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Single-cell analysis of intermediate horseshoe bat (Rhinolophus affinis) organs reveals viral infections and antiviral immune signatures.
Bats are recognized for harboring a diverse array of viruses without manifesting disease symptoms. In this study, we explored the single-cell atlas of wild Rhinolophus affinis (R. affinis) using Viral-Track and identified transcript expression of eight viral species in the R. affinis lung and three viral species in the kidney. Within the R. affinis lung, these viruses were detected across all cell types except ciliated cells. Compared to uninfected cells, virus-infected cells exhibited activation of pathways associated with protein synthesis, tissue repair, and immune responses, as evidenced by increased expression of corresponding genes. Ligand-receptor based analysis revealed that viral infection reshapes intercellular communication networks in the bat lung, with infected fibroblasts and infected proliferative T cells exhibiting enhanced signaling linked to tissue remodeling and immune activation. Through gene module analysis, we identified an immune cell activation-related module by high expression of CD14, CD74, and MRC1, as well as an antiviral related module by elevated expression of SAMHD1, SLC11A1, TYROBP, and IL18 in R. affinis pulmonary macrophages. Additionally, a cross-species single-cell transcriptomic comparative analysis demonstrated that R. affinis pulmonary macrophages exhibit elevated expression of pro-inflammatory genes (IRF9, DDX5, IL6ST and ITGA4), which are associated with antiviral activity and immune activation, and anti-inflammatory genes (IRF2, PTPRE and GPR65), which play critical roles in mitigating excessive immune responses. Compared to the other species, R. affinis pulmonary macrophages exhibited upregulation of genes enriched in pathways related to vacuolar acidification and negative regulation of response to external stimulus. These findings suggest that the R. affinis lung possesses a unique immune system that enables it to balance immune responses during viral infections, thereby preventing excessive immune damage and maintaining lung tissue homeostasis. Our study provides valuable insights into the viral infection risk organs in R. affinis and their distinctive antiviral immune responses.
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Molecular Characterization and Clinical Relevance of ANXA1 in Gliomas via 1,018 Chinese Cohort Patients.
Annexin A1 (ANXA1) is a calcium-dependent phospholipid-binding protein and has been implicated in multiple functions essential in cancer, including cell proliferation, apoptosis, chemosensitivity, metastasis, and invasion. However, the biological role and clinical behavior of ANXA1 in glioma remain unclear. In this study, RNA-seq (n = 1018 cases) and whole-exome sequencing (WES) (n = 286 cases) data on a Chinese cohort, RNA-seq data with different histological regions of glioblastoma blocks (n = 270 cases), and scRNA-seq data (n = 7630 cells) were used. We used the R software to perform statistical calculations and graph rendering. We found that ANXA1 is closely related to the malignant progression in gliomas. Meanwhile, ANXA1 is significantly associated with clinical behavior. Furthermore, the mutational profile revealed that glioma subtypes classified by ANXA1 expression showed distinct genetic features. Functional analyses suggest that ANXA1 correlates with the immune-related function and cancer hallmark. At a single-cell level, we found that ANXA1 is highly expressed in M2 macrophages and tumor cells of the mesenchymal subtype. Importantly, our result suggested that ANXA1 expression is significant with the patient's survival outcome. Our study revealed that ANXA1 was closely related to immune response. ANXA1 plays a key factor in M2 macrophages and MES tumor cells. Patients with lower ANXA1 expression levels tended to experience improved survival. ANXA1 may become a valuable factor for the diagnosis and treatment of gliomas in clinical practice.
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Single-cell atlas of multilineage cardiac organoids derived from human induced pluripotent stem cells.
Human induced pluripotent stem cell (hiPSC)-derived cardiac organoids can be used to model human heart development and cardiovascular disease, and provide therapeutic cells to repair the heart. We used single-cell transcriptome analysis to dissect the development of 3D mini-cardiac organoids (MCOs) consisting of hiPSC-derived cardiomyocytes, and endothelial and smooth muscle cells. We found that the 3D matrix-rich microenvironment significantly promoted the maturation of cardiomyocytes, and mixing endothelial and smooth muscle cells with cardiomyocytes led to the formation of cardiac fibroblast highly expressing DLK1. Modulation of DLK1 signaling affected immunomodulatory gene expression in 2D cultured cardiomyocytes. Transplantation of multilineage MCO into a rat model of myocardial infarction significantly improved cardiac function and reduced fibrosis in the infarcted area. Our single-cell analysis of MCO provided rich information about cell state and fate dynamics in the 3D multilineage microenvironment and brought new insight into the molecular mechanism that promotes cardiomyocyte maturation and heart repair.
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Genomic and Cis-Regulatory Basis of a Plastic C3-C4 Photosynthesis in Eleocharis Baldwinii.
C4 photosynthesis is a crucial trait for efficient carbon fixation; however, the genomic basis and environmental influences on its formation remain under explored. Here, we examined Eleocharis baldwinii, a sedge that exhibits photosynthetic plasticity with C3-like traits underwater and C4-like traits on land, to expand knowledge of C4 photosynthesis. A gap-free allopolyploid genome was assembled and a cellular expression atlas is reconstructed by applying single-nucleus RNA-seq.Subgenome dominance influencing expression of C4 enzyme genes was detected across cell types. cis-regulatory patterns linked to the C4 pathway, Kranz anatomy specialization, and environmental responses are evaluated using single-nucleus transposase-accessible chromatin sequencing and found that the formation of the C4 pathway involves a few environmentally triggered, cell-specialized cis-regulatory elements. Comparative analyses between E. baldwinii and maize further implied that cis-regulator families for Kranz anatomy specialization are conserved across species, whereas those for C4 metabolism differ, underscoring the genetic diversity underlying convergent traits. This study provides genomic and regulatory insights into how plants evolve C4 photosynthesis, especially regarding the effects of environmental factors.
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Deconvolution of cancer cell states by the XDec-SM method.
Proper characterization of cancer cell states within the tumor microenvironment is a key to accurately identifying matching experimental models and the development of precision therapies. To reconstruct this information from bulk RNA-seq profiles, we developed the XDec Simplex Mapping (XDec-SM) reference-optional deconvolution method that maps tumors and the states of constituent cells onto a biologically interpretable low-dimensional space. The method identifies gene sets informative for deconvolution from relevant single-cell profiling data when such profiles are available. When applied to breast tumors in The Cancer Genome Atlas (TCGA), XDec-SM infers the identity of constituent cell types and their proportions. XDec-SM also infers cancer cells states within individual tumors that associate with DNA methylation patterns, driver somatic mutations, pathway activation and metabolic coupling between stromal and breast cancer cells. By projecting tumors, cancer cell lines, and PDX models onto the same map, we identify in vitro and in vivo models with matching cancer cell states. Map position is also predictive of therapy response, thus opening the prospects for precision therapy informed by experiments in model systems matched to tumors in vivo by cancer cell state.
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8-Gene signature related to CD8+ T cell infiltration by integrating single-cell and bulk RNA-sequencing in head and neck squamous cell carcinoma.
Background: CD8+ T cells, a critical component of the tumor immune microenvironment, have become a key target of cancer immunotherapy. Considering the deficiency of robust biomarkers for head and neck squamous cell carcinoma (HNSCC), this study aimed at establishing a molecular signature associated with CD8+T cells infiltration. Methods: Single-cell RNA sequencing data retrieved from the Gene Expression Omnibus (GEO) database was analyzed to obtain the different cell types. Next, the cell proportions were investigated through deconvolution of RNA sequencing in the Cancer Genome Atlas (TCGA) database, and then the immune-related genes (IRGs) were identified by weighted gene co-expression network analysis (WGCNA). LASSO-Cox analysis was employed to establish a gene signature, followed by validation using a GEO dataset. Finally, the molecular and immunological properties, and drug responses between two subgroups were explored by applying "CIBERSORT", "ESTIMATE", and single sample gene set enrichment analysis (ssGSEA) methods. Results: A total of 215 differentially expressed IRGs were identified, of which 45 were associated with the overall survival of HNSCC. A risk model was then established based on eight genes, including DEFB1, AICDA, TYK2, CCR7, SCARB1, ULBP2, STC2, and LGR5. The low-risk group presented higher infiltration of memory activated CD4+ T cells, CD8+ T cells, and plasma cells, as well as a higher immune score, suggesting that they could benefit more from immunotherapy. On the other hand, the high-risk group showed higher abundance of activated mast cells and M2 macrophages, as well as a lower immune score. Conclusion: It was evident that the 8-gene signature could accurately predict HNSCC prognosis and thus it may serve as an index for clinical treatment.
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Exploring tumor endothelial cells heterogeneity in hepatocellular carcinoma: insights from single-cell sequencing and pseudotime analysis.
OBJECTIVE: This study aimed to explore the heterogeneity of tumor endothelial cells (TECs) in hepatocellular carcinoma (HCC) and their role in tumor progression, with the goal of identifying new therapeutic targets and strategies to improve patient prognosis. METHODS: Single-cell RNA sequencing data from nine primary liver cancer samples were analyzed, obtained from the Gene Expression Omnibus (GEO) database. Data preprocessing, normalization, dimensionality reduction, and batch effect correction were performed based on the Seurat package. HCC cell types were identified using uniform manifold approximation and projection (UMAP) and cluster analysis, and the different cell types were annotated using the CellMarker database. Pseudotime trajectory analysis was conducted with Monocle to explore the differentiation trajectory of TECs. MAPK signaling pathway activity and copy number variations (CNV) in TECs were analyzed in conjunction with data from The Cancer Genome Atlas (TCGA), the trans-well and wound healing assay was used for cell invasion and migration activity assessment. RESULTS: Two subgroups of TECs (TECs 1 and TECs 2) were identified, exhibiting distinct functional activities and signaling pathways. Specifically, TECs 1 may be involved in tumor cell proliferation and inflammatory responses, whereas TECs 2 is not only involved in cell proliferation pathways, but also enriched in pathways such as metabolic synthesis. Pseudotime analysis revealed dynamic changes in TECs subgroups during HCC progression, correlating specific gene expressions (such as PDGFRB, PGF, JUN, and NR4A1). Subsequently, the JUN gene was predicted by performing binding sites and was shown to act as a transcription factor that may regulate the expression of the PGF gene. CNV analysis highlighted key genes and pathways in TECs that might influence HCC progression, and the PGF as key regulatory factor mediated cell proliferation and migration. CONCLUSION: The study revealed the heterogeneity of TECs in HCC and their potential roles in tumor progression, offering new perspectives and potential therapeutic targets for HCC molecular mechanisms. The findings emphasize the importance of further exploring TECs heterogeneity for understanding HCC pathogenesis and developing personalized treatment strategies.
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Revealing the Transcriptional and Metabolic Characteristics of Sebocytes Based on the Donkey Cell Transcriptome Atlas.
Worldwide, donkeys (Equus asinus) are valued for their meat and milk, and in China also for the medical value of their skin. Physiological characteristics are key to the donkey's adaptability, including their digestive, respiratory, and reproductive systems, which enable them to survive and work in a variety of environments. However, the understanding of donkey physiological characteristics at the cellular level remains poor. Thus, single-cell transcriptome sequencing is used to construct a detailed transcriptional atlas based on 20 tissues from the Dezhou donkey (in total 84 cell types and 275 050 high quality cells) to perform an in-depth investigation of molecular physiology. Cross-species and cross-tissue comparative analyses reveal SOX10 to be an evolutionally conserved regulon in oligodendrocytes and illuminate the distinctive transcriptional patterns of donkey sebocytes. Moreover, through multispecies skin metabolomics, highly abundant, species-specific metabolites in donkey skin are identified, such as arachidonic acid and gamma-glutamylcysteine, and the pivotal role of sebocytes in donkey skin metabolism is highlighted. In summary, this work offers new insights into the unique metabolic patterns of donkey skin and provides a valuable resource for the conservation of donkey germplasm and the advancement of selective breeding programs.
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Single-cell analysis of a tumor-derived exosome signature correlates with prognosis and immunotherapy response.
BACKGROUND: Tumor-derived exosomes (TEXs) are involved in tumor progression and the immune modulation process and mediate intercellular communication in the tumor microenvironment. Although exosomes are considered promising liquid biomarkers for disease diagnosis, it is difficult to discriminate TEXs and to develop TEX-based predictive biomarkers. METHODS: In this study, the gene expression profiles and clinical information were collected from The Cancer Genome Atlas (TCGA) database, IMvigor210 cohorts, and six independent Gene Expression Omnibus datasets. A TEXs-associated signature named TEXscore was established to predict overall survival in multiple cancer types and in patients undergoing immune checkpoint blockade therapies. RESULTS: Based on exosome-associated genes, we first constructed a tumor-derived exosome signature named TEXscore using a principal component analysis algorithm. In single-cell RNA-sequencing data analysis, ascending TEXscore was associated with disease progression and poor clinical outcomes. In the TCGA Pan-Cancer cohort, TEXscore was elevated in tumor samples rather than in normal tissues, thereby serving as a reliable biomarker to distinguish cancer from non-cancer sources. Moreover, high TEXscore was associated with shorter overall survival across 12 cancer types. TEXscore showed great potential in predicting immunotherapy response in melanoma, urothelial cancer, and renal cancer. The immunosuppressive microenvironment characterized by macrophages, cancer-associated fibroblasts, and myeloid-derived suppressor cells was associated with high TEXscore in the TCGA and immunotherapy cohorts. Besides, TEXscore-associated miRNAs and gene mutations were also identified. Further experimental research will facilitate the extending of TEXscore in tumor-associated exosomes. CONCLUSIONS: TEXscore capturing tumor-derived exosome features might be a robust biomarker for prognosis and treatment responses in independent cohorts.
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A novel immune-related ceRNA network that predicts prognosis and immunotherapy response in lung adenocarcinoma.
BACKGROUND: The tumor microenvironment plays an important role in the progression and malignancy of lung adenocarcinoma and affects the immunotherapy response. There is increasing evidence that long non-coding RNAs (lncRNAs) as competing endogenous RNAs (ceRNAs) have significant functions in the development and treatment response of various kinds of cancer. This study aimed to explore the association between immune-related lncRNA-microRNA (miRNA)-messenger RNA (mRNA)-ceRNA networks, and the prognosis of and immunotherapy response in lung adenocarcinoma. METHODS: RNA-sequencing (RNA-seq) and miRNA-seq data from The Cancer Genome Atlas (TCGA) were used to evaluate the infiltration of immune cells in lung adenocarcinoma samples by undertaking a single-sample gene set enrichment analysis (ssGSEA) to divide the cells into high and low immune cell infiltration groups. The differentially expressed mRNA (DEmRNA) was further analyzed by a weighted gene co-expression network analysis (WGCNA), search tool for recurring instances of neighboring genes (STRING), and Cytoscape to select hub genes. The ceRNA network was constructed using Cytoscape. Additionally, survival analyses were conducted to screen out prognostic candidate genes. RESULTS: Seven thousand five hundred and thirty-eight mRNAs, 540 lncRNAs, and 138 miRNAs were found to be differentially expressed between the high and low immune cell infiltration groups. The two DEmRNA modules most significantly associated with immune cell infiltration were further analyzed, and four clusters, including 179 DEmRNAs, were selected based on Molecular Complex Detection (MCODE) scores. The selected DEmRNAs in the four clusters were mainly enriched in pathways involved in regulating the immune response. Ultimately, a ceRNA network of SNHG6-hsa-miR-30e-5p-CYSLTR1 was identified as being associated with the prognosis of and immunotherapy response in lung adenocarcinoma. CONCLUSIONS: The present study extends understandings of immune-related lncRNA-miRNA-mRNA-ceRNA networks and identifies novel targets and a regulatory pathway for anti-tumor immunotherapy.