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Found: 4 939
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B-Cell Landscape in Inflamed Dental Pulp Reveals Potential Autoimmune Involvement.
Dynamic immune responses are evident during the development of pulpitis. However, the cellular and molecular characterization of B cells in this context has long been neglected. This study investigates pulpitis through the lens of B-cell involvement, combining single-cell RNA sequencing with histopathological analysis to generate a comprehensive cellular atlas of healthy and inflamed dental pulp. Our findings reveal a near absence of B/plasma cells in healthy pulp but a marked increase during inflammation. These cells display active antigen presentation and immunoglobulin secretion. In the mouse pulpitis model, B-cell depletion alleviated pulpal inflammation, highlighting the proinflammatory role of B cells. Subclustering analysis identified 4 transcriptionally distinct B-cell subsets, which were validated at the protein level through multiplex immunofluorescence and flow cytometry. Among these, transitional B cells exhibited a noticeable breakdown of tolerance, suggesting a propensity for autoreactivity. Elevated autoantibodies were detected in both tissue samples and isolated plasma cells. Finally, Mendelian randomization analyses and serological assays in mice indicated potential local-systemic interactions in pulpitis. These findings reveal that B cells may contribute to both the local pathology and systemic immunological characteristics of pulpitis, providing a novel perspective on its pathogenesis through potential autoimmune mechanisms.
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Computational reconstruction of the signalling networks surrounding implanted biomaterials from single-cell transcriptomics.
The understanding of the foreign-body responses to implanted biomaterials would benefit from the reconstruction of intracellular and intercellular signalling networks in the microenvironment surrounding the implant. Here, by leveraging single-cell RNA-sequencing data from 42,156 cells collected from the site of implantation of either polycaprolactone or an extracellular-matrix-derived scaffold in a mouse model of volumetric muscle loss, we report a computational analysis of intercellular signalling networks reconstructed from predictions of transcription-factor activation. We found that intercellular signalling networks can be clustered into modules associated with specific cell subsets, and that biomaterial-specific responses can be characterized by interactions between signalling modules for immune, fibroblast and tissue-specific cells. In a Il17ra-/- mouse model, we validated that predicted interleukin-17-linked transcriptional targets led to concomitant changes in gene expression. Moreover, we identified cell subsets that had not been implicated in the responses to implanted biomaterials. Single-cell atlases of the cellular responses to implanted biomaterials will facilitate the design of implantable biomaterials and the understanding of the ensuing cellular responses.
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Pan-cancer and single-cell analysis reveals FAM83D expression as a cancer prognostic biomarker.
Background: The family with sequence similarity 83 member D (FAM83D) protein is known to play a significant role in many human diseases. However, its role in cancer remains ambiguous. This study aimed to investigate the function of FAM83D in a pan-cancer analysis, with a special focus on breast cancer. Methods: Samples were collected from The Cancer Genome Atlas (TCGA) and used for bioinformatic analysis. Datasets from the Gene Expression Omnibus (GEO) and Genotype-Tissue Expression (GTEx) databases were also analyzed for verification. The potential value of FAM83D as a prognostic and diagnostic biomarker was visualized through R software. The "survival" and "GSVA" package were used for univariate, multivariate and pathway enrichment analyseis. We further analyzed the CancerSEA databases and TISIDB websites for single-cell and immune-related profiling. Lastly, we validated those data in vitro using quantitative reverse transcriptase-polymerase chain reaction (RT‒qPCR), cell counting kit-8 (CCK-8), transwell, flow cytometry, and tumorigenicity assays in a murine cell line model. Results: The expression of FAM83D in tumor samples was significantly higher than in normal tissues for most cancer types in the datasets. We confirmed this finding using RT‒qPCR in a breast cancer cell line. Analysis of multiple datasets suggests that overall survival (OS) was extremely poor for breast cancer patients with high FAM83D expression. The CCK-8 assay demonstrated that MCF-7 cell proliferation was inhibited after genetic silencing of FAM83D. Transwell assay showed that knockdown of FAM83D significantly inhibited the invasion and migration ability of MCF-7 cells compared to the control. The results of flow cytometry showed that silencing FAM83D could block the G1 phase of MCF-7 cells compared with negative groups. The tumorigenicity assay in nude mice indicated that the tumorigenic ability to silence FAM83D decreased compared. Conclusion: Results suggest that FAM83D expression can serve as a valuable biomarker and core gene across cancer types. Furthermore, FAM83D expression is significantly associated with MCF-7 cell proliferation and thus may be a prospective prognostic biomarker especially for breast cancer.
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A temporal single-cell atlas of the retina uncovers the dynamic transcriptomic landscape of sodium iodate-induced retinopathy in mice.
Retinal degeneration involves complex interactions among diverse cell types, yet the dynamic cellular responses and intercellular communication remain incompletely characterized. Here, we generated a temporal single-cell RNA sequencing atlas of the mouse retina following sodium iodate-induced oxidative injury to characterize cell type-specific trajectories and stage-dependent interactions. Our analysis identified a distinct inflammatory-reactive Müller glia subpopulation enriched for Il1r1, Tnfrsf1a, and C3, which exhibited early activation of TNF/NF-κB/MAPK signaling and later engagement in chemokine signaling, ECM-receptor interaction, and synaptic regulation. Photoreceptor profiling further revealed two rod subclusters with differential vulnerability, in which the more susceptible Rod1 subpopulation displayed marked downregulation of phototransduction genes and selective enrichment of tumor necrosis factor (TNF) signaling. Microglia exhibited early expansion and upregulation of inflammatory gene programs, including Il1b, Tnf, and Ccr2, while in vitro assays confirmed that conditioned medium from sodium iodate-activated microglia reduced photoreceptor viability. Together, we show a conceptual model in which sodium iodate-induced oxidative stress is associated with early microglial inflammation and subsequent glia-photoreceptor crosstalk, suggesting a potential pathway that may contribute to selective rod degeneration. This study provides a comprehensive resource for dissecting retinal degenerative mechanisms and highlights critical temporal windows for therapeutic intervention.
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A single-cell transcriptomic atlas of the human ciliary body.
The ciliary body critically contributes to the ocular physiology with multiple responsibilities in the production of aqueous humor, vision accommodation and intraocular immunity. Comparatively little work, however, has revealed the single-cell molecular taxonomy of the human ciliary body required for studying these functionalities. In this study, we report a comprehensive atlas of the cellular and molecular components of human ciliary body as well as their interactions using single-cell RNA sequencing (scRNAseq). Cluster analysis of the transcriptome of 14,563 individual ciliary cells from the eyes of 3 human donors identified 14 distinct cell types, including the ciliary epithelium, smooth muscle, vascular endothelial cell, immune cell and other stromal cell populations. Cell-type discriminative gene markers were also revealed. Unique gene expression patterns essential for ciliary epithelium-mediated aqueous humor inflow and ciliary smooth muscle contractility were identified. Importantly, we discovered the transitional states that probably contribute to the transition of ciliary macrophage into retina microglia and verified no lymphatics in the ciliary body. Moreover, the utilization of CellPhoneDB allowed us to systemically infer cell-cell interactions among diverse ciliary cells including those that potentially participate in the pathogenesis of glaucoma and uveitis. Altogether, these new findings provide insights into the regulation of intraocular pressure, accommodation reflex and immune homeostasis under physiological and pathological conditions.
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Single-Cell Transcriptome Reveals the Cellular Response to PEG-Induced Stress in Wheat Leaves.
Drought is a major factor limiting the production and yield of wheat bread (Triticum aestivum). Therefore, investigating the wheat drought-related response mechanism is an urgent priority. Here, the single-cell transcriptome of drought-nonsusceptible and susceptible wheat seedlings subjected to PEG-induced stress was systematically analyzed to study the drought-related response at the cellular level. We identified five major cell types using known marker genes and constructed a wheat leaf cell atlas. On this foundation, several potential specific marker genes for each cell type were identified, which provide a reference for further cell type annotation. Moreover, we identified cellular heterogeneity in the drought-related response mechanisms and regulatory networks among cell types. Specifically, the drought response of mesophyll cells was correlated with the photosynthetic pathway. Pseudotime trajectory analysis revealed the transition of epidermal cells from their normal function to a defense response under stress. Moreover, we also characterized the genes associated with the drought response. Notably, we identified two transcription factors (TraesCS1D02G223600 and TraesCS1D02G072900) as master regulators in most cell types. Our study provides detailed insights into the response heterogeneity of cells under PEG-induced stress. The gene resources obtained in our study could be applied to breed better crop plants with improved drought tolerance.
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Single-Cell Multiomics Integration Reveals Cell Trajectories and Regulatory Networks in Breast Cancer Progression.
BACKGROUND: Breast cancer is a molecularly heterogeneous disease encompassing distinct subtypes with divergent prognoses and therapeutic responses. Despite extensive bulk genomic characterization, the single-cell transcriptional trajectories, chromatin regulatory landscapes, and intercellular communication networks that drive breast cancer progression from luminal to mesenchymal states remain incompletely understood. Emerging evidence implicates gut microbiome dysbiosis as a systemic modulator of breast cancer risk, immune regulation, and treatment response; however, its coordinated characterization alongside high-resolution single-cell profiling has not been undertaken. Integrating single-cell RNA sequencing (scRNA-seq) with chromatin accessibility profiling (scATAC-seq), cell-cell communication inference, and gut microbiome 16S rRNA analysis offers a comprehensive multilayered approach to dissecting both the intratumoral regulatory logic and the systemic microbial landscape of breast cancer progression. METHODS: We performed integrated multiomics analysis of 42,037 high-quality single cells from breast cancer patient samples obtained from the GEO database (GSE161529), encompassing tumor and adjacent normal tissue. scRNA-seq data were processed using Seurat v4.3.0 and Scanpy v1.9.1. Dimensionality reduction, Leiden clustering, differential expression analysis, pseudotime trajectory inference (Monocle3, scVelo, Slingshot), SCENIC regulon analysis, chromatin accessibility profiling, cell-cell communication inference (CellChat), and functional enrichment analysis were applied. Key marker genes were validated by quantitative RT-PCR in MCF-7 and MDA-MB-231 cell lines. In parallel, gut microbiome 16S rRNA amplicon sequencing data from 599 matched breast cancer-healthy control pairs (266 genera, four BioProjects) were analyzed for alpha/beta diversity, differential genus abundance (Mann-Whitney U with Benjamini-Hochberg correction), genus co-occurrence networks, and random forest breast cancer classification. RESULTS: Unbiased clustering identified 12 observed cell populations spanning luminal (Luminal A, Luminal B), basal, HER2+, cancer-associated fibroblast (CAF), tumor-associated macrophage (TAM), CD8 T cell, regulatory T cell (Treg), NK cell, B cell, endothelial, and pericyte compartments. Quality control confirmed robust data quality with median 2400-3100 genes per cell and mitochondrial content below 20%. Pseudotime trajectory analysis revealed a continuous epithelial-to-mesenchymal transition (EMT) spectrum with three divergent lineages: EMT, senescence, and immune activation branches. SCENIC identified SNAI1(+), ZEB1(+), and FOXM1(+) as the most differentially activated regulons in basal/mesenchymal cells. ATAC-seq chromatin accessibility profiling confirmed EMT transcription factor access through distal enhancers. CellChat identified TGF-β1-TGFBR1 (CAF → tumor) and PD-L1-PD-1 (tumor → CD8 T cell) as dominant intercellular communication axes. Multiomics integration enhanced cell-type classification AUC from 0.76 (scRNA-seq alone) to 0.91 (full multiomics). EMT-high tumor status was associated with significantly inferior overall survival (HR = 2.14, p = 0.001). qRT-PCR validation confirmed ERBB2 enrichment in HER2+ lines and KRT5/VIM enrichment in basal/TNBC lines (all p < 0.001). Gut microbiome analysis revealed significant dysbiosis in breast cancer patients versus healthy controls, with reduced Shannon diversity (1.94 vs. 2.06, p = 6.1 × 10-4), significant community-level separation (Bray-Curtis PERMANOVA F = 30.2, p = 0.001), and nine differentially abundant genera including enriched Faecalitalea (log2 F C = 1.44), Parasutterella (log2 F C = 1.21), and Bacteroides (log2 F C = 1.19). A random forest microbiome classifier achieved a cross-validated AUC of 0.79 (95% CI: 0.74-0.82), supporting the gut-breast axis as a systemic codeterminant of cancer state. CONCLUSIONS: This integrated single-cell multiomics and gut microbiome atlas of breast cancer progression characterizes the transcriptional regulatory architecture driving cellular trajectory diversification, highlights SNAI1-ZEB1-FOXM1 coregulatory networks as candidate therapeutic targets, suggests that multiomics integration can enhance molecular stratification of breast cancer subtypes with clinical prognostic relevance, and identifies gut microbiome dysbiosis as a potential systemic dimension-characterized by loss of microbial diversity and enrichment of specific genera-as a systemic dimension of breast cancer pathobiology that warrants integration with intratumoral molecular profiling.
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HOX gene expression in the developing human spine.
Positional coding along the anterior-posterior axis is regulated by HOX genes, whose 3' to 5' expression correlates with location along this axis. The precise utilisation of HOX genes in different human cell types is not fully understood. Here, we use single-cell and spatial-transcriptomics, along with in-situ sequencing, to create a developmental atlas of the human fetal spine. We analyse HOX gene expression across cell types during development, finding that neural-crest derivatives unexpectedly retain the anatomical HOX code of their origin while also adopting the code of their destination. This trend is confirmed across multiple organs. In the axial plane of the spinal cord, we find distinct patterns in the ventral and dorsal domains, providing insights into motor pool organisation and loss of collinearity in HOXB genes. Our findings shed new light on HOX gene expression in the developing spine, highlighting a HOX gene 'source code' in neural-crest cell derivatives.
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Single-cell DNA Methylome and 3D Multi-omic Atlas of the Adult Mouse Brain.
Cytosine DNA methylation is essential in brain development and has been implicated in various neurological disorders. A comprehensive understanding of DNA methylation diversity across the entire brain in the context of the brain's 3D spatial organization is essential for building a complete molecular atlas of brain cell types and understanding their gene regulatory landscapes. To this end, we employed optimized single-nucleus methylome (snmC-seq3) and multi-omic (snm3C-seq1) sequencing technologies to generate 301,626 methylomes and 176,003 chromatin conformation/methylome joint profiles from 117 dissected regions throughout the adult mouse brain. Using iterative clustering and integrating with companion whole-brain transcriptome and chromatin accessibility datasets, we constructed a methylation-based cell type taxonomy that contains 4,673 cell groups and 261 cross-modality-annotated subclasses. We identified millions of differentially methylated regions (DMRs) across the genome, representing potential gene regulation elements. Notably, we observed spatial cytosine methylation patterns on both genes and regulatory elements in cell types within and across brain regions. Brain-wide multiplexed error-robust fluorescence in situ hybridization (MERFISH2) data validated the association of this spatial epigenetic diversity with transcription and allowed the mapping of the DNA methylation and topology information into anatomical structures more precisely than our dissections. Furthermore, multi-scale chromatin conformation diversities occur in important neuronal genes, highly associated with DNA methylation and transcription changes. Brain-wide cell type comparison allowed us to build a regulatory model for each gene, linking transcription factors, DMRs, chromatin contacts, and downstream genes to establish regulatory networks. Finally, intragenic DNA methylation and chromatin conformation patterns predicted alternative gene isoform expression observed in a companion whole-brain SMART-seq3 dataset. Our study establishes the first brain-wide, single-cell resolution DNA methylome and 3D multi-omic atlas, providing an unparalleled resource for comprehending the mouse brain's cellular-spatial and regulatory genome diversity.
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ESCO2's oncogenic role in human tumors: a pan-cancer analysis and experimental validation.
PURPOSE: Establishment of sister chromatid cohesion N-acetyltransferase 2 (ESCO2) is involved in the mitotic S-phase adhesins acetylation and is responsible for bridging two sister chromatids. However, present ESCO2 cancer research is limited to a few cancers. No systematic pan-cancer analysis has been conducted to investigate its role in diagnosis, prognosis, and effector function. METHODS: We thoroughly examined the ESCO2 carcinogenesis in pan-cancer by combining public databases such as The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression Project (GTEx), UALCAN and Tumor Immune Single-cell Hub (TISCH). The analysis includes differential expression analysis, survival analysis, cellular effector function, gene mutation, single cell analysis, and tumor immune cell infiltration. Furthermore, we confirmed ESCO2's impacts on clear cell renal cell carcinoma (ccRCC) cells' proliferative and invasive capacities in vitro. RESULTS: In our study, 30 of 33 cancer types exhibited considerably greater levels of ESCO2 expression in tumor tissue using TCGA and GTEx databases, whereas acute myeloid leukemia (LAML) exhibited significantly lower levels. Kaplan-Meier survival analyses in adrenocortical carcinoma (ACC), kidney chromophobe (KICH), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), brain lower grade glioma (LGG), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), mesothelioma (MESO), and pancreatic adenocarcinoma (PAAD) demonstrated that tumor patients with high ESCO2 expression have short survival periods. However, in thymoma (THYM), colon adenocarcinoma (COAD) and rectum adenocarcinoma (READ), ESCO2 was a favorable prognostic factor. Moreover, ESCO2 expression positively correlates with tumor stage and tumor size in several cancers, including LIHC, KIRC, KIRP and LUAD. Function analysis revealed that ESCO2 participates in mitosis, cell cycle, DNA damage repair, and other processes. CDK1 was identified as a downstream gene regulated by ESCO2. Furthermore, ESCO2 might also be implicated in immune cell infiltration. Finally, ESCO2'S knockdown significantly inhibited the A498 and T24 cells' proliferation, invasion, and migration. CONCLUSIONS: In conclusion, ESCO2 is a possible pan-cancer biomarker and oncogene that can reliably predict the prognosis of cancer patients. ESCO2 was also implicated in the cell cycle and proliferation regulation. In a nutshell, ESCO2 is a therapeutically viable and dependable target.