Biology subjects

Albrecht, J.

Publications and source records attributed to Albrecht, J..

11 recordsLinked to original sources

bioRxiv2026

The Metabolome of Drosophila Reveals Exercise-Induced Stress and Anti-Inflammatory Response

Exercise is a known remedy for metabolic disorders, including obesity and type II diabetes. In humans and some model organisms, exercise is classified into different types and intensities based on the mode of exercise and the devices used. Since Drosophila has emerged as a model for exercise research, several devices have been developed for exercise training. These devices vary in mechanisms of operation; for example, the Power Tower (PT) uses a repeated drop-and-hit mechanism, and the TreadWheel (TW) uses end-over-end rotation. This variation in mechanisms that trigger the negative geotaxis of flies could impact exercise outcomes, and it remains unclear how this variation drives the response of flies to exercise training. Stress is a known response to exercise in humans and mice. Stress in Drosophila can be induced by various conditions, including heat, cold, chemical exposure, and other environmental stressors, but there is little information on exercise-induced stress. It is also unclear whether different devices elicit distinct stress responses or whether the exercise-induced stress response is similar to other stress responses (e.g., thermal, chemical). To explore the effects of device, sex, and genotype on multiple metabolic pathways, we used an untargeted metabolomics approach to further elucidate the molecular mechanisms of exercise. As no studies have directly examined the exercise metabolome of Drosophila, this study is the first to explore the metabolome of flies post-exercise. Our results revealed that exercising on different devices elicits varying responses and reshapes the metabolome of flies. We also identified specific small compounds that may be linked to stress and inflammatory response more in the PT-exercised flies than in the TW-exercised flies. Overall, the exercise device effect interacted with sex effect and genotype, such that male and female flies have different metabolite compositions post-exercise on TW and PT.

Molecular Biology↗

bioRxiv2025

High-Fidelity Tuning of Olfactory Mixture Distances in the Perceptual Space of Smell Through a Community Effort

A central goal in sensory science is to establish quantitative mappings between physical stimuli and perceptual responses. While such mappings are well characterized in vision and audition, they remain poorly defined in olfaction, limiting progress toward understanding the representations of smell. Predicting perceptual similarity between odor mixtures offers a promising route to formalize these relationships. To advance this effort, the DREAM (Dialogue for Reverse Engineering Assessment and Methods) Olfactory Mixtures Prediction Challenge assembled a curated, cross-study dataset describing the similarity of 507 mixture pairs and an unpublished test set of 46 mixture pairs. Teams competed to predict the perceptual similarity of mixture pairs, and then collaborated post-challenge to create an ensemble combining top-performing models that notably improves predictions over the existing state-of-the-art models. Moreover, ensemble model maintains high predictive accuracy in novel validation set. Our model provides a reproducible framework for neuroscientists, chemists, and engineers to compare odor mixtures and provides a foundation for future efforts towards better understanding the olfactory properties of mixtures.

neuroscience↗

bioRxiv2025

MoveTraits - A database for integrating animal behaviour into trait-based ecology

Trait-based approaches are key to understanding eco-evolutionary processes but rarely account for animal behaviour despite its central role in ecosystem dynamics. We propose integrating behaviour into trait-based ecology through movement traits - standardised and comparable measures of animal movement derived from biologging data, such as daily displacements or range sizes. Accounting for animal behaviour will advance trait-based research on species interactions, community structure, and ecosystem functioning. Importantly, movement traits allow for quantification of behavioural reaction norms, offering insights into species acclimation and adaptive capacity to environmental change. We outline a vision for a living global movement trait database that enhances trait data curation by (1) continuously growing alongside shared biologging data, (2) calculating traits directly from individual-level data using standardised, consistent methodology, and (3) providing information on multi-level (species, individual, within-individual) trait variation. We present a proof-of-concept MoveTraits database with 55 mammal and 108 bird species, demonstrating calculation workflows for 5 traits across multiple time scales. Movement traits have significant potential to improve trait-based global change predictions and contribute to global biodiversity assessments as Essential Biodiversity Variables. By making animal movement data more accessible and interpretable, this database could bridge the gap between movement ecology and biodiversity policy, facilitating evidence-based conservation.

ecology↗

bioRxiv2025

Delayed recovery of seed-dispersal interactions after deforestation

Interactions between plants and animals are crucial for natural forest recovery because most plants rely on seed dispersal by animals to recolonize degraded habitats. Despite this importance, the recovery time of seed-dispersal interactions after deforestation is unknown. We compared the recovery time of the functional diversity of seed-dispersal interactions, frugivorous animals and fleshy-fruited plants by recording trait and interaction data along a chronosequence of tropical forest recovery. Using a Bayesian model, we estimated that plant functional diversity was high shortly after deforestation, but animal functional diversity recovered only after 39 years, and seed-dispersal interactions after 18 years. We demonstrate that seed-dispersal interactions need about two decades to functionally recover which provides a new benchmark for the timing of restoration projects in tropical forests.

ecology↗

bioRxiv2024

Cell identity revealed by precise cell cycle state mapping links data modalities

Several methods for cell cycle inference from sequencing data exist and are widely adopted. In contrast, methods for classification of cell cycle state from imaging data are scarce. We have for the first time integrated sequencing and imaging derived cell cycle pseudo-times for assigning 449 imaged cells to 693 sequenced cells at an average resolution of 3.4 and 2.4 cells for sequencing and imaging data respectively. Data integration revealed thousands of pathways and organelle features that are correlated with each other, including several previously known interactions and novel associations. The ability to assign the transcriptome state of a profiled cell to its closest living relative, which is still actively growing and expanding opens the door for genotype-phenotype mapping at single cell resolution forward in time.

bioinformatics↗

bioRxiv2024

Aberrant remodelling of astrocytic architecture in acute hepatic encephalopathy: complexity of oedematic atrophic astrocytes

Hepatic encephalopathy (HE) following acute liver failure (ALF) is a primary toxic astrocytopathy, although in-depth characterisation of underlying pathogenesis is far from complete. Among the multitude of astrocyte-specific proteins guiding brain functionality, plasmalemma-cytoskeletal linker ezrin, actin-binding protein profilin-1, and water channel aquaporin 4 (AQP4) contribute to astrocytic morphological plasticity through regulation of cell shape, volume, complexity of primary and terminal processes, and positioning astrocytes against other CNS constituents. Changes in these proteins might contribute to the brain oedema and astrocytic morphological remodelling in the HE. Using transmission electron microscopy, confocal fluorescent microscopy, and 3D reconstruction, we found complex morphological alterations of cortical astrocytes in mice with azoxymethane-induced ALF. Astrocytic primary branches demonstrated hypertrophy, whereas terminal leaflets showed atrophy quantified by the reduced area occupied by astrocytes, decreased number and the length of leaflets, decreased leaflets volume fraction, and altered astrocyte-to-neurone landscape. These morphological changes correlat with decreased expression of AQP4, phosphorylated leaflet-associated ezrin, and the actin dynamics regulator, profilin 1, suggesting the contribution of these proteins to astrocytic pathological remodelling. Pathological changes in astrocytes develop in parallel, and are likely causally linked to, the HE-linked neurological decline, manifested by a reduction in electroencephalography power and by excessive glutamate in the brain microdialysates. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC="FIGDIR/small/602491v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@45d6a3org.highwire.dtl.DTLVardef@10e9ac3org.highwire.dtl.DTLVardef@1d28b36org.highwire.dtl.DTLVardef@1b1b866_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstract:C_FLOATNO Hepatic encephalopathy is associated with astrocyte remodelling manifested by swelling of the soma and primary branches together with atrophy of distal branches and leaflets; the latter retract from synapses thus affecting neurotransmission and contribute to the reduced neuronal activity. Astrocyte remodelling was linked to (and probably instigated by) a decrease of plasmalemma-cytoskeleton linker phosphorylated ezrin (Phos-ezrin), actin modulator profilin-1 (PFN1) and water channel aquaporin 4 (AQP4). C_FIG

neuroscience↗

bioRxiv2024

Trophic adaptation of large terrestrial omnivores to global change

Large omnivores at the top of food webs play a key role in ecosystems, as their ability to feed on multiple trophic levels stabilizes food-web dynamics and impacts ecosystem functioning. However, it is largely unexplored how large omnivores adapt their trophic interactions to altered resource availability under global change, particularly in terrestrial ecosystems. Here, we combine macroecological and paleoecological approaches and reveal that extant bears, the largest terrestrial omnivores, adapt their trophic position in food webs dynamically to net primary productivity and growing season length. Throughout their geographic ranges, extant bears occupy higher trophic positions in unproductive ecosystems with short growing seasons than in productive ecosystems with long growing seasons. Consistent with this geographic pattern, the trophic position of the brown bear sharply decreased at the transition from the Late Pleistocene to the Holocene, coinciding with an increase in net primary productivity and growing season length. These findings demonstrate that trophic interactions of omnivores are not static but change dynamically in response to environmental change. Our findings suggest that global change impacts on primary production and vegetation seasonality may trigger shifts in the functional role of omnivores, with consequences for food webs and ecosystem functions. Significance statementLarge omnivores play a key role in ecosystems, as they stabilize food-web dynamics and impact ecosystem functioning. However, how omnivores adapt their trophic interactions to changes in resource availability under global change remains unexplored. Combining macroecological and paleoecological approaches, we show that extant bears, the largest terrestrial omnivores, occupy lower trophic positions in food webs as net primary productivity and growing season length increase. This trophic adaptation is evident across the geographic ranges of all extant terrestrial bear species and for brown bears at the transition from the Late Pleistocene to the Holocene. Therefore, impacts of global change on primary production and vegetation seasonality may trigger shifts in the functional role of omnivores, with consequences for food webs and ecosystems. One sentence summaryGlobal changes in primary productivity and vegetation seasonality alter the functional role of large omnivores in terrestrial ecosystems.

ecology↗

bioRxiv2023

Evaluation and optimization of sequence-based gene regulatory deep learning models

Neural networks have emerged as immensely powerful tools in predicting functional genomic regions, notably evidenced by recent successes in deciphering gene regulatory logic. However, a systematic evaluation of how model architectures and training strategies impact genomics model performance is lacking. To address this gap, we held a DREAM Challenge where competitors trained models on a dataset of millions of random promoter DNA sequences and corresponding expression levels, experimentally determined in yeast, to best capture the relationship between regulatory DNA and gene expression. For a robust evaluation of the models, we designed a comprehensive suite of benchmarks encompassing various sequence types. While some benchmarks produced similar results across the top-performing models, others differed substantially. All top-performing models used neural networks, but diverged in architectures and novel training strategies, tailored to genomics sequence data. To dissect how architectural and training choices impact performance, we developed the Prix Fixe framework to divide any given model into logically equivalent building blocks. We tested all possible combinations for the top three models and observed performance improvements for each. The DREAM Challenge models not only achieved state-of-the-art results on our comprehensive yeast dataset but also consistently surpassed existing benchmarks on Drosophila and human genomic datasets. Overall, we demonstrate that high-quality gold-standard genomics datasets can drive significant progress in model development.

genomics↗

bioRxiv2023

The ontogeny of individual specialization

Individual dietary specialization, where individuals occupy a subset of a populations wider dietary niche, is a key factor determining a species resilience against environmental change. However, the ontogeny of individual specialization, as well as associated underlying social learning, genetic, and environmental drivers, remain poorly understood. Using a multigenerational dataset of female European brown bears (Ursus arctos) followed since birth, we discerned the relative contributions of environmental similarity, genetic heritability, maternal effects, and offspring social learning from the mother to individual specialization. Individual specialization accounted for 43% of phenotypic variation and spanned half a trophic position, with individual diets ranging from omnivorous to carnivorous. The main determinants of dietary specialization were social learning during rearing (13%), environmental similarity (9%), maternal effects (11%), and permanent between-individual effects (8%), whereas the contribution of genetic heritability was negligible. The trophic position of offspring closely resembled the trophic position of their mothers during the first 3-4 years of independence, but this relationship ceased with increasing time since separation. Our study shows that social learning and maternal effects are as important for individual dietary specialization as environmental composition. We propose a tighter integration of social effects into future studies of range expansion and habitat selection under global change that, to date, are mostly explained by environmental drivers.

ecology↗

bioRxiv2023

Including biotic interactions in species distribution models improves the understanding of species niche: a case of study with the brown bear in Europe

Biotic interactions are expected to influence species responses to climate change, but they are usually not included when predicting future range shifts. We assessed the importance of biotic interactions to understand future consequences of climate and land use change for biodiversity using as a model system the brown bear (Ursus arctos) in Europe. By including biotic interactions using the spatial variation of energy contribution and habitat models of each food species, we showed that the use of biotic factors considerably improves our understanding of the distribution of brown bears. Predicted future range shifts, which included changes in the distribution of food species, varied greatly when considering various scenarios of change in biotic factors, warning about future indirect climate change effects. Our study confirmed that advancing our understanding of ecological networks of species interactions will improve future scenarios of biodiversity change, which is key for conserving biodiversity and ecosystem services.

ecology↗

bioRxiv2021

Tripartite networks show that keystone species can multitask

Keystone species are disproportionately important for ecosystem functioning (1,2). However, while all species engage in multiple interaction types with other species, the importance of keystone species is often defined based on a single dimension of their Eltonian niche (3), that is, one type of interaction (e.g., keystone predator). Therefore, it remains unclear whether the importance of keystone species is unidimensional or if it extends across interaction types. We conducted a meta-analysis of tripartite interaction networks to examine whether species importance in one dimension of their niche is mirrored in other niche dimensions, and whether this is associated with interaction outcome, intimacy, or species richness. We show that keystone species importance is positively associated across multiple ecological niche dimensions, independently of species abundance, and find no evidence that multidimensionality of keystone species is influenced by the explanatory variables. We propose that the role of keystone species extends across multiple ecological niche dimensions, with important implications for ecosystem resilience and conservation. Significance StatementKeystone species are often identified by focusing on a single type of interaction (e.g., predation, pollination, herbivory) which contrasts with the multiple roles that species play in biological communities. We conducted a meta-analysis of 18 tripartite interaction networks to explore if keystonness is correlated across the multiple dimensions of species Eltonian niches. Our results suggest that species importance tends to span across multiple interaction types, independently from abundance, which can be key to understand community resilience and collapse in face of multiple threats.

ecology↗