Phenotype and Function of Human T Lymphocyte
Subsets: Consensus and Issues
Victor Appay,1*Rene A. W. van Lier,2Federica Sallusto,3Mario Roederer4
In recent years, a tremendous effort has been devoted to the detailed characterization of
the phenotype and function of distinct T cell subpopulations in humans, as well as to
their pathway(s) of differentiation and role in immune responses. But these studies
seem to have generated more questions than definitive answers. To clarify issues related
to the function and differentiation of T cell subsets, one session of the MASIR 2008
conference was dedicated to this topic. Several points of consensus and discord were
highlighted in the work presented during this session. We provide here an account of
these points, including the relative heterogeneity of T cell subpopulations during infec-
tions with distinct pathogens, the relationship between phenotypic and functional T
cell attributes, and the pathway(s) of T cell differentiation. Finally, we discuss the
problems which still limit general agreement.
Published 2008 Wiley-Liss, Inc.y
? Key terms
phenotype; function; T cells; virus
THE differentiation of naı ¨ve T cells into effector and memory subsets represents one
of the most fundamental facets of T cell mediated immunity. Initial descriptions por-
tray effector T lymphocytes as cells found in settings of active antigenic stimulation
(e.g., during primary viral infection), able to eliminate viruses or tumors by different
effector functions; in contrast, memory T lymphocytes are cells which remain present
in the absence of antigenic stimulation and have the capacity to expand rapidly upon
secondary challenge (1). However, beyond the apparent simplicity of these original
operational definitions lies a complex and controversial classification of an increasing
number of T cell subsets. The simultaneous measurement of a variety of surface and
intracellular markers enables the distinction between a multitude of T cell subsets
(2), particularly in humans. In recent years, a tremendous effort has been devoted to
the detailed characterization of the phenotype and function of these distinct T cell
subpopulations, as well as their pathway(s) of differentiation and their role in
immune response. But these studies seem to have generated more questions than de-
finitive answers, as no general consensus has yet been reached. For the non-expert
eye, the multiplicity of reports and the inherent contradictions between models
represents an important cause of confusion and even skepticism as to the significance
of distinct T cell subsets and their role in immunity. This is counter-productive for
developing a unified model of T cell immunity as well as for conducting meaningful
and comparable studies.
To clarify issues related to the function and differentiation of T cell subsets, one
session of MASIR 2008 was entirely dedicated to this topic. Four experts, who have
been working in the field of human T cell immunity, were invited to present their
views, opinions, and data on the subject. Rene van Lier pioneered the description of
human CD8 T cell subpopulations that could be divided into naı ¨ve, memory, and
effector subsets based on the expression of cell surface receptors (CD27 and
1Cellular Immunology Laboratory,
INSERM U543, Avenir Group, H^ opital
Piti? e-Salp^ etri? ere, Universit? e Pierre et
Marie Curie-Paris6, 75013 Paris, France
2Department of Experimental
Immunology, Academic Medical Center,
Amsterdam, Meibergdreef, 15, 1105 AZ,
Amsterdam, The Netherlands
3Institute for Research in Biomedicine,
Via Vincenzo Vela 6, CH-6500 Bellinzona,
4Vaccine Research Center, National
Institutes of Health, Bethesda, Maryland
Received 2 April 2008; Revision Received
12 June 2008; Accepted 11 August 2008
*Correspondence to: Victor Appay,
Cellular Immunology Laboratory,
INSERM U543, H^ opital Piti? e-Salp^ etri? ere,
Published online 10 September 2008 in
Wiley InterScience (www.interscience.
Published 2008 Wiley-Liss, Inc.y
yThis article is a US government work
and, as such, is in the public domain in
the United States of America.
Cytometry Part A ? 73A: 975?983, 2008
CD45RA) (3). Federica Sallusto originally proposed a classifi-
cation of T cells into central and effector memory (distin-
guished according to the surface expression of CCR7 and
CD45RA), providing an important conceptual advance in
terms of T cell dynamics and compartmentalization (4). Vic-
tor Appay provided a comprehensive description of virus spe-
cific CD8 T cell populations placed along a pathway of differ-
entiation (from early to intermediate to late differentiation)
based on the expression of CD27 and CD28 (5). And finally,
Mario Roederer pioneered the use of polychromatic flow cyto-
metry, a necessary tool to precisely study the phenotype and
understand the function of T cell subsets (6).
Several points of consensus emerged from the work pre-
sented by the different speakers, particularly regarding the het-
erogeneity of T cell subsets and the link between phenotype
and function. But a number of issues were also highlighted
concerning the pathway of T cell differentiation and the rela-
tionship between T cell subset and functional efficacy. Here,
we summarize these points of consensus and remaining issues,
and draw attention to problems that limit general agreement
and the development of a unified model of T cell immunity.
Relative Heterogeneity of T Cell Subpopulations
and Relationship Between Phenotypic and
The T cell population can be divided into distinct subsets
based on their phenotype, i.e. the expression of diverse cell
surface receptors. The most-commonly used markers are
CD45RA (or CD45RO), CCR7, CD27, and CD28. Beyond the
precise identification of naive T cells (CD45RA1CCR71
CD271CD281), the differential expression of these four
molecules allows the distinction between numerous subsets of
‘‘resting’’ (referring to cells that are not involved in primary or
acute infection phases) antigen-experienced T cells. The analy-
sis of new cell surface molecules often results in the identifica-
tion of an increasing number of subpopulations; one may
even find as many T cell subpopulations as there are combina-
tions of markers. This could be a reflection of the large hetero-
geneity of CD4 and CD8 T cell subsets. However, it is essential
to notice that the expression of a surprisingly large number of
markers significantly overlap or associate with each other (6–
24), as summarized in Figure 1. Although such overlap is not
strict, general phenotypic profiles or patterns clearly emerge
within the heterogeneity of the T cell population. For instance,
CCR71CD45RA2CD271CD281 CD81 T cells, referred to
as central memory CD8 T cells, express low levels of molecules
like CD57, PD-1, and CX3CR1 but high levels of CD7, IL-7R,
and CD62L, in contrast to CCR72CD45RA1CD272CD282
CD8 T cells, referred to as highly- or late-differentiated cells.
Since the various receptors and molecules analyzed are
involved in different cellular functions, general T cell profiles
or subsets are associated with a given set of attributes. Several
commonly used markers include a range of receptors involved
in T cell activation (e.g., CD45RA or CD45RO), costimulation
(e.g., CD27 and CD28) or regulation (PD-1). Differences in
homeostatic maintenance are implicated by the variation in
expression of either cytokines (e.g., IL-2) (3,4) or cytokine
receptors (e.g., IL-7R) (20,21). In addition, the expression of
some chemokine receptors (e.g., CCR7 and CX3CR1) (4,17)
as well as adhesion molecules (e.g., CD11a and CD62L) also
seem to follow a common pattern.
Distinctions in effector functions are reflected by the
expression of different intracellular molecules. For instance,
granzyme K production is a trait of CCR72CD271CD281
CD8 T cells, whereas granzyme B production is predominant
in CCR72CD272CD282 CD8 T cells (25,26). Distinct CD8
T cell subsets have also been reported to have different capa-
city to produce cytokines like IL-2 or IFN-c (Fig. 1) (3). Func-
tionally distinct CD4 T cell populations can also be subdivided
according to the expression of chemokine receptors (Fig. 2A).
For instance, CCR5 and CXCR3 expression discriminates CD4
T cells with a TH1 cytokine profile, while CCR3, CCR4, and
CRTh2 expression identifies CD4 T cells with a TH2 cytokine
profile (27). CXCR3 and CCR4 are expressed on distinct sub-
sets of CCR71 central memory CD4 T cells, with CXCR31
and CCR41 subsets representing pre-TH1 and pre-TH2 cells,
respectively (28). Recently, the expression of CCR6 and CCR4
have been reported to characterize a homogeneous population
of CD4 T cells that produce IL-17 but not IFN-c in humans,
referred to as TH17 (29,30). In contrast, expression of CCR6
and CXCR3 identifies a heterogeneous population composed
of TH1 cells and cells producing both IFN-c and IL-17 (29,30).
It should be noted that the broad correlation between
phenotype and cytokine production patterns may not be par-
ticularly strong when considering antigen-specific T cell
responses. For example, Duvall et al. measured five different
functions (IL-2, TNF, IFN-c, and MIP1b production as well as
degranulation) on CD4 and CD8 T cells specific for HIV-2, in
concert with the phenotypic markers CD45RO, CD27, and
CD57 (31) to identify nearly a dozen phenotypically distinct
subsets of T cells. There was remarkably little heterogeneity in
the functional profile of these subsets. The strongest associa-
tions (with putative differentiation) was the loss of IL-2 pro-
duction coupled with the gain in MIP1b production and
degranulation among CD4 T cell subsets—with little differ-
ence in the fraction of HIV-2 specific T cells producing IFN-c
or TNF after stimulation. Within HIV-2 specific CD8 T cells,
there was very little difference in the functional capacity when
comparing cells across a wide swath of phenotypes.
Different T cell subsets can also be characterized by differ-
ent lengths of their telomeres, which implies different replica-
tive histories as well as proliferative potentials (19,32,33). Of
note, the expression of CD57 on the cell surface shows a
strong relationship with telomere length, in that CD571 T
cells have the shortest telomeres (18,32)—implying that these
cells have divided the most and have the least proliferative
potential amongst the T cell subsets. Overall, the association
between distinct subsets and the expression of surface recep-
tors and intracellular molecules implies that these T cell sub-
sets exhibit differential requirements for stimulation and sur-
vival, homing potential (e.g., to lymphoid organs or to pe-
ripheral tissues) and some (immediate) effector functions.
976 Phenotype and Function of Human T Lymphocyte Subsets: Consensus and Issues
Different Pathogens and Distinct T Cell
Although a common feature of the immunity against
infections with pathogens is the central role played by CD4
and CD8 T cells, it has become clear that quite distinct profiles
of T cell responses are established for generating memory or
maintaining latency to different pathogens. T lymphocytes
specific for a virus exhibit some degree of heterogeneity;
Figure 1. Phenotypic associations within CD8 T cell subsets in humans and relationship with functional attributes. Five distinct subsets of
circulating CD8 T cells are defined according to the expression of CD27, CD28, CCR7, and CD45RA. Relative telomere length and expression
of a variety of cell surface receptors and intracellular molecules (related to T cell activation, costimulation, regulation, homeostasis, hom-
ing potential, and functional capacities) are illustrated in these subsets in a ‘‘resting’’ state according to data from the literature. The com-
mon phenotypic distribution of virus specific CD8 T cells is also depicted, after clearance of the virus (Flu) or in latent infection stages (for
HCV, EBV, HIV, and CMV). [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]
Cytometry Part A ? 73A: 975?983, 2008977
however, antigen-specific CD8 T cells display unique profiles
depending on their viral specificity: Cells are predominantly
CD271CD282 or CCR72CD272CD282 during latent
infection with HCV, EBV, HIV, or CMV, respectively (5). Fol-
lowing the infection with cleared viruses such as influenza or
RSV, virus-specific CD8 T cells appear predominantly
CCR71CD271CD281 (34,35). Quite strikingly, the pheno-
typic profile of CD4 T cells specific for these viruses are also
present with very similar distributions (36–40). Although the
reasons for the associations between viruses and T cell pheno-
type remain unclear, a likely role for dictating their profile will
be the level and quality of stimulation, which differ between
distinct infection settings. Indeed, the antigen load and recur-
rence, costimulation, and cytokine environment have been
shown to influence the phenotype of resulting T cells
Beyond the T cell phenotype, interesting associations
between the functional attributes of CD4 or CD8 T cells and
different pathogens have been reported in recent years. In
keeping with the observation made on the CD8 T cell pheno-
type, EBV-specific T cells express high levels of granzyme K
but not B, whereas CMV-specific T cells abundantly express
granzyme B, but little K (RVL, unpublished data). This latter
phenotype is of functional significance as CMV-specific T cells
can execute direct cytolysis ex vivo in a granule exocytosis-
dependent fashion. Of particular interest, CD4 T cells that
lack CD28 expression and display cytolytic potential (43)
emerge after primary CMV infection (44). Moreover, in a
group of healthy adults, CD4 T cells specific for Candida albi-
cans were found primarily in the CCR61CCR41 TH17 subset
whereas CD4 T cells specific for M. tuberculosis were present
in the CCR61CXCR31 TH1 subset (29). The elicitation of IL-
17 responses correlated with the finding that hyphae of C.
Figure 2. Phenotypic dissection of human CD4 T cells into functionally distinct subsets. (A) The expression of chemokine receptors is asso-
ciated with CD4 T cell subpopulations presenting distinct THcytokine profiles. (B) The expression of markers, commonly used to define
CD8 T cell subsets, enables also the distinction between several CD4 T cell subpopulations, including CD4 cytotoxic T cells.
978 Phenotype and Function of Human T Lymphocyte Subsets: Consensus and Issues
albicans primed TH17 responses in vitro and induced IL-23
but not IL-12 production in human dendritic cells. Most
likely, these distinct T cell profiles may reflect differential
requirements for effective cellular immune responses required
to control different pathogens. Viruses differ in cellular tro-
pism, replication kinetics and other biological properties (e.g.,
immune evasion mechanisms). The immune system has
adapted to these specific traits by mounting T cell responses
that appear to be highly adapted to individual pathogens.
The ability to simultaneously measure multiple different
T cell functions reveals another level of complexity. Expression
of different cytokines is not necessarily correlated; thus, when
evaluating the expression of 3 cytokines (e.g., IL-2, TNF, and
IFN-c), each of the seven combinations of coexpression of
these three functions can be identified by polyclonal stimula-
tion of T cells. Antigen-specific responses may be restricted to
a subset of these combinations. This property of T cells, dis-
tinct from their frequency (magnitude of the response) and
phenotype has been referred to as the ‘‘quality’’ of the response
(45). It is becoming clear that the T cell quality of an antigen
response is associated with clinically relevant parameters. The
study of this association is still in its infancy; thus, it remains
open as to what would comprise the best quality for control-
ling any given pathogen, and that different pathogens may
require different combinations of the optimal types of T cells
(different qualities). Nonetheless, a number of studies from
successful vaccines, HIV pathogenesis, and protection against
parasitic infection demonstrate a common thread: For these
instances, ‘‘better’’ quality can be defined as a higher represen-
tation of polyfunctional T cells (those cells that simultaneously
make all or a majority of measured functions). Specifically,
when comparing the HIV-specific T cell response among HIV-
infected, clinically defined progressors or long-term nonpro-
gressors, there is a significantly better quality of the CD8 T cell
response from the latter group (46,47). Similarly, in indivi-
duals infected with HIV-2 (a far less pathogenic virus than
HIV-1), the antigen-specific T cells are of better quality than
in typical HIV-1 infected adults (31). For viral infections that
are well-controlled or cleared (e.g., CMV, vaccinia), the quality
of the response is among the most polyfunctional that has
been measured (48).
Alteration of T Cell Attributes upon Activation
It is important to note that these observations and rela-
tionships between T cell phenotype and functional attributes,
as well as between T cell profile and pathogen have been estab-
lished in the context of resting cells, that is to say, for cells that
are not actively stimulated (e.g., by cognate antigen). Many of
these observations do not hold in a setting of T cell activation
or inflammation. Upon activation, many T cell attributes do
indeed change rapidly, such that activated T cells will behave
differently from their resting state. For instance, during the
acute response to CMV, EBV, and HIV, activated CD8 T cells
can be found in the circulating pool that displays a relatively
‘‘early’’ memory phenotype (i.e., CCR72CD281CD271) yet
these cells abundantly express granzyme B and are highly cyto-
lytic (5,49). In this respect the differentiation of virus-specific
T cells in humans seems to parallel that in mice, in which dif-
ferent memory populations seem to form from a relatively
uniform population of acutely expanded effector cells (50). T
cell regulation is also dependent on antigenic stimulation, as
seen with PD-1, which is upregulated on the surface of CD8 T
cells undergoing activation (24), as a likely mechanism to
control the proliferation and apoptosis of activated cells (51).
In addition, modulation of chemokine receptor expres-
sion occurs upon activation, which implies changes in migra-
tory properties of T cell subsets (52,53). In inflammatory set-
tings, the T cell environment is also altered, which can result
in further changes of T cell behavior. For instance, T lympho-
cytes lacking the lymph node-homing receptors L-selectin and
CCR7 do not migrate to lymph nodes in the steady state (4).
Nonetheless, studies in the mouse have revealed that inflam-
matory or reactive lymph nodes (i.e., draining sites of mature
dendritic cells) can recruit L-selectin-negative CCR7-T cells.
This inflammatory pathway of cell recruitment in lymph
nodes requires CXCR3 or CD62P expression on CD8 or CD4
T cells, respectively [FS, unpublished data and (54)]. In reac-
tive lymph nodes, recruited T cells establish interactions with
dendritic cells to trigger their maturation (CD4 T cells) or kill
them (CD8 T cells). The inducible recruitment of distinct
blood-borne T cell subsets to lymph nodes may represent a
mechanism for regulating the ability of dendritic cells to acti-
vate naive CD4 and CD8 T cells and therefore the immune
Differentiation Pathways of CD8 and
CD4 T Cell Lineages
Although a number of congruencies with regard to the
characterization of T cell subsets have been identified, central
points regarding the differentiation and the role of these sub-
sets remain unresolved. The pathway of T cell differentiation,
i.e. the sequence of development of the different T cell subsets,
remains elusive in humans. Indeed, it is unclear if the differen-
tiation pathway is linear or branched, one-way or reversible.
Data on telomere length, which may be one of most informa-
tive markers of replicative history, supports a linear pathway
of differentiation (see Fig. 1). Moreover, a seminal study in
nonhuman primates provides further clues. SIV-infected
monkeys were treated with BrdU in order to follow the differ-
entiation of antigen-specific T cells. There was a clear pro-
gression of labeled cells, starting from CD281CCR71
CCR52 (‘‘central memory’’), to CD281CCR72CCR52 or
CD281CCR71CCR51 (‘‘transitional memory’’), and then to
CD281CCR72CCR51 (‘‘effector memory’’) T cells; CD28-T
cells appeared as terminally-differentiated and represent the
Following antigen priming, naı ¨ve T cells eventually give
rise to a heterogeneous population of antigen-specific T cells
as seen in vitro (32) and recently in vivo (56); these studies
suggest that differentiation is branched and that reversions
from one subset to previous can occur. Concerning branched
Cytometry Part A ? 73A: 975?983, 2008 979
differentiation, studies in mice have shown that the loss of
CD27 expression from activated T cells seems to be specifically
induced after interaction with its ligand CD70 (57). In both
mice and humans, expression of CD70 is predominantly
found on activated immune cells under TH1 conditions (58).
The vast number of CD272 CD4 and CD8 T cells in latent
CMV infection might be a reflection of the fact that CMV
(re)activation induces upregulation of CD70 (42). However,
different pathogens may preferentially induce other costimula-
tory ligands and/or cytokines which will lead to T cells with
different attributes, in a branched differentiation manner.
Along the same line, our understanding of CD4 T cell dif-
ferentiation remains rather ambiguous. Although CD8 T cells
have been extensively characterized, as exemplified in Figure 1,
CD4 T cells represent a particular complex population, whose
multiple facets have been difficult to grasp. CD4 T cells have
originally been divided according to distinct helper functions
into TH1 and TH2, and lately into TH17 (Fig. 2A). In recent
years, a subpopulation of CD4 T cells has also been shown to
have suppressive properties, and are referred to as regulatory
T cells (TREG). The expression of markers used to dissect the
CD8 T cell population (e.g., CD45RA, CCR7, CD27, CD28),
also enable the distinction between several CD4 T cell subsets
(Fig. 2B). Using these markers, a number of similarities
emerge between CD8 and CD4 T cells, in terms of phenotype,
functional attributes, telomere shortening as well as gene
expression profiles (43,59,60). Strikingly, the subset of CD4 T
cells characterized by a CCR72CD272CD282 phenotype has
strong cytolytic capacities—a function largely associated
with CD8 T cells. The presence of these cells is usually
observed in particular settings like CMV or HIV infections
(43,44), although their role remains unknown to date.
Reconciling these different facets of CD4 T cells and inte-
grating them in a single pathway of differentiation represent
Correlation Between T Cell Attributes and Efficacy
An important issue is the absence of association or corre-
lation between the phenotype of T cells and their protective
efficacy in vivo. A potential link between failed T cell efficacy
and an immature phenotype was initially suggested in that
HIV-specific CD8 T cells show a CD271CCR72CD45RA2
phenotype in contrast to CMV-specific CD8 T cells (character-
ized by a CD272CCR72CD45RA1 phenotype) (61,62)
under the assumption that CMV-infection is well-controlled.
However, subsequent studies showed no consensus on this
theory: HIV-specific CD8 T cells associated with superior
control of HIV were also characterized by a CD271
CCR72CD45RA2 phenotype (47,63); and in the setting of
CMV disease, the majority of CMV-specific CD8 T cells dis-
played also a CD272CCR72CD45RA1 phenotype (64).
Instead, T cells presenting phenotype characterized with the
expression of CCR7 or CD28 were shown to be potentially
more efficient at mediating protection in different settings
(65–68). Today, the interpretation of phenotypic analysis in
relation to T cell efficacy remains ambiguous.
As noted above, polyfunctional T cell representation was
positively associated with better clinical outcome (in HIV-1
and HIV-2 infection); similarly, polyfunctional T cells are
much more prevalent for viral infections that are completely
or well-controlled (vaccinia, CMV). Although these measure-
ments provide a correlate, a recent study of a mouse model of
L. major infection demonstrates that the quality of the T cell
response is predictive of control following challenge (69).
Using a variety of vaccine regimens, mice with similar magni-
tudes (and phenotypes) of antigen-specific T cells but with
dramatically different functional qualities were challenged
with live parasites. Mice with the most polyfunctional T cell
response showed the best protection whereas those with abun-
dant but monofunctional antigen-specific T cells (producing
only IFN-c) were not protected. This study highlights the im-
portance of functional measurements in determining potential
clinical benefit of vaccines or therapeutics. A final aspect of
this study showed that the most efficacious T cells (in terms of
production), which were the most polyfunctional, produced
high levels of cytokine on a per-cell basis. In fact, each poly-
functional T cell produced ?10 times as much IFN-c as
monofunctional T cells (69). Thus, in addition to having the
greatest repertoire of functions, these cells are optimized for
carrying out those functions. Importantly, these cells were
CCR72: suggesting that the most desirable population to be
elicited by a vaccine may be an ‘‘effector memory’’ phenotype
population producing IL-2. Given the dogma that CCR72 T
cells make little IL-2, this finding underscores the confusion in
the literature and the need for a revision of the model.
In summary, there is now a growing body of evidence
that the quality of the T cell response is a correlate of protec-
tion against viral infection. Although the magnitude and the
phenotype of T cell responses will certainly provide additional
information about the overall T cell response, these aspects
have not yielded any clinical correlates.
PROBLEMS LIMITING GENERAL UNDERSTANDING
Further understanding of T cell immunity requires that
such key issues on differentiation pathways or T cell efficacy
should be solved at once. Further work and discussion are
therefore needed, based on the completion of comparable and
meaningful studies. However, this faces a number of hurdles,
some of which are highlighted below.
Need for Consensual Nomenclature
Of utmost importance, there is no harmonization of no-
menclature. Even basic terms like ‘‘memory,’’ ‘‘activated,’’ and
‘‘effector’’ have different meaning in the literature. Memory T
cells may be defined as cells that have seen or been primed
with an antigen (persistent or not), but one may argue that
memory T cells are only found in the absence of antigen. Acti-
vated T cells are sometimes referred to as cells that are simply
no longer naı ¨ve (having been activated at some point by anti-
gen), and are also referred as cells that have been very recently
stimulated with an antigen (and, for example, may be entering
mitosis). Effector T cells can be cells present during the
980 Phenotype and Function of Human T Lymphocyte Subsets: Consensus and Issues
primary or secondary phases of an infection, when fighting to
halt active viral replication, or they can simply be cells which
display effector functions ex vivo (like IFN-c secretion or per-
forin content). Much of the confusion is semantic, that is to
say related to how these terms are understood and used.
Beyond this point, the use of markers to define given subsets
also belies some anarchy. For instance, so-called central mem-
ory T cells have been defined in the literature, from mice to
primates to humans, based on the positive expression of
CCR7 or CD62L or even CD27 or CD28. In humans, effector
T cells are commonly identified to cells that are CD272 and/
or CD45RA1 ‘‘revertant’’, expressing perforin or producing
IFN-c, or expressing low amounts of Bcl-2. Although it is true
that some overlap exists between a number of receptors and
molecules expressed by a given subset (as seen earlier), this
overlap is not strict, and approximation can easily result in
inaccuracy, leading to further lack of consensus when compar-
ing studies. This is particularly true when comparing across
species, where expression patterns may not be conserved. It is
therefore necessary to have reliable definitions for these terms.
Need for Comprehensive Studies and Interpretation
Further efforts need to be devoted to the way studies are
conducted and interpreted to avoid short comings. Lack of
standardization in experimental procedures and technical dif-
ferences (e.g., reagents, kinetic of stimulation, fresh versus fro-
zen materials) can be a source of discrepancy in results. In this
context, the MASIR meeting offers a strong ground for discus-
sions and validations of state-of-the-art flow cytometry based
assays, which is indispensable to deconvolute the complexities
of the T cell immune response. For instance, accurate assess-
ment of T cell cytolytic capacity through measurement of per-
forin production or FATT-CTL assay (see the articles by Betts
and coworkers (70) or van Baalen (71), respectively, in the
present issue of Cytometry) can only benefit the functional
characterization of T cells. Techniques that allow satisfactory
detection of subdominant or low avidity CD81 T cell popula-
tions (see the article by Price and coworkers (72) in the pres-
ent issue of Cytometry) will help us understanding the true
role of these cells, which is often overlooked. New insights
into CD41 T cell subset differentiation and function (as pro-
posed by Kern and coworkers (73) in the case of Mycobacter-
ium tuberculosis infection) implies the use of improved meth-
ods to identify accurately antigen specific CD41 T cells; these
include the use of MHC Class II tetramers or CD154 analysis
(see the articles by Casorati and coworkers (74) or Thiel and
coworkers (75), respectively.
Beyond simple technical considerations, there has also been
a lack of distinction between activated and resting T cells in
most models; however, as mentioned earlier, although these cells
may present a similar phenotype, their specific attributes can be
significantly different. In humans, longitudinal studies of T cell
responses (e.g., from primary infection onwards) are rare (for
practical reasons) so that distinct subsets of resting cells are usu-
ally compared with each other at a given time point. In contrast,
in mice, studies of T cell subsets are mostly performed in a longi-
tudinal manner, and activated (i.e., during primary infection)
versus resting (i.e. later) cells are usually compared. This explains
why in mouse studies, the definition of effector T cells is mainly
related to the timing of their appearance (i.e. during primary
infection), whereas in human studies, effector cells are usually
thought of more in terms of their functional characteristics
(such as their ex vivo cytotoxic potential). It is also important to
consider that infections with different pathogens represent dif-
ferent settings (as discussed earlier), for which comparing re-
spective immune responses may not always be as straightforward
as it seems. What is observed in one system is not necessarily
valid in another system, and different requirements in terms of
T cell efficacy may potentially be involved. Last but not least,
observations made in the human system do not necessarily apply
to the mouse system, and vice versa. It is clear that undue extra-
polation and generalization of findings across models and condi-
tions is a problem, which can be a major source of confusion.
Full understanding of T cell immunity will require making every
effort to perform longitudinal studies in humans, and to take in
consideration changes of T cell attributes upon activation and
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