Agronomy and biodiversity shall address several major societal, economical, and environmental challenges. However, data are being produced in such big volume and at such high pace, it questions our ability to transform them into knowledge and enable, for instance, translational agriculture i.e., rapidly and efficiently transferring results from agronomy research into the farms (“bench to farmside”). Semantic interoperability enables data integration and fosters new scientific discoveries by exploiting various data acquired from different perspectives and domains. D2KAB’s primary objective is to create a framework to turn agronomy and biodiversity data into –semantically described, interoperable, actionable, open– knowledge, along with investigating scientific methods and tools to exploit this knowledge for applications in science and agriculture. We will adopt an interdisciplinary semantic data science approach that will provide the means –ontologies and linked open data– to produce and exploit FAIR (Findable, Accessible, Interoperable, and Re-usable) data. To do so, we will develop original approaches and algorithms to address the specificities of our domain of interests, but also rely on existing tools and methods. D2KAB involves a multidisciplinary (and international) research consortium of three computer science labs (UM-LIRMM, CNRS-I3S, STANFORD-BMIR), four bioinformatics, biology, agronomy and agriculture labs (INRA-URGI, INRA-MaIAGE, INRA-IATE, IRSTEA-TSCF), two ecology and ecosystems labs (CNRS-CEFE, INRA-URFM), one scientific & technical information unit (INRA-DIST), and one association of agriculture stakeholders (ACTA). The consortium’s expertise ranges from ontologies and metadata, semantic Web, linked data, ontology alignment, knowledge reasoning and extraction, natural language processing to bioinformatics, agronomy, food science, ecosystems, biodiversity and agriculture. The project is structured with three work-packages of research and development in informatics and two work-packages of driving scenarios. WP1 will focus on ontologies/ vocabularies and turn the AgroPortal prototype into a reference platform that addresses the community needs and reaches a high level of quality regarding both content and services offered e.g., SKOS compliance, semantic search over linked data, text annotation, interoperability with other repositories. WP2 will focus on the critical issue of ontology alignment and develop new functionalities and state-of-the-art algorithms in AgroPortal using background knowledge methods validated in ag & biodiv. WP3 will design the methods and tools to reconcile the scenarios' heterogeneous ag & biodiv data sources and turn them into linked data within D2KAB distributed knowledge graph. It will also investigate exploitation of this graph through novel visualization, navigation and search methods. WP4 includes four interdisciplinary research driving scenarios implementing translational agriculture. For instances, an ontology-driven decision support system to select the most appropriate food packaging or an augmented semantic reader for Plant Health Bulletins. We will provide a unique scientific knowledge base for wheat phenotypes and offer the first agricultural data resource empowered by linked open data. WP5 will develop semantic resources for the annotation of ecosystem experiments data and functional biogeography observations. A plant trait-environment-relationships study will be conducted to understand the impacts of climatic changes on vegetation of the Mediterranean Basin. Within a dedicated work-package, we will focus on maximizing the impact of our research. Each of the project driving scenarios will produce concrete outcomes for ag & biodiv scientific communities and stakeholders in agriculture. We have planned multiple dissemination actions and events where we will use our driving scenarios as demonstrators of the potential of semantic technologies in agronomy and biodiversity.

The spread and persistence of infectious diseases in livestock have adverse consequences for public health and animal health and welfare. Animal movements contribute to the (re-)introduction of infections in disease-free herds and regions. Our project addresses scientific issues to provide, through an integrative approach, knowledge and novel methodological tools to more effectively control infectious cattle diseases preferentially spreading through trade. We will analyse the dynamical networks representing datasets of cattle trade movements in France over several years and will provide relevant statistical and mechanistic models describing and predicting their temporal evolution. We will build and analyse multi-scale models coupling, at a regional scale, within-herd infection dynamics, mainly through the network of cattle commercial exchanges, and integrating control interventions and behaviours of farmers with respect to animal trade and implementation of control measures. This approach will be applied to the study of the effectiveness of control measures against four major and contrasted cattle infectious diseases (foot-and-mouth disease, bovine tuberculosis, bovine viral diarrhoea and paratuberculosis). We will thus attempt to build a general view of cattle infections spreading at large scale through animal trade and to assess the effectiveness of control strategies, for an integrated and sustainable management of animal health.

As the first available prebiotics for neonates, milk oligosaccharides regulate gut microbial composition and modulate host immune response, playing a crucial role in the holobiont assembly. By using two livestock models (pigs and rabbits) with different maturity levels at birth, HoloOLIGO aims to decipher causal links between milk oligosaccharidesstructures, the offspring microbiota and immune system. We will create a database using data mining of the literature to find, visualise and analyse milk oligosaccharidesstructure diversity patterns within and between mammalian species. We will produce the first MO data in rabbits and expand them in pigs. To understand structure importance of milk oligosaccharides, we will undertake in vitro functional analyses in both species on commensal bacterial strains and intestinal immune cells and further validate results in vivo. Finally, we will evaluate, via in silico analyses (pig) and in vivo (rabbit), the existing genetic variability and assess the genetic determinism of milk oligosaccharidescomposition.

The importance of heterogeneous shedding patterns in the context of infectious diseases is now well documented and recognized. The infected individuals that harbour and shed a given pathogen at higher concentrations than their congeners are often referred to as super-shedder, by opposite to low-shedder individuals. These super-shedders have a much higher transmission rate and thus constitute a key target for epidemiological investigation and management of diseases such as salmonellosis for which poultry constitute the major source of human contamination. However, the conditions that favour their super-shedding phenotype are poorly understood but are a prerequisite to control the reservoir of contamination within a population. As the emergence of the super- and low-shedder phenotypes are determined by the gut microbiota present before infection, and have been observed in various animal species reared in distinct environments and in strikingly diverse gut microbiota compositions, we hypothesized that while different bacterial taxa may lead to similar outcomes in terms of heterogeneous shedding, potential functional and taxonomic commonalities in the intestine should lead to these phenotypes. Thus, based on preliminary data obtained in chicken, heterogeneous shedding appears to depend on a combination of (1) specific gut microbiota features (2) mucosal immune responses parameters (3) a complex metabolites-driven dialogue between host, pathogen and microbiota and (4) several stochastic effects, including the pace and success of the gut colonization by environmental micro-organisms. In contrast, we have shown that host genetics and modification of bacterial virulence do not play a major role. In this project, we will study the causes of the Salmonella Enteritidis heterogeneous shedding in chicken. Based on different conditions known to favour one of these phenotypes by modifying the gut microbiota composition, we will compare the specific gut microbiota features, the mucosal and systemic immune response parameters and the complex metabolites-driven dialog in the intestine. The MOSSAIC project, organized in six tasks, has three main objectives: To provide a deeper and more integrated understanding of the heterogeneous shedding phenomenon; To model the interactions of the partners of the biological “ménage à trois”: Salmonella-host immune response-gut microbiota, taking into account their metabolites; To confirm by using several in vitro and in vivo experiments some hypotheses suggested by the data analyses and mathematical models. The feasibility of our project is based on an original model of infection in isolator, which allow us to clearly identify the super- and low-shedder phenotypes by controlling animal cross contaminations. Moreover, the MOSSAIC project brings together 5 partners with complementary expertise required to carry out the work program: bacteriology, animal infection, avian immunology and metabolism, metabolomics, bioinformatics and modelling. In a long-term perspective, the knowledge gained during the project will serve as a basis for the development of bacterial communities, which could be fed to chicks to standardize their gut microbiota and increase their resistance to pathogens in poultry production sector.

Non-coding pervasive transcription initiating from cryptic signals or resulting from terminator read-through is widespread in all organisms. Its biological role is well-established in eukaryotes, but poorly understood in bacteria. Two major mechanisms control bacterial pervasive transcription: transcription termination by Rho and RNA degradation by RNases. Our recent data suggest a connection between these two pathways. The multidisciplinary project CoNoCo aims to define the mutual contributions of Rho and RNase III in the control of pervasive transcription in the Gram-positive model bacteria Bacillus subtilis and Staphyloccoccus aureus. It will also establish the roles of the non-coding transcriptome in bacterial cell biology highlighted by recent discoveries of Rho-mediated regulation of B. subtilis cell differentiation and the involvement of the double-strand specific RNase III in gene regulation by small non-coding RNAs.