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Regulation of CD8+ T cell differentiation by cytokines and T-box transcription factors

Item Type dissertation

Authors Reiser, John Wyatt

Publication Date 2019

Abstract A protective immune response requires naïve CD8+ T cells to differentiate into effector cells, some of which persist as a memory population to protect against future threats. This differentiation program is controlled by a transcriptional network inv...

Keywords CD8+ T cell; effector; Eomes; T-bet; CD8-Positive T-Lymphocytes (M); Immunologic Memory (M)

Download date 05/10/2021 22:28:36

Link to Item http://hdl.handle.net/10713/9610 Curriculum Vitae John W. Reiser [email protected] www.linkedin.com/in/John-Reiser/ Doctor of Philosophy, 2019

EDUCATION

2013-2019 Ph.D. Candidate, Graduate Program in Molecular Medicine University of Maryland, Baltimore - Baltimore, MD

2009-2013 B.S., General Biology Saint Michael’s College – Burlington, VT

2009-2013 Minor, Chemistry, Spanish Saint Michael’s College – Burlington, VT

RESEARCH EXPERIENCE

2013-2017 Graduate Research Assistant, Mentor: Arnob Banerjee, M.D./Ph.D. University of Maryland School of Medicine

2017-2019 Graduate Research Assistant, Mentor: Nevil Singh, Ph.D. University of Maryland School of Medicine

2012 Undergraduate Research Assistant, Mentor: Cliff Weil, Ph.D.

PUBLICATIONS Reiser, J., K. Sadashivaiah, A. Furusawa, A. Banerjee, and N. Singh. 2018. Eomesodermin driven IL-10 production in effector CD8+ T cells promotes a memory phenotype. Cell Immunol. 335: 93-102

Furusawa, A., J. Reiser, K. Sadashivaiah, H. Simpson, and A. Banerjee. 2018. Eomesodermin Increases Survival and IL-2 Responsiveness of Tumor-specific CD8+ T Cells in an Adoptive Transfer Model of Cancer Immunotherapy. J Immunother 41: 53-63

Reiser, J., and A. Banerjee. 2016. Effector, Memory, and Dysfunctional CD8+ T Cell Fates in the Antitumor Immune Response. J Immunol Res 2016: 8941260

SELECTED PRESENTATIONS Molecular Medicine Seminar Series Baltimore, MD University of Maryland School of Medicine September 2018 Graduate Program in Molecular Medicine Oral presentation: CD8+ T cell differentiation is regulated by T-box transcription factors and cytokines

AAI Immunology Conference Austin, TX Poster presentation: Eomesodermin promotes a central memory May 2018 phenotype in CD8+ T cells through the induction of IL-10

1st Annual Molecular Medicine Retreat Baltimore, MD University of Maryland School of Medicine October 2016 Graduate Program in Molecular Medicine + Poster presentation: Eomesodermin expression promotes a CD8 TCM phenotype through the coordinated regulation of CD62L and Bcl6

7th Annual Cancer Biology Retreat Baltimore, MD University of Maryland School of Medicine May 2016 Graduate Program in Molecular Medicine Poster presentation: Eomesodermin-induced IL-10 expression promotes CD8+ T cell trafficking to lymphoid tissues in the antitumor immune response

38th Annual Graduate Research Conference Baltimore, MD University of Maryland School of Medicine May 2016 Graduate Program in Molecular Medicine Poster presentation: Eomesodermin-induced IL-10 expression promotes CD8+ T cell trafficking to lymphoid tissues in the antitumor immune response

Abstract

Title of Dissertation:

Regulation of CD8+ T cell differentiation by cytokines and T-box transcription factors

John W Reiser, Doctor of Philosophy, 2019

Dissertation Directed by:

Nevil Singh, PhD, Assistant Professor Department of Microbiology and Immunology University of Maryland School of Medicine

A protective immune response requires naïve CD8+ T cells to differentiate into effector cells, some of which persist as a memory population to protect against future threats. This differentiation program is controlled by a transcriptional network involving the T-box transcription factors T-bet and Eomesodermin (Eomes). These factors are in turn differentially regulated by cytokines in the local milieu. The precise architecture of this regulatory network in terms of the individual, synergistic and redundant roles of T-bet,

Eomes and critical cytokines is still poorly understood.

Here we sought to clarify these regulatory pathways, using mice deficient in T-bet,

Eomes or both. Our studies identify a key role for Eomes, but not T-bet, in regulating IL-

10 expression by CD8+ T cells early after activation. We further reveal a feedback loop where Eomes and IL-10 cooperatively enhance the expression of the lymph-node homing selectin CD62L. Consistent with the importance of CD62L in promoting memory T cell homing to secondary lymphoid organs (SLOs), we identify a role for CD8+ T cell-intrinsic

IL-10 in promoting the long-term persistence of memory cells in vivo. In contrast, T cells that home away from the SLOs become terminal effector T cells. Using tumor and infectious disease models, we report that these cells experience a second wave of T-bet induction in the tissue, which may contribute to a heightened effector response.

We also define distinct roles for T-bet and Eomes in regulating effector and memory genes, highlighting their redundant role in repressing Tc2 and Tc17 differentiation in CD8+ T cells. Finally, we demonstrate that in the context of a tumor-specific immune response, the absence of both T-box transcription factors severely limits tumor infiltration without significant alteration in early proliferation or effector functions. Taken together, these findings offer new insights into how T-bet, Eomes and IL-10 regulate effector and memory responses in distinct tissues during the immune response. Future developments targeting individual aspects of T-box and cytokine signaling in T cells may help engineer precise outcomes in the context of tumor immunotherapies, vaccination and transplantation.

Regulation of CD8+ T cell differentiation by cytokines and T-box transcription factors

by John W Reiser

Dissertation submitted to the Faculty of the Graduate School of the University of Maryland, Baltimore in partial fulfillment of the requirements for the degree of Doctor of Philosophy 2019 Acknowledgements

I would first like to both of my mentors, Dr. Arnob Banerjee and Dr. Nevil Singh, for their support, guidance and training throughout my graduate studies. Arnob, you took on a young, naïve student and helped me mature into a genuine graduate-level scientist. Nevil, when I was a stray pup looking for a home, you took me in with open arms. You kept me honest and renewed a drive in me that helped me persevere throughout my studies. You were both a major influence on my growth as a scientist and a professional and it has been an absolute pleasure being your graduate student. Thank you both for your guidance and support. Next, I would like to thank my thesis committee members:

Dr. Tonya Webb, Dr. Martin Flajnik, Dr. Achsah Keegan and Dr. Ferenc Livak for the time taken to support my research efforts with critical and constructive feedback. I’d also like to thank all my lab members, both current and past: Aki, Kavi, Haley, Ken-bop, Allie, Courtney and G-man.

Everyone I worked with helped in an enormous way, and I honestly wouldn’t have made it without you guys. I won’t forget our many constructive conversations in the break room. Next, I’d like to thank all of my many friends, I honestly couldn’t have done this without you. Thanks to my

Baltimore/Fed Hill crew, I will never forget all of the memories we made here, I think we made the most of it. Lastly and most importantly, to my family – thank you for your incredible guidance and love. Danny, Becky, Joey and Jake, you guys were always there when I needed something.

Love you guys. To Mom and Dad, you guys were my crutch and source of unwavering support through all of this. None of the things you have done for me, whether little or small, ever went unnoticed or unappreciated. Thank you.

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Table of Contents

Chapter 1: Introduction ...... 1 1.1 The Immune System and Protective Immunity ...... 1 1.2 T Lymphocytes in Adaptive Immunity ...... 3 1.2.1 Naïve T Cells are Generated in the Thymus and Activated in Draining Lymph Nodes 3 1.2.2 Activated CD8+ T Cells Traffic to Inflamed Tissues ...... 5 1.3. CD8+ T Cell Differentiation in Activated Lymph Nodes is Regulated by Transcription Factors and Cytokines ...... 6 1.3.1 Cytokines in Effector CD8+ T Cell Differentiation ...... 8 1.3.2 T-box Transcription Factors in Effector CD8+ T Cell Differentiation ...... 11 1.3.3 Eomes ...... 12 1.3.4 T-bet...... 14 1.3.5 The TCR and Cytokines Cooperate to Induce T-bet and Eomes Expression ...... 15 1.4 A Memory CD8+ Population Persists After Infection ...... 17 1.4.1 Two Competing Models of Memory CD8+ T Cell Differentiation ...... 18 1.4.2 T-bet and Eomes Influence CD8+ T Cell Memory Differentiation ...... 21 1.4.3 Cytokines Influence CD8+ T Cell Memory Differentiation ...... 22 1.5 Outstanding Questions ...... 25 Chapter 2: Materials and Methods ...... 27 Chapter 3: T-bet and Eomes Regulate a Unique Transcriptional Network in CD8+ T Cells ...... 34 3.1 Introduction ...... 34 3.2 Results ...... 37 3.2.1 T-bet and Eomes Differentially Regulate the CD8+ T Cell Gene Signature ...... 37 3.2.2 T-bet and Eomes Regulate Distinct Gene Clusters in Activated CD8+ T Cells ...... 41 3.2.3 T-bet and Eomes Cooperate to Maintain CD8+ Tc1 Specificity ...... 53 3.2.4 Eomes regulates the expression of CD62L and Ly6c in the CD8+ T cell central memory compartment ...... 56 3.2.5 Eomes regulates the early expression of Bcl6 in activated CD8+ T cells ...... 59 3.3 Discussion ...... 62 Chapter 4: Eomes-driven IL-10 Production in Effector CD8+ T Cells Promotes a Memory Phenotype...... 67

4.1 Introduction ...... 67 4.2 Results ...... 70 4.2.1 Eomes inversely regulates Th1/Th2 differentiation ...... 70 4.2.2 Eomes promotes IL-10 expression in activated CD8+ T cells ...... 71 4.2.3 Eomes is sufficient to promote IL-10 expression in activated CD8+ T cells ...... 73 4.2.4 IL-10 induces the expression of CD62L in activated CD8+ T cells ...... 73 4.2.5 The relative roles of Eomes and IL-10 in the regulation of CD62L expression ...... 76 4.2.6 Cell-intrinsic IL-10 is not required to maintain a central-memory CD8+ T cell phenotype...... 77 4.3 Discussion ...... 81 Chapter 5: Effector CTL Undergo a Second Wave of Maturation in Peripheral Tissues ....87 5.1 Introduction ...... 87 5.2 Results ...... 89 5.2.1 T-bet and Eomes are required for optimal CD8+ T cell infiltration into E.G7 tumors . 89 5.2.2 T-bet and Eomes are dispensable for CD8+ T cell proliferation in the draining lymph node ...... 90 5.2.3 CD8+ T cells undergo a second wave of maturation in the tumor marked by T-bet upregulation...... 92 5.2.4 T-bet levels are increased in inflamed peripheral tissues during an infectious challenge ...... 96 5.3 Discussion ...... 97 Chapter 6: Conclusions, Perspectives and Future Directions ...... 103 6.1 Conclusions ...... 103 6.2 Outstanding Questions and Future Directions ...... 105 6.2.1 Are the effects of T-bet and Eomes direct or indirect? ...... 105 6.2.2 Are the novel targets of T-bet and Eomes expressed at the protein level? ...... 106 6.2.3 How are T-bet levels increased in peripheral tissues during the immune response? . 106 6.2.4 What is the functional consequence of increased T-bet in CD8+ TILs?...... 109 References ...... 111

List of Tables

Table 1.1. Surface molecules associated with CD8+ T cell adhesion and trafficking...... 5 Table 1.2. Cytokines secreted during the immune response and their impact on cells of the immune system...... 10 Table 1.3. Master transcription factors of CD8+ T cell effector and memory differentiation...... 12 Table 1.4. Early studies in knockout mice reveal critical roles for T-bet and Eomes in regulating CD8+ T cell differentiation...... 14

List of Figures

Figure 1.1. Differential kinetics of the innate and adaptive immune systems during an acute infection...... 2 Figure 1.2. T cell differentiation in the adaptive immune response...... 7 Figure 1.3. General schematic comparing the size, weight and length of T-bet and Eomes...... 12 Figure 1.4. Cytokines and T-box transcription factors cooperate to regulate CD8+ T cell effector and memory differentiation ...... 17 Figure 3.1. Expression of T-bet and Eomes 5 days after in vitro activation...... 38 Figure 3.2. T-bet and Eomes differentially regulate CD8+ T cell differentiation ...... 40 Figure 3.3. Cluster 1: Genes induced by T-bet and Eomes...... 42 Figure 3.4. Cluster 2: Genes repressed by Eomes...... 43 Figure 3.5. Cluster 3: Genes induced by both T-bet and Eomes……………………...………45 Figure 3.6. Cluster 4: Genes induced by Eomes...... 47 Figure 3.7. Cluster 5: Genes induced by Eomes alone...... 48 Figure 3.8. Cluster 6: Genes repressed by T-bet...... 50 Figure 3.9. Cluster 7: Genes repressed by T-bet and/or Eomes...... 52 Figure 3.10. Schematic demonstrating potential targets of T-bet and Eomes in differentiating CD8+ T cells ...... 53 Figure 3.11. Pathway enrichment analysis revealed differential regulation of distinct pathways between activated WT and DKO CD8+ T cells ...... 55 Figure 3.12. Cells lacking both T-bet and Eomes revert to a phenotype characteristic of Tc17 cells...... 55 Figure 3.13. Eomes regulates the expression of genes involved in memory differentiation...... 57 Figure 3.14. Eomes regulates the expression of CD62L in the CD8+ T cell central memory compartment ...... 58 Figure 3.15. Eomes regulates the expression of Ly6C in the CD8+ T cell central memory compartment ...... 59

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Figure 3.16. Eomes regulates the early expression of Bcl6 in activated CD8+ T cells ... 61 Figure 3.17. Eomes regulates the early expression of genes involved in CD8+ T cells ... 61 Figure 4.1. T-bet and Eomes differentially regulate CD8+ T cell differentiation ...... 71 Figure 4.2. Eomes promotes the expression of IL-10 in activated CD8+ T cells ...... 72 Figure 4.3. IL-10 temporally regulates the expression of CD62L...... 74

Figure 4.4. Exogenous IL-10 does not increase the frequency of TCM in vitro...... 75 Figure 4.5. Eomes does not require IL-10 to induce CD62L expression in CD8+ T cells 77 + Figure 4.6. CD8 TEFF make IL-10 in response to L. major infection ...... 78 Figure 4.7. Schematic design of adoptive transfer experiment...... 80 Figure 4.8. Cell-intrinsic IL-10 improves the persistence of central-memory CD8+ T cells ...... 80 Figure 4.9. WT and IL-10KO cells exhibit similar viability and expansion pre-transfer and post-transfer...... 81 Figure 4.10. Eomes and IL-10 cooperate to regulate the early expression of memory- associated genes in effector CD8+ T cells...... 86 Figure 5.1. T-bet and Eomes are implicated in CD8+ T cell exhaustion...... 88 Figure 5.2. T-bet and Eomes are required for optimal CD8+ T cell infilration into E.G7 tumors ...... 90 Figure 5.3. T-bet and Eomes are not required for CD8+ T cell proliferation in the draining lymph node...... 92 Figure 5.4. T-bet and Eomes regulate cytokine production and the expression of inhibitory receptors in vivo...... 93 Figure 5.5. CD8+ T cells undergo a second wave of maturation in the tumor marked by T- bet upregulation ...... 95 Figure 5.6. Differential expression of transcription factors in CD8+ T cells in the draining lymph node and tumor ...... 96 Figure 5.7. T-bet expression is increased in CD8+ T cells infiltrating peripheral tissues during infection with L. major ...... 97 Figure 6.1. General schematic outline of thesis aims...... 110

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List of Abbreviations

APC Antigen presenting cell

CFSE Carboxyfluorescein succinimidyl ester CTL Cytotoxic T lymphocyte DC Dendritic cell DKO Double knockout EKO Eomes knockout Eomes Eomesodermin FACS Fluorescence-activated cell sorting GFP Green fluorescent protein IFN Interferon MFI Mean fluorescence intensity MHC Major histocompatibility complex MiT MSCV-IRES-Thy1.1 MSCV Murine stem cell virus PBS Phosphate buffered saline PiG Puromycin-IRES-GFP RT-qPCR Reverse transcription quantitative polymerase chain reaction SD Standard deviation SEM Standard error of the mean SLO Secondary lymphoid organ T-bet T-box expressed in T cells

TCM Central-memory T cell TCM T cell media TCR T cell receptor TDLN Tumor-draining lymph node

TEFF Effector T cell

TIL Tumor-infiltrating lymphocyte TKO T-bet knockout

TMEM Memory T cell

TN Naïve T cell

TRM Resident-memory T cell WT Wildtype

Chapter 1: Introduction

1.1 The Immune System and Protective Immunity

Over time, the vertebrate body has evolved several mechanisms to defend itself against invading pathogens. The collection of specialized cells and molecules that have taken on this crucial role comprise the immune system. Unlike other systems in the human body, the cells of the immune system are free floating and migrate throughout the body in search of threats. This system has been divided into two specialized but intertwined branches: the innate and adaptive immune systems (1, 2). The innate immune system is tasked with preventing infection (using anatomical barriers and chemical secretions at common sites of pathogen entry), responding to pathogens immediately following infection (triggering inflammation, engulfing microbes and other relatively non-specific cellular responses) and recognizing aberrant or transformed host cells (tumors). In these ways, the innate immune system is able to continuously eliminate thousands of potential threats while the host remains healthy (2). In cases where a pathogen or tumor is able to evade the innate immune response, the second arm of the immune system steps in. Unlike the innate system, the adaptive immune system is highly specialized in that the individual cells that are part of it respond to threats in a specific manner. The specificity of this response is due to the fact that subsets of adaptive immune cells express somatically rearranged surface receptors, which recognize specific antigens expressed by the pathogen or tumor. This response typically takes days to occur but is eventually able to eliminate threats in a very focused manner. Furthermore, unlike most of the innate system’s output, the adaptive response can establish immunological memory, where a small population of

1 antigen-specific immune cells remains after the initial infection or tumor is cleared. These cells mount a much quicker response to reinfection by the same pathogen (Fig. 1.1) (1-3).

Although both the innate and adaptive immune systems have distinct functions in the host, they cooperate to fight infections and tumors. While several innate immune mechanisms respond immediately to infectious agents, other innate immune cells effectively prime the adaptive immune system for a pathogen- or tumor-specific response. Underlying the adaptive immune response are specialized cells termed T and B lymphocytes (1).

Figure 1.1. Differential kinetics of the innate and adaptive immune systems during an acute infection. Within 1-2 days following viral infection, innate immune cells secrete cytokines that act as tertiary signals in activating cells of the adaptive immune system. Natural killer cells expand rapidly approximately 3 days following infection and target infected cells that lack MHC expression. Clonal expansion of CTLs occurs between 5-10 days post-infection while CD4+ T cell expansion lags slightly behind. As CD4+ T cells mature, they stimulate antibody production by B cells, which serve as the humoral arm of the adaptive immune system. As cytotoxic T lymphocyte (CTL) expansion and antibody titers peak, the virus is actively cleared, and a subset of antigen-specific memory T cells persists.

1.2 T Lymphocytes in Adaptive Immunity

T lymphocytes (or T cells) originate from hematopoietic stem cells that enter the thymus from the bone marrow and differentiate into immature thymocytes. T cells are defined by the expression of a rearranged surface receptor, termed the T cell receptor

(TCR), which is expressed as a heterodimeric protein. In humans, the majority of circulating T cells (~90%) express the αβ TCR, while roughly 1-5% of T cells express the

ɣδ TCR (4, 5). αβ T cells are further characterized by expression of either the CD4 or CD8 co-receptors, which facilitate their interaction with antigen-presenting cells and enhance downstream T cell signaling (6). CD4+ T cells, or helper T cells, function to enhance the activity of other immune cells including CD8+ T cells, B cells, macrophages and dendritic cells. CD8+ T cells, or cytotoxic T cells, mediate direct killing of infected cells and tumor cells. Together CD4+ and CD8+ T cells cooperate to defend the host against a wide array of intracellular and extracellular pathogens (7). For the remainder of this thesis, we will focus on the CD8+ T cell subset.

1.2.1 Naïve T Cells are Generated in the Thymus and Activated in Draining Lymph

Nodes

A key feature of the adaptive immune system (T and B cells) is that the ability to recognize antigen is generated in a random fashion. As T cells develop from hematopoietic stem cells in the thymus, they randomly rearrange their genomic V, D, and J loci to generate functional alpha and beta TCR genes. Rearrangement of the TCR is stochastic and can potentially generate >1015 different receptors. The implication of this dramatic TCR

3 diversity is that within the naïve T cell population, the number of antigen-specific cells is quite low - approximated at ~102 to 105, with estimates varying (8, 9).

+ + Once fully matured in the thymus, naïve CD4 and CD8 T cells (TN) emigrate into the periphery. Naïve T cells traffic throughout the lymphatic system into specialized structures, where they must be optimally positioned to interact with other immune cells to detect antigen and further differentiate. These specialized structures are termed secondary lymphoid organs (SLOs) (10). T cell egress from the thymus, SLOs and migration throughout the body requires the coordinated regulation of chemokines (signaling molecules that attract lymphocytes) and their receptors, as well as several cell adhesion molecules (integrins, cadherins, selectins). Two such molecules involved in T cell trafficking are S1PR1 and CD62L (10). S1PR1 is the receptor for the signaling sphingolipid S1P, which is abundant in the blood and drives naïve T cell egress from the thymus and lymph nodes per the concentration gradient of S1P (11). CD62L (L-selectin) is a cell adhesion molecule expressed by all naïve T cells and serves as a marker for a subset of memory CD8+ T cells. It binds the ligands GlyCAM-1, MadCAM-1 and CD34, which are highly expressed on high endothelial venules (HEVs); specialized structures that allow migration of naïve (and memory) T cells from the blood into lymph nodes (12).

CD62L is critical in initiating T cell ‘rolling’ along epithelial tissues and promoting transendothelial migration into lymph nodes (13, 14). Several additional surface receptors, including CCR7 and LFA-1 reinforce adhesion and entry of naïve T cells into SLOs, where they become activated (Table 1.1) (10).

Table 1.1. Surface molecules associated with CD8+ T cell adhesion and trafficking.

1.2.2 Activated CD8+ T Cells Traffic to Inflamed Tissues

Naïve T cells peruse resident lymph nodes for an activated dendritic cell (DC) presenting cognate antigen via the major histocompatibility complex (MHC). The intact peptide:MHC (pMHC) complex must be recognized by the cell’s TCR in order for activation to occur, which serves as the fundamental step in the generation of a T cell- mediated adaptive immune response (15, 16). Prolonged DC contact in the lymph node

(with adequate co-stimulation and cytokine signals) initiates a phenotypic switch from a naïve to activated T cell that results in the expression of the activation markers CD44 and

CD69, as well as the cytokines IFNɣ and IL-2 (15). Immediately following activation, T cells are retained in lymph tissues to ensure adequate activation and clonal expansion, as suboptimal stimulation periods limit effector responses (16-19). Like in naïve T cells,

S1PR1 mediates egress of activated T cells from lymph tissues but is repressed upon TCR

5 stimulation through inhibition of the transcription factor Klf2 (20, 21). S1PR1 expression is further antagonized by expression of the early activation marker CD69, which binds

S1PR1, resulting in its internalization and degradation (22). Several days post-activation,

T cells re-express S1PR1 and downregulate the lymph node homing molecules CCR7 and

CXCR4 (23, 24). IFNɣ present in activated lymph nodes represses the expression of the

CCR7 ligand CCL21 and promotes lymphocyte egress (25). By this time, activated T cells have upregulated a number of chemokine receptors and integrins, which drive trafficking to inflamed endothelia and migration through peripheral tissues (Table 1.1) (26).

1.3. CD8+ T Cell Differentiation in Activated Lymph Nodes is Regulated by

Transcription Factors and Cytokines

T cell activation in the lymph node induces a number of changes in gene expression resulting in T cells that acquire unique effector functions (TEFF). The process of differentiation from a naïve to effector T cell is critical, as TN are inert and incapable of initiating an immune response in the periphery. Furthermore, due to the diverse nature of infectious agents, distinct T cell subsets and their corresponding effector functions are required to respond appropriately (27, 28). The three-signal model of T cell activation posits that naïve T cells must receive appropriate stimulation through the pMHC:TCR complex (signal 1), co-stimulation through CD28 (signal 2) and cytokine signals (signal

3). Signal 3 is mediated by polarizing cytokines secreted by activated DCs during T cell priming in the lymph node. DCs use various germline-encoded, sensing mechanisms to recognize specific patterns that allow them to distinguish between diverse pathogens and respond accordingly. The resulting cytokines produced by DCs are dependent on the

6 context of the infection (Fig. 1.2). Importantly, the cytokines produced by antigen presenting cells (APCs) during activation influence T cell differentiation. CD4+ T cells differentiate into distinct helper T cell subsets, and each subset is responsible for responding to different pathogens. CD8+ (Tc1) cells differentiate in response to IL-12, IL-

18 and type I interferons and respond to intracellular pathogens such as viruses, as well as tumor cells (Fig. 1.2) (29, 30). More recently, CD8+ Tc2 and Tc17 subsets have been identified and shown to largely parallel their CD4+ T helper cell counterparts in phenotype and function (31-33). Tc2 cells differentiate in response to IL-4 and secrete IL-5 and IL-

13, and express GATA-3 (32, 34). Tc17 cells are induced by IL-6 or IL-21 plus TGFβ, and express RORɣt (33, 35, 36). These CD8+ T cell subsets have been identified in several inflammatory conditions including viral infection, diabetes and cancer, but their contributions to these conditions has largely been correlated with poor outcomes (31).

These subsets will be discussed further in Chapter 3.

Figure 1.2. T cell differentiation in the adaptive immune response. Dendritic cells become activated following infection with a diverse array of pathogens, including viruses, bacteria and parasites. Depending on the nature

7 of the infection, dendritic cells secrete polarizing cytokines that influence T cell subset differentiation. Each T cell subset expresses discrete master transcription factors, cytokines and has a distinct role in the adaptive immune system.

1.3.1 Cytokines in Effector CD8+ T Cell Differentiation

Several in vitro and in vivo studies have demonstrated that the inflammatory cytokines IL-12 and type I IFNs promote optimal CD8+ T cell clonal expansion and cytolytic activity. Early in vitro studies from Curtsinger et al. demonstrated that CD8+ T cells expand preferentially in response to antigen, co-stimulation and either IL-12 or type

I IFNs (37, 38). Importantly, it was shown that both classes of cytokines signal through

STAT4, which stimulates the expression of granzymes, perforin and Fas ligand (38, 39).

Further studies revealed that type I IFNs and IL-12 cooperate to modify chromatin structure through histone acetylation, inducing a number of effector molecules including IFNɣ, granzyme B and CD25 in CD8+ T cells (40). The sustained expression of CD25 by type I

IFNs and IL-12 enhances sensitivity to IL-2, and promotes cell proliferation at later time points, resulting in the accumulation of effector CD8+ T cells (41). In several in vivo models, antigen-specific CD8+ T cells lacking the IL-12R or IFNAR were shown to inefficiently clear viral infections. This suboptimal response was accompanied by a severe defect in the accumulation of effector CD8+ T cells. The role of type I IFNs and IL-12 in these models was shown to be pathogen-specific. Optimal CD8+ T cell expansion during lymphocytic choriomeningitis (LCMV) infection requires type I IFNs, whereas vesicular stomatitis virus (VSV) and Listeria require both type I IFNs and IL-12 (42-46). Together

IL-12 and type I IFN signals are required to generate sufficient CD8+ T cell clonal expansion and expression of cytotoxic molecules (Fig 1.2).

Similar to IL-12 and type I IFNs, IL-18 serves as a potent stimulator of CD8+ T cell activity. Originally defined as interferon-gamma-inducing-factor, IL-18 was shown to elicit IFNɣ production from NK cells. Further studies demonstrated that IL-18 similarly induces IFNɣ expression in T cells. The addition of exogenous IL-18 expanded CD8+ T cells in culture relative to controls. Similarly, IL-18 promoted increased IFNɣ production and enhanced T cell lysis against a tumor cell line (47). Several studies have demonstrated that IL-12 and IL-18 act synergistically during priming to promote optimal CD8+ T cell responses, as indicated by increased IFNɣ expression and cytotoxic capacity (47-51).

Further studies showed that IL-12 functions to decrease the threshold of IL-18 activation of T cells, possibly through increased IL-18R expression (48, 50).

Apart from type I IFNs, IL-12 and IL-18, the cytokine IL-2 plays a key role in CD8+

T cell priming. Though studies have elucidated a definitive role for IL-2 in sustaining in vitro proliferation (52, 53), its in vivo function is less well understood. Studies thus far have presented contradictory results, with some stating that IL-2 signaling during T cell priming is required for optimal clonal expansion yet others finding that it is dispensable (54).

Adoptive transfer studies in IL-2-/- mice or with CD25-/- CD8+ T cells showed that IL-2 signaling is dispensable for initial proliferation, though the magnitude of the antiviral and antitumor responses was impaired (55-58). Studies using mixed bone marrow chimeras corroborated these findings in several models of viral infection, with CD25-/- CD8+ T cells exhibiting a 2-5-fold decrease in primary expansion compared to wildtype cells (59, 60).

Apart from clonal expansion, several studies have compared the effect of IL-2 signaling on cytolytic activity using ex vivo cytotoxicity assays, with inconsistent results (55, 57, 61,

62). Together, these studies suggest that IL-2 is dispensable for the initial proliferation of

CD8+ T cells but sustains expansion and leads to a greater accumulation of CD8+ T cells in the effector phase of the response.

These above studies suggest that the individual contributions of IL-2, IL-12, IL-18 and type I interferons during priming impacts CD8+ T cell differentiation (Table 1.2).

Similarly, these cytokines cooperate to elicit successful immune responses. IL-12 promotes the expression of both the alpha and beta chains of the IL-2 receptor (46, 63). IL-12 and

IL-18 synergistically stimulate IFNɣ production in CD8+ T cells and IL-12 enhances IL-

18R expression and responsiveness (47, 48, 50). Furthermore, both IL-12 and type I IFNs can regulate the responsiveness of CD8+ T cells to IL-2 in vivo. In turn, IL-2 sustains proliferation of effector T cells and leads to a heightened immune response (41).

Importantly and as discussed below, signaling by these cytokines during CD8+ T cell priming regulates the expression of the lineage-defining transcription factors T-bet and

Eomes. Together with these transcription factors, cytokines encountered in the lymph node during T cell priming influence CD8+ T cell fate decisions.

Table 1.2. Cytokines secreted during the immune response and their impact on cells of the immune system.

1.3.2 T-box Transcription Factors in Effector CD8+ T Cell Differentiation

While the local cytokine milieu dramatically influences effector differentiation,

CD8+ T cells are regulated intrinsically by transcription factors. The two homologous T- box transcription factors T-bet and Eomesodermin, which are encoded by the Tbx21 and

Eomes genes, respectively, cooperate to define the CD8+ T cell transcriptional landscape and subsequent differentiation. T-bet and Eomes are 2 of at least 17 T-box proteins expressed in humans (Fig. 1.3). Of these, T-bet and Eomes are the only T-box proteins expressed in immune cells (64). Expression has been detected in human lymphoid cells, including CD8+ T cells, CD4+ T cells, ɣδ T cells, NKT cells, NK cells and B cells (65).

Several studies have shown that T-bet expression is upregulated in activated dendritic cells, indicating that T-bet and Eomes are expressed in both lymphoid and myeloid lineages (66,

67). The roles of T-bet and Eomes in immune cell function have been best described in

CD8+ T cells. Knockout studies have elucidated their requirement in CD8+ T cell fate decisions (68, 69). Several studies have demonstrated that both T-bet and Eomes induce the expression of key effector molecules including IFNɣ, perforin, granzyme B, CD122, and CXCR3, which are critical in mounting a successful immune response (27, 68, 70, 71).

Together, T-bet and Eomes regulate the gene expression signature of CD8+ T cells and the balance between the two ultimately influences CD8+ T cell fate decisions (Table 1.3) (45,

46, 65, 70, 72, 73).

Figure 1.3. General schematic comparing the size, weight and length of T-bet and Eomes. Exons are labeled as indicated. Percentages represent amino acid similarity between the indicated domains.

Table 1.3. Master transcription factors of CD8+ T cell effector and memory differentiation. The molecules listed in this table have been implicated in CD8+ T cell memory differentiation by several studies. This thesis work focuses on the intricate regulatory network of these transcription factors as they pertain to memory differentiation.

1.3.3 Eomes

Eomes was discovered in the mid 1990’s as a critical gene expressed during mesoderm differentiation in the African clawed toad Xenopus. The central region of Eomes shares significant identity (51%-81%) with 20 previously characterized genes belonging to the T-box domain family of transcription factors, including Brachyury (74). The same group identified a role for Eomes in anterior neural differentiation, suggesting a role for

Eomes in the early development of muscle and brain tissues (75). Germline deletion of

Eomes is embryonic lethal in mice, indicating an absolute requirement for Eomes expression in early mammalian development (76). The highly conserved DNA-binding domain was termed the T-box domain and found to bind the ‘TCACACCT’ consensus sequence (77, 78). Eomes and its homolog T-bet (see below) share 73% amino acid homology in the T-box domain. Homogeneity within the central T-box domain is a hallmark of T-box proteins, with pronounced variation being observed in the N- and C- termini gene sequences (Fig. 1.3) (68).

Eomesodermin expression was first detected in CD8+ T cells following in vitro activation and in antigen-specific CD8+ T cells following LCMV infection (68). Eomes was shown to compensate for T-bet-deficiency in inducing IFNɣ in CD8+ T cells, while similarly inducing the expression of the cytolytic molecules granzyme B and perforin (68).

Though Eomes and T-bet share many overlapping effector functions, studies suggest that

Eomes may have a more dominant role in regulating the expression of perforin, granzyme

B, CXCR3, CXCR4 and CD122 in effector CD8+ T cells, while IFNɣ seems to be regulated redundantly (46, 68-72, 79) (Table 1.4).

Table 1.4. Early studies in knockout mice reveal critical roles for T-bet and Eomes in regulating CD8+ T cell differentiation.

1.3.4 T-bet

A homolog of Eomes, T-box expressed in T cells (T-bet) was discovered in 2000 by Laurie Glimcher’s group as a CD4+ Th1-specific transcription factor that promotes

IFNɣ expression. Furthermore, they showed that T-bet is regulated by TCR signaling and represses Th2 differentiation (79). Subsequent studies demonstrated that T-bet represses

Th2 and Th17 phenotypes through indirect inhibition of GATA3 and RORɣt activity, respectively (80-82). These studies demonstrated that T-bet is a master transcription factor of Th1 lineage specification. In addition to CD4+ T cells, Glimcher’s group demonstrated that T-bet is a critical regulator of effector differentiation in CD8+ T cells as well. T-bet- deficient (Tbx21-/-) CD8+ T cells are defective in IFNɣ expression as well as target cell killing. Similarly, Tbx21-/- mice exhibit poor antiviral responses and survival following infection with LCMV compared to Tbx21+/- or wildtype mice (69). Because T-bet and

Eomes largely function redundantly, CD8+ T cell effector activity is maintained with the

14 loss of either one, though secondary responses are dramatically altered. However, CD8+ T cells lacking both T-bet and Eomes differentiate to a Tc17-like phenotype in vivo and fail to express IFNɣ or respond to LCMV infection (83). T-bet, then, in concert with Eomes, functions as a master transcription factor in CD8+ T cells.

1.3.5 The TCR and Cytokines Cooperate to Induce T-bet and Eomes Expression

As previously mentioned, T-bet and Eomes are upregulated following T cell activation, though the expression kinetics differ between the two. Expression of T-bet and

Eomes mRNA has been demonstrated in naïve T cells, but they do not seem to be expressed at the protein level prior to activation (40, 46, 68, 79, 84). Strong antigen-signaling through the T cell receptor (TCR) in concert with the pro-inflammatory cytokines IL-12, IL-18,

IFNɣ and type I IFNs results in the upregulation of T-bet. T-bet expression then promotes the development of an effector T cell phenotype, characterized by the expression of IFNɣ,

TNFα, perforin and granzyme B (27, 45, 46, 66, 85-88). Signaling through the TCR upregulates T-bet expression in an mTOR-dependent manner in vitro (27, 46, 84), and its expression is augmented with the addition of IL-12 (46, 69, 79, 85). The importance of IL-

12 in inducing T-bet expression in vivo has been similarly shown. T-bet expression was decreased in endogenous and TCR-transgenic effector CD8+ T cells following L. monocytogenes infection in IL-12-/- mice (89). A separate study demonstrated that IL-12 and STAT4 cooperate to induce T-bet expression following adenovirus infection in vivo

(90).

Eomes, on the other hand, is induced 3 days after in vitro activation in a RUNX3- dependent manner (46, 84). Its expression is repressed by TCR stimulation through mTOR-

15 mediated inhibition of FOXO1 activity (91). Eomes is induced by high IL-2 and IFNβ in effector CD8+ T cells (46, 92) and appears to be regulated by IL-12 as well, although the evidence is conflicting. One study demonstrated that IL-12 and type I IFNs promote T-bet expression at the expense of Eomes and induce a terminal effector phenotype in vivo (46).

Another study showed that effector CD8+ T cells taken from IL-12KO mice infected with

L. monocytogenes expressed significantly higher levels of Eomes compared to WT controls. Similarly, CD8+ T cell culture in IL-12 resulted in lower Eomes expression whereas culture with IL-4 increased Eomes expression relevant to non-treated controls

(89). On the other hand, a later paper demonstrated that IL-12 and type I IFNs control epigenetic remodeling of both the T-bet and Eomes loci and induce their expression. The authors claim that the increased Eomes expression observed by Takemoto et al. in IL-12-/- mice was due to a compensatory effect from type I IFNs. However, the latter study was performed in vitro and failed to address Eomes expression at the protein level (40).

Taken together, cytokines and T-box transcription factors cooperate in a complex network to influence the effector activity of CD8+ T cells (Fig. 1.4). Yet several questions remain. Besides the reported redundant functions of T-bet and Eomes in effector cells, their divergent expression in effector and memory T cell populations suggests that they have distinct roles in promoting these phenotypes early after activation. Along these lines, how do T-bet and Eomes differ with regards to gene regulation in activated CD8+ T cells?

Moreover, T-bet and Eomes exhibit significant heterogeneity at the protein level, specifically in their N- and C-termini domains (Fig. 1.3). Do these regions contribute to differential gene regulation? If so, how?

Figure 1.4. Cytokines and T-box transcription factors cooperate to regulate CD8+ T cell effector and memory differentiation. Following activation in the lymph node, T cells differentiate according to the local inflammatory milieu. High antigen levels and proinflammatory cytokines (high IL-2, IL-12, IL-18 and type I IFNs) promote terminal differentiation while reduced antigen levels and homeostatic cytokines (low IL-2, IL-7, IL-10 and IL-15) promote memory differentiation.

1.4 A Memory CD8+ Population Persists After Infection

Upon successful clearance of an infection or tumor, antigen-specific CD8+ T cells remain in vast numbers (93). To maintain homeostasis and prevent excessive energy expenditure, these T cells undergo a dynamic contraction process, to where the percentage of antigen-specific CD8+ T cells that remain following contraction is ~5% (94, 95). This subset persists as a memory population and provides protection against future re-challenge with the same pathogen or tumor relapse. Understanding what governs immunological memory is critical for vaccine design and the development of novel immunotherapies (96).

Importantly, insight from this thesis work will provide understanding into how T cell

17 memory can be established via interactions between cytokines and T-box transcription factors.

1.4.1 Two Competing Models of Memory CD8+ T Cell Differentiation

The mechanism by which antigen-specific CD8+ effector T cells become memory cells is unclear. First, it is evident that a single naïve, antigen-specific CD8+ T cell can form both effector and memory subsets, thus ruling out the possibility that some naïve T cells are predetermined to differentially commit to an effector vs memory lineage (97, 98). This left two general models to be tested: 1) effector and memory fates are determined early upon activation of T cells, where the signals encountered early during priming drive commitment to either phenotype (asymmetric cell fate model) and 2) memory cells differentiate in a step-wise fashion from effector cells (linear differentiation model).

The asymmetric cell fate model posits that the early effector population is multi- potent, where each cell can become either an effector or memory cell. Per this model, each individual cell differentiates in response to signals, both soluble and cell bound, in its microenvironment. Thus, the cumulative strength of signals (antigen, co-stimulatory and cytokine) encountered during priming influences the choice between an effector and memory phenotype. One model that may explain this phenomenon is the asymmetric cell division model. This model suggests that a T cell divides into a proximal and a distal daughter cell in relation to the antigen-presenting cell, one that will become an effector cell and one with a propensity towards a memory precursor (99). Studies at the single-cell level have shown that the T cell that receives the immunological synapse is poised to receive stronger TCR and inflammatory signals and thus become an effector cell, while the distal

18 daughter cell receives less of these molecules and displays a memory phenotype. In line with this model, one study showed that proximal daughter cells expressed higher CD8,

CD69, CD43, CD25, CD44, granzyme B and IFNɣ whereas distal daughter cells expressed higher levels of CD62L and IL-7R (99). This group then showed that T-bet was asymmetrically localized in the proximal daughter cells relative to the distal cells (100). A subsequent study corroborated that T-bet segregates towards one pole of the cell during division in P14 CD8+ T cells following re-challenge with LCMV. Eomes however, was not asymmetrically partitioned (101). These studies provide evidence supporting unequal partitioning of proximal components of the immunological synapse during cell division.

The above model is in stark contrast to the linear differentiation model, which suggests that the antigen-specific CD8+ T cells that survive contraction progress linearly from effector to memory cells (45, 102-106). Per this model, the propensity for a cell to become a memory cell is relatively stochastic. Over the long term, memory-like cells outcompete effector cells because they express pro-survival proteins and/or are hyper- responsive to the homeostatic cytokines IL-7 and IL-15 (107-113). This model is supported by several studies demonstrating that memory CD8+ T cells develop from ‘marked’ effector cells in vivo. Two independent groups used granzyme B-driven Cre constructs to indelibly mark effector T cells and revealed that cells expressing granzyme B during acute viral infection expanded similar to control cells upon secondary challenge and protected the host upon reinfection (103, 106). Another study demonstrated that TCR transgenic

CD8+ T cells activated in vitro persisted and exhibited significant cytotoxicity 70 days after transfer into antigen-free mice (105). Similarly, elegant single-cell studies and mathematical models argue that the asymmetric model of differentiation cannot explain the

19 wide disparity between families of T cell clones (114). Moreover, recent studies have shown that memory cells display similar epigenetic signatures to the effector cells from which they derive, while also re-expressing naïve-associated genes, suggesting a process by which effector cells dedifferentiate into long-lived memory cells (115, 116).

Distinguishing between the two models is not trivial. While asymmetric cell division has been eloquently demonstrated in vivo in both mice and humans, the contributions of unequally partitioned molecules (e.g. Irf4, Tcf1) are unknown (117, 118).

Similarly, it is unclear how each lineage (distal/memory and proximal/effector) is maintained during the expansion phase of an immune response and whether different pathogens and inflammatory contexts influence the extent or quality of asymmetric division (104, 119). On the other hand, extensive TCR stimulation and inflammation predispose T cells to differentiate into terminal effector cells that lose the ability to become memory precursors, arguing against a linear differentiation model (45, 120-125). Similarly, several studies have demonstrated that memory cells have significantly longer telomeres and better telomerase activity than effector cells, which argues against an effector to memory differentiation program (12, 121, 126, 127). These findings are consistent, however, with the branch-off point to a memory phenotype happening early on during clonal expansion. A study by Kaech et al. demonstrated that a small subset of effector

CD8+ T cells (5-15%) express high levels of IL-7R at the peak of the immune response.

Importantly, these cells were more resistant to apoptosis than their IL-7Rlo counterparts and preferentially developed into long-term memory cells, which expressed increased

CD62L, CD27, CD122 and Bcl2 relative to IL-7Rlo cells (111). Furthermore, unequal partitioning of other molecules implicated in T cell memory, namely Tcf1 and CD62L (and

IL-7R), has been observed during the first cell division following formation of an immunological synapse (99, 118). Taken together, these data suggest that early in the effector phase of an immune response, CD8+ T cells give rise to memory precursors, which express a subset of markers that favors memory differentiation.

1.4.2 T-bet and Eomes Influence CD8+ T Cell Memory Differentiation

Though the precise model by which CD8+ memory T cells develop is debatable, the balance between T-bet and Eomes levels correlates strongly with effector and memory cell fates. In contrast to their redundant roles in effector differentiation, T-bet and Eomes levels are expressed reciprocally in memory cells. T-bet expression is highest in terminal effector cells and decreases in memory cells (128). On the other hand, less differentiated,

CD8+ central-memory T cells are associated with higher Eomes expression (27, 46, 72, 85,

129). T-bet deficiency enhances the central memory compartment in lieu of terminal effector cells while Eomes deficiency severely reduces the population of central memory

CD8+ T cells (45, 71-73, 128, 130). Both T-bet and Eomes however, are important in maintaining CD8+ memory T cells through the coordinated regulation of CD122 (45, 89).

Together, these studies demonstrate that the ratio of Eomes/T-bet expression is highest in memory T cells, though they are expressed at various levels in both effector and memory cells (65, 131). An outstanding question in the field is whether Eomes has a functional role in memory differentiation or is merely a consequence of reduced TCR signaling and inflammation. Studies have linked Eomes expression with the expression of Tcf1, Bcl6, and Bcl-2 family members but have not conclusively provided a role for Eomes in memory differentiation (27, 72, 132).

1.4.3 Cytokines Influence CD8+ T Cell Memory Differentiation

Given that T-box transcription factors are regulated by cytokines, and the balance between these transcription factors correlates with effector and memory phenotypes, it is not surprising that cytokines similarly contribute to memory differentiation. Along these lines, cytokines have two key roles in maturing CD8+ T cells: 1) promoting differentiation and/or 2) increasing survival. Though inflammation is largely thought to limit memory T cell differentiation, studies have shown that the absence of IL-2, IL-12 and/or type I IFNs in the priming phase leads to significantly impaired memory responses (54, 133-136).

Interestingly, a lack of IL-18 signaling during priming was shown to delay secondary expansion of CD8+ memory T cells as well (137). A separate group showed that memory

CD8+ T cells express IL-18R but require IL-12 to respond to IL-18 stimulation following

LCMV infection (50). On the other hand, studies suggest that pro-inflammatory cytokines like IL-12 and type I IFNs promote terminal effector differentiation in lieu of memory differentiation (45, 89, 138-140). An intriguing question stemming from these studies is whether cytokine signals encountered early in the priming phase contribute to memory differentiation or confer a survival advantage. If so, which cytokines and to what extent do they enhance memory T cell differentiation? How cytokines and T-box proteins cooperate to influence memory differentiation and T cell survival is unclear.

Several members of the common ɣ chain family of cytokines have been implicated in promoting CD8+ T cell memory. These include IL-2, IL-7, IL-15 and IL-21, all of which signal through the common ɣ chain (CD132) subunit of their cognate receptor. While IL-7 plays a major role in T cell development and naïve T cell homeostasis, studies also suggest that high levels of IL-7 similarly support memory precursor CD8+ T cell survival (141-

144). Interestingly, it has been suggested that antigen-specific memory cells are more dependent on IL-7 then memory precursors. Indeed, abrogating IL-7R signaling reduced the long-term survival of antigen-specific memory CD8+ T cells, at least in part through down-regulation of Bcl-2. Importantly, antigen-specific memory cells maintained a basal level of proliferation in response to IL-15, but this did not confer a survival advantage (145,

146). Along these lines, IL-15 has also been shown to be critical in maintaining homeostatic proliferation of memory CD8+ T cells (147-149). IL-15 synergizes with the ɣ chain cytokines IL-7 and IL-21 to promote T cell memory, suggesting that a threshold of

ɣ chain signaling promotes the maintenance of the memory CD8+ T cell compartment (141,

148). Similar to the role for IL-7, but in contrast to the above study, IL-15 was shown to similarly inhibit apoptosis through Bcl-2 induction (149). Importantly, IL-15 signals through IL-2Rβ (CD122), which is upregulated by T-bet and Eomes, suggesting a mechanism by which T-bet and Eomes support both effector and memory CD8+ T cell responses (70). Together these studies suggest that IL-7 promotes cell survival while IL-

15 supports homeostatic proliferation of memory CD8+ T cells. In addition to the well- studied ɣ chain cytokines IL-7 and IL-15, recent data suggests that the strength and duration of IL-2 signaling encountered during priming alters the balance between effector and memory differentiation. CD4+ T cells serve as a major reservoir of IL-2 production during immune responses (150). Along these lines, CD4+ T cell help during CD8+ T cell priming promotes optimal CD8+ T cell memory responses, largely through IL-2 secretion (151-

153). In addition to IL-2, CD4+ T cells support CD8+ T cell memory by licensing DCs through CD40-CD40L interactions (154). Interestingly, one study showed that CD4+ T cell licensing of DCs is required to enable autocrine IL-2 production from CD8+ T cells, which

23 promotes memory expansion (155). These studies suggest that CD4+ T cell help is critical in promoting CD8+ T cell memory, at least partly through IL-2. Two independent groups showed that in addition to diminished primary expansion, antigen-specific CD25 (IL-2Rα)- knockout CD8+ T cells displayed an even greater defect in secondary expansion compared to wildtype controls (59, 60). In contrast, a study by Obar et al. showed that although

CD25-deficiency impaired the number of CD8+ memory T cells, these cells were still able to proliferate robustly following secondary challenge (58). A similar report revealed that strong IL-2 signaling during priming influences the size of the memory CD8+ T cell population, but not secondary expansion (46). Several additional studies claim that the cumulative contribution of IL-2 with other inflammatory signals influences CD8+ T cell fate decisions. These studies suggest that the strength of IL-2 signaling experienced during priming significantly influences memory differentiation (46, 156).

In addition to IL-2, IL-7 and IL-15, recent studies have suggested a role for IL-10 in promoting CD8+ T cell memory differentiation (141, 157-160). Infection with either L. monocytogenes or lymphocytic choriomeningitis virus (LCMV) in IL-10-knockout (KO) mice markedly reduced the function and frequency of memory CD8+ T cells. In the latter

+ + study, CD4 T regulatory cell (TREG)-derived IL-10 was shown to rescue the defect in CD8 memory T cell numbers observed in LCMV-infected IL-10-deficient mice (161, 162). A separate study suggested that CD11c+ dendritic cell (DC)-derived IL-10 enhances IL-15- driven homeostatic proliferation of CD8+ memory T cells (163). Cui et. al. demonstrated that IL-10 signaling acts directly on CD8+ T cells via STAT3 activation to promote memory

CD8+ T cell maturation. Accordingly, STAT3 deficiency markedly reduced levels of the memory-associated markers Eomes, Bcl6 and suppressor of cytokine signaling 3 (SOCS3)

(132). A role for IL-10 in memory differentiation may be consistent with its role as a cytokine that is essential in resolving inflammation (164). As low levels of inflammation support memory CD8+ T cell differentiation (and not terminal effector differentiation) (27),

IL-10 may contribute to memory maturation indirectly by controlling the surrounding inflammatory environment.

Taken together, the above studies suggest that pro-inflammatory cytokines (IL-12,

IL-18, type I IFNs) drive effector differentiation and clonal expansion, which ensures a robust primary response against infection. While continued inflammation pushes cells further towards a terminal effector fate, low level inflammation and homeostatic cytokines

(IL-2, IL-7, IL-10 and IL-15) favor T cell persistence and memory formation (Fig. 1.4).

1.5 Outstanding Questions

Previous studies have provided substantial insight into the roles of T-box transcription factors in driving CD8+ T cell differentiation, yet several questions remain unanswered. In contrast to the overlapping roles of T-bet and Eomes in CD8+ T cell effector function, these findings warrant a more comprehensive understanding of the individual roles of T-bet and Eomes in regulating CD8+ T cell fate decisions. For one, how do T-bet and Eomes differentially regulate the transcriptional program in activated CD8+ T cells?

Additionally, it is well demonstrated that T-bet functions to prevent aberrant differentiation of CD4+ Th1 cells to Th2 and Th17 phenotypes (81, 82). In line with this, subsets of CD8+ Tc2 and Tc17 T cells have been identified in a number of pathologies (31).

Whether T-bet and Eomes function similarly in CD8+ T cell subsets to maintain Tc1 lineage commitment is less clear.

Studies suggest that the balance between T-bet and Eomes dictates the choice between effector and memory differentiation. Indeed, the Eomes/T-bet ratio is highest in memory T cells (46, 72, 85, 129), but it has yet to be demonstrated whether this is causative or is simply a correlative result of reduced TCR stimulation and decreased inflammation.

If and how Eomes functionally contributes to a memory phenotype remains to be determined.

T-bet and Eomes regulate the expression of IFNɣ during immune response (27). It is possible but unclear whether T-box transcription factors regulate other cytokines and if and how these cytokines influence the local immune response and T cell differentiation.

To this point, insight into the regulation of other cytokines by T-bet and Eomes is warranted.

Finally, TCR stimulation in concert with pro-inflammatory cytokines such as IL-2,

IL-12, IL-18, IFNɣ and TNFα alters the ratio of T-box expression and promotes effector differentiation during priming (45, 46, 135). However, the relative contribution of the inflammatory milieu to T-box transcription factor expression during an immune response is unclear. How local inflammatory signals (cytokines, antigen, etc.) influence T-bet and

Eomes expression levels in the periphery is unknown.

Chapter 2: Materials and Methods

Mice. Mice were bred, housed and utilized in accordance with University of Maryland

School of Medicine Institutional Animal Care and Use Committee Guidelines. C57BL/6,

OT-1, IL-10KO and IL-12p40KO mice were purchased from The Jackson Laboratory.

Tbx21−/− (TKO) mice and Eomesfl/flCD4–Cre (EKO) mice were originally obtained from

S. Reiner (University of Pennsylvania, Philadelphia, Pennsylvania) and developed as previously described (83). Tbx21−/−mice and CD4-Cre Eomesfl/fl mice were crossed to obtain Tbx21−/− CD4-Cre Eomesfl/fl (double KO) mice. OT-1 transgenic mice were used to

+ harvest CD8 T cells that recognize the OVA257-264 antigen presented in the context of murine H-2Kb (MHC I). OT-1 mice were crossed with WT and DKO mice to obtain WT and DKO mice expressing the OT-1 transgene. Mice were then backcrossed to homozygosity at a congenic locus. In order to control for intra-group variance during experiments, we housed mice under SPF conditions on the same rack. Although different strains were housed in separate cages, they were age and sex matched and subjected to similar husbandry and veterinary care. Mice were weaned at least one month before use.

CD8+ T cell activation and in vitro culture. Single cell suspensions were prepared from the spleen, inguinal lymph nodes and axillary lymph nodes of C57BL/6 donor mice. CD8+

T cells were magnetically isolated by negative selection (EasySep Mouse CD8+ T Cell

Isolation Kit, STEMCELL Technologies, Vancouver, Canada or Dynabeads Magentic

Separation Technology, Thermo Fisher Scientific, Waltham, MA). Isolated CD8+ T cells

27 were activated in 24-well culture plates (2-3 x 106/well) with immobilized αCD3 (1 µg/ml) and αCD28 (1 µg/ml) antibodies and cultured in complete T cell media (IMDM + 10%

FBS + 1% Penicillin/Streptomycin + 2mM β-mercaptoethanol) supplemented with 10

U/mL of IL-2 (herein referred to as Tc0 conditions). Cells were split 1:2 every two days and supplemented with fresh T cell media and IL-2. In some experiments, cells were cultured similarly with the addition of IL-10 (20 ng/mL), as indicated.

Microarray and pathway analysis. Single cell suspensions were prepared from spleens of WT, TKO, EKO and DKO mice. CD8+ T cells were isolated via magnetic separation, as above. Cells were cultured as indicated for 5 days. On day 5, cells lysates were prepared, and RNA was harvested per the Qiagen RNeasy protocol (Qiagen, Hilden, Germany). RNA concentration and purity were analyzed via spectrophotometric analysis and submitted to

Affymetrix for microarray analysis. Gene expression was analyzed using BRB-ArrayTools developed by Dr. Richard Simon and the BRB-ArrayTools Development Team. Pathway analysis was conducted using the Ingenuity Pathway Analysis platform (Qiagen) and the

DAVID Bioinformatics platform.

RT-qPCR. Total RNA was prepared from WT, TKO, EKO and DKO CD8+ T cells (as above), and reverse transcribed into cDNA (SuperScript First-Strand Synthesis, Thermo

Fisher Scientific, Waltham, MA). TaqMan probes for Eomes, IL-10, IL-21, Tcf1 and

S1PR1 were purchased from Thermo Fisher Scientific. Primers for Bcl6, CD62L, Ly6C and IL-10Rα were designed using Primer3 software. Bcl6:

CCTGAGGGAAGGCAATATCA (forward), CGGCTGTTCAGGAACTCTTC (reverse);

CD62L: ACCCACTCTCTTGGAGCTGA (forward), CAGGTTGGGCAAGTTAAGGA

(reverse); Ly6C: TGTGCAACCACTCTTTCCTG (forward),

ATGCCTCTAGGGCCAAGAAT (reverse); IL-10Rα: TCTCCAGGGCAGCCTAAGTA

(forward), CTGCAGGTGTACCCCAAGTT (reverse). Β-actin or GAPDH was amplified as an internal control. Quantitative PCR was performed in a total reaction volume of 20µl in 96-well reaction plates using TaqMan or SYBR Green-based detection (Applied

Biosystems). Reactions were conducted at 50°C for 2 min, 95°C for 10 min, and then 40 cycles of 95°C for 15 s and 60°C for 1 min. Plates were run using the 7900HT Fast Real-

Time PCR system (Applied Biosystems), and data processing was performed using SDS v2.1 software (Applied Biosystems). The delta–delta Ct method was used as described by

Perkin-Elmer Applied Biosystems to determine the relative levels of mRNA expression between experimental samples and controls.

Cell staining and flow cytometry. Cells were stained with fluorochrome-labeled antibodies to cell surface molecules for 30 minutes at 4°C prior to fixation and permeabilization (FoxP3/Transcription Factor Staining Buffer Set, eBioscience, San

Diego, CA) and stained with fluorochrome-labeled antibodies to intracellular antigens according to the manufacturer’s instructions. For analysis of cytokine production, cells were re-stimulated with PMA (300 ng/ml) and ionomycin (1 µg/ml) (Sigma-Aldrich, St.

Louis, MO) for 6 hours in the presence of Brefeldin A (10 μg/mL, Life Technologies,

Carlsbad, CA) to inhibit protein secretion. Cells were fixed with 4% PFA/PBS and permeabilized in saponin buffer (1% BSA and 0.1% Saponin in PBS) prior to staining with

29 the indicated fluorochrome-labeled antibodies. Fluorescence-activated cell sorting (FACS) was performed on an Accuri C6 or LSRII (BD Biosciences) flow cytometer. Cells were gated on FSC/SSC to identify the lymphocyte population and subsequently on live/CD8+ cells. FACS analysis was performed using FlowJo software (Tree Star Inc.).

Antibodies. Cells were stained with fluorochrome-labeled antibodies to perforin, granzyme B, CXCR3, Bcl6, Eomes, fixable viability dye (eBiosciences, San Diego, CA),

CD44, CD62L, Ly6C, IL-10 (Biolegend, San Diego, CA), Tcf1 (Cell Signaling

Technology, Danvers, MA), S1PR1 (R&D, Minneapolis, MN), IFNɣ, TCRαβ and CD8

(BD Biosciences, San Jose, CA).

Retroviral constructs. The MSCV-IRES-Thy1.1 retroviral vector (MiT) was a gift from

Dr. Philippa Marrack (Addgene Plasmid #17442) (165). The MSCV-Puro-IRES-GFP

(PiG) was a gift from Dr. Scott Lowe (Addgene plasmid #18751). Eomes cDNA was subcloned into the MiT and PiG backbones to generate the Eomes-MiT and Eomes-PiG constructs, respectively. Empty-vector backbones were used as controls in retroviral transduction experiments, as indicated.

Retroviral transduction. MiT or PiG retroviral genomes were packaged into retrovirus by co-transfecting 293T cells with MiT or PiG vector plasmids and helper plasmids and viral supernatants were harvested at 48 hours. For MiT-RV transductions, CD8+ T cells were transduced two days following T cell activation in complete T cell media in 24-well,

RetroNectin-coated plates (Clontech, Mountain View, CA). Cell culture plates containing cells and virus were centrifuged at 2500 rpm for 2 hours. After centrifugation, viral supernatants were replaced with fresh media with IL-2 and transduced cells were cultured for another three days. Successfully transduced T cells were identified by expression of

Thy1.1. For PiG-RV transductions, CD8+ T cells were transduced as above and selected with puromycin for an additional 3 days (2 µg/ml, Thermo Fisher Scientific, Waltham,

MA). Successfully transduced cells were identified by expression of GFP. The cultures were split 1:2 every 2 days and supplemented with fresh media and IL-2. On day 5, cells were stained with the indicated antibodies and analyzed by flow cytometry.

CFSE Labeling. Single cell suspensions were prepared and enriched as described above.

CFSE labeling was performed as previously described (166). Briefly, 5 x 106 CD8+ T cells were incubated in 1 mL PBS + 5 µM CFSE, vortexed and incubated in the dark at room temperature for 9 minutes. Labeling was stopped with 1 volume of sterile fetal bovine serum (FBS). Cell were spun down and re-suspended in 5 mL of T cell media for 10 minutes.

Adoptive cell transfer. For the WT versus IL-10KO adoptive transfer experiment, single- cell suspensions of C57BL/6 WT (Ly5.1) and IL-10KO (Ly5.2) CD8+ T cells were harvested and activated in vitro by polyclonal stimulation as described. Five days following activation, equal numbers (2 x 106) of T cells from each genotype were injected i.p. into

WT (Ly5.1/2) mice. Cells were harvested from the lymph nodes, spleen, and bone marrow

31 at the indicated times and analyzed by flow cytometry. For tumor experiments, CFSE- labeled, naïve CD8+ OT-1 T cells were re-suspended in PBS and 2 × 106 cells/200 μL of the cell suspension was transferred to each recipient mouse by intraperitoneal (i.p.) injection 1 day prior to injection of E.G7 cells. Mice were euthanized and tissues were harvested 10-12 days post-transfer.

Mouse Lymphoma Model. E.G7 and EL4 cells were purchased from ATCC and cultured as previously described (167). Cells were cultured in complete RPMI 1640 supplemented with 10% FBS, 1% penicillin/streptomycin and 0.05mM 2-mercaptoethanol. G418 (400

μg/ml) (Sigma-Aldrich) was also added to the media for E.G7 for transgene selection. 1 ×

106 E.G7 or EL4 cells in 200 μL phosphate-buffered saline (PBS) were subcutaneously

(s.c.) injected into the right-side flank of 6–12-week-old C57BL/6 recipient mice. The inguinal lymph node adjacent to the tumor was considered the tumor-draining lymph node, and the contralateral inguinal lymph node was used as a control. Mice were euthanized and tissues were harvested 10-16 days following tumor injection.

L. major Infection Model. Leishmania major promastigotes were grown at 25°C in medium 199 supplemented with 20% heat-inactivated fetal calf serum (FCS), 15 mM

HEPES, 0.1 mM adenine (in 50 mM HEPES), 5 μg/ml hemin (in 50% triethanolamine), and 0.6 μg/ml biotin (in 95% ethanol). Infective-stage promastigotes (metacyclics) of L. major were isolated from stationary cultures using peanut lectin agglutinin. Mice were infected in the footpad or ear dermis with 1 x 105 L.major metacyclic promastigotes using

32 a 27-gauge 1/2 needle in a volume of 20 μl. Infection was monitored at 3- or 4-day intervals by measuring the footpad and ear lesion swelling with a caliper. To characterize leukocytes at the infection site, footpad dermal tissue was digested in 1 mL of a 2.5 mg/mL

Collagenase D solution in complete RPMI at 37oC for 2 hours and filtered through a 70

µm filter.

Statistical Analysis. For the microarray analysis, class comparison analysis was conducted between 4 classes (WT, TKO, EKO and DKO genotypes) consisting of 12 samples in total

(3 biological replicates per class). An F-test (two-sample T test) was performed for each gene in the microarray using normalized log-ratio values. A fold-change cut-off value of

1.5 was used with a p-value of <0.01. The significant threshold of univariate test value

(permutation p-value) used was p<0.001. In all other experiments, statistical analyses were performed as indicated using the 2-tailed Student t test. A p-value of less than 0.05 was considered significant. All graphs show average mean values ± S.E.M., unless otherwise indicated.

Chapter 3: T-bet and Eomes Regulate a Unique

Transcriptional Network in CD8+ T Cells

3.1 Introduction

As mentioned in chapter 1, T-bet and Eomes function as master regulators of effector CD8+ T cell differentiation. Together they cooperate to regulate both the transcriptional and epigenetic landscape in activated CD8+ T cells (168). The roles of T- box transcription factors in CD8+ T cell differentiation were first elucidated in the early

2000’s utilizing mouse knockout models. Early studies on the roles of T-bet in CD8+ T cell effector function involved the use of T-bet knockout mice, which were developed by the

Glimcher lab in 2002 (Fig. 1.3). T-bet-/- mice were generated by replacing exon 1 of the wildtype Tbx21 gene with a neomycin resistance gene by homologous recombination.

(169). Pivotal studies using these mice were the first to define a critical role for T-bet as a master transcription factor in CD4+ Th1 cells (67, 69, 169). Steven Reiner’s lab developed a phenotypically identical T-bet-/- mouse in 2005, by targeted deletion of exons 2-6 and similar embryonic stem cell-mediated gene transfer (Fig. 1.3) (70). Studies from this group have provided fundamental insights into the role of T-bet in CD8+ T cell effector and memory differentiation (70, 73, 83, 89). The Reiner group then generated a conditional

Eomes knockout mouse, since germline deficiency of Eomes is embryonic lethal (76). This was achieved by targeting the Eomes locus with a target construct containing the first exon of Eomes flanked by loxP sites. Mice carrying the floxed Eomes allele were crossed to mice that express the Cre recombinase transgene under control of the CD4 promoter. In

34 this model, only cells expressing CD4 (developing thymic αβ T cells) will express Cre and lose Eomes expression (EKO) (83). In the same study, this group crossed mice with homozygous T cell-specific deletion of Eomes (EKO) with germline-deleted Tbx21-/- mice

(TKO), to create mice with combined deficiency for both T-bet and Eomes in the T cell compartment (DKO) (83).

Early studies utilizing these knockout models were seminal in demonstrating the roles of T-box transcription factors in CD8+ T cell differentiation. A number of in vitro and in vivo studies in the past two decades have definitively shown that T-bet and Eomes cooperate to induce the expression of effector molecules including IFNγ, perforin and granzyme B (Table 1.4). Other studies have suggested that the balance between T-box transcription factors influences cell fate decisions, and that both T-bet and Eomes regulate the expression of memory-associated molecules, such as CD122, CXCR3, CXCR4 and

Bcl2 (Table 1.4). Taken together, these essential studies have provided a nexus for how T- bet and Eomes work in CD8+ T cell differentiation. T-bet promotes a terminal effector phenotype characterized by high cytolytic activity and rapid cell proliferation, while Eomes associates with a less differentiated, memory phenotype that persists long-term following infection.

Though pivotal in delineating the roles of T-box transcription factors in CD8+ T cell differentiation, these studies posed several questions. For one, how do T-bet and

Eomes differ with regards to the genes they regulate? Moreover, does Eomes functionally contribute to CD8+ T cell memory differentiation? If so, which genes does Eomes, but not

T-bet, regulate to promote this phenotype? Studies have shown that T-bet and Eomes are expressed at different levels in memory cells, but how the balance between the two controls

35 memory differentiation is unclear (46, 72, 85, 129). Though some molecules implicated in

T cell memory are regulated by T-box transcription factors (Table 1.4) (27, 72), whether

T-box transcription factors directly promote memory differentiation through these genes, or others, is unclear.

In line with data demonstrating that T-bet maintains CD4+ Th1 cell commitment,

CD8+ T cells that are doubly-deficient for T-bet and Eomes (DKO) were shown to acquire a Tc17 phenotype characterized by loss of IFNγ expression and acquired IL-17 expression.

These cells expressed several Tc17-markers including RORγt, IL-17, IL-21, IL-22 and IL-

23R, demonstrating that T-bet and Eomes cooperate to prevent a Tc17 differentiation profile in vivo. DKO cells displayed severely impaired cytolytic activity and failed to reject infection with LCMV (83). This study suggests that T-bet and Eomes may redundantly maintain CD8+ Tc1 lineage specificity and prevent alternate differentiation to Tc2, Tc17 and TREG phenotypes. We sought to determine how T-bet and Eomes cooperate to maintain

Tc1 lineage commitment accordingly.

Here we performed gene expression analysis on wildtype (WT), TKO, EKO and

DKO CD8+ T cells that were activated by αCD3/αCD28 stimulation and cultured in vitro for 5 days. Our data demonstrate that expression of both T-bet and Eomes is required to maintain CD8+ Tc1 commitment and prevent differentiation to Tc2 and Tc17 subsets under non-polarizing conditions. In addition to their cooperative role in regulating differentiation, we show that single-knockout (TKO and EKO) cells display largely distinct gene expression profiles, highlighting non-redundant roles for T-bet and Eomes in early fate decisions. Among these, we demonstrate that Eomes alone (or with T-bet) regulates the expression of genes involved in apoptosis, T cell migration, immune cell recruitment and

36 memory differentiation. Interestingly, many of these molecules are transcription factors while others include costimulatory molecules and inhibitory receptors. Regarding memory differentiation, we found that Eomes regulates the expression of several markers implicated in CD8+ T cell memory. Notably, we show that Eomes regulates CD62L and Ly6c expression specifically in the central-memory compartment. Additionally, we show that

Eomes regulates the expression of the transcriptional repressor Bcl6 early upon CD8+ T cell activation. Together our data suggest that T-bet and Eomes redundantly and differentially contribute to CD8+ T cell fate decisions and lineage commitment.

Importantly, our data suggest that Eomes, but not T-bet, regulates the expression of several genes implicated in T cell memory.

3.2 Results

3.2.1 T-bet and Eomes Differentially Regulate the CD8+ T Cell Gene Signature

In order to determine how T-bet and Eomes individually and collectively function to regulate gene expression in CD8+ T cells following activation, we performed a microarray analysis using RNA harvested from WT, TKO, EKO and DKO cells that were activated in vitro for 5 days, as discussed in the methods. Our protocol for T cell activation was important for analyzing T-bet and Eomes function in T cells since Eomes is not expressed until 3 days after in vitro activation and robustly expressed on day 5 (Fig. 3.1)

(46, 84). Importantly, cells were activated under non-polarizing Tc0 conditions, and therefore culture conditions did not favor differentiation into alternate phenotypes.

Figure 3.1. Expression of T-bet and Eomes 5 days after in vitro activation. CD8+ T cells were isolated from the spleens of WT mice and activated by αCD3/αCD28 stimulation. Cells were cultured in complete T cell media for 5 days under Tc0 conditions and split every 2 days, as described in the methods. On day 5, naïve CD8+ T cells were harvested from littermate controls and stained along with the 5-day cultures for the expression of T-bet and Eomes and analyzed by FACS. Representative histograms are shown with gMFIs indicated.

Twelve samples (3 samples per genotype) comprising 4 classes (WT, TKO, EKO,

DKO) were analyzed using the class comparison tool from BRB ArrayTools (see

Methods). Our analysis revealed significant differential clustering of genes among the 4 genotypes (Fig. 3.2A). Our array results highlighted 429 genes that displayed a significant difference in expression between at least two of the genotypes (>1.5-fold change between any of 2 genotypes, permutation p-value of <0.001) (Fig. 3.2A, 3.2B). Of these genes, the majority (279 or 65%) were differentially regulated only in DKO CD8+ T cells but expressed at similar levels in the other three genotypes. This suggests that most of these target genes require either Eomes or T-bet for regulation (i.e. redundant). 51 genes (11.9%) were regulated by T-bet, being greater than 1.5-fold up or down in both the TKO and DKO genotypes, but not in EKO or control WT cells. This suggests that T-bet, but not Eomes, regulates this subset of genes (Fig. 3.2B). 101 (23.5%) genes were regulated by Eomes, being greater than 1.5-fold up or down in EKO and DKO genotypes, but not in the TKO or control WT cells. This suggests that Eomes, but not T-bet, regulates this subset of genes

(Fig. 3.2B). Noticeably, nearly one-quarter of the genes that met the statistical requirements were regulated by Eomes alone (twice that of T-bet). These genes were differentially regulated (up or down) in the EKO alone or both EKO and DKO cells.

12 genes were differentially regulated only in TKO cells but not WT, EKO or DKO cells, and 57 genes were up- or down-regulated only in EKO cells, but not WT, TKO or

DKO cells. Expression of these genes changes (up or down) when only one transcription factor is present (single KO) but they are expressed at a basal level when both T-bet and

Eomes are expressed (WT) or absent (DKO) (Fig. 3.2B). Genes in these subsets may be antagonistically regulated by T-bet and Eomes. Additionally, T-bet and Eomes may compete to regulate these genes.

Two genes, Ifi204 and Ifitm3, were differentially expressed only in the TKO and

EKO genotypes but expressed at normal levels in WT and DKO cells. Interestingly, both are interferon-inducible genes that have been implicated in dendritic cell biology and particularly in IFNβ signaling and autophagy (170, 171). Three additional genes, IL18r1,

Lum and Fam26f, require both T-bet and Eomes to maintain expression levels relative to

WT cells (Fig, 3.2B). Both IL-18R and Fam26f require T-bet and Eomes for expression whereas T-bet and Eomes cooperate to inhibit Lumican (Lum) expression. Signaling through the IL-18R enhances Tc1 responses in concert with IL-12, specifically through induction of IFNγ expression (47-51). Fam26f is a membrane glycoprotein known to be expressed on subsets of immune cells including NK and T cells. The function of Fam26f is poorly defined but has been suggested to be involved in synapse formation and cell signaling. Interestingly, Fam26f expression was found to be critical to activate NK cells against tumors (172, 173). A role for Lumican in T cell biology has not been defined but

39 its expression on stromal tissues is implicated in tumor development and progression (174).

To confirm that the cells used in our microarray were indeed knockouts, we highlighted T- bet and Eomes expression levels in WT, TKO, EKO and DKO cells per the microarray

(Fig. 3.2C). Together these microarray data suggest that T-bet and Eomes have many overlapping functions in activated CD8+ T cells but maintain divergent roles in effector differentiation. Furthermore, these data suggest that Eomes may have an unappreciated role in directing CD8+ T cell differentiation following activation.

Figure 3.2. T-bet and Eomes differentially regulate CD8+ T cell differentiation. (A) Microarray analysis comparing gene signatures from 5-day-activated CD8+ T cells reveals differential gene clustering in WT, TKO, EKO and DKO cells. (B) Venn diagram displaying redundant or differential gene regulation by T-bet and Eomes in activated TKO, EKO and DKO CD8+ T cells, relevant to WT cells. (C) Expression intensities of T-bet and Eomes between all 4 genotypes, indicating the consistency of the Affymetrix microarray analysis.

3.2.2 T-bet and Eomes Regulate Distinct Gene Clusters in Activated CD8+ T Cells

To further extend the analysis of the microarray from Fig. 3.2, we subdivided the heatmap into 7 distinct clusters based on patterns of expression intensity among the 4 genotypes tested. Gene lists from the subdivided clusters were then subjected to functional annotation analysis (DAVID Bioinformatics Resources) and relevant pathways were identified from the KEGG Pathway Database.

Cluster 1 revealed several genes that were upregulated in activated WT, TKO and

EKO CD8+ T cells but downregulated in DKO cells, suggesting that T-bet and Eomes redundantly promote this subset of genes (Fig. 3.3). We identified 2 modules that were differentially regulated in this cluster, including several T cell-specific transcription factors

(STAT4, T-bet, TOX, FOXP1) and several genes associated with T cell signaling and cancer (KIT, PTEN, CBLB) (Fig. 3.3). The first module suggests that several T cell- specific transcription factors are induced by T-bet and Eomes in activated T cells. STAT4 directly promotes T-bet expression through type I IFN and IL-12 signaling, but a role for

T-box transcription factors in regulating STAT4 has not been documented (27). The transcription factor TOX is critical in positive selection of T cells in the thymus and knockdown decreases T-bet expression in NK cells (175). On the other hand, FOXP1 is known to regulate naïve T cell quiescence, and deletion of this gene promotes an effector phenotype (176). Furthermore, T-bet and Eomes expression levels negatively correlate with FoxP1 levels in human TILs (177). These data reveal that T-bet and Eomes upregulate

FoxP1 levels in activated T cells relative to DKO cells, which may suggest a compensatory feedback loop (Fig. 3.3). Interestingly, several of the genes in this cluster, including TOX and FOXP1, differentially associate with exhausted CD8+ T cells in chronic infection,

41 suggesting a potential role for T-bet and Eomes in T cell exhaustion (see Chapter 5) (178,

179). The second module identified in this cluster revealed that T-bet and Eomes regulate several cell signaling molecules during T cell differentiation. KIT is a receptor tyrosine kinase that is critical in hematopoietic stem cell differentiation and survival. KIT supports the maintenance of HSCs in vivo and its absence significantly reduces the frequency of

HSCs and results in macrocytic anemia in mice (180, 181). Both PTEN and CBLB are negative regulators of T cell signaling, and thus are critical regulators or T cell differentiation, survival and proliferation (182, 183). These 3 genes are upregulated by T- bet and Eomes, suggesting that while promoting effector functions early upon activation,

T-box transcription factors also cooperate to regulate T cell signaling.

Figure 3.3. Cluster 1: Genes induced by T-bet and Eomes.

Cluster 2 of our array revealed genes upregulated in EKO and DKO CD8+ T cells relative to WT and TKO cells, suggesting that Eomes (but not T-bet) functions to repress this gene subset (Fig. 3.4). We identified several molecules associated with T cell signaling and apoptosis as being upregulated in EKO and DKO cells including TNFRSF18,

TNFRSF4, IFNGR2, CD81, ATF3 and SOCS2. TNFRSF4 (or OX40), TNFRSF18 (or

GITR) and CD81 function as critical co-stimulatory molecules expressed on CD8+ T cells

(184-193). IFNGR2 encodes one subunit of the IFNγ receptor and its expression on macrophages and DCs is critical for mounting successful adaptive immune responses.

Though T cells also express the IFNγR, its expression is downregulated upon activation to prevent apoptosis (194-196). Interestingly, the transcription factor Atf3 was shown to be linked to IFNγ expression and apoptosis in Th1 cells (197-199). SOCS2 is a member of the suppressor of cytokine signaling (SOCS) family of proteins, which play critical roles in regulating T cell signaling (200). Together these data suggest that Eomes may function to prevent excessive co-stimulation and proliferation through repression of TNFRSF4,

TNFRSF18, CD81 and SOCS2, while similarly preventing apoptosis through downregulation of Atf3 and IFNGR2.

Figure 3.4. Cluster 2: Genes repressed by Eomes.

Cluster 3 revealed a gene subset that was upregulated in activated WT, TKO and

EKO CD8+ T cells but downregulated in DKO cells, suggesting that this subset is promoted by T-bet and Eomes, similar to cluster 1 (Fig. 3.5). Several genes in this cluster, namely

CXCR3, Ccl3 and Xcl1, are involved with the recruitment or trafficking of immune cells and have been linked in several studies. One study demonstrated that CXCR3 recruits DCs to virally infected sites, and this process is further augmented by the chemokines Ccl3 and

Xcl1, which are secreted by CD8+ T cells (201). Moreover, IFNɣ induces the expression of the CXCR3 ligands CXCL9, CXCL10 and CXCL11. Thus, T-box transcription factors may potentiate T cell trafficking and tumor infiltration through the simultaneous regulation of IFNɣ and CXCR3 expression (202-205). A subsequent study revealed that IFNɣ augments the expression of CXCL9 and CXCL10 in lymph nodes following infection with cowpox virus, while levels of Ccl3 and Xcl1 were similarly upregulated (independent of

IFNɣ) and influenced the recruitment of NK cells (206). The GPI-anchored glycoprotein

Ly6c has been implicated in memory CD8+ T cell homing to lymphoid tissues as well as

CD8+ T cell adhesion to endothelial tissue, possibly through interactions with LFA-1 (207-

209). Our microarray data suggest that Ly6c is primarily regulated by Eomes in activated

CD8+ T cells and may predispose these cells to differential migratory properties as memory precursors. These studies suggest a common module where T-bet and Eomes function to promote immune cell homing and recruitment to peripheral sites.

Figure 3.5. Cluster 3: Genes induced by both T-bet and Eomes.

Cluster 4 revealed several genes that were downregulated in activated EKO and

DKO CD8+ T cells but upregulated in WT and TKO cells, suggesting that Eomes (but not

T-bet) functions to induce this subset of genes (Fig. 3.6). We observed two modules enriched in this cluster, one which comprises the Th1/Tc1-associated cytokine/chemokine receptor pathway and one which includes several genes involved in T cell memory. The first module offers some evidence into the effector role of Eomes in activated CD8+ T cells.

Our array data suggest that Eomes induces expression of the IL-18R, IL18rap, CCR5,

FASL and FUT7, which promote effector differentiation, trafficking to inflammatory sites and cytotoxicity. IL-18, which signals through IL18R in conjunction with IL18rap, cooperates with other inflammatory cytokines to induce T-bet and IFNγ expression, enhance proliferation and lend resistance to apoptosis (47, 137, 210-214). Studies have linked IL-18R expression with augmented self-renewal capacity, and persistent expression enables virus-specific CD8+ T cell survival in chronic LCMV infection (212, 215-217).

CCR5 expression on T cells is associated with trafficking to peripheral tissues, particularly

45 the lung and liver. Interestingly, expression of CCR5 on CD8+ T cells was found to associate with increased FasL expression in a model of GVHD (218). Moreover, FasL engagement with the Fas receptor on APCs resulted in IL-1 and IL-18 maturation in

Kupffer cells. In turn, IL-18 was able to promote FasL expression in hepatic NK cells

(219). These studies highlight an interesting link between IL-18, CCR5 and FasL, which our microarray data suggest may be extended to CD8+ T cells. FUT7 is an enzyme that catalyzes the synthesis of ligands for the E- and P-selectins, which are expressed on endothelial cells. These ligands are expressed on T cells and are critical for directing T cell homing to lymph tissues as well as trafficking to inflamed peripheral tissues (220). These data highlight a potentially unique role for Eomes in effector T cell differentiation and function. In contrast to the first gene subset, the second module revealed that Eomes regulates several molecules involved in CD8+ T cell memory differentiation, including

Hacvcr2 (or Tim-3), Bcl6 and Tcf7 (or Tcf1). Eomes, Bcl6 and Tcf7 have been implicated in several studies as transcription factors that are critical for the differentiation and maintenance of memory CD8+ T cells (Table 1.3) (27, 72, 89). On the other hand, Tim-3 is a co-inhibitory receptor and its expression is associated with restricting memory T cell differentiation in favor of short-lived effector T cells, possibly through activation of mTORC1 signaling (221, 222). That Eomes induces its expression is an interesting phenomenon but may offer a mechanism by which Eomes restricts aberrant effector responses and thus serves as a checkpoint during the acute immune response. These findings further support the intricate dual role of Eomes in promoting both effector and memory CD8+ T cell differentiation.

Figure 3.6. Cluster 4: Genes induced by Eomes.

Cluster 5 of our array revealed several genes that were downregulated specifically in EKO CD8+ T cells but upregulated or expressed basally in WT, TKO and DKO cells, suggesting that Eomes and T-bet may antagonistically regulate this subset of genes (Fig.

3.7). Of the genes listed in this cluster, we identified four that are involved in T cell migration and effector functions: perforin, CCR2, CXCR6 and Slamf6. Notably, CCR2 was the most highly enriched gene in EKO cells compared to WT controls. CCR2 is a

GPCR that responds to the ligand CCL2 and promotes T cell transmigration across endothelial cells (223). Interestingly, CCR2 expression on CD8+ T cells has been implicated in preventing apoptosis as well as in the generation and survival of memory cells (224, 225). CXCR6 regulates trafficking to inflamed peripheral tissues in response to the ligand CXCL16. Studies have demonstrated that CXCR6 is required for trafficking of

T cells to the lung, liver and aorta, among other peripheral sites, and was implicated in promoting the long-term survival of memory cells (226-228). Slamf6, a member of the

Slam family of receptors, is a type 1 transmembrane receptor that functions as a co- stimulatory molecule on T cells. Expression of Slamf6 is associated with enhanced effector

T cell function in models of autoimmune disease and cancer (229-231). While many genes in our array data are redundantly regulated by T-bet and Eomes, these data reveal several genes that may be regulated antagonistically. Therefore, despite the high sequence similarity in the T-box region between T-bet and Eomes, the remaining variation may account for differential regulation of the genes included in this cluster. Alternatively, the

C- and N-termini of the transcription factors (which vary greatly) may be critical in influencing the expression of this particular set of genes.

Figure 3.7. Cluster 5: Genes induced by Eomes alone.

Cluster 6 contains a subset of genes that were upregulated in activated TKO and

DKO CD8+ T cells but downregulated in WT and EKO cells, suggesting that T-bet (but not Eomes) functions to repress these genes (Fig. 3.8). Upon analysis of this cluster, we identified a number of genes that were specifically enriched in this cluster and broadly associated with several modules including a steroid hormone pathway, the Th2/Tc2 and

Th17/Tc17 differentiation pathway, several inhibitory receptors and the Rap1 signaling

48 pathway. The first subdivision includes several genes that are involved in steroid hormone synthesis and regulation. The histone acetyltransferase Ep300 interacts with the activating factor Trerf1 to regulate the Cyp11a1 gene. This step is critical in initiating the conversion of cholesterol to pregnenolone, which is the first step in the production of various steroid hormones and has implications in lymphocyte development and function (232-234). One study demonstrated that androgen signaling through the androgen receptor (Ar) inhibits

Th1 differentiation by upregulating the phosphatase Ptpn1 (235). Furthermore, androgen signaling was shown to increase FoxP3 expression in TREG (236). In the same line, Sgk1 was shown to prevent TREG differentiation in lieu of Th17 differentiation (237). In this way,

T-bet represses steroid synthesis, which may be critical in maintaining the Tc1 lineage. The second module in this cluster revealed that T-bet prevents CD8+ T cell differentiation to the Tc2 and Tc17 cell fates through the coordinated repression of Gata3, c-Maf, Socs3,

Il10 (Tc2) and Batf3, c-Maf, Il1r2, Il17a and IL17f (Tc17). That T-bet represses differentiation of activated CD8+ Tc1 to alternate cell fates has parallels with the role of T- bet in preventing CD4+ Th2 and Th17 differentiation (80). Per our microarray data, several surface receptors that regulate T cell signaling are repressed by T-bet, including Tigit, Icos and Tnfrsf8 (or CD30). While Tigit functions as a co-inhibitory receptor that is expressed on activated T cells and expressed even higher on exhausted T cells (238), Icos functions as a co-stimulatory receptor early during activation but continual signaling through engagement with Icos-ligand on tumor cells promotes T cell exhaustion (239). CD30, on the other hand, seems to have context-specific roles in T cell biology, where studies suggest that it is important for generating CD8+ T cell memory while other suggest that it promotes apoptosis (240, 241). Our analysis further revealed that genes in the Rap1 signaling

49 pathway are repressed by T-bet in activated CD8+ T cells. The Rap1 pathway is critical in mediating inside-out integrin signaling, which promotes LFA-1 expression and enhances

TCR signaling (242). The genes in this cluster include GTPase-modulating proteins (Tiam1 and Sipa1l3), PLCB4, which catalyzes PIP2 metabolism, and the integrins Itgb3 and Itgae

(243-245). Together, this large cluster reveals that T-bet has highly divergent roles in activated T cells and several of these pathways warrant further study.

Figure 3.8. Cluster 6: Genes repressed by T-bet.

Cluster 7 contains several genes that were repressed by T-bet and/or Eomes. This subset was downregulated in the TKO and/or EKO cells as well as WT cells but upregulated in DKO cells (Fig. 3.9). Our analysis revealed two modules that were enriched in this cluster; a Th2 cytokine and receptor pathway and a T cell differentiation and survival pathway. Like cluster 6, this pathway consists of several cytokine/cytokine receptors that

50 are associated with a Th2/Tc2 cell fate. This subset includes IL-4, IL-13, IL-21, IL-24,

Ccr4 and Ccl24. IL-4 promotes CD8+ Tc2 differentiation, and induces GATA3, IL-5 and

IL-13 expression (32, 34). Interestingly, IL-4 signaling promotes a CD8+ ‘memory-like’ phenotype characterized by high Eomes expression (Table 1.2) (246-248). Along with its role in B cell maturation (249), IL-21 has T cell-specific roles, as it restricts IFNγ-secretion by Th1 cells while maintaining RORγt and IL-17 expression in Th17 cells (250, 251). IL-

24 belongs to the IL-10 family of cytokines and similar to IL-21, has been shown to repress

Th1 responses while promoting Th2 responses in filarial infections (252). Ccr4 promotes trafficking of both CD4+ and CD8+ T cells to the skin (253). Interestingly, Ccr4 expression on CD8+ T cells was shown to mark an immature phenotype characterized by type 1 and type 2 cytokine secretion (254). Ccl24 is a chemoattractant that recruits CCR3-expressing

Th2 cells and is a potent attractant of naïve T cells (255, 256). Moreover, the CCR3/Ccl24 axis has been implicated in chronic inflammatory diseases and allergies (255). Together these data suggest that T-bet and Eomes cooperate to prevent Tc2 differentiation. The second module in this cluster revealed an interesting link between T-bet and Eomes and several molecules that regulate TREG differentiation including Ikzf4, Lif, Ahr, Ido and CD4.

CD4 is the co-receptor and defining marker for CD4+ T cells, so it is logical that T-bet and

Eomes might repress its expression in CD8+ T cells. However, this poses an interesting question regarding its regulation in T-bet-expressing CD4+ Th1 cells. The transcriptional repressor Ikzf4 (or Eos) is expressed at higher levels by TREG than effector T cells and was shown to directly interact with Foxp3 and repress IL-2 expression (257). In line with this, leukemia inhibitory factor (Lif) is highly expressed by TREG and was shown to promote

Foxp3 expression while suppressing Th17 differentiation (258). The aryl hydrocarbon

51 receptor (Ahr), though typically associated with Th17 cells, has been shown to be expressed by gut-resident TREG and enhance their suppressive activity (259). Finally, indoleamine 2,3-dioxygenase (Ido) severely limits the activity of effector T cells, but potently activates TREG and prevents their differentiation to Th17 cells (260). Together this cluster suggests that T-bet and Eomes cooperate to prevent aberrant differentiation toward the regulatory T cell phenotype. Eomes as well T-bet restricts the Tc2 and TREG phenotypes through repression of both transcription factors and cytokines associated with these cell subsets. However, T-bet alone is a more significant repressor of aberrant differentiation to the Tc17/Th17 phenotype and regulates several master transcription factors of the Tc2 and

Tc17 cell fates (cluster 6).

Figure 3.9. Cluster 7: Genes repressed by T-bet and/or Eomes.

Taken together, our data demonstrate novel roles for T-bet and/or Eomes in promoting or repressing a number of genes in activated CD8+ T cells (Fig. 3.10). It is

52 important to note that the cells used in our experiment were activated in non-polarizing

Tc0 conditions, as opposed to Tc1 conditions, in which we might expect a transcriptional profile similar to what we observed in the microarray. Furthermore, the priming context of our cells was highly controlled in an in vitro setting, and not necessarily reminiscent of how T-bet and Eomes regulate differentiation in vivo. Indeed, studies have shown that

CD8+ T cells exhibit marked plasticity in vivo, with the ability to acquire a Tc2 or Tc17 phenotype, depending on the context of the immune response. This will be further discussed below (31).

Figure 3.10. Schematic demonstrating potential targets of T-bet and Eomes in differentiating CD8+ T cells. Potential targets were identified from the Affymetrix gene expression analysis using BRB-ArrayTools, as described in the methods.

3.2.3 T-bet and Eomes Cooperate to Maintain CD8+ Tc1 Specificity

Apart from the 7 clusters identified from our microarray analysis, we observed some striking differences between WT and DKO CD8+ T cells that were not immediately

53 apparent in analyzing differences between all 4 genotypes. As DKO cells lack both T-bet and Eomes, differential gene expression between the two genotypes reflects the redundant functions of these T-box transcription factors in regulating the differentiation of effector

CD8+ T cells. The majority of these genes are cytokines, chemokines or their cognate receptors as well as numerous transcription factors associated with alternate CD4+ and

CD8+ T cell fates (Fig 3.11). Of the several pathways identified in our analysis, T-bet and

Eomes appear to cooperatively prevent the aberrant differentiation of CD8+ T cells to Tc2- and Tc17-like cell fates. The Tc2 cytokine and gene expression profile was significantly upregulated in DKO cells as compared to WT cells. Type 2 genes enriched in DKO cells include the transcription factors Maf and Gata3, as well as the Th2-associated cytokines

IL4, IL5 and IL-13 (Fig. 3.11). Our microarray analysis further revealed that T-bet/Eomes- doubly-deficient (DKO) CD8+ T cells significantly upregulated several Type 17-associated genes, including the transcription factors Rorc, Batf and Ahr, as well as IL-17 and the IL-

17R (Fig. 3.12). Together, these preliminary data suggest that T-bet and Eomes restrict effector CD8+ T cell differentiation to Tc2 and Tc17 fates, analogous to the role of T-bet in CD4+ Th1 cells.

Figure 3.11. Pathway enrichment analysis revealed differential regulation of distinct pathways between activated WT and DKO CD8+ T cells. KEGG pathway analysis identified 4 pathways containing genes that were differentially regulated at a significant level between WT and DKO genotypes (p<0.05). The pathways, number of genes, gene names and permutation p-values are listed in the table (bottom).

Figure 3.12. Cells lacking both T-bet and Eomes revert to a phenotype characteristic of Tc17 cells.

3.2.4 Eomes regulates the expression of CD62L and Ly6c in the CD8+ T cell central memory compartment

The current body of literature regarding the roles of T-box transcription factors in

CD8+ T cell effector differentiation focuses on the master regulatory role of T-bet in both

CD4+ Th1 and CD8+ Tc1 cells. T-bet was defined as a master transcription factor in Th1 differentiation in the early 2000s, and its expression correlates with short-lived effector cells. T-bet was subsequently shown to be critical in regulating CD8+ T cell effector responses. Eomes is similarly expressed in effector T cells and shares several redundant functions with T-bet, but an increased Eomes/T-bet ratio correlates with a memory phenotype (27, 46, 72, 85, 129). Despite the striking contrast between T-bet and Eomes expression in effector and memory cells, a functional role for Eomes in promoting memory differentiation is lacking. Our microarray data suggest that Eomes not only significantly regulates a number of effector genes, but it seems to contribute more than T-bet (Fig. 3.2).

Moreover, our gene expression data revealed that Eomes alone is critical in maintaining the expression of the memory-associated markers CD62L and Ly6c (Fig. 3.13). CD62L and Ly6c are surface molecules expressed by naïve and memory CD8+ T cells that have been implicated in T cell homing to lymph tissues (27, 104, 208, 209).

Figure 3.13. Eomes regulates the expression of genes involved in memory differentiation.

As expression of these markers is reduced upon T cell activation, we sought to analyze their expression in T cell memory populations. CD62L, and to some extent Ly6c, are re-

+ expressed in a subset of memory CD8 T cells known as central memory cells (TCM) and their frequencies correlate with increasing levels of Eomes (12, 261). We used mice deficient in Eomes (EKO) or T-bet (TKO) to validate the previously reported differences in memory differentiation in the absence of these transcription factors (72). Inbred laboratory mice found in most SPF colonies contain ~10-20% CD44hiCD62Lhi central memory cells, 70-80% CD44loCD62Lhi naïve cells, and 1-10% CD44hiCD62Llo effector cells (262-266). Although these frequencies were not significantly altered in TKO mice, in the absence of Eomes, as previously reported, the TCM population was significantly decreased (Fig. 3.14A,B) (72). Interestingly, though there was no difference in the frequency of CD62Lhi cells between WT and EKO mice, we observed that EKO cells expressed a significantly lower level of CD62L specifically in the central memory population, when compared to WT controls (Fig. 3.14C,D). We observed a similar trend with the expression of Ly6c, in which EKO cells had a markedly reduced population of

Ly6chi cells as well as a reduced Ly6c MFI (Fig. 3.15A,B). Consistent with its role in

+ promoting a TCM phenotype, analysis of Eomes expression in WT CD8 T cells revealed

that memory CD8+ T cells express higher levels of Eomes than naïve cells whereas effector

T cells exhibit bimodal expression (Fig. 3.14E). Taken together, these results suggest that

Eomes has a previously unappreciated role in regulating the levels of CD62L and Ly6c in

central memory CD8+ T cells.

Figure 3.14. Eomes regulates the expression of CD62L in the CD8+ T cell central memory compartment. Splenocytes were harvested from uninfected WT BL/6 mice and analyzed for expression of the indicated markers by FACS. Plots represent live/CD8+ T cell populations. Teff = effector, Tcm = central memory, Tn = naïve (A) Representative FACS plots of CD8+ T cell populations in WT, TKO and EKO mice. (B) Frequency of CD8+ T cell populations in WT, TKO and EKO mice based on CD44 and CD62L expression. Data are representative of at least 3 mice per group. (C) Representative histograms of CD62L expression in WT and EKO CD8+ T cell subsets. (D) Comparison of the mean fluorescence intensity (MFI) of CD62L in central memory, effector and naïve subsets of WT and EKO CD8+ T cells from (C). Data are representative of at least 3 mice per group. (E) Expression of Eomes in CD8+ T cell populations as analyzed by FACS in a WT mouse.

Figure 3.15. Eomes regulates the expression of Ly6C in the CD8+ T cell central memory compartment. Splenocytes were harvested from uninfected WT BL/6 mice and analyzed for expression of the indicated markers by FACS. Plots represent live/CD8+ T cell populations. Teff = effector, Tcm = central memory, Tn = naïve. (A) Representative histograms of Ly6C expression in WT and EKO CD8+ T cell subsets. (B) Comparison of the percentage of Ly6Chi CD8+ T cells in central memory, effector and naïve subsets of WT and EKO CD8+ T cells from (A). Data are representative of 2 mice per group.

3.2.5 Eomes regulates the early expression of Bcl6 in activated CD8+ T cells

As a follow-up to the microarray data, we focused on markers associated with memory commitment as well as cytokines that have been implicated in T cell memory. We performed RT-qPCR analysis to quantitatively compare mRNA levels of these selected

Eomes targets in WT, TKO, EKO and DKO CD8+ T cells after 5 days of activation.

Because CD8+ T cells downregulate CD62L expression upon activation (Fig. 3.14D), we expected a negligible difference in the expression of this marker in activated CD8+ T cells, regardless of Eomes expression. Surprisingly, we found that Eomes deficiency led to a greater than two-fold reduction in the expression of CD62L and Ly6c in activated cells.

The pattern was similar in analyzing expression of Ly6c (Fig. 3.16A). Importantly, we did not observe differences in expression of the activation markers CD25 and CD69, indicating

59 that changes in expression of these molecules is not an artifact of global changes in transcription. This is consistent with our later data demonstrating that DKO cells do not display a proliferation defect relative to WT cells in vivo, suggesting that DKO cells are still functional relative to WT cells (see Chapter 5). These findings further extend our observations from Figure 3.14 and Figure 3.15 and suggest that Eomes is necessary for the maintenance of both CD62L and Ly6c expression early upon activation in effector CD8+

T cells, and prior to their differentiation into memory cells. Interestingly, we noted that the memory-associated molecule B cell lymphoma-6 (Bcl6) was also decreased at the mRNA level in the absence of Eomes (Fig. 3.16A). This molecule was of particular interest, as strong evidence supports its role in CD8+ T cell memory differentiation (27, 132, 267, 268).

Western blot and FACS analysis of Bcl6 expression in WT and EKO CD8+ T cells at day

5 further confirmed the regulation of Bcl6 by Eomes in activated CD8+ T cells, as Bcl6 expression was reduced by an average of 25% in EKO cells (Fig. 3.16B). Of note, granzyme B and perforin were reduced in EKO cells compared to WT controls, consistent with previous reports (Fig. 3.17) (68, 70). Together with the gene expression array, these data suggest that Eomes promotes a memory precursor phenotype early in differentiating

CD8+ T cells through the induction of CD62L, Ly6c and Bcl6.

Figure 3.16. Eomes regulates the early expression of Bcl6 in activated CD8+ T cells. (A) qRT-PCR analysis of the indicated genes was performed with RNA harvested from WT, TKO, EKO and DKO CD8+ T cells cultured in vitro for 5 days under Tc0 conditions, as described. Expression levels are relative to WT RNA and normalized to GAPDH or β-actin. Plot is representative of 3 mice per genotype (n=3). (B) Representative FACS and Western blot analyses comparing Bcl6 expression in WT and EKO CD8+ T cells after 5 days of culture in vitro. Western blot data (middle, right) are representative of 3 independent experiments.

Figure 3.17. Eomes regulates the early expression of genes involved in CD8+ T cell memory differentiation. (A) Representative FACS plots comparing expression of effector and memory markers in WT and EKO CD44hi CD8+ T cells stained ex vivo. Plots are representative of a single experiment.

3.3 Discussion

Our gene expression analysis revealed an interesting relationship between the redundant and differential roles of T-bet and Eomes in influencing CD8+ T cell effector differentiation. Importantly, it is unclear whether the target genes we identified are directly or indirectly regulated by T-bet and/or Eomes. Instead, the differential expression of genes may be secondary to T-bet and/or Eomes-mediated induction or repression of other regulatory genes. For example, the Tc2 signature is notably increased in DKO cells compared to single KO and WT cells. Whether T-bet and Eomes directly repress Tc2 cytokines or these are upregulated secondary to increased GATA3 expression is unclear

(Fig. 3.8, 3.9). The Tc17 gene signature is similarly increased in DKO cells compared to the other genotypes. Increased expression of the transcription factors associated with this phenotype including Rorc, Batf, Maf and Ahr may be controlling Tc17 differentiation secondary to T-bet and Eomes deficiency. Additionally, several cytokines are differentially regulated in knockout CD8+ T cells relative to WT cells (Fig. 3.11, 3.12). Some of these cytokines influence CD8+ T cell function, including IL-4, IL-10 and IFNɣ (Table 1.2).

Changes in gene expression observed in our microarray analysis may then be secondary to the differential expression of these cytokines. Further insight into the direct regulation of these targets by T-bet and Eomes is warranted.

As classical regulators of CD8+ T cell effector function, T-bet and Eomes induce

IFNɣ, perforin, granzyme, CD122 and CXCR3 expression, which promote cell-mediated immune responses against intracellular pathogens and malignant cells. Intriguingly, we found that T-box transcription factors are implicated in several other processes, including

TCR signaling, apoptosis, migration and memory differentiation (Fig. 3.3-3.9). Moreover,

62 our gene expression data suggests that in a manner analogous to the role for T-bet in CD4+

Th1 cells, T-bet and Eomes cooperatively prevent differentiation to CD8+ Tc2, Tc17 and

TREG phenotypes. These findings may have physiological implications during an immune response, where antigen levels and the local inflammatory milieu influence the expression of T-bet and Eomes. For example, in the context of tissue resident memory cells (TRM), T- bet and Eomes are minimally expressed, which may lend to T cell plasticity in peripheral tissues. Indeed, it has been shown that CD4+ T helper subsets maintain a plastic phenotype as resident memory cells, poised to respond differentially depending on the context of the pathogen (269).

Our findings that T-bet and Eomes control differentiation to alternate cell fates has been is in line with previous studies demonstrating that CD8+ T cells can express IL-4, IL-

5, IL-13 and GATA3 under type 2-polarzing conditions, albeit at different levels than their

Th2 counterparts (32, 34). Yet a direct link between T-bet and Eomes in repressing aberrant

Tc2 differentiation have not been extensively studied. A previous study demonstrated that in vitro-activated TKO CD8+ T cells revert to a Tc2 phenotype characterized by expression of IL-4 and IL-10 even under non-polarizing conditions, indicating that T-bet partially represses Tc2 differentiation (69). Similarly, doubly-deficient CD8+ T cells that were activated in vitro in Tc2 conditions expressed increased IL-4 transcripts compared to WT cells, suggesting that both T-bet and Eomes contribute to repression of the Tc2 phenotype

(71).

Whereas Tc1 cells are beneficial in several pathologic conditions including asthma

(270), CD8+ Tc2 cells were shown to exhibit reduced cytotoxicity and exacerbate allergic airway inflammation in this context (271). In comparison to Th2 cells, Tc2 cells were found

63 to secrete less IL-4 but similar levels of IL-13, which may contribute to exacerbated allergic reactions, as IL-4 has been implicated in negative feedback pathways that mediate airway inflammation while IL-13 aggravates the response (272). While our data suggest that

Eomes cooperates with T-bet to prevent Tc2 differentiation, CD8+ T cell culture in Tc1 conditions favors T-bet expression, while culture in Tc2 conditions favors Eomes expression. However, this finding can be attributed to the role of IL-12 in inducing T-bet and reducing Eomes expression. Interestingly, this study revealed that CD8+ T cell culture in IL-4 enhances Eomes expression, a finding which may have implications in the role of

IL-4 in the development of CD8+ virtual-memory T cells (262, 266, 273).

Like Tc2 cells, our data suggest that T-bet and Eomes cooperate to repress Tc17 differentiation. As with CD4+ Th17 cells, Tc17 cells differentiate in response to IL-6, IL-

21, IL-23 and TGFβ and express the transcription factor RORγt. Interestingly, Irf4, a transcription factor which has been implicated in Tc1 effector function and expansion, is critical in developing Tc17 cells. In this context, Irf4 restricts Tc1 and TREG differentiation, through repression of Eomes and FoxP3, respectively (33, 36, 274, 275). Several studies have demonstrated that T-bet and Eomes cooperate to repress a Tc17 phenotype following both polyclonal stimulation in vitro and in response to an in vivo LCMV challenge (71,

83). Importantly, acquisition of a Tc17 phenotype in vitro required polarization in Tc17 conditions and was pronounced in T-bet and Eomes single-knockout cells but exacerbated in DKO T cells. The authors concluded that DKO TILs similarly acquire a Tc17 phenotype in a B16 melanoma tumor model, though the number of TILs was severely reduced in DKO mice (71). On the other hand, LCMV infection poised DKO cells towards a Tc17 phenotype even without ex vivo re-stimulation. Furthermore, these cells expressed

64 significant levels of IL-17, IL-21, IL-22, IL-23R and RORɣt transcripts, whereas these were virtually undetectable in single knockouts and WT cells. LCMV infection in DKO mice resulted in a CD8+ T cell-dependent inflammatory wasting syndrome, characterized by multi-organ infiltration of neutrophils (83). However, these DKO Tc17 may not represent a physiologically relevant subset, as Tc17 maintain basal T-bet and Eomes expression, though this is dependent on the context of polarizing cytokines (35, 36, 276).

Tc17 cells have been shown to be protective in a number of viral infections, partly through induction of neutrophil infiltration (35, 36). Current evidence suggests that Tc17 cells are less cytotoxic than their Tc1 counterparts due to diminished granzyme B and IFNɣ secretion (35). However, the capability of Tc17 cells to elicit cytotoxic functions may be more dependent on the context of the infection, as adoptively transferred Tc17 cells were shown to convert to IFNɣ-secreting cells that effectively lysed cells in a TCR transgenic model. Moreover, this cell lysis was shown to correlate with increased FasL expression, suggesting this may be a primary mechanism by which Tc17 target cells (276). On the other hand, and similar to their Th17 counterparts, Tc17 cells have been implicated in autoimmunity and transplant rejection (31). The mechanistic role of Tc17 cells in these disorders is unclear, but it might involve IL-17 mediated help to CD4+ T cells as well as granulocyte recruitment (31, 274).

In contrast to the implicated roles of T-bet and Eomes in maintaining the Tc1 lineage, our microarray data suggest novel functional roles for Eomes in influencing the early differentiation of memory precursor CD8+ T cells. Here we show that Eomes promotes the early induction of several memory-associated molecules, including Bcl6,

CD62L and Ly6c. Interestingly, we observed the expression of these markers 5 days after

65 robust polyclonal activation in vitro. Therefore, Eomes may impart an early differentiation program in activated CD8+ T cells, and cells that stochastically express more Eomes may be better primed to adopt a memory phenotype. In line with this, these findings lend credence to the asymmetric cell fate model of CD8+ T cell memory differentiation. Despite evidence that asymmetric partitioning of T cells does not occur following polyclonal activation in vitro (99, 101, 118), our data suggest that Eomes serves as a critical mediator in the early commitment of CD8+ T cells to a memory phenotype, even shortly after activation. These data and this model are discussed in more detail in the next chapter, where our findings support a modified model of memory differentiation that includes interplay between Eomes, IL-10 and CD62L.

Together, data from our microarray analysis suggest several parallels with what is currently known about the regulation of CD4+ T helper subset differentiation by T-bet.

However, our data demonstrate a novel role for Eomes in maintaining Tc1 differentiation as well as influencing the early differentiation of memory CD8+ T cells. We propose that in activated CD8+ T cells, and under non-polarizing conditions, T-bet and Eomes cooperate to prevent differentiation to the Type 2 and Type 17 pathways, while Eomes expression pushes cells towards a memory precursor phenotype early upon activation.

Chapter 4: Eomes-driven IL-10 Production in Effector CD8+ T

Cells Promotes a Memory Phenotype

4.1 Introduction

Following the resolution of an immune response, subsequent protection against the same pathogen is largely dependent on the ability of the host to develop immunological memory. The potential to acquire a memory phenotype is limited to ~5% of the antigen- specific CD8+ effector T cell population that survives contraction (27, 94, 95, 104). This memory-precursor population is phenotypically distinct from terminally differentiated effector cells, as evidenced by distinct surface marker expression, transcription factor profiles and epigenetic signatures (27, 104, 116, 277-279).

The differentiation of activated CD8+ T cells to effector and memory fates is controlled by the T-box transcription factors T-bet and Eomes (45, 46, 65, 70, 72, 73).

Strong antigen-signaling through the T cell receptor (TCR) as well as cytokine signals, including signals downstream of IL-12, results in the upregulation of T-bet. This in turn promotes the development of an effector T cell phenotype, characterized by the expression of IFNɣ, TNFα, perforin and granzyme B (27, 45, 46, 85). Conversely, low levels of TCR signaling in the presence of IL-2, but the absence of inflammation, promotes Eomes expression. It is well established that higher Eomes levels favor the maintenance of a functional CD8+ memory T cell population (27, 46, 72, 85, 129). Though these studies provide strong evidence for the roles of T-bet and Eomes expression in CD8+ T cell effector function and memory differentiation, the individual, synergistic and antagonistic

67 contributions that these related T-box factors make to these processes remain poorly understood. T-bet and Eomes share ~73% amino acid homology in the T-box domain (Fig.

1.3). As discussed previously, their functions are partly redundant (79). Both regulate the expression of IFNɣ, perforin, granzyme B, CD122, and CXCR3, albeit to different extents

(27, 68, 70, 71). T-bet deficiency enhances the central memory compartment in lieu of terminal effector cells while conversely, Eomes deficiency severely reduces the population of central memory CD8+ T cells (45, 71-73, 130). Though the canonical model of memory

CD8+ T cell differentiation implies that increasing Eomes expression correlates with decreasing T-bet levels, expression of these transcription factors fluctuates and is not restricted to one distinct cell fate (65, 131). Along these lines, whether Eomes has a direct or simply correlative role in promoting memory differentiation is unclear.

In this context, an intriguing observation related to Eomes targets discussed in

Chapter 3 is IL-10 (Fig. 3.13, 3.16). As discussed in Chapter 1, T-box transcription factors cooperate with cytokines (e.g. IL-2, IL-7, IL-12, IL-15 and IL-18) to drive CD8+ T cell differentiation. Notably, IL-10 was significantly downregulated in EKO cells but upregulated in TKO and DKO cells (Fig. 3.13, 3.16). This suggests that T-bet and Eomes reciprocally regulate IL-10, and that Eomes functions to promote its expression. In recent years, studies have revealed rather provocative roles for the cytokines IL-10 and IL-21 in

CD8+ T cell memory generation (141, 157-160). Several of these studies suggest that the role for IL-10 in memory differentiation is consistent with its role in resolving inflammation (164). As low levels of inflammation support memory CD8+ T cell differentiation (and not terminal effector differentiation) (27), it might follow that IL-10 contributes to memory maturation indirectly by controlling the local inflammatory

68 environment. Recent studies show that IL-10 functions at another level in support of memory T cell differentiation. Infection with either L. monocytogenes or lymphocytic choriomeningitis virus (LCMV) in IL-10-knockout (KO) mice markedly reduced the function and frequency of memory CD8+ T cells. In the latter study, CD4+ T regulatory

+ cell (TREG)-derived IL-10 was shown to rescue the defect in the CD8 memory T cell population observed in LCMV-infected IL-10-deficient mice (161, 162). A separate study suggested that CD11c+ dendritic cell (DC)-derived IL-10 enhances IL-15-driven homeostatic proliferation of CD8+ memory T cells (163). Finally, an elegant study by Cui et al. demonstrated that IL-10 signaling acts directly on CD8+ T cells via STAT3 activation to promote memory CD8+ T cell maturation. Accordingly, STAT3 deficiency markedly reduced levels of the memory-associated markers Eomes, Bcl6 and suppressor of cytokine signaling 3 (SOCS3) (132). Taken together, these two parallel streams of studies raise the important question of how these the two pathways might converge; i.e. whether T-box transcription factors and IL-10 operate along the same or different pathways to influence

CD8+ T cell memory differentiation. Our data from Chapter 3 showing that Eomes induces

IL-10 expression offered a potential answer to this question, which is the focus of this chapter.

In order to examine this question, we sought to confirm that Eomes regulates IL-10 expression in activated CD8+ T cells. Additionally, we wanted to address the mechanism by which IL-10 imparts a CD8+ T cell memory phenotype. Our data support a role for

Eomes, but not T-bet, in promoting IL-10 production in activated CD8+ T cells.

Furthermore, we show that Eomes and IL-10 induce CD62L expression on CD8+ T cells.

The effects of Eomes and IL-10 on CD62L expression are independent, leading to a

CD44hi/CD62Lhi central memory phenotype. Finally, we demonstrate that the intrinsic ability of CD8+ memory T cells to make IL-10 confers a survival advantage in vivo. Our data suggest that Eomes promotes IL-10 expression and cooperates with IL-10 signaling to optimally maintain the central memory phenotype within the CD8+ T cell compartment.

4.2 Results

4.2.1 Eomes inversely regulates Th1/Th2 differentiation

Our gene expression analysis revealed several pathways that were differentially regulated in TKO, EKO or DKO cells relative to WT cells. Intriguingly, the absence of

Eomes (single knockout) resulted in differential expression of the Th1 and Th2 activation pathways (Fig. 4.1A). With regards to the Th1 pathway, loss of Eomes expression correlated with reduced expression of IL-18R, CXCR3, CCR5 and Tim-3, among others.

With regards to the Th2 pathway, fewer genes were differentially regulated in the single knockouts (TKO and EKO) but many were significantly different in DKO cells (see

Chapter 3), indicating that T-bet and Eomes cooperate to prevent Tc2 differentiation (Fig.

4.1B). Results from the KEGG pathway analyses corroborate our findings from Chapter 3 and imply that T-bet and Eomes function similarly in CD8+ T cells to prevent Tc2 differentiation in favor of a Tc1 phenotype.

Figure 4.1. T-bet and Eomes differentially regulate CD8+ T cell differentiation. Class comparison analysis of genes differentially expressed between WT, TKO, EKO and DKO CD8+ T cells cultured under Tc0 conditions for 5 days. (A) Representative cluster analysis demonstrating highly enriched pathways that are largely dependent on T-bet and/or Eomes. (B) Gene signature profiles from the indicated pathways from (A) demonstrating regulation of individual genes by T-bet and/or Eomes. T (TKO), E (EKO), D (DKO).

4.2.2 Eomes promotes IL-10 expression in activated CD8+ T cells

In addition to the surface markers discussed in the previous chapter, the absence of

Eomes also resulted in differential expression of key cytokine pathways (Fig. 4.1A). Of

these, the IL-10 signaling pathway was especially intriguing (Fig. 4.1B). Recent studies

suggest that IL-10 influences the development of CD8+ memory T cells (132, 161-163).

Zhang et. al. found that Eomes directly bound to and promoted IL-10 expression in CD4+

Tr1 cells (280). However, a connection with Eomes as a regulator of IL-10 in CD8+ T cells

has not been studied. We therefore sought to determine if Eomes regulates IL-10

expression at the protein level in activated CD8+ T cells. We isolated CD8+ T cells from

WT, TKO and EKO mice and cultured them in vitro under Tc0 conditions for 5 days before

analyzing for IFNɣ and IL-10 expression by flow cytometry (Fig. 4.2A). Consistent with

qPCR data from Fig. 3.16, EKO cells exhibited a roughly 2-fold decrease in IL-10

production relative to WT cells (Fig. 4.2B). Of note, there was no observed difference in

expression of IL-10R at either the mRNA or protein levels (Fig. 3.16, 3.17).

Figure 4.2. Eomes promotes the expression of IL-10 in activated CD8+ T cells. (A) CD8+ T cells isolated from WT, TKO and EKO mice were cultured under Tc0 conditions for 5 days. On day 5, cells were re-stimulated (bottom panel) with PMA and ionomycin and analyzed for IFNɤ and IL-10 expression. Cells are gated on live/CD8+ cells. (B) Representative percentages of IL-10-secreting CD8+ T cells in WT and EKO mice from (A). Plots are representative of 5 independent experiments (n=5). (C) WT or EKO CD8+ T cells were activated in vitro and transduced with Eomes or empty-vector retrovirus. On day 5, RNA was harvested from cell cultures and transcript levels were analyzed by RT-qPCR. Expression levels were analyzed relative to empty-vector transduced WT cells and normalized to GAPDH. Error bars represent standard deviation of replicates done in triplicate. Asterisks indicate a p-value<0.05. (D) WT or EKO CD8+ T cells were activated in vitro and transduced with Eomes or empty-vector retrovirus as in (C). Cells were selected with puromycin for 3 days, re-stimulated with PMA/ionomycin (bottom panel) on day 5 and stained for IFNɤ and IL-10. Cells are gated on live/CD8+ cells.

4.2.3 Eomes is sufficient to promote IL-10 expression in activated CD8+ T cells

To assess whether Eomes alone was sufficient to regulate IL-10 expression, CD8+

T cells were isolated from WT and EKO mice and transduced with Eomes-containing retroviruses. The expression levels of Eomes and IL-10 were analyzed by RT-qPCR and flow cytometry on day 5. Relative to WT cells transduced with empty-retrovirus (control), the lack of Eomes (EKO-empty) decreased levels of Eomes and IL-10 mRNA approximately 2-fold (Fig. 4.2C). This result correlated with low expression of IL-10 protein in the EKO-empty cells (1.06%) (Fig. 4.2D). Overexpression of Eomes in WT

CD8+ T cells (Eomes-WT) increased Eomes as expected – but also the IL-10 transcript levels (Fig. 4.2C). This upregulation of mRNA was similarly evident at the protein level as 13.2% of WT-Eomes cells expressed IL-10 compared to 2.5% in the WT-empty control

(Fig. 4.2D). Induction of Eomes expression in EKO cells rescued the IL-10 phenotype to a similar extent as observed in the WT-empty control (2.98% and 2.5%, respectively) (Fig.

4.2D). Together, these data suggest that Eomes alone is sufficient to promote IL-10 production in activated CD8+ T cells.

4.2.4 IL-10 induces the expression of CD62L in activated CD8+ T cells

The precise role of IL-10 in influencing CD8+ T cell memory differentiation is unclear, and while it has been suggested to have roles in effector function or dampening activation (132, 281), our data suggest that it might also impact the Eomes-mediated orchestration of the TCM program. To evaluate this further, we stimulated our 5-day cultures of CD8+ T cells with exogenous IL-10 for different durations. We observed a dramatic increase in the CD62L MFI between 15 and 30 minutes of stimulation, with a gradual

73 decline in expression (Fig. 4.3A). Importantly, the increased expression of CD62L was maintained through 5 days of culture in IL-10 as compared to untreated cells (Fig. 4.3A).

To confirm that IL-10 maintains CD62L expression in vitro, we cultured CD8+ T cells with or without IL-10 for 5 days. These results corroborated those from our previous experiment, as cells cultured in IL-10 maintained increased CD62L expression levels relative to controls (Fig. 4.3B). Notably, there was a ~2-fold increase in CD62L expression on IL-10 treated cells relative to controls (Fig. 4.3B).

Figure 4.3. IL-10 temporally regulates the expression of CD62L. (A) WT CD8+ T cells were cultured for 5 days under Tc0 conditions with or without the addition of exogenous IL-10 (20ng/ml). On day 5, cells were analyzed for expression of CD62L by FACS. (B) The ratio of CD62L expression in IL-10-treated vs untreated CD8+ T cells is shown. Data are representative of cell cultures from 7 mice (n=7) in 3 independent experiments. Median MFI values were used for analysis.

To address whether IL-10 increased the frequency of TCM cells in vitro, we analyzed cell cultures on each day of the 5-day activation period. Though the addition of IL-10

(without exogenous IL-2) slightly increased the percentage of CD62Lhi cells compared to

74 untreated cells, this effect was negated by the addition of IL-2. Therefore, while IL-10 alone may reinforce or support a naïve/memory-like phenotype, IL-2 dominantly promotes

TEFF differentiation in vitro (Fig. 4.4). Taken together, our data suggest that IL-10 functions to maintain the expression of CD62L but does not increase the percentage of TCM cells. At a physiological level, these data imply that the makeup of the local cytokine milieu significantly influences CD8+ T cell homing to and maintenance in SLOs.

+ Figure 4.4. Exogenous IL-10 does not increase the frequency of TCM in vitro. WT CD8 T cells were cultured for 5 days following polyclonal activation with αCD3/αCD28 antibodies with or without the addition of exogenous IL-2 and/or IL-10. Cells were harvested on the indicated days, surface stained and analyzed by flow cytometry. (A) Representative FACS plots comparing CD44 versus CD6L expression. (B) Representative bar graphs depicting frequencies of the indicated populations from (A). Cells are gated on the live/CD8+/TCRβ+ population.

4.2.5 The relative roles of Eomes and IL-10 in the regulation of CD62L expression

Taken together, our data suggested at least two potential mechanisms for the interplay between Eomes and IL-10 in the regulation of CD62L expression. For one, Eomes and IL-10 may independently regulate CD62L, or alternatively, both could be part of the same pathway whereby Eomes regulates IL-10, which in turn regulates CD62L (via

STAT3). In order to distinguish between these mechanisms, we analyzed CD62L expression in WT and IL-10 knockout mice. First, we transduced WT CD8+ T cells with

Eomes-containing or empty-vector retrovirus and cultured the cells for 3 days under Tc0 conditions, as described in the methods. As expected, we observed a greater than 2-fold increase in the percentage of Eomeshi/CD62Lhi cells in WT cells constitutively expressing

Eomes, relative to the empty-vector controls (Fig. 4.5A,B). Because IL-10 maintains

CD62L expression in CD8+ T cells (Fig. 4.3), we next investigated whether Eomes requires

IL-10 to induce CD62L expression. To this end, we transduced CD8+ T cells from IL-

10KO mice with Eomes-containing or empty-vector retrovirus and cultured them for 5 days under Tc0 conditions, as above. Constitutive Eomes expression in IL-10KO cells led to a

4-fold increase in the frequency of Eomeshi/CD62Lhi cells, indicating that Eomes induces

CD62L expression independent of IL-10 (Fig. 4.5A,B). In analyzing the CD62L- expressing population alone, we observed similar percentages of CD62Lhi CD8+ T cells in both the WT and IL10KO cells following Eomes induction (Fig. 4.5B). In this experimental timeframe, Eomes overexpression increased the percentage but did not affect the overall

MFI of CD62L in either WT or IL-10KO cells (Fig. 4.5C). Whereas IL-10 functions to maintain the CD62L MFI (Fig. 4.3), forced Eomes expression increases the overall

76 frequency of CD62L-expressing CD8+ T cells. Together our data show that Eomes and IL-

10 can independently induce CD62L expression in activated CD8+ T cells.

Figure 4.5. Eomes does not require IL-10 to induce CD62L expression in CD8+ T cells. (A) CD8+ T cells were isolated from WT or IL-10KO mice and stimulated under Tc0 conditions for 2 days. On day 2, cells were transduced with Eomes-containing or empty-vector retrovirus (RV) and cultured through day 5. Cells were then analyzed for CD62L and Eomes expression by FACS. Cells are gated on live/CD8+/Thy1.1+ populations. (B) Representative frequency of CD62Lhi cells from (A). (C) Representative CD62L MFI values from CD62L+ populations in (A). Plots are representative of 2 independent experiments with 2 mice per genotype (n=4).

4.2.6 Cell-intrinsic IL-10 is not required to maintain a central-memory CD8+ T cell phenotype

Several studies have shown that CD8+ T cells secrete IL-10 in different infection models (282-287). In line with this, data from our lab demonstrate that a subset of CD8+

TEFF are primed to make IL-10 following infection with Leishmania major. Briefly, we injected wildtype mice with 1 x 105 L. major parasites in the ear and footpad of WT BL/6 mice. Inflamed lesions were measured at regular intervals and mice were euthanized 4

77 weeks post-injection. Infected ears, footpads and draining lymph nodes were harvested and analyzed for immune cell infiltrates by flow cytometry. We observed that activated CD8+

T cells were secreting IL-10 in all tissues in response to L. major infection. Interestingly, in comparing lymph and infected tissues, we observed a small but distinct population of

TEFF making IL-10 in the draining lymph nodes (Fig. 4.6). Together with our previous data, this suggests that IL-10 levels in SLOs may have a role in influencing memory differentiation.

+ 5 Figure 4.6. CD8 TEFF make IL-10 in response to L. major infection. WT mice were infected with 1 x 10 Leishmania major promastigotes in the footpad or ear dermis in a volume of 20 μl. Infection was monitored at 3- or 4-day intervals in the footpad and ear lesions. One month after infection, cells from the indicated tissues were harvested, re-stimulated with PMA and ionomycin and analyzed for IL-10 expression (see methods). Cells are gated on the live/CD8+/TCRβ+ population.

In addition to secreting IL-10, CD8+ T cells express the IL-10R and respond to distinct cellular sources of IL-10 (284, 288-290). In line with this, we sought to investigate whether CD8+ T cells use their own IL-10 to support memory differentiation. We

78 hypothesized that CD8+ T cell-intrinsic IL-10 was required to maintain the CD8+ T cell central-memory compartment. To address this, we implemented an adoptive co-transfer model in which equal numbers of pre-activated, congenically labeled WT and IL10KO cells were injected into recipient WT mice. Lymph nodes, bone marrow and spleen tissues were harvested at the indicated days post-transfer (Fig. 4.7). We observed subtle but insignificant differences in the percentage of TCM at the three time points observed (Fig.

4.8A,B (top)). We failed to observe a significant difference in the CD62L MFI of CD8+ T cells at any time point, regardless of the tissue analyzed (Fig 4.8B (middle)). Interestingly, we observed an increase in the ratio of WT/IL-10KO cells in all tissues at later time points.

On day 77, there was a greater than two-fold increase in the number of WT versus IL-

10KO cells in the bone marrow and spleen. This difference was more pronounced at day

77 than day 35 but not evident at day 3 (Fig. 4.8B (bottom)), suggesting that the intrinsic capability of CD8+ T cells to produce IL-10 confers a survival advantage over time.

Furthermore, we found no difference in viability between WT and IL-10KO cells following in vitro expansion and no difference in the number of transferred cells in any tissue 3 days post-transfer (Fig. 4.9A,B), indicating that the increased ratio of WT to IL-10KO cells observed at day 77 was not due to differences in cell viability or the ability to seed SLOs following injection. Taken together, these data suggest that cell-intrinsic IL-10 by CD8+ T cells confers a survival advantage and promotes long-term persistence of memory cells.

Figure 4.7. Schematic design of adoptive transfer experiment. WT (Ly5.2) and IL-10KO (Ly5.1) CD8+ T cells were activated in vitro by αCD3/αCD28 stimulation and cultured for 5 days, as previously described. On day 5, equal numbers of WT and IL-10KO cells were co-transferred (i.p.) into WT recipients. The hi hi frequency of TCM cells (CD44 CD62L ) was analyzed in the lymph nodes, spleen and bone marrow at the indicated time points by FACS.

Figure 4.8. Cell-intrinsic IL-10 improves the persistence of central-memory CD8+ T cells. The experiment was conducted as depicted in Fig. 4.7. Data from (A) represents central-memory, effector-memory and naïve CD8+ T cells harvested from the spleen. Data from (B) represents the percentages of central-memory cells

(top), geometric mean of CD62L MFI (middle) and the ratio of WT/IL-10KO cells in each tissue (bottom) at the indicated time points. Cells are gated the live/TCRβ+/CD8+ population.

Figure 4.9. WT and IL-10KO cells exhibit similar viability and expansion pre-transfer and post-transfer. (A) Representative purity and viability of in vitro-cultured WT and IL-10KO populations prior to adoptive transfer (Fig. 4.7). (B) Numbers of total WT and IL-10KO cells seeded in the indicated tissues 3 days post- transfer.

4.3 Discussion

The differentiation of memory CD8+ T cells is dependent on a balance between T-

bet and Eomes (27, 128, 131). Both T-bet and Eomes induce the expression of the IL-2/15

receptor beta chain (CD122) early on in effector CD8+ T cells, which supports the eventual

formation of T cell memory by conferring responsiveness to the cytokines IL-2 and IL-15

(45, 70). The availability of IL-2 in both the priming and effector phases influences

memory CD8+ T cell differentiation, and IL-15 supports the maintenance of differentiated

memory T cells (291-294). Inhibition of IL-2, among other pro-inflammatory signals, or

T-bet deficiency, increases the development of KLRG1loL-7Rhi memory CD8+ T cells in

TCR-transgenic models of LCMV infection (45, 46, 128). Overall, these and other studies

81 have offered the field a model that incorporates T-box transcription factors and gamma- chain-dependent cytokines. Our understanding of the role of IL-10 in memory differentiation, however, is still in its infancy.

Several recent studies implicate IL-10 in the differentiation of CD8+ memory T

+ + cells. IL-10 derived from either CD4 T regulatory cells (TREG) or CD11c dendritic cells promotes the development and maturation of CD8+ memory precursor T cells (162, 163).

Cui et. al. demonstrated that IL-10 blockade resulted in a significantly reduced percentage of KLRG1loL-7Rhi memory CD8+ T cells in LCMV infection (132). The authors further showed that IL-10/21 signaling via STAT3 is critical for the functional maturation of memory CD8+ T cells. Importantly, STAT3-/- memory CD8+ T cells expressed significantly less Eomes, Bcl6 and a lower percentage of CD62Lhi cells than WT controls, suggesting that IL-10 and Eomes have critical roles in memory development (132). Here, we identified

IL-10 as an early target of Eomes in activated CD8+ T cells and show that Eomes and IL-

10 act independently to regulate CD62L expression. Our data are in line with a recent study demonstrating that Eomes directly binds the IL-10 promoter in CD4+ Tr1 cells and induces

IL-10 expression (280). Similarly, CCR6+ Th17 cells express high levels of both Eomes and IL-10 in experimental autoimmune encephalitis (295). In line with this, one report demonstrated that treatment of CD8+ T cells with the mammalian target of rapamycin

(mTOR) inhibitor rapamycin increased both Eomes and IL-10 expression in a model of pulmonary aspergillosis (296). A related group of studies revealed an additional link between Eomes and IL-10. Jiang et al. showed that type I IFNs, IL-2 and IL-27 induced

IL-10 expression in CD8+ T cells in a Blimp1- and Irf4-dependent manner (289). A subsequent study demonstrated that type I IFNs similarly promote Eomes expression in

82 memory CD8+ T cells in an IRF9-dependent manner (92). The correlation of Eomes expression in effector and memory CD8+ T cells with the ability of these cells to make and respond to IL-10 warrant a modified model of memory T cell differentiation which includes distinct roles for Eomes and IL-10 in a T cell-intrinsic program driving memory formation.

Exploring the role of cytokines and trophic factors that drive memory differentiation has led to an increased appreciation for the importance of tissue localization of effector T cells in their eventual differentiation to memory (72, 297). Perhaps the most prevalent concept stems from the expression of CD62L by central memory T cells with stem-like properties that sustain long-term memory (12, 298, 299). In this context, the gradual increase in CD62L expression by effector T cells, with the help of Eomes and IL-

10, could set the stage for the arrival of memory precursors to niches where they can undergo further differentiation towards central memory cells. Studies to date have reported decreased frequencies of CD62Lhi STAT3-/- memory CD8+ T cells and reduced numbers of CD44hi/CD62Lhi EKO central memory CD8+ T cells (71, 72), but have not addressed the potential for regulation of the expression levels (MFI) of CD62L. We observed that

+ Eomes deficiency reduced the MFI of CD62L to levels comparable to those in CD8 TN cells. As TN do not express Eomes, this suggests that Eomes selectively increases CD62L expression in effector cells that may be destined to become central memory CD8+ T cells.

At the resolution of an immune response, the differentiation and survival of memory CD8+

T cells may be viewed as a competitive process. In this model, CD8+ T cells compete for the memory niche in SLOs, where they receive the appropriate survival signals at the expense of competing cells. Thus, the relative expression of CD62L might influence the potential for some of the effector cells to enter secondary lymphoid tissues and receive

83 memory-promoting signals. In this way, Eomes and IL-10 may be critical for promoting and maintaining central memory CD8+ T cells.

Our in vivo data revealed that cell-intrinsic IL-10 may be required for maintaining the number of central-memory CD8+ T cells at later time points, yet this question demands further investigation. At day 3 post-transfer, we observed minimal differences in the ratio of WT to IL10KO cells in the lymph nodes, bone marrow and spleen. These ratios increased moderately at day 35 post-transfer and on day 77, we observed a greater than

1.5-fold change in the number of WT versus the number of IL-10KO cells in the lymph nodes and a greater than 2-fold change in the bone marrow and spleen. One rational for this finding is that of the cells cultured in vitro, only WT cells were exposed to IL-10. Our previous findings showed that in vitro culture of WT cells with exogenous IL-10 increased

CD62L expression over 5 days. Therefore, it is possible that the subtle increase in CD62L expression conferred on the WT cells in culture provided increased capacity for entry into lymphoid tissues. In this way, more WT cells home to these tissues and homeostatic conditions favor the persistence of these cells over time. However, no significant difference was observed in the number of cells that seeded lymphoid tissues 3 days post-transfer.

Additionally, this would not explain the progressive increase in the ratio of WT to IL-10KO cells in these tissues. If entry into secondary lymph tissues promotes a central-memory population, the IL-10KO cells that get in these tissues should persist similarly to the WT cells, even if at lower numbers. As this is not the case, it may be that cell-intrinsic IL-10 promotes a survival advantage, especially over time. Indeed, several studies have demonstrated a link between STAT3 signaling and expression of anti-apoptotic members of the Bcl-2 family (300-303). Several subsets of immune cells including macrophages,

+ DCs, TREG and B cells secrete IL-10 at levels equal to or higher than CD8 T cells in vivo

(304). Along these lines, it is possible that paracrine IL-10 from non-CD8+ T cells provides sufficient signaling to both WT and IL-10KO cells to maintain CD62L levels and that CD8+

T cell-intrinsic IL-10 provides an additional ‘boost’ which better enables these cells to persist long-term. The importance of CD8+ T cell-intrinsic IL-10 to the development of a central-memory compartment warrants further investigation.

In summary, our data propose a modified model of memory differentiation where

Eomes acts as a molecular switch in effector CD8+ T cells. As antigen levels and inflammatory stimuli decrease, Eomes expression is favored and induces IL-10. IL-10 then exerts its canonical anti-inflammatory role, harboring T cells from further inflammatory stimuli, while both Eomes and IL-10 cooperate to induce CD62L expression and enhance the in vivo persistence of a subset of CD8+ T cells. In this model, the capacity to become a central memory CD8+ T cell depends on a delicate balance of local inflammatory cues. An anti-inflammatory environment favors Eomes and IL-10 expression, which promotes

CD62L expression and confers a competitive advantage to those cells competing for the memory niche (Fig. 4.10).

Figure 4.10. Eomes and IL-10 cooperate to regulate the early expression of memory-associated genes in effector CD8+ T cells.

Chapter 5: Effector CTL Undergo a Second Wave of

Maturation in Peripheral Tissues

5.1 Introduction

Thus far, our data suggest that T-bet and Eomes have unexplored roles in several pathways, including regulating apoptosis, T cell migration, immune cell recruitment and memory differentiation. Interestingly, our microarray analysis revealed differential expression of an exhaustion profile between WT and DKO cells as well (Fig. 5.1). These findings have obvious implications in tumor immunology, as targeting exhausted T cells is a promising therapeutic approach for many cancers (305). Tox, Cblb, PTEN and FoxP1 were significantly decreased in DKO cells compared to the single knockouts and wildtype cells (Fig. 5.1). As mentioned previously, Cblb and PTEN have roles as negative regulators of T cell signaling (182, 183). Moreover, FoxP1 and Tox have both been implicated in T cell exhaustion and suppressing effector T cell function (176, 306-308). On the other hand, expression of multiple inhibitory receptors was increased in DKO cells, including Tigit,

CD30 and Lag3, along with the co-stimulatory receptor ICOS. These findings propose an interesting nexus in the push and pull effect of T-bet and Eomes in CD8+ T cell fate decisions. Whereas T-bet and Eomes promote a strong effector response in activated T cells, our findings suggest that they concurrently function to restrict excessive stimulation by inhibiting the expression of inhibitory receptors (Tigit, CD30, Lag3) and promoting the expression of negative regulators of cell signaling (Cblb, PTEN). This may offer some context into the roles of T-bet and Eomes in T cell exhaustion.

Along these lines, we sought to investigate whether DKO TILs developed a similar exhaustive profile to WT cells during an antitumor immune response. Studies have previously shown that DKO cells poorly infiltrate syngeneic B16 tumors in mice (71, 130).

This deficit was shown to be due to a lack of T-bet- and Eomes-mediated CXCR3 expression, which impaired subsequent trafficking to the tumor. Indeed, tumor infiltration by CD8+ T cells was partially abrogated in CXCR3-/- mice, albeit not to the extent that was observed in DKO mice. Even so, a small proportion of DKO CD8+ T cells successfully infiltrated the tumor tissue, suggesting that we might be able to examine whether these cells display an exhausted phenotype (71, 130). Furthermore, there is some evidence that while T-box transcription factors are critical in antitumor immune responses, their impact is influenced by the specific tumor line used. The B16 melanoma line, for example, was shown to be considerably restrictive to tumor infiltration by activated lymphocytes (309).

We investigated whether DKO cells are capable of infiltrating a distinct syngeneic tumor model – pursuant to the hypothesis that due to a lack of T-bet and Eomes expression, DKO

TILs would exhibit a less exhausted phenotype during tumor progression.

Figure 5.1. T-bet and Eomes are implicated in CD8+ T cell exhaustion.

5.2 Results

5.2.1 T-bet and Eomes are required for optimal CD8+ T cell infiltration into E.G7 tumors

To assess the contribution of CD8+ T cell infiltration to the antitumor response, we used an adoptive T cell transfer model in which TCR-transgenic CD8+ T cells recognize

b the OVA257-264 antigen presented in the context of murine H-2K (MHC I). In this context, the OVA peptide is transgenically expressed by the E.G7 mouse thymoma cell line but not by the parent EL4 cell line (Fig. 5.2A). To track antigen-specific T cell responses in our tumor model, we injected 2 x 106 naïve, CFSE-labeled OT-1 CD8+ T cells into syngeneic, recipient mice and inoculated the mice with E.G7 or EL4 tumor cells one day later. Mice that did not receive tumor injections were used as a control. We observed significant proliferation of OT-1 cells in the tumor-draining lymph node of mice injected with E.G7 cells but not in mice injected with EL4 cells or in the no tumor control. Importantly, we observed that only cells that had underwent multiple rounds of division (CFSE-negative) infiltrated the tumor whereas no tumor infiltration was observed in mice receiving EL4 cells (Fig. 5.2A). Next we wanted to assess the relative contributions of T-bet and Eomes to CD8+ T cell tumor infiltration in our tumor model. To this end, we injected E.G7 tumor cells into WT recipient mice 10 days prior to ACT to allow tumors to develop. Five days before injection, WT and DKO OT-1 cells were activated in vitro and cultured as described in the methods. OT-1 cells were injected into E.G7-bearing recipient mice on day 0 and analyzed 5 days later. We observed similar frequencies of WT and DKO OT-1 cells in the draining lymph nodes relative to endogenous CD8+ T cells (Fig. 5.2B,C). Similar to studies in the B16 melanoma model (71, 130), we observed a severe deficiency in tumor

infiltration by DKO OT-1 cells relative to the WT counterparts. Whereas WT OT-1 cells

constituted ~25% of the CD8+ TIL population on average, DKO OT-1 cells comprised less

than 2% of the total TIL population (Fig. 5.2C). These findings further support the role for

T-bet and Eomes in promoting CD8+ T cell tumor infiltration.

Figure 5.2. T-bet and Eomes are required for optimal CD8+ T cell infiltration into E.G7 tumors. (A) Naïve, CFSE-labeled WT OT-1 cells were injected into recipient WT mice. One day later, mice were injected with E.G7-OVA or EL4 tumor lines. Cell division in the TDLN and tumor was analyzed 10 days after tumor injection. The no tumor group was used as a control. Cells are gated on the CD8+/live population. (B) Naïve, CFSE-labeled WT or DKO OT-1 cells were injected into recipient WT mice, as before. One day later, mice were injected with E.G7-OVA cells. Cell division in the TDLN and tumor was analyzed 10 days after tumor injection. Cells are gated on the live population (C) Representative percentage of OT-1 cells of the total CD8+ population in the indicated tissue (n=6).

5.2.2 T-bet and Eomes are dispensable for CD8+ T cell proliferation in the draining

lymph node

Because T-bet and Eomes doubly-deficient CD8+ T cells are unable to infiltrate

tumors and potentiate an antitumor response, we next investigated whether these cells were

capable of dividing in the draining lymph node. Though we had observed similar rates of

90 proliferation between WT and DKO cells following polyclonal activation in vitro, it is possible that T-bet and Eomes play a pivotal role in promoting proliferation in vivo. To assess this, we adoptively transferred 2 x 106 naïve, CFSE-labeled WT or DKO OT-1 cells into syngeneic, recipient mice and inoculated the mice with E.G7-OVA cells 1 day later, as previously described. Tumor progression was monitored daily by caliper measurements.

Mice were euthanized, and tissues were harvested when the tumor reached 150 mm in diameter, which typically equated to day 10 post-transfer and was sufficient for optimal T cell infiltration in the case of WT T cells. We observed substantial proliferation in the tumor draining lymph node of both WT and DKO OT-1 cells, as evidenced by a successive decrease in CFSE intensity. Consistent with our previous data, only WT OT-1 cells that had underwent multiple rounds of cell division were found in the tumor. DKO OT-1 cells did not infiltrate the tumor, but endogenous, wildtype CD8+ T cells were found in tumors of all mice, indicating a T cell-intrinsic trafficking defect in DKO cells (Fig. 5.3A).

Furthermore, we observed no difference in the number of WT and DKO OT-1 cells in the draining lymph node at the time of harvest, but there was an approximate 20-fold increase in the number of WT TILs compared to DKO cells (Fig. 5.3B). To assess whether WT and

DKO cells were actively proliferating, we stained OT-1 cells from the draining lymph nodes with the proliferation marker Ki-67. We observed that a higher percentage of WT cells were proliferating compared to DKO cells, however these differences were not significant due to the low number of replicates (Fig. 5.3C). Together these results suggest that CD8+ T cells proliferate in an antigen-specific manner independent of cell-intrinsic T- bet and Eomes expression.

Figure 5.3. T-bet and Eomes are not required for CD8+ T cell proliferation in the draining lymph node. Naïve, CFSE-labeled WT or DKO OT-1 cells were injected into recipient WT mice, as before. One day later, mice were injected with E.G7-OVA cells. Cell division in the TDLN and tumor was analyzed 10 days after tumor injection. (A) Representative FACS plots demonstrating OT-1-specific cell division in the TDLN and tumor. Cells are gated on the CD8+/live population. (B) Comparison in the number of WT and DKO OT-1 cells in the indicated tissues at day 10 post-transfer (n=6). (C) Representative percentages of Ki-67hi OT-1 cells as compared to endogenous CD8+ T cells in the TDLN (n=2).

5.2.3 CD8+ T cells undergo a second wave of maturation in the tumor marked by T- bet upregulation.

Because of the severe homing deficiency of DKO T cells to the tumor in our model, we were unable to address the original hypothesis relating to the exhaustion of these cells compared to WT TILs. However, in looking further at the phenotype of WT and DKO cells in lymphoid tissues, we observed differential expression of cytokines and inhibitory receptors. As expected, DKO cells exhibited a severe deficiency in IFNɣ secretion following ex vivo re-stimulation. However, both WT and DKO cells expressed TNFα at similar levels, suggesting that T-bet and Eomes are dispensable for some effector functions

(Fig. 5.4A). Expression levels of the inhibitory receptors Tim-3 and PD-1 were comparable between the genotypes, but DKO cells exhibited an increase in the expression of Lag3 relevant to WT cells, corroborating our microarray data (Fig. 5.1, 5.4B). These data suggest that T-bet and Eomes may contribute to the exhaustion profile by preventing expression of inhibitory receptors in CD8+ T cells. On the other hand, several molecules were downregulated specifically in DKO cells relative to single knockouts and WT cells per our microarray but were not examined in our model (Fig. 5.1). Investigation into the expression of Tox, Pten, Foxp1 and Cblb in DKO cells is warranted.

Figure 5.4. T-bet and Eomes regulate cytokine production and the expression of inhibitory receptors in vivo. Naïve, CFSE-labeled WT or DKO OT-1 cells were injected into recipient WT mice, as before. One day later, mice were injected with E.G7-OVA cells. Mice were euthanized and cells were harvested from the indicated tissues at day 10 and analyzed by FACS. Cells are gated on live/CD8+ cells. (A) Expression of the indicated cytokines relative to cell division in the draining lymph node of E.G7-bearing mice. Cells were harvested from the draining lymph node and re-stimulated with PMA and ionomycin ex vivo and analyzed for IFNɤ and TNFα expression. (B) Representative histograms comparing expression levels of the indicated inhibitory receptors on WT or DKO cells in the spleens of E.G7-bearing mice.

Upon further analysis of T-bet and Eomes expression levels in WT OT-1 cells in the draining lymph node and tumor, we observed a striking yet consistent increase in T-bet levels in the tumor tissue relative to the draining lymph node. T-bet expression increased as cells divided, but the peak of T-bet expression was noticeably higher in the tumor than the lymph node (Fig. 5.5A). In comparing the divided out (CFSE-low) populations in the lymph node and tumor, we consistently found that T-bet MFIs were several orders of magnitude greater in tumor tissues versus the lymph node. Notably, this tissue-specific increase was evident in both donor OT-1 TILs as well as endogenous TILs (Fig. 5.5B).

This equated to a roughly 2.5-fold increase in T-bet levels between CD8+ T cells in the tumor and draining lymph node, and though Eomes expression increased moderately, T- bet was expressed at a significantly higher level in the tumor than was Eomes (Fig. 5.5C).

To confirm that the tissue-specific increase in T-bet expression was not due to a global increase in transcription in TILs, we analyzed the expression other transcription factors that regulate CD8+ T cell effector and memory responses. In contrast to T-bet, Irf4, Tcf1 and Blimp-1 expression appeared lower in TILs versus cells in the TDLN. Notably, Tcf1hi and Tcflo populations were clearly distinct in the TDLNs and both populations infiltrated the tumor (Fig. 5.6). Surprisingly, the Bcl6 MFI was ~1.25-fold higher in the tumor than the TDLN, a finding that warrants further investigation (Fig. 5.6). Our data suggest that

CD8+ TILs undergo an additional wave of maturation in the tumor site, marked by a secondary increase in T-bet expression. These findings represent a novel phenomenon in which tissue-specific signals regulate the expression of master regulatory transcription factors in T cells during an immune response. Importantly, because we observed

94 differences in T-bet expression in T cells in distinct tissues of the same mouse, these studies could be conducted in WT mice alone, without necessitating the use of knockout mice.

Figure 5.5. CD8+ T cells undergo a second wave of maturation in the tumor marked by T-bet upregulation. Naïve, CFSE-labeled WT OT-1 cells were injected into recipient WT mice, as before. One day later, mice were injected with E.G7-OVA cells. Cell division in the TDLN and tumor was analyzed 10 days after tumor injection. (A) Levels of T-bet and Eomes expression relative to cell division in the TDLN and tumor. Cells are gated on the CD8+/live population. (B) Representative FACS plots comparing median MFI values of T- bet and Eomes in OT-1 and endogenous CD8+ T cells (n=6). (C) Ratio of the indicated transcription factor expression between the tumor and draining lymph node (n=6).

Figure 5.6. Differential expression of transcription factors in CD8+ T cells in the draining lymph node and tumor. Naïve, CFSE-labeled WT OT-1 cells were injected into recipient WT mice, as before. One day later, mice were injected with E.G7-OVA cells. Cells were harvested 10 days after tumor injection and stained for expression of the indicated transcription factors relative to cell division by FACS. Cells are gated on the CD8+/live population.

5.2.4 T-bet levels are increased in inflamed peripheral tissues during an infectious challenge

The above findings suggest a tumor-specific increase in T-bet expression in CD8+

TILs in a murine model of lymphoma. One of the obvious concerns with using the E.G7 line is the expression of a highly immunogenic transgene, resulting in an artificial and poorly translatable tumor model. In this context, we utilized our Leishmania major infection model (as previously described) to investigate whether CD8+ T cells infiltrating infected tissues exhibited a similar upregulation in T-bet expression when compared to the draining lymph nodes. To this end, we injected wildtype mice with 1 x 105 L. major parasites in the ear and footpad of WT BL/6 mice. Inflamed lesions were measured at regular intervals and mice were euthanized 4 weeks post-injection. Infected ear, footpad and draining lymph nodes were harvested and analyzed for immune cell infiltrates by flow cytometry. We observed an increased percentage of T-bethi CD8+ T cells in infected ear tissues when compared to the draining lymph node. However, this finding was tissue- specific, as we observed negligible T-bet staining in CD8+ T cells from infected footpads

(Fig. 5.7A). In line with these findings, we observed increased T-bet MFI levels in ear tissues of infected mice when compared to the draining lymph nodes (Fig. 5.7B). Again, this difference was only evident in analyzing infected ear tissues but was significant over multiple replicates (Fig. 5.7C). Taken together, our findings suggest that distinct tissue- specific signals in peripheral tissues are capable of selectively initiating a second wave of

T-bet upregulation, during both tumor and infectious disease challenges. This is an unappreciated paradigm in tissue immunity and may contribute to the development of tissue-resident memory. In this scenario, the tissue-derived signals would be limiting T-bet and Eomes expression, as these transcription factors are marginally expressed in TRM.

Whether transition to a resident-memory phenotype is influenced by tissue-derived signals warrants additional investigation.

Figure 5.7. T-bet expression is increased in CD8+ T cells infiltrating peripheral tissues during infection with L. major. WT mice were infected with 1 x 105 L. major parasites in the footpad or ear. One month later, footpad, ear and lymph nodes were collected and analyzed for expression of T-bet. (A) FACS plots demonstrating T-bet levels in the indicated tissues relative to CD44 expression. Cells are gated on the live/CD8+/TCRβ+ population. (B) Representative histogram plots comparing median T-bet MFI values between the infected tissue and draining lymph node. (C) Comparison of average T-bet MFI values between the ear and draining lymph node of infected mice (n=4).

5.3 Discussion

Our data corroborate the role of T-bet and Eomes in promoting CD8+ T cell tumor infiltration. Studies have demonstrated significant but not total impairment of T cell infiltration into B16 tumors in mice lacking T-bet and Eomes (71, 130). Our data suggest that DKO CD8+ T cells are almost completely absent from tumors in a unique model. It is

97 difficult to determine whether the few DKO cells present in the tumor are genuine knockout cells, experimental artifacts or escape variants. Our data conclusively demonstrate that neither T-bet nor Eomes are required for antigen-specific proliferation in the draining lymph node during an immune response. Due to the low number of replicates (n=2), we cannot make a conclusive argument in analyzing the differences in proliferation between

WT and DKO cells. Furthermore, the time of harvest (day 10) represents a snap shot of the proliferative environment during the antitumor response. In comparing differences in proliferation, it is possible that mouse-to-mouse variability affects the rate of circulation of naïve T cells into the draining lymph node. Moreover, one cannot rule out possible differences in the kinetics of WT and DKO proliferation, especially in the context of an in vivo tumor response.

Because the population of DKO TILs was virtually nonexistent, we could not study the relative contributions of T-bet and Eomes to T cell exhaustion in our tumor model. We did, however, confirm that WT and DKO cells exhibit differential cytokine (IFNɣ) and inhibitory receptor expression (Lag3) in lymphoid tissues during the antitumor response

(Fig. 5.4). Although PD-1 is used as a canonical marker of exhaustion, we did not observe any difference in its expression between WT and DKO cells in the microarray or at the protein level by flow cytometry. Interestingly, our array data demonstrate decreased expression of transcription factors associated with negative signaling events and exhaustion in DKO cells. Along with increased CD30 and Icos expression in DKO cells, downregulation of these signaling molecules may promote a robust effector phenotype that is more resistant to exhaustion than cells expressing T-box transcription factors.

Importantly, the expression of Lag3 is associated with T cell activation, as is Icos (310).

While expression of these surface receptors is transient, Tox and Cblb expression strongly correlates with T cell dysfunction (183, 306, 307). Subsequent analysis of the expression of these markers and their functional role in DKO cells may provide insight into molecular mechanisms of T cell exhaustion as they pertain to T-bet and Eomes.

Interestingly, our gene expression data suggest that while T-bet may repress the expression of exhaustion markers, Eomes induces the expression of Tigit, Icos, CD30 and

Lag3 (Fig. 5.1). This cluster is interesting because though Tigit and Lag3 are inhibitory receptors that and currently targets of checkpoint blockade therapy, Icos and CD30 are co- stimulatory. This suggests a dual role for Eomes in activated CD8+ T cells, where it functions to both potentiate and antagonize T cell signaling. Discerning the relative contribution of Eomes to these contrasting pathways warrants further investigation. Along these lines, our array analysis suggests that beyond acutely activated CD8+ T cells, Eomes has a functional role in T cell exhaustion. In a study comparing acute versus chronic LCMV infection, EomeshiPD-1hi exhausted T cells represented the majority population, whereas

T-bethiPD-1int cells represented a much smaller, but highly proliferative population specifically during in the chronic state (311). In a separate study, HIV patients displayed an exhausted CD8+ T cell profile characterized by high Eomes expression and low T-bet expression, but this phenotype was absent in acutely infected CMV patients. Importantly, the Eomeshi population displayed elevated expression of multiple inhibitory receptors

(179). Our microarray data suggest that strong TCR stimulation early upon activation promotes varying levels of negative feedback, and Eomes may play a pivotal role. Whereas this role for Eomes in dampening T cell signaling early upon activation may function to limit excessive differentiation, reinforce its own expression or lend to memory

99 differentiation, this may be an unintended consequence of increased Eomes expression in an environment conducive to T cell exhaustion.

Much of the current research in immuno-oncology focuses on the immunosuppressive mechanisms elicited by tumors (iRs, cytokines, recruitment of suppressive immune cells) but the transcriptional network underlying effector TIL function is less well studied. Our model represents a tumor microenvironment favoring a T cell- mediated response, where cytotoxic TILs are not yet dysfunctional or exposed to a severely exhaustive milieu. Though T-box transcription factors have been analyzed in TIL populations, no studies have examined the relative expression of these transcription factors with regards to CD8+ T cells in the draining lymph node versus the tumor. Our in vivo data reveal that T-box transcription factors are regulated by tissue-specific signals in CD8+ TILs during an antitumor response. Furthermore, we demonstrate that T-bet undergoes a secondary wave of expression in CD8+ TILs relative to the draining lymph node, while

Eomes levels were moderately increased. Moreover, we did not observe an upregulation in other CD8+ T cell-defining transcription factors, such as Irf4, Tcf1 and Blimp1, suggesting that tissue-specific signals selectively enhance the expression of transcription factors that promote effector functions.

Because T-bet is upregulated directly through TCR stimulation and IL-12 following antigen presentation by APCs, it follows that T-bet would undergo a second wave of expression in response to either stimulus in the tumor, where antigen levels and cytokine concentrations can be high (41, 46, 63, 69, 79, 86, 296, 312). With respect to TCR stimulation, high levels of tumor antigen, specifically mutated antigens, correspond with increased CD8+ T cell-dependent tumor rejection and patient survival (313-315).

100

Regarding IL-12, levels of this cytokine have been shown to be critical in driving a successful T cell-mediated antitumor immune response (316). Along these lines, IL-12 is being actively researched as a pro-stimulatory adjuvant in several immunotherapies including a new generation of CAR-T therapy (317, 318). We are testing the hypothesis that TCR/antigen interactions and/or IL-12 signals in the tumor microenvironment drive further T-bet expression in CD8+ TILs. These sub-aims are being actively researched.

Regardless of the mechanism of induction, the increase in T-bet expression may have functional consequences in terms of cytotoxicity and/or enhanced IFNɣ secretion. In this context, our studies have implications in tumor immunotherapies that aim to further stimulate TIL activity in the tumor. However, whether these T-bethi TILs are actually more cytotoxic and enhance the antitumor response remains to be determined. It is unclear whether T-bethi TILs are those that are in a transitory phase towards an exhausted phenotype. As they are being chronically stimulated through the TCR, it is likely that this population will become functionally exhausted. T-bethi cells have been shown to convert to an Eomeshi phenotype during chronic viral infection, displaying characteristics of severe exhaustion. However, the T-bethi population itself appears less exhausted and maintains functioning antigen-specific T cells (311, 319). Therefore, from an immunotherapeutic standpoint, it may be beneficial to aim to selectively increase T-bet expression in T-betlo/T- betint TILs to rescue the exhausted phenotype.

Together our data provide evidence that T-bet undergoes a secondary wave of expression in CD8+ TILs during a tumor response. The source and cause of this secondary upregulation in T-bet expression is unclear but suggests that the tissue-specific signals from immune cells or persistent antigen signaling enhances effector functions in the tumor. The

101 finding that signals stemming from peripheral tissues augment immune responses and modulate the transcriptional network in these cells warrants further investigation and needs to be studied in different infection and tumor models and in distinct tissue environments.

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Chapter 6: Conclusions, Perspectives and Future Directions

6.1 Conclusions

Our results provide important insight into novel roles for T-bet and Eomes in regulating CD8+ T cell effector responses following activation. Data from our gene expression analysis revealed that T-bet and Eomes either cooperatively or independently regulate several genes involved in T cell responses including positive and negative mediators of cell signaling as well as genes involved in cell migration, apoptosis, memory differentiation and effector function. Pathway analysis revealed several gene clusters that were previously unknown to be regulated by T-bet or Eomes. Moreover, our analysis provides strong evidence supporting a role for both T-bet and Eomes in repressing type 2, type 17 and regulatory T cell differentiation in CD8+ T cells. Several studies have shown that T-bet inhibits differentiation to Th2 and Th17 subsets in favor of Th1 cells (81, 82).

We found that Eomes, in addition to T-bet, represses transcription factors associated with these subsets, including Gata3, Rorc, Batf, Ahr, and c-Maf. Similarly, T-bet and Eomes cooperate to inhibit transcription of the cytokines associated with these subsets, which is likely secondary to repression of these transcription factors. These data suggest that similar to CD4+ T cells, T-box transcription factors function to prevent alternate differentiation states of CD8+ T cells.

We then demonstrated a previously unappreciated role for Eomes in promoting the early expression of memory genes in activated CD8+ T cells. Our data warrant a modified model of early CD8+ T cell memory differentiation that involves an Eomes-IL-10-CD62L axis. In this context, Eomes drives IL-10 production in activated CD8+ T cells, and both

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Eomes and IL-10 promote CD62L expression. Eomes has been shown to directly induce

IL-10 production in Tr1 cells and IL-10 positively influences the development of memory

CD8+ T cells in several models (132, 162, 163, 280). However, a link between Eomes, IL-

10 and CD62L had not been demonstrated in CD8+ T cells. We propose that the Eomes/IL-

10-driven increase in surface expression of CD62L enhances the probability of successful interactions with endothelial ligands and transmigration into SLOs. Furthermore, we show that CD8+ T cell-intrinsic IL-10 confers a survival advantage in vivo. In addition to this newfound loop, Eomes induces the early expression of Bcl6 and Ly6c, both of which have been implicated in memory differentiation. These data suggest that Eomes imparts an early program of memory precursor differentiation and lends support to the asymmetric differentiation model, where the local inflammatory milieu supports Eomes expression in lieu of T-bet, and Eomes imparts a transcriptional profile favoring central memory differentiation.

Lastly, our data show that CD8+ TILs undergo a second wave of maturation at the tumor, as evidenced by increased expression of T-bet. This finding suggests that the expression level of transcription factors during an effector response oscillates, in response to local, tissue-specific signals. Yet whether the secondary wave of T-bet expression is induced through TCR signaling and/or cytokines is unclear. IL-12 is a key regulator of antitumor responses and its expression in the tumor microenvironment is associated with positive clinical outcomes (316, 320). Similarly, TCR/antigen interactions in the tumor drive CTL-mediated cytotoxicity against target cells and the extent of TIL infiltration positively correlates with patient survival (313-315). Both IL-12 and TCR signaling drive

T-bet expression in effector CD8+ T cells. Our data warrant further study into whether TCR

104 and IL-12 signaling contribute to enhanced CD8+ TIL function in the tumor. A secondary wave of CD8+ T cell-intrinsic T-bet expression is a novel phenomenon that is of clinical relevance in immuno-oncology. Indeed, higher numbers of T-bet-expressing TILs correlates with increased patient survival (321-323). However, studies have not addressed the extent of T-bet expression in the tumor relative to the draining lymph node and whether the level of expression correlates with tumor progression.

6.2 Outstanding Questions and Future Directions

6.2.1 Are the effects of T-bet and Eomes direct or indirect?

As mentioned earlier, our data that T-bet and Eomes regulate distinct pathways in activated CD8+ T cells fails to address whether these are direct or indirect effects. Due to the complexity of the transcriptional network in differentiating CD8+ T cells, it is likely that the absence of T-bet and/or Eomes results in both. Prevention of Tc2 and Tc17 differentiation is likely mediated through the coordinated inhibition of lineage-defining transcription factors by T-bet/Eomes, which in turn regulate other TFs and cytokines to support differentiation. This has been demonstrated in CD4+ helper T cell subsets (GATA3,

Rorc). In the case of GATA3, inhibition was shown to be directly mediated by T-bet (81).

On the other hand, inhibition of Rorc is indirectly mediated by T-bet binding to RUNX1

(82). Furthermore, dysregulated cytokine or chemokine expression in cells lacking T-bet and/or Eomes may influence subsequent differentiation. In depth studies aiming to characterize the specific DNA:protein interactions at regulatory sites and promoter regions of these genes will help clarify the direct roles of T-bet/Eomes in controlling CD8+ T cell

105 subset differentiation as well as how they regulate the genes and pathways highlighted in our microarray analysis.

6.2.2 Are the novel targets of T-bet and Eomes expressed at the protein level?

As an obvious follow up to the previous question, we want to investigate whether the novel targets of T-bet and Eomes that came up in our microarray analysis are relevantly expressed at the protein level. That is, do knockout cells or over-expressing cells demonstrate a significant change in expression compared to controls? It is likely that many of the newfound targets are not regulated (directly or indirectly) by T-box proteins (false positives, background noise) and that several of the described pathways are regulated independently of T-bet and Eomes. However, because of the extent to which T-bet expression influences CD4+ T cell differentiation, it remains likely that T-bet and Eomes contribute to maintaining Tc1 lineage specificity while preventing alternate differentiation of CD8+ T cells. Similarly, several novel pathways revealed in our analysis implicate T- box transcription factors as important regulators of T cell migration, apoptosis, steroid signaling and Rap1 signaling. These gene expression data may have important implications in T cell biology and warrant further investigation.

6.2.3 How are T-bet levels increased in peripheral tissues during the immune response?

The classic model of T-bet upregulation involves dual signaling through the TCR with concurrent IL-12 signaling (27, 129). Therefore, we want to investigate whether

TCR/antigen interactions or local IL-12 signaling in the tumor microenvironment regulates

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T-bet expression. We and others have observed that strong TCR signaling rapidly induces

T-bet expression in CD8+ T cells both in vitro and in vivo (46, 69, 79, 84, 312). Therefore, it is likely that TCR/antigen interactions drive subsequent T-bet expression in the tumor microenvironment. To this end, we will utilize our E.G7/OT-1 tumor model, as strong antigen stimulation will better enable assessment of changes in T-bet expression. To assess differences in the draining lymph node and tumor, we will inject an αMHC-I antibody 3 days after OT-1 transfer. This will allow the initial priming phase of OT-1 cells in the draining lymph node and subsequent trafficking to the tumor. On day 3, after the OT-1 cells have infiltrated the tumor, further TCR/antigen interactions will be blocked. If MHC-

I blockade restores T-bet levels in OT-1 TILs relative to the lymph node when compared to untreated mice, we can conclude that antigen drives secondary T-bet upregulation in the tumor. If we observe that T-bet levels remain high in OT-1 TILs following MHC-I blockade, this would suggest that antigen is unlikely to be causing T-bet upregulation in the tumor. Importantly, we would need to optimize the timing of antibody administration as it relates to sufficient OT-1 tumor infiltration. Similarly, it is possible that a threshold of

T-bet expression is required before CD8+ T cells traffic to the tumor. In this case, once T cells become T-bethi in the lymph node, they immediately traffic to the tumor. To assess this, we would need to sequester primed T cells in the draining lymph node and tumor after sufficient infiltration. Using a drug like FTY720, which sequesters lymphocytes in lymph tissues, we would be able to observe whether CD8+ T cells in the lymph node attain a similar level of T-bet expression to those in the tumor by preventing lymph node egress. If

CD8+ T cells in the draining lymph node achieve equivalent levels of T-bet expression as do CD8+ TILs, we can conclude that instead of the tumor inducing a second wave of T-bet

107 expression, T cells expressing the highest level of T-bet immediately leave the lymph node and traffic to the tumor.

In addition to TCR signals, T-bet is robustly induced through concurrent IL-12 signaling (46, 79, 84, 89). Tumor-infiltrating DCs secrete IL-12 potently to induce antitumor responses, and are associated with increased patient survival (324). Along these lines, we will investigate the hypothesis that local IL-12 levels in the tumor microenvironment mediate the second wave of T-bet upregulation in CD8+ TILs. To this end, we will employ our E.G7-OVA/OT-1 tumor model in WT and IL-12p40KO recipient mice, which are incapable of synthesizing IL-12. T-bet expression levels will be compared between the draining lymph node and tumor of E.G7-bearing WT and p40KO mice. If we observe that the level differential T-bet expression between TILs and lymph node CD8+ T cells in the p40KO mice, this would suggest that IL-12 is critical in inducing a second wave of T-bet in the tumor. To confirm this result, we would introduce exogenous IL-12 directly in the tumor to ensure that it is a tumor-specific response and not mediated by a global deficiency in IL-12. In the case that our findings remain inconclusive, and we find that there is a secondary upregulation of T-bet in tumors that is occurring independently of the

TCR or IL-12, we will explore alternate hypotheses. Type I IFNs have been shown to synergize with CD27 stimulation to increase T-bet and Eomes expression in CD8+ T cells

(325). Furthermore, IFNɣ signaling has been shown to initiate the first wave of T-bet induction in CD4+ Th1 cells, though this has not been demonstrated in CD8+ T cells (326).

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6.2.4 What is the functional consequence of increased T-bet in CD8+ TILs?

Studies have demonstrated that T-bethi CTLs are more cytotoxic than their T-betlo counterparts (65, 84). The finding that CD8+ T cells experience a second wave of T-bet upregulation in tumors suggests that these TILs acquire enhanced cytotoxicity as a result.

Along these lines, it will be interesting to compare the cytotoxic capacity of CD8+ T cells from draining lymph nodes to CD8+ TILs in the same animal. Comparing the cytolytic activity of T-bethi CTLs and T-betint OT-1 cells directly ex vivo will shed light onto a functional role for the secondary wave of T-bet expression in CD8+ TILs. Our model is ideal for this study, because TILs are harvested and analyzed before progression to an exhausted phenotype. We propose that enhanced T-bet expression in acutely cytotoxic

TILs drives optimal antitumor immune responses. In this context, T-bet expression in peripheral tissues during an immune response is transient. Effector CD8+ T cells responding to acute viral infections express high levels of T-bet and actively target infected cells. If the infection becomes chronic, CD8+ TILs are exposed to chronic antigen stimulation and signals promoting exhaustion, which alters T-bet expression in antigen- specific CD8+ T cells, as has been cited by others (179, 216, 327). Along these lines however, intermediate to high levels of T-bet expression in exhausted CD8+ T cells is associated with enhanced protection, suggesting that the maintenance of intermediate T- bet levels is important in containing chronic infection and cancers. After the infection or cancer is cleared, CD8+ T cells persist long-term in the peripheral tissue, as tissue-resident memory cells. These cells persist independently of T-bet, and it remains to be determined whether they re-express T-bet upon reinfection to enhance responsiveness and if this is controlled by local tissue signals.

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In conclusion, this study sheds light on a modified model of CD8+ T cell effector and memory differentiation that is controlled by T-box transcription factors. The conventional view of CD8+ T cell differentiation dictates that T-bet defines the early fate specificity of effector T cells, while Eomes expression associates with the later differentiation of CD8+ T cells. Here we show that Eomes imparts an early differentiation program in memory precursors upon activation while T-bet expression is regulated transiently in peripheral tissues later on in an immune response (Fig. 6.1).

Figure 6.1. General schematic outline of thesis aims.

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