Elsevier

Aquaculture

Volume 479, 1 October 2017, Pages 467-473
Aquaculture

Use of environmental DNA (eDNA) and water quality data to predict protozoan parasites outbreaks in fish farms

https://doi.org/10.1016/j.aquaculture.2017.06.021Get rights and content

Highlights

  • First known study to associate abundance of ciliate protozoans in water and environmental parameters to predict outbreaks.

  • Environmental DNA and qPCR can be used to pre-empt the likelihood of mortalities, particularly during early life stages.

  • Abundance of C. hexasticha in ponds predisposed smaller fish to high mortalities, particularly during warm temperatures.

Abstract

Globally, disease accounts for around 40% of lost aquaculture production. Commonly, disease occurs due to an inability of farm managers to accurately quantify disease risk due to the abundance of the pathogenic agent in their production systems, along with a poor understanding of how outbreaks are linked to changes in water quality parameters. Environmental DNA (eDNA) sampling methodology associated with molecular techniques is suited to rapidly assess the background presence of pathogens in fish farms, thereby providing managers with critical information that can be used to mitigate disease threats. Adopting the ciliate protozoan Chilodonella hexasticha as a model, this study examined the relationship between environmental DNA of C. hexasticha, critical water parameters and the occurrence of disease outbreaks on a commercial barramundi Lates calcarifer farm, where water was sampled monthly over a 1 year timeframe. A qPCR assay based on the small subunit ribosomal DNA gene was used to monitor the abundance of C. hexasticha in pond water (SSU-rDNA copies/μL). Increased C. hexasticha eDNA levels were found to be highly correlated with occurrence of later fish mortality events (r = 0.402; P < 0.001) and also with size of fish (r =  0.189; P < 0.05); smaller fish were more prone to being impacted by an epizootic of the parasite. However, no correlations were found between any of the water quality parameters measured (rainfall, water temperature and dissolved oxygen) and abundance of this parasite, although there were significantly more fish mortalities observed during the warmer, wetter monsoonal season compared to the cooler, dry season (1280 vs. 135 mortalities, respectively; P < 0.05). This study highlights the potential of an eDNA approach as a management tool to quickly assess parasite loads in water and minimise the risk of disease outbreaks in aquaculture systems.

Introduction

Food security is predicted to be a global challenge as the human population reaches nine billion people (FAO, 2014). Aquaculture, which is currently the fastest growing agribusiness, will be a major supplier of future animal protein requirements for this expanding population (FAO, 2016). However, disease currently results in approximately 40% of lost production potential (~ USD$102 billion), from direct (e.g. mortalities) and indirect (e.g. additions of chemicals, waste of feed) factors (FAO, 2012). Consequently, early disease detection and management is critically important for future food production from aquatic farm environments.

Environmental DNA, also known as eDNA, is a novel front-line molecular tool that has the potential to change the way detection and monitoring of disease occurs in aquaculture (Bass et al., 2015). The technique enables non-invasive sampling and detection based purely on the collection of water samples when there is no visible presence of the target organism (Robson et al., 2016). The eDNA approach was first applied by Ogram et al. (1987) to understand microbial communities in sediments. However, it was not until Ficetola et al. (2008), who used eDNA on the American bullfrog, Rana catesbeiana, as a model for invasive species studies, that this technique started to grow in popularity as a tool to detect biodiversity in aquatic systems. Due to its detection power and relative ease application, environmental DNA has now been applied to address questions related to microbial community diversity, evolution, ecology and even interactions between hosts and pathogens (Goldberg et al., 2015, Taberlet et al., 2012, Bass et al., 2015).

Environmental DNA methodologies offer potential to improve animal health monitoring systems in aquaculture, as many pathogens are microscopic, have waterborne life-stages, are hard to directly detect, and clinical signs of diseases are often only observed in advanced stages of infection where subsequent treatment options become ineffective (Bass et al., 2015). Traditional diagnostics, such as histopathology and morphological identification, are time consuming and often lack detection sensitivity unless large numbers of samples from animals are processed, or only detect the presence of a parasite on the species under culture once a widespread epizootic outbreak is in progress (Adrian-Kalchhauser and Burkhardt-Holm, 2016, Bastos Gomes et al., 2016). Through monitoring levels of parasites in water, however, eDNA methodologies may offer a simple early detection and disease risk assessment technique before animals became clinically symptomatic, merely through the sampling of water from ponds or the surrounding aquatic ecosystem. Furthermore, coupling routine eDNA sampling, quantitative PCR (qPCR), fish production data and environmental water parameters may lead to new understandings of the key environmental drivers of disease outbreaks and quantitative prediction of the likelihood of fish mortalities.

Ciliate protozoans are considered among the most economically important parasites for finfish aquaculture (Lom and Dyková, 1992, Bastos Gomes et al., 2016), with Chilodonella spp. (Phyllopharyngea:Chilodonellidae) being particularly harmful to farmed freshwater fishes (Padua et al., 2013, Bastos Gomes et al., 2016). The presence of large numbers of Chilodonella cells in water predispose their attachment to fish gills and skin epithelial cells, causing severe pathology (Noga, 2010, Mitra et al., 2013, Padua et al., 2013). Chilodonellosis (disease caused by Chilodonella spp.) progresses rapidly, causing mortalities within two to three days of infection and losses of 50–95% in fish stocks (Paperna and Van As, 1983, Karvonen et al., 2010). Rapid detection of Chilodonella spp. can be challenging as epidemics often occur without warning (Bastos Gomes et al., 2016). The use of eDNA-based technologies offer a novel approach for the early detection of increasing numbers of Chilodonella spp. in water and can alert farmers to implement pre-emptive, rather than reactive management to minimise production losses.

The aim of this study was to demonstrate the applicability of integrating eDNA-based techniques and farm water quality parameters as a management tool for predicting future parasite epizootics in commercial fish farms. Here quantitative real-time PCR (qPCR) was used to determine the presence and abundance of C. hexasticha in aquaculture ponds and relationships between parasite loads in water, environmental conditions and large-scale fish mortality events were examined to highlight how eDNA methodology may help understand environmental drivers of disease outbreaks.

Section snippets

Pond selection and collection of water samples

Water samples were collected from ~ 1.4 ha earthen ponds (~ 20 Megalitres; ML) within a commercial freshwater barramundi, Lates calcarifer (Bloch), farm near Innisfail, north Queensland, Australia, monthly for one year (from October 2013 to September 2014, except March 2014) (Fig. 1). Four ponds were selected for regular sampling which had a history of Chilodonella infections and another four ponds were opportunistically chosen based on the farm's health reports on the presence of stressed fish

Statistical analyses

Linear regression was used to assess the ability of measured variables (i.e. abundance of C. hexasticha (eDNA), rainfall, dissolved oxygen and water temperature and fish weight), to predict fish mortalities observed in the 5 days post water sampling. Furthermore, linear regression was also used to evaluate whether any of the observed environmental variables could predict the abundance of C. hexasticha in the water samples. Preliminary analyses were conducted to ensure no violation of the

Results

Environmental parameter data from eight farm ponds sampled between October 2013 and August 2014 were analysed. Table 2 shows the statistical summary for all environmental parameters tested in this study. Quantification of C. hexasticha in barramundi farm water varied between ponds, sampling sites (within ponds) and from month to month. Although the abundance of C. hexasticha in water samples (SSU-rDNA copies/μL) was extremely variable, the parasite was constantly present in farm water (Fig. 1).

Discussion

Environmental DNA (eDNA) analyses are revolutionising how aquatic biodiversity surveys are conducted and also have an application in the detection of pathogens impacting on aquaculture. In the present study, an eDNA approach was used to quantify the abundance of an important parasitic protozoan that causes chilodonellosis in commercial freshwater finfish aquaculture. We show that eDNA is a powerful approach to detect and quantify levels of C. hexasticha in commercial barramundi aquaculture

Acknowledgments

The author received an Australian postgraduate award from James Cook University. This research was partially funded through the "Integrated management of parasite infections in tropical aquaculture", Smart Futures Grants, Queensland Government.s

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