Background: Descriptive metadata are vital for reporting, discovering, leveraging, and mobilizing research datasets. However, resolving metadata issues as part of a data management plan can be complex for data producers. To organize and document data, various descriptive metadata must be created. Furthermore, when sharing data, it is important to ensure metadata interoperability in line with FAIR (Findable, Accessible, Interoperable, Reusable) principles. Given the practical nature of these challenges, there is a need for management tools that can assist data managers effectively. Additionally, these tools should meet the needs of data producers and be user-friendly, requiring minimal training. Results: We developed Maggot (Metadata Aggregation on Data Storage), a web-based tool to locally manage a data catalog using high-level metadata. The main goal was to facilitate easy data dissemination and deposition in data repositories. With Maggot, users can easily generate and attach high-level metadata to datasets, allowing for seamless sharing in a collaborative environment. This approach aligns with many data management plans as it effectively addresses challenges related to data organization, documentation, storage, and the sharing of metadata based on FAIR principles within and beyond the collaborative group. Furthermore, Maggot enables metadata crosswalks (i.e., generated metadata can be converted to the schema used by a specific data repository or be exported using a format suitable for data collection by third-party applications). Conclusion: The primary purpose of Maggot is to streamline the collection of high-level metadata using carefully chosen schemas and standards. Additionally, it simplifies data accessibility via metadata, typically a requirement for publicly funded projects. As a result, Maggot can be utilized to promote effective local management with the goal of facilitating data sharing while adhering to the FAIR principles. Furthermore, it can contribute to the preparation of the future EOSC FAIR Web of Data within the European Open Science Cloud framework.

Laminarans are of interest because they have been shown to induce various immune responses in animals and plants. These β-D-glucans differ from each other by their branching rate, which is possibly responsible for their biological activities. In the present study, we characterized a laminaran fraction extracted from Laminaria hyperborea and named LAM2 using sugar composition and structural analyses (NMR). Then, we evaluated its activity as a potential plant elicitor in vitro on tomato seedlings using gene expression analysis and cell wall immunofluorescence labeling. Our study showed that LAM2 isolated from L. hyperborea is a succinylated laminaran which significantly enhanced the plant defense of tomato seedlings and induced cell wall modifications, suggesting a higher elicitor activity than the laminaran standard extracted from Laminaria digitata.

There is a growing demand for molecules of natural origin for biocontrol and biostimulation, given the current trend away from synthetic chemical products. Leachates extracted from plantain stems were obtained after biodegradation of the plant material. To characterize the leachate, quantitative determinations of nitrogen, carbon, phosphorus, and cations (K⁺, Ca²⁺, Mg²⁺, Na⁺), Q2/4, Q2/6, and Q4/6 absorbance ratios, and metabolomic analysis were carried out. The potential role of plantain leachates as fungicide, elicitor of plant defense, and/or plant biostimulant was evaluated by agar well diffusion method, phenotypic, molecular, and imaging approaches. The plant extracts induced a slight inhibition of fungal growth of an aggressive strain of Colletotrichum gloeosporioides, which causes anthracnose. Organic compounds such as cinnamic, ellagic, quinic, and fulvic acids and indole alkaloid such as ellipticine, along with some minerals such as potassium, calcium, and phosphorus, may be responsible for the inhibition of fungal growth. In addition, jasmonic, benzoic, and salicylic acids, which are known to play a role in plant defense and as biostimulants in tomato, were detected in leachate extract. Indeed, foliar application of banana leachate induced overexpression of LOXD, PPOD, and Worky70-80 genes, which are involved in phenylpropanoid metabolism, jasmonic acid biosynthesis, and salicylic acid metabolism, respectively. Leachate also activated root growth in tomato seedlings. However, the main impact of the leachate was observed on mature plants, where it caused a reduction in leaf area and fresh weight, the remodeling of stem cell wall glycopolymers, and an increase in the expression of proline dehydrogenase.

Summary: Plant ecological and evolutionary strategies are shaped by interactions between phylogenetic history and environmental constraints, resulting in leaf and stomatal traits. However, traditional trait-based and phylogenetic approaches often fail to fully explain biochemical mechanisms underlying ecological strategies, particularly for leaf and stomatal traits. Plant metabolomes integrate genetic, physiological, and environmental information and therefore represent a promising intermediate phenotype for investigating links between biochemical diversity, functional traits, and evolutionary patterns. We analysed metabolomic profiles from 74 plant species with various growth forms and ecological types. Using machine learning approaches, we explored whether metabolic variation could predict plant functional divisions, growth forms and phenological types, but also physiological traits related to drought resistance. Metabolomic data contained structured information associated with variation in plant functional traits, ecological strategies, and phylogenetic relationships. Machine learning models identified with high accuracy distinct metabolic signatures linked to differences among plant functional divisions, growth forms, phenology, and trait values. Our study demonstrates that predictive metabolomics provides a powerful and integrative framework to investigate plant ecological and evolutionary strategies. By linking biochemical diversity with plant phylogeny, and ecophysiological traits across multiple species, this approach offers new opportunities to explore the mechanistic basis of plant evolution.

Background: Descriptive metadata are crucial for the discovery, reporting and mobilisation of research datasets. Addressing all metadata issues within the Data Management Plan often poses challenges for data producers. Organising and documenting data within data storage entails creating various descriptive metadata. Subsequently, data sharing involves ensuring metadata interoperability in alignment with FAIR principles. Given the tangible nature of these challenges, a real need for management tools has to be addressed to assist data managers to the fullest extent. Moreover, these tools have to meet data producers requirements and be user-friendly as well with minimal training as prerequisites. Results: We developed Maggot which stands for Metadata Aggregation on Data Storage, specifically designed to annotate datasets by generating metadata files to be linked into storage spaces. Maggot enables users to seamlessly generate and attach comprehensible metadata to datasets within a collaborative environment. This approach seamlessly integrates into a data management plan, effectively tackling challenges related to data organisation, documentation, storage, and frictionless FAIR metadata sharing within the collaborative group and beyond. Furthermore, for enabling metadata crosswalk, metadata generated with Maggot can be converted for a specific data repository or configured to be exported into a suitable format for data harvesting by third-party applications. Conclusion: The primary feature of Maggot is to ease metadata capture based on a carefully selected schema and standards. Then, it greatly eases access to data through metadata as requested nowadays in projects funded by public institutions and entities such as Europe Commission. Thus, Maggot can be used on one hand to promote good local versus global data management with open data sharing in mind while respecting FAIR principles, and on the other hand to prepare the future EOSC FAIR Web of Data within the framework of the European Open Science Cloud.