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Single-Cell RNA Sequencing Reveals Disrupted Stromal-Epithelial Crosstalk Impairs Gut Barrier in Depression.
BACKGROUND: Depressive disorder is commonly associated with gastrointestinal dysfunction, but the specific cellular and molecular alterations within the colonic mucosa remain poorly understood. The role of stromal-epithelial crosstalk in the colonic niche under depressive conditions is particularly unclear. METHODS: A chronic unpredictable mild stress (CUMS) mouse model of depression was established and validated behaviorally. Single-cell RNA sequencing (scRNA-seq) of colon tissues from CUMS and control mice was performed to define cellular composition and transcriptional changes. Pseudotime trajectory, Gene Set Variation Analysis (GSVA), and cell-cell interaction analyses were used to investigate differentiation pathways and functional states. Key findings were validated using intestinal organoid cultures and immunofluorescence staining. RESULTS: The CUMS model successfully induced depression-like behaviors. scRNA-seq revealed a global reduction in colonic epithelial cells and a severely disrupted differentiation trajectory in depressed mice. The continuum from stem to terminally differentiated states was broken, with concomitant downregulation of the stem cell marker Lgr5 and key tight junction genes Ocln, Tjp1(encoding zonula occludens-1, ZO-1), and Cldn2. We identified a profound stromal remodeling, characterized by expansion of specific subsets: cCF1 (colonic crypt-bottom fibroblast 1, which support the stem cell niche) and CTF (crypt-top fibroblasts, which promote epithelial differentiation). CTF cells adopted a pro-inflammatory, oxidative stress phenotype, while cCF1 cells exhibited a pro-fibrotic signature involving enhanced TGF-β and suppressed Wnt/β-catenin signaling. Cell communication analysis demonstrated a globally enhanced interaction network between epithelial stem cells and the expanded cCF1/CTF subsets in depression. Functionally, intestinal organoids derived from depressed mice exhibited altered growth and regenerative capacity, as evidenced by reduced Ki67-positive proliferating cells and Lgr5-positive stem cells in immunofluorescence staining. CONCLUSION: This study provides a single-cell transcriptomic atlas of the colon in depression, preliminary suggesting that disease pathology may involve functional reprogramming of the stromal niche. Expansion of disease-specific stromal populations cCF1 and CTF may disrupt epithelial homeostasis, suggesting a potential role in impaired stem cell function, dysregulated cellular differentiation, and compromised intestinal barrier integrity. These findings suggest a potential cellular mechanism for depression-associated gastrointestinal comorbidity and may provide a reference for the development of future treatment strategies.
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Brain Spatial Genomics Atlases.
Recent advances in single-cell RNA sequencing (scRNA-seq) have transformed neuroscience research by enabling the identification of genes, cell types, and molecular pathways involved in brain development and function. However, scRNA-seq lacks spatial information regarding the anatomic location of gene expression. Emerging spatial genomics technologies, including MERFISH, CosMx, Stereo-seq, and Visium Spatial Gene Expression overcome this limitation by enabling transcriptomic and epigenomic profiling within intact tissue architecture. Integration of spatial genomics with scRNA-seq has revolutionized genomics and biomedical research by allowing gene expression to be mapped in situ at cellular and even subcellular resolution. These advances have facilitated the construction of brain spatial genomics atlases in several species, including mouse, human, non-human primate, and zebrafish. Spatial genomics technologies are particularly valuable for defining cellular heterogeneity across brain regions and characterizing the spatial organization of neuronal circuits when integrated with single-cell sequencing approaches. These reference atlases provide powerful resources for investigating brain development, function and disease, and for identifying region-specific molecular signatures associated with neurological disorders. Here, we review currently available brain spatial genomics atlases and the spatial genomics technologies used to generate these reference resources.
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TCGAimmunosurv: An R package to identify genes associated with patient survival and immune cell state transitions using TCGA and single-cell RNA-seq data.
Cancer is a disease rooted in genomic alterations and has long stood as one of the most formidable foes for humanity since its inception. A patient's survival often hinges on the specific genomic mutations present and the corresponding immune system response. As each genomic alteration has its deleterious damage, identification of potential drivers of cancer progression may risk yielding false positives without a mutation-specific approach. To advance our understanding of tumor biology, there is a need for a systematic computational framework that combines both bulk RNA-seq and single-cell RNA-seq data analyses. In this work, we developed a pan-cancer R package called TCGAimmunosurv that integrates bulk RNA-Seq data from The Cancer Genome Atlas (TCGA) with single-cell RNA-Seq data to identify the genes to investigate mutation-specific immune dynamics. TCGAimmunosurv allows mutation-specific analysis by allowing users to select the genes of interest. It then identifies survival-associated genes from the mutation-specific samples obtained from TCGA. Then, it analyzes the user-given single-cell datasets and performs immune-subtype-specific pseudotime trajectory analysis. Finally, it seeks the gene(s) with strong expression patterns along pseudotime trajectories that are also associated with patient survivability and, thereby, bridges bulk and single-cell analyses for a comprehensive insight into the cancer driver genes.
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A single-cell atlas of Toxoplasma sexual development in the feline intestinal tract.
Toxoplasma gondii undergoes sexual development exclusively in the feline intestine, a process critical for genetic diversity and population expansion. Recent studies have identified genes critical in suppressing presexual development and metabolic differences in felines that may promote sexual development, but to date, the gene regulatory networks driving development in the cat are unknown. To investigate this, we performed single-cell transcriptomics on parasites isolated from cat intestines, using fluorescent reporter strains and flow cytometry. From 15,068 cells across 2 experiments, we identified rare populations, including cells that bear all of the hallmarks of gametes. Candidate genes emerging from this study were tested via CRISPR-Cas9 perturb-seq, identifying AP2X6 as a regulator of macrogametocyte development. Our single-cell data extend what is known about gene expression changes throughout sexual development and should be useful to those in the field working towards inducing gametogenesis, mating and oocyst production in vitro.
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A single-cell atlas of intracranial aneurysm progression identifies a dysfunctional VSMC subpopulation associated with rupture risk.
BACKGROUND: Intracranial aneurysm (IA) rupture is a life-threatening event. While inflammation is implicated, the cellular mechanisms associated with progression from stable lesion to rupture remain poorly defined at single-cell resolution. METHODS: We performed single-cell RNA sequencing (scRNA-seq) on a mouse model spanning sham, formed, and ruptured IA stages. Computational analyses included trajectory inference, cell-cell communication analysis, and metabolic scoring. Key findings were validated using human IA bulk RNA-seq data and protein-level assays on matched clinical tissues. RESULTS: Our single-cell atlas revealed a progressive "inflammatory-lytic" microenvironment marked by immune cell infiltration and vascular smooth muscle cell (VSMC) depletion. We identified a metabolically specialized VSMC subpopulation (VSMC_0) that was selectively lost in formed and ruptured aneurysms. Pseudotime analysis indicated VSMC differentiation blockade, associated with downregulation of the structural genes actin alpha2, smooth muscle (ACTA2) and prolyl 4-hydroxylase subunit alpha2 (P4HA2), which correlated with irregular aneurysm shape a strong clinical predictor of rupture risk. Cell communication analysis positioned VSMC_0 as a signaling hub to macrophages, suggesting a feed-forward inflammatory loop. These findings were validated in human IAs tissues. CONCLUSION: Our study identifies VSMC phenotypic dysregulation as a key correlate of IA instability, linking molecular deficits to clinical rupture predictors. This reframes IA as a disorder of vascular cellular identity and communication, revealing potential therapeutic targets for aneurysm stabilization.
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Integrated single-cell and bulk RNA sequencing unravels neutrophil heterogeneity and validates SPP1 as a prognostic biomarker in cervical cancer.
BACKGROUND: Cervical cancer (CC) remains a major global health burden, with tumor microenvironment (TME) plasticity and immune evasion driving its progression. The intricate heterogeneity of neutrophils and their complex crosstalk within the TME remain poorly understood, thereby limiting the development of targeted therapeutic strategies. Single-cell RNA sequencing (scRNA-seq) provides an unprecedented level of resolution for dissecting neutrophil subpopulations and elucidating their roles in CC pathogenesis. METHODS: We integrated scRNA-seq data from CC tissues (GSE208653, n = 5) with bulk RNA-seq cohorts from The Cancer Genome Atlas - Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (TCGA-CESC) and Genotype-Tissue Expression (GTEx) database. Using Seurat-based clustering, pseudotime trajectory analysis and CellChat, we mapped neutrophil dynamics and intercellular communication networks. Differentially expressed genes (DEGs) were analyzed using the limma package, followed by Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses. A prognostic model was subsequently constructed via LASSO-Cox regression. Key targets were further validated through both in vitro functional assays, immunohistochemical (IHC) and immunofluorescence (IF) analyses of human pathological specimens. RESULTS: Four functionally distinct neutrophil subtypes, including immature, mature, antitumor, and interferon-stimulated populations, were characterized in CC, demonstrating dynamic heterogeneity during tumorigenesis. Secreted Phosphoprotein 1 (SPP1) was identified as a critical differentially expressed gene, with the SPP1-CD44 axis serving as a key mediator of neutrophil-tumor cell crosstalk. Downregulation of SPP1 markedly suppressed CC cell migration, invasion, and proliferation. Furthermore, a prognostic signature based on risk stratification efficiently categorized patients into high- and low-risk cohorts, with validated clinical utility in predicting survival outcomes. CONCLUSIONS: Our study comprehensively characterized the TME in CC through single-cell transcriptomics. Integrated analysis with bulk RNA-seq established and validated a robust prognostic signature, identifying SPP1 as a key oncogenic driver. The SPP1-centric model demonstrates significant clinical utility for risk stratification. These findings provide new insights into neutrophil heterogeneity and establish a mechanistic foundation for precision therapeutics in CC.
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Integrating single-cell RNA-Seq and bulk RNA-Seq data to explore the key role of fatty acid metabolism in hepatocellular carcinoma.
Hepatocellular carcinoma (HCC) is a predominant cause of cancer-related mortality globally, noted for its propensity towards late-stage diagnosis and scarcity of effective treatment modalities. The process of metabolic reprogramming, with a specific emphasis on lipid metabolism, is instrumental in the progression of HCC. Nevertheless, the precise mechanisms through which lipid metabolism impacts HCC and its viability as a therapeutic target have yet to be fully elucidated. In the current investigation, single-cell RNA sequencing in conjunction with weighted gene co-expression network analysis (WGCNA) was utilized to delineate lipid metabolism-related genes correlated with the prognostic outcomes of hepatocellular carcinoma (HCC). Data procurement encompassed transcriptomic and clinical datasets from HCC patients, sourced from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) repositories. Subsequent to this, consensus clustering analysis was implemented to stratify patients into distinct subgroups, contingent upon the expression patterns of lipid metabolism genes. Further analytical procedures involved functional enrichment analysis, evaluation of immune infiltration, and examination of the mutation landscape.PTGES3 was identified as a pivotal gene associated with lipid metabolism. Subsequent to its identification, cellular communication analysis was employed to assess the immunological attributes of PTGES3 within the tumor microenvironment. The functional role of PTGES3 was further corroborated through molecular docking simulations and in vitro experimental assays. We identified 27 genes associated with lipid metabolism, 18 of which exhibited significant correlation with overall survival in HCC patients. PTGES3 emerged as a central gene, demonstrating a robust association with immune cell infiltration and unfavorable prognosis. Cellular communication analysis revealed that PTGES3 exhibits the highest communication intensity with T cells, modulating the tumor microenvironment by potentiating the FN1/CD44 + MDK/NCL signaling pathway. Elevated expression of PTGES3 was linked to immunosuppressive cascades, diminished responsiveness to immunotherapy, and inferior overall survival outcomes. Molecular docking analysis indicated that etoposide, methotrexate, and doxorubicin could effectively bind to PTGES3. In vitro experiments confirmed that PTGES3 knockdown significantly impaired the proliferation, invasion, and migration of HCC cells. This study highlights the pivotal role of lipid metabolism in HCC progression and identifies PTGES3 as a potential prognostic biomarker and therapeutic target. These findings offer new insights into the development of targeted therapies for HCC, particularly in patients with high PTGES3 expression.
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Integrating Single-Cell and RNA Sequencing to Predict Glioma Prognosis Through Lactylation.
Gliomas are the most prevalent primary malignant neoplasms of the central nervous system, distinguished by their high recurrence rates and poor prognosis. Aerobic glycolysis in tumors generates excess lactate, which promotes lactylation, a post-translational modification (PTM). Although accumulating evidence implicates lactylation in glioma initiation and progression, previous lactylation-focused prognostic studies lacked single-cell resolution and broad validation, limiting their generalizability and clinical relevance. Single-cell and bulk RNA sequencing (RNA-seq) data were integrated to identify lactylation-enriched tumor cell populations and derive candidate genes. A risk model was developed using univariate Cox regression and the Least Absolute Shrinkage and Selection Operator (LASSO), and its predictive performance was validated in independent cohorts from the China Glioma Genome Atlas (CGGA). To improve clinical applicability, a nomogram integrating the risk score incorporating key clinical variables was constructed and externally validated. The risk groups showed distinct immune microenvironment profiles and differential drug sensitivity patterns. In this study, we established and validated a lactylation-related gene signature, with the derived risk score serving as a reliable prognostic biomarker for glioma. Furthermore, the model not only predicts overall survival (OS) but also exhibits the potential to inform drug selection and stratify patients for more precise and personalized therapeutic interventions.
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Single-cell transcriptome analyses reveal disturbed decidual microenvironment in women of advanced maternal age.
BACKGROUND: Advanced maternal age (AMA) increases pregnancy risk. However, uterine-specific mechanisms independent of oocyte and embryo quality remain poorly defined. This study aimed to characterise the decidual microenvironment in women with AMA to identify key pathological changes and regulatory pathways. METHODS AND RESULTS: Through integrated histology, organoid modelling, and high-resolution scRNA-seq of first-trimester decidua from women of AMA and controlled reproductive age, we uncovered a pathologically remodelled decidual microenvironment characterised by aberrant cellular states and pathological differentiation pathways, leading to a pro-fibrotic state and accompanied by immune cell dysfunction, and disrupted intercellular communication in the AMA decidua. Central to this pathology was hyperactivated TGF-β signalling, driving fibroblast-to-myofibroblast transition and extracellular matrix overproduction, thereby fuelling fibrosis. Aberrant TGF-β further impaired decidual stromal cell (DSC) differentiation, leading to the failure of the essential mesenchymal-to-epithelial transition. We identified PRR15 as a novel DSC-specific regulator that is markedly suppressed in AMA. PRR15 deficiency unleashed hyperactive TGF-β/SMAD signalling, directly causing decidualisation failure, enhanced fibrosis, and aborted DSC differentiation. Epithelial-mesenchymal transition and immune cell reprogramming towards pro-fibrotic transcriptional signatures further amplify the fibrotic pathology. CONCLUSION: This study established the aged decidual microenvironment, orchestrated by dysregulated TGF-β signalling and PRR15 loss, as a critical independent determinant of reproductive failure in AMA. Thus, it unveils novel diagnostic and therapeutic targets and strategies. KEY POINTS: We provide the first single-cell atlas of the human decidua in advanced maternal age (AMA). A novel PRR15-TGF-β axis is identified, where PRR15 loss drives stromal fibrosis and decidualisation failure. This study reveals that AMA-associated uterine fibrosis begins in the first trimester, shifting focus to maternal factors.
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Single-cell and spatial transcriptomics reveal an arachidonic acid-related cellular atlas in lung adenocarcinoma.
PURPOSE: Arachidonic acid (AA), a membrane-abundant polyunsaturated fatty acid, is primarily liberated from membrane phospholipids by phospholipase A2 (PLA2), and is subsequently metabolized into bioactive eicosanoids involved in vascular tone and inflammation. With lipidomics advances, AA metabolism's multifaceted roles in the tumor microenvironment (TME) have emerged, and it is recognized as a key driver and potential therapeutic axis in lung adenocarcinoma (LUAD). We utilized spatial transcriptomics sequencing (ST-seq) and LUAD-associated single-cell RNA sequencing (scRNA-seq) to explore crucial AA-related biomarkers in LUAD. PATIENTS AND METHODS: ScRNA-seq and ST-seq data underwent quality control, integration, clustering, and annotation. Cellular communication analysis explored TME cell/regional regulatory links. Differential cell populations were identified between primary tumor and normal groups; key cells were selected via enrichment pathways and communication patterns. Biomarkers were chosen through differential expression analysis and protein-protein interaction (PPI) network, followed by enrichment analysis, molecular/drug network construction, key cell re-clustering, and pseudotime analysis. RESULTS: Twelve cell types were identified in scRNA-seq, with T cells and epithelial cells among the top three. ST-seq revealed LUAD tissues comprise cancer, lymph, normal epithelium, and stroma regions. T cells and epithelial cells had extensive intercellular connections, designated as key cells. PTGS2, TBXAS1, AKR1C3, and HPGD were selected as biomarkers via PPI network. Re-clustering and pseudotime analysis showed most LUAD epithelial cells and T cells were terminally differentiated; PTGS2 and HPGD expression rose then declined in the middle-late stages of epithelial cell subpopulation differentiation. CONCLUSION: In this study, we observed the crucial functions of T cells and epithelial cells as well as AA-related biomarkers PTGS2, TBXAS1, AKR1C3, and HPGD in LUAD. These findings provide mechanistic context and suggest testable biomarkers for future translational studies.