A mixed amplicon metabarcoding and sequencing approach for surveillance of drug resistance to levamisole and benzimidazole in Haemonchus spp.

Anthelmintic-resistant parasitic nematodes present a significant threat to sustainable livestock production worldwide. The ability to detect the emergence of anthelmintic resistance at an early stage, and therefore determine which drugs remain most effective, is crucial for minimising production losses. Despite many years of research into the molecular basis of anthelmintic resistance, no molecular-based tools are commercially available for the diagnosis of resistance as it emerges in field settings. We describe a mixed deep amplicon sequencing approach to determine the frequency of the levamisole (LEV)-resistant single nucleotide polymorphism (SNP) within arc-8 exon 4 (S168T) in Haemonchus spp., coupled with benzimidazole (BZ)-resistant SNPs within beta-tubulin isotype-1 and the internal transcribed spacer-2 (ITS-2) nemabiome. This constitutes the first known multi-drug and multi-species molecular diagnostic developed for helminths of veterinary importance. Of the ovine, bovine, caprine and camelid Australian field isolates we tested, S168T was detected in the majority of Haemonchus spp. populations from sheep and goats, but rarely at a frequency greater than 16%; an arbitrary threshold we set based on whole genome sequencing (WGS) of LEV-resistant Haemonchus contortus GWBII. Overall, BZ resistance was far more prevalent in Haemonchus spp. than LEV resistance, confirming that LEV is still an effective anthelmintic class for small ruminants in New South Wales, Australia. The mixed amplicon metabarcoding approach described herein paves the way towards the use of large scale sequencing as a surveillance technology in the field, the results of which can be translated into evidence-based recommendations for the livestock sector. (c) 2023 The Author(s). Published by Elsevier Ltd on behalf of Australian Society for Parasitology. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).