MULTI-STATE OCCUPANCY MODEL ESTIMATES PROBABILITY OF DETECTION OF AN AQUATIC PARASITE USING ENVIRONMENTAL DNA: PSEUDOLOMA NEUROPHILIA IN ZEBRAFISH AQUARIA.

Abstract

Detecting the presence of important parasites within a host and its environment is critical to understanding the dynamics that influence a pathogen's ability to persist, while accurate detection is also essential for the implementation of effective control strategies. Pseudoloma neurophilia is the most common pathogen reported in zebrafish (Danio rerio) research facilities. The only assays currently available for P. neurophilia are through lethal sampling, often requiring euthanasia of the entire population for accurate estimates of prevalence in small populations. We present a non-lethal screening method to detect P. neurophilia in tank water based on the detection of environmental DNA (eDNA) from this microsporidium, using a previously developed qPCR assay that was adapted to the digital PCR (dPCR) platform to complement current surveillance protocols. Using the generated dPCR data, a multi-state occupancy model was also implemented to predict the probability of detecting the microsporidium in tank water under different flow regimes and pathogen prevalence. The occupancy model revealed that samples collected in static conditions were more informative than samples collected from flow-through conditions, with a probability of detection at 80% and 47%, respectively. There was also a positive correlation between the frequency of detection in water and prevalence in fish based on qPCR.