Biology subjects

Krausgruber, T.

Publications and source records attributed to Krausgruber, T..

16 recordsLinked to original sources

bioRxiv2026

Mtor/Rptor Function Globally Prevents Cortical Microcephaly and Cell-autonomously Promotes Postnatal Neuron Survival in Cell Type Specific Manner

The generation of faithful cell-type diversity and correct projection neuron numbers is essential for cerebral cortex development. Corticogenesis is however susceptible to genetic interference of critical signaling pathways, including mutations in Mtor/Rptor that lead to microcephaly. How the loss of Rptor/mTORC1 function affects cortical developmental programs, at single cell level, is still unknown. Here, we utilized Mosaic Analysis with Double Markers (MADM) technology to probe Rptor gene function upon sparse single cell- or global tissue-wide ablation. We found that tissue-wide effects drive the etiology of cortical microcephaly upon loss of Rptor, rather than deficits in projection neuron genesis. Conversely, Rptor function is cell-autonomously required for postnatal projection neuron survival in a highly cell-type-specific manner. Collectively, our results suggest that the fine balance of precise cell-type-specific cell-autonomous Rptor/mTORC1 function in concert with non-cell-autonomous tissue-wide effects is essential for the development of a properly-sized cerebral cortex with accurate projection neuron diversity.

neuroscience↗

bioRxiv2025

IRF4 is a master regulator of multinucleated giant cell formation

Multinucleated giant cells (MGCs) are a hallmark pathological feature of a wide range of diseases, yet the mechanisms underlying their formation and function remain poorly understood. Although it is recognized that MGCs arise from a heterogeneous pool of myeloid precursors, how a committed MGC fate develops therein remains unknown. Here, combining temporal in vitro and in vivo differentiation of bone marrow-derived myeloid precursors with single cell and bulk RNA sequencing as well as CRISPR/Cas9-mediated gene editing, we shed insight into how MGCs emerge. Our findings reveal that coordinated upregulation of cell fusion genes and cellular metabolism, particularly oxidative phosphorylation, regulate the transition from macrophage progenitors to fusion competent cells. In vivo fate-mapping unveils Ms4a3-, and Cd11c-but not Cx3cr1-traced cells as the predominant precursor populations for MGCs in a lung granuloma formation model. Notably, transcription factor profiling in the progression from early myeloid precursors to pre-MGCs identifies IRF4 as a key molecular switch driving MGC generation. IRF4+ MGCs are present in different pathologies, including Schistosoma mansoni egg induced granulomas, Aspergillus fumigatus conidia mediated allergic airway inflammation and human head and neck squamous cell carcinomas. Mechanistically, IRF4 controls critical fusion related genes such as Dcstamp and Ocstamp. Consequently, Irf4 deficient cells are unable to develop into MGCs. Collectively, our work delineates the trajectory of MGC differentiation, establishing IRF4 as a defining transcription factor required for the generation of fusion-competent progenitors that ultimately give rise to MGCs.

immunology↗

bioRxiv2025

Time-resolved immune dynamics in rheumatoid arthritis under Methotrexate therapy

Rheumatoid arthritis (RA) is characterized by immune dysregulation, including alterations in peripheral blood mononuclear cell (PBMC) populations and aberrant cytokine signaling. Methotrexate (MTX) is the preferred first-line treatment for RA, yet its precise mechanisms of action remain incompletely understood. This study employed a multi-omics strategy--combining single-cell RNA sequencing (scRNA-seq) and immunophenotyping--to identify key effector peripheral immune cells and their cellular responses in RA patients over 12 weeks of MTX treatment. In our study, MTX was associated with significant immune modulation, including the restoration of naive T and B cells and reductions in T cell memory subsets with these effects detectable as early as three weeks post-treatment. Plasmablast levels also emerged as a potential biomarker for early therapeutic response, reflecting MTXs impact on immune homeostasis. Transcriptional analysis revealed modulation of key pathways, including TNF- signaling, B cell receptor signaling, and T cell receptor-mediated apoptosis. Network analysis identified critical regulatory hubs, such as EGR1, JAK2, and SOCS1, in monocytes and CD4 memory T cells, highlighting these cell types as key mediators of MTXs effects. In conclusion, these findings advance our understanding of MTXs effects on immune cell dynamics at different stages of treatment, showing for the first time the early cellular changes leading to immune modulation in RA. Altogether, our results provide the foundation for further mechanistic investigations into MTX.

genomics↗

bioRxiv2024

Reconstitution of Human Brain Cell Diversity in Organoids via Four Protocols

Human brain organoids are powerful in vitro models for brain development and disease. However, their variability can complicate use in biomedical research and drug discovery. Both the specific protocol as well as the pluripotent starting cell line influence organoid variability and can result in incomplete representation of brain cell types in an organoid experiment. Here, we systematically analyze the cellular and transcriptional landscape of brain organoids grown from multiple cell lines using four different protocols recapitulating dorsal and ventral forebrain, midbrain, and striatum. We establish the NEST-Score as a quantitative readout for cell line-driven and protocol-driven differentiation propensities by comparing cellular states across multiple cell lines and to in vivo reference data sets. Thereby, we establish a set of organoid protocols that together recreate the vast majority of cell types in the developing human brain and provide a reference for how well cell types are recapitulated across cell lines in each protocol. Additionally, we survey factors contributing to variability during organoid development and identify early gene expression signatures predicting protocol-driven organoid generation at later stages. We provide easy online access to our data through a web-based analysis tool, creating a reference for brain organoid research that allows rapid, straightforward validation of protocol and cell line performance.

developmental biology↗

bioRxiv2024

Multimodal learning of transcriptomes and text enables interactive single-cell RNA-seq data exploration with natural-language chats

Single-cell RNA-seq characterizes biological samples at unprecedented scale and detail, but data interpretation remains challenging. Here we introduce CellWhisperer, a multimodal machine learning model and software that connects transcriptomes and text for interactive single-cell RNA-seq data analysis. CellWhisperer enables the chat-based interrogation of transcriptome data in English language. To train our model, we created an AI-curated dataset with over a million pairs of RNA-seq profiles and matched textual annotations across a broad range of human biology, and we established a multimodal embedding of matched transcriptomes and text using contrastive learning. Our model enables free-text search and annotation of transcriptome datasets by cell types, states, and other properties in a zero-shot manner and without the need for reference datasets. Moreover, Cell-Whisperer answers questions about cells and genes in natural-language chats, using a biologically fluent large language model that we fine-tuned to analyze bulk and single-cell transcriptome data across various biological applications. We integrated CellWhisperer with the widely used CELLxGENE browser, allowing users to in-teractively explore RNA-seq data through an integrated graphical and chat interface. Our method demonstrates a new way of working with transcriptome data, leveraging the power of natural language for single-cell data analysis and establishing an important building block for future AI-based bioinformatics research assistants.

bioinformatics↗

bioRxiv2024

HDAC1 controls the generation and maintenance of effector-like CD8+ T cells during chronic viral infection

CD8+ T cell exhaustion is a complex process that involves the differentiation of persistently activated CD8+ T cells into functionally distinct cell subsets. Here, we investigated the role of the key epigenetic regulator histone deacetylase 1 (HDAC1) in the differentiation of exhausted T (Tex) cells during chronic viral infection. We uncovered that HDAC1 controls the generation and maintenance of effector-like CX3CR1+ Tex cells in a CD8+ T cell-intrinsic manner. Deletion of HDAC1 led to expansion of an alternative Tex cell subset characterized by high expression of T cell exhaustion markers, and this was accompanied by elevated viremia. HDAC1 knockout altered the chromatin landscape in progenitor Tex cells, abrogated the expression of effector-like signature genes and interfered with cell fate specification toward the CX3CR1+ Tex cell subset. We conclude that HDAC1 is functionally required for controlling viral load during chronic infection by ensuring adequate CX3CR1+ Tex cell subset differentiation. HighlightsO_LIHDAC1 promotes the generation of CX3CR1+ effector-like Tex cell subsets in chronic viral infection in a CD8+ T cell-intrinsic manner. C_LIO_LIDeletion of HDAC1 leads to an increase of a cell subset enriched in exhaustion markers and is accompanied with elevated viremia. C_LIO_LIHDAC1 is required for the maintenance of the CX3CR1+ Tex cell pool. C_LIO_LIHDAC1 deletion alters the chromatin landscape at effector-like signature gene loci in progenitor Tex cells. C_LI

immunology↗

bioRxiv2023

Single-cell profiling uncovers regulatory programs of pathogenic Th2 cells in allergic asthma

Lung pathogenic T helper type 2 (pTh2) cells are important drivers of allergic asthma, but fundamental questions remain regarding their regulation and heterogeneity. The differentiation and effector functions of immune cells are tightly regulated by epigenetic processes. Histone deacetylase 1 (HDAC1) is an important epigenetic regulator of T cells, however, its role in pTh2 cells is yet to be determined. Here we investigate immune regulation in allergic asthma by single-cell RNA sequencing (scRNA-seq) in mice challenged with house dust mite, in the presence and absence of HDAC1 function. Our analyses reveal two distinct subsets of lung pTh2 cells: pathogenic effector Th2 (peTh2) and pathogenic Th2 tissue-resident memory (Th2 Trm) cells. Both pTh2 cell subsets are highly proinflammatory and exhibit distinct transcriptional and phenotypic signatures as compared with other lung Th subsets. Based on our scRNA-seq analysis, we identify conditions to generate pTh2 cells in vitro and confirm that these in vitro generated pTh2 cells have a similar transcriptional profile as lung peTh2 cells. Using our new in vitro model, we demonstrate that the p38 mitogen-activated protein kinase pathway is critical for interleukin-5 (IL-5) and IL-13 expression in pTh2 cells. Our data further underline the importance of HDAC1 in limiting the pathogenicity of lung and in vitro pTh2 cells and in the formation of lung Th2 Trm cells. In summary, we have generated novel insights into pTh2 cell biology and established a new in vitro model for investigating pTh2 cells that will be useful for discovering molecular mechanisms involved in pTh2-mediated allergic asthma.

immunology↗

bioRxiv2023

Multi-organ single-cell RNA-sequencing reveals early hyperglycaemia responses that converge on fibroblast dysregulation

Diabetes causes a range of complications that can affect multiple organs. Hyperglycaemia is an important driver of diabetes-associated complications, mediated by biological processes such as dysfunction of endothelial cells, fibrosis and alterations in leukocyte number and function. Here, we dissected the transcriptional response of key cell types to hyperglycaemia across multiple tissues using single-cell RNA-seq (scRNA-seq) and identified conserved, as well as organ-specific, changes associated with diabetes complications. By studying an early timepoint of diabetes, we focus on biological processes involved in the initiation of the disease, before the later organ-specific manifestations had supervened. We used a mouse model of type 1 diabetes and performed scRNA-seq on cells isolated from the heart, kidney, liver and spleen of streptozotocin-treated and control mice after 8 weeks and assessed differences in cell abundance, gene expression, pathway activation and cell signalling across organs and within organs. In response to hyperglycaemia, endothelial cells, macrophages and monocytes displayed organ-specific transcriptional responses, whereas fibroblasts showed similar responses across organs, exhibiting a myofibroblast-like phenotype with altered metabolic gene expression and increased differentiation of myeloid-derived fibroblasts. Further, we found evidence of endothelial dysfunction in the kidney, and of endothelial to mesenchymal transition in streptozotocin-treated mouse organs. In summary, our study represents the first single-cell and multi-organ analysis of early dysfunction in type 1 diabetes-associated hyperglycaemia, and our large-scale dataset (comprising 67,611 cells) will serve as a starting point, reference atlas, and resource for further investigating the events leading to early diabetic disease.

cell biology↗

bioRxiv2023

Large language models are universal biomedical simulators

Computational simulation of biological processes can be a valuable tool in accelerating biomedical research, but usually requires extensive domain knowledge and manual adaptation. Recently, large language models (LLMs) such as GPT-4 have proven surprisingly successful for a wide range of tasks by generating human language at a very large scale. Here we explore the potential of leveraging LLMs as simulators of biological systems. We establish proof-of-concept of a text-based simulator, SimulateGPT, that uses LLM reasoning. We demonstrate good prediction performance for various biomedical applications, without requiring explicit domain knowledge or manual tuning. LLMs thus enable a new class of versatile and broadly applicable biological simulators. This text-based simulation paradigm is well-suited for modeling and understanding complex living systems that are difficult to describe with physics-based first-principles simulation, but for which extensive knowledge and context is available as written text.

bioinformatics↗

bioRxiv2023

Multipotent Progenitors Instruct Ontogeny of the Superior Colliculus

The superior colliculus (SC) in the mammalian midbrain is essential for multisensory integration, attention, and complex behavior (Basso and May, 2017; Cang et al., 2018). The mature SC cytoarchitecture is organized into distinct laminae and composed of a rich variety of neuronal and glial cell types (Ayupe et al., 2023; Edwards et al., 1986; May, 2006; Xie et al., 2021; Zeisel et al., 2018). Precise execution of the developmental programs regulating the generation of SC cell-type diversity is essential, because deficits due to genetic mutations have been associated with neurodevelopmental diseases and SC dysfunction (Jure, 2018; McFadyen et al., 2020). However, the fundamentals directing the ontogeny of the SC are not well understood. Here we pursued systematic lineage tracing at the single progenitor cell level in order to decipher the principles instructing the generation of cell-type diversity in the SC. We combined in silico lineage reconstruction with a novel genetic MADM (Mosaic Analysis with Double Markers)-CloneSeq approach. MADM-CloneSeq enables the unequivocal delineation of cell lineages in situ, and cell identity based on global transcriptome, of individual clonally-related cells. Our systematic reconstructions of cell lineages revealed that all neuronal cell types in SC emerge from local progenitors without any extrinsic source. Strikingly, individual SC progenitors are exceptionally multipotent with the capacity to produce all known excitatory and inhibitory neuron types of the prospective mature SC, with individual clonal units showing no pre-defined composition. At the molecular level we identified an essential role for PTEN signaling in establishing appropriate proportions of specific inhibitory and excitatory neuron types. Collectively, our findings demonstrate that individual multipotent progenitors generate the full spectrum of excitatory and inhibitory neuron types in the developing SC, providing a novel framework for the emergence of cell-type diversity and thus the ontogeny of the mammalian SC.

neuroscience↗

bioRxiv2022

STAT5 Gain-of-Function Variants Promote Precursor T-Cell Receptor Activation to Drive T-Cell Acute Lymphoblastic Leukemia

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive immature T-cell cancer. Hotspot mutations in JAK-STAT pathway members IL7R, JAK1 and JAK3 were analyzed in depth. However, the role of STAT5A or STAT5B mutations promoting their hyperactivation is poorly understood in the context of T-cell cancer initiation and acute leukemia progression. Importantly, the driver mutation STAT5BN642H encodes the most frequent activating STAT5 variant in T-ALL associated with poor prognosis. Here, we show that hyperactive STAT5 promotes early T-cell progenitor (ETP)-ALL-like cancer in mice and upregulated genes involved in T-cell receptor signaling (TCR), even in absence of surface TCR promoting. Importantly, these genes were also overexpressed in human T-ALL and other STAT5-dependent T-cell cancers. Moreover, human T-ALL cells were sensitive to pharmacologic inhibition by dual STAT3/5 degraders or ZAP70 tyrosine kinase blockers. Thus, we define STAT5 target genes in T-ALL that promote pre-TCR signaling mimicry. We propose therapeutic targeting using selective ZAP70 or STAT3/5 inhibitors in a subgroup of T-ALL patients with prominent IL-7R-JAK1/3-STAT5 activity. SignificanceWe provide detailed functional characterizations of hyperactive STAT5A or STAT5B in thymic T-cell development and transformation. We found that hyperactive STAT5 transcribes T-cell-specific kinases or pre-TCR signaling hubs to promote T-ALL. Biomolecular and next-generation-sequencing methods, transgenesis and pharmacologic interference revealed that hyperactive STAT5 is a key oncogenic driver that can be targeted in T-ALL using STAT3/5 or SYK family member tyrosine kinase inhibitors. Conflict of interestThe authors declare no potential conflicts of interest.

cancer biology↗

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↗

bioRxiv2019

Ultra-high throughput single-cell RNA sequencing by combinatorial fluidic indexing

Cell atlas projects and single-cell CRISPR screens hit the limits of current technology, as they require cost-effective profiling for millions of individual cells. To satisfy these enormous throughput requirements, we developed "single-cell combinatorial fluidic indexing" (scifi) and applied it to single-cell RNA sequencing. The resulting scifi-RNA-seq assay combines one-step combinatorial pre-indexing of single-cell transcriptomes with subsequent single-cell RNA-seq using widely available droplet microfluidics. Pre-indexing allows us to load multiple cells per droplet, which increases the throughput of droplet-based single-cell RNA-seq up to 15-fold, and it provides a straightforward way of multiplexing hundreds of samples in a single scifi-RNA-seq experiment. Compared to multi-round combinatorial indexing, scifi-RNA-seq provides an easier, faster, and more efficient workflow, thereby enabling massive-scale scRNA-seq experiments for a broad range of applications ranging from population genomics to drug screens with scRNA-seq readout. We benchmarked scifi-RNA-seq on various human and mouse cell lines, and we demonstrated its feasibility for human primary material by profiling TCR activation in T cells.

genomics↗

bioRxiv2019

Chromatin mapping and single-cell immune profiling define the temporal dynamics of ibrutinib drug response in chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is a genetically, epigenetically, and clinically heterogeneous disease. Despite this heterogeneity, the Bruton tyrosine kinase (BTK) inhibitor ibrutinib provides effective treatment for the vast majority of CLL patients. To define the underlining regulatory program, we analyzed high-resolution time courses of ibrutinib treatment in closely monitored patients, combining cellular phenotyping (flow cytometry), single-cell transcriptome profiling (scRNA-seq), and chromatin mapping (ATAC-seq). We identified a consistent regulatory program shared across all patients, which was further validated by an independent CLL cohort. In CLL cells, this program starts with a sharp decrease of NF-{kappa}B binding, followed by reduced regulatory activity of lineage-defining transcription factors (including PAX5 and IRF4) and erosion of CLL cell identity, finally leading to the acquisition of a quiescence-like gene signature which was shared across several immune cell types. Nevertheless, we observed patient-to-patient variation in the speed of its execution, which we exploited to predict patient-specific dynamics in the response to ibrutinib based on pre-treatment samples. In aggregate, our study describes the cellular, molecular, and regulatory effects of therapeutic B cell receptor inhibition in CLL at high temporal resolution, and it establishes a broadly applicable method for epigenome/transcriptome-based treatment monitoring.

cancer biology↗

bioRxiv2018

STAT3 promotes melanoma metastasis by CEBP-induced repression of the MITF pigmentation pathway

Metastatic melanoma is hallmarked by its ability to switch oncogenic MITF expression. Here we tested the impact of STAT3 on melanoma onset and progression in association with MITF expression levels. We established a mouse melanoma model for deleting Stat3 specifically in melanocytes with specific expression of human hyperactive NRASQ61K in an Ink4a deficient background. Mice with tissue specific Stat3 deletion showed an early onset of disease, but displayed significantly diminished lung metastases. Whole genome expression profiling also revealed a reduced invasion phenotype, which was functionally confirmed in 3D melanoma model systems. Notably, loss or knockdown of STAT3 in mouse or human cells resulted in up-regulation of MITF and induction of cell proliferation. Mechanistically we show that STAT3 induced CEBPa/b expression was sufficient to suppress MITF transcription. Epigenetic analysis by ATAC-seq confirmed that STAT3 enabled CEBPa/b binding to the MITF enhancer region thereby silencing it. We conclude that STAT3 is a metastasis driver in melanoma able to antagonize the MITF oncogene via direct induction of CEBP family member transcription facilitating RAS-RAF-driven melanoma metastasis.\n\nList of Abbreviations\n\nATAC-seq, Assay for Transposase-Accessible Chromatin using sequencing; CEBP, CAAT Box Enhancer Binding Protein; CRE, Cre recombinase; EGF, Epidermal Growth Factor; GEO, Gene Expression Omnibus; GSEA, Gene Set Enrichment Analysis; HSC70, Heat Shock 70 kDa protein; IHC, Immunohistochemistry; IL-6, Interleukin-6; JAK, Janus Kinase; MITF, Microphthalmia-Associated Transcription Factor; NSG, NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ mice; OSM, Oncostatin M; PDGF, Platelet-Derived Growth Factor; pS, phosphoserine; pY, phosphotyrosine; RAS, Rat Sarcoma; RAF, Rapidly Accelerated Fibrosarcoma; RTK, Receptor Tyrosine Kinase; RT-PCR, Reverse Transcription Polymerase Chain Reaction; S100b, Calcium Binding Protein S100 beta; shRNA, short hairpin RNA; SOX10, Sex Determining Region Y-10; STAT, Signal Transducer and Activator of Transcription; TCGA, The Cancer Genome Atlas; TMA, Tissue Micro Array

cancer biology↗

bioRxiv2017

Single cell transcriptomics of regulatory T cells reveals trajectories of tissue adaptation

Non-lymphoid tissues (NLTs) harbour a pool of adaptive immune cells, the development and phenotype of which remains largely unexplored. Here, we used single-cell RNA-seq to characterise CD4+ regulatory (Treg) and memory (Tmem) T cells in mouse skin and colon, the respective draining lymph nodes and spleen. From this data, we modelled a continuous lymphoid-to-NLT trajectory for Treg, and reconstructed the mechanisms of cell migration and NLT adaption. This revealed a shared transcriptional programme of NLT priming in both skin and colon-associated lymph nodes, followed by tissue-specific adaptation. Predicted migration kinetics were validated using a melanoma-induction model, emphasizing the relevance of key regulators and receptors, including Batf, Rora, Ccr8, Samsn1. Finally, we profiled human blood and NLT Treg and Tmem cells, identifying cross-mammalian conserved tissue signatures. In summary, we have identified molecular signals mediating NLT Treg recruitment and tissue adaptation through the combined use of computational prediction and in vivo validation.

immunology↗