Belgium

Suction-feeding is a method of prey capture in fluids by sucking the prey into the predator&#39;s mouth. This highly specialised mechanism has been employed by various taxa, including the salamander group Cryptobranchidae, since the Jurassic period. Modern salamanders of the genus Andrias have preserved this feeding strategy without significant morphological changes since the Oligocene. Understanding the biomechanics of suction-feeding is valuable for analysing the physical and morphological mechanisms that support it, as well as its influence on the evolution of feeding strategies in aquatic amphibians, given that suction-feeding has proven to be a highly successful mechanism.
In this study, we developed a two-dimensional Computational Fluid Dynamics (CFD) model of suction-feeding based on micro-CT scans of a first-generation hybrid Andrias davidianus x Andrias japonicus from the Okayama region, Japan. Transient CFD simulations were conducted using unstructured dynamic meshes, along with an overset approach, which allows bidirectional interaction between the prey and the surrounding fluid. Translation and rotation movements of the skull and lower jaw were implemented, also considering surface deformation. Additionally, the depression of the hyoid was considered. The inertial properties of the dynamic mesh were defined according to data from previous studies on Chinese giant salamander (Andrias davidianus). Variables such as prey position, size, and weight were parameterised. The results reveal that cranial geometry, the hyoid apparatus, and prey properties play a crucial role in generating negative pressures that facilitate feeding.

SEB Conference 2025

Computational Hydrodynamic Analysis of Suction-Feeding in a Giant Salamander (Andrias, Cryptobranchidae)

suction feeding

ct scan

rans

lift coefficien

drag coefficient

turbulence models

hybrid meshes

photogrammetry

computational fluid dynamics

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SEB Conference 2024

SEB’s Annual Conference is celebrated for creating the perfect composition of research, new discoveries and collaborative connections. Be creative and innovative by exchanging ideas and knowledge with masters of biology from all over the world.

Suction-feeding is a method of prey capture in fluids by sucking the prey into the predator's mouth. This highly specialised mechanism has been employed by various taxa, including the salamander group Cryptobranchidae, since the Jurassic period. Modern salamanders of the genus Andrias have preserved this feeding strategy without significant morphological changes since the Oligocene. Understanding the biomechanics of suction-feeding is valuable for analysing the physical and morphological mechanisms that support it, as well as its influence on the evolution of feeding strategies in aquatic amphibians, given that suction-feeding has proven to be a highly successful mechanism.
In this study, we developed a two-dimensional Computational Fluid Dynamics (CFD) model of suction-feeding based on micro-CT scans of a first-generation hybrid Andrias davidianus x Andrias japonicus from the Okayama region, Japan. Transient CFD simulations were conducted using unstructured dynamic meshes, along with an overset approach, which allows bidirectional interaction between the prey and the surrounding fluid. Translation and rotation movements of the skull and lower jaw were implemented, also considering surface deformation. Additionally, the depression of the hyoid was considered. The inertial properties of the dynamic mesh were defined according to data from previous studies on Chinese giant salamander (Andrias davidianus). Variables such as prey position, size, and weight were parameterised. The results reveal that cranial geometry, the hyoid apparatus, and prey properties play a crucial role in generating negative pressures that facilitate feeding.

technical paper

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Metabolism lies at the core of life-history theory, and the ability to adapt to fluctuating environmental conditions is key for survival and fitness. Temperature is a pervasive ecological stressor, influencing metabolic rate, development, and energy allocation. Mitochondria play a central role in temperature adaptation by regulating energy transduction and intermediary metabolism, directly impacting growth and reproduction. However, oxidative phosphorylation (OXPHOS) is uniquely vulnerable, as it depends on coordinated expression of mitochondrial (mt) and nuclear (n) genomes, which face distinct evolutionary pressures. Temperature fluctuations challenge this mitonuclear balance, exacerbating intergenomic incompatibilities. Here, I provide evidence that mitonuclear interactions shape metabolic efficiency and resource allocation in response to temperature variation in Drosophila melanogaster populations. Using coevolved and admixed mitonuclear genotypes, I show that temperature stress amplifies mitonuclear mismatches, delaying development, altering metabolism, and reducing fitness. To uncover mechanisms, I will present RNA-Seq data on mitonuclear coexpression under thermal stress, linking genomic regulation to physiological traits. Results indicate that intergenomic epistasis cascades from cellular bioenergetics to organismal performance, with climate change intensifying these incompatibilities and increasing fitness breakdown risks in hybrid populations. Understanding mitonuclear contributions to temperature adaptation is crucial for predicting evolutionary responses to climate change and identifying genetic pathways buffering metabolic stress.

Temperature adaptation shapes the evolutionary dynamics of mitonuclear interactions

How birds flap their wings, or their kinematics, vary between species, but also individual birds show variation between their wingbeats depending on the flight conditions. Understanding the aerodynamic effects of different wing kinematics can help us explain when and why birds select certain kinematics. A crucial aspect of flapping flight is the transition between successive up- and down-strokes. The pitching motion that occurs at these stages of the flapping cycle, and potential interactions between the wings, may have a large impact on the force production. This is well known for hovering flight but has not been extensively studied in forward flight.
In this presentation, we discuss experiments that were conducted using a robotic, flapping wing in a wind tunnel. The wing kinematics used different timings for the pitching motion in relation to the transition between strokes, and the flapping motion was centered around different mean elevation angles. By measuring the flow behind the wing and analyzing the obtained velocity field, we computed the aerodynamic forces produced by the flapping robot. Our results show that these understudied kinematic parameters affect the absolute and relative production of lift and thrust in flapping flight. Notably, since they have different impacts on the horizontal and vertical forces, they could explain differences in flapping strategies observed in birds at different speeds and in different conditions. The results of this research can thus contribute to understanding bird flight, but also to the design and control of flapping drones.

Aerodynamic effects of the transition between strokes in bird flight, wind tunnel study with a robotic wing

Stick and leaf insects (Phasmatodea) rely on two distinct types of smooth cuticular attachment pads on their tarsi to attach and move on diverse substrates: the pretarsal arolium, which is mainly specialized to generate adhesion, and the tarsal euplantulae, which are mainly responsible for providing friction. Both pads produce fluid secretion in the contact area to support their respective functions. These pads work in a complementary manner, allowing the insects to adapt their attachment strategy to the substrate properties. However, a comparative study of structural and mechanical properties, as well as chemical composition of adhesive secretion of arolium and euplantulae is lacking in the literature.
Here, we aim to bridge this gap and present a comprehensive analysis of both types of attachment pads by integrating ultrastructural analysis (histology, light microscopy), mechanical characterization (atomic force microscopy), and chemical profiling (gas chromatography-mass spectrometry).
Our results reveal that the adhesion-specialized arolium possesses a loosely-distributed fibrous ultrastructure, lower elastic modulus, and higher pull-off forces. It also secretes a larger volume of adhesive fluid, enriched with methyl-branched hydrocarbons. In contrast, the friction-optimized euplantulae exhibit a densely-distributed fibrous ultrastructure, higher elastic modulus, lower pull-off forces, and produce fluid with fewer amount of methyl-branched hydrocarbons. These structural, mechanical, and chemical adaptations underline the complementary roles of the two pad types in insect attachment. Our findings provide a better understanding of structure-function relationships in both types of pads, with potential inspirations for biomimetic design in soft robotics and adhesive technology.

Structural, Mechanical and Chemical Adaptations of Arolium und Euplantulae in the Stick Insect Medauroidea extradentata

The Fukushima nuclear accident in 2011 led to significant radioactive contamination of the environment, resulting in chronic exposure to ionizing radiation (IR) for local wildlife. This chronic exposure raises critical concerns about its impact on biodiversity and particularly on the physiological mechanisms relative to species reproduction, that is one of the most radiosensitive fitness endpoints in non-human biota.
Laboratory experiments have demonstrated that IR impact reproduction on both vertebrate and invertebrates and that male gametes appear particularly vulnerable to genotoxic stressors. In addition, in Fukushima, DNA lesions were detected in the male germ cells of exposed mice. Also, tree frogs in the Chernobyl exclusion zone exhibit, 30 years after the nuclear acc high mutation rates, reduced population sizes and decreased body condition indices that collectively suggest population decline and reproductive challenges.
This study examines, during the breeding season, IR impact on the reproductive traits of male Japanese tree frogs (Dryophytes japonicus), a sentinel species. Transcriptomic analyses of gonadal tissues, sperm count/motility, and testosterone levels were performed.
Frogs from contaminated sites show an increased gonadosomatic index correlated with higher sperm concentrations, while testosterone remains stable. The D. japonicus reference transcriptome was sequenced and assembled; ~9000 genes were detected in the dataset. Clustering and differential expression analyses reveal site-specific patterns, and dose-response analysis highlights around 10% genes significantly modeled with DRomics pipeline, enabling benchmark dose determination. Functional enrichment is underway to identify the most radiosensitive biological processes and analyse datas regarding phenotypic findings, resulting in an integrated overview on their reproductive ability.

Impacts of ionizing radiation on reproductive processes in Fukushima tree frogs: transcriptomic and functional insights

Predicting gene function is indispensable to our understanding of biology. However, these predictions hinge on large collections of experimentally characterized genes, the compilation of which is not only labor-intensive and time-consuming but rendered near-impossible given the volume and diversity of scientific literature. Here, we tackle this challenge by deploying the textmining capacities of Generative Pre-trained Transformer (GPT) to process over 70,000 plant biology articles. Our approach unveiled over 5,000,000 functional relationships between a wide array of biological entities—genes, metabolites, tissues, and others—with a remarkable accuracy of over 85%. We encapsulated these findings in PlantConnectome, a user-friendly database, and demonstrated its diverse utility by providing insights into gene regulatory networks, protein-protein interactions, as well as developmental and stress responses. We believe that this innovative use of AI in the life sciences will significantly accelerate and direct research, drive powerful gene function prediction methods and help us keep up to date with the rapidly growing corpus of scientific literature.

PlantConnectome: knowledge graph encompassing >70,000 plant articles

Extreme heatwaves increasingly threaten viticulture, leading to irreversible leaf and fruit burns. In 2019, we capitalized on an unprecedented heatwave in south France and demonstrated a genetic basis for leaf burn susceptibility on a large panel of 279 potted cultivars representing the diversity ofVitis viniferaL.. Genetic variation in leaf temperature was further explored within this panel under irrigated field conditions, and the influences of key morpho-physiological traits affecting the leaf energy balance, including stomatal conductance, leaf inclination, area, folding, reflectance, and transmittance were investigated. Substantial genetic variation was observed for all these morpho-physiological traits in a range that could theoretically contribute to change in leaf temperature. Among the factors influencing leaf temperature, stomatal conductance emerged as the most influential, followed by transmittance. Genome-wide association studies also identified genomic regions linked to genetic variation in leaf temperature, stomatal conductance, inclination and transmittance. However, no colocalization was detected among these traits, suggesting distinct genetic controls.  Cultivars ranking for heat tolerance may vary with the water regime. Notably, when air temperature reached 60°C in a greenhouse experiment, we observed that exacerbation of leaf burn under drought as compared to well-watered conditions was genotype-dependent. These findings provide valuable insights for breeding programs aiming to mitigate heat stress effects by enhancing heat tolerance.

Leaf burn in grapevine under high temperature: which physiological determinants drive genetic variability?

How are the driving forces of root water uptake altered in crop plants under water deficit? 

Deep Learning-Based Data Driven Yield Estimation for Capsicum Grown in Glasshouses

Grasslands are challenging to characterize due to their homogeneous visual texture and diverse species composition, complicating automated data collection for precision livestock farming adoption. Current methods lack detailed spatial information, hindering effective grassland management. Recent advancements in industrial grade field sensing technologies and 3D data processing provide new opportunities for automated phenotyping.
We propose an integrated pipeline for grassland phenotyping using an autonomous unmanned ground vehicle (UGV) powered by Robot Operating System 2 (ROS2). The UGV follows predefined waypoints using NAV2 to scan the grassland, capturing geo-referenced data. This platform is designed to be easy to replicate, deploy and use, allowing compatibility with a variety of sensors based on specific needs. It features IP67-certified components, USB and Ethernet connectivity for data transfer, and approximately 8 hours of battery life for active operation.
Our current work focuses on combining RGB-D frames into a colorized point cloud using a precise positioning device and registration algorithms to assess sward height, LAI, biomass, and vegetation indices while integrating species composition. Future work will incorporate predictive modeling to assess climate and management impacts on grassland health. Additionally, 3D rendering will simulate virtual environments to optimize acquisition parameters before real data collection. A semantic segmentation pipeline will be developed using synthetic training data to spatially classify plant species and objects of interest.
This approach integrates data acquisition, simulation, and predictive modeling to enhance grassland monitoring and management, enabling data-driven precision agriculture for sustainability and productivity.

Integrating 3D Sensing and Autonomous Robotics for Enhanced Grassland Monitoring

Agriculture is increasingly under pressure from climate and biodiversity crises but has also the potential to adapt and to mitigate them. Wheat, a staple crop worldwide, is particularly vulnerable to biotic stresses caused by fungal pathogens. Developing effective strategies to monitor and manage these diseases is critical for enhancing the resilience and sustainability of agriculture.
This study explores the potential of visible and near-infrared (Vis-NIR) diffuse reflectance spectroscopy to detect biotic stresses in wheat under field conditions. Intensive field campaigns were conducted in Wallonia, Belgium, including experimental trials and farmers' fields. At key growth stages, the overall plant health status of field plots was visually assessed, and Vis-NIR spectra were collected using a portable spectrometer.
Three different data treatment approaches were tested (1) calculation of established vegetation indices known to reflect plant health, (2) development of novel indices optimized for specific disease detection using genetic algorithms and (3) use of multivariate classification methods (PLS-DA, SVM-DA) on spectral variables or on a selection of spectral indices to distinguish between severity classes.
The results demonstrate that biotic stresses induce distinct changes in wheat spectral properties, which could be leveraged for disease detection. Before heading stage, disease detection is possible, but uncertainty is high. Between heading and the end of flowering, the performances of detection are better, with a good accuracy on most field trials and on the farmer’s fields.  By linking plant physiological responses to near-infrared spectral data, this study confirms the potential for improved disease monitoring from proximal or remote platform.

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Temperature adaptation shapes the evolutionary dynamics of mitonuclear interactions

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