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Alterations in Astrocyte Subpopulations in Glioma and Identification of Cuproptosis-Related Genes Using Single-Cell RNA Sequencing.
PURPOSE: Mitochondrial metabolism is essential for energy production and the survival of brain cells, particularly in astrocytes. Cuproptosis is a newly identified form of programmed cell death that occurs due to the disruption of mitochondrial metabolism caused by excessive copper toxicity. However, the relationship between cuproptosis-related genes (CRGs) in the tumor microenvironment (TME) and the prognosis of gliomas remains unclear. PATIENTS AND METHODS: In this study, we utilized 32,293 cells obtained from three in-house single-cell RNA sequencing (scRNA-seq) datasets, along with 6,148 cells acquired from the Chinese Glioma Genome Atlas (CGGA) involving 14 glioma patients, to identify and validate the TME of gliomas. RESULTS: Based on an analysis of 32,293 single cells, we investigated intra-tumor heterogeneity, intercellular communication, and astrocyte differentiation trajectories in gliomas. Our findings revealed that the TGFβ signaling pathway exhibited a higher relative strength in astrocyte subpopulations. Additionally, we identified a novel three-gene signature (CDKN2A, SOX2, and MPC1) was identified for prognostic prediction. Furthermore, glioma patients with a high-risk score demonstrated poorer overall survival (OS) compared to those with a low-risk score in both training and testing datasets (P training set < 0.001; P test set = 0.037). CONCLUSION: Our study revealed the prognostic value of the CRGs in astrocytes exhibiting tumor immunosuppressive characteristics in glioma. We established a novel three-gene prognostic model that offers new insights into the prognosis and treatment strategies for gliomas.
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Single-nucleus transcriptomic atlas reveals autophagy and hormone signaling in early grapevine (Vitis vinifera L.) tendril versus inflorescence determination.
Understanding the early specification of tendrils versus inflorescences in grapevine is key for developmental biology and agricultural applications. Here, we performed a comparative anatomical and cyto-histological analysis of lateral buds from the tendril-prone cultivar "Pinot Noir" ("PN") and the inflorescence-prone cultivar "Einset Seedless" ("EinS"). Our results show that cytological differences between tendril and inflorescence primordia emerge early during floral initiation, prior to any visible structural divergence. In particular, rib zone (RZ) cells in the uncommitted lateral meristem (UM) of "PN" differentiated into vacuolated pith cells more rapidly than those in "EinS." We subsequently applied single-nucleus RNA sequencing (snRNA-seq) to 50 052 nuclei from lateral buds of both cultivars, generating a cell type-resolved transcriptional atlas. Reconstruction of shoot apical meristem (SAM) and UM developmental trajectories revealed accelerated SAM differentiation in "PN." Together with cyto-histological observations of a less abundant UM mantle zone and lower cell cycle gene activity in UM cells, these findings indicate that both accelerated SAM differentiation and reduced UM proliferative activity restrict complete inflorescence formation in "PN," which is consistent with the anatomical differences observed. Analyzing UM and inflorescence meristem differentiation trajectories distinguished inflorescences- and tendril-specific differentiation trajectories, and revealed the involvement of the autophagy and hormone signal transduction pathway in early tendril versus inflorescence determination. Furthermore, transcription factors from the GRF, B3, S1Fa-like, WRKY, GATA, and C2H2 families showed expression patterns correlated with tendril specification. These results provide key insights into the differentiation of homologous reproductive structures in grapevine, thereby advancing the theoretical framework for early tendril versus inflorescence specification and supporting future applied research.
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Pan-cancer analysis of prognostic and immunological role of IL4I1 in human tumors: a bulk omics research and single cell sequencing validation.
BACKGROUND: Interleukin-4 inducible gene 1 (IL4I1) regulates tumor progression in numerous tumor types. However, its correlation with immune infiltration and prognosis of patients in a pan-cancer setting remains unclear. METHODS: Data from the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), UALCAN, Clinical Proteomic Tumor Analysis Consortium (CPTAC), Gene Expression Omnibus (GEO), cBioPortal, Cancer Single-cell State Atlas (CancerSEA), and Tumor IMmune Estimation Resource(TIMER) databases were used to evaluate IL4I1 expression, clinical features and prognostic effects, gene set enrichment, and correlation with immune cell infiltration, as well as the relationship between IL4I1 methylation and expression and survival prognosis. Correlations with 192 anticancer drugs were also analyzed. RESULTS: IL4I1 was significantly overexpressed in the majority of tumors, and the imbalance of IL4I1 was significantly correlated with overall survival and pathological stage. Moreover, total IL4I1 protein was increased in cancer. Therefore, IL4I1 may be used as a prognostic biomarker or protective factor in numerous types of cancer. The methylation level of IL4I1 may also be used as a prognostic marker. The functional enrichment of IL4I1 was closely related to the immunomodulatory pathway. In addition, the level of tumor-associated macrophage infiltration was positively correlated with the expression of IL4I1 in pan-cancerous tissues. scRNA-seq analysis suggested that IL4I1 differ significantly among different cells in the tumor microenvironment and was most enriched in macrophages. Various immune checkpoint genes were positively correlated with IL4I1 expression in most tumors. In addition, patients with high IL4I1 expression may be resistant to BMS-754807 and docetaxel, but sensitive to temozolomide. CONCLUSION: IL4I1 may play a role as promoter of cancer and prognostic indicator in patients. High expression of IL4I1 is associated with the state of tumor immunosuppression and may contribute to tumor-associated macrophage invasion. Therefore, IL4I1 may be a new therapeutic target for the treatment and prognosis of patients with cancer.
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Comparative Transcriptomic Analysis of the Hematopoietic System between Human and Mouse by Single Cell RNA Sequencing.
(1) Background: mouse models are fundamental to the study of hematopoiesis, but comparisons between mouse and human in single cells have been limited in depth. (2) Methods: we constructed a single-cell resolution transcriptomic atlas of hematopoietic stem and progenitor cells (HSPCs) of human and mouse, from a total of 32,805 single cells. We used Monocle to examine the trajectories of hematopoietic differentiation, and SCENIC to analyze gene networks underlying hematopoiesis. (3) Results: After alignment with Seurat 2, the cells of mouse and human could be separated by same cell type categories. Cells were grouped into 17 subpopulations; cluster-specific genes were species-conserved and shared functional themes. The clustering dendrogram indicated that cell types were highly conserved between human and mouse. A visualization of the Monocle results provided an intuitive representation of HSPC differentiation to three dominant branches (Erythroid/megakaryocytic, Myeloid, and Lymphoid), derived directly from the hematopoietic stem cell and the long-term hematopoietic stem cells in both human and mouse. Gene regulation was similarly conserved, reflected by comparable transcriptional factors and regulatory sequence motifs in subpopulations of cells. (4) Conclusions: our analysis has confirmed evolutionary conservation in the hematopoietic systems of mouse and human, extending to cell types, gene expression and regulatory elements.
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An atlas of spider development at single-cell resolution provides new insights into arthropod embryogenesis.
Spiders are a diverse order of chelicerates that diverged from other arthropods over 500 million years ago. Research on spider embryogenesis, particularly studies using the common house spider Parasteatoda tepidariorum, has made important contributions to understanding the evolution of animal development, including axis formation, segmentation, and patterning. However, we lack knowledge about the cells that build spider embryos, their gene expression profiles and fate. Single-cell transcriptomic analyses have been revolutionary in describing these complex landscapes of cellular genetics in a range of animals. Therefore, we carried out single-cell RNA sequencing of P. tepidariorum embryos at stages 7, 8 and 9, which encompass the establishment and patterning of the body plan, and initial differentiation of many tissues and organs. We identified 20 cell clusters, from 18.5 k cells, which were marked by many developmental toolkit genes, as well as a plethora of genes not previously investigated. We found differences in the cell cycle transcriptional signatures, suggestive of different proliferation dynamics, which related to distinctions between endodermal and some mesodermal clusters, compared with ectodermal clusters. We identified many Hox genes as markers of cell clusters, and Hox gene ohnologs were often present in different clusters. This provided additional evidence of sub- and/or neo-functionalisation of these important developmental genes after the whole genome duplication in an arachnopulmonate ancestor (spiders, scorpions, and related orders). We also examined the spatial expression of marker genes for each cluster to generate a comprehensive cell atlas of these embryonic stages. This revealed new insights into the cellular basis and genetic regulation of head patterning, hematopoiesis, limb development, gut development, and posterior segmentation. This atlas will serve as a platform for future analysis of spider cell specification and fate, and studying the evolution of these processes among animals at cellular resolution.
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The Human Cell Atlas: Technical approaches and challenges.
The Human Cell Atlas is a large, international consortium that aims to identify and describe every cell type in the human body. The comprehensive cellular maps that arise from this ambitious effort have the potential to transform many aspects of fundamental biology and clinical practice. Here, we discuss the technical approaches that could be used today to generate such a resource and also the technical challenges that will be encountered.
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An Atlas of Vagal Sensory Neurons and Their Molecular Specialization.
Sensory functions of the vagus nerve are critical for conscious perceptions and for monitoring visceral functions in the cardio-pulmonary and gastrointestinal systems. Here, we present a comprehensive identification, classification, and validation of the neuron types in the neural crest (jugular) and placode (nodose) derived vagal ganglia by single-cell RNA sequencing (scRNA-seq) transcriptomic analysis. Our results reveal major differences between neurons derived from different embryonic origins. Jugular neurons exhibit fundamental similarities to the somatosensory spinal neurons, including major types, such as C-low threshold mechanoreceptors (C-LTMRs), A-LTMRs, Aδ-nociceptors, and cold-, and mechano-heat C-nociceptors. In contrast, the nodose ganglion contains 18 distinct types dedicated to surveying the physiological state of the internal body. Our results reveal a vast diversity of vagal neuron types, including many previously unanticipated types, as well as proposed types that are consistent with chemoreceptors, nutrient detectors, baroreceptors, and stretch and volume mechanoreceptors of the respiratory, gastrointestinal, and cardiovascular systems.
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Automatic cell-type harmonization and integration across Human Cell Atlas datasets.
Harmonizing cell types across the single-cell community and assembling them into a common framework is central to building a standardized Human Cell Atlas. Here, we present CellHint, a predictive clustering tree-based tool to resolve cell-type differences in annotation resolution and technical biases across datasets. CellHint accurately quantifies cell-cell transcriptomic similarities and places cell types into a relationship graph that hierarchically defines shared and unique cell subtypes. Application to multiple immune datasets recapitulates expert-curated annotations. CellHint also reveals underexplored relationships between healthy and diseased lung cell states in eight diseases. Furthermore, we present a workflow for fast cross-dataset integration guided by harmonized cell types and cell hierarchy, which uncovers underappreciated cell types in adult human hippocampus. Finally, we apply CellHint to 12 tissues from 38 datasets, providing a deeply curated cross-tissue database with ∼3.7 million cells and various machine learning models for automatic cell annotation across human tissues.
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Whole-body integration of gene expression and single-cell morphology.
Animal bodies are composed of cell types with unique expression programs that implement their distinct locations, shapes, structures, and functions. Based on these properties, cell types assemble into specific tissues and organs. To systematically explore the link between cell-type-specific gene expression and morphology, we registered an expression atlas to a whole-body electron microscopy volume of the nereid Platynereis dumerilii. Automated segmentation of cells and nuclei identifies major cell classes and establishes a link between gene activation, chromatin topography, and nuclear size. Clustering of segmented cells according to gene expression reveals spatially coherent tissues. In the brain, genetically defined groups of neurons match ganglionic nuclei with coherent projections. Besides interneurons, we uncover sensory-neurosecretory cells in the nereid mushroom bodies, which thus qualify as sensory organs. They furthermore resemble the vertebrate telencephalon by molecular anatomy. We provide an integrated browser as a Fiji plugin for remote exploration of all available multimodal datasets.
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Spatial multi-omics reveals a cancer-associated fibroblast-T cell niche sustaining tissue-resident immunity in clear-cell renal cell carcinoma.
BACKGROUND: Clear-cell renal cell carcinoma (ccRCC) has a lot of immune cells in it, but the performance of the body's immune system against ccRCC and the outcome for patients who have ccRCC vary greatly. Recent studies indicate that not only how many immune cells are present, but also the state of those cells and how they are arranged within the tumor microenvironment (TME) contribute to how well an individual's immune system can eliminate ccRCC. Therefore, this study aimed to systematically characterize the spatial organization and functional interactions of immune and stromal cells in ccRCC using integrated single-cell and spatial multi-omics approaches. METHODS: To better understand ccRCC through this multi-omics analysis, we utilized two cohort studies of single-cell RNA sequencing (scRNA-seq) data combined with spatial transcriptomics (sRNA-seq) data to make a multi-omics atlas of ccRCC. We performed in-depth functional enrichment analysis, survival analysis, modeling of cell-to-cell communication, as well as spatial validation of these analyses, to identify the heterogeneous nature of cell-cell interactions in vivo within the ccRCC TME and determine how they correlate and contribute to prognostic outcomes for ccRCC patients. RESULTS: We identified various epithelial, immune, and mesenchymal cell states in ccRCC, showing distinct differences in their prognostic values: CD4 Trm, iCAFs, PDGFRB+ mesenchymal cells, and proximal tubule-like epithelial programs had positive prognostic associations, while resident CD8 T cells and ascending thin limb-like epithelial cell programs had negative prognostic associations. Spatial and computational analyses of these results showed the presence of a secure iCAF-CD4 Trm cell niche, with fibronectin-integrin α5β1 signaling as an anchor for CD4 Trm residency, located at the tumor-stroma interface. CONCLUSIONS: These results demonstrate that the prognosis of ccRCC is determined by the spatial organization of the immune-stromal cell niche rather than just by the number of immune cells present. The iCAF-CD4 Trm axes may provide opportunities for precision immunomodulatory therapy.