Identifying virus transmission routes and intervention efficacy in aquaculture through novel virus genomic approaches.

Over 40% of farmed fish and shellfish die due to infectious diseases in some aquaculture systems, most because of viruses. Virus outbreaks in aquaculture therefore harm welfare, cost £5 billion annually, and hinder production sustainability. A 35% expansion of aquaculture is planned by 2030 to feed a growing global population. Increased market connectivity, larger and denser aquatic populations, and sectoral growth in countries with poor biosecurity will likely worsen outbreaks. We urgently need new strategies to prevent this.
In the widespread absence of vaccines and prophylaxis, strategies to reduce virus spread rely on interventions like movement bans, equipment cleaning, or culling. To deploy these better, we need to know (i) how viruses move between facilities and (ii) the effectiveness of control measures. The former is not captured by infection data. The latter cannot be easily quantified through measuring observed disease, in part because other fish health metrics (e.g., stress) may affect disease severity and likelihood of observation.
My Fellowship will address this challenge using advances in virus genomics, and computational tools that enable genomes to be analysed along with other big data types. I will achieve this through focus on farmed Atlantic salmon (Salmo salar), the most important aquatic species in the UK.
O1: Resolve the importance of boat-mediated virus transfer of non-notifiable viruses. Salmon farmed at sea are serviced by boats and kept in nets through which seawater flows. Both virus flow in water or on contaminated equipment could cause infections, but resolving the relative importance of these is tricky because patterns of higher virus movement between neighbouring farms is explainable by both. I will solve this through bait-enriched genomic sequencing and phylodynamic analysis of endemic viruses in marine sites that present repeated “natural experiments” across Norway, allowing discrimination between the importance of these transmission modes for diverse common viruses including piscine myocarditis virus.
O2: Develop approaches to measure the importance of virus dispersal modes by joint analysis of multiple data types. Natural experiments are insufficient for pathogens not circulating within them. We need new tools that can analyse virus genomes together with complex dynamic network information on water current data and boat/fish movements to enhance tracking and prediction of spread. I will develop new computational approaches that allow us to better integrate movement networks, disease case data and virus genomes.
O3: Enable producer-personalised solutions to controlling endemic disease. Producers are frustrated by the lack of evidence to guide their actions to try and control non-notifiable endemic diseases. Massive, detailed data on fish health and their environment, already monitored confidentially across sites, could be used with virus genomes to seek innovative and personalised control measures. Working with a multinational producer, I will conduct a high-resolution, longitudinal virus genomic epidemiological study on two sites, bringing together data types to improve producer-led interventions.
Success in my objectives will contribute to reducing salmon disease. Collaborating with industry leaders and government will ensure effective translation across scales. Aquaculture – and animal health more broadly - is in the early stages of a major shift towards routine virus genome sequencing. My work will therefore be important in establishing and proving methods to maximize the value of growing genomic datasets at an early stage of need. Reducing virus outbreaks will improve aquatic animal welfare, enable sustainable industry growth, protect wild populations, and reduce consumer costs.