Pathogen tracing via metagenomics metabolomics and volatilomics for early disease diagnosis in swine and poultry

Project summary

Current pathogen diagnostic methods in the pig and poultry sector often rely on invasive methods, such as blood tests. Moreover, many tests, including culturing, cannot be performed on the farm itself, thereby causing a delay in the diagnosis. The identification of pathogen predictive biomarkers is a first but crucial step in developing on-site pathogen diagnostics, enabling rapid, accurate, and non-invasive disease monitoring and allowing farmers to take immediate action and limit economic losses.

PathOmics aims to identify such predictive biomarkers for early disease diagnosis and control. We will focus on characterizing the metagenomic, metabolomic, and volatilomic signatures during disease pro-gression. Recent data integration techniques allow PathOmics not only to analyse these -omics data separately but to integrate them in a machine learning pipeline, generating far more robust identification of predictive biomarkers. These will be validated in a commercial farm setting.

As case studies, PathOmics focuses on two animal species and both a bacterial and a viral pathogen, showcasing the potential of thedeveloped method for application to other animals and pathogens: enterotoxigenic Escherichia coli (ETEC) in pigs, and Avian Reovirus (ARV) in broilers. Lessons learned and methods developed for these case studies will lead to a blueprint for the identification of biomarkers for viruses and bacteria in farm animals. All samples collected will be made available in an open access biobank for future research.