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Research Call

DAFM Reference

Lead(Collaborating)Institution

DAFM Award

DAFM National Call 2015 15/S/651 UCD (CIT, AFBI, Teagasc, ICBF, DAFM) €959,374

Project Title:

Next generation approaches to improved diagnostics and molecular epidemiology for control of Mycobacterium avium subsp. Paratuberculosis

Project Coordinator:

Prof Stephen Gordon

Project Abstract

Advances in bioinformatics, ‘omics technologies and computational infrastructure are opening up new research avenues in the study on infectious disease. Such Data Analytics or ‘Big Data’ approaches are becoming common in human medicine, and in this proposal we seek to open up such data-rich approaches to the study of endemic infectious diseases of livestock in Ireland. To achieve this we fill focus on Johne’s disease, caused by Mycobacterium avium subsp paratuberculosis (MAP), as our exemplar disease. The focus on Johne’s disease is driven both by the lack of effective diagnostics and control interventions for this disease, as well as to provide underpinning evidence for the Johne’s disease control programme that was launched in Ireland in 2013, which is overseen by Animal Health Ireland (AHI, Republic of Ireland) and Animal Health and Welfare Northern Ireland (AHWNI). Our project seeks to address key knowledge gaps in our understanding of MAP and Johne’s disease, including the need for increased insight into MAP transmission dynamics, improved diagnostic and prognostic biomarkers, and control systems. To achieve this we have assembled a team of highly experienced researchers from across the island of Ireland and supported by international collaborators who will address these research questions using Next generation approaches for control of MAP (NexusMAP). We will combine computational biology and high-throughput ‘omics technologies, integration of extensive datasets on animal movement, and health and geographical information systems to deliver this ambitious project. The outputs from this work will therefore help to support not only the nascent Johne’s disease control programme, but also the sustainable control of other endemic infectious diseases of livestock through the development and application of common approaches for pathogen tracking, antigen mining, data integration, and computational analysis.

Final Report:

Not available yet.