An On-Farm Workflow for Predictive Management of Paralytic Shellfish Toxin-Producing Harmful Algal Blooms for the Aquaculture Industry.

Paralytic shellfish toxins (PSTs) produced by marine dinoflagellates significantly impact shellfish industries worldwide. Early detection on-farm and with minimal training would allow additional time for management decisions to minimize economic losses. Here, we describe and test a standardized workflow based on the detection of sxtA4, an initial gene in the biosynthesis of PSTs. The workflow is simple and inexpensive and does not require a specialized laboratory. It consists of (1) water collection and filtration using a custom gravity sampler, (2) buffer selection for sample preservation and cell lysis for DNA, and (3) an assay based on a region of sxtA, DinoDtec lyophilized quantitative polymerase chain reaction (qPCR) assay. Water samples spiked with Alexandrium catenella showed a cell recovery of >90% when compared to light microscopy counts. The performance of the lysis method (90.3% efficient), Longmire's buffer, and the DinoDtec qPCR assay (tested across a range of Alexandrium species (90.7-106.9% efficiency; r2 > 0.99)) was found to be specific, sensitive, and efficient. We tested the application of this workflow weekly from May 2016 to 30th October 2017 to compare the relationship between sxtA4 copies L-1 in seawater and PSTs in mussel tissue (Mytilus galloprovincialis) on-farm and spatially (across multiple sites), effectively demonstrating an ∼2 week early warning of two A. catenella HABs (r = 0.95). Our tool provides an early, accurate, and efficient method for the identification of PST risk in shellfish aquaculture.

Mapping the development of a Dinophysis bloom in a shellfish aquaculture area using a novel molecular qPCR assay.

Diarrhetic shellfish toxins produced by certain species of the marine dinoflagellate Dinophysis can accumulate in shellfish in high concentrations, representing a significant food safety issue worldwide. This risk is routinely managed by monitoring programs in shellfish producing areas, however the methods used to detect these harmful marine microbes are not usually automated nor conducted onsite, and are often expensive and require specialized expertise. Here we designed a quantitative real-time polymerase chain reaction (qPCR) assay based on the ITS-5.8S ribosomal region of Dinophysis spp. and evaluated its specificity, efficiency, and sensitivity to detect species belonging to this genus. We designed and tested twenty sets of primers pairs using three species of Dinophysis - D. caudata, D. fortii and D. acuminata. We optimized a qPCR assay using the primer pair that sufficiently amplified each of the target species (Dacu_11F/Dacu_11R), and tested this assay for cross-reactivity with other dinoflagellates and diatoms in the laboratory (11 species) and in silico 8 species (15 strains) of Dinophysis, 3 species of Ornithocercus and 2 species of Phalacroma. The qPCR assay returned efficiencies of 92.4% for D. caudata, 91.3% for D fortii, and 91.5% for D. acuminata, while showing no cross-reactivity with other phytoplankton taxa. Finally, we applied this assay to a D. acuminata bloom which occurred in an oyster producing estuary in south eastern Australia, and compared cell numbers inferred by qPCR to those determined by microscopy counts (max abund. ∼6.3 × 103 and 5.3 × 103 cells L-1 respectively). Novel molecular tools such as qPCR have the potential to be used on-farm, be automated, and provide an early warning for the management of harmful algal blooms.