FAIR principles and the IEDB: short-term improvements and a long-term vision of OBO-foundry mediated machine-actionable interoperability.

The Immune Epitope Database (IEDB), at www.iedb.org, has the mission to make published experimental data relating to the recognition of immune epitopes easily available to the scientific public. By presenting curated data in a searchable database, we have liberated it from the tables and figures of journal articles, making it more accessible and usable by immunologists. Recently, the principles of Findability, Accessibility, Interoperability and Reusability have been formulated as goals that data repositories should meet to enhance the usefulness of their data holdings. We here examine how the IEDB complies with these principles and identify broad areas of success, but also areas for improvement. We describe short-term improvements to the IEDB that are being implemented now, as well as a long-term vision of true 'machine-actionable interoperability', which we believe will require community agreement on standardization of knowledge representation that can be built on top of the shared use of ontologies

Epitopes in ChEBI - A Collaboration with the IEDB

*ChEBI background:* Chemical Entities of Biological Interest (ChEBI) is a curated database of small chemical entities important in biosystems. As well as a description of entities, it provides a semantically rich knowledge base; and an internal hierarchy that organises the entities by their molecular structure types and potential rôles.

*The ChEBI-IEDB collaboration:* The Immune Epitope and Analysis Resource (IEDB) is a project supported by contract from the National Institute of Allergy and Infectious Diseases (NIAID). Its goal is to make epitope-related data on infectious diseases and immune disorders freely available to researchers worldwide. In June 2009, ChEBI began working with the IEDB on a project aimed at incorporating into ChEBI, by manual curation, a pilot subset of immunologically important chemicals identified as immune epitopes.

*The significance of the project:* Numerous reports attest to an increasing global prevalence of immune-related diseases, with a multiplicity of contributing factors. This situation underscores the need for cross-talk among the various scientific disciplines, and makes ChEBI involvement in this project particularly relevant. 

*Collaboration outcome:* That collaboration among curators working on different databases can be reciprocally beneficial has been amply demonstrated by the ChEBI-IEDB teamwork described: while the incorporated IEDB items have substantially enriched ChEBI, the latter’s multiplicity of synonyms, structure tree lay-out and expertise in describing non-peptidic epitopes have been equally useful to the IEDB in facilitating the search process.
*Status quo and plans:* We continue to refine our task of assisting the identification, understanding and utilisation of biologically meaningful chemical entities by engaging in further joint projects

Towards Defining Molecular Determinants Recognized by Adaptive Immunity in Allergic Disease: An Inventory of the Available Data

Adaptive immune responses associated with allergic reactions recognize antigens from a broad spectrum of plants and animals. Herein a meta-analysis was performed on allergy-related data from the immune epitope database (IEDB) to provide a current inventory and highlight knowledge gaps and areas for future work. The analysis identified over 4,500 allergy-related epitopes derived from 270 different allergens. Overall, the distribution of the data followed expectations based on the nature of allergic responses. Namely, the majority of epitopes were defined for B cells/antibodies and IgE-mediated reactivity, and relatively fewer T-cell epitopes, mostly CD4+/class II. Interestingly, the majority of food allergen epitopes were B-cells epitopes whereas a fairly even number of B- and T-cell epitopes were defined for airborne allergens. In addition, epitopes from nonhumans hosts were mostly T-cell epitopes. Overall, coverage of known allergens is sparse with data available for only ~17% of all allergens listed by the IUIS database. Thus, further research would be required to provide a more balanced representation across different allergen categories. Furthermore, inclusion of nonpeptidic epitopes in the IEDB also allows for inventory and analysis of immunological data associated with drug and contact allergen epitopes. Finally, our analysis also underscores that only a handful of epitopes have thus far been investigated for their immunotherapeutic potential

The Immune Epitope Database 2.0

The Immune Epitope Database (IEDB, www.iedb.org) provides a catalog of experimentally characterized B and T cell epitopes, as well as data on Major Histocompatibility Complex (MHC) binding and MHC ligand elution experiments. The database represents the molecular structures recognized by adaptive immune receptors and the experimental contexts in which these molecules were determined to be immune epitopes. Epitopes recognized in humans, nonhuman primates, rodents, pigs, cats and all other tested species are included. Both positive and negative experimental results are captured. Over the course of 4 years, the data from 180 978 experiments were curated manually from the literature, which covers ∼99% of all publicly available information on peptide epitopes mapped in infectious agents (excluding HIV) and 93% of those mapped in allergens. In addition, data that would otherwise be unavailable to the public from 129 186 experiments were submitted directly by investigators. The curation of epitopes related to autoimmunity is expected to be completed by the end of 2010. The database can be queried by epitope structure, source organism, MHC restriction, assay type or host organism, among other criteria. The database structure, as well as its querying, browsing and reporting interfaces, was completely redesigned for the IEDB 2.0 release, which became publicly available in early 2009

Immunological consequences of intragenus conservation of Mycobacterium tuberculosis T-cell epitopes

A previous unbiased genome-wide analysis of CD4 Mycobacterium tuberculosis (MTB) recognition using peripheral blood mononuclear cells from individuals with latent MTB infection (LTBI) or nonexposed healthy controls (HCs) revealed that certain MTB sequences were unexpectedly recognized by HCs. In the present study, it was found that, based on their pattern of reactivity, epitopes could be divided into LTBI-specific, mixed reactivity, and HC-specific categories. This pattern corresponded to sequence conservation in nontuberculous mycobacteria (NTMs), suggesting environmental exposure as an underlying cause of differential reactivity. LTBI-specific epitopes were found to be hyperconserved, as previously reported, whereas the opposite was true for NTM conserved epitopes, suggesting that intragenus conservation also influences host pathogen adaptation. The biological relevance of this observation was demonstrated further by several observations. First, the T cells elicited by MTB/NTM cross-reactive epitopes in HCs were found mainly in a CCR6+CXCR3+ memory subset, similar to findings in LTBI individuals. Thus, both MTB and NTM appear to elicit a phenotypically similar T-cell response. Second, T cells reactive to MTB/NTM-conserved epitopes responded to naturally processed epitopes from MTB and NTMs, whereas T cells reactive to MTB-specific epitopes responded only to MTB. Third, cross-reactivity could be translated to antigen recognition. Several MTB candidate vaccine antigens were cross-reactive, but others were MTB-specific. Finally, NTM-specific epitopes that elicit T cells that recognize NTMs but not MTB were identified. These epitopes can be used to characterize T-cell responses to NTMs, eliminating the confounding factor of MTB cross-recognition and providing insights into vaccine design and evaluation

Epitope Specific Antibodies and T Cell Receptors in the Immune Epitope Database

The Immune Epitope Database (IEDB) is a free public resource which catalogs experiments characterizing immune epitopes. To accommodate data from next generation repertoire sequencing experiments, we recently updated how we capture and query epitope specific antibodies and T cell receptors. Specifically, we are now storing partial receptor sequences sufficient to determine CDRs and VDJ gene usage which are commonly identified by repertoire sequencing. For previously captured full length receptor sequencing data, we have calculated the corresponding CDR sequences and gene usage information using IMGT numbering and VDJ gene nomenclature format. To integrate information from receptors defined at different levels of resolution, we grouped receptors based on their host species, receptor type and CDR3 sequence. As of August 2018, we have cataloged sequence information for more than 22,510 receptors in 18,292 receptor groups, shown to bind to more than 2,241 distinct epitopes. These data are accessible as full exports and through a new dedicated query interface. The later combines the new ability to search by receptor characteristics with previously existing capability to search by epitope characteristics such as the infectious agent the epitope is derived from, or the kind of immune response involved in its recognition. We expect that this comprehensive capture of epitope specific immune receptor information will provide new insights into receptor-epitope interactions, and facilitate the development of novel tools that help in the analysis of receptor repertoire data

Curation of complex, context-dependent immunological data

BACKGROUND: The Immune Epitope Database and Analysis Resource (IEDB) is dedicated to capturing, housing and analyzing complex immune epitope related data . DESCRIPTION: To identify and extract relevant data from the scientific literature in an efficient and accurate manner, novel processes were developed for manual and semi-automated annotation. CONCLUSION: Formalized curation strategies enable the processing of a large volume of context-dependent data, which are now available to the scientific community in an accessible and transparent format. The experiences described herein are applicable to other databases housing complex biological data and requiring a high level of curation expertise

OBO Foundry in 2021: Operationalizing Open Data Principles to Evaluate Ontologies

Biological ontologies are used to organize, curate, and interpret the vast quantities of data arising from biological experiments. While this works well when using a single ontology, integrating multiple ontologies can be problematic, as they are developed independently, which can lead to incompatibilities. The Open Biological and Biomedical Ontologies Foundry was created to address this by facilitating the development, harmonization, application, and sharing of ontologies, guided by a set of overarching principles. One challenge in reaching these goals was that the OBO principles were not originally encoded in a precise fashion, and interpretation was subjective. Here we show how we have addressed this by formally encoding the OBO principles as operational rules and implementing a suite of automated validation checks and a dashboard for objectively evaluating each ontology’s compliance with each principle. This entailed a substantial effort to curate metadata across all ontologies and to coordinate with individual stakeholders. We have applied these checks across the full OBO suite of ontologies, revealing areas where individual ontologies require changes to conform to our principles. Our work demonstrates how a sizable federated community can be organized and evaluated on objective criteria that help improve overall quality and interoperability, which is vital for the sustenance of the OBO project and towards the overall goals of making data FAIR. Competing Interest StatementThe authors have declared no competing interest

The Ontology for Biomedical Investigations

The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed in association with OBI. The current release of OBI is available at http://purl.obolibrary.org/obo/obi.owl