CASE NOTES

NSW dashboard for gastrointestinal nematodes & anthelmintic resistance in ruminants

Jan Šlapeta, Sydney School of Veterinary Science, Faculty of Science, The University of Sydney, New South Wales, Emily Francis, Sydney School of Veterinary Science, Faculty of Science, The University of Sydney, New South Wales, and Janina McKay, Elizabeth Macarthur Agricultural Institute, New South Wales Department of Primary Industries, Menangle, New South Wales

Posted Flock & Herd August 2025

INTRODUCTION

Control of gastrointestinal nematodes (GINs) in livestock relies heavily on anthelmintics, but the development of anthelmintic resistance is a global problem^1,2. The three major classes of anthelmintics are macrocyclic lactones, benzimidazoles, and imidazothiazoles like levamisole². In Haemonchus contortus, resistance to levamisole appears to develop more slowly than the other classes. Detecting molecular resistance markers is critical to ensuring the continued efficacy of levamisole³. Traditional phenotypic resistance tests are laborious and lack sensitivity. In contrast, modern molecular diagnostics can detect known causal mutations or genetically linked markers, offering new opportunities for resistance surveillance and evidence-based management⁴.

Recently, through funding from the McGarvie Smith Institute, we developed a rapid molecular diagnostic approach that simultaneously identifies parasite species and screens for resistance to levamisole (LEV) and benzimidazoles (BZ) in livestock GINs⁵. We validated a deep-amplicon sequencing method to detect the LEV-resistant S168T mutation in the acr-8 gene of Haemonchus spp. and combined it with detection of BZ resistance mutations in the β-tubulin isotype-1 gene. Concurrent ITS-2 metabarcoding was used to identify GINs present in field isolates.

We demonstrated that LEV, BZ, and ITS-2 amplicons can be pooled for high-throughput sequencing without compromising data quality. In a preliminary dataset, the S168T mutation was detected in 12/32 (37.5%) field isolates, with two populations exceeding the resistance threshold of 16%. BZ resistance, particularly at codons 167 and 200, was widespread in Haemonchus spp. from sheep and goats, but rare in cattle. This integrated molecular approach offers a powerful tool for large-scale surveillance of anthelmintic resistance in livestock parasites, informing sustainable management strategies⁵.

WormResistanceMonitor (WoRM) Dashboard

Our mixed amplicon metabarcoding approach enables rapid detection of anthelmintic resistance to both LEV and BZ in parasitic nematode populations. This approach overcomes key limitations of current phenotypic resistance tests, such as long turnaround times and poor sensitivity for early-stage resistance. However, these data are not accessible to any producer at this moment and the research remains an academic exercise. To really enable use of these data, communication and dissemination is needed.

To bridge this gap, we developed the WormResitanceMonitor (WoRM) Dashboard - a dynamic, producer-facing platform that presents GIN surveillance data across NSW in a visual format (Figure 1). The dashboard is available at: parasites.shinyapps.io

The dashboard is publicly accessible 24/7 and allows users to zoom in or out of their region of interest. Interactive features, including choropleth maps and selectable filters, allow producers and farm advisors to view parasite species compositions and resistance profiles that can be incorporated into decision-making for parasite control.

Figure 1. The WoRM Dashboard provides dynamic access to data on the distribution of GINs as well as their genetic signatures conferring resistance to BZs and LEV

DISCUSSION

Molecular diagnostics offer an evidence-based foundation for determining which anthelmintics remain effective on a given property^4,5. The results allow farmers to make informed decisions on sustainable parasite management and promote the long-term effectiveness of available anthelmintics. The approach is scalable, leveraging robotics and high-throughput sequencing technologies, and when coupled with an accessible front-end dashboard, can be progressively updated as new surveillance data become available. We have already demonstrated the feasibility of using this approach for medium-scale surveillance of anthelmintic resistance across different livestock hosts in a geographic region. This dashboard provides a platform for translating complex data into actionable insights for producers. Ultimately, it has the potential to guide national and regional parasite management strategies and address one of the ongoing challenges faced by Australia's grazing industries².

ACKNOWLEDGEMENTS

Authors acknowledge the support from Sydney Informatics Hub, The University of Sydney with development and deployment of the dashboard. The work was in part supported by the McGarvie Smith Institute funding.

REFERENCES

Kaplan RM (2004) Drug resistance in nematodes of veterinary importance: a status report Trends in Parasitology 20:477-481
Kotze AC & Hunt PW (2023) The current status and outlook for insecticide, acaricide and anthelmintic resistances across the Australian ruminant livestock industries: assessing the threat these resistances pose to the livestock sector Australian Veterinary Journal 101:321-333
Doyle SR, Laing R, Bartley D et al. (2022) Genomic landscape of drug response reveals mediators of anthelmintic resistance Cell Reports 41:111522
Šlapeta J, Vande Velde F, Martinez-Valladares M et al. (2024) Towards precision parasite management for livestock gastrointestinal nematodes in 2030 Trends in Parasitology 40:886-895
Francis EK, Antonopoulos A, Westman ME et al. (2024) A mixed amplicon metabarcoding and sequencing approach for surveillance of drug resistance to levamisole and benzimidazole in Haemonchus spp. International Journal of Parasitology 54:55-64