Non-invasive farm biosurveillance for livestock health and AMR risk

Overview

Livestock production systems need practical ways to understand pathogen and antimicrobial resistance risk before those risks become harder to manage. Traditional surveillance often depends on individual animal sampling, clinical signs, veterinary investigation or post-event testing. Those approaches remain important, but they can be difficult to scale continuously across busy production environments.

BioSeer's founding team helped deliver farm biosurveillance work with the Veterinary Medicines Directorate and PATH-SAFE partners, exploring how environmental sampling could support earlier and broader monitoring of pathogen and AMR risk in livestock housing. The work demonstrated that air, faecal and saliva sampling can be combined with qPCR, sequencing and bioinformatics to profile microbial communities, screen for key pathogen targets and investigate antimicrobial resistance genes within livestock systems.

The Challenge

Pathogens and antimicrobial resistance do not stay neatly inside individual animals. They move through housing air, faecal material, saliva, surfaces, slurry and the wider farm environment. For producers, veterinarians and policy teams, this creates a practical challenge: how can risk be monitored across a production system without relying solely on individual animal testing?

Farm surveillance also needs to be operationally realistic. Any monitoring approach must work around animal welfare, staff movement, biosecurity controls and the realities of commercial production. The programme asked whether environmental epidemiology could provide a more scalable route: using air and other sample types to detect microbial and AMR signals across the livestock environment.

The integrated approach

• Air, faecal and saliva surveillance. The programme collected environmental and animal-associated samples from livestock housing across defined production time points — before animals entered cleaned housing, early in the production period and later in the housing cycle. Air surveillance was a particular focus because it can monitor the shared environment without requiring direct animal handling, making it attractive for routine, repeatable and lower-disruption biosurveillance in farms, marts, abattoirs and other agri-food settings.
• Targeted qPCR screening. Samples were screened using qPCR panels for selected pathogen and AMR targets. The pathogen panel included assays for Escherichia coli, Klebsiella oxytoca, Streptococcus agalactiae and Salmonella spp. AMR screening included carbapenem-resistant Enterobacteriaceae markers such as NDM-1, KPC, OXA-48, VIM and IMP; vancomycin-resistant Enterococci markers VanA and VanB; and other resistance markers including CA-MRSA, OXA-23, GES and MCR-1.
• Sequencing and microbiome analysis. Long-read sequencing characterised the microbial communities present in air, faecal and saliva samples, providing a broader view than targeted qPCR alone and showing how microbial composition varied by sample type, location and production stage. Sequencing was also used to investigate AMR gene diversity across sample types and to assess whether environmental air sampling could act as a proxy for broader livestock-environment monitoring.
• Related commercial-farm validation. The platform was further supported by a separate air-surveillance study in cattle housing on a commercial farm, used to assay bovine respiratory disease-associated targets including Mycoplasma bovis, Pasteurella multocida, Histophilus somni, Mannheimia haemolytica, bovine coronavirus, bovine RSV and bovine parainfluenza-3.

What the programme delivered

• A practical farm-surveillance model: air, faecal and saliva sampling were used to monitor microbial and AMR signals across livestock housing.
• Lower-disruption monitoring: air surveillance showed particular promise because it can be performed without direct interaction with animals.
• Targeted pathogen screening: qPCR enabled selected pathogen targets to be assayed across relevant sample types and time points.
• AMR gene intelligence: qPCR and sequencing were used to investigate the type, diversity and abundance of AMR genes in the farm environment.
• Microbiome insight: long-read sequencing provided a broader view of bacterial, fungal, viral and eukaryotic community composition.
• Cross-setting potential: related cattle-house work showed how the same air-surveillance model can be adapted to other livestock settings and respiratory pathogen panels.

Why it matters now

The agri-food system needs surveillance tools that are scalable, practical and capable of detecting risk across complex production environments. Environmental biosurveillance offers a way to understand pathogen and AMR signals at the level of the housing environment, not just the individual animal.

For BioSeer, this case study demonstrates how microbiology, genomics, AMR analysis and environmental sampling can be integrated into a practical surveillance workflow for livestock production. Most laboratories specialise. BioSeer integrates.