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Single-Cell Landscape of Mouse Islet Allograft and Syngeneic Graft.
Islet transplantation to treat the late stage of type 1 diabetic patient (T1DM) has recently made inspiring success in clinical trials. However, most patients experience a decline in islet graft function in one to three years due to immune rejection. Although the mechanisms of immune cells, including macrophages, dendritic cells (DCs), neutrophils, natural killer cells (NKs), B cells, and T cells, that mediate immune rejection have been investigated, the overall characteristics of immune infiltrates in islet allografts and syngeneic grafts remain unclear. Single-cell RNA sequencing (scRNA-seq) has provided us with new opportunities to study the complexity of the immune microenvironment in islet transplants. In the present study, we used scRNA-seq to comprehensively analyze the immune heterogeneity in the mouse model of islet transplantation. Our data revealed T lymphocytes and myeloid cells as the main immune components of grafts 7 days post-islet transplantation, especially in allografts. Moreover, our results indicated that allogeneic islet cells were transformed into antigen-presenting cell-like cells with highly expressed MHC class I molecules and genes involved in MHC class I-mediated antigen presentation. This transformation may dramatically facilitate the interaction with cytotoxic CD8+ T cells and promote the destruction of islet allografts. Our study provides insight into the transcriptomics and diverse microenvironment of islet grafts and their impacts on immune rejection.
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A single-cell resolved genotype-phenotype map using genome-wide genetic and environmental perturbations.
Heterogeneity is inherent to living organisms and it determines cell fate and phenotypic variability. Despite its ubiquity, the underlying molecular mechanisms and the genetic basis linking genotype to-phenotype heterogeneity remain a central challenge. Here we construct a yeast knockout library with a clone and genotype RNA barcoding structure suitable for genome-scale analyses to generate a high-resolution single-cell yeast transcriptome atlas of 3500 mutants under control and stress conditions. We find that transcriptional heterogeneity reflects the coordinated expression of specific gene programs, generating a continuous of cell states that can be responsive to external insults. Cell state plasticity can be genetically modulated with mutants that act as state attractors and disruption of state homeostasis results in decreased adaptive fitness. Leveraging on intra-genetic variability, we establish that regulators of transcriptional heterogeneity are functionally diverse and influenced by the environment. Our multimodal perturbation-based single-cell Genotype-to-Transcriptome Atlas in yeast provides insights into organism-level responses.
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Delineating mouse β-cell identity during lifetime and in diabetes with a single cell atlas.
Although multiple pancreatic islet single-cell RNA-sequencing (scRNA-seq) datasets have been generated, a consensus on pancreatic cell states in development, homeostasis and diabetes as well as the value of preclinical animal models is missing. Here, we present an scRNA-seq cross-condition mouse islet atlas (MIA), a curated resource for interactive exploration and computational querying. We integrate over 300,000 cells from nine scRNA-seq datasets consisting of 56 samples, varying in age, sex and diabetes models, including an autoimmune type 1 diabetes model (NOD), a glucotoxicity/lipotoxicity type 2 diabetes model (db/db) and a chemical streptozotocin β-cell ablation model. The β-cell landscape of MIA reveals new cell states during disease progression and cross-publication differences between previously suggested marker genes. We show that β-cells in the streptozotocin model transcriptionally correlate with those in human type 2 diabetes and mouse db/db models, but are less similar to human type 1 diabetes and mouse NOD β-cells. We also report pathways that are shared between β-cells in immature, aged and diabetes models. MIA enables a comprehensive analysis of β-cell responses to different stressors, providing a roadmap for the understanding of β-cell plasticity, compensation and demise.
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A Single-Cell Atlas of the Upper Respiratory Epithelium Reveals Heterogeneity in Cell Types and Patterning Strategies.
UNLABELLED: The upper respiratory tract, organized along the pharyngolaryngeal-to-tracheobronchial axis, is essential for homeostatic functions such as breathing and vocalization. The upper respiratory epithelium is frequently exposed to pollutants and pathogens, making this an area of first-line defense against respiratory injury and infection. The respiratory epithelium is composed of a rich array of specialized cell types, each with unique capabilities in immune defense and injury repair. However, the precise transcriptomic signature and spatial distribution of these cell populations, as well as potential cell subpopulations, have not been well defined. Here, using single cell RNAseq combined with spatial validation, we present a comprehensive atlas of the mouse upper respiratory epithelium. We systematically analyzed our rich RNAseq dataset of the upper respiratory epithelium to reveal 17 cell types, which we further organized into three spatially distinct compartments: the Tmprss11a + pharyngolaryngeal, the Nkx2-1 + tracheobronchial, and the Dmbt1 + submucosal gland epithelium. We profiled/analyzed the pharyngolaryngeal epithelium, composed of stratified squamous epithelium, and identified distinct regional signatures, including a Keratin gene expression code. In profiling the tracheobronchial epithelium, which is composed of a pseudostratified epithelium-with the exception of the hillock structure-we identified that regional luminal cells, such as club cells and basal cells, show varying gradients of marker expression along the proximal-distal and/or dorsal-ventral axis. Lastly, our analysis of the submucosal gland epithelium, composed of an array of cell types, such as the unique myoepithelial cells, revealed the colorful diversity of between and within cell populations. Our single-cell atlas with spatial validation highlights the distinct transcriptional programs of the upper respiratory epithelium and serves as a valuable resource for future investigations to address how cells behave in homeostasis and pathogenesis. HIGHLIGHTS: - Defined three spatially distinct epithelial compartments, Tmprss11a + pharyngolaryngeal, Nkx2-1 + tracheobronchial, and Dmbt1 + submucosal gland, comprising 17 total cell types - Profiled Keratin gene expression code along proximal-distal and basal-luminal axes and highlighted "stress-induced" Keratins KRT6A and KRT17 at homeostasis - Demarcated expression gradients of Scgb1a1 + and Scgb3a2+ club cells along the proximal-distal axes - Specified submucosal gland cell heterogeneity including Nkx3-1+ mucin-producing cells, with ACTA2+ basal myoepithelial cells exhibiting gene profile for neuroimmune mediated signaling.
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Single‑cell atlas reveals a Wilms' tumor 1‑mediated axis driving granulosa cell senescence in human ovarian aging.
Ovarian aging is a key cause of reproductive decline in women. Chronic inflammation and granulosa cell (GC) senescence are implicated in this process; however, the underlying cell‑type‑specific changes and regulatory mechanisms remain incompletely understood. The present study thus aimed to provide insight into these mechanisms. For this purpose, publicly available single‑cell transcriptomic data from human ovarian tissues in the Gene Expression Omnibus database (GSE202601) were analyzed, including four young donors (23‑29 years of age) and four aged donors (49‑54 years of age). Following quality control and integration, clustering, CellChat, pseudotime and SCENIC analyses were performed to define age‑related changes in cellular composition, intercellular communication and transcriptional regulation. Key findings were further supported by complementary in vivo and in vitro experiments in the ovaries of young and aged mice and primary GCs. Integrated analysis revealed marked age‑related shifts in ovarian cellular composition, including the enrichment of a pro‑inflammatory NLRP3+ macrophage subpopulation and a senescence‑associated GC subtype in aged ovaries. Cell‑cell communication analysis suggested enhanced immune‑endocrine crosstalk in aged ovaries, with increased IL‑1β‑IL‑1R1 signaling between macrophages and GCs. Pseudotime and transcriptional regulatory network analyses identified Wilms' tumor 1 (WT1) as a candidate transcription factor upregulated in aged GCs and positively associated with p21 expression, suggesting a potential role in senescence‑associated cell cycle arrest. Experimental validation further supported increased inflammatory signaling, oxidative stress and the activation of the WT1/p21 axis in aged ovaries. On the whole, these findings provide a high‑resolution single‑cell framework for understanding human ovarian aging and suggest that inflammatory signaling and WT1‑associated transcriptional reprogramming may contribute to GC senescence and ovarian functional decline.
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Single-Cell Analysis of the Normal Mouse Aorta Reveals Functionally Distinct Endothelial Cell Populations.
BACKGROUND: The cells that form the arterial wall contribute to multiple vascular diseases. The extent of cellular heterogeneity within these populations has not been fully characterized. Recent advances in single-cell RNA-sequencing make it possible to identify and characterize cellular subpopulations. METHODS: We validate a method for generating a droplet-based single-cell atlas of gene expression in a normal blood vessel. Enzymatic dissociation of 4 whole mouse aortas was followed by single-cell sequencing of >10 000 cells. RESULTS: Clustering analysis of gene expression from aortic cells identified 10 populations of cells representing each of the main arterial cell types: fibroblasts, vascular smooth muscle cells, endothelial cells (ECs), and immune cells, including monocytes, macrophages, and lymphocytes. The most significant cellular heterogeneity was seen in the 3 distinct EC populations. Gene set enrichment analysis of these EC subpopulations identified a lymphatic EC cluster and 2 other populations more specialized in lipoprotein handling, angiogenesis, and extracellular matrix production. These subpopulations persist and exhibit similar changes in gene expression in response to a Western diet. Immunofluorescence for Vcam1 and Cd36 demonstrates regional heterogeneity in EC populations throughout the aorta. CONCLUSIONS: We present a comprehensive single-cell atlas of all cells in the aorta. By integrating expression from >1900 genes per cell, we are better able to characterize cellular heterogeneity compared with conventional approaches. Gene expression signatures identify cell subpopulations with vascular disease-relevant functions.
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The single-cell revolution in transplantation: high-resolution mapping of graft rejection, tolerance, and injury.
Single-cell sequencing technologies are fundamentally revolutionizing our understanding of transplantation biology by providing high-resolution cellular and molecular maps of graft rejection, immune tolerance, and injury. This review systematically summarizes the application of technologies such as single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics in solid organ and islet transplantation, aiming to elucidate the mechanisms that determine graft fate. Single-cell analyses have revealed profound insights unattainable by traditional methods, such as identifying key effector cell subpopulations-clonally expanded CD8+ tissue-resident memory T cells (TRM) - in acute rejection, and discovering new pathogenic pathways in chronic dysfunction, like antibody production driven by innate-like B cells. In parallel, these atlases have also uncovered the complex regulatory networks that mediate immune tolerance, composed of regulatory T cells and specific macrophage subpopulations. Furthermore, this technology has pioneered new clinical applications, including non-invasive monitoring through urinary single-cell sequencing and pre-transplant quality assessment of donor organs. By transitioning transplantation medicine from a morphology-based diagnostic model to a new era of molecular endophenotyping based on precise molecular signatures, single-cell technologies offer unprecedented opportunities for developing personalized immunosuppressive regimens, finding new therapeutic targets, and achieving non-invasive diagnostic monitoring. Although clinical translation still faces challenges, it has the potential to become a key tool for improving transplant outcomes in the future.
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A single-cell Arabidopsis root atlas reveals developmental trajectories in wild-type and cell identity mutants.
In all multicellular organisms, transcriptional networks orchestrate organ development. The Arabidopsis root, with its simple structure and indeterminate growth, is an ideal model for investigating the spatiotemporal transcriptional signatures underlying developmental trajectories. To map gene expression dynamics across root cell types and developmental time, we built a comprehensive, organ-scale atlas at single-cell resolution. In addition to estimating developmental progressions in pseudotime, we employed the mathematical concept of optimal transport to infer developmental trajectories and identify their underlying regulators. To demonstrate the utility of the atlas to interpret new datasets, we profiled mutants for two key transcriptional regulators at single-cell resolution, shortroot and scarecrow. We report transcriptomic and in vivo evidence for tissue trans-differentiation underlying a mixed cell identity phenotype in scarecrow. Our results support the atlas as a rich community resource for unraveling the transcriptional programs that specify and maintain cell identity to regulate spatiotemporal organ development.
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Comprehensive Single-Cell RNA Atlas of Human Laryngeal Normal, Preneoplastic, and Tumorigenic States.
PURPOSE: The mechanisms driving the progression of vocal cord leukoplakia (VCL) to laryngeal squamous cell carcinoma (LSCC) remain unclear, posing a significant barrier to the effective prevention, early diagnosis, and targeted treatment of LSCC. Therefore, it is essential to characterize the cellular microenvironmental differences between VCL and LSCC at single-cell resolution. EXPERIMENTAL DESIGN: In the study, we conducted single-cell RNA sequencing and spatial transcriptomics on surgical tissue specimens obtained from 36 patients diagnosed with vocal cord polyps (VCP), VCL, and LSCC. RESULTS: Our study generated the first single-cell atlas of VCP and VCL while expanding the cancer cell atlas of LSCC. This dataset comprises 318,907 cells and 12,679 spatial transcriptomic spots, allowing the identification of distinct cellular subclusters. We observed that VCL, as a transitional lesion between benign and malignant states, exhibits a hybrid microenvironment that mirrors VCP and LSCC, with early signs of immunosuppressive activity. Immunoregulatory cell populations demonstrate significant gene expression and functional pathway differences between VCL and LSCC. CONCLUSIONS: Our single-cell RNA sequencing and spatial transcriptomics analyses revealed the cellular heterogeneity underlying benign, precancerous, and malignant laryngeal lesions. We identified epithelial subclusters in VCL with malignant potential and observed shared immunosuppressive features with LSCC, suggesting their role in disease progression. These findings provide valuable insights into the molecular transition from VCL to LSCC and emphasize potential targets for early diagnosis and therapeutic intervention.
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Single-Cell RNA Sequencing of Thyroid Tissues Reveals Pathogenesis of Graves' Disease.
Graves' disease (GD) is an autoimmune disorder primarily targeting the thyroid tissue. While major histocompatibility complex (MHC)-dependent B cell activation and thyroid-stimulating hormone receptor (TSHR) autoantibody production are central to GD, the intrathyroidal immune landscape remains largely unexplored. Through single-cell RNA sequencing (scRNA-seq), this work constructed a comprehensive immune cell atlas, revealing dominant IFN-γ-secreting CD4+ T cells, expanded T peripheral helper (Tph) cells, CD11c+ atypical B cells, and CD8+ effector T cells. Notably, stress-surveilling γδ T/NK cells are enriched in GD. Thyroid follicular cells (TFCs) in GD exhibited a stressed phenotype, and in vitro functional assays showed that they promote γδ T cell activation and proliferation. γδ T cells may recruit conventional type 1 dendritic cells (cDC1) via XCL1/XCL2, suggesting a potential link to adaptive immune reorganization. These findings suggest an additional MHC-independent pathway linking TFC stress to autoimmune activation via γδ T cells in GD pathogenesis.