Biology subjects

Schaub, M.

Publications and source records attributed to Schaub, M..

8 recordsLinked to original sources

bioRxiv2026

History of opioid use disorder correlates with altered neuroimmune signatures in the human dorsal root ganglia

Understanding mechanisms for the negative reinforcing effects of opioids are fundamental to improving patient care. Using human dorsal root ganglia (DRG) from donors with and without opioid use disorder (OUD), we set out to examine functional and molecular correlates of chronic opioid use. At a molecular level, we detected disrupted immune signatures throughout cells in the peripheral nervous system (PNS), spanning glial-neuroimmune interactions to changes in non-neuronal senescence. At the physiological level these changes are paired with sensitization of DRG sensory neurons. Our findings reveal a neuro-inflammatory state in the PNS of individuals with OUD. Targeting therapeutics towards these PNS-based mechanisms could be an approach to alleviating the negative reinforcing effects of opioids.

neuroscience↗

bioRxiv2026

Exploring nematode diversity in soils: comparison of extraction methods and sequencing protocols

Soil nematodes play key roles in regulating organic matter decomposition, nutrient cycling and trophic interactions in the soil ecosystem, and are very useful bioindicators of soil condition and soil health. But to characterise them, we need reliable measurements of nematode biodiversity in soils. DNA-based techniques such as metabarcoding have recently explored their biodiversity, with successful results. However, there are many methodological steps that can modify the outcome considerably and require informed decisions. In this study, we tested the effect on nematode alpha and beta diversity metrics of three methodological steps, namely i) type of extraction of genetic material from the matrix, either from soil directly with different starting amount of material or extracting nematodes first via the Baermann or Oostenbrink methods, ii) the choice of taxonomically-relevant DNA segment for amplification, with a nematode specific primer (NemF/18Sr2b) and a universal eukaryotic primer (3NDf/1132rmod), both within 18S rDNA, and iii) the selection of appropriate reference library for taxonomic assignment (comparing three nematode specialised databases and three broad taxonomic databases). Observed differences in alpha diversity were more pronounced when comparing the nematode extraction vs soil extractions. In particular, direct soil extractions co-extracted many non-nematode taxa, especially if amplified with a universal primer, which can significantly reduce the number of nematode reads obtained and therefore the accuracy of nematode community indexes and other nematode-based metrics. The choice of the reference database strongly affected the taxonomic identification, which calls for extreme caution when making this selection. Notably, specialised databases tended to over assign reads to nematodes that were detected as non-nematodes by broad taxonomic databases. However, beta diversity metrics were consistent across methods, highlighting these metrics as robust against methodological choices. Our study clearly demonstrates that the choices of methods for nematode biodiversity studies using molecular tools can have a big impact on the results, and decisions should be made consciously and carefully.

ecology↗

bioRxiv2026

Efficient capture-recapture inference for spatially varying natal dispersal,survival and recruitment

1. Natal dispersal is a key process in population ecology because it links local demographic processes to broader-scale population dynamics by redistributing individuals. When using capture-recapture data, multistate capture-recapture models using discrete spatial units as states are the gold standard for estimating natal dispersal among spatial units while accounting for spatial variation in survival, recruitment and imperfect detection. However, because their computational cost increases rapidly with the number of spatial units, applications have been limited to a small number of units. Therefore, in practice, these models cannot provide spatially detailed inference on natal dispersal across large landscapes. 2. We develop a computationally efficient Bayesian capture-recapture model, called the efficient natal dispersal (END) model, to estimate natal dispersal among discrete spatial units jointly with spatial variation in demographic parameters and detection probabilities. The END model relies on two key structural features: juveniles and breeders are separated into two arrays, and resightings outside the natal spatial unit are aggregated over time for individuals released as juveniles. 3. Using simulations, we show that the END model is considerably (up to 30 times) more computationally efficient than a conventional multistate model, while maintaining comparable parameter accuracy. We then apply the END model to white stork (Ciconia ciconia) capture-recapture data from Germany across 101 hexagonal spatial units, a spatial resolution at which a conventional multistate model is computationally infeasible. We estimate natal dispersal among units jointly with spatial variation in survival and recruitment. This allows us to identify areas of lower or higher survival, earlier or delayed recruitment, and dispersal probabilities among all units. By combining estimated dispersal probabilities with existing data on the number of juveniles born in each spatial unit, we estimate natal dispersal in terms of numbers of individuals and identify units with positive or negative net migration, sources and sinks. 4. Overall, our approach moves capture-recapture analyses from estimating natal dispersal among a few spatial units to inferring dispersal networks and assessing their demographic consequences across large domains. Our approach is applicable to many spatially structured capture-recapture datasets, opening new opportunities for studying spatial population dynamics.

ecology↗

bioRxiv2026

An Integrated Population Model to Incorporate Spatio-Temporal Heterogeneity in Demographic Rates

O_LIDemographic processes in populations are inherently heterogeneous across both space and time. Many ecological models explicitly account for temporal heterogeneity in the demographic rates that govern these processes, but assume spatial homogeneity. Ignoring spatial heterogeneity can bias inference, limit predictive performance, and obscure key spatial structure in demographic rates. Integrated population models (IPMs) offer a powerful framework to estimate spatio-temporal demographic rates by combining diverse ecological data sources collected from multiple sampling locations. However, to accomplish this, IPMs face significant statistical and computational hurdles, including misalignment between different data sources and the need to efficiently account for residual spatial autocorrelation. C_LIO_LIWe present a novel Bayesian spatially explicit integrated population model (sIPM) which integrates population count and capture-recapture data from multiple sampling locations to estimate and predict continuous spatio-temporal demographic rates, such as survival, recruitment and population growth rate, across large geographic domains. This framework employs a joint likelihood approach with change of support to flexibly accommodate spatial and spatio-temporal data misalignment, and incorporates a nearest-neighbor Gaussian process to efficiently model residual spatial autocorrelation and generate spatial predictions. C_LIO_LIWe assess the performance of our sIPM through an extensive simulation study. Results show that our approach provides unbiased and precise estimates and predictions of spatio-temporal demographic rates, even in the presence of significant data misalignment and residual spatial autocorrelation. We demonstrate the utility of our method by analyzing data on Gray Catbirds (Dumetella carolinensis) from the North American Breeding Bird Survey and the Monitoring Avian Productivity and Survivorship program across the eastern coast of the United States from 2004-2014. This analysis results in maps of apparent survival, recruitment and population growth rate, thereby revealing important spatio-temporal variations in demographic rates that would have been obscured by traditional, spatially homogeneous IPMs. C_LIO_LIOur sIPM offers a robust and computationally efficient method for studying spatio-temporal variation in demographic processes across large areas, even in the presence of data misalignment and residual spatial autocorrelation. Ultimately, this framework, applicable to many ecological monitoring programs, facilitates the development of spatially targeted strategies necessary for effective conservation and management. C_LI

ecology↗

bioRxiv2024

PHLOWER - Single cell trajectory analysis using Decomposition of the Hodge Laplacian

Multi-modal single-cell sequencing, which captures changes in chromatin and gene expression in the same cells, is a game changer in the study of gene regulation in cellular differentiation processes. Computational trajectory analysis is a key computational task for inferring differentiation trees from this single-cell data, though current methods struggle with complex, multi-branching trees and multi-modal data. To address this, PHLOWER (decomPosition of the Hodge Laplacian for inferring trajectOries from floWs of cEll diffeRentiation) leverages the harmonic component of the Hodge decomposition on simplicial complexes to infer trajectory embeddings. These natural representations of cell differentiation facilitate the estimation of their underlying differentiation trees. We evaluate PHLOWER through benchmarking with multi-branching differentiation trees and using novel kidney organoid multi-modal and spatial single-cell data. These demonstrate the power of PHLOWER in both the inference of complex trees and the identification of transcription factors regulating off-target cells in kidney organoids.

bioinformatics↗

bioRxiv2023

Chronic warming and dry soils limit carbon uptake and growth despite a longer growing season in beech and oak

Progressively warmer and drier conditions impact tree phenology and carbon cycling with large consequences for forest carbon balance. However, it remains unclear how individual impacts of warming and drier soils differ from their combined one and how species interactions modulate tree responses. Using mesocosms, we assessed the multi-year impact of continuous air warming and lower soil moisture acting alone or combined on phenology, leaf-level photosynthesis, non-structural carbohydrate concentrations, and aboveground growth of young European beech and Downy oak trees. We further tested how species interactions (monocultures vs. mixtures) modulated these effects. Warming prolonged the growing season of both species but reduced growth for oak. In contrast, lower moisture did not impact phenology but reduced trees assimilation and growth for both species. Combined impacts of warming and drier soils did not differ from single ones. Performances of both species in the mixtures were enhanced compared to the monocultures under extreme conditions. Our work revealed that higher temperature and lower soil moisture have contrasting impacts on phenology vs. leaf-level assimilation and growth, with the former being driven by temperature and the latter by moisture. Furthermore, we show a compensation of the negative impacts of extreme events by tree species interactions.

physiology↗

bioRxiv2021

Photosynthetic acclimation and sensitivity to short- and long-term environmental changes

O_LIThe future climate will be characterized by an increase in frequency and duration of drought and warming that exacerbates atmospheric evaporative demand. How trees acclimate to long-term soil moisture changes and whether these long-term changes alter trees sensitivity to short-term (day to months) variations of vapor pressure deficit (VPD) and soil moisture is largely unknown. C_LIO_LILeaf gas exchange measurements were performed within a long-term (17 years) irrigation experiment in a Scots pine-dominated forest in one of Switzerlands driest areas on trees in naturally dry (control), irrigated, and irrigation-stop (after 11 years of irrigation) conditions. C_LIO_LISeventeen years of irrigation increased photosynthesis (A) and stomatal conductance (gs) and reduced the gs sensitivity to increasing VPD but not to soil drying. Following irrigation-stop, gas exchange did not decrease immediately, but after three years, had decreased significantly in irrigation-stop trees. Vcmax and Jmax recovered after five years. C_LIO_LIThese results suggest that long-term release of soil drought reduces the sensitivity to atmospheric evaporative demand and that atmospheric constraints may play an increasingly important role in combination with soil drought. In addition, they suggest that structural adjustments lead to an attenuation of initially strong leaf-level acclimation to strong multiple-year drought. C_LI

plant biology↗

bioRxiv2020

Soil nutrient availability alters tree carbon allocation dynamics during drought

Drought alters allocation patterns of carbon (C) and nutrients in trees and eventually impairs tree functioning. Elevated soil nutrient availability might alter the response of trees to drought. We hypothesize that increased soil nutrient availability stimulates root metabolism and carbon allocation to belowground tissues under drought stress. To test this hypothesis, we subjected three-year-old Pinus sylvestris saplings in open-top cambers during two subsequent years to drought using three different water treatments (100%, 20% and 0% plant available water in the soil) and two soil nutrient regimes (ambient and nitrogen-phosphorus-potassium (N-P-K) fertilization corresponding to 5 g N/m2/yr) and released drought thereafter. We conducted a 15N and 13C labelling experiment during the peak of the first-year drought by injecting 15N labelled fertilizer in the soil and exposing the tree canopies to 13C labelled CO2. The abundance of the N and C isotopes in the roots, stem and needles was assessed during the following year. C uptake was slightly lower in drought stressed trees, and extreme drought inhibited largely the N uptake and transport. Carbon allocation to belowground tissues was decreased under drought, but not in combination with fertilization. Our results indicate a potential positive feedback loop, where fertilization improved the metabolism and functioning of the roots, stimulating the source activity and hence C allocation to belowground tissues. This way, soil nutrients compensated for drought-induced loss of root functioning, mitigating drought stress of trees.

plant biology↗