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A comprehensive single-cell atlas of three centenarian cohorts unveils unique natural killer cell signatures and enhanced mutual interactions among peripheral immune cells.
BACKGROUND: Centenarians are considered as an optimal population for studying healthy ageing. However, immune features associated with super longevity have only been investigated in a few small studies using a single research method. METHODS: In this study, single-cell RNA sequencing (scRNA-seq), mass cytometry, and flow cytometry analysis were used to analyse the immune feature of peripheral blood mononuclear cells (PBMCs) from 17 centenarians (CENs), 9 of their offsprings (COs), and 14 of their offsprings' spouses or neighbours (controls, CTs) from Lingao County of China. scRNA-seq data from the other two cohorts were downloaded from public databases. FINDINGS: Comprehensive analysis of 31 CENs, 17 COs, and 26 CTs from these three cohorts revealed decreased percentages of B cells and CD4+ T cells and an increased percentage of natural killer (NK) cells in PBMCs from CENs, compared with CTs. Moreover, NK cells from CENs exhibited relatively "young" signatures, including cell subset distribution and key membrane receptor expression. Enhanced RUNX3 expression in NK cells was observed in CENs, with reinforced interactions between NK and T cells, which promoted T cell function by modulating MHC-I, CD99 and MIF signalling. INTERPRETATION: CENs exhibit unique immunological features, especially NK cells with young protein expression signatures and immune functions. FUNDING: This study was funded by the Sanya Science and Technology Innovation Special Project (No. 2022KJCX02), National Natural Science Foundation of China (No. 32141005, 82270769), Specific Research Fund of the Innovation Platform for Academicians of Hainan Province, and National Key Research and Development Program of China (Nos. 2022YFC3602900, 2022YFC3602902, 2022YFC3602903).
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Mechanistic insights into FEN1-mediated drug sensitivity and risk signature in colon cancer: An integrative bioinformatics study.
The overexpression of Flap endonuclease 1 (FEN1) has been implicated in drug resistance and prognosis across various cancer types. However, the precise role of FEN1 in colon cancer remains to be fully elucidated. In this study, we employed comprehensive datasets from The Cancer Genome Atlas, Gene Expression Omnibus, and Human Protein Atlas to examine FEN1 expression and assess its correlation with clinical pathology and prognosis in colon cancer. We utilized the pRRophetic algorithm to evaluate drug sensitivity and performed differential expression analysis to identify genes associated with FEN1-mediated drug sensitivity. Gene set enrichment analysis was conducted to further investigate these genes. Additionally, single-cell sequencing analysis was employed to explore the relationship between FEN1 expression and functional states. Cox regression analysis was implemented to construct a prognostic model, and a nomogram for prognosis was developed. Our analysis of The Cancer Genome Atlas and Gene Expression Omnibus datasets revealed a significant upregulation of FEN1 in colon cancer. However, while FEN1 expression showed no notable correlation with prognosis, it displayed associations with metastasis. Single-cell sequencing analysis further confirmed a positive correlation between FEN1 expression and colon cancer metastasis. Furthermore, we detected marked discrepancies in drug responsiveness between the High_FEN1 and Low_FEN1 groups, identifying 342 differentially expressed genes. Enrichment analysis showed significant suppression in processes related to DNA replication, spliceosome, and cell cycle pathways in the Low_FEN1 group, while the calcium signaling pathway, cAMP signaling pathway, and other pathways were activated. Of the 197 genes differentially expressed and strongly linked to FEN1 expression, 39 were significantly implicated in colon cancer prognosis. Finally, we constructed a risk signature consisting of 5 genes, which, when combined with drug treatment and pathological staging, significantly improved the prediction of colon cancer prognosis. This study offers novel insights into the interplay among FEN1 expression levels, colon cancer metastatic potential, and sensitivity to therapeutic agents. Furthermore, we successfully developed a multi-gene prognostic risk signature derived from FEN1.
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Single-cell analysis of diquat-induced oxidative stress and its impact on organ-specific toxicity.
Diquat (DQ) is a commonly used herbicide, and its improper use can lead to multi-organ damage. The characteristics of multi-organ damage induced by DQ are not yet well understood. In this study, we conducted single-cell/single-nucleus RNA sequencing (scRNA-seq/snRNA-seq) on the lungs, liver, and kidneys of mice at consecutive time points (10 hours, 20 hours, and 36 hours) after DQ poisoning, as well as in a control group. In a multi-organ single-cell atlas comprising over 270,000 cells from mice, we found that DQ induces an oxidative stress microenvironment in endothelial and parenchymal cells, primarily characterized by activation of the oxidative phosphorylation pathway and an enhanced inflammatory response. This oxidative stress microenvironment prompted regulatory cell death in parenchymal and immune cells, releasing inflammatory factors and further exacerbating the oxidative environment. Additionally, metabolic reprogramming occurred in both parenchymal and immune cells under oxidative stress, leading to alterations in energy metabolism, reduced hepatic detoxification capabilities, and changes in the activation modes of immune cells, thereby intensifying tissue damage. Notably, no significant fibrosis was observed in the tissue damage caused by DQ, underscoring the importance of early intervention. Overall, using a mouse model, this study revealed the central role of the DQ-induced oxidative stress microenvironment in multi-organ damage and enhanced our understanding of the pathophysiology and complex molecular mechanisms underlying DQ-induced multi-organ injury.
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Profiling of the TNBC Tumor Microenvironment's Functional Heterogeneity by CITE-seq to Guide Personalized Medicine.
UNLABELLED: Introduction / Objective: Triple-negative breast cancer (TNBC) is an aggressive subtype with few effective treatments and frequent resistance to immune checkpoint inhibitors. The heterogeneous and plastic tumor microenvironment (TME) is a dynamic, complex ecosystem. This study aims to deconstruct the TNBC immune ecosystem and generate a cellular atlas of its tumor microenvironment. METHODS: In this study, we apply three CITE-seq datasets from murine TNBC tumors, totaling 2,356 cells. After correcting for technical batch effects, we perform clustering to identify major cell types, followed by focused sub-clustering of tumor-associated macrophages (TAMs) and T cells to analysis their functional states and potential differentiation trajectories. RESULTS: Batch-corrected analysis resolves six primary cell populations within the TNBC microenvironment. TAMs segregate into three distinct subpopulations: a classical antigen-presenting subset, a metabolically active subset enriched for mitochondrial gene expression, and a unique subset with an erythroid-like gene signature consistent with active erythrophagocytosis. T-cell analysis reveals five major states. Furthermore, we identify several therapeutic targets. DISCUSSION: These findings reveal substantial functional diversity within key immune compartments of TNBC, particularly TAMs and T cells, including metabolically specialized and erythrophagocytic TAMs, as well as distinct T cells. Besides, we also identify several potential drug targets for targeted treatment. CONCLUSION: This work provides a detailed single-cell atlas of the TNBC tumor microenvironment and uncovers functional heterogeneity in its immune cells. The resulting map offers a foundation for precision medicine, facilitating patient stratification and the design of tailored therapies that target the specific cellular ecosystems driving TNBC progression.
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A Comprehensive Characterization of Monoallelic Expression During Hematopoiesis and Leukemogenesis via Single-Cell RNA-Sequencing.
Single-cell RNA-sequencing (scRNA-seq) is becoming a powerful tool to investigate monoallelic expression (MAE) in various developmental and pathological processes. However, our knowledge of MAE during hematopoiesis and leukemogenesis is limited. In this study, we conducted a systematic interrogation of MAEs in bone marrow mononuclear cells (BMMCs) at single-cell resolution to construct a MAE atlas of BMMCs. We identified 1,020 constitutive MAEs in BMMCs, which included imprinted genes such as MEG8, NAP1L5, and IRAIN. We classified the BMMCs into six cell types and identified 74 cell type specific MAEs including MTSS1, MOB1A, and TCF12. We further identified 114 random MAEs (rMAEs) at single-cell level, with 78.1% single-allele rMAE and 21.9% biallelic mosaic rMAE. Many MAEs identified in BMMCs have not been reported and are potentially hematopoietic specific, supporting MAEs are functional relevance. Comparison of BMMC samples from a leukemia patient with multiple clinical stages showed the fractions of constitutive MAE were correlated with fractions of leukemia cells in BMMCs. Further separation of the BMMCs into leukemia cells and normal cells showed that leukemia cells have much higher constitutive MAE and rMAEs than normal cells. We identified the leukemia cell-specific MAEs and relapsed leukemia cell-specific MAEs, which were enriched in immune-related functions. These results indicate MAE is prevalent and is an important gene regulation mechanism during hematopoiesis and leukemogenesis. As the first systematical interrogation of constitutive MAEs, cell type specific MAEs, and rMAEs during hematopoiesis and leukemogenesis, the study significantly increased our knowledge about the features and functions of MAEs.
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Single-Nucleus Transcriptomics Uncovers Xaf1-Driven PANoptosis as a Therapeutic Target in Aminoglycoside-Induced Hearing Loss.
Aminoglycoside antibiotics are essential in managing many life-threatening diseases. However, their derivatives, such as neomycin, are associated with severe side effects such as persistent sensorineural hearing loss. Therefore, it is essential to elucidate the molecular and biochemical mechanisms of aminoglycoside-induced ototoxicity and identify targets for alleviating ototoxic injury. Here, we provide a detailed cochlear cell atlas of neomycin-induced acute and chronic ototoxicity-related changes through single-nucleus RNA sequencing profiling. Utilising this cochlear cell atlas, we used the Augur and scDist algorithms to evaluate cell-type-specific susceptibility to neomycin injury. We observed aberrant expression of X-linked inhibitor of apoptosis (Xiap)-associated factor 1 (Xaf1) in neomycin-exposed cochleae using the cochlear cell atlas, and we identified a novel role for Xaf1 in facilitating PANoptosis through overexpression and knockdown assays in vitro. Finally, we assessed the protective role of Xaf1 against neomycin-induced ototoxicity by Xaf1 knockdown in cochlear hair cells using adeno-associated virus-based gene delivery. Mechanistically, Xaf1 orchestrates PANoptosis activation through direct interaction with and transcriptional regulation of ZBP1, establishing its hierarchical position upstream in the signalling cascade. This study presents detailed cochlear cellular maps of neomycin-induced ototoxicity and serves as a valuable resource for identifying transcriptome-wide disease-driving perturbations at the single-cell level. More importantly, we identified Xaf1 as a critical target for modulating the PANoptosis pathway, offering a promising treatment strategy for aminoglycoside-induced ototoxicity.
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A Single-Cell Transcriptomic Atlas Elucidates a Microglial Gene Signature Linking Ferroptosis to Mitochondrial Dysfunction in Epilepsy.
BACKGROUND: Epilepsy is a chronic neurological disorder caused by abnormal synchronous discharges of neurons, with ferroptosis and mitochondrial dysfunction implicated in its progression. However, a lack of resolution at the level of specific cell types has obscured critical roles and molecular mechanisms within the epileptic microenvironment. METHODS: This study integrated single-nucleus RNA sequencing (snRNA-seq) and bulk RNA-seq data from epilepsy and control samples. We performed dimensionality reduction and clustering to identify 13 cell subpopulations, and then assessed the expression of ferroptosis-related genes (FRGs) and mitochondrial-related genes (MRGs) within 7 major cell types. Three machine learning algorithms were further applied to identify key genes in microglia. Subsequent analyses included immune infiltration, pathway enrichment, and drug-target interaction. Molecular docking and molecular dynamics simulations were used to evaluate the potential binding affinity of the predicted drug. In vivo validation included histopathology, mitochondrial electron microscopy, JC-1 staining, and immunohistochemistry (IHC). RESULTS: We identified six key genes (ATM, TGFBR1, ZEB1, PARP14, GJA1, and ALOX5), which link ferroptosis and mitochondrial dysfunction with a central role for microglia in epilepsy. These genes were associated with immune infiltration, including increased Th1 cell levels and reduced CD8+ T cell abundance. Enrichment analyses implicated these hub genes in orchestrating key epileptogenic processes, including neuroinflammatory pathways, ferroptosis, and interferon response. PARP14 was upregulated in epileptic rats, and GJA1 exhibited stable binding with bleomycin. Histopathological and mitochondrial assays confirmed the presence of ferroptosis and mitochondrial damage in epilepsy. CONCLUSION: This study highlights the interplay between ferroptosis and mitochondrial dysfunction in epilepsy, identifying six key microglial genes as high-priority candidates for future mechanistic and therapeutic investigation. Notably, PARP14 is implicated in epileptogenesis for the first time. The stable binding between GJA1 and bleomycin offers a novel avenue for epilepsy treatment, warranting further experimental validation.
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Single-Cell RNA Sequencing Reveals Bidirectional Development of Infantile Hemangioma.
Infantile hemangioma (IH) affects 5-10% of all infants and up to 30% of premature newborns. Further understanding of disease mechanisms and therapeutic strategies requires a deeper knowledge of IH in humans. In this study, we performed single-cell RNA sequencing on hemangioma samples from 3 infants diagnosed with IH. A total of 36,237 high-quality cells were clustered into 10 major cell types, including endothelial cells and hemangioma mural cells. Endothelial cells in IH exhibit strong proliferative capacity and heterogeneity. Furthermore, cell-cell communication analysis and immunofluorescence colocalization revealed that hemangioma mural cells, which constitute >50% of IH, can release ligands such as VEGFA and PGF and act on endothelial cells, thus promoting endothelial cell proliferation and angiogenesis. We also found that the expression levels of VEGFA and Ki-67 are significantly higher in IH than in normal infant skin tissue. Finally, we also found that adrenaline receptor beta 1 is specifically expressed in EC1 and EC2, adrenaline receptor beta 2 is specifically expressed in EC3, and adrenoceptor alpha is specifically expressed in hemangioma mural cells. In summary, our study provides a cellular atlas of proliferative-phase IH and reveals the important roles of endothelial cells and hemangioma mural cells in the development of IH.
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Single-cell transcriptome atlas and genome-wide Mendelian randomization reveal chemokine involvement in diverse immune cells in type 2 diabetes.
BACKGROUND: Chemokine-driven immune dysregulation is increasingly recognized as a hallmark of T2D pathogenesis(T2D), where insulin resistance and metabolic stressors drive chronic inflammation. While chemokine cascades are hypothesized to mediate diabetic immunopathology, causal mediators remain undefined. METHODS: We employed Mendelian Randomization (MR) of genome-wide association studies to identify causal inflammatory mediators, serological validation in streptozotocin-induced murine T2D models, and single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells (PBMC) to map immune cell heterogeneity and intercellular communication networks. RESULTS: MR prioritized IFN-γ, CCL7, MIF, and CXCL9 as genetically supported T2D effectors. Murine validation confirmed CCL7 and MIF as robust circulating mediators. scRNA-seq revealed compartment-specific chemokine receptor dynamics (CCR4/5/6, CXCR3/4/5, CX3CR1), dominated by enhanced CCL5-CCR5 and CCL6-CCR2 crosstalk. CONCLUSION: This work establishes a systems-level framework for chemokine signaling in T2D immunopathogenesis, identifying nodal regulators of immune crosstalk as potential therapeutic vulnerabilities.
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Multiset multicover methods for discriminative marker selection.
Markers are increasingly being used for several high-throughput data analysis and experimental design tasks. Examples include the use of markers for assigning cell types in scRNA-seq studies, for deconvolving bulk gene expression data, and for selecting marker proteins in single-cell spatial proteomics studies. Most marker selection methods focus on differential expression (DE) analysis. Although such methods work well for data with a few non-overlapping marker sets, they are not appropriate for large atlas-size datasets where several cell types and tissues are considered. To address this, we define the phenotype cover (PC) problem for marker selection and present algorithms that can improve the discriminative power of marker sets. Analysis of these sets on several marker-selection tasks suggests that these methods can lead to solutions that accurately distinguish different phenotypes in the data.