Introduction

A new paradigm of vaccine design is now emerging, following essential discoveries in immunology and the development of bioinformatics tools for T-cell epitope prediction from primary protein sequences. One rationale for this new paradigm is that following exposure to a pathogen, epitope-specific memory T-cell clones are established.¹ These clones respond rapidly and efficiently upon any subsequent infection, elaborating cytokines, killing infected host cells, and marshalling humoral and cellular defences against the pathogen. The most efficient immune response to some pathogens is derived from a number of different T cells that respond to an ensemble of pathogen-derived short peptides called epitopes.^{2, 3, 4} Whether an immune response is directed against a single immunodominant epitope or against many epitopes, the generation of a protective immune response does not require the development of T-cell memory to every possible peptide in the entire pathogen. T-cell response to the ensemble of epitopes, not the whole pathogen, is the source from which a protective immune response is derived (Figure 1).

Figure 1.

Epitope-driven vaccine design (EDVD): An eptiope ensemble (EE) is derived, using immuno-informatics, from a genome and inserted into a vaccine vehicle (epitope ensemble: set of CTL and Th epitopes necessary to induce a protective immune response). As has been observered for many vaccines, a protective immune response is not dependent on immunization with epitopes representing the entire pathogen. Instead, a set of epitopes, or epitope ensemble, is sufficient to generate enough T memory cells to contain or eradicate the pathogen upon exposure. The epitope ensemble may contain T helper epitopes, cytotoxic T-cell epitopes, and Bepitopes, or any combination of the three subsets. The observation that immunization with an epitope ensemble is sufficient for protection against pathogens has led to the development of sub-unit vaccines (such as hepatitis B vaccine, based on hepatitis B surface antigen). More recently, 'epitope-driven' vaccines are being developed, following the same line of reasoning.

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Similarly, if an individual is previously exposed to a language, upon hearing just a few words of that language he/she will usually recognize, for example, that French or English is being spoken. Complete mastery of the language is not required for this recognition. Using this analogy to describe epitopes, one could say that they are pathogen-specific 'words' that alert the immune system to the presence of a pathogen. It is now possible to envisage the design of vaccines based on an ensemble of epitopes (a string of words, a few sentences, a paragraph, or a chapter) derived from the genome of a pathogen, using tools that have been developed in the field of immuno-informatics.

This article will review the two main components of immuno-informatics:(i) epitope mapping algorithms; and (ii) in vitro assays that confirm epitopes. Following a decade of discoveries related to MHC-T-cell interactions, as originally described by Zinkernagel and Doherty,⁵ tools that permit the scanning of protein sequences for T-cell epitopes have been developed and refined by a number of teams.^{6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19} A selection of these tools, including EpiMatrix (in a site limited to HIV or tuberculosis sequences), has been made available on the Internet. Others (including EpiMatrix) are also available to researchers who wish to establish academic or commercial relationships with the companies that have developed the tools.^{20, 21, 22}

The field of immuno-informatics has also benefited from the development of a number of sensitive T-cell assays, such as the ELIspot assay,²³ tetramers,²⁴ and intracellular cytokine staining,²⁵ that permit the measurement of vanishingly small numbers of epitope-specific T cells.²⁶ These tools have also allowed researchers to determine more accurately the breadth of T-cell responses in vitro. Achieving the same level of accuracy (detection of one epitope-specific T cell in among 5000 others) was simply not possible using older methodologies, such as T-cell proliferation and chromium release assays, due to the difficulty of separating T-cell responses from background noise. The marriage of epitope-mapping informatics tools with new sensitive in vitro screening methods has been termed computational immunology, or immuno-informatics(Figure 2).

Figure 2.

The process of applying immuno-informatics to developing vaccines involves selecting the subset of proteins of interest from the whole genome sequence; analysing this subset and identifying supertype and/orpromiscuous epitopes, collecting this epitope ensemble and confirming the immunogenicity of the ensemble and any association between recognition of the epitopes with protection from disease, if possible. Confirmation of the epitopes can be performed in vitro or in vivo (transgenic mice). These epitopes, or the proteins from which they are derived, are then included in the candidate vaccine.

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Computational immunology methods dramatically reduce the time and effort involved in screening potential epitopes, ranging between a reduction of 10-20-fold,^{27, 28} to a 95% reduction.²⁹ Genomes can be scanned and in vitro T-cell confirmation can be accomplished in a matter of months, instead of years. The expansion of computational immunology methods coupled with the availability of more than 100 complete and partial genome sequences raises the exciting possibility of developing epitope-driven vaccines by scanning the sequence of the proteins of a pathogen. Some of these proteins have not previously been isolated or cloned, being unique to the pathogen (similar genes are not found in the genomes of other pathogens) and may be excellent candidates for vaccine development.

Many potential barriers to the generation of epitope-driven vaccines still exist. However, immuno-informatics tools are already being applied to whole genomes with the goal of selecting epitopes for possible inclusion in vaccines. As epitope-mapping tools improve, a direct path from genome to vaccine candidate is beginning to emerge.This article will describe some of the new immuno-informatics tools and approaches that are being used to derive immunogenic information from whole genomic sequences for vaccine design.

Epitopes

T cells orchestrate cellular immune defence against intracellular pathogens, such as viruses and some bacteria, and against extracellular pathogens, such as bacteria and most parasites. While B-cell-mediated immune defence, in the form of antibodies, is a critically important component of the immune response, T cells can both augment and diminish B-cell activity,³⁰ in addition to performing protective duties such as killing infected cells or releasing cytokines that activate pathogen-clearance mechanisms. Unlike B cells, which can generate antibodies that recognize 3-D structures on proteins derived from pathogens, T lymphocytes only recognize the presence of a pathogen in the form of peptide fragments bound to MHC class I or class II molecules on the surface of APC. A peptide that binds to both the MHC molecule on the surface of the APC and the complimentary TCR on the surface of a T cell, stimulating T-cell response, constitutes a T-cell epitope (Figure 3).

Figure 3.

The class I eptitope processing and presentation pathway. Pathogens (and vaccines) that reach the cytosol of an antigen-presenting cell may enter the class I pathway. Proteins are cleaved into peptides by the proteasome, enter the endoplasmic reticulum via the transporters associated with antigen processing (TAP), where they combine with class I molecules and are transported to the surface. A peptide, when presented in the context of an MHC molecule and recognized by a T cell, is termed an epitope.

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Selecting antigenic protein subsets

Given the entire gene repertoire of a pathogen, only certain genesare expressed at different time points in the growth cycle of the organism.³¹ Some such proteins, associated with the normal functioning of the cellular machinery (such as cell replication, amino acid biosynthesis, and DNA metabolism), are very similar in sequence between different microbes. The similarities between microbe and host functional proteins make them much less interesting for vaccine development, especially since T cells responding to epitopes derived from these proteins may have been deleted or disabled in the course of immune-system development.³² Inducing a response to these epitopes might also induce autoimmunity. However,the many determinants of autoimmunity remain to be discovered.³³ On the other hand, proteins that are pathogen-specific are more relevant for vaccine development, since they are involved potentially in those activities that make the pathogen dangerous to the host.

Protection from disease has, in some cases, been associated with the cellular immune response to specific classes of proteins, such as antigens secreted by pathogens into their cellular environment, or antigens that span the cellular membrane.³⁴ One means of identifying such proteins has been to identify them by cell fraction separation methods, 2-D gel electrophoresis, and highly focused sequencing methodologies (such as electron spray mass spectrometry).³⁵ Alternatively, such proteins can be identified by scanning genomic sequences with computer programs that predict secretory signal peptides (SignalP and SPScan),³⁶ transmembrane domains (Tmpred)³⁷ and lipoprotein attachment sites (Prosite Scan).³⁸

Microarray technology also provides a means of selecting proteins from genomic sequences that are more relevant to vaccine design. Selecting proteins that are pathogen-specific and are also upregulated under 'host conditions' is one means of reducing the bewildering array of potential genes to screen in any given genome to a manageable number.^{29, 31, 38, 39, 40} Microarray technologies are one way to identify genes that are expressed in several different states (resting, growing, stressed) and under several different conditions (in culture, in the host cell), some of which may be more relevant for vaccine design (Figure 4) (Alland D., unpubl.data).

Figure 4.

This figure illustrates several methods for deriving vaccine components from proteosomes or genomes. More than one genome can also be compared in order to select conserved epitopes for vaccines. These tools are accelerating the pace of vaccine development. MS, Mass spectrophotometry;TMS, tandem mass spectrophotometry.

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Peptide processing pathways

T-cell epitopes are derived from proteins via two pathways. In the first, a protein derived from an intracellular pathogen is delivered to the protein-degradation machinery of the cell by chaperonins.The protein is cleaved into smaller peptides by specific proteases located in the proteasome, and some of these peptides are delivered into the endoplasmic reticulum by cellular transporters associated with antigen processing (TAP), where they combine with MHC class I molecules and beta-2-microglobulin.^{41, 42, 43} Alternatively, proteins derived from pathogens external to the APC are endocytosed by the cell and digested by proteases in a special compartment of the APC called MIIC. Peptides generated in this process then compete for binding in the binding cleft of MHC class II molecules and HLA-DM acts to facilitate this process.⁴⁴ Class Iand class II-peptide complexes are then transported to the surface of the APC, where they are exposed to interrogation bypassing T cells.⁴⁵ From these different antigen-processing and -presentation pathways, two different T-cell responses are generated: (i) a CD4+ T-helper (Th) immune response; and (ii) a CD8+ CTL immune response. Thesetwo types of responses are relevant for different mechanisms ofimmunity. Prophylactic and therapeutic intervention in different disease settings may require the induction of one or the other, or both types of responses. For this reason, the means of eliciting both Th and CTL immunity are critical to the design of effective vaccines.

MHC molecules and the MHC binding groove

In humans, MHC class I molecules include HLA-A, -B and -C and MHC class II molecules include HLA-DR, -DP and -DQ. The two types of MHC molecules have very different requirements for the types of ligands that will fit in their binding groove. In general, MHC class I molecules accommodate peptides 8-10 amino acids in length. Class I peptides usually contain an MHC class I-allelespecific motif sequence of two main anchor residues, usually located at the two poles (amino- and carboxy-termini) of the peptide ligand.^{46, 47, 48} MHC class II molecules bind peptides of 11-25 amino acids, and are predominantly recognized by CD4+ Th cells. Peptides presented by class II molecules are longer and more variable in size than those presented by class I molecules, and usually contain three main anchor residues located at the relative positions 1, 6 and 9.^{49, 50, 51}

The affinity of any given peptide for an MHC molecule is determined by the presence of primary anchor amino acid residues and secondary intermediate residues that may also promote or interfere with binding. Furthermore, whether any given peptide is immunogenic appears to be determined by its affinity for the MHC molecule.⁵² For example, 80% of HLA-B7 peptides selected based on MHC binding potential were indeed immunogenic when tested in ELIspot assays.²⁹

Immunodominant and subdominant epitopes

Not all epitopes that bind with good affinity to MHC molecules are actually recognized during the 'natural' course of immunity. Some T-cell epitopes may not be detected due to 'holes in the T-cell repertoire' due to thymic deletion or peripheral tolerance. Others may dominate the immune repertoire, overshadowing the response to subdominant epitopes. Specialized T-cell assays can be used to detect 'subdominant epitopes', which may be important components of an effective immune defence.²⁶ In these cases, the response is referred to as a subdominant response, and the epitope is correspondingly identified as a subdominant epitope.¹ The discovery of subdominant epitopes may be critical to vaccine design, since immunization with isolated or optimal epitopes (as with epitope-driven vaccine) can often induce T-cell responses that are more effective.^{53, 54}

Furthermore, an association between broad epitope response and protection from disease has been noted in the case of HIV, hepatitis B (HBV), hepatitis C (HCV) lymphocytic choriomeningitis virus, (LCMV), and malaria.^{4, 55, 56, 57, 58, 59, 60, 61, 62} Many of these epitopes may be subdominant.^{63, 64, 65} When designing a novel vaccine, consideration should be given to the inclusion of many different dominant and subdominant epitopes for the same MHC allele, in addition to many epitopes from different alleles.This set of epitopes or 'epitope ensemble' would not include every peptide derived from the protein. Instead, it would include enough epitopes in high enough concentrations and with broad enough coverage to stimulate a protective immune response. Some of the epitopes in the ensemble may need to be class I-restricted (CD8+) epitopes, and some will most certainly need to be Th (CD4+) class II-restricted epitopes.⁶⁶ The selection of epitope ensembles to induce protective immune responses has been dramatically accelerated by the development of epitope-mapping tools.

Factors influencing the selection of the epitope ensemble

A number of conditions extrinsic to the MHC-ligand interaction may influence the final composition of the epitope ensemble that is derived from the proteins of a pathogen, and presented to theT cells of an individual. For example, the ability to induce an immune response may be associated with the relative expression of the protein by the pathogen, as compared to other potential antigens, and the number of different epitopes derived from this protein that are presented on the surface of the APC.⁶⁷ In addition, the amino acids that flank an epitope can influence epitope processing, resulting in diminished or augmented immune responses.^{68, 69} Cleavage by proteolytic enzymes in the proteasome and processing pathways may destroy some potential epitopes.^{70, 71, 72, 73} TheTAP transporter may also determine the selection of T-cell epitopes that are presented to the APC surface.^{74, 75, 76, 77, 78, 79} These and other aspects of antigen processing have been reviewed in detail by Berzofsky and Berkower.⁸⁰

The genetic background (HLA haplotype) of an individual also plays a significant role in limiting the epitope ensemble recognized by T cells (the MHC-restriction of T-cell response). Every individual possesses two copies of each of three HLA class I and class II genes.These genes encode unique MHC molecules, each of which acts to restrict the repertoire of immunogenic peptides that are presented to the immune system in the context of their binding groove.⁵ According to the most recent update of the IMGT/HLA database, the number of different alleles associated with each of the three main class I HLA genes includes 237 A alleles, 472 B alleles, and 113 C alleles as well as 304 DRB1 alleles, 11 DRB4 alleles, and 15 DRB5 alleles (to mention just three of many DR alleles). The IMGT/HLA database, which acts as a repository for all sequences officially assigned by the World Health Organization Nomenclature Committee for Factors of the HLA System, has the most recent information on HLA variability.⁸¹

Not only do different MHC (HLA) backgrounds restrict the selection of the epitope ensemble, but the repertoire of possible MHC-restricted epitopes recognized by the T cells of an individual has been shown to differ, even between MHC-matched individuals.^{3, 82, 83} Thus, despite MHC-restriction similarities, the ensemble of epitopes that protect two MHC-matched individuals probably represents two distinct but overlapping subsets.

Factors extrinsic to the T cell itself, such as the cytokine milieu (often induced in response to a particular component of a vaccine⁸⁴ or pathogen)⁸⁵ also play a major role in the conditioning of the immune response. Thus, T-cell epitopes may be necessary to drive immune responses, but they are not sufficient. Costimulatory molecules or factors that provide a second signal and help determine the nature (Th1 vs Th2) of the immune response are required.^{86, 87}

Finally, the total number of epitopes belonging to the protective ensemble is completely unknown. Fewer epitopes may be required for simpler pathogens such as viruses, while more epitopes, derived from several different proteins, may be required for an effective immune response to more complex pathogens such as bacteria.

These barriers to understanding and formulating epitope-driven vaccines notwithstanding, the concept that an ensemble of epitopes in the context of the appropriate delivery vehicle may be able to stimulate a protective response, is driving the development of epitope-driven vaccines in a large number of laboratories.^{88, 89} Complex vaccines containing Th and B-cell epitopes alongside CTL epitopes derived from a variety of pathogens (such as five viruses and one bacterium) have already been constructed and tested.⁹⁰ A typical epitope-based vaccine construct contains a single start codon with epitopes inserted consecutively in the construct, with or without intervening spacer amino acids. In vitro studies of these constructs have confirmed that the epitopes are expressed, stimulate protective immune responses, and do not interfere withone another.^{89, 90} Another epitope-driven vaccine approach is to mix several plasmids together, each of which contains genes for different proteins or different minigene epitopes. These vaccines have had no adverse effects, may have enhanced responses, and may have shifted responses toward the Th1 phenotype.⁹¹ These discoveries suggest that epitope-based vaccines are feasible and may be useful, particularly for pathogens for which no vaccines currently exist.

It should be noted that the field of immuno-informatics is new and that few of these epitope-driven vaccine constructs have reached the stage of efficacy trials in humans, although several have been shown to be effective in animal models. With the rapid accumulation of accurate sequence information for a wide array of pathogens, the development of immuno-informatics tools has enabled investigators to mine genomes for potential epitopes, accelerating the pace of epitope-driven vaccine development.

Immuno-informatics epitope mapping tools

Basic epitope-mapping tools

During the 1990s, a large number of computer-driven algorithms that used the alphabetic representation of protein sequence information to search for T-cell epitopes were developed. The teams of DeLisi and Berzofsky (1985),⁹² and Rothbard et al.(1988)⁹³ developed the earliest computer-driven algorithms for epitope mapping. These tools were based on empirical observations of the periodicity of amino acid residues in T-cell epitopes. Predictions based on periodicity were a clear improvement over the standard overlapping method of epitope mapping, but the predictive value of these early algorithms was limited.⁹

Subsequently, a better understanding of the MHC-peptide interaction enabled the development of improved computer-driven algorithms. First, based on crystallographic studies of MHC molecules, it became apparent that MHC ligands lay in the MHC binding groove in an extended configuration.^{94, 95} Second, the direct elution and sequencing of MHC ligands revealed the presence of MHC ligand 'motifs' associated with specific amino acid resides in the ligand, which interacted with binding pockets in the floor of the MHC binding groove.^{48, 96} Several researchers described using these anchor-based MHC binding motifs to prospectively identify T-cell epitopes, including Sette et al. in 1989⁹⁷, Falk et al. in 1991,⁴⁸ Lipford et al. in 1993,⁷ Parker et al. in 1994,⁸ Meister et al. in 1995,⁹ and Roberts et al. in 1996.⁹⁸

Matrix-based approaches (in contrast to anchor-motif-based approaches) to mapping T-cell epitopes have been developed by a number of different research teams. Matrix methods assign a positive or negative value to each possible amino acid that could occupy each position in apeptide, based on either empirical data from many known epitopes binding to that MHC molecule, or on computational estimates of the free energy of binding. Matrix methods to predict MHC binding have also been described by Sette et al.,¹⁴ Davenport et al.,¹⁶ De Groot et al.,²⁰ Schafer et al.,²⁸ and several other groups.¹³ In general, a matrix-based computer algorithm searches for putative T-cell epitopes by scanning the entire protein of interest in increments of eight, nine, 10 or 11-mer. EpiMatrix is one of several such tools, which scores each 8-10-mer overlapping frame in a protein sequence on the basis of the estimated probability of its binding (EBP) to a selected MHC molecule. Studies have demonstrated that EpiMatrix, among other matrix-based programs, accurately predicts MHC ligands (in both retrospective²⁰ and prospective studies).⁹⁹

The crucial assumption that the matrix-based method relies upon is that the contribution of each position along the peptide sequence is essentially independent of other positions. This assumption appears to be quite accurate, in most cases, although exceptions exist.¹⁰⁰ The matrix method also enables the assessment of the contribution of secondary anchor residues, engaging secondary binding pockets of the MHC molecule. Including this information may allow matrices to predict epitopes that do not conform to standard anchor-based motifs. As it turns out, predictions based on the main anchors alone have not proven to be very effective. Only approximately 20-30% of anchor-motif-containing peptides bind to MHC molecules. However, the predictive efficacy of a motif-based algorithm increases to70-80% if secondary anchors are considered.¹⁰¹

A number of additional approaches to epitope mapping have been developed. These include predictive strategies based on neural nets, threading algorithms and non-linear functions.^{12, 102} However, in several side-by-side comparisons (unpubl. data), different methods have been found to be essentially equivalent, thus providing powerful support for the 'independent side chain contribution hypothesis' on which the matrix methods are based. The most important determinant of the accuracy of the prediction appears to be the actual quality and quantity of the binding data utilized to derive the predictive method. Following the example of Brusic et al. at the Kent Ridge Digital Laboratories,¹⁰³ researchers who are actively designing epitope-mapping algorithms have amassed large databases of MHC binding peptides for use with matrices and artificial neural network (ANN)-based epitope prediction tools.

Recently, the teams of Sturniolo et al.¹⁹ and Zhang et al.¹⁸ have proposed that unknown motifs might be predicted by mixing and matching MHC-binding-pocket characteristics. In the hands of a number of epitope-mapping researchers, this new means of developing epitope prediction tools is proving to be extremely useful. A list of epitope mapping tools, their corresponding Internet website addresses, and their comparative features is provided in Table 1.

Table 1 - Overview of epitope-prediction tools (1 January 2002).

Full table

MHC restriction, supertypes and promiscuous epitopes

Peptides bind in the binding groove of MHC class I and class II molecules through interactions between their R-group side chains and pockets located on the floor of the MHC molecule. It is now known that different MHC molecules have different types of binding-pocket-R-group interactions, limiting the set of MHC ligands that can be presented in the context of any given MHC molecule. These structural constraints on peptides that bind in the MHC groove result in MHC-linked 'genetic restriction' of the immune response, as described by Zinkernageland Doherty more than two decades ago.⁵ The problem of selecting the peptides that will stimulate a protective immune response, from each pathogen (in the context of the MHC of each individual), has been considered to be a major stumbling block to the development of T-cell epitope-based vaccines. This problem has been mitigated by the discovery of MHC allele supertypes, described by Sette and Sidney.¹⁰⁴ MHC ligands that have been found to bind to one member of the MHC allele supertype family (e.g. A3) are thought to be likely to bind to other members of the same supertype family (e.g. A11), making the task of selecting MHC ligands or T-cell epitopes, which will stimulate the immune response in individuals of different genetic backgrounds, simpler. Prominent examples of MHC allele supertype families include the HLA-A2, -A3, -B7 and -B44 supertypes.

One means of surmounting the MHC-restriction obstacle to developing vaccines based on T-cell epitopes might be to build vaccines out of peptides containing 'supermotifs'. Another means of overcoming the problem of MHC restriction is to identify MHC ligands that contain patterns allowing binding to more than one MHC molecule, regardless of supertype family. Many MHC ligands or T-cell epitopes that are recognized in the context of more than one MHC molecule and recognized by more than one T-cell clone have been identified; these are called 'promiscuous epitopes.' Promiscuous epitopes were originally identified by screening large numbers of individuals for T-cell responses to overlapping peptides;^{105, 106} a time-consuming and expensive undertaking. Bioinformatics tools that search protein sequences for supertype motifs and clusters of MHC binding motifs will accelerate the development of epitope-based vaccines that effectively protect genetically diverse human populations.

Conserved sequences (Conservatrix)

Conservatrix, a sequence matching and counting tool, can be used to compare the sequence of every 10-amino-acid-long peptide in a given sequence database (e.g. one isolate of HIV-1) for identity with every 10-amino-acid-long sequence of another sequence database (e.g. another strain of HIV-1), and can be used to identify broadly conserved (across-clade) epitopes.²⁰ Conservatrix can be configured to allow amino acid substitution at non-anchorpositions. The algorithm has been used to map highly conserved T-cellepitopes in variable genomes (e.g. HIV-1 and HCV).

Are epitope-selection algorithms good predictors of MHC binding?

A range of studies have confirmed the utility of immuno-informatics for selecting MHC ligands and T-cell epitopes. For example, in one study performed by the TB/HIV Research Laboratory and EpiVax, 25 highly conserved HIV-1 peptides restricted by the alleles A*0101,B7 (all subtypes), and A*1101 were selected using Conservatrix and EpiMatrix, two algorithms originally designed by the TB/HIV Research Laboratory and further developed by EpiVax.²⁰ A 25th (control) peptide was selected based on having been previously identified as a CTL epitope as well as on receiving an EpiMatrix score consistent with a high likelihood of binding to the corresponding MHC molecule in vitro. The HLA-A2 published epitope selected for this study was SLYNTVATLY; the HLA-A11 published epitope was TVYYGVPVWK; and the HLA-B7 published epitope was GPGHKARVLA.¹⁰⁷

In vitro evaluation of MHC binding was performed by measuring the ability of exogenously added peptides to stabilize the class I MHC/beta-2 microglobulin structure on the surface of TAP-deficient cell lines as described by Ljundggren et al.¹⁰⁸ Fifty-seven of the 75 peptides (76%) tested in binding studies, including all (3/3) of the control (published and predicted) ligands bound to the T2cells expressing the corresponding MHC molecule. In contrast, none of 22 epitopes bound to T2 cells transfected with HLA that were mismatched for the peptide selection. Thus, EpiMatrix selection proved an excellent predictor of MHC binding.

In a separate EpiMatrix study, performed in collaboration with Jin et al.,⁹⁹ EpiMatrix was used to predict putative MHC ligands for one HIV-infected patient. Amino acid sequences within Env, Vpu, Vpr, Vif and Nef that were deduced from the proviruses of a patient were evaluated using EpiMatrix matrix motifs constructed for HLA-B7. Fifty-five of the highest-scoring peptides for the HLA-B7 matrix from the HIV protein sequences of this patient were selected for binding studies. Fifty-five peptides were selected for in vitro studies. These peptides fell within a range of EpiMatrix scores, from a 40% (high) likelihood of binding, to a 0.1% (low) likelihood of binding, based on comparisons with other known HLA-B7 binders. Twelve (44%) of the top 27 peptides were effective at stabilizing the B7 molecule on the cell surface, indicating their ability to appropriately bind within the peptide-binding groove of the HLA-B7 molecule. All of these peptides fell in the top 50% of the HLA*B7 peptides,as ranked by EpiMatrix score (representing 44% of the top 50%).

Several additional studies have been performed to address whether immuno-informatics tools are effective predictors of MHC class I-binding. In one landmark study, Kast et al. synthesized all possible 9-mer peptides derived from the E6 and E7 proteins of human papilloma virus (HPV)-18 and tested them for binding to HLA-A1,-A2.1, -A3, -A11 and -A24.²⁷ Only 22 (1.8%) out of 1200 peptides evaluated in the exhaustive study of peptide binding affinity were strong binders in vitro.All seven of the peptides with very high binding affinity (at the 50 nmol/L level) contained HLA-specific binding motifs, and almost all of the 22 peptides with strong binding affinities (91%) contained HLA-specific binding motifs. This study demonstrated that motif-based computer-driven analysis of the same proteins would have reduced by more than 10-fold the number of peptides that needed to be synthesized and tested in HLA binding analysis.

Are epitope-selection algorithms good predictors of immunogenicity?

Preliminary evidence that epitope-selection algorithms are generally good predictors of immunogenicity can be extrapolated from the observation that more than 500 such studies have been performed for a range of cancer, viral, bacterial and parasite proteins. A few examples demonstrating the accuracy of epitope-selection methods for predicting MHC binding and T-cell immunogenicity are described below.

In one study, the selection of HIV-1 epitopes that are conserved despite the genomic variability of HIV viruses was addressed by the TB/HIV Research Laboratory. Broadly conserved HIV-1CTL epitopes were identified by screening protein sequences in the Los Alamos National Laboratory HIV Sequence Database with a sequence parsing and matching algorithm (Conservatrix).²⁸ Putative HIV-1 CTL epitopes were selected from this list using the epitope-prediction tool EpiMatrix. One hundred peptides representing putative epitopes, conserved in many isolates of HIV-1, were synthesized. Forty-three (43%) of the 100 peptides, including all (4/4) of the control (published and predicted) epitopes tested, stimulated T-cell responses. The TB/HIV Research Laboratory also used EpiMatrix to prospectively identify 61 candidate A*11-restricted clade E epitopes for the team of Bond et al.¹⁰⁹ Out of these, 26 peptides were confirmed in HLA-A*11 binding assays; peptides that bound to HLA-A*11 were evaluated for immunogenicity in a small cohort of Thai clade E infected patients. A total of 13 epitopes (out of the 26 HLA-A*11 binders) were confirmed. In a separate study of putative epitopes derived from an autologous HIV-1 sequence, four out of six peptides receiving the highest scores in a list of 55 HLA-B*7 predictions, were shown to be CTL epitopes in one HIV-1-infected patient.⁹⁹ A number of other research groups have applied the strategies and tools described above to the identification of HIV-derived epitopes.^{110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120}

EpiMatrix has also been successfully applied to the retrospective analysis of published epitopes,²⁰ to the identification of novel Mycobacterium tuberculosis (Mtb)SOD protein B7-restricted epitopes, and to the selection of cross-reactive HIV-1 and HIV-2 epitopes. (Dong Y, et al. unpubl. data).

The accuracy of epitope-prediction methods based on motifs has also been described by van der Most et al.,^{1, 121} Shastri et al.,⁶⁹ Vitiello et al.,¹²² and Wentworth et al.¹²³ In additional studies by Rotzschke et al., HLA-A*1-, -A*3-and -B*44-specific motifs were utilized to predict potential epitopes derived from various proteins of the influenza A virus.⁵⁰ Out of 18 peptides synthesized, eight bound and six of them (75%) were recognized by CTL derived from individuals who had presumably been naturally exposed to infection with the influenza virus. In the case of HCV, several laboratories have mapped epitopes, presented by HLA-A2.1 molecules, that are capable of inducing CTL in patients and/or HLA-A2-transgenic mice.^{124, 125, 126, 127, 128, 129}

HLA class II-restricted T-cell responses to a number of pathogens, including Mtb, HIV and HCV antigens, are believed to influence the final outcome of the infection.^{34, 132} A seriesof studies have addressed the identification of HLA class II-restricted epitopes for these pathogens, with the aim of including the class II epitopes in therapeutic and prophylactic vaccines. EpiMatrix was used to analyse the sequences of putative secreted proteins derived from the Mtb1551 and H37Rv genomes for regions that contained a high number of MHC class II-binding motif matches (unpubl. data).T-cell responses to selected peptides were evaluated in gamma-interferon release ELIspot assays and in T-cell proliferation assays, using peripheral blood monocytes (PBMC) obtained from healthy, Mtb-infected (Mtb-immune) donors. Thirteen (76.5%) out of the 17 peptides selected for the study stimulated gamma-interferon response in vitro. One highly promiscuous epitope induced gamma-interferon secretion in PBMC from 15 out of 27 Mtb-immune subjects (56%).This promiscuous epitope is an excellent candidate for an epitope-driven tuberculosis vaccine (Figure 5).

Figure 5.

ELIspot responses to T-cell epitopes derived by informatics analysis from open reading frames that are found in Mycobacterium tuberculosis (Mtb) strain 1551 and/or Mtb strain H37Rv, and that also contain a secretory signal (Signal P), are described in this histogram. Several promiscuous epitopes were identified using the approach described in the text. For example, 56% of the Mtb-immune subjects evaluated responded to peptide J with gamma interferon release in vitro; 33% of study subjects responded to peptides D, H, O and V in vitro. Peptide V was only found in Mtb strain H37Rv (a common laboratory strain) and not in the clinical isolate, 1551.

Full figure and legend (29K)

Studies of acutely HIV-1-infected subjects performed by BruceWalker's group have shown convincingly that broad CTL and Th responses to both dominant and subdominant epitopes, restricted by multiple HLA alleles, are associated with better control of HIV-1infection.¹³¹ However, HIV-1is highly variable. In preclinical studies of an epitope-driven 'worldclade' vaccine,¹³² EpiVax and the TB/HIV Research Laboratory used Conservatrix to select 9- and 10-amino-acid-length sequences that were highly conserved in an internal database of 55 000 HIV-1 variants. The top1000 most conserved sequences from each protein were retained for further analysis. The peptides were then scored against all EpiMatrix class II matrices, and ranked by (i) number of HIV-1 strains represented; (ii) EpiMatrix score; and (iii) promiscuity (number of unique MHC motifs contained in the peptide). Given the resulting set of ranked 9-mer peptides, candidate 23-mer peptides were designed by selecting the top-ranked peptide and then searching the remaining list for overlapping peptides. The seed 9-mer peptides were extended by finding a highly conserved and potentially immunogenic 9-mer peptide that overlapped the left flank of the seed peptide by eight amino acids.Where more than one peptide overlapping the seed peptide by eight amino acids could be found, the highest-ranked candidate was chosen.This process was continued until the left flank of the seed peptide had been extended by seven amino acids. With a left flank in place, the process was repeated for the right flank. Eight of the top 100 peptides selected using this approach overlapped with published epitopes, and more than 100 novel highly conserved class II epitopes have been identified. In preliminary studies of 20 unpublished class II epitopes selected using this approach, two of the novel epitopes have been confirmed (using PBMC from HIV-1 infected individualsin ELIspot assays) (unpubl. data). Approximately 60% of the remainder are expected to be immunogenic, based on experience with the EpiMatrix class II matrices described in the section on Mtb, above.

Additional studies, including one on HCV-infected patients by Lamonaca et al., have shown that prospectively selected class II epitopes can indeed be immunogenic.¹³³ By using epitope-mapping algorithms, a number of highly immunogenic class II-restricted T-cell epitopes were identified within HCV core, NS3 and NS4. This team of researchers reported that the epitopes selected by the algorithms were immunodominant, highly conserved among the known HCV isolates, and promiscuous, because they could be presented to T cells by different HLA class II molecules.

Epitope-driven vaccine design

As the process of epitope mapping accelerates, and confidence in the new algorithms grows, researchers are conceptualizing vaccines built entirely out of epitopes linked together like a string of beads.¹³⁴ As described in the introduction, behind this vaccine approach is the following analogy: an epitope is to a pathogen as a word is to a language.Thus, even a single epitope may signal the presence of an infection to the immune system and stimulate a protective response, just as a single word (e.g. bonjour) reminds the hearer of a language.⁵³ However, more than one word (epitope) is usually required to stimulate the immune response in the context of different genetic backgrounds. This is due to the genetic restriction of the immune response. To extend the analogy, researchers have hypothesized that protective immune responses to an entire pathogen may be generated by the recognition of an ensemble of epitope 'words' derived from the proteins of the pathogen, each selected to stimulate an immune response in the context of a different MHC molecule. Alternatively, vaccines based on promiscuous epitopes (words or epitopes that are recognized in the context of more than one MHC molecule) have been proposed.¹³⁵ The concept of designing vaccines based on an ensemble of epitopes has been termed 'reverse immunogenetics' by Davenport and Hill.¹³⁶ We propose an alternative term: epitope-driven vaccine design.

The epitope-driven vaccine concept is an attractive one that is being successfully pursued in a number of laboratories.^{89, 90} Complex vaccines containing T-helper and B-cell epitopes alongside CTL epitopes derived from a variety of pathogens (such as five viruses and one bacterium) have already been constructed and tested.¹³⁷ A typical epitope-based vaccine construct contains a single start codon, with epitopes inserted consecutively in the construct, with or without intervening spacer amino acids. In vitro studies of these constructs have confirmed that the epitopes are expressed, stimulating a protective immune response, and do not interfere with one another.¹³⁴

One approach is to mix several plasmids together, each of which contained genes for different proteins or different minigene epitopes. In animal studies, these vaccines have had no adverse effects, and may have enhanced the response and shifted the response towards the Th1 phenotype.⁹¹

Proof that epitope-driven minigene vaccination can stimulate protective immune responses has been obtained by researchers carrying out minigene vaccination studies in a range of animal models.^{138, 139} For example, CTL elicited by peptide immunization (in adjuvant) have been shown to afford protection against Respiratory Syncitical Virus (RSV) challenge.¹⁴⁰ Similarly, in the murine malaria model, immunization of BALB/c mice with three doses of a peptide construct containing an H-2(d)-restricted CTL epitopeinduced both T-cell proliferation and a peptide-specific CTL response, mediating nitric-oxide-dependent elimination of malaria-infected hepatocytes in vitro, as well as partial protection of BALB/c mice against sporozoite challenge.⁵⁴ In studies performed using intracerebral challenge with a lethal dose of measles virus, immunization of BALB/c and CBA mice with measles virus CTL epitopes resulted in in vivo induction of epitope-specific CTL responses and conferred some protection against encephalitis.¹⁴¹ A conjugate peptide vaccine containing a CTL epitope from HSV-1 elicited protection from intraperitoneal HSV challenge.¹⁴² Vectored (Sindbis virus) minigene vaccines containing CTL epitopes induced epitope-specific CD8+ T-cell responses and elicited a high degree of protection against infection with malaria or influenza A virus.¹⁴² Epitope-driven minigene vaccines have been protective in larger animals; vaccination with a minimal ovine CTL peptide epitope induced epitope-specific CTL, and sheep whose CTL were capable of recognizing (BLV) retrovirus-infected cells were fully protected when challenged.¹⁴⁴

These studies of minigene vaccines have demonstrated the importance of including Th epitopes with CTL epitopes. Specific and highly directed CTL induction is possible by unlinked minigene DNA immunization, but induction of a CTL response, in the absence of a Th response, is not always sufficient to provide protection. Protection induced by a minigene vaccine has been improved by the inclusion of Th epitopes.¹⁴⁵ Thus, induction of a response to a mixture of B-cell (antibody) epitopes, and CTL and Th epitopes may be critical to protection. For example, immunization with a cocktail of peptides consisting of a B-cell epitope, a Th epitope, and a CTL epitope linked to a fusion peptide, resulted in a 190-fold reduction in RSV titre compared to non-immunized mice.¹⁴⁶

Many vaccinologists consider that immunization with whole protein as a vaccine is preferable, as it allows induction of cellular immune responses, as well as induction of humoral immune responses. However,epitope-driven vaccines are advantageous for two reasons. First, vaccination with epitope-based vaccines may avoid the potentially lethal effects of whole-protein vaccines. Second, immunization with the whole protein may preferentially induce an immune response against immunodominant epitopes.¹⁴⁷ More broad-based (multi-epitope) immune responses are afforded by epitope immunization. Multi-epitope immunization (like multidrug treatment) may also limit the ability of the pathogen to evolve to escape CTL recognition.^{148, 149, 150, 151} Epitope evolution due to selection pressure has been described for a number of different pathogens, including HCV,¹⁵¹ HIV¹⁵² and Plasmodium falciparum.¹⁴⁹ Cytotoxic T-lymphocyte responses to a subdominant epitope may also compensate for the loss of a dominant epitope in the evolution of the pathogen.^{153, 154} Thus, the capacity to induce immunity against a broad array of epitopes that are subdominant, highly conserved and critical to the life cycle of the pathogen, is an important attribute of epitope-driven vaccines.¹³²

Monitoring an epitope-specific immune response following vaccination

After using in vitro T-cell assays to select for naturally processed T-cell epitopes, it is important to evaluate the ability of the vaccines derived from these epitopes to induce an immune response in vivo. Non-humanized animal models are not suitable for the evaluation of vaccines designed to induce HLA-restricted immune responses, as their MHC molecules may have different epitope restrictions. Fortunately, a number of transgenic mouse strains that express the most common HLA-A, HLA-B and HLA-DR molecules have been developed.¹⁵⁵ An excellent correlation has been found between CTL responses in infected individuals and CTL responses induced in immunized HLA transgenic mice.^{127, 156, 157} In preclinical studies, HLA transgenic mice are now routinely used to assay and optimize epitope-driven vaccines.^{155, 158, 159}

Altman et al. first developed MHC tetramers just a few years ago, and this group has written several excellent reviews on the topic.²⁴ These specialized constructs bear four MHC molecules in a complex with beta-2-microglobulinand a specific pathogen-derived peptide ligand. Tetramers can bind directly to T cells that recognize the MHC-peptide complex. They can be used for direct ex vivo analysis of the frequency and phenotypes of epitope-specific T cells by the technique of flow cytometry. Tetramers permit the following types of experimental confirmations of epitope-specific T-cell responses in vivo:(i) direct quantification of the number of epitope-specific T cells prior to and following vaccination; (ii) phenotyping of responding T cells (examination for cell surface markers such as CD8, CD4, CD38 and additional activation markers); (iii) monitoring of the immune response to specific epitopes following vaccination; and (iv) direct evaluation of the effect of combinations of epitopes, epitope spacers or linkers and signal sequences on T-cell responses. These reagents will prove to be useful as epitope-driven vaccines move into the first phase of trials, as they provide a means of measuring and timing the immune response directly to the vaccine. Likewise, intracellular cytokine staining flow cytometry assays and ELIspot assays can be used to enumerate cells responding to a given antigenor epitope.

Conclusion

The discipline of immuno-informatics is accelerating the development of vaccines composed of epitope ensembles. These ensembles can be designed to be broadly reactive (across HLA) and broadly conserved (across variant strains). Opportunities for epitope discovery and epitope-driven vaccine design are expanding as the number of pathogens that are entirely sequenced approaches 100, and access to these data improves. Epitope-driven vaccines that are designed and optimized, based on our current knowledge and understanding of the mechanics of immunogenicity and immunodominance, are filling the vaccine development pipelines. Evaluation of selected epitope-driven constructs in animal models has been performed, and preliminary results are positive. Confirmation of these vaccines in clinical trials in humans will serve to usher in an entirely new era of epitope-driven vaccine design.

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Acknowledgements

Initial funding for the tuberculosis genome-to-vaccine analysis was provided by a subcontract to the TB/HIV Research Laboratory from an R01 for the sequencing of the 1551 Mycobacterium tuberculosis genomeawarded to Dr R Fleischmann at the Institute for Genomic Research.Funding for tuberculosis-epitope analysis and T-cell assays described in this manuscript was provided by the Sequella Global TB Foundation in the form of a core scientist award to AS De Groot at EpiVax. Research funding for the HIV studies described in this paper was provided by the Division of AIDS at the National Institutes of Health through grants to AS De Groot (R43 AI 46212, R21 AI 45416 and R01 AI 40888). The authors wish to thank L Vanleynseele (EpiVax) for her assistance with the manuscript, C Grein (TB/HIV Research Laboratory) for the coordination of research activities described in this manuscript, and honorary laboratory members A De Groot and Z Trocchi for their steadfast support and enthusiasm.