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Case study 1: Xanthomonas arboricola pathovar pruni - bacterial pathogen of plants

Xanthomonas arboricola pv. pruni (XAP) is a bacterial pathogen of Prunus species, including peach, almond, and Japanese plum, and is listed as an EPPO A2 quarantine organism. Infection leads to:

  • Unmarketable Fruit: Cracks and necrotic spots result in rejection during grading.

  • Weakened Trees: Premature leaf drop reduces fruit size, weight, and quality, weakening affected orchards.

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Economic Impact

  • Italy: Losses exceed €10,000/ha; during severe outbreaks, 25-75% of peach fruit is unmarketable.

  • Australia: Estimated annual losses of AU$3.1 million.

  • Spain: Almond production losses of 23-46% in 2014.

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Spread and Persistence

Originally confined to Italy and France, XAP has spread across Europe since 2014, with frequent outbreaks on Prunus laurocerasus. In the UK, outbreaks are often linked to nursery interceptions, with recurrent infections detected over multiple years.

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Genomic Surveillance for Disease Management

Whole genome sequencing (WGS) can address critical management challenges:

  1. Recurrence vs. Reinfection: Determine if outbreaks in nurseries are persistent or due to new infections.

  2. Epidemiological Links: Identify whether UK outbreaks are connected or result from separate introductions.

  3. Strain Differentiation: Distinguish pathogenic XAP from non-pathogenic X. arboricola strains, reducing unnecessary regulatory actions.

  4. Plasmid-Associated Pathogenicity: Confirm species identity and plasmid presence, crucial for identifying pathogenic strains.

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FERA's collection of ~90 XAP isolates from the UK and Europe, along with other X. arboricola isolates, provides a robust foundation for genomic investigations. These tools can be applied to other bacterial plant pathogens, enhancing plant disease management strategies.

Case study 2: Koi Herpesvirus Disease - exploiting new sequencing technologies for improved responses and control

Koi herpesvirus disease (KHVD), caused by Cyprinid herpesvirus-3 (CyHV-3), is a highly contagious disease of common carp (Cyprinus carpio). It has been a notifiable disease under the World Organisation for Animal Health (OIE) since 2007 and has been reported in 18 European countries, Asia, South Africa, and Iraq.

KHVD primarily occurs at water temperatures of 17°C to 28°C, with mortality rates reaching up to 100%, particularly during initial outbreaks. In England, fisheries affected by KHVD are placed under statutory movement controls by the Fish Health Inspectorate (FHI), often lasting for years.

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Economic Impact

While the total cost of KHVD to the UK industry is unknown, coarse fisheries had a capital value of £2.3 billion in 2001, with anglers spending nearly £2 billion annually. A widespread outbreak could significantly impact rural economies in England and Wales. For comparison:

  • In Germany, outbreaks cost €150,000 to €250,000 per farm (20 tonnes of fish).

  • Between 2010 and 2016, 138 KHVD outbreaks were recorded in UK fisheries.

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Key Challenges

  1. Transmission Routes: Understanding how the virus spreads between and within fisheries.

  2. Virus Persistence: Assessing how long CyHV-3 remains viable in the environment.

  3. Reactivation: Evaluating the risk of latent virus re-emerging in seemingly healthy fish.

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Molecular Epidemiology of CyHV-3

CEFAS has used Variable Number Tandem Repeat (VNTR) polymorphisms to study CyHV-3 genetic variability. Key findings include:

  • 75 distinct VNTR profiles were identified in UK samples (2003–2016), indicating multiple independent introductions and highlighting even greater genetic diversity of CyHV-3 potentially circulates globally.

  • The large number of unique CyHV-3 haplotypes suggests the importation of infected fish poses a greater risk than local transmission between fisheries.

  • VNTR analysis often links outbreaks to common suppliers, emphasizing the role of biosecurity in preventing disease spread.

VNTR analysis is now routinely used by FHI to investigate outbreak linkages. However, current methods are time-consuming and costly, with only 20% of available cases analysed. By exploiting new genomic techniques such as long-read sequencing, could streamline this process, enabling faster and more comprehensive surveillance.

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Metagenomic approaches for Surveillance

Environmental DNA (eDNA) offers a non-invasive method for KHVD surveillance. However, a key concern with metagenomic sequencing for surveillance when using eDNA, is the inadvertent detection of OIE-listed pathogens, potentially triggering full-scale disease investigations based on ‘suspicion’ of infection, often without clear insight into the infection status inferred from eDNA signals.

CyHV-3-positive ponds provide a natural setting to evaluate eDNA screening, as cyprinid DNA pathogens are limited, reducing the risk of detecting unrelated OIE-listed pathogens. Metagenomic approaches can:

  • Detect low-level CyHV-3 infections in water and sediment samples.

  • Assess intra- and inter-sample variation to improve surveillance accuracy.

By refining genetic and metagenomic tools, KHVD management can be enhanced, reducing economic losses and improving biosecurity across fisheries.

Case study 3: Pork product imports and risks of virus introduction to the UK

The UK pig industry faces ongoing challenges from both endemic and exotic viral diseases, which threaten food security, animal welfare, and economic stability. Among these threats, African Swine Fever Virus (ASFV) is a critical concern due to its rapid global spread and devastating impact on pig populations.

 

Trade and Biosecurity Risks

The UK is a significant player in the global pork market, ranking as the 9th largest importer, accounting for 4% of global pork imports in 2018, valued at £1.1 billion. Approximately 60% of pig meat imports come from European countries like Denmark, Germany, and the Netherlands, posing a moderate biosecurity risk. However, illegal and personal imports—often involving high-risk animal products—represent a greater threat.

A 2019 analysis of UK border inspection seizures revealed that 15% of confiscated goods were pork-related, while 33% involved other meats. These figures highlight the ongoing risk of exotic disease introduction via both legal and illegal trade routes.

ASFV, in particular, remains a significant concern. Since its emergence in China in 2018, ASFV has caused catastrophic losses in Asia and Eastern Europe, with outbreaks reported in Belgium, Sicily, and neighbouring countries. The UK government currently classifies the risk of ASFV introduction as 'medium.' According to APHA and DEFRA, illegal pork products entering the UK through passenger luggage and being discarded in areas accessible to wild boar or domestic pigs present a significant biosecurity challenge.

 

Genomic Surveillance at UK Borders

Current border inspection methods rely on physical screening and conventional diagnostic tests, which can be time-consuming and may not detect pathogens that can survive in imported food products. Integrating real-time genomic surveillance at border inspection points (BIPs) offers a transformative approach to detecting exotic viral pathogens like ASFV.

By deploying portable genomic technologies (e.g., MinION, iSeq, MiniSeq), UK authorities could:

  • Rapidly Detect Pathogens: Identify viral genomes within 24 hours, enabling immediate response and containment.

  • Enhance Traceability: Generate genomic epidemiology data to trace the origin and transmission pathways of detected pathogens.

  • Improve Detection Sensitivity: Combine genomic data with antigen-based 'pen-side' tests to increase the accuracy and reliability of pathogen detection.

 

Addressing Operational Challenges

Effective surveillance requires optimizing where and how to sample to maximize detection efficiency while minimizing costs. Key challenges include:

  • Targeting High-Risk Containers: With thousands of containers entering UK ports daily, determining which to inspect is critical.

  • Sampling Strategies: Identifying the optimal number of samples and their locations within a container (e.g., front, middle, back) can significantly impact detection sensitivity.

  • Sample Selection: Deciding which components of a product to test (e.g., meat, bone, blood) is crucial for pathogen identification.

Genomic technologies offer scalability and cost efficiencies through methods like pooled sampling and automated processing. However, operational research is needed to develop risk-based models that optimize sampling strategies. These models would estimate the likelihood of pathogen detection under different sampling conditions and provide confidence levels for each scenario.

 

Building a Decision-Support Tool

We propose a systematic approach to refine surveillance strategies through direct experimentation and statistical analysis. By varying the intensity and thoroughness of sampling across selected containers, we can empirically collect data to improve risk-based models. The end goal is to develop a decision-support tool that guides border inspectors in selecting high-risk consignments and determining optimal sampling protocols.

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Conclusion

Integrating real-time genomic technologies into UK border surveillance offers a powerful solution to enhance biosecurity in the pig industry. By combining rapid pathogen detection with optimized sampling strategies, the UK can strengthen its defence against exotic viral diseases, safeguarding both the agricultural sector and national food security.

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