Biology subjects

Schneider, M.

Publications and source records attributed to Schneider, M..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Mammalian RAVE couples V-ATPase assembly to organelle acidification and function

Acidification of lysosomes, endosomes, and the Golgi underpins organelle-specific functions within the endomembrane system. This process is driven by vacuolar-type H-ATPases (V-ATPases), which reversibly assemble from peripheral V and membrane-integral V domains to regulate organelle pH. In yeast, V-V assembly at the vacuole is mediated by the RAVE complex, but V-ATPase assembly in mammalian cells remains less well understood. Here, we systematically define physiological roles of mammalian RAVE. Under basal conditions, mRAVE broadly promotes V-ATPase assembly and organelle acidification. Upon mTORC1 inactivation, mRAVE is recruited to lysosomes and required for the resulting increase in V-ATPase assembly and catabolic activity. Loss of mRAVE disrupts organelle acidification, leading to suppression of lysosomal catabolism, accumulation of dysfunctional lysosomes and compensatory lysosomal exocytosis. Restoring lysosomal pH rescues basal function in mRAVE-deficient cells but not the mTORC1-regulated increase in catabolic activity. Thus, mRAVE is an essential V-ATPase assembly factor that couples acidification to organelle function and nutrient signaling.

cell biology↗

bioRxiv2025

Internally twin-Strep tagged CD63 for rapid and efficient isolation of engineered extracellular vesicles encapsulating functional proteins

Extracellular vesicles (EVs) are important mediators of intercellular communication. Achieving high purity of intact engineered EVs through separation from the overwhelming background of unmodified vesicles and cellular or serum-derived contaminants remains a major challenge, yet is critical for fundamental studies of EV biology and EV-based therapeutics. To address this unmet need, we applied structure-guided engineering to canonical EV tetraspanins. Focusing on CD63 and CD9, we identified sites for internal insertion of the twin-Strep tag via flexible linkers into unstructured regions of their large extracellular loops. This design retains functional properties of the scaffolds while providing a robust molecular handle enabling rapid, efficient, and selective antibody-free affinity-based isolation of intact EVs using advanced Strep technology. Fusing proteins of interest (POIs) to the C-terminus of these scaffolds, either directly or via a photoactivatable protein, allowed POI loading into the lumen of twin-Strep tagged EVs with optional optogenetic control of POI release. Proteomic analysis confirmed the high purity of captured engineered EVs with >96% of contaminants removed, enabling sensitive detection of numerous EV-associated proteins. We also report the efficient removal of contaminating virus particles resembling EVs in size and density. Purified engineered EVs successfully delivered an encapsulated fluorescent reporter into target cells, bypassing dye labeling commonly used to track EVs. We demonstrate endosomal escape of the reporter, facilitated by EV decoration with vesicular stomatitis virus glycoprotein, and cytoplasmic release upon optogenetic activation. Our toolbox may serve as a broadly applicable strategy for the efficient production of intact and highly pure engineered EVs to support potential fundamental or translational EV studies.

molecular biology↗

bioRxiv2025

SAME: Topology-flexible transforms enable robust integration of multimodal spatial omics

Spatial omics technologies provide complementary and layered molecular insights that span proteins, transcripts, and metabolites. However, aligning and integrating these modalities across serial tissue sections remains a computational challenge. Existing alignment methods are primarily unimodal and assume preserved topology, often failing with tissue distortions like tears, folds, or anatomical changes. Here, we present SAME (Spatial Alignment of Multimodal Expression) that introduces space-tearing transforms, a framework for controlling localized topological disruptions during cross-sectional alignment. Using integer linear programming to maximize cell type matches across the modalities, we enhance cell-type alignment accuracy by 20% compared to existing methods while preserving biologically meaningful spatial relationships. Applied to protein-RNA integration in healthy tongue tissue and lung adenocarcinoma, SAME revealed cryptic immune subpopulations that were otherwise missed by RNA-only or protein-only classification. In a separate lung adenocarcinoma study, we assayed and integrated protein and metabolomic profiles, uncovering localized mevalonic acid upregulation specifically within tumor-macrophage spatial niches and identifying targeted metabolic crosstalk invisible to single-modality approaches. SAME enables unprecedented experimental designs that leverage each modality independently while computationally recovering cross-modal spatial structure, unlocking multimodal discoveries in complex tissues.

bioinformatics↗

bioRxiv2025

Invasive species drive polymicrobial resistance to amoxicillin in oral biofilms through beta-lactamase release

Since bacterial biofilms often cause refractory infections, antimicrobial susceptibility testing (AST) is highly desirable even for oral peri-implant biofilms. However, characterization of polymicrobial drug resistance is challenging due to high diversity and complexity of these biofilms. In this work, we developed laser-assisted AST and detected polymicrobial amoxicillin resistance in peri-implantitis. TEM-1 {beta}-lactamase production enabled an Enterobacter sp. strain SPS_532 to protect its otherwise susceptible biofilm cohabitants. To understand the {beta}-lactamase driven cross-protection in the human microbiome we aggregated genomic (n = 200,000) and patient microbial data (n = 27,000), developed a cross-protection assay, studied a representative strain collection (n = 118) and established a complex biofilm in vitro model (with an average of 133 species from 164 found in dental plaque). Multiple oral allochthonous species, e.g., Enterobacter, Klebsiella, Escherichia, Staphylococcus, and only a single typical oral microorganism, Haemophilus, were able to cross-protect. Diverse bla genes conferred activity, via a high expression of chromosomal gene, e.g., blaAmpC gene or by the presence of plasmidic gene, e.g., blaTEM-1 gene. Invaders not only cross-protected the biofilm from the antibiotic, but also supported expansion of opportunistic pathogens like Fusobacterium species. Cross-protection in complex biofilms depended on the diffusion rate and population size of the invader, which could be bio-controlled with a phage. Deciphering polymicrobial resistance might support the development of diagnostic and therapeutic approaches to combat implant-associated biofilm infections in the human mouth.

microbiology↗

bioRxiv2025

Human chronic inflammation is orchestrated by spatially restricted inflammation-activated Dendritic cells

Dendritic cells (DCs) form coordinated networks that orchestrate inflammatory responses across tissues. Upon activation, conventional dendritic cells (DCs) undergo changes in their transcriptome, phenotype, and function, depending on the tissue microenvironment. The role of DC activation during human chronic inflammation has yet to be explored. To address this, we aimed to investigate activated DCs across a range of chronically inflamed human tissues, with a focus on cervical lymph nodes (LNs). We performed scRNAseq and flow cytometry on healthy, acutely, chronically inflamed, and cancer-associated human cervical (LNs) and identified a novel inflammation-associated DC (iaDC) cell state, found only within chronically inflamed LNs. iaDCs were defined by a unique cytokine expression profile (CXCL9, CXCL10, IL1B) and could be phenotypically distinguished from other activated DCs by their elevated expression of CD1C, CD206, CD319, and CD274. Functionally, we found that IFN{gamma} signaling induces DC2s to enter the iaDC cell state and that this process can be abrogated by inhibition of JAK-STAT signaling. Using spatial transcriptomics, we observed LN iaDC residing within a specific chronic inflammatory niche, which was enriched for inflammatory monocytes, NK cells, and effector memory CD4+ and CD8+ T cells. Extrapolating our findings to other chronic inflammation-associated diseases, we similarly observed the emergence of iaDCs within the intestines of treatment-resistant Crohns Disease patients, synovial membranes and lymph nodes of rheumatoid arthritis patients and lungs of sarcoidosis patients. Similarly to the lymph node, iaDCs were found to reside in conserved chronic inflammation-associated spatial niches within the small intestine of affected individuals and displayed equivalent transcriptional characteristics and surrounding cellular neighborhoods. Collectively, these data highlight a previously unexplored role of iaDCs in human chronic inflammatory diseases and propose a conserved spatially restricted iaDC-populated chronic inflammatory niche associated with resistance to therapy. These findings highlight novel avenues to shape inflammatory trajectories by targeting iaDCs and their spatial niches, for example, by inhibiting JAK-STAT signaling.

immunology↗

bioRxiv2025

Exogenous dsRNA made accessible to Dicer by two eukaryotic RNA-dependent RNA polymer-ases

Discrimination of self from non-self RNA is a critical requirement for any cell to respond to infections and to maintain cellular integrity. We report novel functions for two RNA-dependent RNA polymerases (RDRs) in Paramecium in the detection of exogenous RNA. In the RNA interference (RNAi) mechanism, RDRs are normally involved in the production of large amounts of secondary siRNAs in response to an initial primary siRNA. To characterize the function of RDRs in context of exogenous RNA recognition, we developed a novel dsRNA delivery system using dextran nanoparticles to deliver heteroduplex dsRNA to cells as food particles, mimicking the natural phagosomal entry pathway. Subsequent small RNA sequencing allows us to dissect siRNAs produced from exogenous RNA or RDR transcripts. Contrary to expectations of how dsRNA-induced silencing is triggered, our data show that Dicer is unable to directly cleave exogenous dsRNA while two RDRs are required for the initial steps of dsRNA-induced RNAi. Paradoxically, these two RDRs must replicate dsRNA to make it available for Dicer cleavage and primary siRNA accumulation. Our data also show that this system works efficiently also with exogenous ssRNA, although RDR2 is dispensable for ssRNA conversion. The function of RDRs in this protist is in contrast to that in animals, plants and fungi and extends the functional diversity of these polymerases. RDR-associated complexes appear to control the entry of food and symbiont-derived RNA into the RNAi machinery, enabling complex RNA interactions with the environment.

genetics↗

bioRxiv2025

Human airway organoids as a versatile model to study BSL-4 virus replication and pathogenesis

Research with BSL-4 viruses such as Ebola, Marburg, and Nipah presents significant challenges due to their high virulence and the stringent containment measures required. A major limitation in studying viral pathogenesis and developing therapeutic strategies is the absence of suitable animal models that accurately replicate human disease. In this context, 3D cell culture systems offer significant advantages over traditional 2D monolayer cultures, mimicking native physiological conditions including cell polarization and composition. Human airway organoids, derived from pluripotent or adult stem cells, closely replicate the structure and function of the human respiratory system, providing a relevant and accessible environment for studying viral replication and pathogenesis. In contrast to conventional cell lines, airway organoids enable investigation of virus-host interactions within a human tissue context, providing insights that are more directly translatable to human disease. In our study, we generated airway organoids from both clinical donor tissues and commercially available nasal epithelial cells and showed in comparative analyses with whole lung tissue that these organoids are comparable in terms of cell composition. Despite donor-specific variations due to genetic factors, airway organoids derived from different sources and donors exhibit a remarkably similar cellular make-up. We further demonstrated that organoids derived from nasal swabs can effectively replicate BSL-4 viruses, establishing them as a standardized 3D model for broader research applications and advancing our understanding of these pathogens, especially in the absence of reliable animal models. Author SummaryThis study establishes human airway organoids as a robust model for investigating BSL-4 pathogens, such as Ebola, Marburg, and Nipah virus. Airway organoids represent reliable systems due to their ability to replicate the complexity of human respiratory epithelia and support viral infection. These organoids exhibit high susceptibility to these viruses, allowing for subsequent analysis of infection kinetics, immune evasion, and tissue-specific tropism within a controlled environment. This platform provides a powerful tool for antiviral testing and studying virus-host interactions, thus helping bridge critical gaps in high-containment virus research.

cell biology↗

bioRxiv2025

Incorporation of complex narratives into dreaming

Reactivation of waking neuronal activity during sleep holds a functional role in memory consolidation. Reprocessing of daytime memory in dreams might aid later memory performance in a similar way. Numerous findings hint at a link between dreaming and sleep-dependent memory processing, however, studies investigating day-residue incorporation in dreaming led to mixed results so far. In this study, we used a naturalistic learning paradigm aimed at biasing dream content by manipulating pre-sleep experience. Participants listened to one of four different audiobooks while falling asleep and were awoken several times during the night to report their dreams. Afterwards, we tested how well they remembered the content of the audiobook. We then asked three blind raters to guess, based solely on anonymized dream reports, which audiobook someone had listened to before experiencing a dream. Our findings show that dreams across the whole night and from both NREM and REM awakenings contain specific information about the content of narratives studied before sleep. Moreover, participants with stronger incorporation of the audiobook in their dreams showed a tendency to recognize more audiobook content across the sleep period. Together, these findings suggest that salient day-time experiences resurface in dreams and that content selected for consolidation during sleep is more strongly incorporated.

neuroscience↗

bioRxiv2025

Crop genotype modulates root rot resistance-associated microbial community composition and abundance of key taxa

Plants are constantly challenged by pathogens, which can cause substantial yield losses. The aggressiveness of and damage by pathogens depends on the host-associated microbiome, which might be shaped by plant genetics to improve resistance. How different crop genotypes modulate their microbiota when challenged by a complex of pathogens is largely unknown. Here, we investigate if and how pea (Pisum sativum L.) genotypes shape their root microbiota upon challenge by soil-borne pathogens and how this relates to a genotypes resistance. Building on the phenotyping efforts of 252 pea genotypes grown in naturally infested soil, we characterized root fungi and bacteria by ITS region and 16S rRNA gene amplicon sequencing, respectively. Pea genotype markedly affected both fungal and bacterial community composition, and these genotype-specific microbiota were associated with root rot resistance. For example, genotype resistance was correlated (R2 = 19%) with root fungal community composition. Further, several key microbes, showing a high relative abundance, heritability, connectedness with other microbes, and correlation with plant resistance, were identified. Our findings highlight the importance of crop genotype-specific root microbiota under root rot stress and the potential of the plant to shape its associated microbiota as a second line of defense.

plant biology↗

bioRxiv2024

EnsembleFlex: Protein Structure Ensemble Analysis Made Easy

EnsembleFlex is a novel tool designed to perform dual-scale flexibility analysis of protein structure ensembles, encompassing both backbone and side-chain dynamics. It integrates dedicated superposition methodologies, two dimension reduction techniques, customizable clustering, an automated ligand binding site analysis and analysis of conserved water molecules, enhancing the accuracy of ensemble flexibility analysis and visualisation. With a user-friendly, no-coding graphical interface as well as a code-based option, EnsembleFlex is accessible to a broad range of researchers. The tool complements experimental ensemble data analysis with predictive methods based on elastic network models, bridging the gap between experimental and computational approaches in protein flexibility analysis, and does so from a global backbone-based perspective, as well as from a focused side-chain and binding site-centred point of view. The need for reliable, streamlined, fast, and user-friendly tools for structural ensemble analysis is critical in todays research environment, and EnsembleFlex addresses these needs efficiently, offering an accessible solution that integrates powerful analysis methods in a single package. Its wide applicability across various domains of molecular design underscores the importance of streamlined flexibility analysis in scientific research.

molecular biology↗

bioRxiv2024

The Blueprint for Survival: The Blue Dasher Dragonfly as a Model for Urban Adaptation

Human alteration of natural environments and habitats is a major driver of species decline. However, a handful of species thrive in human altered environments. The biology, distribution, population structure, and molecular adaptations enabling certain species to thrive in human-altered habitats are not well understood. Here, we evaluate the population and functional genomics, ecological niche and distributions, and geometric morphometrics of the blue dasher (Pachydiplax longipennis), one of the most ubiquitously observed insects in human altered habitats. Using resequencing data we identify a number of genes involved with the success of the blue dasher in human altered habitats, including loci contributing to immune function and response to oxidative stress. Some genes related to these functions are found in regions of strong population structure, while others are not, potentially indicating both regional and widespread adaptations to urban environments within this species. Using one of the most robust locality datasets for any species to date, we also generate habitat suitability predictions which show that P. longipennis has spread with urbanization, suggesting humans have created suitable habitat for this species. These results complement morphological and genomic data showing P. longipennis (particularly East of the Rocky Mountains) has the capacity to rapidly disperse to newly suitable habitats. Given the shared barriers to colonizing an urban habitat, we expect that many of the adaptations we have identified in P. longipennis can be used for predicting what animals might succeed in urban habitats more generally.

evolutionary biology↗

bioRxiv2024

Environmental DNA vs. Community Science: Strengths and Limitations for Urban Odonata Surveys

The study of insect decline remains a major frontier in insect biodiversity and conservation. Despite growing concern about accelerating rates of insect decline generally, relatively little data has been compiled about species of aquatic insects. Data is particularly lacking on the distribution of aquatic insects in urban ecosystems. Here, we compare environmental DNA (eDNA) metabarcoding and community science observation as means of monitoring Odonata within an urban system in Southwest Idaho. We show that the distribution of Odonata across this urban landscape is not uniform and that both monitoring methods have different strengths and weaknesses. We found that eDNA metabarcoding was very sensitive to the identification of genera from underrepresented families in the region, but was unable to distinguish between closely related genera, particularly from localities where eDNA could accumulate more damage. On the other hand, community science observations effectively identified the presence of genera from more speciose families but missed the presence of relatively rare species, and those that had a short flight season. These findings suggest that, in our study system, eDNA and community science are highly complementary of each other. In cases where only one method is employed for a monitoring or conservation project, care should be given to account for the biases of each approach.

ecology↗

bioRxiv2024

Accurate de novo design of high-affinity protein binding macrocycles using deep learning

The development of macrocyclic binders to therapeutic proteins typically relies on large-scale screening methods that are resource-intensive and provide little control over binding mode. Despite considerable progress in physics-based methods for peptide design and deep-learning methods for protein design, there are currently no robust approaches for de novo design of protein-binding macrocycles. Here, we introduce RFpeptides, a denoising diffusion-based pipeline for designing macrocyclic peptide binders against protein targets of interest. We test 20 or fewer designed macrocycles against each of four diverse proteins and obtain medium to high-affinity binders against all selected targets. Designs against MCL1 and MDM2 demonstrate KD between 1-10 M, and the best anti-GABARAP macrocycle binds with a KD of 6 nM and a sub-nanomolar IC50 in vitro. For one of the targets, RbtA, we obtain a high-affinity binder with KD < 10 nM despite starting from the target sequence alone due to the lack of an experimentally determined target structure. X-ray structures determined for macrocycle-bound MCL1, GABARAP, and RbtA complexes match very closely with the computational design models, with three out of the four structures demonstrating Ca RMSD of less than 1.5 [A] to the design models. In contrast to library screening approaches for which determining binding mode can be a major bottleneck, the binding modes of RFpeptides-generated macrocycles are known by design, which should greatly facilitate downstream optimization. RFpeptides thus provides a powerful framework for rapid and custom design of macrocyclic peptides for diagnostic and therapeutic applications.

biochemistry↗

bioRxiv2024

A Transformer-Based Approach to Survival Outcome Prediction

Accurate prediction of patient survival outcomes is a critical challenge in cancer research, with the potential to inform personalized treatment strategies and improve patient care. We leveraged Geneformer, a state-of-the-art transformer model pre-trained on a massive single-cell RNA-seq dataset, to develop a model for the prediction of overall survival (OS). We adapted Geneformer for bulk tumor data analysis by appending a task-specific transformer layer and fine-tuning the model on RNA-seq data from The Cancer Genome Atlas (TCGA). Additionally, we employed a rank-value encoding scheme to prioritize informative genes and reduce noise. Our model demonstrated a robust correlation between predicted and true OS, with Pearson correlation coefficient of 0.72 (p<0.00001). Survival analysis revealed significant differences in survival between patient subgroups stratified based on the models predictions. The Geneformer-based model outperformed traditional machine learning approaches (Random Forest and Neural Network) in patient stratification tasks. Further analysis demonstrated the consistency of the models performance across different tumor stages and patient subgroups. Our study highlights the potential of leveraging pre-trained transformer models, originally developed for single-cell data analysis, to predict clinically relevant outcomes from bulk tumor gene expression data. The superior performance of our Geneformer-based model underscores its potential to enhance prognostication and treatment decision-making in cancer research. Future work will focus on refining the model architecture, incorporating multi-omics data, and validating its performance on external datasets to further advance its clinical utility. Short AbstractAccurate prediction of patient survival has important implications for cancer research as it enables the development of personalized treatment plans, guides clinical decision-making, and can be leveraged for clinical trial optimization. We utilized Geneformer, a transformer model pre-trained on single-cell RNA-seq data, to predict overall survival (OS) from bulk tumor gene expression. Adapting Geneformer for bulk tumor analysis and using rank-value encoding, we achieved strong correlations between predicted and true OS (r=0.72, p<0.00001). Our model outperformed traditional machine learning approaches in patient stratification, demonstrating consistent performance across tumor stages and subgroups. This study highlights the potential of pre-trained transformer models for prognostication in cancer, paving the way for refined, personalized treatment strategies.

bioinformatics↗

bioRxiv2024

An atlas of RNA-dependent proteins in cell division reveals the riboregulation of mitotic protein-protein interactions

Ribonucleoprotein complexes are dynamic assemblies of RNA with RNA-binding proteins (RBPs), which can modulate the fate of the RNA molecules from transcription to degradation. Vice versa, RNA can regulate the interactions and functions of the associated proteins. Dysregulation of RBPs is linked to diseases such as cancer and neurological disorders. RNA and RBPs are present in mitotic structures like the centrosomes and spindle microtubules, but their influence on mitotic spindle integrity remains unknown. Thus, we applied the R-DeeP strategy for the proteome-wide identification of RNA-dependent proteins and complexes to cells synchronized in mitosis versus interphase. The resulting atlas of RNA-dependent proteins in cell division can be accessed through the R-DeeP 3.0 database (R-DeeP3.dkfz.de). It revealed key mitotic factors as RNA-dependent such as AURKA, KIFC1 and TPX2 that were linked to RNA despite their lack of canonical RNA-binding domains. KIFC1 was identified as a new interaction partner and phosphorylation substrate of AURKA at S349 and T359. In addition, KIFC1 interacted with both, AURKA and TPX2, in an RNA-dependent manner. Our data suggest a riboregulation of mitotic protein-protein interactions during spindle assembly, offering new perspectives on the control of cell division processes by RNA-protein complexes. HighlightsO_LIDifferential R-DeeP screens in mitosis and interphase are provided as a resource in a user-friendly database at R-DeeP3.dkfz.de C_LIO_LIAn atlas of RNA-dependent proteins in cell division identifies a substantial number of unconventional RNA-binding proteins among mitotic factors C_LIO_LIInvestigation of protein-protein interactions reveals KIFC1 as a new AURKA and TPX2 interaction partner during spindle assembly C_LIO_LIKIFC1, AURKA and TPX2 interact with each other in an RNA-dependent manner and directly bind to RNA C_LIO_LIAURKA phosphorylates KIFC1 at residues S349 and T359 C_LI

cell biology↗

bioRxiv2024

Extracellular phase separation mediates storage and release of thyroglobulin in the thyroid follicular lumen

Thyroid hormones are produced by the thyroid gland and are essential for regulating metabolism, growth and development. Maintenance of circulating thyroid hormone levels within an appropriate range is thus a prerequisite for health. In vivo, this objective is, at least in part, facilitated through an extracellular storage depot of thyroglobulin, the glycoprotein precursor for thyroid hormones, in the thyroid follicular lumen. The molecular basis for how soluble thyroglobulin molecules form such dense depot assemblies remains elusive. Here, we describe in vitro biophysical analysis of thyroglobulin phase behaviour, suggesting that thyroglobulin is prone to undergoing ionic strength-dependent phase separation, leading to the formation of liquid-like condensates. Fluorescence photobleaching measurements further show that these condensates age as a function of time to form reversible gel-like high density storage depots of thyroglobulin. Immunofluorescence experiments on mouse and human thyroid follicles ex vivo reveal that spherical globules of Tg protein dense phase are present in the follicular lumen, consistent with the idea that Tg undergoes phase separation. These findings reveal a molecular mechanism for the last-come-first-served process of thyroglobulin storage and release, suggesting a role for extracellular phase separation in thyroid hormone homeostasis by providing organizational and architectural specificity without requiring membrane-mediated confinement.

biophysics↗

bioRxiv2024

Active repression of cell fate plasticity by PROX1 safeguards hepatocyte identity and prevents liver tumourigenesis

Cell fate plasticity enables development, yet unlocked plasticity is a cancer hallmark. Regulating cell identity requires gene activation and repression. While master regulators induce lineage-specific genes to restrict plasticity, it remains unclear whether unwanted plasticity is actively suppressed by lineage-specific repressors. Here, we computationally predict so-called safeguard repressors for 18 cell types that block phenotypic plasticity lifelong. We validated hepatocyte-specific candidates using reprogramming, revealing that Prospero homeobox protein 1 (PROX1) enhanced hepatocyte identity by direct repression of alternate fate master regulators. In mice, Prox1 was required for efficient hepatocyte regeneration after injury and acted as a tumour suppressor in multiple liver cancer models. In line with patient data, Prox1 depletion caused hepatocyte fate loss in vivo, and promoted transition of hepatocellular carcinoma to cholangiocarcinoma, conversely, overexpression promoted cholangiocarcinoma to hepatocellular carcinoma transdifferentiation. Our findings provide mechanistic evidence for PROX1 as a hepatocyte-specific safeguard and support a model where individual cell type-specific repressors actively suppress plasticity throughout life to safeguard lineage choice and prevent disease.

cancer biology↗

bioRxiv2024

Scalable Hypothalamic Arcuate Neuron Differentiation from Human Pluripotent Stem Cells Suitable for Modeling Metabolic and Reproductive Disorders

The hypothalamus, composed of several nuclei, is essential for maintaining our bodys homeostasis. The arcuate nucleus (ARC), located in the mediobasal hypothalamus, contains neuronal populations with eminent roles in energy and glucose homeostasis as well as reproduction. These neuronal populations are of great interest for translational research. To fulfill this promise, we used a robotic cell culture platform to provide a scalable and chemically defined approach for differentiating human pluripotent stem cells (hPSCs) into pro-opiomelanocortin (POMC), somatostatin (SST), tyrosine hydroxylase (TH) and gonadotropin-releasing hormone (GnRH) neuronal subpopulations with an ARC-like signature. This robust approach is reproducible across several distinct hPSC lines and exhibits a stepwise induction of key ventral diencephalon and ARC markers in transcriptomic profiling experiments. This is further corroborated by direct comparison to human fetal hypothalamus, and the enriched expression of genes implicated in obesity and type 2 diabetes (T2D). Genome-wide chromatin accessibility profiling by ATAC-seq identified accessible regulatory regions that can be utilized to predict candidate enhancers related to metabolic disorders and hypothalamic development. In depth molecular, cellular, and functional experiments unveiled the responsiveness of the hPSC-derived hypothalamic neurons to hormonal stimuli, such as insulin, neuropeptides including kisspeptin, and incretin mimetic drugs such as Exendin-4, highlighting their potential utility as physiologically relevant cellular models for disease studies. In addition, differential glucose and insulin treatments uncovered adaptability within the generated ARC neurons in the dynamic regulation of POMC and insulin receptors. In summary, the establishment of this model represents a novel, chemically defined, and scalable platform for manufacturing large numbers of hypothalamic arcuate neurons and serves as a valuable resource for modeling metabolic and reproductive disorders.

developmental biology↗