The use of nemabiome metabarcoding to explore gastro-intestinal nematode species diversity and anthelmintic treatment effectiveness in beef calves.

Next-generation deep amplicon sequencing, or metabarcoding, has revolutionized the study of microbial communities in humans, animals and the environment. However, such approaches have yet to be applied to parasitic helminth communities. We recently described the first example of such a method - nemabiome sequencing - based on deep-amplicon sequencing of internal transcribed spacer 2 (ITS-2) rDNA, and validated its ability to quantitatively assess the species composition of cattle gastro-intestinal nematode (GIN) communities. Here, we present the first application of this approach to explore GIN species diversity and the impact of anthelmintic drug treatments. First, we investigated GIN species diversity in cow-calf beef cattle herds in several different regions, using coproculture derived L3s. A screen of 50 Canadian beef herds revealed parasite species diversity to be low overall. The majority of parasite communities were comprised of just two species; Ostertagia ostertagi and Cooperia oncophora. Cooperia punctata was present at much lower levels overall, but nevertheless comprised a substantive part of the parasite community of several herds in eastern Canada. In contrast, nemabiome sequencing revealed higher GIN species diversity in beef calves sampled from central/south-eastern USA and Sao Paulo State, Brazil. In these regions C. punctata predominated in most herds with Haemonchus placei predominating in a few cases. Ostertagia ostertagi and C. oncophora were relatively minor species in these regions in contrast to the Canadian herds. We also examined the impact of routine macrocyclic lactone pour-on treatments on GIN communities in the Canadian beef herds. Low treatment effectiveness was observed in many cases, and nemabiome sequencing revealed an overall increase in the proportion of Cooperia spp. relative to O. ostertagi post-treatment. This work demonstrates the power of nemabiome metabarcoding to provide a detailed picture of GIN parasite community structure in large sample sets and illustrates its potential use in research, diagnostics and surveillance.