Melanoma-Infiltrating Dendritic Cells: Limitations and Opportunities of Mouse Models.…………………………………….………………………………

Type I IFN control of sterile inflammation:

Uncovering mechanisms behind autoimmunity

and antitumor immunity

A dissertation submitted to the Graduate School of the

University of Cincinnati

in partial fulfillment of the requirements for the degree of

Doctor of Philosophy

Immunology Graduate Program, College of Medicine

2016

by Jared Klarquist

A.B., Dartmouth College, 2003

Committee Chair: Edith M. Janssen, Ph.D.

Abstract

Dying cells elicit immune responses toward self antigens which can be either harmful or beneficial. These responses can help control deadly cancers, or they can destroy healthy tissues and initiate debilitating autoimmune diseases. We have sought to define novel mechanisms that drive sterile inflammatory responses toward self antigens which may be exploited in new cancer immunotherapies or in treatments for autoimmune diseases. Type

I interferon (IFN) has been described as a central mediator in bridging innate and adaptive immune responses toward cell-associated antigens, but the pathways both up- and downstream of IFN signaling have remained unclear. Our studies demonstrate that the stimulator of IFN genes (STING) induces type I IFN production by dendritic cells (DCs) in response to dying cell-derived cytosolic DNA. Further, we report that the IFN produced by

DCs results in a positive feedback loop, enhancing their ability to prime effective and long- lasting CD8 T cell responses toward tumor cell-associated antigens. Moreover, we found that STING is also critical to driving autoimmune responses in the bm12 chronic graft- versus-host disease model of systemic lupus erythematosus (SLE). Within the context of bm12 autoimmunity, we determined that type I IFN sensing by CD4 helper T cells protected them from being killed by highly active natural killer (NK) cells, thereby augmenting autoimmune disease. We also showed that direct sensing of IFN enhanced the development of germinal center B cells and plasmablasts in an NK-independent manner.

Lastly, we defined the metabolic programs of key T cell and B cell subsets, uncovering a fundamental role for glycolysis in these autoimmune responses. Together, our studies shine light on previously undescribed pathways controlling anticancer immune responses and autoimmunity, providing opportunities for the development of nuanced treatment strategies which may prove both more specific and more effective than existing therapies.

iii Acknowledgements

First, I would like to express my deepest gratitude to my graduate studies advisor and mentor, Dr. Edith Janssen. Your ambition, cheerfulness, patience, and passion have helped shape my professional abilities and my excitement for science. You have also been a model for how to balance a successful scientific career and a strong commitment to family. Without your continued support, this dissertation would not have been possible. Thank you.

I would also like to thank my dissertation committee members: Dr. Claire Chougnet, Dr. Divaker Choubey, Dr. Michael Jordan, and Dr. Jonathan Katz. I appreciate the time you devoted to helping mentor me and your expert advice. And to my prior mentors, Dr. Hugo Rosen and Dr. Caroline Le Poole, I am grateful for your guidance and your investment in my career.

I owe my thanks to all the current and former members of the Janssen and Hoebe laboratories, especially to Maria Lehn and Cassie Hennies—your tireless work contributed greatly to the projects reported in this dissertation. To Dr. Kasper Hoebe, your mentorship through the years is sincerely appreciated; it has been critical to my progress and my development as a scientist.

Finally, I am grateful for my family. To my parents-in-law, thank you for the immeasurable support you have given me and my wife over the past nine years we have been together. To my brothers, thank you for your steadfast friendships. And to my parents, who have encouraged me personally and professionally since I was a child, and have done everything in their power to help me succeed, thank you. To my wife, Lori, the passion, dedication, and tenacity with which you have approached your career in medicine has provided invaluable inspiration to me. But foremost, your love for me and for our children has sustained me in undertaking this endeavor.

iv Abbreviations used in this dissertation actmOVA membrane-targeted OVA driven by chicken beta actin promoter ANA anti-nuclear antibody APC antigen presenting cell B16-OVA OVA-transfected B16 melanoma cell line B16/F10 C57BL/6-derived melanoma cell line B6 C57BL/6 mice BCL-6 B-cell lymphoma 6 protein BM bone marrow bm12 B6(C)-H2-Ab1bm12/KhEgJ mice cDC conventional DC CFSE carboxyfluorescein succinimidyl ester cGAMP cyclic guanosine monophosphate-adenosine monophosphate (cyclic GMP-AMP) cGAS cyclic GMP-AMP synthase cGVHD chronic graft-versus-host disease CLR C-type lectin receptor CTL cytotoxic T lymphocyte CTLA4 cytotoxic T-lymphocytes associated protein 4 CTV or VT CellTrace Violet proliferation/tracking dye CXCR5 Chemokine (C-X-C motif) receptor 5 DAMP damage-associated molecular pattern DC dendritic cell dsDNA double-stranded deoxyribonucleic acid DT diptheria toxin DTR human diptheria toxin receptor FACS fluorescence-activated cell sorting FAO fatty acid beta oxidation FASL Fas ligand (aka CD95L) FOXP3 forkhead box P3 GC germinal center ICOS inducible T-cell COStimulator IFN interferon IFNAR type I IFN receptor IL interleukin IRAK IL-1R-associated kinase IRF3 interferon regulatory factor 3 ISRE interferon-sensitive response element LPS lipopolysaccharide MAVS mitochondrial antiviral signaling (aka Cardif, IPS-1, Visa) mcDC merocytic DC (aka CD8/CD11b double-negative DC) mDC myeloid DC

v MHC major histocompatibility complex mOVA membrane-targeted OVA MS multiple sclerosis MyD88 myeloid differentiation primary response gene 88 NFκB nuclear factor kappa-light-chain-enhancer of activated B cells NK natural killer OTI TCR transgenic mice specific for the MHC class I-restricted epitope OVA257-264 OTII TCR transgenic mice specific for the MHC class II-restricted epitope OVA323–339 OVA chicken egg ovalbumin OXPHOS oxidative phosphorylation PAMP pathogen-associated molecular pattern PD-1 programmed cell death 1 (aka PDCD1) pDC plasmacytoid DC PRR pattern recognition receptor RAE1 retinoic acid early transcript 1 RIG-I DEXD/H-box helicase 58 (aka DDX58, RLR-1) SAVI STING-associated vasculopathy with onset in infancy SLE systemic lupus erythematosus SMARTA TCR transgenic mice specific for the MHC class II-restricted LCMV GP61-80 SNP single-nucleotide polymorophism STAT signal transducer and activator of transcription STING stimulator of interferon genes (aka Tmem173, ERIS, MPYS, Mita) T-bet T-box transcription factor TBX21 T1D type I diabetes TCR T cell receptor Tfh T follicular helper TGF-β transforming growth factor-β Th T helper TNF tumor necrosis factor TRAF TNF-receptor-associated factor TRAIL TNF-related apoptosis-inducing ligand TRAM TRIF-related adaptor molecule Treg regulatory T cell TREX1 three prime repair exonuclease 1 TRIF TIR domain-containing adaptor inducing IFN WT wild type

vi Table of contents

Abstract………………………………………………………………………………….... ii Acknowledgements……………………………………………………………………… iv List of Abbreviations…………………………….……………………………………..... v Table of contents………………………………………………………………………… vii

CHAPTER 1: A brief overview of the major immunological concepts central to this dissertation.…………………………………….……………………………………….. 1 1.1 A crossroads: innate and adaptive immunity…………………………...... 2 1.1.1 Brief introduction to cells of the immune system.……………… 3 1.1.2 Antigen presentation and T cell priming………………………... 8 1.1.3 PAMPs, DAMPs, and PRRs……………………………………... 10 1.1.4 Type I IFN………………………………………………………….. 14 1.2 Cancer….……………….……………………………………………………. 17 1.2.1 The (re-)emerging field of cancer immunotherapy…………….. 17 1.2.2 Type I IFN in immunotherapy and cancer immunology……..... 20 1.3 Autoimmunity……………………………………………………………….... 21 1.3.1 Systemic lupus erythematosus………………………………...... 22 1.3.2 SLE pathogenesis……………………….………………………... 22 1.3.3 Type I IFN in SLE……………………….………………………… 24 1.4 Cellular Metabolism…………………………………………………………. 26 1.4 Dissertation Aims……………………………………………………………. 28 1.5 References………...…………………………………………….….….……. 30

CHAPTER 2: Melanoma-infiltrating Dendritic Cells: limitations and opportunities of mouse models.…………………………………….………………………………... 40 • Abstract…………………………………….……..………………………….. 41 • Introduction……..………………………….……..………………………….. 41 • Selection of mouse model for melanoma tumors..….….….…………….. 42 o Xenograft models…………………….……..…………………………… 42 o Syngeneic transplantation models….……..…………………………... 43 o Genetically engineered models (GEMM)..…………………………..... 43 • Dendritic cells…….……………………….……..…………………………… 44 • DC populations in mouse and man…….……..………………………….... 45 o Mouse DC populations……………….……..…………………………... 45 o Human DC populations…………….……..…………………………….. 47 o Human melanoma TIDCs………….……..…………………………….. 48 o Mouse melanoma TIDCs.………….……..…………………………….. 49 o Mouse TIDC activation status.…….……..…………………………….. 49 o Mouse TIDC functionality.………….……..…………………………..... 52 o Scientific and therapeutic considerations…...... …………………….. 55 • Acknowledgments, conflict of interest, and ethical statement…….....…. 57 • References…..……………….………….……..…………………………..... 58

vii

CHAPTER 3: Dendritic cells in systemic lupus erythematosus: from pathogenic players to therapeutic tools……………….……………………………………….... 66 • Abstract…………………………………….……..………………………….. 67 • Introduction……………………………….……..…………………………… 67 • DC populations in humans....……..…….……..…………………………... 68 o Myeloid DCs: BDCA1+ DCs and BDCA3+ DCs……………………... 69 o Plasmacytoid DCs….…………….……..………………………………. 69 o Monocyte-associated DCs…………….……..………………………… 70 o Tissue DCs……………..…………….……..…………………………… 71 • DC activation of T cells...... …………….……..…………………………… 71 • Role of DCs in SLE development and progression……………………… 72 • DC abnormalities in SLE patients…..….……..…………………………… 73 • SLE-associated dysfunction in primary DCs...…………………………… 74 • SLE-associated dysfunction in in vitro generated DCs………………..... 76 • Nature versus nurture…..…………….……..……………………………… 76 • Mouse models to dissect role of DCs in SLE pathogenesis……...... 77 • Similarities between mouse and human DCs...………………………….. 78 • The role of DCs in mouse SLE models……....…………………………… 79 • DC targeted therapies for SLE……….……..……………………………... 80 • Acknowledgements……..…………….……..……………………………… 82 • References…..……………….………….……..…………………………..... 83

CHAPTER 4: The bm12 inducible model of systemic lupus erythematosus (SLE) in C57BL/6 mice…………….…………………………..……………………………… 95 • Abstract…………………………………….……..………………………….. 96 • Introduction……………………………….……..…………………………… 96 • Protocol…………………………………….……..………………………….. 98 1. Novel method for genotyping bm12 mice…...………………………... 99 2. Harvesting donor cells…….……..……………………………………... 100 3. Donor cell counting….…….……..……………………………………... 101 4. Donor cell labeling and/or CD4 T cell purification.…………………... 102 5. Injection of donor bm12 cells…..……………………....….…………... 102 6. Determine grafting efficiency…..……………………....….…………… 103 7. Final tissue harvest….…….……..……………………………………... 105 8. Flow staining………...…….……..…………………………………….... 107 • Representative results………………….……..……………………….....… 109 • Discussion………………………………………………………………….… 113 • Acknowledgements and disclosures…...... …………………………….… 116 • References…..……………….………….……..………………………….… 117 CHAPTER 5: STING-mediated DNA sensing promotes antitumor and autoimmune responses to dying cells…………….…………...……..………………………….... 120 • Abstract…………………………………….……..………………………….. 121 • Introduction……………………………….……..…………………………… 122

viii • Materials and Methods………………….……..………………………….... 124 • Results……..……………………………….……..…………………………. 129 o Protective anti-tumor immunity requires type I IFN sensing by DCs. 129 o DCs predominate the type I IFN production elicited by dying cells... 132 o The STING/IRF3 pathway drives type I IFN in response to cell- associated antigen…………………….……..…………………………. 133 o Nuclear DNA-derived structures induce type I IFN production by DCs……………….…………………….……..………………………..... 134 o DC-intrinsic STING regulates CD8+ T cell responses to dying cells. 135 o STING regulates CD4+ T cell and B cell responses in the bm12 SLE model……….…………………….……..………………………..... 137 • Discussion………………………………………………………………….… 139 • Acknowledgements……………………...... ……………………………..... 143 • References…..……………….………….……..………………………….… 144

CHAPTER 6: Type I interferon protects CD4 T cells from NK cell killing in a cGVHD model of SLE…………….…………...... ……..………………………….... 150 • Abstract…………………………………….……..………………………….. 151 • Introduction……………………………….……..…………………………… 152 • Results……..……………………………….……..…………………………. 154 o IFN sensing by CD4 T cells is critical to the expansion of donor CD4 T cells and pathogenic B cell subsets in the bm12 cGVHD model of SLE…………………………………………………………….. 154 o WT and Ifnar -/- bm12 CD4 T cells both differentiate into T follicular helper cells……………………………………………………………….. 155 o Type I IFN acts directly on CD4 T cells to improve their expansion.. 157 o IFN sensing does not prevent grafting………………………………… 158 o IFN inhibits ongoing proliferation of mouse CD4 T cells in vitro.…… 159 o Ifnar -/- CD4 T cells show no cell-intrinsic survival disadvantage…... 160 o IFN protects Tfh from perforin-mediated cell death………………….. 161 o IFN protects Tfh from NK cell killing in bm12 lupus-like disease..…. 162 o IFN promotes development of plasmablasts and GC B cells, but B cells are not NK targets…………………………………………………. 163 • Discussion………………………………………………………………….… 165 • Materials and Methods………………….……..………………………….... 170 • Acknowledgements……………………...... ……………………………..... 174 • Supplemental Figures……….………….……..………………………….… 175 • References…..……………….………….……..………………………….… 181

CHAPTER 7: Dissection of metabolic activity in T follicular helper cells and B cells in systemic lupus erythematosus…...... ……..………………………….... 185 • Abstract…………………………………….……..………………………….. 186 • Introduction……………………………….……..…………………………… 187 • Results……..……………………………….……..…………………………. 190

ix o Tfh cells display increased metabolic activity FN sensing by CD4 T cells is critical to the expansion of donor……………………………… 190 o Glycolysis is increased in Tfh compared to naïve CD4 T cells...... 192 o Fatty acid oxidation (FAO) is the predominant mitochondrial ATP producing pathway…………………………………………………….… 194 o GC B cell and plasmablast responses are associated with increased metabolic activity………………………………………………………… 197 o Increased glycolysis in GC B cells and plasmablasts…………..…… 199 o Limited dependence of B cell responses on FAO………………….... 201 o Inhibition of glycolysis, but not FAO, blocks disease development in vivo………………………………………………….………………….. 203 • Discussion………………………………………………………………….… 207 • Materials and Methods………………….……..………………………….... 213 • References…..……………….………….……..………………………….… 217

CHAPTER 8: Summary and Discussion……….……..………………………….… 219 • Overall summary.…………….………….……..………………………….... 220 • Summary Model Diagram.………….……..………………………….…..... 223 • Discussion..……………………………………………….………………..... 224 • References.……………………………………………….………………..... 235

APPENDICES….……………………………………………………………………...... 239 Appendix I: Copyright notices……………………………………………………...... 240 Appendix II: pdf of Chapter 2……………………………………………………...... 242 Appendix III: pdf of Chapter 3……………………………………………………...... 252 Appendix IV: pdf of Chapter 4……………………………………………………...... 264 Appendix V: pdf of Chapter 5……………………………………………………...... 275

x Chapter 1. A brief overview of the major immunological concepts central to this dissertation

1 1.1 A crossroads: innate and adaptive immunity Innate and adaptive immunity are the two primary arms which comprise the immune system. Each arm plays its own role, but the two are intricately linked and tightly controlled. The innate immune system provides the first line of defense against invading viruses, bacteria, and fungi. Upon sensing conserved, pathogen-associated molecular patterns (PAMPs), innate immune cells can quickly consume and digest microorganisms or infected cells. This occurs rapidly and helps contain infectious agents very early after invasion. The expediency of innate immune responses comes at a cost—they have relatively low specificity—but provides a crucial level of protection during the 4-7 day time period needed to develop adaptive immune responses. As their name implies, adaptive immune cells provide a much higher level of specificity toward infectious particles, even as pathogens evolve and new pathogens are encountered. Specialized cells of the innate immune system, in addition to providing early protection, also play key roles in initiating and directing adaptive immune responses. Dendritic cell (DCs), serve a particularly central function at this interface of innate and adaptive immunity and will be a primary subject in several chapters of this dissertation.

Immune responses can be very powerful and potentially harmful. Some activated immune cells are given the license and several tools by which to kill any cell which appears to be harboring an infection. Other immune cells can produce robust, damaging inflammation. Hence, to avoid unintentional destruction of healthy tissue, multiple systems work in concert to limit immune responses. First, adaptive immune cells undergo a process of selection, which leads to the demise of any overly self-reactive cell. The entire purpose of some specialized lymphocytes is to regulate the responses of others. And finally complex networks within each cell integrate numerous often opposing signals, such that the balance of these signals ultimately determines cellular activity. Dysregu- lation of signals that promote or dampen immunity can therefore lead to profound tissue

2 destruction that may result in autoimmunity. Nuances in these signals may also allow the detection and immune targeting of cancer, the uncontrolled growth of otherwise healthy cells. Subsequent chapters in this dissertation will explore novel mechanisms that regulate immunity to self, with the goal of uncovering new targets for the treatment of cancer and autoimmune disease.

1.1.1 Brief introduction to cells of the immune system The innate immune system is composed of many cell types. Essentially every cell, even highly specialized cells of non-hematopoietic origin, can operate as part of the innate immune system, sensing microbes and alerting other cells of danger. In fact, primary protection from infection is provided by the non-hematopoietic cells that make up epithelial surfaces. Epithelia serve as physical barriers, but also secrete antimicrobial compounds, and can physically expel microorganisms through the action of cilia. Notwithstanding, several unique cells of hematopoietic origin serve specialized functions within the innate immune system and are of particular relevance to the work discussed in this dissertation. These include macrophages, DCs, and natural killer (NK) cells.

DCs were initially described by Ralph Steinman and Zanvil Cohn in 1973, nearly 100 years after Élie Metchnikoff first described macrophages1,2. DCs were recognized as morphologically distinct from macrophages, forming elaborate tree-like “dendritic” structures, yet the two cell types performed similar functions. Macrophages and DCs share the common ability to quickly consume relatively large particles including microorganisms and dying cells or large portions thereof in a process called phagocytosis. Subsequently, these cells have varying abilities to initiate adaptive immune responses through a process called antigen presentation, the subject of the following section. The clearance and recycling of dying cell material via phagocytosis is also critically important for maintaining immunological tolerance3,4. Macrophages are thought to play particularly important roles

3 in promoting tolerance, whereas DCs are considered the antigen presenting cell most capable of initiating adaptive immune responses to foreign and self-antigens5–7. Many different subtypes of DCs exist, performing distinct but overlapping roles in immunity. As previously mentioned, subsequent Chapters 2 and 3 will cover DCs and their functions in cancer and autoimmune disease in much further detail.

NK cells are chiefly known for their function as killers of infected cells. Cells respond to intracellular infections by downregulating inhibitors and upregulating activators of NK function, and the balance these signals determines whether or not the cell becomes an NK target8. The prototypical molecular interaction between NK cells and their targets is the engagement of the NK cell’s killer immunoglobulin receptor (KIR) family proteins by the target cells’ major histocompatibility complex (MHC) class I molecules. Engagement of KIRs by MHC class I produces a signal within the NK cell necessary to inhibit its killer functions—when MHC class I molecules are absent or significantly reduced, NK cells will kill9. Additional signals from target cells can activate NK cell killer functions, including RAE1, MICA, MICB, CD48, and cytokines such as IL-2, IL-12, IL-18, and type I IFN10 (Figure 1).

4 Once activated, NK cells can kill target cells directly or indirectly. Indirect NK killing can include signaling target cells to commit suicide by release of the death-inducing cytokine TNFα or by surface expression of TRAIL or FASL, whereas more direct means of killing can be accomplished by delivering cytolytic granules containing perforin and gran- zymes11,12. It is becoming increasingly clear that infection is not the only cellular stressor that can cause cells to become targets of NK cell killing. Malignant transformation, nu- tritional deficiencies, and DNA damage are a few examples of additional stressors which alter the balance of NK ligand expression such that they will activate NK cell killer function upon encountering NK cells13. Recently, an immunoregulatory role for NK cells has also been described, whereby NK cells can limit vigorous immune responses to viruses by killing proliferating T cells14, although the precise mechanisms promoting NK cell activation in this context have not yet been elucidated.

T cells comprise the major arm of adaptive immunity that develops in the thymus. The term describes a number of different cell types which perform distinct functions, yet these cells all share a highly variable receptor which distinguishes them from other cells, the T cell receptor (TCR). The majority of T cells express a heterodimeric TCR composed of an alpha and beta subunit. Within alpha/beta T cells, two primary divisions exist: CD4+ T cells and CD8+ T cells (hereafter referred to as CD4 T cells and CD8 T cells), which are derived from the same precursor cells15. CD4 and CD8 T cells are positively and negatively selected on MHC class I and II proteins such that T cells which leave the thymus alive react weakly with self antigens, thus preventing autoimmunity, but also ensuring their potential reactivity toward foreign antigens16. CD4 T cells, commonly referred to as “helper” T cells, make critical contributions toward the activation and differentiation of both CD8 T cells and B cells. They also act as effector cells producing a variety of cytokines depending upon their specific differentiation program. Expression of certain master regulator transcription factors determines the differentiation fate of CD4 T cells with some

5 permanence, though some of these cells do exhibit a degree of plasticity (Figure 2)17.

The primary function of CD8 T cells is to kill infected cells, cancer cells, or otherwise damaged cells; thus, they are also called cytotoxic T cells (CTLs). The effector functions of CTLs are similar to those of NK cells, though an important difference between the two cell types is the relatively high degree of specificity of CTL clones toward a limited number of foreign peptide-MHC combinations. CD8 T cells primarily respond to endogenous antigens presented by essentially any cell; typically they recognize non-self, infectious material presented by MHC class I. However, some specialized DCs are capable of presenting exogenous antigens to CD8 T cells, as will be discussed later in this section. In the absence of appropriate regulatory controls, CD4 and CD8 T cells can both react strongly with self antigens and mediate autoimmune disease.

6 B cells are hematopoietic cells that mature in the bone marrow. Their primary functions are mediated by their antigen receptor, the B cell receptor (BCR). The BCR consists of one of several different immunoglobulin proteins complexed with a signaling adapter heterodimer Ig-α/Ig-β (CD79)18. The BCR can be activated successfully with or without T cell help, in so-called T-dependent or T-independent responses; here, we will focus on T-dependent responses. Although many functional subtypes of B cell exist, the most relevant subtypes to this dissertation include plasmablasts and germinal center (GC) B cells. Upon recognition of their cognate antigen, naïve B cells either differentiate into short-lived plasmablasts or GC B cells (Figure 3)19. Plasmablasts differentiate in extra-follicular regions of secondary lymphoid organs in what represents the first step in the development of a B cell response. They undergo class switch recombination (CSR) and are the primary source of early antibody secretion, but because they arise so quickly, plasmablasts

Figure 3: T cell-dependent B cell differentiation. Adapted from Moens L and Tangye SG: Frontiers in Immunology20, copyright 2014. Open access article used here under the terms of the Creative Commons Attribution License.

7 have limited time for somatic hypermutation (SHM) and therefore usually have relatively low antibody affinities20. The rapid proliferation of B cells interacting with antigen-specific T follicular helper CD4 T cells (Tfh) results in the formation of GCs19. GC B cells are the early stage B cells found within these GCs, which undergo CSR and significant SHM19. Eventually GC B cells differentiate into memory B cells or long-lived antibody secreting plasma cells, which mediate highly effective long-term protection19,20. Since the later chapters in this dissertation examine B cell responses within the first two weeks of disease onset, these studies are primarily focused on plasmablasts and GC B cells, the cell types most active in this period.

1.1.2 Antigen presentation and T cell priming Adaptive immune responses are initiated by antigen presentation, a process that includes both phagocytosis-dependent and -independent processes. Professional antigen presenting cells (APCs) express MHC class I and II and are responsible for most productive priming of CD4 and CD8 T cells, although essentially any nucleated cell can present antigen to CD8 T cells via MHC class I.

TCRs are highly specific to unique combinations of MHC protein structures and peptide sequences21, and T cells can only become activated when their TCRs bind MHC-peptide combination with relatively high affinity22. The priming of CD4 T cells generally requires phagocytosis of exogenous material by APCs and presentation of exogenous protein antigens. Professional APCs include DCs as well as B cells, which, upon antigen capture, can present exogenous antigens to CD4 T cells in a similar manner as DCs. After en- gulfment, phagocytosed material remains compartmentalized in the phagosome. Fusion of the phagosome with highly acidic lysosomes leads to the digestion of phagocytosed material by a cocktail of toxic agents including lysozymes, free radicals, and acid hydro- lases23. Small fragments of digested protein between 14 and 20 amino acids in length

8 are loaded on class II MHC proteins to be presented to CD4 T cells via their TCRs24–27. Presentation of peptides 8-10 amino acids in length from endogenous proteins are loaded on to MHC class I and presented to CD8 T cells27. This process is dependent upon the proteasomal degradation of endogenous protein28 and subsequent trafficking of these peptides to the endoplasmic reticulum via TAP proteins29.

DCs can also take up dying cell material and present exogenous cell-associated antigens on MHC class I to CD8 T cells through a process called cross-presentation30–32. Cross-presentation is especially important to this dissertation, because it is by cross-presentation that DCs most effectively initiate immune responses toward self-antigens including antitumor immunity33 and autoimmunity34. The exact mechanism by which exogenous peptide is shuttled onto MHC I is not known, though its dependency on TAP proteins has been established35. Several cell types are known to cross-present antigen, including dendritic cells, macrophages, and even neutrophils36, but they are not equal in their abilities. So-called “lymphoid,” or CD8α+ murine DCs have been described as the most efficient cross-priming DCs35. While “myeloid,” or CD11b+ DCs phagocytose bacteria and proteins well, they only weakly phagocytose dying cells and cross-prime poorly32,37. In mice, “plasmacytoid” DCs (pDCs) are extremely weak at taking up apoptotic cells and are not thought to cross-present cell-associated antigen, though human pDCs are capable32. Although exactly what determines the cross-priming abilities of various DC subsets remains unclear, rapid phagolysosomal acidification was associated with the minimal and transient ability of CD11b+ DCs to cross-present antigen37. Recently, our lab has documented the superior cross-priming ability of the CD8α–CD11b– “merocytic” DCs (mcDC)32,37–40. mcDC acquire dead cell material through the process of merocytosis, wherein they take up small particles into non-acidic compartments followed by prolonged antigen storage and sustained antigen presentation. Upon uptake of dying cell material, mcDCs, but not CD8α+ or CD11b+ DCs, produce the type I IFN required for protective

9 immunity secondary to ablative tumor therapy37, a process that was further dissected in Chapter 5 of this dissertation.

Antigen presentation and TCR engagement is only one of three signals provided by professional APCs that are required to stimulate productive T cell responses. In addition to TCR stimulation, T cells receive activating signals by the engagement of costimulatory molecules and inflammatory cytokines. Costimulation is accomplished by the engagement of several additional cell surface receptors on the T cell41. The ligands CD80 and CD86, ICOS-L, and OX40-L expressed on APCs bind to CD2842,43, ICOS44, and OX4045 on T cells, respectively. Inhibition can also be achieved by engagement of related receptors on the T cells; CTLA446 and PD-147,48 both inhibit T cell responses when ligated by CD80/ CD86 and PD-L1, respectively. Cytokines produced by APCs and other nearby cells provide a third signal which can positively or negatively affect T cell priming. IL-12 and type I IFN are the prototypical signal 3 cytokines that promote T cell activation, differentiation, and proliferation49,50. Inhibition of T cell proliferation and effector functions by IL-10 has been well established51,52, and is one mechanism thought to promote peripheral toler- ance53. Depending on multiple factors, including the balance of pro- and anti-inflammatory cues, antigen presentation by APCs can either prime naïve T cells toward mature cells with effector functions, or it can cause T cell anergy or deletion, and result in tolerance.

1.1.3 PAMPs, DAMPs, and PRRs An important component to the innate immune system is the ability of almost any cell to sense danger. A large number of cytosolic and membrane-bound proteins serve as pattern recognition receptors (PRRs) to an even larger number of danger signals—both foreign and native in origin. Foreign signals derived from invading microbes are known as pathogen-associated molecular patterns (PAMPs). PAMPs comprise conserved protein, sugar, and lipid moieties which are distinct from host molecules and are essential for

10 pathogen survival. Damage-associated molecular patterns (DAMPs), or “alarmins,” are endogenous molecules that alert the immune system of damage, even in the absence of infection. Alarmins are released by cells that undergo an uncontrolled cell death and can be secreted by immune cells. Some hypothesize they exist because most trauma is accompanied by exposure to pathogens, and alarmins can therefore prime the immune system even earlier than it could otherwise recognize the invasion. However, alarmins also aid in tissue repair, and can be beneficial even in sterile settings54. Different PAMPs and alarmins are detected by families of receptors which localize to the cell surface, the internal space of endosomes, and the cytosol.

A large family of innate sensors, the toll-like receptors (TLRs), play a critical role in early immune responses to pathogens. The TLRs include at least 11 proteins with differential specificities toward both PAMPs and alarmins (Table 1)55. Most TLRs are situated in the plasma membrane and recognize extracellular PAMPs and alarmins. TLR3, TLR7, TLR8, and TLR9 are found within endosomal membranes and respond to intracellular pathogens. TLR signaling is accomplished largely through the adapter molecule MyD88, but also TRIF and TRAM. Only TLR3 and TLR4 can induce MyD88-independent signaling. Downstream TLR signaling is mediated by IL-1R-associated kinases (IRAKs), TNF-receptor-associated factor (TRAF) proteins, and several other downstream mediators which ultimately induce the translocation of NFκB or IFN-regulatory factors (IRFs), including IRF3, IRF5, and IRF7. Depending on the signal, these receptors can induce the rapid secretion of IL-6, TNF, and IL-12, among other inflammatory cytokines, or type I IFN.

The C-type lectin receptors (CLRs) provide another layer of protection against most invading pathogens through the recognition of carbohydrates. Most classes of pathogens express carbohydrates that activate CLRs. High levels of mannoses on viruses, myco-

11 Table 1: Toll-like receptors and their ligands. Reprinted by permission from Macmillan Publishers Ltd: Nature Reviews. Immunology55, copyright 2004. bacteria, and fungi are sensed by DC-SIGN (CD209) or Langerin (CD207/CLEC4K)56. Certain strains of bacteria and some helminths express fucose, which is recognized by the same receptors. Dectin1 (CLEC7A) recognizes glucans, including β-1,3-glucan, expressed by several mycobacteria species and fungi57. CLEC9A binds the filamentous actin of dying cells58,59, and thereby aids in the antigen presentation of cell-associated ma- terial60. Recently, attention has been given to targeting CLEC9A in DC-based vaccination strategies, since growing evidence suggest that CLEC9A-expressing DCs are essential for inducing CTL responses61. And, given its role in presenting cell-associated antigens, activating CLEC9A has special promise in eliciting anti-tumor immunity62.

Another major family of innate sensors is the AIM2-like receptor (ALR) or p200 family, which share at least one partially conserved region of 200 amino acids63,64. This family contains several sensors of cytoplasmic DNA, including IFI16 and AIM2. A p200 family

12 is present in mice and humans, encompassing several proteins with similar structure and function; however, the genes exhibit considerable genetic and functional diversity65. Among them, AIM2 is the only evolutionarily conserved gene. AIM2 functions in complex with ASC and caspase1 in a so-called “inflammasome.” Upon activation, the AIM2 inflammasome induces the cleavage of pro-IL-1β into active IL-1β and initiates a highly inflammatory form of programmed cell death called pyroptosis66. Several other innate dsD- NA-sensors including p200 family members signal through the adaptor protein commonly referred to as the stimulator of interferon genes, or “STING” (TMEM173, also known as MPYS, MITA, and ERIS)67–70. STING is also a cytosolic DNA sensor in its own right, directly binding to cyclic guanosine monophosphate–adenosinemonophosphate (cGAMP)71. The cyclic dinucleotide cGAMP is generated by cGAMP synthase (cGAS) from bacterial or endogenous DNA which has entered the cytosol. Once activated, STING activates and serves as a scaffold for TBK1, which phosphorylates IRF372. Phosphorylated IRF3 then translocates to the nucleus, where it induces production of type I IFN. STING will be discussed further in Chapter 5, where we will examine its role in promoting immune responses to dying tumor cells.

An additional family of proteins involved in cytosolic nucleotide sensing is the RIG-I-like family of receptors, including most notably RIG-I73 and MDA5. These are dsRNA heli- cases that mediate their effects through the common signaling intermediate mitochondrial antiviral signaling protein (MAVS; also known as IPS-1, VISA or CARDIF)74. MAVS directs further signaling that ultimately results in the activation and nuclear translocation of IRF3 and NFκB and subsequent production of type I IFN and other inflammatory cytokines. A depiction of the major cytosolic nucleotide sensors and their signaling pathways is shown in Figure 4.

1.1.4 Type I IFN Type I IFN is a dominant effector molecule downstream of myriad danger signals discussed in the previous section. Type I IFN comprises 13 IFNα proteins, IFNβ, IFNκ, and IFNω, all of which signal through a common receptor known as the interferon (alpha and beta) receptor, or IFNAR. Essentially all nucleated cells express IFNAR, a heterodimer including the two distinct subunits IFNAR1 and IFNAR2. A soluble form of IFNAR2 has also been reported in mouse76 and human77 fluids including urine and serum. Soluble mouse Ifnar2 was shown to competitively inhibit Ifnar1/2 signaling in the L929 type I IFN reporter cell line, but it was also shown to complex with type I IFN and Ifnar1 in Ifnar2-/- thymocytes, indicating that soluble Ifnar2 may act as both an agonist and an antagonist to IFNAR signaling76.

14 Upon binding their ligand at the cell surface, the conformation of IFNAR1 and IFNAR2 change and the two proteins dimerize, leading to the autophosphorylation of tyrosine kinase 2 (TYK2) and Janus activated kinase (JAK) 278, signaling molecules associated with the intracellular domains of IFNAR1 and IFNAR2, respectively79. Phosphorylated TYK2 and JAK2, now active, phosphorylate the signal transducer and activator of transcription proteins STAT1 and STAT2 which subsequently dimerize78. The activated STAT proteins rapidly translocate to the nucleus and bind IFN-stimulated response elements (ISREs), initiating the transcription of hundreds of so-called IFN-sensitive genes (ISGs). Activation of alternative STAT pairs, such as STAT4/STAT4, can lead to dimerization and initiation of transcription at so-called gamma-interferon activated sites (GAS) (Figure 5)80. A number of JAK/STAT-independent mechanisms also exist which are important for IFNAR signal transduction, including roles for CRKL, MAP kinases, PI3K, and mTOR in mediating RNA translation, RNA stability, and pro- and anti- apoptotic signals79. Type I IFN is known to initiate a positive feedback loop. In fact, signaling through the IFNAR is required for the expression of some type I IFNs. Two of the IFNs induced early by PRR stimulation, IFNα4 and IFNβ, induce IRF9 activation, which, in concert with STAT1/STAT2 heterodimer, is required for the transcription of other type I IFN genes, including those encoding for IFNα2, 5, 6, and 881,82.

Type I IFN plays well described, key roles in antiviral defenses by conferring direct antiviral effects, inhibiting cellular growth, controlling apoptosis, and by promoting anti-viral immune responses83. Studies have shown both autocrine and paracrine functions of type I IFN in the priming of T cells; for example, IFN produced by DCs can augment signals 1 and 2 within DCs, increasing the antigen presenting capacity of DCs and their expression of cell surface costimulatory molecules, while it can concurrently serve as a signal 3 cytokine, enhancing CD8 T cell priming through its signaling within T cells84–86. Furthermore, type I IFN can promote the activation of B cells, CSR, and is vital to the generation of an-

15 Figure 5: Canonical and alternative JAK/STAT signaling pathways induced by type I IFN. Adapted from Tomasello et al.: Frontiers in Immunology80, copyright 2014. Open access article used here under the terms of the Creative Commons Attribution License. tibody secreting plasma cells87,88. Moreover, type I IFN is a potent stimulator of NK cells, which can efficiently kill infected cells89. Importantly, while damage or pathogen sensing by PRRs can induce inflammation by the release vast quantities type I IFN, constitutive or “tonic” IFN signaling is thought to prime cells to respond more strongly to diverse inflammatory signals and is also thought to contribute to immune homeostasis90,91. Despite the vast literature on the roles of type I IFN in anti-viral immunity, surprisingly little is understood about its precise functions in sterile inflammatory processes, including cancer immunology, cancer immunotherapies, and systemic autoimmune diseases. The current

16 knowledge on the role of type I IFN in these processes will be discussed later in this chapter, and later chapters will seek to uncover previously unknown mechanisms by which IFN functions in disease.

1.2 Cancer The term “cancer” encompasses many diseases which vary widely in pathogenesis, pathology, and prognoses. The primary defining feature of cancer is the dedifferentiation and unrestricted growth of previously healthy cells. These transformed cells have the potential to invade tissues or organs at remote sites from the initial neoplasm, thereby disrupting critical, life-sustaining biological processes. Cancer is among the most common causes of death worldwide, accounting for over 8 million deaths annually92. Cancer treatment can be physically taxing, as well as financially burdensome. The most recent estimates for the national cost of cancer care in the US totaled $125 billion93. And, as treatments for other diseases succeed in extending our average lifespan, cancer incidence is expected to rise rapidly. Research into novel ways to prevent, halt, and eliminate cancer is desperately needed.

1.2.1 The (re-)emerging field of cancer immunotherapy Cancer immunotherapy is any process which augments the body’s immune reactivity toward neoplasms. The ultimate goal of immunotherapy is to eliminate tumors either alone or in conjunction with surgery, ablative therapies such as radiation, or chemotherapies. Some evidence indicates that our cancer burden is reduced by a natural ability of the immune system to recognize and destroy tumors as they arise, through what has been termed “cancer immunosurveillance”94. Moreover, the success of radiotherapy, at least in some cases, is dependent upon a functional immune system95,96. Unfortunately, the natural ability of the immune system to protect against tumors is limited, and may even lead to the outgrowth of transformed cells with reduced immunogenicity, making the de-

17 velopment of effective immunotherapies more challenging97,98. Hence, determining what naturally drives immune protection against neoplasms and might therefore be manipulated to enhance immunotherapies has been an area of intense investigation.

One of the earliest examples of immunotherapy occurred in 1891, at which time the function of the immune system was scarcely understood, when William Coley gave patients intratumoral injections of Streptococcus ‘erysipelatis’ (pyogenes), and was met with some success in treating several solid tumors99. The bacterial infection causes an acute inflammation of the skin and, when in the vicinity of certain carcinomas and sarcomas, led to their destruction. In the many decades since these initial findings, immunotherapies remained largely a niche treatment, especially given the relatively high success rates of radiation therapies and chemotherapy, and the insufficient evidence on the utility of his- torical immunotherapies. However, recent advances in our understanding of immunology together with a profoundly enhanced ability to manipulate or even manufacture immune responses has reinvigorated the field, leading to several FDA approved immunotherapies and more on the horizon100,101.

Direct stimulation of the immune system has been an approach with some efficacy, but also significant potential side effects. In 1992 the administration of high dose IL-2 was approved to treat patients with metastatic renal cancers, and has a reported response rate of between 15 and 25%, with some cases of nearly complete tumor regression102–104. Unfortunately, this treatment has also been responsible for a number of deaths, with significant toxicities including capillary leak syndrome, myocardial infarctions, and gastrointestinal toxicities102. The mechanism by which IL-2 is thought to halt tumor progression or even eliminate tumors is by activating T cells and NK cells, among other lymphocytes with the IL-2 receptor. This approach has also been used for patients with aggressive melanomas, and has been especially effective when it was given in conjunction with a

18 melanocyte-specific gp100 peptide, though response rates are still low, at only 16%, and toxicity is also seen in these patients105. In another attempt to broadly stimulate immunity towards tumors, a novel anti-CD28 agonist was used in patients with renal cancer. Rather than any protective effect, however, this treatment resulted in the rapid release of inflammatory cytokines, a “cytokine storm,” which nearly killed the study volunteers106. This type of damaging acute inflammatory response has been noted in several other immunomodulatory treatments107–109, underscoring the challenge that immunotherapy pos- es, but also its potential strength.

A logical alternative to directly stimulating the immune system is to remove inhibitors of its function by “immune checkpoint” blockade. This approach was considered particularly promising given the increasing evidence that the tumor microenvironment exerted strong inhibitory pressure on infiltrating lymphocytes110,111. Indeed, the promise of immune checkpoint blockade was realized upon the success of clinical trials using ipilimumab, tremelim- umab, and nivolumab, monoclonal antibodies targeting cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and programmed cell death 1 (PD-1), respectively112–114. Adverse events also occur with these treatments, though their toxicity appears to be relatively low, with few study drug-related deaths reported. These treatments halted tumor progression, but also importantly led to tumor regression in a large number of cases115–117. These targets were chosen specifically because of their increasingly well-established immunosuppressive roles in cancer. CTLA-4 is highly expressed on regulatory T cells (Tregs), and suppresses the otherwise co-stimulatory effect of CD80 and CD86 on APCs, possibly by capturing and removing these molecules from the surface of APCs118. Tregs are found at high frequencies in a number of tumors, where they are thought to play an important role in promoting tumor outgrowth through immune suppression119. PD-1 and its ligand PD-L1 also play critical roles in suppressing antitumor immune responses, through the induction of T cell anergy or exhaustion; importantly, many tumors express PD-L1, though

19 anti-PD-1 therapy appears to be nearly as successful in patients bearing PD-L1-negative tumors117. The successes of these and similar immune checkpoint blockades have been instrumental in reviving interest and hope in immunotherapy, though there is still much room for improvement in terms of efficacy and safety.

1.2.2 Type I IFN in immunotherapy and cancer immunology The immunomodulatory cytokine central to much of the work within this dissertation, type I IFN, has itself been the focus of immunotherapies, and has been shown to play key roles in antineoplastic immunity more broadly. Imiquimod, a potent TLR7 agonist, is used as a highly effective treatment for basal cell carcinoma120 and vulvar intraepithelial neopla- sia121. The use of CpG oligodeoxynucleotides, which potently stimulate IFN production via TLR9, has also been shown to prolong the survival of tumor-bearing mice, although its efficacy is most dramatic when combined with tumor ablative therapies122,123. Treat- ment of chronic myeloid leukemia (CML) with recombinant IFNα was shown to be more effective than conventional chemotherapeutics124,125, with upwards of 70% achieving complete hematological remission. Moreover, the 10 year survival in responders was greater than 70%126. While the therapeutic use of type I IFN has shown great efficacy, like many broadly immunomodulatory agents, its use is also associated with significant toxicities, especially flu-like symptoms, which many patients cannot tolerate; however, lower doses may be just as effective as higher doses and result in fewer toxicities127.

Beyond its use as an immunotherapeutic agent, type I IFN also plays key roles in cancer immunology. Several key studies have underscored this point, and have elucidated some mechanisms by which IFN functions. Dunn et al. demonstrated that mice were more susceptible to carcinogen-induced tumors if they lacked IFNAR, and that mice treated with anti-IFNAR antibodies were much more susceptible to transplanted tumor outgrowth than mice given isotype controls128. Fuertes et al. found an IFN signature in human metastatic

20 melanomas and infiltration of those tumors by T cells. In mouse modeling, the group went on to demonstrate that spontaneous antitumor CD8 T cell responses were defective in mice lacking either IFNAR or signal transducer and activator of transcription 1 (STAT1), a transcription factor immediately downstream of IFN signaling129. Burnette et al. showed that radiation therapy of B16F10 tumors induced type I IFN, and that the sustained progression-free survival following radiotherapy was highly dependent on the ability of the animals ability to sense type I IFN96. In work from our lab that is presented later in this dissertation, we show that the type I IFN released following tumor ablative therapies is produced by DCs, and that DCs themselves are the critical cell type which needs to sense IFN in order to prime effective antitumor CD8 T cell responses130. Additionally, we showed that STING within DCs was required for IFN production, and that the ligand responsible for its induction was nuclear DNA from dying tumor cells. Studies like these, which provide further insight into the mechanisms which boost antitumor immunity, are needed to allow the rational design of novel, targeted immunotherapies with increased efficacy and reduced toxicity.

1.3 Autoimmunity Autoimmunity describes the aberrant activity of an organism’s immune system to become highly activated by its own tissues. This can lead to destructive inflammation resulting in the loss of tissues and organs. But like cancer, autoimmunity describes myriad diseases with diverse outcomes, some more severe than others. Autoimmune diseases can be life-threatening, including responses toward major organs like type I diabetes or multiple sclerosis (MS), or in the case of systemic diseases such as systemic lupus erythematosus (SLE). Whether or not they are responsible for early mortality, many autoimmune diseases can be painful or otherwise debilitating.

Our lab recently began studying autoimmunity, because understanding what drives im-

21 mune responses to self-antigens in the context of cancer immunotherapies may provide insight into the mechanisms of autoimmunity. And, reciprocally, insights into autoimmune disease may provide avenues to exploit for novel anticancer immunotherapies. The study of SLE in particular was a natural choice for our lab, because, like antitumor immunity, SLE is a sterile inflammatory process involving atypical cell death and dying cell clearance, which also requires type I IFN.

1.3.1 Systemic lupus erythematosus SLE is a systemic autoimmune disease affecting multiple systems defined most prototypically by the development of anti-nuclear antibodies (ANA), antibody complex formation, and subsequent nephritis. However, SLE can affect patients in different ways and likely encompasses many different conditions with a core set of shared clinical signs. Reported symptoms can also resemble those of distinct diseases. Therefore, a diagnosis of SLE relies upon a patient meeting several well-defined immunological and clinical classification criteria131. Although SLE is usually not fatal, many patients live with significantly burdensome ailments132. In addition to nephritis, clinical signs include cutaneous, oral, neurological, hematological, pulmonary, and cardiac disorders. Estimates of incidence vary—between 10 to 150 cases per 100,000 individuals in the US are affected, with the highest incidence among women and people with African or Hispanic ancestry133–135.

1.3.2 SLE pathogenesis The cause of SLE is not known. Given the heterogeneity of clinical symptoms patients develop, the pathogenesis of SLE almost certainly varies. The current understanding is that disease arises due to the unfortunate conspiration of genetic risk factors and environmental triggers136,137.

Most hypotheses as to what biological process initiates disease involve either dysregulat-

22 ed apoptosis or insufficient clearance of dying cells138–140. Indeed, high levels of apoptotic cells are found in SLE patient serum141, germinal centers142, and in inflamed tissues, such as in the skin of patients with cutaneous lupus erythematosus142 and in the glomeruli of mice with an SLE-like disease143. However, an abundance of apoptotic material alone cannot account for the development of systemic autoimmunity. Under physiological conditions, the clearance of dying cells is a tightly regulated process employing redundant mechanisms to prevent autoimmunity. Although it is not yet clear how immunological tolerance is broken in SLE, DCs likely play key roles. Perhaps the most prominent model proposes that initial injury is due to the unremitting output of type I IFN by pDCs which leads to persistent activation of cDCs and the subsequent expansion of autoreactive T cells144. The known roles for DCs in SLE will be discussed in Chapter 3 of this dissertation.

Genome-wide association studies have linked a number of specific genes to increased risk for developing lupus145. Alterations in these genes generally impart odds ratios of less than 1.5, and a combination of multiple polymorphisms is thought to be necessary to put an individual at significant risk for SLE. A few rare genetic variants may function on their own to greatly increase this risk, however. For example, rare mutations in the cytosolic exonuclease TREX1146–149, and certain members of the complement system150 are believed to dramatically increase the risk for SLE. These and other associations have been supported by work in mice. Mice lacking C1q develop ANA with multiple specificities and glomerulonephritis143. Trex1-deficient mice develop a severe form of autoimmunity and ultimately succumb to inflammatory myocarditis151,152.

Some likely environmental triggers of SLE have been identified, though this remains an area in need of investigation. Infection with Epstein-Barr virus was suggested by Harley and others as a possible environmental trigger for SLE, after recognized a striking sim-

23 ilarity between a short peptide within the splicesome, a common target of lupus ANAs, and an EBV peptide153. A compelling association study supported this hypothesis—in a large study of adolescents, 99% of SLE patients had developed antibodies toward EBV, indicating prior infection, whereas anti-EBV antibodies were detected in only 70% of controls154. SLE has also been associated with an increased sensitivity to sunlight; in controlled studies, patients developed erythema upon exposure to significantly lower levels of ultraviolet light and the erythema lasted longer compared with control subjects155. A role for hormones in lupus etiology has long been suspected, especially since women are at a disproportionately higher risk for developing SLE. The current literature lacks the strength needed to confirm this hypothesis; however, hormones may indeed play a role in existing patients. Pregnancy and the postpartum period, for example, have been associated with increases in disease flares156,157.

1.3.3 Type I IFN in SLE Aberrant overproduction of type I IFN is a prominent feature associated with the development of SLE158–161. Gene expression profiling of SLE patient peripheral blood mononuclear cells (PBMCs) identified the existence of a type I IFN gene signature which was found to correlate with disease severity162,163. Furthermore, the use of IFN to treat hepatitis C virus and cancer has been associated with the induction of SLE164–166, and the administration of IFN induced earlier onset, lethal disease in (NZB x NZW) F1 lupus-prone mice167. Moreover, genetic deletion or antibody blockade of IFNAR in several mouse strains prone to spontaneous development of lupus-like diseases including (B6.Nba2 x NZW) F1, NZB, and BXSB.Yaa, or in pristane-induced lupus resulted in nearly complete abrogation of disease, demonstrating a vital role for type I IFN in murine models of SLE168–171. Together, these findings strongly suggest type I IFN functions to promote human SLE pathogenesis and/or pathology.

24 Elevated levels of free nucleic acids and their uptake by APCs is one mechanism thought to induce the production of type I IFN. APCs, including DCs, may be exposed to higher levels of nucleic acid, due to reductions in serum DNAse I activity172, which normally protect against sterile inflammation by degrading nuclear DNA released from apoptotic and necrotic cells. In fact, some SLE patients have been found to have mutations in DNAse I173, and mice deficient in DNAse I develop an autoimmune disease resembling SLE174. Some reports indicate that immune complexes (ICs), which are abundant in SLE patients, contain self DNAs and RNAs, and their uptake by DCs (particularly pDCs) may induce type I IFN via the engagement of TLR9 and TLR7, respectively175–177. Toll-like receptors have been implicated in many studies, whether or not ICs are critical178–183, and notably autoimmunity in the BXSB/Yaa lupus prone mouse has been causally linked to the translocation and duplication of TLR7184–186.

Cytosolic nucleotide sensing has often been hypothesized to contribute to IFN production in SLE, although relatively little has been done to test these hypotheses. Certainly, the mouse studies on Trex1-deficiency show that cytosolic nucleotide sensing can mediate autoimmunity, and are highly suggestive that nucleotide sensing could be involved in SLE pathogenesis. The Ifi200family of IFN-inducible genes, which includes the cytosolic DNA sensors Aim2 and Ifi204, has been linked to disease in the (NZB x NZW) F1 mice, is notably contained within the NZB-derived Nba2 locus, and is thought to play roles in those and additional mouse models of SLE187. Indeed, we found that STING promoted autoimmunity in the bm12 inducible model of SLE (Chapter 5 of this dissertation), further implicating a possible role for cytosolic nucleotide sensing in SLE130. Additionally, recent clinical studies revealed that activating STING mutations can induce inflammatory diseases with lupus-like features in patients, including high serum levels of type I IFN, autoantibodies, and a classic malar rash188,189. Although these patients were diagnosed with a novel disease, STING-associated vasculopathy with onset in infancy (SAVI), and

25 not SLE, these case reports support a possible role for cytosolic nucleotide sensing and indeed STING in SLE pathogenesis.

Although many studies have assessed the necessity for IFN in SLE, what signals induce IFN, and what cell types produce IFN, relatively few have sought to characterize its mechanism of action in SLE. In 2001, Blanco et al. found that monocytes derived from patient peripheral blood differentiated into DCs, and efficiently presented antigen from dying cells to CD4 T cells. Furthermore, the serum of patients with SLE, but not control serum, could induce healthy donor monocytes to differentiate into DCs, and this process was dependent upon type I IFN. This led the authors to conclude that one role of IFN in lupus may be the constant induction of DCs190. The role for type I IFN sensing by B cells may also be important in SLE, especially since type I IFN is known to promote B cell activation, class switching, and support the generation of antibody secreting plasma cells87,88,191. However, no published reports have tested the role for IFN sensing specifically by B cells, an area of interest our lab is currently pursuing. In Chapter 5 of this dissertation, we provide the first study into the possible roles of IFN sensing by CD4 T cells in SLE. CD4 T cells that differentiate into T follicular helper cells (Tfh) deliver indispensable help to activated B cells in germinal center reactions. In the bm12 cGVHD model of SLE, transferred bm12 CD4 T cells all differentiate into Tfh. We found the ability of bm12 Tfh to sense type I IFN was critical to disease progression, and that the high levels of type I IFN induced in these animals provided Tfh protection from NK cell attack.

1.4 Cellular metabolism The concept of cellular metabolism has been explored by researchers across multiple disciplines, revealing a complex network of molecular interactions which provide energy in the form of ATP, but also the basic components of cellular structure including nucleotides, amino acids, and lipids (Figure 6, left panel). Advances in the technology used

26 Figure 6: Cellular metabolism. A network depicting the integrated metabolic pathways immune cells use at various points during development and upon activation (left panel). A diagram highlighting the distinct relative contributions of the different pathways to different naïve and mature T cell subsets (right panel). Reprinted under the terms of the Creative Commons Attribution License from Buck M, O’Sullivan D, and Pearce E: Journal of Experimental Medicine194, copyright 2015. to interrogate these metabolic pathways, as well as an advanced understanding of various immune cells and the ability to purify them, has led to a recent flood of studies on the cellular metabolism of various immune cell subtypes. T cells have been particularly well studied. Naïve T cells rely predominantly on oxidative phosphorylation (OXPHOS) or fatty acid beta oxidation (FAO) with minimal utilization of glyocolysis192. Upon activation, T cells—in large part—undergo metabolic reprogramming to become much more dependent on aerobic glyocolysis, FAO (Figure 6, right panel)193, and glutaminolysis194. Glycolysis is not strictly required for the proliferation and differentiation of activated T cells195, but it has been recognized as critical to their effector function195,196. The switch to aerobic glycolysis, which was first described 60 years ago by Otto Warburg, who was studying cancer cells at the time197, is not thought to better meet the energetic needs of

27 the cells—especially considering the much higher efficiency of ATP production via the TCA cycle—but rather it is thought to meet these needs adequately while also providing the molecular substrates required in vast quantities during rapid proliferation and production of effector molecules, especially by shuttling glucose derivatives through the pentose phosphate pathway198.198. Glutaminolysis is another major metabolic pathway upregulated in activated T cells which serves multiple purposes194. It can contribute to energy production by converting glutamine into α-ketogluterate, a TCA cycle intermediate. Alternatively, glutaminolysis can also contribute to the production of nucleic acids or amino acids. One notable exception to the paradigm of a metabolic switch toward aerobic glycolysis and glutaminolysis upon activation is regulatory T cells, which maintain their reliance on OXPHOS and FAO and do not switch to aerobic glycolysis199. The metabolic program of T follicular helper cells has remained elusive until now. In Chapter 7, we thoroughly characterized the metabolic program of Tfh using cells isolated from the bm12 cGVHD model of SLE, and determined that these cells utilize both aerobic glycolysis and FAO, but not glutaminolysis. The metabolic program of B cell subsets in vivo has not been well defined. However,in vitro studies have shown increased glycolytic rates within B cells activated by LPS200 or anti-CD40 + anti-IgM201 stimulation. In Chaper 7 we also characterize the metabolic programs of plasmablasts and germinal center B cells directly ex vivo, and demonstrate that these cell types are completely dependent upon glycolysis, with very little utilization of FAO or glutaminolysis.

1.5 Dissertation Aims The immune system is a complex and powerful tool an organism wields to defend itself from invaders. Given its strength, the immune system is subject to tight control. Minor perturbations in signals that promote inflammation can lead to profound tissue destruction. This can be deleterious or helpful, depending on the context—immune responses to tumor antigens can help eliminate deadly tumors, whereas aberrant responses to healthy

28 tissue can cause debilitating autoimmune diseases. The subsequent chapters in this dissertation will explore novel mechanisms that regulate immunity toward self, with the goal of uncovering new targets for the treatment of certain cancers and autoimmune diseases. Briefly, in Chapter 5, we examine how STING-mediated DNA sensing promotes antitumor and autoimmune responses to dying cells via the induction of type I IFN. In Chapter 6, we further dissect the role of type I IFN autoimmune disease, and show that IFN protects Tfh from NK cell attack in the bm12 model of SLE. Finally, in Chapter 7, we originally hypothesized that type I IFN sensing may control CD4 T cell metabolism, but ultimately we examined cellular metabolism more globally in bm12 autoimmunity and found that Tfh, GC B cell, and plasmablasts all relied heavily upon glycolysis, such that inhibiting glycolysis completely abrogated disease.

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39 Chapter 2: Melanoma-infiltrating Dendritic Cells: limitations and opportunities of mouse models*

*This is an open-access article reprinted here under the terms of the Creative Commons Attribution License, originally published 2012: Melanoma-infiltrating dendritic cells: Limitations and opportunities of mouse models. Klarquist J and Janssen EM. Oncoimmunology. 2012 Dec 1;1(9):1584-1593.

40 Abstract The infiltration of dendritic cells (DC) into melanomas has been suggested to play a tumorigenic role due to their capacity to induce tumor tolerance and promote angiogenesis and metastasis. However, studies have also shown that tumor-infiltrating DC (TIDC) induce anti-tumor responses and could therefore be targeted in a cost-effective therapeutic approach to obtain patient-specific DC that presenting relevant tumor-antigens, without the need for ex vivo DC generation or tumor antigen identification. Unfortunately, little is known about the composition, nature and function of TIDC in human melanoma. The development of mouse melanoma models has contributed greatly to the molecular understanding of melanoma immunology in mice, but many questions on TIDC remain to be answered. Here we discuss the current knowledge of melanoma TIDC in various mouse models with regard to its translational potential and clinical relevance.

Introduction The incidence of cutaneous malignant melanoma has been steadily increasing over the last decades. While complete surgical excision yields high 5 year survival for patients with localized tumors with less than 0.75 mm depth, the outcome is poor for patients with a greater depth of tumor invasion or metastases. Consequently, the development of novel therapeutic approaches is of great importance. Interestingly, melanomas are relatively immunogenic tumors and sensitive to CTL mediated lysis. As DC are the main antigen-presenting cell (APC) population capable of inducing CTLs, DC transfer, DC targeting and in situ DC induction, recruitment, and/or activation have become promising immunotherapeutic strategies. Topical or intratumoral administration of DC-activating agents –including IFNa, bacillus Calmette-Guerin (BCG), or purified toll-like receptor (TLR) ligands such as Imiquimod– are recommended as treatment options for patients with in-transit melanoma metastasis1-5. While this approach is relatively successful in cutaneous metastases, efficacy is still poor in subcutaneous metastases. Improved understanding of the type, nature

41 and functionality of TIDC could lead to novel and more effective therapeutic approaches. To circumvent the ethical and TIDC availability constraints associated with human research, various animal models for melanoma have been established including models in Xiphophorus, Danio, guinea pigs, opossum, and small rodents, all of which have unique advantages and disadvantages. The relevance of the selected model depends on the questions to be answered and how closely the model resembles the histological, immunological and metastatic pattern observed in humans6. To date, most work is performed in mice due to the availability of genetically modified mice, insights into mouse immunology, pathology and physiology, and the plethora of mouse-specific research tools. Here we will briefly review the current knowledge of TIDC obtained in the most common mouse melanoma models and the insight it has provided into the human disease.

Selection of mouse model for melanoma tumors Melanoma models are generally divided into 3 different groups based on research focus; xenograft models, which allow for the study of tumor cell behavior; transplantation models to study melanoma immunology, and genetically modified animal models that focus on melanomagenesis. Strictly chemical carcinogen-induced melanoma models have decreased in popularity as they have relatively low relevance to human disease and therefor will not be discussed further.

Xenograft models: Orthotopic or ectopic transplantation of human cancer cells or solid tumors into immune compromised mice. The primary advantage of these models is the preservation of human cancer cell behavior including metastatic potential and preference; however, the absence of a complete immune system does not allow for full replication of interactions between tumors and immune cell subsets. While DC function is relatively normal in some immune compromised strains, various strains –including those on the NOD.Cg-Prkdcscidil2rg background– have defective DC development and function7-9. In

42 addition, human tumor-derived mediators might affect mouse DC recruitment, retention, development and function different than the mouse homologues. The more recent development of human melanoma models in humanized mice10-12 circumvents these issues and provides an intriguing platform for clinically relevant TIDC studies.

Syngeneic transplantation models have been around since the identification of the Cloud- manS91 melanoma in BDA/2 mice, Harding-Passey melanoma in Balb/c x DBA/2F1 mice and B16 melanoma in C57BL/6 mice13-16. The B16 melanoma is currently the most widely used model and has the advantage that it expresses at least 5 homologues of the best characterized human melanoma antigens (gp100/pmel17, MART-1/MelanA, tyrosinase, TRP-1/gp75 and TRP-2/DCT)17, it is immunogenic and it has metastatic potential. The main drawback of this model is the rapid growth of the primary tumor that leads to problems with vascularization, necrosis, and swift mortality that precludes the assessment of prolonged tumor burden on TIDC behavior. Nevertheless, most TIDC studies have been performed in B16 melanoma models.

Genetically engineered models (GEMM): The identification of genetic and epigenetic abnormalities in human melanomas has led to the development of genetically engineered mice with heritable predispositions to the development of melanoma. The use of (tissue-specific) expression of oncogenes including Ret, mutant forms of (N/K/H)Ras and BRaf, and HGF/SF with or without back-crossing to susceptible backgrounds (Ink4a/Arff/f, P53t/t, p19-/-, p16-/-, Cdk4R24C/R24C, etc.) has yielded models with different latency, penetrance of melanoma, and metastatic potential (reviewed in 18, 19). Although melanocyte distribution differs between mouse and human, these models have great clinical relevance as they are based on genes known to be involved in the genesis and progression of human melanoma and can be easily combined with relevant environmental triggers such as UV irradiation to accelerate melanoma incidence. Only recently the field has begun to

43 use these models for TIDC studies.

Dendritic cells DC are a heterogeneous population in terms of origin, morphology, phenotype and function. DC are derived from common myeloid and lymphoid precursors and rely heavily on Flt3L and/or GM-CSF for their development20-22. DC express MHC class I and class II molecules together with a wide variety of membrane associated positive (CD40, CD80, CD86, CD137L, CD70) and negative (PDL1, PDL2) costimulatory molecules. In addition DC can produce a broad range of soluble pro-and anti-inflammatory mediators, including cytokines and chemokines. T cells interacting with DC via cognate TCR-peptide-MHC complexes will undergo apoptosis, anergy, or develop a regulatory phenotype if the degree of negative stimulation outweighs that of positive costimulation23. If the positive sum of the signals surpasses an intrinsic threshold T cells will undergo proliferation, differentiate and acquire effector functions. Immature DC display great phagocytic capacity, relatively poor antigen presenting capacity and low levels of positive costimulatory molecules. Upon activation via innate receptors (TLRs, NLRs), proinflammatory cytokines or cross-linking of CD40, DC mature, reduce their phagocytic capacity, increase antigen presenting capacity, upregulate costimulatory molecules and cytokine production, and migrate to draining (lymphoid)areas where they interact with T cells 24-26.

Cells with DC characteristics have been repeatedly described in human melanoma samples. Depending on the study, the markers used, the localization and maturation status, DC infiltration is linked with a positive27-30 or negative31 prognostic outcome. The discrepancy in outcomes can be contributed to differences in clinical stages, the use of primary versus metastatic lesions, as well as use of markers that are non-specific or restrictive to a subpopulation of DC 32.

44 Studies in several other tumor systems indicate that tumors inhibit dendropoiesis, decelerate DC differentiation and maturation, induce functional deficiencies, and accelerate cell death in DC or precursors33, 34. Maintenance of an immature phenotype or promotion of tolerogenic phenotype could lead to anergy/deletion of tumor-specific T cells and the induction of cells with immunosuppressive functions such as Tregs. Slowed differentiation could contribute to the accumulation of myeloid-derived suppressor cells that are derived from precursors that under steady state conditions would differentiate into DC, macrophages and neutrophils35. In addition, immature and pre-DC have been suggested to promote angiogenesis through the secretion of growth factors (i,e. Vegf) that directly act on the endothelium, secretion of mediators that enhance sensitivity of endothelial cells to growth factors36, 37. Other experimental studies even suggest that DC precursors may undergo endothelial transdifferentiation or provide a scaffold for subsequent lining by endothelial cells38.

DC populations in mouse and man Recent genomic and proteomic approaches have discovered significant similarities between human and mouse DC populations39-43 thereby strengthening the relevance of TIDC research in mouse melanoma models. While several aspects of localization, surface marker expression, TLR expression, phagocytic potential and antigen presenting capacity are relatively comparable between some mouse and human DC subsets, they are not perfect matches and in some cases the equivalent populations are absent. We will briefly describe the mouse and human DC populations in the following sections.

Mouse DC populations Under steady state conditions mouse DC express CD11c and MHC class II and are divided into plasmacytoid DC (pDC) and conventional DC (cDC)21. pDC express intermediate levels of CD11c, and high levels of CD45RA (B220), PDCA1 (CD317) and TLR1,2,4,

45 7, and 9, and play an important role in infection due to their capacity to produce large amounts of type I IFNs44. Antigen presentation by pDC is thought to be relatively poor45. Conventional DC are further divided into blood-derived resident DC and migratory DC. Blood-derived resident cDC are present in lymphoid tissues and encompass: (i) CD- 11chighMHCII+CD8a+CD205+SIRPa-CD11b- (CD8aDC) that express XCL1, Clec9A and often CD103. CD8aDC express mRNA for most TLRs except 7 and 5 and are characterized by high TLR3 expression44. These DC have the greatest potential to prime CTLs to cell-associated antigens via cross-presentation but have relatively low CD4 T cell activation potential46; (ii) CD11chighMHCII+CD8a-33D1+SIRPa+CD11b+(CD11bDC), that predominantly activate CD4 T cells, have poor cross-presentation capacity and express most TLRs except TLR3; (iii) CD11chighMHCII+ cells that lack CD8a, CD4 and CD11b (generally termed “double” or/ “triple” negative DC) that may or may not express XCL1, Clec9A, and TLR3 and CD103. DC subsets in this population have been shown to potently prime both CD4 and CD8 T cells to cell-associated antigens47-49.

Migratory DC can be found in many organs and migrate upon activation into draining lymphoid areas22, 50, 51. As this review focuses on melanoma we will limit our description to skin-resident DC. Various populations of DC have been described in non-inflamed mouse skin. Langerhans cells (LC), CD11b+CD207+CD103- DC reside in the epidermis and express TLR2,4, and 9 but not 7 52. Cross-presentation of cell-associated antigens in LC has not been demonstrated but LC have the capacity to cross-present antigen associated with TLR ligands 53, 54. In the dermis CD11b+CD207- dermal DC (dDC) represent the major DC subset whereas, CD207+CD103+ dDC and CD207-CD11b- dDC represent ~20% of the dDC. dDC express most TLRs and especially the CD103+ dDC population has been associated with the cross-presentation of cell-associated antigens52, 55, 56.

The sharing of multiple markers between DC subsets and their changes in expression

46 levels upon activation complicate the identification of DC subsets. Environmental cues associated with inflammation or tumors can change their surface characteristics, behavior or capacities adding another layer of complexity to identification of DC.

Human DC populations Like mouse DC, human DC are generally divided into pDC and cDC. pDC are lineage negative (lin-) CD11c-HLA-DR+CD123+ BDCA2/4+ and express high levels of TLR 7 and 9 57, 58. In contrast to mouse pDC human pDC have been shown to cross-present cell-associated antigens45, 59. cDC are further divided based on their expression of BDCA- 1 (CD1c) and BDCA-3 (CD141). The BDCA-1+ DC has similarities with the mouse CD11b DC as it expresses SIRPa and CD11b39, strongly responds to TLR1 and 6 stimuli and promotes induction of CD4 T cell responses. The BDCA-3+ DC has strong similarities with mouse CD8aDC and expresses Clec9A, XCR1, and high levels of TLR360, 61. Recently it was shown that the BDCA-3 DCs have the greatest capacity for cross-presentation within the human DC repertoire60-62.

LC are the only DC in healthy epidermis and comprise 2-8% of all epidermal cells. LC express high levels of CD1a, MHC class II, CD207, EpCAM, low levels of CD205, and DC immunoreceptor (DCIR)63. Both DCIR and CD205 are associated with antigen uptake and induction of antigen-specific T cell responses64. LC express mRNA for TLR 1,2,5,6 and 9 (not 4 or 7/8)65. The number of dDC populations described in humans has recently been expanded. The major dDC population is BDCA-1/CD1c+, with most of these cells expressing CD11c and about 50% of the CD1c+ population expressing CD1a 66. CD1cneg BDCA-3/CD141+ dDC represent about 10% of all the CD11c+ dDC and demonstrate superior cross-presentation of soluble antigen compared to other DC populations66. Most dDC express mRNA for TLR1,2,4,8,10 but the exact distribution among subsets needs further delineation63.

47 Human melanoma TIDCs Melanoma-infiltrating DC have been found in primary and metastatic lesions anden- compass a broad spectrum of DC-like cells, including CD207+ LC, pDC, and CD1a+ DC (Table 1)27, 28, 31, 67-69. Due to differences in patient material, the low frequency of TIDC, the use of ambiguous analytical markers, and especially approaches that limits the number of analytical markers there is little consensus on the exact composition of the TIDC pop- ulation32. However, there is a general agreement that the frequency of TIDC is higher in the peritumoral area than the intratumoral area and that the TIDC with the most mature phenotype (DC-LAMP+/CD83+/fascin+) tend to reside in the peritumoral area27, 31, 67, 68. It is thought that immature DC enter the tumors via the vasculature and –following further differentiation and activation– migrate towards the tumor edge. From there, the DC either locally form T cells clusters or continue migrating towards the draining LN where they interact with T cells. The relationship between the presence and location of different TIDC subsets and clinical outcome remains a puzzle as it not only depends on the type of the TIDC, but also their functionality and interactions with other cells, all aspects that are currently poorly understood.

48 Mouse melanoma in TIDCs While mouse models have the advantage of ample tumor material that allows for easy selection of primary from metastatic lesions and selection of different tumor development stages, there is surprisingly little consensus in the field on TIDC frequency, composition, and function. Some of these discrepancies result from the use of different model systems or strain backgrounds. When we compared two xenograft models, 3 syngeneic transplantation models and 2 GEMMs we observed significant differences in TIDC frequency (data not shown) and composition between models (fig 1a). The highest frequency of TIDC was seen in syngeneic transplant models while GEMMs had significantly less TIDC. How- ever, GEMMs showed greater diversity among the TIDC, with marked infiltration by pDC, LC and dDC. Xenografts showed the least variety, completely lacking LC and dDC while in syngeneic transplant models an occasional dDC (CD207+ EpCAM-) cell was found. Although a full comparison between studies is hard to make as not all studies used the same set of markers, a review of mouse melanoma literature showed similar findings in the different model systems (table 2)70-75.

The differences in TIDC composition between models and species highlight the importance of melanoma model validation for each type of study. While all models have significantly contributed to melanoma immunology knowledge, pre-clinical DC targeting studies would benefit from models that more accurately resemble TIDC composition seen in patients.

Mouse TIDC activation status As in human melanoma, mature mouse TIDCs tend to reside in the peritumoral areas and total TIDCs seem to increase upon disease progression (fig.1b,c)72. Most studies assessing mouse TIDC activation and maturation status use flowcytometric analysis of CD11c+ cells from the entire tumor. Consequently, reports show a biphasic distribution

49 of the maturation markers CD40/CD80 and CD8670, 71, 73, 74. Analysis after separation of the peritumoral and intratumoral areas of B16/F10 melanomas replicate the histological observations, showing significantly more mature TIDC in the peritumoral area compared to the intratumoral area (fig. 1d).

It is thought that the tumor environment promotes the recruitment of DC precursors and immature DC, but little is known on the ability of melanomas to support in situ differentiation 76. Diao et al showed that adoptively transferred immediate cDC precursors (Lin-CD- 11c+MHCII-) were recruited to B16/F10 tumors where they proliferated and differentiated into cells with T cell priming capacity in vitro, suggesting at least partial acquisition of DC-like functions77. On the other hand, in vivo data from Fainaru et al. demonstrated that recruitment of immature DC promoted angiogenesis and tumor growth by enhancing

50 Fig. 1. TIDC composition, location and maturation. (A) Composition of CD45+ Lin- CD11c+MHCII+ TIDC in different melanoma models. Tumors (400-600mm2) were harvested from Nu/J nude mice (MV3, A375; n=6/group)), BDA/2 mice (CloudmanS91; n=5/group) and C57BL/6 mice (B16F1 and B16/F10 n=9/group), digested according to standard protocols106, 107, and analyzed by multicolor flowcytometry. β-actin::LSL-KRAS mice crossed onto a Tyr::CreERT2 background108 were repeatedly treated with Tamoxifen between 1and 2 months of age. Tumors were harvested 4-6 months later (1-2 melanomas/ mouse, 3 mice). MT::Ret transgenic mice109 were aged and spontaneous melanomas were harvested when they reached 200-300mm2 (1-3 melanomas/mouse, 4 mice). (B) Representative confocal image of TIDC localization in a snap-frozen B16/F10 tumor seven days after s.c. injection of 2x106 tumor cells in C57Bl/6 mice. CD11c, Red; CD11b, Green, nuclei, DAPI. (C). Relation between total TIDC frequency within the TIL and B16/F10 melanoma size in C57Bl/6 mice as determined by flowcytometry. (D) Differen- tial expression of maturation markers on peritumoral and intratumoral TIDC. B16/F10 tumors (≈ 600mg, n=4-5/group) were harvested and the peritumoral area was collected using ophthalmic blades and peritumoral and intratumoral tissues were processed according to standard protocols106, 107. CD40, CD80 and CD86 expression were determined in the live CD45+ Lin- CD11c+ MHCII+ populations by multicolor flowcytometry.

51 endothelial cell migration and subsequent formation of vascular networks78. Moreover, depletion of CD11c+ cells in CD11c-diphtheria toxin receptor (DTR) transgenic mice significantly reduced the tumor mass of intraperitoneally injected B16/F10 melanoma cells78. While other tumor models suggest roles for endothelial like differentiation of DC-precursors, Vegf-A, b-defensin, bFGF, and TGFb1 in this type of processes, the mechanistic underpinning of DC-supported vasculogenesis in melanoma has not been clearly estab- lished79, 80.

Mouse TIDC functionality In order to be a bona fide APC, DC will need to acquire antigens through one of the phagocytic pathways, process and present antigen, and communicate with T cells locally or upon migration to draining areas. Studies injecting beads into tumors revealed that a sizable fraction of the TIDC acquired one or more beads, indicating that that particulate uptake mechanisms were relatively intact71, 73. However, Gerner et al. showed decreased uptake of intratumoral injected proteins compared to dDC from healthy tissue73. Sepa- rating peritumoral and intratumoral TIDC, we found that in vitro uptake of protein and apoptotic cell material was higher in the peritumoral TIDC than the intratumoral TIDC (fig.2.a). Similar observations were made when peritumoral and intratumoral TIDC were analyzed 4 hours after in vivo intratumoral injection. Interestingly, co-administration of LPS decreased phagocytic uptake in the peritumoral TIDC but not the intratumoral TIDC (fig. 2b).

Most studies show decreased CD4 and CD8 T cell activating capacity of TIDC isolated from antigen expressing tumors or upon pulsing with antigen in vivo 70, 73, 74. However, several studies indicate potent T cell priming capacity in vitro or in vivo 71, 77, 81. This discrepancy can be partly explained by divergent subset composition, DC location, DC maturation state, isolation methods, and in vitro functional assessment protocols. When separating

52 Fig. 2. TIDC functionality. (A) In vitro phagocytic capacity of TIDC. Peritumoral and intratumoral TIDC were isolated from B16/F10 tumors in C57Bl/6 mice (as in figure 1) and cultured for 4 hours with CFSE-labeled apoptotic splenocytes (1:3 ratio) or fluorochrome-conjugated OVA (100ug/ml) in the presence (black bar) or absence (gray bar) of LPS (Salmonella Minnesota R595, 0.1 ug/ml) (n=4-5/group). (B) In vivo phagocytic capacity of TIDC. B16/F10 tumors (≈ 600mm2) were injected with CFSE –labeled apoptotic cells (1x106) or 200ug fluorochrome-conjugated OVA (+/- 10ug LPS). Four hours later peritumoral and intratumoral TIDC were isolated and analyzed by flowcytometry (n=4-5/group). (C) Effect of BrefeldinA (BrefA) inclusion during TIDC isolation from B16-OVA melanomas on endogenous tumor antigen presentation. BrefA was added during digestion, incubations and sorting at a concentration of 40ug/ ml82. Peritumoral and intratumoral TIDC from B16/F10-OVA tumors were cultured with OVA257-264-specific B3Z hybridoma cells and hybridoma activation was determined 20 hours later by chlorophenol red-β-D-galactopyranoside (CPRG) conversion (n=5-6/group)110. TIDC derived from B16/F10 parental tumors were used as negative control. (D,E) Peritumoral and intratumoral TIDC (isolated in the presence of absence of BrefA) were cocultured with CFSE-labeled OVA257-264-specific OT-1 T cells. After 24 hours, activation was determined by CD69 expression in 7-AAD- CD8+ Vα2+ Vβ5+ cells. OT-1 T cell proliferation was assessed by CFSE dilution after 72 hours of culture with indicated TIDC (n=5-6/group).

TIDC based on GR1 expression, Diao et al. showed that GR1+ expressing TIDC had increased IL-10 production and reduced CD8 and CD4 T cell priming capacity compared to GR1- TIDC when loaded in vitro with antigen75. In addition, CD8 T cells primed by GR1+ TIDC demonstrated significantly reduced cytokine production. Gerner et al. suggested that the TIDC’s decreased capacity for CD4 T cell activation resulted predominantly from reduced antigen uptake as antigen processing and presentation was unaltered73. To

53 further dissect the antigen presenting and T cell priming/activating potential we isolated peritumoral and intratumoral TIDC from B16-OVA bearing mice and cultured them with an OVA257-264-specific reporter cell line (B3Z) and CFSE labeled OVA257-264-specific OT-1 T cells. We included brefeldinA in the isolation procedure to prevent turnover of MHC- I-peptide complexes while preserving the TIDC’s maturation state82. Importantly, significant antigen presentation was observed only when brefeldinA was present during the isolation period, illustrating the importance of optimizing and standardizing TIDC isolation protocols. The total TIDC fraction poorly activated the B3Z cells (fig.2.c), suggesting a low frequency of OVA257-264-MHC complexes. Consequently, total TIDC-mediated OT-1 T cell activation and proliferation was poor as determined by CD69 upregulation and CFSE dilution (fig. 2.d,e). However, peritumoral TIDC displayed higher frequencies of

OVA257-264-MHC complexes, and activated and induced proliferation in a sizable frequency of OT-1 T cells (fig. 2.c-e). Intratumoral TIDC had less OVA257-264-MHC complexes and activated OT-1 T cells without inducing proliferation. This lack of proliferation could be restored by addition of IL-2 but not blockade of IL-10 or TGFb, suggesting the induction of T cell non-responsiveness. Importantly, treatment of peritumoral TIDC with TLR4 or 9 ligands significantly increased their potential to induce T cell proliferation while the same treatment did not improve that of intratumoral TIDC (data not shown). Together these observations show that differences in isolation protocols, TIDC subset criteria, and functional assays significantly complicate the comparison between studies and the extrapolative value of the findings.

While many studies indicate a decrease in maturation and functionality of melanoma TIDC, the mechanisms that underpin the changes in APC functions are still unclear. In- creased expression of immunosuppressive cytokines and membrane-associated molecules by TIDC has been implicated in TIDC dysfunction72, 83. Other tumor models suggest that tumor-derived cytokines or reduction in TIDC sensitivity to innate signals prevents

54 maturation, migration and thereby TIDC function84-88. However, prolonged TIDC retention and maintenance of an immature phenotype was recently linked to lipid accumulation associated with increased scavenger receptor A expression89 and LXR-a mediated CCR7 down regulation 90. Norian et al. linked TIDC dysfunction to increased L-arginine metabolism in a spontaneous model of mammary carcinoma91. More importantly, Zhang et al. linked the reduced B16 melanoma TIDC functionality to decreased metabolism resulting from increased SOCS3-pyruvate kinase M2 interactions92. This observation and those in other tumor models clearly exemplify that the focus on basic immunological assays and parameters has become too restricted to determine the mechanisms of TIDC dysfunction. For a full appreciation of the developmental and functional defects in TIDC research approaches will have to incorporate disciplines beyond classical immunology.

Scientific and therapeutic considerations Mouse models have been extensively used to test topical therapeutic therapies. Com- parable to human melanoma, injections with GM-CSF, IFNa, Imiquimod, or BCG have shown various degree of clinical success in mice5, 93-96. In many of these approaches either increased numbers of DC or enhanced DCs maturation was observed in the tumor or tumor draining LN93-96 . In addition, other purified TLR ligands including poly(I:C), CpG, LPS, with our without additional immune-interfering therapies have been used success- fully97-99. Intratumoral administration of crude bacterial products, cytokines and stimulatory molecules expressed by viral vectors, microspheres or nanoparticles are well established in mouse models but have not been translated into the human system5, 100, 101. While all these therapies were suggested to target TIDC or support TIDC functions, it is likely these approaches only partly activated TIDC as some targeted specific DC populations that are absent or poorly represented in the tumor or receptors that are poorly expressed in TIDC or rendered non-functional by the tumor. In those cases, it is more likely that other cells in the tumor environment are stimulated in a manner that promotes a DC activating/

55 restoring microenvironment.

In order to improve the clinical relevance and translational potential of mouse melanoma models for the design, optimization, and identification of novel therapeutic interventions that target TIDC either directly or indirectly we will have to overcome several hurdles. The further identification and characterization of human TIDC will be critical to identify and validate the best mouse models for each type of study. Eventually, the panel of specific markers used in both human and mouse DC studies must be standardized, even as investigators continue to discover new markers and DC populations32. Furthermore, optimization and standardization of protocols for TIDC isolation and functional assessments will be essential for study-to-study comparisons and extrapolation of data between species and laboratories.

However, the greatest gain may be made by increased collaboration between different research disciplines that can provide better mouse models such as humanized mice for xenograft transplantation studies, GEMMs with TIDC patterns that resemble human TIDC profiles at different stages of disease, and new analytical platforms for extended TIDC analyses.

Although it is unlikely that mouse melanoma models will ever completely recapture the complexity of human melanoma in clinical situations, we have currently only scratched the surface of the mouse model potential in the analysis of TIDC dysfunction and therapy. Combining and integrating current models and standardizing analysis methods and expanding the disciplines of research will be instrumental to significantly improving the clinical relevance of mouse models and the identification of novel therapeutic targets.

56 Acknowledgments This work is supported by NIH grant CA138617 (NCI) and AI079545 (NIAID) to EMJ.

Conflict of Interest The authors have no conflict of interest.

Ethical Statement All animal experiments were performed in strict accordance with animal protocols approved by the Institutional IACUC at CCHMC and LIAI that operate according the guidelines by the Association for Assessment and Accreditation of Laboratory Animal Care International and the recommendations in the Care and Use of Laboratory Animals of the National Institute of Health.

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65 Chapter 3: Dendritic cells in systemic lupus erythematosus: from pathogenic players to therapeutic tools*

*This is an open-access article reprinted here under the terms of the Creative Commons Attribution License, originally published 2016, not available in Pubmed at the time this dissertation was completed: Dendritic cells in systemic lupus erythematosus: from pathogenic players to therapeutic tools. Klarquist J, Zhou Z, Shen N, and Janssen EM. Mediators of Inflammation. Volume 2016 (2016), Article ID 5045248.

66 Abstract

System lupus erythematosus (SLE) is a multifactorial systemic autoimmune disease with a wide variety of presenting features. SLE is believed to result from dysregulated immune responses, loss of tolerance of CD4 T cells and B cells to ubiquitous self antigens, the subsequent production anti-nuclear and other auto-reactive antibodies. Recent research has associated lupus development with changes in the dendritic cell (DC) compartment, including altered DC subset frequency and localization, over-activation of mDCs and pDCs, as well as functional defects in DCs. Here we discuss the current knowledge on the role of DC dysfunction in SLE pathogenesis, with the focus on DCs as targets for interventional therapies.

Introduction Systemic Lupus Erythematosus is a chronic autoimmune inflammatory disease that affects multiple organ systems, prototypically characterized by high levels of circulating autoantibodies and glomerulonephritis. Clinical symptoms also encompass musculoskeletal, dermatological, neuropsychiatric, pulmonary, gastrointestinal, cardiac, vascular, endocrine and hematologic manifestations. The reported incidence of SLE nearly tripled over the last 40 years due to improved detection of mild disease1, but SLE prevalence estimates still vary considerably, ranging from 10 to 150 cases per 100,000, depending on geography, race and gender2-5. In the United States, the prevalence of SLE is higher among Asians, African Americans, African Caribbeans, and Hispanic Americans compared with Caucasians 6-9. Similarly, in European countries SLE prevalence is higher among people of Asian and African descent5-9. Interestingly, SLE is reported infrequently in Africa10. Mortality rates are relatively low, at 10-50 per 10,000,000 of the general population and show correlation with renal and cardiovascular manifestations as well as infec- tion11. Importantly, patients commonly experience profound fatigue and joint pain, and a decreased quality of life12-15.

67 The precise etiology of SLE remains unclear, and likely varies, considering its diverse clinical manifestations. Nevertheless, SLE is believed to result from dysregulated immune responses, loss of tolerance of CD4 T cells and B cells to ubiquitous self antigens, and the subsequent production anti-nuclear and other auto-reactive antibodies. This dysregulation is associated with high serum levels of type I IFN, observed in greater than 70% of patients16,17. Current “standard of care” treatments encompass high-dose corticosteroids, anti-malarials, and immunosuppressive drugs that are associated with significant adverse side effects. As these treatments suppress symptoms and do not cure the disease, new therapies are needed.

Contemporary treatment strategies have been shifting emphasis toward the identification of immunological processes, both soluble and cellular, in order to redirect aberrant immune responses. Dendritic cells have recently been recognized as important players in the induction and progression of autoimmune diseases, including SLE18. Human and mouse studies have associated lupus development with altered DC subset frequency and localization, over-activation of mDCs or pDCs, and functional defects in DCs19,20.

However, full dissection of the relative contribution of the causes and the consequences of the dysfunctionality in the different DC subpopulations is needed to understand the processes that govern SLE development, progression, remission and relapses, in order to design interventional treatments that have the potential to redirect the immune system and eventually lead to a cure for this disease.

DC populations in humans DCs are a heterogenous population of professional antigen presenting cells, which bridge innate and adaptive immunity. In the absence of exogenous triggers, DCs contribute to

68 the clearance of dying cells and the maintenance of tolerance. During infection, or in the context of autoimmunity, however, DCs play a pivotal role in the activation of CD4 and CD8 T cells. DCs were initially identified by Ralph Steinman and lack typical lineage markers for T cells (CD3) B cells (CD20) and NK cells (CD56) while expressing high levels of MHC class II21,22. Within this population comparative studies have identified a small number of subsets that have homologues in several mammalian species23,24.

Myeloid DCs: BDCA1+ DCs and BDCA3+ DCs Myeloid DCs are considered “conventional” or “classical” DCs and are characterized by expression of CD11c, CD11b and lack of CD14 and CD16. Within this population we currently distinguish two populations based on the expression of the marker CD1c/BDCA1 and BDCA3/CD14125.

The BDCA1+ DCs are the major myeloid DC population and are found in blood, lymphoid organs, and most tissues. BDCA1+ DCs express a wide variety of pattern recognition receptors including TRL1-8, lectins, and cytokines, allowing them responsiveness to a diverse array of environmental cues. BDCA1+ DCs are strong stimulators of naïve CD4 T cell responses, which can be shaped differently depending on which innate stimuli are present23.

The BDCA3+ DCs make up >10% of the mDCs and have been found in lymphoid and non-lymphoid tissues as well as blood and bone marrow. BDCA3+DCs express high levels of TLR3, XCR1, CLEC9 and have been shown to display an increased capacity to phagocytose dying cells and cross-present cell-associated antigens to CD8 T cells compared to other DCs subsets26-28.

Plasmacytoid DCs

69 pDCs lack the classic mDC markers CD11b and CD11c, and express high levels of CD123, CD303 (BDCA2) and CD304 (BDCA4). pDCs are know for their capacity to produce vast amounts of type I IFNs in response to viruses and/or virus-derived nucleic acids predominantly via engagement of TLR7 and TLR9. pDCs have been shown to prime CD4 T cells and cross-prime CD8 T cells, especially in the context of infection29. Several studies implicate pDCs in the induction and maintenance of tolerance through the induction of regulatory T cells (Tregs)30-32.

Monocyte-associated DCs The are currently several populations of DCs that are thought to develop from monocytes rather than common DC precursors. These cells display a variety of phenotypes and functions, but there is no consensus on their exact classification or their role in vivo.

CD14+ DCs are observed in several non-lymphoid tissues, including the skin. These cells express CD11c, but lack BDCA1 or BDCA3. The CD14+ DCs express low levels of costimulatory molecules or chemokine receptors that promote migration. While these cells have been suggested to be poor at stimulating naïve T cells, they have been found to support the formation of T follicular helper cells and to provide direct help to B cells33-36.

Inflammatory DCs (iDCs) have been suggested to originate from classic CD14+ blood monocytes under inflammatory conditions. These cells may express some of the myeloid DC markers and seem prone to produce pro-inflammatory cytokines. In vitro studies suggest that different types of inflammatory stimuli give rise to populations with distinct pro-inflammatory phenotypes. TNFa/iNOS expressing inflammatory DCs have been found in skin lesions of patients with psoriasis and atopic dermatitis 37,38.

SlanDCs encompass a subset of monocytes with high expression of MHC class II, CD16,

70 and 6-sulpho LacNAc (slan). SlanDCs were shown to express TRL7 and TLR8 and to produce IL-12, IL-23 and TNF, preferentially promoting Th1 and Th17 cell differentiation. This population has been isolated from the inflamed skin of psoriatic patients and SLE patients with cutaneous lupus, the colon and draining lymph nodes of patients with inflammatory bowel diseases, as well as CSF samples and inflammatory brain lesions of patients with MS39-42. Interestingly, SlanDC infiltration in tumors is associated with tolerance and poor prognosis, indicating either diversity within the slanDC population or heterogeneity in its function.

Tissue DCs Non-lymphoid tissue resident DCs are present in most tissues in steady state and have been associated initially with induction of tolerance to self antigens22-24,43-45. These cells migrate at a very low rate to the draining LN under steady state conditions, but show significant increased migration under inflammatory conditions. Several studies have identified networks of tissue resident DCs in the skin, lung, gut, and liver46,47. Each of these networks consists of several subpopulations with different capacities for phagocytosis, antigen processing and presentation, migration, and the type of immune response they promote. Due to accessibility, skin DCs, especially Langerhans cells (LC), have been the most studied tissue-DC in the context of SLE.

DC activation of T cells One of the defining features of DCs is the expression of class I and class II major histocompatibility proteins and the processing and presentation of peptide antigens to T cells. DCs predominantly present self-antigens in low quantities resulting in immunologic tolerance. Once activated, however, DCs mature in a process that usually involves migration to a draining lymph node and the priming of T cells48-50. The factors governing the functional result of T cell priming are multifactorial, including the relative concentration of sur-

71 face peptide/MHC, costimulatory molecule expression, and cytokine release. Ultimately, the combination of these signals will result in either T cell anergy, deletion, or activation, proliferation and differentiation51-53.

A wide variety of cell surface costimulatory proteins expressed by DCs can signal both activation (41-BB, CD40, CD70, CD80, CD83, CD86, GITRL, ICOSL, LTBR, OX40L) and inhibition (PDL1, PDL2) of an engaged T cell( reviewed in 54,55). In addition, secretion of pro- and anti-inflammatory cytokines by DCs contributes to the outcome of T cell priming. DCs can produce a wide variety of cytokines; which cytokines are produced depends upon environmental signals as well as upon the DC subtype. Cytokine production is driven by input from paracrine and autocrine cytokine signaling, as well as input from innate pattern recognition receptors (PRRs) including toll-like receptors (TLRs). The combination of these signals not only influences whether a T cell becomes activated, but also plays a key role in directing T cell differentiation toward various effector fates.

3. Role of DCs in SLE development and progression Although it is not certain how immunological tolerance is broken in SLE, DCs are thought to play key roles56. Perhaps the most prominent model proposes that the initial injury is due to a build up of dying cells, a result of either dysregulated apoptosis or insufficient clearance of dying cells by DCs and other phagocytes57-59. Indeed, high levels of apoptotic cells are found in SLE patient serum, germinal centers, and in inflamed tissues, such as the skin and kidney60,61. Mounting evidence indicates that self RNA and DNA from these dying cells induces the unremitting output of type I IFN by pDCs62 via engagement of TLR9 or TLR763,64, and potentially via other cytosolic nucleotide sensing pathways such as RIG-I/IPS1 and STING (TMEM173)65-67. Type I IFNs produced by DCs promote their own activation and maturation in an autocrine manner, including increased IFN output and increased surface expression of CD80, CD86 and MHC class II, making them better

72 at activating T cells62,68-70. Furthermore, type I IFNs directly promote B cell activation, antibody production, and T cell survival and expansion71-73. Altogether, these data suggest that DCs are key players in SLE pathogenesis, and point to DCs as promising therapeutic targets.

4. DC abnormalities in SLE patients. Several reports indicate that the frequency, composition, and phenotype of DCs in SLE patients differs from that of healthy individuals (see tables 1 and 2). However, it is difficult to compare results between laboratories, given differences in disease activity and manifestations, the effect of various drug treatments on DC development and phenotype, and the variations in analytical parameters.

Studies have shown reduced 74-81, normal80,82 and increased83 levels of CD11c+ mDC frequencies in PBMC from lupus patients compared to healthy controls. Similarly, pDC levels were found to be unaffected, reduced74-78,84,85, or increased79,86. Decreased frequencies of pDCs or mDCs were most often associated with active disease and to a lesser degree with non-active disease75. Interestingly, studies showing peripheral pDCs decreases observed

73 a concomitant infiltration of pDCs in nephritic kidneys, suggesting that active pDCs may have migrated to the sites of inflammation78,82. Similarly, Fiore et al. showed that besides pDCs, BDCA1+ DCs and BDCA3+ DCs were increased in the renal tubulointerstitium of patients with lupus nephritis78. Increased numbers of pDCs and inflammatory/slanDCs are also found in cutaneous lesions of lupus patients, further suggesting migration of DCs to target organs87,88. It is likely that DCs that reside in or have been recruited into the affected tissues will display different characteristics than those circulating in the periphery. Consequently, these populations should be included in further assessments in order to understand their contribution to disease pathogenesis and allow for a rational design of DC-targeting therapeutics.

SLE-associated dysfunction in primary DCs The few published maturation and functionality studies with primary human DCs have given conflicting results. Earlier reports indicated that DC from SLE patients have normal or even reduced levels of costimulatory molecules and are poor stimulators of allogeneic T cells in mixed lymphocyte reactions. Scheinecker et al. reported that in SLE patients B7+

74 and CD40+ DCs were reduced and that DC-enriched APC from SLE patients displayed a diminished T cell-stimulatory capacity in both the allogeneic and the antigen-specific MLR, as compared with healthy individuals76. On the other hand, Mozaffarian et al. showed increased CD80/CD86 and reduced PDL-1 expression on mDC during disease flares and an upregulation of PDL-1 during remission89. Similarly, Gerl et al.81 published that monocytes and mDCs from SLE patients expressed higher levels of CD86 and BAFF, but not CD83 and CD40. Upon further assessment of their migratory capacity, they found that pDCs and mDCs from SLE patients had normal expression of CCR1, CCR5 and CCR7 but reduced expression of the chemokine receptor ChemR23 (CMKLR1). However, pDCs from the SLE patients showed an increased basal and CCL19-specific migration in vitro.

Assessment of peripheral monocytes, total DCs, BDCA1+ DCs and CD14-/lowCD16+ DCs by Henriques et al. showed that a higher percentage of SLE monocytes and CD14-/ lowCD16+ DCs produced pro-inflammatory cytokines as well a higher amount ofcyto- kines produced per cell, particularly in active disease. Data from Kwok et al.90 seemed to indicate that type I IFN production by pDC upon TLR9 engagement was diminished in SLE patients, leading them to hypothesize that the persistent presence of endogenous IFNa-inducing factors induces TLR tolerance in pDCs of SLE patients, resulting in impaired production of IFNa. Studies by Jin et al.79,91 also suggested deficiencies in TLR9 recruitment/signaling and production of pro-inflammatory cytokines in pDCs from SLE patients, however, they also showed that SLE pDC had an increased ability to stimulate T cells. Importantly, while pDCs from healthy donors induced suppressive T regulatory cell features (Foxp3 expression) in T cell cultures upon addition of apoptotic PMNs, SLE pDCs failed to do so.

These studies indicate that SLE is associated with phenotypic and functional changes in DCs and that these changes can affect different aspects of the DCs’ functional program

75 in distinct and divergent ways.

SLE-associated dysfunction in in vitro generated DCs Due to the paucity of DCs in leukopenic SLE patients, many studies have used in vitro generated monocyte-derived DCs (moDCs) to gain insight in DC generation, phenotype and function in the context of SLE.

Initial studies suggest that monocyte-derived DCs had a reduced pro-inflammatory and T cell stimulatory acitivty92 while later studies suggested accelerated differentiation and maturation concomitant with increased activity to maturation stimuli93. MoDCs from SLE patients expressed higher levels of HLA-DR and activating FcγRs, but decreased expression of inhibitory FcγR and expression levels correlated with disease severity92,94. In addition, moDCs spontaneously overexpressed activating costimulatory molecules including CD40, CD80, CD86, and showed increased production of stimulatory cytokines (IL-6, IL-8, BAFF/BlyS), eventually resulting in an increased capacity to activate T cells in an MLR93,95. Similarly, Nie et al.96 demonstrated substantial phenotypic and functional aberrations in DCs generated from (Flt3)-ligand and GM-CSF/IL-4 stimulated bone marrow aspirates. Both immature and mature DCs from SLE donors expressed higher levels of CCR7, CD40 and CD86 and induced stronger T-cell proliferation.

Nature versus nurture Drawing causative relationships between DCs frequencies, maturation status, functionality, and disease is complex as it is not clear whether aberrations in DC frequency and functionality are the driver or a result of the disease. It is likely that genetic alterations in DCs predispose for the development of accelerated maturation and abnormal behavior. Evidence for this intrinsic defect is supported by the observations that moDCs from SLE patients, either generated from PBMC or bone marrow, display accelerated maturation

76 and increased pro-inflammatory status compared to moDC from healthy donors. On the other hand, serum of SLE patients has been shown to contain pro- and anti-inflammatory stimuli like type I IFN, type I IFN-inducing factors, and IL-10 that alter DC differentiation, maturation, and functionality, even in DCs from healthy donors97-99. This raises the question whether the aberrant behavior of DCs in SLE patients is a result from an intrinsic defect, a result of their development in an inflammatory environment, or a combination of these two97. To further confound the interpretation of human clinical data, various classic SLE treatments, including anti-malarials, corticosteroids, and immunosuppressive drugs significantly affect DC number, maturity and functionality100.

Mouse models to dissect the role of DCs in SLE pathogenesis The availability of mouse models provides an exciting opportunity to gain cellular and molecular insight in the role of different DC populations in the development and progression of SLE. There are a variety of spontaneous models, including the F1 hybrid between the New Zealand Black (NZB) and New Zealand White (NZW) strains (NZB/W F1) and its derivatives, the MRL/lpr, and BXSB/Yaa strains, as well as inducible models such as the pristane-induced model and chronic graft-versus-host-disease models (cGVHD)101-104. In recent years the number of models has been expanded with genetically modified mice, targeted in genes that can promote, resist, and modify lupus susceptibility105,106. All of these models display they own variation of lupus-like disease reminiscent of symptoms observed in patients, including, autoantibody production, lymphoid activation and hyper- plasia, lupus nephritis, and skin manifestations. Although all of these models have been instrumental in the identification of several main concepts in this diseases, none of the models can completely recapitulate the complexity and variety of human disease. How- ever, careful pairing of models with patient groups with the similar clinical manifestations can ensure the translational relevance of these preclinical models.

77 Mouse models have several advantages, (i) the relative homology between human and mouse DCs, (ii) the opportunity to genetically or pharmacologically eliminate specific DC populations during specific stages of disease, (iii) access to all target tissues for the assessment of tissue associated or infiltrating DCs, (iv) the opportunity to assess the effects of common treatments on thee parameters, as well as (v) a plethora of biological and pharmacological tools to dissect the relative contribution of specific molecules and mediators to the development and progression of disease.

Similarities between mouse and human DCs Recent genomic, proteomic and functional analyses of mouse and human DCs have identified high homology between the most present highest frequent DC populations107. Like in human DCs, mouse DCs lineages encompass conventional DCs, pDCs, CD14+ DCs, tissue DCs and monocyte derived/inflammatory DCs24,108. Conventional mouse DCs encompass three main subpopulations which are found in circulation as well as in secondary lymphoid organs109: (1) Cd11chighMHCII+Cd8α-33D1+- Sirpα+Cd11b+ (Cd11b DCs), which express most TLRs except Tlr3, display a preference for activation of CD4 T cells, and have high homology with the human BDCA1+ DCs; (2) Cd11chighMHCII+Cd8α+CD205+Sirpα-Cd11b- (Cd8α DCs), which express Xcl1, CD141, Clec9A and express mRNAs coding for most TLRs except Tlr5 and Tlr7, and are characterized by high Tlr3 expression and (3) Cd11chighMHCII+ cells that lack Cd8α, Cd4 and Cd11b (generally termed “double” or “triple” negative) DCs that, like CD8a DC, express Xcl1, CD141, Clec9A and Tlr3110-113. These latter two populations have a high capacity to phagocytose dying cells and cross-present cell-associated or particulate antigens to CD8 T cells. Based on their genomic and functional analysis these two populations are considered to be homologues to the human BDCA3+ DCs.

Like human pDCs, mouse pDCs produce vast amounts of type I IFN in response to virus-

78 es via TRL7/9 mediated pathways. Compared to their human counterparts, mouse pDCs show relatively poor capacity for phagocytosis and antigen presentation. However, both populations have been implied in the maintenance of peripheral tolerance32,114-116.

Various types of inflammatory and monocyte-derived DCs have been identified in mice as well. Tissue infiltrating CD14+ DC-like cells have been found under inflammatory conditions 117,118. Inflammatory DCs have been shown to arise after a wide variety of immunological insults, including pathogenic infection, experimental sterile inflammation, and models of inflammatory diseases such as RA, colitis experimental autoimmune encephalomyelitis and allergic asthma (reviewed in119).

The role of DCs in mouse SLE models Recent studies indicate an important role for DCs in the development and progression of SLE-like disease in mouse models. Similar to human disease, DCs from lupus-prone mice display a range of alterations in their numbers and their functionality120-123. Splenic DCs from NZB/W F1 showed enhanced maturation and a stronger ability to attract B cells and present antigens to T cells than DCs from control mice. pDCs from SLE-prone mice showed increased type I IFN producing capacity upon TLR9 stimulation and increased cell survival compared to pDCs from C57BL/6 mice. Enhanced mDC and pDC activity has also been reported in male BXSB/Mp mice that express an extra copy of Tlr7 on the Y chromosome.

Importantly, depletion studies have now shown causal relationships between DC subsets and disease manifestations. Constitutive depletion of pDCs in lupus prone mice either through genetic ablation of IRF8, a transcription factor required for pDC and Cd8aDC development, or by diphtheria toxin treatment of mice expressing the diphtheria toxin receptor on pDCs resulted in markedly reduced type I IFN production, a reduced IFN signa-

79 ture, reduced auto-antibody production and reduction in the severity of kidney pathology glomerulonephritis124-126. Importantly, transient pDC depletion during the early stages of disease was sufficient to significantly alter the course of the disease, suggesting a more prominent role for pDCs in the induction of the disease than in disease pathogenesis at later stages of disease125. Diphtheria toxin treatment of Cd11c-DTA MLR.Faslpr mice resulted in reduced T cell differentiation, plasma blast numbers and autoantibody levels. Interestingly, these mice developed interstitial kidney infiltrates but failed to progress to glomerular or interstitial nephritis, suggesting that DCs play a role in the development of tissue damage127. In line with this observation, this group also showed that Cd11c depletion, but not LC depletion, resulted in significantly reduced dermatitis, demonstrating that DCs other than LCs control dermatitis in this model127.

Besides the opportunity to assess the relative and temporal contribution of different DC populations to the development of specific disease manifestations, mouse models also allow for the identification of specific processes in DCs which affect disease development. Targeted deletion of regulatory molecules associated with SLE susceptibility in humans, including Shp1, A20, Blimp-1, Lyn or Eat-2, specifically in Cd11c+ cells resulted in increased DC activity and development of inflammatory and autoimmune phenotypes characterized by the production of auto-reactive antibodies, and several manifestations of SLE, including severe glomerulonephritis128-132.

Together these observations indicate that mouse models provide a useful platform for the identification, dissection and targeting of DC intrinsic and extrinsic processes that facilitate the development, progression, and possibly a cure for SLE.

DC targeted therapies for SLE Based on the general role of DC in the regulation of peripheral tolerance to self antigens,

80 the dysregulation of DCs observed in SLE, and the emerging evidence of the contribution of DCs in the initiation and perpetuation of SLE pathogenesis, is it not surprising that DC-targeting therapeutic strategies have become a topic of interest. Especially strategies that would promote self-antigen presentation in a tolerogenic context could be promising for the generation of an abortive or suppressive environment for the auto-reactive T and B cells and restoration of peripheral tolerance133,134. In recent years several ex vivo models have been established for the generation of human DCs with stable tolerogenic functions (reviewed in135 ). Generally, these resulting tolerogenic monocyte-derived DCs express low levels of positive costimulatory molecules and high levels of immune suppressive mediators (PDL-1, IL-10, etc.). Upon pulsing with specific antigens these DCs are anticipated to promote antigen-specific tolerance via the induction of T cell anergy, T cell apoptosis, skewing of T cell phenotypes to more Th2 or regulatory phenotypes, as well as the expansion of regulatory T cells.

Tolerogenic DC therapy is still in its infancy and little data is available on its in vivo potential. The first studies showed that transfer of antigen-loaded tolerogenic DCs could induce antigen-specific regulatory CD8 T cells and inhibit effector functions in antigen-specific CD8 T cells136,137. A clinical trial in patients with type I diabetes using DCs treated with anti-sense oligonucleotides to silence costimulatory molecules was less successful, and although the treatment was well tolerated, only very limited tolerance outcomes were re- ported138. A subsequent trial in T1D patients indicated that transfer of IL-10 and TFGb1 generated tolerogenic DCs pulsed with pancreatic islet cells induced antigen-specific T cell hyporesponsiveness and was associated with better glycemic control139. Similarly, transfer of a single dose of tolerogenic DCs –derived by ex vivo treatment with NF-kB inhibitors– into patients with active RA resulted in a modest improvement in disease activity 3 and 6 months after injection140. Currently there are several trials addressing the therapeutic potential of tolerogenic DCs in Multiple Sclerosis, Rheumatoid Arthritis, Type

81 I Diabetes, and allergic asthma141.

To date no tolerogenic DC transfer studies have been published in preclinical models or SLE patients. However, in vitro data indicate that tolerogenic DCs can be generated from SLE patients83,142,143, and that apoptotic cells can be used as source to load the DCs with auto-antigens143. The insight obtained from currently ongoing tolerogenic DC treatment strategies in other chronic inflammatory diseases will help to identify critical parameters such as dose, route, and duration of treatment leading to the most efficacious outcome 144,145. However, a better understanding of the role of DCs in disease pathogenesis is critically needed in order to select the type of tolerogenic DC that can successfully counteract the dysfunctional adaptive immune responses that maintain the disease.

Acknowledgements This work was supported in part by the Lupus Research Institute (to E.M.J), NCI grant CA138617 (to E.M.J), Charlotte Schmidlapp Award (to E.M.J.), the Albert J. Ryan Fellowship (to J.K.), the National Basic Research Program of China (973 program; 2014CB541902, to N.S.), the National Natural Science Foundation of China (no.81230072; no.81025016; no.81401331, to N.S.), the Program of the Shanghai Commission of Science and Tech- nology (# 12JC1406000 to N.S.), and the Special Fund for Public Benefit Research from the Ministry of Health (no. 201202008, to N.S.).

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Chapter 4: The bm12 inducible model of systemic lupus erythematosus (SLE) in C57BL/6 mice*

*This is reprinted here with permission. The article was originally published in 2015: The bm12 Inducible Model of Systemic Lupus Erythematosus (SLE) in C57BL/6 Mice. Klarquist J and Janssen EM. J Vis Exp. 2015 Nov 1;(105).

95 SHORT ABSTRACT: The transfer of bm12 lymphocytes into a C57BL/6 recipient is an established model of systemic lupus erythematosus. Here we describe how to initiate disease using this model and how to characterize T follicular helper cells, germinal center B cells and plasma cells by flow cytometry.

LONG ABSTRACT:

Systemic lupus erythematosus (SLE) is an autoimmune disease with diverse clinical and immunological manifestations. Several spontaneous and inducible animal models mirror common components of human disease, including the bm12 transfer model. Upon transfer of bm12 splenocytes or purified CD4 T cells, C57BL/6 mice rapidly develop large frequencies of T follicular helper cells (Tfh), germinal center (GC) B cells, and plasma cells followed by high levels of circulating anti-nuclear antibodies. Since this model utilizes mice on a pure C57BL/6 background, researchers can quickly and easily study disease progression in transgenic or knockout mouse strains in a relatively short period of time. Here we describe protocols for the induction of the model and the quantitation Tfh, GC B cells, and plasma cells by multi-color flow cytometry. Importantly, these protocols can also be used to characterize disease in most mouse models of SLE and identify Tfh, GC B cells, and plasma cells in other disease models.

INTRODUCTION: Systemic lupus erythematosus (SLE) is a complex autoimmune disease characterized prototypically by anti-nuclear antibody (ANA) production and glomerulonephritis. Numer- ous other sequelae, including dermal, cardio-pulmonary, and hepatic lesions are associated with disease in some individuals. Prevalence estimates in the US vary widely, from 150,000-1,500,000,1,2 with particularly high incidence in women and minorities3. Although the etiology of SLE has been difficult to discern, it is thought to arise from the interplay

96 of various genetic and environmental factors, which culminate in systemic autoimmunity.

Numerous animal models have been employed to study factors leading to disease onset and progression. Classic mouse models of SLE include genetically predisposed mouse strains including the NZB x NZW F1 model and its NZM derivatives, the MLR/lpr strain, and the BXSB/Yaa strain, and inducible systems, such as the pristane and chronic graft- versus-host disease (cGVHD) models4. Early reports of autoantibody production in GVHD models used various mouse strains or hamster strains for parent into F1 transfers5–8; more common methods used to study lupus-like disease currently include the DBA/2 parent→(C57BL/6 x DBA/2) F1, and the bm12 transfer model described here. Each model has its own caveats, but they generally share a common set of features that correlate with clinical features of human disease. The most often reported parameters in mouse models include splenomegaly, lymphadenopathy, nephritis, ANA production, and at the cellular level, the expansion of T follicular helper cells (Tfh), germinal center (GC) B cells, and plasma cells.

The inducible bm12 model is achieved by the adoptive transfer of lymphocytes from I-Abm12 B6(C)-H2-Ab1bm12/KhEgJ (bm12) mice, a strain identical to C57BL/6 except for 3 amino acid substitutions on MHC class II, into I-Ab C57BL/6 (B6) mice. Alloactivation of donor CD4 T cells by recipient APCs leads to cGVHD with symptoms closely resembling SLE. Specifically, these include expansion of donor-derived Tfh, expansion of recipient-derived GC B cells and plasma cells, and production of ANAs including anti-dsDNA, anti-ssDNA, anti-chromatin, and anti-RBC antibodies9. Over time, recipient mice develop glomerulonephritis associated with IgG deposits in the glomerular, interstitial, and vascular regions of the kidneys10. We have recently shown that, similar to human disease, there is also a critical role for type I IFN in this model11. Notably, the defining criteria for human SLE include the development of nephritis compatible with SLE in the presence of anti-dsDNA

97 antibodies12, both of which are prominent features of this mouse model.

There are several advantages of the bm12 model over the spontaneous models. Clas- sic models that develop SLE-like signs spontaneously rely upon either hybrid mouse strains, inbred mouse strains not on the B6 background, or large genetic loci on the B6 background, which make crossing to knockout or otherwise genetically modified mice difficult and time consuming. With the bm12 inducible model, genetically modified mice can serve as either the donor or recipient, allowing more rapid identification of the cellular compartment in which particular genes may be important for disease. Furthermore, disease development in the bm12 model is much faster, requiring only 2 weeks until the appearance of ANAs, compared to several months for most spontaneous models. More- over, in contrast to the spontaneous models that develop disease at different time points, the disease onset and progression in the bm12→B6 model is highly synchronized. This allows for the generation of appropriately sized cohorts that can be used for interventional or therapeutic strategies at any stage of disease development.

What follows is a detailed protocol for initiating SLE-like autoimmunity by the adoptive transfer of bm12 lymphocytes into C57BL/6 mice, or genetic variants on the B6 background. Additionally, we describe a flow cytometric staining protocol for enumerating Tfh, GC B cells, and plasma cells—cell types associated with human disease. Importantly, these protocols can also be used to characterize disease in most mouse models of SLE and identify Tfh, GC B cells and plasma cells in other disease models.

PROTOCOL:

Animal work was performed under specific pathogen-free conditions in accordance with

98 guidelines set by the Association for Assessment and Accreditation of Laboratory Animal Care International and our Institutional Animal Care and Use Committee (IACUC).

NOTE: Incorporate mice expressing a congenic marker such as CD45.1 on either donor or recipient animals if possible, because this allows for the monitoring of donor graft efficiency and specific expansion of the donor CD4 T cell population. If considering the use of otherwise genetically modified mice as donor or recipients, ensure the strain is properly backcrossed to the B6 background, or transferred cells may be rejected—this will be addressed in greater detail in the representative results and discussion sections.

NOTE: The following procedures detail volumes for harvesting 4 donor bm12 mice, which should yield enough cells to inject 12-16 mice. Six to twelve week-old bm12 mice yield roughly 100-140 million lymphocytes with approximately 25% CD4 T cells. If starting with different numbers of mice, or different mouse strains, scale volumes up or down accordingly. C57BL/6 mice generally give similar yields with closer to only 20% CD4 T cells.

NOTE: Perform all steps at room temperature and use room temperature media to avoid heat and cold shock, which can impair long-term lymphocyte viability. Perform tissue-harvesting and tissue-processing steps in a tissue culture hood using aseptic technique. All media in this protocol is IMDM with 10% heat-inactivated FBS, unless indicated otherwise, and will be simply referred to as “complete media.”

1. Novel method for genotyping bm12 mice

NOTE: A brief restriction digest-based protocol for genotyping is provided here, as a simple and inexpensive alternative to sequencing, which is currently the only published genotyping method for these mice.

1.1) Isolate genomic DNA from mouse tails. Please refer to a previous JoVE article for

99 detailed protocols on mouse tail clipping and the generation of cDNA from tail digests13.

1.2) Perform a reverse-transcriptase polymerized chain reaction (PCR)14the field of microbiology was transformed with the advent of Anton van Leeuwenhoek’s microscope, which allowed scientists to visualize prokaryotes for the first time. The development of the polymerase chain reaction (PCR to amplify a common 474 bp DNA fragment from MHC-II I-Ab and I-Abm12 using primers and thermocycling conditions listed in Table 1.

1.3) Perform restriction digest on ~7 μl of the PCR product using the enzyme PsuI, or one of its isoschizomers (BstX2I, BstYI, MflI, or XhoII), which cuts wild type I-Ab, but not I-Abm12 mutant. Follow digest protocol provided by the manufacturer, which will specify a mixture of water, buffer and enzyme, and an incubation of 5 min. to several hours at 37 °C15.

1.4) Load digest product and run on 1% polyacrylamide gel with ethidium bromide14the field of microbiology was transformed with the advent of Anton van Leeuwenhoek’s microscope, which allowed scientists to visualize prokaryotes for the first time. The development of the polymerase chain reaction (PCR for 30-45 min. at 150V—though optimal voltage and time settings will vary depending on the PCR gel apparatus used. Visualize DNA bands with a UV illuminator. Representative results are shown in Fig. 1.

2. Harvesting donor cells

2.1) Sacrifice donor mice using Institutional Animal Care and Use Committee (IACUC)-ap-

Figure 1. Representative bm12 genotyping results. To identify mice homozygous for I-Abm12/bm12, tail DNA was screened for bm12 by PCR/restriction digest geno-

typing (Step 1). Homozygous wild type (I-Ab/b) DNA yields WT bm12 bm12+/− two bands at 227 and 247 bp (visualized as one thick 500− band at ~250 bp); homozygous bm12 (I-Abm12/bm12) DNA yields one band at 474 bp; and heterozygous (I-Ab- 200− m12/b) DNA yields two bands at ~250 and 474 bp.

100

Figure 1 proved primary and secondary euthanasia methods. For example, euthanize mice by asphyxiation with CO2 followed by cervical dislocation.

2.2) Using aseptic technique, harvest spleens and lymph nodes (superficial cervical, mandibular, brachial, axillary, mesenteric, and inguinal) into 15 ml tubes containing 10 ml complete media as in11-13.

NOTE: Refer to previous reports for detailed lymph node dissection protocols16–18we present methods for adoptive transfer of labeled T cells, isolation of lymph nodes, and imaging motility of CD4+ T cells in the explanted lymph node as first described in 2002 (2. This model is also successful using only mouse splenocytes for transfer, but the addition of lymph nodes significantly reduces the required number of donor mice.

2.3) Generate a single-cell suspension by mashing lymphoid tissues collected in step 2.2 through 70 μm cell strainers using the plunger from a syringe. For better yields, do not overload strainers—use ~6 strainers for every 4 mice processed, and rinse strainers frequently while processing. Combine tissues from 4 mice into two 50 ml conical tubes, then centrifuge cells for 5 minutes at 400 x g and decant supernatant.

2.4) Resuspend cells from both conical tubes in 50 ml complete media and transfer to new conical tube. Keep this tube at room temperature.

NOTE: Fat adheres to the sides of the tube, and if the tube is not replaced, final cellular yields can suffer.

3. Donor cell counting

NOTE: To preserve the highest viability, red blood cell (RBC) lysis of the entire sample is not recommended.

3.1) Mix single cell suspension from step 2.4 well, remove 1 ml and transfer it to a separate 50 ml conical. Set aside remaining, untouched cells (49 ml) at room temperature

101 while counting.

3.2) Add 3 ml of an ammonium chloride-based red blood cell lysis buffer to the 1 ml donor cell sample. Mix gently for 1 min. by rocking, then fill to 50 ml with complete media, and centrifuge for 5 min. at 400 x g and decant supernatant.

3.3) Resuspend RBC-lysed cells in 10 ml complete media and count (e.g. with trypan blue using a hemocytometer). Multiply result by 49—this is the total number of cells remaining in the non-lysed sample that was set aside. Discard RBC-lysed cells.

4. Donor cell labeling and/or CD4 T cell purification

4.1) If desired, purify CD4 T cells at this stage, though this is not necessary. Additionally, if desired, label cells with CFSE, as in19, or other cell tracking dyes, an example of which is shown in Fig. 4 of the representative results section.

NOTE: For CD4 T cell purification, negative magnetic selection is recommended, as it can achieve high purity and leaves cells untouched with high viability as described in20. It is important that endotoxin-free buffers are used; therefore, instead of BSA, make separation buffer with 2% FBS and the recommended concentration of EDTA.

5. Injection of donor bm12 cells

5.1) After counting donor lymphocytes in step 3 (and purified or labeled as in step 4, as desired), centrifuge cells for 5 minutes at 400 x g. Decant supernatant and resuspend cells in PBS at 120 million lymphocytes per ml (or 30 million purified CD4 T cells per ml). Transfer cells to a sterile 5 ml round-bottom tube, or other sterile tube that easily accommodates a 1 ml syringe fitted with a 27.5 G x 13 mm needle.

102 5.2) Prior to injection, set aside a small sample of donor cells from step 5.1 at 4 °C for flow staining to determine the percentage of CD4 T cells within donor samples. Stain these samples as described in Step 8 using the minimal antibody panel (Table 2).

NOTE: If cells from different mouse strains are used as separate donors, this is an important consideration, and if CD4 T cell percentages vary substantially, purification may be required.

5.3) Mix cells gently, but thoroughly. This can be done by pipetting cells up and down using a 1 ml syringe without an attached needle. After mixing, draw cells into the 1 ml syringe. Attach needle after removing any air bubbles. Keeping the needle off while priming the syringe helps maintain cell viability.

5.4) Inject 250 μl per mouse (which is equal to 30 million lymphocytes, or 7.5 million purified CD4 T cells per mouse) intraperitoneally, as described in21two-handed, and restraint with specially designed restraint objects will be illustrated. Often, another part of the research or testing use of animals is the effective administration of compounds to mice and rats. Although there are a large number of possible administration routes (limited only by the size and organs of the animal.

NOTE: In experiments shown here and in our prior work11, each mouse is injected with 30 million total lymphocytes from bm12 donors, rather than the 100 million total splenocytes traditionally used. In unpublished data from our lab, no difference was observed in serum anti-dsDNA at day 14 following injections of 30 or 100 million lymphocytes per mouse. While this significantly reduces the number of mice needed for experiments, the development of nephritis with this number of cells has not been assessed.

7. Determine grafting efficiency

103 NOTE 1: This section will describe how to determine the degree of donor cell grafting in the recipient at day 3 in order to identify any mice which may have received suboptimal injections (e.g. the graft in one mouse is <10% of that seen in all other mice from the same group). These data can also help determine whether cells from a genetically modified mouse strain are rejected at later time points (for details, see representative results section, Fig. 6).

NOTE 2: This section is only possible if donors and recipients are from mice on different congenic backgrounds, e.g. when using CD45.1 bm12 donors and CD45.2 C57BL/6 recipients, or when donor cells are labeled with a cell tracking dye. Importantly, at 3 days post-injection, CD4 T cells have undergone minimal expansion (see representative results section, Fig. 4), so differences observed in the degree of grafting are due to variability in injections, not expansion.

6.1) Anesthetize mice with 4% isoflurane or other IACUC-approved method. Test rear foot reflexes to ensure mouse is properly anesthetized before proceeding to the blood draw.

6.2) Harvest 100-200 μl blood using an IACUC-approved method, such as retro-orbital puncture as in22. Collect blood into individual 0.5 ml microcentrifuge tubes containing an anti-coagulant, such as the plasma collection tubes referenced in the materials table, which contain lyophilized dipotassium EDTA. After blood collection, apply gentle pressure to the mouse eye using a sterile towel or gauze to ensure the bleeding stops, then place the mouse back in its home cage where it will remain until the final tissue harvest (Step 7).

NOTE: Do not leave mice unattended until mice have regained sufficient consciousness to maintain ventral recumbency, and do not return mice to the company of others until fully recovered.

6.3) Bring blood volume to 500 μl with 21 °C PBS and transfer to conical-bottom micro-

104 centrifuge tube, then slowly underlay 200 μl of 21 °C high density cell separation solution with a 200 μl pipet, being careful to minimize mixing between the two phases (see Mate- rials Table for recommended solutions). Centrifuge cells at 700 x g for 20 min. (20-25 °C) with centrifuge brake set to low.

6.4) Remove top layer containing lymphocytes with a 1 ml pipet and transfer to a new microcentrifuge tube containing 800 μl cold complete media. Gently vortex to mix cells. Centrifuge cells at 700 x g for 5 min. (4 °C) and decant supernatant.

6.5) Resuspend cells in 200 μl complete media, transfer to a 96-well U-bottom plate, and stain for flow cytometry as described in Step 8 using a minimal antibody panel (Table 2) to determine the relative abundance of the CD4 T cell graft as a percentage of PBMCs.

7. Final tissue harvest NOTE: The experiments described in the results section were harvested 14 days after injection of donor cells (or in some cases less time), as they focus on the initial development of Tfh cells and plasma cells; however, since this model is a chronic GVHD model of SLE, disease can be monitored at much later time points. The optimal timeframe will depend upon the research question posed in each individual experiment.

7.1) At a predetermined time point after injection of bm12 donor cells (step 5.4), sacrifice mice using an IACUC-approved method of euthanasia. Asphyxiation with CO2 followed by exsanguination is recommended. Cervical dislocation can function as a secondary method of euthanasia, but this may reduce the blood draw yield.

7.2) Wet the abdomen of the mouse lightly with a spray bottle containing 70% ethanol. Make a small, superficial incision with surgical scissors approximately 1 cm above the genitalia. Draw back the skin of the abdomen toward the sternum, being careful to keep the peritoneal fascia intact. NOTE: Diseased mice usually present with 0.5-3 ml ascites at day 14, which, although

105 it has not yet been well characterized, can be measured and analyzed as an additional disease parameter. 7.3) Fit a 5 ml syringe with an 18-gauge needle. Insert the needle into the lower right quadrant of the abdomen with the needle directed up toward the animal’s head and at 15-degree angle to the plane of the fascia. Position the needle tip near the cecum to help prevent the needle from getting clogged with intestine while aspirating ascites. 7.4) Carefully rotate the mouse on its side, then slowly draw ascites into the syringe. Once ascites has been recovered, remove the syringe and record the aspirate volume, based upon the volumetric markings on the side of the syringe. 7.5) Discharge ascites into a 5 ml round-bottom tube and store on ice for later processing. 7.6) Harvest blood via draw from the inferior vena cava (IVC) essentially as in22. Using dull forceps, gently move intestines to the left side of the mouse, uncovering the IVC. Insert a 27.5-gauge needle fitted to a 1 ml syringe into the IVC and slowly draw 400-500 μl of blood. 7.7) To minimize hemolysis, slowly inject blood into a 0.5 ml microcentrifuge serum or plasma collection tube. For later serum analysis of ANAs by ELISA, keep blood on ice. 7.8) Dissect and obtain additional relevant tissues (spleen and, if desired, lymph nodes and kidneys, particularly if collecting at later time points and glomerulonephritis will be scored). Remove spleen by gently placing the intestines back toward the right side of the animal, and pulling on the pancreas, which is the spleen’s primary connective tissue. 7.9) Remove any pancreas remaining, then weigh spleens on a high precision balance immediately after dissection, as gross splenomegaly is a commonly reported parameter in mouse models of SLE. Place lymphoid tissues into individual 1.5 ml tubes filled with 1ml complete media on ice. Fix kidneys in 10% neutral buffered formalin or snap freeze kidneys for later histology as in23. 7.10) Centrifuge blood within 2 h of collection for 3 min. at 10,000 x g (4 °C). Remove serum and store at -80 °C for later analysis of ANA by ELISA. Refer to previous reports for

106 detailed ANA ELISA protocols24,25. Store serum in multiple 10-20 μl aliquots to minimize freeze/thaw cycles, and allow a greater number of future assays. 7.11) Centrifuge ascites 400 x g for 5 min. Remove the supernatant with a 1 ml pipet and aliquot into several 0.5 ml tubes. Freeze supernatant at -80 °C for later analyses of anti-nuclear antibodies (ANAs) or other soluble inflammatory mediators. 7.12) Resuspend cellular fraction in approximately 1 ml complete media and transfer 200 μl to a 96-well U-bottom plate for flow staining (as in Step 8). 7.13) Mash each spleen through 70 μm cell strainers into separate tubes and rinse with complete media. Resuspend splenocytes with 1 ml cold RBC lysis buffer for 1 min. and mix gently by rocking. Bring volume to 10 ml with cold complete media and centrifuge for 5 minutes at 400 x g and decant supernatant.

7.14) Resuspend cell pellet in 5 ml complete media and count using a hemocytometer. Adjust volume such that 200 μl of complete media contains 1-3 million cells. Begin staining for flow cytometry Step( 8) using an extended panel (Table 2) to quantify donor CD4 T cell and recipient B cell differentiation and expansion.

NOTE: Depending upon what laser, photomultiplier tube (PMT), and filter set combinations are available, separating the T and B cell analysis panel into multiple panels may be necessary.

8. Flow staining

8.1) Transfer 1-3 million splenocytes in 200 μl complete media into individual 5 ml round-bottom tubes, or into separate wells of a 96-well U-bottom plate. NOTE: Using a 96-well plate is an efficient way to stain multiple samples, but take care to plate samples in every other well in order to prevent cross-contamination. One 96-well plate can accordingly hold 24 samples.

107 8.2) Centrifuge plate at 500 x g for 3 min., then flick supernatant from plate into appropriate (biohazard) container. 8.3) Resuspend the cell pellets with 100 μl of flow buffer (1% FBS in PBS) containing a fixable viability dye at the manufacturer’s recommended concentration and purified anti-CD16/anti-CD32 antibody cocktail at 1 μg/ml. Incubate for 10 minutes (20-25 °C), then add 100 μl cold complete media to quench viability dye. NOTE: Splenocytes from diseased mice usually contain relatively high numbers of dead or dying cells; therefore, the inclusion of a viability dye is recommended to avoid non-specific antibody labeling of dying cells, resulting in cleaner, more reliable data. Similarly, the anti-CD16/anti-CD32 cocktail is included to block non-specific fluorescently-labeled antibody binding by Fc receptors. 8.4) Centrifuge plate at 500 x g for 3 min., then flick supernatant from plate into biohazard container. Resuspend cells in 200 μl flow buffer. Centrifuge plate at 500 x g for 3 min., then flick supernatant from plate into biohazard container. 8.5) Resuspend cells in 50 μl flow buffer containing antibody cocktail Table( 2). Incubate for 20 minutes (4 °C), then add 150 μl flow buffer. Repeat wash step 8.4. 8.6) Resuspend cells with 100 μl 2% paraformaldehyde in PBS. Incubate for 30 minutes (4 °C), then add 100 μl flow buffer. Centrifuge plate at 500 x g for 3 min., then flick supernatant from plate into biohazard container. 8.7) Resuspend in 200 μl flow buffer, transfer to flow tube inserts or standard flow tubes, add an additional 100-200 μl flow buffer, and store at 4 °C in the dark until acquiring on flow cytometer. 8.8) Acquire on a flow cytometer equipped with the appropriate lasers and PMTs for the chosen antibody panels within several days of staining. Record forward scatter width and/ or height in addition to forward scatter area, side scatter area, and area of the fluorescent parameters utilized. For reliable results, acquire ≥1,000 donor cells in each WT sample, or an equivalent number of total lymphocytes in genetically modified or otherwise ma-

108 nipulated mice that show minimal expansion of donor cells, where collection of so many events may not be feasible. NOTE: Flow cytometry analyses are described in detail in the representative results section (Fig. 3-6).

REPRESENTATIVE RESULTS: Diseased mice develop splenomegaly in as little as 14 days, exhibiting spleens 2-3 times the size of healthy mice in terms of mass and cellularity (Fig. 2).

Spleen mass (mg) Splenocytes (x 10^6)

Figure 2. Spleen growth kinetics after injection of bm12 lymphocytes. Spleens were weighed on a high precision balance directly after excision (left). Live cell numbers were determined by counting with a hemocytometer using trypan blue to exclude dead cells (right). Results are depicted as mean ± SEM, where n = 9, 4, 3, and 6, respectively.

Splenocytes are sequentially gated on light scatter (FSC-A by SSC-A), elimination of dou- Figure 2 blets (FSC-W or -H by FSC-A), viable cells (low staining of viability dye), and CD4+TCRβ+ (Fig. 3A). Donor cells are distinguished from recipient cells based on CD45.1 and CD45.2 (Fig. 3B, bottom left). Donor cells predominantly adopt a T follicular helper (Tfh) cell phenotype, as characterized by the upregulation of PD-1, CXCR5, Bcl-6, and ICOS (Fig. 3B,C). A portion of the recipient CD4 T cell population also differentiates into Tfh (Fig. 3B, bottom right). After an initial die-off and/or migration of transferred cells, the expansion of donor-derived Tfh is logarithmic, reaching 10-20 million cells in the spleens of mice 14 days after injection (Fig. 3D).

109 A C C C C

C C TCRβ B Naïve

Overlay

C Donor Naïve

C CC

14 days after bm12 transfer C CC donor CC

C recipient C CC CC

C Donor Recipient

CCC CC C CC C

A D

C C C (log10 )

C C TCRβ Tf h B Naïve Figure 3 Overlay C Donor Naïve

C CC

14 days after bm12 transfer C CC donor CC

C recipient C CC CC

C Donor Recipient

CCC CC C CC C

D Figure 3. Analysis of T follicular helper cell expansion in the bm12 model of SLE. CD45.1+ bm12 lymphocytes were transferred into C57BL/6 recipients and spleens were analyzed 14 days later. (A) Repre- sentative gating strategy showing “lymphocytes” (first panel), “single cells” (second panel), “live cells” (third (log10 )

panel), and “CD4 T cells” (fourth panel). (B) Donor cells are distinguished from recipient CD4 T cells by CD45.1 and CD45.2 staining and analyzed for expression of PD-1 and CXCR5. (C) Donor cells adopt Tfh phenotype, Tf h as indicated by the upregulation of several proteins commonly associated with Tfh. (D) Typical results showing the expansion of donor-derived Tfh (defined as CD4+CD45.1+PD-1+CXCR5+ live cells) at days 3, 7, and 14 post transfer. Results are depicted as mean ±SEM, where n = 5, 4, 3, and 6, respectively. Figure 3 CFSE-labeling of transferred lymphocytes demonstrated that donor CD4 T cells differentiate into Tfh early after activation; essentially all divided cells observed at days 3, 7, and 14 upregulated CXCR5 and PD-1 (Fig. 4). The proliferation peak profiles also suggest that a relatively low percentage of donor CD4 T cells underwent alloactivation and division. By day 14, most of the detectable donor cells are those that have divided beyond the maximum number of divisions measurable by CFSE.

110 Naïve Day 3 Day 7 Day 14 Figure 4. PD-1 and CXCR5 are upregulated on divid-

ing cells. Bm12 cells were labeled with CFSE prior to injection into C57BL/6 recipients. Representative flow plots are shown for donor CD4 T cells at 3, 7, and 14 days after injection. CC C

The expansion of donor-derived Tfh is accompanied by a corresponding accumulation of endogenousFigure 4 GC B cells and plasma cells (Fig. 5A). Plasma cell accumulation in the spleen is delayed compared to that of Tfh, exhibiting no increase over naïve animals on days 3 or 7 (Fig. 5B). Accordingly, anti-nuclear antibodies are not readily detectable prior to day 9 (data not shown), but can be reliably quantified on day 1411.

A 14 d after B Naïve bm12 inj.

)

C C

Plasma cells (log10 )

Figure 5. Expansion of splenic plasma cells and GC B cells. (A) Representative flow plots from naïve mouse spleens, or those from mice 14 days after CD45.1+ bm12 transfer. Plasma cells are defined as CD138+CD19low live cells (top panels). GC B cells are a subset of CD19+ B cells, which express GL-7 and Fas (bottom panels). (B) Quantitave data showing the accumulation of splenic plasma cells over time. Results are depicted as Figuremean 5 ± SEM, where n = 5, 4, 3, and 6, respectively

111 Through the use of congenic markers, we have observed rejection of donor cells in multiple strains. While this is a common problem when mice are not sufficiently backcrossed to the C57BL/6 background, we also observed rejection when bm12 cells were transferred into B6.PL-Thy1a/CyJ (CD90.1) mice that are generally considered to be fully backcrossed. Therefore, mice are routinely screened at day ~3 by flow staining blood samples to assess the efficiency of the initial CD4 T cell graft; we know from CFSE proliferation experiments that grafted cells have expanded very little at this early time point. These results are then compared to results obtained from the day 14 harvest. In an example case of rejection, 30 million CD45.1+ bm12 lymphocytes were transferred into Cardif-/- mice which had been backcrossed to C57BL/6 mice for 12 generations. At day 5, all mice displayed equivalent grafting (2-3% of circulating CD4 T cells), but by day 14, bm12 donor cells were completely eliminated from the genetically modified recipient (Fig. 6). Day 5 Day 14 (PBMC) (Spleen)

Rejection mutant recipient

Expansion C57BL/6 recipient C C

Figure 6. Bm12 grafts are rejected by some genetically modified recipient mice.CD45.1+ bm12 lymphocytes were transferred into either genetically modified mice (top panels) or C57BL/6 (bottom panels) recipient mice. Mice were bled at 5 days post injection and assessed for graft efficiency. Splenocytes from the same mice were analyzed 14 days later. Figure 6

112 DISCUSSION: The bm12 inducible model is a relatively easy and efficient way to study the cellular and molecular processes of SLE. Chronic activation of adoptively transferred CD4 T cells directed against self antigens leads to the accumulation of Tfh, GC B cells, and plasma cells which can be measured by flow cytometry, as described here. Future studies using this model can quickly and easily interrogate the role of candidate genes and novel therapies in the autoimmune germinal center processes which resemble those occurring in patients with SLE, and ultimately govern the pathological accumulation of autoantibodies. Furthermore, the flow cytometric analysis described here can be used to study additional mouse models that involve the development of immunoglobulins including, but not limited to autoimmunity, infection, and allergy.

Like all animal models of human disease, this model also has its limitations. Given the speed with which disease develops and its magnitude, not all genes involved in the development of SLE are likely to be necessary for pathogenicity in this model. Additionally, care must be taken to rule out graft rejection when data suggest minimal expansion of Tfh in genetically modified recipients. Congenic markers should be used to confirm the presence of donor cells at harvest especially since recipient cells can also differentiate into Tfh (Fig. 3B), which could otherwise mask the absence of donor cells. Using congenic markers, we observed complete elimination of donor cells that evidently harbored rejection antigens by day 14 (Fig. 6). We have successfully used CD45.1+ bm12 and CD45.2+ bm12 mice as donors, and CD45.1+ BoyJ (B6.SJL-Ptprca Pepcb/BoyJ) and CD45.2+ C57BL/6 mice as recipients (Fig. 3, 6, 7, and unpublished data). However, wild type congenic CD90.1+ cells from the B6.PL-Thy1a/CyJ mouse strain do not graft well, nor do CD90.2+ bm12 cells graft well in a CD90.1+ recipient (unpublished data), a phenomenon that is evidently not unique to this model26.

113 Either C57BL/6 or bm12 mice can serve as the donor or the recipient, as initially reported by Morris et al.9 However, in our lab we find the transfer of bm12 cells into B6 mice produces more consistent expansion of T cell and B cell populations at day 14. Furthermore, donor and recipient mice from different groups should be gender- and age-matched. Al- though experiments reported in the first description of the bm12 model found nosig- nificant difference in any disease parameter between male→male and female→female transfers9, male→female transfers are not advised, as male antigen (H-Y) expressed by transferred CD4 T cells may induce graft rejection in female recipients27.

When choosing antibodies and fluorochromes for congenic markers, it should be noted that donor cells become positive for the recipient congenic marker to varying degrees, such that a CD45.2− gate would not constitute the entire CD45.1+ graft. The phenomenon is clearly illustrated in a comparison of CD45.2 expression by CD45.1+ naïve, CD45.1+ donor, and CD45.2+ recipient CD4 T cells (Fig. 7). Notably, donor cells also seem to upregulate expression of their own congenic marker, compared to naïve controls (Fig. 7). Similar results are also seen with CD45.2+ bm12 transfer into CD45.1+ BoyJ mice (data not shown). Presumably, acquisition of recipient CD45 results from trogocytosis28 by activated CD4 T cells following repeated interactions with recipient B cells. In fact, the bm12 model may prove a useful tool in studying the process of trogocytosis in vivo.

Naïve Day 14 Overlay CD45.1+ CD45.1+ donor Naïve CD45.1 Donor CD45.1 Recipient CD45.2

C CD45.2+

recipient C C C

Figure 7. Donor cells acquire recipient CD45 congenic marker. CD45.1+ bm12 lymphocytes were transferred into CD45.2+ C57BL/6 recipients. Donor, recipient, and naïve (CD45.1+) CD4 T cells are assessed for CD45.1 and CD45.2 expression 14 days after transfer.

Figure 7 114 It has been shown that the transfer of purified bm12 CD4 T cells into C57BL/7 mice is sufficient to initiate disease29; however, equivalent disease develops when whole lymphocytes are transferred, and purification is not necessarily required to study disease dependence upon T cell-intrinsic gene expression. Eisenberg and colleagues, clearly demonstrated that the antibody-producing cell in the bm12 model is almost exclusively of recipient origin30. Furthermore, the requirement for recipient CD4 T cells10 is limited to the ‘nurturing’ of B cells during their development, which can be off-set by the addition of exogenous IL-431, although our data indicate that recipient T cells may participate somewhat in the germinal center response, as some of them do develop a Tfh phenotype (Fig. 3B, bottom right).

One critical decision that must be made for every bm12 experiment is when to harvest tissues for analyses. Of course the decision depends upon exactly what factors are important to the current study, which may vary. The experiments described here take up to 14 days, as they focus on the initial development of Tfh cells and plasma cells; however, since this model is a chronic GVHD model of SLE, disease can be monitored much longer. In fact, certain clinical features of SLE, including glomerulonephritis, develop later. Proteinuria has been detected as early as 2 weeks post-injection, but reaches peak levels at 4-8 weeks post-injection10,31. Additionally, the flow cytometric analyses described here have been optimized for experiments lasting 2 weeks. We find a considerable number of GC B cells and plasma cells at this time point; although, given additional time, a large percentage of ANA-secreting plasma cells may reside in the bone marrow32. Moreover, the plasma cells identified by this flow staining panel likely also include plasmablasts—in order to distinguish between these two cell types, additional antibodies would be required. Tfh expansion presumably reaches a peak at some point after the 14-day window on which we have focused. However, to our knowledge, no studies have reported bm12 donor cell number beyond 2 weeks, or used congenic markers to track adoptively transferred cells.

115 ACKNOWLEDGMENTS: This work was supported in part by the Lupus Research Institute, NCI grant CA138617, NIDDK grant DK090978, Charlotte Schmidlapp Award (to E.M.J.), and the Albert J. Ryan Fellowship (to J.K.). We are grateful for the support and instrumentation provided by the Research Flow Cy- tometry Core in the Division of Rheumatology at Cincinnati Children’s Hospital Medical Center, supported in part by NIH AR-47363, NIH DK78392 and NIH DK90971.

DISCLOSURES: The authors have nothing to disclose.

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119

Chapter 5: STING-mediated DNA sensing promotes antitumor and autoimmune responses to dying cells*

*This is reprinted here with permission. The article was originally published 2014: STING-mediated DNA sensing promotes antitumor and autoimmune responses to dying cells. Klarquist J, Hennies CM, Lehn MA, Reboulet RA, Feau S, and Janssen EM. J Immunol. 2014 Dec 15;193(12):6124-34.

120 Abstract Adaptive immune responses to antigens released by dying cells play a critical role in the development of autoimmunity, allograft rejection, and spontaneous as well as therapy-induced tumor rejection. Although cell death in these situations is considered sterile, various reports have implicated type I IFNs as drivers of the ensuing adaptive immune response to cell-associated antigens. However, the mechanisms that underpin this type I IFN production are poorly defined. Here we show that dendritic cells (DCs) can uptake and sense nuclear DNA-associated entities released by dying cells to induce type I IFN. Remarkably this molecular pathway requires STING but not TLR or NLR function and results in the activation of IRF3 in a TBK1-dependent manner. DCs are shown to depend on STING function in vivo to efficiently prime IFN-dependent CD8+ T cell responses to tumor antigens. Furthermore, loss of STING activity in DCs impairs the generation of follicular helper T (Tfh) and plasma cells as well as anti-nuclear antibodies in an inducible model of systemic lupus erythematosus (SLE). These findings suggest that the STING pathway could be manipulated to enable the rational design of immunotherapies that enhance or diminish anti-tumor and autoimmune responses, respectively.

121 Introduction The immune system carefully balances its response to dead and dying cells in order to maintain homeostasis and prevent the development of autoimmunity. Although uptake and clearance of dying cells is generally considered a tolerogenic process, the existence of immunogenic cell death has been well described (1). Depending on the nature of the cell death, dying cells can emit damage-associated molecular patterns (DAMPs) (2) that act as danger signals and increase a dying cell’s immunogenicity. Many of these DAMPs seem to use the sensing and signaling pathways that are normally associated with for the recognition and elimination of pathogens. Given the importance of immune responses to cell-associated antigens in autoimmunity, allograft rejection, and tumor rejection, the identification of these DAMPs, their cognate sensors, and their pro-inflammatory sequelae have become topics of intense research.

Ample studies have implicated type I IFNs in the development or progression of immune responses to self-antigens in autoimmune diseases such as rheumatoid arthritis (RA), type I diabetes mellitus (T1D), Sjögren’s syndrome and systemic lupus erythematosus (SLE) (3). However, type I IFNs were only recently identified as a crucial mediator in the priming of CD8+ T cells to cell-associated antigens in cancer and cancer treatments. Mice lacking type I IFN sensing—either by genetic IFN receptor (IFNAR) deletion or treatment with blocking Ab—develop more chemically-induced tumors and show poorer rejection of transplanted immunogenic tumors than WT mice, highlighting the requirement for type I IFN in spontaneous tumor rejection (4, 5). Additional studies showed that the spontaneous induction of tumor-specific CD8+ T cells in tumor-bearing mice was predominantly mediated by type I IFN sensing in dendritic cells (DC) (6, 7). A similar role for type I IFN was seen in therapy-induced tumor elimination. Burnette and Kang showed increased intratumoral production of type I IFN upon ablative radiotherapy or chemotherapy (8, 9). The ablative effect of the therapy was associated with enhanced (cross)priming capacity

122 of tumor-infiltrating DCs and could be abolished by eliminating IFNAR from the hematopoietic compartment. Our previous work, using tumor cell therapy in vaccination and therapeutic settings, showed a comparable dependency of type I IFN in the induction of protective anti-tumor CD8+ T cell responses (10-12).

While the general immunostimulatory effects of type I IFN on DCs are well studied, little is known on the cellular source of type I IFN, the type I IFN-inducing ligand, and the receptor/signaling pathways involved in its induction upon the sensing and clearance of dying cells. Our previous work indicated that DCs can produce type I IFN upon phagocytosis of dying cells (10-12). Importantly, DCs from MyD88-/-/TRIFlps/lps double deficient mice showed normal type I IFN production upon phagocytosis of dying cells and type I IFN-dependent CD8+ T cell priming to tumor-cell vaccines was comparable in WT and MyD88-/-/TRIFlps/lps mice, indicating that the type I IFN induction requires an unidentified TLR-independent sensing pathway (11).

Using various murine cancer and tumor cell vaccination models and in vitro approaches, we show that the type I IFN production upon sensing of dying cells is not only TLR-independent, but also RLR-independent and requires stimulator of IFN genes (STING)-IRF3 mediated sensing of apoptotic cell-derived nuclear DNA structures by DCs. The ensuing type I IFN production enhances DC functionality in an autocrine manner, resulting in the increased clonal expansion, poly-functionality, and memory formation of tumor-specific CD8+ T cells. Importantly, the role of the STING/IRF3/IFNAR nexus was not limited to CD8+ T cell priming or tumor models; elimination of STING or IFNAR significantly impacted the development of CD4+ T follicular helper cells, plasma cells, and anti-nuclear antibodies in an inducible model of SLE. Collectively, our results demonstrate that STING/ IRF3 sensing of nuclear DNA-derived structures by DCs broadly drives the priming of adaptive immune responses to dying cells.

123 Materials and methods Mice, cells lines, and peptides Mice were maintained under specific pathogen-free conditions in accordance with guidelines by the Association for Assessment and Accreditation of Laboratory Animal Care International. C57BL/6J, B6.PL-Thy1a/CyJ (B6/CD90.1), B6.SJL.Ptpcra (B6/CD45.1), CD11c-DTR mice and B6(C)-H2-Ab1bm12/KhEgJ mice were purchased from The Jack- son Laboratory (Bar Harbor, ME) and H2-Kb−/− from Harlan (Indianapolis, IN). IFNAR−/−, MyD88-/-/TRIFlps/lps, CD11c-DTR-IFNAR-/-, and Act-mOVA/H2-Kb−/− mice were bred in our facility. IRF3-/- and IRF7-/- mice were a gift from Dr. K. Fitzgerald (U. Massachusetts, MA), STING-/- mice a gift form Dr. R. Vance (Berkeley, CA), and IPS-1-/- mice a gift from Dr. J. Tschopp (UNIL, Lausanne). Mixed bone marrow chimeric mice were generated using donors on different congenic backgrounds in 1:1 ratios. All BM chimeric mice were rested for 12 weeks before experiments were started. B16/F10, B16F10-OVA (B16-OVA), EL-4mOVA, MEC.B7.SigOVA, Tap sufficient and deficient MEFs expressing the human adenovirus type 5 early region 1 (Ad5E1-TAKO, I1.2), and ISRE-L929 IFN reporter cells have been described before (13-16). Peptides OVA257–

264 (SIINFEKL), E1B192–200 (VNIRNCCYI), TRP-2180-188 (SVYDFFVWL) and LCMV GP33–41 (KAVYNFATC), were obtained from A&A Laboratories (San Diego, CA).

Cell isolations T cells, B cells, Mph and DCs were sorted by flow cytometry using markers TCRb, CD4, CD8, CD11c, CD11b, CD19, CD45R, MHC II as described before (12). Purity of sorted cells was generally >98% and viability was >97% as determined by 7-AAD staining. Erythrocytes, normoblasts, reticulocytes and red blood cells were generated using a mouse adapted protocol for the long-term ex vivo erythroid differentiation culture protocol described by Giarratana et al (17) and Konstantinidis et al (18). Briefly, low-density

124 bone marrow cells were cultured in erythroblast growth medium (StemPro-34 with 2.6% StemPro-34 supplement; Invitrogen), 20% BIT 9500 (StemCell Technologies), 900 ng/ mL ferrous sulfate, 90 ng/mL ferrous nitrate, 10−6M hydrocortisone, penicillin/streptomycin, L-glutamine), in 3 subsequent phases. For the proliferative phase (days 1-5) cells were expanded with 100 ng/mL SCF, 5 ng/mL IL-3, and 2 IU/mL human erythropoietin (Amgen). In the differentiation step (days 6-7), the cells were supplemented with only erythropoietin in fibronectin coated plates. For enucleation (day 8-9) cells were grown without cytokines. Cells were sorted based on size gating and nucleotide staining using different combinations of Syto-16, Draq5, Mitotracker Red and MitotrackerGreen (Invit- rogen).

DC cytokine production, phagocytosis and T cell activation. Flow cytometry purified DCs were cultured in a 1:3 ratio with irradiated cells (1500-3000 Rad). Parallel experiments were performed with UV irradiation (120-240mJ/cm2), Fas- cross linking (1-20ug/ml), or etoposide treatment (6hr, 1-10 mM) (11). When enucleated cells were compared to nucleated cells, all cells were gamma-irradiated and treated with thrombospondin-1 to upregulate phosphatidylserine on the membrane (19). After 20 hr type I IFN in the supernatant was determined by ISRE-L929 reporter assay that has detection limit of 0.3U/ml (13). For phagosomal acidification studies, diphenyleneiodium (DPI, 10uM), ConB (1 nM), or chloroquine (50uM) were added at the start of the culture (12, 20). Parallel cultures using CpG and LPS were used as controls. In vitro and ex vivo type I IFN analyses were performed by quantitative real-time PCR using SYBR Green and primers for β-actin (fw, TTGCTGACAGGATGCAGAAG; rev, GTACTTGCGCTCAGGAGGAG) and pan IFN-a (fw, TCTGATGCAGCAGGTGGG; rev AGGGCTCTCCAGACTTCTGCTCTG). Samples were treated with DNAse to eliminate genomic DNA contaminations. Gene expression was analyzed using the relative standard curve method and was normalized to Gapdh and β-actin expression.

125 For phagocytosis studies, DCs were incubated with CellTrace Violet-labeled irradiated splenocytes (Molecular Probes). After 3 and 16hr, DCs were stained with Abs to CD11c, CD11b, CD8α, nuclear dye Draq5, and fixable live/dead staining and analyzed by Image- Stream (Amnis, Seattle, WA). At least 10,000 live events were acquired and the number and size of phagocytosed particles were determined using the spot counting and spot size features after tight masking on the brightfield image to exclude membrane-associated extracellular particles for each condition as shown before (12, 21). To determine T cell activating capacity, DCs were incubated with irradiated OVA-Kb-/- cells for 4 hr after which CFSE-labeled purified OT-1-CD45.1 CD8+ T cells were added as described before (11). OT-1 cell proliferation and survival were determined after 70 hr by analysis of CFSE dilution together with staining for CD8a, Va2, CD45.1 and 7-AAD.

DC signaling studies Immune-coprecipitations: purified DCs were incubated with irradiated IRF3- or STING-deficient splenocytes. At different time points DCs were sorted, lysed, precipitated using agarose-bound antibodies to STING (3337, Cell Signaling) or IRF3 (D83B9, Cell Signal- ing) and probed for p-IRF3 (4D4G, Cell Signaling), TBK-1 (72B587, Novus Biologicals), p-TBK1 (D52C2, Cell Signaling), STAT6 (9362, Cell Signaling), and IPS1 (77275, Novus Biologicals). In parallel, CellTrace Violet-labeled irradiated IRF3-/- splenocytes were cultured with WT and STING-/- DCs and analyzed by flow cytometry and Amnis Imagestream upon surface staining with CD11c-PacificBlue and intracellular staining with Draq5 and p-IRF3 (anti-pS386, 4D4G) combined with anti-Rabbit IgG Alexafluor 488. Correlations between intensity of phagocytosed material and p-IRF3 localization in the nucleus were determined using Imagestream by gating on CD11c+ single cells followed by tight masking on the cells to discriminate internalized from bound particles followed by tight masking on the

126 nucleus to determine colocalization of the p-IRF3 staining in the nucleus (12).

In vivo models. Immunizations: mice were injected s.c. or i.p. with irradiated cells (OVA-Kb-/- splenocytes, 106-107; B16-OVA, B16/F10 and 5E1-TAKO, 1-5x106). Alternatively, mice received i.v. 2x105 purified DCs that had been pulsed with peptide or exposed to irradiated cells in vitro (10-12, 21). For DC depletion studies CD11c-DTR mice and mixed bone marrow chimeric mice were treated 24 hr before and 24 hr after immunization with 4ng/g diphtheria toxin i.p. Tumor models: For the cyroablation model mice were subcutaneously injected with 4x105 B16-OVA or B16/F10 in PBS. Ten days later tumors (7–10 mm) were cryoablated using Verucca-Freeze armed with a 6 mm probe (Brymill Cryogenic Systems) (22) for 3x25-second cycles. To test long-term tumor protection, the mice were challenged with 3x104 B16-OVA or B16/F10 40 days after the ablation of the primary tumor and monitored for tumor growth. In the EL-4-mOVA challenge model, mice were immunized with 107 irradiated OVA-Kb-/- splenocytes as described above and 40 days later challenged with 106 EL-4-mOVA cells s.c. SLE model (23): mice of indicated genetic backgrounds received 3x106 B6(C)-H2- Ab1bm12/KhEgJ (bm12) splenocytes i.p.. Splenic B and T cell composition B was analyzed by flow every 2 weeks. Serum levels of anti-dsDNA IgG, IgG1 and IgG2a were determined by ELISA as previously described (24).

T cell analysis Unless stated differently, analysis were performed 7 days after immunization. CD8+ T

b cells were enumerated in spleens and draining lymph nodes using OVA257-264-K tetramers

b (Beckman Coulter) or E1B192–200-D decamers (Immudex) together with staining for CD8a, CD44 and 7-AAD. In parallel cytokine production and polyfunctionality was determined

127 directly ex vivo by intracellular cytokine staining after a 5 hr stimulation with cognate peptide in the presence of brefeldin A as described before (11, 16). Samples were collected on a LSRII flow cytometer with Diva software (BD Pharmingen), and data were analyzed with FlowJo software (Tree Star). In B16/F10 studies, responses to TRP2180-188 were determined by ELISPOT directly ex vivo. Capacity for secondary expansion in vitro was determined by stimulating the splenocytes or purified CD8+ T cells on irradiated MEC.B7.SigOVA (OVA-specific) or I1.2 cells (E1B specific) for 6 days and dividing the absolute number of antigen-specific CD8+ T cells at the beginning of the culture by the absolute number of antigen-specific CD8+ T cells at the end of the culture as described before (16, 25). In vivo secondary expansion was determined by re-injecting the mice with a 10-fold higher number of irradiated cells than used during immunization. Four days after the secondary challenge the frequency antigen-specific CD8+ T cells was compared to non-challenged immunized mice (16).

Statistical analyses Data were analyzed using Prism software (GraphPad Software, Inc.). Unless stated otherwise, the data are expressed as means ± SEM. Survival responses were analyzed by Kaplan-Meier using a log-rank test. All other data were evaluated using a two-way ANO- VA followed by a Dunnett’s test. A p value of <0.05 was considered statistically significant.

128 Klarquist et al. Figure 1 Klarquist et al. Figure 1

0.8 control ee n A WT nai v e B l * p peptide

l IFNAR naive 0.8 control S / 100 ee n a A WT/cryo WT nai WT/cryo v e B0.6 l * v p i WT ll s peptide

l IFNAR naive v IFNAR/cryo S e /

r 100 a Results WT/cryo WT/cryo c

0.6 u

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u 75 T s en t 50 0.4 + Protective anti-tumor immunity requires type I IFN sensing by c DCs CD 8

r * 0.2 e +

en t 50 P c 25 N CD 8 r

I 0.2 e We and others recently showed that type I IFN sensing is critical for the induction of pro-* + P 25 N % 0.0 F 0 T * I

0 20 40 60 W WT % 0.0

0 T tective anti-tumor responses in various tumor models in both vaccination andda ystherapeutic after challenge IFNAR IFNAR 0 20 40 60 W no cryo cryo WT days after challenge IFNAR IFNAR settings (6-8, 22). Cryoablation of B16-OVA tumors in WT mice resultedC in effective prim - D no cry o cryo ee n 100 * 1.0 l 0.8 p l + ee n l

C D * S a / ee n p * ing of OVA -specific CD8 T cells that provided protective immunity upon subsequent WT naive l 257-264 v 100 1.0 0.8 i * p S ll s l / 0.8 ee n v

75 IFNAR naive l

* S

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u WT naive v WT/imm WT/cryo

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IFNAR/imm e 0.6 r B16-OVA challenge. In contrast, IFNAR mice failed to induce adequate OVA -specif- 0.6 257-264 + ll s 50 c l u

WT/imm WT/cryoT

e 0.4 s a en t +

WT T IFNAR/imm c v c

0.6 i + r 50 0.4 CD 8 l T

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ic CD8 T responses and succumbed upon tumor rechallenge (figureP 1a/b). Similarly, im- u v

i 0.2 r CD 8

s 0.4 + m

v r e 0.2 r

25 a N r CD 8

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munization with gamma-irradiated OVA-expressing K splenocytes (OVA-K ) induced % 0.0 r r * 0.0 T Klarquist et al. Figure 1 0 t F T % e

days post challenge I e en t 0 20 40 60 W W WT P c T WT

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+ % e days post challenge IFNAR IFNAR W W WT Klarquista significantly et al. Figure 1more robust OVA -specific CD8 T cell responseP in WT mice than in 257-264 WT b-/- b-/- Kb-/- OVA-Kb-/- K OVA-K IFNAR IFNAR IFNAR IFNAR E b-/- b-/- Kb-/- OVA-Kb-/- 0.8 control K OVA-K

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% 0.0 r 0.0 T T % e days post challenge b-/- b-/- b-/- b-/- W K OVA-K W WT P K OVA-K WT IFNAR IFNAR

E IFNAR IFNAR 8 * Kb-/- OVA-Kb-/- Kb-/- OVA-Kb-/- E FIGURE 1. Protective CD8+ T cell induction requires IFNAR on DCs. (A) WT and IFNAR2/2 mice were n o s.c. 8injectedi 6 with B16-OVA* tumor cells, and palpable tumors were cryoablated 10 d later. Cryoablated and

naiven mice were s.c. challenged with B16-OVA 40 d later and survival was monitored (n = 8–10/group). (B) l pan s o

i 6 4 x a v e

i OVA257–264–specific CD8+ T cell frequency in the spleen 7 d after cryoablation. (C) Mice were immunized

v d r l l pan s u with 4irradiatedo 2 OVA-Kb2/2 or Kb2/2 splenocytes and 40 d later s.c. challenged with EL-4–mOVA cells s.c. s x a F v e i (D) Frequency of splenic OVA257–264–specific CD8+ T cells 7 d after immunization as determined by in- v d r l en t u c o

r 2 0 s tracellular cytokine staining for IFN-g after peptide restimulation and by OVA257–264–Kb-tetramer staining. F T e W P (E) Fold expansion of OVA257–264–specificWT CD8+ T cells upon stimulation with OVA257–264–expressing en t c IFNAR IFNAR

r 0

cells in vitro.T Data of representative experiments (out of three to five) are shown (mean 6 SEM, n = 8–10/ e b-/- b-/- W

P K OVA-K group, *p < 0.05).WT IFNAR IFNAR Kb-/- OVA-Kb-/- 129 -/- + IFNAR mice (figure 1.c/d). The OVA257-264-specific CD8 T cells from WT mice but not IFNAR-/- mice underwent expansion upon secondary encounter with antigen in vitro and in vivo and protected mice from EL-4-mOVA challenge in vivo (figure 1e, figure S1a). Im- portantly, this response was not restricted to OVA or the selected pathways of cell death. Similar results were found when the parental line B16/F10 was used and the response to self-antigen TRP-2 was probed (figure S1b/c). In addition, direct immunization with gamma-irradiated, UV-irradiated, Fas-crosslinked, or etoposide treated cells showed significantly decreased CD8+ T cell responses in IFNAR-/- mice, illustrating a central role for type I IFN in CD8+ T cell priming to cell-associated antigens in various scenarios of cell death (figure ).2

As nearly all cells express IFNAR, we first used bone marrow (BM) chimeras to identify which cells required type I IFN sensing in the CD8+ T cell response to dying cells. BM chimeric mice (WTIFNARKlarquist-/-, WT etWT, al. FigureIFNAR 2-/-WT, IFNAR-/-IFNAR-/-) demonstrated that type I IFN needed to be sensed by the hematopoietic compartment (figure 3a/b).

FIGURE 2. Impaired CD8+ T cell actmOVA-Kb-/- B16-OVA 1.5 0.6 -/- priming in IFNAR mice is inde- control control ee n ee n l l OVA257-264 OVA257-264 p p s pendent of the method of cell death s / / 1.0 0.4 + or cell type. Frequency of splenic + + CD 8 CD 8

Ag-specific CD8 T cells in WT and + + * * * * * -/- 0.5 0.2 N IFNAR mice 7 d after s.c. immuniza- N F F I -/- I % tion with actmOVA-Kb splenocytes % 0.0 0.0 irr . irr . irr . (which were gamma irradiated [1500 irr . s-A b s-A b UV ir r UV ir r a 2 a F rad], UV irradiated [120 mJ/cm ], or F UV irr 24 0 UV irr 24 0 gamma gamma gamma treated with FAS cross-linking Ab gamma -/- -/- [Jo-1, 20 mg/ml; 4 h, 37°C]), 5E1-TA- WT IFNAR WT IFNAR KO cells (3000 rad, 240 mJ/cm2, or 5E1-TAKO 2.0 B16-/F10 treated with etoposide [10 mM]), or 0.15 control control

B16-OVA or B16/F10 cells (3000 rad ee n l

E1B ee n 192-200 l TRP2180-188 2 p 1.5 p s s

or 240 mJ/cm ). Ag-specific T cell fre- / / 0.10 + quencies were determined by intra- + 1.0 CD 8 CD 8 cellular cytokine staining upon incu- + + 0.05 N

N * * * bation with OVA257–264, E1B192–200, 0.5 * * F F I I

TRP- , or control peptide GP % 2180–188 33– % 0.0 0.00 irr . (white bar, control peptide; black irr .

41 irr . irr . bar, specific peptide). Data in all ex- Eto p Eto p UV irr 24 0 UV irr 24 0 gamma gamma UV irr 24 0 UV irr 24 0 periments are expressed as mean 6 gamma gamma WT IFNAR-/- SEM with n = 5. *p < 0.05. WT IFNAR-/-

130 Additional studies with WT/IFNAR-/-WT mixed BM chimeric mice indicated that the diminished CD8+ T cell response could not be attributed to the lack of IFNAR on the CD8+ T cells as IFNAR-/- CD8+ T cells only showed a marginal decrease in clonal expansion (figure 3c). Given the important role of DCs in cross-presentation of cell-associated antigens, we nextKlarquist examined et al. Figure the 3 role of type I IFN sensing on DCs. Mixed BM chimeras were generated in which IFNAR-/- recipients received a combination of WT-CD11c-DTR

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T C IF WT W + R A WT-D C N

IF IF NAR-D C WT-D C NAR-D IF

-/- FIGURE 3. Selective requirement for type I IFN sensing in the DCs. (A) Bone-marrowIFNα relative units chimeric mice (WT-->IFNAR , WT-->WT, IFNAR-/--->WT, IFNAR-/--->IFNAR-/-) were immunized i.p. with irradiated 5E1-TAKO cells and the frequency of + E1B192–200–specific CD8 T cells in the spleens was determined 7 d later (white bar, control peptide; black bar, E1B192–200 peptide). (B) The effect on memory formation using these chimeras was determined by measuring Ag-specific T cell expansion ex vivo. Secondary expansion of E1B192–200–specific CD8+ T cells was calculated by dividing the absolute number of E1B192–200–specific CD8+ T cells at the end of a 6 d culture by the absolute number at the start of the culture. (C) WT/CD90.1 mice were irradiated and reconstituted with WT, IFNAR-/- or a 1:1 ratio of WT(CD45.1):IFNAR-/-(CD45.2) bone-marrow. Mice were i.p. immunized with irradiated 5E1-TAKO cells and the frequency of splenic E1B192-200-specific CD8+ T cells in each graft was determined 7 d later. (D) WTCD11cDTR:IFNAR-/- and WT:IFNAR-/-CD11c-DTR mixed bone-marrow chimeras were treated with DTor vehicle and immunized with irradiated 5E1-TAKO cells. The frequency of + -/- E1B192–200–specific CD8 T cells in the WT compartment was determined 7 d later. (E) Freshly isolated WT and IFNAR DCs were incubated with irradiated 5E1-TAKO cells, sorted and i.v. injected into WT and IFNAR-/- mice. The frequency + of splenic E1B192–200–specific CD8 T cells was determined 7 d later. Data of representative experiments (out of three to five) are shown (mean 6 SEM, n = 5/group, *p < 0.05).

131 and IFNAR-/-/CD45.1 BM or IFNAR-/--CD11c-DTR and WT/CD45.1 BM. In this model the administration of DT yielded animals that contained either WT or IFNAR-/- DCs with an otherwise comparable composition of hematopoietic cells. Depletion of WT DCs significantly decreased the number and frequency of antigen-specific CD8+ T cells. In contrast, depletion of IFNAR-/- DCs had no effect on the number or frequency of antigen specific CD8+ T cells (figure 3d). Similar results were observed when purified WT or IFNAR-/- DCs were pulsed with irradiated cells and transferred into WT and IFNAR-/- recipients, illustrating the critical role of type I IFN sensing by DCs in CD8+ T cell priming to cell-associated antigens (figure 3e).

DCs predominate the type I IFN production elicited by dying cells Besides sensing type I IFNs in the context of CD8+ T cell priming to dying cells, we reasoned that DCs may also be the main producers of type I IFN, thereby establishing a positive IFN-feedback loop. In vitro studies using purified cell populations indicated that type I IFN was produced by DCs upon incubation with dying cells, whereas only nominal IFN Klarquist et al. Figure 4 production was observed in cultures depleted of DCs (figure 4a/b/c) (11, 12). The in vitro

control A 5 B 8 C 2. 5 * D * * irradiated cell FIGURE 4. Type I IFN production* by DCs in 4 * vitro2.0 and in vivo. Total and subset-depleted ) l

) 6 l l 4 m m m / / / 3 splenocytes1.5 (A) or purified cell populations (B) U

(E U

(E U 4

from spleens of naive WT mice were cultured 2 N 1.0 -/- F IF N IF N I with irradiated OVA-Kb 2 splenocytes, and type 2 1 I 0.IFN5 in the supernatant expression IFN α rel. was determined 20 h later (black bars, irradiated cells; white bars, 0 0 0.0 0 l - - C e c D DnoT cells).- + -Data+ are expressedDT - + as- mean+ 6 SEM Klarquist et al. Figure 4 tota Mp h non TCR T cel l B cel l CD11 withnone n = + 4. irr. cells(C) Splenocytesnaive from + irr. cellsCD11c-DTR irr. cells mice (treated with PBS or DT 24 h prior) were + irr cells isolated and cultured with irradiated OVA-Kb-/- control A 5 B 8 C 2. 5 * D * * irradiated cell * splenocytes. Type I IFN in the supernatant was 4 * 2.0 determined 20 h later. (D) CD11c-DTR mice ) l

) 6 l l 4 m m m / / / 3 1.5 were treated with vehicle or DT and 24 h later U

(E U

(E U 4

s.c. injected with irradiated cells. Type I IFNa

2 N 1.0 F IF N IF N I 2 mRNA in draining lymph nodes was assessed 2

1 0.5 expression IFN α rel. 6–8 h later. Representative data of one experiment (out of three to four) are shown (mean 6 0 0 0.0 0 l - - C e c D DT - + - + DT - + - + SEM, n = 5, *p < 0.05). tota Mp h non TCR T cel l B cel l CD11 none + irr. cells naive + irr. cells irr. cells + irr cells 132

data were supported by our observation that IFNa mRNA was readily detectable in the draining LN of control-treated but not DT-treated CD11c-DTR mice upon subcutaneous immunization with irradiated cells (figure 4d). Klarquist et al. Figure 5

60 o A 1 0 B 4 C )

l o The STING/IRF3 pathway drives type I IFN in response* * *to cell-associated37 C antigen m / e ll s

8 c U

( c

i 40 on

i 6

Induction of type I IFNs is generally associatedt with innate sensing of pathogenic dan- 0.20 WT 4 STING odu c

r 20 p phago cy t ger signals. To identify which innate sensing pathways2 facilitated the type I IFN0.15 produc- N % F I 0

-/- lps/lps T -/- STAT6-/- 0 -/-

IP STING T W 0.10

tion, primary DCs from WT, MyD88 /Trif , IRF3 , IRF 3 IRF7IRF 7 Stin g , IPS1 (MAVS/Cardif), and W IPS-1 IPS 1 IRF 3 IRF 7 Stin g IFNAR p-TBK1 IFNAR

-/- MyD88 /T ri f

STING MyD88 /T ri f 10 0.05 ) STING mice deficient were tested for their type I IFN production upon l culture with dying 10 ) m l / 8 U m / C WT STING D 0.20( 8 WT U

-/- lps/lps -/- ( 0.00 -/-

on STING o i 6 i

hr 0 4 8 12 0 4 8 12 HSV t cells. Type I IFN production was similar in WT, MyD88 /Trif , IPS1t , and IRF7 DCs

on 0 4 8 12 16 i a 6 t IP IRF3 r 0.15 4 3 * odu c

r hrs F 4 p odu c

0.10 r 2 /I R N p

indicating that the IFN induction was TLR-, RIG-I- and Mda5-independent.3 In contrast, F 2 I N F F

I 0 R T I 0.05 - 0 W p T IRF 3 IRF 7 Stin g Cardi f W IFNAR significant reductions in type I IFN production were seen with DCs deficient in STINGIRF 3 IRF 7 Stin g and Cardi f

Klarquist et al. Figure 5 0.00 IFNAR 0 4 8 12 1MyD88 /T ri f 6 hrs MyD88 /T ri f

60 o A 1 0 B 4 C )

l o E F * * * 37 C m / e ll s BF CD11c Draq5 VT p-IRF3 overlay

8 c U

4 ( 10 ) c l

i 40 WT e x on i i 6 3 t 0.20 WT p 10

4 STING 2 odu c 10 r

20 (m ean

p phago cy t T

2 0.15 V 1 N 10 % 0 F I 5000 0

0 5 1010000 0 1515000 0 2020000 0 0 nucl. p-IRF3 intensity (10 4 ) T STAT6 0

IP STING T W 0.10 4 IRF 3 IRF 7 Stin g W

) 10 l IPS-1 IPS 1

IRF 3 IRF 7 Stin g STING IFNAR p-TBK1 e x IFNAR i

p 103 MyD88 /T ri f

STING MyD88 /T ri f 10 0.05 ) l 10 102 ) m l (m ean / 8 U m T / ( WT C WT STING D 0.20 8 V 1 U 10 ( 0.00 0 on STING o i 6 i 5000 0 hr 0 4 8 12 0 4 8 12 HSV t

0 5 1010000 0 1515000 0 2020000 0 t

on 0 4 8 12 16 4 i a 6

t nucl. p-IRF3 intensity (10 ) IP IRF3 r 0.15 4 3 * odu c

r hrs F 4 p odu c

0.10 r 2 /I R N p

3 F 2 I N F F

I 0 R T I 0.05 - 0 W p T IRF 3 IRF 7 Stin g Cardi f W IFNAR IRF 3 IRF 7 Stin g Cardi f

0.00 IFNAR

0 4 8 12 1MyD88 /T ri f 6 hrs MyD88 /T ri f

E F FIGUREBF 5. CD11c Type Draq5 I IFN VT induction p-IRF3 overlay requires the STING/IRF3 pathway. (A) Type I IFN production by purified 104 ) l WT

DCs from indicated strains upon 20-h e culture with irradiated splenocytes. (B) Purified DCs from indicated x i 3 strains were cultured at 4°C (white bars)p 10 and 37°C (black bars) with VT-labeled irradiated splenocytes. Up-

102 take of VT materials was determined 6(m ean h later by flow cytometry. Data are expressed as percentage of DCs

T that contain VT. Representative data ofV 10 1one experiment (out of three to four) are shown (mean 6 SEM, n = 0 5000 0 0 5 1010000 0 1515000 0 2020000 0 -/- 4). (C and D) p-IRF3 kinetics in WT andnucl. STING2/2 p-IRF3 intensity (10DCs 4 ) upon incubation with irradiated IRF3 splenocytes.

) 10 (E) ImageStream images of p-IRF3 nuclearl translocationSTING in WT DCs 8 h after incubation with VT-labeled e x -/- i irradiated IRF3 cells. Original magnificationp 103 360. (F) ImageStream analysis of nuclear p-IRF3 intensity -/- 102

and intensity of cytosolic phagocytosed(m ean material in WT and STING DCs. Tight masking on the cytosol

T was done to discriminate between boundV 101 and internalized cellular material. At least three experiments were 0 5000 0

0 5 1010000 0 1515000 0 2020000 0 performed with 800–1000 analyzed cells/condition.nucl. p-IRF3 intensity (10*p 4 ) , <0.05.

133 the transcription factor IRF3 even though their subset compositions, maturation status and phagocytic capacity were similar to WT DCs (figure 5a/b and not shown). Immu- noprecipitation and western blotting studies indicated rapid IRF3 phosphorylation in WT DCs and a significant reduction and delay in IRF3 phosphorylation in STING-/- DCs upon exposure to dying cells (figure 5c/d). To determine whether the magnitude of the nuclear p-IRF3 signal was associated with the frequency and size of phagocytosed particles, WT and STING-/- DCs were incubated with CellTrace Violet (VT)-labeled, irradiated, IRF3- /- splenocytes and analyzed by conventional flow cytometry and imaging cytometry. WT DCs showed a strong correlation between nuclear p-IRF3 intensity and the amount of phagocytosed material. Although STING-/- DCs displayed similar uptake of VT material as WT DCs, they exhibited significantly reduced nuclear p-IRF3 staining, consistent with their limited IFN production (figure 5e/f, figure S2a). Using UV-irradiation, Fas-crosslinking, or etoposide to induce cell death yielded similar outcomes, indicating that the STING/ IRF3 pathway was the dominant IFN-inducing pathway in various forms of sterile cell death (figure S2b).

Nuclear DNA-derived structures induce type I IFN production by DCs We next set out to determine the ligand upstream of STING that was responsible for inducing type I IFN. STING facilitates immune responses to various nucleotide structures, including cytosolic dsDNA, and in some cases dsRNA (26-28). As dsRNA sensing utilizes the RIG-I/IPS-1 pathway and IPS1-/- DCs have normal type I IFN production, it is likely that the IFN-inducing species released by dying cells is a DNA- and not an RNA-based entity. Indeed, addition of DNAses, but not RNAses to WT DC/irradiated cell co-cultures significantly reduced type I IFN production without affecting uptake of cellular material or responses to non-nucleic TLR ligands (figure 6a, figure S2c/d). To more rigorously address the role of DNA complexes in the type I IFN induction, we exploited the process of erythropoiesis where red blood cell (RBC) precursors sequentially lose their nuclei,

134 Klarquist et al. Figure 6

A B Draq5 Annexin V 8 * FIGURE 6. IFN induction by a nucle- * lymphocytes ar DNAderived structure. (A) Type I 6 IFN production by WT DCs upon culture with irradiated splenocytes in the 4 erythroblast presence or absence of RNases and IFN U/m l 2 DNases. (B) Cells at different stages reticulocyte of erythropoiesis were sorted based on 0 nucleotide content, irradiated, and incubated with thrombospondin-1. Flow control DNAs e RNAs e cytometric analysis of nuclear content DC onl y erythrocyte (Draq5) and Annexin V levels in indi-

DNase/RNas e cated cell types before (red line) and + irr. cell control after (blue line) irradiation and throm- irradiated/ thrombospondin1 treated bospondin-1 treatment. (C) Purified WT DCs were cultured with VT-labeled form dsDNA, a common conformation of irradiated/TPS1-treated cells. Uptake independent production of type I IFNs that requires C 4 0 D 5 of VT material was determined 6 h later by flow cytometry. Data are expressed 4 e ll s

) as percentage of DCs that contain VT. c 30 l

c m i / 3 (D) Type I IFN production by WT DCs U 20 upon culture with VT-labeled irradiated/ ( * *

N 2 thrombospondin-1–treated cells at dif- F I phago cy t

10 ferent stages of erythropoiesis. Repre- 1 % sentative data of one experiment (out of 0 t 0 three) are shown (mean 6 SEM, n = 5, t

e e e e *p <0.05). none none lymph o lymph o reticulocyt erythrocyt erythroblas reticulocyt erythrocyt erythroblas ery + irr Kb-/-

mitochondria and ribosomes. Timed RBC cultures were sorted, irradiated and treated with thrombospondin-1 (irr/TSP) to induce comparable phosphatidylserine expression on the membrane and facilitate an “apoptotic phenotype” in the non-nucleated cells (figure 6b). ImageStream analysis showed comparable uptake of the irr/TSP cell subsets by DCs (figure 6c). Nucleated irr/TSP erythroblasts readily induced type I IFN in DCs while enucleated reticulocytes and RBC failed to do so (figure 6d). These data indicate that the IFN-inducing species is nuclear DNA-derived.

DC-intrinsic STING regulates CD8+ T cell responses to dying cells Given the importance of STING-mediated DNA sensing in the type I IFN production, we

next assessed the relative contribution of STING in the priming of CD8+ T cells to dying cell-associated antigens. WT, MyD88-/-/Triflps/lps, IPS-/-, and IRF7-/- mice showed comparable CD8+ T cell priming as determined by tetramer staining, intracellular cytokine staining,

135 and capacity for secondary expansion upon immunization with irradiated 5E1-TAKO cells (figure 7a/b). In contrast, IFNAR-/-, IRF3-/- and STING-/- mice showed significantly reduced CD8+ T cell priming (figure 7c/d). Moreover, the antigen-specific IFNAR-/-, IRF3-/- and STING-/- CD8+ T cells displayed less cytokine polyfunctionality and impaired capacity for secondary expansion (figure 7e). The defect in CD8+ T priming was fully DC-regulated as similar results on CD8+ T cell clonal burst, secondary expansion and cytokine poly- Klarquist et al. Figure 7

A 1. 5 * B 2 0 * ee n l p

io n 15 s * / 1.0

+ *

pan s 10 x CD 8 e

+ 0.5 old N 5 F F I % 0.0 0 f f T T W W IRF 3 IRF 7 IRF 3 IRF 7 IPS-1 IPS-1 IFNAR IFNAR My D88 /Tr i My D88 /Tr i WT IFNAR C D E IFNγ 1.5 * 20 * IFNγ IL-2 IFN TNF

ee n γ/ α l * * p io n 15 IFNγ/IL-2/ TNFα s * * / 1.0 +

pan s 10 x

e STING IRF3 CD 8

+ 0.5 old 5 N F F I % 0.0 0 T G T G W W IRF 3 IPS-1 IRF 3 IPS-1 IFNAR STI N IFNAR STI N F G H WT IFNAR I 0.15 0.4 * * * 10 een * * een p l 0.3 8 * io n s 0.10 p l / s / 0.2 6 pan s * * CD 8 + x + CD 8 + e 4 STING IRF3 0.05 + N 0.1 F N old I 2 F F I % % 0.0 0 0.00 T T G T T G G G W W W W IRF 3 IRF 3 IFNAR IFNAR IFNAR IFNAR STI N STI N STI N STI N irr. cell peptide

FIGURE 7. STING regulates the CD8+ T cells responses to dying cells in vivo. (A) Mice of indicated strains were + immunized with irradiated 5E1-TAKO cells, and the frequency of splenic E1B192–200–specific CD8 T cells was determined 7 d later (white bar, control peptide; black bar, E1B192–200 peptide). (B) Fold expansion of E1B192-200– + specific CD8 T cells from indicated mouse strains upon culture with E1B192–200–expressing feeder cells in vitro. + (C) E1B192–200–specific CD8 T cell frequency in indicated mouse strains 7 d after immunization with irradiated + 5E1-TAKO cells. (D) Secondary expansion of E1B192–200–specific CD8 T cells in vitro. (E) Ex vivo polyfunctionality + of E1B192–200–specific CD8 T cells from (C) as determined by flow cytometry. (F) Frequency of E1B192–200–specific CD8+ T cells in WT mice 7 d after transfer of indicated DCs pulsed with irradiated 5E1-TAKO cells in vitro. (G) + Secondary expansion of E1B192–200–specific CD8 T cells primed by indicated DCs. (H) Ex vivo polyfunctionality + -/- -/- of E1B192–200–specific CD8 T cells primed by indicated DCs. (I) DCs were purified from WT, IFNAR and STING mice and exposed to irradiated 5E1-TAKO cells or pulsed with 1 mM E1B192–200 peptide. DCs were repurified and 5 + 2 x 10 were injected into WT recipients. Seven days later, the frequency of splenic E1B192–200–specific CD8 T cells was determined (white bar, control peptide; black bar, E1B192–200 peptide). Representative data of one experiment (out of three to four) are shown (mean 6 SEM, n = 5–7, *p , 0.05).

136 functionality were seen when purified IFNAR-/-, IRF3-/- and STING-/- DCs were exposed to irradiated cells in vitro and transferred into WT recipients. (figure 7f/g/h). The priming defect of the IFNAR-/-, IRF3-/-, and STING-/- DCs could not be attributed to a decrease in overall DC functionality as peptide-pulsed IFNAR-/-, IRF3-/-, and STING-/- DCs induced comparable CD8+ T cell responses as WT DCs upon transfer in WT recipients (figure 7i). Together, these data demonstrate the requirement for STING, IRF3, and IFNAR in DCs in the cross-priming of CD8+ T cells to cell-associated antigens.

STING regulates CD4+ T cell and B cell responses in the bm12 SLE model To assess whether STING has a broader role in the priming of adaptive immune responses to dying cells, we assessed the induction of CD4+ T cell and B cell responses in the Klarquistbm12-cGVHD et al. Figure model 8 where H-2b B6 hosts develop lupus-like disease upon transfer of B6.C-H2bm12 CD4+ T cells (29). Both IFNAR-/- and STING-/- mice developed considerably A B Tfh plasma cells

3.08 38.3 10 ) 15 6 0

WT 1 * * x

( * 8 * )

6 + een 0 l 1

p 10 FIGURE 8. STING regulates CD4

1.32 s x 9 / ( 6

ll s T cell and B cell responses in the e c een l IFNAR p T

4 bm12 SLE model. (A) Flow cytomet- s / 5 +

Tf h ric analysis of Tfh (gated on CD4 T CD 4

0.314 2 PD-1 4.78 CD138 cells) and plasma cells (total spleen) STING -/- 0 CD 69 + 0 in spleens of WT, STING , and IF- T R T G R 1 1 1 G 1 1 1 -/-

- - - - - A - A N W N W I I N N NAR mice 14 d after i.p. transfer of T T F F I S I S 0.364 3.24 live bm12 splenocytes. (B) Number + WT of splenic Tfh and activated CD4 T naive cells in the spleen of indicated mouse strains. (C) Number of plasma cells CXCR5 CD19 and activated B cells in the spleen of C D indicated mouse strains. Represen-

15 30 6 40 tative data of one experiment (out )

) * ) s

) *

* 6 s 6 of three to five) are shown. (D) An- 0 * 0

* 1 *

1 uni t

uni t x ( x f. ti-dsDNA IgG1 and IgG2a levels in in-

( 30 f. 10 20 4 een

l dicated mouse strains (mean 6 SEM, (r e p 1 pleen 2a (r e s / s G / G

g 20 n = 10–22, *p , 0.05). ll s g I e I ell s c

5 B 10 a 2 DN A DN A m s s

d 10 - d i la s - t i t n P n CD 69 + A A 0 0 T R T G R 0 G 0

1 1 1 1 1 1 T T R R A 1 1 1 G G

- - A - - - - N 1 1 1 W

N - - - W - - - I I A A N N N W N W I T I T N F N F I T S I T S F F I S I S

137 less activated CD4+ T cells and T follicular helper cells than WT recipients upon transfer of bm12 CD4+ T cells (figure 8a/b). Moreover, both IFNAR-/- and STING-/- mice developed considerably less activated B cells, plasma cells and pathogenic anti-dsDNA IgG2a antibodies than WT recipients (figure 8a/c/d). Given that the transferred bm12-CD4+ T cells were IFNAR- and STING-sufficient, these data further support the role for antigen presenting cell-intrinsic STING and IFNAR in the induction of adaptive immune responses to dying cell-derived antigens.

138 Discussion Type I IFNs have been implicated as the upstream events precipitating autoimmune disease and a prerequisite for effective anti-tumor radiotherapy. Here we identify DC sensing of cell-derived nuclear DNA entities via the STING/IRF3 pathway as a key component in the early type I IFN response to dying cells.

Dying cells can emit a plethora of structurally distinct DAMPs and it is likely that the molecular pathways involved in the sensing of these DAMPs are equally diverse. While many DAMPs can contribute to the final adaptive immune response to cell-associated antigens, our data identified type I IFN as the dominant pro-inflammatory factor and STING/IRF3 signaling as the principle pathway in the initiation of the immune responses to cell-associated antigens in our tumor models as well as the autoimmune responses in our SLE model. Although all nucleated cells can sense type I IFN and type I IFN has been shown to directly act on T cells, our data indicate that the early STING/IRF3-mediated type I IFN predominantly acts on DCs. Transfer of IFNAR-/- DCs (pulsed with irradiated cells) into WT recipients resulted in similar deficiencies in CD8+ T cell expansion, functionality and memory formation as the direct immunization of IFNAR-/- mice. Moreover, immunization of WT/IFNAR-/- mixed bone marrow chimeric mice did not show any significant difference in CD8+ T cell clonal expansion or polyfunctionality between the WT and IFNAR-/- grafts. Im- portantly, transfer of STING-/- or IRF3-/- DCs into WT recipients resulted in similar defects in CD8+ T cell responses as the transfer of IFNAR-/- DCs. Likewise, STING-/- recipients showed identical reduction in Tfh cell and plasma cell formation as IFNAR-/- recipients in our SLE model. Together with the observation that STING-/- and IRF3-/- DC have significantly reduced type I IFN induction upon phagocytosis of dying cells, these data implicate that the STING/IRF3 pathway is the critical component in the type I IFN-dependent T cell priming to cell-associated antigens.

139 It has been suggested that different types of death may induce different DAMPs. We observed comparable type I IFN induction and STING/IRF3 engagement in DCs upon phagocytosis of cells treated with gamma irradiation, UV irradiation, Fas-crosslinking antibody, or etoposide, suggesting that these different types of cell death generated a similar nuclear DNA-derived DAMP (figure S2b, and not shown). It is also likely that similar nuclear DNA-associated DAMPs become available in vivo as type I IFN induction and type I IFN-dependent CD8+ T cell priming was readily observed in WT and MyD88/Trif deficient mice, but significantly reduced in STING-/- and IRF3-/- mice upon administration of dying cells (gamma, UV, or FAS-treated) or upon in vivo tumor cryo-ablation (11, 22).

Importantly, the crucial role for type I IFN in the priming of protective adaptive anti-tumor responses is not restricted to situations where massive tumor cell death occurs, as is the case for radiotherapy, chemotherapy, and cryoablative tumor therapies. Recent publications indicate that spontaneous and limited tumor cell death in tumor-bearing mice also resulted in type I IFN-dependent protective immune responses. Fuertes and Diamond showed spontaneous anti-tumor CD8+ T cell induction and tumor rejection in tumor-bearing mice that was critically dependent on type I IFN sensing by cross-priming DCs (6, 7). In this light, it is interesting to notice that STING-/- mice—like IFNAR-/- mice—develop significantly more lung metastases than WT mice upon i.v. injection of low numbers of untreated B16 melanoma cells, illustrating a role for the STING/IFNAR nexus in the antitumor response when cell death is limited (not depicted).

STING can facilitate innate responses to cytosolic bacterial cyclic dinucleotides (c-di- GMP) (30, 31), dsDNA and in some cases cytosolic dsRNA (26-28). Our data strongly suggest that the main type I IFN-inducing ligand is a nuclear DNA species. STING-mediated dsRNA sensing requires RNA with 5’-triphosphate groups in combination with the IPS-1/RIG-I pathway. The absence of IPS-1 recruitment to STING in WT DCs upon

140 phagocytosis of cellular materials as well as the normal type I IFN production and CD8+ T cell responses in IPS1-/- mice, effectively argue against a role for dsRNA sensing in the STING/IFN phenotype. Our hypothesis that the type I IFN inducing ligand is a DNA structure is strongly supported by our in vitro data that show significantly reduced type I IFN induction upon addition of DNAses to the dying cell/DC co-culture. Moreover, the use of enucleated cells dramatically reduced type I IFN production and cross-priming by WT DCs in vitro. Importantly, the latter experiment also suggested that mitochondrial or ribosomal nucleotide structures had no notable role in the type I IFN production as reticulocytes—enucleated but still containing mitochondria and ribosomes—failed to induce type I IFN.

Recent studies indicate direct binding of c-di-GMP and cyclic-GMP-AMP (cGAMP) to STING but have not provided evidence for direct dsDNA-STING interactions (32, 33) suggesting the involvement of upstream DNA sensors. Over the last few years several of candidate sensors have been identified, including cyclic GMP-AMP synthase (cGAS), which has been shown to signal through STING via the production of cGAMP(34-37). DExD/H-box protein family member DDX41 and IFI16 (p204) have also been implicated as possible DNA sensors acting through STING, but their precise molecular interactions have not been fully elucidated (38, 39). At present these candidate DNA sensors are studied in in vitro systems where the DNA is directly delivered into the cytosol via transfection, transduction or infection pathways. However, in order for the phagocytosed DNA-derived structures to be sensed by the STING pathway, either its key components should be recruited to the phagosome or the DNA-derived species should escape into the cytosol. Although STING can translocate from the ER to the Golgi and autophagosome-like compartments, we and others did not observe STING in phagosomes or phagolysosomes (not shown) (40-44). However, phagosomal DNA sensing via STING could still be possible by phagosomal recruitment of p204 that has reported migratory capacity or cGAS

141 that produces the highly mobile secondary messenger cGAMP (34, 36, 39). On the other hand, phagosomal escape is a well reported process in cross-presentation where protein structures escape into the cytosol to be processed for presentation in MHC class I (20, 45). The exact mechanism by which proteins escape into the cytosol is not known but it is strongly associated with alkalinization of the phagosome and prevention of phagosomal acidification (20, 45, 46). Consistent with the latter possibility, STING-mediated type I IFN production was strongly associated with inhibition of phagosomal acidification (45); in vitro treatments of DCs with agents that accelerated phagosomal acidification decreased type I IFN production while alkalinization or the delay of endosomal acidification significantly enhanced type I IFN production (figure S3). Moreover, we found that DC populations that have the greatest capacity for cross-presentation and slowest phagosomal acidification rate also produced the most type I IFN upon phagocytosis of dying cells (data not shown and (11, 12, 47)).

While the exact mechanism by which the nuclear DNA-derived structure activates the STING pathway needs further elucidation, our data strongly demonstrate its potent role in anti-tumor immunity and autoimmunity. Our observations are in line with the findingsthat mice lacking DNAse II, responsible for degradation of phagocytosed DNA, die of TLR-independent pro-inflammatory cytokine production unless the mice are crossed to the IF- NAR-/- or STING-/- background (48-51). Intriguingly, gain of function mutations in STING were recently associated with vasculopathy with onset in infancy (SAVI), a syndrome characterized by a severe cutaneous vasculopathy leading to extensive tissue loss and structural damage, with neonatal-onset systemic inflammation(52). Moreover, the deletion of TREX1 –DNAse III, a DNA exonuclease with functions in DNA degradation– was shown to trigger type I IFN-associated inflammatory responses in a cGAS-dependent manner(53, 54). Furthermore, mutations in TREX1 have been associated with a variety of (multi-organ) inflammatory syndromes, including SLE, Sögrens Syndrome, chilblain

142 lupus, retinal vasculopathy, and Aicardi-Goutieres syndrome(53-60).

Together our data indicate that sensing of nuclear DNA-derived structures via the STING/ IRF3 pathway in DCs is responsible for the early type I IFN induction upon phagocytosis of dying cells. This early type I IFN directly acts on the DCs and endows them with greater capacity to activate adaptive immune responses to cell-associated antigens. Given that type I IFNs have been implicated as the upstream events precipitating autoimmune disease and a prerequisite for effective anti-tumor therapy further characterization of the STING pathway as sensor of dying cell-derived DNA could enable the rational design of new therapies to enhance anti-tumor responses and interfere with the development and progression of autoimmune diseases.

Acknowledgments We are grateful to Dr. H. Singh for comments and discussion on the manuscript; Dr. T. Kalfa for providing reagents and advice for the in vitro erythropoiesis experiments; A. White and M. DeLay for support with the Amnis Imagestream; and the Research Flow Cytometry Core at Cincinnati Children’s Hospital Medical Center.

This work was supported by the National Institutes of Health via National Cancer Institute grant CA138617 (E.M.J.) and National Institute of Diabetes and Digestive and Kidney Diseases grant DK090978 (J.K./E.M.J.) and the Charlotte Schmidlapp Award (E.M.J.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

143 References

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149

Chapter 6: Type I interferon protects CD4 T cells from NK cell killing in a cGVHD model of SLE*

*The following manuscript is in preparation for submission. Klarquist J, Hennies CM, Lehn MA, and Janssen EM.

150 Abstract

Myriad studies have linked type I interferon (IFN) to the pathogenesis of autoimmune diseases, including systemic lupus erythematosus (SLE). While increased levels of type I IFN are found in patients with SLE, and IFN blockade ameliorates disease in many mouse models of lupus, its precise roles in driving SLE pathogenesis remain largely unknown. Here, we dissected the role of type I IFN on disease development using the bm12 cGVHD model of SLE, where IAb (C57BL/6) mice develop SLE-like disease upon transfer of IAbm12 (bm12) CD4 T cells. Our data show increased serum levels of type I IFN over time, concomitant with the development of T follicular helper cells (Tfh), germinal center (GC) B cells, plasmablasts, and anti-nuclear antibodies (ANA). Previously, we showed that these disease parameters were significantly reduced in IFN-α receptor-deficient (If- nar -/-) recipient mice, indicating an important role for type I IFN sensing by non-T cells. In this study, we assessed the effects of type I IFN sensing by CD4 T cells on the development of bm12 disease. Surprisingly, transfer of highly purified Ifnar -/- bm12 CD4 T cells into WT C57BL/6 hosts resulted in poor expansion of the transferred T cells and limited development of GC B cells, plasmablasts, and ANA, indicating a need for IFN sensing by CD4 T cells. Transfer into perforin-deficient animals, or antibody-mediated natural killer (NK) cell depletion restored the expansion of Ifnar -/- CD4 T cells and downstream sequelae, whereas the depletion of CD8 T cells had no effect on disease. These findings suggest a novel mechanism by which type I IFN contributes to autoimmune disease is by regulating the susceptibility of pathogenic CD4 T cells to NK cell killing, thus providing further rationale for the development of anti-IFNAR therapeutics for the treatment of SLE.

151 Introduction The overproduction of type I IFN is a prominent feature associated with the development of SLE and has been implicated in the pathology of other autoimmune diseases including Sjögren’s syndrome, systemic sclerosis, adult-onset rheumatoid arthritis, and possibly type I diabetes mellitus1,2. A role for type I IFN in driving disease pathology has been demonstrated in several genetic and inducible murine models of SLE3–6. Moreover, the therapeutic use of IFN to treat patients with hepatitis C virus and cancer has been associated with the induction of SLE7–9, and the administration of IFN to lupus-prone mice induced earlier onset, lethal disease10. Furthermore, a type I IFN gene signature correlates with disease severity in SLE patients11,12. While these studies strongly implicate type I IFN in promoting SLE pathogenesis, relatively little is known about the precise functions of IFN in SLE.

Type I IFN comprises 13 IFNα proteins, IFNβ, IFNκ, and IFNω, all of which signal through a common receptor, known as the interferon (alpha and beta) receptor, or IFNAR. IF- NAR is expressed by essentially all nucleated cells and plays well described, key roles in antimicrobial defenses by conferring direct antiviral effects, inhibiting cellular growth, controlling apoptosis, and by promoting antimicrobial immune responses13. In SLE, one prevailing hypothesis is that by some combination of genetic and environmental factors, an accumulation of dying cells leads to increased exposure of self-RNA and self-DNA, which induces high levels of IFN production by plasmacytoid dendritic cells (DCs)14–17. Relatively few studies, however, have sought to characterize the mechanism of action of IFN specifically in SLE. Studies of SLE peripheral blood-derived DCs by Blanco et al. indicated a likely role of IFN sensing by DCs in SLE pathogenesis18. And, although the role for type I IFN sensing by B cells has not been specifically examined in the context SLE, it may also be important, given that type I IFN is known to promote B cell activation, class switching, and support the generation of antibody secreting plasma cells19–21.

152 CD4 T cells have been shown to provide vital B cell help during SLE development22–25, and several studies have demonstrated that type I IFN sensing by CD4 T cells can dramatically enhance their priming in the context of certain viral infections and vaccines20,26,27. Additionally, total disruption of type I IFN signaling nearly completely abrogated disease in several mouse models of SLE3–6, whereas in our previous studies we observed only partial reduced disease reduction in Ifnar-deficient recipients of WT bm12 CD4 T cells. We therefore investigated the potential role for type I IFN sensing by CD4 T cells in the bm12 chronic graft-versus-host disease model of SLE, a well established murine model of SLE with clinical signs that correspond to those of SLE patients, including the development of ANA, lupus nephritis, and a recognized role for type I IFN28–30. Here we show that type I IFN acts directly on CD4 T cells to dramatically increase the expansion of T follicular helper cells (Tfh), GC B cells, plasmablasts, activated B cells, and the development of ANA in the bm12 chronic graft-versus-host disease model of SLE. Surprisingly, we found that IFN-insensitive Tfh were selectively killed by NK cells, and the specific depletion of NK cells restored their expansion and allowed normal disease development. Our data provide evidence for novel roles of type I IFN and immunoregulatory NK cells in SLE, providing potential new targets for the development of future immunotherapies.

153 Results IFN sensing by CD4 T cells is critical to the expansion of donor CD4 T cells and pathogenic B cell subsets in the bm12 cGVHD model of SLE Previously, we found that upon the transfer of bm12 cells, development of SLE-like disease was dependent upon recipient expression of the type I IFN receptor (Ifnar)30. Recip- ient mice lacking Ifnar showed reduced expansion of Tfh, plasmablasts, and anti-nuclear antibodies (ANA). In order to better understand the function of type I IFN in this model, we investigated the kinetics of IFN production and the role of IFN sensing by transferred CD4 T cells.

Using a highly sensitive bioassay, we found that type I IFN increased over time in the serum of C57BL/6 mice injected with bm12 CD4 T cells. Moreover, we observed a corresponding increase in the serum levels of the type I IFN-inducible chemokines CXCL9 and CXCL10 (Fig1a, and FigS1a-c). Additional inflammatory cytokines including TNFα, IL-12, and the type II IFN, IFNγ were also induced, though these were present in relatively lower quantities and at generally delayed kinetics compared to the type I IFNs and the IFN-inducible chemokines (Fig 1a, and FigS1d-g).

To explore additional possible roles for type I IFN in SLE, we next asked whether or not IFN sensing by CD4 T cells was important for driving disease development in the bm12 model. We generated CD45.1+ congenic bm12 mice lacking Ifnar, hereafter referred to as Ifnar -/- bm12 mice. Highly purified CD4 T cells from either wild type bm12 mice (also CD45.1+) or Ifnar -/- bm12 mice were adoptively transferred into C57BL/6 recipients, and after two weeks, mice were assessed for disease development. Surprisingly, we found a 3-fold greater accumulation of WT bm12 CD4 T cells compared to Ifnar -/- bm12 CD4 T cells (Fig. 1b,c). B cell responses in these mice were similarly affected. Specifically, we observed significant reductions in splenic plasmablasts (CD138+B220low), germinal cen-

154 a. b. 4.89 c. TT cell cell graft g. SpleenSpleen mass 15 bm12 CD4 400 Days: 4.89 1.41 *

WT *** genotype: 0 1 2 3 4 5 6 7 9 11 14 ifnar

WT 300 WT

IFNα/β 6 6 10 -/- CXCL9 Ifnar CXCL10 1.41 200

TNFα (mg) (mg)

IFNγ CD4 4.89 1.41 -/- Cells x 10 IL-12(p40) Ifnar Cells x 10 5 Viability dye 100 CD4

CD45.1 0 0

CD69++ B cells IgG IgGANAANA IgG IgGANAANA d. e. PlasmablastsPlasmablasts GCGC B cells CD69 B cells f. 1 IgG1 1 IgG2a 2a2a 8 4 * 20 80 80 150150

** * * * 6 3 15 60 60 ) 6 6 6 6 100100

4 2 10 40 (ref. units) 40 CD138 GL-7 Cells x 10 Cells x 10

B220 CD95 (Fas) Cells (x 10 Cells x 10 50 50 Anti-dsDNA (ref. units) (ref. Anti-dsDNA units) (ref. Anti-dsDNA 2 1 5 20 20 units) (ref. Anti-dsDNA units) (ref. Anti-dsDNA Anti- dsDNA

0 0 0 0 0 0 0

Figure 1. Type I IFN sensing by CD4 T cells is critical for bm12 disease. C57BL/6 mice were injected with 8 x 106 purified WT bm12 CD4 T cells. At the indicated days after injection, serum type I IFN was analyzed by bioassay and additional cytokines and chemokines were analyzed by multiplex technology (a). In separate experiments, C57BL/6 mice were injected with 8 x 106 purified CD45.1+ WT or Ifnar -/- bm12 CD4 T cells (n=11/group) and mice were sacrificed after 14 days b-f( ). Representative flow cytometry plots depict the gating strategy for analysis of splenic bm12 CD4 T cells within C57BL/6 recipient mice (b). The absolute number of splenic bm12 CD4 T cells 14 days after transfer (c). Representative splenic B cell population gating (d). B cell populations were first gated on live cells, as in (b). Plasmablasts were then defined as CD138+B220low, GC B cells were B220+CD138−Fas+GL-7+, and activated B cells were B220+CD138−GL-7− CD69+. Splenomegaly was assessed by comparing spleen mass (f). Serum anti-dsDNA antibodies were assessed by ELISA. Data are combined from 3 representative experiments, depicting mean ± SEM, where *p<0.05, **p<0.01, and ***p<0.001 by the student’s t test.

ter (GC) B cells (B220+CD138−Fas+GL-7+), activated B cells (B220+CD138−GL-7−CD69+), and serum anti-dsDNA IgG in animals receiving Ifnar -/- CD4 T cells (Fig. 1d-f). Further- more, splenomegaly, a parameter associated with overall disease activity in this and other models of SLE, was also reduced in recipients of Ifnar -/- CD4 T cells. (Fig. 1g).

WT and Ifnar -/- bm12 CD4 T cells both differentiate into T follicular helper cells Next, we sought to determine whether type I IFN sensing controlled the fate of bm12 helper T cell differentiation. Previously, we showed that proliferating bm12 CD4 T cells adopted a T follicular helper cell (Tfh) phenotype as early as three days post transfer

155 a. b. Tfh

Tfh Sample 150 % bm12Gate CD4

WTFemale_WT_346R_028.fcs 44.4genotype:Graft IfnarFemale_IFNAR_347R_032.fcs -/- 9.2ifnar Graft -/-

p=0.94 WT Figure 2. WT and Ifnar bm12 CD4 T Non-Female_WT_346R_028.fcsTfh 63.6WT Non-Tfh 100 Ifnar -/- cells both differentiate into Tfh. Repre- sentative gating for Tfh within bm12 cells

Bcl-6 50 14 days after transfer into C57BL/6 recipients, where cells were first gated on

% of proliferated donor cells proliferated of % + + PD-1 live, CD4 CD45.1 as in Fig. 1b (a, left). CXCR5 % of proliferated donor cells 0 Representative intracellular Bcl-6 protein expression within WT and Ifnar -/- bm12 c. Pdcd1Pdcd1 Cxcr5Cxcr5 Bcl6Bcl6 50 15 8 bm12 CD4 Tfh, or total, healthy C57BL/6 mouse

genotype: + 40 ifnar CD4 (“non-Tfh”) control cells (a, right).

6 WT -/- 10 WT WT and Ifnar bm12 were labeled with a 30 Ifnar -/- 4 violet proliferation dye prior to transfer into 20 5 Relative RNA levels RNA Relative levels RNA Relative Relative RNA levels RNA Relative C57BL/6 recipients; 14 days later, prolif- 2 Relative mRNA 10 erating cells were identified by their vio- 0 0 0 let dye dilution. The percentages of Tfh Days 0 14 0 14 0 14 post inj. within the proliferated bm12 cells (n=5/ IcosIcos Il21Il21 Ccr7Ccr7 group) were then determined (b). RNA- 15 150 1.2 seq analysis of several genes commonly

associated with Tfh was performed on 10 100 0.8 purified splenic bm12 immediately prior to transfer and sorted on live CD4+CD45.1+ 5 50 0.4 Relative RNA levels RNA Relative Relative RNA levels RNA Relative Relative RNA levels RNA Relative bm12 cells by flow cytometry 14 days af- Relative mRNA ter transfer (n=2/group). 0 0 0.0 Days 0 14 0 14 0 14 post inj. into C57BL/6 recipients31. Here, both WT and Ifnar -/- bm12 CD4 T cells differentiated into Tfh, expressing high levels of PD-1, CXCR5, and the master regulator transcription factor, Bcl-6 (Fig. 2a). To specifically analyze those cells which were actively dividing, we also performed experiments where sorted bm12 CD4 T cells were labeled with a violet proliferation dye prior to transfer into recipient animals. After 2 weeks, essentially all of the violet dye-diluted, proliferating bm12 CD4 T cells were identified as Tfh, regardless of their genotype (Fig. 2b); this result was of particular importance, given recent contrasting reports on the effect of type I IFN on Tfh differentiation32,33. Furthermore, mRNA levels were equivalently upregulated for the prototypical Tfh genes Pdcd1, Cxcr5, Bcl6, Icos, and Il21, whereas Ccr7 was downregulated in both WT and Ifnar -/- bm12 CD4 T cells (Fig. 2d). Taken together, these data indicate that type I IFN insensitivity did not block differentiation of the transferred Ifnar -/- cells into Tfh.

156 Type I IFN acts directly on CD4 T cells to improve their expansion Because Tfh and GC B cell responses are reciprocally supportive of one another34, we considered the possibility that type I IFN may have acted indirectly to promote the expansion of bm12 Tfh. That is, IFN sensing by bm12 CD4 T cells may have caused changes within the bm12 Tfh that better supported a germinal center B cell response. In turn, the boosted GC B cell response could have resulted in enhanced Tfh expansion. To determine whether type I IFN directly or indirectly enhanced CD4 T cell expansion, we transferred both WT and Ifnar -/- CD4 T cells into the same recipient mice, where they would have access to the same environment. Here, CD45.2 WT bm12 CD4 T cells were combined with CD45.1 Ifnar -/- bm12 CD4 T cells at a 1:1 ratio and transferred into CD45.1/2 recipient mice; for comparison, single transfers of only WT or Ifnar -/- cells were also performed using CD45.1/2 recipients (Fig. 3a). Splenic plasmablast, GC, and activated B cell populations were significantly greater in mice which received bm12 CD4 T cells from

a. Immediately prior to transfer c. 14 days post transfer WT Ifnar -/- Mix WT Ifnar -/- Mix 49.0

50.9 CD45.2 CD45.2 CD45.1 CD45.1

b. PlasmablastsPlasma cells GCGC B B cells CD69CD69++ B Bcells d. TfhTfh 10 3 16 8 bm12 CD4

*** ** genotype: 8 ifnar

*** 12 6 * WT WT 6 6 6 6 6 2 6 -/- 6 Ifnar 8 4 4 Cells x 10 Cells x 10 Cells x 10 Cells x 10 Cells x 10 1 Cells x 10 4 2 2

0 0 0 0 -/- -/- -/- WT Ifnar Mix WT Ifnar Mix WT Ifnar Mix Individual Mix injections

Figure 3. Type I IFN acts directly on Tfh to enhance their accumulation. Eight million WTCD45.2 and -/- Ifnar CD45.1 bm12 CD4 T cells were transferred separately (a, left/middle) or together “Mix” (a, right) into

WTCD45.1/2 recipient animals. After 14 days, responding B cells were enumerated (b) and bm12 cells from distinct donors were discriminated by congenic marker expression (c). The total numbers of bm12 Tfh were compared between recipients of either WT bm12, Ifnar -/- bm12, or a equal mixture of both (d). Data are from one representative of three independent experiments, depicting mean ± SEM, where *p<0.05, **p<0.01, and ***p<0.001 by the student’s t-test. A paired t-test was used to compare Tfh within the “Mix” in (d).

157 both WT and Ifnar -/- donors (mix) compared to those which received Ifnar -/- bm12 CD4 T cells alone, but were no different from those which received only WT bm12 CD4 T cells (Fig. 3b). In the mice which received cells from both donors, Ifnar -/- CD4 T cells had access to the same B cells as did their WT counterparts; yet, we still observed a significantly greater accumulation of WT cells over Ifnar -/- cells, demonstrating a direct effect of type I IFN on CD4 T cell accumulation (Fig. 3c-d).

IFN sensing does not prevent grafting To determine whether type I IFN sensing improved the initial grafting of WT over Ifnar -/- CD4 T cells, which could have thereby significantly contributed to the enhanced accumulation of the WT Tfh, we transferred an equal mixture of CD45.2+ CD90.2+ WT and CD45.1+ CD90.2+ Ifnar -/- CD4 T cells into CD45.2+ CD90.1+ recipient mice. The cells used here were from mice which had not been crossed to the bm12 background, so they had proliferated only nominally, eliminating the potential confounding effects of divergent proliferation rates (data not shown). At one and two weeks post transfer, the CD4 T cells had not deviated from their initial 1:1 ratio in the spleen nor in the blood (Fig. S2), indicating that WT and Ifnar -/- CD4 T cells had grafted and persisted equally in this non-inflammatory setting.

Next, we confirmed there were no grafting disparities in the context of bm12 disease. CD4 T cells from WT or Ifnar -/- bm12 donors were labeled with a violet proliferation dye and injected into C57BL/6 hosts. The non-proliferated cells (proliferation dye-positive), which represent the majority of the transferred bm12 cells that do not react to recipient IAb, were enumerated 2 weeks post transfer. Indeed, the number of non-proliferated WT and Ifnar -/- bm12 CD4 T cells were equal despite a reduced accumulation of proliferating cells (Fig. 4), indicating that the donors cells had also grafted equally in the context of the inflammation associated with bm12 disease.

158 Figure 4. Equivalent grafting of WT and Ifnar -/- bm12 CD4 T cells. Bm12 cells were + + Non-proliferated a. CD4 CD45.1 bm12 b. Non-proliferated graft bm12 labeled with a violet proliferation dye prior to

0.6 ifnar transfer into C57BL/6 recipients, and the vi-

-/- p=0.79 WT WT Ifnar WT olet dye dilution was assessed 14 days lat- Ifnar -/- 6 6 0.4 er (a). Although proliferating WT bm12 cells accumulated significantly more than prolifer- -/- Cells x 10 0.2 ating Ifnar bm12, the total number of violet Cells x 10

PD-1 dye-positive, non-proliferating cells remained Violet proliferation dye equal, indicating equivalent grafting and per- 0.0 sistence among CD4 T cells from both geno- types (b). Data are from 1 representative of two independent experiments.

IFN inhibits ongoing proliferation of mouse CD4 T cells in vitro In vivo proliferation data can be skewed by silent clearance of dying cells or migration away from target organs; consequently, we examined the effect of IFN sensing on CD4 T cell proliferation in vitro. Highly purified CD4 T cells from WT and Ifnar -/- donors were combined at a 1:1 ratio in 96-well plates and stimulated with anti-CD3 and anti-CD28. WT and Ifnar -/- cells were distinguished from one another using congenic markers. Cells were cultured in the absence of exogenous IFN, or with the addition of IFNβ at 0, or 24 hours after culture initiation, and all cells were harvested after a total of 72 hours in culture. IFNβ inhibited the proliferation of activated WT, but not Ifnar -/- CD4 T cells (Fig. 5), and a comparable result was observed with IFNα (Fig. S3). These data demonstrated that the anti-proliferative effect of IFN involved direct signaling within the CD4 T cell, since the WT and Ifnar -/- cells were co-cultured, and IFN had no effect on Ifnar -/- proliferation.

Furthermore, the ongoing proliferation of murine CD4 T cells was inhibited by type I IFN, as equivalent results were obtained from cultures where IFN was added immediately upon culture initiation and those in which IFN was added 24 hours later (Fig. 5). These data were seemingly at odds with the phenomenon observed in vivo, where IFN sensing allowed for the increased accumulation of WT CD4 T cells, we therefore shifted our focus toward the potential effect of type I IFN on the survival of these cells.

159 WT Ifnar -/- Figure 5. CD4 T cell proliferation is inhibited by type I IFN in vitro. Highly purified CD4 T cells from NoLegend IFN -/- WTCD45.2 and Ifnar CD45.1 mice were labeled with a vi- IFNLegendβ @ 0 h olet proliferation dye and combined at a 1:1 ratio in Legend Legend 24 well tissue culture plates. Cells were stimulated Legend with plate-bound anti-CD3 and soluble CD28 in the IFNLegendβ @ 24 h presence or absence of recombinant IFNβ, which was administered at the initiation of the culture (top panels), or at 24 h after culture initiation (bottom

Counts panels). Data are from 1 representative of 3 inde- Violet proliferation dye pendent experiments.

Ifnar -/- CD4 T cells show no cell-intrinsic survival disadvantage Prior work on IFN has demonstrated a role for IFN in keeping activated T cells alive35. We considered that this mechanism may have contributed to the impaired accumulation of Ifnar -/- CD4 T cells in our bm12 model, so we performed experiments measuring the survival of our highly active bm12 CD4 T cells directly ex vivo. One week after transferring CFSE-labeled WT or Ifnar -/- bm12 CD4 T cells into C57BL/6 recipients, splenocytes were plated for 24 hours in medium containing serum, but without the addition of T cell activating factors. Survival was determined by comparing the number of live, proliferating bm12 cells directly ex vivo, to the number of live, proliferating bm12 cells remaining CTV- graft d7 CTV+ graft d7 Host CD4 d7

3000 3000 3000 a. 60 No primary No Bcl-X Bcl2A1 Bim Bcl-2 primary No Bcl-X Bcl2A1 Bim Bcl-2

No primary No Bcl-X Bcl2A1 Bim

WT Bcl-2

0 -/- p=0.53 0

Figure 6. WT and Ifnar bm12 CD4 T cells dis- IfnarIFNAR -/- -/- 0 play equivalent survival and Bcl-2 family member expression ex vivo. Bm12 cells were labeled 40

2000 2000 with a violet proliferation dye prior to 2000transfer into

1000 1000 C57BL/6 hosts. Seven days after transfer, recip- 20 1000 MFI MFI MFI ient splenocytes were plated in complete medium MFI MFI % surviving 24h culture containing fetal bovine serum with or without 50 U/ MFI

1000 1000 ml recombinant IFNβ. Survival of the1000 violet-dye 0

2000 2000 diluted, proliferating bm12 cells was determined by No IFN ++IFN IFNββ 2000 calculating the number of proliferating cells plated,

dividing that number by the number of proliferating b. ProliferatingCTV- graft bm12 d7 Non-proliferatingCTV+ graft d7bm12 /- IFNAR 3000 -

0 0 cells remaining after 24 h, and multiplying0 by 100% WT

Bcl-2 Bim Bcl2A1 Bcl-X No primary Bcl-2 Bim Bcl2A1 Bcl-X No primary Bcl-2 Bim Bcl2A1 Bcl-X No primary WT

3000 3000

(a). Proliferating bm12 and non-proliferating bm12 Ifnar -/- 3000

CTV+ graft d7 graft CTV+ d7 graft CTV- cells were also assessed by flow cytometry direct- 2000 d7 CD4 Host ly ex vivo for pro- and anti-apoptotic Bcl-2 family member protein expression (b). Data are from 1 MFI representative of 2 independent experiments, de- 1000 picting mean ± SEM. 0

Bim Bim Bcl-2 Bcl-X No 1° Bcl-2 Bcl-X No 1° Bcl2A1 Bcl2A1

160 after 24 hours of in vitro culture. WT and Ifnar -/- bm12 CD4 T cells survived ex vivo culture equally in the absence of exogenous IFN. Although the addition of IFNβ slightly increased the survival of WT cells, this increase was not significant Fig.( 6a). Another method we employed to identify a possible survival disadvantage in Ifnar -/- cells was to analyze the expression of Bcl-2 family member proteins of proliferating bm12 cells directly ex vivo. Intracellular flow staining revealed an altered pattern of Bcl2 family member expression among proliferating (CFSE-negative) bm12 CD4 T cells compared to non-proliferating (CFSE-high) cells. Most notably, proliferating cells expressed high levels of the anti-apoptotic Bcl2A1 protein, which is suspected to play an important role in keeping activated CD4 T cells alive36,37; however, no differences were noted between WT and If- nar -/- cells (Fig. 6b). Together, these data demonstrated that Ifnar -/- bm12 CD4 T had no intrinsic survival defect compared to their WT counterparts.

IFN protects Tfh from perforin-mediated cell death We postulated that, since type I IFN imparted no obvious cell-intrinsic survival advantage, IFN may be protecting Tfh from cell-extrinsic pressure, namely, killing by NK cells or CD8 T cells. Therefore, we transferred WT or Ifnar -/- bm12 CD4 T cells into C57BL/6 or perforin-deficient (Prf1-/-) recipients. In C57BL/6 recipients, we again saw a 3-fold greater expansion of WT over Ifnar -/- bm12 Tfh. Transfer into Prf1-/- recipients, however, not only improved the expansion of Ifnar -/- cells, but it resulted in a significantly greater accumulation of Ifnar -/- Tfh than WT Tfh (Fig. 7a), perhaps now revealing an anti-proliferative effect of type I IFN in vivo similar to that which was observed in vitro. The enhanced expansion of Ifnar -/- Tfh in Prf1-/- animals dramatically augmented overall disease in these animals, including increases in plasmablasts, GC, and activated B cells, splenomegaly, and serum ANA (Fig. 7b-d).

161 a.Tfh (JK1533 onlyTfh - no staining JK1539)c. Spleen mass 30 600 bm12 CD4

**** *** genotype: *** p=0.06 ifnar

** WT WT -/- Figure 7. Type I IFN protects bm12 6 20 400 Ifnar 6

Tfh from extrinsic, perforin-mediated destruction. WT or Ifnar -/- bm12 CD4 (mg) Cells x 10 x Cells

Cells x 10 200 T cells were transferred into C57BL/6

10 (mg) mass Spleen or Prf1-deficient animalsa-d ( ). Two weeks after transfer, comparisons 0 0 were made between the total number C57BL/6 Prf1-/- C57BL/6 Prf1-/- of bm12 Tfh (a), plasmablasts, GC B b. PlasmablastsPlasma cells GCGC B B cells CD69CD69++ B B cells cells, and activated B cells (b), spleno- 6 p=0.08 32 20 *** ** megaly as defined by spleen mass (c), * p=0.05 p=0.08 and anti-dsDNA antibodies (d). Data are 15 24 from two representative experiments

6 4 6 6 6 (n=4-8/group), depicting mean ± SEM, 10 16 where *p<0.05, **p<0.01, ***p<0.001, Cells x 10 x Cells Cells x 10 x Cells Cells x 10 x Cells

Cells x 10 2 ****p<0.0001 by the student’s t-test. 5 8

0 0 0 C57BL/6 Prf1-/- C57BL/6 Prf1-/- C57BL/6 Prf1-/-

IFN protects Tfh from NK cell killing in bm12 lupus-like disease Since the two most obvious candidates for perforin-mediated cell killing are CD8 T cells and NK cells, we decided to deplete these two cell subsets in separate experiments. NK cells were specifically depleted by i.p. administration of anti-asialo GM1 antibodies prior to the transfer of bm12 CD4 T cells from WT or Ifnar -/- mice (ref38,39 and Fig. S4). NK cell depletion resulted in a significantly increased accumulation ofIfnar -/- bm12 Tfh compared to that in control, NK-sufficient animals Fig.( 8a). Although a subtle increase in WT bm12 Tfh was also seen upon NK cell depletion, this was not significant. As in experiments using Prf1-/- recipients, Ifnar -/- bm12 CD4 T cells transferred to NK-depleted recipients resulted in augmented signs of SLE-like disease, including activated B cell subsets, splenomegaly, and ANA (Fig. 8b-d). Highly efficient, specific depletion of CD8 T cells was achieved by i.p. injection of an anti-CD8β antibody (Fig. S5a); however, this had no effect on the expansion of Tfh (Fig. S5b). These data indicate that NK cells killed Ifnar -/- Tfh in a perforin-dependent manner, and that type I IFN sensing by WT Tfh protects them from NK killing and thereby promotes Tfh expansion and resultant disease in this cGVHD model of SLE.

162 a. TfhTfh c. SpleenSpleen massmass 16 400 bm12 CD4

** **** genotype: *** ifnar

*** WT 12 300 WT Figure 8. NK cell depletion restores -/- -/- 6 Ifnar 6

Ifnar Tfh expansion. WT or Ifnar -/- bm12 CD4 T cells were transferred 8 200 (mg) Cells x 10 x Cells

into NK-depleted (ΔNK) or NK-sufficient Cells x 10 Spleen mass (mg) mass Spleen control animals (a-d). Two weeks after 4 100 transfer, mice were assessed for the total number of bm12 Tfh (a), plasmab- 0 0 ControlControl ΔΔNK ControlControl ΔΔNK lasts, GC B cells, and activated B cells (b), splenomegaly as defined by spleen b. PlasmablastsPlasma cells GCGC B B cellsCD69+ B cellsCD69 (JK1528+ Bonly, cells no staining JK1517) 12 6 20 mass (c), and anti-dsDNA antibodies * * * * * (d). Data are from two representative ** experiments (n=8/group), depicting 15

6 8 4 6 6 mean ± SEM, where *p<0.05, **p<0.01, 6 ***p<0.001, ****p<0.0001 by the stu- 10 Cells x 10 x Cells Cells x 10 x Cells Cells x 10 x Cells dent’s t-test. Cells x 10 4 2 5

0 0 0 ControlControl ΔΔNK ControlControl ΔΔNK Control ΔΔNK

IFN promotes development of plasmablasts and GC B cells, but B cells are not NK targets A limited number of studies have examined the role of IFN sensing by B cells. The development of plasma cells was shown to be augmented by exogenous type I IFN19, as was their ability to produce antibody20. Isotype class switching was also found to be enhanced by exogenous IFN, but this appeared to function through DC IFN sensing21. We hypothesized that the endogenous type I IFN produced in bm12 disease also enhanced the development of plasmablasts and GC B cells. We also wondered whether these activated B cell subsets may also be targets of NK cells in this disease setting. To test these hypotheses, we generated mixed bone marrow chimeras (Fig. 9a). Briefly, bone marrow from CD45.2+ WT and CD45.1+ Ifnar -/- mice on a C57BL/6 background were mixed at a 1:1 ratio and transplanted into lethally irradiated CD45.2+ C57BL/6 recipients. After 12 weeks, half of the mixed bone marrow chimeric mice were depleted of NK cells using the same antibody treatment strategy described above, and half were not depleted. These mice were then given purified CD45.1+/CD45.2+ WT bm12 CD4 T cells. After 2 weeks, the mice were analyzed for disease development. NK cell depletion had no significant im-

163 pact on splenic B cell populations or on any other parameter of disease development—in fact splenomegaly was slightly, but insignificantly reduced in mice receiving NK depleting antibody (Fig. 9b). We did, however, observe a significant impact of B cell genotype on the development of plasmablasts and GC B cells. Specifically, there was a significantly greater proportion of WT than Ifnar -/- plasmablasts and GC B cells, whereas their propor- tions were equal in the non-activated (CD138−GL7−CD69−B220+) B cell populations (Fig. 9c). These data confirm earlier reports that type I IFN can promote the development of plasmablasts, and go beyond these findings, demonstrating that this can occur in the context of endogenously produced type I IFN during the development of lupus-like autoimmunity. Furthermore, the data show that the development of GC B cells can also be augmented by the direct action of type I IFN.

a. b. Spleen mass 300 p=0.22

bm12CD45.1/2 200

WT CD45.2 Analyze 3 months 14 days (mg) 1:1 B cell 100

subsets (mg) mass Spleen WTCD45.2

-‐/-‐ 0 Ifnar CD45.1 ControlControl ΔNK no bm12

c. PlasmablastsPlasmablasts GCGC B B cells Non-activatedNon-activated BB cells cells 80 80 80 **** * B cell

** * genotype:

ifnar

60 60 60 WT

WT Ifnar -/-

40 40 40 % GC B cells B % GC % Plasmablasts % % GC B cells

%Plasmablasts 20 20 20 % Non-activated B cells B Non-activated % % Non-activated B

0 0 0 Control ΔΔNK Control ΔNK Control ΔΔNK

Figure 9. B cell IFN-sensing augments plasmablast and GC B cell development. Depicted is the schema used for a mixed bone marrow chimera. Briefly, bone marrow from WT and Ifnar -/- mice was combined at a 1:1 ratio and transplanted into lethally irradiated C57BL/6 mice. Twelve weeks later, NK cells were depleted in half the mice using anti-asialo GM1 antibody. Then, all mice were given 8 million purified WT bm12 CD4 T cells. (a). Two weeks after transfer, mice were assessed for splenomegaly (b). The percentages of WT and Ifnar -/- cells were then determined within the resultant plasmablasts, GC B cells, and non-activated B cells (c). Data depict the mean ± SEM (n=4-6/group), where *p<0.05, **p<0.01, ****p<0.0001 by the student’s t-test.

164 Discussion A connection between the overproduction of type I IFN and the development of SLE has been well-established, yet the mechanisms by which IFN promotes disease pathology have not been fully elucidated. In this study, we identified a key role for type I IFN in protecting CD4 T cells from NK cell-cytotoxicity in a murine model of SLE.

The potential for immunoregulation of T cell activity by NK cells has been uncovered in recent years. Mounting evidence has established a role for NK cells in limiting T cell responses toward lymphocytic choriomeningitis virus (LCMV) by direct killing of virus-specific T cells40–43. Recently, NK cytotoxicity toward LCMV-specific T cells was shown to be inhibited by type I IFN44,45. These reports were consistent with data published over four decades earlier, in which Hansson, Welsh, and colleagues showed that either LCMV infection, the induction of type I IFN by poly I:C, or pre-treatment with exogenous IFN reduced the sensitivity of normal mouse thymocytes to NK cells in vitro46,47. Here, we present the novel finding that type I IFN also inhibits a similar in vivo regulation of activated CD4 T cells by NK cells in a sterile model of systemic autoimmune disease.

Taken together, these data suggest the intriguing possibility that peripheral tolerance may be maintained in part by the default NK killing of highly active T cells, and that activated T cells can be licensed by type I IFN during certain infections. Aberrant overproduction of type I IFN in a healthy individual could contribute to the inadvertent licensing of self-reactive T cells, and might thus be capable of initiating autoimmune disease. This may be one mechanism behind the induction of autoimmunity, including SLE, which occurs in some patients after the administration of type I IFN to treat conditions such as chronic hepatitis C viral infection7–9,48. One question this raises is how T cells avoid NK killing during positive selection in the thymus. Positive selection involves moderately strong activation of T cells toward self-antigens, and bulk thymocytes are indeed sensitive to killing by NK cells

165 ex vivo46,47. Type I IFNs, however, are massively upregulated in the thymus, particularly in the medulla, and the type I IFN-inducible protein MX1 is preferentially expressed on mature, single-positive thymocytes, which have recently undergone positive selection, suggesting they are especially sensitive to type I IFN, or that the signaling pathways downstream of IFN is enhanced in these cells49. One function of type I IFN in the thymus might therefore be to limit NK killing of activated T cells during and after positive selection. Importantly, MX1 expression is limited to fetal and postnatal thymic tissues, and was not observed in secondary lymphatic tissues or in the peripheral blood of healthy adults, consistent with a role for type I IFN in licensing activated T cells in the periphery. Of course type I IFN sensing by T cells alone may not be necessary or sufficient for this type of licensing in all inflammatory settings—it has been reported to be critical for T cell responses in multiple additional viral infections and vaccination strategies20,26,50, but also dispensable in others27,51, and not all productive inflammation involves type I IFN production.

The pleiotropic effects of type I IFN have been recognized for some time. It was therefore important to examine the possibility that the relatively poor expansion of Ifnar -/- bm12 CD4 T cells in our model was due to multiple direct effects of type I IFN. In fact, IFN likely also affected the proliferation of the transferred bm12 cells. Our in vivo proliferation data showed that both WT and Ifnar -/- bm12 CD4 T cells proliferate many rounds very early after transfer (Fig. 4a), but these data could not conclusively assess the effect of IFN on proliferation since they were in an open system, where cell death or migration could confound the results. Thus, we monitored the effect of IFN on purified CD4 T cells in vitro. Not surprisingly, given the growing consensus regarding the anti-proliferative effect of IFNs on multiple cell types including T cells27,52,53, we also found that type I IFN inhibited the proliferation of activated WT, but not Ifnar -/- CD4 T cells (Fig. 5). Here, in contrast to results from one commonly referenced study using primary human T cells54, the ongoing

166 proliferation of our murine CD4 T cells was inhibited by type I IFN. This is an important point; given the sustained high levels of type I IFN in SLE and other autoimmune diseases, it is vital to understand whether IFN might influence ongoing T cell proliferation, in addition to any effect of IFN might have had on the initial priming of auto-reactive T cells. This is particularly relevant since type I IFN receptor blockade is currently being pursued as a treatment strategy for SLE in clinical trials55. In addition to our in vitro data and that of others, we had some evidence that IFN exerted an anti-proliferative effect in vivo. When the NK immunoregulatory pressure was eliminated by transferring cells into Prf1-deficient animals, Ifnar -/- CD4 T cell response was not only restored, but these cells expanded significantly more than did WT CD4 T cells (Fig. 7).

One additional explanation as to why we observed significantly greater expansion of WT compared to Ifnar -/- CD4 T cells could have been that IFN caused changes within the bm12 Tfh which better supported a germinal center B cell response, considering Tfh and GC B cell responses are reciprocally supportive of one another34. This was an intriguing possibility, especially since type I IFN has been shown to induce IL-21 production in resting and activated human T cells56, and GC B cells rely upon IL-21 for directing their differentiation and proliferation57. The results from our mixed transfer experiments (Fig. 3), however, demonstrated that Ifnar -/- cells exposed to the same environment as WT cells still accumulated less, fitting our ultimate conclusion, that theIfnar -/- cells are chiefly more sensitive to NK cell attack.

Early work by Marrack et al. demonstrated that type I IFN directly enhanced the survival of activated CD8 T cells, and to a lesser extent activated CD4 T cells35. These experiments were done with cells from C57BL/10SgSnJ and 129/SvEv animals, and the extent to which IFN improved the survival of activated T cells varied depending on the mouse strain used. When we cultured our activated CD4 T cells ex vivo for 24 hours, we saw

167 little effect of IFN, although we did use a relatively low concentration of IFNβ compared to what was used in that study, and our cells were from mice on a C57BL/6 background, which was not included in that particular study. Importantly, the T cells studied in the Marrack paper were enriched using nylon wool columns, which efficiently depletes B cells and some myeloid cell populations, thus enriching samples for T cells, however this method also enriches for NK cells58. Therefore, type I IFN may in fact have kept activated T cells alive in that study by protecting them from NK cells, in addition to or in the absence of conferring any cell-intrinsic survival advantage.

One of the recent studies on NK immunoregulation in the context of LCMV showed that type I IFN protected T cells by upregulating an as of yet unidentified Ncr1 ligand or li- gands44. In our sterile inflammatory setting, however,Ifnar -/- Tfh expanded just as poorly in Ncr1-deficient animals as they did in C57BL/6 animals (2.5 ± 0.6 million, versus 3.0 ± 1.3, p=0.77). Furthermore, we were unable to detect Ncr1 ligands upon staining with an Ncr1-hIgG fusion protein. We did consistently observe increases in the expression of several other NK cell receptor ligands in cells from NK-depleted mice, including Icam-1, Icam-2, Mult-1, H-2Db, and Cd48, although these changes were not unique to Ifnar -/- cells, and the variations were generally small (Fig. S6). Moreover, an unbiased comparison of RNA transcript levels in these mice by RNAseq primarily revealed differential expression of a number of IFN-inducible genes, with no known involvement in sensitivity to NK cell attack (Fig. S7 and supplemental data file 1). This suggests that either a complex combination of signals drives NK cell sensitivity in our model, or the main effector ligand or ligands are as of yet unknown. Multiple key differences exist between our studies and those which identified a role for IFN in modulating Ncr1 ligand expression—perhaps most importantly, the studies by Crouse et al. were done in the context of viral infection rather than the sterile inflammatory disease studied here, and they examined monoclonal, TCR-transgenic SMARTA and P14 T cells, whereas we assessed polyclonal CD4 T cells.

168 Either or both distinctions may have contributed to contrasting results regarding the key protein interactions leading to NK cell killing.

Our study provides a significant contribution toward understanding the ways type I IFN can promote autoimmunity. Here, we demonstrated that the direct action of type I IFN on CD4 T cells renders them less susceptible to NK cell killing in an inducible model of SLE. Additionally, we found that plasmablasts and GC B cells were not NK targets in bm12 disease, however, the development of these cells was augmented by the direct action of type I IFN. As we begin to more precisely appreciate the many functions of type I IFN in SLE, this may enable the rational design of more targeted therapies for SLE and other autoimmune diseases with pathological type I IFN production.

169 Materials and Methods Mice and cell lines Mice were maintained under specific pathogen-free conditions in accordance with guidelines by the Association for Assessment and Accreditation of Laboratory Animal Care International. C57BL/6J, B6.SJL-Ptpcra (CD45.1), B6.PL-Thy1a/CyJ (CD90.1), B6.129S2-Ighmtm1Cgn/J (μMT), C57BL/6-Prf1tm1Sdz/J (Prf1-/-), and B6(C)-H2-Ab1bm12/KhEgJ (bm12) mice were purchased from The Jackson Laboratory (Bar Harbor, ME). Ifnar 1-/- mice were originally a gift from Dr. Jonathan Sprent and have since been bred in our facility. ISRE-L929 IFN reporter cells have been described previously59.

Mixed bone marrow (BM) chimeric mice were generated using lethally irradiated C57BL/6 mice. Mice received an initial dose of 700 RAD followed by an additional 475 RAD dose 3 hours later using a 137Cs irradiator (J L Shepherd & Associates, Inc., San Fernando, CA). BM from WT and Ifnar -/- donors on different congenic backgrounds and were mixed at a 1:1 ratio prior to reconstitution, and 6 million total BM cells were transferred via tail vein injection. All BM chimeric mice were given 12 weeks for hematopoietic reconstitution before experiments were started.

CD4 T cell isolation For in vivo and in vitro assays, CD4 T cells were sorted to >97% purity by negative selection using magnetic bead sorting technologies from Miltenyi Biotec (Bergisch Gladbach, Germany) and BioLegend (San Diego, CA). Post sort purity was determined by flow staining for live cells, CD45, CD3, and CD4. bm12 model The bm12 model experiments were performed essentially as previously described31. Briefly, 8 million donor bm12 CD4 T cells were injected intraperitoneally into recipient

170 mice of the specified strain. Fourteen days later, unless indicated otherwise, spleens were harvested, massed, and processed into single cell suspensions for counting and flow staining. Serum was harvested by retro-orbital bleeding prior to sacrificing mice, processed using serum separator tubes (BD Biosciences, San Jose, CA) and stored at −80°C for later cytokine and ANA analyses.

Serum cytokine and ANA analyses Circulating cytokines were analyzed in the serum of mice by Luminex multiplex technology (Austin, TX). Serum type I IFN was measured using the highly sensitive ISRE-L929 bioassay. Serum levels of anti-dsDNA were determined using ELISA essentially as described previously60.

NK and CD8 T cell depletion NK cells were depleted via an intraperitoneal injection of 10 μl anti-asialo GM1 rabbit antiserum (Wako, Richmond, VA) at -1, 1, 5, and 10 days after bm12 cell transfer. CD8 T cells were depleted by an intraperitoneal injection of 25 μg anti-CD8β (clone YTS156.7.7) one day prior to bm12 transfer.

Proliferation assays Spleens and lymph nodes were harvested from the indicated mouse strains, purified, and stained with 3 μM CellTrace Violet (Life Technologies, Carlsbad, CA) per the manufacturer’s protocol. Cells were then stimulated in 24 well polystyrene plates with 1 μg/ml plate-bound anti-CD3 (clone 17A2) and 1 μg/ml soluble anti-CD28 (clone 37.51), using LEAFTM purified antibodies from BioLegend. Cells were stimulated for 72 hours in medium containing 10% fetal bovine serum with penicillin, streptomycin, and L-glutamine with or without 50 U/ml recombinant IFN beta or IFN alpha A (PBL Assay Science, Piscataway, NJ). The recombinant IFN was added immediately at culture initiation unless otherwise

171 indicated. For in vivo assays, bm12 CD4 T cells were purified as described earlier, then stained with 3 μM CellTrace Violet immediately prior to intraperitoneal injection into recipient animals.

Flow cytometry Unless otherwise specified, cells were collected and immediately stained directlyex vivo. For the bm12 model, cells were stained essentially as described previously31. Intracel- lular Bcl-6 (clone K112-91, BD Biosciences) staining was performed using the FoxP3 Staining Buffer Set (eBioscience, San Diego, CA). Samples were collected on a Fortessa flow cytometer with FACSDiva software (BD Biosciences), and data were analyzed with FlowJo software (Tree Star, Ashland, OR).

Flow cell sorting and RNAseq Flow cytometric flow sorting was used to purify bm12 CD4 T cells to >99%. Splenic single cell suspensions were stained with the Fixable Viability dye ef780 (eBioscience), CD4, B220, CD45.1 and CD45.2. Viable CD4+B220−CD45.1+ cells were sorted at 4°C using a MoFlo XPD cell sorter (Beckman Coulter, Brea, CA) and immediately processed with mirVANA lysis buffer (Life Technologies). RNA was extracted according to the mir- VANA RNA extraction kit protocol. Subsequently, 300 ng of total RNA was purified by the NEBNext Poly(A) mRNA Magnetic Isolation Module (New England BioLabs, Ipswich, MA). The NEBNext Ultra Directional RNA Library Prep Kit was used for library preparation. Bioanalyzer (Agilent, Santa Clara, CA) analyses using a DNA high sensitivity chip were performed to determine quality and yield of the purified library. To study differential gene expression, individually indexed and compatible libraries were proportionally pooled (20-50 million reads per sample) for clustering in cBot system (Illumina, San Diego, CA). Libraries at the final concentration of 15 pM was clustered onto a single read (SR) flow cell using TruSeq SR Cluster kit v3, and sequenced for 50 bp using TruSeq SBS kit on

172 an Illumina HiSeq system. Sequence reads were then aligned to the genome by using a standard Illumina sequence analysis pipeline by The Laboratory for Statistical Genomics and Systems Biology at the University of Cincinnati.

173 Acknowledgements We are grateful to Dr. Stephen Waggoner for providing reagents and discussion, to Jeff Bailey and Victoria Sumney in the Comprehensive Mouse and Cancer Core for help with bone marrow chimera experiments, to Alyssa Sproles for technical support with the Lu- minex assays, and to Monica DeLay and the CCHMC Flow Core for flow cytometry and cell sorting support.

Disclosures The authors have no financial conflicts of interest to disclose.

174 Supplemental Figures

a. IFNα/β b. CXCL9CXLC9 (MIG)(MIG) c. CXCL10CXCL10 (IP-10)(IP-10) 7000 1000 800

6000 800 600 )

470 5000 600 (A 470 β

/ 400 pg/ml pg/ml α A

4000 pg /ml 400 IFN

200 3000 200

2000 0 0 0 5 10 15 0 5 10 15 0 5 10 15 Days post transfer Days post transfer Days post transfer

d. TNFTNFαα e. IFNIFNγγ f. IL-12, IL-23,IL-12p40 and/or IL-12p40 50 80 800

40 60 600

30 pg/ml

pg/ml 40 400 α γ pg /ml

20 IFN TNF IL-12p40 pg/ml IL-12p40 20 200 10

0 0 0 0 5 10 15 0 5 10 15 0 5 10 15 Days post transfer Days post transfer Days post transfer

Figure S1. Cytokine and chemokine analysis in bm12 disease. WT bm12 cells were transferred into C57BL/6 recipient animals. Type I IFN was assessed by a highly sensitive bioassay (a). Multiplex technology was used to assess serum levels of CXCL9 (b), CXCL10 (c), TNF (d), IFN (e), and IL-12p40 (f). Data are depicted as mean ± SEM.

175 WT a. 50.3

49.7

Ifnar -/- CD90.2 CD45.2 CD4 CD45.1

Spleen Blood b. bm12 CD4 100 100 genotype:

ifnar WT

WT Ifnar -/-

50 50 % Grafted cells % Grafted % Grafted cells % Grafted % Grafted cells

Days 0 0 post inj. 0 6 1414 0 6 1414

Figure S2. WT and Ifnar -/- CD4 T cells graft equally in non-inflammatory conditions. -/- Purified CD4 T cells from WTCD45.2/CD90.2 and Ifnar CD45.1/CD90.2 mice were co-transferred into

WTCD45.2/CD90.1 recipients. Representative flow cytometry plots show how transferred CD4

T cells were distinguished from recipient splenocytes (a, left), and the ratio of WT to Ifnar -/- cells (a, right). At 0, 6, and 14 days after transfer, the proportion of WT and Ifnar -/- CD4 T cells were assessed as in (a), demonstrating equal grafting and persistence of these cells over time (b). Data depict mean ± SEM.

176 Sample % Gate No IFN + IFNα + IFNβ WTFemale_WT_346R_028.fcs 44.4 Graft IfnarFemale_IFNAR_347R_032.fcs -/- 9.2 Graft Female_WT_346R_028.fcs 63.6 Non-Tfh Counts

Violet proliferation dye

Figure S3. Both IFNα and IFNβ inhibit the proliferation of WT CD4 T cells in vitro. Highly purified CD4 T cells from WT orIfnar -/- mice were labeled with a violet proliferation dye and stimulated with plate-bound anti-CD3 and soluble anti-CD28 in vitro for 72 hours in the presence or absence of 50 U/ml recombinant IFNα3 or IFNβ.

177 a. Control α-Asialo-GM1 NK1.1

NKp46

b. NKNK cellscells CD4CD4 T cellscells BB cells cells 1.2 25 100 ControlWT ** 20 80 αLegend-AGM1 6 6 0.8 6 6 15 60

Cells x 10 10 40 Cells x 10 Cells x 10

Cells x 10 0.4

5 20

0.0 0 0

Figure S4. Anti-asialo antibody treatment specifically and efficiently depletes NK cells. Representative flow cytometry plots show the specific depletion of NKp46+ NK1.1+ NK cells in anti-asialo GM1-treated mice compared to control animals immediately prior to injection of bm12 cells (a). Splenic NK cells, CD4 T cells, and B cells from these mice were enumerated prior to injection with bm12 cells (b).

178 CD8 T cells Tfh a. CD8 T cells b. Donor Tfh bm12 CD4 genotype:

15 15 ns ControlWT WT ifnar

* Legend ns WT αLegend-CD8β WT * Ifnar -/- 6 6

6 10 10 6 Cells x 10 x Cells Cells x 10

Cells x 10 5 Cells x 10 5 % of max

CD8α 0 0 β ControlControl ΔCD8ΔCD8 T cells T cells -CD8 Control α

Figure S5. Anti-CD8β antibody treatment depletes CD8 T cells, but does not affect the expansion of bm12 Tfh. A representative histogram shows the efficient depletion of CD3+CD8α+ T cells in anti-CD8β-treated mice compared to control animals immediately prior to injection of bm12 cells (a). Splenic CD8+ T cells from these mice were enumerated prior to injection with bm12 cells (b). In a separate experiment using the same depletion strategy, purified bm12 CD4 T cells from WT orIfnar -/- mice were transferred into C57BL/6 animals, and bm12 Tfh were assessed 14 days later (c).

179 a.

2.0 H-2Kb H-2Db Inhibitory Qa-1

1.5 Mult-1 Rae1d Activating Icam-1 Icam-2

1.0 Relative protein expression protein Relative Relative protein expression 0.5 WT Ifnar -/-

b. hi 80 Cd48 bm12 CD4

genotype: ifnar

WT 60 WT Ifnar -/-

%bm12 CD4 T cells CD4 T %bm12 20 % bm12 CD4 T cells T % bm12 CD4

0 Control ΔNK

Figure S6. WT and Ifnar -/- CD4 T cells express similar levels of several known NK activating and inhibitory proteins. The relative protein expression was calculated for bm12 CD4 T cells from NK-deficient recipients compared to NK-sufficient controls (a). Expression of Cd48 was unique compared to other NK ligands—bm12 CD4 T cells exhibited a bimodal distribution, expressing either intermediate or high levels. The percentage of Cd48hi expressing cells was compared between WT and Ifnar -/- bm12 CD4 T cells in control or NK-depleted hosts (b).

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184 Chapter 7: Dissection of metabolic activity in T follicular helper cells and B cells in systemic lupus erythematosus*

*The following manuscript is in preparation for submission. Klarquist J1,*, Lehn MA1,*, Hennies CM1, Zhang X2, Ji H3, and Janssen EM1

1 Division of Immunobiology. 2 Division of Human Genetics 3 Division or Asthma Research Cincinnati Children’s Hospital Medical Center and the University of Cincinnati College of Medicine, Cincin- nati, OH, USA * Authors contributed equally

Key words: metabolism, lupus Abbreviations: GC, germinal center, 2-DG, 2-deoxyglucose, 2NBDG, fluorescent 2-deoxyglucose, FAO, fatty acid oxidation; OCR, oxygen consumption rate; ECAR, extracellular acidification rate.

185 Abstract Systemic lupus erythematosus (SLE) is an autoimmune disease affecting multiple organ systems largely due to the production of autoantibodies. B cells and CD4 T cells play important roles in determining the strength and the nature of autoimmune pathologies in SLE patients. Recently, cellular metabolism has been identified as major regulator of immune cell function. We used an inducible model of SLE to determine the metabolic profiles of key CD4 T cell and B cell subsets, including T follicular helper cells (Tfh), germinal center (GC) B cells, and plasmablasts. We found all three cell subsets greatly increased their metabolic activity, shifting their metabolic programs toward one predominantly dependent upon aerobic glycolysis. Tfh, GC B cells, and plasmablasts also increased oxidative phosphorylation (OXPHOS) in a partially fatty acid oxidation (FAO)-dependent manner. The dependence of Tfh and B cells on glycolysis was so great, that its chemical inhibition via 2-deoxy-D-glucose (2-DG) administration was sufficient to completely prevent the development of lupus-like disease.

186 Introduction Systemic lupus erythematosus is characterized by the production of myriad autoantibodies which drive immune complex-related inflammation in various tissues and organs. Breakdown of peripheral tolerance in both CD4 T cells and B cells is considered a major driver of disease. While B cells produce the autoantibodies, the CD4 T cells enhance the production of autoantibodies through their capacity to promote B cell differentiation, maturation and class-switching1,2. Consequently, therapeutic interference of both T cells and B cells and their functions is of high interest.

Metabolism has recently been identified as a key player in the regulation of homeostasis and the cellular function of lymphocytes. There are several metabolic pathways involved in the generation of cellular energy: glycolysis, which encompasses cells metabolizing glucose into pyruvate that can either be shuttled into the tricarboxylic acid (TCA) cycle (oxidative glycolysis) or converted outside of the mitochondria into lactate (aerobic glycolysis); fatty acid oxidation (FAO) and amino acid oxidation/glutaminolysis, the processes where metabolic products of fatty acids and glutamine feed into the TCA cycle for energy production via oxidative phosphorylation (OXPHOS).

There is significant metabolic heterogeneity in distinct lymphocyte subsets. Naïve T cells have low metabolic needs that are met through the oxidation of glucose derived pyruvate or fatty acids via OXPHOS3–6. Upon activation T cells change their metabolic program to meet their energy needs for proliferation and development of specific effector functions. In vitro activated T cells rapidly increase glucose import for aerobic glycolysis and glutamine for OXPHOS while down regulating FAO7,8. However, evidence is accumulating that in vitro activated T cells may not correctly represent the metabolic profile of in vivo activated cells and that there may be large differences between T cells at the beginning and conclusion of an immune response as well as between acutely and chronically stimu-

187 lated T cells. It is currently thought that Th1, Th2, and Th17 CD4 T cells largely depend on aerobic glycolysis while Tregs depend on FAO9,10. Other CD4 T cell subsets, including Tfh cells have not been well characterized. B cells also show metabolic reprogramming upon activation but seem to proportionally increase OXPHOS and aerobic glycolysis11,12. While B cell activation in vitro has been studied, little is known on the metabolic needs of B cells in vivo during the generation of the GC B cell response and plasmablast/cell formation.

Studies to understand the cellular mechanism that drive SLE pathogenesis recently identified metabolic shifts in T cells from mice with features of SLE as well as patients with SLE. Fernandez et al showed elevated mTOR activity and mitochondrial membrane hy- perpolarization in CD4 T cells from SLE patients13. T cells from B6.sle1Sle2Sle3 and B6.lpr mice showed increased glycolysis and mitochondrial oxidative metabolism14,15. As a consequence, treatment of B6.Sle1Sle2Sle3 and B6.MRL-Faslpr mice with either 2-DG (a competitive substrate for hexokinase, an inhibitor of glycolysis) or metformin (a mitochondrial electron transport chain complex I inhibitor) were sufficient to prevent autoimmune activation. Importantly, metformin plus 2-DG combination treatment of mice after estab- lishment of disease significantly reduced ANA.

While these data are exciting and open a door to a new therapeutic approach, several questions remain to be answered. There is currently very little knowledge on the metabolic programs that regulate Tfh in vivo. The published studies used total CD4 T cells from the SLE models and in vitro activation of naïve T cells to assess the effects of the drug treatment. Although the studies claim that oxidation of glucose is particularly important, there are indicators that aerobic glycolysis could be a strong contributor to the disease development, and that oxidative phosphorylation of fatty acids may play a role as well. Moreover, little is known on the metabolic requirements of B cell responses during autoimmune manifestations. B cells do undergo a metabolic reprogramming upon activation

188 to increase glycolysis and lactate production and inhibition of this metabolic transition prevents antibody production. Inhibition of pathways that directly interfere with the B cell response would not only impact the development of the ANA, but also the expansion and maintenance of Tfh cells that is driven by GC B cells.

Here, we used an inducible model of SLE to dissect the metabolic profiles of Tfh cells, GC B cells and plasmablasts upon development of lupus-like disease. Our data show that Tfh have increased metabolic activity with a shift towards aerobic glycolysis, and increases in OXPHOS that are partially FAO-dependent. Aerobic glycolysis was the predominant metabolic pathway utilized by both GC B cells and plasmablasts. Consequently, inhibition of glycolysis, but not OXPHOS significantly reduced both Tfh and B cells responses. Furthermore, the B cell requirement for glycolysis was so strong, that GC B cells and plasmablasts did not develop, even when treatment was initiated after the development of a substantial Tfh population.

189 Results Tfh cells display increased metabolic activity To address the metabolic program in Tfh cells in SLE models, we used an inducible model of SLE where transfer of CD4 T cells from bm12 mice (on a CD45.1 background) into WT C57BL/6 recipients results in SLE-like disease1,2. In this model, transferred CD4 T cells rapidly expand and develop into Tfh, characterized by gene and protein expression of Bcl6, Cxcr5, PD-1, Icos, Cxcr3, and Il21 (fig.1a-c). Flow cytometric assessment of phosphorylated 4EBP1 and S6K, downstream targets of mTORC1—a key sensor of nutrients and regulator of metabolism—showed a significant increase in phosphorylation in both proteins in Tfh compared to naïve CD4 T cells (fig.1d,e). Importantly, a similar increase in p-S6K and p-4EBP1 expression was observed in Tfh cells obtained from B6.Nba2 mice that spontaneously developed ANA and proteinuria (fig.1f).

As this increase in mTOR activity suggested an increase in cellular metabolism, we next used Seahorse extracellular flux analysis to assess the level of OXPHOS and mitochondrial capacity in naïve CD4 T cells and Tfh in real-time. Tfh obtained from the bm12 model showed increased baseline oxygen consumption (OCR) levels compared to naïve CD4 T cells (fig.1g,h). Addition of a combination of rotenone and antimycin A, blockers of mitochondrial complex I and III, respectively, indicated that naïve CD4 T cells and Tfh cells had the same level of non-mitochondrial OCR. Importantly, blocking complex V with oligomycin A, thereby blocking conversion of ADP to ATP, significantly reduced the OCR to levels close to the level of non-mitochondrial OCR in both naïve CD4 T cells and Tfh. This suggests that the increase in baseline OCR in Tfh was used for increased ATP production. Interestingly, Tfh showed a significant increase in ECAR (extracellular acidification rate), suggesting increased use of glycolysis and production of lactate (fig.1i). Together these data indicated that Tfh were metabolically more active than naïve CD4 T cells and suggest that they are increasing both mitochondrial and non-mitochondrial pathways to generate energy.

190 Fig 1 T' in BM12 model

day 1 CXCR5 PD1 Bcl6 Icos CXCR3 IL21 A 150 400 60 B 200 C 100 50 * * 80 40 300 150 100 40 60 30 200 100 40 20 50 20 100 50 20 10 Relative expression Relative expression Relative expression Relative expression Relative Relative expression Relative Relative expression Relative 0 0 0 0 PD-‐1 0 0 CXCR5

naive naive naive naive naive naive naïve CD45.1 CD45.1 CD45.1 CD45.1 CD45.1 CD45.1 CD4 day 14 T' CXCR5 PD1 Bcl6 Icos CXCR3 IL21 150 400 60 200 * 100 50 * 80 40 300 150 100 40 60 30 200 100 40 20 50 20 100 50 20 10 Relative expression Relative expression Relative expression Relative expression Relative Relative expression Relative Relative expression Relative 0 0 CD45.1 0 0 0 0 Bcl-‐6 Icos

naive naive naive naive naive naive CD45.1 CD45.1 CD45.1 CD45.1 CD45.1 CD45.1

bm12 model p4EBP1 pS6K B6.Nba2 model D p4EBP1 E pS6K F 200 p4EBP1 400 pS6K naïve 800 p4EBP1 1500 pS6K * T' 150 * 300 600 * * 1000 100 200 400 GeoMFI GeoMFI GeoMFI GeoMFI 500 200 50 100 p4EBP1 pS6K 0 0 0 0

Tfh Tfh naive naive

CD69-CXCR5-CD69+CXCR5+ CD69-CXCR5-CD69+CXCR5+

G 150 H Basal respiration ATP-linked Coupling efficacy FCCP

oligomycin Rot/Antim 100 100 1.0 100 * 80 80 * 0.8

60 60 0.6

50 40 40 0.4 OCR(pMoles/min) OCR(pmol/min) OCR(pmol/min) OCR(pmol/min) 20 20 0.2

0 0 0.0 0 time (min) Tfh Tfh Tfh naive naive naive

OCR Tfh OCR naive

I ECAR ECAR/OCR 50 50 0.4 * * 40 40 0.3 30 30 0.2 20 20 ECAR / OCR / ECAR

0.1 (mpH/min) ECAR ECAR (mpH/min) ECAR 10 10

0 0.0 0 0 50 100 150 Tfh Tfh naive naive OCR (pmol/min)

Figure 1: Metabolic activity is increased in Tfh from murine models of SLE. Two weeks after transfer into C57BL/6 recipient mice, bm12 CD4 T cells were sorted based on CD45.1 expression. Flow cytometry plots of live splenocytes 1 day or 2 weeks after transfer are shown (A). qPCR was performed on purified cells for the Tfh-associated genes Cxcr5, PD-1, Bcl6, Icos, Cxcr3, and IL-21 (B). The levels of Tfh-associated proteins were determined by flow cytometry (C). Representative flow cytometry plots show p4EBP1 and pS6K protein expression (D). Summarized data show increased levels of p4EBP1 and pS6K in Tfh (E). Tfh isolated from B6.Nba2 mice showed similar increases in p4EBP1 and pS6K compared to controls (F). Mitochondrial stress tests demonstrated greater OCR associated with ATP production in bm12 Tfh compared to naïve CD4 T cells (G). Basal respiration was determined by subtracting OCR after antimycin/ rotenone treatment from baseline OCR; ATP-linked OCR was determined by subtracting the after oligomycin treatment from the baseline OCR; and the coupling efficiency was defined by the inverse ratio of these two values (H). Baseline ECAR levels were also compared between these cells (I).

191 Glycolysis is increased in Tfh compared to naïve CD4 T cells Based on the dramatic increase in ECAR in the Tfh, we assessed whether Tfh increased their glycolysis to meet their metabolic needs. RNA-Seq and quantitative-RT-PCR (qPCR) showed that Tfh cells had increased gene expression of multiple genes associated with glycolysis compared to naïve CD4 T cells (fig 2.a-c). We next performed a glycolysis stress test where ECAR of naïve CD4 T cells and Tfh cells was first measured in the absence of pyruvate and glucose and subsequently upon addition of glucose to determine

25 8 8 A naïve T( B C Slc2a1 Slc2a6 80 Hk1 Hk2 20 * * * 6 60 6 15 4 40 4 10

2 20 2 5 Relative expression Relative Relative expression Relative expression Relative Relative expression Relative

0 0 0 0 Tfh Tfh Tfh Tfh naive naive naive naive

200 300 400 200 Pgam Pgk1 Ldha TPI * * * 150 150 300 200

100 100 200 100 50 50 100 Relative expression Relative expression Relative Relative expression Relative Relative expression Relative

0 0 0 0 Tfh Tfh Tfh Tfh naive naive naive naive

glycolysis ECAR Glycolysis Glycolytic capacity Glycolytic reserve D 50 ECAR CD45.2 #1 E gluc glycolysis oligo ECAR 2DG 30 40 8 naive Glycolysis Glycolytic capacity Glycolytic reserve 50 ECAR CD45.2 #1 40 30 40 8 naive 30 6 20 40 * * 30 T( 30 6 20 20 4

30 10 20 4 20 10 2 ECAR(mpH/min) ECAR(mpH/min) ECAR(mpH/min) 10 ECAR(mpH/min) 20 10 2 ECAR(mpH/min) ECAR(mpH/min) 10 0 0 ECAR(mpH/min) 0 ECAR(mpH/min) 10 naïve 0 TfH 0 TfH 0 TfH 0 naive naive naive time (min) TfH TfH TfH 0 naive naive naive time (min) naivenaive T cell T cell Tfh Tfh F 3000 3000 3000 3000 Figure 2: Tfh utilize aerobic glycolysis for energy production.

2000 2000 2000 2000 Diagram of genes involved in glycolysis (A). RNA-Seq analysis * * * showed differential expression of these and additional related genes 1000 1000 * * 1000 1000 * (B). qPCR confirmed increases in several key genes controlling gly- ATP pMoles ATP pMoles ATP pMoles ATP pMoles colysis (C). Glycolytic stress tests show that Tfh have increased 0 0 0 0 ECAR upon the addition of glucose, which was eliminated by 2-DG Medium + + + + + + glucose + + -‐ + + -‐ treatment (D). Glycolysis was determined by subtracting the base- 2-‐DG -‐ + -‐ -‐ + -‐ line ECAR from the ECAR after glucose challenge; glycolytic capacity was determined by subtracting baseline ECAR from the ECAR after the addition of oligomycin; and glycolytic reserve was determined by subtracting the ECAR value after glucose challenge from the ECAR value after the addition of oligomycin (E). ATP production was determined in cells with and without the addition of exogenous glucose, and with and without 2-DG treatment (F).

192 the rate of glycolysis in the cells. Addition of oligomycin, which blocks mitochondrial ATP production and shifts energy production to glycolysis, was used to determine the maximal glycolytic capacity, while the addition of 2-deoxy-glucose (2-DG) was used to block all glycolysis (fig.2d). Compared to naïve T cells, Tfh displayed significantly higher levels of glycolysis (fig.2d). While the Tfh also display greater glycolytic capacity than naïve CD4 T cells, this glycolytic capacity was close to their baseline level of glycolysis, suggesting that Tfh cells function relatively close to their maximal glycolytic capacity (fig.2.e). In line with these Seahorse data, assessment of ATP showed that ATP generation by Tfh cells was significantly reduced in the absence of glucose or upon treatment with hexokinase inhibitor 2-DG (fig.2f). Together these data indicate that Tfh use glycolysis for energy production at higher levels than naïve cells. Interestingly, CD4 T cells activated by CD3/ CD28 in vitro showed comparable ECAR as Tfh, but significant higher OCR, implying that the existence of a metabolic program in Tfh that is distinct from a generally activated CD4 T cell (s.fig.1).

In line with these observations, Tfh cell expressed higher levels of glucose importer glut1 and showed higher uptake of fluorescent 2-DG (2-NBDG) than naïve CD4 T cells (fig.3.a-c). This was observed in both Tfh from the bm12-CD45.1àC57BL/6 model as well as the spontaneous B6.Nba2 models. Similarly, when 2NBDG was administered i.v. in

cummulative OCR +/- 2DG cummulative ECAR +/- 2DG 500 60 400

40 300

200 20 OCR(pmol/min)

ECAR(mpH/min) 100

0 0

Tfh Tfh naive naive

CD3/Cd28 CD3/Cd28

Supplementary Figure 1: Distinct metabolic programs between Tfh and in vitro activated CD4 T cells. Ex- tracellular flux assays using medium with added glucose show baseline ECAR levels and ECAR after the addition of 2-DG for sorted naïve CD4 T cells, bm12 Tfh, anti-CD3/anti-CD28 in vitro activated CD4 T cells. OCR before and after 2-DG treatment were also determined (B).

193 Bm12 model 2NDBG A B Glut-1 2NDBG 2NDBG 2000 Glut-‐1 1500 600 in vitro vivo

1500 * * 1000 400

1000 GeoMFI 500 200 500 GeoMFI2NBDG 2NBDG GeoMFI Glut1 2-‐NBDG 0 0 0 Tfh Tfh Tfh naive naive naive

Glut1 2-NBDG C B6.Nab2 model 2NDBG D 5000 500 Glut-1 2NDBG 2NDBG 400 100 Glut-‐1 800 in vitro in vivo 4000 400 * 80 * 300 600 3000 300 60 200 200 400 2000 GeoMFI

40 GeoMFIGlut-1 1000 2NBDG GeoMFI 100 100 200 GeoMFI 2NBDG GeoMFI 20 2NBDG GeoMFI 0 0 0 0 0 naive naive Tfh Tfh Tfh naive naive naive

CXCR5+PDi1high CXCR5+PDi1high

Figure 3: Increased glucose importer expression and glucose import within Tfh. Representative flow cytometry plots show Glut1 levels and 2-NBDG uptake by Tfh (black lines) and naïve control cells (gray shaded lines) (A). Glut1 expression and 2-NBDG import was determined for bm12 Tfh exposed to 2-NBDG in vitro, or when 2-NBDG was delivered by intravenous injection prior to tissue harvest, as indicated (B). Naïve CD4 T cells and Tfh from B6.Nba2 mice were similarly assessed for glucose transporter expression and 2-NBDG uptake (C). Glut1 and 2-NBDG uptake was also determined for circulating Tfh and naïve CD4 T cells from human peripheral blood. vivo, Tfh cells in both the inducible bm12-CD45.1àC57BL/6 model and the spontaneous B6.NBA2 model incorporated more 2NBDG than naïve CD4 T cells in the same mouse (fig.3.b,c). Similar to mouse Tfh cells, human peripheral Tfh cells (CD4+CXCR5+PD-1high) showed increased glut-1 expression and in vitro 2NBDG uptake compared to naïve CD4 T cells (CD4+CD45RA+PD-1−) from the same donors (fig.3.d).

Fatty acid oxidation (FAO) is the predominant mitochondrial ATP producing pathway As Tfh showed higher OCR/OXPHOS than naïve cells, we wondered which carbon source was needed to fuel this increased mitochondrial activity. Elimination of glycolysis did not alter OCR in Tfh, suggesting that the pyruvate generated in the glycolytic pathway did not feed into the TCA and contribute to the increased OCR (s.fig.1). We therefore analyzed the contribution of the other 2 main carbon sources for mitochondrial OXPHOS, glutami-

194 nolysis and fatty acid oxidation (FAO).

Compared to naïve CD4 T cells, Tfh showed a limited upregulation of genes associated with glutaminolysis (fig.4.a-c). Glutamine stress tests indicated that elimination of glutamine from the medium did not affect OCR by Tfh (fig.4.d). Similarly, administration of aminooxyacetate (AOA), a chemical inhibitor of glutamate-dependent transaminases that convert glutamate into α-ketoglutarate to cells cultured in the presence of glutamine did not change the OCR by Tfh (fig.4.e). Furthermore, ATP production by Tfh was not affected by the absence or presence of glutamine or AOA (fig.4.f).

While Tfh did not seem to depend on glutaminolysis, they seemed to partly depend on

A naïve T( B C 50 Slc38a1 80 Slc38a2 50 Gls 50 Gls2 40 40 40 60 30 30 30 40 20 20 20 20 10 10 10 Relative expression Relative expression Relative Relative expression Relative expression Relative

0 0 0 0 Tfh Tfh Tfh Tfh naive naive naive naive

100 Glud1 6 Gpt 25 Got1

80 20 4 60 15

40 10 2 20 5 Relative expression Relative Relative expression Relative Relative expression Relative

0 0 0 Tfh Tfh Tfh naive naive naive

glutaminolysis OCR Tfh cummulative OCR +/-glut naive Tnaive cell T cell Tfh D 150 E F 3000 3000 3000 glut 400 3000 none ocr T( +glut ocr 300 2000 100 2000 2000 2000

200 1000 1000 1000 1000 ATP pMoles ATP pMoles ATP pMoles 50 ATP pMoles OCR(pmol/min)

OCR(pmol/min) 100

naïve 0 0 0 0 0 0 Medium + + + + + + time (min) Tfh naive glutamine + + -‐ + + -‐ CD3/Cd28 AOA -‐ + -‐ +

Figure 4: Mitochondrial OXPHOS is not driven by glutaminolysis in Tfh. Diagram of key genes involved in glutaminolysis (A). RNA-Seq (B) and qPCR (C) analysis of these and additional related genes. OCR was measured in extracellular flux assays before and after the chemical inhibition of glutaminolysis by AOA using glutamine-supplemented media (D). OCR was also measured in cells before and after the addition of glutamine using otherwise glutamine-free media (E). ATP production was determined in cells with and without the addition of exogenous glutamine, and with and without AOA treatment (F).

195 A B C 12.5 Acs3 40 Cpt1 * 8 Cpt2 10.0 naïve T( * 30 6 * 7.5 20 4 5.0 10 2 2.5 Relative expression Relative Relative expression Relative Relative expression Relative

0.0 0 0 Tfh Tfh Tfh naive naive naive

80 Acadl 80 Echs1 * 50 Hadha * 40 60 * 60 30 40 40 20 20 20 10 Relative expression Relative Relative expression Relative Relative expression Relative

0 0 0 Tfh Tfh Tfh naive naive naive

FOA OCR 150 D cummulative ocr E +/- eto F naive T cell Tfh eto 250 * 3000 3000

100 200 T( * 2000 * 2000 * 150

50 100

OCR(pmol/min) 1000 1000 OCR(pmol/min) ATP pMoles naïve 50 ATP pMoles 0 0 0 0 time (min) Tfh -‐ eto naive -‐ eto

CD3/Cd28

Figure 5: FAO is critical for OXPHOS-dependent ATP production in Tfh. Diagram of genes involved in FAO (A). RNA-Seq analysis of these and additional related genes within Tfh and naïve CD4 T cells (B). qPCR was also performed on several genes controlling FAO, including the genes essential for long-chain fatty acid transport across the mitochondrial inner membrane, carnitine palmitoyltransferase I (CptI) and II (CptII) (C). OCR was measured at baseline and following chemical inhibition of Cpt1 by etomoxir (D-E). ATP production was also determined in Tfh before and after treatment with etomoxir (F). fatty acid oxidation. Tfh showed modest, but significantly increased expression of various key genes in the FAO pathway (fig.5.a-c). Treatment of Tfh cells with etomoxir, an inhibitor of CPT1, the protein responsible for transporting fatty acids into the mitochondria, resulted in a partial inhibition of OCR (fig.5.d,e). Moreover, treatment with etomoxir significantly reduced ATP production, supporting the importance of fatty acids in T cell metabolism (fig.5.f). Intriguingly, blocking fatty acid oxidation in CD3/CD28 activated T cells resulted in an marked decrease in OCR, but a significant increase in ECAR, indicating that the cells increased the glycolytic pathway to meet their metabolic needs. In contrast, Tfh cells showed a marked decrease in OCR without increasing glycolysis (supplemental figure 2). This is in line with our earlier observation that Tfh function relatively close to their maximal glycolytic capacity.

196 cummulative ecar +/- eto 80

60 Supplemental Figure 2: Chemical inhibition of FAO results in increased glycolytic rates for in 40 vitro activated CD4 T cells, but not Tfh. Base- line ECAR and ECAR following the addition of the 20 ECAR(mpH/min) FAO inhibitor etomoxir was determined for naïve CD4 T cells, Tfh, and anti-CD3/anti-CD28 activat- 0 ed CD4 T cells.

Tfh naive

CD3/Cd28

Together these studies show that Tfh follow a specific metabolic program that is distinct from naïve or globally activated CD4 T cells that predominantly depends of glycolysis and to a lesser degree on fatty acid oxidation.

GC B cell and plasmablast responses are associated with increased metabolic activity As SLE is a disease characterized by dysregulated B cell responses we next assessed metabolic programs of both germinal center B cells and plasmablasts. In the inducible SLE model, transfer of bm12 CD4 T cells results in a rapid increase GC B cells (B220+- Fas+GL7+) and plasmablasts (CD138+B220low), concomitant with the production of antibodies to various nuclear antigens, including dsDNA (fig.6.a,b). Flow cytometric analysis of GC B cells showed increased phosphorylation of S6K, while plasmablasts showed increased phosphorylated S6K and phosphorylated 4EBP1. Similar results were found in GC B cells and plasmablasts from B6.Nba2 mice with proteinuria (fig.6.c).

Real-time assessment of oxidative phosphorylation indicated that naïve B cells, GC B cells and plasmablasts have relatively comparable levels of OCR, ATP-dependent OCR, and coupling efficacy (fig.6.d,e). In contrast, GC B cells and plasmablasts displayed increased ECAR and ECAR/OCR rates compared to naïve B cells, indicating increased glycolytic activity in the GC B cells and plasmablasts.

197 bm12 model A day 1 day 14 B C bm12 p4EBP1 bm12 pS6K

20 1000 p4EBP1 * 4000 pS6K

800 * 3000

GL7 15 600 2000

GeoMFI 400 GeoMFI 10 * 1000 Fas 200 5 0 0

naive naive Anti-dsDNA IgG (ref. units) Anti-dsDNA 0 GC B cell GC B cell d9 d14 plasma blast plasma blast CD138

p4EBP1B6.Nba2 model pS6K B220 200 p4EBP1 * 600 pS6K * 150 400

OCR baseline 100 GeoMFI GeoMFI D 1500 200 * oligo FCCP A/R naive ocr 50 OCR baseline GL7 ocr 0 0 1500 CD138 ocr naive naïve ocr 1000 GL7 GC ocr B cell GC B cell GC B cell naive B cell plasmablast naive B cell plasmablast plasmablastCD138 ocr 1000 500

OCR(pMoles/min) 500 0 OCR(pMoles/min) time (min)

0 time (min) basal ATP dependent coupling efficacy ECAR ECAR/OCR E 500 400 1.5 150 0.5

400 0.4 300 1.0 100 300 0.3 200 200 0.2 0.5 50 100 OCR / ECAR 100 ECAR(mpH/min) 0.1 OCR(pMoles/min) OCR(pMoles/min) OCR(pMoles/min)

0 0 0.0 0 0.0

GC GC GC GC GC naive naive naive naive naive

plasmablast plasmablast plasmablast plasmablast plasmablast

Figure 6: Increased metabolic activity in key B cell subsets. Representative flow cytometry plots show B220+Fas+GL7+ GC B cells and CD138+B220low plasmablasts 1 day and 14 days after transfer of bm12 CD4 T cells into C57BL/6 recipient mice (A). Serum levels of anti-dsDNA antibodies rise to detectable levels 14 days post transfer (B). p4EBP1 and pS6K expression was determined for naïve B cells, GC B cells, and plasmablasts from the bm12 model and from the B6.Nba2 model (C). Mitochondrial stress tests were performed using sorted populations (D). From these tests, basal OCR, ATP-dependent OCR, coupling efficiency, were determined as described earlier (E). Baseline ECAR and the ratio of ECAR to OCR was also determined (E).

198 Increased glycolysis in GC B cells and plasmablasts Similar to Tfh, GC B cells and plasmablasts showed increased expression of genes associated with glycolysis (fig.7.a). Glycolysis stress tests indicated that both GC B cells and plasmablasts had a significantly increased level of glycolysis and glycolytic capacity

compared to naïve B cells (fig.7.b-d). As with Tfh cells, both GC B cells and plasmablasts

time (min) 0

glycolysis ECAR ECAR(mpH/min)

50 200 gluc oligo 2DG

A B ECAR CD138-2 100 ECAR GL7-1 150 ECAR naive 25 Slc2a1 5 Slc2a6 20 Hk1

* * 20 4 ECAR naive * * 150

15 Naïve 15 3 100 ECAR GL7-1

10 GC B cell

10 2 ECAR CD138-2 200 plasmablast

5 50 5 1 ECAR(mpH/min) Relative expression Relative glycolysis ECAR expression Relative expression Relative 0 0 0 0 naive naive naive GC b cell b GC cell b GC cell b GC time (min) plasmablast plasmablast plasmablast C Glycolysis Glycolytic capacity Glycolytic reserve 2.5 25 60 Hk2 Pgam * Ldha 150 200 40 2.0 * 20 * * * * * * 150 30 40 1.5 15 100

1.0 10 100 20 20 50 0.5 5 Relative expression Relative Relative expression Relative expression Relative 50 10 ECAR(mpH/min) ECAR(mpH/min) ECAR(mpH/min) 0.0 0 0 0 0 0 naive naive naive GL7 GL7 GL7 naive naive naive GC b cell b GC GC b cell b GC cell b GC CD138 CD138 CD138 plasmablast plasmablast plasmablast

D E naive naive B cell Bnaive cell B cell GC B GC cell B cellGC B cell plasmablast plasmablast plasmablast cummulative ECAR +/- 2DG 5000 5000 5000 8000 8000 8000 5000 5000 5000

250 4000 4000 4000 4000 4000 4000 * * 6000 6000 6000 200 3000 3000 3000 3000 3000 3000 4000 4000 4000 150 * * * * * * * * * 2000 2000 2000 2000 2000 2000

100 ATP pMoles ATP pMoles ATP pMoles ATP pMoles 2000ATP pMoles 2000 ATP pMoles 2000 ATP pMoles ATP pMoles ATP pMoles 1000 1000 1000 1000 1000 1000

ECAR(mpH/min) 50 0 0 0 0 0 0 0 0 0 0 Medium + + + + + + + + +

GL7 naive glucose + + -‐ + + -‐ + + -‐ CD138 IgM/CD40 2-‐DG -‐ + -‐ -‐ + -‐ -‐ + -‐

Figure 7: Plasmablasts and GC B cells utilize glycolysis. qPCR analysis of glucose importer genes and other glycolysis pathway genes in sorted naïve B cells, GC B cells, and plasmablasts (A). Glycolysis stress tests were also performed on these cells (B). From these tests, glycolysis, glycolytic activity and glycolytic reserve were calculated as described earlier (C). Baseline ECAR and ECAR after the addition of 2-DG was determined for these cells as well as in vitro activated B cells (D). ATP production was determined in cells with and without the addition of exogenous glucose, and with and without 2-DG treatment (E).

199 bm12 model 2NDBG glut1glut1glut1 2NBDG2NBDG2NBDG vitro vitro vitro 2NBDG2NBDG2NBDG vivo vivo vivo F G 400040004000 1000 1000 Glut-‐1 1000 500 500 500 in vitro vivo * * * * 800800800 * * 400400400 300030003000 600600600 300300300 200020002000 GeoMFI GeoMFI GeoMFI 400 200 GeoMFI GeoMFI GeoMFI GeoMFI GeoMFI 400GeoMFI 400 200 200 100010001000 200200200 100100100 Glut-‐1 0 0 0 0 0 0 0 0 0

naivenaivenaive naivenaivenaive naivenaivenaive GC GCB cell GCB cell B cell GC GCB cell GCB cell B cell GC GCB cell GCB cell B cell plasmaplasmaplasma blast blast blast plasmaplasmaplasma blast blast blast plasmaplasmaplasma blast blast blast B6.Nba2 model 2NDBG 2NBDG Glut1 2NBDG 2NBDGGlut1 Glut-‐1 in vitro vivo 1500 500 1500 500 2-‐NBDG * * * * * * 400 400 1000 1000 300 300 GeoMFI GeoMFI GeoMFI GeoMFI GeoMFI 200 200 500 500 100 100

0 0 0 0

GC B cell GC B cell GC B cell GC B cell naive B cell naive B cell naive B cell naive B cell plasmablast plasmablast plasmablast plasmablast H Glut-‐1 2NBDG 5 donor #1 donor #2 donor #3 2.0 donor #1 donor #2 donor #3

3 1.5

2 relative geoMFI relative relative geoMFI relative 1 1.0

naive B cell naive B cell naive B cell naive B cellplasmablastnaive B cellplasmablastnaive B cellplasmablast plasmablast plasmablast plasmablast memory B cell memory B cell memory B cell memory B cell memory B cell memory B cell

Figure 7 continued... Representative flow cytometry plots show Glut1 expression and 2-NBDG uptake for plasmablasts (solid black lines), GC B cells (dotted lines), and naïve B cells (gray shaded lines) (F). Glut1 expression and 2-NBDG import was determined for bm12 Tfh exposed to 2-NBDG in vitro, or in vivo, as indicated (G). Circulating plasmablasts (CD19+IgG−IgD−Cd27+CD38+) and memory B cells (CD19+IgD−Ig- G+CD27+CD38−), and naïve B cells (CD19+IgD+IgG−CD27−CD38−) were analyzed for Glut1 expression and 2-NBDG uptake (H). had relatively small glycolytic reserves, indicating that they operated close to their maximal glycolytic capacity. The glycolytic pathway in the B cells was critically important for the generation of ATP as both the elimination of glucose or the inhibition of glycolysis with 2-DG significantly reduced ATP production (fig.7.e).

Correlating with their baseline level of glycolysis, GC B cells and plasmablasts expressed high levels of Glut-1 and showed increased 2-NBDG uptake in vitro as well as in vivo (fig.7.f,g). This correlative increase in glycolysis, Glut-1 expression and 2-NBDG was also observed in GC B cells and plasmablasts from B6.Nba2 mice with proteinuria (fig.7.g).

200 Importantly, human peripheral plasmablasts (CD19+IgG−IgD−Cd27+CD38+) showed significantly higher levels of Glut-1 and 2-NBDG uptake compared to switched memory cells (CD19+IgD−IgG+CD27+CD38−) and naïve B cells (CD19+IgD+IgG−CD27−CD38−) from the same donor (fig.7.h).

Limited dependence of B cell responses on FAO As with the Tfh cells, elimination of glycolysis did not affect OCR, suggesting that either glutaminolysis or FAO provided that carbon source for the mitochondrial ATP production. Analysis of gene expression of naïve B cells, GC B cells and plasmablasts indicated

cummulative OCR +/- glut 200 40 0.5 6 no glut A Slc38a2 Gls Gls2 Gtp B 600 0.4 150 30 + glut 4 0.3 100 20 400 0.2 2 50 10 0.1 Relative expression Relative Relative expression Relative expression Relative Relative expression Relative

0 0 0.0 0 200 OCR(pMoles/min) naive naive naive naive GC b cell b GC GC b cell b GC GC b cell b GC cell b GC 0 plasmablast plasmablast plasmablast plasmablast GL7 naive CD138 6 100 Glud1 Gtp 30 Got1 IgM/CD40 80 cummulative OCR +/- AOA 4 20 60 500 vehicle 40 2 10 AOA 400 20 Relative expression Relative Relative expression Relative Relative expression Relative 0 0 0 300 naive naive naive 200 GC b cell b GC GC b cell b GC GC b cell b GC plasmablast plasmablast plasmablast 100 OCR(pMoles/min) 0 C 4000 naive40004000naive B cellnaive B cell B cell8000 8000GC8000 B GCcellGC B cell B cell 5000 plasmablast50005000plasmablastplasmablast GL7 naive Cd138 4000 40004000 IgM/CD40 3000 30003000 6000 60006000

3000 30003000 2000 20002000 4000 40004000 2000 20002000 ATP pMoles ATP pMoles ATP pMoles ATP 1000 pMoles ATP 1000 pMoles ATP 1000 pMoles ATP 2000 pMoles ATP 2000 pMoles ATP 2000 pMoles 1000 10001000

0 0 0 0 0 0 0 0 0 Medium + + + + + + + + + glutamine + + -‐ + + -‐ + + -‐ AOA -‐ + -‐ + -‐ +

Figure 8: B cell subsets in murine lupus do not utilize glutaminolysis. Relative expression as determined by qPCR of genes associated with glutaminolysis in naïve, GC B cells, and plasmablasts from C57BL/6 mice 2 weeks after bm12 transfer (A). Baseline OCR and OCR after the addition of AOA, an inhibitor of glutaminolysis, or after the addition of exogenous glutamine was determined by extracellular flux assays (B). ATP production was also determined in cells with and without the addition of exogenous glutamine, and with and without AOA treatment (C).

201 limited changes in genes associated with glutaminolysis (fig.8.a). Seahorse analysis indicated that absence of glutamine or presence of glutaminolysis inhibitor AOA did not affect OCR or ECAR in any of the B cell subsets (fig.8.b). In line with these observations, absence of glutamine or presence of AOA did not alter ATP production in the different B cells (fig.8.c).

Interestingly, little changes in gene expression associated with fatty acid oxidation were observed (fig.9.a). However, treatment of GC B cells and plasmablast with etomoxir resulted in a 30% reduction of OCR (fig.9.b). Similarly, addition of etomoxir significantly reduced ATP production in the B cells (fig.9.c), illustrating an important role for FAO in B cell metabolism.

cummulative OCR +/- eto B 1000 A 30 acads 40 acadm 60 Cpt1a 800

30 600 20 40

20 400

10 20 OCR(pmol/min) 10 200 Relative expression Relative expression Relative Relative expression Relative 0 0 0 0

GL7 naive naive naive naive Cd138 IgM/CD40 GC b cell b GC cell b GC cummulativecell b GC OCR +/- eto cummulative ECAR +/- eto plasmablast plasmablast 1000 plasmablast 200

800 150 15 CPT2 60 Acadl 10 Decr1 600 8 100 10 40 400 6

OCR(pmol/min) 50 200 4 ECAR(mpH/min) 5 20 2 Relative expression Relative 0 expression Relative expression Relative 0 0 0 0 GL7 GL7 naive naive Cd138 CD138 IgM/CD40 IgM/CD40 naive naive naive GC b cell b GC GC b cell b GC cell b GC plasmablast plasmablast plasmablast

4000 naive B cell 8000 GC B cell 4000 plasmablast

C 3000 6000 3000

2000 4000 2000 ATP pMoles ATP pMoles 1000 ATP 2000 pMoles 1000

0 0 0 -‐ eto -‐ eto -‐ eto

Figure 9: Limited role for FAO in plasmablasts and GC B cells. qPCR analysis of genes associated with FAO in naïve B cells, GC B cells, and plasmablasts (A). OCR and ECAR levels were determined by extracellular flux assays at baseline and after the addition of the FAO inhibitor etomoxir (B). ATP production was also determined before and after etomoxir treatment (C).

202 A Spleen mass (mg) Splenocyte # (x 10^6) B AscitesAscites volume volume (ml) (ml)

500 500 4 3

400 400 3 2

6 Figure 10: Treatment with metformin or eto- 300 300

2 moxir does not affect bm12 disease devel-

200 10 x Cells 200 1 Spleen mass (mg) mass Spleen

Ascites volume (ml) volume Ascites opment. Mice were treated for 2 weeks starting Ascites volume (ml) volume Ascites 1 100 100 1 day after bm12 transfer with either metformin,

0 0 0 0 etomoxir, or vehicle controls. Splenomegaly was

Naïve Naïve naive Vehicle Vehicle Vehicle naive Etomoxir Etomoxir Metformin Metformin Vehicle Metformin Etomoxir Metformin Etomoxir assessed by spleen mass and total splenocytes Tfh graft GC B cells Plasma cells number (A). Ascites volume was also measured 5 C 20 20 (B). The absolute numbers of bm12 Tfh, GC B 4 15 15 cells, and plasmablasts were determined by flow 6 6 3 6 cytometry (C). 10 10 Cells x 10 x Cells

Cells x 10 x Cells 2 10 x Cells

5 5 1

0 0 0

naive Naïve Naïve Vehicle Vehicle Vehicle Etomoxir Etomoxir Metformin Metformin Etomoxir Metformin

Inhibition of glycolysis, but not FAO, blocks disease development in vivo As Tfh cells, GC B cells, and plasmablasts in the bm12 model utilize both glycolysis and FAO for their energy production, we next determined the relative contribution of each pathway to disease development.

To address the contribution of FAO to disease, mice were treated with etomoxir for 2 weeks, starting the day after bm12 CD4 T cell transfer. As an additional control, a group of mice were treated with low doses of metformin that did not alter systemic glucose levels but reduced mitochondrial ATP production through the inhibition of mitochondrial complex 1. Mice treated with metformin did not show a significant change in the frequency or absolute number of Tfh cells, GC B cells, and plasmablasts compared to vehicle treated mice (fig.10.a,c). Treatment with etomoxir also did not affect the frequency or absolute number of Tfh cells, GC B cells, and plasmablasts, but resulted in a small reduction of ascites (fig.10.b).

Daily intraperitoneal treatment of mice with 2-DG significantly reduced splenomegaly, ascites, accumulation of Tfh, GC B cells, plasmablasts (fig.11.a-c). Interestingly, the Tfh

203 Ascites volume (ml) A Spleen spleen mass (mg) mass Splenocyte splenocyte # (x 10^6) # B ascites volume 300 200 3

150 200 2 6

100 Cells x 10 x Cells 100 1 Spleen mass (mg) mass Spleen 50 (ml) volume Ascites

0 0 0

2-DG Naïve 2-DG Naïve 2-DG naive Vehicle Vehicle Vehicle 2-‐DG 2-‐DG 2-‐DG naive naive naive vehicle vehicle Tfh graft vehicle GC B cells Plasma cells C 4 T7 8 GC B cells 8 plasmablasts

3 6 6 6 6 6

2 4 4 Cells x 10 x Cells Cells x 10 x Cells Cells x 10 x Cells

1 2 2

0 0 0

2-DG naive 2-DG Naïve 2-DG Naïve Vehicle Vehicle Vehicle 2-‐DG 2-‐DG 2-‐DG naive naive naive vehicle vehicle vehicle

Ascites volume (ml) bm12 vivobm12 2nbdg vivo uptake 2nbdg T uptakeand B T and B A Spleen spleen mass (mg) mass Splenocyte splenocyte # (x 10^6) # B ascites volume D 300 200 3 1500 1500 TfH TfH GC b cell GC b cell 150 200 2 plasma cellplasma cell 6 1000 1000 T naive T naive 100 naive B cellnaive B cell Cells x 10 x Cells 100 1 Spleen mass (mg) mass Spleen 50 (ml) volume Ascites 500 500 GeoMFI2NBDG GeoMFI 2NBDG GeoMFI 0 0 0

2-DG Naïve 2-DG Naïve 2-DG naive Vehicle Vehicle Vehicle 2-‐DG 2-‐DG 2-‐DG naive naive naive vehicle vehicle Tfh graft vehicle GC B cells Plasma cells 0 0 10 10010 1000100 100001000 10000 C 4 T7 8 GC B cells 8 plasmablasts GeoMFI GlutGeoMFI 1 Glut 1

3 6 6 6 6 6

2 4 4 Cells x 10 x Cells Cells x 10 x Cells Cells x 10 x Cells

1 2 2

0 0 0

2-DG naive 2-DG Naïve 2-DG Naïve Vehicle Vehicle Vehicle 2-‐DG 2-‐DG 2-‐DG naive naive naive vehicle vehicle vehicle

bm12 vivobm12 2nbdg vivo uptake 2nbdg T uptakeand B T and B FigureD 11: Inhibition of glycolysis by 2-DG protects mice from bm12 disease. Mice were treated two 1500 1500 weeks with either 2-DG or vehicle TfHstartingTfH 1 day after bm12 transfer. Splenomegaly was assessed by GC b cell GC b cell spleen mass and total splenocytes numberplasma cell plasma(A). Ascitescell volume was also measured (B). The absolute num- bers1000 of 1000bm12 Tfh, GC B cells, and plasmablastsT naive T naive were determined by flow cytometry (C). Glut1 expression versus in vivo uptake of 2-NBDG wasnaive plotted B cellnaive for B cell four individual control mice (D).

500 500 GeoMFI 2NBDG GeoMFI GeoMFI 2NBDG GeoMFI response was reduced by approximately 50%, the reduction in GC B cells and plasmab-

0 0 lasts10 was10010 close1000100 to100001000 90%.10000 This difference in impact of 2-DG treatment suggests that the GeoMFI GlutGeoMFI 1 Glut 1 development of GC B cell and plasmablast responses was more dependent on glycolysis than the development of the Tfh compartment.

In agreement with this observation, our in vivo administration of fluorescent 2-NBDG uncovered a significant difference in the uptake of glucose when these cell populations were compared in vivo (fig.11.d). Plasmablasts and Tfh expressed similar levels of Glut1, but plasmablasts were approximately 4-fold more efficient in the uptake of 2NBDG in vivo. GC B cells expressed 10-fold lower levels of Glut-1 than Tfh, but were still twice as efficient in the uptake of 2-NBDG in vivo (fig.11.d). Similar results were found in the spontaneous B6.Nba2 model with high glucose uptake in GC B cells and plasmablasts and significantly lower uptake in Tfh(supplemental fig. 3).

204 nba2 vivo 2nbdg uptake T and B 1000 TfH GC b cell 800 plasma cell Supplemental Figure 3: Glut1 versus in T naive 600 naive B cell vivo 2-NDBG uptake in B6.Nba2 mice. Cells were stained with antibodies toward 400 Glut1 after in vivo 2-NBDG labeling. Data

GeoMFI 2NBDG GeoMFI are shown for 5 individual B6.Nba2 mice 200 which had developed proteinuria.

0 100 1000 GeoMFI Glut 1

To further dissect the effect of glycolysis on Tfh and the B cells response, mice were either given 2-DG in the drinking water for the entire duration of the experiment (day 2-14) or only during the second week (day 8-14) and analyzed on day 7 and day 14. 2-DG treatment of mice for seven days did not affect the proliferation or accumulation of bm12 CD4 T cells compared to vehicle-treated mice (fig.12.a). Importantly, the percentage and level of expression of CXCR5 and PD-1 was comparable in the bm12 CD4 T cells between 2DG and vehicle treated animals, suggesting that the early development of Tfh cells was not impacted (data not shown). At this time no significant increase in GC B cells or plasmablasts over naïve mice was observed (fig.12.a).

Analysis on day 14 showed markedly reduced Tfh responses and the absence of GC B cell and plasmablast development in mice continuously treated with 2-DG (fig.12.b). Mice that were only treated for the second week of the model resulted in a partial reduction in Tfh compared to continuously treated mice. The frequency of Tfh in these mice was higher than the frequency observed at seven days after CD4 T cell transfer indicating that the Tfh continued to accumulate, even in the absence of glycolysis. However, 2-DG treatment for only the second half of the model still completely inhibited the expansion of GC B cells and plasmablasts, resulting in levels observed in naïve mice (fig.12.b). Together these data indicate that Tfh can develop in the absence of glycolysis, but that GC B cell and plasmablast responses are critically dependent on glycolysis.

205 A Tfh plasmablasts plasmablasts 6 1.0 0.8

0.8 0.6 4 0.6 0.4 0.4 2 0.2 0.2 # CD45.1 Tfh/spleen # CD45.1 Tfh/spleen # CD45.1 Tfh/spleen # CD45.1 0 0.0 0.0

2-DG 2-DG naive 2-DG naive control control control

donor cells B donor T# cells x GC B cells plasmablasts 40 20 3 6 ) 6

30 15 2 4

20 10 1 2 % in cells B % % in spleen in % 10 5 % in CD4+% cells # Tfh/spleen # (10 0 0 0 0

naive naive control control control control 7 day 2DG 7 day 2DG (d1-14) 2DG 2DG contiin 2DG contiin (d8-d14) 2DG (d1-14) (d8-d14)2DG 2DG

Figure 12: The inhibition of glycolysis predominantly blocks plasmablast and GC B cell development. Mice were provided drinking water with or without 2-DG. After one week, bm12 Tfh, plasmablasts, and GC B cells were enumerated in mice given drinking water with 2-DG, control water, or mice which did not receive bm12 cells (naïve) (A). In parallel experiments, bm12 Tfh, GC B cells, and plasmablasts were determined after two weeks of treatment (B).

206 Discussion Here we show that Tfh metabolism is elevated in Tfh cells from mice with inducible and spontaneous characteristics of SLE. The Tfh cells showed a strong shift to aerobic glycolysis and limited increase in OXPHOS. Similar results were found in GC B cells and plasmablasts. Consequently, treatment of mice with agents that inhibited OXPHOS (metformin) or FAO (etomoxir) had no effect on disease development while blocking of glycolysis at the level of the hexokinase step significantly reduced Tfh numbers and completely prevented the development of the B cell response. Together, these data suggest that aerobic glycolysis is the main driver of disease development and that OXPHOS using either fatty acids, glutamine, or pyruvate derived from glycolysis as carbon source is of lesser importance.

These exciting findings are somewhat in contrast with the observations made in two recent papers from Yin et al.14,15. Both studies show that disease development in the spontaneous B6.Sle1Sle2Sle3 model and the B6.MRL-Faslpr could be blocked with either the inhibition of glycolysis (2-DG), or the inhibition of complex I in the mitochondrial electron transport chain (metformin). A combination of both was required to prevent progression of ongoing disease. These studies concluded that oxidative glycolysis, but not aerobic glycolysis was the main driver of pathogenesis and that the effect resulted from an inhibition of the CD4 T cell response. Importantly, these studies do not take into account the metabolic requirements of B cells, key mediators of clinical disease manifestations in these animals.

There are several significant differences in the approach between their models and our models that could provide explanations for the divergent conclusions. Where the studies by Yin et al. used total CD4 T cells from sick mice as well as in vitro activated naïve T cells, we directly compared Tfh cells and naïve T cells. Our data indicate that Tfh cells have a very distinct metabolic profile that is significantly different from naïve T cells and

207 from in vitro activated T cells. Consequently, conclusions on the metabolic profile of cell populations relevant for disease development cannot be made in a mixed population, nor can they be reliably extrapolated from in vitro activated naïve CD4 T cells. Our data suggest that Tfh predominantly use aerobic glycolysis. The inhibition of glycolysis (at the HK level) completely blocked ECAR without affecting OCR. If oxidative glycolysis was critically important for Tfh, we would have expected to see a drop in OCR upon treatment with 2-DG. It is still possible that oxidative glycolysis does occur, and that the Tfh increase the oxidation of another carbon source (glutamine or FA), resulting in a seemingly unaltered OCR. Experiments blocking glycolysis in the absence of other carbon sources would clar- ify the relative contribution of oxidative glycolysis in these cells.

The Ying paper also incorporated the use of dichloroacetate (DCA) that inhibits the conversion of pyruvate into lactate. The authors concluded that this treatment did not alter disease as they did not see significant changes in their percentage of Tfh cells in the total CD4 T cell population and metabolic assessment of the total CD4 population. However, their data shows significant reduction in ANA levels, indicating an important role for the pyruvate-lactate conversion in disease development. Our preliminary data with DCA in the inducible SLE model were not significant due to the small sample size and large standard deviation. Further studies using DCA will need to be completed to determine whether DCA can affect Tfh development, or whether its effects may primarily affect the development of B cell subsets.

Another large difference between the Yin papers and our study is the choice of model. Whereas they used the spontaneous B6.Sle1Sle2Sle3 model and the B6.MRL-Faslpr model, we predominantly used the inducible bm12 model, which is a chronic GVH model of SLE. The accelerated development of disease in this model may shift the metabolic requirements to a somewhat more acute model that would favor aerobic glycolysis. A recent

208 paper by Nguyen et al., studying the metabolic programming of alloantigen-activated T cells after hematopoietic cell transplant (BM + T cells) in a lethally irradiated host, showed that T cells switched from FAO and oxidative glycolysis to a more aerobic glycolysis phenotype with increased dependency on glutaminolysis16. While this model shows several similarities with our model, it also adds the complexity of the absence of a normal immune system in the recipient, homeostatic expansion, as well as the inflammatory response after lethal irradiation. Interestingly, flow cytometric analysis of cells from the B6.Nba2 mice showed comparable changes in Glut-1 expression, 2-NBDG uptake and phosphorylation of 4EBP1 and S6K in Tfh cells, GC B cells, and plasmablasts to those seen in the inducible bm12 model, suggesting that many of the phenomena seen in the bm12 model also translate to the spontaneous model. However, additional studies using Tfh cells, GC B cells and plasmablasts from B6.Nba2 mice will be needed to confirm this assumption.

Through the isolated assessment of metabolic pathways in Tfh, we found that the expansion of Tfh was dependent upon similar metabolic program to other T helper subsets, including Th1, Th2, and Th17 cells. Namely, Tfh relied upon aerobic glycolysis and to some extent FAO; however, we were surprised to find that blocking glutaminolysis with AOA had no observable effect on the metabolic activity within Tfh. These results are suggestive that glutamine is not a primary player in intracellular recycling of amino acids that contribute to Tfh amino acid homeostasis. Additionally, although glutaminolysis can also replenish TCA cycle intermediates that are utilized for biosynthesis, Tfh may overcome this need through alternative mechanisms. With relatively high levels of glucose import, Tfh may shuttle glucose toward the pentose phosphate pathway (PPP), which is capable of amino acid and nucleotide biosynthesis. Further studies are required to examine the importance of the PPP in Tfh development.

Our metabolic assessments on purified cells indicated that both Tfh and B cells use FAO

209 to meet their metabolic needs. In vitro etomoxir treatment significantly reduced OXPHOS and ATP production in all tested cell subsets (without affecting viability). However, treatment with etomoxir in vivo did not alter the frequency or absolute number of Tfh cells, GC B cells or plasmablasts. Only a trend towards less ascites was observed (fig.10.b). It is possible that the Tfh cells, GC B cells, and plasmablasts do not require FAO or OXPHOS to properly expand and accumulate in vivo. However, it is also possible that these cells do require FAO, but that the effect of etomoxir is masked by an effect on a different cell population. Tregs have been shown to require FAO for their development and accumulation. It is indeed possible that treatment with etomoxir affects the Treg population in either number or function, thereby allowing the pathogenic response to increase. In this scenario the direct effect of etomoxir on the Tfh cells GC B cells and plasmablasts would be masked by the enhanced accumulation due to relaxation of the external regulation. Further analysis of the Tregs in this model could provide insight on the validity of this hypothesis.

Our in vivo glycolysis inhibition studies provided further insight into the metabolic requirements of the cell subsets we examined in vitro. Although Tfh clearly utilized glycolysis in our ex vivo assays, their in vivo dependence upon glycolysis was less clear. Tfh developed normally when glycolysis was blocked for the first 7 days after transfer, but when glycolysis was inhibited during days 8-14, their accumulation was constrained. This could be due to distinct temporal metabolic requirements, or it could be due to the close dependence of Tfh maintenance and expansion on the activity of GC B cells17. GC B cells, which develop with delayed kinetics compared with Tfh18, appeared extremely sensitive to the inhibition of glycolysis—their development was completely blocked by short- or long-term 2-DG administration. Thus, the inability of GC B cells to expand when glycolysis was blocked during days 8-14 may have indirectly stifled further Tfh expansion beyond what occurred in the first 7 days. Plasmablasts also failed to expand when mice were treated with 2-DG, indicating that the B cell compartment was particularly reliant upon glycolysis.

210 In B cells, a clear correlation between Glut1 expression, uptake of 2-NBDG, and the developing response was seen (fig.11.b). Naïve B cells had low levels of Glut-1 and 2-NBDG uptake, GC B cells had intermediate levels of Glut-1 and 2-NBDG, while plasmablasts expressed the highest levels of Glut-1 and 2-NBDG. Interestingly, studies in the aged B6.Nba2 mice indicated that Glut1 expression and 2-NBDG uptake was comparable in plasmablasts in the spleen and plasma cells in the bone marrow, suggesting that these later developmental stages have comparable glycolytic needs (data not shown).

Interestingly, Tfh did not fit the correlation of Glut1 expression and 2-NBDG uptake seen in B cells. Tfh expressed significantly higher levels of Glut-1 compared to GC B cells, although they imported less glucose. In fact, Tfh cells expressed similar levels of Glut-1 protein as plasmablast and plasma cells but internalized 3-fold less 2-NBDG. Where one could suggest the lower uptake in GC B cells and Tfh cells resulted from higher com- petition and perhaps lower levels of 2-NBDG in the GC compared to the extrafollicular plasmablasts, this does not explain the differences between the GC B cells and Tfh cells. GC B cells expressed 10-fold lower levels of Glut-1 than Tfh, but still imported twice as much 2-NBDG. A simple explanation would be that glucose transporters other than Glut-1 contribute to the glucose uptake in GC B cells. Currently, 13 glucose transporters have been identified, with many of them based on sequence homology and with little functional data available. There is speculation that each glucose transporter isoform could play a specific role in glucose metabolism that is determined by its pattern of tissue expression, substrate specificity, transport kinetics, and regulated expression under different physiological conditions. Further characterization of these importers and their expression may provide a better explanation for how these cell subsets meet their distinct glycolytic needs.

Together, our data show that Tfh, GC B cells, and plasmablasts from mice and humans

211 utilize aerobic glycolysis to meet their metabolic needs. Our findings that disrupting glycolysis via 2-DG in the bm12 model blocked disease development and inhibited the expansion of these key cell subsets has important implications for pathology of SLE. Fi- nally, these studies uncover a potential new avenue for targeting Tfh, GC B cells, and plasmablasts in SLE as well as during other harmful or otherwise unwanted inflammatory immune responses.

212 Materials and Methods Mice and SLE models Mice were maintained under specific pathogen-free conditions in accordance with guidelines by the Association for Assessment and Accreditation of Laboratory Animal Care International. B6(C)-H2-Ab1bm12/KhEgJ mice were purchased from The Jackson Labora- tory and crossed to a B6.SJL.Ptpcra (B6/CD45.1) background (bm12-CD45.1). C57BL/6J mice were bred in our facility. B6.NZB(D1Mit47-D1Mit209)/BkotJ mice (B6.Nba2) that contain the NZB-derived lupus susceptibility QTL (Nba2) and spontaneously develop antinuclear antibodies and proteinuria were a gift from Dr. Divaker Chaubey, (UC Cincinnati, Cincinnati) and were aged in-house.

For the inducible SLE-like model, 8 x 106 negatively selected CD4+ T cells (Miltenyi, Bio- Legend) from Bm12-CD45.1 mice were i.p. transferred into B6 WT recipients19–21. T and B cell responses in the spleen and bone marrow were analyzed at 14 days after transfer unless stated otherwise18. Serum levels of anti-dsDNA IgG, IgG1 and IgG2a were determined by ELISA as previously described22.

Interference with metabolism in vivo was achieved by daily intraperitoneal injections of 2-DG (1 mg/g), metformin (0.1 mg/g) or etomoxir (15 ug/g), or administration of 2-DG in the drinking water (10 mg/ml) for the duration described in the results section. In vivo glucose uptake studies were performed by intravenous administration of 200 ug 2-NBDG followed with tissue harvest 15 minutes later.

Human donors Blood samples from 3 healthy de-identified donors was procured via the Cell Processing Core at CCHMC. PBMC were isolated by density-gradient-separation and cultured with 100 uM 2-NBDG for 20 minutes (Life Technologies) before staining for flow cytometric

213 analysis. Human T cells were analyzed using antibodies to CD4, CD3, CXCR5, PD-1, (Bi- oLegend) Glut1 (R&D Systems), together with a fixable viability dye (Life Technologies). Human B cells panels included CD19, IgD, IgG, CD27, CD38, HLA-DR (BD Pharmingen), Glut-1 and fixable viability staining. For analysis purposes cells CD19+IgD+IgG- CD27- were considered to be naïve B cells, CD19+IgD-IgG+ CD27+ CD38- switched memory B cells, and CD19+IgD-IgG+ CD27+ CD38+ plasmablasts. Samples were collected on a LSRII flow cytometer with Diva software (BD Pharmingen), and data were analyzed with FlowJo software (Tree Star).

Flow cytometry and cell sorting Assessment of mouse T cells was performed using combinations of the following antibodies CD4, CD45.1, CD45.2, CXCR5, PD-1, CD69, Icos, Bcl-6, pS6K, p4EBP1, (BioLeg- end) Glut-1, together with a fixable viability staining. Murine B cell panels included combinations of antibodies to CD19, B220, CD138, GL7, CD95, CD69 (BioLegend), pS6K, p4EBP1 (Cell Signaling), Glut-1, together with a fixable viability staining. Samples were collected on a LSRII flow cytometer with Diva software (BD Pharmingen), and data were analyzed with FlowJo software (Tree Star). T cell sorting of bm12 Cd45.1 T cells was performed by Moflo (Beckman Coulter) based on expression of CD45.1, PD-1 and CXCR5 and viability dye. B cells were sorted based on their expression of B220, CD19, CD138, GL7 and viability for metabolism experiments and gene expression. Naïve T cells and B cells were isolated based on their absence of CD69 and expression of CD62L and were used as controls. In general, purity was greater than>99% and viability >95%.

Gene expression and RNAseq Purified bm12 CD4 T cells were processed with mirVANA lysis buffer (Life Technologies). RNA was extracted according to the mirVANA RNA extraction kit protocol. Subsequently,

214 300 ng of total RNA was purified by the NEBNext Poly(A) mRNA Magnetic Isolation Mod- ule (New England BioLabs, Ipswich, MA). The NEBNext Ultra Directional RNA Library Prep Kit was used for library preparation. Bioanalyzer (Agilent, Santa Clara, CA) analyses using a DNA high sensitivity chip were performed to determine quality and yield of the purified library. To study differential gene expression, individually indexed and compatible libraries were proportionally pooled (20-50 million reads per sample) for clustering in cBot system (Illumina, San Diego, CA). Libraries at the final concentration of 15 pM was clustered onto a single read (SR) flow cell using TruSeq SR Cluster kit v3, and sequenced for 50 bp using TruSeq SBS kit on an Illumina HiSeq system. Sequence reads were then aligned to the genome by using a standard Illumina sequence analysis pipeline by The Laboratory for Statistical Genomics and Systems Biology at the University of Cincinnati. Genes of interest were confirmed by standard quantitative PCR using SyBRGreen and L32 as an internal control as described before.

Metabolic assays In vitro glucose uptake: for in vitro glucose uptake, cells were cultured for 30 minutes with 100 uM 2-NBDG at 37C, 5% CO2 before staining with the indicated antibodies and subsequent flow cytometric analysis. Real-time analysis of oxidative phosphorylation (Seahorse XF96): Tfh cells, GC B cells, and plasmablasts were purified from spleens from mice in the inducible bm12 SLE model. Naïve CD4 T cells and B cells as well as in vitro activated CD4 T cells (CD3/CD28, 1 ug/ ml, 48 hr) and in vitro activated B cells (CD40 (1 ug/ml) + IgM (10 ug/ml), 48 hr) were used as controls. Purified cells (5 × 105) were plated in XF-96 extracellular flux analysis plates (Seahorse Bioscience) in XF running buffer adapted for the different assays as described below. The oxygen consumption rate (OCR) and the extracellular acidification rate (ECAR) were determined after correction for protein content in each well. To assess overall metabolic health, cells were plated in XF media (supplemented with

215 10 mM dextrose, 2 mM L-glutamax) and cells were sequentially challenged with 10 μM oligomycin, 4 μM FCCP, and 1 μM rotenone plus 10 μM antimycin A (Sigma-Aldrich). For the glycolysis stress test cells were plated in XF media without dextrose or pyruvate and sequentially treated with glucose (final conc. 10mM), oligomycin (final conc. 10 uM), and glycolysis inhibitor 2DG (final conc. 50 mM). For the glutaminolysis stress test cells were plated with XF media without glutamine and treated with glutamine (final conc. 2 mM) followed by glutaminolysis inhibitor AOA (final conc. 100 uM). Fatty acid oxidation was assessed by culturing cells in XF medium (with glucose and glutamine) and blocking the mitochondrial fatty acid importer CTP1 by etomoxir (final conc. 200uM). ATP production: Intracellular ATP levels were assessed in indicated purified cell populations with indicated treatments (20 min, concentrations listed above) by Adenosine 5’-triphosphate (ATP) bioluminescent assay kit (Sigma-Aldrich).

Statistical analyses Data were analyzed using Prism software (GraphPad Software, Inc.). Unless stated otherwise, the data are expressed as means ± SEM. All data were evaluated using a student’s t test (for comparisons of two groups), or a one-way ANOVA (for comparisons of three or more groups) followed by a Dunnett’s test. A p value of <0.05 was considered statistically significant.

216 References

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218 Chapter 8. Summary and Discussion

219 Overall Summary

Immune responses to dying cells are kept in check by multiple layers of immune regulation to avoid autoimmunity. Nevertheless, immune responses to dying cells can and do occur. In some cases these responses prevent the outgrowth of neoplasms, whereas in other cases, they contribute to autoimmune disease. The goal of the studies conducted and reported in this dissertation was to elucidate molecular mechanisms responsible for driving sterile inflammation and immune responses to self antigens. Further insight into these pathways could allow for the development of novel interventions for transplantation, cancers, and autoimmune diseases. Type I IFN has been identified as a central mediator of several sterile inflammatory processes. Spontaneous immune responses to tumor cells1,2, immune responses to dying tumor cells following ablative therapies3,4, and several autoimmune diseases, especially SLE5–7, all rely upon IFN signaling; however, relatively little is known concerning the precise functions of IFN in the development of these immune responses. Moreover, the pleiotropic and sometimes opposing effects of type I IFN make determining its functions in disease difficult8. We have employed reductionist approaches to decipher specific roles of IFN signaling in sterile inflammation, despite its complexity. Additionally, our studies have defined the individual metabolic needs of the T and B cell subsets as being particularly important for driving autoimmunity.

The studies reported in this dissertation reveal several novel mechanisms driving sterile inflammatory processes, with a special emphasis on defining the roles of type I IFN (Figure 1), and the metabolic reprogramming required for the development of key cells associated with humoral autoimmunity. Specifically, the major findings and conclusions of this dissertation are:

220 Chapter 5a: Successful tumor ablative therapies, including radiation and cryother- apy, rely upon STING-mediated type I IFN production, and the CD8 T cell responses it supports. i. Although essentially all nucleated cells express type I IFN, DC sensing of type I IFN is necessary to drive antitumor CD8 T cell responses following ablative therapy (Figures 3 and 7F-I). ii. Not only do DCs need to sense type I IFN for optimal T cell priming, DCs are the chief producer of type I IFN in response to dying tumor cells which have been killed by multiple agents, including gamma radiation, ultraviolet radiation, or the DNA-damaging chemotherapeutic etoposide (Figure 4 and data not shown). iii. Type I IFN induction requires the cytosolic signaling intermediate (and DNA sensor in its own right) STING, as well as IRF3, but not TLRs or RLRs (Fig- ures 5 and 7). iv. The STING/IRF3 axis is activated in response to nuclear DNA, but not RNA or mitochondrial DNA (Figure 6).

Chapter 5b: The bm12 cGHVD model of lupus relies upon recipient STING and IF- NAR expression. i. Recipient STING and IFNAR are critical to the expansion of bm12 Tfh cells and activated CD4 T cells (Figure 8b). ii. Recipient STING and IFNAR augment the development of GC B cells, plasmablasts, and ANA in bm12 disease (Figure 8b).

Chapter 6: Type I IFN sensing by CD4 T cells is essential for the expansion of Tfh and ensuing disease in the bm12 model of SLE. i. In an apparent paradox to the well-studied anti-proliferative effects of IFN,

221 Ifnar-deficient bm12 CD4 T cell expansion is minimal compared to that of WT controls, despite normal differentiation into Tfh (Figures 1 and 2). ii. The effect of IFN on Tfh is direct: co-transfer of WT and Ifnar -/- bm12 CD4 T cells did not restore the expansion of Ifnar -/- Tfh (Figure 3). iii. IFN exerts opposing functions: it simultaneously inhibits CD4 T cell proliferation and protects Tfh from being killed by NK cells (Figures 5, S3, and 8). iv. NK killing of Tfh is perforin-dependent. In the absence of perforin, Ifnar -/- Tfh expand to even greater numbers than WT Tfh (Figure 7). v. The generation of GC B cells and plasmablasts is IFN-dependent, but independent of NK cell regulatory pressure (Figure S6).

Chapter 7: Blocking glycolysis in the bm12 transfer model completely abrogates lupus-like disease: Metabolic profiles of Tfh, GC B cells, and plasmablasts show that each is heavily dependent upon glycolysis. i. RNAseq analysis on naïve bm12 CD4 T cells and bm12 Tfh (bm12 CD4 T cells two weeks after transfer into C57BL/6 mice) revealed a large number of differentially expressed genes involved in glycolysis, FAO, and to a lesser extent glutaminolysis. Careful examination of metabolic pathways revealed that Tfh from the bm12 and B6.Nba2 SLE models met their energetic needs through glycolysis and FAO, but not glutaminolysis (Figures 1-5). ii. Parallel studies in GC B cells and plasmablasts from bm12 and B6.Nba2 mice showed that these activated B cell subsets were more heavily dependent upon glycolysis, with less FAO, and no utilization of glutaminolysis (Figures 7-9). iii. Increased glucose transport was also observed in SLE patients’ circulating follicular helper-like T cells and B cells with phenotypic

222 markers of plasmablasts (Figures 3 and 7). iv. In vivo disruption of glycolysis using 2-deoxy-D-glucose (2-DG) nearly completely inhibited disease development in the bm12 model. Of note, Tfh numbers were reduced by half, whereas GC B cell and plasmablast numbers were reduced more than 5-fold compared to controls, underscoring the relative importance of glycolysis to the development of these cells (Figures 11 and 12).

Figure 1. Working model: the critical roles for type I IFN in antitumor immunity and bm12 lupus-like disease. Red lines indicate the multiple effects of type I IFN demonstrated by the work presented herein. We demonstrated that the STING/IRF3 pathway is activated upon the uptake of dying cell material by DCs. Furthermore, STING activation is dependent upon nuclear DNA and leads to the production of type I IFN by DCs. Subsequently, type I IFN signaling within DCs, but not CD8 T cells, promotes the productive priming of CD8 T cells toward cell-associated antigens (Chapter 5). We also showed that type I IFN sensing by CD4 T cells and B cells was important for the development of autoimmunity in the bm12 cGVHD model of lupus. The expansion of CD4+ Tfh cells was limited by NK cell killing, but the direct action of type I IFN on Tfh prevented this killing, allowing better expansion and advanced disease progression. B cells were not NK cell targets, however plasmablast and GC B cell expansion was also augmented by type I IFN through as of yet unknown molecular mechanisms (Chapter 6). We also examined the metabolic program of Tfh, plasmablast and GC B cells in bm12 disease. The green text depicts the relative dependence of these cell types on glycolysis or fatty acid beta-oxidation (FAO), as indicated by font size. None of these cell types were found to utilize glutaminolysis for their energetic needs. All utilized glycolysis, and to a lesser extent, oxidative phosphorylation downstream of FAO (Chapter 7).

223 Discussion

Despite years of intensive research, the current clinical strategies to boost anticancer immune responses still fail to produce durable protective immunity. Uncovering the molecular pathways that underlie immune responses to dying tumor cells may have significant impact on future treatments; many of the pitfalls of current strategies may be avoided by exploiting the existing mechanisms that promote these immune responses. Yet as we advance our understanding of the sterile inflammation that gives rise to immune responses toward cell-associated antigens, we must also examine whether any of these processes also contribute to autoimmune disease. Further mechanistic knowledge may also greatly benefit treatments for autoimmune diseases, not only increasing their efficacy, but increasing specificity, which may also reduce the complications associated with generalized immunosuppression. The sections that follow will discuss broad implications of the work contained within in the body of this dissertation, and will pose questions to be addressed by future studies.

In the Chapter 5, we found that nuclear DNA sensing drove STING-mediated type I IFN production, thereby enhancing immune responses to tumor cell-associated antigens. We identified DCs as the producers of IFN and the cell type whose sensing of IFN promoted antitumor CTL function. These findings have important implications for future work. Giv- en the amount of effort put into the development of DC-based cancer vaccines and the relatively meager clinical results of those efforts, some authors have suggested that mac- rophages9 or B cells10 may be viable alternatives to DCs as professional APCs capable of initiating antitumor responses. Our data strongly suggest that DCs are the predominant cell type that productively primes antitumor CTLs naturally, and underscore the importance of DC exposure to type I IFN during CTL priming. Moreover, our data showing that

224 nuclear DNA structures induce type I IFN via the signaling adapter STING also provide a novel signaling pathway that might be therapeutically enhanced during priming. Current DC-based vaccine studies have targeted Toll-like receptors as adjuvants which can induce the production of type I IFN11; however, activating STING may represent an alternative approach with a more nuanced signal that provides more effective and longer lasting protection. We found that STING also promoted autoimmunity in the bm12 cGHVD model of SLE. Thus, treatments specifically inhibiting the STING pathway may provide a way to reduce autoimmunity without compromising the ability to fight infections, a common side effect to the generalized immunosuppressive approaches currently employed12,13.

The precise ligand or ligands which activate STING in our model systems are still unknown, as are the receptor(s) upstream of STING. Do dying cells activate STING through endogenous cyclic di-nucleotides produced by cyclic GMP-AMP synthase (cGAS)? Or do upstream cytosolic DNA sensors, such as DDX41, IFI16, or possibly DAI activate STING signaling? No known DNA sensor upstream of STING has been implicated by genome-wide association or sequencing studies, although rare mutations in the cytosolic exonuclease TREX114–17 are believed to dramatically increase the risk for SLE. Further- more, a loss-of-function variant of MAVS, the signaling intermediate downstream of the cytosolic RNA sensors RIG-I and MDA5, has been associated with a subset of lupus patients with a unique clinical phenotype, including reduced circulating type I IFN levels compared with controls18. As further progress is made in defining the candidate receptors upstream of STING, their involvement in SLE can be interrogated. And, greater insight into the ligands and receptors upstream of STING could provide an even more specific and effective target for future anticancer immunotherapies and treatments for autoimmune disease.

After showing a role for STING in the bm12 inducible model of SLE, and that disease was

225 partially dependent upon type I IFN sensing by recipient cells, we saw an opportunity to easily test whether the transferred bm12 CD4 T cells also depended upon IFN for disease induction. To our surprise, we found that disease was even more dependent upon CD4 T cell sensing of type I IFN than IFN sensing by any other cell type in the model. We went on to discover that the type I IFN produced in this system protected bm12 Tfh from being killed by NK cells. These findings raise a number of intriguing questions. One of the central questions that emerges is how does type I IFN protect Tfh from NK attack? NK regulation of T cell responses during infection has been the subject of other recent studies19–22, and some evidence has suggested that IFN signaling reduces the expression of an as of yet undetermined NKp46 ligand22. However, in our studies, we did not detect NKp46 ligand expression, nor did NKp46 deficient NK cells exhibit reduced killing of IFN-insensitive Tfh.

Whether the protective effect of IFN on CD4 T cells is multivariate or context-dependent is yet to be determined and remains an interesting question for future studies. We employed RNAseq as an unbiased approach to determine differentially expressed RNA transcripts, with the hope of discovering differentially expressed NK ligands in our WT and Ifnar -/- Tfh. Unfortunately, analyses of these data did not provide any indication as to how IFN protected the Tfh from NK cells. Future studies utilizing single cell RNAseq would allow for a more precise analysis, where subsets of especially stressed cells may emerge, and may show differential expression of certain NK ligands. As the science of proteomics develops, this may be an even more appropriate method to answer this question, since it has been well established that RNA transcript levels do not always reflect differences in protein levels, and it is protein, not RNA, which largely mediates cellular functions.

We also found that type I IFN sensing by B cells is crucial to the development of GC B cells and plasma cells in bm12 disease. This expands upon previous reports that show

226 that the addition of exogenous type I IFN can enhance the ex vivo differentiation of B cells toward a plasma cell phenotype23,24, and that using IFN as an adjuvant during chicken gamma globulin vaccination increases antibody output24,25. Interestingly, the mechanisms by which type I IFN affects B cells appear to differ from those by which it affects T cells. Whereas IFN signaling protects T cells from NK cell attack, B cells were not subject to NK cell regulatory pressure in bm12 disease, and thus the effects of IFN signaling within B cells were completely independent of NK cells. Moreover, in the absence of perforin-mediated destruction, Ifnar -/- Tfh cells expanded significantly better than WT Tfh, indicating IFN exhibited an anti-proliferative effect in vivo. Despite a vast body of literature describing the anti-proliferative effects of type I IFN on various cell types (nicely reviewed by Bekisz et al.26), no such anti-proliferative effect has been reported in vitro or in vivo for B cells, and in fact here we observe the opposite effect of IFN on GC B cells and plasmablasts. In fact, previous studies using transgenic VI10 transgenic B cells also showed poorer expansion of Ifnar-deficient compared to WT plasmablasts24. One possibility, however unlikely, is that GC B cell and plasmablast expansion is controlled by an Asialo-GM1-negative cell, perhaps even CD8 T cells; in fact, CXCR5-expressing, GC-homing “follicular” CD8 T cells have recently been described, although their function remains unknown27. Future studies looking at the mechanism by which IFN sensing promotes B cell expansion should include perforin-deficient hosts, especially considering this method was more effective than NK depletion at restoring Tfh expansion in our model.

Our studies were limited to the early immune responses following the transfer of bm12 CD4 T cells into C57BL/6 mice—one exciting avenue for future studies would be to look at the longer-term effects of IFN-sensing by B cells. With longer term studies we could ask how IFN sensing by B cells affects the development of bone marrow-resident long-lived antibody-secreting plasma cells. This question could easily be answered by examining CD138-expressing, B220-negative plasma cells in the bone marrow at later time points

227 after bm12 transfer. One tool which would make these studies more practical and perhaps more physiologically relevant than mixed bone marrow chimeras, which we have used in all of our B cell experiments to date, would be mice with Ifnar-/- B cells, generated by flanking the Ifnar gene with loxP sites, and crossing them to CD19-Cre mice. One of our collaborators, Senad Divanovic, is currently generating these mice, and we are planning to perform future experiments with this tool. To determine when IFN sensing is required during disease development, an inducible Cre system could be employed. Or, to look more precisely at when IFN sensing is required during B cell development, Cγ1-Cre or AID-Cre could be utilized. AID (Aicda) is expressed mainly by GC B cells during CSR and SHM. Similarly, Cγ1 (Ighg1) is expressed upon CSR and would be found in a subset of GC B cells and plasma cells, mostly those that express IgG1. To further delineate the requirements of IFN sensing by GC B cells, plasmablasts, and plasma cells, GL7-Cre or CD138-Cre could be used. Although GL7 is also expressed on Tfh, in our bm12 model this would not be a significant confounder, since the Tfh responsible for interacting with these B cells would be the transferred bm12 cells, which would not harbor the GL7-Cre gene.

Another interesting question we could ask with longer term studies is how IFN sensing by B cells affects their memory potential. Answering this question would require even more sophisticated tools, and would probably best be tested using a transgenic B cell in another model system. Since the B cell responses we observe in the bm12 model are toward self antigens, these cells would have continual access to their cognate antigen. A transgenic system, however, would allow cells to be primed in the presence of a model antigen, rested, and then re-challenged again after several months. SWHEL mice would be an excellent model as they are transgenic for a HEL-specific BCR that is capable of CSR28. A similar IFNARfl/fl and Cre system to those proposed above could be used to determine the role of IFN sensing in the development of memory. The initial priming could

228 be done via subcutaneous challenge with soluble HEL and adjuvant. Memory could then be determined 3-6 months later after HEL-rechallenge. Approximately 2 weeks after rechallenge, single cell suspensions from bone marrow and spleen could be subjected to IgG ELISpots, and memory potential would be determined by the comparing the number of HEL-specific antibody secreting cells.

Taken together, we found that type I IFN independently increases the expansion of several key disease-causing adaptive immune cell populations—namely, Tfh, GC B cells, and plasmablasts. Importantly, each of these cell types have been implicated in the pathology of human SLE29–31. Thus, these data have significant implications for the potential of IFN or IFNAR neutralization in lupus patients, providing a mechanism as to why this strategy may be successful. Recent attempts at clinical IFN blockade via neutralizing antibodies produced poor results32,33, although the inability of these antibodies to neutralize all IFN subtypes may easily explain their failure. Early results from a phase 2 clinical trial using an anti-IFNAR antibody, however, showed that patients given the antibody, anifrolumab, had significantly reduced disease activity across multiple clinical parameters34. This treatment is currently being further investigated in a phase 3 trial.

One important consideration for the development of IFNAR neutralization therapies is how its neutralization may affect NK cell activity. Type I IFN signaling has been shown to stimulate the production of IFNγ by NK cells, and NK cells from Ifnar-deficient mice exhibit substantial reductions in their ability to kill certain target cells compared to those from WT mice35,36. This activation of NK cells by type I IFN has been shown to be critical to the protective functions of NK cells in the context of infection35 and antitumor immuni- ty36. Moreover, our findings indicate that active NK cells may also help limit Tfh cells that are participating in autoimmune germinal center reactions. Thus, removing one primary mechanism by which NK cells become activated may have a two-fold negative impact on

229 the health of patients—potentially increasing their susceptibility to infection and cancer, and removing a regulatory control of autoimmune Tfh cells. Indeed, higher incidences of influenza and herpes zoster infections were reported in patients receiving anifrolumab compared with controls in the phase 2 study of the anti-IFNAR antibody34.

We propose that a combination therapy, including neutralization of type I IFN or its receptor, and a means of boosting NK cell activity may result in a more effective treatment with fewer side effects. Of course, non-specific activation of NK cells using, for example, intravenous IL-2, IL-12, or IL-18 would not be advised, given the ability of those cytokines to activate the cells involved in the autoimmune pathology. Instead, we propose a highly targeted approach to activate NK cells either through agonists to the NK cell activating receptor NKp46 (NCR1), or by adoptive transfer of autologous ex vivo activated NK cells. Of course the practicality of the latter approach would be limited by the ability to expand NK cells from each individual undergoing treatment, but this technique has already been pioneered and is being optimized by ongoing translational research in the field of anticancer immunotherapy37. In fact, ex vivo expansion and adoptive transfer of NK cells may prove the best way of enhancing NK cell function, because despite the fact that NK cells from the periphery of SLE patients show phenotypic markers of activation, including higher percentages of CD69+ and IFN-γ+ cells, they also exhibit lower cytotoxicity, and are found in significantly reduced numbers compared to controls38,39. Thus, expanding newly generated NK cells in vitro and subsequent adoptive transfer would more likely enhance NK cell activity in vivo.

Our data within the bm12 model suggests activated NK cells would target activated Tfh in autoimmune GC reactions, but would not target B cell populations. Thus, activating NK cells is not expected to affect the reactivation of autoimmune memory B cells, but it may help prevent the generation of new autoimmune B cells by indirectly limiting GC

230 reactions40. Furthermore, transfer studies in a mouse model similar to the bm12 model showed the transfer of IL-2-activated autologous NK cells significantly limited autoantibody production41. Moreover, studies in the streptozotocin-induced model of type I diabetes (T1D) showed that the transfer of IL-18-activated NK cells delayed and partially prevented the onset of diabetes42. These studies provide substantial rationale for the potential efficacy of activated NK cell transfers in SLE, but they also highlight the possibility of a broader role for NK cell immunoregulation in additional autoimmune diseases. Actually, a type I IFN gene signature precedes the onset of T1D43,44, and the treatment of viral hepatitis with type I IFN has been shown to induce T1D45, although the role for IFN in T1D pathogenesis has not been elucidated. It would be interesting to deplete NK cells in the context of a T1D model to determine whether endogenous NK cells exert any pressure on T cells within that disease.

Our investigations into cellular metabolism, presented in the final research chapter of this dissertation, began with the hypothesis that type I IFN may exert some of its effects on Tfh cells by changing their metabolic program. Specifically, we posited that type I IFN may prevent metabolic stress, and thereby enhance the survival of activated CD4 T cells, by reducing proliferation rates and by controlling expression of c-Myc46–49 and mTOR26, both of which are known to play pivotal roles in directing cellular metabolism50–53. In fact, we did observe effects of IFN on the metabolic program of in vitro activated (anti-CD3, anti-CD28), purified CD4 T cells (Figure 2, unpublished data). We found that Ifnar-deficient CD4 T cells had a lower respiratory reserve than WT cells, and elevated glycolytic rates. These data fit the hypothesis that IFN-insensitive cells undergo greater metabolic stress than do their WT, IFN-sensing counterparts. It is interesting to speculate whether the apparent metabolic stress that IFN-insensitive Tfh are subject to contributes to their susceptibility to NK cell killing, by either expression of activating NK ligands, or a reduction of inhibitory ligands. These results were fascinating, and merit further investigation.

231 350 Oligomycin FCCP An./Rot 350 A B WT WT WTWT + IFNα

250 WT WTWT + IFN + βα IFNα Resp. Maximum IFNAR Reserve Respiratory 250 WT WT + IFN + β IFNβ Capacity IfnarIFNAR-‐/-‐ 150 Baseline Coupling Rate (OCR) OCR (pmol/min) OCR

Rate (OCR) Resp. eﬃciency 150 50 Oxygen Consump.on Oxygen Oxygen Consump.on Oxygen Proton leak (pmol/min) OCR Non-‐mitochondrial respira.on 0 20 40 60 80 Time (min) 50 Time (min.)

0 20 40 60 80 1194 1268 2NBDG_WT_001.fcs Sample

48h_IFNb at 24h_011.fcs 1004 1130 Baseline Resp. Resp. Baseline IFNb_003.fcs + 2NBDG_WT WT

C D Time (min) E 48h_IFNb at 0h_010.fcs 1702 1747 2NBDG_IFNAR_005.fcs + IFNβ

Median: Mean: Geom. Respira.on Max Reserve Glycolysis Sample Uns.m. 48h_No IFN_009.fcs 1.5 1.00 1.00 1.00 1.5 WT WT WTWT IFNAR IfnarIFNARIFNAR-‐/-‐ 0.75 0.75

1.0 0.75 1.0

1277 1359 2NBDG_WT_001.fcs

1819 1867

0.50 0.50 2NBDG_IFNAR_005.fcs WT

-‐/-‐

Median: Mean: Geom. Sample Ifnar OCR ECAR relative to WT to relative relative to WT to relative relative to WT to relative relative to WT to relative Baseline OCR Baseline 0.5 0.50 ECAR Baseline 0.5 RespiratoryReserve Max. Resp. Capacity Resp. Max. 0.25 0.25 relative to WT to relative RespiratoryReserve % of max 0.0 0.00 0.25 0.00 0.0 2-‐NBDG 0.00

Figure 2. Type I IFN alters CD4 T cell mitochondrial respiratory reserve and reduces aerobic glycolysis. (A) Schematic depicting mitochondrial function as defined by a mitochondrial stress test, in which cells are subjected to oligomycin, FCCP, and finally antimycin + rotenone A. (B) One representative experiment demonstrating the effects of IFN signaling on mitochondrial function after 24 h of stimulation. (C-D) Summa- rized OCR (C) and ECAR (D) data from 3 experiments where values are relative to WT, which was defined as 1.0. (E) 2-NBDG uptake (gMFI) by CD4 T cells 24 h after stimulation.

At the same time we made these observations, we investigated the metabolic program of Tfh, since it has not yet been described. Given the massive expansion of Tfh in the bm12 model, and the relative ease by which these cells can be sorted (they are the only cells which express CD45.1 in a CD45.2 host), we had a unique opportunity to analyze large numbers of Tfh. We found that Tfh utilize glycolysis and fatty acid oxidation, and went on to profile the metabolic programs of GC B cell and plasmablasts, which relied almost exclusively on glycolysis. This culminated in a compelling study, where we found that inhibiting glycolysis in vivo using 2-DG completely ameliorated bm12 disease. This was particularly exciting, as the same chemical used in our studies to inhibit glycolysis

232 has been successfully tested for safety in a phase I clinical cancer trial54, suggesting it has potential for therapeutic use in patients with autoimmune disease.

In our studies that examined glucose transporter levels and glucose uptake, an interesting divergence between our B cell subsets and T cell subsets emerged. As B cells be- came activated and differentiated into GC B cells or plasmablasts, we noted a stepwise increase in the uptake of glucose, as represented by 2-NBDG fluorescence, that was logarithmically proportionate to an increase in the glucose transporter, Glut1 (Slc2a1). With T cells, however, we observed an equivalent increase in Glut1 expression as seen in plasmablasts, but only a marginal increase glucose uptake. This could reflect a number of distinct mechanistic possibilities—perhaps, simply, plasmablasts utilize additional glucose transporters to obtain such high levels of glucose uptake, whereas Tfh rely chiefly upon Glut1 for glucose uptake. Alternatively, perhaps plasmablasts have much more glucose available to them due to their extrafollicular localization within secondary lymphoid organs55, such that an equivalent glucose transporter level would allow much more glucose uptake. However, factors other than localization must also be contributing to this phenomenon, since GC B cells and Tfh both localize to the germinal centers, where they rapidly proliferate, and their glucose uptake:Glut1 ratios differ drastically.

An additional question our metabolic data raises is why glucose is evidently so much more important to plasmablasts than the other cell types participating in this autoimmune reaction. As it is with T cells, it may be that mature, activated B cells require a shift to glycolysis for their effector functions rather than for their differentiation and proliferation56,57. Indeed there is some evidence to suggest that B cell utilization of glycolysis is essential for antibody production50. Future studies could test the roles of glycolysis in specific B cell subsets by generating CD138-Cre or GL7-Cre mice and crossing them to Glut1fl/ fl mice, given the high specificity of these phenotypic markers to plasmablasts and GC

233 B cells, respectively. Follow up studies should also more closely examine the potential divergent use of additional glucose transporters, many of which have been detected on lymphocytes58–61.

In summary, our use of mouse modeling has led to significant advancement in our understanding of T cell and B cell biology during sterile inflammation, particularly in the context of anticancer immunity and autoimmunity. Carefully controlled cellular and molecular studies have elucidated previously unappreciated roles for type I IFN in directing T cell and B cell differentiation, proliferation, and function. These studies have identified novel targets for potential use in cancer immunotherapies and treatments for autoimmune disease and raise many interesting questions to be addressed in future studies. We have revealed STING as an important mediator of type I IFN production in cancer treatments as well as in a model of cGVHD-driven autoimmune disease. We also uncovered multiple functions of type I IFN on DCs, CD4 T cells, and B cells, which if specifically targeted could allow for more nuanced, tailored therapies. We also found a potential link between type I IFN and cellular metabolism, though these studies need further investigation. Fi- nally, our work examining the cellular metabolism of Tfh and autoimmune B cells suggests promising opportunities for using inhibitors of glycolysis in the treatment of autoimmune diseases.

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236 34. Furie, R. et al. Anifrolumab, an Anti-Interferon Alpha Receptor Monoclonal An- tibody, in Moderate to Severe Systemic Lupus Erythematosus (SLE) [abstract]. Arthritis Rheumatol. 67 (suppl, (2015). 35. Decker, T., Müller, M. & Stockinger, S. The yin and yang of type I interferon activity in bacterial infection. Nat. Rev. Immunol. 5, 675–87 (2005). 36. Swann, J. B. et al. Type I IFN contributes to NK cell homeostasis, activation, and antitumor function. J. Immunol. 178, 7540–7549 (2007). 37. Childs, R. W. & Berg, M. Bringing natural killer cells to the clinic: ex vivo manipula- tion. Hematology 2013, 234–246 (2013). 38. Hervier, B. et al. Phenotype and function of natural killer cells in systemic lupus erythematosus: Excess interferon-γ production in patients with active disease. Arthritis Rheum. 63, 1698–1706 (2011). 39. Henriques, A. et al. Functional characterization of peripheral blood dendritic cells and monocytes in systemic lupus erythematosus. Rheumatol. Int. 32, 863–9 (2012). 40. Baumjohann, D. et al. Persistent antigen and germinal center B cells sustain T follicular helper cell responses and phenotype. Immunity 38, 596–605 (2013). 41. Harada, M. et al. Natural killer cells inhibit the development of autoantibody production in (C57BL/6 x DBA/2) F1 hybrid mice injected with DBA/2 spleen cells. Cell. Immunol. 161, 42–9 (1995). 42. Ehlers, M. et al. Immunoregulatory Natural Killer Cells Suppress Autoimmunity by Down-Regulating Antigen-Specific CD8+ T Cells in Mice. Endocrinology 153, 4367–79 (2012). 43. Ferreira, R. C. et al. A type I Interferon transcriptional signature precedes autoimmunity in children genetically at risk for type 1 diabetes. Diabetes 63, 2538–2550 (2014). 44. Kallionp????, H. et al. Innate immune activity is detected prior to seroconversion in children with HLA-conferred type 1 diabetes susceptibility. Diabetes 63, 2402– 2414 (2014). 45. Schreuder, T. C. M. a et al. High incidence of type 1 diabetes mellitus during or shortly after treatment with pegylated interferon alpha for chronic hepatitis C virus infection. Liver Int. 28, 39–46 (2008). 46. Matikainen, S. et al. Interferon-alpha activates multiple STAT proteins and upregulates proliferation-associated IL-2Ralpha, c-myc, and pim-1 genes in human T cells. Blood 93, 1980–91 (1999). 47. Jonak, G. & Knight, E. Selective reduction of c-myc mRNA in Daudi cells by human beta interferon. PNAS 81, 1747–1750 (1984). 48. Einat, M., Resnitzky, D. & Kimchi, A. Close link between reduction of c-myc expression by interferon and, G0/G1 arrest. Nature 313, 597–600 (1985). 49. Knight, E., Anton, E. D., Fahey, D., Friedland, B. K. & Jonak, G. J. Interferon regulates c-myc gene expression in Daudi cells at the post-transcriptional level. Proc. Natl. Acad. Sci. U. S. A. 82, 1151–4 (1985). 50. Caro-Maldonado, A. et al. Metabolic reprogramming is required for antibody production that is suppressed in anergic but exaggerated in chronically BAFF-exposed B cells. J. Immunol. 192, 3626–36 (2014).

237 51. Wahl, D. R., Byersdorfer, C. A., Ferrara, J. L. M., Opipari, A. W. & Glick, G. D. Distinct metabolic programs in activated T cells: Opportunities for selective immu- nomodulation. Immunol. Rev. 249, 104–115 (2012). 52. Wang, R. & Green, D. R. Metabolic checkpoints in activated T cells. Nat. Immunol. 13, 907–15 (2012). 53. Buck, M. D., O’Sullivan, D. & Pearce, E. L. T cell metabolism drives immunity. J. Exp. Med. 212, 1345–1360 (2015). 54. Raez, L. E. et al. A phase i dose-escalation trial of 2-deoxy-d-glucose alone or combined with docetaxel in patients with advanced solid tumors. Cancer Chemo- ther. Pharmacol. 71, 523–530 (2013). 55. Roth, K. et al. Tracking plasma cell differentiation and survival. Cytom. Part A 85, 15–24 (2014). 56. Cham, C. M. & Gajewski, T. F. Glucose availability regulates IFN-gamma production and p70S6 kinase activation in CD8+ effector T cells. J. Immunol. 174, 4670– 7 (2005). 57. Chang, C.-H. et al. Posttranscriptional control of T cell effector function by aerobic glycolysis. Cell 153, 1239–51 (2013). 58. Oleszczak, B., Szablewski, L., Pliszka, M., Głuszak, O. & Stopińska-Głuszak, U. Transport of deoxy-D-glucose into lymphocytes of patients with polycystic ovary syndrome. Endocrine 47, 618–24 (2014). 59. Maratou, E. et al. Glucose transporter expression on the plasma membrane of resting and activated white blood cells. Eur. J. Clin. Invest. 37, 282–290 (2007). 60. Malide, D., Davies-Hill, T. M., Levine, M. & Simpson, I. a. Distinct localization of GLUT-1, -3, and -5 in human monocyte-derived macrophages: effects of cell activation. Am. J. Physiol. 274, E516–E526 (1998). 61. Fu, Y. Facilitative glucose transporter gene expression in human lymphocytes, monocytes, and macrophages: a role for GLUT isoforms 1, 3, and 5 in the immune response and foam cell formation. Blood Cells, Mol. Dis. 32, 182–190 (2004).

238 APPENDICES

239 April 19, 2016

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240 Monday, April 11, 2016 at 3:36:27 PM Eastern Daylight Time

Subject: Re: reproduc+on permissions Date: Monday, April 11, 2016 at 3:34:57 PM Eastern Daylight Time From: Kathleen Doyle To: Klarquist, Jared (Jared Klarquist) Dear Mr. Klarquist,

You have our permission to use your JoVE ar+cle "Klarquist, J., Janssen, E. M. The bm12 Inducible Model of Systemic Lupus Erythematosus (SLE) in C57BL/6 Mice. J. Vis. Exp. (105), e53319, doi:10.3791/53319 (2015)." in your disserta+on as requested. Monday, April 11, 2016 at 3:36:27 PM Eastern Daylight Time Please be sure to cite the ar+cle accordingly and consider this email as approval. Do not hesitate to email me with any Subject: other Re: ques+ons reproduc+on and permissions have a great day. Date: Monday, April 11, 2016 at 3:34:57 PM Eastern Daylight Time Best Regards, Ka+eFrom: Kathleen Doyle To: Klarquist, Jared (Jared Klarquist) On Mon, Apr 11, 2016 at 1:43 PM, Klarquist, Jared (Jared Klarquist) wrote: Dear Good Mr. a^ernoon, Klarquist,

You For have the life our of permission me, I to cannot use your find JoVE anywhere ar+cle at "Klarquist, JoVE.com J., that Janssen, covers E. M. The bm12 Inducible Model of how to obtain any necessary permission to Systemic reuse a Lupus por+on Erythematosus of an ar+cle. (SLE) in I am an author of hap://www.jove.com/video/53319 C57BL/6 Mice. J. Vis. Exp. (105), e53319, , and doi:10.3791/53319 I would like (2015)." in to include your the disserta+on print por+on as of requested. the ar+cle in my disserta+on. May I do so? Do I need to obtain official permission do so, and if so, can you direct me toward how I can officially request permission? Please be sure to cite the ar+cle accordingly and consider this email as approval. Do not hesitate to email me with any Thank other you, ques+ons and have a great day. Jared Best Regards, Ka+e

-‐-‐ On Mon, Apr 11, 2016 at 1:43 PM, Klarquist, Jared (Jared Klarquist) wrote: KatieGood Doyle aêrnoon, Peer Review Specialist JournalFor of the Visualized life of Experiments me, I (JoVE) cannot find anywhere at JoVE.com that covers how to obtain any necessary permission to 1 Alewifereuse Center, a por+on Suite 200, of Cambridge, an ar+cle. MA 02140 I am an author of hap://www.jove.com/video/53319, and I would like to include Phonethe 617-674-1888 print por+on Ext. 803 of | Fax the 1-866-381-2236 ar+cle in my disserta+on. May I do so? Do I need to obtain official permission do so, and if so, can you direct me toward how I can officially request permission?

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Jared S. Klarquist and Edith M. Janssen*

Division of Cellular and Molecular Immunology; Cincinnati Children’s Hospital Research Foundation; University of Cincinnati College of Medicine; Cincinnati, OH USA

Keywords: dendritic cells, melanoma, mouse model

Abbreviations: APC, antigen presenting cell; CCR7, chemokine receptor 7; cDC, conventional DC; CTL, cytotoxic T lymphocyte; DC, dendritic cell; dDC, dermal DC; IFN, interferon; GEMM, genetically engineered mouse model; LC, Langerhans cell; LXRα, liver X receptor alpha; NLR, NOD-like receptor; pDC, plasmacytoid DC; SOCS3, suppressor of cytokine signaling 3; TIDC, tumor-infiltrating DC; TLR, Toll-like receptor; VEGF, vascular endothelial growth factor

recommended as treatment options for patients with in-transit The infiltration of melanoma lesions by dendritic cells (DCs) has melanoma metastasis.1–5 While this approach is relatively suc- been suggested to play a tumorigenic role due to the capacity of DCs to induce tumor tolerance and promote angiogenesis as cessful against cutaneous metastases, efficacy is limited for sub- well as metastasis. However, it has also been shown that tumor- cutaneous metastases. An improved understanding of the type, infiltrating DCs (TIDCs) induce antitumor responses and hence nature and functionality of TIDCs could lead to novel and more may be targeted in cost-effective therapeutic approaches effective therapeutic approaches. To circumvent ethical issues and to obtain patient-specific DCs that present relevant tumor TIDC availability constraints associated with human research, antigens, without the need for ex vivo DC expansion or tumor various animal models for melanoma have been established in antigen identification. Unfortunately, little is known about the organisms including Xiphophorus, Danio rerio, guinea pigs, opos- composition, nature and function of TIDCs found in human sum and small rodents, all of which have unique advantages and melanoma. The development of mouse melanoma models disadvantages. The relevance of the model under examination has greatly contributed to the molecular understanding of depends on the questions to be answered and how closely the melanoma immunology in mice, but many questions on TIDCs model mimics the histological, immunological and metastatic remain unanswered. Here, we discuss current knowledge 6 about melanoma TIDCs in various mouse models with regard pattern observed in humans. To date, most work is performed to their translational potential and clinical relevance. in mice due to the availability of genetically modified animals, insights into mouse immunology, pathology and physiology and the plethora of mouse-specific research tools. Here, we will briefly review the current knowledge of TIDCs Introduction obtained in the most common mouse melanoma models and the insight they have provided into the human disease. The incidence of cutaneous malignant melanoma has been steadily increasing over the last decades. While complete surgi- Selection of Mouse Model for Melanoma cal excision yields high 5-year survival for patients with localized tumors exhibiting a depth < 0.75 mm, the outcome is poor Melanoma models are generally divided into 3 different groups for patients with a greater depth of invasion or bearing metasta- based on research focus: xenograft models, which allow for the ses. The development of novel therapeutic approaches is there- study of tumor cell behavior; transplantation models, to study fore of great importance. Interestingly, melanomas are relatively melanoma immunology; and genetically modified animal mod- immunogenic tumors and sensitive to cytotoxic T lymphocyte els, which focus on melanomagenesis. Pure chemical carcinogen- (CTL)-mediated lysis. As dendritic cells (DCs) are the main induced melanoma models have decreased in popularity as they antigen-presenting cell (APC) population capable of inducing have relatively low relevance to human disease and therefore will CTLs, DC transfer, DC targeting and in situ DC induction, not be discussed further in this article. recruitment and/or activation have been explored as promising Xenograft models consist of orthotopic or ectopic transplan- immunotherapeutic strategies against melanoma. The topical or tation of human cancer cells or solid tumors into immunocom- intratumoral administration of DC-activating agents—including promised mice. The primary advantage of these models is the interferon α (IFNα), bacillus Calmette-Guérin (BCG), or puri- preservation of human cancer cell behavior, including meta- fied Toll-like receptor (TLR) ligands such as imiquimod—are static potential and tissue preference. However, the absence of a functional immune system does not allow for the study of the *Correspondence to: Edith M. Janssen; Email: [email protected] interactions between tumors and immune cell subsets. While Submitted: 09/12/12; Revised: 10/24/12; Accepted: 10/24/12 DC function is relatively normal in some immunocompromised http://dx.doi.org/10.4161/onci.22660 mouse strains, various others—including those with a NOD.

242 1584 OncoImmunology Volume 1 Issue 9 review REVIEW

Cg-Prkdcscidil2rg background—exhibit defective DC development and low levels of positive co-stimulatory molecules. Upon activa- and function.7–9 In addition, human tumor-derived mediators tion via innate receptors such as TLRs or NOD-like receptors might affect the recruitment, retention, development and func- (NLRs), pro-inflammatory cytokines or cross-linking of CD40, tion of mouse DCs in a different fashion than their mouse homo- DCs mature, reduce their phagocytic potential, increase anti- logs. The more recent development of human melanoma models gen-presenting capacity, upregulate co-stimulatory molecules, in humanized mice10–12 circumvents these issues and provides an change their cytokine production profile (qualitatively and quan- intriguing platform for clinically relevant TIDC studies. titatively) and migrate to draining (lymphoid) areas, where they Syngenic transplantation models have been around since the interact with T cells.24–26 identification of the Cloudman S91 melanoma in BDA/2 mice, Cells with DC characteristics have been repeatedly described Harding-Passey melanoma in BALB/c × DBA/2F1 mice and B16 in human melanoma samples. Depending on study, markers melanoma in C57BL/6 mice.13–16 B16 is currently the most widely used, localization and maturation status, DC infiltration has used melanoma model and has the advantages that it expresses at been linked to a positive27–30 or negative31 prognostic outcome. least 5 homologs of the best characterized human melanoma anti- The discrepancy in outcomes can be attributed to differences in gens (gp100/pmel17, MART-1/MelanA, tyrosinase, TRP-1/gp75 clinical stages, the use of primary vs. metastatic lesions, as well and TRP-2/DCT),17 it is immunogenic and it displays metastatic as use of markers that are relatively non-specific or restrictive to a behavior. The main drawback of this model is the rapid growth of subpopulation of DCs.32 the primary tumor, resulting in problems related to vasculariza- Studies in several other tumor systems indicate that malignant tion, necrosis and swift mortality that preclude the assessment of cells inhibit dendropoiesis, decelerate DC differentiation and prolonged tumor burden on TIDC behavior. Nevertheless, most maturation, induce functional DC deficiencies and accelerate TIDC studies have been performed in B16 melanoma models. cell death in DCs or their precursors.33,34 The maintenance of an Genetically engineered models (GEMM). The identification immature phenotype or the promotion of a tolerogenic one could of genetic and epigenetic abnormalities in human melanomas has lead to anergy/deletion of tumor-specific T cells and the induc- led to the development of genetically engineered mice with a heri- tion of cells with immunosuppressive functions such as FOXP3+ table predisposition to the development of melanoma. The (tissue- regulatory T cells (Tregs). An inhibited DC differentiation might specific) expression of oncogenes includingRet , mutant forms of also contribute to the accumulation of myeloid-derived suppres- (N/K/H)-Ras and Braf and Hgf, coupled or not to backcrossing in sor cells, as the latter generate from precursors that under physi- susceptible genetic backgrounds (Ink4a/Arff/f, Tp53 t/t, Cdkn2d−/−, ological conditions would differentiate into DCs, macrophages Cdkn2a−/−, Cdk4R24C/R24C, etc.) has yielded melanoma models with and neutrophils.35 In addition, immature DCs and pre-DCs have different latency, penetrance and metastatic potential (reviewed been suggested to promote angiogenesis through the secretion of in refs. 18, 19). Although the distribution of melanocytes differs growth factors (i.e., vascular endothelial growth factor, VEGF) between mice and humans, these models have great clinical rel- that directly act on the endothelium, or the production of media- evance as they are based on genes known to be involved in the tors that enhance the sensitivity of endothelial cells to growth genesis and progression of human melanoma, and can be easily factors.36,37 Some studies suggest that DC precursors might even combined with relevant environmental triggers such as UV irra- undergo endothelial transdifferentiation or provide a scaffold for diation, to accelerate melanoma incidence. Only recently the field subsequent lining by endothelial cells.38 has begun to use these models for TIDC studies. Murine and Human DC Populations Dendritic Cells Recent genomic and proteomic approaches have discovered DCs are a heterogeneous population in terms of origin, mor- significant similarities between human and mouse DC popula- phology, phenotype and function. DCs are derived from com- tions,39–43 thereby strengthening the relevance of TIDC research mon myeloid and lymphoid precursors and rely heavily on FLT3 in mouse melanoma models. While several aspects of localiza- ligand (FLT3L) and/or granulocyte macrophage colony-stimu- tion, surface marker and TLR expression, phagocytic poten- lating factor (GM-CSF) for their development.20–22 DCs express tial and antigen presenting capacity are relatively comparable on their surface MHC Class I and Class II molecules together between some mouse and human DC subsets, these are not per- with a wide variety of positive (CD40, CD80, CD86, CD137L, fect matches and in some cases the equivalent populations are CD70) and negative (PDL1, PDL2) co-stimulatory molecules. absent. We will briefly describe the mouse and human DC popu- In addition, DCs can produce a broad range of soluble pro-and lations in the following sections. anti-inflammatory mediators, including multiple cytokines and Mouse DC populations. Under steady-state conditions, chemokines. T cells interacting with DCs via cognate TCR- mouse DCs express Cd11c as well as MHC Class II molecules peptide-MHC complexes will undergo apoptosis, anergy, or and can be subdivided into plasmacytoid DC (pDCs) and con- develop a regulatory phenotype if the balance of co-stimulation is ventional DCs (cDCs).21 pDCs express intermediate levels of tilted on the negative side.23 Conversely, if positive signals surpass Cd11c as well as high levels of Cd45ra (B220), Pdca1 (Cd317), an intrinsic threshold, T cells will undergo proliferation, differen- Tlr1, Tlr2, Tlr4, Tlr7 and Tlr9, and play an important role in tiate and acquire effector functions. Immature DCs display great infection due to their capacity to produce large amounts of Type I phagocytic functions, relatively poor antigen-presenting capacity IFNs.44 Antigen presentation by pDCs is thought to be relatively

243 www.landesbioscience.com OncoImmunology 1585 poor.45 cDCs can be further subdivided into blood-derived resi- levels of CD205 and the DC immunoreceptor (DCIR).63 Both dent cDCs and migratory cDCs. DCIR and CD205 are associated with antigen uptake and induc- Blood-derived resident cDCs are present in lymphoid tissues and tion of antigen-specific T-cell responses.64 LCs express mRNA encompass: (1) Cd11chighMHCII+Cd8α+CD205+Sirpα−Cd11b − coding for TLR1, TLR2, TLR5, TLR6 and TLR9 (but not for (Cd8α DCs), which express Xcl1, Clec9A and often Cd103. Cd8α TLR4, TLR7 and TLR8).65 The number of dDCs populations DCs express mRNAs coding for most TLRs except Tlr5 and Tlr7, described in humans has recently been expanded. The major and are characterized by high Tlr3 expression.44 These DCs have the dDC population is BDCA-1+, and most of these cells express greatest potential to prime CTLs against cell-associated antigens CD11c while only about 50% of the BDCA-1+ population via cross-presentation, but have relatively low CD4+ T-cell activa- express CD1a.66 CD1c−BDCA-3+ dDCs represent about 10% of tion potential;46 (2) Cd11c highMHCII+Cd8α−33D1+Sirpα+Cd11b + all CD11c + dDCs and demonstrate superior cross-presentation of (Cd11b DCs), which predominantly activate CD4+ T cells, have soluble antigens as compared with other DC populations.66 Most poor cross-presentation capacity and express most TLRs except dDCs express mRNA coding for TLR1, TLR2, TLR4, TLR8 Tlr3; (3) Cd11chighMHCII+ cells that lack Cd8α, Cd4 and Cd11b and TLR10 but the exact distribution of these TLRs among spe- (generally termed “double” or “triple” negative DCs), which may cific DC subsets needs further delineation.63 or may not express Xcl1, Clec9A, Tlr3 and Cd103. DC subsets in Human melanoma TIDCs. Melanoma-infiltrating DCs this population have been shown to potently prime both CD4+ have been found in primary and metastatic lesions and encom- and CD8+ T cells against cell-associated antigens.47–49 pass a broad spectrum of DC-like cells, including CD207+ LCs, Migratory DCs can be found in many organs and migrate pDCs and CD1a+ DCs (Table 1).27,28,31,67– 69 Due to differences in upon activation into draining lymphoid areas.22,50,51 As this patient material, the relatively low frequency of TIDCs, the use review focuses on melanoma we will limit our description to of ambiguous analytical markers, and approaches that limit the skin-resident DCs. Various populations of DCs have been number of available analytical markers, there is little consensus described in non-inflamed mouse skin. Langerhans cells (LCs), on the exact composition of the TIDC population.32 However, Cd11b +Cd207+Cd103− DCs reside in the epidermis and express there is a general agreement on the fact that the frequency of Tlr2, Tlr4 and Tlr9 but not Tlr7.52 The cross-presentation of cell- TIDCs is higher in the peritumoral area than within neoplas- associated antigens by LCs has not been demonstrated, but LCs tic lesions and that TIDCs with the most mature phenotype have the capacity to cross-present antigen associated with TLR (DC-LAMP+CD83+fascin+) tend to reside in the peritumoral ligands.53,54 In the dermis Cd11b+Cd207− dermal DC (dDCs) area.27,31,67,68 It is thought that immature DCs enter tumors via the represent the major DC subset, whereas Cd207+Cd103 + dDCs vasculature and—following further differentiation and activa- and Cd207−Cd11b − dDCs represent ~20% of the entire dDC tion—migrate toward the tumor edge. There, DCs either locally population. dDCs express most TLRs and the Cd103+ dDC form T-cell clusters or continue to migrate toward the draining population has been associated with the cross-presentation of lymph node, where they interact with T cells. The relationship cell-associated antigens.52,55,56 between the presence and location of different TIDC subsets The fact that distinct DC subsets share several surface mark- and clinical outcome remains a puzzle, as it not only depends ers and that their expression levels change upon activation com- on the type of TIDCs, but also on their activity as well as on plicate the identification of DC subsets. Environmental cues functional interactions with other cells, all aspects that remain associated with inflammation or tumors can change the surface poorly understood. characteristics of DCs as well as their functional properties, add- Mouse melanoma TIDCs. While mouse models have the ing another layer of complexity to identification of DCs. advantage of providing abundant tumor material, which allows Human DC populations. Like mouse DCs, human DCs are for an easy selection of tumors at different developmental stages, generally divided into pDCs and cDCs. pDCs are lineage nega- there is surprisingly little consensus in the field about mouse tive (lin−) CD11c−HLA-DR+CD123 +BDCA2/4+ and express TIDC frequency, composition and function. Some of these high levels of TLR7 and TLR9.57,58 In contrast to mouse pDCs, discrepancies result from the use of different model systems or human pDCs have been shown to cross-present cell-associated genetic backgrounds. When we compared two xenograft models, antigens.45,59 Human cDCs can be further divided based on 3 syngenic transplantation models and 2 GEMMs, we observed their expression of BDCA-1 (CD1c) and BDCA-3 (CD141). significant differences in TIDC frequency (data not shown) and On one hand, BDCA-1+ DCs are similar to mouse Cd11b DCs composition between models (Fig. 1A). The highest frequency of as they express SIRPα and CD11b,39 strongly respond to TLR1 TIDCs was seen in syngenic transplant models, while GEMMs and TLR6 agonists and promote CD4+ T-cell responses. On exhibited significantly less TIDCs. However, GEMMs showed the other hand, BDCA-3+ DCs exhibit strong similarities with a greater diversity of TIDCs, with marked infiltration by pDCs, mouse Cd8α DCs and express CLEC9A, XCR1 and high lev- LCs and dDCs. Xenografts showed the least diverse variety, els of TLR3.60,61 It has recently been shown that BDCA-3 DCs completely lacking LCs and dDCs, while in syngenic transplant have the greatest capacity for cross-presentation of all human models an occasional dDC (CD207+EpCAM−) subset was found. DC subsets.60–62 Although a full comparison is hard to make as not all studies LCs are the only DCs found in healthy human epidermis and used the same set of markers, a review of the current literature comprise 2–8% of all epidermal cells. LCs express high levels of on mouse melanoma revealed similar findings in different model CD1a, MHC Class II molecules, CD207 and EpCAM, and low systems (Table 2).70–75

244 1586 OncoImmunology Volume 1 Issue 9 Table 1. Human melanoma TIDC Study DC marker DC specifics S100+CD1a+ (LC) increased in peritumoral infiltrate compared with overlying epidermis. Garcia-Plata69 S100, CD1a, HLA-DR HLA-DR levels variable. CD123, DC-LAMP, fascin, CD1a+ and CD207+ cells in epidermis of regressing lesion infiltration; fascin+/DC-LAMP+ cells Movassagh28 CD1a, CD207 accumulation around microvessels within tumor area (tumor regression) Observed in majority of melanomas; numbers higher in infiltrating and metastatic samples. Salio102 CD123, BDCA2, CLA Numbers increase with severity of disease Increase in dermal myeloid and pDC compared with healthy skin. CD1a, CD123, CD207, Intratumoral immature: MR+/DC-SIGN+/CD1a- and CD1a+/CD207- cells Vermi68 DC-Sign DC-LAMP, MR Peritumoral immature: CD1a+/CD207+LC; MR+/DC-SIGN+/CD1a-; CD1a+/CD207-; CD123+/BDCA-2+; Peritumoral mature: CD83+DC-LAMP+ CD1a+ in melanoma cell nests and stroma, DC-LAMP+ in peritumoral area: inverse correlation CD1a+ Ladanyi27 CD1a, DC-LAMP and DC-LAMP+ cells with melanoma thickness Simonetti67 CD83, CD207 Inverse correlation langerin+ cells with tumor depth; lower density of CD83(+) DC in thick melanomas Observed in 37% of cases. Located close to the tumor within the peritumoral leukocyte infiltrate, rep- Charles103 BDCA-2 resenting 2–5% of these cells CD123 infiltration: tumor stroma (~30%), tumor nest (~15%) of samples Jensen31 CD123, DC-LAMP DC-LAMP+ infiltration: tumor stroma (~30%), peritumoral (~50%) of samples > 1% of CD45 cells: Metastasis to LN contain higher number of LAMP+ cells compared with metastasis Erdag30 DC-LAMP, CD163neg to skin/soft tissue peritoneum, small intestine DC-LAMP+ cells frequently associated with tumor HEV; Density of DC-LAMP+ cells correlates Martinet104 DC-LAMP, fascin with density of tumor HEV

The differences in the composition of TIDCs across mod- CD11c-diphtheria toxin receptor (DTR) transgenic mice has els and species highlight the importance of model validation for been shown to significantly reduce the tumor mass of intraperi- each type of study. While all models have significantly contrib- toneally injected B16/F10 melanoma cells.78 While other mod- uted to the current understanding of melanoma immunology, els suggest a role for an endothelial-like differentiation of DC pre-clinical DC targeting studies would benefit from models precursors, VEGFA, β defensin, basic fibroblast growth factor that more accurately resemble the TIDC composition seen in (bFGF) and transformin growth factor β1 (TGFβ1) in this pro- patients. cess, the mechanism underpinning DC-supported vasculogen- Mouse TIDC activation status. As in human melanoma, esis in melanoma has not been clearly established.79,80 mature mouse TIDCs tend to reside in the peritumoral areas Mouse TIDC functionality. In order to operate as bona and total TIDCs seem to increase upon disease progression fide APCs, DCs need to acquire antigens through one of the (Fig. 1B and C).72 Most studies assessing mouse TIDC activa- phagocytic pathways, process and present them and communi- tion and maturation status were based on the flowcytometric cate with T cells locally or upon migration to draining areas. analysis of CD11c+ cells from the entire tumor. Consequently, Studies injecting beads into tumors revealed that a sizable frac- most reports show a biphasic distribution of the maturation tion of TIDCs acquire one or more beads, indicating that that markers CD40/CD80 and CD86.70,71,73,74 The differential particulate uptake mechanisms is relatively intact.71,73 However, analysis of the peritumoral and intratumoral zones of B16/F10 Gerner et al. showed that TIDCs manifest a defect in the uptake melanomas replicate histological observations, showing signifi- of intratumorally injected proteins as compared with dDCs cantly more mature TIDCs in the peritumoral area as compared from healthy tissue.73 Separating peritumoral and intratumoral with the intratumoral one (Fig. 1D). It is thought that the TIDCs, we found that the in vitro uptake of proteins and apop- tumor environment promotes the recruitment of DC precur- totic cell material was higher for peritumoral, as compared with sors and immature DCs, but little is known on the ability of intratumoral, TIDCs (Fig. 2A). Similar observations were made melanomas to support in situ DC differentiation.76 Diao, et al. when peritumoral and intratumoral TIDCs were analyzed 4 h showed that adoptively transferred immediate cDC precursors after the intratumoral injection of proteins in vivo. Interestingly, (Lin−CD11c +MHCII− cells) are recruited to B16/F10 tumors, the co-administration of lipopolysaccharide (LPS) appears to where they proliferate and differentiate into cells with T-cell decrease the phagocytic uptake by peritumoral TIDCs, but not priming capacity in vitro, suggesting at least a partial acquisi- by their intratumoral counterparts (Fig. 2B). tion of DC-like functions.77 On the other hand, in vivo data Most studies reveal a decreased CD4+ and CD8+ T-cell acti- from Fainaru, et al. demonstrate that the recruitment of imma- vating capacity of TIDCs isolated from antigen-expressing ture DCs promotes angiogenesis and tumor growth by enhanc- tumors or upon antigen pulsing in vivo.70,73,74 However, other ing endothelial cell migration and the subsequent formation of studies indicate potent T-cell priming capacity of TIDCs, both vascular networks.78 Moreover, the depletion of CD11c+ cells in in vitro or in vivo.71,77,81 This discrepancy can be partly explained

245 www.landesbioscience.com OncoImmunology 1587 Figure 1. Composition, location and maturation of tumor-infiltrating dendritic cells. (A) Composition of CD45+Lin−CD11c+MHCI I + tumor-infiltrating dendritic cells (TIDCs) in different melanoma models. Tumors (400–600mm2) were harvested from Nu/J nude mice (MV3, A375; n = 6 mice per group), BDA/2 mice (CloudmanS91; n = 5 mice per group) and C57BL/6 mice (B16F1 and B16/F10; n = 9 mice per group), digested according to standard protocols,106,107 and analyzed by multicolor flow cytometry. β-actin::LSL-KRAS mice crossed onto a Tyr::CreERT2 background108 were repeatedly treated with tamoxifen between 1 and 2 mo of age. Tumors were harvested 4–6 mo later (1–2 melanomas per mouse, n = 3 mice). MT::Ret transgenic mice109 were aged and spontaneous melanomas were harvested when their surface reached 200–300 mm2 (1–3 melanomas per mouse, n = 4 mice). (B) Representative localization of TIDCs in a snap-frozen B16/F10 tumor seven days after the subcutaneous injection of 2 × 106 tumor cells in C57Bl/6 mice, as observed by confocal microscopy. Red, CD11c; Green, CD11b; Blue, nuclei (4',6-diamidino-2-phenylindole, DAPI). (C) Relationship between the frequency of TIDCs among tumor-infiltrating lymphocytes (TILs) and the size of B16/F10 melanomas growing in C57Bl/6 mice, as determined by flow cytometry. (D) Differential expression of maturation markers on peritumoral and intratumoral TIDCs. B16/F10 tumors (≈600 mg, n = 4–5 tumors per group) were harvested and the peritumoral area was collected using ophthalmic blades, followed by the processing of peritumoral and intratumoral tissues according to standard protocols.106,107 CD40, CD80 and CD86 expression were determined among live CD45+Lin−CD11c+MHCI I + cells by multicolor flow cytometry. by the fact that these studies differed relative to TIDC composi- predominantly from reduced antigen uptake as they found anti- tion, TIDC localization, TIDC maturation state, TIDC isola- gen processing and presentation to be unaltered.73 To further tion methods and in vitro functional assessment protocols. By dissect the antigen presenting and T-cell priming/activating separating TIDCs based on GR1 expression, Diao et al. showed potential of TIDCs, we isolated peritumoral and intratumoral that GR1+ expressing TIDCs produce more interleukin (IL- TIDCs from ovalbumin (OVA)-expressing B16 tumor-bearing + + 10) and exhibit lower CD8 and CD4 T-cell priming capac- mice and cultured them with an OVA257–264-specific reporter cell − 75 ity than GR1 TIDCs when loaded with antigens in vitro. In line (B3Z) and CFSE-labeled OVA257–264-specific OT-1 T cells. addition, CD8+ T cells primed by GR1+ TIDCs demonstrated We included brefeldin A in the isolation procedure to prevent significantly reduced cytokine production compared with CD8+ the turnover of MHC-I-peptide complexes while preserving the T cells primed by GR1− TIDCs. Gerner, et al. suggested that TIDC maturation state.82 Importantly, significant antigen pre- the decreased TIDC capacity for CD4+ T-cell activation results sentation was observed only when brefeldin A was present during

246 1588 OncoImmunology Volume 1 Issue 9 Table 2. Mouse melanoma TIDC characteristics Model DC marker Frequency DC subpopulation Characteristics ~35/5 high power Scid-MV3 xenograft105 BSA- I binding - - fields All CD11b +; further Partially activated; reduced capacity for protein uptake B16/F10. s.c.73 CD11c+,I MHCI + - negative for EpCAM, and subsequent MHC II presentation; PDCA-1, CD4, CD8α less sensitive to TLR stim

All CD11b +; most F4/80+ GR1+ less mature populations, fails to stimulate MLR, B16/F10. s.c.75 CD11c+,I MHCI + - produce more IL-10; protein pulsed Gr1+ DC poorly + ~23.5%, GR1 ; few pDC activate OVA-specific CD4 and CD8 T cells in vivo

CD11c+,I MHCI + Pre-DC (Lin-CD11c+MHCII-Flt3+) cells are recruited B16/F10 sec.c.77 in the tumor, differentiate and activated CD8 T cells in vitro upon peptide pulsing CD11c+ TIDC express high levels of SOCS3 B16/F10 sec.c.92 - - and have reduced M2-PK activity. Mostly CD11b+, I mmature phenotype; fail to activate OVA-specific B16-OVA s.c.74 CD11c+,I MHCI + ~30% of TIL ~5% pDC, hardly CD4 and CD8 T cells ex vivo CD207+ ~33% CD11b +MHCI I high, Partially mature; no in vitro activation of OVA-specific B16-OVA s.c.70 CD11c+ ~20% of TIL rest CD11b- MHCIImedium CD4 and poor activation of CD8 T cells ~3% pDC, Decreased number compared with skin; 0.13 ± 0.07% of ~2.25% CD8αDC, B16/F10 sec.c71,81 CD11c+,I MHCI + Immature phenotype, particle uptake in vivo normal; total cells > 95% non-pDC non protective upon transfer. CD8α 4.0 ± 0.22% of ~15% pDC, Increased number compared with skin; K17–3571 CD11c+,I MHCI + total cells ~12% CD8αDC immature phenotype; particle uptake in vivo normal ~58% pDC, Tyr:N-RasQ61K+ DMBA/ 0.02 ± 0.004 of Decreased number compared with skin; CD11c+,I MHCI + C H O71 total cells ~40% non pDC non immature phenotype 3 6 CD8αDC Increasingly immature phenotype MT/ret72 CD11c+,I MHCI + 3–10% of TIL - upon melanoma progression the isolation period, illustrating the importance of optimizing While many studies indicate a decrease in the maturation and standardizing TIDC isolation protocols. The total TIDC and functionality of melanoma TIDCs, the mechanisms that fraction poorly activated B3Z cells (Fig. 2C), suggesting a low underpin such changes in APC functions are still unclear. frequency of OVA257–264-MHC complexes. Consequently, total Increased expression of immunosuppressive cytokines and TIDC-mediated OT-1 T-cell activation and proliferation, as membrane-associated molecules by TIDCs has been impli- determined by CD69 upregulation and CFSE dilution assays, was cated in TIDC dysfunction.72,83 Other models suggest that relatively poor (Fig. 2D and E). However, peritumoral TIDCs tumor-derived cytokines or a reduction in the sensitivity of displayed a comparatively higher frequency of OVA257–264-MHC TIDCs to innate signals prevents maturation, migration and complexes and activated (while inducing the proliferation) of thereby impair TIDC function.84–88 However, prolonged TIDC a sizable fraction of OT-1 T cells (Fig. 2C–E). Intratumoral retention and the maintenance of an immature phenotype has

TIDCs exhibited less OVA257–264-MHC complexes and activated recently been linked to lipid accumulation following increased OT-1 T cells without inducing proliferation. This lack of prolif- scavenger receptor A expression89 and LXRα mediated CCR7 eration could be restored by the addition of IL-2 but not upon the downregulation.90 Norian et al. have linked TIDC dysfunction blockade of IL-10 or TGFβ, suggesting the induction of T-cell to increased l-arginine metabolism in a spontaneous model of non-responsiveness. Importantly, the treatment of peritumoral mammary carcinoma.91 More importantly, Zhang, et al. have TIDCs with TLR4 or TLR9 ligands significantly increased their correlated the reduced functionality of B16 melanoma TIDCs potential to induce T-cell proliferation, while the same treatment to a decreased metabolic proficiency, resulting from increased did not improve the functionality of intratumoral TIDCs (data SOCS3-pyruvate kinase M2 interactions.92 These observa- not shown). Altogether, these observations show that differences tions clearly exemplify that the focus on basic immunological in isolation protocols, TIDC subsets, and functional assays sig- assays and parameters has become too restricted to determine nificantly complicate the comparison between studies and the the mechanisms of TIDC dysfunction. For a full appreciation extrapolative value of their findings. of the developmental and functional defects in TIDC, research

247 www.landesbioscience.com OncoImmunology 1589 Figure 2. Functionality of tumor-infiltrating dendritic cells. A( ) In vitro phagocytic capacity of tumor-infiltrating dendritic cells (TIDCs). Peritumoral and intratumoral TIDCs were isolated from B16/F10 tumors growing in C57Bl/6 mice (as described in the legend of Figure 1) and cultured for 4 h with CFSE-labeled apoptotic splenocytes (1:3 ratio) or 100 μg/mL fluorochrome-conjugated ovalbumin (OVA) in the presence (black bar) or absence (gray bar) of 0.1 μg/mL lipopolysaccharide (LPS, from Salmonella minnesota R595) (n = 4–5 tumors per group). (B) In vivo phagocytic capacity of TIDCs. B16/F10 tumors (≈600 mm2) were injected with 1 × 106 CFSE-labeled apoptotic cells or 200 μg fluorochrome-conjugated VO A in the presence or absence of 10 μg LPS. Four hours later, peritumoral and intratumoral TIDCs were isolated and analyzed by flow cytometry (n = 4–5 tumors per group). (C) Effect of brefeldin A (BrefA) employed during TIDC isolation from B16-OVA melanomas on endogenous tumor-antigen presentation. BrefA was added during digestion, incubations and sorting at a concentration of 40 μg/mL.82 Peritumoral and intratumoral TIDCs from OVA-expressing B16/

F10 tumors were cultured with OVA257–264-specific B3Z hybridoma cells and hybridoma activation was determined 20 h later by chlorophenol red- β-D-galactopyranoside (CPRG) conversion (n = 5–6 tumors per group).110 TIDC derived from B16/F10 parental tumors were used as negative control.

(D and E) Peritumoral and intratumoral TIDCs (isolated in the presence or absence of BrefA) were co-cultured with CFSE-labeled OVA257–264-specific OT-1 T cells. After 24 h, activation was determined by CD69 expression in 7-AAD−CD8+Vα2+Vβ5+ cells. OT-1 T-cell proliferation was assessed by CFSE dilution after 72 h of culture with the indicated TIDCs (n = 5–6 tumors per group). disciplines beyond classical immunology will have to be incor- to target TIDCs or support TIDC functions, it is likely that they porated into the experimental approaches. only partly activate TIDCs, as (1) some specifically targeted DC populations are absent or poorly represented in the tumor, and Scientific and Therapeutic Considerations (2) some specifically targeted receptors are poorly expressed by TIDCs or rendered non-functional by the tumor microenviron- Mouse models have been extensively used to test topical therapeu- ment. In these cases, it is more likely that other cells in the tumor tic therapies. Comparable to human melanoma, the injection of environment are stimulated to promote a DC activating/restor- GM-CSF, IFNα, imiquimod, or BCG has been shown to result ing microenvironment. in various degrees of therapeutic success in mice.5,93–96 In many of In order to improve the clinical relevance and translational these approaches, either increased numbers of DCs or enhanced potential of mouse melanoma models for the design, optimiza- DC maturation was observed in the tumor or tumor-draining tion, and identification of novel therapeutic interventions that lymph node.93–96 In addition, other purified TLR ligands includ- target TIDCs we will have to overcome several hurdles. An ing poly(I:C), CpG oligonucleotides, LPS, alone or coupled to improved identification and characterization of human TIDCs additional immunomodulatory therapies have been used suc- will be critical to identify and validate the best mouse models for cessfully.97–99 The intratumoral administration of crude bacte- each type of study. Eventually, the panel of DC specific markers rial products, cytokines and stimulatory molecules delivered by used in human and mouse studies will have to be standardized, viral vectors, microspheres or nanoparticles is well established even as investigators continue to discover new markers and DC in mouse models but has not been translated to the human sys- populations.32 Furthermore, the optimization and standardiza- tem.5,100,101 While all these therapeutic approaches were suggested tion of protocols for TIDC isolation and functional assessments

248 1590 OncoImmunology Volume 1 Issue 9 will be essential for allowing study-to-study comparisons and clinical relevance of mouse models and the identification of the extrapolation of data across species as well as laboratories. novel therapeutic targets. This said, a great gain might be made by an increased collaboration between different research disciplines. This could Disclosure of Potential Conflicts of Interest result, for instance, in the generation of better mouse models, No potential conflicts of interest were disclosed. such as humanized mice for xenograft transplantation studies and GEMMs with TIDC patterns that resemble human TIDC Acknowledgments profiles at different stages of disease, as well as new analytical This work is supported by NIH grant CA138617 (NCI) and platforms for extended TIDC analyses. AI079545 (NIAID) to E.M.J. Although it is unlikely that mouse melanoma models will ever completely recapitulate the complexity of human mela- Ethical Statement noma in clinical situations, so far we have only scratched the All animal experiments were performed in strict accordance surface of the true potential of mouse models for the analysis of with animal protocols approved by the Institutional IACUC TIDC dysfunction and the development of therapeutic inter- at CCHMC and LIAI that operate according the guidelines by ventions. Combining and integrating current models, stan- the Association for Assessment and Accreditation of Laboratory dardizing analytical methods and expanding the disciplines of Animal Care International and the recommendations in the Care research will be instrumental for significantly improving the and Use of Laboratory Animals of the National Institute of Health.

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Review Article Dendritic Cells in Systemic Lupus Erythematosus: From Pathogenic Players to Therapeutic Tools

Jared Klarquist,1 Zhenyuan Zhou,2 Nan Shen,2,3 and Edith M. Janssen1

1 Division of Immunobiology, Cincinnati Children’s Hospital Medical Center and the University of Cincinnati College of Medicine, Cincinnati, OH 45229, USA 2Shanghai Institute of Rheumatology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China 3Center for Autoimmune Genomics and Etiology (CAGE), Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA

Correspondence should be addressed to Edith M. Janssen; [email protected]

Received 9 November 2015; Accepted 13 March 2016

Academic Editor: Carolina T. Pineiro˜

Copyright © 2016 Jared Klarquist et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

System lupus erythematosus (SLE) is a multifactorial systemic autoimmune disease with a wide variety of presenting features. SLE is believed to result from dysregulated immune responses, loss of tolerance of CD4 T cells and B cells to ubiquitous self-antigens, and the subsequent production of anti-nuclear and other autoreactive antibodies. Recent research has associated lupus development with changes in the dendritic cell (DC) compartment, including altered DC subset frequency and localization, overactivation of mDCs and pDCs, and functional defects in DCs. Here we discuss the current knowledge on the role of DC dysfunction in SLE pathogenesis, with the focus on DCs as targets for interventional therapies.

1. Introduction commonly experience profound fatigue and joint pain and a decreased quality of life [12–15]. Systemic lupus erythematosus is a chronic autoimmune The precise etiology of SLE remains unclear and likely inflammatory disease that affects multiple organ systems, varies, considering its diverse clinical manifestations. Never- prototypically characterized by high levels of circulat- theless,SLEisbelievedtoresultfromdysregulatedimmune ing autoantibodies and glomerulonephritis. Clinical symp- responses, loss of tolerance of CD4 T cells and B cells to ubiq- toms also encompass musculoskeletal, dermatological, neu- uitous self-antigens, and the subsequent production of anti- ropsychiatric, pulmonary, gastrointestinal, cardiac, vascular, nuclear and other autoreactive antibodies. This dysregulation endocrine, and hematologic manifestations. The reported is associated with high serum levels of type I IFN, observed incidence of SLE nearly tripled over the last 40 years due to in greater than 70% of patients [16, 17]. Current “standard of improved detection of mild disease [1], but SLE prevalence care” treatments encompass high-dose corticosteroids, anti- estimates still vary considerably, ranging from 10 to 150 cases malarials, and immunosuppressive drugs that are associated per 100,000, depending on geography, race, and gender [2– with significant adverse side effects. As these treatments sup- 5]. In the United States, the prevalence of SLE is higher press symptoms and do not cure the disease, new therapies among Asians, African Americans, African Caribbeans, and are needed. Hispanic Americans compared with Caucasians [6–9]. Simi- Contemporary treatment strategies have been shifting larly, in European countries SLE prevalence is higher among emphasis toward the identification of immunological pro- people of Asian and African descent [5–9]. Interestingly, SLE cesses, both soluble and cellular, in order to redirect aber- is reported infrequently in Africa [10]. Mortality rates are rant immune responses. Dendritic cells have recently been relatively low, at 10–50 per 10,000,000 of the general pop- recognized as important players in the induction and pro- ulation and show correlation with renal and cardiovascular gression of autoimmune diseases, including SLE [18]. Human manifestations as well as infection [11]. Importantly, patients and mouse studies have associated lupus development with

252 2 Mediators of Inflammation altered DC subset frequency and localization, overactivation 2.3. Monocyte-Associated DCs. There are currently several of mDCs or pDCs, and functional defects in DCs [19, 20]. populations of DCs that are thought to develop from mono- However, full dissection of the relative contribution of the cytes rather than common DC precursors. These cells display causesandtheconsequencesofthedysfunctionalityinthe a variety of phenotypes and functions, but there is no consensus on their exact classification or their role in vivo. different DC subpopulations is needed to understand the pro- + cesses that govern SLE development, progression, remission, CD14 DCs are observed in several nonlymphoid tissues, including the skin. These cells express CD11c but lack BDCA1 and relapses, in order to design interventional treatments + that have the potential to redirect the immune system and or BDCA3. The CD14 DCsexpresslowlevelsofcostimula- eventually lead to a cure for this disease. tory molecules or chemokine receptors that promote migration. While these cells have been suggested to be poor at stim- 2. DC Populations in Humans ulating na¨ıve T cells, they have been found to support the formation of T follicular helper cells and to provide direct help to DCs are a heterogenous population of professional antigen B cells [46–49]. Inflammatory DCs (iDCs) have been suggested to origi- presenting cells, which bridge innate and adaptive immunity. + In the absence of exogenous triggers, DCs contribute to the nate from classic CD14 blood monocytes under inflamma- clearance of dying cells and the maintenance of tolerance. tory conditions. These cells may express some of the myeloid DC markers and seem prone to produce proinflammatory During infection, or in the context of autoimmunity, however, cytokines. In vitro studies suggest that different types of DCs play a pivotal role in the activation of CD4 and CD8 T inflammatory stimuli give rise to populations with dis- cells. DCs were initially identified by Ralph Steinman and lack tinct proinflammatory phenotypes. TNF𝛼/iNOS expressing typical lineage markers for T cells (CD3), B cells (CD20), and inflammatory DCs have been found in skin lesions of patients NK cells (CD56) while expressing high levels of MHC class with psoriasis and atopic dermatitis [50, 51]. II [35, 36]. Within this population comparative studies have SlanDCs encompass a subset of monocytes with high identified a small number of subsets that have homologues in expression of MHC class II, CD16, and 6-sulpho LacNAc several mammalian species [37, 38]. (slan). SlanDCs were shown to express TRL7 and TLR8 and

+ + to produce IL-12, IL-23, and TNF, preferentially promoting 2.1. Myeloid DCs: BDCA1 DCs and BDCA3 DCs. Myeloid Th1 and Th17 cell differentiation. This population hasbeen DCs are considered “conventional” or “classical” DCs and are isolated from the inflamed skin of psoriatic patients and SLE characterized by expression of CD11c and CD11b and lack of patients with cutaneous lupus, the colon, and draining lymph CD14 and CD16. Within this population we currently distin- nodes of patients with inflammatory bowel diseases, as well guish two populations based on the expression of the markers as CSF samples and inflammatory brain lesions of patients CD1c/BDCA1 and BDCA3/CD141 [39]. with MS [52–55]. Interestingly, SlanDC infiltration in tumors + The BDCA1 DCs are the major myeloid DC population is associated with tolerance and poor prognosis, indicating andarefoundinblood,lymphoidorgans,andmosttissues. either diversity within the slanDC population or heterogene- + BDCA1 DCs express a wide variety of pattern recognition ity in its function. receptors including TRL1–8, lectins, and cytokines, allowing them responsiveness to a diverse array of environmental cues. 2.4. Tissue DCs. Nonlymphoid tissue resident DCs are + BDCA1 DCs are strong stimulators of na¨ıve CD4 T cell present in most tissues in steady state and have been associ- responses, which can be shaped differently depending on ated initially with induction of tolerance to self-antigens [36– which innate stimuli are present [37]. 38, 56–58]. These cells migrate at a very low rate to the drain- + The BDCA3 DCs make up >10% of the mDCs and have ing LN under steady state conditions but show significant beenfoundinlymphoidandnonlymphoidtissuesaswellas increased migration under inflammatory conditions. Several + bloodandbonemarrow.BDCA3 DCs express high levels studies have identified networks of tissue resident DCs in the skin, lung, gut, and liver [59, 60]. Each of these networks of TLR3, XCR1, and CLEC9 and have been shown to display consists of several subpopulations with different capacities an increased capacity to phagocytose dying cells and cross- for phagocytosis, antigen processing and presentation, migra- present cell-associated antigens to CD8 T cells compared to tion, and the type of immune response they promote. Due to other DCs subsets [34, 40, 41]. accessibility, skin DCs, especially Langerhans cells (LC), have been the most studied tissue-DC in the context of SLE. 2.2. Plasmacytoid DCs. pDCs lack the classic mDC markers CD11b and CD11c and express high levels of CD123, CD303 2.5. DC Activation of T Cells. One of the defining features (BDCA2), and CD304 (BDCA4). pDCs are known for their of DCs is the expression of class I and class II major histo- capacity to produce vast amounts of type I IFNs in response compatibility proteins and the processing and presentation to viruses and/or virus-derived nucleic acids predominantly of peptide antigens to T cells. DCs predominantly present via engagement of TLR7 and TLR9. pDCs have been shown to self-antigens in low quantities resulting in immunologic prime CD4 T cells and cross-prime CD8 T cells, especially in tolerance. Once activated, however, DCs mature in a process the context of infection [42]. Several studies implicate pDCs that usually involves migration to a draining lymph node in the induction and maintenance of tolerance through the and the priming of T cells [61–63]. The factors governing induction of regulatory T cells (Tregs) [43–45]. the functional result of T cell priming are multifactorial,

253 Mediators of Inflammation 3

Table 1: pDCs in SLE.

Markers used to identify Reference Frequency Phenotype Function subset ↓ in blood, correlated with + + LN and BDCA2 CD123 Tucci et al. [82] ↑ in kidney (more than other DC subsets) ↓ in blood in active disease DCs in kidney were immature + − BDCA2 (blood) and and (DC-LAMP ), localized to + Fiore et al. [78] BDCA4 (kidney) ↑ in kidney (more than tubulointerstitium, in clusters, and other DC subsets) lacked dendrites + − BDCA2 Lin. + Migita et al. [77] ↓ in blood HLA-DR − CD123high CD11c − + Henriques et al. [80] ↓ in blood in active disease CD16 HLA-DR + ↓ IFN𝛼 production by PBMC per pDC BDCA2 CD123high Kwok et al. [90] Normal in blood upon CpG stimulation + + ↑ Tcell BDCA2 BDCA4 + Jin et al. [79] ↑ in blood per total PBMC Normal HLA-DR,CD86,CD83,CCR7 proliferation in CD123 MLR Normal HLA-DR, CD86, CD83, CCR7, ↑ basal and + − BDCA2 CD11c Gerl et al. [81] na CD40, BAFF, CCR1, and CCR5 and ↓ CCL19-specific CMKLR1 migration ↓ SLAMF5/CD84, + + − SLAMF7/CRACC/CD319, normal BDCA-2 CD4 CD11c Hagberg and Ronnblom¨ − SLAMF1, SLAMF2/CD48, Lin [86] SLAMF3/CD229, SLAMF4/CD244, and SLAMF6/CD352 including the relative concentration of surface peptide/MHC, dysregulated apoptosis or insufficient clearance of dying cells costimulatory molecule expression, and cytokine release. by DCs and other phagocytes [22, 23, 69]. Indeed, high levels Ultimately, the combination of these signals will result in of apoptotic cells are found in SLE patient serum, germinal either T cell anergy, deletion, or activation, proliferation, and centers, and inflamed tissues, such as the skin and kidney differentiation [64–66]. [24, 27]. Mounting evidence indicates that self-RNA and self- A wide variety of cell surface costimulatory proteins DNA from these dying cells induce the unremitting output expressed by DCs can signal both activation (41-BB, CD40, of type I IFN by pDCs [21] via engagement of TLR9 or CD70, CD80, CD83, CD86, GITRL, ICOSL, LTBR, and TLR7 [31, 70] and potentially via other cytosolic nucleotide OX40L) and inhibition (PDL1, PDL2) of an engaged T cell sensing pathways such as RIG-I/IPS1 and STING (TMEM173) (reviewed in [67, 68]). In addition, secretion of pro- and anti- [28,71,72].TypeIIFNsproducedbyDCspromotetheirown inflammatory cytokines by DCs contributes to the outcome of activation and maturation in an autocrine manner, including Tcellpriming.DCscanproduceawidevarietyofcytokines; increasedIFNoutputandincreasedsurfaceexpressionof which cytokines are produced depends upon environmental CD80, CD86, and MHC class II, making them better at signalsaswellasupontheDCsubtype.Cytokineproduction activating T cells [21, 25, 26, 73]. Furthermore, type I IFNs is driven by input from paracrine and autocrine cytokine sig- directly promote B cell activation, antibody production, and naling,aswellasinputfrominnatepatternrecognitionrecep- T cell survival and expansion [29, 32, 33]. Altogether, these tors (PRRs) including toll-like receptors (TLRs). The combi- data suggest that DCs are key players in SLE pathogenesis and nation of these signals not only influences whether a T cell point to DCs as promising therapeutic targets. becomesactivated,butalsoplaysakeyroleindirectingTcell differentiation toward various effector fates. 4. DC Abnormalities in SLE Patients 3. Role of DCs in SLE Several reports indicate that the frequency, composition, Development and Progression and phenotype of DCs in SLE patients differ from those of healthy individuals (see Tables 1 and 2). However, it is difficult Although it is not certain how immunological tolerance is to compare results between laboratories, given differences broken in SLE, DCs are thought to play key roles [30]. in disease activity and manifestations, the effect of various Perhaps the most prominent model proposes that the initial drug treatments on DC development and phenotype, and the injury is due to a build-up of dying cells, a result of either variations in analytical parameters.

254 4 Mediators of Inflammation

Table 2: DCs in SLE. Markers used to Reference Frequency Phenotype Function identify subset ↓ blood in active DCs in kidney were immature + disease and − BDCA1 Fiore et al. [78] (DC-LAMP ), localized to ↑ kidney in active tubulointerstitium disease DCs in kidney were immature ↓↓ blood and − + (DC-LAMP ), localized to BDCA3 Fiore et al. [78] ↑ kidney in active tubulointerstitium, with disease elongated processes ↓ CD83, especially in active + + BDCA1 CD11c ↓ in blood per total disease, − − Jin et al. [91] BDCA4 CD19 PBMC normal HLA-DR, CD86, and CCR7 + − HLA-DR Lin Scheinecker et al. + + + + ↓ in blood ↓ CD40 ,B7 , and CD11c ↓ T cell proliferation in MLR CD4 [76] Normal in blood, + + BDCA1 CD11c Tucci et al. [82] relatively few in kidney Normal Tcellproliferationin + + + − ↑ in blood (though ↑ CD86 ,CD80 , normal MLR, moDCs fail to increase CD11c Lin Crisp´ın et al. [83] + + not significant) HLA-DR ,andCD40 costimulatory molecule expression upon activation ↑ CD86, BAFF, normal − HLA-DR, CD83, CD40, CD11chigh CD14 Gerl et al. [81] na CCR7, CCR1, and CCR5 and ↓ CMKLR1 Adherent, ↑ CD86, CD80, HLA-DR, and monocyte-derived Ding et al. [93] na CD1a and ↑ T cell proliferation in MLR DCs (MDDCs) ↓ CD83 after 5–7 d culture + ↓ HLA-DR after 8–10 d CD14 sorted, culture, normal CD86, CD83, ↑ antigen-specific T cell monocyte-derived Koller¨ et al. [92] na CD80, CD40, CD54, and proliferation and normal MLR DCs (MDDCs) CD33 ↑ in skin of patients ↑ TNF𝛼 production by healthy with cutaneous LE In situ TNF production in donor slanDCs in response to M-DC8 (slanDCs) Hansel¨ et al. [53] and “strong cutaneous LE SLE serum compared with inflammation” SLE control serum

Studieshaveshownreduced[74–81],normal[80,82],and those circulating in the periphery. Consequently, these pop- + increased [83] levels of CD11c mDC frequencies in PBMC ulations should be included in further assessments in order fromlupuspatientscomparedtohealthycontrols.Similarly, to understand their contribution to disease pathogenesis and pDC levels were found to be unaffected, reduced [74–78, 84, allow for a rational design of DC-targeting therapeutics. 85], or increased [79, 86]. Decreased frequencies of pDCs or mDCs were most often associated with active disease and toa 5. SLE-Associated Dysfunction in Primary DCs lesser degree with nonactive disease [75]. Interestingly, studies showing peripheral pDCs decreases observed a concomi- The few published maturation and functionality studies with tant infiltration of pDCs in nephritic kidneys, suggesting that primary human DCs have given conflicting results. Earlier active pDCs may have migrated to the sites of inflammation reports indicated that DCs from SLE patients have normal [78, 82]. Similarly, Fiore et al. showed that besides pDCs, or even reduced levels of costimulatory molecules and are + + BDCA1 DCs and BDCA3 DCs were increased in the poor stimulators of allogeneic T cells in mixed lymphocyte + renal tubulointerstitium of patients with lupus nephritis [78]. reactions. Scheinecker et al. reported that in SLE patients B7 + Increased numbers of pDCs and inflammatory/slanDCs are and CD40 DCs were reduced and that DC-enriched APC also found in cutaneous lesions of lupus patients, further from SLE patients displayed a diminished T cell-stimulatory suggesting migration of DCs to target organs [87, 88]. It is capacity in both the allogeneic and the antigen-specific MLR, likely that DCs that reside in or have been recruited into as compared with healthy individuals [76]. On the other the affected tissues will display different characteristics than hand, Mozaffarian et al. showed increased CD80/CD86 and

255 Mediators of Inflammation 5 reduced PDL-1 expression on mDC during disease flares and 7. Nature versus Nurture an upregulation of PDL-1 during remission [89]. Similarly, Gerl et al. [81] published that monocytes and mDCs from SLE Drawing causative relationships between DCs frequencies, patients expressed higher levels of CD86 and BAFF, but not maturation status, functionality, and disease is complex as CD83 and CD40. Upon further assessment of their migratory it is not clear whether aberrations in DC frequency and capacity, they found that pDCs and mDCs from SLE patients functionality are the driver or a result of the disease. It is likely had normal expression of CCR1, CCR5, and CCR7 but that genetic alterations in DCs predispose to the development reduced expression of the chemokine receptor ChemR23 of accelerated maturation and abnormal behavior. Evidence (CMKLR1).However,pDCsfromtheSLEpatientsshowed for this intrinsic defect is supported by the observations that an increased basal and CCL19-specific migration in vitro. moDCs from SLE patients, generated from either PBMC or Assessment of peripheral monocytes, total DCs, bone marrow, display accelerated maturation and increased + −/ + BDCA1 DCs, and CD14 lowCD16 DCs by Henriques et al. proinflammatory status compared to moDC from healthy showed that a higher percentage of SLE monocytes and donors. On the other hand, serum of SLE patients has been −/ + shown to contain pro- and anti-inflammatory stimuli like CD14 lowCD16 DCs produced proinflammatory cytokines as well as a higher amount of cytokines produced per cell, type I IFN, type I IFN-inducing factors, and IL-10 that alter particularly in active disease. Data from Kwok et al. [90] DC differentiation, maturation, and functionality, even in seemed to indicate that type I IFN production by pDC DCs from healthy donors [97–99]. This raises the question upon TLR9 engagement was diminished in SLE patients, whether the aberrant behavior of DCs in SLE patients is leading them to hypothesize that the persistent presence of a result from an intrinsic defect, a result of their develop- endogenous IFN𝛼-inducing factors induces TLR tolerance ment in an inflammatory environment, or a combination of in pDCs of SLE patients, resulting in impaired production these two [97]. To further confound the interpretation of of IFN𝛼. Studies by Jin et al. [79, 91] also suggested human clinical data, various classic SLE treatments, including deficiencies in TLR9 recruitment/signaling and production antimalarials, corticosteroids, and immunosuppressive drugs of proinflammatory cytokines in pDCs from SLE patients; significantly affect DC number, maturity, and functionality however, they also showed that SLE pDC had an increased [100]. ability to stimulate T cells. Importantly, while pDCs from healthy donors induced suppressive T regulatory cell features 8. Mouse Models to Dissect Role of (Foxp3 expression) in T cell cultures upon addition of DCs in SLE Pathogenesis apoptoticPMNs,SLEpDCsfailedtodoso. These studies indicate that SLE is associated with pheno- The availability of mouse models provides an exciting oppor- typic and functional changes in DCs and that these changes tunity to gain cellular and molecular insight in the role of can affect different aspects of the DCs’ functional program in different DC populations in the development and progression distinct and divergent ways. of SLE. There are a variety of spontaneous models, including the F1 hybrid between the New Zealand Black (NZB) and 6. SLE-Associated Dysfunction in New Zealand White (NZW) strains (NZB/W F1) and its In Vitro Generated DCs derivatives,theMRL/lprandBXSB/Yaastrains,aswellas inducible models such as the pristane-induced model and Due to the paucity of DCs in leukopenic SLE patients, many chronic graft-versus-host-disease models (cGVHD) [101– studies have used in vitro generated monocyte-derived DCs 104]. In recent years the number of models has been expanded (moDCs) to gain insight in DC generation, phenotype, and with genetically modified mice, targeted in genes that can function in the context of SLE. promote, resist, and modify lupus susceptibility [105, 106]. All Initial studies suggest that monocyte-derived DCs had a of these models display their own variation of lupus-like dis- reduced proinflammatory and T cell stimulatory activity [92] ease reminiscent of symptoms observed in patients, including while later studies suggested accelerated differentiation and autoantibody production, lymphoid activation and hyperpla- maturation concomitant with increased activity to matura- sia, lupus nephritis, and skin manifestations. Although all of tion stimuli [93]. MoDCs from SLE patients expressed higher these models have been instrumental in the identification of levels of HLA-DR and activating Fc𝛾Rs, but decreased expres- severalmainconceptsinthisdiseases,noneofthemodelscan sion of inhibitory Fc𝛾R and expression levels correlated with completely recapitulate the complexity and variety of human disease severity [92, 94]. In addition, moDCs spontaneously disease. However, careful pairing of models with patient overexpressed activating costimulatory molecules including groups with the similar clinical manifestations can ensure the CD40, CD80, and CD86 and showed increased production of translational relevance of these preclinical models. stimulatory cytokines (IL-6, IL-8, and BAFF/BlyS), eventually Mousemodelshaveseveraladvantages:(i)therelative resultinginanincreasedcapacitytoactivateTcellsinanMLR homology between human and mouse DCs, (ii) the oppor- [93, 95]. Similarly, Nie et al. [96] demonstrated substantial tunity to genetically or pharmacologically eliminate specific phenotypic and functional aberrations in DCs generated DC populations during specific stages of disease, (iii) access from Flt3-ligand and GM-CSF/IL-4 stimulated bone marrow to all target tissues for the assessment of tissue associated or aspirates. Both immature and mature DCs from SLE donors infiltrating DCs, (iv) the opportunity to assess the effects of expressed higher levels of CCR7, CD40, and CD86 and common treatments on the parameters, and (v) a plethora of induced stronger T cell proliferation. biological and pharmacological tools to dissect the relative

256 6 Mediators of Inflammation contribution of specific molecules and mediators to the producing capacity upon TLR9 stimulation and increased cell development and progression of disease. survival compared to pDCs from C57BL/6 mice. Enhanced mDCandpDCactivityhasalsobeenreportedinmaleBXSB/ 9. Similarities between Mouse and Mp mice that express an extra copy of Tlr7 on the Y chromosome. Human DCs Importantly, depletion studies have now shown causal relationships between DC subsets and disease manifestations. Recent genomic, proteomic, and functional analyses of Constitutive depletion of pDCs in lupus-prone mice either mouse and human DCs have identified high homology through genetic ablation of IRF8, a transcription factor between the most abundant DC populations [107]. Like in required for pDC and CD8𝛼DC development, or by diphthe- humanDCs,mouseDCslineagesencompassconventional + ria toxin treatment of mice expressing the diphtheria toxin DCs, pDCs, CD14 DCs, tissue DCs, and monocyte-derived/ receptor on pDCs resulted in markedly reduced type I IFN inflammatory DCs [38, 108]. production, a reduced IFN signature, reduced autoantibody Conventional mouse DCs encompass three main production,andreductionintheseverityofkidneypathology subpopulations which are found in circulation as glomerulonephritis [124–126]. Importantly, transient pDC well as in secondary lymphoid organs [109]: (1) high + 𝛼− + 𝛼+ + depletion during the early stages of disease was sufficient CD11c MHCII CD8 33D1 Sirp CD11b (CD11b DCs), to significantly alter the course of the disease, suggesting a which express most TLRs except Tlr3, display a more prominent role for pDCs in the induction of the disease preference for activation of CD4 T cells, and have + than in disease pathogenesis at later stages of disease [125]. high homology with the human BDCA1 DCs; lpr high + 𝛼+ + 𝛼− − 𝛼 Diphtheria toxin treatment of CD11c-DTA MLR.Fas mice (2) CD11c MHCII CD8 CD205 Sirp CD11b (CD8 resulted in reduced T cell differentiation, plasmablast num- DCs), which express Xcl1, CD141, and Clec9A and express bers, and autoantibody levels. Interestingly, these mice devel- mRNAs coding for most TLRs except Tlr5 and Tlr7, oped interstitial kidney infiltrates but failed to progress to and are characterized by high Tlr3 expression; and (3) glomerular or interstitial nephritis, suggesting that DCs play high + 𝛼 CD11c MHCII cells that lack CD8 , CD4, and CD11b a role in the development of tissue damage [127]. In line with (generally termed “double” or “triple” negative) DCs that, like this observation, this group also showed that CD11c deple- CD8a DC, express Xcl1, CD141, Clec9A, and Tlr3 [110–113]. tion, but not LC depletion, resulted in significantly reduced These latter two populations have a high capacity to dermatitis, demonstrating that DCs other than LCs control phagocytose dying cells and cross-present cell-associated or dermatitis in this model [127]. particulate antigens to CD8 T cells. Based on their genomic Besides the opportunity to assess the relative and tem- and functional analysis these two populations are considered + poral contribution of different DC populations to the devel- to be homologues to the human BDCA3 DCs. opment of specific disease manifestations, mouse models Like human pDCs, mouse pDCs produce vast amounts also allow for the identification of specific processes in of type I IFN in response to viruses via TRL7/9 mediated DCs which affect disease development. Targeted deletion of pathways. Compared to their human counterparts, mouse regulatory molecules associated with SLE susceptibility in pDCs show relatively poor capacity for phagocytosis and humans, including Shp1, A20, Blimp-1, Lyn, or Eat-2, specif- + antigen presentation. However, both populations have been ically in CD11c cells resulted in increased DC activity and implied in the maintenance of peripheral tolerance [45, 114– development of inflammatory and autoimmune phenotypes 116]. characterized by the production of autoreactive antibodies Various types of inflammatory and monocyte-derived and several manifestations of SLE, including severe glomeru- DCshavebeenidentifiedinmiceaswell.Tissueinfiltrating + lonephritis [128–132]. CD14 DC-like cells have been found under inflammatory Together these observations indicate that mouse models conditions [117, 118]. Inflammatory DCs have been shown to provide a useful platform for the identification, dissection, arise after a wide variety of immunological insults, including and targeting of DC intrinsic and extrinsic processes that pathogenic infection, experimental sterile inflammation, and facilitate the development, progression, and possibly a cure models of inflammatory diseases such as RA, colitis experi- for SLE. mental autoimmune encephalomyelitis, and allergic asthma (reviewed in [119]). 11. DC Targeted Therapies for SLE 10. The Role of DCs in Mouse SLE Models BasedonthegeneralroleofDCintheregulationof peripheral tolerance to self-antigens, the dysregulation of Recent studies indicate an important role for DCs in the DCs observed in SLE, and the emerging evidence of the development and progression of SLE-like disease in mouse contribution of DCs in the initiation and perpetuation of SLE models. Similar to human disease, DCs from lupus-prone pathogenesis, it is not surprising that DC-targeting thera- mice display a range of alterations in their numbers and their peutic strategies have become a topic of interest. Particularly, functionality [120–123]. Splenic DCs from NZB/W F1 showed strategies that would promote self-antigen presentation in a enhanced maturation and a stronger ability to attract B cells tolerogenic context could be promising for the generation of and present antigens to T cells than DCs from control mice. an abortive or suppressive environment for the autoreactive T pDCs from SLE-prone mice showed increased type I IFN and B cells and restoration of peripheral tolerance [133, 134].

257 Mediators of Inflammation 7

In recent years several ex vivo models have been established ScienceFoundationofChina(no.81230072;no.81025016;no. for the generation of human DCs with stable tolerogenic 81401331, to Nan Shen), the Program of the Shanghai Com- functions (reviewed in [135]). Generally, these resulting mission of Science and Technology (no. 12JC1406000 to Nan tolerogenic monocyte-derived DCs express low levels of Shen), and the Special Fund for Public Benefit Research from positive costimulatory molecules and high levels of immune the Ministry of Health (no. 201202008, to Nan Shen). suppressive mediators (PDL-1, IL-10, etc.). Upon pulsing with specific antigens these DCs are anticipated to promote References antigen-specific tolerance via the induction of T cell anergy, Tcellapoptosis,skewingofTcellphenotypestomoreTh2 [1]K.M.Uramoto,C.J.MichetJr.,J.Thumboo,J.Sunku,W.M. or regulatory phenotypes, and the expansion of regulatory T O’Fallon, and S. E. Gabriel, “Trends in the incidence and mortality of systemic lupus erythematosus, 1950–1992,” Arthritis & cells. Rheumatism,vol.42,no.1,pp.46–50,1999. Tolerogenic DC therapy is still in its infancy and little data [2]D.Pineles,A.Valente,B.Warren,M.Peterson,T.Lehman,and isavailableonitsin vivo potential. The first studies showed L. N. Moorthy, “Worldwide incidence and prevalence of pedi- that transfer of antigen-loaded tolerogenic DCs could induce atric onset systemic lupus erythematosus,” Lupus,vol.20,no. antigen-specific regulatory CD8 T cells and inhibit effector 11, pp. 1187–1192, 2011. functions in antigen-specific CD8 T cells [136, 137]. A clinical [3]G.J.Pons-Estel,G.S.Alarcon,L.Scofield,L.Reinlib,andG.´ trial in patients with type I diabetes using DCs treated with S. 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Ozen,¨ “Quality of life measures and psychiatric symptoms in adolescents with systemic lupus erythematosus Acknowledgments and familial Mediterranean fever,” International Journal of Adolescent Medicine and Health,vol.26,no.4,pp.541–549,2014. This work was supported in part by the Lupus Research [14]E.Waldheim,A.-C.Elkan,S.Petterssonetal.,“Health-related Institute (to Edith M. Janssen), NCI Grant CA138617 (to quality of life, fatigue and mood in patients with SLE and high Edith M. Janssen), Charlotte Schmidlapp Award (to Edith levels of pain compared to controls and patients with low levels M. Janssen), the Albert J. Ryan Fellowship (to Jared Klar- of pain,” Lupus, vol. 22, no. 11, pp. 1118–1127, 2013. quist), the National Basic Research Program of China (973 [15] J. Yazdany, “Health-related quality of life measurement in program; 2014CB541902, to Nan Shen), the National Natural adult systemic lupus erythematosus: Lupus Quality of Life

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263 Journal of Visualized Experiments www.jove.com

Video Article The bm12 Inducible Model of Systemic Lupus Erythematosus (SLE) in C57BL/6 Mice

Jared Klarquist1, Edith M. Janssen1 1 Division of Immunobiology, Cincinnati Children's Hospital Medical Center and University of Cincinnati College of Medicine

Correspondence to: Edith M. Janssen at [email protected]

URL: http://www.jove.com/video/53319 DOI: doi:10.3791/53319 Keywords: Medicine, Issue 105, T follicular helper cell (Tfh), germinal center (GC) B cell, plasma cell, ascites, flow cytometry, animal model, anti- nuclear antibody (ANA), autoimmunity, nephritis, trogocytosis, chronic graft-versus-host disease (cGVHD), type I interferon (IFN) Date Published: 11/1/2015 Citation: Klarquist, J., Janssen, E.M. The bm12 Inducible Model of Systemic Lupus Erythematosus (SLE) in C57BL/6 Mice. J. Vis. Exp. (105), e53319, doi:10.3791/53319 (2015).

Abstract

Systemic lupus erythematosus (SLE) is an autoimmune disease with diverse clinical and immunological manifestations. Several spontaneous and inducible animal models mirror common components of human disease, including the bm12 transfer model. Upon transfer of bm12 splenocytes or purified CD4 T cells, C57BL/6 mice rapidly develop large frequencies of T follicular helper cells (Tfh), germinal center (GC) B cells, and plasma cells followed by high levels of circulating anti-nuclear antibodies. Since this model utilizes mice on a pure C57BL/6 background, researchers can quickly and easily study disease progression in transgenic or knockout mouse strains in a relatively short period of time. Here we describe protocols for the induction of the model and the quantitation Tfh, GC B cells, and plasma cells by multi-color flow cytometry. Importantly, these protocols can also be used to characterize disease in most mouse models of SLE and identify Tfh, GC B cells, and plasma cells in other disease models.

Video Link

The video component of this article can be found at http://www.jove.com/video/53319/

Introduction

Systemic lupus erythematosus (SLE) is a complex autoimmune disease characterized prototypically by anti-nuclear antibody (ANA) production and glomerulonephritis. Numerous other sequelae, including dermal, cardio-pulmonary, and hepatic lesions are associated with disease in some individuals. Prevalence estimates in the US vary widely, from 150,000-1,500,0001,2, with particularly high incidence in women and minorities3. Although the etiology of SLE has been difficult to discern, it is thought to arise from the interplay of various genetic and environmental factors, which culminate in systemic autoimmunity.

Numerous animal models have been employed to study factors leading to disease onset and progression. Classic mouse models of SLE include genetically predisposed mouse strains including the NZB x NZW F1 model and its NZM derivatives, the MLR/lpr strain, and the BXSB/Yaa strain, and inducible systems, such as the pristane and chronic graft-versus-host disease (cGVHD) models4. Early reports of autoantibody production in GVHD models used various mouse strains or hamster strains for parent into F1 transfers5–8; more common methods used to study lupus- like disease currently include the DBA/2 parent→(C57BL/6 x DBA/2) F1, and the bm12 transfer model described here. Each model has its own caveats, but they generally share a common set of features that correlate with clinical features of human disease. The most often reported parameters in mouse models include splenomegaly, lymphadenopathy, nephritis, ANA production, and at the cellular level, the expansion of T follicular helper cells (Tfh), germinal center (GC) B cells, and plasma cells.

The inducible bm12 model is achieved by the adoptive transfer of lymphocytes from I-Abm12B6(C)-H2-Ab1bm12/KhEgJ (bm12) mice, a strain identical to C57BL/6 except for 3 amino acid substitutions on MHC class II, into I-Ab C57BL/6 (B6) mice. Alloactivation of donor CD4 T cells by recipient APCs leads to cGVHD with symptoms closely resembling SLE. Specifically, these include expansion of donor-derived Tfh, expansion of recipient-derived GC B cells and plasma cells, and production of ANAs including anti-dsDNA, anti-ssDNA, anti-chromatin, and anti-RBC antibodies9. Over time, recipient mice develop glomerulonephritis associated with IgG deposits in the glomerular, interstitial, and vascular regions of the kidneys10. We have recently shown that, similar to human disease, there is also a critical role for type I IFN in this model11. Notably, the defining criteria for human SLE include the development of nephritis compatible with SLE in the presence of anti-dsDNA antibodies12, both of which are prominent features of this mouse model.

There are several advantages of the bm12 model over the spontaneous models. Classic models that develop SLE-like signs spontaneously rely upon either hybrid mouse strains, inbred mouse strains not on the B6 background, or large genetic loci on the B6 background, which make crossing to knockout or otherwise genetically modified mice difficult and time consuming. With the bm12 inducible model, genetically modified mice can serve as either the donor or recipient, allowing more rapid identification of the cellular compartment in which particular genes may be important for disease. Furthermore, disease development in the bm12 model is much faster, requiring only 2 weeks until the appearance of ANAs, compared to several months for most spontaneous models. Moreover, in contrast to the spontaneous models that develop disease

at different time points, the disease onset and progression in the bm12→B6 model is highly synchronized. This allows for the generation of appropriately sized cohorts that can be used for interventional or therapeutic strategies at any stage of disease development.

What follows is a detailed protocol for initiating SLE-like autoimmunity by the adoptive transfer of bm12 lymphocytes into C57BL/6 mice, or genetic variants on the B6 background. Additionally, we describe a flow cytometric staining protocol for enumerating Tfh, GC B cells, and plasma cells—cell types associated with human disease. Importantly, these protocols can also be used to characterize disease in most mouse models of SLE and identify Tfh, GC B cells and plasma cells in other disease models.

Protocol

Animal work was performed under specific pathogen-free conditions in accordance with guidelines set by the Association for Assessment and Accreditation of Laboratory Animal Care International and our Institutional Animal Care and Use Committee (IACUC).

NOTE: Incorporate mice expressing a congenic marker such as CD45.1 on either donor or recipient animals if possible, because this allows for the monitoring of donor graft efficiency and specific expansion of the donor CD4 T cell population. If considering the use of otherwise genetically modified mice as donor or recipients, ensure the strain is properly backcrossed to the B6 background, or transferred cells may be rejected—this will be addressed in greater detail in the representative results and discussion sections.

NOTE: The following procedures detail volumes for harvesting 4 donor bm12 mice, which should yield enough cells to inject 12-16 mice. Six to twelve week-old bm12 mice yield roughly 100-140 million lymphocytes with approximately 25% CD4 T cells. If starting with different numbers of mice, or different mouse strains, scale volumes up or down accordingly. C57BL/6 mice generally give similar yields with closer to only 20% CD4 T cells.

NOTE: Perform all steps at RT and use RT media to avoid heat and cold shock, which can impair long-term lymphocyte viability. Perform tissue- harvesting and tissue-processing steps in a tissue culture hood using aseptic technique. All media in this protocol is IMDM with 10% heat- inactivated FBS, unless indicated otherwise, and will be simply referred to as “complete media.” 1. Novel Method for Genotyping bm12 Mice

NOTE: A brief restriction digest-based protocol for genotyping is provided here, as a simple and inexpensive alternative to sequencing, which is currently the only published genotyping method for these mice.

1. Isolate genomic DNA from mouse tails. Please refer to a previous JoVE article for detailed protocols on mouse tail clipping and the generation of cDNA from tail digests13. 2. Perform a reverse-transcriptase polymerized chain reaction (PCR)14 to amplify a common 474 bp DNA fragment from MHC-II I-Ab and I-Abm12 using primers and thermocycling conditions listed in Table 1. 3. Perform restriction digest on ~7 µl of the PCR product using the enzyme PsuI, or one of its isoschizomers (BstX2I, BstYI, MflI, or XhoII), which cuts wild type I-Ab, but not I-Abm12 mutant. Follow digest protocol provided by the manufacturer, which will specify a mixture of water, buffer and enzyme, and an incubation of 5 min. to several hours at 37 °C15. 4. Load digest product and run on 1% polyacrylamide gel with ethidium bromide14 for 30-45 min. at 150V—though optimal voltage and time settings will vary depending on the PCR gel apparatus used. Visualize DNA bands with a UV illuminator. Representative results are shown in Figure 1.

Figure 1. Representative bm12 genotyping results.

To identify mice homozygous for I-Abm12/bm12, tail DNA was screened for bm12 by PCR/restriction digest genotyping (Step 1). Homozygous wild type (I-Ab/b) DNA yields two bands at 227 and 247 bp (visualized as one thick band at ~250 bp); homozygous bm12 (I-Abm12/bm12) DNA yields one band at 474 bp; and heterozygous (I-Abm12/b) DNA yields two bands at ~250 and 474 bp. Please click here to view a larger version of this figure. 2. Harvesting Donor Cells

1. Sacrifice donor mice using Institutional Animal Care and Use Committee (IACUC)-approved primary and secondary euthanasia methods. For example, euthanize mice by asphyxiation with CO2 followed by cervical dislocation. 2. Using aseptic technique, harvest spleens and lymph nodes (superficial cervical, mandibular, brachial, axillary, mesenteric, and inguinal) into 15 ml tubes containing 10 ml complete media as in11-13.

NOTE: Refer to previous reports for detailed lymph node dissection protocols16–18. This model is also successful using only mouse splenocytes for transfer, but the addition of lymph nodes significantly reduces the required number of donor mice.

3. Generate a single-cell suspension by mashing lymphoid tissues collected in step 2.2 through 70 µm cell strainers using the plunger from a syringe. For better yields, do not overload strainers—use ~6 strainers for every 4 mice processed, and rinse strainers frequently while processing. Combine tissues from 4 mice into two 50 ml conical tubes, then centrifuge cells for 5 min at 400 x g and decant supernatant. 4. Resuspend cells from both conical tubes in 50 ml complete media and transfer to new conical tube. Keep this tube at RT.

NOTE: Fat adheres to the sides of the tube, and if the tube is not replaced, final cellular yields can suffer. 3. Donor Cell Counting

NOTE: To preserve the highest viability, red blood cell (RBC) lysis of the entire sample is not recommended.

1. Mix single cell suspension from step 2.4 well, remove 1 ml and transfer it to a separate 50 ml conical. Set aside remaining, untouched cells (49 ml) at RT while counting. 2. Add 3 ml of an ammonium chloride-based red blood cell lysis buffer to the 1 ml donor cell sample. Mix gently for 1 min. by rocking, then fill to 50 ml with complete media, and centrifuge for 5 min. at 400 x g and decant supernatant. 3. Resuspend RBC-lysed cells in 10 ml complete media and count (e.g., with trypan blue using a hemocytometer). Multiply result by 49—this is the total number of cells remaining in the non-lysed sample that was set aside. Discard RBC-lysed cells. 4. Donor Cell Labeling and/or CD4 T Cell Purification

1. If desired, purify CD4 T cells at this stage, though this is not necessary. Additionally, if desired, label cells with CFSE, as in19, or other cell tracking dyes, an example of which is shown in Figure 4 of the representative results section.

NOTE: For CD4 T cell purification, negative magnetic selection is recommended, as it can achieve high purity and leaves cells untouched with high viability as described in20. It is important that endotoxin-free buffers are used; therefore, instead of BSA, make separation buffer with 2% FBS and the recommended concentration of EDTA. 5. Injection of Donor bm12 Cells

1. After counting donor lymphocytes in step 3 (and purified or labeled as in step 4, as desired), centrifuge cells for 5 min at 400 x g. Decant supernatant and resuspend cells in PBS at 120 million lymphocytes per ml (or 30 million purified CD4 T cells per ml). Transfer cells to a sterile 5 ml round-bottom tube, or other sterile tube that easily accommodates a 1 ml syringe fitted with a 27.5 G x 13 mm needle. 2. Prior to injection, set aside a small sample of donor cells from step 5.1 at 4 °C for flow staining to determine the percentage of CD4 T cells within donor samples. Stain these samples as described in Step 8 using the minimal antibody panel (Table 2).

NOTE: If cells from different mouse strains are used as separate donors, this is an important consideration, and if CD4 T cell percentages vary substantially, purification may be required. 3. Mix cells gently, but thoroughly. This can be done by pipetting cells up and down using a 1 ml syringe without an attached needle. After mixing, draw cells into the 1 ml syringe. Attach needle after removing any air bubbles. Keeping the needle off while priming the syringe helps maintain cell viability. 4. Inject 250 µl per mouse (which is equal to 30 million lymphocytes, or 7.5 million purified CD4 T cells per mouse) intraperitoneally, as described in21.

NOTE: In experiments shown here and in our prior work11, each mouse is injected with 30 million total lymphocytes from bm12 donors, rather than the 100 million total splenocytes traditionally used. In unpublished data from our lab, no difference was observed in serum anti-dsDNA at day 14 following injections of 30 or 100 million lymphocytes per mouse. While this significantly reduces the number of mice needed for experiments, the development of nephritis with this number of cells has not been assessed. 6. Determine Grafting Efficiency

NOTE 1: This section will describe how to determine the degree of donor cell grafting in the recipient at day 3 in order to identify any mice which may have received suboptimal injections (e.g., the graft in one mouse is <10% of that seen in all other mice from the same group). These data can also help determine whether cells from a genetically modified mouse strain are rejected at later time points (for details, see representative results section, Figure 6).

NOTE 2: This section is only possible if donors and recipients are from mice on different congenic backgrounds, e.g., when using CD45.1 bm12 donors and CD45.2 C57BL/6 recipients, or when donor cells are labeled with a cell tracking dye. Importantly, at 3 days post-injection, CD4 T cells have undergone minimal expansion (see representative results section, Figure 4), so differences observed in the degree of grafting are due to variability in injections, not expansion.

1. Anesthetize mice with 4% isoflurane or other IACUC-approved method. Test rear foot reflexes to ensure mouse is properly anesthetized before proceeding to the blood draw. 2. Harvest 100-200 µl blood using an IACUC-approved method, such as retro-orbital puncture as in22. Collect blood into individual 0.5 ml microcentrifuge tubes containing an anti-coagulant, such as the plasma collection tubes referenced in the materials table, which contain lyophilized dipotassium EDTA. After blood collection, apply gentle pressure to the mouse eye using a sterile towel or gauze to ensure the bleeding stops, then place the mouse back in its home cage where it will remain until the final tissue harvest (Step 7).

NOTE: Do not leave mice unattended until mice have regained sufficient consciousness to maintain ventral recumbency, and do not return mice to the company of others until fully recovered. 3. Bring blood volume to 500 µl with 21 °C PBS and transfer to conical-bottom microcentrifuge tube, then slowly underlay 200 µl of 21 °C high density cell separation solution with a 200 µl pipet, being careful to minimize mixing between the two phases (see Materials Table for recommended solutions). Centrifuge cells at 700 x g for 20 min at 20-25 °C with centrifuge brake set to low.

4. Remove top layer containing lymphocytes with a 1 ml pipet and transfer to a new microcentrifuge tube containing 800 µl cold complete media. Gently vortex to mix cells. Centrifuge cells at 700 x g for 5 min at 4 °C and decant supernatant. 5. Resuspend cells in 200 µl complete media, transfer to a 96-well U-bottom plate, and stain for flow cytometry as described in Step 8 using a minimal antibody panel (Table 2) to determine the relative abundance of the CD4 T cell graft as a percentage of PBMCs. 7. Final Tissue Harvest

NOTE: The experiments described in the results section were harvested 14 days after injection of donor cells (or in some cases less time), as they focus on the initial development of Tfh cells and plasma cells; however, since this model is a chronic GVHD model of SLE, disease can be monitored at much later time points. The optimal timeframe will depend upon the research question posed in each individual experiment.

1. At a predetermined time point after injection of bm12 donor cells (step 5.4), sacrifice mice using an IACUC-approved method of euthanasia. Asphyxiation with CO2 followed by exsanguination is recommended. Cervical dislocation can function as a secondary method of euthanasia, but this may reduce the blood draw yield. 2. Wet the abdomen of the mouse lightly with a spray bottle containing 70% ethanol. Make a small, superficial incision with surgical scissors approximately 1 cm above the genitalia. Draw back the skin of the abdomen toward the sternum, being careful to keep the peritoneal fascia intact.

NOTE: Diseased mice usually present with 0.5-3 ml ascites at day 14, which, although it has not yet been well characterized, can be measured and analyzed as an additional disease parameter. 3. Fit a 5 ml syringe with an 18 G needle. Insert the needle into the lower right quadrant of the abdomen with the needle directed up toward the animal’s head and at 15° angle to the plane of the fascia. Position the needle tip near the cecum to help prevent the needle from getting clogged with intestine while aspirating ascites. 4. Carefully rotate the mouse on its side, then slowly draw ascites into the syringe. Once ascites has been recovered, remove the syringe and record the aspirate volume, based upon the volumetric markings on the side of the syringe. 5. Discharge ascites into a 5 ml round-bottom tube and store on ice for later processing. 6. Harvest blood via draw from the inferior vena cava (IVC) essentially as in22. Using dull forceps, gently move intestines to the left side of the mouse, uncovering the IVC. Insert a 27.5 G needle fitted to a 1 ml syringe into the IVC and slowly draw 400-500 µl of blood. 7. To minimize hemolysis, slowly inject blood into a 0.5 ml microcentrifuge serum or plasma collection tube. For later serum analysis of ANAs by ELISA, keep blood on ice. 8. Dissect and obtain additional relevant tissues (spleen and, if desired, lymph nodes and kidneys, particularly if collecting at later time points and glomerulonephritis will be scored). Remove spleen by gently placing the intestines back toward the right side of the animal, and pulling on the pancreas, which is the spleen’s primary connective tissue. 9. Remove any pancreas remaining, then weigh spleens on a high precision balance immediately after dissection, as gross splenomegaly is a commonly reported parameter in mouse models of SLE. Place lymphoid tissues into individual 1.5 ml tubes filled with 1ml complete media on ice. Fix kidneys in 10% neutral buffered formalin or snap freeze kidneys for later histology as in23. 10. Centrifuge blood within 2 hr of collection for 3 min. at 10,000 x g (4 °C). Remove serum and store at -80 °C for later analysis of ANA by ELISA. Refer to previous reports for detailed ANA ELISA protocols24,25. Store serum in multiple 10-20 µl aliquots to minimize freeze/thaw cycles, and allow a greater number of future assays. 11. Centrifuge ascites 400 x g for 5 min. Remove the supernatant with a 1 ml pipet and aliquot into several 0.5 ml tubes. Freeze supernatant at -80 °C for later analyses of anti-nuclear antibodies (ANAs) or other soluble inflammatory mediators. 12. Resuspend cellular fraction in approximately 1 ml complete media and transfer 200 µl to a 96-well U-bottom plate for flow staining (as in Step 8). 13. Mash each spleen through 70 µm cell strainers into separate tubes and rinse with complete media. Resuspend splenocytes with 1 ml cold RBC lysis buffer for 1 min. and mix gently by rocking. Bring volume to 10 ml with cold complete media and centrifuge for 5 min at 400 x g and decant supernatant. 14. Resuspend cell pellet in 5 ml complete media and count using a hemocytometer. Adjust volume such that 200 µl of complete media contains 1-3 million cells. Begin staining for flow cytometry (Step 8) using an extended panel (Table 2) to quantify donor CD4 T cell and recipient B cell differentiation and expansion.

NOTE: Depending upon what laser, photomultiplier tube (PMT), and filter set combinations are available, separating the T and B cell analysis panel into multiple panels may be necessary. 8. Flow Staining

1. Transfer 1-3 million splenocytes in 200 µl complete media into individual 5 ml round-bottom tubes, or into separate wells of a 96-well U- bottom plate.

NOTE: Using a 96-well plate is an efficient way to stain multiple samples, but take care to plate samples in every other well in order to prevent cross-contamination. One 96-well plate can accordingly hold 24 samples. 2. Centrifuge plate at 500 x g for 3 min., then flick supernatant from plate into appropriate (biohazard) container. 3. Resuspend the cell pellets with 100 µl of flow buffer (1% FBS in PBS) containing a fixable viability dye at the manufacturer’s recommended concentration and purified anti-CD16/anti-CD32 antibody cocktail at 1 µg/ml. Incubate for 10 min at 20-25 °C, then add 100 µl cold complete media to quench viability dye.

NOTE: Splenocytes from diseased mice usually contain relatively high numbers of dead or dying cells; therefore, the inclusion of a viability dye is recommended to avoid non-specific antibody labeling of dying cells, resulting in cleaner, more reliable data. Similarly, the anti-CD16/ anti-CD32 cocktail is included to block non-specific fluorescently-labeled antibody binding by Fc receptors. 4. Centrifuge plate at 500 x g for 3 min., then flick supernatant from plate into biohazard container. Resuspend cells in 200 µl flow buffer. Centrifuge plate at 500 x g for 3 min., then flick supernatant from plate into biohazard container. 5. Resuspend cells in 50 µl flow buffer containing antibody cocktail (Table 2). Incubate for 20 min at 4 °C, then add 150 µl flow buffer. Repeat wash step 8.4.

6. Resuspend cells with 100 µl 2% paraformaldehyde in PBS. Incubate for 30 min at 4 °C, then add 100 µl flow buffer. Centrifuge plate at 500 x g for 3 min., then flick supernatant from plate into biohazard container. 7. Resuspend in 200 µl flow buffer, transfer to flow tube inserts or standard flow tubes, add an additional 100-200 µl flow buffer, and store at 4 °C in the dark until acquiring on flow cytometer. 8. Acquire on a flow cytometer equipped with the appropriate lasers and PMTs for the chosen antibody panels within several days of staining. Record forward scatter width and/or height in addition to forward scatter area, side scatter area, and area of the fluorescent parameters utilized. For reliable results, acquire ≥1,000 donor cells in each WT sample, or an equivalent number of total lymphocytes in genetically modified or otherwise manipulated mice that show minimal expansion of donor cells, where collection of so many events may not be feasible.

NOTE: Flow cytometry analyses are described in detail in the representative results section (Figures 3-6).

Representative Results

Diseased mice develop splenomegaly in as little as 14 days, exhibiting spleens 2-3 times the size of healthy mice in terms of mass and cellularity (Figure 2).

Splenocytes are sequentially gated on light scatter (FSC-A by SSC-A), elimination of doublets (FSC-W or -H by FSC-A), viable cells (low staining + + of viability dye), and CD4 TCRβ (Figure 3A). Donor cells are distinguished from recipient cells based on CD45.1 and CD45.2 (Figure 3B, bottom left). Donor cells predominantly adopt a T follicular helper (Tfh) cell phenotype, as characterized by the upregulation of PD-1, CXCR5, Bcl-6, and ICOS (Figure 3B, C). A portion of the recipient CD4 T cell population also differentiates into Tfh (Figure 3B, bottom right). After an initial die-off and/or migration of transferred cells, the expansion of donor-derived Tfh is logarithmic, reaching 10-20 million cells in the spleens of mice 14 days after injection (Figure 3D).

CFSE-labeling of transferred lymphocytes demonstrated that donor CD4 T cells differentiate into Tfh early after activation; essentially all divided cells observed at days 3, 7, and 14 upregulated CXCR5 and PD-1 (Figure 4). The proliferation peak profiles also suggest that a relatively low percentage of donor CD4 T cells underwent alloactivation and division. By day 14, most of the detectable donor cells are those that have divided beyond the maximum number of divisions measurable by CFSE.

The expansion of donor-derived Tfh is accompanied by a corresponding accumulation of endogenous GC B cells and plasma cells (Figure 5A). Plasma cell accumulation in the spleen is delayed compared to that of Tfh, exhibiting no increase over naïve animals on days 3 or 7 (Figure 5B). Accordingly, anti-nuclear antibodies are not readily detectable prior to day 9 (data not shown), but can be reliably quantified on day 1411.

Through the use of congenic markers, we have observed rejection of donor cells in multiple strains. While this is a common problem when mice are not sufficiently backcrossed to the C57BL/6 background, we also observed rejection when bm12 cells were transferred into B6.PL-Thy1a/ CyJ (CD90.1) mice that are generally considered to be fully backcrossed. Therefore, mice are routinely screened at day ~3 by flow staining blood samples to assess the efficiency of the initial CD4 T cell graft; we know from CFSE proliferation experiments that grafted cells have expanded very little at this early time point. These results are then compared to results obtained from the day 14 harvest. In an example case of rejection, 30 million CD45.1+ bm12 lymphocytes were transferred into Cardif-/- mice which had been backcrossed to C57BL/6 mice for 12 generations. At day 5, all mice displayed equivalent grafting (2-3% of circulating CD4 T cells), but by day 14, bm12 donor cells were completely eliminated from the genetically modified recipient (Figure 6).

+ Figure 3. Analysis of T follicular helper cell expansion in the bm12 model of SLE. CD45.1 bm12 lymphocytes were transferred into C57BL/6 recipients and spleens were analyzed 14 days later. (A) Representative gating strategy showing “lymphocytes” (first panel), “single cells” (second panel), “live cells” (third panel), and “CD4 T cells” (fourth panel). (B) Donor cells are distinguished from recipient CD4 T cells by CD45.1 and CD45.2 staining and analyzed for expression of PD-1 and CXCR5. (C) Donor cells adopt Tfh phenotype, as indicated by the upregulation of several proteins commonly associated with Tfh. (D) Typical results showing the expansion of donor-derived Tfh (defined as CD4+CD45.1+PD-1+CXCR5+ live cells) at days 3, 7, and 14 post transfer. Results are depicted as mean ±SEM, where n = 5, 4, 3, and 6, respectively. Please click here to view a larger version of this figure.

Figure 4. PD-1 and CXCR5 are upregulated on dividing cells. Bm12 cells were labeled with CFSE prior to injection into C57BL/6 recipients. Representative flow plots are shown for donor CD4 T cells at 3, 7, and 14 days after injection. Please click here to view a larger version of this figure.

Figure 5. Expansion of splenic plasma cells and GC B cells. (A) Representative flow plots from naïve mouse spleens, or those from mice 14 days after CD45.1+ bm12 transfer. Plasma cells are defined as CD138+CD19low live cells (top panels). GC B cells are a subset of CD19+ B cells, which express GL-7 and Fas (bottom panels). (B) Quantitave data showing the accumulation of splenic plasma cells over time. Results are depicted as mean ± SEM, where n = 5, 4, 3, and 6, respectively. Please click here to view a larger version of this figure.

+ Figure 6. Bm12 grafts are rejected by some genetically modified recipient mice. CD45.1 bm12 lymphocytes were transferred into either genetically modified mice (top panels) or C57BL/6 (bottom panels) recipient mice. Mice were bled at 5 days post injection and assessed for graft efficiency. Splenocytes from the same mice were analyzed 14 days later. Please click here to view a larger version of this figure.

Primer Name Sequence (5' - 3') Annealing Temperature Bm12F CGTGGTCCCCGCTGTCCCCC *65 °C Bm12R GGGCAGAGGGCAGAGGTGAG

Segment Number of cycles Temperature Duration 1 1 95 °C 2 min. 2 40 95 °C 15 sec. *65 − 0.5 °C/step 15 sec. 72 °C 45 sec. 3 1 72 °C 10 min.

Table 1: Primers and thermocycling conditions for bm12 genotyping. Optimal thermocycling conditions will depend upon the exact reagents and instruments used. These conditions have been optimized for a thermocycler capable of changing annealing temperature at every step, though the protocol may also work using a static annealing temperature.

Table 2: Antibody panels for splenic Tfh, GC B and plasma cell identification by flow cytometry. Presented are panels we have used successfully for assessing graft efficiency at day 3 (left) and the analysis of T and B cells at day 14 after bm12 cell injection (middle). These have been optimized for an LSRII with 5 lasers (355, 405, 488, 561, and 640 nm). Recommended filter sets for each fluorochrome are listed (right), though these may not be the best option for every machine. Depending upon what laser, PMT, and filter set combinations are available, separating the T and B cell analysis panel into multiple panels may be necessary.

Discussion

The bm12 inducible model is a relatively easy and efficient way to study the cellular and molecular processes of SLE. Chronic activation of adoptively transferred CD4 T cells directed against self antigens leads to the accumulation of Tfh, GC B cells, and plasma cells which can be measured by flow cytometry, as described here. Future studies using this model can quickly and easily interrogate the role of candidate genes and novel therapies in the autoimmune germinal center processes which resemble those occurring in patients with SLE, and ultimately govern the pathological accumulation of autoantibodies. Furthermore, the flow cytometric analysis described here can be used to study additional mouse models that involve the development of immunoglobulins including, but not limited to autoimmunity, infection, and allergy.

Like all animal models of human disease, this model also has its limitations. Given the speed with which disease develops and its magnitude, not all genes involved in the development of SLE are likely to be necessary for pathogenicity in this model. Additionally, care must be taken to rule out graft rejection when data suggest minimal expansion of Tfh in genetically modified recipients. Congenic markers should be used to confirm the presence of donor cells at harvest especially since recipient cells can also differentiate into Tfh (Figure 3B), which could otherwise mask the absence of donor cells. Using congenic markers, we observed complete elimination of donor cells that evidently harbored rejection antigens by + + + a b day 14 (Figure 6). We have successfully used CD45.1 bm12 and CD45.2 bm12 mice as donors, and CD45.1 BoyJ (B6.SJL-Ptprc Pepc / + + BoyJ) and CD45.2 C57BL/6 mice as recipients (Figures 3, 6, 7, and unpublished data). However, wild type congenic CD90.1 cells from the B6.PL-Thy1a/CyJ mouse strain do not graft well, nor do CD90.2+ bm12 cells graft well in a CD90.1+ recipient (unpublished data), a phenomenon that is evidently not unique to this model26.

Either C57BL/6 or bm12 mice can serve as the donor or the recipient, as initially reported by Morris et al.9 However, in our lab we find the transfer of bm12 cells into B6 mice produces more consistent expansion of T cell and B cell populations at day 14. Furthermore, donor and recipient mice from different groups should be gender- and age-matched. Although experiments reported in the first description of the bm12 model found no significant difference in any disease parameter between male→male and female→female transfers9, male→female transfers are not advised, as male antigen (H-Y) expressed by transferred CD4 T cells may induce graft rejection in female recipients27.

When choosing antibodies and fluorochromes for congenic markers, it should be noted that donor cells become positive for the recipient congenic marker to varying degrees, such that a CD45.2− gate would not constitute the entire CD45.1+ graft. The phenomenon is clearly + + + illustrated in a comparison of CD45.2 expression by CD45.1 naïve, CD45.1 donor, and CD45.2 recipient CD4 T cells (Figure 7). Notably, donor cells also seem to upregulate expression of their own congenic marker, compared to naïve controls (Figure 7). Similar results are also seen with CD45.2+ bm12 transfer into CD45.1+ BoyJ mice (data not shown). Presumably, acquisition of recipient CD45 results from trogocytosis28 by activated CD4 T cells following repeated interactions with recipient B cells. In fact, the bm12 model may prove a useful tool in studying the process of trogocytosis in vivo.

+ + Figure 7. Donor cells acquire recipient CD45 congenic marker. CD45.1 bm12 lymphocytes were transferred into CD45.2 C57BL/6 recipients. Donor, recipient, and naïve (CD45.1+) CD4 T cells are assessed for CD45.1 and CD45.2 expression 14 days after transfer. Please click here to view a larger version of this figure.

It has been shown that the transfer of purified bm12 CD4 T cells into C57BL/7 mice is sufficient to initiate disease29; however, equivalent disease develops when whole lymphocytes are transferred, and purification is not necessarily required to study disease dependence upon T cell-intrinsic gene expression. Eisenberg and colleagues, clearly demonstrated that the antibody-producing cell in the bm12 model is almost exclusively of recipient origin30. Furthermore, the requirement for recipient CD4 T cells10 is limited to the ‘nurturing’ of B cells during their development, which can be off-set by the addition of exogenous IL-431, although our data indicate that recipient T cells may participate somewhat in the germinal center response, as some of them do develop a Tfh phenotype (Figure 3B, bottom right).

One critical decision that must be made for every bm12 experiment is when to harvest tissues for analyses. Of course the decision depends upon exactly what factors are important to the current study, which may vary. The experiments described here take up to 14 days, as they focus on the initial development of Tfh cells and plasma cells; however, since this model is a chronic GVHD model of SLE, disease can be monitored much longer. In fact, certain clinical features of SLE, including glomerulonephritis, develop later. Proteinuria has been detected as early as 2 weeks post-injection, but reaches peak levels at 4-8 weeks post-injection10,31. Additionally, the flow cytometric analyses described here have been optimized for experiments lasting 2 weeks. We find a considerable number of GC B cells and plasma cells at this time point; although, given additional time, a large percentage of ANA-secreting plasma cells may reside in the bone marrow32. Moreover, the plasma cells identified by this flow staining panel likely also include plasmablasts—in order to distinguish between these two cell types, additional antibodies would be required. Tfh expansion presumably reaches a peak at some point after the 14-day window on which we have focused. However, to our knowledge, no studies have reported bm12 donor cell number beyond 2 weeks, or used congenic markers to track adoptively transferred cells.

Disclosures

The authors have nothing to disclose.

Acknowledgements

This work was supported in part by the Lupus Research Institute, NCI grant CA138617, NIDDK grant DK090978, Charlotte Schmidlapp Award (to E.M.J.), and the Albert J. Ryan Fellowship (to J.K.). We are grateful for the support and instrumentation provided by the Research Flow Cytometry Core in the Division of Rheumatology at Cincinnati Children’s Hospital Medical Center, supported in part by NIH AR-47363, NIH DK78392 and NIH DK90971.

References

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STING-Mediated DNA Sensing Promotes Antitumor and Autoimmune Responses to Dying Cells

Jared Klarquist,*,1 Cassandra M. Hennies,*,1 Maria A. Lehn,* Rachel A. Reboulet,* Sonia Feau,† and Edith M. Janssen*

Adaptive immune responses to Ags released by dying cells play a critical role in the development of autoimmunity, allograft re- Downloaded from jection, and spontaneous as well as therapy-induced tumor rejection. Although cell death in these situations is considered sterile, various reports have implicated type I IFNs as drivers of the ensuing adaptive immune response to cell-associated Ags. However, the mechanisms that underpin this type I IFN production are poorly defined. In this article, we show that dendritic cells (DCs) can uptake and sense nuclear DNA-associated entities released by dying cells to induce type I IFN. Remarkably, this molecular pathway requires STING, but not TLR or NLR function, and results in the activation of IRF3 in a TBK1-dependent manner. DCs are shown to depend on STING function in vivo to efficiently prime IFN-dependent CD8+ T cell responses to tumor Ags. Furthermore, http://www.jimmunol.org/ loss of STING activity in DCs impairs the generation of follicular Th cells and plasma cells, as well as anti-nuclear Abs, in an inducible model of systemic lupus erythematosus. These findings suggest that the STING pathway could be manipulated to enable the rational design of immunotherapies that enhance or diminish antitumor and autoimmune responses, respectively. The Journal of Immunology, 2014, 193: 6124–6134.

he immune system carefully balances its response to diseases such as rheumatoid arthritis, type I diabetes mellitus, dead and dying cells to maintain homeostasis and prevent Sjo¨gren syndrome, and systemic lupus erythematosus (SLE) (3). the development of autoimmunity. Although uptake and However, type I IFNs were only recently identified as a crucial at Univ of Cincinnati Serials Receiving Acq Dept on February 23, 2015 T + clearance of dying cells is generally considered a tolerogenic mediator in the priming of CD8 T cells to cell-associated Ags in process, the existence of immunogenic cell death has been well cancer and cancer treatments. Mice that lack type I IFN sensing, described (1). Depending on the nature of the cell death, dying either by genetic IFN receptor (IFNAR) deletion or treatment with cells can emit damage-associated molecular patterns (DAMPs) (2) blocking Ab, develop more chemically induced tumors and show that act as danger signals and increase a dying cell’s immunoge- poorer rejection of transplanted immunogenic tumors than wild- nicity. Many of these DAMPs seem to use the sensing and sig- type (WT) mice, highlighting the requirement for type I IFN in naling pathways that are normally associated with the recognition spontaneous tumor rejection (4, 5). Additional studies showed and elimination of pathogens. Given the importance of immune that the spontaneous induction of tumor-specific CD8+ T cells in responses to cell-associated Ags in autoimmunity, allograft re- tumor-bearing mice was predominantly mediated by type I IFN jection, and tumor rejection, the identification of these DAMPs, sensing in dendritic cells (DCs) (6, 7). A similar role for type I their cognate sensors, and their proinflammatory sequelae have IFN was seen in therapy-induced tumor elimination. Burnette become topics of intense research. et al. (8) and Kang et al. (9) showed increased intratumoral pro- Ample studies have implicated type I IFNs in the development or duction of type I IFN upon ablative radiotherapy or chemotherapy. progression of immune responses to self-Ags in autoimmune The ablative effect of the therapy was associated with enhanced (cross)priming capacity of tumor-infiltrating DCs and could be abolished by eliminating IFNAR from the hematopoietic com- *Division of Immunobiology, Cincinnati Children’s Hospital Medical Center, Uni- partment. Our previous work, using tumor cell therapy in vacci- versity of Cincinnati College of Medicine, Cincinnati, OH 45229; and †Division of Developmental Immunology, La Jolla Institute for Allergy and Immunology, La Jolla, nation and therapeutic settings, showed a comparable dependency CA 92037 of type I IFN in the induction of protective antitumor CD8+ T cell 1J.K. and C.M.H. contributed equally to this article. responses (10–12). Received for publication July 23, 2014. Accepted for publication October 13, 2014. Although the general immunostimulatory effects of type I IFN This work was supported by the National Institutes of Health via National Cancer on DCs are well studied, little is known on the cellular source of Institute Grant CA138617 (to E.M.J.) and National Institute of Diabetes and Diges- type I IFN, the type I IFN–inducing ligand, and the receptor– tive and Kidney Diseases Grant DK090978 (to J.K. and E.M.J.) and a Charlotte Schmidlapp Award (to E.M.J.). The funders had no role in study design, data col- signaling pathways involved in its induction upon the sensing and lection and analysis, decision to publish, or preparation of the manuscript. clearance of dying cells. Our previous work indicated that DCs Address correspondence and reprint requests to Dr. Edith Janssen, Cincinnati Chil- can produce type I IFN upon phagocytosis of dying cells (10–12). dren’s Hospital Research Foundation, University of Cincinnati College of Medicine, Importantly, DCs from MyD882/2/TRIFlps/lps double-deficient Immunobiology, S5.419, 240 Sabin Way, Cincinnati, OH 45229. E-mail address: [email protected] mice showed normal type I IFN production upon phagocytosis + The online version of this article contains supplemental material. of dying cells, and type I IFN–dependent CD8 T cell priming 2/2 Abbreviations used in this article: BM, bone marrow; cGAMP, cyclic-GMP-AMP; to tumor cell vaccines was comparable in WT and MyD88 / lps/lps cGAS, cGAMP synthase; DAMP, damage-associated molecular pattern; DC, den- TRIF mice, indicating that the type I IFN induction requires dritic cell; DT, diphtheria toxin; IFNAR, IFN receptor; SLE, systemic lupus eryth- an unidentified TLR-independent sensing pathway (11). ematosus; Tfh, follicular Th cell; VT, CellTrace Violet; WT, wild-type. Using various murine cancer and tumor cell vaccination models Copyright Ó 2014 by The American Association of Immunologists, Inc. 0022-1767/14/$16.00 and in vitro approaches, we show that the type I IFN production www.jimmunol.org/cgi/doi/10.4049/jimmunol.1401869 275 The Journal of Immunology 6125 upon sensing of dying cells is not only TLR independent, but also In vitro and ex vivo type I IFN analyses were performed by quantitative RLR independent, and requires STING-IRF3–mediated sensing of real-time PCR using SYBR Green and primers for b-actin (forward, 59- apoptotic cell–derived nuclear DNA structures by DCs. The en- TTGCTGACAGGATGCAGAAG-39; reverse, 59-GTACTTGCGCTCAG- GAGGAG-39) and pan IFN-a (forward, 59-TCTGATGCAGCAGGTGGG- suing type I IFN production enhances DC functionality in an 39; reverse 59-AGGGCTCTCCAGACTTCTGCTCTG-39). Samples were autocrine manner, resulting in the increased clonal expansion, treated with DNAse to eliminate genomic DNA contaminations. Gene ex- polyfunctionality, and memory formation of tumor-specific CD8+ pression was analyzed using the relative standard curve method and was b T cells. Importantly, the role of the STING/IRF3/IFNAR nexus normalized to Gapdh and -actin expression. + For phagocytosis studies, DCs were incubated with CellTrace Violet was not limited to CD8 T cell priming or tumor models; elimi- (VT)–labeled irradiated splenocytes (Molecular Probes). After 3 and 16 h, nation of STING or IFNAR significantly impacted the develop- DCs were stained with Abs to CD11c, CD11b, CD8a, nuclear dye Draq5, ment of CD4+ follicular T h cells (Tfh), plasma cells, and anti- and fixable live/dead staining, and analyzed by ImageStream (Amnis, nuclear Abs in an inducible model of SLE. Collectively, our Seattle, WA). At least 10,000 live events were acquired, and the number results demonstrate that STING/IRF3 sensing of nuclear DNA- and size of phagocytosed particles were determined using the spot counting and spot size features after tight masking on the bright-field image to ex- Downloaded from derived structures by DCs broadly drives the priming of adap- clude membrane-associated extracellular particles for each condition as tive immune responses to dying cells. shown before (12, 21). To determine T cell activating capacity, we incubated DCs with irradiated 2 2 Materials and Methods OVA-Kb / cells for 4 h, after which CFSE-labeled purified OT-1-CD45.1 CD8+ T cells were added as described previously (11). OT-1 cell prolif- Mice, cells lines, and peptides eration and survival were determined after 70 h by analysis of CFSE dilution together with staining for CD8a,Va2, CD45.1, and 7-AAD.

Mice were maintained under specific pathogen-free conditions in accor- http://www.jimmunol.org/ dance with guidelines by the Association for Assessment and Accreditation of Laboratory Animal Care International. C57BL/6J, B6.PL-Thy1a/CyJ DC signaling studies a (B6/CD90.1), B6.SJL.Ptpcr (B6/CD45.1), CD11c-DTR, and B6(C)-H2- Immune coprecipitations. Purified DCs were incubated with irradiated Ab1bm12/KhEgJ mice were purchased from The Jackson Laboratory IRF3- or STING-deficient splenocytes. At different time points, DCs were 2/2 (Bar Harbor, ME) and H2-Kb mice from Harlan (Indianapolis, IN). sorted, lysed, precipitated using agarose-bound Abs to STING (3337; Cell 2/2 2/2 lps/lps 2/2 IFNAR , MyD88 /TRIF , CD11c-DTR-IFNAR , and Act- Signaling) or IRF3 (D83B9; Cell Signaling), and probed for p-IRF3 (4D4G; b2/2 2/2 2/2 mOVA/H2-K mice were bred in our facility. IRF3 and IRF7 Cell Signaling), TBK-1 (72B587; Novus Biologicals), p-TBK1 (D52C2; mice were a gift from Dr. K. Fitzgerald (University of Massachusetts Cell Signaling), STAT6 (9362; Cell Signaling), and IPS1 (77275; Novus 2/2 Medical School, Worcester, MA), STING mice a gift from Dr. R. Vance Biologicals). 2/2 (University of Berkeley, Berkeley, CA), and IPS-1 mice a gift from In parallel, VT–labeled irradiated IRF32/2 splenocytes were cultured Dr. J. Tschopp (University of Lausanne, Lausanne, Switzerland). with WT and STING2/2 DCs, and analyzed by flow cytometry and Amnis at Univ of Cincinnati Serials Receiving Acq Dept on February 23, 2015 Mixed bone marrow (BM) chimeric mice were generated using donors ImageStream upon surface staining with CD11c–Pacific Blue and intra- on different congenic backgrounds in 1:1 ratios. All BM chimeric mice cellular staining with Draq5 and p-IRF3 (anti-pS386, 4D4G) combined were rested for 12 wk before experiments were started. with anti-rabbit IgG Alexa Fluor 488. Correlations between intensity of B16/F10, B16F10-OVA (B16-OVA), EL-4mOVA, MEC.B7.SigOVA, phagocytosed material and p-IRF3 localization in the nucleus were de- Tap-sufficient and -deficient MEFs expressing the human adenovirus type termined using ImageStream by gating on CD11c+ single cells followed by 5 early region 1 (Ad5E1-TAKO, I1.2), and ISRE-L929 IFN reporter cells tight masking on the cells to discriminate internalized from bound particles have been described previously (13–16). Peptides OVA257–264 (SIINFEKL), followed by tight masking on the nucleus to determine colocalization of E1B192–200 (VNIRNCCYI), TRP-2180–188 (SVYDFFVWL), and LCMV the p-IRF3 staining in the nucleus (12). GP33–41 (KAVYNFATC) were obtained from A&A Laboratories (San Diego, CA). In vivo models Cell isolations Immunizations. Mice were injected s.c. or i.p. with irradiated cells (OVA-Kb2/2 splenocytes, 106–107; B16-OVA, B16/F10, and 5E1-TAKO, 1–5 3 106). T cells, B cells, Mph, and DCs were sorted by flow cytometry using markers Alternatively, mice received i.v. 2 3 105 purified DCs that had been pulsed TCRb, CD4, CD8, CD11c, CD11b, CD19, CD45R, and MHC class II as with peptide or exposed to irradiated cells in vitro (10–12, 21). For DC de- . described previously (12). Purity of sorted cells was generally 98% and pletion studies, CD11c-DTR mice and mixed BM chimeric mice were treated . viability was 97% as determined by 7-AAD staining. 24 h before and 24 h after immunization with 4 ng/g diphtheria toxin i.p. Erythrocytes, normoblasts, reticulocytes, and RBCs were generated Tumor models. For the cryoablation model, mice were s.c. injected with 4 3 using a mouse-adapted protocol for the long-term ex vivo erythroid dif- 5 ferentiation culture protocol described by Garderet et al. (17) and Kon- 10 B16-OVA or B16/F10 in PBS. Ten days later, tumors (7–10 mm) were stantinidis et al. (18). In brief, low-density BM cells were cultured in cryoablated using Verruca-Freeze armed with a 6-mm probe (Brymill Cryogenic Systems) (22) for 3 3 25-s cycles. To test long-term tumor erythroblast growth medium (StemPro-34 with 2.6% StemPro-34 supple- 3 4 ment; Invitrogen), 20% BIT 9500 (Stemcell Technologies), 900 ng/ml protection, we challenged the mice with 3 10 B16-OVA or B16/F10 ferrous sulfate, 90 ng/ml ferrous nitrate, 1026 M hydrocortisone, penicillin/ 40 d after the ablation of the primary tumor and monitored for tumor growth. In the EL-4–mOVA challenge model, mice were immunized with streptomycin, L-glutamine, in three subsequent phases. For the prolifera- 2 2 107 irradiated OVA-Kb / splenocytes as described earlier and 40 d later tive phase (days 1–5), cells were expanded with 100 ng/ml stem cell factor, 6 5 ng/ml IL-3, and 2 IU/ml human erythropoietin (Amgen). In the differen- challenged with 10 EL-4–mOVA cells s.c. tiation step (days 6–7), the cells were supplemented with only erythro- SLE model. In the SLE model (23), mice of indicated genetic backgrounds 6 poietin in fibronectin-coated plates. For enucleation (days 8–9), cells were received 3 3 10 B6(C)-H2-Ab1bm12/KhEgJ (bm12) splenocytes i.p. grown without cytokines. Cells were sorted based on size gating and nucle- Splenic B and T cell composition B was analyzed by flow every 2 wk. otide staining using different combinations of Syto-16, Draq5, MitoTracker Serum levels of anti-dsDNA IgG, IgG1, and IgG2a were determined by Red, and MitoTracker Green (Invitrogen). ELISA as previously described (24). DC cytokine production, phagocytosis, and T cell activation T cell analysis Flow cytometry purified DCs were cultured in a 1:3 ratio with irradiated Unless stated differently, analyses were performed 7 d after immunization. cells (1500–3000 rad). Parallel experiments were performed with UV ir- CD8+ T cells were enumerated in spleens and draining lymph nodes using 2 b b radiation (120–240 mJ/cm ), Fas cross-linking (1–20 mg/ml), or etoposide OVA257–264-K tetramers (Beckman Coulter) or E1B192–200-D decamers treatment (6 h, 1–10 mM) (11). When enucleated cells were compared with (Immudex) together with staining for CD8a, CD44, and 7-AAD. In par- nucleated cells, all cells were gamma-irradiated and treated with allel, cytokine production and polyfunctionality was determined directly thrombospondin-1 to upregulate phosphatidylserine on the membrane (19). ex vivo by intracellular cytokine staining after a 5-h stimulation with After 20 h, type I IFN in the supernatant was determined by ISRE-L929 cognate peptide in the presence of brefeldin A as described previously (11, reporter assay that has detection limit of 0.3 U/ml (13). For phagosomal 16). Samples were collected on an LSRII flow cytometer with Diva soft- acidification studies, diphenyleneiodonium (10 mM), ConB (1 nM), or ware (BD Pharmingen), and data were analyzed with FlowJo software chloroquine (50 mM) were added at the start of the culture (12, 20). Par- (Tree Star). In B16/F10 studies, responses to TRP2180–188 were determined allel cultures using CpG and LPS were used as controls. by ELISPOT directly ex vivo. 276 6126 STING PROMOTES IMMUNE RESPONSES TO DYING CELLS

Capacity for secondary expansion in vitro was determined by stimulating + Results the splenocytes or purified CD8 T cells on irradiated MEC.B7.SigOVA Protective antitumor immunity requires type I IFN sensing by (OVA-specific) or I1.2 cells (E1B specific) for 6 d and dividing the absolute number of Ag-specific CD8+ T cells at the beginning of the culture DCs + by the absolute number of Ag-specific CD8 T cells at the end of the We and others recently showed that type I IFN sensing is critical for culture as described previously (16, 25). In vivo secondary expansion was determined by reinjecting the mice with a 10-fold higher number of irra- the induction of protective antitumor responses in various tumor diated cells than used during immunization. Four days after the secondary models in both vaccination and therapeutic settings (6–8, 22). challenge, the frequency of Ag-specific CD8+ T cells was compared with Cryoablation of B16-OVA tumors in WT mice resulted in effective nonchallenged immunized mice (16). + priming of OVA257–264–specific CD8 T cells that provided protective immunity upon subsequent B16-OVA challenge. In con- Statistical analyses 2/2 trast, IFNAR mice failed to induce adequate OVA257–264– Data were analyzed using Prism software (GraphPad Software). Unless specific CD8+ T responses and succumbed upon tumor rechallenge stated otherwise, the data are expressed as means 6 SEM. Survival re- (Fig. 1A, 1B). Similarly, immunization with gamma-irradiated, Downloaded from sponses were analyzed by Kaplan–Meier using a log-rank test. All other b2/2 b2/2 data were evaluated using a two-way ANOVA followed by a Dunnett’s OVA-expressing K splenocytes (OVA-K ) induced a sig- + test. A p value ,0.05 was considered statistically significant. nificantly more robust OVA257–264–specific CD8 T cell response http://www.jimmunol.org/ at Univ of Cincinnati Serials Receiving Acq Dept on February 23, 2015

FIGURE 1. Protective CD8+ T cell induction requires IFNAR on DCs. (A) WT and IFNAR2/2 mice were s.c. injected with B16-OVA tumor cells, and palpable tumors were cryoablated 10 d later. Cryoablated and naive mice were s.c. challenged with B16-OVA 40 d later and survival was monitored (n =8– + b2/2 10/group). (B)OVA257–264–specific CD8 T cell frequency in the spleen 7 d after cryoablation. (C) Mice were immunized with irradiated OVA-K or b2/2 + K splenocytes and 40 d later s.c. challenged with EL-4–mOVA cells s.c. (D) Frequency of splenic OVA257–264–specific CD8 T cells 7 d after im- b munization as determined by intracellular cytokine staining for IFN-g after peptide restimulation and by OVA257–264–K -tetramer staining. (E) Fold ex- + pansion of OVA257–264–specific CD8 T cells upon stimulation with OVA257–264–expressing cells in vitro. Data of representative experiments (out of three to five) are shown (mean 6 SEM, n = 8–10/group, *p , 0.05). 277 The Journal of Immunology 6127

2/2 in WT mice than in IFNAR mice (Fig. 1C, 1D). The OVA257–264– position of hematopoietic cells. Depletion of WT DCs significantly specific CD8+ T cells from WT mice, but not IFNAR2/2 mice, decreased the number and frequency of Ag-specific CD8+ T cells. In underwent expansion upon secondary encounter with Ag in vitro contrast, depletion of IFNAR2/2 DCs had no effect on the number and in vivo, and protected mice from EL-4-mOVA challenge or frequency of Ag-specific CD8+ T cells (Fig. 3D). Similar results in vivo (Fig. 1E, Supplemental Fig. 1A). Importantly, this response were observed when purified WT or IFNAR2/2 DCs were pulsed was not restricted to OVA or the selected pathways of cell death. with irradiated cells and transferred into WT and IFNAR2/2 recip- Similar results were found when the parental line B16/F10 was ients, illustrating the critical role of type I IFN sensing by DCs in used and the response to self-Ag TRP-2 was probed (Supplemental CD8+ T cell priming to cell-associated Ags (Fig. 3E). Fig. 1B, 1C). In addition, direct immunization with gamma- irradiated, UV-irradiated, Fas–cross-linked, or etoposide-treated DCs predominate the type I IFN production elicited by dying cells cells showed significantly decreased CD8+ T cell responses in Besides sensing type I IFNs in the context of CD8+ T cell priming IFNAR2/2 mice, illustrating a central role for type I IFN in CD8+ to dying cells, we reasoned that DCs may also be the main pro- Downloaded from T cell priming to cell-associated Ags in various scenarios of cell ducers of type I IFN, thereby establishing a positive IFN-feedback death (Fig. 2). loop. In vitro studies using purified cell populations indicated that Because nearly all cells express IFNAR, we first used BM chimeras type I IFN was produced by DCs upon incubation with dying to identify which cells required type I IFN sensing in the CD8+ cells, whereas only nominal IFN production was observed in cul- T cell response to dying cells. BM chimeric mice (WT→IFNAR2/2, tures depleted of DCs (Fig. 4A–C) (11, 12). The in vitro data WT→WT, IFNAR2/2→WT, IFNAR2/2→IFNAR2/2) demonstrated were supported by our observation that IFN-a mRNA was readily that type I IFN needed to be sensed by the hematopoietic compart- detectable in the draining lymph nodes of control-treated, but not http://www.jimmunol.org/ ment (Fig. 3A, 3B). Additional studies with WT/IFNAR2/2→WT diphtheria toxin (DT)-treated, CD11c-DTR mice upon s.c. immu- mixed BM chimeric mice indicated that the diminished CD8+ nization with irradiated cells (Fig. 4D). T cell response could not be attributed to the lack of IFNAR on the CD8+ T cells because IFNAR2/2 CD8+ T cells showed only STING/IRF3 pathway drives type I IFN in response to a marginal decrease in clonal expansion (Fig. 3C). Given the im- cell-associated Ag portant role of DCs in cross-presentation of cell-associated Ags, we Induction of type I IFNs is generally associated with innate sensing next examined the role of type I IFN sensing on DCs. Mixed BM of pathogenic danger signals. To identify which innate sensing 2/2

chimeras were generated in which IFNAR recipients received pathways facilitated the type I IFN production, we tested primary at Univ of Cincinnati Serials Receiving Acq Dept on February 23, 2015 a combination of WT-CD11c-DTR and IFNAR2/2/CD45.1 BM or DCs from WT, MyD882/2/Triflps/lps, IRF32/2, IRF72/2, IPS12/2 IFNAR2/2-CD11c-DTR and WT/CD45.1 BM. In this model, the (MAVS/Cardif), and STING2/2-deﬁcient mice for their type I IFN administration of diphtheria toxin yielded animals that contained production upon culture with dying cells. Type I IFN production either WT or IFNAR2/2 DCs with an otherwise comparable com- was similar in WT, MyD882/2/Triflps/lps, IPS12/2, and IRF72/2

FIGURE 2. Impaired CD8+ T cell priming in IFNAR2/2 mice is independent of the method of cell death or cell type. Frequency of splenic Ag-specific CD8+ T cells in WT and IFNAR2/2 mice 7 d after s.c. immunization with actmOVA-Kb2/2 splenocytes (which were gamma irradiated [1500 rad], UV irradiated [120 mJ/cm2], or treated with FAS cross-linking Ab [Jo-1, 20 mg/ml; 4 h, 37˚C]), 5E1- TAKO cells (3000 rad, 240 mJ/cm2, or treated with etoposide [10 mM]), or B16-OVA or B16/F10 cells (3000 rad or 240 mJ/cm2). Ag-specific T cell frequencies were determinedbyintra- cellular cytokine staining upon incubation with OVA257–264,E1B192–200, TRP-2180–188, or control peptide GP33–41 (white bar, control peptide; black bar, specific peptide). Data in all experiments are expressed as mean 6 SEM with n =5.*p , 0.05.

278 6128 STING PROMOTES IMMUNE RESPONSES TO DYING CELLS Downloaded from http://www.jimmunol.org/ at Univ of Cincinnati Serials Receiving Acq Dept on February 23, 2015

FIGURE 3. Selective requirement for type I IFN sensing in the DCs. (A) Bone-marrow chimeric mice (WT→IFNAR2/2,WT→WT, IFNAR2/2→WT, 2/2 2/2 + IFNAR →IFNAR ) were immunized i.p. with irradiated 5E1-TAKO cells and the frequency of E1B192–200–specific CD8 T cells in the spleens was determined 7 d later (white bar, control peptide; black bar, E1B192–200 peptide). (B) The effect on memory formation using these chimeras was determined + by measuring Ag-specific T cell expansion ex vivo. Secondary expansion of E1B192–200–specific CD8 T cells was calculated by dividing the absolute + number of E1B192–200–specific CD8 T cells at the end of a 6 d culture by the absolute number at the start of the culture. (C) WT/CD90.1 mice were irradiated and reconstituted with WT, IFNAR2/2 or a 1:1 ratio of WT(CD45.1):IFNAR2/2(CD45.2) bone-marrow. Mice were i.p. immunized with irra- + CD11cDTR 2/2 diated 5E1-TAKO cells and the frequency of splenic E1B192-200-specific CD8 T cells in each graft was determined 7 d later. (D)WT :IFNAR and WT:IFNAR2/2CD11cDTR mixed bone-marrow chimeras were treated with DT or vehicle and immunized with irradiated 5E1-TAKO cells. The frequency + 2/2 of E1B192–200–specific CD8 T cells in the WT compartment was determined 7 d later. (E) Freshly isolated WT and IFNAR DCs were incubated with 2/2 + irradiated 5E1-TAKO cells, sorted and i.v. injected into WT and IFNAR mice. The frequency of splenic E1B192–200–specific CD8 T cells was determined 7 d later. Data of representative experiments (out of three to five) are shown (mean 6 SEM, n = 5/group, *p , 0.05).

DCs, indicating that the IFN induction was TLR, RIG-I, and Mda5 DCs (Fig. 5A, 5B, and data not shown). Immunoprecipitation and independent. In contrast, significant reductions in type I IFN Western blotting studies indicated rapid IRF3 phosphorylation in production were seen with DCs deficient in STING and the WT DCs and a significant reduction and delay in IRF3 phos- transcription factor IRF3 even though their subset compositions, phorylation in STING2/2 DCs upon exposure to dying cells maturation status, and phagocytic capacity were similar to WT (Fig. 5C, 5D). To determine whether the magnitude of the nuclear

FIGURE 4. Type I IFN production by DCs in vitro and in vivo. Total and subset-depleted splenocytes (A) or puriﬁed cell populations (B) from spleens of naive WT mice were cultured with irradiated OVA-Kb2/2 splenocytes, and type I IFN in the supernatant was determined 20 h later (black bars, irradiated cells; white bars, no cells). Data are expressed as mean 6 SEM with n =4.(C) Splenocytes from CD11c-DTR mice (treated with PBS or DT 24 h prior) were isolated and cultured with irradiated OVA-Kb2/2 splenocytes. Type I IFN in the supernatant was determined 20 h later. (D) CD11c-DTR mice were treated with vehicle or DT and 24 h later s.c. injected with irradiated cells. Type I IFNa mRNA in draining lymph nodes was assessed 6–8 h later. Representative data of one experiment (out of three to four) are shown (mean 6 SEM, n =5,*p , 0.05). 279 The Journal of Immunology 6129

FIGURE 5. Type I IFN induction requires the Downloaded from STING/IRF3 pathway. (A) Type I IFN production by purified DCs from indicated strains upon 20-h culture with irradiated splenocytes. (B) Purified DCs from indicated strains were cultured at 4˚C (white bars) and 37˚C (black bars) with VT-labeled irradiated splenocytes. Uptake of VT materials was determined 6 h later by flow cytometry. Data are http://www.jimmunol.org/ expressed as percentage of DCs that contain VT. Representative data of one experiment (out of three to four) are shown (mean 6 SEM, n = 4). (C and D) p-IRF3 kinetics in WT and STING2/2 DCs upon incubation with irradiated IRF32/2 splenocytes. (E) ImageStream images of p-IRF3 nuclear translocation in WT DCs 8 h after incubation with VT-labeled irradiated IRF32/2 cells. Original magnification 360. (F) ImageStream analysis of nuclear p-IRF3 intensity and intensity of cytosolic at Univ of Cincinnati Serials Receiving Acq Dept on February 23, 2015 phagocytosed material in WT and STING2/2 DCs. Tight masking on the cytosol was done to discriminate between bound and internalized cellular material. At least three experiments were performed with 800–1000 analyzed cells/condition. *p , 0.05

p-IRF3 signal was associated with the frequency and size of responses to various nucleotide structures, including cytosolic phagocytosed particles, we incubated WT and STING2/2 DCs dsDNA, and in some cases dsRNA (26–28). Because dsRNA with VT-labeled, irradiated IRF32/2 splenocytes and analyzed by sensing uses the RIG-I/IPS-1 pathway and IPS12/2 DCs have conventional flow cytometry and imaging cytometry. WT DCs normal type I IFN production, it is likely that the IFN-inducing showed a strong correlation between nuclear p-IRF3 intensity and species released by dying cells is a DNA-based and not an RNA- the amount of phagocytosed material. Although STING2/2 DCs based entity. Indeed, addition of DNases, but not RNases, to WT displayed similar uptake of VT material as WT DCs, they ex- DC/irradiated cell cocultures significantly reduced type I IFN hibited significantly reduced nuclear p-IRF3 staining, consistent production without affecting uptake of cellular material or with their limited IFN production (Fig. 5E, 5F, Supplemental Fig. responses to non-nucleic TLR ligands (Fig. 6A, Supplemental 2A). Using UV irradiation, Fas cross-linking, or etoposide to in- Fig. 2C, 2D). To more rigorously address the role of DNA com- duce cell death yielded similar outcomes, indicating that the plexes in the type I IFN induction, we exploited the process of STING/IRF3 pathway was the dominant IFN-inducing pathway in erythropoiesis where RBC precursors sequentially lose their nu- various forms of sterile cell death (Supplemental Fig. 2B). clei, mitochondria, and ribosomes. Timed RBC cultures were sorted, irradiated and treated with thrombospondin-1 (irr/TSP) to Nuclear DNA-derived structures induce type I IFN production induce comparable phosphatidylserine expression on the mem- by DCs brane and facilitate an “apoptotic phenotype” in the non-nucleated We next set out to determine the ligand upstream of STING that cells (Fig. 6B). ImageStream analysis showed comparable uptake was responsible for inducing type I IFN. STING facilitates immune of the irr/TSP cell subsets by DCs (Fig. 6C). Nucleated irr/TSP 280 6130 STING PROMOTES IMMUNE RESPONSES TO DYING CELLS

FIGURE 6. IFN induction by a nuclear DNA- derived structure. (A) Type I IFN production by WT DCs upon culture with irradiated splenocytes in the presence or absence of RNases and DNases. (B) Cells at different stages of erythropoiesis were sorted based on nucleotide content, irradiated, and incubated with thrombospondin-1. Flow cytometric Downloaded from analysis of nuclear content (Draq5) and Annexin V levels in indicated cell types before (red line) and after (blue line) irradiation and thrombospondin-1 treatment. (C) Puriﬁed WT DCs were cultured with VT-labeled irradiated/TPS1-treated cells. Uptake of VT material was determined 6 h later by ﬂow cytometry. Data are expressed as percentage of http://www.jimmunol.org/ DCs that contain VT. (D) Type I IFN production by WT DCs upon culture with VT-labeled irradiated/ thrombospondin-1–treated cells at different stages of erythropoiesis. Representative data of one experiment (out of three) are shown (mean 6 SEM, n =5,*p , 0.05). at Univ of Cincinnati Serials Receiving Acq Dept on February 23, 2015

erythroblasts readily induced type I IFN in DCs, whereas enu- STING regulates CD4+ T cell and B cell responses in the bm12 cleated reticulocytes and RBCs failed to do so (Fig. 6D). These SLE model data indicate that the IFN-inducing species is nuclear DNA de- To assess whether STING has a broader role in the priming of rived. adaptive immune responses to dying cells, we assessed the induction of CD4+ T cell and B cell responses in the bm12-cGVHD DC-intrinsic STING regulates CD8+ T cell responses to dying model where H-2b B6 hosts develop lupus-like disease upon cells 2 2 transfer of B6.C-H2bm12 CD4+ T cells (29). Both IFNAR / Given the importance of STING-mediated DNA sensing in the type and STING2/2 mice developed considerably less activated CD4+ I IFN production, we next assessed the relative contribution of T cells and Tfh than WT recipients upon transfer of bm12 CD4+ STING in the priming of CD8+ T cells to dying cell-associated T cells (Fig. 8A, 8B). Moreover, both IFNAR2/2 and STING2/2 2 2 2 2 2 2 Ags. WT, MyD88 / /Triflps/lps, IPS / , and IRF7 / mice mice developed considerably less activated B cells, plasma cells, showed comparable CD8+ T cell priming as determined by tet- and pathogenic anti-dsDNA IgG2a Abs than WT recipients ramer staining, intracellular cytokine staining, and capacity for (Fig. 8A, 8C, 8D). Given that the transferred bm12-CD4+ T cells secondary expansion upon immunization with irradiated 5E1- were IFNAR and STING sufficient, these data further support the 2 2 2 2 TAKO cells (Fig. 7A, 7B). In contrast, IFNAR / , IRF3 / , role for Ag-presenting, cell-intrinsic STING and IFNAR in the 2 2 and STING / mice showed significantly reduced CD8+ T cell induction of adaptive immune responses to dying cell-derived 2 2 priming (Fig. 7C, 7D). Moreover, the Ag-specific IFNAR / , Ags. IRF32/2, and STING2/2 CD8+ T cells displayed less cytokine polyfunctionality and impaired capacity for secondary expansion Discussion (Fig. 7E). The defect in CD8+ T priming was fully DC regulated Type I IFNs have been implicated as the upstream events pre- as similar results on CD8+ T cell clonal burst, secondary expan- cipitating autoimmune disease and a prerequisite for effective sion, and cytokine polyfunctionality were seen when purified antitumor radiotherapy. In this study, we identify DC sensing of IFNAR2/2, IRF32/2, and STING2/2 DCs were exposed to irra- cell-derived nuclear DNA entities via the STING/IRF3 pathway as diated cells in vitro and transferred into WT recipients (Fig. 7F– a key component in the early type I IFN response to dying cells. H). The priming defect of the IFNAR2/2,IRF32/2,andSTING2/2 Dying cells can emit a plethora of structurally distinct DAMPs, DCs could not be attributed to a decrease in overall DC func- and it is likely that the molecular pathways involved in the sens- tionality as peptide-pulsed IFNAR2/2, IRF32/2, and STING2/2 ing of these DAMPs are equally diverse. Although many DAMPs DCs induced comparable CD8+ T cell responses as WT DCs upon can contribute to the final adaptive immune response to cell-asso- transfer in WT recipients (Fig. 7I). Together, these data demon- ciated Ags, our data identified type I IFN as the dominant proin- strate the requirement for STING, IRF3, and IFNAR in DCs in the flammatory factor and STING/IRF3 signaling as the principle cross-priming of CD8+ T cells to cell-associated Ags. pathway in the initiation of the immune responses to cell-associated 281 The Journal of Immunology 6131 Downloaded from http://www.jimmunol.org/ at Univ of Cincinnati Serials Receiving Acq Dept on February 23, 2015

FIGURE 7. STING regulates the CD8+ T cells responses to dying cells in vivo. (A) Mice of indicated strains were immunized with irradiated 5E1-TAKO + cells, and the frequency of splenic E1B192–200–specific CD8 T cells was determined 7 d later (white bar, control peptide; black bar, E1B192–200 peptide). + (B) Fold expansion of E1B192-200–specific CD8 T cells from indicated mouse strains upon culture with E1B192–200–expressing feeder cells in vitro. (C) + E1B192–200–specific CD8 T cell frequency in indicated mouse strains 7 d after immunization with irradiated 5E1-TAKO cells. (D) Secondary expansion of + + E1B192–200–specific CD8 T cells in vitro. (E) Ex vivo polyfunctionality of E1B192–200–specific CD8 T cells from (C) as determined by flow cytometry. (F) + Frequency of E1B192–200–specific CD8 T cells in WT mice 7 d after transfer of indicated DCs pulsed with irradiated 5E1-TAKO cells in vitro. (G) + + Secondary expansion of E1B192–200–specific CD8 T cells primed by indicated DCs. (H) Ex vivo polyfunctionality of E1B192–200–specific CD8 T cells primed by indicated DCs. (I) DCs were purified from WT, IFNAR2/2, and STING2/2 mice and exposed to irradiated 5E1-TAKO cells or pulsed with 1 mM 5 + E1B192–200 peptide. DCs were repurified and 2 3 10 were injected into WT recipients. Seven days later, the frequency of splenic E1B192–200–specific CD8 T cells was determined (white bar, control peptide; black bar, E1B192–200 peptide). Representative data of one experiment (out of three to four) are shown (mean 6 SEM, n = 5–7, *p , 0.05).

Ags in our tumor models, as well as the autoimmune responses in recipients in our SLE model. Together with the observation that our SLE model. Although all nucleated cells can sense type I IFN, STING2/2 and IRF32/2 DCs have significantly reduced type I IFN and type I IFN has been shown to directly act on T cells, our data induction upon phagocytosis of dying cells, these data implicate that indicate that the early STING/IRF3-mediated type I IFN pre- the STING/IRF3 pathway is the critical component in the type I dominantly acts on DCs. Transfer of IFNAR2/2 DCs (pulsed with IFN–dependent T cell priming to cell-associated Ags. irradiated cells) into WT recipients resulted in similar deficiencies It has been suggested that different types of death may induce in CD8+ T cell expansion, functionality, and memory formation as different DAMPs. We observed comparable type I IFN induction the direct immunization of IFNAR2/2 mice. Moreover, immuni- and STING/IRF3 engagement in DCs upon phagocytosis of cells zation of WT/IFNAR2/2 mixed BM chimeric mice did not show treated with gamma irradiation, UV irradiation, Fas–cross-linking any significant difference in CD8+ T cell clonal expansion or Ab, or etoposide, suggesting that these different types of cell death polyfunctionality between the WT and IFNAR2/2 grafts. Impor- generated a similar nuclear DNA-derived DAMP (Supplemental tantly, transfer of STING2/2 or IRF32/2 DCs into WT recipients Fig. 2B and data not shown). It is also likely that similar nuclear resulted in similar defects in CD8+ T cell responses as the transfer DNA-associated DAMPs become available in vivo as type I IFN of IFNAR2/2 DCs. Likewise, STING2/2 recipients showed iden- induction, and type I IFN–dependent CD8+ T cell priming was tical reduction in Tfh and plasma cell formation as IFNAR2/2 readily observed in WT and MyD88/Trif-deficient mice, but sig- 282 6132 STING PROMOTES IMMUNE RESPONSES TO DYING CELLS

FIGURE 8. STING regulates +

CD4 T cell and B cell responses in Downloaded from the bm12 SLE model. (A)Flowcy- tometric analysis of Tfh (gated on CD4+ T cells) and plasma cells (total spleen) in spleens of WT, STING2/2, and IFNAR2/2 mice 14 d after i.p. transfer of live bm12 splenocytes. (B)

Number of splenic Tfh and activated http://www.jimmunol.org/ CD4+ T cells in the spleen of indicated mouse strains. (C)Numberof plasma cells and activated B cells in the spleen of indicated mouse strains. Representative data of one experiment (out of three to ﬁve) are shown. (D) Anti-dsDNA IgG1 and IgG2a levels in indicated mouse strains (mean 6 SEM, n =10–22,*p , 0.05). at Univ of Cincinnati Serials Receiving Acq Dept on February 23, 2015

nificantly reduced in STING2/2 and IRF32/2 mice upon admin- The absence of IPS-1 recruitment to STING in WT DCs upon istration of dying cells (gamma, UV, or FAS treated) or upon phagocytosis of cellular materials, as well as the normal type I in vivo tumor cryoablation (11, 22). IFN production and CD8+ T cell responses in IPS12/2 mice, ef- Importantly, the crucial role for type I IFN in the priming of fectively argue against a role for dsRNA sensing in the STING/ protective adaptive antitumor responses is not restricted to sit- IFN phenotype. Our hypothesis that the type I IFN–inducing li- uations where massive tumor cell death occurs, as is the case for gand is a DNA structure is strongly supported by our in vitro data radiotherapy, chemotherapy, and cryoablative tumor therapies. that show significantly reduced type I IFN induction upon addition Recent publications indicate that spontaneous and limited tumor of DNases to the dying cell/DC coculture. Moreover, the use of cell death in tumor-bearing mice also resulted in type I IFN–de- enucleated cells dramatically reduced type I IFN production and pendent protective immune responses. Fuertes et al. (7) and cross-priming by WT DCs in vitro. Importantly, the latter exper- Diamond et al. (6) showed spontaneous antitumor CD8+ Tcell iment also suggested that mitochondrial or ribosomal nucleotide induction and tumor rejection in tumor-bearing mice that was structures had no notable role in the type I IFN production as critically dependent on type I IFN sensing by cross-priming DCs. reticulocytes, enucleated but still containing mitochondria and In this light, it is interesting to note that STING2/2 mice, like ribosomes, failed to induce type I IFN. IFNAR2/2 mice, develop significantly more lung metastases than Recent studies indicate direct binding of cyclic-di-GMP and WT mice upon i.v. injection of low numbers of untreated B16 cyclic-GMP-AMP (cGAMP) to STING but have not provided melanoma cells, illustrating a role for the STING/IFNAR nexus evidence for direct dsDNA–STING interactions (32, 33) sug- in the antitumor response when cell death is limited (data not gesting the involvement of upstream DNA sensors. Over the last shown). few years, several candidate sensors have been identified, in- STING can facilitate innate responses to cytosolic bacterial cluding cGAMP synthase (cGAS), which has been shown to cyclic dinucleotides (cyclic-di-GMP) (30, 31), dsDNA, and in signal through STING via the production of cGAMP (34–37). some cases cytosolic dsRNA (26–28). Our data strongly suggest DExD/H-box protein family member DDX41 and IFI16 (p204) that the main type I IFN–inducing ligand is a nuclear DNA spe- have also been implicated as possible DNA sensors acting through cies. STING-mediated dsRNA sensing requires RNA with 59-tri- STING, but their precise molecular interactions have not been phosphate groups in combination with the IPS-1/RIG-I pathway. fully elucidated (38, 39). Currently, these candidate DNA sensors 283 The Journal of Immunology 6133 are studied in in vitro systems where the DNA is directly delivered ImageStream, and the Research Flow Cytometry Core at Cincinnati Chil- into the cytosol via transfection, transduction, or infection path- dren’s Hospital Medical Center. ways. However, for the phagocytosed DNA-derived structures to be sensed by the STING pathway, either its key components should Disclosures be recruited to the phagosome or the DNA-derived species should The authors have no financial conflicts of interest. escape into the cytosol. Although STING can translocate from the endoplasmic reticulum to the Golgi and autophagosome-like compartments, we and others did not observe STING in phagosomes or References phagolysosomes (data not shown) (40–44). However, phagosomal 1. Green, D. R., T. Ferguson, L. Zitvogel, and G. Kroemer. 2009. Immunogenic and tolerogenic cell death. Nat. Rev. Immunol. 9: 353–363. DNA sensing via STING could still be possible by phagosomal 2. Matzinger, P. 2002. The danger model: a renewed sense of self. Science 296: recruitment of p204 that has reported migratory capacity or cGAS 301–305. that produces the highly mobile secondary messenger cGAMP (34, 3. Theofilopoulos, A. N., R. Baccala, B. Beutler, and D. H. Kono. 2005. 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