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Crit Rev Immunol. Author manuscript; available in PMC Jan 1, 2015.
Published in final edited form as:
Crit Rev Immunol. 2014; 34(2): 121–146.
PMCID: PMC4062920
NIHMSID: NIHMS590283
CD4 T-Cell Memory Generation and Maintenance
David J. Gasper, Melba Marie Tejera, and M. Suresh
Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, WI, USA
Comparative Biomedical Sciences Graduate Program, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, WI, USA
Address all correspondence to: M. Suresh, Department of Pathobiological Sciences, School of Veterinary Medicine, University of
Wisconsin-Madison, 2015 Linden Drive Madison, WI, USA 53706; Tel.: 1 608-265-9791; Fax: 1-608-263-0438; Email:
sureshm@svm.vetmed.wisc.edu
Copyright notice and Disclaimer
Abstract
Immunologic memory is the adaptive immune system's powerful ability to remember a previous antigen
encounter and react with accelerated vigor upon antigen re-exposure. It provides durable protection against
reinfection with pathogens and is the foundation for vaccine-induced immunity. Unlike the relatively
restricted immunologic purview of memory B cells and CD8 T cells, the field of CD4 T-cell memory must
account for multiple distinct lineages with diverse effector functions, the issue of lineage commitment and
plasticity, and the variable distribution of memory cells within each lineage. Here, we discuss the evidence
for lineage-specific CD4 T-cell memory and summarize the known factors contributing to memory-cell
generation, plasticity, and long-term maintenance.
Keywords: CD4 T cell, memory, model, Th1, Th2, Tfh, Treg
I. INTRODUCTION
The immune system is continually confronted by threats from divergent sources. Viruses, bacteria,
protozoan and metazoan parasites, fungi, and altered cells from the host's own body each present unique
challenges for the host's immune defenses. In response, branches of the adaptive immune system with
specialized effector functions have emerged to counter certain categories of threats. This effector
specialization is perhaps best illustrated by antibody-secreting plasma cells that broadly target extracellular
pathogens and by cytotoxic CD8 T cells that are particularly effective at cell-by-cell elimination of
intracellular pathogens. The CD4 T-cell compartment, by contrast, contains at least seven functionally
distinct subsets with diverse effector functions. These CD4 subsets play integral roles in all branches of
adaptive immunity and can directly influence innate responses. Importantly, CD4 subsets are
differentially recruited according to the type of immunologic threat, and multiple subsets with overlapping
or disparate functions may be co-recruited. The breadth of their involvement allows CD4 T cells to help
coordinate and balance the contribution of each branch of adaptive immunity, helping ensure that each
type of immunologic threat is met with an appropriate immune response. If the threat is resolved by a
balanced, threat-specific response, then the majority of the adaptive immune effector cells is lost to
apoptosis during the contraction phase. Fortunately, a small proportion of the responding cells survives
contraction and differentiates into long-lived memory cells. These memory cells persist in greater numbers
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than their naïve counterparts, and competent memory cells endow the host with enhanced secondary
immune responses that are significantly more rapid and efficient than the primary response. Fittingly, these
protective memory cells have been referred to as “... the most important biological consequence of the
development of adaptive immunity...” Conversely, aberrant or dysregulated CD4 T-cell memory is
suspected to contribute to multiple chronic or recurring inflammatory and immune-mediated disorders and
to the progression of neoplastic disease. These remarkably powerful memory cells also provide the
critical foundation for vaccine-induced immunity.
Not surprisingly, immune memory cells have been the focus of intense investigation for decades, and
significant progress has been made in elucidating the mechanisms underlying their generation and
maintenance. Historically, the greatest advances have occurred in the fields of CD8 T-cell and B-cell
memory. These fields have benefitted from their limited range of effector phenotypes and robust
proliferative capacity, a relatively restricted immunological purview, the early identification and
characterization of lineage-specific memory cells, and an inherent phenotypic fidelity between primary and
secondary effector cells. This contrasts with the broad phenotypic range of CD4 effector cells, a
substantially more constrained proliferative capacity, and the limited evidence for memory cells and
secondary effector responses for some phenotypes. Additionally, in vitro and in vivo phenotypic plasticity
has been widely documented in both primary and secondary CD4 effector cells of some lineages. This
makes the broad application of findings from CD8 T-lineage-restricted models to CD4 cells problematic.
To overcome some of these concerns, many recent studies have taken compartmentalized approaches to
CD4 memory by limiting investigation to similar or overlapping phenotypes. Notably, the more nuanced
model of CD8 T-cell memory generally remains the guiding framework for CD4 investigations.
Despite the aforementioned challenges, the investigation of CD4 T-cell memory has been successfully
guided by several key paradigms, including the classical T-cell response and systems for classifying
memory cells according to their effector phenotype, patterns of tissue migration, and capacity for
secondary responses. The T-cell response is perhaps the primary paradigm that provides context for the
generation of memory. In the section II of this review, we examine the T-cell response and mechanisms
operating at key transition points leading to the generation and maintenance of CD4 T-cell memory. In
section III, we review current models of CD4 T-cell memory generation and propose the development of
an integrated model of CD4 T-cell memory differentiation. In section IV, we cover the functional and
migratory divisions of T-cell memory, including the classical central memory (Tcm) and effector memory
(Tem) pools, and the more recently characterized tissue-resident memory (Trm) and recirculating memory
(Trcm) pools. Finally, key features of secondary memory are summarized in section VI.
It is evident that the characterization of CD4 T-cell memory may be approached using multiple non-
exclusive and often complementary methods. Our goal is to review the current literature regarding the
generation and maintenance of CD4 T-cell memory in the context of the dominant paradigms guiding this
exciting field.
II. EARLY CD4 T-CELL MEMORY DEVELOPMENT
The classical “T-cell response” paradigm provides the framework for understanding the development of
CD4 T-cell memory. The T-cell response is comprised of three phases, which begin when mature naïve
CD4 T cells are activated by recognition of antigen in the context of appropriate costimula-tory signals.
Activation is followed by rapid clonal proliferation and differentiation into functional effector CD4 T cells
in the expansion phase. The primary activation of naïve T cells is often referred to as priming to
differentiate it from the more rapid secondary activation of memory cells. Optimal priming requires a
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complex cascade of signaling events initiated by antigen recognition and perpetuated by cell-to-cell, co-
receptor, and cytokine signaling. In CD4 T cells, priming occurs over 1 to 2 days or more and culminates
with the installation of a new transcriptional program that endows the T cells with effector functions and a
robust proliferative capacity. This activated effector program also alters the expression of cell-surface
molecules. In mice, for example, this includes permanently inducing the expression of the activation
marker CD44, down-regulating the expression of other adhesion molecules such as CD62L and CCR7, and
up-regulating molecules such as CD62E and CXCR5 to facilitate trafficking to peripheral sites or
lymphofollicular zones, which were previously restricted. Elimination of the immunologic threat
leads to the death of the majority of the expanded effector cells in the contraction phase. A small number
of expanded cells survive contraction and persist as a quiescent population in the memory phase. Memory
CD4 T cells are maintained in greater numbers than naïve cells and may persist for extended periods of
time. These phases are repeated upon antigenic rechallenge, inducing memory cells to undergo a second
expansion phase that is remarkably more rapid than the primary expansion and that yields secondary
effector cells with enhanced functionality. If the secondary expansion quickly controls the threat, it is again
followed by a contraction phase, further enhancing the of size of the secondary memory pool and its
capacity for subsequent responses.
Secondary effector cells have been described for most T-cell lineages, with classical memory and
secondary responses in the Th1 and Th2 subsets being the most well characterized. The early investigation
of Th1 and Th2 T-cell memory responses benefited from experimental models that maintained a high
degree of lineage fidelity between primary and secondary effectors, similar to that exhibited by CD8 T
cells. In contrast, the early investigation of memory in the Th17, Tfh, and Treg lineages was challenging,
owing to a lack of consistent lineage fidelity. It is now widely considered that primary and secondary
effectors from these groups can exhibit varying degrees of phenotypic plasticity. While this review focuses
on the better-described Th1 and Th2 memory sets, discussions of Th17, Tfh, and Treg memory are
included, along with implications and consequences of their apparent plasticity. We note that Treg cells are
often considered apart from the other lineages, and their inclusion in this review is consequent to some
notable advances in the characterization of Treg memory. Two recent reports employing in vivo studies in
mice confirmed that antigen-specific Foxp3 Treg cells exhibit classical expansion and contraction phases
in response to acute viral infections with influenza and vaccinia virus. These studies demonstrated
that a long-lived Treg memory population persists beyond the contraction phase and is capable of
mounting enhanced antigen-specific recall responses in these models. In contrast, the nature of memory in
the recently characterized Th9 and Th22 lineages is unclear. Although secondary effectors with Th9 and
Th22 phenotypes have been reported, further research is necessary to fully characterize their origin and
disposition, and a full discussion is best saved for future reviews.
A. Precursor Frequency of Naïve CD4 T Cells Regulates Memory
Naïve CD4 T cells are mature, quiescent, postthymic T lymphocytes. They typically bear T-cell antigen
receptors (TCRs) with single-antigen specificity, and CD4 receptors that restrict the antigen recognition
capacity of the TCR to only peptides presented on MHC class II molecules, collectively referred to as the
peptide-MHCII complex (p:MHCII). Naïve cells are guided by a transcriptional program that maintains
their capacity for homeostatic trafficking and antigen surveillance but does not endow the naïve cells with
significant effector capacity. Classically, these cells bear the characteristic surface receptors CD62L and
CCR7. These receptors are generally believed to promote localization of naïve CD4 T cells to central and
regional antigen surveil-lance via continual trafficking through the secondary lymphoid organs (SLOs) via
the blood, though a recent study has questioned the functional necessity for CCR7. This trafficking
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pattern targets T cells to the paracortical regions of lymph nodes and the parafollicular regions of the
spleen, where they scan antigen-presenting cells (APCs), particularly dendritic cells, for cognate
antigens. Importantly, naïve T cells in mice lack expression of the murine activation marker CD44, while
human naïve T cells bear the naïveté-associated surface marker CD45RA but not the activation markers
CD45RO or CD69.
The size of the naïve CD4 precursor pool directly affects the magnitude of the primary response and
ultimately the size of the memory pool. Physiologic numbers of naïve antigen-specific CD4 T cells can
vary dramatically between pathogens. In mice and humans, the number of naïve CD4 T cells specific for
a given epitope is generally in the range of 1–100 per million naïve CD4 T cells; however, the reported
number varies significantly by epitope and MHCII allele and may range from 100 to 3000 cells per
mouse. A convincing report from Whitmire et al. suggested that earlier studies may have
overestimated precursor frequencies and that a mouse spleen more likely contains approximately 100
naïve CD4 T cells specific for a given epitope. Subsequent studies using advanced investigative tools,
such as T-cell libraries, have reported similar findings. The individual naïve cells within this peptide-
specific pool each have a unique TCR, resulting in the possibility of differential strength and duration of
TCR signaling during a primary response. TCR signaling, as will be discussed later, plays an early
critical role in establishing cell lineage and the potential for a cell to persist into memory. This intrinsic
TCR diversity within the naïve epitope-specific pool plays a signifi-cant role in generating heterogeneous
effector and memory populations. Thus, TCR diversity and precursor frequency may synergistically alter
the resulting effector phenotype, the magnitude of the response, and the subsequent predisposition for
memory.
All naïve CD8 T cells are recruited to the primary response regardless of antigen dose or type of infection;
however, this has not been conclusively demonstrated for CD4 T cells. It is likely that most naïve
antigen-specific CD4 cells are activated during the primary response; however, multiple studies have
demonstrated that a broad range of fitness is exhibited within the naïve pool, and not all of the naïve
antigen-specific cells are represented in the memory pool. There is strong evidence that the precursor
frequency of antigen-specific cells and the antigen load may have significant effects on the overall
activation and differentiation of the precursor pool. An interesting phenomenon observed only in
CD4 T cells suggests that, under some conditions, high precursor frequency may actually adversely impact
activation and recruitment into memory. In an elegant study by Celli et al., real-time manipulation and
two-photon imaging of the interactions between antigen-specific CD4 T cells and antigen-bearing DCs
revealed that access to antigen-bearing DCs was a limiting factor in the recruitment and activation of
precursor CD4 T cells. In this study, induction of clonal expansion was dependent on a minimum of 6
hours of TCR-p:MHCII interaction, and the frequency and duration of interaction between DCs and CD4
T cells decreased as precursor frequency increased. This finding suggests that increasing precursor
frequency also increases interclonal competition for TCR-p:MHCII signaling, which results in shorter T
cell-DC interactions and, as discussed in the next section, may ultimately skew selection of CD4 T cells
for primary and memory responses. Regardless of T-cell precursor frequency, CD4 T cells do not match
the proliferative capacity of their CD8 T-cell counterparts. In a model of acute lymphocytic
choriomeningitis virus (LCMV) infection in mice, the clonal expansion of CD4 cells specific for the
dominant MHC class II epitope may yield a population of up to 10 million cells in the spleen alone. It is
important to consider, however, that this CD4 expansion was at least 20 times smaller than the concurrent
clonal expansion of CD8 T cells, and the disparity persisted into memory. Nonetheless, it is likely that the
size of the CD4 precursor pool and the extent of their recruitment into the response determine the
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magnitude of CD4 T-cell memory.
B. TCR Signaling: TCR Avidity, Duration, and Intensity Regulate CD4 T-Cell Memory
Multiple studies have demonstrated that TCR-p:MHCII signaling is one of the most important factors
influencing the generation of robust CD4 memory. TCR signaling not only exerts the greatest
influence during T-cell priming and polarization but also impacts secondary responses. In the primary
response, the unique character of the TCR signaling in each cell differentially affects its selection from the
naïve CD4 T-cell pool and helps determine which selected clones may preferentially mount primary and/or
memory responses. It also helps drive the progressive increase in functional avidity exhibited by memory
CD4 T cells throughout the course of primary and subsequent challenges.
Most studies of TCR-p:MHCII interactions have used models generating the CD4 T-cell subsets Th1 and
Th2. Primary and memory Th1-cell responses are well characterized and are easily reproduced in
many acute viral and intracellular bacterial infections. Full CD4 T-cell priming and maximal proliferation
during the expansion phase are dependent on prolonged TCR-p:MHCII signaling. The optimum TCR-
p:MHCII interaction occurs over several days and possibly continues throughout the expansion phase
when antigens and APCs are not limiting factors. Because multiple clones with unique TCRs are
recruited during activation, the character of TCR signaling is different for each clone. These differences
are important because studies in acute viral infections indicate that only a subset of the antigen-specific
TCR clones recruited for the primary response is maintained in the memory phase, and it is vital to
understand how and why the clones are selected. Some studies have argued that survival to memory is
primarily influenced by the functional avidity with which the TCR binds p:MHCII, such that higher
avidity clones gain a survival advantage. From this background it has also been demonstrated that
rechallenge progressively yields higher avidity CD4 T-cell clones in the memory pool. In one notable
study of LCMV infection by Williams et al., an initial pool of naïve cells with a broad range of avidity
became progressively more constrained through the primary response and memory phase, with the
surviving clones exhibiting increased avidity. Thus, in this model, activated CD4 cells bearing TCRs
with lower functional avidity were less likely to persist into long-term memory.
Notably, mounting evidence indicates that the complex TCR-p:MHCII interactions leading to the
generation of CD4 T-cell memory encompass more than avidity. Indeed, more recent studies have
demonstrated that binding avidity alone does not necessarily promote entry into memory. Building on
their earlier findings, Williams et al. recently reported that the LCMV-specific CD4 T-cell memory pool
actually contains clones bearing a variety of TCR complexes ranging from low to very high MHCII
binding avidity. Their investigation revealed that TCR clones, which exhibited a slow rate of TCR-
p:MHCII dissociation, or “off-rate,” were preferentially recruited to memory over competing clones, with
little regard for binding avidity. Thus, the memory pool is likely initially enriched for TCR clones that are
capable of prolonged TCR contact, and perhaps from this pool the higher avidity clones may gain
competitive advantage. It is possible that the resulting heterogeneity in the initial memory pool may allow
some degree of clonal selection.
Importantly, in some in vivo models, not all CD4 T-cell clones surviving in the memory pool played a
prominent effector role in the primary response. Weber et al. reported that Th1 cells with genetically
engineered TCRs specific for two closely related Listeria monocytogenes peptides from the Listeria LLO
protein were compared: one preferentially mounted a robust primary effector response at the expense of a
meager secondary response, while the other mounted a modest primary response but a more robust
secondary response. This finding was interpreted to suggest that some subsets of responding Th1 cells
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preferentially function as memory, without mounting a maximal primary response, and that this constitutes
evidence of Th1 subset specialization. According to this study, elevated levels of CD5, a negative regulator
of TCR signaling, resulted in enhanced memory response at the expense of the primary response. Whether
CD5 regulation can yield CD4 effector subsets functionally analogous to the SLEC/MPEC division of
CD8 effectors, as discussed in section III.B, remains to be determined. Clearly, multiple mechanisms
involving TCR-p:MHCII signaling contribute to the generation of memory CD4 T cells, and further
studies are warranted.
C. Costimulatory Signaling and Cytokine Milieu During Priming and Expansion Phase Regulate CD4 T-
Cell Memory
TCR-p:MHCII signaling alone is necessary but not sufficient to confer full priming of CD4 T cells. TCR
signaling must be reinforced by costimulatory signaling via additional surface molecule interactions, with
the APC as well as cytokines in the local milieu. The most well-characterized cell-to-cell signaling
pathways involve interactions between the paired CD40-CD40L and B7-CD28 cell surface receptors.
CD40 on APCs binds to CD40L (CD154) on T cells, triggering a variety of signaling pathways in both cell
types. This interaction is critical for CD4 T-cell responses, and in the absence of CD40L signaling, the
clonal expansion of antigen-specific CD4 T cells in vivo is severely impaired. CD4 T cells significantly
up-regulate CD40L expression during TCR engagement, and in turn, APCs up-regulate CD40 expression
in response to CD40-CD40L interaction. This suggests that a key function of CD40L signaling is to help
ensure that non-specific CD4 T-cell activation in minimized. While naïve CD4 T cells form CD40L de
novo during priming, new evidence indicates that non-regulatory CD4 effector and memory cells store
preformed CD40L that can be rapidly mobilized. This likely contributes to the increased efficiency with
which CD4 memory T cells mount a secondary response. Conversely, blockade of CD40-CD40L signaling
can reduce the magnitude of the primary CD4 responses by up to 90% in mouse models of acute LCMV
infection. The CD28 signaling pathway has not been fully elucidated; however, its activation is required
for maximal clonal expansion of activated CD4 cells and subsequent memory formation. Activated
antigen-bearing APCs up-regulate B7 expression, and B7 binding to CD28 lowers the threshold sensitivity
to TCR-p:MHCII signaling. Thus, the CD4 cells are more sensitive to p:MHCII complexes when the APC
is activated. In addition to lowering the threshold for activation, CD28 signaling strongly up-regulates
transcription of IL-2 and inhibitors of apoptosis, thereby increasing the capacity for proliferation and the
probability of surviving the contraction phase.
Full CD4 T-cell priming also requires cytokine signaling. During priming, the nature and combination of
the cytokine signaling in the local milieu influence the proliferative and effector capacities of the
activating cells. The prevailing balance of cytokine signals helps drive the CD4 lineage commitment and,
depending on the subset, may influence their capacity for survival into memory. An array of CD4
lineage-inducing and lineage-defining cytokines and their respective transcription factors have been
described for Th1, Th2, Th17, Tfh, and Treg subsets, and these are summarized in numerous
reports. While the capacities of the Th1 cytokine IL-12, and IFN-γ, as well as the Th2 cytokine
IL-4 to drive lineage commitment are well documented, their roles in the generation of CD4 T-cell
memory are not well understood. Further, it is challenging to extricate these roles in generating competent
effector cells from their subsequent roles in the generation of memory cells. The role of these cytokines in
the lineage fidelity and plasticity of secondary responses are further discussed later in this section and
again briefly in sections III and IV.
Recently, Liao et al. comprehensively reviewed the role of IL-2 signaling in CD4 T-cell activation and
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differentiation. IL-2 is the most well-characterized T-cell costimulatory cytokine, and it is produced in
high quantities by some CD4 subsets upon activation. Its primary functions in CD4 T cells are to act as a
growth factor to induce entry into the cell cycle, reinforce TCR signaling, differentially influence the
lineage selection of CD4 T cells during activation, and help control the population dynamics of effector
cells surviving contraction. While early studies suggested that IL-2 signaling was unrelated to
antigen-induced proliferation, more recent studies have demonstrated a role for IL-2 in initial activation
as well as expansion and lineage commitment. Compared to CD8 T cells, both naïve and memory
CD4 T cells are relatively refractory to IL-2–induced proliferation unless there is concurrent TCR
engagement. In CD4 T cells, TCR engagement functions to down-regulate cyclin-dependent kinase
inhibitors (CDKIs) and up-regulate the expression of key IL-2r subunits, facilitating entry in to the cell
cycle and increasing responsiveness to IL-2. This is important for memory generation, as the strength
of IL-2 signaling correlates with the magnitude of the proliferative response exhibited by some CD4
lineages. This is most prominent in Th1 and Th2 cells, in which this response appears to ensure that an
optimally expanded effector population is available for entry into memory. IL-2 signaling during
priming also leads to late up-regulation of IL-7rα on the expanded effectors, thereby further enhancing the
size of the effector pool that survives to memory.
Concurrently, the magnitude of IL-2 signaling during activation differentially affects the responsiveness of
activated CD4 T cells to lineage-promoting cytokines. IL-2 signaling increases responsiveness to IL-
12 and IL-4 but not IL-17, thereby favoring Th1 and Th2 differentiation over Th17. Increased IL-2
signaling is also required for Treg cell differentiation; thus, it appears that stronger IL-2 signaling
preferentially selects for certain lineages to be maintained into memory at the expense of others. The
ratio of IL-2 signaling strength to that of other cytokines also appears to be important in some cases.
Studies by Choi et al. indicated that differential signaling by IL-2 and ICOS during priming can regulate
Tfh differentiation and memory. They reported that lower expression of IL-2rα and increased ICOS
signaling during priming and expansion can lead to the preferential development of Tfh cells.
Further supporting the role of IL-2 signaling in the generation of lineage-specific memory, IL-2rα (CD25)–
deficient mice experimentally infected with Listeria monocytogenes (LM) exhibit markedly impaired Th1
memory. Notably, in the same experiment, CD25-deficiency did not inhibit the generation of an
interesting set of putative central memory precursors, defined as CD4 CD44 CCR7 CXCR5 PD-1
cells. In WT mice, these Tcm-like cells were cogenerated in vivo with Th1 and Tfh (CD4 CD44
CCR7 CXCR5 PD-1 ) cells during the primary response to experimental LM infection. When
adoptively transferred to naïve hosts and rechallenged to LM infection, the Tcm-like cells were capable of
generating heterogeneous secondary responses of Tcm-like, Th1, and Tfh lineages. The provenance of
these Tcm-like cells has been previously debated, with some sources suggesting that they are resting Tfh
cells; however, this evidence suggests that they may represent an uncommitted, but lineage-restricted,
Tcm-like population. If this assertion stands, then, contrary to some models of CD4 T-cell memory
generation, the IL-2–independent Tcm-like pool lacks a defined effector-phenotype intermediate. The
adoptive transfer studies conducted by Pepper et al. suggest that CXCR5 /PD-1 coexpression is tied to a
Tfh phenotype, and lack of PD-1 expression yields a Tcm-like population capable of secondary expansion
to form Th1, Tfh, and additional Tcm-like cells. Given the documented anti-proliferative effect of PD-1
expression, it is reasonable to question whether Tfh memory cells would benefit from maintenance of PD-
1 expression, or whether loss of PD-1 expression at the termination of the germinal center reaction would
allow these cells to regain the proliferative capacity important for memory responses. Clearly, IL-2
signaling plays important and complex roles in the generation of memory cells of several CD4 lineages.
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The implications of the intriguing Tcm-like CD4 CD44 CCR7 CXCR5 PD-1 cells are revisited in
section III.
D. Contraction
In models of acute infection, pathogen clearance curtails the primary effector CD4 T-cell response and
initiates the transition from the peak of expansion phase to the contraction phase. The length of the CD4 T-
cell contraction phase has been variably reported to occur over 1–2 weeks or up to 4 weeks, during
which the cessation of effector proliferation is augmented by the loss of up to 90–95% of the expanded
cells. The overall magnitude of CD4 T-cell expansion and contraction are significantly lower than in
CD8 T cells, and in some reports the loss of CD4 T cells continued in the memory phase. As
recently reviewed by McKinstry et al., the mechanisms underlying CD4 contraction have not been
completely elucidated, but they likely include induction of a combination of convergent apoptotic and non-
apoptotic death pathways in the lost cells and multiple survival and anti-apoptotic mechanisms in the
effector cells surviving to memory. McKinstry et al. also suggested that cell fate is influenced by signaling
during priming as well as during the effector stage and resolution of the immunogenic threat. A prior study
by Whitmire et al., using a mouse model of acute LMCV infection, demonstrated that a lack of B cells
during the contraction phase doubled the rate of Th1 cell contraction and reduced the generation of CD4 T-
cell memory. They further demonstrated that B-cell signaling was independent of antigen and antigen–
antibody complexes; however, the underlying mechanisms have not been determined. Recent studies using
SMARTA transgenic T cells indicate that increased expression of the proapoptotic factor Bim relative to
the antiapoptotic factor Bcl-2 contributes to the rapid attrition of lower-affinity Th1 cells following acute
Lm-gp61infection in mice, affirming a role for apoptosis in preventing some low-affinity cells from
reaching memory. Another recent in vivo study in mice suggested that differential expression of CD47
might play a substantial role in non-apoptotic loss of CD4 T cells during contraction. In that study,
newly activated CD4 cells transiently down-regulated CD47, rendering them susceptible to death by
phagocytic cells, unless CD47 expression is rescued by IL-2 signaling. Subsequently, cells lost during the
contraction phase tended to be CD47 low, while the resulting memory pool was CD47 high, suggesting
that mechanisms that restore CD47 expression also facilitate survival to memory. It is also notable that,
while IL-7 signaling is important for CD4 T-cell survival into memory, in vivo IL-7 blockade did not
enhance the contraction of antigen-specific cells in vaccinia-infected mice.
III. DIFFERENTIATION OF MEMORY CD4 T CELLS
The CD4 T cells that survive the contraction phase must undergo another critical transition to become
competent memory cells. This transition requires a phenotypic shift from a functionally active, highly
proliferative effector state to a quiescent, functionally alert memory state. Unlike naïve cells, memory cells
are transcriptionally poised to rapidly regain their proliferative and functional capacity upon re-encounter
with antigen. This is due in part to epigenetic alterations occurring during differentiation and to the
installation of a transcriptional program distinct from naïve and effector cells that facilitates survival via
multiple mechanisms.
Memory CD4 T cells are classically defined as the set of T cells produced during a primary immunogenic
challenge that persist and are capable of generating a recall response to secondary challenge. Using
this definition, many early investigators focused on linear models of differentiation from naïve to effector
to memory cells, particularly within in the Th1 and Th2 cell paradigm to understand memory. They were
able to demonstrate that neither persistence of antigen nor TCR-p:MHCII signaling are required for these
CD4 T cells to become long-lived memory cells, and that the removal of antigenic stimulation fostered the
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1. Linear Differentiation Model
transition to memory. Subsequently, further characterization of the memory pool has identified multiple
additional CD4 effector lineages with multiple tissue-trafficking patterns, a range of effector and
proliferative capacities, and plasticity or the interconversion between some CD4 lineages prior to entering
and emerging from the memory pool. Thus, over time, ample evidence has accumulated to suggest that the
activated CD4 T cells surviving beyond the primary response are plastic and remarkably
heterogeneous.
Before reviewing evidence from studies attempting to identify and characterize memory CD4 T cells, it is
important to note that it is not clear whether there is a single differentiation pathway by which memory
cells are produced. In fact, the exact route by which memory T cells are generated has long been debated,
and the demonstration of multiple sets of memory cells and lineage plasticity in primary and secondary
effectors complicate the picture. Multiple theoretical models of CD4 memory development have been
advanced in an attempt to account for this diversity of long-lived antigen-experienced cells. We will
briefly examine the most widely cited theoretical models of CD4 T-cell memory generation, followed by
the associated identifying characteristics of cells destined for and within the memory pool. In later
sections, we examine the categorical divisions that have been developed to characterize the resulting
phenotypically heterogeneous CD4 memory pool.
A. Models of Memory CD4 T Cell Differentiation
The path or paths by which memory T cells are generated has been debated since their earliest description.
Numerous models of memory differentiation have been suggested in attempts to account for various
phenomena reported for memory differentiation; however, the exact relation between naïve CD4 T cells,
heterogeneous effector cells generated during a primary response, and heterogeneous memory cells
generating secondary responses remains unclear. The traditional memory differentiation paradigms
reviewed by Kaech et al. have not changed substantially in more than a decade. Multiple studies have
since offered refinements to these models, and others have added to the burgeoning complexity of memory
CD4 T-cell generation; however, a single unifying theory accounting for the diversity of CD4 T-cell
memory has not yet emerged. Rather, the evidence suggests that multiple mechanisms of CD4 T-cell
memory generation may be differentially employed depending on the effector lineage and inflammatory
environment. We focus on variations of the linear differentiation model and the divergent or disparate fate
model. These models can be roughly divided into two groups based on pathogen clearance. The former are
dependent upon pathogen clearance for memory generation, while the latter contend that memory
generation begins prior to, and is independent of, antigen clearance.
The traditional linear differentiation model of T-cell development posits that,
upon antigen challenge, naïve CD4 T cells become activated and proliferate into effector cells, which then
survive the contraction phase and persist as quiescent memory cells. This model borrows from the
CD8 T-cell differentiation model, with the actual transition from effector to memory occurring during and
after the contraction phase following pathogen elimination. This model concept also holds that there is
lineage fidelity between the primary and secondary effectors. Indeed, the existence of long-lived memory
Th1 and Th2 cells capable of mounting competent secondary responses is well described, and several
groups have demonstrated that these Th1 memory cells emerge directly from the initial pool of Th1
effector cells generated during the primary response. In one key set of studies using IFN-γ
reporter mice, it was demonstrated that naïve endogenous CD4 cells specific for LCMV and LM-OVA
yielded Th1 effector cells which then persisted into memory and retained their phenotype upon
rechallenge. These studies were supported by contemporary reports from Lohning et al., who also
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2. The Decreasing Potential/Progressive Differentiation Model
demonstrated that memory cells can and do emerge from the primary effector population when purified
functionally active antigen-specificTh1 or Th2 cells are adoptively transferred to naïve hosts. When
primed in vitro or during viral infection in vivo, these antigen-specific cells form memory in the adoptive
host and are capable of producing secondary responses when rechallenged. Two caveats should be noted,
however. In the latter studies, antigen-specific memory was also formed by activated non-functional Th1
and Th2 cells generated and transferred under the same conditions, and in vivo rechallenge with LCMV
caused some memory cells derived from functionally active Th2 cells to adopt a Th1-like phenotype with a
shift to IFN-γ production, or co-production with IL-4. This would suggest that at least two memory pools
might exist, one generated by effector cells actively producing lineage-defining cytokines, and one by
activated cells not producing lineage-defining cytokines. Further, in the data presented by Lohning et al.,
the secondary effectors generated by the transferred non-cytokine secretors from both Th1 and Th2 groups
were equally capable of IFN-γ production comparable to the memory cells derived from the cytokine-
producing Th1 group. Notably, the Th2-derived cells co-produced significant amounts of IL-4 regardless
of the cytokine-producing capacity of the adoptively transferred progenitor cells. While it is likely that the
linear differentiation model accurately characterizes the differentiation of certain CD4 T-cell memory
subsets, there is significant evidence that some subsets are generated through alternative differentiation
pathways.
The decreasing potential model suggests that,
within the framework of linear differentiation, primary effector cells become progressively differentiated
with increasing strength and duration of TCR and costimulatory signaling. In this model, the ability of
effector cells to generate memory is progressively restricted in proportion to signaling, with failure of
memory generation coincident with maximal signaling and the terminal differentiation of the majority of
the responding cells. A recent study in CD4 T cells focused on the progressive differentiation model
variant, which may also account for the differential production of the central memory (Tcm) and effector
memory (Tem) pools. The results suggested that only cells of intermediate differentiation are able to
respond to memory-supporting survival signals and that terminally differentiated effector cells are not
maintained into memory. Thus, progressively greater levels of activation-associated signaling drive CD4
T-cell terminal differentiation at the expense of responsiveness to the survival signals present at the
termination of the primary response. The capacity for effector cells to survive into memory is then
dependent upon the point at which antigen is cleared. Another variation on this model, proposed by
Moulton et al., suggested that shorter duration of antigen exposure generated less-differentiated precursors
which preferentially yielded CD62L Tcm cells, while an increasing duration of antigen exposure
progressively favored CD62L Tem cells. Although this model was referred to as a divergent model, it
more closely follows the paradigms of linear differentiation than the divergent differentiation or disparate
fate models discussed next.
Notably, an additional level of complexity may also arise from these models. Because naïve T cells sharing
antigen specificity bear different receptors, reside in different locations and signaling milieu, and may have
different interactions with antigen, the naïve cells are inherently subject to different levels of signaling.
Differential signaling means that not all naïve cells are equally recruited or activated and may give rise to a
variety of effectors phenotypes, each with its own response with regard to terminal differentiation and
memory formation. As some cells in this model would not be terminally differentiated, differential
signaling could also provide a mechanism to account for plasticity in recall responses should the balance
of extracellular lineage-determining signals change. Differential signaling could also address some of the
inconsistent findings of Lohning et al., described above, with regard to the generation of memory by
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non-cytokine–producing cells and cytokine shifts. In LCMV infection, Th2 cells constitute a minor
component of the CD4 T-cell response that is dominated by Th1-associated signaling. Thus, the adoptively
transferred Th2 cells with the capacity for memory would be less differentiated and capable of responding
to the Th1-cyotkines dominating the inflammatory milieu of secondary responses to LCMV.
According to the divergent differentiation model, the initial
proliferation of activated cells during the expansion phase yields heterogeneous progeny with different
capacities for differentiation to either effector or memory cells. In this model, the dividing, newly activated
cell differentially distributes factors between the daughter cells, with one of the cells receiving factors
which preferentially equip it for survival into memory. In this way, a subset of responding antigen-specific
cells with a competitive advantage for generating memory are created during the initial response. This,
then, occurs without regard for duration of antigen exposure and is independent of antigen clearance. A
growing body of evidence supports this model, and perhaps the most convincing evidence is derived from
studies examining asymmetric cell division in which the memory- and lineage-associated factors in the
parent cell are unequally distributed to the daughter cells. Chang et al. investigated whether newly
activated CD4 T cells equally distributed their receptors among daughter cells during the initial cell
following activation. Using CD4 T cells with transgenic Leishmania-specific TCRs, they
demonstrated that the distribution of specific activation-associated signaling receptors was asymmetric in
vivo and that the disparity in receptor distribution was evident during initial divisions of the expansion
phase. These insights revealed a potential mechanism by which multiple phenotypes could arise from the
activation of a single antigen-specific CD4 T cell.
Asymmetric cell division was subsequently suggested to contribute to the diversity of CD4 effector and
memory lineages, with the range of effector phenotypes and the propensity for memory influenced by the
number of sequential asymmetric divisions. While Choi et al. did not examine the effects on CD4 T-
cell fate, they did suggest that multiple repetitions of this phenomenon during expansion may help explain
the concurrent emergence of Bcl6 Tfh and Blimp1 Th1 CD4 effector lineages within two cell divisions
of activation. This would support arguments that asymmetric cell division may underlie the generation
of some types of memory cells. Others have demonstrated asymmetric division at work in several T-cell
models; however, they are largely restricted to CD8 T-cell investigations and target the development of the
well-defined memory precursor effector cells (MPECs) and short-lived effector cells (SLECs) which have
been characterized only in the CD8 lineage. Even so, some findings with regard to linkage between
the nature of TCR signaling and asymmetric distribution of fate-determining factors fit well within the
previously discussed framework of TCR signaling and differential clonal selection for memory in CD4 T
cells. The implications of asymmetric cell division on the interpretation of CFSE-based cell proliferation
studies was recently addressed, with a review of several mathematical models devised to account for this
phenomenon. Further investigation into asymmetric cell division in CD4 T cells is necessary and will
continue to yield instructive insights into memory CD4 T-cell formation.
B. Terminal Effector and Memory Precursor CD4 T Cells
In the CD8 T-cell memory field, the identification of two distinct effector CD8 T-cell populations that
emerge during the expansion phase was a critical development. The first population, the short-lived
effector cells (SLECs), are lost during contraction, while the second population, the memory precursor
effector cells (MPECs), survive contraction and subsequently differentiate into competent memory cells.
CD8 SLECs and MPECs are distinguished by differential expression patterns of cell surface receptors.
SLECs are characterized by high expression of the senescence-associated molecule KLRG-1 and low
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expression of CD127, the alpha subunit of the IL-7 receptor. In contrast, MPECs are characterized by low
expression levels of KLRG-1 and high expression of CD127. A remarkable amount of productive
investigation has focused on the mechanisms underlying the differential production of SLECs and MPECs.
While the discovery of SLECs and MPECs was a key step toward elucidating the generation of CD8 T-cell
memory, an analogous paradigm broadly applicable to the field of CD4 T-cell memory has been elusive.
Recently, a similar division within the primary CD4 Th1 effector pool was reported by Kaech et al.
Using an LCMV model of acute viral infection, they identified a pool of primary effectors with memory
precursor-like phenotype, which persisted beyond the contraction phase and exhibited a superior capacity
for secondary effector and proliferative responses. These memory precursors were identified based on the
expression levels of the cell surface molecules Ly6c and PSGL-1 and the transcription factor T-bet. The
memory precursors were PSGL-1 Ly6c and T-bet , while the remainder of terminally differentiated
Th1 effector cells were PSGL-1 / Ly6c /T-bet . Ly6c expression is regulated by T-bet expression,
suggesting that greater T-bet signaling during priming yields a robust, terminally differentiated effector
phenotype, which exhibits a greater proliferative history during the primary response. In contrast,
moderately attenuated T-bet signaling yields smaller initial populations that are longer-lived and retain
significant proliferative capacity for secondary responses. When Kaech et al. compared the level of Tbx21
gene (encodes T-bet) expression levels between the groups at D8 and D60 post infection, they found that
Tbx21 levels were nearly identical in the Ly6c /T-bet groups at both times, and they offered this as
evidence that the transcriptional program allowing entry into Th1 the memory pool was established early
in the T-cell response. Sharing further similarity to the CD8 T-cell paradigm, the Ly6c T-bet
population eventually gives rise to a Th1 population with a central memory-like phenotype (CD62L
CCR7 ), with differential localization to the splenic T-cell zones, while the Ly6c /T-bet cells localize
to the red pulp and can potentially give rise to effector memory cells.
However, Kaech et al. noted two important distinctions between CD8 SLECs and MPECs, and Th1
Ly6c /T-bet effector and Ly6c /T-bet memory precursors. The memory pool of Th1 cells always
contains a fraction of Ly6c /T-bet cells whose frequency rapidly declines to a low but steady state.
Although the Th1 pool initially exhibits heterogeneity of CD127 expression, all cells became CD127
regardless of phenotype when adoptively transferred. When cells from the Ly6c / T-bet or Ly6c /T-
bet were separately adoptively transferred to naïve mice, they found that only the Ly6C /T-bet cells
exhibited prolonged survival and subsequently generated a subpopulation of Ly6c /T-bet cells. The
Ly6c /T-bet eventually accounted for approximately 40% of the memory cells in the absence of
antigen. Thus, they contend that Th1 memory cells may continually repopulate an effector pool in addition
to generating a central-memory-like pool. A possible mechanism was suggested by the ability of Type I
interferons to non-specifically induce Ly6C expression. They did not report the level of CD62L or CCR7
expression on the new Ly6c / T-bet effector pool generated from the transferred Ly6c /T-bet cells.
It is possible that the memory-generated pool of Ly6c /T-bet effectors was CD127 and was
responsible for the apparent conversion of Ly6c /T-bet primary cells to CD127 . Thus, it is possible
that elevated CD127 expression may still be a viable marker for memory precursors in these cells. It is
likely that the identification of CD4 memory effector precursors will dramatically expand the CD4
memory field as it did the CD8 field, and further research is necessary. To this end, it would be interesting
to investigate the role of TCR-p:MHCII avidity, dissociation rates, and CD5 expression, as discussed in
section II.B, in the generation of these recently characterized Th1 Ly6c /T-bet effectors and Ly6c /T-
bet CD4 memory precursors.
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Many groups have investigated whether true lineage-committed Tfh memory cells exist, and different
experimental models have generated conflicting results (briefly reviewed by Hale et al. ). While
examining the role of Ly6C expression in CD4 memory precursor subsets memory, Marshall et al. reported
that Tfh cells generated in their experiments exhibited functional attenuation, and it was not clear whether
the Tfh cells persisting into memory maintained lineage fidelity or regained effector functions upon
rechallenge. Contemporary studies using Listeria monocytogenes models or influenza infection in Il21-
reporter mice have suggested the CXCR5 memory Tfh population could repopulate both Th1 (CXCR5 )
and Tfh populations. Hale et al. expanded on Marshall's findings by distinguishing Th1 effector and
memory from Tfh cells based on differential expression of Ly6C, granzyme B, T-bet, CXCR5, and Bcl-6
expression. They confirmed the lineage specificity of CXCR5 /Ly6c /granzyme B /T-bet /Bcl-
6 cells as Th1 precursors and CXCR5 /Ly6c / granzyme B /CXCR5 /Bcl-6 cells as Tfh memory
precursors. These Th1 and Tfh memory cells were generated from a clonal population of SMARTA
transgenic cells and generally maintained lineage fidelity, and secondary effector functions mirrored
primary effector functions. Interestingly, both Th1 and Tfh cells exhibited demethylation of IFN-γ and IL-
21 gene loci at all time points following activation. In concert with the findings of Luthje et al., Hale et
al. also reported that Th1 memory cells predominantly formed a Th1 recall response, whereas a
considerable amount of variability was reported in the phenotype of the Tfh recall responses, with a
significant number acquiring a Th1 phenotype.
C. An Integrated Model for CD4 T-Cell Memory Differentiation
Based on the discussions in sections II.C and III.B, it is clear that, when considered separately, the current
models of T-cell memory generation cannot account for the range of phenomena reported in recent CD4 T-
cell memory literature. It is likely that multiple pathways of memory generation contribute to the range of
phenotypes and capacity for plasticity reported in the memory pool, and that complementary and divergent
developmental pathways are necessary to provide flexibility to this critical central component of the
immune system. Although data for memory in some CD4 T-cell lineages are scant, and the relationship
between certain lineages remains unclear, it is reasonable to attempt to reconcile the empirical evidence
with our guiding conceptual model of memory CD4 T-cell generation. To this end, we propose the
development of an integrated model of CD4 T-cell memory differentiation (Fig. 1). The initial framework
for this model, as depicted in Figure 1, would incorporate recent evidence that the differentiation of
memory Th1 and Tfh cells is dictated by several factors: (1) the duration and intensity of signaling
triggered by exposure to IL-2, IL-12, and IL-21, and (2) the interaction of CD4 T cells with B
cells. In this model, the exposure of activated CD4 T cells to IL-12 and varying concentrations
of IL-2 induces intermediate to high levels of T-bet and Blimp1, which in turn inhibit the expression of
Bcl-6. The increased T-bet:Bcl-6 ratio drives the generation of terminally differentiated T-bet Th1
SLECs or the T-bet MPECs, which further differentiate into Tem or potential Tcm memory cells,
depending upon the interaction with B cells. Alternatively, under IL-2-limiting conditions, exposure to IL-
21 and interactions with B cells, CD4 T cells differentiate into a plastic population of Tfh-like cells that
give rise to Tfh memory or Tcm cells. Upon subsequent exposure to antigens, cells from the Tfh, Tcm, and
Tem pools may then differentiate into Th1 effectors and Tfh effectors. It is our intention that this integrated
model of memory differentiation will account for phenotypic plasticity and will be adapted as new data
become available to address the complex relationships between additional lineages.
D. Epigenetic Basis of Memory CD4 T-Cell Features
One of the hallmarks of resting memory T cells is that their functional and metabolic quiescence is linked
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to the maintenance of a poised transcriptional state from which effector and proliferative functions can be
rapidly regained. As concisely reviewed by Youngblood et al., investigations into the mechanisms
underlying this poised state have focused on the epigenetic alterations occurring during activation and
lineage commitment. In CD4 T cells, depending on the lineage, it is likely that many key epigenetic
alterations also function to ensure lineage fidelity, to prevent detrimental gene expression, or to facilitate
the expression of previously suppressed genes. It is also likely that commonly studied epigenetic
modifications, including DNA methylation states, histone modifications, and microRNA expression, each
play an important role in T-cell memory.
Extensive investigations by Wei et al. examined paired suppressive and facilitative histone methylation
states across a range of genes in CD4 T cells, including activation-associated genes and lineage-associated
genes encoding IFN-γ, IL-4, IL-17, RORγt, and Foxp3. They found that cells expressing
lineagespecific genes tended to exhibit consistent facilitative epigenetic modification of those genes, while
the same cells did not always exhibit compensatory suppressive modification of the signature genes
typically expressed by other lineages. They reported that suppressive methylation of the interferon gamma
locus prevented IFN-γ expression in non-IFN-γ-secreting lineages; however, IL-4 was only epigenetically
suppressed in Th1 and Th17 cells, but not in Treg cells. These findings suggested that epigenetically
driven lineage specificity was limited to certain subsets of lineage-associated genes and only occurred in
some lineages. Thus, some CD4 lineages were not epigenetically prevented from expressing transcription
factors or cytokines traditionally associated with other lineages, suggesting a mechanism for phenotypic
plasticity in secondary effectors.
Building on the findings of Wei et al., subsequent studies by Hale et al. recently demonstrated that
differential epigenetic alteration of the Gzmb locus in Th1 and Tfh cells during the primary response to
LCMV was maintained in memory. This modification, Th1 Gzmb demethylation, helped maintain
lineage fidelity during the secondary response and facilitated the rapid re-expression of granzyme B in Th1
cells while suppressing granzyme B expression in Tfh cells. Youngblood et al. recently studied
competing epigenetic changes occurring during differentiation of Th1 versus Th2 cells. They found that
the interferon gamma locus in Th1 effector cells was modified by demethylation and transcription-
facilitating open histone modifications, while the locus in Th2 cells maintained transcriptionally
suppressive methylation and closed histone modifications. Concurrently, the activity of DNA
methyltransferase 1 in Th1-polarized cells results in methylation of IL-4 and FoxP3 loci, thereby
suppressing Th2 and Treg differentiation and enforcing a Th1 phenotype. These findings provide further
evidence that epigenetic modifications occurring during the primary response affect genes that are key to
determining the range of secondary effector responses available to memory cells.
Clearly, epigenetic modifications do not globally enforce all aspects of lineage-specific gene expression in
CD4 T cells, and a lack of suppressive epigenetic modification appears to confer considerable latitude for
some cell types, particularly Th17 and Tregs, to express genes associated with other CD4 lineages.
Furthermore, interesting data suggest that epigenetic changes that occur during memory development may
actually sensitize some memory cells to epigenetic modifications to which their naïve counterparts are
refractory. Investigation of Treg secondary responses in humans have indicated that naïve (CD45RA )
Tregs exhibited stable suppressive methylation of the RORC locus when stimulated under Th17-polarizing
conditions, whereas the locus was demethylated in memory (CD45RA Tregs under similar
circumstances. Thus, naïve human Tregs were refractory to in vitro Th17 repolarization, whereas
previously activated Tregs were surprisingly susceptible. As previously mentioned, the problem of lineage
infidelity and plasticity has complicated the investigation of memory in several lineages, but it has perhaps
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been most problematic with regard to the burgeoning field of Treg cells, and it is likely that epigenetic
modifications underlie a significant proportion of this plasticity. While investigations of
epigenetic modification have greatly expanded our understanding of CD4 T-cell memory and hold great
promise for expanding our understanding of the well-described lineages as well as elucidating the origins
of poorly defined memory cells lacking clear evidence of lineage commitment. Youngblood et al.
expressed concern that many epigenetic investigations utilized in vitro polarized CD4 lineages and that
these may not be representative of in vivo gene regulation. We echo these concerns and suggest that
future investigations continue to explore the dynamic epigenetic alterations occurring during primary and
secondary CD4 T-cell responses in vivo, as well as those influencing transitions between functionally
defined sets of memory cells such as Tem, Tcm, Trm, and Trcm discussed in section IV.
E. Maintenance of CD4 T-Cell Memory
The maintenance of CD4 memory cells is not completely understood, and it is likely that multiple
mechanisms differentially contribute to the proliferative renewal and homeostatic turnover of various
memory populations. Maintenance of memory CD4 T cells is dependent upon homeostatic TCR signaling
and multiple cytokines including IL-7 and IL-15. Studies using mice transgenically altered to
allow inducible TCR signaling blockade have demonstrated that homeostatic (non-specific) TCR signaling
is not required for primary effector CD4 cells to transition to memory; however, it is required for CD4
memory-cell homeostatic turnover and longevity. The mechanisms have not been fully elucidated, but it
has been reported that TCR signaling blockade during memory decreases responsiveness to IL-7
signaling. IL-7 is required during the transition from CD4 T-cell effector to memory in the SLOs
and target tissues, and again for long-term maintenance of CD4 memory. Similar to
memory CD8 T cells, memory CD4 T cells require IL-15 for long-term maintenance, and the relative
strengths of IL-7 and IL-15 signaling may significantly alter the rate of homeostatic turnover of memory
CD4 T cells and influence the proliferation of secondary responses. The sources of IL-7
signaling are incompletely characterized, but have been investigated by multiple groups using several
techniques. The cumulative evidence indicates that stromal tissues in multiple SLOs including
lymph nodes, spleen, and bone marrow produce IL-7. Clearly, memory T cells reside in numerous
additional tissues, and there is interesting evidence that at least a fraction of the memory CD4 T-cell pool
actively traffics to the SLOs for targeted interaction with IL-7–producting stromal cells. IL-15 is
produced by a variety of cells, including antigen-presenting cells, bone marrow stromal cells, and
epithelial cells in the skin and respiratory and gastrointestinal tracts, and IL-15 has been demonstrated to
elicit chemotaxis in T cells.
Combined TCR signaling and IL-7 and IL-2 cytokine signaling have also been shown to suppress pro-
apoptotic pathways during the transition to memory in human CD4 T cells. Riou et al. demonstrated that
the CD3/CD28 and IL-2/IL-7 signaling pathways induce inhibitory phosphorylation of the transcription
factor FoxO3a, thus preventing FoxO3a from activating transcription of Bim and FasL while
concurrently inducing the inhibitory phosphorylation of target STATs downstream of FoxO3a. Riou et
al. also demonstrated that the degree of inhibitory FoxO3a phosphorylation was significantly greater in the
Tcm compared to Tem, and they suggested a differential need for antiapoptotic signaling to promote the
survival of each group. FoxO3a phosphorylation is expected to reduce the induction of one of its target
gene, the CDKI p27 . Interestingly, loss of p27 prevented slow attrition in the number of memory
CD4 T cells by reducing apoptosis; however, the underlying mechanisms are unclear.
As discussed in the next section, the majority of memory CD4 T cells are maintained in the SLOs. The
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spleen appears to be the primary reservoir for circulating memory cells of all types, with progressively
fewer cells maintained in the lymph nodes, mucosa-associated lymphoid tissues, and peripheral target
tissues, respectively. A substantial fraction of memory CD4 T-cell traffic to bone marrow, where they are
maintained indefinitely and have been suggested to constitute a secondary lymphoid organ. Memory
CD4 T cells constitute up to 2% of the bone marrow and have recently been characterized as CD4
CD44 CD62L CD69 Ly6C CD49b . This finding suggests that memory CD4 T cells
are similar to the Th1 Tem memory cells, with an enhanced capacity for bone marrow homing; however,
further studies to characterize the prevailing transcriptional programs with respect to lineage-determining
transcription factors should prove instructive. While CD69 and CD49b expression on these memory cells
is reported to facilitate homing to niches containing IL-7-expressing BM stromal cells, memory
maintenance is also facilitated by CD11c dendritic cells, which may also provide antigen presentation for
secondary responses.
A mechanism for recruitment of memory cells from the bone marrow for homeostatic surveillance and
secondary responses has not been elucidated but would most likely follow venous drainage, as the bone
marrow is not drained by lymphatic vessels. Early studies of T-80 antibody-labeled helper T cells in the
tibial bone marrow of domestic sheep demonstrated a relatively high rate of egress from the marrow with
wide dissemination to SLOs under homeostatic conditions. Notably, a significant population of
marrow-origin T cells labeled by transfusion in one tibia was recovered from remote and contralateral
bone marrow samples. It is likely that this homeo-static trafficking is enhanced under inflammatory
conditions, as demonstrated for conventional SLOs. A study in a mouse influenza model demonstrated that
memory CD4 T cells recruited from SLOs to lung tissues for secondary responses include both antigen-
specific and nonantigen-specific cells. This indicates that inflammatory signaling may induce memory
cells in SLOs to traffic to target tissues, thereby enhancing peripheral immunosurveillance independent of
antigen specificity.
IV. DIVISIONS OF CD4 MEMORY
Competent memory CD4 T cells may variously be defined by the phenotype of their effector lineage,
homeostatic trafficking pattern, tissue distribution, or capacity for secondary responses. The classical
distinction between Tcm and Tem has been augmented with tissue-resident memory (Trm) and
recirculating memory (Trcm).
A. Central versus Effector Memory
The first T-cell memory classification system devised by Sallusto et al. divided the memory pool into Tcm
and Tem. Briefly, Tcm is characterized by trafficking between SLOs via the blood. Markers of Tcm
include high expression of the lymphoid homing cell-surface receptors CD62L and CCR7. These cells
have great proliferative potential and upon rechallenge their effector cytokine production favors IL-2
rather than lineage-specific cytokines. In contrast, Tem is characterized by trafficking between the spleen
and nonlymphoid tissues, arriving from the lymphoid tissues via the blood and returning via lymphatics.
CD62L and CCR7 are absent or poorly expressed by Tem while alternative adhesion molecules that
facilitated entry into nonlymphoid target tissues are up-regulated. Tem express lineage-specific
transcriptional programs and produce appropriate cytokines upon rechallenge, but tend to lack the full
proliferative potential of Tcm.
The cytokines and transcription factors linked to effector lineage commitment concurrently influence
entrance into the Tcm and Tem memory pools. There is evidence that IL-21signaling and Bcl-6 expression
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favor a Tcm phenotype, whereas Tem differentiation can be driven by the IL-2/Stat5 pathway. Even
though the surface marker CCR7 has long been characterized as a critical component underpinning the
characteristic SLO homing ability of naïve T cells and Tcm cells, it is worth noting that the actual role of
CCR7 in guiding memory T cells to the lymph nodes has been called into question.
Interestingly, in the previously discussed studies by Lohning et al. and Harrington et al., memory cells
generated by cytokine-producing progenitors were predisposed to maintaining a CD62L phenotype.
This finding suggests that cytokine-producing effector cells tend to populate the Tem pool rather than Tcm.
In the latter study, non-IFN-γ-producing Th1 progenitors exhibited a lower propensity for maintaining a
CD62L status, suggesting that memory formed by this group may enter the Tcm pool. While functional
effector cells appear to be favored for entry into the Tem, it also appears that, under some circumstances,
they may shift from the Tem pool to the Tcm pool, which appears to differentially favor the more
functional effectors. A dynamic differentiation model proposed by Schwendemann et al. suggested that
that human peripheral blood CD4 cells could differentiate from Tcm from cells within the circulating Tem
pool.
B. CD4 T Resident Memory and Recirculating Memory
Trm is a recently characterized population that lacks CD62L and CCR7 and appears to traffic to target
tissues, particularly the skin and mucosae, but does not recirculate. Originally reported in CD8 T
cells, Trm cells were characterized by their expression of the adhesion molecule CD103, a receptor
reported to facilitate their retention within epithelia. It has been challenging to apply the CD103
marker to memory CD4 T cells, as they may express it at undetectable or low levels, particularly in the
skin and mucosae. CD4 Trm cells appear to share tissue distribution with CD8 Trm;
however, they exhibit different localization within the tissues. CD4 primary effector and
effector memory cells typically localize to the dermis and submucosa, while their CD8 analogues exhibit
intraepithelial localization. Thus, CD4 cells, though present in sites complementary to CD8 Trm, they lack
the characteristic CD8 Trm marker CD103, and they have ready access back to circulation via lymphatics
and blood vessels.
Curiously, despite this relatively unrestricted access to circulation in the dermis and submucosa, and the
existence of a clearly demonstrated circulating memory pool, it is apparent that a fraction of the CD4
memory cells in these target tissue locations do not traffic back into circulation in parabiosis experiments,
and this fraction appears to represent Trm. Some authors have subsequently suggested that the large
pool of memory Treg cells in non-lymphoid organs represent a subset of the recently described CD4 Trm,
as they do not appear to recirculate.
The two tissues in which conventional CD4 Trm are most well characterized are the lung and the skin,
while relatively little is known about gut-specific Trm.
In mice, a subset of CD69 CD11a (LFA-1) CD4 memory T cells bearing transgenic TCRs
specific for influenza H1 hemaglutinin were recently demonstrated to remain in the lung following
resolution of H1N1 PR8 influenza infection. These cells preferentially trafficked to the lung when
adoptively transferred to naïve mice and did not migrate during parabiosis experiments up to 3 weeks in
duration. These cells were classified as lung-tissue memory cells and exhibited enhanced proliferative and
functional antiviral responses compared to circulating spleen-derived CD4 memory cells. A recent study
comparing Trm cells in patient-derived human skin and lung-tissue biopsies demonstrated a robust Trm
population in both tissues. Both shared surface expression patterns of Tem cells; however, VLA-1 was
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preferentially expressed in lung Trm but not skin cells. The lung cells did not express the T-cell skin-
homing marker CLA or intestinal-homing marker α4β7, suggesting that VLA-1 may be a marker for
human lung Trm. When stimulated ex vivo by microbeads coated with α-CD2, α-CD3, and
α-CD28, the lung Trm cells were capable of triple cytokine production of IFN-γ, IL-2, and TNF-α. Smaller
fractions of the lung Trm were capable of producing IL-17, IL-4, or IL-17.
The CD4 Trcm in the initial study by Kaede et al. were defined as
CD4 /CD44 /CCR7 /CD62L / CD69 / CD103 /E-selectin ligand . Bromely et al.,demonstrated
two distinct CD4 memory cell populations within the skin, while exit of Trcm from the skin was CCR7-
dependent, a Trm (CD4 /CD69 / CD103 /CCR7 ) population did not exit the skin. They noted that
some CD4 cells entering the draining lymph node were CD103 ; however, these cells were also CD69 ,
suggesting that the combination of CCR7 /CD103 /CD69 were necessary for indefinite retention within
the skin compartment. Interestingly, the Trcm population maintained homing markers for both lymphoid
tissue (CD62L/CCR7) and skin homing markers (CCR4 and E-selectin ligands). Upon ex vivo stimulation
with α-CD3 and α-CD28, the Trcm produced IL-2 and up-regulated CD40L in vitro, but did not express
cytokines IFN-γ or IL-10. The proliferative capacity was not reported, and additional studies using
antigen-specific cells would improve the characterization of this newly reported memory population.
In contrast to Trm, a recently characterized subset of memory CD4 T cells within the skin-resident pool is
also capable of actively exiting the skin and trafficking to lymph nodes or inflamed skin. It has been
suggested that this subset be non-exclusively classified as recirculating memory T cells (Trcm). It is
possible that, as the Trm pool characterization progresses, the Trcm classification may serve to distinguish
this subset from a CD8-like CD4 Trm population (CD62L /CCR7 / CD103 ), which enters but does not
exit the skin, and from the CD4 Tem population (CD62L /CCR7 /CD103 ), which enters but is not
retained in the skin. The categorization of CD4 T-cell memory by functionally and migrationally
defined subsets greatly facilitates investigation and discussion. These memory divisions are not rigid, and
pathways likely exist for transition between divisions. We expect that the divisions will continue to be
modified as new memory populations, such as the previously described bone-marrow-homing memory
CD4 T cells, are more fully characterized.
V. SECONDARY CD4 T-CELL RESPONSES
Competent memory CD4 T cells produce protective secondary CD4 T-cell responses, which are more
rapid and efficient but no less influential than primary responses. Secondary CD4 T cells can exhibit rapid
cytokine production to help recruit and orchestrate threat-specific responses. Some memory CD4 T-cell
subsets accelerate and enhance CD8 T-cell responses, while others facilitate rapid B-cell responses, and
under some conditions, the secondary CD4 T cells may even function via direct cytolytic pathways. In
contrast to the prolonged interaction required for naïve CD4 T-cell activation, memory-cell TCR-p:MHCII
interactions are rapid and efficient during a secondary encounter. A growing body of evidence suggests
that the strength and type of secondary challenge affects the generation and maintenance of CD4 T cells in
a similar capacity to the primary challenge. A strong primary response followed by a strong secondary
response appears to yield the greatest net increase in memory cell numbers, functional avidity, and
longevity. It has also been demonstrated that the frequency and nature of subsequent secondary
challenges may further shift the memory-cell phenotype from central memory to effector memory. Mueller
et al. reviewed several studies summarizing how the quick removal of antigen during infection, or
administration of single-dose peptide vaccination, tends to elicit a Tcm phenotype, while multiple repeated
infections and prime-boost protocols for peptide vaccination elicit a progressive phenotypic shift to Tem
150
148,149,157,158
+Hi Int Int −(+/−) +
+ + + −138
+ + −
−+ +
139
138,139
− − Hi
− − −
138,139
147
125,132
159
116
87
with each subsequent exposure.
Ravkov and Williams reported that the magnitude of the secondary response is strongly influenced by the
strength and length of secondary challenge, with shorter duration of antigen exposure and lower levels of
inflammation resulting in attenuated CD4 T-cell responses. They found that rapid pathogen clearance
by cytotoxic CD8 T cells impaired the ability of the CD4 cells to mount a secondary response. Their
data suggested that some memory CD4 T cells may need a duration of antigen exposure in excess of 48
hours to mount an optimal Th1 secondary response. Kim et al., subsequently reported that recovered mice
previously infected with a strain of LCMV Armstrong did not mount a significant secondary response
when rechallenged with LCMV Armstrong, but it did mount a robust secondary response to Listeria
monocytogenes genetically modified to express the LCMV peptide GP61-80 (Lm-gp61). They found a
similar but less robust augmentation of secondary expansion following primary infection with LM-gp61
and rechallenge with LCMV Armstrong. They also found that the robust secondary response to
heterologous challenge subsequently generated memory cells with higher TCR affinity and greater
turnover rates (assessed by BRDU incorporation at 75 and 200 days) compared to primary responses and
homologous rechallenge. There were no differences between groups with regard to expression levels of
CD122 or CD127, or Bcl-2. They also reported that heterologous challenge resulted in significantly greater
secondary effector and secondary memory cell generation and survival in the target organs, particularly the
liver. However, despite the strong secondary response, the size of the memory Th1 cell population
generated by heterologous rechallenge did continue to decline, though less so than the homologous
challenge. It is important to point out that the mice exposed to the homologous challenge were adequately
protected, and a costly (energetic) secondary challenge was not needed; however, the quantity and quality
of secondary memory cells did decline over time. Further, in both primary and secondary responses, the
Th1 memory cells progressively became more sensitive to antigen stimulation. The implications for these
findings are not clear. As vaccinologists commonly employ strategies using separate immunizing agents in
prime and boost vaccines, further work with heterologous challenge models is necessary to fully elucidate
the mechanisms underlying these divergent responses and provide a rational basis for future vaccine
design.
VI. CONCLUSIONS AND FUTURE DIRECTIONS
It is well established that CD4 T cells orchestrate several key aspects of the humoral and cell-mediated
immune response in a multitude of ways. CD4 T cells coordinate the interplay of innate immune cells,
humoral immunity, and cytotoxicity such that the contribution of each component is tailored to a specific
threat. This orchestration is critical as the potential threats are diverse; the most effective type of initial
response is tailored to the threat and the type of memory that will be protective is likely to also be threat
dependent. The importance of CD4 T cells in immune defense is graphically illustrated by the profound
immune deficiencies seen in human patients with HIV/AIDS as well as SIV and related viral infections in
nonhuman primates, and the need to understand CD4 T cell responses cannot be overstated.
Immunologists have made significant strides in unraveling the complexities of the CD4 T-cell response.
More recently, this has been particularly true with the advancement of our understanding of the
differentiation of distinct CD4 T-cell subsets in response to a spectrum of infectious insults. Still, the
molecular and cellular basis of CD4 T-cell memory is poorly understood, and its study is complicated by
the presence of numerous functionally distinct subsets of effectors that might differ in their phenotype,
genetic stability, half-life, maintenance requirements, and trafficking patterns, as well as their intrinsic
abilities to differentiate into memory cells. It remains unclear whether all subsets of effector CD4 T cells
differentiate into memory, and whether those that do become memory retain their lineage-defining
87
160
160
116
differentiation signatures after their transition to memory. We expect that developments such as the recent
identification and characterization of CD4 memory precursor cells in Th1 and Tfh lineages will facilitate
further investigation in this regard. It also remains to be determined to what degree various memory CD4
T cells maintain lineage fidelity between primary and secondary responses. Other important but less
understood aspects of CD4 T-cell memory are the differentiation pathways of central, effector, resident,
and recirculating memory cells, and the importance of CD4 T-cell memory in the maintenance of memory
B cells. The development of murine models using multiple concurrent gene-expression reporter constructs
could provide insights into these relationships.
Due to the sheer breadth of the CD4 T-cell memory field, the focus of this review was, by necessity,
largely limited to infectious agents generating Th1-like and complementary Tfh and Treg responses.
Numerous investigations reviewed elsewhere have also examined the role of CD4 T cells, particularly
Treg cells, in tumor immunology and immune-mediated diseases. More broadly, the role of memory CD4
T cells in diverse conditions such as immunity to helminth infection, the progression of asthma, and
immune-mediated diseases such as psoriasis have been investigated; however, the role of cross- and
auto-reactive memory CD4 T cells in immune defense and immunopathology generally remains
understudied. The field of CD4 T-cell memory is an exciting area of research, and it is expected that
emerging technologies will lead to a better understanding of the physiology of CD4 T-cell memory. In
turn, new research is expected to foster the development of novel vaccine approaches to elicit and maintain
durable and effective CD4 T-cell memory, as well as identify targets for interventional immuotherapeutics.
ACKNOWLEDGMENTS
The authors would like to acknowledge Eui Ho Kim and Erin Plisch in the Suresh Molecular Immunology
Laboratory for their helpful discussions of CD4 T-cell memory. Work was supported by PHS grants
AI048785 and AI101976 to MS. DJG was supported by the NIH Institutional Training Grant
T32OD010423, and MMT was supported by the NIH Virology Training Grant T32AI078985.
ABBREVIATIONS
Ab antibody
Ag antigen
IFN-γinterferon gamma
IL- interleukin
KO knock out
Tcm central memory T cell
Tem effector memory T cell
Tfh T follicular helper cell
Th helper T cell
Trcm recirculating memory T cell
Treg T regulatory cell
Trm resident memory T cell
WT wild type
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Figures and Tables
FIG. 1
An integrated model of CD4 T-cell memory differentiation
TH1: Exposure of CD4 T cells to IL-12 and IL-2 leads to T-bet up-regulation and subsequent TH1 cell differentiation;
while sustained interaction of CD4 T cells with DCs and varying levels of IL-2 and IL-12 signaling lead to the
differentiation of TH1 terminal effectors or TH1 memory precursors. TH1 memory precursors differentiate into TEM
cells. TFH: Sustained interaction of CD4 T cells with B cells up-regulates Bcl-6 and represses T-bet expression, which
favors TFH-cell differentiation or development of TCM cells. After pathogen clearance, the cells undergo contraction, and
the fraction of TH1 and TFH cells that survive become long-lived memory cells of TCM, TEM, and TFH memory
phenotypes. Upon secondary antigen encounter, TH1 memory CD4 T cells secondary expansion are thought to give rise to
more TH1 like 2° effector cells, while TFH memory cells are more plastic and can give rise to TH1 and TFH 2° effector
cells.
