Search bioRxiv⌕ Search

Biology subjects

Boltengagen, A.

Publications and source records attributed to Boltengagen, A..

10 recordsLinked to original sources

Spatiotemporal dynamics of tumor microenvironment remodelling

During tumorigenesis, interactions between tumor and stromal cells progressively remodel the tumor microenvironment (TME) towards pro-tumoral functions. Understanding early TME remodeling dynamics is therefore crucial for developing interceptive therapies. However, clinical samples typically provide isolated, late tumorigenesis snapshots. To overcome this limitation, we generated triple-negative breast cancer mice that develop multifocal, asynchronous tumors along a continuous luminal-to-basal transdifferentiation trajectory. Ordering spatial transcriptomes from 100+ ducts along this trajectory reveals the spatiotemporal dynamics of TME remodeling and underlying molecular mechanisms. Cancer-associated myofibroblasts (myCAFs) emerge as key players in advanced tumors, where they orchestrate pro-invasive remodeling of the tumor-stromal interface. myCAFs are conserved in patient-derived xenograft models and steer tumor trajectories towards invasive phenotypes when co-injected with tumor cells in syngeneic mice. Our study shows that temporal ordering of spatially-resolved disease snapshots unravels some of the molecular "forces" that, starting from the cell-of-origin, propel cells/microenvironments along a disease trajectory.

cancer biology↗

Open-ST: High-resolution spatial transcriptomics in 3D

Spatial transcriptomics (ST) methods have been developed to unlock molecular mechanisms underlying tissue development, homeostasis, or disease. However, there is a need for easy-to-use, high-resolution, cost-efficient, and 3D-scalable methods. Here, we report Open-ST, a sequencing-based, open-source experimental and computational resource to address these challenges and to study the molecular organization of tissues in 3D. In mouse brain, Open-ST captured transcripts at subcellular resolution and reconstructed cell types. In primary tumor and patient-matched healthy/metastatic lymph nodes, Open-ST captured the diversity of immune, stromal and tumor populations in space. Distinct cell states were organized around cell-cell communication hotspots in the tumor, but not the metastasis. Strikingly, the 3D reconstruction and multimodal analysis of the metastatic lymph node revealed spatially contiguous structures not visible in 2D and potential biomarkers precisely at the 3D tumor/lymph node boundary. We anticipate Open-ST to accelerate the identification of spatial molecular mechanisms in 2D and 3D.

systems biology↗

High-resolution molecular atlas of a lung tumor in 3D

Cells live and interact in three-dimensional (3D) cellular neighborhoods. However, histology and spatial omics methods mostly focus on 2D tissue sections. Here we present a 3D spatial atlas of a routine clinical sample, an aggressive human lung carcinoma, by combining in situ quantification of 960 cancer-related genes across [~]340,000 cells with measurements of tissue-mechanical components. 3D cellular neighborhoods subdivided the tumor microenvironment into tumor, stromal, and immune multicellular niches. Interestingly, pseudotime analysis suggested that pro-invasive epithelial-to-mesenchymal transition (EMT), detected in stroma-infiltrating tumor cells, already occurred in one region at the tumor surface. There, myofibroblasts and macrophages specifically co-localized with pre-invasive tumor cells and their multicellular molecular signature identified patients with shorter survival. Moreover, cytotoxic T-cells did not infiltrate this niche but colocalized with inhibitory dendritic and regulatory T cells. Importantly, systematic scoring of cell-cell interactions in 3D neighborhoods highlighted niche-specific signaling networks accompanying tumor invasion and immune escape. Compared to 2D, 3D neighborhoods improved the characterization of immune niches by identifying dendritic niches, capturing the 3D extension of T-cell niches and boosting the quantification of niche-specific cell-cell interactions, including druggable immune checkpoints. We believe that 3D communication analyses can improve the design of clinical studies investigating personalized, combination immuno-oncology therapies.

systems biology↗

Urinary single-cell sequencing captures intrarenal injury and repair processes in human acute kidney injury

Acute kidney injury (AKI) is a major health issue, the outcome of which depends primarily on damage and reparative processes of tubular epithelial cells (TEC). Mechanisms underlying AKI remain incompletely understood, specific therapies are lacking and monitoring the course of AKI in clinical routine is confined to measuring urine output and plasma levels of filtration markers. Here we demonstrate feasibility and potential of a novel approach to assess the cellular and molecular dynamics of AKI by establishing a robust urine-to-single cell RNA sequencing (scRNAseq) pipeline for excreted kidney cells via flow cytometry sorting. We analyzed 42,608 single cell transcriptomes of 40 urine samples from 32 AKI patients and compared our data with reference material from human AKI post-mortem biopsies and published mouse data. We demonstrate that TEC transcriptomes mirror intrarenal pathology and reflect distinct injury and repair processes, including oxidative stress, inflammation, and tissue rearrangement. We also describe an AKI-specific abundant urinary excretion of progenitor-like cells. In conclusion, single cell transcriptomics of kidney cells excreted in urine provides non-invasive, unprecedented insight into cellular processes underlying AKI, thereby opening novel opportunities for target identification, AKI sub-categorization and monitoring of natural disease course and interventions. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=130 SRC="FIGDIR/small/479234v2_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@e7175corg.highwire.dtl.DTLVardef@1aed1e6org.highwire.dtl.DTLVardef@5655f4org.highwire.dtl.DTLVardef@2512a7_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

Transcriptomic responses of the human kidney to acute injury at single cell resolution

BackgroundAcute kidney injury (AKI) occurs frequently in critically ill patients and is associated with adverse outcomes. Cellular mechanisms underlying AKI and kidney cell responses to injury remain incompletely understood. MethodsWe performed single-nuclei transcriptomics, bulk transcriptomics, molecular imaging studies, and conventional histology on kidney tissues from 8 individuals with severe AKI (stage 2 or 3 according to Kidney Disease: Improving Global Outcomes (KDIGO) criteria). Specimens were obtained within 1-2 hours after individuals had succumbed to critical illness associated with respiratory infections, with 4 of 8 individuals diagnosed with COVID-19. Control kidney tissues were obtained post-mortem or after nephrectomy from individuals without AKI. ResultsHigh-depth single cell-resolved gene expression data of human kidneys affected by AKI revealed enrichment of novel injury-associated cell states within the major cell types of the tubular epithelium, in particular in proximal tubules, thick ascending limbs and distal convoluted tubules. Four distinct, hierarchically interconnected injured cell states were distinguishable and characterized by transcriptome patterns associated with oxidative stress, hypoxia, interferon response, and epithelial-to-mesenchymal transition, respectively. Transcriptome differences between individuals with AKI were driven primarily by the cell type-specific abundance of these four injury subtypes rather than by private molecular responses. AKI-associated changes in gene expression between individuals with and without COVID-19 were similar. ConclusionThe study provides an extensive resource of the cell type-specific transcriptomic responses associated with critical illness-associated AKI in humans, highlighting recurrent disease-associated signatures and inter-individual heterogeneity. Personalized molecular disease assessment in human AKI may foster the development of tailored therapies.

molecular biology↗

Optogenetic perturbations of RNA expression in tissue space

Organoids derived from stem cells become increasingly important to study human development and to model disease. However, methods are needed to control and study spatio-temporal patterns of gene expression in organoids. To this aim, we combined optogenetics and gene perturbation technologies to activate or knock-down RNA of target genes, at single-cell resolution and in programmable spatio-temporal patterns. To illustrate the usefulness of our approach, we locally activated Sonic Hedgehog (SHH) signaling in an organoid model for human neurodevelopment. High-resolution spatial transcriptomic and single-cell analyses showed that this local induction was sufficient to generate stereotypically patterned organoids in three dimensions and revealed new insights into SHHs contribution to gene regulation in neurodevelopment. With this study, we propose optogenetic perturbations in combination with spatial transcriptomics as a powerful technology to reprogram and study cell fates and tissue patterning in organoids.

bioengineering↗

The neuroinflammatory interleukin-12 signaling pathway drives Alzheimer's disease-like pathology by perturbing oligodendrocyte survival and neuronal homeostasis

Alzheimers disease (AD) is characterized by deposition of pathological amyloid-{beta} (A{beta}) and tau protein aggregates and involves chronic neuroinflammation, ultimately leading to neurodegeneration and cognitive decline. Central in AD-related neuroinflammation is the proinflammatory interleukin-12 (IL-12)/IL-23 signaling pathway whose inhibition has been shown to attenuate pathology and cognitive defects in AD-like mice. In order to explore which cell types are involved in this neuroinflammatory cascade, we used single-nuclei RNA sequencing in AD-like APPPS1 mice lacking or harboring IL-12/IL-23 signaling. We found Il12b transcripts encoding the common p40 subunit of IL-12/IL-23 signaling to be expressed preferentially, but not exclusively, in microglia in an AD-specific manner. In contrast, transcripts for the other subunits of the IL-12 signaling pathway were expressed constitutively in neurons and oligodendrocytes irrespective of AD pathology, while transcripts for IL-23 were almost undetectable. Notably, genetic ablation of IL-12/IL-23 signaling did not affect the inflammatory gene expression profile of the AD-specific disease associated microglia (DAM), but reversed the loss of mature myelin-producing oligodendrocytes and alterations in neuronal homeostasis in APPPS1 mice. Taken together, our results reveal that IL-12, but not IL-23 is the main driver of AD-specific IL-12/IL-23 neuroinflammation, which alters neuronal and oligodendrocyte functions. Given that drugs targeting IL-12 already exist, our data may foster first clinical trials in AD subjects using this novel neuroimmune target.

neuroscience↗

Single-cell RNA-sequencing of Herpes simplex virus 1-infected cells identifies NRF2 activation as an antiviral program

Herpesvirus infection initiates a range of perturbations in the host cell, which remain poorly understood at the level of individual cells. Here, we quantified the transcrips of single human primary fibroblasts during the first hours of lytic infection with HSV-1. By applying a generalizable analysis scheme, we defined a precise temporal order of early viral gene expression and found unexpected bifurcations and bottlenecks. We identified individual host cell genes and pathways relevant in early infection by combining three different computational approaches: gene and pathway overdispersion analysis, prediction of cell-state transition probabilities as well as future cell states. One transcriptional program, which was turned on in infected cells and correlated with increased resistance to infection, implicated the transcription factor NRF2. Consequently, Bardoxolone methyl, a known NRF2 agonist, impaired virus production, suggesting that NRF2 activation restricts the progression of viral infection. Our study provides novel insights into early stages of HSV-1 infection and serves as a general blueprint for the investigation of heterogenous cell states in virus infection.

systems biology↗

The Drosophila Embryo at Single Cell Transcriptome Resolution

Drosophila is a premier model system for understanding the molecular mechanisms of development. By the onset of morphogenesis, ~6000 cells express distinct gene combinations according to embryonic position. Despite extensive mRNA in situ screens, combinatorial gene expression within individual cells is largely unknown. Therefore, it is difficult to comprehensively identify the coding and non-coding transcripts that drive patterning and to decipher the molecular basis of cellular identity. Here, we single-cell sequence precisely staged embryos, measuring >3100 genes per cell. We produce a transcriptomic blueprint of development - a virtual embryo where 3D locations of sequenced cells are confidently identified. Our \"Drosophila-Virtual-Expression-eXplorer\" performs virtual in situ hybridizations and computes expression gradients. Using DVEX, we predict spatial expression and discover patterned lncRNAs. DEVX is sensitive enough to detect subtle evolutionary changes in expression patterns between Drosophila species. We believe DVEX is a prototype for powerful single cell studies in complex tissues.

genomics↗

Cell fixation and preservation for droplet-based single-cell transcriptomics

BackgroundRecent developments in droplet-based microfluidics allow the transcriptional profiling of thousands of individual cells, in a quantitative, highly parallel and cost-effective way. A critical, often limiting step is the preparation of cells in an unperturbed state, not compromised by stress or ageing. Another challenge are rare cells that need to be collected over several days, or samples prepared at different times or locations.\n\nResultsHere, we used chemical fixation to overcome these problems. Methanol fixation allowed us to stabilize and preserve dissociated cells for weeks. By using mixtures of fixed human and mouse cells, we showed that individual transcriptomes could be confidently assigned to one of the two species. Single-cell gene expression from live and fixed samples correlated well with bulk mRNA-seq data. We then applied methanol fixation to transcriptionally profile primary single cells from dissociated complex tissues. Low RNA content cells from Drosophila embryos, as well as mouse hindbrain and cerebellum cells sorted by FACS, were successfully analysed after fixation, storage and single-cell droplet RNA-seq. We were able to identify diverse cell populations, including neuronal subtypes. As an additional resource, we provide dropbead, an R package for exploratory data analysis, visualization and filtering of Drop-seq data.\n\nConclusionsWe expect that the availability of a simple cell fixation method will open up many new opportunities in diverse biological contexts to analyse transcriptional dynamics at single cell resolution.

genomics↗