Biology subjects

Perez-Escudero, A.

Publications and source records attributed to Perez-Escudero, A..

11 recordsLinked to original sources

bioRxiv2026

The Marginal Value Theorem in Caenorhabditis elegans

The Marginal Value Theorem (MVT) is an important part of Optimal Foraging Theory, predicting the optimal time to leave a food patch. It has been mostly studied in birds, insects and mammals, even though simpler organisms also need to forage efficiently in patchy environments. Here we test whether the nematode Caenorhabditis elegans implements the MVT. We recorded individual nematodes exploring patchy environments, across four inter-patch distances and three different food qualities, and found that C. elegans behavior matches MVT predictions: When food patches are further away, each food patch is exploited for a longer time. In previous studies animals achieved this by modulating the duration of visits to food patches. Similarly, we found that C. elegans also increases visit duration with inter-patch distance, but this only accounts for half of the increase in total exploitation time. The other half of the increase comes from C. elegans revisiting food patches multiple times, and the number of these revisits increasing with inter-patch distance. This increase in the number of revisits is not due to behavioral changes in response to distance, but rather to a passive interaction between trajectories and environment geometry. These results show that C. elegans can learn the statistics of an environment and use this information in a way consistent with the MVT, but also that part of the fitness-relevant outcomes can emerge passively. SIGNIFICANCEDespite being key in understanding foraging in patchy resources, the Marginal Value Theorem (MVT) has been tested almost exclusively in relatively complex animals. We extensively tested the MVT in a simple, non-visual organism, showing that Caenorhabditis elegans increases patch exploitation time when inter-patch distance increases. This effect is partially driven by the same behavioral adaptation found in complex animals, but also by an increase in the number of patch revisits. This second driver, which had not been reported before and is probably key for non-visual organisms, requires no behavioral adaptation and produces around half of the fitness-relevant outcome. Our results highlight the need for adapting Optimal Foraging Theory to a wide range of taxa spanning from microbes to small invertebrates.

animal behavior and cognition↗

bioRxiv2025

Optimal foraging for simple organisms, the single-input marginal valuetheorem

Most organisms devote a great deal of time and energy to locating and consuming food, making efficient foraging crucial for their evolutionary success. Consequently, Optimal Foraging has been widely studied, but mainly in relatively complex animals with strong sensory and cognitive abilities. However, most living organisms, from bacteria to lower invertebrates, lack these abilities and still must forage efficiently. Here we extend one of the main theorems in Optimal Foraging, the Marginal Value Theorem, to organisms with minimal sensory and cognitive abilities; in particular, we consider individuals whose only sensory input is their feeding rate. To do so, we reformulate a continuous version of the Marginal Value Theorem, finding that individuals should adapt their speed to achieve a marginal feeding rate equal to the average feeding rate for the environment whenever possible, where the marginal feeding rate is defined as the feeding rate they would have if they returned to an already-visited location. We also find that, when faced with uncertainty, moving intermittently is more efficient than moving at constant speed, because this speed variability enables more robust estimates of the marginal feeding rate. Our results generalize Optimal Foraging Theory to organisms with strong sensory constraints, and unify classical results derived for patchy environments to those applicable in arbitrary environments.

animal behavior and cognition↗

bioRxiv2024

Cellects, a software to quantify cell expansion and motion

Cellects is a user-friendly and open-source software for automated quantification of biological growth, motion, and morphology from 2D image data and time-lapse sequences (2D + t), acquired under a wide range of experimental conditions and biological systems (from fungal colonies to unicellular branching networks). The software is available as a stand-alone version, featuring a graphical interface that supports interactive parameter tuning, visualization, validation, and batch processing. The analysis pipeline can be extended and customized using a dedicated Python API. The typical inputs and outputs are as follows. Cellects is designed to process grayscale or color images originating from standard microscopy, macroscopic imaging setups, or camera-based platforms. The software supports single or multiple organisms growing or moving in one or several arenas and can analyze multiple folders sequentially. All quantitative results (area, circularity, orientation axes, centroid trajectories, oscillations, network topology...) are exported as standardized .csv files suitable for downstream statistical analysis, ensuring reproducibility and integration into existing workflows.

bioinformatics↗

bioRxiv2023

Fungal infection alters collective nutritional intake of ant colonies

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. HighlightsO_LIThe insect-pathogenic fungus Metarhizium brunneum performs best on protein-rich diets and is able to solve complex nutritional challenges C_LIO_LIWhile harmful to healthy ants, protein-rich diets did not shorten infected ants lifespan C_LIO_LIContrary to healthy ants, when given a choice, infected and immune-stimulated ants choose a protein-rich diet C_LI

animal behavior and cognition↗

bioRxiv2022

Modeling bee movement shows how a perceptual masking effect can influence flower discovery, foraging efficiency and pollination

Understanding how pollinators move across space is key to understanding plant mating patterns. Bees are typically assumed to search for flowers randomly or using simple movement rules, so that the probability of discovering a flower should primarily depend on its distance to the nest. However, experimental work shows this is not always the case. Here, we explored the influence of flower size and density on their probability of being discovered by bees by developing a movement model of central place foraging bees, based on experimental data collected on bumblebees. Our model produces realistic bee trajectories by taking into account the autocorrelation of the bees angular speed, the attraction to the nest, and a gaussian noise. Simulations revealed a << masking effect >> that reduces the detection of flowers close to another, which may have critical consequences for pollination and foraging success. At the plant level, flowers distant to the nest were more often visited in low density environments, suggesting lower probabilities of pollination at high densities. At the bee colony level, foragers found more flowers when they were small and at medium densities, suggesting that there is an optimal flower size and density at which collective foraging efficiency is optimized. Our results indicate that the processes of search and discovery of resources are potentially more complex than usually assumed, and question the importance of resource distribution and abundance on plant-pollinator interactions. Authors summaryUnderstanding how pollinators move in space is key to understanding plant reproduction, which in turn shapes entire ecosystems. Most current models assume simple movement rules that predict that flowers are more likely to be visited--and hence pollinated--the closer they are to the pollinators nest. Here we developed an explicit movement model that incorporates realistic features of bumblebees, including their flight characteristics and their tendency to return regularly to the nest, and calibrated it with experimental data collected in naturalistic conditions. This model revealed that the probability to visit a flower does not only depend on its position, but also on the position of other flowers that may mask it from the forager. This masking effect means that pollination efficiency depends on the density and spatial arrangement of flowers around the pollinators nest, often in counter-intuitive ways. Taking these effects into account will be key for improving precision pollination and pollinator conservation.

animal behavior and cognition↗

bioRxiv2022

A taste for numbers: Caenorhabditis elegans foraging follows a low-dimensional rule of thumb

Rules of thumb are behavioral algorithms that approximate optimal behavior while lowering cognitive and sensory costs. One way to reduce these costs is by reducing dimensionality: While the theoretically optimal behavior may depend on many environmental variables, a rule of thumb may use a low-dimensional combination of variables that performs reasonably well. Experimental proof of a dimensionality reduction requires an exhaustive mapping of all relevant combinations of several environmental parameters, which we performed for Caenorhabditis elegans foraging by covering all combinations of food density (across 4 orders of magnitude) and food type (across 12 bacterial strains). We found a one-dimensional rule: Worms respond to food density measured as number of bacteria per unit surface, disregarding other factors such as biomass content or bacterial strain. We also measured fitness experimentally, determining that the rule is near-optimal and therefore constitutes a rule of thumb that leverages the most informative environmental variable.

animal behavior and cognition↗

bioRxiv2022

The Motor Wisdom of the Crowd

Wisdom of the Crowd is the aggregation of many individual estimates to obtain a better collective one. This effect has an enormous potential from the social point of view, as it means that a decision may be taken more effectively by vote among a large crowd than by a small minority of experts. Wisdom of the Crowd has been demonstrated in a wide range of cognitive tasks, all of which involve rational thinking. Here we tested this effect in the context of drawing simple geometrical shapes which, while still enacting cognitive processes, mainly involved visuo-motor control. We asked more than 700 school students to trace with their finger a predefined pattern shown on a touchscreen, and analyzed whether their individual trajectories could be aggregated in a way that improved the match with the original pattern. We found that this task has all the characteristics of the strongest examples of Wisdom of the Crowd: First, the aggregate trajectory can be up to 5 times more accurate than the individual ones. Second, this great improvement requires aggregating trajectories from different individuals (rather than different trials from the same individual). Third, the aggregate trajectory outperforms >99% of the individual trajectories. Fourth, when we split our dataset between young children (<10.5 years old) and older children, we find that older individuals outperform younger ones, as naively expected. However, a crowd of young children outperforms the average older individual. In sum, we demonstrate for the first time the Wisdom of the Crowd phenomenon in the realm of motor control, opening the door to further studies of human but also animal behavioral trajectories and their mechanistic underpinnings. Significance statementWisdom of the Crowd is the aggregation of many individual estimates to obtain a better collective one. Thanks to a combination of mathematical, psychological and social factors, this collective estimate can be surprisingly accurate, even when it comes from a crowd of poorly informed individuals. Originally proposed in the context of simple tasks (such as estimating a number), a general version of this concept now pervades our society, from being a key reason behind the success of democracies to being explicitly used to generate collective high-quality knowledge, from Wikipedia to Stack Exchange. Despite this enormous practical success, academic research lags behind, with most studies focusing on simple and narrow tasks. Here we apply the concept for the first time to a sensory-motor task, testing whether the combination of many drawings traced by different subjects resembles the original template. This type of task is wildly different from previous studies of Wisdom of the Crowd, as it depends on continuous sensory-motor control, rather than explicit reasoning or discrete decision-making. We demonstrate that the effect is strong: The aggregate trajectories are more accurate than an overwhelming majority of the individual ones, and a crowd of young children outperforms the average teenager with more mature motor skills.

animal behavior and cognition↗

bioRxiv2020

Inversion of pheromone preference optimizes foraging in C. elegans

Foraging animals have to locate food sources that are usually patchily distributed and subject to competition. Deciding when to leave a food patch is challenging and requires the animal to integrate information about food availability with cues signaling the presence of other individuals (e.g. pheromones). To study how social information transmitted via pheromones can aid foraging decisions, we investigated the behavioral responses of the model nematode Caenorhabditis elegans to food depletion and pheromone accumulation in food patches. We experimentally show that animals consuming a food patch leave it at different times and that the leaving time affects the animal preference for its pheromones. In particular, worms leaving early are attracted to their pheromones, while worms leaving later are repelled by them. We further demonstrate that the inversion from attraction to repulsion depends on associative learning and, by implementing a simple model, we highlight that it is an adaptive solution to optimize food intake during foraging.

ecology↗

bioRxiv2018

Attraction to pheromones in Caenorhabditis elegans can be reversed through associative learning

Despite the ubiquity and importance of chemical signaling, we have only limited insight about the role of learning in the response to pheromones. Here, we demonstrate that responses to pheromones can be reprogrammed through associative learning. In particular, we show that attraction to ascaroside pheromones in the model nematode Caenorhabditis elegans can be reversed by training the animals to associate either a pheromone blend or single synthetic ascarosides with the lack of food. This behavioral plasticity alters worm preference for pheromones following consumption of a food patch, possibly improving foraging in natural environments. By bridging the gap between the current knowledge on the chemical language and the learning abilities of C. elegans, we provide insight on the possible links between learning and chemical signaling in animals.

ecology↗

bioRxiv2017

Asymmetric migration decreases stability but increases resilience in a heterogeneous metacommunity

Many natural communities are spatially distributed, forming a network of subcommunities linked by migration. Migration patterns are often asymmetric and heterogeneous, with important consequences on the ecology and evolution of the species. Here we investigated experimentally how asymmetric migration and heterogeneous structure affect a simple metacommunity of budding yeast, formed by one strain that produces a public good and a non-producer strain that benefits from it. We find that asymmetric migration increases the fraction of producers in all subpopulations of the metacommunity. Furthermore, asymmetric migration decreases the metacommunitys tolerance to challenging environments, but increases its resilience to transient perturbations. This apparent paradox occurs because tolerance to a constant challenge depends on the weakest subpopulations of the network, while resilience to a transient perturbation depends on the strongest ones.\n\nOne Sentence SummaryAsymmetric migration decreases the stability of experimental yeast metacommunities but increases their resilience to transient shocks.

ecology↗

bioRxiv2017

Histone 4 acetylation regulates behavioral individuality in zebrafish

Animals can show very different behaviors even in isogenic populations, but the underlying mechanisms to generate this variability remain elusive. We found that laboratory and isogenic zebrafish (Danio rerio) larvae showed consistent individual behaviors when swimming freely in identical wells or in reaction to stimuli. We also found that this behavioral inter-individual variability was reduced when we impaired the histone deacetylation pathway. Individuals with high levels of histone H4 acetylation, and specifically H4K12, behaved similar to the average of the population, but those with low levels deviated from it. More precisely, we found a set of genomic regions whose histone H4 acetylation is reduced with the distance between the individual and the average population behavior. We found evidence that this modulation depends on a complex of Yin-yang 1 (YY1) and histone deacetylase 1 (HDAC1) that binds to and deacetylates these regions. These changes were not only maintained at the transcriptional level but also amplified, as most target regions were located near genes encoding transcription factors. We suggest that stochasticity in the histone deacetylation pathway participates the generation of genetic-independent behavioral inter-individual variability.

animal behavior and cognition↗