Chemokine Receptor Responses on T Cells Are Achieved Through Regulation of Both Receptor Expression and Signaling

Ronald L. Rabin, Matthew K. Park, Fang Liao, Ruth Swofford, David Stephany and Joshua M. Farber
J Immunol April 1, 1999, 162 (7) 3840-3850;

Abstract

To address the issues of redundancy and specificity of chemokines and their receptors in lymphocyte biology, we investigated the expression of CC chemokine receptors CCR1, CCR2, CCR3, CCR5, CXCR3, and CXCR4 and responses to their ligands on memory and naive, CD4 and CD8 human T cells, both freshly isolated and after short term activation in vitro. Activation through CD3 for 3 days had the most dramatic effects on the expression of CXCR3, which was up-regulated and functional on all T cell populations including naive CD4 cells. In contrast, the effects of short term activation on expression of other chemokine receptors was modest, and expression of CCR2, CCR3, and CCR5 on CD4 cells was restricted to memory subsets. In general, patterns of chemotaxis in the resting cells and calcium responses in the activated cells corresponded to the patterns of receptor expression among T cell subsets. In contrast, the pattern of calcium signaling among subsets of freshly isolated cells did not show a simple correlation with receptor expression, so the propensity to produce a global rise in the intracellular calcium concentration differed among the various receptors within a given T cell subset and for an individual receptor depending on the cell where it was expressed. Our data suggest that individual chemokine receptors and their ligands function on T cells at different stages of T cell activation/differentiation, with CXCR3 of particular importance on newly activated cells, and demonstrate T cell subset-specific and activation state-specific responses to chemokines that are achieved by regulating receptor signaling as well as receptor expression.

Lymphocytes are a highly heterogeneous population of naive and memory/effector cells that show complex patterns of trafficking related to both homeostasis and recruitment to sites of active immune and inflammatory responses (1, 2). It has been appreciated for some time (3, 4, 5) that lymphocyte extravasation requires activation of Giα-coupled receptor(s) on the migrating cells. The discovery of chemokines, a family of >30 chemotactic cytokines that act through seven-transmembrane domain, G protein-coupled receptors (reviewed in 6), provided candidate factors for regulating migration and perhaps other aspects of lymphocyte biology. The possible importance of chemokines in lymphocyte trafficking is suggested by the large number of chemokines, found in each of the four chemokine subfamilies, that have been shown to be active on lymphocytes in vitro (reviewed in Refs. 7 and 8). While the array of chemokines that target lymphocytes is wide enough to suggest the possibility of specific relationships between individual chemokines and lymphocyte subsets, the logic underlying these relationships has not been readily apparent.

A number of studies have described differential effects of particular chemokines on lymphocyte subsets (9, 10, 11, 12, 13, 14, 15, 16) and have investigated the effects of T cell activation on responses to chemokines (11, 17, 18, 19, 20, 21, 22). Most of the work on chemokine targeting of lymphocyte subsets has relied on in vitro chemotaxis assays, and as revealed by the reading of the above cited papers, these assays have sometimes yielded contradictory results. For example, MIP-1β2 has been reported to favor CD4 T cells over CD8 T cells (10, 11) and CD8 T cells over CD4 T cells (12) and to show no real CD4/CD8 bias (14). MIP-1α has been reported to attract selectively memory cells (14) (11) and to attract memory and naive cells equally (10). Similarly, T cell activation through CD3 has been reported to enhance (11) or inhibit (18, 19) migration to MIP-1α, RANTES, and other CC chemokines.

Recently, as Abs to some chemokine receptors have become available, information has begun to emerge on the expression of receptors on lymphocyte subsets (15, 23, 24, 25, 26, 27, 28, 29, 30). In an attempt to clarify and expand information on selective activities for chemokines on subsets of resting and activated lymphocytes, we have systematically evaluated chemokine receptor expression on human T cells isolated from peripheral blood, either freshly isolated or after short term activation through Ag receptor in vitro. We have correlated receptor expression with two indicators of chemokine responsiveness, an increase in [Ca]i and chemotaxis. The chemokine-induced rise in [Ca]i is an early consequence of receptor activation, and the assay for calcium flux has the advantages of avoiding the idiosyncrasies of particular chemotaxis assays and, when performed on the flow cytometer, allowing for the phenotyping of responding cells using an array of surface markers. Additionally, the calcium assay can be used equally well with resting and activated T cells for analyzing the phenotypes of cells responding to chemokines, while phenotypic analysis of responses among activated cells using the chemotaxis assay can be problematic due to the high background chemokinesis. We have, however, analyzed chemotaxis in resting cells because of the assay’s physiological relevance and to correlate chemotaxis with the results using the calcium flux assay.

By analyzing a panel of chemokine receptors and chemokines, we have been able to appreciate significant connections between individual chemokine receptors and their ligands and subsets of activated and resting T cells. Our data suggest distinct roles for chemokine receptors during the T lymphocyte’s transition from naive to memory cell. Moreover, we have demonstrated that at least one consequence of receptor activation in lymphocytes, namely the ability to produce a global rise in [Ca]i, is regulated independently of receptor expression per se. Together, our data show that there are significant T cell subset-specific effects of chemokines that are achieved by varying both receptor expression and receptor signaling, and our findings predict that as we increase the number of parameters by which we analyze lymphocyte responses to chemokines we will discover that receptors and ligands that appear redundant in fact serve unique functions.

Materials and Methods

Reagents

All culture media, salt solutions, and FBS were obtained from Life Technologies (Gaithersburg, MD). Anti-CD3 mAb (OKT3, pharmaceutical grade) was obtained from Ortho Biotech (Raritan, NJ). The fluorescein conjugates anti-CD45RO (clone UCHL-1) and anti-CD8 (clone HIT8a) were purchased from PharMingen (San Diego, CA). Phycoerythrin (PE)-conjugated anti-CD8 (clone HIT8a), avidin, anti-CCR5 (clone 2D7), and anti-CXCR4 (clone 12G5) were obtained from PharMingen, and PE-anti-CD62L (clone TQ1) was obtained from Coulter Diagnostics (Hialeah, FL). PE-goat anti-mouse and anti-rabbit IgG were purchased from Southern Biotechnology (Birmingham, AL). Cy5PE-conjugated anti-CD8 (clone HIT8a) was obtained from PharMingen, Cy5PE-anti-CD4 (clone Q4120) was purchased from Sigma (St. Louis, MO), and allophycocyanin conjugate of anti-CD8 (clone RPA-T8) was purchased from PharMingen. The anti-CD56 (clone NCAM 16.2) was conjugated to Cy5PE by Becton Dickinson (San Jose, CA) and was the gift of Calman Prussin, National Institute of Allergy and Infectious Diseases, National Institutes of Health (Bethesda, MD). Rabbit polyclonal anti-CCR1 was the gift of Naofumi Mukaida, Kanazawa University (Ishikawa, Japan). Normal rabbit IgG was purchased from Pierce (Rockford, IL). Biotin anti-CCR2 was purchased from R&D Systems, (Minneapolis, MN). Anti-CXCR3 and anti-CCR3 (clones 1C6 and 7B11, respectively) were the gifts of Paul Ponath (Leukosite, Cambridge, MA). The anti-CCR3 mAb was conjugated to succinimidyl-4-(N-maleimidomethyl)cyclohexane-1-carboxylate-PE (Prozyme, San Leandro, CA) according to the protocol of A. Kantor and M. Roederer (http://cmgm. stanford.edu/roederer/abcon/).

Recombinant HuMig was produced and purified from supernatants of insect cells as previously described (31). We used HuMig that was produced in our laboratory or obtained from PharMingen; the sp. act. of the in-house vs commercial preparations were identical as determined by calcium responses on the B10 tumor-infiltrating lymphocyte (TIL) line (data not shown). Recombinant SDF-1α and SDF-1β were gifts of Monica Tsang (R&D Systems). All other recombinant chemokines were purchased from PeproTech (Rocky Hill, NJ).

TIL and PBMC

The B10 TIL line, described previously (32), was maintained in RPMI, 10% FBS, and 500 U/ml IL-2 (Cetus, Emeryville, CA). This line has been determined to be monoclonal by virtue of amplification by PCR of only a single band from the cDNA encoding the Vβ11 TCR chain (Mark Connors, National Institute of Allergy and Infectious Diseases, unpublished observation).

Buffy coats were collected from normal donors by the Department of Transfusion Medicine at the National Institutes of Health, PBMC were isolated by Ficoll-Hypaque (Pharmacia, Uppsala, Sweden) density centrifugation, and residual RBC were lysed with ACK lysing buffer (Biofluids, Rockville, MD). For activation, PBMC were then placed in culture in 24-well plates at a density of 5 × 106/ml with penicillin/streptomycin and the anti-CD3 mAb OKT3 (5 μg/ml) for 3 days.

Multiparameter flow cytometry

PBMC, either freshly isolated or stimulated with OKT3 for 3 days, were suspended in HBSS with calcium and magnesium, 10 mM HEPES, and 1% FBS (HBSS/FBS). To this cell suspension, the fluorescent calcium probe indo-1 (indo-1/acetoxymethylester) and the detergent Pleuronic (Molecular Probes, Eugene, OR) were added at final concentrations of 10 μM and 300 μg/ml, respectively. Also added were anti-CD14-conjugated magnetic beads (Dynal, Lake Success, NY). The final suspension of cells, probe, and magnetic beads was incubated at 30°C for 45 min with frequent gentle agitation. After removal of magnetic beads (and adhered monocytes/macrophages), PBL were washed twice and incubated with saturating levels of conjugated mAb for 15 min at room temperature with frequent agitation, after which they were washed and resuspended in HBSS/FBS. Monocytes/macrophages in the PBL after treatment with magnetic beads were usually <1% of all viable cells and were always <2%. The use of magnetic beads and indo-1 did not affect the relative percentages of lymphocyte subsets (data not shown).

For phenotypic analysis, PBL were analyzed on a FACSCalibur or a FACSVantage flow cytometer (Becton Dickinson Immunocytometry Systems, San Jose, CA). For calcium flux, PBL were analyzed on a FACSVantage flow cytometer equipped with an argon laser tuned to 488 nm and a krypton laser tuned to 360 nm. Indo-1 fluorescence was analyzed at 390/20 and 530/20 for bound and free probe, respectively (33). The signals for bound and unbound indo-1 were collected in the linear mode. The FACSVantage was equipped with two modifications necessary for reproducible measurement of chemokine-induced calcium flux: a Time Zero injection module (Cytek, Fremont, CA) and a ratio offset, so that the gain of the fluorescent ratio could be increased while keeping the baseline signal in the lower channels.

For each stimulation, an aliquot of PBL (0.5 ml total volume) was warmed at 37°C for 3 min before loading into the Time Zero module. Cells were collected for 30 s, at which time 50 μl of HBSS/FBS was added as a sham injection. At 60 s, chemokine, also in a total volume of 50 μl, was injected. The final concentration of chemokine was well above that which was determined to yield the maximal response according to dose-response curves (2 μg/ml). Cells were analyzed at a rate of 1000–2000 cells/s. The flow cytometer is configured such that the delay between ligand addition and signal detection is <15 s. Thus, detection of calcium levels by the flow cytometer is usually before or coincident with the onset of the calcium flux and is always prior to its peak (∼25 s).

The percentage of cells that responded by an increase in intracellular calcium after stimulation with chemokine was determined using Multitime Software for Analysis of Kinetic Flow Cytometry Data (Phoenix Flow Systems, San Diego, CA). A threshold of ratio fluorescence was determined in the window of time after buffer addition but before addition of chemokine. The threshold separated the 5% of the cells with the highest ratio from the cells whose fluorescence ratios were lower. This threshold was then applied to the time window following the addition of chemokine. The maximum number of cells above the threshold averaged over a 6-s time interval (so that spurious spikes in calcium flux do not result in overestimation of the number of responding cells) was expressed as a percentage of all the cells in the same interval. From this number we subtracted 5, the percentage of cells above threshold in the resting time window, to obtain the percentage of cells responding.

Chemotaxis

Monocyte-depleted PBL were suspended in RPMI with 1% human serum albumin and loaded in triplicate into a disposable chemotaxis apparatus (ChemoTx, Neuroprobe, Gaithersburg, MD). Chemokines were placed in the lower wells at concentrations determined to yield maximum migration (300–600 ng/ml). After incubation for 3 h at 37°C, cells from 20 lower wells were pooled; stained for expression of CD4, CD8, CD45RO, and CD62L; fixed; and analyzed on a FACSCalibur flow cytometer.

Statistics

Differences in responses among the chemokines tested were determined by analysis of variance. Differences between the responses of two subsets to a given chemokine were determined by paired t test. All statistical analysis was performed with StatView for the Macintosh operating system (Abacus Concepts, Berkeley, CA).

Results

Chemokine receptor expression on resting and activated PBL

We first determined the expression of a panel of chemokine receptors on naive and memory T cell subsets, on both freshly isolated cells and cells activated in vitro. We defined the naive subset (rounded gate, Fig. 1⇓) as being both CD45RO− and CD62L+ (34), and the memory subset as being CD45RO+ (rectangular gate, Fig. 1⇓) or CD45RO− CD62L−. For activations, PBMC were incubated with OKT3 for 3 days to produce lymphoblasts analogous to cells fully activated, but in the early stages of differentiation after encountering Ag. In the text that follows, we will refer to both freshly isolated and recently activated cells that are CD45RO− and CD62L+ as naive, recognizing that the latter are in transition to effector/memory cells.

FIGURE 1.
FIGURE 1.

Subsets of CD4 and CD8 T cells as defined by expression of CD45RO and CD62L in the freshly isolated and OKT3-activated human PBL. Gates are set on the naive subset (CD45RO− CD62L+; rounded gate) and the CD45RO+ memory subset (rectangular gate) for subsequent chemokine receptor analysis.

Receptor staining is shown in Fig. 2⇓. On freshly isolated T cells, none of the chemokine receptors was exclusively expressed on CD4 vs CD8 T cells, although expression of CCR2 was barely detected on CD8 T cells. Expression of CCR2 and CCR5 was restricted to memory T cells. Within the CD45RO+ (memory) cells, CCR2 and CCR5 were expressed on the CD62L− CD26+ subset (not shown), consistent with published data (15, 23). In contrast to CCR2 and CCR5, CCR1, CXCR3, and CXCR4 were expressed on both naive and memory CD4 and CD8 T cells, although staining of naive CD4 cells for CXCR3 was minimal. Within the memory subset, these receptors were not restricted to CD62L− cells (not shown). Furthermore, CXCR4 levels were higher on naive CD4 and CD8 T cells than on their memory counterparts, and CXCR3 was higher on naive compared with memory CD8 T cells. CCR3 was not detectable on resting T cells in our analyses.

FIGURE 2.
FIGURE 2.

Chemokine receptors (solid lines) vs Ab controls (dashed lines) on memory (CD45RO+) and naive subsets of CD4 and CD8 T cells, freshly isolated and OKT3 activated. The experiment shown is representative of five experiments.

Short term activation of T cells with OKT3 showed subset-dependent effects on receptor expression. On the recently stimulated naive CD4 T cells, CCR2, CCR3, and CCR5 all remained undetectable; CCR1 showed no change; and CXCR4 levels were increased slightly. The major effect was on CXCR3, where expression was increased dramatically. On memory CD4 T cells, activation led to no changes in levels of CCR1 and CCR2; small but detectable increases in levels of CCR3, CCR5, and CXCR4; and again a significant increase in the level of CXCR3. For the recently stimulated naive CD8 T cells, as for CD4 T cells, CCR2 and CCR5 remained undetectable and CXCR3 expression increased significantly. Expression of CCR1 and CCR3 increased slightly, while CXCR4 expression was unchanged. With activation of memory CD8 T cells, there were no significant changes in levels of CCR2, CCR5, and CXCR4; expression of CCR3 became detectable; and levels of CCR1 and CXCR3 were increased. In summary, CXCR3 was increased on all subsets after short term activation and was the only receptor to be up-regulated on naive CD4 T cells under these conditions. Activation also led to an increase in CCR1 on CD8 T cells, to an increase in CCR5 on CD4 T cells, and to detectable expression of CCR3 on both CD4 and CD8 T cells.

Chemotaxis of freshly isolated PBL

Table I⇓ shows relationships among chemokine receptors and chemokines that are relevant to this study to facilitate understanding the data that follow on chemokine responses. For the reasons discussed in the introduction, among them the difficulties in obtaining reliable chemotaxis data on lymphocyte subsets in OKT3-activated cells that have high levels of background chemokinesis (not shown), we relied primarily on our flow cytometry-based assay of calcium signaling to analyze responses among T cell subsets. However, for comparative purposes we also performed modified Boyden chamber chemotaxis assays with selected chemokines on the freshly isolated lymphocytes, as shown in Fig. 3⇓. Fig. 3⇓A shows the lower chamber cells stained for CD4 and CD8 and demonstrates that MCP-1 preferentially attracted CD4 T cells. Using a minimum estimate of preferential migration obtained by comparing percentages of CD4 and CD8 T cells in the lower wells in the absence and the presence of chemokines for three experiments, the CD4 vs CD8 bias for MCP-1 was significant when compared with either no chemokine (paired t test, p = 0.02), or HuMig (p = 0.02) or RANTES (p = 0.002, not shown). These data are consistent with the receptor staining in Fig. 1⇑, where levels of CCR2 were minimal on resting CD8 T cells. Also consistent with the receptor staining data for CCR5 as well as CCR1, RANTES showed preferential activity on CD8 vs CD4 cells compared with no chemokine (p = 0.01), and HuMig showed a trend in the same direction that was not statistically significant (not shown). The data for memory and naive subsets in Fig. 3⇓B show that all three chemokines preferentially attracted the memory subsets of CD4 T cells, and consistent with CXCR3 expression, HuMig attracted significant numbers of naive CD8 T cells. The lack of a detectable response to MCP-1 and RANTES among naive CD8 T cells is in line with the staining data for CCR2 and CCR5 on these cells presented in Fig. 2⇑, although some activity with RANTES might have been expected given the presence of CCR1. It is noteworthy that the preferential migration of the memory subset among CD8 T cells to MCP-1 compared with no chemokine, as shown in Fig. 2⇑B, indicates that although MCP-1 showed a clear CD4 T cell bias, some CD8 T cells also responded. The preferential responses of memory cells to RANTES and MCP-1 have been well described in the literature (9, 13).

FIGURE 3.
FIGURE 3.

Phenotypes of freshly isolated T cells migrating to MCP-1, HuMig, and RANTES correlate with patterns of receptor expression. The numbers are the percentages of CD4 and CD8 T cells among total lymphocytes (A) and of each subset of CD4 and CD8 T cells (B) from the starting population or pooled from the lower wells. The concentrations of chemokines used were those that induced peak chemotaxis responses (300–600 ng/ml). The experiment shown is representative of four experiments.

View this table:
Table I.

Chemokine receptors and their ligands

Chemokine receptor signaling

Our flow-based assay for calcium flux permitted us to identify responding subsets directly by using phenotypic surface markers and to compare responses quantitatively in terms of the percentage of cells within a subset showing an increase in [Ca]i above a threshold value (see Materials and Methods for details). With few exceptions (see below) calcium signals were not seen with chemokines on freshly isolated cells, but only after activation with OKT3. Because, in general, the signaling data using the OKT3-activated cells correlated with patterns of receptor expression, the data using the OKT3-activated cells will be shown first. Some chemokines failed to produce detectable calcium responses, even on activated cells, including eotaxin, IL-8, GRO-α, PF-4, I-309, and lymphotactin, and these negative data are omitted.

To illustrate one of the general features of the calcium responses in PBL, Fig. 4⇓ compares signals to the CCR5-specific ligand MIP-1β in OKT3-activated PBL with the signals in a monoclonal line of TIL maintained by repeated stimulation in vitro. All calcium flux assays were performed using concentrations of chemokines well above those producing maximal responses as determined by dose titrations (not shown). As anticipated, the responses of the TIL line were uniform (Fig. 4⇓A). In contrast, there were partial responses among the heterogeneous populations of PBL. One obvious possibility for the heterogeneity in signaling was cell-to-cell differences in levels of receptor expression. Fig. 4⇓B shows responses to MIP-1β of cells stained for CCR5. Staining did not alter the calcium responses, since approximately the same percentage of cells responded to MIP-1β in the absence of anti-CCR5 (data not shown). While MIP-1β responses were found only in the CCR5+ cells, not all CCR5+ cells responded to MIP-1β with a calcium flux. Fig. 4⇓C also demonstrates that there was almost no difference between levels of staining for CCR5 in the MIP-1β-responding vs nonresponding cells, so that other unknown factors must be accounting for the differences in signaling.

FIGURE 4.
FIGURE 4.

Signaling is not a simple function of receptor level in PBL. A, Calcium flux in a chronically stimulated, monoclonal TIL CD4 T cell line in response to MIP-1β (2 μg/ml). In this scattergram of calcium flux and those that follow, the y-axis shows channel numbers that reflect the fluorescence ratio of the calcium probe indo-1. B, OKT3-activated PBMC were stained for CD4, CD8, and CCR5. Calcium flux in response to MIP-1β is restricted to CCR5-expressing T cells, but not all CCR5-expressing T cells respond with calcium flux. C, CD4 T cells from B, gated on the time when the cells were responding to MIP-1β. The contour plot on the left demonstrates no difference in levels of CCR5 expression between responding cells (solid line rectangle) and nonresponding cells that express CCR5 (dashed line rectangle). On the right are corresponding histograms of CCR5 expression. The experiment shown is representative of five experiments.

Fig. 5⇓ demonstrates chemokine responses in activated PBL stained for CD4, CD8, and CD56. The scattergrams of a representative experiment are shown in Fig. 5⇓A, and the combined quantitative analysis from 17 experiments, 11 of which included staining for CD56, is shown in Fig. 5⇓B. For each sample, the value for the percentage of cells responding represents the maximum value for the percentage of cells with ratio fluorescence above threshold as determined in sequential 6-s windows taken during the study (see Materials and Methods). It is important to note that the results from a single experiment shown in scattergrams may not match the cumulative data in every respect. The analysis in Fig. 5⇓ demonstrates that CXC chemokines were more potent, i.e., stimulated a higher percentage of cells, than did the CC chemokines. Comparison of chemokine potencies for CD4 T cells, CD8 T cells, or NK cells demonstrates that the CXC chemokine SDF-1 was the most potent for each subset (p = 0.01–0.0001, by analysis of variance), and that except for SDF-1, HuMig stimulated more CD8 T cells than any other chemokine (p ≤ 0.05–0.0001). Paired t tests of the cumulative data confirmed that MCP-1 and MCP-3 stimulated significantly more CD4 than CD8 T cells (MCP-1, p ≤ 0.001; MCP-3, p ≤ 0.04). Conversely, HuMig stimulated a rise in intracellular calcium in significantly more CD8 than CD4 T cells (p ≤ 0.001). No other chemokines tested demonstrated a significant preference between CD4 and CD8 T cells among the activated cells.

FIGURE 5.
FIGURE 5.

CXC chemokines are more potent that CC chemokines as activators of lymphocytes. A, Representative scattergrams of responses of activated lymphocyte subsets to chemokines. All scattergrams show 100% of the events collected and are from the same experiment. In each stimulation, buffer was injected at 30 s, and chemokine (2 μg/ml) was injected at 60 s. B, Cumulative results of 17 experiments in which lymphocytes were costained for expression of CD4 and CD8. In 11 of these experiments, the lymphocytes were also stained for expression of CD56, and NK cells were defined as CD56+, CD4−, and CD8− or CD8dim. Data are represented as the mean ± SEM.

Fig. 6⇓ shows representative scattergrams and cumulative data from 15 experiments analyzing responses to chemokines of subsets of CD4 T cells activated in vitro. The most striking finding, consistent with the data for receptor expression, was that SDF-1, IP-10, and HuMig stimulated the recently activated naive CD4 T cells, and the CC chemokines did not. The combined analysis also showed no significant differences in the responses of CD62L+ vs CD62L− memory CD4 T cells to a given chemokine.

FIGURE 6.
FIGURE 6.

CXC, but not CC chemokines, stimulate activated naive CD4 T cells. A, All scattergrams show 100% of the events collected and are from the same experiment as that in Fig. 5⇑. Occasional responses in a small number of naive cells to CC chemokines as shown here for MIP-1β and RANTES were not reproducible. B, Cumulative results of 15 experiments in which lymphocytes were costained for expression of CD4, CD45RO, and CD62L. Data are represented as the mean ± SEM. The contour plot shows a representative distribution of CD4 T cell subsets with mean percentages and their SDs for the 15 experiments.

The data from 10 experiments in which PBL were costained for expression of CD8, CD45RO, and CD62L are shown in Fig. 7⇓. Data for MCP-1 and MCP-3 are omitted because the low number of responding cells prohibited meaningful analysis. Similar to the findings for the CD4 cells, the CXC chemokines SDF-1, HuMig, and IP-10 were much more potent on the activated naive cells compared with the CC chemokines. In contrast to the effects on CD4 memory T cell subsets, the cumulative analysis in Fig. 7⇓ reveals differences in the potencies of chemokines among the CD8 T cell memory subsets. IP-10 and HuMig were particularly potent at stimulating the CD45RO+ CD62L+ memory subset of CD8 T cells, especially when compared with their effects on the other CD8 T cell memory subsets (p ≤ 0.05–0.0005); this was clearly not the case for the CC chemokines. There were also differences in potencies among the CC chemokines for the CD8 T cell memory subsets. MIP-1α was more potent for all three memory subsets than MIP-1β (p ≤ 0.05–0.01) and was more potent for the CD45RO+ CD62L+ (p ≤ 0.05) subset than RANTES. The higher activities of MIP-1α and RANTES on CD8 cells overall compared with MIP-1β might have been due to signaling through CCR1. Indeed, with considerable donor-dependent variability, saturating amounts of MIP-1β did not fully desensitize the activated T cells to MIP-1α (not shown).

FIGURE 7.
FIGURE 7.

CXC chemokines are potent stimulators of activated naive and CD62L+ memory CD8 T cells. A, All scattergrams show 100% of the events collected and are from the same experiment as that in Figs. 5⇑ and 6⇑. MCP-1 and MCP-3 were excluded from this analysis because too few cells responded for meaningful analyses. The poor response of CD8 T cells to IP-10 in the experiment shown here was not representative. B, Cumulative results of 10 experiments in which lymphocytes were costained for expression of CD8, CD45RO, and CD62L. Data are represented as the mean ± SEM. The contour plot shows a representative distribution of CD8 T cell subsets with mean percentages and their SDs for the 10 experiments.

Taken together, these data on activated T cells in response to chemokines show that 1) MCP-1 and MCP-3 signaled preferentially on CD4 T cells, and HuMig signaled preferentially on CD8 T cells; 2) those chemokines that stimulated calcium flux in CD8 T cells also stimulated NK cells; 3) SDF-1 was the most potent at stimulating CD4 and CD8 T cells because it stimulated more cells in each of the subsets than the other chemokines tested; 4) the CXC chemokines IP-10 and HuMig were more potent than the CC chemokines for CD4 and CD8 T cells because, like SDF-1, IP-10 and HuMig stimulated the activated naive subset and in the case of CD8 T cells were generally more potent on the CD62L+ memory subset; and 5) as a group, the CC chemokines did not stimulate a calcium flux in recently activated naive CD4 cells and did so only poorly in the corresponding CD8 T cells. In general, these signaling patterns were consistent with subset receptor expression on OKT3-activated cells as shown in Fig. 2⇑. The one apparent exception was for MCP-1, since among the activated memory subsets the significant differences in signaling on CD4 vs CD8 cells were not consistent with the unimpressive differences in receptor expression seen in Fig. 2⇑.

In contrast to OKT3-activated lymphoblasts, freshly isolated PBL did not flux calcium in response to most chemokines tested, including HuMig, IP-10, MIP-1α, MIP-1β, and RANTES. However, calcium fluxes were seen in response to SDF-1 and MCP-1, but only in the memory subset of CD4 T cells (Fig. 8⇓). Because we had shown that cellular activation potentiated receptor signaling, we stained the freshly isolated cells for the activation markers HLA-DR, CD69, and CD25, but found that the responding memory cells were negative for these cell surface Ags (not shown). While the results for MCP-1 correlated with expression of CCR2 as seen in Fig. 2⇑, signaling by SDF-1 clearly did not correlate with levels of expression of CXCR4, since CXCR4 was no higher on the CD4 memory subset of fresh CD4 T cells than on the other subsets where no calcium signals were seen. Additionally, on a number of subsets of freshly isolated PBL that failed to signal, receptors were expressed at levels similar to those on responding subsets of activated cells. For example, levels of CCR5 were similar on fresh and activated memory CD8 T cells, and levels of CXCR4 were similar on fresh and activated naive CD8 T cells, yet signaling by MIP-1β and SDF-1 were seen only on these subsets after activation. Similarly, despite readily detectable CXCR3 on CD8 and memory CD4 T cells, no calcium signals were seen with HuMig and IP-10 without prior cellular activation. It also follows from the data presented above that chemotactic responses in resting T cell subsets to specific chemokines were seen in the absence of calcium signals, as, for example, with HuMig and RANTES and with MCP-1 on CD8 T cells.

FIGURE 8.
FIGURE 8.

SDF-1 and MCP-1 trigger a calcium flux in freshly isolated CD4 memory T cells. Chemokines were used at 2 μg/ml, and gated for CD4 and CD8 (A) and CD45RO and CD62L (B).

Discussion

We have analyzed freshly isolated and activated T cell subsets for chemokine receptor expression and have evaluated receptor function using chemotaxis and calcium flux to obtain a more comprehensive understanding of the role of chemokines in lymphocyte physiology. For assaying calcium fluxes we used a flow cytometer that was modified to allow us to detect and analyze chemokine responses of lymphocyte subsets in a manner more sensitive and reproducible than previously reported.

Combining data on naive and memory cells freshly isolated and after activation can provide information not only about the possible role of receptors and chemokines on these subsets per se, but also about the evolution of receptor expression and function as a T cell moves from naive to activated to memory and then through subsequent reactivation. Our activation protocol used OKT3 to cross-link CD3 in the presence of macrophages for 3 days. In vivo studies show that T cell blasts begin to leave the lymph node after 2 days of Ag challenge (35), so that our activation protocol might be expected to produce cells equivalent to blasts that circulate during the early phases of an immune response.

Of the six receptors we analyzed, only CXCR4 and CCR1 were found at significant levels on freshly isolated naive CD4 cells, consistent with published data (24, 36). The activity of CCR1 on freshly isolated PBL has not been well characterized due to an absence of a CCR1-specific agonist. For CXCR4, however, it is clear that its specific ligand, SDF-1, can deliver potent chemotactic signals to all subsets of resting lymphocytes, including naive CD4 cells (37), and can rapidly induce adhesion of naive CD4 cells to ICAM-1 (38), providing strong circumstantial evidence that SDF-1 and CXCR4 are relevant in the trafficking of these cells.

Activation of naive CD4 cells led to rapid up-regulation of CXCR3, but not of the CC chemokine receptors. Not only was CXCR3 expressed on these cells, but the receptor was functional, as measured by calcium flux on cells from multiple donors to both HuMig and IP-10 (Fig. 6⇑). These results suggest that CXCR3 and its ligands may play a unique role in the early stages of T cell activation. Expression of functional CXCR3 on CD4 lymphoblasts would be anticipated to direct activated cells, for example those effector cells and effector cell precursors exiting lymphoid tissue in the days following Ag stimulation, to peripheral sites where the CXCR3 ligands HuMig, IP-10, and IFN-inducible T cell α chemoattractant (ITAC) are being expressed. Because the CXCR3 ligands are all dramatically induced by IFN-γ, with some responding as well to other IFNs and inflammatory cytokines (39, 40), the expected result would be for newly activated CD4 cells to continue to differentiate in a Th1 environment, leading to the production of Th1 cells and a Th1-biased response overall. Furthermore, naive CD8 T cells, which express CXCR3 and respond by chemotaxis to HuMig (Fig. 3⇑), produce IFN-γ in response to stimulation through the TCR (34). So naive CD8 cells, responding to CXCR3 ligands, might also contribute to a Th1-biased response. These results add to the data in the literature showing preferential expression of CXCR3 on T cells differentiated to a Th1 compared with a Th2 phenotype (29).

Our results on the induction of CXCR3 expression within several days of Ag receptor cross-linking are at odds with a previous report (26). In experiments of in vitro activation, these authors reported that CXCR3 was induced similarly to CCR5 only after prolonged incubation with IL-2. However, in analysis of freshly isolated PBL the authors also reported that, unlike CCR5, CXCR3 was coexpressed with CD25 and CD69, markers of acute activation. While we have no explanation for the discrepancies in the observations on the effects of in vitro activation on CXCR3 expression, the presence of CXCR3 on recently activated cells in the freshly isolated PBL is consistent with our findings. Most importantly, the validity of our results is reinforced by our data on calcium responses to both HuMig and IP-10 in 3-day activated naive CD4 cells from multiple donors.

The CC chemokine receptors CCR2, CCR3, and CCR5 were not expressed on fresh, naive CD4 cells (Fig. 2⇑). The absence of these receptors on resting, naive CD4 cells is well described in the literature (15, 23, 28). As a result of the absence of receptors on these cells, it would be expected that the corresponding chemokine ligands, expressed at peripheral sites, would not divert resting naive cells from trafficking appropriately through peripheral lymphoid tissue. In marked contrast with CXCR3, however, the CC receptors were not induced on naive CD4 cells that had been recently activated, nor were significant responses seen on activated naive cells to the CC ligands (Figs. 6⇑ and 7⇑). Published data demonstrate induction of high expression of functional CC chemokine receptors after long term incubation with IL-2 (19) and/or after repeated activation in defined Th1 or Th2 cytokine environments (28, 29, 41), and we have shown high levels of receptor mRNA expression (42) and CC chemokine signaling (R. L. Rabin and J. M. Farber, unpublished observations) on lines of tumor infiltrating lymphocytes that have been maintained in vitro with IL-2 and repeated rounds of restimulation with PHA. Together, these data suggest that on CD4 T cells, this group of CC chemokine receptors functions only on the fully differentiated populations.

Patterns of receptor expression on CD8 T cells differed in some respects from those seen on CD4 T cells. CXCR3, for example, was readily detected and functional, as judged by chemotaxis, on resting naive CD8 T cells, although, as on CD4 T cells, CXCR3 expression was markedly increased during activation. An interesting observation for CXCR3 and memory CD8 T cells was the preferential signaling of HuMig and IP-10 on the CD62L+ subset (Fig. 7⇑) despite no obvious difference in receptor levels between the CD62L+ and CD62L− cells (not shown). CLA+ memory T cells that home specifically to skin are found within the CD62L+ subset of CD8 T cells, and we have shown that all the freshly isolated CLA+ cells express CXCR3 (R. L. Rabin and J. M. Farber, unpublished observation). Because CLA is induced by IL-12 (43), this finding is consistent with persistent expression of CXCR3 on cells differentiated in a Th1 environment. In particular, this finding suggests that CXCR3 and its ligands may be important in contact hypersensitivity, a Th1-type response produced by CD8+ effector cells (44). Of note, HuMig and IP-10 have been shown to be produced at high levels by keratinocytes treated with IFN-γ (45, 46).

CC chemokine receptors were also expressed and regulated somewhat differently on CD8 vs CD4 T cells. Like naive CD4 T cells, resting and activated naive CD8 T cells were negative for CCR5, but unlike memory CD4 T cells, memory CD8 T cells showed no up-regulation of CCR5 after activation. In contrast, while CCR1 showed little induction on activated CD4 T cells, CCR1 expression was modestly enhanced by activation of CD8 T cells. CCR2 was unusual in that it functioned preferentially on CD4 T cells in assays for both chemotaxis and calcium flux despite the lack of a dramatic difference in CCR2 expression between CD4 and CD8 T cells. While some of the published literature has reported no differences in chemotaxis of CD4 and CD8 PBL (47) or T cell clones (18) to MCP-1 and MCP-3, other published chemotaxis data (13, 14) support our observations, which, in the case of our calcium flux assays, are based on cumulative data from 17 donors. Our data for preferential migration of resting CD8 vs CD4 T cells to RANTES are also at odds with published data showing either no chemotaxis (9) or significant, but no preferential, chemotaxis (14) of CD8 T cells to RANTES. While we have no explanation for these discrepancies, our data our consistent with the higher expression of CCR5 on resting CD8 compared with CD4 cells as shown in Fig. 2⇑ and as demonstrated previously (30).

Lastly, our analysis of calcium responses to chemokines showed, not surprisingly, a correlation between signaling on NK cells and CD8 cells, with NK cells responding to SDF-1, HuMig, IP-10, MIP-1α, and RANTES with little or no response to MIP-1β, MCP-1 and MCP-3. Except for SDF-1, which has been shown to produce a calcium signal in NK cells (48), other published data on NK cell responses to chemokines have relied on chemotaxis and have shown responses to MIP-1α, MCP-1, MCP-3, RANTES, and IP-10, with one group reporting negative (49) and one group reporting positive (50) results for MIP-1β. Because our analysis of NK cell responses was limited to calcium signaling, we cannot exclude the possibility that NK cells may show other responses, such as chemotaxis, to MIP-1β, MCP-1, and MCP-3.

A novel conclusion from our study is that receptor expression is often not the sole determinant of responses to chemokines. This is reflected in our observations, using the calcium flux assay, that 1) only a minority of receptor-expressing cells respond with a rise in [Ca]i, and the response is not simply a function of the level of receptor expression; 2) there are subset-related differences in signaling by a given receptor, such as a calcium flux to SDF-1 in freshly isolated cells occurring only in the memory subset of CD4 T cells despite equal or higher levels of CXCR4 in other subsets, preferential activity for MCP-1 (and MCP-3) on CD4 compared with CD8 T cells that could not be explained by differences in CCR2 expression, and preferential signaling in the activated CD62L+ memory CD8 T cells by HuMig and IP-10 despite no difference in CXCR3 expression between the CD62L+ and CD62L− memory CD8 T cells (data not shown); and 3) calcium signaling is affected by cellular activation. For example, prominent calcium responses to SDF-1 are seen on activated, but not freshly isolated, naive CD8 T cells despite equal or higher levels of CXCR4 on the fresh naive cells; responses are seen on activated, but not freshly isolated, memory CD8 T cells with MIP-1β despite equal or greater expression of CCR5 on the fresh memory cells, and no calcium fluxes are seen on resting cells with HuMig or IP-10 despite readily detectable CXCR3 expression. These last observations suggest that pathways leading to calcium fluxer are subject to physiological regulation within cells of a given subset.

Where we compared chemotaxis and calcium signals on the freshly isolated cells, there were clear discrepancies, with the results of the chemotaxis assays more closely reflecting the pattern of receptor expression among T cell subsets. Once the cells had been activated, however, receptors were competent to produce global increases in [Ca]i, so that patterns of calcium signaling more closely matched those of receptor expression, although contributions from CCR1 were not seen consistently, and we detected no signals from the low levels of expression of CCR3.

While our data are limited by not visualizing both chemotaxis and calcium fluxes simultaneously in individual cells, our finding of chemotaxis in populations of cells without detectable calcium flux is in line with the well-documented dissociation between the two phenomena. Calcium fluxers have been shown to be neither necessary nor sufficient for stimulation of actin association with cytoskeleton (51) or for chemotaxis in standard assays using a variety of chemotactic factors (52, 53, 54). For chemokines specifically, MCP-2 is chemotactic for monocytes without producing demonstrable increases in [Ca]i (55), and MIP-1α was shown to mobilize calcium in neutrophils without causing chemotaxis (56). One interpretation of our data might be that calcium flux has and chemotaxis in lymphocytes are independent consequences of a common G protein-dependent signaling pathway, but that detecting the calcium signal requires that the amplitude of the signal through that pathway be increased by cellular activation. Against this simple model is the report that chemotaxis mediated through CCR2 can be inhibited by diminishing the concentration of agonist-induced free G protein βγ subunits without eliminating calcium flux (54). In light of these findings, chemokine-induced calcium flux in activated T cells may be the result not simply of increasing the amplitude of the signaling pathways present in resting cells, but of the induction of an additional G protein-dependent pathway(s) subject to independent regulation.

If calcium flux and chemotaxis are independent phenomena, then it is reasonable to ask whether calcium fluxes have a physiological role in responses to chemotactic factors. One possible role would be in nonchemotactic processes induced by chemotactic factors, such as in adhesion or as has been shown for the requirement for calcium in exocytosis in neutrophils (57). There are, however, data suggesting that although not necessary for chemotaxis in the usual in vitro assays, calcium flux is important for chemotaxis on particular substrates that are relevant in vivo, such as fibronectin and vitronectin. On these substrates, buffering of [Ca]i leads to neutrophil immobilization due to an inability to break strong attachments (53). How these observations relate to lymphocytes are unknown, but they point out that although calcium flux may be unrelated to cellular motility per se, these fluxes may be central to trafficking in the more complex environment found in vivo.

By comparing receptor cell surface expression, calcium signaling, and chemotaxis for multiple chemokine receptors/chemokines in resting and activated lymphocyte subsets we have strengthened some previously reported observations and uncovered new relationships that suggest distinguishable roles for individual receptors and their ligands. A number of recent reports have described the selective expression of chemokine receptors on Th1 and Th2 cells that have been fully differentiated in vitro, often by repeated rounds of stimulation in highly polarized environments with cytokines (28, 29, 41, 58, 59, 60). Our data contribute to an additional perspective. In this view, the chemokine system can be understood not only within the Th1/Th2 paradigm, but also in terms of the stages of T cell activation and differentiation that are characterized by distinct patterns of trafficking. In reference to the ligands and receptors investigated here, SDF-1, a chemokine not associated with inflammatory responses, and its receptor CXCR4 can function on all subsets, including naive, resting cells; CXCR3 and its ligands become functional on recently activated, undifferentiated cells; and CXCR3 expression is subsequently maintained and poised for rapid up-regulation with reactivation. Receptors such as CCR2, CCR3, and CCR5 function only on the fully differentiated cells, and receptor expression is enhanced with continued and repeated cellular activation. In addition, we have found that the ability to produce a global calcium signal differs among receptors within a given T cell subset, and that for a given receptor signaling pathways can be regulated, depending on the cell’s state of activation and differentiation. These data may help in the design of interventions to manipulate the chemokine system to augment immunity or diminish inflammatory injury.

Acknowledgments

We thank Monica Tsang (R&D Systems) for SDF-1, Calman Prussin for Cy5-PE-conjugated anti-human CD56, Eileen O’Hara for expert technical assistance, Larry Duckett (BDIS) for modifying the FACSVantage flow cytometer with the linear ratio offset, Paul Ponath (LeukoSite) for generously providing anti-CCR3 and CXCR3 mAbs, and Naofumi Mukaida (Kanazaua University) for the anti-CCR1 antibodies.

Footnotes

  • ↵1 Address correspondence and reprint requests to Dr. Joshua M. Farber, Laboratory of Clinical Investigation, National Institute of Allergy and Infectious Diseases, Building 10, Room 11N-228 MSC 1888, National Institutes of Health, Bethesda, MD 20892. E-mail address: joshua_farber{at}nih.gov

  • ↵2 Abbreviations used in this paper: MIP, macrophage inflammatory protein; [Ca]i, intracellular calcium concentration; PE, phycoerythrin; CCR, CC chemokine receptor; CXCR, CXC chemokine receptor; HuMig, human monokine induced by interferon-γ; TIL, tumor-infiltrating lymphocytes; SDF-1, stromal cell-derived factor-1; MCP, macrophage chemoattractant protein; CLA, cutaneous lymphocyte-associated antigen; IP-10, interferon-γ-inducible protein-10.

  • Received October 21, 1998.
  • Accepted December 22, 1998.

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The Journal of Immunology: 162 (7)
The Journal of Immunology
Vol. 162, Issue 7
1 Apr 1999
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