Biology subjects

Müller, L.

Publications and source records attributed to Müller, L..

13 recordsLinked to original sources

bioRxiv2026

Single-cell proteomics resolves major cell populations and protein-defined chondrocyte states in the adult human osteoarthritic joint

Objective Single-cell RNA sequencing has transformed our understanding of cellular heterogeneity within osteoarthritic (OA) joint tissues, yet transcript abundance provides only an indirect measure of cellular phenotype and function. Recent advances in mass spectrometry now enable proteins to be measured directly at single-cell resolution. Here, we applied single-cell proteomics (SCP) to primary human OA cartilage and synovium to determine whether cellular heterogeneity within the diseased joint can be resolved directly at the proteome level. Design Cartilage and synovium were obtained from patients undergoing total knee arthroplasty for OA. Low-input proteomic profiling was first performed to establish proteome depth from limited cell numbers and validate biologically relevant clustering. SCP was then applied to individual cells, followed by unsupervised clustering, differential protein abundance analysis and iterative biological annotation. Results Low-input proteomics identified 7,800 proteins from 1,000 cells while retaining tissue- and cell-associated biological differences. Across the SCP dataset, ~2,300 unique proteins were detected, resolving chondrocyte, synovial fibroblast and immune-cell populations that closely paralleled those previously defined by single-cell transcriptomics. Higher-resolution analysis distinguished lining and sublining fibroblasts, discrete immune populations and multiple protein-defined chondrocyte states. Conclusions SCP enables direct characterisation of cellular heterogeneity within the human OA joint at the level of the proteome. By independently recovering established cellular populations while revealing protein-defined chondrocyte states, our findings establish SCP as a powerful complement to single-cell transcriptomics and open a new route to investigating functional cellular states and disease mechanisms that cannot be inferred from RNA abundance alone.

genetics↗

bioRxiv2026

Aging modifies microstructure and material properties of mineralized cartilage and subchondral bone in the murine knee

The osteochondral junction is a specialized region ensuring the biomechanical and biological integration of the unmineralized articular cartilage with the subchondral bone through an intermediate layer of mineralized cartilage. This location is of clinical relevance, being the target of osteoarthritis. While aging is considered a risk factor for osteoarthritis, the interplay between microstructural and material changes during aging and predisposing to joint degeneration is not fully clear. This is especially true for mineralized cartilage, which remains understudied despite its critical role in load transfer from unmineralized articular cartilage to bone. We investigate age-related alterations of mineralized cartilage and subchondral bone in rat tibiae of adult and aged animals using a multimodal, high-resolution, correlative analysis. Our approach includes micro-computed tomography to measure microstructural features, second harmonic generation imaging to visualize collagen organization, quantitative backscattered electron imaging to map local mineral content, and nanoindentation to obtain mechanical properties. Mineralized cartilage and subchondral bone exhibited distinct age-related modifications. At the architectural level, the subchondral plate thickened and the trabecular network became coarser, those changes being different from those observed in the metaphysis. At the tissue level, mineralized cartilage was less mineralized than bone but exhibits a greater relative increase of mineral content with age, underlying differences in mineralization. A central observation is that aging led to an abrupt transition in mineral content and mechanical properties across the interface between unmineralized and mineralized cartilage, with a conceivable impact on stress localization. Overall, these changes may alter load transfer and contribute to age-related joint degeneration.

bioengineering↗

bioRxiv2025

MALDI-TOF mass spectrometry and proteomics as phenotypic screening tools for anti-inflammatory drugs

Phenotypic screening is a powerful technology to discover drug candidates in physiologically relevant systems without prior knowledge of molecular targets; however, mass spectrometry (MS) remains underutilised as readout strategy. In this proof-of-concept study, we developed and evaluated two complementary MS-based phenotypic screening approaches to identify anti-inflammatory compounds in human induced pluripotent stem cell-derived macrophages and compared them to a conventional targeted cytokine profiling assay. First, we established a novel MALDI-TOF MS fingerprinting strategy that effectively distinguished macrophage phenotypes, identified phenotype-specific biomarkers, and maintained high-throughput capabilities while reducing cost. Secondly, we performed an in-depth LC-MS proteomic analysis using low cell input on an Evosep-timsTOF HT setup, providing rich molecular detail. Both MS-based approaches demonstrated large comparability with the cytokine assay, with a large proportion of hits overlapping. Notably, the proteomics workflow uniquely enabled deeper insight into inflammation pathway engagement, off-target effects, compound potency, and cytotoxicity. Together, these findings highlight the potential of MS-driven phenotypic screening to enhance early drug discovery by enabling efficient, informative, and cost-effective hit selection. O_FIG O_LINKSMALLFIG WIDTH=196 HEIGHT=200 SRC="FIGDIR/small/691706v1_ufig1.gif" ALT="Figure 1"> View larger version (59K): org.highwire.dtl.DTLVardef@c83cb7org.highwire.dtl.DTLVardef@a14d4org.highwire.dtl.DTLVardef@1dda6d7org.highwire.dtl.DTLVardef@f47564_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2025

RNA-seq derived sequence variations are excellent features for cell line identification

1Cell lines are indispensable models for analyzing molecular mechanisms underlying human diseases. However, incorrect annotation and cross-contamination can introduce severe bias in respective studies. Accordingly, various publishers request authentication of cell lines before publication. Short tandem repeat profiling is commonly used to verify cell line identity and purity but does not guarantee that published results are based on the samples tested by this method. In this study, we demonstrate that RNA-seq-derived sequence variation information is eligible for unambiguous cell line-specific clustering. Based on this finding, we propose methods for reliable cell line identification from RNA-seq data using supervised machine learning methods. In addition, we demonstrate the ability to detect cross-contamination of human cell lines. The presented methods are insensitive to different data pre-processing steps and quality measures. The proposed TopFracCCLE algorithm for cell line identification and detection of cross-contamination is available as R-script at https://github.com/HuettelmaierLab/topFracCCLE.

genomics↗

bioRxiv2025

Optimal positioning and size of high-density electrocorticography grids for speech brain-computer interfaces

Speech-based brain-computer interfaces (BCIs) can offer an intuitive means of communication for those who have lost the ability to speak due to paralysis. Significant progress has been made in classifying individual words from high numbers of electrocorticographic (ECoG) electrodes on the sensorimotor cortex (SMC). As implantations of larger grids with more ECoG electrodes are associated with higher surgical risk, we here examined whether confined electrode configurations can match the classification accuracy of larger grids. To this end, we analyzed data from eight able-bodied participants with high-density ECoG grids (64 to 128 electrodes) who performed a task that involved speaking 12 Dutch words. Word pronunciation was associated with changes in high frequency band activity in two SMC foci, one in the ventral SMC and another in the dorsal SMC. Using a combinatorics approach, we found that a smaller, rectangular, configuration with a surface area of 325 mm2 to 561 mm2 (32 electrodes) could achieve a word classification accuracy similar to that of the larger grids: 76{+/-}16% versus 75{+/-}17% across participants, respectively (practical chance level 16.7%). The best configurations were oriented vertically and centered on the central sulcus. These findings indicate that a 32-electrode ECoG grid placed optimally can be sufficient for achieving high word classification accuracy on a closed set of words. We conclude that targeted placement of small ECoG grids can reduce surgical demands on end users and justify energy- and complexity-efficient designs of fully implantable BCI devices for individuals with severe paralysis.

neuroscience↗

bioRxiv2024

Lipidome visualisation, comparison, and analysis in a vector space

A shallow neural network was used to embed lipid structures in a 2- or 3-dimensional space with the goal that structurally similar species have similar vectors. Tests on complete lipid databanks show that the method automatically produces distributions which follow conventional lipid classifications. The embedding is accompanied by the web-based software, Lipidome Projector. This displays user lipidomes as 2D or 3D scatterplots for quick exploratory analysis, quantitative comparison and interpretation at a structural level. Author summaryLipids are not just the basis of membranes. They carry signals and metabolic energy. This means that the presence, absence, and quantity of lipids reflects a cells biochemical state - starving, nourished, sick or healthy. Lipidomics (measuring all lipids in a biological specimen) provides lists of the chemical species and their quantities. We have used a shallow neural network from natural language modelling to embed lipids in a continuous vector space. Firstly, this means that similar molecules have similar positions in this space. Conventional lipid categories cluster automatically. Secondly, the accompanying web-based software, Lipidome Projector imports a lipidome and displays it as a set of points. Reading several lipidomes at once allows quantitative and structural comparisons. Combined with the ability to show structure and abundance diagrams, the software allows exploratory analysis and interpretation of lipidomics datasets.

bioinformatics↗

bioRxiv2022

Efficient SARS-CoV-2 detection utilizing chitin-immobilized nanobodies synthesized in Ustilago maydis

The COVID-19 pandemic has greatly impacted the global economy and health care systems, illustrating the urgent need for timely and inexpensive responses to a pandemic threat in the form of vaccines and antigen tests. The causative agent of COVID-19 is SARS-CoV-2. The spike protein on the virus surface interacts with the human angiotensin-converting enzyme (ACE2) via the so-called receptor binding domain (RBD), facilitating virus entry. The RBD thus represents a prime target for vaccines, therapeutic antibodies, and antigen test systems. Currently, antigen testing is mostly conducted by qualitative flow chromatography or via quantitative ELISA-type assays. The latter mostly utilize materials like protein-adhesive polymers and gold or latex particles. Here we present an alternative ELISA approach using inexpensive materials and permitting quick detection based on components produced in the microbial model Ustilago maydis. In this fungus, heterologous proteins like biopharmaceuticals can be exported by fusion to unconventionally secreted chitinase Cts1. As a unique feature, the carrier chitinase binds to chitin allowing its additional use as a purification or immobilization tag. In this study, we produced different mono- and bivalent SARS-CoV-2 nanobodies directed against the viral RBD as Cts1 fusions and screened their RBD binding affinity in vitro and in vivo. Functional nanobody-Cts1 fusions were immobilized on chitin forming an RBD tethering surface. This provides a solid base for future development of an inexpensive antigen test utilizing unconventionally secreted nanobodies as RBD trap and a matching ubiquitous and biogenic surface for immobilization.

molecular biology↗

bioRxiv2022

GOAT: Deep learning-enhanced Generalized Organoid Annotation Tool

Organoids have emerged as a powerful technology to investigate human development, model diseases and for drug discovery. However, analysis tools to rapidly and reproducibly quantify organoid parameters from microscopy images are lacking. We developed a deep-learning based generalized organoid annotation tool (GOAT) using instance segmentation with pixel-level identification of organoids to quantify advanced organoid features. Using a multicentric dataset, including multiple organoid systems (e.g. liver, intestine, tumor, lung), we demonstrate generalization of the tool to annotate a diverse range of organoids generated in different laboratories and high performance in comparison to previously published methods. In sum, GOAT provides fast and unbiased quantification of organoid experiments to accelerate organoid research and facilitates novel high-throughput applications.

bioinformatics↗

bioRxiv2022

Spectroscopic and QM/MM studies of the Cu(I) binding site of the plant ethylene receptor ETR1

Herein, we present the first spectroscopic characterization of the Cu(I) active site of the plant ethylene receptor ETR1. The X-ray absorption (XAS) and extended X-ray absorption fine structure (EXAFS) spectroscopy presented here establish that ETR1 has a low-coordinate Cu(I) site. The EXAFS resolves a mixed first coordination sphere of N/O and S scatterers at distances consistent with potential histidine and cysteine residues. This finding agrees with the coordination of residues C65 and H69 to the Cu(I) site, which are critical for ethylene activity and well-conserved. Further, the Cu K-edge XAS and EXAFS of ETR1 exhibit spectroscopic changes upon addition of ethylene that are attributed to modifications in the Cu(I) coordination environment, suggestive of ethylene binding. Results from umbrella sampling simulations of the proposed ethylene binding helix of ETR1 at a mixed quantum mechanics/molecular mechanics (QM/MM) level agree with the EXAFS fit distance changes upon ethylene binding, particularly in the increase of the distance between H69 and Cu(I), and yield binding energetics comparable to experimental dissociation constants. The observed changes in the copper coordination environment might be the triggering signal for the transmission of the ethylene response.

biophysics↗

bioRxiv2022

cGAS/STING-DEPENDENT SENSING OF ENDOGENOUS RNA

Defects in nucleic acid metabolizing enzymes lead to spontaneous but selective activation of either cGAS/STING or RIG-like receptor (RLR) signaling, causing a pathogenic type I interferon response and inflammatory diseases. In these pathophysiological conditions, cGAS-driven IFN production is linked to spontaneous DNA damage. Physiological, or tonic, IFN signaling on the other hand is essential to functionally prime nucleic acid sensing pathways. Here we show that low-level chronic DNA damage in mice lacking the Aicardi-Goutieres syndrome gene SAMHD1 reduced tumor-free survival when crossed to a p53-deficient, but not to DNA mismatch repair-deficient background. Increased DNA damage did not result in higher levels of type I interferon. Instead, we found that the chronic interferon response in SAMHD1-deficient mice was driven by the MDA5/MAVS pathway but required functional priming through the cGAS/STING pathway. Our work positions cGAS/STING upstream of tonic IFN signaling and highlights an important role of the pathway in physiological and pathophysiological innate immune priming. SummaryLoss of the dNTPase and DNA repair enzyme SAMHD1 is associated with cancer and causes systemic autoimmunity. We show transformation-promoting spontaneous DNA damage and MDA5-driven but cGAS/STING-dependent chronic type I interferon production in SAMHD1-deficient mice.

immunology↗

bioRxiv2022

Nuclear receptor corepressor 1 controls regulatory T cell subset differentiation and effector function

FOXP3+ regulatory T cells (Treg cells) are key for immune homeostasis. Here, we reveal that nuclear receptor corepressor 1 (NCOR1) controls naive and effector Treg cell states. Upon NCOR1 deletion in T cells, effector Treg cell frequencies were elevated in mice and in in vitro-generated human Treg cells. NCOR1-deficient Treg cells failed to protect mice from severe weight loss and intestinal inflammation associated with CD4+ T cell transfer colitis, indicating impaired suppressive function. NCOR1 controls transcriptional integrity of Treg cells, since effector gene signatures were already upregulated in naive NCOR1-deficient Treg cells while effector NCOR1-deficient Treg cells failed to repress genes associated with naive Treg cells. Moreover, genes related to cholesterol homeostasis including targets of liver X receptor (LXR) were dysregulated in NCOR1-deficient Treg cells. However, genetic ablation of LXR{beta} in T cells did not revert the effects of NCOR1 deficiency, indicating that NCOR1 controls naive and effector Treg cell subset composition independent from its ability to repress LXR{beta}-induced gene expression. Thus, our study reveals that NCOR1 maintains naive and effector Treg cell states via regulating their transcriptional integrity. We also reveal a critical role for this epigenetic regulator in supporting the suppressive functions of Treg cells in vivo.

immunology↗

bioRxiv2021

Population size, density, and ranging behaviour in a key leopard population in the Western Cape, South Africa

Globally, leopards are the most widespread large felid. However, mounting anthropogenic threats are rapidly reducing viable leopard populations and their range. Despite the clear pressures facing this species, there is a dearth of robust and reliable population and density estimates for leopards across their range, which is particularly important in landscapes that consist of protected and non-protected areas. We conducted a camera trapping survey between 2017 and 2018 in the Western Cape, South Africa to estimate the occupancy, density, and population size of a leopard population. Leopards were recorded at 95% of camera trapping sites, which resulted in a high occupancy that showed no significant variation between seasons, habitat types, or along an altitudinal gradient. Our results indicated a low leopard density in the study area, with an estimated 1.53 leopards/100 km2 in summer and 1.62 leopards/100 km2 in winter. Mean leopard population size was therefore estimated at 107 and 113 individuals in the winter and summer respectively. Leopard activity centres for female ranges were centred in the core study area and could be predicted with good certainty, while males appeared to move out of the study area during winter which resulted in a higher uncertainty in locations of activity centres. Interestingly, livestock depredation events in the surrounding farmlands were significantly higher in winter, which coincides with male leopards moving outside the core protected area into the surrounding farmlands. To reduce livestock losses and retaliatory leopard killings, we suggest that human-carnivore conflict mitigation measures be intensely monitored during the winter months in the study area. We also suggest that future leopard conservation efforts should focus on privately-owned land as these non-protected areas contain the majority of the remaining suitable leopard habitat and may provide important dispersal corridors and buffer zones on which the long-term sustainability of leopard populations depends.

ecology↗

bioRxiv2019

Differential effects of day-night cues and the circadian clock on the barley transcriptome

The circadian clock is a complex transcriptional network that regulates gene expression in anticipation of the day-night cycle and controls agronomic traits in plants. However, in crops, information on the effects of the internal clock and day-night cues on the transcriptome is limited. We analysed the diel and circadian leaf transcriptomes in the barley cultivar Bowman and derived introgression lines carrying mutations in EARLY FLOWERING 3 (ELF3), LUX1, and EARLY MATURITY 7 (EAM7). Mutations in ELF3 and LUX1 abolished circadian transcriptome oscillations under constant conditions, whereas eam7 maintained oscillations of {approx}30% of the circadian transcriptome. However, day-night cues fully restored transcript oscillations in all three mutants and thus compensated for a disrupted oscillator in the arrhythmic barley clock mutants elf3 and lux1. Nevertheless, elf3 but not lux1 affected the phase of the diel oscillating transcriptome and thus the integration of external cues into the clock. Using dynamical modelling, we predicted a structure of the barley circadian oscillator and interactions of its individual components with day-night cues. Our findings provide a valuable resource for exploring the function and output targets of the circadian clock and for further investigations into the diel and circadian control of the barley transcriptome.

plant biology↗