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| Funder | Horizon Europe Guarantee |
|---|---|
| Recipient Organization | University of Edinburgh |
| Country | United Kingdom |
| Start Date | Sep 30, 2024 |
| End Date | Sep 29, 2026 |
| Duration | 729 days |
| Number of Grantees | 2 |
| Roles | Fellow; Principal Investigator |
| Data Source | UKRI Gateway to Research |
| Grant ID | EP/Z00182X/1 |
The proliferation of the global wildlife trade has increased the risk of disease spill-over into human, wildlife, and farmed animal populations, with potentially catastrophic consequences. Increasing capacity for rapid and inexpensive diagnosis of disease in wildlife to understand the source of the traded items and the disease risks is a crucial step towards tackling this significant issue.
Few diagnostic platforms explicitly combine disease and wildlife diagnostics, following a One Health approach; currently, the analysis of a trade item typically involves the use of different tests performed in different laboratories to identify pathogens and their associated wildlife host. Further, utilising high-throughput sequencing in wildlife diagnostics is impractical for most laboratories due to the monetary and time costs required, or its use is limited to specific species/pathogen groups.
I propose to harness recent advancements in DNA sequencing and a novel 'adaptive sampling' technology that allows users to target specific DNA sequences in real-time using state-of-the-art software. This innovative adaptive sampling approach simply requires the user to input the relevant diagnostic genetic markers into a computer program; these genetic markers are then targeting during DNA sequencing, without prior laboratory enrichment steps.
I will leverage these technological advances to develop and optimise a workflow capable of detecting pathogens and their wildlife vectors in a single assay.
Simultaneous analysis of host and pathogen species to inform population disease risk, biodiversity conservation and law enforcement in a wildlife trade scenario, is novel and multi-faceted in application. This research will therefore provide advanced and interdisciplinary experience for the Fellow, directly aligning with the goals of this Call. Project outcomes will inform a blueprint to implement adaptive sampling in other wildlife diagnostic systems, and in applied genetics more broadly.
University of Edinburgh
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