phospholipase d signaling in t cells
TRANSCRIPT
Loyola University Chicago Loyola University Chicago
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Dissertations Theses and Dissertations
2010
Phospholipase D Signaling in T Cells Phospholipase D Signaling in T Cells
Uma Chandrasekaran Loyola University Chicago
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LOYOLA UNIVERSITY CHICAGO
PHOSPHOLIPASE D SIGNALING IN T CELLS
A DISSERTATION SUBMITTED TO
THE FACULTY OF THE GRADUATE SCHOOL
IN CANDIDACY FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
PROGRAM IN MICROBIOLOGY AND
IMMUNOLOGY
BY
UMA CHANDRASEKARAN
CHICAGO, IL
DECEMBER 2010
Copyright by UMA CHANDRASEKARAN, 2010 All rights reserved
iii
ACKNOWLEDGEMENTS
First and foremost, I would like to thank my mentor, Dr. Makio Iwashima
for providing an excellent learning environment in the laboratory that has
facilitated my development as a scientist. I am forever grateful to Dr. Knight for
her mentoring and encouragement throughout my graduate school career.
I would also like to thank my dissertation committee, Dr. Christopher
Wiethoff, Dr. Herbert Mathews and Dr. Adriano Marchese for their helpful
suggestions. I am especially grateful to Medical College of Georgia for providing
me a solid foundation during the start of my graduate school career.
I would like to thank all present and past members of the Iwashima Lab for
their technical help and suggestions. Special thanks to Dr. Nagendra Singh,
Mayuko Takezaki, Dr. Yoichi Seki and Dr. Mutsumi Yamamoto; without their
technical expertise, my project would not have been possible. I would also like to
thank my friends Oana Maier, Mariko Takami and Kathleen Mishler for their
friendship and unwavering support.
Finally, I would like to thank my parents, my brother, my husband and the
rest of my family for their continued support, love and encouragement.
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TABLE OF CONTENTS ACKNOWLEDGEMENTS iii LIST OF TABLES vii LIST OF FIGURES viii LIST OF ABBREVIATIONS xi ABSTRACT xv INTRODUCTION 1 CHAPTER ONE: LITERATURE REVIEW 5 The T lymphocyte in Immunology 5 Introduction 5 Establishing the role and function of Thymus 7 Delineation of two major lymphocyte subsets 8 Subdivision of T lymphocytes: CD4 and CD8 10 Heterogeneity of helper T cells 12 Introduction 12 Identification of Th1 and Th2 cells 12 Development and regulation of Th1 and Th2 cells 14 Effector functions and disease implications 16 Th17 cells: new member of effector T cells 16 Heterogeneity of Regulatory T cells 20 Introduction 20 Identification of distinct subsets of Treg cells 21 Phenotypic and functional characteristics of Treg cells 23 Immune homeostasis: population balance between 29 effector and regulatory T cell subsets Role of TCR mediated signaling pathways in altering 32 the immune balance Balancing act of Phospholipase D signaling in T cells 34 PLD: structure, function and expression 34 Regulation of catalytic activity of PLD 38 TCR signaling and PLD 40 Modulation of Phospholipase D signaling by 42 extra-cellular stimuli
v
Adenosine and PLD signaling 45 Conclusion 47 CHAPTER TWO: MATERIALS AND EXPERIMENTAL 48 METHODS Mice 48 Southern blot 49 Adoptive transfer in mice 49 Cell isolation and culture 50 Flow cytometry 53 T cell proliferation assay 54 ELISA 55 Phospholipase D (PLD) assay 56 cAMP measurement 57 Western blot 57 Generation of PLD YFP fusion constructs 58 Confocal microscopy 59 CHAPTER THREE: EXPERIMENTAL RESULTS 65 Regulation of Phospholipase D signaling by exogenous factors 65 Ethanol and CD4 T cell population dynamics 66 Effect of alcohol ingestion on the balance between 80 Foxp3+ and Foxp3- CD4 T cells Clostridium difficile toxin: Hijacking the immune system 82 through PLD signaling Regulation of phospholipase D signaling by endogenous factors 90 Adenosine and CD4 T cell population dynamics 97 Cross talk between adenosine receptor and 101 Phospholipase D signaling Adenosine A3 receptor signaling and cAMP 105 PLD signaling: synergy between ethanol and adenosine 111 Structure-function analysis of Phospholipase D 115 Determinants of PLD1 peri-nuclear localization 116 Determinants of PLD2 plasma membrane localization 122 Effect of PLD2 gene deletion on T cell response 125 CHAPTER FOUR: DISCUSSION 136 Introduction 136 Immune balance: effect of exogenous factors 137
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Immune balance: effect of endogenous factors 140 AB-MECA and Ethanol: Potential use as a 146 Tolerogenic adjuvant PLD localization: interaction between multiple structures 147 PLD2 and T cell functioning 149 Concluding remarks 151 REFERENCES 152 VITA 191
vii
LIST OF TABLES
Figure Page
1. PCR primers 64
viii
LIST OF FIGURES
Figure Page
1. A schematic presentation of the hypothesis proposed 4
2. Heterogeneity of CD4 T cells 19
3. Different subsets of regulatory T cells 28
4. Schematic representation of catalytic reaction of PLD 36 and domain structure of PLD isoforms found in mice 5. Western blot analysis of PLD1 deletion mutant constructs 60
6. Western blot analysis of PLD2 deletion mutant constructs 61
7. Confocal microscopic analysis of YFP fusion constructs 63
8. Effect of ethanol on CD4 T cells in vitro 67
9. Effect of ethanol on CD4 T cells in the presence of 69 antigenic stimulation in vitro
10. Proliferation kinetics of CFSE labeled CD4 T cells 70 in the presence of ethanol
11. Flow cytometry analysis and quantification of cell 73 numbers of CD4 T cells in mice injected with ethanol 12. Effect of ethanol on the proliferation kinetics of Foxp3 74 positive and Foxp3 negative CD4 T cells in vivo in the presence of antigen
ix
13. Effect of ethanol on homeostatic proliferation of 77 CD4 T cells 14. Effect of alcohol containing diet on mice CD4 T cells 81
15. Analysis of proliferation kinetics of Foxp3+ and Foxp3- 83 T cells in the presence of C.difficile toxin supernatants 16. Flow cytometric analysis of activation markers expressed 86 by CD4 T cells following antigenic stimulation in the presence of C.difficile supernatants 17. Flow cytometric analysis of Foxp3+ T cell percentage in 88 mice infected with C.difficile spores 18. Western blot analysis of adenosine A3 receptor 92 expression on CD4 T cells 19. Analysis of activation markers on T cells following 93 antigenic stimulation in the presence of A3 receptor signaling 20. Comparison of proliferation and cytokine secretion profile 95 of DMSO and AB-MECA treated CD4 T cells 21. Effect of adenosine A3 receptor signaling on CD4 T 98 cell population dynamics 22. Flow cytometric analysis of Foxp3 induction in CD4+CD25- 100 T cells following adenosine A3 receptor signaling
23. Effect of A3 receptor signaling on the proliferation kinetics of 102 Foxp3 positive and Foxp3 negative CD4 T cells in vivo 24. Assay of PLD activity in AB-MECA treated CD4 T cells 104 25. Assay for cAMP levels and activity in CD4 T cells 106 26. Western blot analysis of phosphorylation patterns of 110 PKA substrates in AB-MECA treated CD4 T cells 27. Combinatorial effect of ethanol and adenosine on CD4 112 T- cell population dynamics.
x
28. Western blot analysis of phosphorylation patterns of PKA 114 substrates in CD4 T cells treated with a combination of ethanol and AB-MECA 29. Confocal microscopic analysis of the sub-cellular localization 117 of PLD1 loop deletion mutant 30. Confocal microscopic analysis of the sub-cellular localization 118 of PLD1 loop alone or loop and full length PLD1 combinations 31. Schematic representation of the mutant PLD1 constructs 120 and confocal microscopy of their sub-cellular localization 32. Schematic representation of the mutant PLD2 constructs 123 and confocal microscopy of their sub-cellular localization 33. Phenotypic analysis of conditional PLD2 deficient mice 126 34. Characterization of CD4 T cell function in PLD2 128 deficient T cells 35. Cytokine profiles of PLD2 deficient CD4 T cells 130 36. Differentiation of PLD2 CD4 T cells into Th1, Th2 132 and Th17 effector cells 37. Effect of A3 receptor agonist on PLD2 deficient 133 CD4 T cells 38. Effect of ethanol on PLD2 deficient CD4 T cells 134
39. Schematic representation of A3 receptor signaling 145 in CD4 T cells
xi
LIST OF ABBREVIATIONS
AB-MECA N6-(4-Aminobenzyl)-9-[5-(methylcarbonyl) -b-D-ribofuranosyl]adenine
Ado Adenosine
Ag antigen
AHR aryl hydrocarbon receptor
APC Antigen presenting cells
ARF ADP ribosylation factor
CAMP Cyclic adenosine monophosphate
CD Cluster of differentiation antigen
CDAD Clostridium Difficile - associated diarrhoea
CFSE Carboxyfluorescein succinimidyl ester
CFU Colony forming unit
ConA Concanavalin A
CTLA-4 Cytotoxic T lymphocyte antigen-4
DAG Diacylglycerol
DC Dendritic cells
DEX dexamethasone
DMSO Dimethyl sulfoxide
xii
DNA Deoxyribonuclease
EAE Experimental autoimmune encephalomyelitis
ELISA Enzyme-linked immunosorbent assay
ERK Extracellular signal-regulated protein kinase
FACS Fluorescence activated cell sorting
FCS Fetal Calf Serum
Foxp3 Forkhead box protein 3
FICZ Formylindolo (3,2-b) carbazole
GITR Glucocorticoid-induced TNF receptor family related protein
HIV Human immunodeficiency virus
IBD Inflammatory Bowel disease
IFN-γ Interferon-γ
IL Interleukin
i.p intraperitoneal
i.v intravenous
ITAM Immunoreceptor tyrosine-based activation motif kDa kilodalton
LAT Linker of activated T cell
Lck leukocyte-specific protein tyrosine kinase
LP Lamina propria
MACS Magnetic cell sorting
MBP Myelin basic protein
xiii
MHC Major histocompatibility complex
mTOR Mammalian target of rapamycin
nTregs Naturally occurring regulatory T cells
PA Phosphatidic acid
PBS Phosphate buffered saline
PC Phosphatidyl Choline
PCR Polymerase chain reaction
PGE Prostaglandin
PH Pleckstrin homology
PKA Protein kinase A
PLC Phospholipase C
PLD Phospholipase D
PKC Protein kinase C
PX Phox homology domain
RA Rheumatoid arthritis
RAG-1 Recombination activating gene-1
ROR Retinoid-related orphan receptor
RPMI Roswell Park Memorial Institute
SDS-PAGE Sodium dodecylsulfate-polyacyrlamide gel electrophoresis STAT Signal Transducer and Activator of Transcription
T-bet T-box transcription factor
TCR T cell receptor
TcdB Toxin B
xiv
TGF Transforming growth factor
Th T helper
TNF Tumour necrosis factor
Tregs T regulatory cells
T1D Type-1 diabetes
Zap-70 Zeta-chain-associated protein 70
xv
ABSTRACT
Antigen stimulation of T lymphocytes induces the activation of
phospholipase D (PLD) signaling. Phospholipase D (PLD) is a
phosphodiesterase that catalyzes the conversion of phosphatidyl choline (PC) to
phosphatidic acid (PA). PA is an important lipid second messenger and is known
to mediate a variety of cellular functions. However, the specific role of PA in T
lymphocytes has not been established. Previous studies indicated differential
requirement for TCR induced PLD signaling in regulatory and non-regulatory T
cells. Inhibition of TCR induced PLD signal preferentially suppressed the growth
of non-regulatory T cells while allowing the proliferation of regulatory T cells in
the presence of exogenous IL-2. Based on this observation, we hypothesized
that PLD signaling is a critical factor that balances the population dynamics
between regulatory and non-regulatory T cells.
For my dissertation work, I focused on elucidating the functional and
molecular regulation of PLD signaling in T cells. In this study, we identified that
various exogenous (alcohol and Clostridium difficile toxin) and endogenous
factors (adenosine) modulate PLD signaling altering the population dynamics of
regulatory and non-regulatory T cells.
xvi
PLD has two isoforms namely PLD1 and PLD2 expressed in mammalian
cells. These isoforms are 50% identical and have distinct localization in the cell.
PLD1 has peri-nuclear localization while PLD2 localizes to the plasma
membrane. Molecular analysis of PLD1 and PLD2 using domain deletion
suggested that a region unique to PLD1 known as the ‘loop’ confers the distinct
peri-nuclear localization of PLD1.
Further, we addressed the specific function of PLD2 in CD4 T cells using
PLD2 knock out mice. We found that PLD2 is dispensable for T cell activation
and proliferation but might play an important role in effector T cell differentiation.
The results from this study delineate some of the functions of PLD signaling in T
cells and provide insight into immunological regulation during T cell activation.
1
INTRODUCTION
The mammalian immune system exists in a state of equilibrium that allows
for immune activation (reactivity) against pathogens (foreign antigens) while
maintaining tolerance (non-reactivity) towards self-antigens. This balance is
achieved primarily through interactions between different subsets of T
lymphocytes (Littman and Rudensky, 2010). T cell receptors (TCR) recognize
short peptides derived from both self and foreign antigens in the context of major
histocompatibility complex (MHC) thus underscoring their role in both host
defense and autoimmunity (Sette et al., 1993). The fate of a T cell following
antigen recognition is influenced by the environmental cues it receives from the
surrounding milieu like the presence of different cytokines. Through the activation
of specific transcription factors, various cytokines promote distinct effector T cell
lineage commitment (Th1, Th2, Th17) thus conferring protection against a wide
variety of pathogens (Bettelli et al., 2007; Delgoffe et al., 2009). To avoid
uncontrolled immune activation against foreign and host molecules causing harm
to the host, the immune system employs various tolerance mechanisms.
Regulatory T cell mediated immune suppression plays a major role in regulating
immune response by effector T cells and maintenance of tolerance towards self
(Sakaguchi, 2004).
2Hence, tightly controlled balance between effector and regulatory T cell
populations maintain immune homeostasis. But various ex vivo (alcohol, bacterial
toxins) and in vivo factors (anti-inflammatory agents) can shift the balance
between these two T cell populations with opposing effects. For example, alcohol
and adenosine have long been known to be immunosuppressive (Cook, 1998;
Hasko et al., 2008; Nelson and Kolls, 2002). However, the precise molecular
mechanism through which these molecules alter the immune balance was largely
unknown. Previous reports have suggested that immune balance is sensitive to
alterations in TCR signaling pathways (Dragone et al., 2006; Goodnow, 2001).
Also, differences in the signaling pathways downstream of TCR activation have
been reported in Treg cells versus effector T cells (Gavin et al., 2002). In
particular, our lab had previously reported differential requirement for TCR
induced phospholipase D (PLD) signaling between effector and regulatory T
cells. Inhibition of PLD signaling in effector T cells blocked their proliferation and
survival while it had no significant effect on Treg proliferation (Singh et al., 2006).
Taken together, these data indicated that PLD signaling in T cells is a critical
factor controlling the balance between Treg cells and non-Treg cells.
The goal of my dissertation project was to identify the mechanism of PLD
regulation in T cells. Based on previous data, we hypothesized that inhibition of
PLD signal in T cells may promote dominance of Treg cells while activation of
PLD signaling may promote expansion of effector T cells (Fig 1). We focused on
the possibility that external factors (alcohol and bacterial toxin) and an
endogenous factor (adenosine) might mediate immune-suppression by
3
negatively regulating PLD signaling. Also, the specific role of PLD2 isoform in
altering the T cell balance was determined using mice with T cell specific deletion
of PLD2. Further, we identified the critical region controlling the sub-cellular
localization of PLD isoforms.
In the sections to follow, the significance of PLD signaling in T cells and
rationale and discussion of the experiments performed to address the hypothesis
is described.
4
Ethanol, Adenosine, C.diff toxin
Fig 1. A schematic presentation of the hypothesis proposed. Active PLD
signaling following TCR stimulation leads to expansion of effector T cells (white
circles) accompanied by a modest proliferation of nTreg cells (grey circles). TCR
signaling in the presence of various exogenous factors (alcohol, bacterial toxins)
and endogenous factors (adenosine) suppresses PLD signaling thus inhibiting
the expansion of effector T cells. (Courtesy: Dr.Iwashima)
5
CHAPTER ONE
LITERATURE REVIEW
THE T LYMPHOCYTE IN IMMUNOLOGY
Introduction
The immune system can be perceived as an army of organs, tissues, cells
and molecules that protect the host against a wide variety of invading pathogens
(Eberl, 2010). The coordinated effort of these various immune components
provides the host with layered defenses of increasing specificity (Alberts, 2002) .
At first, the physical barrier like skin prevents bacteria and viruses from entering
the host. In case of entry into the host, the innate immune response provides an
immediate but non-specific immune response. If pathogens escape the innate
immune response, vertebrates are equipped with an adaptive immune system.
The adaptive immune system makes use of variable receptors to target specific
pathogen antigens. Also, adaptive immune responses provide faster and
heightened responses upon re-infection with the pathogen due to maintenance of
immunological memory.
Bone marrow derived (B cells) and Thymus derived lymphocytes (T cells)
are now considered the key mediators of adaptive immune responses. However,
6 this was not always the case. Until 1950, the only property known about
lymphocytes was that they were motile (Miller, 2002). Using tritiated thymidine
and cannulation of thoracic duct, James Gowans showed that small lymphocytes
continuously re-circulate from the thoracic duct to blood and secondary lymphoid
tissue and back to the thoracic duct (Gowans, 1996) (Masopust et al., 2007).
Miller et al., in 1961 were the first to demonstrate the existence of two major
interacting subsets of lymphocytes, T and B cells. Further research suggested
that T cells could be divided into two distinct subsets on the basis of their cell
surface markers: CD4 and CD8. In terms of their function, CD4 T cells were
thought to help antibody synthesis (thus, helper T cells) while CD8 T cells
mediated cytotoxic effect on pathogens. In 1986, Mossman and Coffman showed
that CD4 T cells were heterogeneous and based on their pattern of cytokine
production can be further divided into Th1 and Th2 cells. Recent investigations
have further expanded the helper T cell subsets into Th17, regulatory T cells and
follicular helper T cells. Thus, the central role of T cells in orchestrating the
immune response against a wide variety of pathogens and maintenance of self-
regulatory network has been firmly established.
Despite the tremendous increase in the knowledge of T cell subsets, their
specific contribution to disease progression is not well established. Researchers
are only now beginning to apply the knowledge gained from scientific
experiments to therapeutic interventions.
7
Establishing the role and function of Thymus
Ancient Greeks noted the presence of a large mass of tissue in the chest above
the heart and they concluded that it had to be the seat of the ‘Soul’ (Miller, 2002).
The wasting away of the soul after puberty was never addressed (Miller, 2002).
As early as 1777, William Hewson noted that the thymus was filled with particles
resembling those in lymph and blood. Also, he believed that the thymus exists
during the early periods of life only when those particles seem to be most wanted
(Miller, 2002). Another hematologist, John Beard also echoed the same views as
Hewson and suggested that thymus must be regarded as the parent source of all
lymphoid structures of the body and that leukocytes starting from their birth place
in the thymus penetrate into all parts of the body and perform functions in the
body (Miller, 2002). Although, both Hewson and Beard had the right views they
did not have the right tools and technical skills to demonstrate their idea.
In the late 1950s, Gross showed that filtered extracts of leukemic tissues
from high leukemic strain mice could induce the disease in a low leukemic strain
of mice if the extracts were injected at birth (Gross, 1951; Miller, 1999, 2002).
The role of thymus in leukemogenesis was known as it was previously
demonstrated that adult thymectomy prevented spontaneous mouse leukemia
developing in high leukemic strains of mice as well as leukemia induced by
chemical carcinogens. Miller hypothesized that virus given at birth multiplied in
the developing thymus and thus led to leukemogenic transformation. In order to
test this hypothesis, he neonatally thymectomized mice. If his hypothesis was
correct, he expected that neonatal mice lacking a thymus from birth should no
8
longer be susceptible to virus infection and would not develop leukemia when
grafted with thymic tissue later. However, he found that these neonatally
thymectomized mice were healthy at first but wasted away after weaning and
died irrespective of virus inoculation. On the other hand, adult thymectomized
mice survived and never showed any signs of weight loss or any other pathology.
This led him to conclude that “ the thymus at birth may be essential to life “(Miller,
1961).
Histological examination of the tissues of neonatally thymectomized mice
displayed a marked deficiency of lymphocytes in the lymphoid tissues and in the
circulation along with the presence of liver lesions suggesting infection by
hepatitis virus (Miller, 1999, 2002). Further these mice failed to reject skin grafts
derived from foreign mouse strains indicating immune deficiency. Conversely,
inoculation of lymph node/spleen cells or implantation of thymic tissue led to the
recovery of immunological functions in these mice as efficiently as normal mice
(Miller, 2002). In summary, these studies firmly established the crucial role of
thymus in normal immune system development and function.
Delineation of two major lymphocyte subsets
Based on the observations of defective cellular immunity and impaired antibody
producing capacity in neonatally thymectomized mice, it was accepted that
mammalian thymus produced lymphocytes that participated in both cellular and
humoral immunity. In 1962, Burnet and colleagues reported division of labor
among chicken lymphocytes as they found that early bursectomy was associated
9
with defects in antibody formation and early thymectomy was associated with
defects in cellular response (failure to reject homografts) (Warner et al., 1962).
Also, Parrott et al., observed that neonatally thymectomized mice had a
deficiency of lymphocytes limited to those areas of lymph node and spleen
associated with histological changes induced by cell mediated immune
responses but not in those areas where antibody producing cells appeared
(Parrott et al., 1966). All these emerging data intrigued Dr.Miller and he set out to
understand the contribution of thymus to the pool of small lymphocytes and to
antibody forming capacity. Using histocompatibility differences as markers, Miller
et al., proposed the existence of two major subsets of lymphocytes. They were
antibody forming cell precursors derived from lymphocytes in bone marrow (B
cells) and thymus-derived cells (T cells) essential to allow the former to respond
to antigen by producing antibody and mediating cellular immunity against foreign
grafts (Miller and Mitchell, 1967) (Mitchell and Miller, 1968).
Following the reports of two families of lymphocytes, several physical and
biochemical techniques were developed to distinguish these cell populations on
the basis of their surface markers, response to a number of mitogens etc (Hirst et
al., 1975). By 1970, it was widely accepted that T cells reacted with Thy-1 (θ)
antisera, thus serving as a specific T cell marker (Masopust et al., 2007) (Raff,
2008).
10
Sub-division of T lymphocytes: CD4 and CD8
In 1960, Govaerts demonstrated that lymphocytes from immunized
animals rather than the serum, destroyed allogeneic targets in vitro (Govaerts,
1960). Interestingly, destruction of T cells with anti-θ antiserum eliminated this
capability of lymphocytes to destroy allogeneic targets in vitro (Cerottini et al.,
1970). Several researchers corroborated this finding of cytotoxicity mediated by
T cells (Golstein et al., 1972).
T lymphocytes were reported to participate in a variety of cell-mediated
immune reactions like alloreactivity, cell mediated cytotoxicity and amplification of
antibody production by B cells (Cantor and Boyse, 1975). However, it was not
known whether T cells acquire these diverse functions following antigenic
stimulation or whether functionally distinct T cell subclass were present in non-
immune animals. To address this question, Cantor et al., undertook experiments
to define cell surface components selectively expressed by T cells mediating
these distinct functions. Cantor et al., hypothesized that genes coding for such
components would be exclusively expressed in T cells. Previous work had
reported that Ly antigens are expressed exclusively on thymus-derived
lymphocytes, so Cantor determined if these functionally distinct T cell populations
could be classified on the basis of expression of different Ly alloantigens. He
reported that helper T cells exclusively expressed Ly-1 while cytotoxic T cells
expressed Ly-23. Also, these subclasses of T cells were found in non-immune
animals indicating that commitment of T cells to participate in either helper or
cytotoxic function is a differentiative process independent of antigen exposure.
11
Further, Cantor et al, demonstrated using adoptive transfer of Ly-1 and Ly-23
expressing T cells into lethally irradiated mice, the absence of inter/ sequential
conversion of Ly-1 and Ly-23 expressing T cells in the host mice even after
prolonged periods (Huber et al., 1976). Taken together, these studies
demonstrated the presence of two functionally different subsets of T-cells,
representing distinct lineages of thymus-derived lymphocytes.
Further, researchers extended the surface molecule analysis of T cells to
humans and found the human analog of Ly-1 as CD4 and Ly-23 as CD8 (Chess,
2006). Moreover, Rao et al., demonstrated that expression of Ly antigens
determined major histocompatibility complex (MHC) specificity of T cells in
addition to their function (Rao et al., 1983). Thus, CD4+ T cells were found to be
MHC class II restricted, whereas CD8+ T cells were found to be MHC class I
restricted (Chess, 2006). Many years of research culminated in the
understanding of the role of CD4 and CD8 as not just surface markers of T cell
subsets but rather functionally important molecules involved in the recognition of
antigen along with the Ag-specific α,β TCR (Chess, 2006).
12
HETEROGENEITY OF HELPER T CELLS Introduction
Following the discovery of B and T lymphocytes, Miller performed
additional experiments using neonatally thymectomized mice and suggested
possible interactions between B and T cells in antibody responses (Miller, 1999).
This idea was further strengthened by work of Claman et al., and led to the
proposal of the “two cell” theory of antibody production (Claman and Chaperon,
1969). The discovery of two distinct lymphocyte populations and their synergism
in antibody production posed many interesting questions to researchers like the
nature of the contact between these two cells, timing, dosage of antigen, method
of information transfer etc. The process of answering these questions and much
technical advancement led to the identification of heterogeneity among helper T
cells (Fig 2).
Identification of Th1 and Th2 cells
By 1970, it was generally accepted that a homogeneous population of
thymus derived T cells participated in both cell mediated immunity (delayed–type
hypersensitivity reactions) and humoral immunity (helper cells in antibody
response (Liew and Parish, 1974). In 1971, Parish et al, found an inverse
relationship between humoral and cell mediated immunity and proposed the
possibility of different sub-populations of T cells mediating delayed type
hypersensitivity and helper functions (Liew, 2002; Liew and Parish, 1974).
13
Marrack et al further confirmed the existence of different sub-populations of CD4
T cells. They demonstrated the presence of antigen specific and non-specific Th
cells (Marrack and Kappler, 1975). Furthermore, Tada et al., demonstrated the
presence of two types of helper T cells that act either independently or
synergistically to help the B-cell response to an antigen (Tada et al., 1978). He
further distinguished these subsets of CD4 T cells on the basis of their
adherence to nylon wool column and the expression of Ia antigen. Accordingly,
Th1 cells were nylon non-adherent, did not express the Ia antigen and led to
modest increase in B cell responses, while Th2 cells were nylon adherent,
expressed the Ia antigen and led to maximal stimulation of B cell responses.
All of the above-mentioned experiments were conducted by stimulating
whole T cell fractions isolated from spleen with an antigen, thus depicting
polyclonal activation of T cells. However, by using the recently established
method for deriving alloreactive T cell clones (Fathman and Hengartner, 1978),
Mossman and Coffman established a panel of antigen specific helper T cell
clones. They categorized these helper T cell clones on the basis of their pattern
of cytokine production (Liew, 2002). They tested the effect of these cytokines
(derived by stimulating individual Th cell clones with ConA) on the proliferative
ability of 3 main cell lines namely HT2, NFS60 and MM3 cell lines (Mosmann et
al., 1986). This led to the identification of two distinct types of CD4 T cells. Type
I cells produced IL-2, IFN-γ, GM-CSF and IL-3 in response to antigenic
stimulation while type II cells produced IL-3, IL-4 and IL-5 (Liew, 2002). In line
with previous observations of Tada et al., type I helper T cell clones enhanced
14
IgG1 production by 10 fold and did not induce Ia expression on B cells while type
II T cell clones enhanced IgE production by 100 fold and induced Ia expression
on B cells. Hence, Mossman et al., used the same nomenclature proposed
earlier and categorized these CD4 T cells as Th1 and Th2 (Liew, 2002).
Following this discovery using T cell lines, attempts were made to define
CD4 T cell subsets in mice under physiological conditions. This led to the
proposal of four different CD4 T cell subsets: cells producing Th1 cytokines, Th2
cytokines, both Th1 and Th2 cytokines and neither Th1 /Th2 cytokine (Hayakawa
and Hardy, 1988). Additional results on the same cell lines led to the proposal of
a Th0 subset, which produced both Th1 and Th2 cytokines and were thought to
be uncommitted precursors of Th1 and Th2 subsets of CD4 T cells (Firestein et
al., 1989).
Development and regulation of Th1 and Th2 cells
Confirmation of the existence of Th1/Th2 subsets of CD4 T cells led to
further investigations into their development and mechanisms of regulation.
Gajewski and Fernandez-Botran et al., reported that the products of Th1 and Th2
cells could act as autocrine growth factors for further expansion of these cells
and also reciprocally inhibit the opposite cell type (Liew, 2002). IFN- γ enhanced
Th1 cell growth and inhibited the proliferation of Th2 cells while IL-4 promoted
Th2 cell expansion and limited the proliferation of Th1 cell (Fernandez-Botran et
al., 1988; Gajewski and Fitch, 1988).
15
These findings posed many important questions: What initiates the
development of Th1 versus Th2 cells? Are these cells derived from a common
precursor that are instructed to differentiate into various lineages or do they arise
from different precursors that are pre-programmed to develop into different
lineages? Researchers answered these questions using cells from TCR
transgenic mice. Hsieh et al, were the first to demonstrate that naïve T cells from
TCR transgenic DO11.10 mice can develop into both Th1 and Th2 phenotypes
under appropriate cytokine and stimulation conditions (Hsieh et al., 1992).
Similar findings by others established that Th1 and Th2 cells have a common
precursor and that the cytokine microenvironment is the primary determining
factor of the helper T cell subset fates (Liew, 2002). Over the years, many other
factors like antigen dose (Hosken et al., 1995), major histocompatibility complex
haplotypes (Constant et al., 1995) have also been shown to influence the
differentiation of Th1 and Th2 subsets. Also, studies were conducted to
elucidate the mechanism through which cytokines determine the lineage
decisions of helper T cells. Evidence so far indicates that IL-12 drives Th1
differentiation through activation of the transcription factor T-bet in T cells through
STAT4 signaling (Jacobson et al., 1995) (Szabo et al., 2000). Conversely, IL-4
induces Th2 cell differentiation through activation of another transcription factor,
GATA3 via STAT6 signaling (Takeda et al., 1996; Zheng and Flavell, 1997). It is
also proposed that the mutually exclusive expression of T-bet and GATA3 might
reflect the ability of these factors to antagonize each other (Liew, 2002).
16
Effector functions and disease implications
One of the earliest evidence for the role of helper T cell lineages in
disease pathogenesis was suggested in 1981 based on studies of Leishmania
major infections. Howard et al reported that BALB/c mice are highly susceptible
to Leishmania tropica infection compared to C57BL/6 mice (Howard et al., 1980;
Howard et al., 1981). Further using adoptive cell transfer it was shown that the
protection of C57BL/6 mice (resistant strain) correlated with an appropriate
increase in IFN-γ mediated Th1 response and susceptibility of Balb/c mice
correlated with an inappropriate IL-4 mediated Th2 response (Heinzel et al.,
1989; Scott et al., 1988). Th1 response and IFN-γ were also found to be critical to
protect hosts from a variety of infections mediated by intracellular pathogens,
viruses and tumors (Wan and Flavell, 2009). Also, excessive Th1 response has
been related to incidence of inflammatory diseases like IBD and autoimmune
diseases like rheumatoid arthritis (Wan and Flavell, 2009). On the other hand,
Th2 response protects hosts against infections from a variety of extra cellular
pathogens like helminthes. Th2 responses also participate in mucosal immunity
and in allergic diseases (Wan and Flavell, 2009).
Th17 cells: new member of effector T cells
Mossman used the ability of T cell clones to induce footpad swelling as a marker
for delayed type hypersensitivity reactions (Mosmann et al., 1986). Based on
these experiments, he proposed that DTH was mediated solely by Th1 cells. The
lymphocytic infiltrates found in the patients with autoimmune diseases like
17
rheumatoid arthritis (RA) and multiple sclerosis (MS) bear the hallmarks of DTH
(Steinman, 2007). So based on Mossman’s findings it was hypothesized that
administration of IFN-γ would worsen EAE (animal model of MS) while blocking
IFN-γ would ameliorate EAE. Further, one would have also predicted that EAE
would be attenuated or absent in IFN-γ deficient mice.
Contrary to these predictions, the results were just the opposite. For
example, paralysis in the EAE model was worsened in IFN-γ mice. In 2003,
multiple studies demonstrated that IL-23 knock out mice were resistant to the
induction of various autoimmune diseases like EAE, IBD and arthritis (Cua et al.,
2003) (Murphy et al., 2003). The cytokine IL-23 is a heterodimeric molecule,
sharing the p40 subunit with the Th1 cytokine IL-12 but differing from IL-12
because of its p19 subunit (Steinman, 2007). IL-23 does not promote the
development of Th1 cells, but instead it is one of the essential factors driving the
expansion of CD4 T cells producing IL17, IL17F, IL6 and TNF (Langrish et al.,
2005). Using passive transfer studies, authors demonstrated that IL-17 producing
T cells induced EAE while IFN-γ producing T cells did not (Steinman, 2007). Cua
and colleagues showed that EAE, driven by IL-23 and IL-17, was worsened with
administration of neutralizing antibody to γ-IFN suggesting that Th1 and Th17
were reciprocal in terms of their function (Cua et al., 2003).
In an attempt to identify factors that inhibited the TGF-β mediated
conversion of naïve T cells into Foxp3 expressing T cells, Bettelli et al,
discovered that TGF-β along with IL-6 led to differentiation of naïve T cells into
IL-17 producing T cells (Korn et al., 2009). Not surprisingly, IL-6 knock out mice
18
are resistant to EAE and anti-IL6 improves disease condition in EAE (Steinman,
2007). IL-6 or IL-21 in the presence of low amounts of TGF-β result in the
induction of the steroid nuclear receptor, RORα and RORγt in T cells through
STAT3 signaling (Korn et al., 2009). However, the mechanism through which
RORγt regulates Th17 cell differentiation is not yet determined.
In addition to inducing tissue inflammation in autoimmune diseases like
EAE and RA, Th17 cells also participate in host defense against variety of
microbes. Korn et al propose that Th17 cells function in the clearance of specific
types of pathogens that require massive inflammatory responses, which cannot
be dealt with by Th1 and Th2 immunity (Korn et al., 2009). Pathogens as diverse
as Citrobacter rodentium and Candida albicans can trigger Th17 responses
(Huang et al., 2004; Korn et al., 2009). Interestingly, Th17 cells are abundant in
the lamina propria (LP) of the small intestine. Ivanov et al, showed that Th17
cells are induced in the LP in response to specific components of the commensal
microbiota, underscoring their importance in maintaining intestinal immunity
(Ivanov et al., 2008).
19
Figure 2. Heterogeneity of CD4 T cells. Differentiation into different effector
CD4+ T cell lineages, T helper (Th) 1, Th2, Th17, and T regulatory (Treg) cells is
initiated following antigenic stimulation of uncommitted (naïve) CD4+ T helper
cells (Thp). The effector cell types are characterized by their synthesis of specific
cytokines and their immuno-regulatory functions, as indicated on the right. The
differentiation along different lineages involves different cytokines and the
activation of distinct signaling cascades and transcription factors that result in the
induction of additional cyto/chemokines and cyto/chemokine receptors, which
may be part of positive and negative feedback loops. Modified from Jetten et al
((Jetten, 2009)
20
HETEROGENEITY OF REGULATORY T CELLS
Introduction
Immunologists have appreciated the concept of self versus non-self
discrimination by the immune system since the late 19th century. Ray Owen was
the first to observe the phenomenon of immunological tolerance in vivo when he
documented the coexistence of two types of erythrocytes in the blood of dizygotic
cattle twins and the lack of immune reactivity against each other (Owen, 1945;
Wood et al., 2010). This led Burnet to propose the concept of “Neonatal
tolerance” wherein he stated that exposure to an antigen early in life would
induce specific tolerance to that antigen. Burnet further postulated in his clonal
selection theory that during ontogeny, antibodies against self-antigens would be
deleted (Martini and Burgio, 1999; Wood et al., 2010).
In 1970,Gershon and Kondo reported the finding that T cells not only
augmented but also dampened immune responses (Gershon and Kondo, 1970;
Sakaguchi et al., 2007). This suppressive function was found to be mediated by
a subset of T cells called suppressor T cells. It was soon determined that I-J was
the key suppressor molecule expressed by this subset of T cells. However, no
such gene could be found within MHC that encoded this molecule (Steinman,
2007) (Ishii et al., 1982) (Kronenberg et al., 1983).
In the 80s, using newly developed tools (monoclonal antibodies and TCR
transgenic mice) Marrack and von Boehmer’s group reported clonal deletion and
anergy as key mechanisms of immunological tolerance (Marrack and Kappler,
1987; Sakaguchi et al., 2007) (Kisielow et al., 1988). Most of these results were
21
inferred from experiments wherein tolerance was induced towards an exogenous
antigen.
The question of tolerance was addressed from a diametrically opposite
spectrum by investigators like Sakaguchi and Penhale. They studied the effect of
loss of tolerance towards self-antigens and thus the etiology of autoimmune
diseases. This led to the identification of a subset of T cell called regulatory T cell
(Treg cells) that prevented the onset of autoimmunity and is central to the
maintenance of tolerance to self-antigens. An improved understanding of the
mechanisms of tolerance has led to new possibilities for the treatment of
autoimmune diseases (Martini and Burgio, 1999).
Identification of regulatory T cell subset
Ehlrich postulated “Horror autotoxicus” in 1900 suggesting the
unwillingness of the organism to endanger itself by the formation of toxic
autoantibodies (Silverstein, 2001). However, Donath and Landsteiner
demonstrated that the cause of Paroxysmal cold hemoglobinuria is due to the
formation of autoantibodies against patient’s own erythrocytes (Silverstein,
2001). Many other diseases of autoimmune origin were discovered as well but
these results faded in the wake of biochemical pursuits by scientists to uncover
antibody–antigen interactions.
In the late 1960s many studies reported that neonatal thymectomy of
normal mice/rats (day 3 after birth) led to the development of inflammatory tissue
damage along with the appearance of tissue-specific autoantibodies in circulation
22
(Penhale et al., 1973; Sakaguchi et al., 2007). Also, adoptive transfer of CD4 T
cells from these mice with autoimmune disease was sufficient to induce disease
in T cell deficient recipients (McKeever et al., 1990). Interestingly, adoptive
transfer of CD4 T cells from normal syngeneic animals into thymectomized mice
inhibited the development of these diseases. Based on these studies, it was
inferred that there might exist two types of CD4 T cells in the periphery of normal
untreated mice/rats: one capable of mediating autoimmune disease and the other
capable of dominantly suppressing them (Sakaguchi et al., 1985).
Following this, attempts were made to separate these two putative CD4+
T cells on the basis of cell surface markers. In 1985, Sakaguchi demonstrated
that transfer of the CD5low CD4+ T cell subset into nude mice led to the
development of autoimmunity similar to neonatally thymectomized mice while co-
transfer with normal untreated CD4+ T cells inhibited autoimmunity (Sakaguchi et
al., 1985). Similar findings by Powrie and Morrissey, demonstrated the role of
CD45RB CD4+T cells in mediating autoimmune diseases (Powrie et al., 1993)
(Morrissey et al., 1993). In 1995, Sakaguchi et al., identified CD25 as a definitive
marker of CD4 T cells capable of suppressing autoimmune diseases based on
adoptive transfer studies (Sakaguchi et al., 1995). As one would expect based
on previous findings, CD25+ T cells were confined in the CD5 and CD45RB
fraction of CD4 T cells (Sakaguchi et al., 2007). Furthermore, removal of CD25+
T cells not only elicited autoimmune disease but also led to enhanced immune
response against non-self antigens (Sakaguchi et al., 1995). Together, all these
results collectively led to the identification of thymus derived CD4+ CD25+ T cells
high
high low
23
that mediates the maintenance of tolerance to self and controls the magnitude of
immune response to non-self. These CD4+CD25+ T cells were termed as
naturally occurring regulatory T cells (nTreg cells).
Around the same time as the discovery of nTreg cells, two other reports of
CD4 T cells with regulatory properties surfaced. Groux et al., showed that naive
T cells from OVA TCR-transgenic mice, repeatedly stimulated with OVA and IL-
10, differentiated into T cells with a unique cytokine profile distinct from Th1 or
Th2 cells (Groux et al., 1997). They produced IL-10, some IL-5, and IFN- , with
or without TGF- , but showed only marginal or no IL-2 and IL-4 production.
These cells prevented the development of T cell mediated autoimmune
responses. Consequently, these cells were designated as type 1 regulatory T
cells (Tr1) (Jonuleit and Schmitt, 2003) (Beissert et al., 2006) (Fig 3).
Also, Chen et al., described a subset of T cells in mice that suppressed
the onset of myelin basic protein (MBP)-specific experimental autoimmune
encephalitis following induction of oral tolerance to MBP (Jonuleit and Schmitt,
2003). The suppression of these T cells was primarily mediated through TGF
(Transforming growth factor)-β and was called T helper type 3 (Th3) cells
(Beissert et al., 2006)(Fig 3).
Phenotypic and functional characteristics of Treg cells
+ +Naturally arising Treg cells are mostly CD4 CD25 and constitute 5–10% of
peripheral T cells in normal mice (Fehervari and Sakaguchi, 2004). These cells
suppress cytokine production (e.g. IL-2, IL-4, IFN-γ) and proliferation of antigen-
24
receptor stimulated non-regulatory CD4 and CD8 T cells. Although their mode of
suppression is not clearly understood, emerging studies have put forth many
interestingly mechanisms that can be broadly classified into three classes:
contact dependent, soluble factors and killing of target cells. The contribution of
cell contact dependent mechanisms have been suggested based on the inability
of Treg cells to suppress effector T cell proliferation when the two populations
were separated using a semi-permeable membrane (Thornton and Shevach,
1998). Following cell contact, Treg cells might deliver negative signals to
responding T cells through increased cAMP levels (Bopp et al., 2007), which is
inhibitory for T cell proliferation and IL-2 production. Also, production of the
immunosuppressive nucleoside, adenosine through the action of CD39 and
CD73 expressed on the surface of Treg cells has been suggested (Deaglio et al.,
2007). Also, Treg cells have been proposed to suppress immune responses
through cytokine deprivation induced apoptosis of effector T cells (Pandiyan et
al., 2007). IL-2 is a critical growth/survival factor for Treg cells (Fontenot et al.,
2005). At the same time, the presence of exogenous IL-2 abrogates the
suppressive property of Treg cells.
Although surface phenotype of CD4+CD25+ was originally used to isolate
these populations, it is not a definitive marker of natural regulatory T cells since
activated effector T cells also express CD25. Many other cell surface markers
expressed by Treg cells are CD38 (Martins and Aguas, 1999; Read et al., 1998),
CD62L (Ermann et al., 2005; Mudter et al., 2002; You et al., 2004), CD103 (Banz
et al., 2003), glucocorticoid-induced tumor necrosis factor (TNF) receptor
25
(GITR)(Shimizu et al., 2002), or low levels of cell-surface CD45RB (Powrie et al.,
1996; Powrie et al., 1994; Read et al., 2000; Taams et al., 2001), though none of
these are exclusive to Treg cells. Currently, the most reliable marker that
exclusively distinguishes Treg cells from non-Treg cells is a transcriptional
repressor Foxp3 (forkhead box P3)(Fontenot et al., 2003; Gambineri et al., 2003;
Hori et al., 2003; Khattri et al., 2003; Schubert et al., 2001). Mutations of foxp3
gene result in severe autoimmune disorders both in human and mouse (Bennett
et al., 2001; Brunkow et al., 2001; Chatila et al., 2000; Wildin et al., 2001). Foxp3
gene is required for the production and maintenance of regulatory T cells
(Fontenot et al., 2003; Kim et al., 2007) and most importantly Foxp3 is not
induced upon activation of non-suppressive murine CD4+CD25- T cells (Fontenot
et al., 2003; Hori et al., 2003; Khattri et al., 2003).
Accumulating evidence suggests that the function of Treg cells is not
limited to suppression of autoimmunity and they play significant roles impairing
the immune response to chronic viral infections (Mills, 2004; Mills and McGuirk,
2004; Rouse and Suvas, 2004; Suvas et al., 2004; Suvas et al., 2003; Toka et
al., 2004). This was first reported using persistent Friend leukemia virus infection
of mice (Iwashiro et al., 2001). Mice infected with this virus have suppressed
CD8 T cell-mediated immunity against virus-infected cells. When CD4+CD25+ T
cells are removed from peripheral T cells of infected mice, CD8 T cells markedly
reduced viral levels during persistence (Dittmer et al., 2004). Increase of Treg
cells was also reported in cases of infection with HIV (Weiss et al., 2004).
26
Other studies have demonstrated that the frequency of Treg cells
increases under tumor bearing conditions (Waldmann, 2006), as well as during
pregnancy (Saito et al., 2005; Zenclussen, 2005). Conversely, decrease of Treg
cells was reported in cases of autoimmune disease such as multiple sclerosis,
type I diabetes, and rheumatoid arthritis (Lan et al., 2005).
As mentioned previously, regulatory T cells (CD4+Foxp3+) can also be
induced in the periphery and hence are called “adaptive” or “induced” Treg cells.
IL-10 producing Tr1 cells proliferate poorly after polyclonal or Ag-specific
activation in vitro and functional studies revealed that these cells have
immunosuppressive properties and can prevent the development of T cell-
mediated autoimmune responses (Levings et al., 2002) (Jonuleit and Schmitt,
2003). Tr1 can control the activation of naive and memory T cells both in vitro and
in vivo and suppress Th1- and Th2-mediated immune responses to pathogens,
tumors, and alloantigens (Groux, 2003). Furthermore, supernatants of activated
Tr1 cells strongly reduce the capacity of dendritic cells (DC) to induce
alloantigen-specific T cell proliferation (Levings et al., 2002) (Roncarolo et al.,
2001). The suppressive effects of Tr1 cells are reversed by blocking Abs against
IL-10, showing that the inhibitory capacity of Tr1 cells is mainly mediated through
production of immunosuppressive IL-10 (Groux et al., 1997; Levings et al., 2002).
Regulatory Th3 cells are a unique T cell subset induced by orally
administered Ag in vivo and triggered in an Ag-specific fashion (Jonuleit and
Schmitt, 2003). They provide help for IgA production and have suppressive
properties for Th1 and Th2 cells (Jonuleit and Schmitt, 2003; Weiner, 2001a).
27
However, the suppression of immune responses mediated by Th3 cells are Ag
nonspecific and can occur as bystander suppression through secretion of TGF-β.
Because TGF-β is broadly expressed and influences the functional activity of
multiple cell types, TGF-β secreting Th3 cells probably have a major role in many
aspects of immune regulation and T cell homeostasis (Weiner, 2001b).
28
Fig 3. Different subsets of regulatory T cells. Naturally occurring regulatory T
cells mature and migrate from the thymus and constitute 5–10% of peripheral T
cells in normal mice. The inducible populations of regulatory T cells include
distinct subtypes of CD4+ T cell: TR1 cells, which secrete high levels of IL-10 and
TH3 cells, which secrete high levels of TGF-β. TGF-β can also induce Foxp3
expression CD25- T cells and thus confer regulatory properties to T cells in the
periphery. Modified from Milojevic et al (Milojevic et al., 2008).
29
IMMUNE HOMEOSTASIS: POPULATION BALANCE BETWEEN EFFECTOR
AND REGULATORY T CELL SUBSETS
The immune system faces the daunting task of protecting the host against
a wide variety of pathogens at the same time maintaining peace towards self.
CD4 T cells play key roles in orchestrating both the functions of the immune
response. As mentioned previously, naïve CD4 T cells specialize to become
distinct subsets and produce restricted patterns of cytokines that are tailored to
combat various pathogens. The range of infections afflicting HIV infected
individuals following decline in their CD4 T cell count underscores the importance
of CD4 T cells in host defense (O'Shea and Paul, 2010). On the other hand,
heterogenous populations of CD4+ regulatory T cells suppress the immune
response to both self and non-self antigens. Adoptive transfer of Treg depleted
CD4 T cells leads to development of spontaneous autoimmunity, illustrating the
dominant role of Treg cells in mediating tolerance and autoimmunity.
Homeostasis of the immune response depends on the balance of
population dynamics and functionality between these effector and regulatory T
cell subsets (Mills, 2004). Perturbations in this balance have been reported in
many diseases. Tang et al, reported that type I diabetes (T1D) progression in the
NOD mice was associated with a progressive loss of functional Treg cells in the
inflamed islets (Tang et al., 2008). Conversely, expansion of Treg cells in
inflammatory mouse models like EAE has been reported to be associated with
disease resolution (Knoechel et al., 2005) (Korn et al., 2007).
30
Various mechanisms have been proposed to explain the alterations in the
balance between Treg cells and effector T cells in vivo. The importance of IL-2
levels in the maintenance of homeostasis is evident from different studies. For
instance, Tang et al observed that low dose injections of IL-2 supported the
growth and survival of Treg cells over effector T cells (Teff) whereas a high dose
of IL-2 led to rapid expansion of effector T cells (Tang et al., 2008). Based on
these observations they further proposed that Treg cells versus effector T cells
regulate each other through a feedback loop. IL-2 production by activated Teff
cells expands and sustains Treg cells, which in turn feeds back to suppress the
Teff cell response and maintain normal immune homeostasis. Disruption of this
crosstalk can lead to the dysregulation of the Treg cell: Teff balance thus
contributing to the development of disease (Tang et al., 2008).
Recent emerging studies suggest that plasticity and interconvertibility
among different subset of T cells might also alter the immune balance (Wan and
Flavell, 2009). Foxp3 expressing T cells from wild type mice lose Foxp3
expression and exhibit activated-memory phenotype and produce inflammatory
cytokines (Zhou et al., 2009). Also, fully differentiated Th17 cells were shown to
convert into Th1 cells in the absence of TGF-β (Lee et al., 2009). However, the
mechanism and the proportion of T cells undergoing such inter-conversion are
not known. This newly defined property of CD4 T cells can have far reaching
consequences in the pathogenesis and treatment of variety of diseases ranging
from autoimmunity to cancer.
31
Studies of immune evasion by various pathogens also provide clues to the
mechanisms of alteration of immune balance. One of the common immune
evasion strategy employed by many pathogens involves increasing the
production of various immunosuppressive or anti-inflammatory molecules to
skew the immune response towards regulatory phenotype. Many intracellular
pathogens and viruses either induce cellular IL-10 or encode their own IL-10
homolog to delay or suppress the host immune response (Redpath et al., 2001).
Various environmental toxins have also been shown to tip the immune
balance between the effector and regulatory T cells. Quintana and Veldhoen et al
demonstrated that dioxin signaling through aryl hydrocarbon receptor (AHR)
increased Treg activity and proliferation while activation of AHR by FICZ led to
increased Th17 activity (Quintana et al., 2008) (Veldhoen et al., 2008).
Manipulation of the immune balance serves as an attractive target for
therapy for a range of human diseases. The ideal treatment for autoimmune
disease would be to decrease the frequency of effector T cells and increase the
frequency of Treg cells. Several investigators have devised many therapeutic
strategies to tip the Treg: effector T cell balance. For example, administration of
monoclonal antibodies to CD3, CD4 or CD40L in the presence of antigen causes
selective expansion of Foxp3+ Treg cells, producing the dominancy of Treg cells
over effector T cells (Wing and Sakaguchi, 2010). Rapamycin, an inhibitor of the
Akt-mTOR pathway, increases the number of Foxp3+ T cells in part by enhancing
Foxp3 transcription and by rendering Treg cells resistant to apoptosis (Basu et al.,
2008; Strauss et al., 2007c; Wing and Sakaguchi, 2010). Administration of IL-2–
32
anti-IL-2 complexes selectively expands Foxp3+ Treg cell populations (Webster et
al., 2009; Wing and Sakaguchi, 2010). On the other hand, the ideal treatment in
the case of tumours would be to increase the frequency of effector T cells and
reduce the numbers of Treg cells. Administration of anti-CD25 mAb (PC61) has
been reported to cause reduction in the number of CD4+CD25+ cells thus
enabling tumour rejection (Onizuka et al., 1999).
Role of TCR mediated signaling pathwyas in altering the immune balance
The underlying theme in the above mentioned strategies for selective
expansion/inhibition of Treg cells/Teff is the manipulation of IL-2 and/or IL-2R
signaling in CD4 T cells. The potential caveat in these strategies is that IL-2 is a
T cell growth factor for both effector and regulatory T cells and this might lead to
high variability in the in vivo effect in a heterogeneous patient population.
An alternative strategy would be to identify specific factors/signaling
cascades present exclusively in one subset versus the other and to exploit those
molecules for therapeutic applications. Consistent with this notion several studies
have reported the role of specific TCR associated signaling molecules in
controlling the direction of helper T cell subset differentiation.
Recognition of MHC–antigen peptide complex by T cell receptor triggers a
cascade of downstream signaling events. The most proximal biochemical event
is the tyrosine phosphorylation of the immunoreceptor tyrosine-based activation
motifs (ITAMs) of the TCR/CD3 complex (Guy and Vignali, 2009; Iwashima,
2003; Nakayama and Yamashita, 2010). Lck, an Src family tyrosine kinase plays
33
an important role in the tyrosine phosphorylation of ITAMs. Then, the Zap70 Syk
family kinase is recruited to the phosphorylated ITAMs through the SH2 domains
of ZAP70. The recruited ZAP70 is then phosphorylated and activated by
surrounding Lck tyrosine kinase, thus leading to the phosphorylation of LAT
molecules (Nakayama and Yamashita, 2010). Following these proximal events,
the activation of various distinct signaling pathways is initiated, including (i) the
Ras/ERK MAPK cascade, (ii) the Ca/calcineurin/NF-AT pathway, and (iii) the
PKC/NF-κB pathway (Nakayama and Yamashita, 2010). Interestingly, the
differential requirement for various signaling molecules involved in both proximal
and distal events of TCR signaling has been reported in different subsets of CD4
T cells. For instance, Lck activity is required for the generation of Th2 cells as
dominant negative (DN) Lck transgenic mice shows impaired Th2 cell generation
as against intact Th1 cells (Yamashita et al., 1998). In the same lines, Tan et al.,
showed that PKC is necessary for IL-17 production in the mice (Tan et al., 2006).
Further, inhibition of ERK/MAPK cascade using pharmacological inhibitor or DN
Ras results in increased Th1 cell differentiation (Yamashita et al., 1999). Recent
studies from our lab group reported the differential requirement for phospholipase
D (PLD) signaling between regulatory versus non-regulatory T cells. Suppression
of TCR induced increases in PLD activity led to selective inhibition in the
proliferation and survival of effector T cells. As a consequence, the frequency of
Treg cells increased under these conditions. Thus, manipulation of PLD activity
may serve as a tool to alter the immune balance. Hence, identification of
34
factors/molecules that modulate PLD activity will be of significant therapeutic
importance.
BALANCING ACT OF PHOSPHOLIPASE D (PLD) IN T CELLS
PLD: structure, function and expression
PLD belongs to the phosphodiesterase family of proteins, found in
bacteria, fungi and animals (Melendez and Allen, 2002). Mammalian PLDs
catalyze the hydrolysis of phosphatidylcholine (PC) to phosphatidic acid (PA) and
choline (Exton, 2002). Phosphatidic acid is an important lipid second messenger,
which mediates the downstream effects of PLD signaling. PA is an abundant
phospholipid that can be also synthesized from pathways other than PLD
signaling (Athenstaedt and Daum, 1999) .
A unique characteristic of PLD is that primary (1–) alcohol serves as a
more competitive substrate compared to water (> 1000 fold), and the presence of
1–alcohol effectively blocks PLD signaling (Morris et al., 1997) (Fig 4a). In the
presence of 1–alcohol (such as ethanol or 1–butanol), PLD prefers
transphosphatidylation to hydrolysis and produces phosphatidyl–alcohol, which is
poorly metabolized. As a result, the production of PA is significantly reduced.
Thus, 1-alcohol is a potent suppressive regulator of PLD signaling.
Two isoforms of PLDs are expressed in mammalian tissues namely PLD1
and PLD2, which share 55% identity (Frohman et al., 1999). The domain
structure of PLDs contains phox homology (PX) and pleckstrin homology (PH)
35
domains at the N-terminal followed by four conserved sequences (I-IV) (Sung et
al., 1999)(Fig 4b). PX and PH domains are implicated in phospholipid and protein
binding. Results from deletional analysis indicate that PIP2 binds at PH domain
and at conserved sequences located between catalytic sites II and III (Hodgkin et
al., 1999) (Sciorra et al., 1999). The catalytic sites II and III contain the
characteristic ‘HxKxxxxD’ motifs (Frohman et al., 1999). In addition, PLD1
contains an 116 amino acid ‘loop’ region inserted between the II and III catalytic
sites. The C-terminal four amino acids of mammalian PLDs are evolutionarily
conserved and modification of these residues (mutation/deletion) causes loss of
catalytic activity (Xie et al., 2000) (Liu et al., 2001). PLD1 exists as two splice
variants, PLD1a and PLD1b that differ in the length of the loop region. This
region may function as a negative regulator of PLD1 since deletion of the loop
has been shown to cause modest up regulation of basal catalytic activity of PLD1
(Frohman et al., 1999).
Although PLD1 and PLD2 have the same substrate specificity, the
activities of PLD1 and PLD2 are regulated differently. PLD1 has low basal
activity in vitro and it can be stimulated in vitro using agonists as it is coupled to
receptor signaling via the small GTPases, ARF1/6, Rho, CDC42, and RalA. PKC
mediated phosphorylation also up regulates PLD1 activity. In contrast, PLD2 is
less responsive to small GTPases and may be constitutively active and regulated
by inhibition (Colley et al., 1997).
36
A)
B)
Fig 4. Schematic representation of catalytic reaction of PLD and domain
structure of PLD isoforms found in mice. (A) In aqueous solution, PLD
catalyzes hydrolysis of phospholipid to yield Phosphatidic acid (PA). But in the
presence of small amounts of ethanol, PLD yields Phosphatidyl ethanol (PEt).
R1, R2 and R3 are fatty acid side chains. B) Domain structure of PLD isoforms in
mice. PX, phox homology; PH, pleckstrin homology domain. Motifs I~IV are
conserved regions and II and IV contain HKD sequences. Modified from
(Frohman et al., 1999).
37
PLD1 is mainly found in perinuclear regions, whereas PLD2 localizes
predominantly in the plasma membrane (Colley et al., 1997; Sung et al., 1997).
Both PLD1 and PLD2 are palmitoylated in the pleckstrin homology (PH) domain
and found associated with membrane raft fractions (Sugars et al., 1999; Xie et
al., 2001). The site of generation of PA and the availability of effector targets
determines its downstream signaling. Hence, the sub–cellular distribution of both
the isoforms of PLD is an important factor affecting its function and regulation.
Functions of PA
PA is now recognized as a vital second messenger for many cell types
(Andresen et al., 2002; Chen, 2004; Chen and Fang, 2002; Cummings et al.,
2002; English, 1996; Ghosh and Bell, 1997; Houslay and Adams, 2003; Rizzo
and Romero, 2002). For instance, the direct interaction of PA has been
demonstrated for several signaling proteins, namely cRaf-1 (Ghosh et al., 1996;
Rizzo et al., 1999; Rizzo et al., 2000; Wang et al., 2002), mTOR (Chen and
Fang, 2002; Fang et al., 2003; Fang et al., 2001; Lim et al., 2003),
phosphodiesterase 4D3 (El Bawab et al., 1997; Grange et al., 1998; Grange et
al., 2000; Savany et al., 1996), PKC ξ (Bandyopadhyay et al., 2001; Limatola et
al., 1994),SHP-1(Frank et al., 1999; Tomic et al., 1995) and sphingosine kinase-1
(Delon et al., 2004). PA plays a significant role in the regulation of the function of
these proteins. The binding of PA to SHP-1, for instance, activates the
phosphates in vitro (Zhao et al., 1993). PA also functions in protein recruitment.
38
Interactions with PA are essential for the recruitment of cRaf-1 to membranes
(Rizzo et al., 2000).
PA is also a precursor for a number of alternative signaling molecules.
For example, PA can be converted to diacylglycerol (DAG), by phosphatidic acid
phosphohydrolases (Balboa et al., 1995; Billah et al., 1989; Lassegue et al.,
1993; Mullmann et al., 1990). DAG is an activator of conventional and novel
PKC isoforms and other signaling molecules (Cummings et al., 2002;
Gudermann et al., 2004; Haeffner, 1993; Kikkawa et al., 1989; Yang and
Kazanietz, 2003). DAG is also generated by the hydrolysis of
phosphatidylinositol (4,5)-bisphosphate by phospholipase C (Haeffner, 1993;
Nishizuka, 1992). The nature of the DAG species generated by the action of
phospholipase C differs from that derived from PA through the action of
phospholipid phosphohydrolases (Liu et al., 1999; Plo et al., 2000). The
consequences of this difference are currently unknown.
Hence, PA mediates a variety of cell functions including cell survival,
proliferation, cytoskeletal rearrangement and vesicular trafficking (Fang et al.,
2001; Ghosh et al., 1996; Lim et al., 2003; Rizzo et al., 1999). However, the
precise role of PA in modulating T cell function and survival is not clear.
Regulation of catalytic activity of PLD
Various in vitro studies have elucidated the role of certain co-factors in the
catalytic activation/inactivation of PLD. They can be classified into 3 classes.
39
i. Phospholipids
PIP2 was determined to be essential for catalytic activity of PLDs (Brown et al.,
1993). PIP3 is also effective in up regulation of PLD activity. A PIP2 binding site
is located between conserved regions II and III of the catalytic domain and
mutation in this region abrogates PLD activity without altering their sub cellular
localization (Frohman et al., 1999). Another PIP2 binding site has been reported
to be present within the PH domain. This binding site affects PLD activity by
altering their sub cellular localization (Oude Weernink et al., 2007).
ii. Small GTPase
Several small GTPase’s can activate PLD. Activation of PLD1 by ARF is GTP
dependent and requires the N-terminal region of PLD. However, the detailed
mechanism of PLD activation by ARF is not known (Frohman et al., 1999).
Several Rho family proteins, namely RhoA, Rac and CDC42 are also involved in
PLD activation. Invitro, GTPγs activated forms of these proteins have been
shown to activate PLD (Hammond et al., 1997). Botulinum C3 toxin has been
reported to block PLD activation by inactivating Rho (Malcolm et al., 1996;
Schmidt et al., 1996). C-terminus of PLD1 is reported to be the interaction site for
Rho (Du et al., 2000).
Iii PKC
Treatment of cells with phorbol esters effectively activated PLD, suggesting that
Protein Kinase C (PKC) is upstream of PLD activation (Exton, 2002). Several
40
phosphorylation dependent and independent modes phosphorylation by PKC has
been reported (Hammond et al., 1997).
TCR signaling and PLD
Attachment of the T cell receptor complex by its cognate antigen triggers a
cascade of downstream signaling events including phosphorylation of ITAM
motifs, phosphoinositide hydrolysis and calcium flux. Emerging results indicate
that antigen receptors that transduce signals via immuno–receptor tyrosine
based activation motifs (ITAMs) are coupled to PLD activation (Melendez and
Allen, 2002). Fcγ and ε receptors activate PLD by the antigen-antibody complex
(Cockcroft et al., 2002; Gewirtz and Simons, 1997; Gruchalla et al., 1990; Jose
Lopez-Andreo et al., 2003; Kusner et al., 1999; Loegering and Lennartz, 2004).
TCR stimulation was also shown to upregulate PLD activity by 2~300% (Reid et
al., 1997). Inhibition of PLD activity in T cell line caused loss of AP-1 activation,
cytokine production and proliferation (Mollinedo et al., 1994). BCR was also
shown to activate PLD (Forssell et al., 2000; Hitomi et al., 1999).
Previously our lab group had demonstrated that PLD1 and PLD2 signaling
are involved in different stages of TCR signaling (Singh et al., 2006). Over
expression of both PLD1 and PLD2 potentiated NF-AT activation by TCR in
Jurkat cells. CD2/ZAP-70, a fusion protein between the extracellular and
transmembrane domains of CD2 with Zap-70 activates NFAT when expressed in
Jurkat cells. When co-expressed with CD2/Zap-70, PLD1 induced marked
41
upregulation of NFAT activity whereas PLD2 induced only a slight upregulation.
Conversely, lipase inactive PLD2 but not PLD1, blocked anti-TCR antibody
induced tyrosine phosphorylation of TCR ζ. Together, the data indicated that
PLD2 is required for TCR signaling events proximal to the recruitment of Zap-70
to ITAM while PLD1 is involved in events distal to tyrosine phosphorylation of ζ.
It is not yet clear how PLDs are coupled to TCR. Several groups have
reported the presence of PLD enzymes in caveolae, which are specialized
domains of the plasma membrane, related to sphingolipid and cholesterol-rich
micro domains or rafts (Gidwani et al., 2003; Hekman et al., 2002; Zheng et al.,
2003). In view of the fact that molecules with a key role in T cell signaling like
Lck also localize to these domains, it is tempting to suggest that lipid rafts might
provide the perfect platform for PLD and TCR coupling.
In our recent study, we also demonstrated that the increase in PLD activity
after TCR stimulation was two fold in CD4+CD25- cells and rather unchanged in
CD4+CD25+ T cells. Moreover, PLD1 expression was substantially lower in
CD4+CD25+ cells than in CD4+CD25- cells indicating differences in the
requirement for PLD signaling between regulatory and non-regulatory T cells.
Inhibition of the TCR induced increase in PLD activity in CD4+CD25- T cells
substantially affected their activation; proliferation and cytokine secretion while it
had no effect on CD4+CD25+ T cells. Consequently, culture of heterogeneous
population of naïve CD4 T cells in the presence of TCR stimulation and
exogenous IL-2 led to preferential expansion of Foxp3+CD4+ T cells. Moreover,
these expanded Treg cells exhibited potent immune suppression in a mouse
42
model of inflammatory bowel disease (IBD) indicative of their functional
capabilities. These data also illustrated the biological significance of PLD
signaling in T cells. Investigations to elucidate the anti-proliferative effect of
inhibition of PLD signaling on CD4+CD25- T cells suggested that blockade of
high affinity IL-2 receptor (CD25) expression may be a factor. However, the
precise molecular mechanism of regulation of CD25 expression by PLD is still
unknown. Also, the specific function of the PLD isoforms in mediating this
differential effect on CD4 T cells is unknown.
Modulation of PLD activity by extracellular stimuli
The above mentioned data suggested to us that PLD signal regulation
could play a pivotal role in controlling the balance between regulatory and non-
regulatory T cells. In vivo suppression of PLD signaling may promote dominance
of naturally arising Treg cells under physiological conditions. Conversely,
augmenting PLD signaling may promote growth of effector T cells and break the
immune suppression by Treg cells. This led us to ask: Is it possible for
pathogens/tumours to inhibit PLD activity (directly / indirectly through secretion of
factors) to subvert the protective immune responses of the host? Alternatively,
does elevated PLD activity contribute to autoimmune responses?
There have been a number of studies that indicate the modulation of PLD
activity by various extracellular stimuli. These stimuli in turn mediate their effect
on PLD through the help of above-mentioned cofactors of PLD signaling. Alcohol
43
is an exogenous factor that alters the immune phenotype of the host (Nelson and
Kolls, 2002). T cells from individuals who were exposed to alcohol both
chronically and acutely showed a higher frequency of T cells expressing CD25
(Cao et al., 1998; Laso et al., 1996a; Laso et al., 1996b; Sacanella et al., 1998;
Santos-Perez et al., 1996). One study showed that these T cells were
exclusively CD4+ (Laso et al., 1996b). Moreover, the frequency of CD25+ T cell
remained high even 9 months after alcohol withdrawal. In another study, clear
positive correlation was observed between total estimated life time dose of
ethanol consumed and the percentage of PBLs expressing CD25 (Sacanella et
al., 1998). Our studies suggested that these effects might be channeled through
suppression of PLD signaling and increased frequency of Treg cells.
Pathogens like Clostridium difficile might also alter the host immune
response through PLD signaling. The major virulence factors produced by
C.difficile are Toxin A (TcdA) and Toxin B (TcdB) (Genth et al., 2008). Inside the
host cell, these toxins mono-glucosylate and thereby inactivate small G proteins
of the Rho sub-family (Genth et al., 2008). Since PLD is one of the downstream
effector molecules of Rho, these toxins indirectly inhibit PLD activity (Schmidt et
al., 1996). We propose that the functional consequence of inhibiting PLD
signaling is enrichment of Treg cells. This in turn might facilitate the evasion of
host immune response by C.diff through elimination of the effector response by
non-Treg cells.
The receptor system that has been linked to PLD regulation includes G-
protein coupled receptors and tyrosine kinase coupled receptors (Frohman et al.,
44
1999). G-protein coupled receptors include chemokine receptors (RANTES, IL8)
(Bacon et al., 1995; Bacon et al., 1998), adenosine receptors (Selvatici et al.,
2006; Thibault et al., 2002), N-formyl peptide receptor (FPR) (Selvatici et al.,
2006), P2Z/P2X7 nucleotide receptor (Coutinho-Silva et al., 2003) and
prostaglandin (PGE2) receptors (Burelout et al., 2004). Tyrosine kinase coupled
receptors include TCR, BCR, FcReRI, and FcRI (Melendez and Allen, 2002) and
Insulin receptors (Farese, 1988).
These extracellular stimuli alter PLD activity in both a positive and
negative manner. Antigen and chemokine receptors elevate the activity of PLD
(Bacon et al., 1995; Bacon et al., 1998). FPR, which recognizes bacterial
peptides, also elevates PLD activity (Selvatici et al., 2006). On the other hand,
inflammation related receptors, including adenosine receptors (Selvatici et al.,
2006; Thibault et al., 2002), lipoxin A (4) receptor (Levy et al., 1999) and PGE2
receptors (Burelout et al., 2004) suppress PLD activation. Interestingly, a recent
report indicated that PGE2 induces enrichment of regulatory T cells (Baratelli et
al., 2005).
Most of the studies indicate that PLD1 is associated with receptor induced
PLD activity and this involves the role of small GTPases or PKCs whereas PLD2
may be constitutively active and is a target of negative regulation. In contrast to
the activation process of PLD, the process that inactivates PLD is not well
characterized. Adenosine (A2a) receptor signaling in neutrophils (Thibault et al.,
2002) and A3 receptor signaling in ischemic heart (Mozzicato et al., 2004) has
been shown to modulate PLD activity. PGE2 receptor has also been shown to
45
inhibit PLD activity. Both A2a and PGE2 stimulate adenylate cyclase and thereby
increase the intracellular cAMP levels. These data indicate that downstream
targets of cAMP, such as PKA may mediate suppression of PLD activity.
However, no clear connection between PKA and PLD has been made at this
point. Interestingly, a recent report showed that βγ subunits of G protein could
inhibit PLD1 activity by direct interactions (Preininger et al., 2006). Other
negative regulatory factors of PLD include ceramide (Nakamura et al., 1996),
presqualene diphosphate (PSDP) (Levy et al., 1999) and munc-18-1 (Lee et al.,
2004).
Adenosine and PLD signaling
Adenosine (Ado) is a purine nucleoside formed from its precursor ATP by
the action of CD39 [nucleoside triphosphate dephosphorylase (NTPD)] and
CD73 (5-ectonucleotidase)(Hasko et al., 2008). Adenosine is constitutively
present at low concentrations in extracellular space however metabolically
stressful conditions (hypoxia, cell death) increase its levels in extracellular space
drastically (Fredholm et al., 2001; Linden, 2001). Numerous studies suggest the
role of Ado as an immune modulator. First, high concentrations of Ado represent
a pre-eminent alarm signal indicating tissue injury to the surrounding cells.
Secondly, Ado occupies its cognate receptor present on a variety of immune
cells including dendritic cells (Panther et al., 2003; Schnurr et al., 2004),
neutrophils (Cronstein et al., 1983) and lymphocytes and mediates immune
46
suppression (Borsellino et al., 2007; Hasko et al., 2008; Kobie et al., 2006; Zarek
et al., 2008). A physiological response of Ado is elicited by engaging one or
more of the four G-protein coupled receptors (A1, A2a, A2b and A3) (Jacobson
and Gao, 2006).
Recent studies have elucidated an important role for adenosine in
mediating the immunosuppressive properties of Treg cells. It was demonstrated
that Treg cells express CD39/CD73 and thus hydrolyze extra cellular ADP and
ATP to adenosine (Deaglio et al., 2007; Kobie et al., 2006). Also, Treg cells
isolated from CD39 knockout mice do not suppress the proliferation of
CD4+CD25- cells, indicating the role of CD39 in modulating Treg function
(Deaglio et al., 2007). Similarly, Treg cells isolated from wild type mice failed to
suppress CD4+CD25- cells from A2a receptor knockout mice (Naganuma et al.,
2006; Zarek et al., 2008). Numerous studies have established the
immunosuppressive function of A2a receptor signaling. Indeed activation of A2a
receptor on Treg cells causes upregulation of Foxp3 expression (Zarek et al.,
2008). Interestingly, A2a receptor occupancy on neutrophils reduces PLD activity
by limiting the recruitment of Arf, RhoA, and PKC to membranes (Thibault et al.,
2000).
The combined effects of activated adenosine A2 and A3 receptors (A2AR,
A3AR) on mononuclear cells of the immune system are considered anti-
inflammatory (Hasko et al., 2008; Jacobson and Gao, 2006). Activation of A3
receptors on macrophages inhibits the release of tumor necrosis factor alpha
(TNF-α) and thus exerts beneficial effect in treating inflammatory disorders like
47
arthritis (Baharav et al., 2005). Conversely, A3 receptor activation on mast cells
triggers histamine release (Salvatore et al., 2000) and thus is an important player
in mediating asthma (Hasko et al., 2008). In addition, A3 receptors have been
demonstrated to utilize PLD and RhoA in dictating cell functions. However, the
precise function of A3 receptor in T cells has not been established.
Based on these studies, we set out to determine the effect of adenosine in
modulating PLD signaling in T cells. We also tested if PLD signaling plays any
role in mediating the immune suppression of adenosine.
CONCLUSION
The heterogeneity of T cell subsets has led us to appreciate the functional
importance of CD4 T cells in fighting pathogens, inducing autoimmunity as well
as maintaining tolerance to self. It is widely accepted that the population balance
between the various subsets of CD4 T cells is central to maintaining immune
homeostasis. Hence, identification of factors controlling this population balance
like PLD signaling will provide novel therapeutic strategies for controlling variety
of diseases ranging from autoimmunity to tumors.
48
CHAPTER TWO
MATERIAL AND EXPERIMENTAL METHODS
Mice
All mouse work was done in accordance with the Animal Care and Use
Committee guidelines of Medical College of Georgia and Loyola University.
Animals were housed in pathogen-free conditions prior to manipulations.
C57BL/6 mice and RAG-1 knock out mice were obtained from Jackson
laboratory. CD4 CRE mice were obtained from Taconic. P25 TCR transgenic
mice was generously gifted by Dr. T. Saito (Japan) (Tamura et al., 2004).
D011.10 TCR transgenic mice were housed in pathogen free facility in Medical
College of Georgia (Augusta, Georgia, USA).
Generation of PLD2 -/- mice
PLD2fl/fl mice were generated by selecting the PLDneo ES cell clone
(Mayuko Takezaki). The floxed mouse PLD2 (PLD2fl/fl) mice line was bred with
FLP transgenic mice to delete the neo transgene. Then PLD2fl/fl (minus neo)
mice were bred with mice carrying CD4 cre transgene. Mice were routinely
screened by genotyping of the tail DNA using PCR. Primers used for genotyping
49
are listed in Table I. Genomic DNA was isolated from CD4 T cells and analyzed
by southern genomic blot for targeted recombination.
Southern Blot
Genomic DNA was isolated from CD4 T cells using standard procedures
(Blin and Stafford, 1976). Ten micrograms of genomic DNA was digested with
the restriction enzyme Bgl II, electrophoresed on a 0.7% agarose gel, transferred
to Hybond-N and UV cross-linked according to the manufacturer’s suggestion
(Amersham Pharmacia Biotech). Filters containing the immobilized DNA were
incubated with 1-5*106 cpm/ml of radio labeled probe. 25ng cDNA-probe was
labeled with 32P using the Prime It® II Random Primer Labeling Kit (Stratagene
#300385). The PLD2 targeting probe corresponds to a 340bp XhoI-EcoRI
fragment located immediately upstream of the short arm of the targeting
construct. Filters were washed at 65 °C in a solution containing 0.1X SSC and
0.1% SDS and analyzed by autoradiography.
Adoptive transfer
CFSE labeled (0.5uM) (donor) p25 CD4 T cells (2.5-5×106 ) were injected
intravenously into Ly5.1 (recipient) mice on day 0. Recipient mice were injected
with 2.5ug of p25 peptide intravenously on day 1. Recipient mice were given
intraperitoneal injections of vehicle (DMSO in PBS), AB-MECA (200ug /kg),
Ethanol (2.9g/kg body weight in 20% vol/vol) in 200 ul from day 0-6. Mice were
sacrificed on day 8 and spleen, mesenteric lymph nodes and all peripheral lymph
50
nodes (axillary, brachial, cervical, inguinal and popliteal) were harvested and
intracellular staining for Foxp3 expression was performed. Proliferation function
in flowjo software was used to determine number of cells in each cell division.
RAG1 -/- mice
CFSE (0.5uM) labeled CD4 T cells (1- 5x106) from wild type B6 mice were
intravenously transferred into recipient RAG1-/- mice. Mice were injected with
ethanol or PBS intraperitoneally as described previously for 5 days. Mice were
sacrificed on day 6 and splenocytes were analyzed for Foxp3 expression by flow
cytometry.
Cell isolation and culture
Splenic CD4 T cells were isolated using either positive or negative
selection kit from BD Biosciences or MACS Miltenyi Biotec as per manufacturers
protocol. Cell purity was confirmed to be 95% by BDFACS Canto. Cells were
cultured in vitro in RPMI 1640 medium supplemented with 10% v/v heat-
inactivated FBS, 2mM glutamine, 5×10-5 M 2-ME, and 100 U/mL penicillin and
100 µg/mL streptomycin (all were obtained from Thermo Scientific Hyclone).
Treg enrichment
61×10 CD4 T cells were pre-incubated with DMSO, AB-MECA (A3R agonist,
SIGMA), 0.5 % ethanol (SIGMA, 200 proof) and 2 % ethanol (2ml in 24 well
plate). After 16 hrs, we replaced 1.5 ml of culture supernatant with fresh medium
containing 0.2ug/ml of anti-CD3 (e-bioscience), γ-irradiated splenocytes (2500
rad) (2-5×106 cells/well) and different treatment constituents like DMSO. We
51
replaced 1 ml of medium for the next 72 hrs with medium containing anti-CD3,
2ng/ml of mouse recombinant IL-2 and respective treatment constituents. We
washed the cells on day 4 and cultured them with IL-2 (2ng/ml) for next 3 days.
On day 7, cells were harvested, washed and counted. Cells were then stained
with different fluorescent antibodies and analyzed by flow cytometry.
Activation markers
1×106 CD4 T cells were activated with anti-CD3 (0.2ug/ml) and APCs (T
cell depleted γ-irradiated splenocytes (2500 rad), (2-5×106 cells/well) in the
presence of DMSO, AB-MECA, varying concentrations of ethanol and C.difficile
culture supernatants. 24 hrs later cells were harvested and analyzed by flow
cytometry. In some experiments, CD4 T cells were further sorted into CD4+
CD25+ and CD4+ CD25- T cells using BDFACSAria.
CFSE labeling
Purified CD4 T cells were labeled with 2.5μM CFSE (Invitrogen) for 10 min
at 37°C in PBS. The reaction was quenched by the addition of medium
containing 10% FCS and then washed twice in PBS. CFSE labeled cells were
cultured for 7 days as mentioned above. In some experiments, cells were labeled
with 2.5uM PKH-26 (a red fluorescent cell labeling dye, SIGMA). Cells were
harvested on Day 5 after stimulation.
Cytokine assay
To analyze cytokine production by ELISA, CD4 T cells were stimulated
with plate bound anti-CD3 (2 ug/ml) and soluble CD28 (1 ug/ml) in the presence
52
of DMSO or AB-MECA. Supernatants were collected at 24, 48 and 72 hrs and
enzyme linked immunoassays were performed as described previously.
To detect cytokine production by intracellular staining, CD4 T cells were
stimulated with plate bound anti-CD3 (2ug/ml) and soluble CD28 (1ug/ml) for 48-
72 hrs. Cells were then rested for 48 hrs in the presence of IL-2. On day 5, cells
were washed and 1×106 were restimulated with PMA (50ng/ml) and Ionomycin
(1ug/ml) for 6 hrs in the presence of Golgistop (Monesin, 2uM). Cells were then
harvested and stained with fluorescent antibodies and analyzed by flow
cytometry.
Th1, Th2 and Th17 skewing conditions
For Th1 skewing conditions, CD4 T cells were stimulated as before and
cultured in media supplemented with mIL-12 (10ng/ml) and anti-IL-4 (10ug/ml).
After 48 hrs, medium was supplemented with additional IL-2.
For Th2 skewing conditions, CD4 T cells were stimulated as before and
cultured in media supplemented with mIL-4 (10ng/ml), anti-IL-12 (10ug/ml) and
anti-IFNγ(10ug/ml). After 48 hrs, medium was supplemented with additional IL-4.
Cells skewed to Th17 were supplemented with TGF-β (2ng/ml), mIL-6
(10ng/ml), anti-IL-4 (2ug/ml) and anti-IFNγ (2ug/ml). Th17 skewed cells were
harvested on day3 or 4 washed and stimulated with PMA and Ionomycin and
analyzed by flow cytometry. Th1 and Th2 skewed cells were harvested on day5
after stimulation and restimulated with PMA and ionomycin.
53
Induction of Treg cells
To test for induction of Treg cells, CD4+CD25- T cells were stimulated
with APCs (whole splenocytes) and anti-CD3 (0.2-0.4ug/ml). Medium was
supplemented with AB-MECA or DMSO. TGF-β (5ng/ml) was added to positive
control wells. IL-2 (2ng/ml) was added to all wells on day 1 and day 2. Cells were
harvested on Day 5 or 6 and analyzed for Foxp3 expression by flow cytometry.
Flow cytometry
Cell surface staining
Cells in culture were harvested and washed once with FACS buffer (5%
FCS and 0.1% azide in 1X PBS). 1x106
cells were stained with various antibodies
for 1hr at 4 degree and cells were washed three times with FACS buffer. Before
staining with antibodies, cells were incubated for 5-10 mins with 2.4G2(FcR
block). Purified, fluorochrome and biotin-coupled monoclonal antibodies specific
for CD4 (RMA 4–4, GK1.5), CD8 (53–6.7), CD25 (PC61, 7D4), CD3 (145-2C11)
and FoxP3 (FJK-16s) were purchased from eBiosciences (San Diego, CA). Thy
1.2, Ly 5.2 and Vβ11were purchased from Biolegend (San Diego, CA).
Fluorescent antibodies against IL-2, IL-4, IFN-γ was purchased from e-bioscience
and IL-17 was purchased from Biolegend.
Intracellular cytokine staining
0.5-1x106
cells were surface stained and then fixed for 15 mins with 4%
Paraformaldehyde (Sigma) at room temperature. Cells were diluted with FACS
54
buffer and kept at 4 degrees overnight. The following day, cells were washed and
incubated with permeabilization buffer (50mM Nacl, 5mM EDTA, 0.02% Azide,
0.5 % Triton-X pH7.5) for 15 mins followed by blocking (3% BSA in PBS). Cells
were then incubated with fluorescent antibodies for 45 mins on ice. Finally, cells
were washed three times in FACS buffer and analyzed by flow cytometry.
Intracellular Foxp3 staining
1x106
cells were surface stained with anti-CD4 and anti-CD25, fixed
overnight with Fix/Perm buffer (eBioscience). After 12-16 hrs, cells were then
washed twice with IX permeabilization buffer (eBioscience) and stained with anti-
Foxp3 antibody in IX FACS buffer at 4°C for 1hr. Cells were washed thrice with
IX FACS buffer and analyzed by flow cytometry.
All the data was acquired using FACSCanto or FACSCanto II (Becton
Dickinson) at the LUMC FACS Core Facility, and data was analyzed using
FlowJo analysis software (©Tree Star, Inc).
T cell proliferation assay
CD4 T cells (2x104 – 3x104) were stimulated with anti-CD3 (0.2ug/ml) and
(T cell depleted splenocytes, γ-irradiated, 2500 rads) APCs in 96 well plates
(200ul). Depending on the experiment, medium was supplemented with DMSO,
AB-MECA, and 0.5%-2% ethanol and toxin or no-toxin supernatants from
C.difficile culture. 72 hrs after stimulation cells were assayed for proliferation
using CellTiter-Glo Luminescent cell viability assay (Promega). The kit uses
luciferase as the detection enzyme. Luciferase enzyme requires ATP to generate
55
light. Since metabolically active cells produce more ATP, the light signal detected
is proportional to the amount of ATP present that in turn correlates with the
number of viable cells. Luminescence is measured using plate reader (Turner
Biosystems) and analyzed using VERITAS software.
ELISA
96 well plates were coated with purified mIL-2, mIL-4 or mIFN-γ (capture
antibody, 1:500-1:1000) in 0.1M NaHCO3 buffer overnight at 4 deg. Next day,
wells were washed twice in ELISA wash buffer (0.05% Tween in 1xPBS) and
blocked with blocking buffer (3% BSA in PBS) at room temperature for 1 hr. Then
the wells were washed again and incubated with sample supernatants (serially
diluted in 1:3) overnight at 4 deg. The following day wells were washed and
incubated with biotin-conjugated antibodies (mIL-2, mIL-4 or mIFN-γ) for 1-2hrs.
Further, streptavidin-HRP (1:1000) was added and incubated for 30 mins at room
temperature. 100ul of 3,3', 5,5’-Tetramethylbenzidine (TMB) liquid substrate
(Sigma, St. Louis, MO) was added to each well after washing the plates five
times with wash buffer. Upon color development, the reaction was stopped by
adding 50ul of stop buffer (4 water: 1 HCl: 1 H2SO4) to the wells. The plates were
then read at 450 nm using plate reader (Biotek, El x 800) and the data was
analyzed using KC junior software.
56
Phospholipase D Assay
Lymphocytes were harvested from P25 TCR transgenic mice and
incubated overnight with (1-10ug/ml) P25 peptide. The following day cells were
harvested, washed with RPMI three times to remove any residual antigen
peptide. CD4 T cells were sorted and kept at room temperature until use. Cells
were then suspended in 10% RPMI containing 10mM HEPES (1-5x106/500ul)
and pretreated with DMSO or AB-MECA (50uM) for 30 mins in 37 deg water
bath. Following pretreatment, CD4 T cells were stimulated with soluble biotin
conjugated anti-CD3 and avidin for different time points (15-30 mins). Cells were
centrifuged and resuspended in RIPA lysis buffer (10mM phosphate buffer pH
7.2,150mM NaCl, 1% Triton-X, 0.5% sodium deoxycholate, 0.1% SDS)
containing Dnase. Cell lysates were assayed using the commercially available
Amplex Red PLD assay kit (Invitrogen (Molecular Probes)). In this assay, PLD
activity is monitored indirectly by using 10-acetyl-3, 7-dihydrophenoxasine, called
the Amplex Red reagent. PLD cleaves the L-α-phosphatidylcholine (PC) substrate
to yield choline and phosphatidic acid. Choline is oxidized by choline oxidase
(provided in the kit) (choline oxidase from an Alcaligenes sp.) to betaine and
H2O2. Finally, H2O2 in the presence of horseradish peroxidase reacts with the
Amplex Red reagent to generate the highly fluorescent product resorufin
(excitation and emission maxima, ~563 and 587 nm, respectively), an H2O2
fluorogenic sonde. As per manufacturers manual, this kit is specific for
membrane PLD enzymes, with optimal activity at nearly neutral pH (pH 8).
Purified PLD from Streptomyces chromofuscus and 10 μM H2O2 served as
57
positive controls. The PLD assay kit can detect PLD levels as low as 10 mU/ml.
One unit of PLD is defined as the amount of enzyme that liberates 1.0 μmol of
choline from PC per minute at pH 8.0 at 30°C. Cell lysates were incubated with
the reagents provided in the kit for 1hr at 37 deg and the fluorescence intensity
was read using fluorometer (BMG Labtech).
cAMP Assay
CD4 T cells from P25 transgenic mice were sorted and stimulated as previously
described in PLD assay. In the case of cAMP assay, CD4 T cells were stimulated
for 5 mins. Further, to assess cytosolic cAMP concentrations, T cells were
washed three times in ice-cold PBS, lysed in 0.1 N HCl (107/ml) for 30 mins.
Supernatants were assayed using the acetylated version of cAMP-specific ELISA
kit (Correlate EIA Direct Cyclic AMP Enzyme Immunoassay kit; Assay Design).
Western Blots
In general, cell pellets were suspended in 1xSDS sample buffer (0.5-1x106
cells in 25 ul) and boiled for 5-7 mins with intermediate vortexing. The proteins
were then separated on 8% polyacrylamide gels. Proteins were then transferred
to nitrocellulose membrane (Millipore) overnight in transfer buffer. The following
day membrane was blocked with 5% milk in TBST for 1 hr. Blots were then
washed three times in 1X TBST and incubated with the primary antibody
overnight at 4 deg. Next day, blots were washed and incubated with secondary
antibody for 1 hr at room temperature. ECL substrate (GE healthcare) was
58
added to the blot for 1 min before developing.
To determine adenosine A3 receptor expression, CD4+CD25+ and
CD4+CD25- T cells were sorted using MACS column. Cells were stimulated with
plate bound anti-CD3 (2ug/ml) and anti-CD28 (2ug/ml) for 72 hrs. Both
unstimulated and stimulated cells were harvested, washed in 1xPBS and
pelleted. Cells pellets were processed as described above. Adenosine A3
receptor antibody (Santa Cruz Biotechnology, 1:500) was diluted in antibody
dilution buffer (0.2% BSA, 0.1% azide in 1X TBST). Anti-rabbit HRP (Cell
Signaling, 1:5000) was used as secondary antibody. The membrane was
stripped with buffer containing 2-ME and probed with β-actin (Sigma) antibody.
For phospho PKA analysis, splenocytes from P25 TCR transgenic mice
were stimulated as described in PLD assay. Sorted CD4 T cells were incubated
with AB-MECA or DMSO for 30 mins before stimulation. T cells were stimulated
with biotin anti-CD3 (2C11, 10ug/ml) for 1 min followed by addition of 2.5ug/ml of
avidin for 5 mins at 37 deg. Cells were then pelleted and processed as described
above. Phospho-PKA substrate antibody (Cell Signaling, 1:1000) was diluted in
antibody dilution buffer. Anti-rabbit HRP (1:5000) was used as secondary
antibody.
Generation of PLD YFP fusion constructs
The plasmid encoding human PLD1 and mouse PLD2 were kindly provided by
Dr. Michael Frohman. DNA encoding full length PLD1 and PLD2 were sub-
cloned into pMEYFPzeo-C1 vector by Dr. Nagendra Singh. Deletion mutants of
59
PLD1 and PLD2 in pMEYFPzeo-C1 were constructed using convenient
restriction sites or polymerase chain reaction-based strategies and were
sequenced at all junctions to ensure that the reading frame was maintained.
Plasmids were sequenced to confirm the intended mutation. The mutant
constructs of both PLD1 and PLD2 were confirmed to be expressed at similar
levels and at the expected sizes (Fig 5 and 6). Primers used for the generation of
the constructs are listed in Table 1.
Confocal microscopy
Jurkat T antigen cells were transfected with the PLD YFP fusion constructs by
electroporation. Live cells were isolated (16-18 hrs after transfection,) using
lymphocyte separation medium (Mediatech, Inc). Approximately 105 cells in 50μl
medium were spread on 0.1% lysine coated glass slides. The cells were left to
adhere to the glass slide for 5 mins and the excess medium was drained. Cells
were fixed with 4% Paraformaldehyde for 10-20 mins and washed with 1x PBS
for three times. For nuclear staining, DAPI (Molecular probes) or Propidium
iodide was added to cells for 5 mins and washed with 1x PBS three times. One
drop of prolong antifade (Molecular probes) was added on top of the cells and
mounted with cover slip. Slides were left overnight at room temperature in the
dark and analyzed using Zeiss® LSM-510 laser scanning microscope at the
LUMC and MCG core imaging facility. LSM image examiner software was used
for image acquisition and analysis.
60
kDa
A) B)
Fig 5. Western blot analysis of PLD1 deletion mutant constructs. Full length
and deletion mutant constructs of hPLD1b were transfected into Jurkat T antigen
cells by electroporation. The following day live cells were isolated and lysed in
1xSDS sample buffer. A) Proteins were separated on 8% polyacrylamide gel and
probed with anti-GFP antibody. B) Proteins were separated on 12%
polyacrylamide gel and probed with anti-GFP antibody. Protein markers sizes
(kDa) are indicated on the left side of the gel. Protein of expected size was
obtained for the different constructs. Vector only: 30 kDa, Full length PLD1: 150
kDa, loop deleted PLD1: 130 kDa, PH+PX+C: 75 kDa, PH + PX only: 62 kDa, N-
terminal deletion: 100 kDa, C-terminal only: 40 kDa.
61
kDa
Fig 6. Western blot analysis of PLD2 deletion mutant constructs. Full length
and deletion mutant constructs of mPLD2 were transfected into Jurkat T antigen
cells by electroporation. The following day live cells were isolated and lysed in 1x
SDS sample buffer. Proteins were separated on 8% polyacrylamide gel and
probed with anti-GFP antibody. Protein markers sizes (kDa) are indicated on the
left side of the gel. Protein of expected size was obtained for the different
constructs. Full length PLD2: 125 kDa, PH+PX+C: 75 kDa, C-terminal only: 40
kDa.
62
In contrast to the diffuse cytoplasm and nuclear localization of YFP-vector
alone, PLD1YFP and PLD2YFP have peri-nuclear and plasma membrane
localization respectively (Fig 7).
63
Vector PLD1 PLD2
Fig 7. Confocal microscopic analysis of YFP fusion constructs. YFP fusion
(green) construct of vector alone, full length PLD1 and PLD2 were transfected in
Jurkat T antigen cell line. The sub cellular localization of these constructs was
determined using confocal microscopy.
64
G TGG GCT CAC CAT GAG - 3'6 5'- TAT CAC ATG GAC GTA AGC GGC GT -3'
7 hPLD1b (PX+PH+C) 5'- CTC AAA GAT CAT CGA TTT GGG TCA GTT GTC CTT GGC TAT CTT GAT GAC - 3'
Table 1. PCR primers
T TA
Number Primer Name Sequence
1 hPLD1b ( PX+PH only) 5'- GGC CGC GAT ATC TCA CTA A - 3'2 5'- TA
T TT
G TGA GAT ATC GC- 3'
3 hPLD1b ( loop deletion) 5'- TAA ACT ACG GAT GGA CCC GGT AGT GAC CCG CTT CAC ACT - 3'
4 5'- AGT GTG AAG CGG GTC ACT ACC GGG TCC ATC CGT AGT TTA - 3'
5 5'- TA
8 5'- TTC AAA ATT AAG GTG GGG AAG - 3'
9 hPLD1b (C terminal only) 5'- GGA TAT TCA TGC GGC CGC TCA TTA AGT CCA AAC CTC CAT GGG - 3'
10 5'- TTT AGG CTC GAG CTG TTG TCC TTG GCT ATC TTG AT - 3'
11 mPLD2 (PX+PH+C) 5'- CTA CAG CTA CAT CAG CAT GAC AGC GTG ATT CTT GGG GCA AAT ACC TGG - 3'
12 5'- TCC CTG ATT CTC AAA TGC AGC AGC -3'13 5'- TTC ACC TTC TGT GGC CGA GAC C - 3'14 5'- CCA GGT ATT TGC CCC AAG AAT CAC
GCT GTC ATG CTG ATG TAG CTG TAG - 3'
15 mPLD2 (C terminal only) 5'- AAG GAC TCC TTC CTG CTG TAC ATG - 3'16 5'- TTC AGT CTC GAG CTG TGA TTC TTG
GGG CAA ATA CC- 3'
PLD2 (- / -) mice genotyping primers17 P274 5'- GCC ATC TCA TTT GTT CAG CTT T - 3'18 P275 5'- GCT GTC ATG CTG ATG TAG CTG T - 3'
19 CD4 CRE FWD 5'- CGA TGC AAC GAG TGA TGA GG - 3'20 CD4 CRE REV 5'- GCA TTG CTG TCA CTT GGT CGT - 3'
21 FLP FWD 5'- CAC TGA TAT TGT AAG TAG TTT GC- 3'22 FLP REV 5'- CTA GTG CGA AGT AGT GAT CAG G - 3'
CHAPTER THREE
EXPERIMENTAL RESULTS
REGULATION OF PHOSPHOLIPASE D SIGNALING BY EXOGENOUS
FACTORS
Antigen stimulation of lymphocytes results in increased PLD activity.
Primary alcohol is a well-known inhibitor of PLD signaling. Previous studies have
documented the inhibition of T cell activation in the presence of primary alcohols
in vitro. Singh et al (Singh et al., 2006) analyzed the effect of inhibiting PLD
signaling in different subsets of CD4 T cells using 0.3% 1-butanol. Inhibition of
PLD signaling selectively blocked the proliferation of CD4+CD25- (effector) T
cells and led to the enrichment of Foxp3+ regulatory T cells. This study
highlighted the differential requirement for PLD signaling among effector versus
regulatory T cell subsets.
We then sought to determine the role of PLD signaling in dictating the
immune response of the host. We hypothesized that in vivo suppression of PLD
signaling may promote immune suppression through dominance of Treg cells
under physiological/pathological conditions. Conversely, enhancement of PLD
signaling under certain conditions might promote dominance of effector T cells
65
66
and thus promote immune reactivity. For my studies, I focused on identifying
various exogenous and endogenous factors that alter the immune status of the
host through modulating PLD signaling.
Ethanol and CD4 T cell population dynamics
Based on the effect of 1-butanol, we predicted that another 1-alcohol,
ethanol would also inhibit PLD signaling. Ethanol is widely consumed for
recreational purposes and is considered as an immunosuppressive agent (Cook,
1998; Nelson and Kolls, 2002; Zhang and Meadows, 2005). Excessive alcohol
intake has been associated with increased incidence of infection, cancer and
autoimmunity (Song et al., 2002). Previous studies in mice indicate that alcohol
administration for short duration causes reduced cell numbers of immune cells
like T cell, B cell and NK cells and concomitant reduction in the cellularity of
spleen and thymus (Chadha et al., 1991). However, the effect of alcohol on CD4
T cells in specific and the mode of action were not delineated.
To determine if ethanol can enrich for Treg cells, we treated murine CD4 T
cells with varying concentrations of ethanol in the presence of anti-CD3
stimulation in vitro for 4 days. After 72 hrs of stimulation, cells were washed and
cultured for 3 days in the presence of IL-2. Cells were harvested and stained for
regulatory T cell markers, Foxp3 and CTLA4. When T cells were stimulated by
anti-CD3 antibody in the presence of low concentrations of alcohol (0.5%), no
enrichment of Foxp3+ Treg cells was observed and the frequency of Foxp3+
67
0.5% Ethanol Medium
1% Ethanol 2% Ethanol
0.86
4.91 16.56
Foxp3
CTL
A4
0.78
Figure 8. Effect of ethanol on CD4 T cells in vitro. Total CD4+ T cells were
cultured with anti-CD3 plus antigen presenting cells in medium containing
increasing concentrations (0.5% - 2%) ethanol for 3 days. After 3 days, cells
were placed in medium containing IL-2 (20ng/ml) for 4 days. Seven days after
the start of culture, cells were harvested and analyzed by flow cytometry for
Foxp3 and CTLA4 expression. Representative data from 3 independent
experiments is shown.
68
cells was similar to medium-treated samples. When higher doses of ethanol
were used (1.0%, 2.0%), however, we observed a clear dose dependent
increase in Treg frequency (Fig 8) among CD4 T cells and observed 4.9 and
16.5% of CD4 T cells becoming Foxp3+, respectively. Similar to 1-butanol, CD4
T cells expanded in the presence of 2% ethanol contain higher percentages of
Foxp3+ cells.
The experiment shown above used stimulation of T cells by anti-CD3
antibodies. To determine if ethanol can enrich for antigen specific Treg cells, we
next tested the effect of ethanol on antigen-induced T cell proliferation using CD4
T cells from P25 TCR transgenic mice. The P25 mouse carries a transgene
encoding the TCR specific for peptide-25 of Mycobaterium tuberculosis (Tamura
et al., 2004). T cells were stimulated with the antigen peptide in the presence of
irradiated antigen presenting cells for 3 days followed by culture in the presence
of IL-2 for 4 days. Similar to anti-CD3 stimulated cultures, the frequency of
Foxp3+ cells in 2% ethanol treated cultures were 22% as against 0.6% in both
medium and 0.5% ethanol treated samples (Fig 9).
The increase in percentage of Foxp3+ cells could be due to increased
proliferation of Foxp3+ cells in 2% ethanol treated cultures or due to decreased
proliferation of Foxp3- T cells. To test for these possibilities, we labeled CD4 T
cells with CFSE and measured the dilution of CFSE to monitor proliferation.
Compared to 0.5% ethanol, very few Foxp3- T cells proliferated in 2% ethanol
treated cultures as seen from the CFSE dilution plots (Fig 10).
69
Medium 0.5 % ethanol
2% ethanol
Foxp
3
CD25
Figure 9. Effect of ethanol on CD4 T cells in the presence of antigenic
stimulation in vitro. Total CD4+ T cells from P25 TCR transgenic mice were
cultured with P25 peptide (0.1ug/ml) plus antigen presenting cells in medium
containing different percentages of ethanol for 3 days. After 3 days, cells were
placed in medium containing IL-2 (20ng/ml) for 4 days. Seven days after the start
of culture, cells were harvested and analyzed by flow cytometry for Foxp3 and
CD25 expression. Representative data from 2 independent experiments is
shown.
70
Tota
l cel
l num
bers
Figure 10. Proliferation kinetics of CFSE labeled CD4 T cells in the
presence of ethanol. Total CD4+ T cells were labeled with CFSE (2.5ug/ml) and
cultured with anti-CD3 (0.2ug/ml) and APCs in medium containing 0.5% ethanol
(solid line) or 2% ethanol (dotted line) for 3 days. Cells were placed in medium
containing IL-2 (20ng/ml) for next 4 days. On day 7 after stimulation, cells were
harvested and analyzed by flow cytometry for Foxp3 and CFSE expression. A)
Line graph depicting number of Foxp3- T cells in different generations B) Line
graph depicting number of Foxp3+ T cells in different generations.
0
0
0
0
0
5000
0
0 1 2 3 4 5 6 7
100
200
300
400
6000.5 % ethanol2 % ethanol
Tota
l cel
l num
bers
0
0.05
0.1
0.15
2
0.25
3
0.35
0 1 2 3 4 5 6 7 8
0.
0.0.5 % ethanol2 % ethanol
(106) A)
B)
Generations
71
As a result, the total Foxp3- T cell numbers recovered from 0.5% ethanol treated
cultures were 8 times more than that recovered from 2% ethanol cultures. In
contrast, Foxp3+ cells from samples treated with 2.0% ethanol showed no
difference in CFSE levels between 0.5% and 2% ethanol treated samples.
Together, the data demonstrate that ethanol causes increased frequency of
Foxp3+ cells by decreasing the proliferation of Foxp3- T cells.
Epidemiological studies showed that alcohol abusers are predisposed to
more frequent and more severe infections (Cook, 1998). In particular, increased
incidence of infections and enhanced severity of disease such as pneumonia and
tuberculosis were associated with chronic consumption of alcohol (Cortese et al.,
1992; Esposito, 1984; Fernandez-Sola et al., 1995; Friedman et al., 1987; Moss
et al., 1996; Ruiz et al., 1999; Winterbauer et al., 1969). The incidence of chronic
Hepatitis C Virus (HCV) infection is also increased in alcohol abusers (Degos,
1999; Harris et al., 2001; Khan and Yatsuhashi, 2000; Lima et al., 2000; Schiff,
1999). Also, studies on rodents show that animals are more vulnerable to
infection after chronic or acute exposure to alcohol. These observations can be
interpreted based on our in vitro studies in the following manner: Consistent
intake of alcohol might lead to selective elimination of effector T cells and
consequent enrichment of regulatory T cells. This in turn might increase the
susceptibility of the host to various infections. Also, antigenic exposure in the
presence of alcohol might inhibit the proliferation of antigen specific effector T
cells thus compromising the overall health of the host.
72
We tested for these possibilities in vivo in mice using two different
experimental set-ups. First, the effect of ethanol on CD4 T cell subsets in mice in
the absence of antigen was determined. Wild type C57BL/6 mice were injected
with either PBS or 20% ethanol intraperitoneally (i.p) for 7 days. Mice were then
sacrificed and their spleen and mesenteric lymph nodes were harvested and
stained for regulatory T cell markers. As expected, spleen of mice treated with
ethanol contained 23.56% of Foxp3+ cells compared to 17.5% in PBS treated
mice (Fig 11a). This increase in frequency of Foxp3+ cells was due to significant
decrease in the total Foxp3- CD4 T cell numbers; no significant change in
Foxp3+ T cell numbers was observed (Fig 11b). These data confirmed our
prediction that ethanol selectively eliminates Foxp3- T cells even in the absence
of antigenic proliferation.
Secondly, we determined if ethanol inhibits antigen-induced effector T cell
proliferation while allowing Treg cells to proliferate in vivo, as we observed in
vitro. To test the effect of ethanol in vivo, we used the protocol that has been
previously described by others. Briefly, mice were injected with 2.9g/kg body
weight ethanol in 20% vol/vol saline intraperitoneally (i.p) (Meadows et al., 1989;
Obradovic and Meadows, 2002; Song et al., 2002). This dose of ethanol injection
leads to blood ethanol level of 300mg/dl in 30 minutes. We adoptively transferred
CFSE labeled CD4 T cells from P25 TCR transgenic mice into C57.BL/6 CD45.1
recipient mice intravenously. These recipient mice express CD45.1 isoform,
which is distinguishable from the CD45.2 isoform expressed by the donor mice.
73
EthanolPBS A)
CTL
A4
Foxp3
Figure 11. Flow cytometry analysis and quantification of cell numbers of
CD4 T cells in mice injected with ethanol. Wild type mice were injected
intraperitoneally with either PBS or 20% ethanol for 7 days. On day 7, mice were
sacrificed and their spleen cells were stained for Foxp3, CD4 and CTLA4. A)
Representative FACS plots of spleen CD4 T cells from PBS and ethanol treated
mice. B) Bar graphs of total Foxp3- T cell numbers in spleen of PBS (white bars)
and ethanol (black bars) treated mice. C) Bar graphs total Foxp3+ T cell numbers
in spleen of PBS (white bars) and ethanol (black bars) treated mice.
0
5
10
15
20
25
30
1
PBSEtoH
B) C)
0
1
2
3
4
5
6
1
(103) (103)
74
CFSE
Tota
l cel
l num
bers
To
tal c
ell n
umbe
rs
PBSNo antigen Ethanol Fo
xp3
(103)
B)
C)
A)
0
1
2
3
4
5
6
7
0 1 2 3 4 5 6 7
GENERATIONS
CONTROLETHANOL
0
50
100
150
200
250
300
0 1 2 3 4 5 6 7
GENERATIONS
CTRLETHANOL
75
Figure 12. Effect of ethanol on the proliferation kinetics of Foxp3 positive
and Foxp3 negative CD4 T cells in vivo in the presence of antigen. CFSE
labeled CD4 T cells from P25 TCR transgenic (Ly5.2) mice were intravenously
transferred to Ly5.1 recipient mice. 24 hrs later, the recipients were challenged
with 2.5ug of P25 peptide along with either PBS (control) or 20% ethanol (i.p) for
a period of 7 days. On day 8, mice were sacrificed and all their peripheral lymph
nodes (axial, cervical, inguinal, popliteal) were isolated and pooled for analysis
by flow cytometry. A) Representative FACS plots showing CFSE dilution in
lymphocytes of control and ethanol treated mice. B) Line graphs depicting the
number of foxp3- T cells in each generation of control (dotted lines) and ethanol
treated (solid lines) mice. C) Line graphs depicting the number of foxp3+ T cells
in each generation of control (dotted lines) and ethanol treated (solid lines) mice.
Data is representative of 2 independent experiments.
76
One day after injection of T cells the recipient mice were injected with the antigen
peptide. Immediately after injection of peptide, mice received ethanol injection as
described above. Mice were administered ethanol daily for 7 days. On day 8,
mice were euthanized and spleen, mesentric and peripheral lymph nodes
(inguinal, brachial, axial, popliteal, cervical) were harvested. The state of
proliferation of adoptively transferred T cells was determined by analyzing the
CFSE level of CD45.2+ T cells (Fig. 12a). T cells of mice that received no antigen
showed no proliferation after 7 days while T cells from mice that received antigen
peptide in PBS showed significant level of proliferation in both Foxp3+ and
Foxp3- populations. The frequency of Foxp3+ T cells in PBS treated mice was
3.5%. Mice injected with ethanol showed a marked reduction in proliferation of
Foxp3- T cells and the frequency of Foxp3+ T cells was 9.75%. The majority of
Foxp3- T cells in control mice were in between generation 3 to generation 6 (i.e.
most of these cells underwent 3 cell divisions)(Fig 12b). However, there was no
clear peak in the cell division of Foxp3- T cells of ethanol treated mice suggesting
that majority of cells did not proliferate effectively. In stark contrast, the level of
cell division of Foxp3+ cells was comparable between ethanol treated and PBS
treated mice (Fig 12c). As a consequence, the total cell numbers that were
obtained from ethanol treated and untreated mice were comparable for Foxp3+ T
cells but the cell numbers was significantly lower in ethanol treated animals for
Foxp3- cells. Together, the data demonstrate that ethanol does block antigen
induced Foxp3- effector T cell proliferation while allowing Treg cells to expand in
vivo.
77
PBS ETHANOL ETHANOL
CFSE
FOXP
3
A)
B)
0
5 0
1 0 0
1 5 0
2 0 0
2 5 0
T O T A L C D 4
CEL
L C
OU
NT
P B SE T H A N O L # 1E T H A N O L # 2
C) D)
(103)
(103
0
50
100
150
200
250
1
CEL
L C
OU
NT
0
5
10
15
20
25
30
FOXP3 POS
) (103
PBS)
ETHANOL #1ETHANOL #2
78
Figure 13. Effect of ethanol on homeostatic proliferation of CD4 T cells.
CD4 T cells from wild type mice were intravenously transferred into RAG1 KO
mice along with intraperitoneal injections of either PBS or 20% ethanol for 5
days. On day 6, mice were sacrificed and their spleen cells were stained for
Foxp3 and CD4 T cells. A) Representative FACS plots of PBS and two ethanol
treated mice showing CFSE dilution in spleen CD4 T cells. B) Bar graphs of total
cell numbers of CD4 T cells in the spleen. C) Bar graphs depicting the number of
foxp3- T cells in each of control (white bars) and ethanol treated mice (filled
bars). D) Bar graphs depicting the number of foxp3+ T cells in each of control
(white bars) and ethanol treated mice (filled bars).
79
Zhang et al reported that chronic alcohol consumption (2 weeks-6 months)
results in T cell lymphopenia, which in turn induces homeostatic proliferation
(Zhang and Meadows, 2005). Since we also observed similar reduction in cell
numbers in mice injected with ethanol for 1 week (Fig 11b), we investigated
whether ethanol affects homeostatic proliferation. We tested the primary effect of
ethanol on the proliferation of CD4 T cells under well-established homeostatic
condition like RAG1 KO mice. We adoptively transferred CFSE labeled CD4 T
cells from wild type mice into RAG-1 knock out mice intravenously followed by
ethanol injection for 5 days. Under lymphopenic conditions, T cells are stimulated
by self-peptide and self-MHC (Zhang and Meadows, 2005). We monitored
proliferation of T cells based on dilution of CFSE. As seen in (Fig 13b), the total
CD4 T cell counts in ethanol injected mice were 5 times lower than PBS injected
mice. Unlike antigen-induced proliferation of CD4 T cells, we did not observe
selective decrease in Foxp3- T cells alone. Both Foxp3- and Foxp3+ T cells
counts were reduced by injection of ethanol (Fig 13 c). Thus, the data show that
in acute phase of homeostatic expansion, ethanol inhibits proliferation of both
Foxp3- and Foxp3+ CD4 T cells. Further experiments could be aimed at looking
for specific markers of homeostatic proliferation such as expression of CD44 and
lack of CD69.
80
Effect of alcohol ingestion on the balance between Foxp3+ and Foxp3- CD4 T
cells
The data indicate that continuous and high dose exposure of T cells to alcohol
may induce a relative increase in the frequency of Foxp3+ T cells. Despite the
minute presence of endogenous ethanol, alcohol consumption by humans is the
major source of ethanol in the human body (Antoshechkin, 2001). To study the
effects of in vivo ethanol exposure on CD4 T cells, we fed mice with liquid diet
containing alcohol. DO11.10 TCR (T cell receptor) transgenic mice (receptor
specific for ovalbumin (OVA) plus I-Ad) were fed an alcohol-containing nutrient-
supplemented liquid diet (Bio-Serv, NJ) (ethanol concentration was gradually
increased from 1% to 6.3% w/v every 2 days) or calorie matched control diet for
10 days (sex-matched 12-week-old male mice, 6 mice per group). Mice were
euthanized on day 10, and mucosal CD4 T cells were analyzed for expression of
Foxp3 by flow cytometry. CD4 T cells from the mesenteric lymph nodes of
alcohol-fed mice showed a moderate but clear increase in Foxp3+ CTLA4+ T
cells compared to the control group (Fig 14a). Average frequency of Foxp3+
CD4 T cells increased significantly compared to control diet fed animals (Fig
14b). These results show that continuous presence of ethanol in the diet causes
relative increase of Foxp3+ T cell in mucosal associated lymphoid organs and
suggest that continuous alcohol consumption by humans might lead to selective
enrichment of Treg cells and immune suppression leading to heightened
susceptibility to opportunistic infections.
81
A)
B)
Figure 14. Effect of alcohol containing diet on mice CD4 T cells. Mice were
fed on liquid diet containing water or varying concentration of ethanol for 10 days.
Mice were sacrificed on day 10 and their mesenteric lymph node was stained for
Foxp3 and CTLA4. A) Representative FACS plots of mesenteric lymph node of
two control and two alcohol fed mice. B) Data from 2 different experiments were
pooled and the percentage of Foxp3 positive cells in control versus alcohol fed
mice is shown as a graph.
82
Clostridium difficile toxin: Hijacking the immune system through PLD
Clostridium difficile (C.diff) is a spore forming, anaerobic, gram-positive
bacterium (Genth et al., 2008). Its role in the pathogenesis of
pseudomembranous colitis is well established. Recently, it has emerged as the
leading cause of nosocomial diarrhea in patients (Genth et al., 2008). Bacterial
pathogens interact with the mammalian cells through the production of protein
toxins (Fiorentini et al., 2003). These toxins serve as virulence factors and aid in
establishing their niche in the host. The major virulence factors produced by
C.difficile are Toxin A and Toxin B. Following cell entry, these toxins mono-
glucosylate and thereby inactivate lower molecular mass GTP binding proteins of
the Rho sub family (Genth et al., 2008). As mentioned previously, PLD is one of
the downstream effector molecules of Rho. As a consequence, C.difficile toxins
are considered inhibitors of PLD signaling.
Thus, we hypothesized that C.difficile might evade the host T cell effector
response by inhibiting PLD signaling. If these toxins inhibit PLD signaling in T
cells as well, then we expect to see inhibition of effector T cell proliferation in the
presence of these toxins. To test the effect of C.difficile toxins on T cell
proliferation, PKH-26 (analog of CFSE) labeled CD4 T cells were stimulated with
anti-CD3 in the presence of varying amounts of supernatants from toxigenic and
non-toxigenic strains of C.difficile (C.difficile supernatants were kindly provided
by Michelle Merrigan). As seen in (Fig 15a,b), following TCR stimulation 50% of
both Foxp3+ and Foxp3- T cells had undergone one cell division.
83
A)
B)
0 10 2 10 3 104 105
PE-A 0 20 40 60 80
100 % of Max
US / S
8.37 / 50.2
0 102 103 104 105
PE-A
0
20
40
60
80
100
% o
f Max
6.79 / 55
0 102 103 104 105
PE-A
0
20
40
60
80
100
NT / TO.15%
50 / 31.8
% o
f Max
0 102 103 104 105
PE-A
0
20
40
60
80
100
% o
f Max
56.6 / 47.7
Foxp3 negative
PKH
Foxp3 positive
PKH
84
C)
Toxin B concentration (
μg/ml)
Fig 15. Analysis of proliferation kinetics of Foxp3+ and Foxp3- T cells in the
presence of C.difficile toxin supernatants. CD4 T cells were labeled with 5μM
PKH-26 and stimulated with anti-CD3 (0.2ug/ml) and APCs. Varying amounts of
supernatants from toxigenic (Tcd) or non-toxigenic (non-Tcd) (0.05%-0.25%)
strains of C.difficile were added to the culture medium. 72 hrs after stimulation,
cell were harvested and stained with anti-Foxp3 antibody. A) Histograms
comparing the proliferation of Foxp3- T cells (top row) and Foxp3+ T cells
(bottom row) between medium (left side) and 0.15% of C.difficile supernatants
(right side) treated samples. Left panels: blue line (stimulated sample) and red
line (unstimulated sample). Right side: blue line (supernatant from toxigenic C.diff
strain) and red line (supernatant from non-toxigenic C.difficile strain) B) Graph
showing percentage of growth inhibition between samples containing increasing
amounts of C.difficile culture supernatants. C) Bar graph showing percentage of
growth inhibition in Foxp3+ and Foxp3- T cells in the presence of purified TcdB
(μg/ml).
85
In comparison, the Foxp3- T cell proliferation was decreased substantially
when the concentration of toxin containing supernatants was increased. Also, we
observed some inhibition in the proliferation of Foxp3+ T cells at higher
concentrations of the toxin supernatants (Fig 15b). Since we used supernatants
from C.difficile cultures as the source of toxin, it is possible that components
other than toxins might exhibit non-specific effects at high concentrations.
Further, to confirm that toxins specifically mediate the effect on T cell
proliferation, we performed this experiment with purified Toxin B. Purified toxin B
(1ug/ml) inhibited the proliferation of Foxp3- T cells by 60% while inhibition of
proliferation of Foxp3+ T cells was 10% (Fig 15c). These results suggest that
C.difficile toxin B (TcdB) through inhibiting PLD signaling blocks effector T cell
proliferation significantly.
Why does inhibiting PLD signaling selectively affect the proliferation of
Foxp3- (effector) T cells? In our studies with 1-butanol, we showed that PLD
signal inhibition abrogates activation induced expression of CD25 on Foxp3-
(effector) T cells. In contrast, Foxp3+ Treg cells express CD25 constitutively.
CD25 is IL-2 receptor alpha chain, up regulated on effector T cells following their
activation. IL-2 is an important survival/proliferation cytokine for activated T cells.
To test the effect of C.difficile toxin on the expression of CD25, CD4 T cells were
stimulated with anti-CD3 both in the presence and absence of toxin containing
supernatants. CD25 expression on these samples was determined 24 hrs after
stimulation. Stimulation of T cells resulted in significant up regulation of CD25
and CD69 in medium or non-toxigenic supernatant containing samples (Fig 16).
86
Figure 16. Flow cytometric analysis of activation markers expressed by
CD4 T cells following antigenic stimulation in the presence of C.difficile
supernatants. CD4 T cells were stimulated with anti-CD3 and APCs. Equal
amounts (0.15%) of culture supernatants from either toxigenic or non-toxigenic
C.difficile strains were added. 24 hrs after stimulation, cells were harvested,
stained for activation markers, CD25 and CD69 and analyzed by flow cytometry.
87
In contrast, the expression of CD25 was not increased in samples treated with
toxin containing supernatants. This result is in agreement with our previous
finding that inhibition of PLD signal blocks CD25 up regulation. Future
experiments can be performed to determine if C.difficile toxin B specifically
inhibits CD25 expression on Foxp3- T cells.
Based on our data on alcohol diet fed mice, we predicted that mice
exposed to C. difficile toxin/spores would have increased frequency of Treg cells.
To test this possibility, we analyzed the frequency of Foxp3+ T cells in mice
infected with C. difficile spores. Treatment with antibiotics disrupts the normal
commensal microbiota in the host intestine and is often associated with
increased incidence of Clostridium Difficile- associated diarrhoea (CDAD) (Giel et
al., 2010; Vollaard and Clasener, 1994). Based on these studies, mice were
treated with various antibiotics prior to introduction of C. difficile spores to induce
CDAD. Mice were treated with antibiotics and infected with C. difficile spores by
Pehga Mohseni. Compared to wild type mice, mesenteric lymph nodes of mice
colonized with C. difficile had higher percentages of Foxp3+ T cells (Fig 17 a). As
expected, this increase in Foxp3+ percentage was due to concomitant decrease
in Foxp3- T cell numbers (Fig 17b). However, a potential caveat of this
experiment is the absence of mice injected with spores derived from non-
toxigenic strain of C. difficile as a negative control. It is possible that the stringent
treatment with antibiotics might have contributed to the increased frequency of
Treg cells. Future experiments could be aimed at comparing mice colonized with
spores from both toxigenic and non-toxigenic strains.
88
Wild type C. Difficile spores # 1
Fig 17. Flow cytometric analysis of Foxp3+ T cell percentage in mice
infected with C. difficile spores. C57BL/6 mice were treated with broad-
spectrum antibiotics for 72 hrs. For the next 48 hrs, these mice were fed normal
drinking water and injected intraperitonealy with clindamycin. 24 hrs later, these
mice were given (50,000 CFU) C. difficile spores by oral gavage. 72 hrs later
these mice were sacrificed and their mesenteric lymph nodes were harvested
and stained using anti-CD4 and Foxp3 antibodies. A) FACS plots from wild type
0 1 2 1 3 1 4 1 5<APC
01 2
1 3
1 4
1 5
<P
0. 4.
12820 1 2 1 3 1 4 1 5
<APC-
01 2
1 3
1 4
1 5
<P
17. 31.
9.141.0 1 2 1 3 1 4 1 5
<APC
01 2
1 3
1 4
1 5
<P
19 26
350
CTL
A4
Foxp3
A)
B)
0
10
20
30
40
50
60
70
1
Tota
l cel
l num
bers
C) (10
WTC.diff # 1C.diff # 2
0
5
10
15
1
WTC.diff # 1C.diff # 2
3) (103)
C. Difficile spores # 2
89
mice (WT) and two different mice infected with C. difficile spores showing the
percentage of CD4 T cells expressing Foxp3. B) Bar graph of Foxp3- T cell
numbers in wild type and C. difficile spores-infected mice. C) Bar graph of
Foxp3+ T cell numbers in wild type and C. difficile spores-infected mice.
90
Nevertheless, based on evidence from other models of PLD signal inhibition, it is
tempting to speculate that exposure to C. difficile toxins might lead to preferential
enrichment of Treg cells in vivo.
REGULATION OF PHOSPHOLIPASE D SIGNALING BY NATURALLY
PRESENT ENDOGENOUS FACTORS
Adenosine (Ado) is an endogenous molecule that mediates a wide
spectrum of biologic effects by engaging 4 kinds of cell surface receptors: A1,
A2a, A2b and A3. Ado is found in very high concentrations under hypoxic
conditions like tissues surrounding inflammatory sites and tumors. Notably, these
Ado rich environments have an immune suppressive phenotype. For example,
increased frequency of Treg cells has been reported in most human solid tumors
(Beyer and Schultze, 2006). Several reports highlight the immune modulatory
effects of Ado acting through A2a receptor on T cells. However, there is little
experimental evidence for a role of A3 receptors mediating effects of Ado in T
cells. Interestingly, both A2a and A3 receptors have been previously reported to
modulate cell functions through regulating PLD activity. We hypothesized that
one mechanism by which adenosine can decrease immune responsiveness is
through inhibiting PLD signaling.
TCR stimulation has been shown to modulate the expression of adenosine
receptors in mice (Lappas et al., 2005) and humans (Gessi et al., 2004b). To
understand the role of adenosine A3 receptor signaling on T cell activation, we
investigated the kinetics of A3 receptor expression on CD4+CD25+ regulatory T
91
cells (Treg cells) and CD4+CD25- T cells (non-Treg cells) under resting and
activated conditions. We purified CD4+CD25- and CD4+CD25+ T cells from
C57.BL/6 mouse splenocytes and stimulated them with anti-CD3 and anti-CD28
antibodies. Total cell lysates from each group of T cells were separated by SDS-
PAGE and analyzed by Western blot for expression of the A3 receptor. Under
resting conditions, freshly isolated CD4+CD25- T cells did not express detectable
level of adenosine A3 receptor while CD4+CD25+ T cells expressed barely
detectable levels of the receptor. However, following stimulation both
CD4+CD25+ and CD4+CD25- T cells express comparable levels of adenosine A3
receptor (Fig 18).
We then examined the functional relevance of A3 receptor expression on
CD4 T cells using adenosine A3 receptor selective agonist, AB-MECA. We
stimulated splenic CD4 T cells with anti-CD3 antibody plus irradiated T-depleted
splenocytes (APCs) in the presence or absence of AB-MECA. We first examined
the effect of AB-MECA on the expression of early activation markers on T cells
namely CD69 and CD25 (IL-2 receptor α chain) following 24 hrs of stimulation.
Under these conditions, 65% of stimulated T cells expressed both CD25 and
CD69 whereas CD69 and CD25 alone were expressed by 5% and 13%
respectively (Fig 19a). In contrast, in cultures treated with AB-MECA, the
frequency of CD69+CD25+ T cells decreased to 40% and CD25 alone increased
to 21% and we observed little effect on CD25+CD69- T cells as the frequency
remained at 5%. Since naturally occurring regulatory T cells (nTreg cells)
constitutively express CD25 and non-Treg (CD4+CD425-) T cells express CD25
92
- + - + CD25 CD 25
Freshly isolated Invitro expanded
75 kD
50 kD
66 kD
Fig 18. Western blot analysis of adenosine A3 receptor expression on CD4
T cells. Treg cells (CD4+CD25+) and non-Treg (CD4+CD25-) T cells were
sorted from wild type mice by flow cytometry. Lysates of unstimulated versus
stimulated T cells were separated on 8% polyacrylamide gel, transferred onto
nitrocellulose membrane and blotted with antibody against A3 receptor
(66kDa)(Top blot). Molecular weights are indicated on the left side of the blot.
The membrane was stripped and probed with antibody against β-actin as loading
control (bottom row).
93
Unstimulated DMSO AB-MECA
Fig 19. Analysis of activation markers on T cells following antigenic
stimulation in the presence of A3 receptor signaling. CD4 T cells or
CD4+CD25- T cells were stimulated with anti-CD3 (0.2ug/ml) and T cell depleted
splenocytes (APCs) for 24 hrs in the presence of DMSO or AB-MECA. T cells
were stained with anti-CD25, anti-CD69 and analyzed by flow cytometry. A) Dot
plots of CD4 T cells expressing CD25 and CD69. B) Histograms of CD4+ CD25-
T cells expressing CD25 after TCR stimulation. Shaded peaks represent
unstimulated controls and solid black lines denote activation induced up -
regulation of CD25.
CD
25
CD 69
0 102 103 104 105
<PE- 0
20
40
60
80
100
% of Max
53 46
AB-MECA
0 102 103 104 105
<PE- 0
20
40
60
80
100
% of Max
30 70
DMSO
CD 25
A)
B)
94
only upon activation, we sorted Treg cells and non-Treg cells and determined the
expression of CD25. 70% of non-Treg cells in control cultures were CD25
positive in comparison to 45% in AB-MECA treated cultures (Fig 19 b). These
data collectively indicate that AB-MECA inhibits the expression of CD25 on non-
Treg cells and has no effect on Treg cells as they constitutively express CD25.
Next, we examined the effect of AB-MECA on CD4 T cell proliferation at
72 hrs post stimulation (Fig 20a). In the presence of AB-MECA, there was
approximately 3-fold reduction in the proliferation of CD4 T cells. A similar
inhibitory effect of AB-MECA was observed even in the presence of exogenous
IL-2 consistent with the reduced expression of CD25 (IL-2 receptor α chain) (Fig
20b). Also, we measured cytokine secretion by CD4 T cells both in the presence
and absence of AB-MECA. For this experiment, purified CD4 T cells were
stimulated with plate-bound anti-CD3 antibody plus soluble anti-CD28 antibody.
After 24~72 hours of stimulation, culture supernatant was collected and analyzed
by ELISA (Fig 20c). Stimulation of CD4 T cells under these conditions induced
substantial amount of IL-2, IFN-γ, and IL-4 and the level of cytokines in the
supernatant continued to increase for 72 hours. When AB-MECA was present,
the initial 24 hours of cytokine production was not significantly affected.
However, the level of cytokine production in AB-MECA treated samples showed
profound reduction compared to the control samples at later time points (48 and
72 hrs). Among the cytokines examined, IFNγ and IL-4 production were severely
reduced, potentially due to inhibition of proliferation of activated T cells.
95
(10
3)
0
50
100
150
200
250
CD3 + IL2
DMSOA3
p= 0.04
DMSO AB-MECA
A)
(103)
0
10
20
30
40
50
60
CD3
p = 0.02265
O.D
B)
IL- 2
0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
0 24 48 72 HRS
IFN- γ
0
0.1
0.2
0.3
0.4
0.5
0.6
0 24 48 72 HRS
DMSO AB-MECA
O.D
96
DMSO
AB-MECA IL- 4
0
0.1
0.2
0.3
0.4
0.5
0.6
0 24 48 72 HRS
Fig 20. Comparison of proliferation and cytokine secretion profile of DMSO
and AB-MECA treated CD4 T cells. A) CD4 T cells were stimulated anti-CD3
(0.2ug/ml) and APCs in the presence of DMSO or AB-MECA (50uM) for 72 hrs.
Cells were harvested and proliferation was measured using cell titer glo kit
(Molecular probes). (A) in the absence of IL-2 (B) in the presence of IL-2
(20ng/ml) C) CD4 T cells were stimulated with plate bound anti-CD3 (2ug/ml) and
anti-CD28 (1ug/ml). Supernatants were collected at different time points and
analyzed using ELISA.
97
Adenosine and CD4 T cell population dynamics
In addition to determining the effect of A3 receptor signaling on the effector
functions of CD4 T cells, we investigated the effect of A3 receptor signaling on
CD4 T population dynamics. Based on the previous observation of inhibition of
CD25 expression on non-Treg cells by AB-MECA, we predicted that culture of
CD4 T cells with exogenous IL-2 and AB-MECA would cause preferential
enrichment of Treg cells. To test this hypothesis, CD4 T cells were stimulated
with anti-CD3 in the presence of DMSO or AB-MECA for 3 days followed by
expansion in IL-2 containing medium for 3 days. The culture medium was
supplemented with fresh AB-MECA and anti-CD3 every 24 hrs for the first 3
days. As predicted, flow cytometry showed 22% of CD4 T cells were Foxp3 and
CTLA4+ in AB-MECA treated samples in contrast to <2% in DMSO treated
samples (Fig 21 a).
The increased percentage of Foxp3+ CD4 T cells in AB-MECA treated
cultures could result from either expansion of Foxp3+ T cells or from induction of
Foxp3 expression in CD4+CD25- T cells. To test for the possibility of increased
expansion of Foxp3+ cells, we tested the effect of AB-MECA on the proliferation
of CD4+CD25- and CD4+CD25+ T cells separately. AB-MECA substantially
reduced the proliferation of CD4+CD25- T cells (50% reduction) and had no
significant effect on the proliferation of CD4+CD25+ T cells (Fig 21b). This result
of inhibition of CD4+CD25- T cell proliferation was confirmed using CFSE
proliferation assay as well.
98
AB-MECA DMSO
22.01.61
FOXP3
C
TLA
4
p < 0.001
0
20
40
60
80
100
CD4+CD25- CD4+CD25+
Rel
ativ
e lig
ht u
nit
DMSO
A3
A)
B)
AB-MECA
Fig 21. Effect of adenosine A3 receptor signaling on CD4 T cell population
dynamics. A) Total CD4 T cells were cultured with anti-CD3 antibody plus APCs
in medium containing DMSO or adenosine A3 receptor specific agonist (AB-
MECA, 50uM) for 72 hrs. After 3 days, cells were placed in medium containing
IL-2 (20ng/ml) for 4 days and analyzed for Foxp3 and CTLA4 expression. B)
CD4+CD25- and CD4+ CD25+ T cells were sorted from mice splenocytes and
cultured with anti-CD3 and APCs along with DMSO or AB-MECA for 72 hrs.
Proliferation was assessed using cell titer glo kit (Molecular probes).
99
Relative increase in Foxp3+ T cells with AB-MECA could also be caused
by de novo induction of Foxp3+ cells from naïve T cells (Chen et al., 2003). To
address this possibility, CD4+CD25- T cells were stimulated with anti-CD3 in the
presence or absence of AB-MECA. TGF-beta has been shown previously to
induce Foxp3 expression in CD4+ CD25- T cells and thus served as positive
control for this experiment. However, similar treatment of naïve T cells with AB-
MECA did not lead to induction of Foxp3+ expression in CD4 T cells (Fig 22, top
row). Interestingly, co-culture of AB-MECA with TGF-β led to significant reduction
in the percentages of Foxp3+ CD4 T cells (8%) compared to 20% of TGF-β alone
treated cultures (Fig 22, bottom row). This result could mean that A3 receptor
signaling antagonizes TGF-β signaling in naïve T cells. Taken together, these
data rule out the possibility of Foxp3 induction by AB-MECA and rather strongly
suggest preferential enrichment of Foxp3+ T cells.
Next, we asked whether adenosine A3 receptor signaling could inhibit
effector T cell proliferation in vivo in mice. To address this question, CFSE
labeled transgenic mouse derived CD4 T cells were intravenously transferred
into congenic Ly5.1 mice and challenged in vivo with the cognate antigenic
peptide with or without AB-MECA. As the source of CD4 T cells, we used p25
TCR transgenic mouse T cells, specific to Mycobacterium Tuberculosis antigen
p25 peptide (Tamura et al., 2004). The antigen challenged mice also received
AB-MECA or vehicle control through intraperitoneal (i.p) injection daily for 1
week. Expression levels of Foxp3 and CFSE were measured on day 8 after
antigen administration.
100
Foxp3
0 102 103 104 105
<APC-A>
0
102
103
104
105
<PE-
A>
62.6 2.17
3.7631.40 102 103 104 105
<APC-A>
0
102
103
104
105
<PE-
A>
49.4 0.58
149.1
CTL
A4
DMSO AB-MECA
0 102 103 104 105
<APC-A>
0
102
103
104
105
<PE-
A>
43.7 8.64
2.1245.60 102 103 104 105
<APC-A>
0
102
103
104
105
<PE-
A>
42.7 21.6
4.431.4
Fig 22. Flow cytometric analysis of Foxp3 induction in CD4+CD25- T cells
following adenosine A3 receptor signaling. CD4+CD25- T cells were cultured
with anti-CD3 stimulation and APCs in medium containing DMSO or adenosine
A3 receptor agonist (AB-MECA) for 72 hrs. After day 3, cells were placed in
medium containing IL-2 (20ng/ml) for 4 days and analyzed for Foxp3 and CTLA4
expression (Top row). Exogenous TGF-β (5ng/ml) was added to the medium
(bottom row).
101
Intravenous injection of 2.5μg antigen peptide in the recipient mice caused
effective proliferation of CD4 T cells as seen from the progressive dilution of
CFSE in dividing cells (Fig 23a). As expected from in vitro data, CFSE labeled
CD4 T cells proliferated considerably less in AB-MECA treated mice compared
vehicle treated control mice. Also, we observed increased frequency of Foxp3+
CD4 T cells in AB-MECA treated mice. Further, we compared the total cell
numbers in each cell division of the Foxp3- and Foxp3+ T cell fraction (Fig 23b).
Consistent with the in vitro data, we found reduced cell numbers in Foxp3- T cell
fraction alone of AB-MECA treated mice. This result led us to suggest that A3
receptor (A3R) signaling selectively inhibits effector T cell proliferation in vivo as
well. Thus, under adenosine rich conditions (eg: excessive inflammation, hypoxia
induced cell death in solid tumors), A3R activation might inhibit effector T cell
proliferation with a concomitant increase in the frequency of Treg cells and
change the balance towards immune suppression.
Cross talk between Adenosine receptor and Phospholipase D signaling
Ado receptors, A2a and A3 have been reported to utilize PLD in mediating
cell functions (Thibault et al., 2000) (Mozzicato et al., 2004). In light of our
findings with A3 receptor signaling in CD4 T cells, we next determined the effect
of A3R signaling on PLD activity in CD4 T cells. TCR induced PLD activity was
measured in AB-MECA treated CD4 T cells using a commercially available PLD
assay kit (Molecular Probes). First, whole splenocytes from P25 TCR transgenic
mice were stimulated with the cognate P25 peptide overnight to induce the
102
CFSE
FOXP
3 No Antigen
Ag + DMSO Ag + AB-MECA
0
1000
2000
3000
4000
5000
6000
7000
0 1 2 3 4 5 6 7
GENERATIONS
TOTA
L C
ELL
NU
MB
ERS
DMSOA3
0
50
100
150
200
250
300
0 1 2 3 4 5 6 7GEN ER A T ION S
Tota
l cel
l num
bers
DMSOA3
A)
B)
C)
103
Figure 23. Effect of A3 receptor signaling on the proliferation kinetics of
Foxp3 positive and Foxp3 negative CD4 T cells in vivo. CFSE labeled CD4 T
cells from P25 TCR transgenic (Ly5.2) mice were intravenously transferred to
Ly5.1 recipient mice. 24 hrs later, the recipients were challenged with 2.5ug of
P25 peptide along with either DMSO (control) or AB-MECA (200ug/Kg) (i.p) for a
period of 7 days. On Day 8, mice were sacrificed and all their peripheral lymph
nodes (axial, cervical, inguinal, popliteal) were isolated and pooled for analysis
by flow cytometry. A) Representative FACS plots showing CFSE dilution of
adoptively transferred T cells in DMSO and AB-MECA treated mice. B) Line
graphs depicting the number of foxp3- T cells in each generation of DMSO
(dotted lines) and AB-MECA treated (solid lines) mice. C) Line graphs depicting
the number of foxp3+ T cells in each generation of DMSO (dotted lines) and
ethanol treated (solid lines) mice. Data is representative of 2 independent
experiments.
104
84
86
88
90
92
94
96
98
100
102
104
1
FLU
OR
SCEN
CE
INTE
NSI
TY
DMSO USp = 0.000592DMSO STIM A3 USA3 STIM
Fig 24. Assay of PLD activity in AB-MECA treated CD4 T cells. Total
splenocytes from P25 TCR transgenic mice were incubated overnight with the
P25 peptide (1ug/ml). Following day, CD4 T cells were sorted and pre-treated
with DMSO or AB-MECA for 30 mins. Cells were stimulated with soluble biotin
conjugated anti-CD3 (10ug/ml) and avidin for 30 mins. Lysates were then probed
for PLD activity as per manufacturers instruction. Filled bars are DMSO treated
samples and open bars are AB-MECA treated samples.
105
expression of A3 receptor. The following day CD4 T cells were sorted and
pretreated with AB-MECA for 30 min before restimulation with soluble anti-CD3
for 30 min. The total cell lysate from these samples were then used for PLD
assay as per manufacturers instruction. As reported previously, we observed an
increase in PLD activity in CD4 T cells following stimulation and this increase is
not seen in samples treated with AB-MECA (Fig 24). Thus, A3 receptor signaling
in CD4 T cells blocks TCR induced PLD activity. This indicates that the selective
inhibition of Foxp3- T cell proliferation in AB-MECA treated cells is caused in part
by blockade of PLD signaling.
Adenosine A3 receptor signaling and cAMP
A3 receptor activation is linked to Gi-mediated inhibition of adenylyl cyclase
(Gessi et al., 2008). Recent reports indicate that A3 receptors dictate cellular
responses such as mast cell degranulation in part by decreasing intracellular
cAMP concentration (Hasko et al., 2008). To determine the effect of A3 receptor
activation on cAMP levels in CD4 T cells, splenocytes from P25 TCR transgenic
mice were stimulated with P25 peptide overnight to induce expression of A3
receptor. On the following day, CD4 T cells were sorted by MACS column and
incubated with DMSO or AB-MECA for 30 min. CD4 T cells were then stimulated
with biotin conjugated anti-CD3 and avidin for 5 mins. Cells were then lysed in
0.1N HCL and the supernatants were assayed using cAMP-specific ELISA (Fig
25a).
106
02468
101214161820
1
cAM
P (p
mol
/ml)
DMSOUnstimulatedDMSO Stimulated
AB-MECAUnstimulatedAB-MECAStimulated
FOXP3
CTL
A4
cAMP (1uM) cAMP (10uM)1.4
cAMP (100uM) cAMP (1mM)
21.2 30.0
A)
B)
#
*
107
Fig 25. Assay for cAMP levels and activity in CD4 T cells. A) Total
splenocytes from P25 TCR transgenic mice were incubated overnight with the
P25 peptide (1ug/ml). On the following day, CD4 T cell were sorted and pre-
treated with DMSO or AB-MECA for 30 mins. Cells were stimulated with soluble
biotin conjugated anti-CD3 (10ug/ml) and avidin for 5 mins and lysed in 0.1N
HCL. A) The supernatants were assayed for cAMP levels using cAMP specific
ELISA. (* p<0.07, # p= 0.065) B) CD4 T cells were cultured with anti-CD3 and
APCs along with varying doses of cAMP (1μM to 1mM) for 3 days. Cells were
further cultured in IL-2 containing medium for 4 days and analyzed by flow
cytometry. C) Total Foxp3- T cell numbers (left) and Foxp3+ T cell numbers
(right) in exogenous cAMP treated cultures on day 7.
0
1
2
3
4
5
6
1
Tota
l cel
l num
bers
0
0.05
0.1
0.15
0.2
0.25
0.3
1
cAMP (1uM)cAMP (10uM)
cAMP (100uM)cAMP (1000uM)
(106) (106)
C)
108
We did not observe any increase in cAMP levels in either stimulated or non-
stimulated cells of control (DMSO) treated samples. In contrast, we detected high
concentration of cAMP in both unstimulated and stimulated samples treated with
AB-MECA. This observation is in stark contrast to what has been reported in
other immune cells regarding A3 receptors decreasing intracellular cAMP
concentrations (Jin et al., 1997).
The second messenger cAMP is shown to be a negative regulator of T cell
activation and proliferation (Bopp et al., 2007; Ramstad et al., 2000). A previous
study showed that cAMP-dependent signal transduction interferes with CD25
expression and IL-2 production (Ramstad et al., 2000). To test if A3 receptor
signaling blocks effector T cell activation/proliferation via cAMP, CD4 T cell
proliferation was determined following addition of exogenous cAMP (dibutyryl-
cAMP, Db-cAMP, a cell permeable analog of cAMP, Calbiochem). Total CD4 T
cells were stimulated with anti-CD3 antibody and APCs in the presence of
increasing concentrations of Db-cAMP for 3 days followed by culture in IL-2
containing medium for 4 days. Flow cytometric analysis of Foxp3 and CTLA4
expression show that low concentrations (1uM-10uM) of cAMP have no effect of
CD4 T cells population dynamics, whereas high concentration (100-1000μM)
cause increased frequency of Treg cells (Fig 25 b, c). Hence, increase in cAMP
level selectively causes inhibition of Foxp3- T cell proliferation similar to those
observed with AB-MECA. Taken together, these findings indicate that cAMP is
involved in mediating the effects of adenosine A3 receptor on CD4 T cells.
109
Various studies suggest that the effect of cAMP in T cells is mediated by
the cytosolic cAMP-dependent protein kinase A (PKA) type I (Ramstad et al.,
2000). It is reported that cAMP binds to the two regulatory subunits in the inactive
PKA tetrameric holoenzyme to release two active catalytic subunits. In turn,
these catalytic subunits phosphorylate diverse proteins to regulate their activity
(Yao et al., 2002). Based on these observations, it was hypothesized that the
increase in cAMP levels in A3R agonist treated samples would lead to activation
of PKA followed by increased phosphorylation of its downstream effector
molecules. To test this experimentally, western blot analysis was performed on
CD4 T cells stimulated with anti-CD3 in the presence of AB-MECA. The lysates
were assayed for phosphorylation patterns by western blot analysis using anti-
phospho-PKA substrate antibody. In comparison to both unstimulated and
stimulated control (DMSO) treated samples, stimulated AB-MECA treated
samples showed increased phosphorylation of PKA substrates (Fig 26a). cAMP
assay showed increased cAMP levels in both unstimulated and stimulated
samples treated with AB-MECA. We further determined the effect of A3 receptor
signaling on PKA activity in both stimulated and unstimulated T cells. As
predicted from the data on cAMP, AB-MECA increased PKA substrate
phosphorylation in unstimulated AB-MECA treated CD4 T cells (Fig 26b). A mild
increase in PKA substrate phosphorylation was observed in AB-MECA treated
CD4 T cells stimulated with anti-CD3.
110
DMSO
DM
SO
DM
SO
AB
-MEC
A
(50u
M)
AB
-MEC
A
(100
uM)
US S US S
AB-MECA (50uM)
US S S SA)
B)
Fig 26. Western blot analysis of phosphorylation patterns of PKA
substrates in AB-MECA treated CD4 T cells. Total splenocytes from P25 TCR
transgenic mice were incubated overnight with the P25 peptide (1ug/ml). The
following day, CD4 T cell were sorted and pre-treated with DMSO or AB-MECA
for 30 mins. Cells were stimulated with soluble biotin conjugated anti-CD3
(10ug/ml) and avidin for 5 mins and the lysate were separated on 8%
polyacrylamide gels, transferred on to nitrocellulose membrane and blotted with
antibody against phospho-PKA substrates. A and B) (Top blot) phosphoPKA blot,
(bottom) beta actin, loading control. US = Unstimulated sample, S = Stimulated
sample.
111
In conclusion, these data indicate that adenosine signaling through A3
receptor blocks T cell proliferation via an increase in cAMP and decrease in PLD
signaling.
PLD signaling: synergy between ethanol and adenosine
Since both ethanol and adenosine A3 receptor agonist inhibit PLD activity
and result in enrichment of Treg cells, we examined if there is synergy between
the A3R agonist (AB-MECA) and ethanol. CD4 T cells from mouse spleen were
stimulated with anti-CD3 antibody both in the presence and absence of ethanol
and AB-MECA. Lower concentrations of ethanol (0.5%) alone did not cause
increased frequency of Treg cells. However, when 0.5% ethanol was combined
with 50μM AB-MECA, substantial increase in the percentage of Foxp3+ T cells
was observed (Fig 27 a). Also, the comparison of Foxp3+ and Foxp3-T cell
numbers indicate decreased proliferation of Foxp3- T cells in cultures treated
with either AB-MECA alone or AB-MECA and 0.5% ethanol (Fig 27 b) indicating
enrichment of Treg cells in these culture conditions. The synergy between these
two factors may be due to increased suppression of PLD signaling and/or
inhibition of multiple signaling pathways that collectively block non-Treg
activation.
Previously, it was reported that ethanol increases adenosine receptor
stimulated cAMP levels in human lymphocytes (Hynie et al., 1980) (Gordon et al.,
1986). Increased cAMP levels in the presence of both ethanol and adenosine
could contribute to the observed synergy in Treg enrichment. However, we
112
DMSO
0.78
AB-MECA (50μM)
4.74
0.5% ethanol 0.86
A3 + 0.5% ethanol 11.74
1.0% ethanol 4.91
A3 + 1.0% ethanol 20.35
A)
Foxp3
CTL
A4
113
Fig 27. Combinatorial effect of ethanol and adenosine on CD4 T cell
population dynamics. Total CD4 T cells were cultured with anti-CD3 and APCs
along with ethanol alone or in combination with AB-MECA(50uM) for 3 days.
Cells were further cultured in IL-2 containing medium for 4 days and analyzed by
flow cytometry. A) Flow cytometric plots depicting Foxp3 in the x-axis and CTLA4
in the y-axis. B) Total Foxp3- T cell (left) and Foxp3+ (right) T cell numbers in
0.5% ethanol, AB-MECA and in AB-MECA + 0.5% ethanol treated cultures.
0
1
2
3
4
5
6
7
8
1
Tota
l cel
l num
bers
0
20
40
60
80
100
120
1
0.5 % ethanol
AB-MECA
AB-MECA +0.5% ethanol
(106) (103)
B)
114
1 2 3
1. AB-MECA (50μM)
2. 0.5 % ethanol
3. AB-MECA + 0.5 % ethanol
Fig 28. Western blot analysis of phosphorylation patterns of PKA
substrates in CD4 T cells treated with a combination of ethanol and AB-
MECA. Total splenocytes from P25 TCR transgenic mice were incubated
overnight with the P25 peptide (1μg/ml). Following day, CD4 T cell were sorted
and pre-treated with ethanol (0.5%) or AB-MECA or both for 30 mins. Cells were
stimulated with soluble biotin conjugated anti-CD3 (10μg/ml) and avidin for 5
mins and the lysate were separated on 8% polyacrylamide gels, transferred on to
nitrocellulose membrane and blotted with antibody against phospho-PKA
substrates. A) (Top blot) phospho PKA blot, (bottom) beta actin, loading control.
115
observed very little, if any, increase in phosphorylation of PKA substrates in
samples treated with the combination of AB-MECA (50μM) and 0.5% ethanol
compared to 0.5% ethanol alone (Fig 28). Since there are many potential bands
that are not separated by 1D gel analysis, further analysis is needed to determine
whether ethanol and AB-MECA have synergistic effect on PKA activity.
STRUCTURE-FUNCTION ANALYSIS OF PHOSPHOLIPASE D
The data presented above show that various exogenous and endogenous
factors influences the immune outcome by regulating PLD signaling. However,
the contribution of PLD to T cell signaling is not clearly understood. As described
previously, the catalytic action of PLD on phosphatidyl choline (PC) results in the
formation of phosphatidic acid (PA) and soluble choline. The formation of PA
constitutes the crucial contribution of PLD to cellular signaling and function. PA is
an important lipid second messenger that can also be synthesized by several
other routes and thus the contribution of PLD to the overall mass of PA in cells is
quite miniscule (Ktistakis et al., 2003). Therefore, PLD is thought to only
influence the local levels of PA. Thus, delineation of the spatial regulation of PLD
isoforms in T cells will help us understand its function in T cells.
As mentioned previously, the two isoforms of PLD localize at different
locations in the cell. Over expression and epitope tag studies reveal that PLD1 is
found mainly in punctate structures around perinuclear regions while PLD2 is
primarily found in the plasma membrane. To determine the region that controls
the localization of PLD1 and PLD2, a series of mutants of both PLD1 and PLD2
116
were generated. In order to assess the localization of these mutants in the cell,
these mutants were tagged with YFP in the N-terminal and transfected in Jurkat
T antigen cells, which express SV40 large T antigen to allow high level of
expression of transfected genes (Northrop et al., 1993) . After transfection (24
hrs), live cells were separated using Ficoll gradient, mounted on glass slides
coated with lysine, fixed and covered with cover slip. These slides were then
analyzed using confocal microscopy.
Determinants of PLD1 perinuclear localization
At first, we addressed the region responsible for the differential localization
of PLD1 and PLD2. The primary sequence of PLD1a revealed the presence of
116 amino acid ‘loop region’ inserted between catalytic sites II and III (Frohman
et al., 1999). Previous studies in which the loop region of PLD1 was deleted
have reported modest increase in the basal activity of PLD1 (Sung et al., 1999).
Based on this observation, we hypothesized that deletion of the loop region
redistributes PLD1 similar to PLD2 and this results in increased catalytic activity
of PLD1. To test this idea, mutant human PLD1b with loop (aa. 504-585) deletion
was constructed and its localization was assessed using confocal microscopy.
The loop deletion mutant of PLD1 lost its ability to localize in punctate structures
surrounding the nucleus and localized to the plasma membrane, similar to PLD2
(Fig 29). These data suggested that the loop region is a required component for
PLD1 localization in vesicular structures.
117
PLDc
5851 1036
Fig 29. Confocal microscopic analysis of the sub-cellular localization of
PLD1 loop deletion mutant. PLD1 and PLD2 full length and loop deletion
mutant are tagged with YFP. Green indicates the localization of the respective
construct and red in propidium iodide staining of the nucleus. These constructs
were transfected in jurkat T antigen cells. LIve cells were isolated 24 hours later
by ficoll gradient and plated on lysine coated glass slides. Cells were then
imaged using the confocal microscope and images were processed using LSM
image examiner software.
PX PH PLDc
loop
C-term
504
PLDc
5861 1036
PX PH C-ter
503
PLDc
PLDc
1 933
PLDcPX PH C-term
Full length PLD1b
Full length PLD2
Loop deleted PLD1b
Full length PLD1
Full length PLD2
Loop deleted
118
Full length PLD1
+ Full length PLD1
58loop
50FLAG
58loop
50FLAG
Fig 30. Confocal microscopic analysis of the sub-cellular localization of
PLD1 loop region alone or loop region and full length PLD1 combinations.
PLD1 full length is tagged with YFP. Green indicates the localization of the full-
length PLD1 construct. Loop alone construct was tagged with FLAG. Blue is the
DAPI staining of the nucleus. Loop alone construct was detected using anti-
FLAG conjugated with flurochrome. PLD1 and loop construct were transfected in
jurkat T antigen cells either alone or together. Live cells were isolated 24 hours
later by ficoll gradient and plated on to lysine coated glass slides. Cells were then
imaged using the confocal microscope and the images were processed using
LSM image examiner software.
119
Next, we determined if the loop region is sufficient to determine the
localization of PLD1 into vesicular structures. Furthermore, if loop interacts with
unknown target molecules in the cell that dictate the localization of PLD1 then
expression of the loop alone construct could interfere with PLD1-target molecule
interaction. Therefore, flag tagged ‘loop alone’ construct was co-transfected with
YFP fusion full length PLD1. Full length PLD1 localized in punctate structures
and when co-transfected with the ‘loop alone” construct, there were no
observable differences in its localization (Fig 30). The loop alone construct was
mainly detected in the plasma membrane. The data suggest that the loop region
is required for PLD1 sub-cellular localization in the vesicular structures but loop
alone (aa 504-585) is not sufficient to create the structure of PLD1 that interacts
with the cellular target that determines the localization of PLD1.
Also, we determined the contribution of PX, PH and C-terminal regions to
the peri-nuclear localization of PLD1 by deletion of the corresponding regions
from full length PLD1. These constructs were transfected into Jurkat T antigen
cells and their localization was determined by confocal microscopy. The
construct lacking PX and PH domain (a.a 1-333 deletion) localized entirely in the
cytoplasm (Fig 31). The mutant with only PX and PH domain (a.a 1-342) had
diffuse localization in both nucleus and cytoplasm, similar to vector alone.
Interestingly, the construct with only the C-terminal (aa. 933 -1036) localized
entirely in the nucleus. This suggests that the C-terminal (aa-933-1036) has
nuclear import property. Indeed, PLD1b localization in the nucleus has been
reported before (Freyberg et al., 2001).
120
PLDc
5851 1036
PLDcPX PH loop
C-term
504
PLD1b Full length
C-term
PLDc
585334 1036
PLDc loop
504
N-terminal deletion of PLD1
1
PX PH
342PX+ PH only
C-terminal only
1036 933
C-termina
Full length PLD1b
N-terminal deletion PX+PH only C-terminal only
Merged
YFP
DAPI
121
Fig 31. Schematic representation of the mutant PLD1 constructs and
confocal microscopy of their sub-cellular localization. All the constructs are
tagged with YFP. Green indicates the localization of these constructs. Blue is the
DAPI staining of the nucleus. These constructs were transfected in jurkat T
antigen cells. Live cells were isolated 24 hours later by ficoll gradient and plated
on lysine coated glass slides. Cells were then imaged using the confocal
microscope and images were processed using LSM image examiner software.
122
Together, these data suggest that the interaction of PX, PH domain with the rest
of PLD1 domains determines the perinuclear localization of PLD1. It is evident
that interactions between different domains rather than a single domain are key
to the sub cellular localization of PLD1.
Determinants of PLD2 plasma membrane localization
PLD2 has strikingly restricted distribution to the plasma membrane. Thus,
YFP fusion constructs of PLD2 deletion mutants were made to determine the
domain necessary for its plasma membrane localization. The construct
containing PX+PH+ C-terminal localized to the cytoplasm (Fig 32). Similar to
PLD1, 'C-terminal only’ construct of PLD2 localized to the nucleus. This
observation is in agreement with previous studies indicating highly homologous
C-termini of both PLD isoforms (Liu et al., 2001). Together, these observations
suggest that the interaction of PX, PH and C-terminal with the catalytic region
determines the plasma membrane localization of PLD2.
Future studies can be aimed at assaying the catalytic activities of both
PLD1 and PLD2 mutant constructs and its effect of TCR signaling to pinpoint with
certainty the contribution of PLDs to the functioning of the immune system.
123
PLDc
1 933
PLDcPX PH C-term
Full length PLD2
C term
1 933
PX PHPH+PX+C
C
termC terminal only
Full length PLD2
PH+PX+C C terminal only
Merged
YFP
PI
124
Fig 32. Schematic representation of the mutant PLD2 constructs and
confocal microscopy of their sub-cellular localization. All the constructs are
tagged with YFP. Green indicates the localization of these constructs. Red is the
propidium iodide staining of the nucleus. These constructs were transfected in
jurkat T antigen cells. Live cells were isolated 24 hours later by ficoll gradient and
plated on lysine coated glass slides. Cells were then imaged using the confocal
microscope and the images were processed using LSM image examiner
software.
125
EFFECT OF PLD2 GENE DELETION ON T CELL RESPONSES
Delineating the isoform specific contribution of PLD1 and PLD2 would be
critical to address their role in regulatory T cell enrichment. In order to delineate
the potential role of PLD2 in regulating the balance between effector and
regulatory T cell subsets, we generated mice deficient in PLD2 specifically in T
cells. Mice carrying floxed PLD2 genes were crossed with CD4 CRE mice in
order to delete the gene in double positive (CD4+CD8+) and CD4 and CD8
single positive T lymphocytes. PLD2 gene was successfully deleted in CD4 T
cells as detected by the differential size of DNA segments (WT mice = 6 kb,
PLD2 +/- = 6 and 5.2kb, PLD2 -/- = 5.2Kb) on southern blots (Fig 33a).
At first, we characterized PLD2flox/floxCD4cre mice to determine the effect
of deletion of PLD2 on thymocyte differentiation and peripheral T cell activation.
The absence of PLD2 had minimal effect on T cell development as determined
by flow cytometric analysis of thymocytes from WT and PLD2 (+/- and -/-) mice
(Fig 33B). Also, CD4:CD8 ratios in the spleen were similar between PLD2 (+/-)
and PLD2 (-/-) mice (Fig 33 C). Based on our previous in vitro findings, we
expected increased frequency of regulatory T cells in PLD2 knock out mice.
Surprisingly, deletion of PLD2 did not alter the development of naturally occurring
CD4+ CD25+ Foxp3+ regulatory T cells (Fig 33D). These observations suggest
that deleting PLD2 at the double positive stage of T cell development does not
affect the development of CD4, CD8 and regulatory T cells.
126
WT +/- -/-
WT +/- - / -
CD
8
CD 4 CD 4
Foxp3
A)
B)
C)
D)
CD
8
CD
25
Fig 33. Phenotypic analysis of conditional PLD2 deficient mice. A) Southern
blot analysis of CD4 T cells from WT or PLD2 (+/-), PLD2 (-/-) mice. B) Flow
cytometric analysis of thymocytes from PLD2 deficient mice. X-axis corresponds
to CD4 T cells and y-axis corresponds to CD8 T cells. C and D) Flow cytometric
analysis of splenocytes from PLD2 deficient mice. Foxp3 versus CD25 is gated
on CD4+ T cells.
127
Next, we determined the functional consequences of TCR induced
signaling in PLD2 deficient T cells. Sorted CD4 T cells were stimulated with anti-
CD3 and irradiated APCs overnight. Expression of CD69 (very early activation
antigen) and CD25 (IL-2Rα) was determined by flow cytometry. Both WT and
PLD2 (-/-) mice up regulated activation markers to the same extent (Fig 34A).
Concomitant with activation status, both WT and PLD2 (-/-) mice had similar
proliferation kinetics 72 hrs after activation (Fig 34B). Although, our previous in
vitro experiments suggested that inhibition of PLD signaling using 1-
alcohol/adenosine blocks proliferation of effector CD4 T cells, proliferation of CD4
T cells from PLD2 knock out mice did not exhibit any significant differences. This
result indicates that the ability of PLD2 (-/-) CD4 T cells to initially become
activated is not affected by their lack of PLD2.
In addition, we determined the cytokine secretion by CD4 T cells of PLD2
knock out mice. Sorted CD4 T cells were added to tissue culture plates coated
with anti-CD3 along with soluble anti-CD28 for 72 hrs. After 72 hrs of stimulation,
cells were rested for 48 hrs and then re-stimulated with PMA and ionomycin.
Intracellular cytokine staining on these cells indicate that in PLD2 (-/-) mice, the
CD4 T cells have 24% IL-2 positive cells compared to 5% (WT) and 12%
(PLD2+/-) mice (Fig 35). In contrast, the percentage of IL-4 secreting cells was
lower in PLD2 (-/-) mice (6%) compared to WT (18%) and PLD2 (+/-) mice
(12%). We did not observe any significant differences in the cytokine levels of IL-
17 and TNF-α between WT and PLD2 (-/-) mice. Thus, the data indicate that
128
A)
B)
αCD3
0.5
CD25
CD
69
Unstimulated μg/ml 0.2 μg/ml
PLD2 (+/+)
PLD2 (+/-)
PLD2 (-/-)
APC + CD3
0.E+00
1.E+02
2.E+02
3.E+02
4.E+02
5.E+02
6.E+02
0 0.1 0.3 0.5 1anti-CD3 concentration
O.D
APC + CD3 + IL2
0.E+00
5.E+05
1.E+06
2.E+06
2.E+06
3.E+06
0 0.1 0.3 0.5 1
ANTI-CD3 CONCENTRATION (ug/ml)
wtwt hetero d2hetero d2 homo d2homo d2
129
Fig 34. Characterization of CD4 T cell function in PLD2 deficient T cells. A)
Activation markers, CD69 (y-axis) and CD25 (x-axis) following stimulation. Cells
are gated on CD4 T cells after 24 hrs of stimulation with anti-CD3. B)
Proliferation analysis of PLD2 deficient CD4 T cells after 72 hrs of stimulation
with different concentrations of anti - CD3. WT, PLD2 (+/-) and PLD2 (-/-) mice
are littermates.
130
IL-2
IL-4
IL
-17
TNF-α
IFN- γ
PLD2 (-/-) PLD2 (+/-)PLD2 (+/+)
Fig 35. Cytokine profiles of PLD2 deficient CD4 T cells. A) CD4 T cells from
WT and PLD2 KO mice were stimulated with plate bound anti-CD3 and soluble
CD28 for 72 hrs, following which cells were rested for 2 days. Cells were re-
stimulated with PMA and ionomycin and intracellular FACS staining for IL-2,
IFN- γ, IL-4, IL-17 and TNF-α was performed.
131
PLD2 deficient CD4 T cells remain as IL-2 producers after three days of
stimulation and have impairment in differentiation into Th2 type T cells.
To test if PLD2 is necessary for effector T cell differentiation into different
subsets namely Th1, Th2 or Th17, CD4 T cells from WT and PLD2 knock out
mice were activated under Th1 (in the presence of IFN-γ, IL-12 and anti-IL-4),
Th2 (in the presence of IL-4 and anti-IFN-γ) or Th17 (in the presence of TGF-β
and IL-6) skewing conditions and FACS staining was performed to detect
intracellular cytokine expression. Under Th1 induction conditions, 78% of WT
CD4 T cells were IFN-γ positive and 11% were IL-2 positive while in PLD2 (-/-)
mice 21% were IL-2 positive and 66% were IFN-γ positive (Fig 36, top row)
indicating slight resistance to differentiate into Th1 phenotype. On the other
hand, under Th2 induction conditions 1.8% of WT CD4 T cells were IL-4 positive
in comparison to 0.8% of PLD2 (-/-) T cells (Fig 36, middle row). Under Th17
skewing conditions, ~8% of CD4 T cells in PLD2 (-/-) mice were IL-17 positive
compared to 6% of WT T cells (Fig 36, bottom row). Together, the data suggest
that PLD2 (-/-) mice have slight impairment in differentiation into Th1/Th2 cell
types and remain at IL-2 secreting stage. We can further assess effector T cell
differentiation in PLD2 (-/-) mice in vivo (eg: by using P25 peptide, a strong
inducer of Th1 response).
In light of our previous findings, we next determined if ethanol/adenosine
inhibits effector T cell proliferation through inhibiting PLD2. To test this, we
treated WT, PLD2 (+/-) and PLD2 (-/-) mice with DMSO, A3 agonist or A3 agonist
plus 0.5% ethanol. We predicted that if A3 agonist inhibited PLD2 signaling, then
132
PLD2 (+/+) PLD2 (+/ -) PLD2 (- / -) IL
-2IL
-4IL
-17
TH1 induction
TH2 induction
TH 17 induction
IFN- γ
Fig 36. Differentiation of PLD2 CD4 T cells into Th1, Th2 and Th17 Effector
cells. Spleen CD4 T cells were stimulated with anti-CD3 in vitro and rested 5
days in the presence of Th1, Th2 or Th17 skewing conditions. T cells were re-
stimulated with PMA and Ionomycin and intracellular cytokine staining was
performed.
133
WT
PLD2 (+/-)
PLD2 (-/-)
DMSO AB-MECA
CTL
A4
Foxp3
Fig 37. Effect of A3 receptor agonist on PLD2 deficient CD4 T cells. CD4 T
cells isolated from WT and PLD2 KO mice spleen were stimulated with APC and
anti-CD3 either in presence of A3 agonist (AB-MECA) or carrier control (DMSO)
for 3 days. On day 4, cells were washed and placed in medium containing IL-2
for 4 days. On day 7, cells were harvested and stained for detection of Foxp3
expression and analyzed using flow cytometry.
134
WT
PLD2 (+/-)
PLD2 (-/-)
2% ethanol 1% ethanol0.5% ethanol
Foxp3
CTL
A4
Fig 38. Effect of ethanol on PLD2 deficient CD4 T cells. CD4 T cells isolated
from WT and PLD2 KO mice spleen were stimulated with APC and anti-CD3 in
the presence of varying concentrations of ethanol for 3 days. On day 4, cells
were washed and placed in medium containing IL-2 for 4 days. On day 7, cells
were harvested and stained for detection of Foxp3 expression and analyzed
using flow cytometry.
135
treatment of PLD2 (+/-) with A3 agonist and ethanol would lead to increased
frequency of Foxp3+ cells. However, we found no differences in the frequency of
Foxp3+ cells between WT and PLD2 knock out mice under these treatment
conditions (Fig 37 and 38). This suggests that A3 agonist/ethanol mediated
enrichment of Treg cells might involve additional signaling pathways other than
PLD2. Future experiments can be conducted to determine the level of PLD
activity in PLD2 (-/-) T cells. Based on the experiments of Treg enrichment using
AB-MECA/ethanol it is very likely that PLD1 compensates for the lack of PLD2 in
PLD2 (-/-) mice thus exhibiting no difference in PLDactivity levels.
Future studies in PLD2 (-/-) mice can be conducted to determine its role in
T cell signaling and function. Previous data from the lab indicated that PLD2 is
involved in proximal TCR signaling events. We can determine if PLD2 (-/-) mice
exhibit altered TCR signaling pathway compared to WT mice.
CHAPTER FOUR
DISCUSSION
Introduction
The response to pathogenic attack and maintenance of immune
homeostasis requires precise coordination between different cell types of helper
T cell subsets. Population balance between different types of cells is key to
sustaining a balanced immune system. Many studies have reported altered
balance between effector versus regulatory T cell subsets as the prime cause of
disease pathogenesis. For instance, increased frequency and suppressor
function of Treg cells have been reported and proposed as potential mechanism
of immune suppression in patients with tumor and HIV-infection (Strauss et al.,
2007a) (Strauss et al., 2007b) (Sempere et al., 2007). On the other hand,
reduced number/function of Treg cells and increased effector T cell function have
been reported in patients with allergic/autoimmune diseases (Dejaco et al., 2006)
(Bacchetta et al., 2006).
Hence, ideal treatment for conditions of excessive immune suppression
would be to enhance the frequency/ function of effector T cells and vice–versa for
autoimmune diseases. Therapeutic potential of this strategy has spurred the
136
137
interests of researchers leading to the discovery of many mechanisms for
specific enrichment of either Treg cells or effector T cells.
Previously, our lab reported the differential requirement for PLD signaling
in Treg cells versus effector T cells. As a consequence, inhibition of PLD
signaling led to preferential enrichment of Treg cells by inhibiting effector T cell
proliferation. Interestingly, other reports suggest increased PLD expression and
signaling in autoimmune myocarditis and chronic inflammation (Ahn et al., 2004).
For my dissertation work, I focused on identification of mechanisms regulating
PLD signaling in T cells. The data demonstrated that various exogenous
(ethanol, bacterial toxins) and endogenous (adenosine) factors alter the immune
balance through regulating PLD signaling. PLD2 deficient mice showed that the
effect of these molecules on the Teff: Treg balance is not dependent on PLD2
alone. Further the structure that controls the sub cellular localization of PLD1 and
PLD2 was determined using mutant construct analysis.
IMMUNE BALANCE: EFFECT OF EXOGENOUS FACTORS
The human body is exposed to myriads of pathogens, pollutants, and
environmental and bacterial toxins in day-to-day life. The immune system has
evolved in many ways to combat these intruders and to maintain peace with self
through mechanisms like plasticity of helper T cell subsets. But some pathogens
and various exogenous molecules selectively manipulate the immune balance to
their advantage by shifting the equilibrium between these activities one way or
138
the other. For instance, environmental toxin like dioxin has been shown to cause
immune suppression by increasing Treg frequency (Quintana et al., 2008). Our
data demonstrate that by inhibiting PLD signaling, exogenous factors like ethanol
and C. difficile toxin tip the balance towards immune suppression.
Our results suggest that these external factors by means of inhibiting PLD
signaling, block the up regulation of activation induced CD25 expression on
naïve CD4 T cells. IL-2 is an important T cell growth factor and CD25 is required
for the proper function/signaling of IL-2. However, Treg cells constitutively
express CD25 and thus expand in the presence of exogenous IL-2. The
functional significance of ethanol/C. difficile toxin mediated inhibition of PLD
signaling is suggested by the decreased proliferation of antigen specific effector
T cells and increased frequency of antigen specific Treg cells in vivo.
There is extensive evidence that ethanol consumption leads to immune
suppression. Recently, both acute and chronic alcohol intake have been shown
to result in specific defects in innate and adaptive immunity (Nelson and Kolls,
2002). It is suggested that ethanol results in loss of splenic and circulating T and
B cells through apoptosis (Shao et al., 1995) (Sibley and Jerrells, 2000). Our
experiments using ethanol provide evidence to suggest that this loss of T cells
might be due to lack of PLD signaling and its effect on naïve T cells. In addition
to mediating its effect through CD4 T cells, alcohol has been shown to modulate
the functioning of other immune cells like macrophages, neutrophils, dendritic
cells with antigen presenting capabilities (Szabo et al., 1993) (Nelson and Kolls,
139
2002). The lack of activation induced marker expression on CD4 T cells might
also be mediated through lack of antigen presentation through these APCs.
Thus, in our experimental set up we cannot rule out the effect of ethanol on these
APCs and the consequent reduction in TCR activation and PLD signaling.
In contrast to mice injected with ethanol intraperitoneally, mice fed on
alcohol diet showed increased frequency of Treg cells only locally (mesenteric
lymph nodes). This result can be explained based on previous studies
suggesting that oral administration of ethanol results in increased availability and
metabolism of ethanol in the gut resulting in less entry of ethanol into the blood
stream while intraperitoneal injections result in rapid appearance of ethanol in the
blood stream (Livy et al., 2003). Thus oral exposure of alcohol reflects the
localized effect of ethanol on T cells while intraperitoneal injection reflects
systemic effect of ethanol on T cells. This phenomenon of local immune
suppression could in principle be exploited for treatment of gut associated
inflammatory diseases like IBD and colitis.
Our studies with C. difficile toxin demonstrate a new facet of immune
evasion strategy through PLD signaling. C. difficile toxins have long been known
to induce reorganization of actin filaments due to modification of Rho proteins
(Ottlinger and Lin, 1988). Since PLD is an effector molecule of Rho, C. difficile
was also reported to inhibit PLD signaling. However, functional relevance for the
lack of PLD signaling was not previously established. On the basis of our
experimental results, we propose that by inhibiting PLD signaling in naïve T cells
140
through toxin B, C. difficile eliminates effector T cell functions. The consequent
increase in the frequency of Treg cells aids the pathogen’s success in promoting
illness and furthering its own survival. Although we report the effect of Toxin B on
altering the immune balance, we have not tested the effect of blocking Toxin B
using anti-Toxin B antibodies. Based on our results, we predict that blocking of
Toxin B would mitigate the effects of C. difficile on the immune system and
ameliorate the disease progression by promoting effector and memory T cell
expansion.
IMMUNE BALANCE: EFFECT OF ENDOGENOUS FACTORS
One of the drawbacks of a powerful immune response is uncontrolled immune
response against pathogens and associated collateral damage to self. The
restraint of uncontrolled immune response is mediated through negative feed
back mechanisms. Adenosine (Ado) is an endogenous molecule well known for
its role in mediating the negative feed back mechanisms of immune responses.
Previous studies have reported inhibition of inflammation following activation of
adenosine receptors. Adenosine receptors are expressed by all immune cells
and A2a receptor signaling on macrophages, dendritic cells and T cells have
been shown to inhibit effector function (Zarek et al., 2008). Based on many
studies, A2a receptors are considered the dominant receptor dictating
lymphocyte responses in T cells.
141
Here we demonstrate the role of A3 receptor in inhibiting effector T cell
responses. The data indicate that stimulation of T cells in the presence of A3
receptor agonist inhibits TCR induced activation of PLD signaling. This inhibition
of PLD signaling abrogates CD25 expression, effector T cell proliferation, and
cytokine secretion. Although, signaling through A3 receptor in other immune cells
results in low cAMP concentrations, we found that signaling through A3 receptor
in CD4 T cells results in elevated cAMP levels and increased PKA activity.
Previous studies on A3 receptors report both pro and anti-inflammatory
effects depending on the system investigated (mast cells, macrophages) and
species examined (rat, humans) etc (Gessi et al., 2008). However, the specific
effect of activating A3 receptors on CD4 T cells has never been studied. In the
heart, A3 receptors mediate cardioprotection through modulating PLD signaling
(Mozzicato et al., 2004). This led us to determine the effect of A3 receptor
signaling on CD4 T cells. We found that A3 receptor signaling blocked TCR
induced PLD activation. At present, we do not know the exact mechanism of A3
receptor signaling leading to PLD signal inhibition. Inhibition of PLD by A2a
receptors is mediated by interference with the translocation of small GTPases,
Arf and Rho (Thibault et al., 2000). In future, we can test if A3 receptor inhibits
PLD through translocation of small GTPases as well. One recent study also
demonstrated inhibition of PLD1 activity directly by Gβγ subunits (Preininger et
al., 2006).
142
Since adenosine receptors are coupled to G-protein, signaling is thought
to occur either through the inhibition or stimulation of adenylyl cyclase resulting in
a decrease or increase of intracellular cAMP concentration respectively. The
classical signaling pathway associated with A3 receptor suggests Gi mediated
inhibition of adenylyl cyclase with a concomitant decrease in cAMP
concentrations. We experimentally determined the effect of A3 receptor
activation on cAMP concentrations. Contrary to previous reports, we found
increased cAMP levels in A3 receptor agonist treated CD4 Tcells. This increased
cAMP levels also resulted in increased PKA activity. The effect of A3 receptor
activation on inhibition of effector T cell proliferation and concomitant increase in
Treg frequency was indeed reproducible by the cell permeable analog of cAMP,
db-cAMP. Future experiments can be done to determine if the effect of A3
receptor is solely mediated by cAMP and PKA by co-culturing CD4 T cells with
A3R agonist and PKA inhibitor H-89.
A3 receptor is coupled to trimeric GTP binding proteins, Gαi and/or Gαo
and Gβγ dimers. The αi subunits directly inhibit adenylyl cyclase. However βγ
dimers from Gi/o are known to activate adenylyl cyclase (AC) isozymes II and IV
(Yao et al., 2002). We speculate that the increase in cAMP levels caused by A3R
activation is mediated through βγ dimers. We can test if this is indeed the case by
inhibiting βγ signaling. One way to inhibit βγ signaling is through over expression
of the carboxyl terminal of βARK1 retrovirally in CD4 T cells. Previous evidence
143
suggests that expression of carboxyl terminus of βARK1 binds free βγ dimers and
thus inhibits βγ signaling (Yao et al., 2002) (Koch et al., 1994).
Depending on the cell type studied, cAMP has been reported to inhibit (Le
Stunff et al., 2000; Thibault et al., 2002) or activate (Mamoon et al., 1999) PLD
activity through PKA signaling. In our experiments, we detected increased
cAMP levels in CD4 T cells treated with A3R agonist 5 mins following T cell
stimulation and observed a decrease in the PLD activity 15-30 mins after TCR
stimulation. Based on these results, it is very likely that increased cAMP levels
caused by A3 receptor signaling results in inhibition of PLD signaling. The
experiment using inhibitor of PKA (H-89) and/or constitutively active form of PKA
could also be used to determine PLD activity following PKA signaling.
Based on our various observations, we propose the following model
depicting A3 receptor signaling in CD4 T cells (Fig 39). Two different pathways
can mediate the effect of A3 receptor signaling in T cells. A central role for Gi/o
βγ is proposed. A3 receptor activation can lead to increased cAMP levels and
PKA signaling. PKA has been demonstrated to inhibit PLD activation. Another
possibility is βγ dimers can directly inhibit PLD activity (Preininger et al., 2006).
The ability of A3 receptor agonist to promote regulatory T cell enrichment
in vivo suggests that it could be used for treatment of autoimmune diseases.
Studies in mice and rats demonstrate that the anti-inflammatory effects of
methotrexate are in part mediated via A3 receptors (Montesinos et al., 2003).
144
Perhaps, methotrexate acting through A3 receptor on CD4 T cells blocks PLD
signaling and leads to Treg enrichment.
Interestingly, it has been demonstrated that A3 receptor is over expressed
in cancer tissues in comparison to normal tissues (Gessi et al., 2004a). It should
be noted that the concentration of adenosine in solid tumor reaches as high as
100μM due to high levels of hypoxia (Hasko and Cronstein, 2004). Thus, it is
highly likely that T cells activated by MHC class II positive APCs in these tissues
are selectively blocked via A3 receptor signaling. Moreover, since A3 receptor
agonists inhibit IFN-γ secretion, A3 receptor antagonists could be effective in
tumor immunotherapy.
145
A3 R
adenosine
α i/o - βγ
AC II and IV
cAMP
PKA
PLD
adenosine
PA PC
Fig 39. Schematic representation of A3 receptor signaling in CD4 T cells. A
central role for Gi/o βγ subunits is proposed. A3 receptor activation leads to
increased cAMP levels and activates PKA. PKA has been demonstrated to inhibit
PLD activation. Another possibility is βγ dimers directly inhibit PLD activity
(Preininger et al., 2006).
146
AB-MECA AND ETHANOL: POTENTIAL USE AS A TOLEROGENIC
ADJUVANT
Our data show that concurrent presence of PLD suppressive factors such
as adenosine and ethanol impose substantial suppression of immune response.
We observed that 0.5% ethanol had no effect of inhibition of effector T cell
proliferation or expansion of Treg cells. However, combination of 0.5% ethanol
with A3 receptor agonist led to substantial decrease in effector T cell
proliferation. This suggests that there exists a threshold for PLD activity in T cells
and the combination of ethanol and AB-MECA pushes PLD activity well below
this threshold. Under these conditions, we see a sizable effect of PLD inhibition
on effector T cell proliferation and subsequent enrichment of Treg cells.
A very high concentration of ethanol leads to cell death due to the toxic
effects of by products of ethanol (Lieber, 1997). However, we can avoid these
toxic effects by using a combination of low doses of ethanol and AB-MECA.
Induction/expansion of antigen-specific Treg cells is of great therapeutic
interest for the treatment of autoimmunity, allergy and organ transplantation. Our
studies using AB-MECA/ethanol show expansion of antigen specific Treg cells in
vivo. Therefore, AB-MECA alone or combination of AB-MECA and low dose
ethanol may be used in immunotherapy of various diseases.
A recent study proposed the use of immunosuppressants like
dexamethasone (DEX) as tolerogenic adjuvants (Kang et al., 2008). They
demonstrated that antigenic immunization combined with DEX led to block of
147
dendritic cell (DC) maturation and preferential expansion of antigen specific
Foxp3+ cells. Based on the similar effect observed with AB-MECA /ethanol, we
propose that agents inhibiting PLD signaling can be used as tolerogenic
adjuvants. However, we do not know the effect of AB-MECA and ethanol on the
status of DC maturation. Future experiments can be designed to evaluate the
effect of PLD signaling in antigen presenting cells like DC.
PLD LOCALIZATION: INTERACTION BETWEEN MULTIPLE STRUCTURES
PLD1 and PLD2 are 50% identical and display similar domain structures.
However, they localize to different regions in the cell. It is suggested that
localization determines intermolecular interaction with downstream target
molecules thus serving different functions in signal transduction. A previous
report shows that deletion of the loop region in PLD1 led to an increase in its
basal activity levels but the localization of the loop deletion mutant was not
determined. We over expressed loop deletion mutant in the Jurkat T cell line and
found that it had plasma membrane localization similar to PLD2. Since PLD2 is
characterized by high basal activity it is very likely that the increased activity of
the loop deletion mutant is in part due to its plasma membrane localization and
potential modification by membrane attached enzymes (eg: phosphorylation).
A puzzling observation was that the isolated loop domain had plasma
membrane localization as well. Since deletion of loop from PLD1 abrogates its
distribution from vesicular structures we hypothesize that the coordinated
148
interaction of loop within PLD1 and with unknown structure in the cell sequesters
it to vesicular structures. One way to test this hypothesis is to insert the isolated
loop domain into full length PLD2. If the interaction of loop with the other domains
is the factor governing its vesicular localization, then PLD2 will localize similar to
PLD1.
A previous report suggests that PH, PX and palmitoylation sites on the N-
terminal region of PLD1 serve as potential membrane binding determinants
(Sugars et al., 2002). In agreement with previous studies, in a deletion mutant
encompassing all 3 potential sites (N-terminal deletion mutant), the membrane
binding determinants redistributed to the cytoplasm. We also tested the cellular
distribution of the isolated ‘PH+PX’ domain of PLD1. The localization of this
mutant did not resemble that of full length PLD1. Rather it was found to have a
diffuse localization in both cytoplasm and nucleus similar to vector construct.
Based on this result, we suggest that ‘PH+PX’ domain cannot be studied in
isolation. Other studies suggest that an intact C-terminus of PLD1 is required for
its function (Liu et al., 2001). We made a deletion mutant containing the C-
terminus fused with YFP. Interestingly, this mutant localized only in the nucleus
of the cell. Taken together, we propose that a single domain does not determine
the localization of PLD1. Rather interactions between different domains of PLD1
and with other cellular components regulate localization of PLD1 in sub cellular
structures. The presence of C-terminal region alone determines its nuclear
localization while interaction of the C-terminal region with catalytic domains and
149
the loop region redistributes PLD1 to the cytoplasm. Further, the interaction of N-
terminal domains (PX+PH) with the rest of PLD1 determines its localization in
membranous vesicles like golgi.
We undertook experiments to determine the domains necessary for the
plasma membrane localization of PLD2. As proposed for PLD1, similar
interaction between domains determines its plasma membrane localization.
Isolated C-terminus mutant of PLD2 had nuclear localization while the mutant
with the presence of PH+PX along with the C-terminus redistributed to the
cytoplasm. Further, the interaction of the region containing the catalytic domains
with the rest of PLD2 results in its plasma membrane localization. Our studies
provide evidence for the role of different domains of PLD1 and PLD2 in
determining their respective localizations under basal condition. Future
experiments can be conducted to determine the cellular binding target of PLD
proteins particularly the loop and N-terminal half. It is possible that various
modifications of typical residues mediate the hierarchy of localization signals.
This can be addressed using a site directed mutagenesis approach. Also, we
have not examined the functional effect of these mutations. Functional studies in
future will provide a better understanding of the role of localization in determining
specific functions.
PLD2 AND T CELL FUNCTIONING
As a result of the critical role of PLD in development, PLD null mutants are
embryonic lethal (LaLonde et al., 2006). In PLD2flox/flox CD4 cre mice, PLD2 is
150
deleted relatively late (double positive stage). Our data demonstrate that PLD2
is dispensable for T cell development after the double positive stage of
thymocyte differentiation. Our data does not address the role of PLD2 in earlier
aspects of T cell development.
Also, deficiency of PLD2 did not affect CD4 T cell activation and
proliferation. On the other hand, we did observe differences in cytokine secretion
profiles of PLD2 deficient T cells. PLD2 deficient T cell cultures had more IL-2
positive cells than wild type T cells and showed resistance to differentiate in to
Th1 and Th2 lineage in vitro. This effect on effector T cell differentiation might be
caused by blockade of transcription factors like T-bet and GATA3. These
possibilities can be investigated in the future.
Surprisingly, PLD2 deletion had very little effect, if any, on the expansion
of regulatory T cells. One possible explanation is that PLD1 compensates for the
lack of PLD2. We can test for this possibility by inducibly deleting PLD1 alone in
PLD2 CD4 cre knock out mice. Another possibility is that PLD2 deficient T cells
are inherently different due to their thymocyte development and differentiation in
the absence of PLD2 signals. The other exciting possibility is perhaps that PLD2
is more important under conditions of physiological stress. This possibility can be
addressed by inducing autoimmunity or by observing the immunological
response to pathogens in PLD2 deficient mice in vivo. Nonetheless, these
experiments in PLD2 knock out mice have brought to light previously unknown
questions and answers.
151
CONCLUDING REMARKS
PLD signaling in T cells was discovered in 1991. However, until now the
specific role of PA and PLD in T cell functioning has not been clear. Our lab
group was the first to highlight the differential requirement of PLD signaling in
effector versus regulatory T cells. This led us to investigate the role of PLD
signaling in T cells. My dissertation work has focused on identifying the
regulation of PLD signaling in T cells. I found that physiological molecules like
adenosine maintain immune homeostasis by modulating PLD signaling. In
addition, I discovered that pathogens/ exogenous molecules could alter the host
immune response by virtue of their PLD inhibiting properties. Further, I
determined the structure that controls the sub-cellular localization of PLD
isoforms and their specific role in T cell function. These studies highlight the
complex array of functions mediated by PLD in T cells. In the process of studying
PLD, we have also discovered the role of adenosine A3 receptor signaling in T
cells. This study highlights the role of crosstalk between different signaling
pathways in human health and disease.
152
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VITA
The author, Uma Chandrasekaran was born in Chennai, India on March
13, 1983 to Mr. and Mrs.Chandrasekaran. She received a Bachelor of
Engineering in Electronics & Instrumentation and Masters in Biological Sciences
from Birla Institute of Technology & Sciences (BITS-Pilani), India in May 2005.
In August of 2005, Uma joined the graduate program in Biomedical
Sciences at Medical College of Georgia (Augusta, GA). Shortly, thereafter she
joined the laboratory of Dr.Makio Iwashima. Uma moved with Dr. Iwashima to
Loyola University, Chicago in Aug 2007. In Dr.Iwashima’s laboratory, Uma
studied mechanisms of regulation of Phospholipase D (PLD) signaling in T cells.
After completing her Ph.D., Uma will begin a post-doctoral position in Dr.
Alessandra Pernis’s laboratory at Weill Medical College of Cornell University
(New York, NY) where she will study the role of IL-17 producing T cells in the
pathogenesis of autoimmune disorders like Rheumatoid Arthritis and Lupus.
191
