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Mapping transcription factor functions in astrocytes using in vivo gain-of-function Perturb-seq.
An in vivo approach combining high-throughput screening with cell type-specific readouts could enable elucidation of genotype-phenotype relationships in complex tissues. We developed an in vivo gain-of-function Perturb-seq platform, termed iGOF-Perturb-seq, to build a functional atlas of ~1000 transcription factors (TFs) in astrocytes, a cell type essential to many brain functions. We then identified cofunctional modules, annotated uncharacterized TFs, and predicted disease-associated TF clusters. Furthermore, iGOF-Perturb-seq performed in a mouse neuroinflammatory model identified Ferd3l as a therapeutic candidate, and astrocyte-specific overexpression of Ferd3l alleviated Alzheimer's disease symptoms in mice. This study provides resources for understanding gene regulation and disease mechanisms in vivo and for identifying potential therapeutic targets for different brain diseases.
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Single-cell atlas of human lung aging identifies cell type dyssynchrony and increased transcriptional entropy.
Age is a major risk factor for lung disease. We characterized the changing cellular, transcriptional, and genomic landscape of human lung aging using single-cell RNA sequencing. We find that lung aging is cell-type dyssynchronous, with alveolar epithelial and endothelial cells exhibiting the greatest transcriptional changes. Among alveolar epithelial cells, aging is associated with a decreased relative proportion of surfactant-expressing SPChigh AT2 cells. Among alveolar capillary cells, we observed loss of differentiation and capillary function. Analysis of somatic mutations called from single-cell data revealed an increase with aging, with alveolar epithelial and endothelial cell types exhibiting greater mutation burdens. Transcriptional entropy was increased with aging and was an independent predictor of age. Notably, cells expressing commonly accepted senescence signatures did not increase with age. Our results reveal cell type dyssynchrony in human lung aging with age-related changes concentrated in alveolar epithelial and endothelial cells.
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Single-cell RNA sequencing reveals hypoxia-associated stress response signatures in the immune and stromal microenvironment of laryngeal squamous cell carcinoma.
BACKGROUND: Laryngeal squamous cell carcinoma (LSCC) remains a major clinical challenge with limited therapeutic options and unsatisfactory outcomes. Hypoxia-induced stress responses are known to contribute to tumor progression, immune remodeling, and therapeutic resistance. However, the cell type-specific hypoxia-associated transcriptional programs within the immune and stromal microenvironment of LSCC remain incompletely understood. METHODS: We analyzed an immune-enriched LSCC single-cell RNA sequencing dataset (GSE150321, GSM4546858), generated by CD45-based magnetic bead sorting, to characterize hypoxia-associated stress response signatures across immune and stromal cell populations. The workflow included quality control, dimensionality reduction, unsupervised clustering, cell type annotation, pathway enrichment, hypoxia score assessment, robust rank aggregation, pseudotime trajectory inference, and cell-cell communication analysis. Representative hypoxia-associated genes were further validated experimentally in LSCC-related cell models. RESULTS: Nine major cell populations were identified, including T cells, epithelial cells, B cells, macrophages, dendritic cells, cycling cells, fibroblasts, mast cells, and endothelial cells. Hypoxia-associated pathway activity was broadly enriched, with particularly strong activation in myeloid populations. Slingshot analysis using macrophages as the trajectory root revealed a monocyte-to-macrophage maturation trajectory, along which hypoxia scores were highest in macrophages and decreased toward lymphoid cells (Spearman R = -0.271, P = 1.78 × 10-¹7). Myeloid-specific hypoxia-associated genes, including PLA2G7, CD163, and APOC1, were identified. Robust rank aggregation further highlighted candidate hypoxia-associated genes such as HIF1A, CXCL8, S100A8, and ENO1. Experimental validation in THP-1 cells confirmed hypoxia-induced upregulation of these genes, and ELISA showed increased CXCL8 secretion under hypoxia (985 ± 87 vs. 215 ± 34 pg/mL, P < 0.001). In contrast, the novel myeloid-specific genes showed negligible expression in Hep-2 epithelial cells, supporting their cell-type specificity. CONCLUSIONS: This study characterizes hypoxia-associated transcriptional programs within the immune and stromal microenvironment of LSCC rather than providing a comprehensive malignant epithelial tumor atlas. The findings highlight myeloid-centered hypoxia adaptation as potential sources of biomarker candidates and therapeutic insight for LSCC. THP-1 monocytic cell validation provides functional support for myeloid-centered hypoxia adaptation.
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Single-cell transcriptomic atlas of Alzheimer's disease middle temporal gyrus reveals region, cell type, and sex specificity of gene expression with novel genetic risk for MERTK in female.
BackgroundAlzheimer's disease (AD), the most common age-related neurodegenerative disease, is closely associated with both amyloid-β plaque and neuroinflammation. Two thirds of AD patients are female, and they have a higher disease risk; women with AD have more extensive brain histological changes than men along with more severe cognitive symptoms and neurodegeneration.ObjectiveThis study aimed to determine how sex difference induces structural brain changes and molecular cell vulnerabilities in AD, with a focus on identifying sex-specific transcriptional alterations and genetic risk factors.MethodsWe performed single nucleus RNA sequencing on postmortem brains from individuals with AD and age- and sex-matched controls, focusing on the middle temporal gyrus, a cortical brain region strongly affected by the disease, and integrated single nucleus RNA sequencing results with genome-wide association study (GWAS) data using cell type-specific enrichment and generalized gene-set analysis approaches. The analysis pipeline is provided with threshold information.ResultsWe identified a selectively vulnerable subpopulation of layer 2/3 excitatory neurons that were RORB-negative and CDH9-expressing in both males and females. Disease-associated, but sex-independent, reactive astrocyte signatures were also present. In clear contrast, the microglia signatures of AD brains differed between males and females. Integrating single cell transcriptomic data with results from GWAS, we identified MERTK genetic variation as a candidate novel risk factor for AD selectively in females.ConclusionsTaken together, our single cell atlas of middle temporal gyrus revealed a unique cellular-level view of sex-specific transcriptional changes in AD, illuminating GWAS identification of sex-specific AD genes. These data serve as a rich resource for interrogation of the molecular and cellular basis of AD.
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Single-cell spatial transcriptomic analysis of human skin anatomy.
The skin is the largest human organ and a site of substantial disease burden, yet its cellular and molecular organization across the body is largely undefined. Here we construct an organ-wide single-cell spatial atlas of ~1.2 million cells from normal adult human skin, resolving the location of 45 cell types across 114 samples encompassing 15 anatomic sites. We uncover site-specific stereotypic cell-type composition and their organization into ten multicellular neighborhoods, most notably a perivascular neighborhood reminiscent of skin-associated lymphoid tissue. Within this neighborhood, ligand-receptor (L-R) analyses identify a central role for tumor necrosis factor in maintaining CCL19+ perivascular fibroblasts, highlighting homeostatic immune-stromal crosstalk. Finally, comparing neighborhood dynamics in spatial transcriptomics of skin disease, we find pan-disease immune alterations in this perivascular neighborhood, suggesting spatial compartmentalization of pathogenic activity. Thus, multicellular neighborhoods underlie the skin's multiscale molecular to macroanatomic organization, orchestrate cell-cell interactions and anatomic site specialization and exhibit architectural disruption in disease.
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Single-cell and bulk transcriptomic profiling of metabolism-related lncRNAs reveals tumor heterogeneity and prognostic markers in non-small cell lung cancer.
PURPOSE: Non-small cell lung cancer (NSCLC), including lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), exhibits marked tumor heterogeneity and poor prognosis. Metabolic reprogramming is a hallmark of cancer, and long non-coding RNAs (lncRNAs) have emerged as important regulators of tumor metabolism and immune interactions. This study aimed to systematically characterize metabolism-related lncRNAs in NSCLC using single-cell and bulk transcriptomic data, and to evaluate their associations with tumor heterogeneity, immune microenvironment, and clinical outcomes. METHODS: RNA sequencing and clinical data for LUAD and LUSC were obtained from The Cancer Genome Atlas. Metabolism-related lncRNAs were identified through partial correlation analysis combined with KEGG pathway-based gene set enrichment analysis. Tumor microenvironment characteristics were assessed using CIBERSORTx. Consensus clustering based on the top 20 metabolism-related lncRNAs was applied to define molecular subtypes. Cis- and trans-regulatory relationships were explored using Spearman correlation, and competing endogenous RNA networks were constructed by integrating TargetScan-predicted miRNA-mRNA interactions. Findings were validated across six independent datasets, and single-cell transcriptomic data were used to assess cell-type-specific expression patterns. RESULTS: A subset of metabolism-related lncRNAs was significantly enriched among differentially expressed and survival-associated lncRNAs in NSCLC. AL365181.2 was identified as a key lncRNA associated with multiple metabolic pathways and poor prognosis. Single-cell analysis revealed immune cell-specific expression patterns, particularly in B cells, CD8+ T cells, and natural killer cells. Metabolic lncRNA-based clustering defined distinct molecular subtypes with significant differences in immune profiles and clinical outcomes. CONCLUSIONS: Metabolism-related lncRNAs contribute substantially to tumor heterogeneity and prognosis in NSCLC and may serve as valuable biomarkers for patient stratification and personalized therapeutic strategies.
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Single-Cell Transcriptome Analysis of Peripheral Neutrophils From Patients With Idiopathic Pulmonary Arterial Hypertension.
BACKGROUND: Idiopathic pulmonary hypertension (IPAH) is a rare and devastating disease often accompanied by persistent inflammation and immune responses. We aim to provide a reference atlas of neutrophils to facilitate a better understanding of cellular phenotypes and discovery of candidate genes. METHODS: Peripheral neutrophils from naive patients with IPAH and matched controls were profiled. Whole-exon sequencing was performed to exclude known genetic mutations before establishing single-cell RNA sequencing. Marker genes were validated by flow cytometry and histology in a separate validation cohort. RESULTS: Seurat clustering analysis revealed that the landscape of neutrophils encompassed 5 clusters, including 1 progenitor, 1 transition, and 3 functional clusters. The intercorrelated genes in patients with IPAH were mainly enriched in antigen processing presentation and natural killer cell mediated cytotoxicity. We identified and validated differentially upregulated genes, including MMP9 (matrix metallopeptidase 9), ISG15 (ISG15 ubiquitin-like modifier), and CXCL8 (C-X-C motif ligand 8). The positive proportions and fluorescence quantification of these genes were significantly increased in CD16+ neutrophils in patients with IPAH. The higher proportion of positive MMP9 neutrophils increased mortality risk after adjustment for age and sex. Patients with higher proportions of positive MMP9 neutrophils had worse survival, while the fraction of ISG15- or CXCL8-positive expression neutrophils failed to predict outcome. CONCLUSIONS: Our study yields a comprehensive dataset of the landscape of neutrophils in patients with IPAH. The predictive values of a neutrophil cluster characterized by higher MMP9 expression indicate a functional role for neutrophil-specific matrix metalloproteinases in the pathogenesis of pulmonary arterial hypertension.
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Single-cell transcriptional atlas reveals distinct immune-chondrocyte crosstalk mechanisms in temporomandibular joint osteoarthritis induced by different types of occlusal disorder.
Temporomandibular joint (TMJ) osteoarthritis (OA) is a progressive degenerative disease in which the intricate mechanisms of the condyle cartilage damage are yet to be disclosed. A detailed characterization of cellular composition and signal networks involved in the pathogenesis is in need. This study, for the first time, identified chondrocytes heterogeneity and subchondral immune microenvironments based on single-cell transcriptomes of the mouse mandibular condyle, and provided insights into the cellular and signaling basis of the homeostasis of the condyle and pathogenesis of TMJOA by healthy-to-diseased comparisons. The differentially expressed gene pattern distinguished 8 chondrocyte subsets and 9 immune cell types in the condyle. Close interactions were found between these cell populations, with enhanced communication between chondrocytes and immune cell subsets in the condyles subjected to anterior premature contact (APC) model or unilateral anterior crossbite (UAC) model. The single-cell transcriptomic changes suggested predominant roles of neutrophils in immune-chondrocyte interactions in these occlusal disorder models. Neutrophils-derived TNF-α signaling was inferred to be the most greatly enhanced information flow in the condyle of the APC model, while increased Thbs1-Sdc4 signaling in mediating neutrophils-to-chondrocytes interactions was indicated in the UAC-model condyle, with predominant BSP signaling. Interfering in these signaling by drug administration demonstrated therapeutic potential for the APC- or UAC-induced TMJOA.
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Cellular communities reveal trajectories of brain ageing and Alzheimer's disease.
Alzheimer's disease (AD) has recently been associated with diverse cell states1-11, yet when and how these states affect the onset of AD remains unclear. Here we used a data-driven approach to reconstruct the dynamics of the brain's cellular environment and identified a trajectory leading to AD that is distinct from other ageing-related effects. First, we built a comprehensive cell atlas of the aged prefrontal cortex from 1.65 million single-nucleus RNA-sequencing profiles sampled from 437 older individuals, and identified specific glial and neuronal subpopulations associated with AD-related traits. Causal modelling then prioritized two distinct lipid-associated microglial subpopulations-one drives amyloid-β proteinopathy while the other mediates the effect of amyloid-β on tau proteinopathy-as well as an astrocyte subpopulation that mediates the effect of tau on cognitive decline. To model the dynamics of cellular environments, we devised the BEYOND methodology, which identified two distinct trajectories of brain ageing, each defined by coordinated progressive changes in certain cellular communities that lead to (1) AD dementia or (2) alternative brain ageing. Thus, we provide a cellular foundation for a new perspective on AD pathophysiology that informs personalized therapeutic development, targeting different cellular communities for individuals on the path to AD or to alternative brain ageing.
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[Immune cell characteristics of the liver in a mouse model of fatty liver disease induced by high-ethanol-producing Klebsiella pneumoniae based on single-cell transcriptome sequencing].
Objective: To construct a single-cell transcriptomic atlas of the liver in a mouse model of fatty liver disease induced by high-ethanol-producing Klebsiella pneumoniae (HiAlc Kpn) and characterize the heterogeneity of hepatic immune cell subtypes in this model. Methods: Twelve six-week-old male C57BL/6 mice were randomly divided into a control group (n=6) and a model group (n=6). The model group was gavaged with a HiAlc Kpn TH1 strain (HiAlc Kpn, 1×107 CFU/ml, 200 μl in YEPD medium) every 2 days for 8 weeks to induce fatty liver disease, while controls received YEPD medium alone. After the model establishment, livers were harvested for single-cell RNA sequencing (10×Genomics). Sequencing data were processed in R for quality control, dimensionality reduction, clustering, and cell-type annotation, followed by pseudo-time trajectory analysis, pathway enrichment analysis, and ligand-receptor interaction network analysis. Results: The single-cell atlas revealed marked immunological shifts in the model livers compared to controls. T cells were less prevalent in the model (46.48% vs. 64.91%, χ2=569.14, P<0.001), whereas B cells were more abundant (29.97% vs. 15.19%,χ2=530.21, P<0.001). Within T cell subtypes, the model group had fewer effector CD4+T cells (15.55% vs. 29.50%, χ2=530.21, P<0.001), effector CD8+T cells (13.41% vs. 20.19%, χ2=66.96, P<0.001), and a cytotoxic CD8+T subset (1.18% vs. 4.89%, χ2=84.68, P<0.001). By contrast, naive CD4+T cells (17.96% vs. 11.32%, χ2=79.67, P<0.001), naive CD8+T cells (30.59% vs. 15.90%, χ2=277.63, P<0.001), and exhausted CD8+T cells (7.75% vs. 5.99%, χ2=10.44, P=0.001) were more frequent in the model. Notably, exhausted cytotoxic CD8+T cells in the model exhibited diminished expression of cytotoxic genes (Ifng, Gzma, t=2.74, P=0.006; t=1.97, P=0.048) alongside upregulation of inhibitory receptors (Lag3, Tigit, t=-3.09, P=0.002; t=-2.38, P=0.017), indicating functional exhaustion. B cell compartment changes were also pronounced. The model showed a corresponding reduction in germinal center B cells (5.67% vs. 56.53%, χ2=1157.50, P<0.001) and plasma cells (9.09% vs. 21.56%, χ2=109.81, P<0.001), with a dramatic expansion of naive B cells (42.71% vs. 6.81%, χ2=542.07, P<0.001) and proliferating B cells (33.16% vs. 7.02%, χ2=332.20, P<0.001). Pathway enrichment analysis indicated that B cell subtypes in the model group were enriched for pathways related to B cell activation, whereas B cells in the control group were enriched for pathways maintaining homeostasis. Additionally, ligand-receptor interaction analysis revealed an enhanced communication network between plasma B cells and T cell subtypes in the model group compared to controls. Conclusion: This study has constructed a comprehensive single-cell transcriptomic map of HiAlc Kpn-induced fatty liver disease under high glucose conditions in mice and provided new insights into the immune cell heterogeneity underlying this disease model.