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Regulatory mechanisms of ER body formation and its function in Brassicaceae plants
No full textInternational audienceEndoplasmic reticulum (ER) bodies are unique ER subdomains with a spindle-shaped structure in Brassicaceae, Cleomaceae, and Capparaceae plants, and they accumulate high levels of β-glucosidases (BGLUs). ER body-localized BGLUs are crucial for the hydrolysis of glucosinolates that are responsible for the chemical defense. In Arabidopsis thaliana, ER body-deficient mutants are vulnerable to non-herbivorous arthropods and non-pathogenic fungi, and display altered root microbiota assembly. ER bodies are predominantly observed in seedlings and roots, as well as in the epidermal cells above leaf midveins and margins. ARABIDOPSIS THALIANA MERISTEM LAYER1 (ATML1) transcription factor controls ER body accumulation in leaves through the activation of the NAI1 transcription factor, which upregulates the expression of ER body-related genes. ER bodies are further induced by wounding, indicating that their accumulation is also controlled in response to environmental signals. Jasmonate plays a key role in regulating ER body induction through CORONATINE INSENSITIVE1 (COI1), and the transcription factors MYC2, MYC3, and MYC4, which further control the expression of MYB47 and MYB95, key regulators of ER body-related genes. The conservation of orthologous and paralogous genes among ER body-related genes is observed in Brassicaceae plant genomes, indicating the conservation of ER body accumulation mechanisms among Brassicaceae species
Comparison of different strategies based on β-casein dynamics to encapsulate curcumin in casein micelles
No full textInternational audienceCasein micelles (CM) are colloidal phospho-protein-mineral complexes naturally present in milk. Cooling inducesβ-casein dissociation from CM. The aim of the present research is to improve curcumin encapsulation in β-casein depleted CM. This study proposes an extraction and separation process including cooling, low acidification (pH 5.8) and membrane filtration at a pilot scale allowing a removal of 45 ±5 % of β-casein fraction from CM.Special care was taken to preserve the CM integrity. Investigation of the depleted CM topography by atomic force microscopy (AFM) reveals a swelling of the micellar structure with a mean width of 193 ±10 nm and a mean height of 80 ±5 nm. Concurrently, exploration of the elastic properties displays a stiffer nanomechanicalsignature compared to native CM, with a mean elasticity modulus of 195 ±17 kPa. The β-caseins extracted from CM were bound to curcumin prior to their encapsulation in depleted CM. This new encapsulation strategy was compared to two other methods, and the results show that it significantly increases the binding efficiency of curcumin to CM
Digging deeper: deep joint species distribution modeling reveals environmental drivers of Earthworm Communities
No full textInternational audienceEarthworms are key drivers of soil function, influencing organic matter turnover, nutrient cycling, and soil structure. Understanding the environmental controls on their distribution is essential for predicting the impacts of land use and climate change on soil ecosystems. While local studies have identified abiotic drivers of earthworm communities, broad-scale spatial patterns remain underexplored. We developed a multi-species, multi-task deep learning model to jointly predict the distribution of 77 earthworm species across metropolitan France, using historical (1960–1970) and contemporary (1990–2020) records. The model integrates climate, soil, and land cover variables to estimate habitat suitability. We applied SHapley Additive exPlanations (SHAP) to identify key environmental drivers and used species clustering to reveal ecological response groups. The joint model achieved high predictive performance (TSS >0.7) and improved predictions for rare species compared to traditional species distribution models. Shared feature extraction across species allowed for more robust identification of common and contrasting environmental responses. Precipitation variability, temperature seasonality, and land cover emerged as dominant predictors of earthworm distribution but differed in ranking across species and functional groups. Species clustering into response groups to climatic, land use and soil revealed distinct ecological strategies including a gradient of sensitivity to precipitation seasonality, differential habitat preferences in terms of vegetation cover and wetness and trade-offs between soil acidity and organic matter quality. Our study advances both the methodological and ecological understanding of soil biodiversity. We demonstrate the utility of interpretable deep learning approaches for large-scale soil fauna modeling and provide new insights into earthworm habitat specialization. These findings highlight land cover and seasonal climate variability as efficient proxies for soil biodiversity, providing actionable indicators for global monitoring initiatives and helping to identify habitat requirements of earthworm species to guide emerging earthworm conservation strategies in the face of global environmental change
A narrative review of the impact of anthropogenic light and noise on owls
No full textInternational audienceToday, owls are exposed to increasingly brightly lit nights and noisy environments because of human activities. To understand the impacts of artificial light at night (ALAN) and anthropogenic noise we performed an evidence synthesis. We searched four literature databases and Google Scholar and we collected 39 relevant articles (1945-2024) providing 125 cases (64 on light pollution and 61 on noise pollution), targeting 25 species (c. 10% of owl species). We found harmful effects of both sensory pollutants on several outcomes. First, ALAN tends to reduce acoustic communication and to be associated with a lower occurrence of owl species, although it is difficult to confirm whether ALAN leads to silent or absent owls. Moreover, ALAN disturbs owl-prey interactions. Although light probably improves owl vision, the light-avoidance behaviour of small mammals could result in poorer hunting success of owls feeding on mammals. Conversely, ALAN enhances food provisioning and even breeding of owls feeding on insects that are attracted by light, to the detriment of these prey populations. Second, human-induced noise clearly tends to reduce owl vocalization, yet that vocalization may be essential to communication between individuals. The ability of owls to detect prey (hunting success) is also reduced under noise exposure (even at low amplitude), probably as the result of masking and distraction. Studies also demonstrate that anthropogenic noise can cause physiological and behavioural stress and disturbance to owls. Such adverse effects may contribute to declines in reproduction and occurrence of owls observed in noisy areas. As a result, we recommend reduction of both sensory stressors as much as possible, for owls and for ecosystem stability, for example by maintaining and restoring quiet and dark areas. We also recommend more consideration of owls in sensory ecology research to fill knowledge gaps.De nos jours, les rapaces nocturnes sont exposés à des nuits de plus en plus lumineuses et à un environnement de plus en plus bruyant en raison des activités humaines. Pour comprendre l'impact potentiel de la lumière artificielle nocturne et du bruit anthropique, nous avons réalisé une revue de littérature. Nous avons interrogé 4 bases de données bibliographiques et Google scholar et nous avons collecté 39 articles pertinents (1945–2024) fournissant respectivement 125 cas (64 sur la pollution lumineuse et 61 sur la pollution sonore), ciblant en tout 25 espèces (~10% des Strigiformes ). Nous avons trouvé plusieurs effets néfastes des pollutions lumineuse et sonore. Tout d'abord, la lumière artificielle tend à diminuer la communication acoustique et est associée à une occurrence plus faible, bien qu'il soit difficile de confirmer si les chouettes sont plus silencieuses ou absentes. Il est indéniable que l'éclairage nocturne perturbe les interactions entre les rapaces nocturnes et leurs proies, ce qui peut expliquer en partie cette situation pour les espèces qui se nourrissent de rongeurs, selon les effets documentés de la luminosité de la lune: alors que la lumière améliore la vision des chouettes/hiboux, le comportement d'évitement de la lumière des petits mammifères pourrait entraîner un moins bon succès de chasse. Inversement, l'éclairage artificiel améliore l'approvisionnement en nourriture et même la reproduction des chouettes insectivores, probablement au détriment des populations de proies attirées par la lumière. Deuxièmement, les sons artificiels tendent clairement à diminuer la vocalisation des chouettes, pourtant essentielle à la communication (par exemple entre partenaires). La capacité des Strigiformes à détecter leurs proies (succès de chasse) est également réduite en cas d'exposition au bruit (même à faible amplitude), sûrement par un effet de masquage et de distraction. Les données démontrent également que le bruit anthropique provoque du stress et des perturbations, tant au niveau physiologique que comportemental. Ces effets négatifs peuvent être responsables de la tendance à la baisse de la reproduction et de l'occurrence des rapaces nocturnes qui est également observée dans les zones bruyantes. Par conséquent, nous recommandons de réduire autant que possible les deux facteurs de stress sensoriel—pour les chouettes/hiboux et pour la stabilité des écosystèmes—par exemple en maintenant et en rétablissant des zones calmes et sombres. Nous demandons également que les Strigiformes soient davantage pris en compte dans la recherche en écologie sensorielle afin de combler les lacunes en matière de connaissances
Optimal structures of crop irrigation strategies with state constraints
No full textInternational audienceWe investigate an optimal control problem of crop irrigation with non-autonomous and non-smooth dynamics. Depending on contexts and objectives, several formulations associated to different constraints and criteria can be derived. Our work aims at providing optimal feedback solutions for these problems by deriving and analyzing the optimality necessary conditions. To this end, we assemble the different problems into a common formulation, and we carry out a dedicated way of handling state constraints. We show that all optimal irrigation strategies belong to a family of simple parameterized time-varying feedback controls, independently of the context and objective, and suitable for computational purposes
The Maize ZmbHLH118 Transcription Factor Regulates Vacuolar Nitrate Loading by the NO <sub>3</sub> <sup>−</sup> Transporter ZmCLCa
No full textInternational audienceNitrate (NO 3-) is a major nutrient promoting plant growth and crop yield. Vacuolar nitrate storage is essential for nitrate acquisition and remobilization within the plant. However, the transcriptional regulation of transporters facilitating nitrate influx into the vacuole remains unclear. Here, we identified a bHLH transcription factor, ZmbHLH118, that negatively regulates the expression of ZmCLCa , thereby modulating nitrate vacuolar loading and uptake in maize ( Zea mays ). ZmbHLH118 overexpression and ZmCLCa loss-of-function in maize impaired root NO 3 -uptake, and further reduced nitrate content and plant growth.Moreover, ZmbHLH118 directly binds to the promoter and inhibits the expression of ZmCLCa , which encodes a tonoplast-localized nitrate transporter. Electrophysiological analysis showed that ZmCLCa mediates NO 3 -fluxes across the vacuolar membrane, indicating that ZmCLCa-mediated NO 3 -influx is required for vacuolar nitrate storage. Our data identify the ZmbHLH118 as a molecular actor of the transcriptional regulation of ZmCLCa in response to extracellular nitrate. This provides insights into the regulatory mechanisms acting upstream of the CLCa-mediated vacuolar nitrate transport. Finally, field assays showed that the regulation mechanisms of vacuolar nitrate affect maize growth and grain yield, highlighting their value for nitrogen use efficiency improvement in crop plants
CIRAD's advanced research towards marker assisted selection of high yielding resistant oil palm (E. guineensis Jacq.): Integrating plant genetics, phytopathology and genomics approaches
No full textSource Agritrop Cirad (https://agritrop.cirad.fr/616431/)International audienceMarker-assisted selection (MAS) offers a powerful method for optimizing the development of diseaseresistant oil palm (E. guineensis Jacq.). An efficient and cost-effective approach involves investigating the genetic basis of resistance by directly exploiting data from ongoing breeding programs. Our results on Fusarium wilt, caused in Africa by Fusarium oxysporum F. sp. elaeidis, and on Basal Stem Rot (BSR), caused by Ganoderma boninense in Southeast Asia, illustrate the potential of this approach for identifying the genomic regions responsible for oil palm disease resistance. They provide key information not only on the genomic regions targeted by MAS, but also on the complexity of the genetic architecture of disease resistance, the genetic sources of favourable alleles, and the potential relationships between different traits of interest. MAS leverages as well knowledge of pathogens. In this context, the G. boninense–oil palm pathosystem is attracting increasing interest within the scientific community. An early inoculation test, enabling the induction of BSR in young seedlings under controlled conditions, allowed the identification of resistance Quantitative Trait Loci (QTL). This method, commonly used for selecting partially resistant progeny, allows for functional studies on the interactions between G. boninense and oil palm. Pathogen's genetic diversity data have led to a better understanding of the importance of sexual reproduction, scale of spore dispersal and of the demographic dynamics of the species in South- East Asia. A transcriptomic study performed on artificially inoculated oil palms showed that G. boninense expresses enzymes already known to be involved in the aggressiveness of other white rot fungi like CAZymes wood decay enzymes and detoxification proteins. The complete genome sequence of G. boninense further enhances our knowledge
Natural variation in Arabidopsis uncouples leaf and flower development and reveals massive transcriptomic heterochrony
No full textInternational audiencePlant development is a sequence of precisely timed and spatially coordinated events that produce organs such as leaves and flowers. In Arabidopsis thaliana, for example, the development of leaves (called bracts in the inflorescence) halts once the first flower forms. Understanding how this transition is regulated is key for decoding how developmental programmes are coordinated during the floral transition. In this study, we investigated a natural phenotypic variation that uncouples bract repression from flower initiation. We discovered that the continued formation of bracts after the floral transition involves complex genetic interactions across at least four loci. Interestingly, none of these loci included known floral identity genes previously linked to bract repression, pointing to novel regulators in the coordination of bract and flower development. Using time-series transcriptomics and curve registration, we found that differences in gene expression levels when bracts persist are mainly driven by a massive desynchronization of gene dynamics. This affects a wide range of biological processes beyond those associated with leaf identity. These findings align with the ‘inverse hourglass’ model, which proposes that transcriptomic divergence at transitional stages contributes to morphological variation. Our results suggest that this model may also explain trait variability within species, highlighting how transcriptome dynamics shape phenotypic robustness during developmental transitions
Monitoring liveweight and performance responses to nutrition in Sarda dairy ewes using a walk-over-weighing system
No full textIn Mediterranean dairy sheep systems, seasonal feed shortages can lead to periods of undernutrition, with negative consequences for animal performance and welfare, particularly during lactation. Liveweight (LW) is a practical indicator of nutritional status and body reserve dynamics, but conventional weighing is labour-intensive and typically performed at low frequency. Walk-over-weighing (WoW) systems integrated with electronic identification (EID) enable frequent, low-labour monitoring of individuals and may improve the detection of nutritionally driven LW changes.This study evaluated the sensitivity of a WoW system to detect moderate LW changes associated with contrasting nutritional levels in Sarda dairy ewes managed indoors or at pasture. Two experiments were conducted: (i) non-lactating ewes housed indoors and subjected to a short-term nutritional challenge; and (ii) lactating ewes managed on pasture with different daily access times and supplemented with hay and concentrate. In both experiments, ewes under the lower nutritional level exhibited lower LW, and WoW detected these differences over time. Under grazing and lactation, differences in nutritional level were also reflected in milk performance indicators.Overall, automated LW monitoring using WoW provides a feasible approach to track LW trajectories in dairy ewes under contrasting management conditions. Integration of LW with routinely collected production data (e.g. milk yield and composition) could support earlier identification of nutritional shortfalls and improve decision-making for welfare-oriented management
KGAP: An RDF Knowledge Graph of Agricultural Commodity Prices
No full textInternational audienceThis article presents the Knowledge Graph for Agricultural Prices (KGAP), which is a knowledge graph (KG) that integrates agricultural commodity prices data from three major Brazilian institutions: Cepea, Conab, and Ipea. The datasets, originally published in heterogeneous formats, were harmonized and converted into RDF/Turtle using the Almes Core metadata schema as the data model. Agricultural products were classified with the Agricultural Product Types Ontology (APTO), and geographic references were aligned with GeoNames identifiers, ensuring semantic consistency and adherence to the FAIR data principles. KGAP is archived on Zenodo and GitHub, and hosted on the Platform Linked Data Nederland (PLDN) with a public SPARQL endpoint. It contains metadata, price observations, product types, and location entities, allowing users to query and compare agricultural prices across institutions, regions, and time periods. The knowledge graph can potentially support applications in agricultural economics, policy analysis, journalism, data science, and machine learning. By explicitly modeling metadata such as reference quantities, KGAP enables semantically-aware queries that prevent common analytical errors and reveal insights previously obscured by data heterogeneity