Combinatorial peptide libraries and biometric score matrices permit the quantitative analysis of specific and degenerate interactions between clonotypic TCR and MHC peptide ligands

Identification of peptides from human pathogens able to cross-activate an HIV-1-gag-specific CD4+ T cell clone

Antigen recognition by T cells is degenerate both at the MHC and the TCR level. In this study, we analyzed the cross-reactivity of a human HIV-1 gag p24-specific CD4(+) T cell clone obtained from an HIV-1-seronegative donor using a positional scanning synthetic combinatorial peptide library (PS-SCL)-based biometrical analysis. A number of decapeptides able to activate the HIV-1 gag-specific clone were identified and shown to correspond to sequences found in other human pathogens. Two of these peptides activated the T cell clone with the same stimulatory potency as the original HIV-1 gag p24 peptide. These findings show that an HIV-1-specific human T helper clone can react efficiently with peptides from other pathogens and suggest that cellular immune responses identified as being specific for one human pathogen (HIV-1) could arise from exposure to other pathogens.

Contribution of peptides to multiple sclerosis research

Multiple sclerosis (MS) is an autoimmune disease associated with chronic inflammatory demyelination of the central nervous system in genetically susceptible individuals. Because of the disease complexity and heterogeneity, its pathogenesis remains unknown despite extensive research efforts, and specific effective treatments have not yet been developed. Peptide-based research has been important in attempts to unravel particular aspects of this complex disease, including the characterization of the different molecular mechanisms of MS, with the goal of providing useful products for immune-mediated therapies. In fact, in the past decade, peptide-based research has been predominant in research aimed to identify and/or develop target antigens as synthetic probes for specific biomarkers as well as innovative immunomodulating therapies. This review presents an overview of the contributions of peptide science to MS research and discusses future directions of peptide-based investigations.

Recognition of conserved amino acid motifs of common viruses and its role in autoimmunity

The triggers of autoimmune diseases such as multiple sclerosis (MS) remain elusive. Epidemiological studies suggest that common pathogens can exacerbate and also induce MS, but it has been difficult to pinpoint individual organisms. Here we demonstrate that in vivo clonally expanded CD4+ T cells isolated from the cerebrospinal fluid of a MS patient during disease exacerbation respond to a poly-arginine motif of the nonpathogenic and ubiquitous Torque Teno virus. These T cell clones also can be stimulated by arginine-enriched protein domains from other common viruses and recognize multiple autoantigens. Our data suggest that repeated infections with common pathogenic and even nonpathogenic viruses could expand T cells specific for conserved protein domains that are able to cross-react with tissue-derived and ubiquitous autoantigens.

High level of cross-reactivity in influenza virus hemagglutinin-specific CD4+ T-cell response: implications for the initiation of autoimmune response in multiple sclerosis

Viral infections play a role in shaping and maintaining the peripheral T-cell repertoire, as well as in the initiation of autoimmune response via mechanisms of molecular mimicry. In this study, we addressed the flexibility of T-cell receptor (TCR) recognition and the degree of structural and sequence homology required for cross-reactive immune response in the induction of autoimmune response. We studied the extent of cross-reactivity of a CD4+T-cell clone (TCC) specific for the immunodominant influenza virus hemagglutinin (Flu-HA) peptide derived from a patient with multiple sclerosis (MS) using positional scanning synthetic peptide combinatorial libraries (PS-SCL). We documented cross-reactivity against 14 Flu-HA variants, 11 viral, 15 human, and 3 myelin-derived peptides. Moreover, we identified six naturally occurring peptides with higher stimulatory potency than the native ligand, implicating high potential for cross-reactivity even for a virus-specific memory TCC. Our study demonstrates that flexibility of TCR recognition is present even in a clone with a high degree of TCR specificity for an infectious agent. The results have implications for vaccine design and for antigen-specific treatment strategies for autoimmune diseases.

Structure of a human autoimmune TCR bound to a myelin basic protein self-peptide and a multiple sclerosis-associated MHC class II molecule

Multiple sclerosis is mediated by T-cell responses to central nervous system antigens such as myelin basic protein (MBP). To investigate self-peptide/major histocompatibility complex (MHC) recognition and T-cell receptor (TCR) degeneracy, we determined the crystal structure, at 2.8 A resolution, of an autoimmune TCR (3A6) bound to an MBP self-peptide and the multiple sclerosis-associated MHC class II molecule, human leukocyte antigen (HLA)-DR2a. The complex reveals that 3A6 primarily recognizes the N-terminal portion of MBP, in contrast with antimicrobial and alloreactive TCRs, which focus on the peptide center. Moreover, this binding mode, which may be frequent among autoimmune TCRs, is compatible with a wide range of orientation angles of TCR to peptide/MHC. The interface is characterized by a scarcity of hydrogen bonds between TCR and peptide, and TCR-induced conformational changes in MBP/HLA-DR2a, which likely explain the low observed affinity. Degeneracy of 3A6, manifested by recognition of superagonist peptides bearing substitutions at nearly all TCR-contacting positions, results from the few specific interactions between 3A6 and MBP, allowing optimization of interface complementarity through variations in the peptide.

Immunology of multiple sclerosis

Multiple sclerosis (MS) develops in young adults with a complex predisposing genetic trait and probably requires an inciting environmental insult such as a viral infection to trigger the disease. The activation of CD4+ autoreactive T cells and their differentiation into a Th1 phenotype are a crucial events in the initial steps, and these cells are probably also important players in the long-term evolution of the disease. Damage of the target tissue, the central nervous system, is, however, most likely mediated by other components of the immune system, such as antibodies, complement, CD8+ T cells, and factors produced by innate immune cells. Perturbations in immunomodulatory networks that include Th2 cells, regulatory CD4+ T cells, NK cells, and others may in part be responsible for the relapsing-remitting or chronic progressive nature of the disease. However, an important paradigmatic shift in the study of MS has occurred in the past decade. It is now clear that MS is not just a disease of the immune system, but that factors contributed by the central nervous system are equally important and must be considered in the future.

Discovery and characterization of highly immunogenic and broadly recognized mimics of the HIV-1 CTL epitope Gag77-85

Human immunodeficiency virus (HIV)-specific cytotoxic T lymphocytes (CTL) play an important role in HIV infection. Given the viral genetic diversity, the selection of suitable antigens and epitope variants will be important in the design of an effective vaccine. We have previously shown that combinatorial libraries are useful tools to identify epitope mimics as well as potentially cross-reactive natural sequences in protein databases. We have applied this approach to the HIV Gag p17-derived epitope SL9 (SLYNTVATL) to identify broadly recognized SL9 mimics and to assess the cross-recognition of naturally occurring SL9 variants. Nine nonapeptides were identified that were up to one order of magnitude more effective than SL9 in stimulating CTL responses in PBMC from HIV-infected subjects. Using transgenic mice, we demonstrate that a number of these epitope mimics were able to generate de novo T cell responses that cross-reacted with the original SL9 sequence. Particularly, mimics with changes at the relatively conserved F-pocket anchor residue were frequently cross-recognized. This approach may lead to vaccine candidates with higher in vivo immunogenicity and increased potential for cross-recognition of naturally occurring SL9 variants.

Candidate epitope identification using peptide property models: application to cancer immunotherapy

Peptides derived from pathogens or tumors are selectively presented by the major histocompatibility complex proteins (MHC) to the T lymphocytes. Antigenic peptide-MHC complexes on the cell surface are specifically recognized by T cells and, in conjunction with co-factor interactions, can activate the T cells to initiate the necessary immune response against the target cells. Peptides that are capable of binding to multiple MHC molecules are potential T cell epitopes for diverse human populations that may be useful in vaccine design. Bioinformatical approaches to predict MHC binding peptides can facilitate the resource-consuming effort of T cell epitope identification. We describe a new method for predicting MHC binding based on peptide property models constructed using biophysical parameters of the constituent amino acids and a training set of known binders. The models can be applied to development of anti-tumor vaccines by scanning proteins over-expressed in cancer cells for peptides that bind to a variety of MHC molecules. The complete algorithm is described and illustrated in the context of identifying candidate T cell epitopes for melanomas and breast cancers. We analyzed MART-1, S-100, MBP, and CD63 for melanoma and p53, MUC1, cyclin B1, HER-2/neu, and CEA for breast cancer. In general, proteins over-expressed in cancer cells may be identified using DNA microarray expression profiling. Comparisons of model predictions with available experimental data were assessed. The candidate epitopes identified by such a computational approach must be evaluated experimentally but the approach can provide an efficient and focused strategy for anti-cancer immunotherapy development.

Peptides from common viral and bacterial pathogens can efficiently activate diabetogenic T-cells

Cross-reactivity between an autoantigen and unknown microbial epitopes has been proposed as a molecular mechanism involved in the development of insulin-dependent diabetes (type 1 diabetes). Type 1 diabetes is an autoimmune disease that occurs in humans and the nonobese diabetic (NOD) mouse. BDC2.5 is an islet-specific CD4+ T-cell clone derived from the NOD mouse whose natural target antigen is unknown. A biometrical analysis of screening data from BDC2.5 T-cells and a positional scanning synthetic combinatorial library (PS-SCL) was used to analyze and rank all peptides in public viral and bacterial protein databases and identify potential molecular mimic sequences with predicted reactivity. Selected sequences were synthesized and tested for stimulatory activity with BDC2.5 T-cells. Active peptides were identified, and some of them were also able to stimulate spontaneously activated T-cells derived from young, pre-diabetic NOD mice, indicating that the reactivity of the BDC2.5 T-cell is directed at numerous mouse peptides. Our results provide evidence for their possible role as T-cell ligands involved in the activation of diabetogenic T-cells.

Successful identification of novel agents to control infectious diseases from screening mixture-based peptide combinatorial libraries in complex cell-based bioassays

Mixture-based peptide synthetic combinatorial libraries (SCLs) represent a valuable source for the development of novel agents to control infectious diseases. Indeed, a number of studies have now proven the ability of identifying active peptides from libraries composed of thousands to millions of peptides in cell-based biosystems of varying complexity. Furthermore, progressing knowledge on the importance of endogenous peptides in various immune responses lead to a regain in importance for peptides as potential therapeutic agents. This article is aimed at providing recent studies in our laboratory for the development of antimicrobial or antiviral peptides derived from mixture-based SCLs using cell-based assays, as well as a short review of the importance of such peptides in the control of infectious diseases. Furthermore, the use of positional scanning (PS) SCL-based biometrical analyses for the identification of native optimal epitopes specific to HIV-1 proteins is also presented.

The initiation of the autoimmune response in multiple sclerosis

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system (CNS). Most evidence supports the autoimmune pathogenesis of the disease. According to this hypothesis, the activation of autoreactive T-cells is a central event in the development of autoimmune response in MS. We examined molecular events involved in the initiation of autoimmune response in MS. Recent studies in our laboratory have reported an unexpectedly high degree of T-cell receptor (TCR) degeneracy and molecular mimicry as a frequent phenomenon that might play a role in the initiation of autoimmune response in MS. This paper provides insights into the physiologic and pathologic role of autoreactive T-cells, and characterizes structurally and functionally the specific targets for new therapies of MS.

A novel method for evaluation and screening of caspase inhibitory peptides by the amino acid positional fitness score

Background

Since caspases are key executioners of apoptosis in cases of severe diseases including neurodegenerative disorders such as Alzheimer's disease and Huntington's disease, and viral infection diseases such as AIDS and hepatitis, potent and specific inhibitors of caspases have clinical potential. A series of peptide inhibitors has been designed based on cleavage sites of substrate proteins. However, these peptides are not necessarily the most potent to each caspase. Moreover, so far, it has proved to be difficult to design potent and specific peptide inhibitors of each caspase from sequence data of known cleavage sites in substrate proteins. We have attempted to develop a computational screening system for rapid selection of potent and specific peptide inhibitors from a comprehensive peptide library.

Results

We developed a new method for rapid evaluation and screening of peptide inhibitors based on Amino acid Positional Fitness (APF) score. By using this score, all known peptide inhibitors of each caspases-3,-7,-8, and -9 were rapidly selected in their enriched libraries. In this libraries, there were good correlations between predicted binding affinities of the known peptide inhibitors and their experimental Ki values. Furthermore, a novel potent peptide inhibitor, Ac-DNLD-CHO, for caspase-3 was able to be designed by this method. To our knowledge, DNLD is a first reported caspase-3 inhibitory peptide identified by using the computational screening strategy.

Conclusion

Our new method for rapid screening of peptide inhibitors using APF score is an efficient strategy to select potent and specific peptide inhibitors from a comprehensive peptide library. Thus, the APF method has the potential to become a valuable approach for the discovery of the most effective peptide inhibitors. Moreover, it is anticipated that these peptide inhibitors can serve as leads for further drug design and optimization of small molecular inhibitors.

Predicting peptide binding to MHC pockets via molecular modeling, implicit solvation, and global optimization

Development of a computational prediction method based on molecular modeling, global optimization, and implicit solvation has produced accurate structure and relative binding affinity predictions for peptide amino acids binding to five pockets of the MHC molecule HLA-DRB1*0101. Because peptide binding to MHC molecules is essential to many immune responses, development of such a method for understanding and predicting the forces that drive binding is crucial for pharmaceutical design and disease treatment. Underlying the development of this prediction method are two hypotheses. The first is that pockets formed by the peptide binding groove of MHC molecules are independent, separating the prediction of peptide amino acids that bind within individual pockets from those that bind between pockets. The second hypothesis is that the native state of a system composed of an amino acid bound to a protein pocket corresponds to the system's lowest free energy. The prediction method developed from these hypotheses uses atomistic-level modeling, deterministic global optimization, and three methods of implicit solvation: solvent-accessible area, solvent-accessible volume, and Poisson-Boltzmann electrostatics. The method predicts relative binding affinities of peptide amino acids for pockets of HLA-DRB1*0101 by determining computationally an amino acid's global minimum energy conformation. Prediction results from the method are in agreement with X-ray crystallography data and experimental binding assays.

Immunoproteomics: Mass spectrometry-based methods to study the targets of the immune response

The mammalian immune system has evolved to display fragments of protein antigens derived from microbial pathogens to immune effector cells. These fragments are typically peptides liberated from the intact antigens through distinct proteolytic mechanisms that are subsequently transported to the cell surface bound to chaperone-like receptors known as major histocompatibility complex (MHC) molecules. These complexes are then scrutinized by effector T cells that express clonally distributed T cell receptors with specificity for specific MHC-peptide complexes. In normal uninfected cells, this process of antigen processing and presentation occurs continuously, with the resultant array of self-antigen-derived peptides displayed on the surface of these cells. Changes in this peptide landscape of cells act to alert immune effector cells to changes in the intracellular environment that may be associated with infection, malignant transformation, or other abnormal cellular processes, resulting in a cascade of events that result in their elimination. Because peptides play such a crucial role in informing the immune system of infection with viral or microbial pathogens and the transformation of cells in malignancy, the tools of proteomics, in particular mass spectrometry, are ideally suited to study these immune responses at a molecular level. Here we review recent advances in the studies of immune responses that have utilized mass spectrometry and associated technologies, with specific examples from collaboration between our laboratories.

T-cell epitope prediction with combinatorial peptide libraries

T cell receptors (TCR) recognize antigenic peptides in complex with the major histocompatibility complex (MHC) molecules and this trimolecular interaction initiates antigen-specific signaling pathways in the responding T lymphocytes. For the study of autoimmune diseases and vaccine development, it is important to identify peptides (epitopes) that can stimulate a given TCR. The use of combinatorial peptide libraries has recently been introduced as a powerful tool for this purpose. A combinatorial library of n-mer peptides is a set of complex mixtures each characterized by one position fixed to be a specified amino acid and all other positions randomized. A given TCR can be fingerprinted by screening a variety of combinatorial libraries using a proliferation assay. Here, we present statistical models for elucidating the recognition profile of a TCR using combinatorial library proliferation assay data and known MHC binding data.

Systematic analysis of the combinatorial nature of epitopes recognized by TCR leads to identification of mimicry epitopes for glutamic acid decarboxylase 65-specific TCRs

Accumulating evidence indicates that recognition by TCRs is far more degenerate than formerly presumed. Cross-recognition of microbial Ags by autoreactive T cells is implicated in the development of autoimmunity, and elucidating the recognition nature of TCRs has great significance for revelation of the disease process. A major drawback of currently used means, including positional scanning synthetic combinatorial peptide libraries, to analyze diversity of epitopes recognized by certain TCRs is that the systematic detection of cross-recognized epitopes considering the combinatorial effect of amino acids within the epitope is difficult. We devised a novel method to resolve this issue and used it to analyze cross-recognition profiles of two glutamic acid decarboxylase 65-autoreactive CD4(+) T cell clones, established from type I diabetes patients. We generated a DNA-based randomized epitope library based on the original glutamic acid decarboxylase epitope using class II-associated invariant chain peptide-substituted invariant chains. The epitope library was composed of seven sublibraries, in which three successive residues within the epitope were randomized simultaneously. Analysis of agonistic epitopes indicates that recognition by both TCRs was significantly affected by combinations of amino acids in the antigenic peptide, although the degree of combinatorial effect differed between the two TCRs. Protein database searching based on the TCR recognition profile proved successful in identifying several microbial and self-protein-derived mimicry epitopes. Some of the identified mimicry epitopes were actually produced from recombinant microbial proteins by APCs to stimulate T cell clones. Our data demonstrate the importance of the combinatorial nature of amino acid residues of epitopes in molecular mimicry.

Combinatorial peptide library methods for immunobiology research

The field of combinatorial peptide chemistry has emerged as a powerful tool in the study of many biological systems. This review focuses on combinatorial peptide library methodology, which includes biological library methods, spatially addressable parallel library methods, library methods requiring deconvolution, the "one-bead one-compound" library method, and affinity chromatography selection method. These peptide libraries have successfully been employed to study a vast array of cell surface receptors, as well as have been useful in identifying protein kinase substrates and inhibitors. In recent immunobiological applications, peptide libraries have proven monumental in the definition of MHC anchor residues, in lymphocyte epitope mapping, and in the development of peptide vaccines. Peptides identified from such libraries, when presented in a chemical microarray format, may prove useful in immunodiagnostics. Combinatorial peptide libraries offer a high-throughput approach to study limitless biological targets. Peptides discovered from such studies may be therapeutically and diagnostically useful agents.

Proteomics in Vaccinology and Immunobiology: An Informatics Perspective of the Immunone

The postgenomic era, as manifest, inter alia, by proteomics, offers unparalleled opportunities for the efficient discovery of safe, efficacious, and novel subunit vaccines targeting a tranche of modern major diseases. A negative corollary of this opportunity is the risk of becoming overwhelmed by this embarrassment of riches. Informatics techniques, working to address issues of both data management and through prediction to shortcut the experimental process, can be of enormous benefit in leveraging the proteomic revolution. In this disquisition, we evaluate proteomic approaches to the discovery of subunit vaccines, focussing on viral, bacterial, fungal, and parasite systems. We also adumbrate the impact that proteomic analysis of host-pathogen interactions can have. Finally, we review relevant methods to the prediction of immunome, with special emphasis on quantitative methods, and the subcellular localization of proteins within bacteria.

Identification of tumor-associated HLA-ligands in the post-genomic era

Over 10 years ago, the identification of the first tumor-specific T cell epitope shed light on the molecular principles underlying the phenomenon of tumor eradication by the immune system. Since then, a considerable number of different approaches for this task have been introduced and employed successfully, reflecting the growing knowledge about the cellular processes preceding antigen presentation as well as significant technical developments. This review tries to give an overview over available conventional strategies as well as current developments that utilize the potent large-scale screening tools of the post-genomic era.

Genomics-based identification of self-ligands with T cell receptor-specific biological activity

Self-peptide/major histocompatibility complex (MHC) complexes profoundly influence the biology of T lymphocytes. They promote the selection of the T cell receptor (TCR) repertoire in the thymus, maintain the homeostasis of peripheral T cells prior to encounter with antigen, and modify the responsiveness of T cells to foreign antigens. In addition, they can serve as antigens for autoaggressive T cells that induce autoimmune diseases. The complete sequencing of the genomes of human, mouse, and many pathogenic organisms now provides us with a comprehensive list of all possible proteins that may be the source of foreign antigenic and self-peptides. A computational approach using profile-based similarity searches on potential self-MHC-binding peptides can be used to efficiently predict self-peptides with biological activities. The common feature of the identified peptides is similarity to antigen. Thus, self-peptides may form 'hazy' images of the universe of antigens that are used as templates to create and maintain the TCR repertoire.

Positional scanning-synthetic peptide library-based analysis of self- and pathogen-derived peptide cross-reactivity with tumor-reactive Melan-A-specific CTL

Synthetic combinatorial peptide libraries in positional scanning format (PS-SCL) have recently emerged as a useful tool for the analysis of T cell recognition. This includes identification of potentially cross-reactive sequences of self or pathogen origin that could be relevant for the understanding of TCR repertoire selection and maintenance, as well as of the cross-reactive potential of Ag-specific immune responses. In this study, we have analyzed the recognition of sequences retrieved by using a biometric analysis of the data generated by screening a PS-SCL with a tumor-reactive CTL clone specific for an immunodominant peptide from the melanocyte differentiation and tumor-associated Ag Melan-A. We found that 39% of the retrieved peptides were recognized by the CTL clone used for PS-SCL screening. The proportion of peptides recognized was higher among those with both high predicted affinity for the HLA-A2 molecule and high predicted stimulatory score. Interestingly, up to 94% of the retrieved peptides were cross-recognized by other Melan-A-specific CTL. Cross-recognition was at least partially focused, as some peptides were cross-recognized by the majority of CTL. Importantly, stimulation of PBMC from melanoma patients with the most frequently recognized peptides elicited the expansion of heterogeneous CD8(+) T cell populations, one fraction of which cross-recognized Melan-A. Together, these results underline the high predictive value of PS-SCL for the identification of sequences cross-recognized by Ag-specific T cells.

Presentation of native TROP-2 tumor antigens to human cytotoxic T lymphocytes by engineered antigen-presenting cells

Professional antigen-presenting cells (APC), e.g. dendritic cells, express immuno-proteasome components and process proteins for MHC presentation differently from non-immune cells. Thus, they induce reactivities against sets of peptides that do not overlap with those generated by non-professional APC, i.e., tumor cells, and stimulate cytotoxic T lymphocytes (CTL) that may not recognize them. The goal of this work was to establish a system for antigen presentation and in vitro stimulation of human CTL using "tumor-cell-like" engineered APC. Murine fibroblasts were transfected with human HLA Class I alleles, together with the B7.1, ICAM-1 and germ-line TROP2 genes. The last encodes a cell surface glycoprotein widely expressed by human cancers. Unseparated peripheral blood mononuclear cells from HLA Class I-matched individuals were stimulated in vitro by the engineered APC. These efficiently induced the activation and proliferation of antigen-specific HLA-restricted CTL lines and clones. The Trop-2-specific CTL demonstrated high specific cytotoxicity against the appropriate transfected target cells. They also efficiently lysed MCF-7 human tumor cells expressing endogenous HLA-A2.1, Trop-2 together with ICAM-1. These results demonstrate that Trop-2 is a target molecule recognized by human CTL. Moreover, they demonstrate that non-immune engineered APC efficiently process and present native tumor-specific proteins in the context of human MHC Class I, and stimulate the growth and cytotoxicity of specific anti-tumor CTL.

Findings on T cell specificity revealed by synthetic combinatorial libraries

Combinatorial libraries and in particular positional scanning synthetic combinatorial libraries (PS-SCL) allow the study of T cell specificity. This is a systematic and unbiased approach that does not require any previous knowledge about the clones to be studied, neither their specificity nor they major histocompatibility complex (MHC) restriction. Two different types of T cell clone ligands can be identified: (1) peptides that do not necessarily correspond to proteins described in the databases, and (2) peptides that are fragments of natural proteins. In this paper, relevant examples of the application of PS-SCL and the deconvolution strategies followed to identify T cell epitopes for clones of known and unknown specificity will be reviewed. Also, important issues like the immunogenicity of such T cell ligands will be discussed.

Degeneracy of antigen recognition as the molecular basis for the high frequency of naive A2/Melan-a peptide multimer(+) CD8(+) T cells in humans

In contrast with the low frequency of most single epitope reactive T cells in the preimmune repertoire, up to 1 of 1,000 naive CD8(+) T cells from A2(+) individuals specifically bind fluorescent A2/peptide multimers incorporating the A27L analogue of the immunodominant 26-35 peptide from the melanocyte differentiation and melanoma associated antigen Melan-A. This represents the only naive antigen-specific T cell repertoire accessible to direct analysis in humans up to date. To get insight into the molecular basis for the selection and maintenance of such an abundant repertoire, we analyzed the functional diversity of T cells composing this repertoire ex vivo at the clonal level. Surprisingly, we found a significant proportion of multimer(+) clonotypes that failed to recognize both Melan-A analogue and parental peptides in a functional assay but efficiently recognized peptides from proteins of self- or pathogen origin selected for their potential functional cross-reactivity with Melan-A. Consistent with these data, multimers incorporating some of the most frequently recognized peptides specifically stained a proportion of naive CD8(+) T cells similar to that observed with Melan-A multimers. Altogether these results indicate that the high frequency of Melan-A multimer(+) T cells can be explained by the existence of largely cross-reactive subsets of naive CD8(+) T cells displaying multiple specificities.