Ontology development for the Immune Epitope Database Bjoern Peters La Jolla Institute for Allergy and Immunology

Overview Background –Epitopes –Immune Epitope Database (IEDB)‏ IEDB Ontology development –History –Ontology for Biomedical Investigations (OBI)‏ –IDO

Mouse Virus APC CD8 + T cell epitopes in viral infection MHC-I

APC MHC-I T Cytokine Release Cytotoxicity T T Proliferation Mouse Virus TCR CD8 CD8 + T cell epitopes in viral infection

Why study epitopes? Vaccines/ immunotherapy –Evaluations –Subunit design Diagnostics –Correlate with disease outcomes Basic studies –Host-pathogen interactions –Immunodominance and interplay between different immune reactivities

Goal: To catalog, organize and make accessible immune epitope related information IEDB Literature curation Epitope discovery contract submission The Immune Epitope Database (IEDB)‏

IEDB Team SAIC Scott Stewart Tom Carolan Hussein Emami San Diego Supercomputer Center Phil Bourne Julia Ponomarenko Zhanyang Zhu Technical University of Denmark Ole Lund Morten Nielsen University of Copenhagen Søren Buus La Jolla Institute for Allergy & Immunology

Literature Curation Progress

Curation Priorities Category A-C pathogens & toxins Infectious diseases Allergens (started 10/2007)‏ Self antigens involved in autoimmunity Transplant rejection antigens and other alloantigens Cancer epitopes

What epitope information is extracted in curation?

The Immune Epitope Database (IEDB)‏ Permits complex queries and analysis Total of >100 fields How where fields chosen and how are they filled?

Epitope defining experiments have shared components MHC Binding APC MHC Ligand Elution T APC T Cell Response TB B Cell Response

IEDB data structure Sathiamurthy et al, Immunome Research, 2005 Need to specify exactly what is meant to ensure consistency for curators, users and machines Data structure extended over time to deal with information not captures well initially (e.g. Allergy epitopes, immunotherapy, challenge assays)‏ Simultaneously, formal ontology was developed. Redesign of data structure to separate objects, roles and processes. Scope limited by 'epitopyness'. We care about a peptide sequence. We don't care about how a peptide was synthesized.

Towards a formal ontology source_of plays_role Antigen_role

Integrate into larger ontology effort Upper level ontology from BFO Shared concepts from other biomedical ontologies (GO, NCBI taxonomy, FMA,...)‏ Experiment terms from Ontology of Biomedical Investigations (OBI)‏  IDO should be the source of our infectious disease related terms  Need for IO to generalize? (Immunology ontology)‏

Experimental Terms → Ontology for Biomedical Investigations (OBI)‏

Protocol application for T cell response Break experiment down into sub processes –Inject mice with virus –Take T cells from mice –Test T cells for reactivity to peptide in ELISPOT assay T APC T Cell Response T

Administering substance in vivo Define process in terms of objective = desired output in terms of required inputs A process with the objective to give a substance to an organism through a specified route of administration Relations –has input: organism (role: recipient)‏ –has input: material entity (role: administered substance)‏ –has output: organism and has_part (anatomical entity has_part administered substance)‏  infinity of subclasses: 'Administering mice with Vaccina Virus intraperitonial at base of tail using syringe T APC T Cell Response T

Taking sample from organism is a process with the objective to obtain material from an organism. Pseudo OWL –has input: organism (role: donor)‏ –has output: object (role: sample) derived from anatomical entity of (organism and has_role donor_role)‏ T APC T Cell Response T

ELISPOT Assay an assay with the objective to count the number of cells in a population that produce a certain biomaterial using ELISPOT plates 'Pseudo OWL definition' –has input: cell population (role: sample)‏ –utilizes: ELISPOT plate, biomaterial label –has output: data and is_proxy_for number of cells in input population producing biomaterial Subclass: "T cell response to peptide stimulus IFN-g ELISPOT" Two assays, one with additional input 'peptide' and role antigen.  data is proxy for 'T cell response to peptide' T APC T Cell Response T

Parent protocol application Connect the inputs and ouputs –Administering substance in vivo output organism = input for –Taking sample from organism output sample is input for –ELISPOT assay Also: Time intervals, controls, multiple repeats, dose response etc. T APC T Cell Response T

OBI scope artifact objects Instruments Reagents samples objective driven processes Measurements, Material preparation Data transformation, Information artifacts Data Protocols Hypothesis

IDO / IO

OBI is missing immunology OBI: Administration in vivo IEDB: –Immunization, Immunogen –Host –Adjuvant OBI: ELISPOT = count protein secreting cells IEDB: –Antigen –APC / Effector cells –Immune Response T APC T Cell Response T

Epitope basics Notation: class, relation Adaptive immune receptor is a object (union of TCR, BCR, Ab)‏ T cell is a cell and has_part TCR B cell is a cell and has_part BCR Epitope role is a role born by (object or object part)‏ Epitope binding by adaptive immune receptor is a process –is_realization_of epitope role –has_participant adaptive immune receptor bound_to (material entity has_role epitope role) Shortcut: Epitope is a material entity and plays_role Epitope role

Immunization Immunogen role is born by object Adaptive immune effector function is born by (Antibody or T cell or, B cell)‏ Immunization is a process –is_realization_of 'immunogen role' –has_part epitope binding by adaptive immune receptor and (epitope part_of immunogen or derived_from immunogen)‏ –has_result ((T cell or B cell) and has_function adaptive immune effector function)‏ Immunization in vivo is a immunization –has_process_location (organism and has_role host_role)‏ Immunization in vitro is a immunization –has_process_location cell culture

Immune response Antigen role is born by object Adaptive immune response is a process –is_realization_of antigen role –is_realization_of Adaptive immune effector function –has_part epitope binding by adaptive immune receptor and (epitope part_of antigen or derived_from antigen)‏

Disease Disease is a disposition Occurrence of disease is a process –is realization of disease –is realization of host role –has process location (organism and has_role host_role)‏ –has_part pathologic process Infectious agent role is born by organism Occurrence of infectious disease is a occurrence of disease –is_realization_of (infectious agent role born by organism)‏ –is_preceded_by host exposure to infectious agent

Exposure / Proximity host exposure to infectious agent is a process –has_participant organism bears_role host –has_participant organism bears_role infectious agent role –Infectious agent part of or adjacent to host Administered exposure with infectious agent –Is a administering substance in vivo (OBI)‏ –Has participant material and plays_role administered substance and has_role infectious agent role Environmental exposure to infectious agent –Is a host exposure to infectious agent –Preceded by environmental proximity to infectious agent Environmental proximity to infectious agent

IEDB Team SAIC Scott Stewart Tom Carolan Hussein Emami San Diego Supercomputer Center Phil Bourne Julia Ponomarenko Zhanyang Zhu Technical University of Denmark Ole Lund Morten Nielsen University of Copenhagen Søren Buus La Jolla Institute for Allergy & Immunology