Expression of Pd-1, Cd160 and 2B4 on Cd8 T Cells During HIV Infection: Markers of Exhaustion?

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Publicly Accessible Penn Dissertations

2015

Expression of Pd-1, Cd160 and 2b4 on Cd8 T Cells During HIV infection: Markers of Exhaustion?

Carolina Pombo University of Pennsylvania, [email protected]

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Part of the Allergy and Immunology Commons, Immunology and Infectious Disease Commons, Medical Immunology Commons, and the Virology Commons

Recommended Citation Pombo, Carolina, "Expression of Pd-1, Cd160 and 2b4 on Cd8 T Cells During HIV infection: Markers of Exhaustion?" (2015). Publicly Accessible Penn Dissertations. 1951. https://repository.upenn.edu/edissertations/1951

This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/1951 For more information, please contact [email protected]. Expression of Pd-1, Cd160 and 2b4 on Cd8 T Cells During HIV infection: Markers of Exhaustion?

Abstract HIV infection is typically associated with dysfunction of the immune system. Evidence indicates that CD8 T-cells are crucial in the fight against HIV, but with disease progression CD8 T-cells become functionally exhausted rendering them unable to control viral replication and spread. Unlike chronically infected individuals (CP), HIV elite controllers (EC) retain CD8 T-cell polyfunctionality and killing function. These characteristics have been linked to the ability of EC to suppress viral replication to undetectable levels without therapy intervention. It remains unclear whether EC manifest T-cell exhaustion similar to CP, and whether exhaustion level measured in blood is representative of that in lymphatic tissues, a site of persistent viral replication. Current antiretroviral therapies successfully reduce viral replication to undetectable levels in blood, but fail to eliminate the viral reservoir within lymph nodes (LN), highlighting the importance in developing means to reinvigorate immune responses in these tissues.

To date, studies focusing on T-cell exhaustion use a lack of IL-2, IFNγ and TNF together with co- expression of inhibitory receptors to define exhausted populations. However, these studies fail to address conflicting data on the oler of these receptors as markers of activation and their involvement in cytolytic activity, a known correlate of protection against HIV in elite controllers. To address this, we assembled a cohort of EC, CP and healthy individuals and simultaneously measured expression PD-1, Lag-3, CD160 and 2B4, cytokines IFNγ and TNF, and cytolytic molecule perforin. We also compared CD8 T-cell exhaustion in blood and LN in a cohort of HIV+ individuals on and off ART.

We report that EC have a high proportion of potentially exhausted (PD1+CD160+2B4+) HIV-specific CD8 -T cells comparable to that in CP, a population also present in HIV+ LN on and off ART. However, EC also harbor a population of HIV-specific CD160+2B4+ CD8 -cellsT associated with perforin not commonly present in CP. This indicates that coexpression of CD160 and 2B4 delineates a population of cytolytic CD8 T-cells important for the control of HIV in blood. However this association is not present in LN CD8 T-cells indicating differential regulation of cytolytic factors within these tissues.

Degree Type Dissertation

Degree Name Doctor of Philosophy (PhD)

Graduate Group Cell & Molecular Biology

First Advisor Michael R. Betts

Keywords CD8 T cells, HIV, Inhibitory Receptors, T cell Exhaustion

Subject Categories Allergy and Immunology | Immunology and Infectious Disease | Medical Immunology | Microbiology | Virology

This dissertation is available at ScholarlyCommons: https://repository.upenn.edu/edissertations/1951 EXPRESSION OF PD-1, CD160 AND 2B4 ON

CD8 T CELLS DURING HIV INFECTION: MARKERS OF EXHAUSTION?

Carolina Pombo

A DISSERTATION

Cell and Molecular Biology

Presented to the Faculties of the University of Pennsylvania

Partial Fulfillment of the Requirements for the

Degree of Doctor of Philosophy

2015

Supervisor of Dissertation ______Michael R. Betts, Ph.D, Associate Professor of Microbiology

Graduate Group Chairperson ______Daniel S. Kessler, Ph.D, Associate Professor of Cell and Developmental Biology

Dissertation Committee E. John Wherry, Ph.D, Associate Professor of Microbiology Ronald G. Collman, MD, Professor of Medicine James A. Hoxie, MD, Professor of Medicine Daniel E. Kaufmann, MD, Associate Professor (Ragon Institute of MGH, MIT and Harvard)

EXPRESSION OF PD-1, CD160 AND 2B4 ON

CD8 T CELLS DURING HIV INFECTION: MARKERS OF EXHAUSTION?

2015

Carolina Pombo

This work is licensed under the Creative Commons Attribution- NonCommercial-ShareAlike 3.0 License

To view a copy of this license, visit http://creativecommons.org/licenses/by-ny-sa/2.0/ Dedication

I dedicate this thesis to my parents, Sergio and Omayra, and to my siblings and their families, for their love, support and unwavering believe in me through out the course of my graduate studies. I love you all and I am grateful to have you in my life. I also dedicate this work to my grandparents, Alicia de Pombo and Julio Cesar Gonzalez, you are always in my heart and your love keeps me going.

iii

ACKNOWLEDGMENT

I would like to thank my thesis mentor, Michael R. Betts, for his guidance and support during my time in his laboratory. I would also like to acknowledge members of my thesis committee for their helpful discussions through out my time in graduate school.

Furthermore, I would also like to thank past and present members of the Betts lab for their scientific and emotional support through out the years, especially Jay Gardner,

Danielle Haney and Morgan Reuter. Finally, I want to thank the EE Just Biomedical society and my friends outside of lab, specifically Ileana Pazos and Arielle Glatman-

Zaretsky for providing me with much needed life outside of lab.

ABSTRACT

EXPRESSION OF PD-1, CD160 AND 2B4 ON CD8 T CELLS DURING

HIV INFECTION: MARKERS OF EXHAUSTION?

Carolina Pombo

Michael R. Betts

HIV infection is typically associated with dysfunction of the immune system.

Evidence indicates that CD8 T-cells are crucial in the fight against HIV, but with disease progression CD8 T-cells become functionally exhausted rendering them unable to control viral replication and spread. Unlike chronically infected individuals (CP), HIV elite controllers (EC) retain CD8 T-cell polyfunctionality and killing function. These characteristics have been linked to the ability of EC to suppress viral replication to undetectable levels without therapy intervention. It remains unclear whether EC manifest

T-cell exhaustion similar to CP, and whether exhaustion level measured in blood is representative of that in lymphatic tissues, a site of persistent viral replication. Current antiretroviral therapies successfully reduce viral replication to undetectable levels in blood, but fail to eliminate the viral reservoir within lymph nodes (LN), highlighting the importance in developing means to reinvigorate immune responses in these tissues.

To date, studies focusing on T-cell exhaustion use a lack of IL-2, IFNγ and TNF together with co-expression of inhibitory receptors to define exhausted populations.

However, these studies fail to address conflicting data on the role of these receptors as

markers of activation and their involvement in cytolytic activity, a known correlate of protection against HIV in elite controllers. To address this, we assembled a cohort of EC,

CP and healthy individuals and simultaneously measured expression PD-1, Lag-3,

CD160 and 2B4, cytokines IFNγ and TNF, and cytolytic molecule perforin. We also compared CD8 T-cell exhaustion in blood and LN in a cohort of HIV+ individuals on and off ART.

We report that EC have a high proportion of potentially exhausted

(PD1+CD160+2B4+) HIV-specific CD8 T-cells comparable to that in CP, a population also present in HIV+ LN on and off ART. However, EC also harbor a population of

HIV-specific CD160+2B4+ CD8 T-cells associated with perforin not commonly present in CP. This indicates that coexpression of CD160 and 2B4 delineates a population of cytolytic CD8 T-cells important for the control of HIV in blood. However this association is not present in LN CD8 T-cells indicating differential regulation of cytolytic factors within these tissues.

TABLE OF CONTENTS

ABSTRACT ...... V

LIST OF FIGURES...... X

CHAPTER 1: INTRODUCTION ...... 1

Pathogenesis of the Human Immunodeficiency Virus ...... 1

Innate Immunity and HIV Infection...... 4

Adaptive Immune Responses and HIV Infection ...... 6

Humoral Immunity to HIV ...... 6

HIV-Specific CD4 T-cells ...... 7

HIV-specific CD8 T-cells...... 8

T-cell Exhaustion ...... 10

Phenotypic markers of T-cell exhaustion ...... 12

PD-1 ...... 13

CD160...... 14

2B4...... 15

LAG-3...... 16

vii

THESIS GOALS...... 17

CHAPTER 2: ELITE CONTROLLERS EXPRESS MORE CD160 AND LESS PD-1

THAN CHRONIC PROGRESSORS...... 19

SUMMARY...... 19

INTRODUCTION ...... 20

MATERIALS AND METHODS...... 22

DISCUSSION...... 27

CHAPTER 3: CO-EXPRESSION OF CD160 AND 2B4 IS ASSOCIATED WITH

PERFORIN EXPRESSION IN VIRUS-SPECIFIC CD8 T-CELLS ...... 35

SUMMARY...... 35

INTRODUCTION ...... 36

MATERIALS AND METHODS...... 38

RESULTS...... 39

DISCUSSION...... 44

viii

CHAPTER 4: EXPRESSION OF INHIBITORY RECEPTORS IN HIV+ LYMPH

NODES IN CHRONIC PROGRESSORS AND SUBJECTS ON

ANTIRETROVIRAL THERAPY...... 55

SUMMARY...... 55

INTRODUCTION ...... 56

MATERIALS AND METHODS...... 60

RESULTS...... 63

DISCUSSION...... 70

CHAPTER 5: DISCUSSION...... 86

BIBLIOGRAPHY...... 90

LIST OF FIGURES

Figure 1: Flow cytometry gating scheme...... 30

Figure 2: Representative flow cytometry lots of Individual expression of inhibitory

receptors PD-1, Lag-3, CD160 and 2B4...... 31

Figure 3: Individual expression of PD-1, Lag-3, CD160 and 2B4 on total CD8 T-

cells ...... 32

Figure 4: Individual expression of PD-1, Lag3, CD160 and 2B4 on naïve and

memory CD8 T-cells...... 33

Figure 5: PD-1, Lag-3, CD160 and 2B4 coexpression patterns on total and memory

CD8 T-cells...... 34

Figure 6: PD-1, Lag-3, CD160 and 2B4 expression on HIV and EBV-specific CD8 T-

cells...... 47

Figure 7: Comparison between the proportion of memory, HIV and EBV-specific

CD8 T-cells ...... 48

Figure 8: PD-1, Lag-3, CD160 and 2B4 coexpression patterns on HIV and EBV-

specific CD8 T-cells...... 49

Figure 9: Number of inhibitory receptors expressed by HIV and EBV-specific CD8

T-cells...... 50

Figure 10: Functional profile of HIV and EBV-specific CD8 T-cells...... 51

Figure 11: PD-1, CD160 and 2B4 co-expression on perforin+ and perforin virus-

specific CD8 T-cells...... 52

Figure 12. Association between perforin and expression of PD-1 but not CD160 or

2B4...... 53

Figure 13. Association between perforin and co-expression of CD160 and 2B4...... 54

Figure 14: Gating strategy for PD-1, CD160 and 2B4 expression on total, naïve and

memory CD8 T-cells from blood and lymph node...... 74

Figure 15: Memory distribution of CD8 T-cells from blood and lymph nodes...... 75

Figure 16: Comparison expression of PD-1, CD160 and 2B4 on CD8 T cells from

HIV negative, chronic progressors and ART subjects ...... 76

Figure 17: Comparison between blood and lymph node expression of PD-1, CD160

and 2B4 on CD8 T-cells ...... 77

Figure 18: Co-expression of inhibitory receptors on memory CD8 T-cells from blood

and lymph node...... 78

Figure 19: Gating scheme for detection of virus-specific responses...... 79

Figure 20: Functional profile of HIV and EBV-specific CD8 T cells...... 80

Figure 21: Comparison between blood and lymph node expression of PD-1, CD160

and 2B4 on CD8 T-cells ...... 81

Figure 22: Co-expression of inhibitory receptors on memory CD8 T-cells from blood

and lymph node...... 82

Figure 23. Association between perforin and co-expression of CD160 and 2B4...... 83

Figure 24: T-bet expression in Gag and EBV-specific CD8 T cells from blood and

lymph node...... 84

Figure 25. Association between high expression of T-bet and co-expression of CD160

and 2B4...... 85

xii

CHAPTER 1: Introduction

Pathogenesis of the Human Immunodeficiency Virus

The Human Immunodeficiency Virus (HIV) was identified in 1983 from a lymph node of an individual with lymphadenopathy by two separate groups (Barré-Sinoussi et al., 2004; Gallo et al., 1983). It was later determined that HIV is the causative agent of

Acquired Immunodeficiency Syndrome (AIDS). Since its discovery 35 years ago, approximately 40 million people have died of AIDS related causes. According to data collected by the World Health Organization (WHO), there are currently 35 million people living with HIV world wide, including 3.2 million children. If left untreated, the majority of HIV-infected individuals, known as chronic progressors (CP), will develop gradual immunodeficiency that results in an increased risk of opportunistic infections and tumors

7–10 years, on average, after infection. Despite great efforts by WHO and other organizations to distribute antiretroviral therapy in an effort to slow the epidemic, there were 2.1 million new infections and 1.5 millions deaths world wide in 2013.

HIV is an enveloped retrovirus, a member of the genus Lentivirus, from the family Retroviridae (Gonda, 1988). The viral particle contains two copies of positive single-stranded RNA that encodes three major polyproteins: gag (spliced into capsid protein P24, matrix protein P17 and nucleocapsid P15), pol (spliced into protease, reverse transcriptase, integrase), and env (envelope protein spliced into gp120 and gp41)

(Sundquist & Kräusslich, 2012). The viral genome also codes for regulatory elements

involved in viral replication (tat, rev, vpr) and immune modulation (vif, nef) (Arhel et al.,

2009; Sundquist & Kräusslich, 2012).

HIV entry into target cells is mediated by interactions between the viral envelope protein (env) and both the T-cell receptor CD4 and a chemokine receptor, either CCR5 or

CXCR4. Upon entry, viral cDNA is synthesized from viral RNA by reverse transcriptase and transported into the nucleus where it is integrated into the host DNA by the viral protein integrase. The viral reverse transcriptase is prone to errors providing the virus with a high mutation rate that allows rapid evolution and escape from competent immune detection and elimination (Boutwell, Rolland, Herbeck, Mullins, & Allen, 2010; Richman et al., 2004).

During acute infection, HIV primarily infects activated CD4+ T-cells in gut- associated lymphoid tissues (GALT) leading to rapid depletion of this population. As disease progresses, HIV dissemination to peripheral lymphoid tissues coupled with immune activation contribute to destruction of lymphoid tissue architecture, disruption of homeostatic processes that maintain T cell numbers and antigen presentation (Brenchley et al., 2004). Progressive loss of CD4 T-cells also extends to peripheral blood contributing to immunodeficiency and disease progression. CD4 T-cell depletion is partly due to direct killing of infected cells, but it is exacerbated by production of pro- inflammatory cytokines such as IFNγ and TNF that induce activation and death of uninfected by-stander CD4 T-cells (Brenchley et al., 2004; Groux et al., 1992).

Furthermore, structural damage to GALT tissues leads to translocation of microbial

products from the gut lumen into systemic circulation, further contributing to general immune activation. As a consequence of prolonged antigen stimulation and immune activation, T cells gradually become less effective at fighting not only HIV but also other opportunistic infections, leading to the onset of AIDS.

However, a small subset of HIV-infected individuals, referred to as elite controllers (EC), is capable of suppressing viral replication to very low levels without the need for antiretroviral therapy. Understanding the factors involved in maintenance of chronic disease and differences in the CD8+ T-cell response between pathogenic and non-pathogenic infection may provide insights into correlates of immune protection, thereby informing the development of HIV vaccines and immunotherapeutic strategies.

Elite control of HIV has been attributed to host factors that impede viral replication and reduce systemic immune activation. A 32-base pair deletion within the

CCR5 gene (CCR5-Δ32) results in a reduction of surface expression of this receptor.

Individuals homozygous for this mutation are protected from infection with HIV viruses requiring use of CCR5 co-receptor for entry. Individuals heterozygous for CCR5-Δ32 have lower viral set-point and experience slower disease progression (Baker, Block,

Rothchild, & Walker, 2009). Elite control of HIV is also associated with high expression cellular intrinsic factors such as APOBEC3G and TRIM5α, both part of the innate immune response to infection (Baker et al., 2009). In addition, expression of the natural killer (NK) cell receptor KIR3DS1 was shown to significantly reduce viral replication

(O'Connell, Han, Williams, Siliciano, & Blankson, 2009). Expression of certain HLA

alleles, such as HLA-B57 and HLA-B27, are associated with viral escape mutations associated with diminished replicative fitness (Bailey, Brennan, O'Connell, Siliciano, &

Blankson, 2008; Miura et al., 2009). There is also evidence from studies looking at pathogenic and non-pathogenic HIV and SIV infection of non-human primates that CD8

T-cells play an important role in controlling viral replication (Bailey et al., 2008; Betts et al., 2006; Grabar et al., 2009; Hersperger et al., 2010; Migueles et al., 2002; 2008; Sáez-

Cirión et al., 2007)

Innate Immunity and HIV Infection

The innate immune system is the first line of defense against viral infection.

During the initial stages of HIV infection, innate immunity has an important role in viral control but can also contribute to disease pathology. Cell intrinsic factors such as Toll- like Receptors (TLRs) and restriction factors (APOBEC3, TRIM5a, SAMHD1 and

Tetherin) interfere with viral replication as spread by recognizing viral RNA and trigger production of type-I interferons that interfere with viral replication, maturation and budding from the host cell (Reviewed in (Altfeld & Gale, 2015)). Production of pro- inflammatory cytokines and chemokines lead to activation of monocytes, macrophages and dendritic cells (DC). Macrophages and DCs then travel to lymph nodes where they activate the adaptive immune response by presenting antigen to T cells. However, high levels of IFNα trigger apoptosis of CD4 T-cells in GALT, further contributing to disease progression (Baker et al., 2009). HIV uses DCs and macrophages as vehicles in to lymph nodes, providing the virus with a target rich environment and further contributing to viral

spread. Once infected cells reach lymphatic tissues, HIV induces a reduction of motility allowing formation of virological synapses for better cell-to-cell spread, establish the viral reservoir and disrupt lymph node structure, further contributing to immune dysfunction (Arhel et al., 2009; Baxter et al., 2014; Nasr, Harman, Turville, &

Cunningham, 2014).

Activation of natural killer (NK) cells is triggered by multiple activating and inhibitory receptors that allow detection of infected cells that downregulate MHC-I. In response to pro-inflammatory stimuli, NK cells migrate to the site of infection where they release cytolytic molecules (perforin and granzymes) for direct killing of infected cells

(Gosselin, TomoIu, Gallo, & Flamand, 1999). NK cells in elite controllers have a higher cytotoxic capacity compared to progressors despite having similar expression of inhibitory and activating receptors (O'Connor, Holmes, Mulcahy, & Gardiner, 2007).

Expression of specific killer cell immunoglobulin like receptors (KIRs) alleles were found to correlate with elite control of HIV (discussed above). NK cells also suppress

HIV viral replication by production of chemokines RANTES, MIP-1α and MIP-1β, which bind to the CCR5 receptor, a co-receptor required for HIV entry into target cells

(Kottilil et al., 2004; O'Connor et al., 2007). Deregulation of NK cells during HIV infection is evident early after infection by decreased cytotoxic capacity (reduced perforin and granzymes) in combination with an aberrant activating and inhibitory receptor expression profile (Altfeld, Fadda, Frleta, & Bhardwaj, 2011; Kottilil et al.,

2004). NK cells from viremic individuals have increased expression of inhibitory

receptors compared to healthy controls (Mavilio et al., 2003). Still a number of questions related to the role of specific NK inhibitory receptors and their expression patterns in NK dysfunction during HIV infection remain unanswered and deservers further study.

Adaptive Immune Responses and HIV Infection

Humoral Immunity to HIV

HIV infection triggers production of a variety of antibodies capable of binding to

HIV that may or may not be able to interfere with viral spread. The humoral immune response to HIV is made up of binding antibodies, neutralizing antibodies and monoclonal antibodies with broad neutralizing activity (reviewed in (Baum, 2010)).

Antibodies that bind to the HIV envelope glycoprotein are capable of neutralizing the virus through antibody-dependent cell-mediated viral inhibition (ADCVI) and antibody dependent cell-mediated cytotoxicity (ADCC). However high titters of neutralizing antibodies are necessary for protection since any unbound HIV env protein can trigger infection of a target cell. Furthermore, the majority of binding antibodies isolated from

HIV chronic progressors are specific for the initial or “founder” virus (Baum, 2010) but are unable to limit HIV spread due to the virus’ rapid evolution away from recognized epitopes.

On the other hand, broadly neutralizing antibodies are specific for conserved regions of the viral envelope, such as the CD4 binding region, and are able to neutralize most isolates (Baum, 2010; Overbaugh & Morris, 2012). However, these broad 6

neutralizing antibodies take time to emerge and are not present during the initial stages of

HIV infection (Baum, 2010). Inadequate T cell help provided to B cells in lymph nodes as disease progresses affects B cell survival and further contribute to emergence of ineffective antibodies against HIV (Cubas et al., 2013). Great effort is being put into developing vaccines capable of inducing broad neutralizing antibodies against HIV, but their success remains unclear (Baker et al., 2009; Overbaugh & Morris, 2012; Willis et al., 2015).

HIV-Specific CD4 T-cells

During HIV infection, HIV-specific memory CD4 T-cells are preferentially infected and killed (Douek et al., 2002), primarily affecting CD4 T cells outside lymphoid tissues such as the intestinal mucosa. CD4 T cells are comprised of subsets with distinct immunological function including Th1, Th2, Th17, T follicular helper (TFH) and T regulatory (Treg). The initial depletion of CD4 T cells is countered by homeostatic proliferation of memory CD4 T cells due to immune activation, slowing the progressive loss of total CD4 counts. However, this regeneration does not restore all CD4

T cell populations and it is not stable long term, eventually resulting in the decline CD4 T cell numbers (Reviewed in (Okoye & Picker, 2013)). The progressive loss of CD4 T cells is used as a measure of disease progression. CD4 T-cells are an essential component of an effective immune response, often referred to as T helper cells. CD4 T-cells promote immune control by providing help to B cells and CD8 T-cells. Lack of CD4 T cell help contributes to dysfunction of B cells and CD8 T-cells and is linked to development of

opportunistic infections in AIDS patients (Rosenberg et al., 2000). There is also evidence supporting the role of CD4 T-cells in controlling viral replication through direct cytolytic activity (Norris et al., 2004), though this might also contribute to CD4 T-cell depletion and disease progression.

Lymph node-resident TFH cells migrate from the T cell zone into B cell follicles where they interact with antigen-specific B cells in specialized structures called germinal centers, enhancing antibody affinity, maturation and differentiation of follicular B cells into memory B cells or plasma cells; initiating the humoral response to HIV infection

(discussed above). TFH cells are preferentially enriched in HIV+ lymph nodes and are believed to serve as viral reservoirs. Efforts focused on eliminating the HIV reservoir are concentrated in understanding the regulatory mechanisms of TFH cells as well as other lymph node-resident immune cells to determine the best approach to eliminate infected cells in the this important anatomical site. Studies to determine the advantages of early initiation of ART reported a delayed time to AIDS and maintenance of mucosal CD4 T cells preventing microbial translocation and general immune activation (Grinsztejn et al.,

2014; Schuetz et al., 2014). It would be of interest to determine the effect this approach would have on lymph node architecture, CD4 T helper function and establishment of the

HIV reservoir.

HIV-specific CD8 T-cells

CD8 T cells are primarily responsible for recognizing host cells that are either abnormal or infected by an invading intracellular pathogen. Circulating CD8 T cells that

have not encountered antigen are referred to as naïve CD8 T cells, which are mostly quiescent and have little to no effector functions. Upon recognition of antigen through interactions between the T cell receptor (TCR) and the MHC-I:peptide complex, along with co-stimulatory signals, naïve T-cells differentiate and acquire effector functions such as cytokines (e.g. IFNγ, TNF, or IL-2), chemokines (e.g. MIP1α, MIP1β or

RANTES) or cytolytic molecules (e.g. perforin and granzymes) for direct killing of target

T-cells. CD8 T cell responses can therefore be classified into polyfunctional memory

(IL2+IFNγ+ and other functions) or polyfunctional effector (perforin+IFNγ+ and other functions) based on viral specificity (Makedonas et al., 2010). Mature CD8 T-cells are highly specific for a limited number of peptide epitopes presented on major histocompatibility class I (MHC-I) molecules found on the surface of professional antigen presenting cells, abnormal cells or infected cells.

In the context of HIV infection, the role of CD8 T cells in viral control has been inferred by the resolution of peak viremia to a lower set point coincides with CD8+ T-cell emergence and elimination infected cells by direct and indirect killing (Gulzar &

Copeland, 2004). HIV-specific CD8 T-cell responses have been measured even before antibodies can be detected during acute HIV infection (Mackewicz, Yang, Lifson, &

Levy, 1994). Researchers have further characterized this dynamic using SIV infection of non-human primates. CD8 T-cell depletion during SIV infection confirmed the critical role played by CD8 T-cells in early control of viremia (Jin et al., 1999; Schmitz et al.,

1999).

Nevertheless the frequency of HIV-specific T-cells alone is not a correlate of immune protection and does not predict disease progression (Betts et al., 2001; Schellens et al., 2008). The quality of the CD8 T-cell response is measured by the polyfunctionality of individual cells, defined by their capacity to respond to antigen stimulation by simultaneously producing multiple effector functions. These functions include the ability to proliferate, produce cytolytic molecules (perforin, Granzymes), multiple cytokines (IL-

2, TNFα, IFNγ) and differentiate into memory T-cells. There is evidence suggesting that number of T-cells with highly polyfunctional effector responses correlates with immune protection of elite controllers during HIV infection (Almeida et al., 2007; Betts et al.,

2001; 2006; Darrah et al., 2007; Gulzar & Copeland, 2004; Precopio et al., 2007;

Schellens et al., 2008). But as a consequence of continued exposure to viral antigens and immune activation CD8 T-cells gradually lose their functional ability (Wherry et al.,

2007), a process referred to as T-cell exhaustion. As disease progresses into the chronic stage, HIV-specific CD8+ T-cells have a decreased ability to proliferate and secrete cytokines (Jagannathan et al., 2009).

T-cell Exhaustion

After acute viral infection, CD8+ T-cells rapidly activate effector functions and have a high proliferative potential. After antigen burden is resolved, the antigen-specific

CD8 T-cell population contracts allowing a protective memory population to form and be maintained by antigen-independent homeostatic proliferation. In contrast, during chronic

infection the antigen is not cleared and antigen-specific CD8+ T-cells gradually become less functional and lose proliferative capacity, leaving them unable to clear the antigen

(Barber et al., 2006). The loss of function is hierarchical: proliferation potential and IL-2 are lost early, TNF persists longer and in extreme cases the last function lost is IFN

(reviewed in (Wherry, 2011)). In severe cases, especially when CD4+ help is lacking such as during HIV infection, virus-specific CD8+ T-cells fully lacking effector functions can be found (Wherry et al., 2007).

T-cell exhaustion was first described using LMCV infection of mice, where

CD4+ depleted mice resulted in the most profound CD8+ T-cell exhaustion, but the main features of exhaustion were preserved in the presence of CD4+ T-cells (reviewed in (Shin

& Wherry, 2007)). T-cell exhaustion has been studied in mice (Blackburn et al., 2008;

Bucks, Norton, Boesteanu, Mueller, & Katsikis, 2009; Jackson, Berrien-Elliott, Meyer,

Wherry, & Teague, 2013; Utzschneider et al., 2013), non-human primates (Petrovas et al., 2007; Velu et al., 2007) and human subjects suffering from chronic diseases (Bengsch et al., 2010; Fourcade et al., 2012; Kroy et al., 2014; Riches et al., 2013; Yamamoto et al., 2011). Though there are differences among the models used, a common characteristic of T-cell exhaustion is that it is antigen specific. HIV+ patients exhibit T- cell exhaustion on HIV-specific CD8 T-cells but not EBV, FLU or CMV-specific CD8 T- cells, suggesting that CD8 T-cell responses are determined by the duration and intensity of antigenic exposure and could therefore be a consequence of viremia (D'Souza et al.,

2007; Jagannathan et al., 2009; Nakamoto et al., 2008; Petrovas et al., 2006).

Furthermore, T-cells maintain an exhausted phenotype after antigen withdrawal and population re-expansion, suggesting the exhausted phenotype is passed to daughter cells, even when T-cells are no longer exposed to high levels of antigen (Streeck et al., 2008).

In addition, exhausted T-cells have translational, metabolic and bioenergetic deficiencies as well as a cumulative expression of inhibitory receptors (Aldy, Horton, Mathew, &

Mathew, 2011; Bengsch et al., 2010; Blackburn et al., 2008; Fourcade et al., 2012; Kroy et al., 2014; Riches et al., 2013; Wherry et al., 2007; Yamamoto et al., 2011).

Phenotypic markers of T-cell exhaustion

Co-stimulatory signals and Inhibitory receptors are important regulators of T-cell function, working together to regulate the initiation and termination of effective adaptive immune responses. However, the accumulation of inhibitory receptors in the presence of persistent antigen can result in the inability to respond upon re-stimulation. In the last ten years a number of studies have shown associations between expression of inhibitory receptors and T-cell exhaustion in the setting of chronic disease (Barber et al., 2006;

Blackburn et al., 2008; Day et al., 2006; Peretz et al., 2012; Tian et al., 2015; Trautmann et al., 2006; Utzschneider et al., 2013; Velu et al., 2007). The most common inhibitory receptor associated with T cell exhaustion is PD-1. The transcription profile of exhausted

LCMV-specific CD8 T cells and phenotype profile of HIV-specific CD8 T cells identified other markers upregulated during chronic infection. Inhibitory receptors

CD160, 2B4, Lag-3, CTLA-4, PIR-B and GP49b, TIM 3 (Blackburn et al., 2008;

Odorizzi & Wherry, 2012; Parry et al., 2005; Wherry et al., 2007; Z.-Z. Yang et al.,

2012). This work focused on on the four inhibitory receptors shown to be strongly associated with T cell exhaustion, PD-1, CD160, 2B4 and Lag-3 (Wherry et al., 2007).

PD-1

PD-1 is a member of the immunoglobulin gene superfamily, first identified in two lymphoid cell lines as a cell death-associated gene playing a role in programmed cell death (Ishida, Agata, Shibahara, & Honjo, 1992). PD-1 is expressed upon engagement of the antigen-receptor on activated T-cells, NK cells, B cells and myeloid cells (Agata et al., 1996; Blackburn et al., 2010; Freeman et al., 2000). Several studies in mice chronically infected with LCMV clone 13 have demonstrated that engagement of PD-1 has a negative effect on proliferative expansion, cytokine production and cytotoxicity as well as increased sensitivity to apoptosis of virus-specific CD8 T-cells (Barber et al.,

2006; Blackburn et al., 2010; Freeman et al., 2000; Shin & Wherry, 2007; Wherry, 2011).

Two ligands for PD-1 have been identified, PD-L1 and PD-L2, both members of the B7 family. Though non-lymphoid tissues such as lung, heart, placenta and skeletal muscle constitutively express varying levels of PD-L1 and PD-L2, IFNγ induces expression of these ligands on monocytes (Freeman et al., 2000; Latchman et al., 2001). Engagement of PD-1 by PD-L1 or PD-L2 on target T-cells can suppress effector T-cell function by reducing phosphorylation of TCR associated proteins by recruitment of Src homology 2

(SH2) domain–containing tyrosine phosphatase 2 (SHP2) (Barber et al., 2006; Freeman et al., 2000; Latchman et al., 2001; Yokosuka et al., 2012). Blocking the PD-1/PD-L1 signaling pathway by using an anti-PD-L1 antibody results in enhanced T-cell responses

and restores the proliferation capacity of CD8 T-cells while they continued to express the

PD-1 receptor, suggesting continuous engagement of PD-1/PD-L1 is necessary for inhibition (Barber et al., 2006)

In the context of HIV infection, a high level of PD-1 expression on HIV-specific

CD8 T-cells is associated with high viral load and disease progression (D'Souza et al.,

2007; Day et al., 2006; Petrovas et al., 2006; Trautmann et al., 2006; Zhang et al., 2007).

However, PD-1 expression is also high on EBV-specific CD8 T-cells and these cells are not dysfunctional (Petrovas et al., 2006). Furthermore, several reports suggest PD-1 expression alone is not necessarily a marker of exhaustion, but can serve as a marker of

T-cell activation and differentiation (Legat, Speiser, Pircher, Zehn, & Fuertes Marraco,

2013; Zelinskyy et al., 2011), highlighting the importance of measuring multiple parameters to determine functional exhaustion.

CD160

CD160 was first identified as a GPI-anchored cell surface molecule expressed on

NK cells, CD8 T-cells and intestinal intraepithelial T lymphocytes (Anumanthan et al.,

1998; Nikolova, Marie-Cardine, Boumsell, & Bensussan, 2002). An alternative isoform of CD160 with a transmembrane domain (CD160-TM) has also been detected in activated NK cells. CD160 is expressed as a disulfide-linked multimer with a broad specificity for binding both classical and non-classical MHC class I molecules (Nikolova et al., 2002) and a higher affinity to the herpes virus entry mediator (HVEM) receptor

(Cai et al., 2008). Several reports suggest a dual function for CD160 determined by its

binding partner. Interactions between CD160 and MHC class I molecules enhance CD3- induced proliferation (Nikolova et al., 2002) and cytotoxicity (Nikolova et al., 2005; Rey et al., 2006). Whereas, interaction between CD160 and HVEM results in an inhibitory signal marked by reduced cytokine expression and cytotoxicity (Cai et al., 2008; Kojima,

Kajikawa, Shiroishi, Kuroki, & Maenaka, 2011). The exact mechanism through which

CD160 exerts its effect is not fully understood. However, a soluble form of CD160

(sCD160)has been detected in culture of activated T cells and has been shown to inhibit migration of monocytes and immanure dendritic cells. Generation of sCD160 was shown to occur through a metalloprotease-dependent shedding (Giustiniani, Marie-Cardine, &

Bensussan, 2007). Further insight into the regulatory mechanisms of CD160 expression and function are necessary before this marker can be considered a candidate for therapeutic development.

2B4

2B4 (CD244) is a member of the CD2 superfamily expressed on NK cells, CD8

T-cells, thymocytes, monocytes and basophils (Boles, Stepp, Bennett, Kumar, &

Mathew, 2001). Several studies have shown that expression of 2B4 correlates with effector differentiation (Boles et al., 2001; Legat et al., 2013; McNerney, Lee, & Kumar,

2005; Rey et al., 2006). 2B4 has dual function depending on levels of expression, availability of the SLAM-associated protein (SAP) and degree of cross-linking

(Chlewicki, Velikovsky, Balakrishnan, Mariuzza, & Kumar, 2008) Engagement of this receptor can lead to an inhibitory or a stimulatory signal. An inhibitory signal results in a

decrease in proliferation, cytolytic activity and production of IFNγ. On the other hand, the stimulatory signal can induce proliferation and potentiate cytolytic activity (Meinke

& Watzl, 2013). The ligand for 2B4 is CD48, which has a wide distribution in the hematopoietic system and is particularly expressed in EBV-infected B lymphocytes (Rey et al., 2006). Similar to CD160, further understanding of the regulatory mechanisms involved in defining the function of 2B4 are necessary in order to consider this receptor for therapeutic purposes.

LAG-3

Lag-3 is a ligand for MHC class II and it is genetically related to CD4 (Hannier,

Tournier, Bismuth, & Triebel, 1998; Triebel et al., 1990). Lag-3 is primarily expressed on activated CD8 T-cells and to a lesser extent on CD4+ T-cells found in inflamed secondary lymphoid organs or tissues and even though it has a high affinity to MHC class

II it does not disturb CD4-MHC class II interactions (Triebel, 2003). Cell capping experiments demonstrated Lag-3 recruitment to the CD3 complex in lipid rafts after antigen recognition where it starts a negative signal cascade that results in reduced homeostatic expansion and proliferation of activated T-cells in vivo by preventing entry of the T-cell into the cell cycle (Hannier et al., 1998; Workman & Vignali, 2005). In the context of HIV infection, Lag-3 expression by CD8 T-cells from blood of infected patients is low (Yamamoto et al., 2011). However, there is data showing high expression of Lag-3 in tissues relevant for HCV infection and tumor microenvironment (Grosso et

al., 2007; Kroy et al., 2014; Woo et al., 2012). There is also evidence of a role for Lag-3 in exhaustion and disease progression (Okazaki et al., 2011; Tian et al., 2015)

THESIS GOALS

Immune dysregulation is a hallmark of HIV infection. Efforts to reverse T-cell exhaustion have concentrated around the inhibitory receptor PD-1. Studies have shown that PD-1 alone is not sufficient to induce T-cell exhaustion. Evidence points to a high correlation between high expression of PD-1 and co-expression of inhibitory receptors

Lag-3, CD160 and 2B4 in exhausted T cells. Contradicting data establishes CD160 and

2B4 as both inhibitory and stimulatory, bringing their role in T cell exhaustion into question. In this study we aimed to characterize the expression of PD-1, Lag-3, CD160 and 2B4 on human CD8 T-cells in the context of HIV infection and determined if these receptors truly are markers of T cell exhaustion. To this end, we measured expression of these exhaustion markers along with effector functions previously shown to be correlates of immune protection in a cohort of elite controllers and chronic progressors.

Even with the introduction of antiretroviral therapy immune re-constitution is incomplete and interruption of treatment results in a rebound of viral load. In addition, there is evidence of on-going low-level viral replication in subjects fully suppressed by

ART. In the last few years there has been a growing effort to identify the source of that virus, believed to be TFH cells in germinal centers. Evidence suggests establishment of the viral reservoirs occurs in the lymph nodes during early infection. However, little is 17

known about the ability of lymph node-resident immune cells to find and kill infected cells. Of interest, the ability of lymph node CD8 T cells to recognize and eliminate infected TFH cells in germinal centers and/or their exhausted state is yet to be determined. To date, most of what we know about T-cell exhaustion is from peripheral blood CD8 T-cells. The second aim of this study was to determine if levels of exhaustion observed in CD8 T-cells from blood represent the level of CD8 T cell exhaustion in HIV positive lymph nodes. To this end, we measured expression of PD-1, CD160 and 2B4 on

CD8 T-cells from blood and lymph nodes of HIV+ subjects on and off ART. At the same time, we measured IFNγ, TNF and perforin expression after HIV-specific stimulation to identify associations between expression of PD-1, CD160, 2B4 and T cell responses. To this day, HIV infection remains incurable due to early establishment of viral reservoirs. We hope that the results from this work will aid in the effort to improve existing ART and develop new vaccine platforms against HIV.

CHAPTER 2: ELITE CONTROLLERS EXPRESS MORE CD160

AND LESS PD-1 THAN CHRONIC PROGRESSORS

SUMMARY

During the chronic phase of HIV infection virus-specific CD8 T-cells lose their ability to proliferate, produce multiple cytokines and kill infected cells, a state known as

T-cell exhaustion. However, unlike chronically infected individuals, HIV elite controllers suppress HIV replication without the need for antiretroviral therapy. Several studies have shown that elite controllers also retain CD8 T-cell polyfunctionality and killing function, characteristics considered correlates of protection. It remains unclear whether HIV elite controllers manifest T-cell exhaustion similar to chronically progressing HIV infected subjects. Here we assessed the co-expression of inhibitory markers PD-1, Lag-3, CD160 and 2B4 in a cohort of HIV elite controller subjects compared to HIV chronic progressors as a measure of T-cell exhaustion. We find that elite controllers have a broad range of co- expression of these inhibitory receptors. Elite controllers have a significantly higher proportion of CD160+2B4+ CD8 T-cells compared to chronic progressors. Additionally, elite controllers have proportion of potentially exhausted (PD1+CD160+2B4+) HIV- specific CD8 T-cells comparable to that observed in chronic progressors. This work was published in (Pombo, Wherry, Gostick, Price, & Betts, 2015)

INTRODUCTION

Untreated HIV infection is typically a chronic progressive disease associated with a gradual and progressive loss of control of viral replication and a steady decline in CD4

T-cell counts resulting in the collapse of the immune system (Hubert et al., 2000).

During the early stages of infection CD8 T-cells play and important role in controlling viral replication by eliminating infected cells (reviewed in (Gulzar & Copeland, 2004)), but lose this ability as the disease progresses into the chronic stage (reviewed in (El-Far et al., 2008)). However, there is a small subset of HIV infected individuals referred to as elite controllers that are capable of suppressing viral replication to very low levels without the need for anti-retroviral therapy (ART). Several studies looking to understand differences in CD8 T-cell responses between HIV chronic and elite subjects have shown the importance of the cytotoxic CD8 T-cell (CTL) function in suppressing HIV replication (O'Connell et al., 2009). However, a better understanding of the degree of T- cell exhaustion, if any, in elite controllers could further elucidate correlates of immune protection and aid in the development of therapies and vaccines.

Elite controllers are a rare subset (<1%) of HIV infected individuals that have the ability to suppress HIV viral replication to undetectable levels (<50 copies/mL) for many years without the need for ART. These individuals have stable CD4 T-cell counts and no history of AIDS defining illnesses (Grabar et al., 2009). A study looking a discordant couples with one elite controller and one progressor showed that in both individuals the virus is replication competent, and the only difference was the host genetics and immune system, suggesting that host genetics and immune responses play a role in elite control 20

(Bailey et al., 2008). Despite maintaining control of viral replication, the presence of HIV escape variants with mutations to CTL epitopes is evidence of low-level viral replication present within these subjects (Miura et al., 2009)

T-cell exhaustion has been studied in mice (Blackburn et al., 2008; Bucks et al.,

2009; Jackson et al., 2013; Utzschneider et al., 2013), non-human primates (Petrovas et al., 2007; Velu et al., 2007) and human subjects suffering from chronic diseases (Bengsch et al., 2010; Fourcade et al., 2012; Kroy et al., 2014; Riches et al., 2013; Yamamoto et al., 2011). Typical markers associated with T-cell exhaustion include PD-1, Lag-3,

CD160 and 2B4. Additionally, studies have shown a strong association between high levels of PD-1, HIV viral loads and disease progression (Day et al., 2006; Petrovas et al.,

2006; Trautmann et al., 2006). Different patterns of inhibitory receptor expression have been shown to identify exhausted populations defined by a decrease in IL-2, TNF and

IFNγ (Bengsch et al., 2010; Blackburn et al., 2008; Peretz et al., 2012; Rey et al., 2006;

Viganò et al., 2014; Yamamoto et al., 2011). However there is also evidence that some of these receptors have dual function and can act as co-stimulatory ligands (Meinke &

Watzl, 2013; Nikolova et al., 2005). While the majority of previous work has been done in the context of chronic progressive disease, the level of exhaustion in the context of controlled HIV infection has not been explored. In this study, we assessed the potential exhaustion of CD8 T-cells in elite controllers using previously defined markers of exhaustion PD-1, Lag-3, CD160 and 2B4. Our results show lower expression of PD-1 but higher expression of CD160 on elite controller CD8 T-cells compared to those from chronic progressors. Furthermore, elite controllers have a significant fraction of CD8 T- 21

cells co-expressing CD160 and 2B4. Interestingly, elite controllers have a population of

PD-1+CD160+2B4+ CD8 T-cells previously defined exhausted. This potentially exhaustion population was comparable to that of chronic progressors, a possible indication of on-going low-level viral replication within these subjects.

MATERIALS AND METHODS

PBMC samples

Peripheral blood mononuclear cells (PBMC) were obtained from healthy subjects at the University of Pennsylvania's Center For AIDS Research Human Immunology Core and cryopreserved in fetal bovine serum (FBS; ICS Hyclone, Logan Utah) containing

10% dimethyl sulfoxide (DMSO; Fisher Scientific, Pittsburgh, Pennsylvania). PBMCs from HIV positive individuals were obtained from three sources in compliance with the guidelines set by the respective institutional internal review boards: the University of

Pennsylvania’s Center for AIDS Research Human Clinical Core Facility and clinics associated with Harvard University and the University of Alabama Birmingham.

Chronic progressors were defined as untreated individuals with HIV plasma RNA levels above 2,000 copies/mL (range: 2,319-484,699; median: 10,193) infected for >2 years. Elite controllers were defined as therapy naïve individuals with viral loads <75

HIV RNA copies/mL at multiple time points and infected for >2 years. All subjects had

CD4 counts > 200 cells/mm3 and lacked evidence of an AIDS defining illness. All samples were cryopreserved before use.

Antibodies

Antibodies for surface staining included anti-CD4 PE-Cy5.5 (clone S3.5,

Invitrogen), anti-CD8 Qdot605 (clone 3B5, Invitrogen) or Brilliant Violet 605 (clone

RPA-T8, Biolegend), anti-CD27 Qdot 655 (clone CLB-27/1, Invitrogen) or Brilliant

Violet 650 (clone O323, Biolegend), anti-CD45RO ECD (clone UCHL1, Beckman

Coulter), anti-PD-1 PE (clone EH12.2 H7, Biolegend), anti-CD160 (Cai et al., 2008), conjugated in-house) FITC and anti-CD244 (2B4) PE-Cy5 (clone C1.7, Beckman

Coulter), anti-CD14 APC-AF750 (clone TüK4, Invitrogen), anti-CD19 APC-AF750

(clone SJ25-C1, Invitrogen), anti-Lag-3 biotin (polyclonal, R&D Systems), Streptavidin-

APC (Invitrogen), and anti-APC biotin (clone eBioAPC-62A, eBiosicience). Intracelluar staining: anti-CD3 Qdot 585 (custom conjugation performed in our laboratory as previously described (Chattopadhyay et al., 2006) or Brilliant Violet 570 (clone UCHL1,

Biolegend).

FACS staining assay

After 5 hours of stimulation, cells were washed once with FACS buffer and stained for Lag-3 in four steps: First adding anti-Lag-3 biotin (R&D Systems) for 15 minutes then washed with FACS buffer, next Streptavidin APC (Invitrogen) for 15 minutes then washed with FACS buffer, followed by addition of anti-APC biotin

(eBiosicience) for 15 minutes then washed with FACS buffer and finally staining with

Streptavidin APC for 15 minutes. After washing with PBS and staining with Aqua amine-reactive viability dye (Invitrogen) for 10 minutes to exclude non-viable events, the cells were stained for surface markers with an antibody cocktail for an additional 30 minutes. Following a wash with FACS buffer, the cells were permeabilized with Cytofix 23

Cytoperm (BD Biosciences) as per manufacturer’s instructions. Next, a cocktail of antibodies against intracellular markers was added and incubated for an hour. Lastly, the cells were washed with Perm Wash Buffer (BD Biosciences) and fixed in PBS containing

1% paraformaldehyde. All incubations were done at room temperature in the dark.

Fixed cells were stored at 4°C until the time of collection.

Flow cytometric analysis

For each sample, between 5x105 and 1x106 total events were acquired on a modified flow cytometer (LSRII; BD Immunocytometry systems) equipped for the detection of 18 fluorescent parameters and longitudinally standardized for signal consistency using the previously described calibration methods (Perfetto, Ambrozak,

Nguyen, Chattopadhyay, & Roederer, 2012). Antibody capture beads (BD Biosciences) were used to prepare individual fluorophore matched compensation tubes for each antibody used in the experiments. Data analysis was performed using FlowJo version

9.6.4 (TreeStar, Inc). Reported functional data have been corrected for background.

Statistical analysis was performed with Prism, version 5.0. Comparison of inhibitory receptor expression among cohorts was analyzed using the Mann-Whitney U test.

Correlation coefficients were calculated using the Spearman rank sum test. All tests were

2-tailed, and P values less than 0.05 were considered significant

RESULTS

Elite controllers express less PD-1 but more CD160 than chronic progressors

To determine the level of potential T-cell exhaustion present in elite controllers

(EC) and assess differences from what is known in chronic progressors (CP), we began by using the differential expression of CD27 and CD45RO to distinguish between the naïve (CD27+CD45RO-) and memory CD8+ T-cell populations (Figure 1A). Naïve cells were then used as reference to determine surface expression of individual exhaustion markers PD-1, Lag-3, CD160 and 2B4 (Figure 1B). Flow cytometry plots showing expression of PD-1, Lag-3, CD160 and 2B4 on Naïve and memory CD8 T-cells for an

HIV negative (HIV-), a CP and an EC are shown in Figure 2.

Systemic immune activation due to microbial translocation can be a determinant of clinical progression in both chronic progressors and elite controllers regardless of viremia (León et al., 2015). Once can hypothesize that the persistent presence of microbial products can contribute to exhaustion of the bulk CD8 T-cell compartment. To assess this possibility, we measured surface expression of PD-1, Lag-3, CD160 and 2B4 as markers or exhaustion on total CD8 T-cells. A significantly higher proportion of CD8

T-cells from elite controllers expressed CD160 compared to both CP and HIV-negative subjects but significantly less PD-1 (Figure 3A). Previous reports linked expression of inhibitory receptors on CD8 T-cells to differentiation and activation status, with naïve T- cells expressing the less than memory T-cells (Legat et al., 2013). Therefore we determined the memory distribution of CD8 T-cells within in the HIV-negative, CP and

EC groups and compared expression of PD-1, Lag-3, CD160 and 2B4 between naïve and memory CD8 T-cells (Figure 3B). Naïve CD8 T-cells from HIV-negative, CP and EC express low levels of PD-1, Lag-3 and 2B4 (mean: <15%), but naïve CD8 T-cells from 25

HIV-negative and EC expressed significantly more CD160 than those from CP (Figure

4A). To better compare the EC, CP and HIV- groups we excluded the naïve population and continued our analysis focusing on the memory population.

In accordance to previous reports (Zhang et al., 2007) EC memory CD8+ T-cells expressed PD-1 at significantly lower frequencies (mean: 30%) compared to memory

CD8 T-cells from CP (mean: 45%; p<0.01) and HIV- subjects (mean: 40%; p<0.01)

(Figure 4B). Furthermore, Lag-3 was expressed at low frequencies on memory CD8 T- cells (mean: 5-10%) regardless of infection status (Figure 4B). Memory CD8 T-cells in the EC cohort expressed significantly more CD160 (mean: 58%) compared to CP (mean:

27%, p<0.01) and HIV- individuals (mean: 32%, p<0.05) (Figure 4B). On the other hand, EC memory CD8 T-cells expressed 2B4 at frequencies comparable to those within

CP (mean: 84% and 86% respectively) but higher than their HIV- counterparts (mean:

72%, p<0.001) (Figure 4B). Differences in the proportion of memory CD8 T-cells expressing PD-1 and CD160 between elite controllers and chronic progressors could due to differences in differentiation status within the memory pool.

HIV elite controllers express a high frequency of CD160+2B4+ double positive CD8 T- cells A characteristic of T-cell exhaustion is the co-expression of inhibitory receptors on the cell surface (Blackburn et al., 2008; Wherry et al., 2007); therefore we assessed co-expression of PD-1, Lag-3, CD160 and 2B4 on total (Figure 5A) and memory CD8 T- cells (Figure 5B). A majority of the total and memory CD8 T-cells were grouped into

four populations: PD-1+Lag3-CD160+2B4+, PD-1-Lag-3-CD160+2B4+, PD-1+Lag-3-

CD160-2B4+ and PD-1-Lag-3-CD160-2B4+. Differences in frequency between the total and memory populations in EC, CP and HIV negative subjects were due to the fraction of naïve CD8 T-cells present (data not shown); therefore we continued our analysis on memory CD8 T-cells. EC had a higher frequency of PD-1-Lag-3-CD160+2B4+ memory

CD8 T-cells compared to CP (p<0.0001) and HIV negative individuals (p<0.0001). In contrast, EC expressed less PD-1+Lag-3-CD160-2B4+ than CP and HIV- subjects

(p<0.0001) and less PD-1-Lag-3-CD160-2B4+ than CP (p<0.05) (Figure 5B). We found a trend towards a higher frequency of the triple positive (PD-1+CD160+2B4+) population previously defined as exhausted (Yamamoto et al., 2011) in HIV positive subjects compared to HIV negative subjects, but this trend did not reach statistical significance.

DISCUSSION

Elite control of HIV infection is generally associated with the increased presence of polyfunctional and effector-like CD8 T-cell responses against HIV (Almeida et al.,

2007; Bailey et al., 2008; Betts et al., 2006; Gulzar & Copeland, 2004; Hersperger et al.,

2010). However, given the chronic nature of infection in these subjects and the continual need for effective immunosurveillance to prevent HIV recrudescence, one could hypothesize that CD8 T-cells in HIV elite controllers may display some indications of

CD8 T-cell exhaustion. Conversely, it is also possible that CD8 T-cell exhaustion does not manifest in HIV elite controllers, thus permitting superior longitudinal control of HIV

viremia. Here we began to address these issues by comparing the expression of previously identified exhaustion markers (Barber et al., 2006; Day et al., 2006; Doering et al., 2012; Trautmann et al., 2006; Zhang et al., 2007) on total and memory CD8 T-cells from elite controllers, chronic progressors and HIV negative individuals.

In line with previous reports, we found that elite controllers express low levels of

PD-1 compared to chronic progressors. Low expression of this receptor on the CD8 T cell population implies that CD8 T-cells in elite controllers do not experience the same level of population-wide exhaustion observed in chronic progressors. Interestingly, expression of CD160 on memory CD8 T-cells from elite controllers was significantly higher than in both chronic progressors and HIV negative subjects. CD160 expression has been shown be involved in both CD8 T-cell inhibition and induction of cytotoxicity.

Since elite control of HIV has been associated with increased cytolytic activity, in the context of elite controllers the high expression of CD160 could be a marker for CTL activity not inhibition. Further studies are needed to identify the signaling pathways involved in modulating expression and signaling of CD160.

In the context of T-cell exhaustion in HIV, co-expression of PD-1, CD160 and

2B4 has been associated with high viral loads and decreased polyfunctionality. If these markers truly define exhaustion, then our data would suggest the presence of a large population of exhausted (PD-1+CD160+2B4+) HIV-specific CD8 T-cells in elite controllers. Such a population might be indicative on ongoing low-level viral replication in lymphatic tissues known to harbor the viral reservoir and difficult to detect in blood.

Even though elite controllers suppress viral replication to undetectable levels, studies 28

have shown they can experience gradual loss of CD4 T-cells and immune activation due to microbial translocation (León et al., 2015; Novati, Sacchi, Cima, & Zuccaro, 2015) leading to clinical progression. The presence of exhausted T-cells in elite controllers supports the idea that factors other than viremia drive immune activation than can lead to immune dysfunction.

We also found that elite controllers have significant proportion of CD8 T-cells co- expressing CD160 and 2B4 not usually observed in chronic progressors. Both of these receptors have been previously associated with increased cytolytic activity. Co- expression of these markers in the absence of PD-1 could define a cytolytic population within these subjects. Such a population has been previously associated with elite control of HIV viral replication. In the last few years there has been an increased interest in the therapeutic value of blocking PD-1 clinic. These findings would suggest that PD-1 signaling is disrupting the cytolytic signaling pathway associated with expression of

CD160 and 2B4, providing a mechanism through which anti-PD-1/PD-L1 therapy works to re-invigorate CD8 T cell responses. Further studies into downstream signaling targets of PD-1 engagement are necessary to understand this idea further.

Figure 1: Flow cytometry gating scheme Flow cytometry gating scheme used on total peripheral blood mononuclear cells (PBMCs) to identify (A) memory phenotype and (B) expression of inhibitory receptors.

Figure 2: Representative flow cytometry lots of Individual expression of inhibitory receptors PD-1, Lag-3, CD160 and 2B4. Representative flow cytometry plots showing individual expression of inhibitory receptors on naïve and memory CD8 T-cells from an HIV negative, a chronic progressors and an elite controller subject.

Figure 3: Individual expression of PD-1, Lag-3, CD160 and 2B4 on total CD8 T- cells (A) The percentage of total CD8 T-cells from HIV-negative (blue circles), CP (red circles) and EC (green circles) individuals expressing each receptor. (B) Memory distribution of CD8 T-cells from HIV negative (HIV-; blue dots), chronic progressors (CP; red dots) and elite controllers (EC; green dots). Error bars represent mean + SEM. Dots indicate individual subjects. Statistical analysis was carried out using one-way ANOVA tests (nonparametric; Kruskal-Wallis) followed by a Dunns test for multiple comparisons. *p<0.05, ** p<0.01, *** p<0.001

Figure 4: Individual expression of PD-1, Lag3, CD160 and 2B4 on naïve and memory CD8 T-cells. (A) The percentage of naïve CD8 T-cells from HIV-negative (HIV-), chronic progressor (CP) and elite controllers (EC) expressing individual inhibitory receptors. (B) The percentage of memory CD8 T-cells from HIV-negative (HIV-), chronic progressor (CP) and elite controllers (EC) individuals expressing each receptor. Error bars represent mean + SEM. Statistical analysis was carried out using one-way ANOVA tests (nonparametric; Kruskal-Wallis) followed by a Dunns test for multiple comparisons. ** p<0.01, *** p<0.001

cells. - vidual subjects. *p<0.05, ** vidual ) (black bars), CP (dark grey bars) bars), CPgrey (dark ) (black - negative (HIV negative - analysis to get the relative expression of each possible inhibitory inhibitory possible of expression each relative the get to analysis cells from HIV cells - 3, CD160 and 2B4 coexpression patterns onandCD83, CD160total memory T and 2B4 coexpression -

1, Lag - PD

Figure 5: Figure Boolean a used in were gates expression Single CD8 of profile T expression memory receptor indi of Dots expression. indicate mean bars). Bars represent grey (light EC and p<0.01, *** p<0.001

CHAPTER 3: CO-EXPRESSION OF CD160 AND 2B4 IS

ASSOCIATED WITH PERFORIN EXPRESSION IN VIRUS-

SPECIFIC CD8 T-CELLS

SUMMARY

As discussed in chapter 2, we found that elite controllers have a population of potentially exhausted memory CD8 T-cells (PD-1+CD160+2B4+). In addition, we found a population of CD160+2B4+memory CD8 T-cells not commonly seen in chronic progressors. Both of these markers are associated with dual function when expressed, they are involved in increased cytolytic activity and T-cell exhaustion. The role of these receptors in the context of elite control of HIV infection remains unclear. To elucidate if expression of these markers in elite controllers delineate an exhausted population we measured co-expression of PD-1, CD160 and 2B4 together with the cytolytic molecule perforin and cytokines IFNγ and TNF on HIV-specific CD8 T-cells from elite controllers and compared them to CD8 T-cells from chronic progressors. We found that elite controllers have a proportion of possibly exhausted HIV-specific CD8 T-cells comparable to that of chronic progressors. However, we also found that the

CD160+2B4+ CD8 T-cells in elite controllers correlates with cytolytic capacity as measured by perforin expression. This double positive a population is not commonly found in HIV chronic progressors. We therefore propose that coexpression of CD160 and 2B4 delineate a population of CD8 T-cells important in the control of viral replication. This work was published in (Pombo et al., 2015) 35

INTRODUCTION

Cytolytic T lymphocytes (CTL) from elite controllers have a state of low immune activation, measured by HLA-DR and CD38, with the capacity for rapid proliferation

(Sáez-Cirión et al., 2007). Evidence shows that proliferative capacity is linked to increased perforin expression, facilitating the killing of infected cells and thus contribute to the efficacy of the cytotoxic response (Migueles et al., 2002). Previous work from our lab has shown that CD8 T-cell responses can be classified into polyfunctional memory

(IL2+IFNγ+ and other functions) or polyfunctional effector (perforin+IFNγ+ and other functions) responses based on viral specificity (Makedonas et al., 2010). In the context of non-progressive HIV disease, highly functional effector HIV-specific CD8 T-cells are preferentially maintained and are an important component in the control of HIV replication (Betts et al., 2006; Gea-Banacloche et al., 2000; Hersperger et al., 2010;

Migueles et al., 2008; Sáez-Cirión et al., 2007). Additional evidence suggests that the number of T-cells with a highly polyfunctional effector response correlates with immune protection during viral infections (Almeida et al., 2007; Betts et al., 2001; Darrah et al.,

2007; Precopio et al., 2007; Schellens et al., 2008). Furthermore, the non-human primate model of SIV infection supports the role of CD8 T-cells in controlling viral replication, where depletion of CD8 T-cells correlates with an increase in SIV viral load and rapid disease progression (Jin et al., 1999; Schmitz et al., 1999). However, during chronic progressive HIV disease, HIV-specific CD8 T-cells lose their ability to proliferate,

become non-cytolytic and lose polyfunctionality (Peretz et al., 2012; Trautmann et al.,

2006; Yamamoto et al., 2011).

Several studies have shown a strong association between high levels of the inhibitory receptor PD-1, viral loads and disease progression (D'Souza et al., 2007; Day et al., 2006; Freeman, Wherry, Ahmed, & Sharpe, 2006; Petrovas et al., 2006; Trautmann et al., 2006; Yamamoto et al., 2011). A previous study found that CD8 T-cells from elite controllers expressed remarkably low levels of PD-1 compared to that of chronic progressors (Zhang et al., 2007).

However, T cell exhaustion is characterized by an accumulation of inhibitory receptors including CD160 and 2B4 (Blackburn et al., 2008; Peretz et al., 2012;

Yamamoto et al., 2011). To better understand the relationship between expression of inhibitory receptors and T-cell function in the context of elite control of HIV infection, we measured PD-1, Lag-3, CD160 and 2B4 expression patterns on HIV-specific CD8 T- cells from elite controllers and chronic progressors. In addition, we assessed the ability of CD8 T-cells expressing multiple inhibitory receptors to produce effector functions such as IFNγ, TNF and perforin. We found that Gag-specific CD8 T-cells from elite controllers co-express PD-1, CD160 and 2B4 suggesting a level of exhaustion similar to that of chronic progressors. However, elite controllers also have a large population of

Gag-specific CD8 T-cells co-expressing CD160 and 2B4 that is associated with cytolytic potential. Together these data suggests that the co-expression of inhibitory markers on

HIV-specific CD8 T-cells must be interpreted within the context of T-cell function and phenotype, as well as HIV disease control status.

MATERIALS AND METHODS

PBMC samples: See chapter 2.

Antibodies

Antibodies for surface staining included anti-CD4 PE-Cy5.5 (clone S3.5, Invitrogen), anti-CD8 Qdot605 (clone 3B5, Invitrogen) or Brilliant Violet 605 (clone RPA-T8,

Biolegend), anti-CD27 Qdot 655 (clone CLB-27/1, Invitrogen) or Brilliant Violet 650

(clone O323, Biolegend), anti-CD45RO ECD (clone UCHL1, Beckman Coulter), anti-

PD-1 PE (clone EH12.2 H7, Biolegend), anti-CD160 (Cai et al., 2008), conjugated in- house) FITC and anti-CD244 (2B4) PE-Cy5 (clone C1.7, Beckman Coulter), anti-CD14

APC-AF750 (clone TüK4, Invitrogen), anti-CD19 APC-AF750 (clone SJ25-C1,

Invitrogen), anti-Lag-3 biotin (polyclonal, R&D Systems), Streptavidin-APC

(Invitrogen), and anti-APC biotin (clone eBioAPC-62A, eBiosicience). Antibodies for intracellular staining included anti-CD3 Qdot 585 (custom conjugation performed in our laboratory as previously described (Chattopadhyay et al., 2006) or Brilliant Violet 570

(clone UCHL1, Biolegend), anti-Perforin Pac Blue (clone B-D48, custom conjugation performed in our laboratory as previously described (Chattopadhyay et al., 2006) or

Brilliant Violet 421 (clone B-D48, Biolegend), anti-IFN-γ Alexa-700 (clone B27,

Invitrogen), and anti-TNF PE-Cy7 (clone MAb11, BD Biosciences).

PBMC Stimulation

Cryopreserved PBMCs were thawed and then rested overnight at 37°C, 5% CO2 in complete medium [RPMI (Mediatech Inc; Manassas, Virginia) supplemented with

10% FBS, 1% L-glutamine (Mediatech Inc; Manassas, Virginia) and 1% Penicillin- streptomycin (Lonza; Walkersville, Maryland), sterile filtered at a concentration of 2x106 cells/ml of medium. The next day, the cells were washed with complete medium and resuspended at a concentration of 1x106 cells/ml with co-stimulatory antibodies (anti-

CD28 and anti-CD49d; 1µg/ml final concentration; BD Biosciences; San Jose,

California), in the presence of brefeldin A (1µg/ml final concentration; Sigma-Aldrich;

St. Louis, Missouri). Next, cells were stimulated with exogenous peptide pools for HIV gag-PTE (NIH AIDS Reference Reagent Program) or EBV proteins (BCRF1, BMLF1,

BMRF1, BRLF1, BZLF1, gp85, gp110, gp350 and EBNA4 at 2µg/mL each peptide) at

5µL/mL. Stimulation with SEB (1 µg/ml; Sigma-Aldrich) was used as a positive control or DMSO (5µL/mL) as a negative control. PBMCs were then incubated at 37°C, 5%

CO2 for 5 hours.

FACS staining assay: See chapter 2.

Flow cytometry analysis: See chapter 2.

RESULTS

Expression of PD-1, Lag-3, CD160 and 2B4 on HIV- & EBV-specific CD8 T-cells

To investigate the potential level of T-cell exhaustion within HIV elite controllers, we measured expression of PD-1, Lag-3, CD160 and 2B4 on HIV-specific CD8 T-cells.

For comparison, we also measured expression of these inhibitory receptors on EBV- specific CD8 T-cells known to express high levels of PD-1 but remain functional

(Petrovas et al., 2006). Virus-specific CD8 T-cells were identified by intracellular staining for IFNγ and TNF after 6 hours of stimulation with an overlapping peptide pool spanning the HIV Gag protein or with an EBV peptide pool containing previously defined EBV epitopes derived from the EBV proteins BCRF1, BMLF1, BMRF1,

BRLF1, BZLF1, gp85, gp110, gp350 and EBNA4 for CD8 T-cell responses. Figures 6A and B show representative flow cytometry plots of PD-1, Lag-3, CD160 and 2B4 expression on HIV and EBV-specific cells from EC and CP, as well as EBV-specific

CD8 T-cells from HIV- subjects overlaid onto corresponding memory populations.

Similar to the memory compartment, HIV-specific CD8 T-cells from EC expressed less PD-1 (mean: 50%) and more CD160 (mean: 65%) than CP (mean: 75%, p<0.0001; mean: 20%, p<0.0001 respectively) (Figure 6C). Gag-specific CD8 T-cells from EC and CP had a higher proportion of PD-1 expression compared to their memory subset (p=0.0004, p<0.0001 respectively) but not CD160 or 2B4 (Figure 7A and B).

Gag-specific CD8 T-cells from EC also had a higher proportion of Lag-3 expression compared to the memory population (p=0.006). In comparison, EBV-specific CD8 T- cells from EC and CP had similar levels of PD-1, Lag-3 and 2B4 expression; but

CD160+ EBV-specific cells were significantly higher in EC (mean: 60%) compared to

CP (mean: 20%, p <0.001; Figure 6D). Unlike HIV-specific CD8 T-cells, the proportion 40

of PD-1, Lag-3 and CD160 expression on EBV-specific CD8 T-cells from EC and CP did not significantly differ from that of their corresponding memory populations; however, a higher proportion of EBV-specific CD8 T-cells from HIV- individuals expressed PD-1 and Lag-3, but less CD160, than their memory populations (p=0.04, p=0.003, p=0.03 respectively) (Figure 7C).

Gag-specific CD8 T-cells from EC express multiple inhibitory receptors

We next evaluated co-expression of PD-1, Lag-3, CD160 and 2B4 on HIV and

EBV-specific CD8 T-cells. HIV-specific CD8 T-cells from EC were mainly distributed between three major populations: PD-1+CD160+2B4+, CD160+2B4+ and PD-1+2B4+ with a small percentage of cells expressing only 2B4 (Figure 8A). In comparison, HIV- specific CD8 T-cells from CP were restricted into two major populations: PD-

1+CD160+2B4+ and at a higher proportion than EC, PD-1+2B4+ (p<0.0001), with a minor proportion expressing 2B4 alone (Figure 8A). Consistently, EBV-specific CD8 T- cells from EC, CP and HIV- subjects expressed the same key combinations of inhibitory receptors seen in HIV-specific cells (Figure 8B).

Previous work has linked the co-expression of 3 or more inhibitory receptors on antigen-specific CD8 T-cells to exhaustion (Bengsch et al., 2010; Blackburn et al., 2008;

Riches et al., 2013; Yamamoto et al., 2011); therefore, we examined the number of receptors co-expressed by HIV and EBV-specific CD8 T-cells. Thirty percent of HIV- specific CD8 T-cells from EC expressed any combination of 3 inhibitory receptors.

Surprisingly, a significantly smaller proportion of the HIV-specific CD8 T-cells from CP 41

expressed 3 inhibitory receptors (19%, p<0.01) (Figure 9A). Of interest, a considerable percentage of HIV-specific CD8 T-cells from EC (46%) and CP (52%) expressed only 2 inhibitory receptors (Figure 9A), indicating that a large portion of the HIV-specific CD8

T-cell response falls within this group. On the other hand, EBV-specific CD8 T-cells from EC, CP and HIV- subjects are equably divided between co-expression of 2 inhibitory receptors and a single inhibitory receptor (Figure 9B). Together, this data suggests that even though previous work has associated the triple positive (TP) population PD-1+CD160+2B4+ with T-cell exhaustion, the presence of this population alone does not explain the differences between EC and CP; instead, the presence or absence of the CD160+2B4+ and PD1+2B4+ populations could contribute to the differences between EC and CP.

Co-expression of CD160 and 2B4 is associated with cytolytic capacity of CD8 T-cells

Highly functional effector HIV-specific CD8 T-cells are preferentially maintained and are an important component in the control of HIV replication (Almeida et al., 2007;

Betts et al., 2006; Hersperger et al., 2010). Effector responses can be characterized by the presence of the cytolytic molecule perforin, along with expression of IFNγ and/or

TNF and the lack of IL-2 expression (Makedonas et al., 2010). In addition, expression of

PD-1 has been associated with decreased cytolytic effector function, but CD160 and 2B4 have been shown to both stimulate and inhibit cytolytic activity (Meinke & Watzl, 2013;

Nikolova et al., 2002; 2005; Rey et al., 2006; Schlaphoff et al., 2011; Sinha, Gao, Guo, &

Yuan, 2010; Šedý et al., 2013; Viganò et al., 2014; Yamamoto et al., 2011). Furthermore, 42

there is evidence that expression of these markers increases upon activation and those cells remain functional (Legat et al., 2013; Meinke & Watzl, 2013; Nikolova et al., 2005;

Zelinskyy et al., 2011).

To examine the relationship between expression of PD-1, CD160 and 2B4 in the context of CD8 T-cell functionality, we first assessed the functional profile of the HIV- specific and EBV-specific CD8 T-cells by staining for the cytolytic marker perforin in combination with IFNγ and TNF. Representative flow cytometry plots indicating the gating scheme is shown in figure 10A. In accordance to previous reports, EC had a higher proportion of perforin+ HIV-specific responses (p<0.01) compared to CP, whose responses consisted mainly of IFNγ+ CD8 T-cells (p<0.001) (Figure 10B). Similarly, EC had a high proportion of perforin+ EBV-specific responses compared to CP and HIV- negative individuals (p<0.5), but a large proportion of the EBV-specific response from the tree groups was TNF+IFNγ+ (Figure 10). Next, we divided responding cells into two subsets; effector responses: perforin+ (IFNγ+ and/or TNF+) and memory responses: perforin- (IFNγ+ and/or TNF+), and assessed the co-expression of PD-1, CD160 and 2B4

(Figure 11).

A significantly high proportion of the perforin+ HIV and EBV-specific responses were grouped within the PD-1 negative subsets. In contrast, a significant portion of the perforin- (IFNg+ and/or TNF+) HIV and EBV-specific responses were grouped within the PD-1+ subsets (Figure 11A and B). We next assessed the relationship between perforin and PD-1, CD160 and 2B4 expression individually or in combination by HIV- specific CD8 T-cells. We found an inverse correlation between perforin and PD-1 (Figure 43

12A), but not with CD160 or 2B4 (Figure 12B and C). However, there was a negative correlation between the fraction of perforin+ effector responses and the proportion of responding cells co-expressing PD-1+2B4+, and a positive correlation with co-expression of CD160+2B4+ in both HIV and EBV-specific CD8 T-cells (Figure 13A and B).

Together these data suggest that specific inhibitory receptor co-expression patterns define

CD8 T-cells with different functional capacities and that certain inhibitory receptor combinations may be associated with markers of viral control.

DISCUSSION

We have previously shown that perforin expression by HIV-specific CD8 T-cells is a correlate of protection against HIV disease progression in HIV elite controllers

(Hersperger et al., 2010). Interestingly, our results indicate that perforin expression in

HIV-specific CD8 T-cells in EC and CP is highly associated with the expression of

CD160 and 2B4. These two co-receptors have been shown to have both inhibitory and stimulatory roles in effector functions of T-cells and NK cells. (Meinke & Watzl, 2013;

Merino et al., 2007; Nikolova et al., 2002; 2005; Rey et al., 2006; Schlaphoff et al., 2011;

Sinha et al., 2010; Šedý et al., 2013; Viganò et al., 2014; Yamamoto et al., 2011). CD160 can be expressed in two isotypes: GPI-anchored (CD160-GPI) and with a transmembrane domain (CD160-TM). Cross-linking CD160-GPI has been shown to have an activating effect on CD4 and CD8 T-cell function (El-Far et al., 2014). However the signaling pathway of CD160-TM has not been characterized, and further studies are necessary to

elucidate a possible role in T-cell exhaustion. On the other hand, the duality of 2B4 has been associated to expression levels of the adaptor proteins SAP and EAT-2 or recruitment of FynT (Meinke & Watzl, 2013). Our results imply that expression of

CD160 and 2B4, rather than signifying exhaustion, may identify a population of activated cytolytic CD8 T-cells important in the response against HIV. In this context, CD160 and

2B4 may be acting as activating co-receptors and not as inhibitory receptors. We therefore hypothesize that PD-1 signaling in the exhausted triple positive population tempers the association between perforin, CD160 and 2B4. Further studies are necessary to elucidate if a downstream target of PD-1 signaling modulates CD160-TM signaling as well as its involvement in modulating 2B4 downstream signaling by regulating SAP or

FynT levels.

Differences between elite controllers and chronic progressors have been studied in order to identify correlates of protection that can be used to improve current therapies and develop vaccines against HIV. Efforts to revitalize antigen-specific CD8 T-cell responses to chronic infections and cancer by blocking the PD-1 inhibitory pathway are ongoing and clinical trials in solid tumors show promising results (reviewed in (Harvey,

2014); A5326: Anti-PD-L1 Antibody in HIV-1, https://actgnetwork.org/study/a5326-anti- pd-l1-antibody-hiv-1; NCT01629758: Safety Study of IL-21/Anti-PD-1 Combination in the Treatment of Solid Tumors, http://www.clinicaltrials.gov/ct2/show/NCT01629758?term=PD-1&rank=4). This study shows that not all “inhibitory” receptors are detrimental and in fact some may play a positive role in the anti-viral response. In the context of HIV infection, studies involving 45

expression of inhibitory receptors and T-cell exhaustion would benefit from simultaneously measuring effector functions such as proliferation, IL-2 and perforin production, since these functions delineate different but important T-cell populations and are not always expressed by the same cell. Additionally, expression of inhibitory receptors is not only linked to T-cell exhaustion but also to differentiation/activation status, antigen specificity and anatomical localization (Baitsch et al., 2012; Legat et al.,

2013). For the development of new therapeutics, one must take into account the context in which inhibitory markers are being expressed and whether expression signifies exhaustion or delineates an immunologically important population. Additionally, it is important to understand the unintended consequences blocking these inhibitory receptor pathways may have on non-exhausted T-cell populations.

Figure 6: PD-1, Lag-3, CD160 and 2B4 expression on HIV and EBV-specific CD8 T- cells. PBMCs were stimulated for 6 hours with a Gag-PTE peptide pool or an EBV pool containing peptides derived from lytic proteins. Responding CD8 T-cells were identified by IFNγ and TNF production. (A) Representative flow cytometry plots of PD-1, Lag-3, CD160 and 2B4 expression on HIV-specific (red) and (B) EBV-specific (blue) CD8 T- cells. (C) Percentage of Gag-specific CD8 T-cells expressing individual inhibitory receptors. (D) Percent of EBV-specific CD8 T-cells expressing individual inhibitory receptors. Error bars represent mean + SEM. ** p<0.01, *** p<0.001

Figure 7: Comparison between the proportion of memory, HIV and EBV-specific CD8 T-cells The proportion of memory CD8 T-cells expressing individual inhibitory receptors was compared to the proportion of expression on HIV-specific and EBV-specific CD8 T- cells. (A) elite controllers (EC), (B) Chronic progressors (CP), (C) HIV-negative. Bars represent the mean and error bars indicate SEM. *p<0.05, ** p<0.01, *** p<0.001

- -

specific CD8 T specific - specific and B) EBV and specific - expressed. - sors (CP), and elite controllers (EC). (EC). controllers sors (CP),elite and negative, chronic progres chronic negative, - 3, CD160 and 2B4 coexpression patterns on 3, CD160HIV and and 2B4 coexpression EBV - cells were then grouped by the number of receptors co of number receptors by the grouped then were cells - cells from HIV cells 1, Lag - -

Figure 8: PD Figure cells. cells. relative the get to analysis Boolean a used in were TNF+ on IFN cells + and/or gates γ expression Single of profile expression A) Gag receptor inhibitory possible ofexpression each CD8 T specific CD8 Responding T

Figure 9: Number of inhibitory receptors expressed by HIV and EBV-specific CD8 T-cells. (A) Percent of Gag-specific CD8 T-cells co-expressing inhibitory receptors. (B) Percent of EBV-specific CD8 T-cells co-expressing inhibitory receptors. HIV-negative (blue line), CP (red line), and EC (green line). Error bars represent mean + SEM. * p<0.05, ** p<0.01, *** p<0.001

Figure 10: Functional profile of HIV and EBV-specific CD8 T-cells. Proportion of cytokine and perforin production by CD8 T-cells in response to peptide pool stimulation of PBMCs with a Gag-PTE peptide pool or an EBV pool containing peptides derived from lytic proteins. (A) Representative flow cytometry plots showing the gating scheme for IFNγ, TNF and perforin expression. (B) HIV Gag-specific response. (C) EBV-specific response. HIV-negative (HIV-, blue bars), chronic progressors (CP, red bars) and elite controllers (EC, green bars). Bars represent mean of expression: each dot represents a subject. * p<0.05, ** p<0.01, *** p<0.001

Figure 11: PD-1, CD160 and 2B4 co-expression on perforin+ and perforin virus- specific CD8 T-cells. Responding CD8 T-cells identified by IFNγ and/or TNF production were divided into perforin+ and perforin- responses. (A) Relative expression of each possible inhibitory receptor expression profile of perforin+ (dark gray) and perforin- (light gray) HIV-specific responses from EC (top) and CP (bottom). (B) Relative expression of each possible inhibitory receptor expression profile of perforin+ (dark gray) and perforin- (light gray) EBV-specific responses from HIV negative (top), EC (middle) and CP (bottom). Bars represent mean of expression: each dot represents a subject. ** p<0.01

Figure 12. Association between perforin and expression of PD-1 but not CD160 or 2B4. Correlation between the percent of the HIV-specific CD8 T-cell response that is perforin+ and the percent of the response expressing (A) PD-1, (B) CD160 or (C) 2B4. CP (red dots), EC (green dots). Spearman R and p value of correlations are depicted in the upper right corner of each graph. Lines represent linear regression.

Figure 13. Association between perforin and co-expression of CD160 and 2B4. Correlation between the percent of the (A) HIV-specific and (B) EBV-specific CD8 T- cell response that is perforin+ and the percent of the response co-expressing inhibitory receptors. HIV negative (blue dots), CP (red dots), EC (green dots). Spearman R and p value of correlations are depicted in the upper right corner of each graph. Lines represent linear regression.

CHAPTER 4: EXPRESSION OF INHIBITORY RECEPTORS IN HIV+ LYMPH

NODES IN CHRONIC PROGRESSORS AND SUBJECTS ON

ANTIRETROVIRAL THERAPY

SUMMARY

Early in HIV infection viral replication occurs preferentially in tissues, including the gastrointestinal tract and secondary lymphoid organs (Pantaleo et al., 1991). Viral replication in LNs exceeds the levels in plasma by several orders of magnitude and is associated with a gradual destruction of the highly ordered architecture of the LN, marked by a follicular hyperplasia, massive CD4 T-cell apoptosis, and the final involution of the LN (Cohen, Pantaleo, Lam, & Fauci, 1997).

ELISpot assays were used to detect HIV-specific responses in lymph nodes even after full viral suppression on ART (Altfeld et al., 2002). These observations suggested that lymph nodes are also major sites of viral replication and harbor the viral reservoir even when virus is undetectable in blood (Altfeld et al., 2002). Though immune responses to HIV infection have been widely studied in blood, much less is known about the role of the virus-specific cellular immune responses in the lymphoid tissues. To this day, HIV remains an incurable disease, partly due to the inability to find and eliminate latently infected CD4 T cells. Cytolytic CD8 T cells resident in the lymph nodes are good candidates for that task. Here, we measured markers of exhaustion on CD8 T cells from HIV chronic individuals (CP) and HIV+ individuals on antiretroviral therapy (ART) and compared it to expression on CD8 T cells from blood. We find that CP lymph nodes 55

have a large proportion of exhausted PD-1+CD160+2B4+ HIV-specific CD8 T cell population than that in blood. We also found that LN CD8 T cells express low levels of

T-bet, a transcriptor factor associated with perforin expression. However we also find that in LN, perforin expression dissociates from T-bet, suggesting there are other factors involved in modulating cytolytic activity within these tissues.

INTRODUCTION

Lymphatic tissues contain 95% of the body’s lymphocytes, with approximately

41% residing in lymph nodes, 15% in the spleen and 20% in gut tissues including GALT and LP. In contrast, only 2% of total lymphocytes are found in the blood (Ganusov & De

Boer, 2007). Lymph nodes are of great immunological significance in the fight against infection and are major sites of antigen presentation and surveillance (Altfeld et al.,

2002). Lymph contain 95% of the body’s lymphocytes and are major site of antigen presentation and surveillance (Altfeld et al., 2002). The lymph node structure separates T cells into the T-cell zone and B cells into the B cell follicle. When dendritic cells from tissues migrate to lymph nodes carrying antigens they stimulate naive T cells by interactions between the T cell receptors and MHC-I:antigen complexes and other co- stimulatory molecules. Activated CD4 T-cells (TFH) then migrate into B cell follicles and form germinal centers, where they stimulate B cell proliferation, antibody production and isotype switching. Follicular dendritic cells (FDC) bind antigen-antibody complexes in

germinal centers and serve to stimulate T-cells in the T-cell zone and drive affinity maturation of the B cell response (reviewed in (Mondino, Khoruts, & Jenkins, 1996).

During the initial stages of HIV infection dendritic cells and macrophages present in GALT are among the first to encounter the virus. HIV then uses these cells as vehicles to reach the lymph nodes where it gains access to a target rich environment (Baxter et al.,

2014; Harman, Kim, Nasr, Sandgren, & Cameron, 2013; Nasr et al., 2014). In fact, a large number of latently infected CD4 T-cells and macrophages can be found in LN through out the course of disease (Embretson et al., 1993). Though NK cells in the periphery respond to HIV infection and are able to kill infected cells (O'Connell et al.,

2009), these cytotoxic NK cells do not accumulate in LN during acute infection (Luteijn et al., 2011), allowing robust viral replication and viral reservoirs to be established

(Pantaleo et al., 1991).

Current antiretroviral therapies reduce viral replication to undetectable levels in both blood and lymph nodes, but that requires strict adherence to treatment guidelines

(Gray et al., 2000). However, treatment interruption and lapses in adherence allow HIV viral loads rebound (Altfeld et al., 2002) and can allow new T cell depletion and drug resistant mutations that result in therapy failure. Immune reconstitution during antiretroviral therapy (ART) has been shown to be incomplete regardless of increased

CD4 and CD8 T-cell numbers, particularly affecting GALT (MD et al., 2009).

Furthermore, with new infections in adolescents and young adults on the rise, the number of years an individual will spend on ART has increased significantly. This brings into

question the long-term effects of ART. Thus there is a vast effort to find a viable way of eradicating the viral reservoir present in lymphatic tissues and de-intensify the use of antiretroviral drugs.

There are Important differences between blood and lymph node CD8 T-cells during HIV infection, including significantly lower levels of perforin expression in LN

(O. O. Yang et al., 2005). Furthermore, Immunohistochemistry studies showed high levels of PD1 expression mostly on CD45R0+ helper/inducer T-cells (TFH) localized in the germinal centers, these levels do not change after initiation of ART (Cubas et al.,

2013; MD et al., 2009). PD-1 is expressed on a small proportion of LN CD8 T-cells on chronic subjects, after ART the levels of expression on CD8 T cells remained the same, the number of PD-1+ CD8 T cells within the LN was significantly reduced (MD et al.,

2009). T cell exhaustion in the context of HIV infection has been mainly characterized using T-cells derived from blood. Tissue specific differences in PD-1 expression in animal models (Blackburn et al., 2010) and humans (Fourcade et al., 2012; Kroy et al.,

2014; MD et al., 2009; Wu et al., 2014) highlight the importance of understanding T cell exhaustion in tissues relevant to disease. In the case of HIV infection, lymph nodes are a major source of target cells, viral replication and harbor the viral reservoir.

Efforts to reinvigorate the immune system, primarily by blocking interactions between PD-1 and PD-L1, have shown that the PD-1 profile of PBMCs is not sufficient to predict how an individual will react to PD-1 blockade therapy. In the context of HCV infection, CD8 T cells in the liver were highly PD-1 positive, profoundly dysfunctional,

and poorly responsive to PD-1/PD-L blockade, unlike CD8 T cells in blood. This suggest a differential level of HCV-specific CD8 T-cell exhaustion in HCV-infected patients that is defined by their compartmentalization and PD-1 expression (Nakamoto et al., 2008).

This data also emphasizes that looking at the PD-1 expression profile in lymph nodes is crucial to understanding the effects on blockade therapy and if the CD8 T-cells present in

LN will be able to eliminate the HIV reservoir.

The ability of CD8 T cells to directly kill target cells is associated with expression of the lytic molecule perforin. However, the proportion of CD8 T cells in the lymph node that express perforin is small (O. O. Yang et al., 2005). Whether the low level of perforin expression is low due to tissue-specific requirements or due to exhaustion remains to be determined. Here, we measure transcription factor T-bet, a member of the T-box family, is involved in T-cell development and modulation of effector functions. T-bet expression reached its maximal induction at the effector phase and partially declined in the memory phase (Takemoto, Intlekofer, Northrup, Wherry, & Reiner, 2006). Expression of high levels of T-bet correlates with effector CD8 T cell phenotype in blood and it is associated with cytolytic activity in elite control of HIV (Buggert et al., 2014; Hersperger et al.,

2011; Kao et al., 2011; Knox, Cosma, Betts, & McLane, 2014). Our previous study

(chapter 3) showed an association between CD160+2B4+ expression and perforin.

Therefore we assessed if there is an association between co-expression of these receptors and expression of the transcription factor T-bet in blood and lymph nodes.

MATERIALS AND METHODS

PBMC and LNMC samples

Peripheral blood mononuclear cells (PBMC) were obtained from HIV negative subjects at the University of Pennsylvania's Center for AIDS Research Immunology Core and cryopreserved in fetal bovine serum (FBS; ICS Hyclone, Logan Utah) containing

10% dimethyl sulfoxide (DMSO; Fisher Scientific, Pittsburgh, Pennsylvania). Lymph node mononuclear cells (LNMC) from HIV negative individuals were obtained from the

Geriatric Research, Education and Clinical Center (GRECC), Louis Stokes Cleveland VA

Medical Center, Division of Infectious Disease, Case Western Reserve University.

PBMCs and LNMCs from HIV positive individuals were obtained from the Center for

Research on Infectious Disease (CIENI), National Institute of Respiratory Disease,

Mexico DF, Mexico. All samples were collected in compliance with the guidelines set by the institutional IRBs.

Chronic progressors (CP) were defined as untreated individuals with HIV plasma

RNA levels >4,000 copies/mL (range: 4,000-150,00, mean: 66,000), diagnosed for >1 year and ART naïve. ART subjects were defined as on therapy for >6 months and fully suppressed viral loads <100 HIV RNA copies/mL. All subjects had CD4 counts >200 cells/mm3.

Antibodies

Antibodies for surface staining included anti-CD4 PE-Cy5.5 (clone S3.5,

Invitrogen), anti-CD8 BV605 (clone RPA-T8, Biolegend), anti-CD27 BV650 (clone

O323, Biolegend), anti-CD45RO ECD (clone UCHL1, Beckman Coulter), anti-PD-1 60

BV711 (clone EH12.2 H7, Biolegend), anti-CD160 FITC ((Cai et al., 2008)), anti-CD244

(2B4) PE-Cy5 (clone C1.7, Beckman Coulter), anti-CD14 APC-Cy7 (clone TüK4,

Invitrogen), anti-CD19 APC-Cy7 (clone SJ25-C1, Invitrogen). Antibodies for intracellular staining included anti-CD3 BV570 (clone UCHL1, Biolegend), anti-T-bet

PE (clone 4B10, eBioscience), anti-Perforin BV421 (clone B-D48, Biolegend), anti-IFN-

γ Alexa-700 (clone B27, Invitrogen), and anti-TNF PE-Cy7 (clone MAb11, BD

Biosciences).

PBMC and LNMC Stimulation

Cryopreserved PBMC and LNMC were thawed and rested overnight at 37°C, 5%

CO2 in complete medium [RPMI (Mediatech Inc; Manassas, Virginia) supplemented with

10% FBS, 1% L-glutamine (Mediatech Inc; Manassas, Virginia) and 1% Penicillin- streptomycin (Lonza; Walkersville, Maryland) at a concentration of 2x106 cells/ml of medium. The cells were then washed with complete medium and re-suspended at a concentration of 1x106 cells/ml with co-stimulatory antibodies (anti-CD28 and anti-

CD49d; 1µg/ml final concentration; BD Biosciences; San Jose, California), in the presence of brefeldin A (1µg/ml final concentration; Sigma-Aldrich; St. Louis, Missouri).

Next, cells were stimulated with exogenous peptide pools for HIV Gag-PTE (NIH AIDS

Reference Reagent Program) or EBV proteins (BCRF1, BMLF1, BMRF1, BRLF1,

BZLF1, gp85, gp110, gp350 and EBNA4) at 400µg/ml. Stimulation with SEB (1 µg/ml;

Sigma-Aldrich) was used as a positive control or DMSO (5µL/mL) as a negative control.

PBMC and LNMC were stimulated at 37°C, 5% CO2 for 5 hours. 61

FACS staining assay

After stimulation, cells were washed once with FACS buffer and stained with

Aqua amine-reactive viability dye (Invitrogen) for 10 minutes to exclude non-viable events, the cells were then stained for surface markers with an antibody cocktail for an additional 30 minutes. Following a wash with FACS buffer, cells were permeabilized with Cytofix Cytoperm (BD Biosciences) as per manufacturer’s instructions. Next, a cocktail of antibodies against intracellular markers was added and incubated for an hour.

Lastly, cells were washed with Perm Wash Buffer (BD Biosciences) and fixed in PBS containing 1% paraformaldehyde. All incubations were done at room temperature in the dark. Fixed cells were stored at 4°C until the time of collection.

Flow cytometric analysis

Antibody capture beads (BD Biosciences) were used to prepare individual fluorophore matched compensation tubes for each antibody used in the experiments. Data analysis was performed using FlowJo version 9.8.1 (TreeStar, Inc). Reported functional data have been corrected for background. Statistical analysis was performed with Prism version

5.0. Comparisons between HIV negative blood and LN samples were analyzed using the

Mann-Whitney tests. Comparisons between HIV blood and LN samples from CP and

ART treated individuals were analyzed using a paired T test since this samples were 62

matched. Comparisons amongst cohort groups were analyzed using one-way ANOVA tests (nonparametric; Kruskal-Wallis) followed by a Dunns test for multiple comparisons.

Correlation coefficients were calculated using the Spearman rank sum test. All tests were

2-tailed and P values less than 0.05 were considered significant.

RESULTS

High expression of PD-1 by CD8 T cells from lymph nodes compared to blood

To determine if the levels of T-cell exhaustion, in blood are representative of the lymph node environment and determine the effect of antiretroviral therapy, we collected matched CD8 T-cells from blood (PBMCs) and lymph nodes (LNMCs) from 14 HIIV chronic progressors (CP), 9 HIV+ patients on ART (ART) and 15 (not matched) HIV negative individuals. We used polychromatic flow cytometry to simultaneously measure expression of inhibitory receptors PD-1, CD160 and 2B4 as a measure of exhaustion.

Blood and lymph node samples were analyzed together to minimize experimental variability. Representative flow cytometry plots showing the gating scheme for analysis of PD-1, CD160 and 2B4 are shown in figure 14. Differential expression of CD27 and

CD45RO was used to identify naïve CD8 T cells (Figure 14A). As with the previous study (Chapter 2), the naïve population from PBMCs was used as reference to determine surface expression of individual inhibitory receptors. Gates from the PBMC sample was then “dropped” onto the corresponding LNMCs. Flow cytometry plots showing differential expression of PD-1, CD160 and 2B4 on naïve and memory CD8 T cells from 63

blood and lymph node from a CP, ART and an HIV negative subject are shown in Figure

14B and C.

The presence of a larger proportion of naïve CD8 T-cells in the lymph nodes compared to blood (Figure 15A) can skew comparisons between these two compartments; therefore we excluded this population from further analysis. Additionally,

HIV negative subjects have more naïve CD8 T-cells compared to both CP and ART subjects (Figure 15A). Lymph nodes also have a larger proportion of CM, no significant difference between HIV negative, CP and ART subjects (Figure 15B). There is a greater proportion of EM CD8 T-cells in HIV positive subjects compared to HIV negatives.

(Figure 15C). Of note, there is also a large difference in the proportion of effector cells found in blood versus the lymph node (Figure 15D).

In the blood, CP shows a trend towards higher expression of PD-1 compared to

ART or HIV negative subjects though it does not reach statistical significance (Figure

16A). However, expression of CD160 and 2B4 is significantly higher in CP compared to

HIV negative subjects (p<0.001) (Figure 16A). Of note, expression of CD160 in chronic progressors is higher in this cohort than CP from the cohort used in our previous study

(Figure 4). A caveat of this study is that we are comparing CP and ART subjects from

Mexico City to HIV negative subjects from the United States. Genetic or environmental differences could explain the discrepancy in CD160 expression. This issue can be addressed by sampling HIV negative subjects in the same geographical area as a control.

In the lymph node, chronic progressors expressed significantly more PD-1 than

HIV negative subjects (p<0.001) and there is reduced expression on ART subjects

(Figure 16B). Expression of CD160 in LN was not statistically different between the three groups. 2B4 expression was higher in CP than HIV negative subjects (p<0.001).

Subjects on ART showed a trend towards lower expression than CP (Figure 16B).

Overall, the relationships of inhibitory receptor expression observed in blood are preserved in the LN.

Next, we compared expression individual of inhibitory receptors on memory CD8

T cells from blood to those from LN. PD-1 expression is significantly higher in LN memory CD8 T cells compared to blood in CP (p<0.001), ART (p<0.01) and HIV negative subjects (p<0.5) (Figure 17A). CP and ART subjects also have a significantly higher per-cell expression (MFI) of PD-1 in LN compared to blood (p<0.001, p<0.01 respectively) (Figure 17B). Though there are no differences in the proportion of CD160+ memory CD8 T cells in LN or blood, the per-cell levels of expression in HIV negative

LN is significantly higher than that of blood (p<0.01) (Figure 17C and D). Interestingly, both the proportion and per-cell levels of 2B4 expression in blood and LN from CP and

ART subjects did not differ, but the proportion in HIV negative lymph nodes was significantly lower (p<0.01) (Figure 17E and F).

Co-expression of CD160 and 2B4 by CD8 T cells from Chronic progressors and HIV+ on ART

To assess any differences in the level of CD8 T-cell exhaustion in lymph nodes and blood, we measured the co-expression of PD-1, CD160 and 2B4. Various groups have shown that co-expression of these receptors define a population of exhausted CD8

T-cells in blood (Figure 18). In agreement with our previous findings, memories CD8 T- cells from blood of HIV negative individuals were primarily PD-1-CD160-2B4+ and to a smaller proportion PD-1-CD160+2B4+. In comparison, LN memory CD8 T-cells had a range of co-expression and did not associate with any one co-expression pattern (Figure

18, top graph). On the other hand, a large portion of the blood and LN memory CD8 T- cells from CP and ART subjects were primarily grouped into PD-1+CD160+2B4+, PD-1-

CD160+2B4+, with a greater proportion of blood memory CD8 T cells in this category, and to a lower extent PD-1-CD160-2B4+ (Figure 18, middle and bottom graphs). Of note, there is a significant proportion of PD-1-CD160+2B4+ in CP and ART, a population we associated with perforin expression in the previous cohort (Figure 13).

Expression of PD-1, CD160 and 2B4 on HIV and EBV-specific CD8 T cells in blood and lymph node

To further investigate differences in expression of PD-1, CD160 and 2B4 on CD8

T-cells from blood and lymph node, and to assess the extent of HIV-specific exhaustion, we measured expression of these inhibitory receptors on Gag-specific and EBV-specific

CD8 T-cells by flow cytometry. Simultaneously we measured production of IFNγ, TNF and perforin. Representative flow cytometry plots showing the gating strategy to identify responding cells are shown in figure 19. Perforin+ cells were considered responding cells

when express with IFNγ and/or TNF. Boolean gates were then used to assess the polyfunctionality of CD8 T-cells responding to HIV-Gag or EBV. In accordance to previous reports (O. O. Yang et al., 2005), HIV-Gag and EBV-specific CD8 T-cells derived from blood expressed more perforin compared to virus-specific LN CD8 T-cells in all subjects (Figure 20). Of interest, CP in this cohort expressed high amounts of perforin, an attribute of elite control of viral replication, yet these subjects remain progressors. It is important to understand why perforin in these subjects does not correlate with protection. Preliminary data from the Reyes-Teran group (Mexico City) has found differences in HLA protective alleles in subjects from Central America compared to what is found in the literature (data not published). Differences in genetic background could explain the discrepancies between our two cohorts. Further work dissecting these differences is necessary to clarify the lack of control in these subjects.

To determine differences in expression of inhibitory receptors in HIV-specific LN and blood CD8 T-cells, we measured expression of PD-1, CD160 and 2B4. We began by measuring single expression of these receptors. Gag-specific LN CD8 T-cells in the LN from CP expressed significantly more PD-1 (p<0.01) than in the blood. In agreement to previously published data (MD et al., 2009), expression of PD-1 is decreased after initiation of ART (Figure 21A). This change in expression appears to be HIV-specific as

PD-1 expression on EBV-specific LN CD8 T-cells remains high in all subjects (Figure

21B). One possible explanation is that removal of HIV viral antigen in LN after ART induces HIV-specific cell death, whereas EBV-specific cells are unaffected. The

proportion of HIV-Gag-specific CD160+ LN CD8 T-cells was significantly lower in CP

(p<0.01) compared to blood, but not ART or HIV negative subjects (Figure 21C). There was no difference in expression of CD160 on EBV-specific CD8 T-cells from blood and

LN (Figure 21D). Expression of 2B4 on HIV-Gag and EBV-specific CD8 T-cells from blood and LN was similar in CP, ART and HIV negative subjects (Figure 21E and F).

Co-expression of PD-1, CD160 and 2B4 on blood and lymph node CD8 T-cells

A high proportion of cytolytic CD160+2B4+ CD8 T-cells were found in the blood of elite controllers (chapter 3). This population of cells is not commonly found in CP; instead they have a significant proportion of PD1+CD160+2B4+ CD8 T-cells believed to be exhausted. To determine if these relationships between perforin expression and patterns of inhibitory receptor expression were different between blood and lymph node, we analyzed co-expression of these inhibitory receptors by HIV-Gag and EBV-specific

CD8 T cells. In this cohort, HIV-Gag and EBV-specific CD8 T-cell responses in blood and LN from CP and ART subjects were primarily divided into PD-1+CD160+2B4+ and

PD-1-CD160+2B4+ (Figure 22A and B [middle and bottom graphs]). Lymph nodes in chronic progressors exhibited a higher proportion of potentially exhausted PD-

1+CD160+2B4+ virus-specific CD8 T cells compared to blood (p=0.01) (Figure 22A top graph, and B middle graph). On the other hand, blood CD8 T cells had a higher proportion of CD160+2B4+ expression compared to LN, a population associated with perforin expression (chapter 3). In contrast, a majority of the EBV-specific responses in 68

blood and LN from HIV-negative subjects were PD-1-CD160-2B4+, with smaller proportions also PD-1-CD160+2B4+ or negative for the three receptors (Figure 22B, top graph). Unexpectedly, in contrast with our previous findings (Figure 13), there was no correlation between the proportion of perforin+ response and co-expression of CD160 and 2B4 in either blood or lymph node for both HIV-Gag and EBV-specific responses

(Figure 23).

Dissociation between perforin and T-bet in lymph node CD8 T-cells

Our lab and others have shown that high expression of T-bet (T-betbright) correlates with cytolytic activity in CD8 T-cells from blood, measured by perforin and granzymes (Buggert et al., 2014; Hersperger et al., 2011). To further address differences between CD8 T-cells in the blood and lymph node, we examined expression transcription factor T-bet in HIV-Gag and EBV-specific cells. Overall, memory CD8 T-cells in the lymph node express significantly lower levels of T-bet compared to blood (data not shown). This is not surprising given the high proportion of effector CD8 T cells found in blood compared to LN. Similarly, there is a significantly smaller proportion of HIV-

Gag-specific CD8 T cells from lymph nodes expressing T-bet compared to blood (CP: p<0.001, ART: p<0.01), and per-cell expression is also lower than in blood (CP: p<0.01,

ART: p<0.01) (Figure 24A and B). Per-cell levels of T-bet expression increase after

ART (p<0.01) (Figure 24B). These levels of expression were similar in EBV-specific

CD8 T cells from HIV+ subjects (Figure 24C and D). Similar patterns of expression were observed for blood and lymph node EBV-specific CD8 T cells in HIV negative

subjects. However, HIV negative lymph nodes have a significantly larger population of

EBV-specific CD8 T-cells that are T-bet+ compared to HIV+ lymph nodes (CP: p-0.05,

ART: p=0.01) (Figure 24B).

In agreement with previous reports, we found a significant association between perforin and high levels of T-bet (T-betbright) in HIV-Gag-specific CD8 T-cells from blood in CP. The statistical significance is lost after initiation of ART, but the trend remains (Figure 25A). However, this association is lost in lymph node CD8 T-cells from both CP and ART (Figure 25B). Similarly, EBV-specific CD8 T-cells from HIV negative and ART subjects had a strong association between perforin and T-betbright. The trend was the same for CP, but it did not reach statistical significance (Figure 25C).

Whereas HIV negative lymph nodes showed the same correlation for EBV-specific CD8

T-cells, CP and ART LN CD8 T-cells do not (Figure 25D). Together, these data indicate dissociation between perforin and T-bet in lymph nodes.

DISCUSSION

It has been known since the early 1990s that lymph nodes function as a major reservoir during HIV infection (Pantaleo et al., 1991). Despite successful suppression of

HIV replication to undetectable levels, ongoing viremia can be detected at levels of 1 to

50 copies/ml in patients (Altfeld et al., 2002; Richman et al., 2009). Regardless of the effectiveness of current antiretroviral therapy, HIV remains incurable; therapy must be maintained for life with interruptions resulting in viral rebound and emergence of escape 70

mutants. It has become clear that it is necessary to eliminate the viral reservoir if there is hope for a cure. Current efforts include the development of drugs to stimulate latently infected cells that would trigger clearance by the immune system in combination with

ART (Richman et al., 2009). But the ability of lymph node-resident immune cells, such as CD8 T cells, to clear infected cells remains a question important to address for this approach to be successful.

Lymph nodes are important for immune reconstitution. B cell maturation and T cell activation take place within the lymph nodes. However, little is known of the state of immunologically important cells within these sites, and whether they can respond appropriately to clear infected cells. Regulatory mechanisms such as expression of inhibitory receptors are in place to protect the integrity of the lymph node architecture.

This work gives a baseline of expression of PD-1, CD160 and 2B4 in healthy lymph nodes. In healthy individuals, there is a higher proportion of CD8 T cells expressing PD-

1 compared to blood CD8 T cells. One can infer that PD-1 upregulation is induced upon entry into the lymph node to dampen harmful responses and preserve the lymph node architecture. On the other hand, there is a lower proportion in expression of 2B4 in lymph node CD8 T cells compared to blood CD8 T cells that can be interpreted as a way of dampening the cytolytic response of cytotoxic CD8 T cells while in the lymph node.

In blood, cytotoxic CD8 T-cells are a correlate of protection against HIV in elite controllers. It is possible that CD8 T cells in lymph nodes with cytolytic potential could be reinvigorated to kill and clear infected cells. CD8 T cells in HIV positive lymph

nodes express high levels of PD-1. Though this marker is strongly associated with T-cell exhaustion, its expression alone is not sufficient to render a cell exhausted. However, lymphatic endothelial cells induce tolerance via the PD-1/PD-L1 pathway aiding in the protection of infected cells. The majority of data available on T-cell exhaustion in the context of HIV infection has been gathered from peripheral blood. In this study we examined CD8 T-cell exhaustion in blood and lymph nodes from a group of chronic progressors (CP) and HIV+ subjects on antiretroviral therapy (ART) to determine if the parameters observed in blood are representative of the lymph node.

We measured expression of PD-1, CD160 and 2B4 in combination with functional markers IFNγ, TNF and perforin. In accordance to a previous report (MD et al., 2009), we find that CD8 T-cells in lymph nodes have a high expression of PD-1 compared to those from blood. Additionally, lymph node CD8 T-cells have a large population of PD-1+CD160+2B4+, previously defined as exhausted. This population is significantly larger in lymph nodes than in blood, suggesting that we are underestimating the extent of exhaustion occurring during HIV infection. This can have an important repercussion for immune reconstitution. Additionally, this exhausted population could be a target for anti-PD-1/PD-L1 therapy in an effort to re-invigorate immune responses.

Importantly, the anti-PD-1/PD-L1 blocking antibody needs to be able to access CD8 T cells in relevant tissues to exert its effect. In addition, target cells need to be able to respond to stimulation with the desired functions. What those desired functions are remains to be determined.

We also report that lymph nodes have small populations of CD8 T-cells expressing perforin. Though there is a small proportion of cytolytic CD8 T-cells in LN, those cells may be enough to eliminate infected TFH cells. The question remaining is whether those cells are able to reach the infected cells sequestered in B cell follicles.

Further studies into the lymph node architecture and whether CD8 T cells can infiltrate the B cell follicle will be required. Additionally, the fact that CD8 T-cells in lymph nodes do not express high levels of perforin does not indicate they are unable to upregulate its expression upon stimulation. Transcription factor T-bet modulates perforin expression and suppresses expression of PD-1. We find that 40% of lymph node CD8 T- cells express T-bet. However, the per-cell levels of expression are low compared to CD8

T cells in the blood. We have previously shown that per-cell levels (MFI) of T-bet expression are associated with its ability to function. Dim levels of expression is associated with cytoplasmic localization of this transcription factor, whereas bright levels of expression associates with nuclear, therefore active, T-bet (McLane et al., 2013).

Finding a way to induce T-bet translocation into the nucleus could be a target of therapeutic value.

Figure 14: Gating strategy for PD-1, CD160 and 2B4 expression on total, naïve and memory CD8 T-cells from blood and lymph node A) Gating scheme of Peripheral blood mononuclear cells (PBMC) identify naïve CD27+CD45RO-) and memory CD8 T-cells. The same gating strategy was used on lymph node mononuclear cells (LNMC). Representative flow plots showing expression of PD-1, CD160 and 2B4 on naïve and memory CD8 T-cells from blood (B) and lymph

nodes (C) from an HIV chronic subject (top row), an HIV+ on therapy (ART, middle row) and an HIV negative individual (bottom row).

Figure 15: Memory distribution of CD8 T-cells from blood and lymph nodes. After gating on CD3+ CD8+ lymphocytes, differential expression of CD27 and CD45RO was used to identify (A) naïve (CD27+CD45RO-), (B) central memory (CD27+CD45RO+), (C) effector memory (CD27-CD45RO+) and (D) effector (CD27- CD45RO-) CD8 T-cells collected from blood (closed circles) and lymph nodes (open circles) from HIV negative (blue), chronic (red) and HIV+ on ART (orange). Each dot represents a subject, bars represent the mean. Statistical differences between blood and lymph nodes from HIV negative subjects were calculated by a non-parametric T test. Statistical differences between blood and lymph nodes from chronics and ART subjects were calculated by paired T tests. p values < 0.05 were considered significant. * p<0.05, ** p<0.01, *** p<0.001

Figure 16: Comparison expression of PD-1, CD160 and 2B4 on CD8 T cells from HIV negative, chronic progressors and ART subjects Memory CD8 T-cells were identified by exclusion of the naïve population (CD27+CD45RO-). (A) The percentage of memory CD8 T-cells derived from blood of HIV negative (HIV-), chronic progressors (CP) and HIV+ on ART (ART) expressing individual receptors. (B) The percentage of memory CD8 T cells derived from lymph nodes from HIV negative, CP and ART subjects expressing individual receptors. Each dot represents a subject. Error bars represent mean + SEM. Statistical analysis was carried out using one-way ANOVA tests (nonparametric; Kruskal-Wallis) followed by a Dunns test for multiple comparisons. ** p<0.01, *** p<0.001

Figure 17: Comparison between blood and lymph node expression of PD-1, CD160 and 2B4 on CD8 T-cells Individual expression of inhibitory receptors (A) PD-1, (C) CD160 and (E) 2B4 was measured on memory CD8 T-cells by exclusion of the naïve CD27+CD45RO- population. The mean fluorescence Intensity (MFI) was used to measure per-cell levels of expression of (B) PD-1, (D) CD160 and (F) 2B4. Statistical differences between blood and lymph nodes from HIV negative subjects were calculated by a non-parametric T test. Statistical differences between blood and lymph nodes from chronics and ART subjects were calculated by paired T tests. p values < 0.05 were considered significant. * p<0.05, ** p<0.01, *** p<0.001

Figure 18: Co-expression of inhibitory receptors on memory CD8 T-cells from blood and lymph node. Single expression gates for each inhibitory receptor were used in a boolean gate analysis to determine all possible combinations of inhibitory receptor expression on CD8 T-cells from blood (black bars) and lymph nodes (grey bars) from HIV negative (top graph), HIV chronic (middle graph) and HIV subjects on ART (bottom graph). Each dot represents a subject. Statistically significant differences were calculated using the T test function within the SPICE program. p values <0.05 were considered significant. * p<0.05, ** p<0.01, *** p<0.001

Figure 19: Gating scheme for detection of virus-specific responses. Representative flow cytometry plots showing expression of IFNγ, TNF and perforin on CD8 T-cells from (A) blood and (B) lymph node. A no-stimulation condition was used as a negative control to identify responses above background. Naïve CD8 T-cells were used to determine gate placements.

Figure 20: Functional profile of HIV and EBV-specific CD8 T cells. Proportion of cytokine and perforin production by CD8 T cells in response to peptide pool stimulation of PBMCs (black bars) and LNMCs (grey bars) with a Gag-PTE peptide pool or an EBV pool containing peptides derived from lytic proteins. (A) HIV Gag- specific response from chronic progressors (top graph) and HIV+ subjects on ART (bottom graph). (B) EBV-specific response from HIV negative (top graph), chronic progressors (middle graph) and HIV+ subjects on ART (bottom graph). Bars represent mean of expression: each dot represents a subject. * p<0.05, ** p<0.01, *** p<0.001

Figure 21: Comparison between blood and lymph node expression of PD-1, CD160 and 2B4 on CD8 T-cells Individual expression of inhibitory receptors was measured on Gag-specific and EBV- specific CD8 T cells. PD-1 expression on (A) HIV-Gag-specific and (B) EBV-specific CD8 T cells from blood (grey bar) and lymph node (white bar). CD160 expression on (C) HIV-Gag-specific and (D) EBV-specific CD8 T cells from blood (dark gray bar) and lymph node (white bar). 2B4 expression on (E) HIV-Gag-specific and (F) EBV-specific CD8 T cells from blood (dark gray bar) and lymph node (white bar) was measured on Gag-specific CD8 T-cells. Statistical differences between blood and lymph nodes from HIV negative subjects were calculated by a non-parametric T test. Statistical differences between blood and lymph nodes from chronics and ART subjects were calculated by paired T tests. p values < 0.05 were considered significant. * p<0.05, ** p<0.01, *** p<0.001

Figure 22: Co-expression of inhibitory receptors on memory CD8 T-cells from blood and lymph node. Single expression gates for each inhibitory receptor were copied from the total memory population. Single expression gates from cells responding to peptide pool stimulation were then used in a boolean gate analysis to determine all possible combinations of inhibitory receptor expression on CD8 T-cells from blood (black bars) and lymph nodes (grey bars) (A) HIV-Gag-specific responses from HIV chronic subjects (top graph) and HIV subjects on ART (bottom graph). (B) EBV-specific responses from HIV negative (top graph), HIV chronic progressors (middle graph) and HIV subjects on ART. Each dot represents a subject. Statistically significant differences were calculated using the T test function within the SPICE program. p values <0.05 were considered significant. * p<0.05, ** p<0.01, *** p<0.001

Figure 23. Association between perforin and co-expression of CD160 and 2B4. Correlation between the percent of the (A) HIV-specific and (B) EBV-specific CD8 T- cell response that is perforin+ and the percent of the response co-expressing inhibitory receptors. HIV negative (blue dots), CP (red dots), EC (green dots). Spearman R and p value of correlations are depicted in the upper right corner of each graph. Lines represent linear regression.

Figure 24: T-bet expression in Gag and EBV-specific CD8 T cells from blood and lymph node. Expression transcription factor T-bet was measured on (A) Gag and (C) EBV-specific CD8 T-cells. The mean fluorescence Intensity (MFI) was used to measure per-cell levels of expression of T-bet on (B) Gag and (D) EBV-specific CD8 T cells. Statistical differences between blood and lymph nodes from HIV negative subjects were calculated by a non-parametric T test. Statistical differences between blood and lymph nodes from chronics and ART subjects were calculated by paired T tests. p values < 0.05 were considered significant. * p<0.05, ** p<0.01, *** p<0.001

Figure 25. Association between high expression of T-bet and co-expression of CD160 and 2B4. Correlation between the percent of the (A) HIV-specific and (B) EBV-specific CD8 T- cell response that is perforin+ and the percent of the response co-expressing inhibitory receptors. HIV negative (blue dots), CP (red dots), EC (green dots). Spearman R and p value of correlations are depicted in the upper right corner of each graph. Lines represent linear regression.

CHAPTER 5: DISCUSSION

This body of work focused on the characterization of T cell exhaustion in the context of HIV infection. Immune dysfunction during HIV infection emerges as a consequence of prolonged antigen stimulation and immune activation, where cells gradually become less functional and eventually are unable to suppress HIV viral replication. In the long run, the destruction of the immune system is so severe the infected individual is left susceptible to opportunistic infections. Understanding the mechanisms of T cell exhaustion has become an area of extensive research. T cell exhaustion has been linked to expression of a variety of inhibitory receptors including

PD-1, CD160, 2B4, CTLA-4, Lag-3, BTLA, Tim-3 and others. Previous work has shown that co-expression of these receptors identify exhausted populations in animal models and during chronic human disease (Blackburn et al., 2008; Peretz et al., 2012; Tian et al.,

2015; Yamamoto et al., 2011). However, there is also evidence that some of these receptors are also involved with effector function, namely CD160 and 2B4. We used polychromatic flow cytometry to measure expression of PD-1, CD160, 2B4 and Lag-3 in the context of controlled HIV infection in elite controllers. We chose these receptors based on a previously performed microarray analysis of exhausted T cells showed a high association between expression of CD160, 2B4 and Lag-3 with PD-1.

Elite controllers are HIV infected individuals capable of suppressing viral replication without the need for ART. These subjects have highly functional HIV-

specific CD8 T cells with high cytolytic potential. Our question was whether these subjects exhibited signs of T cell exhaustion as measured by PD-1, CD160 and 2B4.

Interestingly, we found that elite controllers exhibit signs of T cell exhaustion.

We found a population of HIV-specific PD-1+CD160+2B4+ HIV-specific CD8 T cells not common in chronic progressors (Pombo et al., 2015). These findings are consistent with reports that elite controllers experience ongoing replication in lymph nodes that is undetectable in serum (Moir, Chun, & Fauci, 2011). We also report that elite controllers have a population of CD160+2B4+ HIV-specific CD8 T cell not found in chronic progressors (Pombo et al., 2015). Co-expression of CD160 and 2B4 is strongly associated with cytolytic potential. Several lines of evidence demonstrate that CD160 and 2B4 play a role in enhancing cytotoxic activity (Cai & Freeman, 2009; Meinke &

Watzl, 2013; Nikolova et al., 2002; Rey et al., 2006; Saborit-Villarroya et al., 2008). We propose that expression of PD-1 in the triple-positive exhausted population modulates the activating functions of CD160 and 2B4. More insight into downstream targets of PD-1 signaling could point to a molecule involved in CD160 and/or 2B4 signaling.

Alternatively, PD-1 could modulate signals directly affecting perforin expression or degranulation.

We also report that expression of inhibitory receptors measured in the blood underestimate levels of expression in lymph nodes. We report that there is a greater proportion of PD-1+CD160+2B4+ CD8 T cells in lymph nodes compared to blood. In addition, perforin expression is significantly reduced within these tissues. Unexpectedly,

a previously established relationship between perforin expression and T-bet was not observed in lymph nodes. This implies the possibility of another factor controlling perforin expression in this tissue, such as another T-box transcription factor Eomes.

Increased expression of Eomes has been linked to T-cell exhaustion in the context of HIV

(Buggert et al., 2014).

Lymph nodes play an important role in immunity; they harbor the majority of the body’s lymphocytes and it is where antigen presentation and maturation of B and T cells takes place. However, lymph nodes also play a vital role in HIV infection. Several groups have shown that lymph nodes harbor the HIV reservoir and are the main source of

HIV replication. The inability to clear infected cells in the lymph node and eliminate the

HIV reservoir forces HIV+ subjects to remain on therapy for a lifetime. Any lapses or regiment interruption can result in re-emergence of virus and evolutionary mutation rendering the virus drug resistant (Richman et al., 2009). In addition, concern for toxic effects of long-term antiretroviral therapy is pushing the field to find a cure. Some studies point to increased rates of heart disease, diabetes, liver disease, and forms of cancer in aging HIV-infected patients who are receiving treatment (Richman et al., 2009)

Furthermore, with infections in adolescents on the rice, the number of years a person will spend on ART has increased on average by 20 years. The goal of being able to stop ART without viral rebound is made difficult by the presence of the immune reservoir.

Understanding T cell exhaustion in lymph nodes is important in the development of therapeutics aimed at re-invigorating CD8 T cells at the sites where infected cells live

(i.e. the lymph node). For these therapies to be effective, they must take into account the microenvironment in which the T-cell will be exerting its function.

In conclusion, this work shows that expression of inhibitory receptors does not always signify exhaustion; CD160 and 2B4 were associated with perforin expression in elite controllers. However it is clear that PD-1 plays an important role inhibiting CD8 T- cells, but expression of this receptor alone does not control CD8 T-cell. We also showed that it is important to measure exhaustion directly in tissues important for disease, as blood is not always a good surrogate.

Though we did not measure other inhibitory markers in this thesis, a comprehensive understanding of their role in immune modulation and exhaustion needs to be performed. The role inhibitory markers such as CTLA, TIM-3, Lag-3 in exhaustion of CD4 T cells and NK cells demonstrate the complexity involved in immunomodulation.

Additionally, further understanding on the regulatory pathway triggered upon interaction of these receptors with their ligands is important for continued development of strategies involved in reinvigorating exhausted cells. Blocking studies in-vivo using the SIV model of infection of non-human primates should be more fully develop to elucidate the unintended consequences of manipulating inhibitory receptors. My work, along with others, show the importance of concentrating significant efforts in looking at secondary lymphoid tissues, particularly lymph nodes, when developing new vaccine platforms or therapies

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