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Review
. 2007 Jun;7(6):485-90.
doi: 10.1038/nri2092.

Integrating epitope data into the emerging web of biomedical knowledge resources

Bjoern Peters  1 , Alessandro Sette
Affiliations
Review

Integrating epitope data into the emerging web of biomedical knowledge resources

Bjoern Peters et al. Nat Rev Immunol. 2007 Jun.

Abstract

The recognition of immune epitopes is an important molecular mechanism of the vertebrate immune system to discriminate between self and non-self. Increasing amounts of data on immune epitopes are becoming available due to technological advances in epitope-mapping techniques and the availability of genomic information for pathogens. Organizing this data poses a challenge that is similar to the successful effort that was required to organize genomic data, which needed the establishment of centralized databases that complement the primary literature to make the data readily accessible and searchable by researchers. As described in this Innovation article, the Immune Epitope Database and Analysis Resource aims to achieve the same for the more complex and context-dependent information on immune epitopes, and to integrate this data with existing and emerging knowledge resources.

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Conflict of interest statement

The authors declare no competing financial interests.

Figures

Figure 1
Figure 1. Generating a formal ontology for the Immune Epitope Database (IEDB).
The initial ontology of the IEDB described all elements of the database as classes with associated characteristics (left panel shows this for the immunogen class). In the development process towards a formal ontology, these elements are placed in a hierarchy (simplified view depicted on the right), in which relationships between the different classes are made explicit. For example, the previously separate and unconnected classes Antigen, Immunogen and Adjuvant are now recognized as being objects (for example, Proteins), which participate in a certain role (as Immunogens) in a specific process (such as Immunization).
Figure 2
Figure 2. Querying and reporting epitope information.
Three steps in an advanced query for B-cell epitopes are illustrated. First, criteria are specified to query for epitopes that are recognized in mice, where the immunogen applied was the epitope source species and the species is selected to be severe acute respiratory syndrome (SARS)-associated coronavirus (a). On submitting this query, a summary of epitope records matching these criteria are displayed (b). This includes information on the curated reference, epitope structure, epitope source, and assay used. When choosing the 'Details' link for a specific epitope, the complete curated information is displayed (c).
Figure 3
Figure 3. Homology mapping of an epitope into its three-dimensional source protein structure.
For a given epitope and its source protein, the homology tool of the Immune Epitope Database and Analysis Resource identifies homologous proteins with known three-dimensional structures, and maps the location of epitopes in these structures. In this example, the peptide NTNSGPDDQIGYYRRATR (shown in blue), which is recognized by antibodies from mice immunized with inactivated severe acute respiratory syndrome (SARS)-associated coronavirus (SARS-CoV)34, is mapped to an X-ray structure of the SARS-CoV nucleocapsid protein. The arrow indicates a section of the epitope that is exposed at the surface of the virus, making it a candidate binding site for the antibody in the native protein structure.
Figure 4
Figure 4. Distribution of influenza A virus epitope data.
After curating all journal articles published with immune epitope information, several summary analyses could be carried out. This pie chart illustrates the relative number of antibody and T-cell epitopes identified. Surprisingly, although protective immunity against the influenza virus is known to be largely mediated by antibodies, this chart reveals that much more data is available on T-cell epitopes for this virus.
See this image and copyright information in PMC

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