Development and application of an eDNA-based sampling and analytic approach for integrated surveillance of wildlife-related pathogens

Recent emerging priorities in wildlife disease surveillance have created the need for integrated monitoring approaches across Europe. These methodologies, which merge passive and active surveillance with population monitoring, are essential for enhancing early pathogen detection, evaluating epidemiological dynamics, and assessing the progress or results of disease management interventions. This scientific report focuses on the use of eDNA in light of the need for integrated wildlife health monitoring. This study aims to test several hypotheses to further these goals: firstly, test if camera trap data can effectively inform the selection of sampling sites; secondly, the effectiveness of combining metabarcoding with metagenomic approaches for pathogen surveillance; and thirdly, the development of a harmonized strategy for selecting sampling sites to optimize sensitivity. Using as pilot areas three study sites monitored within the framework of the European Observatory of Wildlife we had the opportunity of confronting three areas similar in terms of biodiversity (i.e. number of vertebrate species detectable by camera traps), all within the southern and western bioregions of Europe. In these three study areas wildlife trapping rates were coupled with topo-hydrographic data to identify suitable areas for environmental sampling characterized by high and low presence of animals respectively. Water and soil were used as environmental matrices. eDNA extracted from collected samples was analysed in parallel using metabarcoding and native sequencing (i.e., PCR-free metagenomic sequencing using nanopore technology). The obtained results confirmed the optimal complementarity of both sample matrices and sequencing methodology which greatly contributed to increase detected biodiversity, both for mammals as well as for arthropod vectors and wildlife-related pathogens. The strategy for sampling site selection combining topo-hydrographic and wildlife trapping rate showed no significant difference in terrestrial biodiversity (considering only mammals and birds which are likely to be detected by camera trapping). The possibility of improving species detection (and thus of related pathogens') is suggested when considering only sampling sites close to known areas of high occupancy (Camera traps with high trapping rate).  While both methods provide valuable insights, they detect overlapping but distinct subsets of the community, highlighting the importance of integrating multiple approaches for biodiversity assessments. This pilot study marks a significant advancement in the standardization of eDNA methods, contributing to more effective wildlife surveillance systems. The integration of eDNA-based approaches with prior knowledge of the hydrographic features and watersheds of the study areas, together with prior knowledge of wildlife presence and abundance gives significant guidance to further pursue this line of research to integrate eDNA in wildlife health surveillance