Key Expoitable Results (KERs)

Microfluidic technology can expedite nucleic acid testing by converting the functions of bulky laboratory instruments and protracted bench methodologies into easy-to-use and inexpensive miniaturised systems without compromising speed and reliability. We developed a lab-on-a-chip (LOC) platform that integrates a dimethyl adipimidate (DMA)-based functionalised silica DNA isolation and pre-concentration method with a rapid and real-time loop-mediated isothermal amplification (LAMP) for detecting domoic acid-producing phytoplankton, Pseudo-nitzschia. An optimised design of a lab on a chip extraction module achieved a maximum DNA capture capacity of 61.73 ± 0.98 ng μL−1. The DMA-based method reduced reagent costs per sample by 97% compared to a commercial nucleic acid isolation kit. A subsequent on-chip LAMP process was capable of sensitively quantifying cytochrome P450 homologous to the dabD gene, coding for a component of the domoic acid toxin production pathway, with a limit-of-detection of 10 cells per mL. LAMP-based detection of the target gene was achieved using dry-preserved reagents with a shelf-life of five months without refrigeration. There was no significant difference in assay performance between the preserved LAMP and freshly prepared LAMP mixtures. The total analysis time at the LOD of 10 cells per mL, from sample to result, was achieved within one hour. Our results demonstrate the long-term stability of assay reagents, rapid turnaround, and cost-effectiveness, offering a simple and economical approach to environmental monitoring and environmental bio-hazard diagnostics.

The present deliverable (D4.4) reports on AtlantECO’s Handbook of Standards and Best Practices. It was developed throughout the project, and its content is presented in three deliverables (D4.1, D4.2 & D4.4), which are all publicly accessible under a single DOI (https://doi.org/10.5281/zenodo.4897860) and also available via UNESCO’s Ocean Best Practices. AtlantECO generated new observations as part of the project’s sampling activities in synergy with other European and International projects (see deliverable D4.7). The Handbook provides a set of Standard Operating Procedures (SOPs) for methodologies used across these activities to study the Ocean microbiome. These SOPs also constitute a basis for comparing protocols and aggregating results from different observation programmes. The SOPs are generic and describe key methodological concepts, materials and procedural steps, which gives the different observation programmes enough flexibility to adopt the standards and best practices and adapt the SOPs to their specific context.

Thesis

Understanding the complexity of food webs is crucial for assessing ecosystem dynamics. However, the high number of trophic interactions in typical food webs complicates the identification of clear top-down or bottom-up regulatory effects. In this study, we applied interaction asymmetry analysis to examine causality within food webs, allowing for the identification of critical interactions based on topological importance (TI) metrics, which incorporate indirect interactions. We evaluated this method using 34 food web models from the Ecobase database and compared its performance with widely used network metrics. By constructing asymmetry graphs, we transformed original, undirected binary food webs into directed networks highlighting strong causal interactions. Pairwise correlation analyses revealed that ecosystems with higher total biomass indicated stronger bottom-up causal links and greater consumer diversity. Our findings suggest that asymmetry-based metrics provide robust quantitative indicators of causality, offering a straightforward yet powerful tool for assessing ecosystem functioning and health.

As the volume of accessible marine pelagic observations increases exponentially, incorporating diverse data types such as metagenomics and quantitative imaging, the need for standardized modelling frameworks becomes critical to predict biogeographic patterns in space and time and across the diverse range of emergent sampling methods. In response, we introduce CEPHALOPOD (Comprehensive Ensemble Pipeline for Habitat modelling Across Large-scale Ocean Pelagic Observation Datasets), a standardized, highly automated and flexible framework designed to integrate and analyse heterogeneous marine data for multi-species habitat modelling following best practices in the field. CEPHALOPOD is built on observational data from federating initiatives such as AtlantECO, OBIS, GBIF, associated with already existing statistical and machine learning methods that enable to extract and model information from heterogeneous, scarce and biased field observations. It is highly automated and follows explicit quality checks informing the user of the predictive accuracy and interpretability of the results. Here, we document our statistical ensemble modelling approach and then assess its strengths and limitations with a virtual ecologist approach. We show how our framework performs in reproducing a range of distributions from biased field samples. Our modelling framework serves as a foundation for the consistent generation of Essential Biodiversity and Ocean Variables (EBVs and EOVs) and carries the potential to significantly advance our comprehension of biodiversity and marine ecosystem functioning. Finally, it provides an unprecedented opportunity to foster collaborations in the field of marine science, sustainable ecological practices, and ultimately contribute to the preservation of global marine biodiversity.

Understanding the drivers and consequences of horizontal gene transfer (HGT) is a key goal of microbial evolution research. Although co-occurring taxa have long been appreciated to undergo HGT more often, this association is confounded with other factors, most notably their phylogenetic relatedness. To disentangle these factors, we analyzed 15 339 marine prokaryotic genomes (mainly bacteria) and their distribution in the global ocean. We identified HGT events across these genomes and enrichments for functions previously shown to be prone to HGT. By mapping metagenomic reads from 1862 ocean samples to these genomes, we also identified co-occurrence patterns and environmental associations. Although we observed an expected negative association between HGT rates and phylogenetic distance, we only detected an association between co-occurrence and phylogenetic distance for closely related taxa. This observation refines the previously reported trend to closely related taxa, rather than a consistent pattern across all taxonomic levels, at least here within marine environments. In addition, we identified a significant association between co-occurrence and HGT, which remains even after controlling for phylogenetic distance and measured environmental variables. In a subset of samples with extended environmental data, we identified higher HGT levels associated with particle-attached prokaryotes and associations of varying directions with specific environmental variables, such as chlorophyll a and photosynthetically available radiation. Overall, our findings demonstrate the significant influence of ecological associations in shaping marine prokaryotic evolution through HGT.

Particles sinking from the surface to the deep ocean play a key role in the biological carbon pump, whose efficiency depends partly on sinking velocities. Over the last decade, in situ imaging has enabled critical advances in our understanding of particle dynamics in the ocean. Yet, in situ velocity measurements are scarce and often inferred only from the bulk population of particles. Here, we introduce the VisuTrap, a new tool to measure in situ velocities of marine particles. It consists of an Underwater Vision Profiler 6 (UVP6) camera inserted into different types of sediment traps, which isolate a volume of water. Continuous image acquisition during shortterm or long-term deployments enables reconstruction of particle tracks and estimation of their in situ vertical velocities. We detail the configuration and special UVP6 settings for this application, as well as the image processing and track analysis pipeline. Then, we present results from several experiments in the Mediterranean Sea to illustrate the VisuTrap's use as a new approach to understand the dynamical behavior of marine particles in situ. In light of the broad range of morphological data generated by the UVP6, we discuss technical additions to refine in situ velocity measurements and the possibility of integrating such data into carbon flux assessments.

The ENA Data Hubs Portal provides an interface for the data hubs at ENA, which are workspaces and sets of tools that enable users to share, analyse, visualize, search, and retrieve their sequence data. The data hubs are built on top of ENA infrastructure, utilising the same storage, data, and metadata models. A key feature is the ability for a group of users to collaborate on data, sharing it amongst themselves initially whilst preparing their scholarly publication and coincident public data release (in line with ENA’s data release policy). This differs from ENA’s more-personalized Webin accounts for users. Overall, this supports collaborative researchers and groups to better structure, manage, and prepare their data prior to publication. The portal now supports applications beyond infectious disease, and automated data hub setup and management.

The AtlantECO GeoNode is based on the open-source GeoNode project, a geospatial content management system (CMS) and a spatial data infrastructure (SDI) platform designed to enable sharing and collaboration of geospatial data and maps. The project aims to promote the use of geospatial data and make it more accessible to people all over the world. It does this by building on state-of-the-art, open-source geospatial web technologies and standards, supported by the Open Source Geospatial Foundation (OSGEO) and the Open Geospatial Consortium (OGC). As such, it can be customized to meet the needs of the AtlantECO project. The AtlantECO GeoNode was launched on April 2022 and is available at https://atlanteco-geonode.eu/. The web platform was customized to match the look and feel of the AtlantECO project website4. After some tests with the AtlantECO maps NetCDF files, data population of the AtlantECO GeoNode has kicked off in the spring of 2023 and will continue throughout the lifetime of the project, as new versions and datasets become available. The AtlantECO GeoNode aims to promote the research outputs of the project by: ● Providing a web platform that allows to search for, visualise, download and share the AtlantECO MAPSboth within the project as well as to other stakeholders. ● Providing standard OGC web services that allow to search for, visualise and download AtlantECO MAPS within common Geospatial Information System (GIS) tools (e.g. QGIS, ArcGIS) as well as scripting languages (e.g. R, Python) ● Enabling wider dissemination of AtlantECO MAPS by inclusion in other web map projects like the European Atlas of the Seas5 that support the OGC standards.