Mr Amir Reza Varzandi1, Mr Tim Reska2, Dr Lara Urban2, Dr Stefania Zanet1, Ms Ilaria Pastori1, Prof. Ezio Ferroglio1
1University Of Turin, Grugliasco, Italy, 2Helmholtz Pioneer Campus, Munich, Germany
Biography:
I am in the course of becoming a wildlife biotechnologist. I have studied veterinary biotechnology at the University of Bologna and I am currently pursuing my PhD at the University of Turin in the field of Veterinary Sciences focusing on early detection of wildlife-related pathogens from eDNA samples.
Abstract:
Introduction: Surveillance of wildlife populations for diseases is essential for the early detection of emerging epidemiological situations, safeguarding both animal conservation efforts and public health. Environmental DNA (eDNA) techniques have become increasingly popular due to their non-invasive nature and efficiency, making them preferred for tracking wildlife-related pathogens (WRP). eDNA offers distinct advantages over direct sampling methods, particularly in the detection of parasitic diseases, where the environment serves as a common reservoir for various parasitic life-cycle stages and hosts. With the advent of portable sequencing technologies, eDNA sequencing has emerged as a leading tool for frontline environmental surveillance and the early detection of parasitic infections in wildlife.
Materials and Methods: This study focuses on eDNA collected from lotic waters in and around La Mandria Park’s fenced-off area (Piedmont region, Italy), recognized as one of the primary European hotspots of Fascioloides magna, an invasive trematode of wild and domestic ruminants (Bassi., 1875). We employed active (targeting detection of F. magna and associated hosts involved in its life-cycle) and passive surveillance approaches simultaneously by performing shotgun sequencing coupled with Nanopore’s Adaptive Sampling (PCR-free real-time in silica target enrichment) on eDNA samples previously investigated for F. magna identification.
Results and Conclusions: Our results demonstrate the potential of Nanopore’s Adaptive Sampling not only for efficient, and cost-effective targeted surveillance of parasitic diseases but also in simultaneous passive surveillance by capturing broader biodiversity information and enabling the early detection of other potential WRPs. This approach suggests a promising pathway toward real-time in situ genomic-informed surveillance programs.