SNEP: SNP-derived Epitope Prediction program for minor H antigens

The bioinformatics analyses reveal novel antigen epitopes in major outer membrane protein of Chlamydia trachomatis

PURPOSE

The aim of this study was to predict the T-cell and B-cell epitopes in major outer membrane protein (MOMP) of Chlamydia trachomatis (CT) by using online software and also to analyse the secondary structure of MOMP through bioinformatics tools.

MATERIALS AND METHODS

The predictions of secondary structure of MOMP protein were carried out using SOPMA software, and the prediction of B-cell epitopes in MOMP protein was carried out using IEDB and LEPS software, while the T-cell epitopes were predicted by the software of IEBD and SYFPEITHI. The predictions from the software were combined with MOMP protein characteristics, including surface features, hydrophilicity, flexibility, accessibility and plasticity, to analyse the common epitope areas' response by T-cells and B-cells.

RESULTS

In the secondary structure of CT MOMP, the alpha-helices accounted for 41.62% of total amino acid, while the beta sheets and random coil accounted for 19.80% and 32.49%, respectively. Predictions combined with MOMP protein surface features, hydrophilicity, flexibility, accessibility and plasticity were further characterised, and three high-score B-cell epitope areas were found as located in 24-31, 307-311 and 318-327 amino acids of MOMP protein, respectively; in the meanwhile, three high-score T-cell epitope areas were found in 234-236, 323-329 and 338-343 amino acids of MOMP using major histocompatibility complex (MHC) class I HLA-A 0201 restrictive T-cell epitope analyser.

CONCLUSION

We established the methods by using the biological information network technologies for looking the T-cell antigen epitopes and B-cell antigen epitopes in MOMP of CT, and three novel T-cell epitopes as well as three novel B-cell epitopes were identified in the current study. It provides important information for further studying the antigenicity of CT MOMP protein and also provides useful information for developing highly efficient subunit vaccines for CT.

Minor histocompatibility antigens: past, present, and future

Minor histocompatibility (H) antigens are key molecules driving allo-immune responses in both graft-versus-host-disease (GvHD) and in graft-versus-leukemia (GvL) reactivity in human leukocyte antigen (HLA)-matched hematopoietic stem-cell transplantation (HSCT). Dissection of the dual function of minor H antigens became evident through their different modes of tissue and cell expression, i.e. hematopoietic system-restricted or broad. Broadly expressed minor H antigens can cause both GvHD and GvL effects, while hematopoietic system-restricted minor H antigens are more prone to induce GvL responses. This phenomenon renders the latter group of minor H antigens as curative tools for HSCT-based immunotherapy of hematological malignancies and disorders, in which minor H antigen-specific responses are enhanced in order to eradicate the malignant cells. This article describes the immunogenetics of minor H antigens and methods that have been developed to identify them. Moreover, it summarizes the clinical relevance of minor H antigens in transplantation, with special regards to allogeneic HSCT and solid-organ transplantation.

EpiToolKit--a web-based workbench for vaccine design

EpiToolKit is a virtual workbench for immunological questions with a focus on vaccine design. It offers an array of immunoinformatics tools covering MHC genotyping, epitope and neo-epitope prediction, epitope selection for vaccine design, and epitope assembly. In its recently re-implemented version 2.0, EpiToolKit provides a range of new functionality and for the first time allows combining tools into complex workflows. For inexperienced users it offers simplified interfaces to guide the users through the analysis of complex immunological data sets.

AVAILABILITY AND IMPLEMENTATION

http://www.epitoolkit.de

CONTACT

schubert@informatik.uni-tuebingen.de

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Strategies for the identification of T cell-recognized tumor antigens in hematological malignancies for improved graft-versus-tumor responses after allogeneic blood and marrow transplantation

Allogeneic blood and marrow transplantation (allo-BMT) is an effective immunotherapeutic treatment that can provide partial or complete remission for patients with hematological malignancies. Mature donor T cells in the donor inoculum play a central role in mediating graft-versus-tumor (GVT) responses by destroying residual tumor cells that persist after conditioning regimens. Alloreactivity towards minor histocompatibility antigens (miHA), which are varied tissue-related self-peptides presented in the context of major histocompatibility complex (MHC) molecules on recipient cells, some of which may be shared on tumor cells, is a dominant factor for the development of GVT. Potentially, GVT can also be directed to tumor-associated antigens or tumor-specific antigens that are more specific to the tumor cells themselves. The full exploitation of allo-BMT, however, is greatly limited by the development of graft-versus-host disease (GVHD), which is mediated by the donor T cell response against the miHA expressed in the recipient's cells of the intestine, skin, and liver. Because of the significance of GVT and GVHD responses in determining the clinical outcome of patients, miHA and tumor antigens have been intensively studied, and one active immunotherapeutic approach to separate these two responses has been cancer vaccination after allo-BMT. The combination of these two strategies has an advantage over vaccination of the patient without allo-BMT because his or her immune system has already been exposed and rendered unresponsive to the tumor antigens. The conditioning for allo-BMT eliminates the patient's existing immune system, including regulatory elements, and provides a more permissive environment for the newly developing donor immune compartment to selectively target the malignant cells. Utilizing recent technological advances, the identities of many human miHA and tumor antigenic peptides have been defined and are currently being evaluated in clinical and basic immunological studies for their ability to produce effective T cell responses. The first step towards this goal is the identification of targetable tumor antigens. In this review, we will highlight some of the technologies currently used to identify tumor antigens and anti-tumor T cell clones in hematological malignancies.

Tools and methods for identification and analysis of rare antigen-specific T lymphocytes

T lymphocytes are essential as effector and memory cells for immune defense against infections and as regulatory T cells in the establishment and maintenance of immune tolerance. However, they are also involved in immune pathology being effectors in autoimmune and allergic diseases or suppressors of immunity in cancer, and they often cause problems in transplantation. Therefore, strategies are being developed that allow the in vivo amplification or isolation, in vitro expansion and genetic manipulation of beneficial T cells for adoptive cell therapies or for the tolerization, or elimination of pathogenic T cells. The major goal is to make use of the exquisite antigen specificity of T cells to develop targeted strategies and to develop techniques that allow for the identification and depletion or enrichment of very often rare antigen-specific naïve as well as effector and memory T cells. Such techniques are very useful for immune monitoring of T cell responses in diagnostics and vaccination and for the development of T cell-based assays for the replacement of animal testing in immunotoxicology to identify contact allergens and drugs that cause adverse reactions.

Immunoinformatics and systems biology methods for personalized medicine

The immune system plays an important role in the development of personalized medicine for a variety of diseases including cancer, autoimmune diseases, and infectious diseases. Immunoinformatics, or computational immunology, is an emerging area that provides fundamental methodologies in the study of immunomics, that is, immune-related genomics and proteomics. The integration of immunoinformatics with systems biology approaches may lead to a better understanding of immune-related diseases at various systems levels. Such methods can contribute to translational studies that bring scientific discoveries of the immune system into better clinical practice. One of the most intensely studied areas of the immune system is immune epitopes. Epitopes are important for disease understanding, host-pathogen interaction analyses, antimicrobial target discovery, and vaccine design. The information about genetic diversity of the immune system may help define patient subgroups for individualized vaccine or drug development. Cellular pathways and host immune-pathogen interactions have a crucial impact on disease pathogenesis and immunogen design. Epigenetic studies may help understand how environmental changes influence complex immune diseases such as allergy. High-throughput technologies enable the measurements and catalogs of genes, proteins, interactions, and behavior. Such perception may contribute to the understanding of the interaction network among humans, vaccines, and drugs, to enable new insights of diseases and therapeutic responses. The integration of immunomics information may ultimately lead to the development of optimized vaccines and drugs tailored to personalized prevention and treatment. An immunoinformatics portal containing relevant resources is available at http://immune.pharmtao.com.

Towards in silico design of epitope-based vaccines

BACKGROUND

Epitope-based vaccines (EVs) make use of immunogenic peptides (epitopes) to trigger an immune response. Due to their manifold advantages, EVs have recently been attracting growing interest. The success of an EV is determined by the choice of epitopes used as a basis. However, the experimental discovery of candidate epitopes is expensive in terms of time and money. Furthermore, for the final choice of epitopes various immunological requirements have to be considered.

METHODS

Numerous in silico approaches exist that can guide the design of EVs. In particular, computational methods for MHC binding prediction have already become standard tools in immunology. Apart from binding prediction and prediction of antigen processing, methods for epitope design and selection have been suggested. We review these in silico approaches for epitope discovery and selection along with their strengths and weaknesses. Finally, we discuss some of the obvious problems in the design of EVs.

CONCLUSION

State-of-the-art in silico approaches to MHC binding prediction yield high accuracies. However, a more thorough understanding of the underlying biological processes and significant amounts of experimental data will be required for the validation and improvement of in silico approaches to the remaining aspects of EV design.

MaHCO: an ontology of the major histocompatibility complex for immunoinformatic applications and text mining

MOTIVATION

The high level of polymorphism associated with the major histocompatibility complex (MHC) poses a challenge to organizing associated bioinformatic data, particularly in the area of hematopoietic stem cell transplantation. Thus, this area of research has great potential to profit from the ongoing development of biomedical ontologies, which offer structure and definition to MHC-data related communication and portability issues.

RESULTS

We introduce the design considerations, methodological foundations and implementational issues underlying MaHCO, an ontology which represents the alleles and encoded molecules of the major histocompatibility complex. Importantly for human immunogenetics, it includes a detailed level of human leukocyte antigen (HLA) classification. We then present an ontology browser, search interfaces for immunogenetic fact and document retrieval, and the specification of an annotation language for semantic metadata, based on MaHCO. These use cases are intended to demonstrate the utility of ontology-driven bioinformatics in the field of immunogenetics.

AVAILABILITY AND IMPLEMENTATION

The MaHCO Ontology is available via the BioPortal: http://www.bioontology.org/tools/portal/bioportal.html, and at: http://purl.org/stemnet/.

Targeting minor histocompatibility antigens in graft versus tumor or graft versus leukemia responses

Allogeneic hematopoietic cell transplantation (alloHCT) represents the only curative therapy for several hematologic malignancies, and shows promise as a nascent treatment modality for select solid tumors. Although the original goal of alloHCT was hematopoietic reconstitution after sub-lethal chemoradiotherapy, recognition of a profound donor lymphocyte-mediated graft-versus-leukemia (GVL) or graft-versus-tumor (GVT) effect has shifted the paradigm from pre-transplant cytoreduction to tumor control via donor lymphocytes. In human leukocyte antigen (HLA)-compatible alloHCT, GVL and GVT reactions are induced primarily by donor T-cell recognition of minor histocompatibility antigens (mHAgs). Here we review the literature regarding mHAg-specific T cells in GVL and GVT reactions, and discuss the prospects of exploiting mHAgs as immunotherapeutic targets.

SYFPEITHI: database for searching and T-cell epitope prediction

Reverse immunology has been used for about 12 years in order to identify T-cell epitopes from pathogens or tumor-associated antigens. In this chapter, we discuss the advantages and pitfalls of T-cell epitope prediction compared to classical experimental procedures such as epitope mapping and cloning experiments. We introduce our three established programs, SYFPEITHI, PAProc, and SNEP, which are freely accessible at no cost in the World Wide Web for the prediction of either HLA-peptide binding or proteasomal processing of antigens. We demonstrate the performance of our epitope prediction programs with several examples and in comparison to other epitope prediction programs available. We also reflect the actual possibilities and limitations of such computer-aided work.

EpiToolKit--a web server for computational immunomics

Predicting the T-cell-mediated immune response is an important task in vaccine design and thus one of the key problems in computational immunomics. Various methods have been developed during the last decade and are available online. We present EpiToolKit, a web server that has been specifically designed to offer a problem-solving environment for computational immunomics. EpiToolKit offers a variety of different prediction methods for major histocompatibility complex class I and II ligands as well as minor histocompatibility antigens. These predictions are embedded in a user-friendly interface allowing refining, editing and constraining the searches conveniently. We illustrate the value of the approach with a set of novel tumor-associated peptides. EpiToolKit is available online at www.epitoolkit.org.

The immunoinformatics of cancer immunotherapy

We review here the developments in the field of immunoinformatics and their present and potential applications to the immunotherapeutic treatment of cancer. Antigen presentation plays a central role in the immune response, and as a result in immunotherapeutic methods such as adoptive T-cell transfer and antitumor vaccination. We therefore extensively review the current technologies of antigen presentation prediction, including the next generation predictors, which combine proteasomal processing, transporter associated with antigen processing and major histocompatibility complex (MHC)-binding prediction. Minor histocompatibility antigens are also relevant targets for immunotherapy, and we review the current systems available, SNEP and SiPep. Here, antigen presentation plays a key role, but additional types of data are also incorporated, such as single nucleotide polymorphism data and tissue/cell-type expression data. Current systems are not capable of handling the concept of immunodominance, which is critical to immunotherapy, but efforts have been made to model general aspects of the immune system. Although tough challenges lie ahead, when measuring the field of immunoinformatics on its contributions thus far, one can expect fruitful developments in the future.

Mechanisms of minor histocompatibility antigen immunogenicity: the role of infinitesimal versus structurally profound polymorphisms

Minor histocompatibility antigens (mHAgs) are a diverse collection of major histocompatibility complex (MHC)-bound peptides that play a critical role in the induction of detrimental graft-versus-host disease (GVHD) or the development of beneficial graft-versustumor (GVT) effects after allogeneic hematopoietic stem cell transplantation. mHAgs are a consequence of allelic polymorphism that translates to disparity in MHC-presented peptide epitopes between transplant donor and recipient. This donor/recipient allelic disparity can range from infinitesimal amino side chain differences between MHC-presented peptides, to profound structural polymorphisms in genes and proteins that can nullify transcription or translation of one allelic variant and result in the complete abrogation of its presentation by MHC.

Contribution of mass spectrometry-based proteomics to immunology

Antigen processing forwards various information about the cellular status and the proteome to the cell surface for scrutiny by the cellular immune system. Thus the repertoire of major histocompatibility complex (MHC)-bound peptides and the MHC ligandome, indirectly mirrors the proteome in order to make alterations instantly detectable and, if necessary, to oppose them. Mass spectrometry is the core technology for analysis of both proteome and MHC ligandome and has evoked several strategies to gain qualitative and quantitative insight into the MHC-presented peptide repertoire. After immunoaffinity purification of detergent-solubilized peptide-MHC complexes followed by acid elution of peptides, liquid chromatography-mass spectrometry is applied to determine individual peptide sequences and, thus, allow qualitative characterization of the MHC-bound repertoire. Differential quantification based on stable isotope labeling enables the relative comparison of two samples, such as diseased and healthy tissue. Targeted searches for certain natural ligands, such as the 'predict-calibrate-detect' strategy, include motif-based epitope prediction and calibration with reference peptides. Thus, various approaches are now available for exposing and understanding the intricacies of the MHC ligand repertoire. Analysis of differences in the MHC ligandome under distinct conditions contributes to our understanding of basic cellular processes, but also enables the formulation of immunodiagnostic or immunotherapeutic strategies.

SiPep: a system for the prediction of tissue-specific minor histocompatibility antigens

Approximately 50 years ago it was found that inbred strains of mice were able to reject tumours and skin grafts from major histocompatibility complex (MHC) identical donors. They proposed that additional transplantation antigens must exist outside the MHC. These were described as minor histocompatibility antigens (mHAgs). Since then, related studies in humans have identified 16 human mHAgs. The aim of this work is to increase the number of known mHAgs by prediction of candidate minor histocompatibility loci by identifying coding single nucleotide polymorphisms (SNPs) where the amino acid variation lies within an MHC-binding peptide and alters the ability of that peptide to bind. We have developed an algorithm called SiPep which uses peptide sequences derived from the flanking regions of known non-synonymous SNPs, various MHC-binding and proteolytic cleavage evaluation methods and protein expression data to predict mHAgs. We have processed 45094 SNPs using the SiPep algorithm and have stored the results in a database called SNPBinder. The facilities to process submitted proteins through the SiPep algorithm as well as the SNPBinder database are available to the public. A set of peptides that are predicted as possible mHAgs by the SiPep algorithm have been tested using refolding assays and gel filtration and the results are presented in this paper. The SiPep tools and SNPBinder database are available free of charge via the internet. An HTML interface providing search facilities can be found at the following address: http://www.sipep.org/.

SVMHC: a server for prediction of MHC-binding peptides

Identification of MHC-binding peptides is a prerequisite in rational design of T-cell based peptide vaccines. During the past decade a number of computational approaches have been introduced for the prediction of MHC-binding peptides, efficiently reducing the number of candidate binders that need to be experimentally verified. Here the SVMHC server for prediction of both MHC class I and class II binding peptides is presented. SVMHC offers fast analysis of a wide range of alleles and prediction results are given in several comprehensive formats. The server can be used to find the most likely binders in a protein sequence and to investigate the effects of single nucleotide polymorphisms in terms of MHC-peptide binding. The SVMHC server is accessible at http://www-bs.informatik.uni-tuebingen.de/SVMHC/.