Growth fronts of slime molds are characterized through a direct geometric analysis based on Loewner evolutions, using experimentally acquired time-resolved images. The associated Loewner driving functions reconstructed from expanding pseudopod boundaries display statistical properties consistent with Gaussian-like behavior. A geometric estimate of the diffusivity parameter κ is inferred from fractal scaling, while Brownian diagnostics are assessed on the reconstructed driving signal. These findings show that the boundaries of a growing living organism display statistical and geometric properties consistent with emergent Loewner dynamics over experimentally accessible scales. This study establishes a quantitative framework for analyzing biological growth interfaces and suggests new connections between morphogenesis, stochastic geometry, and network reorganization under varying environmental conditions. We provide, to our knowledge, the first explicit reconstruction of a Loewner driving function from a living growth interface, revealing an emergent Brownian-like conformal growth regime at expanding fronts.

ABSTRACT Ultraviolet (UV) radiation exerts strong selective pressures on microbial life, yet many microorganisms display extraordinary resistance, revealing strategies that may be broadly useful for understanding survival under extreme stress. We systematically examined how UVA, UVB and UVC affect two slime mould species with contrasting pigmentation, Physarum polycephalum and Badhamia utricularis. Across more than 20 000 behavioural assays, we quantified growth, locomotion, photoavoidance, recovery capacity, fusion outcomes and revival from dormancy. UVB emerged as the most deleterious wavelength, causing rapid and sustained declines in growth and motility, while UVC produced intermediate, species-dependent effects, and UVA had a negligible short-term impact, though prolonged exposure over weeks eventually reduced locomotion. Damage was spatially restricted to irradiated plasmodial regions via compartmentalization but could spread through cytoplasmic fusion with stressed partners. Intermittent dark intervals enabled partial recovery, particularly from UVC, consistent with efficient photorepair, whereas UVB damage was more persistent. Strikingly, both species revived from sclerotia with near-perfect success even after a full week of continuous UV exposure, underscoring dormancy as a robust survival strategy. Badhamia utricularis consistently outperformed P. polycephalum. These findings reveal that slime moulds deploy wavelength-specific, species-dependent and state-dependent strategies to withstand UV stress, with rapid damage compartmentalization limiting immediate dysfunction and dormancy ensuring long-term survival under extreme irradiation.

Fungus-animal symbioses have evolved countless times across the tree of life. While the stability of these mutualistic or parasitic interkingdom interactions often depends on optimised nutrient exchange, we lack a framework to explore whether animal-derived nutrients are optimal for fungal symbionts. This conceptual gap has constrained studies about the ecological success and evolutionary stability of fungus-animal symbioses. We use Nutritional Geometry (NG) to harness nutritional niche theory and identify the crucial nutritional niche dimensions of fungi that mediate symbiotic stability. We hypothesise that these fungal nutritional niche dimensions are governed by symbiotic role (mutualist vs. pathogen), degree of animal host control over nutritional competition (monoculture vs. polyculture), and breadth of host associations (specialist vs. generalist). We explore the promise of integrating NG with advanced imaging and -omics approaches to test coevolutionary hypotheses at precise microscales where fungus and animal cells trade nutrients. We conclude that niche-based theory can advance studies of coevolutionary dynamics from arms races to the emergence of economically important pathogens.

The slime mold Physarum polycephalum is an amoebozoa that grows forming a cytoplasm network that adapts its geometry to external stimuli. The cytoplasm is made of ectoplasm tubes in which the endoplasmic fluid flows. Endoplasmic flow is due to the rhythmic contraction of the actomyosin fibers of the ectoplasm, which induces a peristaltic wave that can be tracked through the spatiotemporal variations of the tube diameters. Slime mold behavior depends on many periodic modes of tube diameter variation, which is believed to allow a smooth transition between migration directions. Physarum polycephalum can solve mazes and grow optimal networks to solve traveling salesman and Steiner tree problems. Slime mold network dynamics have been modeled through cell automata and stochastic approaches, as well as fluid flow equations, electronic analogs, and multi-agent systems. Here, we examine the modeling strategies available to date to simulate flow-network adaptation in slime molds. However, we found no theoretical framework that can properly predict the evolution of the network as it morphs from an initial configuration to a pseudo-asymptotic optimum or explain the physical phenomena that drive endoplasmic flow or memory encoding at the scale of the entire network. Multi-frame object tracking by k-partite graphs holds promise for slime mold network analysis and tracking, whereas deep learning could be used to classify sequences of latent features to help characterize the behavior of Physarum polycephalum. The combination of the two could pave the way to a new class of predictive behavior models for slime molds.

Growth and motion quantification is a crucial step in studying the evolution, growth and behavior of many species. However, there is no free and easy to use software to automatically quantify the growth of an organism, and that works across a wide range of species. To fill this gap, we developed Cellects, an open-source software that quantifies growth and motion under any conditions and for any species. Summary Automated quantification offers unique opportunities to study biological phenomena, increasing reproducibility, replicability, accuracy, and throughput, while reducing observer biases. We present Cellects, a tool to quantify growth and motion in 2D. This software operates with image sequences containing specimens growing and moving on an immobile flat surface. Its user-friendly interface makes it easy to adjust the quantification parameters to cover a wide range of species and conditions, and includes tools to validate the results and correct mistakes if necessary. The software provides the region covered by the specimens at each point of time, as well as many geometrical descriptors that characterize it. We validated Cellects with Physarum polycephalum , which is particularly difficult to detect because of its complex shape and internal heterogeneity. This validation covered five different conditions with different background and lighting, and found Cellects to be highly accurate in all cases. Cellects’ main strengths are its broad scope of action, automated computation of a variety of geometrical descriptors, easy installation and user-friendly interface. github link: <https://github.com/Aurele-B/Cellects> Highlights ### Competing Interest Statement The authors have declared no competing interest.

We investigated the emerging traffic patterns of Argentine ants (Linepithema humile) as they navigated a narrow bridge between their nest and a food source. By tracking ant movements in experiments with varying bridge widths and colony sizes and analyzing the resulting trajectories, we discovered that a small subset of ants stopped for long periods of time, acting as obstacles and affecting traffic flow. Interestingly, the fraction of these stopped ants increased with wider bridges, suggesting a mechanism to reduce traffic flow to a narrower section of the bridge. To quantify transport efficiency, we measured the average speed of the ants on the bridge as a function of the pressure of ants arriving at the bridge, finding this relationship to be an increasing but saturating function of the pressure. We developed an agent-based model for ant movement and interactions to better understand these dynamics. Including stopped agents in the model was crucial to explaining the experimental observations. We further validated our hypothesis by introducing artificial obstacles on the bridges and found that our simulations accurately mirrored the experimental data when these obstacles were included. These findings provide new insights into how Argentine ants self-organize to manage traffic, highlighting a unique form of dynamic obstruction that enhances traffic flow in high-density conditions. This study advances our understanding of self-regulation in biological traffic systems and suggests potential applications for managing human traffic in congested environments.

Colonies of ants can complete complex tasks without the need for centralised control as a result of interactions between individuals and their environment. Particularly remarkable is the process of path selection between the nest and food sources that is essential for successful foraging. We have designed a stochastic model of ant foraging in the absence of direct communication. The motion of ants is governed by two components - a random change in direction of motion that improves ability to explore the environment, and a non-random global indirect interaction component based on pheromone signalling. Our model couples individual-based off-lattice ant simulations with an on-lattice characterisation of the pheromone diffusion. Using numerical simulations we have tested three pheromone-based model alternatives: (1) a single pheromone laid on the way toward the food source and on the way back to the nest; (2) single pheromone laid on the way toward the food source and an internal imperfect compass to navigate toward the nest; (3) two different pheromones, each used for one direction. We have studied the model behaviour in different parameter regimes and tested the ability of our simulated ants to form trails and adapt to environmental changes. The simulated ants behaviour reproduced the behaviours observed experimentally. Furthermore we tested two biological hypotheses on the impact of the quality of the food source on the dynamics. We found that increasing pheromone deposition for the richer food sources has a larger impact on the dynamics than elevation of the ant recruitment level for the richer food sources.

In animals, parasitic infections impose significant fitness costs.1-6 Infected animals can alter their feeding behavior to resist infection,7-12 but parasites can manipulate animal foraging behavior to their own benefits.13-16 How nutrition influences host -parasite interactions is not well understood, as studies have mainly focused on the host and less on the parasite.9,12,17-23 We used the nutritional geometry framework24 to investigate the role of amino acids (AA) and carbohydrates (C) in a host -parasite system: the Argentine ant, Linepithema humile, and the entomopathogenic fungus, Metarhizium brunneum. First, using 18 diets varying in AA:C composition, we established that the fungus performed best on the high -amino -acid diet 1:4. Second, we found that the fungus reached this optimal diet when given various diet pairings, revealing its ability to cope with nutritional challenges. Third, we showed that the optimal fungal diet reduced the lifespan of healthy ants when compared with a high -carbohydrate diet but had no effect on infected ants. Fourth, we revealed that infected ant colonies, given a choice between the optimal fungal diet and a high -carbohydrate diet, chose the optimal fungal diet, whereas healthy colonies avoided it. Lastly, by disentangling fungal infection from host immune response, we demonstrated that infected ants foraged on the optimal fungal diet in response to immune activation and not as a result of parasite manipulation. Therefore, we revealed that infected ant colonies chose a diet that is costly for survival in the long term but beneficial in the short term-a form of collective self -medication.

Changes in behaviour over the lifetime of single-cell organisms have primarily been investigated in response to environmental stressors. However, growing evidence suggests that unicellular organisms undergo behavioural changes throughout their lifetime independently of the external environment. Here we studied how behavioural performances across different tasks vary with age in the acellular slime mould Physarum polycephalum. We tested slime moulds aged from 1 week to 100 weeks. First, we showed that migration speed decreases with age in favourable and adverse environments. Second, we showed that decision making and learning abilities do not deteriorate with age. Third, we revealed that old slime moulds can recover temporarily their behavioural performances if they go throughout a dormant stage or if they fuse with a young congener. Last, we observed the response of slime mould facing a choice between cues released by clone mates of different age. We found that both old and young slime moulds are attracted preferentially toward cues left by young slime moulds. Although many studies have studied behaviour in unicellular organisms, few have taken the step of looking for changes in behaviour over the lifetime of individuals. This study extends our knowledge of the behavioural plasticity of single-celled organisms and establishes slime moulds as a promising model to investigate the effect of ageing on behaviour at the cellular level. This article is part of a discussion meeting issue 'Collective behaviour through time'.

Summary In many animals, parasitic infections impose significant fitness costs [1–6]. Animals are known to alter their feeding behavior when infected to help combat various parasites [7–12]. For instance, they can adjust nutrient intake to support their immune system [13,14]. However, parasites can also manipulate host foraging behavior to increase their own development, survival and transmission [15–18]. The mechanisms by which nutrition influences host-parasite interactions are still not well understood. Until now, studies that examine the impact of diet on infection have mainly focused on the host, and less on the parasite [12,13, 19–25]. Using Nutritional Geometry [26], we investigated the role of key nutrients: amino acids and carbohydrates, in a host-parasite system: the Argentine ant, Linepithema humile, and the entomopathogenic fungus, Metarhizium brunneum . We first established that the fungus grew and reproduced better on diets comprising four times less amino acids than carbohydrates (1:4 AA:C ratio). Second, when facing food combinations, the fungus exploited the two complementary food resources to reach the same performance as on this optimal diet, revealing the ability of fungal pathogens to solve complex nutritional challenges. Third, when ants were fed on this optimal fungal diet, their lifespan decreased when healthy, yet not when Metarhizium -infected, compared to their favored carbohydrate-rich diet. Interestingly, when the ants were given a binary choice between different diets, the foragers of uninfected colonies avoided intake of the fungal optimum diet, whilst choosing it when infected. Experimental disentanglement of full pathogenic infection and pure immune response to fungal cell wall material, combined with immune measurements, allowed us to conclude that this change of nutritional choice in infected ants did not result from pathogen manipulation but likely represents a compensation of the host to counterbalance the cost of using amino acids during the immune response. The observed change in foraging behavior in infected colonies towards an otherwise harmful diet (self-medication), suggests a collective compensatory mechanism for the individual cost of immunity. In short, we demonstrated that infected ants converge on a diet that is proven to be costly for survival in the long term but that could help them fight infection in the short term. Highlights The insect-pathogenic fungus Metarhizium brunneum performs best on protein-rich diets and is able to solve complex nutritional challenges While harmful to healthy ants, protein-rich diets did not shorten infected ants’ lifespan Contrary to healthy ants, when given a choice, infected and immune-stimulated ants choose a protein-rich diet

BACKGROUND:Physarum polycephalum is an unusual macroscopic myxomycete expressing a large range of glycosyl hydrolases. Among them, enzymes from the GH18 family can hydrolyze chitin, an important structural component of the cell walls in fungi and in the exoskeleton of insects and crustaceans.METHODS:Low stringency sequence signature search in transcriptomes was used to identify GH18 sequences related to chitinases. Identified sequences were expressed in E. coli and corresponding structures modelled. Synthetic substrates and in some cases colloidal chitin were used to characterize activities.RESULTS:Catalytically functional hits were sorted and their predicted structures compared. All share the TIM barrel structure of the GH18 chitinase catalytic domain, optionally fused to binding motifs, such as CBM50, CBM18, and CBM14, involved in sugar recognition. Assessment of the enzymatic activities following deletion of the C-terminal CBM14 domain of the most active clone evidenced a significant contribution of this extension to the chitinase activity. A classification based on module organization, functional and structural criteria of characterized enzymes was proposed.CONCLUSIONS:Physarum polycephalum sequences encompassing a chitinase like GH18 signature share a modular structure involving a structurally conserved catalytic TIM barrels decorated or not by a chitin insertion domain and optionally surrounded by additional sugar binding domains. One of them plays a clear role in enhancing activities toward natural chitin.GENERAL SIGNIFICANCE:Myxomycete enzymes are currently poorly characterized and constitute a potential source for new catalysts. Among them glycosyl hydrolases have a strong potential for valorization of industrial waste as well as in therapeutic field.

Self-organisation is the spontaneous emergence of spatio-temporal structures and patterns from the interaction of smaller individual units. Examples are found across many scales in very different systems and scientific disciplines, from physics, materials science and robotics to biology, geophysics and astronomy. Recent research has highlighted how self-organisation can be both mediated and controlled by confinement. Confinement occurs through interactions with boundaries, and can function as either a catalyst or inhibitor of self-organisation. It can then become a means to actively steer the emergence or suppression of collective phenomena in space and time. Here, to provide a common framework for future research, we examine the role of confinement in self-organisation and identify overarching scientific challenges across disciplines that need to be addressed to harness its full scientific and technological potential. This framework will not only accelerate the generation of a common deeper understanding of self-organisation but also trigger the development of innovative strategies to steer it through confinement, with impact, e.g., on the design of smarter materials, tissue engineering for biomedicine and crowd management.

Laboratory studies on insects face the dual challenge of maintaining organisms under artificial conditions, and in reduced spaces while mimicking the species' ecological requirements as much as possible. Over decades, myrmecologists have developed and continuously improved laboratory methods and artificial nests for rearing ants. However, the setups commonly used to house colony fragments of few individuals or even isolated individuals present disadvantages such as insufficient ventilation, difficult access to specific workers, and problems with water delivery. Here, we developed and tested a new setup for keeping ants or similar sized insects in small groups. The setup consisted of a Petri dish containing a piece of plaster connected underneath to a water tank by a sponge. The sponge is immersed in the water on one side and embedded in the plaster on the other side, maintaining the plaster permanently moist and thus offering a water source to the ants. We tested the setup with two ant species of different sizes, Platythyrea punctata and Cardiocondyla obscurior in feeding, starvation, and desiccation conditions. Our results showed that our new setup worked equally well for both species in all conditions in comparison to a more conventional setup with the advantage of reducing maintenance costs and ant manipulation, but also preventing death by drowning and offering water ad libitum. The setup was quick to build, with cheap and reusable materials for further experiments. Therefore, we are confident that it will facilitate future studies on isolated or small groups of individuals and that such a standardized setup will make future studies more comparable.

Use of animal models in experiments has raised serious concerns in translational research in medicine, especially in Europe. In this context, efforts are being made to find alternatives to the traditional in vivo phase in various studies. Currently, organoid and 3D cellular structures in vitro are increasingly being used in translational research, however they only mimic part of the organism under study, not the entire organism. Here, we propose to use the acellular slime mold Physarum polycephalum ( Pp ) as a new model system. Pp is a large polynucleated unicellular organism (up to several hundred square centimeters) [1] that responds to its environment and exhibits complex behaviors [2] . This work aims to better understand the effects of an exposure to a non-thermal plasma at atmospheric pressure and to the associated pulsed electric field. The experiments on Pp LU352, were carried out with a µs pulse helium Plasma Gun [3] working at frequencies ranging up to 20 kHz and a reactor high voltage ranging up to 20 kV. We will present results on both the viability and the growth of Pp LU352 in interaction with the plasma. We will describe the effect of the plasma on the slime mold environment and how it affects the behavior of the organism.

Optimality analysis of value-based decisions in binary and multi-alternative choice settings predicts that reaction times should be sensitive only to differences in stimulus magnitudes, but not to overall absolute stimulus magnitude. Yet experimental work in the binary case has shown magnitude sensitive reaction times, and theory shows that this can be explained by switching from linear to multiplicative time costs, but also by nonlinear subjective utility. Thus disentangling explanations for observed magnitude sensitive reaction times is difficult. Here for the first time we extend the theoretical analysis of geometric time-discounting to ternary choices, and present novel experimental evidence for magnitude-sensitivity in such decisions, in both humans and slime moulds. We consider the optimal policies for all possible combinations of linear and geometric time costs, and linear and nonlinear utility; interestingly, geometric discounting emerges as the predominant explanation for magnitude sensitivity.

There is growing appreciation for how social interactions influence animal foraging behavior, especially with respect to key nutrients. Ants, given their eusocial nature and ability to be reared and manipulated in the laboratory, offer unique opportunities to explore how social interactions influence nutrient regulation and related processes. At the colony-level, ants simultaneously regulate their protein and carbohydrate intake; a regulation tied to the presence of larvae. However, even though 45% of the approximately 10,000 ant species are polygynous, we know little about the influence of queen number on colony-level foraging behavior and performance. Here we explored the direct effects of queen number on colony-level protein-carbohydrate regulation, food collection, survival, and brood production in two polygynous ant species (Nylanderia fulva and Solenopsis invicta). For both species we conducted choice and no-choice experiments using small experimental colonoids (20 workers) with 0, 1, or 2 queens. Both species regulated their relative intake of protein and carbohydrate around a P1:C2 mark. However, only N. fulva responded to the addition of queens, increasing overall food collection, biasing intake towards carbohydrates, and over-collecting imbalanced foods. N. fulva also exhibited reduced survival and reproduction on protein-biased foods. In contrast, S. invicta showed no response to queen number and reduced food collection on the protein-biased diet while maintaining high survival and reproduction. Our results demonstrate the potential for queens of some ant species to impact colony-level foraging and performance, with interspecific variation likely being shaped by differences in life history traits.

The acellular slime mold Physarum polycephalum provides an excellent model to study network formation, as its network is remodelled constantly in response to mass gain/loss and environmental conditions. How slime molds networks are built and fuse to allow for efficient exploration and adaptation to environmental conditions is still not fully understood. Here, we characterize the network organization of slime molds exploring homogeneous neutral, nutritive and adverse environments. We developed a fully automated image analysis method to extract the network topology and followed the slime molds before and after fusion. Our results show that: (1) slime molds build sparse networks with thin veins in a neutral environment and more compact networks with thicker veins in a nutritive or adverse environment; (2) slime molds construct long, efficient and resilient networks in neutral and adverse environments, whereas in nutritive environments, they build shorter and more centralized networks; and (3) slime molds fuse rapidly and establish multiple connections with their clone-mates in a neutral environment, whereas they display a late fusion with fewer connections in an adverse environment. Our study demonstrates that slime mold networks evolve continuously via pruning and reinforcement, adapting to different environmental conditions.

The survival of all species requires appropriate behavioral responses to environmental challenges. Learning is one of the key processes to acquire information about the environment and adapt to changing and uncertain conditions. Learning has long been acknowledged in animals from invertebrates to vertebrates but remains a subject of debate in non-animal systems such a plants and single cell organisms. In this review I will attempt to answer the following question: are single cell organisms capable of learning? I will first briefly discuss the concept of learning and argue that the ability to acquire and store information through learning is pervasive and may be found in single cell organisms. Second, by focusing on habituation, the simplest form of learning, I will review a series of experiments showing that single cell organisms such as slime molds and ciliates display habituation and follow most of the criteria adopted by neuroscientists to define habituation. Then I will discuss disputed evidence suggesting that single cell organisms might also undergo more sophisticated forms of learning such as associative learning. Finally, I will stress out that the challenge for the future is less about whether or not to single cell organisms fulfill the definition of learning established from extensive studies in animal systems and more about acknowledging and understanding the range of behavioral plasticity exhibited by such fascinating organisms.