A potentially game-changing breakthrough in disease diagnostics could pave the way for earlier detection of Johne’s Disease in cattle, thanks to pioneering work by the biotechnology firm MI:RNA. Using microRNA biomarkers in combination with AI-powered predictive modelling, scientists believe they can now detect the disease in its early stages – before any visible symptoms emerge or productivity is lost.
The innovation offers the promise of significant benefits for farmers and the environment alike. By identifying the disease earlier, it may be possible to avoid major losses, improve herd health, and reduce greenhouse gas emissions – all while saving the UK farming sector tens of millions of pounds annually.
Johne’s Disease, an inflammatory condition affecting cattle and sheep, is alarmingly widespread – with prevalence rates within UK herds estimated at up to 50 per cent. The disease often spreads silently through infected animals that show no obvious signs, making it notoriously difficult to manage with current diagnostics.
Existing screening methods have focused on identifying and removing affected animals, but with limited reliability. MI:RNA’s approach, developed in collaboration with scientists from Scotland’s Rural College (SRUC), centres on microRNAs – small molecules that regulate gene expression and offer stable, easily detectable biomarkers in bodily fluids.
“Animal health is more important than ever, with Johne’s disease costing farmers tens of millions around the UK each year,” said Dr Eve Hanks, Founder and CEO at MI:RNA Diagnostics. “For MI:RNA this is a key area of research and development. Biomarker science combined with our AI-powered modelling means that we can significantly improve animal health, reduce financial strain on farmers, while also reducing greenhouse gas output as a result. We believe miRNAs can assist with progressing future diagnostic testing and understanding diseases more effectively.”
The team’s preliminary study analysed miRNA expression in samples taken from both infected and uninfected cattle, using machine learning to assess the diagnostic potential. The early results suggest this combined approach can reliably distinguish infected animals even in the disease’s early stages.
Professor Spiridoula Athanasiadou of SRUC added: “SRUC has been at the forefront of Johne’s disease control via the Premium Cattle Health Scheme for over 25 years and is in support of research that feeds into practice. At SRUC we value our ongoing collaboration with MI:RNA Diagnostics, which has generated data that demonstrates potential for added benefits of the new tool. Upscaling is important for wider implementation and further development.”
While the study’s sample size was small, future research aims to expand the dataset and refine the method for even greater accuracy. MI:RNA is also exploring whether the approach could be adapted to distinguish Johne’s from other infections, strengthening the role of miRNA diagnostics across animal health.
For the farming industry, this development may represent a timely and much-needed advance. With each undetected case of Johne’s estimated to cost around £200 per cow annually – nearly half of some farmers’ profits – effective early detection is not just a scientific milestone, but an economic imperative.
Pictured: L to R: Dr Paul Capewell (Bioinformatics consultant), Dr Frank Turnbull (Lab Manager), Dr Robert Coultous (CSO), Marta Lis (Lab tech), Dr Eve Hanks (CEO)