Search Results (731)

Background and Objective: Colorectal cancer (CRC) liver metastasis (CRLM) represents a major clinical challenge, and acquired resistance to radiotherapy (RT) significantly limits therapeutic efficacy. A deep and comprehensive understanding of the cellular and molecular mechanisms driving RT resistance is urgently required to develop effective combination strategies. Here, we aimed to dissect the dynamic cellular landscape of the tumor microenvironment (TME) and identify key epigenetic regulators mediating radioresistance in CRLM by integrating cutting-edge single-cell and spatial omics technologies. Methods and Results: We performed integrated single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) on matched pre- and post-radiotherapy tumor tissues collected from three distinct CRLM patients. Employing a robust machine-learning framework on the multi-omics data, we successfully identified MORF4L1 (Mortality Factor 4 Like 1), an epigenetic reader, as a critical epigenetic mediator of acquired radioresistance. High-resolution scRNA-seq analysis of the tumor cell compartment revealed that the MORF4L1-high subpopulation exhibited significant enrichment in DNA damage repair (DDR) pathways, heightened activity of multiple pro-survival metabolic pathways, and robust signatures of immune evasion. Pseudotime trajectory analysis further confirmed that RT exposure drives tumor cells toward a highly resistant state, marked by a distinct increase in MORF4L1 expression. Furthermore, cell–cell communication inference demonstrated a pronounced, systemic upregulation of various immunosuppressive signaling axes within the TME following RT. Crucially, high-resolution ST confirmed these molecular and cellular interactions in their native context, revealing a significant spatial co-localization of MORF4L1-expressing tumor foci with multiple immunosuppressive immune cell types, including regulatory T cells (Tregs) and tumor-associated macrophages (TAMs), thereby underscoring its role in TME-mediated resistance. Conclusions: Our comprehensive spatial and single-cell profiling establishes MORF4L1 as a pivotal epigenetic regulator underlying acquired radioresistance in CRLM. These findings provide a compelling mechanistic rationale for combining radiotherapy with the targeted inhibition of MORF4L1, presenting a promising new therapeutic avenue to overcome treatment failure and improve patient outcomes in CRLM. Full article

The establishment and development of single-cell RNA-sequencing (scRNA-seq) technology has accelerated the analysis of cell genome characteristics down to the single-cell level. Despite the rapid development of scRNA-seq technology, we cannot obtain a complete gene expression matrix in the biological experiments, and the scRNA-seq data obtained from experiments also have a high dropout rate. Unfortunately, gene expression analysis and clustering tools require a complete matrix of gene expression values for classification or clustering calculations. Most imputation methods focus on the impact of the imputed high-dimensional expression matrix on clustering and cannot obtain the low-dimensional representation matrix, which may have an even better guiding effect on clustering. To this end, we designed an iterative imputation pipeline called scIRT to estimate dropout events for scRNA-seq and achieve dimensionality reduction simultaneously by combining the synthetic minority over-sampling technique (SMOTE) and non-negative matrix factorization (NMF). The adaptation of SMOTE effectively imputes missing data, while NMF performs dimensionality reduction and feature extraction on high-dimensional data. Using several scRNA-seq datasets, we demonstrated that this new approach achieved better and more robust performance than the existing approaches. We also compared the different effects of the imputed matrix and the low-dimensional representation matrix on clustering. ScIRT is a tool that can be used to preprocess scRNA-seq data. It can effectively recover missing data from scRNA-seq to facilitate downstream analyses such as cell type clustering and visualization. Full article

Skeletal muscle orchestrates a remarkable journey from embryonic formation to age-related decline, yet its cellular intricacies in goats remain largely uncharted. We present the first single-cell RNA sequencing (scRNA-seq) atlas of the longissimus dorsi muscle from goats, profiling 120,944 cells across 14 developmental stages from embryonic day 30 (E30) to 11 years postnatal (Y11). We focused on skeletal muscle satellite cells (MuSCs) and fibro-adipogenic progenitors (FAPs), identifying a unique MuSCs_ACT1_high subpopulation in early embryogenesis and a senescence-associated MuSCs_CDKN1A_high subpopulation in later developmental stages. In FAPs, we characterized the early-stage FAPs_MDFI_high subpopulation with differentiation potential, which further exhibited the capacity to commit to both adipogenic and fibrogenic lineages. Transcription factor analysis revealed strikingly similar regulatory profiles between MuSCs and FAPs, suggesting that these two cell types are governed by shared signaling pathways during development. Cell–cell interaction analysis demonstrated that the DLK1-NOTCH3 ligand-receptor pair plays a critical role in enabling early embryonic FAPs to maintain the quiescent state of MuSCs. This dynamic single-cell transcriptomic atlas, spanning 14 developmental stages of skeletal muscle in ruminants for the first time, provides a valuable theoretical foundation for further elucidating the differentiation of skeletal muscle satellite cells and fibro-adipogenic progenitors in ruminants. Full article

Micronutrients, particularly boron (B), iron (Fe), manganese (Mn), and zinc (Zn), are pivotal for cotton (Gossypium spp.) growth, reproductive success, and fiber quality. However, their critical roles are often overlooked in fertility programs focused primarily on macronutrients. This review synthesizes recent advances in the physiological, molecular, and agronomic understanding of B, Fe, Mn, and Zn in cotton production. The overarching goal is to elucidate their impact on cotton nutrient use efficiency (NUE). Drawing from the peer-reviewed literature, we highlight how these micronutrients regulate essential processes, including photosynthesis, cell wall integrity, hormone signaling, and stress remediation. These processes directly influence root development, boll retention, and fiber quality. As a result, deficiencies in these micronutrients contribute to significant yield gaps even when macronutrients are sufficiently supplied. Key genes, including Boron Transporter 1 (BOR1), Iron-Regulated Transporter 1 (IRT1), Natural Resistance-Associated Macrophage Protein 1 (NRAMP1), Zinc-Regulated Transporter/Iron-Regulated Transporter-like Protein (ZIP), and Gossypium hirsutum Zinc/Iron-regulated transporter-like Protein 3 (GhZIP3), are crucial for mediating micronutrient uptake and homeostasis. These genes can be leveraged in breeding for high-yielding, nutrient-efficient cotton varieties. In addition to molecular hacks, advanced phenotyping technologies, such as unmanned aerial vehicles (UAVs) and single-cell RNA sequencing (scRNA-seq; a technology that measures gene expression at single-cell level, enabling the high-resolution analysis of cellular diversity and the identification of rare cell types), provide novel avenues for identifying nutrient-efficient genotypes and elucidating regulatory networks. Future research directions should include leveraging microRNAs, CRISPR-based gene editing, and precision nutrient management to enhance the use efficiency of B, Fe, Mn, and Zn. These approaches are essential for addressing environmental challenges and closing persistent yield gaps within sustainable cotton production systems. Full article

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has a wide range of clinical manifestations modulated by genetic factors. The aim of this study was to identify genetic determinants of severe COVID-19 affecting protein sequence to gain insight into disease pathogenesis. Variants prioritized in two patients requiring lung transplant were tested in the Milan FOGS cohort (487/869 cases/controls), highlighting an independent association between the p.F8S low-frequency variant of interferon alpha receptor 2 gene (IFNAR2) and severe disease (OR = 1.73 [1.24–2.42], p = 0.001), replicated in the COVID-19 Host Genetics Initiative cohort (26,167/2,061,934 cases/controls). In the FOGS cohort, the p.F8S variant was linked to higher circulating IL-6 levels. In keeping, bulk transcriptomic analysis in PBMCs at the peak of infection (n = 57) showed that carriers of the p.F8S variant had upregulation of immune signaling and pathogens response (p < 0.05). Functional flow cytometry experiments in healthy donors (n = 12) revealed that membrane IFNAR2 protein expression was reduced in B lymphocytes, but higher in dendritic cells (p < 0.05). Finally, by interrogating a public scRNAseq resource of PBMC of people with COVID-19, we showed that p.F8S carriers had upregulation of immune pathways specifically in dendritic cells (p < 0.05). These results suggest that the p.F8S variant may influence COVID-19 severity by enhancing adaptive immune response, thereby favoring inflammation. Full article

Background: Paroxysmal nocturnal hemoglobinuria (PNH) is a clonal hematopoietic stem cell disease characterized primarily by intravascular hemolysis, thrombosis, and bone marrow failure. Complement inhibitors are commonly used in clinical treatment and show limited efficacy, highlighting the urgent need to identify new therapeutic targets and explore alternative treatment strategies to provide theoretical guidance for clinical practice. Methods: We established a PNH cell model and constructed an miRNA–mRNA regulatory network to identify key miRNAs and core target genes. Single-cell sequencing data were analyzed to further clarify the critical genes. Finally, integrated drug database analysis identified potential therapeutic agents for PNH, which were validated by molecular docking and molecular dynamics simulations. Results: Using CRISPR/RNP technology, we successfully constructed a PIGA-knockout (PIGA-KO) THP-1 cell model. Differential expression analysis identified 1979 differentially expressed mRNAs (DEmRNAs) and 97 differentially expressed miRNAs (DEmiRNAs). The multiMiR package in R was used to predict the target genes of DEmiRNAs, from which those experimentally validated through dual-luciferase reporter assays were selected. After integration with the DEmRNAs, an miRNA–mRNA regulatory network was constructed, comprising 26 miRNAs and 38 mRNAs. Subsequent miRNA pathway enrichment analysis identified hsa-miR-23a-3p as a key miRNA, with CXCL12, CXCL8, HES1, and TRAF5 serving as core target genes. The integration of single-cell sequencing datasets (PRJNA1061334 and GSE157344) was performed, followed by cell communication and enrichment analysis. This approach, combined with clinical relevance, identified the neutrophil cluster as the key cluster. Intersection analysis of neutrophil cluster differential analysis results with key modules from hdWGCNA further clarified the critical genes. Drug prediction using EpiMed, CMap, and DGIdb identified Leflunomide, Dipyridamole, and Pentoxifylline as potential therapeutic agents. Molecular docking and molecular dynamics simulations showed stable binding of these potential drugs to the critical molecules, indicating a viable molecular interaction foundation. Conclusions: Leflunomide, Dipyridamole, and Pentoxifylline may serve as promising therapeutic agents for PNH, and the hsa-miR-23a-3p/CXCL8 regulatory axis could play a pivotal role in the pathogenesis and progression of PNH. Full article

Analysis of pulmonary vascular dysfunction in various lung pathologies remains challenging due to the lack of functional ex vivo models. Paracrine signaling in the lung plays a critical role in regulating endothelial maturation and vascular homeostasis. Previously, we employed single-cell RNA-sequencing (scRNAseq) to systematically map ligand–receptor (L/R) interactions within the lung vascular niche. However, the functional impact of these ligands on endothelial biology remained unknown. Here, we systematically evaluated selected ligands in vitro to assess their effects on endothelial barrier integrity, anti-inflammatory responses, and phenotypic maturation. Among the top soluble ligands, we found that adrenomedulin (ADM) exhibited superior barrier enhancing effect on human pulmonary endothelial cell monolayers, as evidenced by electrical cell impedance sensing (ECIS) and XperT assays. ADM also exhibited anti-inflammatory properties, decreasing ICAM1 and increasing IkBa expression in a dose-dependent manner. Perfusion is commonly used in bioengineered vascular model systems. Shear stress (15 dynes/cm²) alone increased endothelial characteristics, including homeostatic markers such as CDH5, NOS3, TEK, and S1PR1. ADM treatment maintained the enhanced level of these markers under shear stress and further improved anti-coagulation by increasing THBD and decreasing F3 expression and synergistically enhanced the expression of the native lung aerocyte capillary endothelial marker EDNRB. This effect was completely attenuated by a blockade of ADM receptor, RAMP2. Together, these findings identify ADM/RAMP2 signaling as a key paracrine pathway that enhances vascular barrier integrity, anti-inflammatory phenotype, and endothelial homeostasis, providing a framework for improving the physiological relevance of engineered vascular models. Full article

Background: ALG13-CDG is an X-linked N-linked glycosylation disorder caused by pathogenic variants in the glycosyltransferase ALG13, leading to severe neurological manifestations. Despite the clear CNS involvement, the impact of ALG13 dysfunction on human brain glycosylation and neurodevelopment remains unknown. We hypothesize that ALG13-CDG causes brain-specific hypoglycosylation that disrupts neurodevelopmental pathways and contributes directly to cortical network dysfunction. Methods: We generated iPSC-derived human cortical organoids (hCOs) from individuals with ALG13-CDG to define the impact of hypoglycosylation on cortical development and function. Electrophysiological activity was assessed using MEA recordings and integrated with multiomic profiling, including scRNA-seq, proteomics, glycoproteomics, N-glycan imaging, lipidomics, and metabolomics. X-inactivation status was evaluated in both iPSCs and hCOs. Results: ALG13-CDG hCOs showed reduced glycosylation of proteins involved in ECM organization, neuronal migration, lipid metabolism, calcium homeostasis, and neuronal excitability. These pathway disruptions were supported by proteomic and scRNA-seq data and included altered intercellular communication. Trajectory analyses revealed mistimed neuronal maturation with early inhibitory and delayed excitatory development, indicating an E/I imbalance. MEA recordings demonstrated early network hypoactivity with reduced firing rates, immature burst structure, and shortened axonal projections, while transcriptomic and proteomic signatures suggested emerging hyperexcitability. Altered lipid and GlcNAc metabolism, along with skewed X-inactivation, were also observed. Conclusions: Our study reveals that ALG13-CDG is a disorder of brain-specific hypoglycosylation that disrupts key neurodevelopmental pathways and destabilizes cortical network function. Through integrated multiomic and functional analyses, we identify early network hypoactivity, mistimed neuronal maturation, and evolving E/I imbalance that progresses to compensatory hyperexcitability, providing a mechanistic basis for seizure vulnerability. These findings redefine ALG13-CDG as disorders of cortical network instability, offering a new framework for targeted therapeutic intervention. Full article

Multiple Myeloma (MM) is an incurable malignancy that progresses from asymptomatic precursor stages—Monoclonal Gammopathy of Undetermined Significance (MGUS) and Smouldering Multiple Myeloma (SMM)—to active disease. Despite ongoing research, the molecular mechanisms driving this progression remain poorly understood. In this study, we aimed to uncover key regulatory factors involved in MM progression by integrating single-cell RNA sequencing (scRNA-seq) data with curated a priori biological knowledge of MM. To this end, we first integrated a priori knowledge from databases in a synthetic gene network map to play the role of an MM-related backbone to project findings from scRNA analysis on CD138⁺ Plasma Cells. This was followed by stage-specific regulatory network construction and analysis using Integrated Value of Influence (IVI) metrics to identify the most influential genes across disease stages. Our findings revealed GSK3B, RELA, CDKN1A, and PCK2 as central regulators shared across multiple stages of the disease. Notably, several of these genes had not previously been included in established MM gene sets, highlighting them as prime candidates for biomarkers and drug targets. Full article

Nucleated erythroid cells (NECs) have emerged as active participants in immune responses in addition to their canonical oxygen transport function. The subpopulations and immune heterogeneity of chick erythroid cells (ch-ECs) upon infection have not been fully characterized. Single-cell RNA sequencing (scRNA-seq) was used to profile ch-ECs in chicks infected with avian pathogenic Escherichia coli (APEC). Unsupervised clustering uncovered ten distinct ch-EC subpopulations (C1–C10), with significant compositional shifts between infected and control groups. Pseudotime analysis revealed a developmental continuum: C1, C3, C5, and C9 as early progenitors; C2, C4, C6, C7, and C10 as mature erythroid cells; and C8 as a naive population. We revealed 62 immune-related genes, including protein kinases and heat shock proteins, and subpopulation-specific differentially expressed genes (DEGs) linked to immune functions. SCENIC analysis revealed Fos, Srf, and Stat3 as key transcription factors with elevated regulon activity and specificity following infection. Subpopulations C2, C4, C6, and C7, which exhibited marked abundance changes, were scrutinized for immune relevance through integrated multi-omics analysis. Immune-related genes including FOS, AKAP9, HS6ST1, GAB3, TFRC, HSPA8, HSP90AA1, and DNAJB6 were identified. Enrichment analysis indicated activation of the MHC class I antigen presentation pathway, while pathways such as Mitogen-Activated Protein Kinase (MAPK) signaling, NOD-like receptor (NLR) signaling, and the heat shock response were found to be suppressed. In conclusion, this study delineates the immune gene repertoire and signaling networks of ch-ECs during APEC infection, offering new perspectives on NEC immunoregulatory functions. Full article

Erythro-myeloid progenitors (EMPs) originate from the haemogenic endothelium in the yolk sac via an endothelial-to-haematopoietic transition (EHT) to generate blood and immune cells that support embryo development. Yet, the transitory nature of EHT and the limited availability of molecular markers have constrained our understanding of the origin, identity, and differentiation dynamics of EMPs. Here, we have refined the annotation of yolk sac haemato-vascular populations in publicly available single-cell RNA sequencing (scRNAseq) datasets from mouse embryos to identify novel molecular markers of haemogenic endothelium and EMPs. By sub-clustering key cell populations followed by pseudotime analysis, we refined cluster annotations and then reconstructed differentiation trajectories. Subsequent differential gene expression analysis between clusters identified novel cell surface markers for haemogenic endothelial cells (Fxyd5 and Scarf1) and EMPs (Fcer1g, Tyrobp, and Mctp1). Further, we have identified candidate signalling and metabolic pathways that may regulate yolk sac haematopoietic emergence and differentiation. The specificity of FXYD5, SCARF1, and FCER1G for haemogenic endothelium and EMPs was validated by immunostaining of the mouse yolk sac. These insights into the transcriptional dynamics in the yolk sac should support future investigation of EHT and haematopoietic differentiation during early mammalian development. Full article

Plant roots interact dynamically with complex environments, and their capacity to adapt is crucial for growth, development, survival, and productivity. Basic leucine zipper (bZIP) transcription factors have emerged as key regulators in managing the root’s response to various environmental signals. The shift from bulk tissue analysis to single-cell RNA sequencing (scRNA-seq) has enabled the creation of a highly detailed expression atlas for root bZIPs, significantly enhancing our understanding of their functions. This review first summarizes the classification and structural features of bZIPs in Arabidopsis, and compares representative members with their orthologs in cereal crops. Next, we integrate the expression patterns of various bZIP members in root cells and clarify their roles through single-cell expression profiling. Furthermore, we delineate characterized bZIP regulatory modules that respond to signals spanning light, hormones, nutrients, and stresses, thereby orchestrating transcriptional reprogramming to facilitate plant adaptation. By combining single-cell omics with functional genetics, we reveal how bZIPs control critical processes, including responses to light signals, hormonal interactions, nutrient uptake and balance, and reactions to abiotic stresses. Ultimately, this integrated perspective highlights the potential for targeting bZIP transcription factors in the development of climate-resilient crops with optimized root systems, thereby enabling them to adapt to changing environmental conditions. Full article

The fields of medical diagnostics, nephrology, and the sequencing of cellular genetic material are pivotal for precise quantification of kidney diseases. Single-cell sequencing, enhanced by automation and software tools, enables efficient examination of biopsies at the individual cell level. This approach shows the complex cellular mosaic that shapes organ function. By quantifying gene expression following injury, single-cell analysis provides insight into disease progression. In this review, new developments in single-cell analysis methods, spatial integration of single-cell analysis, single-nucleus RNA sequencing, and emerging methods, including expression quantitative trait loci, whole-genome sequencing, and whole-exome sequencing in nephrology, are discussed. These advancements are poised to enhance kidney disease diagnostic processes, therapeutic strategies, and patient prognosis. Full article

Background: Lung adenocarcinoma (LUAD) exhibits pronounced cellular and molecular heterogeneity that shapes tumor progression and therapeutic response. Although nucleotide metabolism is essential for sustaining tumor proliferation and coordinating immune interactions, its single-cell heterogeneity and clinical implications remain incompletely defined. Methods: We integrated a publicly available scRNA-seq dataset derived from independent LUAD patients to construct a comprehensive LUAD cellular atlas, identified malignant epithelial cells using inferCNV, and reconstructed differentiation trajectories via Monocle2. Cell–cell communication patterns under distinct nucleotide metabolic states were assessed using CellChat. A nucleotide metabolism-related signature (NMRS) was subsequently developed across TCGA-LUAD and multiple GEO cohorts using 101 combinations of machine learning algorithms. Its prognostic and immunological predictive value was systematically evaluated. The functional relevance of the key gene ENO1 was further verified through pan-cancer analyses and in vitro experiments. Results: We identified substantial nucleotide metabolic heterogeneity within malignant epithelial cells, closely linked to elevated proliferative activity, glycolytic activation, and increased CNV burden. Pseudotime analysis showed that epithelial cells gradually acquire enhanced immune-modulatory and complement-related functions along their differentiation continuum. High-metabolism epithelial cells exhibited stronger outgoing communication—particularly via MIF, CDH5, and MHC-II pathways—highlighting their potential role in shaping an immunosuppressive microenvironment. The NMRS built from metabolism-related genes provided robust prognostic stratification across multiple cohorts and surpassed conventional clinical parameters. Immune profiling revealed that high-NMRS tumors displayed increased T-cell dysfunction, stronger exclusion, higher TIDE scores, and lower IPS, suggesting poorer responses to immune checkpoint blockade. ENO1, markedly upregulated in high-NMRS tumors and functioning as a risk factor in several cancer types, was experimentally shown to promote invasion in LUAD cell lines. Conclusions: This study delineates the profound impact of nucleotide metabolic reprogramming on epithelial cell states, immune ecology, and malignant evolution in LUAD. The NMRS provides a robust predictor of prognosis and immunotherapy response across cohorts, while ENO1 emerges as a pivotal metabolic–immune mediator and promising therapeutic target. Full article

Immunization is the most effective way to prevent transmission of the hepatitis B virus. However, about one-quarter of hepatitis B vaccinees (HepB vaccinees) aged around 18 years have lost their immune memory. What is responsible for the loss? Five subjects who became asymptomatic HBsAg carriers after anti-HBs seroconversion and ten controls who were negative for both HBsAg and anti-HBs were recruited from individuals born in 1987 and vaccinated at birth. scRNA-seq was performed on peripheral blood mononuclear cells, including library preparation, sequencing, quality control and filtering, normalization, dimensionality reduction, clustering, cell type annotation, differential expression analysis and trajectory analysis. Twelve cell types and nine subpopulations of T cells were identified. No significant differences in the proportions of cell types and subpopulations were found between cases and controls. The expression levels of immune memory-related genes, IL7R in total T cells and BACH2 in naive CD4+ T cells and naive CD8+ T cells, were significantly downregulated in the cases (p = 2.2 × 10⁻³⁰⁸, 3.31 × 10⁻²⁷ and 9.41 × 10⁻¹⁰⁰, respectively). IL7R is expressed throughout cellular development, while BACH2 is expressed only in the early stage of cellular development. Downregulation of the IL7R and BACH2 in T cells is associated with immune memory loss, identifying them as candidate genes for future functional studies to explore their potential role in the loss of immune memory. This could inform adjuvant design if a causal mechanism is firmly established. Full article