In vitro interaction between plant secondary metabolite and benzimidazole on the egg hatch of resistant Haemonchus contortus

The livestock industry relies on the regular use of anthelmintic treatment to mitigate production losses due to helminth infections. One such species that can cause heavy production losses is Haemonchus contortus. Resistance has developed in this species towards the currently used classes of anthelmintic; to counter this rise in resistance complementary controls have been used these include plant secondary metabolites (PSM), fungi and vaccination. These alternative controls have no known resistance but often have lower efficacy compared to anthelmintic. The current study evaluates an in vitro method for determining the combined effect of PSM and anthelmintic on the GIN egg stage. To test this combination, egg hatch tests were used in which resistant H. contortus were exposed to a tannin extract and thiabendazole. The bliss independence test was used to determine the nature of the interaction. The egg hatch plates found the interaction to be synergistic at the egg stage of development. This was seen at low tannin concentrations, in which the observed significantly exceeded the predicted 76% (predicted) compared to 88% (observed) for sainfoin. This effect was also seen when the anthelmintic concentration increased, 90% (predicted) compared to 97% (observed) at the same concentration of sainfoin (100µg/ml); anthelmintic concentrations being 0.05 µg/ml and 0.01 µg/ml respectively. The respective independence indices being 0.11 and 0.07 both indicative of a synergistic interaction. Different tannin sources were also investigated, with tannin from wormwood showing no significant difference from predicted at 0.05 µg/ml of thiabendazole. The current study has highlighted that at the egg stage of development the benzimidazole and PSM interaction is synergistic against resistant H. contortus. This would need further testing in more natural conditions, and by breaking down the treatment interaction at different stages. This could help implement combined treatment, knowing how controls interact at each stage.