Examination of Type I IFN Mediated Regulation of the Post-Transcriptional Antiviral Response

Examination of type I IFN mediated regulation of the post-transcriptional antiviral response

J. Daniel Burke

A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Graduate Department of Immunology University of Toronto

Doctor of Philosophy Department of Immunology University of Toronto 2015

Abstract Interferons (IFNs) are pleiotropic cytokines that regulate both innate and adaptive immunity. Early post viral infection, there is induction and secretion of IFN-β which alerts nearby cells and primes leukocytes for an immune response. A rapid response is necessary for effective control of virus replication and spread. Previously in our lab, the IFN-α/β inducible PI-3’K/mTOR mediated induction of translation was shown to operate in concert with the prototypical JAK/STAT mediated transcription of IFN stimulated genes (ISGs). In the absence of key signaling intermediates of the PI-3’K/mTOR pathway, namely, Akt or PI- 3’K, an IFN-α/β inducible antiviral response was abolished. Given the apparent importance of this pathway, we sought to enhance IFN-α/β signaling by targeting key negative regulatory intermediates. In vitro experiments demonstrated that cells lacking suppressors of translation, TSC2 or 4E-BP1, are more sensitive to IFN-α/β inducible effects as indicated by increased antiviral protein synthesis, and enhanced resistance to virus infection. In vivo experiments showed that mice lacking 4E-BP1 are similarly more resistant to virus infection, and also more sensitive to the antiviral effects of IFN-β treatment. These in vitro and in vivo effects were demonstrated for different viruses, including Vaccinia virus, Influenza virus and Coxsackievirus. Given these findings of rapid mRNA translation to enable a robust IFN antiviral response, and aware that this is an ATP consuming process, we next examined whether IFN-α/β treatment also exerted effects on cell metabolism. Through a series of in vitro experiments we demonstrated rapid IFN-α/β-mediated regulation of glucose uptake in an Akt and PI-3’K dependent manner. Given the number of signaling intermediates shared by IFN-α/β and insulin, we examined the in vivo effects of metformin, an insulin sensitizer, during antiviral treatment with IFN-β. Interestingly, prophylactic treatment with both metformin and IFN-β produced a significant antiviral effect during the acute phase of viral myocarditis caused by Coxsackievirus B3 infection.

ii Taken altogether, the work described in this thesis provides further evidence for the importance of post-transcriptional regulation exerted by IFN-α/β during a virus infection.

iii Acknowledgements

Thank you. I am indebted to so many who have helped me climb this mountain. When hiking a mountain, not every step is predictable, and often there are slips and falls. You have been there to keep me on the path, and help me up along the way.

Firstly, Eleanor, you have been immensely supportive over the years! Thank you for your steadfast guidance and abundant patience. You know that this has not been a path easily navigated, but you have seen me through to the end. Your kindness and generosity have been hallmarks of the lab, and I will never forget the confidence that you invested in your trainees. I look forward to the years to come, and will take with me your ‘can-do’ attitude, and perseverence. Thank you for being my mentor!

Dana and Gary, I thank you both for your support through my degree. I recognize that you both have such busy schedules. You have so kindly taken time to hear updates about my project and provide helpful feedback. Thank you especially in this last stage of my program for reviewing my thesis!

I have heard people say that PhD stands for “permanent head damage”. There is more than a grain of truth to this. In and around the lab many of you have kept this effect to a minimum by diluting the tedium of cell splitting and virus titrations with laughter and levity. Ramtin, you were an incredible multi-dimensional encouragement all through my degree. From the pre-interview that I had with you before ever meeting Eleanor, all the way to my defense you had my back. Thomas, you were an excellent scientific role model! I thank you for bringing your fastidious attention to experimental detail to the lab. Such a high benchmark that you’ve set! Jae, I will never forget the degree to which you persevered and worked to get those papers out. I hope to emulate the fervour with which you approached your science. Carole, you were an everflowing fount of knowledge in both technical and general principles alike. Thank you for initiating so many lunchroom scientific discourses. I will miss your “ridiculous” questions! Beata, you are a cornerstone of the lab. Beyond keeping everything running so smoothly, your positive outlook was continually a source of reassurance that the sky would not fall. Danlin, thank you for the energy and laughter that you added during your time here. You kept me on my toes. I’m still “thinking about it”. Olivia, thank you for your cheerful presence all along the way, even after migrating across University Ave. The word metabolism has been given new meaning because of discussions with you. Ben, I have appreciated your enormously helpful and diligent character. Thank you for being the pillar that you are in the Fish lab! Leesa, your meticulous conduct and hard work in the lab has been a real inspiration to me. May your antibodies always be bright! Craig, thank you for keeping me company by the spec. Whether you knew it or not, you often added a much needed perspective when I was buried in 100s of mouse tissues. Darrin, I am really excited to see you move forward with the metabolism work. I can’t wait to see it on Pubmed! Erin, you added a healthy dose of vitality to the lab. I hope that ps20 did not do any irreversible damage, and that you go to help solve real problems in the medical world of Toronto!

iv There are so many in the research community that I have failed to mention, but have contributed to making this journey just that little bit smoother. I think of the many individuals in support-staff roles that are never included on papers. They are owed a great debt of gratitude as well. Thank you for your service!

To my dear friends at Grace Toronto, you were an integral thread to my life in Toronto! You challenged me in real ways, and were such a tangible representation of what the ‘Body of Christ’ is as a community. It is so exciting to see the impact that Grace is having in reaching the hidden, and not so hidden, brokeness of this great city.

Mom and Dad, you have been unspeakable supports to me in my academic pursuit! My DNA is from you, and you have given me this curiousity to pursue science. Through all the rapids and calm water you have been with me in the canoe. Thank you for the ceaseless prayer that you offered on my behalf. I am incredibly fortunate to have supportive parents like you! Andrea, I’m not sure who convinced who to get into Immunology, but now it seems that we’re both branded with this super-cool field of medicine. Thank you for the natural ability that you bring to facilitating community and relationships. Both you and Meg found Jenny! Thanks! Meg, it’s been fun to tag along with you periodically to meet your uber-hip architecture friends. I’m certain that God has you in this sphere for a particular reason, and that you are impacting those around you in ways that you do not know. Joe, you’re a great brother! You are such a positive and helpful person to be around. You add such a “spark” whereever you go. I think that you should come with a warning label. Aaron, you’re now a new brother, and a brave one at that. I’m looking forward to the future adventures that we will experience together.

To my new friends in the West, I thank you. Since before Jenny and I were married, you have supported us. I am so thankful for the many practical ways that you have done this. In addition, I deeply appreciate that you continually pray for one another, and that we have been recipients of this real aspect of Christian life.

Larry and Connie, thank you for the kindness that you have shown toward me as I learn the ropes of marriage. I am so thankful for your support, and that you pray for us so diligently. I look forward to the crazy family adventures that lie ahead of us. Even now, I am sitting on a beach in Nassau writing this as you float down a lazy river. Thank you!

Jenny, you have been my partner in this last leg of the journey. I have so much to be thankful for in having you by my side! You are a wonderful woman! Your steady encouragement and confidence in me have been crucial in getting me to the finish line. And your continual prayer has undoubtedly been instrumental in getting me past so many hurdles. Thank you. I am excited to see where God leads us in the coming years as He continues to unfold His plan for our family!

It feels as though I have reached the summit of a significant mountain on this journey. As I continue on through this mountain range, I will take with me many friendships and experiences. From the bottom of my heart, I thank you for how you have shaped me during these years in grad school!

v Table of Contents

Title Page………………..………………………………………………………………………………………….………….. i Abstract………………………………………………………………………………………………………………………… ii Acknowledgements…………………………………………………………………………………………………..……iii Table of Contents………...…………………………………………………………………….……………………….v-vii List of Figures.…………………………………………………………………………………………………………...... viii List of Tables………………………………………………………………………………………………………….………ix List of Abbreviations…………………………………………………………………………………………….……x-xiv

CHAPTER 1: Introduction………………………………………………………………………………..……....1-48

1.1. Interferons………………………………………………………………………………………….……..…..2 1.1.1. Subtypes and Classification…………………………………………………………….………2 1.1.2. Genes and Chromosome Location…………………………………………………….……..6 1.1.3. IFN Expression………………………………………………………………………………..……..7 1.1.4. IFN Signaling…………………………………………………………………………………..…...11 1.1.4.1. STAT mediated transcriptional regulation…………………………………….14 1.1.4.2. MAPK mediated transcriptional and post-transcriptional regulation ………………………………………….……………………………………………………………………16 1.1.4.3. PI-3’K/Akt/mTOR mediated post-transcriptional regulation………....20 1.1.5 Negative Regulation of IFN Signaling……………..………………………………………24

1.2. mTOR and Metabolism……………………………………………………..……………………..……27 1.2.1. mTOR signal integration (amino acid, energy, stress and oxygen) …..……..27 1.2.2. mTOR mediated translational regulation…..……..……..……..……..……..……...…30 1.2.3. mTOR effects on cellular immunity…..……..……..……..……..……..……..………..…36 1.2.3.1. mTOR effects on T cells…....……..……..……..……..……..……..…………….....…36 1.2.3.2. mTOR effects on dendritic cells…..……..……..……….…………….…..……..…37 1.2.3.3. mTOR effects on monocytes/macrophages…..……..………………..……….37 1.2.3.4. mTOR effects on B cells…..……..……..……...... ……..…….…..……..…38 1.2.3.5. mTOR effects on Natural Killer cells…..……..……..……..……..………...…….38

1.3 IFNs and Antiviral Immunity…..……..……..……..……..……..……..……..………...……..…….39 1.3.1. Influenza Virus…..……..……..……..……..……..……..……..……………..……..……..……39 1.3.2. Vaccinia Virus…..……..……..……..……..……..……..……..……..………..……..……..……40 1.3.3. Coxsackievirus…..……..……..……..……..……..……..……..……..………..…..……..……..42 1.3.4. Antiviral Effects of Type I IFNs…..……..……..……..……..……….....……..……..…….44 1.3.5. Type I IFN Effects on Immune Cells…..……..……..……..……....……..……..……..…47 1.3.5.1 IFN Regulated Chemotaxis…..……..……..……..……..……...……..……..……..…47 1.3.5.2 IFN Regulation of Leukocyte Effector Function…..…………..……..……..…49

1.5 Hypothesis and Objectives…..……..……..……..……..……..……..……..……..…….…..……..…52

vi CHAPTER 2: Antiviral effects of IFNs-α/β are enhanced in the absence of the translational suppressors 4E-BP1 and TSC2. …..……..…………..……..……..……..…53-86

2.1. Abstract…..……..……..……..……..……..……..……..……..……..……..……..……..……………….…54

2.2. Introduction…..……..……..……..……..……..……..……..……..……..……..……..…………...…..…55

2.3. Materials and Methods…..……..……..……..……..……..……..……..……..……..……………..…57 2.3.1. Animals, cells and virus…..……..……..……..……..……..……..……..…………..……..…57 2.3.2. Immunoblotting…..……..……..……..……..……..……..……..……..……..…...…..……..…57 2.3.3. IFN treatment and virus infection…..……..……..……..……..………..……...……..…58 2.3.3.1. In vitro virus infection…..……..……..……..……..……..……..……..………..…58 2.3.3.2. In vivo CVB3 infection…..……..……..……..……..……..……..……..…….…..…58 2.3.3.3. In vivo Influenza virus infection…..……..……..……..……..……..……..……58 2.3.4. Real time PCR detection of gene expression…..……..……..……..……..………..…59 2.3.5. Histopathology…..……..……..……..……..……..……..……..……..……..……..………....…59

2.4. Results…..……..……..……..……..……..……..……..……..……..……..……..……..……..……….....…61 2.4.1. IFN-α induces increased translation of antiviral proteins in cells lacking negative regulators of protein synthesis…..……..……..……..……..………..…….61 2.4.2. IFN-α/β invokes enhanced antiviral effects in cells lacking the translational suppressor 4E-BP1…..……..……..……..……..……..……..………...…64 2.4.3. IFN-β elicits a stronger antiviral effect in CVB3-infected mice lacking the translational suppressor 4E-BP1…..……..……..……..……..……..……..……...……70 2.4.4. IFN-β treatment reduces inflammation in the hearts of CVB3 infected mice …..……..……..……..……..……..……..……..……..……..……..……..……..……..…………..…78 2.4.5. IFN-β exerts a strong antiviral effect in influenza virus-infected mice which lack the translational suppressor 4E-BP1. …..……..……..………..…….81

2.5. Discussion…..……..……..……..……..……..……..……..……..……..……..……..……..……….…..…84

CHAPTER 3: IFN-β regulation of glucose metabolism is PI-3’K/Akt-dependent and important for antiviral activity against Coxsackievirus B3…..……..…….....….87-111

3.1. Abstract…..……..……..……..…..……..……..……..…..……..……..……..…..……..………..…..……..88

3.2. Introduction…..……..……..……..…..……..……..……..…..……..……..……..…..……..…..……..…89

3.3. Materials and Methods…..……..……..……..…..……..……..……..…..……..…………..…..……..91 3.3.1. Cells, virus and reagents…..……..……..……..…..……..……..………..…..……..……..…91 3.3.2. Cell Lysis and Immunoblotting…..……..……..……..…..………………...……..…...…..91 3.3.3. Glucose Uptake Assay…..……..……..……..…..……..……..……..…..……..……..…...…..91 3.3.4. Intracellular ATP Determination…..……..……..……..…..……..……..……..……....…92 3.3.5. GLUT4 Measurement…..……..……..……..…..……..……..……..…..………..……..……..92 3.3.6. CVB3 Infection of MEFs…..……..……..……..…..……..……..………..…..……..…….…..92 3.3.7. In vivo studies…..……..……..……..…..……..……..……..…..……..…………………..……..93 3.3.8. Statistical Analysis…..……..……..……..…..……..……..……..……...…….…..……..……..93 vii

3.4. Results…..……..………..…..……..……..……..…..……..……..……..…..……..……..……………....….94 3.4.1. Effects of IFN-β on AMPK phosphorylation and intracellular ATP………….94 3.4.2. IFN-β induces glucose uptake mediated by regulation of the PI-3’K/Akt signaling cascade. …..……..……..……..…..……..……..……..…..……..…………..……..97 3.4.3. Inhibition of glycolysis affects the antiviral activity of IFN-β…..…...…..….100 3.4.4. Treatment with metformin enhances the antiviral activity of IFN-β. …...103

3.5. Discussion…..……..……..……..…..……..……..……..…..……..……..……..…..……..……..…..…..106

CHAPTER 4: Discussion and Future Directions…..……..……..……..…..……..……...…..….112-124

4.1. Application of Type I IFNs…..……..……..……..…..……..……..……..…..……..……..………..113 4.2. 4E-BP1 Regulation of mRNA Translation…..……..……..……..…..……..…………..……..115 4.3. Influence of IFN-α/β on specific mRNA translation…..……..……..…………..……..…117 4.4. Influence of 4E-BP1 on the Hematopoietic Compartment…..……..…………..……..118 4.5. Metabolic Effects of Type I IFNs…..……..……..……..…..……..……..……....…..….…..……120 4.6. Conclusions…..……..……..……..…..……..……..……..…..……..……..……..…..……….……..…..123

CHAPTER 5: References…..……..……..……..…..……..……..……..…..……..……..……..…..….……125-162

viii List of Figures

CHAPTER 1

Figure 1.1. Type I IFN Signaling Cascade…..……..……..……..…..……..……..……..………..….….9 Figure 1.2. Interferon Inducible STAT dimers…..……..……..……..…..……..…………………..12 Figure 1.3. MAPK Signaling……..……..…..……..……..……..…..……..……..……..…..…………..…..15 Figure 1.4. Regulation of mTORC1 and mTORC2……..……..…..……..……..…………..…..…..19 Figure 1.5 IFN-α/β Regulated Translation Initiation……..……..…..……..……..……..…...…29

CHAPTER 2

Figure 2.1. IFN-α4 differentially regulates ISG15 expression in MEFs lacking translational supressors 4E-BP1 orTSC2.…..…..……..………..…..……..……...…59 Figure 2.2. MEFs lacking translational suppressors 4E-BP1 and TSC2 are more resistant to infection with VACV and more sensitive to treatment with IFN-α4. …..……..………..…..……..……..………..…..……..……..………..…..………...…….62 Figure 2.3. IFNs-α/β induce potent antiviral effects against CVB3 in cells lacking 4E-BP1 or TSC2. …..……..………..…..……..……..………..…..……..……..………..……..65 Figure 2.4. Mice lacking 4E-BP1 are more resistant to infection with CVB3……….….69 Figure 2.5. Mice lacking 4E-BP1 exhibit increased expression of antiviral genes during the course of CVB3 infection..…..……..………..…..……..………..……….…71 Figure 2.6. Mice lacking 4E-BP1 are more sensitive to the effects of treatment with IFN-β during infection with CVB3. ..…..……..………..…..……..………..…………...73 Figure 2.7. CVB3 infected 4E-BP1-/- mice exhibit less severe pathology……..……...…76 Figure 2.8. IFN-β exerts a stronger antiviral effect in influenza virus-infected mice which lack the translational suppressor 4E-BP1. ..……...……...………....…….79

CHAPTER 3

Figure 3.1. IFN-β reduces AMPK phosphorylation and increases intracellular ATP ……..……. ..……. ..……. ..……. ..……. ..……. ..……. ..……. ..……. ..……. ..……. ..……….92 Figure 3.2. IFN-β influences glucose uptake. ..……. ..……. ..……. ..……. ..……. ..……. ..…….95 Figure 3.3. Glucose metabolism is critical for induction of an IFN-β mediated antiviral response. ..……. ..……. ..……. ..……. ..……. ..……. ..……. ..……. ..………...98 Figure 3.4. Metformin enhances antiviral effect of IFN-β during infection with CVB3 ……...……. ..……. ..……. ..……. ..……. ..……. ..……. ..……. ..……. ..……. ..……. ..…….101 Figure 3.5. Schematic of IFN-β mediated regulation of PI-3’K/Akt/mTOR signaling and pharmacological agents active in this pathway. ..……. ..……. ..………..107

ix List of Tables

CHAPTER 1

Table 1.1 Interferon expression patterns ……………………………………………………………...4 Table 1.2. Pattern recognition receptors………………………………………………………………..8

x List of abbreviations

2-DG 2-Deoxy-D-Glucose 4E-BP eIF4E Binding Protein ACC Acetyl CoA Carboxylase ADP Adenosine Diphosphate AMP Adenosine Monophosphate AMPK AMP-Activated Protein Kinase AP Activator Protein ARE AU-rich Elements ATF Activating Transcription Factor ATM Ataxia-Telangiectasia Mutated ATP Adenosine Triphosphate BCR B Cell Receptor BMDM Bone Marrow Derived Macrophage BSA Bovine Serum Albumin CaMKK Calcium/Calmodulin Dependent Protein Kinase Kinase CCL Chemokine Ligand CCR Chemokine Receptor CD Cluster of Differentiation CDK Cyclin Dependent Kinase CMV Cytomegalovirus CRE cAMP Responsive Element cRNA Complementary RNA CVB Coxsackievirus B DC Dendritic Cell DCM Dilated Cardiomyopathy DEPTOR DEP domain-containing mTOR interacting protein DMEM Dulbecco’s Minimal Essential Medium DNA Deoxyribonucleic Acid dsRNA Double Stranded RNA ECL Enhanced Chemiluminescence EDTA Ethylenediaminetetracetic Acid eIF Eukaryotic Initiation Factor EMCV Encephalomyocarditis Virus EPO Erythropoietin ER Endoplasmic Reticulum ERK Extracellular Signal-Regulated Kinase EV Enveloped Virion FACS Fluorescence Activated Cell Sorting FCS Fetal Calf Serum FKBP FK506 Binding Protein GAP GTPase Activating Protein GAS Gamma Activating Sequence GCN General Control Non-Derepressible GDP Guanine Diphosphate

xi GEF Guanine Exchange Factor GLUT Glucose Transporter GM-CSF Granulocyte Macrophage – Colony Stimulating Factor GS Glycogen Synthase GSK Glycogen Synthase Kinase GTP Guanine Triphosphate GVHD Graft Versus Host Disease H Hemagglutinin H&E Hematoxylin and Eosin HCMV Human Cytomegalovirus HCV Hepatitis C Virus HIF Hypoxia Inducible Factor HIV Human Immunodeficiency Virus HK Hexokinase HLA Human Leukocyte Antigen HRI Haem-Regulated Inhibitor HSC Hematopoietic Stem Cell HSV Herpes Simplex Virus i.p. Intraperitoneal IFN Interferon IFNAR Type I IFN Receptor IKK IκB Kinase IL Interleukin IRES Internal Ribosome Entry Site IRF Interferon Response Factor IRS Insulin Receptor Substrate ISG Interferon Stimulated Gene ISRE IFN-Stimulated Response Element IκB Inhibitory-κB JAK Janus Activated Kinase JNK c-Jun N-Terminal Kinase KRH Krebs Ringer HEPES KSHV Kaposi’s Sarcoma-associated Herpesvirus LC-MS/MS Liquid Chromatography-tandem Mass Spectrometry LCMV Lymphocytic Choriomeningitis Virus LKB Liver Kinase B LPS Lipopolysaccaride M Matrix MAPK Mitogen Activated Protein Kinase MAPKAPK MAPK Activating Protein Kinase MAVS Mitochondrial Antiviral Signaling Protein MCP Monocyte Chemotactic Protein MDA Melanoma Differentiation Associated Protein MDCK Madin Darby Canine Kidney MDSC Myeloid Derived Suppressor Cell MEF Murine Embryonic Fibroblast MERS-CoV Middle Eastern Respiratory Syndrome Corona Virus xii MET Metformin MFI Mean Fluorescence Intensity mg milligram MHC Major Histocompatibility Complex MHV Murine Hepatitis Virus mIFN Murine IFN MK MAPK Activating Protein Kinase mL milliliter mLST Mammalian Lethal with Sec13 Protein mM millimolar MNK MAPK Interacting Kinase MOI Multiplicity Of Infection mSIN Mammalian Stress Activated Protein Kinase Interacting Protein MSK Mitogen and Stress Activated Kinase mTOR Mechanistic Target Of Rapamycin mTORC mTOR Complex MV Mature Virion MX Orthomyxovirus Resistance Protein N Neuraminidase NFκB Nuclear Factor-κB NK Natural Killer NKT Natural Killer T cell nm nanometer NO Nitric Oxide NP Nucleoprotein NS Non-Structural OAS Oligoadenylate Synthetase ORF Open Reading Frame PABP Poly A Binding Protein PAGE Poly Acrylamide Gel Electrophoresis PAMP Pathogen Associated Molecular Pattern PBS Phosphate Buffered Saline PCR Polymerase Chain Reaction pDC Plasmacytoid Dendritic Cell PDCD Programmed Cell Death PDK Pyruvate Dehydrogenase Kinase PERK PKR-like Endoplasmic Reticulum Kinase pfu plaque forming unit PGC Peroxisome proliferator-activated receptor gamma coactivator PH Pleckstrin Homology PHAS Phosphorylated Heat and Acid Stable Protein PI-3’K Phosphatidylinositol 3’-Kinase PIAS Protein Inhibitor of Activated STAT PIC Preinitiation Complex PIKK PI-3’K Related Kinase PIP2 phosphatidylinositide 4,5 phosphate PIP3 phosphatidylinositide 3,4,5 phosphate xiii pIRE Palindromic IFN Response Element PKC Protein Kinase C PKR RNA Dependent Protein Kinase PRAS Proline Rich Akt Substrate PRD Positive Regulatory Domain PRO Protease PROTOR Protein Observed with RICTOR PRR Pattern Recognition Receptor PTP Protein Tyrosine Phosphatase RAG Ras-Related GTPase RANTES Regulated on Activation, Normal T Cell Expressed and Secreted RAPTOR Regulatory-Associated Protein of mTOR REDD Regulated in Development and DNA Damage RHEB Ras Homolog Enriched in Brain RICTOR RAPTOR Independent Companion of TOR RIG Retinoic Acid Inducible Gene RLR RIG-I-Like Receptor RNA Ribonucleic Acid RNP Ribonucleoprotein ROR Retinoic Related Orphan Receptor rp Ribosomal Protein RPMI Roswell Park Memorial Institute medium RSK 90 kDa Ribosomal Protein S6 Kinase S1P Sphingosine-1-Phosphate S6K 70 kDa Ribosomal Protein S6 Kinase SARS-CoV Severe Acute Respiratory Syndrome Coronavirus SCF Skp, Cullin, F-Box Containing Complex SDS Sodium Dodecyl Sulphate SEM Standard Error of the Mean Ser Serine SERPIN Serine Protease Inhibitor SGK Serum and Glucocorticoid Inducible Kinase SH Src Homology SHP Src Homology-2 Protein Tyrosine Phosphatase siRNA Silencing RNA SOCS Suppresor Of Cytokine Signaling SREBP Sterol Regulatory Element Binding Protein SSC Side Scatter ssRNA single stranded RNA STAT Signal Transduction And Transcription TBK TANK-Binding Kinase TBST Tris Buffered Saline with Tween TC Ternary Complex TC-PTP T Cell Protein Tyrosine Phosphatase TCR T Cell Receptor TGF Transforming Growth Factor Th T helper xiv Thr Threonine TLR Toll Like Receptor TNF Tumor Necrosis Factor TOS Target Of Rapamycin Signaling Treg Regulatory T Cell TRIF TIR-domain-containing adapter-inducing interferon-β tRNA Transfer RNA TSC Tuberous Sclerosis Complex TYK Tyrosine Kinase Tyr Tyrosine U Unit uCi micro Curie UCP Uncoupling Protein ULK UNC51 Like Kinase USP Ubiquitin Specific Protease UTR Untranslated Region VACV Vaccinia Virus vCCI VACV CC Chemokine Inhibitor vCKBP VACV Chemokine Binding Protein vRNA Viral RNA VSV Vesicular Stomatitis Virus µg microgram µL microliter µM micromolar µm micrometer

Chapter 1

Introduction

1 1.1 Interferons

Interferon (IFN) was discovered by Isaacs and Lindenmann in 1957, as a secreted factor produced by virus infected cells that could, in turn, sensitize and protect other cells from subsequent viral infections (1). The ensuing characterization of IFN revealed a variety of distinct subtypes with varied immunomodulatory effects (2). Today, IFNs are used clinically to treat a variety of diseases, including hepatitis B and C virus infections (3), malignant neoplasms such as chronic myeloid leukemia (CML) (4) and multiple sclerosis (5).

1.1.1. Subtypes and Classification In the early 1960’s type I and II interferons (IFNs) were broadly classified according to their initial characterization of acid-stability, antigenic structure and stimuli inducing their expression (6). Originally, IFNs were divided into leukocyte, fibroblast and immune IFNs, and then later reclassified as IFNs-α, –β and –γ, respectively (7) (Table 1.1). A large number of IFN subtypes have been identified and there are currently three classes of IFNs designated as type I, II and III. IFNs are phylogenetically conserved and found in mammals as well as variety of non-mammalian vertebrates, including fish, amphibians, reptiles and birds (8). The mammalian type I IFNs are comprised of IFNs-α(alpha), -β(beta), -ε(epsilon), -κ(kappa),-ω(omega), -δ(delta), -τ(tau), -ν(nu) and –ζ(zeta) (9). A subset of these are found in humans, including 13 IFN-α subtypes, and single IFNs -β, -ε, -κ and -ω. Some of these IFNs have unique tissue expression, such as IFN-ε, which is limited to epithelial cells of the reproductive tract. Notably, the receptor for IFN-ε is upregulated by estrogen. Additionally, it is also constitutively expressed in male reproductive tissue (10). IFN-κ, possessing similar antiviral activity as other type I IFNs, displays restricted expression in human keratinocytes, and inducible expression in monocytes and dendritic cells (11). IFN-ω has only been identified in humans, exhibits similar antiviral activity and expression patterns as the IFN-αs, but is distinct in it’s antigenic structure (12). IFNs-δ and -τ, are unique to pigs and ruminants respectively, IFN-ν is unique to felines and IFN-ζ, also known as limitin, is unique to mice (13).

2 Type II IFN contains a sole member, IFN-γ (gamma), which is highly conserved among vertebrates (14). More recently, type III IFNs have been added to the family which were previously identified as IL-29, IL-28A and IL-28B, the nomenclature now being IFNs –λ1, – λ2 and –λ3 (15). IFN-λ4 has been discovered most recently, and is biologically active in some human populations carrying a single nucleotide deletion which permits expression of a full length protein (16).

3 Table 1.1 Interferon Expression Patterns IFN and receptor expression are shown for human cells. ‘+’ indicates the presence of receptor or responsiveness to IFN; ‘-‘ indicates the absence of receptor or non- responsiveness to IFN. Table is compiled from data from de Weerd and Nguyen (12) and George et al (410).

IFN$Type I II III IFN$Subtype Sources IFN$Subtype Sources IFN$Subtype Sources T$cells,$NK,$NKT,$ nucleated$cells,$ α's$(1'13) γ (DC,$B$cells,$ λ's$(1'4) nucleated$cells pDCs Macrophages) β nucleated$cells ε uterine$epithelium κ keratinocytes ω nucleated$cells

Genomic$Location 9p21 12q14 19q13

Cognate$Receptor IFNAR1,$IFNAR2 IFNGR1,$IFNGR2 IFNLR1,$ILI10R2

Tissue Receptor$Distribution T$cell + +/' ' B$cell + + ' pDC + + + Macrophage + + ' NK$cell + + ' Eosinophil + + + Epithelial$cell + +/' + Endothelial$cell + + ' Adipocyte + + ' Hepatocyte + + + Astrocyte + + ' Fibroblast + + ' Keratinocyte + + +

5 1.1.2. Genes and Chromosome Location Genomic organization of the human IFN genes reveals clustering of type I IFNs on chromosome 9, type II IFN on chromosome 12, and type III IFNs on chromosome 19 (17). Sequence analysis has revealed the absence of introns in the genes of type I IFNs (except IFN- κ), whereas both types II and III IFN genes contain multiple introns (15). There is limited homology among the different IFNs at the amino acid sequence level with IFN-αs sharing 50-100% identity, and only 29% similarity to IFN-β, and 20% similarity to IFN-λs at the protein level (9, 15, 18-21).

Phylogenetic relationships exist among IFNs and other class II cytokines which include the family of IL-10-like cytokines (IL-10, -19, -20, -22, -24, -26) (22). These cytokines are differentiated from the larger family of class I cytokines based on functional and structural differences (23). Functionally, class I cytokines are generally involved in clonal cell expansion or differentiation e.g. IL-2, -3, -4, -5, -6, -7, -12, GM-CSF, EPO, whereas class II cytokines are involved in minimizing tissue damage following insult eg type I, III IFNs, IL- 10, -22 (23, 24). Structurally, class I cytokines are configured as both α-helices and β-sheets whereas class II cytokines are solely composed of alpha helices (23). In parallel, the receptors through which these cytokines signal also segregate into structurally defined categories. These receptors are single-pass transmembrane glycoproteins possessing extracellular fibronectin domains, but differing in conserved cysteine residues which form disulfide bonds (23).

Varying degrees of N-glycosylation can be observed across the different types of IFNs, which influences their secretion and biological effects (25, 26). Glycosylation of IFNs can be accounted for by signal peptides found in the amino terminal of precursor proteins which traffic them through the endoplasmic reticulum. Mature type I and III IFN polypeptides contain multiple disulphide bonds, whereas IFN-gamma is lacking such modification (17, 27).

6 1.1.3. IFN Expression Type I and III IFNs are rapidly induced in response to viral infections. IFN expression levels vary among the different subtypes, with type I and III IFNs exhibiting the most similarity, displaying broad expression among tissues. Type II IFN expression has previously been limited to T-cells, NK and NKT cells (14), but evidence has also been provided for the secretion of IFN-γ by dendritic cells, macrophages and B cells (28-30). IFN expression patterns relate to their distinct roles in governing innate and adaptive immunity. Nearly all nucleated cells are able to produce IFNs-α, –β and -λ, whereas, IFN-γ expression is restricted to a subset of leukocytes.

As type I IFNs are involved in responses to infection, they are rapidly induced by a large variety of receptors involved in bacterial and viral pathogen recognition which include cell surface, endosomal and cytosolic pattern recognizing receptors (PRRs) (31-38) (Table 1.2).

Table 1.2 Pattern recognition receptors. Abbreviations: H, human; M, mouse; ND, not determined

8 SENSOR SPECIES LOCATION LIGAND SOURCE TLR1/2 H,M Extracellular Triacyl5lipopeptides Bacteria,5Mycobacteria TLR2/6 H,M Extracellular Diacyl5Lipopeptides Mycoplasma Lipoteichoic5acid5 Gram5(+)5Bacteria Zymosan Fungi TLR2 H,M Extracellular Phospholipomannan Fungi Glucuronoxylomannan Fungi tGPIJmucin Parasite Peptidoglycan5(PG) Gram5(+)5Bacteria Porins Bacteria Lipoarabinomannan Mycobacteria Hemagglutinin Virus TLR3 H,M Endolysosome dsRNA Virus poly5(I:C) Synthetic poly5(U) Synthetic TLR4 H,M Extracellular5and5 Endolysosome Lipopolysaccaride5(LPS) Bacteria Monophosphoryl5Lipid5A Synthetic TLR5 H,M Extracellular Flagellin Flagellated5Bacteria TLR7/8 H,M Endolysosome GUJrich5ssRNA Virus short5dsRNA Virus RJ8485(Imidazoquinolines) Synthetic TLR9 H,M Endolysosome CpGJDNA Bacteria CpGJODN synthetic DNA Bacteria,5Virus Hemozoin Parasite TLR10 H ND ND ND TLR11 M Endolysosome Profilin Parasite Flagellin Flagellated5Bacteria TLR12 M Endolysosome Profilin Parasite TLR13 M Endolysosome 23S5rRNA Bacteria NOD1 H,M Cytosol dJglutamylJmesoJdiaminopimelic5acid Gram5(J)*5Bacteria NOD2 H,M Cytosol Muramyl5dipeptide Bacteria dsRNA Virus NLRP3 H,M Cytosol PAMPs5(LPS,5MDP,5RNA) Bacteria,5Virus DAMPs5(ATP,5K+,5Ca2+) Host toxins,5drugs,5particulates,5nanoparticles Synthetic poly5(I:C) Synthetic NLRP1 H,M Cytosol MDP Bacteria AIM2 H,M Cytosol dsDNA Bacteria,5Virus RIGJI H,M Cytosol 5'JPPPJssRNA Virus short5dsRNA Virus short5poly5(I:C) Synthetic MDA5 H,M Cytosol dsRNA Virus poly5(I:C) Synthetic LGP2 H,M Cytosol dsRNA Virus ZBP1 H,M Cytosol dsDNA Virus

9 Induction of type I IFNs is tightly regulated at the level of transcription, and is well charcterized for the IFN-β promoter. Signaling through the various PRRs assembles a multimeric complex, known as the enhanceosome, composed of three different types of transcription factors. The necessary components include the IRFs (-1,-3,-5,-7), nuclear factor (NF)-κB, and c-Jun/ATF2 (AP-1) (39). Activation of NFkB is dependent upon release from inhibitory (I)-kB, and translocation from the cytosol to the nucleus. IκB kinase epsilon (IKKε) and TANK-binding kinase 1 (TBK1) are two non-canonical IKKs responsible for IRF phosphorylation. Induction of IFN-α/β expression is dependent on the binding of positive regulatory domains (PRDs) by transcription factors. IRFs bind IFN-stimulated response element (ISRE) sites (PRDI and III), NF-κB binds the κB site (PRDII), and c-Jun/ATF2 binds the cAMP-responsive element (CRE) (PRDIV). IRF-1 dependent expression of IFN-β and ISGs relies on the co-activation and binding of NF-κB (40). IRF-3 is expressed in all cell types at a basal level (41), whereas, IRF-5 is limited to expression in B-cells and dendritic cells. IRF-7 is predominantly expressed in lymphoid cells, but is highly expressed in plasmacytoid dendritic cells (pDCs). Both IRF-5 and -7 expression can be induced by type I IFN treatment (42, 43). Their activation and nuclear translocation is dependent on phosphorylation and requires binding of the CBP/p300 coactivator to induce target gene transcription (41). IRF-3 has been shown to be sufficient in inducing IFN-β, whereas IRF-7 predominantly regulates IFN-αs. IRF-5 elicits the expression of a partially overlapping set of IFN-αs and ISGs, and is also able to interact with IRF-7 to produce an inhibitory effect (41).

The classical IFN-inducible antiviral response involves a two-stage signaling cascade whereby the initial virus is detected through PRRs which induce expression of IFN-β and IFN-α4 along with some ISGs, including IRF-7. Autocrine and paracrine signaling of these IFNs through type I IFN receptors (IFNAR) enhances the response further by inducing a broader set of antiviral proteins and governing cell survival. The nascent IRF-7 is then able to sense any additional viral replication and amplify a larger set of IFN-αs for further autocrine and paracrine effects. Co-expression of type I and III IFNs are the consequence of common regulatory elements in their promoters regions (15).

10 1.1.4. IFN Signaling All type I IFNs signal through the same heterodimeric receptors, IFNAR1 and IFNAR2, expressed on nearly all nucleated cells (44). Three IFNAR2 isoforms (IFNAR2-a,-b,-c) have been identified, which arise from varied expression patterns involving exon skipping, alternative splicing and differential polyadenylation site usage (45). IFNAR2c is the complete transmembrane form which transmits signals, whereas IFNAR2b is a truncated transmembrane form which can act as a dominant negative during signaling (46). Present in serum, IFNAR2a is a secreted form, which binds IFN-α/β, and is understood to modulate signaling through IFNAR1/2c in both agonistic and antagonistic manners (47). It has been estimated that between 200-10,000 IFN binding sites exist on the surface of most cells (48). Added to this, the different IFN subtypes display varied binding affinities toward the individual receptor subunits. Stability of the ternary signaling complex also appears to influence qualitative effects of signaling (49). The ternary complex formed at the cell surface between cytokine, IFNAR1 and IFNAR2, first initiates intracellular cross phosphorylation of receptor-associated Janus kinases, Jak1 and Tyk2 (20) (Figure 1.1).

Figure 1.1 Type I IFN signaling cascade. Type I IFNs engage their cognate heterodimeric receptor and induce signaling through a series of unique and coordinate pathways. IFNaR-associated JAKs are activated, and phosphorylate cytoplasmic tails of IFNaRs. Recruitment of various signaling effectors is mediated by SH2-domain interactions with the phosphorylated IFNaRs. 1) STAT signaling is initiated by JAK phosphorylation of individual STAT proteins, leading to their dimerization and recruitment of additional factors for nuclear import and binding to specific promoter sequences for the induction of IFN-stimulated gene (ISG) expression. 2) Activation of mitogen activated protein kinases (MAPK) signaling is initiated by JAK phosphorylation of guanine exchange factors (GEFs) (ie VAV1) which activate downstream Rho-family GTPases (ie RAC1). Subsequent activation of a series of MAPK kinases leads to activation of the three major MAPKs (JNK, p38, ERK). Downstream targets include transcription induction, histone modification and translation initiation regulation. 3) Activation of mamalian target of rapamycin (mTOR) is initiated through JAK phosphorylation of IRS proteins and subsequent recruitment and activation of the PI3’K. Generation of phosphatidylinositide 3,4,5 phosphate (PIP3) at the plasma membrane recruits Akt into close proximity with PDK1, which phosphorylates and activates Akt. Phosphorylation of the downstream GTPase activating protein (GAP), TSC2, destabilizes its interaction with TSC1 thereby decreasing subsequent activation of the GTPase, Rheb. GTP- bound Rheb accumulates, and associates with mTORC1, which is necessary for kinase activity. Akt also activates mTORC1 through a 14-3-3 dependent mechanism as well. Inhibition of mTORC1 activity is regulated by AMPK through phosphorylation and activation of TSC2 GAP activity. Activated Rheb converts GTP to GDP, thereby reducing its association with and activation of mTORC1. AMPK also indirectly inhibits mTORC1 activity through phosphorylation of RAPTOR. Substrates of mTORC1 include S6K and 4E-BP1. Phosphorylation of these targets results in translation initiation.

12 Figure 1.1

These tyrosine kinases then phosphorylate conserved tyrosine residues in the intracellular receptor tails, thereby recruiting SH2-containing signaling effectors and adapter proteins (50). These include STAT proteins (51), insulin receptor substrate (IRS-1,-2) (52), CrkL (53), Vav (54), c-cbl (55) and Src family proteins (lyn, fyn) (56). The three major signaling pathways that are regulated through these proteins include STAT transcriptional initiation, MAPK mediated transcriptional and post-transcriptional modulation, and PI3’K/mTOR regulation of post-transcriptional processes.

1.1.4.1. STAT mediated transcriptional regulation STAT proteins were discovered in the context of types I and II IFN signaling(57), and have since been shown to mediate signaling from a variety of other cytokine and growth factors receptors (58). Seven STAT molecules have been identified that are able to dimerize in different homo- and heterotypic combinations upon tyrosine phosphorylation, interact with other co-regulators and bind gene promoter elements with sequence specificity (59)(Figure 1.2).

Figure 1.2 Interferon inducible STAT dimers. Signaling initiated by type I IFNs induce dimerization of different combinations of STAT molecules, in certain instances also associated with IRF9. Different STAT complexes dictate binding specificity for promoters upstream of interferon stimulated genes.

Located in the cytoplasm, STAT proteins are recruited to activated IFNAR-associated Jak1 and Tyk2 and are phosphorylated on key tyrosine residues, which permits their SH2 domain dependent dimerization (60). Additional association of p48/IRF9 with STAT2- containing dimers confers binding specificity for STAT1:2, STAT2:2 and STAT2:6 dimers to interferon stimulated response elements (ISREs), found in the promoters of various interferon stimulated genes (ISG). Inclusion of IRF9 in these complexes, known as ISGF3, improves binding to ISRE sites by 20-30 fold (61). In the absence of IRF9, other activated STAT dimers can bind gamma activating sequences (GAS) or GAS-like palindromic IFN response elements (pIREs)(59, 62). GAS sites were initially discovered as IFN-γ inducible elements, but have since been demonstrated to be activated by type I IFNs as well (63). Promoter analysis of different ISGs has revealed the presence of single elements, or combinations of ISRE, GAS and pIRE, which can partially account for the variation in ISG expression.

Beyond JAK-mediated activation, STAT-driven transcription can be regulated through a variety of different signaling inputs operating downstream of the initial activation event (64). Serine phosphorylation of STATs in their C-terminal transcription activation domain (TAD) is necessary for optimal transcriptional induction (65), and is initiated by inputs from p38 MAPK, JNK, Akt, PKC-δ, -ε, IKKε, CaMKII and CDK8 (66-71). It is clear from human and mouse studies that STAT1, STAT2 or IRF9 are necessary for an effective immune response to infection. Lacking any of these functional proteins leads to an impaired immune response towards viral and bacterial pathogens alike (72-74).

1.1.4.2. MAPK mediated transcriptional and post-transcriptional regulation The mitogen activated protein kinases (MAPKs) are a highly conserved family of serine/threonine kinases that play an important role in regulating transcriptional and post- transcriptional processes induced by various cytokines, growth factors and stress-stimuli (75, 76). Processes governed include gene expression, cell cycle, metabolism, apoptosis, motility and differentiation. Three of the most studied signaling effectors in this family include p38 MAP kinases (p38MAPK-α,-β,-γ,-δ), extracellular signal-regulated protein

16 kinases (ERK-1,-2) and c-Jun NH2-terminal kinases (JNK-1,-2,-3) (76, 77) and are important to the effects induced by types I and II IFNs (20) (Figure 1.3).

Figure 1.3 MAPK signaling. Signaling initiated by type I IFNs leads to the activation of a hierarchy of signaling intermediates which induce MAPK activity. JNK activation influences transcription through c-Jun and ATF2 transcription factors. Activation of p38 MAPK influences histone modification through MSK1/2, mRNA stability by MK2/3 and translation initiation through MNK1. Activation of ERK1/2 also influences histone modification through MSK1/2 and translation initiation through MNK1/2 and RSK.

Figure 1.3

19 The hierarchy of signaling effectors which activate the MAPKs upon type I IFN treatment follows a scheme of membrane-proximal guanine exchange factors (vav-1, C3G) (53, 54, 78) activating Rho family GTPases (eg. Rac-1, Rap-1, cdc42) (79, 80), which in turn activate MAPK kinase kinases (MAPKKK)(Raf-1, MEKK1) (81, 82), MAPK kinases (MAPKK)(MKK-3,- 4,-6) (82), followed by the MAPKs (p38, JNK, ERK) (75, 83). Similar to STAT signaling, receptor-associated JAKs initiate types I and II IFN signaling among the MAPKs (81, 84, 85). Downstream targets of the MAPKs are MAPK activated protein kinases (MAPKAPKs) which include ribosomal S6Ks (RSK), MAPK interacting kinases (MNK), mitogen and stress activated kinases (MSK) and MKs (77). Acting in concert with the mTOR/S6K pathway, RSK1 has been shown to influence mRNA translation through phosphorylation of eIF4B Ser422 which is necessary for translation initiation (86). Additionally, RSK1 has been shown to influence phosphorylation and inhibition of the tumor suppressor, PDCD4, a factor which interferes with the helicase activity of eIF4A (87). Further MAPK-mediated translational effects can be observed through the ERK1/2 dependent phosphorylation and activation of Mnk1 which regulates eIF4E mRNA binding (88). Mnk1 also positively regulates the translation of mRNA transcripts containing AU-rich elements (ARE), such as TNF-α, through the phosphorylation of a binding factor, PSF (polypyrimidine tract-binding protein (PTB)-associated splicing factor) (88). Mnk1/2 also induce Sprouty proteins which act as feedback inhibitors of p38 MAPK signaling (89). Transcriptional regulation through p38 MAPK and ERK1/2 is mediated by MSK1, which phosphorylates histone H3 and HMG- 14 (90). Further transcriptional regulation is modulated by p38 MAPK through MK2 which is necessary for ISG15 transcription (91). While not yet shown in the context of IFN signaling, MK2 has also been shown to play a role in post-transcriptional mRNA stabilization of cytokine transcripts containing AREs (92).

1.1.4.3. PI-3’K/Akt/mTOR mediated post-transcriptional regulation The PI-3’K/Akt/mTOR signaling pathway is critical to the regulation of cell growth, proliferation, survival and metabolism. Responding to growth hormone or cytokine stimulation, this pathway integrates intracellular metabolic cues of amino acid availability, ATP flux, hypoxia, osmotic stress and DNA damage, to regulate the catabolic process of autophagy and anabolic processes of translation initiation, lipid biosynthesis, transcription

20 and ribosome biogenesis, through downstream targets of mechanistic target of rapamycin (mTOR) (93, 94).

Activation of PI3’K has been demonstrated for both type I and II IFNs (95), yet there is no evidence for the engagement of this pathway by type III IFNs. Early studies delineating this signaling pathway were in the context of insulin signaling. Since then, however, a number of immune-related stimuli have been demonstrated to influence this pathway (96). Examples include T and B cell receptors (97, 98), cytokines (99), TLRs (100) and growth factors (101). The PI3’K family of lipid kinases is divided into three classes, I, II and III (102), of which, class I PI-3’Ks are intensively studied for their prominent oncogenic effect upon dysregulation. The class IA PI-3’Ks are uniquely able to generate the signaling intermediate phosphatidylinositide 3,4,5 triphosphate (PIP3) from phosphoinositide 4,5 diphosphate (PIP2) which is necessary for the recruitment and activation of Akt (103). As a heterodimer, PI-3’K is composed of a p110 catalytic domain and p85 regulatory domain. Engagement of PI-3’K by type I IFNs is initiated by Tyk2-mediated phosphorylation of the IFNAR-proximal IRS1/2, which allows binding of SH2-domain containing proteins (52). Recruitment of PI-3’K through the SH2 domain found in the p85 subunit brings it in close proximity with phospholipids of the inner membrane. Conversion of PIP2 to PIP3 facilitates binding of the pleckstrin homology (PH) domain containing Akt, and subsequent activation through phosphorylation by phosphoinositide dependent kinase1 (PDK1) (104). Full activation of Akt requires phosphorylation at Thr308 and Ser473. PDK1 mediates phosphorylation of Thr308, and mTORC2 is responsible for phosphorylation of Ser473 (105). Approximately 100 targets of Akt have been indicated in the literature, with only a subset of those having been verified independently (106). Of the many cellular processes influenced by Akt, translation initiation is regulated by Akt through multiple cooperative mechanisms. Phosphorylation and inhibition of PRAS40 and TSC2 produce a net upregulation of mTORC1-mediated translation initiation (106) (Figure 1.4).

21 Figure 1.4 Regulation of mTORC1 and mTORC2. Activation of mTORC1 and mTORC2 is regulated by different inputs. Activation of mTORC1 is sensitive to association with GTP-bound Rheb. The upstream GTPase activating protein (GAP), TSC2 is inactivated through phosphorylation by Akt, and recruitment of 14-3-3 which disrupts interaction with TSC1. TSC2 activity can be recovered by hypoxia-induced REDD1 which dephosphorylates TSC2. Akt can also induce mTORC1 activity by phosphorylation of the inhibitory protein, PRAS40, and recruitment of 14-3-3. Feedback inhibition of Akt activity occurs through mTORC1 mediated phosphorylation and inhibition of IRS1/2. mTORC1 is also be inhibited effectively by AMPK through phosphorylation of RAPTOR and recruitment of 14-3-3 which interferes with S6K and 4E-BP binding sites. In addition to regulating downstream translation initiation, mTORC1 also regulates activation of different transcription factors. Activation of S6K also regulates mTORC2 activity through phosphorylation of RICTOR and mSIN1. Activation of mTORC2 is influenced by direct interaction with TSC1/2 and results in phosphorylation of Akt, SGK1 and PKCα. Akt further activates mTORC1 signaling, while SGK1 and PKCα regulate cell survival, metabolism and cytoskeletal dynamics.

22 Figure 1.4

Akt mediated phosphorylation of the proline-rich Akt substrate 40kDa (PRAS40) causes its dissociation from the mTORC1 complex, thereby relieving its inhibitory effect (107). As a GTPase activating protein (GAP), inhibition of TSC2 by Akt-mediated phosphorylation enhances its interaction with the inhibitory protein 14-3-3, and prevents downstream GTPase activity of ras homolog enriched in the brain (Rheb) (108, 109). Bound to GTP, Rheb is able to associate with mTORC1 and increase its kinase activity (107). Opposite this effect, active TSC1/2 is able to directly associate with mTORC2 and enhance its activity (108). In both cases, feedback signaling occurs, where mTORC1 mediated serine phosphorylation of IRS-1 is inhibitory, and mTORC2 mediated phosphorylation of Akt at Ser 473 is activating (108).

An additional target of Akt is glycogen synthase kinase 3β (GSK3β). The constitutive inhibitory kinase activity of GSK3B is repressed by insulin signaling via Akt-mediated phosphorylation at Ser9 (110). IFN-β has also been shown to regulate GSK3β phosphorylation at Ser9. Downstream targets include glycogen synthase (GS), which modulates glucose homeostasis; kinesin light chains (KLCs), involved in intracellular glucose transporter localization (111); and eIF2B, a guanine exchange factor (GEF) necessary for translation initiation (110, 112). Phosphorylation of GS by GSK3β is inhibitory, and leads to reduced incorporation of glucose into stored glycogen. Phosphorylation of KLCs is also inhibitory, and impedes anterograde vesicle transport. Phosphorylation of eIF2B is inhibitory, and prevents formation of the eIF2-GTP-Met-tRNA (ternary complex).

1.1.5. Negative Regulation of IFN signaling An important element of IFN signaling is feedback inhibition, which prevents excessive inflammation, and is exerted at different levels in the signaling cascades (113). At the level of IFNAR, cell surface expression of IFNAR1 is regulated by several ligand-dependent and - independent mechanisms of receptor modification which mediate endocytic and proteasomal degradation (114, 115). Engagement by type I IFNs increases the rate of receptor internalization, thereby resulting in proteasomal degradation of IFNAR1. This

24 effect is mediated by the E3 ubiquitin ligase, SCF(βTrCP2), which is dependent upon PDK2- mediated Ser535 phosphorylation of IFNAR1 (116). Additionally, p38-MAPK has been implicated in ligand-independent ubiquitination and degradation of IFNAR1 (117). The ubiquitin-specific protease UBP43 (USP18), which modulates ISG15 conjugation, has also been demonstrated to interact with IFNAR2 and interfere with JAK-receptor interactions (118). Mice lacking UBP43 are hypersensitive to type I IFNs, as evidenced by rapid lethality following injection with the type I IFN inducer poly I:C (119).

Suppressors of cytokine signaling (SOCS) -1 and -3 are a part of an 8-member family of SOCS proteins, and are important in providing negative feedback for JAK/STAT signaling induced by type I and II IFNs (120, 121). Indeed, their expression is IFN-inducible, as reflected by the presence of STAT1 and STAT3 binding sites in their promoters. Their mechanisms of action differ slightly, with SOCS-1 binding Tyk2 through its SH2 domain, thereby inhibiting kinase activity, and SOCS-3 binding the phosphorylated receptor, possibly interfering with STAT binding or Jak kinase activity (120, 122). SOCS proteins are further involved in influencing the ubiquitination-mediated degradation of various receptor-associated signaling effectors such as Jak2, Vav and IRS proteins (123-125). Additionally, SOCS proteins are themselves regulated, both positively and negatively: Pim kinases improve the stability of SOCS1, and microRNA-155 downregulates expression of SOCS1 (126, 127). Given the number of regulatory targets that SOCS proteins govern in IFN signaling, it is not surprising that mice lacking SOCS1 succumb to severe multi-organ inflammation shortly after birth (128), and mice lacking SOCS3 are embryonic lethal (129).

While greater than 100 phosphatases have been identified in the human genome (130), a number have been demonstrated to influence IFN signaling. At the receptor level, Src Homology-2 protein tyrosine phosphatase-1 (SHPTP1/SHP-1) is able to associate with IFNAR and desphosphorylate Jak1 specifically, having minimal effect on Tyk2 phosphorylation (131). Interestingly, SHPTP2/SHP-2 plays a dual role of both positively regulating signaling at the receptor level and in the nucleus, where it dephosphorylates STAT1 (132, 133). PTP1B influences both type I and II IFN signaling through its regulation

25 of JAK2 and TYK2 dephosphorylation (134). T-cell PTP (TC-PTP) can also regulate STAT1 dephosphorylation in the nucleus (135) and Jak1 in the cytosol (136).

STAT signaling is also influenced by members of the protein inhibitors of activated STAT (PIAS) family of E3 ubiquitin-like ligases which have been shown to influence more than 60 proteins (137). STAT1 is specifically inhibited by PIAS1-mediated sumoylation, resulting in reduced DNA binding ability. In contrast to ubiquitination, this covalent modification is reversible by the isopeptidase SENP1 (138). Interestingly, PIAS1 has also been shown to regulate PTP1B activity, thereby indirectly influencing IFN signaling (139). PIASγ behaves as a transcriptional repressor of STAT1 without inhibiting its DNA binding ability (140).

26 1.2 mTOR and Metabolism

1.2.1 mTOR signal integration (amino acid, energy, stress and oxygen) The ability of mTOR to appropriately regulate catabolic and anabolic processes is influenced at multiple levels. Energy balance within a cell is critical to cell survival and is sensed through the heterotrimeric AMP-activated protein kinase (AMPK). Rather than sensing absolute quantities of ATP within the cell, AMPK senses the relative ratio of AMP or ADP:ATP at the regulatory gamma-subunit, and is activated by high ratios of AMP or ADP:ATP (141). Activation of AMPK requires both binding of AMP or ADP and phosphorylation at Thr172. Phosphorylation by upstream kinases LKB1 or CaMKKa/B are necessary to activate AMPK by phosphorylation (142). LKB1 and CaMKKB (CaMKK2) are consitutively active, whereas CaMKKa (CaMKK1) activity is influenced by intracellular increases in Ca2+ (142). Physiological and environmental factors that activate AMPK include heat shock, oxidative stress, osmotic stress, hypoxia, low glucose and exercise (muscle) (143). AMPK activation is also influenced by a variety of chemical compounds that inhibit mitochondrial function and respiration. Modulation of AMPK signaling has been a focus of type II diabetes research, since insulin sensitivity is improved with AMPK activation. Compounds used in the clinic include the antidiabetic biguanide drugs metformin (144) and phenformin (145), and thiazolidindiones, rosiglitazone (146) and pioglitazone (147). The first downstream targets of AMPK were identified using the synthetic activator, 5-aminoimidazole-4-carboxamide riboside (AICAR), which converts to an AMP analogue, AICAR monophosphate (ZMP) upon cellular uptake (148). AMPK mediated inhibition of both acetyl-CoA-carboxylase (ACC) and 3-hydroxy-3-methylglutaryl- CoA-reductase (HMG-CoA) resulted in reduced fatty acid and cholesterol synthesis (148). Additional downstream targets include glucose transporters (GLUT1, 4), phosphofructokinase-2 (PFK-2), hexokinase 2 (HK2) and fatty acid translocator (FAT/CD36), which are upregulated to increase ATP synthesis derived from glycolysis and fatty acid oxidation (143, 149). Transcriptional targets also influence mitochondrial biogenesis (143). An important downstream target of AMPK is TSC2 which inhibits mTOR activity. Phosphorylation of TSC2 at Thr1227 and Ser1345 increases its GAP activity, thereby inhibiting mTORC1 activation through conversion of RHEB-GTP to RHEB-GDP.

27 Additionally, AMPK mediates phosphorylation of Raptor, and subsequent mTORC1- inhibiting recruitment of 14-3-3 (150).

Regulation of mTORC1 is also influenced by DNA-damage and reactive oxygen or nitrogen species (151, 152). Activation of ataxia-telangiectasia mutated (ATM) protein kinase by double stranded DNA breaks or oxidative/nitrosative stress (ie H2O2, NO) regulates the G1/S cell cycle checkpoint through phosphorylation of p53, and checkpoint kinase 2 (CHK2) (153). ATM also activates AMPK in an LKB1 dependent manner, thereby inhibiting mTORC1 activation (153). ATM has also been shown to transiently de-repress protein translation by phosphorylation of 4E-BP1 at Ser111 in response to ionizing radiation (154). This rapid response results in expression of a variety of DNA repair proteins.

Oxygen sufficiency is necessary for maintaining oxidative phosphorylation which produces the most ATP per molecule of glucose. In circumstances of reduced oxygen availability, cells respond by decreasing oxygen consumption through inhibition of oxidative phosphorylation, and also limiting ATP consuming anabolic processes such as protein synthesis (155-157). The transcription factor hypoxia inducible factor-1α/β (HIF1-α/β) is a dimer that is sensitive to the presence of oxygen in the cytosol. During normoxia, HIF1α is hydroxylated and degraded through ubiquitinylation (155). However, under hypoxic conditions, the HIF1 heterodimer is stabilized, and induces transcription of various metabolic genes which promote glycolytic metabolism (158). Inhibition of protein synthesis is achieved through the hypoxia-inducible regulated in development and DNA damage-1 (REDD1). REDD1 dissociates 14-3-3 from TSC2, thereby inhibiting mTORC1 activity (109, 159). Alternately, rapid inhibition of mTORC1 is REDD1-independent, and occurs via AMPK activation as influenced by reduced ATP production from oxygen- sensitive oxidative phosphorylation (157). Interestingly, hypoxia mediated inhibition of mTORC1 and protein synthesis is dominant over growth factor stimulating signaling (160).

Also necessary for cell growth is the availability of amino acids for integration into nascent proteins. mTORC1 localization and subsequent activity is governed by obligate heterodimers of the GTPase proteins, RagA/B and RagC/D. Although not entirely clear how

28 amino acids influence Rag activity, it is known that a multimeric protein complex forms between GTP-bound Rag dimers, lysosomal associated Ragulator, vacuolar-ATPase and mTORC1 (161, 162). This complex is brought in proximity with RHEB, and is subsequently activated.

In response to limited nutrient availability, cells are able to recycle cellular components through a conserved process known as macroautophagy (referred to as autophagy) (163). In nutrient rich conditions where mTORC1 is active, Ulk1/2 are phosphorylated and inhibited. However, when mTORC1 signaling is reduced, inhibitory phosphorylation is relieved by phosphatases, and Ulk1/2 are activated by AMPK-mediated phosphorylation (164). Ulk1/2 activation is necessary for the formation of the nascent double membrane autophagosome, and requires the sequential association of multiple ATG (autophagy gene) subunits (165). Mature autophagosomes are then fused with lysosomes, where the enclosed contents are degraded. Beyond the function of recycling cellular components, autophagy also plays important roles in both innate and adaptive immunity. Autophagy also exhibits interplay with the proteasomal pathway to process antigens for presentation on MHC-I and MHC-II (166). Early studies highlighted the importance of autophagy in protection against intracellular bacteria infection (167). Autophagy also plays an important role in host defense and recognition of viral pathogens. During infection of pDCs with vesicular stomatitis virus (VSV), autophagosome processing of viral particles is necessary for downstream TLR7 recognition of viral RNA and induction of IFN-α (168). Certain viruses, such as HSV-1, antagonize autophagy by interfering with PKR-mediated eIF2a phosphorylation and consequently inhibiting autophagosome formation (169). Alternately, some positive sense RNA viruses instead induce autophagosome membranes as a platform for virus replication, and also interfere with maturation of autophagosomes to the stage of degradation. Examples of viruses benefiting from autophagy induction include, Denguevirus, Hepatitis C virus, SARS-CoV, Influenza virus A, Poliovirus and Coxsackievirus B3 (170-172). Experimental downregulation of different ATGs using siRNA has also reduced viral replication (173, 174). It is thought that the immature autophagosomes shield replicating RNA viruses from detection by dsRNA sensitive PKR (172).

29 1.2.2. mTOR-mediated translational regulation Belonging to the phosphoinositide 3’-kinase (PI3’K)-related kinase (PIKK) family, mTOR (mechanistic target of rapamycin) is a serine/threonine kinase with multiple downstream targets (94). Specificity towards those targets is determined by mTOR-associated factors (175). Two functionally distinct high molecular weight mTOR complexes have been identified, mTORC1 and mTORC2, which are composed of six and seven subunits respectively (Figure 1.4). Common to both complexes are mTOR, mLST8, DEPTOR and Tti/Tel2. Unique components of mTORC1 include RAPTOR and PRAS40, whereas the mTORC2 complex is distinguished by the presence of RICTOR, mSin1 and protor1/2 (107). Downstream targets of mTORC1 include two regulators of translation initiation, 4E-BP1 and S6K, as well as other transcription factors such as HIF1α, PPARα/γ, STAT3, SREBPs, PGC1α/YY1 and TFEB which influence a variety of metabolic processes such as cell survival, growth and proliferation (176). Unique targets of mTORC2 are Akt, PKCα and SGK1, which influence cell survival, metabolism and cytoskeletal dynamics (107). Specific inhibition of mTORC1 by rapamycin is owing to the mTORC1-inhibitory complex formed between rapamycin and FK506 binding protein-12 (FKBP-12), which disrupts mTOR interaction with RAPTOR (177). Discovered as a bacterially derived anti-fungal molecule from Easter Island (Rapa Nui), rapamycin and its synthetic derivatives have been used as immunosuppressants and anti-cancer agents (178). While mTORC2 is considered rapamycin-insensitive, it has been shown that prolonged treatment of cells at high doses does result in inhibition of mTORC2. This is likely due to the cross-talk observed between the two pathways.

Activation of mTORC1 influences translation initiation through the phosphorylation of 4E- BP1 and S6K. Both contain target of rapamycin signaling (TOS) motifs which are necessary for their interaction with raptor and mTOR (179). The translational repressor, 4E-BP1, was originally identified as a small 10-12 kDa phosphorylated heat and acid stable protein (PHAS-1) that is sequentially phosphorylated at multiple serine and threonine residues upon insulin stimulation, resulting in dissociation from eIF4E (180-184). Seven phosphorylation sites are found in 4E-BP1, four of which have been shown to be regulated and necessary for influence on translation initiation (185). Phosphorylation of two priming

30 sites (Thr36/45) is necessary for the subsequent phosphorylation of Thr69 and Ser64 which mediate release from eIF4E (186). While mTORC1 is considered the predominant regulator of 4E-BP phosphorylation, Mnk1 has also been shown to phosphorylate Ser65 (in human cells) (187). The same study also illuminated a mechanism whereby Mnk1 regulates Ser209 phosphorylation of eIF4E which interferes with 4E-BP binding. Three 4E-BPs (4E- BP1/2/3) have been identified with varied tissue distributions (188, 189). Notably, 4E-BP1 is expressed at higher levels in skeletal muscle, pancreas, liver and heart tissue. Mice lacking 4E-BP1 have been shown to have less white fat tissue, and enhanced metabolism (190). Mice lacking both 4E-BP1/2 were more resistant to viral infection as a consequence of enhanced IRF7 expression in plasmacytoid cells, and subsequent IFN-α expression (191).

Since predominant regulation of protein synthesis occurs at the point of translation initiation, there are a number of steps influencing the association and activation of necessary eukaryotic initiation factors (eIFs). One rate limiting step in protein synthesis is the sequestration of the eukaryotic initiation factor 4E (eIF4E) by 4E-binding proteins (4E- BPs) which inhibit efficient binding to the scaffolding protein eIF4G and association with 5’-m7GTP-capped mRNAs (192) (Figure 1.5).

Figure 1.5 IFN-α/β regulated translation initiation. IFN-α/β induced signaling through PI3’K/mTOR leads to hyperphosphorylation of 4E-BP1 thereby releasing it from eIF4E. Recruitment of the large scaffolding protein, eIF4G, and ATP-dependent RNA helicase, eIF4A, forms the eIF4F complex. Recognition of the 5’m7- GTP-capped mRNAs by eIF4E leads to the melting of secondary RNA structure found in the 5’ UTR. The activated mRNA/protein complex then binds the multisubunit 43S preinitiation complex through interactions between eIF4G and eIF3. ATP-dependent scanning identifies the AUG start codon, and releases tRNA-associated eIF2α-GTP through GTP-hydrolysis. Formation of the ternary complex (TC) from recycled eIF2α is necessary for translation initiation, and is negatively regulated by eIF2α kinases (eg PKR).

Figure 1.5

Free eIF4E is also a limiting factor in translation initiation since it is less abundant than other initiation factors. Interestingly, increased expression of eIF4E is observed in 30% of malignancies, and is an indicator of poor prognosis (193). The complex formed by eIF4E/4G/4A is termed eIF4F. Phosphorylation of eIF4B through either mTOR or MAPK influences its association and stabilization of eIF4A (194). Secondary structure often found in the 5’ untranslated region of capped mRNAs is unwound by the ATP-dependent eIF4A helicase to provide single stranded mRNA for the recruitment and binding of the small ribosomal subunit as mediated by eIF3. Additionally, the poly-A binding protein (PABP) is associated with poly-adenylated 3’-tails of mRNAs and binds to eIF4G, thus creating a stable circular structure (195).

Prior to the recruitment of the mRNA/protein complex, formation of the 43S pre-initiation complex (PIC), containing eIF-1,-1A,-2,-3 and -5, MET-tRNAi and 40S ribosomal subunit is required. Assembly of the PIC is dependent upon association of the ternary complex with the 40S ribosomal subunit. The ternary complex is comprised of eIF2-GTP and MET-tRNAi, and is a critical point of regulation influenced by kinases such as PKR, PERK, GCN2 and HRI (196). PKR (RNA-dependent protein kinase) is responsive to cytosolic dsRNA, a hallmark of many replicating viruses, and is an IFN-inducible antiviral effector (44). PERK (PKR-like endoplasmic reticulum kinase) is induced during ER stress. GCN2 (general control non- derepressible 2) is a sensitive to a variety of stresses, including amino acid insufficiency. GCN2 is activated by the presence of uncharged tRNAs, and limits protein synthesis cooperatively with mTORC1 (197). HRI (haem-regulated inhibitor) is important in erythroid cells, and senses haem-deprivation, oxidative and heat stresses (198).

The multi-subunit guanine exchange factor (GEF), eIF2B, acts on eIF2 to promote an active GTP-bound state. However, phosphorylation of the alpha subunit of eIF2 at Ser51 increases its inhibitory function towards eIF2B (199). Consequently, eIF2-GDP accumulates thereby inhibiting formation of the ternary complex. Interestingly, during this translation limiting step, a small proportion of mRNAs are translated which are involved in mediating a stress response. The transcription factor ATF4 is translated, and subsequently induces

34 transcription of genes governing nutrient uptake, metabolism, redox status and apoptosis (199).

A number of genetic studies have been undertaken to evaluate the influence of the PI- 3’K/Akt/mTOR pathway on a type I IFN mediated antiviral response. MEFs lacking the p85α/β subunits of PI-3’K were less responsive to treatment with IFN-α during virus infection, as a consequence of an impaired ability to induce translation (200). Similarly, MEFs lacking Akt1/2 isoforms were also less responsive to IFN-α treatment, and more susceptible to virus infection, as a consequence of reduced translation capacity (201). The inhibitory effect of TSC2 in type I IFN signaling was apparent in MEFs lacking TSC2 that were more sensitive to IFN-α/β treatment, as shown by increased translation of an antiviral protein, ISG15, and decreased susceptibility to virus infection (202). In the same study, a parallel observation showed that MEFs lacking 4E-BP1 were also more sensitive to IFN-α treatment and less permissive to virus infection (202).

35 1.2.3. mTOR effects on cellular immunity The use of rapamycin, and its analogues (Sirolimus, Temsirolimus, Everolimus and Deforolimus) as immunosuppressants has yielded insights into their wider effects on immune cell function. Specifically, it has been appreciated that both mTORC1/2 complexes influence T-cells and B-cells, γδ T-cells, macrophages, neutrophils, mast cells, natural killer cells and dendritic cells, beyond the effect of merely regulating cell proliferation (162, 203).

1.2.3.1 mTOR effects on T cells For T-cell differentiation upon stimulation, mTOR has been proposed to integrate multiple extracellular cues to modulate co-stimulation (‘signal 2’) during T-cell stimulation (204). mTOR is able to influence the expression of different transcription factors such as T-bet, RORγt and GATA-3, which are necessary for skewing of Th1, Th17 and Th2 phenotypes, respectively (162). Stimulation of either naïve CD4 T cells in the presence of rapamycin and TGF-β, or transgenic mTOR hypomorphs, leads to the generation of FoxP3+ regulatory T cells (Tregs) (162). Cells deficient in mTOR activity also fail to differentiate to Th1, Th2 or Th17. This is thought to be an effect of dual inhibition of mTORC1/2. Generation of RHEB deficient CD4 T cells, which specifically inhibited mTORC1 activity, yielded a failure to develop Th1 and Th17 cells, but maintained ability to skew towards Th2 (205). Conversely, CD4 T-cells lacking Rictor, an essential component of mTORC2, failed to differentiate toward a Th2 phenotype, whereas they were able to maintain Th1 and Th17 phenotypes following stimulation (205). These effects were strongly dependent on transcription factor expression, as seen by low T-bet and RORγt expression, and high GATA-3 expression in RHEB deficient cells. Similarly, Rictor deficient cells expressed the opposite pattern of transcription factors (205). In CD8+ T cells, mTOR also affects memory cell development. During infection with LCMV, rapamycin treated mice produced an enhanced virus-specific CD8+ T cell response along with an increased pool of memory cells, owing to improved survival during the contraction phase (206).

In addition to T-cell differentiation, mTOR signaling is also able to influence cellular trafficking and effector function. During an immune response, levels of CD62L and CCR7 dictate T cell homing to lymph nodes. Activation of PI-3’K/mTOR signaling has been shown

36 to decrease their surface expression thereby favouring egress from lymph nodes upon activation, and migration to peripheral tissues (207). Additionally, the chemotactic response of activated T-cells through CCR5 signaling has been demonstrated to be mTOR dependent (208). Sphingosine-1-phosphate (S1P) signaling through S1P-receptors via mTOR also influences the migration of a wide variety of cells, including T-cells, NK-cells, monocytes, macrophages, neutrophils, dendritic cells, eosinophils and mast cells (209).

1.2.3.2. mTOR effects on dendritic cells Critical to orchestrating an effective cellular immune response, dendritic cells are sources of type I IFN, and modulate antigen presentation, co-stimulation and instruction of T-cells. Production of type I IFNs by plasmacytoid dendritic cells (pDCs) is inhibited by rapamycin through disruption of the MyD88-TLR9 complex which is necessary for IRF-7 activation (210). Myeloid DCs treated with rapamycin produced a tolerogenic DC phenotype resistant to maturation, which were able to reduce alloantigen T-cell proliferation and IFN-γ production. Indeed, skewing of T-cells to a regulatory T-cell phenotype has been experimentally shown to inhibit graft-versus-host disease (GVHD) with improved graft survival in the absence of immunosuppression (211, 212). Pro-inflammatory responses of DCs to TLR stimuli are increased in hypoxic conditions as mediated by hypoxia inducible factor-1 alpha (213). This effect is blunted through inhibition by rapamycin, and may play a role in reducing ischemia/reperfusion injury seen in solid-organ transplants and myocardial infarction (214). Additionally, mTOR has been shown to influence the balance of IL-12/IL-10 produced by DCs in response to TLR stimuli, with inhibition of mTOR producing more IL-12 (215).

1.2.3.3. mTOR effects on monocyte/macrophages In macrophages, inhibition of mTOR reduces LPS-inducible nitric oxide (NO) production through impairment of IFN-β mediated autocrine signaling (216). Treatment of peritoneal macrophages with rapamycin reduces LPS inducible IL-10, and increases TNF-α expression (217). Interestingly, in the context of adipose tissue macrophages (ATMs) polarization is influenced by mTORC1 activation. Activation of mTOR skews cells toward a proinflammatory M1 phenotype, whereas inhibition of mTOR signaling produces an anti-

37 inflammatory M2 phenotype (218). Downstream of PRR signaling in bone marrow derived macrophages (BMDM), mTOR activity inhibits activation of caspase-1, thereby limiting production of bioactive IL-1β (219). Treatment of monocytes with LPS and rapamycin inhibited upregulation of PD-L1 and CCR5, but did increase levels of co-stimulatory CD86 and CCL22, a T cell chemoattractant. Co-culture with allogenic T cells resulted in Th1 and Th17 polarization, as indicated by IFN-γ and IL-17 cytokine production (220).

1.2.3.4. mTOR effects on B cells B cell development and function can also be affected by mTOR signaling. Developmentally, mTOR has been shown to influence the expression of rag1, 2 and IL-7 receptor genes, through phosphorylation and inhibition of the FoxO1 transcription factor. Treatment of B- cells with rapamycin, or in cells lacking sin1, an increased expression of rag1, 2 and IL-7 receptor is detected (221). Consequently, enhanced pro-B-cell survival and V(D)J recombination occurs. The IL-7 mediated survival signal for developing T- and B-cells is also mTOR-dependent (222). B cell receptor stimulated cells require signaling through the PI-3’K/mTOR pathway to survive and proliferate (223).

1.2.3.5. mTOR effects on Natural Killer cells In a liver allograft model, treatment with rapamycin was inhibitory for NK cell proliferation, as evidenced by a failure to progress from the G1 to S phase of the cell cycle. NK cells also exhibited blunted cytotoxic effector function (224). Similarly, in mice treated with rapamycin, reduced proliferation of NK cells was observed, along with impaired IFN-γ and granzyme B expression, which resulted in increased CMV burden (225).

Taken altogether, mTOR signaling contributes to the development and function of different immune cells.

38 1.3. IFNs and Antiviral Immunity IFNs have long been known to exert antiviral effects towards a variety of viruses. Their broad spectrum activity has been demonstrated through the regulation of intracellular antiviral proteins, as well as the activation of different immune cells. Not surprisingly, viruses also possess a variety of antagonistic mechanisms which directly interfere with antiviral proteins, and resist elimination by the immune system.

1.3.1. Influenza Virus Influenza viruses are a group enveloped negative sense (-) ssRNA viruses belonging to the Orthomyxoviridae family (226). Disease caused by influenza viruses is respiratory in nature, exhibited as fever and cough (227). Seasonal influenza is usually self-limiting, without severe consequences. Classification of these viruses is based on antigenic differences in proteins found in the virions. Influenza virus types A, B and C are differentiated based on their nucleoprotein (NP) and matrix (M) proteins (226, 228). The most studied of these viruses are the type A viruses, which cause seasonal outbreaks, and infrequently cause more severe pandemics. Type A viruses are typed based on their membrane glycoproteins, hemagglutinin (H) and neuraminidase (N) (229). Viral infection begins with hemagglutinin recognition of sialic acid residues that are specifically conjugated to galactose on glycoproteins and glycolipids present on cell membranes. Recognition of the sialic acid linkage to galactose is a strong determinant for the infectivity of influenza viruses among different species (229). Receptor mediated endocytosis projects viral particles towards gradually acidified endosomes where pH-sensitive conformational changes to the structure of hemagglutinin facilitates uncoating of the viral RNA and associated ribonucleoproteins (RNPs) (226). Transport to the nucleus for mRNA synthesis is mediated by RNPs which bear nuclear localization signals. Three RNA dependent RNA polymerase (PB1, PB2, PA) subunits which are part of the RNP complex are responsible for replicating vRNA via complementary RNA (cRNA) and generating capped and polyadenylated mRNA for protein expression (230). Capping of viral mRNA is termed ‘cap snatching’ as PA endonuclease activity cleaves the 5’m7GTP caps of nascent cellular pre-mRNAs and uses them as primers for positive sense mRNA transcription (231). Both vRNA and mRNAs are exported from the nucleus to the endoplasmic reticulum (ER) where protein synthesis occurs. Post-

39 translational modification and virion packaging is facilitated in the Golgi apparatus (229). Mature virions are enveloped, containing 8 genomic vRNA segments, and bud from the cell surface. Among the 10 gene products of type A influenza viruses, the non-structural protein-1 (NS1) is most critical for antagonizing host immunity (232, 233). To facilitate viral replication, NS1 is abundantly expressed in cells and successfully antagonizes a number of different intracellular host defences. Since host recognition of influenza virus relies largely upon detection of pathogen associated molecular patterns e.g. vRNA motifs, NS1 is able to interfere with this process. Sequestration of dsRNA by NS1 prevents recognition and activation of PKR and 2’5 OAS, thereby preventing their antiviral functions (234, 235). Additionally, NS1 inhibits ubiquitination of RIG-I, which is necessary for its 5’- triphosphate RNA dependent activation of downstream MAVS and IRF3 (236). Along with PA-mediated cap-snatching, NS1 also antagonizes host mRNA processing and poly(A) mRNA export from the nucleus, consequently inhibiting IFN-α/β and ISG expression (237). Interactions between NS1 and host eIF4G and the poly(A) binding protein (PABP) have been shown to promote virus-specific mRNA translation (238). NS1 also interacts with p85 through its SH2 domain, resulting in activation of PI-3’K (239). Notably, NS1 also impedes IFN-α/β signaling through interactions with components of the JAK-STAT signaling cascade (232).

1.3.2. Vaccinia virus Vaccinia virus (VACV) is a large enveloped dsDNA virus belonging to the Poxviridae family of viruses, and is closely related to variola virus (smallpox virus). Consequently it was used in the vaccine which was instrumental in eradicating smallpox (240). Much of our understanding of poxviruses has arisen from studies of VACV. Infectious virions exist in two forms, with the nucleoprotein core enclosed in a single membrane, termed mature virion (MV), or enclosed in a double membrane, termed the enveloped virion (EV). The different forms arise from alternate modes of viral release from cells. EVs bud from cells, whereas MVs are released by cell lysis. MVs are both more abundant, and more stable, and thus have been most commonly used experimentally. Infection of MVs occurs preferentially through endocytosis, and less frequently by direct membrane fusion (241). The large genome size of poxviruses has accordingly produced a large number of proteins from

40 approximately 200 open reading frames (ORFs) that are involved in viral replication and host-antagonism (242, 243). This is reflected in the complexity of different stages of the viral life cycle. Certainly, during viral entry this is evident as VACV utilizes 12 proteins in membrane fusion, a process for which other enveloped viruses typically only use one or two glycoproteins (244). Following this, VACV is an unusual DNA virus in that it replicates in the cytoplasm, instead of the nucleus where most DNA viruses replicate. Transcription is tightly regulated, and can be delineated by early, intermediate and late periods of expression. Early transcription occurs entirely within the virion core by packaged RNA processing proteins, with mRNAs exported to the cytoplasm where they associate with polyribosomes (245). Nearly half of the genome is transcribed and translated at this stage, with resultant proteins involved in nucleotide biosynthesis, DNA replication, intermediate gene transcription and host-evasion (246). Following DNA replication, intermediate transcription occurs. These proteins are involved in DNA binding and core packaging (243). Finally, late transcripts are predominantly associated with virion assembly and budding (243). Interestingly, the viral life cycle occurs rapidly, with infectious virions (MV) budding from cells within 12 hours of infection. Intracellular infectious virions (EV) can be detected within 6 hours of infection (247).

The large size of poxvirus genomes provides the capacity for producing host-antagonistic proteins. Indeed, many such proteins have been identified. Secreted proteins have been shown to antagonize IFNs, cytokines, chemokines and complement (248). Decoy receptors have been identified in VACV that bind soluble IL-1β, TNFα, IFN-α/β and IFN-γ (249, 250). Inhibitors of complement have also been demonstrated to influence viral infectivity in vivo (251). Viral interference with chemokine activity has also been shown for the secreted proteins VACV chemokine-binding protein (vCKBP) and VACV CC chemokine inhibitor (vCCI) which interact with a number of CC-class chemokine (252). Synthesis of these cytokines and chemokines is also impaired through blockade of different signaling pathways regulated through NFkB, IRF or STAT signaling (250, 253). Interestingly, the virally encoded phosphatase, VH1, is incorporated into virions and is an effective inhibitor of both IFN-α/β and IFN-gamma signaling following infection (254). A consequence of this inhibition impairs not only ISG expression, but has also been shown to inhibit antigen

41 presentation through reduced expression of MHCII (255). A number of anti-apoptotic viral Bcl-2 homologues have also been identified which exert pro-survival effects on infected cells (256). VACV encoded serine protease inhibitor (serpin) homologues also exert an anti- inflammatory effect through inhibition of different caspases, including caspase-1 which is necessary for activation of IL-1β (257). E3L is another virally encoded protein with multiple host-antagonistic functions. With both RNA and DNA binding capacity, E3L inhibits PKR, 2’5 OAS and DAI (DNA-dependent activator of IFN) activation through sequestering nucleic acid motifs (258). E3L also interacts with and inhibits ISG15 activity (259). Additionally, PKR-mediated effects on translation are also abrogated by a virally encoded protein, K3, which behaves as an eIF2a pseudo-substrate through association with PKR (253).

1.3.3. Coxsackievirus The Picornaviridae (small RNA virus) is a family of human and animal viruses containing a number of medically important human pathogens. Notably, within the Enterovirus genus, serotypes of Poliovirus, Rhinovirus, Enterovirus and Coxsackievirus can be found. As suggested by the name, Enteroviruses gain entry via the gastrointestinal tract where the robust pH-stable virions infect intestinal lymphoid cells found in Peyer’s patches (260, 261). Specifically, in vivo evidence suggests B-cells as significant carriers of virus in the circulation to secondary sites of infection (261). Virions are spherical non-enveloped particles approximately 30nm in diameter (262). Receptor mediated entry of virions induces conformational changes in the capsid, thereby releasing viral RNA directly into the cytoplasm (263). The genome of Picornaviruses are conserved across species and are composed of a single stranded positive sense RNA approximately 7 kb in length, and contain a single ORF encoding one polyprotein (263). Post-transcriptional proteolytic processing yields 12 mature proteins which include structural and non-structural components that are necessary for viral replication and host-antagonism. Located in the 5’ UTR of the viral genome, the internal ribosome entry site (IRES) facilitates cap- independent RNA translation. Proteolytic cleavage of eIF4G by viral protease 2Apro produces selective shutoff of host mRNA translation (264-266). The 3Cpro has been shown to cleave TRIF and MAVS, thereby interfering with induction of type I IFNs via RLRs (RIG-I

42 and MDA5) and TLR3 and also impairing induction of apoptosis (267). Indeed, MDA-5 has been shown to be a strong determinant for mounting an effective type I IFN response to infection with CVB (268). Additional inhibition of apoptosis is mediated by 2BC, which associates and impairs cleavage of caspase-3 (269). Observations have also indicated that CVB and other Enteroviruses induce immature autophagosomes for efficient replication, and possibly as a mechanism of escaping TLR mediated recognition of viral RNA, and impeding MHC antigen presentation (270). Poliovirus proteins 2BC and 3A expressed in cells in the absence of replicating virus is sufficient to induce ultrastructural changes reflective of autophagy (271).

The range of disease severity caused by Enteroviruses extends from a mild, common cold to acute flaccid paralysis. Enterovirus infections are very common, and do not usually lead to severe disease. For instance, even during infection by poliovirus, only 1% of those infected develop paralysis (272). Although often causing mild symptoms, the Coxsackievirus serotypes can cause serious disease and infect the heart, pancreas and central nervous system. They are linked to diseases such as type I diabetes, acute and chronic viral myocarditis, which can lead to dilated cardiomyopathy (DCM) (263). Due to complications of congestive heart failure and arrhythmias, diagnosis of DCM indicates a 5 year survival rate of 50% (273). Young children and infants are particularly sensitive to infection by enteroviruses, and myocarditis among individuals less than 40 years of age accounts for 20% of sudden unexpected deaths (274, 275). It has also been shown that Coxsackieviruses account for >85% of aseptic meningitis in newborns and infants (276). Since these infections are often sub-clinical, the prevalence of viral myocarditis is likely under-reported. A study of nearly 13000 autopsies revealed lymphocytic myocarditis in 1% of cadavers (277). In cases of chronic disease, such as viral myocarditis or type I diabetes, the initial viral infection can be sub-clinical, yet it has been shown that auto-antibodies arise in patients, and that these are related to autoimmune disease (278-281). A mechanism of molecular mimicry has been suggested whereby viral antigens bear similarity to autoantigens, however, this remains to be shown definitively (282, 283). It is, however, understood that a significant role is played by the adaptive immune response in the progression from viral infection to post-inflammatory dilated cardiomyopathy (DCM). In

43 murine models of CVB-induced myocarditis, disease is less severe in animals depleted of T- cells, athymic animals or animals with blocked T-cell activation (284, 285). Concordant with this, patients diagnosed with lymphocytic myocarditis and treated with immunosuppressants show improved cardiac function (286). Similarly, adoptive transfer of regulatory T cells (Tregs) into infected mice reduces the severity of myocardial inflammation (287). Administration of inflammatory agents such as LPS, IL-1 or TNFα can overcome resistance to CVB infection in mice, and induce disease (288). Treatment of susceptible mice with IL-1 or IL-2 can enhance CVB3-induced myocarditis (289). While excessive inflammation exacerbates CVB-induced myocarditis, B cells appear to be critical for limiting viral infection (290). In B cell deficient mice, animals are unable to resolve CVB3 infection. Transfer of B cells from CVB3 immune mice to B cell deficient infected mice is able to resolve disease (290). Interestingly, in CVB infection a notable sex bias has also been observed in Balb/C mice whereby males are more susceptible to infection as a consequence of mounting strong Th1 responses. Indeed, female mice which produce an IL- 4 Th2 mediated response show reduced myocarditis (291, 292). However, this response appears to be most important during acute infection, since a prolonged Th2 response appears to be pathogenic resulting in chronic myocarditis (293).

While the adaptive immune response during viral myocarditis was a focus of early studies, it has become clear that an effective innate immune response is critical for elimination of CVBs. An immediate type I IFN response is critical to host survival as evidenced by the multiple host antagonizing viral proteins discussed above. This is highlighted by genetic studies, where either the IFNAR or IFN-β genes were targeted and mice were evaluated for an antiviral response against CVB3 infection. Not surprisingly, in both cases, mice were unable to control viral replication and succumbed to infection after only several days (294, 295). Moreover, comparing CVB3-susceptible A/J mice to CVB3-resistant C57Bl/6 mice revealed enhanced expression of IFN-β and multiple IFN-α subtypes in the resistant C57Bl/6 mice following CVB3 infection (296). Studies evaluating PRRs and related signaling molecules have also highlighted the importance of type I IFNs in an innate antiviral response.

44 1.3.4. Antiviral Effects of Type I IFNs Reflective of the pleiotropic nature of IFNs, targeting many aspects of an immune response, the effects exerted by ISGs within cells can be observed at different stages of viral replication. Upon engagement of IFNAR by type I IFNs in a target cell, a transcriptional program is rapidly induced, producing hundreds of gene products which exert direct and indirect antiviral effects (297, 298). However, the mechanisms by which many of those proteins function is not well understood. While a number of potent IFN-inducible antiviral effectors have been identified to date, such as PKR, 2’5 OAS, RNaseL, MX GTPases and ISG15, a gradient of potencies can be observed for many of the remaining ISGs as demonstrated by in vitro screens against different viruses (298, 299). It is also evident that many antiviral proteins are virus-specific in their inhibition (298). Examples can be seen with MX1 which effectively inhibits influenza A virus and not HIV-1, whereas the converse is true of MX2 (300). The MX GTPases, named for their resistance toward Orthomyxoviruses such as influenza virus A, inhibit a variety of other viruses, including Coxsackieviruses (301, 302). MX-mediated antiviral activity occurs through the early inhibition of genome transcription through interference with ribonucleoprotein transport (303, 304).

Given that viruses are obligate intracellular parasites, they require translational machinery for protein synthesis during replication. Consequently, a number ISGs have been shown to interact with components of host cell translational machinery to limit viral protein synthesis. An in vitro screen of ISG activity against HCV infection revealed that the strongest translational inhibitors were also the most potent inhibitors of viral replication (297). The translational inhibitor, dsRNA-sensitive PKR, is expressed at a basal level in cells, and quickly limits protein translation upon activation by virus replication. Not surprisingly, viruses have adapted effective mechanisms to antagonize this. Among its many antagonistic functions, the non-structural gene, NS1, from types A and B influenza viruses, is able to effectively bind and sequester dsRNA and thus prevent PKR activation (235). NS1 has also been shown to interfere with other transcriptional and post-transcriptional processes such as IFN-α/β inducible STAT signaling, mRNA splicing, poly-adenylation, mRNA transport and translation initiation (232, 305).

45 Another antiviral defense triggered by viral dsRNA replicative intermediates is 2’-5’-OAS and RNaseL activation. Activation of 2’-5’-OAS, by dsRNA, leads to the catalysis of a signaling intermediate, 2’-5’-adenylate, which induces dimerization and activation the endoribonuclease RNase L (306). Cleavage of ssRNA by RNase L (including cellular RNAs) not only impedes viral replication, but it also generates small 3’-monophosphate RNAs which are recognized by RIG-I and/or MDA-5, thereby amplifying IFN-β expression (307). Interestingly, RNase L also exerts an inhibitory effect on protein synthesis, metabolism and proliferation by degradation of specific cellular mRNAs and rRNAs (308). While RNase L is a strong antiviral effector, it is not surprising that viral antagonism of this pathway has been identified among different viruses. The murine hepatitis virus (MHV) encodes a 2’-5’- phosphodiesterase which cleaves 2’-5’ A and effectively impairs RNase L activation (309). Additionally, the VACV protein E3L binds and sequesters dsRNA thereby preventing 2’-5’- OAS activation in a manner similar to that observed for PKR (310). Viral replication may also be inhibited through a mechanism that involves the induction of apoptosis through activation of JNK (311).

Expression of ISG15 is another mechanism utilized by type I IFNs to limit viral replication. ISGylation is similar to ubiquitination in that ISG15 is conjugated to targeted proteins and signaling their degradation (312). ISG15 is one of the most highly expressed ISGs following IFN treatment, and is effective in limiting replication of certain viruses, including influenza A viruses. Notably, the NS1 protein of influenza A virus has been demonstrated as a substrate of ISG15, thereby limiting replication (313). ISGylation of NS1 is shown to impede its dsRNA binding capacity, and also interfere with its binding of nuclear transport proteins (314). Proteomic studies have also revealed that ISG15 targets other ISGs, and there are data to suggest it may be secreted, but its subsequent mechanism of action is not understood (315).

Because of the emergence of drug resistance among viruses, increasing attention is focused on identifying host factors that function as antivirals that activate cellular effectors, rather than developing antivirals that target a virus (316). The advantage of this approach is the broad-spectrum nature of potential drugs that could specifically regulate antiviral effectors.

1.3.5. Type I IFN Effects on Immune Cells IFNs are pleiotropic cytokines that influence a variety of biological processes related to immune function. Their influence extends from hematopoiesis to innate and adaptive immune responses. Indeed, type I IFNs have been demonstrated to positively affect hematopoietic stem cell (HSC) renewal in the bone marrow (317) and influence differentiation in development. Mice lacking IFN-β exhibit defects in the maturation of different leukocyte lineages (318). Interestingly, type I IFNs have been shown to be expressed constitutively in the thymus and bone marrow (319, 320). During an acute infection, type I IFNs are produced in response to pathogenic stimuli. Acting in an autocrine and paracrine manner, type I IFNs regulate the immune response, influencing immune cell activation and recruitment through the expression of chemokines and adhesion molecules (321).

1.3.5.1. IFN Regulated Chemotaxis Early in an infection, recognition of pathogenic signals via PRRs leads to the production of chemokines and cytokines which recruit and activate both tissue resident immune cells and circulating leukocytes. Secretion of IFN-β by infected cells and tissue resident DCs stimulates amplified production of chemokines. Examples of type I IFN inducible chemokines are CCL2 (MCP-1), CCL12 (MCP-5), CCL5 (RANTES), CXCL9, CXCL10 (IP-10) and CXCL11, which influence the migration and also differentiation of monocytes, macrophages, DCs, activated T cells, B cells and NK cells. Interestingly, early events during a viral infection produces lymphopenia as a result of changes in leukocyte migration in the blood and lymphatics, and this effect is strongly influenced by IFN-β (322, 323).

Type I IFNs elicit different effects based on the type of cell engaged and stimulatory milieu. For example, during HSV-1 infection of corneal epithelial cells, induced type I IFNs can upregulate the chemokine CCL2 to recruit monocytes and NK cells to the site of infection (324). In the context of bacterial infection, IFN-β augments the LPS-inducible production of CCL2, CCL12, CCL5 and CXCL10 in peritoneal macrophages, to recruit additional monocytes, (325, 326). In contrast, during viral or bacterial infection, type I IFNs inhibit expression of

47 CXCL1 and CXCL2, thereby decreasing recruitment of neutrophils (327, 328). Indeed, neutrophils can elicit severe immunopathology if recruited in excess. In a model of pulmonary arterial hypertension, type I IFNs upregulate CCL5 and CXC3L1 in endothelial cell lines, but not CCL2 (329). In vitro IFN stimulation of monocyte derived DCs induces CXCL9, CXCL10 and CXCL11 which are chemotactic towards activated T and B cells expressing CXCR3 (330). In pDCs isolated from patients with multiple sclerosis, IFN-β treatment was able to blunt TLR9 induced chemokines CCL3, CCL4 and CCL5, which recruit Th1 type T cells (331). Additionally, in a model of cerebral malaria, IFN-β downregulates the chemokine CXCL9, the adhesion molecule ICAM-1 and chemokine receptor CXCR3 on T cells, thereby minimizing inflammation in the brain (332). Conversely, in melanoma cells, treatment with either IFN-α or IFN-γ increases expression of CXCL9, CXCL10 and CXCL11, thereby facilitating infiltration of activated CXCR3 expressing cytotoxic T cells (333), thus influencing the balance of immune cell chemotaxis (334). IFN-β also impairs migration of eosinophils through downregulation of the adhesion molecule ICAM-1 in lungs (335).

Type I IFNs also influence the chemotactic response of immune cells by regulating surface expression of chemokine receptors, thus playing an important role in the sequential and coordinated migration of different subsets of leukocytes to and from sites of infection and secondary lymphoid organs. At the site of infection, maturation of dendritic cells alters their responsiveness to different chemokines. In monocyte derived DCs treated with type I IFNs, expression of CCR7 is enhanced, thereby increasing their responsiveness to the cognate ligands, CCL19 and CCL21 (336). Concurrently, DCs also down-regulate chemokine receptors such as CCR2, thereby permitting their exit from the inflamed tissue (337). This coordinate switch in chemokine receptor expression causes DCs to migrate towards lymph nodes for interaction with T and B cells. IFN-β also directly influences T and B cell retention in lymph nodes through up-regulation of CD69 and subsequent impairment of the S1P1 response to S1P, which is found at higher concentrations in circulation (338). Following activation, T cells upregulate chemokine receptors such as CCR5 and migrate towards the site of inflammation. CD69 surface expression on neutrophils is also induced by IFN-α, however, the functional significance of this is not clear.

48 1.3.5.2. IFN Regulation of Leukocyte Effector Function In addition to influencing the chemotactic response of leukocytes, type I IFNs also play important roles in defining effector function of leukocytes. Dendritic cells are critical regulators of cellular immunity, and are themselves a significant source of type I IFNs. Treatment of peripheral blood monocytes with type I IFNs and GM-CSF influences their rapid differentiation into IFN-DCs possessing strong CD8 T cell cross-priming activity with enhanced antigen uptake and increased CD40, CD80, CD86 and HLA class I expression (339, 340).

Dependent on the type of pathogenic stimulus or tissue injury, DCs play an instructional role in determining the type of adaptive immune response. A long-standing paradigm of CD4+ T cell differentiation has held that cytokine and stimulatory cues produced by DCs define IFN-γ secreting Th1 versus IL-4 secreting Th2 phenotypes. Other defined lineages T cell lineages include IL-17 producing Th17 cells and IL-10 producing regulatory T cells (Tregs). Differentiation of these cells is influenced by a network of STAT molecules and coordinate lineage defining transcription factors. Th1 defining factors include T-bet, STAT1 and STAT4 (activated by IFNs and IL-12); Th2 defining factors include GATA-3 and STAT6 (activated by IL-4); Th17 cells are differentiated by RORγT and STAT3 (activated by IL-6, IL-21 and IL-23); and Tregs are defined by FOXP3 and STAT5 (activated by IL-2) (341). Type I IFNs have been shown to influence the emergence of these different phenotypes, and this effect appears to be regulated by the cytokine milieu and temporal effects. Type I IFNs have both positive and negative effects on Th1 differentiation. Monocyte derived DCs matured with TNF-α in the presence of IFN-β strongly promote Th1 differentiation through production of IL-12, whereas treatment of mature DCs with IFN-β at the time of naïve T cell stimulation inhibits Th1 polarization (342, 343). In terms of Th2 differentiation, type I IFN signaling is antagonistic towards the IL-4 induced signaling through STAT6 which is necessary for Th2 differentiation. This effect is mediated by type I IFN inducible expression of SOCS1, which negatively regulates STAT6 (344). The converse is also true, where type I IFN and IL-12 signaling is inhibited by IL-4 (345, 346). Downstream consequences of Th1 polarization include the inhibition of Th2 immune responses mediated by such cells as mast cells, eosinophils, and basophils (335). The differentiation of Th17 cells is inhibited by

49 both IL-4 and type I IFNs (347-349). The suppression of Th17 cell development lessens the proinflammatory effect of IL-17 induced IL-1β, IL-6 and TNFα (350). In patients suffering from relapsing-remitting multiple sclerosis, treatment with IFN-β leads to increased serum levels of IL-10, which also suppresses pathogenic Th1 and Th17 driven inflammation (351). Mechanistically, IFN-β appears important in maintaining FoxP3 expression in Tregs, which are critical for balancing inflammation (352). Indeed, the importance of Tregs can been seen in many inflammatory pathologies, including pulmonary virus infection (353), viral hepatitis (354), autoimmune arthritis (355), colitis (352), and transplantation (356).

Type I IFNs also influence humoral immunity through the regulation of B lymphocyte function. During rotavirus infection, IFN-α produced by pDCs plays an important role in B cell activation (357). Type I IFN mediated activation of B cells is evidenced by upregulation of the surface markers CD69, CD86 and CD25 (320). Type I IFN signaling has also been shown to be necessary for the rapid activation and polyclonal IgM response to virus infection (358). Additional IFN mediated effects include increased survival and resistance to Fas-mediated apoptosis, as well as enhanced response to BCR-ligation (320). Cytokines, BAFF and APRIL are also induced by type I IFNs in DCs, and modulate B cell antibody class switching (359).

Type I IFNs strongly influence NK cell function during the innate phase of an immune response. Their unique ability to discriminate transformed or virus-infected cells from healthy cells indicates their important role in innate immunity. Cytokines such as IL-15 and IFN-β, which are produced by DCs, can activate NK cells and influence effector function (360, 361). Type I IFNs also enhance NK cell cytotoxicity, thereby facilitating strong antitumor and antiviral immunity (362, 363). A modest effect of NK cell proliferation can also be induced by type I IFNs (364).

Granulocytes, such as mast cells, basophils and eosinophils also respond to type I IFNs. Well recognized for their significant role in mediating allergic pathologies, mast cells are also involved in regulating immune responses to viral, bacterial and parasitic infections, although this role is not well defined yet (365). Additionally, mast cells have been

50 implicated in diseases such as inflammatory bowel disease and multiple sclerosis (366, 367). Type I IFNs influence the effects of mast cells on T cell stimulation, through production of TGF-β and IL-10, as well as OX40L expression (368). Widely distributed through various tissues, mast cells secrete MCP-1, a strong chemoattractant for macrophages and NK cells, in response to treatment with IFN-β (369). In contrast to this, the effect of type I IFNs on basophil activity is suppressive, through limitation of IL-3 mediated effects in the context of allergic responses (370). Interestingly, in patients with allergic asthma, virus induced IFN-α production is blunted, suggesting a possible dysregulation of IFN in allergic conditions (371). Type I IFNs have also been shown to negatively regulate eosinophils, albeit through indirect mechanisms. Skewing of CD4 T helper cells towards a Th1 phenotype by type I IFNs inhibits Th2 release of eosinophil activating cytokines.

51 1.5. Hypothesis and Objectives

Hypothesis:

Type I IFN-mediated regulation of post-transcriptional processes is critical to an antiviral response.

Obectives:

Chapter 2: Examine the roles of translational suppressors, 4E-BP1 and TSC2, during a type I IFN antiviral response.

Chapter 3: Characterize the influence of type I IFNs on glucose metabolism in the context of an antiviral response.

Chapter 2

Antiviral effects of IFNs-α/β are enhanced in the absence of the translational suppressors 4E-BP1 and TSC2.

Figures 2.3, 2.6 and 2.7 in this chapter were published in:

Burke, J.D., Sonenberg, N., Platanias, L.C., Fish, E.N. Antiviral effects of interferon-β are enhanced in the absence of the translational suppressor 4E-BP1 in myocarditis induced by Coxsackievirus B3. Antiviral Therapy 2011; 16:577–584.

All experiments were performed by JDB. Assistance with real time PCR was provided by Jiabing Chen.

53 2.1. Abstract

Type I IFNs play a critical role in the resolution of viral infections through the regulation of innate and adaptive immunity. Secreted from leukocytes or virally infected cells, type I IFNs engage cells in the surrounding microenvironment to induce an antiviral state through the expression of many interferon stimulated genes (ISGs). A specific role for IFNs-α/β in the regulation of mRNA translation has been identified which involves PI3’K/mTOR signaling. In the present study we investigated the roles of two translational suppressors, 4E-BP1 and TSC2, during an IFN-mediated antiviral response. We provide in vitro evidence that cells lacking 4E-BP1 or TSC2 induce enhanced ISG15 protein expression upon stimulation with IFN-α4, that is associated with increased resistance to infection with vaccinia virus (VACV) or coxsackievirus B3 (CVB3). Studies conducted in 4E-BP1-/- mice provide evidence for a stronger antiviral response to acute CVB3 infection as indicated by enhanced gene expression of type I IFNs-α/β, ISG15, PKR and 2’5-OAS, compared with 4E-BP1+/+ mice. . When treated with IFN-β, 4E-BP1-/- mice are more sensitive to the antiviral effects of IFN-β compared with 4E-BP1+/+ mice, as shown by reduced viral burden and inflammation in the hearts when infected with CVB3. Similarly, 4E-BP1-/- mice infected with influenza virus A/WSN/33 are more sensitive to the effects of IFN-β, as indicated by lower viral titers in the lungs and less virus-induced weight loss. Taken altogether, these data demonstrate an important role for translational regulation during a type I IFN mediated antiviral response against different viruses, and also suggest 4E-BP1 and TSC2 as possible targets to enhance the potency of IFN-β.

54 2.2. Introduction

The emergence of new viral pathogens that threaten human health is a challenge for the development of targeted antivirals such as vaccines or pathogen-specific small molecule inhibitors, such as siRNAs or inhibitors of viral polymerases. Additionally, the potential for viruses developing drug resistance against these pathogen-specific antivirals poses a serious problem. Consequently, there is renewed interest in targeting host immunity instead of directly targeting viral proteins. Examples can been seen with the use of synthetic TLR ligands and type I and III IFNs as immunomodulatory agents for the treatment of viral infections (372). Certainly, type I IFNs are effective in treating a variety of viral diseases. The most common indication for type I IFN treatment is HCV infection (373), but studies in humans have highlighted the prophylactic and therapeutic potential of type I IFNs for different virus infections: influenza virus A/B (374, 375), parainfluenza virus (375), adenovirus (375, 376), respiratory syncytial virus (377), coronavirus (378), rhinovirus (379-382), severe acute respiratory syndrome coronavirus (SARS CoV) (383), West Nile virus (384-386), enterovirus (387-390), human immunodeficiency virus (391- 394), herpes zoster (395-397), genital herpes (398-401). A number of emerging viruses such as hantaan virus (402), ebola virus (403), MERS-CoV (404, 405), enterovirus 71 (406), chikungunya virus (407), dengue virus (408, 409) have also been shown to be sensitive to the antiviral effects of type I IFNs.

The broad-spectrum antiviral activity elicited by type I IFNs makes them attractive candidates for further investigation. Yet existing concerns related to the undesirable side effects of type I IFNs, which include fevers, chills and myalgia, often preclude their further evaluation as antivirals in acute virus infections (410). Additionally, cells may become refractory to IFN stimulation, unable to sustain elevated expression of different antiviral effectors upon continual treatment with IFNs (411). This has been proposed as a potential contributing factor that may account for the loss of response to IFN treatment in HCV patients that become non-responders, i.e. those that do not have a sustained response to therapy. (412-414). Given that many viruses encode in their genomes factors that either inhibit IFN production (267, 415-418) or target specific signaling effectors that would limit

55 an IFN response (232, 419-421), we undertook studies to identify potential signaling effectors associated with an IFN-induced antiviral response that might serve as candidates to target for enhancing antiviral activity.

Previous in vitro studies that utilized cells lacking various components of the PI3’K signaling pathway, revealed important post-transcriptional regulators of ISG protein expression (200-202). Cells lacking either p85α/β or Akt exhibit reduced ISG expression, which correlates with an impaired antiviral response upon type I IFN treatment (200, 201). By contrast, cells lacking the translational suppressors, TSC2 or 4E-BP1, exhibit enhanced ISG expression along with a stronger antiviral response upon type I IFN treatment (202).

The respiratory pathogen, influenza virus A, and the cardiotropic virus, coxsackievirus B3 (CVB3), are viruses which exhibit strong antagonism towards a type I IFN response to infection (233, 267, 422, 423). In these studies we examined the antiviral effects of type I IFNs in the context of these virus infections in vitro and in vivo. We provide evidence that IFN-α4 induces enhanced ISG15 protein expression in cells lacking the translational suppressors 4E-BP1 or TSC2. Additionally, we show that cells lacking 4E-BP1 or TSC2 are also less permissive to infection with CVB3, influenza virus A/WSN/33 and vaccinia virus. We provide evidence for increased sensitivity to IFN-β in 4E-BP1-/- and TSC2-/- MEFs during infection with CVB3, and increased sensitivity to IFN-α4, when infected with vaccinia virus. In vivo we demonstrate that 4E-BP1-/- mice exhibit enhanced resistance to acute infection with either CVB3 or influenza virus A/WSN/33 (H1N1) relative to 4E- BP1+/+ mice. Additionally, when compared to 4E-BP1+/+ mice, 4E-BP1-/- mice are more sensitive to the antiviral effects of IFN-β during infection with CVB3 or influenza virus A/WSN/33.

56 2.3 Methods and Materials

2.3.1 Animals, cells and virus 4E-BP1+/+ and 4E-BP1-/- mice (C57Bl/6 background) were maintained in a sterile, pathogen-free environment according to the Animal Care Committee guidelines of the Toronto General Research Institute (Toronto, ON, Canada). Splenocytes were isolated by mechanical dissociation of spleens harvested from 4E-BP1+/+ and 4E-BP1-/- mice, 8 weeks of age. Cells were stimulated in plates coated with anti-CD3 and anti-CD28 antibodies (BD Pharmingen, Mississauga, ON, Canada) for 2 days followed by addition of 50 U/ml mouse IL-2 (mIL-2; R&D Systems, Minneapolis, MN, USA) in 10% fetal calf serum (FCS) RPMI-1640 supplemented with 50 µM β-mercaptoethanol (Invitrogen, Burlington, ON, Canada). Proliferating cells were harvested by Lympholyte® (Cedarlane, Burlington, ON, Canada) separation, according to the manufacturer’s instructions. Primary CD3+ T cells were seeded at a density of 106 cells/ml. MEFs derived from 4E-BP1+/+ and 4E-BP1-/- mice (202) were maintained in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% heat- inactivated FCS, 100U/ml penicillin, 100ug/ml streptomycin. Coxsackievirus B3 CVB3 strain, Charles Gauntt, was propagated and titrated in HeLa cells as previously described (295). Vaccinia virus Western Reserve 65 (VACV-WR65) was propagated in BGMK cells as previously described (424). Influenza virus A/WSN/33 was propagated and titrated in MDCK cells as previously described (425).

2.3.2. Immunoblotting MEFs were plated overnight at sub-confluent density in DMEM supplemented with 2% FCS and 100U/mL penicillin, 100µg/mL streptomycin. Mouse IFN-α4 (1000U/mL) was added to cells for the indicated times. Medium was aspirated then washed twice with ice-cold PBS, and cells lysed in RIPA lysis buffer containing phosphatase and protease inhibitor cocktail (Cell Signaling, Boston, MA, USA). Protein concentration was determined using the Bradford assay (BioRad, Hercules, CA, USA). Lysates were heat denatured in Laemmli sample reducing buffer and 30 µg was resolved by sodium dodecyl sulphate polyacrylamide electrophoresis (SDS-PAGE). Proteins were transferred to a nitrocellulose membrane followed by blocking with 5% BSA (w/v) in TBST (0.1% Tween-20).

57 Membranes were probed with anti-ISG15 (Cell Signaling Technology, Boston, MA, USA) and anti-β-actin (Sigma-Aldrich, Burlington, ON, Canada) antibodies. Proteins were visualized by enhanced chemiluminescence (ECL) (Pierce Thermo Fisher Scientific, Rockford, IL, USA). Quantification of proteins was determined by densitometry using Quantity One (Bio-Rad, Hercules, CA, USA).

2.3.3 IFN treatment and virus infection 2.3.3.1 In vitro: Cells were plated at a sub-confluent density in 2% medium prior to treatment with IFN and incubated at 37°C in 5% CO2. Following a 12h treatment with IFN-β or IFN-α4, cells were infected with CVB3 at a multiplicity of infection (MOI) of 1.0 in 2% FCS DMEM and the virus was allowed to adsorb for 90 minutes. Cells were then washed three times with 2% FCS DMEM and incubated for a further 12 h. Cells were lysed in phosphate-buffered saline (PBS) by 3 freeze thaw cycles at -80°C. Virus titers were then determined by standard plaque assay in HeLa cells. For experiments using VACV, MEFs were plated in 96-well tissue culture plates at a sub-confluent density in 2% FCS DMEM and incubated overnight at 37°C in 5% CO2. Cells were then infected at indicated MOI for 16 hours. Medium was then aspirated and viral replication quantified by a colorimetric assay measuring the abundance of the reporter β-galactosidase.

2.3.3.2. In vivo CVB3 infection: Mice, aged 6 -12 weeks were injected intraperitoneally (i.p.) with 100 µl PBS carrier or mouse IFN-β. This injection was followed 4 h later by i.p. inoculation with 103 plaque-forming units (pfu) of CVB3. At the indicated times, mice were euthanized, and hearts were aseptically removed and frozen in liquid nitrogen. After three freeze-thaw cycles, viral titers were determined by plaque assay in HeLa cells, and expressed as pfu/gram of tissue.

2.3.3.3. In vivo influenza virus infection: Mice, aged 6-12 weeks were injected intraperitoneally with 100 µl mouse IFN-β dissolved in PBS or PBS alone. This injection was followed 12 h later by intraperitoneal administration of 100 µg Xylazine and 1.8 mg Ketamine anaesthetic and intranasal inoculation of 200 pfu influenza virus suspended in 50 µl PBS. Mouse weight loss was recorded daily. At the indicated times, mice were euthanized,

58 and lungs were aseptically removed and frozen in liquid nitrogen. Tissue was subsequently homogenized and titrated on MDCK cells following three freeze-thaw cycles.

2.3.4. Real time PCR detection of gene expression Gene expression was detected as previously described (232, 296). Briefly, total RNA was extracted by mechanical homogenization of frozen heart tissue using Trizol reagent (Invitrogen, Burlington, ON, Canada). RNA concentration and purity was determined by UV photospectrometry at 260/280 nm (Beckman-Coulter, Indianapolis, IN, USA). cDNA was prepared from 1 µg RNA template and random hexamer primers using Superscript III reverse transcriptase according to the manufacturer’s protocol (Invitrogen, CA). Amplification of target genes was accomplished using a Roche LightCycler® with LightCycler® FastStart DNA Master SYBR Green PLUS I kits (Roche). Primer sequences are as follows: hprt: F: 5'-atcagtcaacgggggacata-3', R: 5'-ttgcaaccttaaccattttgg-3', ifnb: F:5'- tgcgttcctgctgtgcttct-3', R: 5'-ttggatggcaaaggcagtgt-3', ifna4: F: 5'-gccatccttgtgctaagag-3', R: 5'-tcaagaggaggttcctgcatcac-3', irf7: F: 5'-ctggatgtgaccatcatgt-3', R: 5'-aagtgctgaagtcgaagatg- 3', isg15: F: 5'-gtgtcagaactgaagaag-3', R: 5'-cgttcctcaccaggatgc-3', pkr: F: 5'- ggctcctgtgtgggaagtca-3', R: 5'-tatgccaaaagccagagtcctt-3', oas: F: 5'-tgagcgccccccatct-3', R: 5'- catgacccaggacatcaaagg-3'. Primers were used with an annealing temperature of 60°C. Gene expression was quantified using RelQuant Software (Roche, Indianapolis, IN, USA). Reaction conditions are as follows: preincubation at 95°C for 10 min, followed by 45 cycles of denaturation at 95°C for 10s, annealing for 5s, extension at 72°C for 10s, melting curve analysis from 65°C to 95°C with a temperature transition rate of 0.1°C/s. Each reaction contained 400 ng of template cDNA, 1 µl forward and reverse primers (20 µM stock), 4 µl SYBR Green reagent and PCR grade water to a reaction volume of 20 µl.

2.3.5. Histopathology Heart tissue was harvested from CVB3-infected mice and processed for hematoxylin and eosin (H & E) staining of thin sections. Whole hearts were fixed in 10% (v/v) formalin (Sigma-Aldrich, Oakville, ON, Canada), embedded in paraffin, and sectioned at 5 µm. Cross- sectioned tissues were stained with H & E. Myocardial inflammation was graded using a

59 blind scoring method: 0 (normal), 1 (lesion extent not exceeding 1% of a transverse section), 2 (not exceeding 10%), 3 (not exceeding 50%), 4 (exceeding 50%) (426).

60 2.4 Results

2.4.1. IFN-α induces increased translation of antiviral proteins in cells lacking negative regulators of protein synthesis. Previous studies from our group provided evidence for enhanced IFN-α/β inducible ISG15 protein expression in cells lacking the suppressors of translation, TSC2 or 4E-BP1, 48 hours after IFN treatment (202). At the outset, we undertook a more extensive time course study. Murine embryonic fibroblasts (MEFs) lacking either 4E-BP1 or TSC2 were either left untreated or treated with IFN for the indicated times, then analyzed by Western immunoblots for ISG15 expression. We provide evidence for enhanced ISG15 protein expression in MEFs null for 4E-BP1 or TSC2, relative to wildtype cells (Fig 2.1). Relative to wildtype cells, that are sufficient for both 4E-BP1 and TSC2, IFN-inducible ISG15 protein expression was induced to a greater extent in the TSC2-/- cells beginning at approximately 6 hours following treatment, compared with the 4E-BP1-/- cells.

Figure 2.1. IFN-α4 differentially regulates ISG15 expression in MEFs lacking translational supressors 4E-BP1 or TSC2.

(A) 5x105 MEFs were serum starved overnight and then stimulated with 1000 U/mL IFN- α4 for indicated times. Cells were lysed, proteins resolved by SDS-PAGE, then analyzed in Western immunoblots with anti-ISG15 and anti-β-actin antibodies. (B) Protein expression was measured by densitometry and recorded as a fold induction relative to mock-treated cells. Protein expression was normalized for each sample relative to β-actin. Data are representative of three independent experiments * p<0.05.

Figure 2.1

A& IFN)α4& )& +& +& +& +& +&

Time&(h)& 0& 1& 2& 4& 6& 24&

ISG15& Wildtype& β)actin&

ISG15& 4E&BP1)/)& β)actin&

ISG15& TSC2&)/)& β)actin&

B& 25& *" Wildtype& 20& 4E)BP1)/)& *" TSC2)/)& 15&

10& *" Fold&Induction&

5& *"

0& 0& 6& 12& 18& 24& Hours&Post)Treatment&

2.4.2 IFN-α/β invokes enhanced antiviral effects in cells lacking the translational suppressor 4E-BP1 Previous studies showed MEFs lacking 4E-BP1 or TSC2 to be less permissive to infection with EMCV than wildtype MEFs (202). Additionally, MEFs doubly deficient for 4E-BP1 and 4E-BP2 were less permissive to infection with vesicular stomatitis virus (191). VSV is routinely employed in IFN-bioassays as it is very sensitive to the antiviral effects of IFN (427, 428). By contrast, in a first series of virus infection studies, we chose to focus on a virus that is less sensitive to the antiviral effects of IFNs and, unlike EMCV, utilizes cap- dependent translation for virus replication. We examined the sensitivity of MEFs null for 4E-BP1 or TSC2 to infection with vaccinia virus (VACV). Infection of 4E-BP1-/- or TSC2-/- MEFs at various MOI, revealed increased resistance to infection relative to wildtype MEFs (Figure 2.2 A). Similar to previously published data for EMCV, TSC2-/- MEFs exhibited greater resistance to VACV infection, compared with 4E-BP1-/- MEFs. IFN-α4 treatment of 4E-BP1-/- and TSC2-/- MEFs resulted in stronger antiviral activity compared with the wildtype MEFs, albeit to a lesser extent than that reported with EMCV infection (Fig 2.2 B, C). Specifically, for VACV infection, IFN-α4 IC50 values were: wildtype MEFs ~9.7 U/mL; 4E-BP1-/- ~5.5 U/mL and TSC2-/- ~1.5 U/mL. According to the extra sum-of-squares F test, statistically significant differences were calculated between the dose-response curves of wildtype and TSC-/- MEFs, yet were not present between wildtype and 4E-BP1-/- MEFs.

Figure 2.2 MEFs lacking translational suppressors 4E-BP1 and TSC2 are more resistant to infection with VACV and more sensitive to treatment with IFN-α4.

(A) MEFs were plated at sub-confluent density and serum starved overnight prior to infection with VACV at the indicated MOI. Following 16 h of infection, virus replication was measured by colorimetric detection of the reporter β-galactosidase. Measurements are expressed as the mean of quadruplicate assays (±SEM). Values indicate arbitrary units of optical density at 420nm. Data reflect 3 independent experiments. Statistical significance within the treatment group is indicated relative to wildtype samples *p<0.05. (B, C) MEFs were plated at sub-confluent density prior to treatment with serial dilutions of mouse IFN- α4 for 12 h. Following treatment, IFN-α4 was aspirated and cells infected at MOI=1.0 for a further 16 h. Virus replication was measured by colorimetric detection of the reporter β- galactosidase. Protection was calculated relative to untreated and infected cells and plotted as the mean value from quadruplicate samples. Prism Graphpad was used to generate dose- response curves. Statistical analysis was performed using the extra sum-of-squares F tests, and indicated for each treatment group. Data are from 5 independent experiments, combined.

Figure 2.2

A$ 1$ Wildtype$ *" *" 4E0BP10/0$ 0.1$ *" *" TSC20/0$

O.D.$ 0.01$ *" *"

0.001$ *"

0.0001$ 10$ 5$ 1$ 0.1$ MOI$ B$ 120$

100$ Wildtype$ 80$ 4E0BP10/0$ 60$ p=0.065&

%$Protection$ 40$

20$

0$ 02$ 0$ 2$ 4$ IFN0α4$(log$U/mL)$ C$

120$

100$ Wildtype$ 80$ TSC20/0$ 60$ p<0.0001&

%$Protection$ 40$

20$

0$ 02$ 0$ 2$ 4$ IFN0α4$(log$U/mL)$

66 Next we examined the effects of IFN-α/β treatment on the replication of CVB3 in 4E-BP1-/- and TSC2-/- MEFs. Given that the doubling time of 4E-BP1-/- cells and TSC2-/- cells is shorter than their wildtype counterparts and, as a consequence, 4E-BP1-/- and TSC2-/- cells support increased CVB3 replication over a period of 12 hours, the effects of IFN-β treatment are presented as both absolute titers and relative fold-reduction in viral titers (Fig 2.3 A, B). Treatment with IFN-β induced a strong antiviral response in both 4E-BP1-/- MEFs and TSC2-/- MEFs, effectively reducing viral replication. This is reflected in their respective IC50 values: wildtype MEFs ~6.9U/mL; 4E-BP1-/- MEFs ~4.3U/mL; TSC2-/- MEFs~1.5U/mL. In subsequent experiments, we examined the antiviral effects of IFN-α/β in primary cells derived from wildtype and 4E-BP1-/- mice, namely splenocytes. Notably, these primary cells exhibited no difference in proliferative capacity whether derived from wildtype or 4E-BP1 null mice. As for the MEFs, the data demonstrate that the absence of 4E-BP1 enhances sensitivity to the antiviral effects of IFN-α/β, albeit to a lesser extent (Figure 2.3 C, D, E, F).

Figure 2.3. IFNs-α/β induce potent antiviral effects against CVB3 in cells lacking 4E- BP1 or TSC2.

(A) MEFs were plated at sub-confluent density and serum starved in 2% FCS DMEM overnight prior to treatment with the indicated doses of IFN-β for 12 h. Cells were infected with CVB3 at an MOI of 1.0. After 12 h, infected cells were lysed and viral titersmeasured as described in Materials & Methods. Values are shown as absolute pfu/mL (A) and calculated as fold reduction relative to mock-treated, infected cells (B) (±SEM). Student’s t-test indicates significant (p<0.05) effects of IFN-β in 4E-BP1-/- versus 4E-BP1+/+ (§) or TSC2-/- versus TSC2+/+ (*) MEFs. Data are representative of 3 independent experiments. (C) Splenocytes were isolated from spleens of 4E-BP1+/+ and 4E-BP1-/- mice and stimulated for 2 days with plate bound anti-CD3 and anti-CD28 antibodies and IL-2. Proliferating cells were collected and resuspended in 2% FCS RPMI, then serum starved overnight prior to treatment with the indicated doses of IFN-α4 (C, D) or IFN-β (E, F) for 12 h. Cells were then infected with CVB3 for 12 h at an MOI of 1.0. Infected cells were then lysed and viral titers determined. Values are shown as absolute pfu/mL (C, E) and calculated as fold reduction relative to mock-treated, infected cells (D, F) (±SEM). Data are representative of 2 independent experiments.

Figure 2.3

A" B" 8" 1000" *" Wildtype" 7" *" 4E4BP14/4" §" 6" §" TSC24/4" /mL)" 100" §" 5" *" pfu §" 4" *" 10" 3" Fold"Reduction"

Titer"(log" 2" 1" 1" 0" 1" 2" 3" 0" 1" 2" 3" IFN4β"(log"U/mL)" IFN4β"(log"U/mL)"

C" D" 4E4BP1+/+" 500" 3" 4E4BP14/4" 400" 2" /mL)" 300" pfu 200" 1" Titer"( 100" Fold"Reduction"

0" 0" 0"1" 10"1" 100"2" 1000"3" 0"1" 10"1" 100"2" 1000"3" IFN4α4"(log"U/mL)" IFN4α4"(log"U/mL)" E" F" 500" 3" 4E4BP1+/+" 400" 4E4BP14/4"

/mL)" 2" 300" pfu 200" 1" Titer"(

100" Fold"Reduction"

0" 0" 0"1" 10"1" 100"2" 1000"3" 0"1" 10"1" 100"2" 1000"3" IFN4β"(log"U/mL)" IFN4β"(log"U/mL)"

2.4.3. IFN-β elicits a stronger antiviral effect in CVB3-infected mice lacking the translational suppressor 4E-BP1 Previously, we demonstrated that mice lacking IFN-β are more susceptible to CVB3 infection than wild-type mice; other studies have consistently shown that IFN-α/β treatment reduces the severity of CVB3-induced myocarditis (295, 388, 429-431). To investigate the role that translational regulation exerts in an antiviral response in vivo, we infected 4E-BP1+/+ and 4E-BP1-/- mice with a sublethal dose of CVB3. Over the course of the acute phase of infection (days 1-7), viral titers were determined in tissues that are targeted by CVB3. For both wildtype and 4E-BP1-/- mice, a similar course of infection was observed in the different organs, with peak viral burden 3 days post-infection, followed by progressive clearance of the virus from the heart 7 days post-infection. 4E-BP1-/- mice exhibited less viral replication compared to their wildtype counterparts (Fig 2.4). In time course studies, we next examined the effect of virus infection of the heart on mRNA expression for IFN-α4 and IFN-β and ISGs. The data suggest that CVB3 induces IFN-β, IFN-α4, IRF7, PKR and ISG15 to similar levels in the hearts of both wildtype and 4E-BP1-/- mice (Fig 2.5). Interestingly, 2’5’-OAS mRNA detection was significantly higher at both 1 and 3 days post-infection.

Next we treated 4E-BP1+/+ and 4E-BP1-/- mice with IFN-β prior to infection with a sublethal dose of CVB3. All mice exhibited signs of disease, including reduced activity, ruffled fur and weight loss. In one series of experiments, three of the five control 4E-BP1+/+ mice (PBS as mock treatment) succumbed between days 3 and 5 post-infection. As anticipated, mice treated with IFN-β were more active and did not exhibit such severe disease symptoms as their mock-treated counterparts. Comparison between untreated (carrier alone) 4E-BP1+/+ and 4E-BP1-/- mice revealed only modest differences in viral titers during the course of infection (Fig 2.6 A). Consistent with previous reports, treatment with IFN-β elicited a protective effect in the hearts of CVB3 infected mice, reducing the viral titers. Interestingly, 4E-BP1-/- mice showed an enhanced sensitivity to IFN-β treatment, as indicated by an approximate 2 log-fold lower viral load in mice treated with 105 U IFN-β than that measured in the 4E-BP1+/+ treated mice at the peak of infection, day 3 post-infection (Fig 2.6 A). A lesser, but still notable reduction in viral load in the hearts of 4E-BP1-/- mice was 70 also observed at the lower treatment dose of 104 U IFN-β (Fig 2.6 C). A similar protective effect was also observed in the livers of mice treated with IFN-β (Fig 2.6 B). Notably, by day 7, the virus was no longer detectable in the livers of all mice.

Figure 2.4 Mice lacking 4E-BP1 are more resistant to infection with CVB3.

Mice were infected intraperitoneally (i.p.) with a sub-lethal dose of CVB3 (103 pfu) and monitored for signs of disease (ie weight loss, reduced activity and ruffled fur). During the acute phase of infection at 1, 3 and 7 days post-infection, animals (n=4/group) were euthanized and organs collected for viral titration. Titers are plotted as mean log pfu/g tissue (±SEM). Student’s t-test indicates statistical significance (*p<0.05). Data are combined from two independent experiments.

Figure 2.4

A& Heart& B& Liver&

8& 8" 4E4BP1+/+& 7& 7" 4E4BP14/4& /g)& 6& /g)& 6" pfu 5& pfu 5" *" 4& 4" 3& 3" Titer&(log& 2& Titer&(log& 2" 1& 1" 0& 0" 0& 2& 4& 6& 8& 0" 2" 4" 6" 8" Days&Post4Infection& Days&Post4Infection&

C& Spleen& D& Pancreas&

8& 12& 7& 10& 6& /g)& /g)& 5& 8& pfu pfu 4& 6& 3& 4& Titer&(log& 2& Titer&(log& 1& 2& 0& 0& 0& 2& 4& 6& 8& 0& 2& 4& 6& 8& Days&Post4Infection& Days&Post4Infection&

Figure 2.5 Mice lacking 4E-BP1 exhibit increased expression of antiviral genes during the course of CVB3 infection.

Gene expression was measured in the hearts of mice infected i.p. with a sub-lethal dose of CVB3 (103 pfu). Following infection, mice (n= 4/group) were euthanized at days 1, 3 and 7 post infection and hearts collected for RNA extraction and cDNA synthesis. Hearts collected from littermate controls were used to measure basal gene expression levels. Real-time PCR was used to quantify gene expression of ifnb, ifna4, irf7, isg15, pkr, and oas. The housekeeping gene hprt, was used to normalize expression. Data are expressed as the mean fold induction relative to wildtype expression (±SEM). Student’s t-test indicates statistical significance (*p<0.05). Data are combined from two independent experiments.

Figure 2.5

A& IFN4β& B& IFNα4& 2.0& 2.0& 4E4BP1+/+& 1.5& 1.5& 4E4BP14/4&

1.0& 1.0&

0.5& 0.5& Fold&Induction& Fold&Induction&

0.0& 0.0& 0& 1& 3& 7& 0& 1& 3& 7& Days&Post4Infection& Days&Post4Infection&

C& IRF47& D& ISG15& 1000000& 1000& 100000& 10000& 100& *" 1000& 10& 100& 10& Fold&Induction& 1& Fold&Induction& 1& 0& 0& 0& 1& 3& 7& 0& 1& 3& 7& Days&Post4Infection& Days&Post4Infection&

E& PKR& F& 2'5'OAS& 12& 25& *"

10& 20& 8& 15& 6& 10& 4& *" Fold&Induction& Fold&Induction& 2& 5&

0& 0& 0& 1& 3& 7& 0& 1& 3& 7& Days&Post4Infection& Days&Post4Infection&

Figure 2.6 Mice lacking 4E-BP1 are more sensitive to the effects of treatment with IFN-β during infection with CVB3.

In separate experiments mice (n= 5 / group) were treated i.p. with 105 U (A, B) and 104 U (C) IFN-β 4 h prior to i.p. infection with a sub-lethal dose of CVB3 (103 pfu). Mice were euthanized at the indicated days following infection and organs collected to determine viral titers. Titers are expressed as the mean log pfu/g tissue (±SEM). Data in A, B are combined from 3 independent experiments, and data in C are from one experiment (*p<0.05).

Figure 2.6

A& Heart& 4E4BP1+/+&carrier& 8& 4E4BP14/4&carrier& 7& 4E4BP1+/+&IFN4B&

/g)& 6& 4E4BP14/4&IFN4B&

pfu 5& 4& *" 3& *" 2& Titer&(log& 1& *" 0& 0& 2& 4& 6& 8& Days&Post4Infection&

B& Liver& 9& 8&

/g)& 7& 6& pfu 5& 4& 3& 2& Titer&(log& 1& *" §" 0& 0& 2& 4& 6& 8&

Days&Post4Infection&

C& Heart& 8&

/g)& 7& 6& pfu 5& 4& 3&

Titer&(log& 2& 1& 0& 0& 2& 4& 6& 8& Days&Post4Infection&

2.4.4 IFN-β treatment reduces inflammation in the hearts of CVB3 infected mice An important aspect of CVB3-induced myocarditis is the degree of infiltration of leukocytes into the infected myocardium. In an earlier study we showed that IFN-β null mice are more susceptible to CVB3-induced myocarditis, with increased infiltration of leukocytes into the myocardium (295). Accordingly, we next examined the effects of IFN-β treatment on leukocyte trafficking into the myocardium of CVB3-infected mice and assessed whether or not translational suppression mediated by 4E-BP1 contributes to a reduction in this leukocyte infiltration (Fig 2.7). Scoring of H&E stained heart sections confirmed the previously described observation that IFN-β treatment reduces myocardial inflammation (Fig 2.7 II). Our data reveal that there are less inflammatory infiltrates in the hearts of untreated 4E-BP1-/- mice than 4E-BP1+/+ mice. We were unable to detect a difference in the extent of myocardial leukocyte infiltration between untreated and IFN-β treated 4E-BP1-/- mice. Close examination of infiltrating cells at high magnification (400x), reveals different immune cell types, including monocytes, neutrophils and T cells (Fig 2.7, panels G-I).

78 Figure 2.7 CVB3 infected 4E-BP1-/- mice exhibit less severe pathology

(I) Representative hematoxylin and eosin–stained sections of hearts from 4E-BP1+/+ (naïve (A), PBS treated (B) and IFN-β treated (C)) and 4E-BP1-/- (naïve (D), PBS treated (E) and IFN-β treated (F)) mice harvested on day 7 post-CVB3 infection. 40 x magnification. Leukocyte infiltration is indicated in the hearts of 4E-BP1+/+ mice 7 days post-CVB3 infection (G) (400x magnification). Monocyte (M), neutrophil (N) and T cell (T) enlarged images are shown in H and I. (II) Heart sections were scored blind for degree of leukocyte infiltration 0 (normal), 1 (lesion extent not exceeding 1% of a transverse section), 2 (not exceeding 10%), 3 (not exceeding 50%), 4 (exceeding 50%) Data are expressed as the mean score ± SEM. * p≤ 0.05 (Student’s t-test).

Figure 2.7

(I)&

(II)& 3& *" *"

2& 0.009& 0.07& 0.05&

1& InWiltrate&Score&

0& 1" 4E4BP1& +/+& 4/4& +/+& 4/4&

Carrier& IFN4β&

80 2.4.5 IFN-β exerts a strong antiviral effect in influenza virus-infected mice which lack the translational suppressor 4E-BP1. Type I IFNs are critical for the generation of an effective antiviral response during influenza virus infections, mediating both direct inhibitory effects on viral replication and modulation of cellular immunity which limits viral replication and spread (232, 432-434). The importance of type I IFNs as antivirals is underscored by the number of different mechanisms that influenza viruses employ to antagonize an IFN response to infection (232, 435). Accordingly, we reasoned that the enhanced sensitivity to type I IFN observed in 4E- BP1-/- mice during CVB3 infection may, similarly, occur in mice infected with influenza virus. Earlier in vitro studies with 4E-BP1-/- and 4E-BP2-/- MEFs provided evidence for reduced permissivity to infection with influenza virus, a consequence of increased IRF7 and IFN expression (191). In agreement, we provide evidence for reduced weight loss in the 4E- BP1-/- mice compared with the wildtype mice, during the course of influenza virus infection, and lower lung viral titers (Fig. 2.8). Additionally, our results show that IFN-β treatment confers greater protection in the 4E-BP1-/- mice than the 4E-BP1+/+ mice: less weight loss and lower viral titers (Fig. 2.8). In 4E-BP1-/- mice, treatment with IFN-β produces a 58% (2.4 fold) reduction in viral burden versus a 46% (1.8 fold) reduction measured in 4E- BP1+/+ mice.

81 Figure 2.8 IFN-β exerts a stronger antiviral effect in influenza virus-infected mice which lack the translational suppressor 4E-BP1.

Mice (n= 3/group) were treated with IFN-β (105 U) or mock treated with PBS carrier 12 h prior to intranasal inoculation of 200 pfu influenza virus A/WSN/33 (H1N1). During the course of infection, weight loss in animals was recorded daily (A). At 3 and 6 days post- infection, animals were euthanized and lungs collected for determination of viral titers by plaque assay on MDCK cells (B). Titers are expressed as mean pfu/g (±SEM). Student’s t- test indicates statistical significance between untreated and IFN-β treated 4E-BP1+/+ (*) and 4E-BP1-/- (§) mice. Data are representative of two independent experiments.

82 Figure 2.8

100& 4E4BP1+/+&(Carrier)& 4E4BP14/4&(Carrier)& 4E4BP1+/+&(IFN4B)& 4E4BP14/4&(IFN4B)& 90&

80& Weight&(%&Baseline)&

70& 0& 1& 2& 3& 4& 5& 6& 7&

Days&Post4Infection&

B& Lungs& 7&

4& /g&x&10^6)& 3& *" pfu 2& §"

Titer&( 1&

0& 0& 1& 2& 3& 4& 5& 6& 7& Days&Post4Infection&

83 2.5 Discussion

IFNs exhibit pleiotropic effects in the context of innate and adaptive immunity. Accordingly, they have clinical application as therapeutics for viral, neurodegenerative and malignant diseases (4). Type I IFNs are rapidly produced in response to virus infection, inducing an antiviral state in neighbouring cells and thereby limiting the spread of virus. Following cell surface receptor activation in target cells, IFNs-α/β invoke a series of intracellular signaling events that culminate in the expression of approximately 300 IFN sensitive genes. In addition to the well described transcriptional regulation exerted by IFNs-α/β through the Janus kinase/signal transducers and activators of transcription pathway, we have identified a novel pathway whereby IFNs-α/β coordinately regulate translation though the phosphatidylinositol-3 kinase/mammalian target of rapamycin (PI-3’K/mTOR) pathway (202, 436, 437). Other studies have highlighted important roles for PI-3’K/mTOR signaling in the regulation of IFN-α/β induction via Toll-like receptor signaling (100, 210, 219) and there is evidence that the absence of translational suppressors 4E-BP1/2 enhances the production of virus-induced IFN-α/β (191).

Distinct from these studies, which investigated the importance of PI-3’K/mTOR signaling in the induction of IFNs-α/β by viral or synthetic stimuli, we sought to examine the effects of IFN-α/β treatment on the PI-3’K/mTOR pathway in the context of viral infection. Given the evidence supporting an important role for IFN-α/β in viral myocarditis, and our earlier observation that cells lacking the translational suppressor 4E-BP1 are more sensitive to IFN-α treatment, we reasoned that treating 4E-BP1 null mice with IFN-β would elicit a more robust innate immune response to CVB3 infection. Our data suggest that 4E-BP1 null mice are already more resistant to infection with CVB3, possibly as a consequence of enhanced expression of endogenous type I IFNs and ISGs. Interestingly, in the hearts of 4E- BP1-/- mice we observed enhanced mRNA expression of 2’5’OAS, an upstream antiviral factor regulating RNaseL, which has previously been shown critical to survival during infection with CVB4 (583).

84 Within the microarchitecture of the myocardium unique roles have been attributed to cardiac fibroblasts and cardiac myocytes in the context of a viral infection (438, 439). A model has been proposed whereby cardiac myocytes express high basal levels of IFN-β, thereby inducing high basal levels of interferon regulatory factor 7 in an autocrine fashion. This effectively pre-arms the myocyte innate immune response to rapidly produce IFN-α in response to viral infection and stimulate fibroblasts to produce antiviral proteins to further limit viral spread. Intriguingly, fibroblasts express high basal levels of the IFN-α/β receptor 1 and are thus highly sensitive to the IFN-α/β produced by myocytes. We speculate that this cooperative interplay between cardiac myocytes and cardiac fibroblasts is affected in the absence of translational repression, in such a way as to enhance the innate immune response through the translation of antiviral proteins.

Data presented here demonstrate the importance of translational regulation in an IFN-α/β antiviral response to infection. Our studies examining ISG15 protein expression indicate a rapid response to IFN-α/β treatment, with noticeable differences observed among wildtype, 4E-BP1-/- and TSC2-/- MEFs, evident after 6 hours of treatment. One-step growth curves for CVB3 and related enteroviruses display logarithmic viral replication between 4 to 8 hours following infection. Thus, a rapid induction of the antiviral state is absolutely critical to limiting viral replication and spread.

Consistent with previously published in vitro data using encephalomyocarditis virus, we show that MEFs lacking the translational suppressors 4E-BP1 or TSC2 are more sensitive to the effects of IFN-α4 and IFN-β treatment than their wildtype counterparts when infected with CVB3 or VACV. It is worth noting that although CVB3 is considerably more virulent, and antagonizes an IFN-α/β response (440, 441), enhanced IFN-α/β responsiveness is still observed in 4E-BP1-/- cells.

Viral myocarditis is a particularly insidious disease, as acute viral infection of the myocardium often leads to autoimmunity, where the host’s own inflammatory immune response damages the heart, ultimately leading to dilated cardiomyopathy. Several studies have shown that a reduction in T cell infiltration into the heart improves the outcome of

85 viral myocarditis and that type I IFNs contribute toward limiting T cell infiltration (429, 442-444). As anticipated, our data revealed less cell infiltration in the hearts of mice treated with IFN-β. We speculate that this may be due to a reduced level of necrosis in the myocardium, resulting from an inhibition of viral replication by IFN-β. It is also interesting to note that the degree of leukocyte infiltration in mock treated 4E-BP1-/- mice was comparable to the level of infiltration measured in IFN-treated mice. Although the viral titers do not reflect a difference between 4E-BP1+/+ and 4E-BP1-/- mice early in the infection, at 7 days post-infection the mock treated 4E-BP1-/- mice appear to be clearing virus as efficiently as the IFN-β treated mice. Given the immunopathologies associated with chronic infection, the accelerated clearance of virus observed in 4E-BP1-/- mice may have clinical implications in diseases such as type I diabetes and viral myocarditis.

The type I IFN antiviral response is critical to the resolution pulmonary influenza virus infection through regulation of innate and adaptive immune processes (74, 445, 446). A strong determinant of influenza virulence has been linked to the non-structural protein-1 (NS1) which suppresses type I IFN-mediated induction of ISGs (232, 447). Consistent with our in vitro data which demonstrate enhanced expression of ISGs in the absence of translational suppression through either TSC2 or 4E-BP1, we also show reduced viral titers in the lungs of 4E-BP1-/- mice treated with IFN-β and infected with a sub-lethal dose of influenza virus A/WSN/33. IFN-β-mediated antiviral effects were most apparent 3 days post-infection, but these effects were diminished by day 7 post-infection. We speculate that multiple post-infection treatments with IFN-β may be necessary to maintain the beneficial effect of 4E-BP1 during the resolution of infection.

Data presented in this study provide evidence supporting the utility in targeting the PI3’K/mTOR signaling pathway, specifically the translational suppressor 4E-BP1, to augment the antiviral activity of IFN-β in the context of different virus infections.

Chapter 3

IFN-β regulation of glucose metabolism is PI-3’K/Akt-dependent and important for antiviral activity against Coxsackievirus B3

Chapter 3 was published as:

Burke JD, Platanias LC, Fish EN. 2014. Beta interferon regulation of glucose metabolism is PI-3’K/Akt dependent and important for antiviral activity against coxsackievirus B3. J. Virol. 88:3485–3495.

JDB performed all experiments, analyzed data and drafted the manuscript.

87 3.1. Abstract An effective type I interferon (IFN)-mediated immune response requires the rapid expression of antiviral proteins that are necessary to inhibit viral replication and virus spread. We provide evidence that IFN-β regulates metabolic events important for the induction of a rapid antiviral response: IFN-β decreases the phosphorylation of AMPK, coincident with an increase in intracellular ATP. Our studies reveal a biphasic IFN-β- inducible uptake of glucose by cells, mediated by PI-3’K/Akt, and IFN-β-inducible regulation of GLUT4 translocation to the cell surface. Additionally, we provide evidence that IFN-β regulated glycolytic metabolism is important for the acute induction of an antiviral response during infection with Coxsackievirus B3 (CVB3). Lastly, we demonstrate that the anti-diabetic drug, metformin, enhances the antiviral potency of IFN-β against CVB3 both in vitro and in vivo. Taken altogether, these findings highlight an important role for IFN-β in modulating glucose metabolism during a virus infection, and suggest that the use of metformin in combination with IFN-β during acute virus infection may result in enhanced antiviral responses.

3.2. Introduction Type I interferons (IFNs)-α/β are pleiotropic cytokines that were originally identified for their ability to interfere with viral replication (1) and are now recognized for their potent immunomodulatory effects (2, 44, 448). Engagement of their cognate heterodimeric receptor, comprised of IFNAR1 and IFNAR2, initiates signaling which culminates in the expression of interferon stimulated gene (ISG) associated proteins, critical for antiviral activity. Given the rapid replication of viruses, in the order of several hours (449-452), the IFN-α/β response must be equally fast and robust , with the rapid production of IFN-β and subsequent activation of signaling cascades downstream of IFNAR1 and IFNAR2 within hours of infection (296, 453, 454). IFNAR activation by IFN results in the induction of ISGs (455-457). This rapid response initiated by IFN-αs and IFN-β is governed by a series of signaling effectors that are intermediates in the JAK/STAT, MAPK and PI-3’K/mTOR pathways, which coordinately regulate the transcriptional and translational expression of ISGs (20, 448).

Previously, we and others have shown signaling effectors in the PI-3’K/mTOR pathway to be critical in governing an effective IFN-α/β mediated antiviral response. Cells lacking p85α/β or Akt1/2, showed defective antiviral responses and reduced IFN-α/β inducible ISG protein expression (200, 201). Pharmacological inhibition of PI-3’K, Akt or mTOR inhibits IFN-β mediated suppression of HCV in a cell-based replicon system (458). Additionally, cells lacking repressors of IFN-α/β mediated translational regulation, namely TSC2 or 4E- BP1, show enhanced responsiveness to IFN-α/β and greater inducible expression of ISG proteins (202, 459). In mice lacking the translational suppressor 4E-BP1 we also showed enhanced IFN-β antiviral potency on infection with Coxsackievirus B3 (CVB3) (459).

Since protein synthesis consumes a large proportion of cellular ATP, cellular processes are required to maintain energy homeostasis during the induction of translation. AMPK, an important sensor of cellular ATP flux, is invoked to balance energy consuming pathways, mediated by regulation of mTOR and glucose uptake (460). Indeed, various growth factors (insulin, PDGF, IGF-1, VEGF) and cytokines (IL-3, IL-5, IL-6, IL-7, GM-CSF, TNF-a, CCL5) that

89 signal through PI-3’K/Akt/mTOR have been shown to regulate glucose metabolism, specifically through the PI-3’K/Akt/mTOR pathway (455-457, 461-473). Cognizant that IFNs-α/β engage PI-3’K/Akt/mTOR signaling to upregulate protein synthesis, we undertook studies to investigate any influence that IFN-β may exert on glucose metabolism in the context of protection from viral infection. Our data suggest IFN-β mobilization of metabolic events. Given the common signaling effectors downstream of their respective cell surface receptors between IFN-β and insulin, we examined the effects of metformin, an insulin sensitizer, during an acute viral infection with CVB3. Our data reveal that IFN-β treatment engages mechanisms that meet the energy requirements of cells thereby enabling an IFN-β induced antiviral response and that metformin enhances the antiviral effects of IFN-β.

3.3. Materials and Methods

3.3.1. Cells, virus and reagents. Recombinant mouse IFN-β was provided by Dr. Darrin Baker, Biogen Idec (Cambridge MA, USA). Human insulin was purchased from Eli Lilly. Immortalized mouse embryonic fibroblast (MEF) cultures were derived from transgenic mice are described elsewhere: p85a-/-β-/- (200, 436, 437, 474), Akt1-/-2-/- (201, 475, 476), TSC2-/- (202, 477, 478), AMPKa1-/-a2-/- (479, 480) Cells were cultured in RPMI-1640 (Sigma) supplemented with 10% FCS (Hyclone) and antibiotics. Coxsackievirus B3-CG (CVB3) was available in the laboratory as a stock of 1.3x109 plaque forming units (PFU)/mL. Monoclonal anti-phospho- AMPK (Thr172) was purchased from Cell Signaling and monoclonal anti-alpha-Tubulin was purchased from Sigma (Mississauga, ON). Monoclonal anti-phosho-STAT1 (Tyr 701) and monoclonal anti-ISG15 were purchased from Cell Signaling Technology (Danvers, Massachusetts). Monoclonal anti-GLUT4 (clone 3G10A3) was purchased from Abcam (Cambridge, UK). Metformin was purchased from Sigma (St. Louis, MO). 2-deoxy-D-glucose (2-DG) was purchased from Sigma (Mississauga, ON). 2-[1,2-3H(N)]-Deoxy-D-Glucose was purchased from Perkin Elmer (Massachusetts, USA).

3.3.2. Cell Lysis and Immunoblotting Cells were cultured in medium containing 2% FCS for 16 h, then either left untreated or treated for the indicated times with 10mM 2-DG, in the absence or presence of 1000 U/mL of IFN-β, or with 1000 U/ml IFN-β alone, then the medium aspirated and the cells lysed with RIPA buffer (Cell Signaling) containing a protease and phosphatase inhibitor cocktail (Cell Signaling). 5x Laemmli reducing buffer was added and samples boiled for 10 minutes. 30µg of protein lysate was resolved on a 12% SDS-PAGE gel and transferred overnight to a Immobilon PVDF membrane, and blocked in TBST containing 5% BSA (w/v) and 0.1% Tween-20 (v/v). Blots were then probed with the indicated antibodies and visualized by chemiluminesence (BioRad).

3.3.3. Glucose Uptake Assay

91 Sub-confluent cell monolayers were cultured in 6-well plates in 2% FCS medium for 16 h at 37°C in 5% CO2, then treated with vehicle, IFN-β or insulin at the indicated doses for the indicated times. Cells were washed twice with Krebs Ringer HEPES (KRH) buffer, followed by addition of 1mL of KRH containing 0.5 uCi/mL 2-[1,2-3H(N)]-Deoxy-D-Glucose (29.8Ci/mmol). Cells were then incubated at 37°C for 10 minutes and 3H-2-deoxy-D- glucose (3H-2-DG) uptake was terminated quickly by placing plates on ice, and washing 3 times with ice-cold PBS. Cells were then lysed by the addition of 500µLof Milli-Q water followed by freezing and thawing. 3H-2-DG uptake was measured in a liquid scintillation counter (PerkinElmer).

3.3.4. Intracellular ATP Determination Sub-confluent monolayers of MEFs were cultured in 10mm plates in 2% FCS medium for 16 h prior to treatment with mIFN-β or 2-DG. Cells were treated with 10mM 2-DG or control medium for 30 minutes prior to the addition of mIFN-β for 1 hour. Medium was aspirated and cells immediately lysed by the addition of 2.5% TCA, 4mM EDTA. Cell lysates were then diluted 10 times with 100mM Tris, 2mM EDTA, pH 7.75 and assayed for intracellular ATP using the ATP Bioluminescent Assay Kit (Sigma).

3.3.5. GLUT4 Measurement Sub-confluent MEF monolayers were cultured in 2% medium for 16 hours. Cells were then trypsinized and resuspended in 2% FCS medium at a density of 106 cells/mL. Cells were kept in FACS tubes for 2 h at 37°C in 5% CO2. IFN-β or insulin were then added to the cells for the indicated time, after which the cells were fixed with 2% formalin in 2% serum containing FACS buffer, and subsequently washed with FACS buffer before staining with anti-GLUT4 antibody. Alexfluor-488 conjugated goat anti-rabbit was used as a secondary antibody. Cell fluorescence was measured using a BD FacsCalibur flowcytometer and analyzed using BD Cellstar software.

3.3.6. CVB3 Infection of MEFs MEFs were cultured in 2% FCS medium for 16 h. IFN-β was added 6 hours prior to infection with CVB3-CG at an moi of 1 (1 pfu/cell). After 8 hours of incubation with virus, cells were

92 washed twice with PBS and viral titers measured by plaque assay using HeLa cells, as described previously (295, 459). For those experiments where the influence of 2-DG on IFN-β inducible antiviral effects was evaluated, 2-DG was added either 30 min prior to IFN- β treatment, or at specified times following IFN-β treatment, and remained in the medium for the duration of virus infection. In experiments evaluating the effect of metformin on IFN-β, metformin (10mM) was added 30 min prior to treatment with the indicated doses IFN-β, and remained in the medium for the duration of virus infection. Quantitation of differences between untreated and IFN-β treated cells in each group were calculated by dividing viral titers determined in untreated cells by the titers determined in treated cells and expressing this value as a fold-reduction.

3.3.7. In vivo studies Female C57Bl/6J mice aged 8-12 weeks were ordered from Taconic or The Jackson Laboratory and housed in pathogen free conditions. All procedures were approved by the Toronto General Research Institute Animal Care Committee. One day prior to infection, treated mice were administered metformin ad libitum at a dose of 200mg/kg/day, based on previous measurements of daily water consumption. Water consumption was found to be equivalent in both metformin treated and control animals. Normal drinking water was given to the mice at the time of infection. Prior to CVB3 infection, mice were administered an intraperitoneal injection of 105 U of mIFN-β. Four hours later, mice were infected by intraperitoneal injection with a sublethal dose of CVB3 (103pfu). At 3 days post infection, mice were euthanized and tissues aseptically harvested and frozen in liquid nitrogen. After 3 freeze-thaw cycles, viral titers were determined by plaque assay in HeLa cells as described previously (295, 459).

3.3.8. Statistical Analysis Statistical significance was measured by analysis of variance. p values ≤0.05 were considered statistically significant. Data are expressed as mean ± S.E.

93 3.4 Results

3.4.1. Effects of IFN-β on AMPK phosphorylation and intracellular ATP Since AMP-activated protein kinase (AMPK) is a central sensor and regulator of cellular ATP stores, at the outset we undertook studies to determine any effects that IFN-β would exert on AMPK activation, by examining phosphorylation of AMPK on Thr172. As anticipated, IFN-β treatment of wild type (WT) MEFs resulted in the rapid tyrosine phosphorylation of STAT1 (Figure 3.1A). A simultaneous decrease in AMPK activation, i.e. Thr172 phosphorylation, was observed (Figure1A). Next, we examined the effects of IFN–β treatment on ATP production and the data in Figure 1B show a dose-dependent increase in IFN-β-inducible ATP production. This IFN-β inducible ATP is inhibited in the presence of the non-metabolized analog of glucose, 2-DG (Figure 3.1B).

94 Figure 3.1. IFN-β reduces AMPK phosphorylation and increases intracellular ATP.

(A) MEFs were treated with 1000 U/mL IFN-β for the indicated times. Cells were harvested and protein lysates resolved by SDS-PAGE and immunoblotted with anti-phospho-AMPKα (Thr172) or anti-phospho-STAT1 (Tyr701) antibodies. Membranes were stripped and reprobed with anti-AMPKα or anti-α-Tubulin antibody for loading. Phosphorylation is shown relative to untreated cells and normalized for loading. Data are representative of two independent experiments (±SEM). (B) MEFs were either pre-treated with medium or 10mM 2-DG for 30 min prior to treatment with the indicated doses of IFN-β for 1 h. Cells were lysed and intracellular ATP quantified by a bioluminescent assay. Quantification is shown relative to control treated samples. Data are representative of 4 independent experiments (±SEM). *, p<0.05.

95 Figure 3.1

A pAMPK

AMPK

pSTAT1

tubulin

Time (min) 0 10 20 30 60 120

pSTAT1 (y701) pAMPK (Thr 172)

15 1.5

10 1.0

5 0.5 Fold Induction Fold Fold Induction Fold

0 0.0 0 20 40 60 80 100 120 140 0 20 40 60 80 100 120 140 Time (min) Time (min)

B 105 * * Control 10 mM 2-DG

100

(% (% Control) 95 Intracellular [ATP] [ATP] Intracellular 70

0 1 10 100 1000 10000 IFN-β (U/mL)

96 3.4.2. IFN-β induces glucose uptake mediated by regulation of the PI-3’K/Akt signaling cascade.

As glucose is a major source of cellular ATP, we next investigated the influence of IFN-β treatment on glucose uptake. In time course experiments we identified a biphasic enhancement of glucose uptake by IFN-β treated cells (Figure 3.2A). Using 3H-2-DG, we observe a rapid spike in 3H-2-DG uptake within minutes of IFN treatment, followed by a sustained decrease in uptake over a period of hours. Subsequent studies revealed that the influence of IFN-β treatment on glucose uptake is dose-dependent, albeit less potent than the effects observed for 100nM insulin treatment (Figure 3.2B).

To identify potential IFN-regulated signaling effectors that might contribute to regulation of glucose uptake, we employed a panel of MEFs with targeted disruption of elements of the PI-3’K/Akt/mTOR signaling cascade (Figure 3.2C). Earlier published studies have shown that MEFs with targeted disruption of the p85 subunits of PI-3’K or Akt1/2 fail to respond to the antiviral effects of IFN when challenged with virus (200, 201). By contrast, targeted disruption of TSC1/2, results in enhanced responsiveness to the antiviral effects of IFN (202). In contrast to wild type MEFs that respond to IFN-β treatment with a modest but rapid uptake of 2-DG, cells that lack the p85α/β subunits of PI-3’K or Akt1/2 had decreased 3H-2-DG uptake (Figure 3.2C) in response to IFN-β treatment. In terms of 3H-2-DG uptake, cells lacking TSC2 remained responsive to treatment with IFN-β, whereas cells lacking AMPKα1/2 exhibited an intermediate responsiveness to treatment with IFN-β (Figure 3.2C).

Glucose uptake is mediated by cell surface glucose transporters (481). Amongst these, GLUT4 is responsive to insulin treatment. Notably, insulin also regulates glucose uptake mediated by PI-3’K signaling (468, 482). Accordingly, we examined the effects of IFN-β treatment on cell surface expression of GLUT4 and observed a modest, yet reproducible, increase in expression by one hour (Figure 3.2D).

97 Figure 3.2.

(A) MEFs were either treated with medium or 1000 U/mL IFN-β for the indicated times. At time 0, cells were washed and then incubated with 0.5 uCi 3H-2-deoxy-D-glucose for 10 min. Reactions were quenched and radioactivity measured by liquid scintillation counting. Data are shown relative to control treated samples at each time point and are combined from 3 independent experiments (±SEM). (B) MEFs were either treated with the indicated doses of IFN-β or 100nM insulin for 1 h. Uptake was measured as described above. Data are shown relative to control treated samples and are combined from 3 independent experiments (±SEM). * p<.05. C, MEFs were either treated with medium or 1000 U/mL IFN- β for 1 h. Uptake was measured as described above. Data are combined from 3 independent experiments (±SEM). * p<.05. D, Serum starved MEFs were either treated with medium, 1000 U/mL IFN-β or 100nM insulin for 1 h. Cells were fixed with 2% paraformaldehyde and stained for surface GLUT4 expression and analyzed by FACS and quantified for mean fluorescence intensity (MFI). Data are shown relative to medium treated control and collected from 4 independent experiments (±SEM).

98 Figure 3.2

A B

120 120 *

110 110 * *

100 (% Control) (% (% Control) (% 100 H-2-DG Uptake Uptake H-2-DG H-2-DG Uptake Uptake H-2-DG 3 80 3

60 90 0 10 20 30 0 10 50 100 1000 Insulin (100nM) Time (hr) IFN-β (U/mL) C D

120 200 Control IFN-β * 150 110 ** ** *

100 100 MFI (% Control) (% (% Control) (% H-2-DG Uptake Uptake H-2-DG 3 50 90 0 Control IFN-β Insulin -/- WT β 2-/- (1000 U/ml) (100nM) -/- α α TSC2-/- 1-/- α p85 Akt1-/-2-/-

AMPK

99 3.4.3. Inhibition of glycolysis affects the antiviral activity of IFN-β To investigate the importance of glycolytic metabolism during an IFN-induced antiviral response we next examined the effects of 2-DG treatment on an IFN-induced anti-CVB3 response. When cells were treated with IFN-β in the presence or absence of 2-DG, we observed a dose-dependent blunting of the IFN-β inducible antiviral response in the presence of 2-DG (Figure 3.3A). 2-DG treatment alone also inhibits viral replication. To further demonstrate the importance of glycolytic metabolism during the earliest stages of an IFN-induced antiviral response, we added 2-DG at various times relative to IFN-β treatment and examined the antiviral response (Figure 3.3B,C). The results indicate that inhibition of glycolysis by 2-DG inhibits an IFN response in a time - dependent manner, specifically during the earliest induction phase of an IFN response (Figure 3.3C). Additionally, expression of the IFN-β inducible antiviral protein, ISG15, was also sensitive to glycolytic inhibition by 2-DG (Figure 3.3D). Given that the IFN-β dose employed, 103U/ml, induces a robust antiviral response in vitro, the inhibitory effects of blocking glycolysis underscores the relevance of glycolysis to an IFN-induced antiviral response.

100 Figure 3.3. Glucose metabolism is critical for induction of an IFN-β mediated antiviral response.

(A) MEFs were pretreated with medium or indicated doses of 2-DG 30 min prior to addition of medium or 1000U/mL IFN-β for 6 h. Cells were then infected with CVB3 at a dose of moi=1. Cells were washed and lysed by freeze thaw after 8 h and viral titers determined by plaque assay. Data are shown as pfu/mL and the antiviral effect indicated as a fold reduction relative to medium. Data are from 3 independent experiments (±SEM). (B, C) MEFs were treated with either medium or 1000 U/mL IFN-β 6 h prior to infection with CVB3 (moi=1). At the indicated times following IFN-β treatment, 2-DG was added. Following an 8 h infection, cells were washed and lysed. Time points for 2-DG treatment are indicated as h prior to infection. Data are representative of 2 independent experiments (±SEM). IFN-β inducible antiviral effect is quantified as fold reduction relative to control treated cells. D, MEFs were pretreated with medium or 10mM 2-DG 30 min prior to addition of medium or 1000U/mL IFN-β for 6 h. Cells were harvested and protein lysates resolved by SDS-PAGE and immunoblotted with anti-ISG15 and anti-α-tubulin antibodies. Expression is shown relative to untreated cells and normalized for loading. Data are representative of technical triplicates and 3 independent experiments (±SEM).

101 Figure 3.3

A 1000000 100 Control

IFN-β 80 100000 * 60 ** ** **

pfu/ml ** 40 10000 ** Fold Reduction Fold *** 20

1000 0 0 1 5 10 0 1 5 10 2-DG (mM) 2-DG (mM)

B CVB3 Lyse IFN-β

2-DG

Time (hr) -6 -5 -4 -2 0 8

C 1000000 150 Control IFN-β

100000 100

pfu/ml ** 10000 50 * ** ** ** Reduction Fold *

1000 0 5 4 2 0 5 4 2 0 Time (hr) Time (hr)

D 4

3 ISG15

2 tubulin Fold Induction Fold FoldInduction 1 - - IFN-β + +

2-DG - + - + 0 IFN-βIFN-β + + 2-DG - + 2-DG - +

102 3.4.4. Treatment with metformin enhances the antiviral activity of IFN-β. Metformin, an anti-diabetic drug, increases insulin sensitivity, activates AMPK and enhances GLUT4 translocation to the cell surface (483). Accordingly, we next examined the effects of combination treatment with IFN-β and metformin against CVB3 infection of MEFs. As shown in Figure 4A, treatment of MEFs with a combination of metformin and IFN-β led to an enhanced antiviral response, above that of either treatment alone.

In a final series of experiments, given our preceding data that suggest a role for IFN-β in regulating metabolic events that would meet the energy needs of a cell to invoke an antiviral response, we examined the effect of combination treatment with IFN-β and metformin on CVB3 infection in mice. Our earlier published studies identified that IFN-β treatment is protective against infection with cardiotropic CVB3 (295, 459). When infected with CVB3, mice exhibit signs of infection – reduced activity and ruffled fur. Heart viral titers indicate acute virus infection, with peak viral burden three days post-infection, then progressive clearance of the virus from the heart (459). Mice were allowed ad libitum access to metformin in their water supply. We observed no difference in water consumption whether metformin was included in the water or not. Mice were either left untreated or treated with IFN-β, then challenged with CVB3. Three days post-infection all mice were euthanized and blood and various tissues aseptically harvested and viral titers measured. The results in Figure 3.4B demonstrate that combination treatment with IFN-β and metformin significantly reduced heart, liver, spleen and serum viral titers compared with IFN-β or metformin alone. A similar trend was observed, although less pronounced in the pancreata of infected mice.

103

Figure 3.4. Metformin enhances antiviral effect of IFN-β during infection with CVB3.

(A) MEFs were either left untreated or treated with 10mM metformin 30 min prior to treatment with the indicated dose of IFN-β. Following 6 h of treatment, cells were infected with CVB3 for 8 h. Data are combined from 3 independent experiments, and shown as mean pfu/ml (±SEM). (B) Mice were administered metformin ad libitum in drinking water prior to treatment with IFN-β for 4 h prior to infection with CVB3. At three days following infection, mice were sacrificed and tissues collected for determination of viral titers. Data are combined from 5 independent experiments and shown as mean log pfu/g (±SEM). Data from 15 mice were collected for each treatment group. p values are given relative to control treated samples *p<.05, ***p<.001.

104 Figure 3.4

A 50000

40000

30000

pfu/ml 20000

10000

0 IFN-β (U/mL) 0 10 0 10 100 Metformin (mM) 0 0 10 10 0

Heart B Liver 7 8

6 *** 7 *** log pfu/g log pfu/g 5 6

4 5 IFN-β - + - + IFN-β - + - + Metformin - - + + Metformin - - + +

Spleen Pancreas 8 9

* 7 8 log pfu/g log pfu/g 6 7

5 6 IFN-β - + - + IFN-β - + - + Metformin - - + + Metformin - - + + Serum 7

6 *

log pfu/ml 5

4 IFN-β - + - + Metformin - - + +

105 3.5. Discussion Type I IFNs exert their immunomodulatory influence in a wide variety of cell types and, in the context of virus infections, do so rapidly to inhibit virus replication and limit virus spread. This antiviral activity is mediated by transcriptional and post-transcriptional signaling proteins including STATs, MAPKs and PI-3’K (20). In recent years, the role of type I IFNs in regulating PI-3’K/mTOR-mediated post-transcriptional effects has become better defined, with a significant area of focus on translational regulation (200-202, 437, 458, 484-486). It has become increasingly apparent that mTOR is a central sensor of metabolic stresses and, in addition to translation, regulates processes such as autophagy and lipid and carbohydrate metabolism, thereby maintaining cellular energy homeostasis (94). Herein, we report on the influence of IFN-β on glucose metabolism in the context of virus infection.

Given the high energy demands of IFN-inducible protein synthesis, we anticipated an effect on AMPK activation and cellular ATP synthesis accompanying treatment with IFN-β. Indeed, IFN-β treatment reduced AMPK phosphorylation at Thr172, associated with a concurrent increase in STAT1 phosphorylation at Tyr701, that is indicative of an IFN-β inducible cell response. Since AMPK is a sensitive indicator of the cytosolic ratio of AMP:ATP (487), activated by phosphorylation in the presence of low ATP concentrations, we infer that the decrease in Thr172 phosphorylation we identified on IFN-β treatment is associated with an increase in ATP production. Indeed, IFN-β treatment of MEFs resulted in an increase in ATP production. It is unlikely that IFN-β directly regulates AMPK phosphorylation, but rather that IFN-β induces an effect which indirectly influences AMPK activation through changes in the ratio of AMP:ATP. IFN-β mediated changes in ATP levels were abrogated in the presence of the non-metabolizable glucose analog, 2-DG. This inhibition of glycolytic- derived ATP provides evidence that IFN-β influences glucose metabolism. In support of this, we demonstrate that IFN-β promotes a dose-dependent uptake of 3H-2-DG by cells.

For IFNs to be most effective as antivirals it is crucial that cells respond rapidly in terms of producing antiviral proteins that will inhibit viral replication. Accumulating data implicate IFNs-α/β in the regulation of translation of host protein synthesis and the corresponding expression of antiviral proteins. (200-202). Our data suggest that there is a rapid and

106 robust uptake of glucose by cells, within minutes of IFN-β treatment, consistent with meeting the energy demands of protein synthesis. Moreover, the nature of the biphasic response whereby glucose uptake is initially increased, followed by a suppression, is in agreement with the paradigm of type I IFN-mediated antiproliferative effects (6, 120, 488- 501). Specifically, in uninfected cells, the early translation of antiviral proteins is followed by a progressive shut-down of protein synthesis that would disable cell growth and, upon infection, inhibit viral protein synthesis. Indeed, this biphasic response is consistent with a scenario where virus replicates rapidly and infection spreads. An infected cell produces and secretes IFN-β in response to viral replication prior to viral progeny egress, thereby activating the antiviral response in neighbouring uninfected cells (453, 454, 502). Transiently, uninfected cells rapidly increase their metabolism to support the synthesis of antiviral proteins such as 2’5-OAS, PKR and RNaseL followed by the subsequent downregulation of metabolism. Upon viral spread, IFN-β primed cells respond to viral RNA by secreting additional IFN-α, thereby inhibiting further viral replication and spread.

By contrast, when astrocytes are exposed to low concentrations of IFN-α2a, IFN-α2b or IFN-β (<5U/mL), no significant changes in glucose consumption are observed over 2 hours, yet chronic exposure to low dose IFN reduces glucose uptake (501). This model of low dose, chronic IFN exposure was intended to reflect systemically low plasma concentrations of type I IFN in HCV-infected individuals over the duration of a chronic infection. By contrast, our studies reflect a scenario of localized virus infection where cells in close proximity experience high concentrations of IFNs-α/β produced by tissue resident cells or plasmacytoid dendritic cells during an acute immune response to virus infection. In other studies, Navarro et al. examined the effects of type I IFN treatment on glucose metabolism in primary mesenteric and splenic lymphocytes after 48 hours, and likewise showed a suppression of glucose uptake (503). Notably, in the earliest IFN experiments of Isaacs et al, conducted in chick embryo cells, they identified a modest IFN-inducible effect on lactate production after 4 hours, an indicator of glycolysis (504).

A number of studies have confirmed the roles of PI-3’K and Akt signaling in regulating glucose uptake induced by growth factors or cytokines in adipocytes, skeletal muscle cells

107 and lymphocytes (461-472). Our strategy was to examine the contribution of different effector intermediates in the PI-3’K/Akt/mTOR signaling cascade on the IFN-β-inducible regulation of glucose uptake that we observed, specifically using MEFs with targeted disruption of certain genes (Figure 3.5). A striking effect was observed in cells null for either p85α/β or Akt1/2. Lacking either of these two signaling effectors was sufficient to completely ablate IFN-β inducible glucose uptake. Consistent with the negative regulatory role that TSC2 exerts on mTOR activity, IFN-β inducible glucose uptake in TSC2-/- cells was unaffected. MEFs lacking mLST8, a non-essential component of mTORC1, exhibited a partial reduction in IFN-β inducible glucose uptake, suggestive of a role for mTORC1 in regulating glucose uptake. Surprisingly, in cells lacking AMPKα1/2, an upstream negative regulator of mTOR through TSC2 (505), we observed only a partial reduction in responsiveness to IFN-β inducible glucose uptake. This may be attributed to the other role that AMPK has in influencing GLUT4 translocation to the cell surface (483). Consistent with our findings of IFN-β regulation of glucose uptake, surface expression of GLUT4 was also increased upon treatment with IFN-β. PI-3’K and Akt activation are associated with GLUT4 translocation to the cell surface (468, 482), providing further support for a potential mechanism whereby IFN activation of these effectors enhances expression of glucose transporters required for glucose uptake.

Previous publications have identified that treatment of cells with 2-DG reduces the replication of a variety of viruses, including CVB3 (506, 507). Limiting the energy supplies in an infected cell would affect protein synthesis and the assembly of viral progeny. By contrast, a rapid burst of energy will enable an early robust IFN response, as we show, yet the biphasic nature of the effect we observe supports subsequent inhibition of cell growth and viral replication.

Clinical studies have drawn attention to a correlation between insulin- and IFN- sensitivity in individuals who are infected with Hepatitis C virus (508). Expression levels of TNF-α are often increased in HCV infected livers. TNF-α up-regulates the activity of the phosphatase, PTP-1B, which is responsible for the down-regulation of insulin and type I IFN signaling (509). In the same study, metformin, an inhibitor of PTP-1B, was used effectively to restore

108 insulin and IFN sensitivity in mouse livers expressing high levels of TNF-α. Indeed, metformin is used to treat insulin resistance in patients with type 2 diabetes (510). Moreover, earlier studies demonstrated the negative regulatory effects of PTP-1B on Jak/STAT signaling (134, 511-513). We therefore reasoned that metformin may be administered along with IFN-β to enhance antiviral potency during a virus infection. Coxsackie viruses encompass a group of cardiotropic viruses that can cause acute myocarditis and lead to dilated cardiomyopathy (514). While not a standard treatment for viral myocarditis, administering IFNs-α/β has been shown to improve cardiac function (388, 515). Interestingly, patient TNF-α expression levels are measured in the serum and heart during acute virus myocarditis, reflective of an inflammatory response to infection (287, 516-518). Given our data, it is intriguing to speculate that this TNF may influence endogenous type I IFN signaling in the heart, exacerbating infection. In our study, we provide evidence that metformin enhances the antiviral effects of low dose IFN-β treatment of MEFs challenged with CVB3. Similarly, treatment of mice with IFN-β and metformin prior to infection with CVB3 enhanced the antiviral effects of IFN-β, most notably reducing viral titers in the hearts, livers, spleens and sera of infected mice. We speculate that the antiviral effects of metformin alone may be associated with promoting endogenous type I IFN activity.

Viewed altogether, our data provide new evidence that IFN-β modulates glucose metabolism through a PI-3’K/Akt-dependent mechanism, and that this regulation of metabolism appears important for the induction of an effective antiviral response. Additionally, we provide evidence for the application of metformin to enhance the antiviral activity of IFN-β.

109 Figure 3.5 Schematic of IFN-β mediated regulation of PI-3’K/Akt/mTOR signaling and pharmacological agents active in this pathway.

110 Figure 3.5

IFNOα/β' Glucose'

IFNaR1' IFNaR2'

P" P" PDK1' GLUT4' PI3K' PIP2' PIP3' TYK2' JAK1' P" p110' Akt' P" P" p85' IRS1/2' P" TSC2' STATs' P" P" LY294002' P" STATs' PTP1B' TSC1' AMPK' AMP:ATP'

me=ormin' RHEB' rapamycin' me=ormin' TRANSCRIPTION' S6K' P" PRAS40' mTOR' mLST8' TRANSLATION' RAPTOR' 4EOBP1' mTORC1' P"

A A

111

Chapter 4

Discussion and Future Directions

112 4.1. Application of IFNs The past five decades of IFN research has illuminated a pleiotropic role for IFNS in governing immunity. With the increasing understanding of their powerful immunomodulatory activity, type I IFNs have been licensed in the clinic to treat a variety of diseases. The two most common indications for IFN-α/β treatment are multiple sclerosis and hepatitis C virus which respectively afflict 2.1 million and 180 million individuals worldwide (519, 520). While IFN-α/β treatment provides favourable response rates when treating both chronic diseases, there remains room for improvement as is evident by the occurrence of non-responders. Among those individuals non-responsive to IFN-α/β therapy for multiple sclerosis or HCV, pre-treatment expression levels of ISGs are higher than those of responders (412, 521). Basal activation of type I IFN signaling precludes additional responsiveness to treatment. It is evident during viral infections that sufficient induction of the type I IFN system is necessary to eliminate a pathogen. This is underscored by the number of mechanisms that viruses employ to specifically antagonize IFN-α/β signaling. Even in viruses with small genomes such as Influenza virus or Coxsackievirus, host-antagonizing proteins are essential for replicative fitness. In the absence of these antagonistic proteins, virulence is diminished and viruses are unable to overcome host immunity.

It is with the aim of modulating host sensitivity to IFN-α/β that we have investigated post- transcriptional pathways of IFN signaling. Previous studies from our laboratory have detailed the coordinate IFN-α/β regulation of protein synthesis through engagement of the PI3’K/mTOR pathway in conjunction with JAK/STAT regulated mRNA transcription of ISGs (200-202, 437, 484, 522). These in vitro studies identified signaling intermediates which influence the amplitude of an IFN-α/β response. Specifically, in the absence of either Akt or PI3’K, an impaired response towards toward IFN-α/β during infection with EMCV was observed (200, 201). This was attributed to a failure to induce protein translation. On the other hand, however, the absence of two negative regulatory proteins, TSC2 or 4E-BP1, led to an enhanced responsiveness to treatment with IFN-α/β during EMCV infection (202). In the absence of either TSC2 or 4E-BP1, IFN-α/β inducible antiviral protein expression was enhanced above that of wild type cells. These studies prompted us to expand upon these

113 observations with additional in vitro and in vivo virus infection models. During our early experiments, data were published using mice deficient for 4E-BP1 and 4E-BP2, showing them resistant to VSV and fibroblasts derived from these mice resistant to infection with EMCV, sindbis virus and influenza virus (191). The mechanism identified for enhanced resistance to infection was an increased basal expression of IRF-7 and subsequent increased inducible expression of IFN-α. Our data from 4E-BP1-/- mice also showed a modest resistance to infection with coxsackievirus B3 and influenza virus. Given the lack of exogenous IFN-α/β, this implied a stronger innate antiviral response in 4E-BP1-/- mice, possibly through a similar mechanism as reported by Colina et al. Our data showing an enhanced mRNA expression of antiviral effectors (eg ISG15, PKR, 2’5OAS) in 4E-BP1-/- mice are consistent with the higher basal protein expression of the transcription factor, IRF-7, reported by Colina et al in 4E-BP1-/- 4E-BP2-/- mice. A challenge is presented in comparing the single 4E-BP1-/- to the double 4E-BP1-/- 4E-BP2-/- since the in vivo model examined by Colina et al. (191) utilized VSV, which is exquisitely sensitive to IFN-α/β, whereas CVB3 exhibits strong antagonism towards IFN-α/β through specific cleavage of MAVS and TRIF (267). Both MAVS and TRIF are dsRNA signaling intermediates necessary for induction of IFN-β via NFκB, IRF-3 and IRF-7. Additionally, CVB3 non-structural proteins also interfere with protein secretion, MHC-I expression and cap-dependent translation (265, 423, 523, 524). Nevertheless, in both virus models, the absence of translational suppression confers a degree of enhanced innate immunity. Their investigations did not specifically address the responsiveness to treatment with exogenous IFN-α/β. In our 4E-BP1-/- model, pre-treatment of mice with IFN-β prior to infection with CVB3 showed that the 4E-BP1-/- mice are significantly more responsive to IFN-α/β mediated antiviral effects than their wild type counterparts. Interestingly, the magnitude of difference observed between viral titers among different groups of IFN-β treated and mock-treated CVB3 infected mice are much larger than those detected in influenza virus infected mice (ie logarithmic versus less than two-fold differences). It is possible that the absence of 4E-BP1, a repressor of 5’-capped mRNA translation, while enhancing IFN-α/β inducible translation of antiviral proteins, also increases the rate of translation of 5’-capped viral RNAs necessary for influenza virus replication. This effect would not be observed during CVB3 replication since virus replication is IRES driven, and independent of 5’-

114 capped-RNA translation. Alternatively, the antagonism of IFN-α/β signaling may also be stronger for influenza virus than that observed with CVB3, and thus account for the diminished antiviral effects observed during influenza infection. Differences in the timing of IFN-β administration could have also influenced the resultant antiviral effect. Mice infected with influenza virus were treated with IFN-β 12 hours prior to infection, whereas mice infected with CVB3 were treated only 4 hours prior to infection. Imaging studies from Mx-luciferase reporter mice suggest that ISG expression peaks between 4 and 12 hours following IFN-α/β treatment (457). Interestingly, a temporal pattern of ISG expression has been suggested whereby different classes of ISGs are expressed in temporal patterns of early, intermediate, late and very late expression (525). Hence, the timing of IFN-β administration could exert differential effects.

4.2. 4E-BP1 regulation of mRNA translation Data from our experiments provide evidence of an important role for IFN-α/β in governing post-transcriptional elements of innate immunity, and indicate areas of further investigation. From several studies, it is well understood that type I IFNs engage translational regulation by phosphorylation of multiple targets including 4E-BP1, EIF4E, EIF4B, PDCD4 and rpS6, which in turn influence the rapid synthesis of antiviral proteins. However, it is not well understood how this additional layer of regulation beyond transcriptional signaling influences the translation of specific IFN-α/β stimulated mRNAs. Previously, in our lab, the CCL5-sensitive MCF-7 breast cancer epithelial cell line was used to demonstrate a mechanism for post-transcriptional regulation of several specific mRNAs (cyclin-D1, c-myc, dad-1) through CCL5 activation of mTORC1 (526). These mRNAs were identified by microarray analysis of transcripts associated with polyribosomes. Through similar profiling experiments, differential association of mRNA transcripts with polyribosomal fractions was identified in 4E-BP1-/- 4E-BP2-/- MEFs relative to wild type cells (191). In the absence of 4E-BP1 and 4E-BP2, the IRF-7 transcript was enriched in polyribosomes, and expressed in greater abundance at the protein level. Consequently, enhanced IRF-7 translation yielded increased IFN-α production upon PAMP stimulation. In MEFs possessing an altered regulatory residue (Ser209) in eIF4E, a similar mRNA-selective phenomenon was also observed (527). In eIF4E (S209A) MEFs, however, association of the

115 IκBα transcript with polyribosomes was decreased, thereby producing reduced amounts of the protein. Since IκBα is a negative regulator of NFκB, reduced expression of the negative regulator indirectly influenced increased expression of IFN-β upon PAMP stimulation. This mechanism for selective mRNA translation by translation initiation factors is not well understood. While there is some redundancy among the 4E-BPs, distinct roles are still being defined. In mice lacking only 4E-BP2, which is normally abundantly expressed in the brain, a phenotype mimicking autism spectrum disorder (ASD) is observed (528). In experiments identifying this phenotype, polyribosomal profiling of hippocampal tissue from 4E-BP2-/- mice revealed enrichment of neuroligin transcripts, encoding adhesion molecules which influence synaptic activity.

Previously, two 4E-BP1-/- mouse lines have been generated independently (190, 529). While both groups demonstrated a leaner phenotype among 4E-BP1-/- mice, Tsukiyama- Kohara et al. showed this to be a consequence of increased expression of PGC1 at the protein level. PGC1 is a transcriptional regulator of uncoupling protein 1 (UCP1) in brown adipose tissue. Regulating thermogenesis, UCP1 uncouples oxidative phosphorylation from ATP synthesis by dissipating the mitochondrial H+ gradient (530). Consequently, 4E-BP1- /- mice expressing higher levels of UCP1 in adipose tissue exhibited increased metabolic activity. To date, however, polyribosomal profiling experiments have not been performed in cells lacking 4E-BP1 to identify other translationally regulated proteins. Our data showing that 4E-BP1-/- mice are more resistant to infection with CVB3 and influenza virus, suggest a difference in the basal immune status of these animals. Given the intriguing differences observed between polyribosomal profiling of 4E-BP1/2-/-, 4E-BP2-/- and eIF4E (S209A) mice, in future studies we propose experiments that might define unique characteristics of the 4E-BP1-/- background in the context of innate and adaptive immunity. From our experiments, during the early phase of infection, mRNA transcripts of ISGs were elevated in the hearts of infected 4E-BP1-/- mice. Hence, we will investigate the selective mRNA association with polyribosomes in the hearts of 4E-BP1-/- mice. Following from the polyribosome analysis in 4E-BP1-/- 4E-BP2-/- MEFs, we anticipate the possibility of selective polyribosome association of transcription factors similar to IRF-7. We will examine mRNA from whole-cell and polyribosomal fractions from the hearts of naïve 4E-

116 BP1-/- and wild type mice using microarray gene expression analysis and compare for enriched mRNAs (526, 531). Identified genes will be validated at the protein level in lysates from heart tissue.

4.3. Influence of IFN In a similar vein, the influence of IFN-α/β on translational regulation of specific mRNAs has not been thoroughly investigated. Certainly, numerous studies have provided data for the transcriptional induction of ISGs under various conditions and at different time points, but it is clear that mRNAs are also subject to regulation at the level of translation initiation (20, 532). A recent study in hematopoetic stem cells indirectly showed IFN-α mediated translational regulation of c-myc expression, which was independent of changes in transcription (533). The authors of this study suggest such a post-transcriptional regulatory mechanism to be a rapid means of adjusting c-myc expression during periods of hematopoiesis and stem cell differentiation. Translational regulation is particularly relevant in circumstances where a rapid response to physiological cues is required. Indeed, it is well known that IFN-α/β engages intracellular signaling within minutes of ligand- receptor interactions. IFN-α induced mTOR activity can be detected within 5 minutes of treatment (437). In spite of this early initiation of translational programs, a 30-60 minute lag time still remains for transcription, mRNA biogenesis and nuclear export following extracellular signals (534). This begs the question of which mRNAs are being actively translated in an IFN-α/β dependent manner prior to the biogenesis of mature ISG mRNAs. A previous proteomic study examining IFN-β-treated ex vivo brain slices, found only 19 proteins to be differentially regulated within 3 hours of treatment (535). Interestingly, the majority of these proteins were associated with cytoskeleton assembly, protein transport, nucleotide and energy metabolism and the oxidative stress response. While the 2- dimensional gel electrophoresis used in this study is a powerful proteomic tool to identify proteins and their post-translational modifications, certain limitations of sensitivity are inherent to this technology (536). Only 933 protein spots were detected in this study, whereas recent developments in deep sequence analysis of ribosomal-associated mRNA can provide a quantitative and broader (genome-wide) coverage of expressed proteins (537-539). Hence, we propose to investigate early translational regulation of IFN-α/β

117 inducible mRNAs through ribosome profiling. Since many cytokines, chemokines and their receptors are known to be regulated post-transcriptionally (540), we anticipate the possibility of IFN-α/β influencing early translation initiation of specific immune-related proteins.

4.4. Influence of 4E-BP1 on the Hematopoietic Compartment Another important question to consider is the relative contribution of hematopoietic and non-hematopoietic compartments towards antiviral immunity in 4E-BP1-/- mice. A previous study of hematopoiesis indicated differential regulation of 4E-BP1 and 4E-BP2 expression during myelopoiesis (541). Further investigation of myelopoiesis in mice lacking either 4E-BP1 or 4E-BP2 also revealed unique differences in the bone marrow and spleen as judged by CD11b and Gr1 staining, and colony forming assays (542). Notably, mice lacking either 4E-BP1 or 4E-BP2 exhibited impaired maturation of granulocytes, and showed enhanced numbers of monocytic precursors and mature monocytes. Increased numbers of immature granulocytes (CD11b+, Gr1+) observed in 4E-BP1-/- mice suggests the presence of granulocytic or monocytic myeloid derived suppressor cells (MDSC) (543, 544). MDSC-mediated suppressive effects toward innate and adaptive immunity have been demonstrated in infectious, autoimmune, allograft and tumor disease models (544-547). Interestingly, in the context of CVB3 infection, reduction of T cell driven inflammation has been shown to be beneficial to the outcome of disease (284, 285). Our observed reduction of inflammatory infiltrates in the hearts of 4E-BP1-/- mice (Fig 2.7) may be the result of MDSC mediated effects on the adaptive immune response. To investigate this possibility, we plan to characterize the myeloid hematopoietic compartment more thoroughly in naïve and CVB3-infected 4E-BP1-/- mice.

Additionally, the developmental imbalance of myeloid cells observed in 4E-BP1-/- mice may have consequences in the formation of macrophage and dendritic cell populations. Given the importance of DCs in modulating adaptive immunity, and in particular, the unique ability of pDCs to produce large quantities of IFN-α, investigation of DC populations in 4E-BP1-/- mice may yield insights into the observed resistance towards infection with CVB3.

118

In contrast to the observed differences in myelopoiesis, Olson et al did not identify any differences in T cell development in the thymus of 4E-BP1-/- mice, as indicated by CD4+ and CD8+ staining of thymocytes. However, in spite of this, it is possible that subsequent lineage skewing would be influenced. Indeed, it has been demonstrated that CD4+ Th1, Th2, Th17 and Treg development is strongly influenced by mTOR activity (548, 549). Similarly, CD8+ T cell effector and memory function is also regulated by mTOR (550). Inhibition of mTOR activity through pharmacological or genetic means produces increased numbers of CD4+ Tregs, and also a memory phenotype in CD8+ T cells (551). Alternatively, conditional deletion of TSC1 in CD4+ T cells resulted in mTOR activity, and consequently, led to increased numbers of Th1 and Th17 cells, and fewer Tregs (552). These effects have been attributed to differences in transcription factor expression (162). Interestingly, IL-4- dependent regulation of Th2 differentiation requires the specific translational regulation of GATA-3 expression as induced by TCR signaling through PI-3’K/mTOR (553). Differentiation of mTOR-inhibited CD8+ T cells towards a memory phenotype resulted from depressed expression of T-bet and increased expression of eomesodermin (550). Given the evidence that mTOR influences T cell differentiation, partly through the regulation of translation of transcription factors, we anticipate possible 4E-BP1 mediated effects.

Given the possibility for differences in immunophenotypes in 4E-BP1-/- mice, we plan to examine myeloid and lymphoid cells in naïve and CVB3-infected mice. To confirm the data published by Olson et al, we will examine splenic myeloid and lymphoid cell frequency, and their functional capacities. MDSCs will be identified by flow cytometry as CD11b+Ly6G- Ly6Chigh monocytic MDSC and CD11b+Ly6G+Ly6Clow granulocytic MDSC (554, 555). Using flow cytometry, differences in granularity have been used to differentiate neutrophils (SSChigh) from G-MDSC(SSClow) (556). Following enrichment of splenic CD11b+ myeloid cells by magnetic sorting, fluorescence activated cell sorting (FACS) will be utilized to isolate CD11b+Ly6G-Ly6Chigh monocytic MDSC and CD11b+Ly6G+Ly6ClowSSClow granulocytic MDSC and neutrophils CD11b+Ly6G+Ly6ChighSSChigh (556, 557). In vitro T-cell suppression assays and measurement of secreted arginase-1, Il-10 and ROS will determine the

119 functional capacity of MDSCs. Plasmacytoid dendritic cells (pDC) will be identified as mPDCA1+CD11cintCD11b- and conventional dendritic cells (cDC) as CD11chiCD11b+ (446, 558). Since pDC derived from 4E-BP1-/-4E-BP2-/- mice produced higher amounts of IFN-α (191), we also plan to measure IFN-α produced by polyI:C-stimulated pDC isolated from the spleens of naïve 4E-BP1-/- mice. Following infection with CVB3, inflammatory infiltrates from spleens and hearts will be quantified by FACS at days 3 and 7 post-infection. Different CD4+ T cell lineages will also be identified as CD4+CD8α-TCRβ+ combined with intracellular staining of IFN-γ (Th1), IL-4 (Th2), IL-17 (Th17) and FoxP3 (Treg). CD8+ effector and memory T cells will be determined by CD4-CD8α+TCRβ+CD44highCD62Lhigh (memory) and CD4-TCRβ+CD44highCD62Llow (effector) (559).

Since our experiments have primarily focused on the acute phase of CVB3 infection, and we know that type I IFNs produced by non-hematopoietic cells play an important role in innate immunity, we aim to determine the relative contributions of the different compartments toward the outcome of CVB3 infection in 4E-BP1-/- mice. Presumably, leukocytes lacking 4E-BP1, such as pDC, will produce increased quantities of IFN-α in response to infection. Alternatively, non-hematopoietic cells lacking 4E-BP1 will be more responsive to the effects of IFN-α/β by producing greater levels of ISGs, thereby limiting virus spread. Hence, we plan to perform bone marrow transplant experiments to determine where 4E-BP1 exerts the most influence during an antiviral response. Briefly, mice will be sub-lethally irradiated prior to transfer of congenic bone-marrow derived hematopoietic stem cells. Following hematopoietic reconstitution, mice will be infected with CVB3, and viral titers measured in the hearts, livers, pancreata, spleens and serum at days 3 and 7 post-infection.

4.5. Metabolic Effects of Type I IFNs Our data presented in Chapter 2 indicate an important role for type I IFNs in regulating protein synthesis through mTOR activation. Since a large portion of cellular ATP is consumed by protein synthesis (560), we sought to identify possible IFN-α/β mediated influences on cellular bioenergetics. Based on previous studies identifying growth factor and cytokine regulation of glucose metabolism through Akt and PI3’K signaling (561), we

120 investigated IFN-β inducible effects on glucose uptake in MEFs. Indeed, upon treatment with IFN-β we observe a temporal increase in glucose uptake accompanied by slight increases in intracellular ATP levels (Fig 3.1, Fig 3.2). The timeframe in which these effects are observed provides further support for the rapid effects that type I IFNs exerts on target cells. Consistent with previous reports, IFN-β mediated glucose uptake is dependent on intact Akt and PI-3’K signaling (Fig 3.2). Interestingly, although inhibition of glycolysis by 2-deoxy-D-glucose (2-DG) impaired IFN-β inducible antiviral effects, it did not completely abolish antiviral activity. When treated with 2-DG, cellular ATP levels were only depleted by ~30%, an effect which is consistent with ATP derived from mitochondrial oxidative phosphorylation (562). Indeed, oxidative phosphorylation is also major source of ATP in normal cell metabolism. Shifts in the balance between aerobic glycolysis and oxidative phosphorylation have been shown to accompany different immunological activation processes. Activation of T cells profoundly changes their metabolic profile from oxidative phosphorylation to aerobic glycolysis in favor of the anabolic process of proliferation (561, 563, 564). Similarly, TLR stimulation of DCs also increases aerobic glycolysis significantly to favor biosynthetic processes necessary for mounting an immune response (565). In addition to the generation of biosynthetic precursors through aerobic glycolysis, Krawczyk et al also suggest that this represents a rapidly available source of ATP. Building on our data which suggest an important role for IFN-β in regulating rapid uptake of glucose, we will investigate the influence of type I IFNs on the balance of glycolysis and oxidative phosphorylation. IFN-β mediated effects will be detected through measurement of oxygen consumption and extracellular acidification rates, which correlate with rates of oxidative phosphorylation and glycolysis, respectively. Preliminary experiments using the Seahorse XF Extracellular Flux Analyzer provided evidence of IFN-β mediated reduction of oxygen consumption. However, this effect was not consistently detected with a coordinate increase in extracellular acidification rate. Utilizing specific inhibitors of oxidative phosphorylation, we will also be able to detect changes in mitochondrial function and capacity (566).

Concordant with possible effects of IFN-β on mitochondrial activity, a recent study revealed that mTOR regulates mitochondrial biogenesis through 4E-BPs (567). This effect was measured following 12 hours of treatment with the mTOR inhibitor, PP242. However, since

121 a biphasic effect on glucose uptake was observed over a period of nearly 12 hours (Fig 3.2), we expect that any effects on mitochondrial oxidative phosphorylation would necessarily fall within this time, and likely be transient. That being said, this mTOR-mediated effect was identified through polysomal profiling, and those specific mRNAs could still be examined following treatment with IFN-β.

It has long been understood that viruses require cell-derived metabolites for their replication (568). Though in recent years, the dynamics of this interaction have become more appreciated. The development of high-throughput technologies has permitted simultaneous surveys of large numbers of metabolites (metabolomics) and the associated changes over time (fluxomics) (569). Using mass spectrometry, Vastag et al examined specific metabolites (~200) in cells infected with closely related herpes viruses, HCMV and HSV-1, and identified virus-specific alterations of host-metabolism (570). Interestingly, over the course of infection, HCMV skewed cell metabolism toward production of fatty- acids, whereas HSV-1 favoured synthesis of pyrimidines. The authors speculate that these specific alterations are linked to virus replication kinetics, with HSV-1 requiring more rapid synthesis of DNA resulting from faster replication rates than HCMV. Other studies have also identified unique virus metabolic requirements and alterations of host-cell metabolism. Metabolomic analysis of HCV infected cells also revealed specific changes in lipid metabolism which appeared to be regulated at a post-transcriptional level (571). Hollenbaugh et al have also shown that HIV-1 induces distinct metabolic changes in CD4+ T cells versus macrophages (572). Similarly, a variety of other viruses including influenza virus (573), dengue virus (574), vaccinia virus (575) and Kaposi sarcoma-associated herpesvirus (KSHV) (576) have also been shown to influence cellular metabolism to facilitate replication. These virus-specfic alterations in cell metabolism have been proposed as potential targets for pharmalogical development. Indeed, based on findings from their metabolomic analysis of HCMV infected cells, Rabinowitz et al utilized a clinically available inhibitor of acetyl-CoA synthetase, 5-tetradecyloxy-2-furoic acid (TOFA), to specifically inhibit virus replication >1000 fold (577). Certainly, these findings also raise the question of possible immunological alterations in cell metabolism. Beyond the ability of PRRs to shift cell metabolism from oxidative phosphorylation towards glycolysis, can other specific

122 changes in metabolism be detected as well? Indeed, it is abundantly clear that mitochondria are intimately associated with innate immunity as is indicated by the roles played in PRR signaling and apoptosis (578, 579). Interestingly, in a recent study of CVB3- induced myocarditis, Ebermann et al showed mouse strain-dependent differences in mitochondrial respiratory complex expression and activity which dictated disease outcome (580). The authors speculate that unique immune signals contribute to the observed differences in mitochondrial respiratory activity. Additionally, early studies revealed IFN- α/β dependent negative regulation of mitochondrial mRNA expression following 16 hours of treatment (581, 582). Given the apparent connection between metabolism and antiviral immunity, we anticipate a possible role for IFN-α/β in affecting these processes. LC-MS/MS will be utilized to examine cellular metabolites at early and late time points following treatment with IFN-α/β to capture metabolic fluxes. Metabolites from a variety of biosynthetic pathways will be measured using LC-MS/MS. Particular focus will be given to the biosynthetic pathways involved in purine/pyrimidine, amino acid and fatty acid metabolism.

4.6. Conclusion Since their discovery in the late 1950s, IFNs have been extensively studied, and their application in the clinic has been realized. Although type I IFNs have been used to treat diseases such as multiple sclerosis and hepatitis C, their mechanism of action is incompletely understood. Certainly, in the context of viral infections, the importance of type I IFNs is appreciated given the number of viruses possessing a variety of antagonistic defenses. Our examination of type I IFN signaling was driven by a goal to increase the efficacy of treatment and overcome virus-encoded antagonistic defenses. The studies described in this thesis examined the utility in targeting post-transcriptional modes of type I IFN signaling to gain an enhanced antiviral effect. Indeed, cells and mice lacking different negative regulators of translation showed increased sensitivity of treatment with IFN-α/β as a consequence of increased translation of antiviral proteins. Coupled with the regulation of protein synthesis, we were also able to show an important role for type I IFNs in regulating cell metabolism. Additionally, we identified that metformin a widely available pharmaceutical, is able to enhance the antiviral potency of IFN-β during virus infection.

123 Taken altogether, the work shown in this thesis reinforces the importance of type I IFNs in regulating antiviral responses, and indicates potential areas of therapeutic development. Given the number of continually emerging viruses, the broad-spectrum antiviral nature of type I IFNs makes them attractive targets for continued therapeutic development.

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