Anthrax toxin-mediated delivery of a cytotoxic T-cell epitope in vivo.

The protective antigen (PA) component of anthrax toxin mediates entry of the toxin's lethal factor (LF) and edema factor into the cytosolic compartment of mammalian cells. The amino-terminal domain of LF (LFn; 255 amino acids) binds LF to PA, and when fused to heterologous proteins, the LFn domain delivers such proteins to the cytoplasm in the presence of PA. In the current study, we fused a 9-amino acid cytotoxic T-lymphocyte (CTL) epitope (LLO91-99) from an intracellular pathogen, Listeria monocytogenes, to LFn and measured the ability of the resulting LFn-LLO91-99 fusion protein to stimulate a CTL response against the epitope in BALB/c mice. As little as 300 fmol of fusion could stimulate a response. The stimulation was PA-dependent and occurred with the peptide fused to either the amino terminus or the carboxyl terminus of LFn. Upon challenge with L. monocytogenes, mice previously injected with LFn-LLO91-99 and PA showed a reduction of colony-forming units in spleen and liver, relative to nonimmunized control mice. These results indicate that anthrax toxin may be useful as a CTL-peptide delivery system for research and medical applications.

Systemic versus cartilage-specific expression of a type II collagen-specific T-cell epitope determines the level of tolerance and susceptibility to arthritis.

Immunization of mice with rat type II collagen (CII), a cartilage-specific protein, leads to development of collagen-induced arthritis (CIA), a model for rheumatoid arthritis. To define the interaction between the immune system and cartilage, we produced two sets of transgenic mice. In the first we point mutated the mouse CII gene to express an earlier defined T-cell epitope, CII-(256-270), present in rat CII. In the second we mutated the mouse type I collagen gene to express the same T-cell epitope. The mice with mutated type I collagen showed no T-cell reactivity to rat CII and were resistant to CIA. Thus, the CII-(256-270) epitope is immunodominant and critical for development of CIA. In contrast, the mice with mutated CII had an intact B-cell response and had T cells which could produce gamma interferon, but not proliferate, in response to CII. They developed CIA, albeit with a reduced incidence. Thus, we conclude that T cells recognize CII derived from endogenous cartilage and are partially tolerized but may still be capable of mediating CIA.

T-cell epitope analysis using subtracted expression libraries (TEASEL): application to a 38-kDA autoantigen recognized by T cells from an insulin-dependent diabetic patient.

Studies on circulating T cells and antibodies in newly diagnosed type 1 diabetic patients and rodent models of autoimmune diabetes suggest that beta-cell membrane proteins of 38 kDa may be important molecular targets of autoimmune attack. Biochemical approaches to the isolation and identification of the 38-kDa autoantigen have been hampered by the restricted availability of islet tissue and the low abundance of the protein. A procedure of epitope analysis for CD4+ T cells using subtracted expression libraries (TEASEL) was developed and used to clone a 70-amino acid pancreatic beta-cell peptide incorporating an epitope recognized by a 38-kDa-reactive CD4+ T-cell clone (1C6) isolated from a human diabetic patient. The minimal epitope was mapped to a 10-amino acid synthetic peptide containing a DR1 consensus binding motif. Data base searches did not reveal the identity of the protein, though a weak homology to the bacterial superantigens SEA (Streptococcus pyogenes exotoxin A) and SEB (Staphylococcus aureus enterotoxin B) (23% identity) was evident. The TEASEL procedure might be used to identify epitopes of other autoantigens recognized by CD4+ T cells in diabetes as well as be more generally applicable to the study low-abundance autoantigens in other tissue-specific autoimmune diseases.

Fine specificity of the antibody response to myelin basic protein in the central nervous system in multiple sclerosis: the minimal B-cell epitope and a model of its features.

T cells, B cells, and antibody are found in the white matter of the central nervous system in multiple sclerosis. The epitope center for the antibody response to human myelin basic protein (MBP) fits precisely the minimal epitope Pro85-Val-Val-His-Phe-Phe-Lys-Asn-Ile-Val-Thr-Pro96 for that reported for HLA DR2b (DRB1*1501)-restricted T cells that recognize MBP [Wucherpfenning, K.W., Sette, A., Southwood, S., Oseroff, C., Matsui, M., Strominger, J. & Hafler, D. (1994) J. Exp. Med. 179, 279-290], and overlaps with the reported DR2a-restricted epitope for T cells reactive to MBP [Martin, R., Howell, M. D., Jaraquemada, D., Furlage, M., Richert, J., Brostoff, S., Long, E. O., McFarlin, D. E. & McFarland, H. F. (1991) J. Exp. Med. 173, 19-24]. We describe a molecular model of this epitope.

Similar antigenic surfaces, rather than sequence homology, dictate T-cell epitope molecular mimicry.

Molecular mimicry, normally defined by the level of primary-sequence similarities between self and foreign antigens, has been considered a key element in the pathogenesis of autoimmunity. Here we describe an example of molecular mimicry between two overlapping peptides within a single self-antigen, both of which are recognized by the same human self-reactive T-cell clone. Two intervening peptides did not stimulate the T-cell clone, even though they share nine amino acids with the stimulatory peptides. Molecular modeling of major histocompatibility complex class II-peptide complexes suggests that both of the recognized peptides generate similar antigenic surfaces, although these are composed of different sets of amino acids. The molecular modeling of a peptide shifted one residue from the stimulatory peptide, which was recognized in the context of the same HLA molecule by another T-cell clone, generated a completely different antigenic surface. Functional studies using truncated peptides confirmed that the anchor residues of the two "mimicking" epitopes in the HLA groove differ. Our results show, for two natural epitopes, how molecular mimicry can occur and suggest that studies of potential antigenic surfaces, rather than sequence similarity, are necessary for analyzing suspected peptide mimicry.

SARS coronavirus nucleocapsid immunodominant T-cell epitope cluster is common to both exogenous recombinant and endogenous DNA-encoded immunogens

Correspondence between the T-cell epitope responses of vaccine immunogens and those of pathogen antigens is critical to vaccine efficacy. In the present study, we analyzed the spectrum of immune responses of mice to three different forms of the SARS coronavirus nucleocapsid (N): (1) exogenous recombinant protein (N-GST) with Freund's adjuvant; (2) DNA encoding unmodified N as an endogenous cytoplasmic protein (pN); and (3) DNA encoding N as a LAMP-I chimera targeted to the lysosomal MHC II compartment (p-LAMP-N). Lysosomal trafficking of the LAMP/N chimera in transfected cells was documented by both confocal and immunoelectron microscopy. The responses of the immunized mice differed markedly. The strongest T-cell IFN-gamma and CTL responses were to the LAMP-N chimera followed by the pN immunogen. In contrast, N-GST elicited strong T cell IL-4 but minimal IFN-gamma responses and a much greater antibody response. Despite these differences, however, the immunodominant T-cell ELISpot responses to each of the three immunogens were elicited by the same N peptides, with the greatest responses being generated by a cluster of five overlapping peptides, N76-114, each of which contained nonameric H2(d) binding domains with high binding scores for both class I and, except for N76-93, class II alleles. These results demonstrate that processing and presentation of N, whether exogenously or endogenously derived, resulted in common immunodominant epitopes, supporting the usefulness of modified antigen delivery and trafficking forms and, in particular, LAMP chimeras as vaccine candidates. Nevertheless, the profiles of T-cell responses were distinctly different. The pronounced Th-2 and humoral response to N protein plus adjuvant are in contrast to the balanced IFN-gamma and IL-4 responses and strong memory CTL responses to the LAMP-N chimera. (C) 2005 Elsevier Inc. All rights reserved.

Immunoinformatic evaluation of multiple epitope ensembles as vaccine candidates:E coli 536

Epitope prediction is becoming a key tool for vaccine discovery. Prospective analysis of bacterial and viral genomes can identify antigenic epitopes encoded within individual genes that may act as effective vaccines against specific pathogens. Since B-cell epitope prediction remains unreliable, we concentrate on T-cell epitopes, peptides which bind with high affinity to Major Histacompatibility Complexes (MHC). In this report, we evaluate the veracity of identified T-cell epitope ensembles, as generated by a cascade of predictive algorithms (SignalP, Vaxijen, MHCPred, IDEB, EpiJen), as a candidate vaccine against the model pathogen uropathogenic gram negative bacteria Escherichia coli (E-coli) strain 536 (O6:K15:H31). An immunoinformatic approach was used to identify 23 epitopes within the E-coli proteome. These epitopes constitute the most promiscuous antigenic sequences that bind across more than one HLA allele with high affinity (IC50 <50nM). The reliability of software programmes used, polymorphic nature of genes encoding MHC and what this means for population coverage of this potential vaccine are discussed.

Proteins accessible to immune surveillance show significant T-cell epitope depletion:implications for vaccine design

T cell activation is the final step in a complex pathway through which pathogen-derived peptide fragments can elicit an immune response. For it to occur, peptides must form stable complexes with Major Histocompatibility Complex (MHC) molecules and be presented on the cell surface. Computational predictors of MHC binding are often used within in silico vaccine design pathways. We have previously shown that, paradoxically, most bacterial proteins known experimentally to elicit an immune response in disease models are depleted in peptides predicted to bind to human MHC alleles. The results presented here, derived using software proven through benchmarking to be the most accurate currently available, show that vaccine antigens contain fewer predicted MHC-binding peptides than control bacterial proteins from almost all subcellular locations with the exception of cell wall and some cytoplasmic proteins. This effect is too large to be explained from the undoubted lack of precision of the software or from the amino acid composition of the antigens. Instead, we propose that pathogens have evolved under the influence of the host immune system so that surface proteins are depleted in potential MHC-binding peptides, and suggest that identification of a protein likely to contain a single immuno-dominant epitope is likely to be a productive strategy for vaccine design.

Toward the prediction of class I and II mouse major histocompatibility complex-peptide-binding affinity:in silico bioinformatic step-by-step guide using quantitative structure-activity relationships

Quantitative structure-activity relationship (QSAR) analysis is a cornerstone of modern informatics. Predictive computational models of peptide-major histocompatibility complex (MHC)-binding affinity based on QSAR technology have now become important components of modern computational immunovaccinology. Historically, such approaches have been built around semiqualitative, classification methods, but these are now giving way to quantitative regression methods. We review three methods--a 2D-QSAR additive-partial least squares (PLS) and a 3D-QSAR comparative molecular similarity index analysis (CoMSIA) method--which can identify the sequence dependence of peptide-binding specificity for various class I MHC alleles from the reported binding affinities (IC50) of peptide sets. The third method is an iterative self-consistent (ISC) PLS-based additive method, which is a recently developed extension to the additive method for the affinity prediction of class II peptides. The QSAR methods presented here have established themselves as immunoinformatic techniques complementary to existing methodology, useful in the quantitative prediction of binding affinity: current methods for the in silico identification of T-cell epitopes (which form the basis of many vaccines, diagnostics, and reagents) rely on the accurate computational prediction of peptide-MHC affinity. We have reviewed various human and mouse class I and class II allele models. Studied alleles comprise HLA-A*0101, HLA-A*0201, HLA-A*0202, HLA-A*0203, HLA-A*0206, HLA-A*0301, HLA-A*1101, HLA-A*3101, HLA-A*6801, HLA-A*6802, HLA-B*3501, H2-K(k), H2-K(b), H2-D(b) HLA-DRB1*0101, HLA-DRB1*0401, HLA-DRB1*0701, I-A(b), I-A(d), I-A(k), I-A(S), I-E(d), and I-E(k). In this chapter we show a step-by-step guide into predicting the reliability and the resulting models to represent an advance on existing methods. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made are freely available online at the URL http://www.jenner.ac.uk/MHCPred.

Toward prediction of class II mouse major histocompatibility complex peptide binding affinity:in silico bioinformatic evaluation using partial least squares, a robust multivariate statistical technique

The accurate identification of T-cell epitopes remains a principal goal of bioinformatics within immunology. As the immunogenicity of peptide epitopes is dependent on their binding to major histocompatibility complex (MHC) molecules, the prediction of binding affinity is a prerequisite to the reliable prediction of epitopes. The iterative self-consistent (ISC) partial-least-squares (PLS)-based additive method is a recently developed bioinformatic approach for predicting class II peptide−MHC binding affinity. The ISC−PLS method overcomes many of the conceptual difficulties inherent in the prediction of class II peptide−MHC affinity, such as the binding of a mixed population of peptide lengths due to the open-ended class II binding site. The method has applications in both the accurate prediction of class II epitopes and the manipulation of affinity for heteroclitic and competitor peptides. The method is applied here to six class II mouse alleles (I-Ab, I-Ad, I-Ak, I-As, I-Ed, and I-Ek) and included peptides up to 25 amino acids in length. A series of regression equations highlighting the quantitative contributions of individual amino acids at each peptide position was established. The initial model for each allele exhibited only moderate predictivity. Once the set of selected peptide subsequences had converged, the final models exhibited a satisfactory predictive power. Convergence was reached between the 4th and 17th iterations, and the leave-one-out cross-validation statistical terms - q2, SEP, and NC - ranged between 0.732 and 0.925, 0.418 and 0.816, and 1 and 6, respectively. The non-cross-validated statistical terms r2 and SEE ranged between 0.98 and 0.995 and 0.089 and 0.180, respectively. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made freely available online (http://www.jenner.ac.uk/MHCPred).

MHCPred : a server for quantitative prediction of peptide-MHC binding

Accurate T-cell epitope prediction is a principal objective of computational vaccinology. As a service to the immunology and vaccinology communities at large, we have implemented, as a server on the World Wide Web, a partial least squares-base multivariate statistical approach to the quantitative prediction of peptide binding to major histocom-patibility complexes (MHC), the key checkpoint on the antigen presentation pathway within adaptive,cellular immunity. MHCPred implements robust statistical models for both Class I alleles (HLA-A*0101, HLA-A*0201, HLA-A*0202, HLA-A*0203,HLA-A*0206, HLA-A*0301, HLA-A*1101, HLA-A*3301, HLA-A*6801, HLA-A*6802 and HLA-B*3501) and Class II alleles (HLA-DRB*0401, HLA-DRB*0401and HLA-DRB* 0701).

EPIPOX:immunoinformatic characterization of the shared T-cell epitome between variola virus and related pathogenic orthopoxviruses

Concerns that variola viruses might be used as bioweapons have renewed the interest in developing new and safer smallpox vaccines. Variola virus genomes are now widely available, allowing computational characterization of the entire T-cell epitome and the use of such information to develop safe and yet effective vaccines. To this end, we identified 124 proteins shared between various species of pathogenic orthopoxviruses including variola minor and major, monkeypox, cowpox, and vaccinia viruses, and we targeted them for T-cell epitope prediction. We recognized 8,106, and 8,483 unique class I and class II MHC-restricted T-cell epitopes that are shared by all mentioned orthopoxviruses. Subsequently, we developed an immunological resource, EPIPOX, upon the predicted T-cell epitome. EPIPOX is freely available online and it has been designed to facilitate reverse vaccinology. Thus, EPIPOX includes key epitope-focused protein annotations: time point expression, presence of leader and transmembrane signals, and known location on outer membrane structures of the infective viruses. These features can be used to select specific T-cell epitopes suitable for experimental validation restricted by single MHC alleles, as combinations thereof, or by MHC supertypes.

Combining MHC tetramer and intracellular cytokine staining for CD8(+) T cells to reveal antigenic epitopes naturally presented on tumor cells.

As more tumor antigens are discovered and as computer-guided T cell epitope prediction programs become more sophisticated, many potential T cell epitopes are synthesized and demonstrated to be antigenic in vitro. However, it is estimated that about 50% of such tumor antigen-specific T cells have not been demonstrated to recognize the naturally presented epitopes due to either technical difficulties, such as T cell cloning which is still challenging for many laboratories; or the predicted T cell epitopes are not generated or not generated in sufficient amounts by the antigen processing machinery. However, to potentially identify clinically relevant vaccine candidate epitopes, it is essential to demonstrate natural antigen presentation. Here we combine the advantages of MHC tetramer and intracellular cytokine staining to sensitively detect natural antigen presentation by tumor cells for epitopes of interest. The novel method does not require T cell cloning or long-term T cell culture. Because the antigen-specific T cells are positively identified, this method is much less influenced by IFNgamma producing cells with unknown specificities and should be widely applicable.

Crystal structure of an H-2Kb-ovalbumin peptide complex reveals the interplay of primary and secondary anchor positions in the major histocompatibility complex binding groove.

Sequence analysis of peptides naturally presented by major histocompatibility complex (MHC) class I molecules has revealed allele-specific motifs in which the peptide length and the residues observed at certain positions are restricted. Nevertheless, peptides containing the standard motif often fail to bind with high affinity or form physiologically stable complexes. Here we present the crystal structure of a well-characterized antigenic peptide from ovalbumin [OVA-8, ovalbumin-(257-264), SIINFEKL] in complex with the murine MHC class I H-2Kb molecule at 2.5-A resolution. Hydrophobic peptide residues Ile-P2 and Phe-P5 are packed closely together into binding pockets B and C, suggesting that the interplay of peptide anchor (P5) and secondary anchor (P2) residues can couple the preferred sequences at these positions. Comparison with the crystal structures of H-2Kb in complex with peptides VSV-8 (RGYVYQGL) and SEV-9 (FAPGNYPAL), where a Tyr residue is used as the C pocket anchor, reveals that the conserved water molecule that binds into the B pocket and mediates hydrogen bonding from the buried anchor hydroxyl group could not be likewise positioned if the P2 side chain were of significant size. Based on this structural evidence, H-2Kb has at least two submotifs: one with Tyr at P5 (or P6 for nonamer peptides) and a small residue at P2 (i.e., Ala or Gly) and another with Phe at P5 and a medium-sized hydrophobic residue at P2 (i.e., Ile). Deciphering of these secondary submotifs from both crystallographic and immunological studies of MHC peptide binding should increase the accuracy of T-cell epitope prediction.