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The roles of SH2-containing inositol 5'-phosphatase 1 (SHIP1) and signal transducer and activator of… Tsz Ying Sylvia, Cheung 2016

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  THE ROLES OF SH2-CONTAINING INOSITOL 5'-PHOSPHATASE 1 (SHIP1) AND SIGNAL TRANSDUCER AND ACTIVATOR OF TRANSCRIPTION 3 (STAT3) IN INTERLEUKIN-10 REGULATION OF ACTIVATED MACROPHAGES  by  Tsz Ying Sylvia Cheung  B.Sc, The University of British Columbia, 2009  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  DOCTOR OF PHILOSOPHY  in The Faculty of Graduate and Postdoctoral Studies  (Biochemistry and Molecular Biology)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) October 2016 ©  Tsz Ying Sylvia Cheung, 2016     ii Abstract Inflammation is a protective mechanism against infection, but it must be appropriately regulated to prevent pathological consequences including inflammatory diseases.  Interleukin-10 (IL-10) is a key anti-inflammatory cytokine that inhibits the activation of many immune cell types, including the macrophage, to prevent exaggerated immune responses.  Understanding the signalling pathway downstream of IL-10 and IL-10 receptor (IL-10R) is essential in developing therapeutics to treat inflammatory diseases.  Canonically, IL-10R signalling is described as solely depending on the activation of the transcription factor STAT3 and the expression of STAT3-response genes.  However, our laboratory has previously shown that IL-10 also activates the inositol 5'-phosphatase SHIP1 to mediate its anti-inflammatory responses, such as inhibiting the expression of pro-inflammatory cytokines.  Moreover, we have now found that IL-10 is able to inhibit expression of miRNA-155 (miR-155) in macrophages activated by the bacterial product lipopolysaccharide (LPS).  This inhibition by IL-10 requires both STAT3 and SHIP1, and occurs at the maturation step, but not at the transcription step, of miR-155.  Consistent with SHIP1’s involvement in IL-10 function, a previously described SHIP1 activator, AQX-MN100, mimics IL-10 and inhibits LPS-induced miR-155.  Next, we investigated the roles of STAT3 and SHIP1 in IL-10 regulation of global gene expression in activated macrophages.  Among the genes identified as IL-10 regulated, we have found different subsets of genes potentially to be SHIP1-regulated, STAT3-regulated, and SHIP1-STAT3 regulated.   Considering the importance of SHIP1 activation in IL-10 function, SHIP1 activators provide an alternate way to control inflammation.  We have previously shown  iii that SHIP1 activators bind to SHIP1’s C2 domain and regulate SHIP1 enzymatic activity allosterically.  Using x-ray crystallography, we obtained the crystal structure of SHIP1’s phosphatase and C2 domains, the minimal region necessary for allosteric activation by SHIP1 activators.  Analysis of the crystal structure revealed differences between SHIP1 and related phosphatases.  Biochemical and biophysical methods have been employed to identify amino acid residues potentially interacting with SHIP1 activators.   Together, this work strengthens the model that STAT3 and SHIP1 work together to mediate the anti-inflammatory function of IL-10.  We also described the structure of SHIP1, providing the first step in rational drug design to generate better small molecule SHIP1 activators.       iv Preface Contributions: The design of all research, data analysis and manuscript preparation were completed with the assistance of Dr. Alice Mui. All experiments were performed by the author with the following exceptions: Chapter 3: The pGL3- IkBζ promoter luciferase reporter construct was generated by Eva So, who also assisted in performing the luciferase reporter assay.  The SHIP1 siRNA, STAT3 siRNA and SCRMB siRNA transduced cell lines were previously generated by Dr. Andrew Ming-Lum and Gary Golds.  Chapter 4:  Experiment using the continuous flow apparatus was performed by Joanna Chan. The J2M KO:SHIP1 WT and J2M KO:SHIP1 Y190F cell lines were generated by Soroush Shakibakho, and the TNF production assays using these cell lines were performed by Kamaldeep Kaur Jawanda.  The mRNA microarray was performed by Anne Haegert from the Vancouver Prostate Centre’s Laboratory for Advanced Genome Analysis facility.  Chapter 5: The generation of bacterial expression plasmids, expression and purification of proteins were performed with the assistance of Eun-Jung Kim, Lauren Coombe, Melissa Ng, Alix Thomson, Udit Dalwadi, Lisa Lee and Lucy Mei.  The in vitro phosphatase assays were performed with the assistance of Alix Thomson, Lisa Lee and Kevin Chung.  The crystal structures were solved with the assistance of Dr. Bernd Gardill and Dr. Filip  v Van Petegem.  The STD-NMR experiments were performed by our collaborators, Dr. Raymond Andersen and Dr. David Williams.  List of Publication: The data presented in Chapter 3 have been published: Cheung, S.T., So, E.Y., Chung, D., Ming-Lum, A., and Mui, A.L. (2013) Interleukin-10 Inhibits Lipopolysaccharide Induced miR-155 Precursor Stability and Maturation. PloS ONE 8(8): p. e71336. Ethics Approval:  All biohazardous experiments were performed in accordance with the Health Canada, Laboratory Biosafety Guidelines under protocols B12-0012 and B15-0187.  All animal experiments were performed in accordance with the UBC Animal Care Committee guidelines under the following protocols:  SHIP1 KO mouse colony: A13-0203 Harvest of tissues and cells: A11-0218      vi Table of Contents Abstract ............................................................................................................................... ii Preface ................................................................................................................................ iv Table of Contents .............................................................................................................. vi List of Tables ..................................................................................................................... ix List of Figures ..................................................................................................................... x List of Abbreviations ....................................................................................................... xii Acknowledgements ......................................................................................................... xvi Dedication ...................................................................................................................... xviii Chapter 1: Introduction .................................................................................................... 1 1.1. Inflammation ......................................................................................................... 2 1.2. Macrophages ......................................................................................................... 5 1.2.1. Macrophage activation by TLR ligands .......................................................... 6 1.3. Lipopolysaccharide (LPS) .................................................................................... 8 1.3.1. Toll-like receptor 4 (TLR4) signalling ............................................................ 9 1.3.2. Negative regulation of TLR4 signalling ........................................................ 12 1.4. microRNAs (miRNAs) ........................................................................................ 14 1.4.1. miRNA biogenesis ........................................................................................ 15 1.4.2. miRNA functions .......................................................................................... 20 1.4.3. miRNAs in immune cells .............................................................................. 23 1.4.4. miRNA-155 ................................................................................................... 24 1.5. Interleukin-10 (IL-10) ........................................................................................ 31 1.5.2. IL-10 signalling ............................................................................................. 33 1.6. Signal transducer and activator of transcription 3 (STAT3) ......................... 36 1.6.1. STAT3 functions in immune system .............................................................. 36 1.6.2. STAT3’s role in IL-10 signalling .................................................................... 37 1.7. SH2-containing inositol-5´-phosphatse 1 (SHIP1) ........................................... 39 1.7.1. SHIP1 structure ............................................................................................. 40 1.7.2. SHIP1 functions in immune cells .................................................................. 42 1.7.2.1. SHIP1 function in B cell activation ............................................................. 42 1.7.2.2. SHIP1 function in T cell activation ............................................................. 43 1.7.2.3. SHIP1 function in NK cells function ........................................................... 43 1.7.2.4. SHIP1 function in mast cells ....................................................................... 44 1.7.2.5. SHIP1 function in macrophages .................................................................. 44 1.7.3. SHIP1 regulation ........................................................................................... 45 1.7.4. SHIP1 in diseases .......................................................................................... 47 1.8. Objectives and aims ............................................................................................ 49  vii Chapter 2: Materials and Methods ................................................................................ 52 2.1 Cells and reagents ................................................................................................ 53 2.2 Mouse colonies ..................................................................................................... 54 2.3 Plasmids ................................................................................................................ 55 2.3.1 Mammalian expression plasmids ................................................................... 55 2.3.2 Bacterial expression plasmids ........................................................................ 56 2.4 Lentivirus production and transduction ........................................................... 57 2.5 Cell stimulation .................................................................................................... 57 2.6 Luciferase reporter analysis ............................................................................... 58 2.7 Fractionation of nuclear and cytoplasmic RNA ............................................... 58 2.8 Immunoblot analysis ........................................................................................... 58 2.9 RNA extraction and real-time quantitative PCR ............................................. 59 2.10 RT-PCR of pri-miR-155 for DNA sequencing analysis .................................. 59 2.11 Measurement of TNFα production level .......................................................... 60 2.12 Continuous flow system ..................................................................................... 60 2.13 In vitro pull down assay ..................................................................................... 61 2.14 mRNA microarray ............................................................................................. 61 2.15 Identification of SHIP1, STAT3 regulated genes ............................................ 62 2.16 Protein expression and purification ................................................................. 63 2.16.1 HEK293T expression system ....................................................................... 63 2.16.2 Bacterial expression system ......................................................................... 63 2.17 In vitro phosphatase assay ................................................................................. 65 2.18 Protein crystallization, data collection, phasing and refinement .................. 66 2.19 Protein lipid overlay (PLO) assay .................................................................... 68 2.20 Saturation transfer difference nuclear magnetic resonance (STD-NMR) ... 69 2.21 Isothermal titration calorimetry (ITC) ............................................................ 69 2.22 Statistical analysis .............................................................................................. 70 Chapter 3: LPS and IL-10 Regulate miR-155 at the Maturation Step in Macrophages .................................................................................................................... 71 3.1. Introduction ......................................................................................................... 72 3.2. Results .................................................................................................................. 74 3.2.1. IL-10 inhibits LPS-induced pri-miR-155 and miR-155 expression in macrophages ................................................................................................ 74 3.2.2. LPS and IL-10 do not regulate miR-155 at the level of transcription ........... 75 3.2.3. Pri-miR-155 is constitutively transcribed but maintained at low level via degradation mechanism. .............................................................................. 78 3.2.4. LPS and IL-10 do not cause editing of pre-miR-155 .................................... 79 3.2.5. LPS and IL-10 do not regulate nuclear export of pre-miR-155 .................... 79 3.2.6. IL-10 inhibits LPS induction of miR-155 via SHIP1 and STAT3 ................ 82 3.3. Discussion ............................................................................................................ 87  viii Chapter 4: STAT3 and SHIP1 Work Together to Mediate IL-10 Functions ............ 91 4.1. Introduction ......................................................................................................... 92 4.2. Results .................................................................................................................. 95 4.2.1 Both STAT3 and SHIP1 mediate IL-10 inhibition of LPS-induced TNFα production. ................................................................................................... 95 4.2.2 Physical interaction of SHIP1 and STAT3 .................................................... 96 4.2.3 Y190F mutation on SHIP1 abolishes IL-10’s ability to inhibit TNFα .......... 97 4.2.4 SHIP1 and STAT3 co-regulate a number of IL-10 regulated genes. ........... 100 4.3. Discussion .......................................................................................................... 124 Chapter 5: Crystal Structure of SHIP1 Fragment Reveals Insight into SHIP1 Activator Binding ........................................................................................................... 130 5.1 Introduction ....................................................................................................... 131 5.2 Results ................................................................................................................. 133 5.2.1 The minimal enzymatic region of SHIP1 contains the phosphatase and C2 domains. ..................................................................................................... 133 5.2.2 Crystal structure of PAC .............................................................................. 139 5.2.1.1 Overall structure ........................................................................................ 141 5.2.1.2 Phosphatase domain .................................................................................. 142 5.2.1.3 C2 domain .................................................................................................. 149 5.2.1.4 Phosphatase-C2 interface .......................................................................... 154 5.2.3 Binding of SHIP1 activators to SHIP1 ......................................................... 158 5.3 Discussion ........................................................................................................... 164 Chapter 6: Conclusions ................................................................................................. 170 6.1. Conclusions ........................................................................................................ 171 References ....................................................................................................................... 179 Appendices ...................................................................................................................... 214     ix List of Tables  Table 1.1:   Negative regulation of TLR4 signalling ......................................................... 13 Table 1.2:   Regulation of miRNA biogenesis ................................................................... 18 Table 1.3:   Validated targets of miR-155.......................................................................... 25 Table 4.1:   SHIP1-regulated genes identified after 0.5-hour stimulation of LPS and LPS+IL-10 in SHIP1 WT and SHIP1 KO macrophages .............................. 102 Table 4.2:   Comparison of expression profiles of Lang et al. identified IL-10/STAT3-regulated genes in SHIP1 WT and SHIP1 KO cells. .................................... 106 Table 4.3:   Enriched pathways identified by NetworkAnalyst using Reactome database ....................................................................................................................... 111 Table 4.4:   Microarray data of previously described SHIP1-regulated genes. ............... 113 Table 4.5:   TargetScan analysis of SHIP1, STAT3, SHIP1-STAT3 gene subsets ......... 123 Table 5.1:   Data collection and refinement statistics ...................................................... 140 Table A.1:   Primers used in qPCR .................................................................................. 215 Table A.2:   Site-directed mutagenesis primers ............................................................... 217 Table A.3:   Ligase-independent cloning primers ............................................................ 218 Table A.4:   Results of SERp server ................................................................................ 220         x List of Figures  Figure 1.1       LPS/TLR4 signalling. ................................................................................... 8 Figure 1.2       Biogenesis of miRNA................................................................................. 17 Figure 1.3       The structure of SHIP1 and its binding partners. ....................................... 40 Figure 3.1       IL-10 inhibits LPS induction of pri-miR-155 and miR-155 expression in macrophages. .............................................................................................. 75 Figure 3.2       IL-10 does not regulate miR-155 expression at the transcription level. ..... 77 Figure 3.3       LPS and IL-10 do not cause editing on the pre-miR-155 sequence. .......... 79 Figure 3.4       IL-10 does not affect the export of pre-miR-155 from the nucleus to the cytoplasm. .................................................................................................. 81 Figure 3.5       SHIP1 mediates IL-10 inhibition of miR-155. ........................................... 85 Figure 3.6       SHIP1 and STAT3 play additive roles in IL-10 inhibition of miR-155. .... 86 Figure 4.1       Deficiency in STAT3 or SHIP1 results in impaired IL-10 inhibition in the first peak of TNFα production, but not the second peak. ........................... 96 Figure 4.2       His6-SHIP1 does not bind to Flag-STAT3 in an in vitro pulldown assay. . 97 Figure 4.3       Location of the mutated tyrosine in SHIP1 sequence. ............................... 98 Figure 4.4       SHIP1 Y190F impairs IL-10 inhibition of TNFα in activated macrophages. .................................................................................................................... 99 Figure 4.5       Identification of candidate SHIP1-STAT3 regulated genes. .................... 108 Figure 4.6       Interacting genes in the SHIP1-regulated gene subset. ............................ 110 Figure 4.7       Real time PCR revealed that many of the IL-10 regulated genes require SHIP1 and STAT3. .................................................................................. 119 Figure 5.1       PPAC and PAC have similar enzymatic activity as full length SHIP1. ... 135 Figure 5.2       AQX-MN100 is able to enhance the enzymatic activity of PPAC and PAC. .................................................................................................................. 136 Figure 5.3       Calcium reduces basal enzyme activity but enhances activation by SHIP1 activators. ................................................................................................. 138  xi Figure 5.4       Structures of wild type PAC2 and PAC1cc. ............................................. 142 Figure 5.5       Sequence alignments of mouse phosphoinositol-5'-phosphatases. .......... 144 Figure 5.6       Superposition of mouse SHIP1, human INPP5B and human SHIP2 phosphatase domains. ............................................................................... 147 Figure 5.7       Position of LC1R and LC2R in mouse SHIP1 or INPP5B phosphatase domains. ................................................................................................... 149 Figure 5.8       Structures of C2 domains. ........................................................................ 150 Figure 5.9       SHIP1 C2 domain does not contain the polybasic cluster as other C2 domains. ................................................................................................... 153 Figure 5.10     The interface between phosphatase domain and C2 domain. ................... 155 Figure 5.11     Potential AQX-MN100 binding sites in PAC. ......................................... 157 Figure 5.12     SHIP1 binds to both PI(3,4)P2 and PI(3,4,5)P3 through its C2 domain. .. 159 Figure 5.13     Binding of AQX-151 and PI(3,4)P2 to C2 domain by STD-NMR. ......... 161 Figure 5.14     No binding of AQX-1125 or PI(3,4)P2-diC8 to PAC1 is detected by ITC. .................................................................................................................. 163 Figure A.1      The BIC promoter reporter is unresponsive to LPS and IL-10. ............... 218 Figure A.2      CHX treatment alters the expression level of GAPDH and actin, but not that of 18S rRNA. ..................................................................................... 219 Figure A.3      4-HT treatment in the AKT-ER cells increases phosphorylation of GSK3β. .................................................................................................................. 220     xii List of Abbreviations  4-HT 4-hydroxytamoxifin AGO Argonaute AMBP alpha-1-microglobulin/bikunin precursor AML Acute myeloid leukemia AMPK AMP-activated protein kinase AP-1 Activator protein 1  ARE AU-rich element ATF1 Activating transcription factor 1 BCR B cell receptor BCR/ABL Breakpoint cluster region/Abelson virus oncogene BIC B cell integration cluster BMDM Bone marrow derived macrophage BRCA Breast cancer (e.g. BRCA1) BTK Bruton’s tyrosine kinase CBR Calcium binding region CCL C-C motif chemokine ligand (e.g. CCL2) CD Custer of differentiation (e.g. CD14) ChIP Chromatin immunoprecipitation CREB cAMP-responsive-element binding protein CRLF2 Cytokine receptor-like factor 2 CSF-1 Colony stimulating factor-1 CXCL Chemokine (C-X-C motif) ligand (e.g. CXCL2) DAG Diacylglycerol DAMP Damage-associated molecular pattern DCP Decapping protein DGCR8 DiGeorge syndrome chromosoal region 8 DMEM Dulbecco's Modified Eagle Medium Dox Doxycycline eIF Eukaryotic initiation factor ER Estrogen receptor Ets E26 transformation specific EXP5 Exportin-5 FCS Fetal calf serum FcγR Fcγ-receptor FOXP3 Forkhead box P3 FZD7 Fizzled class receptor 7 GPR35 G protein-coupled receptor 35  xiii HDAC Histone deacetylase IBD Inflammatory bowel disease ICAM Intracellular adhesion molecule IFN Interferon IKK IκB kinases  IL Interleukin (e.g. IL-6, IL-10) ILK Integrin-linked kinase IMDM Iscove's modified Dulbecco's media IP3 Inositol-1,3,4-trisphosphate IP4 Inositol-1,3,4,5-tetrakisphosphate IRAK IL-1-receptor-associated kinase IRES Internal ribosome entry site IRF Interferon regulatory factor 3  ITAM Immune receptor tyrosine-based activation motif ITIM Immune receptor tyrosine-based inhibition motif IκB Inhibitor of κ light chain gene enhancer in B cells  Jak1 Janus kinase 1 JNK c-Jun N-terminal kinase KHSV Kaposis sarcoma-associated herpesvirus KO Knockout KSRP KH-type splicing regulatory protein LBP LPS-binding protein LC1R Lipid chain 1 recognition LIC Ligase-independent cloning LPS Lipopolysaccharide LysM lysozyme M M1 classically activated macrophage M2 alternatively activated macrophage MAPK Mitogen-activated protein kinase MCH Major histocompatibility complex MDSC Myeloid-derived suppressor cell MDV Marek's disease virus miRNA microRNA MyD88  Myeloid differentiation primary response gene 88 NFκB  Nuclear factor κ B P4IM P4-interacting motif PABP Polyadenylate-binding protein PAC Phosphatase-C2  xiv PAMP Pathogen-associated molecular pattern PBS Phosphate buffered saline Perimacs Peritoneal macrophages PH Pleckstrin homology PI(3,4,5)P3 Phosphatidylinositol-3,4,5-trisphosphate PI(3,4)P2 Phosphatidylinositol-3,4-bisphosphate PI(4,5)P2 Phosphatidylinositol-4,5-bisphosphate PI3K Phosphoinositide 3-kinase PKB Protein kinase B PRR Pattern recognition receptor PRR Proline-rich region PTEN Phosphatase and tensin homolog PX Phox homology RA Rheumatoid arthritis RIP1 Receptor-interacting protein 1 RISC RNA-inducing silencing complex RNS Reactive nitrogen species ROS Reactive oxygen species SDS Sodium dodecyl sulphate SH2 Src-homology 2 SHIP1 SH2-containing inositol-5'-phosphatase 1 SMAD Sma and Mad related protein SNP Single nucleotide polymorphism SOCS1 Suppressor of cytokine signalling 1 SP Specificity protein (e.g. SP1, SP2) STAT Signal transducer and activator of transcription T2D Type 2 diabetes TAB TAK1-binding protein TAK1 TGFβ-activated kinase 1 TANK TRAF family member-associated NFκB activator TBK TANK binding kinase  TCR T cell receptor TGF Transforming growth factor Th T cell helper (e.g. Th1, Th2) TIR Toll/interleukin-1 receptor TIRAP  TIR domain containing adaptor protein  TLR Toll-like receptor TNFα Tumour necrosis factor alpha  xv TRAF6 TNF receptor-associated factor 6  TRAM TRIF-related adaptor molecule TRBP Transactivating response RNA-binding protein Treg Regulatory T cell TRIF TIR-domain-containing adapter-inducing interferon-β Tyk2 Tyrosine kinase 2 UBC13 Ubiquitin-conjugating enzyme 13  UEV1A Ubiquitin-conjugating enzyme E2 variant 1 isoform A UTR Untranslated region WT Wild type     xvi  Acknowledgements  This dissertation would not have been possible without the help and support of many people.  First and foremost, I would like to express the deepest appreciation to my supervisor, Dr. Alice Mui, who has always believed in me and constantly driven me to go beyond what I thought is the limit.  Her persistent encouragement and guidiance are invaluable in my doctoral studies.  Secondly, sincere thanks to the members of my supervisory committee, Dr. Filip Van Petegem and Dr. Eric Jan, who provided priceless input and recommendations to my studies throughout the years.  An additional thanks to Dr. Filip Van Petegem, who not only made an impact in my graduate studies, but also supported me tremendously in my undergraduate thesis.  While Dr. Franck Duong and Dr. Guy Tanantzapf research on fields unrelated to my doctoral studies, I am thankful for having them as my co-op supervisors in my undergraduate years; the time I spent in their labs have inspired me to pursue graduate studies and continue my dream to be a competent scientist. Thank you to all the past and present members in the Mui lab, especially the undergraduate students (aka, my minions), who tirelessly contributed to reagent preparation and data acquisition, as well as fulfilled my occasional requests for holiday decorations in the lab.  My thanks are extended to the members of the Van Petegem lab, who quickly took me as one of them and granted me the title of “honorary lab member”.  To my science friends, your insightful suggestions in my studies have been wonderful, and your endless support and encouragement have helped me through some of the most stressful days in this PhD journey.  To my non-science friends, thank you for  xvii being patient and tolerant of my countless “5 more minutes”, and for boosting my confidence and lifting my spirits whenever I doubt myself.   My family is clearly my biggest supporter, to whom I will forever be in debt.  They take care of me in every way possible so I can focus all my energy on my studies.  Thank you for always loving me, even when I am being unreasonable and unpleasant to live with at times.  You are awesome and I love you with all my heart.   Getting a PhD is certainly the hardest things I have ever done, and will be one of the most challenging things I will ever do in my life, but I have no regret about the decision to participate in this path.  It has been an eye-opening and inspiring journey.  Not only have I grown as a scientist, but I have also grown as a person – a stronger and better person who understands her values and dreams more than ever.  Because of this, I thank myself for not giving up and for soldiering on even in the most stressful times.    xviii Dedication       謹將此博士論文獻給我的外婆 1     Chapter 1: Introduction     2 1.1. Inflammation Inflammation is a complex physiological process involving both the immune and the circulatory systems, whose main activities are to protect the host from invading pathogens, and to repair damaged tissues.  The symptoms of inflammation were first described in the first century as pain, heat, redness and swelling, and later in the 1800s, loss of function was added as the fifth symptom [1,2].  Since then, considerable efforts have been put into understanding the source, the process and the resolution of inflammation.  Despite being a protective response, deregulated inflammation is associated with various inflammatory/immune disorders and diseases.  Today, partly due to a change of lifestyle in developed countries, we see a rise in various inflammation-related diseases such as inflammatory bowel diseases (IBD) and Type 2 diabetes (T2D).  Studies have found that westernized lifestyle, such as increased sugar and animal protein intake may increase the risk of developing IBD [3-5], while elevated sugar and fatty acids, along with a sedentary lifestyle, produces a chronic inflammatory state that underlies T2D [6-10].  Thus, understanding the cellular and molecular mechanisms of inflammation has become more urgent than ever.   Inflammatory response involves four stages that are characterized by: (1) inflammatory stimuli, (2) sensor cells, (3) inflammatory mediators produced by the sensor cells, and (4) the affected tissues [11].  Inflammatory stimuli can be categorized into exogenous and endogenous.  Examples include pathogen-associated molecular patterns (PAMPs) [12-14] and damage-associated molecular patterns (DAMPs) [15-17].  PAMPs are conserved molecules commonly expressed on specific groups of pathogens, while DAMPs are host molecules, many of which are cytosolic and nuclear proteins that  3 are only released outside of the cells during tissue injury.  PAMPs or DAMPs are sensed by specific receptors on the surface of resident mast cells and macrophages, which become activated and secrete soluble pro-inflammatory mediators that cause vasodilation and increased permeability of the blood vessels in the local area.  These mediators include cytokines such as tumour necrosis factor α (TNFα), interleukin-1 (IL-1), IL-6, IL-8 and IL-12, chemokines such as chemokine (C-C motif) ligand 2 (CCL2) and CCL3, as well as other non-protein factors such as histamine, prostaglandins and reactive oxygen and nitrogen species (ROS/RNS) [11].  The consequence is an increase in blood flow to the area and the entrance of blood plasma to the damaged tissue.  Concurrently, the expression of adhesion molecules is upregulated on the luminal surface of the endothelial cell layer.  Circulating leukocytes including neutrophils and monocytes in the blood establish interaction with these adhesion molecules that slow down their movement, and cause them to roll along the endothelial wall [18].  These leukocytes eventually leave the blood vessels to enter the tissue and migrate to the affected site following a chemotactic gradient [19,20].  The recruited leukocytes are activated by secreted cytokines, mainly TNFα, and together with plasma components such as complement proteins and antibodies, kill the invading pathogens or clear damaged cells.  Successful removal of the inflammatory stimuli switches on the tissue repair mechanism, whereas failure leads to the initiation of adaptive immune response [21,22].      Overall, inflammation is beneficial to the host.  However, the degree of inflammation needs to be tightly regulated to prevent pathologies from arising.  On one hand, too little inflammation impairs the ability of our immune cells to remove harmful stimuli (e.g. bacterial infection) leading to persistent sickness or progressive tissue  4 destruction.  On the other hand, excessive inflammation is destructive.  The inflammatory mediators secreted by activated leukocytes are harmful to healthy tissues when persistent.  For example, the process of acute systemic inflammation can result in over-accumulation of neutrophils and macrophages in organs causing dysfunctionality and even death [23,24].  Chronic inflammation in the colon causes IBD [25], and that in the joints causes rheumatoid arthritis (RA) [26].  The pathogenesis of atherosclerosis also involves inappropriate inflammation in which macrophages are activated by excess lipid uptake [27,28].  Inflammation must be properly restrained to avoid the development of these diseases.  Negative regulation of inflammation occurs at several levels.  The first one is the prevention of inflammatory stimuli from interacting with the receptors.  For example, PAMPs can be sequestered by the expression of soluble receptors [29-31].  The second level of regulation to terminate the inflammatory signalling pathways is via the production of cytosolic signalling inhibitors [32-34].  The third level involves the inhibition of pro-inflammatory cytokine expression through transcriptional and post-transcriptional controls.  Transcriptional control includes the inactivation of transcription factors important in inflammation [35-39], the expression of transcription repressors [40-43], or chromatin remodeling [44,45].  In addition, RNA binding proteins [39,46,47] and microRNAs [48-50] constitute the repertoire of post-transcriptional control.  The fourth level of negative regulation includes the production of decoy receptors [51,52] and receptor antagonists [53]; pro-inflammatory cytokines are prevented from initiating inflammatory pathways inside the cells.  The next layer of regulation is the production of anti-inflammatory cytokines such as IL-10 and transforming growth factor β (TGFβ) [11].  These negative regulators inhibit inflammation on multiple levels.  Examples include the  5 inhibition of TNFα production by IL-10 [36,46,54-56], and the expression of IL-1 receptor antagonist (IL1Ra) by IL-10 [57,58].   1.2. Macrophages Macrophages play a key role in inflammation [59-62].  They belong to the innate immune system, and provide an immediate response to invading pathogens in three main ways: phagocytosis and digestion of engulfed pathogens, production of pro-inflammatory cytokines and chemokines that activate and recruit other immune cells to the affected tissues, and presentation of antigens derived from digested pathogens to stimulate T cell activation and proliferation [63-65].  Macrophages also participate in the homeostasis of our body by removing apoptotic cells in the blood such as red blood cells [65].   Different subsets of macrophages have been described.  While the first classification divided macrophages into two types depending on their activation states: the “classically” activated (M1) macrophages and the “alternatively” activated (M2) macrophages, it has been greatly revised, and a more complicated and nuanced model exists [65-68].  The M1-M2 paradigm arose from observations that interferon-γ (IFNγ) and IL-4 elicited different reactions from macrophages in vitro.  Macrophages activated by IFNγ or ligands of Toll-like receptors (TLRs) such as lipopolysaccharide (LPS) express pro-inflammatory cytokines including IL-1, IL-6 and TNFα, as well as ROS and RNS [69].  Originally referred to as M1 type macrophages, these cells also upregulate the expression of major histocompatibility complex class II (MHC II) and antigen presentation molecules on the surface, both of which are essential for activating the adaptive immune system.  While M1 macrophages are responsible for the inflammatory response, another type of macrophages is derived by IL-4, IL-13 or glucocorticoid  6 treatment, and expresses relatively higher level of IL-10 that inhibits inflammation [70,71].  Initially called M2 type macrophages, these cells are associated with antagonizing inflammation and enhancing tissue repair response.  However, it has been shown that the M1 and M2 classifications are not mutually exclusive, and that they often co-existed.  Added to the complication in macrophage classification is the ability of macrophages to switch between the different activation states [72].  Moreover, a recent non-biased transcriptome based analysis showed that macrophages existed in an activation “spectrum” with M1 (IFNγ treated) and M2 (IL-4 treated) at the two ends, instead of discrete activation states [73].  To this end, two proposals have been suggested to revise and unify the nomenclatures in the macrophage system to reflect the diverse phenotypes that macrophages can adapt [68,74,75].  One proposal suggested the nomenclature to be based on the origin of macrophages, the source of activation and the expression of surface markers [68], and the other proposal suggested an ontology based approach [74,75].   1.2.1. Macrophage activation by TLR ligands Macrophages express different pattern recognition receptors (PRRs) that recognize different PAMPs and DAMPs.  Among PPRs, Toll-like receptors (TLRs) are probably the most studied [76].  There are 10 different TLRs in human (TLR1 to TLR10) and 12 in mouse (TLR1 to TLR9 and TLR11 to TLR14), and each of them recognizes different PAMPs, including lipids, nucleic acids, carbohydrate and peptides, either on their own or in partnership with another TLR [77].  Some TLRs (e.g. TLR1, TLR2 and TLR4) reside on the cell surface, whereas the others are localized at the membranes of endosomes (e.g. TLR3, TLR7, TLR8 and TLR9).    7 TLRs belong to the interleukin-1 receptor/toll-like receptor superfamily, defined by the presence of a Toll-IL-1 receptor (TIR) domain at the cytosolic side of the receptor [78]  (Figure 1.1).  TLRs also have a leucine-rich extracellular domain and a transmembrane domain.  Upon recognition of PAMPs, TLRs recruit different TIR-domain-containing adaptor proteins such as myeloid differentiation primary response 88 (MyD88), TIR-domain-containing adaptor-inducing interferon-β (TRIF), TIR-domain containing adaptor protein (TIRAP) and toll-like receptor 4 adaptor protein (TRAM), and activate downstream molecules that eventually lead to the expression of pro-inflammatory mediators [79].  Depending on the adaptor proteins recruited, these signalling events can be divided into either MyD88-dependent or MyD88-independent pathways.  Although both of these pathways lead to the activation of nuclear factor kappa B  (NFκB) and mitogen-activated protein kinases (MAPK), the consequence is somehow different.  The MyD88-dependent pathway is associated with the expression of pro-inflammatory cytokines, while the MyD88-independent pathway mediates the expression of Type I interferons. TLRs have a crucial role in macrophage activation and infection control.  Macrophages lacking TLRs or the adaptor proteins show hyposensitivity to pathogenic ligands and defective activation [80,81], and TLRs (or MyD88) knockout mice have an inability to clear infections [81-83].    8   Figure 1.1 LPS/TLR4 signalling.   LPS binding to TLR4 is facilitated by LBP, CD14 and MD2.  Both MyD88-dependent and MyD88-independent pathways are activated, leading to the expression of pro-inflammatory cytokines (such as TNFα), Type I interferons, as well as microRNAs.    1.3.  Lipopolysaccharide (LPS) LPS is a major component of the outer membrane of Gram-negative bacteria, and it has a vital role in the viability of the bacteria.  LPS contributes to the structural integrity of the bacteria by increasing the negative charge of the membrane and stabilizing the membrane structure, as well as protects the bacterial membrane from certain chemical attacks [84].  Liberated LPS from dying bacteria or multiplying bacteria binds strongly to the TLR4 complex on immune cells such as macrophages, and initiates inflammatory responses [85].    9 LPS has a molecular mass of 10-20 kDa, and its structure consists of a lipid component called lipid A, a core oligosaccharide and an O antigen [84].  The O antigen is the outermost domain of LPS, and is a repetitive glycan polymer consisting of one to eight glycosyl residues.  The composition of the O antigen varies among different bacterial strains.  Because the O antigen is exposed to the environment, it can be recognized by host antibodies and confers the immunogenicity of LPS.  The core oligosaccharide is attached to the O antigen, and commonly contains sugar such as 3-deoxy-D-mannococtulosonic acid and heptose, as well as non-carbohydrate components including phosphate and amino acids.  The lipid A is made up of a phosphorylated glucosamine disaccharide core that is covalently linked to multiple fatty acids.  These fatty acids anchor the molecule to the bacterial membrane while the rest of the molecule projects out to the environment.  The lipid A moiety is very conserved and is responsible for activating immune cells by binding to TLR4 [85].   1.3.1. Toll-like receptor 4 (TLR4) signalling LPS does not directly bind to TLR4, but instead requires additional proteins.  The first protein that LPS interacts with is the LPS-binding protein (LBP) [86].  LBP is a soluble lipid transferase that transfers LPS to CD14, a glycoprotein anchored into the host cell membrane [87].  CD14 then facilitates the transfer of LPS to the TLR4/MD-2 complex.  MD-2 is a soluble protein that non-covalently associates with TLR4 and enables responsiveness to LPS [88].  TLR4 then undergoes oligomerization and triggers a cascade of signalling events via the TIR domain in its cytoplasmic tail [85].  Depending on the identities of the recruited adaptor proteins, TLR4 downstream signalling can be divided into MyD88-dependent and MyD88-independent pathways [89-91] (Figure 1.1).    10 In the MyD88-dependent pathway, MyD88 and TIRAP are recruited to the activated TLR4 through the TIR domain.  MyD88 contains a death domain, and the death domain-containing IL-1-receptor-associated kinase-4 (IRAK-4) is recruited to the membrane where it is phosphorylated and activated [92].  IRAK-4 subsequently recruits and activates additional IRAKs including IRAK1 [93] and IRAK2 [94].  The IRAK4-IRAK1/2 complex dissociates from the receptor and activates TNF receptor-associated factor 6 (TRAF6), which then associates with ubiquitin-conjugating enzyme 13 (UBC13) and ubiquitin-conjugating enzyme E2 variant 1 isoform A (UEV1A) and becomes activated by Lys63-linked polyubiquitin chain [95].  TRAF6 subsequently activates transforming growth factor-β-activated kinase 1 (TAK1) [96].  TAK1 is involved in the activation of NFκB via the induction of IκB kinases (IKKs).  IKKα, IKKβ and IKKγ form a complex and phosphorylate inhibitor of κ light chain gene enhancer in B cells (IκB) proteins.  Phosphorylated IκB is then ubiquitinated and degraded by the proteasome, leading to the translocation of the transcription factor NFκB to the nucleus [97].  TAK1 also activates the p38 MAPK pathway and the subsequent induction of another transcription factor, activator protein 1 (AP-1) [98].  The activation of these transcription factors controls expression of pro-inflammatory cytokines, such as TNFα.   In the MyD88 independent pathway, TRIF is recruited to TLR4 via the adaptor protein TRAM [99,100].  TRIF then recruits TRAF3, which in turn associates with TRAF family member-associated NFκB activator (TANK), TANK binding kinase 1 (TBK1) and IKKε to mediate the activation of interferon regulatory factor 3 (IRF3) [101].  IRF3 is a transcription factor that controls the expression of Type 1 interferons such as IFNα and IFNβ [37].  TRIF also activates receptor-interacting protein 1 (RIP1) through TRAF3.   11 RIP1 is not involved in IRF3 activation, but is responsible for the activation of NFκB and MAPK pathways [102].    Figure 1.1 depicts a schematic diagram of TLR4 singalling and includes important signalling mediators in both MyD88-dependent and independent pathways.  However, the real picture is more complicated.  For example, TRIF interacts with TRAF6 or TBK, and these two interactions differentially regulate NFκB and IRF3 activation [103].  In addition, there are reports showing that TLR4 signalling leads to the activation of phosphoinositide 3-kinase (PI3K), involving MyD88 or TRIF [104-106], although the details of the mechanism are not well defined.  Upon activation, PI3K is recruited to the plasma membrane, where it converts phosphatidylinositol-4,5-phosphate, PI(4,5)P2, into phosphatidylinositol-3,4,5-phosphate, PI(3,4,5),P3, which then acts as second messenger and recruits pleckstrin homology (PH) domain or phox homology (PX) domain containing proteins.  These include Bruton’s tyrosine kinase (BTK) [107], integrin-linked kinase (ILK) [108] and protein kinase B (PKB, also known as AKT) [109-112].  These proteins are then activated and initiate signalling cascades that mediate cell growth, proliferation, activation and motility.  The role of PI3K in TLR signalling has been confusing with reports showing positive and negative contributions (reviewed in [113]).  Besides gene transcription, TLR4 signalling also plays a role in the post-transcriptional regulation of these cytokines.  For example, the translation of TNFα mRNA is mediated by the TRIF-dependent MAPK pathway [114].  TLR4 activation also stimulates the production of microRNAs (miRNAs), usually via NFκB activation [115-118].  miRNAs are small non-coding RNAs that regulate gene expression via mRNA  12 stability and degradation, as well as affecting translation [119].  Examples include miR-155 [120-122], miR-146b [123] and miR-21 [49]. 1.3.2. Negative regulation of TLR4 signalling  TLR4 signalling is necessary for pathogen clearance, but it also needs to be tightly regulated to prevent excessive signalling that eventually leads to pathological consequences.  Numerous negative regulators of TLR4 signalling have been discovered and their modes of actions can be divided into four categories: dissociation of signalling complex, degradation of signalling proteins, transcriptional control, and post-transcription control [124].  These are summarized in Table 1.1.  Some of these negative regulators are induced by LPS itself through a negative feedback mechanism (e.g. TRIM30a [125], Ah receptor [42]), while others are induced or further induced by anti-inflammatory cytokines, including IL-10 and TGFβ (e.g. miR-146b [48], miR-187 [126]). Positive regulators of TLR4 signalling can at the same time have negative roles in TLR signalling.  For example, TIRAP can associate with IRF7, but not IRF3, and inhibit its activation [127].  The consequence is a specific blockage of TLR3-induced IFNβ production, while TNFα and IL-6 productions are unaffected [127].  Another adaptor protein, TRIF, has been shown to negatively regulate TLR3, 4 and 5 signalling by causing the degradation of TLRs and inhibition of cytokine production [128-130].    13 Table 1.1: Negative regulation of TLR4 signalling Regulators Description References Degradation of signalling molecules  Atg16L1 negatively regulates TRIF-dependent pathway [131] Pin1 binds to phosphorylated IRF3 and promotes its proteasomal degradation [132] RAUL directly ubiqutinates IRF3 and IRF7, leading to their degradation [133] TAG required for TLR4 degradation [134] TRIM30a promotes degradation of TAB2-TAB3-TAK1 signal complex via lysosome [125] TRIM38 binds to TRAF6 and promotes K48-linked polyubiqutination for proteasomal degradation [135] Dissociation of signalling complexes  A20 removes K63-linked polyubiquitin chains from TRAF6 and inhibits TLR activation; binds to and inhibits IKK activation by TAK1 [32] BCAP interacts with MyD88 and TIRAP [136] soluble CD14 diminishes monocyte responses to LPS by transferring cell-bound LPS to lipoproteins [30] CD33 binds to CD14 to prevent its downstream signalling [137] cylindromatosis (CYLD) removes K63-linked polyubiquitin chains from TRAF6 and TRAF7 to suppress TLR activation [138] DUBA removes K63-linked polyubiquitin chains on TRAF3, and suppresses TLR-induced type 1 IFN production but does not affect NFκB activation [139] Fliih interacts with MyD88 [140] IRF4 competes with IRF5 for MyD88 causing inhibition of IRF-5 induced gene expression [41] NLRC3 interacts with TRAF6, and attenuates K63-linked ubiqutination of TRAF6 to inhibit NKfB activation [141] p38γ and p38δ MAPK isoforms block ERK activation in macrophages and dendritic cells [142] RP105 TLR homologue that lacks signalling domain; directly interacts with TLR4 signalling complex to prevent ligand binding [143] SARM bind to TRIF and block TRIF-TRAM complex formation [144] SENP6 deSUMOylates IKKγ and allows deubiquitinase CYLD to remove polyubiquitn chain necessary for function [145] SHP inhibits TRAF6 ubiquitination necessary for its function [146] SHP2 binds to the kinase domain of TBK1, and inhibits TRIF-dependent type 1 IFN production [147] TAG competes with TRAM for TRIF binding to inhibit TRIF-dependent pathway [134] TAK1 negatively regulates p38 activation [34] TANK binds to TRAF6, and inhibits ubiquitination and thus activation of TRAF6 [148]  14 Regulators Description References TERM2 transduces inhibitory signal to reduce production of TNFα, IL-12 p70, IL-6 and IL-10 [149] soluble TLR4 sequesters LPS [29] TNFAIP8L2 (TIPE2) binds to caspase 8 and regulates AP-1 and NFκB activation [150] USP4 removes K63-linked polyubiquitin chains from TRAF6 and suppress NFκB activation [38] Zc3h12a removes K63-linked polyubiquitin chains from TRAF6 and suppress NFκB activation [151] Transcription control  Ah receptor interacts with STAT1 and NFκB in IL-6 promoter and reduces IL-6 production [42] ATF3 recruits HDAC1 to pro-inflmmatory cytokine gene promoter; histone deacetylation limits access of transcription factors to inflammatory genes [44] Bcl-3 prevents p50 ubiquitination and degradation, and occupies NFκB DNA binding site to limit duration of TLR responses [152] IκBδ inhibits NKκB [35] MSK1/2 promotes binding of phosphorylated CREB and ATF1 to promoters of anti-inflammatory cytokines such as IL-10 and DUSP1 [153] Nurr1 interacts with p65, and represses transcription [40] Post-transcription control  miR-21 targets PDCD4 expression, which has pro-inflammatory functions by regulating NFκB activity and IL-10 production [49] miR-146b targets TRAF6 and IRAK1 mRNA [48] miR-155 bidirectional, fine tunes TLR signalling; targets MyD88, TAB2 and IKKε, as well as SHIP1 [154] miR-187 targets TNFα mRNA stability and translation, and indirectly decreases IL-6 and IL-12p40 expression via downregulation of IκBζ [126] TTP binds to AU-rich elements in TNFα mRNA and promotes mRNA degradation [43] Zc3h12a degrades IL-6 and IL-12p40 mRNA [155]  1.4. microRNAs (miRNAs) Discovered approximately two decades ago, miRNAs have been recognized as a new class of regulatory molecules in cells.  miRNAs are small non-coding RNAs that regulate target mRNA translation and stability in the cytoplasm.  This regulation depends on the association of the miRNAs to mostly the 3'-untranslated region (UTR) of the target  15 mRNAs [119].  It has been found that instead of one miRNA regulating one mRNA, one miRNA can regulate multiple mRNAs, and that each mRNA can be regulated by multiple miRNAs [156].  The intricate web of miRNA-mRNA interactions makes studying the function of a single miRNA difficult.  In addition, while the cytoplasm is the major site of action for miRNAs, emerging studies have found that mature miRNAs can be shuttled back to the nucleus and may play a role in pre-mRNA silencing, epigenetic regulation and alternative splicing [157].   1.4.1. miRNA biogenesis  The biogenesis of miRNAs (Figure 1.2) starts with the generation of a long primary miRNA transcript (pri-miRNA) transcribed by RNA polymerase II [158] or RNA polymerase III [159].  Majority of the human miRNA genes are located within the introns of protein-coding or non-coding transcripts, but some are encoded by exonic regions [160], indicating that miRNAs may be transcribed in parallel with mRNA transcripts.  There are also miRNAs that are expressed as their own transcripts.   Maturation of pri-miRNA is initiated by the microprocessor [161].  The microprocessor complex is composed of the class III RNase Drosha, and DiGeorge syndrome chromosomal region 8 (DGCR8) that binds to Drosha to increase its stability [160].  The size of the pri-miRNAs varies, but they typically contain a stem-loop that upon processing becomes the precursor miRNA (pre-miRNA).  Pre-miRNAs can also be directly spliced out of introns, bypassing the microprocessor; these are known as mirtrons [162].  A pre-miRNA is about 65 nucleotides in length. After Drosha processing, the pre-miRNA is transported from the nucleus to the cytoplasm via a transport complex formed by Exportin-5 (EXP5) and the GTP-binding  16 nuclear protein, Ran-GTP [163].  GTP is hydrolyzed after translocation of the pre-miRNA, causing the release of pre-miRNA from the complex into the cytoplasm.  It has been shown that a 2-nucleotide overhang at the 3'-end of pre-miRNAs is preferred for nuclear export [164].  In additional to exporting pre-miRNA, EXP5 may have a role in protecting pre-miRNA from degradation in the nucleus, since knocking down EXP5 does not cause an accumulation of pre-miRNAs in the nucleus [163]. In the cytoplasm, further processing is carried out by another class III RNase, Dicer, which cleaves away the terminal loop of pre-miRNA to produce an imperfect RNA duplex about 22 nucleotides long [165].  Dicer forms a complex with transactivating response RNA-binding protein (TRBP), recruits Argonaute (AGO), and loads AGO with one of the RNA strands, which becomes the functional miRNA [166].  AGO is part of the RNA-inducing silencing complex (RISC) that functions to regulate mRNA.  Inside RISC, miRNA acts as a guide by base pairing with its target mRNAs, and AGO recruits other factors necessary for downstream functions.  There are four AGOs in mammals, named AGO1 to AGO4, but only AGO2 has endonuclease activity [167].  The four AGO proteins have overlapping functions [168] and do not show preference for specific sets of miRNAs [168-170].  17   Figure 1.2 Biogenesis of miRNA.   Pri-miRNA is transcribed by RNA Pol II or RNA Pol III, and then processed by the microprocessor complex to generate pre-miRNA.  Subsequently, pre-miRNA is transported from the nucleus to the cytoplasm through Exportin-5.  In the cytoplasm, Dicer/TRBP complex further processes the pre-miRNA into miRNA duplex.  The guide strand is then loaded into RISC to form a functional RISC, which reduces protein expression by translational repression and mRNA degradation.   The biogenesis and function of miRNAs have to be tightly regulated for many reasons, including the fact that more than 60% of human protein-coding transcripts contain at least one conserved miRNA binding site [171] and hence, may be regulated by  18 miRNAs.  Furthermore, dysregulation of miRNA expression is often associated with human diseases [172,173].  Thus, it is not surprising that every step of the miRNA biogenesis is regulated (Table 1.2). Table 1.2: Regulation of miRNA biogenesis Name Effect on miRNAs References Regulation of miRNA transcription DNMT1, DNMT3b reduces methylation of miRNA-20a promoter in glioma cells [174,175] MYC induces transcription of miR-17~92 and miR-9 but inhibits miR-15a; regulates transcription of Drosha [119,176-178] MYOD1 activates transcription of miR-1 [119,176,179] p53 induces transcription of miR-34 and miR-107 [119] REST (NRSF) recruits histone deacetylases and methyl CpG binding protein MeCP2 to inhibit miR-124 [180] ZEB1 and ZEB2 repress transcription of miR-200 [119,176,181] Regulators of microprocessor complex-mediated processing Drosha cleaves DGCR8 mRNA leading to its degradation [182,183] ERK1/2 phosphorylates DGCR8 to increase its stability [184] GSK3b phosphorylates Drosha; requires for its nuclear localization [185,186] HDAC1 deacetylates DGCR8 to increase its affinity to pri-miRNAs [187] MECP2 binds to DGCR8 to prevent miRNA processing [188] RNA-binding proteins ARS2 stimulates Drosha/Dicer processing and maturation of miR-21, miR-155, and let-7 [189,190] hnRNP A1 component of Drosha complex; binds loop regions of pri-miR-18a and facilitates Drosha-mediated processing [191,192] KSRP binds to terminal loop of miR-198 and facilitates its cleavage by Drosha [192] Lin-28 blocks Drosha and Dicer processing of pri/pre-let-7 by interacting with its terminal loop; blocks pre-miR-128 cleavage by Dicer; recruite TUT-4 [193-195] Nanog interacts with p68 and Drosha; regulates processing of pri-miR-21 [196] NF90/NF45 binds to pri-let-7a, pri-miR-15a~16-1, -21, -30a and reduces DGCR8 accessibility [197] p68/p72 components of Drosha complex, facilitates Drosha mediated processing of selected pri-miRNAs [198]  19 Name Effect on miRNAs References P53 interacts with p68; facilitates Drosha complex assembly and processing of selected pri-miRNAs [199] R-SMADs interacts with p68; facilitates processing of pri-miR-21and pri-miR-199a upon vascular TGFb and BMP stimulation [200,201] SF2/ASF facilitates Drosha-mediated cleavage of pri-miR-7, and possibly pri-miR-221 and -222, independently on its splicing factor activity [202] SNIP1 binds to Drosha and regulates maturation of miR-21, miR-22, miR-23, miR-25 and let-7i [203] SRp20, SRSF3 binds CNNC motifs on pri-miRNA and increase the processing of human pri-miRNAs (79% of human miRNAs) [204] TDP43 interacts with and increases the stability of Drosha; promotes Drosha and Dicer processing [205,206] Regulators of Dicer-mediated processing BCDIN3D binds to pre-miRNA and inhibits access of Dicer [207] ERK phosphorylates TRBP; upregulates growth-promoting miRNAs, and downregulates let-7 miRNAs [208] FMRP interacts with Dicer and TRBP, and pre-miRNAs; depletion impairs miRNA biogenesis [209] IRE1α cleaves selected pre-miRNAs during ER stress to release translational repression of the pro-apoptotic caspases 2 [210] KSRP binds to terminal loop of pre-miRNA, and facilitates Dicer-mediated processing [211] let-7 targets Dicer1 mRNA [212,213] MCPIP1 cleaves the terminal loop of the pre-miRNA [214] Regulators of RISC activity AKT3 phosphorylates AGO2 at Ser38 and enhances localization within the processing bodies [215] CP4H hydroxylizes Pro700 of AGO2, increases the stability of AGO2 and localization within the processing bodies [216,217] EGFR phosphorylates AGO2 at Tyr393, causing dissociation from Dicer [218] LIN41 ubiquitylates AGO2 for proteosomal degradation [219] MAPKAPK2 phosphorylates AGO2 at Ser387 in response to stress, leads to increased localization within the processing bodies [220] PARP polyADP-ribosylates RISC and inhibits their activity to repress targets [221] TRIM71 ubiquitylates AGO2 for proteosomal degradation [219]    20 Name Effect on miRNAs References Modification of the RNA molecules ADAR1/2 changes the RNA sequence of pri-miR-142, pri-miR-376a and pre-miR-151, and blocks processing by Drosha and Dicer [222,223] BCDIN3D methylates the 5'-end of pre-miRNAs and interferes with Dicer mediated processing [207] DIS3L2 recognizes the U tail generated by TUT4 and degrades the RNA [224,225] HEN1 adds terminal 2'O-methyl group to stabilize the miRNA [226] GLD2 adenylates miR-122 to increase its stability [227] PNPT1 degrades miRNAs [228] Tudor-SN interacts and cleaves dsRNA substrates containing multiple IU and UI pairs [222,229] XRN1 and XRN2 degrades miRNAs [230] Zcchc11 (TUT4) adds terminal uracil to miRNAs to stabilize or destabilize it [195,231]  1.4.2. miRNA functions Target recognition is important in miRNA-mediated gene regulation.  In plants, the miRNA-mRNA interaction is almost always near perfect complementarity, resulting in direct endonucleolytic cleavage and mRNA degradation [232].  However, in mammals, mismatches between miRNAs and target mRNAs are common, and target recognition is driven by the following “rules”: perfect match of the “seed” region on the miRNA, which spans from nucleotide position 2 to 7 from the 5'-end, to the mRNA target; mismatch in the central region of the miRNA-mRNA duplex; and complementary 3'-sequence to stabilize the interaction [204,233].  Targeting with mismatch at the seed region has also been reported [234-236].  This non-canonical targeting is generally less effective [234].  The most frequent site for miRNA binding is the 3'-UTR of target mRNAs.  Targeting within the 5'-UTR [237,238] (e.g. miR-10a [238]) or the coding region (e.g. let-7 in Dicer mRNA [239]) is less frequent as the translation machinery may displace RISC as it  21 moves along the mRNA.  Also, miRNA binding sites are preferentially found in AU-rich (ARE) region in the 3'-UTR [233].  Usually, multiple sites for the same miRNA or different miRNAs are required for efficient repression [240].  The GW182 proteins are an essential factor in RISC [241].  They interact directly with and act downstream of AGO.  Tethering GW182 to an mRNA is sufficient for translational repression, even in the absence of AGO1 in Drosophila [242], showing that GW182 is an effector of AGO function.   Recruitment of RISC to the target mRNAs leads to translational repression, as well as mRNA deadenylation and subsequent degradation.  There have been much discussions on whether miRNA-mediated translational repression and mRNA degradation act separately, in parallel or in sequence.  Accumulating reports have shown that the primary event mediated by miRNAs is translational repression, and that mRNA degradation may occur subsequently [243-247].  However, it is apparent that translation repression is required for miRNA-mediated mRNA degradation [247].  Several kinetic studies have demonstrated that translational repression precedes mRNA degradation [244-246] (Figure 1.2).   Translation initiation starts with the recognition of the mRNA 5'-terminal-7-methylguanosine (m7G) cap by the eukaryotic initiation factor 4F (eIF4F) through one of its subunits, eIF4E [248].  eIF4F also contains eIF4A and eIF4G.  eIF4A is an RNA helicase that unwinds the secondary structure of the mRNA 5'-UTR.  eIF4G interacts with polyadenylate-binding protein (PABP), which binds to the polyadenylated, or poly(A), tail of the mRNA.  This leads to “circularization” of the mRNA, which increases the affinity of eIF4F to the m7G cap and stimulates translation initiation.  eIF4G then  22 recruits eIF3, which facilitates the association of the 40S ribosomal subunit to the mRNA.  The 40S subunit scans the mRNA until it finds the start codon (AUG), followed by the joining of the 60S subunit and the beginning of the elongation step.  Initiation can also occur at internal ribosome entry sites (IRES) with some or no initiation factors [249].  Experiments on target mRNA reporters containing either the m7G cap or different IRES showed that miRNA-mediated translational repression only occurs on mRNAs that have a m7G cap [247], indicating that the translation initiation step is the major target for miRNA action and that the activity of the eIF4F complex may be affected by the miRNA machinery.  In fact, repression can be overcome in vitro by an excess amount of eIF4F [243].  It is also reported that eIF4A2 is a key component in the eIF4F complex through which miRNA functions, although the mechanism of action is unclear [247].  Translational repression is usually associated with subsequent mRNA degradation through the recruitment of deadenylase complexes.  Two complexes have been described: the CCR4-NOT complex and the Pan2-Pan3 complex [242,250-252], both of which can directly interact with GW182 of RISC.  Whether these complexes have redundant or distinct functions is still unclear.  In addition, GW182 can interact with PABP to compete for eIF4G binding [253,254], which is required for miRNA-mediated deadenylation of target mRNAs.  PABP can also associate with CCR4-NOT directly to initiate deadenylation [253].  The shortening of the poly(A) tail leads to decapping of the target mRNA, which leads to degradation [255].  GW182 has been reported to interact with decapping enzyme complexes DCP1:DCP2 [242,256]. miRNAs can also upregulate gene expression.  One of the first reports showed that while miR-369-3p normally represses the expression of TNFα, in quiescent cells,  23 miR-369-3p can upregulate TNFα translation [257].  miR-155 has also been shown to increase TNFα production after LPS stimulation [120] or alcohol treatment [121] in macrophages.  Another example is miR-10a, which binds to the 5'-UTR of ribosomal protein mRNAs to enhance their translation [238].   1.4.3. miRNAs in immune cells The essential role of miRNA in all biological processes is highlighted by the fact that knocking out Dicer in the mouse germline cells results in embryonic lethality [258].  Therefore, efforts have been made to generate lineage-specific knockout of Dicer in mice.  Transgenic mice with conditional Dicer-KO in T cells show a number of immunopathologies including splenomegaly, enlarged intestinal lymph nodes and colitis [259].  T cells isolated from these mice have reduced viability, impaired development and differentiation, as well as abnormal cytokine production [259].  Ablation of Dicer expression in early B cell progenitors blocks the transition from pro-B cells to pre-B cells [260].  In dendritic cells, Dicer is essential for maturation, turnover, and MHC II antigen presentation capacities [261].  Deletion of Dicer in macrophages enhances expression of LPS-induced cytokines, such as IL-1β and IL-10, indicating that miRNAs are important in LPS-induced macrophage activation [262]. miRNAs are crucial in the regulation of both innate and adaptive immunity [263-265].  Within the innate immune system, up to 52% of innate immune genes are predicted to be the targets of miRNAs [156], again pointing to the importance of miRNA-mediated regulation in the immune system.  The first step to understanding this regulation is to identify miRNA expression profiles in immune cells.  In fact, all immune cells express five specific miRNAs (miR-142, miR-144, miR-150, miR-155, and miR-223) [266].   24 Cells from different lineages also have unique miRNA expression profiles. Many of these miRNAs are involved in inflammatory responses, and they are implicated in different human inflammatory diseases including multiple sclerosis [267], rheumatoid arthritis [268,269], systemic lupus erythematosus [270,271], type 1 and type 2 diabetes [272,273], atopic dermatitis [274,275], IgA nephropathy [276], IBD [277], and celiac disease [278].  One of the most studied miRNAs in the immune system is miR-155.   1.4.4. miRNA-155 miR-155 was first identified as the B cell integration cluster (BIC) gene that is induced by a viral promoter insertion in the chicken genome [279].  Later, homologous genes were found in human and mouse, and comparison of these homologs showed a 78% identity over 138 nucleotides [280].  BIC is mapped to chromosome 21 in human (and chromosome 16 in mouse) [280], and miR-155 is mapped within an exon of BIC [281].  miR-155 is highly expressed in the thymus and spleen [280], but also detected in all human tissues [282].  Bioinformatics analysis using TargetScan 7.0 (August 2015) [283] predicted 3297 human transcripts and 2109 mouse transcripts to be miR-155 target candidates.  Validated targets are listed in Table 1.3, including genes involved in hematopoiesis (e.g. AICDA, ETS1, JARID2, SPI1), inflammation (e.g. SHIP1, SOCS1, MYD88, FADD, BACH1, RIPK1), and tumour suppressor genes (e.g. ZNF652).  It is consistent with the observation that high levels of miR-155 are associated with cancer [284].    25 Table 1.3: Validated targets of miR-155 Gene symbol  Gene name References Nuclear proteins AID  Activation-induced cytidine deaminase  [285,286] ARID2  AT rich interactive domain 2  [287] ARNTL  Aryl hydrocarbon receptor nuclear translocator-like [288] BACH1  BTB and CNC homology 1, basic leucine zipper transcription factor1  [287,288] BCL-6 B-cell lymphoma 6 protein [289] C/EBPβ CCAAT/enhancer binding protein, beta  [287,288] CUTL1 (CUX1)  Cut-like homeobox 1  [288] ETS1  v-ets erythroblastosis virus E26 oncogene homologue 1  [290,291] FOS FBJ murine osteosarcoma viral oncogene homologue [292] HDAC4 Histone deacetylase 4 [292] HIF  Hypoxia-inducible factor 1  [288,292] HIVEP2  Human immunodeficiency virus type I enhancer binding protein 2  [287] MAF  v-maf musculoaponeurotic fibrosarcoma oncogene homologue (avian)  [293] MEIS1  Meis homeobox 1  [291] PU.1 (SPI1)  Spleen focus forming virus (SFFV) proviral integration oncogene spi1  [288,294] SMAD2 SMAD family member 2 [295] SMAD5  SMAD family member 5  [287]  ZIC3  Zic family member 3  [287] ZNF652  Zinc finger protein 652  [287] JARID2  Jumonji, AT rich interactive domain 2  [288] TP53INP1  Tumour protein p53 induced nuclear protein 1  [296] Protein receptors AT1R  Angiotensin II receptor, type 1  [297,298] CSF1R  Colony stimulating factor 1 receptor  [288] CTLA-4 Cytotoxic T-lymphocyte-associated protein [299] IL13Rα1 IL-13 receptor α1 [300] S1PR1 Sphingosine-1-phosphate receptor 1 [299] TLR3 Toll like receptor 3 [301] Cytosolic proteins FADD  Fas (TNFRSF6)-associated via death domain protein  [302] MyD88 Myeloid differentiation primary response gene 88 [154,303] NKIRAS1 NFκB inhibitor-interacting Ras-like protein 1 [304]  26 Gene symbol  Gene name References PICALM  Phosphatidylinositol binding clathrin assembly protein  [288] RHOA  Ras homologue gene family, member A  [305] SLA  Scr-like-adaptor  [288] SOCS1 Suppressor of cytokine signalling protein 1 [306,307] Enzymes CASP3 Caspase-3 [308] IKKɛ  Inhibitor of kappa light polypeptide gene enhancer in B cells, kinase ɛ [302] MAP3K7IP2 (TAB2)  Mitogen-activated protein kinase kinase kinase 7 interacting protein 2  [309,310] RIPK1  Receptor (TNFRSF)-interacting serine/threonine kinase 1  [302] SHIP1 SH2 domain containing inositol 5'-phosphatase 1 [311-313]  1.4.4.1. miR-155 functions  miR-155 is required for normal immune function in both adaptive and innate immunity, as evident in the miR-155 knock out mice [293].  These mice contain normal numbers of most myeloid and lymphoid cells, probably because miR-155 expression is generally low in homeostasis.  However, protective immunity against Salmonella enterica serovar Typhimurium appears to be impaired, as vaccination with an attenuated form of the pathogen does not prevent these knockout mice from dying, unlike wild type mice.  Specifically, these mice have impaired B cell (reduced production of IgM and switched antigen-specific antibodies) and T cell responses.  In vitro assays using purified subsets of cells show that dendritic cells, although they mature normally in the absence of miR-155, fail to activate T cell efficiently, indicating a defect in antigen presentation.  Additional studies have suggested that miR-155 has important roles in the development and functions of different T cell subsets, including Th1, Th2, Th17 and regulatory T cells (Tregs) [314].    27  miR-155 has been implicated as a positive regulator of inflammation.  Bone marrow derived dendritic cells from miR-155 knockout mice show reduced production of pro-inflammatory cytokines such as IL-12 and IL-6 in response to LPS [315].  When miR-155-specific oligonucleotides are introduced in human monocyte-derived dendritic cells to reduce miR-155 inside the cells, production of IL-1β is decreased [316].  Similarly in macrophages, expression of miR-155 is strongly induced by ligands of TLR2, TLR3, TLR4, and TLR9, as well as pro-inflammatory cytokines TNFα, IFNβ and IFNγ [122].  This induction of miR-155 by TLR ligands is important for the production of pro-inflammatory cytokines.  For instance, miR-155 can enhance TNFα potentially via mRNA stabilization [120,121].  Another target of miR-155 is SH2 containing inositol 5'-phosphatase 1 (SHIP1) [311].  SHIP1 is a negative regulator of the PI3K/AKT pathway, which has a role in TLR-mediated cytokine production [317].  Luciferase reporter assays show that miR-155 targets SHIP1 by direct interaction at the 3'-UTR of SHIP1 mRNA.  Overexpression of miR-155 in the macrophage cell line RAW264.7 reduces SHIP1 protein level, and thereby increases AKT activation after LPS stimulation [311].  The strong link between SHIP1 and miR-155 is emphasized by the fact that knocking down SHIP1 or overexpressing miR-155 in the hematopoietic system in mice show strikingly similar histological features of myeloproliferative disorders [288].   The importance of miR-155 in inflammation is also seen in human disorders.  Patients with RA have upregulated level of miR-155 in their synovial membrane and synovial fluid macrophages, and this upregulation is associated with lower SHIP1 level and higher TNFα production [318].  Similarly, peripheral blood samples of RA patients have upregulated TNFα and IL-1β levels [319].  In vitro studies have suggested that the  28 underlying mechanism might involve miR-155 repression of suppressor of cytokine signalling 1 (SOCS1) expression [319].  In mice, knocking out miR-155 prevents the development of collagen-induced arthritis [318].  However, miR-155 also has a negative role in inflammation.  In macrophages, miR-155 suppresses LPS/TLR4 signalling by targeting IKKɛ, RIPK1, and FADD [120].  MyD88 is also a target of miR-155, and silencing miR-155 enhances inflammatory responses in the human macrophage-like cell line THP-1 [154].  These observations highlight that miR-155 has a fine-tuning role, rather than merely acts as an on/off switch for inflammation. miR-155 may be oncogenic, because overexpressing miR-155 in the B cells of transgenic mice eventually leads to the development of B-cell lymphomas [320].  Furthermore, an elevated level of miR-155 was found in B cell lymphomas (e.g. diffuse large B-cell lymphoma (DLBCL) [281,321], Hodgkin lymphoma [322,323] and primary mediastinal B-cell lymphoma (PMBL) [323]), B-cell chronic lymphocytic leukemia (B-CLL) [324], B cell and T cell acute lymphoblastic leukemia [325], and acute myeloid leukemia (AML) [326].  In addition, miR-155 is overexpressed in solid tumors such as breast cancer, colon cancer, cervical cancer and lung cancer [327].   1.4.4.2. miR-155 regulation Due to its wide-ranging effects on immune cell functions as well as its association with cancer, extensive efforts have been put into identifying the signalling pathways responsible for the expression of BIC/miR-155.  Promoter analysis of the BIC gene revealed that it contains a classic TATA box, and binding sites for transcription factors including NFκB, AP-1, and E26 transformation specific (Ets) [328].  With the use of different synthetic pathway inhibitors as well as luciferase reporter assays, B cell  29 activation has been found to induce miR-155 upregulation via AP-1 and NFκB, but not Ets [328].  Both AP-1 and NFκB pathways are also utilized by Epstein-Barr virus to attenuate miR-155 expression in B cells [287].   Genome-wide studies in Tregs showed that miR-155 is a direct target of the Treg-specific transcription factor, forkhead box P3 (FOXP3) [329,330].  miR-155 deficiency results in impaired development of Tregs [330].  By targeting SOCS1 in Tregs, miR-155 is involved in the homeostasis and survival of Tregs [330].  Interestingly, SOCS1 is also necessary for Treg function partly by maintaining FOXP3 expression [331].  This is another example of how miR-155 fine-tunes cell functions.   In macrophages that are stimulated by TLR ligands, both MyD88-dependent and independent signalling pathways are involved in the induction of miR-155, and this induction is blocked by inhibition of the c-Jun N-terminal kinase (JNK), suggesting that AP-1 is involved in miR-155 expression [122].  TNFα, IFNα and IFNβ stimulations also induce miR-155 expression [122].  While upregulation by IFNβ and IFNγ are mediated through the autocrine production of TNFα, TNFα directly activates miR-155 expression, also via JNK/AP-1 signalling [122].  Consistent with this observation, TNFα induction of miR-155 in THP-1 cells is reversed by pretreatment with an anti-inflammatory compound (resveratrol) due to the induction of miR-633, which decreases AP-1 activity [332].  Luciferase reporter assays confirm that LPS-induced miR-155 expression is mediated via the AP-1 site, but not the Ets or the NFκB sites [333].  The same study also shows that the anti-inflammatory cytokine IL-10 suppresses miR-155 expression, and that it requires the Ets site in the promoter region of BIC gene.  Although, the AP-1 mediated pathway is important in miR-155 upregulation, Tili et al. reports that LPS upregulates miR-155 in  30 RAW264.7 cells in an NFκB-dependent manner [120].  NFκB is required for vesicular stomatitis virus (VSV) infection and Helicobactor pylori infection to upregulate miR-155 expression in mouse bone-marrow derived macrophages (BMDM) [334,335].  Together, these studies showed that TLR agonists can stimulate the transcription of BIC/miR-155 through both AP-1 and NFκB-dependent mechanisms.     miR-155 is regulated by other transcription factors in non-immune cells.  SMAD4 mediates miR-155 expression in epithelial cells after TGFβ stimulation [336].  Requirement for BRCA1 to suppress miR-155 expression was discovered in differentiating mouse embryonic stem cells and depends on the interaction between BRCA1 and HDAC2 complex, suggesting that the BIC/miR-155 promoter is regulated epigenetically [337]. Besides transcriptional regulation, post-transcriptional regulation is also important in the production of mature miR-155 in LPS-stimulated macrophages.  Maturation of miR-155 is mediated by the RNA-binding protein, KH-type splicing regulatory protein (KSRP) [262].  KSRP binds to the terminal loop of pre-miR-155, which promotes the maturation of pre-miR-155 to functional miR-155.  Deficiency of KSRP causes an accumulation of pri-miR-155 and pre-miR-155, and a reduction in mature miR-155 level.  Besides miR-155, KSRP also binds to the terminal loop of let-7a-1, miR-21, miR-206, miR-1-1 and miR-1-2, and promotes their maturation at the Drosha-mediated processing, Dicer-mediated processing, or both [211].   1.4.4.3. miR-155 orthologue  To date, two viral-encoded miR-155 orthologues have been discovered.  miR-K12-11, found in the Kaposis sarcoma-associated herpesvirus (KSHV), has an identical  31 seed region as mammalian miR-155 [338].  Moreover, this viral miRNA shows functional similarity to miR-155 such as repressing BACH1 [339], C/EBPβ [339] and SMAD5 [340].  miR-K12-11 also shows similar in vivo activity to miR-155 in a mouse model [341].  Overexpression of miR-K12-11 or miR-155 results in splenic B cell expansion by targeting C/EBPβ.  The investigators suggested that it may be the underlying mechanism for the development of KSHV-associated lymphomagenesis.  More recently, Marek’s disease virus (MDV) was also found to encode a miR-155 orthologue, named mdv1-miR-M4-5p [342], which may play a role in the induction of Marek’s disease lymphomas [342,343]. 1.5.Interleukin-10 (IL-10) IL-10 was first discovered as a Th2 cell secreted factor, and originally named cytokine synthesis inhibitory factor due to its ability to inhibit Th1 cell cytokine production [344].  Later, it was found that much of the inhibitory role of IL-10 on T cells is indirectly mediated by its effect on macrophages.  IL-10 inhibits the production of pro-inflammatory cytokines (e.g. TNFα, IL-1β, IL-6, IL-8, IL-12 and IL-18) and chemokines (e.g. CXCL2, CXCL3 and IL-8), as well as the expression of MHC II and co-stimulating molecules that are important for macrophages to activate T cells [345-347].   IL-10 is produced by almost all immune cells, but its major producers are macrophages/monocytes, Th2 cells, mast cells and Tregs [348].  Expression of IL-10 can be induced by a wide range of stimuli including TLR agonists (e.g. LPS [345]), as well as TLR-independent stimuli (e.g. dectin-1 [349]).  In macrophages, IL-10 induction by LPS is MyD88 and TRIF-dependent, and requires both MAPK and NFκB pathways [350-353].  IL-10 is transcriptionally regulated by numerous transcription factors including NFκB,  32 C/EBPβ, specific protein 1 (SP1), SP2, activating transcription factor 1 (ATF1) and cAMP-responsive-element binding protein (CREB).  IL-10 expression is also mediated post-transcriptionally via its mRNA 3'-UTR [354], involving RNA-binding proteins (e.g. tristetraprolin [355]) and miRNAs (e.g. miR-106a [356], and miR-466I [357], miR-146b [354], and let-7 [358]).   IL-10 functions as a homodimer, and each monomer consists of 160 residues in human, and 157 residues in mouse, with 72% overall sequence identity.  The two monomers associate with each other non-covalently.  Structural studies show that each monomer consists of six α-helices, four of which from itself and the other two from the other monomer [359].  As a result, a homodimer with a V-shaped structure is formed.   1.5.1. IL-10 functions  IL-10 exerts effects on cells in both innate and adaptive immunity [348].  Macrophages are considered the major target of IL-10 due to its high expression level of the IL-10 receptor (IL-10R).  Specifically, when IL-10R1 was deleted in specific immune cells in mice, only myeloid-specific knockout, but not T-cell or B-cell specific knockout, showed an increased sensitivity to LPS administration [360], suggesting that IL-10 signalling in myeloid cells (including monocytes, macrophages and neutrophils) is crucial in controlling LPS response.  In the presence of inflammatory stimuli, macrophages become activated and execute an inflammatory response.  IL-10 suppresses cell activation via multiple ways.  Firstly, IL-10 can potently inhibit the production of cytokines (e.g. IL-1α, IL-1β, IL-6, IL-12, TNFα), chemokines (e.g. IL-8, CCL2, CCL3), and non-protein factors (e.g. nitric oxide, prostaglandin E2).  IL-10 also changes the expression of surface proteins.  IL-10 inhibits the expression of MCH II and co- 33 stimulatory molecule CD80 and CD86, which are necessary for antigen presentation and as a result, decreases macrophage’s ability to activate T cells.  In addition, IL-10 downregulates adhesion molecules such as intracellular adhesion molecule 1 (ICAM1) to inhibit macrophage interaction with epithelial cells, but upregulates the expression of CD16 and CD64, Fcγ-receptors (FcγR), to promote phagocytosis of inflammatory stimuli.  Meanwhile, IL-10 induces the production of anti-inflammatory mediators such as IL-1 receptor agonist (IL1Ra) and soluble TNFα receptor, which sequester the respective cytokines to inhibit their subsequent actions on neighbouring immune cells.  Furthermore, IL-10 modulates the expression of non-coding RNAs including miRNAs.  Examples include inhibition of LPS-induced miR-155 [333], and upregulation of miR-187 that targets the NFκB pathway to suppress expression of TNFα, IL-6 and IL-12p40 [361].   1.5.2. IL-10 signalling IL-10-mediated signalling starts with the engagement of IL-10 to the IL-10R [362].  The IL-10R is a tetramer composing of two copies each of two proteins: IL-10R1 [362] and IL-10R2 [363].  While IL-10R2 is shared by other cytokines in the IL-10 family, IL-10R1 is only utilized by IL-10 [364-366].  IL-10R1 is responsible for ligand association, and together with IL-10R2, transmits signals to downstream molecules [362,367].  Activation of the IL-10R causes the trans-phosphorylation and activation of receptor-bound tyrosine protein kinases, the Janus kinase 1 (Jak1) and tyrosine kinase 2 (Tyk2) [368].  These kinases in turn phosphorylate IL-10R1 at Y446 and Y496 in human (Y427 and Y477 in mouse), which then become the docking sites for signal transducer and activator of transcription 3 (STAT3) [369].  The interaction is mediated via the Src- 34 homology 2 (SH2) domain of STAT3 [369].  Upon recruitment, STAT3 is phosphorylated at Y705 and Y727, which promote its dimerization and its transactivational activity [368].  A recent study showed that the AMP-activated protein kinase (AMPK) is required for IL-10-induced phosphorylation of STAT3 [370].  The dimerized STAT3 then translocates to the nucleus, binds to STAT response elements, and regulates the expression of IL-10-response genes that execute the anti-inflammatory response.  IL-10 also suppresses inflammation via post-transcriptional mechanisms, such as increasing mRNA stability of anti-inflammatory molecules (e.g. IL1Ra) while destabilizing certain cytokine mRNAs (e.g. IL-1 [46,371], and TNFα [46,56,371,372]).   Analysis of intracellular signalling pathways downstream of the IL-10R has led to the model that activation of the STAT3 and expression of STAT3-response genes are sufficient to mediate all the anti-inflammatory actions of IL-10 [55,373,374].  However, there are both in vitro and in vivo evidence showing that STAT3 is not the sole mediator of IL-10 signalling (see Section 1.6.2).  Previous and ongoing studies in our laboratory found that the inositol 5'-phosphatase, SHIP1, could mediate IL-10 inhibition of activated macrophages [56,375,376].  Deficiency of SHIP1 results in reduced IL-10-mediated inhibition of LPS-induced TNFα both in a macrophage cell line and primary mouse macrophages [376].  IL-10 inhibits TNFα both transcriptionally, by reducing RNA polymerase II association with the TNFα promoter, and post-transcriptionally, by destabilizing TNFα mRNA.  SHIP1 appears to be involved in both processes [56,376].  Furthermore, IL-10 inhibits the mRNA levels of an additional 17 LPS-induced genes, and SHIP1 deficiency abolishes this inhibition for the majority of them [376].  Administration of IL-10 to mice treated with LPS in an endotoxemia model shows that IL-10 inhibits  35 TNFα production in wild type but not SHIP1 knockout mice [376].  These data support a role of SHIP1 in IL-10 function.   1.5.3. IL-10 in human diseases Due to its anti-inflammatory property, a defect in IL-10 signalling is associated with many autoimmune/inflammatory diseases [348,377].  The phenotype of IL-10 knockout mice clearly demonstrates the normal anti-inflammatory functions of IL-10.  These mice spontaneously develop colitis, and they become hypersensitive to inflammatory stimuli [378-380].  Similarly, in human, deficiencies or mutations in IL-10 or IL-10R cause early onset of IBD [381].  Also, polymorphisms in IL-10 genes are associated with asthma, allergies, and RA [382-384].  Emerging studies have shown a link between inflammation and metabolic disorders such as T2D [385], and in support of this link, several studies have found that IL-10’s anti-inflammatory action was compromised in T2D [10,386-388].  However, enhanced IL-10 activity is also not desirable.  Many tumour cells and pathogens express or induce expression of IL-10 to escape from the host immune system and to enhance their survival [389,390]. In the search for treating inflammatory diseases, IL-10 administration has showed satisfactory efficacy in mouse colitis models [391,392].  However, similar approaches in human IBD patients were not successful [393,394].  That may be because systemic IL-10 administration is not sufficient to deliver IL-10 to the inflammatory site in these patients [393].  Moreover, systemic IL-10 stimulates the production of pro-inflammatory cytokines such as IFNγ [395].  Also, some IBD patients have polymorphisms in their IL-10R1 gene [381], and that may cause them to be unresponsive to IL-10 administration.    36 1.6.Signal transducer and activator of transcription 3 (STAT3)  STAT3 is a transcription factor that belongs to the STAT protein family, all of which have similar structures consisting of a N-terminal domain, a coiled coil region, a DNA-binding domain, a linker, a SH2 domain and a transactivating domain [396].  STAT3 proteins were discovered through their ability to transmit signals from IFN and IL-6 receptors [397-399].  Mutations or activation of STAT3 are associated with different diseases in human.  Gain-of-function mutations in STAT3 have been reported to cause early-onset multisystem autoimmunity [400-402], whereas loss-of-function mutations in STAT3 are responsible for hyperimmunoglobulin E syndrome, characterized by recurrent infection, unusual skin rashes and severe lung infections [403].  These highlight the importance of STAT3 in regulation of immunity.  Besides, STAT3 (and STAT5) have been associated with cancer progression and survival [404-406].  In particular, persistent activation of STAT3 in cancer suppresses anti-tumour immunity, and mediates tumour-promoting inflammation [407-411].   1.6.1. STAT3 functions in immune system Knocking out STAT3 in mice lead to embryonic lethality, indicating the importance of STAT3 in early embryogenesis [412].  Thus, cell lines containing a dominant negative STAT3, as well as cell specific-knockout mice of STAT3 have been generated to assess the functions of STAT3 in different cell types in the immune system.   STAT3 plays a critical role in deactivation of macrophages and neutrophils.  Mice lacking STAT3 specifically in macrophages and neutrophils are highly susceptible to LPS-induced endotoxin shock, and produce increased levels of TNFα, IL-1β and IFNγ, compared to wild type mice [413].  Macrophages isolated from these mice are  37 constitutively activated, and secrete augmented levels of inflammatory mediators in response to LPS [413].  Furthermore, IL-10 is unable to suppress the production of these inflammatory mediators, indicating that STAT3 is essential in IL-10’s anti-inflammatory functions in macrophages [413].  STAT3 is also important in other immune cells.  Studies using mouse pro-B cell line BAF-B03 in which dominant negative STAT3 proteins (Y705F or D434A/D435A) were overexpressed have shown that IL-6 mediated STAT3 activation is involved in preventing B cells from undergoing apoptosis [414].  Similarly, using T cell specific knockout of STAT3, Takeda et al. showed that STAT3 is required for IL-6 to prevent apoptosis of normal T cells, and that STAT3 deficiency severely impairs T cell proliferation [415].  These studies demonstrate the anti-apoptotic properties of STAT3.  1.6.2. STAT3’s role in IL-10 signalling Microarray analysis shows that IL-10 only inhibits about 24%, and further induces about 6%, of LPS-induced transcription [416].  STAT3’s role is to stimulate the expression of specific gene products to mediate IL-10’s anti-inflammatory response [45].  Many of these genes have implication in inhibiting TNFα expression.  Bcl-3 inhibits TNFα transcription by interfering the binding of NFκB to the TNFα promoter [36].  ETV3, a transcription repressor, and SBNO2, a co-repressor, are also shown to inhibits NFκB transcription activity [417].  Furthermore, tristetraprolin (TTP), a RNA binding protein, binds to and destabilizes TNFα mRNA [46].   Recent genome-wide studies have revealed further details of STAT3’s role in IL-10 signalling [45,418].   Many IL-10 induced genes have proximal STAT3 binding sites in their promoter regions, and the major effect of STAT3 is to activate the transcription of  38 specific gene products [45].  Since IL-10 inhibits LPS signalling by downregulating LPS-induced transcription, one of the possible ways STAT3 function is to stimulate the expression of transcription repressors that ultimately suppress the expression of pro-inflammatory genes [45].  Moreover, distinct sets of STAT3-binding events have been identified in different cell types [418].  A small set of 35 genes are found to be STAT3-regulated in all four cell types tested, and these genes are involved in the regulation of STAT3’s own functions and cells growth [418].   The majority of STAT3-repsonse genes are cell-type specific, which can be explained by the different co-factors that STAT3 interacts with in each cell type [418].  In macrophages, IL-10 mediated STAT3 action is associated with the AP-1 transcription factor family, as well as the ETS family members [418].  While many of the studies aruge that STAT3 is sufficient for all IL-10 functions [55,373,374], other reports support a STAT3-independent mechanism.  First of all, a dominant negative STAT3, which lacks the transactivation domain, blocks IL-10-mediated inhibition of cell proliferation, but IL-10 is still able to suppress LPS-induced expression of IL-1β and TNFα [419].  Secondly, human monocytes containing another dominant negative STAT3 (Y705F) behave like the STAT3 knockout cells [420].  In cells containing STAT3 Y705F, IL-10 cannot inhibit the expression of TNFα receptor, COX2 and MHC II, as well as LPS-induced TNFα and IL-6 expression [420].  However, TNFα mRNA is still suppressed in these cells at early time point, while reversal of this suppression is seen at later time points, suggesting that a STAT3-independent mechanism is utilized by IL-10 to suppress TNFα mRNA at early time point.  39 The presence of a STAT3-independent mechanism is also supported by in vivo studies when comparing the results of endotoxemia experiments done in IL-10 knockout mice [421] and myeloid-specific STAT3 knockout mice [413].  In wild type mice, LPS administration leads to increasing serum TNFα levels peaking at 1 hour, which then slowly declines to baseline level after 3 hours.  In the IL-10 knockout mice, LPS-induced TNFα levels are sustained up to 6 hours [421].  In contrast, in the myeloid-specific STAT3 knockout mice, the high serum TNFα level induced by LPS gradually declines, which coincides with the production of endogenous IL-10 [413], suggesting that a STAT3-independent signalling pathway can mediate IL-10 function in these mice. 1.7.SH2-containing inositol-5´-phosphatse 1 (SHIP1)  SHIP1 is a negative regulator of the PI3K pathway by hydrolyzing PI(3,4,5)P3, which in effect, stops recruitment of downstream signalling molecules.  Two other phosphatases are also important in stopping PI3K activation; they are phosphatase and tensin homologue (PTEN) and SHIP2.  PTEN converts PI(3,4,5)P3 to PI(4,5)P2, and is a well-known tumour suppressor, whose mutations or deletions are often found in human cancers [422].  PTEN-deficient cells show over-activation of AKT, a crucial mediator of PI3K signalling, preventing them from responding to normal apoptotic signals, and resulting in abnormal tissue growth [422].  While SHIP1 and SHIP2 share high sequence identity and both convert PI(3,4,5)P3 to PI(3,4)P2, they have dissimilar roles in vivo due to the differences in their tissue distribution [423,424] and the protein-protein interaction domains they each possess [425].  SHIP2 is ubiquitously expressed and is important in insulin signalling.  SHIP1 has a more restricted expression profile.  It is primarily expressed in the hematopoietic system, but it is also found in osteoblasts and  40 mesenchymal stem cells [423].  The biological functions of SHIP1 not only depend on its phosphatase activity, but also rely on its adaptor function via its multiple protein domains [425,426].   1.7.1. SHIP1 structure SHIP1 is encoded by the INPP5D gene on chromosome 2 in human, and was first identified as a 145-kDa phosphorylated protein based on its ability to interact with adaptor proteins, Shc and Grb2, in immune cells after cytokine and growth factor stimulation [427].  SHIP1 was subsequently cloned and characterized as an inositol 5'-phosphatase [428].  Besides the phosphatase domain, SHIP1 contains an N-terminal SH2 domain, a PH-related (PH-R) domain [429], a C2 domain [430], and a C-terminal proline-rich region (PRR) that contains two NPXY motifs (Figure 1.3).    Figure 1.3 The structure of SHIP1 and its binding partners. SHIP1 contains a N-terminal SH2 domain, a central catalytic domain that is flanked by a PH-R domain and a C2 domain, and a C-terminal region that contains two NPXY motifs and three  Catalytic C2 PH-R SH2 NPXY PXXP Dok1/2 Shc P85 Gal1/2 Dab1 Grb2 PKCγ Src Lyn Hck Abl Shc SHP-2 CD22 PSTPIP2 2B4 Cas C-Cbl SLAM DAP10 DAP12 Doks FcγRIIA FcγRIIB FcγRIII Gab KLRG1 LAT PECAM-1 PI(3,4,5)P3 SHIP1 activators  41 PXXP motifs.  Proteins or small molecules that have been shown to interact with SHIP1 are indicated with the arrows.    SHIP1 has been demonstrated to hydrolyze inositol-1,3,4,5-tertrakisphosphatase (IP4) in vitro, and PI(3,4,5)P3 in vitro and in vivo.  SHIP1 has been described by our laboratory as an allosterically regulated enzyme that can be activated by its product, PI(3,4)P2, with the C2 domain being the binding site of PI(3,4)P2 [430].  A SHIP1 mutant that lacks the C2 domain shows normal catalytic activity, but PI(3,4)P2 can no longer enhance its activity [430].   Other domains on SHIP1 are important for its interaction with other proteins, as well as its recruitment to the plasma membrane, where its substrate is located [429,431-437].  The SH2 domain is characterized by a highly conserved sequence (DGSFLSV) that can mediate interaction with phosphorylated tyrosine (pTyr) of many proteins, including Shc, Grb2, Doks proteins, and with membrane receptors via their immune receptor tyrosine-based inhibition motif (ITIM) or immune receptor tyrosine-based activation motif (ITAM).  Conversely, when one or both of the NPXY motifs in SHIP1 are phosphorylated, SHIP1 can interact with SH2-containing proteins such as Shc, Dok1/2, and Grb2.  Moreover, the C-terminal PRR contains both Type I and Type II pro-rich motifs [438], which can mediate interaction with SH3-containing proteins like Grb2.  These protein-protein interactions indirectly bring SHIP1 to the plasma membrane.  Recently, our laboratory has identified the PH-R domain, a previously unknown domain of SHIP1, as a PI(3,4,5)P3 binding site, and found that it is important for direct recruitment of SHIP1 to the plasma membrane during phagocytosis [429].  42 1.7.2. SHIP1 functions in immune cells The importance of SHIP1 in immune homeostasis is demonstrated in SHIP1 knockout mice [439-442].  These mice are smaller in size, have shorten lifespan, and display abnormal pathologies such as progressive splenomegaly, osteoporosis, and massive myeloid infiltration of the lungs [439].  Their mast cells are hypersensitive, producing elevated levels of TNFα, IL-6 and IL-5, and causing chronic lung inflammation.  Myeloid cells from SHIP1 knockout mice are also hypersensitive to cytokines, growth factors and chemokines, causing the overproductions of granulocytes, mast cells and macrophages.  As a result, the SHIP1 knockout mice develop splenomegaly.  In addition, the SHIP1 knockout mice exhibit higher level of myeloid-derived suppressor cells (MDSCs) [443] and Tregs [444,445], possibly as a counter response to the inflammatory environment created by overproduction and hypersensitivity of myeloid cells.  Development of B cells and T cells are also altered in these mice, but studies using cell specific knockout mice show that these are indirect effects of SHIP1-deficient myeloid cells [446].   1.7.2.1. SHIP1 function in B cell activation   SHIP1 acts as a negative regulator in the activation of the B cell receptor (BCR) [426].  After BCR crosslinking with specific antigens, the ITAM region of BCR is phosphorylated and triggers downstream signalling events including the activation of PI3K pathway and MAPK pathway [447-449].  The generation of PI(3,4,5)P3 recruits AKT, which promotes cell growth, survival and differentiation [450], as well as BTK, which activates the phosphatase PLCγ2 that generates soluble effector inositol triphosphate (IP3) and diacylglycerol (DAG) [451].  These factors are important for  43 proper BCR activation.  Negative regulation is achieved via the activation of the inhibitory Fc receptor, FcγRIIB, and the subsequent recruitment of SHIP1 to the receptor’s phosphorylated ITIM [452].  There, SHIP1 dephosphorylates PI(3,4,5)P3 to inhibit AKT and BTK activation [453].  Also, SHIP1 interacts with other adaptor proteins (such as Grb2, Dok1 and Dok3) to suppress MAPK activation [454]. 1.7.2.2. SHIP1 function in T cell activation  SHIP1 is also implicated in the negative regulation of T cell activation.  Engagement of the T cell receptor (TCR) results in the phosphorylation of the TCR and the recruitment of tyrosine kinases such as ZAP70 [455].  That leads to the activation of PI3K-induced AKT and PLCγ2 via the adaptor LAT [455].  TCR activation also causes phosphorylation of DOK1 and DOK2, which then recruits SHIP1 through SHIP1’s SH2 domain [456].  At the same time, SHIP1 interacts with Grb2 via its PRR.  The SHIP1-Doks-Grb2 complex is then recruited to LAT, and subsequently inhibits PI3K and PLCγ2 activation [456].  However, in vivo studies using T cell specific knockout mice show that deficiency of SHIP1 does not alter TCR signalling [444,446]. 1.7.2.3. SHIP1 function in NK cells function  Natural killer cells, or NK cells, are cytotoxic cells that mediate rejection of virally infected and tumour cells.  They express a wide range of receptors including FcγRIIIA that can recognize abnormalities on target cells in order to induce apoptosis [457].  NK cells can also produce inflammatory cytokines such as TNFα and IFNγ [458].  SHIP1 has been shown to negatively regulate FcγRIIIA-mediated cytotoxicity by its interaction with the receptor-associated adaptor Shc [459].  This interaction is mediated via the pTyr on Shc and SHIP1’s SH2 domain [459].  44 1.7.2.4. SHIP1 function in mast cells Mast cells have cytoplasmic granules that contain various mediators including cytokines, chemokines, proteolytic enzymes and vasoactive mediators.  The best characterized stimulus for mast cells is IgE, which has important roles in allergic reaction [460].  Upon binding of IgE to its receptor, FcεRI, the ITAM of FcεRI is phosphorylated, and recruits and activates the Src kinase Syk, leading to the activation of PI3K and degranulation [461].  Activated mast cells also produce cytokines such as TNFα and IL-6 via the phosphorylation of LAT, recruitment of adaptor proteins, and the activation of Ras-dependent MAPK pathway [461].  SHIP1 has been shown to interact with FcεRI directly under supra-optimal IgE stimulation to downregulate PI3K-dependent signalling [462].  In addition, SHIP1 can suppress MAPK signalling through its interaction with Dok1, which recruits Ras GTPase-activating protein (RasGAP) to promote hydrolysis of GTP bound to Ras, resulting in the downregulation of Ras activation [463]. 1.7.2.5. SHIP1 function in macrophages Macrophages can adopt any activation state along an activation spectrum with one end having the previously named “M1” macrophages and the other end with “M2” macrophages [73].  Macrophages isolated from SHIP1 knockout mice demonstrate an M2 skewing phenotype [464], suggesting a suppressive role of SHIP1 in the development of this macrophage subtype.  Indeed, it has been showed that SHIP1 degradation induced by IL-4 is crucial for M2 skewing [465].  Also, SHIP1 knockout macrophages are hypersensitive to immune stimuli such as LPS; they produce elevated levels of TNFα, IL-6, IFNβ, IL-1β and ROS.  Therefore, SHIP1 is implicated in the development of endotoxin tolerance, a phenomenon of desensitization of certain immune cells to LPS by  45 prior exposure to a low dose of LPS.  Tolerant cells produce less pro-inflammatory cytokines in response to second challenge of LPS.  The development of endotoxin tolerance protects the host from hyperactivation of innate immune cells that can cause cell damage and eventually death.  In fact, SHIP1 knockout mice cannot establish an endotoxin tolerant state [112].  These studies suggest a negative role for SHIP1 in TLR4 signalling.  SHIP1 is upregulated by LPS via the production of TGFβ [466].  Upregulation of SHIP1 causes inhibition of the PI3K activation and thus decreases the production of TLR4-induced cytokines [112,317,466].  SHIP1 can also inhibit TLR4 signalling through a phosphatase-independent manner, perhaps by interference with the association of TLR4 and MyD88 [317].  Similarly, SHIP1 has a negative role in TLR3-induced IFNβ production possibly by destabilizing the interaction between TBK1 and the TRIF [467]. Moreover, SHIP1 has both positive and negative regulatory roles in the phagocytic activity of macrophages.  While SHIP1 knockout cells have enhanced particle uptake, SHIP1 overexpressing cells have attenuated phagocytosis [468].  Imaging experiments showed that SHIP1 localized to the phagocytic cup and the generation of PI(3,4)P2 by SHIP1 is essential for the proper formation and maturation of phagosome [469,470].  Our laboratory has shown recently that the PH-R domain is responsible for recruiting SHIP1 to the phagocytic cup [429].   1.7.3. SHIP1 regulation Expression of SHIP1 protein can be regulated via both transcriptional and post-transcriptional controls.  TGFβ induces SHIP1 expression through the SMAD transcription factors [466,471].  Additionally, SHIP1 mRNA is a target of miR-155 [311- 46 313,472].  Ubiquitination of SHIP1 and subsequent proteosomal degradation are also observed as a way to reduce SHIP1 protein level in cells [473].   The function of SHIP1 also depends on its cellular localization through different protein-protein interactions mediated by its NPXY motifs, PRR and SH2 domains, or direct interaction with the plasma membrane through PH-R domain, as summarized in Section 1.7.1.  SHIP1 enzyme activities can be altered as well.  For example, SHIP1 can be phosphorylated on Ser440 (mouse numbering) by cyclic AMP-dependent protein kinase (PKA), and this phosphorylation increases SHIP1’s catalytic activity [474,475].  Furthermore, the C-terminal region of SHIP1 may have inhibitory effects on the enzyme since a truncated mutant (residues 1-822) shows activity 8-10 fold higher than full length SHIP1 [474].  A more recent study suggested that SHIP1’s SH2 domain could interact with pTyr1020 in the SHIP1’s C-terminus to regulate its interaction with ITAM of FcεRI [476].   SHIP1 enzymatic activity can also be modulated by small molecules.  Our laboratory has discovered that SHIP1 phosphatase activity is allosterically activated by its product.  The allosteric binding domain is defined to be a C2-like domain C-terminal to the phosphatase domain [430].  We screened for small molecules that can act as allosteric activators of SHIP1 and identified a naturally occurring meroterpenoid called pelorol found in a Papua New Guinea sea sponge, Dactylospongia elegans, as a SHIP1 agonist [477].  Structural derivatives of pelerol were tested for the SHIP1-activating ability and one called AQX-016A, was found to have more potent activation ability on SHIP1 than pelorol [430].  AQX-016A inhibits macrophage and mast cell activation, and this inhibition is abolished in SHIP1 knockout cells, showing that AQX-016A selectively  47 targets SHIP1 [430].  In vitro enzyme assays show that AQX-016A preferentially activates SHIP1 over its close homologue SHIP2 [430].  Moreover, AQX-016A inhibits LPS-induced TNFα, as effective as dexamethasone (a reference standard), in a mouse endotoxemia model [430].  Another pelorol-based SHIP1 activator, AQX-MN100 was also described in the same study, and found to have the same activity as AQX-016A both in vitro and in vivo [430].  AQX-MN100 directly interacts with the C2 domain of SHIP1, as shown by scintillation proximity assay [430].  Furthermore, competitive assay suggests that AQX-MN100 competes with SHIP1’s natural activator (also its product), PI(3,4)P2, for the same site in the C2 domain, indicating that AQX-MN100 acts as an allosteric activator [430].  When a SHIP1 mutant that lacks the C2 domain was tested in an in vitro enzyme assay, it was found that this mutant was as active as the wild type enzyme, but it could no longer be activated by either AQX-MN100 or PI(3,4)P2, showing that the C2 domain is necessary for SHIP1’s allosteric activation [430].  In a later study, AQX-MN100 was found to decrease cell viability and induce apoptosis in several multiple myeoloma cell lines [478].  Additional studies showed that AQX-MN100 could enhance the efficacy of drugs currently used to treat multiple myeloma patients [478], suggesting a potential for SHIP1 activator to use in synergy with existing drugs.  Other SHIP1 agonists such as australin E [479] and turnagainolide B [480], as well as antagonists (3-α-aminocholestane, 3AC [481]), have also been described (review in [482]).   1.7.4. SHIP1 in diseases Given SHIP1’s negative effect on PI3K/AKT signalling, mutations or altered expression of SHIP1 are associated with a number of diseases including cancer and inflammatory diseases.  For example, SHIP1 expression is often downregulated in cells  48 from AML patients.  Moreover, 10 different missense mutations have been described in 3% of the patients, including mutations at the SH2 domain, the phosphatase domain and the C-terminal region of SHIP1 [483].  Interestingly, a high level of miR-155 has been found as a high-risk factor for AML [326], which may be due to miR-155 mediated reduction of SHIP1 levels.  Mutations or total loss of SHIP1 expression are also observed in T acute lymphoblastic leukemia (T-ALL) [484].  In chronic myelogenous leukemia (CML), SHIP1 is phosphorylated by a mechanism depending on the oncogenic BCR/ABL protein-tyrosine kinase [473].  Phosphorylated SHIP1 is then targeted for polyubiqutination by the E3 ligase c-Cbl and subsequent proteosomal degradation [473].  These studies suggest that SHIP1 is a tumour suppressor.  However, emerging data have pointed to a more complicated role of SHIP1 in cancer.  In fact, both agonistic [478] and antagonistic [481] SHIP1 modulators have demonstrated abilities to kill multiple myeloma cells.  That leads to the development of the “Two PIP Hypothesis” [436].  Unlike PTEN, which hydrolyzes PI(3,4,5)P3 to regenerate the PI3K substrate PI(4,5)P2, SHIP1 generates PI(3,4)P2.  This difference is crucial as it allows PTEN and SHIP1 to have very different effect on AKT signalling.  In fact, the PH domain of AKT actually has higher affinity to PI(3,4)P2 than to PI(3,4,5)P3 [485].  There is also evidence showing that the presence of both PI(3,4,5)P3 and PI(3,4)P2 are necessary for full activation of AKT [486,487].  Therefore, elevated levels of PI(3,4)P2 can potentially enhance AKT activation, and thus mediate cancer cell growth.  Consistent with this hypothesis, some leukemia cells contain increased levels of PI(3,4)P2 [488].  Moreover, mutations in, or reduced expression of, the INPP4B gene, which normally encodes a phosphatase that converts PI(3,4)P2 to PI(3)P, are associated with increased transformation of human  49 mammary epithelial cells, as well as decreased patients survival in breast and ovarian cancers  [489].  It must also be added that PI(3,4)P2 can actually recruit a distinct set of proteins to the plasma membrane [469,490-498].  These results highlight the importance of balancing PI(3,4,5)P3 and PI(3,4)P2 levels in cells to avoid the development of malignancies.   Since SHIP1 is a negative regulator of inflammatory signalling events in the immune system, SHIP1 is also implicated in inflammatory diseases.  SHIP1 knockout mice develop inflammation in their small intestine that closely resembles human IBD [499,500].  Consistent with that, single nucleotide polymorphisms (SNPs) that are enriched in patients with Crohn’s disease, a form of IBD, have been found in the area where the SHIP1 gene is located in the human genome [501].  Recently, significant reduction in SHIP1 protein level was found in about 15% of IBD patients, despite having normal mRNA levels [502].  While the details of SHIP1 action in these diseases are still being discovered, there is a clear implication of targeting SHIP1 as a potential therapeutic.   Because of SHIP1’s restricted expression in the immune system, drugs that specifically target SHIP1 will only affect the immune system with minimal side effects on other tissues.  In fact, a specific SHIP1 agonist, AQX-1125, is currently being developed and is shown to have satisfactory efficacy in reducing the symptoms of inflammation in different human diseases in clinical trials [503-505]. 1.8. Objectives and aims The overall objective of this thesis is to define the roles of STAT3 and SHIP1 in mediating IL-10 inhibition of activated macrophages.  Our laboratory has shown that both STAT3 and SHIP1 are required for IL-10 action, as SHIP1-deficient cells are  50 similarly resistant to IL-10 treatment, like STAT3-deficient cells.  Work from previous members of our laboratory has implicated SHIP1 in the regulation of transcription and translation of a representative inflammatory mediator, TNFα.  We hypothesized that IL-10 can also regulate non-coding RNAs such as miRNAs.  During the course of the project, two miRNAs have been independently identified by two other research groups as IL-10 regulated [333], one of which was also identified by us.  Furthermore, we expanded our search for other IL-10 regulated genes that depend on SHIP1, STAT3, or both proteins.  Finally, we have previously described a small molecule that activates SHIP1 enzymatic activity, and executes anti-inflammatory action similar to IL-10.  We characterized the ligand-SHIP1 interaction in hope of developing other (better) small molecular modulators of SHIP1.   The first aim of my thesis research was to determine the mechanism by which IL-10 inhibits miR-155 in LPS-stimulated macrophages.  miR-155 is one of the highly expressed miRNAs in TLR-activated macrophages, and while its targets include molecules involved in both positive and negative regulatory action, it is overall considered as a pro-inflammatory mediator.  McCoy et al. [333] has shown that IL-10 could inhibit LPS upregulation of miR-155 in a STAT3-dependent manner.  We specifically asked if SHIP1 is also involved in IL-10 inhibition of miR-155.  My second aim was to examine how STAT3 and SHIP1 work together downstream of IL-10.  To do this, we explored the relative contribution of STAT3 and SHIP1 on IL-10 regulation in activated macrophages with the use of a continuous flow system and also through global gene expression profiling.  Data from the first two aims reiterate the involvement of SHIP1 in IL-10 signalling, and highlight the use of SHIP1 activators to mimic IL-10  51 function to deactivate immune cells.  Thus, my final aim focused on the characterization of the interaction between SHIP1 and SHIP1 activators.  Specifically, we have characterized the SHIP1’s phosphatase and C2 domains, the minimal regions necessary for the regulation by SHIP1 activators, through the use of x-ray crystallography and other biochemical approaches.    52           Chapter 2: Materials and Methods     53 2.1 Cells and reagents RAW264.7 cells were obtained from American Type Culture Collection and cultured in Dulbecco's Modified Eagle Medium (DMEM) supplemented with 9% (v/v) fetal calf serum (FCS) (Thermo Fisher Scientific, Nepean, ON).  The generation of the doxycycline (Dox) inducible Scrambled siRNA and SHIP1 knockdown cell lines is described previously [56].  To generate the AKT-ER stable cell line, RAW264.7 cells were transduced with an AKT-ER construct as described in the “Plasmids and Lentivirus” section below.  AKT-ER expressing cells were selected by growth in 5 µg/ml blasticidin.   Primary peritoneal macrophages (perimacs) were isolated from mice by peritoneal lavage with 3 ml of sterile Phosphate Buffered Saline (PBS) (Thermo Fisher Scientific, Nepean, ON).  Perimacs were collected and transferred to “Primary cell media” consisting of Iscove’s Modified Dulbecco’s Medium (IMDM) (Thermo Fisher Scientific, Nepean, ON) supplemented with 10% (v/v) FCS, 10 µM β-mercaptoethanol, 150 µM monothioglycolate and 1 mM L-glutamine.  Bone marrow-derived macrophages (BMDMs) were generated by first collecting femurs and tibias from mice, and then flushing out the bone marrow through a 26-G needle.  Extracted cells were plated in “Primary cell media” on a 10-cm tissue culture plate for 2 hours at 37°C.  Non-adherent cells were collected and seeded at 9×106 cells per 10-cm tissue culture plate.  Cells were then cultured in the presence of 5 ng/ml colony stimulating factor-1 (CSF-1) (Stem Cell Technologies, Vancouver, BC).  Differentiated BMDMs were used after 7 to 8 days.  All cells were maintained in a 37°C, 5% CO2, 95% humidity incubator. Antibodies used include anti-SHIP1 (P1C1) mouse antibody (Santa Cruz Biotechnology, Santa Barbara, CA), anti-STAT3 mouse antibody (BD Transduction  54 Laboratories, Mississauga, ON), anti-His mouse antibody (Sigma-Aldrich, St. Louis, MO), and Alexa Fluor® 660 anti-mouse IgG antibody (Invitrogen, Burlington, ON).  LPS (E.  coli Serotype 0111:B4) was purchased from Sigma-Aldrich (St.  Louis, MO) and His6-tagged IL-10 was made in-house by expression in the mammalian 293T cells and purified by column chromatography to homogeneity as assessed by Coomassie staining of SDS-PAGE gels.  The STAT3 inhibitor STA-21 (Cedarlane Laboratories, Burlington, ON) was dissolved in dimethylsulphoxide (DMSO).  AQX-MN100 (Aquinox Pharmaceuticals, Vancouver, BC) and AQX-151 (Dr. Raymond Andersen, University of British Columia, Vancouver, BC) were dissolved in ethanol.  AQX-1125 (Aquinox Pharmaceuticals, Vancouver, BC) was dissolved in appropriate aqueous buffers depending on the experiments.   2.2 Mouse colonies BALB/c mice wild type (WT) or SHIP1 knockout (SHIP1 KO) mice were provided by Dr. Gerald Krystal (BC Cancer Research Centre, Vancouver, BC).  The generation of STAT3 KO mice started with crossing C57BL/6 STAT3flox/flox mice (Dr. Shizuo Akira, Hyogo College of Medicine, Nishinomiya, Japan) with  C57BL/6 LysMcre mice (Jackson Laboratory) Their offspring were heterozygous on both alleles, which were then crossed with homozygous STAT3flox/flox mice to produce mice that had genotype of STAT3 flox/flox /LysMCre+/-.  These mice were crossed with STAT3flox/flox mice to generate both STAT3 flox/flox /LysMCre+/- mice (referred to be STAT3 KO mice) and STAT3flox/flox mice (STAT3 WT mice) in the same litters.  All mice were maintained in accordance with the ethic protocols approved by the University of British Columbia Animal Care Committee.  55 2.3 Plasmids  2.3.1 Mammalian expression plasmids Luciferase reporter plasmids containing the BIC promoter were obtained from Dr. Eric Flemington (Tulane University, New Orleans, LA).  The mouse IkBζ promoter luciferase reporter was constructed into the pGL3-basic plasmid (Promega, Madison, WI) between the SacI and NheI sites, and contained the IkBζ promoter fragment (-400 to +1) generated by reverse transcription and PCR amplification from total mouse RNA.  The c-fos promoter reporter was previously described [506]. A plasmid construct containing a modified form of human AKT was kindly provided by Dr. Megan Levings (University of British Columbia, Vancouver, BC).  This AKT construct lacks the PH domain but has a src myristoylation signal sequence at the amino terminal end and the steroid binding domain of the estrogen receptor (ER) and a hemagglutinin tag at the carboxyl terminal end.  The AKT-ER sequence was sub-cloned into the pENTR-1A vector (Invitrogen, Mississauga, ON) and recombined into a modified lentiviral vector, pTRIPZ.   The mammalian expression plasmids of SHIP1 and PPAC were generated previously by past members of our laboratory.  Briefly, the coding region of full length SHIP1 or the PPAC fragment were amplified by PCR and cloned into the pENTR1A vector (Life Technologies) between the EcoRI and XhoI sites.  To generate the SHIP1 Y190F mutant, standard site-directed mutagenesis method was employed.  pENTR1A-His6-SHIP1 WT plasmid was used as the template for site-directed mutagenesis.  The primers used are in Table A.2.  The presence of the mutation was confirmed by DNA sequencing.  Subsequently, a LR reaction (Invitrogen, Burlington, ON) was performed  56 between pENTR1A construct and FUGWBW, which contains an ubiquitin promoter and a blasticidin-resistant gene to generate the desired expression plasmids.  Success of the LR reaction was confirmed by restriction enzyme digest. 2.3.2 Bacterial expression plasmids Ligase-independent cloning (LIC) methodology was used to make the bacterial expression plasmids.  The LIC-HMT plasmid was obtained from Dr. Filip Van Petegem (University of British Columbia, Vancouver, BC).  This plasmid contains a N-terminal tag composed of His6 and maltose binding protein (MBP), followed by a TEV protease cleavage site (abbreviated as the HMT-tag).  PCR was performed on pENTR1A-His6-SHIP1 WT with primers listed in Table A.3.  The PCR product was purified and treated with T4 DNA polymerase (LIC-quality) (Novagen, Madison, WI) in the presence of dCTP only.  The LIC-HMT vector was digested with SspI and the linearized plasmid was treated with T4 DNA polymerase in the presence of dGTP only.  Equal volumes of insert and vector were mixed and incubated at room temperature for 10 minutes, followed by transformation into chemical competent E.  coli DH5α cells using the standard heat shock protocol, and selection on kanamycin-containing LB agar plates.  To generate different PAC mutants, standard site-directed mutagenesis was employed.  Primers used are listed in Table A.2.  Identity of all plasmids were confirmed by DNA sequencing.   His6-C2 (residues 725 to 861) expression plasmid was generated by a past member of our laboratory using standard cloning strategy; PCR fragment containing His6-C2 coding sequence was cloned in the pET28c vector between EcoRI site and NdeI site.  Residue numbering of mouse SHIP1 sequence is based on the RefSeq entry with accession number of NP_034696.   57 2.4 Lentivirus production and transduction VSV-pseudotyped second-generation lentiviruses were produced by transient 3-plasmid co-transfection into HEK293T cells using either calcium phosphate method (AKT-ER reconstituted cells) or polyethylenimine (PEI) (Polysciences Inc., Warrington, PA) [507] as the transfection reagent (J2M KO reconstituted cells).  Lentivirus supernatant was concentrated by ultracentrifugation (25000 rpm for 2.5 hours) to generate the AKT-ER reconstituted cells, while fresh lentrivirus supernatant was used on J2M KO cells directly without purification.  FUGWBW lentivirus was also made as a control.  Cells were transduced with these viruses in the presence of 8 µg/ml protamine sulphate.  The successfully transduced cells were selected by growth in 5 µg/ml blasticidin (Invitrogen, Burlington, ON).   2.5 Cell stimulation RAW264.7 cells were seeded at 1.5 x 106 cells per well on 6-well tissue culture plates or 3 x 105 cells per well on 24-well tissue culture plates 1 day prior to stimulation.  The SHIP1 siRNA-transduced cell lines were left untreated or treated with 2 μg/ml Dox for 24 hours prior to cell seeding (a total of 48 hours treatment before stimulation) to induce knockdown of SHIP1.  The AKT-ER transduced cells were pretreated with 150 nM 4-hydroxytamoxifin (4-HT) for 20 minutes prior to stimulation.  For the STA-21 experiments, 30 μM STA-21 or DMSO control was added to the cells 1 hour prior to stimulation.  Cells were stimulated with 1-10 ng/ml LPS with or without the indicated concentrations of IL-10.  Perimacs were seeded at 3 x 106 cells per well in 6-well tissue culture plates and allowed to adhere overnight before stimulation.  For mRNA microarray analysis, 2 x 106 perimacs were seeded per well in 6-well tissue culture plate and left to  58 adhere for 2 hours prior to stimulation with 10 ng/ml LPS +/- 100 ng/ml IL-10 for 30 minutes. 2.6 Luciferase reporter analysis RAW264.7 cells were seeded at 2 x 105 cells per well on 24-well tissue culture plates 4 hours before transfection.  Each promoter reporter plasmid was co-transfected with phRL-TK using the XtremeGene HP transfection reagent (Roche Diagnostics, Laval, QC) according to manufacturer’s instruction.  Cells were rested for 24 hours prior to stimulation with LPS +/- IL-10.  Cells were then lysed in 200 μl of 1X Passive Lysis Buffer (Promega, Madison, WI) and luciferase activities were measured using the Dual-Luciferase Reporter Assay System (Promega, Madison, WI).  The typical transfection efficiency in RAW264.7 macrophages was about 20%. 2.7 Fractionation of nuclear and cytoplasmic RNA After stimulation, cells were rinsed with PBS and lysed in lysis buffer containing 10 mM Tris-HCl pH7.4, 150 mM NaCl, 1.5 mM MgCl2 and 0.65% Nonidet P-40 (NP-40), supplemented with 100 unit/ml RNase inhibitor (Roche Diagnostics, Laval, QC) for 30 minutes at 4°C.  Nuclei were pelleted by centrifugation and the supernatant (cytoplasmic fraction) was transferred to a new tube.  Both cytoplasmic and nuclear fractions were then prepared in Trizol reagent (Invitrogen, Burlington, ON) for RNA extraction. 2.8 Immunoblot analysis  Cells were lysed with lysis buffer containing 50 mM HEPES, 2 mM EDTA, 1 mM NaVO4, 100 mM NaF, 50 mM NaPPi and 1% NP-40, supplemented with Complete Protease Inhibitor Cocktail  (Roche Diagnostics, Laval, QC).  Lysates were incubated at  59 4°C for 30 minutes and clarified by centrifugation for 20 minutes at 12,000 g.  Proteins were then separated on a 7.5% SDS-PAGE and transferred onto polyvinylidene fluoride (PVDF) membrane (Millipore, Etobicoke, ON).  The membrane was blocked, probed with the indicated primary antibodies overnight, washed, developed with the Alexa Fluor® 660 anti-mouse IgG antibody and imaged using a LICOR Odyssey Imager.  Band intensities were quantified using the Quantity One Software (BioRad, Mississauga, ON). 2.9 RNA extraction and real-time quantitative PCR Total RNA was extracted using Trizol reagent (Invitrogen, Burlington, ON) according to manufacturer’s instructions.  About 2-5 μg of RNA were treated with DNAseI (Roche Diagnostics, Laval, QC) according to the product manual.  For miRNA expression analysis, 20 ng of RNA were used as the starting material in miRNA TaqMan assays (Applied Biosystems, Burlington, ON) according to manufacturer’s instructions.  For mRNA expression analysis, 120 ng of RNA were used in the Transcriptor First Strand cDNA synthesis kit (Roche Diagnostics, Laval, QC), and 0.1 μl to 0.2 μl of cDNA generated were analyzed by SYBR Green-based real time PCR (real time-PCR) (Roche Diagnostics, Laval, QC) using 300 nM of gene-specific primers (Table A.1).  Expression levels of miRNA and mRNA were measured with the 7300 RT-PCR system (Applied Biosystems, Burlington, ON), and the comparative Ct method was used to quantify miRNA or mRNA levels using snoRNA202 or GAPDH as the normalization control.  In the CHX studies, 18S rRNA was used as normalization control instead of GAPDH. 2.10 RT-PCR of pri-miR-155 for DNA sequencing analysis Total RNA was extracted from unstimulated or stimulated cells, as well as treated with DnaseI as described in the previous section.  About 500 ng of RNA were used to  60 generate cDNA consisting the pre-miR-155 sequence using a gene-specific RT primer (5’- TCTGTCTAGAAGTGGACTATCCTAGTAACC-3’).  The resultant cDNA was then amplified by PCR using the following primers: forward, 5’-TATGCTCGAGACCAGCTCATCTGAGAAAAC-3’; reverse primer was the gene-specific RT primer.  RT-PCR products were purified from agarose gel with the Qiagen Gel Extraction Kit (QIAGEN, Mississauga ON, Canada), and the sequence was determined through sequencing.   2.11 Measurement of TNFα production level J2M macrophages were seeded at 50000 cells per well in a 96-well tissue culture plate the day prior to experiment.  Media was changed the next day about an hour prior to stimulation.  Cells were stimulated with 1 ng/ml LPS +/- various concentrations of IL-10 for 1 hour.  Supernatant was collected and secreted TNFα protein levels were measured using a BD OptEIA Mouse TNFα Enzyme-Linked Immunosorbent Assay (ELISA) kit (BD Biosciences, Mississauga, ON).  Triplicates wells were used for each stimulation condition.   2.12 Continuous flow system  The continuous flow apparatus was constructed by a previous member of our laboratory [376].  BMDMs were seeded at 3x105 cells per well in a 24-well tissue culture plate that had been coated with poly-L-lysine (Thermo Fisher Scientific, Nepean, ON) and rinsed with PBS.  After overnight incubation, culture media was removed and Leibovitz’s L-15 (L-15) media (Invitrogen, Burlington, ON) supplemented with 3% FCS, 10 µM β-mercaptoethanol and 150 µM monothioglycolate was added.  Cells were allowed to equilibrate in L-15 media for 1 hour before being placed in the continuous  61 flow apparatus.  Stimulation solution was made in the same media equilibrated at 37°C, and was passed through a modified inlet fitted to the well by a syringe pump (New Era Syringe Pumps Inc., Farmingdale, NY).  A flow rate of 150 μl per minute was used.  At the same time, cell supernatants were removed from the well at the same flow rate, and fractions were collected at 5-minute intervals over the course of 4 hours.  These fractions were analyzed for secreted TNFα levels by ELISA.   2.13 In vitro pull down assay Flag-STAT3 was expressed in HEK293T cells in a similar fashion as His6-SHIP1, as described below.  Cell lysate was prepared in the same lysis buffer but without TCEP, and then incubated with M2-affinity resins (Eastman Kodak Company, New Haven, CT) for 1 hour at 4°C on a nutator.  Unbound proteins were washed by 3 x 10 column volumes (CV) of wash buffer (50 mM TrisHCl pH7.4, 150 mM NaCl, 0.02% Tween-20).  (Semi-)purified His6-SHIP1 protein was prepared in wash buffer, supplemented with 6 mM MgCl2, 2 mM CaCl2, and/or 20 μM AQX-151 before incubating with the Flag-STAT3 bound M2 affinity resins for 1 hour at 30C with agitation.  Resins were then washed three times in wash buffer, and proteins bound were released with the addition of boiled 1X SDS sample buffer.  Samples were then analyzed by immunoblotting with anti-SHIP1 antibody and anti-Flag antibody.   2.14 mRNA microarray Total RNA was extracted using Trizol reagent according to manufacturer’s instructions.  The quality of the RNA was assessed with the Agilent 2100 Bioanalyzer (Agilent, Mississauga, ON), and only samples with a RNA integrity number (RIN) greater than or equal to 8.0 were used for microarray analysis.  The suitable RNA  62 samples were then prepared following instruction of Agilent’s One-Color Microarray-Based Gene Expression Analysis Low Input Quick Amp Labeling kit (v6.0).  Briefly, 100 ng of total RNA were used to generate Cyanine-3 labeled cRNA and samples were hybridized on the Agilent Whole Mouse Genome Oligo Microarrays (Design ID 014868).  Arrays were then scanned with the Agilent DNA Microarray Scanner.  Data was processed with Agilent Feature Extraction 10.5.1 software and analyzed in Agilent GeneSpring 7.3.1 program.   2.15 Identification of SHIP1, STAT3 regulated genes  Data sets of 41174 probes were compared using Microsoft Excel (Microsoft, Redmond, WA).  We first excluded genes that were scored absent in any of the samples.  To identify differentially expressed genes, fold change was calculated as the “LPS+IL-10/LPS” ratio separately in SHIP1 WT and KO cells at 0.5 hour.  Threshold ratio was set to be smaller than 0.5 or greater than 1.5 for the genes to be considered as IL-10 regulated.  Genes that showed a 2-fold difference in “LPS+IL-10/LPS” ratios between SHIP1 WT and SHIP1 KO cells were considered as potential SHIP1-regulated genes.  A total of 122 genes were identified.   To identify IL-10/STAT3-regulated genes, two publications were consulted: Lang et al. [480] and Hutchins et al. [45].  Genes that appeared in both the SHIP1-regulated list (described above) and in one or both of these two publications were considered as potential SHIP1-STAT3-regulated genes.  The remaining STAT3-regulated genes that were not in our SHIP1-regulated gene subset were refereed as STAT3-regulated genes.    63 2.16 Protein expression and purification 2.16.1 HEK293T expression system  About 6 x 106 HEK293T cells per plate were seeded on 15 cm tissue culture plate the day prior to transfection.  Using polyethylenimine (PEI) (Polysciences Inc., Warrington, PA) as the transfection reagent, 60 μg of the expression plasmid were introduced in the cells.  Usually 3-6 plates of HEK293T were transfected at once.  Transfection media was replaced by fresh media after 4 hours incubation at 37°C, and cells were left in the incubator for about 60-66 hours before cells were collected by centrifugation at 2000 rpm for 15 minutes at 4°C.  Cell pellet was washed once with PBS, and lysed in lysis buffer containing 20 mM Tris-HCl pH 7.4, 150 mM NaCl, 10 mM tris(2-carboxyethyl)phosphine (TCEP) (Soltec Ventures, Beverly, MA), 5 mM imidazole,  0.5% NP-40, supplemented with 1X EDTA-free Protease Inhibitor Cocktail (Roche Diagnostics, Laval, QC) for 30 minutes at 4°C with nutation.  Cell debris was removed by centrifugation at 18000 rpm for 30 minutes at 4°C, and cleared cell lysate was loaded directly onto a Talon Co2+-affinity column (Clontech, Mountain View, CA).  The column was washed with 5 CV of Buffer I (20 mM Tris-HCl pH 7.4, 150 mM NaCl, 1 mM TCEP, 5 mM imidazole, 0.5% NP-40), followed by 5 CV of Buffer II (20 mM Tris-HCl pH 7.4, 250 mM NaCl, 1 mM TCEP, 5 mM imidazole, 0.005%-0.05% Tween-20).  Bound proteins were eluted with 6 CV of Buffer III (Buffer II + 50 mM imidazole).  The purity of the protein was analyzed by SDS-PAGE. 2.16.2 Bacterial expression system  The procedure for the expression and purification of PAC1 and PAC2 is as follows.  LIC-HMT expression vector was transformed into E.  coli Rosetta(DE3) placI  64 cells.  Overnight culture was inoculated with a 250-fold dilution to start the actual culture.  The cells were grown at 37°C in LB medium (supplemented with 50 μg/ml of kanamycin and 34 μg/ml of chloramphenicol) with shaking at 225 rpm.  When OD600 reached about 0.6, the culture was cooled down to room temperature before the addition of 0.4 mM isopropyl β-D-1-thiogalactopyranoside (IPTG) to induce the expression of recombinant protein.  Culture was left in the shaker overnight (usually 16-18 hours) at 22°C, and then collected by centrifugation (5000 rpm for 10 minutes at 4°C).  The cell pellet was subsequently resuspended in lysis buffer (20 mM Tris-HCl pH 7.4, 350 mM NaCl, 10 mM TCEP, 5 mM imidazole, supplemented with 1X EDTA-free Protease Inhibitor Cocktail (PIC) (Roche Diagnostics, Laval, QC) and 25 μg/ml lysozyme), and lysed via sonication (2 cycles of 2 minutes pulse) on ice.  Cell debris was removed by two rounds of centrifugation, first at 5000 rpm for 15 minutes at 4°C followed by 18000 rpm for 30 minutes at 4°C.  Supernatant was filtered with a 0.45 μm filter and loaded onto a Talon Co2+-affinity column, previously equilibrated with Buffer A (20 mM Tris-HCl pH 7.4, 250 mM NaCl, 1 mM TCEP), and washed with 10 CV of Buffer B (Buffer A + 5 mM imidazole).  Bound proteins were eluted with 6 CV of Buffer C (Buffer A + 50 mM imidazole).  To remove the HMT tag, TEV protease (purified in house as a His6-tagged protein) was added to the eluted protein, which was then dialyzed against Buffer D (20 mM Tris-HCl pH 7.4, 250 mM NaCl, 1 mM TCEP) overnight at 4°C with gentle stirring.  The dialyzed sample was loaded onto the Amylose column (New England Biolabs, Whitby, ON), and the flow through, which contained the untagged protein, was loaded onto the Talon column to remove the His6-TEV protease.  The flow through from the Talon column was dialyzed against Buffer E (20 mM Tris-HCl pH 7.4, 25 mM NaCl, 1  65 mM TCEP) overnight at 4°C with gentle stirring, and then loaded onto the ResourceQ column (6 ml column volume) (GE Healthcare, Mississauga, ON), followed by washes with 3 CV of Buffer E.  To elute the protein, Buffer F (20 mM Tris-HCl pH 7.4, 1000 mM NaCl, 1 mM TCEP) was also used.  A gradient from 25 mM NaCl (0% buffer G) to 200 mM NaCl (20% Buffer G) was used across 20 CV to separate the components in the protein sample.  The fractions were analyzed by SDS-PAGE.  PAC1/2 usually eluted from the ResourceQ column at ~130 mM NaCl.  The purified protein was concentrated to about 5-10 mg/ml using Amicon concentrators with 30K MWCO (Millipore, Etobicoke, ON), and exchanged into the desired buffer.  For protein crystallization, the desired buffer contained 50 mM Tris-HCl pH7.4, 25 mM NaCl and 0.5 mM TCEP.  Protein was stored at 4°C and used within 2-3 weeks of time.  We found that freezing and thawing the protein caused precipitation of the protein; thus, for long-term storage at -20°C, we included 50% glycerol in the protein solution to prevent freezing.  Expression and purification of His6-C2 were similar to those of HMT-tagged fusion protein, with the exclusion of TEV protease incubation, Amylose column and the second Talon column.   2.17 In vitro phosphatase assay The concentration of enzyme used in the reaction was pre-determined as followed: (1) phosphatase assay was performed on a 3-fold dilution series of each batch of enzymes in the absence of any activator under standard assay condition (described below), (2) a titration curve was plotted as A650 vs enzyme concentration, and (3) the concentration of enzyme that gave half-maximal A650 value was chosen for experiments.  Usually, 2 to 5 nM of enzyme were used.   The assay was performed in 96-well plates, and the standard volume per reaction  66 well was 25 ul.  Assay buffer contained 20 mM Tris-HCl pH 7.4, 150 mM NaCl, 0.05% Tween-20 and 4-10 mM MgCl2 +/- 2 mM CaCl2.  Enzyme was diluted in the assay buffer, and was incubated with or without test compounds (dissolved in ethanol) for 10 minutes at room temperature, before the addition of 50 μM of inositol-1,3,4,5-tetrakisphosphate (IP4) (Echelon Bioscience Inc., Salt Lake City, Utah).  The reaction was allowed to proceed for 10 minutes at 37C, and then stopped by the addition of malachite green reagent.  The amount of inorganic phosphate released was assessed by absorbance measurement at 650 nm.  Triplicate wells were done with each reaction.   For enzyme kinetics studies, different concentration of IP4 was used and reactions were stopped at different time points.  Initial velocities were calculated, and Vmax and Km were determined using the GraphPad 6 software. 2.18 Protein crystallization, data collection, phasing and refinement Initial crystallization hits were obtained via sparse matrix screening.  The sitting drop vapour diffusion method was performed in 96-well plates using commercially available crystallographic solutions (Qiagen, Toronto, ON).  The protein mixture was allowed to equilibrate for at least 19 hours before scoring under the microscope.  Several conditions gave crystals of PAC1 or PAC2, but none of these conditions gave diffraction quality crystals.  Optimization of crystallization conditions were performed by varying the pH and/or precipitant concentrations from the original screen conditions, as well as changing the concentration of protein used, in 24-well plate format using the hanging drop vapour diffusion method.  Diffraction-quality protein crystals were obtained at 4-7 mg/ml protein at room temperature: wild type PAC2 crystallized in 0.1 M Tris-HCl pH.5 and 20% PEG5000; PAC1cc crystallized in 0.1 M Tris-HCl pH7.7, 22% PEG1500 and 2  67 mM MgCl2 (space group C121), or 0.1 M HEPES-NaOH pH6.7, 20% PEG1500 and 5 mM MgCl2 (space group P 21 21 21).  Unique fragments of crystal clusters of protein were soaked for 5 to 10 seconds in the crystallization solution containing 25% isopropanol, and flash-frozen under liquid nitrogen.   Diffraction data sets were collected at the Advance Proton Source (APS) beamline 23-ID-D-GM/CA and the Canadian Light Source (CLS) beamline 08ID-1, and processed with XDS [508].  The first model built was PAC1cc with space group C121.  The data set was processed to 1.74Å.  Matthews coefficient calculation predicted two molecules in the asymmetric unit (ASU) with a solvent content of 42%.  A mixed model of the phosphatase-domain was created with the SCWRL server at the JCSG [509], built from SHIP2 phosphatase domain (PDB ID: 3NR8).  Initial phases were then obtained using Phaser MR [510], which could place two molecules (two phosphatase domains).  The result was analyzed in COOT [511] with obvious errors corrected and model in areas of weak density deleted.  After a round of restrained refinement in Refmac5 [512], ARP/wARP Classic [513] was used for automated model building starting from existing model.  ARP/wARP was able to build large parts of one C2 domain and fragments of the other.  These models for C2 domain were merged with the previous phosphatase-domain model from Refmac5.  After several rounds of manual model building, another round of ARP/wARP was utilized that built further pieces of the C2 domains as alanine backbone.  After this step, it was feasible to assign several stretches of sequence in one C2 domain and to manually build additional pieces in the second C2 domain.  The model was completed with subsequent rounds of manual model building in COOT and refinement in Refmac5.  The utilized resolution was limited to 2.1Å during this stage.  Automatically  68 generated local non-crystallographic symmetry (NCS) restraints were used in the refinement.  Towards the completion of the model, one TLS group per domain was defined and used in Refmac5.  For the second PAC1cc structure, the Matthews coefficient calculation indicated one molecule per ASU with a solvent content of 38%.  Chains A (phosphatase domain) and B (C2 domain) from the first PAC1cc model were used as a search model in Phaser.  One solution was found with RFZ=6.3, TFZ=8.5, PAK=6, LLG=144, LLG=11942.  The loop consisting of residues 436-444 was responsible for the clashes in the solution, and thus was removed in subsequent refinement.  The final model was built and refined with COOT and Refmac5. The Matthews Coefficient calculation of the wild type PAC2 data set predicted three, four or five molecules in the ASU.  Probability for 4 molecules was 0.70 with a predicted solvent content of 47%.  A search model was built from the second PAC1cc structure, with some areas deleted prior to the search.  The used search model consisted of residues 403-438, 446-516, 522-659, 669-718, 733-741, 749-768, 784-827 and 834-856.  Phaser MR was able to place four molecules with TFZ-scores between 21.8 and 89.3.  Model was refined using local NCS restraints throughout and TLS refinement in the final stages. 2.19 Protein lipid overlay (PLO) assay PLO assays were described previously [429] with minor modifications.  Lyophilized PI(3,4)P2-diC16 and PI(3,4,5)P2-diC16 were reconstituted in methanol:water (2:1.8 ratio), and diluted in the same solution to desired concentration before spotting on PVDF membranes (Millipore, Etobicoke, ON).  The membranes were dried, incubated in  69 blocking buffer (3% BSA in TBS) for 1 hour at room temperature, and then washed with TBST buffer (TBS and 0.05% Tween-20) until the membranes were wet.  Purified proteins were diluted in TBS and incubated with the PIP-spotted membranes for 5 hours at room temperature with gentle agitation.  Membranes were then washed with TBST thrice, incubated with anti-His antibody for 1 hour at room temperature, and washed again with TBST thrice before being incubated with the Alexa Fluor® 660 anti-mouse IgG antibody for 45 minutes at room temperature.  After three final washes in TBST, the membranes were imaged using LI-COR Odyssey Imager, and intensities were quantified with the ImageStudio software (LI-COR, Lincoln, NE).   2.20 Saturation transfer difference nuclear magnetic resonance (STD-NMR) Purified protein was concentrated and exchanged into D2O buffer containing 20 mM Tris-HCl pH7.4, 150 mM NaCl, and 1 mM TCEP.  Concentration of H2O was kept below 1% in all cases.  In some experiments, 6 mM MgSO4 was included in the buffer.  The STD 1H NMR spectra were recorded on a Bruker AV-600 spectrometer with a 5-mm CPTCI cryoprobe utilizing a standard Bruker pulse sequence (Bruker Corporation, Milton, ON).  In all experiments, 1.01 mM ligand and 10.1 µM of protein were used with a total volume of 600 μl D2O/buffer.  When AQX-151 was used, the total volume included 6 μl of DMSO-d6 containing 0.2 mg of ligand. 2.21 Isothermal titration calorimetry (ITC) Purified recombinant protein was dialyzed against ITC buffer (50 mM HEPES-NaOH pH 7.4, 150 mM NaCl, 1 mM TCEP) overnight at 4C with gentle stirring.  Protein was collected and any precipitation was removed by centrifugation at 13000 rpm for 15 minutes at 4C.  Protein concentration was determined by first measuring absorbance at  70 280 nm (A280) and then performing the appropriate conversion using the theoretical extinction coefficient, according to Beer’s Law.  Protein was then diluted to 0.1 mM with ITC buffer.  Lyophilized PI(3,4)P2-diC8 or AQX-1125 were reconstituted in ITC buffer at 1 mM on the day of experiment.  ITC experiments were performed in an ITC200 instrument (GE Healthcare, Mississauga, ON) at 25°C and a stirring speed of 300 rpm.  Twenty injections of 2 μl ligands were titrated into protein at a 3-minute interval.  Control experiment corresponded to ligand titration into ITC buffer.  Data were processed using MicroCal Origin 7.0 SR4.   2.22 Statistical analysis  All statistical analysis was performed using GraphPad Prism 6 software.     71         Chapter 3: LPS and IL-10 Regulate miR-155 at the Maturation Step in Macrophages    72 3.1.  Introduction Since the discovery of the first miRNA (lin-4) in 1993 [514] and the term “microRNAs” was coined in 2001 [515], scientists have found that miRNAs are involved in essentially all biological processes.  In particular, the critical roles of miRNAs in the development, maintenance and functions of immune cells have been extensively studied.   The first TLR-induced miRNA expression profiling study was done in human macrophages, and found that miR-146a, miR-132 and miR-155 are upregulated by LPS [123].  Subsequent studies reported that TLR activation upregulates the production of other miRNAs including miR-147 [516], miR-9 [517], miR-21 [49], miR-27b [518], miR-210 [519] and let-7e [520].  TLR activation also downregulates the expression of certain miRNAs such as miR-223 [521], miR-125b [120], and miR-98 [522].  The interplay of these miRNAs fine-tunes TLR signalling [115,116,523].   Our studies focus on miR-155, whose enhanced expression is associated with cancer [284,306,312] and inflammation-related diseases such as rheumatoid arthritis [318].  Thus, studying the regulation of miR-155 will be beneficial for development of useful therapeutics to treat the diseases.  miR-155 was the first miRNA that has been knocked out in mice, which developed normally but had defective innate and adaptive immunity [293].  When miR-155 is ubiquitously expressed in the hematopoietic compartment, the mice develops a myeloproliferavtive disorder, characterized by granulocyte and monocyte expansion, and splenomegaly due to extramedullary hematopoiesis [288].   Besides LPS, miR-155 expression can be induced by a wide range of immune stimuli [122], and its expression is positively correlated with the production of pro- 73 inflammatory cytokines such as TNFα [120].  Interestingly, miR-155 effect on TNFα production appears to be direct [121,302], likely due to increased stability of TNFα mRNA in the presence of miR-155 [121].  Other miR-155 targets include SHIP1 [311] and SOCS1 [335], both of which have negative roles in macrophage activation [112,317,524-526].  Even though the overall effect of miR-155 is pro-inflammatory, miR-155 also fine-tunes inflammation by targeting signalling molecules important in TLR signalling, such as IKKɛ [120], RIPK1 [120], and MyD88 [154]. Since IL-10 is a negative regulator of inflammation and macrophage activation, we hypothesized the IL-10 might suppress miR-155 induction by TLR agonists.  Indeed, as detailed in this chapter, IL-10 is able to inhibit miR-155 expression.  During the course of the experiments described in this chapter, another research group has also found that IL-10 inhibits LPS-induced miR-155 expression [333].  These investigators have showed that LPS induces miR-155 expression via the activation of the JNK pathway, and requires the AP-1 motif in the BIC promoter.  They have also demonstrated that IL-10 inhibits miR-155 expression in a STAT3-dependent manner via the Ets1 motif in the BIC promoter.  In addition, Ruggiero et al. [262] have found that LPS induction of miR-155 is post-transcriptionally regulated by the RNA binding protein KSRP, which specifically facilitates the maturation of pre-miR-155 to matured miR-155. Here, we show that IL-10 treatment does not affect the transcription of the miR-155 host gene nor the nuclear export of pre-miR-155, but rather destabilizes both pri-miR-155 and pre-miR-155 transcripts, as well as interferes with the final maturation of miR-155.  This inhibitory effect of IL-10 on miR-155 expression involves both the transcription factor, STAT3, and the phosphoinositol phosphatase, SHIP1.    74 3.2. Results 3.2.1. IL-10 inhibits LPS-induced pri-miR-155 and miR-155 expression in macrophages  We first examined the kinetics of IL-10 inhibition of pri-miR155 and mature miR155.  On one hand, as shown in Figure 3.1A, LPS-induced expression of pri-miR-155 was detected as early as 1 hour in the RAW264.7 macrophage cell line, peaked at 2 hours and declined after that.  The level of mature miR-155, on the other hand, was barely detectable at 1 hour and continued to increase over the course of 4 hours.  Addition of IL-10 inhibited expression of pri-miR-155, but inhibition was only observed after 1 hour and was statistically significant after 2 hours and later.  IL-10 inhibition of miR-155 was also delayed, with inhibition being statistically significant only at 4 hours.  Similar kinetics was observed in peritoneal macrophages freshly isolated from mice (Figure 3.1B).  The inhibitory effect of IL-10 on pri-miR-155 and miR-155 levels are similar to that reported previously [333].    75  Figure 3.1 IL-10 inhibits LPS induction of pri-miR-155 and miR-155 expression in macrophages.   (A) RAW264.7 parental cells or (B) perimacs were stimulated with LPS +/- IL-10 for the indicated times prior to total RNA extraction.  Expression levels of pri-miR-155 and miR-155 were determined by real time PCR and plotted relative to unstimulated samples.  Statistical significance between LPS and LPS + IL-10 treatments was calculated by a two-way ANOVA test with a 95% confidence (* p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001).  Similar results were observed in at least three independent experiments.  Representative data are shown.    3.2.2. LPS and IL-10 do not regulate miR-155 at the level of transcription  Several check points are in place to regulate the level of particular miRNAs in cells: transcription of pri-miRNA, Drosha-mediated generation of pre-miRNA, export of pre-miRNA and finally Dicer-mediated maturation of miRNA.  The kinetics of miR-155 expression in response to LPS +/- IL-10 (Figure 3.1A-B) indicated that the regulation of pri-miR-155 and mature miR-155 differs.  We first examined the potential effect of LPS ABRAW parental: pri-miR-1550 1 2 3 4 50306090120150180******Stimulation time (hour)relative pri-miR-155 expressionover 18SPerimacs: miR-1550 1 2 3 4 5051015LPSLPS + IL-10***Stimulation time (hour)relative miR-155 expression over snoRNA202 RAW parental: miR-1550 1 2 3 4 5020406080LPSLPS + IL-10****Stimulation time (hour)relative miR-155 expression over 18SPerimacs: pri-miR-1550 1 2 3 4 50204060*****Stimulation time (hour)relative pri-miR-155 expression over GAPDH 76 and IL-10 on the transcription of pri-miR-155 by using a luciferase reporter construct controlled by the BIC promoter (the host gene of miR-155).  A reporter harbouring the promoter of IkBζ acted as the control for our reporter assays.  IkBζ is a known LPS response gene.  As shown by real time PCR, we found that IL-10 inhibited LPS-induced IkBζ mRNA expression in RAW264.7 cells (Figure 3.2A).  The IkBζ promoter reporter showed similar LPS induction and IL-10 inhibition pattern (Figure 3.2B).  In contrast, we found that LPS did not induce BIC promoter activity compared to the unstimulated control (Figure 3.2B).  Similarly, addition of IL-10 did not affect the activity of the BIC promoter either.  The data were surprising since pri-miR-155, the primary transcript from the BIC gene, increased with LPS stimulation and decreased with IL-10 treatment (Figure 1A).  Also, the unresponsiveness of the BIC reporter to stimuli differs from McCoy et al.’s finding that LPS stimulated, while IL-10 inhibited, BIC reporter activity [333].  We assessed whether the difference between our and McCoy et al.’s BIC reporter results might be due to cell stimulation time, transfection reagent used, and/or transfection times; however, we consistently observed no change in the BIC reporter activity upon LPS and IL-10 treatment (Figure A.1).    77  Figure 3.2 IL-10 does not regulate miR-155 expression at the transcription level.   (A) RAW264.7 parental cells were stimulated with LPS +/- IL-10 for 1 hour before total RNA was extracted.  Expression levels of IkBζ were determined by real time PCR and plotted relative to unstimulated samples.  Statistical significance between the treatments was calculated by an unpaired two-tailed student’s t-test with a 95% confidence (** p < 0.01, **** p < 0.0001).  (B) RAW264.7 cells were transfected with TK-Renilla and BIC promoter reporter or IkBζ promoter reporter.  After 24 hours rest, cells were stimulated with LPS +/- IL-10 for 2 hours.  Reporter ACDBIkBζrelative ikbζ expressionover 18Sunstimulated LPSLPS + IL-10050100150200******pri-miR-1550 1 20.00.20.40.60.81.01.2Time (hour)relative pri-miR-155 expression over GAPDHDMSOActD******  pri-miR-1550 1 2020406080LPS+DMSOLPS+CHX****Stimulation time (hour)relative pri-miR-155 expression over 18S****Luciferase  Reporterunstimulated LPSLPS+IL-10unstimulated LPSLPS+IL-100246810BIC promoterIkBζ promoterFold  Change*******pri-miR-1550 1 205101520********DMSOCHXTime (hour)relative pri-miR-155 expressionover 18S 78 activity was normalized to the TK-Renilla and plotted as fold change relative to the unstimulated sample.  (C – D) RAW264.7 cells were treated with (C) ActD, CHX or DMSO, or (D) LPS + DMSO or CHX for the indicated time prior to RNA extraction and determination of pri-miR-155 level by real time PCR.  Statistical significance between DMSO treatment and drug treatment was calculated by a two-way ANOVA test with a 95% confidence (**** p < 0.0001).  Similar results were observed in at least two independent experiments. Representative data are shown.  3.2.3. Pri-miR-155 is constitutively transcribed but maintained at low level via degradation mechanism. The lack of responsiveness of the BIC reporter to LPS and IL-10 was unexpected, since LPS clearly increased the level of pri-miR-155 in cells (Figure 3.1).  However, the steady state transcript level of a gene is not a sole result of increased transcription; it can also be due to decreased transcript degradation.  To examine the possibility that the pri-miR-155 is constitutively transcribed and undergoes regulated degradation, we looked at the effect of the transcription inhibitor actinomycin D (ActD) or translation inhibitor cycloheximide (CHX) on pri-miR-155 levels.  In the experiments using CHX, we used 18S rRNA as the normalization control, instead of GAPDH, because the GAPDH expression level was sensitive to CHX treatment while 18S rRNA expression level was not (Figure B.2).   We treated resting RAW264.7 with ActD and found that steady state pri-miR-155 level dropped more than 2-fold by 1 hour and was almost undetectable at 2 hours (Figure 3.2C, left panel).  This indicated that pri-miR-155 is constitutively transcribed even in unstimulated RAW264.7 cells.  By contrast, CHX treatment increased pri-miR-155 levels by 6-fold in 1 hour, which indicated that de novo translation of short-lived decay factors contributes to maintain pri-miR-155 level at a low level in unstimulated cells (Figure 3.2C, right panel).  CHX treatment also enhanced LPS-induced pri-miR-155 expression (Figure 3.2D).  79 3.2.4. LPS and IL-10 do not cause editing of pre-miR-155  miRNAs can also be regulated by RNA editing, such as by adenosine deaminases (ADARs) [222,527,528].  These enzymes modify the RNA sequence by converting adenosine to inosine.  Since inosine is being read as guanosine, the biological consequence is an A to G conversion.  This can affect both Drosha- and Dicer-mediated cleavage, as well as the export of pre-miRNAs. We addressed this possibility by sequencing two samples of cDNA obtained from cells left unstimulated, stimulated with LPS or LPS+IL-10.  The sequencing analysis revealed that there is no nucleotide change in pre-miR-155 sequence upon LPS or LPS+IL-10 treatment (Figure 3.3).    Figure 3.3 LPS and IL-10 do not cause editing on the pre-miR-155 sequence.   DNA sequencing results of RT-PCR products were performed on pri-miR-155.  The expected sequences of pre-miR-155 and mature miR-155 are included at the top.  Two samples of each treatment (unstimulated, LPS, LPS+IL-10) were analyzed, and showed in blue.    3.2.5. LPS and IL-10 do not regulate nuclear export of pre-miR-155 Another miRNA regulation checkpoint occurs at the export of pre-miRNAs from the nucleus to the cytoplasm.  The delayed expression of mature miR-155 relative to pri-miR-155 and pre-miR-155 might be due to delayed export of pre-miR-155 into the cytoplasm for processing by Dicer.  To investigate the possible effect of LPS and IL-10  80 on the nuclear export of pre-miR-155, we stimulated RAW 264.7 cells with LPS +/- IL-10 and fractionated the cells into nuclear and cytoplasmic fractions.  The levels of pre-miR-155 expression in the total cellular, nuclear, and cytoplasmic fractions were determined by real time PCR.  The kinetics of pre-miR-155 expression in total cellular RNA (Figure 3.4A) mirrored that of pri-miR-155 (Figure 3.1A).  Pre-miR-155 expression was induced quickly by LPS and peaked at 2 hours.  IL-10 inhibition of pre-miR-155 was observed at 2 hours.  The kinetic profiles of pre-miR-155 in nuclear and cytoplasmic RNA fractions were quite similar to that in total RNA, indicating that neither LPS nor IL-10 regulated or altered the nuclear export of pre-miR-155.    81  Figure 3.4 IL-10 does not affect the export of pre-miR-155 from the nucleus to the cytoplasm.   RAW264.7 cells were stimulated with LPS +/- IL-10 for the indicated times prior to fractionation of nuclei and cytoplasm.  Levels of pre-miR-155 in (A) total, (B) nuclear and (C) cytoplasmic fractions were determined by real time PCR.  Statistical significance between LPS and LPS + IL-10 treatment was calculated by a two-way ANOVA test with a 95% confidence (* p < 0.05, ** p < 0.01, *** p < 0.001).  Similar results were observed in at least three independent experiments.  Representative data are shown.  ABCTotal RNA: pre-miR-1550 1 2 3 4 50102030LPSLPS + IL-10******Stimulation time (hour)relative pre-miR-155 expression over  GAPDHNuclear RNA: pre-miR-1550 1 2 3 4 5010203040LPSLPS + IL-10******Stimulation time (hour)relative pre-miR-155 expression over  GAPDHCytoplasmic RNA: pre-miR-1550 1 2 3 4 50102030LPSLPS + IL-10*** ***Stimulation time (hour)relative pre-miR-155 expression over  GAPDH 82 3.2.6. IL-10 inhibits LPS induction of miR-155 via SHIP1 and STAT3  McCoy et al. [333] found that IL-10 inhibition of miR-155 expression required the presence of STAT3 protein.  The STAT3 pathway is the best-characterized pathway downstream of the IL-10R.  However, we recently found that IL-10 also signals through the phosphatase SHIP1 [56], so we investigated the contribution of SHIP1 to IL-10 inhibition of pre-miR-155 and mature miR-155 levels.  We tested the ability of IL-10 to inhibit miR-155 in peritoneal macrophages (perimacs) from wild type or SHIP1 knockout (SHIP1 KO) mice.  As shown in Figure 3.5A, IL-10 could not inhibit miR-155 expression to the same extent in SHIP1 deficient cells as compared to wild type cells. To confirm these findings, we generated RAW264.7 cell lines in which SHIP1 protein levels were reduced by RNA silencing.  siRNA sequence targeting SHIP1 or a scrambled (SCRMB) sequence was cloned into the pTRIPZ lentiviral vector that contains miRNA-like processing elements to express the siRNA sequence under the control of a doxycycline (Dox) regulated promoter.  The addition of Dox to the SHIP1 siRNA transduced cells reduced SHIP1 protein expression by 80% (Figure 3.5B).  Similar to that observed in wild type perimacs, IL-10 inhibited pri-miR-155 and miR-155 in the SCRMB siRNA transduced cells (Figure 3.5C).  Similar to SHIP KO perimacs, the SHIP1 siRNA transduced cells had reduced IL-10 inhibition of mature miR-155 (Figure 3.5C). Our data suggested that SHIP1 negatively regulated LPS-induced miR-155 expression.  To determine whether activation of SHIP1 alone could inhibit miR-155 expression, we made use of a small molecule SHIP1 activator, AQX-MN100, which binds to the allosteric activation site on SHIP1 and activates its phosphatase activity.   83 AQX-MN100 is specific for SHIP1 and does not activate even the closely related SHIP2 inositol phosphatase.  We found AQX-MN100 inhibited miR-155 expression in LPS-stimulated macrophages (Figure 3.5D), indicating that SHIP1 activation alone can reduce miR-155 levels.  Notably, SHIP1 activation alone does not reduce miR-155 levels to the same extent as IL-10 (Figure 3.5C), suggesting other IL-10 regulated signalling pathways also contribute to IL-10’s effect. Since SHIP1 is a negative regulator of the PI3K/AKT pathway, we reasoned that the PI3K/AKT pathway would have a positive role in miR-155 expression.  We tested this hypothesis by expressing a conditionally active form of AKT in RAW264.7 cells.  This AKT-Estrogen Receptor (ER) fusion protein is activated by the addition of 4-hydroxytamoxifen (4-HT), which displaces HSP90 and allows AKT-ER access to its substrates.  Pretreating the cells with 150 nM 4-HT for 20 minutes was sufficient to activate AKT-ER, indicated by the increased phosphorylation of GSK3β, a substrate of AKT (Figure A.3).  The untreated cells and the 4-HT treated cells produced similar miR-155 level in respond to LPS, but their responses to IL-10 differed (Figure 3.5E).  IL-10 inhibition of miR-155 was impaired in 4-HT treated AKT-ER expressing cells (Figure 3.5E).  84   ACDSCRMB SHIP1siRNADoxanti-SHIP1anti-STAT3+ - +-BEPerimacs: miR-155relative miR-155 expression over snoRNA2020 20 0 200.00.51.01.5**[IL-10] ng/mlWT SHIP1  KO  0relative SHIP1 expression04080120****pri-miR-155 relative pri-miR-155 expressionover GAPDH0 10 0 100.00.51.01.5[IL-10] ng/mlSCRMB siRNA+ DoxSHIP1 siRNA+ Dox***  0miR-155relative miR-155 expression over snoRNA202 0 10 0 100.00.51.01.5[IL-10] ng/mlSCRMB siRNA+ DoxSHIP1 siRNA+ Dox*  0RAW264.7: miR-155relative miR-155 expression over snoRNA202unstimulated LPSLPS + MN10005101520***AKT-ER: miR-155relative miR-155 expression over snoRNA202 0 10 0 100.00.51.01.5[IL-10] ng/mlno 4-HT + 4-HT*   85 Figure 3.5 SHIP1 mediates IL-10 inhibition of miR-155.   (A) Perimacs were extracted from either WT or SHIP1 KO mice, and stimulated with 10 ng/ml LPS or LPS + 10 ng/ml IL-10.  miR-155 expression levels were measured by real time PCR and plotted relative to the LPS alone sample in each cell type.  (B) SCRMB and SHIP1 siRNA transduced cells were treated with 2 μg/ml Dox for 48 hours or left untreated prior to immunoblotting analysis for SHIP1 and STAT3 (loading control).  Band intensities were quantified using the Quantity One Software.  Statistical significance between treatments was calculated by a two-way ANOVA test with a 95% confidence (**** p < 0.0001).  (C) SCRMB and SHIP1 siRNA transduced cells were treated with 2 μg/ml Dox for 48 hours and then stimulated with LPS +/- IL-10 for 2 or 4 hours.  Expression levels of pri-miR-155 in the 2-hour samples and miR-155 in the 4-hour samples were measured by real time PCR and plotted relative to the LPS alone samples.  (D) RAW264.7 cells were left untreated, treated with 10 M AQX-MN100 or ethanol control for 30 minutes before being stimulated with LPS or LPS+AQX-MN100 for 4 hours.  Expression level of miR-155 was measured by real time PCR and plotted relative to LPS samples.  (E) AKT-ER transduced cells were treated with 150 nM 4-HT for 20 minutes or left untreated before being stimulated by LPS +/- IL-10 for 4 hours.  Expression level of miR-155 was measured by real time PCR and plotted relative to the LPS alone samples.  Statistical significance between stimulation conditions was calculated by a two-way ANOVA test with a 95% confidence (** p < 0.01, ***, p < 0.001, **** p < 0.0001).  Similar results were observed in at least two independent experiments.  Representative data are shown.  We then examined whether the contribution of STAT3 and SHIP1 to IL-10 inhibition of mature miR-155 were additive or redundant.  To do this we made use of the synthetic STAT3 inhibitor, STA-21.  We first tested the efficacy of STA-21 by testing its ability to inhibit IL-10 activation of the STAT3-responsive, c-fos promoter luciferase reporter.  RAW264.7 cells were transiently co-transfected with the c-fos firefly luciferase and SV40 renilla luciferase control constructs.  Cells were then treated with STA-21 or vehicle control, and stimulated with IL-10 or left unstimulated.  As shown in Figure 3.6A, IL-10 induced the activity of the c-fos promoter, but pretreatment of 30 µM STA-21 reduced this induction.  We then added STA-21 to SCRMB or SHIP1 siRNA transduced cells and measured the levels of pri-miR-155 and mature miR-155.  As shown in Figure 3.6B, STA-21 impaired IL-10’s ability to inhibit pri-miR-155 and mature miR-155 in both cells.  In cells lacking SHIP1, the effect of STA-21 was more pronounced  86 than untreated cells.  In fact, the expression of pri-miR-155 and miR-155 was enhanced, rather than inhibited by IL-10.  These data suggest that SHIP1 and STAT3 play additive, non-redundant roles in IL-10 inhibition of miR-155.  Figure 3.6 SHIP1 and STAT3 play additive roles in IL-10 inhibition of miR-155.   (A) RAW264.7 cells were transfected with the c-fos promoter reporter and TK-Renilla, and were pretreated with DMSO or 30 μM STA-21 for 1 hour prior to IL-10 stimulation for 6 hours.  Luciferase activity was measured and plotted as firefly/renilla ratio.  (B) SCRMB and SHIP1 siRNA transduced cells were treated as Figure 4C except the cells were pretreated with DMSO or 30 μM STA-21 for 1 hour prior to stimulation.  Expression levels of pri-miR-155 at 2 hours and miR-155 at 4 hours were measured by real time PCR and plotted relative to the LPS alone samples.  Statistical significance between stimulation conditions was calculated by a two-way ABc-fos luciferaseFirefly/renilla ratiounstim6h IL-10unstim6h IL-10012345 DMSOSTA-21********pri-miR-155relative pri-miR-155 expression over GAPDH0 10 0 10 0 10 0 100.00.51.01.52.0STA-21[IL-10] ng/mlSCRMB siRNA + Dox SHIP1 siRNA + Dox++++-    -    -    -    ****************  0miR-155relative miR-155 expression over snoRNA2020 10 0 10 0 10 0 100.00.51.01.52.0STA-21[IL-10] ng/mlSCRMB siRNA + Dox SHIP1 siRNA + Dox++++-   -   -   -   ***************  0 87 ANOVA test with a 95% confidence (** p < 0.01, *** p < 0.001, **** p < 0.0001).  Similar results were observed in at least two independent experiments.  Representative data are shown.  3.3. Discussion miRNAs regulate both immune cell development and function [118,263,265].  In particular, miR-155 is extensively involved in different aspects of the immune system including haematopoiesis, T cell development, B cell differentiation, dendritic cell maturation, as well as mediating inflammation [122,288,293,294,309].  Enhanced miR-155 expression is associated with various human diseases such as rheumatoid arthritis [318] and cancers [284,306,323].  The multiple roles of miR-155 are mediated by its numerous targets that include transcription factors, protein receptors, kinases and other signalling molecules [314].  Because of miR-155’s pro-inflammatory roles in macrophage activation, we examined whether IL-10 regulated miR-155 levels in our cells and if so, whether SHIP1 played a role.  We found that IL-10 was able to inhibit the expression of miR-155 in activated macrophages (Figure 1.1A-B), which is consistent with a previous report.  However, unlike McCoy et al. [333], we found that neither LPS nor IL-10 regulated miR-155 at the transcriptional level. miRNAs can be regulated at multiple steps: transcription, nuclear export and maturation.  We, Ruggiero et al. [262], and McCoy et al. [333] all observe upregulation of pri-miR-155 RNA.  Although Ruggiero et al. [262] and we both concluded that pri-miR-155 levels are regulated primarily through post-transcriptional mechanisms [262], McCoy et al. [333] concluded that pri-miR-155 levels rise through increased transcription.  Ruggiero et al. [262] used chromatin immunoprecipitation and sequencing to show that pri-miR-155 transcription rates do not change with LPS stimulation.  We came to the same conclusion using BIC promoter luciferase reporter assays and cycloheximide  88 experiments.  Our results with the BIC promoter reporter differed from McCoy et al.’s BIC promoter reporter assays in that they found LPS stimulated reporter activity while we did not.  We do not know why our results differ, but we note that McCoy et al. [333] based their conclusion solely on luciferase reporter experiments, without using any other additional experimental approaches such as the ones Ruggiero et al. [262] and we used.  Although neither LPS nor IL-10 altered BIC promoter activity, the level of pri-miR-155 transcript increased with LPS and decreased with IL-10 treatment.  Steady state transcript levels are controlled not only by transcriptional activity, but also maintained through transcript stability.  Therefore we used ActD and CHX treatments to examine whether pri-miR-155 transcript levels were being kept low in resting cells through degradation (Figure 3.2C-D).  ActD reduced pri-miR-155 levels while CHX enhanced it, indicating that pri-miR-155 is constitutively transcribed and, at the same time, degraded in unstimulated cells.   Interestingly, although IL-10 significantly decreases the levels of pri-miR-155 by 2 hours after addition, significant decreases in mature miR-155 do not occur until 4 hours after stimulation.  This discrepancy in kinetics suggests an additional layer of control past the regulation of pri-miR-155 levels.  Thus, we examined whether IL-10 regulated the nuclear export of pre-miR-155 by fractioning total RNA into nuclear and cytoplasmic RNA.  We found that the kinetics of pre-miR-155 expression in the nucleus and the cytoplasm were similar, which suggested that nuclear export of miR-155 was not regulated by IL-10.  From these observations, we deduced that IL-10 likely regulated the processing of pre-miR-155 to functional, mature miR-155.  Emerging evidence shows that miRNA biogenesis or processing can be regulated at the post-transcriptional steps by  89 different RNA-binding proteins that modulate Drosha or Dicer activities.  In particular, the RNA binding protein KSRP was found to be required for miR-155 maturation in response to LPS stimulation in macrophages [262].  Furthermore, the ability of KSRP to support miRNA maturation was found to be stimulated by AKT-mediated phosphorylation [529].  Future studies in the laboratory are directed to examine whether IL-10 may modulate the function of KSRP to inhibit the production of mature miR-155.   IL-10 function is well known to be mediated by the transcription factor STAT3 [368,374,413,416,420] and STAT3 is involved in IL-10 inhibition of miR-155 [333].  We also found that the phosphatase SHIP1 is also involved in mediating IL-10 inhibition of LPS-induced TNFα production and AKT activation [56,376].  We now report that IL-10 inhibition of miR-155 expression was impaired in macrophages lacking SHIP1 but such inhibition could be achieved by the addition of the SHIP1 activator, AQX-MN100 (Figure 3.5).  The addition of the STAT3 inhibitor STA-21 further reduced IL-10 inhibition (Figure 3.6).  The additive effect of SHIP1 knockdown and STAT3 inhibition suggests that SHIP1 and STAT3 regulate miR-155 expression through independent mechanisms.   Consistent with the fact that SHIP1 is a negative regulator of the PI3K/AKT pathway, we found that 4-HT mediated activation of AKT-ER abolished IL-10 inhibition of miR-155 expression (Figure 3.5C), indicating a positive role of AKT in miR-155 expression.  This finding appears to disagree with a previous study in which a myristylated, constitutively active AKT reduced LPS-induced miR-155 in macrophages [520].  The difference in conclusions between ours and the Androulidaki et al.’s [520] studies may be due to the use of the constitutively active AKT in their study.  Persistent  90 activation of AKT may change the nature of the cells.  In contrast, the AKT-ER fusion protein we used in our experiments was only active when we added 4-HT.   SHIP1 is a well-characterized miR-155 target.  Thus, the involvement of SHIP1 in IL-10 inhibition of miR-155 expression constitutes an elegant regulatory circuit composed of SHIP1, AKT and miR-155: LPS-induced activation of AKT promotes the expression of miR-155, which suppresses SHIP1, to allow PI3K/AKT pro-inflammatory events.  Conversely, IL-10 mediated activation of SHIP1 inhibits AKT signalling and reduces miR-155 expression.  As a result, SHIP1 protein translation is resumed and further suppresses macrophage activation. Together, our data supported a new mode of action for the anti-inflammatory cytokine IL-10 in which IL-10 controls the overall level of functional miR-155 by regulating the stability of pre-miR-155 and its maturation through SHIP1 and STAT3-dependent mechanisms.     91         Chapter 4: STAT3 and SHIP1 Work Together to Mediate IL-10 Functions    92 4.1. Introduction Since the discovery of IL-10, a large number of genes have been identified as regulated by IL-10 in activated macrophages including cytokines, chemokines, adhesion molecules, receptor proteins and enzymes [348].  For a long time, the transcription factor STAT3 was thought to be the sole molecule responsible for all IL-10 functions by either inducing expression of anti-inflammatory mediators (such as IL-1RA [530]), or inducing expression of other factors that inhibit selective gene expression.  Lang et al. [416] performed microarray analyses of LPS +/- IL-10 regulated genes in macrophages derived from IL-10 knockout mice.  They have found that IL-10 represses about 24% of LPS-induced genes, including cytokines (e.g.TNFα, and IL-10 itself), transcription factors (e.g. B-ATP, BCL-6 and C/EBPβ), surface molecules (e.g. IL-4Rα), genes implicated in NFκB activation (e.g. metallothionein-2 [531] and BCL-3 [532]), and those involved in regulating the MAPK pathway (e.g. GADD45γ [533] and TPL-2 [534]).  Some of these genes (TNFα, B-ATF and IL-4Rα.) have also been verified to be STAT3-dependent by RT-PCR based analyses of IL-10 induced genes in wild type and STAT3 KO macrophages.  A more recent study combined the use of chromatin immunoprecipitation-sequencing (ChIP-seq) and RNA-sequencing (RNA-seq) to identify IL-10 regulated genes whose promoter regions are bound by STAT3 upon IL-10 treatment [45].  Many of the genes that are upregulated by IL-10 and possess STAT3-binding sites (within 20 kb of their transcription start site, as defined by the authors) are implicated in chromatin remodeling, suggesting major chromatin remodeling may be one mechanism IL-10 uses to mediate gene expression.  The authors have also found that IL-10, through STAT3, upregulates a number of transcription repressors that might be the ultimate effectors of  93 IL-10 anti-inflammatory responses by inhibiting the expression of pro-inflammatory cytokines. However, data from our laboratory and other laboratories have showed that IL-10 can still function in the absence of STAT3 activity.  For example, STAT3 deficiency or STAT3 inactivation (for example, through the expression of a dominant negative mutant) cannot completely abolish IL-10’s ability to inhibit LPS-induced TNFα [419,420,535].  Also, a comparison of IL-10 KO [421] and STAT3 KO [413] mice in endotoxin models shows that although STAT3 KO mice, similar to IL-10 KO mice, produce elevated serum TNFα level after LPS injection, their TNFα eventually declines, unlike in IL-10 KO mice, where TNFα level remains high throughout the course of the experiment.  More importantly, the decline of TNFα level in STAT3 KO mice coincides with the production of endogenous IL-10 [413], suggesting that IL-10 can reduce TNFα via a STAT3-independent manner.  Through chromatin immunoprecipitation experiments using RNA polymerase II antibodies, we have found that IL-10 inhibits the transcription of TNFα by interfering with the elongation signal of RNA polymerase II, and that such inhibition is impaired in SHIP1-deficient macrophages [376].  In addition, we have also showed that SHIP1 is involved in IL-10 inhibition of TNFα production by inhibiting its translation, and that a small molecule SHIP1 activator can mimic IL-10 action [56].  Moreover, as detailed in Chapter 3 [375], although knocking out SHIP1 or inhibiting STAT3 activity alone does impair IL-10’s ability to inhibit miR-155 expression, complete impairment is only observed when both SHIP1 and STAT3 actions are blocked.  We thus hypothesize that SHIP1 and STAT3 cooperate to mediate IL-10 function.  94 SHIP1 negatively regulates the PI3K pathway by hydrolyzing the second messenger, PI(3,4,5)P3, and thus reducing the recruitment and activation of PH-domain containing proteins.  Besides its catalytic domain, SHIP1 also functions by acting as an adaptor protein through its multiple protein domains [426].  These domains allow SHIP1 to be recruited to the plasma membrane, where it hydrolyzes its substrate, or to act as an adaptor protein such as in the case of suppressing B cell activation [426].  While SHIP1 enzymatic activity is needed to suppress the activated PI3K pathway, SHIP1 decreases Ras activation by interacting with another adaptor protein Shc, dissociating the Shc-containing complex necessary for Ras activation [454].  This suppression of Ras activation does not require the enzymatic property of SHIP1.  Other SHIP1-interacting proteins include Grb2, Dok1 and Dok2, whose interaction is important for inhibiting T cell activation [456].  Moreover, while SHIP1 negatively regulates TLR4-signalling by inhibiting PI3K in activated macrophages, a phosphatase dead SHIP still partly suppresses TNFα production in LPS-activated macrophages [317], again supporting an adaptor role for SHIP independent of its phosphatase activity.  Perhaps, in the context of IL-10 signalling, SHIP1 cooperates with STAT3 by acting as an adaptor to recruit STAT3 to the IL-10R or other signalling proteins necessary for IL-10 function. This chapter describes experiments that determine whether SHIP1 and STAT3 interact with each other, as well as global gene expression data that show the regulatory range of each protein in IL-10 inhibition of macrophages.    95 4.2. Results 4.2.1 Both STAT3 and SHIP1 mediate IL-10 inhibition of LPS-induced TNFα production. To understand the relative contribution of SHIP1 and STAT3 in IL-10 function, we constructed a continuous flow apparatus, in which cells are exposed to stimulation media under continuous flow.  In the conditions of continuous flow, cells experience similar environment as they are inside an animal where the flow of blood and extracellular fluid are continually removing autocrine factors from the cells.  BMDMs derived from STAT3 WT and STAT3 KO mice were stimulated with LPS+/- IL-10.  Consistent with previous data, we found that LPS induced two waves of TNFα production (Figure 4.1A), which peaked at about 75 minutes and 160 minutes, respectively.  Inclusion of IL-10 drastically reduced TNFα production at both peaks in STAT3 WT cells.  As reported [413], STAT3 KO cells produced higher level of TNFα upon LPS stimulation.  We found that these cells also displayed the biphasic TNFα production profile as STAT3 WT cells.  However, IL-10 function was impaired in the inhibition of the first peak of TNFα production.  Similarly, IL-10 was not able to inhibit the first peak of TNFα production in SHIP1 KO cells, compared to SHIP1 WT cells.  By contrast, IL-10 was capable to inhibit the second peak of TNFα production in STAT3 KO and SHIP1 KO cells, suggesting that IL-10 uses more than just STAT3 or SHIP1 to mediate its effects. Together with our finding that STAT3 and SHIP1 additively mediate IL-10 inhibition of miR-155 [375], we believe that STAT3 and SHIP1 work together.    96  Figure 4.1 Deficiency in STAT3 or SHIP1 results in impaired IL-10 inhibition in the first peak of TNFα production, but not the second peak.   STAT3 WT, STAT3 KO, SHIP1 WT and SHIP1 KO BMDMs were stimulated with LPS (dotted line) or LPS+/- IL-10 (solid line) over the course of 200 minutes in the continuous-flow apparatus.  Fractions were collected every 5 minutes, and were subjected to TNFα ELISA analysis.  STAT3 WT and STAT3 KO cells were from mice with C57BL/6 background, whereas the SHIP1 WT and SHIP1 KO cells were from mice with BALB/c background.  Data are representative of two independent experiments.     4.2.2 Physical interaction of SHIP1 and STAT3 Concurrent with functional assays to elucidate the relative contribution of SHIP1 and STAT3 in IL-10 function, data from our laboratory revealed that epitope-tagged SHIP1 was able to pull down endogenous STAT3 in IL-10 treated macrophages (data not shown).  We thus want to explore the possibility that these proteins physically interact with each other to function.  To do that, we first immobilized Flag-tagged STAT3 onto M2 affinity resins, and incubated these beads with purified His6-tagged SHIP1.  After washes, immunoblotting analysis was used to determine the amount of His6-SHIP1 0 0  97 binding to Flag-STAT3.  Different buffer conditions were also examined, including MgCl2 that is necessary for SHIP1’s enzymatic function, CaCl2 that enhances SHIP1 activation by its activator (see Chapter 5), and AQX-151, a SHIP1 modulator that shows similar biological function as AQX-MN100 [430].  However, despite our efforts, we saw no evidence that Flag-STAT3 interacted with His6-SHIP1 (Figure 4.2).  One possible explanation is that one (or both) of these proteins needs to be phosphorylated for interaction to occur. Figure 4.2 His6-SHIP1 does not bind to Flag-STAT3 in an in vitro pulldown assay.   Flag-STAT3 was expressed in HEK293T cells and immobilized on M2 affinity resins, and then incubated with purified His6-SHIP1 in TBS+0.02% Tween-20 supplementaed with different reagents.  The pulldown samples were then analyzed by immunoblotting with anti-SHIP1, anti-Flag and anti-mouse IgG antibodies.     4.2.3 Y190F mutation on SHIP1 abolishes IL-10’s ability to inhibit TNFα  One regulatory mechanism of signalling proteins is the phosphorylation states on selected amino acid residues including tyrosine.  Phosphorylated tyrosine (pTyr) is able to interact with the SH2 domain of another protein leading to subsequent signalling events.  Since both SHIP1 and STAT3 can be phosphorylated at tyrosine residues, we wondered if any of the pTyr in one of these proteins could be recognized by the SH2 domain of the other protein.  We decided to look at phosphorylation sites on SHIP1.   98 Using the online prediction tool NetPhos 2.0 [536], we identified 11 tyrosine residues that can be potentially phosphorylated.  Comparing to the conventional STAT3’s SH2 domain recognition sequences, we decided to focus our effects on four potential tyrosine residues (Figure 4.3).  Three of the residues (Y657, Y659, Y799) locate within known structured domains (catalytic and C2 domains), while Y190 is in the region between SH2 and PH-R domains. FoldIndex program predicts whether a protein will fold based on its hydrophobicity [537], and using the SHIP1 primary sequence as the input, the program found that the area around Y190 might be folded.     Residue  Location on SHIP1 Amino acid sequence Y190 Between SH2 and PH-R domains EEHLKAIQDYLSTQLLLDSD Y657 Within catalytic domain RLTRDKYAYTKQKATGMKYN Y659 Within catalytic domain RLTRDKYAYTKQKATGMKYN Y799 Within C2 domain KPIISDPEYLLDQHILISIK  Figure 4.3 Location of the mutated tyrosine in SHIP1 sequence.   (A) The FoldIndex program [537] was used to predict the folded and unfolded regions of SHIP1.  A schematic diagram of the SHIP1 structure is on top, and the stars show where the identified tyrosine residues are.  (B) Summary of the residues mutated.     These residues were mutated individually to phenylalanine, and the SHIP1 mutants were introduced into the J2M SHIP1 KO macrophage cell line.  As shown in Figure 4.4, J2M SHIP1 KO macrophages reconstituted with wild type SHIP1 (J2M  Catalytic C2 PH-R SH2 A NPXY PXXP B  99 KO:SHIP1 WT) showed expected LPS and IL-10 responses.  However, we found that J2M KO:SHIP1 Y190F cells became resistant to IL-10.  Efforts are currently focused on determining if Y190 is indeed phosphorylated by IL-10, and if this phosphorylation is necessary for STAT3 interaction.  All the other mutants showed similar IL-10 response as J2M KO:SHIP1 WT (data not shown).  Figure 4.4 SHIP1 Y190F impairs IL-10 inhibition of TNFα in activated macrophages.   (A) Immunoblot analysis of J2M SHIP1 KO reconstituted with either SHIP1 WT or SHIP1 Y190F.  Anti-SHIP1 antibody was used to detect the expression of the recombinant SHIIP1 proteins.  Actin was the loading control.  (B) These cells were stimulated with LPS +/- IL-10 for 1 hour.  TNFα level in the supernatant was measured by ELISA.  (C) The same data were replotted as a percentage of LPS alone treated samples.   A B C  --     WT   Y190F J2M KO SHIP1 Actin 0.001 0.010 0.100 1 10 100050100150[IL-10] ng/ml% of LPS alone% LPSJ2M KO: SHIP1 WTJ2M KO: SHIP1 Y190F0 100 4.2.4 SHIP1 and STAT3 co-regulate a number of IL-10 regulated genes.   To this point, we have only examined the roles STAT3 and SHIP1 play in IL-10 inhibition of specific molecules, miR-155 and TNFα, in activated macrophages.  However, IL-10 is known to be a general negative regulator of macrophage activation, and it regulates a wide variety of molecules.  We decided to perform a microarray analysis to measure the global effect of IL-10 in activated macrophages and to identify genes that are regulated by SHIP1 alone, STAT3 alone, or SHIP1/STAT3.   To identify SHIP1-regulated genes, we compared the gene expression profiles from SHIP1 WT and SHIP1 KO perimacs treated with LPS +/- IL-10 for 30 minutes.  We are aware that the time point and the macrophage type chosen have a tremendous effect on gene expression profiling.  We chose to look at a relatively short time point for two main reasons.  First of all, with long treatment, cytokines produced by the cells could feedback to the cell in an autocrine cytokine manner; that can mask the direct effect of IL-10.  Secondly, we found previously that LPS was able to induce TNFα mRNA expression as early as 30 minutes, and that IL-10 was able to suppress its production.  We also decided to use perimacs as our choice of macrophages because these cells develop inside the mice without ex vivo manipulation (besides the stimulation) and likely give the most physiological relevant response, compared to macrophages differentiated and matured in a tissue culture dish (i.e. BMDMs).  From our own experiences as well as from the literature [416], BMDMs produced a much higher level of endogenous IL-10 than perimacs upon LPS stimulation, and thus using BMDMs in our studies may blunt our ability to determine the complete range of IL-10 induced changes in cells.    101 Expression levels of 27,122 genes, 4,578 long non-coding RNAs were measured, and we found that over 100 genes were regulated by IL-10 in activated macrophages.  A comparison of the gene expression profiles of wild type macrophages treated with LPS or LPS+IL-10, we found that 341 genes were regulated by IL-10 by at least 2-fold at 0.5 hour (194 induced, 147 repressed).  One hour stimulation showed 654 genes whose expression were altered at least 2-fold by IL-10  (336 induced, 318 repressed).  About 80 genes were regulated by IL-10 at both time points.  Our microarray analysis confirmed a number of known IL-10 regulated genes [348] including TNFα, IL-1R antagonist, CSF3, SBNO2 and IL-10 itself.  Since only 0.5-hour data were available in SHIP1 knockout cells, we decided to work with the set of 0.5-hour IL-10 regulated genes.  In the SHIP1 knockout cells, 122 out of the 341 genes were differentially regulated by IL-10 showing at least a 2-fold difference from SHIP1 wild type cells.  Among them, 70 were induced by IL-10 in SHIP1 WT cells, while 52 were repressed.  We defined these genes as the SHIP1-regulated genes (Table 4.1).  Surprisingly, TNFα is not in this gene subset even though we have other data supporting SHIP1’s role in its regulation [56,376].  We examined the microarray data closely and found that there was a modest IL-10 resistance observed in SHIP1 KO cells (~11% less inhibited by IL-10) at 0.5 hour, lower than our selection criteria of 2-fold changes.  Nevertheless, it is reassuring to confirm in our microarray that TNFα is regulated by IL-10 through SHIP1.  We decided to add TNFα in our SHIP1-regulated gene subset.         102 Table 4.1: SHIP1-regulated genes identified after 0.5-hour stimulation of LPS and LPS+IL-10 in SHIP1 WT and SHIP1 KO macrophages GenBank ID Gene Symbol SHIP1 WT SHIP1 KO Fold difference between WT and KO  LPS+IL-10 over LPS LPS+IL-10 over LPS IL-10 Upregulated Genes NM_001039392 Tmsb10 2.046 0.16 12.50 X71478 Cyp4a10 2.453 0.25 9.74 NM_022320 Gpr35 2.748 0.29 9.44 NM_080561 Rnf216 2.081 0.23 9.08 NM_008564 Mcm2 2.180 0.25 8.58 NM_001081281 Trim55 8.533 1.24 6.89 NM_133731 Prss22 2.399 0.37 6.43 AK009475 Zfp560 2.392 0.39 6.14 NM_008462 Klra2 3.250 0.54 6.02 NM_022028 Sav1 3.068 0.61 5.05 NM_025297 Mecr 2.732 0.56 4.84 NM_028276 Utp14a 2.073 0.44 4.71 NM_019928 Klk4 3.038 0.69 4.42 NM_025706 Tbc1d15 2.958 0.71 4.20 AK032013 Anxa7 2.264 0.56 4.08 NM_001039552 2210404J11Rik 2.641 0.68 3.87 BC038320 4930581F22Rik 2.318 0.60 3.87 NM_026615 Urm1 2.433 0.65 3.75 NM_010638 Klf9 2.224 0.60 3.72 NM_153820 Arhgap15 2.670 0.72 3.71 NM_029786 Pomgnt1 2.021 0.55 3.70 NM_028121 Adpgk 2.281 0.62 3.68 NM_027147 Enho 2.295 0.63 3.62 XM_980696 AI607873 2.300 0.64 3.59 NM_023884 Ralgps2 2.125 0.60 3.54 NM_007968 Ewsr1 2.052 0.58 3.53 XM_001001284 EG667795 2.362 0.69 3.41 NM_021893 Cd274 4.249 1.25 3.39 NM_172015 Iars 2.684 0.82 3.27 AK078885 AI842136 3.527 1.13 3.12 NM_178700 Grsf1 2.266 0.74 3.07 NM_153585 Cnot10 2.373 0.81 2.92 ENSMUST00000042610 AI607873 2.703 0.94 2.88 U63712 Tfam 2.179 0.76 2.85 NM_175013 Pgm5 2.684 0.95 2.83 NM_133238 Cd209a 4.125 1.46 2.82 NM_025837 Mpi 2.551 0.92 2.79  103 GenBank ID Gene Symbol SHIP1 WT SHIP1 KO Fold difference between WT and KO  LPS+IL-10 over LPS LPS+IL-10 over LPS NM_024172 Hspbp1 2.171 0.78 2.78 NM_013683 Tap1 2.345 0.85 2.76 NM_010072 Dpm1 4.202 1.53 2.75 NM_198602 Cux1 2.182 0.82 2.65 NM_177224 Chd9 2.422 0.92 2.63 NM_008684 Neo1 2.709 1.05 2.59 NM_172488 9030625A04Rik 2.132 0.84 2.54 NM_008965 Ptger4 3.682 1.50 2.46 AK045877 Atp6v0a1 2.888 1.19 2.43 NM_008039 Fpr2 2.476 1.05 2.36 NM_008950 Psmc5 2.369 1.01 2.34 AK017886 5830400J07Rik 5.801 2.48 2.34 NM_015741 Krtap9-1 2.517 1.09 2.30 NM_011274 C80913 2.072 0.90 2.30 AK020773 A430106F12Rik 2.575 5.87 2.28 NM_007969 Expi 3.453 1.52 2.28 NM_013785 Ip6k1 2.111 0.93 2.26 NM_024495 Car13 2.361 1.05 2.25 NM_008654 Myd116 2.028 0.90 2.24 NM_145431 Nle1 2.038 0.92 2.22 NM_172501 Nhlrc3 2.258 1.02 2.21 NM_016715 Crlf2 2.492 1.14 2.18 NM_029068 Snx16 2.335 1.08 2.17 AK148276 Slc11a2 2.127 0.99 2.15 AK009502 Tia1 2.316 1.08 2.14 AK035265 Aftph 2.545 1.19 2.14 AK036220 Rbm18 2.123 1.00 2.13 NM_008057 Fzd7 2.629 1.25 2.10 NM_007443 Ambp 4.522 2.16 2.10 NM_023892 Icam4 2.699 1.31 2.05 NM_139236 Nol6 2.041 1.00 2.04 NM_172911 D8Ertd82e 2.104 1.03 2.04 NM_028810 Rnd3 2.277 1.13 2.02 AK041830 Pcif1 2.318 1.15 2.01 IL-10 Downregulated Genes NM_027572 Slc22a16 0.150 1.33 8.88 NM_175294 Nucks1 0.233 1.60 6.88 NM_030253 Parp9 0.361 2.24 6.21 NM_001081216 Phip 0.476 2.94 6.17 NM_018745 Azin1 0.366 2.19 5.99  104 GenBank ID Gene Symbol SHIP1 WT SHIP1 KO Fold difference between WT and KO  LPS+IL-10 over LPS LPS+IL-10 over LPS NM_013742 Cars 0.449 2.16 4.82 NM_133871 Ifi44 0.369 1.70 4.61 NM_008320 Irf8 0.429 1.96 4.56 BY711602 Klf12 0.352 1.56 4.42 NM_144884 Tor1a 0.457 2.00 4.38 NM_019825 Ncoa6 0.405 1.70 4.21 NM_145564 Fbxo21 0.422 1.77 4.20 NM_025886 Rassf7 0.328 1.29 3.93 NM_008522 Ltf 0.197 0.77 3.92 NM_029083 Ddit4 0.321 1.24 3.85 NM_009114 S100a9 0.306 1.16 3.80 M89786 Gas2l1 0.322 1.21 3.74 NM_019972 Sort1 0.478 1.68 3.52 NM_015743 Nr4a3 0.453 1.58 3.48 BC061478 2010109K11Rik 0.433 1.49 3.44 AY149175 Zfp640 0.227 0.75 3.31 BC042572 H2-Q10 0.395 1.30 3.29 NM_026952 Crkrs 0.420 1.28 3.04 AK077833 Cpsf6 0.484 1.39 2.88 AK049901 Mthfd2l 0.499 1.41 2.82 NM_016812 Banp 0.463 1.30 2.81 NM_009058 Ralgds 0.452 1.25 2.77 NM_172503 Zswim4 0.359 0.99 2.76 AK020355 Zkscan1 0.452 1.24 2.74 NM_011075 Abcb1b 0.463 1.24 2.68 NM_145459 Zfp503 0.472 1.21 2.56 NM_026219 Uqcrb 0.487 1.23 2.53 NM_007684 Cetn3 0.496 1.21 2.44 AK077312 D7Ertd413e 0.319 0.78 2.43 NM_001033156 Fbxo33 0.423 1.02 2.41 NM_153063 Zfp472 0.340 0.82 2.40 NM_027044 Pfdn5 0.427 1.02 2.40 NM_173396 Tgif2 0.484 1.15 2.38 NM_025965 Ssr1 0.214 0.51 2.37 NM_020507 Tob2 0.487 1.15 2.36 NM_013613 Nr4a2 0.330 0.78 2.36 BC058175 Bcl2l11 0.362 0.84 2.33 NM_013650 S100a8 0.476 1.10 2.31 BC035255 Gpatch8 0.454 1.04 2.29 NM_138953 Ell2 0.460 1.04 2.26  105 GenBank ID Gene Symbol SHIP1 WT SHIP1 KO Fold difference between WT and KO  LPS+IL-10 over LPS LPS+IL-10 over LPS AK036755 Apbb1ip 0.312 0.70 2.25 AK014174 Chka 0.470 1.05 2.24 NM_001002927 Penk1 0.357 0.79 2.23 NM_029466 Arl5b 0.437 0.97 2.21 NM_020596 Egr4 0.437 0.89 2.05 NM_001025566 Chka 0.476 0.97 2.04 NM_026518 Rnf146 0.356 0.72 2.03 NM_009829 Ccnd2 0.497 0.99 2.00  Then we compared the SHIP1-regulated gene subset more closely with published data on IL-10 regulated genes, focusing on two studies that specifically looked at gene expression in IL-10 treated macrophages.  Lang et al. [416] examined the gene expression profiles of IL-10 KO BMDMs treated with LPS +/- IL-10 for 3 hours and identified 112 genes that were regulated by IL-10 in LPS-activated macrophages.  Three of these genes were on our SHIP1 subset (Ambp, Bcl2l11, Fzd7) (Figure 4.5A).  These investigators also found STAT3-dependence in 13 of these IL-10 regulated genes using quantitative RT-PCR and Northern blot in STAT3 KO macrophages.  AMBP is one of the STAT3-regulated genes.  AMBP is a precursor of two proteins, α1-microglobulin (α1-m) and bikunin.  α1-m (also called protein HC) belongs to the lipocain protein family, which acts as transporter of small hydrophobic molecules, and has been found to suppress immune response of lymphocytes and neutrophils [538].  Bikunin is a member of the Kunin family of serine protease inhibitors, and also has negative role in multiple immune processes including leukocyte migration and activation [539].  We and Lang et al. [416] both found that AMBP was upregulated upon IL-10 treatment, consistent with its immunosuppressive properties.  BCL2L11, commonly known as BIM, is an apoptosis  106 facilitator [540,541].  FZD7 is a receptor for the Wnt signalling which is involved in modulating inflammatory response [542].  Other STAT3-regulated genes verified by Lang et al. [416] are either not detected on our microarray (e.g. Il12p40 and Ccl12), not upregulated by IL-10 by at least 2-fold in SHIP1 WT cells (e.g. Bcl3, Mt2 and protein C receptor), not regulated by SHIP1 (e.g. Nfil3) or only weakly affected by SHIP1 KO, i.e.  < 2-fold difference between SHP1 WT and KO cells (e.g. Tnf and Map3k8) (Table 4.2).   Table 4.2: Comparison of expression profiles of Lang et al. identified IL-10/STAT3-regulated genes in SHIP1 WT and SHIP1 KO cells.   GenBank ID Gene Symbol Probe ID SHIP WT SHIP KO Fold difference between WT and KO LPS+IL-10 over LPS LPS+IL-10 over LPS NM_007443 Ambp A_51_P145785 4.522 2.16 2.10 NM_001303244 Il12b N/A N/A N/A N/A NM_011331 Ccl12 N/A N/A N/A N/A NM_001039701 Il1rn A_51_P307166 1.441 0.23 6.18 A_52_P431159 1.434 0.94 1.53 NM_016767 Batf A_51_P114616 1.814 0.78 2.32 NM_011171 Procr A_51_P382152 0.852 1.78 2.09 NM_010288 Gja1 A_52_P174915 1.533 0.80 1.92 NM_001008700 Il4ra A_51_P464478 1.412 2.29 1.62 NM_008630 Mt2 A_51_P246317 0.970 1.23 1.27 NM_033601 Bcl3 A_51_P136542 1.219 1.39 1.14 NM_017373 Nfil3 A_51_P111492 1.797 1.67 1.08 A_52_P500027 1.231 1.48 1.20 A_51_P111492 1.797 1.67 1.08 A_52_P500027 1.231 1.48 1.20 D13759 Map3k8 A_51_P115575 2.177 1.48 1.47 NM_013693 Tnf A_51_P385099 0.377 0.49 1.31  Hutchins et al. [45] has recently identified over 354 genes that were upregulated by IL-10 and that have nearby STAT3 binding sites, constituting a global view of IL-10/STAT3 mediated anti-inflammatory response in mouse macrophages.  A comparison with our subset of SHIP1-regulated genes showed that Cd274, Gpr35 and Crlf2 are  107 potentially upregulated by IL-10 in a SHIP1- and STAT3-dependent manner (Figure 4.5B).  CD274, also known as B7-H1 or PD-L1, is a co-stimulating molecule that is involved in negative regulation of T cell activation and cytokine production by inducing the production of IL-10 in monocytes [543].  GPR35 mRNA was found to be repressed by LPS in both BMDMs (2 hours and 6 hours) and perimacs (1 hour and 7 hours), as determined in microarray analysis [544] and its polymorphism is associated with a form of IBD [545].  Our microarray data showed that GPR35 was repressed by LPS at 0.5 hour, but induced at 1 hour.  CRLF2 can activate STAT3, STAT5 and JAK2, all of which have important role in immune cell function, and its overexpression is strongly linked to B-cell acute lymphoblastic leukemias (B-ALLs) [546].  Moreover, thymic stroma lymphopoietin (TSLP), the ligand of CRLF2, was shown to induce IL-10 expression in dendritic cells [547].  Whether these proteins contribute to IL-10 anti-inflammatory response will require further research.                        108    Figure 4.5 Identification of candidate SHIP1-STAT3 regulated genes.   Overlap of SHIP1-regulated gene subset with (A) IL-10 regulated gene subset from Lang et al. [416] or (B) IL-10 regulated genes that have STAT3 binding sites within 20 kb of transcription start site from Hutchins et al. [45] Identities of overlapping genes are listed.     130 6 247 0.5 hour IL-10 regulated Hutchins et al. IL-10 upregulated STAT3 binding sites  3 119 SHIP1-regulated Lrp1, Il17ra, Arid5a, Sbno2, Sema6b, Gbp5 Cd274 Gpr35 Crlf2   142 4 216 0.5 hour IL-10 regulated Hutchins et al. IL-10 downregulated STAT3 binding sites  1 121 SHIP1-regulated  Id3, Prdx6 Rgs2, Impact  Psmc5   137 9 100 0.5 hour IL-10 regulated Lang et al. IL-10 regulated  3 119 SHIP1-regulated  Saa2, Cebpd, Gadd45g, Csf3,   Zfand5, Sema6b, Map3k8, Mt1  Ambp Bcl2l11 Fzd7 A B  109 We also examined if there is a particular biological network that SHIP1 may mediate its function.  To do that, we used the NetworkAnalyst web-based tool that looks for enriched network using the user input gene list and genes (proteins) that directly interact with them [548].  The subset of SHIP1-regulated genes identified in our mircroarray (94 genes) was used as an input.  As shown in Figure 4.6, 17 SHIP1-regulated genes are strongly connected with IRF8 in the centre of the largest sub-network.  IRF8 is a transcription factor that can be upregulated by inflammatory stimuli including IFNγ and LPS [549], and downregulated by IL-10 [550].  Our microarray data also showed that IL-10 inhibited Irf8 in activated macrophages.  The deficiency of SHIP1 actually caused IL-10 to increase IRF8 level, indicating a strong requirement for SHIP1 in IL-10 inhibition of IRF8.  Out of the 17 genes mapped onto the network, 11 of them were downregulated by IL-10 at 0.5 hour in SHIP1 WT cells in our microarray, and SHIP1 deficiency either lessened the inhibition (e.g. BCL2L11 and TNFα), or actually reversed it to upregulation (e.g. IRF8).  Given that IRF8 and related genes are represented in the SHIP1-regulated network, it is not surprising to see “Interferon signalling” as one of the enriched pathways, as determined by pathway analysis using the Reactome database.  Other top hits include “Apoptosis” and “Cytokine signalling in immune system” (Table 4.3).  Both STAT3 and SHIP1 have implication in apoptosis.  STAT3 activation is likely to be anti-apoptotic since inhibition of STAT3 signalling causes cell death [551-554].  SHIP1, being a negative regulator of the survival-promoting PI3K, is usually considered as pro-apoptotic [555-558], but other reports showed that SHIP1 inhibits apoptosis [555,559,560].  Similarly, IL-10 has been shown to be apoptosis-inducing [561-563] and inhibiting [564-568], depending on the cell type, the state of  110 differentiation, and the type of stimuli.  However, IL-10 appears to prevent apoptosis in activated macrophages [564-567].    Figure 4.6 Interacting genes in the SHIP1-regulated gene subset.   The subset of SHIP1-regulated genes were analyzed in terms of network connectivity with NetworkAnalyst [548].  A total of 17 SHIP1-regulated genes are mapped into a network of 471 genes.  Labeled genes/nodes are from the SHIP1-regulated gene subset, and non-labeled nodes are directly interacting proteins.  Genes that are upregulated by IL-10 in SHIP1 WT cells are labeled in light purple, while downregulated genes are labeled black.  The most highly connected node is further indicated by a yellow circle.       111 Table 4.3: Enriched pathways identified by NetworkAnalyst using Reactome database  Rank Pathway P-Value 1 Immune system 4.46E-17 2 Apoptosis 7.67E-09 3 Cytokine signalling in immune system 9.31E-09 4 Adaptive immune system 1.54E-08 5 Interferon signalling 4.87E-07 6 Innate immune system 6.06E-07 7 Antigen processing-cross presentation 1.27E-06 8 Class I MHC mediated antigen processing & presentation 1.69E-06 9 Activation of BH3-only proteins 3.21E-06 10 Intrinsic pathway for apoptosis 4.68E-06 11 Death receptor signalling 7.29E-06 12 Extrinsic pathway for apoptosis 7.29E-06 13 Interferon gamma signalling 7.80E-06 14 ER-phagosome pathway 1.04E-05 15 Antigen presentation: folding, assembly and peptide loading of class I MHC 1.64E-05 16 TNF signalling 2.12E-05 17 TRIF-mediated programmed cell death 4.15E-05 18 Phagosomal maturation (early endosomal stage) 6.97E-05 19 Latent infection of Homo sapiens with Mycobacterium tuberculosis 6.97E-05 20 BH3-only proteins associate with and inactivate anti-apoptotic BCL-2 members 7.30E-05 21 Activation of BIM and translocation to mitochondria  9.02E-05 22 Inflammasomes 0.000152 23 Toll-like receptors cascades 0.000176 24 TRIF-mediated TLR3/TLR4 signalling  0.000325 25 MyD88-independent cascade  0.000325 26 Toll-like receptor 3 (TLR3) Cascade 0.000325 27 Activated TLR4 signalling 0.000536 28 Signalling by the B cell receptor (BCR) 0.000541 29 RIG-I/MDA5 mediated induction of IFN-alpha/beta pathways 0.000657 30 Downstream signalling events of B cell receptor (BCR) 0.000667   Our ultimate goal was to categorize IL-10 regulated genes to be SHIP1-regulated, STAT3-regulated or SHIP1-STAT3-regulated subsets.  The analysis described thus far  112 identified Ambp, Fzd7, Bcl2l11, Cd274, Gpr35, Crlf2 and Tnf to be SHIP1-STAT3 regulated.  Comparing the ChIP-seq data from Hutchin et al. [45] with our SHIP1-regulated gene subset, we found 11 SHIP1-regulated genes to have STAT3 bound near their transcription start site.  These are also grouped in the SHIP1-STAT3 subset.  The other genes in our SHIP1-regulated gene subset are considered as solely SHIP1-dependent.  Besides these genes, our laboratory has identified another 14 genes to be regulated by IL-10 in a SHIP1-dependent manner by real time-PCR [376].  None of these genes have passed our criteria for SHIP1-regulated genes in our microarray analysis. However, 12 of these genes showed modest dependence to SHIP1 (>10% difference between SHIP WT and SHIP KO cells) (Table 4.4).  Genes described by Lang et al. [416] and Hutchins et al. [45] that did not show differential expression in SHIP1 WT and SHIP1 KO cells were considered STAT3-regulated.      113 Table 4.4: Microarray data of previously described SHIP1-regulated genes.   Genbank ID Gene Symbol Probe ID SHIP1 WT SHIP1 KO Fold Change between WT and KO LPS+IL-10 over LPS LPS+IL-10 over LPS NM_011333 Ccl2 A_51_P286737 1.99 1.51 1.32 NM_011337 Ccl3 A_51_P140710 1.77 1.39 1.28 NM_008176 Cxcl1 A_51_P363187 1.00 0.94 1.07 NM_009140 Cxcl2 A_51_P217463 1.04 1.09 1.05 NM_007913 Egr1 A_51_P367866 0.80 0.92 1.15 NM_010493 Icam1 A_52_P613241 1.78 0.94 1.89 BC008626 Icam1 A_51_P408506 1.12 0.79 1.42 NM_008416 Junb A_51_P159194 0.83 1.14 1.38 NM_008416 Junb A_51_P159201 0.85 1.12 1.31 NM_010807 Marcksl1 A_51_P257550 0.87 1.36 1.57 NM_010807 Marcksl1 A_52_P35801 1.18 0.85 1.39 NM_010907 Nfkbia A_51_P295192 0.82 1.93 2.36 NM_030612 Nfkbiz A_51_P387591 0.73 0.63 1.16 NM_010444 Nr4a1 A_51_P239654 0.72 0.69 1.05 NM_023324 Peli1 A_51_P232889 0.75 1.33 1.77 NM_023324 Peli1 A_52_P298093 1.22 1.03 1.19 AK047301 Pim1 A_52_P535619 1.82 1.56 1.17 NM_008842 Pim1 A_52_P530291 1.08 0.94 1.15 NM_013671 Sod2 A_51_P172573 0.82 1.37 1.67 NM_013693 Tnf A_51_P385099 0.38 0.49 1.31 NM_009404 Tnfsf9 A_51_P460004 2.50 2.33 1.07  Expression of selected genes from these three categorizes were measured by real time-PCR analysis using RNA extracted from SHIP1 WT and KO perimacs, as well as STAT3 WT and KO perimacs, stimulated with LPS +/- IL-10.  The SHIP1 KO cells and the STAT3 KO cells were obtained from mice with different genetic backgrounds (BALB/c and C57/BL6), and thus two different WT cells were used in the experiments (Figure 4.7).  Out of the 42 genes tested, 10 genes were not regulated by IL-10 in both SHIP1 WT and STAT3 WT cells (Figure 4.7E), and a further 11 genes were only regulated by IL-10 in either SHIP1 WT or STAT3 WT cells but not both (Figure 4.7F).  Among the 21 validated IL-10 regulated genes, 11 showed dependence to SHIP1 and  114 STAT3 (Figure 4.7A), 2 to SHIP1 alone (Impact and Ccl3) (Figure 4.7B), and 1 to STAT3 alone (Id3) (Figure 4.7C).  IL-10 regulation of 3 genes (Bcl2l11, Irf8 and Nfil3) showed no impairment in SHIP1 KO and STAT3 KO cells (Figure 4.7D).  The remaining 4 genes did not fall into any of the criteria above (Figure 4.7G).  For example, Ambp was upregulated by IL-10 in both SHIP1 and STAT3 WT cells.  While deficiency of SHIP1 reduced IL-10 induction, deficiency of STAT3 actually increased IL-10 induction, indicating opposite functions of SHIP1 and STAT3 in the regulation of Ambp.      115   A   STAT3-SHIP1 regulated  116   B   SHIP1-regulated C   STAT3-regulated D   Not SHIP1 nor STAT3 regulated  117   E   Not regulated by IL-10 in both WT cells  118  F   Not regulated by IL-10 in one of the WT cells  119  Group Genes SHIP1-STAT3 regulated Cd274, Gpr35, Map3k8, Bcl3, Ptger4, Il4ra, Abcb1b, Nr4a1, Tnf, Ccl2, Tnfsf9 SHIP1-regulated Impact, Ccl3 STAT3-regulated Id3 Not SHIP1 nor STAT3 regulated Bcl2l11, Nfil3, Irf8 Not IL-10 regulated in both WT cells Psmc5, Rnf216, Nucks1, Tfam, Tor1a, Dpm1, Arida5, Lpr1, Crlf2, Ewsr1 Not IL-10 regulated in one of the WT cells Sbno2, Sod2, Icam1, Ccnd2, Nfkbia, Marksl1, Prdx6, Junb, Nfkbiz, Pim1, Egr1 Uncategorized Ambp, Peli1, Cxcl2, Rgs2  Figure 4.7 Real time PCR revealed that many of the IL-10 regulated genes require SHIP1 and STAT3.   Perimacs extracted from BALB/c mice (SHIP1 WT and SHIP1 KO), or C57BL/6 mice (STAT3 WT and STAT3 KO) were stimulated with LPS +/- IL-10 for 1 hour prior to total RNA extraction.  Expression levels of different genes were determined by real time PCR and plotted relative to LPS alone samples.  Statistical significance between WT and KO was calculated by a two-way ANOVA test with a 95% confidence (* p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001).  (A) IL-10 regulated genes that required both SHIP1 and STAT3, (B) SHIP1 alone, (C) STAT3 alone, (D) or neither SHIP1 nor STAT3. (E) Genes that were not regulated by IL-10 in both SHIP1 WT and STAT3 WT cells. (F) Genes that were not regulated by IL-10 either in SHIP1 WT H G   Uncategorized  120 or STAT3 WT. (G) Genes that do not belong to any of the groups above. (H) Table summarizing the gene expression data.   Among the SHIP1-STAT3 subset, we found that the expression levels of Ambp, Fzd7 and Crlf2 were relatively low in perimacs; Fzd7 expression was even below detection limit.  Crlf2 expression was not affected by IL-10 treatment.  Similar to the microarray analysis, real time-PCR analysis showed that Bcl2l11 was downregulated by IL-10, while Ambp, Cd274 and Gpr35 were upregulated by IL-10.  However, unlike the microarray analysis, deficiency of SHIP1 or STAT3 did not affect IL-10 regulation of Bcl2l11 (Figure 4.7F). By contrast, IL-10’s ability to upregulate Cd274 and Gpr35 was impaired in both SHIP1 KO and STAT3 KO cells, indicating these genes were regulated by IL-10 in a SHIP1-STAT3 dependent manner (Figure 4.7C).  We have also examined the expression levels of selected validated STAT3-regulated genes and genes in our SHIP1-regulated gene subset.  Consistent to the observations Lang et al. [416] had, Map3k8, Bcl3 and Il4ra were found to be IL-10/STAT3 regulated genes as STAT3 KO cells showed resistance to IL-10 treatment as compared to STAT3 WT cells (Figure 4.7C).  Additionally, we found that the absence of SHIP1 reduced IL-10 induction of these genes, showing SHIP1 involvement in IL-10 regulation of these genes.  Correspondingly, a few genes in the SHIP1-regulated subset were also found to be regulated by STAT3; these included Ccl2, Nr4a1, Tnfsf9, Abcb1b and Ptger4 (Figure 4.7C).  Unexpectedly, real time PCR showed that Irf8 was downregulated by LPS and upregulated by IL-10 (Figure 4.7GF), opposite to our microarray data and previous reports [549,550].  Also, SHIP1 deficiency did not impair IL-10 regulation of Irf8, unlike the observation shown by microarray.    121 Combining the microarray data and the real-time PCR data, we have generated new subsets of SHIP1-regulated, STAT3-regulated and SHIP1-STAT3 regulated genes; there are 113, 1089, and 22 genes in each gene subset respectively.  To determine the transcription factors responsible for the differential gene regulation, enrichment analysis was done with Enrichr [569].  The ChIP-x Enrichment Analysis (ChEA) database contains gene lists extracted from reported experiments of profiling of transcription factors binding to DNA from mammalian cells, and was used to identify transcription factors that were enriched for our gene subsets.  Expectedly, STAT3 is ranked 1st for both the STAT3 subset and STAT3-SHIP1 subset.  In the SHIP1 subset, STAT3 is ranked 44th.  The most enriched transcription factor is E2F transcription factor 1 (E2F1), which plays a crucial role in cell cycle control.  In addition, E2F1 has been shown to suppress NFκB activity [570-573], and may exert anti-inflammatory properties.  However, others have reported that E2F1 can bind to the p65 subunit of NFκB and act as a transcriptional activator for NFκB target genes [574].  Interestingly, p65 is the 3rd ranked transcription factor enriched in the SHIP1 subset, when we used another enrichment analysis tool, position weight matrices (PWMs) from TRANSFAC and JASPAR, also offered by Enrichr, which scan for transcription factor binding sites in the gene region composing    -2000 to +500 from the transcription start site.  However, p65 is ranked 46th and 52th, respectively, for the STAT3 and SHIP1-STAT3 subsets.  These observations indicate that maybe SHIP1 predominately regulates NFκB target genes via regulation on E2F1.  Besides transcription factors enriched in our gene subsets, we also examined the possibility of differential miRNA-mediated regulation using the TargetScan database.  Table 4.5 lists the first 10 miRNAs enriched in each gene subset.  In the 1st ranked  122 miRNA family enriched in the SHIP1 subset, miR-93 was reported to reduce LPS-induced NFκB cytokine production by targeting IRAK4 in mouse macrophages [575].  This miRNA family is ranked 45th and 63th in the STAT3 and SHIP1-STAT3 subsets respectively, suggesting that it may be involving in the SHIP1-only regulation.  For the STAT3 subset, the second ranked miRNA, miR-181, has been shown to regulate inflammatory response by decreasing the production of pro-inflammatory cytokines such as IL-1α and IL-6 [576,577] and increasing the production of IL-10 [578].  miR-181 is ranked 58th and 25th in the SHIP1 and SHIP1-STAT3 subsets respectively.  The most enriched miRNA in the SHIP1-STAT3 subset is miR-448, which was found to form an autoregulatory loop with NFκB in breast cancer cells [579], and associated with interferon-mediated antiviral response [580].  miR-448 is ranked 78th in the SHIP1 subset, and 88th in the STAT3 subset.  The non-overlapping miRNA enrichment analysis suggests that the three gene subsets may be regulated differentially at the post-transcriptional level.      123 Table 4.5: TargetScan analysis of SHIP1, STAT3, SHIP1-STAT3 gene subsets Index Name P-value Adjusted p-value Z-score Combined score SHIP1-regulated genes 1 AGCACTT,MIR-93,MIR-302A,MIR-302B,MIR-302C,MIR-302D,MIR-372,MIR-373,MIR-520E,MIR-520A,MIR-526B,MIR-520B,MIR-520C,MIR-520D 0.0011 0.1225 -1.9 3.99 2 TATTATA,MIR-374 0.0018 0.1225 -1.88 3.95 3 TGTGTGA,MIR-377 0.0078 0.2711 -1.74 2.27 4 ACATTCC,MIR-1,MIR-206 0.0102 0.2845 -1.75 2.2 5 CACTGCC,MIR-34A,MIR-34C,MIR-449 0.0075 0.2711 -1.64 2.15 6 AAGCACT,MIR-520F 0.0158 0.2914 -1.72 2.12 7 GTCTTCC,MIR-7 0.0210 0.2914 -1.59 1.96 8 ACCATTT,MIR-522 0.0183 0.2914 -1.55 1.91 9 TGTTTAC,MIR-30A-5P,MIR-30C,MIR-30D,MIR-30B,MIR-30E-5P 0.0245 0.3098 -1.62 1.9 10 TTCCGTT,MIR-191 0.0151 0.2914 -1.47 1.81 STAT3-regulated genes 1 GTGTTGA,MIR-505 0.0001 0.0148 -1.89 7.97 2 TGAATGT,MIR-181A,MIR-181B,MIR-181C,MIR-181D 0.0001 0.0148 -1.86 7.85 3 TTGCACT,MIR-130A,MIR-301,MIR-130B 0.0008 0.0438 -1.91 5.96 4 TTTGCAC,MIR-19A,MIR-19B 0.0008 0.0438 -1.89 5.9 5 ATGTACA,MIR-493 0.0024 0.0998 -1.77 4.08 6 CATTTCA,MIR-203 0.0040 0.1195 -1.73 3.67 7 ACTTTAT,MIR-142-5P 0.0038 0.1195 -1.68 3.57 8 GTGCAAT,MIR-25,MIR-32,MIR-92,MIR-363,MIR-367 0.0058 0.1529 -1.64 3.08 9 TGCTTTG,MIR-330 0.0092 0.1759 -1.63 2.84 10 GCTTGAA,MIR-498 0.0082 0.1759 -1.63 2.83 SHIP1-STAT3 regulated genes 1 ATATGCA,MIR-448 0.0042 0.2936 -1.82 2.23 2 ACTGTGA,MIR-27A,MIR-27B 0.0368 0.3803 -1.89 1.83 3 CACTTTG,MIR-520G,MIR-520H 0.0547 0.3803 -1.76 1.7 4 CAGCTTT,MIR-320 0.0622 0.3803 -1.72 1.67 5 GTGACTT,MIR-224 0.0258 0.3803 -1.69 1.63 6 ATGTTAA,MIR-302C 0.0563 0.3803 -1.68 1.63 7 ACATTCC,MIR-1,MIR-206 0.0819 0.3803 -1.64 1.58 8 TGCACTG,MIR-148A,MIR-152,MIR-148B 0.0847 0.3803 -1.62 1.56 9 GTAAACC,MIR-299-5P 0.0815 0.3803 -1.62 1.56 10 TTGCACT,MIR-130A,MIR-301,MIR-130B 0.1350 0.3803 -1.53 1.48   124 4.3. Discussion IL-10 and IL-6 both induce STAT3 activation, but these cytokines have opposite effects on macrophage functions: IL-6 stimulation induces a pro-inflammatory phenotype while IL-10 is considered anti-inflammatory.  One mechanism underlying the divergent effect of STAT3 activated by IL-6 and IL-10 is the action of the protein SOCS3 [581].  Both IL-6 and IL-10 are able to induce the expression of SOCS3 mRNA and protein in a STAT3-dependent manner [582], with IL-10 induction being stronger.  However, SOCS3 only inhibits IL-6 signalling but not IL-10 signalling because the gp130 subunit of the IL-6 receptor contains a binding site for SOCS3, while IL-10 receptor does not [581].  In macrophages lacking SOCS3 or carrying a mutation in the SOCS3-binding site of IL-6 receptor, IL-6 actually becomes anti-inflammatory and inhibits LPS-induced TNFα production.  However, we must be cautious in making the conclusion that SOCS3 is the only essential molecule distinguishing IL-6 signalling and IL-10 signalling.  Thus, it is necessary to determine other mediators downstream of STAT3-activation that are differentially induced by these cytokines. The majority of the studies have suggested that STAT3 is responsible for all IL-10’s anti-inflammatory functions by activating the expression of specific gene products that inhibit pro-inflammatory signalling [55,333,373,374,416,583].  But now, we know that although STAT3 is required for IL-10 function, it is not sufficient [419,420,535].  In particular, SHIP1 is also necessary for IL-10 function, and that SHIP1 appears to interact with STAT3 to mediate IL-10 function.  This chapter has described studies that examined the SHIP1-STAT3 model.    125 Consistent with data obtained from standard stimulation procedure, our data from using the continuous flow cell apparatus also showed that SHIP1 and STAT3 were required to mediate IL-10 inhibition of LPS-induced TNFα production, and deficiency of one but not the other showed incomplete inhibition (Figure 4.1).  We speculated that SHIP1 and STAT3 form a signalling complex for IL-10 function; indeed, we found that upon IL-10 or SHIP1 activator treatment, SHIP1 becomes associated with STAT3 in macrophages (data not shown).  However, our efforts to show the physical interaction of SHIP1 and STAT3 and to map out the interacting domain using purified His6-SHIP1 and Flag-STAT3 have been fruitless (Figure 4.2).  Certain interaction features must be missing in our system, for example, phosphorylation events commonly required on signalling molecules.  It is also possible that another protein is either acting as a bridge between SHIP1 and STAT3, or necessary for stabilizing the SHIP1-STAT3 complex.  A candidate protein is AMPK, which phosphorylates and activates STAT3 after IL-10 stimulation [370].  Moreover, AMPK deficiency leads to the loss of STAT3 activation and insufficient inhibition of pro-inflammatory cytokine production in activated macrophages [370].  Consistent with its role in IL-10 function, our unpublished data showed that AMPK was actually pulled down by SHIP1 in IL-10 treated macrophages, strengthening the hypothesis that AMPK may be part of the SHIP1-STAT3 complex (S. Shakibakho, unpublished). To address the possibility that phosphorylation may be required for SHIP1-STAT3 function, we mutated 4 different tyrosine residues in SHIP1 and examined if any of these mutants behaved differently from wild type SHIP1.  By measuring IL-10 inhibition of TNFα production in LPS-stimulated macrophages, we found that cells  126 containing Y190F SHIP1 were no longer inhibited by IL-10 (Figure 4.3), suggesting that Y190 may be important to interact with STAT3 (and potentially other proteins) to form the necessary signalling complex.  Also, the integrity of the SHIP1 protein structure could be disrupted with the Y190F mutation, causing misfolding of the protein and thus eliminating its biological functions.  These can be examined by determining if this SHIP1 mutant could still pull down STAT3 in IL-10 treated macrophages in a pull down assay.  An in vitro phosphatase assay performed with SHIP1 Y190F protein would be informative on its structure as well; misfolded protein should have reduced or even no enzymatic activity.  However, it is worth noting that the catalytic activity of SHIP1 may not be essential for its anti-inflammatory role; a triple-point mutation in the active site of SHIP1, which causes the enzyme to be inactive, was still able to inhibit TNFα production in activated macrophages (to a lesser extent) [317].   IL-10 inhibition of macrophages is not limited to TNFα production alone, and several studies have looked at IL-10 regulating global gene expression profiling [45,416,584,585] and identified previously unknown IL-10 regulated genes in macrophages.  We decided to focus on two studies, one using microarray analysis [416], and the other using a combination of ChIP-seq and RNA-seq [45].  The first observation we had is the small number of overlapping genes identified in their studies and our presented data.  That can be due to the differences in cell types (BMDMs vs perimacs), the stimulation condition (with or without LPS and the concentration of IL-10), the time points (0.5 hour vs 3 or 4 hours), as well as the differential gene sets detectable in each methodology.  Also, SHIP1 KO macrophages were found to be skewed towards an alternatively activated phenotype [464], which may affect expression of certain genes.   127 Nevertheless, we have identified a few IL-10 induced genes that may be regulated by both SHIP1 and STAT3 when we compared our SHIP1-regulated gene subset to each of the two studies (Figure 4.6 and 4.7).   Ambp, Bcl2l11, Fzd7, Cd274, Gpr35 and Crlf2 are all upregulated by IL-10 in our microarray analysis.  Expression of Ambp was verified to be STAT3-dependent by RT-PCR [416], and Cd274, Gpr35 and Crlf2 have STAT3 bound near their promoters after IL-10 treatment [45].  Among these, we are particularly interested in GPR35, a G-protein coupled receptor that has anti-inflammatory properties [586].  Genome wide studies have associated polymerophism of the GPR35 gene with inflammatory diseases such as IBD [587], type 2 diabetes [588], and atherosclerosis [589].  Also, a number of GRP35 agonists and antagonists have been described ([590-592], reviewed in [593]).  In macrophages, binding of GPR35 by kynurenic acid has been shown to attenuate LPS-induced TNFα [591], suggesting an inhibitory role in macrophage activation.  It is consistent with IL-10’s ability to upregulate GPR35.  Our real time-PCR analysis confirmed IL-10 induction of GPR35 mRNA, and also showed that both SHIP1 and STAT3 were required for this upregulation.  Future experiments should focus on whether the GPR35 protein level is altered by IL-10, as well as the biological relevance of this regulation.   Through network analysis, apoptosis is one of the highest ranked pathways that may also be regulated via SHIP1.  Lang et al. [416] and we both found that Bcl2l11 (also known as Bim), an apoptosis facilitator, was regulated by IL-10.  Lang et al. [416] showed that IL-10 enhanced the LPS-induced Bcl2l11 by 1.3-fold at 3 hours, but we found that IL-10 actually downregulated Bcl2l11 as detected by both microarray and real  128 time-PCR analysis.  The discrepancy may be due to the cell types used or the time points tested.  Bcl2l11 is upregulated by TLR signalling through MAPK activation [564,594] At the same time, TLR signalling results in the phosphorylation of Bcl2l11 that leads to degradation of the protein [595].  Previous studies show that IL-10 induces apoptosis in the development and differentiation of different myeloid cells in order to maintain immune hemostasis [561-563] but IL-10 usually inhibits apoptosis in activated cells [564,565].  The downregulation of Bcl2l11 by IL-10 in LPS-stimulated macrophages is consistent with these reports.  However, we did not observe SHIP1 and STAT3 involvement in IL-10 regulation of Bcl2l11 by real time-PCR.  More replicates and experimental conditions will be required to draw definitive conclusion.  The literatures supported an anti-apoptosis function mediated by STAT3 [551-554].  While studies using overexpression of SHIP1 in cells or SHIP1 KO cells showed that SHIP1 promoted apoptosis [555-557], inhibition of SHIP1 may actually be anti-apoptotic [481,558-560].  The actual role of SHIP1 in IL-10 mediated apoptosis will require further experimentation.   The last part of the study focuses on a wider view on IL-10 regulation on gene expression via SHIP1 and STAT3 by categorizing genes into SHIP1-regulated, STAT3-regulated, and SHIP1-STAT3 regulated subsets.  Preliminary efforts to identify differential regulatory mechanism with bioinformatics tools have shown that the transcription factor E2F1 may be important for SHIP1-regulated genes.  E2F1 is known to regulate NFκB activity, but both positive and negative regulations have been reported.  [570-574].  While E2F1 is not identified as highly enriched in our STAT3 subset (rank 19th) and SHIP1-STAT3 gene subset (rank 166th), a genome-wide study has shown that  129 STAT3 is recruited to E2F1 pre-bound DNA in four different cell types including macrophages [418].  The specific mechanism E2F1 uses may be cell type, stimulation, and time dependent.  Additionally, we found that the three gene subsets may be regulated differentially via post-transcriptional mechanism because each subset is enriched for seed sequences of different miRNAs.  One of the caveats of our analysis is that the STAT3 subset is quite substantial with 1089 genes, compared to only 113 and 22 genes in the SHIP1 and SHIP1-STAT3 subsets.  Nevertheless, with our real time PCR data, we found that a large percentage of IL-10 regulated genes require both SHIP1 and STAT3, suggesting that SHIP1 and STAT3 may cooperate to mediate IL-10 regulation and it may be a more common mechanism than SHIP1 and STAT3 work independently downstream of IL-10.   In summary, we have provided evidence that SHIP1 and STAT3 cooperate to mediate IL-10’s anti-inflammatory function in macrophages, perhaps due to the formation of a signalling complex consisting of SHIP1, STAT3 and other unconfirmed proteins, and the subsequent signalling events triggered by such a complex.  Our microarray analysis supports a model in which SHIP1 and STAT3 differentially mediate IL-10’s regulation of gene expression, although further delineation will be needed.  This new mechanism opens up the possibility to regulate specific clusters of genes using a SHIP1 modulator or a STAT3 modulator in conditions where global inhibition of IL-10 function is not desired.   130        Chapter 5: Crystal Structure of SHIP1 Fragment Reveals Insight into SHIP1 Activator Binding     131 5.1 Introduction  Class I PI-3 kinases (PI3K) have critical roles in regulating cell proliferation, survival, differentiation and metabolism in all cell types.  In immune cells, ligand engagement of nearly all receptors can activate PI3K.  Once activated, PI3K phosphorylates PI(4,5)P2 to generate PI(3,4,5)P3 in the plasma membrane.  PI(3,4,5)P3 then triggers a cascade of downstream signalling events via the recruitment of PH-domain containing proteins such as AKT.  Deregulation of the PI3K pathway has been implicated in cancer and inflammatory disorders [596], and therefore intensive research has been put into the development of therapeutics targeting PI3K and its downstream signalling molecules.  However, because PI3K is involved in so many cellular processes, PI3K inhibitors can easily show off-target effects and lead to undesired complications [597-600].  Also, emerging studies show that the different isoforms of PI3K can have different roles, and even opposite roles, in certain processes [601-604].  Drugs that inhibit individual PI3K isoforms are wanted in this case.  Thus, isoform specific inhibitors have been developed, but that leads to the question of whether other isoforms may compensate for the functions of the inhibited isoforms.  Because kinases and phosphatases orchestrate the phosphorylation changes necessary for proper cell functions, an attractive alternative is to develop drugs that can activate phosphoinositol phosphatases to reduce PI(3,4,5)P3 level.  SHIP1 is an especially unique target in treating immune-related disorders, because its expression is restricted to cells in the hematopoietic lineages, and any therapeutics targeting SHIP1 should limit its effect to these cells and minimalize any side-effects.   SHIP1 contains a 300-residues catalytic domain common to all 5'-phosphatases as predicted by primary sequence alignments; this domain has a similar fold to the  132 apurineic/apyrimidinic repair endonucleases [605].  SHIP1 also contains additional protein domains that facilitate its functions (Figure 5.1A), as described in Chapter 1.  The regulation of SHIP1 was previously thought to be solely dependent on its location in the cells, which is mediated mainly by its SH2 domain and its C-terminal regions.  However, this view has been challenged in recent years.  We showed by kinetic studies that SHIP is allosterically activated by its end product PI(3,4)P2, as well as a small molecule AQX-MN100 [430].  This allosteric regulation requires PH-R and C2 domains that flank the phosphatase catalytic domain; deletion of either domain abolishes the impact of AQX-MN100 on SHIP1 enzyme activity ([430] and data not shown).  We have also identified the site of AQX-MN100 binding to be the C2 domain [430], while the PH-R domain is the PIP3 binding site [429].   The objective of this chapter is to characterize the molecular basis of the association of SHIP1 activators to SHIP1.  We first identified the minimal region of SHIP1 that can be allosterically activated by SHIP1 activators.  We then solved the structure of this region via x-ray crystallography, which, together with various biochemical approaches, provides valuable information on the interaction of the SHIP1 activators and the SHIP1 enzyme.     133 5.2 Results  5.2.1 The minimal enzymatic region of SHIP1 contains the phosphatase and C2 domains.  To gain more understanding of the interaction between SHIP1 and its activators, we aimed to obtain a crystal structure of the protein-ligand complex.  However, crystallizing the full-length protein would be challenging because (1) SHIP1 is a relatively large protein (about 145 kDa with 1911 amino acids in mouse SHIP1) and thus contains multiple flexible loops that likely hinder crystallization, (2) full-length SHIP1 is quite unstable and has the tendency to degrade during purification.  Hence, a truncated SHIP1 construct containing the PH-R, phosphatase and C2 domains (PPAC) was generated (Figure 5.1A).  PH-R and C2 domains were included, because they were shown to be required for allosteric regulation [430].   To verify the integrity of the enzyme, we first expressed and purified SHIP1 and PPAC from HEK293T cells and compared their enzymatic properties in an in vitro phosphatase assay using IP4 as the substrate (Figure 5.1B).  PPAC had a similar Kcat value as SHIP1 but had a higher affinity to the substrate (lower Km but statistically insignificant), suggesting that the domains that were deleted did not appear to affect the catalytic activity of enzyme.  We also tested whether the synthetic SHIP1 activator, AQX-MN100, could still enhance activity of PPAC, and found that PPAC was activated by AQX-MN100 to similar level as full length SHIP1 (Figure 5.2).   HEK293T expression systems are impractical for producing enough protein for crystallization screening so we attempted to express PPAC in bacteria, as well as in Sf9, an insect cell line.  Unfortunately, recombinant PPAC was mostly insoluble when  134 expressed in bacteria, even when it was expressed as a fusion protein with maltose binding protein (MBP), a well-known solubility enhancer [606].  The small amount of soluble PPAC protein purified from bacteria was found to have similar enzymatic properties as PPAC expressed in HEK293T cells (Figure 5.1B).  While we obtained reasonable amounts of active PPAC from Sf9 cells for crystallization, this protein did not yield any crystal in all the conditions tested.  We also systematically screened for different PPAC constructs by shortening the C-terminus.  The N-terminus was not altered because the structure of the PH-R domain was previously modeled based on NMR studies [429].  However, none of these constructs crystallized.   Previous data showed that SHIP1 activators directly interact with C2 domain but not PH-R domain [430].  We thus decided to generate a second set of truncated constructs that only contain the phosphatase and the C2 domains (PAC).  Two different C-termini were chosen, and these proteins were named PAC1 (residues 402-861) and PAC2 (residues 402-857) respectively.  Satisfyingly, we were able to produce a large quantity of both PAC1 and PAC2 proteins from bacteria as MBP-fusion proteins.  The proteins were soluble and stayed as monomers after tag removal.  Similar to PPAC, PAC2 has a lower Km value than SHIP1 and a comparable Kcat as SHIP1 (Figure 5.1B).  Surprisingly, AQX-MN100 was still able to enhance activity of PAC2 to the same extend as SHIP1 (Figure 5.2), even though PAC2 lacks the PH-R domain.    135     Enzyme Kcat (min -1) Km  (μM) Kcat/Km (pmol PO4/min /pmol enzyme /µM substrate) SHIP1 (293T) 1290 +/- 420 148+/-9 8.7 +/-3.3 PPAC (293T) 1032 +/-413 67 +/-34 16.0 +/-1.7 PPAC (E. coli) 1020 +/-203 65 +/-8 15.5 +/-1.3 PAC2 (E. coli) 708 +/-355 66 +/-22 10.3 +/-3.1  Figure 5.1 PPAC and PAC have similar enzymatic activity as full length SHIP1.   (A) Schematic diagram of the different SHIP1 truncation constructs.  (B) Initial velocities were determined at the indicated concentrations of IP5.  Kcat and Km values were calculated using GraphPad software.  B A  Catalytic C2 PH-R SH2 NPXY PXXP  Catalytic C2 PH-R  Catalytic C2 SHIP1 PPAC PAC1/2  136   Figure 5.2 AQX-MN100 is able to enhance the enzymatic activity of PPAC and PAC.   (A) The structure of AQX-MN100.  (B) Recombinant proteins were preincubated with 0.2 mM AQX-MN100 or ethanol (solvent control) for 10 minutes at 23°C before incubating with 50 uM IP4 for 10 minutes at 37°C.  The reaction was stopped by the addition of Malachite Green reagent.  Data are presented as fold activation compared to the ethanol treatment.  Statistical significance between treatments was calculated by a two-way ANOVA test with a 95% confidence (** p < 0.01, **** p < 0.0001).  Similar results were observed in at least two independent experiments.    To more definitively determine the role of C2 domain in regulating SHIP1 phosphatase activity, we made a construct containing only the phosphatase domain (residues 402 to 718).  However, this isolated phosphatase domain was found to be highly insoluble in bacteria and we were not able to determine the complete enzyme kinetic parameters of this domain alone.  This observation agrees with a recent study showing that the phosphatase domain of SHIP2, a close homologue of SHIP1, is only marginally active compared to other 5'-phosphatases [607].  The authors pointed out the possibility that SHIP2’s phosphatase domain might require other domains to reach optimal activity.  Also, our definition of minimal enzymatic region (PAC) is consistent with previous report [608] that defines the minimal enzyme as having the boundaries between residues Fold change over 1% EtOH0.00.51.01.5PAC2 (E. coli)PPAC (E. coli)PPAC (HEK293T)SHIP1 (HEK293T)********************** **** **** ****  -  +  +     -   +  +     -  +  +    -  +  +  -   -  +     -    -  +     -   -  +    -   -  +EtOHAQX-MN100AQX-MN100 A B  137 400 and 866 in mouse SHIP1.  We thus conclude that PAC is the minimal catalytic region of SHIP1 that can be regulated allosterically, and used both PAC1 and PAC2 in our crystallization screens. We have also explored the possibility that the enzyme might be regulated by calcium because it contains a C2 domain, a known calcium-binding domain.  As shown in Figure 5.3A, the addition of CaCl2 decreased the basal activity of SHIP1 and PAC1, but did not inhibit enzyme activation by AQX-MN100.  To our surprise, calcium actually enhanced the activation ability of AQX-MN100, as demonstrated by comparison to untreated sample (Figure 5.3B).  We thus included CaCl2 in some of our crystallization conditions.    138  Figure 5.3 Calcium reduces basal enzyme activity but enhances activation by SHIP1 activators.   PAC1 enzyme was preincubated with, 0.2 mM AQX-MN100, ethanol (solvent control), or 80 μM of PI(3,4)P2-diC8 for 10 minutes at 23°C before incubating with 50 μM IP4 for 10 minutes at 37°C.  The reaction was stopped by the addition of Malachite Green reagent.  Data are presented as either (A) background-corrected A650 values, (B) fold change compared to the ethanol treatment for AQX-MN100 or (C) fold change compared to untreated sample for PI(3,4)P2.  Statistical significance between treatments was calculated by a two-way ANOVA test with a 95% UntreatedEtOHAQX-MN100UntreatedEtOHAQX-MN1000123Fold change over EtOHActivation by AQX-MN100No Ca2+ 2 mM Ca2+****UntreatedEtOHAQX-MN100PI(3,4)P 2UntreatedEtOHAQX-MN100PI(3,4)P 20.000.020.040.060.080.10A650 minus backgroundEnzyme ActivityNo Ca2+ 2 mM Ca2+********************A B C UntreatedPI(3,4)P 2UntreatedPI(3,4)P 2012345Fold change over UntreatedActivation by PI(3,4)P2No Ca2+ 2 mM Ca2+**** 139 confidence (**** p < 0.0001).  Similar results were observed in at least two independent experiments.   Representative data are shown.   5.2.2 Crystal structure of PAC The first crystal obtained was of wild type PAC2 and it diffracted at resolution of 2.56Å.  SHIP2’s phosphatase domain (PDB: 3NR8) was used in molecular replacement to determine the structure of PAC2 phosphatase domain.  However, we exhausted our means in solving the C2 domain and were still unsuccessful; there were too many regions with discontinued electron density, suggesting that the C2 domain might be quite flexible in nature.  We approached this problem by mutating residues in those flexible regions.  Residues with flexible side chains on the protein surface can impede the ability of the protein to form intermolecular contacts necessary for crystal formation.  The Surface Entropy Reduction (SER) approach, as described by Derewenda [609], replaces large and flexible hydrophilic residues chains, such as Lys and Glu, to smaller side chains, usually Ala, on the surface of the protein.  Using the SERp server [610], we identified three regions in the PAC2 protein that are enriched with either Lys or Glu; we labeled them as Cluster A to Cluster C (Table A.4); only Cluster C is located in the C2 domain.  These mutations were introduced in both PAC1 and PAC2.  We obtained diffraction-quality crystals of PAC1 with mutation at Cluster C (E770A E772A E773A); this mutant is termed as PAC1cc.  Crystals of PAC1cc diffracted at a higher resolution than those of wild type PAC2.  We were able to determine its structure and then used it to solve structure of wild type PAC2 using molecular replacement.  PAC1cc were found to crystallize in two different space groups (Table 5.1).      140 Table 5.1: Data collection and refinement statistics  PAC1cc wild type PAC2 PAC1cc  X-ray source CLS-08ID-1 APS-IDD APS-IDD Wavelength 1.03317 1.03317 1.03319 Detector CCD CCD CCD Space group C121 P 1 21 1 P 21 21 21 Unit cell parameters (Å) a=128.21, b=45.1, c=162.56 a=140.07, b=45.53, c=155.17 a=45.10, b=73.20, c=125.21 Unit cell angles (°) α=90.0, β= 107.7, γ= 90.0 α=90.0, β= 91.44, γ= 90.0 α=90.0, β= 90.0   γ= 90.0 Angle increment (°) 0.5 1 0.5 Number of images 360? 180 267 Biological assembly per ASU 2 4 1 Solvent content (%) 42 47 38 Resolution range (Å) a 47.12-2.10  (2.15-2.10) 48.64-2.34  (2.48-2.34) 47.36-1.50  (1.59-1.50) Completeness (%) a 99.7 (99.8) 97.8 (91.9) 98.9 (98.6) Rmeas (%)a 8.6 (106.0) 11.9 (112) 5.9 (78.7) CC (1/2) 99.8 (68.6) 99.6 (60.6) 99.9 (68.2) Unique reflections a 51106 (3678) 80146 (11997) 66070 (10528) Observed reflections a 191535 (13756)  295158 (41343) 217029 (34822) Average redundancy a 3.7 (3.7) 3.68 (3.44) 3.28 (3.31) Average I/σ(I) a 12.0 (1.49) 11.14 (1.33) 13.79 (1.85) Wilson B factor (Å2) 39.73 50.94 25.38         Refinement statistics REFMAC 5.8.0071 REFMAC 5.8.0071 REFMAC 5.8.0071 Rwork / Rfree / Rtotal 19.06/23.67/19.29 22.12/25.56/22.29 18.27/20.72/18.35 R.m.s.d.   bond length (Å)/bond angle (°)  0.015/1.726  0.020/1.930  0.019/1.965 Ramachandran plot  (% of residues in core/ additional allowed/  disallowed regions) 97/2.53/0.47 95.8/3.77/0.43 97.28/2.18/0.54 Average B values (Å2)   53.339/51.811/ 55.839/42.741/ 49.340  50.101/48.663/ 51.573/29.663/ none  23.299/21.183/ 25.219/25.037/ 25.762 all atoms/protein main chain/ protein side chains/solvent atoms/isopropanol atoms Number of protein atoms 6871 13234 3591 Number of solvent atoms 114 46 175 Number of ligand atoms 4 0 4 a Numbers in parenthesis indicate data in the last resolution shell.   141 5.2.1.1 Overall structure The PAC structures contained the phosphatase and the C2 domains (Figure 5.4A).  The phosphatase domain has a similar fold as found in other phosphoinositide 5'-phosphatases including INPP5B, OCRL and SHIP2 [607].  The structure of SHIP1 C2 domain is similar to other C2 domains despite low sequence identity (Figure 5.9).  The C2 domain interacts with the phosphatase domain extensively across an interface that is away from the active site.  The C2 domain may be more mobile than the phosphatase domain, indicated by an overall higher B factor (Figure 5.4B-D).  The B-factor describes how spread-out the electron density is for each atom, and gives the uncertainty for the position of each atom.  A number of factors can contribute to a high B factor, including high mobility of individual atoms and side chains.  In all three solved structures, the linker between the two domains (about 20 residues long) gave no electron density and thus is not modeled.   There are four, two, and one molecules in the asymmetrical units for the three crystals respectively, and their overall structures and domain orientations are similar to each other with slight shift in the positions in the loops and some β-strands.  We focused on the structure of wild type PAC2 for majority of analyses, but the differences in these three structures will be discussed when appropriate.  142   Figure 5.4 Structures of wild type PAC2 and PAC1cc.   (A) Superposition of the three structure: wild type PAC2 (Green), PAC1cc (Space group C121, Purple) and PAC1cc (Space group P 21 21 21, Magenta).  (B-D) The structures are coloured based on B-factor.  Red represents high dynamic regions while blue represents low dynamic regions.    5.2.1.2 Phosphatase domain The phosphatase domain has an overall fold of a β-sandwich containing eleven β-strands that are surrounded by a few α-helices at the periphery.  Sequence alignments A B C D 0Å 75Å C2 Phosphatase Wild type PAC2 PAC1cc, C121 PAC1cc, P 21 21 21 P4IM Active site Cluster C  mutations  143 show that SHIP1 contains all the conserved residues in the active sites as other 5’phosphatases (Figure 5.5).  A structure of the INPP5B phosphatase domain with PI(3,4)P2 has been solved recently (PBD:4CML) and detailed interaction between the active site and PI(3,4)P2 have been documented [607].  In the same study, the authors had also determined the structure of the OCRL phosphatase domain bound by a phosphate ion that mimics the position of the 5-phosphate in the substrate.  These two structures give us crucial information of the interaction between the active site and the enzyme substrate PI(3,4,5)P3, such as the conversed residues important for substrate binding, the atomic basis of substrate specificity, and potential membrane interaction interface.    144  Figure 5.5 Sequence alignments of mouse phosphoinositol-5'-phosphatases.   The sequence alignments of the phosphatase domains of a few mouse phosphoinositol-5-phosphatases were performed by Clustal Omega [611].  The secondary structure, according to the SHIP1 structure, is showed at the top of the sequences.  Residues that are identically conserved are written in white with red background.  Residues that are 70-100% functionally conserved are written in bold with yellow background.  The inositol-ring interacting residue is indicated by a cyan diamond.  Residues interacting with 1-phosphatase, 3/4-phosphates and 5-phosphates are indicated with blue circles, white circles and magenta circles respectively.  The P4 interacting motif, the lipid chain 1 recognition and the lipid chain 2 recognition motifs, as defined in the INPP5B by Tresaugues et al. [607], are labeled as P4IM, LC1R and LC2R.  Residues that were selected for Ala mutations are indicated with red stars.  145 Figure 5.6 shows a superposition of the structures of SHIP1, SHIP2 and PI(3,4)P2-bound-INPP5B phosphates domains.  Comparison of the SHIP1 phosphatase domain to the structure of SHIP2 phosphatase domain shows a root-mean squared deviation (rmsd) of 0.437 Å for 233 superimposed Cα atoms out of 317 Cα atoms (SHIP1 structure).  The similarity lies within the core of the domain while the periphery is more dissimilar.  The rmsd value from PI(3,4)P2-bound-INPP5B is 0.524 Å (183 Cα atoms), with highly similar folds in the core of the domains.  Most of the residues interacting with 1-P and 5-P units of substrate are conserved and are positioned similarly in SHIP1 phosphatase domain with minor differences.  In the INPP5B structure, the 1-P moiety of the substrate forms hydrogen bond with the side chain of Asn379 (Asn523 in SHIP1) and Lys380 (Lys524), but in the SHIP1 structure, Asn523 points to a different direction (Figure 5.6B).  This shift of the side chain could be due to the lack of ligand in the SHIP1 phosphatase domain.  Ala403 in INPP5B lines the inositol ring, and this residue is replaced by Ser547 in SHIP1 (and SHIP2), which should be small enough to accommodate the inositol ring.  The 5-P moiety locates in a highly conserved pocket in 5-phosphatases containing six conserved residues (Asn523, Lys524, His544, Asp590, Asn592, His704 in SHIP1) (Figure 5.6C); the positions of these residues in SHIP1 structure are almost identical to those in other 5-phosphatases, with minor shifts in the side chains of Asn523 and Lys525.   Most 5-phosphatases prefer to hydrolyze the 5-P from either PI(4,5)P2 or PI(3,4,5)P3 [612,613], suggesting the enzymatic selectivity towards the 4-phosphate.  SHIP1 and SHIP2 have an additional requirement for 3'-position to be phosphorylated [614,615].  INPP5B extensively interacts with the 4-P moiety through a conserved loop  146 called the P4-interacting motif (P4IM), which contains Tyr502, Lys503, Arg518 and Lys516.  These residues stabilize 4-P through a combination of hydrogen bonds and electrostatic interactions.  The P4IM loop is seven residues longer in SHIP1 (and SHIP2), making it quite different than that in INPP5B (Figure 5.5).  A molecular dynamics study using the structure of SHIP2 in complex with a competitive inhibitor (PDB:4A9C) indicates that the longer P4IM loop could fold over and provide additional interaction [616].  Arg682 and Asn684 in SHIP2 are well positioned to interact with 3-P and 4-P.  The corresponding residues in SHIP1 are Lys668 and Asn670, both of which should still be able to interact with 3-P and 4-P (Figure 5.6D).  Worthy of note is that the P4IM loop is not modeled in majority of molecules in the asymmetrical unit, pointing out the flexibility of the loop.  We also found that the P4IM loop in our wild type PAC2 structure adopts an “opened” conformation, while one of the PAC1cc structures shows a “closed” conformation (Figure 5.6E).  While the conformation adopted in different crystals is likely a result of the different crystal environments (e.g. in the “open” conformation, the loop interacts with the neighbouring molecule in the crystal lattice), the flexibility of this loop cannot be ignored – it may shift its position depending on ligand binding.  Tresaugues et al. [607] suggested that the driving force for this conformation change would likely be caused by the interaction of 3-P of the substrate and Arg682 in SHIP2 (Lys668 in SHIP1).  The additional interactions form after closing of the P4IM could explain why SHIP1 and SHIP2 strongly prefer substrates that contain a phosphate at the 3'-position on the inositol ring even thought both only hydrolyze the 5'-phosphate [615,617].  147  Figure 5.6 Superposition of mouse SHIP1, human INPP5B and human SHIP2 phosphatase domains.   (A) Ribbon diagrams of mouse SHIP1 (green), human INPP5B (PDB:4CML, cyan) and human SHIP2 (PDB:3NR8, brown).  PI(3,4)P2 from the INPP5B structure is depicted as stick representation in yellow, and Mg2+ ion is shown as a grey sphere.  (B) Residues interacting with 1-phosphate and inositol ring of PI(3,4)P2.  (C) Residues interacting with 5-phosphate of PI(3,4)P2.  (D) Comparison of the P4IM loops.  (E) Comparison of the P4IM loops in wild type PAC2 (Green), PAC1cc (Space group C121, Purple) and PAC1cc (Space group P 21 21 21, Magenta).    N523 N379 N540 K524 K380 K541 S547 A403 S564 N523 N379 N540 K524 K380 K541 H544 H400 H561 D590 D447 D607 N592 N449 N609 H704 H549 H718 K668 K516 R682 N670 R518 N684 A B C D E Phosphatase domain C2 domain (SHIP1 only) P4IM Active site  148  INPP5B contains two loops that provide interaction to the aliphatic regions of PI(3,4)P2.  These loops are called lipid chain 1 recognition motif (LC1R-motif) and lipid chain 2 recognition motif (LC2R-motif), and they serve as the membrane-interacting regions for the phosphatase to penetrate into the membrane.  SHIP1 and SHIP2 lack the first motif, and they do not have the equivalent lipid-interacting residues in the second motif as shown by sequence alignment (Figure 5.5).  Since the phosphatase domain would need to interact with the membrane, where the substrate locates, for catalysis to occur, we have examined closely at the area to determine potential lipid-interacting residues (Figure 5.7).  The LC2R loop is not modeled in the SHIP2 structure due to its apparent flexibility.  We found this loop to be flexible in SHIP1 as we were only able to model this loop in the wild type PAC2 structure, but not in PAC1cc structures.  Overlaying the PI(3,4)P2-bound INPP5B structure to our structure, we saw that the two LC2R loops do not correlate well in position.  The LC2R motif in SHIP1 shifts so it also occupies where the LC1R motif would be, with Ile517 and Leu521 as the potential lipid-interacting residues.    149  Figure 5.7 Position of LC1R and LC2R in mouse SHIP1 or INPP5B phosphatase domains.   Structures of SHIP1 (green) and INPP5B (cyan) phosphatase domains are superposed.  LC1R and LC2R are indicated with arrows.  PI(3,4)P2 is depicted in orange and Mg2+ ion is represented as a grey sphere.  5.2.1.3 C2 domain The C2 domain forms a β-sandwich core that contains two sheets of 4 antiparallel β-strands, with 1 α-helix at the peripheral, and it interacts with the phosphatase domain on the surface away from the active site.  The mutations in PAC1cc locate after β2-strand, and appear to stabilize the structure around that region (Figure 5.4).  The wild type PAC2 structure is actually missing (part of) β3-strand due to the disordered nature of this region.  Structure-based sequence alignment (VAST-MMDB) [618] using wild type PAC2 as input found that the SHIP1 C2 domain is most similar to the C2B domain of the extended synaptotagmin 2 (E-Syt2) (PDB: 4NPJ) [619] with a VAST score of 13.6 (Figure 5.8).  Similar to E-Syt2 C2B, SHIP1 C2 adopts a Type II topology (as described LC1R LC2R LC2R P4IM  150 in Rizo et al. [620]), with both N- and C-termini located at the bottom of the domain, opposite to the (potential) calcium-binding regions (CBRs).  There are four loops at the top (the loop between β3and β4 is not modeled) and three loops at the bottom of the domain, one of which forms a short α-helix.     Figure 5.8 Structures of C2 domains.   The structures of SHIP1 C2, E-Syt2 C2B (PDB: 4NPJ), PKCα C2 (PDB: 3GPE) and rabphilin C2A (PDB: 4NS0) are shown in cartoon representation.  Coils are coloured in green, α-helices are coloured in red and β-strands are coloured in yellow.    C2 domains were discovered as a calcium-binding domain, and numerous structural studies reported five conserved Asp residues critical for Ca2+ binding.  We found that SHIP1 C2 lacks all but one of these Asp residues (Asp813 in CBR3 loop), and likely does not bind Ca2+ ions.  However, our in vitro phosphatase results showed that Ca2+ ions reduced the basal enzymatic activity of SHIP1 and PAC1.  It is possible that the Ca2+ ions may be interacting with the protein in the phosphatase domain.  Unfortunately, we were unable to produce a co-crystal structure of PAC1/2 and Ca2+ ions.   Another feature of C2 domains is the ability to interact with phospholipids (such as phosphoserine) at near the CBRs by a combination of hydrophobic interaction and Rabphilin C2A PKCα C2 E-Syt2 C2B SHIP1 C2  151 electrostatic interaction (review in [621]).  Ca2+ binding changes the electrostatic potential needed for the protein to associate with the negatively charged phosphate head group of phospholipid.  At the same time, phospholipid binding also enhances the affinities of Ca2+ ions, because its phosphate head groups fill the coordination shell of the ions.  Some C2 domains show phospholipid binding in a Ca2+-independent manner [622-625]; one example is the C2 domain of PTEN.  PTEN C2 only contains one Asp residues in the CBR loops and does not bind Ca2+; however, it was able to bind to vesicles consisting of anionic phospholipid [626].  The authors used full length PTEN, which has a much higher affinity to phospholipid vesicles than isolated C2 domain, to compare protein binding to phosphoserine and phosphoglycerol, and found no significant difference indicating that the binding was likely due to non-specific electrostatic interactions.  The positively charged CBR3 loop (+5 net charge) may play a role.  By contrast, SHIP1 C2 does not contain a loop enriched with basic residues that could serve as interacting partners for anionic phospholipids.  This observation does not rule out the possibility that SHIP1 C2 may bind to neutral phospholipids such as phosphatidylchloline in the case of cPLA2.   C2 domains are also capable of associating with phosphoinositides involved in signal transduction and membrane traffic [621,627,628].  The X-ray structure of PKCα C2 in complex with Ca2+, phosphoserine and PI(4,5)P2 showed that PI(4,5)P2 bound at the concave surface formed by β3and β4 strands (PDB: 3GPE) [629].  This cluster was named lysine-rich cluster, polybasic cluster, or β -groove.  The authors identified six key residues involved in PI(4,5)P2 binding [629].  In a review, Corbalan-Garcia and Gomez-Fernandez [630] compared sequences of different C2 domains and proposed a consensus  152 PI(4,5)P2-binding sequence (Y-X-K-Xn-K-X-K-Xn-W-Y/L/C-Xn-N).  A few of those C2 domains used in their report also showed up in our VAST search, and using their sequence alignment as a guide, we found that the corresponding PIP2-binding sequence in SHIP1 C2 does not follow the consensus sequence (Figure 5.9A).  Also, electrostatic potential calculation shows that SHIP1 C2 has a relatively neutral surface, as compared to the C2 domain PKCα and the C2A domain of rabphilin 3A (Figure 5.9C).  This observation shows that it is unlikely for PIP2 to binds to SHIP1 C2 at the nonbasic “β-groove”.  It is surprising to us, because we have shown that the C2 domain is important for SHIP1’s allosteric activation by PI(3,4)P2 and that it directly interacts with PI(3,4)P2 [430].  Where PI(3,4)P2 exactly binds SHIP1 C2 domain remains to be determined.    153   Figure 5.9 SHIP1 C2 domain does not contain the polybasic cluster as other C2 domains.   (A) Comparison of PI(4,5)P2 binding sequences and SHIP1 C2 sequence.  (B) The surface of wild type PAC2 structure is coloured according to Coulombic electrostatic potential as calculated by A Consensus       333 Y X K …………. K X K …………. W (Y/L/C) ……. N SHIP1              752 Y L E …….……. F V K …………. K ……………… D 815   B PKCα C2 PI(4,5)P2 Rabphilin 3A C2A PI(4,5)P2 SHIP1 C2 -10 kcal/(mol*e) 10 kcal/(mol*e) C Artificially pulled apart  180° Phosphatase  C2 P4IM  154 Chimera.  The two domains are artificially pulled apart in the bottom panel.  (C) Electrostatic potential of different C2 domains.  PKCα C2 structure (PBD:3GPE), rabphilin 3A C2A (PBD:4NS0) and SHIP1 C2, as coloured by Coulombic electrostatic potential calculation by Chimera.  Both PKCa C2 and rabphilin 3A C2A are in complex with PI(4,5)P2, as showed as stick representation in the polybasic cluster.     5.2.1.4 Phosphatase-C2 interface Interface analysis using the PISA server [631] suggests that about 25 residues from each domain participate in domain-domain interaction, burying a surface area of about 900Å2 (Figure 5.10).  The interface has a hydrophobic core formed between the flexible loops of phosphatase domain (mainly α4-β8 and β9-β10 loops) and β-strands of the C2 domains (β4 and β5).  In particular, the α4-β8 loop protrudes out of the phosphates domain and fits quite well into a shallow cavity on the C2 domain (Figure 5.10B).  In addition, the carboxyl oxygen of Pro684 and Leu685 forms hydrogen bond interactions with the side chain of His804 and Arg826 respectively (Figure 5.10C).    155  Figure 5.10 The interface between phosphatase domain and C2 domain.   (A) The two domains in wild type PAC2 structure is artificially pulled apart, with phosphatase domain in green and the C2 domain in purple.  Interfacing surfaces are colored in yellow or magenta.  (B) The residues involved in the interface.  Phosphatase domain and C2 domain are shown in green and purple respectively.  Interacting residues as predicted by PISA analysis are represented as sticks.  The red box shows where the hydrogen bond interactions occur.  (C) Hydrogen bond interactions at the interface.     Besides PI(3,4)P2, SHIP1 C2 also contains the binding site for the synthetic SHIP1 activator, AQX-MN100 [430].  Furthermore, AQX-MN100 was found to bind to the same site as PI(3,4)P2, as the addition of AQX-MN100 interfered with C2’s ability to bind to PI(3,4)P2 in a protein lipid overlay (PLO) assay [430].  Using the first PAC1cc structure as a docking template, we have predicted two potential AQX-MN100 binding B C Pro684 Leu685 His804 Arg826  A  180°  156 sites in the structure (Figure 5.11A-D), both of which are located at the phosphatase-C2 interface; they are designated as Pocket 1 and Pocket 2 [632].  A number of single mutations have been made in these pockets, and in vitro phosphatase assays were performed to assess their ability to be activated by AQX-MN100 (Figure 5.11E).  Purification of all mutants as an MBP-fusion, except H635A, gave similar yield as wild type protein, indicating that the mutations mostly did not affect the integrity of the protein.  These proteins were then tested for their ability to be activated by AQX-MN100 in in vitro phosphatase assay as MBP-fusion proteins.  A titration of enzyme was first performed to determine the amount of enzymes needed to give half-max activity, as described in Materials and Methods.  Figure 5.11F shows an immunoblot of the amount of each mutants used in the assays.  As shown in Figure 5.11E, none of the mutants lost their response to AQX-MN100.  Mutant Y683A may be slightly defective in response to AQX-MN100, compared to other mutants, but it was still significantly activated by the ligand.  Two possibilities could explain this observation: AQX-MN100 does not bind either of the two sites, or the single mutations are not enough to abolish binding of AQX-MN100.  Further experiments with PAC1 mutants containing more than one mutation will be needed to determine which is true.  157   Figure 5.11 Potential AQX-MN100 binding sites in PAC.   (A-B) The locations of AQX-MN100 binding sites are predicted by docking.  (C-D) Close-up of Pocket 1 and Pocket 2.  Several interacting residues are depicted in stick.  Residues indicated with an asterisk are selected for alanine scanning mutagenesis analysis.  (E) Recombinant MBP-tagged PAC1 mutants were incubated with 0.2 mM AQX-MN100 or ethanol (solvent control) for 10 minutes at 23°C before incubating with 50 μM IP4 for 10 minutes at 37°C.  The reaction was L573A Y683A S758A H635A0.000.050.100.150.20A650 minus backgrounduntreatedEtOHAQX-MN100Tyr683* Ser758* Leu573* His635* Pro839 Lys681  180° A B   C D P4IM E L573A Y683A S758A H635A0.00.51.01.52.02.5FOLD CHANGE over 1% EtOHuntreatedEtOHAQX-MN100*L573A Y683A S758A H635A F  158 stopped by the addition of Malachite Green reagent.  Data are presented as background-corrected A650 values (left) or fold change compared to the ethanol treatment (right).  Statistical significance of AQX-MN100 response in different mutants was calculated by a two-way ANOVA test with a 95% confidence (*p < 0.05).  Results were observed in one independent experiment.  (F) The amounts of mutant proteins used in the in vitro phosphatase assay were detected by immunoblotting with anti-His antibody.     5.2.3 Binding of SHIP1 activators to SHIP1 To characterize the binding of lipid to SHIP1, we employed the protein lipid overlay (PLO) assay [633].  Recombinant His6-SHIP1 was expressed in HEK293T cells and purified before incubating with PVDF membranes that had been spotted with either PI(3,4)P2-diC16 or PI(3,4,5)P3-diC16.  Bound protein was then detected by anti-His antibody.  As shown in Figure 5.12A, His6-SHIP1 was able to bind to its substrate, PI(3,4,5)P3.  Binding to its product PI(3,4)P2 is also detected, consistent with previous observation that PI(3,4)P2 acts as an allosteric activator (Figure 5.2) [430].  About five times more PI(3,4)P2 amounts than PI(3,4,5)P3 were needed to generate similar protein binding intensity, suggesting that SHIP1 binds to PI(3,4,5)P3 at a higher affinity than to PI(3,4)P2.  Recombinant His6-C2 was similarly tested in PLO assay, and we reproduced previous results showing that C2 indeed bound to PI(3,4)P2 (Figure 5.12B) [430].  C2 also bound PI(3,4,5)P3 seemingly with a higher affinity.  The presence of Ca2+ ions increased both PI(3,4)P2 and PI(3,4,5)P3 binding.  PLO assays using PAC were not performed, because His6-PAC did not express in HEK293T cells, and it was mostly insoluble when expressed in bacteria making it unfeasible to produce enough protein in bacteria.  159  Figure 5.12 SHIP1 binds to both PI(3,4)P2 and PI(3,4,5)P3 through its C2 domain.   (A) Recombinant His6-SHIP1 was incubated with PVDF membrane spotted with different amounts of PI(3,4)P2-diC16 and PI(3,4,5)P3-diC16 for 5 hours at room temperature.  Bound protein was detected by anti-His antibody.  The membranes were 0 100 200 300050000100000150000200000250000pmol PI(3,4)P2-diC16IntensityPI(3,4)P2-diC16His6-SHIP1BufferA PI(3,4,5)P3-diC16  Buffer His6-SHIP1    pmol     0    12.5    25     50  Buffer  His6-SHIP1     pmol       0     62.5   125    250 PI(3,4)P2-diC16 0 20 40 60050000100000150000200000250000PI(3,4,5)P3-diC16pmol PI(3,4,5)P3-diC16IntensityHis6-SHIP1Buffer Buffer  His6-C2 alone  His6-C2 + CaCl2  Buffer  His6-C2 alone His6-C2 + CaCl2    pmol     0    62.5   125  250  500 PI(3,4)P2-diC16 PI(3,4,5)P3-diC16    pmol      0    12.5    25    50   100 B 0 50 1000500000100000015000002000000250000030000003500000pmol PI(3,4,5)P3-diC16IntensityHis6-C2 aloneHis6-C2 + CaCl2Buffer**0 200 400 6000500000100000015000002000000250000030000003500000pmol PI(3,4)P2-diC16IntensityHis6-C2 aloneHis6-C2 + CaCl2Buffer ******** 160 scanned with the Odyssey instrument, and the intensities of the spots were quantified using the ImageStudio software.  Similar results were observed in at least two independent experiments.  (B) Recombinant His6-C2 was tested in PLO assay in identical condition as (A) except the addition of 2 mM CaCl2 in one of the conditions.  Statistical significance between His6-C2 +/- CaCl2 at individual amount of lipid was calculated by a two-way ANOVA test with a 95% confidence (** p < 0.01, **** p < 0.0001).  Similar results were observed in at least two independent experiments.   We also tested the binding of pelorol-based small molecule SHIP1 activators to SHIP1.  However, AQX-MN100 is quite insoluble in aqueous solution and that hinders our ability to measure its binding to SHIP1.  We thus used the derivative AQX-151, which is more water-soluble than AQX-MN100, in saturation transfer difference nuclear magnetic resonance (STD-NMR) experiments.  The methodology detects protein-ligand interaction by measuring the transfer of magnetization from the protein to the ligand.  Only ligands that bind to the protein will give an STD signal.  We found that AQX-151 bound to isolated C2 domain, as well as PAC1 (Figure 5.13A-B).  The transfer was quite strong in the aromatic signals, with weaker transfer in the methyl groups.  PI(3,4)P2 also associated with the C2 domain but with weaker signal; all the transfer went into the acryl chains from the terminal methyl groups and along the chain (Figure 5.13C).  Unfortunately, the experimental set-up does not allow us to detect binding between the head group and the protein.  However, given that the STD signal for PI(3,4)P2 was quite weak, it is possible that the major interaction may be mediated by the phosphates in the head group.  Controls including PI(3,4,5)P3 and other PIP2 (that do not activate SHIP1) will be needed to determine if the specific head group dictates the interaction.   161  Figure 5.13 Binding of AQX-151 and PI(3,4)P2 to C2 domain by STD-NMR.   STD-NMR spectra of (A) AQX-151 and isolated C2 domain, (B) AQX-151 and PAC1 in buffer supplemented with 6 mM MgSO, and (C) PI(3,4)P2-diC8 and isolated C2 domain.  A B C Protein: C2 Ligand: AQX-151 Protein: PAC1 Ligand: AQX-151 Protein: C2 Ligand: PI(3,4)P2-diC8  162 To obtain quantitative measurement of the protein-ligand interaction, isothermal titration calorimetry (ITC) was used.  Both AQX-MN100 and AQX-151 require ethanol or DMSO to dissolve, and thus become unsuitable in ITC experiments.  We hence obtained AQX-1125, a completely water-soluble derivative of AQX-MN100.  High concentration of AQX-1125 was titrated into either buffer or PAC1, and the measured heat changes were then used to determine the thermodynamic parameters of the protein-ligand interaction.  ITC analysis showed no binding of AQX-1125 to PAC1 (Figure 5.14); the heat changes generated were identical to AQX-1125 titration into buffer.  Similarly, no binding was observed when the natural ligand PI(3,4)P2-diC8 was titrated into PAC1.  This result was unexpected, since PLO assays and STD-NMR clearly showed ligand binding to the protein (either to C2 alone or PAC1).  A possibility is that the ligand binding was too weak to be detected by ITC.  PIP2 binding to other proteins have been investigated by ITC, and the Kd values are of the low micromolar range [623,634,635].  These studies all used PIP2-containing vesicles (with phosphatidylchloline) as the interacting partners, while we purposely used soluble, short chained PI(3,4)P2 in our ITC experiment.  There are caveats in using the different forms of phosphoinositides in in vitro binding assays, as discussed by Narayan and Lemmon, and they pointed out that vesicles provide a more representative system of the cellular situation and less prone to artefacts [636].  Also, it has been observed that membrane curvature, in additional to membrane charge, could have an effect in protein membrane, as shown with acyl-CoA binding protein (ACBP) that preferentially interacted with small unilameter vesicles (i.e. highly curved) rather than large unilameter vesicles (i.e. less as curved) [637].  Perhaps the formation of vesicles provide additional (and necessary)  163 features for protein interaction, and using soluble PI(3,4)P2 in our study may have contributed to our inability to detect PI(3,4)P2 binding to the protein.    Figure 5.14 No binding of AQX-1125 or PI(3,4)P2-diC8 to PAC1 is detected by ITC.   (A) 1 mM of AQX-1125 or (B) 1 mM of PI(3,4)P2-diC8 was titrated into ITC buffer or 0.1 mM PAC1 over the course of 20 injections of 2 μl at 180-second interval at room temperature.  Shown are plots of heat produced of each titration. AQX-1125 into PAC1 WT AQX-1125 into buffer PI(3,4)P2-diC8 into PAC1 WT PI(3,4)P2-diC8  into buffer A B  164  5.3 Discussion Phosphoinositides are important in many cellular signalling events.  The reversible phosphorylation of the inositol ring is tightly controlled by the activity of inositol kinases and phosphatases.  While a large number of drugs have been developed to target inositol kinases such as PI3K, recent studies also focus on the search for drugs that modulate the activity of inositol phosphatases.  One example is the development of SHIP2 inhibitors in treating Type 2 diabetes, characterized by insulin resistance and glucose intolerance.  SHIP2 is a negative regulator of insulin signalling, which activates the PI3K pathways.  Treating diabetic mice with a SHIP2-specific inhibitor (AS1949490) restored insulin signalling and caused significant improvement in glucose tolerance [638].  Thus, drugs targeting inositol phosphatases can be used as an alternative to modulate the PI3K pathway.   SHIP1 is a particularly attractive target in treating hematopoietic malignance, and inflammatory and autoimmune diseases due to its restricted expression in hematopoietic cells.  Previous work from our laboratory has found that SHIP1 can be allosterically regulated by its product PI(3,4)P2, and also identified AQX-MN100 as a specific SHIP1 allosteric activator [430].  Domain deletion analysis shows that the PH-R and the C2 domains are required for the allosteric activation.  While PI(3,4)P2 can bind to both the PH-R and C2 domains, AQX-MN100 only interacts with the C2 domain [429]. Here, we performed more in-depth studies in the regulation of SHIP1 by its activators.  We showed by in vitro phosphatase assay that SHIP1 fragment containing only the phosphatase and C2 domains (aka PAC), but not the PH-R domain, corresponds to the minimal enzyme (Figure 5.1).  PAC was activated by PI(3,4)P2 or AQX-MN100  165 equally well compared to full length SHIP1, which tends to discount a role of PH-R domain in SHIP1 allosteric activation.  This observation seemed surprising at first, because SHIP1 enzyme lacking PH-R domain (SHIP1 ΔPH-R) showed inability to be activated by both activators, even though SHIP1 ΔPH-R retains enzymatic activity.  However, deleting an entire domain may potentially alter the folding of the protein outside of the phosphatase domain.  In fact, when comparing the enzyme kinetic parameters of PAC to PPAC, which contains the PH-R domain, PAC showed a lower Vmax value but similar Km value (Figure 5.1).  The lack of PH-R domain showed a similar effect on enzyme activity as a noncompetitive inhibitor would, suggesting that the conformation of the enzyme may have changed in the absence of PH-R domain.  Worthy of note is that PH-R domain has a high affinity to PI(3,4,5)P3 (and a lesser affinity to PI(3,4)P2), and recruits SHIP1 to the plasma membrane [429].  Point mutations in the PH-R domain (K370A/K397A) reduced both PI(3,4,5)P3 and PI(3,4)P2 binding, but full length SHIP1 containing these mutations has indistinguishable allosteric activation profile as wild type SHIP1 [429].  It is consistent with present data showing only the C2 domain is needed for allosteric activation.  Yet, even though PI(3,4)P2 was shown to bind to C2 domain by PLO assay (Figure 5.12) and STD-NMR (Figure 5.14), we were unable to measure the affinity of PI(3,4)P2 to PAC by ITC or obtain a co-crystal structure of PI(3,4)P2-PAC, suggesting that PI(3,4)P2 affinity to PAC is very weak, with Kd value likely above high micromolar range.  That leads to the hypothesis that PH-R domain may facilitate PI(3,4)P2 binding to the enzyme even though it does not participate in allosteric regulation.    166 Structures of SHIP1 phosphatase and C2 domains reveal a few differences from other 5'-phosphatases at the enzyme active site.  The first difference is a longer P4IM loop in SHIP1 (and SHIP2) that may explain the strong preference of 3-P in the enzyme substrate.  Arg668 and Asn670, especially Arg668, could potentially be the driving force for this preference.  The second difference lies in the region that binds to the aliphatic region of the substrate, LC1R and LC2R loops.  SHIP1 lacks the LC1R loop that contains multiple hydrophobic residues necessary for substrate interaction.  SHIP1 maintains a LC2R that could interact with the lipid.  Additional tryptophan residues (Trp489 and Trp600) may also facilitate membrane interaction.  It is also likely that SHIP1 phosphatase domain does not interact with the membrane as extensively as the other 5-phosphatases.  SHIP1 is a multi-domain protein, and other domains in SHIP1 might have a bigger role in membrane binding.  For example, the SH2 domain in the N-terminal end or the NPXY motifs at the C-terminal end mediate membrane recruitment indirectly via transmembrane receptor proteins, or adaptor proteins such as Shc and Dok [426].  The PH-R domain directly interacts with the PI(3,4,5)P3 and is necessary for SHIP1 recruitment to the phagocytic cup [429].   PTEN is another phosphatase that contains a C2 domain, adjacent to its phosphatase domain, that is necessary for its membrane interaction and its biological functions [639].  The PTEN C2 domain resides right next to the active site, and contains two basic regions, one at the CBR3 and one at the α-helix next to the CBRs, that target PTEN to the membrane and position the active site to its substrate within the membrane.  However, our structure showed that the SHIP1 C2 domain lacks both of these basic regions and it also interacts with the phosphatase domain away from the active site.   167 Since the SHIP1 C2 domain has a relatively neutral surface, it likely does not interact with the positively charged head group of PIPs, but we cannot exclude the possibility that the C2 domain may interact with lipids via hydrophobic interaction instead of electrostatic interactions.  Whether the SHIP1 C2 domain could serve as the membrane interacting domain of SHIP1 inside the cells remains to be elucidated.  Regardless, the C2 domain is certainly important in the catalytic activity of the enzyme (in addition to its role in binding allosteric activators) by facilitating lipid binding, providing structural integrity, or both.  The isolated phosphatase domain has surprisingly low activity (data not shown), while the PAC construct is fully functional, compared to the full-length protein (Figure 5.1).   Our structure showed that the SHIP1 C2 domain, unlike other C2 domains, lacks the binding site for Ca2+, but PLO assays showed that Ca2+ enhances binding of PI(3,4)P2 to the C2 domain.  However, we need to interpret these results carefully.  The isolated C2 domain, although soluble, exists as a higher order oligomer (likely a dimer) in solution according to its size exclusion profile.  The lack of other domains could potentially expose hidden hydrophobic surfaces that is now accessible to interact with each other, or with other molecules such as lipids.  Electrostatic potential representation of the C2 domain shows that it is highly hydrophobic (Figure 5.9).  Moreover, the addition of Ca2+ in the assay increases the ionic strength of the PLO buffer, potentially driving the interaction between hydrophobic surface of the C2 domain and the hydrophobic lipid chain of PI(3,4)P2.  Nevertheless, Ca2+ appears to associate with SHIP1/PAC and inhibit its enzymatic activity (Figure 5.2).  This inhibitory effect of Ca2+ is also seen in SPsynaptojanin, an archetypal inositol 5'-phosphatase [615].  In this case, Ca2+ acts as a  168 competitive inhibitor of Mg2+ that is required for 5'-phosphatase activity.  The crystal structure of SPsynanptojanin shows that a Ca2+ ion actually occupies the active site [640].  Our data also support the association of Ca2+ ion(s) to the SHIP1 phosphatase domain.  The physiological basal concentration of Ca2+ is very low compared to the level used in the in vitro phosphatase assay (<100 nM in the cytoplasm of resting cells vs 2 mM).  A titration of CaCl2 showed that SHIP1 enzyme activity was not affected at concentration lower than 2 mM CaCl2 (data not shown), showing that the low resting concentration of Ca2+ inside the cells likely would have no effect on SHIP1 activity.  Upon specific extracellular signals, intracellular Ca2+ level may rise up to 0.5 to 1 mM [641], and some proteins such as PI3K require elevated Ca2+ for activity [642,643].  Whether SHIP1 is regulated similarly by Ca2+ level inside the cell remains to be determined.   In summary, we have described the structure of the SHIP1 phosphatase domain and C2 domain for the first time.  The SHIP1 C2 domain, although structurally similar to other C2 domains, contains unique features that may exert different functional roles from other C2 domains.  Being an allosterically activated enzyme with the C2 domain as the binding site of allosteric modulators, this structure of SHIP1 will certainly aid in the development of drugs (either activators or inhibitors) in treating different immune disorders.  For example, we have determined possible sites for AQX-MN100 binding by ligand-docking approach (Pocket 1: L573, Y683, S758, and Pocket 2: H635, K681, P839).  While we still need further experiments to fully determine the ligand-interacting residues and the binding mechanism, we are confident that it can be done.  A protein structure can be used in silico to screen for potential enzyme modulators [644,645].  Unfortunately, this kind of screening can only be performed once we have determined the  169 binding site of at least one ligand, either by structural analysis or site-directed mutagenesis approach.  Usually, the in silico identified modulators interact with the active site to prevent access of the substrate or interfere with catalysis [646].  By comparing structures of related proteins (e.g. SHIP2 structure in complex with its inhibitor [616]) and identifying the differences, specific drugs that only affect selected proteins can be designed.  However, functionally related enzymes usually have similar active sites, and thus the specificity of these active site modulators can be compromised.  Thus, once we determine the allosteric regulator binding site in SHIP1/PAC, we will be able to screen for other potential allosteric regulators [647].      170         Chapter 6: Conclusions    171 6.1. Conclusions This thesis investigated the role of STAT3 and SHIP1 in IL-10 regulation of activated macrophages.  The importance of STAT3, SHIP1 and IL-10 in immune function has been shown biologically with knockout models, and through observed deficiencies in these proteins in human inflammatory diseases [382-384,403,502,648,649].  Thus, understanding how the mechanisms by which STAT3 and SHIP1 mediate IL-10 action will be beneficial in developing therapeutics to treat inflammatory diseases.   Since the discovery of IL-10 about two decades ago, a large number of studies have been published that support a model in which STAT3 is the dominant downstream molecule in IL-10 signalling and that STAT3 inhibits inflammation by inducing the expression of specific gene products.  Some investigators even believed that STAT3 was the sole mediator of IL-10 signalling [374].  However, work from previous members from our laboratory has shown that while STAT3 is essential for IL-10’s inhibition of immune cell activation, the 5'- phosphatase SHIP1 is also required, and that SHIP1 can regulate gene expression through transcriptional and post-transcriptional controls [56,376].  Our work favours a revised model in which both SHIP1 and STAT3 mediates the anti-inflammatory response of IL-10.   The findings presented in this thesis expand our understanding of IL-10 signalling and regulation.  In Chapter 3, we examined IL-10 regulation of a particular miRNA, miR-155, in activated macrophages.  miRNAs are indispensable in the development and function of the immune system as indicated by the fact that knocking out Dicer in mice causes embryonic lethality [258].  A growing number of miRNAs have been implicated  172 in different human diseases.  We chose to focus on miR-155 due to its high expression in immune cells and its multiple roles in immune cell function.  Kinetics studies show that LPS treatment induces pri-miR-155 transcription followed by maturation into functional miR-155, and that IL-10 inhibited pri-miR-155 expression at 1 hour and mature miR-155 expression at 4 hours.  Interestingly, pri-miR-155 is transcribed constitutively in resting cells, but its expression level is greatly enhanced in the presence of LPS.  Luciferase reporter assays show that both LPS and IL-10 does not affect pri-miR-155 transcription during the course of our experiments.  These results prompted us to speculate that pri-miR-155 is being made at all times with its level kept low through some kind of degradation mechanism, but in the presence of an immune stimulus such as LPS, the degradation mechanism is removed and maturation into miR-155 begins.  However, IL-10 switches on the degradation mechanism again to remove pri-miR-155, as well as interferes with the maturation process to prevent the generation of mature miR-155.  We also found that the regulatory step exists between pre-miR-155 and mature miR-155.  These observations open up a few questions that warrant further investigation.  What factors are involved in maintaining the resting state of pri-miR-155 level and how do they function? Which of these factors do LPS and IL-10 regulate to convert pre-miR-155 to mature miR-155? To identify the factors that regulate pri-/pre-miR-155 RNA stability and the maturation step, RNA pulldown using pre-miR-155 oligo in combination with mass spectrometry analysis will reveal RNA binding proteins that bind to pre-miR-155.  By comparing the differential binding pattern in unstimulated, LPS stimulated, and LPS+IL-10 stimulated cells, the proteins that regulate miR-155 maturation can be  173 identified.  Validation experiments will include overexpression and knockdown of the candidate proteins, and measuring miR-155 level upon LPS and LPS+IL-10 treatment.   We also found that miR-155 expression is regulated by both SHIP1 and STAT3.  Their contributions appear additive, but we unexpectedly found that the SHIP1 activator, AQX-MN100 is by itself sufficient to mimic the inhibitory effect of IL10 on miR-155 expression.  That may seem surprising at first, because STAT3 is not activated (defined by the absence of phosphorylation at Y705) by treatment of cells with AQX-MN100.  It is possible that activated SHIP1 (either by IL-10 or AQX-MN100) may modulate STAT3 activity independent of STAT3 phosphorylation, or that unphosphorylated STAT3 is still active in gene regulation (see discussion below).  Lastly, miR-155 is only one of the many miRNAs involved in macrophage activation.  Expanding our research to other miRNAs, for example through microarray analysis or other high-throughput approaches, will complement our current understanding of IL-10 regulation of miRNAs.  Having observed SHIP1 and STAT3 cooperativity in mediating IL-10 suppression of TNFα [376] and miR-155 (Chapter 3) [375], in Chapter 4, we investigated the role of SHIP1 and STAT3 on IL-10 regulation in gene expression globally.  Using microarray analysis, we compared the gene expression profiles from either SHIP1 WT or SHIP1 KO macrophages stimulated with LPS or LPS+IL-10, and then identified a subset of genes that were regulated by IL-10 in a SHIP1-dependent manner.  Both upregulated and downregulated genes were observed.  Preliminary real time PCR experiments of selected genes show that many of the SHIP1-regulated genes are also regulated by STAT3, but we also identified a few genes that only required SHIP1 or STAT3 to be regulated by IL-10.    174 Thus, future experiments will include validating more candidate genes identified in our microarray studies.  Besides determining mRNA levels of these genes from WT, SHIP1 KO and STAT3 KO macrophages that are stimulated by LPS +/- IL-10, it is also important to determine protein levels through immunoblot analyses.  A time-course experiment will provide evidence on the kinetics of the regulation.  Once validation is completed, the next question is whether the regulation of the validated genes is at the transcriptional level or post-transcriptional level.  These can be examined via the use of luciferase reporters harbouring either the promoter region or the 3'-UTR.  Also, we previously show that SHIP1 mediated IL-10 inhibition of TNFα translation without affecting its transcription [56].  SHIP1 may regulate the newly validated genes through similar mechanism, and that can be examined by determining the level of actively translated mRNA in SHIP1 WT and SHIP1 KO cells after IL-10 treatment.  Similar experiments should be performed in STAT3 WT and STAT3 KO to elucidate the role of STAT3 in the regulation of these genes.  STAT3 is a well-established transcription factor, and activates gene expression at the transcription level.  However, a non-transcriptional role has been described for STAT3 in different cancer cells, including regulating DNA methyltransferase 1 (DNMT1) binding to gene promoters to induce promoter methylation, which causes repression of gene expression [650,651].  This activity of STAT3 requires acetylation at Lys685 but not phosphorylation [650,651].  Whether IL-10 induces STAT3 acetylation, and whether this acetylation is important for IL-10 function will require further investigation. The results in our studies thus far support a model in which SHIP1 and STAT3 work together to mediate IL-10 function, and we have examined the possibility that  175 SHIP1 and STAT3 form a signalling complex.  While we were not able to observe physical interaction between SHIP1 and STAT3, we cannot exclude that they may interact through a third protein.  In addition, the SHIP1 activator, AQX-MN100 has been shown to inhibit TNFα [376] and miR-155 (Chapter 3) [375] even in the absence of STAT3 activation (STAT3 phosphorylated at Y705).  Previous reports have shown that unphosphorylated STAT3 could also regulate gene expression upon cytokine stimulation [652,653].  These unphosphorylated STAT3 molecules can form dimers or remain as monomer to activate gene expression [654], or interact with the NFκB p65 homodimer and interfere with gene expression [655].  It is possible that SHIP1 works with unphosphorylated STAT3 to modulate gene expression.  In support of this idea, we found that AQX-MN100 was able to cause nuclear translocation of STAT3 within 20 minutes (data not shown).  If this hypothesis is correct, a STAT3 Y705 mutant will still be able to regulate gene expression in the presence of AQX-MN100.  Furthermore, SHIP1 can act as an enzyme as well as a scaffold protein, and the use of an inactive enzyme in our cell-based assays will distinguish whether the activity of SHIP1 is due to its catalytic activity or the proteins that it recruits.   As described in Chapters 3 and 4, I have studied IL-10 regulation of miRNAs and mRNAs separately.  The next step would be to generate an IL-10 regulated miRNA-mRNA interaction network to gain insight into how miRNAs and mRNAs interact to mediate IL-10 function [656].  Analysis of SHIP1 WT and SHIP1 KO or STAT3 WT and STAT3 KO macrophages stimulated with LPS +/- IL-10 may reveal the specific IL-10 regulated miRNA-mRNA network mediated by SHIP1, STAT3, or SHIP1 and STAT3.  176 Given the importance of SHIP1 in IL-10 signalling, and that SHIP1 activation by small molecule agonist, AQX-MN100, can mimic IL-10 biological function both in vitro [56,375] and in vivo [376], we investigated the structural basis of the interaction between SHIP1 and its activators in Chapter 5.  We described a minimal enzyme composing only the phosphatase domain and the C2 domain, namely PAC.  The PAC enzyme has similar enzymatic properties to full length SHIP1, as assessed by in vitro phosphatase assay.  Our laboratory has previously identified the C2 domain as the binding site of SHIP1 agonists including AQX-MN100, and the SHIP1 product PI(3,4)P2 [430].  Besides its role in allosteric regulation, we found that C2 domain may also provide additional support to the phosphatase domain for catalysis, since an isolated phosphatase domain has very low enzymatic activity.  From the crystal structure of PAC, we found that the phosphatase domain and the C2 domain interact via a large interface, and that the C2 domain is located away from the active site.  The phosphatase domain resembles previously described structures of other inositol 5'-phosphatases, especially that of SHIP2.  Differences at the active site may explain the substrate preference of the different phosphatases, as well as requirement of the other domains in the proteins.  Comparison to other C2 domains reveal that SHIP1 C2 domain lacks the basic loops at the top of the domain for Ca2+ binding and phospholipid binding, as well as the polybasic groove made up by two β-strands at the side of the structure for PIP binding.  Surprisingly, while we observed PI(3,4)P2 binding to isolated C2 domains via PLO and STD-NMR, we did not find potential binding pockets in the structure of the C2 domain.  Similarly, STD-NMR studies showed that AQX-151, a derivative of AQX-MN100, is able to interact with C2 and PAC but we have not been able to obtain crystals of PAC containing either PIP2 or  177 AQX-151.  We have attempted to obtain a ligand-PAC crystal structure either by soaking apo-PAC crystals in ligand-containing solution or by screening for new crystallization conditions.  However, our efforts have been fruitless.  Perhaps the binding of ligand has drastically changed the conformation of PAC and thus none of the conditions screened was the right condition to crystallize the complex, or the ligand-bound protein is too flexible for crystallization.  It is also possible that the binding affinity of the ligands is too weak or too unstable for crystallization.  Alternatively, NMR can be employed.  Our initial STD-NMR experiments showed that PI(3,4)P2 and AQX-151 interacted with both the isolated C2 domain and the PAC protein.  Further experiments will validate this finding and also identify the interacting determinants on the ligands.  It may give us more insight on the type of interactions, and thus the type of amino acid residues, involved.  Using a site-directed mutagenesis approach, we can screen for the exact amino acid residues that interact with the lipid.  Other types of NMR (e.g. 13C-15N-NMR) may also be used for identification of ligand-interacting residues on the protein.  However, due to the size limitation on NMR, only the isolated C2 domain can be tested in this type of experiment.  Since these ligands are allosteric regulators, they likely regulate enzyme activity by inducing conformational changes.  In this case, small-angle x-ray scattering (SAXS) may be useful to detect these large structural changes by comparing the apo-PAC and the ligand-bound PAC.  While this method will not directly identify the ligand-interacting residues, it may reveal the approximate binding location of ligands on the protein.  Combining this information into our crystal structure may aid in pinpointing candidate residues important in ligand binding.  178 In summary, the data presented in this thesis has provided more insight into SHIP1’s participation in IL-10 signalling and functions.  This STAT3-independent pathway opens up a new field of research into treating inflammatory diseases, especially with the development of small molecule SHIP1 activators.  The crystal structure of PAC (composing the minimal allosteric regulated region of SHIP1) reveals the unique features of the two domains for the first time.  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Nat Methods 4, 1045-9.     214      Appendices    215 Table A.1: Primers used in qPCR Name  Primer Sequence 18S Fwd CAAGACGGACCAGAGCGAAA 18S Rev GGCGGGTCATGGGAATAAC Abcb1b Fwd CTGTTGGCGTATTTGGGATGT Abcb1b Rev CAGCATCAAGAGGGGAAGTAATG ambp Fwd CTGCGTCAACACTGCCAGATA ambp Rev CTTGTCCTTAATGCGGCTCAG Arid5a Fwd CCACTCACGGGTGCTAGTAG Arid5a Rev GGGGACTGTCTTGAATGTCCT Bcl2l11 Fwd CCCGGAGATACGGATTGCAC Bcl2l11 Rev GCCTCGCGGTAATCATTTGC bcl3 Fwd CCGGAGGCCCTTTACTACCA bcl3 Rev GGAGTAGGGGTGAGTAGGCAG ccl2 Fwd TTAAAAACCTGGATCGGAACCAA ccl2 Rev GCATTAGCTTCAGATTTACGGGT ccl3 Fwd TTCTCTGTACCATGACACTCTGC ccl3 Rev CGTGGAATCTTCCGGCTGTAG Ccnd2 Fwd GAGTGGGAACTGGTAGTGTTG Ccnd2 Rev CGCACAGAGCGATGAAGGT Cd274 Fwd GCTCCAAAGGACTTGTACGTG Cd274 Rev TGATCTGAAGGGCAGCATTTC Crlf2 Fwd GAGTTCCGTTATGGCACTGG Crlf2 Rev GCTGCCTAGCCTTAAACACCA cxcl1 Fwd CTGGGATTCACCTCAAGAACATC cxcl1 Rev CAGGGTCAAGGCAAGCCTC Cxcl2 Fwd CCAACCACCAGGCTACAGG Cxcl2 Rev GCGTCACACTCAAGCTCTG Dpm1 Fwd CCCACCTACAACGAACGGG Dpm1 Rev CAGCTTTTTCTCTCGTGGTCTTA egr1 Fwd TCGGCTCCTTTCCTCACTCA egr1 Rev CTCATAGGGTTGTTCGCTCGG Ewsr1 Fwd CCCACTGGTTATAGCACTCCA Ewsr1 Rev CAGTCTGAGCTGCGTAAGAGG Fzd7 Fwd AGACCCACCTTTCACTGCG Fzd7 Rev AAGTACATGAGGCCGTTAGCA Gpr35 Fwd ACAACCTGTAACAGCACCCTC Gpr35 Rev GCGATAGCAGAATACCCAGAGT icam1 Fwd GTGATGCTCAGGTATCCATCCA icam1 Rev CACAGTTCTCAAAGCACAGCG Id3 Fwd CTGTCGGAACGTAGCCTGG Id3 Rev GTGGTTCATGTCGTCCAAGAG il4ra Fwd TCTGCATCCCGTTGTTTTGC il4ra Rev GCACCTGTGCATCCTGAATG Impact Fwd GTGAAGAAATCGAAGCAATGGC Impact Rev GGTACTCACTTGGCAACATCA Irf8 Fwd CGGGGCTGATCTGGGAAAAT Irf8 Rev CACAGCGTAACCTCGTCTTC junB Fwd TCACGACGACTCTTACGCAG  216 Name  Primer Sequence junB Rev CCTTGAGACCCCGATAGGGA Lrp1 Fwd ACTATGGATGCCCCTAAAACTTG Lrp1 Rev GCAATCTCTTTCACCGTCACA map3k8 Fwd ATGGAGTACATGAGCACTGGA map3k8 Rev GGCTCTTCACTTGCATAAAGGTT marcksl1 Fwd CAATGGAGACTTAACCCCCAAG marcksl1 Rev GGCCACTCAATTTGAAAGGCT mGAPDH Fwd AATGTGTCCGTCGTGGATCT mGAPDH Rev GCTTCACCACCTTCTTGATGT nfil3 Fwd GAACTCTGCCTTAGCTGAGGT nfil3 Rev ATTCCCGTTTTCTCCGACACG nfkbia Fwd TGAAGGACGAGGAGTACGAGC nfkbia Rev TTCGTGGATGATTGCCAAGTG nfkbiz Fwd GCTCCGACTCCTCCGATTTC nfkbiz Rev GAGTTCTTCACGCGAACACC nucks1 Fwd TCTCGGCCTGTCAGAAATAGG nucks1 Rev GGGGAGATGACCGAATCTTCTTA peli1 Fwd GCCCCAGTAAAATATGGCGAA peli1 Rev CCCCATTTGCCTTAGGTCTTT pim1 Fwd CTGGAGTCGCAGTACCAGG pim1 Rev CAGTTCTCCCCAATCGGAAATC Prdx6 Fwd CGCCAGAGTTTGCCAAGAG Prdx6 Rev TCCGTGGGTGTTTCACCATTG Pre-mmu-155 Fwd GCTAATTGTGATAGGGGTTTTGG Pre-mmu-155 Rev GTTAATGCTAACAGGTAGGAGTC Pri-mmu-155 Fwd GACACAAGGCCTGTTACTAGCAC Pri-mmu-155 Rev GTCTGACATCTACGTTCATCCAGC Psmc5 Fwd AACTTGACCAGGGGGATCAAC Psmc5 Rev AGTCCTCCTGAGTGACGTGG Ptger4 Fwd ACCATTCCTAGATCGAACCGT Ptger4 Rev CACCACCCCGAAGATGAACAT Rgs2 Fwd GAGAAAATGAAGCGGACACTCT Rgs2 Rev GCAGCCAGCCCATATTTACTG Rnf216 Fwd GCCCATCCTCTAGGAGAGCTT Rnf216 Rev CCGTTTCTTTCACTAACAGTGGA Sbno2 Fwd CATCCAGCTACAGAACCGACT Sbno2 Rev GAACCCACGAACTGTTGGTTT sod2 Fwd CAGACCTGCCTTACGACTATGG sod2 Rev CTCGGTGGCGTTGAGATTGTT Tfam Fwd ATTCCGAAGTGTTTTTCCAGCA Tfam Rev TCTGAAAGTTTTGCATCTGGGT Tnf Fwd TCTTCTCATTCCTGCTTGTGG Tnf Rev GGTCTGGGCCATAGAACTGA tnfsf9 Fwd CGGCGCTCCTCAGAGATAC tnfsf9 Rev ATCCCGAACATTAACCGCAGG Tor1a Fwd GAGCCCATCAGCCTGAGTC Tor1a Rev AAACCAGACACGGCGTTTAGG   217 Table A.2: Site-directed mutagenesis primers Residue numbering of mouse SHIP1 sequence is based on the RefSeq entry with accession number of NP_034696.   Name Sequence Description SHIP1-Y190F SDM Fwd AAGCCATCCAGGATTTCCTGAGCACTCAGCTCC Potential tyrosine phosphorylation site SHIP1-Y190F SDM Rev AGCTGAGTGCTCAGGAAATCCTGGATGGCTTTC  SHIP770to773 SDM Fwd AGAGTCAGGAAGGAGCGAATGCAGCGGGAAGTGAAGGAGAG Surface Entropy Reduction Mutations SHIP770to773 SDM Rev CTCTCCTTCACTTCCCGCTGCATTCGCTCCTTCCTGACTCTTG SHIP1-L573A SDM Fwd CCTGGGAGACAAGAAGGCAAGCCCATTTAACATCAC Potential AQX-MN100 binding site SHIP1-L573A SDM Rev GTGATGTTAAATGGGCTTGCCTTCTTGTCTCCCAGG SHIP1-Y683A SDM Fwd AGTCCTCTGGAAGTCTGCACCGCTGGTGCATGTG Potential AQX-MN100 binding site SHIP1-Y683A SDM Rev CACATGCACCAGCGGTGCAGACTTCCAGAGGAC SHIP1-S758A SDM Fwd ACTTGGAGTTCCACTCAGCCTGCTTAGAGAGTTTTG Potential AQX-MN100 binding site SHIP1-S758A SDM Rev ACAAAACTCTCTAAGCAGGCTGAGTGGAACTCCAAG  SHIP1-H635A SDM Fwd ACCAGAAGGTCTTCCTGGCCTTTGAGGAGGAAGAG Potential AQX-MN100 binding site SHIP1-H635A SDM Rev CTCTTCCTCCTCAAAGGCCAGGAAGACCTTCTGG SHIP1-H580A SDM Fwd CCATTTAACATCACCGCCCGCTTCACCCACCTC Potential AQX-MN100 binding site SHIP1-H580A SDM Rev AGGTGGGTGAAGCGGGCGGTGATGTTAAATGG SHIP1-H704A Fwd CATCATGACGAGTGACGCCAGCCCTGTCTTTGCC Potential AQX-MN100 binding site SHIP1-H704A Rev GGCAAAGACAGGGCTGGCGTCACTCGTCATGATG SHIP1-D590A Fwd TCTTCTGGCTTGGGGCTCTCAACTACCGCGTG Potential AQX-MN100 binding site SHIP1-D590A Rev ACGCGGTAGTTGAGAGCCCCAAGCCAGAAGAG     218 Table A.3: Ligase-independent cloning primers Residue numbering of mouse SHIP1 sequence is based on the RefSeq entry with accession number of NP_034696.   Name Sequence Description SHIP 402 LIC Fwd TTACTTCCAATCCAATGCACCAGAGCCTGACATGATCACCATC Forward primer for both PAC1 and PAC2 SHIP857 LIC Rev TTATCCACTTCCAATGTTATTACTGCAGCTTAATCTCTCCCCTG Reverse primer for PAC2 SHIP861 LIC Rev TTATCCACTTCCAATGTTATTAGCCCTGGGAGGTCTGCAGC Reverse primer for PAC1    Figure A.1 The BIC promoter reporter is unresponsive to LPS and IL-10.   The BIC promoter reporter constructs were transfected into RAW264.7 cells using either XtremeGene HP transfection reagent or GeneJuice transfection reagent according to the manufacturer’s instructions.  Cells were then rested in medium containing 9% or 5% serum for 24-48 hours before stimulation for the indicated time.  Luciferase activity was measure with Dual-Glo Luciferase Assay System, and plotted as % of the unstimulated samples. BIC promoter reporter% unstimulatedunstimLPSLPS+IL-10unstimLPSLPS+IL-10unstimLPSLPS+IL-10unstimLPSLPS+IL-10unstimLPSLPS+IL-10unstimLPSLPS+IL-10unstimLPSLPS+IL-10unstimLPSLPS+IL-100501001502002 hrs 6 hrs 4 hrs 18 hrs5%9 %Stimulation time 4 hrs2 hrs 6 hrs 2 hrs% serum 9 %9 %9 %9 %9 % 5%XtremeGene HP GeneJuicereagent 219  Figure A.2 CHX treatment alters the expression level of GAPDH and actin, but not that of 18S rRNA.   RAW264.7 cells were treated with DMSO, CHX, ActD, LPS or LPS+CHX for 1 or 2 hours prior to RNA extraction and determination of pri-miR-155, GAPDH, actin and 18S rRNA levels by real time PCR.  Raw Ct values of pri-miR-155 were plotted against those of each normalization control.  pri-miR-155 CT vs GAPDH CTGAPDH CTpri-miR-155 CT16 17 18 19 20 2122242628303234CHX 2hLPS+CHX 2hunstim 1hunstim 2hDMSO 1hDMSO 2hCHX 1hCHX 2hLPS 1hLPS 2hLPS+DMSO 1hLPS+DMSO 2hLPS+CHX 1hLPS+CHX 2hpri-miR-155 CT vs actin CTActin CTpri-miR-155 CT18 19 20 21 22 2322242628303234CHX 2hLPS+CHX 2hunstim 1hunstim 2hDMSO 1hDMSO 2hCHX 1hCHX 2hLPS 1hLPS 2hLPS+DMSO 1hLPS+DMSO 2hLPS+CHX 1hLPS+CHX 2hpri-miR-155 CT vs 18S CT18S CTpri-miR-155 CT6.5 7.0 7.5 8.022242628303234unstim 1hunstim 2hDMSO 1hDMSO 2hCHX 1hCHX 2hLPS 1hLPS 2hLPS+DMSO 1hLPS+DMSO 2hLPS+CHX 1hLPS+CHX 2hCHX 2hLPS+CHX 2h 220  Figure A.3 4-HT treatment in the AKT-ER cells increases phosphorylation of GSK3β.   AKT-ER cells were either untreated or treated with 150 nM 4-HT for 20 minutes or 2 hours prior to immunoblotting analysis for phospho-GSK3β (pGSK3β) and vinculin (loading control).     Table A.4: Results of SERp server Residue numbering of mouse SHIP1 sequence is based on the RefSeq entry with accession number of NP_034696.   Cluster Suggested Mutation Description Cluster A: E 637 => A Residues 637 - 639: EEEE SERp Score: 7.77 E 638 => A E 639 => A  Cluster B: E 550 => A Residues 550 - 552: EKK SERp Score: 5.86 K 551 => A K 552 => A  Cluster C: E 770 => A Residues 770 - 773: QEGENEEGSEGE SERp Score: 5.85 E 772 => A E 773 => A    Anti-vinculinAnti-pGSK3b4HT time 0 min 20 min 2 hr4HT time (min)pGSK3b/vinculin0 20 12002468********

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