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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
J Immunol. Author manuscript; available in PMC Dec 4, 2009.
Published in final edited form as:
PMCID: PMC2788825
NIHMSID: NIHMS156932

Increasing the CD4+ T Cell Precursor Frequency Leads to Competition for IFN-γ Thereby Degrading Memory Cell Quantity and Quality1

Abstract

The precursor frequency of naive CD4+ T cells shows an inverse relationship with the number of memory cells generated after exposure to cognate Ag. Using the lymphocytic choriomeningitis virus (LCMV) model, we show here that only when the initial number of naive virus-specific CD4+ T cell precursors is low (≤104 per spleen) do they give rise to abundant and homogeneous memory cells that are CD62Llow, IL-7Rhigh, and imbued with an enhanced capacity to produce cytokine, proliferate, and survive over time. Furthermore, memory cells derived from a high naive precursor number show functional deficits upon secondary exposure to virus. The negative effect of higher naive precursor frequency was not attributable to competition for limiting amounts of Ag, because LCMV-naive CD4+ TCR-transgenic CD4 T cells were recruited into the LCMV-induced response even when their initial number was high. Instead, the T cells appear to compete for direct IFN-γ signals as they differentiate into memory cells. These results are consistent with a model of T cell development in which the most fit effector T cells that receive sufficient direct IFN-γ signals are selected to differentiate further into memory cells.

We and others have used the lymphocytic choriomeningitis virus (LCMV)3 model to estimate that, for a given MHC class I or class II epitope, there are ~100 naive Ag-specific CD4+ or CD8+ T cells in the mouse spleen (1, 2), and a similar frequency has been reported for influenza virus-specific naive CD8+ precursors (3). Brief exposure of these naive cells to cognate Ag (46) triggers an intrinsic developmental program that alters cell quantity and quality: the cells proliferate and differentiate into a large effector cell population that subsequently diminishes in size until a stable population of memory cells is established. In most models, the numbers of CD4+ and CD8+ memory cells remain relatively stable over extended periods of time (months/years). Reflecting the above, the T cell response is routinely described as having three separate phases: expansion, contraction, and memory. However, it is now clear that there is extensive overlap between the phases, and that memory cell differentiation begins during the expansion phase of the primary immune response (7). Even a brief encounter with cognate Ag is sufficient to trigger the entire developmental program of CD4+ (8) and CD8+ T cells (46). There are two models of memory cell development. The first model holds that memory T cells are a separate lineage from effector cells, and that the latter are short-lived. In this model, some of the naive precursors are induced to differentiate directly into memory cells, while the rest differentiate into effector cells; the latter die, and the former survive. However, several lines of evidence support a second model, which suggests that T cell differentiation is linear, with all memory cells having passed through the effector stage (911). Memory T cell precursors—identified by elevated expression of CD127 (the IL-7R)—can be found within the pool of effector cells at the peak of the response (1215), but this does not strongly discriminate between the two models. Regardless of which model (if either) is correct, it is now generally accepted that memory cell differentiation begins early; if not immediately upon Ag encounter, then certainly sometime during the primary response.

As noted above, appropriate Ag contact causes naive T cells to change in both quantity and quality. The number of memory CD8 T cells present long after acute infection is thought to be related to the burst size of the response: a larger primary response correlates with greater numbers of memory cells (7, 16). The magnitude of the primary CD4 response (17) and the number of CD4 and CD8 memory T cells are affected by the longevity of Ag (1821); although some evidence indicates that CD4 memory is unaffected by abbreviating the early exposure of T cells to Ag (22). It has been proposed that Ag competition is a defining feature of T cell regulation, and that the size of the Ag-specific T cell pool is constrained by the availability of Ag-loaded APCs (2328); this competition for Ag will increase later in the response, as Ag levels decline and T cell numbers ascend. Consistent with this idea, increasing the number of CD8 precursors by giving mice OT-1 TCR-transgenic cells to create greater levels of intraclonal competition led to a diminished endogenous response to recombinant Listeria monocytogenes (rLM)-OVA (26). A similar finding was reported for the endogenous gp33 response in mice containing P14 CD8+ T cells (29). When intraclonal competition was reduced by giving mice peptide-coated DC, there was an increase in the number of primary cells. CD4 T cells responding to rLM-OVA or peptide immunization compete with one another during the expansion phase, suppressing cell division and cytokine production (24, 27). Recent data suggest that intraclonal competition may also affect T cell memory, including the lineage commitment of memory CD8+ T cells (25) and the survival of memory CD4+ T cells (30).

The number of effector cells and of memory T cells can be increased by cytokines, for example, IL-2 (4, 31, 32), IL-7 (1215), and IL-15 (33, 34). Memory cell abundance is also enhanced by the presence of IFN-αβ (35, 36) and IFN-γ (3739); although some reports suggest that these cytokines are inhibitory to memory cell number, perhaps by “programming” T cells to undergo contraction (40, 41). Some of these regulatory molecules (IFN-γ, IFN-αβ, IL-1β) are made by cells of the innate immune system, and this, along with the recent findings that TLR signals enhance T cell responses (42), links innate immune responses with memory cell abundance. IFN-γ and IL-2 also are made by responding T cells, providing a mechanism by which T cell burst size can impact long-term T cell memory.

Evaluating the quality of memory T cells is more complex than their enumeration, in part because so many different criteria can be measured. Although CD8 T memory cells do develop in the absence of CD4+ T cells, their quality is defective: their survival is foreshortened, and they differ in their protective function (4347). The “helpless” CD8+ memory cells differ epigenetically from their “helped” counterparts (48). It is not clear whether the helpful effects of CD4+ T cells are administered early in the CD8+ T cell response (49), or during the maintenance phase of the CD8 T cell memory (50), but early events can be important: exposure to IL-2 during priming affects long-term memory CD8 T cell function (51), consistent with the naive cells (or their immediate progeny) being “programmed”. However, memory cell differentiation appears to continue even after the peak of the primary response; memory cells show functional improvements and change their patterns of gene expression over the ensuing weeks (52). These later events appear to affect only the quality of the memory cells and not their number. It is speculated that these changes are related to homeostatic cell division and survival, or to the cytokines that regulate homeostasis.

Most of the above studies focused on CD8+ T cells, which differ from CD4+ T cells in their activation requirements, and in the kinetics and size of the response, suggesting that the rules governing memory establishment may differ between the two cell types. In this study, the primary and memory CD4 responses to LCMV were compared in mice containing different numbers of naive precursor CD4+ T cells. We find that clonal competition during and after the expansion phase diminishes the number and functional quality of memory cells, and that the competition is dependent on the key antiviral cytokine IFN-γ.

Materials and Methods

Mice

C57BL/6J mice were purchased from The Scripps Research Institute (TSRI) Rodent Breeding Facility and used when 6–8 wk of age. IFN-γR-knockout (KO) mice, which are deficient in IFN-γR1, were purchased from The Jackson Laboratory. SMARTA-transgenic mice produce CD4+ T cells with a TCR that is Vα2+ and Vβ8.3+ and which is specific for the LCMV-gp61–80 epitope presented by I-Ab (53). These mice were bred to B6.Ly5a mice to generate SMARTA.Ly5a mice or to B6.PL mice to generate SMARTA.Thy1.1+ mice (2). SMARTA mice were mated to IFN-γRKO mice to generate SMARTA/IFN-γRKO mice. Between 6 and 8 wk of age, C57BL/6J mice were infected i.p. with 2 × 105 PFU of LCMV-Armstrong-3e. Where indicated, some mice containing memory cells were challenged i.v. with a greater amount, 2 × 106 PFU of LCMV-Armstrong, to better stimulate the memory cells. All mouse studies were approved by TSRI Institutional Animal Care and use Committee.

Adoptive transfers

Single-cell suspensions of spleens cells from LCMV-naive SMARTA mice were counted, and defined numbers of Vα2+, Vβ8.3+, CD4+ donor cells were injected i.v. in a volume of 0.9 ml of RPMI 1640. The number of donor cells found in the spleen several days posttransfer—the “take”—is ~10% of that transferred into the mice. Therefore, the number of SMARTA cells referred to in the text is 10% of the number injected. Mice were infected 4–7 days after cell transfer. In the rechallenge experiments, CD4 T cells were purified by positive selection with magnetic beads using a kit from StemCell Technologies.

Flow cytometry

Single-cell suspensions of spleen cells were surface stained using Abs from eBioscience that were specific for CD4 clone RM4–5, CD8 clone 53–6.7, Ly5a (Ly5.1), clone A20, CD44 clone IM7, and CD62L clone MEL-14. Anti-Vα2 clone B20.1 and anti-Vβ8.3 clone 1B3.3 were purchased from BD Pharmingen. For intracellular staining, cells were cultured in the presence of brefeldin-A and gp61–80 for CD4 T cells or gp33–41 for CD8 T cells or no peptide. Intracellular cytokines were detected using eBioscience Abs specific for IFN-γ clone XMG1.2 or IL-2 clone JES6–5H4. Cells were acquired by four-color flow cytometry using FACSCalibur (BD Biosciences) at the TSRI Core Facility, and the data were analyzed with FlowJo software (Tree Star).

Results

Adoptively transferred SMARTA CD4+ T cells show typical primary and memory responses to LCMV infection, and memory is stable for at least ~1 year

This study was designed to determine whether the quality and quantity of CD4+ T cell memory vary depending on the frequency of naive precursor cells, and, if an effect was seen, to determine the underlying mechanism. To facilitate this investigation, we used SMARTA TCR-transgenic mice (53), in which the vast majority of CD4+ T cells are specific for the LCMV epitope gp61–80 presented by I-Ab; these mice were bred onto congenic mice (see Materials and Methods), generating donor mice that contain SMARTA cells expressing the Ly5a allele; this allowed us to readily distinguish transferred SMARTA cells from the endogenous CD4+ T cell response mounted by the (Ly5b) host animal. We considered it important to first ensure that the kinetics with which adoptively transferred naive SMARTA cells respond to LCMV infection were similar to those previously described for the endogenous CD4+ T cell response to this virus, and that the Ly5a cells could be maintained long-term in the Ly5b hosts (without which we would be unable to evaluate memory development). As shown in Fig. 1A, the adoptively transferred cells responded robustly, peaking at ~8 days postinfection at ~107 cells/spleen; >90% of the cells were lost over the ensuing 3–4 wk, and the residual memory cells were stably maintained for the period of follow-up (~1 year). Thus, the kinetics of SMARTA responses appear to be very similar to those reported for the endogenous response (54, 55), and the adoptively transferred Ly5-distinct cells can be maintained long-term in the recipient mice. Naive SMARTA CD4 T cells in the spleen express CD62L, which is down-regulated after infection by day 8 (2); however, the CD62L expression pattern on LCMV-specific memory CD4 T cells has not been reported. As shown in Fig. 1B, the CD62Llow status observed in d8 SMARTA CD4 T cells is maintained long after infection, with relatively few CD62Lhigh cells being present after ~6 mo. This contrasts with CD8+ memory T cells (Fig. 1C). Several reports have shown that CD8+ T cells quite rapidly regain their CD62Lhigh status (26, 56), although others have proposed that the extent to which this occurs may vary depending on the precursor frequency (25).

FIGURE 1
Antiviral responses of adoptively transferred SMARTA cells. The SMARTA CD4 T cell response was followed over time after infection in mice that initially contained 103–104 naive SMARTA CD4 T cells. A, The number of SMARTA CD4 T cells in the spleen ...

The extent of CD4+ T cell expansion during the primary response varies inversely with the number of naive precursors, even though almost all cells are recruited into the response

To determine the extent to which precursor frequency affects the development of antiviral CD4+ T cell memory, the primary and memory CD4+ T cell responses to LCMV were compared in mice in which the number of naive SMARTA cells differed by ~75-fold (2 × 103–1.5 × 105). All mice were infected with LCMV and, at various time points, the number and activation status of the SMARTA cells were examined by flow cytometry. Expansion was more rapid in mice with the large number of precursors, but the peak response occurred at ~8 days postinfection regardless of the precursor frequency of naive cells (Fig. 2A). The absolute numbers of cells present at ~8 days postinfection were calculated. Surprisingly, both groups of mice had a similar number of cells; the difference was only ~2- to 3-fold, indicating that SMARTA cell expansion was ~30-fold greater in the mice with the fewer precursors (Fig. 2B). What might explain this difference in expansion of CD4+ T cells? One obvious possibility is that Ag stimulation is limiting: perhaps, in mice containing a very large number of naive precursors, only a subset of the cells would encounter Ag, or perhaps the exceedingly high number of virus-specific CD4+ T cells has some effect on virus Ag load. Such a reduced recruitment of naive SMARTA cells into the response appeared unlikely, because the expansion of SMARTA cells in “high number” mice was somewhat faster than in “low number” mice (day 6 postinfection, Fig. 2A), but we further investigated the extents to which naive cells were recruited, by determining the expression levels of CD44 and CD62L (Fig. 2C). At 8 days postinfection, SMARTA cells (CD4+/Ly5a) were abundant in both groups of recipient mice (Fig. 2C, left column). Regardless of the initial number of naive precursor cells, the majority of the SMARTA cells at 8 days postinfection were CD44high and CD62Llow, consistent with their having been activated. The frequency of CD25+CD4+ T cells was similar between the groups (Fig. 2C, right column), suggesting that differential induction of regulatory T cells was unlikely to mediate the observed differences in CD4+ T cell expansion. Finally, to more definitively establish whether most of the cells in “high precursor number” mice actually encountered cognate Ag, mice with 105 CFSE-labeled SMARTA cells were infected with virus; a control group of mice were not infected. The vast majority of cells in the control mice remained CFSEhigh, as expected (Fig. 2D, top row), but essentially all of the donor cells in the LCMV-infected mice became CFSE negative by 4 days postinfection (Fig. 2D, bottom row), indicative of their having undergone at least seven rounds of cell division and confirming that all of the precursor cells were recruited into the response. Taken together, these data indicate that all of the naive donor CD4 T cells in “high number” mice encountered authentic viral Ag, became activated and underwent cell division, but—for reasons investigated below—these cells expanded to a lesser extent than cells in “low number” mice.

FIGURE 2
Naive precursor frequency affects primary expansion. B6 mice received defined numbers of spleen cells from SMARTA.Ly5a mice so that after take, they contained the indicated number of SMARTA CD4+ T cells. After 4–8 days to allow the cells to engraft, ...

Naive precursor number affects early memory cell development and the contraction phase

The above data indicate that all of the SMARTA cells were recruited into the primary response, so next we evaluated memory cell development and the contraction phase of the response. The early expression of CD127 (IL-7R) has been shown to play a key role in the development of CD4+ T cell memory (1315). Compared with the level on resting naive SMARTA CD4 T cells, IL-7R was down-regulated on effector cells at days 6 and 8 but, by day 12, IL-7R expression had increased on SMARTA CD4 T cells, consistent with their transition to memory cells (Fig. 3A). Furthermore, the proportion of cells that are CD127high early in the memory phase was greater in mice that had received a lower number of naive cells—that is, CD127 expression was enhanced on cells that had undergone the largest relative expansion; representative data are shown in Fig. 3A, and data from multiple mice are shown in Fig. 3B. Thus, the presence of high numbers of naive responders appears to diminish the emergence of cells that are normally destined for the memory pool. Is CD4+ T cell contraction affected? Our preliminary measurement of kinetics, conducted using spleen cells, suggested that contraction might be more profound in mice that had contained high numbers of naive precursors (open squares, Fig. 2A), and we confirmed this observation by serial measurements of PBMC in many individual mice (Fig. 3, C, and D). Representative data from two mice that differed 100-fold in naive precursor frequency are shown in Fig. 3C, and cumulative data from multiple mice in the two groups are shown in Fig. 3D. SMARTA CD4+ T cell contraction was most profound in mice that had originally contained the larger number of naive precursors (Fig. 3D, squares). Hence, elevating the number of precursor cells compromises the emergence of CD127+ memory-destined cells, and increases the attrition during the contraction phase; as a result, and somewhat counterintuitively, the frequency of memory cells at ~3 mo postinfection was several-fold lower in mice that had originally contained a 100-fold higher number of naive precursors (Fig. 3D).

FIGURE 3
Naive precursor number affects early memory development, and the contraction phase. Groups of mice containing many or few naive SMARTA CD4 T cells were given LCMV, and at various times after infection, effector SMARTA cell responses were followed by flow ...

Elevated precursor number diminishes the quality of memory cells

To evaluate whether naive precursor number affects memory cell quality, mice that contained a high (2 × 105) or low (1 × 103) number of naive precursor cells were given LCMV, and the quality of their memory cells 2–4 mo later was analyzed by flow cytometry. During this memory phase, SMARTA CD4+ T cells in both groups were CD44high, CD62Llow (Fig. 4A), indicating that these markers of memory were not affected by precursor number. Interestingly, extending the observation regarding IL-7R expression in early memory development (Fig. 3B), IL-7R expression was ~2-fold lower on the late memory cells that had been derived from a large number of precursors (Fig. 4A, right panel). There also were functional differences between these groups of CD4+ memory T cells: when stimulated ex vivo, fewer of the memory cells from mice that initially contained a large number of naive precursors made IFN-γ or IL-2, and the responding cells produced a lower quantity of both cytokines (Fig. 4B). We next determined whether memory cells derived from a high or low precursor number differed in their recall responses to secondary viral infection. We chose not to carry out the secondary infection directly in the recipient mice, because the various recipient groups might differ not only in the number of CD4+ memory cells, but also in the levels of antiviral Ab or in the numbers of CD8+ memory T cells (although the latter did not appear to vary between groups; data not shown). Therefore, to avoid these or other confounding factors, memory SMARTA CD4 T cells were purified from the two groups of immune recipient mice using magnetic bead-based positive selection; the resulting populations were >90% CD4+ (Fig. 4C). The same number of SMARTA CD4+ memory T cells from each group (5 × 104 cells) were adoptively transferred into naive recipients, allowing us to compare these cells’ responses to secondary challenge. One day after adoptive transfer of these memory cells, the recipient mice were challenged with LCMV. Six days after rechallenge, the number and quality of the secondary SMARTA effectors were evaluated by flow cytometry. Memory cells that had been obtained from mice that originally contained low numbers of naive SMARTA precursor cells underwent more expansion in the infected hosts (Fig. 4D, left column), recapitulating what we had observed for primary cells (see Fig. 1A); the frequency of these responding SMARTA CD4+ T cells was ~8-fold greater than those derived from immune mice that had originally contained high numbers of precursors. All of the secondary effector cells made robust amounts of IFN-y when stimulated directly ex vivo (Fig. 4D, center column), and the mice developed similar antiviral CD8+ T cell responses (Fig. 4D, right column). Analyses of several mice in the two groups confirmed the conclusion that memory cells that were derived from fewer precursors expanded at least five times more following secondary exposure to virus (Fig. 4E); the difference between the groups is statistically significant (p < 0.031). Thus, artificially increasing the number of naive CD4+ T cell precursors can negatively impact the ability of the resulting memory cells to expand in response to secondary encounter with virus.

FIGURE 4
A high precursor number has detrimental effects on memory cell quality and their subsequent secondary expansion. Mice containing the indicated number of naive precursors were given LCMV, and 77 days later memory CD4 T cells in the spleen were analyzed ...

The negative effects of naive precursor number require direct IFN-γ signaling into CD4 T cells

In addition to its direct antiviral functions, IFN-γ plays a key role in regulating the development of primary and memory CD4+ and CD8+ T cell responses (57). Immunodominant CD8+ T cells (those that are most abundant during the primary response) and cells that transition into the memory phase are characterized by their very rapid initiation of IFN-γ synthesis (58), and the involvement of this cytokine in the regulation of CD4+ and CD8+ responses has been clearly demonstrated using adoptive transfer of cells that differ in their expression of IFN-γR1. CD4+ and CD8+ T cells that receive direct signals through this receptor become more abundant than T cells that lack IFN-γR (37, 38), and we have recently found that these signals have a profound positive effect on the numbers of CD4+ and CD8+ memory cells that are present long after the infection has been resolved (39). These findings led us to evaluate the possible role of IFN-γ in the differences reported in the present manuscript. Wild-type mice with either a low or a high number (103 or 105) of either wild-type or IFN-γRKO SMARTA cells were infected with LCMV, and the quantity of the SMARTA CD4+ T cells in PBMC was determined at various times after infection in individual mice. Time courses for the IFN-γR+ and IFN-γRKO cells are shown in Fig. 5, A and B, respectively; in each panel, the low number group is represented by filled squares, and the high number group by open squares. These graphs illustrate clearly the effect of the IFN-γR. At lower frequencies (similar to physiological; solid squares), the ability to respond to IFN-γ is highly beneficial for CD4+T cells, during both primary and memory phases, as we have previously shown (38, 39). However, at very high (nonphysiological) initial frequencies, the cells carrying the IFN-γR (Fig. 5A) still expand to high levels, but are susceptible to the deleterious effects of a high precursor frequency (Fig. 5A, open squares), leading to an exaggerated decline in their numbers between days ~15 and 40. In contrast, cells lacking the IFN-γR (Fig. 5B) expand less than their receptor-bearing counterparts, but they show a near-linear relationship between the number of naive precursors, and the number of cells at various times postinfection; for these cells, more precursors leads to more memory. Moreover, the proportion of SMARTA cells in PBMC (Fig. 5, A and B) accurately reflects the absolute SMARTA cell numbers, which were measured in the spleen on the day of mouse sacrifice (65 days postinfection); as shown in Fig. 5C, the negative effects of high precursor frequency were seen only when the cells carried the IFN-γR. A limited qualitative analysis of the cells shown in Fig. 5C indicated that there was little difference in their expression of CD44 or of the IL-7R. The only observed difference was in the IFN-γRKO/low cells (green in panels Fig. 5, C and D) fewer of which produced IL-2 in response to in vitro peptide stimulation; however, this conclusion is tentative, as these cells were few in number, and no such difference was found for the IFN-γRKO/high cells (shown as purple). We conclude that, in the absence of the IFN-γR, the detrimental effects of high precursor frequency are blunted. These data are consistent with the hypothesis that T cells compete for IFN-γ as they develop into memory cells and that, in mice carrying normal numbers of naive T cells, the successful acquisition of IFN-γ signals is necessary to produce memory cells of high quality and quantity.

FIGURE 5
The effects of intraclonal competition are dependent on direct IFN-γ signaling. To test whether T cells compete for direct IFN-γ signals, naive, IFN-γR+, or IFN-γR SMARTA CD4 T cells were transferred into separate ...

Discussion

The competition-based model of T cell selection proposes that the CD4+ T cell response is sculpted by limiting amounts of Ag that are required for T cell expansion (24). Mechanistically, one could envision that T cells might use their effector functions to delete Ag-bearing DC, thus preventing the triggering of other naive T cells. Alternatively, a large number of CD4+ or CD8+ T cells might swamp APCs, physically impeding access by other cells; or, using trogocytosis (59, 60), they might scour DC of MHC/peptide complexes so that other T cells cannot be not stimulated. The net effect of these events may be to reduce the time of stable T cell/DC interactions (61); shorter interactions may diminish T cell differentiation. Recent data suggest that Ag competition also may affect memory cell quality, leading to changes in CD62Llow or CD62Lhigh subsets (25, 26). Our data show that intraclonal competition affects the number of CD4+ memory T cells following virus infection, but—perhaps because viruses represent an abundant and renewable source of Ag—this does not appear to be mediated primarily by Ag competition; most, if not all, of the naive SMARTA CD4 T cells were recruited into the response when present at between 103 and 1.5 × 105 cells per spleen (Fig. 2D). The effects of T cell precursor frequency on memory cell abundance is related to reduced expression of IL-7R on CD4+ T cells that develop from a high number of naive precursors (Fig. 3, A and B). Consistent with our data, recent work by others (62) has shown that precursor frequency has minimal effect on T cell recruitment, although these authors concluded that Ag competition had a negative impact on the generation of memory CD4+ T cells. We offer an alternative, or additional, explanation; that competition for cytokine in general, and IFN-γ in particular, may play an important role. Our conclusions are based on analyses of the CD4+ T cell responses measured in spleen and blood, and it will be interesting to determine whether they hold true when evaluated in other organs, such as the lymph nodes and peripheral tissues.

As the T cell response expands following infection, there may be competition for limiting amounts of not only Ag, but also costimulatory molecules, ILs, and IFNs. The data in Fig. 5 implicate IFN-γ, and suggest that the CD4+ T cells that receive direct IFN-γ signals are more likely to survive. We have reported that IFN-γR expression on T cells is modulated throughout the primary response, and that the level of IFN-γ expression is increased on T cells during the expansion phase. In addition, at least for CD8+ T cells, the cells that most rapidly respond to Ag eventually become immunodominant (58). Moreover, direct IFN-y signals augment primary CD4+ and CD8+ T cell responses (37, 38) and play a major role in inducing T cell memory (39). Together, these data are consistent with a model in which the T cells that most rapidly produce abundant IFN-γ can out-compete other T cells for direct IFN-γ signals; these cells become the most abundant population during the primary response, and are permitted to enter the memory pool. Perhaps because they re-express IL-7R faster and to a higher level than the other cells, they establish higher numbers of memory cells that can survive over time; in regard to memory cell survival, we have not determined the effect of high/low precursor frequencies on the homeostatic proliferation of the resulting memory cells. Competition for cytokines also could be important during the course of a chronic infection, when antiviral T cells can become nonfunctional (63). In some chronic infections, new thymic emigrants are recruited into the response, supplementing the existing, but exhausted, older cells and helping to control the infection (64). In this case, one can imagine that competition by an elevated number of pre-existing Ag-specific T cells might have a detrimental impact on the induction and differentiation of these new cells. We are currently evaluating the effects of precursor frequency, and of direct IFN-γ signaling, during chronic LCMV infection.

The number and the quality of memory cells may be determined by the degree to which precursor cells expand during the primary response. Perhaps cell division itself is a key criterion for developing “good” memory CD4 T cells; cells in low-precursor number mice expanded substantially more than those in high-precursor number mice (Fig. 2A), and resulted in better memory. The magnitude of the initial T cell response—and, implicitly, the number of T cell divisions—differs from infection to infection, so it will be interesting to compare the effects of precursor frequency in several different viral and bacterial infections. What extent of vaccine-driven expansion is required to ensure optimal memory development? We show here that cells that undergo a 2300-fold expansion develop into a high-quality memory population, but cells that had expanded only ~75-fold were lower in quality (Fig. 4). Our previous analyses indicate that, for a given MHC-restricted foreign Ag, there are ~100 epitope-specific endogenous precursor CD4 T cells in the spleen (2). Combining these two datasets, a high-quality memory pool would be generated if a vaccine caused 100 naive precursor cells to expand to a peak of ~2 × 105 effector cells. However, an additional question may be asked: is it always advantageous to have the largest possible number of memory cells? For example, it is possible that the competition effects shown here for naive cells might also apply to memory cells, in which case an overabundance of memory cells might diminish the efficacy of the immune response to secondary Ag encounter: is there a numerical limit of “good” memory cells, beyond which recall responses are not improved, and may even be reduced?

Previous analyses examining endogenous CD8 memory cells after LCMV, Sendai, bacillus Calmette-Guérin-OVA, or rLM-OVA infections found a mixed population of cells that were CD62Lhigh or CD62Llow (25, 26, 56, 65). Increasing the initial CD8+ T cell precursor number resulted in memory cells that tended to be CD62Lhigh (25, 26), and reducing this competition preferentially resulted in memory CD8 T cells that were CD62Llow (25). We also find a mixed population of CD8+ (P14) memory cells (Fig. 1C) but, in contrast, memory SMARTA CD4+ T cells are homogeneously CD62Llow after LCMV infection (Fig. 1B). Furthermore, increasing the number of precursors did not increase the proportion of memory CD4+ T cells that were CD62Lhigh (Fig. 4A), indicating that, so long as all of the T cells are recruited into the response, selection into the memory CD4+CD62Lhigh or CD62Llow subset is not affected by clonal competition, contrary to what occurs for CD8+ T cells. Our observation that the majority of CD4+ T cells become CD62Llow differs from that reported for CD4+ responses against a soluble protein Ag (66), in which many CD4+ T cells were found to be CD62Lhigh; we speculate that this may be due to the efficiency of recruitment and the amount or longevity of Ag. It would be interesting to learn whether the CD62Llow phenotype is hard-wired into memory CD4+ T cells or if it is caused by periodic stimulation by very low quantities of MHC class II-restricted peptide that originate from persisting immune complexes. These complexes would have to cause suboptimal T cell activation, leading to CD62L loss on memory CD4 T cells without robust Ag-driven cell division.

In conclusion, we provide here evidence of intraclonal competition among CD4+ T cells, mediated in part by competition for IFN-γ. The effects of this competition were most evident when IFN-γ-responsive cells were present at an unusually high precursor frequency (Fig. 5A); however, we propose that such competition is an integral regulator of the normal T cell response, and occurs as T cell numbers are increasing soon after infection. T cells also may cooperate: this has been shown to occur among T cells of different specificities and this, like the competition identified herein, appears to be mediated by endocrine or paracrine factors (67). Perhaps the expression of IFN-γ by cells of one specificity can stimulate APC to better express other epitopes, thus fostering new and different T cell responses. Alternatively, the robust secretion of IFN-γ by numerous cells of one specificity might directly stimulate, in a paracrine manner, nearby T cell populations of another specificity that are present at lower frequency. We propose that the two processes may take place serially: interclonal cooperation might occur early, increasing the diversity of the T cell response, while intraclonal competition supersedes when T cell numbers increase, actively selecting the best cells within each population to differentiate into memory.

Acknowledgments

We thank François Chouinard for technical assistance in confocal microscopy. We are grateful to Annette Lord for secretarial support. This is manuscript number 18862 from The Scripps Research Institute.

Footnotes

1This work was supported by National Institutes of Health R-01 Grants AI-052351 and AI-077607 (to J.L.W.).

3Abbreviations used in this paper: LCMV, lymphocytic choriomeningitis virus; KO, knockout; LM, Listeria monocytogenes.

Disclosures

The authors have no financial conflict of interest.

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