Research project GENOme based PREDICTion of risks posed by Viral Pathogens in a OneHealth approach

General introduction

In the field of viral diseases of plants, a useful prediction tool has been developed within the GenoPREDICT research project. This tool better estimates the risk of future disease outbreaks caused by RNA viruses. RNA viruses, particularly from the Riboviria kingdom, pose a major challenge to global disease control due to their rapid evolution and adaptability to the host. At the end of the project, valorization is already a reality: The Belgian NPPO (National Plant Protection Organization) is implementing the tool, in order to better target its monitoring programs for virus diseases. The tool will be optimized in terms of easy (online) accessibility.

Research approach

The project followed a three-phase approach: (1) compiling a comprehensive viral-proteomic database, (2) developing machine learning models for predictive analysis, and (3) validating models on both well-characterized and poorly characterized viral species.
This project integrated multidisciplinary expertise, including virology, bioinformatics, and data
science, to develop a scalable, data-driven approach to understanding viral evolution. The
ultimate goal was to create a predictive framework/tool, capable of identifying potential outbreak risks
by assessing key biological features of unknown viruses.

Relevance/Valorization

The relevance is high. In addition to the availability of the prediction tool, GenoPREDICT has provided valuable scientific insights into virus-host interactions, transmission mechanisms and evolutionary dynamics. These are crucial for epidemic preparedness and global (plant) health security. NPPO promises to pay attention to keeping the database up-to-date, essential for the tool's relevance into the future.