A generic approach for the development of short-term predictions of Escherichia coli and biotoxins in shellfish

Microbiological contamination or elevated marine biotoxin concentrations within shellfish can result in temporary closure of shellfish aquaculture harvesting, leading to financial loss for the aquaculture business and a potential reduction in consumer confidence in shellfish products. We present a method for predicting short-term variations in shellfish concentrations of Escherichia coli and biotoxin (okadaic acid and its derivates dinophysistoxins and pectenotoxins). The approach was evaluated for 2 contrasting shellfish harvesting areas. Through a meta-data analysis and using environmental data in situ, satellite observations and meteorological nowcasts and forecasts), key environmental drivers were identified and used to develop models to predict E. coli and biotoxin concentrations within shellfish. Models were trained and evaluated using independent datasets, and the best models were identified based on the model exhibiting the lowest root mean square error. The best biotoxin model was able to provide 1 wk forecasts with an accuracy of 86%, a 0% false positive rate and a 0% false discovery rate (n = 78 observations) when used to predict the closure of shellfish beds due to biotoxin. The best E. coli models were used to predict the European hygiene classification of the shellfish beds to an accuracy of 99% (n = 107 observations) and 98% (n = 63 observations) for a bay (St Austell Bay) and an estuary (Turnaware Bar), respectively. This generic approach enables high accuracy short-term farm-specific forecasts, based on readily accessible environmental data and observations

Field scale modelling of explosion-generated crack densities in granitic rocks using dual-support smoothed particle hydrodynamics (DS-SPH)

This is the author accepted manuscript. The final version is freely available from Elsevier via the DOI in this record.The need to ensure future food security and issues of varying estuarine water quality is driving the expansion of aquaculture into near-shore coastal waters. It is prudent to fully evaluate new or proposed aquaculture sites, prior to any substantial financial investment in infrastructure and staffing. Measurements of water temperature, salinity and dissolved oxygen can be used to gain insight into the physical, chemical and biological water quality conditions within a farm site, towards identifying its suitability for farming, both for the stock species of interest and for assessing the potential risk from harmful or toxic algae. The latter can cause closure of shellfish harvesting. Unfortunately, commercial scientific monitoring systems can be cost prohibitive for small organisations and companies to purchase and operate. Here we describe the design, construction and deployment of a low cost (<£5,000) monitoring buoy suitable for use within a near-shore aquaculture farm or bathing waters. The mooring includes a suite of sensors designed for supporting and understanding variations in near-shore physical, chemical and biological water quality. The system has been designed so that it can be operated and maintained by non-scientific staff, whilst still providing good quality scientific data. Data collected from two deployments totalling 14 months, one in a coastal bay location, another in an estuary, have illustrated the robust design and provided insight into the suitability of these sites for aquaculture and the potential occurrence of a toxin causing algae (Dinophysis spp.). The instruments maintained good accuracy during the deployments when compared to independent in situ measurements (e.g. RMSE 0.13–0.16 °C, bias 0.03–0.08 °C) enabling stratification and biological features to be identified, along with confirming that the waters were suitable for mussel (Mytilus spp.) and lobster (Homarus gammarus) aquaculture, whilst sites showed conditions agreeable for Dinophysis spp.The authors wish to thank the shellfish farmers (Gary Rawle and Marina Rawle) for their assistance in the deployment, maintenance of the buoy and advice for its design. This work was carried out as part of the UK Biotechnology and Biological Science Research Council (BBRSC) and National Environmental Research Council (NERC) funded ShellEye project (contract number BB/M026698/1)

Early Warning Systems for Shellfish Safety: The Pivotal Role of Computational Science

Toxins from harmful algae and certain food pathogens (Escherichia coli and Norovirus) found in shellfish can cause significant health problems to the public and have a negative impact on the economy. For the most part, these outbreaks cannot be prevented but, with the right technology and know-how, they can be predicted. These Early Warning Systems (EWS) require reliable data from multiple sources: satellite imagery, in situ data and numerical tools. The data is processed and analyzed and a short-term forecast is produced. Computational science is at the heart of any EWS. Current models and forecast systems are becoming increasingly sophisticated as more is known about the dynamics of an outbreak. This paper discusses the need, main components and future challenges of EWS

Comparison of methodologies for the extraction of bacterial DNA from mussels-relevance for food safety

The control of the microbiological quality of bivalve molluscs assumes particular importance because they are among the most produced seafood products and mostly consumed as a whole, raw, or lightly cooked. The composition of the bacterial community associated with bivalves depends mostly on the microbiology of the surrounding environment at growing sites. Once the relationship between microbiology of bivalves and environment is established, a better classification and monitoring of the shellfish beds and evaluation of depuration strategies can be achieved. In this work, we tested if the methods of DNA extraction commonly used for the culture-independent microbiological analysis of sediment and water could be used directly, or with modifications, for the analysis of bacteria in mussels. The commercial kits Genomic DNA Purification Kit (MBI Fermentas, Vilnius, Lithuania), UltraClean(TM) Soil DNA Isolation Kit (MOBIO Laboratories, Inc., Carlsbad, CA) and the method described by Griffiths and collaborators for DNA/RNA co-extraction were compared. The efficiency of extraction was assessed by DNA fluorescence and the denaturing gradient gel electrophoresis gel patterns of 16S ribosomal RNA gene fragments were used to compare the reproducibility and representativeness of the extraction methods. Results showed that the DNA/RNA co-extraction method with modifications was the most suitable. However, the results must be interpreted in the light of the purpose of the study and the relevance of maximizing extraction yield or diversity estimate, without compromising reproducibility. To our knowledge, this was the first attempt to transpose the procedure currently used for DNA extraction from sediments or waters, to the analysis of whole mussels