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Adversarial domain translation networks for integrating large-scale atlas-level single-cell datasets.
The rapid emergence of large-scale atlas-level single-cell RNA-seq datasets presents remarkable opportunities for broad and deep biological investigations through integrative analyses. However, harmonizing such datasets requires integration approaches to be not only computationally scalable, but also capable of preserving a wide range of fine-grained cell populations. We have created Portal, a unified framework of adversarial domain translation to learn harmonized representations of datasets. When compared to other state-of-the-art methods, Portal achieves better performance for preserving biological variation during integration, while achieving the integration of millions of cells, in minutes, with low memory consumption. We show that Portal is widely applicable to integrating datasets across different samples, platforms and data types. We also apply Portal to the integration of cross-species datasets with limited shared information among them, elucidating biological insights into the similarities and divergences in the spermatogenesis process among mouse, macaque and human.
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Invasion status stratifies the composition of the human pancreatic cancer perineural niche.
UNLABELLED: The peripheral nervous system innervates the pancreatic ductal adenocarcinoma (PDAC) microenvironment, and perineural invasion (PNI), the invasion of cancer cells in and around nerves, correlates with metastatic burden and poor outcomes. Though PDAC innervation is near universal and the majority of PDAC patients harbor PNI, the cellular and molecular composition of the heterocellular perineural niche is largely unknown, obscuring functional significance. Here we provide a deeply phenotyped spatial and single-cell atlas of the human PDAC perineural niche, enabling a high-resolution comparison of invaded versus non-invaded nerve neighborhoods. This atlas leverages a novel vision-centric artificial intelligence model for imaging-based spatial transcriptomics, coupled with pathology-guided single-nucleus RNA-seq. These analyses revealed that invaded nerve neighborhoods harbor cancer cells of the classical subtype, together with myofibroblastic cancer-associated fibroblasts (CAFs) and lipid-associated macrophages. Non-invaded nerve neighborhoods, in contrast, harbor inflammatory CAFs and infiltration of B and T lymphocytes. These findings raise the possibility that PNI and not innervation itself is immune-suppressive in this setting, motivating functional studies. STATEMENT OF SIGNIFICANCE: Human PDAC is innervated and almost invariably harbors PNI, but the composition and functions of perineural niches remain unclear. Here we provide a spatial and single-cell atlas of the human PDAC perineural niche, defining cancer and stromal cell states in the context of PNI and nominating this process as potentially immune-suppressive.
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Single-cell chemokine receptor profiles delineate the immune contexture of tertiary lymphoid structures in head and neck squamous cell carcinoma.
Tertiary lymphoid structures (TLSs) are organized aggregates of immune cells associated with favourable prognosis and response to immunotherapy in cancer, but the immune architecture of TLSs remains poorly elucidated. Here, we hypothesize that the spatial architecture of leukocytes in TLSs can be reconstructed de novo, at least partially, by cell-inherent chemokine receptors profiles. Single-cell RNA-sequencing (scRNA-seq) revealed 47 subpopulations of leukocytes in head and neck squamous cell carcinoma (HNSC). Combined with bulk RNA-seq, we observed that CXCR3, CCR7, CCR6, CXCR5, and CCR1 are TLS-associated chemokine receptors. According to the spatial reference, the cellular atlas with TLS-associated chemokine receptors in HNSC TLSs was elaborately portrayed by multiplex immunohistochemistry (mIHC). Subsequently, we explored the functions and evolutionary trajectory of cells distributed in TLSs. Our investigation presents an approach to reconstructing the immune architecture of TLSs, which would help boost the antitumor immune response by inducing neogenesis TLSs in HNSC.
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Single-Cell RNA Sequencing Reveals Dynamic Transcriptional Landscape of Testicular Maturation in Dezhou Donkeys.
Testicular development and spermatogenesis are critical for male reproduction, but their molecular mechanisms in Dezhou donkeys remain understudied. This study used single-cell RNA sequencing (scRNA-seq) to analyze testicular tissues from Dezhou donkeys at juvenile (2 months), pre-pubertal (12 months), and mature (24 months) stages. A total of 24,606 high-quality cells were profiled, constructing a comprehensive single-cell transcriptional atlas. Unsupervised clustering identified nine major cell types: three germ cell subtypes (spermatogonia, spermatocytes, spermatids) and six somatic cell subtypes (Leydig cells, Sertoli cells, peritubular muscle cells, macrophages, endothelial cells, T cells). Key marker genes (AMH, TNP1, UTF1, ZMYND10) were validated by immunofluorescence. Pseudotemporal trajectory analysis revealed sequential germ cell differentiation (spermatogonia → spermatocytes → spermatids) and Sertoli cell maturation (immature → mature), while Leydig cells and peritubular muscle cells shared common progenitors. CellChat analysis identified critical ligand-receptor pairs in BMP, IGF, WNT, and FSH pathways, which regulate testicular development. This study provides the comprehensive single-cell transcriptional map of Dezhou donkey testicular development, elucidating key molecular mechanisms of germ and somatic cell maturation. The findings offer valuable insights into donkey reproductive biology, supporting breeding improvement and male infertility research.
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Single-Cell Transcriptome Atlas and Regulatory Dynamics in Developing Cotton Anthers.
Plant anthers are composed of different specialized cell types with distinct roles in plant reproduction. High temperature (HT) stress causes male sterility, resulting in crop yield reduction. However, the spatial expression atlas and regulatory dynamics during anther development and in response to HT remain largely unknown. Here, the first single-cell transcriptome atlas and chromatin accessibility survey in cotton anther are established, depicting the specific expression and epigenetic landscape of each type of cell in anthers. The reconstruction of meiotic cells, tapetal cells, and middle layer cell developmental trajectories not only identifies novel expressed genes, but also elucidates the precise degradation period of middle layer and reveals a rapid function transition of tapetal cells during the tetrad stage. By applying HT, heterogeneity in HT response is shown among cells of anthers, with tapetal cells responsible for pollen wall synthesis are most sensitive to HT. Specifically, HT shuts down the chromatin accessibility of genes specifically expressed in the tapetal cells responsible for pollen wall synthesis, such as QUARTET 3 (QRT3) and CYTOCHROME P450 703A2 (CYP703A2), resulting in a silent expression of these genes, ultimately leading to abnormal pollen wall and male sterility. Collectively, this study provides substantial information on anthers and provides clues for heat-tolerant crop creation.
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Single-Cell Transcriptomic Analysis of Cardiac Progenitor Differentiation.
PURPOSE OF REVIEW: Emerging single-cell RNA sequencing technologies hold great promises to boost our understanding of the heterogeneity and molecular regulation of diverse cell phenotypes during organ development. In this review, we aimed at summarizing recent advances in employing single-cell transcriptomic analysis to depict the landscape of embryonic heart development, in particular, focusing on cardiac progenitor (CP) differentiation. RECENT FINDINGS: Recent studies unbiasedly cataloged and characterized cardiac cell types in the spatial and temporal resolution during early heart development. Pseudo-time analysis revealed a temporal continuum of the differentiation progress from embryonic day (E) 6.5 to E9.5, implicating early cardiac lineage restriction during mouse gastrulation. First and second heart field (FHF and SHF) CPs adopted different differentiation strategies and underwent distinct transcriptional regulation. Collectively, the comprehensive molecular atlases yield a rich resource for identification of the key cardiac regulators and signaling molecules within the key cardiac gene regulatory network (GRN) governing cardiac cell fate determinations. This review offers insights into the exquisite process and its regulation of CP differentiation at single-cell resolution. As single-cell technologies continuously grow and evolve, computational integration of multimodal single-cell data with well-designed experimental validation promises to further delineate molecular basis in deploying cardiac progenitors of distinct sources with anatomical information.
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Exploring Cellular Heterogeneity: Single-Cell and Spatial Transcriptomics of Alzheimer Disease Brains and iPSC-Derived Microglia.
BACKGROUND: Substantial evidence has established the critical role of microglia, the brain's resident immune cells, in the pathogenesis of Alzheimer's disease (AD). Microglia exhibit diverse transcriptional states in response to neuroinflammatory stimuli, and understanding these states is crucial for elucidating the underlying mechanisms of AD. METHODS: In this work, we integrated single-cell and spatially resolved transcriptomics data from multiple cohorts and brain regions, including microglia from experimental and human brains. RESULTS: This comprehensive atlas revealed a great heterogeneity of microglial states, with a significant enrichment of specific states, including activated microglia, in AD brains compared to controls. Further integration of spatial transcriptomics and immunohistochemistry showed that activated microglia are predominantly located in the external cortical layers near amyloid plaques, while homeostatic microglia are more prevalent in the internal cortical layers and further away from the plaques. These spatial patterns were further validated using P2RY12 immunostaining, which confirmed the reliability of the transcriptomic data. CONCLUSION: By integrating single-cell and spatial transcriptomics, we have provided a detailed atlas of microglial diversity, revealing the regional and pathological specificity of microglial states.
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L2,1-Extreme Learning Machine: An Efficient Robust Classifier for Tumor Classification.
With the development of cancer research, various gene expression datasets containing cancer information show an explosive growth trend. In addition, due to the continuous maturity of single-cell RNA sequencing (scRNA-seq) technology, the protein information and pedigree information of a single cell are also continuously mined. It is a technical problem of how to classify these high-dimensional data correctly. In recent years, Extreme Learning Machine (ELM) has been widely used in the field of supervised learning and unsupervised learning. However, the traditional ELM does not consider the robustness of the method. To improve the robustness of ELM, in this paper, a novel ELM method based on L2,1-norm named L2,1-Extreme Learning Machine (L2,1 -ELM) has been proposed. The method introduces L2,1-norm on loss function to improve the robustness, and minimizes the influence of noise and outliers. Firstly, we evaluate the new method on five UCI datasets. The experiment results prove that our method can achieve competitive results. Next, the novel method is applied to the problem of classification of cancer samples and single-cell RNA sequencing datasets. The experimental results on The Cancer Genome Atlas (TCGA) datasets and scRNA-seq datasets prove that ELM and its variants has great potential in the classification of cancer samples.
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Single-cell and spatial transcriptomics reveal a potential role of ATF3 in brain metastasis of lung adenocarcinoma.
BACKGROUND: Brain metastasis (BrM) has been a challenge for lung cancer treatment, but the mechanisms underlying lung cancer BrM remain elusive. This study aims to dissect cellular components and their spatial distribution in human BrM tumors of lung adenocarcinoma (LUAD) and identify potential therapeutic targets. METHODS: We performed single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) on three LUAD BrMs, and validated our findings using public scRNA-seq data of 10 LUAD BrMs. Western blotting, quantitative real-time polymerase chain reaction (qRT-PCR) and functional experiments were employed for experimental studies. RESULTS: By combining scRNA-seq and ST, our analysis revealed the inter- and intra-tumoral heterogeneity of cellular components and their spatial localization within LUAD BrMs. Through RNA velocity and transcription factor (TF) regulatory activity analyses, we identified ATF3 as a potential regulator of the mesenchymal-epithelial transition (MET) program, which plays crucial roles in the colonization of tumor cells at metastatic sites. Furthermore, we demonstrated that knockdown of ATF3 significantly inhibited cancer cell proliferation while promoting cancer cell migration. Mechanistically, ATF3 knockdown could reverse the MET program. Additionally, we revealed that LGALS3/ANXA2-mediated cell-cell interaction between macrophage and tumor cells may also promote the MET program. CONCLUSIONS: Our study provides a single-cell atlas of the cellular composition in BrM of LUAD and identifies ATF3 as a potential therapeutic target for BrM treatment.
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PYCR1 promotes glutamine metabolism and the progression of lung adenocarcinoma by regulating the expression of OPLAH.
Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. Glutamine plays a critical role in the progression of LUAD. However, the function of pyrroline-5-carboxylate reductase 1 (PYCR1) and its regulatory role in glutamine metabolism remain unclear. Transcriptomic and clinical data for LUAD were obtained from The Cancer Genome Atlas (TCGA) and validated using Gene Expression Omnibus (GEO) datasets (GSE19188, GSE13213). Glutamine metabolism-related genes were analyzed for differential expression and prognostic significance. Functional enrichment was performed via gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) analyses. Single-cell RNA-seq data (GSE117570) were processed using Seurat, and cell-cell communication was inferred with CellChat. In vitro, lentiviral overexpression, Western blotting, EdU, CCK-8, and glutamine uptake assays were conducted. An orthotopic xenograft model was established in nude mice to assess tumor growth in vivo. Six glutamine-metabolism-related genes were found significantly overexpressed in LUAD tissues and associated with poor overall survival. Single-cell sequencing revealed predominant PYCR1 expression in malignant cells. Functional assays demonstrated that PYCR1 overexpression enhanced glutamine uptake, proliferation, and inhibited apoptosis in LUAD cells, effects mediated via suppression of the P53 pathway. PYCR1 promoted tumor growth in a xenograft model and was found to transcriptionally upregulate 5-oxoprolinase (OPLAH), which augmented its oncogenic effects. Our findings identify the PYCR1/OPLAH axis as a key driver of LUAD progression via p53 signaling, revealing a promising therapeutic target.