scholarly journals First Detection of Paralytic Shellfish Toxins from Alexandrium pacificum above the Regulatory Limit in Blue Mussels (Mytilus galloprovincialis) in New South Wales, Australia

2020 ◽  
Vol 8 (6) ◽  
pp. 905
Author(s):  
Abanti Barua ◽  
Penelope A. Ajani ◽  
Rendy Ruvindy ◽  
Hazel Farrell ◽  
Anthony Zammit ◽  
...  
Keyword(s):  
Mytilus Galloprovincialis ◽  
Blue Mussel ◽  
New South ◽  
New South Wales ◽  
Mussel Tissue ◽  
Shellfish Toxins ◽  
Paralytic Shellfish Toxins ◽  
South Wales ◽  
Paralytic Shellfish ◽  
Cell Concentrations

In 2016, 2017 and 2018, elevated levels of the species Alexandrium pacificum were detected within a blue mussel (Mytilus galloprovincialis) aquaculture area at Twofold Bay on the south coast of New South Wales, Australia. In 2016, the bloom persisted for at least eight weeks and maximum cell concentrations of 89,000 cells L−1 of A. pacificum were reported. The identity of A. pacificum was confirmed using molecular genetic tools (qPCR and amplicon sequencing) and complemented by light and scanning electron microscopy of cultured strains. Maximum reported concentrations of paralytic shellfish toxins (PSTs) in mussel tissue was 7.2 mg/kg PST STX equivalent. Elevated cell concentrations of A. pacificum were reported along the adjacent coastal shelf areas, and positive PST results were reported from nearby oyster producing estuaries during 2016. This is the first record of PSTs above the regulatory limit (0.8 mg/kg) in commercial aquaculture in New South Wales since the establishment of routine biotoxin monitoring in 2005. The intensity and duration of the 2016 A. pacificum bloom were unusual given the relatively low abundances of A. pacificum in estuarine and coastal waters of the region found in the prior 10 years.

scholarly journals Combined effects of warming and acidification on accumulation and elimination dynamics of paralytic shellfish toxins in mussels Mytilus galloprovincialis

2018 ◽  
Vol 164 ◽  
pp. 647-654 ◽  
Author(s):  
Ana C. Braga ◽  
Carolina Camacho ◽  
António Marques ◽  
Ana Gago-Martínez ◽  
Mário Pacheco ◽  
...  
Keyword(s):  
Mytilus Galloprovincialis ◽  
Combined Effects ◽  
Shellfish Toxins ◽  
Paralytic Shellfish Toxins ◽  
Paralytic Shellfish

scholarly journals Toxicity and histopathological effects of toxic dinoflagellate, Alexandrium catenella exudates on larvae of blue mussel, Mytilus galloprovincialis, and Pacific oyster, Crassostrea gigas

2020 ◽  
Vol 12 (2) ◽  
pp. 188
Author(s):  
Supono Supono ◽  
Graeme Knowles ◽  
Christopher Bolch
Keyword(s):  
Crassostrea Gigas ◽  
Mytilus Galloprovincialis ◽  
Pacific Oyster ◽  
Blue Mussel ◽  
Larval Mortality ◽  
Larval Rearing ◽  
Toxic Dinoflagellate ◽  
Alexandrium Catenella ◽  
Paralytic Shellfish Toxins ◽  
Paralytic Shellfish

HighlightToxicity and pathological effects of A. catenella were investigated on shellfish larvaeUnfiltered exudates of A. catenella caused significant mortality of blue mussel larvaeApplication of 0.22 mm filtration on A. fundyense exudates potentially decrease the toxicity effectsPathological effects of A. catenella occurred as early as 3 h after exposureThe prevalence and intensity of necrosis increased with exposure duration to A. catenella exudatesAbstractBlooms of the toxic dinoflagellate Alexandrium catenella have affected shellfish industries globally due to their capacity to produce paralytic shellfish toxins(PST). This study aimed to investigate the toxicity effect of exudate A. catenella on larvae of blue mussel Mytilus galloprovincialis and Pacific oyster Crassostrea gigas and filtration methods to reduce the toxic effect. Blue mussel and Pacific oyster larvae were assessed their survival and histopathological changes after exposure to extracellular exudates of A. catenella ranging from 100 to 1,000 cells ml-1 . The results showed that exposure to exudate A. catenella caused significantly higher larval mortality (39 to 52%) than exposure to an equivalent biovolume of the nontoxic species, Tisochrysis lutea (33%) or unfed controls (17%). Filter-sterilization (0.22 µm) of exudates and activated carbon filtration decreased the mortality of Pacific oyster larvae to a level similar to controls (unfed), with the exception of the highest concentrations (600 and 1,000 cells ml-1 ) and mortality of bluemussel larvae mortality by 32% respectively. Blue mussel larvae exposed to exudate A. catenella showed pathological changes mainly in the stomach (digestive gland and style sac) as early as three hours after onset of exposure. The findings of this study suggest that early detection of blooms in the vicinity of mussel and Pacific oyster hatcheries and taking steps to mitigate their effects, is important to reduce the effects of A. catenella blooms on shellfish larval rearing.

scholarly journals Temporal Prediction of Paralytic Shellfish Toxins in the Mussel Mytilus galloprovincialis Using a LSTM Neural Network Model from Environmental Data

Toxins ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 51
Author(s):  
Jisun Shin ◽  
Soo Mee Kim
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Coastal Waters ◽  
Mytilus Galloprovincialis ◽  
Environmental Data ◽  
Temporal Prediction ◽  
Shellfish Toxins ◽  
Paralytic Shellfish Toxins ◽  
Paralytic Shellfish

Paralytic shellfish toxins (PSTs) are produced mainly by Alexandrium catenella (formerly A. tamarense). Since 2000, the National Institute of Fisheries Science (NIFS) has been providing information on PST outbreaks in Korean coastal waters at one- or two-week intervals. However, a daily forecast is essential for immediate responses to PST outbreaks. This study aimed to predict the outbreak timing of PSTs in the mussel Mytilus galloprovincialis in Jinhae Bay and along the Geoje coast in the southern coast of the Korea Peninsula. We used a long-short-term memory (LSTM) neural network model for temporal prediction of PST outbreaks from environmental data, such as water temperature (WT), tidal height, and salinity, measured at the Geojedo, Gadeokdo, and Masan tidal stations from 2006 to 2020. We found that PST outbreaks is gradually accelerated during the three years from 2018 to 2020. Because the in-situ environmental measurements had many missing data throughout the time span, we applied LSTM for gap-filling of the environmental measurements. We trained and tested the LSTM models with different combinations of environmental factors and the ground truth timing data of PST outbreaks for 5479 days as input and output. The LSTM model trained from only WT had the highest accuracy (0.9) and lowest false-alarm rate. The LSTM-based temporal prediction model may be useful as a monitoring system of PSP outbreaks in the coastal waters of southern Korean.

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