Strategies to query and display allergy-derived epitope data from the immune epitope database

Prediction and identification of epitopes in the Echinococcus multilocularis thrombospondin 3 antigen

BACKGROUND: Alveolar echinococcosis is an epidemic disease caused by the parasitism of Echinococcus multilocularis (Em) larvae in the intermediate or final host. OBJECTIVE: To identify and analyze B-cell and T-cell (Th1, Th2, and Th17) epitopes of the Em antigen protein thrombospondin 3 (TSP3). METHODS: The amino acid sequence of TSP3 was obtained, and the secondary structural characteristics of TSP3 were predicted using bioinformatics software to further predict its potential T-cell and B-cell epitopes. The spleen lymphocytes of BALB/c mice, which were immunized with the TSP3 protein, were collected for co-culture with B-cell and T-cell antigen small peptides. The B-cell epitopes and T-cell epitope subtypes Th1, Th2, and Th17 were identified as having good immunogenicity. RESULTS: After identification, it was found that the predominant epitopes of B cells existing in TSP3 were T18-33, T45-55, and T110-122. Furthermore, the predominant epitopes of T cells existing in TSP3 were T33-42, T45-55, T80-90, and T110-122 in the T1 subtype, T45-55, T68-77, and T92-104 in the Th2 subtype, and T53-63 and T80-90 in the Th17 subtype. CONCLUSIONS: Six T-cell and eight B-cell dominant epitopes of the TSP3 antigen were revealed; these results may be applied in the development of a dominant epitope vaccine.

The effect of immunotherapy on cross-reactivity between house dust mite and other allergens in house dust mite -sensitized patients with allergic rhinitis

INTRODUCTION

House dust mite (HDM) is a main perennial allergen causing allergic rhinitis (AR). It has been shown that HDM cross-reacts with a variety of other allergens. Presently, allergen-specific immunotherapy (AIT) is an effective way for management of mono-sensitized HDM⁺ AR patients. However, management approaches to polysensitized HDM-sensitized AR patients are not standardized yet.

AREA COVERED

This article reviews the data available in the literature for cross-reactivity between HDM and inhalant or food allergens, the diagnosis of cross-reactivity in HDM-sensitized AR patients, and the effect of immunotherapy on cross-reactivity in HDM-sensitized AR patients; which may help to develop effective therapeutic strategies for management of polysensitized HDM-sensitized AR patients in the future.

EXPERT OPINION

Pan-allergen proteins such as tropomyosin, arginine kinase (AK), glutathione S-transferase (GST), and hemocyanin are responsible for cross-reactivity between HDM and other allergens. To distinguish genuine or cross-reactive sensitization, molecular- or component-resolved diagnosis is suggested to apply in HDM-sensitized AR patients. The effect of HDM immunotherapy to treat the associated cross-reactivity in HDM-sensitized AR patients is still contradictory, and might be dependent on the degree of homology between two allergens. Furthermore, targeting tropomyosin might be a promising way to treat HDM patients with allergen cross-reactivity.

ABBREVIATIONS

AIT: allergen-specific immunotherapy; AK: arginine kinase; AR: allergic rhinitis; CRD: component-resolved diagnostics; Der f: Dermatophagoides farina; Der p: Dermatophagoides pteronyssinus; EAACI: European Academy of Allergy and Clinical Immunology; GST: glutathione S-transferase; GWAS: genome-wide association study; HDM: house dust mite; IgE: immunoglobulin E; RAST: radioallergosorbent test; sIgE: specific IgE; SIT: specific immunotherapy; SCIT: subcutaneous immunotherapy; SLIT: sublingual immunotherapy; SPT: skin prick test.

The COMPARE Database: A Public Resource for Allergen Identification, Adapted for Continuous Improvement

Motivation: The availability of databases identifying allergenic proteins via a transparent and consensus-based scientific approach is of prime importance to support the safety review of genetically-modified foods and feeds, and public safety in general. Over recent years, screening for potential new allergens sequences has become more complex due to the exponential increase of genomic sequence information. To address these challenges, an international collaborative scientific group coordinated by the Health and Environmental Sciences Institute (HESI), was tasked to develop a contemporary, adaptable, high-throughput process to build the COMprehensive Protein Allergen REsource (COMPARE) database, a publicly accessible allergen sequence data resource along with bioinformatics analytical tools following guidelines of FAO/WHO and CODEX Alimentarius Commission.

Results: The COMPARE process is novel in that it involves the identification of candidate sequences via automated keyword-based sorting algorithm and manual curation of the annotated sequence entries retrieved from public protein sequence databases on a yearly basis; its process is meant for continuous improvement, with updates being transparently documented with each version; as a complementary approach, a yearly key-word based search of literature databases is added to identify new allergen sequences that were not (yet) submitted to protein databases; in addition, comments from the independent peer-review panel are posted on the website to increase transparency of decision making; finally, sequence comparison capabilities associated with the COMPARE database was developed to evaluate the potential allergenicity of proteins, based on internationally recognized guidelines, FAO/WHO and CODEX Alimentarius Commission

Conservation Analysis of B-Cell Allergen Epitopes to Predict Clinical Cross-Reactivity Between Shellfish and Inhalant Invertebrate Allergens

Understanding and predicting an individual's clinical cross-reactivity to related allergens is a key to better management, treatment and progression of novel therapeutics for food allergy. In food allergy, clinical cross-reactivity is observed in patients reacting to unexpected allergen sources containing the same allergenic protein or antibody binding patches (epitopes), often resulting in severe allergic reactions. Shellfish allergy affects up to 2% of the world population and persists for life in most patients. The diagnosis of shellfish allergy is however often challenging due to reported clinical cross-reactivity to other invertebrates including mites and cockroaches. Prediction of cross-reactivity can be achieved utilizing an in-depth analysis of a few selected IgE-antibody binding epitopes. We combined available experimentally proven IgE-binding epitopes with informatics-based cross-reactivity prediction modeling to assist in the identification of clinical cross-reactive biomarkers on shellfish allergens. This knowledge can be translated into prevention and treatment of allergic diseases. To overcome the problem of predicting IgE cross-reactivity of shellfish allergens we developed an epitope conservation model using IgE binding epitopes available in the Immune Epitope Database and Analysis Resource (http://www.iedb.org/). We applied this method to a set of four different shrimp allergens, and successfully identified several non-cross-reactive as well as cross-reactive epitopes, which have been experimentally established to cross-react. Based on these findings we suggest that this method can be used for advanced component-resolved-diagnosis to identify patients sensitized to a specific shellfish group and distinguish from patients with extensive cross-reactivity to ingested and inhaled allergens from invertebrate sources.

Antigen-specific regulatory T-cell responses against aeroantigens and their role in allergy

The mucosal immune system of the respiratory tract is specialized to continuously monitor the external environment and to protect against invading pathogens, while maintaining tolerance to innocuous inhaled particles. Allergies result from a loss of tolerance against harmless antigens characterized by formation of allergen-specific Th2 cells and IgE. Tolerance is often described as a balance between harmful Th2 cells and various types of protective "regulatory" T cells. However, the identity of the protective T cells in healthy vs. allergic individuals or following successful allergen-specific therapy is controversially discussed. Recent technological progress enabling the identification of antigen-specific effector and regulatory T cells has significantly contributed to our understanding of tolerance. Here we discuss the experimental evidence for the various tolerance mechanisms described. We try to integrate the partially contradictory data into a new model proposing different mechanism of tolerance depending on the quality and quantity of the antigens as well as the way of antigen exposure. Understanding the basis of tolerance is essential for the rational design of novel and more efficient immunotherapies.

Contributions and Future Directions for Structural Biology in the Study of Allergens

Allergy is defined as an inappropriate immune response to something normally considered harmless. The symptomatic immune response is driven by IgE antibodies directed against allergens. The study of allergens has contributed significantly to our understanding of allergic disease in 3 main areas. First, identifying allergens as the cause of symptoms and developing allergen standards has led to many advances in exposure assessment and patient diagnostics. Second, a biochemical understanding of allergens has suggested a number of hypotheses related to the mechanisms of allergic sensitization. And finally, studies of allergen-antibody interactions have contributed to understanding the cross-reactivity of allergens, mapping patient epitopes, and the development of hypoallergens. In this review, a few select cases are highlighted where structural biology, in particular, has contributed significantly to allergen research and provided new avenues for investigation.

Navigating through the Jungle of Allergens: Features and Applications of Allergen Databases

The increasing number of available data on allergenic proteins demanded the establishment of structured, freely accessible allergen databases. In this review article, features and applications of 6 of the most widely used allergen databases are discussed. The WHO/IUIS Allergen Nomenclature Database is the official resource of allergen designations. Allergome is the most comprehensive collection of data on allergens and allergen sources. AllergenOnline is aimed at providing a peer-reviewed database of allergen sequences for prediction of allergenicity of proteins, such as those planned to be inserted into genetically modified crops. The Structural Database of Allergenic Proteins (SDAP) provides a database of allergen sequences, structures, and epitopes linked to bioinformatics tools for sequence analysis and comparison. The Immune Epitope Database (IEDB) is the largest repository of T-cell, B-cell, and major histocompatibility complex protein epitopes including epitopes of allergens. AllFam classifies allergens into families of evolutionarily related proteins using definitions from the Pfam protein family database. These databases contain mostly overlapping data, but also show differences in terms of their targeted users, the criteria for including allergens, data shown for each allergen, and the availability of bioinformatics tools.

The contribution of biotechnology toward progress in diagnosis, management, and treatment of allergic diseases

'Biotechnology' has been intuitively used by humans since thousands of years for the production of foods, beverages, and drugs based on the experience without any scientific background. However, the golden era of this discipline emerged only during the second half of the last century. Incredible progresses have been achieved on all fields starting from the industrialization of the production of foods to the discovery of antibiotics, the decipherment of the genetic code, and rational approaches to understand and define the status we now call 'healthy'. The extremely complex interactions between genetic background, life style, and environmental factors influencing our continuously increasing life span have become more and more evident and steadily generate new questions which are only partly answered. Here, we try to summarize the contribution of biotechnology to our understanding, control, and cure of IgE-mediated allergic diseases. We are aware that a review of such a vast topic can never cover all aspects of the progress achieved in the different fields.

Bioinformatic prediction of epitopes in the Emy162 antigen of Echinococcus multilocularis

The aim of the present study was to predict the secondary structure and the T- and B-cell epitopes of the Echinococcus multilocularis Emy162 antigen, in order to reveal the dominant epitopes of the antigen. The secondary structure of the protein was analyzed using the Gamier-Robson method, and the improved self-optimized prediction method (SOPMA) server. The T- and B-cell epitopes of Emy162 were predicted using Immune Epitope Database (IEDB), Syfpeithi, Bcepred and ABCpred online software. The characteristics of hydrophilicity, flexibility, antigenic propensity and exposed surface area were predicted. The tertiary structure of the Emy162 protein was predicted by the 3DLigandSite server. The results demonstrated that random coils and β sheets accounted for 34.64 and 21.57% of the secondary structure of the Emy162 protein, respectively. This was indicative of the presence of potential dominant antigenic epitopes in Emy162. Following bioinformatic analysis, numerous distinct antigenic epitopes of Emy162 were identified. The high-scoring T-cell epitopes were located at positions 16–29, 36–39, 97–103, 119–125 and 128–135, whilst the likely B-cell epitopes were located at positions 8–10, 19–25, 44–50, 74–81, 87–93, 104–109 and 128–136. In conclusion, five T-cell and seven B-cell dominant epitopes of the Emy162 antigen were revealed by the bioinformatic methods, which may be of use in the development of a dominant epitope vaccine.

Navigating diabetes-related immune epitope data: resources and tools provided by the Immune Epitope Database (IEDB)

Background

The Immune Epitope Database (IEDB), originally focused on infectious diseases, was recently expanded to allergy, transplantation and autoimmunity diseases. Here we focus on diabetes, chosen as a prototype autoimmune disease. We utilize a combined tutorial and meta-analysis format, which demonstrates how common questions, related to diabetes epitopes can be answered.

Results

A total of 409 references are captured in the IEDB describing >2,500 epitopes from diabetes associated antigens. The vast majority of data were derived from GAD, insulin, IA-2/PTPRN, IGRP, ZnT8, HSP, and ICA-1, and the experiments related to T cell epitopes and MHC binding far outnumbers B cell assays. We illustrate how to search by specific antigens, epitopes or host. Other examples include searching for tetramers or epitopes restricted by specific alleles or assays of interest, or searching based on the clinical status of the host.

Conclusions

The inventory of all published diabetes epitope data facilitates its access for the scientific community. While the global collection of primary data from the literature reflects potential investigational biases present in the literature, the flexible search approach allows users to perform queries tailored to their preferences, including or excluding data as appropriate. Moreover, the analysis highlights knowledge gaps and identifies areas for future investigation.