Ontology-based representation and analysis of host-Brucella interactions

Area of Science:

• Biomedical Informatics
• Immunology
• Microbiology

Background:

• Biomedical ontologies standardize data and enable automated reasoning.
• IDOBRU is an ontology specifically designed for Brucella and brucellosis.
• Brucella causes brucellosis, a prevalent zoonotic disease.

Purpose of the Study:

• To model and analyze host-pathogen interactions using Brucella as a model.
• To integrate and understand Brucella pathogenesis and host immunity mechanisms.
• To leverage the IDOBRU ontology for detailed interaction analysis.

Main Methods:

• Ontological representation of host-Brucella interactions at different levels.
• Modeling of Brucella entry, intracellular trafficking, and replication within macrophages.
• Incorporation of Brucella pathogenesis mechanisms (Type IV secretion system, erythritol metabolism) and host cell death pathways.

Main Results:

• Defined ontological levels for host-Brucella interactions.
• Represented key virulent Brucella-macrophage processes and pathogenesis mechanisms.
• Modeled Brucella-associated cell death, including vaccine strain effects.
• Annotated 432 Brucella virulence factors using OGG and PRO.
• Implemented seven inference rules and identified critical virulence factors and biological processes via SPARQL queries.

Conclusions:

• Provided the first comprehensive ontological model for host-pathogen interactions using Brucella.
• Demonstrated the utility of IDOBRU for systematic analysis of host-pathogen mechanisms.
• Proposed that the methods and ontology are generalizable to other pathogens.