Biology subjects

Mueller, J.

Publications and source records attributed to Mueller, J..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Enhancing experimentally the structural heterogeneity of forests increase soil fungal diversity but functional lifestyles in contrasting ways

Fungal communities in soils are highly diverse both in species and functions forming a major backbone of forest ecosystems. Recent observational high-throughput-sequencing studies have shown that fungal diversity is correlated with resource availability and climate across different spatial scales. However, the underlying mechanisms remain poorly understood. Across Germany, we experimentally manipulated 11 typically homogeneous, broadleaf production forests to increase their between-patch-heterogeneity (ESBC) and compared them with a control forest. In specific, we enhanced light availability via canopy openness and deadwood resources in the ESBC treatments. Fungal communities were determined by metabarcoding at 234 patches and analysed using a novel meta-analytical approach for pairwise comparisons of taxonomic and phylogenetic diversity along Hill numbers. We hypothesized that {gamma}-diversity is primarily driven by {beta}-diversity increasing with canopy mediated microclimate variability and secondarily by -diversity increasing with resource availability. Furthermore, we expected an increase in {gamma}-diversity by unique phylogenetic lineages supporting the insurance hypothesis. Our results showed a significant increase in {gamma}-diversity in ESBC forests, first by - and second by {beta}-diversity, both of which were influenced mainly by microclimate and not resource availability. The increase of phylogenetic diversity with ESBC was weak indicating functional similarity of species. Analysis of symbiotic, saprotrophic and parasitic fungal assemblages revealed contrasting effects of resource availability and microclimate across the scales. As in the UN Decade of Ecosystem Restoration many forest managers aim to increase the heterogeneity of forests and are simultaneously face rising tree mortality, our study provides first robust empirical evidence for the varying effects of forest gaps and deadwood on fungal diversity across -, {beta}-, {gamma}-scales for this major kingdom.

ecology↗

bioRxiv2025

Temperate forest heterogeneity decreases local and landscape-scale spider diversity through habitat filtering despite species turnover

O_LISpiders are key components of forest food webs, making use of the three-dimensional forest structure. Yet modern silviculture has homogenized temperate forest structure at local and landscape scales. The consequences of this homogenization for landscape-level spider diversity, however, remain largely unknown. C_LIO_LITherefore, we sampled spiders using pitfall traps across 234 patches in a large-scale, replicated field experiment at 11 paired European beech (Fagus sylvatica) forest sites in Germany. In one district per site, we experimentally diversified between-forest-patch complexity (ESBC) through canopy gap creation and deadwood enrichment and kept a second district untreated as a structurally homogeneous control. C_LIO_LIWe applied a novel meta-analytic framework to compare -, {beta}-, and {gamma}-diversity of spiders between treatment and control districts, standardized for sample coverage, along Hill numbers giving increasing weight to abundance and for taxonomic, functional, and phylogenetic diversity. To gain a deeper insight into the effects of our intervention on the processes affecting the assembly of spider communities, we investigated the response of functional-phylogenetic diversity quantified by standardized effect sizes of mean pairwise distances (SES MFPD) to our treatments. C_LIO_LIBased on 18,540 spider individuals from 206 species, treatment districts exhibited significantly lower {gamma}- and -diversity across all diversity facets and Hill numbers, particularly when focusing on rare species (q = 0). In contrast, {beta}-diversity increased in treatment districts for phylogenetic and functional diversity across all Hill numbers (q = 0, 1, 2). Although spider abundances were higher in treatment patches, functional-phylogenetic diversity decreased in gaps and ESBC districts in general, indicating a shift from limiting similarity towards habitat filtering. C_LIO_LIOur findings corroborate earlier results of high abundances but lower taxonomic and functional diversity in canopy gaps due to strong habitat filtering effects, resulting in overall lower -diversity, which cannot be compensated by increasing {beta}-diversity. Hence, the greater three-dimensional complexity of homogeneous forests supports more diverse spider metacommunities at the {gamma}-scale, particularly when controlling for sample coverage, suggesting that canopy spider diversity in temperate forests may be underestimated. Nonetheless, higher abundances in treatment districts point to increased predator pressure and greater prey availability in structurally diversified forests. C_LI

ecology↗

bioRxiv2025

Higher bat and bird γ-diversity in structurally complex forests is driven by distinct α- and β-diversity responses

Effective conservation management and habitat restoration rely on understanding how biodiversity responds to environmental change. Centuries of silviculture have homogenized forests and their species communities globally, reducing biodiversity. To test whether restoring forest structural complexity can promote biodiversity, we conducted a large-scale, spatially explicit landscape experiment. At 11 sites across Germany, we compared bat and bird diversity in forests with experimentally enhanced heterogeneity by increasing deadwood and canopy complexity to homogeneous production forests. Both taxa were investigated by autonomous acoustic recorders and automatic species identification. We quantified within-patch (-), between-patch ({beta}-), and landscape-level ({gamma}-) diversity, emphasizing infrequent to highly frequent species for taxonomic, functional, and phylogenetic diversity. The pairwise comparisons of the sites were synthesized using a newly developed meta-analysis of rarefaction-extrapolation curves. {gamma}-diversity increased significantly in structurally heterogeneous forests for both taxa, albeit through distinct taxon-specific mechanisms. Bat {gamma}-diversity gains were primarily driven by higher {beta}-diversity, indicating greater dissimilarity in species assemblages among patches, while bird {gamma}-diversity increased via higher -diversity within patches. Bat diversity increases were mainly taxonomic, suggesting functional similarity in the communities, whereas birds showed the highest gains in functional diversity, indicating that experimental treatments resulted in greater trait dissimilarity. Our results provide experimental evidence under real-world conditions that {gamma}-diversity can be shaped by different diversity mechanisms. These patterns likely originate from differences in activity ranges, such as the large-scale movements of foraging bats in contrast to the more spatially restricted, territorial behavior of birds. This highlights the need for taxon-specific restoration strategies in homogenized landscapes.

ecology↗

bioRxiv2025

A continuum of information-based temporal stability measures and their decomposition across hierarchical levels

When biodiversity-stability relationships are assessed from temporal patterns of species (or species assemblages) biomass or other key variables, ecological stability is commonly quantified as the inverse of the coefficient of variation (CV) or its square. However, just as biodiversity cannot be fully characterized by a single value, the complexity of temporal stability/invariability cannot be completely captured by one metric, especially since CV is disproportionally sensitive to large data values. Ecologists now recognize that species diversity can be fully characterized by a continuum of Hill-number-based measures parametrized by a diversity order q[≥]0, which determines the sensitivity of the measure to species abundance. Building on the intuitive concept that temporal stability can be quantified by the closeness between the data vector and the ideally maximally stable vector, we propose a continuum of information-based measures of temporal stability/invariability parameterized by an order q>0. This continuous parameter q determines the sensitivity of the measure to the magnitude of biomass or other ecosystem functions. By varying q, researchers can differentially weight small, medium, or large values in a time series, thereby disentangling their respective contributions to stability. Our framework unifies and generalizes classical measures: the case q=1 links to Shannon entropy, reflecting MacArthurs 1955 stability concept; q=2 connects to the conventional CV-based measure. Unlike these traditional metrics, our approach explicitly accounts for the number of data values (i.e., time points), adjusting for time-series-length effects to enable fair and meaningful comparisons across datasets of varying lengths. We extend the framework to hierarchical structures by developing additive and multiplicative decompositions of stability in a metacommunity (or metapopulation) into alpha and beta components. The beta component can be further used to obtain measures that quantify (a)synchrony among communities (or populations). For q=2, the resulting (a)synchrony measure provides a mathematically rigorous, CV-based metric. The proposed measures are illustrated using 22-year biomass time series data from the Jena Experiment in Germany. We developed the R package iSTAY (information-based stability measures) and online tools for computation and visualization. Our measures are adaptable to other functions beyond biomass and are applicable in both temporal and spatial contexts. Open Research StatementThe original biomass data of the Jena Experiment, covering the years 2003 to 2023, can be retrieved from https://jexis.idiv.de/ddm/Data/ShowData/624, while the 2024 data are available at https://jexis.idiv.de/ddm/Data/ShowData/695. These datasets, along with the R code used in this study, are currently accessible on Github at https://github.com/AnneChao/MS_iSTAY for review purposes and will be archived on Zenodo upon journal acceptance.

ecology↗

bioRxiv2025

Cultivation in a Natural Microbial Community Enhances the Industrial Performance of a Genetically Engineered Cyanobacterium for Bioplastic Production

Large-scale production of polyhydroxybutyrate (PHB), a biodegradable bioplastic, using genetically engineered cyanobacteria offers a sustainable alternative to petrochemical-derived plastics. However, monoculture-based phototrophic systems face major limitations, such poor resilience in large-scale reactors, hindering industrial upscaling. To address these challenges, we established a hybrid photosynthetic microbiome by replacing the native cyanobacterium of a natural microbial consortium with a genetically engineered Synechocystis strain optimized for PHB production. This new community retained the ecological structure and stability of the original microbiome while gaining synthetic production capacity. Compared to the axenic strain, the hybrid system exhibited enhanced robustness under abiotic stress, including light and temperature fluctuations, and improved tolerance to operational instability. These features made it suitable for upscaling and application in non-sterile environments. The hybrid microbiome sustained PHB production in scaled photobioreactors, reaching up to 32% PHB per cell dry weight (CDW) equal to [~]230 mg L-1 under fully photoautotrophic conditions. Production was also achieved under dark conditions with acetate supplementation, highlighting the systems metabolic flexibility. This work demonstrates the successful integration of an engineered phototroph into a stable native microbiome, positioning hybrid communities as powerful platform for industrial biotechnology.

microbiology↗

bioRxiv2025

Inconsistent short-term effects of enhanced structural complexity on soil microbial properties across German forests

Structural and biotic homogenization can result from forestry practices that lack promotion of canopy gaps and deadwood. This can lead to biodiversity loss and impaired ecosystem functions. Enhancing structural complexity (ESC) has been proposed to counteract these effects, but its impact on soil properties remains insufficiently understood. Overall, we hypothesize that ESC enhances soil abiotic properties, their spatial variability, and microbial functioning, with effects modulated by environmental context and increasing over time. Data were collected from 148 patches (50 x 50 m) in eight beech forests across Germany. In half of the patches, structural complexity was enhanced by felling 30% of the basal area of living trees through two spatial patterns--aggregated (one large gap) and distributed (small gaps)--combined with leaving or removing deadwood (stumps, logs, and snags). The other half served as controls, representing typically managed, homogeneous production forests. Soil C:N, C%, and N% increased near deadwood. Soil microbial biomass and activity were significantly affected in three of eight forest sites, with effects ranging from -30% to +62%. Higher soil water content was associated with increased microbial biomass, and greater understorey biomass correlated with a lower microbial respiratory quotient. No temporal trends were observed over five years. Although soil properties showed resistance to structural interventions, site-specific effects underline the importance of soil moisture and the understorey vegetation for microbial functioning. Further research building on our results is needed to develop practical forest management strategies to clarify how structural complexity may support soil functioning and ecosystem resilience. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=127 SRC="FIGDIR/small/664741v1_ufig1.gif" ALT="Figure 1"> View larger version (53K): org.highwire.dtl.DTLVardef@10790f2org.highwire.dtl.DTLVardef@1bd2f95org.highwire.dtl.DTLVardef@17eed6dorg.highwire.dtl.DTLVardef@15a049_HPS_FORMAT_FIGEXP M_FIG C_FIG Highlights- Deadwood addition increases soil C%, N%, and the soil C:N ratio - Enhanced structural complexity alters soil microbial properties in site-specific ways - Soil water content changes are linked to shifts in microbial biomass - Understorey biomass changes are linked to shifts in the respiratory quotient

ecology↗

bioRxiv2025

Natural Product-Like Fragments Unlock Novel Chemotypes for a Kinase Target - Exploring Options beyond the Flatland

In this study we utilized a high-performance soaking system of protein kinase A (PKA) to perform a crystallographic screening of a natural product-like fragment library. We resolved 36 fragment-bound structures, corresponding to a hit rate of 41%. Nine fragments bound within the ATP site, nine peripherally, and 18 interacted with both the ATP and peripheral sites. One fragment binds to the same site as the approved allosteric kinase inhibitor asciminib, while another induces an unexpected conformational change. Systematic database mining revealed that both the fragments and their natural product parents have not been previously associated with PKA or kinase activity. A scaffold/chemotype analysis further underscored their novelty. Cheminformatics analyses confirmed that these fragments occupy a distinct chemical space, enriched in saturation, spatial complexity and molecular three-dimensional character compared to kinase binders from reference datasets. These properties have previously been linked to increased selectivity, reduced CYP450 inhibition, and higher overall clinical success rates. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/659015v4_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1643255org.highwire.dtl.DTLVardef@124a28eorg.highwire.dtl.DTLVardef@2c4033org.highwire.dtl.DTLVardef@12ae4c5_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2025

PAK1 activation drives divergent resistance mechanisms to aromatase inhibition and Tamoxifen in a luminal A breast cancer model

Breast cancer is the most frequent malignancy and the second leading cause of cancer-related mortality in women worldwide, and is a heterogeneous disease regarding driver mechanisms, therapies, and outcome. Estrogen receptor-positive (ER+) tumors are treated with endocrine therapies such as Tamoxifen or aromatase inhibitors (AI), aimed at disrupting tumor-promoting estrogen signaling. While these therapies are initially effective, resident tumor cells can develop resistance, leading to relapse. The p21-activated kinase 1 (PAK1) is a key regulator of multiple oncogenic signaling pathways and has been implicated in resistance to Tamoxifen. However, it remains unclear, whether PAK1 also affects the response to other endocrine therapies. Using global phosphoproteomic profiling of endocrine resistant cell line models, we observed elevated PAK1 activity in cells resistant to Tamoxifen and to estrogen deprivation, respectively, with further increases following EGF stimulation. Pharmacological inhibition of PAK1 effectively reduced cell proliferation in both resistance models, however, with distinct effects on PAK1 downstream substrates and pathways. In the Tamoxifen resistance context, PAK1 reduces apoptosis via inhibition of the pro-apoptotic protein BAD, whereas in the AI resistance model PAK1 rather triggers proliferation via RAF1. Our findings position PAK1 as a common mediator of resistance to different endocrine therapies and offer insights into the distinct signaling networks that are involved. In summary, our results suggest that targeting PAK1 may present a novel therapeutic strategy to overcome endocrine therapy resistance in ER+ breast cancer, potentially enhancing the efficacy of both Tamoxifen and AI treatments.

cancer biology↗

bioRxiv2025

Acoustic indices predict recovery of tropical bird communities for taxonomic and functional composition

Quantifying the success of biodiversity restoration is a major challenge in the UN Decade on Ecosystem Restoration. We evaluated the potential of acoustic indices to predict the recovery success of bird communities within abandoned agricultural areas. Using audio recordings from a lowland tropical forest region, we identified 334 bird species and calculated established acoustic indices. Community composition was analyzed using Hill numbers, accounting for incomplete sampling. Acoustic indices effectively predicted independent species data (R2 = 0.59-0.76), capturing not only taxonomic but also functional and phylogenetic composition. Taxonomic composition was best predicted for common and dominant species, while functional and phylogenetic compositions were more accurately predicted for rare and common species. In addition, community composition was strongly influenced by the surrounding habitat. Our findings demonstrate that a small set of acoustic indices, once validated by stratified ground truth data, provides a powerful tool for assessing restoration success over large tropical areas, even for functional composition of rare tropical birds.

ecology↗

bioRxiv2025

Mitochondrial DNA heteroplasmy drives cortical neuronal disturbances in human organoids harbouring the common m.3243A>G mutation

Mitochondrial diseases frequently affect the brain leading to severe and disabling neurological symptoms. The heteroplasmic m.3243A>G mutation in MT-TL1, encoding mt-tRNALeu, is responsible for [~]80% of mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS), which is one of the most characteristic mitochondrial syndromes, leading to disability and early death. There are no animal models harbouring this mutation to provide precise mechanistic insights informing therapeutic interventions. Here, we generated a human iPSC-derived cerebral organoid slice model that recapitulates cortical architecture and mitochondrial pathology. Using biological assays and single-cell RNA sequencing, we uncovered heteroplasmy-dependent transcriptional shifts and changes in key cellular processes in cortical neurons. Organoids with high heteroplasmy showed a predominant impairment of deep-layer neurons triggered by mitochondrial stress, leading to axonal degeneration and apoptosis, similar to brain autopsy of a MELAS patient. Our findings provide insights into the vulnerability of long-range projection neurons in mitochondrial diseases, advancing our understanding of disease mechanisms with a view to potential therapeutic strategies.

neuroscience↗

bioRxiv2025

Prenatal DEHP plastic chemical exposure increases the likelihood of child autism and ADHD symptoms through epigenetic programming

Increasing evidence implicates prenatal exposure to di-(2-ethylhexyl) phthalate (DEHP), a common endocrine-disrupting plastic chemical, in autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD). However, the underlying mechanisms are poorly understood. Here we examined whether cord blood DNA methylation, a key epigenetic marker, mediates the association between prenatal DEHP exposure and ASD/ADHD symptoms in 847 children enrolled in the Barwon Infant Study. ASD and ADHD are complex phenotypes characterised by differences at the gene regulatory network and neuronal circuit level, where heterogeneous genetic and environmental risk factors converge. Accordingly, we employed a data-driven computational strategy that helped elucidate broader functional epigenetic signatures of ASD and ADHD elicited by DEHP exposure. This included (1) a methylation profile score for DEHP exposure (MPSDEHP), and (2) an analysis of co-methylated gene networks. Causal mediation analysis demonstrated that both MPSDEHP and a DEHP-associated network of co-methylated genes mediated the effect of DEHP exposure on increased ASD and ADHD symptoms at ages 2 and 4 years (proportion of effect mediated ranged from 0.21 to 0.80). The co-methylation network was enriched for neural cell-type markers, ASD risk genes (including FOXP1, SHANK2, and PLXNB1), and targets of endocrine receptors previously linked to DEHP (including targets of the estrogen receptor ER and the glucocorticoid receptor GR), providing biological plausibility. We validated key results in independent blood (n=66) and postmortem brain (n=40) DNA methylation datasets. These findings provide mechanistic evidence linking DEHP to ASD and ADHD symptoms and reinforce growing concerns regarding the risks of prenatal exposure.\n\nSignificanceExposure to endocrine-disrupting plastic chemicals has been linked to adverse neurodevelopment, but the underlying biological mechanisms remain unclear. We demonstrate that prenatal exposure to di-(2-ethylhexyl) phthalate (DEHP), a common plasticizer, increases autism and ADHD symptoms through alterations in DNA methylation, a key epigenetic regulator of gene activity. Using birth cohort data, we identify epigenetic signatures of prenatal DEHP exposure, including alterations in an endocrine-related co-methylation network enriched for neural cell-type markers and known autism-associated genes. These signatures mediate the effects of DEHP on autism and ADHD symptoms and are also associated with autism in external blood and postmortem-brain datasets, providing independent validation. This causal evidence further underscores concerns regarding the consequences of prenatal plastic-chemical exposure on the developing brain.

neuroscience↗

bioRxiv2025

Ultrasensitive fitness costs arise from membrane proteome displacement under protein overexpression

Protein overexpression is crucial in many diseases and can lead to antibiotic resistance by increasing the expression of drug targets or resistance genes, such as membrane-localized efflux pumps. Using a high-throughput colony-imaging technique, we performed a quantitative genome-wide study of protein overexpression in Escherichia coli. Our results show that most membrane proteins impose steep overexpression costs, leading to an abrupt growth collapse beyond a critical expression threshold. By manipulating synthetic membrane proteins to target different translocation pathways, we ruled out saturation of these pathways as the cause of these fitness costs. Instead, we found that the growth collapse is driven by the displacement of endogenous membrane proteins, which we show directly using single-cell time-lapse imaging with fluorescently tagged membrane proteins in a microfluidic device. Displacement of as little as 10% of the membrane proteome trapped most bacteria in a non-growing state. Our findings enhance the quantitative understanding of expression costs, with implications for antibiotic resistance and the biotechnological production of membrane proteins.

systems biology↗

bioRxiv2025

A short cut to sample coverage standardization in meta-barcoding data provides new insights into land use effects on insect diversity

The use of metabarcoding for insect species identification has grown rapidly, but the absence of abundance data hinders meaningful diversity metrics like sample coverage-standardized species richness. Additionally, the vast number of taxa often lacks a unified phylogeny or trait database. We present a framework for constructing a phylogenetic tree encompassing the majority of insect families, standardisation of sample coverage (an objective measure of sample completeness) and assessment of both taxonomic and phylogenetic diversity using the Hill series for metabarcoding data. Applied to central Europe, our framework analysed insect diversity from 400 families along a land-use gradient. Results revealed land-use intensity significantly affects sample coverage, emphasizing the need for biodiversity standardization. After standardization, taxonomic diversity declined by 27-44%, and phylogenetic diversity by 13-29% across 39,000 Operational Taxonomic Units, from forests to agricultural areas. Rare species exhibited greater phylogenetic diversity loss than taxonomic, while dominant species showed smaller phylogenetic losses but stronger declines in taxonomic diversity. Our findings underscore agricultures detrimental effects on specific insect taxa, even after adjusting for sample coverage, and provide new insights into the loss of functional diversity, as represented by phylogeny.

ecology↗

bioRxiv2024

Quantification of CAR T cell performance against acute myeloid leukemia using Bayesian inference

Chimeric Antigen Receptor (CAR) T-cell therapy has transformed cancer immunotherapy by genetically engineering T-cells to target tumor antigens. Acute myeloid leukemia (AML) presents unique challenges due to resistance mechanisms, especially in patients with TP53 loss mutations. The complex dynamics of CAR T-cell expansion remain poorly understood. The field lacks validated quantitative frameworks to systematically evaluate different CAR T-cell target constructs, such as CD33, CD123, and CD371, against resistant AML variants. We address this gap by combining mathematical modeling with in vitro assay data and Bayesian inference. We select, train, and validate a two-compartment deterministic mathematical model that describes the nonlinear dynamics of target AML and CAR T cells, accounting for expansion, killing, and exhaustion. Using Bayesian inference, we train and select the best-performing functional form for CAR T expansion and then validate it on unseen data. Our framework selects a CAR T-cell expansion model that accounts for handling time and T-cell self-interference, highlighting that expansion is a dynamic process in which target-cell handling time and T-cell crowding negatively affect T-cell expansion. Analysis of posterior parameter distributions reveals target-antigen-specific responses against TP53-deficient AML. For instance, CD33-targeting CARs have reduced attack rates against TP53-deficient cells, while CD123- and CD371-targeting CARs show moderately increased attack rates; however, the former exhibit higher death rates, and the latter have increased handling times, impeding efficacy. This target-dependent form of resistance challenges the assumption of uniform performance and reveals a unifying nonlinear expansion model for integrated, yet antigen-specific, preclinical predictions of efficacy. Short SummaryWe identified the target antigen-specific expansion properties and the efficacy of CAR T cells against TP53 wild-type and deficient AML by integrating experimental data from cytolytic assays, mechanistic mathematical modeling, and Bayesian inference.

cancer biology↗

bioRxiv2024

BioStructNet: Structure-Based Network with Transfer Learning for Predicting Biocatalyst Functions

Enzyme-substrate interactions are essential to both biological processes and industrial applications. Advanced machine learning techniques have significantly accelerated biocatalysis research, revolutionizing the prediction of biocatalytic activities and facilitating the discovery of novel biocatalysts. However, the limited availability of data for specific enzyme functions, such as conversion efficiency and stereoselectivity, presents challenges for prediction accuracy. In this study, we developed BioStructNet, a structure-based deep learning network that integrates both protein and ligand structural data to capture the complexity of enzyme-substrate interactions. Benchmarking studies with the different algorithms showed the enhanced predictive accuracy of BioStructNet. To further optimize the prediction accuracy for the small dataset, we implemented transfer learning in the framework, training a source model on a large dataset and fine-tuning it on a small, function-specific dataset, using the CalB dataset as a case study. The model performance was validated by comparing the attention heat maps generated by the BioStructNet interaction module, with the enzyme substrate interactions revealed by enzyme-substrate complexes revealed from molecular simulations. BioStructNet would accelerate the discovery of functional enzymes for industrial use, particularly in cases where the training datasets for machine learning are small.

bioinformatics↗

bioRxiv2024

Altered Hormone and Bioactive Lipid Plasma Profile in Rodent Models of Polycystic Ovarian Syndrome Revealed by Targeted Mass Spectrometry

Polycystic ovarian syndrome (PCOS) symptoms include excessive body or facial hair, irregular periods, reduced fertility, and reoccurring pregnancy loss. Hyperandrogenism and chronic inflammation are hallmarks of PCOS, which is diagnosed by analysing steroid hormones in the blood. Studies suggest that bioactive lipids are contributing to chronic inflammation. To research PCOS, animal models, such as letrozole- and dihydrotestosterone-treated rats, are used. They display similar ovarian and metabolic characteristics, although plasma lipid profiles have not been determined. Therefore, in order to validate the use of these models for PCOS, we have optimised a mass spectrometry based targeted lipidomics workflow which increases the sensitivity of measuring these lipids in rat plasma. Our analysis shows that letrozole caused a significant elevation of 5-androstene-3,17-dione and testosterone. Dihydrotestosterone treatment resulted in increased dehydroepiandrosterone-sulphate and allopregnanolone but a reduction in testosterone, progesterone, pregnenolone, and D-sphingosine. In both models 25-hydroxycholesterol and leukotriene C4 were significantly diminished and 4-cholesten-3-one was significantly increased, and these particular metabolites are not known to be changed in human PCOS. These results suggest that the plasma lipids of these rodent models have some changes akin to human PCOS and other changes that are not.

biochemistry↗

bioRxiv2024

Protonation effects in protein-ligand complexes - a case study of endothiapepsin and pepstatin A with computational and experimental methods

1Protonation states serve as an essential molecular recognition motif for biological processes. Their correct consideration is key to successful drug design campaigns, since chemoinformatic tools usually deal with default protonation states of ligands and proteins and miss atypical protonation states. The protonation pattern for the Endothiapepsin/PepstatinA (EP/pepA) complex is investigated using different dry lab and wet lab techniques. ITC experiments revealed an uptake of more than one mole of protons upon pepA binding to EP. Since these experiments were performed at physiological conditions (and not at pH=4 at which a large variety of crystal structures is available), a novel crystal structure at pH=7.6 was determined. This crystal structure showed that only modest structural changes occur upon increasing the pH value. This lead to computational studies to reveal the exact location of the protonation event. Both computational studies could reveal a significant pKa shift resulting in non-default protonation state and that the catalytic dyad is responsible for the uptake of protons. This study shows that assessing protonation states for two separate systems (protein and ligand) might result in the incorrect assignment of protonation states and hence incorrect calculation of binding energy.

molecular biology↗

bioRxiv2024

Salicylic Acid restricts cell elongation and induces changes of vacuolar morphology and pH

The phytohormone salicylic acid (SA) is a key factor to balance plant defence as well as growth and development. While its role in plant defence has been investigated for decades, regulation of plant growth and development has only come into focus recently. It has been demonstrated that SA application inhibits growth independently of the established Non-expressor of Pathogenesis Related (NPR) receptors. However, the underlying mechanism of this growth inhibition on the cellular level remains largely elusive. Here we show that SA restricts cell elongation and induces changes of vacuolar morphology and pH. Rapidly upon SA application we observe homotypic vacuole fusion and a significant increase in vacuolar pH. These changes seem to be independent of the phytohormone auxin which has been reported to crosstalk with SA. By increasing vacuolar pH, SA directly impacts basic cellular functions such as vesicle trafficking or nutrient storage, leading eventually to cell size restriction and limited growth. Our results demonstrate an NPR-independent mechanism to attenuate growth, potentially allowing free resources to be relocated to withstand environmental stresses. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=90 SRC="FIGDIR/small/611645v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@af7652org.highwire.dtl.DTLVardef@1813f64org.highwire.dtl.DTLVardef@68e2e8org.highwire.dtl.DTLVardef@92a13_HPS_FORMAT_FIGEXP M_FIG C_FIG Salicylic Acid (SA) triggers a reduction in cell size and leads to a spherical vacuolar phenotype. This morphological change is accompanied by an increase in vacuolar pH, potentially due to the enhanced activity of a glycosylated SA (SAG) H+-antiporter and/or the inhibition of V-ATPase activity. In addition, SA disrupts the polarity of PIN2 auxin transporters, resulting in their uniform distribution across the cell membrane.

plant biology↗