Abstracts Division 1

16. Semantic modelling of Adverse Outcome Pathways and the implementation in reproducible workflows

Martens M.1, Evelo C.T.1,2  and Willighagen E.L.1

1 Department of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, Maastricht, The Netherlands
2 Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The Netherlands

The purpose of Adverse Outcome Pathways is to organize mechanistic knowledge on toxicological processes upon exposure to a stressor leading to an Adverse Outcome through a series of Key Events (KEs). The implementation of this concept for risk assessments is aimed to facilitate the replacement, reduction, refinement (3Rs) of animal testing. Qualitative descriptions of AOPs are generally stored in the public AOP-Wiki. However, its content remains relatively isolated and is only manually queryable or through downloading the full dataset, limiting the capabilities of this rich resource of toxicological knowledge.

We tackled this AOP-Wiki limitation by FAIRifying into the AOP-Wiki Resource Description Framework (RDF) as triples. We used over twenty ontologies for the semantic annotation of property-object relations, and we introduced over 10,000 database descriptors for chemicals, genes and proteins..
 
The AOP-Wiki RDF has been made available at aopwiki.rdf.bigcat-bioinformatics.org where SPARQL queries can be used to extract information and answer biological and toxicological questions, manually or computationally.

As a demonstration, we developed a notebook that adds information to an AOP of interest and finds and extracts supporting experimental data from ToxCast and TG-GATES based on the molecular targets and stressor chemicals, and perform transcriptomics pathway enrichment analysis with WikiPathways.

Overall, the AOP-Wiki RDF improves the accessibility and interoperability of the database, providing additional ways of querying the data and enabling the implementation in automated workflows. By focusing on increasing the machine-readability of AOPs and using consistent vocabularies and ontologies, AOPs become an increasingly useful tool for integrating toxicological knowledge and data, thereby increasing the effectiveness of the concept and addressing the 3Rs in toxicological studies.

This project has received funding from the European Union’s Horizon 2020 (EU 2020) research and innovation program under grant agreement no. 681002 (EU-ToxRisk) and EINFRA-22-2016 program under grant agreement no. 731075 (OpenRiskNet).

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