Cellular immune responses to pathogens, allergens, deregulated or mutated proteins, and self-antigens play critical roles in health and disease. The ability of T cells to respond to the immense diversity of possible targets relies on the corresponding diversity of the repertoire of TCRs that can be generated by the immune system. The T cell population in each individual is diverse and dynamic. Even after exposure to a potent T cell antigen, an individual TCR clone seldom accounts for more than 5% of the total population of T cells in a normal human or mouse. Moreover, the specificities and phenotypes of the individual's T cell repertoire may provide a rich picture of the immunological history, the physiological status, and perhaps the disease susceptibilities of that individual. A broad picture of the dynamic responses of the T cell repertoire to an immunological challenge should illuminate our understanding of the immune response and may point to individual-specific response patterns that can help guide design of immunological therapies.
The development of peptide–MHC tetramers (Altman et al. 1996
) and variations (Greten et al. 1998
) as staining reagents has greatly aided the analysis of antigen-specific populations of CD4 and CD8 T cells. Unfortunately, the number of specificities that can be analyzed is severely limited by the fluorescence spectra available for conjugation to individual peptide–MHC complexes.
Furthermore, the complex compensation required for multiple fluorophores and numerous controls required for adequate tetramer staining, such as a control tetramer, propidium iodide for dead cell staining, anti-CD8, anti-CD11, anti-CD19, and anti-CD56, further restrict the ability to analyze multiple specificities simultaneously. Hence, analyzing more than a few specificities is difficult and is impractical for a typical clinical sample. By using specified, predetermined spatial coordinates rather than fluorescent tags, microarray technology has revolutionized the analysis of gene and protein expression, allowing the simultaneous analysis of hundreds to thousands of different variations in gene and protein expression. This approach has been recently used to analyze intact cells (Belov et al. 2001
; Brown et al. 2003), allowing the simultaneous characterization of hundreds of cell surface molecules, by applying a homogenous population of cells to an array of mAbs. We have extended the experimental logic of that approach to the characterization and isolation of antigen-specific populations of T cells from a heterogeneous cell mixture. Furthermore, cospotting peptide–MHCs with other effector molecules and/or co-culturing the T cells with other effector cells may allow for high throughput examination of MHC presentation in the context of other molecular signals and might open exciting avenues for antigen-specific intercellular interaction assays. Together, these methods should provide an efficient approach to epitope discovery and broad, systematic characterization of TCR specificity and the relations between epitope recognition and T cell activation, reactivity, anergy, and cell death.
The excellent performance of peptide–MHC complexes as binding probes in our cellular microarray format is somewhat surprising because the typical TCR affinity is about 103
- to 104
-fold lower than that of a typical mAb and its antigen (Davis et al. 1998
). Still, sufficient numbers of peptide–MHC complexes bound to a given cell can compensate for relatively low affinity of a single peptide–MHC–TCR interaction. In fact, a simple order of magnitude calculation shows that for a typical peptide–MHC concentration, as few as approximately 200 peptide–MHC–TCR interactions are sufficient to capture and stably hold a cell against typical flow forces experienced during the washing of unbound cells (an example of this calculation is provided in the Supporting Information section).
The combination of large spots on an inert substrate allows the reliable detection of as few as three to five bound cells per spot. For cells with a diameter of 10 μm on a 400 μm spot, this corresponds to a dynamic range of about 300-fold, which can be further increased using larger spot sizes (i.e., dispensing more drops on each spot) or using multiple spots of the same size. More importantly, since rare populations of cells can be detected only when a sufficient number of them encounter the appropriate probe region, the total probe area (i.e., surface area of one spot multiplied by the number of identical spots) has a major effect on the sensitivity. We have shown that the limit of detection with a single 400 μm spot of a weak model antigen is about 0.1% (i.e., one positive out of 1,000 cells). Increasing the number of identical spots results in an improvement in sensitivity, the extent of which is under investigation. Further improvement might be achieved by increased exposure of cells to each MHC-printed region (e.g., by sample agitation, reloading, or directed flow). Another route towards a significant improvement in both sensitivity and signal-to-noise ratio is cell enrichment prior to MHC array analysis. For example, preselection of CD8+ or CD4+ from peripheral blood mononuclear cells (e.g., by bead selection or FACS sorting) results in approximately a 10-fold enrichment of specific target cells and eliminates the nonspecific binding of a subpopulation of CD11b+ cells to MHC spots. Further enrichment via negative and/or positive selection using common markers would almost certainly extend the lower limit of partial abundance required for detection.
The number of cells captured on the array depends on the abundance of cells expressing the appropriate TCR, its expression level, and affinity to the peptide–MHC complex, the concentration, functionality, and accessibility of that complex, and several other factors, including the local cell density, incubation, and washing conditions, local film, integrity etc. Consequently, estimating the frequency of cells expressing a given antigen specificity requires the development of a standardized protocol. One possible approach is to coexpose differentially labeled cell populations to the same spots using a standard pool of T cells as a common internal standard in each analysis, analogous to the reference RNA commonly used for DNA microarray studies of gene expression (Eisen and Brown 1999
). The use of a common internal standard can provide a way to eliminate local spot- and slide-dependent factors and obtain a relative measure for the number of cells that are above the threshold for functional binding, allowing quantitative differential profiling of cell surface markers based on the relative number of bound cells.
The use of printed arrays of specific binding reagents for characterizing populations of cells has similarities to FACS in concept and applications. FACS has the advantage of allowing analysis on a cell-by-cell basis, while the cellular microarray approach allows a much larger number of molecules to be analyzed in a population of cells. Currently, a single cellular microarray can accommodate more than 1,000 peptide–MHC probes (without decreasing the spot size), which allows detection of 1,000 antigen-specific cell populations in a single assay. Each cellular microarray-based assay is easy to perform, utilizes fixed gating that eliminates the subjective gating of FACS-based analysis, and allows many samples to be analyzed side by side either on the same slide (for small arrays) or on different slides. The high throughput should make it practical to screen a sample population of cells (e.g., from a patient) against a large panel of candidate peptide–MHC complexes or to discover novel MHC-restricted epitopes by screening libraries of random, mutated, and chemically modified sequences. Although the fractional abundance of specific T cells required for detection in our experiments (0.1%) is not as low as can be detected in the best FACS analyses (0.01%), it is already sufficient to identify an immune response of clinical relevance and is likely to improve with further optimization.
What are the prospects for efficient array-based detection of immune responses and characterization of the TCR recognition and activation landscape? The actual set of TCR specificities and sensitivities, at any given time, depends on the history of exposure to antigens, genotype, and the physiological parameters. We have shown that a physiologically relevant response to an antigen challenge is detectable as cell capture by the cognate peptide–MHC (see ). Since an expanded population of activated T cells may cross-react with epitopes having a considerable degree of sequence homology (Reay et al. 1994
; Wucherpfennig and Strominger 1995
; Kersh and Allen 1996
; Bach et al. 1998
; Honeyman et al. 1998
; Mason 1998
; Zhao et al. 1998
; Hiemstra et al. 1999
; Misko et al. 1999
), a signature of binding to multiple peptides is also possible, especially for structurally similar epitopes (high surface concentration of the peptide–MHC may further contribute to the ability to capture cross-reacting T cells). Moreover, in numerous important pathologies associated with both specific and nonspecific polyclonal activation of the host immune system, the binding of activated clones to many unrelated (and often self-protein-derived) peptides is very plausible. For example, a single cancer patient can develop immune responses to multiple tumor-associated antigens (Rosenberg 2001
). In one case, tumor-infiltrating lymphocytes from a single patient recognized tyrosinase (a differentiation antigen presented by human leucocyte antigen [HLA] class I), β-catenin (a class I mutation), p15 (a class I antigen involved in posttranscriptional control), gp100 (a class I intronic sequence and class II normal sequence), tyrosinase-related protein-1 (TRP-1, a class II differentiation antigen), TRP-2 (a class II differentiation antigen), and Ki-67 (a class II mutation).
The wide range of specificities against nonhomologous antigens demonstrated in this and other reports strongly supports the feasibility of cellular microarray-based characterization of patient-specific immune response patterns. An example for a nonspecific, clinically important response is a superantigen-induced stimulation, which often leads to a massive polyclonal lymphocyte activation that might account for up to 30% of the host T cell repertoire (depending on the number of Vβ
families capable of interacting with the superantigen) (Muller-Alouf et al. 2001
). Still, while the cellular microarray should be sensitive enough to identify and examine binding patterns in activated samples, its ability to characterize the naive repertoire might be limited. This drawback may be mitigated by modifying the geometry of the array and/or the sample introduction method so as to increase the chances of rare cell populations encountering each of the peptide–MHC complexes.
Taking advantage of the full potential of this approach requires convenient means for synthesizing diverse arrays of peptide–MHC complexes. Conventional MHC tetramer synthesis is cumbersome and technically difficult, making the effective implementation of large, functional peptide–MHC libraries a practical challenge. However, usage of reloadable MHC constructs such as DimerX (BD Biosciences) or the MHC tetramer-based Epitope Discovery System (Beckman Coulter) should allow for an efficient production of printable MHC molecules loaded with diverse peptide epitopes of interest. Indeed, preliminary experiments suggest that the DimerX peptide-loadable reagent has a similar specificity and sensitivity to that of peptide–MHC tetramers.
The experimental strategy introduced here provides a powerful tool for simultaneous detection and study of antigen-specific T cell populations. This technique can be performed rapidly (10 min), requires little technical expertise, and allows screening of a single clinical sample (with CD4+ and/or CD8+ T cells) against a library of specific or random peptide–MHCs. Although the data presented here were generated using cells derived from mice, preliminary results indicate that this approach works equally well with human samples. Numerous clinically significant MHC-restricted epitopes have already been defined. These can be easily printed on a single microarray to provide a rapid test for the cognate T cell responses and to study the involvement of multiple epitopes during the course of a disease or following vaccination. Co-immobilization with effector molecules and cells may assist in identifying key factors that take part in the regulation of T cell effector function. Thus, the development of peptide–MHC cellular microarrays should provide valuable insights into dynamic and individual variations in the global repertoire of T cell specificities and the mechanisms that control them.