The development and deployment of a field-based loop mediated isothermal amplification assay for virulent Dichelobacter nodosus detection on Australian sheep Academic Article uri icon


  • Dichelobacter nododus is the causative agent of footrot, a major disease of sheep that creates welfare concerns and large economic loss. The virulence of D. nododus depends on the presence of extracellular proteases, AprV2 and AprB2, which differ by one amino acid. Strains possessing AprV2 can cause clinically virulent disease, while AprB2 may cause clinically benign disease. Current methods for detecting D. nodosus are difficult, laborious and time consuming. New techniques capable of rapidly detecting and typing D. nodosus are needed to aid control programs. Molecular methods, like real-time polymerase chain reaction (rtPCR) can detect aprV2 and aprB2, however, this assay is not field-deployable and cannot support local decision-making during an outbreak. Here we present a field-based molecular assay for detecting aprV2, using loop mediated isothermal amplification (LAMP). The aprV2 LAMP (VDN LAMP) assay was optimised to reliably detect aprV2 from laboratory purified genomic (gDNA) of virulent D. nodosus down to 5x10(-3) ng μL-1, with time to positive (Tp) ≤ 16 minutes, while aprB2 was unreliably detected at 5 ng μL-1 from 16-20 minutes. The use of field collected samples that were rtPCR positive for aprB2 resulted in no amplification, while aprV2 positive field samples by VDN LAMP assay are defined as having Tps' of < 20 minutes and melting temperature between 88.0-88.9°C. When compared to rtPCR, the VDN LAMP was shown to have a diagnostic specificity of 100% and sensitivity of 83.33%. As proof of concept, the VDN LAMP was taken on farm, with all processing occurring in-field. The on farm VDN LAMP successfully detected 91.67% aprV2 positive samples, no aprB2 positive samples (n = 9) or D. nodosus negative (n = 23) samples, with a kappa agreement of 'almost perfect' to rtPCR. This highlights the potential of the assay to inform local treatment decisions for management.

publication date

  • 2018