Multi-scale occupancy approach to estimate Toxoplasma gondii prevalence and detection probability in tissues: an application and guide for field sampling

Abstract

Increasingly, birds are recognised as important hosts for the ubiquitous parasite Toxoplasma gondii, although little experimental evidence exists to determine which tissues should be tested to maximise the detection probability of T. gondii. Also, Arctic-nesting geese are suspected to be important sources of T. gondii in terrestrial Arctic ecosystems, but the parasite has not previously been reported in the tissues of these geese. Using a domestic goose model, we applied a multi-scale occupancy framework to demonstrate that the probability of detection of T. gondii was highest in the brain (0.689, 95% confidence interval=0.486, 0.839) and the heart (0.809, 95% confidence interval=0.693, 0.888). Inoculated geese had an estimated T. gondii infection probability of 0.849, (95% confidence interval=0.643, 0.946), highlighting uncertainty in the system, even under experimental conditions. Guided by these results, we tested the brains and hearts of wild Ross's Geese (Chen rossii, n=50) and Lesser Snow Geese (Chen caerulescens, n=50) from Karrak Lake, Nunavut, Canada. We detected 51 suspected positive tissue samples from 33 wild geese using real-time PCR with melt-curve analysis. The wild goose prevalence estimates generated by our multi-scale occupancy analysis were higher than the naïve estimates of prevalence, indicating that multiple PCR repetitions on the same organs and testing more than one organ could improve T. gondii detection. Genetic characterisation revealed Type III T. gondii alleles in six wild geese and Sarcocystis spp. in 25 samples. Our study demonstrates that Arctic nesting geese are capable of harbouring T. gondii in their tissues and could transport the parasite from their southern overwintering grounds into the Arctic region. We demonstrate how a multi-scale occupancy framework can be used in a domestic animal model to guide resource-limited sample collection and tissue analysis in wildlife. Secondly, we confirm the value of traditional occupancy in optimising T. gondii detection probability in tissue samples.

Keywords: Arctic; Occupancy modelling; Ross’s goose; Snow goose; Tissue detection; Toxoplasma.