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Single-cell reanalysis identifies macrophage-associated transcriptional and intercellular communication features in diabetic foot ulcers.
BACKGROUND: Diabetic foot ulcers (DFUs) are devastating diabetic complications characterized by an extremely high non-healing rate and elevated risk of life-threatening outcomes. To characterize the cellular landscape and macrophage-associated alterations between DFU tissue and diabetic non-ulcer foot (DNFU) skin, we performed a comprehensive reanalysis of publicly available single-cell RNA sequencing (scRNA-seq) datasets. METHODS: A fully reproducible R-based analytical pipeline was used to process public scRNA-seq count matrices (GSE165816) from 5 DFU and 8 DNFU skin samples. A total of 27,844 cells (16,579 from DFU and 11,265 from DNFU skin) passed stringent quality control filters. Data normalization, integration, dimensionality reduction, unsupervised clustering, and marker-based cell type annotation were performed using the Seurat and Harmony packages. Sample-level comparisons included cell fraction analysis and UCell pathway scoring. Macrophages were further investigated through subclustering analysis, edgeR-based pseudobulk differential expression analysis, volcano plot visualization, GO over-representation analysis, enrichment analysis, and CellChat ligand-receptor interaction inference. RESULTS: The integrated single-cell atlas resolved 10 major cell compartments including epithelial, stromal, endothelial, lymphatic endothelial, smooth muscle/pericyte, lymphoid, myeloid, mast cell, plasma cell, and melanocyte/Schwann cells. Sample-level cell fraction analysis revealed a nominal reduction in lymphatic endothelial cells in DFU; however, no cell type proportion differences remained statistically significant after false discovery rate (FDR) correction. Similarly, no significant differences were observed in macrophage UCell pathway scores for glycolysis, lactate metabolism, combined glycolysis-lactate metabolism, TNF-NF-κB signaling, or insulin/IGF signaling between DFU and DNFU skin following FDR correction. Macrophage subclustering identified DFU-enriched subpopulations, and macrophage pseudobulk analysis prioritized multiple DFU-associated genes. Notably, sex-linked genes including XIST, RPS4Y1, and DDX3Y reached statistical significance after FDR correction, indicating that a portion of the observed transcriptional signal may be attributed to demographic imbalance between groups. Exploratory enrichment analysis of nominal and ranked macrophage differentially expressed genes highlighted DFU-directional enrichment of translation, oxidative phosphorylation, electron transport, and antigen presentation terms, while DNFU-directional genes were enriched for transcriptional regulation and rhythmic process terms. CellChat analysis prioritized macrophage-associated CD99-CD99 and MIF-CD74/CXCR4 ligand-receptor pairs as key DFU-associated intercellular communication hypotheses. CONCLUSION: This single-cell reanalysis comparing DFU and DNFU skin identifies putative ligand-receptor interaction hypotheses, transcriptomic alterations, and macrophage subpopulation shifts that require definitive validation in larger, clinically well-characterized, and spatially resolved patient cohorts.
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Single-cell transcriptome analysis reveals cellular heterogeneity and highlights Fstl1-regulated alveolar myofibroblasts in mouse lung at birth.
The matricellular protein, follistatin-like 1 (FSTL1), regulates lung development and saccular formation. Here, we employed single-cell RNA sequencing (scRNA-seq) to construct a transcriptomic atlas of 22,774 individual cells from wild-type (WT) and Fstl1-/- lung (E18.5) samples and identified 27 cell subtypes. We observed abnormal population sizes and gene expression profiles in diverse cell subtypes in Fstl1-/- lung samples. We identified Pdgfra and Tgfbi as genetic markers specifically expressed in postnatal myofibroblasts (MyoFBs). Fstl1 deletion decreased the number of MyoFB cells and downregulated their roles in ECM organization and muscle tissue/vasculature development, partly through the TGF-β1/BMP4 signaling pathway. Our data provide a single-cell view of the cellular heterogeneity and the molecular mechanisms underlying abnormal saccular formation and atelectatic lungs in Fstl1-/- mice.
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Single-Cell Transcriptomic Atlases of Camels and Cattle Unravel Molecular Evolution of Digestive and Metabolic Systems.
Cellular and molecular characterization of mammals with multi-chambered stomachs is crucial to our understanding of evolution in digestive and metabolic systems. Here, we generate single-cell transcriptomic atlases of 253,448 and 279,057 cells from 54 tissues in camels and cattle, discovering 124 cell types. Cross-species comparisons at four developmental stages reveal a common evolutionary origin among camel glandular sac, third-chambered stomach, and bovine abomasum, with the camel lineages uniquely harboring a cell population characterized by heightened expression of genes involved in cell proliferation. Also, the advantages of camel hepatocytes in prevention of excessive fat deposition are uncovered. Interestingly, the spatial transcriptomic analysis further reveals a unique population of S100A4+ vascular smooth muscle cells in camel rather than other mammalian kidneys, potentially involved in prevention of renal hypertension. Altogether, our study provides invaluable resources for evolutionary biology and highlights cellular innovations underlying mammalian adaptation.
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Single-cell transcriptomics reveals the toxic mechanism and therapeutic target of ubiquitously distributed mycotoxin deoxynivalenol.
BACKGROUND: Deoxynivalenol (DON), a prevalent mycotoxin contaminating herbal medicines and daily diets, poses significant threats to male reproductive health, yet dissection of its testicular toxicity at single cell resolution remains unexplored. PURPOSE: Herein, we integrated single-cell RNA sequencing (scRNA-seq) with functional analyses to characterize the cellular and molecular features of DON-induced testicular toxicity. METHODS: The toxicity of DON was evaluated by morphology, organ index, sex hormones, sperm morphology and quantity, and H&E staining. scRNA-seq was used to dissect the cellular and molecular mechanisms of DON-induced testicular injury. Nuclear spreading immunostaining, Western blot, and supplement of inhibitor were used to confirm the toxic mechanism of DON. RESULTS: In sexually mature rats, chronic DON exposure caused dose-dependent testicular structural damage, hormonal imbalance, and impaired sperm quality. scRNA-seq of 70,000 testicular cells revealed DON-driven aberrant accumulation of early spermatocytes. Further analysis indicated defective meiotic progression at the leptotene stage, accompanied by suppressed homologous recombination-related genes including Brca2 and Rad51, and disrupted chromosome pairing. SCENIC regulatory network analysis suggested that KDM5A is functionally associated with leptotene spermatocyte maturation, and its activity was inhibited by DON. Notably, pharmacological activation of KDM5A using agonist D18 reversed the pathological decrease of BRCA2 and RAD51, partially rescued meiotic progression, and ameliorated sperm defects in DON-exposed models. CONCLUSION: Our study establishes the first single-cell atlas of DON-induced testicular injury and identifies KDM5A as a critical component of the regulatory network disrupted during mycotoxin-impaired spermatogenesis. These findings provide mechanistic insights into mycotoxin-related male infertility and highlight a potential therapeutic avenue for its mitigation.
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4D single-cell spatial transcriptomics reveals dynamic morphogenetic gradients and regenerative domains in planarians.
BACKGROUND: Understanding how organisms reconstruct complex tissue architectures following injury requires precise mapping of gene expression and cellular responses across space and time. Although planarians serve as a classic model for whole-body regeneration, capturing the continuous spatiotemporal dynamics of positional information and cell fate decisions at the organismal scale remains a significant challenge. RESULTS: Using high-definition spatial transcriptomics, we generated a 4-dimensional atlas encompassing over 3.5 million cells from whole animals across 8 distinct regeneration timepoints. This comprehensive dataset enabled the definition of 36 spatial domains and the tracing of body axis restoration, revealing that positional control genes recover through self-organizing dynamics analogous to an underdamped control system. We identified an injury-induced spatial domain termed the anterior regenerative zone. This unique region is characterized by the convergence of epidermal, muscular, and neural lineages enriched with positional signals. Furthermore, we demonstrated that the transcriptional co-factor Mediator 8 is a critical regulator of this zone. Depletion of Mediator 8 impairs the formation of the anterior regenerative zone, disrupts polarity establishment, and prevents successful blastema formation. CONCLUSIONS: Our study provides a holistic molecular and cellular reconstruction of whole-body regeneration, directly linking dynamic gene expression gradients to morphological restoration. The discovery of the Mediator 8-regulated anterior regenerative zone highlights the importance of spatial domains in coordinating tissue repair. The resulting interactive atlas serves as a foundational resource for deciphering the logic of spatiotemporal patterning in regeneration.
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Single-Cell Multi-Omics Reveal Gene Regulatory Mechanisms Underlying Cardiac Embryonic Development.
Background/Objectives: Cardiac embryonic development is a highly coordinated and dynamic process governed by precise spatiotemporal gene regulation. Increasing evidence indicates that cellular heterogeneity and lineage specification during heart development are tightly controlled by complex gene regulatory networks (GRNs) and epigenetic mechanisms. Recent advances in single-cell multi-omics technologies provide unprecedented resolution to dissect these regulatory processes. This review aims to summarise current applications of single-cell multi-omics approaches to elucidate gene regulatory mechanisms underlying cardiac embryogenesis and their implications for congenital heart disease (CHD). Methods: We systematically reviewed recent literature on single-cell RNA sequencing (scRNA-seq), single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq), spatial transcriptomics, and integrative multi-omics analyses applied to embryonic heart development. Studies were analysed to evaluate how these technologies contribute to cell-type identification, lineage trajectory reconstruction, GRN inference, and epigenetic landscape characterisation. Results: Single-cell multi-omics approaches have enabled the construction of high-resolution cardiac cell atlases, revealing previously unrecognised cellular heterogeneity and transitional states during heart development. Integrative analyses of transcriptomic and chromatin accessibility data have provided insights into lineage commitment, key transcription factors, enhancer-promoter interactions, and dynamic GRNs. These findings have advanced understanding of developmental genetics in cardiac morphogenesis and offered new perspectives on the molecular mechanisms underlying CHD. Conclusions: Single-cell multi-omics technologies provide a powerful framework for investigating gene regulatory mechanisms during cardiac embryogenesis. Continued methodological refinement and integrative analyses are expected to further clarify developmental processes and facilitate translational insights into CHD.
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A Cross-Species Single-Cell Atlas Reveals Conserved Regulatory Networks and Candidate Hearing Loss Genes in the Cochlea.
Background: The cochlea is a specialized sensory organ essential for hearing. To elucidate its cellular and molecular architecture and prioritize candidate genes associated with hearing loss (HL), we constructed a cross-species single-cell transcriptomic atlas of human fetal and postnatal mouse cochleae. Methods: We integrated single-cell and single-nucleus RNA sequencing datasets from human fetal cochleae and postnatal mouse cochleae to build a comprehensive cross-species single-cell transcriptomic atlas. Cell-type annotation, transcriptional regulator analysis, intercellular communication, and disease phenotypes were performed to dissect the cochlear cellular landscape, regulatory programs, and potential HL gene candidates. Results: A total of 19 major cochlear cell types were identified in both species, with conserved cellular composition and transcriptional programs. Comparative analysis revealed strong transcriptional conservation between matched human and mouse cell types, particularly in supporting, schwann cells and hair cells. Cell-cell communication analysis revealed conserved signaling pathways, including the BDNF-NTRK2 axis, potentially involved in cochlear development and auditory function. Regulatory network inference uncovered conserved and previously undercharacterized transcription factors, such as SKOR1, RFX2, and PAX2, predicted to be associated with hair cell identity and function. We further defined a conserved gene module of 3138 hair cell-enriched genes, from which 24 candidate HL-associated genes (e.g., ATP8B1, BDNF, and SOD1) were prioritized through integration with human disease databases and mouse auditory phenotype annotations. Conclusions: This study provides a high-resolution cross-species cochlear atlas, revealing conserved molecular programs and candidate HL-associated genes, offering valuable insights into auditory biology and potential avenues for further investigation.
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Spatial analysis identifies LAMTOR2 overexpression in hepatocellular carcinoma with vessels encapsulating tumor clusters.
BACKGROUND: Vessels encapsulating tumor clusters (VETC) is a distinct angiogenic pattern in hepatocellular carcinoma (HCC). While VETC-positive HCC is associated with poor prognosis, it demonstrates improved responses to vascular-targeted therapies. However, the molecular signatures that define VETC-positive HCC remain elusive. This study employed spatial transcriptomics and single-cell RNA sequencing to characterize the molecular landscape of VETC-positive HCC and identify candidate biomarkers. METHODS: Using GeoMx Digital Spatial Profiling, we analyzed tumor and adjacent liver tissues from 24 HCC patients, focusing on VETC-positive, VETC-negative, or non-neoplastic liver regions. Differential gene expression and pathway enrichment analyses were performed. Candidate genes were further evaluated using immunohistochemistry, The Cancer Genome Atlas (TCGA) dataset, and single-cell RNA sequencing. RESULTS: Spatial transcriptomic analysis identified 39 genes upregulated in VETC-positive regions, with enrichment of angiogenesis, WNT/β-catenin, Hedgehog, and p53 signaling, epithelial-mesenchymal transition, and fatty acid metabolism pathways, and suppression of immune-related pathways. Among these, LAMTOR2, DPP4, ZNHIT1, and MLXIPL were consistently upregulated in VETC-positive regions compared to both VETC-negative and normal liver regions. LAMTOR2 demonstrated tumor-specific localization in TCGA dataset. Immunohistochemistry confirmed that peripheral accentuation pattern of LAMTOR2 expression was restricted to tumor cells and strongly correlated with RNA expression and VETC positivity. Single-cell RNA sequencing further revealed LAMTOR2 upregulation in malignant hepatocytes, particularly within VETC-high subpopulations enriched for lipid degradation, fatty acid oxidation, and detoxification pathways. CONCLUSION: VETC-positive HCC exhibits a distinct transcriptomic and metabolic profile. LAMTOR2, which is consistently upregulated in VETC-positive HCCs, may contribute to angiogenic and metabolic reprogramming, offering potential implications for therapeutic stratification in HCC.
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Cross-species integration of single-cell data reveals conserved pathology-associated cell populations across animal models and human samples.
Single-cell RNA sequencing (scRNA-seq) enables high-resolution profiling of cellular heterogeneity, but integrating data across species remains challenging due to technical variation and complex gene homology. We present TACMAN (transformer-based alignment of cross-species metapath aggregation network), a computational framework for cross-species scRNA-seq integration that combines a metapath-based heterogeneous graph neural network with an encoder-only transformer. TACMAN aligns conserved cell types across species under normal physiological conditions while preserving biological signals. We demonstrate its utility by integrating clinical human and mammalian model scRNA-seq data, revealing conserved cell subtypes in tumor, inflammatory, and infectious diseases. Notably, using our in-house single-cell transcriptomic atlas of an evolutionarily distant Caenorhabditis elegans germline tumor model, TACMAN identifies tumor-related cell populations conserved in human testicular germ cell tumor samples, enabling cross-species comparison under pathological conditions. TACMAN thus offers a powerful tool for comparative single-cell analysis, advancing translational research using animal models.
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Integrated single-cell transcriptomic atlas of human gastric and colorectal tissues across diverse phenotypes.
Gastrointestinal cancer is one of the most burdensome health threats worldwide, accounting for approximately one-quarter of all cancer incidences. Gastric and colorectal cancers are among the most prevalent and lethal malignancies of the gastrointestinal tract globally. Despite steadily rising incidence, the complex cellular landscape comprising the tumor microenvironment and accelerating tumorigenesis remains insufficiently explored. Although single-cell transcriptomics has been employed to investigate this complexity, previous studies are limited by the small number of cells analyzed. In this study, we present a comprehensive single-cell transcriptomic atlas comprising 574,532 cells across 70 cell types from 229 human stomach tissues and 479,629 cells across 70 cell types from 220 human colorectal tissues, spanning diverse phenotypes. Data quality and cell type annotations were rigorous validated utilizing multiple computational tools. Additionally, standardized cell type definitions and annotated clinical information facilitate the usability of this dataset, enabling analysis across clinical subtypes and metastatic states. This resource provides a valuable foundation for meta-analyses of gastric and colorectal cancers at single-cell resolution.