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Temporal specificity and heterogeneity of Drosophila immune cells.
Immune cells provide defense against non-self and have recently been shown to also play key roles in diverse processes such as development, metabolism, and tumor progression. The heterogeneity of Drosophila immune cells (hemocytes) remains an open question. Using bulk RNA sequencing, we find that the hemocytes display distinct features in the embryo, a closed and rapidly developing system, compared to the larva, which is exposed to environmental and metabolic challenges. Through single-cell RNA sequencing, we identify fourteen hemocyte clusters present in unchallenged larvae and associated with distinct processes, e.g., proliferation, phagocytosis, metabolic homeostasis, and humoral response. Finally, we characterize the changes occurring in the hemocyte clusters upon wasp infestation, which triggers the differentiation of a novel hemocyte type, the lamellocyte. This first molecular atlas of hemocytes provides insights and paves the way to study the biology of the Drosophila immune cells in physiological and pathological conditions.
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Mapping human development at single-cell resolution.
Human development is regulated by spatiotemporally restricted molecular programmes and is pertinent to many areas of basic biology and human medicine, such as stem cell biology, reproductive medicine and childhood cancer. Mapping human development has presented significant technological, logistical and ethical challenges. The availability of established human developmental biorepositories and the advent of cutting-edge single-cell technologies provide new opportunities to study human development. Here, we present a working framework for the establishment of a human developmental cell atlas exploiting single-cell genomics and spatial analysis. We discuss how the development atlas will benefit the scientific and clinical communities to advance our understanding of basic biology, health and disease.
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Single-cell RNA sequencing reveals peripheral immunological features in Parkinson's Disease.
Although many researchers of Parkinson's disease (PD) have shifted their focus from the central nervous system (CNS) to the peripheral blood, a significant knowledge gap remains between PD severity and the peripheral immune response. In the current study, we aimed to map the peripheral immunity atlas in peripheral blood mononuclear cells (PBMCs) from PD patients and healthy controls using single-cell RNA sequencing (scRNA-seq). Our study employed scRNA-seq analysis to map the peripheral immunity atlas in PD by profiling PBMCs from PD-Early, PD-Late patients and matched controls. By enlarging the blood sample size, we validated the roles of NK cells in numerous immune-related biological processes. We also detected the infiltration of NK cells into the cerebral motor cortex as the disease progressed, using human brain sections, and elucidated the communication between the periphery and CNS and its implications for PD. As a result, cell subpopulation atlases in PBMCs from PD patients and healthy controls along with differentially expressed genes in NK cells were identified by scRNA-seq analysis, representing 6 major immune cell subsets among which NK cells declined in the progression of PD. We further validated NK cell reduction in increasing samples and found that they participated in numerous immune-related biological processes and infiltration into the cerebral motor cortex as the disease proceeded, evidencingd the close communication between the peripheral immune response and CNS. Strikingly, XCL2 positively correlated with PD severity, with good predictive performance of PD and specific expression in subclusters C2 and C5 of NK cells. All these findings delineated the critical role of peripheral immune response mediated by NK cells in the pathogenesis of PD. NK cell-specific XCL2 could be used as a diagnostic marker for treating PD. The indispensable function of NK cells and NK cell-specific molecular biomarkers highlighted the implication of the peripheral immune response in PD progression. Trial registration: ChiCTR, ChiCTR1900023975. Registered 20 June 2019 - Retrospectively registered, https://www.chictr.org.cn/showproj.html?proj=31035 .
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A test metric for assessing single-cell RNA-seq batch correction.
Single-cell transcriptomics is a versatile tool for exploring heterogeneous cell populations, but as with all genomics experiments, batch effects can hamper data integration and interpretation. The success of batch-effect correction is often evaluated by visual inspection of low-dimensional embeddings, which are inherently imprecise. Here we present a user-friendly, robust and sensitive k-nearest-neighbor batch-effect test (kBET; https://github.com/theislab/kBET ) for quantification of batch effects. We used kBET to assess commonly used batch-regression and normalization approaches, and to quantify the extent to which they remove batch effects while preserving biological variability. We also demonstrate the application of kBET to data from peripheral blood mononuclear cells (PBMCs) from healthy donors to distinguish cell-type-specific inter-individual variability from changes in relative proportions of cell populations. This has important implications for future data-integration efforts, central to projects such as the Human Cell Atlas.
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Breaking barriers: improving time and space resolution of arbuscular mycorrhizal symbiosis with single-cell sequencing approaches.
The cell and molecular bases of arbuscular mycorrhizal (AM) symbiosis, a crucial plant-fungal interaction for nutrient acquisition, have been extensively investigated by coupling traditional RNA sequencing techniques of roots sampled in bulk, with methods to capture subsets of cells such as laser microdissection. These approaches have revealed central regulators of this complex relationship, yet the requisite level of detail to effectively untangle the intricacies of temporal and spatial development remains elusive.The recent adoption of single-cell RNA sequencing (scRNA-seq) techniques in plant research is revolutionizing our ability to dissect the intricate transcriptional profiles of plant-microbe interactions, offering unparalleled insights into the diversity and dynamics of individual cells during symbiosis. The isolation of plant cells is particularly challenging due to the presence of cell walls, leading plant researchers to widely adopt nuclei isolation methods. Despite the increased resolution that single-cell analyses offer, it also comes at the cost of spatial perspective, hence, it is necessary the integration of these approaches with spatial transcriptomics to obtain a comprehensive overview.To date, few single-cell studies on plant-microbe interactions have been published, most of which provide high-resolution cell atlases that will become crucial for fully deciphering symbiotic interactions and addressing future questions. In AM symbiosis research, key processes such as the mutual recognition of partners during arbuscule development within cortical cells, or arbuscule senescence and degeneration, remain poorly understood, and these advancements are expected to shed light on these processes and contribute to a deeper understanding of this plant-fungal interaction.
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The Transcriptional Cell Atlas of Testis Development in Sheep at Pre-Sexual Maturity.
Sheep testes undergo a dramatic rate of development with structural changes during pre-sexual maturity, including the proliferation and maturation of somatic niche cells and the initiation of spermatogenesis. To explore this complex process, 12,843 testicular cells from three males at pre-sexual maturity (three-month-old) were sequenced using the 10× Genomics ChromiumTM single-cell RNA-seq (scRNA-seq) technology. Nine testicular somatic cell types (Sertoli cells, myoid cells, monocytes, macrophages, Leydig cells, dendritic cells, endothelial cells, smooth muscle cells, and leukocytes) and an unknown cell cluster were observed. In particular, five male germ cell types (including two types of undifferentiated spermatogonia (Apale and Adark), primary spermatocytes, secondary spermatocytes, and sperm cells) were identified. Interestingly, Apale and Adark were found to be two distinct states of undifferentiated spermatogonia. Further analysis identified specific marker genes, including UCHL1, DDX4, SOHLH1, KITLG, and PCNA, in the germ cells at different states of differentiation. The study revealed significant changes in germline stem cells at pre-sexual maturation, paving the way to explore the candidate factors and pathways for the regulation of germ and somatic cells, and to provide us with opportunities for the establishment of livestock stem cell breeding programs.
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Rhaponticin inhibits the proliferation, migration, and invasion of head and neck squamous cell carcinoma (HNSCC) cells through modulation of the IL6/STAT3 signaling pathway.
BACKGROUND: Rhaponticin, a bioactive compound derived from rhubarb, has been demonstrated anti-tumor effects in various types of cancer. However, its impact on HNSCC remains unexplored. This study aims to investigate the specific molecular mechanisms by which Rhaponticin inhibits the invasion and metastasis of HNSCC cells. METHOD: The potential target genes that rhaponticin acts on in HNSCC were identified using online databases. The mechanisms by which rhaponticin influences the occurrence and progression of HNSCC were investigated through network pharmacology, molecular docking, bioinformatics analysis, and cellular experiments. RESULT: Using network pharmacology, we identified 40 hub genes from the collected gene set. Subsequently, by analyzing The Cancer Genome Atlas (TCGA) data with four machine learning algorithms, we identified IL-6 as a potential target associated with the occurrence and progression of HNSCC. Based on the average expression level of IL-6, we classified the samples into high-expression and low-expression groups and conducted survival analysis. Our results indicated that IL-6 expression was significantly correlated with patient survival. Gene Set Enrichment Analysis (GSEA) revealed that Rhaponticin might influence HNSCC via the IL6/STAT3 signaling pathway. Using the CIBERSORT algorithm, we assessed the differences in infiltration levels of 22 immune cell types between the high and low IL-6 expression groups. Our findings suggest that multiple immune cells may be involved in the pathogenesis of HNSCC. Additionally, we analyzed single-cell RNA sequencing (scRNA-seq) data from the GEO database to compare IL6 expression levels in tumor and normal tissues and evaluated its prognostic impact using Receiver Operating Characteristic (ROC) curve analysis. Molecular docking studies demonstrated that Rhaponticin binds stably to IL6. In the experimental section, we used two HNSCC cell lines (CAL 27 and SCC-9) to investigate the effects of Rhaponticin. Our results showed that Rhaponticin effectively inhibited cell proliferation, invasion, and migration, and reduced the expression of proteins in the IL6/STAT3 signaling pathway. CONCLUSION: Rhaponticin shows promise in treating HNSCC by inhibiting the IL6/STAT3 signaling pathway.
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High NLRC5 Expression Is Associated with an Immunosuppressive Tumor Microenvironment and Poor Prognosis in Esophageal Squamous Cell Carcinoma.
Background: Immunotherapy efficacy in esophageal squamous cell carcinoma (ESCC) is often limited by an immunosuppressive tumor microenvironment (TME). NLRC5, a key regulator of MHC-I antigen presentation, exhibits context-dependent roles in tumor immunity; however, its function in ESCC remains unclear. This study aimed to systematically investigate the expression pattern, prognostic value, and immunological role of NLRC5 in ESCC. Methods: An integrated analysis of bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq) data was performed using multiple cohorts, including The Cancer Genome Atlas, Gene Expression Omnibus, and an in-house ESCC cohort. Differential expression, survival analysis, immune infiltration estimation, and functional enrichment analyses were conducted to elucidate the role of NLRC5 in the tumor microenvironment. Results: NLRC5 was significantly upregulated in ESCC and its high expression independently predicted poor patient survival. Although NLRC5 expression was associated with increased CD8+ T cell infiltration, it was paradoxically accompanied by features of T-cell exhaustion and elevated expression of multiple immune checkpoints. Moreover, NLRC5-high tumors were enriched in transcriptional programs related to PANoptosis, indicating an additional immunosuppressive mechanism within the TME. Conclusions: NLRC5 is not only a prognostic biomarker but also a key modulator of an immune-active yet functionally suppressed tumor microenvironment in ESCC. These findings highlight NLRC5 as a potential therapeutic target for restoring effective antitumor immunity.
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Cell Atlas of The Human Fovea and Peripheral Retina.
Most irreversible blindness results from retinal disease. To advance our understanding of the etiology of blinding diseases, we used single-cell RNA-sequencing (scRNA-seq) to analyze the transcriptomes of ~85,000 cells from the fovea and peripheral retina of seven adult human donors. Utilizing computational methods, we identified 58 cell types within 6 classes: photoreceptor, horizontal, bipolar, amacrine, retinal ganglion and non-neuronal cells. Nearly all types are shared between the two retinal regions, but there are notable differences in gene expression and proportions between foveal and peripheral cohorts of shared types. We then used the human retinal atlas to map expression of 636 genes implicated as causes of or risk factors for blinding diseases. Many are expressed in striking cell class-, type-, or region-specific patterns. Finally, we compared gene expression signatures of cell types between human and the cynomolgus macaque monkey, Macaca fascicularis. We show that over 90% of human types correspond transcriptomically to those previously identified in macaque, and that expression of disease-related genes is largely conserved between the two species. These results validate the use of the macaque for modeling blinding disease, and provide a foundation for investigating molecular mechanisms underlying visual processing.
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Landscape of epithelial cell subpopulations in the human esophageal squamous cell carcinoma microenvironment.
AIMS: We sought to reveal the landscape of epithelial cell subpopulations in the human esophageal squamous cell carcinoma microenvironment and investigate their parts on esophageal squamous carcinoma (ESCC) development. BACKGROUND: Epithelial cells play an important role in the occurrence and development of ESCC through multiple mechanisms. While the landscape of epithelial cell subpopulations in ESCC, remains unclear. OBJECTIVE: Exploring the role of epithelial cell subpopulations in ESCC progression. METHODS: Seurat R package was used for single-cell RNA sequencing (scRNA-seq) data filtering, dimensionality reduction, clustering and differentially expressed genes analysis. Cellmarker database was adopted for cell cluster annotation. Functional enrichment analysis was carried out by Gene Ontology (GO) analysis. InferCNV package was conducted for copy number variation (CNV) of epithelial cell subpopulations in all chromosomal regions. Pseudotime trajectory analysis was implemented for exploring differentiation trajectory of epithelial cells subgroups during the cancer progression. CellChat analysis was used for probing the interactions between epithelial cells and NK/T cells. cellular experiments were performed using Quantitative Real-Time Polymerase Chain Reaction (RT-qPCR), Wound-Healing Assay and transwell. RESULTS: 11 major cell subpopulations were identified in ESCC and adjunct tissues. Further reclassification of epithelial cells uncovered 4 subpopulations. Enrichment analysis revealed that highly expressed genes in 4 epithelial cell subpopulations were related to cell proliferation, immune response and angiogenesis. CNV analysis found that UBD + epithelial cells and GAS2L3+ epithelial cells had a higher proportion of CNV. Cell differentiation trajectories disclosed that KRT6C+ and GSTA1+ epithelial cells were in an intermediate state of differentiation, while UBD+ and GAS2L3+ epithelial cells are in an end state of differentiation during ESCC progression. Finally, we found that four epithelial cell subpopulations all inhibited NK/T cells through NECTIN2-TIGIT and CLEC2B-KLRB1. Low ATF3 and DDIT3 mRNA expression inhibited ESCC cell migration and invasion. CONCLUSION: Here, we obtained a through epithelial cell atlas of ESCC at single-cell resolution, explored the role of epithelial cell in ESCC progression, and unveiled immunosuppressive signals to NK/T cells in promoting ESCC. Our findings expand the comprehension of epithelial cells and offer a theoretical guidance for future anti-epithelial cell treatment of ESCC.