THE PENNSYLVANIA STATE UNIVERSITY SCHREYER HONORS COLLEGE DEPARTMENT OF VETERNIARY AND BIOMEDICAL SCIENCES

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1 THE PENNSYLVANIA STATE UNIVERSITY SCHREYER HONORS COLLEGE DEPARTMENT OF VETERNIARY AND BIOMEDICAL SCIENCES CD4+ T CELL HELP AS A DIRECT OR INDIRECT REQUIREMENT FOR THE DEVELOPMENT OF FUNCTIONAL CD8+ T CELL MEMORY JULIE CHEUNG Spring 2012 A thesis submitted in partial fulfillment of the requirements for a baccalaureate degree in Immunology and Infectious Disease with honors in Immunology and Infectious Disease Reviewed and approved* by the following: Surojit Sarkar Assistant Professor of Veterinary Science Thesis Supervisor James Howell Coordinator of Undergraduate Advising Honors Adviser * Signatures are on file in the Schreyer Honors College.

2 i ABSTRACT One of the largest contributors towards the success of a vaccine is the ability of the cells in the immune system to produce what is known as immunological memory, a specific characteristic of the adaptive arm in immunity The main effector cells during a vaccine immunization, and bacterial or viral infection are CD8+ T cells that directly combat pathogenic particles and infected cells. Some of these effector cells either die or become memory cells. These memory cells can persist in the body up to the lifetime of an individual and are activated to differentiate into effector cells when they recognize an invasion by the same pathogen. They respond in a stronger, much quicker fashion during this secondary response, and the time to clear infection noticeably decreases. There have been many studies that show that the help provided by CD4+ T cells are absolutely required for the production of functional CD8+ memory T cells using animal models. However a question that remains to be answered is whether or not the presence of CD4+ T cell is required for direct communication with CD8+ T cells. This thesis tests a hypothesis that perhaps the CD4+ T cell merely conditions the environment in some way that allows for the robust functionality of CD8+ memory T cells and thus suggesting an indirect requirement. CD4+ T cell deficient mice and regular wild-type mice are infected with the Listeria Monocytogenes (LM) bacteria and then tested for their ability to produce functional CD8+ T cell memory. In each group, half are treated with Ampicillin and half remain untreated. The purpose of treatment is to bypass issue of persisting infection, in case CD8+ T cells become functionally exhausted. This otherwise would obscure results if CD8+ T cells result in having poor memory. Results in this experiment show that CD4+ T celldeficient mice provide similar numbers in CD8+ T cells as wild-type mice. Further experimentation is required to determine whether CD8+ T cell is functional during a secondary recall response.

3 ii TABLE OF CONTENTS ACKNOWLEDGEMENTS... iii Chapter 1 Introduction... 1 Brief History... 1 The Immune System... 1 Immunological Memory... 7 Goals Chapter 2 Materials and Methods Materials Experimental protocols Data analysis Chapter 4 Results Experimental Setup Cellular Markers Peptide Stimulation Chapter 5 Discussion References... 38

4 iii ACKNOWLEDGEMENTS I would like to deeply thank Dr. Surojit Sarkar and Dr. Vandana Kalia for giving me the invaluable opportunity of being a part of such exciting research, and for imparting insurmountable knowledge in the field of immunology to not only be able to complete this thesis, but also to prepare me for a future career in research and medicine. My sincerest gratitude goes to Laura Penny, our research technician whom has been the glue to every experiment gone right and has provided me the greatest support throughout my time in the lab. Lastly, I would like to also thank the rest of the Sarkar-Kalia lab for the immense assistance and support they have given along this journey.

5 1 Chapter 1 Introduction Brief History Perhaps one of the body s top lines of defense against infections, CD8 T cells have made profound contributions to an individual s health. After all, the key to a successful vaccine in part relies on the specific ability of CD8 T cells to generate memory. One of the first discoveries for the basis of vaccines arises from Edward Jenner s findings regarding smallpox immunity in He discovered that milkmaids infected with cowpox were immune to smallpox, a much more devastating disease than the former. Jenner tested his hypothesis by inoculating a young boy with the cowpox disease, later infecting him with smallpox, and his results proved to be right (Kindt, 2007). It was those findings and findings from other contributors such as Louis Pasteur and Robert Koch that brought about the advancements made in the modern world. However, what is known today far exceeds the simplicity and risks of mere observations made in the past. Recent studies in immunology and vaccinology have paved the way for the successful outcome of preventing disease, and such impact was seen in the eradication of smallpox in 1977 (Kindt, 2007). Nonetheless, there is much that still needs to be learned about a disease and how the body responds to it before the prospect of eradication of that disease can even occur. The Immune System The immune system provides a great level of protection to a host against infection, and these infections arise from bacteria or microbes that are capable of spreading disease. Prior to an onset of infection by a pathogen, the pathogen first must cross several physical and chemical barriers that prevent

6 2 it from entering. These include the skin, mucosal membranes and the stomach acid (Kindt, 2007). After it enters the host, infection can ensue thus the body devises a mechanism to protect itself. These protective mechanisms are found in two specific arms of the immune system: innate immunity and adaptive immunity. The body s first line of defense to any infection comprises the innate immunity, whose response by exposure to pathogen occurs quickly within hours in contrast to the adaptive response, which can take days (Murphy, 2012). Within each component of the immune system the tasks are the same: to protect the individual from infection. These tasks can further be divided into immunological recognition, immune effector functions, and immune regulation (Murphy, 2012). Recognition of an infection must occur in order for the body to mobilize effector cells and destroy foreign particles associated with the infection in various ways. Immune regulation is a pivotal role in the defense mechanism as it serves to protect the body from any self-damage that can occur if the immune response is too intense. A task specific for the adaptive immune system is immunological memory, in which the cells in this arm of the immune system is of producing memory cells when exposed to infection. In doing so, the body can provide a quicker, more powerful response to future exposures to the same infection (Murphy, 2012). Innate immunity The innate component of the immune system is less advantageous against infection in that it does not have the immunological memory function compared to its adaptive counterpart, and it is usually unable to terminate infection alone. However, their function is nonetheless vital for the successful elimination of infection. They are much like pawns pieces in chess games that combat the enemy first before other pieces of higher rank (the adaptive component) enter the battlefield. Again similar to chess, they also assist the adaptive immune system in various ways in order to protect the king. Consequently, these two arms of the immune system are not independent functions of one another, rather they form

7 combined efforts that eliminate infection much more effectively than if they were to do so individually 3 (Kindt, 2007). One of the most noted functions of innate immunity is the ability of cells to recognize broad class of molecules. There are molecules found on bacteria or viruses that are never seen in humans. This makes an individual body able to differentiate between self and foreign cells. There are receptors on cells of the innate system that can recognize these foreign molecules or proteins, which allows them to eliminate microbes when they invade the host (Figure 1.1). This is known as pattern recognition (Kindt, 2007). Effector cells performing these and other similar functions are commonly neutrophils, monocytes, macrophages, dendritic cells and natural killer (NK) cells that circulate throughout the body (Murphy, 2012). Cells of the innate immune system can also produce antiviral cytokines, antimicrobial peptides, toxins and other factors to fight infection. The presence of foreign molecules in the body can also lead to activation of complement, a series of proteins and molecules that are released to interact and directly fight off infection or marking it for destruction by innate cells (Kindt, 2007). Activation of the complement system creates a domino effect. It triggers release of effector cells, which then secrete cytokines. This cascade of events leads to inflammation, caused by leakage of proteins and fluid into the tissues due to the influx of effector cells and the cytokines released that increase permeability of blood vessels (Murphy, 2012). [Thus, immunological regulation is a critical function of the immune system.] Cytokines are signaling molecules, as well as are chemokines, which are also generated upon interaction. They perform other functions such as signaling the synthesis or recruitment of other molecules to combat infection, including activation of cells of the adaptive component to further enhance clearance of infection (Kindt, 2007).

8 4 Fig. 1.1 Various receptors on macrophages that are specific for recognizing foreign particles from microbes (taken from Murphy, 2012) Adaptive immunity The adaptive immune response has four properties tailored for its specificity. These are antigenic specificity, diversity, immunologic memory and self-nonself recognition (Kindt, 2007). Antigenic specificity describes how cells of adaptive immunity can recognize specific foreign particles called antigens. These are protein particles within a single species of pathogens that may have subtle differences in proteins or slight genetic variation from other species, whereas pathogen recognition particles are molecules commonly found on most pathogenic species Kindt, 2007). Cells not only distinguish these subtle differences in foreign particles, but distinguish them from self-antigens in the body as well (Murphy, 2012). This gives them the ability to eliminate foreign particles without harming the body.

9 Once they interact and respond to an antigen, they can then form memory cells that recognize that 5 particular antigen for future exposure to the same infection. There are two separate but highly collaborative categories of cells that form the adaptive immune system: B lymphocytes (B cells) and T lymphocytes (T cells). The B cells comprise of the humoral branch of immunity and mature in the bone marrow, whereas T cells make up the cell-mediated part of the immune system and mature in the thymus (Kindt, 2007). Upon maturation, B cells enter the circulatory system and produce antibodies. These are either membrane-bounded or secreted. The two major cells of the T lymphocytes are CD8 + cytotoxic T lymphocytes (CD8 T cells, CTL) and CD4 + T lymphocytes (CD4 T cells, T helper ). Antibodies function to neutralize toxins or viruses by coating them. This prevents them from infecting or binding to host cells. CD8 T cells directly eliminate tumor or virally infected cells and can produce antiviral cytokines. CD4 T cells also produce cytokines that provide help in activating B cells and CD8 T cells (thus named T helper) and also engage other defensive mechanisms (Murphy, 2012) Antigenic presentation of B cells The activation of B and T cells to perform their function requires the presentation of antigens. When B cells mature and exit the bone marrow, they are called naïve B cells because they have not interacted with antigens (Murphy, 2012). These B cells have receptors, which are membrane-bound antibodies. When they first bind to an antigen, they differentiate into antibody-secreting plasma cells (effector cells) and memory B cells. Effector cells secrete soluble antibodies, which are specific for the antigen that activated the naïve cells. These antibodies continue on to remove the specific antigenic particles in the body. Memory B cells cease to divide and live on to be activated by the same antigen to induce a secondary antibody response towards it (Kindt, 2007). When they are activated, they differentiate into effector cells and repeat the cycle again. Antibodies do not simply recognize and bind to

10 an antigen but recognize an antigenic determinant or epitope of an antigen (Kindt, 2007). Epitopes are 6 specific parts of an antigen located on its surface that antibodies can bind to their binding site, and various antibodies can bind various epitopes (Murphy 2012). This allows for antibodies to bind and coat viral particles that express various epitopes. These antigens recognized by B cells are protein particles formed by viruses or other microbes and expressed on their membrane. Once antibodies bind, they can either neutralize the virus or mark it for degradation by other cells (opsonization) in an antibody-dependent fashion or induce complement that is antibody-mediated (Murphy, 2012). Antigenic presentation of T cells T cells differ from B cells in antigen presentation in that the antigen particles must be bound to specific proteins called major histocompatibility complex molecules (MHC molecules). A foreign antigen first has to be partially degraded, processed and then the antigen fragments have to form a peptide-mhc molecule in order for T cells to recognize it (Murphy, 2012). These proteins are found on nearly all nucleated cell membranes but the two major types that are only recognized by T cells are called MHC Class I and MHC Class II (Kindt, 2007). CD4 and CD8 have T cell receptors (TCRs) that are only specific for binding MHC Class II and MHC Class I, respectively. MHC Class I molecules are found on nearly all nucleated cell membranes whereas MHC Class II is found only on APCs (Kindt, 2007). Thus, APCs can express both MHC Class I or II. There are three most common APCs: dendritic cells, B cells and macrophages. They differ in how they uptake the antigen, constitutive expression of MHC Class II molecules and costimulatory signaling (Kindt, 2007). Dendritic cells serve as the main APC for CD4 T cells because they constitutively express high levels of MHC Class II molecules and provide the costimulatory signal required to activate CD4 T cells. Nearly any cell that expresses class II MHC molecules can present antigen to CD8 T cells (Murphy, 2012). These cells and APCs are targets to T cells

11 and once T cells are activated, they can carry on their function of eliminating infection. Similarly to B 7 cells, when naïve T cells are activated, they can differentiate into effector T cells or memory T cells. Immunological Memory After an infection or immunization, the body generates memory that is long-lived even years later (Murphy, 2012). This aspect of the adaptive immune response is distinctive because it confers protection from the same pathogen and can prevent the same infection from occurring. When subsequent exposure to a previously encountered pathogen does occur, the immune system is able to mount a much quicker and more powerful response to clear the pathogen (Kalia et al, 2010). Memory B cells play a large role in humoral immunity, which is immunity provided by circulating antibodies that clear antigen in the extracellular space (Kindt, 2007). Memory T cells on the other hand primarily comprise cell-mediated immunity, which provide responses that eliminate intracellular pathogens (i.e. virally infected cells) (Kindt, 2007). The collaborative roles between memory cells are essential for life-long protection of the immune system. B cell memory During the first exposure of pathogen to a naïve B cell, they present antigen on the surface of their cell via the MHC Class II molecule, acting as an APC for CD4 T cells (Murphy, 2012). This interaction between the peptide-mhc Class II complex on the B cell and a CD4 helper T cell allows the T cell to provide proper signaling to induce the B cell to undergo proliferation and differentiation (Kindt, 2007). Similar to the naïve cells, memory cells rapidly proliferate and differentiate into effector cells and more memory cells during re-exposure. This period of differentiation into memory cells or plasma cells and clonal selection and expansion is defined as the lag phase during duration of pathogen exposure

12 (Murphy, 2012). The lag phase is a characteristic and distinct feature among primary and subsequent 8 exposures (Kindt, 2007). After exposure to the same pathogen, this lag period is generally shortened, with a greater magnitude of antibody response that lasts longer. Additionally, antibodies that have undergone subsequent exposures generally have a stronger affinity for their antigens than those from the primary exposure (Kindt, 2007). T cell memory After appropriate presentation of antigen peptide by the respective MHC molecule and proper signaling to a T cell, it becomes activated and the primary response begins (Prlic, 2007). This first results in a significant rise in the production of effector T cells (expansion phase) specific for that antigen that then pulls back to a lower amount (contraction phase) but still remains at a higher level than the initial frequency from prior to the restimulation. These remaining effector cells will then persist on as long-lived memory cells (memory phase) (Murphy, 2012, Kalia et al, 2010). Both CD4 and CD8 T cells are capable of differentiating into two subsets of memory cells, each with their own characteristic form of activation (Murphy, 2012). These two types are effector memory cells and central memory cells. Effector memory cells migrate to peripheral tissues, where they differentiate into an effector cell population and secrete high levels of cytokines with antiviral properties upon restimulation by antigen, making them capable of releasing a quicker and marked response (Kalia et al, 2010). Central memory cells differ in that they can recirculate to peripheral lymphoid tissues (i.e. lymph nodes, spleen) and differentiate and divide more quickly into effector cells, but provide a slower effector response upon restimulation by antigen (Kalia et al, 2010). Thus, they secrete less cytokines than effector memory cells (Murphy, 2012).

13 CD4 T cell memory 9 CD4 T cell require antigen presentation by a MHC class II molecule on APCs followed by cytokine stimulation in order to be activated and form effector and memory cells (Kindt, 2007, Murphy, 2012). To reiterate, the three main functional APCs for activation of CD4 T cells are dendritic cells, B cells and macrophages. Experimental data has shown that the presence of B cells is required for the generation of CD4 T cell memory in acute and chronic infections (Whitmire et al, 2009). B cell-deficient mice displayed a dramatic drop of CD4 T cell during the contraction phase, which resulted in significantly less memory T cells. Two weeks after the expansion and contraction phase, there was total depletion of CD4 memory T cells (Whitmire et al, 2009). In comparison to naïve CD4 T cells, memory CD4 T cells do not require MHC for survival but in some systems B cells are required for CD4 T cell memory maintenance (Whitmire et al, 2009). CD8+ T cell memory CD8 T cell memory differs from CD4 memory in that they form larger expansion responses than CD4, quicker contraction, and higher levels of memory cells. After infection, the contraction phase occurs within the second week for CD8 T cells whereas CD4 T cells response occurs over a month (Whitmire et al, 2009). In one experimental study, B cell-deficient mice demonstrated no loss of CD8 T cell memory in acute infection. However, these mice were unable to clear chronic infection, indicating that there is an indirect effect on CD8 T cell memory (Whitmire et al, 2009). The differences between acute and chronic infection are listed below on Table 1. Following an acute infection, CD8 T cell responses undergo the three major phases (Figure 2; Kalia et al, 2009). The first is the effector or expansion phase, in which naïve cells become activated, divide and differentiate into effector CD8 T cells (effector CTLs). The second is the contraction phase, which a majority of effector cells die after antigen is cleared and the remaining live on to be memory cells. Lastly the memory differentiation and maintenance phase consist

14 10 of the persisting memory pool that acquires memory traits whose levels are maintained and remain stable for years long after infection (Kalia et al, 2009). Figure 2. Naïve cells first encounter antigen at day 0 and develop effector CD8 cells to fight infection and at or around day 8 is the peak of the expansion phase of the effector cells. Following it immediately is the contraction phase in which an estimated 90-95% of effector cells become terminally differentiated cells and die, and the remaining can live on for the lifetime of an individual as memory cells in the memory maintenance phase. It is important to note that the amount of CD8-specific T cells in this phase is maintained at levels higher than that of naïve.

15 11 Table 1. Derived from Kalia et al, Characterization of differences between acute and chronic infections and how CD8 T cell differentiation is impacted under these conditions. CD4+ T cell help required for functional CD8 T cell memory There are many studies that show the help provided by CD4+ T cells are required for the overall functionality of CD8+ memory T cells in animal models. However, the manipulation of these models using various experimental conditions determines exactly when and where CD4 T cells are required. Generally speaking, there is a need for CD4-activated dendritic cells to provide a stimulus to CD8 T cells for a complete CD8 T cell response (Murphy, 2012). However certain infections, in particular that of the Listeria monocytogenes (LM) bacteria, can facilitate the activation of dendritic cells by providing immunostimulatory signals (Sun and Bevan, 2003). This allows CD8 T cells to mount the first response to infection without CD4 T cell help. Studies have determined that mice that were CD4 T cell-deficient cleared primary infection just as effectively as wild-type (WT; normal with CD4 T cells) mice, and there

16 12 were similar contraction, expansion and memory phases (Murphy, 2012, Sun and Bevan, 2003, Shedlock and Shen, 2003). Although these CD8 T cell responses do not differ, the functionality of CD8 memory T cells becomes evidently defective (Sun and Bevan, 2003). One way to test the efficacy of CD8 memory T cell response is by measuring their ability to lyse infected cells and produce interferon-γ (IFN-γ) upon stimulation. IFN-γ is a cytokine important for reducing infection, such as inhibiting viral replication. Experimental data shows that mice with a MHC class II molecule deficiency (MHC class II knock out/ko) generate poor CD8 T cell memory upon secondary exposure to pathogen during acute infection (Sun and Bevan, 2003). The CD4 T cells in these mice are nonfunctional due to lack of interaction and activation by the MHC class II molecule. After initial exposure to antigen, the memory pool of CD8 cells from both the MHC class II KO mice and WT mice were separately transferred into another individual set of naïve WT mice. These recipient mice were then re-challenged with the same antigen to test the response of the cells. The results showed a stronger CD8 T cell response in the WT memory pool compared to a weaker and slower response during the expansion phase from the MHC class II KO pool (Sun and Bevan, 2003, Murphy, 2012). However, in another experiment normal WT mice were infected and allowed to undergo expansion, contraction and memory phases. CD4 T cells were then depleted at 80 days post-infection and subsequently challenged a second time and there showed no defect in CD8 T cell memory response to the challenge (Sun and Bevan, 2003). Similarly, in an experiment by Shedlock and Shen using CD4-deficient (CD4 KO) mice and infecting them with LM, CD8 cells transferred into WT recipients mounted a weaker recall response as well (Shedlock and Shen, 2003). They also tested how CD8 cells that were initially primed in WT mice would respond when transferred into a CD4 T cell KO environment upon re-challenge. They transferred CD8 cells primed in WT mice into CD4 KO and another set of WT mice. Results showed that the recall response of the CD8 cells in the KO recipient was as effective as the cells transferred into WT (Shedlock and Shen, 2003). In both studies by Shedlock and Shen and Sun and Bevan, their results suggest that CD4 T cells may be required only during the

17 13 priming/initial infection phase of mice in order to make functional CD8 T cell memory, since CD8 T cell memory markedly decrease only when CD4 T cells were not present during that phase of infection. Although the above studies provided a general indication that CD4 T cell help is needed during the initial infection, other studies questioned specifically at which point of a CD8 T cell s life during the initial infection time, in terms of function and survival, are they dependent on CD4 cells. Sun et al. determined that CD4 T cell help is only necessary for the maintenance but not programming of CD8 T cell memory cells during initial infection (Sun et al, 2004). This was shown experimentally by initially transferring cells in P14 mice into a set of MHC class II-deficient and WT mice primary recipients (Figure 3). P14 mice are transgenic mice containing T cells that only recognize the glycoprotein 33- specific (GP33-specific) epitope naturally expressed by lymphocytic choriomeningitis virus (LCMV). Thus, these cells can be tracked for their ability to differentiate and proliferate in response to antigen. For many experiments such as those mentioned earlier, the LM bacteria are genetically altered to display this epitope so it is capable of eliciting a bacterial response in mice. These P14 cells in both mice groups were then primed and infected with LCMV. On day 8 after infection, the effector P14 CD8 T cells in both the WT and MHC class II KO primary recipients were transferred into WT and MHC class II KO secondary recipients (Figure 3; Sun et al, 2004). The eighth day is generally the peak of expansion and beginning of contraction thus the formation of memory cells could be detected and tracked (Kalia et al, 2010). Both sets of donor cells from the WT and MHC Class II KO primary recipients showed similar marked decrease in contraction and memory cell numbers when transferred in the MHC class II KO secondary recipients (Sun et al, 2004). Interestingly, the WT and MHC class II KO primary recipient cells both displayed similar but normal levels of contraction and maintenance when transferred into WT secondary recipients. This is evidence that the initial programming of memory T cells during activation of naïve cells does not require CD4 T cell help but rather, the maintenance phase of CD8 T cell memory during initial infection at least from day 8 and on does require CD4 help (Sun et al, 2004).

18 14 Figure 3. Taken from Sun et al, 2004, Primed P14 cells in (a) WT primary recipients and (b) MHC class II KO primary recipients were transferred to either WT or MHC class II KO secondary recipients. When cells from either primary recipient were transferred into WT secondary recipients, there were normal numbers of GP33-specific CD8+ effector cells. When cells from either primary recipient were transferred into the KO secondary recipients, there was a defect in the ability to mount a response and fewer numbers of GP33-specific cells CD8+ effector cells. Goals It is now apparent with the research available regarding how CD4 T cells play a role in CD8 T cell memory that there is some requirement of CD4 help in developing quality functional CD8 memory T cells. It is also without a doubt evident that the immunological system provides vast forms of protection to a host with one of the key players being CD8 effectors, which can employ its abilities to directly eliminate infected cells. Furthermore, the production of immunological memory from these cells is critical for evading severe infection from recurring microbes. Thus, it is important to understand the many factors and changes that affect CD8 T cells during their lifespan, such as the unmistakable effect made by CD4 T cells. While there is research dictating the necessity of CD4 T cells, there are others than refute its

19 15 absolute requirement. This prompts the question: why are CD4 cells only a transient requirement during a CD8 T cell s existence? To further analyze this question, we sought to determine exactly how these CD4 T cells were providing help by experimentation on a mice model. Therefore the true goal of this thesis seeks to answer whether or not CD4 T cells provide help directly through some sort of contact with CD8 cells, or indirectly by conditioning the environment in which they live. The hypothesis is centralized on the latter, which can explain not only the necessity of the CD4 T cell help, but also why the need of CD4 help appears to occur occasionally. The hypothesis was directly tested by performing an experiment that tested for differences in CD8+ memory T cell formation using wild-type B6 and CD4 KO mice after infection with LM-33. In both groups, several mice were given Ampicillin treatment. The purpose for treatment of mice is to bypass any issue of pathogen clearance. Sometimes persisting antigen may be the reason for poor CD8 T cell memory due to cell exhaustion thus this factor is accounted for in the treatment group and used to compare, contrast and determine the quality of memory for both mice groups.

20 16 Chapter 2 Materials and Methods Materials The mice used for this experiment are a common inbred strain known as C57BL/6 (B6) purchased from The Jackson Laboratory (Bar Harbor, ME). CD4 knock out (CD4 KO, CD4 -/- ) mice were purchased from The Jackson Laboratory as well. Recombinant Listeria monocytogenes (LMgp33), which express the GP33 epitope, were titered, frozen, and thawed until ready for use. Ampicillin antibiotic was used for treatment of infection in treatment mice. Fluorescently tagged antibodies used for surface staining were purchased directly from BioLegend (San Diego, CA). Antibodies used for intracellular staining were purchased from Invitrogen (Grand Island, NY). Each antibody comes from a mixture concentrated at 0.2 mg/ml in a 5ml bottle. These antibodies are made to bind to specific cell protein markers and in conjunction are labeled with a fluorochrome that fluoresces so it can be detected by the cytometer and allow for analysis of cells. (Fig #) 4% solid citrate dissolved in distilled water is made in the lab and used as an anticoagulant. Roswell Park Memorial Institute (RPMI) medium was purchased from Fisher Scientific and used to culture cells. 2% Fetal bovine serum (FBS) was used to supplement the RPMI medium. Histopaque-1077 density gradient was purchased from Sigma Aldrich.

21 17 Figure 4. Antibodies that are labeled with fluorochromes can bind to specific cell markers, which can then be analyzed by a flow cytometer. Experimental protocols Peripheral blood mononuclear cells (PBMC) Isolation Retro-orbital bleeds were performed on days 8, 15, 23, 30, 48, 72, and 86 on each mouse. Ten 12x75 blood tubes were labeled and subsequently filled with 0.5ml of 4% solid sodium which functions to prevent clots during the isolation process. All mice were anesthetized with Isoflurane saturated on gauze and enclosed in a small bell jar. Approximately 0.2ml of blood was taken from each mouse using 250µl capillary tubes and placed into the respective tube. All mice were handled properly per procedural requirement. After collection of blood, 2.0ml of RPMI with the 2% FBS was placed into each sample. Histopaque density gradient was layered underneath the blood and then the samples were centrifuged for 20 minutes at 2,000 revolutions per minute (rpm) with no brake set at 20ºC. The density gradient provides a gradient that separates out cells based on density. In this case it has a density that is separates what is not needed from the lymphocytes. A glass pipette was used to remove the PBMC layer at the interface

22 between the gradient and the RPMI. These samples were placed into newly labeled tubes filled with 18 RPMI+2% FBS media. Samples were placed in the centrifuge for 10 minutes at 2,000 rpm at 4ºC with brakes on. During this spin, a master mix of antibodies was made for the surface and intracellular staining. FITC, PerCP, PE, PE-Cy5.5, APC, Alexa 700 and Pacific Blue were the fluorochromes used to tag the KLRG-1 and BCL-2, CD8, CD127, GranzymeB, GP33, CD44 and CD62L antibodies, respectively and with a dilution of 1:100 and 1:5, 1:100, 1:100, 1:50, 1:100, 1:100 and 1:100, respectively. APC-Alexa 750 and APC-Cy7 fluorochromes were also used to tag CD44 when Alexa 700 was not available, with a dilution of 1:200 for both. Using these dilutions, antibodies were mixed into a 2ml tube with FACs buffer (for surface staining) or Perm/Wash buffer (for intracellular staining) and placed on ice until needed. Following the 10-minute spin, the media portion was removed and 150µl of FACs (1X distilled phosphate-buffered Saline (PBS) + 1% FBS + 0.1% sodium azide) was added and tubes were set on ice. Splenocyte Isolation RPMI + 2% FBS (2ml) media were placed into 15ml tubes labeled for each mice being sacrificed and placed on ice. Spleens were collected and placed into the media. Spleen and media were poured into a petri dish and cut into pieces using the edge of two frosted glass microscope slides. The tissue was rubbed to extract the cells and slides were carefully washed off with media in a 5ml syringe. All liquid with cells were transferred from the petri dish back into the 15ml tube and spun in the centrifuge for 10 minutes at 1,200 rpm, 4ºC with brakes on. Media was dumped leaving behind the pellet. Tubes were pressed and rubbed against a peg rack 4-6 times to mix the cells. Cells were given 1 ml of 0.83% Ammonium chloride, vortexed and sat in solution for exactly one minute. Tubes were topped off with media and centrifuged for ten more minutes. Media was dumped off leaving the behind the pellet, and again tubes were pressed and rubbed against a peg rack to mix cells. More media (4-6ml) was placed into each tube and gently swirled to mix.

23 19 Cell surface and intracellular staining Lymphocytes were stained for cell surface markers KLRG-1, CD8, CD127, CD62L, GP33 and CD44 on days 8, 15, 23, 30, 48, 72 and 86 following each bleed day. On day 8 and day 15 intracellular markers granzymeb and BCL-2 were stained for, respectively. On day 86, spleen cells were extracted and stained. Following the PBMC and splenocyte isolation protocol, cells in the 150µl of FACs buffer (PBMC isolation) or RPMI media (splenocyte isolation) were mixed and transferred into a 96-well U- bottom plate. Each well was topped off with 100µl of FACs and spun in the centrifuge at 1,800 rpm, 4ºC for 2 minutes. FACs buffer was flicked off into trash while pellets remained in the wells. In each well, 50µl of the antibody mix with FACs was added and left to incubate for 45 minutes on ice in dark condition by covering the well with aluminum foil. This is done to minimize the loss of fluorescence of each antibody. After incubation, 150µl of FACs buffer was added to each well and washed by placing into the centrifuge to spin for 2 minutes at 1,800 rpm at 4ºC. Cells were washed twice more with 200µl of FACs (The wash step is necessary to remove any antibodies that did not bind to cells; this ensures that when reading cells, which would appear due to the fluorescence on the antibodies, they are bound to cells.) The aforementioned steps apply to both intracellular and surface staining. When continuing with surface staining, cells were fixed with 100µl of 4% paraformaldehyde (PFA) dissolved in PBS and 100µl of FACs for 20 minutes on ice following the washes. Cells were either read using the flow cytometer following the fix, or placed in 200µl of FACs left in 4ºC dark condition and read within 24 hours. When intracellular staining was done, cells were fixed with 70µl of 1X Cytofix/Cytoperm reagent following the washes for 20 minutes on ice in dark condition. Cells were then washed using 150µl of 1X Perm/Wash buffer (originally 10X concentration diluted in distilled water) at 2,200 rpm, 4ºC for 2 minutes. This was done twice more using 200µl of the Perm/Wash buffer. Cells were stained with 50µl of the diluted granzymeb antibody on day 8 and BCL-2 antibody on day 15 and left to incubate for 45 minutes under dark condition on ice. Following this, 150µl of the Perm/Wash buffer was added and one

24 cycle of the wash was performed at 2,200 rpm, 4ºC for 2 minutes. Cells were washed twice more with µl of Perm/Wash and then twice more with FACs buffer. Cells were then fixed with 100µl of 4% PFA and 100µl of FACs for 20 minutes on ice in dark condition. Similarly to the surface stain, samples were either read following the stain or stored in 200µl of FACs buffer in 4ºC dark condition and read within 24 hours following the completion of staining. Peptide Stimulation Following the spleen isolation, cells were also isolated in individual wells for peptide stimulation. They were incubated with the GP33 antibody for 5 hours and then stained for the cytokine expression of tumor necrosis factor-α (TNF-α), interleukin-2 (IL-2) and interferon-γ (IFN-γ). Flow cytometry After cells are stained and fixed with PFA, they must be read within 24 hours on a multi-color flow cytometer. The machine sorts all cells from samples individually based on cell size and shape, internal complexity and fluorescent intensity. The four main characteristics of a flow cytometer are fluidics, optics, detectors and electronics. When cells are taken up by the cytometer, they travel through a flow chamber that contains a stream of sheath fluid. This stream places the cell samples in the center of the chamber and allows them to individually pass through a laser beam. When this occurs they deflect the incident light and create a forward and side scatter. The forward-scattered light is representative of the surface area/size of a cell whereas side-scattered light represents its internal complexity. The reflected light is then collected by a series of lens and filters that directs them to optical detectors specified for their wavelength. Additionally, as cells they pass through the chamber, their attached fluorochromes are excited at a specific wavelength by the laser and that causes the fluorochrome to emit light at another wavelength. There are fluorochromes with different wavelengths for different antibodies. The light is then detected by a photodetector, which transmits an electrical pulse that is processed by an electronics signal

25 processor of the cytometer. The electronics system will calculate the cell size, internal complexity and 21 fluorescent intensity from the pulse. The computer then utilizes the FACSDiva software to acquire and analyze the data it obtains. Data analysis After obtaining data from the flow cytometer, the files were exported and opened in a program called FlowJo. FlowJo allows for greater flexibility in editing the collected data. With this, cells can be isolated into subpopulations of interest from the initial cell population. A gate is placed around cells of interest and only cells those cells within will appear for the following analysis. At any time, these gates can be altered. Cells appear on a graph, and the x- and y-axis can be changed to display the desired cells. For this experiment, the GP33 Antigen (Ag)-specific CD8+ T cells were the cells of interest; consequently all gates and markers were only extracted using those parameters. The graph can be divided into four quadrants to represent the populations of cells. The bottom left quadrant represents the double negative population, which are cells that are neither the labeled x- nor y-axis variable. The double positive population appears on the top right quadrant and represents cells of both x- and y-axis variable origin. The cells on the top left consist only of cells of the y-axis variable and not the x-axis variable, and conversely, the cells on the bottom right represent cells of the x- and not y-axis variable. The graphs in figure 5 show a live lymphocyte gate and GP33 Ag-specific CD8+ T cell gate. The rectangular gate in the latter graph represents all CD8+ T cells, while the oval gate represents both CD8+ and GP33 Ag-specific T cells. A problem that is often encountered is when the wavelengths of two or more fluorochromes overlap. Thus, the signals detected by the cytometer are not representative of the signal of the cell. This would then give the appearance that a cell is displaying a marker based on the fluorochrome signaling that it does not actually have. When this occurs, the signals are compensated for and adjusted either manually or automatically, and parameters on the flow cytometer can be standardized by performing and applying a

26 22 single color compensation control stain. After cells are gated, numerical data is compiled and organized into a graph for visual representation of trends and determining significance of results. This is done by using the program Prism, which statistically calculates data and any errors associated with the cell numbers of populations provided by FlowJo. A) Live Lymphocytes B) CD8+ T Cells Forward Scatter GP33 Ag-Specific T Cells Side Scatter CD8+ T Cells Figure 5. Graphs that represent cells obtained from the flow cytometer. Gates are placed around cells of interest; left graph (A) shows a gate of the live lymphocytes and the right graph (B) shows a rectangular gate around CD8+ T cells and oval gate around CD8+ GP33+ Ag-specific T Cells

27 23 Chapter 4 Results Experimental Setup A total of ten mice (n=10) were used, five of which were wildtype B6 mice and five of which were CD4 KO. In both groups, three of the mice were given Ampicillin treatment and two were left untreated. Blood in mice were periodically extracted by bleeding behind the eyes, and the lymphocytes were isolated to test for expression of certain protein markers that are indicators of CD8 effector and memory T cell formation, differentiation and maintenance. Mice were infected with LMgp33 (5 x 10 4 colony-forming units (c.f.u.)) intravenously (i.v.). Three CD4 KO and three B6 mice were treated daily with 1mg/mouse of Ampicillin in PBS intraperitoneally (i.p.) from days 5 through 12 post-infection. Their standard drinking water was treated with 2mg of Ampicillin per ml of water from days 5 through 12 post-infection. Remaining mice not undergoing treatment were given 500µl PBS. On day 86, mice were sacrificed so their spleens could be isolated to extract the T cells and test for cytokine signaling via peptide stimulation. Figure 6 displays the full experimental layout. In order to fully understand the rational behind having a treatment group, it must be thought of in terms of what the potential outcome/result would be in this experiment. If the CD4 KO untreated group displayed poor CD8 T cell memory, it cannot be certain whether this is due to lack of CD4 T cell help or if it is because of persisting antigen. By using a treatment group, the possibility of poor memory from persisting antigen is eliminated, thus based on those circumstances, it can be predicted whether or not CD4 T cell help is a direct requirement. Moreover on a hypothetical scale, if the CD4 KO treated mice provide good memory while the CD4 KO untreated mice provide bad memory, it can inferred that the direct need for CD4 T cell help is not required, otherwise the CD4 KO treatment mice should also display

28 bad memory simply from the lack of CD4 cells. Thus, perhaps, CD4 cells must merely serve to 24 "condition" an environment that better facilitates CD8 T cell memory formation, albeit not necessarily vital. Experimental Design Figure 6. An organizational plan for the experiment that tests whether CD4 T cell is a direct or indirect requirement for CD8 T cell memory. During the course of the experiment, one of the mice in the B6 treated group died on day 8 while being bled. Furthermore, cells obtained from bleeds on day 30 were lost due to technical complications with the flow cytometer, thus the data from this day is not included with the results. It is also worth noting

29 25 that single color controls were not set up for this experiment, subsequently resulting in data with several compensation issues. Cellular Markers KLRG-1 The data obtained from the flow cytometer were gated for specific cell surface and intracellular markers commonly expressed on CD8 T cells. KLRG-1 (killer cell lectin-like receptor G1) is an important terminal effector (TE) cell marker. There is generally a high expression of these cells on day 8, the peak that indicates the end of the expansion phase and beginning of memory. KLRG-1 is upregulated on these effector cells denoting their fate of death upon clearing antigen in the body. As previously mentioned, approximately 90-95% of these cells die, and the remaining percent are memory precursors that persist in the body and are maintained as long-lived memory cells (Sarkar, et al). Thus, KLRG-1 is a principal indicator used to distinguish TE cells from memory precursors. In this experiment, expression of KLRG-1 on day 8 appeared consistent with standard expression from any infected mice. Though numbers varied within each group, they were not significantly different. Cell population expression of KLRG-1 markers can be seen on Figure 7. On day 15, cells were not stained for KLRG-1 because the fluorochrome FITC was used for the intracellular marker BCL-2. On day 23, cell numbers in both B6 groups provided inconsistencies within groups. The difference between one B6 mice with the other in either treated or non-treated group was two-fold, and this data is not seen because the values are averaged between the mice when plotted on a graph. Nonetheless the data was unable to be interpreted, as there were only two mice in both treatment and non-treatment group for B6 mice (after one had died) and both had such marked differences in numbers that there was not enough mice for extracting data to establish or determine a bona fide trend. On subsequent days 48, 72 and 86, similar results were seen in the high differences in cell numbers between several mice in the same groups.

30 26 Again, this cannot be seen because the graph only represents the average taken between the mice in each group. Furthermore, the graphical representation of the mice in each group does not provide a clear trend (Figure 8). There appears to be somewhat higher KLRG-1 cells in the B6 group versus the CD4 KO mice; however, the error bars indicate that the results are not significant. An important factor to remember is that KLRG-1 markers should be greatly downregulated after day 8. It is clear that after the expansion peak, there is a sharp decline in cell marker expression. However, some of the data dictated otherwise and suggested some higher expression of KLRG-1 markers. This result should not be ignored; but it should also be considered when interpreting results that these KLRG-1 markers are gated off of a very small population of GP33+ Ag-specific T cells, which in some mice were diminished in number. Fewer cells are harder to analyze and provide a less accurate statistical representation of cell trend.

31 Figure 7. Mice chosen from each group on days 8, 23, 72 and 86 to represent their pattern of KLRG-1 expression 27

32 KLRG-1+ CD8+ T Cells 28 Figure 8. Graphical representation of all KLRG-1+ T cells from each group of mice extracted from the GP33+ CD8+ T cell pool. The average values were plotted per stain day post-infection on days 8, 23, 48, 72 and 86. CD127 Another important marker that was stained for was CD127, which is a protein marker expressed by memory cells. In naïve mice, CD8 T cells strongly upregulate his marker. After infection, the marker is downregulated during the contraction and expansion phase, reaching its minimum at the peak of expansion, and then greatly upregulated during the onset of memory precursor and formation stage. It generally represents the formation of memory precursors since its upregulation re-appears after antigen clearance. It is apparent that in comparison to KLRG-1 expression, the expression of CD127 is the inverse. Thus, this marker is also used to comparatively divide the TE cells from the memory precursors after infection is introduced. For this experiment, CD127 expression was observed to decline after infection, similarly to what is expected. At day 8, though it appears that CD127 may be upregulated sooner in both CD4 KO groups

33 in comparison to the B6 groups that are beginning regulation at or around day 15, this result is 29 insignificant due as statistically represented by the error bars. Likewise in the expression of KLRG-1, several mice had marked differences in expression within similar groups and due to only have two mice in most of the groups, no solid comparison can be made nor concrete interpretation of the data obtained. The graphical representation of the CD127 marker over time for this experiment is not what is normally seen (Figure 10). In analyzing any marker, the B6 treated or untreated group should act as a control/standard for the experiment in which it can provide a reference point of how other cells from the other groups are behaving in comparison to itself. Yet, the data obtained has yielded similar results for every group. Though there appears to be a trend, the results should be analyzed with caution because of the various factors that influence the data, most importantly, as previously mentioned, the small population of GP33+ CD8+ T cells that these are taken from. When memory formation is made, expression of CD127 generally remains steady for days beyond the memory phase. Thus, expression of CD127 would be expected to remain around the same past day 15 or 23 in this experiment. Instead, it continues to increase to day 48 and gently continues to drop to day 86. Perhaps, there were other factors influencing this memory maintenance population that were not known or unable to be accounted for prior to experimentation. Figure 9 shows the original subpopulation of CD127 cells in a specific mouse from each group during each bleed. Most of the numbers are fairly consistent in each groups for each day, however data is skewed because some have more or less cells that are gated off of in analyzing the CD127 marker.

34 Figure 9. Mice chosen from each group on days 8, 23, 72 and 86 to represent their pattern of KLRG-1 expression 30

35 31 Figure 10. Graphical representation of CD127+ T cells from each group of mice extracted from the GP33+ CD8+ T cell pool. The average values were plotted per stain day post-infection on days 8, 23, 48, 72 and 86. Peptide Stimulation A peptide stimulation tests the capability of CD8 memory cells to perform a cytolytic effect, thereby also testing the functionality of the memory cells that were generated. The cells are primed with the GP33 antigen for 5 hours. There is not enough for cells to elicit a full immune response but it is enough to detect several cells and their ability to generate cytolytic functions and cytokine signaling. The cytokines that are commonly produced by CD8 T cells during an infection are interferon-γ (IFN-γ). TNFα, and interleukin-2 (IL-2) and those were the markers tested for during this experiment.

36 32 In a typical T cell during the memory stage, the production of IFN-γ, TNF-α, and IL-2 markers are highly expressed. These can be differentiated from their effectors and naïve cells in that IFN-γ is downregulated in naïve and upregulated in effectors, while IL-2 is the inverse. However, TNF-α remains upregulated throughout every phase of their life during and after infection. The expression of these markers seen on figure 12 correctly identifies with a cell in the effector stage, as should be during a peptide stimulation. The production of IL-2 is apparently low, and the expression of TNF-α and IFN-γ are high. Graphical representations of these markers show that IL-2 production is less than 10% within all IFN-γ cells in each mice group, and TNF-α is expressed at over 80% of that in all IFN-γ in every mice group (figure 11). In figure 11A, IL-2 production is more or less equal for all cells because of the significant differences as indicated by the error bars. A %IL-2+ of IFNr+ T Cells %IL-2+ of IFNr+ Population B6 UnTx B6 Tx CD4 KO UnTx CD4 KO Tx %TNFa+ of IFNr+ T Cells B %TNFa+ of IFNr+ Population B6 UnTx B6 Tx CD4 KO UnTx CD4 KO Tx Figure 11. The average of all mice in each group were plotted for percentage of A) IL-2 production or B) TNF-α (TNFa) within the IFN-γ (IFNr) population. As expected of effector T cells, %IL-2 are low and TNFa levels are high following the pep stim.

37 Day 86 Peptide Stimulation 33 B6 UnTx B6 Tx CD4 KO UnTx CD4 KO UnTx Figure 12: Data from a mouse from each group was taken to depict pattern of IL-2 and TNF-α production following pep stim, plotted against IFN-γ.