London: UK researchers are embarking on a 1-million-pound study to establish the extent to which badgers are responsible for spreading tuberculosis (TB) in cattle.
By using a combination of DNA sequencing and mathematical modelling, researchers at the University of Glasgow hope the results will inform effective and scientifically-guided policies for curbing bovine TB.
Bovine TB is the most prominent disease of livestock in Britain and Ireland and is caused by the bacterium Mycobacterium bovis.
Several measures exist for controlling the disease, most controversially badger culling.
This strategy relies on the notion that badgers make the biggest contribution to the persistence and transmission of the disease.
However, the evidence is incomplete ? for example, it is not known precisely how the bacterium spreads between animals.
In order to identify the best strategy for controlling disease the science on which intervention policies are based needs to be refined.
The team led by Professor Rowland Kao in the Institute of Biodiversity, Animal Health and Comparative Medicine, will study thousands of archived samples of bacteria that have been isolated from badgers and cattle over a period of 20 years.
They will read the entire DNA of M bovis , and then analyse it using advanced mathematical and statistical models.
This groundbreaking study will take advantage of the cutting-edge sequencing technologies at Glasgow Polyomics, a flagship facility at the University of Glasgow.
This large-scale DNA study will provide unprecedented information: it will reveal an accurate map of how the bacterium moves across the landscape, providing a much deeper understanding of the mechanisms of this spread and whether it is mainly cattle or badgers that are responsible.
Affordable and rapid DNA-sequencing technologies are increasingly being used to advance our understanding of the risks to human and animal health, and inform policy to minimise those risks.
Professor Kao, who will work on this project with his University of Glasgow colleagues Dr Roman Biek and Dr Pawel Herzyk, said, "This study is an excellent example of the potential for new technologies to transform our understanding of epidemiology.
"The mathematical models produced for this study are important for understanding not only the transmission of bovine TB, but also the dynamics of other infectious diseases," he said.