The Adriatic Sea Encyclopedia

Tetrodotoxins (TTXs), potent neurotoxins, have become an increasing concern in Europe in recent decades, especially because of their presence in mollusks. The European Food Safety Authority published a Scientific Opinion setting a recommended threshold for TTX in mollusks of 44 µg equivalent kg−1 and calling all member states to contribute to an effort to gather data in order to produce a more exhaustive risk assessment. The objective of this work was to assess TTX levels in wild and farmed mussels (Mytilus galloprovincialis) harvested in 2018–2019 along the coastal area of the Marche region in the Central Adriatic Sea (Italy). The presence of Vibrio spp. carrying the non-ribosomal peptide synthetase (NRPS) and polyketide synthase (PKS) genes, which are suspected to be involved in TTX biosynthesis, was also investigated. Out of 158 mussel samples analyzed by hydrophilic interaction liquid chromatography coupled with tandem mass spectrometry (HILIC-MS/MS), 11 (7%) contained the toxins at detectable levels (8–26 µg kg−1) and 3 (2%) contained levels above the EFSA safety threshold (61–76 µg kg−1). Contaminated mussels were all harvested from natural beds in spring or summer. Of the 2019 samples, 70% of them contained V. alginolyticus strains with the NRPS and/or PKS genes. None of the strains containing NRPS and/or PKS genes showed detectable levels of TTXs. TTXs in mussels are not yet a threat in the Marche region nor in Europe, but further investigations are surely needed.

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Artificial neural network analysis of microbial diversity in the central and southern Adriatic Sea

Scientific Reports ◽

10.1038/s41598-021-90863-7 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Danijela Šantić ◽

Kasia Piwosz ◽

Frano Matić ◽

Ana Vrdoljak Tomaš ◽

Jasna Arapov ◽

...

Keyword(s):

Neural Network ◽

Network Analysis ◽

Bacterial Community ◽

Microbial Diversity ◽

Community Composition ◽

Adriatic Sea ◽

Bacterial Community Composition ◽

Environmental Data ◽

Large Contribution ◽

Neural Network Analysis

AbstractBacteria are an active and diverse component of pelagic communities. The identification of main factors governing microbial diversity and spatial distribution requires advanced mathematical analyses. Here, the bacterial community composition was analysed, along with a depth profile, in the open Adriatic Sea using amplicon sequencing of bacterial 16S rRNA and the Neural gas algorithm. The performed analysis classified the sample into four best matching units representing heterogenic patterns of the bacterial community composition. The observed parameters were more differentiated by depth than by area, with temperature and identified salinity as important environmental variables. The highest diversity was observed at the deep chlorophyll maximum, while bacterial abundance and production peaked in the upper layers. The most of the identified genera belonged to Proteobacteria, with uncultured AEGEAN-169 and SAR116 lineages being dominant Alphaproteobacteria, and OM60 (NOR5) and SAR86 being dominant Gammaproteobacteria. Marine Synechococcus and Cyanobium-related species were predominant in the shallow layer, while Prochlorococcus MIT 9313 formed a higher portion below 50 m depth. Bacteroidota were represented mostly by uncultured lineages (NS4, NS5 and NS9 marine lineages). In contrast, Actinobacteriota were dominated by a candidatus genus Ca. Actinomarina. A large contribution of Nitrospinae was evident at the deepest investigated layer. Our results document that neural network analysis of environmental data may provide a novel insight into factors affecting picoplankton in the open sea environment.

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Modelling the Quality of Bathing Waters in the Adriatic Sea

Water ◽

10.3390/w13111525 ◽

2021 ◽

Vol 13 (11) ◽

pp. 1525

Author(s):

Christian Ferrarin ◽

Pierluigi Penna ◽

Antonella Penna ◽

Vedrana Spada ◽

Fabio Ricci ◽

...

Keyword(s):

Adriatic Sea ◽

Management Tool ◽

Negative Consequences ◽

Sea Temperature ◽

Bathing Water Directive ◽

Bathing Waters ◽

Diffusion Dynamics ◽

Study Sites

The aim of this study is to develop a relocatable modelling system able to describe the microbial contamination that affects the quality of coastal bathing waters. Pollution events are mainly triggered by urban sewer outflows during massive rainy events, with relevant negative consequences on the marine environment and tourism and related activities of coastal towns. A finite element hydrodynamic model was applied to five study areas in the Adriatic Sea, which differ for urban, oceanographic and morphological conditions. With the help of transport-diffusion and microbial decay modules, the distribution of Escherichia coli was investigated during significant events. The numerical investigation was supported by detailed in situ observational datasets. The model results were evaluated against water level, sea temperature, salinity and E. coli concentrations acquired in situ, demonstrating the capacity of the modelling suite in simulating the circulation in the coastal areas of the Adriatic Sea, as well as several main transport and diffusion dynamics, such as riverine and polluted waters dispersion. Moreover, the results of the simulations were used to perform a comparative analysis among the different study sites, demonstrating that dilution and mixing, mostly induced by the tidal action, had a stronger effect on bacteria reduction with respect to microbial decay. Stratification and estuarine dynamics also play an important role in governing microbial concentration. The modelling suite can be used as a beach management tool for improving protection of public health, as required by the EU Bathing Water Directive.

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