Biology subjects

Kuehn, S.

Publications and source records attributed to Kuehn, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Genomics of Educational Attainment Across 80 Years of Social and Political Transformation in Germany

Abrupt social and political transformations in twentieth-century Germany may have shifted how polygenic indices relate to educational outcomes across birth cohorts. Following a prespecified analysis plan, we harmonized genomic, educational, and regional data from four German studies, comprising 13,049 individuals born between 1918 and 1995. Polygenic index associations with educational attainment were robust and strengthened modestly across more recent birth cohorts, with no detectable difference between East and West Germany. Associations with intergenerational educational mobility showed no evidence of such strengthening but were stronger in the East than in the West. Polygenic indices were less predictive of educational attainment and educational mobility for women than for men, with no evidence of regional variation. We discuss the methodological limitations of polygenic indices for examining gene-environment interactions, and emphasize that evaluating whether these differences represent progress towards equal educational opportunity requires a normative framework that social science genetics alone cannot supply.

genomics↗

bioRxiv2026

The ecological context of enzymatic variation

Among the challenges in understanding microbial ecosystems is the presence of physics at vastly different scales. Reactions, catalyzed by enzymes but regulated at the level of the cell, propel the flux of carbon and nitrogen through our atmosphere. Compounding this is the presence of pervasive enzyme sequence variation; this variation has been shown to contain coevolving modes of amino acids which encode the enzyme's evolutionary history. In this work, we take steps towards bridging the gap between the enzymatic variation present in an ecosystem and its subsequent activity. We employ the reduction of nitrate by NarG as a model system, which acts as an essential step in the nitrogen cycle by mediating both the return of di-nitrogen to the atmosphere and the assimilation of nitrate into biomass. Considering both metagenomic reconstructions as well as functional data from soil nitrate reducers, we find that sequence variants of enzymes obey predictable responses to environmental fluctuations. That is, while prior community-level metagenomic studies have characterized the response of bacterial strains to the environment, our study provides an enzyme variant level sequence-to-response map. Further, we demonstrate that a simple statistical model can predict the organismal phenotype from variant sequence; in soil samples not originally seen by that model, the prediction of a variant's reduction rate correlates with how much cells with that variant grow in abundance.

biophysics↗

bioRxiv2026

Bacterial vitamin sharing emerges from a balance between release and uptake

Vitamin availability often shapes microbial communities, as many microbes use vitamins they cannot synthesize. Yet how vitamins become available to users remains poorly understood. To explore this process, we quantified vitamin B12 synthesis, uptake, and extracellular accumulation across hundreds of diverse soil, freshwater, and marine bacterial isolates. These measurements revealed distinct source-sink phenotypes and showed that producers vary substantially in the amount of B12 they provide extracellularly. B12 synthesis was predictable across divergent bacterial lineages from genome content, whereas uptake and extracellular accumulation were not. Controlled cell-death experiments and independently parameterized models showed that extracellular B12 could be quantitatively predicted from release by dead cells and reuptake by surviving cells. Thus, extracellular B12 availability is governed not by synthesis alone, but by the balance between release and uptake, with producer reuptake acting as a previously overlooked sink.

microbiology↗

bioRxiv2026

Hierarchical control of bacterial growth efficiency by substrate and taxonomy

Heterotrophic bacteria utilize organic carbon as a source of energy and material for growth. The balanced allocation of carbon between these two processes, termed growth efficiency, is a key physiological property of microbes because it links energy and biomass production, and determines the fraction of carbon lost as CO2. However, we do not understand what controls growth efficiency in microbes or how it correlates with taxonomy and resource identity. Here, we develop a quantitative high-throughput method for measuring CO2 production during bacterial growth. For 23 bacterial strains spanning three phyla, grown on two carbon substrates, we quantify growth efficiency by measuring dynamic CO2 production and carbon accumulation in biomass. Intra-phylum comparisons show that glycolytic substrates yield higher efficiency growth (less CO2 produced per biomass carbon) than gluconeogenic substrates. However, growth efficiency varies as much across resources as it does across phyla. A physiological model shows that variation in the growth efficiency depends on the ATP produced per respired CO2 and the ATP needed per biomass on a given substrate, suggesting phylum level differences in energy supply and demand dictate differences in growth efficiency. This theory predicts no global correlation between growth rate and growth efficiency, a finding our data support. Finally, we report phylum-level variation in the dynamics of CO2 production, which we link to the presence of overflow metabolism on glycolytic sub-strates. This study revises our understanding of how taxonomy and substrate identity impact carbon allocation during growth and sets the stage for understanding CO2 production in communities. SignificanceBacteria are responsible for roughly half of all biological CO2 production on the planet, much of it in soils. How organic carbon flows through microbial metabolism sets the rate at which soils return CO2 to the atmosphere. Bacterial growth efficiency, defined by the fraction of consumed carbon that is retained as biomass rather than released as CO2, determines the fluxes of carbon into the atmosphere. At present, we do not understand what controls growth efficiency in bacteria. We develop a new quantitative measurement of growth efficiency which we apply to 23 soil bacteria from three phyla on two substrates. We show that efficiency is structured hierarchically, at the highest level substrate identity defines efficiency which then varies substantially across taxa. So both the identity of species involved and the compounds they consume determine the rate of carbon loss.

microbiology↗

bioRxiv2026

Phylogenetic coherence in microbiome composition across environmental gradients

Global surveys of microbial communities across biomes have shown that environmental variables such as depth and pH are strong determinants of community composition. However, we do not understand how the traits of individual taxa, and their evolutionary conservation, conspire to give rise to these patterns. Exploiting large-scale surveys of top soil and marine microbiomes, we use canonical correlation analysis (CCA) to concurrently infer directions of environmental variation and the associated compositional changes. We find that the primary canonical direction, capturing the dominant environmental gradient, exhibits a strong phylogenetic signal: individual species responses to environmental shifts along this direction are similar among taxa with shared evolutionary history. In contrast, secondary canonical directions show weak or no phylogenetic structure. Together, these results suggest a two-scale view of microbial community assembly. Deeply evolutionarily conserved traits govern community reorganization along the main environmental driver of community composition. Additional environmentally driven changes in community composition then reflect traits that are more evolutionarily labile.

ecology↗

bioRxiv2026

Natural Selection in the Wake of Catastrophe

Living organisms, from bacteria to humans, are more likely to survive if their traits enhance fitness. In populations well adapted to their environmental niches, natural selection proceeds via rarely beneficial mutations. But when a catastrophe wipes out niche diversity, sudden adaptation often follows. Here, we present a data-validated theory of natural selection in the wake of catastrophe and unveil a simple law that emerges during recovery: the mean fitness relaxes inversely with time, with a prefactor proportional to the number of traits coupled to the post-catastrophe environment. We put our approach to test using experimental fitness landscapes measured following antibiotic administration to E. coli. The resulting mean trait adaptation is not described by gradient ascent on a fitness landscape, instead it follows an algorithm known as Levenberg-Marquardt optimization. Near fitness peaks, evolutionary trajectories are biased against greediness -- from an optimization perspective, post-catastrophic selection is optimistic.

evolutionary biology↗

bioRxiv2026

Global epistasis in ecosystems arises from resource constraints

Global epistasis refers to the observation that the effect of a mutation or modification depends on the state of a biological system, not its detailed composition. Such patterns have been reported across biological scales, from proteins to organisms and ecosystems. In its simplest form, global epistasis appears as a linear relationship between the change in function or fitness due to a perturbation, and the background level of function or fitness. The mechanistic basis of global epistasis, particularly in ecological systems, remains unresolved. Here, we propose that in microbial communities, global epistasis describing the impact of adding a species to a community on function arises generically from constraints imposed by shared resource pools. We illustrate this mechanism in a single-species system growing on multiple substitutable resources, where global epistasis follows directly from nutrient limitation by an essential non-substitutable resource. We then extend this framework to multi-species communities competing for a single resource and show that the marginal effect of adding a species depends linearly on background community function, with a slope determined by the fraction of the resource claimed by the added species. We show that global epistasis persists in trophic cascades, but that facilitation and niche partitioning qualitatively break the linear dependence. This study provides a simple explanation for the appearance of global epistasis in ecosystems, and suggests that global epistasis should be a null expectation in ecosystems governed by competition. Our results propose that coupling between perturbations and shared resource pools might also help explain global epistasis at the organismal level.

ecology↗

bioRxiv2026

Face in the facade: How face-likeness modulates memory and neural representations

Evidence suggests that information represented more reliably in neural activity patterns across repeated exposures is more likely to be remembered. However, this relationship varies across category-selective regions of the ventral visual cortex. Specifically, for house stimuli neural reliability has been robustly linked to memory outcomes in the parahippocampal place area (PPA), but less consistently for faces in the fusiform face area (FFA). The reason for this mismatch is unknown. To address this discrepancy, we implemented a novel within-category manipulation by presenting highly face-like and non-face-like house stimuli during fMRI, followed by a memory test. Non-face-like houses were more likely to be remembered than face-like houses. Although face-likeness did not elicit face-selective responses in the FFA, representational reliability in ventral visual cortices, particularly in the FFA, showed an association with individual differences in memory performance. Finally, symmetry emerged as a potential perceptual factor underlying differences in mnemonic outcomes.

neuroscience↗

bioRxiv2026

Fast and Luminous: CLIP-tag2

CLIP-tag is a self-labeling protein tag used for the specific fluorescence labeling of proteins. However, its low labeling speed and the poor cell permeability of its substrates result in low labeling efficiencies in live-cell applications. Here, we introduce a substrate optimized for live-cell applications, as well as an engineered CLIP-tag variant, CLIP-tag2, which reacts with the new substrate almost 1000-fold faster than the original CLIP-tag-substrate pair. CLIP-tag2 fusion proteins can be specifically and efficiently fluorescently labeled in cells within minutes at nanomolar substrate concentrations, and can be multiplexed with other self-labeling tags such as SNAP-tag2 and HaloTag7. These advances establish CLIP-tag2 as a powerful tagging platform for high-performance live-cell bioimaging.

biochemistry↗

bioRxiv2026

Learning functional groups in complex microbiomes

From soil to the gut, communities composed of thousands of microbes perform functions such as carbon sequestration and immune system regulation. Here, we introduce a data-driven approach that explains how community function can be traced to just a few groups of microbes or genes. In gut communities, our neural-network based clustering algorithm correctly recovers known functional groups. In the ocean metagenome, it distills ~500 gene modules down to three sparse groups highlighting survival strategies at different depths. In soils, it distills ~ 4400 bacterial species into two groups that enter a mathematical model of nitrate metabolism. By combining interpretable ML with strain isolation and sequencing experiments, we connect the metabolic specialization of each group to community-wide responses to perturbations. This integrated approach yields simple structure-function maps of microbiomes, allowing the discovery of molecular mechanisms underlying human and environmental health. More broadly, we illustrate how to do function-informed dimensionality reduction in biology. O_FIG O_LINKSMALLFIG WIDTH=158 HEIGHT=200 SRC="FIGDIR/small/709366v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@1f76c74org.highwire.dtl.DTLVardef@f13bdcorg.highwire.dtl.DTLVardef@19107c6org.highwire.dtl.DTLVardef@9558f7_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO An integrated ML and experimental pipeline to discover functional groups and their dynamics in complex microbiomes and beyond. (a) First, our Soft Clustering Function Informed (SCiFI) algorithm identifies functional groups directly from species abundances data using neural networks. Crucially, the learned functional groups are informed by a chosen community function. (b) Descriptions of the system in terms of the original high-dimensional abundances of individual species are prohibitively complex (left). By contrast, a description in terms of the few functional groups identified by SCiFI leads to a simple structure-function map (right). (c) Next, the identified groups can be directly input as variables into predictive mathematical models for the dynamics of the community. (d) The last step of our pipeline relies on the identified groups comprising only a small number of species. This sparsity enables targeted experiments that interrogate isolated species (e.g. with whole-genome sequencing or phenotyping) shedding light on the mechanistic underpinnings of the structure-function map with potential applications beyond microbiomes, from gene expression to neuronal activity. C_FIG

microbiology↗

bioRxiv2025

Learning the mechanism of collective microbial function via random community-media pairing

In microbial systems, many biochemical functions arise from pathways encoded and executed at the community level. The collective nature of these functions complicates bottom-up efforts to determine each species contribution. Previous work has shown that regression over randomly sampled datasets of collective functions succeeds at predicting those functions. Building on this top-down idea, this paper asks whether regression can also reveal mechanistic insight into a cross-feeding relationship. For this, we propose extending the random sampling method to vary the growth environment, cultivating each community in the spent medium of another randomly constructed community. With a model-based analysis, we show that the new protocol extracts more mechanistic information, enabling assignment of species to the correct cross-feeding pathway steps and identification of species essential to the collective function, both achieved with simple LASSO regressions. More generally, our work illustrates that the utility of machine learning-based approaches can be greatly enhanced by a synergistic experimental design.

ecology↗

bioRxiv2025

From Perception to Appraisal: Hierarchical Brain Responses to Natural and Built Features in Urban Environments

Exposure to urban rather than natural environments has been linked to elevated stress and diminished well-being, prompting interest in the underlying mechanisms and influences of specific urban elements. This study investigated how semantic and lower-level visual characteristics of urban scenes influence subjective experience and underlying neural processes. A total of 63 adults viewed street-level photographs depicting urban environments with varying proportions of vegetation, buildings, vehicles, and sky visibility while electroencephalography (EEG) was recorded. Subjective ratings indicated that urban scenes with more greenery compared to built elements were consistently perceived as more positive. In terms of lower-level image features, images with higher non-straight edge density also led to scenes being perceived as more positive. In contrast, a more visible sky area and a higher mean metric depth led to more negative scene appraisal. On a neural level, urban scenes with higher greenery/built ratios enhanced visual evoked P1 amplitudes, while higher straight-edge density led to more pronounced N1 amplitudes. Further analysis showed that later P3 and LPP components were associated with subjective ratings on higher-level evaluative but not basic affective dimensions. These results partially replicate previous studies, suggesting that urban greenery exerts an effect on subjective well-being and influences early visual processing. Moving forward, Neuro-Urbanism research should employ more diversified stimuli and leverage immersive or in situ paradigms to refine our understanding of the relationship between greenery in urban environments and well-being to inform evidence-based urban design strategies. HighlightsO_LIHigher proportions of greenery in urban environments lead to more positive responses across a variety of subjective rating scales. C_LIO_LIMore urban greenery elicited more pronounced P1 amplitudes, replicating previous findings. C_LIO_LIEarliest visual processing (P1) responds to natural elements of the environment, before processing of visual features characteristic of artificial elements (N1). C_LIO_LILater ERP components (P3, LPP) are associated with subjective scene appraisal of higher level and aesthetic evaluation, pointing to a separation between perceptual and evaluative processes. C_LI

neuroscience↗

bioRxiv2025

Avian influenza causes age-related mortality in a long-lived seabird

Recently, highly pathogenic avian influenza (HPAI) A (H5N1) clade 2.3.4.4b viruses have caused mass mortality events in seabirds worldwide, raising concern for long-lived species with low reproductive rates. Using individual-level data from the 2022 mass mortality event in northwestern European Sandwich terns (Thalasseus sandvicensis), we show that older individuals were disproportionately more affected, while no sex bias was observed. This age-specific mortality likely removed the most experienced individuals from the population. Our findings highlight a previously underappreciated mechanism through which HPAI outbreaks may impair the resilience of long-lived avian populations.

ecology↗

bioRxiv2025

Human Skin Model from 15 GHz to 110 GHz

In the recently revised guidelines for electromagnetic safety, basic restrictions expressed in terms of the absorbed power density (APD) at frequencies higher than 6 GHz were introduced. Testing for APD compliance of wireless devices requires experimental and numerical body models or phantoms that conservatively reproduce the absorption characteristics of human skin. Previous studies of APD indicate that frequency-dependent impedance-matching effects are caused by the low-permittivity stratum corneum (SC) layer. The objective of this study is to complement previous work (Christ et al., 2020) and to develop dispersive dielectric models to represent reflection and absorption of electromagnetic fields at the surface of the skin across a frequency range up to 110 GHz. The reflection coefficient of the skin of human volunteers was measured at frequencies of 15 to 43 GHz with open waveguide probes, complementing previous data from 45 to 110 GHz (Christ et al., 2020). The volunteers represented both sexes and different age groups and occupations; measurements were made at various regions of the body. The statistical analysis of the results show that the reflection coefficient follows a normal distribution in regions where the SC is relatively thin, which permits development of a conservative skin model that covers the 95th percentile of the tested population. As expected, in regions where the SC is thicker, e.g., the palms, the reflection coefficient is not normally distributed, because the thickness of the SC depends on the mechanical stress and friction to which the hands are exposed during routine daily activities. There was no evidence of relevant differences due to sex, but there is evidence for a slight age-dependent difference. The measured data - via fitting to the numerical model - allow the derivation of two-layer dielectric dispersive models that represent absorption and reflection at the surface of the skin with known uncertainty. The proposed models can be used to conservatively demonstrate compliance with the APD limits of wireless devices operating at frequencies of up to 110 GHz in any of the 5G and 6G bands defined. HighlightsO_LIbroadband evaluation of the skin reflection coefficient with open waveguide probes; C_LIO_LIcorroboration of increased absorption of millimeter wave radiation in body regions with increased stratum corneum thickness; C_LIO_LIdispersive dielectric models representing reflection and absorption at the skin surface with known population coverage. C_LI

bioengineering↗

bioRxiv2025

Collective Microbial Effects Drive Toxin Bioremediation and Enable Rational Design

The metabolic activity of microbial communities is essential for host and environmental health, influencing processes from immune regulation to bioremediation. Given this importance, the rational design of microbiomes with targeted functional properties is an important objective. Designing microbial consortia with targeted functions is challenging due to complex community interactions and environmental heterogeneity. Community-function landscapes address this challenge by statistically inferring impacts of species presence or absence on function. Similar to fitness landscapes, community-function landscapes are shaped by both additive effects and interactions (epistasis) among species that influence function. Here, we apply the community-function landscape approach to design synthetic microbial consortia to degrade the toxic environmental contaminant bisphenol-A (BPA). Using synthetic communities of BPA-degrading isolates, we map community-function landscapes across increasing BPA concentrations, where higher BPA means greater toxicity. As toxicity increases, so does epistasis, indicating that collective effects become more important in degradation. Further, we leverage landscapes to rationally design communities with predictable BPA degradation dynamics in vitro. Remarkably, designed synthetic communities are able to remediate BPA in contaminated soils. Our results demonstrate that toxicity can drive epistatic interactions in community-function landscapes and that these landscapes can guide microbial consortia design for bioremediation.

microbiology↗

bioRxiv2025

Microbial functional guilds respond cohesively to rapidly fluctuating environments

Microbial communities experience environmental fluctuations across timescales from rapid changes in moisture, temperature, or light levels to long-term seasonal or climactic variations. Understanding how microbial populations respond to these changes is critical for predicting the impact of perturbations, interventions, and climate change on communities. Since communities typically harbor tens to hundreds of distinct taxa, the response of microbial abundances to perturbations is potentially complex. However, while taxonomic diversity is high, in many communities taxa can be grouped into functional guilds of strains with similar metabolic traits. These guilds effectively reduce the complexity of the system by providing a physiologically motivated coarse-graining. Here, using a combination of simulations, theory, and experiments, we show that the response of guilds to nutrient fluctuations depends on the timescale of those fluctuations. Rapid changes in nutrient levels drive cohesive, positively correlated abundance dynamics within guilds. For slower timescales of environmental variation, members within a guild begin to compete due to similar resource preferences, driving negative correlations in abundances between members of the same guild. Our results provide a route to understanding the relationship between functional guilds and community response to changing environments, as well as an experimental approach to discovering functional guilds via designed nutrient perturbations to communities.

biophysics↗

bioRxiv2025

Inferring resource competition in microbial communities from time series

The competition for resources is a defining feature of microbial communities. In many contexts, from soils to host-associated communities, highly diverse microbes are organized into metabolic groups or guilds with similar resource preferences. The resource preferences of individual taxa that give rise to these guilds are critical for understanding fluxes of resources through the community and the structure of diversity in the system. However, inferring the metabolic capabilities of individual taxa, and their competition with other taxa, within a community is challenging and unresolved. Here we address this gap in knowledge by leveraging dynamic measurements of abundances in communities. We show that simple correlations are often misleading in predicting resource competition. We show that spectral methods such as the cross-power spectral density (CPSD) and coherence that account for time-delayed effects are superior metrics for inferring the structure of resource competition in communities. We first demonstrate this fact on synthetic data generated from consumer-resource models with time-dependent resource availability, where taxa are organized into groups or guilds with similar resource preferences. By applying spectral methods to oceanic plankton time-series data, we demonstrate that these methods detect interaction structures among species with similar genomic sequences. Our results indicate that analyzing temporal data across multiple timescales can reveal the underlying structure of resource competition within communities.

ecology↗

bioRxiv2024

Nature exposure induces hypoalgesia by acting on nociception-related neural processing

Nature exposure has numerous psychological benefits, and previous findings suggest that exposure to nature reduces self-reported acute pain. Given the multi-faceted and subjective quality of pain and methodological limitations of prior research, it is unclear whether the evidence indicates genuine hypoalgesia or results from domain-general effects and subjective reporting biases. This preregistered functional neuroimaging study aimed to identify how nature exposure modulates nociception-related and domain-general brain responses to acute pain. We compared the self-reported and neural responses of healthy neurotypical participants (N = 49) receiving painful electrical shocks while exposed to virtual nature or to closely matched urban and indoor control settings. Replicating existing behavioral evidence, pain was reported to be lower during exposure to the natural compared to the urban or indoor control settings. Crucially, machine-learning-based multi-voxel signatures of pain demonstrated that this subjective hypoalgesia was associated with reductions in nociception-related rather than domain-general cognitive-emotional neural pain processing. Preregistered region-of-interest analyses corroborated these results, highlighting reduced activation of areas connected to lower-level somatosensory aspects of pain processing (such as the thalamus, secondary somatosensory cortex, and posterior insula). These findings demonstrate that nature exposure results in genuine hypoalgesia and that neural changes in lower-level nociceptive pain processing predominantly underpin this effect. This advances our understanding of how nature may be used as a non-pharmacological pain treatment. That this hypoalgesia was achieved with brief and easy-to-administer virtual nature exposure has important practical implications and opens novel avenues for research on the precise mechanisms by which nature impacts our mind and brain.

neuroscience↗