Disease dynamics in freshwater ecosystems: validation of eDNA for informing exposure risk to wild and farmed fish

Lead Research Organisation: University of Nottingham
Department Name: School of Life Sciences

Abstract

All organisms leave traces of DNA in the environment via sloughed cells, mucous, excretions etc. Such environmental DNA (eDNA) can be extracted from water samples and used to track e.g. rare or invasive species, or to characterise biodiversity more broadly (e.g. fish communities or diversity of invertebrate taxa). Parasites shed from hosts into water can also be detected and quantified simultaneously with the eDNA of their hosts. Such eDNA-based, simultaneous tracking of the host and parasite distributions has the potential to greatly aid in understanding the epidemiology of aquatic diseases. This is important because disease is the major obstacle to the expanding aquaculture industry, and detection, monitoring and surveillance of disease agents via eDNA may provide an important tool for achieving sustainable aquaculture. Aquaculture is closely associated with natural aquatic systems (lochs, rivers, lakes or estuaries) and pathogen spill-over between natural and farmed animals is a constant risk. eDNA may provide particularly important insights to pathogen dispersal, spill-over potential and the temporal variation in exposure risk of farmed animals. This project will focus on eDNA sampling in rivers to track the distributions of parasites and their hosts and assess how parasite transport in rivers affects exposure risk on associated fish farms.

The project is interdisciplinary (joint between Life Sciences and Geography) and the student will receive training in: 1a) Field work (eDNA and invertebrate host collections) AND 1b) Molecular lab work (eDNA extraction, quantitative PCR, NGS library preparation and sequencing and bioinformatics). 2) Laboratory experiments (quantifying variation in eDNA and parasite spore decay and release). 3) Spatially explicit analysis/modelling (eDNA and spore transport/decay) and quantifying the environmental correlates of infection hotspots. Field Collections and Molecular Work: Our previous work on a parasite of salmonid fish has shown that hotspots of high parasite densities in water occur in different parts of a river network. The student will use eDNA sampling to track parasite concentrations across rivers in the UK, and relate the concentrations to the presence of fish and invertebrate hosts (measured from eDNA via "metabarcoding") to reveal exposure and infection 'hotspots'. Sampling locations will include sites upstream and downstream from fish farms,
in key river systems, to assess the likelihoods of spill-over between natural and farmed settings. Lab experiments: Our preliminary work suggests that parasite detection in water is more variable than detection of host DNA. The student would design and conduct experiments in the lab/field to contrast the detection of eDNA naturally sloughed by hosts with the eDNA originating from parasite spores in water. Spatially explicit models: Understanding the variation in the dispersal, retention and detection likelihoods of parasites is crucial for better reconstructing the distributions of the infected hosts and understanding the effective infective range of spores within networks The student will be trained in geospatial analysis techniques and use state-of-the-art remote sensing to map river networks and habitat features. The aim is to identify the key properties that constrain or facilitate the spread of infectious agents and how river network topology modifies the species distribution information gained from eDNA sampling.
References:
Bush, A., Sollmann, R.,Wilting, A., Bohmann, K., Cole, B., Balzter, H., Martius, C., Zlinszky, A., Calvignac-Spencer, S., Cobbold, C.A. and Dawson, T.P., 2017. Connecting Earth observation to highthroughput biodiversity data. Nature Ecology & Evolution, 1(7), p.0176. https://www.nature.com/articles/s41559-017-0176Carraro, L., Hartikainen, H., Jokela, J., Bertuzzo, E. and Rinaldo, A., 2018. Estimating species distribution and abundance in river networks using environmental DNA.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
BB/T008369/1 01/10/2020 30/09/2028
2434399 Studentship BB/T008369/1 01/10/2020 30/09/2024