (loss of function), the first four of which were described by Celsus in his work de Medicina, around the 1st century BC, with the last purportedly added by Galen in the second century AD, although this is contentious (Rather 1971). The inflammatory response presents in the cardinal signs – heat and reddening due to additional blood flow to the local area, swelling due to the “leaky” blood vessels allowing more fluid into the tissue, and pain due to nerve stimulation by some inflammatory mediators, such as bradykinin.

1.1.1 The cellular inflammatory response Immediately following injury extravasated blood thrombocytes, or platelets, form a clot to prevent further blood loss. Platelets and neutrophils within the clot release factors that amplify the aggregation of platelets and cells, initiate coagulation, and act as chemoattractants for cells of the immune system. Local innate immune cells in the tissue, such as macrophages and dendritic cells detect the damage during local environment surveillance, by recognition of DAMPs (damage associated molecular patterns), endogenous molecules such as cytosolic proteins or DNA released by necrotic or damaged cells, not during apoptosis, and PAMPs (pathogen associated molecular patterns), such as cell surface proteins or lipopolysaccharide (LPS) particular to bacteria (Bianchi 2007). This activates these cells in order to initiate a response to the infection or injury, such as by phagocytosis of the infectious agent or activation of signalling pathways, also the release of inflammatory mediators and chemoattractants. PAMPs are usually detected via toll-like receptors on macrophages and other leukocytes in the tissue, which activate signalling pathways such as NF-κB. T cells are activated in response to antigen presented in the major histocompatibility complex (MHC) on the surface of macrophages and dendritic cells, and also by some other cells in response to certain cytokines. B cells detect their specific antigen via their B cell receptors, with an additional signal from T-helper cells, they can produce and secrete antibodies, which bind to microbes, making them easier to detect by phagocytic cells.

Blood capillary wall endothelial cells are activated in response to pro-inflammatory cytokines IL-1β, TNF-α and IFNγ, this causes the cells to express certain adhesion molecules necessary for adhesion of leukocytes flowing in the blood, initially mainly neutrophils. The leukocytes respond to this adhesion by rolling and creeping along the epithelial wall, as an interaction of leukocyte cell surface integrins with endothelial cell adhesion molecules such as P- and E-selectins and ICAM-1 and -2, until they reach a site of access to the area of damage. This epithelial transmigration occurs at the junctions between the cells, which are loosened in response to leukocyte adhesion molecule intracellular signalling, such as ICAM- 1 (Zen and Parkos 2005), thought to occur in a step-wise “unzipping” of the adhesins with the leukocyte replacing the endothelial cell-cell attachment, and is known as the paracellular route. Leukocytes have also been found to cross endothelial cells in a transcellular way, travelling through the cytoplasm in response to the same attachment- signalling (Engelhardt and Wolburg 2004).

Once at the site of injury, leukocytes can clear up damaged tissue and released cell contents by phagocytosis, as well as release antimicrobials and proteases, and further cytokines to induce chemotaxis of macrophages, T cells and neutrophils, and to modify the immune response of these cells once they arrive at the site of damage (Theilgaard-Monch et al. 2004). Cytokines, chemokines and enzymes promote the breakdown of extracellular matrix by activated immune cells, allowing for cellular motility and reorganisation, as well as inducing angiogenesis and migration and proliferation of cells of the tissue that is damaged and fibroblasts necessary for the resolution of wound healing – ideally, the restoration to “normal” tissue state and function, which is of course dependent on the tissue affected and the extent of the damage.

1.1.2 Innate vs. adaptive immunity The response to microbial infection is similar to that of wound healing, whether the trauma is endogenous, e.g. muscle damage induced by exercise, or exogenous, such as extreme temperatures, mechanical or chemical damage. The immune response is usually divided into the innate and the adaptive response, the innate response being rapidly directed toward targets whose receptors are specified by the genome, which are commonly expressed by infectious agents, such as LPS and double-stranded RNA. The adaptive response is generated in response to a newly-recognised threat; generally by immune cell receptors presenting protein antigens of, for example, pathogens, to other cells of the immune system, which are then activated and a response is initiated. This is delayed in comparison to the innate response. The adaptive system also has a “memory” function, 19

once the inflammatory process has subsided, memory B cells retain the ability to produce specific antibodies, and memory T cells retain the specific receptor for pathogen antigen, making it easier to recognise a challenge in future in order to mount a more rapid immune response. Although there is a division made between these two systems, there are overlaps between the two, as some cell types have functions for both, therefore it has been postulated that the immune response should therefore be viewed as a continuum rather than a dichotomy (Borghesi and Milcarek 2007). Some of the major signalling pathways in response to bacterial infection in immune cells are shown in Figure 1-1

1.1.3 Chronic inflammation It was suggested that chronic inflammation, as found in asthma for example, arises as a result of failure to resolve recurrent bouts of acute inflammation (Lawrence and Gilroy 2007). Asthma is characterised by a lung hyper-reactivity to various stimuli – commonly allergens, cold, exercise – which elicits an acute inflammatory response, and associated bronchospasm or narrowing of the airways, as well as a later secondary inflammatory response which may be delayed by several hours (Reed 1988).

1.1.4 Autoimmune disease B and T cells are screened for auto-reactivity, that is, recognition of self-antigens, before being allowed to fully mature and leave the bone marrow and thymus respectively to pass into the circulation. However, auto-immune diseases still occur. Multiple sclerosis (MS) is characterised by the immune cells attacking the myelin sheath of neuronal axons. It has been proposed that MS autoimmune attack is caused by misrecognition of myelin proteins as foreign, due to its sequence similarity to bacterial or viral surface proteins, so-called molecular mimicry (Klee and Zand 2004). Rheumatoid arthritis is thought to be caused by an abnormal B cell-T cell interaction, involving the presentation of self-antigens to T-cells and initiating a self-reactive response (Aarvak and Natvig 2001). In cases of autoimmune disease, drug treatments usually attempt to dampen-down the acute and on-going inflammatory process.

Figure 1 -11 (Aliprantis Major signalling et al. pathways 2000) in T-cell activation

1.1.5 Anti-inflammatory actions of glucocorticoids The immune response is optimised to be specific for safe removal of infection, and resolution of damage. As the activated immune cells produce enzymes and reactive oxygen species, for example, that could potentially damage self-cells, and cytokines and chemokines that propagate and accelerate the inflammatory response, the immune response itself must be reduced and resolved. Over the time course of inflammation, once they have done their job, inflammatory cells should leave the site of inflammation, or undergo apoptosis and be phagocytosed by other cells such as macrophages. Activated cells must also revert to a non-activated state, and therefore cease production of pro-inflammatory cytokines. The resolution of inflammation is produced by the cessation of pro-inflammatory signalling, in concert with anti-inflammatory, or pro-resolution, signalling (Serhan 2011; Serhan et al. 2007). As there is inherent danger to self in the progression of an inflammatory process, there are endogenous negative feedback mechanisms that are activated in order to restore homeostasis. One such mechanism is the production of glucocorticoids (GC) by the HPA axis in response to cytokines produced during inflammation, which have an immunosuppressive effect on T-cells, macrophages and neutrophils. GC signalling is also involved in various metabolic processes, such as control of glucose homeostasis, bone and skeletal muscle metabolism, protein, lipid and carbohydrate metabolism, effects on neurones and hormone signalling (Necela and Cidlowski 2004; Rose et al. 2010).

1.1.6 The development of synthetic glucocorticoids Synthetic cortisone, developed in conjunction with the Merck laboratories, was first used to treat rheumatoid arthritis in 1948. It was then known as Kendall’s compound E, from the corresponding isolated fraction of the adrenal cortex. Compound E, 17-hydroxy-11- dehydrocorticosterone, was isolated in 1936, but not synthesised in usable quantities until 1948 due to difficulties in perfecting the synthetic pathway (Sneader 2005). At this point, 1 g was given to Philip Hench of the Mayo clinic, who had been researching arthritis and the alleviation of symptoms that occur in cases of jaundice or pregnancy. He and his colleagues had hypothesised that the relief was dependent on a naturally occurring, specific biological compound produced in these conditions, and conjectured that it was an adrenal hormone; a view strengthened by observations of arthritic patients who experienced some relief following procedures that stimulate the adrenal cortex, such as general anaesthesia and surgery. The first patient, a 29 year old woman, was admitted to the clinic with acute arthritic symptoms that had progressed until she was barely able to move without intense pain. On receiving the synthetic compound E, the patient was administered 100 mg by 22

intragluteal injection daily. She initially showed little improvement, but after three days was able to move with less pain, and within a week swelling had reduced and movement was greatly improved. Hench and colleagues repeated the experiment with a further larger cohort of patients with similar results, using the less expensive and more easily prepared compound E acetate. They found that the effect was significantly better than a placebo, which gave no effect, and that the beneficial effect was usually rapidly terminated with recurrence of symptoms upon cessation of treatment (Hench et al. 1949). Kendall, Reichstein and Hench were awarded the 1950 Nobel Prize in Physiology or Medicine "for their discoveries relating to the hormones of the adrenal cortex, their structure and biological effects".

1.1.7 Side effects of glucocorticoid treatment Glucocorticoids are one of the most commonly used treatments for diseases comprising autoimmune reactions and/or chronic inflammation, however, the side effects can be quite severe, especially with long term glucocorticoid treatment due to the diversity of effects from GC signalling including metabolic actions of glucocorticoids, and the off-target interactions with other members of the steroid receptor family, such as the mineralocorticoid and estrogen receptors. Side effects may result from transactivation (induction of gene expression), transrepression (inhibition of transcription), or a combination of the two. Side effects include skin thinning, delayed or disturbed wound healing via effects on the inflammatory response (Beer et al. 2000), growth inhibition, changes in bone metabolism leading to increased osteoporosis risk via inhibition of osteoblasts (Leclerc et al. 2005), as well as reduced calcium absorption from the gut, skeletal muscular atrophy (Ma et al. 2003) via protein degradation and inhibition of protein synthesis, as well as disturbed glucose metabolism via increased gluconeogenesis which may lead to diabetes mellitus (Gulliford et al. 2006), and increased glucose uptake by muscle tissue which may increase muscular atrophy. Long-term systemic GC treatment commonly affects the HPA axis, as normal endogenous GC production has a negative- feedback effect on the production of further steroid hormone. HPA axial suppression may result in adrenal insufficiency, growth inhibition and symptoms of Cushing’s syndrome, that include enhanced fat deposition, hirsutism, moon face and buffalo hump (Hopkins and Leinung 2005). GCs may also affect the cardiovascular system (Walker 2007), resulting in hypertension from increased vascular reactivity, effects on the eye, causing glaucoma or cataracts (Taylor et al. 2010), and effects on the gastrointestinal system, including gastrointestinal bleeding, peptic ulcers and pancreatitis, most likely resulting from reduced mucus production coupled with increased acid production (Cushman 1970). The general 23

immunosuppressive effects of GCs may also leave patients more open to opportunistic infections, and less able to sufficiently fight off infections when they occur. Mechanisms of GC side effects are extensively reviewed by (Schacke et al. 2002). Glucocorticoids are also involved in normal cognitive function; the stress response induces release of cortisol, which enhances fear conditioning and affects learning and memory. Corticosteroid therapy has been found to correlate with impaired memory function, as well as symptoms of hypomania, mania, depression and psychosis (Brown and Chandler 2001; Brown 2009).

Due to the range and severity of side effects, some of which may be irreversible, it is important to modulate the off-target effects of glucocorticoid treatment, especially where high doses have to be taken. Attempts to reduce the side effect profile include targeting the application to topical areas to limit systemic effects, for example topical creams for dermal inflammation, inhaled corticosteroids for treatment of asthma, and eye drops. “Soft” steroids are also being developed, these are applied locally, for example to the lung, where they have their effect, but are rapidly broken down by hydrolysis once in the circulation, prior to first pass metabolism at the liver which is usually the earliest site for metabolism of drugs (Ricclardolo 2007). The aim of pharmacological development of new glucocorticoids is to modify the structure of the drugs to preferentially target GR subtypes, or protein-interaction states, to promoted the desired transcriptional or transrepressive effects and specific genes without affecting unwanted gene effects. Recent GC development focussed on dissociative compounds; that is compounds that target the transrepressive signalling without affecting transcriptional activity of GR-responsive genes (Newton and Holden 2007). However, the desired signalling effect may not be purely one or the other, and may require upregulation of some genes as well as down regulation of others. Better knowledge of the intricacies of glucocorticoid receptor signalling and regulation, including GR subtypes, and other proteins involved is needed in order to create more specific ligands to achieve desired therapeutic results.

1.2 The glucocorticoid receptor The glucocorticoid receptor (GR) belongs to the nuclear receptor superfamily, which includes receptors for steroid hormones (e.g. glucocorticoids, estrogens, androgens and mineralocorticoids) as well as receptors for other hydrophobic molecules such as prostaglandins, fatty acids and thyroid hormones. Nuclear receptors share a similar structural organisation and mode of action, via transcriptional activation (transactivation) or repression of transcription (transrepression).

1.2.1 The structure of the glucocorticoid receptor The GR consists of three main domains; the N-terminal domain (NTD), the DNA-binding domain (DBD) and the Ligand-binding domain (LBD), with a hinge region between the LBD and DBD. This modular structure is broadly conserved across the nuclear receptor superfamily. The modular structure of the glucocorticoid receptor is shown in Figure 1-2.A

1.2.2 The N-terminal domain of the glucocorticoid receptor The N-terminal domain (NTD) is the most variable region. It contains the AF-1 transactivation domain, mapped in the human GR to amino acids 77-262 using deletion analysis (Hollenberg and Evans 1988), of which 32% of the amino acids are conserved among mammalian species and Xenopus (Lavery and McEwan 2005). The AF-1 domain can activate transcription of certain target genes, which are different from those targeted by the c-terminal AF-2 domain (Rogatsky et al. 2003). A constitutively active form of steroid hormone receptor can be produced by deletion of the ligand binding domain, this shows that transactivation by the AF-1 domain is independent of ligand. The AF-1 domain binds co-regulators and other proteins of the basal transcription machinery in order to initiate transcription, such as the TATA box binding protein.

1.2.3 The DNA-binding domain of the glucocorticoid receptor The DNA-binding domain (DBD) of the GR is the most conserved region across the nuclear hormone receptor superfamily. It contains two “zinc finger” structural motifs, the N- terminal zinc finger binds specifically to the DNA response element (glucocorticoid response element, GRE), and the second is thought to be involved in protein-protein interactions, such as when the receptor forms a dimer. Once the dimerised GR has bound to the GRE, it can recruit other transcription factors in order to initiate transcription (Georges et al. 2010).

1.2.4 The ligand binding domain of the glucocorticoid receptor The ligand binding domain is at the C-terminal end of the protein. The structure of the receptor binding pocket consists of 12 α-helices and four β-sheets that form a hydrophobic pocket to which the steroid hormone preferentially binds. This conformational structure is dependent on the co-association of the chaperone protein hsp90, which maintains the receptor in the open position in order to accept ligand binding (Pratt and Toft 1997). Once glucocorticoid is bound to the ligand-binding domain, there is a further conformational change of the receptor. This leads to dissociation of various chaperones and exposure of the nuclear localisation signals found in the hinge region between the LBD and DBD (NL1), and in the ligand binding domain (NL2). The LBD also contains a secondary activation 25

factor, AF-2, which recruits co-regulators in a ligand-dependent manner (McMaster and Ray 2007).

1.2.5 Post-translational modifications of the glucocorticoid receptor Post-translational modifications of the NTD occur via phosphorylation and sumoylation. Phosphorylation of the human GR occurs at serine residues 203 and 211 in response to hormone binding, and is thought to influence the localisation of the receptor in the cell, with phosphorylation of Ser203 causing the receptor to be cytoplasmic, and phosphorylation of Ser211 promoting translocation to the nucleus (Wang et al. 2002). Phosphorylation at serines 203 and 211 are homologous with phosphorylation at serines 212 and 220 in mice, and serines 224 and 232 in rat, respectively (Galliher-Beckley and Cidlowski 2009). Here, reference is made to the human phosphorylation site numbering, as they are equivalent. Glucocorticoid receptor post-translational modification sites are indicated in Figure 1-2.B. Phosphorylation of the glucocorticoid receptor changes its interaction with cofactors and target gene expression (Chen et al. 2008b). Sumoylation is the covalent linkage of the small peptide SUMO-1 (small ubiquitin-related modifier-1) to the acceptor motif ψKxE (where ψ is a hydrophobic residue and K is the acceptor lysine residue), which is found in all steroid hormone receptor N-terminal domains except estrogen receptors α and β (Lavery and McEwan 2005). Sumoylation is thought to induce repression of transcription and thereby modify the response to hormone, as deletion of the acceptor motif results in higher transcriptional activity at multiple response elements (Iniguez-Lluhi and Pearce 2000).

The glucocorticoid receptor, with a few other nuclear hormone receptors such as the androgen receptor and ERα, can also be modified by acetylation by histone acetyltransferases (which also regulate histone activity by acetylation). GR is acetylated following ligand binding at an acetylation site in the hinge region/DBD, and deacetylation of GR by histone deacetylase-2 (HDAC2) enables GR binding to the NF-κB complex, to repress NF-κB-driven inflammatory gene expression (Ito et al. 2006).

1.2.6 Glucocorticoid receptor isoforms Alternative splicing of the GR gene near the end of the primary transcript generates two GR isoforms, GRα and GRβ, which differ at the C-terminal end of the receptor (as shown in Figure 1-2.C). The GRα splice variant contains additional 50 amino acids that encode alpha- helices 11 and 12 of the ligand binding domain, and also co-regulator recruitment via AF2. The GRβ isoform contains a different 15 amino acids at the C-terminal, consequently the structure and conformation of the receptor is different to that of GRα. GRβ cannot bind 26

glucocorticoid or glucocorticoid agonists such as dexamethasone, is located in the nucleus rather than the cytoplasm, and does not regulate transcription of GRα-regulated genes. However, co-expression of GRβ with GRα has been found to create a dominant-negative inhibitor of GRα transactivation and transrepression, possibly via the formation of inactive heterodimers, or competition for GRE binding sites or co-regulators. GRβ has also been found to affect the induction and repression of several genes that are not affected by GRα (Kino et al. 2009), and can bind the GR antagonist RU-486, with an inhibitory effect of gene expression (Lewis-Tuffin et al. 2007). Studies have found an increase in GRβ expression over that of GRα in response to pro-inflammatory cytokines, TNF-α and IFNγ, that is associated with glucocorticoid resistance (Tliba et al. 2006; Webster et al. 2001). This implies that GRβ may have a modulatory effect on GR responsiveness.

Further GR isoforms have also been found. GRγ has an extra arginine residue (Arg452) within the DNA binding domain, between the two zinc fingers, as a result of alternate splicing in the intron between exons 3 and 4. This generates a receptor that can bind ligand and DNA, but with a reduced capacity to activate glucocorticoid-responsive reporters, and regulates a different subset of genes from those transcribed by GRα. Other isoforms GR-P, also known as GRδ, and GR-A are truncated proteins that lack parts of the ligand-binding domain, the C-terminal and N-terminal halves, respectively. These therefore cannot bind glucocorticoid hormone, and are found predominantly in cancerous cells, such as multiple myeloma. These may, like GRβ, have an effect on GRα response to GC, for example GR-P was found to increase the activity of GRα in transfection studies (de Lange et al. 2001).

1.2.7 Alternative translation start sites generates glucocorticoid receptor subtypes Subtypes of GR can be produced alternative translation from multiple translation initiation start sites. GRα has eight isoforms generated from a single mRNA due to the presence of eight distinct AUG start codons from exon 2, which result in receptors of differing length N- terminal domains. These eight start codons are conserved in the human, monkey, rat and mouse genome, and produce the isoforms GRα-A, -B, -C1-3 and D1-3. Ribosomal leaky scanning can lead to “skipping” of the first AUG start codon, found with GRα-B and -C, and initiation of translation at a later AUG downstream, and ribosomal shunting, in which the ribosomes bind normally to the mRNA, then jump upstream towards the 5’ end where they initiate translation. These isoforms, shown in Figure 1-2C, have differential tissue distribution and transcriptional regulatory profiles, for example GRα-C was found to be significantly higher in the rat lung compared to the liver (Lu and Cidlowski 2005). This

differential patterning allows greater flexibility in the glucocorticoid response, allowing for transrepression or transcription of different target genes, in different tissues, at different times, coupled with regulation of the expression of the receptor, and its subcellular location, and that of chaperone proteins and cofactors, this allows for the many varied responses of cells to GC.

Figure 1-2 Structure of the glucocorticoid receptor

1.3 Glucocorticoid receptor effects: Genomic signalling Steroid hormones have a typical arrangement of four cycloalkane rings, and are derived from enzymatic processing of cholesterol. They therefore are lipid soluble and can easily cross the cell membrane to bind the ligand binding region of the cytoplasmic GR, which is held in the open conformation by the heterocomplex of chaperones such as immunophilins and heat shock proteins (hsp). This binding induces a conformational change in the receptor, dissociation of the chaperone proteins, phosphorylation of the receptor and exposure of nuclear localisation signals (NLS). Nuclear import proteins such as importins bind to these NLS and transport the GR to the nucleus (Freedman and Yamamoto 2004).

1.3.1 GR binding to DNA Once in the nucleus, the GR dimerises and binds via the zinc finger motifs directly to glucocorticoid response elements (GRE) which are conserved signals usually upstream of target genes. This can enhance or repress transcription of the downstream genes, depending on the GRE present, and the availability of other transcription factors. If the GRE promotes transcription, the GR once bound recruits co-activators and other transcription factors, this leads to increased chromatin remodelling, further cofactor recruitment, and eventual recruitment of RNA polymerase 2 (RNA Pol II)which transcribes the DNA to RNA. There are also negative GRE (nGRE), where GR binding causes repression of transcription of downstream genes, for example by blocking the promoter or other transcription factor binding sites. Glucocorticoid actions at DNA response elements are outlined in Figure 1-3. Some genes that are directly regulated by GC binding to GRE are identified by (Rogatsky et al. 2003), these include glucocorticoid-induced leucine zipper (GILZ), IGFBP1, and metallothionein 1X (MT1X). GILZ is involved in proliferation and epithelial sodium channel activity (Soundararajan et al. 2007). GILZ also plays a key role in GC immunomodulation, control of protein trafficking and signalling. It decreases macrophage sensitivity to LPS, TNF-α and RANTES, also known as CCL5, a chemokine expressed by T-cells. GILZ modulates T-lymphocyte activation as well as other immune cells, IL-2 production, apoptosis, and cell proliferation. It interacts with and inhibits NF-κB, interacts with AP-1, Raf-1 and Ras, which are all involved in GC effects - GC interaction with these leads to inhibition of target gene expression, i.e. transrepression of inflammatory genes e.g. cytokines and their receptors, pro-inflammatory enzymes such as NOS, COX-2. Dex treatment upregulates GILZ, which mimics some of the GC effects, therefore GILZ has an additive immunosuppressive effect with GC treatment (Ayroldi and Riccardi 2009).

Figure 1-3 Glucocorticoid action as a transcription factor

1.3.2 GR tethering to other DNA bound transcription factors. The GR can also modulate gene transcription by tethering to other transcription factors. For example by interacting with transcription factors AP-1 (activator protein-1) and NF-κB, GR can inhibit the production of cytokines, chemokines, adhesion molecules, matrix metalloproteinases (MMPs), which degrade extracellular matrix but are also involved in proliferation and other aspects of cell signalling, cyclooxygenase-2 (COX-2) and therefore influence prostaglandin signalling, and inducible nitric oxide synthase (iNOS) involved in the macrophage “oxidative burst” release of reactive oxygen species, as well as influencing cell differentiation, proliferation and survival signalling controlled by these pathways (Angel and Karin 1991; Hess et al. 2004; Li and Verma 2002). GR influences gene transcription differently at different genes to inhibit AP-1 and NF-κB signalling, via tethering to the DNA- bound protein, or a “composite” of direct GRE binding and interaction with neighbouring transcription factors. Tethering of GR or composite interaction can also increase transcription, such as its association with STAT (signal tranducer and activator of transcription) proteins in the Jak-STAT signalling pathway. This pathway is commonly used in cytokine signalling, where cytokine binding to its surface receptor activates the Janus kinase (Jak) and STAT phosphorylation cascade. STATS also interact with other cofactors, not just GR, to modify cytokine signalling (Rogatsky and Ivashkiv 2006).

1.3.2.1 GR and NF-κB NF-κB is a major pro-inflammatory signalling factor, which up-regulates the expression of multiple inflammatory factors, such as interleukins IL-6, IL-1β and cytokines such as TNF-α, as well as enzymes and adhesion molecules. NF-κB is involved in the rapid response of cells to inflammatory stimuli such as LPS, TNFα and IL-1β via TLR MAPK signalling, as it exists in the cytoplasm in an inactive state and does not require the process of transcription to become active. NF-κB is a heterodimer of transcription factors that share the Rel-homology domain p65/RelA, which is also used as a cofactor in GR-induced transcription. Cytoplasmic NF-κB is complexed with its inhibitory protein IκBα (NF-κBIκBα); in response to inflammatory signals IκB is phosphorylated by IκB kinase (IKK), which was itself phosphorylated by the TLR signalling cascade, which causes the dissociation of IκB from NF- κB revealing a nuclear localisation signal. NF-κB moves to the nucleus where it binds to the promoter region of target genes, and initiates transcription. IκB, dissociated from NF-κB is ubiquitinated and targeted for degradation in the proteasome. NF-κB signalling has a lot of crosstalk with other signalling pathways, including GSK3β, p38, or PI3K, and transcription factors such as STAT3 or p53 (Hoesel and Schmid 2013).

There are three main models for how GR may interact with and suppress the action of inflammatory transcription factors NF-κB and AP-1; through upregulation of IκBα, thereby increasing the level of inhibition, direct protein-protein interaction, and competition for cofactors (De Bosscher et al. 2000a). In protein-protein interaction in NF-κB signalling, activated GR is thought to bind to NF-κB and inhibit its transcriptional activity. Mutation analysis and domain-swapping experiments have linked this interaction to the DNA-binding domain of the GR, and to the p65 domain of NF-κB (De Bosscher et al. 2003). Inversely, the NF-κB p65 domain has also been found to interact with GR and repress GR transactivation. These effects are dependent on the promoter, such as the presence of the TATA box, receptor and cell type, which may explain some inconsistencies between different reports. It is thought that this interference of GR with NF-κB transactivation, and NF-κB with GR transactivation, occurs as a result of steric interference – such as conformational changes within the transcription initiation complex, or masking of transactivating domains (De Bosscher et al. 2000b).

Studies have also found an upregulation of IκBα with Dex treatment in certain cell lines, which associates with NF-κB released in response to inflammatory challenge, dampening the NF-κB signalling (e.g. (Scheinman et al. 1995)). Another mechanism suggested for NF- κB/GR cross talk is “cofactor squelching”, i.e. competition for cofactors such as CREB- binding protein (CBP) required in transcription by both, however, not all pathways using the same cofactors repress one another therefore this may not be a key mechanism in all instances of transrepression. As GR transactivation requires some of the same cofactors as NF-κB, the competition model may contribute, but does not fully explain GR repression of NF-κB activity, as GC can effect repression independent of levels of CBP (De Bosscher et al. 2000b). NF-κB-mediated transcription requires the phosphorylation of RNA Pol II at S2 of the C- terminal domain, by Cdk9 in the Cdk9/cyclinT1 P-TEFb complex, in order to transcribe IL-8 and ICAM1 in response to TNFα. GCs can interfere with this S2 phosphorylation, as well as competing with P-TEFb for binding to NF-κB p65, thereby inhibiting IL-8 transcription (Beck et al. 2009).

1.3.2.2 GR and AP-1 As mentioned previously, GR can interact with AP-1 (activator protein-1) and inhibit its transcriptional activity in a similar manner to the GR interaction with NF-κB, and the same mechanisms have been proposed for this as for NF-κB. AP-1 is activated in response to TLR- MAPK signalling, as NF-κB is, and also induces the production of inflammatory factors. AP-1 33

is a heterodimer, consisting of proteins from the Jun, Fos and ATF families, is involved in various processes within the cell including response to infection, but also proliferation and differentiation, and is activated in response to the Jun N-terminal kinase cascade (JNK or SAPK/JNK). This cascade is activated as part of the same MAP kinase cascade that leads to the activation of NF-κB, and involves some of the same kinases (Hess et al. 2004; Kyriakis and Avruch 2001). AP-1 activation by JNK phosphorylation of c-Jun leads to the recruitment of the transcriptional coactivator CREB-binding protein (CBP), and consequent transcriptional activity. GR is thought to compete with AP-1 for CBP, as with NF-κB signalling, as both require CBP for transcription. However, a study by De Bosscher has found that glucocorticoid repression is unaffected by altering levels of CBP in the cell (De Bosscher et al. 2001), and rather occurred by a different mechanism of nuclear interplay than competition for factors. Activated, steroid bound, nuclear hormone receptors such including GR were found by (Caelles et al. 1997) to prevent c-Jun phosphorylation on serines 63 and 73, blocking the JNK signalling cascade, and thereby antagonising AP-1 activity by blocking the activation of AP-1. As other signalling cascades, including NF-κB, involve the activation of c-Jun, this mechanism may be involved in other signalling events (De Bosscher et al. 2003; De Bosscher and Haegeman 2009).

1.4 Glucocorticoid receptor effects: Non-genomic signalling Genomic signalling by the activated, ligand-bound glucocorticoid receptor is necessarily a rather long process. Gene transcription and expression and post-translational processing of protein may take several hours, with the minimum time for an effect to be measurable at least 15 minutes. However, glucocorticoids have been shown to elicit effects on cells within a few seconds to minutes which are not sensitive to inhibition of transcription (e.g. by cycloheximide) or protein synthesis, and on cells that don’t have a functional nucleus, such as platelets, this implies that there is another form of signalling at work. Non-genomic signalling can also be investigated using inhibitors of GR, such as RU-486, to inhibit classical ligand-binding activation of cytosolic glucocorticoid receptor, or by stimulation with dexamethasone conjugated to BSA (Dex:BSA), which results in a compound that cannot pass the membrane to act on the intracellular receptor, therefore signalling in response to this must be via a membrane-associated receptor (Losel et al. 2003; Strehl et al. 2011).

1.4.1 The stress response In response to stressful or threatening situations, corticosteroids are released by the hypothalamic-pituitary-adrenocortical (HPA) axis. Neuronal signalling to the paraventricular

nucleus (PVN) of the hypothalamus in response to perceived danger causes the release of corticotrophin releasing hormone (CRH) and vasopressin, which stimulates the release of adrenocorticotrophic hormone (ACTH) from the pituitary into the blood stream. This is carried to the adrenal glands, above the kidneys, where it stimulates production of corticosteroids, such as mineralocorticoids and glucocorticoids, from cholesterol by the adrenal cortex. In order to respond quickly to dangerous stimuli, the body must produce an adaptive behavioural response such as increased locomotion and risk assessment. A physiological response is also produced by the sympathetic action of the autonomic nervous system to produce the so-called “fight or flight” response via acetylcholine (ACh), epinephrine and norepinephrine signalling. Corticosteroid signalling in the brain modulates the stress response, with mineralocorticoids affecting appraisal of the situation, and glucocorticoids acting on consolidation of information, to together tailor the response best to the new situation (de Kloet et al. 1999).

1.4.1.1 Rapid GC feedback to the HPA axis The production of glucocorticoids has an inhibitory effect on the HPA axis, inhibiting the release of CRH and ACTH, to decrease the release of further corticosteroids, this occurs in a delayed genomic manner, but effects have been found to occur within 5-15 minutes, an effect that was found to be insensitive to inhibition of protein synthesis, and reactive to BSA-conjugated dexamethasone. This non-genomic, membrane-associated fast feedback is thought to act via endocannabinoid signalling in the PVN, as it is sensitive to endocannabinoid inhibitors (Evanson et al. 2010). The neurons of the PVN of the hypothalamus have a high number of glucocorticoid receptors, which would account for the genomic inhibitory effect on the HPA axis. The production of ACTH at the pituitary is also inhibited in a fast as well as delayed manner, although the mechanism is still unclear (reviewed (Groeneweg et al. 2011)), GR-dependent and GR-independent signalling may be involved (Buckingham et al. 2003; Hinz and Hirschelmann 2000).

1.4.2 Mechanisms of non-genomic signalling Several mechanisms have been proposed for the non-genomic effects of glucocorticoid signalling. These include effects mediated by a membrane-associated GR (mGR), via GC ligand-binding to a different receptor to the GR, such as glutamate receptors or acting via G-protein coupled receptors (GPCRs) such as endocannabinoid receptors, or having a direct effect on the membrane. Effects of glucocorticoid signalling to the cytosolic GR have also been proposed to elicit non-genomic effects via proteins released when the receptor complex is disrupted upon ligand binding. The effects observed have included activation of

second-messenger systems, changes in ion flow, and activation of kinase pathways (Tasker et al. 2006).

1.4.2.1 GR-independent effects via the plasma membrane At high doses, usually greater than the physiological concentration, corticosteroids can elicit so-called “unspecific non-genomic” effects, not mediated by the GR. As steroids are lipid-soluble, they can diffuse into the cells plasma membrane and alter the physicochemical properties of the membrane, affecting proteins within the membrane, such as ion channels. The effect has been measured in human primary bronchial epithelial cells, where a low dose of dexamethasone (1 nM) decreased intracellular Ca2+ and ATP- dependent Ca2+ levels. Using specific antagonists, this effect was linked to adenylate

2+ 2+ cyclase and PKA signalling stimulating the Ca -ATPase pump, lowering [Ca ]i, which decreased Ca2+-dependent Cl- secretion. This may be relevant in asthma treatment, as it may explain the anti-secretory effect of glucocorticoids in reducing mucus production (Urbach et al. 2002). However, the results could not be repeated with topical glucocorticoids used in asthma treatment, hydrocortisone, triamcinolone and budesonide (Losel and Wehling 2003), possibly because dexamethasone is more lipid-soluble, and therefore has a greater effect on the plasma membrane. However, this may be relevant in acute high-dose treatment with glucocorticoids, for example affecting lymphocytes in autoimmune diseases such as multiple sclerosis or spinal cord trauma (Buttgereit et al. 1997). Non-specific effects have also been measured on the mitochondrial membrane of lymphocytes (Martens et al. 1991), increasing H+ leak, and therefore partially uncoupling oxidative phosphorylation. As lymphocytes require high energy consumption for their various functions, such as migration, phagocytosis, and activation, high dose glucocorticoid treatment may show therapeutic benefit by interfering with the energy metabolism of immune cells in this way (Buttgereit and Scheffold 2002).

1.4.2.2 Membrane-associated Glucocorticoid receptor The classical GR has no transmembrane domain, and therefore it is unclear how or whether it is possible for this to associate with the membrane. Studies have shown e.g. by immunocytochemical staining that there is a GR-specific stain-sensitive protein that can be detected in proximity to the plasma membrane, which in some cases is associated with higher expression in disease states. In human and mouse lymphoid cell lines, the mGR appears to be a higher molecular weight than intracellular GR, with different ligand specificity, yet still maintaining a functional DNA-binding domain, and probable protein- protein interaction (Gametchu et al. 1991). This mGR is also found in normal human peripheral blood mononuclear cells (PBMC) and B cells, but not T cells, and is up-regulated 36

in response to LPS challenge and correlates with disease activity in rheumatoid arthritis patients (Bartholome et al. 2004). Immunoaffinity isolation of mouse lymphoma mGR produced proteins with a range of molecular weights from 42-150 kDa, and also pulled down molecular chaperones HSP70 and HSP90, along with other proteins (Powell et al. 1999). The some of the variation in molecular weight range may be due to post- translational modifications of the GR (Gametchu et al. 1999). Recently, Strehl (2011) found that mGR originates from the same gene as cytosolic GR, and has the ability to function though activation of the p38-MAPK signalling pathway in human +CD14 monocytes stimulated with LPS (Strehl et al. 2011). Despite the experimental evidence, the membrane glucocorticoid receptor is still controversial and has not yet been properly characterised, and its interactions with other proteins have not yet been fully mapped out (Losel et al. 2003).

1.4.2.3 Glucocorticoid receptor and G-protein coupled signalling In the brain, there is evidence for a membrane-associated GR that may be involved in modulation of the activity of neurones involved in HPA axial signalling, and the central stress response (reviewed (Tasker et al. 2005), among others). It has been suggested that this receptor acts via G-protein interactions, as it is sensitive to inhibitors of G-protein activity (Maier et al. 2005; Orchinik et al. 1992)

1.4.2.3.1 G-proteins and Fast-feedback inhibition of the HPA axis Endocannabinoid signalling is thought to be involved in the rapid GC negative feedback of the HPA axis. Stimulation of neurosecretory neurons of the hypothalamic PVN occurs via excitatory glutamatergic synaptic input. GCs can block this presynaptic glutamate release, and this inhibition can be blocked by inhibitors of G-proteins on the post-synaptic neuron, and blocked or mimicked by antagonists and agonists of CB1 cannabinoid receptors on the pre-synaptic neuron. GCs appear to activate a G-protein-dependent signalling mechanism, causing the release of endocannabinoid from the post-synaptic neuron into the synaptic cleft, which binds to the CB1 receptor on the pre-synaptic neuron, inhibiting glutamate release (Di et al. 2003; Evanson et al. 2010). This mechanism may also be relevant in neurons for the secretion of other hormones, including CRH and vasopressin, which have rapid GC inhibitory effects.

1.4.2.3.2 Glucocorticoids and memory consolidation Glucocorticoids, particularly cortisol, are released in stressful situations, and are involved in memory consolidation of these events, to enable long-term recall of stress cues that precede a potentially dangerous situation.

1.4.2.3.3 GR and adrenergic signalling GR potentiates norepinephrine signalling via interaction with GPCRs such as β- adrenoceptors. This was shown by, for example, the β-adrenoceptor antagonist atenolol block of GR agonist-induced memory enhancement. GCs increase efficacy of noradrenergic signalling in memory consolidation in the basolateral amygdala by activating cAMP, probably via membrane-associated GR coupling with α1-adrenoceptor, which interacts with the membrane-bound β-adrenoceptor, which then activates the cAMP/PKA cascade, thereby allowing GC modulation of noradrenergic signalling (Roozendaal et al. 2002). This was also found following emotionally arousing experiences again in vivo, where GC or epinephrine administration enhanced memory formation, via an interaction with the noradrenergic system of the amygdala, yet high circulating levels of stress hormone had a transient effect impairing working memory and memory retrieval at the time of acute stress (Roozendaal et al. 2008).

1.4.2.3.4 GR and PKC Corticosterone inhibits the calcium influx induced by nicotinic ACh receptor action on voltage-dependent L-type calcium channels in neurons, such as PC-12 cells and hippocampal CA1 neurons, an effect that can be blocked by protein kinase C (PKC) and GPCR inhibitors. This inhibition could occur via mGR coupled to G-protein that activates PKC, increasing its inhibitory activity on calcium channels or the nAChR (Qiu et al. 1998). PKC also inhibits potassium channels of pituitary corticotrophs, which influence voltage- activated calcium channels, controlling ACTH secretion, an effect that is blocked by GC (Tian et al. 1999).

1.4.2.4 GC and NMDA and AMPA glutamate receptors Glucocorticoid actions of glutamate receptors, such as the ionotropic NMDA and AMPA receptors, may have an effect on modifying neuronal excitability via modification of excitatory glutamatergic signalling. GCs have been found to have a significant non-genomic effect on hippocampal neurons, inhibiting NMDA-evoked currents via NMDA-receptor ion channels. This effect seems to be mediated by mGR activation of G-proteins which affect multiple pathways, including increased cAMP production via activation of adenylate cyclase by activated Gs activation of

PKA, activated PLC and IP3 signalling and release of intracellular calcium stores from the endoplasmic reticulum, PLC activates PKC signalling, downstream of which affects MAPK signalling (Zhang et al. 2012). PKC has roles in phosphorylation of other proteins; one such is the secreted glycoprotein Stanniocalcin 1 (Stc1), which is thought to act in an autocrine or paracrine manner to affect cellular signalling, possibly via increasing calcium signalling 38

which has wide-reaching effects, and phosphate transport. Stc1 may have a role in a number of physiological processes, including cellular proliferation, and has been found to inhibit migration and inflammatory response of macrophages (Huang et al. 2009; Yoshiko and Aubin 2004) and T-cells (Huang et al. 2009), decreasing mobility and diminishing their responsiveness to cytokines, as well as inhibiting NF-κB and JNK activation in endothelial cells (Chen et al. 2008a), thereby acting in a negative-feedback loop. GC treatment has been found to decrease expression levels of Stc1 in cells with high levels of expression, which could be rescued with cAMP treatment (Groves et al. 2001), and conversely, in another study with rat Sertoli and Leydig cells, the inverse was found, where Dex stimulated Stc1, and cAMP inhibited (Li and Wong 2008).

In the hippocampus and other parts of the limbic system, corticosteroid signalling enhances miniature excitatory postsynaptic current (mEPSC) amplitude and therefore neuronal excitability, by modification of AMPA glutamate receptors, increasing the trafficking and cell surface expression of these receptors, via serum- and glucocorticoid-inducible kinase (SGK) (Lang et al. 2006; Liu et al. 2010). In response to stress, MR increase neuronal excitability in the CA1 area of the hippocampus over the long term, through their transcriptional activity in response to corticosterone. Yet there are also rapid changes in the frequency of mEPSCs, which correspond to synaptic glutamate release, via membrane- MR activation of the p44/42 (ERK1/2) MAPK pathway. This is later reversed by the transcriptional effects of GR. In the basolateral amygdala, this MR-mediated rapid enhancement of glutamatergic transmission is longer in duration, and the opposing action of GR is enhanced and rapid in animals with a history of stress, blocking the MR-enhanced mEPSC frequency. This may have relevance to patients susceptible to post-traumatic stress disorder (PTSD) (Karst et al. 2010).

1.4.2.5 Non-genomic signalling via GC binding to cytosolic GR and Src kinase activity Ligand binding to the cytosolic glucocorticoid receptor causes a dissociation of the GR from the receptor complex, required for its translocation to the nucleus, but the dissociation of the receptor complex may also allow other proteins to mediate signalling via genome- independent mechanisms (Buttgereit and Scheffold 2002). For example, (Croxtall et al. 2000) found that GR and Src, a tyrosine kinase, are independently released from the hsp90 complex in response to Dex treatment. This released Src can then have signalling effects in the cell, in this example, in the activation of lipocortin and inhibition of arachidonic acid release. Src kinase has also been implicated in the apoptosis of thymocytes induced by Dex,

via phosphorylation of phosphatidylinositol-specific phospholipase C (PI-PLC) by GR- associated Src kinase, resulting in downstream activation of caspase-8, -9 and -3, and cytochrome c release (Marchetti et al. 2003), see Figure 1-4. In T-cell receptor signalling via the T-cell receptor signalling complex, Lck, lymphocyte-specific protein tyrosine kinase, a member of the Src family, propagates T-cell receptor signalling by phosphorylating the receptor, allowing induction of PLC, IP3 and DAG signalling, as well as increasing the response of IP3R on the endoplasmic reticulum, thereby increasing intracellular calcium signalling (see Figure 1-1) and increasing NFAT transactivation. In Lck-expressing T-cells, GC-induced apoptosis is blocked by activation and signalling, which diminishes the clinical benefit of using GC to treat lymphoid malignancies in lymphatic cancer. Inhibition of Src kinase Lck has been found to enhance the pro-apoptotic GC signalling by Dex, and also acts to downregulate IP3R, and may override GC resistance in some lymphoma patients (Harr et al. 2010; Harr et al. 2009).

1.5 Cross talk with other signalling pathways and the relationship between genomic and non-genomic signalling mechanisms It appears that there is a lot of overlap between the genomic and non-genomic signalling pathways in steroid receptor signalling. This is important to allow a flexible response to different situations. For example, to give a rapid response that is required immediately that can be overtaken by an increasing genomic response that takes longer to initiate. This is also shown in the example given above of the MR-GR interaction in CA1 hippocampal neurones, where the rapid effects of MR are replaced in the long term by the slower effects of GR. This can also occur via activation of kinase cascades, which may have an indirect genomic effect, such as the above mentioned activation of Src kinase.

Figure 1-4 Signalling sequence in glucocorticoid-induced T cell apoptosis

1.5.1 Post-translational modifications of proteins in signalling: Phosphorylation The glucocorticoid receptor can interact with other signalling pathways by

3- phosphorylation. This is the addition of a phosphate group (PO4 ) by a kinase protein to a serine (S, Ser), threonine (T, Thr), histidine (H, His) or tyrosine (Y, Tyr) residue, which can change the hydrophobicity of the protein, and therefore its conformation. Phosphates are removed by phosphatases, reversing this phosphorylation. Phosphorylation and dephosphorylation is important in controlling the activity of various enzymes within the body, and modulates various signalling events. Phosphorylation of proteins is a way of transducing extracellular signals to the intracellular environment, as kinase cascades are often initiated by cell surface receptors in response to ligand binding, such as G-protein coupled receptors (GPCRs), Toll-like receptors (TLRs) and tyrosine kinase receptors.

1.5.1.1 Phosphorylation and the glucocorticoid receptor GR activity is regulated by phosphorylation of sites in the GR N-terminal domain by Cyclin- dependent kinases (Cdks), JNK and p38 MAPKs, and may influence DNA and ligand binding, subcellular localisation, nuclear localisation, cofactor interaction, and therefore the transactivating and transrepressing capabilities of GR. Dephosphorylation is likely to reverse these effects, for example phosphatase PP5 is thought to “reset” GR returning from the nucleus to a ligand-accepting state. GR can mediate some of its effects by influencing the activity of kinases and phosphatases. GR has been found to suppress the activity of p38, JNK and ERK MAPKs in different cell lines. For example, Dex has been found to inhibit p38 MAPK in macrophages, which is activated in response to LPS activation of toll-like receptor 4 (TLR4) (Bhattacharyya et al. 2007). As these kinases act in a signalling cascade, suppression of their activity consequently inhibits downstream kinases such as MAPK- activated protein kinases (MKs). GCs can also affect the expression of kinases or their inhibitors, such as with Cdks (Beck et al. 2009).

1.5.1.2 Glucocorticoid receptor phosphorylation by GSK-3β In addition to phosphorylation at the better-characterised Ser211 and Ser203 phosphorylation sites, human GR can also be phosphorylated at Ser404 by Glycogen Synthase Kinase-3β (GSK-3β). This residue is not in the AF1 region, unlike Ser211 and Ser203, rather closer to the DNA binding domain which may explain why cells with constitutive GSK-3β GR phosphorylation are found to have decreased transcriptional responses. Cells engineered to be unable to be phosphorylated at this residue had several variations in signalling as a result of being unable to recruit transcriptional cofactors CBP/p300 and p65/RelA subunit of NFκB. GSK-3β phosphorylation was also found to inhibit

GR repression of NF-κB (Galliher-Beckley et al. 2008). In addition to these functions of GSK- 3β phosphorylation of GR, it acts to phosphorylate a number of other proteins within the cell involved in metabolism and survival, and is itself phosphorylated by PKB/Akt, downstream of PI3K, downregulating its activity and suppressing proliferation and survival (Fang et al. 2000). GSK-3 has been found to be involved in GC-induced apoptosis in T-cells and thymocytes (T-cell precursors), GSK-3α is associated with GR in the absence of ligand, and upon GC ligand binding dissociates and GSK-3α interacts with GSK-3β and pro- apoptotic factor Bim, inducing apoptosis (Spokoini et al. 2010).

1.5.2 Other inhibitors of NF-κB inflammatory signalling Because NF-κB is such a major mediator of pro-inflammatory signalling, other proteins have been found that interfere with NF-κB signalling. For example, Zinc finger AN1-type domain 5 (Zfand5) is thought to interfere with NF-κB signalling by competition for IKKγ, which is required for NF-κB activation (Huang et al. 2004a). Glutamate-ammonia ligase, or Glul, which catalyses the formation of glutamine, also inhibits NF-κB signalling. Glutamine is a source of cellular energy, and has anti-inflammatory effects in vivo by reduced NF-κB activity, attenuated degradation of IκBα, inhibition of MAPK and ERK signalling pathways, and thereby reduces inflammatory cytokine production (Coeffier et al. 2001; Singleton et al. 2005; Singleton and Wischmeyer 2008) Glucocorticoids have been found to induce Glul expression, as with GILZ, GC may increase their effects by upregulating the expression of inhibitory factors (Olkku et al. 2004).

1.6 Caveolin and caveolae In 1999, Kim et al., found that a membrane-associated estrogen receptor (mER), which was purported to be responsible for the rapid non-genomic response to 17β-estradiol (E2), localised to areas of the plasma membrane known as caveolae (Kim et al. 1999). Caveolae are areas of the plasma membrane that are characterised by a high level of caveolin, an integral membrane protein of which there are three types in vertebrates: Cav-1,-2 and -3. The first caveolin was identified as a 22kDa protein which can be phosphorylated (Rothberg et al. 1992). Caveolins form a hairpin loop that is inserted into the plasma membrane with both the N- and C-terminals at the intracellular face, and come together to form homo- oligomers of 14-16 monomers. The different subtypes show different levels of expression in different cell types, for example Cav-1 is most highly expressed in adipocytes, endothelial and smooth muscle cells and oligomerises with Cav-2 (Williams and Lisanti 2004). Caveolin associates with cholesterol and sphingolipids to form a type of lipid raft that can appear as invaginations on the surface of the cell. These caveolae are thought to have a role in

endocytosis and scaffolding of signal transduction complexes, as lipid-anchored proteins such as receptors, kinases, G-proteins and other signal transducers have been found to localise to caveolae (Anderson 1998). As there is high functional and sequence homology between steroid receptors, it was proposed that mGR may also associate with caveolae at the plasma membrane to facilitate the non-genomic effects of GC signalling, as was found with mER (Arvanitis et al. 2004). See Figure 2-5.

Figure 1-5 Structure of caveolae and lipid raft 45

1.6.1 Caveolin knockout mice Caveolin-1 knockout (Cav-1-/-) mice were bred by the Lisanti group in order to study the role of caveolin in caveolae biogenesis, endocytosis, cell proliferation, and endothelial nitric-oxide synthase (eNOS) signalling. The mice lack expression of Cav-1, and cultured endothelial fibroblasts (mouse embryonic fibroblasts, MEFs) from the animals lack caveolae and Cav-2 expression, implying that Cav-1 is necessary to stabilise Cav-2 expression. There were defects in endocytosis and a hyperproliferative phenotype in the Cav-1-/- MEFs, which could be rescued by recombinant cDNA Cav-1 expression (Razani et al. 2001). Cav-1-/- mice also have a cardiac phenotype characterised by hypertrophy and over-activation of the p42/44 MAPK pathway, upregulation of iNOS (Cohen et al. 2003), and constitutive activation of endothelial nitric oxide synthase (eNOS) which catalyses the production of nitric oxide, NO, and causes microvascular hyperpermeability (Schubert et al. 2002). Caveolin-1 knockout mice were reported to have normal life span, growth and fertility in early reports, however, life span has been found to be significantly reduced over 2 years by the progression of disease states involving pulmonary fibrosis and hypertension, and cardiac hypertrophy (Park et al. 2003).

1.6.1.1 Cav-1-/- mice have changes in pulmonary phenotype The Cav-1-/- mice were viable but lung parenchyma showed structural remodelling with hypercellularity and thickened alveolar septa. This phenotype is also found with congestive heart failure (CHF), along with pulmonary hypertension and dilated cardiac myopathy, features also shared with the Cav-1-/- mice (Abramson et al. 1992; Jasmin et al. 2003; Maniatis et al. 2008). The down-regulation of Cav-1 and -2 expression in pulmonary hypertension induced by myocardial infarction has been linked to the activation of the STAT3/Cyclins pathway, leading to changes in lung structure (Jasmin et al. 2004), a pathway that is involved in crosstalk with NF-κB signalling (Grivennikov and Karin 2010; Hoesel and Schmid 2013), and GC-induced production of IL-6 and IL-10 (Unterberger et al. 2008; Zhang et al. 1997). Caveolin 2 is less well defined than caveolin-1, although is expressed in many cells, especially endothelial cells, and may also have roles in signalling complexes which may be tissue specific (Sowa 2011). Cav-2 heterooligomerises with Cav-1 and cannot reach the cell membrane without this co-expression and is retained in the Golgi body (Mora et al. 1999). Interestingly, Cav-2-/- mice also have a pulmonary phenotype characterised by hypercellularity, “identical” to that of Cav-1-/- mice, although they still express caveolae (Razani et al. 2002), indicating the role of Cav-2 in this lung phenotype.

1.6.1.2 Neurological and behavioural changes in Cav-1-/- mice

The mice show some evidence of a neurodegenerative phenotype characterised by global brain atrophy and decreased motor function that decreased further with age, gait abnormalities and clasping behaviour, along with a unique “spinning” phenotype (Trushina et al. 2006). Cav-1-/- mice also appeared more anxious, and had lower habituation to novel or displaced objects, indicating an effect of Cav-1 in formation of memory (Gioiosa et al. 2008).

1.6.2 Caveolin, NF-κB and pulmonary inflammation and fibrosis In an investigation of pulmonary sepsis by inflammatory challenge with IP injection of LPS, Cav-1-/- mice showed a decreased inflammatory response with attenuated neutrophil sequestration in blood vessels, inhibition of microvascular barrier breakdown and reduced oedema, leading to lower levels of lung injury and mortality. Cav-1-/- mice show increased NO plasma concentration, from increased eNOS activity, as well as suppression of NF-κB activity, both of which appear to be regulated by Cav-1 (Garrean et al. 2006). Neutrophil sequestration is increased time neutrophils reside in pulmonary capillaries before infiltration of lung tissue found in acute lung inflammation, which leads to increased tissue damage(Brown et al. 1995), and may be related to fibrosis or increased scarring of lung tissue with abnormal wound healing (Selman et al. 2001). Caveolin is thought to play a key role in the regulation of extracellular matrix overproduction in idiopathic pulmonary fibrosis (IPF), as patients with IPF have lower expression levels of Cav-1 in pulmonary fibroblasts and Cav-1 suppressed ECM production induced by transforming growth factor- β1 (TGF-β1) via JNK signalling, a signalling pathway which is upregulated in IPF (Wang et al. 2006b). Recent examination of human bronchial epithelial cells and monocytes in patients with asthma, a chronic inflammatory lung state that can lead to fibrosis, found a loss of caveolin-1 in bronchial epithelia and peripheral blood monocytes, and an increase in collagen I and other extracellular matrix proteins tenascin and perioscin in the lung (Bains et al. 2012). There is a binding site for NF-κB in the promoter for matrix metalloproteinase (MMP)-9, and NF-κB regulates MMP-1, -3 and -9, which break down extracellular matrix in the inflammatory response (Bond et al. 2001). Reduced NF-κB activity with reduced Cav-1 expression may play a role in abnormal wound healing and pulmonary fibrosis.

1.6.2.1 Caveolin and endothelial barrier integrity Caveolin has multiple functions in endothelial cells. Transcellular trafficking of particles, for example from blood to tissue, has been found to be dependent on caveolin and caveolae, as transport of BSA was found to not occur in caveolin-1 knockout mice across lung endothelial cells (Schubert et al. 2001). Normally, albumin is transported by caveolae, where endocytosis is initiated by association with caveolin and Src activation, which is not 47

possible in the absence of caveolin. However, electron micrographs have shown presence of vesicle-like structures that resemble caveolae in caveolin-1 KO mice endothelial cells, suggesting a means of caveolin- and clathrin-independent formation of vesicles (Minshall et al. 2003). The constitutive activity of eNOS in the absence of caveolin-1 affects vascular permeability, the vessels lack tone and show increased vasodilation in response to ACh. Tissues have higher levels of oedema, as more fluid moves from the blood into tissues (Frank et al. 2003). This effect can be reversed by the re-addition of the Caveolin-1 scaffolding domain, which regulates signalling complexes, inhibiting ACh-induced vasodilation and NO production in endothelial cells, and systemically was found to have effects similar to glucocorticoids or eNOS inhibitors in counteracting acute inflammation and vascular leak (Bucci et al. 2000). In inflammation, infiltrating immune cells must also cross these epithelial cell barriers, using adhesion mechanisms. In one model of lung injury, polymorphonuclear neutrophils (PMNs) from caveolin-1 knockout mice were found to have reduced adhesion and migration across endothelial barriers, when perfused to wild type mice, (Hu et al. 2008)

1.6.2.2 Caveolin and cell-cell junctions In addition to changes in vascular tone, electron micrographs of Cav-1 KO lung capillaries show defects in tight junctions and in endothelial cell adhesion to basement membranes, with tight junctions appearing on average ~3.5 times smaller than WT (Schubert et al. 2002). This apparent “leakiness” may go some way to compensating for the lack of transcellular trafficking in Cav-1 KO mice. One experiment using siRNA to knockdown caveolin-1 expression in brain microvascular epithelia found an associated decrease in adherens junction associated proteins, zonula occludens-1 and occludin, which dissociated from the cytoskeleton, and alterations in VE-cadherin, and β-catenin allowing monocytes to cross the blood brain barrier (Song et al. 2007). It is likely that in normal functioning, levels of caveolin at cell membranes vary to facilitate a change in membrane functioning. In response to thrombin, a pro-inflammatory blood factor involved in clotting and cell migration to injury sites, phosphorylated caveolin-1 associates with β- and γ-catenin, causing dissociation of VE-cadherin/catenin complexes, loss of junction-associated actin filaments and junction reorganisation leading to loss of barrier function. This is important in cell migration across endothelial barriers, and was not found in caveolin-1 knockout endothelial cells (Kronstein et al. 2012). PKC signalling is also involved in VE-cadherin- associated endothelial barrier breakdown, an effect that was not found in caveolin-1 deficient cells (Waschke et al. 2006). In a model of ventilator-induced lung injury, in comparison to wild type mice in which high levels of injury were induced, caveolin-1 48

knockout mice were found to have lower levels of vascular permeability markers, cytokines CXCL1 and IL-6 in bronchoalveolar lavage (BAL), and BAL neutrophilia (infiltrating cells). This is thought to be due to the lack of thrombin response to stretch injury in these mice, as thrombin-induced albumin hyperpermeability and p44/42 MAP kinase phosphorylation was not found in cultured microvascular endothelial cells from Cav-1 knockout mice (Maniatis et al. 2012). Caveolin-1 may also be involved in maintaining integrity of the blood brain barrier through similar mechanisms. In CNS injury inflammatory processes can have detrimental effects as mechanisms, which in other tissues are beneficial, can result in damage. GC treatment in some instances has paradoxical pro-inflammatory effects in the CNS, and GC was found to decrease levels of occudin, claudin 5 and caveolin-1 in myeloid cells (Sorrells et al. 2013) and thereby may affect the integrity of cell-cell junctions.

1.6.3 Caveolin and inflammatory pathways Caveolin is also thought to regulate AP-1 activation in inflammation. Down regulation of Cav-1 in murine macrophages has been found to increase pro-inflammatory TNF-α and IL-6 production, with decreased anti-inflammatory IL-10 production in response to LPS, an effect reversed with Cav-1 overexpression. This cytokine production in response to inflammatory challenge is thought to be mediated via Cav-1 regulation of the MKK3/p38 MAPK pathway in the activation of AP-1 and NF-κB signalling (Wang et al. 2006a). This was also found in mammary epithelial cells with Cav-1 gene silencing, where LPS-induced p38 MAPK and JNK MAPK activation was found to be increased, and IL-6 and IL-6R expression also increased via TLR4-MAPK signalling (Wang et al. 2013).

The recent review by (Feng et al. 2013), draws together research looking at caveolin-1 and caveolae signalling in sepsis and endotoxemia, which is a model of systemic inflammation involving LPS injection (Andreasen et al. 2008), the model used in some of the studies mentioned above. Caveolae and caveolin-1 have been found in most immune cells, such as monocytes, macrophages, dendritic cells and myeloid cells, as well as human neutrophils. In response to LPS, multiple signalling pathways have been reported to be activated, and caveolin may be important in structuring these complexes. As mentioned previously, caveolin-1 interacts with eNOS as an inhibitory regulator, by binding to it, and with the removal or knockdown of Cav-1, eNOS and NO signalling become hyper-activated leading to NF-κB activation which is particularly important in lung inflammation. In this pathway, TLR4 binding of LPS leads to NFκB –induced production of cytokines, such as TNF-α and IL- 6. In addition, the signalling protein IRAK4 has also been found to be nitrated by eNOS

activation, which inhibits TLR4 signalling, resulting in reduced NF-κB response in CavKO mice (Mirza et al. 2010).

Caveolin-1 has also been found to influence the MKK3/p38 MAPK pathway, where overexpression of Cav-1 has been found to increase phosphorylation of p38-MAPK, and inhibit JNK and PKB/Akt phosphorylation (Wang et al. 2006a). With Cav-1, there was a reduced LPS-induced TNF-α and IL-6 response, and increased IL-10. The cytosolic phospholipase 2/p38 MAPK pathway was found to be involved in increased cell injury with caveolin overexpression (Lv et al. 2010). In cases of bacterial infection, caveolin knockout mice had a greater inflammatory response involving higher cytokine production and mortality, involving dysregulation of the cytokine response by the Cav-1/STAT3/NF-κB pathway, which may be due to more than LPS activation (Yuan et al. 2011). In addition, they found reduced phagocytic ability of macrophages from CavKO mouse BAL.

Cytokine IL-1β association with receptor IL1-R1 induces caveolin-1 dependent internalisation of the receptor in order to produce reactive oxygen species, and downstream IRAK, TRAF6 and IκB kinase kinase (IKK) activity, to activate NFκB (Oakley et al. 2009). Caveolin-1 may also be involved in cyclooxygenase-2, COX-2, degradation leading to increased prostanoid production in caveolin-1 knockout mice, implying a role for caveolin in regulation of inflammation such as in fibroblasts (Chen et al. 2010). Neutrophils from Cav-1 KO mice were also found to be deficient in oxidant production, in comparison to wild type. PMNs from Cav-1 KO showed no activation of Rac1 and Rac2, unlike wild type PMNs indicating a connection between caveolin-1 and these signalling molecules in superoxide production (Hu et al. 2008).

The interaction of caveolin in signalling pathways appears to be very complex, with some instances for caveolin involvement inhibiting inflammatory injury, and others in the promotion of inflammatory activity, with variation dependent on which tissues are involved, genetic background, and model of induction of inflammation. For this reason, caveolin is thought to be significant in inflammation, yet requires further elucidation of its role in signalling pathways. There also appears to be a lot of overlap in the signalling pathways affected by glucocorticoids as those mediated by caveolin in structuring of signalling, where both may act to regulate the inflammatory response. It is possible that caveolin may act to modulate signalling of glucocorticoids.

1.6.4 GR association with caveolin 50

Matthews et al., found that mGR associated with caveolin in lipid rafts, and interacts via the N-terminal AF1 domain of GR to mediate non-genomic signalling events (Matthews et al., 2008). Treatment of A549 lung carcinoma cells with Dex caused rapid phosphorylation of caveolin, GR and cytosolic Akt (PKB), downstream of which mTOR and GSK-3β were phosphorylated. This effect was disrupted by the abolition of lipid rafts and with a dominant-negative form of caveolin that could not localise to the membrane, implying that phosphorylated caveolin (p-caveolin) is required for GC-dependent PKB/Akt activation. Phosphorylation of GSK-3β removes its inhibitory function, and allows it to phosphorylate other pathways, including the NFAT family of transcription factors involved in the inflammatory response, allowing for an indirect genomic effect of GC signalling. Knockdown of caveolin removed the induced phosphorylation of PKB/Akt and GR in an amount proportional to the level of caveolin knockdown, demonstrating a link between caveolin and phosphorylation of GR and PKB/Akt. Stimulation of cells with TNF-α as an inflammatory challenge usually induces IL-6 expression, this effect was blocked with shRNA knockdown of caveolin expression. Caveolin knockout fibroblasts from Cav-1-/- mice showed a higher basal level of phosphorylation of GR and PKB/Akt, and downstream mTOR and GSK3β, implying that caveolin may regulate the basal phosphorylation of these proteins. GC treatment with Dex usually inhibits growth and proliferation of cells, however, Cav-1 KO cells did not show this effect. There was an absence of the block in G1/S cell cycle transition, which implies caveolin is involved in the anti-proliferative effect of GC. From this, it is theorised that caveolin mediates non-genomic signalling of GC, mediating the interaction between GR and other signalling proteins at the cell membrane, and signalling pathways in the cell involved in inflammation and proliferation.

In addition, GC treatment has been recently found to induce the expression of caveolin, as mRNA and expressed protein in vascular endothelial cells. Dexamethasone was found to attenuate induced phosphorylation of PKB/Akt and ERK1/2 (p44/42 MAPK), and reduce Rac1 and NO activity in response to VEGF (vascular endothelial growth factor) and when caveolin induction was reduced, the effect of glucocorticoid on these kinases and signalling molecules was reversed (Igarashi et al. 2013). Glucocorticoid treatment has also been found to up-regulate expression of caveolin-1 in A549 cells (Barar et al. 2007). The non- genomic effects of mGR activation have been found to relate to the classical GR activity associated with cell death and apoptosis, and mGR appears to reside in caveolae. While membrane localisation of GR was found to not be dependent on the presence of caveolin- 1, if expressed Cav-1 dimerises with mGR and was found to modulate mGR induced

signalling, in COX and HADH (hydroxyacyl-CoA dehydrogenase) signalling and therefore oxidation (Vernocchi et al. 2013).

Glucocorticoids are widely used in therapy for inflammatory conditions, for relief of acute inflammatory states as well as long term use in persistent inflammatory conditions, such as arthritis, asthma, and other autoimmune diseases. Glucocorticoids are effective in reducing inflammation, as this is one of the roles they have within the body. However, there are also a number of side effects of long term therapy, as a result of off-target actions of the drug commonly via gene repression (Schacke et al. 2002), affecting the musculoskeletal, cardiovascular, endocrine and central nervous systems (Moghadam-Kia and Werth 2010). There are also problems with development of glucocorticoid resistance, where in inflammatory states such as COPD, glucocorticoids cease to be effective requiring the need for stronger drugs, with higher side effects (Barnes and Adcock 2009). In order to alleviate these problems, better elucidation of the signalling effector pathways activated by glucocorticoids is required to better tailor drug therapy to specific actions. Rapid effects of glucocorticoid action may be mediated through the glucocorticoid receptor, or by glucocorticoids activating other membrane-associated receptors, such as G-protein coupled receptors (GPCRs), or ion channels (Tasker et al. 2006). It has been proposed that in immune cells, rapid glucocorticoid actions may be mediated in one of three ways (reviewed in (Buttgereit and Scheffold 2002, 2003)):

1) Activation of the cytosolic GR by ligand binding, but not by gene transcription. As conformational change causes dissociation of the receptor complex, which includes kinases such as MAP kinases and Src, these released proteins can induce signalling events. 2) Non-specific membrane actions, such as physicochemical changes, found with very high dose glucocorticoids. This affects energy metabolism, and in immune cell systems there is a high energy requirement in order to mount an immune response. High dose glucocorticoids are thought to affect membranes by inhibition of Con A-stimulated respiration. 3) Actions via mGR, the membrane-associated form of glucocorticoid receptor, and affect signalling mechanisms through second messenger pathways including Ca2+,

IP3, cAMP and PKC signalling, as was found with GC actions on hippocampal neurons activating GPCRs (Zhang et al. 2012). With relation to immune cells, Buttgereit and Scheffold (2002) claim to have identified mGR in PBMCs at low

levels in B-lymphocytes and monocytes, but not in T-lymphocytes. Non-genomic immune repressive actions of GC occur in macrophages, thymocytes and CD4+ splenocytes in mouse mutants that cannot bind GR to GRE, indicating that this effect is not mediated by direct transcription of GR binding GRE (Reichardt et al. 2001).

Caveolin, a key component of lipid rafts, has a significant role in structuring complexes of signalling proteins at the cell membrane, promoting the activation of multiple kinase signalling pathways in many cell types. There is a large body of evidence to suggest that caveolin is involved in signalling pathways in inflammatory processes, many of which overlap with glucocorticoid receptor pathways. A few studies have found interaction between caveolin and the glucocorticoid receptor, leading to alteration in GC signalling when levels of caveolin are altered (Igarashi et al. 2013; Matthews et al. 2008; Vernocchi et al. 2013).

1.7 Project Outline It has previously been shown that GR functionally interacts with caveolin-1 at the plasma membrane. The consequences of this interaction remain unclear. There is evidence for effects on cell phenotype, such as changes in proliferation and signalling pathways, and genes that appear to be differentially regulated in the absence of caveolin, but with some target genes not showing any caveolin dependence. This suggests that caveolin acts to mediate only a portion of the actions of GC hormones and drugs in target cells.

Caveolin-1 null mice are viable, but they are subject to a pulmonary phenotype, characterised by fibrosis. This is interesting as glucocorticoids are used in the lung to treat patients with pulmonary fibrosis, as this is attributed to underlying chronic, non-resolving inflammation. Caveolin-1 is also implicated in the regulation of signalling pathways in inflammation, many of which overlap with those affected by glucocorticoids.

Idiopathic pulmonary fibrosis (IPF) is a rare but life limiting condition, for which there is no defined cause, and which currently has no cure and very few options for drug therapy. Medical treatments involve long-term oxygen supplementation and steroid treatment for acute symptoms (Raghu et al. 2011). Following diagnosis, patients may have a steady decline in lung function, but for some this decline is rapid. Median survival following

diagnosis in 2013 was 2-3 years. There is very little known about the causes of IPF, or the cause of bouts of acute exacerbation in disease progression which are found in 5 to 10% of patients (Kim 2013). In addition, patients with IPF can present with concurrent diseases such as emphysema which may be found in up to 35% of IPF sufferers (Cottin 2013), and may experience depressive symptoms (Akhtar et al. 2013), as depression is found to occur more in patients with chronic disease than in the populace in general. Rates of IPF in the UK and globally appear to be on the rise, with the incidence in the UK thought to be increasing by 5% yearly, and therefore also the associated cost of treatment to healthcare providers is increasing (Nalysnyk et al. 2012; Navaratnam et al. 2013). If more is known about the causes and progression of pulmonary fibrosis, perhaps more can be done to alleviate symptoms and disease progression and to design novel therapeutic agents to combat the disease.

1.7.1 Hypothesis Caveolin is a modulator of glucocorticoid action in the lung. It is proposed that the functional interactions between caveolin and the GR in the lung are important, not only for normal lung development but also for pulmonary inflammation. It is therefore predicted that dysregulation of caveolin will detrimentally affect glucocorticoid action within the lung.

1.7.2 Aim The aim of this project is to define membrane actions of the GR and its contribution to global glucocorticoid signalling, in relation to caveolin. Levels of caveolin-1 will be manipulated and glucocorticoid effects in in vitro and in vivo models will be characterised.

Specific Aim 1 - Establish a robust cell model to study GR/caveolin interactions, and to determine which GR target genes are reliant on caveolin for GR regulation. To investigate the variation in gene expression and protein phosphorylation in response to glucocorticoids in mouse embryonic fibroblasts (MEFs) cultured from wild type and Caveolin-1 knockout mice. Real-time quantitative PCR will be used to measure the expression of a number of targets identified by microarray to be differently regulated in the absence of caveolin. Western immunoblot will be used to assay relative levels of protein expression. Transfection of vectors of caveolin-1 will be used to identify whether re- introduction of caveolin is able to rescue any differences in Caveolin-1 knockout cells. Manipulation of lipid rafts in the cell membrane will be assayed, and the effect on GR translocation in live cells will be measured.

Specific Aim 2 - Determine the expression pattern of GR and caveolin in the lung in vivo. 54

The expression of GR and caveolin in MEFs from wild type and caveolin knockout mice will be determined, using antibodies to GR and caveolin in immunofluorescence. From this, a method of staining caveolin and GR in mouse tissue ex vivo will be developed.

Specific Aim 3 - Investigate how caveolin affects the anti-inflammatory effects of glucocorticoids in the lung using knockout mice. The inflammatory pathways in mouse lung in caveolin-1 knockout mice subject to immune challenge with aerosolised LPS will be examined, and whether this is altered with treatment with dexamethasone prior to challenge, and compared with the response in wild type mice. From this, measurements of protein phosphorylation by Western blot and gene transcription by RT-PCR in the lung will be made. The structure of the lung in wild type and caveolin-1 knockout mice will be compared by histochemical analysis.

1.1.1 Major techniques to be used to investigate aims

1.1.1.1 Gene expression A previous microarray (unpublished) was performed to identify genes that had a variation in expression between mouse embryonic fibroblasts cultured from wild type and caveolin knockout mice. Of these, several targets were selected that are thought to be involved in signalling pathways in inflammation, for these targets, primers can be designed and RT- QPCR performed to quantify gene expression. The targets identified to be assayed were GILZ, Zfand5, Ptchd1, MT1, Stc1, Cdh11, Runx1t1, Glul and RpS6. TSC22 domain family, member 3 (Tsc22d3), also known as Glucocorticoid-induced leucine zipper or GILZ, is a transcriptional regulator. The expression of GILZ is stimulated by glucocorticoids, as well as by the chemokine IL-10. GILZ has an anti-inflammatory and immunosuppressive effect by binding to NF-κB, inhibiting NF-κB-induced transcription of pro-inflammatory cytokines, and IL-2 induced apoptosis (Ayroldi and Riccardi 2009; Beaulieu and Morand 2011). Zinc finger AN1-type domain 5 (Zfand5) inhibits NF-κB activation in certain circumstances by competition for the binding site of IκKγ (Huang et al. 2004a). Ptchd1 is involved in Hedgehog signalling, and Patched has been previously associated with lipid rafts for Hedgehog signal transduction across membranes (Shi et al. 2013), although the majority of research on Ptchd1 concerns possible links between deletion and autism spectrum disorders for example (Filges et al. 2011). Metallothionein 1 (MT1) is a protein with a high number of cysteine residues that bind heavy metals. Transcription of metallothioneins is upregulated by heavy metals and glucocorticoids (Kelly et al. 1997). Stanniocalcin-1 has anti-inflammatory effects on macrophages and T-cells. Stc1 gene encodes a glycoprotein 55

and is secreted as a phospho-protein hormone, activated by PKC (Jellinek et al. 2000). Cdh11 (Cadherin 11) is an adhesion molecule in cell-cell junctions, and is linked to calcium signalling and inflammation in fibroblasts (Chang et al. 2011). Runx1t1 (Runt-related transcription factor 1; translocated to 1 (cyclin d-related) is found in chromosomal translocation mutations leading to a form of acute myeloid leukaemia. Runx1t1 is a transcription regulator that interacts with DNA bound transcription factors to recruit transcriptional co-repressors (Rochford et al. 2004). Glul (glutamate-ammonia ligase or glutamine synthetase) is a catalyst for the synthesis of glutamine from glutamate and ammonia (Rose et al. 2013). RpS6 (Ribosomal protein S6) is part of the Ribosomal 40S subunit, and Ribosomal protein S6 kinase can be used as a marker for mTOR activity in the PI3K/Akt/mTOR pathway (Choi et al. 2014).

RT-qPCR can be used to quantify increase in gene expression in tissues in response to inflammatory stimuli, and thereby measure inflammatory response in these tissues. GILZ (Glucocorticoid-Induced Leucine Zipper), as has been mentioned previously, is an anti- inflammatory mediator, MT1 (Metallothionein 1) is also a mediator of inflammation and has been found to have effects in pulmonary inflammation (Inoue et al. 2009). Both GILZ and MT1 can be said to have general effects to suppress inflammation. IL-6 mediates the acute phase response in inflammation, inducing inflammatory cytokine production, and CXCL1/KC is a chemokine that has pro-inflammatory effects such as neutrophil recruitment. IL-6 and CXCL1/KC can therefore be said to have a generally pro-inflammatory profile. Primers for these genes can be used to quantify expression of GILZ, MT1, IL-6 and CXCL1/KC.

In RT-qPCR, the qPCR machine cycles through a series of temperatures, which allow for expansion of the DNA product dependent on the primers, which act as a template to amplify the gene of interest. SYBR green Master Mix contains deoxyribonucleotides, the building blocks for synthesis of new DNA strands, as well as a buffer solution and DNA polymerase, and SYBR Green I. The sample is heated to 95°C to melt the double stranded DNA, the temperature is then reduced to 60°C and forward and reverse primers can bind to this single strand, and DNA polymerase acts to extend the double-strand of DNA between the primers. SYBR green I is a fluorophore dye that binds double-stranded DNA and emits light in the green spectrum upon stimulation with blue light by the thermal cycler. The machine quantifies the level of fluorescence in each sample, in real time. As the gene product is amplified, the fluorescence produced by SYBR green as it binds to double stranded DNA increases in proportion to the amount of gene product. The result of PCR

thermal cycling, the fluorescence emitted from the specific product exceeds that of the background or threshold level, which corresponds to an exponential increase in the product, and the cycle at which this occurs is the CT value. Genes that start with a high copy number, corresponding to the amount of mRNA of that target, will reach the exponential phase after fewer cycles than those with a lower number of copies. A melt curve can be produced, recording the temperature peak at which 50% of the DNA dissociates to single strands as measured as an increase in UV absorbance, the optical density of the solution.

1.1.1.2 Signalling proteins in inflammatory pathways Many of the signalling proteins and the interaction between inflammatory signalling pathways are illustrated in figure 1-1. A large proportion of the proteins involved in inflammation are kinases, such as the MAP kinases. These are activated by phosphorylation and in turn phosphorylate other proteins, leading to a signalling cascade. Western blot can be used to quantify the relative abundance of particular proteins in a sample, and also the phosphorylation state of these proteins by the use of antibodies that are specific to proteins and their phosphorylation state.

1.1.1.3 Histochemical analysis of tissues Antibody specificity can also be used to identify proteins in tissues ex vivo, these can be labelled using fluorescent secondary antibodies and can be visualised on a microscope capable of exciting fluorophores using specific wavelengths of light and detecting the light emitted. By this the relative location of proteins in tissues can be established. Histological stains can be used to identify the overall structure of tissues by, for example, using compounds that have an affinity for environments of a particular pH. In H&E stains, Hemalum in the haematoxylin stains nuclei dark blue, where other structures were stained shades of pink/red by Y eosin, which is acidic and preferentially binds basic structures. Nuclear staining can be used to identify different types of white blood cell which vary in the morphology, such as the presence of granular bodies or a multi-lobular nucleus. Agents can be used that bind specific structures in the cell, for example Phalloidin is a peptide molecule that binds F-actin with high affinity. Rhodamine Phalloidin is phalloidin conjugated to the fluorescent dye tetramethylrhodamine, which fluoresces in the red channel, and can be detected using fluorescent microscopy, likewise there are fluorescent compounds that can be used to stain nuclei, such as DAPI or Hoechst stain. Tissues and cells must first be fixed, then for dyes and antibodies to access the interior structures of cells they are permeabilised, for example with the use of a detergent to perforate or disrupt cell membranes. 57

2 Materials and Methods

2.1 Mammalian cell culture

2.1.1 Cell maintenance Cells were maintained in a monolayer in Dulbecco's Modified Eagles Medium (DMEM), high glucose, with L-Glutamine and sodium bicarbonate, (Sigma-Aldrich), with 10% FCS (Foetal

Calf Serum, Sigma-Aldrich) at 37°C and 5% CO2. Cell culture was performed under aseptic conditions, in a laminar flow hood (Labcaire SC-R (Class II) microbiological safety cabinet). Cultured cell populations were propagated from aliquots of wild type (WT) Mouse Embryonic Fibroblasts (MEFs) or MEFs cultured from caveolin-1 knockout mice, which had been isolated, immortalised, and preserved in liquid nitrogen between passages 5 to7 (Prof. Richard Anderson). Cells were split regularly to new T-75 cell culture flasks (Corning) when they reached approximately 100% confluence, adherent cells were detached by incubation with 10X Trypsin EDTA (5g porcine trypsin, 2g EDTA, Sigma-Aldrich). Caveolin-1 knockout (CavKO) MEFs were split more frequently than WT, as cell populations doubled more rapidly. A549 cells were maintained under the same conditions as MEFs, although separately to avoid cross-contamination from the primary cell lines.

2.1.2 Cryoprocessing Adherent cells were trypsinised, and cell suspension centrifuged at 1000 RPM for 5 min and media discarded. Pellet was resuspended in 3 ml Freezing media (50% FCS, 40% DMEM, 10% DMSO) and split to three cryovials. These were frozen slowly to -80°C then transferred to liquid nitrogen storage. To thaw cells, freezing media was gradually replaced by warm DMEM with 10% FCS and cell suspension transferred to T-75, and cells allowed to adhere for 24h, then media changed to fresh DMEM with 10% FCS.

2.1.3 Plating cells for experiments Cells were split to appropriate size dishes at 5x10^4 cells/ml. Cell number was calculated using an automated cell counter (Bio-Rad TC10). A cell suspension of trypsinised cells in media was stained with 0.4% Trypan Blue dye (Bio-Rad) at a 50:50 dilution and 10 µl added to one chamber of a TC10 Counting Slide. The cell counter calculated the number of cells in suspension in a given volume, and calculated dilutions for the required volume of media and cells. Multiple procedures were performed from the same experimental treatment, as illustrated in Figure 2-1 below. In vitro experimental design

Figure 2-1 Experimental design for cell culture

Experimental protocol for wild type and caveolin knockout cells, with transfection with caveolin, and with dexamethasone treatment, for Western blot, qPCR and Immunofluorescence imaging Figure illustrates the general procedure for in vitro experiments in MEF cells, not all of these conditions were used in every instance. Cells were seeded to 10 cm dishes at 1x10^5 cells/ml and transfected with a vector of caveolin, or empty vector, then pooled and divided into further 10 cm dishes for treatment with 100 nM dexamethasone or vehicle, before lysis for the respective experimental procedures, RT- qPCR or western blot. Pooled transfected cells were also seeded to sterile 12 mm glass coverslips for treatment, then fixation with 4% PFA (in PBS) for fluorescent immunohistochemistry. Treatment duration was 10 min for Western blot, 1 h for immunofluorescence, and 4 h for qPCR.

2.1.4 Treatment with Dexamethasone Prior to treatment, media was changed to DMEM supplemented with 10% Charcoal- stripped foetal calf serum (CSS, Sigma-Aldrich), as this is delipidated and therefore has no steroid hormones and other factors that may interfere with treatment with dexamethasone, and to establish a known concentration of steroid hormone on the cells. A solution of 100 nM dexamethasone (Sigma-Aldrich) was made up in DMSO (solvent

Dimethyl Sulfoxide, Sigma-Aldrich) and serum free media, for the untreated control a solution of the vehicle was made using DMSO and serum free media.

2.2 Animal housing Mice were purchased from The Jackson Laboratory and a breeding colony was established from three breeding pairs. Mice were B6.Cg-Cav1tm1Mls/J, a strain which is homozygous for global caveolin-1 knockout, on a C57BL/6J background. Mice were housed under a 12 h light, 12 h dark cycle (7 AM to 7 PM), and maintained to appropriate standards of animal husbandry under Home Office regulations, and procedures were performed under a relevant Home Office licence, according to the UK Animals (Scientific Procedures) Act, 1986.

2.2.1 In vivo Experimental design 17 CavKO mice were of sufficient age at time of study for experimentation; from 4 litters, aged between 13 to 19 weeks, 11 male and 6 female. Wild type mice, strain C57BL/6, were obtained from The Jackson Laboratory to be matched for age and sex of the Caveolin knockout mice. Mice were allowed to acclimatise following transport before experimentation. Animals were divided into groups according to treatment, and marked for identification. The treatment groups were as follows: Saline – 4 male WT, 4 male CavKO; LPS – 4 male 3 female WT, 4 male 3 female CavKO; LPS with Dex pre-treatment 3 male 3 female WT, 3 male 3 female CavKO. All animals were weighed, and weight recorded. Aerosolised challenge, tissue collection and bronchoalveolar lavage were performed by Dr Julie Gibbs (JG) and Louise Kearney (LK).

2.2.2 Animal treatment Dexamethasone was administered to the dexamethasone-treated mice 1 hour prior to aerosolised challenge, via intra-peritoneal injection at a dosage of 1 mg/kg. LPS was made up in saline to a concentration of 2 mg/ml. Mice were placed in an exposure chamber according to treatment group, and exposed to aerosolised LPS 2mg/mL or saline (vehicle) by nebuliser (6 ml total volume) for 20 minutes, and then returned to a clean cage dependent on their home cage and treatment. 5 hours post-challenge, mice were culled via intraperitoneal injection of sodium pentobarbitone. Experimental design for sample analysis is shown in figure 2-2, below.

Figure 2-2 Experimental design for in vivo LPS challenge

Diagram to illustrate experimental process for in vivo experiment aerosolised challenge with LPS, with pre-treatment with dexamethasone, in wild type and Caveolin-1 knockout mice Following treatment, bronchoalveolar lavage (BAL) was performed and the fluid collected for ELISA to establish cytokine production, cell counting and cytospin to quantify the proportion of infiltrating cell types present. Trunk blood was collected and serum separated to establish serum corticosterone levels. Adrenal glands were dissected out for weighing and possible later study. Lungs were removed and separated for further study. Right lobes were immersed in 4% PFA for tissue processing and paraffin embedding for immunohistochemistry (IHC). The left lobes were divided and snap frozen for protein extraction for western blot, RNA extraction for QPCR, Mass spectrometry and NanoPro protein analysis (performed by Dr. Toryn Poolman). Liver was removed, lobes separated and snap frozen for RNA extraction for QPCR and protein extraction for western blot. Snap- frozen issues were stored at -80°C until required. 2.3 Plasmid preparation Plasmids for transfections were grown in E. coli bacteria that had been transformed to overproduce plasmids containing the gene of interest. Plasmids also contain a gene for resistance to the antibiotic Ampicillin which allows for selection for bacteria expressing the plasmid. For this study, plasmids had previously been engineered and selected to include 62

the gene of interest, caveolin. For the hCav1 plasmid, this was a backbone of pcDNA3.1 (5428 bp) with an insert of 550 bp of the gene for human caveolin 1 (Toyoshi Fujimoto). For control transfections, cells were transfected with a plasmid of pcDNA3. These plasmids are stored as a stock in glycerol at -80°C. Competent cells (Agilent Technologies XL 1-Blue) were transformed to take up plasmids by mixing the cells with plasmid and applying a heat shock which punches holes in the plasma membrane and induces uptake of plasmid, according to the supplied protocol but at half the volume of cells stated. These were plated on LB agar (Sigma-Aldrich) plates with Ampicillin (Sigma-Aldrich). Bacterial expansion is encouraged by incubating plates at 37°C overnight. This selects bacteria that have taken up the Ampicillin resistance gene in the plasmid.

2.3.1 Miniprep Bacterial colonies were transferred to 5 ml LB broth (Luria-Bertani microbial growth medium, from powder, Sigma-Aldrich) with Ampicillin and incubated in a shaker overnight at 37°C. Of this 5 ml of bacteria solution, 4.5 ml was pelleted and miniprep (QIAprep Spin Miniprep #27104) was performed to isolate the plasmid from the bacteria by lysing cells, binding DNA to the column and eluting in water. The plasmid DNA content was assessed by NanoDrop spectrophotometer (NanoDrop 2000, ThermoScientific). The culture that had the highest concentration was taken forward.

2.3.2 Restriction Digest A restriction digest was performed to confirm that the plasmid contains the gene of interest. For this, a 10 µl aliquot of the plasmid in buffer solution was incubated with restriction enzymes that correspond to sites in the plasmid backbone either side of the gene of interest where the plasmid can be cut to yield fragments of known length here EcoRV and HindIII. Four incubations of plasmid were prepared of no enzyme (uncut), HindIII, EcoRV, and HindIII with EcoRV, with SuRE/Cut Buffer B (all by Roche), at 37°C for 2 h. The products of digestion were run on a 1.2% Agarose gel, with TBE and SafeView (ABM), loaded with DNA loading buffer and Hyperladder 1 (Bioline), at 90V for 30 min. When viewed with a UV scanner (Bioline), uncut plasmids travelled the least distance through the gel, plasmids with one cut corresponded to ~6000 bp, and plasmid with caveolin insert had been cut out at both restriction enzyme sites and had two bands of ~5400 bp (backbone) and ~550 bp (caveolin). Cut pcDNA3 plasmids were ~5400 bp as they had no gene insert (just plasmid backbone).

2.3.3 Maxiprep

Following plasmid verification, bacterial culture (0.5 ml) was added to 200 ml of LB broth with Ampicillin and incubated in a shaker at 37°C overnight, and also frozen down as glycerol stock at -80°C for future use. The expanded bacteria was pelleted from the broth and a maxiprep was performed (QIAGEN HiSpeed Plasmid Maxi Kit, with QIAfilter and QIAprecipitator), to lyse cells, bind DNA to column, purify, and elute in water following the supplied protocol. Plasmid concentrations were recorded (in ng/µl) to be used for transfection calculations.

2.4 Transfections

2.4.1 Plasmid transfection Transfection mixes were prepared using RPMI media (Sigma-Aldrich), FuGENE 6 Transfection Reagent (Promega) and plasmid DNA. Plasmids used were PC DNA 3 (control), PC DNA 3 : human Cav-1 (hCav1), and Cav myc RFP. A 10 cm dish was transfected with 4 µg of DNA, where a 12 well plate had 0.5 µg of DNA per well, FuGENE was used at 3 µl per µg of DNA. Transfected cells were incubated for 24 h (unless stated), then in most instances split to further 10 cm dishes for experimentation (see Figure 2-1 above). Transfections with Cav myc RFP produced cells that expressed hCav1 with a fluorescent tag of Red Fluorescent Protein.

2.4.2 Transfection of siRNA against Caveolin In siRNA transfection, the transfection mix was made of Lipofectamine RNAIMAX Transfection Reagent (Invitrogen), with Hs_CAV1_6 or Allstars negative control (both Qiagen) to give a final concentration of 10 nM DNA on the cells, following the supplied protocol. Transfections were incubated for 24, 48 and 72h before lysis with RIPA buffer and standardised samples were analysed by western blot for levels of Caveolin, GR (M20 GR) and α-tubulin.

2.5 Western blot

2.5.1 Extracting protein from Cells

2.5.1.1 Cell lysis Media was removed from culture dishes by aspiration and cells were washed twice with PBS (Sigma-Aldrich) and dishes were transferred on to ice. Cells were lysed with either RIPA buffer, or Bicine buffer, as stated. RIPA buffer 5X stock solution was composed of 50mM Tris HCl, 1% NP 40 /IGEPAL, 0.25% Na-deoxycholate, 150 mM NaCl, 1 mM EDTA, pH 7.4, which for lysis was diluted to 1X with dH20, to which protease and phosphatase inhibitors were added at a 1:100 dilution (Sigma-Aldrich; Protease inhibitor (P8340), phosphatase

inhibitor cocktail 2 (P5726) and phosphatase inhibitor cocktail 3 (P0044)). Bicine buffer was composed of 20 mM Bicine buffer, 150 mM NaCl, 100 mM Potassium acetate, 3 mM MgCl2,

1 µM ZnCl2, and 1 µM CaCl2, pH 7.4. To aliquots of this was added 0.5% Triton-X and 0.25% IGEPAL, then Roche cOmplete Mini Protease Inhibitor Cocktail and PhosSTOP Phosphatase Inhibitor Cocktail tablets were added. Lysis buffer was applied for ~2 min, 350 µl per 10 cm dish, before scraping cells and transferring to 1.5 ml Eppendorf tubes. Samples were mixed by vortexing and kept on ice until all treatment conditions had been treated and lysed, as experiments were scheduled to complete over a staggered time period. Lysates were spun in a microcentrifuge at 13000 RPM for 20 min, and supernatants transferred to clean 1.5 ml Eppendorf tubes, and protein concentration determined by Bradford assay.

2.5.1.2 Protein assay of cell lysates A Bradford assay (Bio-Rad Protein Assay cat: 500-0006), was performed to establish protein concentration in relation to BSA standards, with optical absorbance at 595 nm read on a plate reader. From this was calculated the volume of each sample required to load 10 µg of protein per sample. Samples were diluted with PBS, and SDS/Glycerol loading buffer (0.125M Tris, pH 6.8 with HCl, 0.1% SDS, 20% Glycerol, 0.2% β-mercaptoethanol, 0.001% bromophenol blue) was added to each sample to a final volume of 20 µl per lane on the gel. Samples were boiled at 95°C for 5 min to denature proteins.

2.5.2 Extracting protein from fresh tissues

2.5.2.1 Tissue lysis Fresh tissue samples from wild type mice (C57BL/6) were washed to remove blood in PBS with 1mM EDTA (pH 7.4) to inhibit enzyme action, additionally, work was performed on ice. Bicine Lysis buffer (as before, see 2.5.1.1) was added in a volume relative to the size of the tissue sample, 50-200 µl. A glass pestle and mortar was used to homogenise the tissues. DNA in the homogenised samples was digested using RQ1 RNase-Free DNase (Promega #M6101), 15 min on ice. Samples were then spun at 13000 RPM for 5 min at 4°C, supernatant transferred to a new tube and protein concentration determined by Bradford assay.

2.5.2.2 Protein assay of tissue lysates Bradford assay was performed using Coomassie plus – the better Bradford assay reagent (Thermo Scientific #23238). A serial dilution of each sample was produced, to achieve the 1-30 µg protein/ml range of detection of this Bradford reagent, and the assay was performed. Optical absorbance at 595 nm was measured and compared to BSA standards (Bovine Serum Albumin, Sigma-Aldrich). From this, it was calculated the amount of lysate

required to produce 50 µl of 10 µg/µl normalised sample, which was made up in PBS. Normalised samples were combined with NuPAGE LDS Sample buffer (Lithium dodecyl sulphate, detergent and surfactant) and NuPAGE Sample reducing agent (containing DTT, dithiothreitol, a reducing agent) (both Invitrogen) and boiled for 10 minutes at 70°C to denature proteins, achieve a final protein load of 50 µg per well.

2.5.3 Extracting protein from snap-frozen tissues The procedure was as above for extracting protein from tissues, with a few modifications. Lung tissue was removed following in vivo experiment, aerosolised LPS challenge, and snap-frozen in an Eppendorf tube on dry ice then transferred to -80°C for storage. A small amount of the lung tissue was separated and thawed in 300 µl of Bicine lysis buffer, and homogenised using an electric rotor-stator homogeniser, with a clean probe used for each sample. DNA was digested, as before, and samples were spun down and supernatant transferred to a new tube, before freezing at -80°C before continuing. Thawed samples were spun down, and 50 µl of supernatant transferred to a clean tube. Of this, 5 µl were diluted 1:1000 to correspond to the range of the standard curve for protein concentration, and protein assay (Coomassie Plus) run as before to establish µg of protein per µl sample. Samples were made up with PBS, LDS buffer and DTT reducing agent as before, to load 22 µg of protein per lane in 15 µl, and boiled at 70°C to denature proteins, and run on four gels, to allow for blotting with multiple antibodies.

2.5.4 SDS Gel Electrophoresis and transfer of proteins to membrane The vertical electrophoresis system (Bio-Rad Mini-PROTEAN Tetra) was assembled using the appropriate size precast 4-12% tris-glycine gel (e.g. 1.5mm x 15 well Bio-Rad Mini- PROTEAN TGX), and filled with Tris/Glycine/SDS running buffer (TGS 10x, Bio Rad, #161-

0772, diluted to 1x with dH2O), combs were removed and wells of the gel were flushed using running buffer. Samples were vortexed to mix, and loaded alongside protein marker ladder (Bio-Rad Precision Plus Protein Dual Colour Standard Marker #161-0374). Gels were run for 30 minutes at 200V, room temperature. Proteins were transferred from gels to nitrocellulose membrane (0.2 µM pore size) by wet transfer, using the Bio-Rad Mini Trans- Blot Cell following the supplied protocol to run at 4°C, overnight at 30 V, constant, 90 mA., or 1h at 100 V, constant, 350 mA. Transfer buffer was composed of 25 mM Tris Base, 192 mM Glycine, 200 mM Methanol, with dH20. Membranes were washed with PBS to remove all traces of gel, and blocked in blocking buffer of 1% milk, 150 mM NaCl, Tween 20 (1

µl/ml) in dH20 (to 500mL), for at least 4 hours at room temperature to block non-specific protein binding, before probing with antibodies.

2.5.5 Protein labelling with antibodies Primary antibodies were used at a dilution of 1:1000 or 1:2000, depending on the antibody and altered according to optimisation, made up in blocking buffer. Membranes were incubated with antibodies in heat-sealed bags for 2 h at room temperature or overnight at 4°C, on a rocker. Primary antibodies were then washed in three changes of wash buffer to remove non-specific binding (0.25% milk, 25 mM Tris Base, 48 mM Tris HCl and Tween (1 µl/ml)), before incubation with appropriate HRP-conjugated secondary antibody made up in wash buffer at a dilution of 1:5000, for 1 hour at room temperature followed by a further three washes.

Antibody binding was detected by chemiluminescence (ECL) using luminol/peroxidase detection reagents (Thermo Scientific Pierce Western Blotting Substrate #32209, and Lumigen TMA-6 (GE), with different strength of detection agents used in sequence to optimise detection) and exposure to light-sensitive film (Kodak Biomax XAR 165 1454, Kodak Biomax MR 870 1302). Films were developed using an automated processor, and were scanned.

2.5.5.1 Densitometry analysis Optical density of the bands (densitometry) was quantified using ImageJ software, relative to the loading control, α-tubulin, and background subtracted. For this, a scan of the blot was opened in ImageJ, or a composite of scans if multiple blots were run at the same time from the same samples, and the polarity of the image inverted. Using the “draw” tool, a box was drawn around the largest band to fit tight to the edges of the band excluding background. Using this box, the “measure” function was applied to all bands, as well as the background (no bands). The measurements were copied to Microsoft Excel and background measurement subtracted from each value. Results normalised to the control were calculated by (target protein – background) / (loading control – background) for each sample, where target was the optical density of the band for protein of interest, and loading control was optical density of loading control, e.g. α-Tubulin, for that sample. Where possible, a mean average was made of repeats, and this average and standard error of the mean depicted a bar chart, otherwise bar chart depicts optical density of bands relative to loading control for each sample.

2.6 Antibodies used for protein detection in Western blot and Immunofluorescence

Table 2 - Antibodies Antibodies used in experiments Primary and secondary antibodies used for western blotting and immunofluorescence, usually at a 1:1000 dilution of primary antibodies with 1:5000 dilution of secondary antibodies for Western blotting, and at 1:200 dilution of primary and 1:1000 dilution of secondary antibodies for immunofluorescence.

2.7 Real Time Quantitative Polymerase Chain Reaction (RT-QPCR)

2.7.1 RNA extraction from cells

Media was removed from culture dishes by aspiration and cells were washed twice with PBS and dishes were transferred on to ice. RNA was extracted following the procedure in the QIAGEN RNeasy mini kit (#74104), for animal cells spin, working on ice. Cells were lysed in 350 µl RLT buffer with β-mercaptoethanol (β-ME inhibits enzyme activity, such as RNase). Cells were detached using a clean cell scraper, and transferred to a QIAshredder (Qiagen #79654), then homogenised by spinning in a microcentrifuge through the QIAshredder, at 1400 RPM (144xg) for 2 minutes. To each homogenised sample was added an equal volume of ethanol (350 µl), which was mixed by pipet and transferred to a spin column to separate nucleic material, which binds to the column. Columns were spun at 10000 RPM (8000xg) for 15 s to remove non-nucleic material, which was discarded. Samples were washed using buffer RW1 to further remove biomolecules such as carbohydrates, fatty acids and proteins, and an on-column DNA digest was performed to eliminate contamination with DNA using Qiagen RNase-Free DNase Set (#79254), for 15 min at room temperature, then columns were washed again with RW1 buffer. Buffer RPE was then added to wash salts from the column leftover from previous wash buffer. Columns were spun to dry and remove any traces of ethanol, and RNA was eluted in sterile RNA and DNA-free water.

The RNA content was quantified using a NanoDrop spectrophotometer (NanoDrop 2000, ThermoScientific), and RNA was reverse transcribed to DNA using High capacity RNA to cDNA kit (Applied Biosystems) to convert 2 µg of RNA to 2 µg of DNA. Samples were standardised with water to 2 µg RNA in 11 µl, to which reaction buffer (10 µl contains dNTPs, deoxynucleotide triphosphates) and reverse transcription enzyme (1 µl) was added. A negative control was also produced of RNA and reaction buffer without enzyme, by transferring 2 µl of the 11 µl water and RNA mix to a clean tube and adding 2µl reaction buffer, to establish if there is DNA contamination. Samples were spun down to the bottom of the tube and incubated at 37°C for 60 min for reverse transcription to take place, heated to 95°C to denature the enzyme, and stored at 4°C until ready to proceed (same day) or stored at -80°C.

2.7.2 RNA extraction from lung tissue RNA was extracted using QIAGEN RNeasy mini kit (74104), as with RNA extracted from cell culture. Lung tissues were snap frozen on dry ice in 1.5 ml Eppendorf tube, and stored at - 80°C, to preserve RNA and limit enzyme activity, these were kept on dry ice after removing from storage. All probes and work surfaces were treated with RNAseZAP to remove RNAse contamination. Using a sterile scalpel, a piece of tissue 2 to 3 mm across was broken off the 69

sample, and transferred to 600 µl buffer RLT+βME. Samples were homogenised using a rotor-stator homogeniser with a clean probe. Samples were spun in a microcentrifuge at 13000 RPM for 3 min, and supernatant transferred to a new tube. An equal volume of ethanol was added (570 µl), mixed by pipet, and transferred to a spin column, as before. The same procedure was followed as for cell culture samples to extract RNA, as detailed above. In addition to measurement of RNA on NanoDrop spectrophotometer (NanoDrop 2000, ThermoScientific), RNA was run on a 1% agarose gel with SafeView at around 0.5 µg RNA, and was confirmed by viewing under UV light to have two bands half way down the gel, corresponding to rRNA, with a background smear of mRNA. If these bands were not visible RNA extraction was repeated. Genomic DNA contamination would have been visible as a tight DNA band of high molecular weight, which was not observed. RNA was converted to DNA, as before, and RT-QPCR was performed, as before, to quantify expression of GILZ, MT1, IL-6 and CXCL1/KC, relative to β-actin, by ΔΔCT, and results were presented as median and interquartile range. GILZ and MT1 primers were the same as had been used for cell culture QPCR, and additionally IL-6 and CXCL1/KC primers were used to measure changes in cytokine levels.

2.7.3 Setting up the Real-Time qPCR reaction Each well of the Microamp fast optical 96 well plate (Applied Biosystems) contained 7 µl SYBR green (Applied Biosystems Power SYBR® Master Mix 4367659), 0.5 µl DNA, 0.25 µl each of forward and reverse primers for the gene target, and 4.5 µl of RNase and DNase free water to total 12.5 µl. Primers were diluted to a stock of 10 pM before adding to master mix. Samples were run in duplicate or triplicate, depending on the plate layout. A negative control was also run, using the RNA to cDNA control that had no reverse transcriptase, to test for genomic DNA contamination. Plates were spun down, and sealed with ABI prism optical adhesive film (Applied Biosystems) to prevent well to well cross- contamination.

2.7.4 Real-Time qPCR reaction Thermal Cycler Reactions were run on a Real-Time QPCR machine (Applied Biosystems StepOnePlus Real Time PCR System) controlled by StepOne software. Temperature cycle: Denaturation 95°C, 15s, annealing and extension 60°C, 1 min. The machine was run for 40 cycles (approximately 2 h). Amplification plots and melt curves were produced for each sample.

2.7.5 Analysis of QPCR results by ΔΔCT CT results were exported to Microsoft Excel and analysed using ΔΔCT to give the expression level for each gene target and treatment in relation to expression levels in the control,

untreated sample, and for the expression level of the housekeeping gene, β-actin. CT values were arranged according to treatment and cell type i.e. biological replicates, and target, then the mean and standard deviation were calculated for each condition. Delta CT was calculated in control (vehicle treated) samples by subtracting the mean value for reference gene, control treated (β-actin, vehicle wild type) from each target CT. Delta Delta CT was then calculated by subtracting the ΔCT for reference control from ΔCT for the target control, and power calculated as (2, -ΔΔCT). For target genes for treatment conditions, ΔCT was calculated by subtracting the mean for reference gene for the same treatment from CT, then ΔΔCT was calculated by subtracting ΔCT treatment and target, from mean control ΔCT for that target. Power was calculated as before (-2, ΔΔCT), and expression was calculated as Power mean control for the target divided by Power for treatment and target. This gave expression levels in relation to untreated, wild type cells for reference gene and for treatment, of which the mean values were presented as a bar chart for cell types and treatment, with error bars showing standard deviation. Expression levels for experimental replicates were combined to present mean of all experimental repeats, with standard error of the mean.

2.7.6 Primer design and validation Primers were designed according to the NCBI published gene sequence for specific genes in Mus musculus, using the NCBI Primer blast online program, then manually checked against the sequence and run through an in silico PCR program (http://genome.ucsc.edu). Primer pairs were synthesised by Eurofins MWG Operon. Sequences for each primer target are shown in the table below. Primers were validated by running a PCR reaction with a serial dilution of pooled DNA. From this, the amplification plot showed a signal in the exponential phase at each cycle corresponding to each dilution, with no amplification in the negative control (minus reverse transcriptase). The plate was set up as with the reaction detailed above. StepOne software calculated the “efficiency” value for the reaction, which was between 90 and 110%. A melt curve was also produced, which showed one peak for each target, corresponding to the temperature at which the product of the reaction dissociates, Multiple peaks would have indicated contamination with genomic DNA or primer-dimers. The end-products of the PCR reaction were run on an agarose gel (1.7%, in TBE buffer, with SafeView Nucleic Acid Stain (ABM), samples made up with loading dye (Bioline), with Hyperladder IV (Bioline)). The gel showed one band, corresponding to the size of the amplicon for the primer pair. Double bands would indicate contamination with genomic DNA. Where these conditions were not met, the primer was redesigned and new primers synthesised. 71

2.7.7 Sequences of primers used in QPCR

Table 3 - Primer sequences

Primer sequences for real-time quantitative PCR and PCR for genotyping of Caveolin knockout mice. Primers were designed for RT-QPCR to be specific to the target gene in Mus musculus. Primer sequences for genotyping of CavKO mice were obtained from The Jackson Laboratory. 2.8 Genotyping Genotyping of mice was performed on tissue samples from ear punches and tail snips. DNA extraction buffer was composed of 300 mM NaCl, 50 mM Tris base, 0.5% SDS, 5 mM EDTA, pH to 8 with HCl. Clippings were placed in 1.5 ml Eppendorf tube with 300 µl extraction buffer, to which was added 5 µl of 10 mg/ml Proteinase K (Sigma-Aldrich), and incubated overnight at 55°C to digest tissues and to break down cell membranes. Samples

were incubated at room temperature on a shaker for 5 min. 100 µl saturated 5M NaCl was added to break down bonds between DNA and water. Samples were centrifuged at 13000 RPM for 10 min, and supernatant transferred to a clean Eppendorf. 250 µl of isopropanol was added to cause the DNA to precipitate, mixed by inversion, and incubated at -20°C for 1 h. The samples were centrifuged at 13000 RPM for 10 min, and supernatant gently removed from the pellet. Pellet was washed with 70% EtOH, then centrifuged again, removing the supernatant and allowing the pellet to dry. The DNA pellet was then resuspended in RNAse and DNase free water, and DNA concentration was measured on a NanoDrop spectrophotometer (NanoDrop 2000, ThermoScientific). DNA samples were combined with water to get 10 µl of 50 ng/µl DNA, by (50 ng/µl)/(measured ng/µl) = volume of sample containing 50 ng DNA, plus water to make 10 µl.

PCR reaction was optimised from that provided by the Jackson Laboratory for genotyping for standard PCR (available at http://jaxmice.jax.org/strain/007083.html, under Genotyping), for BioTaq Polymerase with this protocol. Known and test DNA samples were run at a temperature gradient of 50.5 to 69.6°C, of which approximate 64.6 to 66.8°C gave the best results which agreed with the protocol temperature for extension at 65°C. PCR was run using a series of concentrations of Mg2+ 1.5 mM, 2 mM, 2.5 mM, 3 mM and 4 mM, with known and test DNA samples at 65°C, with clearest bands seen at 2.5 mM, higher than the 1.5 mM specified in the protocol. PCR was performed using BioTaq DNA Polymerase kit, and dNTP set (Bioline). A PCR mastermix was made containing per sample; 1.2 µl reaction buffer (1x), 0.96 µl 2.5 mM dNTPs (0.2 mM), 0.6 µl of each of the three primers specified in the protocol (1µM of each, see table 2 for sequence, synthesised by Eurofins MWG Operon), 0.06 µl Taq polymerase (0.03 units/µl), 0.6 µl Mg2+ (2.5 mM) and water to make up to 10 µl, to which 2 µl of 50 ng/µl DNA solution was added. PCR ran for 35 cycles of 94°C for 3 min, 94°C for 30s, 65°C for 1 min, 72°C for 1 min, then 72°C for 2 min and held at 10°C.

PCR samples were run on a 1.5% Agarose gel made and run in TBE buffer (89 mM Tris Base, 89 mM Boric Acid, 2 mM EDTA), with SafeView (Applied Biological Materials), with Hyperladder IV (Bioline). Samples were combined with nucleic acid sample loading buffer (Bioline), and loaded onto the gel and run at 90V until the marker was sufficiently separated. Gels were imaged on a UV viewer (BioRad, operating QuantityOne software). CavKO mice had one band at 410 bp, wild type mice had one band of 690 bp including the gene for Caveolin-1, and heterozygous mice would have had both bands.

2.9 Live cell microscopy A549 cells were plated at 1x10^5 cells/ml to a glass bottomed 4 chamber cell culture dish (5x10^4 cells/well, Grenier Bio-One CELLView Cell culture dish with glass bottom #627870), in 10% CSS media. Cells were transfected with a vector of Halo-Tag GR fusion protein (pHTGR), transfection mix was composed of 0.5 µg pHTGR and 0.5 µg empty vector (PC DNA 3) to give 1 µg DNA/well, with 3 µl FuGENE 6 per µg DNA, made up in RPMI media, and labelled with 0.25 µl of TMR (red) Halo ligand per well. Halo ligand and vector base from Promega, plasmid vector pHTGR (Halo-Tag GR fusion protein).

After 24 h, media was changed for fresh CSS media, and cells were treated overnight with 20 ng/ml cholesterol (66 µM), 66 µM methyl-β-cyclodextrin, or 10 µM simvastatin, solutions of which were made up in DMSO and serum free media (simvastatin) or just serum free media (methylcyclodextrin, cholesterol) (Sigma-Aldrich). Methylcyclodextrin concentration was 66 µM to match that of the cholesterol solution, which uses methylcyclodextrin as a vector for inserting cholesterol into cell membranes.

Cells were imaged on a microscope with temperature controlled stage, at 37°C with 5-10%

CO2. Images were acquired on a Delta Vision (Applied Precision) restoration microscope using a 40x/ 1.30 Uplan FLN objective and the Sedat filter set (Chroma 89000v2), with excitation and emission in the Rh-TR-PE (Red) channel to produce signal in labelled cells. Images were collected using a Coolsnap HQ CCD camera (Photometrics). Around ten positions were chosen for recording for each condition, and images were collected at 2 minute intervals for approximately 4 hours. 100 nM Dexamethasone was added after around 1 h of baseline recording, and this time point marked, before continuing image collection so that translocation of Halo-tag GR to the nucleus was recorded. Raw images were then deconvolved using the Softworx software and processed using ImageJ to produce continuous video of each position.

2.9.1 Analysis of GR translocation in Live Cell experiment For each cell, the frame number was recorded where Halo-ligand labelled GR had fully translocated to the nucleus. Data was analysed in Excel for the mean average translocation time for each treatment condition, and graphs produced.

2.10 Immunofluorescence in Cells

2.10.1 Cell fixing and permeabilization

Cells were plated to a 12 well plate (Costar), with a 12 mm sterile glass coverslip (Assistent) per well. Following treatment, media was removed and cells were washed twice with PBS. Cells were fixed with 4% PFA (in PBS), incubated for 1 hour at 4°C, before washing twice in PBS. Cells were permeabilised using 0.1% Triton X-100 (detergent) in PBS for 30 min at 4°C.

2.10.2 Antibody labelling To block non-specific protein binding, plates were incubated in blocking buffer (PBS, 0.1% Triton X-100, 10% sterile FCS) for 1 hour at room temperature on the rocker, before transferring to 4°C for overnight storage. Primary antibodies were applied at 1:200 dilution made up in blocking buffer, sealed in a moist box to prevent drying out, and incubated at room temperature on a rocker overnight. Primary antibody was washed out with 5 changes of PBS, each 10 min. Fluorescent secondary antibodies (Alexa Fluor, Molecular Probes) were applied at 1:500 dilution, made up in blocking buffer and incubated at room temperature in the dark for 2 hours. Secondary antibody was washed out with 5 changes of PBS, each 10 minutes, with the first containing Hoechst nuclei counterstain, at 1:50000 dilution (Sigma-Aldrich). From application of secondary antibody, plates were kept in the dark as much as possible as the fluorescent secondary antibodies are light sensitive, to prevent diminution of signal. Coverslips were mounted to clean glass microscope slides, inverted, in hard set mountant (Vectashield, Vector Labs), and stored at 4°C before imaging.

2.10.3 Imaging Immunofluorescence Images were acquired on a Delta Vision (Applied Precision) restoration microscope using a 40x/ 0.85 Uplan Apo objective, and 60x/ 1.42 Plan Apo N objective, with Sedat filter set (Chroma 89000v2), with excitation and emission in the DAPI (blue), Rh-TR-PE (Red) and FITC (green) channels to produce signal in labelled cells. The images were collected using a Coolsnap HQ CCD camera (Photometrics) with a Z optical spacing of 0.2 μm. Raw images were then deconvolved using the Softworx software and processed using ImageJ to false colour and merge channels.

2.10.4 Phalloidin Actin stain with fluorescent FITC dexamethasone

2.10.4.1 Treatment with FITC dexamethasone A549 cells were plated to a 12 well cell culture plate with a sterile 12 mm coverslip per well, at 5x10^4 cells/ml and allowed to adhere for 24h. Media was changed to fresh media supplemented with 10% CSS. A solution of FITC-conjugated dexamethasone (FITC Dex, Sigma-Aldrich) was made up in DMSO and serum free media to a final concentration on the cells of 100 nM. This is light sensitive so was kept dark as much as possible, as was the plate

in all subsequent stages. FITC Dex was added at 10 and 5 minute intervals, to give final time course of dexamethasone treatment times of 0, 5, 10, 15, 20, 25, 30, 40, 50, 60, 70 and 80 minutes. As time point was reached, media was removed and cells fixed in 4% PFA (in PBS) for 30 minutes at room temperature on a rocker in a light sealed box. This was removed, cells washed twice in PBS and IF blocking buffer (PBS, 0.1% Triton X-100, 10% sterile FCS) was added for 15 minutes, which also permeabilises cells allowing dye entry.

2.10.4.2 Actin staining Coverslips were transferred to a clean 12 well plate for fluorescent Actin staining. Rhodamine Phalloidin (Invitrogen, R415), was diluted in methanol to 200 units/ml, approximately 6.6 µM, and used at 1:100 dilution in 250 µl PBS per coverslip. Phalloidin dye was incubated at room temperature for 15 min, before washing 5 times 5 minutes in PBS, the first containing the Hoechst nuclei counterstain (1:50000, as before). Coverslips were mounted in hard-set mountant (Vectashield, Vector Labs) on glass microscopy slides, and stored in the dark at 4°C before imaging.

2.10.4.3 Imaging of fluorescent labelled Actin and Glucocorticoid receptor Images were acquired on a Delta Vision (Applied Precision) restoration microscope using a 40x/ 0.85 Uplan Apo objective, with Sedat filter set (Chroma 89000v2), with excitation and emission in the DAPI (blue), Rh-TR-PE (Red) and FITC (green) channels to produce signal in labelled cells. The images were collected using a Coolsnap HQ CCD camera (Photometrics) with a Z optical spacing of 0.2 μm. Raw images were then deconvolved using the Softworx software and processed using ImageJ to false colour and merge channels.

2.11 Immunohistochemistry in tissues

2.11.1 FFPE (formalin fixed paraffin embedded) Tissue processing Lung and liver from wild type mice (homozygous null on a Per2:Luc C57BL/6 background) were fixed by perfusion with 4% solution of PFA in PBS, then transferred to a solution of 70% EtOH. With lung tissue, structures were fixed open by inflating with PFA, by intratreacheal injection. Tissues were enclosed in a cassette and processed using an automatic tissue processor (Shandon Citadel 2000), passing tissues through a series of baths of increasing concentration of ethanol to rehydrate and perfuse with paraffin. The sequence is shown in table 3 below.

Processed tissues were embedded in paraffin blocks (ThermoShandon Histocentre2) and cut on a microtome (Leica RM 2155). Blocks were chilled on ice, then trimmed down to tissue level and slices of 5 µm thickness were cut. These sections were floated on a water bath at 40°C and mounted on electrostatically charged adhesion microscope slides (Shandon Superfrost Plus, Thermo Scientific).

Table 4 - Automated sequence of baths for rehydration of tissues for paraffin embedding

2.11.2 Antibody labelling of tissue sections, Immunofluorescence Tissue sections were de-waxed by passing through a series of Xylene baths, and hydrated by passing through increasing concentrations of alcohol (70%, 95%, 100%, 100%), then placed into running water. Antigen retrieval was achieved through boiling in citrate buffer (11.4 µM trisodium citrate, 4.4 mM HCl in dH20, pH 6.24) for 12 minutes in a microwave oven at full power, then cooled to room temperature in the buffer. Slides were transferred to PBS, and sections were circled using a PAP pen, then rinsed in PBS for two five minute washes. Slides were blocked for 90 min at room temperature with a 2% solution of normal donkey serum in PBS (matched to the animal the secondary antibody was raised in) to block non-specific protein binding. Primary antibody was applied at 1:200 (or 1:500) dilution in PBS-serum and incubated at 4°C overnight. Primary antibody was washed in 5 changes of PBS with 0.3% Triton-X (PBS-X), each 5 minutes. Fluorescent secondary antibody

was applied at a 1:500 (or 1:1000) dilution in PBS-serum, for 2 hours at 4°C in the dark. Secondary was washed out with 5 x 5 min changes of PBS-X. For single antibody controls the omitted antibody step was replaced by incubation in blocking buffer. Dual labelling of antibodies was performed in sequence after the first primary antibody and secondary, and whilst other sections were incubated in blocking buffer. All sections were then counterstained, Sudan Black B stained and mounted.

2.11.3 Nuclei counterstaining Hoechst stain was applied at a 1:50000 dilution in the first PBS wash after secondary antibody application, slides were then dehydrated to Xylene in a series of baths (70% EtOH 10s, 90% EtOH 10s, 100% EtOH 3 min, Xylene 1 for 2 min, Xylene 2 for 2 min) then mounted with a coverslip (Scientific Laboratory Supplies, 22x50 mm, no. 1.5) in Entellan (Merck). For sections counterstained with DAPI, this was applied after secondary antibody staining in solution of DAPI 100 ng/ml in PBS, for 5 minutes at room temperature before mounting in aqueous mountant (ThermoScientific Permafluor Aqueous Mounting Medium). Once set, slides were stored at 4°C in the dark before viewing on a microscope. If no antibody staining was used then the same sequence of steps were followed, omitting antibody incubation.

2.11.4 Quenching of autofluorescence using UV and Sudan Black B Slides were exposed to UV radiation prior to dewaxing and antibody staining using a Spectrolinker XL-1000 UV crosslinker (254 nm) for 2 hours, as this was deemed the safest available equipment in the lab for this long-term UV exposure. Slides were then processed as above (2.12.2) for antibody labelling. Sudan Black B staining was applied after secondary antibody staining. Sudan Black B solution (0.1% Sudan Black B in 70% EtOH and filtered to remove particles) was applied for 20 min at room temperature, in the dark. This was rinsed with 10 rapid changes of PBS, not PBS-X as solvents remove the Sudan Black B stain, and nuclei were counterstained with DAPI (in PBS) and mounted in aqueous mountant (Permafluor, ThermoScientific) to prevent leaching of the stain out of tissues over time.

2.11.5 Visualising fluorescent antibody labelling in tissues Slides were viewed on a Snapshot Widefield microscope, with three different microscopes used over the course of image collection dependent on which filter sets were required. Images were collected on Olympus BX51 upright microscope using UPlanFLN objectives 10x/ 0.30, 20x/ 0.50, 40x/ 0.75 and 60x/ 0.65-1.25 (oil immersion) and captured using Coolsnap ES, HQ and EZ cameras (Photometrics) through MetaVue Software (Molecular Devices). Specific band pass filter sets for DAPI, FITC, Texas red, Cy3 and Cy5 were used to 78

prevent bleed through from one channel to the next, and images were collected across the channels for the same section of tissue. Images were processed using ImageJ (http://rsb.info.nih.gov/ij) to false-colour and merge channels.

2.12 Bronchoalveolar lavage Bronchoalveolar lavage (BAL) was performed by instilling and removing 1 ml of BAL fluid

(12.7 mM EDTA in 1 l dH2O with 1g BSA, 0.01%) into the trachea of each mouse, and removed to an Eppendorf tube on ice. The volume of fluid was quantified. The collected BAL fluid was centrifuged at 13000 RPM for 7 minutes at 4°C, and supernatant removed to be analysed using an ELISA to establish cytokine production (results not shown). The pellet was resuspended in 0.5 ml of fresh BAL fluid. Cell count was performed (JG) by taking 5 µl of this resuspension diluted in 10 ml CASY ton fluid (Roche) and read on an automatic cell counter (CASY Cell Counter, Innovatis), gated between 6 and 40 µm to exclude red blood cells. 200 µl of BAL cell suspension was used to produce CytoSpin slides (Thermo Scientific, JG), where cells are deposited onto a defined area of a microscopic adhesion slide (Shandon Superfrost Plus, cut corners) by centrifugation to produce a single layer for microscopy.

2.13 Serum Corticosterone ELISA Enzyme-linked immunosorbent assay (ELISA) was performed to establish serum corticosterone levels (Corticosterone EIA kit, Enzo Life Sciences ADI-900-097), according to the standard protocol provided. Plates (96 well) were coated with the capture antibody in an overnight incubation, and washed before blocking with reagent diluent containing BSA, then washed again. All samples were treated with steroid displacement reagent, (SDR solution, 1:100 dilution in water, 10 µl added to each sample), vortexed and left to stand to allow steroids to move out of solution. Samples were run in duplicate at a 1/8 dilution in EIA assay buffer, except two samples which had too low volume (run at 1/10 and 1/12), and factored into calculations of concentration for analysis. Diluted samples were added to antibody coated wells and incubated for 2 h, before washing out. The corticosterone binds to the antibody in the wells. Streptavidin-HRP was added, incubated for 20 min, and washed out. Streptavidin binds to the biotin label on detection antibodies. Substrate solution was then added which reacts with HRP to produce a colour change in the solution, followed by stop solution to end the reaction. A higher proportion of corticosterone resulted in a higher optical density. The plates were then read on a microplate reader to record the optical density at 450 nm (Berthold Technologies, Mithras LB 940, with Mikrowin 2000 Software). Assay performed alongside Louise Kearney, and analysed by her,

to give corticosterone concentration in relation to standard curve (standards are supplied in the kit and run on the same plate).

2.14 Histochemistry

2.14.1 Leishman’s Stain of CytoSpins CytoSpins were then stained with Leishman’s Eosin Methylene Blue Solution (Merck), by immersing slides in a sequence of steps – 3 min Neat Leishman’s solution, 6 min dilute Leishman’s solution (30 ml Leishman’s solution, 150 ml dH20, 20 ml buffer solution), 3 changes of buffer solution (1 buffer tablet pH 7.2 Merck 1094680100 in 1 l dH20), each 1 min, 95% ethanol for 4 dips in and out of the bath, 100% ethanol 4 dips in and out of the bath, then dipped twice in Xylene. A coverslip was mounted to each dry slide using DePeX (Sigma-Aldrich) to cover the surface of the slide. Cells were viewed using a Leica Brightfield microscope at 40x magnification (JG), and on an Axiovision upright microscope using a 40x/ 0.95 Plan Apochromat objective and images captured using an Axiocam colour CCD camera, through Axiovision software. Cell types were quantified using ImageJ, tagging cell types according to morphology, such as the shape of the nucleus, corresponding to macrophages, neutrophils and other. Quantification was completed by JG. These results are shown in the discussion.

2.14.2 Histochemical staining with Haematoxylin and Eosin Lungs were fixed in PFA for 24h then moved to ethanol. Lungs were placed in cassettes and processed to perfuse with paraffin, in the automated Shandon Tissue Processor, as before and embedded in paraffin blocks. Some samples had not been completely processed, and were soaked in a bath of paraffin at 60°C to allow water to diffuse out, then reembedded in paraffin blocks. 5 µM sections were mounted on charged adhesion slides, as before. To ensure sections had adhered, slides were placed on a hot plate for a couple of seconds to melt the paraffin then moved to a cool surface, to flatten tissue sections that had not adhered smoothly. Tissue sections were de-waxed by passing through Xylene baths (1 and 2, 3 min each), and hydrated by passing through increasing concentrations of alcohol (95%, 100%, 2 min each) and transferred to dH20 (2 min) to rinse, then stained with haematoxylin and eosin. Slides were submerged in filtered Hematoxylin Solution, Harris Modified (HHS32, Sigma-Aldrich) for 5 min, then transferred to running water to remove the stain, about 5 min. Slides were submerged in Eosin Y solution, alcoholic (HT110116 Sigma-Aldrich) for 3 min, then moved through two changes of dH2O, each 2 min. Slides were then prepared for mounting by passing through 2 min baths of 90% EtOH, 100% EtOH, Xylene 1 and 2, then coverslips were

mounted with Entellan (Merck). Hemalum in the haematoxylin stained nuclei dark blue, where other structures were stained shades of pink/red by Y eosin. Images were acquired using a 20x/0.80 Plan Apo objective on 3D-Histech Pannoramic 250 Flash Slide Scanner. Slides were viewed using Pannoramic Viewer software to digitally magnify areas of the slide and images were captured.

2.15 Statistics Fold-change between conditions, for example in induction of gene expression (calculated as described in 2.7.5) or change in the optical density of bands on Western blot was calculated by the following formulae

For an increase: For a decrease:

Fold change = B/A Fold change = 0 – (A/B)

Where A is the initial condition and B is the second. For example, “A” values included WT, untreated, or male and “B” values included Cav-1 KO, treated with Dex or exposed to LPS, Female.

Average in most cases is the mean value, calculated as the sum of results for a condition divided by the number of replicates. Standard deviation was calculated in Microsoft Excel 2010 using the formula

where x is the sample mean and n is the sample size.

For median and interquartile range this was calculated by the QUARTILE.INC function, for an array of data (A:Z) where the first quartile (25th percentile) was calculated by QUARTILE.INC(A:Z,1), median by QUARTILE.INC(A:Z,2), third quartile (75th percentile) by QUARTILE.INC(A:Z,3) and the interquartile range by the third quartile – first quartile.

Statistical significance was calculated using IBM SPSS Statistics 20 to compare means using a t test. Data arrays were also tested for normality in this program using Kolgomorov- Smirnov before means were compared.

3 Results Previously, it has been shown that rapid glucocorticoid signalling is mediated by Caveolin-1 (Matthews et al., 2008). In order to investigate this further, it was proposed that comparisons be made of the signalling profiles and responses to glucocorticoids of mouse embryonic fibroblasts from Caveolin-1 knockout mice and wild type mice, with a view to investigating this in vivo in wild type and Caveolin-1 knockout mice. Techniques were used to look at phosphorylation of signalling proteins in vitro in response to glucocorticoid treatment by Western blot, and also how gene transcription is altered in response to dexamethasone in Cav-1 KO and WT MEFs by real-time quantitative PCR.

In developing experimental techniques for investigating this, Western blotting was used to assay different antibodies to Caveolin-1 in cultured cells as well as a few different tissues ex vivo. Different vectors were tried in order to transfect Cav-1 KO MEF cells with Caveolin-1 to see if it was possible to rescue the wild type phenotype. A knockdown of caveolin in wild type cells using siRNA directed against Caveolin-1 was attempted. In this research, a few experimental procedures were tried that were later discontinued as the results were inconclusive and required more optimisation, such as shRNA against Caveolin-1 and reporter gene assays (not presented here).

In order to visualise caveolin and GR by fluorescent immunohistochemistry, different antibodies were assayed to stain caveolin in fixed cultured cells, and a protocol was optimised for staining caveolin and GR in ex vivo tissue, including a method to quench autofluorescence present in lung and liver tissues. It was investigated whether it was possible to alter the response of live cells to dexamethasone by altering conditions for the formation of lipid rafts, by changing the conditions for cholesterol production and at the cell membrane, which was visualised by the use of Halo-tagged GR with fluorescent ligand.

A number of breeding pairs of Caveolin-1 knockout mice were obtained in order to establish a working colony for experimentation in vivo. Genotyping of offspring was performed, and the procedure for this was optimised.

The culmination of this project was an in vivo inflammatory challenge of nebulised LPS in Caveolin-1 knockout and wild type mice, with prior treatment with dexamethasone, to establish differences between Caveolin-1 knockout and wild type mice. Caveolin-1 knockout mice have been found previously to have an altered pulmonary phenotype

(Razani et al. 2001), and caveolin has been previously implicated in pulmonary diseases involving inflammation, fibrosis and hypertension, among others. In this experiment, bronchoalveolar lavage was used to quantify the immune response in immune cell migration and infiltration, and cytokine production. Serum corticosterone levels were assayed to see the effect on levels of circulating corticoid hormone. Tissue samples were taken and RT-qPCR was used to investigate gene transcription, as well as Western blot for alteration in signalling proteins, and histochemical analysis. Other tissues were also collected for further assays by other means, such as mass spectrometry or a bioplex assay, and preserved for later investigation.

3.1 Verification of previous findings and Experimental optimisation of procedures to investigate GR and caveolin interaction

3.1.1 Verification of GR signalling in A549, Matthews et al. (2008)

Figure 3-1 Glucocorticoid response in A549 cells

A) and B) Phosphorylation of glucocorticoid receptor (ser211) and PKB/Akt in A549 cells in response to treatment with Dexamethasone. Human lung alveolar basal epithelial adenocarcinoma cell line. A549 cells at 90% confluency in media with 10% charcoal stripped serum (CSS) were treated with 100nM dexamethasone for 10, 20, 30, 40 and 60 min, or just media (0 min) before lysis in RIPA buffer. A) Standardised samples were analysed by western blot for levels of glucocorticoid receptor (GR), phosphorylated GR (pGR, at serine 211), Protein Kinase B (PKB/Akt) and phosphorylated PKB/Akt (pPKB). B) Densitometry was performed to quantify levels of GR, pGR and pPKB, relative to PKB/Akt. C) Real-time Q-PCR analysis of RNA transcripts from A549 in response to in vitro dexamethasone (100 nM) treatment for 0, 15 and 240 minutes, measuring GILZ and FKBP5 transcription. A549 cells at 90% confluency were treated then lysed using RLT buffer, RNA was extracted, samples were standardised, reverse transcribed and Real-time Quantitative PCR (qPCR) was performed to 84

quantify levels of expression of targets GILZ and FKBP5, with SYBR green fluorescence detection. Graphs depict average fold change in expression per treatment, calculated as ΔΔCT relative to GAPDH and untreated condition, with error bars showing standard deviation from the mean and n=2.

In A549 human adenocarcinoma cells, a reportedly glucocorticoid-responsive cell line, (Matthews et al. 2008) found rapid phosphorylation of PKB and GR phosphorylation with dexamethasone. To establish a baseline reference for glucocorticoid response, in A549 cells, an attempt was made to reproduce these findings and also look at how dexamethasone affects reportedly glucocorticoid responsive genes FKBP5 and GILZ, this is shown in figure3-1. Following dexamethasone treatment in A549 cells, phosphorylated glucocorticoid receptor levels increased by 3.7-fold up to 60 mins, as reciprocal total glucocorticoid receptor levels decreased by around 2-fold. Levels of phosphorylated PKB/Akt also increased over time following glucocorticoid receptor activation, although levels were initially high, it decreased 11-fold between 0-10 min, then increased 13-fold from 10-60 min, due to this high initial level at 0 min there was only a 1.2 fold increase between 0 and 60 min. Over time, transcription of GILZ and FKBP5 was increased in response to dexamethasone treatment, with GILZ increasing 2.25-fold at 15 min and 26- fold after 240 min, and FKBP5 increasing 0.1-fold after 15 min and 1.44-fold after 240 min. These results reinforce the previous findings.

3.1.2 Experimental optimisation of procedures to investigate GR and caveolin interaction A number of techniques were used to establish the relationship between caveolin and glucocorticoid receptor signalling, such as Western blotting, immunofluorescence microscopy, and the use of expression vectors to introduce protein expression into cell systems. These techniques involve the use of reagents that may have varying qualities and that need to be optimised. For example, different antibody dilutions were assayed to achieve a clearer Western blot image (not all presented here). Following from the results in section 3.1, after optimisation of conditions, the results presented in sections 3.2 to 3.4 present novel findings.

3.1.3 Optimisation of antibodies to caveolin

Figure 3-2 Caveolin antibodies raised in goat, comparison in MEFs

Comparison of antibodies raised in goat for different isoforms of caveolin, in MEFs transfected Cav myc RFP expression vector, showing detection of Cav-1 and Cav-2 isoforms Caveolin-1 knockout cells were transfected with caveolin using a vector of Cav myc RFP. Wild type (WT), Caveolin-1 knockout (KO) and Transfected cells at 90% confluency were lysed (Bicine buffer) A) Standardised samples were analysed by western blot for levels of Caveolin, using antibodies raised in goat against isoforms 1, 2 and 3 of caveolin, and antibody raised in rabbit against caveolin 1 B) Densitometry was performed to quantify relative levels of Caveolin detection, minus background

Antibodies to different isoforms of caveolin are available, raised in different animal hosts. These may have different performance characteristics in western blotting and other experimental techniques. In figure 3-2, Caveolin antibodies raised in goat were compared to the rabbit caveolin-1 antibody sc894, to establish efficiency of these new antibodies. Sc894 has been used in the majority of the experiments here and had previously been verified, and therefore was taken as the standard. The goat caveolin 1 antibody picked up caveolin 1, but weakly in comparison to sc894, with an optical density (OD) of 6.5 compared to 145 with sc894, approximately 5% of the standard. Staining was increased in transfected cell lysates. The goat caveolin 2 antibody detected Cav2 in all three cell types at similar levels, with ODs of 72 in WT, 71 in KO and 68 in transfected. Caveolin 3 was not measurably detected, as would be expected. In later experiments, the concentration of the goat Cav-2 antibody was reduced by half (1:1000 to 1:2000) to limit background, and the goat Cav-1 antibody was increased to elicit a clearer signal (1:1000 to 1:750), shown in figure 3-3.

Figure 3-3 Caveolin antibodies, tissue comparison

Tissue comparison for GR and caveolin isoforms (using goat- and rabbit-derived antibodies) with α-tubulin and β-actin loading control in tissues taken from wild type mice showing differing levels of caveolin isoforms Lung, liver, brain and gut tissue samples taken from wild type mice were snap frozen, homogenised and protein extracted. A) Standardised samples were analysed by western blot for levels of glucocorticoid receptor (M20 GR), phosphorylated GR (serine 211) and Caveolin, using antibodies raised in goat against isoforms 1, 2 and 3 of caveolin (Gt Cav1, Gt Cav2 and Gt Cav3), and antibody raised in rabbit against caveolin 1 (Cav1 (rb)), α-tubulin and β-actin B) Densitometry was performed to quantify levels of GR, p211 GR, Caveolin isoforms and β-actin, relative to tubulin

Caveolin is thought to be differentially expressed in different tissues of the body. In figure 3-3, caveolin antibodies raised in rabbit and goat to the different isoforms of caveolin, 1, 2, and 3, as well as antibodies to glucocorticoid receptor were used to assay relative levels in mouse tissues taken from the lung, liver, brain and gut, as well as establishing the efficacy of the goat-derived antibodies. This shows differing relative abundances of isoforms in different tissues, with high caveolin staining in the lung. In figure 3-3 optical density is relative to tubulin. Lung tissue has measurable levels of two of the three caveolin isoforms probed, with OD of 1.2 for sc894 Cav1, 0.9 for gtCav1 and 1.2 for gtcav2, and glucocorticoid receptor at 0.96. Liver and brain tissues also have detectable levels of GR and caveolin 1 and 2, although this is not as high as in the lung tissue (OD GR 0.8 liver, 0.9-fold lower than lung, 0.4 brain, 0.5-fold lower; sc894 Cav1 0.7 liver, 0.6 brain, both 0.6-fold lower than in lung). The goat-derived caveolin 1 antibody did not detect much caveolin 1 compared to the rabbit-derived caveolin 1 antibody, OD 0.9 vs 1.2 in lung, which is 1.2-fold lower, OD 0.1 vs 0.7 in liver, which is 5-fold lower, and 0.1 vs 0.6 in brain which is 8-fold lower. Caveolin 3

was not strongly detected in any of the tissues here, with OD of <0.06. The protein extracted from gut tissue appears to have been degraded as no clear bands are measurable. β-actin appeared to have varying levels of expression in the different tissues with OD from 0.5 in lung to 0.1 in liver.

3.1.4 Transfection optimisation

Figure 3-4 Comparison of hCav1 and Cav myc RFP transfection

Embryonic Fibroblast cells from wild type and Caveolin-1-knockout mice, transfected with Caveolin-1, comparison of transfection of caveolin using hCav1 and Cav myc RFP expression vectors in MEF cells in vitro showing varying levels of transfection. Caveolin-1 knockout MEF cells were transfected with caveolin using a vector of human caveolin 1 with red fluorescent protein (RFP) (Cav1 myc RFP), or human caveolin 1 (hCav1), or empty vector. Wild type MEF (WT), Caveolin-1 knockout (KO), and transfected cells at 90% confluency in CSS media were lysed with RIPA buffer. A) Standardised samples were analysed by western blot for levels of glucocorticoid receptor (M20 GR), Caveolin and α- tubulin. B) Densitometry was performed to quantify levels of GR and caveolin, relative to tubulin.

Two different caveolin vectors were available to transfect into the caveolin knockout MEF cells, hCav1 and RFP-conjugated caveolin 1 (Cav myc RFP), in order to rescue caveolin-1 expression in these cells. There appeared to be a difference in the transfection efficiency of these two constructs, shown in figure 3-4, as caveolin was detected in the lysates of transfected cells, at different abundances. Levels of Cav myc RFP were similar to levels of caveolin in WT mice, with OD of 1.6 in both. Recovery of caveolin expression with hCav1 was approximately a third of that achieved with Cav myc RFP, at OD 0.6 with hCav1, this corresponds to caveolin levels ~3-fold lower than wild type.

Figure 3-5 Transfection time course

Mouse Embryonic Fibroblast cells from Caveolin-1-knockout mice, transfected with Caveolin using hCav1 and Cav myc RFP expression vectors showing change in efficiency with time MEF cells from caveolin knockout mice were transfected with hCav1 or Cav myc RFP expression vectors for 24, 48 and 72 h, or with an empty vector as control, before lysis with RIPA buffer. A) Standardised samples were analysed by western blot for levels of Caveolin, GR (M20 GR) and α-tubulin. B) Densitometry was performed to quantify levels of GR and Caveolin, relative to tubulin

The efficiency of caveolin rescue with transfection to Caveolin-1 KO MEF cells had been variable across experiments, and it was possible that increasing the length of time the transfected cells are incubated with the expression vector may increase the level of recovery in caveolin expression, as shown in figure 3.5. Longer durations of transfection incubation resulted in higher protein expression levels detected, with lowest levels at 24h (hCav1 OD 0.85, ~16-fold increase, RFP 0.64 ~12-fold increase) and highest at 72h (hCav1 OD 0.95, ~20-fold increase; RFP 0.90, ~18-fold increase). Increase was linear but not exponential. In this experiment, levels of Cav myc RFP expression were lower than hCav1 expression, contrary to previous findings.

3.1.5 Caveolin-1 knockdown with siRNA

Figure 3-6 siRNA against caveolin1 in A549 and MEFs

Transfection of A549 and Mouse Embryonic Fibroblast cells from wild type mice using siRNA against Caveolin-1 for 24, 48 and 72h showing varying levels of inhibiton of caveolin expression. Human alveolar adenocarcinoma cell line A549 cells (A549) and wild type MEFs were transfected with siRNA directed against Caveolin-1 or AllStars negative control siRNA, using Lipofectamine RNAIMAX transfection reagent, following the supplied protocol to give final concentration of 10 nM siRNA on cells. Transfections were incubated for 24, 48 and 72h before lysis with RIPA buffer. A) Standardised samples were analysed by

western blot for levels of Caveolin, GR (M20 GR) and α-tubulin. B) Densitometry was performed to quantify levels of GR and Caveolin, relative to tubulin

As it appeared that rescue of caveolin expression in Cav KO MEFs via transient transfection was difficult to achieve with consistent results, it was assayed whether was possible to knock down caveolin expression in wild type MEFs using siRNA transfection, with a view to using this in other experimental procedures to study GR-caveolin interactions. In figure 3.6, A549 cells responded well to caveolin knockdown, although this was not 100% reduction in expressed protein (OD at 24h 0.50 for control, 0.05 for siRNA) which corresponds to a 9- fold reduction. Over time, overall caveolin expression in A549s decreased with longer incubation times in control-treated (OD 48h 0.27, 72h 0.14) and those with siRNA against Caveolin-1 (OD 48h 0.04, a 6-fold reduction; 72h 0.03, a ~4-fold reduction). MEFs were much less responsive to caveolin knockdown, with maximal response at 72h in OD showing approximately 25% reduction in expression compared to levels in control siRNA treated cells at the same time point (OD 0.59 in MEFs), but which corresponds to only a ~1.4-fold reduction. Additionally, it appears that the M20 GR antibody is much more specific to mouse GR than human GR, as there was a much higher signal in MEFs in comparison to A549 (average OD 0.19 in A549, 1.3 in MEF, around 7-fold higher). This technique was not expanded in other experimental procedures, although it had been used in other cell lines to investigate GR-caveolin interaction, as caveolin knockdown in MEFs was deemed insufficient to have had a clear effect on signalling.

3.1.6 Optimising Immunofluorescence to visualise Caveolin and GR in fixed Cav-1 KO and WT MEFs

Figure 3-7 Immunofluorescence in fixed cells, hCav1 transfection, antibodies to GR (GR8E9) and Cav1 (sc7875 sc894)

Immunofluorescent microscopy of Mouse Embryonic Fibroblast cells from wild type and Caveolin-1-knockout mice, transfected with caveolin, showing poor specificity in antibody staining Wild type, caveolin knockout, and hCav1 transfected cells at 90% confluency in 10% CSS media on glass coverslips were treated with 100nM dexamethasone for 60 min, or vehicle, before fixing with 4% paraformaldehyde and permeabilization with Triton X. Coverslips were incubated with antibodies to caveolin (A) sc7875, and B) and C) sc-894, and GR (GR8E9, A,B and C), with fluorescent secondary (Alexa-Fluor anti-mouse 488, and anti- rabbit 546). Transfected cells were incubated with antibody to GR (M20) and fluorescent secondary. Nuclei were counterstained with Hoechst. Images were taken on a fluorescent confocal microscope, deconvolved and Z stacks produced. A) and B) WT MEFs C) Cav KO MEFs transfected with hCav1 92

In Figure 3-7, cells were probed with antibodies to GR (GR8E9) and two caveolin antibodies, sc894 and sc7875, and with caveolin transfection with human caveolin 1 (hCav1) in order to assess the suitability of these antibodies for immunofluorescence. The top panel, 3-7A, labelling GR with GR8E9 and Cav-1 with sc7875 shows lack of specificity for either target. The structure of the cell can be seen as autofluorescence at maximum exposure to maximise the signal. In panel 3-7B, wild type cells, staining for caveolin-1 can be seen with sc894. The lower image of this again shows autofluorescence in maximum exposure in the green channel, not GR. In the bottom panel, 3-7C, CavKO cells were transfected with hCav1. In the top image in C, antibody staining at the Golgi body with the caveolin antibody can be seen at high exposure settings. In the bottom panel of C, there is evidence of caveolin transfection and this appears to be concentrated on one side of the cell. This experiment also acts as confirmation of the transfection efficiency for one of the QPCR experiments (QPCR experiment 5). Western blotting was also used to confirm transfection efficiency for this experiment (shown in Figure 3-27).

Figure 3-8 Immunofluorescence fixed cells, transfection of Cav myc RFP Immunofluorescent microscopy of Mouse Embryonic Fibroblast cells from wild type and Caveolin-1-knockout mice, transfected with RFP-conjugated caveolin, showing staining with antibodies to Caveolin-1 and glucocorticoid receptor Wild type, caveolin knockout, and Cav1 myc RFP transfected cells at 90% confluency on glass coverslips in 10% CSS media were treated with 100 nM dexamethasone for 60min, or vehicle, before fixing with 4% paraformaldehyde and permeabilization with Triton X. Coverslips were incubated with antibodies to caveolin (sc-894) and GR (GR8E9), with fluorescent secondary (Alexa Fluor 94

anti-mouse 488, and anti-rabbit 546). Transfected cells were incubated with antibody to GR (M20) and fluorescent secondary. Nuclei were counterstained with Hoechst. Images were taken on a fluorescent confocal microscope, deconvolved and Z stacks produced. A) WT MEFs B) Cav KO MEFs, C) Cav KO MEFs transfected with Cav myc RFP

Figure 3-8, shows antibody staining with GR and RFP-conjugated Caveolin expression, but not co-staining for GR and Cav-1.Caveolin is effectively labelled with the sc-894 antibody, in the wild type cells (3-8A) this is seen as a speckling near the cell membrane, and some banding. In Caveolin-1 knockout cells (3-8B) the anti-caveolin antibody shows staining the Golgi apparatus at high exposure, as before in figure 3-7. GR8E9 shows a speckled pattern throughout the cells, but does not translocate with dex indicating a lack of specificity. In (3- 8C), transfection with Cav myc RFP is present and RFP-Cav1 can be seen expressed in some of the cells, these images are representative. In the transfected cells the GR antibody M20 was used. This gave a clean result showing diffuse spread of GR in the cytoplasm of untreated cells, which translocated to the nucleus with dexamethasone treatment. This experiment is confirmation of caveolin transfection for one of the QPCR experiments (QPCR experiment 4). M20 GR antibody cannot be used alongside sc894 for staining caveolin as they are raised in the same species and will have cross-reactivity.

Figure 3-9 Immunofluorescence fixed cells, Cav1 (goat ab) and M20 GR Immunofluorescent microscopy of Mouse Embryonic Fibroblast cells from wild type and caveolin-knockout mice, transfected with caveolin, with antibodies to caveolin and glucocorticoid receptor and treated with dexamethasone Caveolin knockout MEF cells were transfected with caveolin using a vector of human caveolin 1 (hCav1), or empty vector. Cells were seeded to glass coverslips and wild type, caveolin knockout, and transfected cells at 90% confluency in 10% CSS media were treated with 100nM 96

dexamethasone for 60 min, or vehicle, before fixing with 4% paraformaldehyde and permeabilization with Triton X. Coverslips were incubated with antibodies to caveolin (derived from goat) and GR (M20GR), with fluorescent secondary (Alexa-Fluor anti-goat 488, and anti-rabbit 546). Nuclei were counterstained with Hoechst. Images were taken on a fluorescent confocal microscope, deconvolved and Z stacks produced. A) WT MEFs B) Cav KO MEFs, C) Cav KO MEFs transfected with hCav1. Unlike figures 3-8 & 3-9, here GR is red and caveolin is green, as the anti-goat secondary antibody is Alexa Fluor 488.

In order to visualise caveolin alongside GR, the M20 GR antibody, which had shown specific staining in the previous figure 3.8, was used alongside antibody to caveolin 1, raised in goat shown in figure 3.9. The goat caveolin antibody was used to avoid species cross-reactivity in antibody detection. AlexaFluor 488 signal of gtCav1 antibody showed diffuse speckling through all cell types, including CavKO, indicating non-specific staining. GR staining with M20 showed diffuse staining in untreated cells, with translocation to the nucleus in dexamethasone treated cells and strong staining at lamellipodia, indicating specificity. In later experiments the dilution of the anti-goat fluorescent secondary antibody was reduced to limit this non-specific signal detection.

3.1.7 Quenching of autofluorescence using infrared radiation and Sudan Black B staining Lung and liver tissues have a high level of autofluorescence, which can lead to high amounts of background fluorescence and make it difficult to distinguish specific signals from antibody labelled proteins in fluorescence microscopy (See figure 3-10). Two solutions to quench autofluorescence identified by Viegas et al., 2007, were the use of treatment with ultraviolet (UV) radiation, or a solution of the dye Sudan Black B prior to antibody detection.

3.1.7.1 Autofluorescence levels in lung

Figure 3-10 Autofluorescence in mouse lung

Mouse lung showing autofluorescence across blue, green and red excitation and emission spectra Wild type mouse lung sections, fixed inflated by perfusion with 4% paraformaldehyde, and mounted in paraffin. Magnification (A) x20 (B) x40. Sections shown with and without Hoechst nuclear counterstain, no antibody labelling. Fluorescence detected across the spectra shows the lung tissue architecture. Hoechst stain (blue) appears to cause diffuse background “haze” so later experiments switch to DAPI counterstain for clearer signal.

To establish the base level of autofluorescence in lung, tissue sections were stained only with Hoechst DNA counterstain for nuclei, or unstained and viewed on a fluorescent microscope. At red, blue and green wavelength absorption and emission spectra, it is possible to see the structure of the tissues in figure 3-10. This is due to autofluorescence, as only nuclei have been stained.

3.1.7.2 Quenching of autofluorescence in mouse Lung, with antibody labelling of the glucocorticoid receptor

Figure 3-11 Quenching of Autofluorescence in mouse lung Quenching of autofluorescence using infrared radiation and Sudan Black B staining, with antibody labelling of the glucocorticoid receptor in mouse Lung Wild type mouse lung sections, fixed inflated by perfusion with 4% paraformaldehyde. Sections were mounted in paraffin and exposed to either UV radiation (B), a solution of Sudan Black B in ethanol (C), or both UV radiation and Sudan Black B (D). Untreated sections are presented as a control 99

(A) to show background autofluorescence. Exposure to UV is prior to antibody staining and Sudan Black B after antibody staining. The upper panel of each condition shows no antibody staining, and the lower panel shows labelling using antibodies to glucocorticoid receptor, with Alexa Fluor 594 fluorescent secondary antibody (red), with nuclear counterstaining with DAPI on all sections. Images were collected on the blue, green and red emission spectra (DAPI, Ex. BP350/350, Em. BP460/50; FITC Ex. BP480/40, Em. BP535/50; Texas red, Ex. BP560/55, Em. BP645/75), and processed to merge the images. X20 magnification.

Two methods were used to quench autofluorescence in lung tissue using Sudan Black B and UV radiation to achieve a clearer signal for fluorescent antibody labelling. Figure 3-11 shows this, with antibody staining for GR. In untreated sections, there is a moderate level of background autofluorescence at all wavelengths, which is reduced in the Sudan Black B treated sections. UV irradiation appears to have increased the level of autofluorescence. In sections treated first with UV radiation followed by Sudan Black B staining, the Sudan Black B staining was not sufficient to counteract the increased levels of fluorescence that appear to have come from the UV irradiation, being brighter on both blue and red channels compared to Sudan Black B staining alone. Levels of background fluorescence in these double-treated sections is similar to the untreated control, although the green channel has reduced fluorescence. DAPI staining for nuclei seems to be more specific and “cleaner” than the Hoechst staining used in the previous figure (Fig 3-10). In these sections, there was also antibody labelling of the glucocorticoid receptor with Alexa Fluor 594 secondary labelling. This is detected in the red channel (Texas red), and is visible in the untreated sections with some background interference, quite clear in the Sudan Black B stained sections, and almost indistinguishable from the background in the UV irradiated sections. It is also apparent that red blood cells have a high level of autofluorescence, as these can be seen in the lumen of the blood vessel.

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3.1.7.3 Quenching of autofluorescence in mouse Liver, with antibody labelling of the glucocorticoid receptor

Figure 3-12 Quenching autofluorescence in mouse liver Quenching of autofluorescence using infrared radiation and Sudan Black B staining, with antibody labelling of the glucocorticoid receptor in mouse Liver. Wild type mouse liver fixed in 4% paraformaldehyde. Sections were mounted in paraffin and exposed to either UV radiation (B), a solution of Sudan Black B in ethanol (C), or both UV radiation and Sudan 101

Black B (D). Untreated sections are presented as a control (A) to show background autofluorescence. Exposure to UV is prior to antibody staining and Sudan Black B after antibody staining. The upper panel of each condition shows no antibody staining, and the lower panel shows labelling using antibodies to glucocorticoid receptor, with Alexa Fluor 594 fluorescent secondary antibody (red), with nuclear counterstaining with DAPI on all sections. Images were collected on the blue, green and red emission spectra (Filter sets – DAPI, Ex. BP350/350, Em. BP460/50; FITC Ex. BP480/40, Em. BP535/50; Texas red, Ex. BP560/55, Em. BP645/75), and processed to merge the images. X20 magnification.

Liver tissue, like lung tissue, shows high levels of autofluorescence. Liver tissue sections in figure 3-12 received the same treatment as figure 3-11 (above), i.e. untreated, Sudan Black B alone, UV irradiation, and UV irradiation with Sudan Black B staining. The effect of these is similar to the above figure 3-11, with UV irradiation appearing to increase background fluorescence and Sudan Black B staining to reduce it. In 3-12(A), the exposure settings were set to the brightest area of the field. In the top row which has no antibody the red background is very high, whereas the row below, the brightest area of the field is the red antibody-labelled GR, which comes through clearer, and the background autofluorescence appears less. This means that caution must be used when selecting exposure settings to increase clarity of specific signals and to limit background interference. In later experiments, the same exposure settings were used for all sections.

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3.1.7.4 Imaging of autofluorescence across different excitation and emission spectra

Figure 3-13 Comparison of autofluorescence quenching across different spectra Imaging of lung autofluorescence across different excitation and emission spectra, Quenching of autofluorescence using infrared radiation and Sudan Black B staining, with 103

antibody labelling of the glucocorticoid receptor Wild type mouse lung sections, fixed inflated by perfusion with 4% paraformaldehyde. Sections were mounted in paraffin and exposed to either a solution of Sudan Black B in ethanol (C), UV radiation (D), or both UV radiation and Sudan Black B (E). Exposure to UV is prior to antibody staining and Sudan Black B after antibody staining. In (A) there is no antibody staining, in (B, C, D, E) Primary antibody is to the glucocorticoid receptor, with Alexa Fluor 594 secondary. DAPI counterstain for nuclei in all sections. Images collected sequentially at different wavelengths of light, to indicate at which the largest amount of autofluorescence is observed. The lowest amount of autofluorescence can be seen using the CY5 channel. Merge is processed from DAPI (blue), FITC (green) and each of the three red channels, Texas red, CY3 and CY5 (Filter sets – DAPI, Ex. BP350/350, Em. BP460/50; FITC Ex. BP480/40, Em. BP535/50; Texas red, Ex. BP560/55, Em. BP645/75; Cy3, BP545/30, Em. BP610/75; Cy5, Ex. BP620/60, Em. BP700/75). X20 magnification.

Some of the snapshot microscopes available are capable of producing and recording excitation and emission spectra at different wavelengths, in the channels CY3 and CY5 further toward the far red end of the spectrum. As autofluorescence had been recorded across the usual channels of red, green and blue, to varying degrees (see preceding figures 3-11 3-12), the opportunity was used to see if there was a variation in autofluorescence across the available spectra. In figure 3-13, autofluorescence appears to come through least on the DAPI, FITC and CY5 channels. Quenching of autofluorescence on the FITC and DAPI channels is achieved by Sudan Black B staining. In the Texas red channel (Ex. BP560/55, Em. BP645/75) as for Alexa Fluor 594 secondary antibody, there is a high level of autofluorescence, which is not quenched by Sudan Black B staining, making it difficult to distinguish specific signal from the background. Quenching does not appear to occur on the CY3 channel sufficiently to enable this wavelength to be used for antibody staining.

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3.2 Characterisation of Cav-1 KO and Wild Type MEF response to Glucocorticoid treatment in vitro, and Lipid raft disruption in live cell

3.2.1 Western Blots of signalling proteins

Figure 3-14 Western blot for signalling protein phosphorylation, 10 min dexamethasone Mouse Embryonic Fibroblast cells from wild type and Caveolin-knockout mice, transfected with Caveolin, with in vitro treatment with dexamethasone, showing alteration in phosphorylation of signalling proteins Caveolin knockout cells were transfected with caveolin using a vector of human caveolin 1 (hCav1) or empty vector. Wild 105

type (WT), Caveolin knockout (KO) and Transfected cells at 90% confluency in 10% CSS media were treated with 100 nM dexamethasone for 10 min, or vehicle (0 min) before lysis (Bicine buffer). A) Standardised samples were analysed by western blot for levels of glucocorticoid receptor (M20 GR), phosphorylated GR (serines 211 and 203, p211 and p203 GR), Protein Kinase B (PKB/Akt), phosphorylated PKB/Akt (pPKB), phosphorylated p44/42 MAPK (ERK1/2), phosphorylated p54- and p46-SAPK/JNK, phosphorylated GSK3β and α- tubulin. B) Densitometry was performed to quantify levels of GR, p211 GR, p203 GR, PKB/Akt and pPKB, phospho-p44/42MAPK, phosphorylated p54- and p46-SAPK/JNK and pGSK3β, relative to α-tubulin.

Figure 3-15 Confirmation of caveolin transfection

Blot to quantify Caveolin transfection for experiment in Figure 3-14 A) Untreated standardised samples were analysed by western blot for levels of Caveolin, GR and α- tubulin. B) Densitometry was performed to quantify levels of GR and Caveolin from blot B), relative to α-tubulin.

To investigate whether there is a difference in the response of wild type and caveolin-1 knockout MEF cells to dexamethasone treatment in vitro, and which signalling proteins are involved in the rapid response to dexamethasone, levels of total GR, phosphorylated GR at serines 203 and 211, PKB/Akt and phosphorylated PKB, Phosphorylated SAPK/JNK, Phosphorylated p44/42 MAPK and GSK3β were measured. These levels are depicted in figure 3-14, with caveolin levels in figure 3-15. This shows a difference between the levels of phosphorylated proteins in WT and KO cells, for example pPKB/Akt increased in KO cells but not in WT and GSK3β increased in KO but decreased in WT, a finding that was also found with p46-SAPK/JNK. There were also differences between KO and WT in the magnitude of the change in GR, p44/42 MAPK, p54-SAPK/JNK. Caveolin transfection in KO cells resulted in expression equivalent to about 25% of the wild type caveolin levels detectable by western blot (OD WT 3.7, hCav1 0.96 fold change of ~3.9 lower than WT). In response to dexamethasone treatment, GR was phosphorylated at ser211, and the response appeared to be greater in caveolin knockout cells (OD 0.69 to 0.91, an increase of 0.22 or 1.3-fold increase) compared to WT (OD 0.81 to 0.74, apparently decrease of 0.07, 1.09-fold). The p211 GR response in transfected cells was also greater 106

than WT (OD 0.55 to 0.88, increase of 0.33 or 1.6-fold). The levels of GR phosphorylated at serine 203 appeared to be higher in knockout and transfected cells compared to WT in the untreated condition, although densitometry analysis relative to tubulin found only small variation (untreated for all OD ~1.36, WT decrease of 0.11, around 1-fold; KO increase of 0.04, 0.97-fold; hCav1 increase of 0.06, 1.05-fold). Levels of phosphorylation of PKB/Akt in response to dex were higher in KO cells with an OD of 0.25 rising to 0.40, 1.6-fold increase, in comparison to WT OD 0.22 which did not change with dex. An increase also present in transfected cells at OD 0.23 rising to 0.39, fold change 1.7. WT cells had the highest basal level of phosphorylated p44/42-MAPK. There was a greater difference in phosphorylation of p44/42-MAPK between WT treated and untreated cells (OD 1.92 to 1.62, a decrease of 0.3 or ~1.2-fold) compared to KO (1.1-fold decrease compared to KO), although there was also a difference in treated compared to untreated KO cells, this was much smaller (OD 1.56 to 1.39 a decrease of 0.17 or 1.02-fold), transfected cells appeared to have little difference in levels in response to treatment relative to tubulin (OD decrease of only 0.04). WT cells had the highest level of phosphorylated p46-SAPK/JNK (OD WT 1.54 in comparison to 1.01 and 1.10 in KO and hCav1 respectively), and levels of this increased in KO cell types in response to dex (KO OD increased by 0.13, 1.12-fold, and hCav1 by 0.08, 1.07-fold), whereas there was a decrease in WT (OD decrease of 0.13, 1.08-fold). There was more of a response increasing levels of phosphorylated p54-SAPK/JNK in KO and transfected cells compared to WT (WT OD increased by 0.03, 1.03-fold, in comparison to 0.21 and 0.20 in KO 1.26-fold, and hCav1 1.22-fold). Looking at the blots, it appears that levels of phosphorylated GSK3β increased in response to dex in all cell types, although the levels were not very different from the untreated condition, however the densitometry analysis shows that change in OD in WT was -0.11, 1.08-fold decrease, whereas KO increased by 0.08, 1.08-fold increase, and hCav1 by 0.14, 1.13-fold increase. WT had higher basal levels of GSK3β OD 1.38, compared to 1.08 and 1.09 in KO and hCav1. This experiment occurred in tandem with qPCR experiment 6.

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Figure 3-16 Dexamethasone time course, immunoblot for GR phosphorylation Mouse Embryonic Fibroblast cells from wild type and Caveolin-knockout mice, transfected with Caveolin, with in vitro treatment with dexamethasone, showing changes in phosphorylation of the glucocorticoid receptor over time. Caveolin knockout cells were transfected with caveolin using a vector of human caveolin 1 with red fluorescent protein (RFP) (Cav1 myc RFP), or empty vector. Wild type, Caveolin knockout, and transfected cells at 90% confluency in 10% CSS media were treated with 100nM dexamethasone for 10, 20, 30, 40 and 60 min, or just SFM (0 min) before lysis (Bicine buffer). A) WT MEFs vs. Cav KO MEF, B) Cav KO MEF vs. Cav KO MEF transfected with Cav myc RFP. Standardised samples were analysed by western blot for levels of glucocorticoid receptor (M20 GR), phosphorylated GR (serines 211 and 203, p211 and p203 GR), caveolin, and α-tubulin. Densitometry was performed to quantify levels of GR, p211 GR, p203 GR, relative to tubulin.

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Figure 3-17 Caveolin transfection confirmation for dexamethasone time course

Caveolin densitometry result for the experiment shown in Figure 3-16. Caveolin knockout cells were transfected with caveolin using a vector of human caveolin 1 with red fluorescent protein (RFP) (Cav1 myc RFP), or empty vector. Wild type, Caveolin knockout, and transfected cells at 90% confluency in 10% CSS media were treated with 100nM dexamethasone for 10, 20, 30, 40 and 60 min, or just SFM (0 min) before lysis (Bicine buffer). A) WT MEFs vs. Cav KO MEF, B) Cav KO MEF vs. Cav KO MEF transfected with Cav myc RFP. Standardised samples were analysed by western blot for levels of caveolin and α- tubulin (shown above). Densitometry was performed to quantify levels of caveolin, relative to tubulin.

Wild type and caveolin knockout MEFs appear to have a different response in rapid signalling events within 10 min of dex treatment via phosphorylation of the glucocorticoid receptor, as shown in Figure 3-14. To see if this pattern is borne out over a longer time period, the change in levels of GR phosphorylation were measured over 0-90 min exposure to dex, as shown in Figure 3-16, with levels of caveolin shown in Figure 3-17, showing a difference in signalling profiles between Cav-1 KO and WT cells. Wild type and Cav KO cells both had phosphorylation of the glucocorticoid receptor at serines 203 (p203-GR), and 211 (p211-GR). Levels of GR phosphorylated at ser211 (p211-GR) increased over 90 min, with a similar increase in WT (OD increase +0.58), KO (OD increase +0.55) and transfected (OD increase +0.53), which corresponds to a fold increase of ~8.4-fold for WT, 6.4 and 10.4-fold increase in KO (different blots) and 10.5-fold increase in transfected. Whereas levels of p203-GR appeared to peak around 20-30 min and drop off (maximal at 20 min OD increase WT +0.33, KO +0.24, hCav1 +0.14). Levels of p203-GR were higher in KO vs. WT cells (basal OD WT 0.6, KO 0.74) although the maximal OD for both was similar (~0.93), as was the fold increase (WT 1.6-fold, KO 1.3-1.4-fold, hCav1 1.2-fold). Levels of total GR appear to decrease after 30 min of treatment in WT cells by around 2-fold, whereas this is not seen as strongly in KO cells where the total GR at 90 is around the same as at 0 min. In Cav KO cells transfected with caveolin, the caveolin rescue is approximately 25-30% of the caveolin 109

levels detected in WT cells when blotting for caveolin. The pattern of GR phosphorylation is similar between KO and transfected cells. After 20 min, levels of p211-GR appeared to be higher in WT than KO cells (WT OD 0.52, KO 0.46), whereas levels were higher at 10 and 15 min in KO cells (10 min OD WT 0.15, KO 0.18; 15 min WT 0.32, KO 0.36), indicating that KO cells reached a maximal earlier than WT although the maximal was lower. In figure 3-16B, levels of p203-GR followed a similar curve as in 3-16A, peaking at 20-30 min then decreasing. Although levels appeared slightly higher in the transfected condition over KO, the fold change was less at 1.3-fold for KO and 1.2-fold for hCav1 at maximal, and there was a greater increase at 90 min in transfected compared to KO. Levels of total GR also appeared slightly higher in the transfected cells.

3.2.2 Real-time Quantitative PCR (RT-qPCR) analysis of responses to dexamethasone in vitro To see if there is a variation in the expression of GILZ, Zfand5, Ptchd1,MT1, Stc1, Cdh11, Runx1t1, Glul and RpS6 real-time quantitative PCR was performed to establish mRNA transcription following dexamethasone treatment, and to establish if there is variability in cells with and without caveolin.

3.2.2.1 Glucocorticoid-induced Leucine Zipper

Figure 3-18 RT-QPCR GILZ expression

Real-time Q-PCR analysis of RNA transcripts from MEF cells from wild type and caveolin knockout mice with caveolin transfection, in response to in vitro dexamethasone (100 nM) treatment for 0 and 240 minutes, showing induced GILZ transcription Mouse Embryonic Fibroblast (MEF) cells cultured from caveolin knockout mice were transfected with caveolin using a vector of human caveolin 1 (hCav1 or RFP-conjugated hCav1) or empty vector. Wild type (WT), Caveolin-1 knockout (CavKO) and Transfected (KO+Cav)MEF cells at 90% confluency in 10% CSS media were treated with 100 nM dexamethasone for

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240 min, or vehicle (control) before lysis in RLT buffer. RNA was extracted, samples were standardised, reverse transcribed and Real-time Quantitative PCR (qPCR) was performed to quantify levels of expression of target. Primers used were designed from the NCBI published sequence, with SYBR green fluorescence detection. GILZ (TSC22 domain family, member 3 (Tsc22d3), transcript variants 1 and 2) Primers generated by NCBI Primer Blast, primer designed against transcript variant 2, with cross-product only transcript variant 1 (amplicon 128) Forward - GCAGGCCATGGACCTCGTGAAG (22), Reverse - TCAGGAGGGTGTTCTCGCGCT (21). Graph depicts average fold change in expression per treatment, calculated as ΔΔCT relative to β-actin and untreated condition, with error bars showing standard error of the mean. All samples run in duplicate or triplicate, with n=2 per condition and N=5. Caveolin transfection was validated with immunofluorescence or western blot.

GILZ transcription is strongly induced by glucocorticoid treatment in MEF cells cultured from both caveolin knockout and wild type mice, figure 3-18, with WT showing a fold change of 1 compared to 13.8-fold in treated cells and KO at 1.3-fold rising to 14-fold upon treatment. There does not seem to be a large difference between gene expression levels from WT or KO MEF cells, with basal and induced levels being within 1-fold difference between cell types.

3.2.2.2 Zinc finger AN1-type domain 5

Figure 3-19 RT-QPCR Zfand5 expression

Real-time Q-PCR analysis of RNA transcripts from MEF cells from wild type and caveolin knockout mice with hCav1 transfection, in response to in vitro dexamethasone (100 nM) treatment for 0 and 240 minutes, showing induced Zfand5 transcription Mouse Embryonic Fibroblast (MEF) cells cultured from caveolin knockout mice were transfected with caveolin using a vector of human caveolin 1 (hCav1 or RFP-conjugated hCav1) or empty vector. Wild type (WT), Caveolin-1 knockout (CavKO) and Transfected (KO+Cav) MEF cells at 90% confluency in 10% CSS media were treated with 100 nM dexamethasone for 240 min, or vehicle (control) before lysis in RLT buffer. RNA was extracted, samples were standardised, reverse transcribed and Real-time Quantitative PCR (qPCR) was performed to quantify levels of expression of target. Primers used were designed from the NCBI published sequence, with SYBR green fluorescence detection. Zfand5 (zinc finger, AN1-type domain 5) primers generated by NCBI Primer blast (amplicon 146) Forward CCCAGGGCCCATGCTGTGTAG (21), Reverse TGGAACCACTAGCTGTCCCCAT (22). Graph 111

depicts average fold change in expression per treatment, calculated as ΔΔCT relative to β- actin and untreated condition, with error bars showing standard error of the mean. All samples run in duplicate or triplicate, with n=2 per condition and N=5. Caveolin transfection was validated with immunofluorescence or western blot.

Zfand5 transcription is somewhat induced by glucocorticoid treatment in MEF cells cultured from both caveolin knockout and wild type mice, figure 3-19, with a fold-change induction of 1 to 1.75-fold in WT and 1.15-fold to 1.76-fold in KO, which is <1. There does not seem to be a large difference between gene expression levels from WT or KO MEF cells with basal and induced levels approximately equivalent between cell types, within 0.2-fold change.

3.2.2.3 Patched domain containing 1

Figure 3-20 RT-QPCR Ptchd1 expression

Real-time Q-PCR analysis of RNA transcripts from MEF cells from wild type and caveolin knockout mice with caveolin transfection, in response to in vitro dexamethasone (100 nM) treatment for 0 and 240 minutes, showing variation in Ptchd1 transcription between KO and WT and in response to Dex Mouse Embryonic Fibroblast (MEF) cells cultured from caveolin knockout mice were transfected with caveolin using a vector of human caveolin 1 (hCav1 or RFP-conjugated hCav1) or empty vector. Wild type (WT), Caveolin-1 knockout (CavKO) and Transfected (KO+Cav) MEF cells at 90% confluency in 10% CSS media were treated with 100 nM dexamethasone for 240 min, or vehicle (control) before lysis in RLT buffer. RNA was extracted, samples were standardised, reverse transcribed and Real-time Quantitative PCR (qPCR) was performed to quantify levels of expression of target. Primers used were designed from the NCBI published sequence, with SYBR green fluorescence detection. Ptchd1 (Patched domain containing 1) primers generated by NCBI Primer blast (amplicon 154) Forward TGCAGGACTGTGTCCGCAGC (20), Reverse CCATGACCTAGCATGACGAAAGGGA (25). Graph depicts average fold change in expression per treatment, calculated as ΔΔCT relative to β-actin and untreated condition, with error bars showing standard error of the mean. All samples run in duplicate or triplicate, with n=2 per condition and N=4. Caveolin-1 transfection was validated with immunofluorescence or western blot.

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In figure 3-20 there is a difference between gene expression levels from WT or Cav-1 KO MEF cells in Ptchd1 expression, with low levels in WT cells, and much higher levels in untreated cells from Cav-1 KO mice with Cav-1 KO 12-fold higher than WT. In response to glucocorticoid treatment Ptchd1 transcription is reduced in Cav-1 KO MEFs to approximately 50% of untreated expression levels from 12.3-fold to 5.7-fold change. There was no induction in WT cells in response to Dex. The analysis of results from the final Q-PCR experiment have been excluded from this graph, as the induced fold change levels were in the factor of thousands, which skewed the results, although the overall pattern is the same as the above results.

3.2.2.4 Metallothionein 1

Figure 3-21 RT-QPCR MT1 expression

Real-time Q-PCR analysis of RNA transcripts from MEF cells from wild type and Caveolin-1 knockout mice with Caveolin-1 transfection, in response to in vitro dexamethasone (100 nM) treatment for 0 and 240 minutes, showing variation in MT1 transcription between KO and WT and in response to Dex Mouse Embryonic Fibroblast (MEF) cells cultured from Caveolin-1 knockout mice were transfected with caveolin using a vector of human caveolin 1 (hCav1 or RFP-conjugated hCav1) or empty vector. Wild type (WT), Caveolin-1 knockout (CavKO) and Transfected (KO+Cav) MEF cells at 90% confluency in 10% CSS media were treated with 100 nM dexamethasone for 240 min, or vehicle (control) before lysis in RLT buffer. RNA was extracted, samples were standardised, reverse transcribed and Real-time Quantitative PCR (qPCR) was performed to quantify levels of expression of target. Primers used were designed from the NCBI published sequence, with SYBR green fluorescence detection. MT1 (Metallothionein1) Primers generated by NCBI primer blast (amplicon 121) Forward AAGAAGAGCTGCTGCTCCTGCTGTC (25) Reverse GGTGGCAGCGCTGTTCGTCA (20). Graph depicts average fold change in expression per treatment, calculated as ΔΔCT relative to β-actin and untreated condition, with error bars showing standard error of the mean. All samples run in duplicate or triplicate, with n=2 per condition and N=5. Caveolin transfection was validated with immunofluorescence or western blot.

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MT1 transcription is induced by glucocorticoid treatment in MEF cells cultured from both Caveolin-1 knockout and wild type mice, figure 3-21, with WT expression rising to 5.2-fold after treatment. There appears to be a stronger induction in Caveolin-1 knockout cells, compared to wild type cells, with mRNA levels on average twice as high in Cav-1 KO MEFs following dexamethasone treatment, 0.6-fold untreated rising to 10-fold on treatment.

3.2.2.5 Stanniocalcin 1

Figure 3-22 RT-QPCR Stc1 expression

Real-time Q-PCR analysis of RNA transcripts from MEF cells from wild type and Caveolin-1 knockout mice with Caveolin-1 transfection, in response to in vitro dexamethasone (100 nM) treatment for 0 and 240 minutes, showing decrease in Stc1 transcription in response to Dex Mouse Embryonic Fibroblast (MEF) cells cultured from Caveolin-1 knockout mice were transfected with caveolin using a vector of human caveolin 1 (hCav1 or RFP- conjugated hCav1) or empty vector. Wild type (WT), Caveolin-1 knockout (CavKO) and Transfected (KO+Cav) MEF cells at 90% confluency in 10% CSS media were treated with 100 nM dexamethasone for 240 min, or vehicle (control) before lysis in RLT buffer. RNA was extracted, samples were standardised, reverse transcribed and Real-time Quantitative PCR (qPCR) was performed to quantify levels of expression of target. Primers used were designed from the NCBI published sequence, with SYBR green fluorescence detection. Stc1 (Stanniocalcin 1) primers were generated using the NCBI primer blast design tool (amplicon 135). Forward CTCCAAAACTCAGCAGTGATTCT (23), Reverse GAGGCAGCGAACCACTTCA (19). Graph depicts average fold change in expression per treatment, calculated as ΔΔCT relative to β-actin and untreated condition, with error bars showing standard error of the mean. All samples run in duplicate or triplicate, with n=2 per condition and N=4. Caveolin transfection was validated with immunofluorescence or western blot.

Stc1 transcription, figure 3-22, is somewhat decreased following glucocorticoid treatment in MEF cells cultured from both Caveolin-1 knockout and wild type mice, with levels in treated cells approximately 50% of untreated, in WT this is 1 decreasing to 0.5-fold and KO 0.97-fold decreasing to 0.6-fold. There does not seem to be a large difference between gene expression levels from WT or KO MEF cells, although this effect could have been 114

masked by the analysis method ΔΔCT which fixes the level for the reference sample at 1. The analysis of results from the final Q-PCR experiment have been excluded from this graph, as the induced fold change levels in Cav-1 KO cells were in the factor of hundreds, which skewed the results, although the pattern is the same as the above results. Taken alone, one experiment had very little Stc1 mRNA in the Cav-1 KO cells.

3.2.2.6 Cadherin 11

Figure 3-23 RT-QPCR Cdh11 expression Real-time Q-PCR analysis of RNA transcripts from MEF cells from wild type and Caveolin-1 knockout mice with caveolin transfection, in response to in vitro dexamethasone (100 nM) treatment for 0 and 240 minutes, showing no discernable variation in Cdh11 transcription between KO and WT or in response to Dex Mouse Embryonic Fibroblast (MEF) cells cultured from Caveolin-1 knockout mice were transfected with caveolin using a vector of human caveolin 1 (hCav1 or RFP-conjugated hCav1) or empty vector. Wild type (WT), Caveolin-1 knockout (CavKO) and Transfected (KO+Cav) MEF cells at 90% confluency in 10% CSS media were treated with 100 nM dexamethasone for 240 min, or vehicle (control) before lysis in RLT buffer. RNA was extracted, samples were standardised, reverse transcribed and Real-time Quantitative PCR (qPCR) was performed to quantify levels of expression of target. Primers used were designed from the NCBI published sequence, with SYBR green fluorescence detection. Cdh11 (Cadherin 11) primers were generated using NCBI Primer Blast (amplicon 118). Forward GCCGCCGACTTGTGAATGGG (20), Reverse GTAATTTCTGGGGCCGTTGCGG (22). Graph depicts average fold change in expression per treatment, calculated as ΔΔCT relative to β-actin and untreated condition, with error bars showing standard error of the mean. All samples run in duplicate or triplicate, with n=2 per condition and N=4. Caveolin transfection was validated with immunofluorescence or western blot.

Cdh11 transcription, figure 3-23, does not seem to be greatly affected by glucocorticoid treatment in MEF cells cultured from both Caveolin-1 knockout and wild type mice. There is a small decrease on average following dexamethasone treatment of less than 0.1-fold, in KO this is 1.02-fold decreasing to 0.95-fold, and WT is roughly equivalent 1 to 0.97. There does not seem to be a large difference between gene expression levels from WT or KO MEF

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cells with expression levels in all at around 1. The analysis of results from the final Q-PCR experiment have been excluded from this graph, as the induced fold change in WT cells treated with Dex was much higher than the range of results in the other four replicates, which skewed the results, although the pattern is the same as the above results in Cav-1 KO cells.

3.2.2.7 Runt-related transcription factor 1; translocated to 1 (cyclin d-related)

Figure 3-24 RT-QPCR Runx1t1 expression

Real-time Q-PCR analysis of RNA transcripts from MEF cells from wild type and Caveolin-1 knockout mice with caveolin transfection, in response to in vitro dexamethasone (100 nM) treatment for 0 and 240 minutes, showing low variation in Runx1t1 transcription Mouse Embryonic Fibroblast (MEF) cells cultured from Caveolin-1 knockout mice were transfected with caveolin using a vector of human caveolin 1 (hCav1 or RFP-conjugated hCav1) or empty vector. Wild type (WT), Caveolin-1 knockout (CavKO) and Transfected (KO+Cav) MEF cells at 90% confluency in 10% CSS media were treated with 100 nM dexamethasone for 240 min, or vehicle (control) before lysis in RLT buffer. RNA was extracted, samples were standardised, reverse transcribed and Real-time Quantitative PCR (qPCR) was performed to quantify levels of expression of target. Primers used were designed from the NCBI published sequence, with SYBR green fluorescence detection. Runx1t1 (Runt-related transcription factor 1; translocated to 1 (cyclin d-related)) primers were generated using NCBI Primer Blast (amplicon 310), with cross-reactivity across transcript variants 1, 2, and 3. Forward GGCGCTCCCTCACCGCCTAA (20), Reverse GCAGGGGCAGGTTGGCCTTCA (21). Graph depicts average fold change in expression per treatment, calculated as ΔΔCT relative to β-actin and untreated condition, with error bars showing standard error of the mean. All samples run in duplicate or triplicate, with n=2 per condition and N=4. Caveolin transfection was validated with immunofluorescence or western blot.

Runx1t1 transcription, figure 3-24, does not seem to be strongly modified by glucocorticoid treatment in MEF cells cultured from both Caveolin-1 knockout and wild type mice. There is

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a small decrease on average following dexamethasone treatment in Cav-1 KO cells, from 1.5-fold to 1.4-fold change, and an apparent slight increase in wild type cells from 1 to 1.35-fold. In the untreated conditions, Cav-1 KO cells appear to have a slightly greater basal expression level of Runx1t1 in comparison to WT (1 to 1.5). The analysis of results from the final Q-PCR experiment have been excluded from this graph, as the induced fold change in WT cells treated with Dex was much higher than the range of results in the other four replicates, which skewed the results, although the pattern is the same as the above results in Cav-1 KO cells.

3.2.2.8 Glutamate-ammonia ligase

Figure 3-25 RT-QPCR Glul expression

Real-time Q-PCR analysis of RNA transcripts from MEF cells from wild type and Caveolin-1 knockout mice with caveolin transfection, in response to in vitro dexamethasone (100 nM) treatment for 0 and 240 minutes, showing Dex-induced Glul transcription Mouse Embryonic Fibroblast (MEF) cells cultured from Caveolin-1 knockout mice were transfected with caveolin using a vector of human caveolin 1 (hCav1 or RFP-conjugated hCav1) or empty vector. Wild type (WT), Caveolin-1 knockout (CavKO) and Transfected (KO+Cav) MEF cells at 90% confluency in 10% CSS media were treated with 100 nM dexamethasone for 240 min, or vehicle (control) before lysis in RLT buffer. RNA was extracted, samples were standardised, reverse transcribed and Real-time Quantitative PCR (qPCR) was performed to quantify levels of expression of target. Primers used were designed from the NCBI published sequence, with SYBR green fluorescence detection. Glul (Glutamate-ammonia ligase) primers were generated using NCBI Primer Blast (amplicon 152), Forward GCCACCGCTCTGAACACCTTCC (22), Reverse TGCAGCGCAGTCCTTCTCCG (20). Graph depicts average fold change in expression per treatment, calculated as ΔΔCT relative to β-actin and untreated condition, with error bars showing standard error of the mean. All samples run in duplicate or triplicate, with n=2 per condition and N=4. Caveolin transfection was validated with immunofluorescence or western blot.

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Glul transcription is induced by glucocorticoid treatment in MEF cells cultured from both Caveolin-1 knockout and wild type mice, shown in figure 3-25. There is a difference between gene expression levels from WT and KO MEF cells on average, with lower basal levels in untreated Cav-1 KO cells at just over 50% of untreated wild type, at 0.6-fold, and a lower average induction of expression with Cav-1 KO induction approximately two thirds of that seen in WT cells, with WT increasing from 1 to 4.5-fold and KO from 0.6-fold to 2.8- fold. The analysis of results from one Q-PCR experiment have been excluded from this graph, where comparison for ΔΔCT was made to untreated Cav-1 KO cells rather than WT, which resulted in much higher rates of apparent induction in treated cells to approximately 8-9-fold that of untreated.

3.2.2.9 Ribosomal protein S6

Figure 3-26 RT-QPCR RpS6 expression

Real-time Q-PCR analysis of RNA transcripts from MEF cells from wild type and Caveolin-1 knockout mice with caveolin transfection, in response to in vitro dexamethasone (100 nM) treatment for 0 and 240 minutes, showing low variation in Rsp6 transcription Mouse Embryonic Fibroblast (MEF) cells cultured from Caveolin-1 knockout mice were transfected with caveolin using a vector of human caveolin 1 (hCav1 or RFP-conjugated hCav1) or empty vector. Wild type (WT), Caveolin-1 knockout (CavKO) and Transfected (KO+Cav) MEF cells at 90% confluency in 10% CSS media were treated with 100 nM dexamethasone for 240 min, or vehicle (control) before lysis in RLT buffer. RNA was extracted, samples were standardised, reverse transcribed and Real-time Quantitative PCR (qPCR) was performed to quantify levels of expression of target. Primers used were designed from the NCBI published sequence, with SYBR green fluorescence detection. RpS6 (Ribosomal protein S6) primers were generated using NCBI Primer Blast (amplicon 102), Forward TTCTTGGTGAATGGTAGTGG (20), Reverse AACTACCTTCACACCTAAGC (20). Graph depicts average fold change in expression per treatment, calculated as ΔΔCT relative to β-actin and untreated condition, with error bars showing standard error of the mean. All samples run in duplicate or triplicate, with n=2 per condition and N=5. Caveolin transfection was validated with immunofluorescence or western blot.

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RpS6 transcription does not seem to be greatly affected by glucocorticoid treatment in MEF cells cultured from both Caveolin-1 knockout and wild type mice, figure 3-26. There is a small increase on average following dexamethasone treatment, in WT this is 1 rising to 1.06-fold change and KO 1.2-fold rising to 1.3-fold. There does not seem to be a large difference between gene expression levels from WT or KO MEF cells.

3.2.2.10 Transfection of caveolin-1 to Cav-1 KO MEFs and the effect on gene expression In the RT-QPCR experiments shown in figures 3-19 to 3-26, CavKO cells were transfected with vectors of human caveolin-1, either hCav1 or Cav myc RFP, to see if this is capable of rescuing the wild type phenotype and abrogating the difference between Caveolin-1 knockout and wild type cells in gene expression of the targets. In the figures above 3-19 to 3-26, there is very little difference in the average gene expression for Cav-1 KO and transfected cells, with the largest change being an increase of 1.5 in GILZ response in dex treated cells of 14-fold change in KO to 15.5 with caveolin transfection. In most comparisons the change between KO and transfected is less than 0.2, with the mean average of 0.23, with a median of 0.09 and most frequently being no change in the fold- change values between KO and transfected. In the western blot confirmation of transfection (shown in fig. 3-27 below) the rates of transfection are very low, and in one instance not observable at all. In q-PCR experiment 7, the transfection to rescue the expression of caveolin in the Caveolin-1 knockout cells was unsuccessful, despite transfection being 72h, which had been previously shown to be the most effective (Figure 3-5). Western blot densitometry quantitation found around 20-25% of the expression found in wild type. Caveolin transfection was also confirmed using coverslips of transfected cells and immunofluorescent microscopy. For Cav myc RFP transfected cells, a representative sample of images from immunofluorescence showed a level of around 2 transfected cells per 10 visible on images (20%). From the qPCR data it appears that the level of transfection efficiency was insufficient to rescue the wild type phenotype.

Figure 3-27 Caveolin transfection confirmation for RT-QPCR

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Western blotting to establish caveolin transfection efficiency in cell populations for qPCR experiments Cell populations were plated in duplicate for qPCR and western blot analysis from wild type, Cav-1 KO and transfected cells. These were treated with dexamethasone or vehicle for 4h for qPCR and 10 min for western blot before lysis and processing for the respective techniques. Untreated standardised samples were analysed by western blot for levels of Caveolin-1, GR and α-tubulin

3.2.3 Live cell experiments, altering membrane fluidity and its effect on glucocorticoid receptor translocation

Figure 3-28 Live cell GR translocation with disruption of lipid rafts

Live cell experiment measuring time taken for GR to translocate in response to dexamethasone in conditions of high cholesterol, and disruption of lipid rafts showing variation in GR translocation time A549 cells in 10% CSS media, were transfected with Halo-tagged GR and treated overnight with 20ng/ml cholesterol (66µM), 66µM methylcyclodextrin, or 10µM simvastatin. TMR (red) Halo ligand was added and cells were imaged on a microscope with temperature controlled stage, at 37°C with 5-10% CO2. After baseline recordings were taken, 100nM dexamethasone was added and translocation of GR to the nucleus was recorded. Mean time taken for HALO-ligand labelled GR to translocate fully to the nucleus in dexamethasone treated A549 cells, subject to pre-treatment with (B) methylcyclodextrin and simvastatin and (A) also with cholesterol added. (B) shows average of three experiments, with 10-27 cells for each treatment condition. Error bars show standard deviation from the mean. Data presented in (A) is one experiment with cholesterol added, as beyond this the cholesterol was infected and therefore could not be

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used. (C)Representative frames of live cell recording before and after dexamethasone added, showing GR translocation under treatment with cholesterol, methylcyclodextrin and simvastatin.

In order to investigate the effect of membrane fluidity and lipid rafts on the rate of glucocorticoid receptor translocation to the nucleus in response to dexamethasone, A549 human adenocarcinoma cells were transfected with Halo-tagged GR to enable visualisation of the glucocorticoid receptor. These were then subject to treatment with additional cholesterol to increase formation of lipid rafts, or with simvastatin or methylcyclodextrin to reduce cholesterol content and disrupt lipid rafts. With the addition of the fluorescent Halo ligand, it was possible to visualise and record the cells using a fluorescent microscope. As shown in figure 3-28, in comparison to vehicle treated cells the average time taken for GR to translocate to the nucleus was longer in cells treated with methylcyclodextrin (MβCD) at 1.2-fold longer, and simvastatin, 1.1-fold longer (Mean Veh. = 29.8 min, st. dev. = 9.2; MβCD = 36.2 min, st.dev. = 11.9; Simv. = 33.9 min, st.dev. = 19.8). Translocation in cholesterol-treated cells was also slightly longer than control, 1.13-fold longer, although for this treatment there was only N=1 (Veh.= 33.5 min, st.dev. = 5.7; Chol. = 38.1, st.dev. = 10.3). There was a very high variability in the rates of translocation in simvastatin-treated cells, with a much higher range of values than in the other treatment conditions (Range values for treatments (in minutes): Vehicle, max. 50, min. 12, range 38 (n=55); Cholesterol, max. 72, min. 24, range 48 (n=18); Methylcyclodextrin, max. 88, min. 12, range 76 (n=61); Simvastatin, max. 164, min. 18, range 146 (n=65)). Of the cells that had been transfected, it was possible to see cells that were in the process of cell division as well as cells that underwent apoptosis. Data was analysed for significance using independent samples t test (SPSS), to compare mean translocation time vs vehicle-treated control. Methylcyclodextrin t(114)=-3.200 p=.02, which is significant, Simvastatin t(118)=-1.407 p=.162, which is not significant, Cholesterol t(71)=-3.231 p=.002 which is significant.

3.3 Immunohistochemistry, visualisation of GR and Caveolin

3.3.1 Phalloidin actin stain with fluorescent-labelled dexamethasone treatment

To see the structure of the cytoskeleton in relation to GR, actin was stained with Phalloidin and cells were treated with FITC-dex, and fixed at 0, 5, 10, 15 and 20 min, this is shown in figure 3-29, below. By this, we can see the translocation of ligand-bound GR relative to actin. GR translocates to the nucleus in response to dex, yet there may be some co-

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localisation of GR and Actin in the early phase of GR activation, as can be seen at the edge and projections of the cell.

Figure 3-29 Fluorescent Phalloidin actin stain and GR translocation in A549 cells

Immunofluorescent microscopy of A549 cells stained with phalloidin and treated with FITC-conjugated dexamethasone showing GR translocation in relation to the actin cytoskeleton Human alveolar adenocarcinoma cell line A549 cells were seeded to glass coverslips at 90% confluency in 10% CSS media, and were treated with 100nM FITC- conjugated dexamethasone for A) 0, B) 10, C) 15 and D) 20 min, before fixing with 4% paraformaldehyde and permeabilization with Triton X. Nuclei were counterstained with Hoechst. Images were taken on a fluorescent confocal microscope, deconvolved and Z stacks produced.

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3.3.2 Immunofluorescence – dual labelling of GR and caveolin

3.3.2.1 Control incubations of single antibodies

Figure 3-30 Control sections, single antibody incubations Antibody controls for Lung sections Wild type mouse lung sections, fixed inflated by perfusion with 4% paraformaldehyde. Sections were mounted in paraffin and exposed to a solution of Sudan Black B in ethanol after antibody staining. Individual incubation with antibodies against caveolin (A), glucocorticoid receptor (GR M20) (B) (dilutions 1:500 and 1:200), secondary antibodies Alexa Fluor 488 (C), and Alexa Fluor 647 (D) (dilutions 1:1000

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and 1:500). DAPI counterstain for nuclei on all sections. Images collected sequentially at different wavelengths of light. Merge is processed from DAPI (blue), FITC (green) and CY5 (Filter sets – DAPI, Ex. BP350/350, Em. BP460/50; FITC Ex. BP480/40, Em. BP535/50; Cy5, Ex. BP620/60, Em. BP700/75). X20 magnification.

Figure 3-30, as these antibodies have been untested in tissue section fluorescent microscopy in this lab, single incubations were performed for any fluorescence produced when each antibody is applied alone. Fluorescence was not detected with single antibody application, above the slight residual background autofluorescence not completely quenched by Sudan Black B staining.

3.3.2.2 Caveolin-1 labelling

Figure 3-31 Fluorescent caveolin labelling in lung Caveolin-1 labelling, with fluorescent secondary antibody Wild type mouse lung sections, fixed inflated by perfusion with 4% paraformaldehyde. Sections were mounted in paraffin and exposed to a solution of Sudan Black B in ethanol after antibody staining. Incubation with antibodies against caveolin-1 (dilutions (A) 1:200 and (B) 1:500, raised in goat), with secondary antibody Alexa Fluor 488 (green, dilution 1:500). DAPI counterstain for nuclei on all sections. Images collected sequentially at different wavelengths of light. Merge is processed from DAPI (blue), FITC (green) and CY5 (Filter sets – DAPI, Ex. BP350/350, Em. BP460/50; FITC Ex. BP480/40, Em. BP535/50; Cy5, Ex. BP620/60, Em. BP700/75). X20, x40 and x60 magnification.

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The goat-derived caveolin-1 antibody labelling caveolin was assayed in figure 3-31 in lung tissue. The Caveolin-1 antibody with fluorescent secondary antibody appears to label caveolin with specificity. A 1:200 dilution of primary antibody gives a brighter signal than 1:500. Caveolin staining appears to occur in all cells comprising the alveoli and at the surface of cells lining the pulmonary blood vessels, is labelled much less strongly in epithelial cells (ciliated cuboidal cells) lining the bronchioles with speckling visible at higher magnification, and is present at the layer of cells that support these on the outside of the bronchiole. Comparing this distribution to the image taken on the CY3 channel (not shown), it is clear that this is not autofluorescence and can be said to be specific staining for caveolin.

3.3.2.3 Glucocorticoid receptor labelling

Figure 3-32 GR labelling with Far-Red Glucocorticoid receptor labelling, with fluorescent secondary antibody Wild type mouse lung sections, fixed inflated by perfusion with 4% paraformaldehyde. Sections were mounted in paraffin and exposed to a solution of Sudan Black B in ethanol after antibody staining. Incubation with antibodies against glucocorticoid receptor (GR M20, dilutions (A) 1:200 and (B) 1:500 raised in rabbit), with secondary antibody Alexa Fluor 647 (far red, dilution 1:500). DAPI counterstain for nuclei on all sections. Images collected sequentially at different wavelengths of light, relative to brightest area in field. Merge is processed from DAPI (blue), FITC (green) and CY5 (Filter sets – DAPI, Ex. BP350/350, Em. BP460/50; FITC Ex. BP480/40, Em. BP535/50; Cy5, Ex. BP620/60, Em. BP700/75). X20 and x40 magnification.

Figure 3-32 shows GR M20 antibody with Alexa Fluor 647 fluorescent secondary antibody, which appears to label glucocorticoid receptor with specificity. There is not a great 125

difference between the brightness of signal from 1:200 to 1:500 dilutions of the primary antibody. In panel B, X40 magnification, the exposure setting for the FITC channel is too bright, leading to a “greening” of the image. It is therefore important to keep the same exposure settings for all sections. At X40 magnification 1:200 dilution, there is strong staining for GR in cells adjacent to the blood vessel and in some of the cells that comprise the blood vessel, and it is possible to see speckled patterning of GR on the cells lining the bronchiole (top image of (A) at higher magnification). Comparisons with the same image taken in the Texas red channel, which highlights autofluorescence in red blood cells, GR may also be present in the endothelial cells that make the alveolar capillaries (not shown).

3.3.2.4 Dual labelling of Caveolin-1 and glucocorticoid receptor

Figure 3-33 Colocalisation of GR and caveolin in the lung

Dual caveolin 1 and glucocorticoid receptor labelling, with fluorescent secondary antibody Wild type mouse lung sections, fixed inflated by perfusion with 4% paraformaldehyde. Sections were mounted in paraffin and exposed to a solution of Sudan Black B in ethanol after antibody staining. Incubation with antibodies against caveolin 1 (goat), with secondary antibody Alexa Fluor 488 (green), glucocorticoid receptor (GR M20, rabbit), with secondary antibody Alexa Fluor 647 (far red). Primary antibodies were at 1:200, and secondary at 1:500. DAPI counterstain for nuclei on all sections. Images collected sequentially at different wavelengths of light, relative to brightest area in field. Merge is processed from DAPI (blue), FITC (green) and CY5 (Filter sets – DAPI, Ex. BP350/350, Em. BP460/50; FITC Ex. BP480/40, Em. BP535/50; Cy5, Ex. BP620/60, Em. BP700/75). x10, x20, x40 and x60 magnification.

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Figure 3-33 shows that both caveolin and GR can be stained together for fluorescent immunohistochemistry using antibodies to glucocorticoid receptor with Alexa Fluor 647 secondary antibody, and caveolin 1 with Alexa Fluor 488 secondary antibody. In the larger magnification and full size image, it is possible to see the speckled distribution of caveolin and patterning as shown figure 3-31 for caveolin antibody alone. GR patterning is also the same as in the previous figure 3-32 for the single target. The many of the cells of the alveoli that stain strongly for GR appear to also stain for caveolin. Cells of the pulmonary artery wall that stain strongly for caveolin, also stain for GR in some of these cells. Some cells that stain strongly for GR do not have as strong a signal for caveolin, although it is hard to determine from these images the type of cell that these may be; for example there is a cluster of cells near the bronchiole that has strong GR signal, but weak caveolin signal compared to the cells of the alveoli or blood vessel.

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3.4 In vivo experiment to characterise inflammatory responses in Caveolin-1 knockout mice Aerosolised lipopolysaccharide (LPS) procedure was performed to investigate whether caveolin-1 knockout mice differ from wild type mice in their response to a systemic immune challenge, and whether the immune response is affected by treatment with dexamethasone. Caveolin -1 knockout mice were matched for age and sex with wild type C75BL6 mice and treated and exposed to aerosolised challenge as detailed previously (see figure 2-2, for experimental procedure workflow). Tissues were collected and analysed for protein, gene expression etc., and the results of tests are presented below.

3.4.1 Genotyping

Figure 3-34 Genotyping

Genotyping of mice used in in vivo experiment DNA extracted from mouse tail snips, run following the JAX master protocol Cav1tm1Mls, Standard PCR, adjusted to 2.5 mM Mg2+ using BIOTAQ DNA Polymerase. Samples visualised on 1.5% agarose gel, with SafeVew. Band at ~690 bp is Wild Type, Cav null mutant has band at ~410 bp (two bands would indicate heterozygous). Scan of lab book, ladders clearer on original gel scan printout. Sample from animal 32 re-run as did not transfer to gel.

In order to confirm Cav-1 KO and wild type genotype, PCR was performed on DNA extracted from tail snips following the provided protocol from the mouse supplier, adjusted as per optimisation, the results are shown in figure 3-34. Animals were numbered according to schedule of treatment and culling. Numbers 1 to 4, Cav-1 KO LPS male; numbers 5 to 8, WT LPS male; numbers 9 to 11, Cav-1 KO Dex and LPS male; numbers 12 to 14, WT Dex and LPS male; numbers 15 to 17, Cav-1 KO LPS female; numbers 18 to 20, WT LPS female; numbers 21 to 23, Cav-1 KO Dex and LPS female; numbers 24 to 26, WT Dex and LPS female, number 27, WT LPS male; numbers 28 to 31, Cav-1 KO saline (male); numbers 32 to 35, WT saline (male). This confirms the expected genotype.

3.4.2 Western blot

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3.4.2.1 Caveolin and Glucocorticoid receptor

Figure 3-35 Western blot 1, lung, Caveolin and GR

Western blot to quantify levels of caveolin and GR phosphorylation in lung tissue from wild type and Caveolin-1 knockout mice subject to aerosolised challenge with LPS, and with pre-treatment of dexamethasone prior to challenge Animals were subject to LPS challenge in vivo for 20 min, or saline-only, with dexamethasone peritoneal injection 1h prior to challenge for that condition. Cav-1 KO and WT mice were matched for age and sex. All were sacrificed 5h post-challenge and lung was removed following broncho-alveolar lavage. Lung tissue samples were snap frozen, homogenised and protein extracted, using Bicine buffer. A) Standardised samples were analysed by western blot for levels of glucocorticoid receptor (M20 GR), glucocorticoid receptor phosphorylated at serine 211 (p211GR), caveolin 1 and α-tubulin using antibodies specific to those proteins. B) Densitometry was performed to quantify optical density of bands for GR, p211GR and caveolin, relative to tubulin. Error bars indicate standard error of the mean. There was n=2 per group analysed by western blot (male).

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To confirm genotype of CavKO mice by Western blot, and assay levels of GR, Western blot of protein extracted from whole lung homogenates was probed for caveolin, GR and phosphorylated GR (serine 211), shown in figure 3-35. Caveolin levels are as expected, with no caveolin-1 present in the caveolin knockout mice. This reinforces the finding of the genotyping (Figure 3-35). Cav-1 KO mice showed a stronger response to LPS than WT, which appeared to be counteracted by dex. Relative levels for GR and phosphorylated GR (serine 211, pGR) are similar in WT and Cav-1 KO mice in the saline-only condition, although the band for pGR in one Cav-1 KO animal was less intense than in the other which reduced the mean, to 0.6 for KO sal compared to 0.8 in WT. In the LPS-challenged mice, GR decreased in both wild type and knockout mice compared to control, with a greater decrease in Cav-1 KO, showing a 2.2-fold decrease in Cav-1 KO compared to 1.3-fold decrease in WT. Levels of detected pGR decreased in both WT and Cav-1 KO with LPS, compared to control, with levels in Cav-1 KO showing a 13-fold reduction in LPS-treated in comparison to saline, compared to 3.3–fold decrease in WT. In Animals treated with LPS and dexamethasone, WT and Cav-1 KO mice had similar levels of GR, with this being similar also to the levels found in the LPS-treated WT mice (WT dex mean 0.79, Cav-1 KO dex mean 0.71, with the mean for control WT and Cav-1 KO ~1).

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3.4.2.2 NFκB p65 and PKB/Akt

Figure 3-36 Western blot 2, lung, p65-NFκB, phospho-NFκB, PKB/Akt and pAkt

Western blot to quantify levels of NF-κB and Akt phosphorylation in lung tissue from wild type and caveolin knockout mice subject to aerosolised challenge with LPS, and with pre- treatment of dexamethasone prior to challenge Animals were subject to LPS challenge in vivo for 20 min, or saline-only, with dexamethasone peritoneal injection 1h prior to challenge for that condition. Cav-1 KO and WT mice were matched for age and sex. All were sacrificed 5h post-challenge and lung was removed following broncho-alveolar lavage. Lung tissue samples were snap frozen, homogenised and protein extracted, using Bicine buffer. A) Standardised samples were analysed by western blot for levels of p65-NFκB, phosphorylated p65-NFκB (phospho-NFκB), PKB/Akt and phosphoprylated Akt (pAkt) using antibodies specific to those proteins. B) Densitometry was performed to quantify optical density of bands, relative to tubulin shown previously (Fig.3-36). Error bars indicate standard error of the mean. There was n=2 per group analysed by western blot (male).

To see how the levels of phosphorylation of NF-κB and PKB/Akt are affected by aerosolised challenge in caveolin-1 knockout and wild type mice, and if is this altered with dexamethasone treatment; a Western blot of protein extracted from whole lung homogenates was probed for p65-NFκB (NF-κB), phosphorylated p65-NFκB (pNF-κB), PKB/Akt and phosphorylated Akt (pAkt), shown in figure 3-36. In animals treated only with saline, levels of NF-κB and p- NF-κB are similar between WT and Cav-1 KO mice, with levels

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of both being slightly higher in Cav-1 KO mice by around 1.2-fold. In response to LPS challenge, levels of NF-κB were similar to saline-only, with a slight increase in WT mice (1.2- fold higher than sal) and a slight decrease in Cav-1 KO (1.04-fold lower). Levels of p-NF-κB in WT mice were again similar to saline-treated, although 1.48-fold higher, however, in LPS- treated Cav-1 KO mice there was a clear 6.8-fold decrease compared to Cav-1 KO saline in the amount of pNF-κB detected. When animals were treated with dexamethasone and LPS, levels of NF-κB were similar to those found in saline-treated and LPS-treated conditions. In Cav-1 KO mice treated with dexamethasone and LPS, levels of pNF-κB were similar to those found in vehicle-treated Cav-1 KO mice (1.12-fold decrease). With dexamethasone treatment, levels of pNF-κB in WT mice were 2.5-fold higher than those in mice treated saline. Levels of PKB/Akt in saline-only treated mice were similar in Cav-1 KO and WT mice. Levels of pAkt were also similar between WT and Cav-1 KO mice, being slightly higher, by 1.27- fold, in Cav-1 KO mice. In response to LPS, levels of PKB/Akt in WT mice were slightly lower (1.09-fold) and Cav-1 KO were slightly higher (1.06-fold) compared to control. With LPS challenge, levels of pAkt increased in both WT and Cav-1 KO mice, with a greater increase of 1.72-fold over saline-treated found in WT mice, compared to 1.2-fold increase in Cav-1 KO. In dexamethasone treated mice, levels of PKB/Akt were similar to vehicle-treated mice in both Cav-1 KO and WT mice, with a slight decrease in Cav-1 KO mice 1.07-fold over saline-treated, a 1.14-fold lower level than LPS-treated. WT mice treated with dexamethasone and LPS showed a large decrease in pAkt levels 3.22-fold decrease compared to the levels found in vehicle-treated mice. Dexamethasone and LPS treated Cav- 1 KO mice had similar levels of pAkt as LPS-treated mice, although there was a large variation between the two animals shown here.

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3.4.2.3 SAPK/JNK

Figure 3-37 Western blot 3, lung, SAPK/JNK

Western blot to quantify levels of SAPK/JNK phosphorylation in lung tissue from wild type and Caveolin-1 knockout mice subject to aerosolised challenge with LPS, and with pre- treatment of dexamethasone prior to challenge Animals were subject to LPS challenge in vivo for 20 min, or saline-only, with dexamethasone peritoneal injection 1h prior to challenge for that condition. Cav-1 KO and WT mice were matched for age and sex. All were sacrificed 5h post-challenge and lung was removed following broncho-alveolar lavage. Lung tissue samples were snap frozen, homogenised and protein extracted, using Bicine buffer. A) Standardised samples were analysed by western blot for levels of p46- and p54- SAPK/JNK, and phosphorylated p46- and p54-SAPK/JNK (Thr183/Tyr185), using antibodies specific to those proteins. B) Densitometry was performed to quantify optical density of bands, relative to tubulin shown previously (Fig.3-36). Error bars indicate standard error of the mean. There was n=2 per group analysed by western blot (male).

Figure 3-37 shows the results of the Western blot probing for phosphorylated SAPK/JNK and SAPK/JNK in LPS-challenged WT and Cav-1 KO mice. Antibodies detect p46 and p54 isoforms of SAPK/JNK. Levels of p46 phos-SAPK/JNK were similar between WT and Cav-1 KO mice in the control saline-only condition, with a 1.06-fold lower level in Cav-1 KO. Levels of p46 SAPK/JNK were also similar between Cav-1 KO and WT mice, with Cav-1 KO 1.01-fold higher than WT, with a larger variation in the WT mice. In response to LPS, levels of both p46 SAPK/JNK and p46 phos-SAPK/JNK increased in WT and Cav-1 KO mice, with higher

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levels found in Cav-1 KO (WT p46 SAPK/JNK by 1.1-fold over saline-treated, phos-SAPK/JNK by 1.21-fold, Cav-1 KO p46 SAPK/JNK by 1.26-fold and p46 phos-SAPK/JNK by 1.25-fold). With dexamethasone treatment prior to LPS challenge, there was a lower increase in both p46 SAPK/JNK and p46 phos-SAPK/JNK in both WT and Cav-1 KO mice compared to LPS- challenged mice although this was still increased in comparison to saline-only mice (WT p46 SAPK/JNK by 1.09-fold over saline-treated, phos-SAPK/JNK by 1.08-fold, Cav-1 KO p46 SAPK/JNK by 1.06-fold and p46 phos-SAPK/JNK by 1.17-fold).

Levels of phosphorylated p54-SAPK/JNK were similar across all treatment conditions. In wild type mice there was a slight decrease in LPS- and dexamethasone and LPS-treated conditions compared to saline-only, and these were at a similar level (WT LPS 1.09-fold lower than WT saline, WT LPS-Dex 1.11-fold lower). There was a slight increase in p54 phos-SAPK/JNK in Cav-1 KO mice in response to LPS, compared to saline-only, and there was an increase again with dexamethasone treatment although there was variation between the two samples shown here (KO LPS 1.1-fold higher, Dex-LPS 1.19-fold higher). In response to LPS-challenge, levels of p54 SAPK/JNK increased compared to control in both WT (1.27-fold) and Cav-1 KO mice (1.32-fold), and there is a smaller response with dexamethasone pre-treatment (WT 1.19-fold, Cav-1 KO 1.1-fold). Levels of p54-SAPK/JNK were slightly higher in vehicle and LPS conditions for Cav-1 KO mice than WT, and slightly lower than WT with dexamethasone treatment.

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3.4.2.4 IRAK1 and Pin1

Figure 3-38 Western blot 4, lung, IRAK1 and Pin1

Western blot to quantify levels of IRAK1 and Pin1 in lung tissue from wild type and Caveolin-1 knockout mice subject to aerosolised challenge with LPS, and with pre- treatment of dexamethasone prior to challenge. Animals were subject to LPS challenge in vivo for 20 min, or saline-only, with dexamethasone peritoneal injection 1h prior to challenge for that condition. Cav-1 KO and WT mice were matched for age and sex. All were sacrificed 5h post-challenge and lung was removed following broncho-alveolar lavage. Lung tissue samples were snap frozen, homogenised and protein extracted, using Bicine buffer. A) Standardised samples were analysed by western blot for levels of Interleukin-1 receptor- associated kinase 1 (IRAK1) and Pin1, using antibodies specific to those proteins. B) Densitometry was performed to quantify optical density of bands, relative to tubulin shown previously (Fig. 3-36). Error bars indicate standard error of the mean. There was n=2 per condition analysed by western blot (male).

The results of probing Western blots with antibodies to IRAK1 and Pin1 are shown in figure 3-38. The antibody for IRAK 1 produces two bands 78 and 105 kDa, they have been analysed separately to see if there are any variations. In the control saline-only mice, levels of IRAK1 were similar across both wild type and Cav-1 KO mice, and both bands (78 and 105 kDa) had a similar intensity. In mice exposed to LPS challenge, there was a large reduction in 78 kDa IRAK1 in WT and Cav-1 KO, almost undetectable in Cav-1 KO which showed a 15.5-fold decrease in relation to saline-treated and WT showed an apparent 24- 135

fold decrease, which appears to be a greater decrease by this calculation. This may be due to the average OD for IRAK1 78 kDa is negative value compared to tubulin for Cav-1 KO LPS, which does not work for this calculation of fold-change. In WT mice treated with LPS, the 105 kDa band had similar intensity to levels in control condition, whereas in Cav-1 KO mice treated with LPS this was less than half of the levels found in control mice, a 2.59-fold reduction. In mice treated with dexamethasone before LPS challenge, the amount of 78 kDa IRAK1 was higher than LPS-treated mice in both Cav-1 KO and WT, and this was higher in WT than Cav-1 KO. The amount of 105 kDa IRAK1 in both WT and Cav-1 KO was approaching the levels found in the control and LPS-treated WT mice. Levels of Pin1 in Cav-1 KO mice were 2.9-fold higher than WT in the saline-only condition. In response to LPS, levels of Pin1 increased in both WT and Cav-1 KO, by 1.86-fold in WT and 1.26-fold in Cav-1 KO in comparison to saline-treated. Of the Cav-1 KO mice, the increase was more strongly marked in one animal than the other. In WT mice treated with dexamethasone prior to LPS exposure, the Pin1 response to LPS was lower than in LPS- treated showing a 1.62-fold increase. In Cav-1 KO mice, the levels of Pin1 decreased 1.38- fold in comparison to levels in control Cav-1 KO mice.

3.4.3 Real-Time Quantitative PCR of mouse lung To see if exposure to aerosolised challenge with LPS affects transcription of genes involved in the immune response in Caveolin-1 knockout mouse lung, and any effect be altered with treatment with dexamethasone prior to immune challenge; Real-time quantitative PCR was performed on RNA extracted from lung homogenates from the in vivo immune challenge experiment in figure 2-2. Primers were used to quantify expression of GILZ, MT1, IL-6 and CXCL1/KC. Analysis of qPCR gene expression was calculated by ΔΔCT relative to β-actin for saline-only control in wild type mice. This means that the expression for this is condition is limited to “1”, and does not show the spread of values that may occur in this condition in the different expression targets. “Average” values are calculated for data from both sexes combined relative to combined values for β-actin for that treatment, whereas male (M) and female (F) are relative to β-actin for that sex and treatment, which affects the median (med) and interquartile range (IQR). Results for each gene are shown below.

3.4.3.1 Glucocorticoid-induced leucine zipper

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Figure 3-39 RT-QPCR lung GILZ expression

RT Q-PCR analysis of RNA transcripts for GILZ from lung tissue from male and female wild type and Caveolin-1 knockout mice, subject to aerosolised challenge, with Dexamethasone pre-treatment Quantitative PCR (qPCR) for the experiment shown in figure 2-2, male and female wild type and Caveolin-1 knockout mice were subjected to aerosolised challenge with LPS, or saline control, with pre-treatment with dexamethasone. RNA was extracted from whole lung samples, samples were standardised, reverse transcribed and qPCR was performed to quantify levels of expression of target GILZ with SYBR green fluorescence detection. Fold change calculated as ΔΔCT relative to WT saline and β-actin. Boxplots depict median and interquartile range per treatment group for average, then male and female animals, whiskers indicate range. ΔΔCT calculated for “average” relative to average of both male and female responses, Male and Female relative to each sex, respectively. All samples run in duplicate. Group sizes WT saline n=4 (all male), Cav-1 KO saline n=4 (all male), WT LPS m=5 f=3, Cav-1 KO LPS m=3 f=3, WT Dex+LPS m=3 f=3, Cav-1 KO Dex+LPS m=3 f=3

Figure 3-39 shows GILZ expression in lung tissue, which did not seem to have a high variation in expression. The levels of GILZ in Cav-1 KO control mice (saline-only) were slightly lower than the median values for WT control (WT sal fixed to 1, Cav-1 KO sal med = 0.9, IQR = 0.8 to 1.2). There was not a high magnitude of variation detected in GILZ gene expression overall. In WT mice exposed to LPS, median GILZ expression was 2.5-fold lower than WT control (WT LPS med = 0.4, IQR = 0.2 to 0.7). Of these WT LPS-treated mice, levels of GILZ in males (M) were 2.3-fold lower than in females (F), with males showing 3.3-fold 137

decrease compared to control and females a 1.43-fold decrease, also the spread of values was lower in males (WT LPS M, med = 0.3, IQR = 0.3 to 0.5; F, med = 0.7, IQR = 0.2 to 1.1). Cav-1 KO mice treated with LPS had very low levels of GILZ in both male and female mice, with the median values 2-fold lower than WT LPS, and also a small range of values, and a 4.5-fold decrease in relation to Cav-1 KO control. Levels were 2-fold higher in Cav-1 KO LPS females than males, with levels in males 9-fold lower than control and female 4.5-fold lower (Cav-1 KO LPS average med = 0.2, IQR = 0.1; M, med = 0.1, IQR = 0.1 to 0.2; F, med = 0.2, IQR = 0.0). WT mice treated with Dex prior to LPS exposure had average expression 2.5-fold lower than control, male values were the same as control treated, but with a larger spread of values. Female WT mice treated with Dex had 3.3-fold lower GILZ expression levels than males, and were of a comparable level to Cav-1 KO mice in response to LPS (WT Dex average med = 0.4, IQR = 0.3 to 0.8; M, med = 1.0, IQR = 0.5 to 1.4; F, med = 0.3, IQR = 0.2 to 0.4). Cav-1 KO mice treated with Dex on average had expression levels 1.125–fold lower than controls, however when this was analysed by sex male values had a median 1.2- fold higher than controls, whereas females had expression 2.25-fold lower than control, with female 2.75-fold lower than male in this treatment (Cav-1 KO Dex average med = 0.8, IQR = 0.5 to 1.2; M, med = 1.1, IQR = 0.9 to 1.4; F, med = 0.4, IQR = 0.4 to 1.0).

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3.4.3.2 Metallothionein 1

Figure 3-40 RT-QPCR lung MT1 expression

RT Q-PCR analysis of RNA transcripts for MT1 from lung tissue from male and female wild type and Caveolin-1 knockout mice, subject to aerosolised challenge, with Dexamethasone pre-treatment Quantitative PCR (qPCR) for the experiment shown in figure 2-2, male and female wild type and Caveolin-1 knockout mice were subjected to aerosolised challenge with LPS, or saline control, with pre-treatment with dexamethasone. RNA was extracted from whole lung samples, samples were standardised, reverse transcribed and qPCR was performed to quantify levels of expression of target MT1 with SYBR green fluorescence detection. Fold change calculated as ΔΔCT relative to WT saline and β-actin. Boxplots depict median and interquartile range per treatment group for average, then male and female animals, whiskers indicate range. ΔΔCT calculated for “average” relative to average of both male and female responses, Male and Female relative to each sex, respectively. All samples run in duplicate. Group sizes WT saline n=4 (all male), Cav-1 KO saline n=4 (all male), WT LPS m=5 f=3, Cav-1 KO LPS m=3 f=3, WT Dex+LPS m=3 f=3, Cav-1 KO Dex+LPS m=3 f=3

Figure 3-40 shows MT1 expression in lung tissue. The level of MT1 expression in saline-only control mice was slightly higher in Cav-1 KO than WT (WT fixed to 1, Cav-1 KO med = 1.8, IQR = 1.5 to 2.1). MT1 expression was induced in all mice in response to LPS. In WT mice exposed to LPS, MT1 induction was 21.6-fold on average. Male and female responses were in a similar range, with expression levels in females 1.28-fold higher than males (WT LPS average, med = 21.6, IQR = 16.5 to 26.1; M, med = 19.2, IQR = 16.1 to 23.1; F, med = 24.6,

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IQR = 18.4 to 30.2). MT1 expression levels in Cav-1 KO mice in response to LPS were not as high as in WT mice, with Cav-1 KO 0.48-fold lower than WT LPS. Median values in Cav-1 KO LPS on average show a 5.83-fold increase compared to control and were similar for male and female, with female responses 1.12-fold greater than male and having a wider range of values (Cav-1 KO LPS average, med = 10.5, IQR = 8.2 to 11.8; M, med = 9.8, IQR = 8.6 to 12.0, 5.44-fold change from control; F, med = 11.0, IQR = 9.0 to 13.3, 6.1-fold change from control). WT mice treated with Dex prior to LPS challenge on average had 1.3-fold lower levels of MT1 expression than WT mice exposed to LPS without Dex, having an average 16.6-fold increase over control. When this was analysed by sex, males had a 2.76-fold higher median MT1 expression than females, with the highest variation in expression for MT1 in all conditions, whereas females had lower expression that was comparable to levels expressed in Cav-1 KO mice in response to LPS (WT Dex average, med = 16.6, IQR = 12.7 to 21.4; M, med = 27.4, IQR = 22.9 to 45.4; F, med = 9.9, IQR = 7.2 to 11.7). The response of Cav-1 KO mice with Dex and LPS had the highest median expression levels for MT1 of 13.8- fold over control, with males having 2.13-fold higher expression than females (Cav-1 KO Dex average, med = 24.8, IQR = 23.6 to 32.7; M, med = 40.7, IQR = 34.0 to 43.9, 22.6-fold over control; F, med = 19.1, IQR = 17.6 to 19.1, 10.6-fold over control).

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3.4.3.3 Interleukin-6

Figure 3-41 RT-QPCR lung IL-6 expression

RT Q-PCR analysis of RNA transcripts for IL-6 from lung tissue from male and female wild type and Caveolin-1 knockout mice, subject to aerosolised challenge, with Dexamethasone pre-treatment Quantitative PCR (qPCR) for the experiment shown in figure 2-2, male and female wild type and Caveolin-1 knockout mice were subjected to aerosolised challenge with LPS, or saline control, with pre-treatment with dexamethasone. RNA was extracted from whole lung samples, samples were standardised, reverse transcribed and qPCR was performed to quantify levels of expression of target IL-6 with SYBR green fluorescence detection. Fold change calculated as ΔΔCT relative to WT saline and β-actin. Boxplots depict median and interquartile range per treatment group for average, then male and female animals, whiskers indicate range. ΔΔCT calculated for “average” relative to average of both male and female responses, Male and Female relative to each sex, respectively. All samples run in duplicate. Group sizes WT saline n=4 (all male), Cav-1 KO saline n=4 (all male), WT LPS m=5 f=3, Cav-1 KO LPS m=3 f=3, WT Dex+LPS m=3 f=3, Cav-1 KO Dex+LPS m=3 f=3

Interleukin-6 (IL-6) expression in mouse lung was induced by exposure to LPS, shown in figure 3-41. There were very low levels in control (saline-only treated) mice, with levels slightly higher in Cav-1 KO cells (WT fixed to 1, Cav-1 KO med = 1.4, IQR = 1.3 to 1.5). In WT mice IL-6 levels were induced 99.6-fold over control levels with LPS, with a 1.34-fold higher response in females compared to males, and a higher variability in females (WT LPS average, med = 99.6, IQR = 77.0 to 117.1; M, med = 74.5, IQR = 68.4 to 89.4; F, med =

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100.2, IQR = 78.3 to 119.6). IL-6 expression with LPS was 1.21-fold higher in Cav-1 KO mice on average than WT, showing an average increase of 86.6-fold over control. The LPS response in males was higher than in females, at 109.9-fold higher than control and females 74.2-fold higher. Males also had a larger variation in expression levels (Cav-1 KO LPS average, med = 121.2, IQR = 87.7 to 202.0; M, med = 153.9, IQR = 81.0 to 216.9; F, med = 103.9, IQR = 79.8 to 110.4). WT mice treated with Dex prior to LPS exposure had average median expression levels, at 113.4-fold over control, comparable to that of WT mice without Dex although slightly (1.07-fold) higher and an unequal interquartile range. When analysed by sex males had a 3.8-fold lower median expression level than females, who had an expression level closer to that of WT mice not treated with Dex and to Cav-1 KO LPS, although both sexes had a large range of expression values (WT Dex average, med = 113.4, IQR = 33.7 to 119.1; M, med = 40.4, IQR = 31.4 to 119.6; F, med = 154.1, IQR = 146.5 to 242.6). Cav-1 KO mice treated with Dex had a 2.18-fold lower median expression level than WT mice treated with Dex on average, which was 37-fold lower than control. When this was analysed by sex, female IL-6 expression levels were 2.27-fold higher than male, with males 32.3-fold higher than control whereas female were 73.6-fold higher than control. Female Cav-1 KO mice had 1.5-fold lower expression levels than female WT mice treated with Dex (Cav-1 KO Dex average, med = 51.8, IQR = 33.9 to 81.9; M, med = 45.2, IQR = 43.2 to 72.3; F, med = 103.0, IQR = 38.4 to 143.3).

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3.4.3.4 CXCL1/KC

Figure 3-42 RT-QPCR lung CXCL1/KC expression

RT Q-PCR analysis of RNA transcripts for CXCL1/KC from lung tissue from male and female wild type and Caveolin-1 knockout mice, subject to aerosolised challenge, with Dexamethasone pre-treatment Quantitative PCR (qPCR) for the experiment shown in figure 2-2, male and female wild type and Caveolin-1 knockout mice were subjected to aerosolised challenge with LPS, or saline control, with pre-treatment with dexamethasone. RNA was extracted from whole lung samples, samples were standardised, reverse transcribed and qPCR was performed to quantify levels of expression of target CXCL1/KC with SYBR green fluorescence detection. Fold change calculated as ΔΔCT relative to WT saline and β-actin. Boxplots depict median and interquartile range per treatment group for average, then male and female animals, whiskers indicate range. ΔΔCT calculated for “average” relative to average of both male and female responses, Male and Female relative to each sex, respectively. All samples run in duplicate. Group sizes WT saline n=4 (all male), Cav-1 KO saline n=4 (all male), WT LPS m=5 f=3, Cav-1 KO LPS m=3 f=3, WT Dex+LPS m=3 f=3, Cav-1 KO Dex+LPS m=3 f=3

Expression of CXCL1/KC was induced in lung in response to LPS, shown in figure 3-42. Expression levels of CXCL1/KC in control (saline-only) were almost the same for Cav-1 KO and WT mice (WT fixed to 1, Cav-1 KO med = 1.1, IQR = 1.0 to 1.2). In WT mice exposed to LPS, CXCL1/KC was induced 93-fold over levels found in control WT mouse lung, when analysed by sex males had a 1.16-fold lower level of expression and a much smaller interquartile range than females (WT LPS average, med = 93.0, IQR = 71.5 to 101.1; M, med

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= 82.6, IQR = 75.1 to 89.4; F, med = 96.0, IQR = 68.5 to 124.9). Cav-1 KO mice exposed to LPS showed on average a 92-fold increase in comparison to control, which when analysed by sex became a marked increase on levels in both male and females, with males exhibiting a 100-fold difference in expression over control and females 107.3-fold. Levels between LPS-treated WT and Cav-1 KO were 1.08-fold higher in Cav-1 KO on average, with 1.33-fold higher in males and 1.23-fold higher in females in comparison to WT LPS (Cav-1 KO LPS average, med = 101.3, IQR = 75.5 to 145.2; M, med = 110.2, IQR = 76.4 to 139.4; F, med = 118.0, IQR = 88.3 to 138.9). CXCL1/KC expression in WT mice with Dex treatment prior to LPS exposure had an average median level similar to Cav-1 KO mice without dex treatment but with a much larger range of values. WT Dex-treated female expression levels were much higher than all other treatment conditions, 147.9-fold higher than control and 1.54- fold higher than LPS-treated WT females. There is a 2.15-fold difference between Dex- treated WT males and females, with no overlap of expression (WT Dex average, med = 103.9, IQR = 54.4 to 186.3; M, med = 68.9, IQR = 44.4 to 86.8; F, med = 147.9, IQR = 115.9 to 159.5). Expression values for Cav-1 KO Dex-treated mice on average were 55.4-fold higher than control, where males were 47.5-fold higher than control, and females 61.4-fold higher than controls, with a 1.29-fold difference between male and female. Expression levels in females were slightly higher than the average, and males were slightly lower than the average but with an unequal interquartile range (Cav-1 KO Dex average, med = 60.9, IQR = 41.1 to 88.0; M, med = 52.2, IQR = 51.2 to 86.9; F, med = 67.5, IQR = 31.3 to 79.7). Cav-1 KO mice treated with dex had a 1.66-fold lower average median expression than LPS- exposed Cav-1 KO mice, whereas WT Dex-treated mice had a 1.11-fold increase over WT LPS.

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3.4.4 Enzyme-linked immunosorbent assay for serum Corticosterone levels

Figure 3-43 ELISA for serum [CORT]

ELISA performed to quantify levels of corticosterone in blood serum from wild type and Caveolin-1 knockout mice subject to aerosolised challenge with LPS, and with dexamethasone treatment Enzyme-linked immunosorbent assay on blood serum from mice in experiment shown in figure 2-2. ELISA was performed according to the standard protocol provided (Corticosterone ELISA kit, Enzo Life Sciences, ADI-900-097). Samples were run in duplicate at a 1/8 dilution, except two samples which had too low volume (run at 1/10 and 1/12), this was factored into calculations of concentration. All samples were treated with steroid displacement reagent, as specified in the provided protocol. Assay performed alongside Louise Kearney, and analysed by her. Bars depict mean concentration, with “average” showing male and female combined, then divided by sex. Error bars show standard error of the mean.

An ELISA was performed to establish whether serum corticosterone levels in response to LPS challenge varied between wild type and Caveolin-1 knockout mice, figure 3-43. Levels in saline-only control mice were 1.12-fold lower in Cav-1 KO than WT (161.7 ng/ml vs. Cav- 1 KO 131.9 ng/ml). In LPS-treated WT mice, on average the levels were similar to control, and when divided by sex corticosterone levels increased 1.17-fold in males and decreased 1.4-fold in females compared to control mice (Ave. 161.1, M = 188.8, F = 115.0 ng/ml). In Cav-1 KO mice, corticosterone levels decreased in response to LPS and were approximately half that of saline-only control (1.87-fold decrease compared to control), again with levels slightly higher in males (1.68-fold decrease) than females (2.24-fold decrease) (Ave. 70.2, M = 78.7, F = 58.9 ng/ml). In WT mice treated with dexamethasone prior to LPS exposure, corticosterone levels were 2.38-fold lower than LPS-treated WT mice, comparable to LPS- treated Cav-1 KO mice at less than half the level of the control. Levels were approximately

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the same in male and female animals, with 1.08-fold higher in females and quite a wide spread of values across the 3 animals of each sex in this condition (Ave. 67.7, M = 65.2, F = 70.3 ng/ml. SEM for M = 32.0, F = 39.5). Serum corticosterone levels in dexamethasone- treated Cav-1 KO mice were much lower than in any other condition. The average was 5.9 ng/ml, with values of 1 to 2 ng/ml in individual males and slightly higher in females at 10.4 ng/ml, with a higher variation in values seen in females. This is a 22.4-fold decrease over control on average, a 12.7-fold decrease in females and a 94-fold decrease in males compared to control. There is a 7.4-fold increase in corticosterone levels in Dex-treated Cav-1 KO females over males, and an 11.9-fold decrease over LPS treated Cav-1 KO on average. Dex-treated Cav-1 KO males show a 56.2-fold decrease in corticosterone over LPS- treated males. (Ave. 5.9, M = 1.4, F = 10.4 ng/ml. SEM for M = 0.2, F = 7.5).

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3.4.5 Haematoxylin and Eosin stained lung tissue sections

3.4.5.1 Saline treated mice

Figure 3-44 H&E lung WT and CavKO Saline

Haematoxylin and Eosin stain of lung tissue section from Wild Type and Caveolin-1 knockout mice exposed to in vivo inflammatory lung challenge, nebulised Saline-only control Lung tissue from Cav-1 KO and WT mice exposed to inflammatory challenge, here saline-only vehicle control, culled 5 h post-challenge, lung excised and right lobe immersed in 4% PFA to fix. Tissues were processed and paraffin-embedded. Figure 3-45 shows 2 mice from each condition, all male. 5 µm slice mounted on charged adhesion slides. Deparaffinised tissues were stained with standard Haematoxylin and Eosin stain. Images were acquired using a 20x/0.80 Plan Apo objective on 3D-Histech Pannoramic 250 Flash Slide Scanner, magnification 10X, 20X and 40X, scale bars indicate 200, 100 and 50 µm.

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3.4.5.2 LPS-exposed C57BL6 Wild Type mice

Figure 3-45 H&E WT lung LPS

Haematoxylin and Eosin stain of lung tissue section from Wild Type mice exposed to in vivo inflammatory lung challenge, nebulised LPS Lung tissue from WT (C57BL6) mice exposed to inflammatory challenge, here 2 mg/mL LPS, culled 5 h post-challenge, lung excised and right lobe immersed in 4% PFA to fix. Tissues were processed and paraffin- embedded. Figure 3-46 shows lung from 4 mice, all male. 5 µm slice mounted on charged adhesion slides. Deparaffinised tissues were stained with standard Haematoxylin and Eosin stain. Images were acquired using a 20x/0.80 Plan Apo objective on 3D-Histech Pannoramic 250 Flash Slide Scanner, magnification 10X, 20X and 40X, scale bars indicate 200, 100 and 50 µm.

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3.4.5.3 LPS-exposed Cav-1 KO mice

Figure 3-46 H&E CavKO lung LPS

Haematoxylin and Eosin stain of lung tissue section from Caveolin-1 Knockout mice exposed to in vivo inflammatory lung challenge, nebulised LPS Lung tissue from Cav-1 KO mice exposed to inflammatory challenge, here 2 mg/mL LPS, culled 5 h post-challenge, lung excised and right lobe immersed in 4% PFA to fix. Tissues were processed and paraffin- embedded. Figure 3-47 shows lung from 4 mice, all male. 5 µm slice mounted on charged adhesion slides. Deparaffinised tissues were stained with standard Haematoxylin and Eosin stain. Images were acquired using a 20x/0.80 Plan Apo objective on 3D-Histech Pannoramic 250 Flash Slide Scanner, magnification 10X, 20X and 40X, scale bars indicate 200, 100 and 50 µm.

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3.4.5.4 Dexamethasone-treated LPS-exposed Wild Type and Cav-1 KO mice

Figure 3-47 H&E CavKO and WT, LPS and Dex

Haematoxylin and Eosin stain of lung tissue section from Wild Type and Caveolin-1 knockout mice exposed to in vivo inflammatory lung challenge, nebulised LPS with pre- treatment with Dexamethasone Lung tissue from Cav-1 KO and WT mice exposed to inflammatory challenge, here 2 mg/mL LPS with treatment with 1 mg/kg dexamethasone I.P. 1 h prior to LPS exposure, culled 5 h post-challenge, lung excised and right lobe immersed in 4% PFA to fix. Tissues were processed and paraffin-embedded. Figure 3-48 shows lung from 2 mice from each condition, all male. 5 µm slice mounted on charged adhesion slides. Deparaffinised tissues were stained with standard Haematoxylin and Eosin stain. Images were acquired using a 20x/0.80 Plan Apo objective on 3D-Histech Pannoramic 250 Flash Slide Scanner, magnification 10X, 20X and 40X, scale bars indicate 200, 100 and 50 µm.

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Figures 3-44 to 3-47 are hematoxylin and eosin stained sections of mouse lung, from the experiment in figure 2-2, in vivo aerosolised challenge with LPS, with dex treatment in wild type and Caveolin-1 knockout mice. Hemalum in the hematoxylin stains nuclei dark blue, where other structures are stained shades of pink/red by Y eosin. Figure 3-44 shows A) Wild type saline-only control and B) Cav-1 KO saline-only control. In these sections we can see various structures of the lung, such as bronchi recognisable by the columnar epithelial cells, surrounded by a layer of smooth muscle cells, accompanied by blood vessels and surrounded by lighter pink-staining collagenous connective tissue. The alveoli are not clearly visible, especially in the top panel of 3-44-A, where the tissue appears dense and compacted. I believe the loose webbing here is connective tissue, stretched. In the bottom panel of 3-45-B, we can see a longitudinal cut through a branch of the bronchioles where furrows are visible. Figure 3-45 shows wild type lung, from 4 mice exposed to LPS. Again, it is possible to see the main structures of bronchioles and blood vessels, and here the alveoli are clearer, although in the top panel the structures are somewhat compressed. Figure 3- 46 shows lung sections from 4 Cav-1 KO mice exposed to LPS. Here, we can see evidence of inflammatory response. There are cells within the lumen of the bronchiole in the top panel, and possibly also evidence of oedema in pink staining in some of the alveolar spaces. There may also be inflammatory cells in the alveolar spaces in the bottom panel. Figure 3-47 shows lung from A) wild type and B) Cav-1 KO mice treated with dexamethasone prior to LPS exposure. In the top panel there are areas of intense pink staining in the alveoli, although it is unclear what this may be. The second panel again shows tissue that appears dense and compacted. There appears to be a high level of connective tissue in the Cav-1 KO lung, but this may be a result of the depth of the slice through the lung taking in a section with a high amount of connective tissue. These figures (3-44 to 3-47) indicate some interesting aspects of the structure of Caveolin-1 knockout and wild type mouse lung, to elucidate the differences further the following figures (3-48 to 3-51) show more direct comparisons, again from the H&E stained lung sections as the above.

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3.4.5.5 Immune cells in LPS-exposed Wild Type mice

Figure 3-48 Immune cells in WT lung with LPS

Haematoxylin and Eosin stain of lung tissue section from Wild Type mice exposed to in vivo inflammatory lung challenge, nebulised with markers to indicate immune cells Lung tissue from WT mice exposed to inflammatory challenge of 2 mg/mL LPS, culled 5 h post- challenge, lung excised and right lobe immersed in 4% PFA to fix. Tissues were processed and paraffin-embedded. Figure 3-49 shows lung from 4 mice from each condition, all male. 5 µm slice mounted on charged adhesion slides. Deparaffinised tissues were stained with standard Haematoxylin and Eosin stain. Images were acquired using a 20x/0.80 Plan Apo objective on 3D-Histech Pannoramic 250 Flash Slide Scanner, magnification 10X, scale bars indicate 200 µm.

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3.4.5.6 Immune cells in LPS-exposed Cav-1 KO mice

Figure 3-49 Immune cells in CavKO with LPS

Haematoxylin and Eosin stain of lung tissue section from Caveolin-1 knockout mice exposed to in vivo inflammatory lung challenge, nebulised LPS, with markers to indicate immune cells Lung tissue from Cav-1 KO mice exposed to inflammatory challenge of 2 mg/mL LPS, culled 5 h post-challenge, lung excised and right lobe immersed in 4% PFA to fix. Tissues were processed and paraffin-embedded. Figure 3-50 shows lung from 4 mice from each condition, all male. 5 µm slice mounted on charged adhesion slides. Deparaffinised tissues were stained with standard Haematoxylin and Eosin stain. Images were acquired using a 20x/0.80 Plan Apo objective on 3D-Histech Pannoramic 250 Flash Slide Scanner, magnification 10X, scale bars indicate 200 µm.

Figure 3-46 showed evidence of immune cells in the lumen of the bronchiole in LPS-treated Cav-1 KO lung. To show this in other sections, Figures 3-48 and 3-49 depict areas of the mouse lung where there appear to be inflammatory cells, in wild type and Cav-1 KO mice respectively. These cells are indicated by the arrowheads. Figure 3-48 shows LPS-exposed WT lung, which shows some immune cells predominantly in the lumen of the smaller airways, with some in the blood vessel in animal #5. Figure 3-49 shows a much higher

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number of immune cells in the lumen of the airways, in the blood vessels, and also in the alveolar space. In saline treated mice, these cells were not visible, and in mice treated with Dex prior to LPS exposure, it was hard to see the cells and to differentiate these from “normal”. The cells were much more apparent in LPS-exposed mice.

3.4.5.7 Structural comparison in lungs of Wild Type and Cav-1 KO mice

Figure 3-50 H&E Lung structural comparison WT CavKO

Haematoxylin and Eosin stain of lung tissue section from Wild Type and Caveolin-1 knockout mice indicating hypercellular lung phenotype Lung tissue from wild type and Cav-1 KO mice exposed to inflammatory challenge, here 2 mg/mL LPS with treatment, culled 5 h post-challenge, lung excised and right lobe immersed in 4% PFA to fix. Tissues were processed and paraffin-embedded. 5 µm slice mounted on charged adhesion slides. Deparaffinised tissues were stained with standard Haematoxylin and Eosin stain. Images were acquired using a 20x/0.80 Plan Apo objective on 3D-Histech Pannoramic 250 Flash Slide Scanner, magnification 10X, scale bars indicate 200 µm.

In the previous figures 3-48 and 49, it was possible to see some differences in the structure of the lung between Cav-1 KO and WT mice. For straightforward comparison, a section of each are presented here in figure 3-50 side by side. It is clear that the walls of the alveoli are much thicker in the Cav-1 KO mice, right panel, which may be indicative of hyperplasia of the cells. Fibrosis in the lung is characterised by excessive collagen production, which is associated with caveolin reduction, this is hard to quantify here. Pulmonary fibrosis is also characterised by enlarged alveolar spaces, which we can see in both these sections, yet may be as a result of processing of the tissues rather than indicative of pathology.

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4 Discussion

4.1 In vitro characterisation of Caveolin-1 knockout MEFs, developing a robust cell model to study GR and Caveolin interactions and GR target genes reliant on Caveolin As a means to study the effects of caveolin on glucocorticoid signalling in vitro, the effect of dexamethasone treatment on mouse embryonic fibroblasts (MEFs) from wild type and caveolin-1 knockout mice was investigated. Western blots for phosphorylation of signalling proteins in response to dexamethasone in WT and Cav-1 KO MEFs show phosphorylation of many of these signalling proteins was rapidly increased, however the levels differed between Cav-1 KO cells and WT. In some proteins, higher phosphorylation was found in Cav-1 KO compared to WT, for instance phosphorylation of GR at serines 203 and 211, and phosphorylation of PKB/Akt. Caveolin may be involved in the glucocorticoid responsive repression of p46 JNK/SAPK and p44/42 MAPK phosphorylation, and phosphorylation of GR at ser203 may be involved in these early signalling events in the cytoplasm.

RT-qPCR data indicates variation in the expression of some genes in response to dexamethasone, including GILZ, Zfand5 and Stc1, and a further variation in the response of some glucocorticoid-regulated genes in the absence of caveolin, such as in Ptchd1, MT1 and Glul. This indicates that GR signalling can be modulated by caveolin and this has effects on gene expression. The translocation of GR to the nucleus in response to dexamethasone was altered by manipulation of lipid rafts by the addition and removal of cholesterol from the cell membrane. This indicates that there is a structural component of lipid rafts, such as caveolin, that modulates GR signalling at the membrane and thus affects GR signalling within the cell.

There are limitations to the interpretation of these results. In many cases there was a small sample size and difficulties with techniques such as transfection efficiency, specificity of antibody labelling and other limiting factors meant that there were a low number of replicates and therefore it was not possible to perform statistical analysis of confidence that the apparent results are significant. Additionally, there was high variation in the responses in some experimental conditions, which could not be adequately controlled for and optimised in the duration of this research, and some experimental techniques that

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would have given further depth to the investigation of GR signalling and caveolin were discontinued for these reasons.

4.1.1 Changes in the phosphorylation of signalling proteins in response to glucocorticoids and in the presence and absence of Caveolin

4.1.1.1 In non-serum starved conditions, GC treatment may induce phosphorylation of PKB in CavKO but not wild type MEFs In WT mice, pPKB/Akt appeared to decrease with dex, whereas it increased in CavKO. Total PKB in all decreased. This result mostly disagrees with (Matthews et al. 2008), both found that CavKO cells had a higher basal phosphorylation of PKB, however, they found that with the removal of caveolin-1, there was a loss of the GC induced phosphorylation of PKB, which was not found here. In fact WT cells had little to no GC induction of pPKB, nor GSK3β, and KO had higher levels of pPKB in response to dex. It may be that in this experiment, the level of serum has an effect on PKB phosphorylation. Here, the cells were in 10% CSS, whereas Matthews et al., 2008 the cells were serum starved. There is evidence that serum starvation, as a metabolic stressor, can increase phosphorylation sensitivity of certain cell lines in pathways of PI3K/PKB/Akt and MAPK/STAT (Levin et al. 2010), and this pathway activation in response to growth factors and hormones has an anti-apoptotic effect, which is induced by serum starvation (Kennedy et al. 1997; Kuzman et al. 2005; Trencia et al. 2003). Total PKB decreased in all conditions, which is interesting, as with GC treatment PKB has been seen to decrease equivalent to pPKB increase (Buren et al. 2002), or is unchanged (Hazlehurst et al. 2013). Levels of phosphorylated GSK3β, which is downstream of PKB/Akt, increased in response to dex in CavKO cells, although the levels were not very different from the untreated condition, there was also not a high induction of pPKB. However, levels of GSK3β were again higher in WT than CavKO at baseline, which disagrees with the findings in Matthews et al.,(2008), of serum starved cells, and reflects the higher activity of GSK3β in WT cells as they are proliferating in growth media (Fang et al. 2000).

4.1.1.2 Caveolin may be involved in GC induced reduction of p44/42 MAPK phosphorylation GC are thought to reduce p44/42 (ERK1/2) MAPK phosphorylation by increased activity of MAPK phosphatase-1 (MKP1) (Lin et al. 2008), and by this they in inhibit migration and proliferation. There was a higher reduction in phosphorylation of p44/42 MAPK in WT cells, implying that caveolin is involved in modulating this phosphatase activity. A decrease was also seen in CavKO cells, at a lower magnitude, which means that this decrease is not dependent on caveolin.

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WT cells appeared to have higher basal levels of phosphorylated p44/42 MAPK (ERK 1/2) than Cav-1 KO. Additionally, there did not appear to be a great difference in Cav-1 KO in response to dex in comparison to untreated cells. The basal level of p44/42 MAPK phosphorylation in CavKO disagrees with the finding by (Galbiati et al. 1998), where downregulation of caveolin-1in NIH 3T3 cells (immortalised MEFs) induced hyperactivation of the p44/42 MAPK (ERK 1/2) cascade, or (Murata et al. 2007) which found p44/42 MAPK (ERK 1/2) to be constitutively activated in Cav-1 KO mice. This may be because downregulation of Cav1, or other signalling pathways such as high calcium in vivo, induces changes in p44/42 MAPK(Kim et al. 2003), whereas these cells are unstimulated and quiescent.

4.1.1.3 Caveolin may be involved in GC induced reduced phosphorylation of p46 SAPK JNK Dexamethasone can reduce phosphorylation of p46 SAPK JNK in wild type, but not Cav-1 KO cells. Levels of basal phosphorylation of SAPK/JNK, which is downstream of MAPK, adjacent to ERK1/2, were higher in WT cells than Cav-1 KO, and in WT cells phosphorylation decreased in p46 and showed a slight increase in p54 with dex. Cav-KO cells showed an increase in phosphorylation of p54- and p46- SAPK/JNK. The decrease in phospho-p46 levels in WT with GC treatment agrees with (Bhattacharyya et al. 2007), where glucocorticoids bind JNK to inhibit activity. This inhibition of JNK was not seen in Cav-1 KO cells, perhaps caveolin is required to mediate binding of activated GR to JNK in order to facilitate inhibition (Bruna et al. 2003). In the absence of inflammatory signal, such as LPS, which induces these pathways (Swantek et al. 1997), it is difficult to suggest why phosphorylation may increase, perhaps temperature change may induce stress. The p46 isoform of SAPK/JNK is preferentially activated in macrophages in response to TNF-α, which may be why GR has a higher effect on this isoform (Chan et al. 1997).

4.1.1.4 Phosphorylation at serine 203 of GR may be involved in cytoplasmic signalling early in GR activation There was agreement in result of the GC time course with the 0 and 10 min dex treatment blot, where Cav-1 KO cells had a greater level of phosphorylation at ser203. In both cell types, WT and CavKO, GR phosphorylation at serine 203 increased up to around 15-20 min, and then decreased, whereas phosphorylation at p211 continued to increase after this time. It has been previously seen that phosphorylation at serine 203 is measurable in untreated cells, and that p211 levels are low, and these blots appear to confirm previous findings (Wang et al. 2002; Wang et al. 2007). In addition, phosphorylation at ser203 causes GR to be cytoplasmic, and at serine 211 the receptor is seen to move to the nucleus. It is

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possible that this early cytoplasmic location of the activated receptor is involved in non- genomic signalling of GR, in association with other cytoplasmic signalling proteins. It has also been proposed that GR is phosphorylated at ser203 by ERK/MAPK, and that this acts to reduce the transcriptional activity of GR (Krstic et al. 1997). However there was no significant increased activation of p44/42 MAPK (ERK 1/2), therefore increased p203 GR in CavKO mice must be mediated by another factor, perhaps increased sensitivity to signal through chaperones (Kovacs et al. 2005).

4.1.1.5 Wild type cells have a more robust GR response of phosphorylation at serine 211 than CavKO, which leads to transcription In the cells treated with dex for 10 min, there was a stronger response in CavKO cells than WT. When the cells were subject to dex over time, at 10 min CavKO cells also had a higher level of p211 GR, yet this did not persist. Cav-1 KO cells appeared to have a faster rate of induction of p211 GR than wild type, with stronger signal at 10 and 15 min in CavKO than in WT. However, phosphorylation at ser211 (p211) in WT seemed to increase in a fairly linear pattern resulting in a higher level overall, where in CavKO there was an apparent decline in p211 at 30 min, resulting in a double peak and slightly lower levels after 20 min to 90 min of treatment. This implies that although there is rapid signalling in CavKO, WT cells have more robust p211 activation, which may be as a result of caveolin stabilising the receptor complex. In addition, the reported p44/42 MAPK (ERK 1/2) hyperactivation in CavKO mice may also have an effect here, where phosphorylation at this serine residue by ERK has also been reported to have an inhibitory effect on transcription. In WT mice there may be higher levels of pro-transcription phosphorylation of GR, leading to higher overall levels of ser211 phosphorylation and GR translocation to the nucleus. To support this, in WT cells there was a decrease in the level of total GR over time, which was not seen in CavKO. GR is degraded via the ubiquitin proteasome pathway after it has induced transcription in order to terminate glucocorticoid activity, without this degradation there is an enhanced on- going level of GR transcription (Wallace and Cidlowski 2001). Where the GR has not induced transcription, and returns to an unphosphorylated state by phosphatase activity, there would be no need for targeted degradation of the receptor.

4.1.2 Real-time quantitative PCR to establish which genes are reliant on caveolin for GR regulation Wild type and Caveolin-1 knockout MEFs were treated with Dexamethasone for 4h in order to induce gene transcription. Real time QPCR was performed to quantify the expression of mRNA of target genes GILZ, Zfand5, Ptchd1, MT1, STC1, Cdh11, Runx1t1, Glul and RpS6. There were varying responses of these target genes to GR activation, and these responses

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can be divided into three main categories for the 9 targets: GR regulated genes that are affected by the absence of caveolin, Ptchd1, MT1 and Glul; GR regulated genes that appear to be caveolin-independent, GILZ, Zfand5 and Stc1; and genes that did not have a strong pattern of response to GR or caveolin, Cdh11, Runx1t1 and RpS6.

4.1.2.1 Glucocorticoid Receptor regulated genes that are dependent on caveolin include Ptchd1, MT1 and Glul The glucocorticoid-induced responses in Ptchd1 (Patched domain containing 1), MT1 (Metallothionein 1) and Glul (Glutamate- ammonia ligase) appears to be influenced by caveolin. These genes showed a change in expression level in response to glucocorticoid treatment, with an increase in expression of Ptchd1 and MT1, both of which were higher in Cav-1 KO cells, and an increase in the expression of Glul, which was higher in WT. Ptchd1 expression was much higher in caveolin-1 knockout MEFs in comparison to WT, and the expression was reduced with glucocorticoids. The gene Ptchd1 (Patched domain containing 1) encodes a membrane protein with a patched domain. The Sonic Hedgehog receptor Patched has previously been co-precipitated with Caveolin-1, and therefore Caveolin-1 may be associated with structuring complexes for Wnt and TGF-β signalling (Karpen et al. 2001). This gene was identified in a previous microarray to be strongly variable between wild-type and Cav-1 KO MEFs, and this finding is reinforced here. The increased Ptchd1 receptor expression in CavKO cells may contribute to the proliferative phenotype of CavKO cells, as Hedgehog signalling is involved in proliferation (Plaisant et al. 2011). GC decrease in Hh receptor complexes could decrease proliferation induced by this route. Metallothionein 1 (MT1) expression was induced by dexamethasone, and this was much higher in CavKO cells compared to WT. Metallothionein 1 (MT1) is a protein with a high number of cysteine residues that bind heavy metals. Transcription of metallothioneins is upregulated by heavy metals and glucocorticoids; the promoter sequence for MTs contains GRE consensus sequences allowing glucocorticoid receptor response element binding (Kelly et al. 1997). MTs are thought to protect against oxidative stress by binding oxidant radicals (antioxidant activity) (Ghoshal et al. 1998). MTs have anti-inflammatory roles in various inflammatory conditions, and modulate activation of NF-κB (Inoue et al. 2009; Waeytens et al. 2009). The suppression of NF-κB activity in caveolin knockout mice found by (Garrean et al. 2006)may be mediated by this enhanced MT1 expression. Glutamate-ammonia ligase (Glul) was induced by dex in both WT and CavKO cells, with a higher response in WT. Glul (glutamate-ammonia ligase or glutamine synthetase) is a catalyst for the synthesis of glutamine from glutamate and ammonia. Glutamine is a source

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of cellular energy, and has anti-inflammatory effects in vivo by reduced NF-κB activity, attenuated degradation of IKBα, inhibition of MAPK and ERK signalling pathways, and thereby reduces inflammatory cytokine production (Coeffier et al. 2001; Singleton et al. 2005; Singleton and Wischmeyer 2008). These results support the finding by (Olkku et al. 2004) that GC induce expression of Glul, and the induction of this may be dependent on caveolin. Glutamine provides energy for activated immune cells, the energy demand is high for processes such as phagocytosis in macrophages. It is possible that this reduced induction of Glul in CavKO mice could result in a lower energy production, and may explain the finding of (Yuan et al. 2011) of reduced phagocytic ability in CavKO macrophages, in in vivo bacterial challenge.

4.1.2.2 Glucocorticoid receptor regulated genes that are not dependent on caveolin include GILZ, Zfand5 and Stc1 The glucocorticoid-induced response in GILZ (Glucocorticoid-induced Leucine Zipper), Zfand5 (Zinc Finger AN1-domain containing 5) and Stc1 (Stanniocalcin1) do not appear to be influenced by caveolin. These genes showed a change in expression level in response to glucocorticoid treatment, with an increase in expression of GILZ and Zfand5, and a reduction in the expression of Stc1. The response of GILZ expression induced by dexamethasone was almost identical in WT and CavKO cells on average, with a difference of around 6 units (fold change) above or below the response in WT cells when the results are seen individually. GILZ is a gene that is well known to be induced by dexamethasone, and may be seen to have an additive action to classical glucocorticoid effect on inflammatory pathways by transrepression (Ayroldi and Riccardi 2009). Perhaps because of the nuclear-localisation of its activity, and its similar role to classical glucocorticoid genomic activity, there is less of a requirement for caveolin in the mediation of this pathway. Zfand5 is said to interfere with NF-κB by competition for IKKγ (Huang et al. 2004a), in this way it inhibits NF-κB activation in certain circumstances, such as activation induced by TNF- α, IL-1 and Toll-like receptor 4 (TLR4) activation, and may have a role in regulation of NF-κB activation and apoptosis. There does not appear to be much research linking Zfand5 to GR and if any interaction occurs between them, apart from a few instances of gene arrays that find it is upregulated with GR and PKA (Misior et al. 2009) or NF-κB co-activation (Rao et al. 2011). Here, we also find that GR activation induces transcription of Zfand5 in MEFs, and that this seems to not be reliant on Caveolin-1, as the level of basal expression and GC- induced expression are similar between the two cell types.

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Stanniocalcin 1 levels in untreated cells were similar in untreated MEFs with and without caveolin. The level of Stc1 reduced to about half with dexamethasone treatment, when experiments were averaged. However, when looking at the results individually, in some cases signalling Stc1 expression was much higher in CavKO cells than WT, and vice versa, although in all cases dex reduced Stc1 expression. Previous studies have found a divergence in the effect of GC on Stc1, with some finding an increase (Li and Wong 2008) and others a decrease (Groves et al. 2001). (Yeung and Wong 2011) found that Stc1 expression was inhibited with inhibition of PKB/Akt and GSK3β, which may be a mechanism by which glucocorticoid action could increase the expression of Stc1. Upregulation of ERK1/2 as a pro-survival signalling mechanism has been found to upregulate Stc1 expression, which then acts in a negative feedback loop on MAPK activation by MEK, and GC suppression of this pathway may explain the reduction in Stc1 (Nguyen et al. 2009). It is probable that the Stc1 signalling pathway is complex as many factors come into play, some of which may be mediated by caveolin, and could include cell density or cell cycle, as these cells were not synchronised before the start of each experiment and Stc1 is implicated in proliferation.

4.1.2.3 Genes that do not appear to be strongly regulated by Glucocorticoid receptor in MEF cells include Cdh11, Runx1t1 and RpS6 Dexamethasone treatment did not appear to induce or repress the expression of Cdh11 (cadherin 11), Runx1t1 (Runt-related transcription factor 1; translocated to 1 (cyclin d- related)) and RpS6 (Ribosomal protein S6), nor were there clear differences between Caveolin-1 knockout or wild type cells, which disagrees with the finding of the microarray from which these genes were selected. Cadherin 11 levels did not appear to have high variation in CavKO or WT MEFs, nor was there a clear induction or repression in response to dexamethasone. Cdh11 (Cadherin 11) is an adhesion molecule in cell-cell junctions, and is linked to calcium signalling. Cdh11 is expressed in fibroblasts and embryonic cells, and has been found to be involved in inflammation, where activation causes pro-inflammatory secretion of IL-6 via MAPK and NF-κB (Chang et al. 2011). Cdh11 is increased in wound healing and fibrotic skin, and has been found to be upregulated in pulmonary fibrosis and in response to TGF-β (Schneider et al. 2012). Glucocorticoids have been implicated in the regulation of cadherins, reducing the cadherin expression at the cell membrane and a change in connections with the cytoskeleton. GC effects have been seen in levels of Cadherin-11, E-cadherin, N-cadherin, T-cadherin and VE-cadherin (Blecharz et al. 2008; Bromhead et al. 2006; Celojevic et al. 2012; Evang et al. 2013; Ferrand et al. 2012; Zhang et al. 2010). However, this has not been

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seen to be due to direct GR initiated transcription at the cadherin promoter, rather by indirect interference, such as with cofactors for cadherin expression (e.g. Snail1 in E- cadherin). This may be the case here, as there does not seem to be great change in transcription with dexamethasone treatment, only a slight decrease. Runx1t1 (Runt-related transcription factor 1; translocated to 1 (cyclin d-related)) transcription does not appear to be induced by glucocorticoid activation in wild type or caveolin knockout MEF cells. Runx1t1 is a transcription regulator that interacts with DNA bound transcription factors to recruit transcriptional co-repressors. It has a role in adipogenesis inhibiting activation of C/EBPα promoter by C/EBPβ (Rochford et al. 2004). C/EBPα is also involved in regulation of differentiation and cell function in various tissues, such as differentiation of monocytes to granulocytes (Ross et al. 2004). C/EBPα/β has been seen to transform fibroblasts to macrophage-like cells (Feng et al. 2008). C/EBP expression is altered in response to acute inflammation to control expression of various cytokines (Poli 1998), for example in response to NF-κB in neutrophil production, C/EBPα as inhibitor of IL- 10 (anti-inflammatory cytokine) production by binding to the promoter, and may be involved in glucocorticoid signalling in the lung (Jang et al. 2013; Roos and Nord 2012; Wang et al. 2009). However, it does not appear that in mouse embryonic fibroblasts under these conditions that Runx1t1 expression is induced by dexamethasone, and it is unclear whether C/EBP is produced by another means. Ribosomal protein S6 expression does not appear to be induced by glucocorticoid treatment in Caveolin-1 knockout or wild type cells. RpS6 (Ribosomal protein S6) is part of the Ribosomal 40S subunit, which is involved in checking complementarity of tRNA to mRNA in translation. Phosphorylation of RpS6 is involved in proliferation and protein synthesis, and is thought to be a downstream effector of PKB/Akt/mTOR signalling (Ruvinsky et al. 2005). mTOR signalling is thought to regulate inflammatory effects by suppression of NF-κB, as with GC, and inhibition of mTOR signalling with rapamycin also inhibits the action of GC in therapeutic use (Weichhart et al. 2011). However, it does not appear that glucocorticoids induce transcription in MEFs under the conditions here. It is possible that, as was suggested in the varying levels of protein phosphorylation, that the regulation of these genes may also be more variable in stressed environments, such as serum starvation.

4.1.3 Altering membrane fluidity to investigate the translocation rate of GR Lipid rafts are areas of the cell membrane enriched with cholesterol, glycoproteins and sphingolipids. Signalling proteins are known to associate with lipid rafts, and by this means, 162

signalling complexes are promoted, leading to for e.g. phosphorylation cascades. The addition of cholesterol to a membrane increases the formation of lipid rafts (Crane and Tamm 2004). Translocation of GR to the nucleus is mediated by chaperone proteins such as hsp90, hsp70, FKBP51 and FKBP52 etc., that keep the receptor in an open conformation to receive ligand in the cytoplasm, and these chaperone proteins and GR are subject to post- translational modifications in order to transport the receptor to the nucleus (Echeverria et al. 2009; Kovacs et al. 2005). In order for these post-translational modifications, such as phosphorylation and acetylation to take place, the receptor complex requires further proteins to be recruited and activated in order to become activated. This large complex requires an element of order to organise the contact and proximity of proteins, and it has been suggested that in genomic signalling, as well as non-genomic signalling, scaffolded signalling complexes exist to structure and facilitate signalling (Millar and Pawson 2004), and these localise to caveolae lipid rafts. Lipid rafts can be disrupted, changing signalling within the cell; methylcyclodextrin can remove cholesterol from a membrane (Zidovetzki and Levitan 2007), and simvastatin disrupts synthesis of cholesterol by the cell, and therefore also depletes cholesterol from lipid rafts (Zhuang et al. 2005). To investigate if lipid raft composition had an effect on GR translocation in live cells, a fluorescent Halo-tag fusion protein vector of GR was transfected, and cells were treated with compounds to alter membrane fluidity. Dexamethasone was added, and the translocation of GR was recorded.

There was a difference between control and manipulated cells in rates of GR translocation, where translocation was slightly longer in cells treated with cholesterol (+4.6 min, p=.002, small sample), methylcyclodextrin (+6.4 min, p=.02) and simvastatin (+4.1 min, p=.162). Measured rate of translocation of GR is comparable to that measured in GFP-conjugated GR to fully translocate to the nucleus (29.8 min) (Htun et al. 1996). It might be anticipated that increasing the cholesterol content of membranes would cause the membrane to become more rigid, as the membrane becomes less disordered. This may limit the ability of signalling molecules to move and come in to contact, and may increase the signalling of the cells as signalling molecules cannot move as easily to dissociate. This was found in T-cells, where cholesterol increase sensitised cell surface interleukin receptors and STAT signalling pathways (Surls et al. 2012). Cholesterol enrichment also has effects on most ion transport proteins in the cell membrane, activating most transporters and inhibiting ATPases (Bastiaanse et al. 1997), thereby changing the cellular conditions and homeostasis. Ablation of lipid rafts, on the other hand, could decrease the rate of

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activation of receptors, as the scaffolding effect may be altered, making it less likely that the right conformation of signalling molecules come in to contact compared to the rapid signalling with scaffolding, thereby slowing GR activation and translocation.

With cholesterol depleting agents, Methylcyclodextrin and Simvastatin, effects on signalling pathway involving PKB/Akt have been measured (Zhuang et al. 2005), and Ras ERK and PKC (Kabouridis et al. 2000), affecting cell survival. Methylcyclodextrin has been shown to have a direct effect on cell signalling via tyrosine kinases. Of the cells that had been transfected, it was possible to see cells that were in the process of cell division as well as cells that underwent apoptosis. In cells that divided, there was a delay in the translocation of GR to the nucleus as this occurred after the cell had completed division. Cell division was observed more in cells treated with methylcyclodextrin, possibly via activation of the Ras/MAPK/ERK pathway as has been found previously (Kabouridis et al. 2000). Apoptosis occurred most in cells treated with simvastatin, although some instances occurred in other treatment conditions. It was only possible to visualise these processes in cells that had been successfully transfected, the total number of cells affected is unknown. Lipid raft depletion has previously been found to increase levels of apoptosis (Li et al. 2006), via the PKB/Akt signalling pathway (Zhuang et al. 2005). Apoptosis could have occurred overnight during treatment, this may be evident in the low percentage of transfected cells and the apparent low density of cells when choosing positions for recording, despite plating to a density of 1x105cells/ml. Ideally, cholesterol addition and removal conditions should be optimised for the cell type, and the effect on cholesterol present quantified (Zidovetzki and Levitan 2007). Here, low concentrations were used as the procedure was of long duration. In the protocol by (Kline et al. 2010), they state that a different cyclodextrin, 2-hydroxypropyl-β-cyclodextrin, causes less extensive damage than methyl-β-cyclodextrin when used to remove cholesterol from cell membranes, however, altered signalling profiles would still initiate apoptosis.

4.1.4 Limitations of experimental conditions involving transfection

4.1.4.1 Caveolin rescue in MEFs from caveolin-1 knockout mice The efficiency of caveolin rescue with transfection to Caveolin-1 KO MEF cells had been variable across experiments, as seen in Western blot and immunofluorescence, and there appeared to be a variation in the level of caveolin recovery between the two constructs, Cav1 myc RFP and hCav1. Transfection with RFP-conjugated caveolin appears to have greater success, resulting in a higher level of protein expression detectable when compared with transfection with hCav1 expression vector. Recovery of caveolin expression with 164

hCav1 was approximately a third of that achieved with Cav myc RFP, measured on Western blot. Cav myc RFP expression may be improved by the presence of c-myc in the vector construct, which targets expression to the constitutively active CMV promoter. To assay if transfection duration may increase the level of recovery in caveolin expression, cells were transfected with either hCav1 or Cav myc RFP expression vectors and incubated for 24, 48 and 72 h, and caveolin expression measured by Western blot. The longer the cells were incubated after transfection, the higher the level of caveolin detected. The increase in protein expression was linear, but not exponential, and therefore may have limiting factors. Beyond this 72 h, detectable levels may drop again, as the transfection is transient. The duration of transfection is dependent on the turnover of protein in the cell, and the rate of cell division (Kim and Eberwine 2010). In this experiment, levels of Cav myc RFP expression were lower than hCav1 expression, contrary to previous findings. In all of the gene targets for RT-QPCR, there was no difference in levels of gene expression between transfected and CavKO cells. The rate of transfection efficiency, as seen in Western blot and immunofluorescence to be at best around 20% of the caveolin expression seen in wild type cells. This was not enough to cause a significant change in the expression of these targets, and any variation of expression was within the range of expression for CavKO cells. The expression in transfected cells was therefore equivalent to the expression in CavKO cells. In terms of practicality, Western blotting when used to confirm transfection efficiency for these experiments, and was found to be a less time-sensitive and more effective method of establishing transfection levels in comparison to immunofluorescence, as it is easier to quantify and can show the total level of caveolin in a population of cells. This was especially evident in cases where the antibody for caveolin had not been optimised, and therefore it was difficult to accurately state the level of transfection success without protein content.

4.1.4.2 Caveolin Knockdown by interference with gene expression MEF cells cultured from CavKO mice may have more variations in signalling than just the absence of caveolin. As compensation mechanisms may occur with global knockout, it would be interesting to compare the pathways in caveolin-1 knockdown and knock out and see how this affects GR signalling. In order to investigate protein ablation in wild type cells, it is possible to use small interfering (si) RNA to knock down expression transiently, or small hairpin (sh) RNA that is inserted to the genomic DNA and expressed for a longer duration knockdown of protein expression. Protein knockdown with siRNAs works by the siRNA binding to messenger RNA (mRNA) and inhibiting translation, as the double stranded RNA is targeted for degradation. With siRNA against caveolin, A549 cells responded well to 165

caveolin knockdown, although this was not 100% reduction in expressed protein. MEFs were much less responsive to caveolin knockdown, with maximal response at 72h being approximately 25% reduction in expression compared to levels in control siRNA treated cells at the same time point. The siRNA may be less specific for mouse Cav-1 than human Cav-1, although there are only around 11 amino acids that are different in sequence homology comparisons between human and mouse caveolin (Tang et al. 1994). In addition, knockdown of caveolin in MEFs with shRNA was attempted, yet the results were inconclusive (data not shown). Over time, overall caveolin expression in A549s decreased with longer incubation times in control-treated as well as those targeted with siRNA. This cannot be explained by contact inhibition, or serum starvation, as both these have been found to increase caveolin expression (Galbiati et al. 2001). GR expression also decreased with time. It is possible that the longer exposure to transfection reagents in the media may have toxic effects, and cause down-regulation of proteins, which may account for this confounding factor (Breunig et al. 2007).

4.2 In vitro to in vivo determination of Glucocorticoid Receptor and Caveolin pattering in cells and tissues

4.2.1 Determining caveolin isoform expression patterns Different caveolin antibodies, raised in rabbit and goat to the different isoforms of caveolin, 1, 2, and 3, as well as antibodies to glucocorticoid receptor were used to assay relative levels in MEFS and mouse tissues, lung, liver, brain and gut, as well as establishing the efficacy of the goat-derived antibodies. The goat-derived caveolin 1 antibody did not detect much caveolin 1 compared to the rabbit-derived caveolin 1 antibody in cell and tissue samples, with stronger staining from the rabbit-derived Cav1 antibody sc894 in the brain and liver, suggesting that sc894 may have a higher binding affinity. Lung tissue has high levels of all caveolin isoforms, and glucocorticoid receptor. Liver and brain tissues also have detectable levels of GR and caveolin 1 and 2, although this is not as high as in the lung tissue. This supports the finding that caveolin in the liver is related to regeneration from injury and adipogenesis (Frank and Lisanti 2007; Mastrodonato et al. 2012), and that caveolin was identified in the brain (Cameron et al. 1997), where it has been implicated in blood-brain-barrier function (Deng et al. 2012), as has glucocorticoid action (Blecharz et al. 2008). The goat caveolin 2 antibody detected Cav2 in the three cell types at similar levels, this is because the caveolin knockout mice (caveolin-1 knockout) still express caveolin 2, yet this is not present at the cell membrane as it cannot be trafficked to the cell membrane in the 166

absence of caveolin 1. This effect was also seen in fixed cell immunofluorescence, where sc894 (rabbit-raised) Cav1 antibody showed signal at the Golgi body at high exposure levels, by cross reacting with Cav2 in the absence of Cav1, which supports the finding of (Mora et al. 1999). Caveolin 3 was not detected in MEF cells, as this is specific to muscle cells and is found to be involved in nAChR signalling at the neuromuscular junction (Hagiwara et al. 2000; Hezel et al. 2010). Caveolin is differentially expressed in different tissues of the body. Caveolin 3 was not strongly detected in any of the tissues taken from the lung, liver, brain and gut, and these tissue samples have low levels, if any, of muscle fibres. On comparing the tissue samples, the protein extracted from gut tissue appears to have been degraded, this may be because there are high levels of enzymes in the gut (Motta et al. 2011) that were not effectively removed or counteracted with enzyme inhibitors in lysis buffer, and protease digestion of tissues would start quickly after death. Interestingly, β-actin and α-tubulin also had varying levels of expression in the different tissues, this should be considered when comparing between different tissues.

4.2.2 Determining caveolin and GR patterning in fixed MEF cells, relation to cell polarity and migration In fixed wild type MEF cells, staining for caveolin with sc894 antibody shows banding patterns. This could indicate the interaction of caveolin with the cell cytoskeleton that may be involved in cell migration, where caveolin-1 anchors caveolae to the actin cytoskeleton (Navarro et al. 2004). In the cell transfected with caveolin, this appears to be concentrated on one side of the cell. This may be related to the role that caveolin 1 has in cell polarisation and directional migration, where (Grande-Garcia et al. 2007) found caveolin to be involved in the inactivation of Src kinase and Rho and Rac GTPase signalling pathway necessary for directional migration in fibroblasts. GR staining with M20 GR antibody showed strong staining at the lamellipodia of the cell, which may also indicate an association with the actin cytoskeleton in cell motility, as GR is associated with adherens junctions, by association with α-catenin (Stojadinovic et al. 2013), which are involved in actin filament organisation in polarised fibroblasts and epithelial cells (Yonemura et al. 1995). Additionally, glucocorticoid-induced phagocytosis by macrophages has been associated with high levels of Rac (Giles et al. 2001). Rac activity is controlled by Serum/Glucocorticoid –regulated kinase (SGK), expression of which is induced by GC (Webster et al. 1993) and which phosphorylates Rac, and is downstream of P13K/PKB/Akt signalling (Park et al. 1999). In response to FITC-conjugated dex, GR mainly translocated to the nucleus, but GR also showed some evidence of co-localisation with phalloidin-stained

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actin at the edge and projections of the cell. This related patterning of caveolin and glucocorticoid receptor and related overlap in signalling pathways could indicate a relation between caveolin-1 and GR in cell migration in fibroblasts and inflammation.

4.2.3 Quenching of autofluorescence in lung and liver tissue Liver and lung tissues have a level of autofluorescence that can be confounding to identification of specific signals in immunofluorescent labelling. Autofluorescence can be useful in certain diagnostic applications, as it does not require staining, and levels of autofluorescence can change in certain disease states, such is where there is an increase in production of collagen or other endogenous fluorophores (Monici 2005) In order to visualise the distribution of caveolin and GR in the lung, it was necessary to reduce the amount of fluorescence in the tissue. (Viegas et al. 2007) identified two methods to reduce autofluorescence, UV exposure and Sudan Black B stain. Under UV radiation, autofluorescence in the tissues was increased, this is indicative of the composition of the tissues, as several components of endothelia have been found to increase fluorescence with UV radiation, these include the pigment melanin, and the amino acid tryptophan (Brancaleon et al. 1999; Elleder and Borovansky 2001; Schaue et al. 2012). Sudan Black B staining was much more effective at quenching autofluorescence, although it was unable to quench the induced additional fluorescence from UV exposure. Sudan Black B has been found to be effective in quenching autofluorescence in other tissues, such as brain and renal tissue (Schnell et al. 1999; Sun et al. 2011), and had been achieved in liver in the Viegas (2007) study. Autofluorescence was not found in the far red channel, CY5, and autofluorescence was best reduced in the FITC green channel. Therefore, it was decided to proceed with a different secondary, Alexa Fluor 647, which fluoresces in the CY5 channel (Ex. BP620/60, Em. BP700/75), rather than Alexa Fluor 594, and Alexa Fluor 488 (green) which fluoresces in the FITC green channel, (Ex. BP480/40, Em. BP535/50) to enable dual labelling using two different antibodies.

4.2.4 Dual-labelling of Caveolin-1 and GR in the lung in vivo The distribution of caveolin in the lung as seen with labelling with goat-derived anti-Cav1 antibody with Alexa Fluor 488 supported previous immunohistochemical staining for caveolin in mouse lung (Odajima et al. 2007). GR appears to be present in different cell types in these lung sections, including the cells lining blood vessels and bronchi, with focal points of strong staining near or overlapping with the nuclei of some of the cells of the alveoli, but not all. This may identify between type I and II pneumocytes that comprise the alveoli, with GR present in type II pneumocytes as has been found previously (Fujisawa et 168

al. 1986; Zhang et al. 2011). There was a lot of overlap between cells that expressed both caveolin and GR in the lung, and it would be interesting to assay these sections using biomarkers , for example to Clara cells (Tsao et al. 2007), to identify cell types where GR and caveolin strongly co-localise, and where they are not found together.

4.3 Investigating how caveolin affects the anti-inflammatory effects of glucocorticoids in the lung using knockout mice. In inflammatory challenge with injected endotoxin in humans and mice, there is a peak in signalling response in TNF-α and other cytokines and chemokines ~2 h after challenge, and by 4 h the levels of pro-inflammatory signalling molecules are reduced in order to limit inflammatory signalling and lead to resolution. Around 4 h is when there is the maximal change in circulating white blood cells, for example, increase in circulating neutrophils (neutrophilia) reaches a plateau, and there is an increase from this point in expression of anti-inflammatory factors (Copeland et al. 2005; Haddad et al. 2001; Remick et al. 1989).

4.3.1 Changes in circulating corticosterone levels in vivo LPS-exposed wild type mice had the highest levels of serum corticosterone, with GC release induced by inflammatory signalling in the normal stress response (Necela and Cidlowski 2004). Levels were lower in CavKO mice exposed to LPS, indicating an insufficiency in GC signalling in these mice. With Dex treatment, levels of corticosterone in WT mice were suppressed, and this level of suppression was even greater in CavKO mice. With dexamethasone, the level of circulating hormone was nearly zero in CavKO mice. The injected dexamethasone could have had an additive effect on the lower production in CavKO mice by negative feedback and suppression of the HPA axis (Di et al. 2003; Evanson et al. 2010), perhaps with enhanced signalling on the feedback axis from dysregulated signalling in CavKO cells by some mechanism involving the hyper-activated signalling pathways seen at resting state. There was some variation between female and male levels, with the female being slightly lower than male in CavKO LPS, and a larger divide between WT male and female, with female again lower. Caveolin KO mice appear to have suppression of circulating hormone, which could result in a diminished inhibition of inflammation. It must, however, be remembered that circulating corticosterone levels have a circadian rhythm, which are controlled by the suprachiasmatic nucleus control of the HPA-axis, as well as showing pulsatile release in response to stress (Chung et al. 2011; Kalsbeek and Buijs 2002; Sarabdjitsingh et al. 2012). Animals were sacrificed over a long time period, which may have coincided with differing levels of circulating corticosterone,

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and this may be reflected in these results, for example with females sacrificed later in the day than males.

4.3.2 CavKO mice had higher levels of infiltrating immune cells in the airways, than WT

Figure 4-1 Immune cells in BAL fluid

Cell count of total neutrophils in bronchoalveolar lavage (BAL) fluid from Caveolin-1 knockout mice, subject to aerosolised challenge with LPS, with dexamethasone A) Total neutrophil count from differential count of cells from BAL fluid from WT and CavKO mice subject to aerosolised challenge with Saline vehicle, LPS 2 mg/ml, for 20 min, and with 1 mg/kg dexamethasone 1 h prior to challenge. BAL fluid collected 4h post-challenge B) Frame of CytoSpin with Leishman’s stain, cells tagged according to type. 40x magnification.

CavKO mice exposed to LPS had the highest number of cells in the airways, as was suggested in the H&E stained sections where immune cells could still be seen in the airways. Additionally, males had higher cell infiltration than females.

4.3.3 Phosphorylated protein changes between wild type and Cav KO lung Western blot was performed for signalling proteins in mouse lung 4 h subsequent to inflammatory challenge. This will not show levels of signalling directly induced by the inflammatory stimulus, but will show which pathways may still be activated or affected in the switch to a resolving state. Levels of phosphorylated GR (ser211) in mouse lung were lower in LPS-treated mice, with the lowest levels in CavKO LPS treated mice. Total glucocorticoid receptor levels were also decreased. This may be explained by ligand-dependent degradation of the GR in order to limit hormone responsiveness following activation and gene transcription effects (Wallace and Cidlowski 2001), as these mice appeared to have had the biggest inflammatory response. However it could also indicate a global reduction in the amount of glucocorticoid

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present and active in CavKO mice. In vitro, MEFs from CavKO mice had a lower total GR than WT mice, so it is possible that they have an overall reduction. Phosphorylated NF-κB signalling was high in Dex and LPS treated WT mice, suggesting continued pro-inflammatory signalling not inhibited by dex. Phospho-NFκB was very low in LPS-treated CavKO mice in comparison to WT. With dex and LPS, phospho-NFκB was induced in WT mice, and was higher than LPS alone in CavKO. Pre-treatment with dexamethasone before in vivo LPS challenge has been found to not inhibit NF-κB at low doses, and increase NF-κB activation at high doses (Sadikot et al. 2001) which may be what is seen here in WT mice, and that dex pre-treatment at levels that inhibit TNF-α production does not affect miRNAs expression, indicating a role for non-classical induction of inflammatory transcription (Moschos et al. 2007). The low levels of NF-κB in CavKO mice may indicate a role for caveolin-dependent inflammatory induction of NF-κB. In dex treated WT mice pPKB/Akt was decreased, and in CavKO this was increased, this reflects the pattern seen in vitro here, as PKB phosphorylation was previously found to be decreased by glucocorticoids in WT but not CavKO. This suggests that GC induced increase in pPKB/Akt occurs in serum starved state, but not in normal tissue, as the PI3K pathway is primed for activation. The difference seen here between WT and CavKO reinforces the suggestion that GC effects on PKB may be caveolin-dependent, but also subject to further regulation in the cell. In LPS-challenge, there was not a great change in levels of phosphorylated p46 SAPK/JNK, with a slight increase only between saline and LPS treated, there was a greater increase in phosphorylated p54-SAPK/JNK. This disagrees with the finding by (Chan et al. 1997) in macrophages that this isoform is preferentially activated with TNF-α. In this study, protein lysates were derived from whole lung, mostly epithelia, which may account for differences as it is not a specific cell type, and gives an average of the response in lung. Response in CavKO and WT mice was similar, indicating that this activation is not caveolin-dependent, in whole lung, but may still be important in specific cell types, as there was a difference in vitro. As with the in vitro assay, dexamethasone was found to reduce levels of SAPK/JNK phosphorylation. IRAK1 levels decreased in LPS-exposed mice, with a larger decrease in CavKO which exhibited a decrease in both 105 kDa and 78 kDa protein isoforms, whereas WT mice had a reduction in 78 kDa only. Dexamethasone treatment reversed this effect on the 105 kDa protein difference, and slightly diminished the reduction in78 kDa. IRAK1 is involved in TLR4 activation in response to LPS, affecting the NF-κB pathway, and differences here indicate different action in the absence of caveolin. IRAK1 has been connected with STAT3

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activation in IL-10 production, aside from classical NF-κB activation (Huang et al. 2004b), and perhaps the different molecular weight bands infer different posttranslational modifications of this kinase leading to different function. Pin1 is a modulator of steroid receptor phosphorylation involved in modulating the function of steroid hormone receptors (Weigel and Moore 2007; Yi et al. 2005). In a recent paper, (Poolman et al. 2013), Pin1 was involved in mediating transactivation, via changes in phosphorylation at ser211 and ser203. Here we see that Pin1 levels are much higher in CavKO mice than WT, and there is a larger reduction in levels with dex pre-treatment with CavKO mice. This could account for the rapid induction in p211 and p203 GR seen CavKO MEFs in vitro. There is a difficulty here of extrapolating from this data, as protein from only two animals per condition could be run together at the same time, and therefore may not be wholly representative. As a follow-up, I would extract protein from all 34 mice and run each treatment group together to see if the reactions were consistent. This may indicate any differences between male and female mice at protein level, as the RT-QPCR data indicates sexual dimorphism at gene expression.

4.3.4 Sex differences in response to glucocorticoids and to LPS Male mice had a higher response than females in the number of immune cells in BAL fluid, GILZ levels with dex pre-treatment and Metallothionein induction with dex pre-treatment whereas females had higher response than males in IL-6 expression and CXCL1/KC expression. This agreed with the finding by (Duma et al. 2010) that glucocorticoid responses are sexually dimorphic, where in response to LPS males had better survival. Here males had increased expression of anti-inflammatory signal, whereas females have enhanced pro- inflammatory signalling. Interestingly, the corticosterone levels recorded did not agree with (Coleman et al. 1998), who found females had a faster induction and reached a plateau at a higher maximal level before males in exercised induced stress, as females were slightly lower than males, although this was 4 h after stimulus. The review by (Kudielka and Kirschbaum 2005) suggests that the female response is greater after HPA axis stimulation. Perhaps with faster induction there is also faster extinction. Human males have been found to be more sensitive than females to glucocorticoids, despite cortisol levels being similar (Rohleder et al. 2001). This may explain what is happening here, as the GC-induced genes are expressed at higher levels in males.

4.3.5 Structural differences between CavKO and WT lung

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Wild type and CavKO lungs appeared to be generally similar, with the same structures visible in each. In some areas it appears that in CavKO sections there is more connective tissue – but this cannot be generalised as some sections of WT lung also appear to have high collagenous tissue. Instead of increased collagen deposits, as since seen in CavKO (Aravamudan et al. 2012), this may represent a different depth of cut through the lung, which shows the larger bronchioles which are supported by a wider band of connective tissue. A trichrome stain, such as Masson’s Trichrome would more clearly stain collagen, and show collagen deposits in the alveolar wall if present, as found in pulmonary fibrosis. One structural element that became visible once comparable sections were put side by side is that the CavKO mice appear to have thickened alveolar septum. It appears that the alveolar spaces are compacted, but again we cannot be certain as the lungs were not fixed inflated. This supports (Park et al. 2003; Razani et al. 2001) in their definition of cellular changes in the lung of caveolin-1 KO mice. There were immune cells in the lumen of airways in caveolin-1 knockout and WT mice that had been exposed to dex. The number of cells was much higher in CavKO mice, supporting the finding of the cell count. There may also be other signs of inflammation here, including an accumulation of fluid in the alveolar space in CavKO mice. These immune cells were much less visible in Dex-treated mice, and became harder to distinguish from normal lung tissue, suggesting that there is a much smaller amount of cell migration in wild type mice lung with immune challenge. This reinforces the finding of the cell count.

4.4 Conclusion Glucocorticoid receptor and caveolin-1 was visualised in lung and cell models to have a colocalisation of expression. In the cell, GR was associated with the actin cytoskeleton at the cell membrane in early glucocorticoid activation, reinforcing the idea of a membrane- associated GR. In the lung, caveolin and GR were seen together in many cells, especially in the alveoli. Interestingly, this was not the case in all cells of the alveoli, which may indicate a difference between type I and type II pneumocytes, where GR is found in type II.

Several differences were found between caveolin knockout and wild type mice, and in embryonic fibroblast cells cultured from these. In looking at protein phosphorylation, there appeared to be differences in the phosphorylation of GR isoforms, with a faster induction of response in Cav-KO cells and a higher change in abundance, with p211-GR increasing ~10-fold in KO and ~8-fold in WT in comparison to control over 90 min. There also appeared to be alterations in phosphorylation of PKB/Akt which in CavKO cells increased

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1.6-fold compared to no discernable change in WT, whereas in LPS challenge in mouse lung, the inverse was found, a ~3-fold decrease in WT that was not found in Cav-1 KO. In vivo there was also a change in phosphorylation of p65-NF-κB, with a greater change in CavKO showing a 6.8-fold decrease over control, which was 8.4-fold lower than the change seen in WT LPS-exposed mice. There also seemed to be variation in other signalling pathways, such as SAPK/JNK, but the small sample size meant that conclusions cannot be drawn with confidence.

Three genes were identified that appeared to be caveolin-dependent in their response to glucocorticoid signalling in vitro, these were Ptchd1, MT1 and Glul. Ptchd1 had high basal levels in KO, 12-fold higher than WT, decreasing to 5.7-fold with dexamethasone, which was not seen with WT. Expression of Glul in WT had a higher basal level, twice that of KO, and a higher induction with dexamethasone, with the induction in CavKO 2/3 of that seen in WT. MT1 showed a greater increase in expression with dexamethasone, increasing 10- fold in CavKO, compared to 5-fold in WT in vitro, and in vivo WT showed a greater increase in expression 16-fold over control, whereas CavKO showed a 5.8-increase over control in lung tissue. In vivo, there was a difference in GILZ expression, though this was not seen in vitro, with LPS there was a 2-fold lower median level in CavKO compared to WT. These differences imply a role for caveolin in glucocorticoid signalling in isolated fibroblasts, and in the lung.

Caveolin does appear to have an influence in glucocorticoid signalling, and has been shown to affect the lung phenotype in Caveolin-1 knockout mice. There appeared to be a sexual dimorphism in response to LPS, and in the glucocorticoid response. These differences may have implications for glucocorticoid therapy, although further research would be needed to increase confidence in these conclusions. The caveolin-dependent differences in glucocorticoid targets MT1, GILZ and Glul and the differences in NF-κB and kinase signalling pathways may have an effect on the modulation of glucocorticoid signalling. The further elucidation of signalling pathways in GR and its relation to caveolin, as to some extent shown here, would be beneficial to enable drug-design for specific on-target effects and the decrease of side-effects.

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