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Schulte-Schrepping, J.

Publications and source records attributed to Schulte-Schrepping, J..

15 recordsLinked to original sources

Perturb-seq identifies co-regulated gene programs shaping hematopoietic stem and progenitor cell function

To sustain blood formation, hematopoietic stem and progenitor cells (HSPCs) coordinate a multitude of cell biological processes, from cell cycle control and stress responses to lineage priming. While many genetic regulators of high-level HSPC function have been identified, how HSPCs coordinate more basal cell biological programs, and how such programs relate to stem cell function, remains incompletely understood. Here we use Perturb-seq to profile the transcriptional consequences of targeting 520 genes by CRISPRi in primary mouse HSPC cultures. We developed an analytical strategy to separate perturbation-induced changes in cell-state abundance and clonal heterogeneity from cell-state-local transcriptional effects. From these local perturbation signatures, we identified 19 gene regulatory programs (GRPs) that are defined by co-regulation in response to genetic perturbation, in contrast to co-expression or human curation, and align well with cell biological processes. By decomposing gene expression data from functional and clinical studies into program activity, we show that GRP activities associate with, and predict, phenotypes such as clonal output after transplantation, as well as survival and drug response in retrospective acute myeloid leukemia (AML) cohorts. Together, our study establishes perturbation-derived co-regulation programs as an interpretable framework for linking genetic regulators, cell-biological processes and stem-cell-associated phenotypes.

genomics↗

Memory T Cells in MHC-Deficient Humanized Mice

Major histocompatibility complexes (MHC) govern antigen presentation and T cell receptor (TCR) selection. Accurate in vivo modeling of human immunity therefore requires physiological human MHC TCR interactions. Humanized NOD scid IL2null (NSG) mice engrafted with human CD34+ hematopoietic stem cells are widely used to provide preclinical platforms for the development of advanced therapies; however, interactions between murine MHC and human TCR can promote xenoreactivity and alter T cell development. Here, we investigated how elimination of murine MHC together with different conditioning regimens shapes human T cell maturation in vivo. CD34+ cells from ten cord blood donors were transplanted into conventional NSG mice or murine MHC deficient NSG derivatives (DKO) following either sublethal irradiation or myeloablative busulfan conditioning. Integrated analyses combining flow cytometry, plasma cytokine profiling, and bulk and single cell TCR sequencing revealed marked differences in T cell differentiation across models. Busulfan conditioned DKO mice developed highly proliferative, activated, and cytotoxic T cells together with clonally expanded TCR repertoires. In contrast, irradiated NSG mice preferentially accumulated naive, NKT, and regulatory T cell populations. Busulfan-conditioned DKO mice showed no evidence of xenogeneic graft versus host disease and represent a refined enabling platform for human T cell development and provide a foundation for future preclinical evaluation of advanced gene and cell therapies.

immunology↗

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↗

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↗

Molecular determinants of brain-resident CD8+ T cell formation and function

Tissue-resident memory T (Trm) cells are strategically located to provide frontline protection upon antigen re-encounter while possessing tissue-specific transcriptional programs. Whether brain Trm cells similarly adapt to their tissue environment, and to what extent their molecular signature is altered in neuropathology, remains unclear. Here we profile brain Trm cells under homeostasis and in the contexts of aging, beta-amyloidosis, and systemic viral infection. From these studies, a tissue-specific CD8+ T cell landscape emerged, defined by the expression of the transcription factor TCF-1 and the inhibitory receptor PD-1. TCF-1 was critical for the formation and phenotypic maturation of brain CD8+ Trm cells, while PD-1 signaling was necessary for robust effector function and antigen-specific recall response. In addition, the cytokine transforming growth factor (TGF)-{beta} was required for the differentiation of brain CD8+ Trm cells and restricted their transition into effector-like cells upon antigenic rechallenge. These findings highlight common as well as tissue-specific features of brain CD8+ Trm cells and provide insights into the molecular mechanisms governing their formation and function.

immunology↗

Molecular architecture of human dermal sleeping nociceptors

Human dermal sleeping nociceptors display ongoing activity in neuropathic pain, affecting 10% of the population. Despite advances in rodents, a molecular marker for these mechano-insensitive C-fibers (CMis) in human skin remains elusive, preventing targeted therapy. In this translational Patch-seq study, we combine single-cell transcriptomics following electrophysiological characterization with single-nucleus and spatial transcriptomics from pigs and humans. We functionally identified CMis in pig sensory neurons with patch-clamp using adapted protocols from human microneurography. We identified oncostatin-M-receptor (OSMR) and somatostatin (SST) as marker genes for CMis. Following dermal injection in healthy human volunteers, oncostatin-M, the ligand of OSMR, exclusively modulates CMis. We identified the entire molecular architecture of human dermal sleeping nociceptors, providing new therapeutic targets and the basis for a mechanistic understanding of neuropathic pain. One Sentence SummaryWe identify the molecular architecture and specifically OSMR and SST as molecular markers for human dermal sleeping nociceptors, key players in the generation of neuropathic pain. Short versionIn this Patch-seq study, we identify OSMR and SST as molecular markers for human dermal sleeping nociceptors, key players in the generation of neuropathic pain.

neuroscience↗

BBSome-dependent ciliary Hedgehog signaling governs cell fate in the white adipose tissue

The primary cilium has emerged as critical in regulating whole-body energy metabolism, as reflected in the Bardet-Biedl syndrome (BBS), where primary cilia dysfunction leads to obesity due to hyperphagia and white adipose tissue (WAT) remodeling. The regulation of cell fate and differentiation of adipocyte precursor cells (APCs) is key to maintaining WAT homeostasis during obesity. Using mice that recapitulated the BBS patient phenotype (Bbs8-/-), we demonstrate that primary cilia dysfunction reduces the stem-cell-like P1 APC subpopulation by inducing a phenotypic switch into a fibrogenic progenitor state, characterized by extracellular matrix (ECM) remodeling and upregulation of CD9. Single-cell RNA sequencing revealed a direct transition of stem-cell-like P1 cells into fibrogenic progenitors, bypassing the committed P2 cells. Ectopic ciliary Hedgehog signaling upon loss of BBS8 emerged as a central driver of the molecular changes in Bbs8-/- APCs, altering differentiation into adipocytes and lipid uptake. These findings unravel a novel role for primary cilia in governing APC fate, determining the delicate balance between adipogenesis and fibrogenesis. The identified molecular mechanisms provide insights into potential therapeutic targets for obesity.

cell biology↗

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↗

Decoding mechanism of action and susceptibility to drug candidates from integrated transcriptome and chromatin state

Omics-based technologies are driving major advances in precision medicine but efforts are still required to consolidate their use in drug discovery. In this work, we exemplify the use of multi-omics to support the development of 3-chloropiperidines (3-CePs), a new class of candidate anticancer agents. Combined analyses of transcriptome and chromatin accessibility elucidated the mechanisms underlying sensitivity to test agents. Further, we implemented a new versatile strategy for the integration of RNA-seq and ATAC-seq data, able to accelerate and extend the standalone analyses of distinct omic layers. This platform guided the construction of a perturbation-informed basal signature able to predict cancer cell lines sensitivity and to further direct compound development against specific tumor types. Overall, this approach offered a scalable pipeline to support the early phases of drug discovery, understanding of mechanism and potentially inform the positioning of therapeutics in the clinic.

systems biology↗

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↗

Soluble mannose receptor induces pro-inflammatory macrophage activation andobesity-associated metaflammation

Pro-inflammatory activation of macrophages in metabolic tissues is critically important in induction of obesity-induced metaflammation. Here, we demonstrate that the soluble mannose receptor (sMR) plays a direct, functional role in both macrophage activation and metaflammation. We show that sMR binds CD45 on macrophages and inhibits its phosphatase activity, leading to a Src/Akt/NF-{kappa}B-mediated cellular reprogramming towards an inflammatory phenotype both in vitro and in vivo. Remarkably, increased serum sMR levels were observed in obese mice and humans and directly correlated with body weight. Additionally, MR deficiency lowers pro-inflammatory macrophages in metabolic tissues and protects against hepatic steatosis and whole-body metabolic dysfunctions in high-fat diet-induced obese mice. Conversely, administration of sMR in lean mice increases serum pro-inflammatory cytokines, activates tissue macrophages and promotes insulin resistance. Altogether, our results reveal sMR as novel regulator of pro-inflammatory macrophage activation which could constitute a new therapeutic target for metaflammation and other hyperinflammatory diseases.

immunology↗

Alterations of multiple alveolar macrophage states in chronic obstructive pulmonary disease

Despite the epidemics of chronic obstructive pulmonary disease (COPD), the cellular and molecular mechanisms of this disease are far from being understood. Here, we characterize and classify the cellular composition within the alveolar space and peripheral blood of COPD patients and control donors using a clinically applicable single-cell RNA-seq technology corroborated by advanced computational approaches for: machine learning-based cell-type classification, identification of differentially expressed genes, prediction of metabolic changes, and modeling of cellular trajectories within a patient cohort. These high-resolution approaches revealed: massive transcriptional plasticity of macrophages in the alveolar space with increased levels of invading and proliferating cells, loss of MHC expression, reduced cellular motility, altered lipid metabolism, and a metabolic shift reminiscent of mitochondrial dysfunction in COPD patients. Collectively, single-cell omics of multi-tissue samples was used to build the first cellular and molecular framework for COPD pathophysiology as a prerequisite to develop molecular biomarkers and causal therapies against this deadly disease.

systems biology↗

Memory-driven computing accelerates genomic data processing

Next generation sequencing (NGS) is the driving force behind precision medicine and is revolutionizing most, if not all, areas of the life sciences. Particularly when targeting the major common diseases, an exponential growth of NGS data is foreseen for the next decades. This enormous increase of NGS data and the need to process the data quickly for real-world applications requires to rethink our current compute infrastructures. Here we provide evidence that memory-driven computing (MDC), a novel memory-centric hardware architecture, is an attractive alternative to current processor-centric compute infrastructures. To illustrate how MDC can change NGS data handling, we used RNA-seq assembly and pseudoalignment followed by quantification as two first examples. Adapting transcriptome assembly pipelines for MDC reduced compute time by 5.9-fold for the first step (SAMtools). Even more impressive, pseudoalignment by near-optimal probabilistic RNA-seq quantification (kallisto) was accelerated by more than two orders of magnitude with identical accuracy and indicated 66% reduced energy consumption. One billion RNA-seq reads were processed in just 92 seconds. Clearly, MDC simultaneously reduces data processing time and energy consumption. Together with the MDC-inherent solutions for local data privacy, a new compute model can be projected pushing large scale NGS data processing and primary data analytics closer to the edge by directly combining high-end sequencers with local MDC, thereby also reducing movement of large raw data to central cloud storage. We further envision that other data-rich areas will similarly benefit from this new memory-centric compute architecture.

bioinformatics↗

Diagnostic value of blood gene expression-based classifiers as exemplified for acute myeloid leukemia

ABSTRACTAcute Myeloid Leukemia (AML) is a severe, mostly fatal hematopoietic malignancy. Despite nearly two decades of promising results using gene expression profiling, international recommendations for diagnosis and differential diagnosis of AML remain based on classical approaches including assessment of morphology, immunophenotyping, cytochemistry, and cytogenetics. Concerns about the translation of whole transcriptome profiling include the robustness of derived predictors when taking into account factors such as study- and site-specific effects and whether achievable levels of accuracy are sufficient for practical use. In the present study, we sought to shed light on these issues via a large-scale analysis using machine learning methods applied to a total of 12,029 samples from 105 different studies. Taking advantage of the breadth of data and the now much improved understanding of high-dimensional modeling, we show that AML can be predicted with high accuracy. High-dimensional approaches - in which multivariate signatures are learned directly from genome-wide data with no prior biological knowledge - are highly effective and robust. We explore also the relationship between predictive signatures, differential expression and known AML-related genes. Taken together, our results support the notion that transcriptome assessment could be used as part of an integrated genomic approach in cancer diagnosis and treatment to be implemented early on for diagnosis and differential diagnosis of AML.\n\nOne Sentence SummaryBlood gene expression data and machine learning were used to develop robust and accurate classifiers for diagnosis and differential diagnosis of acute myeloid leukemia based on analysis of more than 12,000 samples derived from more than 100 individual studies

genomics↗

Cellular reprogramming of human monocytes is regulated by time-dependent IL4 signalling and NCOR2

The clinical and therapeutic value of human in vitro generated monocyte-derived dendritic cell (moDC) and macrophages is well established. However, in line with recent findings regarding myeloid cell ontogeny and due to our limited understanding of their physiological counterparts, transcriptional regulation and heterogeneity, the full potential of these important cellular systems is still underestimated.\n\nIn this study, we use cutting edge high-dimensional analysis methods to better understand the transcriptional organization, phenotypic heterogeneity and functional differences between human ex vivo isolated and in vitro generated mononuclear phagocytes with the aim to better realize their full potential in the clinic.\n\nWe demonstrate that human monocytes activated by MCSF or GMCSF most closely resemble inflammatory macrophages identified in vivo, while IL4 signalling in the presence of GMCSF generates moDCs resembling inflammatory DCs in vivo, but not steady state cDC1 or cDC2. Moreover, these reprogramming regimes lead to activated monocytes that present with profoundly different transcriptomic, metabolic, phenotypic and functional profiles. Furthermore, we demonstrate that CD14+ monocytes are integrating multiple exogenous activation signals such as GMCSF and IL4 in a combinatorial and temporal fashion, resulting in a high-dimensional cellular continuum of reprogrammed monocytes dependent on the mode and timing of cytokine exposure. Utilizing nanostraw-based knockdown technology, we demonstrate that the IL4-dependent generation of moDCs relies on the induction, nuclear localization and function of the transcriptional regulator NCOR2.\n\nFinally, we unravel unappreciated heterogeneity within the clinically moDCs population and propose a novel high-dimensional phenotyping strategy to better tailor clinical quality control strategies for patient need and culture conditions to enhance therapeutic outcome.

immunology↗