Biology subjects

Schultze, J. L.

Publications and source records attributed to Schultze, J. L..

At least 19 recordsLinked to original sources

bioRxiv2026

A high-throughput cost-efficient in vitro platform for the screening of immune senomodulators

With advancing age, the immune systems capacity to effectively combat pathogens diminishes. This decline of the overall immune function impacts both the innate and adaptive compartments, contributing in many cases to a systemic state of chronic inflammation which further increases the risk of the most prevalent non-communicable diseases and severe infections. Given the increase in median life expectancy with a demographic development towards a larger number of elderly people, identifying interceptive strategies to mitigate the individual and societal impact of diseases related to immune aging is of paramount importance. We developed a molecularly defined strategy to guide interventions with the aim to reduce immune aging. We introduce an omics-based drug screening platform to identify and characterize the pharmacological profile of immune senomodulators applicable to cross-age human cohorts using human-derived peripheral immune cells. To this aim we developed a robust experimental approach to screen for effective anti-aging compounds directly on human cells. This methodology allows us to quickly screen for drug candidates at different scales: from cost-effective bulk transcriptomics for a broader high-throughput overview of cellular responses, down to single-cell resolution approaches for a more detailed look at gene expression and other molecular data. This in vitro screening method is designed to maximize the clinical relevance of our findings, providing a direct link between preclinical research and patient care. By analyzing how different compounds affect the immune cells of individual persons, we can identify treatments that are most likely to be effective against aging in a subject-specific manner--a key step toward personalized medicine. In short, our approach enables a faster translation of anti-aging immune treatments from the lab to the clinic, tailoring them to each individuals unique biological makeup.

systems biology↗

bioRxiv2026

Downregulation of Satb1 is required to prevent autoimmunity by maintaining Tfh homeostasis

T follicular helper (Tfh) cells are a specialized subset of CD4 T cells that localize to germinal centers (GC), where they provide critical help to B cells through the delivery of IL-21 and other cytokines. Here, we demonstrate that the tight control of the chromatin remodeler Special AT-rich sequence-binding protein 1 (Satb1) is key for this process, as overexpression of Satb1 drives lymphoproliferation and expansion of the T cell and B cell compartments in secondary lymphoid organs. Specifically, Satb1 overexpression induces a pronounced shift towards Tfh cell differentiation and increased GC formation accompanied by an increase in non-classed switched GC B cells and auto-antibody secretion. These findings highlight the importance of the precise regulation of Satb1 in fine-tuning CD4 T cells and B cells responses and suggest a potential role for dysregulation of Satb1 in the pathogenesis of autoimmune disease such as systemic lupus erythematodes (SLE).

immunology↗

bioRxiv2026

A reproducible human brain tissue model to study physiological and disease-associated microglia phenotypes

Stem-cell-based in vitro models offer promising potential to elucidate human brain cell functions and interactions under physiological and pathological conditions. However, harnessing this potential is impaired by low reproducibility, maturity, or cell-type diversity of existing models. Especially, prolonged incorporation of mature microglia and studies of neuroinflammation have proven challenging. Here, we developed a 3D cortical brain tissue model (3BTM) containing neurons, astrocytes, and microglia with high reproducibility, maturity, and viability. 3BTMs show morphological, functional, and proteomic maturation of all cell types, leading to high similarity to their in vivo counterparts. Incorporated microglia survive for over 6 months and display mature morphology, functions, and gene expression. Importantly, when engineered to model Alzheimers disease pathology, 3BTMs recapitulate key disease hallmarks including amyloid deposition, increased phospho-Tau levels, and neuroinflammation, with microglia shifting their transcriptional landscape to disease-relevant signatures. Together, our model offers unprecedented possibilities for studying physiological and pathological states of human brain tissue and translational applications.

neuroscience↗

bioRxiv2025

SATB1 maintains naive-like identity in antiviral CD8⁺ T cells by limiting chromatin remodelling at effector gene loci.

Optimal CD8+ T cell differentiation requires the engagement of transcriptional programs that drive effector phenotypes and function, whilst also shutting down transcriptional programs that maintain the naive state. While the distinct factors that underpin each state are well studied, the molecular mechanisms that control the switch from the naive to effector state are not fully understood. Utilising integrated analysis of single-cell genomic data, we identified CD8+ T cell effector transcriptional networks that are restrained in the naive state by the chromatin binding protein Special AT-rich sequence binding protein-1 (SATB1). Utilising a SATB1-Tg model, whereby activated CD8+ T cells are unable to down regulate SATB1 upon activation, we observed limited effector differentiation and an inability to engage effector programs in response to both primary and secondary influenza A virus infection. Mechanistically, SATB1 limited chromatin remodelling at key gene loci required for the full engagement of the CD8+ T cell effector program. Hence, SATB1 is a master gatekeeper that maintains the naive T cell state and whose downregulation is necessary to allow transition from a naive to effector state upon T cell activation. SATB1 modulation may provide new strategies for improving CD8+ T cell longevity and self-renewal capacity in different immunotherapeutic treatments.

immunology↗

bioRxiv2024

ConvexGating infers gating strategies from clusters in single cell cytometry data

Manual expert gating remains common practice for the definition of specific cell populations in the analysis of flow cytometry data. The increasing number of measured parameters per individual cell and high inter-rater variability makes manual gating inconsistent in many scenarios such as multi-center studies. Here, we propose ConvexGating, an AI tool that automatically learns gating strategies in an unbiased, fully data-driven, yet interpretable manner. ConvexGating scales efficiently with increasing parameter space, creating proficient strategies with low-contamination in the extracted population for previously known and so far unknown or ill-defined cell populations. The inferred strategies are independent of parent populations, for instance, plasmacytoid dendritic cells (pDCs) can be fully identified as CD45RA- CD123+. In addition to flow cytometry data, ConvexGating derives gating strategies for cyTOF (Cytometry by Time of Flight) and CITEseq (Cellular Indexing of Transcriptomes and Epitopes by Sequencing) data and supports optimal design of marker panels for cell sorting.

immunology↗

bioRxiv2024

Characterizing human CMV-specific CD8+ T cells using multi-layer single-cell omics

In this study we established a comprehensive workflow to collect multi-omics single-cell data using a commercially available micro-well based platform. This included whole transcriptome, cell surface markers (targeted sequencing-based cell surface proteomics), T cell specificities, adaptive immune receptor repertoire (AIRR) profiles and sample multiplexing. With this technique we identified novel paired T cell receptor sequences for three prominent human CMV epitopes. In addition, we review the ability of dCODE dextramers to detect antigen-specific T cells at low frequencies by estimating sensitivities and specificities when used as reagents for single-cell multi-omics. MotivationIn this study, we report the first five-layer multi-omics dataset using the BD Rhapsody single-cell platform for the characterization of human antigen-specific T cells. Modalities include whole transcriptome, T cell receptor (TCR) sequences, T cell antigen specificity measured by dCODE dextramers, surface marker proteins and combinatorial sample multiplexing combining two distinct hashing approaches.

genomics↗

bioRxiv2024

TREM2 expression level is critical for microglial state, metabolic capacity and efficacy of TREM2 agonism

Triggering receptor expressed on myeloid cells 2 (TREM2) is a central regulator of microglial activity and sequence variants are major risk factors for late onset Alzheimers disease (LOAD). To better understand the molecular and functional changes associated with TREM2 signalling, we generated a TREM2 reporter mouse model and observed a gradual upregulation of reporter expression with increasing plaque proximity. Isolated microglia were sorted based on reporter expression and their transcriptomic profiles acquired in both wildtype and APP transgenic animals, allowing us to disentangle TREM2 versus pathology-specific effects. Bulk RNA-sequencing highlighted TREM2 level-dependent changes in major immunometabolic pathways, with enrichment of genes in oxidative phosphorylation and cholesterol metabolism in microglia with increased TREM2 expression. To confirm these findings, we next analysed uptake of fluorodeoxyglucose (FDG) and examined metabolomic and lipidomic profiles. Again, independent of A{beta} pathology, TREM2 expression correlated with uptake of FDG as well as increased cellular redox, energetics, and cholesterol homeostasis. Finally, we performed chronic treatment with a brain penetrant TREM2 agonist and identified a window of TREM2 expression where microglia are most responsive. Thus, our data provide novel insights into TREM2-mediated regulation of microglial metabolic function and informs current efforts to bring TREM2 agonists into clinical application.

neuroscience↗

bioRxiv2024

DrugDiff - small molecule diffusion model with flexible guidance towards molecular properties

With the cost/yield-ratio of drug development becoming increasingly unfavourable, recent work has explored machine learning to accelerate early stages of the development process. Given the current success of deep generative models across domains, we here investigated their application to the property-based proposal of new small molecules for drug development. Specifically, we trained a latent diffusion model -- DrugDiff -- paired with predictor guidance to generate novel compounds with a variety of desired molecular properties. The architecture was designed to be highly flexible and easily adaptable to future scenarios. Our experiments showed successful generation of unique, diverse and novel small molecules with targeted properties. The code is available at https://github.com/MarieOestreich/DrugDiff.

bioinformatics↗

bioRxiv2024

Unveiling the Power of High-Dimensional Cytometry Data with cyCONDOR

High-dimensional cytometry (HDC) is a powerful technology for studying single-cell phenotypes in complex biological systems. Although technological developments and affordability have made HDC broadly available in recent years, technological advances were not coupled with an adequate development of analytical methods that can take full advantage of the complex data generated. While several analytical platforms and bioinformatics tools have become available for the analysis of HDC data, these are either web-hosted with limited scalability or designed for expert computational biologists, making their use unapproachable for wet lab scientists. Additionally, end-to-end HDC data analysis is further hampered due to missing unified analytical ecosystems, requiring researchers to navigate multiple platforms and software packages to complete the analysis. To bridge this data analysis gap in HDC we developed cyCONDOR, an easy-to-use computational framework covering not only all essential steps of cytometry data analysis but also including an array of downstream functions and tools to expand the biological interpretation of the data. The comprehensive suite of features of cyCONDOR, including guided pre-processing, clustering, dimensionality reduction, and machine learning algorithms, facilitates the seamless integration of cyCONDOR into clinically relevant settings, where scalability and disease classification are paramount for the widespread adoption of HDC in clinical practice. Additionally, the advanced analytical features of cyCONDOR, such as pseudotime analysis and batch integration, provide researchers with the tools to extract deeper insights from their data. We used cyCONDOR on a variety of data from different tissues and technologies demonstrating its versatility to assist the analysis of high dimensionality data from preprocessing to biological interpretation.

bioinformatics↗

bioRxiv2023

Fecal microbial transfer and complex carbohydrates mediate protection against COPD

ObjectiveChronic obstructive pulmonary disease (COPD) is a major cause of global illness and death, most commonly caused by cigarette smoke. The mechanisms of pathogenesis remain poorly understood, limiting the development of effective therapies. The gastrointestinal microbiome has been implicated in chronic lung diseases via the gut-lung axis, but its role is unclear. DesignUsing an in vivo mouse model of cigarette smoke-induced COPD and fecal microbial transfer (FMT), we characterized the fecal microbiota using metagenomics, proteomics and metabolomics. Findings were correlated with airway and systemic inflammation, lung and gut histopathology, and lung function. Complex carbohydrates were assessed in mice using a high resistant starch diet, and in sixteen COPD patients using a randomized, double-blind, placebo-controlled pilot study of inulin supplementation. ResultsFMT alleviated hallmark features of COPD (inflammation, alveolar destruction, impaired lung function), gastrointestinal pathology and systemic immune changes. Protective effects were additive to smoking cessation. Disease features correlated with the relative abundance of Muribaculaceae, Desulfovibrionaceae and Lachnospiraceae family members. Proteomics and metabolomics identified downregulation of glucose and starch metabolism in cigarette smoke-associated microbiota, and supplementation of mice or human patients with complex carbohydrates improved disease outcomes. ConclusionThe gut microbiome contributes to COPD pathogenesis and can be targeted therapeutically. What is already known on this topicO_LIChanges in gut microbiota are associated with COPD but the underlying host and microbial mechanisms are unclear, limiting the therapeutic applications. C_LI What this study addsO_LIMicrobiome composition and metabolism is reproducibly correlated with lung and gastrointestinal pathology in experimental COPD. C_LIO_LIMicrobiome modifying interventions effectively alleviate disease, including protective effects supplementing smoking cessation. C_LIO_LINutritional interventions targeting the microbiome in COPD patients demonstrate efficacy in a small pilot study. C_LI How this study might affect research, practice or policyO_LIMicrobiome-targeting therapeutics and nutritional interventions may be developed for COPD, including as supplements to smoking cessation. C_LI

physiology↗

bioRxiv2023

Donor tissue-resident memory-like T and NK cells generate a transient peripheral chimerism in lung transplant recipients, potentially protective from chronic lung allograft dysfunction

Lung transplantation (LTx) is the only definite treatment option of patients suffering from end- stage lung disease. Long-term outcome is hampered by chronic allograft dysfunction resulting from poorly defined immune mechanisms. In this study of 97 lung recipients, we demonstrate dynamic changes of T, B and NK cell subsets early after lung transplantation with a selective decrease in memory CD4+ and CD8+ T cells accompanied by a relative increase in NK cells. Simultaneously, donor-derived T and NK cells were detected in recipient blood (n=44) immediately after LTx, persisting for three weeks. Donor T and NK cells displayed a CD69+ but CD103-CD49a- CD25- phenotype, which was shared by T and NK cells in lung perfusion solutions. In order to uncover the origin of these donor T and NK cells, the immune compartment of human lung explant tissue, i.e. trachea and parenchyma, was analyzed and it revealed three major subsets: classical circulating CD69-CD103-CD49a- T and NK cells, CD69+CD103+CD49a+ tissue-resident memory (TRM) T and NK cells and CD69+CD103-CD49a- TRM-like T and NK cells. Single-cell RNA sequencing confirmed the presence of TRM-like subsets with unique features, which reflected the phenotypes of donor T and NK cells and created a transient chimerism in recipient blood. Higher frequencies of donor T cells within the first three weeks showed a tendency for protection from chronic lung allograft dysfunction (CLAD) two years after transplantation although the correlation analyses did not reach statistical significance. To the best of our knowledge, we show for the first time that a transient chimerism is established within the first weeks after lung transplantation by donor TRM- like T and NK cells, which may contribute to protection from chronic lung allograft dysfunction (CLAD) development. Single Sentence SummaryDonor TRM-like T and NK cells cause a transient chimerism in lung recipients and potentially contribute to protection from CLAD.

immunology↗

bioRxiv2022

Pytometry: Flow and mass cytometry analytics in Python

Flow and mass cytometry data are commonly analyzed via manual gating strategies which requires prior knowledge, expertise and time. With increasingly complex experiments with many parameters and samples, traditional manual flow and mass cytometry data analysis becomes cumbersome if not inefficient. At the same time, computational tools developed for the analysis of single-cell RNA-sequencing data have made single cell genomics analysis highly efficient, yet they are mostly inaccessible for the analysis of flow and mass cytometry data due to different data formats, noise assumptions and scales. To bring the advantages of both fields together, we developed Pytometry as an extension to the popular scanpy framework for the analysis of flow and mass cytometry data. We showcase a standard analysis workflow on healthy human bone marrow data, illustrating the applicability of tools developed for the larger feature space of single cell genomics data. Pytometry combines joint analysis of multiple samples and advanced computational applications, ranging from automated pre-processing, cell type annotation and disease classification.

systems biology↗

bioRxiv2022

Apolipoprotein E controls Dectin-1-dependent development of monocyte-derived alveolar macrophages upon pulmonary β-glucan-induced inflammatory adaptation

The lung is constantly exposed to the outside world and optimal adaptation of immune responses is crucial for efficient pathogen clearance. However, mechanisms which lead to the functional and developmental adaptation of lung-associated macrophages remain elusive. To reveal such mechanisms, we developed a reductionist model of environmental intranasal {beta}-glucan exposure, allowing for the detailed interrogation of molecular mechanisms of pulmonal macrophage adaptation. Employing single-cell transcriptomics, high dimensional imaging and flow cytometric characterization paired to in vivo and ex vivo challenge models, we reveal that pulmonary low-grade inflammation results in the development of Dectin-1 - Card9 signaling-dependent monocyte-derived macrophages (MoAM). MoAMs expressed high levels of CD11b, ApoE, Gpnmb and Ccl6, were glycolytic and produced large amounts of interleukin 6 upon restimulation. Myeloid cell specific ApoE ablation inhibited monocyte to MoAM differentiation dependent on M-CSF secretion, promoting MoAM cell death thus impeding MoAM maintenance. In vivo, {beta}-glucan-elicited MoAMs limited the bacterial burden of Legionella pneumophilia post infection and ameliorated fibrosis severity in a murine fibrosis model. Collectively these data identify MoAMs that are generated upon environmental cues and ApoE as an important determinant for lung immune resilience.

immunology↗

bioRxiv2021

Aberrant paracrine signalling for bone remodelling underlies the mutant histone-driven giant cell tumour of bone.

Oncohistones represent compelling evidence for a causative role of epigenetic perturbations in cancer. Giant cell tumours of bone (GCTs) are characterised by a mutated histone H3.3 as the sole genetic driver present in bone-forming osteoprogenitor cells but absent from abnormally large bone-resorbing osteoclasts which represent the hallmark of these neoplasms. While these striking features imply a pathogenic interaction between mesenchymal and myelomonocytic lineages during GCT development, the underlying mechanisms remain unknown. We show that the changes in the transcriptome and epigenome in the mesenchymal cells caused by the H3.3-G34W mutation contribute to increase osteoclast recruitment in part via reduced expression of the TGF{beta}-like soluble factor, SCUBE3. In turn, osteoclasts secrete unregulated amounts of SEMA4D enhancing proliferation of mutated osteoprogenitors and arresting their maturation. These findings provide a mechanism by which GCTs undergo differentiation upon denosumab treatment, a drug that depletes osteoclasts. In contrast, gain of hTERT activity, commonly found in malignant GCT, makes neoplastic cells insensitive to osteoclasts, predicting the unresponsiveness to denosumab. We provide a mechanism for GCT initiation and its response to current treatment, the basis of which is dysfunctional cross-talk between bone-forming and bone-resorbing cells, emphasising the importance of tumor/microenvironment bidirectional interactions in tumorigenesis.

cancer biology↗

bioRxiv2021

Multiple trajectory alignment reconstructs disease dynamics for discovery and clinical benefit

Diseases change over time, both phenotypically and in underlying driving molecular processes. Though understanding disease progression dynamics is critical for diagnostics and treatment, capturing these dynamics is difficult, due to their complexity and the high heterogeneity between individuals. We developed TimeAx, an algorithm which builds a comparative framework for capturing disease dynamics using high-dimensional short time-series data. We demonstrate TimeAx utility by studying disease progression dynamics for multiple diseases and data types. Notably, for urothelial bladder cancer tumorigenesis, we identified a stromal pro-invasion point on the disease progression axis, characterized by massive immune cell infiltration to the tumor microenvironment and increased mortality. Moreover, the continuous TimeAx model differentiated between early and late tumors within the same tumor subtype, uncovering novel molecular transitions and potential targetable pathways. Overall, we present a powerful approach for studying disease progression dynamics, providing improved molecular interpretability and clinical benefits for patient stratification and outcome prediction.

systems biology↗

bioRxiv2021

Multi-layered transcriptomic analyses reveal an immunological overlap between COVID-19 and hemophagocytic lymphohistiocytosis associated with disease severity

Severe COVID-19 patients present a clinical and laboratory overlap with other hyperinflammatory conditions such as hemophagocytic lymphohistiocytosis (HLH). However, the underlying mechanisms of these conditions remain to be explored. Here, we investigated the transcriptome of 1596 individuals, including patients with COVID-19 in comparison to healthy controls, other acute inflammatory states (HLH, multisystem inflammatory syndrome in children [MIS-C], Kawasaky disease [KD]), and different respiratory infections (seasonal coronavirus, influenza, bacterial pneumonia). We observed that COVID-19 and HLH share immunological pathways (cytokine/chemokine signaling and neutrophil-mediated immune responses), including gene signatures that stratify COVID-19 patients admitted to the intensive care unit (ICU) and COVID-19_nonICU patients. Of note, among the common differentially expressed genes (DEG), there is a cluster of neutrophil-associated genes that reflects a generalized hyperinflamatory state since it is also dysregulated in patients with KD and bacterial pneumonia. These genes are dysregulated at protein level across several COVID-19 studies and form an interconnected network with differentially expressed plasma proteins that point to neutrophil hyperactivation in COVID-19 patients admitted to the intensive care unit. scRNAseq analysis indicated that these genes are specifically upregulated across different leukocyte populations, including lymphocyte subsets and immature neutrophils. Artificial intelligence modeling confirmed the strong association of these genes with COVID-19 severity. Thus, our work indicates putative therapeutic pathways for intervention.

immunology↗

bioRxiv2021

The stem cell-specific protein TRIM71 inhibits maturation and activity of the pro-differentiation miRNA let-7 via two independent molecular mechanisms

The stem cell-specific RNA-binding protein TRIM71/LIN-41 was the first identified target of the pro-differentiation and tumor suppressor miRNA let-7. TRIM71 has essential functions in embryonic development and a proposed oncogenic role in several cancer types, such as hepatocellular carcinoma. Here, we show that TRIM71 regulates let-7 expression and activity via two independent mechanisms. On the one hand, TRIM71 enhances pre-let-7 degradation through its direct interaction with LIN28 and TUT4, thereby inhibiting let-7 maturation and indirectly promoting the stabilization of let-7 targets. On the other hand, TRIM71 represses the activity of mature let-7 via its RNA-dependent interaction with the RNA-Induced Silencing Complex (RISC) effector protein AGO2. We found that TRIM71 directly binds and stabilizes let-7 targets, suggesting that let-7 activity inhibition occurs on active RISCs. MiRNA enrichment analysis of several transcriptomic datasets from mouse embryonic stem cells and human hepatocellular carcinoma cells suggests that these let-7 regulatory mechanisms shape transcriptomic changes during developmental and oncogenic processes. Altogether, our work reveals a novel role for TRIM71 as a miRNA repressor and sheds light on the precise mechanistic dual regulation of let-7.

molecular biology↗

bioRxiv2021

Induction of peri-implantation stage synthetic embryos using reprogramming paradigms in ESCs

Blastocyst-derived stem cell lines were shown to self-organize into embryo-like structures in 3D cell culture environments. Here, we provide evidence that synthetic embryo-like structures are generated solely based on transcription factor-mediated molecular reprogramming of embryonic stem cells in a simple 3D co-culture system. ESCs in these cultures self-organize into elongated, compartmentalized synthetic embryo-like structures over the course of reprogramming exhibiting anterior visceral endoderm formation and symmetry breaking. Single-cell RNA-Seq reveals transcriptional profiles resembling epiblast, visceral endoderm, and extraembryonic ectoderm of early murine embryos around E4.5-E5.5. Within the epiblast, compartment marker gene expression supports primordial germ cell specification. After transplantation, synthetic embryo-like structures implant in uteri and initiate the formation of decidual tissues. This system allows for fast and reproducible generation of synthetic embryo-like structures, providing further insights into synthetic embryology.

synthetic biology↗