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Abdominal aortic aneurysm (AAA), a life‐threatening cardiovascular disorder, necessitates the identification of novel molecular biomarkers to facilitate early diagnosis and precision therapeutic interventions. In this study, we employed an integrative bioinformatics strategy to systematically identify and characterise a potential biomarker for AAA. By reanalyzing GEO datasets and applying Lasso regression, we identified 10 candidate genes, whose intersection with known AAA‐associated genes pinpointed LEF1 as a pivotal regulator. Single‐cell transcriptomic analysis further demonstrated that LEF1 is predominantly expressed in aortic wall‐resident T cells, suggesting a spatially restricted regulatory role. Functional enrichment analysis highlighted significant associations with MHC class II protein complex binding and ribosomal structural integrity, implicating LEF1 in immune and translational regulation. Immunohistochemical analysis demonstrated significantly elevated expression of CD3, CD4 and CD8 markers in AAA tissues compared to controls. Flow cytometry and immunofluorescence analyses confirmed LEF1 co‐localisation with both CD8+ effector T cells and CD4+ memory T cells, with significantly enhanced LEF1 expression in AAA specimens versus controls. Overall, our study systematically discovered an important hub gene LEF1, which may serve as a biomarker for AAA.

The regulation of spermatogonial proliferation and apoptosis is of great significance for maintaining spermatogenesis. The single-cell RNA sequencing (scRNA-seq) analysis of the testis was performed to identify genes upregulated in spermatogonia. Using scRNA-seq analysis, we identified the spermatogonia upregulated gene origin recognition complex subunit 6 (Orc6), which is involved in DNA replication and cell cycle regulation; its protein expression in the human and mouse testis was detected by western blot and immunofluorescence. To explore the potential function of Orc6 in spermatogonia, the C18-4 cell line was transfected with control or Orc6 siRNA. Subsequently, 5-ethynyl-2-deoxyuridine (EdU) and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assays, flow cytometry, and western blot were used to evaluate its effects on proliferation and apoptosis. It was revealed that ORC6 could promote proliferation and inhibit apoptosis of C18-4 cells. Bulk RNA sequencing and bioinformatics analysis indicated that Orc6 was involved in the activation of wingless/integrated (Wnt)/β-catenin signaling. Western blot revealed that the expression of β-catenin protein and its phosphorylation (Ser675) were significantly decreased when silencing the expression of ORC6. Our findings indicated that Orc6 was upregulated in spermatogonia, whereby it regulated proliferation and apoptosis by activating Wnt/β-catenin signaling.

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for investigating cellular biology at an unprecedented resolution, enabling the characterization of cellular heterogeneity, identification of rare but significant cell types, and exploration of cell–cell communications and interactions. Its broad applications span both basic and clinical research domains. In this comprehensive review, we survey the current landscape of scRNA-seq analysis methods and tools, focusing on count modeling, cell-type annotation, data integration, including spatial transcriptomics, and the inference of cell–cell communication. We review the challenges encountered in scRNA-seq analysis, including issues of sparsity or low expression, reliability of cell annotation, and assumptions in data integration, and discuss the potential impact of suboptimal clustering and differential expression analysis tools on downstream analyses, particularly in identifying cell subpopulations. Finally, we discuss recent advancements and future directions for enhancing scRNA-seq analysis. Specifically, we highlight the development of novel tools for annotating single-cell data, integrating and interpreting multimodal datasets covering transcriptomics, epigenomics, and proteomics, and inferring cellular communication networks. By elucidating the latest progress and innovation, we provide a comprehensive overview of the rapidly advancing field of scRNA-seq analysis.

The advances in single-cell RNA sequencing technologies and the development of bioinformatics pipelines enable us to more accurately define the heterogeneity of cell types in a selected tissue. In this report, we re-analyzed recently published single-cell RNA sequencing data sets and provide a rationale to redefine the heterogeneity of cells in both intact and injured mouse peripheral nerves. Our analysis showed that, in both intact and injured peripheral nerves, cells could be functionally classified into four categories: Schwann cells, nerve fibroblasts, immune cells, and cells associated with blood vessels. Nerve fibroblasts could be sub-clustered into epineurial, perineurial, and endoneurial fibroblasts. Identified immune cell clusters include macrophages, mast cells, natural killer cells, T and B lymphocytes as well as an unreported cluster of neutrophils. Cells associated with blood vessels include endothelial cells, vascular smooth muscle cells, and pericytes. We show that endothelial cells in the intact mouse sciatic nerve have three sub-types: epineurial, endoneurial, and lymphatic endothelial cells. Analysis of cell type-specific gene changes revealed that Schwann cells and endoneurial fibroblasts are the two most important cell types promoting peripheral nerve regeneration. Analysis of communication between these cells identified potential signals for early blood vessel regeneration, neutrophil recruitment of macrophages, and macrophages activating Schwann cells. Through this analysis, we also report appropriate marker genes for future single cell transcriptome data analysis to identify cell types in intact and injured peripheral nerves. The findings from our analysis could facilitate a better understanding of cell biology of peripheral nerves in homeostasis, regeneration, and disease.

Background Starting from pools of undifferentiated cells, plants generate new organs postembryonically in response to external and endogenous signals. This requires a dynamic coordination of cell division with cellular growth and differentiation regulatory programs. However, little is known about how this coordination is achieved at the molecular level during flower development. Results We used time-series single-nucleus RNA sequencing (snRNA-seq) experiments of synchronized Arabidopsis thaliana flower developmental stages to characterize the transcriptome dynamics and the connections between cell cycle and developmental regulatory programs during early flower development. The results show a bifurcation between transcriptional trajectories corresponding to cell cycle progression and floral development. We identify the regulation of the cell cycle inhibitor KIP-RELATED PROTEIN 2 (KRP2) by FRUITFULL (FUL) as a key regulatory point on this bifurcation point and validate the importance of this regulation in vivo. Conclusions Our work illustrates how time-series snRNA-seq experiments can be used to identify bifurcation points between regulatory programs and to identify candidate regulators on these bifurcations. In particular, we identify the regulation of KRP2 by FUL as an important regulatory point to balance cell division and developmental differentiation in plants.

BackgroundMyocardial infarction (MI) is the leading cause of heart failure. The adult human heart, unlike mouse or early neonatal hearts, lacks the capability to undergo extensive regeneration. Rapid re-establishment of blood flow post MI is vital for limiting tissue damage and preserving cardiac function. A better understanding of the mechanisms underpinning cardiovascular regeneration in adult hearts is needed. Recent technologies including single cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) have empowered studies of healthy and diseased tissue at unprecedented resolution.Methods and ResultsFirst, we established an EC-specific multispectral lineage-tracing mouse model (Pdgfb-iCreERT2-R26R-Brainbow2.1) and assessed EC clonal proliferation in the adult heart post MI. We discovered a significant increase in clone size in the MI hearts compared to the healthy controls (cells per clone = 4.0 ± 2.1 vs. 10.3 ± 10.6, P < 0.0001), demonstrating that the structural integrity of adult endothelium following MI was maintained through clonal proliferation by resident ECs in the infarct border region. We then isolated the Pdgfb-lineage ECs from the healthy (12,780) and injured (15,818) hearts through FACS, performed scRNA-seq and downstream analysis, and defined ten transcriptionally discrete heterogeneous EC states and associated pathways that might impact upon cardiovascular regeneration. Next, high-quality scRNA-seq data from 10 curated studies of the mouse and human hearts were integrated for a cross-species systematic meta-analysis. Coronary ECs were enriched in silico based on the expression of 45 endothelial markers and analysed using Seurat. Unsupervised clustering of integrated neonatal and adult mouse coronary ECs revealed 15 transcriptionally distinct clusters. The subsequent DEG analysis identified the Vegfc pathway as a program that can potentially augment adult cardiovascular regeneration in the neonatal heart. The integration of the mouse and human coronary EC data and the DEG analysis identified 41 commonly upregulated genes after ischaemic injuries, including KLF4, EGR1 and ZFP36. Further, spatial transcriptomics analysis of MI patient-derived heart tissues revealed the elevation of these conserved targets in the damaged tissues in the acute phase. We validated the upregulation of these targets in the injured human coronary ECs (% KLF4+ CD31+ EC = 29.7 ± 7.5% versus 7.3 ± 6.4%, P = 0.0009;% EGR1+ CD31+ EC = versus 10.1 ± 3.5% versus 3.4 ± 2.5%, P = 0.004; ZFP36 expression was high the diseased tissue but minimal in control hearts). In vitro siRNA knockdown of ZFP36 in cultured human cardiac microvascular endothelial cells (HCMECs) showed that cell proliferation was significantly inhibited compared to the control siRNA treatment (Fold change of%EdU+ HCMECs = 0.84 ± 0.19 vs 0.25 ± 0.12, P = 0.0007). In vivo, we used the multi-spectral MI mouse model and showed that the administration of rhVEGF-C significantly increased neovascularisation in the infarct border in the adult mouse heart compared to the PBS treated controls (vascular clone volume (μm3) = 3072 ± 491.2 versus 426 ± 105, P = 0.02).ConclusionWe have successfully developed and implemented a robust framework, using meta-analysis of scRNA-seq, spatial transcriptomics, tissue section immunofluorescence, primary human cell culture, and multispectral MI mouse model, to collectively identify, assess, and validate novel mechanisms and targets potential to promote vascular regeneration.

Chronic rhinosinusitis with nasal polyps is affecting up to 3% of Western populations. About 10% of patients with nasal polyps also suffer from asthma and intolerance to aspirin, a syndrome called aspirin-exacerbated respiratory disease. Although eosinophilic inflammation is predominant in polyps of both diseases, phenotypic differences in the tissue-derived microenvironment, elucidating disease-specific characteristics, have not yet been identified. We sought to obtain detailed information about phenotypic and transcriptional differences in epithelial and immune cells in polyps of aspirin-tolerant and intolerant patients. Cytokine profiles in nasal secretions and serum of patients suffering from aspirin-exacerbated respiratory disease (n = 10) or chronic rhinosinusitis with nasal polyps (n = 9) were assessed using a multiplex mesoscale discovery assay. After enrichment for immune cell subsets by flow cytometry, we performed transcriptomic profiling by employing single-cell RNA sequencing. Aspirin-intolerant patients displayed significantly elevated IL-5 and CCL17 levels in nasal secretions corresponding to a more pronounced eosinophilic type 2 inflammation. Transcriptomic profiling revealed that epithelial and mast cells not only complement one another in terms of gene expression associated with the 15-lipoxygenase pathway but also show a clear type 2-associated inflammatory phenotype as identified by the upregulation of POSTN , CCL26 , and IL13 in patients with aspirin-exacerbated respiratory disease. Interestingly, we also observed cellular stress responses indicated by an increase of MTRNR2L12 , MTRNR2L8 , and NEAT1 across all immune cell subsets in this disease entity. In conclusion, our findings support the hypothesis that epithelial and mast cells act in concert as potential drivers of the pathogenesis of the aspirin-exacerbated respiratory disease.

Triple negative breast cancer (TNBC) remains the worst molecular subtype due to high heterogeneity and lack of effective therapeutic targets. Here we investigated the tumor and immune microenvironment heterogeneity of TNBC using scRNA-seq and bulk RNA-seq data from public databases and our cohort. Macrophage subpopulations accounted for a high proportion of tumor immune microenvironment (TIME), and M1 macrophages were associated with better clinical outcomes. Furthermore, three maker genes including IFI35, PSMB9, and SAMD9L showed a close connection with M1 macrophages. Specifically, IFI35 was positively associated with macrophage activation, chemotaxis, and migration. Also, patients with high IFI35 expression had a better prognosis. In vitro studies subsequently demonstrated that IFI35 was upregulated during the M1 subtype differentiation of macrophages. In summary, our data suggested that IFI35 maybe a promising novel target that helps to reshape macrophage polarization towards the M1 subtype for anti-tumor effects.

Currently, there is a significant shortage of transplantable organs for patients in need. Interspecies chimerism and blastocyst complementation are alternatives for generating transplantable human organs in host animals such as pigs to meet this shortage. While successful interspecies chimerism and organ generation have been observed between evolutionarily close species such as rat and mouse, barriers still exist for more distant species pairs such as human–mouse, marmoset–mouse, human–pig, and others. One of the proposed barriers to chimerism is the difference in developmental stages between the donor cells and the host embryo at the time the cells are introduced into the host embryo. Hence, there is a logical effort to stage-match the donor cells with the host embryos for enhancing interspecies chimerism. In this study, we used an in silico approach to simultaneously stage-match the early developing embryos of four species, including human, marmoset, mouse, and pig based on transcriptome similarities. We used an unsupervised clustering algorithm to simultaneously stage-match all four species as well as Spearman’s correlation analyses to stage-match pairs of donor–host species. From our stage-matching analyses, we found that the four stages that best matched with each other are the human blastocyst (E6/E7), the gastrulating mouse embryo (E6–E6.75), the marmoset late inner cell mass, and the pig late blastocyst. We further demonstrated that human pluripotent stem cells best matched with the mouse post-implantation stages. We also performed ontology analysis of the genes upregulated and commonly expressed between donor–host species pairs at their best matched stages. The stage-matching results predicted by this study will inform in vivo and in vitro interspecies chimerism and blastocyst complementation studies and can be used to match donor cells with host embryos between multiple species pairs to enhance chimerism for organogenesis.

Background This study identified fibroblast-specific genes to develop a RiskScore model to improve prognostic accuracy and guide personalized treatment in glioblastoma (GBM). Methods We analyzed fibroblast-specific signatures in the GSE273274 cohort using “Seurat” R package for scRNA-seq data processing. Fibroblast-related gene modules were identified via WGCNA, and functional enrichment was assessed with “clusterProfiler” package. A RiskScore model was established using univariate, Lasso Cox regression analysis, and “survival” package, validated by “timeROC” for receiver operator characteristic (ROC) curve. Finally, immune infiltration and drug sensitivity was evaluated applying “ESTIMATE,” “TIMER,” “MCPcounter,” and “pRRophetic” packages. Experimental validation included qPCR for gene expression detection, and CCK-8, wound healing, and Transwell assays for functional measurement. Results The scRNA-seq analysis identified nine cell types of cells, with fibroblasts elevated in the GBM group. Fibroblast signatures were linked to tumorigenesis, cytoskeleton remodeling, and regulation of neuronal development process that affected GBM invasion. A 6-gene RiskScore divided GBM patients into high- and low-risk groups in training and validation sets, with high-risk patients exhibiting poorer survival, elevated StromalScore, and negative correlations with the infiltration of neutrophils and B_cells. Moreover, high-risk patients demonstrated heightened sensitivity to Cisplatin, MG-132, AZ628, Dasatinib, CGP-60474, A-770041, TGX221, and Bortezomib. Finally, qPCR showed that the VWA1 was upregulated in GBM cells, while knock-down of VWA1 inhibited the cell proliferation, migration, and invasion activity. Conclusion We constructed a RiskScore model for predicting the survival outcomes based on fibroblasts-related genes. These findings highlighted the role of fibroblasts in GBM development and offered six potential therapeutic targets ( VWA1 , DUSP6 , LOXL1 , IGFBP4 , CYGB , and ZIC3 ) for GBM treatment. Additionally, immune infiltration analysis and drug sensitivity prediction further supported the model’s utility in guiding personalized treatment of GBM.