The Role of BRF1 and BRF2 in the Immune Response
Rebecca Crawford
A thesis submitted for the degree of Doctor of Philosophy to the Imperial College Faculty of Medicine
Imperial College London
September 2008
The Kennedy Institute for Rheumatology Division
Faculty of Medicine Imperial College London
Chapter 1 Introduction
Declaration
This thesis is the result of my own work. Some figures were contributed with the help of other members of the laboratory. These figures are labeled as such. The work was carried out at the Kennedy Institute of Rheumatology Division, Imperial College School of Medicine, London.
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Acknowledgements
I would like to thank a number of people for their help, advice and patience over the past four years. First, my supervisor Dr. Andy Clark, who has provided continual support and advice particularly whilst writing this thesis. Secondly I would like to acknowledge the members of the lab who have provided me with ideas and technical assistance throughout my PhD. Finally, I would like to thank Alison, Tom and Liaquat without whose support and encouragement I would have struggled to reach this stage.
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Abstract
Tristetraprolin (TTP), butyrate response factor 1 (BRF1) and butyrate response factor 2 (BRF2) are members of a family of zinc finger containing ARE binding proteins known as the Zfp36 family. They all possess a conserved tandem zinc finger domain, which facilitates their binding to mRNAs that contain adenosine/uridine rich elements (ARE) in their 3’ untranslated region (3’UTR). Binding to the target mRNA results in its destabilisation. Several mRNAs containing an ARE in their 3’UTR are stabilised by the mitogen activated protein kinase (MAPK) p38 pathway. Both the expression and the mRNA destabilising function of TTP are controlled by the p38 MAPK pathway. Much less is known about BRF1 and BRF2 functions, and it is not clear whether their expression or function is regulated by the p38 MAPK pathway. So far no difference has been seen in the binding specificities of the three proteins in vitro, however the phenotypes of knockout mice suggest that they have distinct functions, and may have different mRNA targets in vivo.
Western blotting and quantitative PCR (qPCR) have been used to investigate the expression of members of the Zfp36 family. RNA interference was used to knock down the expression of BRF1 and BRF2 in HeLa cells, and the effects on p38-regulated inflammatory mediator expression were examined. BRF1-/- mouse embryonic fibroblast (MEF) cell lines were used to investigate the function of this family member. No evidence that BRF1 or BRF2 contributes to the post-transcriptional regulation of inflammatory mediators by the p38 MAPK pathway in HeLa cells or MEFs was found. BRF1 null MEFs over-expressed IL-6, protein, IL-6 mRNA and Cox-2 mRNA but did not over-express KC protein. The hypothesis that BRF1 is regulating IL-6 and Cox-2 by controlling mRNA stability was disproved. As a result investigation of the transcriptional regulation of these genes was researched. Primary transcript qPCR showed that both IL-6 and Cox-2 under-go more rapid transcription in BRF1-/- MEFs. This suggests that IL-6 and Cox-2 are indirect targets of BRF1 and that their regulation is through a transcription factor which is itself a target of BRF1.
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Contents
Title page………………………………………………………………………………….....1 Declaration…………………………………………………………………………………..2 Acknowledgements……………………………………………………………………….....3 Abstract…………………………………………………………………………………...…4 Table of contents…………………………………………………………………………….5 List of figures and tables…………………………………………………………………….9
1) INTRODUCTION ...... 22 1.1) The immune system...... 22 1.1.1) Introduction...... 22 1.1.2) Innate Immunity and the inflammatory response- the initial response to infection ...... 22 1.1.3) Leukocytes...... 23 1.1.4) Fibroblasts...... 24 1.1.5) Cytokines ...... 25 1.1.5.1) Interleukin-1 (IL-1)...... 26 1.1.5.2) Interleukin -6 (IL-6) and its receptor ...... 27 1.1.5.3) Cyclooxygenase-1/2 (Cox-1/2)...... 29 1.1.5.4) Chemokine (CXC motif) family: Interleukin-8 (IL-8), growth-regulated oncogene (GRO)α and keratinocyte chemokine (KC)...... 31 1.2) Inflammatory signalling pathways ...... 33 1.2.1) Introduction...... 33 1.2.2) Interleukin-1 receptor (IL-1R) and the toll-like receptor (TLR) superfamily ... 33 1.2.3) IL-1 Signalling...... 34 1.2.4) TLR Signalling ...... 34 1.2.5) The mitogen activated protein kinase (MAPK) pathway ...... 40 1.2.5.1) Extra cellular regulated kinase (ERK) pathway ...... 42 1.2.5.2) MAPKp38 Pathway ...... 43 1.2.5.3) The c- jun amino terminal kinase (JNK) pathway...... 45 1.2.6) The Phosphoinositide 3-kinase (PI3K) Pathway ...... 46 1.3) Gene Expression ...... 47 1.3.1) Introduction...... 47 1.3.2) Transcription...... 48 1.3.2.1) Chromatin structure ...... 48 1.3.2.2) Chromatin modifications ...... 48 1.3.2.3) Transcription activation and repression...... 49 1.3.2.4) Initiation of transcription ...... 50 1.3.2.5) Elongation...... 51 1.3.3) mRNA processing and translation...... 53 1.3.3.1) Introduction...... 53
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1.3.3.2) mRNA regulation- an important mechanism in the control of gene expression...... 55 1.3.3.3) mRNA decay ...... 56 1.3.3.4) Processing bodies (PBs) and stress granules (SGs)...... 58 1.3.3.5) mRNA surveillance: Nonsensense-mediated decay (NMD) ...... 60 1.3.3.6) RNA interference (RNAi) pathway ...... 61 1.3.4) Adenosine/ uridine rich element (ARE) mediated decay (AMD) ...... 62 1.3.4.1) Introduction...... 62 1.3.4.2) Classification of AREs ...... 63 1.3.5) Signalling pathways and mRNA decay ...... 64 1.3.5.1) The p38 pathway and mRNA stabilisation...... 65 1.3.5.2) Mechanism of p38 mRNA mediated stabilisation...... 66 1.4) Adenosine/uridine rich element binding proteins (AUBPs)...... 68 1.4.1) Introduction...... 68 1.4.1.1) Human antigen R (HuR)...... 68 1.4.1.2) Heterogeneous ribonucleoprotein (hnRNP)...... 71 1.4.1.3) T cell –restricted antigen (TIA)-1 and TIA related protein (TIAR) ...... 74 1.4.1.4) The far upstream sequence element binding protein (FBP) family...... 76 1.4.1.5) The zinc finger 36 (Zfp36) family ...... 79 1.4.1.5.1) Introduction...... 79 1.4.1.5.2) The tandem zinc finger (TZF) domain ...... 79 1.4.1.5.3) Discovery of Zfp36 proteins...... 80 1.4.1.5.4) Expression and localisation ...... 82 1.4.1.5.5) Knockout phenotypes and binding targets...... 83 1.4.1.5.6) Phosphorylation ...... 88 1.4.1.5.7) Mechanism of Zfp36 mediated mRNA decay ...... 90 1.5) Aims...... 91 2) MATERIALS AND METHODS...... 93 2.1) Materials ...... 93 2.1.1) General...... 93 2.1.2) Antibodies...... 94 2.1.3) Inhibitors...... 95 2.2) Tissue culture...... 96 2.2.1) A549 cells ...... 96 2.2.2) HeLa cells ...... 96 2.2.3) Isolation and culture of mouse bone marrow derived macrophages ...... 96 2.2.4) Mouse embryonic fibroblasts (MEFs) ...... 97 2.2.5) RAW264.7 cells...... 97 2.2.6) Freezing and thawing of cell stocks...... 98 2.3) Transient transfections...... 98 2.3.1) Transient transfection of pFLAGCMV-TTP, pFLAGCMV-BRF1, pFLAGCMV-BRF2 plasmids into HeLa cells...... 98 2.3.2) Transient transfection of HeLa cells with siRNA...... 98 2.4 Cell harvesting and extract preparation...... 99 2.4.1) Preparation of whole cell lysates ...... 99 2.4.2) Preparation of nuclear and cytoplasmic protein extracts...... 99
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2.4.3) Bradford protein assay...... 99 2.4.4) SDS polyacyrilamide gel electrophoresis (PAGE)...... 100 2.4.5) Transfer of protein onto polyvinylidene difluoride (PVDF) or nitrocellulose membranes ...... 100 2.4.6) Western blotting...... 100 2.4.7) IL-6 and IL-8 human ELISAs...... 101 2.4.8) IL-6 and KC mouse ELISAs...... 102 2.5 Molecular biology ...... 102 2.5.1 Cloning of BRF1...... 102 2.5.2) Subcloning of BRF1 into pCMVFLAG vector ...... 103 2.5.3) Site directed mutagenesis ...... 104 2.5.4) Small scale preparation of plasmid DNA (Miniprep)...... 104 2.5.5) large scale preparation of plasmid DNA...... 104 2.5.6) RNA extraction...... 105 2.5.7) Quantitative reverse transcriptase PCR (RT-qPCR)...... 105 2.5.7.1) Taqman® ...... 106 2.5.7.2) Primary Transcript PCR ...... 106 2.5.7.2.1) Reverse transcription ...... 106 2.5.7.2.2) Primer design and optimisation ...... 107 2.5.7.2.3) Reaction composition and conditions...... 108 3) CHAPTER 3: DIFFERENTIAL EXPRESSION OF MEMBERS OF THE ZFP36 FAMILY ...... 110 3.1) Characterisation of antibodies and antisera against the Zfp36 family of proteins. 110 3.1.1) Introduction...... 110 3.1.2) Characterisation of antibodies and antisera...... 112 3.1.3) Summary...... 113 3.2) Expression of Zfp36 family members– protein and mRNAs ...... 118 3.2.1) Introduction...... 118 3.2.2) Expression of Zfp36 family members in HeLa cells ...... 118 3.2.2.1) Zfp36 protein expression in HeLa cells in response to inflammatory stimuli ...... 118 3.2.2.2) Expression of Zfp36 mRNAs in HeLa cells treated with inflammatory stimuli...... 123 3.2.2.3) Effects of dexamethasone on the expression of Zfp36 proteins ...... 127 3.2.2.4) Effects of dexamethasone on expression of Zfp36 mRNAs...... 127 3.2.3) Expression of Zfp36 family members in A549 cells ...... 131 3.2.3.1) Zfp36 protein expression in A549 cells...... 131 3.2.3.2) Zfp36 mRNA expression in A549 cells...... 131 3.2.4) Expression of Zfp36 family in RAW264.7 cells ...... 134 3.2.5) Expression of Zfp36 family in primary macrophages ...... 134 3.3) Summary and discussion ...... 138 4) CHAPTER 4: KNOCKDOWN OF BRF1 AND BRF2 IN HELA CELLS...... 151 4.1) Introduction...... 151
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4.2) BRF1 knockdown ...... 151 4.2.1) Optimisation of BRF1 knockdowm...... 151 4.2.2) Use of individual siRNA duplexes to silence BRF1 expression ...... 152 4.2.3) Consequences of BRF1 knockdown...... 156 4.3) BRF2 knockdown ...... 161 4.3.1) Optimisation of BRF2 knockdown...... 161 4.3.2) Use of individual siRNA duplexes to silence BRF2 expression ...... 161 4.3.3) Consequences of BRF2 knockdown...... 161 4.4) Summary and Discussion ...... 168 5) CHAPTER 5: INVESTIGATION OF PUTATIVE TARGETS OF BRF1...... 174 5.1) Introduction...... 174 5.2) Characterisation of BRF1 +/+ and BRF1-/- MEFs ...... 174 5.2.1) Expression of Zfp36 proteins in MEFs...... 174 5.2.2) Morphology of BRF1+/+ and BRF1-/- MEFs ...... 175 5.2.3) p38 phosphorylation in MEFs ...... 175 5.3) Consequences of BRF1 knockout on protein expression of ARE containing inflammatory mediators in MEFs ...... 179 5.4) Consequences of BRF1 knockout on mRNA expression of ARE containing inflammatory mediators in MEFs ...... 186 5.5) Does BRF1 exert post-transcriptional control over IL-6 and or Cox-2? ...... 193 5.6) Validation of primary transcript qPCR technique ...... 204 5.6.1) Introduction...... 204 5.6.2) Primary transcript qPCR...... 204 5.6.3) Optimising primers ...... 206 5.6.4) Non-reverse transcribed controls and melting curves...... 206 5.6.5) Verification of product using agarose gel...... 208 5.6.6) IL-6, Cox-2 and KC Primary transcript qPCR ...... 210 5.6.7) Normalising to GAPDH primary transcript mRNA ...... 218 5.7) Does BRF1 function as a transcription factor or does it regulate expression of another transcription factor? ...... 220 5.7.1) Do BRF1-/- cells up-regulate IL-6 gene transcription in an NFκB and HAT dependent manner?...... 221 5.7.2) Is BRF1 a direct or indirect regulator of IL-6 gene expression? ...... 227 5.7.3) Transcription factor analysis...... 229 5.8) Summary and Discussion ...... 232 6) CHAPTER 6: FINAL DISCUSSION...... 251 References...... 260
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List of figures and tables
Figure 1.1: The three TLR signalling pathways Figure 1.2: Signalling cascades leading to activation of the MKs Figure 1.3: The deadenylase as an inhibitor of translation initiation and decapping Figure 1.4: Mechanisms of RNA degradation Figure 1.5: A Schematic representation of TTP, BRF1, and BRF2 Figure 3.1: Peptide sequence alignment of human BRF1, human BRF2, human TTP and mouse TTP Figure 3.2: Characterisation of rat monoclonal antibodies Figure 3.3: Characterisation of commercial antibodies Figure 3.4: Characterisation of SAK 20 and SAK 21 antibodies Figure 3.5: IL-1α induced changes of Zfp36 family members in IL-1α stimulated HeLa cells Figure 3.6: PMA induced changes of Zfp36 family members in IL-1α stimulated HeLa cells Figure 3.7: IL-1α and PMA induced chages in expression of TTP, BRF1 and BRF2 mRNA in HeLa cells Figure 3.8: Relative abundances of Zfp36 mRNAs Figure 3.9: Dexamethsone induced changes of Zfp36 protein expression in HeLa cells Figure 3.10: Dexamethasone induced changes of Zfp36 mRNA expression in HeLa cells Figure 3.11: IL-1α and dexamethasone induced changes of Zfp36 protein expression in A549 cells Figure 3.12: IL-1α and dexamethasone induced changes of Zfp36 mRNA expression in A549 cells Figure 3.13: LPS and dexamethasone induced changes of Zfp36 protein expression in RAW264.7 cells Figure 3.14: LPS and dexamethasone induced changes of Zfp36 protein expression in primary mouse macrophages Figure 4.1: Optimisation of the knockdown of BRF1 in HeLa cells using Smartpool® siRNA
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Figure 4.2: Optimisation of the BRF1 knockdown in HeLa cells using individual duplexes Figure 4.3: BRF1 knockdown had no effect on Cox-2 protein Figure 4.4: BRF1 knockdown using siRNA had no effect on IL-6 protein Figure 4.5: BRF1 knockdown using siRNA had no effect on IL-8 protein Figure 4.6: Optimisation of BRF2 knockdown in HeLa cells using Smartpool® siRNA Figure 4.7: Optimisation of the BRF2 knockdown in HeLa cells using individual duplexes Figure 4.8: Cox-2 is slightly up-regulated in response to BRF2 knockdown Figure 4.9: BRF2 knockdown had no effect on IL-6 protein Figure 4.10: BRF2 knockdown has no effect on IL-8 protein Figure 5.1: Zfp36 protein expression in BRF1+/+ and BRF1-/- MEFs Figure 5.2: The morphology of BRF1+/+ and BRF1-/- MEFs differs Figure 5.3: Pp38 is detected 15 minutes after IL-1α treatment in BRF1+/+ and BRF1-/- MEFs Figure 5.4: Cox-2 protein is constitutively expressed in BRF1+/+ and BRF1-/- MEFs Figure 5.5: KC protein is expression is comparable between BRF1+/+ and BRF1-/- MEFs in response to IL-1α Figure 5.6: IL-6 protein is over-expressed in BRF1-/- MEFs by comparison with BRF1+/+ MEFs in response to IL-1α Figure 5.7: Cox-2 mRNA is over-expressed in BRF1-/- MEFs by comparison with BRF1+/+ MEFs in response to IL-1α Figure 5.8: KC mRNA is over-expressed in BRF1-/- MEFs by comparison with BRF1+/+ MEFs in response to IL-1α Figure 5.9: IL-6 mRNA is over-expressed in BRF1-/- MEFs by comparison with BRF1+/+ MEFs in response to IL-1α Figure 5.10: Cox-2 mRNA decays at the same rate in BRF+/+ and BRF1-/- MEFs Figure 5.11: Cox-2 mRNA decays at the same rate in BRF1+/+ MEFs regardless of p38 activity Figure 5.12: Cox-2 mRNA decays at the same rate in BRF1-/- MEFs regardless of p38 activity
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Figure 5.13: IL-6 mRNA decays at the same rate in BRF1+/+ and BRF-/- MEFs Figure 5.14: IL-6 mRNA decays at the same rate in BRF1+/+ MEFs regardless of p38 activity Figure 5.15: IL-6 mRNA decays at the same rate in BRF1-/- cells regardless of p38 activity Figure 5.16: Cox-2 mRNA decays at the same rate in BRF1-/- and BRF1+/+ MEFs, even when an alternative transcriptional inhibitor is used Figure 5.17: Cox-2 mRNA decays at the same rate in BRF1+/+ and BRF1-/- MEFs regardless of P38 activity, even when an alternative transcriptional inhibitor is used Figure 5.18: Optimisation of primer sets Figure 5.19: verification of the specificity the SYBR green technique for measuring IL-6 primary transcript Figure 5.20: Cox-2 primary transcript mRNA is over-expressed in BRF1-/- cells in comparison to BRF1+/+ cells in response to IL-1α Figure 5.21: KC primary transcript mRNA is expressed in similar amounts between BRF1+/+ and BRF1-/- MEFs in response to IL-1α Figure 5.22: IL-6 primary transcript is over-expressed in BRF1-/- MEFs in comparison to BRF1+/+ MEFs in response to IL-1α Figure 5.23: Normalisation of data using GAPDH primary transcript Figure 5.24: Effect of trichostatin A (TSA) on Cox-2 primary transcript mRNA expression in BRF1+/+ and BRF1-/- MEFs Figure 5.25: Effect of TSA on KC primary transcript mRNA expression in BRF1+/+ and BRF1-/- MEFs Figure 5.26: Effect of TSA on IL-6 primary transcript mRNA expression in BRF1+/+ and BRF1-/- MEFs Figure 5.27: Sub cellular fractionation of MEFs Figure 5.28: Differences in transcription factor expression between BRF1+/+ and BRF1-/- MEFs Figure 5.29: Percentage expression of each transcription factor in comparison to its predicted abundance
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Tables: Table 1: TLRs and their ligands Table 5.1: Alternative normailisation of Cox-2, KC and IL-6 primary transcripts
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Abbreviations
Ago Argonaute AMD Are mediated decay AP1 Activating protein APRIL Acid protein rich in leucine ATF Activating transcription factor ATCC American type culture collection ARE Adenosine uridine rich element ASK Apoptosis-regulating signal kinase ATP Adenosine triphosphate AUBP Adenosine uridine rich element binding protein AUF ARE/poly(U) binding/degradation factor BRF1/2 Butyrate response factor 1/2 BSA Bovine serum albumin CBP CREB binding protein CBS Cockayne syndrome B cAMP Cyclic adenosine mono phosphate cIAP2 Human inhibitor of apoptosis protein-2 CPEB Cytoplasmic polyadenylation element-binding protein CCR Carbon catabolite repression CFP Cyan fluorescent protein CHIP Chromatin immunoprecipitation CMV Cytomegalovirus Cox-1/2 Cyclooxygenase-1/2 CRE cAMP response element CREB CRE binding CEBP CCAAT/enhancer binding protein CSAID Cytokine synthesis anti inflammatory drug CSF Colony stimulating factor CTD Carboxy repeat terminal domain
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C-terminal Carboxy-terminal Dcr Dicer DLK Dual leucine zipper kinase DMEM Dulbecco’s Modified Eagle’s medium DMSO Dimethyl sulfoxide dNTPs deoxyribonucleotides 5’triphosphates DNA Deoxyribose nucleic acid DRB 5,6-dichloro-1-β-D-ribofuranosylbenzimidazole DSIF DRB sensitivity inducing factor dsRNA Double stranded RNA DTT Dithiothreitol DUSP Dual specificity phosphatase E64 Trans-epoxysuccinyl-L-leucylamido(4-guanido)-butane ECL Enhanced chemiluminescence Edc Enhancer of decapping EDTA Ethylenediamine tetraacetic acid eIF Eukaryotic transcription factor ELAV Embryonic lethal abnormal vision ELK ETS-like transcription factor EMSA Electromobility shift assay EGF Epidermal growth factor ERK Extra cellular regulated kinase Ets E26 transformation-specific FAST fas- activated serrine/threonine phosphoprotein FCS Foetal calf serum FBP FUSE binding protein FBS Foetal bovine serum FGF Fibroblast growth factor FOXO Forkhead box O FRET Florescence resonance energy transfer GAPDH Glyceraldehyde-3-phosphate dehydrogenase
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G-CSF Granulocyte-colony stimulating factor GDP Guanosine diphosphate GM-CSF Granulocyte macrophage-colony stimulating factor GFP Green fluorescent protein GRO Growth-regulated oncogenes GTF General transcription factors GTP Guanosine triphosphate gp Glycoprotein HAT Histone aceyltransferase HDAC Histone deacetyltranferase HMB HuR binding motif hnRNP Heteronuclear ribonuclear protein HNSCC Human head and neck squamous cell carcinoma cell lines HRP Horse radish peroxidase HSP Heat shock protein HSF Heat-shock transcription factor HuR Human-antigen R IκB Inhibitor of kappa B ICAM Intracelluar adhesion molecule IDO Indoleamine 2,3 dioxygenase Ier Immediate early response Ig Immunoglobulin IGF Insulin growth like factor INF Interferon iNOS Inducible nitric oxide synthase IL Interleukin IL-1R IL-1 receptor IL-1Ra IL-1 receptor antagonist protein IL-1RAcP IL-1R accessory protein IL-8R IL-8 receptor IKK IκB kinase
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IRAK IL-1 receptor associated kinase IRAP IL-1 receptor antagonist protein IRF Interferon regulatory factors ISG Interferon stimulated gene JNK c-jun N-terminal kinase IOD Indoleamine-pyrrole 2,3 dioxygenase KC Keratinocyte chemokine KSRP KH-type splicing regulatory protein LPS Lipopolysaccharide Lsm Sm-like LT Lymphotoxin MADS MCM1, agamous, deficiens, SRF MAL MyD88-adaptor like protein MAPK Mitogen activated protein kinase MAPKK MAPK kinase MAPKKK MAPK kinase kinase MBD Membrane binding domain MEF Mouse embryonic fibroblast MEF2A Monocyte enhance factor 2A MEK MAPK/ERK kinase MEKK MAPK kinase kinase M-CSF Macrophage- colony stimulating factor MHC Major histocompatibility complex MIP Macrophage inflammatory protein miRNA MicroRNA MK MAPK activated protein kinase MKK MAPK/ERK kinase MKK MAPK activated protein kinase kinase MKP MAPK dual specificity phosphatase MLK Mixed-lineage kinase MMP Matrix metalloproteinase
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MNK MAPK-interacting kinase MRE miRNA recognition elements mRNA Messenger RNA mRNP Ribonucleoprotein particle MSK Mitogen- and stress- activated kinase MUK MAPK-upstream protein kinase MYD88 Myeloid differentiation 88 NELF Negative transcription elongation factor NES Nuclear export sequence NFβa Nuclear factor βa NF-κB Nuclear factor kappa B NHS Nucleocytoplasmic shuttling sequence NK cells Natural killer cells NLS Nuclear localization signal NMD Nonsense mediated decay NOT Negative regulator of transcription NSAIDs Non steroidal anti-inflammatories NSS Nucleocytoplasmic shuttling sequence NP-40 Nonidet P40 N-terminal Amino-terminal NPC Nuclear pore complex PABP Poly(A) binding protein PAGE Polyacrylamide gel electrophoresis PAI Pasminogen activator inhibitor PAN Poly(A) nuclease PARN Poly(A) ribonuclease PB Processing body PBS Phosphate buffered saline PCR Polymerase chain reaction PDGF Platelet derived growth factor PDK1 Phosphoinositide dependent kinase 1
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PGE2 Prostaglandin E2 PH Plekstrin homology domain PI3K Phosphatidylinositol-3-kinase PIWI P-element induced wimpy testis in Drosophila PKB Protein kinase B PKC Protein kinase C PMA Phorbol 12-myristoyl 13-acetate PMSF Phenylmethylsulfonyl fluoride Pol ІІ RNA polymerase ІІ POP Processing of precursor PP2A Protein phosphatase 2A priRNA Primary RNA PTC Premature termination codons PVDF Polyvinylidene difluoride membrane qPCR Quantitative PCR RA Rheumatoid arthritis RCE Retinoblastoma control element RNA Ribose nucleic acid RNAi RNA interference RNP Ribonucleoprotein RIP RNA immunopreciptitation RIP1 Receptor-interacting protein kinase 1 RISC RNA induced silencing complex RRM RNA recognition motif RSKs Ribosomal S6 kinases RT Reverse transcription RTK Receptor tyrosine kinases RT-qPCR RT-quantitative PCR SARM Sterile α- and armadillo-motif containing protein SDS Sodium dodecylsulphate SG Stress granule
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siRNA Short interfering RNA SIRT Silent information regulator STAT Signal transducer activator of transcription SOD Superoxide dismutase SoS Son of sevenless SRE Serum response element TAB TGFβ- binding protein TAK TGFβ activated kinase TAO One amino acid TBP TATA binding protein TBS Tris buffered saline T-cells Thymus-cells TGF Transforming growth factor TFR Transferrin receptor TIA T-cell intracellular antigen TIAR TIA-1 related TIR Toll-IL-1 receptor TLR Toll-like receptor TMB Tetramethylbenzidine TNF Tumour necrosis factor TNFR TNF receptor Tpl-2 Tumor progression locus 2 gene TRAF TNFR associated factor TRAM TRIF-related adapter molecule TRE PMA responsive element TRIF TIR-domain-containing adapter protein inducing INF-β TSA Trichostatin A TTP Tristetraprolin TZF Tandem zinc finger UTR 3’ untranslated region UV Ultra violet
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VCAM Vascular adhesion molecule VEGF Vascular endothelial growth factor YFP Yellow fluorescent protein Zfp Zinc finger protein
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Chapter 1:
Introduction
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1) INTRODUCTION
1.1) The immune system
1.1.1) Introduction The immune system is a highly specific recognition system that allows the body to direct its destructive powers towards pathogens. Due to the diversity of pathogens the immune system is highly complex. Circulating macrophages and neutrophils respond to infection by phagocytosing pathogens, at the same time an inflammatory response is initiated. This forms a non specific first line of defence against invading organisms which is termed innate immunity.
If the innate response is unsuccessful at eliminating invading pathogens then the specific immune response comes into play. B-Lymphocytes produce immunoglobulins (IgGs) which have the ability to recognise specific antigens on the surface of pathogens and direct them for destruction. The process by which they are able to do this is extremely complicated and involves exposure to the pathogen before an antibody is generated to destroy it, hence the term acquired immunity. Those lacking this ability to acquire immunity die very prematurely.
1.1.2) Innate Immunity and the inflammatory response- the initial response to infection The function of the inflammatory response is to recruit leukocytes from the bloodstream to the infected tissue. There are four main events which occur during inflammation to facilitate this: (1) Vasodilation, widening of the blood vessels to increase blood flow to the site of infection, therefore supplying the area with cells and other factors required for defence. (2) Activation of endothelial cells which line the blood vessels to allow the adhesion of white blood cells. (3) Increased vascular permeability which allows the movement of cells and factors required for the immune response across the endothelial cell monolayer. (4) Release of cytokines and chemokines which function to attract other cells to the area of infection amongst other systemic effects.
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The process of diapedesis (the migration of leukocytes across the endothelial monolayer) begins with their adherence to the endothelial cell wall via adhesion molecules such as intracellular adhesion molecule-1 (ICAM-1) and vascular adhesion molecule-1 (VCAM-1). Engagement of these molecules brings about a series of signalling cascades within endothelial cells altering their tight and adherens junctional properties resulting in leukocyte migration into surrounding tissue (Turowski et al., 2005).
1.1.3) Leukocytes Several different types of leukocytes contribute to the immune response which all are derived from hematopoietic stem cells. Neutrophils are often the first type of leukocyte to invade a tissue. They phagacytose the invading pathogen, following this they are unable to renew and they die. Their death in large numbers is often seen as pus. Neutrophils also release inflammatory mediators which in turn attract macrophages. Macrophages can phagocytose larger pathogens than neutrophils and can themselves release inflammatory mediators which attract mast cells. Mast cells can also release cytokines and chemokines, further amplifying the response.
Macrophages, along with neutrophils are the first line of defence. They can be activated by a variety of stimuli such as bacterial pathogens, cytokines, interferon (INF)γ, tumour necrosis factor (TNF)α and ultra violet (UV) light. Following this they express a multitude of antimicrobial and cytotoxic substances in addition to the cytokines already mentioned as well as adhesion molecules and prostaglandins. As well as this they also have a function in the adaptive immune response. They can present antigens to T-cells therefore functioning as antigen presenting cells (APCs).
Mast cells are granulocytes. When they release their granule contents which includes histamine, heparin and proteolytic enzymes, eosinophils, neutrophils and basophils are attracted. Eosinophils and basophils are involved in the allergic responses.
Lymphocytes are sub divided in to three main groups: B-cells which produce antibodies; natural killer (NK) cells; thymus (T) -cells of which there are two main groups: CD4 T cells
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and CD8 T cells and. In addition to these there are several other sub-sets of T-cells they are mainly involved in the adaptive immune response. However NK cells bridge the gap between the adaptive and innate immune responses. NK cells recognise glycolipid antigen presented via a molecule called CD1d. Once activated these cells can perform functions ascribed to both CD4 and CD8 cells (i.e., cytokine production and release of cytolytic/cell killing molecules). Also interleukin (IL)-12 activates NK cells, stimulating them to produce INFγ and enabling them to kill cancerous and virally infected cells and attract macrophages. They are therefore an important part of the innate immune response.
1.1.4) Fibroblasts Fibroblasts have a role in embryogenesis, physiological and pathological tissue remodeling. Fibroblasts are morphologically heterogeneous depending on their location and function. They were originally described as having a function in providing mechanical support to tissues in its role in the extracellular matrix (Brewer, 1967). Their ability to secrete cytokines, chemokines and prostaglandins has led to their identification as having a role in inflammation (Buckley et al., 2001). Several links have been demonstrated between various fibroblast types and inflammatory mediators. For example when stimulated with INFγ and CD40, human lung fibroblasts can increase prostaglandin E2 synthesis through the up- regulation of cyclooxgenase (Cox)-2 (Zhang et al., 1998). Rel B deficiency in murine kidney fibroblasts causes them to over-express macrophage inflammatory protein (MIP)- 1α, MIP-1β, macrophage chemotractant protein (MCP)-1 and chemokine (CXC motif) ligand 1 (CXCL1) following lipopolysaccharide (LPS) stimulation (Xia et al., 1997). As well this fibroblasts also display mitogen activated protein kinase (MAPK) signalling. c-jun N-terminal kinase (JNK)1 deficient fibroblasts are under-proliferative whereas JNK2 deficient fibroblasts are over-proliferative. MAPK p38 and extracellular regulated kinase (ERK) have been linked to IL-6 and IL-8 production in human lung fibroblasts (Hayashi et al., 2000). If the expression of these inflammatory mediators becomes disregulated then chronic inflammation can occur in the tissues composed of these cells. Chronic inflammation is a characteristic of diseases such as rheumatoid arthritis (RA) and Crohn’s disease.
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1.1.5) Cytokines Cytokines are small proteins or glyco-proteins (normally less than 20 KD) which act as chemical communicators. They act through cell surface receptors present on either the cell from which they are released or on other cells which are normally within close proximity. The main groups of cytokines are the: interleukins (IL-1- IL-35), interferons (INFαβγ), tumour necrosis factors (TNFα and TNFβ), colony stimulating factors (CSFs): granulocyte (G)-CSF, macrophage (M)-CSF and granulocyte/macrophage (GM)-CSF, chemokines and growth factors: transforming growth factor (TGF) and insulin growth like factor (IGF) and many more. Cytokine receptors have also been classified into groups according to their structural features which are highly conserved between them. The main families are hematopoietin receptors, interferon receptors, TNF receptors, IL-1/toll-like receptors, tyrosine kinase receptors and chemokine receptors. Following engagement of the receptors signalling cascades are activated and gene transcription follows.
Cytokines have a central role in the immune response but are also important in other processes such as embryogenesis. They display some key features in common: pleitropy (i.e. they have more than one function), redundancy (they often display overlapping functions), potency (required in small amounts to exert their effect) and they normally act as part of a cascade of events. A single cell will be exposed to several cytokines at any one time and often more than one cell type is able to produce a particular cytokine. It is the combination of cytokines which will determine the behaviour of the cell to which they are exposed.
Macrophages produce a range of cytokines such as IL-1, IL-6 and TNFα. TNFα acts on endothelial cells to increase vascular permeability and can also along with IL-1 increase the expression of adhesion molecules such as E-selectin and ICAM-1. IL-1 and TNF can also stimulate macrophages and endothelial cells to produce chemotractants such as IL-8, which further attracts neutrophils. Cytokines also have systemic effects. For example IL-1, IL-6 and TNFα affect the brain causing fever and the liver causing the acute phase response. Sustained expression of these inflammatory mediators in the absence of a pathogen leads to
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chronic inflammation, a characteristic of diseases such as RA, Crohn’s disease, asthma and atherosclerosis.
1.1.5.1) Interleukin-1 (IL-1) IL-1 was one of the first cytokines to be described, reviewed by Stylianou and Saklatvala 1989, Dinarello 1994 and 1996 (Dinarello, 1994; Dinarello, 1996; Stylianou and Saklatvala, 1998). Its ability to cause fever, stimulate the acute phase response, initiate lymphocyte responses, induce degenerative changes in the joints and increase the number of bone marrow cells meant that many independent investigators studying these different processes were unknowingly working on IL-1 simultaneously but referring to it by different names. Originally three members of the IL-1 family were cloned: IL-1α, IL-1β and IL-1 receptor antagonist protein (IRAP/IL-1Ra). All three share 20-25% amino acid sequence homology and bind the same receptor (IL-1RІ/a). Their structure is barrel shaped and composed of 12-14 β-strands. IL-1α and IL-1β are synthesised as 31 KD cytosolic precursors which are later cleaved to 17 KD and released from the cell. Two isoforms of IRAP exist; an intracellular and an extracellular form.
More recently seven novel members of the IL-1 cytokine family have been identified on the basis of sequence homology, three dimensional structure, gene location and receptor binding. They are known by several different names but are known by the IL-1 family standard nomenclature as IL-1F5, IL-1F6, IL-1F7, IL-1F8, IL-F9, IL-1F10 and IL-1F11 (better known as IL-33) (reviewed by Barksby et al. 2007 (Barksby et al., 2007)).
Regulation of the expression of the three original IL-1 isoforms is slightly varied. Their promoter regions differ, IL-1α does not have a typical TATA box but the others do (Furutani et al., 1986; Shirakawa et al., 1993; Smith et al., 1992), all three have nuclear factor kappa B (NF-κB) sites, IL-1α and IL-1β have CCAAT/enhancer binding protein (CEBP)/β sites. IL-1β and IL-1Ra have activating protein (AP)-1 and cAMP response element binding protein (CEBP) binding sites as well as another site for a novel nuclear factor; NFβa. IL-1α and IL-1β are produced mainly by macrophages and monocytes but also by endothelial cells, fibroblasts and epidermal cells. IRAP is made mainly by monocytes. IL-1α and IL-1β are produced in response to LPS and cytokines. At present
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relatively little is known about the expression and regulation of the novel IL-1 family members. IL-1F6, 8 and 9 are known to be up-regulated in monocytes following LPS stimulation probably a by similar pathway that causes the IL-1β response (Towne et al., 2004).
IL-1α and IL-1β generally exert the same effects, some are mentioned above. They induce leukocyte accumulation by inducing adhesion receptors and chemokines. They can stimulate the production of other cytokines, prostanoids and inducible nitric oxide synthase (iNOS). They have also been shown to regulate extracellular matrices and cause cartilage and bone resorption. IL-1β and IL-1α/β knockout mice were unable to develop a fever but were otherwise healthy, however, IL-1Ra knockout mice were growth retarded. IL-1α/β knockout mice also revealed that IL-1 is needed for its own induction and that of Cox-2 (Horai et al., 1998).
There are three members of the IL-1R family; IL-1RІ/a which is expressed ubiquitously but in low abundance and is 80 KD in size (Stylianou et al., 1992); IL-1RІІ/b which is also found on many cells but is primarily found on neutrophils, monocytes and B-lymphocytes and is 67 KD; and the T1/ST2/fit-1 receptor. T1/ST2/fit-1 shares 26% homology with IL- 1RІ and IL-1RІІ but does not bind IL-1. The IL-1RІ/a has a 213 amino acid cytoplasmic domain, which serves as a tyrosine kinase target and transduces the IL-1 signal whereas IL- 1RІІ/b has a 29 amino acid cytoplasmic domain, and therefore cannot signal. It has been suggested that IL-1RІІ serves as a decoy, binding IL-1 to reduce its biological effects (Mantovani et al., 1996).
Engagement of the IL-1 receptor results in the activation of intracellular cascades culminating in the transcription of various pro-inflammatory genes. These signalling cascades will be discussed in section 1.2.3.
1.1.5.2) Interleukin -6 (IL-6) and its receptor IL-6 was first cloned in 1980 as a product from fibroblasts stimulated with the double stranded RNA poly(I) poly(C) (poly I:C) which mimics viral activity (Weissenbach et al., 1980). Since then it has been found to be involved in a plethora of biological activities. One
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of its main activities and often most associated with IL-6 is its role in inflammation and the immune response. IL-6 is partially responsible for the acute phase response. It acts on the liver to stimulate production of acute phase proteins which include C-reactive protein and complement (Sehgal et al., 1989). As well as its role in the innate immune response, IL-6 also has a function in the adaptive immune response. It can induce the differentiation of activated B cells aiding them to produce IgGs (Ambrosino et al., 1990). IL-6 also aids T- cell differentiation (Uyttenhove et al., 1988) and can activate NK cells (Luger et al., 1989).
As well as its immunological roles, IL-6 has a number of other functions. It has been shown to stimulate osteoclastogenesis, a process in bone metabolism (Kurihara et al., 1990; Tamura et al., 1993). It has a role in reproduction in menses (Tabibzadeh et al., 1995; Tabibzadeh et al., 1989) and spermatogenesis (Hakovirta et al., 1995) and also in skin proliferation, neural cell differentiation and proliferation (Hama et al., 1989; Satoh et al., 1988). Due to this diverse range of activities, disregulation of IL-6 results in a number of disorders which include; inflammation, osteoporosis, neoplasia, Alzheimer’s and autoimmune (Keller et al., 1996).
Human IL-6 has a molecular weight of 21-28 KD depending on post-translational modifications such as glycosylation and phosphorylation (May et al., 1988a; May et al., 1988b). The human IL-6 gene shares 65% homology with the murine version which is reduced to 42% at the protein level (Van Snick, 1990). The IL-6 gene consists of five exons and four introns and is located on chromosome 7p21 (Sehgal et al., 1986). Its activity is controlled by a promoter region which is highly conserved between mouse and human (they share 80% homology) (Tanabe et al., 1988). The IL-6 promoter has several regulatory elements which can either have stimulating or repressive effects. Exactly which of these is responsible for IL-6 regulation is cell and stimulus specific.
IL-6 signals through the IL-6 receptor (IL-6R) was fist cloned in 1988 (Yamasaki et al., 1988). IL-6R has a mass of 80 KD and its gene is located on chromosome 1q21 (Kluck et al., 1993). Sequence analysis of IL-6R revealed that it has an extracellular, a transmembrane and an intracellular region. The intracellular region does not contain any
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kinase domains (Yamasaki et al., 1988). For IL-6 signal transduction to occur a hexameric complex must associate. It consists of two molecules of IL-6 which bind two molecules of IL-6R which together form a low affinity receptor complex. This complex then associates with two molecules of gp130 (a non ligand binding glycoprotein), homodimerisation of gp130 is required for IL-6 signal transduction (Ward et al., 1994). There is a high degree of homology between the IL-6R and other cytokine receptors. It contains two tandem fibronectin type ІІІ motifs present in a 200 amino acid region which is common to many other cytokine and growth factor receptors (Bazan, 1989). IL-6R is expressed in a variety of cells including monocytes, B-cells, T-cells and hepatocytes and its expression is induced by several factors including dexamethasone and IL-1 (Bauer et al., 1989). Conflicting reports exist about the induction of IL-6R and the cell type in which it can be expressed, which is again probably down to cell-specific and stimulus-specific differences.
IL-6 null mice develop normally but have impaired immune and acute phase response (Kopf et al., 1994). However the disregulation of IL-6 is associated with autoimmune diseases such as RA, Crohn’s disease, Castlemen’s disease and juvenile idiopathic arthritis (Nishimoto et al., 2000). IL-6 is over-expressed in the synovial fluid of patients with RA (Madhok et al., 1993; Sack et al., 1993) and its blockade has been developed as a potential RA therapy. A humanized monoclonal antibody against human IL-6R, tocilizumab inhibits IL-6 binding to IL-6R and specifically interferes with IL-6 actions. It has been shown to be well tolerated and therefore a promising treatment for rheumatic disease (Nakahara and Nishimoto, 2006). Tocilizumab (trade name Actemra) has been licenced to treat Castleman’s disease, RA, juvenile idiopathic arthritis and systemic-onset juvenile idiopathic in Japan but is still awaiting approval in the USA and Europe.
1.1.5.3) Cyclooxygenase-1/2 (Cox-1/2) Cox-1 and Cox-2 are the enzymes that catalyse the rate limiting step in the conversion of arachidonic acid into prostaglandins. They share 60% homology in their nucleic acid and amino acid sequences, and are also of similar sizes (70-74 KD). Cox-1 is constitutively expressed in a range of tissues (Feng et al., 1993; Inoue et al., 1994; Kosaka et al., 1994; Roshak et al., 1996). In contrast to this, Cox-2 is generally undetectable in unstimulated
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conditions but is induced as part of an inflammatory response (Chen et al., 1997; Inoue et al., 1995; Roshak et al., 1996; Xie and Herschman, 1996; Yamamoto et al., 1995). Prostaglandins are members of the eicosanoid family of oxygenated C20 fatty acids and are produced by nearly every cell of the body. They have a number of roles in processes such as vasodilatation, vascular permeability and diapedesis during the inflammatory response.
Cox-1 and -2 exist and function as homodimers. Each monomer consists of three structural domains: an epidermal growth factor domain (EGF) of around 50 amino acids which is at the amino (N)-terminus, a membrane binding domain (MBD), also of about 50 amino acids in size and a carboxy (C)-terminal catalytic domain of 460 amino acids (Picot et al., 1997). Both Cox-1 and -2 are present on the luminal surface of the endoplasmic reticulum and on the inner and outer membranes of the nuclear envelope (Morita et al., 1995; Spencer et al., 1999). Cox-2 is glycosylated at two-four sites which is commonly seen on sodium dodecylsulphate (SDS) polyacrylamide gels as a doublet (Otto et al., 1993).
Cox-2 can be induced by stimuli such as IL-1, LPS, phorbol esters, TNFα and platelet derived growth factor (PDGF) (Chen et al., 1997; Inoue et al., 1995; Roshak et al., 1996; Xie and Herschman, 1996; Yamamoto et al., 1995) and can be suppressed by glucocorticoids and anti-inflammatory cytokines (DeWitt, 1999). Cox-2 has a definitive role in inflammation, pain, fever and its regulation by c-fos and c-myc suggest a role in mitogenesis and wound repair. Cox-2 is also involved in a variety of other biological processes: reproduction (Lim et al., 1997), immunity (Rocca et al., 1999), renal physiology (Cheng et al., 1999), neurotransmission (Breder et al., 1995), bone resorption (Pilbeam et al., 1997) and pancreatic secretion (Robertson, 1998). As with IL-6 the physiological activity that results is dependent on the stimulus and the cell type affected. Transcription of the Cox-2 gene has been observed as a result of a range of signalling pathways including the MAPK pathways (Su and Karin, 1996) and NF-κB pathways. These will be discussed later on in this chapter. The Cox-2 promoter possess various transcriptional regulatory elements including Cyclic adenosine mono-phosphate (cAMP) response element (CRE), CEBP/β, and NFκB, meaning that its expression can potentially induced in a variety of ways. Cox-2 has also been shown to be post-transcriptionally regulated by the MAPK p38
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pathway in HeLa cells (Ridley et al., 1998) and in monocytes (Dean et al., 1999) which will also be discussed in greater detail later in the chapter.
Cox-2 null mice did not display any clear role for Cox-2 in inflammatory disease (Dinchuk et al., 1995). However Cox-2 has been detected in the synovial fluid of patients with RA (Kang et al., 1996). Cox-2 has also been implicated in colorectal cancer (Sano et al., 1995), ovarian cancer (Raspollini et al., 2006) and other cancers. Pharmacological inhibition of Cox by non steroidal anti-inflammatories (NSAIDs) such as aspirin and ibuprofen can prevent pain and inflammation and have been used in the treatment of RA. Studies have shown that Cox-2 specific inhibitors may be chemoprotective against colon cancer in rats (Kawamori et al., 1998).
1.1.5.4) Chemokine (CXC motif) family: Interleukin-8 (IL-8), growth- regulated oncogene (GRO)α and keratinocyte chemokine (KC) Humans express several chemokines, which have been divided into four main families on the basis of their structure and their chemotactic activity on different leukocyte populations. The CXC family has a sub group which contains a glycine-leucine-arginine (ELR) motif immediately preceding the CXC residues. In humans there are seven identified members of this family but only four in mice, one of these is keratinocyte chemokine (KC) which is the murine equivalent of growth-regulated oncogene (GRO)α.
IL-8 was identified in 1987 as neutrophil attracting cytokine (Baggiolini et al., 1989). Since then it has been found to have chemotractant effects on basophils (White et al., 1989), T- lymphocytes (Larsen et al., 1989) and lymphokine activated killer cells (Sebok et al., 1993). In addition to this it has been shown to induce the expression of adhesion molecules on neutrophils (Detmers et al., 1990). This gene and ten other members of the CXC chemokine gene family form a chemokine gene cluster on a region mapped to chromosome 4q. It is clear that there is a great deal of redundancy between the proteins, whether this is because IL-8 has such a vital role and backups are required or whether it is due to differential expression in different tissue types or whether they do in fact have distinct but as yet unknown functions is unclear. IL-8 is generated as a 99 amino acid precursor which is secreted after cleavage of a 20 amino acid signal peptide. There are several variants which
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result from N-terminal extracellular processing. IL-8 contains four cysteines which form two disulphide bonds, which if reduced cause its inactivation.
IL-8 can be produced by a variety of cell types including endothelial cells, macrophages, fibroblasts, keratinocytes, synovial cells, chondrocytes, epithelial cells, tumour cells and even by neutrophils themselves (Baggiolini et al., 1989). IL-1 and TNFα have been found to stimulate IL-8 from all of the cell types studied so far, other stimuli include phorbol esters and IL-3. IL-8 receptors of which there are two types; A (Holmes et al., 1991) and B (Murphy and Tiffany, 1991), belong to a G-protein coupled receptor family with seven transmembrane domains. IL-8RA and IL-8RB have a high degree of homology except in the NH2-terminal first extracellular domain (Holmes et al., 1991; Murphy and Tiffany, 1991). Both types have been shown to bind IL-8 with high affinity but type B can also bind GROα with high affinity (Lee et al., 1992). IL-8RA and IL-8RB are expressed on neutrophils, monocytes and NK cells (Morohashi et al., 1995). Again IL-8 disregulation has been linked with inflammatory syndromes and also schizophrenia (Brown et al., 2004).
KC was first identified from a cDNA library of a PDGF induced fibroblast cell line (Bozic et al., 1995). Like IL-8 KC functions to recruit neutrophils, aid their migration and their activation at the site of infection and injury.
In addition to the inflammatory mediators mentioned above, there are many others which are involved in the inflammatory response and immunity. A common theme seems to be that their disregulation is associated to inflammatory diseases. Often inflammatory diseases are the result of the collective disregulation of inflammatory mediators causing chronic inflammation, an effect of diseases such as RA, Crohn’s disease and inflammatory bowl syndrome and it has been heavily implicated in certain cancers. Cytokines, chemokines and inflammatory mediators such as Cox-2 therefore provide targets for therapeutic development. This may involve targeting the signalling pathways which are responsible for their activation. These are discussed in the next section.
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1.2) Inflammatory signalling pathways
1.2.1) Introduction
Microbial invasion, physical damage and damage by UV light also drive the inflammatory response. Receptors present on the surface of affected cells are responsible for initiating the internal signal cascade which follows, resulting in the expression of inflammatory genes. Among these receptors are the IL-1 receptor (IL-1R), the TNF receptor (TNF-R) and the toll-like receptors which recognise pathogen-associated molecules such as LPS, a component of gram negative bacterial cell walls.
1.2.2) Interleukin-1 receptor (IL-1R) and the toll-like receptor (TLR) superfamily
IL-1R and toll like receptors (TLRs) share a common cytoplasmic domain known as toll/IL-1 receptor (TIR) domain. It was named as such because of the similarity in the sequences of type 1 IL-1R and the Drosophila melanogaster protein Toll (Gay and Keith, 1991). Toll was identified as having a role in embryogenesis and later was shown to be critical in the immune response to fungal infection (Lemaitre et al., 1996). Following this a human homologue of Toll was identified, now known as toll-like receptor 4 (TLR4) (Medzhitov et al., 1997). The TIR domain functions by recruiting other proteins also containing a TIR domain. It is approximately 200 amino acids in length and has three regions which are highly conserved amongst those proteins in which it exists.
There are three obvious groups that constitute the IL-1/TLR superfamily. Their differences lie in their structure which determines their ligands. The IL-1R family, reviewed by Suramaniam et al. 2004 (Subramaniam et al., 2004) have three IgG-like extracellular domains whereas the TLRs are characterised by leucine rich repeats in their extracellular domains. Engagement of these receptors ultimately results in the transcription of pro- inflammatory genes which occurs via various signalling pathways including: the NF-κB pathway and the MAPK pathways. The third group are adaptor proteins which are cytosolic and are involved in the signalling cascade.
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1.2.3) IL-1 Signalling The IL-1R sub-family includes IL-1Ra and IL-1Rb. The major pathway activated by IL-1 culminates in the activation of NF-κB and in the activation of the MAPK pathways. IL-1R accessory protein (IL-1RAcP) and IL-1R form a heterodimeric complex upon IL-1 binding and myeloid differentiation factor (MYD) 88 is recruited followed by recruitment of IL-1R associated kinase-1 (IRAK1) and IRAK4. There is a third adaptor protein, Tollip which is thought to be associated with IRAK1 in unstimulated cells. Tollip may block IRAK1 signalling. Upon IL-1 stimulation Tollip/IRAK1 is translocated to the active IL-1R complex and brings the death domains of IRAK1 and MYD88 into contact. Tollip then dissociates and IRAK1 dimerises. IRAK1 is auto-phosphorylated and or cross- phosphorylated by IRAK4. IRAK1 then dissociates from the IL-1R complex and interacts with TNF receptor associated factor 6 (TRAF6) (reviewed by Inoue et al. (Inoue et al., 2000)), which auto-polyubiquitinates and then recruits, TGFβ activated kinase-1 (TAK1), TGFβ- binding protein 1 (TAB1) and TAB2 (Shibuya et al., 1996; Takaesu et al., 2000). TAK1 (which is a MAPK kinase kinase- MAPKKK) phosphorylates the inhibitory factor κB (IκB) kinase (IKK) which results in the activation of the NF-κB pathway. TAK1 can also phosphorylate MAPK kinases (MKK) which then activate the MAPK pathways (Ninomiya-Tsuji et al., 1999; Shirakabe et al., 1997).
1.2.4) TLR Signalling At present thirteen mammalian TLRs have been identified (ten in humans and twelve in mice) (Beutler, 2004). As mentioned above they have a leucine rich extracellular domain which is at the N-terminus also they have a transmembrane region and a C-terminal cytoplasmic domain. It is the C-terminal region which contains the TIR. TLRs are responsive to a range of bacterial and viral ligands. Some TLRs can detect multiple ligands of bacterial and viral origin and some are more specific. For example TLR2 can bind the bacterial ligands; triacylated lipoprotein, lipoteictoic acid, peptidoglycan, zymosan and diacylated lipoprotein and the viral ligand hemaglutinin. TLR1 can only bind bacterial ligands and TLR3, 7 and 8 are only engaged by viral components. TLR1, 2, 4, 5 and 6 are expressed on the cell surface and TLR3, 7, 8 and 9 are located intracellularly on endosomal membranes. As well as having bacterial and viral ligands, TLRs also have endogenous
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ligands. The various ligands, endogenous and exogenous are outlined in table 1.1 and are reviewed by Watters et al. 2007 (Watters et al., 2007).
Upon ligation, TLRs form homo- or heterodimers. For example TLR4 homodimerises whereas TLR2 forms heterodimers with TLR1 or TLR6. Adaptor proteins are recruited to the cytoplasmic domain via their TIR domains. There are five TIR containing adapter proteins, reviewed by Watters et al. 2007 (Watters et al., 2007): MYD88, MYD88 adapter like (MAL), TIR- domain-containing adapter protein inducing INF-β (TRIF), TRIF-related adapter molecule (TRAM), and sterile α- and armadillo-motif containing protein (SARM). There are three pathways involved in TLR signalling: the MYD88 dependent pathway, the TRIF dependent/MYD88 independent pathway and the alternative MYD88 pathway (figure 1.1 gives an overview of these three pathways).
All TLRs use MYD88 except for TLR3 which uses TRIF TLR4 uses both. In the case of TLR4 which dimersises upon ligation, MAL binds via the TIR domain which in turn recruits MYD88. This pathway is very similar to the IL-1 signalling pathway detailed above which results in the activation of the NF-κB or MAPK pathways which go on to initiate transcription of pro-inflammatory cytokines. MYD88 can also activate the interferon regulatory factors (IRF) family of transcription factors via TLR signalling.
The TRIF dependent pathway/MYD88 independent pathway was discovered when MYD88 deficient cells were found to still be able to mediate NF-κB and MAPK signalling in response to LPS and Poly I:C (Kawai et al., 1999). TRIF can associate with TLR4 via TRAM and with TLR3 directly. TRIF signalling through TLR3 results in IRF3 activation (Yamamoto et al., 2002b). TRIF activated by TLR4 activates receptor-interacting protein kinase (RIP)1, which is something TLR3 activated TRIF can also accomplish (Yamamoto et al., 2003a), TRAF6 is activated and the downstream consequences are as previously described for the MYD88 dependent pathway.
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The final TLR signalling pathway only occurs in plasmacytoid dentritic cells through the activation of TLR7, 8 and 9. In this case MYD88 binds and IRAK1 and 4 are recruited followed by activation of TRAF6 which activates IRF7 only.
SARM, the 5th TIR containing adapter protein differs from the others in that it does not activate NF-κB or IRF3, instead it acts as a negative regulator of TLR signalling. It has been shown to bind TRIF and inhibit TFIF dependent NF-κB activation. The exact mechanism by which this occurs remains elusive.
It is clear that MYD88 has a very central role in TLR signalling as it is used by all but one of the TLRs. Essential roles have been suggested for the others but it is clear that they are not as diverse as MYD88. MAL deficient mice were unable to signal through TLR2 (Yamamoto et al., 2002a). Also TRIF has been documented to be essential for the TLR-3 and 4 MYD88-independent pathway (Yamamoto et al., 2003a) and TRAM also has an essential role in TLR4 mediated MYD88-idependent pathway (Yamamoto et al., 2003b). TRAF6 deletion completely abrogates TIR signalling, demonstrating its importance (Lomaga et al., 1999; Naito et al., 1999).
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Figure 1.1: The three TLR signalling pathways. There are three common pathways involved in Toll-like receptor (TLR) signalling. (a) The MyD88-dependent pathway: This pathway is used by all TLRs except TLR3. It is initiated in the case of TLR4 by the TIR domain of Mal binding the TIR domain of TLR4, which has dimerized after ligand binding. Mal recruits MyD88, which binds IRAK4 and -1. IRAK1 is phosphorylated by itself and IRAK4 and leaves the membrane to activate TRAF6. After TRAF6 is ubiquitinated, it interacts with TAB2 to activate TAK1. TAK1 activates the IKK complex and IκB is phosphorylated, ubiquitinated and degraded allowing NF- κB to translocate to the nucleus to produce pro-inflammatory cytokines. TAK1 also activates MKK6 which in turn activates JNK and p38 leading to AP-1 activation and the production of pro-inflammatory cytokines. TRAF6 can also activate IRF5. (b) The TRIF-dependent pathway: This pathway is used by TLR3 and with TLR4 by binding TRAM at the membrane. This pathway begins with the activation of TBK-1 leading to the activation of IRF3, a transcription factor that translocates to the nucleus to produce IFN-inducible genes. Alternatively RIP1 is activated by TRIF and this feeds into the MyD88 pathway by activating TRAF6. (c) The alternative
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MyD88 pathway: This only occurs in plasmacytoid dendritic cells with the activation of TLR7 and -9 leading to the activation of TRAF6 through MyD88, IRAK4 and -1. This results in the activation of IRF7 which translocates to the nucleus to produce IFNγ and IFN-inducible genes. Taken from Watters et al. 2007.
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Table 1.1: TLRs and their ligands. Taken from Watters et al. 2007
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1.2.5) The mitogen activated protein kinase (MAPK) pathway There are three main MAPK pathways; c- jun amino terminal kinase (JNK), p38 and extracellular regulated kinase (ERK) (reviewed by Roux and Blenis 2004 (Roux and Blenis, 2004)). There are other MAPK pathways that exist for example the ERK5 pathway, however much less is understood about this pathway than the other three. The MAPK pathways and NFκB pathway are activated by receptors with a TIR domain, TNF-R and UV light. In addition to this, p38 and JNK are activated in response to cellular stress such as heat or osmotic shock and are often referred to as stress kinases. There are several isoforms of each MAPK, each with a specific role. In each MAPK signalling cascade there are three evolutionarily conserved kinases: a MAPK, a MAPK kinase (MAPKK), a MAPK kinase kinase (MAPKKK) which are activated sequentially (starting with the MAPKKKs). The MAPKs themselves are activated through a core signalling module that consists of threonine and tyrosine residues within a conserved TxY motif located in the activation loop of the kinase domain sub domain VІІІ (Kyriakis and Avruch, 2001), which is near the adenosine triphosphate (ATP)- and substrate- binding sites of the kinase. The x in the TxY motif is glutamic acid in ERK, proline in JNK and glycine in p38. The MAPKKK are serine/threonine kinases and are often activated by phosphorylation or as a result of interaction with small guanosine triphosphate (GTP)-binding proteins of the Ras/Rho family in response to extracellular stimuli (Kolch, 2000) other than this the connection between the MAPKKKs and the cell surface receptors is poorly understood. There are a range of targets which are phosphorylated by MAPKs which include phospholipases, transcription factors, cytoskeletal proteins and a group of protein kinases called MAPK activated protein kinases (MKs) (reviewed by Gaestel 2006 (Gaestel, 2006)). The MK family comprise the ribosomal S6 kinases (RSKs), mitogen- and stress- activated kinases (MSKs), MAPK- interacting kinases (MNKs) and MK2, 3 and 5. These targets are specific to the individual MAPK. A summary of MAPK signalling is shown in figure 1.2.
MAPK activation is normally transient. The levels of the MAPKs themselves do not change much between resting and stimulated cells but rather their phosphorylation status. Phosphatases play a major role in the down regulation of their activity (reviewed by Owens and Keyse 2007 (Owens and Keyse, 2007)). For example p38 can be down regulated by
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Figure 1.2: Signalling cascades leading to activation of the MKs. Mitogens and cellular stresses lead to activation of the ERK1/2 and p38 cascades, which in turn phosphorylate and activate the five subgroups of MKs. Taken from: Roux and Blenis 2004
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protein phosphatase 2A and by MAPK dual specificity phosphatases (MKP)-7 (Tanoue et al., 2001), and MKP-5 and MKP-1 (Camps et al., 2000).
1.2.5.1) Extra cellular regulated kinase (ERK) pathway The two ERK isoforms ERK1 and ERK2 were first identified as serine/threonine kinases rapidly activated by insulin treatment of 3T3-L1 adipocytes, and capable of phoshorylating microtubule associated protein 2 (Ray and Sturgill, 1987). ERK1/2, which are 42 and 44 KD respectively, share 83% homology and are expressed to varying degrees in all tissues (Chen et al., 2001b). In unstimulated cells ERK1/2 are distributed throughout the cell but upon stimulation they localise in the nucleus (Chen et al., 1992). The ERK pathway is activated by growth factors, phorbol esters, serum, heterotrimeric G protein coupled receptor, cytokines and microtubule disorganisation.
The ERK pathway consists of A-raf, B-raf, Raf-1 and c-Mos (which are the MAPKKKs), MAPK/ERK kinase (MEK)1 and 2 (which are the MAPKKs) and ERK1 and 2 (which are the MAPKs). The ERK pathway is activated by receptor tyrosine kinases (RTK) and G protein –coupled receptors which transmit activating signals to the Raf/MEK/ERK cascade through Ras which is itself activated by son of sevenless (SOS). SOS is a Ras activating guanine nucleotide exchange factor which stimulates Ras to exchange guanosine diphosphate (GDP) for GTP. Once Ras is activated it can interact with a variety of downstream MAPKKK (which are named above). Activated A-Raf/ B-raf/ Raf-1 and c-Mos bind and phosphorylates MEK1 and 2, which then phosphorylate ERKs1 and 2 through their TxY motif.
Downstream targets of ERK1 and 2 (reviewed by Yoon and Seger 2006 (Yoon and Seger, 2006)) include various membrane proteins (e.g.: calnexin), transcription factors e.g. c-fos, c-myc, signal transducer activator of transcription (STAT)-3, activating transcription factor (ATF)2, E26 transformation-specific (Ets)1 and ETS-like transcription factor (Elk)1), cytoskeletal proteins (neurofilaments and paxillin) and MKs. All three sub-families of MKs (RSKs, MSKs and MNKs) can be activated by ERK, although RSKs are exclusively activated by ERK (Frodin and Gammeltoft, 1999). The different cellular functions which ERK1/2 mediate are reviewed by Raman et al. 2007 (Raman et al., 2007).
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It is essential that this interaction between Ras and Raf is regulated to maintain normal cell proliferation. Mutations in Ras and Raf have been heavily implicated in cancers. Ras is mutated in 30% of all human cancers and B-Raf is mutated in 60% of malignant melanomas (Chong et al., 2003). This has meant that ERK pathway inhibitors are potential treatments for cancer. Currently small-molecule MEK inhibitors are in clinical trials (Friday and Adjei, 2008). In the laboratory U0126 and PD98059 are used to investigate functions of the ERK pathway. They are non competitive specific inhibitors of MEK1/2/5 which inhibit ERK1/2/5, reviewed by Ballif and Blenis 2001 (Ballif and Blenis, 2001).
1.2.5.2) MAPKp38 Pathway There are four isoforms of p38: p38α, β, γ and δ. The isoforms share 60% homology in their amino acids sequences, and approximately 40% homology with other MAPKs. P38α/β are ubiquitously expressed whereas p38γ is mainly expressed in skeletal muscle and p38δ is found in the lung, kidney, testes, pancreas and small intestine. The p38 pathway was discovered by two groups at similar times. Firstly the various isoforms were cloned as molecules that bound to pyridinyl imidazole compounds (also known as cytokine synthesis anti inflammatory drugs -CSAIDs). These compounds were known to inhibit IL-1 and TNF production from stimulated monocytes (Lee et al., 1994). Simultaneously p38 was identified as a component of a pathway activated by IL-1 which resulted in the phosphorylation of heat shock protein (HSP) 27 through MK2 (Freshney et al., 1994). The afore mentioned pharmacological inhibitors such as SB202190 and SB203580 have accelerated studies of p38α/β. Much less is known about p38γ/δ as they are not sensitive to these compounds.
As mentioned previously p38 is activated in response to cellular stresses in preference to mitogens which activate ERK1/2. Stimuli include UV radiation, osmotic shock, hypoxia, pro-inflammatory cytokines (IL-1 and TNFα), LPS (and other bacterial pathogens), GM- CSF and fibroblast growth factor (FGF) (reviewed by Chen et al. 2001, Ono and Han 2000 (Chen et al., 2001b; Ono and Han, 2000)).
The p38 module consists of a multitude of MAPKKKs, some of which are common to the JNK pathway. They include MAPK kinase kinase (MEKK)1-4, mixed-lineage kinase
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(MLK)2/3, dual leucine zipper kinase (DLK), MAPK-upstream protein kinase (MUK), apoptosis-regulating signal kinase (ASK)-1, one amino acid (TAO)1/2 kinase, tumor progression locus 2 gene (Tpl)-2 and TAK-1 (reviewed by Kyiakis and Avruch 2001 (Kyriakis and Avruch, 2001)). MAPKKKs phosphorylate serine/threonine residues on their target MAPKK which are MEK3/6 (Raingeaud et al., 1996). MEK3/6 are p38 specific, MEK6 can activate all 4 isoforms whereas MEK3 preferentially activates p38α/β. Once p38 itself has been activated it can phosphorylate several downstream substrates including several transcription factors: ATF1/2, monocyte enhance factor 2A (MEF2A), Elk-1 (Raingeaud et al., 1996), NF-κB (Beyaert et al., 1996), forkhead box O (FOXO)1 (Asada et al., 2007), Sap-1 (Janknecht and Hunter, 1997) and p53. It can also phosphorylate other kinases such as MKs: MSK1/2 (Deak et al., 1998), MNK1/2 (Waskiewicz et al., 1997) and MK2/3 (Freshney et al., 1994; McLaughlin et al., 1996).
Information on the sub cellular localization of p38 is relatively poor and conflicting. One study details how upon stimulation p38 may translocate from the cytoplasm to the nucleus (Raingeaud et al., 1995) however there is evidence from another group to suggest that active p38 is also present in the cytoplasm (Ben-Levy et al., 1998). Many studies of the p38 pathway point to a critical role in immunity and inflammatory responses. Its active form is detected in several cell types, especially those which are components of the immune system such as macrcophages, neutrophils, and T cells. p38 has been shown to participate in macrophage and neutrophil functional responses such as respiratory burst activity, chemotaxis, granular exocytosis, adherence, apoptosis and can mediate T cell differentiation by regulating IFNγ production. p38 also has a role in post-transcriptional regulation of gene expression by stabilising mRNAs. This will be discussed in greater detail later in the chapter.
Inhibition of p38 and components of its pathway provide a target for therapeutic development (reviewed by O’Neill 2006 and Saklatvala 2004 (O'Neill, 2006; Saklatvala, 2004)). CSAIDs were identified in 1994, since then many p38 inhibitors have been generated but only three have made it into phase ІІ clinical trials. BIRB-796 was hoped to treat RA, Crohn’s disease and psoriasis, however it did not make it past phase ІІ clinical
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trials. SCIO-469 is in clinical trails for pain, multiple myeloma and RA. VX-702 successfully met its objectives in phase ІІ clinical trials and will move forward for further testing (Dominguez et al., 2005; Goldstein and Gabriel, 2005).
1.2.5.3) The c- jun amino terminal kinase (JNK) pathway Three genes encode JNK: JNK1, JNK2, JNK3. There are ten or more alternatively spliced forms. JNK1/2 are ubiquitously expressed whereas JNK3 is mainly expressed in the brain. Like p38 they are activated in response to a range of stimuli including cytokines, UV irradiation, growth factor deprivation, DNA damaging agents and to a lesser extent G protein coupled receptors, serum and growth factors.
As detailed previously their activity depends on the phosphorylation of the conserved TxY motif. The MAPKK that are responsible for JNK activation are MEK4/7 which are themselves phosphorylated by the same group of MAPKKKs that phosphorylate p38 (MEKK1-4, MLK2/3, DLK, MUK, ASK-1, TAO1/2, Tpl-2 and TAK-1). Sub-cellular localization of JNK is also relatively poorly understood. JNK may also relocate from the cytoplasm to the nucleus upon activation (Mizukami et al., 1997).
The most well known JNK substrate is c-jun, which is a constituent of the AP1 transcription factor. JNK phosphorylates c-jun on serines-63 and -73. Mutation of these sites causes defects in malignant transformation (Behrens et al., 2000). Other transcription factors that are known to be phosphorylated by JNK include ATF2, NF-ATc1, heat-shock factor (HSF)1 and STAT3. JNK has a well established role in apoptosis, JNK deficient mice exhibit defects in apoptosis and immune responses. Also fibroblasts which lack JNK expression have defects in AP1 activity and decreased proliferation associated with increased expression of ARF, p53 and p21. As a result these cells were also resistant to stress induced apoptosis (Tournier et al., 2000). Other cellular processes that JNK has been implicated in include cell proliferation, differentiation, development and the inflammatory response. It has also been implicated in pathological conditions such as cancer, diabetes, autoimmune disease and ischemic tissue injury, reviewed by Weston and Davis 2007 (Weston and Davis, 2007). Drugs that inhibit JNK may therefore be useful, reviewed by Salklatvala 2004 and O’Neill 2006 (O'Neill, 2006; Saklatvala, 2004)). Several JNK
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inhibitors have been described (Waetzig and Herdegen, 2005), SP600125 is a small molecule inhibitor of JNK. It inhibits TNF production in monocytes and leukocyte migration in a rat model of allergic airway inflammation (Eynott et al., 2004). More recently drugs targeting JNK in mice have demonstrated therapeutic efficacy against type 2 diabetes (Kaneto et al., 2004) and tissue injury caused by ischemic disease such as stroke (Borsello et al., 2003; Graczyk et al., 2005; Guan et al., 2006; Hirt et al., 2004) and cardiac infarction (Milano et al., 2007).
1.2.6) The Phosphoinositide 3-kinase (PI3K) Pathway The PI3K pathway is one of the most important signalling pathways used by cell surface receptors which recognise growth factors, inflammatory stimuli, hormones and antigens. Cellular processes such as growth, survival, proliferation and movement are all affected.
PI3Ks are a family of enzymes that catalyse the phosphorylation of the D3 position of the inositol ring in one or more phosphoinositide substrates. PI3Ks have been classified into three groups: І, ІІ and ІІІ according to their substrate preference and sequence homology. Class І are primarily responsible for the production of D3 phosphorylated lipids. They are heterodimers of regulatory (p85) and catalytic subunits (p110). Receptors become engaged and cause the activation of tyrosine kinases, which phosphorylate tyrosine residues of adaptor proteins such as GAB-1. PI3K is bought to the membrane and directly activated by binding to phosphorylated tyrosine residues on the adaptor proteins or on the receptors themselves. Activated PI3K converts the plasma membrane lipid phosphatidylinositol-4,5- bisphosphate [PI(4,5)P2] into phosphatidylinositol-3,4,5-triphosphate [PI(3,4,5)P3]/PIP3. PIP3 recruits proteins with pleckstrin homology (PH) domains, such as Akt (also known as protein kinase B- PKB) and phosphoinositide-dependent kinase 1 (PDK1). PDK1 phosphorylates Akt, Akt then phosphorylates a multitude of other proteins which are involved with cell growth, cell cycle entry and cell survival. Phosphorylation of these targets by Akt normally has an inhibitory effect.
The main biological functions of these signalling pathways are in cell metabolism, cell cycle and survival, protein synthesis, cell polarity and mobility and vesicle sorting. Cell metabolism in muscle and fat is affected by Akt which promotes the uptake of glucose by
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stimulating the membrane translocation of the glucose transporter GLUT4. In addition to this Akt regulates fatty acid synthesis and can inhibit gluconeogenesis by blocking FOXO- mediated transcription of gluconeogenic enzymes. Akt can also affect cell cycle and survival by blocking the transcription of cell cycle inhibiters and of pro apoptotic factors.
Disregulation of the PI3K pathway has particular implications in the pathogenesis of diabetes and cancers. Insulin resistance is thought to occur at the proximal end of insulin signalling where the activation of PI3K is attenuated. The pathway has also been shown to be one of the most mutated systems in human cancers. The PI3K pathway therefore provides a target for therapeutic development especially in areas of cell growth and proliferation. There are currently Akt PI3K inhibitors in development, their success may depend upon the need for specificity in the targeting of the various PI3K isoforms.
The overview of signalling pathways in this chapter demonstrates the complexity of the processes involved in regulating inflammation. Prolonged inflammation is a symptom of many debilitating diseases, some of which have been mentioned above. Despite several successes with various anti-inflammatory therapies such as NSAIDs and TNFα inhibiting agents there are still many areas where needs have not been met. In addition lack of responsiveness and resistance to drugs have proven to be a problem. For these reasons there is still a lot of scope for the identification of novel anti-inflammatories.
Of these pathways this thesis is primarily concerned with the p38 pathway which is known to stabilise a group of inflammatory mRNAs which will be discussed later on in this chapter.
1.3) Gene Expression
1.3.1) Introduction Gene expression involves many steps, the first of which is transcription. mRNAs are synthesized in the nucleus by RNA polymerase ІІ (pol ІІ). Pol ІІ binds the promoter and synthesis begins at the start site and ends at the termination signal, at this point the newly synthesized mRNA along with the RNA polymersase is released.
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1.3.2) Transcription
1.3.2.1) Chromatin structure DNA is packaged in to chromosomes in the form of chromatin. Chromatin is a nucleoprotein complex consisting of a approximately 2:1 ratio of protein to DNA. Histones, which are a component of chromatin, are small positively charged proteins which allow DNA to become tightly bound to them. There are five types of histone which fall into two categories: nucleosomal histones and H1 histones. The nucleosomal histones: H2A, H2B, H3 and H4 make up nucleosomes. Each nucleosome consists of two heterodimers of histones H3 and H4 and two heterodimers of H2A and H2B histones resulting in an cylinder-like octomeric complex around which DNA can coil (Luger et al., 1997). The nucleosome is the fundamental repeating unit of chromatin. Each nucleosome allows 1.65 turns of DNA (146 bp) to wrap around it. Adjacent nucleosomes are connected by a region of linker DNA which varies between 0-80 bp in length (Kornberg and Lorch, 1999; Zlatanova et al., 1999). Nucleosomes are then folded into chromatin fibres (Zlatanova et al., 1998) which are approximately 30 nm in length. H1 histones have been implicated in the organization of nucleosomes into fibres (Belikov and Karpov, 1998).
The structure of chromatin plays a role in the regulation of gene expression (Wyrick et al., 1999). Firstly interactions between the histones and the phosphate backbone allow the DNA to be tightly wrapped around the nucleosome. Secondly, there is interaction between the N-terminal tails of the histones and adjacent nucleosome particles. Thirdly, the wrapping of the DNA around the nucleosome is irregular which provides a degree of flexibility or instability in the structure that may play a role in histone-DNA interactions critical for gene expression. The packaging of DNA into nucleosomes can repress or potentiate gene expression depending on the requirements of the promoter (Kornberg and Lorch, 1999; Luger et al., 1997; Luger and Richmond, 1998).
1.3.2.2) Chromatin modifications Higher order structure of chromatin is mediated partly by interaction between DNA and the N-termini of the histones which undergo a variety of modifications. Histones can be acetylated, phosphorylated, methylated or ubiquitinated. Histone H3 is acetylated at lysines 9, 14, 18 and 23, phosphorylated at serine 10 and methylated at lysines 9 and 27. (Spencer
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and Davie, 1999). These modifications also have a part in the regulation of gene expression but also in other cellular processes such as DNA template assembly, mitosis and replication (Strahl and Allis, 2000). Of these modifications acetylation is the most heavily implicated in regulation of gene expression. For example hyperacetylated histones are associated with transcriptionally active domains and more accessible chromatin structure whereas hypoacetylated histones are transcriptionally silent (Hebbes et al., 1988). Histone acetylation may influence transcription in more than one way. Firstly by disrupting the higher order chromatin structure and allowing greater access to the DNA sequence for the transcription apparatus and its regulators (reviewed by Spencer and Davie 1999 (Spencer and Davie, 1999)). Secondly acetylation of the histone may disrupt the nucleosome structure by neutralizing positively charged lysines thus decreasing their affinity for DNA or neighboring nucleosomes (Grunstein, 1997). Finally acetylation may promote or repress interactions with specific transcription factors (Davie and Spencer, 1999). Acetylation is facilitated by histone acetyltransferases (HATs) and can be reversed by histone deacetylases (HDACs).
Phosphorylation of histones H1 and H3 has been implicated in chromosome condensation during mitosis (Wei et al., 1998) and phosphorylation of H3 has also been linked to transcriptional activity, e.g.: phosphorylation of H3 correlates with the activity of SV40 immediate early response genes (Zlatanova et al., 1998). Histone H2A, H2B and H3 can be reversibly ubiquitinated which are modifications associated with transcriptionally active DNA (Davie and Murphy, 1994). Histones H2B, H3 and H4 can be methylated but the affect on transcription is poorly understood. There may be a correlation between methylation and acetylation and transcriptional activity as methylation is associated with acetylated forms of H3 and H4 (Hendzel and Davie, 1991).
1.3.2.3) Transcription activation and repression In addition to the basal factors mentioned above there are many sequence-specific transcription factors and coregulators that assist in transcription initiation. These are discussed further on in the chapter.
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Transcriptional activation is affected by the binding of transcriptional activators to upstream activating sequences, where they recruit and regulate the activities of chromatin modifying complexes and the transcriptional apparatus (Zlatanova et al., 1998). The enhanceosome is the term used to refer to the collection of multiple regulatory proteins which are bound to the DNA enhancer site which affect gene expression. Activators generally consist of two domains, one that binds specific DNA sequences and one that recruits and stimulates the activity of the basal transcription machinery. Activators can recruit chromatin modifying complexes such as the co-activator p300/CREB binding protein (CBP) which have HAT activity. Activators bind, thereby recruiting the pol ІІ containing transcription initiation apparatus. The advantage of the enhanceosome is that it allows the various transcriptional inputs to be coordinated into a single output signal.
Gene expression is regulated by repressors as well as activators. There are a variety of known transcriptional repressors with varying mechanisms. They can be divided into general and gene specific repressors. General negative regulators usually function via interactions with TATA biding protein (TBP) (Lee and Young, 1998). Mot1, negative cofactor 2 and the Not proteins are examples of repressors that function in this way (Auble et al., 1997; Collart and Struhl, 1994; Goppelt et al., 1996). Gene specific repressors function by binding activators or by competing for activator binding sites. For example Hsp90 binds to the heat shock transcription factor (Hsf1), preventing the formation of Hsf1 trimers required for the binding of heat shock DNA element (Zou et al., 1998). As discussed above HDACs can repress gene expression by affecting chromatin structure. The interplay between activators and repressors is important in the regulation of gene expression.
1.3.2.4) Initiation of transcription For the initiation of transcription in eukaryotes a translation initiation complex is required. The initiation complex assists pol ІІ (which consists of twelve subunits) and is composed of a group of proteins known as general transcription factors (GTFs) (reviewed by Conaway and Conaway 1997 (Conaway and Conaway, 1997)): TFІІA, TFІІB, TFІІD (contains TBP), TFІІE, TFІІF and TFІІH. Pol ІІ is capable of unwinding DNA, synthesizing RNA and rewinding DNA, however it is unable to recognise a promoter and initiate transcription, for
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these functions the general transcription factors are required. Pol ІІ along with the GTFs are able to carry out basal transcription in vitro. As well as the pol ІІ transcription machinery the coactivater known as Mediator is also required for transcription of almost all pol ІІ promoters (reviewed by Malik and Roeder 2005 (Malik and Roeder, 2005)). Mammalian Mediator contains up to 30 subunits and can interact with pol ІІ directly and with activator proteins (Takagi and Kornberg, 2006). It forms a tight complex with an activator at an enhancer site and then interacts with pol ІІ and the GTFs at the promoter to initiate transcription (Kornberg, 2005). The term ‘coactivator’ is not strictly true as the coactivator is in fact important for the negative regulation of transcription as well. Pol ІІ, GTFs and Mediator together make up the pre-initiation complex which is composed of nearly 60 proteins totaling a mass of 3080 KD. Pol ІІ provides the platform upon which all the other factors are assembled.
The TATA box is usually located 25 base pairs upstream to the transcription start site. It provides a binding site for TFІІD which contains the TBP, after this the other components for basal transcription associate, in the following order: TFІІA, TFІІB, pol ІІ, TFІІF TFІІE and TFІІH. TBP interacts with the minor groove of the TATA element, inducing a sharp DNA bend accompanied by a partial unwinding of base pairs that may be instrumental in the process of initiation. The sharp bend in the DNA is produced through projection of four phenylalanine residues into the minor groove. As the DNA bends its contact with TBP increases, thus enhancing the DNA-protein interaction. The strain imposed on the DNA through this interaction initiates separation of the strands. Because this region of DNA is rich in adenine and thymine residues, which base pair through only two hydrogen bonds, the DNA strands are more easily separated. Separation of the two strands exposes the 12-15 bp of the promoter DNA and allows RNA pol ІІ to begin initiation of transcription. Polymerases repeatedly initiate transcription releasing small RNAs, a process termed abortive initiation. The transition from abortive initiation to elongation requires two processes: promoter escape and promoter clearance.
1.3.2.5) Elongation It is thought that phosphorylation of RNA pol ІІ C-terminal repeat domain (CTD) is required for the transition between initiation and elongation. RNA pol ІІ CTD is the largest
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subunit of the RNA pol ІІ its phosphorylation status is closely related to the stage and function of the RNA pol ІІ in the transcription process. Unphosphorylated RNA pol ІІ CTD is found in initiation complexes whereas during elongation the RNA pol ІІ CTD is heavily phosphorylated, reviewed by Dahmus 1996 (Dahmus, 1996). Phosphorylated RNA pol ІІ CTD has a role in recruiting the capping enzyme to the newly synthesised transcript. There are several factors that have been identified as having a role in promoter escape, promoter clearance and in the elongation process. Those involved in promoter escape and clearance can be described as either positive or negative elongation factors, reviewed by Luse and Samkurashvili 1998 (Luse and Samkurashvili, 1998).
5,6-dichloro-1-β-D-ribofuranosylbenzimidazole (DRB) sensitivity inducing factor (DSIF), negative transcription elongation factor (NELF) and transcription release factor 2 are negative elongation factors. As the name suggests transcription release factor 2 affects the ATP-dependent release of nascent transcripts (Price et al., 1987). DSIF and NELF confer sensitivity to the transcriptional inhibitor DRB which inhibits RNA synthesis and CTD phosphorylation (Dubois et al., 1994). Another transcriptional inhibitor, actinomycin D, has a different mode of action. Actinomycin D binds to the pre-melted DNA conformation present within the transcriptional complex. This immobilizes the complex, interfering with the elongation of growing RNA chains (Sobell, 1985).
TFІІF and TFІІH aid in the formation of elongation competent complexes. P-TEFb counters the negative activity NELF and DSIF (Yamaguchi et al., 1998). As well as having a role in translation initiation, TFІІF and TFІІH affect elongation (Bengal et al., 1991). TFІІF decreases the repetition of abortive initiation and helps the early elongation complex maintain its activity (Yan et al., 1999). It has been proposed that the mechanism by which TFІІF promotes elongation stimulation is by wrapping DNA around RNA pol ІІ (Robert et al., 1998), association with elongation factors (Kim et al., 1999) and kinase activity (Rossignol et al., 1999). TFІІH’s role in elongation may be through the kinase activity it exerts on RNA pol ІІ CTD. TFІІS, Elongin, ELL, cockayne syndrome B (CSB), tat-SF1 and FACT are all other additional factors which affect the elongation process.
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Once abortive initiation has finished and elongation has begun, the RNA pol ІІ moves along the DNA releasing the completed single stranded RNA molecule as it goes. Elongation continues until RNA pol ІІ encounters the termination signal. For termination, a run of uridine residues are synthesized following the synthesis of a self complementary RNA nucleotide sequence. The self complementary RNA nucleotide, the sequence of which varies between transcripts, forms a hairpin helix that is critical in the process of transcription termination.
1.3.3) mRNA processing and translation
1.3.3.1) Introduction A fully processed mRNA includes a 5' cap, a 5’ untranslated region (UTR), a coding region, a 3' UTR, and a poly(A) tail. The 5' cap consists of a 7-methylguanosine residue (7mGpppN) and the 3’ end is polyadenylated. The cap structure is added immediately to the mRNA as it is processed and is a guanine residue methylated at position 7 connected to the first residue of the mRNA by a 5’-5’ triphosphate linkage (Shatkin, 1976). The poly(A) tail is approximately 200 adenine nucleotides in length, added to the 3’ end by the enzyme poly(A) polymerase (Colgan and Manley, 1997). The poly(A) tail is added down stream of a polyadenylation signal sequence; AAUAAA or AUUAAA. mRNA is cleaved at this site and poly(A) polymerase synthesises the poly(A) tail. These structures function to protect the mRNA from exonucleolytic decay. UTRs are sections of non protein coding RNA situated before the start codon and after the stop codon. They are important in mRNA stability, mRNA localisation and degradation. Following this processing the mRNA is spliced and exported to the cytoplasm through nuclear pore complexes (NPCs) where it undergoes either translation, degradation or storage for subsequent translation. Translocation is facilitated by the messenger ribonucleoprotein particle (mRNP) complex, the structure of this complex plays a role in the balance between translation and mRNA stability. The mRNP complex includes splicing factors and heterogeneous nuclear ribonucleoprotein (hnRNPs).
During translation, deadenylation is prevented by Poly(A) binding protein (PABP) which binds to the poly(A) tail of the mRNA (Gorlach et al., 1994) forming a complex with
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translation initiation factor (eIF4F), causing the mRNA to form a ‘loop’. eIF4F is a multi subunit factor consisting of eIF4G, eIF4A and eiF4E which mediates the recruitment of mRNA to the ribosomes. The loop formation inhibits mRNA decay by protecting the 3’ and 5’ ends from the deadenylase poly(A) ribonuclease (PARN) and the decapping enzymes. Translation occurs when the translation initiation complex is assembled at the 5’ cap (figure 1.3).
1.3.3.2) mRNA regulation- an important mechanism in the control of gene expression. mRNA decay is an important mode of gene expression regulation. It has been shown to be of particular importance in the regulation of mRNAs encoding immediate early response genes, such as proto-oncogenes, cytokines and growth factors. Often the presence of specific sequences in the 3’UTR of these mRNAs allows their expression in low levels in resting cells but also allows their rapid accumulation upon stimulation. Once the stimulus has subsided rapid decay takes over and maintains low resting levels of these proteins.
Several studies have used micro-array analysis to demonstrate the importance of mRNA stability in gene expression regulation in response to extracellular stimuli (Cheadle et al., 2005; Fan et al., 2002; Kawai et al., 2004; Raghavan et al., 2002; Scholzova et al., 2007). Fourty to fifty per cent of changes in gene expression were found to be attributable to mRNA stability in response to external stimuli (Cheadle et al., 2005; Fan et al., 2002). These investigations showed that mRNA turnover i.e. accumulation and degradation is as important as transcriptional regulation in the control of mRNA abundance.
Due to the critical functions of the transcripts regulated by this mechanism disregulation of this process contributes to the pathogenesis of many diseases. For example alterations in the mRNA turnover rate of transcripts encoding proto-oncogenes and cell cycle regulators have been associated with cancer, reviewed by Audic and Hartley 2004 (Audic and Hartley, 2004). Inflammatory cytokines such as INFγ, IL-2, TNFα and IL-17 contribute to autoimmune diseases such as RA. An imbalance between the stabilisation and decay of
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Figure 1.3: The deadenylase as an inhibitor of translation initiation and decapping. mRNA is thought to be circularised by interactions between translation initiation factors eIF4E (4E) and eIF4G (4G) and the polyA binding protein (PABP). This conformation protects the 3’ and 5’ ends of the mRNA from decapping and deadenylase activity. Poly A ribonuclease (PARN) can somehow penetrate the closed loop and remove the poly A tail whilst simultaneously blocking translation and decapping. Once deadenylation is complete PARN dissociates and the decapping enzymes hydrolyse the 5’ cap of the message. Taken from Wilusz et al. 2001.
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these mRNAs have been proposed to be part of the mechanism involved in autoimmunity, (reviewed by Seko 2006 (Seko et al., 2006)).
1.3.3.3) mRNA decay Decay of the majority of mammalian mRNAs is initiated by the shortening of the poly(A) tail (reviewed by Beelman and Parker 1995, Garneau et al. 2007 and Mitchell and Tollervey 2001 (Beelman and Parker, 1995; Garneau et al., 2007; Mitchell and Tollervey, 2001)). Some mRNAs have been shown to be decayed alternative mechanisms which are known as the deadenylation independent pathway and endonuclease-mediated decay (figure 1.4). The deadenylation-independent pathway bypasses the deadenylation step and the transcript is directly decapped. Examples of mRNAs which use this route are RSP28B (Badis et al., 2004) and enhancer of decapping (Edc)1 (Muhlrad and Parker, 2005). Endonucleolytic cleavage of the mRNA results in the generation of two products, a 5’ fragment which is a substrate for 3’-5’ decay and a 3’ fragment which is subject to 5’-3’ decay. Examples of mRNAs which are degraded in this way include 9E3, insulin growth- like factor 2 (IGF2) and transferrin receptor (TFR) (Beelman and Parker, 1995).
Deadenylation is initiated when PARN, disrupts the PABP-eIF4F complex simultaneously. PARN has cap-dependent deadenylase activity and inhibits the decapping enzyme from interacting with the 5’ end of the mRNA. PARN is not the only eukaryotic deadenylase, others include the poly(A) nuclease (PAN)2-PAN3 complex and the carbon catabolite repression (CCR)4- negative regulator of transcription (NOT) complex. The CCR4-NOT complex is the main deadenylase in Saccharomyces cerevisiae and PAN2-PAN3 is involved in the initial stages of poly(A) shortening. Once deadenylation has completed, mRNA is degraded by one of two main pathways; either by 5’-3’ degradation or by 3’- 5’degredation (reviewed by Liu and Kiledjian 2006 (Liu and Kiledjian, 2006)).
Following deadenylation PARN dissociates and the decapping enzyme can access the 5’ cap (figure 1.4). The 5’ decay pathway begins with the mRNA decapping, complex Dcp1- Dcp2, where Dcp2 is the catalytic subunit (Beelman et al., 1996). After decapping the 5’ end is exposed and digested by the exoribonuclease Xrn1. This occurs in the cytoplasm at foci known as processing bodies (PBs). There are several additional factors that are
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Figure 1.4: Mechanisms of RNA degradation. (A) The deadenylation-dependent pathway. (B) deadenylation-independent pathway. (C) Endonuclease-mediated mRNA decay. Taken from Garneau and Wilusz 2007.
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required for optimal decapping such as Sm-like (Lsm) proteins (Tharun et al., 2000) and the Edc proteins (Schwartz et al., 2003).
The 3’ pathway is facilitated by the exosome, a 10-12 subunit complex of 3’ exonucleases and polypeptides which exist in the nucleus and the cytoplasm (Butler, 2002). The exosome continues to degrade the mRNA body from the 3’ end after deadenylation has taken place, leaving an oligonucleotide with the cap structure still present. The cap structure is hydrolysed to m7GMP by the scavenger decapping enzyme (DcpS) (Liu et al., 2002).
3’ to 5’ decay was, until recently, thought to be the pathway preferred by mammalian cells whereas in yeast both pathways are in use but the 5’ to 3’ route is dominant (reviewed by Coller and Parker 2004 (Coller and Parker, 2004)). However it now seems that the 5’ to 3’ pathway could be equally important in mammalian cells as in yeast (Stoecklin et al., 2006; Yamashita et al., 2005).
How the decision is reached to translate mRNA or degrade it is thought to be influenced by the structure of the mRNPs (reviewed by Eulalio et al. 2007, Kedersha and Anderson 2007 and Shyu 2008 (Eulalio et al., 2007; Kedersha and Anderson, 2007; Shyu et al., 2008)). mRNPs are protein-mRNA complexes that form once an mRNA has been transcribed. Individual mRNP components allow specific mRNAs to interact with machinery that determine their subcellular localisation, translation and decay, in other words mRNP remodeling has a role in the decision to translate or decay. mRNPs have been shown to accumulate at two types of cytoplasmic foci known as stress granules (SGs) and processing bodies (PBs) (reviewed by Parker and Sheth 2007, Eulalio et al. 2007, Kedersha and Anderson 2007). Other RNA granules have been described, whether these are distinct from PBs and SGs is currently unknown. They may sub-classes of these structures.
1.3.3.4) Processing bodies (PBs) and stress granules (SGs) PBs are aggregates of translationally repressed mRNPs associated with translation repression and mRNA decay machinery. Their components can be roughly divided into three groups. The first consists of the mRNA decapping machinery Dcp1p/Dcp2p (Ingelfinger et al., 2002; van Dijk et al., 2002) decapping enzyme activators (Parker and
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Sheth, 2007), Lsm1p-7p complex (Ingelfinger et al., 2002), the 5’-3’ exonuclease Xrn1p (Ingelfinger et al., 2002) and the CCR4/processing of precursor (POP)2/NOT complex (Cougot et al., 2004). Secondly they contain components which are limited to specific organisms or affect subclasses of mRNAs, for example PBs in Drosophila melanogaster neurons have been shown to contain staufen and FMRP containing RNPs which suggest a function for post-transcriptional regualtion in neuronal development (Barbee et al., 2006). Also PBs in metazoans include proteins involved in microRNA (miRNA) function. miRNAs are single-stranded RNA molecules of about 21–23 nucleotides in length, their main function is to down regulate gene expression. By contrast these proteins are not found in the PBs of Saccharomyces cerevisiae (Liu et al., 2005). Thirdly PBs contain mRNAs themselves (Liu et al., 2005).
When a cell is subjected to stresses such as heat shock, UV light or oxidative stress, repression of bulk mRNA translation occurs and they form cytoplasmic aggregates known as SGs. The formation of SGs is reversible once the stress has been alleviated. SGs are distinguishable from PBs in that they contain translation initiation factors and 40S ribosomal subunits (Anderson and Kedersha, 2006). eIF3, eIF4G, PABP and Ras-GTPase- activating SH3 domain binding protein are all found exclusively in SGs. Conversely, Dcp1p, Dcp2p and GW182 are found exclusively in PBs, which indicates that these structures are distinct from one another, however they are thought to be dynamically linked (Eulalio et al., 2007). This is supported by the observation that several components are common to both PBs and SGs. RCK/p54, cytoplasmic polyadenylation element-binding protein (CPEB), Xrn1, eIF4E, fas-activated serine/threonine phosphoprotein (FAST) and tristetraprolin (TTP) have all been found in PBs but relocate to SGs during times of stress (Eulalio et al., 2007). T-cell intracellular antigen-1 (TIA-1) and TIA-1 related (TIAR) proteins are mainly found in SGs but small amounts have been detected in PBs. Both PBs and SGs can be dispersed by cycloheximide (a translational inhibitor). In contrast puromycin (promotes the release of mRNA from ribosomes) can increase their numbers and their size (Eulalio et al., 2007).
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In their recent review, Parker and Sheth, propose a model for the dynamics of cytoplasmic mRNAs (Parker and Sheth, 2007). They suggest that mRNAs exported from the nucleus fall into 2 categories: 1) house keeping genes, which directly enter translation following export. These can subsequently enter SGs when the cell is exposed to stress. 2) Sub-sets of mRNAs that form a different kind of mRNP from those which are formed by housekeeping genes are automatically directed to PBs, adding an extra point of translational control. Those mRNAs which enter the translation process and are associated with the polysomes may enter the PBs if a defect in translation initiation or termination occurs or if they interact with decay machinery to form a mRNP. mRNAs which become associated with decay machinery can either be subjected to 5’-3’ decay, remain in the PB or exit the PB and re-enter translation. Finally, mRNAs whose translation has terminated may associate with proteins to form mRNPs which are directed to SGs, once an abundance of these is accumulated this enhances their re-entry into translation.
Components of various mRNA decay pathways have been identified in both PBs and SGs. For example Upf1, Upf2, Upf3, Smg5 and Smg7 have been found in PBs and are all factors required in nonsense mediated decay (NMD) (Sheth and Parker, 2006; Unterholzner and Izaurralde, 2004). PBs also contain factors involved in miRNA mediated silencing of gene expression, including: Argonaute, Rck/p54 and GW182 (reviewed by Eulalio et al. 2007, Kedersha and Anderson 2007 and Parker and Sheth 2007 (Eulalio et al., 2007; Kedersha and Anderson, 2007; Parker and Sheth, 2007)). Adenosine/uridine rich element (ARE) mediated decay (AMD), is facilitated by RNA binding proteins that destabilise their targets via an AU rich element present in their 3’UTR. The AU rich binding protein (AUBP) TTP has been shown to localise predominantly in PBs but also to a lesser extent in SGs.
1.3.3.5) mRNA surveillance: Nonsensense-mediated decay (NMD) The production of mRNA is subject to error. Mechanisms have evolved to protect the cell from faulty mRNAs which potentially encode toxic proteins. Surveillance mechanisms are present in the nucleus and in the cytoplasm. NMD is one of three cytoplasmic surveillance mechanisms and is capable of detecting and degrading mRNAs that contain premature termination codons (PTCs). PTCs can be a result of mutations, frame shifts, inefficient processing, leaky translation initiation and extended 3’UTRs. Translation of mRNAs with
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PTCs can result in truncated proteins with aberrant functions. Following PTC identification the aberrant mRNA is subject to decay by either the 5’- 3’ pathway or the 3’- 5’ route.
As mentioned above there are various regulatory mechanisms that control mRNA translation and decay. They include AMD which shall be the focus of the next section in this chapter.
1.3.3.6) RNA interference (RNAi) pathway RNA interference (RNAi) is a highly conserved pathway used by eukaryotes as a cellular line of defence directed against viral genomes or as a method to clear the cells of aberrant transcription products. Double stranded RNAs (dsRNA) lead to the silencing of genes of homologous sequence. The first description of RNAi was in made in plants in 1997 (Depicker and Montagu, 1997). One year later Fire et al. described the pathway in animals in a study where Caenorhabditis elegans were injected with dsRNA which caused potent and specific down regulation of their target genes (Fire et al., 1998). The cellular RNA interference machinery can be employed to specifically down regulate expression of target genes following transfection of cells with short dsRNA oligonucleotides of appropriate sequence (siRNAs).
The RNAi pathway is described as two stages; the initiation step and the effector step. RNAi is initiated by the ribonuclease enzyme Dicer (Dcr). During the initiation step, long dsRNAs are cleaved into 21-23 nucleotide fragments called siRNAs (Bernstein et al., 2001). Following this siRNAs move in to the effector stage. Their aim being to target mRNAs for cleavage. siRNAs are assembled into the RNAi induced silencing complex (RISC) which includes a member of the Argonaute (Ago) protein family. Assembly involves the unwinding of the siRNA within RISC which enables it to recognise the target mRNA (Cullen, 2002). The P-element induced wimpy testis in Drosophila melanogaster (PIWI) domain within Ago then acts as an endonuclease and cleaves the mRNA strand (Martinez and Tuschl, 2004; Sontheimer and Carthew, 2004). miRNAs, another type of small double stranded RNA molecule, are also capable of RNAi. The miRNA pathway is an evolutionary conserved pathway for controlling gene expression
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(reviewed by Tang et al. 2008 (Tang et al.)). More recently evidence to suggest that miRNAs have a role in the regulation of immunity has surfaced. This is thought to be bought about by several mechanisms including the control of the release of inflammatory mediators (reviewed by Lindsay 2008 (Lindsay, 2008)). To a large extent they employ the same machinery as siRNAs to cleave complementary target mRNAs and repress their translation. miRNAs are formed from long primary RNAs (priRNA) which are cleaved by an RNase ІІІ enzyme called drosha (Lee et al., 2003). Following cleavage a hairpin RNA of approximately 65 nucleotides known as pre-miRNA is produced. Pre-mRNAs are exported to the cytoplasm by exportin 5 where further processing by Dcr takes place to form miRNAs (Lee et al., 2003; Yi et al., 2003). miRNAs then employ the RISC complex and Ago protein to mediate gene silencing either by blocking mRNA translation, reducing mRNA stability or inducing mRNA cleavage (Liu et al., 2004; Meister et al., 2004). They do this following imperfect binding to miRNA recognition elements (MREs) within the 3’ and 5’ UTR of target mRNA genes (Didiano and Hobert, 2006; Doench and Sharp, 2004; Lewis et al., 2003). Imperfect miRNA:mRNA interactions means that individual miRNAs have the ability to target a variety of mRNAs and is a feature which separates this pathway from the siRNA pathway mentioned above (Krek et al., 2005; Lewis et al., 2005).
1.3.4) Adenosine/ uridine rich element (ARE) mediated decay (AMD)
1.3.4.1) Introduction One factor in determining mRNA stability is the presence of cis-acting element in the 3’UTR of transcripts. By far the most well understood of these is the ARE. ARE containing mRNAs often encode proto-oncogenes, cytokines and growth factors. Their disregulation is often observed in cancers, autoimmune diseases and diseases which are characterised by chronic inflammation. Because of this these genes require very precise control which is achieved by transcriptional and translational mechanisms as well as the control of their mRNA stability. These cis-acting elements are rich in adenosine and uridine residues and are not the only elements to have been identified in connection with mRNA instability. Stem loop structures found in the 3’UTRs of GM-CSF (Brown et al., 1996) and G-CSF (Putland et al., 2002) mRNAs have been found to promote destabilisation. The 5’UTR of some mRNAs such as IL-2 and KC (Tebo et al., 2000) and the coding region of c-fos, c-
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myc and β-tubulin contain elements which confer instability (Ross, 1995). Although AREs can confer stability as well as instability the term usually refers to those mRNAs which are prone to destabilisation.
AREs were first identified and hypothesized to have a regulatory role in mouse TNFα, and IL-1, human lymphotoxin, rat fibronectin and murine and human INFs (Caput et al., 1986). This was closely followed by work from another group who showed that the ARE of GM-CSF was able to cause the decay of the normally stable rabbit β-globin reporter mRNA (Caput et al., 1986). Since then many more genes encoding ARE containing mRNAs have been identified. It is estimated that five to eight per cent of human mRNAs have an ARE. These genes encode a diverse array of proteins with many different functions which have been organised into a database on the basis of their ARE type and organisation (Bakheet et al., 2001; Bakheet et al., 2003).
AREs are between 50 to 150 nucleotides in length. AUUUA is the classic motif, characteristically many overlapping copies, will be found in the 3’UTR within U rich regions. AUUUA and the presence of other U residues are important in mRNA degradation but they cannot account for the full extent of the destabilising activity which is observed by these motifs. The minimum sequence to cause instability is the nonamer UUAUUUA(U/A)(U/A), however the insertion of only one of these nonamers to a 3’UTR does not significantly increase destabilisation (Lagnado et al., 1994; Zubiaga et al., 1995). In support of this mutations of the GM-CSF ARE demonstrated that two copies of the nonamer were far more efficient at promoting destabilisation than one (Lai et al., 2005). Also mutation of the UUAUUUAUU in c-fos does not prevent it from being destabilised (Chen et al., 1994). These findings suggest that there may be other consensus sequences and factors that contribute to mRNA stability as well as AREs.
1.3.4.2) Classification of AREs AUUUA is the characteristic motif, but the size AU content and organisation of AREs can vary. AU rich elements have been classified into three groups depending on this information; (Chen and Shyu, 1995) Class І have one to three dispersed copies of the AUUUA motif in addition to U rich regions which are in close proximity. Class І AREs are
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found in the transcription factors c-fos and c-myc, in the genes coding for the cytokines IL-6 and IL-4 , proto-oncogenes and cell cycle regulatory proteins. Class ІІ AREs are mainly cytokines (e.g.: GM-CSF, TNFα, IL-2 and IL-3), and contain between five and eight copies of the AUUUA motif which may overlap and cluster. Class ІІ AREs have further been classified into five sub-groups (Bakheet et al., 2001; Bakheet et al., 2003). C-jun and β adrenergic receptor mRNAs contain class ІІІ AREs. Class ІІІ AREs do not have the AUUUA motif but are characterised by long U-rich regions. Different classifications of the ARE direct deadenylation in one of two ways. Class ІІ AREs direct asynchronous poly(A) shortening whereas classes І and ІІІ direct synchronous poly(A) shortening (Chen et al., 1995; Peng et al., 1996; Xu et al., 1997).
The exact mechanism by which AREs mediate mRNA decay has yet to be fully understood. One suggestion is that they promote deadenylation (Xu et al., 1997) and decapping (Gao et al., 2001). Several studies have shown that ARE containing mRNAs are preferably degraded by the exosome in the 3’-5’ direction (Chen et al., 2001a; Gherzi et al., 2004; Mukherjee et al., 2002). However, more recently 5’-3’ decay has also been shown to occur (Stoecklin et al., 2006). A role for miRNAs in ARE mediated decay has been proposed (Jing et al., 2005). Jing et al. show that RISCs are directed to ARE containing mRNAs.
1.3.5) Signalling pathways and mRNA decay Several signalling pathways have been implicated in mRNA decay, the JNK pathway has been shown to regulate IL-3 mRNA turnover in mast cells (Ming et al., 1998) and IL-2 mRNA in T-cells (Chen et al., 1998) both via their 3’ UTRs. MK2 has been shown to regulate TNF and IL-6 biosynthesis via their AREs (Neininger et al., 2002). Pitx2, c-jun, cyclin D1 and cyclin D2 mRNAs are stabilised via the Wnt/beta catenin pathway (Briata et al., 2003). The PI3-K pathway was shown to stabilise IL-3 mRNA. Schmidlin et al. showed destabilising factors to be phosphorylated by PKB causing it to complex with 14:3:3 proteins, resulting in its inactivation and finally ARE mRNA stabilisation was achieved (Schmidlin et al., 2004). By far the most heavily implicated pathway in mRNA stabilisation is the MAPK p38 pathway.
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1.3.5.1) The p38 pathway and mRNA stabilisation The p38 pathway can control gene expression at the transcriptional and post-transcriptional levels. At the transcriptional level p38 can control NFκB activation, the phosphorylation of and phosphoacetylation of histone H3, the phosphorylation of the TBP; TFІІB and the expression of c-jun through the phosphorylation of transcription factor MEF2C. Control of post-transcriptional gene expression by the MAPK p38 is facilitated by AREs (Brook et al., 2000; Lasa et al., 2000; Winzen et al., 1999).
Post-transcriptional regulation of gene expression by p38 was initially thought to be through translational control. TNFα and IL-1 protein expression was blocked in LPS stimulated human monocytes when treated with p38 inhibitors. mRNA levels were also measured and little change was observed suggesting p38 controls the expression of these genes by translational regulation. In support of this, an MK2 knockout mouse displayed decreased TNFα protein but normal steady state mRNA levels (Kontoyiannis et al., 2001; Kotlyarov et al., 1999). However later work by the same group showed that TNFα, IL-6 and other mRNAs were unstable in MK2 deficient mice (Hitti et al., 2006; Neininger et al., 2002).
The link between the p38 pathway and mRNA stabilisation was first described for Cox-2, which contains a class ІІ ARE. Inhibition of p38 in IL-1 treated fibroblasts caused Cox-2 protein expression and mRNA levels to decrease (Ridley et al., 1997). Further to this actinomycin D chase experiments have shown that Cox-2 mRNA induced by IL-1 in HeLa cells (Ridley et al., 1998) and by LPS in primary human monocytes (Dean et al., 1999) destabilised when p38 was blocked. There was no effect on transcription confirming that mRNA can be stabilised by the p38 pathway. Other inflammatory mRNAs that have been shown to be stabilised by the p38 pathway (reviewed by Clark 2003 (Clark et al., 2003)) are IL-1β, GRO-α (Sirenko et al., 1997), IL-6 (Li et al., 1999), TNFα (Brook et al., 2000; Lasa et al., 2000; Winzen et al., 1999), MIP-1α (Wang et al., 1999), GMCSF (Tebo et al., 2000), vascular endothelial growth factor (VEGF) (Berra et al., 2000) and matrix metalloprotinases-1 and 3 (MMP-1 and -3) (Reunanen et al., 2002). All of these genes contain an ARE in their 3’UTR. Although stabilisation of an mRNA by the p38 pathway
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depends upon the presence of an ARE, not all ARE containing transcripts are regulated in this way (Frevel et al., 2003). c-myc and c-jun are examples of mRNAs which have AREs but are not regulated by the p38 pathway (Dean et al., 2003; Rutault et al., 2001). p38 has therefore been implicated in the regulation of gene expression at two levels. However the idea of p38 in translational regulation should be regarded with some caution. Often where p38 was described as a translational regulator later studies have revealed the same targets to be regulated by controlling mRNA turnover. A prime example of this is TNFα mRNA, mentioned earlier in the text. Since the understanding of mRNA stability as a gene expression regulatory mechanism has developed, many more examples of this type gene expression regulation can be cited than of translational regulation. Whether this is in part due technical difficulties in studying translational mechanisms or whether in actual fact translational regulation has a more minor role than originally thought remains to be seen. The decision to exert translational control or control of the message stability or both could be cell type dependent, however both methods are dependent on the presence of an ARE and are mediated by MK2.
1.3.5.2) Mechanism of p38 mRNA mediated stabilisation How exactly the p38 pathway brings about message stability is still unclear. It probably involves deadenylation, MK2 and an ARE. Deadenylation assays showed that tetracycline regulated reporter β-globin mRNAs that contained Cox-2 and TNFα AREs displayed delayed deadenylation when p38 was active. The rate of decay once deadenylation had occurred remained unchanged (Dean et al., 2003). As mentioned earlier in the chapter mRNAs are protected from degradation by their ‘loop’ conformation. The ‘loop’ formation has been proposed to promote circulation of ribosomes around the mRNA molecule which in turn leads to enhanced translation (Gingras et al., 1999; Wells et al., 1998). Therefore the regulation of deadenylation could simultaneously control translation and mRNA stability. It could also explain why p38 was suggested to control certain mRNAs at the levels of mRNA stability and translation.
The investigation of the downstream substrates of p38 provides a link between p38 and mRNA stability. MK2 has been shown to regulate the stability of several mRNAs. Reporter
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assays showed that Cox-2, IL-6, IL-8 and TNFα transcript stability was mediated by MK2 and that this was ARE dependent (Brook et al., 2000; Han et al., 2002; Lasa et al., 2000; Neininger et al., 2002; Winzen et al., 1999). MK2 has its own downstream substrates which include Hsp27. Hsp27 has been shown to be required for the stabilisation of Cox-2 and IL-6 mRNAs in IL-1 stimulated HeLa cells (Alford et al., 2007). Another MK2 substrate is TTP (Mahtani et al., 2001). TTP has been shown to bind and destabilise TNFα mRNA (Lai et al., 1999). When TTP is phosphorylated by MK2 it is unable to exert its destabilising effect resulting in TNFα mRNA stabilisation (Stoecklin et al., 2004). There are several other AUBPs which will be discussed in detail in the next section.
Transcript specificity of the p38 pathway is not fully understood. Clearly an ARE is required but the presence of one does not necessarily confer p38 mediated stabilisation on the transcript. Several studies indicate that a complex arrangement of several AUUUA motifs may render the transcript susceptible to p38 regulation. However contrary to this a micro-array analysis designed to identify novel p38 sensitive targets revealed several examples of p38 sensitive ARE containing mRNAs with one AUUUA motif (Frevel et al., 2003). Cox-2, GM-CSF and TNFα all have multiple copies of the AUUUA pentamer but with differing organisations within their 3’UTRs. When mutated these transcripts were no longer responsive to p38 mediated post-transcriptional control (Brook et al., 2000; Winzen et al., 1999). Reporter assays showed that Cox-2 mRNA stabilisation by the p38 pathway was dependent on two distinct AREs which each contained three copies of the AUUUA motif. Several proteins (AUBPs) were demonstrated to bind the Cox-2 ARE, potentially these provide the link between the p38 pathway and ARE mediated stabilisation (Sully et al., 2004). In the case of GM-CSF mutation of the AUUUA motifs alone was not enough and additional flanking sequences were required for it to function in response to p38 (Brook et al., 2000; Winzen et al., 1999). Another study revealed that IL-8 had two distinct ARE domains. One which was responsive to p38/MK2 resulting in transcript stabilisation or destabilisation depending on MAPK activity. A second ARE confers sensitivity to HuR, resulting in IL-8 transcript stabilisation. Differing ARE domains within the same mRNA can subject it to regulation via different mechanisms (Winzen et al., 2004).
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Disregulation of mRNA stability has been implicated in the cause of some carcinomas, inflammatory diseases, thalassemia and Alzheimer’s disease. Disregulation of Cox-2 at the post-transcriptional level leading to its constitutive expression has been implicated in colorectal tumourgenesis (Dixon, 2004). In addition to this several cancers have been reported to result from the stabilisation of proto-oncogenes (reviewed by Audic and Hartley, 2004 (Audic and Hartley, 2004)). In Alzheimer’s disease iron accumulates in the brain but without an increase in ferritin. It has been suggested that Alzheimer’s disease brains could stabilise TfR mRNA while inhibiting ferritin synthesis (Pinero et al., 2000). Disregulation of TNFα mRNA has been shown to cause severe polyarticular erosive arthritis in mice (Taylor et al., 1996a).
1.4) Adenosine/uridine rich element binding proteins (AUBPs)
1.4.1) Introduction AREs provide sites to which AUBPs can bind. Several AUBPs have been identified (reviewed by Dean et al. (Dean et al., 2004)). Several AUBPs have been suggested to be regulated by the p38 pathway to bring about mRNA stabilisation but none have been proven. AUBPs can be mRNA destabilisers or stabilisers. Their exact mechanism remains unclear, p38 may regulate message stability either by inhibiting destabilising AUBPs or by activating stabilising AUBPs. Whatever the mechanism there are a number of criteria that they should fulfill: (1) The protein should be present in tissues/cells where p38 mediated post-transcriptional control occurs. (2) The protein should be present in the cytoplasm of the proposed cells, as this is where mRNA degradation takes place. (3) The protein should be able to control deadenylation. (4) The protein should only bind AREs regulated by p38/MK2 (Dean et al., 2004).
1.4.1.1) Human antigen R (HuR) HuR is a member of the embryonic lethal abnormal vision (ELAV)- like family of RNA binding proteins (reviewed by Brennan and Steitz, 2001 (Brennan and Steitz, 2001)). The ELAV locus is required for the development of the nervous system in Drosophila melanogaster (Robinow et al., 1988). HuR is not a particularly abundant protein and is ubiquitously expressed which is in contrast to the other family members (HuB, HuC and HuD) which are expressed only in the brain (Robinow et al., 1988).
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HuR and its family members have two N-terminal RNA recognition motifs (RRM) with high affinity for a U rich sequence known as HuR binding motif (HBM) followed by a nucleocytoplasmic shuttling sequence (NSS) and a C-terminal RRM which recognises the poly(A) tail (Fan and Steitz, 1998a; Fan and Steitz, 1998b; Lopez de Silanes et al., 2004). Deletion of one of the RRMs resulted in the loss of HuR’s ability to stabilise target reporter ARE containing mRNAs (Fan and Steitz, 1998b). HuR is found predominantly in the nucleus, but can shuttle between the nucleus and the cytoplasm, via the NSS which is located between the second and third RRM. At present the lack of an HuR knockout mouse means that techniques such as RNAi and over-expression assays have been employed to investigate its function.
Over-expression of HuR has been found to stabilise reporter mRNAs of TNFα (Dean et al., 2001), GM-CSF (Fan and Steitz, 1998b), IL-3 (Ming et al., 1998) and Cox-2 (Dean et al., 2004) mRNAs by blocking their decay after deadenylation. HuR does this by blocking the decay of the deadenylated mRNA. For example, c-fos deadenylation rate was not affected by HuR over-expression. HuR stabilised the deadenlyated c-fos mRNA (Peng et al., 1996). This differs from the mechanism p38 uses to stabilise mRNAs, which by contrast inhibits deadenylation. HuB was also able to inhibit mRNA destabilisation in the same way as HuR (Ford et al., 1999). In agreement with over-expression assays, depletion of HuR by RNAi results in the destabilisation of VEGF (Levy et al., 1998), cyclins A and B1 (Wang et al., 2000a) and p21 (Wang et al., 2000b).
HuR has been shown to bind the poly(A) tail of mRNA in both the nucleus and cytoplasm (Gallouzi et al., 2000). mRNA stabilisation correlates with an increase in the cytoplasmic levels of HuR which has been observed in over-expression systems as well as those looking at endogenous HuR. Its ability to shuttle led to suggestions that HuR might bind mRNAs in the nucleus and aid their transport to the cytoplasm, preventing them from interacting with the decay machinery. Several examples of mRNA stabilisation associated to cytoplasmic accumulation of HuR have been detailed. Following UV treatment HuR translocates to the cytoplasm in RKO colorectal carcinoma cells which is associated with the stabilisation of cyclin dependent kinase inhibitor p21 (Wang et al., 2000a). The onset of myogenesis in
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myocytic cells corresponds to a cytoplasmic increase in HuR (van der Giessen et al., 2003). The involvement of the p38 pathway is unclear. One report suggests that over-expression of an active mutant of MK2 increases cytoplasmic HuR (Tran et al., 2003) whereas work from this lab has failed to implicated p38 in HuR control in either RAW264.7 cells (Dean et al., 2001). As well as this, the stability of a reporter mRNA containing the Cox-2 ARE was tested in HeLa tet-off cells and was shown to be unaffected following the depletion of HuR using RNAi in the absence or presence of p38 activity (Sully et al., 2004).
Four protein ligands of HuR have been identified (Brennan et al., 2000): SETα, SETβ, pp32 and acid protein rich in leucine (APRIL). SETα, SETβ and pp32 are inhibitors of protein phosphatase 2A (PP2A). PP2A is a serine/threonine phosphatase which has affects on cell cycle progression, DNA replication, transcription, splicing, development and morphogenesis. Pp32 and APRIL are nucleocytoplasmic shuttling proteins and it is thought that these ligands increase HuR’s affinity for its target mRNAs and aid nuclear exportation. This is supported by a study which shows blocking of CRM1 (a nuclear export factor) results in the increased association of HuR with pp32 and APRIL within the nucleus and an increase in the ability of HuR to bind the poly(A) tail of a target mRNA. The fact that these ligands are inhibiters of PP2A, suggests that it is likely to be involved in the signalling cascades that are regulating the stability of mRNAs (Brennan and Steitz, 2001).
Its ability to stabilise pro-inflammatory mRNAs and a study which implicates HuR in the development of autoimmunity has led to its alleged function as an activator of inflammatory mediators (Di Marco et al., 2001). Contrary to this and expectations another study has revealed a role in inflammatory suppression. Katsanou et al. over-expressed HuR in macrophages and showed that it had no effect on the accumulation of TNFα and Cox-2 mRNAs in the absence of TTP (which has a destabilising role). Also they showed HuR synergized with TIA-1 to reduce translation of these transcripts (Katsanou et al., 2005). The authors say this is not necessarily a direct contradiction to previous work by other groups but that HuR has multiple functions that may have so far only been viewed in isolation.
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1.4.1.2) Heterogeneous ribonucleoprotein (hnRNP) The hnRNPs family of proteins were originally identified as having a role in pre-mRNA splicing (reviewed by Dreyfuss et al. 1993 (Dreyfuss et al., 1993)). hnRNPA1 and hnRNPC were the first of these proteins to be identified as mRNA binding proteins (Hamilton et al., 1993). Since then many more have been discovered but most studies have centered around ARE/poly(U) binding/degradation factor (AUF1).
AUF1 exists as four different isoforms: p37, p40, p42 and p45, generated by alternative splicing of a single mRNA (Wagner et al., 1998). Common to all four isoforms of AUF1 is an N-terminal, alanine rich stretch of 28 amino acids putatively required for dimerisation of the isoforms in solution and a C-terminal glutamine-rich domain required for high-affinity ARE binding (DeMaria et al., 1997). All four isoforms are predominantly nuclear and are nucleocytoplasmic shuttling proteins. The expression pattern of the various isoforms is cell- type specific. Mononuclear cells, purified from the umbilical cord peripheral blood of newborns, express p37, p40 and p42 AUF1 isoforms whereas the same cell type derived from adults express the p42 and p45 isoforms (Buzby et al., 1996). Mutagenesis of the C- terminal domain of AUF1 revealed that the p42 and p45 isoforms possess the nuclear export signal. Whereas nuclear import is probably facilitated by the p37 and p40 isoforms (Sarkar et al., 2003a).
AUF1 was originally identified, using in vitro assays, as a protein that binds the c-myc 3’UTR. AUF1 was found in human erythroleukemia K562 cells in a fraction that had ARE activity and caused the decay of c-myc mRNA (Brewer, 1991). However subsequent in vitro work could not implicate AUF1 in c-myc mRNA control. Affinity chromatography purification of the AUF1 containing fraction to remove AUF1 did not affect the stability of c-myc (Zhang et al., 1993). Other than c-myc, AUF1 has been associated other ARE containing mRNAs, such as the proto-oncogenes, c-fos and c-myc (Brewer, 1991; DeMaria and Brewer, 1996; Ehrenman et al., 1994; Xu et al., 2001; Zhang et al., 1993) the p38 regulated cytokines TNFα (Wison 2003), GM-CSF and Cox-2 (Lasa et al., 2000) and the cell cycle regulatory protein cyclin D1 (Lin et al., 2000).
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Both destabilising and stabilising roles have been suggested for AUF1. Loflin et al. showed that over-expression of isoforms p37 and p42 in hemin induced erythriod differentiation of K562 cells prevented the decay of a reporter mRNA. Conversely, the over-expression of the p40 and p45 isoforms partially restored the levels of ARE containing mRNAs. The effect that AUF1 has is therefore isoform specific (Loflin et al., 1999). Subsequent work by the same group showed that the AUF1 isoforms are potent stabilisers of mRNAs containing class ІІ AREs in NIH 3T3 cells (Xu et al., 2001). Another group compared the effect of over-expressing the different isoforms on ARE containing transcript stability in CHO cells. They found that over-expression of p37 and to a lesser extent p40 caused instability of target mRNAs. The over-expression of the other two isoforms had little effect (Sarkar et al., 2003b). Another example of the differing effects that the AUF1 isoforms have was demonstrated in a study that showed the p37 isoform to have the highest affinity for the cfos ARE and p40 the lowest (Wagner et al., 1998). Another group hypothesized that it is the relative abundance of the isoforms that determines the overall effect that AUF1 exerts rather than the absolute amounts. HT1080 cells which stably expressed green fluorescent protein (GFP) linked to an ARE were used to study mRNA turnover. siRNAs which targeted sequences common to all four isoforms did not affect fluorescence whereas selective down regulation of p40 and p45 strongly increased fluorescence by stabilising the GFP-ARE reporter mRNA (Raineri et al., 2004). Currently, the precise role AUF1 is not wholly understood. It seems that its function as a stabiliser or a destabiliser may be cell type and isoform dependent (Laroia and Schneider, 2002).
A functional link between HuR and AUF1 has been postulated. This is based on the fact that there is an overlap in their tissue distribution, both preferentially localise to the nucleus and can influence the expression of many common target RNAs (Lu and Schneider, 2004). HuR and AUF1 can simultaneously or competitively bind to a single ARE, which has been shown biochemically (Lal et al., 2004) and more recently using immunofluorescence which has enabled the sub-cellular localisation of the interactions to be investigated. Using fluorescence resonance energy transfer (FRET) and fluorescently labeled cyan fluorescent protein (CFP)/ yellow fluorescent protein (YFP) fusion proteins of HuR and p37AUF1 David et al. showed homodimer and heterodimer interactions of HuR and p37AUF1 in both
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nucleus and the cytoplasm (David et al., 2007). Furthermore, treatment with the MAPK activator, anisomycin, which commonly stabilises ARE-containing mRNAs, caused rapid nuclear to cytoplasmic shuttling of HuR. AUF1 also underwent shuttling, but on a longer time scale (David et al., 2007). Whether HuR and AUF1 bind concurrently or competitively is probably influenced by more than one factor, including the sequence of the target RNA, the relative abundance of each AUBP, the environmental influences on the cell and the sub- cellular location of the RNP complex (Lal et al., 2004).
More recently a role in translational regulation for AUF1 has also been proposed. C-myc has been implicated as an AUF1 target in previous studies and its disregulation is central to tumour formation. RNAi was used to deplete AUF1 and had no effect on mRNA stability, further analysis showed that translation of c-myc and cell proliferation was inhibited in the absence of AUF1. TIAR had the opposite effect and displayed translational repression of c- myc. Both AUF1 and TIAR mediate their effects on c-myc via its 3’ ARE. These observations suggest a mechanisms for translational control of an ARE containing transcript where the ratios of AUF1 and TIAR determine the outcome (Liao et al., 2007). In support of a role in translation for AUF1, interactions with components of the translational apparatus have been demonstrated. Work from other groups showed that all four AUF1 isoforms can bind directly to the translation initiation factor eIF4G at a C-terminal site (Lu et al., 2006) and with PABP to access the poly(A) tail and prevent translation (Sagliocco et al., 2006).
AUF1 is phosphorylated in vivo (Wilson et al., 2003a; Wilson et al., 2003b; Zhang et al., 1993), which makes it a possible candidate for mediating p38 mRNA stabilisation. THP-1 cells were used to show that stabilisation of some ARE containing mRNAs following phorbol ester treatment was accompanied by the dephosphorylation of serines 83 and 87 of the polysome associated AUF1 isoform p40 (Wilson et al., 2003b). Another publication from the same group showed that phosphorylation of p40 affects ARE binding and the physical interaction of p40 with the ARE. The conclusion was that regulation of p40 phosphorylation was able to mediate stability of its target mRNA by causing conformational changes and therefore remodeling of the RNA structure (Wilson et al.,
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2003a). Another group showed that blocking the p38 pathway in human monocytes prevented IL-1β stabilisation and reduced binding of AUF1 to its ARE (Sirenko et al., 1997). Despite these data neither p38 or MK2 have been shown to phosphorylate AUF1, meaning a link between AUF1 and p38 mediated mRNA stabilisation is still unproven.
CarG box-binding factor A (re-named AUF2) was identified in this lab. It shares high sequence homology with AUF1. It was identified in chromatographic fractions of cell extracts which were part of a complex with a TNFα ARE probe in electro mobility shift assay (EMSA). It was purified by ion exchange chromatography and identified by mass spectrometry. The extract contained all of the AUF1 isoforms and two AUF2 isoforms, p37 and p42. Recombinant AUF2 was found to bind both the TNFα ARE and Cox-2 in EMSA. Over-expression of AUF2 caused a partial destabilisation of Cox-2 ARE reporter mRNA. So far no link between AUF2 and the p38 pathway has been established (Dean et al., 2002).
1.4.1.3) T cell –restricted antigen (TIA)-1 and TIA related protein (TIAR) The TIA-1 polypeptide has three RRMs and a C-terminal Q (glutamine) -rich domain (Beck et al., 1996; Kawakami et al., 1994). In humans a second gene that encodes TIAR is present. The two share 80% amino acid homology and they both bind U-rich stretches of RNA (Dember et al., 1996). Recently TIAR has been shown to bind and exert stability via a C-rich region within the 3’UTR of its targets (Kim et al., 2007). There are at least two alternatively spliced forms of TIA-1 and TIAR (Beck et al., 1996; Kawakami et al., 1994). The function of the Q-rich domain is to direct mRNAs associated to TIA/TIAR to SGs during translational silencing (Gilks et al., 2004). The Q rich region along with the N-terminal RRM (RRM1) functions to recruit the U1 spliceosomal component (snRNP) (Forch et al., 2002). RRM1 also recruits single stranded DNA molecules (Suswam et al., 2005a). The C-terminal RRM (RRM3) can be co-immunoprecipitated with cellular RNAs (Dember et al., 1996). RRM2 binds the U-rich region on its target mRNA (Forch et al., 2002).
Cells lacking both TIA-1 and TIAR are not viable, indicating that these proteins are essential for survival (Le Guiner et al., 2003). Knockout of either TIA-1 or TIAR in the mouse results in mild arthritis due to an over-expression of inflammatory cytokines (Fechir
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et al., 2005; Mazan-Mamczarz et al., 2006; Phillips et al., 2004; Piecyk et al., 2000; Tong et al., 2007; Yu et al., 2003b). Two types of targets have been identified for TIA-1 and TIAR: (1) the 3’UTR of certain mRNAs including IL-8, MMP-13, Cox-2 and TNFα. (2) The U-rich sequence near the 5’ splice sites of pre-mRNAs such as FGF2, fas and TIAR itself. When the 3’UTR is bound TIA-1/TIAR tends to exert a translational silencing effect by sequestering these mRNAs in SGs away from the translational machinery whereas the binding of pre-mRNA results in splicing (Suswam et al., 2005a). More recently a gene array analysis was published showing that sub-set of mRNAs over-expressed in the absence of TTP were also over-expressed in the absence of TIA-1. The results suggested a mechanism whereby TIA-1 induces enhanced mRNA decay by promoting polysome disassembly which renders some specific mRNAs available for degradation via either of the 3’-5’ or the 5’-3’ decay pathways (Yamasaki et al., 2007). In contrast to this TTP is thought to aid mRNA decay by bringing it into contact with the decay machinery. This will be discussed in greater detail later in this chapter. Decay of a transcript is therefore probably dependent on the presence and interactions of multiple factors.
TIAR’s role as an AUBP was identified by it binding to TNFα (Gueydan et al., 1999). TIA-1 has also been shown to bind the TNFα ARE using supershifts in EMSA (Piecyk et al., 2000). The TIA-1 knockout mice do not display higher levels of TNFα mRNA nor is its stability affected (Piecyk et al., 2000). However, macrophages taken from these mice, treated with LPS do produce twice as much TNFα protein as those taken from wildtype mice (Piecyk et al., 2000). Cox-2 protein but not mRNA was also shown to be increased in fibroblasts taken from TIA-1 knockout fibroblasts (Dixon et al., 2003). IL-1β, IL-6, GM-CSF and IFNγ were all unaffected by the lack of TIA-1 (Piecyk et al., 2000). These data suggest it unlikely that TIA-1 is responsible for p38 mediated mRNA stabilisation as the afore mentioned genes are p38 regulated. Due to its inability to affect mRNA stability TIA-1 has been suggested as a translational silencer, which is further supported by a report which shows an increase in the association of TNFα mRNA with polysomes. This regulation appears to be p38 independent, as demonstrated by the addition of the p38 inhibitor to cytoplasmic cell fractions in TIA-1 wildtype and knockout cells. The effect was
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the same in both cases; TNFα mRNA shifted from polysomal to monosomal fractions (Piecyk et al., 2000).
1.4.1.4) The far upstream sequence element binding protein (FBP) family The FBP family consists of three members: FBP1, FBP2 (also known as KH-type splicing regulatory protein-KSRP) and FBP3. FBP1 was first described as a single stranded DNA binding protein that activates transcription via the far upstream binding element of c-myc (Duncan et al., 1994). In this lab FBP1 has been identified as a putative Cox-2 AUBP in HeLa cells (Sully et al., 2004) and as a TNFα AUBP in RAW cells. KSRP has four RNA binding K homology (KH) motifs (Min et al., 1997). These motifs are necessary and sufficient for promoting rapid mRNA decay (Gherzi et al., 2004).
KSRP has been reported to promote decay of a variety of ARE containing transcripts. One group showed by in vitro decay assays that KSRP could destabilise IL-2, c-fos and TNFα mRNAs. They went on to show that this was also the case in vivo, and was shown in Jurkat, HeLa and HT1080 cells. Furthermore, using heterologous CAT mRNAs containing various AREs in their 3’UTRs, suppression of KSRP compromises the rapid decay of mRNAs from all three ARE classes (Gherzi et al., 2004). In another study KSRP is shown to have an involvement in regulating the stability of Pitx2, c-jun and cyclins D1 and D2 mRNAs (Briata et al., 2003). In C2C12 myoblasts, KSRP was able to destabilise a sub-set of myogenic transcripts (Briata et al., 2005). Finally, KSRP has also been shown to bind and destabilise iNOS (Linker et al., 2005) β-catenin (Gherzi et al., 2006) and IL-8 mRNAs (Suswam et al., 2005b; Winzen et al., 2007).
Recently two micro-array studies have identified several more potential KSRP targets. Winzen et al. performed a micro-array analysis in HeLa cells. They stimulated HeLa cells for two hours with IL-1 and measured differences in gene expression using two different parameters: (1) Enrichment in pull-down with KSRP. (2) Increase in transcript after KSRP knockdown. Over 30,000 genes were screened and of those 1734 showed a mean increase of two fold or higher in the KSRP knockdown cells compared to the level for GFP knockdown cells. One hundred mRNAs were enriched in KSRP pull-down whose levels were also increased following KSRP knockdown. Of these, ten mRNAs decayed more
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slowly in the knockdown cells. The 10 mRNAs included the inflammatory cytokines IL-8, IL-6 and GM-CSF, chemokine (C-X-C motif) ligands 2/3 (CXCL2 and CXCL3) and the inflammatory mediator Cox-2 (Winzen et al., 2007).
Another study was prompted by one group’s initial observation that β-catenin mRNA is stabilised by the PI3K pathway (Gherzi et al., 2006) which mediates its effects by phoshorylation of KSRP, preventing it from performing its destabilising activity (Gherzi et al., 2006). Ruggiero et al. identified twelve possible KSRP targets in pituitary αT3-1 cells. Of these seven were shown to accumulate upon KSRP knockdown or PI3K activation. The mRNAs identified include RNA binding proteins, signalling molecules and replication- independent histone (Ruggiero et al., 2007).
Several signalling pathways have been implicated in the selective regulation of various mRNAs shown to be targeted by KSRP. The wnt/β-catenin pathway stabilises Pitx2 mRNA and causes cytoplasmic levels of KSRP and its interaction with target AREs to decrease (Briata et al., 2003). MAPK p38 but not MK2 was shown to phosphorylate KSRP at threonine 692 in C2C12 myoblasts resulting the stabilisation of myogenin and p21 transcripts (Briata et al., 2005). Another group showed that KSRP can interact with the IL-8 ARE to promote degradation in vitro and in vivo in HeLa cells. They also showed that IL-1 (an activator of the p38 pathway) could promote IL-8 stabilisation by impairing the function of KSRP through phosphorylation by p38. This effect was reversed by the addition of the p38 inhibitor (Winzen et al., 2007). Although MK2 has not been shown to phosphorylate KSRP, an indirect link between it and KSRP cannot be ruled out. As mentioned above the PI3K pathway stabilises and up-regulates β-catenin mRNA and a group of 7 other mRNAs in the pituitary αT3-1 cell line through phosphorylation and functional inactivation of KSRP (Gherzi et al., 2006; Ruggiero et al., 2007).
KSRP has been reported to interact with TTP and HuR (Linker et al., 2005) and co-purifies with the exosome (Chen et al., 2001a). Addition of a recombinant KSRP to purified exosome caused degradation of an ARE containing transcript (Chen et al., 2001a). Although KSRP has been found to be predominantly nuclear (Hall et al., 2004), recent
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reports mentioned above indicate that in some circumstances it must be translocated to the cytoplasm. In support of this is the fact that it has been found in association with the exosome which is cytoplasmic. Based on this and the work of independent groups it would be reasonable to postulate that KSRP brings about mRNA decay by recruiting their target mRNAs to the exosome where they undergo 3’-5’ degradation (Chen et al., 2001a; Gherzi et al., 2004). TTP has also been shown to associate with the exosome (Chen et al., 2001a). Linker et al. propose a mechanism of complex interplay between KSRP, HuR and TTP in the stabilisation of iNOS mRNA in DLD-1 cells following cytokine stimulation. They suggest that in untreated DLD-1 cells, KSRP binds to the iNOS ARE and recruits the exosome thus bringing about its decay. After cytokine treatment, TTP expression and therefore TTP/KSRP interactions are enhanced. TTP cannot bind the iNOS ARE but its interaction with KSRP results in dislodgment of KSRP/exosome complex from the iNOS mRNA. HuR and KSRP are capable of competitively binding to the same site of the iNOS ARE, as KSRP has been dislodged HuR can bind, resulting in iNOS mRNA stabilisation and subsequently iNOS protein expression (Linker et al., 2005).
Two groups have shown IL-8 mRNA to be destabilised by KSRP. The first used malignant breast cancer cells treated with IL-1 and showed that both KSRP and HuR could bind the 3’UTR of IL-8 (Suswam et al., 2005b). As well as this, Winzen et al. showed how IL-8 could be destabilised by both KSRP and TTP in HeLa cells. The two were both inhibited by signalling from p38 however KSRP was directly phosphorylated whereas TTP was phosphorylated by MK2 which is its down stream kinase (Winzen et al., 2007). HeLa cells therefore have two methods of IL-8 post-transcriptional regulation. Other common targets have been identified such as GM-CSF. The decision as to whether KSRP or TTP mediates decay is probably cell-type and stimulus specific.
It is clear that AUBP mediated mRNA decay is extremely complex, and that the interactions between AUBPs as well as their targets are not yet fully understood. KSRP has been shown to interact with numerous ARE containing transcripts but also with those that lack an ARE (Winzen et al., 2007). Many of the targets identified are involved in the
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inflammatory response and have been shown to be under the control of the p38 pathway. These recent findings suggest KSRP has a role in p38 ARE mediated mRNA decay.
1.4.1.5) The zinc finger 36 (Zfp36) family
1.4.1.5.1) Introduction In mammals, butyrate response factor 1 (BRF1), also known as TIS11b, ERF1, Zfp36L1 or cMG1 and butyrate response factor 2 (BRF2), also known as TIS11d, ERF2 or Zfp36L2 are members of a family of zinc finger containing ARE binding proteins. They will be referred to as BRF1 and BRF2. TTP (also known as TIS11, GOS24 and NUP475) is the other member (Blackshear, 2002; Carrick et al., 2004). They will be collectively referred to as the Zfp36 family. Recently a fourth member has been described in mice and has been designated Zfp36L3. Zfp36L3 is expressed mainly in the placenta (Blackshear et al., 2005). There is also another member found in frogs. The generation of a TTP knockout mouse has enabled it to become the most widely researched and best understood of the zinc finger proteins (Zfps). Much less is known about the biological roles of BRF1 and BRF2, which will be the focus of this project.
Human BRF1 is a 331 amino acid protein encoded by a gene on chromosome 14. BRF2 has 491 amino acids and the gene is located on chromosome 2. TTP consists of 326 amino acids and is encoded by a gene found on chromosome 19. the members of the Zfp36 family have several properties in common: a highly conserved tandem zinc finger (TZF) domain, leucine-rich nuclear export sequences, high levels of phoshorylation and the ability to bind and destabilise a set of common mRNAs in vitro. These similarities along with their emerging differences will be discussed in the following section.
1.4.1.5.2) The tandem zinc finger (TZF) domain This family of proteins is defined by a highly conserved central TZF domain (figure 1.5). Each member has two zinc fingers spaced 18 amino acids apart and contains three cysteine and one histidine residue with the spacing CX8CX5CX3H. The TZF domain is preceded with the amino acid sequence R(K)YKTEL. The TZF domain forms part of a sequence of 67 amino acids that are conserved between all three proteins (figure 1.5). BRF1 and BRF2 share 93% homology in their TZF domain. Outside of the TZF domain, the proteins are not
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closely related in structure (Varnum et al., 1991). All three also have regions rich in proline and serine. The TZF domain is necessary and sufficient for binding of Zfp36 family members to RNA (Amann et al., 2003; Worthington et al., 2002). Mutations in the TZF domain results in loss of ARE binding activity and therefore function (Lai and Blackshear, 2001; Lai et al., 1999; Lai et al., 2002; Stoecklin et al., 2002). The TZF has been identified in Caenorhabditis elegans (Tabara et al., 1999), Drosophila melanogaster (Ma et al., 1997) and Xenopus laevis (De et al., 1999), suggesting that the Zfp36 family have been evolutionary conserved. UUAUUUAUU has been identified as the sequence within the TNFα 3’ UTR to which TTP binds (Blackshear et al., 2003; Worthington et al., 2002). Hudson et al. propose an NMR structure of the TZF domain of BRF2 in complex with the above target sequence (Carrick et al., 2004; Hudson et al., 2004).
1.4.1.5.3) Discovery of Zfp36 proteins TTP was originally identified at similar times in three laboratories. Firstly TTP was identified in the Blackshear lab as a protein that accumulates in 3T3 fibroblasts upon insulin stimulation, displaying the characteristics of an immediate early response gene (Lai et al., 1990). Secondly the Herschman group described it as a gene responsive to phorbol esters (Varnum et al., 1989). Thirdly TTP was discovered as a serum response gene at John Hopkins University in Baltimore (Lau and Nathans, 1987). BRF1 was discovered in 1990 by Brown and colleagues who were the first group to describe the TZF domain (Gomperts et al., 1990). BRF2 was later cloned by Herschman’s group in 1990, on the basis of its homology with TTP and BRF1.
As previously mentioned, TTP gene expression is induced by various mitogens and growth factors (DuBois et al., 1990; Lai et al., 1990; Varnum et al., 1989). Induction by the cytokines IL-4, IL-6, TGFβ and interferons has been described (Nakajima and Wall, 1991; Sauer et al., 2006; Suzuki et al., 2003; Varnum et al., 1989). It is also known to be up regulated by TNF-α or lipopolysaccharide (Carballo et al., 1998) and recently dexamethasone (Smoak and Cidlowski, 2006), cinnamon (Cao et al., 2007b) and green tea (Cao et al., 2007a). As TTP destabilises TNFα mRNA it is thought to function in a negative feedback loop to prevent TNF-α over-expression. TTP can also bind to an ARE in its own 3’UTR, potentially regulating its own expression (Brooks et al., 2004; Tchen et al., 2004).
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Figure 1.5: A Schematic representation of TTP, BRF1, and BRF2. The RNA-binding zinc-finger domain is shown in black (RBD-Zn). The N-terminal (NTD) and C-terminal (CTD) mRNA decay activation domains defined in this study are indicated. The percent amino acid identity to TTP, of the NTD, RNA-binding domain, and CTD of BRF1 and BRF2 is given. (aa) Amino acids. Taken from Lykke-Andersen and Wagner, 2005.
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The BRF1 and BRF2 genes are also induced by mitogens or sodium butyrate, a histone deacetylase inhibitor. BRF1 and BRF2 have also been found to be induced by phorbol 12- myrisate-13 acetate (PMA) and LPS (Carrick et al., 2004). Unfortunately, because of a lack of reagents, expression of BRF1 and BRF2 has been studied largely at the mRNA level, and little is known about the expression of their proteins.
1.4.1.5.4) Expression and localisation The expression patterns of the three proteins has not been fully elucidated, much more is known about the expression of their mRNAs. A recently published study comparing the levels of the Zfp36 transcripts in several tissue types is probably the most comprehensive assessment of these mRNAs. In a previous publication they used quantitative (q)PCR to measure the relative abundance of TTP, BRF1 and BRF2 in human monocytes. Here they show that each transcript is induced rapidly by LPS. Of the three, TTP is the most dramatically induced. When their relative abundance is taken into account they have similar basal levels of expression but following stimulation, TTP accounts for 69% of the total Zfp36 transcript expression (Carrick et al., 2004). In the second more recent publication they show a thorough investigation into the relative expression levels of the three proteins in a range of tissue types. Ovary, bladder, lung and cervix were among the highest expressing tissues, TTP was particularly abundant in the cervix. On the whole, a tissue displayed either high or low levels of all three transcripts. The exceptions were the pancreas and thymus where elevated BRF1 and BRF2 mRNAs were observed in comparison to TTP (Carrick and Blackshear, 2007). They conclude that BRF1 and BRF2 mRNAs exist at higher basal levels than TTP mRNA but are less inducible.
TTP protein has been shown to be expressed in a variety of cell types in response to various stimuli including RAW cells, myeloid cells (Carballo et al., 1998), mast cells (Suzuki et al., 2003) and recently a group has shown it to be expressed in HeLa cells (Jing et al., 2005). This is of interest as members of this lab have found it hard to detect TTP protein in HeLa cells. Very little information about the protein expression of BRF1 and BRF2 exists which is mainly due to a lack of sensitive and specific reagents to detect them. A very recently published paper describes the production of recombinant BRF1 protein in Escherichia coli and an antiserum for its detection. Cao et al. show the differential expression of TTP and
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BRF1 in 3T3-L1 adipocytes and RAW264.7 cells. In response to LPS, BRF1 protein was undetectable in RAW264.7 cells whereas TTP was strongly induced, by contrast BRF1 was constitutively expressed in adipocytes and TTP was induced by cinnamon extract but not LPS (Cao et al., 2008).
All three members of the Zfp36 family are nucleocytoplasmic shuttling proteins (Phillips et al., 2002). Initially TTP was observed in fibroblasts as a nuclear protein (DuBois et al., 1990). Nuclear export was promoted by similar stimuli to those that cause its initial accumulation (Taylor et al., 1995; Taylor et al., 1996b). Contrasting observations were made in other cell types, such as macrophages and other leukocytes, which exhibited almost exclusively cytosolic TTP (Carballo et al., 1998; Fairhurst et al., 2003; Taylor et al., 1996b). Murata et al. detected TTP in the nucleus and the cytoplasm of COS-7 cells. Leptomycin-B inhibition of the nuclear export receptor CRM1 caused a nuclear accumulation of TTP, indicating that TTP was a nucleocytoplasmic shuttling protein. Using a GFP fusion protein system and mutagenesis a nuclear localisation signal (NLS) was mapped to the TZF domain of TTP, in addition to this an N-terminal leucine rich region of TTP served as a leptomycin B sensitive nuclear export signal (NES), indicating TTP uses a CRM1 dependent shuttling pathway (Murata et al., 2002). This work was confirmed for all three of the Zfp36 family members in another study. Similarly GFP fusion proteins of TTP, BRF1 and BRF2 were used. Predominantly cytoplasmic distribution of all three proteins was observed in 293 and HeLa cells. Deletion and mutagenesis analysis showed nuclear export signals in the N-terminus for TTP and in the C-termini of BRF1 and BRF2. Abolition of CRM1 activity resulted in nuclear accumulation of TTP, BRF1 and BRF2 (Phillips et al., 2002). Nup214 is nuclear pore protein which has been suggested to have an involvement in TTP localisation (Carman and Nadler, 2004).
1.4.1.5.5) Knockout phenotypes and binding targets To date there is no evidence for any differences in RNA binding specificity of the Zfp36 family. The fact that all three members of the Zfp36 family can bind and destabilise TNF-α, GM-CSF and IL-3 mRNAs (Lai and Blackshear, 2001; Lai et al., 1999; Lai et al., 2003) suggests that there is at least some overlap in their functions. A genetic screening approach also suggested similar function of TTP and BRF1 (Stoecklin et al., 2002). A stable HT1080
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cell line was generated, expressing GFP fused to the IL-3 ARE. After several rounds of chemical mutagenesis, a sub-line was identified in which GFP protein expression was increased (i.e., the GFP-IL-3 mRNA had not been degraded). Although the defect in GFP- IL-3 mRNA degradation was caused by mutation of both BRF1 alleles it could be rescued by exogenous expression of either BRF1 or TTP (Stoecklin et al., 2002; Stoecklin et al., 2000; Stoecklin et al., 2001). RNA interference experiments supported the conclusion that although only BRF1 was normally expressed in HT1080 cells, either TTP or BRF1 could destabilise GFP-IL-3 mRNA (Raineri et al., 2004; Stoecklin et al., 2002; Stoecklin et al., 2000; Stoecklin et al., 2001).
Although their in vitro binding specificities are the same, the phenotypes of knockout mice suggest some differences of the Zfp36 family members function in vivo. After a few months, TTP knockout mice display weight loss, severe poly-articular erosive arthritis and myeloid hyperplasia (Taylor et al., 1996a). Subsequent studies of macrophages derived from the TTP knockout mice demonstrated that these symptoms are caused by increased stability of TNF-α and GM-CSF mRNAs and over-expression of their corresponding cytokines (Carballo et al., 1997; Carballo et al., 1998; Carballo et al., 2000). Monoclonal anti-TNFα antibodies were injected in to newborn TTP knockout mice and the inflammatory phenotype was completely abrogated, confirming that TNFα was a true physiological target of TTP (Carballo and Blackshear, 2001; Taylor et al., 1996a). GM- CSF was identified as a second physiological substrate of TTP. Its mRNA was seen to stabilise in bone marrow derived stromal cells from TTP knockout cells in comparison to cells taken from wildtype mice (Carballo et al., 2000). It is not known whether GM-CSF is responsible for the myeloid hyperplasia characteristic of the TTP knockout phenotype. Primary T-lymphocytes taken from TTP knockout mice have been shown to display stabilisation of IL-2 mRNA. However it is not clear how IL-2 over-expression could relate to the phenotype of the TTP knockout mice (Ogilvie et al., 2005). Until recently, TNFα, GM-CSF and IL-2 were the only physiological targets of TTP that had been identified. Since an estimated 5-8% of all genes possess a putative ARE in their 3’UTR, TTP has the potential to affect a large number of transcripts. Other approaches have been used to
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identify new TTP targets, amongst these are over-expression experiments, RNAi and more recently micro-array analyses.
Over-expression studies suggest that TTP can bind the mRNA of IL-3 (Lai and Blackshear, 2001; Stoecklin et al., 2000), Cox-2 (Sawaoka et al., 2003), IL-6 (Stoecklin et al., 2001), plasminogen activator inhibitor (PAI) type-2 (Yu et al., 2003a), IL-8, VEGF (Suswam et al., 2008) and TTP itself (Brooks et al., 2004; Tchen et al., 2004). Silencing of TTP using RNAi identified β-1,4galactosyltranferase as target of TTP in human umbilical cord endothelial cells (Gringhuis et al., 2005). c-myc, cyclin D1 (Marderosian et al., 2006), VEGF (Essafi-Benkhadir et al., 2007), IL-6, IL-12 and MIP-2 (Jalonen et al., 2006) mRNAs we also suggested as TTP targets using RNAi. In vivo and in vitro studies showed that that TTP could bind Pitx2 and cause it destabilisation (Briata et al., 2003).
The Blackshear group, who were responsible for the creation of the TTP knockout mouse, performed the first of two recently published micro-array studies to identify additional TTP substrates. They took comparable stable fibroblast cell lines derived from both TTP knockout and wildtype mice. Two hundred and fifty mRNAs were stabilised in serum stimulated TTP knockout cells. Twenty three transcripts containing two or more copies of the optimal UAUUUA sequence to which TTP binds were selected for further analysis. Of these seven were confirmed to be significantly stabilised in TTP knockout cells and a further two to a lesser extent. These novel target transcripts for TTP included mRNAs encoding secreted proteins, protein kinases and enzymes. The most dramatically affected transcript encoded the protein immediate early response 3 (Ier3). Ier3 has been implicated in the physiological control of blood pressure. The 3’UTR of Ier3 has several highly conserved potential TTP binding sites and shares other features in common with other known TTP targets such as its ability to be rapidly induced and a short half-life. As well these it is also interesting to note that Ier3 can post-transcriptionally regulated by the p38 pathway (Corcoran et al., 2006). The stability of Ier3 was unaffected in BRF1 knockout cells, indicating that the Zfp36 proteins do have different in vivo targets. Interestingly β- 1,4galactosyltranferase was also detected in the micro-array amongst the most significantly stabilised transcripts. Ier3 underwent rigorous testing to prove its status as a TTP target, the
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other potential targets identified in this study will be subjected to the same tests before they can be declared TTP targets (Lai et al., 2006).
The second study took a slightly different approach. They used RNA isolated from affinity purified RNA-binding proteins otherwise known as RNA-immunoprecipitation (RIP). This RNA was then subjected to genome wide analysis (RIP-chromatin immunoprecipitation- CHIP). Stoeklin et al. used RIP-CHIP to identify mRNAs associated to TTP in LPS stimulated RAW264.7 cells. One hundred and thirty seven mRNAs were identified, amongst these was IL-10. IL-10 mRNA was subsequently shown to be stabilised in TTP knockout macrophages, identifying it as another physiological target of TTP. The ability of TTP to bind its targets appears to be highly dependent on the presence of the AUUUA pentamer or the UUAUUUAUU nonomer in their 3’UTRs (Stoecklin et al., 2008).
KC and E2A-encoded transcription factor E47 have also been suggested as TTP targets. KC mRNA was stabilised in HEK293 cells which are TTP deficient, and expression of TTP caused its destabilisation. KC mRNA was also found to be more stable in TTP-/- primary macrophages than in wildtype macrophages. In addition to this LPS induced stabilisation of KC in wildtype macrophages was sensitive to the p38 inhibitor but this was not the case in the TTP knockout cells (Datta et al., 2008). Another study looked at the expression of TTP in B cells. They found that TTP mRNA and protein were higher in stimulated splenic B cells from old mice in comparison to those isolated from young mice. This was inversely proportional to the levels of E47 expression. E47 regulates the expression and class switch of splenic B cells. The decreased E47 levels in old B cells was shown to be as a result of increased decay rates due an increase in TTP (Frasca et al., 2007). These studies are an indication of how TTP function might vary in different cell types. Although CXC chemokines were detected in the micro-array published by Lai et al. their half lives were only moderately affected by the absence of TTP. One possible explanation for this could be that the micro-array was carried out using fibroblasts rather than macrophages. E47 was not highlighted by either of the recent genome wide analyses, again suggesting that TTP function is cell type specific. It is also of interest to note that Datta et al. observed KC
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instability in cells that do not express TTP, suggesting that a single transcript could be a substrate of multiple AUBPs whose expression could be cell type dependent.
Finally, a very recent publication describes the identification of several TTP targets involved in dendritic cell maturation (Emmons et al., 2008). TTP immunoprecipitation followed by micro-array screening of human immature and mature dendritic cells highlighted 393 mRNAs as putative TTP mRNA targets. qPCR and functional studies were used to validate the micro-array data of six of the proposed TTP targets. Dual specificity phosphatase (DUSP)1, indoleamine 2,3 dioxygenase (IDO), superoxide dismutase (SOD)2, CD86 and major histocompatibility complex (MHC) classes 1B and F genes were found to be regulated by TTP via their 3’UTRs. DUSP1, SOD2 and IOD are all ARE containing transcripts. CD86 does not contain a canonical ARE nonamer but does have two ARE-like sequences. MHC class 1 on the other hand does not have an ARE or any related sequence and is therefore concluded to be regulated by a non-ARE-dependent mechanism (Emmons et al., 2008).
Stumpo and colleagues describe how disruption of the BRF1 gene causes embryonic lethality at day 9-11 of mouse embryogenesis, caused by failure of chorio-allanotoic fusion (Stumpo et al., 2004). Although it is difficult to identify the targets of BRF1, the fact that the knockout is lethal suggests that it has a critical biological role. Another study has also shown the BRF1 knockout to be lethal due to defects in vasculogenesis. These mice were found to exhibit elevated levels of VEGF. Interestingly, VEGF mRNA was not found to be unstable in BRF1 null cells but it was found to be abundantly associated with polyribosomes implicating BRF1 in VEGF translational control (Bell et al., 2006). This is slightly puzzling as VEGF contains a destabilising ARE in its 3’UTR. By contrast another group reported that in cells where BRF1 was over-expressed destabilisation of VEGF mRNA occurred. BRF1 was also shown to bind the 3’UTR of VEGF in vivo (Ciais et al., 2004). VEGF plays a crucial role in angiogenesis and endocardial development (Ferrara and Davis-Smyth, 1997). Its disregulation therefore could have adverse affects during development which would fit with the BRF1 phenotype. Human inhibitor of apoptosis protein-2 (cIAP2) has also recently been identified as a target of BRF1 in human head and
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neck squamous cell carcinoma cell lines (HNSCC). These cells were shown to over-express BRF1 in HNSCC cells sensitive to cisplatin (a chemotherapeutic) (Lee et al., 2005). Destabilisation of cIAP-2 resulted in increased caspase-3 activity resulting in cisplatin sensitivity in HNSCC cells (Lee et al., 2005). A recent micro-array screen to identify genes differentially expressed during myogenesis identified BRF1 as a strongly induced gene during this process. The C2C12 myoblast cell line was differentiated or left undifferentiated by addition or not of TGFβ, which is an inhibitor of myogenic differentiation. Actinomycin D experiments revealed that BRF1 was being regulated transcriptionally. Its expression was also dependent on p38 activity, something which has also been observed by ourselves (Busse et al., 2008).
Ramos and colleagues describe a BRF2 gene disruption that causes a truncated protein to be expressed, resulting in female infertility. It was discovered that embryonic development was blocked at the two cell stage, leading to the hypothesis that BRF2 has a role in mRNA regulation during embryogenesis (Ramos et al., 2004). BRF2 has also been identified as a candidate oncogene in breast cancer (Garcia et al., 2005), and as a p53 target gene. Induction of BRF2 resulted in the inhibition of cell proliferation and apoptosis (Jackson et al., 2006).
1.4.1.5.6) Phosphorylation TTP, BRF1 and BRF2 activity and localisation are probably controlled by phosphorylation. TTP is phosphorylated on several sites (Cao et al., 2006). As previously mentioned MAPK p38 is strongly activated by pro-inflammatory stimuli, and in turn activates MK2. MK2 phosphorylates TTP at serine residues 52 and 178, resulting in the recruitment of 14-3-3 proteins, which are phospho-serine- or phospho-threonine specific adaptor proteins (Chrestensen et al., 2004). It has been proposed that MK2-mediated phosphorylation of TTP causes inactivation, which accounts for the stabilisation of mRNAs by the p38 pathway (Anderson et al., 2004; Stoecklin et al., 2004) and that binding to 14:3:3 causes TTP to be localised to the cytoplasm (Johnson et al., 2002). In contrast Grighuis et al. have proposed that TTP mediated mRNA degradation is dependent on the phosphorylation of 14-3-3 by IKKβ and protein kinase C (PKC)δ (Gringhuis et al., 2005). Another report suggests that p38 does not regulate TTP function but does affect its exclusion from SGs in
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conjunction with 14-3-3 proteins (Rigby et al., 2005). Over 30 sites of phosphorylation have been identified for TTP, however all of their functions have yet to be determined. Some of these sites are located in regions that are relatively conserved across the three proteins (Cao et al., 2006), suggesting that BRF1/2 are also phosphorylated on several residues. Until recently MK2 was the only known kinase capable of phosphorylating TTP, however a newly published study shows that recombinant TTP can be phosphorylated in vitro by GSK3b, PKB, PKC, ERK, p38 and JNK (Cao and Lin, 2007). Another report shows that ERK as well as p38 inhibition are required for decay of TNFα mRNA by TTP (Deleault et al., 2008). Phosphorylation is also responsible for the sub-cellular localisation of TTP. Upon de-phosphorylation, as a result of p38 inhibition, TTP is relocated from the cytoplasm to the nucleus (Brook et al., 2006).
Sites of phosphorylation for BRF1 and BRF2 have yet to be fully determined. Schmidlin et al. have proposed two putative phosphorylation sites of BRF1. Similar to the model proposed by Stoecklin et al. for TTP de-activation, another laboratory have shown in vitro that PKB phosphorylates BRF1 at serine 92 causing it to complex with 14-3-3 resulting in mRNA stabilisation (Schmidlin et al., 2004). A second site at serine 203, identified by the same group, is also a PKB regulatory site. They show that both serine 92 and 203 work together to mediate BRF1’s decay activity. As well as mediating decay activity, serine 203 was found to have a role in the stabilisation of BRF1 protein itself. Benjamin et al. propose a model whereby phosphorylation of BRF1 causes it to bind 14-3-3 which inhibits both its decay activity and degradation. Prevention of its degradation ensures that there is sufficient BRF1 should decay need to be re-initiated (Benjamin et al., 2006). The requirement for a BRF1 stock could be an indication of the importance of BRF1 in the regulation of its targets and give partial insight into the inability of mice lacking BRF1 to survive. Most recently data has been published proposing four sites of BRF1 phosphorylation. Maitra et al. show that MK2 can phosphorylate BRF1 on serines 54, 92 and 203 as well as an unidentified site in the C-terminus. The other sites are in the N-terminus. Co-expression of active MK2 inhibits BRF1 decay activity but does not alter its ability to associate with its target mRNA or with mRNA decay enzymes (Maitra et al., 2008). Bands identified as BRF1 from HeLa cells extracts on SDS gels have different mobilities. On the basis of this
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the prediction is that some of these are phosphorylated forms of BRF1 and BRF2 (Tomas Santalucia- unpublished observations).
1.4.1.5.7) Mechanism of Zfp36 mediated mRNA decay Little is known about the precise mechanism that AUBPs use to alter decay rates. One possibility is that ARE-protein complexes alter the interactions between PABP and the poly(A) tail or between eIF4E and the 5’ cap allowing PARN to access the mRNA. TTP has been shown to associate with components of the exosome. Exosome associated TTP recruits ARE containing mRNAs, promoting 3’ to 5’ degradation (Chen et al., 2001a). Lykke-Anderson and Wagner have shown that TTP and BRF1 trigger decay by recruiting enzymes by two ARE mediated decay activation domains, one at the N- terminus and one at the C- terminus. These domains recruit enzymes from both pathways and are responsible for a range of activities including decapping, deadenylation and exonucleolytic decay (Lykke-Andersen and Wagner, 2005). More recently they have shown that TTP and BRF1 are able to deliver ARE containing GM-CSF and TNFα reporter mRNAs to PBs, RNAi depletion of TTP and BRF1 was able to reverse this. In agreement with previous work, the N- and C-terminal domains of TTP were found to be responsible for the localisation to PBs. Interestingly, delivery to PBs appeared to be enhanced during times of poor availability of mRNA decay enzymes, suggesting TTP and BRF1 sequester mRNAs to PBs when mRNA decay is inefficient. This indicates that TTP and BRF1 are able to facilitate mRNA decay even when decay machinery is limiting (Franks and Lykke-Andersen, 2007). TTP has also been implicated in miRNA mediated mechanism of ARE dependent mRNA degradation by interacting with components of the RNA induced silencing (RISC) complex (Jing et al., 2005).
As detailed in this chapter, the functions of the TTP homologs BRF1 and BRF2 are at unknown. Due to the lethal effect of BRF1 absence on mouse embryos and the lack of a complete BRF2 knockout mouse, study of these genes is problematic. We know that they are able to exert their effects by the same mechanism as TTP to down regulate the same ARE containing transcripts. However the phenotypes of the knockout mice suggest independent roles for these three genes. We also know that BRF1 can be phosphorylated by MK2 and PKB, the role that this has in mediating BRF1 effects has yet to be fully
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understood. It is also likely that BRF2 is phosphorylated, the significance of this is again unknown. This thesis seeks to characterise the expression of BRF1 and BRF2 and examine their possible physiological roles.
1.5) Aims • To investigate the regulation of TTP, BRF1 and BRF2 in a variety of cells including HeLa cells in response to pro-inflammatory stimuli. • To determine whether members of the Zfp36 family have different mRNA targets in vivo, and identify putative targets of BRF1 and BRF2. • To investigate the hypothesis that BRF1 and BRF2 are involved in the regulation of inflammatory mRNA stability by p38 MAPK.
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Chapter 2:
Materials and Methods
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2) MATERIALS AND METHODS
2.1) Materials
2.1.1) General All chemicals and reagents were from Sigma Aldrich unless listed below. • Dulbecco’s Modified Eagle’s medium, RPMI medium and trypsin were from PAA. • Foetal Calf Serum and penicillin and streptomycin were from Biowest or PAA. • SB202190 was from Calbiochem. • Agarose Gel Extraction Kit, Plasmid DNA Miniprep Kit, RNA Blood Kit, Qiashredders and Superfect were from Qiagen Ltd. • 1000 plasmid kit was from Novagen. • Polyvinylidene difluoride membrane (PVDF), film and enchanced chemifluorescence (ECL) kit were from GE Healthcare. • 100 bp marker and Shrimp Alkaline Phosphatase were from Promega. • PCRBlunt cloning kit, TOP 10 competent cells, See Blue Markers, Oligofectamine, optemem and dNTPs were from Invitrogen. • QuikChange site directed mutagenesis kit was from Stratagene. • All primers were synthesised and sequencing carried out by MWG. Restriction enzymes and Vent polymerase were from New England Biolabs. • Horse Radish Peroxidise (HRP) secondary antibodies were from Dako. • RTqPCR probes were from Molecular Probes. • RTqPCR master mix, RTqPCR enzyme and SYBR green master mix were from Applied Biosysytems or Invitrogen. • IL-6 human ELISA kit was from BD Pharmingen. • IL-6 and KC murine ELISA kits were from R and D systems. • Re-blot Plus Strong Solution was from Chemicon • TMB Peroxidase Substrate and TMB Peroxidase Substrate B was from KPL • Recombinant murine macrophage colony-stimulating factor was from Peprotech.
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2.1.2) Antibodies
Antibody Name Species Conditions Origin SB1/30.13 Rat monoclonal 1:1000 in 5%milk/1x PBS Raised against (gift from M.Turner) recombinant human BRF1 SB2/24.8 Rat monoclonal 1:1000 in 5%milk/1x PBS Raised against (gift from M.Turner) recombinant human BRF1. SB1/77.7 Rat monoclonal 1:1000 in 5%milk/1x PBS Raised against (gift from M.Turner) recombinant human BRF1. SB2/31.4 Rat monoclonal 1:1000 in 5%milk/1x PBS Raised against (gift from M.Turner) recombinant human BRF1. Anti-TTP Santa-Cruz Goat 1:200 in 5%milk/1x PBS Raised against the (G20) polyclonal N terminus of mouse TTP Anti-TTP Santa-Cruz Goat 1:200 in 5%milk/1x PBS Raised against the (N18) polyclonal N terminus of human TTP Anti-TTP Santa-Cruz Rabbit 1:200 in 5%milk/1x PBS Raised against (H-120) polyclonal amino acids 166- 285 near the C- terminus of human TTP SAK20A Rabbit 1:1000 in 5%milk/1x Raised against an N polyclonal PBS/Tween 20 terminal peptide of 0.01% mouse TTP: AIYESLLSLSPD SAK21A Rabbit 1:1000 in 5%milk/1x Raised against a C polyclonal PBS/Tween 20 terminal peptide of 0.01% mouse TTP: PRRLPIFNRISVSE Anti BRF1/BRF2 Rabbit 1:1000 in 5%milk/1x PBS Raised against the Cell Signalling Polyclonal C-terminus of human BRF1 COX-2 Human Rabbit 1:500 in 5%milk/1x Peptide (Alexis) polyclonal PBS/Tween 20 corresponding to aa 0.01% 567-599 COX-2 Mouse Rabbit 1:3000 in 5%milk/1x (Caymen) polyclonal PBS/Tween 20 0.01% FLAG (sigma) Monoclonal 1:5000 in 5%milk/1x Recognises FLAG PBS/Tween 20 sequence at the N 0.01% terminals as well as
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met-N terminal or the C- terminal Tubulin (Sigma) Monoclonal 1:20000 in 5%milk/1x Raised against PBS/Tween 20 0.01% native chick brain microtubules
NF-κB p65 Rabbit 1:200 in 5%milk/1x Epitope mapping (Santa Cruz) Polyclonal PBS/Tween 20 0.01% within the N- terminus of p65 of human origin CEBP/β (Cell Rabbit 5% BSA/1x TBS/Tween 20 Epitope mapping Signalling) Polyclonal 0.01% within the N- terminal region of human origin cfos Rabbit 1:200 in 5%/1x TBS/Tween Epitope mapping polyclonal 20 within N-terminus of c-fos of human origin ATF2 5% BSA/1x TBS/Tween 20 Raised against 0.01% amino acids 1-96 of ATF2 of human origin Pp38 (Cell Rabbit 1:1000 5% BSA/1x Raised against a signalling) Polyclonal TBS/Tween 20 0.01% phospho-peptide mapping corresponding to residues around Thr180/Tyr182 of human p38 MAPK Histone H1 Monoclonal 1:1000 in 5%/1x TBS/Tween Raised against 20 human leukaemia biopsy cells
2.1.3) Inhibitors Inhibitor Target Supplier Actinomycin D RNA polymersae Sigma Aprotinin serine protease Sigma 5,6-dichloro-1-β-D- Inhibits RNA synthesis, Calbiochem ribofuranosylbenzimidazole CTD phosphorylation (DRB) through casein kinase II inhibition E64 cysteine proteases Sigma Microcystin protein phosphatase 2A Alexis Corporation protein phosphatase 1
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Pepstatin aspartic proteases Sigma PMSF serine protease Sigma SB201290 MAPK p38 Calbiochem Trichostatin A HDAC inhibitor Sigma
2.2) Tissue culture
2.2.1) A549 cells A549 cells (cultured respiratory epithelial cells isolated from human lung tumour) were obtained from American Type Culture Collection (ATCC). They were cultured in DMEM with 10 % (v/v) FCS (Biowest). Cells were cultured in a humidified atmosphere with 5 % o CO2 at 37 C. All cell culture was carried out in a class ΙΙ laminar flow cabinet. For passaging, cell were washed twice with sterile PBS, 5 ml trypsin was added and cells incubated at 37 oC for approximately 5 minutes. Once cells were detached they were pelleted by centrifugation for 5 minutes at 600 g in a sterile tube containing an equal volume of DMEM to neutralise the trypsin. For general maintenance cells were seeded at a ratio of 1:3.
2.2.2) HeLa cells HeLa cells (human cervical carcinoma cells) were from ATCC and were cultured in DMEM supplemented with 10 % (v/v) FCS (Biowest). Cells were cultured in a humidified o atmosphere with 5 % CO2 at 37 C. All cell culture was carried out in a class ΙΙ laminar flow cabinet. For passaging, cells were washed twice with sterile PBS, 5 ml trypsin was added and cells incubated at 37 oC for approximately 5 minutes. Once cells were detached they were pelleted in a sterile tube containing an equal volume of DMEM to neutralise the trypsin (5 minutes, 600 g). Cells were passaged every second day and re-seeded at a ratio of 1:5 for general maintenance.
2.2.3) Isolation and culture of mouse bone marrow derived macrophages
Mice were sacrificed using CO2 and the skin was removed from the lower part of the body in sterile conditions. Legs were dissected away from the body and the tissue removed from them. The pelvic and femoral bones were further cleaned from all tissue in order to prevent contaminating marrow with other cells and they were then separated at knee joint. From
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this point on, all procedures were carried out under sterile conditions. The ends of each bone were cut off using a sterile scalpel. Using a needle and a syringe filled with DMEM medium , the bone marrow was flushed from both ends of the bone with a jet of medium into a 50ml falcon tube. The suspension obtained was vortexed until the cell aggregates were broken up. The volume was made to 30 ml with bone marrow medium and the cells were seeded in a 140 mm Sterilin Petri Dish in RPMI 1640 medium supplemented with 10 % (v/v) FCS and 1% penicillin and streptomycin. Cells were incubated for 5 to 7 days at
37°C in a humidified atmosphere with 10% CO2. The cells were supplemented with fresh medium on day 5. Growth medium was completely changed on day 6. On day 7, cells were trypsinised, counted and seeded at a density of 1 x 106 cells/well in a 6 well plate in bone marrow medium supplemented with 10 ng/ml M-CSF.
2.2.4) Mouse embryonic fibroblasts (MEFs) MEFs (provided by M.Turner, Babraham institute) were cultured in DMEM with 10 %
(v/v) FCS (Biowest). Cells were cultured in a humidified atmosphere with 5 % CO2 at 37 oC. All cell culture was carried out in a class ΙΙ laminar flow cabinet. For passaging, cell were washed twice with sterile PBS, 5 ml trypsin was added and cells incubated at 37 oC for approximately 5 minutes. Once cells were detached they were pelleted in a sterile tube containing an equal volume of DMEM to neutralise the trypsin (5 minutes, 600 g). Cells were passaged for general maintenance every week at ratios of either 1:5 or 1:10 depending on demand.
2.2.5) RAW264.7 cells RAW 264.7 cells are a mouse macrophage/monocyte cells line derived from Balb/c mice infected with Abelson leukaemia virus and were obtained from ATCC. They were cultured in DMEM with 10 % (v/v) FCS (PAA). For passaging, cells were washed once with serum free medium, 20 ml fresh medium was then added to the flask and cells were scraped using a sterile scraper and resuspended into the fresh medium. Cells were re-seeded at a ratio of 1:5 for general maintenance.
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2.2.6) Freezing and thawing of cell stocks To freeze, cells were pelleted as described above and resuspended in DMEM containing 10% (v/v) FCS and 10% (v/v) DMSO. Cells were then aliquoted into cryotubes and left to freeze at -70 oC before transferring to liquid nitrogen.
To thaw, frozen stocks were rapidly defrosted and added to an appropriate flask containing DMEM supplemented with 10 % (v/v) FCS. Cells were allowed to adhere overnight and then media was replaced with fresh DMEM supplemented with 10 % (v/v) FCS.
2.3) Transient transfections
2.3.1) Transient transfection of pFLAGCMV-TTP, pFLAGCMV-BRF1, pFLAGCMV-BRF2 plasmids into HeLa cells HeLa cells were seeded into 6 well plates at a density of 2.5 X 105/ well and left to grow overnight. The cells were transfected with 0, 10, 31.6, 100, 316 or 1000 ng of either pFLAGCMV-TTP, pFLAGCMV-BRF1 or pFLAGCMV-BRF2. The empty pFLAG vector was also added so that a total of 1 ug of DNA was transfected in each case. Each plasmid was complexed with superfect according to the manufacturer’s instructions and then added to the cells for 4 hours after which time the transfection mix was removed and the cells were washed twice with sterile 1x PBS [1.7 mM KH2PO4, 5.2 mM NaHPO4, 150 mM NaCl] and fresh DMEM supplemented with 10 % (v/v) FCS was added. Cells were left to o proliferate at 37 C, 5 % CO2 for 24 hours and were then harvested.
2.3.2) Transient transfection of HeLa cells with siRNA HeLa cells were seeded at a density 1 X 105 cells/ well and left to proliferate overnight. Cells were washed twice prior to addition of transfection complexes with serum free optemem. Smartpool or individual oligo siRNAs for BRF1, BRF2, scramble or luciferase were complexed with oligofectamine, according to the manufacturer’s instructions. A mock transfection control was included. The cells were then exposed to the siRNA:oligofectamine transfection mix for 4 hours after which cells were washed twice with sterile 1x PBS. The transfection mix was replaced with fresh Optimem supplemented with 5 % (v/v) FCS. Cells were harvested 48 – 72 hours following transfection.
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2.4 Cell harvesting and extract preparation
2.4.1) Preparation of whole cell lysates All of this procedure was carried out on ice. Media was removed and the cells were washed twice with ice cold PBS. Each sample was lysed in 1X Laemmli sample buffer [for 50 ml: 12.5 ml 1M tris/HCl pH6.8, 20 ml 10%SDS, 17.5 ml glycerol, 10 mg bromophenol blue, 40 µl DTT/ ml of buffer]. Genomic DNA was sheared by passing each lysate through a Qiashredder and centrifuged at 13000 rpm for 1 minute.
2.4.2) Preparation of nuclear and cytoplasmic protein extracts All steps in this procedure were performed on ice. The cells were washed twice with ice cold PBS and lysed in lysis buffer [10 mM HEPES pH7.6.3 mM MgCl2, 40 mM KCl, 2 mM DTT, 5% glycerol, 0.5% NP40, 2 mM NaF, 1 mM NaV, 1 mM phenylmethlsulfonyl fluoride (PMSF), 10μM E64, 2 μg/ml pepstatin A, 10 μg/ml aprotinin, 1 μM microcystin]. Nuclei were pelleted by centrifugation for 10 minutes at 600 g, the supernatant was retained as the cytoplasmic extract and snap frozen in liquid nitrogen. The nuclear pellet was washed twice with wash buffer [10 mM HEPES pH7.6, 3 mM MgCl2, 10 mM KCl, 1 mM DTT, 2 mM NaF, 1 mM NaV, 1 mM PMSF, 10μM E64, 2 μg/ml pepstatin A, 10 μg/ml aprotinin, 1 μM microcystin] and re-pelleted by centrifugation at 13000 rpm for 1 minute. The nuclear pellet was then resuspended in nuclear extraction buffer [20 mM HEPES pH7.6, 0.42 mM NaCl, 25% glycerol, 1.5 mM MgCl2, 0.2 mM EDTA, 1 mM DTT, 2 mM, NaF, 1 mM NaV, 1 mM PMSF, 10μM E64, 2 μg/ml pepstatin A, 10 μg/ml aprotinin, 1 μM microcystin] and incubated for 30 minutes with occasional vortexing (every 10-15 minutes). A final centrifugation at 13000 rpm for 15 minutes was performed to remove debris. The supernatants were retained as the nuclear extract and snap frozen in liquid nitrogen Supernatants and nuclear extracts were stored at -80oC until use.
2.4.3) Bradford protein assay 2 μl of sample and 98 μl of water were mixed with 900 μl of Bradford reagent [0.01% coomassie brilliant blue G-250, 4.7% (v/v) ethanol and 8.5% (v/v) H3PO4]. Absorbencies were read at 595 nM (A595) using a spectrophotometer. The concentration of each sample was calculated by comparison of the A595 readings from a standard curve generated from known concentrations of bovine serum albumin (BSA).
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2.4.4) SDS polyacyrilamide gel electrophoresis (PAGE) Proteins were separated by SDS PAGE. Each gel consisted of a separating gel composed of: 380 mM Tris-HCl pH 8.8, 0.1% (w/v) SDS, 10% (w/v) acrylamide and a stacking gel, composed of: 125 mM Tris-HCl pH 6.8, 0.1% (w/v) SDS, 5% (w/v) acrylamide. Up to 100 μg of protein was loaded in to each lane alongside 10-30 μl of see blue markers depending on the size of the gel. Big gels were electrophoresed using 45 mA and mini gels were electrophoresed using 20 mA in tris glycine running buffer [25 mM Tris-base, 192 mM glycine, 0.1% (w/v) SDS].
2.4.5) Transfer of protein onto polyvinylidene difluoride (PVDF) or nitrocellulose membranes Following electrophoresis, the gel (minus the stacking gel) and 6 pieces of 3 mm Whatman paper were soaked for 10 minutes in transfer buffer [25 mM Tris-base, 192 mM glycine, 20% (v/v) methanol]. PVDF membrane was hydrated in methanol for 1 minute and then soaked in transfer buffer for 5 minutes. Nitrocellulose membrane was hydrated in distilled water for 1 minute and then soaked in transfer buffer for 5 minutes. The gel and the PVDF/nitrocellulose membrane were sandwiched between 3 pieces of 3 mm paper. Proteins were transferred by electrophoresis onto the membrane using 100 V for 1 hour at 4 oC or 10 volts overnight.
2.4.6) Western blotting All procedures, apart from the final step were carried out on the tilting platform. The membrane was blocked for 2 hours in blocking buffer [5% milk, 1x PBS/0.1% (v/v) tween], for 2 hours at room temperature. Some of the antibodies used were not compatible with milk or tween (refer to the table in section 2.1.2 for details). In the case of phospho- specific antibodies BSA was substituted for milk in the blocking buffer. The membrane was then incubated in the appropriate dilution of primary antibody (refer to table in section 2.1.2 for dilutions) either for 2 hours at room temperature or overnight at 4oC. The membrane was then washed 3 times for 10 minutes with 1x PBS/0.1% (v/v) tween (tween was only used if it was contained in the blocking buffer). The membrane was then incubated for 1 hour at room temperature with the appropriate IgG/horseradish peroxidase
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(HRP) conjugated secondary antibody, diluted 1:2000 in blocking buffer. The membrane was washed 3 times with 1x PBS/0.1% (v/v) tween for 10 minutes. The antigen was detected using enhance chemiluminescence (ECL) detection reagents according to the manufacturer’s instructions.
If stripping of the membrane was required, it was incubated on the tilting platform in 1x Re-Blot Plus strong Solution from Chemicon for 20 minutes at room temperature. The membrane was then washed in 1x PBS and re-incubated in primary antibody.
2.4.7) IL-6 and IL-8 human ELISAs Media from the treated cells was collected on ice and stored at -20 oC until use. ELISAs were carried out according to manufacture’s instructions. Briefly, between each step with antibody or sample the plates were washed 3 times with 100 μl 1x PBS/0.05% tween. Each incubation was carried out on the tilting shaker at room temperature unless otherwise stated. Plates were coated with 2 μg/ml purified rat anti-human IL-6/IL-8 antibody in 1x PBS at 4oC, 24 hours prior to loading. Non-specific binding sites were blocked with 100 μl blocking buffer [1x PBS (v/v) 2% BSA] for 2 hours. 1:5, 1:10 and 1:20 dilutions of each sample were prepared using fresh serum free media (SFM) without FCS as a diluent. A standard curve was also prepared by 7 sequential 1:3 dilutions of recombinant human 10 μg/ml IL-6/IL8 (for IL-6 standards ranged from 10 ng/ml-0.01 pg/ml and for IL-8 standards ranged from 30 ng/ml-0.04 pg/ml), again SFM media without FCS was used as a diluent. 100 μl of each sample was loaded in triplicate and 100 μl of each standard was loaded in duplicate and plates were incubated for 2 hours. 100 μl biotinylated rat anti-human IL-6/IL- 8 for 1 hour was added to detect IL-6 or IL-8 bound to the plate. For quantitation, 100 μl of streptavidin conjugated HRP was added followed by the addition of 100 μl of 1:1 tetramethylbenzidine (TMB) peroxidase and peroxidase substrate solution B. The reaction was allowed to proceed until the colour in the 4th standard developed, when 100 μl 1 M
H2SO4 was added to terminate the reaction. Absorbance was measured at 450 nm (A450). Individual sample IL-6/IL-8 protein concentrations were calculated by comparison with the standards.
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2.4.8) IL-6 and KC mouse ELISAs Media from the treated cells was collected on ice and stored at -20 oC until use. ELISAs were carried out according to manufacture’s instructions. Briefly, between each step with antibody or sample the plates were washed 3 times with 100 μl 1x PBS/0.05% tween. Each incubation was carried out on the tilting shaker at room temperature unless otherwise stated. Plates were coated in 360 μg of rat anti mouse IL-6/KC antibody overnight at 4oC. The plates were then blocked in blocking buffer [1x PBS 1% (w/v) BSA] for 2 hours. For IL-6 each sample was loaded neat. For KC 1:5, 1:10 and 1:40 dilutions of each sample were prepared using blocking buffer as the reagent diluent. A standard curve was prepared by 7 sequential 1:2 dilutions (again using blocking buffer as the diluent) of recombinant mouse IL-6/KC. For IL-6 the standards ranged from 6000 pg/ml- 93.75 pg/ml and for KC, 3000 pg/ml-46.875 pg/ml. 100 μl of each sample and standard were loaded in triplicate and duplicate respectively. The plates were incubated overnight at 4oC. 100 μl of 36 μg/ml of biotinylated goat anti mouse IL-6/KC was loaded for detection of IL-6/KC bound to the plate. For quantitation, 100 μl of streptavidin conjugated HRP was added followed by the addition of 100 μl of 1:1 tetramethylbenzidine (TMB) peroxidase and peroxidase substrate solution B. The reaction was allowed to proceed until the colour in the 4th standard developed, when 100 μl of 1 M H2SO4 was added to terminate the reaction. Absorbance was measured at 450 nm (A450 nm). Individual sample IL-6/KC protein concentrations were calculated by comparison with the standards.
2.5 Molecular biology
2.5.1 Cloning of BRF1 Human BRF1 was amplified by PCR from PC3-DNA-myc vector. The oligonucleotides used for the PCR were: ACBRF15: 5’ GCG AAT TCG ACC ACC ACC CTC GTC TC ACBRF13: 3’ GCG AAT TCT TAG TCA TCT GAG ATG GA PCR was performed in 50 μl reactions using 50 pmoles of each primer, 0.5 μl template DNA, 250 μM dNTPs, 100 nM Mg, 1X Thermopol Buffer and Vent polymerase. PCR conditions were as follows: 95° for 5 minutes
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30 cycles of: 95°C 30 seconds 55°C 30 seconds 72°C 60 seconds 72°C for 10 minutes
The PCR product was pre-stained with 1X SYBR green and was loaded onto a 1 % TBE agarose gel and electrophoresed at 100 V for 1 hour using 0.5 % TBE as the running buffer. The PCR product was visualised using a dark reader, excised from the gel and purified using Qiagen gel extraction kit as described by the manufacturer. The PCR product was then cloned into the pCR Blunt vector using the Blunt pCR cloning kit as directed by the manufacturer. The construct was transformed into TOP 10 competent cells using heat shock (30 minutes on ice, 45 seconds at 42 °C, 2 minutes on ice). The bacteria were allowed to recover for 1 hour at 37 °C in 250 μl LB without antibiotic. Bacteria were then plated on to LB-agar plates containing 50 ug/ml kanamycin and left to grow overnight at 37 °C. 6 colonies were individually picked and grown, in 5 ml LB containing kanamycin, over night at 37 °C. Plasmid DNA was prepared using plasmid miniprep kit. Recombinant clones were identified by restriction digest and sequencing. A larger amount of DNA was prepared from the clones with the correct sequence using 1000 plasmid kit.
2.5.2) Subcloning of BRF1 into pCMVFLAG vector pCR blunt-BRF1 was digested with EcoR1 the BRF1 fragment purified as previously described. pFLAGCMV-TTP was digested and linearised with EcoR1 the pFLAGCMV fragment was purified as previously described. pFLAGCMV was dephosphorylated using shrimp alkaline phosphatase for 1 hour at 37 °C. The BRF1 was fragment was ligated into the pFLAGCMV vector for 1 hour at 16 °C. 1 μl of the ligation mixture was transformed into TOP 10 competent cells, in the same way as previously. Plasmid DNA was prepared using mini prep kit and restriction digests were performed to identify positive clones and restriction digests were performed to check the orientation of the insert. 1 μg of DNA from three colonies was sequenced by MWG and a single base pair mutation was found in the N terminus. This mutation was from an A → G which in turn alters the amino acid which is coded for by this codon from a histidine to an arginine. In case this mutation was able to
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alter the functioning of BRF1 I used site directed mutagenesis to restore its consensus sequence.
2.5.3) Site directed mutagenesis A Stratagene site directed mutagenesis kit was used to mutate a single point mutation identified in the BRF1 gene.
Primers used: Forward primer: CTG AGG AGC TGG TTC TGG TGG AAC TTG GAG CTG G Reverse primer: CCA GCT CCA AGT TCC ACC AGA ACC AGC TCC TCA G
The procedure was carried out as directed in the manufacturer’s manual.
2.5.4) Small scale preparation of plasmid DNA (Miniprep) DNA mini prep were prepared using the QIAprep® spin miniprep kit from Qiagen. Single colonies were cultured overnight at 37oC and constantly rotated, in 5 ml of LB containing appropriate antibiotic (50 μg/ml kanamycin or 100 μg/ml ampicillin). The bacteria were pelleted from 1.5 ml of each culture by centrifugation at 13000 g for 1 minute. The supernatant was discarded and the bacteria were lysed and DNA purified according to the manufacturer’s instructions. DNA was eluted in 50 μl of Tris EDTA (pH 8.0). DNA absorbencies were measured at 260 nm (A260) to give its concentration and its purity was assessed using A260/A280 ratio.
2.5.5) large scale preparation of plasmid DNA 500 ml of LB were inoculated with bacteria from a glycerol stock. The culture was incubated at 37oC overnight whilst being constantly rotated. The bacteria were pelleted by centrifugation at 6000 g for 15 minutes. The supernatant was discarded and the DNA from the pellet was purified using the UltraMobius 1000 plasmid kit from Novagen. The final DNA pellet was resuspended in up to 500 μl of Tris EDTA (pH 8.0). DNA concentration and purity were measured as described previously for the miniprep.
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2.5.6) RNA extraction Either HeLa, A549 or MEFs were seeded at a density of 4 x 105 cells per well of a 6 well plate. Cells were left to grow overnight and the experiment was performed as indicated. Afterwards, the media was removed and the cells were washed twice with ice cold 1x PBS. RNA was extracted and purified using a QIAamp RNA extraction kit according to the manufacturer’s instructions. RNA was eluted in 50 μl of RNase free H2O and its concentration and purity determined by measuring the absorbance at 260 nm and at 280 nm. RNA was stored at -80 oC. If the samples were intended for qPCR analysis using primers and SYBR green then a 30 minute DNAse step was included to remove genomic DNA contaminants.
2.5.7) Quantitative reverse transcriptase PCR (RT-qPCR) RT-qPCR is a quantitative method for measuring mRNA abundance. There are two main methods that can be used to do this; either by using primers and SYBR green or by using specifically designed Taqman® probes and primers. In this thesis both methods have been used as Taqman® probes are not available for all applications of RT–qPCR, however where they do exist they have been used. The Taqman® system is preferable as it does not allow non-specific amplification or amplification of genomic DNA. This is in contrast to the primer/SYBR green system where several validation and optimisation steps have to be carried out to ensure a trustworthy result. Both methods rely on the measurement of fluorescence to calculate the abundance of a particular template. SYBR green fluoresces when it binds double stranded DNA, and fluorescence is directly proportional to the product abundance. A Taqman® probe consists of a non-extendable oligonucleotide complementary to the target sequence that is labelled with a 5'-reporter dye and a 3' quencher dye. When the probe is intact, the fluorescence emission of the reporter dye is quenched owing to the physical proximity of the reporter and quencher dyes. During PCR, forward and reverse primers hybridise to a specific sequence of the target of DNA and the Taqman® probe hybridises to the target sequence internal to the primer sequences. During the extension phase of PCR, the 5' exonuclease activity of Taq polymerase hydrolyses the Taqman® probe. The reporter dye and quencher dyes are separated upon cleavage resulting in increased fluorescence of the reporter.
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In both cases the number of PCR cycles required for the fluorescence associated with the reaction to be greater than an arbitrary threshold level is designated the cycle threshold (Ct). To control for variation in absolute quantity of cDNA/RNA put into each reaction, results were normalised to the house keeping gene GAPDH. GAPDH is assumed to remain unaffected throughout the experiments shown. Relative abundance of template was calculated using the delta delta (ΔΔ) Ct approach. ΔCt is the difference between the averages of threshold cycles for the reference gene (usually GAPDH) and the target gene.
ΔΔCt determines a relative value (an arbitrary constant) to which other values from a particular group are normalised. To establish the fold difference between samples, the value 2- ΔΔCt was used. This value is the amount of target normalised to an endogenous reference and relative to a control where the 2- ΔΔCt value for control mRNA (which is in most cases unstimulated) equals one.
2.5.7.1) Taqman® All of the RT-qPCR shown is carried out using Taqman® primers and probes, apart from the primary transcript PCR which is detailed later on and the steady state measurements for KC. Taqman® probes were obtained for BRF1, BRF2, TTP, IL-6 and Cox-2. qPCR was carried out using the SuperScript™ ІІІ platinum One-Step Quantitative RT-PCR System from Invitrogen. Each reaction was set up to contain 10 μl in total, each sample was measured in duplicate. 1 μl of RNA, 5 μl 2x buffer, 0.25 μl SuperScript™ ІІІ platinum® taq mix, 3.75 μl RNAse free water. The conditions for the RTqPCR were: 48 °C for 30 minutes (for the RT step), 95 °C 10 minutes, 40 cycles of: 95 °C 15 seconds, 60 °C 1 minute. When the reaction was complete, Ct values were obtained and delta delta Ct analysis was used to calculate the relative fold change in transcript in comparison to a designated control. All measurements were normalised to GAPDH.
2.5.7.2) Primary Transcript PCR
2.5.7.2.1) Reverse transcription Reverse transcription (RT) of RNA complementary to DNA (cDNA) was performed using Promega Reverse Transcription System according to manufacturer’s instructions. Briefly, 1 μg of total RNA was incubated at 70oC for 10 minutes, then placed on ice, nuclease free water was used to adjust the final volume to 10 μl. The RT reaction was then assembled to
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give a final volume of 20 μl; 4 μl dNTPs (10 mM), 2 μl MgCl2 (25 mM), 0.5 μl reverse transcriptase, 1 μl random primers, 0.5 μl RNAsin and 1 μg RNA. For the RT reaction, the following conditions were used: 21 oC 10 minutes, 42 oC 45 minutes, 95 oC 10 minutes, 4 oC until end. cDNA was stored at -20 oC until use.
2.5.7.2.2) Primer design and optimisation Primary transcript RT-qPCR was used a measure of transcription rates. Primers were designed to measure un-spliced (or primary transcript) IL-6, Cox-2, KC and GAPDH RNAs. These primers were designed to flank an intron:exon boundary. Corresponding primers to measure spliced (mature/fully processed mRNA) were also designed. Where possible these primers were designed around the same intron as for the primary transcript primer pair. They were also designed to amplify a region of similar size. The sequences are shown below:
Primer Sequence Optimal primer volume/10 μl reaction (μl) GAPDH steady state forward ggg tgt gaa cca cga gaa at 0.4 GAPDH steady state reverse atc cac agt ctt ctg ggt gg 0.4 GAPDH primary transcript tct gat ctc agc tcc cct gt 0.6 forward GAPDH primary transcript gaa ttt gcc ctc agt gga gt 0.6 reverse IL-6 steady state forward tcc ttc cta ccc caa ttt cc 0.5 IL-6 steady state reverse acc aca gtg agg aat gtc ca 0.5 IL-6 primary transcript caa cga tga tgc act tgc ag 0.5 forward IL-6 primary transcript gcc tga ctg gga ctg tac aa 0.5 reverse Cox-2 steady state forward agg act ctg ctc acg aag g 0.6 Cox-2 steady state reverse tca tac att ccc cac ggt t 0.6 Cox-2 primary transcript agg act ctg ctc acg aag g 0.6 forward Cox-2 primary transcript cct gaa agt ggg ttg cag 0.6 reverse KC steady state forward tgt tgt gcg aaa aga agt gc 0.6
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KC steady state reverse cga gac gag acc agg aga aa 0.6 KC primary transcript gcg agg ctt gcc ttg acc 0.6 forward KC primary transcript acc aca ct ttc cg acc tcc 0.6 reverse
Primer optimisation was carried out according to the manufacturer’s instructions. Briefly, concentrations of each primer ranging from 50 nM – 900 nM were compared in combination with each other in their success at amplifying 1 ng of a cDNA template.
2.5.7.2.3) Reaction composition and conditions Each reaction was set up to a final volume of 10 μl and contained: 5 μl 2x SYBR green PCR master mix from Applied Biosystems, the appropriate volume of each primer and 1 μl of cDNA diluted 1:2 with nuclease free water. Each reaction was made up to a final volume of 10 μl with nuclease free water. The PCR conditions were: 50 oC 2 minutes, 95 oC 10 minutes followed by 40 cycles of: 95 oC 15 minutes and 60 oC 1 hour.
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Chapter 3: Results
Differential expression of members of the Zfp36 family
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3) CHAPTER 3: DIFFERENTIAL EXPRESSION OF MEMBERS OF THE ZFP36 FAMILY
3.1) Characterisation of antibodies and antisera against the Zfp36 family of proteins.
3.1.1) Introduction Of the three members of the Zfp36, family TTP is the most widely studied and best understood. The focus of this work is to understand the function and regulation of the other two members of the family, BRF1 and BRF2. Through external collaborations and within our laboratory we have a number of reagents designed to detect these three proteins. Provided to us by an external collaborator were four rat monoclonal antibodies; SB1/30.13, SB2/31.4, SB2/24.8 and SB1/77.7 raised against recombinant human BRF1 protein. Santa Cruz manufacture three polyclonal antibodies designed to detect TTP. They are: G-20, a goat polyclonal antibody raised against the N-terminus of mouse TTP; N18 which is a goat polyclonal antibody raised against the N-terminus of human TTP; and H120 which is a rabbit polyclonal antibody raised against the C-terminus of human TTP. In this lab two rabbit antisera are in use; SAK20 and SAK21. They are designed to detect the N-terminus and C-terminus of mouse TTP respectively. Recently Cell Signaling Technology have provided a BRF1/2 polyclonal antibody raised in rabbit against the C-terminus of human BRF1.
The specificity and sensitivity of these reagents are somewhat ambiguous. To enable close study of the functions of these proteins it is necessary to understand the detection range of the antibodies available. To do this a strategy was devised based on expression of FLAG tagged versions of the three proteins in HeLa cells. These were then readily detectable using an anti-FLAG antibody. The same set of samples was then subjected to further western blotting with each antibody designed to detect the Zfp36 family members. Afterwards each blot could be compared and relative specificity and sensitivity of each reagent determined. FLAG-TTP and FLAG-BRF2 and a myc tagged version of BRF1 were already in existence. To allow a direct comparison and detection with a single antibody it was appropriate to generate a FLAG-BRF1 construct.
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Figure 3.1: Peptide sequence alignment of human BRF1, human BRF2, human TTP and mouse TTP. The peptide sequences to which SAK20 and SAK21 were raised are indicated by the red boxes.
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3.1.2) Characterisation of antibodies and antisera Having generated the pFLAGCMV-BRF1 construct, various antibodies were tested. Quantities ranging from 0-1000 ng of pFLAGCMV-TTP, pFLAGCMV-BRF1 and pFLAGCMV-BRF2 plasmid DNA were transiently transfected into HeLa cells (only 10- 1000 ng shown in figure 3.2). After 24 hours whole cell lysates were prepared and western blotted with the antibodies indicated (Figure 3.2B-E). Transfection efficiency was assessed using anti-FLAG antibody (figure 3.2A), and a tubulin blot was performed to confirm equal loading (Figure 3.2F). FLAG-TTP and FLAG-BRF2 were expressed at comparable levels, but FLAG-BRF1 was slightly under-expressed in comparison. SB1/30.13, SB2/31.4, SB2/24.8 and SB1/77.7 detected all three of the Zfp36 family members. SB1/30.13 was the most sensitive, having a similar affinity for TTP, BRF1 and BRF2. Interestingly SB1/77.7 had a greater affinity for BRF1 and BRF2 than TTP. Multiple bands were detected for each of the three proteins. In the cases of TTP and BRF1 there were three main bands between the 45 KD and 50 KD markers. In the case of BRF2 there were two main bands that migrated just below the 66 KD marker. These multiple bands are most likely indicative of post-translational modifications such as phosphorylation, which alter protein electrophoretic mobility. TTP is known to be extensively phosphorylated in vivo (Cao et al., 2006), and treatment with phosphatase increases its electrophoretic mobility (Mahtani et al., 2001). Similarly, experiments in our lab have shown that the electrophoretic mobilities of endogenous BRF1 and BRF2 are increased by phosphatase treatment, suggesting that these proteins are also extensively phosphorylated.
As previously, HeLa cells were transiently transfected with quantities ranging from 0-1000 ng of pFLAGCMV-TTP, pFLAGCMV-BRF1 and pFLAGCMV-BRF2 plasmid DNA (only 10-1000 ng shown in figure 3.3A-F). After 24 hours whole cell lysates were prepared and western blotted with anti-TTP G20 (figure 3.3B), anti-TTP N18 (figure 3.3C), anti-TTP H120 (figure 3.3D) and anti BRF1/2 (figure 3.3E). A FLAG blot is also shown to confirm transfection efficiency (figure 3.3A) and a tubulin blot to confirm equal loading of protein (figure 3.3F). All three of the Santa Cruz polyclonal antibodies appeared highly specific for TTP. The pFLAGCMV-TTP construct contains murine TTP. It is probably for this reason that the G20 goat polyclonal antibody seemed the most sensitive, but it was not able to
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detect endogenous TTP in human cell lines (data not shown). The epitope against which G20 was raised may not be conserved between mouse and human. The N18 goat polyclonal antibody was less sensitive than G20 and did not detect endogenous TTP in human cells either (data not shown). H120 had moderate sensitivity, however non-specific bands of similar molecular weight to TTP were consistently detected. This remains the only completely TTP-specific antibody which detects endogenous TTP in human cells (figures 3.5 and 3.6). However, I have found considerable variation between batches of this antibody. Interestingly the Cell Signaling Technology rabbit polyclonal antibody detected BRF1 and not TTP. The epitope detected at ~64 KD is likely to be a non-specific band, deduced by the fact that it was detected in all lanes, and its intensity did not change with increasing expression of FLAG-BRF2. Based on its size this band could be mistaken for BRF2.
Again HeLa cells were transiently transfected with quantities ranging from 0-1000 ng of pFLAGCMV-TTP, pFLAGCMV-BRF1 and pFLAGCMV-BRF2 plasmid DNA (only 10- 1000 ng shown in figure 3.4). After 24 hours whole cell lysates were prepared and western blotted with SAK20 (figure 3.4B) and SAK21 (figure 3.4C). A FLAG blot is also shown (figure 3.4A) and a tubulin blot to show equal loading (figure 3.4D). SAK20 is very TTP specific but its sensitivity is low. We have also found it hard to use in western blotting. SAK21 detected all three of the Zfp36 family members but had a higher affinity for TTP and BRF2 than for BRF1. The region of the polypeptide that SAK 20 is raised against is moderately conserved between the three proteins (figure 3.1).
3.1.3) Summary Having investigated the properties of theses antibodies, the detection range of each is clearer. To summarise, G20 (Santa Cruz), N18 (Santa Cruz), H120 (Santa Cruz) and SAK20 are all TTP specific, however endogenous TTP is close to or below their detection limit. The antibody from Cell Signaling Technology is BRF1 specific and is able to detect endogenous BRF1. SB1/77.7 preferentially detects BRF1 and BRF2 but has low sensitivity. SB1/30.13, SB2/31.4, SB2/24.8 and SAK21 strongly detect all three of the Zfp36 family members. In other words specific antibodies or antisera tend to have low affinity, whereas high affinity antibodies and antisera tend not to be very specific. Presumably the most
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highly conserved regions of the Zfp36 proteins (for example the zinc finger domain) are also the most antigenic. Until recently it has been a significant problem in discriminating between members of the family, in particular TTP and BRF1, which are similar in electrophoretic mobility. A custom made affinity purified polyclonal antiserum against BRF1, predicted to detect only this protein, failed to detect BRF1 at all (data not shown). However the recently acquired BRF1 specific Cell Signaling Technology antibody and the anti-TTP H120 antibody from Santa Cruz have partially alleviated this problem.
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Figure 3.2: Characterisation of rat monoclonal antibodies. HeLa cells transiently transfected with quantities ranging from 0-1000 ng (only 31.6-1000 ng shown for TTP and 10-1000 ng shown for BRF1 and BRF2) of pFLAGCMV-TTP, pFLAGCMV-BRF1 and pFLAGCMV-BRF2 vectors. Whole cell lysates were prepared and protein was separated by SDS PAGE and was then transferred on to PVDF membrane. Western blots representative of three separate experiments with the following antibodies are shown. (A) Anti-FLAG, (B) SB1/30.13, (C) SB2/31.4, (D) SB2/24.8, (E) SB1/77.7 and (F) Anti- tubulin.
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Figure 3.3: Characterisation of commercial antibodies. The experimental procedure was exactly as detailed in legend for figure 3.1. Western blots representative of at least two separate experiments with the following antibodies are shown: (A) Anti-FLAG, (B) Anti- TTP (G20) Santa Cruz, (C) Anti-TTP (N18) Santa Cruz, (D) Anti-TTP (H120) Santa Cruz , (E) Anti-BRF1/BRF2 Cell Signaling Technology (F)Anti-tubulin.
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Figure 3.4: Characterisation of SAK 20 and SAK 21 antibodies. The experimental procedure was exactly as detailed in legend for figure 3.2. Western blots representative of two separate experiments with the following antibodies are shown: (A) Anti-FLAG, (B) SAK 20, (C) SAK 21, (D) Anti-tubulin.
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3.2) Expression of Zfp36 family members– protein and mRNAs
3.2.1) Introduction The pattern of BRF1 and BRF2 protein expression has yet to be fully determined. So far most studies have concentrated on their mRNA levels (Carrick and Blackshear, 2007). TTP protein expression has been much more widely investigated. TTP was first identified in fibroblasts stimulated with insulin (Lai et al., 1990), in Swiss 3T3 cells after phorbol ester treatment (Varnum et al., 1989), and as a serum response gene (DuBois et al., 1990). Since then it has been found to be induced by IL-4 and IL-6 (Suzuki et al., 2003), transforming growth factor β (TGFβ) (Ogawa et al., 2003), TNFα, LPS (Carballo et al., 1998; Mahtani et al., 2001), interferons (Sauer et al., 2006) and recently dexamethasone (Smoak and Cidlowski, 2006). BRF1 and BRF2 have also been found to be induced by PMA and LPS (Carrick et al., 2004). As described in the Introduction, TTP is thought to mediate regulation of mRNA stability by the p38 MAPK pathway. Until recently, members of this lab have failed to detect TTP protein in HeLa cells, although these cells are competent for regulation of mRNA stability by p38 MAPK (Lasa et al., 2000; Ridley et al., 1998). I wanted to investigate the role of BRF1 and BRF2 in the regulation of inflammatory responses, and the possibility that one or both of these proteins might contribute to post- transcriptional regulation by p38 MAPK. The following experiments characterised the expression of BRF1 and BRF2 in a variety of cell types including HeLa, A549 (a pulmonary epithelial cancer cell line), RAW264.7 (a mouse macrophage-like cell line) and primary mouse macrophages. Another group’s observation that TTP is expressed in HeLa cells (Jing et al., 2005) prompted a re-investigation of the expression of TTP protein in these cells.
3.2.2) Expression of Zfp36 family members in HeLa cells
3.2.2.1) Zfp36 protein expression in HeLa cells in response to inflammatory stimuli HeLa cells were stimulated with 20 ng/ml IL-1α for time points ranging between zero and eight hours (Figure 3.5). Whole cell lysates were prepared, electrophoresed by SDS PAGE then the protein was immobilized on PVDF membrane. Membranes were blotted for all three of the Zfp36 family members using SB1/30.13 (figure 3.5A) and for BRF1
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specifically, using the Cell Signaling Technology antibody (figure 3.5B). Finally TTP was detected specifically in the same lysates using the H120 rabbit polyclonal antibody from Santa Cruz (figure 3.5C). In figure 3.5A the bands indicated just above the 52 KD marker represent BRF2, which was expressed in resting HeLa cells and slightly up-regulated upon IL-1α stimulation. The electrophoretic mobility of the protein also changed, with a distinct shift towards a lower mobility form, particularly at the earlier time points.
On the basis of this western blot (Figure 3.5A), BRF1 and TTP proteins could not be distinguished with any confidence. Using a more specific antibody (Figure 3.5B) it could be shown that BRF1 protein was weakly expressed in resting cells, but accumulated upon IL-1α stimulation. Expression peaked at approximately one hour and remained elevated throughout the rest of the time course. At least three distinct bands were detected by this antibody, and a time-dependent change in the distribution of these bands was observed. Particularly at the 0.5 hour time point there was a distinct shift towards the lowest mobility (perhaps most phosphorylated) form of BRF1. TTP was transiently expressed in response to IL-1α, and was clearly present at the one hour time point (Figure 3.5C). A lower mobility form of TTP may also be present just below a non-specific band at the two hour time point. At other time points TTP protein could not be detected. By comparing the band patterns between the SB1/30.13 blot, BRF1/2 blot and the H-120 blot it can be assumed that most of the protein detected by SB1/30.13 is BRF1 rather than TTP. An exception is the weak, high mobility band seen after one hour (Figure 3.5A), which is likely to be TTP.
HeLa cells were stimulated with 100 ng/ml phorbol 12-myrisate-13 acetate (PMA) for time points between zero and eight hours (Figure 3.6). As previously, whole cell lysates were subjected to western blot analysis by SB1/30.13, anti-BRF1/2, and anti-TTP H120. Figure 3.6A shows a group of bands above the 52 KD marker, which are BRF2. Again these were detectable in unstimulated cells and appeared to be induced steadily by PMA. The bands also changed mobility, decreasing in electrophoretic mobility after stimulation, suggesting that the stimulus may cause phosphorylation of BRF2. BRF1 accumulated rapidly after PMA treatment and peaked between two and four hours of stimulation. BRF1 expression was sustained up until eight hours (figure 3.6B). As in the previous experiment, in resting
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cells three bands of very low intensity were detected by the BRF1/2 rabbit polyclonal antibody. PMA treatment caused a more sustained shift towards a lower mobility form than previously observed after IL-1α treatment. TTP protein was detected only at the one and two hour time points after HeLa cell stimulation with IL-1α (Figure 3.6C).
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Figure 3.5: IL-1α induced changes of Zfp36 family members in IL-1α stimulated HeLa cells. Hela cells were stimulated for the indicated times with 20 ng/ml IL-1α, whole cell lysates were prepared and run and protein was separated by SDS PAGE and was then transfered onto PVDF membrane. Western blots repesentaive of at least two separate experiments are shown using the following antibodies (A) SB1/30.13, (B) anti-BRF1, (C) anti-TTP H120 and their corresponding tubulin loading controls.
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Figure 3.6: PMA induced changes of Zfp36 family members in IL-1α stimulated HeLa cells. Hela cells were stimulated for the indicated times with 100 ng/ml PMA, whole cell lysates were prepared and run, protein was separated by SDS PAGE and was then transfered onto PVDF membrane. Western blots representative of at least two separate experiments are shown using the following antibodies (A) SB1/30.13, (B) Anti-BRF1, (C) Anti-TTP H120 and their corresponding tubulin loading controls.
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3.2.2.2) Expression of Zfp36 mRNAs in HeLa cells treated with inflammatory stimuli The expression of TTP, BRF1 and BRF2 mRNAs was measured in HeLa cells using quantitative PCR (qPCR). HeLa cells were stimulated with 100 ng/ml PMA or 20 ng/ml IL- 1α for times ranging between zero hours and eight hours. RNA was prepared from HeLa cells using a Qiagen kit (see materials and methods section for details). Each measurement was normalised to GAPDH expression, and then analysed using delta delta Ct analysis to give a fold increase in comparison to unstimulated cells. Figure 3.7A follows TTP, BRF1 and BRF2 mRNA fluctuations up to two hours. There was a peak of TTP mRNA after 30 minutes to one hour of stimulation with IL-1α (8 fold increase) and PMA (6 fold increase). BRF1 and BRF2 mRNA levels remained relatively constant throughout. Figure 3.7B shows mRNA fluctuations over eight hours. Again there was a peak of TTP mRNA at one hour of IL-1α stimulation (approximately 15 fold increase) and with one hour of stimulation with PMA (13 fold increase). Again there was little change in the BRF1 and BRF2 mRNA levels over the time course.
Although TTP is the most affected mRNA of the Zfp36 family by inflammatory stimuli its abundance is actually much lower than that of BRF1 and BRF2. Figure 3.8A illustrates this point. It shows the amplification curves for each of the three mRNAs in unstimulated HeLa cells and IL-1α stimulated cells. The most abundant mRNAs are amplified above the arbitrary threshold in fewer PCR cycles than those of low abundance. The point at which they cross the threshold is the Ct value. Therefore a lower Ct value corresponds to an mRNA of greater abundance. The lines which represent BRF2 clearly cross the threshold before those for BRF1 and TTP. As well as this there is little difference in the Ct values for
BRF2 in unstimulated and stimulated cells. However when the Ct values for TTP between unstimulated and stimulated cells are compared, there is far greater difference.
The pie chart in figure 3.8B shows the proportions of Zfp36 mRNAs in unstimulated HeLa cells. This purely an estimation and relies on the assumption that the efficiencies of the PCR reactions are the same. Again it shows that BRF2 is the most abundant mRNA in HeLa cells, accounting for approximately 90% of the total Zfp36 content. Most of the
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remaining 10% is accounted for by BRF1, but a small fraction is TTP. This is not surprising as earlier data in the chapter demonstrates the low but inducible levels of TTP protein in HeLa cells. The assumption that the efficiencies of the PCR reactions are similar seems to be reasonable on the grounds that the primers have been carefully optimised by Applied Biosystems, and curves are very similar in shape. To validate the conclusion would require careful measurement of mRNA quantities by construction of standard curves. This has not yet been done.
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A
9 TTP 8 BRF1 7 BRF2
6 5 4 3 2 1
TTP,BRF1,BRF2 mRNA/GAPDH 0 0 0.25 0.5 1 2 0.25 0.5 1 2 IL-1 (hours) PMA (hours)
B
17.5 TTP 15.0 BRF1 12.5 BRF2 10.0 7.5 5.0 2.5
0.0 0 1 2 4 8 1 2 4 8 TTP, BRF1, BRF2 mRNA/GAPDHTTP, BRF1, BRF2 IL-1 (hours) PMA (hours)
Figure 3.7: IL-1α and PMA induced chages in expression of TTP, BRF1 and BRF2 mRNA in HeLa cells. HeLa cells were stimulated with either 20 ng/ml IL-1α or with 100 ng/ml PMA for the indicated times, RNA was isolated and qPCR performed using taqman® probes to TTP, BRF1 and BRF2. Results shown are the average of two experiments where each point was measured in triplicate. Delta delta Ct analysis was used to calculate the fold change in TTP, BRF1 and BRF2 mRNA in relation to an unstimulated control. All data are normalised to GAPDH. Error bars represent the standard error of the mean. (A) 0–2 hour time course, (B) 0–8 hour time course.
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Figure 3.8: Relative abundances of Zfp36 mRNAs. (A) The plot above is taken directly from the PCR machine read out. The data are plotted on a log scale. HeLa cells were stimulated with either 20 ng/ml IL-1α for one hour or left unstimulated. RNA was isolated and qPCR performed using taqman® probes to TTP, BRF1 and BRF2. The software measures the cycle number at which the fluorescence crosses the arbitrary line, the threshold, shown in red. This crossing point is the Ct value. More abundant samples will cross this line sooner than those with less of the target gene. (B) A pie chart to represent the estimated relative abundances of Zfp36 proteins in unstimulated HeLa cells. This chart was made based on the assumption that the efficiencies of the qPCRs were the same.
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3.2.2.3) Effects of dexamethasone on the expression of Zfp36 proteins In a previous micro-array experiment in our lab TTP mRNA was up-regulated 4.34 and 4.88-fold by 100 nM or 1 μM dexamethasone treatment of HeLa cells for two hours. BRF2 mRNA was up-regulated 1.82 or 1.71 fold under the same conditions, whereas BRF1 mRNA did not change (Lasa et al., 2002). These findings have not yet been confirmed. Recently Smoak et al. reported that dexamethasone exerts anti-inflammatory effects by inducing expression of TTP in A549 cells, a human alveolar basal epithelial cell line (Smoak and Cidlowski, 2006). I therefore investigated the regulation of expression of Zfp36 family members by dexamethasone in HeLa cells.
HeLa cells were treated with 100 nM dexamethasone, 20 ng/ml IL-1α or a combination of the two. Whole cell lysates were prepared and western blotted using SB1/30.13 (detects all Zfp36 members), as shown in figure 3.9. Figure 3.9A reiterates previous observations that IL-1α induced changes in the expression and mobility of BRF1 and BRF2. A high mobility band detected at one and two hour time points was tentatively identified as TTP. Dexamethasone alone had no effect on the expression or mobility of members of the Zfp36 family (figure 3.9B). When IL-1α and dexamethasone were added in combination, the pattern of TTP, BRF1 or BRF2 expression was very similar to that observed with IL-1α alone (figure 3.9C).
Attempts were made to blot for TTP alone using the H120 antibody from Santa Cruz. This antibody readily detected TTP in positive control lysates (from LPS-stimulated RAW264.7 cells), but detected no antigen in lysates of HeLa cells treated with IL-1α, dexamethasone or both (data not shown).
3.2.2.4) Effects of dexamethasone on expression of Zfp36 mRNAs HeLa cells were stimulated with 100 nM dexamethasone for times ranging between zero and eight hours. RNA was prepared using a Qiagen kit and expression of TTP, BRF1 and BRF2 mRNAs were measured by qPCR. Each measurement was normalised to GAPDH expression, and then analysed using delta delta Ct analysis to give a fold increase in comparison to unstimulated cells. A slight increase in TTP mRNA was detected after dexamethasone treatment (figure 3.10), peaking at six hours (3.5 fold). This then dropped
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back to basal levels by eight hours. BRF1 and BRF2 mRNAs followed a similar pattern to TTP but the levels of induction were much lower. Based on the assumption that the Taqman® probes detect all three mRNAs with similar efficiency, basal expression of the Zfp36 family was very similar to that shown in figure 3.8B. In other words BRF2 mRNA was significantly more abundant than BRF1 and TTP mRNA. TTP mRNA was extremely low in abundance.
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Figure 3.9: Dexamethsone induced changes of Zfp36 protein expression in HeLa cells. Hela cells were stimulated for the indicated times with: (A) 20 ng/ml IL-1α, (B) 100 nM dexamethasone, (C) 20 ng/ml IL-1α and 100 nM dexamethasone. Whole cell lysates were prepared protein was separated by SDS PAGE then transfered onto PVDF membrane. Western blots with SB1/30.13 are shown and are reprentative of two separate experiments. Their corresponding tubulin loading controls are also shown.
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4.5 4.0 3.5 TTP BRF1 3.0 BRF2 2.5 2.0 1.5 1.0 0.5 0.0
TTP, BRF1, mRNA/ BRF2 GAPDH 0.0 0.5 1.0 2.0 4.0 6.0 8.0 Dexamethasone (hours)
Figure 3.10: Dexamethasone induced changes of Zfp36 mRNA expression in HeLa cells. HeLa cells were stimulated with 100 nM dexamethasone for the indicated times, RNA was isolated and qPCR performed using taqman® probes to TTP, BRF1 and BRF2. Results shown are the average of two experiments where each point was measured in triplicate. Delta delta Ct analysis was used was used to calculate the fold change in TTP, BRF1 and BRF2 mRNA in relation to an unstimulated control. All data are normalised to GAPDH. Error bars represent the standard error of the mean.
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3.2.3) Expression of Zfp36 family members in A549 cells
3.2.3.1) Zfp36 protein expression in A549 cells To extend these observations the effects of dexamethasone on the expression of Zfp36 proteins and mRNAs in A549 cells were investigated (figure 3.11). A549 cells were subjected to treatment with 20 ng/ml IL-1α, 100 nM dexamethasone or a combination of the two for time points ranging over ten hours. Whole cell lysates were prepared and analysed by western blot for all three of the TTP family members using the rat monoclonal antibody SB1/30.13 (figure 3.11A). IL-1α treatment did not induce BRF2 above basal levels but it did induce bands below 50 KD corresponding to BRF1 and or TTP. The two bands of approximately 50 KD probably correspond to BRF1 (on the basis of comparison with HeLa cells). These bands peaked in intensity at four hours but remained detectable up to ten hours. A higher mobility band was detected only at one, two and four hour time points. This band was tentatively identified as TTP, however this could not be confirmed because H120 and SAK20 detected no antigens in these lysates (data not shown). Dexamethasone had no detectable impact on the pattern of expression of Zfp36 proteins, either on its own (Figure 3.11B) or in combination with IL-1α (Figure 3.11C).
3.2.3.2) Zfp36 mRNA expression in A549 cells Similarly TTP mRNA expression was measured in A549 cells treated with IL-1α, dexamethasone or a combination of the two (figure 3.12A). Dexamethasone alone induced TTP mRNA only very weakly (approximately 2-3 fold). IL-1α treatment induced a very transient increase of TTP mRNA, peaking at almost 10-fold at the one hour time point. IL- 1α and dexamethasone additively regulated TTP mRNA expression, resulting in a pattern of expression that combined an early transient peak with a long sustained phase. This is similar to findings by Smoak et al. who showed additive regulation of TTP mRNA by dexamethasone and TNFα in the same cells. By contrast BRF1 mRNA was unaffected by IL-1α or dexamethasone treatment or by the two used in combination (figure 3.12B)
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Figure 3.11: IL-1α and dexamethasone induced changes of Zfp36 protein expression in A549 cells. A549 cells were stimulated for the indicated times with (A) 20 ng/ml IL-1α, (B) dexamethasone or (C) 20 ng/ml IL-1α and 100 nM dexamethasone. whole cell lysates were prepared and protein was separated by SDS PAGE and was then transferred on to PVDF membrane. Western blots representative of two separate experiments are shown using SB1/30.13 and their corresponding tubulin loading controls.
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A 17 16 15 IL-1 14 13 dexamethasone 12 IL-1+ dexamethasone 11 10 9 8 7 6 5
TTP mRNA/ GAPDH 4 3 2 1 0 0 1 2 3 4 5 6 7 8 9 time (hours)
B
15.0 IL-1 12.5 dexamethasone IL-1+dexamethasone 10.0
7.5
5.0 BRF1/mRNA GAPDH 2.5 0.0 0 1 2 3 4 5 6 7 8 9 time (hours)
Figure 3.12: IL-1α and dexamethasone induced changes of Zfp36 mRNA expression in A549 cells. A549 cells were stimulated with either 20 ng/ml IL-1α, 100 nM dexamethasone or a combination of the two over a period of ten hours. RNA was isolated at the indicated time points and qPCR using taqman® probes to TTP and GAPDH was performed. Each point was measured in triplicate and delta delta Ct analysis was used, all results are normalised to GAPDH. (A) TTP mRNA (N=3), (B) BRF1 mRNA (N=2)
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3.2.4) Expression of Zfp36 family in RAW264.7 cells RAW264.7 cells were stimulated with 10 ng/ml LPS, 100 nM dexamethasone or both (figure 3.13). Whole cell lysates were prepared and analysed for Zfp36 proteins by western blot. Lysates were either blotted for all three of the family members simultaneously (using SB1/30.13) or for BRF1 specifically (using anti-BRF1/2 from Cell Signaling Technology). BRF2 was detected in unstimulated cells and was slightly up-regulated by LPS, dexamethasone and the combined treatment (figure 3.13A). LPS also seemed to alter its mobility, again indicating the possible phosphorylation of BRF2.
A BRF1-specific antibody detected only a very faint single band of near 50 KD in lysates from LPS-treated RAW264.7 cells (figure 3.13B). Therefore it can be assumed that the lower bands indicated in figure 3.13A are mainly TTP. The time-dependent change in mobility of TTP was highly similar to that previously described and shown to be caused by phosphorylation (Mahtani et al., 2001). Dexamethasone alone did not induce detectable expression of BRF1 or TTP. If anything it slightly decreased the expression of TTP in RAW264.7 cells stimulated with LPS.
3.2.5) Expression of Zfp36 family in primary macrophages Primary bone marrow macrophages were isolated and cultured from C57 black 6 mice (see materials and methods for details). Macrophages were treated with 10 ng/ml LPS or 100 nM dexamethasone or a combination of the two for up to four hours. Whole cell lysates were prepared and subjected to western blotting using either SB1/30.13 (detects all three of the TTP family members) or anti-BRF1/2 (detects BRF1 only).
Figure 3.14A shows a faint band appearing at around the 64 KD marker which is assumed to be BRF2. It is undetectable in the untreated control cells, and seems to be most abundant where a combined LPS and dexamethasone treatment had been applied, although, when the tubulin blot is considered it could be attributable to differential loading. The lower bands on this blot are probably a combination of BRF1 and TTP. Again neither is detectable in the unstimulated cells but a sustained induction is observed following LPS treatment after one hour. BRF1 is definitely present in these cells (figure 3.14B). It appears to be induced by
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the LPS and dexamethasone combination. It is possible that it is induced by LPS alone, and that it is undetectable due to the under loading of the gel.
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Figure 3.13: LPS and dexamethasone induced changes of Zfp36 protein expression in RAW264.7 cells. RAW264.7 cells were stimulated for theindicated times with 10 ng/ml LPS, 100 nM dexamethasone or with a combination of both, whole cell lysates were prepared and run and protein was separated by SDS PAGE and was then transfered onto PVDF membrane. Western blots representative of two separate experiments are shown using the following antibodies: (A) SB1/30.13, (B) Anti-BRF1 and their corresponding tubulin blots.
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Figure 3.14: LPS and dexamethasone induced changes of Zfp36 protein expression in primary mouse macrophages. Primary macrophages were stimulated for indicated times with 10 ng/ml LPS or 100 nM dexamethasone or a combination of the two. Whole cell lysates were prepared and protein was separated by SDS PAGE and was then transferred on to PVDF membrane. Western blots using the following antibodies are shown: (A) SB1/30.13, (B) Anti-BRF1/2. Their corresponding tublin blots are shown below. This experiment was only performed once.
Preparation of the macrophages was carried out by Roberta Perelli.
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3.3) Summary and discussion
In this chapter the various reagents designed to detect the Zfp36 family of proteins have been characterised. These have subsequently been used to investigate the patterns of expression of their targets. In addition to this the mRNAs of these proteins were also assessed. This was carried out in a variety of cell types.
A good understanding of the detection ranges of the various antibodies and antisera designed to detect Zfp36 proteins along with a couple of specific reagents provided more recently by commercial companies has made working with this group of proteins slightly easier. However the overall remaining issue is that sensitive antibodies are non-specific and specific antibodies are not very sensitive. BRF2 can be readily detected because it is clearly definable from the other two Zfp36 proteins by its size. The use of a BRF1 specific antibody (from Cell Signaling Technology) has allowed the detection of endogenous levels of this protein. The detection of TTP is still very problematic. The H120 polyclonal antibody from Santa Cruz was able to detect endogenous TTP in HeLa cells, however this was not always reproducible. Unfortunately batch to batch variation of H120 quality meant that the antibody was not always reliable when used for western blotting. Even when attempts were made to enrich TTP concentration by immunoprecipitation, H120 still failed to detect it (data not shown). Immunoprecipitation with most of the antibodies was attempted by myself and other group members. The main problem encountered was that either the antibody did not work for this application or large amounts of material were required to successfully pull down these proteins. Although western blotting and immunoprecipitation were extensively attempted other applications such as immunohistochemistry were not. The fact that these antibodies were difficult to use in the above mentioned applications suggests that successful and reliable immunohistochemistry would also have been difficult to perform.
The majority of the protein detected by the SB1/30.13 antibody that co-migrates with the 38 KD marker was historically assumed to be BRF1. A faster migrating band which was some way below the 38 KD marker was detected by the SB1/30.13 antibody in HeLa and A549 cells after one hour of IL-1α stimulation. The fact that a similar sized epitope is
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detected by the H120 antibody strengthens the case for the epitope detected by SB1/30.13 being TTP. When the auto-radiographs of these blots using the two different detection reagents were compared it seems that this band could plausibly be TTP. If this is so then an estimation as to the relative quantities of the Zfp36 proteins in these cells can be made. In HeLa cells BRF2 is the most abundant in resting cells and accumulates upon addition of IL- 1α. BRF1 is also detectable in resting cells and accumulates with IL-1α treatment. At the peak of BRF1/BRF2 expression there is probably more BRF1 protein. TTP on the other hand is undetectable in unstimulated cells and is up-regulated in response to IL-1α. At the peak of expression, TTP is probably the least abundant and the most transiently expressed cells of the Zpf36 proteins in these cells.
As well as being able to make predictions about Zfp36 relative protein abundance, estimates can be made about their mRNAs. The pie chart in figure 3.8B represents the relative amounts of each of the three Zfp36 mRNAs in unstimulated cells. According to this BRF2 is the most abundant followed by BRF1 and then TTP which is virtually non-existent in comparison to the other two. These calculations were made assuming that the efficiencies of the PCRs were the same for all three genes. Figure 3.8A, which shows the amplification plots of each gene from the PCR machine readout consolidates this point. BRF2 message expression in cells either left unstimulated or stimulated for one hour with IL-1α was amplified above the threshold after approximately 18 cycles. The lack of a difference in Ct value reflects the minor fold change in this mRNA in response to an inflammatory stimulus. This reflects the BRF2 protein observations which do not change much in response to IL-1α stimulation. Unstimulated BRF1 was amplified after approximately 23 cycles and after one hour of IL-1α stimulation it was detected after 22 cycles. TTP on the other hand was not amplified above the threshold until after 27 cycles in resting cells but in stimulated cells its abundance had dramatically increased and it was amplified above the threshold after 23 cycles.
There are clear differences in the regulation of Zfp36 gene expression as demonstrated by the variation in the expression of their transcripts . TTP and BRF1 have been shown to be phosphorylated (Cao et al., 2006; Schmidlin et al., 2004) and most probably BRF2 is as
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well. Their protein expression have all been shown to be in part dependent on p38 activity (shown in chapters 4 and 5 for BRF1 and BRF2) suggesting that this type of post- translational modification has a part in the regulation of their expression as well as other possible mechanisms.
As explained in the introduction, TTP was previously undetectable in HeLa cells. The basis for this project was formed around this observation. HeLa cells were shown to display p38 mediated stabilisation of mRNAs encoding inflammatory cytokines and mediators (Lasa et al., 2000). The absence of TTP meant that in this case p38 was not mediating mRNA regulation through this particular AUBP. BRF1 and BRF2 were obvious alternative candidates for this due to their mechanistic similarities to TTP and because they are expressed in these cells. The presence of TTP in HeLa cells re-ignites the debate as to whether after all it is in fact the AUBP responsible for p38 mediated stabilisation of pro- inflammatory cytokines. In support of this, recent data from our lab shows that a p38 inhibitor failed to destabilise IL-10, TNFα, COX-2, IL-1α and IL-6 mRNAs in mouse TTP- /- macrophages. This suggests that, at least in those cells, p38 exerts its stabilising effect by inactivating TTP (C. Tudor unpublished observations). These data along with the fact that TTP protein is detectable in HeLa cells provides the basis for a re-investigation of the involvement of the Zfp36 family of proteins in mRNA turnover in HeLa cells. One method could involve RNAi as used for BRF1 and BRF2 (chapter 4). Unfortunately the technical problems outlined above would probably hinder this process. It is possible that there is some functional redundancy between these proteins and that when one of the three proteins is depleted the other two can compensate for this. If this was true then RNAi to knockdown the expression of all three of the Zfp36 proteins expression would be necessary. Again this would be likely to encounter technical problems which will be discussed in greater detail in the next chapter.
Another possible interpretation of the data that could explain the role of these three proteins may lie within their differential kinetics. TTP is the most transiently expressed within HeLa cells. It accumulates from undetectable levels, peaking after one hour and then rapidly disappears. It would therefore be difficult for TTP to be responsible for the stabilisation of
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pro-inflammatory mRNAs prior to its accumulation or at time points beyond two hours. For example Cox-2 mRNA was shown to be destabilised in cells where the p38 pathway was blocked following stimulation for two hours with IL-1α in HeLa cells (Ridley et al., 1998). It would be interesting to re-examine the effects of p38 inhibition on COX-2 mRNA stability at later time points such as four or eight hours, when TTP is apparently no longer present. If a similar destabilising effect was observed, this might suggest that different members of the Zfp36 family are involved in the control of mRNA stability at different stages of the response to an inflammatory stimulus.
As well as BRF1 and BRF2 there are other AUBPs which could fulfill the role of post- transcriptional cytokine regulation. Recently published micro-array data from IL-1α stimulated HeLa cells showed that KSRP was involved with the regulation of several inflammatory cytokine mRNAs including IL-8, IL-6 and GM-CSF. Destabilisation of IL-8 mRNA by KSRP was shown to be inhibited by p38 MAPK (Winzen et al., 2007). TTP has also been shown to destabilise IL-8 mRNA in HeLa cells in a p38-sensitive manner. In another study TTP, HuR and KSRP were shown to interact to control the expression of iNOS (Linker et al., 2005). These examples demonstrate that more than one AUBP can control a single transcript which adds to the complexity of the way in which these proteins regulate gene expression. Taking these points into consideration it now seems that our original hypothesis may not be wrong but the idea that p38 targets one AUBP which in turn affects mRNA stability is simplistic. In actual fact there are probably many more factors involved in post-transcriptional gene regulation in HeLa cells.
BRF1 mRNA was only slightly affected by PMA or IL-1α stimulation in HeLa cells which was also true in A549 cells. Its protein on the other hand, was subject to sharp inductions, estimated at up to five times above basal levels, in response to these stimuli. BRF2 mRNA was slightly increased by PMA in HeLa cells, again like BRF1 its protein was much more dramatically affected. The response to IL-1α by BRF2 mRNA and protein was less dramatic. These observations are in agreement with data published by Carrick et al. who show BRF1 and BRF2 mRNAs are expressed constitutively at high levels and are much less inducible than TTP, which by contrast is extremely scarce in unstimulated cells
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(Carrick and Blackshear, 2007). This discrepancy in the inducibilities of the mRNA and proteins of BRF1 and BRF2 suggests that their expression is regulated at the level of either translation or protein stability.
As well as showing an accumulation of the Zfp36 members to certain stimuli in a range of cells, some of the bands identified as BRF1 and BRF2 from HeLa cell extracts on SDS PAGE gels have different mobilities, the suspicion is that some of these are phosphorylated forms of BRF1 and BRF2 (figures 3.5 and 3.6). The pattern of bands observed differed between stimuli. IL-1α seems to induce three main bands believed to be BRF1. Presumably the upper band is the most heavily phosphorylated whilst the lower ones are probably phosphorylated but not to the same degree. Two bands are induced by IL-1α which are thought to be BRF2, again the explanation is that these are differentially phosphorylated forms of the protein. PMA on the other hand induced only a single band suspected to be BRF1, but at least two for BRF2, suggesting that this stimulus does not activate the same signalling pathways as IL-1α.
Further evidence in support of the idea that translational mechanisms are at least in some part responsible for BRF1 gene expression is shown by Benjamin et al. The stability of BRF1 protein was shown to be dependent on the integrity of phosphorylation sites serine 92 and serine 203 which are the phosphorylated by PKB. In PBK null cells BRF1 protein was shown to rapidly degraded (Benjamin et al., 2006). TTP protein expression is also dependent on p38 activity (Brook et al., 2006; Hitti et al., 2006). Brook et al. showed that inhibition of p38 caused dephosphorylation of TTP resulting in its relocalisation to the nucleus followed by proteosomal degradation. Regulation of localisation and protein stability were both shown to be MK2 dependent (Brook et al., 2006). In addition, Hitti et al. also showed that phosphorylation of TTP by MK2 increased TTP protein stability whilst inhibiting its destabilising activity. The result of this mechanism is the maintenance of TTP levels within the cell (Hitti et al., 2006).
As well as being important in the stability and therefore the expression of these genes, phosphorylation has been shown to be important in the sub-cellular localisation of Zfp36
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proteins. In addition to the study of their expression in various tissues, some work has been carried out to look at Zfp36 protein sub-cellular localisation. All three of the Zfp36 proteins possess a leucine rich nuclear export sequence which is responsible for their ability to shuttle between the nucleus and cytoplasm. TTP was shown to be sequestered in the cytoplasm when the p38 pathway is active. Inhibition of p38 caused translocation of TTP to the nucleus and its degradation by the proteasome (Brook et al., 2006). BRF1 localisation has also been shown to be regulated by phoshorylation (Benjamin et al., 2006). Stress granules (SGs) are cytoplasmic foci that sequester mRNAs encoding housekeeping proteins in times of stress. Processing bodies (PBs) are sites of mRNA degradation, BRF1 and TTP have been associated with these structures which is probably, in part, regulated by phosphorylation. Although work in this chapter has not directly addressed sub-cellular localisation and phosphorylation of these proteins it is something that is touched upon in later chapters. For example, in chapters 4 and 5 the expression of BRF1 and BRF2 are shown to be p38 dependent and in chapter 5the cellular location of the Zfp36 proteins is investigated.
Apart from phosphorylation, transcription factors and the structure of the 3’UTR most probably affect expression of the Zfp36 family of genes. Gene expression is most commonly regulated by the interaction of transcription factors with enhancer sequences located in the 5’ flanking region of the gene. These sequences are normally located within a few hundred base pairs of the transcription start site. Constitutive BRF1 gene expression has been shown in rat cells to be a result of a 14 base pair promoter region upstream of the transcription start site (Corps et al., 1995). Little is known about the BRF2 promoter but as its mRNA displays similar kinetics to BRF1 and is therefore likely to have similarities within its promoter.
So far there has been little characterisation of the TTP promoter region. What is known is that its promoter includes a consensus sequences for the binding of the transcription factors; early growth response (EGR)-1, activating protein (AP)-2, Sp1 and TTP promoter element 1 (TEP1) (Lai et al., 1995). These binding elements contribute to the serum inducibility of TTP. TTP has also been suggested to be a target of NFκB in a micro-array experiment
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(Carayol et al., 2006). The presence of AUUUA motifs could account for destabilisation of TTP mRNA after one hour of inflammatory stimulus. Murine TTP contains three distinct AUUUA motifs in its 3’UTR which are located in a ~75% AU rich region, designating it a class І ARE. As well as being regulated by MK2 through the p38 pathway, TTP has been shown to negatively regulate itself through its own 3’UTR forming a feedback loop to limit its own expression (Brooks et al., 2004; Tchen et al., 2004).
AREs in the 3’UTRs of certain pro-inflammatory mRNAs have been shown to confer a transcript to p38 mediated stabilisation. BRF1 and BRF2 are likely to be phosphorylated and this is likely to be by p38, as well as PKB in the case of BRF1. Their expressions are at least in some part dependent on p38 activity (observation from chapters 4 and 5). With this in mind one might hypothesize that this regulation is also the result of an ARE present in the 3’UTR of these genes. A quick investigation of their 3’UTRs showed that BRF1 contains a single AUUUA motif and BRF2 has three. Classically, other p38 stabilised mRNAs, such as Cox-2, TNFα, IL-6 and IL-8, differ in that they have multiple copies of the AUUUA pentamer which sometimes overlap (in other words they have class ІІ AREs). However more recently several more p38 targets have been described as a result of micro- array analysis, some which contain as little as one AUUUA but it is unknown as to whether the p38 responsiveness is 3’UTR dependent or not (Frevel et al., 2003).
The pattern of TTP protein expression observed in HeLa cells in response to PMA and IL-1α is very transient which is in contrast to its expression in RAW264.7 cells in response to LPS. Myself and others from this lab have shown that TTP accumulates in RAW264.7 cells after LPS treatment peaking after one hour. Levels of TTP then remain elevated over a four hour time course but the band pattern changes. The mobility of the bands decrease, something which has been attributed to a change in the phosphorylation status of the protein. TTP mRNA expression in RAW264.7cells is biphasic. The first wave of induction is attributed to the LPS stimulus. Following this TTP can negatively auto-regulate causing a drop in mRNA expression. Sauer et al. show that STAT1, which is an interferon activated transcription factor, is required for full expression of TTP. STAT1 is activated in macrophages by LPS. LPS stimulates both INF and MAPK p38 signalling pathways which
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are both required for STAT1 to become transcriptionally active on the TTP promoter (Sauer et al., 2006). STAT1 could therefore be responsible for the second wave on TTP induction in RAW264.7cells. As previously mentioned, TTP can negatively auto-regulate its own mRNA in macrophages. This could also be happening in the HeLa cells but the ability to activate STAT1 may be lacking.
Glucocorticoids are involved in several functions such glucose metabolism, cell differentiation, growth control, apoptosis and inflammatory response control (Gottlicher et al., 1998). It is their ability to inhibit pro-inflammatory gene expression which has allowed them to be exploited as therapeutics (Clark, 2007; Newton and Holden, 2007). Glucocorticoids exert their function through the up-regulation of anti-inflammatory regulators such as IL-10, IL-1R antagonist and DUSP1, a mechanism known as transactivation. They have also been shown to inhibit the production of many pro- inflammatory mediators including TNFα, IL-1β, GM-CSF, IL-6, IL-8, Cox-2, iNOS and adhesion molecules such as ICAM-1 and E-selectin. There is evidence to suggest that these genes can be affected by glucocorticoids at a transcriptional and a post-transcriptional level, dependent on the cell type and stimulus.
Inhibition at the transcriptional level is known as transrepression. By binding to the operator, repressor proteins prevent RNA polymerase from creating messenger RNA. AP-1 and NF-κB. IL-1, IL-6, TNFα and VEGF are regulated by glucocorticoids post- transcriptionally. They all contain an ARE in their 3’ UTR and are therefore p38 pathway targets. Work from our lab shows that in HeLa cells glucocorticoids activate DUSP1 (a phosphatase) which dephosphorylates p38 therefore causing its inactivation and inhibiting its ability to stabilise Cox-2 mRNA (Lasa et al., 2002; Lasa et al., 2000). This was later shown to be partially dependent on p38 and JNK MAPKs. In macrophages derived from a DUSP1 knockout mouse, dexamethasone was unable to abrogate the expression of TNFα, Cox-2, IL-1α and IL-1β mRNAs making the link between DUSP1, p38 mediated mRNA stabilisation and glucocorticoid mode of action (Abraham et al., 2006).
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The role of dexamethasone in the regulation of anti-inflammatory cytokines is of interest because it has recently been postulated that these mediate their activity through TTP. Recently Smoak et al. reported that dexamethasone exerts its anti-inflammatory effects by inducing expression of TTP in A549 cells (Smoak and Cidlowski, 2006). Contradictory to this work is another publication from a different group which describes the inhibitory effects that glucocorticoids have on LPS induced TTP in macrophages (Jalonen et al., 2005). Glucocorticoids exert anti-inflammatory effects, a mechanism which involves TTP would provide a novel pathway for their effects to be mediated. As well as these reports, a handful of micro-array experiments have detected an up-regulation of TTP in response to glucocorticoids. TTP was shown to be increased by 2.2 fold after four hours of glucocorticoid treatment in primary human keratinocytes (Stojadinovic et al., 2007). A previous micro-array experiment from our lab detected an up-regulation of TTP mRNA by 4.34 and 4.88-fold by 100 nM or 1 μM dexamethasone treatment of HeLa cells for two hours. BRF2 mRNA was up-regulated 1.82 or 1.71 fold under the same conditions, whereas BRF1 mRNA did not change (Lasa et al., 2002).
Results in this chapter show that dexamethasone induced a four fold change in TTP mRNA in HeLa cells in response to IL-1α treatment. BRF1 mRNA was induced by up to two fold and BRF2 mRNA was induced by 1.5 fold at the same time point. In A549 cells TTP mRNA was again the mRNA which is the most dramatically affected by dexamethasone. In these cells dexamethasone increased TTP mRNA expression by up to eight fold. A combination of dexamethasone and IL-1α had a synergistic affect on TTP mRNA expression increasing it by up to 15 fold. Parallel observations of BRF1 made in HeLa cells, showed that it was barely affected by dexamethasone. BRF2 was not measured, my suspicion would be that it too is unaffected by dexamethasone in these cells. This coincides with the findings of Smoak and Cidlowski and with the micro-array data from our lab.
Whether TTP is an important target for anti-inflammatory actions has yet to be resolved. The recent Smoak and Cidlowski publication did address this. They used siRNA to silence TTP achieving a good but by no means complete knockdown. They then used luciferase reporter constructs containing the TNFα 3’ UTR to assess the effect of dexamethasone on
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TNFα in TTP deficient cells. They show a significant increase of luciferase in siRNA against TTP treated cells in comparison to the dexamethasone treated siRNA free control. They also show that the percentage inhibition is greater following dexamethasone treatment in siRNA treated cells. The problem with these results is that when TTP is absent TNF is over-expressed, and when dexamethasone is added TNFα is decreased. Both of these things are happening in the siRNA treated cells it is therefore difficult to conclusively say that dexamethasone’s anti-inflammatory effect is mediated through TTP. To gain a more conclusive answer about TTP as a glucocorticoid target, cells derived from the TTP knockout mouse would be a better system to use than siRNA directed against TTP.
The relative abundance and induction patterns of the Zfp36 mRNAs varies between different cell types. For example in resting human monocytes all three of the proteins are present at approximately the same levels. Following LPS treatment TTP accounts for 69% of the total Zfp36 mRNA(Carrick and Blackshear, 2007). This is in contrast to results shown in this chapter for HeLa cells which have been previously discussed. Monocytes clearly express more TTP than BRF1 or BRF2 as seen by other groups and by ourselves in the RAW264.7 cells. Another difference was described in Zfp36 family member expression; Zfp36L3, the fourth, most recently identified member of the family was found to be undetectable until day 8.5 of embryonic development whereas BRF1 was expressed consistently throughout development. In addition to this Zfp36L3 transcript was found solely in the placenta of the mouse conceptus (Blackshear et al., 2005). Here, a role for this protein in regulation of placenta development is clear. As Zfp36l3 is exclusive to mice, may be one of the other family members fulfils this role in human cells. As well as being cell- type specific, Zfp36 gene expression is probably stimulus specific. Although they all seem to be up-regulated by inflammatory stimuli and by phorbol esters differences were observed when treated with glucocorticoids. Glucocorticoids were only successful at inducing TTP mRNA in HeLa and A549 cells. They had no affect on the proteins of TTP, BRF1 or BRF2.
Another aspect to the study by Carrick and Blackshear was to investigate the expression of these proteins in cancer cell lines from various tissue types. Several cell lines for a range of
147 Chapter 3 Differential expression of members of the Zfp36 family
cancers were screened. Again, a heterogeneity was noted between certain cell lines, either they expressed all three Zfp36 members or did not express them. However there were some differences, BRF2 was shown to be predominant in blood cancer cell lines whereas BRF1 was over-expressed in the kidney cancer cell lines. Greater proportions of both BRF1 and BRF2 were expressed in skin, breast and ovary cancer cells in comparison to TTP. Explanations for these differences in expression among certain cell types could, again, lie with differences in the activity of the promoters and with mRNA decay activity. Other reasons could be deletions that result in silencing of the relevant locus (Carrick and Blackshear, 2007). These data show that whilst their expression patterns in normal tissues may show some similarities, disregulation of specific family members could have particular pathological effects. BRF2 has previously been implicated in breast cancer (Garcia et al., 2005). Targeting these genes specifically in the relevant tissues could provide a new avenue of chemo-therapeutics.
Although they are differentially expressed, the Zfp36 genes are all capable of binding the same targets. This and the fact that their kinetics differ between cell types and stimuli indicates that perhaps they do target the same transcripts, associating with them at different points during the time course. For example it could be possible that TTP, BRF1 and BRF2 are involved in Cox-2 regulation but at different time points in response to IL-1α. As mentioned previously there are already examples of more than one AUBP controlling a single mRNA. Complex interplay between AUBPs to control mRNA turnover is more than likely and is something which is at present only vaguely understood. To address such a hypothesis, that different AUBPs associate with same mRNA but at different time points, a ribonucleoprotein complex- immunoprecipitation micro-array (RIP-CHIP) could be used. Targets of RNA binding proteins have historically been studied using techniques such as EMSAs. Unfortunately these techniques cannot be used to identify the cellular context within which they associate and neither can they be used to study the dynamic composition of the RNP in response to a stimulus. A RIP-CHIP experiment would combine biochemical techniques with genomic techniques to identify de novo targets of the Zfp36 proteins. Briefly, cell extracts are immnuoprecipitated for the AUBP of interest. The RNP is then released from the beads and the RNA is extracted from the complex. The purified RNA is
148 Chapter 3 Differential expression of members of the Zfp36 family
then identified using micro-array screening (Keene et al., 2006). Dynamic remodeling of RNP complexes may hold the key to the differential functioning and expression of the Zfp36 genes.
It is clear that many cell types are capable of simultaneously expressing the Zfp36 genes however there are differences in their abundance and expression patterns. Whether they have distinct targets or they are all together involved in the regulation of a set of common targets is presently unknown. The next two chapters will try and address these issues firstly by using siRNA to deplete BRF1 and BRF2 and secondly using a stable cell line which lacks BRF1.
149 Chapter 4 Knockdown of BRF1 and BRF2 in HeLa cells
Chapter 4: Results
Knockdown of BRF1 and BRF2 in HeLa cells
150 Chapter 4 Knockdown of BRF1 and BRF2 in HeLa cells
4) CHAPTER 4: KNOCKDOWN OF BRF1 AND BRF2 IN HELA CELLS
4.1) Introduction
TTP knockout mice display weight loss, severe poly-articular erosive arthritis and myeloid hyperplasia (Taylor et al., 1996a). A BRF1 knockout is embryonic lethal (Stumpo et al., 2004) and disruption of the BRF2 gene causes female infertility in mice (Ramos et al., 2004). So far there is no indication that there are any differences in the specificity of binding of the Zfp36 family members. Despite the similarities in their binding specificities the phenotypes of the knockouts suggest different functions of the TTP proteins. Presumably, like TTP, BRF1 and BRF2 each have specific targets, which account for the differences in the knockout phenotypes, however these have yet to be identified. BRF1 and BRF2 were detected in HeLa cells during an inflammatory response (section 3.2.2) which gave rise to an investigation of their involvement in MAPK p38 mediated stabilisation of mRNAs. The hypothesis was that BRF1 and or BRF2 can bind to the ARE of inflammatory cytokines and destabilise them, in a p38 sensitive manner. siRNAs designed to knockdown BRF1 and BRF2 were used to test this in HeLa cells in conjunction with a p38 inhibitor.
RNAi is a highly conserved pathway used by eukaryotes as a cellular line of defence directed against viral genomes or as a method to clear the cells of aberrant transcription products. dsRNA lead to the silencing of genes of homologous sequence. RNAi was first discovered in 1998 in a study where Caenorhabditis elegans were injected with dsRNA which caused potent and specific down regulation of their target genes (Fire et al., 1998). The cellular RNA interference machinery can be employed to specifically down regulate expression of target genes following transfection of cells with short dsRNA oligonucleotides of appropriate sequence (siRNAs).
4.2) BRF1 knockdown
4.2.1) Optimisation of BRF1 knockdowm Optimisation of the BRF1 knockdown is shown in figure 4.1 using Smartpool® siRNA. Smartpool® siRNA is a mixture of four duplexes that (according to the manufacturer’s
151 Chapter 4 Knockdown of BRF1 and BRF2 in HeLa cells
guarantee) will silence target gene expression at the mRNA level by at least 75% when used under standard conditions which are; 100 nM siRNA for 24 hours. Scramble is a non targeting siRNA used as a negative control. In more recent experiments firefly luciferase is used instead of scramble as a negative control. Mock transfected cells undergo the transfection procedure but siRNA is replaced with siRNA buffer (provided by Dharmacon).
HeLa cells were transfected with either 1 nM, 10 nM or 100 nM of Smartpool® siRNA or scramble siRNA or mock transfected or left untreated for 72 hours. 10 nM BRF2 siRNA was used as a positive control to ensure the knockdown technique was working. Whole cell lysates were prepared and run on a 10% polyacrylamide gel. Western blots were performed using SB1/30.13 (detects TTP, BRF1 and BRF2) and an anti-tubulin antibody to show equal protein loading. Figure 4.1 shows BRF1 knockdown in unstimulated HeLa cells. The knockdown seems to be effective using 10 nM and 100 nM siRNA. Here the previously discussed problem that TTP and BRF1 have similar mobilities is encountered. However although SB1/30.13 detects both TTP and BRF1, TTP usually migrates with higher mobility than the bands seen in this gel, and is expressed only very weakly (if at all) by unstimulated HeLa cells. This issue is later addressed in more detail using a BRF1-specific antibody as the possibility that SB1/30.13 is detecting some TTP in these cells cannot be ruled out. The other possibility is that the BRF1 knockdown is not 100% complete. A combination of the two is probably likely. Subsequently 100 nM BRF1 Smartpool® siRNA was used to gain a better knockdown.
4.2.2) Use of individual siRNA duplexes to silence BRF1 expression In theory the Dharmacon Smartpool® reagents maximise the probability of achieving efficient reduction of target gene expression. Individual siRNA duplexes from the four duplexes included in BRF1 Smartpool® were assessed (figure 4.2). HeLa cells were transfected with 1 nM, 10 nM or 100 nM BRF1 siRNA or of scramble siRNA or were mock transfected. Cells were then cultured for a further 72 hours and were then harvested. Whole cell lysates were prepared and proteins were separated by SDS PAGE. Western blots are shown using SB1/30.13 (detects TTP, BRF1and BRF2) and an anti-tubulin antibody (figure 4.2). All four of the duplexes have some effect on BRF1 when compared to the controls, however the knockdown is incomplete and does appear to have some off
152 Chapter 4 Knockdown of BRF1 and BRF2 in HeLa cells
target effects on BRF2. In all subsequent experiments, where individual duplex were used, 100 nM of duplex 2 was used to knockdown BRF1 for 72 hours.
153 Chapter 4 Knockdown of BRF1 and BRF2 in HeLa cells
Figure 4.1: Optimisation of the knockdown of BRF1 in HeLa cells using Smartpool® siRNA. HeLa cells were transfected with the indicated concentrations of either scramble siRNA or BRF1 Smartpool® siRNA or left untreated. Cells in the final lane were transfected with 10 nM BRF2 Smartpool® siRNA as a positive control. Cells were harvested after 48 hours, whole cell lysates were prepared and protein was separated by SDS PAGE and was then transferred on to PVDF membrane and western blotted for BRF1 using SB1/30.13 (detects TTP, BRF1 and BRF2) and tubulin. The blot shown is representative of two separate experiments.
154 Chapter 4 Knockdown of BRF1 and BRF2 in HeLa cells
Figure 4.2: Optimisation of the BRF1 knockdown in HeLa cells using individual duplexes. HeLa cells were transfected with indicated concentrations of siRNA duplexes 1- 4 or transfected with scramble siRNA or mock transfected for 72 hours. Whole cell lysates were prepared and protein was separated by SDS PAGE and was then transfered onto PVDF membrane. Western blots using SB1/30.13 (detects TTP, BRF1 and BRF2) and tubulin are shown.
155 Chapter 4 Knockdown of BRF1 and BRF2 in HeLa cells
4.2.3) Consequences of BRF1 knockdown To assess the role of BRF1 in p38-mediated mRNA stabilisation, protein levels of inflammatory mediators that contain an ARE in their 3’ UTR were studied. Techniques used to do this were western blotting and ELISA. Cox-2 catalyses the rate limiting step in the synthesis of prostaglandins such as PGE2 from arachidonic acid. Its expression is regulated in response to pro-inflammatory stimuli such as IL-1α. The IL-1α induced increase in Cox-2 expression is dependent on p38-mediated stabilisation of Cox-2 mRNA (Lasa et al., 2000; Ridley et al., 1997). IL-1α.-induced expression of IL-6 is also post- transcriptionally regulated by p38 MAPK in HeLa cells (J. Dean, unpublished observations). IL-8 is also an example of a pro-inflammatory cytokine mRNA stabilised by the p38 pathway (Winzen et al., 2004). The hypothesis that that p38-mediated regulation of Cox-2, IL-6 and IL-8 expression is dependent on BRF1 was tested.
HeLa cells were transfected with 100 nM BRF1 siRNA, or 100 nM scramble siRNA or mock transfected for 72 hours and were either stimulated with 20 ng/ml IL-1α for four hours or left unstimulated in the absence or presence of 1 μM of p38 inhibitor SB202190. Whole cell lysates were prepared and proteins were separated by SDS PAGE then western blotted using SB1/30.13 (detects TTP, BRF1 and BRF2) - figure 4.3A, and with anti- BRF1/2 (BRF1 specific) - figure 4.3B, to confirm the knockdown was effective. A western blot to show the effect of BRF1 knockdown on Cox-2 is included (figure 4.3C). Supernatants of the cells were collected and analysed for IL-6 by ELISA (figure 4.4) and IL-8 (figure 4.5).
The expression of a ~50 KD epitope was induced by IL-1α and inhibited by SB202190. The expression of this epitope was also inhibited by siRNA directed against BRF1. This is clearly shown in the panel where the BRF1 specific antibody was used as well as in the panel where the non-specific Zfp36 antibody is used (figure 4.3). In addition to this the epitope at 64 KD (BRF2) is also affected by the siRNA directed against BRF1 which could be explained as being off target effects.
156 Chapter 4 Knockdown of BRF1 and BRF2 in HeLa cells
As expected Cox-2 was induced in response to IL-1α. IL-1α induced expression appeared slightly higher in BRF1 knockdown cells, however taking the loading control and other experiments into account, no consistent differences can be observed. In all cases Cox-2 expression was inhibited by 1 μM SB202190 (figure 4.3C, the Cox-2 band is indicated by *).
Absolute quantities of cytokines expressed were quite variable between experiments, therefore I arbitrarily assigned a 100% value to the cytokine expression in mock- transfected, IL-1α-stimulated cells and normalised other values against this. The effect of this normalisation was to decrease the sizes of error bars and make effects of SB202190 and siRNAs easier to see. IL-6 (figure 4.4) protein levels were not significantly elevated in cells treated with BRF1 siRNA in comparison to the mock and scramble controls. Surprisingly there was a significant inhibition of IL-6 protein in cells treated with BRF1 siRNA when compared to the scramble control but not of the mock control. Inhibition of p38 also significantly decreased IL-6 production by approximately 50% in all cases. No significant effect on IL-8 protein levels was measured following BRF1 knockdown (figure 4.5). p38 was required for IL-8 expression, its inhibition caused extremely significant abrogation of IL-8 expression. Both IL-6 and IL-8 expression partially depends upon the activity of p38, but this is independent of BRF1.
157 Chapter 4 Knockdown of BRF1 and BRF2 in HeLa cells
Figure 4.3: BRF1 knockdown had no effect on Cox-2 protein. HeLa cells were transfected with either 100 nM BRF1 siRNA (duplex 2) or 100 nM scramble siRNA or mock transfected for 72 hours followed by either a four hour stimulation with 20 ng/ml IL- 1α or left unstimulated in the presence of 1 μM p38 inhibitor SB202190 or vehicle treated with DMSO. Whole cell lysates were prepared and protein was separated by SDS PAGE and was then transfered onto PVDF membrane. Western blots shown are represenative of three separate experimants. And are using the following antibodies: (A) SB1/30.13 (detects TTP, BRF1 and BRF2), (B) anti-BRF1/2 (Cell Signaling Technology), (C) Cox-2 (indicated by *) and for tubulin.
158 Chapter 4 Knockdown of BRF1 and BRF2 in HeLa cells
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Figure 4.4: BRF1 knockdown using siRNA had no effect on IL-6 protein. HeLa cells were transfected with either 100 nM BRF1 siRNA (duplex 2) or 100 nM scramble siRNA or mock transfected for 72 hours followed by either a four hour stimulation with 20 ng/ml IL-1α or left unstimulated in the presence of 1 μM of p38 inhibitor SB202190 or vehicle treated with DMSO. Supernatants were harvested and analysed for IL-6 by ELISA. Results shown represent the average of four independent experiments where each point was measured in triplicate. Error bars represent the standard error of the mean. The significance of the effect of the p38 inhibitor and of the BRF1 siRNA was measured using a one way ANOVA test followed by Bonferroni’s multiple comparison test. ns= p value of >0.05 (not significant), *= p value of 0.01 to 0.05 (significant), **= p value of 0.001 to 0.01 (very significant), ***= p value of <0.001 (extremely significant).
159 Chapter 4 Knockdown of BRF1 and BRF2 in HeLa cells
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Figure 4.5: BRF1 knockdown using siRNA had no effect on IL-8 protein. The experimental procedure and statistical analysis were carried out exactly as detailed in the legend for figure 4.4 except that supernatants were analysed for IL-8. Results shown represent the average of three independent experiments where each point was measured in triplicate.
160 Chapter 4 Knockdown of BRF1 and BRF2 in HeLa cells
4.3) BRF2 knockdown
4.3.1) Optimisation of BRF2 knockdown A similar set of experiments is shown in the next section, the focus is BRF2. HeLa cells were transfected with either 10 nM of Smartpool® siRNA or 10 nM of scramble siRNA or mock transfected or left untreated for either 24, 48 or 72 hours. Whole cell lysates were prepared, run on a 10% polyacrylamide gel and blotted with SB1/30.13 (detects TTP, BRF1 and BRF2) or with an anti-tubulin antibody to show equal loading. Figure 4.6A shows BRF2 knockdown was achieved after 24 hours and was still working at 48 and 72 hours. An approximately 80% knockdown was observed. Figure 4.6B shows the effects of a dose response of BRF2 siRNA ranging from 1–100 nM. HeLa cells were either transfected with 1 nM, 10 nM or 100 nM of BRF2 siRNA or scramble siRNA, mock transfected or left untreated. 10 nM of HSP27 siRNA was used as an additional control for efficiency of RNAi. Whole cell lysates were prepared after 48 hours of transfection and were blotted for BRF2 using SB1/30.13 (which detects TTP, BRF1 and BRF2) (Figure 4.6B). A good knockdown was seen using 1 nM of siRNA but a better knockdown was seen at the higher 10 nM and 100 nM dose. BRF2 knockdown conditions that are used in subsequent experiments are: 10 nM siRNA for 48 hours.
4.3.2) Use of individual siRNA duplexes to silence BRF2 expression As previously for BRF1, individual siRNA duplexes were assessed from the four duplexes included in the BRF2 Smartpool®. Duplex one and two efficiently reduced expression of BRF2. Duplexes three and four were less effective. Subsequent experiments were using 10 nM duplex one for 48 hours.
4.3.3) Consequences of BRF2 knockdown
As previously for BRF1, similar experiments to examine the effects of BRF2 knockdown on ARE containing inflammatory mediators were carried out. HeLa cells were transfected with either 10 nM BRF2 siRNA, or 10 nM scramble siRNA or mock transfected for 48 hours and were either stimulated with 20 ng/ml IL-1α for four hours or left unstimulated in the absence or presence of 1 μM of the p38 inhibitor SB202190. Whole cell lysates were prepared, proteins were separated using SDS PAGE then western blotted for BRF2, using SB1/30.13 to confirm the knockdown was effective, for Cox-2 and for tubulin to ensure
161 Chapter 4 Knockdown of BRF1 and BRF2 in HeLa cells
Figure 4.6: Optimisation of BRF2 knockdown in HeLa cells using Smartpool® siRNA. (A) HeLa cells were either transfected with 10 nM scramble siRNA, 10 nM BRF2 siRNA, or mock transfected (labelled 0 nM). Cells were harvested at the indicated times and whole cell lysates were prepared and proteins were separated by SDS PAGE and western blotted for BRF2 using SB1/30.13 (detects TTP, BRF1 and BRF2) and for tubulin. (B) HeLa cells were transfected with the indicated concentrations with either BRF2 siRNA or scramble siRNA or left untreated. Cells were harvested after 48 hours, whole cell lysates were prepared and protein was separated by SDS PAGE and was then transfered onto PVDF membrane. A western blot for BRF2 using SB1/30.13 (detects TTP, BRF1 and BRF2) is shown.
162 Chapter 4 Knockdown of BRF1 and BRF2 in HeLa cells
Figure 4.7: Optimisation of the BRF2 knockdown in HeLa cells using individual duplexes. HeLa cells were transfected with indicated concentrations of siRNA duplexes 1- 4 or scramble siRNA or mock transfected for 72 hours. Whole cell lysates were prepared and protein was separated by SDS PAGE and was then transfered onto PVDF membrane. A western blot using SB1/30.13 is shown.
163 Chapter 4 Knockdown of BRF1 and BRF2 in HeLa cells
equal loading (figure 4.8). Supernatants of the cells were collected and analysed by ELISA for IL-6 (figure 4.9) and for IL-8 (figure 4.10).
An approximately 80% BRF2 knockdown was achieved in comparison to the scramble and mock transfected controls (figure 4.8A). With IL-1α treatment BRF2 was induced and was seen even after knockdown, the knockdown was therefore incomplete but was probably still 80% complete in comparison to the relevant controls. Basal expression of Cox-2 appeared slightly higher in BRF2 knockdown cells. As expected Cox-2 was induced in response to IL-1α. IL-1α induced expression appeared slightly higher in BRF2 knockdown cells however this was inconsistent and was not observed in all experimental replicates. In all cases Cox-2 expression was inhibited by 1 μM SB202190.
Figures 4.9 and 4.10 show ELISA data for IL-6 and IL-8 expression following BRF2 knockdown. Again as with the ELISAs shown previously for BRF1 knockdown absolute quantities of cytokines expressed were very variable between experiments. For this reason I have shown a representative experiment for each cytokine. A value of 100% was arbitrarily assigned to the cytokine expression in mock-transfected IL-1α-stimulated cells and other values were normalised against this. When compared with the mock transfected control IL- 6 protein expression was unaffected but when compared to the scramble control a significant increase in IL-6 was measured. This observation was inconsistent and was not always the case in replicate experiments. Overall the expression of IL-6 was not significantly different from the controls in cells treated with siRNA against BRF2. siRNA against BRF2 did not increase basal or IL-1α -induced expression of IL-8 (figure 4.10). In the experiments shown, SB202190 had a more pronounced effect on IL-6 than on IL-8 expression. In most cases inhibition of p38 reduced cytokine expression significantly. These experiments do not support the hypothesis that BRF2 is required for p38-mediated regulation of Cox-2, IL-6 and IL-8 expression. However, the incomplete nature of the knockdown creates a problem. It is possible that the low levels of BRF2 that remain are sufficient for controlling gene expression in a p38-sensitive manner, therefore it is difficult to draw firm conclusions about the role of BRF2 in the response to p38.
164 Chapter 4 Knockdown of BRF1 and BRF2 in HeLa cells
Figure 4.8: Cox-2 is slightly up-regulated in response to BRF2 knockdown. HeLa cells were transfected with either with 10 nM BRF2 siRNA (duplex 1), 10 nM scramble siRNA or mock transfected for 48 hours followed by either a four hour stimulation with 20 ng/ml IL-1α or left unstimulated in the presence of 1 μM p38 inhibitor SB202190 or vehicle treated with DMSO. Western blots shown are representative of three separate experiments using the following antibodies: (A) SB1/30.13 (detects TTP, BRF1 and BRF2) (B) Cox-2 and for tubulin.
165 Chapter 4 Knockdown of BRF1 and BRF2 in HeLa cells
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Figure 4.9: BRF2 knockdown had no effect on IL-6 protein. HeLa cells were transfected with either 10 nM BRF2 siRNA (duplex 1) or 10 nM scramble siRNA or mock transfected for 48 hours followed by either a four hour stimulation with 20 ng/ml IL-1α or left unstimulated in the presence of 1 μM of p38 inhibitor SB202190 or vehicle treated with DMSO. Supernatants were harvested and analysed for IL-6 by ELISA. The result shown is representative of four independent experiments, the error bars represent he standard error of the mean of triplicate values in that experiment. The significance of the effect of the p38 inhibitor and of the BRF2 siRNA was measured using a one way ANOVA test followed by Bonferroni’s multiple comparison test. ns= p value of >0.05 (not significant), *= p value of 0.01 to 0.05 (significant), **= p value of 0.001 to 0.01 (very significant), ***= p value of <0.001 (extremely significant).
166 Chapter 4 Knockdown of BRF1 and BRF2 in HeLa cells
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Figure 4.10: BRF2 knockdown has no effect on IL-8 protein. The experimental procedure and statistical analysis were carried out exactly as detailed in the legend for figure 4.9 except that supernatants were analysed for IL-6 by ELISA. The graph shown is representative of two separate experiments where each point was measured in triplicate.
167 Chapter 4 Knockdown of BRF1 and BRF2 in HeLa cells
4.4) Summary and Discussion
The knockdown of BRF1 or BRF2 had little or no effect on the ARE containing inflammatory mRNAs IL-6, IL-8 and Cox-2. Whether this was due to the incompleteness of the knockdown or due to the fact that they are not involved in the regulation of these genes is unknown. Also in this chapter the relevance of the p38 pathway in BRF1 and BRF2 function was investigated. These experiments could not show a link between BRF1 or BRF2 and the p38-dependent expression of pro-inflammatory mediators.
It was difficult to gain a consistently good knockdown of BRF1 in HeLa cells. Assessing the extent of the BRF1 knockdown with the BRF1 specific antibody gave the impression that a better knockdown was achieved, suggesting that in the earlier experiments the apparent incompleteness of the knockdown may have been because the antibody used was detecting TTP. As well as this the BRF1 specific antibody may not be sensitive enough to detect very low levels of BRF1 that remain in the system post siRNA treatment. BRF1 siRNAs also have off target effects on BRF2 which may be because the oligos have been designed to a region in BRF1 where the two genes have some homology. The extent of the off target effects were variable between experiments and were not seen with all of the oligos. Those that were more effective at silencing BRF1 had a greater off target effect on BRF2. Previously, Smartpool® were thought to increase off target effects, recently opinion has changed. Strong on target gene knockdown can be achieved with minimal off target effects if a pool consisting of highly functional multiple siRNA is substituted for individual duplexes (Review-Dharmacon website). Perhaps the progression onto the use of individual duplexes was partly responsible for an increase in off target effects of the BRF1 siRNA on BRF2.
In the case of BRF2, it appears difficult to achieve a 100% knockdown using siRNA. This is especially problematic when an inflammatory stimulus is applied to the cells. Optimisation experiments show that a good knockdown is achieved in resting cells. However, after knockdown and IL-1α treatment, BRF2 was detected. Although there was less BRF2 in the siRNA treated cells than the control cells, a significant amount was still expressed. Unfortunately small amounts of remaining protein may be enough to carry out
168 Chapter 4 Knockdown of BRF1 and BRF2 in HeLa cells
their destabilising role, which was hard to overcome as a knockdown using siRNA is rarely 100% effective. Because of this, future experiments using this technique may be not be particularly useful. However my colleagues have improved efficiency of siRNA knockdown of their target genes using a method which subjects the cells to two rounds of treatment with the siRNA 24 hours apart. This is a method which could achieve better results in the silencing of these genes.
Having demonstrated TTP presence in HeLa cells, an siRNA designed to silence it was acquired. Verifying TTP knockdown in the HeLa cells proved to be an arduous task (data not shown). Given that the detection of TTP in HeLa cells is inconsistent due to batch variation with the Santa Cruz H120 antibody it was difficult to verify the efficiency of siRNA-mediated knockdown. qPCR was also used to try and establish the extent of the TTP knockdown but technical difficulties were encountered with this. As with BRF1 and BRF2 small amounts of the proteins may be enough for their destabilising functions to be carried out. For these technical reasons the role of TTP in HeLa cells was not studied further.
It is possible that members of the Zfp36 family have redundant functions in the regulation of Cox-2, IL-6 and IL-8 expression in HeLa cells. If this is the case, it is possible that all three of the proteins need to be silenced simultaneously to see an effect. We do know that the Zfp36 genes can substitute one another to carry out destabilising effects on their targets (Stoecklin et al., 2002) however the phenotypes of the knockout mice are strong evidence that they have their own sets of targets. Whether this is in addition to targets which may be common to the Zfp36 family or not is unknown. To fully understand whether or not redundancy does exist between TTP, BRF1 and BRF2 a good knockdown of all three genes simultaneously would be needed.
I assessed the possibility that the p38 pathway was targeting BRF1 or BRF2 to mediate cytokine mRNA regulation. Experiments in this chapter do not provide any evidence to suggest that this is the case. Results show that although IL-6, IL-8 and Cox-2 expression were all partially dependent on the activity of p38, BRF1 and BRF2 were not themselves
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targets in their regulation by p38. Therefore the hypothesis that BRF1 and or BRF2 are involved in p38 mediated mRNA stabilisation was unproven in this system. There is no doubt that the p38 pathway stabilises mRNAs in HeLa cells (Ridley et al., 1998). Whether BRF1 and or BRF2 are regulated by this pathway remains to be seen. Other signalling pathways have also been implicated in mRNA stabilisation but the p38 pathway is the most widely documented as having a role in this process (Brook et al., 2000; Clark et al., 2003; Dean et al., 1999; Winzen et al., 1999).
Although these experiments did not indicate that p38 targets BRF1 or BRF2 to mediate inflammatory cytokine mRNA expression they do show that BRF1 and BRF2 protein expression is partially dependent on the activity of p38 (figures 4.3 and 4.8). In the previous chapter western blots showed multiple bands of changing mobilities on SDS gels that represent BRF1. These bands appear after 30 minutes of treatment with an inflammatory stimulus. Speculation is that they are phosphorylated forms of BRF1, a theory formed on the basis of some experiments where phosphatase treatment of cell extracts caused BRF1 and BRF2 bands to ‘collapse’ to a faster-migrating form (Tomas Sanatlucia - unpublished observations). In addition, as mentioned above work from another lab has shown that BRF1 is phosphorylated at serine 92 and at serine 203 (Benjamin et al., 2006; Schmidlin et al., 2004). TTP has been shown to be phosphorylated at several residues (Cao et al., 2006) by MK2 (Mahtani et al., 2001), p38 and ERK (Cao and Lin, 2007). It is likely that BRF1 and BRF2 are also phosphorylated on several residues by more than one kinase which have not yet been identified. Again, as discussed in the previous chapter it probably depends on the stimulus and cell type as to what phosphorylates BRF1. The phosphorylation of these proteins is complex but probably holds the key to some unanswered questions about the differences in their activities and functions.
Using siRNA in the HeLa cells to try and establish the functions of these proteins has proved problematic. Firstly, the discovery of TTP in these cells meant that TTP could in fact be responsible for the p38 mediated stabilisation of inflammatory mRNAs. This had previously been ruled out on the basis of its absence. Secondly, the antibodies available in the early stages of the project were unable to distinguish between BRF1 and TTP, making it
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difficult to know whether BRF1 was being knocked down sufficiently or not. Thirdly, it was sometimes difficult to achieve a complete knockdown with siRNA of the target protein. To conclude, no obvious differences following BRF1 or BRF2 knockdown were observed. An alternative approach to assessing BRF1 function is described in the next section (chapter 5), and is based on the use of BRF1-/- mouse embryonic fibroblasts.
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172 Chapter 5 Investigation of putative targets of BRF1
Chapter 5: Results
Investigation of putative targets of BRF1
173 Chapter 5 Investigation of putative targets of BRF1
5) CHAPTER 5: INVESTIGATION OF PUTATIVE TARGETS OF BRF1
5.1) Introduction To enable further study of BRF1 function, BRF1-/- mouse embryonic fibroblast (MEF) cell lines were obtained from an external collaborator (Martin Turner, Babraham Institute, Cambridge). The BRF1 knockout is embryonic lethal, with BRF1 null mice dying of angiogenic defects at approximately day 10.5. BRF1+/+ (lines 614 and 619) and BRF1-/- fibroblasts (lines 611 and 618) were isolated from littermates at day 9 and immortalised using SV40 T antigen. BRF1-/- MEFs have been reported to over-express VEGFA (Bell et al., 2006), a growth factor important in angiogenesis during development (Breen, 2007; Ferrara and Davis-Smyth, 1997). VEGFA mRNA contains an ARE that mediates destabilisation by BRF1 in transfected cells (Ciais et al., 2004). However, VEGFA mRNA stability was not found to be significantly increased in BRF1-/- MEFs (Bell et al., 2006).
5.2) Characterisation of BRF1 +/+ and BRF1-/- MEFs
5.2.1) Expression of Zfp36 proteins in MEFs Figure 5.1 shows the levels of expression of TTP, BRF1 and BRF2 proteins in the MEFs. MEFs from both the knockout clones and from the clones were stimulated with 20 ng/ml IL-1α for time points ranging over eight hours, either in the presence of the p38 inhibitor SB202190 or with a DMSO vehicle treatment. Whole cell lysates were prepared and proteins were separated by SDS PAGE. The western blots shown in figure 5.1 are with SB1/30.13, which detects all of the Zfp36 proteins. The band indicated in all four blots at ~ 64 KD is BRF2. BRF2 was expressed in resting cells and was slightly up-regulated in response to IL-1α. Induction of this band was slightly attenuated by blocking the p38 pathway. These observations are in parallel with those discussed in chapter 3, where other cell lines have been characterised.
Looking at the upper panels in figure 5.1, which show the wildtype MEFs (clones 619+/+ and 614+/+) there is a group of bands below the 50 KD marker which could correspond to BRF1 and or TTP. In support of the argument that they are BRF1, the lower panels of the same figure show that these bands are completely absent in the BRF1-/- cells. MEFs either
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do not express TTP protein, or express it at such low levels that it remains below the threshold of detection by SB1/30.13. The expression of BRF1 in the wildtype cells displays a similar pattern to that previously observed in other cell lines. Very small amounts can be detected in resting cells and it is strongly induced by IL-1α. In this case the peak is at two hours but levels remain elevated throughout the eight hour time course. Again the expression of BRF1 in the wildtype cells is p38 dependent.
5.2.2) Morphology of BRF1+/+ and BRF1-/- MEFs Figure 5.2 shows photographs taken using phase contrast light microscopy of the MEF knockout and the wildtype clones. These images were taken to illustrate the differences in the morphology of the two cell types. The wildtype cells are much rounder and form a more regular ‘paving stone’-like monolayer whereas the knockout cells are much more elongated and tend to grow in an irregular fashion, often growing on top of one another. The knockout cells take longer to reach confluencey. These observations suggest BRF1 targets may be mRNAs with structural roles. The precise identity of these has yet to be uncovered.
5.2.3) p38 phosphorylation in MEFs Phosphorylation of p38, which is a good indicator of its activity in these cells, was confirmed by western blot. Figure 5.3 shows western blots of each MEF cell line for phospho-p38 (Pp38). Cells were treated with IL-1α over an eight hour time course and whole cell lysates were prepared. In each case Pp38 was strongly phosphorylated after 15 minutes of IL-1α treatment, followed by a gradual decline. These are the expected kinetics for p38 phosphorylation (Saklatvala et al. 1993), confirming that there are no abnormalities of p38 MAPK signalling in the BRF1-/- MEFs used in this study.
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Figure 5.1: Zfp36 protein expression in BRF1+/+ and BRF1-/- MEFs. Knockout and wildtype MEFs were stimulated for the indicted times with 20 ng/ml IL-1α in the presence of 1 μM SB202190 or vehicle treated with DMSO. Whole cell lysates were prepared and protein was separated by SDS PAGE and transferred onto PVDF membrane. Western blots are shown for the Zfp36 family using SB1/30.13 and for tubulin as a loading control and are representative of two separate experiments.
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Figure 5.2: The morphology of BRF1+/+ and BRF1-/- MEFs differs. Photographs taken with a 20x lens. (A) clone 614+/+ confluent, (B) clone 614+/+ sub-confluent, (C) Clone 619+/+ confluent, (D) clone 619+/+ sub-confluent, (E) clone 611-/- confluent, (F) 611-/- sub- confluent, (G) clone 619-/- confluent, (H) clone 619 sub-confluent.
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Figure 5.3: Pp38 is detected 15 minutes after IL-1α treatment in BRF1+/+ and BRF1-/- MEFs. BRF1+/+ and BRF-/- MEFs were treated for the indicated times with 20 ng/ml IL-1α. Whole cell lysates were prepared and protein was separated by SDS PAGE then transferred on PVDF membrane. Western blots are shown for Pp38 and for tubulin and are representative of two separate experiments.
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5.3) Consequences of BRF1 knockout on protein expression of ARE containing inflammatory mediators in MEFs
As previously described in Chapter 4, one aim of this project was to identify the role of BRF1 and BRF2 in p38-mediated stabilisation of inflammatory mRNAs. TTP, the close relative of BRF1, has been shown to have an affinity for ARE containing transcripts, most notably TNFα, but several more have been identified (Beyaert et al., 1996; Briata et al., 2003; Brooks et al., 2004; Carballo and Blackshear, 2001; Carballo et al., 1997; Carballo et al., 1998; Carballo et al., 2000; Datta et al., 2008; Emmons et al., 2008; Essafi-Benkhadir et al., 2007; Frasca et al., 2007; Gringhuis et al., 2005; Jalonen et al., 2006; Lai and Blackshear, 2001; Lai et al., 2006; Marderosian et al., 2006; Ogilvie et al., 2005; Sawaoka et al., 2003; Stoecklin et al., 2000; Stoecklin et al., 2001; Stoecklin et al., 2008; Suswam et al., 2008; Taylor et al., 1996a; Tchen et al., 2004; Yu et al., 2003a). In vitro assays have shown that BRF1 can bind and destabilise TNFα and other TTP targets by the same mechanism as TTP (Lai and Blackshear, 2001; Lai et al., 1999; Lai et al., 2003). For the next experiments I selected three genes (IL-6, Cox-2 and KC) that are induced by pro- inflammatory stimuli, post-transcriptionally regulated by the p38 MAPK pathway and have been identified as targets of TTP (Dai et al., 2003; Datta et al., 2008; Dean et al., 2001; Miyazawa et al., 1998; Sawaoka et al., 2003; Stoecklin et al., 2001). As described in the Introduction, IL-6 is a pleiotropic pro-inflammatory cytokine, Cox-2 catalyses the rate- limiting step in the biosynthesis of prostaglandins, and KC (otherwise known as CXCL1 or Gro-α) is a chemokine that plays a critical role in recruitment of neutrophils. The expression and p38-dependence of these three genes was examined in BRF1+/+ and BRF1-/- MEFs.
It was not practical to analyse inflammatory responses simultaneously in all four clones because of the number of experimental points and replicates required. Furthermore the differences in the growth rates of the clones would have made it difficult to synchronize such large experiments. The decision was taken to arbitrarily pair the clones: 611-/- was paired with 614+/+ and 618-/- with 619+/+. The implications of this are discussed later in the chapter.
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Cox-2 protein was analysed by western blot (figure 5.4). Each clone was stimulated for the times indicated with IL-1α and whole cells lysates were prepared and blotted for Cox-2. In all of the clones, regardless of whether they express BRF1 or not, Cox-2 was constitutively expressed. This is unexpected as Cox-2 is generally considered to be an inducible gene (Smith et al., 1996). At first it was suggested that the epitope detected was not Cox-2 but a cross-reacting protein of similar molecular weight. To confirm that the band was Cox-2, control lysates were prepared from a different MEF line, untreated or stimulated with IL-1α for four hours. In this case little or no basal expression of Cox-2 protein was detected, and IL-1α caused clear induction of a band that appeared identical in mobility to the main epitope in BRF1+/+ and BRF1-/- cells. The control MEFs and the BRF1+/+ and BRF1-/- MEFs used in this experiment differ in their method of immortalisation. It may be that immortalisation by large T antigen results in constitutive expression of Cox-2.
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Figure 5.4: Cox-2 protein is constitutively expressed in BRF1+/+ and BRF1-/- MEFs. MEFs were stimulated for the indicated time with 20 ng/ml IL-1α. Whole cell lysates were prepared and protein was separated by SDS PAGE and transferred onto PVDF membrane. Western blots are shown for Cox-2 and for tubulin which is used as a loading control. These blots are representative of three separate experiments. Some technical assistance was provided by Roberta Perelli for this figure.
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Confluent MEFs were stimulated with 20 ng/ml IL-1α in the absence or presence of the p38 inhibitor SB202190 over an eight hour time course. Supernatants were harvested and analysed by ELISA for KC (Figure 5.5). Basal expression of KC protein was detected in both wildtype and BRF1-null cells. Expression was steadily increased over eight hours in response to IL-1α. Under most conditions the expression of KC protein was not significantly inhibited by SB202190. At some time points statistically significant differences in expression of KC by BRF1+/+ and BRF1-/- cells were found, however the pattern was not consistent. MEF cell line 611 (BRF1-/-) expressed less KC than 614 (BRF1+/+), whereas 618 (BRF1-/-) expressed more than 619 (BRF1+/+). Comparing the expression of KC protein by all four cell lines (Figure 5.5C), it is clear that there is as much variation between MEF lines of the same genotype as there is between MEF lines of different phentotype. In other words there is no evidence that the absence of BRF1 causes any change in the expression of KC protein.
Figure 5.6 shows ELISA data for IL-6. As previously for KC, both pairs of clones were evaluated (clone 614+/+ compared with 611-/- and 619+/+ compared with 618-/-). In the absence of stimulus, detectable IL-6 was expressed only by 611-/-. However there were no statistically significant differences in basal expression between BRF1+/+ and BRF1-/- cells. In BRF1-/- cells following IL-1α treatment, IL-6 increased dramatically and linearly, reaching 450 or 800 pg/ml by eight hours (clones 611-/- and 618-/-). Comparatively little IL-6 was expressed by BRF1+/+ cells. At every time point after addition of IL-1α, differences in expression of IL-6 between BRF1+/+ and BRF1-/- cells were significant (p<0.05) or highly significant (p<0.001). Figure 5.6C compares IL-6 expression of all four lines, making the point that comparative over-expression of IL-6 is a consistent feature of BRF1-/- MEFs, regardless of which pair-wise comparisons are made.
The addition of the p38 inhibitor caused an approximately 50% inhibition of IL-6 production in most cell lines and at most time points. In BRF1+/+ cells, which expressed relatively large amounts of IL-6, the inhibitory effect of SB202190 was statistically significant at all but the earliest time point. In BRF1-/- cells, which expressed relatively
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A BRF1 +/+ 614 BRF1 -/- 611 ns 45000 ns * ns ns 40000 * ns 35000 ns ns * 30000 ns * 25000 20000
KC (pg/ml)KC 15000 10000 ns 5000 0 - + - + + - + + - + + - + SB - - + + - + + - + + - + + IL-1 2 h 4 h 6 h 8 h
B BRF1 +/+ 619 BRF1 -/- 618 ns *** ** 50000 ns ns ns ns ns C 40000 *** unstimulated IL-1 8 hours 50000 30000 ns ns ns 40000 20000 30000 KC (pg/ml) 20000 10000 KC (pg/ml) ns 10000
0 0 614 619 611 618 - + - + + - + + - + + - + SB wildtype BRF1 KO - - + + - + + - + + - + + IL-1 2 h 4 h 6 h 8 h
Figure 5.5: KC protein expression is comparable between BRF1+/+ and BRF1-/- MEFs in response to IL-1α. MEFs were stimulated with 20 ng/ml IL-1α with 1µM SB202190 or vehicle treated with DMSO for the indicated times. Supernatants were harvested and KC protein quantified by ELISA. Results shown are the mean values for triplicate experiments. Error bars represent the standard error of the mean. On each graph the significance of the difference in KC protein expression between the knockout and the wildtype cells is shown at all time points. Significance was calculated using a one way ANOVA test followed by
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Bonferroni’s multiple comparison test. ns= p value of >0.05 (not significant), *= p value of 0.01 to 0.05 (significant), **= p value of 0.001 to 0.01 (very significant), ***= p value of <0.001 (extremely significant). (A) Clones 614+/+ and 611-/- N=3 (B) Clones 619+/+ and 618-/- N=3 (C) A graph to show that the arbitrary pairing of the clones does not affect the overall conclusions.
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A BRF1 +/+ 614 BRF1 -/- 611
ns ** *** *** 500 *** *** ns
400 *** ***
300 ns ns 200 *** IL-6 (pg/ml) IL-6 ns 100
0 - + - + + - + + - + + - + SB - - + + - + + - + + - + + IL-1 2 h 4 h 6 h 8 h B BRF1 +/+ 619 BRF1 -/- 618 ns *** *** 1000 ns *** *** 750 C ns unstimulated IL-1 8 hours 1000 500 *** *** 750 ns (pg/ml) IL-6 500 250 * ns IL-6 (pg/ml) IL-6 250 ns 0 0 614 619 611 618 - + - + + - + + - + + - + SB wildtype BRF1 KO - - + + - + + - + + - + + IL-1 2 h 4 h 6 h 8 h
Figure 5.6: IL-6 protein is over-expressed in BRF1-/- MEFs by comparison with BRF1+/+ MEFs in response to IL-1α. The experimental procedure and statistical analysis were carried out exactly as detailed in the legend for figure 5.5 except supernatants were quantified for IL-6. (A) Clones 614+/+ and 611-/- N=3, (B) Clones 619+/+ and 618-/- N=3, (C) A graph to show that the arbitrary pairing of the clones does not affect the overall conclusions.
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little IL-6, the inhibitory effect of SB202190 was statistically significant in only one case (614 cells at the eight hour time point). A reasonable interpretation of these data is that p38 MAPK regulates the expression of IL-6 similarly in BRF1+/+ and BRF1-/- cells. There is certainly no evidence that regulation of IL-6 expression by p38 MAPK is dependent on BRF1 (see discussion).
To summarise, BRF1-/- MEFs over-express IL-6, but not KC, in response to IL-1α. IL-6 expression can be reduced by up to 50% by blocking p38, again this is not the case for KC. Cox-2 is constitutively expressed in these cells regardless of whether BRF1 is present or not.
5.4) Consequences of BRF1 knockout on mRNA expression of ARE containing inflammatory mediators in MEFs
The mechanism through which BRF1 regulates its targets is at the moment controversial. There is strong evidence to suggest that it functions in a similar way to TTP which binds and destabilises its targets via an ARE present in their 3’UTR. BRF1 has also been shown to function by the same mechanism, however this has only been exhibited in over- expression studies. In contrast to this another group has suggested that BRF1 functions via a translational mechanism. Under normoxic conditions BRF1-/- MEFs significantly over- expressed VEGFA protein but did not significantly over-express VEGFA mRNA. This suggested that BRF1 may function as a negative regulator of VEGFA translation. Consistent with this hypothesis, VEGFA mRNA was more strongly associated with polysomes in BRF1-/- cells (Bell et al. 2006). To investigate whether BRF1 also regulates the expression of IL-6, Cox-2 and KC at the translational or post-translational level the corresponding mRNAs were measured in BRF1+/+ and BRF1-/- cells stimulated with IL-1α for up to eight hours.
Figure 5.7 shows a comparison of Cox-2 steady state mRNA levels between BRF1+/+ and BRF1-/- cells. These mRNAs were measured using qPCR over a period of eight hours following IL-1α treatment. Cox-2 mRNA was transiently up-regulated in all clones, peaking after one hour. At one and two hour time points Cox-2 mRNA was more highly
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expressed by the BRF1-/- clones. At later time points differences were not statistically significant. As previously, an additional graph has been included to show that the pairing of the clones has no bearing on the findings of these experiments (figure 5.7C). Cox-2 mRNA was consistently over-expressed (though only about 2-fold) by BRF1-/- MEFs.
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A BRF1 +/+ 614
BRF1 -/- 611
25 ***
20
15 ** 10 ns ns ns ns 5
COX-2/ GAPDH mRNA 0 0 1 2 4 6 8 IL-1 (hours)
B BRF1 +/+ 619 BRF1 -/- 618
25 *** 20 * 15 C Unstimulated IL-1 1 hour 25
10 20 ns ns ns ns 15 5 10 5 COX-2/GAPDH mRNA 0 0 COX-2/GAPDH mRNA 614 619 611 618 -5 0 1 2 4 6 8 wildtype IL-1 (hours) BRF1 KO
Figure 5.7: Cox-2 mRNA is over-expressed in BRF1-/- MEFs by comparison with BRF1+/+ MEFs in response to IL-1α. MEFs were stimulated for the indicated time with 20 ng/ml IL-1α. RNA was isolated and quantified for Cox-2 and GAPDH mRNA using ® Taqman probes. Delta delta Ct analysis was used to calculated the fold change in Cox-2 mRNA expression in comparison to the unstimulated BRF1+/+ sample, all results were normalised to GAPDH. Results shown are the mean values for three experiments, the error
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bars represent the standard error of the mean. On each graph the significance of the difference in Cox-2 mRNA expression between the knockout and the wildtype cells is shown at all time points. Significance was calculated using a one way ANOVA test followed by Bonferroni’s multiple comparison test. ns= p value of >0.05 (not significant), *= p value of 0.01 to 0.05 (significant), **= p value of 0.001 to 0.01 (very significant), ***= p value of <0.001 (extremely significant). (A) Clones 614+/+ and 611-/- N=3, (B) Clones 619+/+ and 618-/- N=3 (C) A graph to show that the arbitrary pairing of the clones does not affect the overall conclusions.
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A BRF1 +/+ 614 BRF1 -/- 611 *** 500
400
300 *** ns 200 ** **
100 KC/GAPDH mRNA ns 0 0 1 2 4 6 8 IL-1 (hours)
B
BRF1 +/+ 619 BRF1 -/- 618 800 *** 700 600 * C 500 unstimulated IL-1 1 hour * 1000 400 ns ns 750 300 200 500
KC/ GAPDH mRNA 100 ns 250 KC/GAPDH mRNA
0 0 614 619 611 618 0 1 2 4 6 8 wildtype BRF1 KO IL-1 (hours)
Figure 5.8: KC mRNA is over-expressed in BRF1-/- MEFs by comparison with BRF1+/+ MEFs in response to IL-1α. The experimental procedure and statistical analysis were carried out exactly as detailed in the legend for figure 5.7 except that RNA was quantified for KC. (A) Clones 614+/+ and 611-/-, (N=3) (B) Clones 619+/+ and 618-/- (N=3). (C) A graph to show that the arbitrary pairing of the clones does not affect the overall conclusions.
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A BRF1 +/+ 614
BRF1 -/- 611
800 ***
700 *** 600 *** 500 *** 400 ns 300 200 ns
IL-6/GAPDH mRNA 100
0 0 1 2 4 6 8 IL-1 (hours)
B
BRF1 +/+ 619 BRF1 -/- 618 *** 400 *** ***
300 ** C Unstimulated IL-1 2 hours 200 ns 300
200 100 ns 100 IL-6/GAPDH mRMA IL-6/GAPDH
mRNAIL6/GAPDH 0 0 614 619 611 618 0 1 2 4 6 8 wildtype BRF1 KO IL-1 (hours)
Figure 5.9: IL-6 mRNA is over-expressed in BRF1-/- MEFs by comparison with BRF1+/+ MEFs in response to IL-1α. The experimental procedure and statistical analysis were the same as detailed in the legend for figure 5.7 except that RNA was quantified for IL-6. (A) Clones 614+/+ and 611-/-, (N=3) (B) Clones 619+/+ and 618-/- (N=3). (C) A graph to show that the arbitrary pairing of the clones does not affect the overall conclusions.
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KC steady state mRNA was measured by qPCR in BRF1+/+ and BRF1-/- cells treated for up to eight hours with IL-1α, (figure 5.8). KC mRNA was substantially induced by the IL-1α stimulus. Following the ELISA results where little difference was observed in the level of KC protein expression between BRF1+/+ and BRF1-/- cells, it would be logical to expect no difference in KC mRNA expression in these cells. However BRF1-/- cells were found to over-express KC mRNA. As in the case of Cox-2, differences were most apparent at early time points, but statistically significant over-expression of KC mRNA was still detected in BRF1-/- cells at the eight hour time point. Figure 5.8C is an inset graph to show data from all four clones from unstimulated cells and cells treated for eight hours with IL-1α. It substantiates the point that regardless of the pairing combination of the clones the outcome of the experiments was the same.
Figure 5.9 shows a comparison of IL-6 steady state mRNA levels between BRF1 knockout and wildtype cells. These mRNAs were measured using qPCR over a period of eight hours following IL-1α treatment. Clearly, IL-1α treatment stimulates IL-6 mRNA expression. When fold changes in IL-6 expression were expressed in relation to the unstimulated wildtype cells which are always set to a value of one, the fold change was far greater in the knockout clones (up to 400 fold in 618-/-) than in the wildtype clones (less than 50 fold in 619+/+). At most time points after IL-1α stimulation the over-expression of IL-6 mRNA is extremely significant, an observation applicable to both clone sets. There were no significant differences between the BRF1+/+ and BRF-/- cells when the cells were left unstimulated.
Again to demonstrate that the pairing of the clones does not affect the conclusion that IL-6 mRNA is over-expressed in BRF1-/- MEFs an additional graph has been included. Figure 5.9C shows data from all four clones from unstimulated cells and cells treated for up to eight hours with IL-1α. It is clear that the pairing of the clones is irrelevant to the outcome of the experiment.
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5.5) Does BRF1 exert post-transcriptional control over IL-6 and or Cox-2? Having seen an over-expression of Cox-2 mRNA and IL-6 protein and mRNA in BRF1-/- MEFs it was hypothesized that perhaps BRF1 was involved in the post-transcriptional regulation of these genes. The next experiments examined the effect of BRF1 absence on Cox-2 and IL-6 mRNAs. To fully investigate mRNA stability a series of actinomycin D chase experiments were performed. Actinomycin D is a transcriptional inhibitor. If BRF1 was responsible for causing the decay of Cox-2 and IL-6 mRNA, these mRNAs would be expected to be more stable in BRF1 null cells.
Actinomycin D chase experiments were performed to assess the effect of BRF1 absence on Cox-2 mRNA stability. The measurements were made by qPCR and were all normalised using GAPDH as an internal control. Cells were stimulated for one hour with IL-1α as this was found to be the peak of Cox-2 mRNA induction (figure 5.7). After one hour of IL-1α treatment, actinomycin D was added (time = 0) and mRNA decay was followed over 75 minutes at 15 minute intervals. No significant differences were observed in Cox-2 mRNA stability between the knockout and the wildtype cells (figure 5.10). The effect of inhibiting p38 was also investigated. The addition of the p38 inhibitor had no effect on the stability of Cox-2 mRNA in either the wildtype (figure 5.11) or the knockout cells (figure 5.11). In both cases the decay rates remained similar.
As similarly described for Cox-2, actinomycin D chase experiments were used to determine the effect of BRF1 absence on IL-6 mRNA stability. Actinomycin D was added at time zero to either BRF1 knockout or wildtype MEFs that were stimulated with IL-1α for two hours. Decay of IL-6 mRNA was followed over a 75 minute time course at 15 minute intervals (figure 5.13). The measurements were made by qPCR and were all normalised against GAPDH. No differences in the decay rate between clone 619+/+ and clone 618-/- were measured. A slight difference was measured in the other set of clones, however, IL-6 mRNA in the knockout cells was less stable than that in the wildtype which is the inverse of what would be expected if BRF1 was regulating IL-6 mRNA stability.
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A 140 130 BRF1 +/+ 614 120 BRF1 -/- 611 110 100 90 80 70 60 50 40 30 20
COX-2/GAPDH % of t=0 10 0 0 10 20 30 40 50 60 70 80
Act D (minutes)
B 110 100 BRF1 +/+ 619 90 BRF1 -/- 618 80 70 60 50 40 30 20 10 COX-2/GAPDH % of t=0 0 0 10 20 30 40 50 60 70 80 Act D (minutes)
Figure 5.10: Cox-2 mRNA decays at the same rate in BRF+/+ and BRF1-/- MEFs. BRF1+/+ and BRF1-/- MEFs were stimulated for one hour with 20 ng/ml IL-1α, an unstimulated control was also included. At time zero 100 ng/ml actinomycin D was added and RNA was isolated every 15 minutes over a 75 minute period. RNA was quantified for ® Cox-2 and GAPDH using Taqman probes. Delta delta Ct analysis was applied to the data, and fold changes in Cox-2 mRNA expression were calculated in relation to a BRF1+/+ unstimulated control. Results are expressed as a percentage of the IL-1α stimulated control. All results are normalised to GAPDH. Error bars represent the standard error of the mean. (A) Clones 614+/+ versus 611-/- (N=3), (B) Clones 619+/+ versus 618-/- (N=3).
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A
140 130 BRF1 +/+ 614 120 110 BRF1 +/+ 614+SB 100 90 80 70 60 50 40 30 20 10 COX-2/GAPDH % of t=0 0 0 10 20 30 40 50 60 70 80 Act D (minutes)
B 120 110 BRF1 +/+ 619 100 BRF1 +/+ 619 + SB 90 80 70 60 50 40 30 20 10 COX-2/GAPDH % of t=0 0 0 10 20 30 40 50 60 70 80 Act D (minutes) Figure 5.11: Cox-2 mRNA decays at the same rate in BRF1+/+ MEFs regardless of p38 activity. BRF1+/+ MEFs were stimulated for one hour with 20 ng/ml IL-1α in the presence of 1 μM SB202190 or vehicle treated with DMSO. The rest of the experimental procedure and delta delta Ct analysis were carried out exactly as detailed in the legend for figure 5.10 (A) Clone 614+/+ (N=3). (B) Clone 619+/+ (N=3).
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A 125 BRF1 -/- 611
100 BRF1 -/- 611+SB
75
50
25
% t=0 of COX-2/GAPDH 0 0 10 20 30 40 50 60 70 80 Act D (minutes)
B 110 100 BRF1 -/- 618 90 BRF1 -/- 618 + SB 80 70 60 50 40 30 20 10
COX-2/GAPDH % of t=0 0 0 10 20 30 40 50 60 70 80 Act D (minutes)
Figure 5.12: Cox-2 mRNA decays at the same rate in BRF1-/- MEFs regardless of p38 activity. BRF1-/- MEFs were stimulated for one hour with 20 ng/ml IL-1α in the presence of 1 μM SB202190 or vehicle treated with DMSO. The rest of the experimental procedure and delta delta Ct analysis were carried out exactly as detailed in the legend for figure 5.10. (A) Clone 611-/- (N=3). (B) Clone 618-/- (N=3).
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The effect of p38 inhibition on IL-6 mRNA stability was also investigated. SB202190 was added at the same time as actinomycin D to the MEF culture medium. mRNA decay was then measured over 75 minutes in both the wildtype clones (figure 5.14) and in the knockout clones (figure 5.15). In neither case of the knockout or the wildtype was there a difference in the rate of IL-6 mRNA decay when the p38 pathway was blocked.
These results did not suggest a role for BRF1 in post-transcriptional regulation of either Cox-2 or IL-6. To be absolutely sure that differences in mRNA stability were not being overlooked due to artefactual effects of actinomycin D, further experiments were carried out using an alternative transcriptional inhibitor called 5,6-dichloro-1-β-D- ribofuranosylbenzimidazole (DRB). DRB and actinomycin D have different modes of action. Actinomycin D inhibits transcription in a non-specific manner by forming a stable complex with double stranded DNA thus inhibiting DNA-primed RNA synthesis. It can also cause single stranded breaks in DNA. DRB accentuates premature termination of transcription close to the promoter. It inhibits casein kinase ІІ dependent RNA polymerase ІІ transcription.
Taking clones 619+/+ and 618-/-, Cox-2 decay rates were measured using DRB as the transcriptional inhibitor (figure 5.16). Again as previously seen in experiments where actinomycin D was used, no obvious differences could be observed in the decay rates of Cox-2 between the knockout cells and the wildtype cells. As before the effect of adding the p38 inhibitor were assessed. Figure 5.17 shows wildtype cells (619+/+) and knockout cells (618-/-) stimulated for one hour with IL-1α followed by the addition of DRB with or without the p38 inhibitor SB202190. The result clearly showed that blocking the p38 pathway in conjunction with this alternative transcriptional inhibitor had no impact on the decay rates of Cox-2.
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A 110 100 BRF1 +/+ 614 90 BRF1 -/- 611 80 70 60 50 40 30 20
t=0 % of GAPDH IL6/ 10 0 0 10 20 30 40 50 60 70 80 Act D (minutes)
B 120 110 BRF1 +/+ 619 100 BRF1 -/- 618 90 80 70 60 50 40 30
IL6/GAPDH % t=0 20 10 0 0 10 20 30 40 50 60 70 80 Act D (minutes)
Figure 5.13: IL-6 mRNA decays at the same rate in BRF1+/+ and BRF-/- MEFs. The experimental procedure and delta delta Ct analysis were carried out exactly as detailed in the legend for figure 5.10 except that RNA was quantified for IL-6. (A) Clones 614+/+ versus 611-/- (N=3). (B) Clones 619+/+ versus 618-/- (N=2).
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A 120 110 BRF1 +/+ 614 100 BRF1 +/+ 614 + SB 90 80 70 60 50 40 30 20 IL6/GAPDH %IL6/GAPDH of t=0 10 0 0 10 20 30 40 50 60 70 80 Act D ( minutes)
B 130 120 BRF1 +/+ 619 110 BRF1 +/+ 619 + SB 100 90 80 70 60 50 40 30 20 IL6/GAPDH % of t=0 of % IL6/GAPDH 10 0 0 10 20 30 40 50 60 70 80 Act D (minutes)
Figure 5.14: IL-6 mRNA decays at the same rate in BRF1+/+ MEFs regardless of p38 activity. The experimental procedure and delta delta Ct analysis were carried out exactly as detailed in the legend for figure 5.11 except that RNA was quantified for IL-6. (A) Clone 614+/+ (N=3). (B) Clone 619+/+ (N=3).
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110 100 BRF1 -/- 611 90 BRF1 -/- 611 + SB 80 70 60 50 40 30 20
IL6/GAPDH % of t=0 10 0 0 10 20 30 40 50 60 70 80 Act D (minutes)
Figure 5.15: IL-6 mRNA decays at the same rate in BRF1-/- cells regardless of p38 activity. The experimental procedure and delta delta Ct analysis were carried out exactly as detailed in the legend for figure 5.11 except that RNA was quantified for IL-6. Results shown are for clone 611-/- only (N=3).
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120 110 BRF1 +/+ 619 100 BRF1 -/- 618 90 80 70 60 50 40 30 20 10 COX-2/GAPDH % of t=0 0 0 10 20 30 40 50 60 70 80 DRB (minutes)
Figure 5.16: Cox-2 mRNA decays at the same rate in BRF1-/- and BRF1+/+ MEFs, even when an alternative transcriptional inhibitor is used. BRF1+/+ and BRF1-/- MEFs were stimulated for one hour with 20 ng/ml IL-1α, an unstimulated control was also included. At time zero 100 ng/ml DRB was added and RNA was isolated every 15 minutes over a 75 ® minute period. RNA was quantified for Cox-2 and GAPDH using Taqman . Delta delta Ct analysis was applied to the data, and fold changes in Cox-2 mRNA expression were calculated in relation to a BRF1+/+ unstimulated control. Results are expressed as a percentage of the IL-1α stimulated control. All results are normalised to GAPDH. Error bars represent the standard error of the mean. Results shown are for clones 619+/+ and 618-/- only (N=3).
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A 120 110 BRF1 +/+ 619 100 BRF1 +/+ 619 + SB 90 80 70 60 50 40 30 20 10 COX-2/GAPDH % of t=0 0 0 10 20 30 40 50 60 70 80 DRB (minutes)
B 110 100 BRF1 -/- 618 90 BRF1 -/- 618 + SB 80 70 60 50 40 30 20 10 COX-2/GAPDH % of t=0 0 0 10 20 30 40 50 60 70 80 DRB (minutes)
Figure 5.17: Cox-2 mRNA decays at the same rate in BRF1+/+ and BRF1-/- MEFs regardless of p38 activity, even when an alternative transcriptional inhibitor is used. BRF1+/+ and BRF1-/- MEFs were stimulated for one hour with 20 ng/ml IL-1α in the presence of I μM SB202190 or vehicle treated with DMSO. An unstimulated control was also included. At time zero 100 ng/ml DRB was added and RNA was isolated every 15 minutes over a 75 minute period. RNA was quantified for Cox-2 and GAPDH using ® Taqman probes. Delta delta Ct analysis was applied to the data, and fold changes in mRNA expression were calculated in relation to a BRF1+/+ unstimulated control. Results
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are expressed as a percentage of the IL-1α stimulated control. All results are normalised to GAPDH. Error bars represent the standard error of the mean. (A) Clone 619+/+ (N=3), (B) Clone 618+/+ (N=3).
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5.6) Validation of primary transcript qPCR technique
5.6.1) Introduction Having discovered that BRF1 was not exerting post-transcriptional regulation on Cox-2 or IL-6, alternative mechanisms were considered. IL-6 protein was over-expressed in BRF1-/- cells by between three and six fold. IL-6 mRNA was over-expressed in these cells by between three and ten fold, depending on the time point and clones compared. Both the mRNA and the protein were elevated to similar degrees, therefore the absence of BRF1 does not appear to cause changes in the efficiency of translation of IL-6 mRNA, as was concluded in the case of VEGFA (Bell et al., 2006). Having considered mRNA stability and translational regulation as possible points of control, and ruled them out, transcriptional regulation was investigated. A new hypothesis was considered; the rate of Cox-2, IL-6 and KC transcription in is altered in BRF1-/- MEFs.
5.6.2) Primary transcript qPCR Conventionally, the methods used to measure transcription rates are very technically difficult. Nuclear run on assays are particularly hard assays to perform and require a large amount of radiation, making the technique an undesirable one to use. More recently a qPCR method known as primary transcript qPCR has been established which eliminates the requirement for the use of radioactive material. Primary transcript qPCR measures the amount of un-spliced or nascent mRNA in a sample whereas conventional PCR measures fully processed mRNA. This technique uses a set of primers where one of the primers is complementary to a region within an intron and the other primer is complementary to a region within an exon, therefore amplifying a region which spans an exon:intron boundary. Any product which is formed, should in theory, be nuclear mRNA. From this it is possible to make some conclusions about the rate of transcription for the gene of interest. Because this technique uses primers and SYBR green rather than the specific Taqman primer-probe system there are limitations. They include: • Amplification of genomic DNA. This is a risk as pre-spliced mRNA has the same sequence as genomic DNA which means that the primers are just as likely to anneal to the latter as well as the former. In
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addition to this SYBR green dye binds to double stranded nucleic acids and therefore cannot distinguish between RNA and DNA. • Non-specific amplification or mis-priming and amplification of contaminants. Mis-priming occurs when PCR products are made due to annealing of the primers to complementary, or partially complementary sequences on non-target DNAs. Another potential problem is that contaminating DNA may be amplified by the PCR and generate an artefactual signal. • Primer-dimer formation. This occurs when the primers are present in the wrong concentrations or have too much complementarity to one another. Production of primer-dimer can lower the amplification yield of the target region and again generate an artefactual signal that is not dependent on nascent nuclear pre-mRNA.
To ensure that these risks were kept to a minimum certain procedures can be followed. • A DNAse step should be included in the RNA purification procedure. • Inclusion of controls: Un-reverse transcribed controls and no template controls should be run alongside the samples of interest. Each RNA should undergo the amplification procedure alongside the cDNAs which were generated from them. Amplification occurring in these samples may be attributable to genomic DNA contamination. Depending on its relative abundance to the cDNA samples an assessment can be made as to whether the levels are high enough to interfere with overall results. In addition to this a no template control should be included which consists of all the components of the PCR reaction, but replacing the cDNA with water. Again, no amplification should occur in this sample. • Melting curves should be performed by the PCR machine. The melting curve is useful way of checking for contaminants, primer-dimers and mis- priming. After amplification the machine can be programmed to do a melt curve. The temperature is raised by a fraction of a degree and the change in fluorescence is measured. At the melting point, the two strands of DNA will separate and the fluorescence rapidly decreases. The software plots the rate of change of the relative
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fluorescence units (RFU) with time (T) (-d(RFU)/dT) on the Y-axis versus the temperature on the X-axis, and this will peak at the melting temperature (Tm). A primer-dimer will give a peak of different Tm. All curves should look similar, differences could be attributed to mis-priming or contamination. • Confirm PCR product specificity using an agarose gel. To confirm that the amplified products are the intended product they can be checked for size and run on an agarose gel. This can also be useful to check that only one product is amplified.
5.6.3) Optimising primers
To demonstrate the process of optimisation and verification of the specificity of the PCR process figures 5.18 and 5.19 illustrate this using some examples of the read outs that are generated by the real-time PCR machine.
Each set of primers used for PCR should be optimised, to make sure that the reaction is working to the maximum efficiency. The method used to do this is explained in detail in the materials and methods section. Briefly, each primer set is prepared in varying combinations of concentration and then a stock cDNA is added to each reaction. Each reaction has a corresponding control to which water is added instead of cDNA (no amplification should be observed in these samples). Figure 5.18 shows the traces from the PCR machine for each set of primers tested (samples in blue, controls in pink). The optimal volume of each primer per reaction was 0.6 μl/ 10 μl reaction (figure 5.18). In most cases no amplification is seen in the control samples which is as expected. If there was amplification this could be attributable to contamination of the primers themselves with nucleic acids or of the water used in the reaction. If the contaminating products are much less abundant than that amplified from the samples (i.e.: their Ct values are much higher) this would indicate that these primer sets would still be able to give an accurate result as the contamination is minimal.
5.6.4) Non-reverse transcribed controls and melting curves As previously discussed, a number of controls should be run alongside the samples to check the specificity of the PCR. Firstly, controls that contain un-reverse transcribed RNA should
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Figure 5.18: Optimisation of primer sets. Each primer set was optimised according to the recommendations from molecular probes (see materials and methods). Varying concentrations of primers were used to find the optimal combination (shown by the blue traces). The pink lines in each graph represent the controls. (A) IL-6 primary transcript primers (B) Cox-2 primary transcript primers (C) KC primary transcript primers (D) GAPDH primary transcript primers.
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go through the same processing as the samples of interest. Figure 5.19 shows selected samples to demonstrate the purpose of the controls. Graph A shows the PCR traces for IL-6 primary transcript; the turquoise trace represents unstimulated BRF1 wildtype cells and the pink line is its control; the black line represents unstimulated BRF1 knockout cells and the red line is its control. In the wildtype samples the Ct value was approximately 28 whereas in the knockout samples the Ct value was approximately 26. In theory no amplification should have been observed in the controls however there was some in the wildtype control, the Ct value of this was approximately 32. This did not have a significant effect on the overall outcome of the experiment because the contamination was minimal. When the Ct value increases by one the amount of starting cDNA decreases by a factor of two. In this case four doublings took place before the contaminant DNA was detected. In addition the un-reverse transcribed DNA was added to the PCR reaction at much higher concentration than the cDNA (approximately four times more concentrated). Taking these things into consideration we concluded that the contamination was minimal. Also the contamination was not observed in all samples suggesting that rather than genomic DNA contamination it could be a non-specific amplification, supported by the fact that the contaminant was not detected on the agarose gel (see below- section 5.6.5). Graph C shows the traces for the corresponding GAPDH measurements. The Ct value for all GAPDH in all samples was generally around 12 as it is an abundant transcript present in equal quantities in all samples. Again there was some amplification in some of the controls, as before this occurred at later cycles and should therefore not affect the overall result.
As well as the amplification traces, melt curves are shown (figure 5.19, graphs B and D). In the melt curve for IL-6 (figure 5.19B) the black and turquoise peaks are similar which is as expected, the significantly smaller pink peak is that of the contaminant. The GAPDH melt curve for the samples are again similar and help verify the purity of the product.
5.6.5) Verification of product using agarose gel Once the PCR had taken place, the products were run on an agarose gel (figure 5.19E). Products of approximately 250 bp were detected in all of the samples and either nothing or only a very faint band of the wrong size was detected in the control lanes, suggesting that
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Figure 5.19: verification of the specificity the SYBR green technique for measuring IL-6 primary transcript. (A) Shows amplification of IL-6 primary transcript in unstimulated 618+/+ (turquoise line) and its control (red line), unstimulated 619-/- (black line) and its control (pink line). (B) Shows the melt-curve of IL-6 products shown in A. (C) Shows amplification of GAPDH in same samples as in A. (D) Shows the melt-curve of GAPDH products of samples shown in C. (E) Shows the products on an agarose gel of the PCR shown in A and C.
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any contaminants detected were of different mobilities or were too low in abundance to detect and weren’t therefore genomic IL-6 or GAPDH, but non-specific contaminants. The fact that the contaminants are much lower in abundance means that it is unlikely that they would be able to cause distortion of the overall results.
5.6.6) IL-6, Cox-2 and KC Primary transcript qPCR As discussed primary transcript levels were measured in both sets of the BRF1-/- and BRF1+/+ clones. Figure 5.20 shows the results for Cox-2. BRF1-/- and BRF1+/+ cells were stimulated with IL-1α for up to one hour and RNA was harvested (DNase step included). cDNA was prepared and qPCR was performed using primers designed to detect Cox-2 primary transcript and GAPDH steady state mRNA. In addition to the primary transcript, the corresponding steady state mRNA levels were also measured (figure 5.20- graphs C and D) also by using the SYBR green method. In control reactions where reverse transcriptase was omitted, no signal was generated, confirming that the assay detects nuclear pre-mRNA transcript rather than genomic DNA contamination. As measured by this method, basal Cox-2 transcription appeared to be higher in BRF1-/- clones, but this difference was not found to be statistically significant. Cox-2 transcription was rapidly increased by IL-1α, peaking at 30 or 60 minutes. As expected, steady state Cox-2 mRNA levels responded with a clear lag, and still appeared to be increasing at the one hour time point. At both steady state mRNA and primary transcript levels, Cox-2 was over-expressed by BRF1-/- cells. In the case of the primary transcript, differences were statistically significant at most time points. In the case of the steady state mRNA, differences were statistically significant at later time points only. These results confirm the previous Cox-2 steady state results (figure 5.7). The similar over-expression of Cox-2 at primary transcript and steady state levels strongly suggests that absence of BRF1 results in disregulation of Cox-2 at the transcriptional level.
KC primary transcript was measured using the same method as for Cox-2. Both primary transcript and steady state mRNAs were measured, and the results are shown in figure 5.21. Primary transcript levels were inducible by IL-1α (up to 200 fold seen in clone 619+/+), however there was no significant difference in the levels of KC primary transcript between the knockout and the wildtype cells. This was also true of the steady state mRNA levels
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which are shown in the lower two graphs. These data are consistent with the observation that KC protein is not over-expressed by BRF1-/- cells. However there is some inconsistency with previous experiments that showed over-expression of KC mRNA by BRF1-/- cells one hour after stimulation with IL-1α.
Figure 5.22 shows the results for IL-6. As previously for Cox-2 and KC, BRF1-/- and BRF1+/+ cells were stimulated with IL-1α for up to one hour and RNA was harvested (DNAase step included). cDNA was prepared and qPCR using primers designed to detect IL-6 primary transcript and GAPDH steady state was performed. In addition to the primary transcript, the corresponding steady state mRNA levels were also measured (figure 5.22- graphs C and D) again using the SYBR green method. Over the 60 minute time course, IL-6 primary transcript levels increased in both the BRF1+/+ and BRF1-/- MEFs. This increase was greatest in the knockout cells. At each time point following IL-1α treatment there was an extremely significant (p value <0.001) difference in IL-6 primary transcript mRNA between the knockout cells and wildtype cells. Steady state IL-6 levels followed a similar pattern to the primary transcript; steadily increasing over time, with much higher levels in the knockout cells than in the wildtype (as seen earlier in figure 5.9). The over- expression of steady state IL-6 mRNA was found to be extremely significant (p value <0.001) after 30 and 60 minutes of IL-1α treatment. No significant difference was measured in primary transcript or steady state mRNA in unstimulated samples. As with Cox-2 this result suggests that the absence of BRF1 causes disregulation of IL-6 gene expression at the transcriptional level.
For each of the three figures displaying cytokine primary transcript expression, an inset graph has been included to compare the four clones. The inset graph displays the primary transcript mRNA measurement from unstimulated cells and IL-1α stimulated cells (time point varies depending on cytokine). As previously, the purpose of this is to conclusively show that the pairing of the clones has no affect on the outcome of the experiments. To summarise, the transcription rate of IL-6 and Cox-2 but not KC is higher in the BRF1 knockout cells that the BRF1 wildtype MEFs.
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An important point to note is that these figures in fold change are calculated relative to the unstimulated wildtype sample in each experiment. For example, fold changes in IL-6 primary transcript in BRF1-/- clone 618 are relative to the BRF1+/+ clone 619 unstimulated sample. If the wildtype and knockout clones are analysed separately and fold changes calculated from their own unstimulated control then the fold changes are actually quite similar between the knockout and the wildtype. In other words the knockout clones 618 and 611 have a higher basal rate of transcription but the fold response to IL-1α is not actually enhanced. Table 5.1 displays the fold changes of each clone relative to its own unstimulated sample for each gene in response to IL-1α. Taking the Cox-2 data first, the difference in fold changes between BRF1-/- 618 and BRF1+/+ 619 has been abolished by this alternative analysis. The figures for clones 611-/- and 614+/+ do not demonstrate this as clearly but the difference between the wildtype and knockout is reduced by this alternative method. Any significant difference in IL-6 transcription rate between BRF1-/- and BRF+/+ is also lost when each clone is expressed relative to its own unstimulated control.
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A B BRF1 +/+ 614 BRF1 +/+ 619
BRF1 -/- 611 BRF1 -/- 618 *** 13 *** 35 *** 12 *** 11 30 10 9 25 ** 8 7 20 6 ns 5 15 4 3 ns 10 2 ns 1 5
COX-2 PT/GAPDHmRNA 0 COX-2 PT/ GAPDH mRNA GAPDH PT/ COX-2 0 0 15 30 60 60' (-ve control) 0 15' 30' 60' 60' (-ve control) IL-1 (minutes) IL-1 (minutes) C D BRF1 +/+ 614 BRF1 +/+ 619 BRF1 -/- 611 BRF1 -/- 618 *** 20 *** 17.5 15.0 15 12.5 *** *** 10.0 10 7.5 ns ns 5 ns 5.0 ns 2.5 COX-2/mRNA GAPDH COX-2/ GAPDH mRNA 0 0.0 0 15' 30' 60' 60' (-ve control) 0 15' 30' 60' 60' (-ve control) IL-1 (minutes) IL-1 (minutes) E unstimulated IL-1 (15 minutes) 30
20
10
COX-2 PT/ GAPDH 0 614 619 611 618 wildtype BRF1 KO
Figure 5.20: Cox-2 primary transcript mRNA is over-expressed in BRF1-/- cells in comparison to BRF1+/+ cells in response to IL-1α. BRF1+/+ and BRF1-/- MEFs were stimulated with 20 ng/ml IL-1α for the indicated times. RNA was isolated and a cDNA template was generated. Using primers and SYBR green dye; Cox-2 primary transcript,
Cox-2 steady state and GAPDH steady state mRNAs were quantified. Delta delta Ct analysis was used to obtain fold changes in either Cox-2 primary transcript or Cox-2 steady state mRNA normalised to GAPDH steady state mRNA. Error bars represent the standard
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error of the mean. On each graph the significance of the difference in Cox-2 primary transcript mRNA expression between the knockout and the wildtype cells is shown at all time points. Significance was calculated using a one way ANOVA test followed by Bonferroni’s multiple comparison test. ns= p value of >0.05 (not significant), *= p value of 0.01 to 0.05 (significant), **= p value of 0.001 to 0.01 (very significant), ***= p value of <0.001 (extremely significant). (A) Cox-2 primary transcript in clones 614+/+ and 611-/- (N=3). (B) Cox-2 primary transcript in clones 619+/+ and 618-/- (N=3). (C) Cox-2 steady state in clones 614+/+ and 611-/- (N=3). (D) Cox-2 primary transcript in clones 619+/+ and 618-/- (N=3). (E) A graph to show that the arbitrary pairing of the clones does not affect the overall conclusions.
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A B BRF1 +/+ 614 BRF1 +/+ 619 BRF1 -/- 611 BRF1 -/- 618 ns ns 200 250
150 200 ns ns 150 ns 100 ns 100 50 50 ns ns KC PT/ GAPDH mRNA GAPDH PT/ KC KC PT/ GAPDH mRNA 0 0 0 15' 30' 60' 60' (-ve control) 0 15' 30' 60' 60' (-ve control) IL-1 (minutes) IL-1 (minutes)
C D BRF1 +/+ 614 BRF1 +/+ 619 BRF1 -/- 611 BRF1 -/- 618 ns ns 175 250 150 200 125 ns ns 100 150 75 100 ns 50 ns
KC/ GAPDH mRNA 25 50 ns mRNAKC/ GAPDH ns 0 0 0' 15' 30' 60' (-ve control) 0' 15' 30' 60' 60' (-ve control) IL-1 (minutes) IL-1 (minutes)
E unstimulated IL-1 30 minutes 250 200 150 100
KC PT/GAPDH 50
0 614 619 611 619 wildtype BRF1 KO
Figure 5.21: KC primary transcript mRNA is expressed in similar amounts between BRF1+/+ and BRF1-/- MEFs in response to IL-1α. The experimental procedure and statistical analysis were carried out exactly as detailed in the legend for figure 5.20 except RNA was quantified for KC. (A) KC primary transcript in clones 614+/+ and 611-/- (N=3). (B) KC primary transcript in clones 619+/+ and 618-/- (N=3). (C) KC steady state in clones 614+/+ and 611-/- (N=3). (D) KC primary transcript in clones 619+/+ and 618-/- (N=3). (E) A graph to show that the arbitrary pairing of the clones does not affect the overall conclusions.
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A B BRF1 +/+ 614 BRF1 +/+ 619 BRF1 -/- 611 BRF1 -/- 618 *** *** 125 90 80 100 70 60 *** 75 *** 50 *** 40 ** 50 30 ns 20 25 ns 10 IL-6 PT/GAPDH mRNA PT/GAPDH IL-6 IL-6 PT/ GAPDH mRNA GAPDH PT/ IL-6 0 0 0 15 30 60 60 (-ve control) 0 15' 30' 60' 60' (-ve control) IL-1 (minutes) IL-1 (minutes)
C BRF1 +/+ 614 D BRF1 +/+ 619 BRF1 -/- 611 *** BRF1 -/- 618 150 *** 120 110 100 100 90 *** 80 70 *** 60 ns 50 50 ns 40 ns 30
IL-6/ GAPDH mRNA GAPDH IL-6/ 20 IL-6/ GAPDH mRNA ns 10 0 0 0 15' 30' 60' 60' (-ve control) 0 15' 30' 60' 60' (-ve control) IL-1 (minutes) IL-1 (minutes) E unstimulated IL-1 (1 hour)
125
100
75 50
IL-6 PT/ GAPDH 25
0 614. 619 611 618 wildtype BRF1 KO
Figure 5.22: IL-6 primary transcript is over-expressed in BRF1-/- MEFs in comparison to BRF1+/+ MEFs in response to IL-1α. The experimental procedure and statistical analysis was carried out exactly as shown in legend for figure 5.20 except RNA was quantified for IL-6. (A) IL-6 primary transcript in clones 614+/+ and 611-/- (N=3). (B) IL-6 primary transcript in clones 619+/+ and 618-/- (N=3). (C) IL-6 steady state in clones 614+/+ and 611-/- (N=4). (D) IL-6 primary transcript in clones 619+/+ and 618-/- (N=3). (E) A graph to show that the arbitrary pairing of the clones does not affect the overall conclusions.
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Gene Time 611-/- 614+/+ 618-/- 619+/+ (minutes) Cox-2 0 1.0 1.0 1.0 1.0 15 5.5 11.6 7.6 8.1 30 5.9 12.7 7.5 6.1 60 5.8 9.2 5.0 3.6 KC 0 1.0 1.0 1.0 1.0 15 55.7 44.8 94.7 52.7 30 103.9 56.8 157.0 99.9 60 147.1 71.8 70.9 53.0 IL-6 0 1.0 1.0 1.0 1.0 15 3.8 4.1 10.4 9.0 30 3.8 3.7 6.5 7.6 60 13.4 9.1 19.8 25.3 Table 5.1: Alternative normalisation of Cox-2, KC and IL-6 primary transcript levels. Fold changes in primary transcript levels were calculated relative to the unstimulated control of the same cell line.
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5.6.7) Normalising to GAPDH primary transcript mRNA In the experiments in the previous section, data were normalised to GAPDH steady state. As primary transcript was being measured it is arguable that a nascent transcript would be preferable to a mature transcript as a normalising control for these measurements. Therefore I generated and validated probes for the measurement of GAPDH primary transcripts, and examined the outcome of different methods of normalisation.
Figure 5.23 shows experiments where MEFs were stimulated with IL-1α for time points ranging over six hours. In the same way as before, RNA was harvested and cDNA prepared. Primary transcript PCR was performed with primers to GAPDH primary transcript mRNA, GAPDH steady state mRNA and to IL-6 primary transcript mRNAs.
Graphs A and B show IL-6 primary transcript normalised to GAPDH steady state which is how data in the previous section was presented. In agreement with those previous data, there is a marked increase in IL-6 mRNA primary transcript in the knockout cells in comparison to the wildtype cells. The peak of this expression is after one hour of stimulation with IL-1α.
Graphs C and D show the same data normalized to GAPDH primary transcript. Comparing this with graph above, the pattern of expression and the difference between the knockout cells and the wildtype is either the same or possibly more pronounced. The purpose of these experiments was to demonstrate that normalising to GAPDH steady state mRNA was giving accurate results.
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A B BRF1 +/+ 614 BRF1 +/+ 619 BRF1 -/- 611 BRF1 -/- 618
110 200 100 90 80 150 70 60 50 100 40 30 50 20 10 0
Fold change IL-6Fold change PT/GAPDH 0 Fold change IL-6 PT/GAPDH IL-6 change Fold 0 30 60 120 240 360 0 30 60 120 240 360 IL-1 (minutes) IL-1 (minutes)
C D BRF1 +/+ 614 BRF1 +/+ 619 BRF1 -/- 611 BRF1 -/- 618 250 350 300 200 250 150 200 100 150 100 50 50 0 0 0 30 60 120 240 360 0 30 60 120 240 360 Fold change IL-6 PT/GAPDH PT PT/GAPDH IL-6 change Fold Fold change IL-6 PT/GAPDH PT PT/GAPDH IL-6 change Fold IL-1 (minutes) IL-1 (minutes)
Figure 5.23: Normalisation of data using GAPDH primary transcript. BRF1+/+ and BRF1-/- MEFs were treated with 20 ng/ml IL-1α for the indicated times. RNA was isolated and a cDNA template was generated. cDNA was quantified for GAPDH primary transcript,
GAPDH steady state, and IL-6 primary transcript. Delta delta Ct analysis was the used to obtain fold changes in relation to the unstimulated BRF1+/+ control in: (A and B) IL-6 primary transcript normalised to GAPDH steady state, (B and C) IL-6 primary transcript normalised to GAPDH primary transcript. In all cases N=1.
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5.7) Does BRF1 function as a transcription factor or does it regulate expression of another transcription factor? The previous section shows a clear difference in basal transcription rates of IL-6 and Cox-2 between BRF1+/+ and BRF1-/- cells. The next step was to try and establish the exact mechanism. Unfortunately due to time limitations this has been difficult to complete. One of the most important questions to try and answer was whether BRF1 itself is acting as a transcription factor which negatively regulates IL-6 and Cox-2 or whether it is mediating its effects through another independent factor, in other words is the effect direct or indirect?
Knowing that IL-6 and Cox-2 transcripts but not KC were up-regulated in BRF1 knockout cells, the literature was searched for candidate transcription factors that had been linked with IL-6 and Cox-2 but not KC. Several regulatory elements such as multiple responsive element (MRE), cAMP response element (CRE) and binding sites for the transcription factors AP1, 5’CEBPβ, 3’CEBPβ, and NF-κB have been identified within the human IL-6 promoter region (Akira et al., 1993). Independent groups have studied IL-6 activation, collectively and found these regulatory elements to be responsible for IL-6 gene expression in a cell type-specific and stimulus-specific manner. Studies have shown a direct interaction of the IL-6 promoter with various transcription factors, for example various groups showed by EMSA that NF-κB, CEBPβ and AP1 are able to bind to the promoter region of IL-6 and regulate it (Grassl et al., 1999; Miyazawa et al., 1998). Other groups have mutagenised the AP-1, MRE, CEBPβ and NF-κB sites and found that this affected IL-6 transcription. The extent of this effect was dependent on the stimulus (Dendorfer et al., 1994). Supershift analysis has demonstrated the affinity of several transcription factors for the IL-6 promoter region including JunB, JunD c-Foc, Fra-1,CREB-1, ATF-2, NF-κB p50, p52, p65 and CEBP-δ (Grassl et al., 1999). Cox-2 had also been shown to contain CRE, and binding sites for CEBPβ and NF-κB within its promoter (Roshak et al., 1996; Yamamoto et al., 1995). Like IL-6, NF-κB has been shown to bind to two sites within the Cox-2 promoter, by EMSA. Supershift analysis revealed that the binding, was in part, due to the p65-p50 heterodimer and the p50 homodimer (Crofford et al., 1997). NF-κB and CEBP/β are the two most widely implicated transcription factors in the regulation of these genes, neither has been shown to have any affect on KC.
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5.7.1) Do BRF1-/- cells up-regulate IL-6 gene transcription in an NFκB and HAT dependent manner? The prominence of NFκB as a regulatory factor in IL-6 and Cox-2 gene transcription prompted a set of speculative experiments. Histone acetylation may influence transcription in more than one way. Firstly by disrupting the higher order chromatin structure and allowing greater access to the DNA sequence for the transcription apparatus and its regulators (reviewed by Spencer and Davie 1999 (Spencer and Davie, 1999)). Secondly acetylation of the histone may disrupt the nucleosome structure by neutralizing positively charged lysines thus decreasing their affinity for DNA or neighboring nucleosomes (Grunstein, 1997). Finally acetylation may promote or repress interactions with specific transcription factors (Davie and Spencer, 1999). Acetylation is facilitated by histone acetyltransferases (HATs) and can be reversed by histone deacetylases (HDACs). Recently a study by Berghe et al. describes NFκB to be an essential mediator of TNF induced IL-6 transcription which was dependent on the transcriptional co-activator CBP/p300 and HAT activity. They observed a distinct increase in IL-6 gene activation in response to sustained histone-4 acetylation activity following treatment with trichostatin A (TSA), a potent inhibitor of HDACs (Vanden Berghe et al., 1999).
Based on this information and the knowledge that NFκB is commonly involved in IL-6 gene regulation I investigated the possibility that the difference in IL-6 primary transcript expression between BRF1+/+ and BRF1-/- cells was due to an NFκB dependent mechanism. I consistently observed an over-expression of IL-6 primary transcript in BRF1-/- cells at time points of less than one hour. This may be a reflection of the fact that the absence of BRF1 causes chromatin remodeling, poising it for transcriptional induction. If this was the case then the addition of TSA could, in theory, elevate the rate of IL-6 and Cox-2 transcription in the wildtype cells to a level approximately equal to that observed in the knockout cells.
Figure 5.24 shows Cox-2 primary transcript levels in wildtype and knockout cells that have been left unstimulated, treated for one hour with IL-1α or TSA or treated for one hour with TSA and IL-1α. Figures 5.25 and 5.26 show the same experiment previously described but the primary transcript measurements are for KC and IL-6 respectively. In all three
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experiments there was a sharp induction of gene expression after one hour of IL-1α treatment and a significant over-expression of the measured gene in the BRF1 null cells. Again in all three cases the addition of TSA caused an overall suppression of primary transcript. The observed effect of TSA addition was the same between wildtype and knockout cells. However, the effect of TSA addition differed between genes; KC and Cox-2 seemed to be less responsive to TSA. IL-6 primary transcript inhibition by TSA was always extremely significant whereas Cox-2 and KC gene expression was more variable and less sensitive to TSA.
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BRF1+/+ 619 ns
-/- BRF1 618 * ** 10.0
7.5
5.0
2.5
Cox-2/ GAPDH mRNA GAPDH Cox-2/ 0.0
IL-1 1 h 1 h TSA
unstimulated TSA + IL-1 1 h Figure 5.24: Effect of trichostatin A (TSA) on Cox-2 primary transcript mRNA expression in BRF1+/+ and BRF1-/- MEFs. BRF1+/+ and BRF1-/- MEFs were either left unstimulated or were stimulated with 20 ng/ml IL-1α or treated with 100 ng/ml TSA alone or with 20 ng/ml IL-1-α plus 100 ng/ml TSA for one hour. RNA was isolated and a cDNA template was generated. Using primers and SYBR green dye; Cox-2 primary transcript and
GAPDH steady state mRNAs were quantified. Delta delta Ct analysis was used to obtain fold changes in Cox-2 primary transcript mRNA normalised to GAPDH steady state mRNA. The experiment was performed three times. Within each experiment triplicate measurements of each experimental point were made. Error bars represent the standard error of the mean for three experiments. The significance of the TSA effect is shown in the knockout and the wildtype MEFs and the significance of the difference in Cox-2 production in response to IL-1α between the knockout and wildtype MEFs is also shown. Significance was calculated using a one way ANOVA test followed by Bonferroni’s multiple comparison test: ns= p value of >0.05 (not significant), *= p value of 0.01 to 0.05
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(significant), **= p value of 0.001 to 0.01 (very significant), ***= p value of <0.001 (extremely significant).
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A *** BRF1 +/+ 614
BRF1 -/- 611 * *** 800 700 600 500 400 300 200
KC/ GAPDH mRNA 100 0
IL-1 1 h 1 IL-1 TSA 1 h
unstimulated
1 h IL-1 + TSA B
BRF1 +/+ 619 *** BRF1 -/- 618 ** *** 350 300 250 200 150 100
KC/ mRNA GAPDH 50 0
IL-1 1 h TSA 1h
unstimulated IL-1 1 + h TSA
Figure 5.25: Effect of TSA on KC primary transcript mRNA expression in BRF1+/+ and BRF1-/- MEFs. The experimental procedure and statistical analysis were carried out exactly as detailed in the legend for figure 5.24 except KC primary transcript mRNA was measured. (A) Clone 614+/+ versus 611-/- (N=3), (B) 619+/+ versus 618-/- (N=3).
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A *** BRF1 +/+ 614 BRF1 -/- 611 *** ** 75
50
25
mRNA GAPDH IL-6/ 0
60' IL-1 TSA 1h TSA + IL-1 + TSA
unstimulated
B BRF1 +/+ 619 *** BRF1 -/- 618 *** *** 110 100 90 80 70 60 50 40 30 20 IL-6/ GAPDH mRNA 10 0
IL-1 60' IL-1 TSA 1 h
unstimulated TSA + IL-1 60' IL-1 TSA +
Figure 5.26: Effect of TSA on IL-6 primary transcript mRNA expression in BRF1+/+ and BRF1-/- MEFs. The experimental procedure and statistical analysis were carried out exactly as detailed in the legend for figure 5.24 except IL-6 primary transcript mRNA was measured. (A) Clone 614+/+ versus 611-/- (N=3), (B) 619+/+ versus 618-/- (N=3)
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5.7.2) Is BRF1 a direct or indirect regulator of IL-6 gene expression? To address the question of a direct involvement for BRF1 in IL-6 and Cox-2 gene expression, a blot for the Zfp36 proteins themselves was included (figure 5.27A). If BRF1 is acting as a transcription factor to directly regulate IL-6 transcription, it has to be present in the nucleus. IL-1α stimulated BRF1-/- and BRF1+/+ MEFs were separated in to a cytoplasmic containing fraction and a nucleus containing fraction. The quality of the fractionation is demonstrated by the western blots for histone, which is exclusively nuclear and tubulin, which is exclusively cytoplasmic. Clearly there is no BRF1 present in the knockout cells in either the nuclear or the cytoplasmic fractions. In the wildtype cells BRF1 is present in both the cytoplasmic and nuclear compartments. BRF2 is present in much higher quantities in the cytoplasm of the wildtype cells and is virtually non-existent in the nuclear fraction. By contrast the knockout cells have comparable levels of cytoplasmic BRF2 to the wildtype but nuclear BRF2 is much more abundant in these cells. This supports earlier observations where whole cell lysates were used and slightly more BRF2 in the BRF1-/- cells was detected.
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Figure 5.27: Sub-cellular fractionation of MEFs. MEFs were stimulated with 20 ng/ml IL-1α for the indicated times, nuclear and cytoplasmic extracts were prepared. Protein was separated by SDS PAGE and the transferred on to PVDF membrane. Western blots are shown for (A) SB2/31.4 for Zfp36 proteins, (B) tubulin, (C) histone.
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5.7.3) Transcription factor analysis To further investigate the possibility of differential transcription factor expression between the BRF1+/+ and BRF1-/- cells we employed a commercial service (Marligen) to assess the expression of 50 transcription factors in BRF1+/+ and BRF1-/- MEFs. Briefly, nuclear lysates are prepared and allowed to bind to biotinylated, double-stranded oligonucleotide probes containing consensus transcription factor binding sites. Unbound probes are removed, then transcription factor-bound probes are detected and quantified using Luminex technology. Importantly this procedure will not discriminate between different proteins that bind to the same oligonucleotide probe. For example different combinations of Fos and Jun proteins may give similar signals from the probe that contains an AP1 consensus sequence.
A higher basal rate of transcription of IL-6 and COX-2 was observed in BRF1-/- cells, therefore I elected to analyse expression of transcription factors in the absence of an IL-1 stimulus. Four BRF1+/+ nuclear extracts (two 614 and two 619) and four BRF1-/- nuclear extracts (two 611 and two 618) were analysed. Each possible pair wise comparison of wildtype versus knockout cell was performed. For each comparison transcription factor abundances in BRF1+/+ and BRF1-/- cells were plotted against each other and a best-fit regression line was calculated. Two examples are shown in Figures 5.28A and 5.28B. In every case the slope of the best-fit line was close to 1, indicating that the extracts were of comparable quality and that there were few major differences in transcription factor abundance. Factors that fall below the line are under-expressed in BRF1-/- cells, whereas factors that fall above the line are over-expressed. For each comparison the best-fit line was used to calculate the abundance of each individual transcription factor in the BRF1-/- cells as a percentage of its predicted abundance. Means and standard deviations of these values were calculated and plotted (Figure 5.29). Transcription factors that deviated from 100% by more than three standard deviations were considered to be significantly under- or over- expressed (coloured red in Figure 5.29). Three transcription factors (NF-κB, MEF2 and octamer) were significantly under-expressed by BRF1-/- cells, whereas three factors (AP-2, hypermethylated in cancer (HIC)-1 and PMA responsive element (TRE)-AP-1) were over- expressed in BRF1-/- cells.
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Figure 5.28: Differences in transcription factor expression between BRF1+/+ and BRF1-/- MEFs. Each possible pair wise comparison of wildtype versus knockout cell was examined. For each comparison transcription factor abundances in BRF1-/- and BRF1+/+ cells were plotted against each other and a best-fit regression line was calculated. (A) BRF1+/+ 614 versus BRF1-/- 611, (B) BRF1+/+ 619 versus BRF1-/- 618.
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Figure 5.29: Percentage expression of each transcription factor in BRF1-/- MEFs in comparison to its predicted abundance. For each wildtype and knockout comparison the best-fit line was used to calculate the abundance of each individual transcription factor in the BRF1-/- cells as a percentage of its predicted abundance. Mean values were calculated and plotted on the graph above and standard deviations are represented by the error bars. Transcription factors that deviated from 100% by more than three standard deviations were considered to be significantly under- or over-expressed (indicated in red).
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5.8) Summary and Discussion Assessment of the expression of the Zfp36 proteins in the wildtype MEFs that have been the focus of the investigations in this chapter show that they express BRF1, BRF2 and possibly TTP. BRF2 is easily detectable in the BRF1-/- MEFs and as expected BRF1 is undetectable in these cells. The expression of BRF1 and BRF2 is partially dependent on p38 activity.
TTP has not been detected in either the wildtype or the knockout cells but its presence cannot be categorically ruled out in either cell line. The presence of TTP was not extensively investigated with TTP specific antibodies, however it was not detectable in BRF1-/- cells with the SB1/30.13 rat monoclonal antibody. This antibody readily detects relatively low levels of TTP, therefore if TTP was present in these cells it would be reasonable to expect the detection of epitopes of the corresponding size to TTP in figure 5.1. This is contrary to the findings of Lai et al. 2006 who used TTP expressing MEFs in comparison with TTP-/- MEFs in a micro-array experiment to identify novel TTP targets (Lai et al., 2006). Lai et al. showed that TTP is easily detectable following stimulation with foetal bovine serum (FBS) (Lai et al., 2006). This discrepancy could be accounted for by the difference in the immortalisation procedures between the two different MEF cell lines. Lai et al. use the NIH method whereas the cells used in this chapter (provided by Bell et al.) were immortalised using the SV40 large T antigen. SV40 large T antigen is an oncoprotein that immortalises cells by perturbation of the retinoblastoma and p53 tumour suppressor proteins. It can also bind to p300 and CBP which are transcriptional co- activators (Ali and DeCaprio, 2001). Following transfection, SV40 large T antigen transforms the cell and it enters into an unregulated proliferation loop. The NIH (or 3T3) protocol differs, instead the cells are passaged continuously under normoxic conditions until they reach senescence. Prior to senescence the cells proliferate rapidly but as they approach senescence, growth slows until little or no growth is observed. This usually occurs between passages 10 and 25. Eventually a subset of cells will spontaneously overcome senescence and begin proliferation again. These immortal cultures will continue to divide indefinitely. Sometimes the immortalisation process can alter the characteristics of the cells and these different methods may do this in different ways. Therefore one
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explanation for the lack of TTP in these cells but not in other MEFs could be due to their transformation using SV40 large T antigen. Further experiments could determine the presence of TTP in these cells. Loading increased amounts of protein onto SDS PAGE gels and then attempting western blots with TTP specific antibodies may increase the chances of detection. Another approach would be to concentrate TTP protein by immunoprecipitation from a large volume of cellular material using a TTP specific antibody and then perform western blots.
Both BRF1 and BRF2 accumulate in BRF1+/+ MEFs and BRF2 accumulates in BRF1-/- MEFs in response to IL-1α. Simultaneous treatment with SB202190 reduces their expression indicating that their expression depends partially on the activity of p38. These observations reinforce data shown in chapters 3 and 4. In chapter 3 several cells lines are shown to express Zfp36 proteins induced by inflammatory stimuli. Data in chapter 4 also show that BRF1 and BRF2 expression can be attenuated by up to approximately 50% following the inhibition of p38 activity.
At present the regulation of the Zfp36 proteins themselves is something which is not fully understood. We know from work in our lab and from others that these proteins are heavily phosphorylated (Cao et al., 2006; Chrestensen et al., 2004). The kinases that are responsible for these phosphorylations and the functional role of each one are still being pieced together. Again, as with many other aspects of the studies in to this group of proteins, far more is known about TTP than BRF1 or BRF2 phosphorylation and the consequences of these modifications on their activity, expression and localisation within the cell.
IL-1α increases BRF1 and to a lesser extent BRF2 proteins in several cell lines, however there is not a corresponding increase in mRNA (observations from chapter 3). By contrast TTP is inducible at the protein and transcript levels. TTP mRNA expression is dependent on MK2 which is a downstream kinase of p38 (Mahtani et al., 2001; Tchen et al., 2004). BRF1 and BRF2 protein expression is also at least in some part dependent on p38 activity. PKB, a kinase that has been shown to stabilise mRNAs via its signalling cascade, phosphorylates BRF1 (Benjamin et al., 2006; Schmidlin et al., 2004). Benjamin et al.
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showed that BRF1 protein stabilises upon phosphorylation of serines 92 and 203 by PKB. This was confirmed by the observation that BRF1 protein is destabilised in PKB-/- cells (Benjamin et al., 2006). Recently published data show that MK2 can also phosphorylate BRF1 on three serine residues; 54, 92 and 203 and on another unidentified site in its C- terminus (Maitra et al., 2008). However the data only link these phosphorylations to BRF1 mediated decay activity and not its expression. Maitra et al. went on to show that MK2 can phosphorylate serines 92 and 203 through PKB and predict that these pathways probably target BRF1 both independently and in parallel to regulate BRF1 ARE mediated decay. To investigate whether MK2 phosphorylates and stabilises BRF1 further experiments would need to be carried out. Cycloheximide could be added to cells in the absence or the presence of a p38 inhibitor. This would determine whether blockade of p38 causes the disappearance of BRF1 protein in the absence of ongoing protein synthesis. Also the use of an MK2-/- mouse would help identify a role for MK2 in the regulation of BRF1 protein and mRNA stability.
The investigation into Cox-2 expression yielded some perplexing results. The seemingly constitutive expression of Cox-2 protein but inducible mRNA provokes many questions. It may simply be that the band detected in figure 5.4 is not Cox-2. The antibody used in these experiments may be detecting a non-specific epitope of a similar size to the one which is expected. Alternatively it could be that Cox-2 is actually constitutively expressed in these cells. Although it is generally considered an inducible gene there have been cases where this is not so; Cox-2 has been shown to be constitutively expressed in the brain (Yamagata et al., 1993), testes (Simmons et al., 1991), tracheal epithelia (Walenga et al., 1996) and macula densa in the kidney (Harris et al., 1994). To confirm that the detected band is Cox- 2, western blotting could be attempted using an alternative antibody. If an alternative antibody failed to give conclusive results an ELISA which would measure prostaglandin E2
(PGE2) could be used. PGE2 is the product of the reaction that Cox-2 catalyses. It is therefore an indirect measurement of Cox-2 abundance. ELISAs for PGE2 are commonly used to gain quantitative measurements of this protein.
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As previously mentioned in conjunction with TTP expression, the immortalisation process with SV40 large T antigen may have altered some of the cellular processes resulting in artifacts such as unusual expression of Cox-2. Cox-2 up-regulation in several cell types transformed with oncogenic Ras has been documented (Heasley et al., 1997; Sheng et al., 1997; Sheng et al., 1998; Subbaramaiah et al., 1996). SV40 large T antigen, also an oncogene may have similar effects. As previously discussed, SV40 large T antigen is known to bind the transcriptional co-activators p300 and CBP. p300 is the predominant co- activator that is essential for Cox-2 transcriptional activation by pro-inflammatory mediators (Deng et al., 2004). Perhaps the interaction of SV40 large T antigen and p300 causes the basal up-regulation of Cox-2. Another study shows that SV40 large T antigen can interact with multiple components of the transcription factor complex (Gruda et al., 1993). In the literature it is clear that the SV40 large T antigen interacts with the cellular transcriptional machinery which may ultimately result in the constitutive expression of Cox-2 protein. However in these cells Cox-2 mRNA is inducible and the protein is constitutively expressed suggesting that the transcriptional process is unaffected by SV40 but rather the translational machinery.
Several studies have documented the p38 mediated stabilisation of Cox-2 mRNA. Contrary to this actinomycin D chase experiments in figure 5.12 show that Cox-2 mRNA stability in BRF1-/- MEFs is unaffected by the presence of the p38 inhibitor (SB202190). Artefactual stabilisation by actinomycin D was ruled out by the use of the alternative transcriptional inhibitor DRB. The Cox-2 chase experiments shown in figures 5.10-5.12 and 5.16-5.17 and were carried out following one hour of stimulation with IL-1α. Similar experiments were also performed using cells stimulated for two hours (data not shown). Cox-2 mRNA stability was unaffected by the time point at which the transcriptional inhibitor was added. Again this could be a side effect of the transformation with SV40 large T antigen which was used for the immortalisation of these cells. Another possibility is that p38 mediated Cox-2 stabilisation requires TTP which is so far undetected in these cells. A system where TTP is the only AUBP capable of p38 mediated mRNA stabilisation would partially help explain these results. As well as p38, lack of BRF1 also has little effect on Cox-2 mRNA stability. Decay rates were similar between BRF1+/+ and BRF1-/- MEFs. Half life was
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measured as approximately 40-45 minutes in all four MEF clones (figure 5.10). Under no circumstances was a difference in Cox-2 mRNA decay rates observed leading to the conclusion that this gene is not regulated post-transcriptionally by BRF1 in this cell type. Studies examining the transcriptional regulation of Cox-2 were preceded by extensive validation steps to ensure that the results were authentic. Firstly each primer set was validated to ensure optimal concentrations were used to avoid primer-dimer formation. Negative controls were included to exclude the possibility of genomic DNA contamination which would result in false positives. PCR products were run on agarose gels to ensure that a single product of the correct size for each reaction was obtained. Finally melting curves were used to check for contaminants and primer-dimers.
Cox-2 primary transcript was more abundant in BRF1-/- MEFs than in the wildtype MEFs (figure 5.20). However the actual fold changes in Cox-2 mRNA were similar between wildtype and knockout clones. These results imply that the basal rate of transcription rather than a difference in the level of induction following stimulation is an important factor in the over-expression of Cox-2 mRNA in BRF1-/- cells.
Investigation of KC, the second putative target to be examined in this chapter, provided some important results. Firstly the ELISA data showed that there was little variation in KC protein expression levels between the knockout and the wildtype cells. In fact there was the same degree of variation between the two wildtype clones (614 and 619) and the two knockout clones (611 and 618) as there was between wildtype and knockout pairs of clones. KC steady state mRNA levels were a little more variable and in some experiments significant differences were measured between the knockout and wildtype MEFs. However these were inconsistencies and the overall pattern that emerged was that again all four clones expressed similar levels of KC steady state mRNA. Examination of KC primary transcript failed to detect any significant difference between BRF1+/+ and BRF1-/- MEFs and. These results gave no indication that BRF1 has any impact on the expression of KC at any level. For this reason it served as a useful control demonstrating that differences in Cox-2 and IL-6 gene expression were not just the result of a global effect on gene expression that BRF1 absence may have. Another point to note is that KC protein
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expression was unaffected by addition of the p38 inhibitor. This is despite the fact that KC mRNA expression has recently been postulated to be p38 dependent (Datta et al., 2008). Other than this there are relatively few examples of systems where KC may be a p38 target. We can at least say that in these cells KC is not a p38 target which helps confirm the specificity of the p38 inhibitor enhancing the credibility of other observations in this chapter.
IL-6, the third putative target to be investigated in this chapter was probably the most interesting. Over-expression of IL-6 protein, steady state mRNA and of its primary transcript in BRF1-/- cells suggests that BRF1 is involved in its regulation. As yet the only physiological target for BRF1 that has been suggested is VEGFA (Bell et al., 2006; Ciais et al., 2004). Previous work provides no evidence that there is any difference in the binding specificities of the Zfp36 proteins and shows that BRF1 and BRF2 can function in the same way that TTP does. However the work by Bell et al. showed that VEGF protein and mRNA were over-expressed in the BRF1 knockout mouse but they were unable to show that BRF1 was regulating its stability and instead came to the conclusion that BRF1 was exerting translational control on this protein, demonstrated by increased association of BRF1 with polyribosomes (Bell et al., 2006). This was despite the fact that VEGF contains an ARE in its 3’UTR and that another group had showed that BRF1 can bind and destabilise a luciferase reporter gene containing the VEGF 3’UTR (Ciais et al., 2004). Although the MEFs used in this chapter are derived from the same BRF1-/- mouse that was used by Bell et al., a common mechanism for the control of VEGFA and IL-6 would not be compatible with the results which I have obtained.
When IL-6 protein and steady state mRNA were found to be over-expressed in BRF1-/- MEFs, the immediate assumption was that BRF1 would be controlling IL-6 mRNA stability. Numerous actinomycin D chase experiments were performed to assess whether this was the case. In chase experiments (shown in figures 5.13-16) the sample labeled time zero represents MEFs stimulated for two hours with IL-1α. This time point was chosen on the basis of earlier experiments where IL-6 steady state mRNA peaked its expression after two hours of IL-1α treatment (figure 5.9). To ensure that the stability of IL-6 in these
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experiments was not time-point dependent I also performed these experiments where cells were stimulated for one hour and four hours (data not shown). The decay rates between the BRF1 wildtype and knockout MEFs were unaffected by the length of IL-1α stimulation. As previously with Cox-2, the role of the p38 pathway in IL-6 mRNA stability was tested. Again as was observed for Cox-2, IL-6 mRNA stability was comparable between cells treated with the p38 inhibitor in both BRF1+/+ and BRF1-/- cells. These results lead to some confusion as IL-6 and Cox-2 are well documented p38 targets (Dean et al., 1999; Lai et al., 1999; Ridley et al., 1998).
BRF1 did not appear to cause changes in the efficiency of translation of IL-6 or Cox-2 mRNAs hence the decision not to investigate translational control. Instead primary transcript was measured as an indicator of transcription rate. These measurements revealed elevated IL-6 primary transcript in BRF1 knockout cells (figure 5.22). As was discussed previously in connection with Cox-2 the degree of induction was similar between BRF1+/+ and BRF1-/- MEFs and that the difference in primary transcript levels could be attributed to increased basal IL-6 transcription rate in the BRF1 knockout cells.
One of two possibilities exist: either BRF1-/- itself is directly responsible for the control of IL-6 and Cox-2 transcription or it indirectly controls IL-6 and Cox-2 transcription by modulating the expression of another transcription factor. Originally TTP was suggested to be a transcription factor on the basis of its exclusively nuclear localisation (DuBois et al., 1990). This was also based on its possession of a zinc finger, a structure then thought to be mostly involved in recognition of double-stranded DNA. If BRF1 was shown to be acting as a transcription factor in this system it would have a repressive effect on the IL-6 and Cox-2 promoters. If this was the case, supershift analysis would show a direct interaction of the IL-6 and or the Cox-2 promoters with BRF1.
Activation of transcription commonly involves the transcription factor-mediated recruitment of HATs such as p300 and CBP. These modify histones and contribute to the local remodeling of chromatin. In turn this allows other transcription factors to become associated with the promoter region, increases accessibility to the polymerase complex and
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enhances the rate of transcription initiation. The process of histone acetylation and chromatin opening is countered by HDACs which can be recruited to promoters by negative regulatory transcription factors. Increased basal transcription, as observed in the case of IL-6 in BRF1-/- MEFs, might be associated with an open chromatin state in the absence of a stimulus. Furthermore, sensitivity to TSA, an HDAC inhibitor, is a hallmark of NFκB-mediated activation of the IL-6 promoter in L929 cells. I tested whether TSA affected basal or IL-1α-induced transcription of IL-6, Cox-2 and KC in BRF1+/+ and BRF1- /- cells. One prediction was that basal transcription would be elevated by TSA, and that cells containing or lacking BRF1 might show different sensitivities. Unexpectedly, TSA did not elevate basal transcription of any of the genes tested, and generally inhibited IL-1α-induced transcription. There were no clear differences in TSA sensitivity of wildtype and knockout cells.
In fact more recent publications suggest that HATs and HDACs modulate the acetylation status of not only histones but also transcription factors and other proteins. Hence HDAC inhibitors may also decrease gene expression. For example TSA reduced the expression of cyclin D1 in mouse JB6 cells by preventing the binding of NFκB to its cognate site (Hu and Colburn, 2005). In murine dendritic cells and macrophages two HDAC inhibitors blocked the induction of IL-12p40 and TNF by TLR engagement (Bode et al., 2007). In a micro- array study 105 genes were up-regulated and 100 were down-regulated by the HDAC inhibitor FK228 (Sasakawa et al., 2005). Perhaps HATs and HDACs ought to be renamed ATs and DACs. Certainly, the consequences of HDAC inhibition are unpredictable, and unfortunately their use did not shed any light on the mechanisms underlying IL-6 over- expression in BRF1-/- cells.
The IL-6 promoter region has several cis-acting regulatory elements including binding sites for the transcription factors AP-1, CEBP/β, NFκB and ATF2 and the DNA elements MRE and retinoblastoma control element (RCE). These can either have inhibitory or repressive effects. Exactly which of these is responsible for IL-6 regulation is cell-type and stimulus specific. MRE and the CEBP/β binding site are components of serum response element (SRE), which is activated in response to serum in serum starved cells to cause gene
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transcription (Fisch et al., 1987; Gilman, 1988). MRE causes IL-6 induction when cells are treated with PMA, serum, forskolin, IL-1α and TNF (Ray et al., 1989). As well as induction, transcriptional inhibition is also regulated through various combinations of trans- acting factors on the above mentioned cis-elements, examples include the binding of c-Fos to SRE, retinoblastoma protein binding to RCE and a variety of steroids, reviewed by Keller et al. 1996 (Keller et al., 1996).
The Cox-2 promoter contains multiple putative cis-acting elements for transcription factors, such as NF-κB, CEBP/β, AP2, ATF/CRE and E-box (Fletcher et al., 1992; Kosaka et al., 1994; Sirois et al., 1993). The consensus cis-acting sites of NF-κB, CEBP/β and CRE are the main factors involved in Cox-2 induction in response to hormones, cytokines and tumour promoters. Cox-2 gene transcription has been observed in a variety of cell types. This is achieved by the combination of interactions between the cis-acting elements mentioned above and the trans-acting factors which they are exposed to within these different environments.
To further investigate the mechanism of up-regulation of IL-6 and Cox-2 transcription in BRF1-/- cells a commercial screening technique that measures differences in transcription factor expression between two cell populations, provided some candidates. NFκB, MEF2 and octamer were all under-expressed in the BRF1-/- cells and AP2, HIC-1 and TRE-AP1 were all over-expressed.
NFκB is a widely studied transcription factor that has already been mentioned earlier in this chapter in connection with IL-6 and Cox-2, both of which contain binding sites for it within their promoters. NFκB is activated following TLR engagement. Its targets include several genes involved in the inflammatory response as well as genes that control the cell cycle. So far NFκB has been implicated as a positive regulator of expression of IL-6 and Cox-2. It is difficult to reconcile the over-expression of IL-6 and Cox-2 mRNAs with the apparent down regulation of NFκB DNA binding activity in BRF1-/- cells. However this assay is dependent on binding of transcription factors to consensus oligonucleotides, and does not provide any insight into the complexities of NFκB subunit composition and binding to
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more relevant DNA sequences, such as the cognate binding sites from IL-6 or Cox-2 promoters. Because of the clear evidence that NFκB is an important regulator of IL-6 and Cox-2 expression this observation merits further investigation. It would be interesting to compare the expression of NFκB subunits at the protein and mRNA levels in BRF1+/+ and BRF1-/- MEFs. In addition, EMSA and supershift experiments should be carried out using probes derived from murine IL-6 and Cox-2 promoters, to determine whether NFκB complexes have different composition in wildtype and knockout cells. One possible explanation is that the larger NFκB family is composed of two sub-families; the rel proteins (p65 (RelA), RelB, c-rel Drosophila Melanogaster Dorsal and Dif) and the NFκB proteins (p50 (NFκB1), p52 (NFκB2) and Drosophila Melanogaster Relish). Independently the members of the NFκB sub-family cannot activate transcription, in most cases they must form dimers with a member of the Rel sub-family. Vertebrate forms of NFκB proteins can form homo- or heterodimers except for RelB which can only form heterodimers. As a result there is a high degree of combinatorial diversity which enables each NFκB dimer composite to regulate distinct and overlapping sets of target genes (reviewed by Gilmore 2006 (Gilmore, 2006)). Although the Marligen data showed a decrease in NFκB expression in BRF1-/- MEFs it is unknown as to which NFκB dimer combination this refers to or whether it has a role in the regulation of IL-6 or Cox-2 transcriptional regulation.
MEF2 proteins belong to an evolutionarily conserved family of transcription factors: MCM1, agamous, deficiens, SRF (MADS). Vertebrates have four versions of the MEF2 gene: MEF2a, MEF2b, MEF2c and MEF2d. MEF2 contains a MADS binding domain and a MEF2 binding domain. The N-terminal MADS domain is highly conserved across the four isoforms, in this region they share 95% amino acid homology. However, due to sequence divergence at the C-terminal they share an overall amino acid homology of approximately 50%. The MADS-box serves as the minimal DNA-binding domain, however an adjacent 29-amino acid extension called the MEF2 domain is required for high affinity DNA-binding and dimerisation. Through an interaction with the MADS-box, MEF2 transcription factors have the ability to homo- and heterodimerize, and a classic NLS in the C-terminus of MEF2A, -C, and – D ensures nuclear localisation of the protein.
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Interestingly, D-MEF2 (which is MEF2 protein found in Drosophila melanogaster) and MEF2B lack this conserved NLS but are still found in the nucleus.
The MEF2 proteins are involved in many cellular processes that control organogenesis and differentiation. MEF2 expression and its transcriptional activity depend upon interaction with and recruitment of other transcription factors, signalling pathways and the repressive function of HDACs. MAPK signalling pathways converge on MEF2 resulting in its phosphorylation by ERK5 which is a MEF2 co-activator. Following this, MEF2 target genes are activated in a variety of cell types including skeletal muscle, cardiac muscle, neural crest cells, endothelial cells, chondrocytes, smooth muscle, neurons and lymphocytes. Calcium signalling also activates MEF2 by activating calcium dependent kinases which phosphorylate class ІІ HDACs. Phosphorylated class ІІ HDACs target MEF2 but rather than inducing transcription of target genes in the tissues mentioned above they cause MEF2 to dissociate from them resulting in their down regulation. Studies in mice and Drosophila melanogaster have revealed a role for MEF2 in myogenesis, skeletal muscle differentiation, cardiac structural and contractile protein expression, neural crest development, ossification, control of vascular integrity, neuronal differentiation and T-cell development (reviewed by Potthoff and Olson 2007 (Potthoff and Olson, 2007)).
Interestingly MEF2 contains three overlapping AUUUA motifs within its 3’UTR. Also MEF2 has been described as a p38 target in myoblast cells during muscle development (Keren et al., 2006). However whether its 3’UTR condems it to p38 sensitivity or not is ambiguous. A micro-array study of AU-rich p38 targets found that in THP-1 cells treated with LPS for two hours and a p38 inhibitor, the half life of MEF2 was 60 minutes. This amounted to a decrease of no more than 1.5 fold in comparison to the control cells (Frevel et al., 2003).
Of particular significance is the role of MEF2 in the control of vascular integrity in the developing endothelium and smooth muscle cells. There are two processes involved in vascular development; vasculogenesis (the de novo formation of new blood vessels from mesodermal progenitor cells) and angiogenesis (the expansion of the capillary network
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from existing vessels). MEF2C expression has been detected in all endothelial cells in the developing mouse embryo and yolk sac at day 8.5 of embryogenesis (De Val et al., 2004). The MEF2C null mouse resulted in lethality by day 9.5 of embryogenesis due to severe vascular abnormalities. These mice had differentiated endothelial cells but they were unable to organise properly whereas its smooth muscle cells did not differentiate (Lin et al., 1998). Maintenance of vascular integrity depends upon ERK5 induction of MEF2C. A conditional knockout of ERK5 in endothelial cells caused vascular death and embryonic lethality at day 9.5 to 10.5 due to apoptosis and the inability of the endothelium to proliferate (Hayashi et al., 2004). The apoptotic effect of ERK5 absence in these cells was partially elevated by addition of MEF2C-VP16 (Hayashi et al., 2004).
The vascular abnormalities observed in MEF2C-/- mice draw parallels with those observed in the BRF1-/- mouse and in mice lacking VEGF (Carmeliet et al., 1996) or its receptors Flt- 1(Fong et al., 1995) and Flk-1 (Dumont et al., 1995). So far two studies have described the lethality of the absence of the BRF1 gene (Bell et al., 2006; Stumpo et al., 2004). In the first, mice died between days 9 and 11 of embryogenesis due to failure of chorio-allanotoic fusion (Stumpo et al., 2004). In the second embryos died between days 9.5 and 10.5 of embryogenesis due to defects in vasculogenesis. These mice were found to over-express VEGF (Bell et al., 2006). By contrast embryos from MEF2C null mice had similar levels of VEGF mRNA as their wildtype counter parts (Lin et al., 1998). This would suggest that the vascular defects in these mice are not a result of down regulation of vascular signalling by MEF2 absence and that VEGF is not a MEF2 target. VEGF lacking embryos appeared normal at day 8.5 of development, by day 9.5 they were retarded and were all dead by day 10.5 (Carmeliet et al., 1996).
If BRF1 does affect MEF2 and VEGF the mechanism by which they interact is probably complex. It cannot simply be that BRF1 negatively regulates MEF2 mRNA stability because MEF2 expression is decreased in BRF1 negative cells. It is more likely that BRF1 controls MEF2 indirectly.
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ATTTGCAT is the DNA motif known as octamer. It provides a docking site for Oct-1, which is ubiquitously expressed and Oct-2 which is a lymphoid specific protein. There are several other members of this family of transcription factors; Oct3/4, Oct6, Oct7 Oct8 and Oct9 which were identified as a result of the cloning of Oct-2. This family is a distinct family of homeobox containing genes known as the POU domain, class 1, transcription factors. The term POU was given due to it presences in Pit-1, Oct-1/Oct-2 and Unc-1 genes. The POU domain is a DNA binding domain that consists of two helix-turn-helix DNA binding structures, an N-terminal POU specific domain and a C-terminal POU-homeo domain joined by a flexible linker. The different POU containing sub-family of homeobox genes have varying functions. For example; Oct1 is a transcription factor involved in growth hormone regulation. The POU domains of Oct1 and Oct2 are involved in basal transcription factor recruitment. Oct4 is involved in the self renewal of stem cells and is often used as a stem cell marker. Oct7 is involved in mammalian neurogenesis. These genes have been highly conserved across evolution as a result of their DNA binding and transcriptional regulatory properties. Octamer’s involvement in basal transcription may help partly explain the increase in the basal rate of IL-6 and Cox-2 transcription. However octamer is under-expressed in BRF1-/- clones which would suggest that if it is involved in IL-6 and Cox-2 transcriptional regulation then it negatively regulates their transcription. This would contradict much of the literature which suggests a positive role for octamer in transcriptional activity. A search of the literature did not indicate any links between IL-6 or Cox-2 with the octamer sub-family.
AP1 is a heterodimeric transcription factor complex composed of proteins from the Fos, Jun and sometimes from the activating transcription factor families. The Jun proteins (c- Jun, JunB and JunD) form homodimers or can heterodimerise with the Fos proteins, which are c-Fos, FosB, Fra-1 and Fra-2, through their leucine zipper domains. By contrast Fos proteins can only heterodimerise. AP1 up-regulates genes which contain a TRE with the consensus sequence TGACTCA following activation by MAPK, TGFβ or Wnt signalling pathways. AP1 targets a variety of genes including regulators of cell proliferation, differentiation, apoptosis and those involved in the pathogenesis of inflammatory diseases.
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The target is determined by the combinatorial interactions among AP1 dimer components, cell type and the signalling pathway by which they are activated.
Due to the diversity of AP1 targets, the Jun proteins have several roles (reviewed by Zenz et al. 2008 (Zenz et al., 2008)). Interestingly JunB-/- embryos have impaired vasculogenesis and embryogenesis and die at approximately day 9.5 of embryogenesis (Schorpp-Kistner et al., 1999). This is similar to the phenotype which was described in BRF1-/- (Bell et al., 2006; Stumpo et al., 2004), MEF2-/- (Lin et al., 1998) and VEGF-/- embryos (Carmeliet et al., 1996). VEGF is a known c-Jun target and in c-Jun deficient cells VEGF is also lacking. By contrast VEGF is over-expressed in BRF1-/- cells which demonstrates the importance and sensitivity in controlling the expression of VEGF.
Other AP1 functions have been revealed by knockout mice. JunD over-expression suggested a role in the regulation of the immune response through control of T-cell development (Zenz and Wagner, 2006). c-Jun-/- embryos die between days 12.5 and 14.5 of development due to heart and liver defects (Zenz and Wagner, 2006). Inducible simultaneous conditional knockdown of JunB/jun genes in epidermal cells resulted in a psoriasis like disease (Zenz et al., 2005). By contrast JunD is involved in post-natal growth regulation. JunD null mice are viable but are growth retarded, have reproductive defects, hormone imbalances and impaired spermatogenesis (Thepot et al., 2000). Jun proteins have also been suggested as positive and negative regulators of cell proliferation and as regulators of liver regeneration (Weitzman et al., 2000).
Fos proteins are important in bone development and in tumour formation. Transgenic expression of FosB and Fra-1 resulted in osteosclerosis, FosB over-expression also resulted in impaired T-cell development and induced osteosarcoma. The Fra-1 knockout was embryonic lethal at day 9.5 due to placental defects. Over-expression of Fra-2 resulted in occular malformations and fibrosis of the lungs. Fra-2 knockout mice died shortly after birth due to defects in chondrocyte differentiation and matrix production . The link between AP1 and inflammatory disease is demonstrated by the JunB/c-Jun double mutant. Inflammatory diseases such as psoriasis, inflammatory bowel disease, and RA are
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characterised by the disregulation of inflammatory cytokines, some of which are under the control of AP1. The functions of the AP1 proteins are reviewed by Zenz et al. 2008 (Zenz et al., 2008).
IL-6 contains an AP1 response element within its promoter. cFos has been implicated in negative regulation of IL-6 in HeLa cells in response to IL-1α (Ray et al., 1989) but also positively when it dimerises c-Jun to form AP1 in monocytes and fibroblasts (Dixon et al., 2003). This demonstrates the complexity of IL-6 activation. In addition, Cox-2 transcription can also be stimulated by AP-1(Ramsay et al., 2003).
In support of AP1 as a BRF1 target c-fos contains a class І ARE within its 3’UTR and c-Jun has a class ІІІ ARE within its 3’UTR. JunB has been shown to be stabilised by p38 (Frevel et al., 2003) as has c-fos and c-Jun (Roduit and Schorderet, 2008). Again there are several different combinatorial forms that AP1 can take. The specific combination that is up-regulated in BRF1-/- cells is unspecified. It is therefore something that would need to be established. Potentially BRF1 regulates the stability of one or more of these mRNAs encoding AP1 components. The disregulation of AP1 could contribute to the over- expression of IL-6 and Cox-2 and possibly also the developmental defects in BRF1 null mice.
To identify whether AP1 is the transcription factor involved in IL-6 and Cox-2 regulation in BRF1-/- MEFs, further experiments would be needed. As previously described for NFκB, western blots and qPCR could be used to identify the presence of AP1 and its expression profile in BRF1 knockout and the wildtype MEFs. Following this EMSAs using an IL-6 probe followed by incubation with antibodies specific to members of the Fos and Jun families may help identify which of these components are involved. Lastly chromatin immunoprecipitation experiments would also help to elucidate whether AP1 can bind the IL-6 or Cox-2 promoter regions.
The AP2 family of transcription factors has five members; AP2α, AP2β, AP2γ, AP2δ and AP2ε. A spectrum of genes involved in a variety of biological functions such as embryonic
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development, cell cycle control and cell differentiation are regulated by the AP2 family members. They include p21WAF/CIP (Zeng et al., 1997), TGFα (Wang et al., 1997), estrogen receptor (McPherson et al., 1997), keratinocyte specific genes (Leask et al., 1991) and c-myc (Gaubatz et al., 1995) to name a few. The AP2 proteins share a highly conserved helix-span-helix dimerisation and binding domain in their C-termini. There is little sequence homology at the N-terminus but all have proline and glutamine rich regions and AP2α, AP2β, AP2γ and AP2ε all have a PY motif which is responsible for most of their transcriptional activities.
All of the AP2 proteins are found to be expressed in the developing neural crest however the phenotypes of the individual knockout suggest independent as well as over lapping functions. The AP2α knockout mouse begins to malform at day 9.5 of embryogenesis. Craniofacial clefts develop, their lung development is impaired and the development of the head, face, neck and limbs is affected (Schorle et al., 1996; Zhang et al., 1996). The result is mortality during birth. AP2β null mice die postnatally of polycystic kidney disease (Moser et al., 2003). AP2γ gene disruption causes gastrulation after implantation which suggests a critical role in embryogenesis for this member of the AP2 family. AP2δ is the most divergent of the AP2 family in that it lacks the PY motif and has a weak affinity for AP2 binding sites. Its role has yet to be fully understood but it has been shown to recruit histone methyltransferases to specific target genes (Moser et al., 2003). AP2ε may regulate skin specific gene expression (Tummala et al., 2003).
Again it is interesting to note that a gene affected by BRF1 absence is involved in embryonic development. The Cox-2 promoter contains a putative cis-acting element for the transcription factor AP2. Kirtikara et al. found that the AP2 element played a significant role in regulating Cox-2 promoter activity in a human micro-vascular endothelial cell line. However the DNA-protein complexes formed with the AP2 sequence motif did not contain AP2α (Kirtikara et al., 2000). Another group showed that staurosporine induced Cox-2 production in MC3T3-E1 cells (a mouse osteoblast cell line) was dependent on AP2 activity in a PKC dependent manner through its cis-acting AP2 regulatory site (Wang et al., 2002). By contrast IL-6 does not contain a putative AP2 regulatory element within its
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promoter region. Further investigations would be required to determine whether AP2 was important in Cox-2 regulation in the MEFs used in this chapter. Comparative EMSAs in BRF1+/+ and BRF1-/- MEFs using a probe containing the Cox-2 promoter region followed by incubation with an antibody with an affinity for AP2 to induce a supershift of any AP2 containing complexes would reveal a role for this transcription factor in the Cox-2 regulation in this system.
HIC-1 is a zinc finger domain containing a transcription factor located on chromosome 17 in a region where tumour suppressor genes are known to reside (Wales et al., 1995). It is a sequence specific transcriptional repressor which is ubiquitously expressed in normal tissues but is under-expressed in different tumour cells where it is hypermethylated (Wales et al., 1995). Over-expression of HIC-1 in colon and breast cancer cell lines reduced clonal growth and induced differentiation changes (Wales et al., 1995). HIC-1 homozygous knockout mice die perinatally due a combination of developmental defects which occur during the latter stages of embryogenesis. Defects affecting HIC-1-/- mice include acrania, exencephaly, cleft palate, limb abnormalities and omphalocele (Carter et al., 2000). These deformities resonate with patients who have Miller-Dieker syndrome (MDS) who have developmental abnormalities such as craniofacial dysmorphology, limb and digit defects and omphalocele (Chitayat et al., 1997; Scriver et al., 1995). Heterozygote knockouts of HIC-1 develop cancers (Chen et al., 2003). At present only one direct target of HIC-1 has been identified; the human homolog of the yeast silent information regulator 2 gene (SIRT1) (Chen et al., 2005a). HIC-1 works with p53 to suppress age dependent development of cancers. Where HIC-1 is absent SIRT1 becomes disregulated and can inactivate p53 which enables cells to avoid apoptosis and replicate despite impairment of DNA (Chen et al., 2005b).
Although HIC-1 is clearly up-regulated in BRF1-/- MEFs it is difficult to make the link between it and IL-6 or Cox-2 transcriptional regulation. At present there are no studies to link HIC-1 to these inflammatory mediators. Whether or not HIC-1 is a direct target of BRF1 is something that would require further investigation. Again assays to assess the ability of BRF1 to bind HIC-1 would give some insight into this. Whether or not HIC-1
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over-expression is in any way responsible for any aspect of the BRF1-/- phenotype would also need further inquiry.
The MEF cell lines used in this chapter were in theory clonal cells lines, giving rise to the possibility that just by chance the over-expression of IL-6 is a defect of the cell line which may have occurred over time or during the transformation process. To eliminate this possibility and prove that IL-6 over-expression is directly related to BRF1 absence, an experiment to rescue the phenotype of the BRF1-/- cells would be required. Transfection of BRF1 protein into the BRF1 negative cells should in theory reduce IL-6 levels so that they are comparable to those measured in wildtype MEFs.
Future experiments would probably concentrate on the candidate transcription factors identified in the Marligen screening process. EMSAs to show whether BRF1 can bind them or not and chromatin immunoprecipitation assays to assess their ability to bind to the IL-6 promoter region. In addition, western blotting nuclear and cytoplasmic fractionated samples of these cells could be used to verify their presence in the nuclei and therefore their ability to act as transcription factors in this system. It may be that different transcription factors are individually responsible for IL-6 and Cox-2 over-expression whether this is the case or not would be revealed with the investigations outlined above.
It is clear that the mechanism of IL-6 and Cox-2 gene regulation in BRF1-/- MEFs is not straight forward and there is still some way to go in fully understanding it. BRF1 absence has a far greater effect than simply causing an increase in IL-6 and Cox-2 transcription. It also has a clear role in the regulation of genes involved in embryonic development. Of the six transcription factors that are differentially regulated in BRF1-/- MEFs, four have functions in embryonic development. As well as IL-6 and Cox-2 we know that VEGF levels are affected by BRF1 deficiency, in addition there may well be other cytokines affected, but non were investigated. A micro-array experiment may help give a more thorough over view of other differences in gene expression resulting from a lack of BRF1.
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Chapter 6:
Final discussion
250 Chapter 6 Final discussion
6) CHAPTER 6: FINAL DISCUSSION
The purpose of this project was to investigate the functions of BRF1 and BRF2 and to identify their role within the immune response. I began by characterising all of the antibodies made available to me that were able to detect one or more of the Zfp36 proteins. From the work that has been carried out, it is clear that the lack of highly specific sensitive reagents is problematic. However I achieved an understanding of the detection range of each, enabling me to use them in combination with one another to gain an understanding of the expression patterns of the Zfp36 proteins. A BRF1 specific antibody helped overcome the main problem which was the inability to distinguish between BRF1 and TTP protein by western blot. Due to the lack of sensitivity future studies may require techniques such as immunopreciptation which would serve to concentrate Zfp36 proteins. Combining this with western blotting would help partially alleviate the problem of low sensitivity reagents.
Defining the expression patterns of the Zfp36 proteins was problematic due to the above mentioned technical issues. Of the three proteins TTP expression was probably the hardest to characterise. This project was partially initiated by the observation that TTP was lacking in HeLa cells. Despite this p38 mediated stabilisation of mRNAs was detected in these cells. Consideration of these two facts led to the hypothesis that another AUBP could be the target of the p38 pathway to bring about mRNA stabilisation in HeLa cells. Phosphorylation of TTP renders it inactive but also stabilises its expression. Therefore active (or unphosphorylated TTP) is unstable and more difficult to detect. As a result low levels of TTP could be capable of fulfilling a destabilising role within HeLa cells and may also be physiologically relevant. Thorough investigation of Zfp36 protein expression in HeLa cells identified the transient expression of TTP in response to an inflammatory stimulus.
Use of siRNA to silence gene expression is a relatively recent development. The siRNA mechanism was described by Fire et al. in 1998. Caenorhabditis elegans were injected with dsRNA causing potent and specific down regulation of their target genes (Fire et al., 1998). Since then several techniques have developed to mediate RNAi within cells and it has
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become a widely used tool to examine gene function. However more recently the limitations of this technique have become increasingly apparent. The initial limitation of this technique is the design of an effective siRNA sequence capable of gene silencing. There are a number of factors which affect the efficiency of an siRNA including the sequence and structure of the siRNA and the ability of the cell into which it is delivered to process it (Kim et al., 2005; Siolas et al., 2005). Another big factor in the use of siRNA as a laboratory tool is the issue of off target effects. Non specific and off target effects present limitations for siRNAs as gene silencers in basic research. When siRNA was initially characterised as a research tool high specificity was generally assumed. The general effects that dsRNAs may be having on cell metabolism were not considered. As RNAi has become a more widespread technique the additional effects that it may have in addition to gene silencing have become more apparent.
There are three main types of non-specific RNAi effects that have been observed. The first is the up-regulation of alternative dsRNA responsive pathways such as the innate immune response. For example interferon stimulated gene (ISG) up-regulation has been reported. This can be explained as an ‘siRNA specific’ effect as opposed to ‘target gene-specific’ mode of semi-global gene regulation. In this case the sequence of the siRNA is irrelevant. The second type of effect, known as off target, occurs when the expression of a gene which is not targeted by the siRNA is altered. Off target effects are dependent on the sequence of the siRNA. Thirdly the same cellular machinery is used for experimental RNAi and for endogenous miRNA mediated gene regulation. It has been suggested that the two functions could disrupt one another (reviewed by Sledz and Williams 2005 (Sledz and Williams, 2005)).
During this project the use of siRNA to knockdown BRF1 and BRF2 expression was technically difficult for two reasons; firstly achievement of a good quality knockdown was problematic; secondly, assessing the extent of the knockdown was difficult with the available reagents. The concentration of siRNA and duration of treatment was optimised to maximise siRNA effectiveness. Confirmation of the knockdown was difficult because some of the more specific antibodies were not so effective for detection of low levels of Zfp36
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protein. These technical difficulties were problematic in this project because the Zfp36 proteins are up-regulated by pro-inflammatory stimuli, a response which is not effectively blocked by RNAi. This presents a problem because as previously mentioned low levels of the Zfp36 proteins may be enough for them to function normally. Therefore although siRNA mediated absence of BRF1 and BRF2 had no effect on the investigated inflammatory mediators, BRF1 and BRF2 involvement in the regulation of these genes has not been dis-proved.
Due to limitations of the RNAi technique an alternative approach was taken which is described in chapter 5. Further studies focused on a MEF cell line derived from BRF1-/- mice which die during embryogenesis. Given the phenotype of these mice this was the only cell line available. BRF1+/+ and BRF1-/- MEFs were immortalised using the SV40 large T antigen. Previous studies cite numerous examples of p38 mediated mRNA stabilisation (reviewed by Clark 2003 (Clark et al., 2003)). However this type of post-transcriptional regulation was not observed in these MEFs making them not particularly useful to investigate the role of BRF1 in post-transcriptional regulation by p38. IL-1α treatment of the cells did activate p38 giving rise to the possibility that the immortalisation process may have had some adverse effects on the functioning of these cells. This issue could be addressed by use of a primary MEF cell line or a MEF cell line that has not been immortalised using an oncogene but by an alternative method, for example the NIH protocol.
Since only two immortalised cell lines of both BRF1+/+ and BRF1-/- MEFs were available, the possibility that IL-6 over-expression was not a direct effect of BRF1 absence exists. The only way to be completely sure that this is not the case would be to transfect the cells with BRF1. If the reintroduction of BRF1 into BRF1-/- MEFs caused the expression of IL-6 to be restored to levels comparable with those observed in BRF1+/+ MEFs then this would prove a link between BRF1 and IL-6. As well as this it would be useful to investigate the patterns of IL-6 and Cox-2 gene expression in primary MEFs and in other cell lines from differentiated embryonic stem cells derived from the BRF1-/- mouse. This would firstly establish that the differences in gene expression were not a consequence of the
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immortalisation process and give some insight in to whether IL-6 over-expression is tissue specific or not.
I have shown that the expression of TTP protein and mRNA in HeLa cells is transient in response to inflammatory stimuli. TTP protein accumulated after one hour of IL-1α or PMA treatment and had disappeared again after two hours with IL-1α or after four hours with PMA. This contrasted with observations made in RAW264.7 cells which displayed a sustained up-regulation of TTP protein and a biphasic induction of its mRNA (Tchen et al., 2004). It has been shown that in macrophages TTP can negatively regulate itself which accounts for the dip in TTP mRNA expression. Following this it may be that a factor, for example a cytokine, released by the macrophage itself as a result of TTP up-regulation induces a second phase of TTP mRNA expression and maintains TTP protein levels. Sauer et al. suggest that this second wave of TTP mRNA induction and prolonged protein expression in RAW264.7 cells could be attributable to STAT1. STAT1, an interferon activated transcription factor, is required for full expression of TTP in LPS stimulated macrophages (Sauer et al., 2006). Whether or not STAT1 activation would have the same effect in HeLa cells is unknown. To investigate this HeLa cells could be stimulated with IL- 1α or with INFγ and with a combination of the two. TTP protein and mRNA expression could then be measured by western blot and qPCR. STAT1 activity could then be detected using an antibody to detect phosphorylated STAT1. If active STAT1 was not detected in these cells then this may provide an explanation for the differences in TTP expression in HeLa and RAW264.7 cells. If STAT1 was found to be present in HeLa cells the dependency of TTP expression on it could then tested by elimination of STAT1 using siRNA followed by the experiments outlined above.
TTP protein was unaffected by dexamethasone treatment and its mRNA was only weakly up-regulated. The up-regulation of TTP through dexamethasone would be a novel mechanism for glucocorticoids to exert their anti-inflammatory effect. Glucocorticoids are a known inhibitor of the p38 pathway (Lasa et al., 2002). Dexamethasone up-regulates TTP and at the same time it inhibits p38 by up-regulating MKP1. Therefore any TTP that is expressed under these conditions is probably not phosphorylated at serines 52 and 178
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which would result in its instability making it difficult to detect but highly active. The up- regulation of TTP mRNA in HeLa and A549 cells is very subtle and difficult to detect, the above mechanism may provide an explanation for this but is only speculative at this stage.
It has been well established that p38 is required for TTP expression. In this lab it was shown that activity of the p38 regulated kinase MK2 is required for LPS induced TTP mRNA expression in RAW264.7 cells (Brook et al., 2006; Mahtani et al., 2001; Tchen et al., 2004). Subsequently it was shown that this regulation was mediated through an ARE present in the 3’UTR of TTP (Tchen et al., 2004).
More recently TTP protein expression has also been shown to be dependent on p38 activity. Regulation of localisation and protein stability were both shown to be MK2 dependent (Brook et al., 2006). Another study from around the same time demonstrated the importance of MK2 in the regulation of TTP destabilising activity (Hitti et al., 2006). In primary macrophages, immortalised macrophages and spleen cells derived from the MK2-/- mouse TTP protein levels were reduced (Hitti et al., 2006).
Human TTP has been shown to be phosphorylated in vitro on over 30 sites (Cao et al., 2006). Two of these: serines 52 and 178 have been shown to result in the recruitment of 14:3:3 proteins (Chrestensen et al., 2004). Another group showed that by complexing with 14:3:3 proteins TTP became excluded from stress granules (which are sites associated with mRNA stabilization) (Stoecklin et al., 2004). Another report does not agree with this proposed 14:3:3 mechanism of TTP inactivation it therefore remains controversial (Rigby et al., 2005). More recently the phosphorylation by MK2 of serines 52 and 178 on TTP have been shown to regulate sub-cellular localisation as well as TTP protein stability (Brook et al., 2006). Brook et al. showed that inhibition of p38 caused dephosphorylation of TTP resulting in its relocalisation to the nucleus and proteosomal degradation. Phosphorylation by MK2 causes TTP stabilisation and at the same time inhibits its destabilising activity (Hitti et al., 2006). This is important as it could be that BRF1 is regulated by a similar mechanism.
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The expression of both BRF1 and BRF2 proteins is up-regulated in response to PMA and IL-1α. Of the two proteins, up-regulation of BRF1 is the most dramatic. By contrast the changes in mRNA expression are mild which suggests that these proteins are either regulated post-transcriptionally or translationally. In both HeLa cells and in the MEFs BRF1 protein expression was partially dependent on p38 activity and also BRF2 protein but to a lesser extent. Recently MK2 was shown to phosphorylate BRF1 on serine residues 92 and 203 (Maitra et al., 2008). One of the same residues, serine 203, is phosphorylated by PKB resulting in BRF1 stabilisation (Benjamin et al., 2006). It is probable that p38 mediates the stability of BRF1 protein through the phosphorylation of this residue. To test this hypothesis experiments would begin by demonstrating the need for p38 in BRF1 expression. In the presence of a p38 inhibitor, IL-1α induced BRF1 protein would be expected to decline. Possible post-translational regulation of BRF1 could be examined by the addition of cycloheximide in the absence or presence of the p38 inhibitor. In cells treated with only cycloheximide BRF1 protein would be expected to remain relatively stable. By comparison, if p38 does regulate BRF1 stability, cells where p38 is blocked in conjunction with cycloheximide treatment, BRF1 would rapidly destabilise. The mRNAs of the BRF1 and BRF2 were not measured following p38 inhibition in either HeLa cells or in the MEF cell lines it would be interesring to address this in future experiments.
As previously mentioned, prior to the commencement of this project TTP had not been detected in HeLa cells, yet HeLa cells had been shown to support mRNA stabilisation mediated by the p38 pathway (Dean et al., 1999; Ridley et al., 1998). The possibility that the destabilising activity of BRF1 and BRF2 was inhibited by phosphorylation by p38 leading to mRNA stabilisation was investigated. Data presented in this thesis suggest that it is unlikely that BRF1 or BRF2 are the AUBPs which link p38 and mRNA stability but that there is every possibility that TTP is actually fulfilling this role. It could be that having detected TTP at low levels in HeLa cells that it is actually the AUBP which is being targeted in this mechanism. Although I have not shown TTP expression in the MEF cell lines used in chapter 5, given the difficulty with detecting TTP protein it does not mean it is absent from these cells. Since I was unable to show that p38 was critical for mRNA stabilisation in the MEFs used in this project one could speculate that this is consistent with
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the need for TTP in p38 mediated mRNA stabilisation. To test whether TTP is in fact involved in p38 mediated mRNA stability in HeLa cells the siRNA approach that was described for BRF1 and BRF2 could be used. Obviously similar problems may be encountered that were previously detailed for BRF1 and BRF2. If TTP was found to be targeted in p38 mediated mRNA stability in HeLa cells then this would support the experiments shown in TTP-/- macrophages where a p38 inhibitor failed to destabilise the mRNAs of IL-10, TNFα, Cox-2, IL-1α and IL-6 suggesting that p38 exerts it stabilising effect by inactivating TTP (unpublished observations- C. Tudor). Further investigation of this could focus on other cell types derived from the TTP-/- mice which would give a broader overview of TTP function. Although TTP protein has been detected in HeLa cells detection is not always easy this is probably due to the poor sensitivity of the TTP specific antibody and probably because TTP is not particularly abundant in these cells. TTP may well be expressed at other time points following IL-1α treatment but it may just be that it is below the detection range of the antibody. The p38 inhibitor could be added at later time points when there is no detectable TTP to analyse the effect on the mRNAs of genes encoding inflammatory mediators.
Although I have failed to show that BRF1 has a post-transcriptional effect on three putative inflammatory mediators I think it is still likely that it has a role in mRNA destabilisation. There is overwhelming evidence that it can function in the same way as TTP to destabilise ARE containing mRNAs. BRF1 can bind and destabilise TNF-α, GM-CSF and IL-3 mRNAs (Lai and Blackshear, 2001; Lai et al., 1999; Lai et al., 2003). As well as this both BRF1 and TTP have been shown to interact with mRNA decay enzymes which bring about deadenylation, decapping and exonuclolytic decay and with Ago2 (which is involved in RNAi) (Chen et al., 2001a; Jing et al., 2005; Lykke-Andersen and Wagner, 2005). PBs are discrete cytoplasmic foci at which proteins involved in mRNA decay and translational silencing are abundant. There is evidence that BRF1 and TTP deliver ARE containing mRNAs to PBs (Franks and Lykke-Andersen, 2007). Such evidence further supports the idea that BRF1 function is post-transcriptional.
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When it was first identified, TTP was hypothesized to be a transcription factor. The likelihood that BRF1 is a transcription factor seems extremely unlikely given its ability to function in such a similar way to TTP. Other suggestions for BRF1 function have been made. They include the idea presented by Bell et al. that it has a role in translational regulation (Bell et al., 2006) and by Ciais et al. who suggest it can function to regulate VEGF post-transcriptionally and most recently Busse et al. propose a role for it in myogenesis although how it carries out its effect on this process is unknown (Bell et al., 2006; Busse et al., 2008; Ciais et al., 2004).
Alternatively BRF1 has an indirect effect by targeting an intermediate factor which in turn regulates IL-6 and or Cox-2 transcription. Presented in chapter 5 is data from the Marligen screening process which screened 40 transcription factors and identified those differentially expressed between BRF1+/+ and BRF1-/- MEFs. The results from this do not conclusively identify a candidate for this mechanism but do give some suggestions. NFκB, MEF2 and octamer were all found to be under-expressed whereas AP1, TRE-AP2 and HIC-1 were all found to be over-expressed in BRF1-/- MEFs. Further experiments would be needed to clarify the role of any of these transcription factors in IL-6 and or Cox-2 regulation. As the Marligen screening process focused on a specific set of transcription factors it could be that the ones involved in this particular mechanism were not screened. However it has at least identified some useful candidates that could form the basis of future investigations.
Whether or not any of the transcription factors identified by the Marligen screening process are involved in IL-6 or Cox-2 regulation it would be interesting to follow them up and identify whether they are in any way responsible for the phenotype of the BRF1-/- mouse. A search of the literature identified several examples of their involvement in transcriptional regulation of genes involved in embryonic development. This is unsurprising given that BRF1 absence caused premature death of embryos. Whatever the true physiological mechanism of BRF1 it is clear that artificially it can regulate mRNAs post- transcriptionally. It may be that in vivo BRF1 can regulate different targets by different mechanisms and that it has different functions in different tissues. It will be interesting to
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further ascertain the mechanism of BRF1 in the MEF cell line and seek to identify if this has any relation to BRF1 function in other systems.
There is still some way to go in determining the physiological targets of BRF2. Of the three proteins BRF2 is the least understood, probably due to the lack of a knockout mouse. Studies therefore rely on siRNAs to deplete this protein but this can also be problematic as discussed previously. Perfection of a good siRNA knockdown of BRF2 could be followed by a micro-array experiment to identify specific candidate genes under its regulation. It will be interesting to see what future studies discover about BRF2.
259 References
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260 References
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