Sudden peak in tetrodotoxin in French oysters during the summer of 2021: Source investigation using microscopy, metabarcoding and droplet digital PCR.

Tetrodotoxin (TTX) is a potent neurotoxin causing human intoxications from contaminated seafood worldwide and is of emerging concern in Europe. Shellfish have been shown to contain varying TTX concentrations globally, with concentrations typically higher in Pacific oysters Crassostrea gigas in Europe. Despite many decades of research, the source of TTX remains unknown, with bacterial or algal origins having been suggested. The aim of this study was to identify potential source organisms causing TTX contamination in Pacific oysters in French coastal waters, using three different techniques. Oysters were deployed in cages from April to September 2021 in an estuary where TTX was previously detected. Microscopic analyses of water samples were used to investigate potential microalgal blooms present prior or during the peak in TTX. Differences in the bacterial communities from oyster digestive glands (DG) and remaining flesh were explored using metabarcoding, and lastly, droplet digital PCR assays were developed to investigate the presence of Cephalothrix sp., one European TTX-bearing species in the DG of toxic C. gigas. Oysters analysed by liquid chromatography-tandem mass spectrometry contained quantifiable levels of TTX over a three-week period (24 June-15 July 2021), with concentrations decreasing in the DG from 424 µg/kg for the first detection to 101 µg/kg (equivalent to 74 to 17 µg/kg of total flesh), and trace levels being detected until August 13, 2021. These concentrations are the first report of the European TTX guidance levels being exceeded in French shellfish. Microscopy revealed that some microalgae bloomed during the TTX peak, (e.g., Chaetoceros spp., reaching 40,000 cells/L). Prokaryotic metabarcoding showed increases in abundance of Rubritaleaceae (genus Persicirhabdus) and Neolyngbya, before and during the TTX peak. Both phyla have previously been described as possible TTX-producers and should be investigated further. Droplet digital PCR analyses were negative for the targeted TTX-bearing genus Cephalothrix.

Metal concentrations in transitional and coastal waters measured by passive (Diffusive Gradients in Thin-films) and spot sampling: MONITOOL Project Dataset.

The MONITOOL project (2017-2023) was carried out to describe the relationships between total dissolved and labile metal concentrations measured in spot water samples and in concurrently deployed Diffusive Gradients in Thin-films (DGTs) passive samplers, respectively. The ultimate aim was to adapt existing marine metal Environmental Quality Standards (EQS marine water) for DGTs, enabling their use in the context of the European Directives (the Water Framework Directive (WFD) and the Marine Strategy Framework Directive (MSFD)). Time-integrated metal concentrations provided by DGTs, representing several days, are an advantage compared to conventional spot sampling, especially in highly dynamic systems, such as transitional waters. Hence, the MONITOOL project aimed to provide a robust database of dissolved and labile metal concentrations in transitional and coastal waters, based upon co-deployments of DGTs and collection of spot water samples at several sampling sites (England, France, Ireland, Italy, Northern Ireland, Portugal, Scotland and Spain), followed subsequently by DGT and water metal analysis. Samplings were carried out in 2018 and 2022, following agreed protocols developed in the framework of the project. The MONITOOL dataset includes metal concentrations from DGTs, measured with Inductively Coupled Plasma Mass Spectrometry (ICP-MS: Cd, Co, Cu, Fe, Mn, Ni, Pb, Zn) and in concurrently collected spot water samples by ICP-MS (Al, Cd, Co, Cu, Mn, Ni, Pb, Zn) and Anodic/Cathodic Stripping Voltammetry (ASV/CSV: Cd, Pb, Ni). Moreover, data on seawater physical-chemical parameters (salinity, temperature, dissolved oxygen, pH, turbidity, total suspended solids, dissolved organic carbon, and total organic carbon) is provided. This database presents the results obtained using, concurrently, different forms of sampling and analytical techniques, enabling the comparison of the results obtained by these strategies and allowing the adaptation of EQS in marine water (EQS marine water) to DGTs (EQS DGT), in the context of the WFD. Moreover, due to the large number of sampling sites, it could also be used for other types of research, such as those dealing with metal speciation or the determination of baseline levels.

Can shellfish be used to monitor SARS-CoV-2 in the coastal environment?

The emergence and worldwide spread of SARS-CoV-2 raises new concerns and challenges regarding possible environmental contamination by this virus through spillover of human sewage, where it has been detected. The coastal environment, under increasing anthropogenic pressure, is subjected to contamination by a large number of human viruses from sewage, most of them being non-enveloped viruses like norovirus. When reaching coastal waters, they can be bio-accumulated by filter-feeding shellfish species such as oysters. Methods to detect this viral contamination were set up for the detection of non-enveloped enteric viruses, and may need optimization to accommodate enveloped viruses like coronaviruses (CoV). Here, we aimed at assessing methods for the detection of CoV, including SARS-CoV-2, in the coastal environment and testing the possibility that SARS-CoV-2 can contaminate oysters, to monitor the contamination of French shores by SARS-CoV-2 using both seawater and shellfish. Using the porcine epidemic diarrhea virus (PEDV), a CoV, as surrogate for SARS-CoV-2, and Tulane virus, as surrogate for non-enveloped viruses such as norovirus, we assessed and selected methods to detect CoV in seawater and shellfish. Seawater-based methods showed variable and low yields for PEDV. In shellfish, the current norm for norovirus detection was applicable to CoV detection. Both PEDV and heat-inactivated SARS-CoV-2 could contaminate oysters in laboratory settings, with a lower efficiency than a calicivirus used as control. Finally, we applied our methods to seawater and shellfish samples collected from April to August 2020 in France, where we could detect the presence of human norovirus, a marker of human fecal contamination, but not SARS-CoV-2. Together, our results validate methods for the detection of CoV in the coastal environment, including the use of shellfish as sentinels of the microbial quality of their environment, and suggest that SARS-CoV-2 did not contaminate the French shores during the summer season.

SmartCRF: A Prototype to Visualize, Search and Annotate an Electronic Health Record from an i2b2 Clinical Data Warehouse.

Clinical information in electronic health records (EHRs) is mostly unstructured. With the ever-increasing amount of information in patients' EHRs, manual extraction of clinical information for data reuse can be tedious and time-consuming without dedicated tools. In this paper, we present SmartCRF, a prototype to visualize, search and ease the extraction and structuration of information from EHRs stored in an i2b2 data warehouse.

Romedi: An Open Data Source About French Drugs on the Semantic Web.

The W3C project, "Linking Open Drug Data" (LODD), linked several publicly available sources of drug data together. So far, French data, like marketed drugs and their summary of product characteristics, were not integrated and remained difficult to query. In this paper, we present Romedi (Référentiel Ouvert du Médicament), an open dataset that links French data on drugs to international resources. The principles and standard recommendations created by the W3C for sharing information were adopted. Romedi was connected to the Unified Medical Language System and DrugBank, two central resources of the LODD project. A SPARQL endpoint is available to query Romedi and services are provided to annotate textual content with Romedi terms. This paper describes its content, its services, its links to external resources, and expected future developments.