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Benchmarking single-cell RNA-sequencing protocols for cell atlas projects.
Single-cell RNA sequencing (scRNA-seq) is the leading technique for characterizing the transcriptomes of individual cells in a sample. The latest protocols are scalable to thousands of cells and are being used to compile cell atlases of tissues, organs and organisms. However, the protocols differ substantially with respect to their RNA capture efficiency, bias, scale and costs, and their relative advantages for different applications are unclear. In the present study, we generated benchmark datasets to systematically evaluate protocols in terms of their power to comprehensively describe cell types and states. We performed a multicenter study comparing 13 commonly used scRNA-seq and single-nucleus RNA-seq protocols applied to a heterogeneous reference sample resource. Comparative analysis revealed marked differences in protocol performance. The protocols differed in library complexity and their ability to detect cell-type markers, impacting their predictive value and suitability for integration into reference cell atlases. These results provide guidance both for individual researchers and for consortium projects such as the Human Cell Atlas.
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Deciphering decidual deficiencies in recurrent spontaneous abortion and the therapeutic potential of mesenchymal stem cells at single-cell resolution.
BACKGROUND: Recurrent spontaneous abortion (RSA) is a challenging condition that affects the health of women both physically and mentally, but its pathogenesis and treatment have yet to be studied in detail. In recent years, Wharton's jelly-derived mesenchymal stem cells (WJ-MSCs) have been shown to be effective in treating various diseases. Current understanding of RSA treatment using WJ-MSCs is limited, and the exact mechanisms of WJ-MSCs action in RSA remains largely unclear. In this study, we explored the decidual deficiencies in RSA and the therapeutic potential of WJ-MSCs at single-cell resolution. METHODS: Three mouse models were established: a normal pregnancy group, an RSA group, and a WJ-MSC treatment group. Decidual tissue samples were collected for single-cell RNA sequencing (scRNA-seq) and functional verification, including single-cell resolution in situ hybridization on tissues (SCRINSHOT) and immunofluorescence. RESULTS: We generated a single-cell atlas of decidual tissues from normal pregnant, RSA, and WJ-MSC-treated mice and identified 14 cell clusters in the decidua on day 14. Among these cell populations, stromal cells were the most abundant cell clusters in the decidua, and we further identified three novel subclusters (Str_0, Str_1, and Str_2). We also demonstrated that the IL17 and TNF signaling pathways were enriched for upregulated DEGs of stromal cells in RSA mice. Intriguingly, cell-cell communication analysis revealed that Str_1 cell-related gene expression was greatly reduced in the RSA group and rescued in the WJ-MSC treatment group. Notably, the interaction between NK cells and other cells in the RSA group was attenuated, and the expression of Spp1 (identified as an endometrial toleration-related marker) was significantly reduced in the NK cells of the RSA group but could be restored by WJ-MSC treatment. CONCLUSION: Herein, we implemented scRNA-seq to systematically evaluate the cellular heterogeneity and transcriptional regulatory networks associated with RSA and its treatment with WJ-MSCs. These data revealed potential therapeutic targets of WJ-MSCs to remodel the decidual subpopulations in RSA and provided new insights into decidua-derived developmental defects at the maternal-foetal interface.
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Exploring ribosome biogenesis in lung adenocarcinoma to advance prognostic methods and immunotherapy strategies.
BACKGROUND: Lung adenocarcinoma (LUAD) presents a considerable danger to human health and has evolved into a major public health concern. Ribosome biogenesis (RiboSis) is a critical process for synthesizing ribosomes, closely associated with cancer initiation, progression, and treatment resistance, potentially serving as a target for future cancer therapies. METHODS: Utilizing single-cell RNA sequencing (scRNA-seq) technology, a single-cell atlas of LUAD was delineated, focusing on the analysis of T cell subpopulations. Cells were scored based on the expression patterns of 331 genes associated with RiboSis across different cell types, and monocle2 was employed to analyze the developmental trajectory of CD4+ T cells. Employing various machine learning algorithms, a ribosome biogenesis-related signature (RBS) was constructed and compared to 140 published LUAD prognostic models. The relationship between RBS risk scores and various factors in LUAD patients, including prognosis, the tumor immune microenvironment (TIME), responsiveness to immunotherapy, and sensitivity to pharmacological treatments was specifically analyzed. Immunohistochemistry was utilized to validate the expression levels of immune markers in the high- and low- RBS groups, and in vitro experiments were performed to validate the functional role of the pivotal gene KIF23 in the progression of LUAD. RESULTS: Using single-cell analysis, two distinct T cell subtypes were identified: CD8+ interferon (IFN) response T cells and CD4+ stress response T cells. It was observed that CD4+ naive-like T cells exhibit high expression of RiboSis-related genes, with a gradual decrease in RiboSis activity as CD4+ T cells develop. Compared to other prognostic models, RBS demonstrated superior performance in prognosis prediction. The low-RBS group exhibited a tumor microenvironment (TME) more favorable for efficient immune monitoring and reaction, higher responsiveness to immunotherapy, and a better prognosis. Immunohistochemistry confirmed higher expression levels of immune markers in the low-RBS group, while in vitro experiments validated the promoting role of KIF23 in LUAD cell proliferation, migration and invasion. CONCLUSION: This study delves into the relationship between RiboSis and LUAD cell subpopulations, identifying a potent prognostic biomarker for LUAD. This biomarker aids in assessing immunotherapy efficacy in LUAD patients, ultimately enhancing their prognosis and guiding clinical decision-making.
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Multimodal Human Scalp Atlas Defines Cell Landscape and Lineage Architecture In Situ.
Human scalp hair has an extraordinary ability to grow continuously for years while maintaining structural and functional integrity. However, the cell states and lineage organization that enable this capacity and how they are disrupted in inflammatory hair loss disorders remain poorly defined in humans. Here we establish a high-resolution, multimodal atlas of human scalp by integrating deep-coverage spatial transcriptomics with single-cell RNA-seq and multiomics data. This reference resolves spatially organized epithelial and mesenchymal states and links in situ transcriptional programs to chromatin accessibility dynamics and lineage trajectories at single-cell resolution, revealing human-specific principles of tissue organization and previously unrecognized features of hair follicle architecture and lineage progression. We validate key aspects of matrix cell organization and cell activities using live imaging, connecting molecularly defined cell states to dynamic cell behaviors and lineage progression in the matrix. Leveraging the atlas as a spatial reference, we project patient scRNA-seq profiles from alopecia areata and lichen planopilaris onto defined cell compartments, resolving disease-specific perturbations in fibroblasts, epithelial and immune populations. This comparison delineates distinct cellular programs associated with non-scarring versus scarring hair loss and highlights compartment- and state-specific pathways with diagnostic and therapeutic potential. Together, this work provides a foundational resource for human hair biology and establishes a generalizable framework for spatially resolved, multimodal interrogation of tissue organization and disease in complex human tissues.
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MUC1-C integrates activation of the IFN-γ pathway with suppression of the tumor immune microenvironment in triple-negative breast cancer.
BACKGROUND: Immune checkpoint inhibitors (ICIs) have had a profound impact on the treatment of many tumors; however, their effectiveness against triple-negative breast cancers (TNBCs) has been limited. One factor limiting responsiveness of TNBCs to ICIs is a lack of functional tumor-infiltrating lymphocytes (TILs) in 'non-inflamed' or 'cold' tumor immune microenvironments (TIMEs), although by unknown mechanisms. Targeting MUC1-C in a mouse transgenic TNBC tumor model increases cytotoxic tumor-infiltrating CD8+ T cells (CTLs), supporting a role for MUC1-C in immune evasion. The basis for these findings and whether they extend to human TNBCs are not known. METHODS: Human TNBC cells silenced for MUC1-C using short hairpin RNAs (shRNAs) were analyzed for the effects of MUC1-C on global transcriptional profiles. Differential expression and rank order analysis was used for gene set enrichment analysis (GSEA). Gene expression was confirmed by quantitative reverse-transcription PCR and immunoblotting. The The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) datasets were analyzed for effects of MUC1 on GSEA, cell-type enrichment, and tumor immune dysfunction and exclusion. Single-cell scRNA-seq datasets of TNBC samples were analyzed for normalized expression associations between MUC1 and selected genes within tumor cells. RESULTS: Our results demonstrate that MUC1-C is a master regulator of the TNBC transcriptome and that MUC1-C-induced gene expression is driven by STAT1 and IRF1. We found that MUC1-C activates the inflammatory interferon (IFN)-γ-driven JAK1→STAT1→IRF1 pathway and induces the IDO1 and COX2/PTGS2 effectors, which play key roles in immunosuppression. Involvement of MUC1-C in activating the immunosuppressive IFN-γ pathway was extended by analysis of human bulk and scRNA-seq datasets. We further demonstrate that MUC1 associates with the depletion and dysfunction of CD8+ T cells in the TNBC TIME. CONCLUSIONS: These findings demonstrate that MUC1-C integrates activation of the immunosuppressive IFN-γ pathway with depletion of TILs in the TNBC TIME and provide support for MUC1-C as a potential target for improving TNBC treatment alone and in combination with ICIs. Of translational significance, MUC1-C is a druggable target with chimeric antigen receptor (CAR) T cells, antibody-drug conjugates (ADCs) and a functional inhibitor that are under clinical development.
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Dendritic-cell diversity in equine blood revealed by single-cell transcriptomics.
INTRODUCTION: Detailed classification of equine dendritic cells (DC) is necessary to address various research questions, such as the role of DC subsets in immune-mediated diseases of horses. METHODS: We applied single-cell RNA sequencing (scRNA-seq) on DC enriched from the blood of two horses. RESULTS: All main DC subsets were detected by key gene expression, including conventional DC type 1 (cDC1; XCR1) and type 2 (cDC2; FCER1A, CD1E), as well as plasmacytoid DC (pDC; TCF4). In addition, we detected a small cluster of hematopoietic progenitors, as well as transitional DC (tDC; FCER1A, TCF4) and putative DC type 3 (DC3; FLT3, CD163). Our data confirms the previously reported phenotype of equine pDC (Flt3+MHC-IIlowCADM1lowCD172aint), cDC1 (Flt3+MHC-IIhighCADM1highCD172alow-int), and cDC2 (Flt3+MHC-IIhighCADM1intCD172ahigh), while also highlighting considerable CD14 expression for cDC2. Two subclusters of equine cDC2 were found to be enriched in FCER1A or CX3CR1 transcripts (cDC2.1 and cDC2.2, respectively), with suggested enhanced extravasation and T-cell stimulatory capacities of the latter. Conservation of DC subsets across species (horse, pig, human, mouse) was illustrated by enrichment analyses with subset-specific gene signatures and by cross-species data integration with publicly available scRNA-seq datasets. CONCLUSION: Our atlas of equine blood DC is a valuable resource for comparative analyses, and it forms the foundation for understanding the involvement of distinct DC subsets in infections and immune-mediated pathologies.
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Single-cell RNA-Seq reveals the heterogeneity of fibroblasts within the tympanojugular paraganglioma microenvironment.
Tympanojugular paragangliomas (TJP) originate from the parasympathetic ganglia in the lateral base of the skull. Although the cellular composition and oncogenic mechanisms of paragangliomas have been evaluated, a comprehensive transcriptomic atlas specific to TJP remains to be established to facilitate further investigations. In this study, single-cell RNA sequencing and whole-exome sequencing were conducted on six surgically excised TJP samples to determine their cellular composition and intratumoral heterogeneity. Fibroblasts were sub-classified into two distinct groups: myofibroblasts and fibroblasts associated with bone remodeling. Additionally, an elaborate regulatory and cell-cell communication network was determined, highlighting the multifaceted role of fibroblasts, which varies depending on expression transitions. The Kit receptor (KIT) signaling pathway mediated interactions between fibroblasts and mast cells, whereas robust connections with endothelial and Schwann cell-like cells were facilitated through the platelet-derived growth factor signaling pathway. These findings establish a foundation for studying the mechanisms underlying protumor angiogenesis and the specific contributions of fibroblasts within the TJP microenvironment. IL6 signaling pathway of fibroblasts interacting with macrophages and endothelial cells may be involved in tumor regrowth. These results enhance our understanding of fibroblast functionality and provide a resource for future therapeutic targeting of TJP.
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Gene selection for optimal prediction of cell position in tissues from single-cell transcriptomics data.
Single-cell RNA-sequencing (scRNAseq) technologies are rapidly evolving. Although very informative, in standard scRNAseq experiments, the spatial organization of the cells in the tissue of origin is lost. Conversely, spatial RNA-seq technologies designed to maintain cell localization have limited throughput and gene coverage. Mapping scRNAseq to genes with spatial information increases coverage while providing spatial location. However, methods to perform such mapping have not yet been benchmarked. To fill this gap, we organized the DREAM Single-Cell Transcriptomics challenge focused on the spatial reconstruction of cells from the Drosophila embryo from scRNAseq data, leveraging as silver standard, genes with in situ hybridization data from the Berkeley Drosophila Transcription Network Project reference atlas. The 34 participating teams used diverse algorithms for gene selection and location prediction, while being able to correctly localize clusters of cells. Selection of predictor genes was essential for this task. Predictor genes showed a relatively high expression entropy, high spatial clustering and included prominent developmental genes such as gap and pair-rule genes and tissue markers. Application of the top 10 methods to a zebra fish embryo dataset yielded similar performance and statistical properties of the selected genes than in the Drosophila data. This suggests that methods developed in this challenge are able to extract generalizable properties of genes that are useful to accurately reconstruct the spatial arrangement of cells in tissues.
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Distinct T and innate-like lymphocyte reprogramming following lyophilized fecal microbiota transplantation in recurrent C. difficile infection.
Fecal microbiota transplantation (FMT) is highly effective in preventing recurrent Clostridioides difficile infection (rCDI), yet its immunological mechanisms remain poorly defined. While bacterial engraftment and recovery of microbial diversity are central to FMT efficacy, accumulating evidence suggests that host immune reprogramming is involved. In murine models, regulatory CD4⁺ T cells are indispensable for clearing C. difficile. To address this mechanistic gap, we examined systemic immune reprogramming following FMT by performing flow cytometry and single-cell RNA sequencing (scRNA-seq) on a subset of successfully treated participants from a clinical trial comparing lyophilized FMT (LFMT) with lyophilized sterile fecal filtrate (LSFF, no live bacteria) for preventing rCDI. Flow cytometry was performed on peripheral mononuclear cells from 19 LFMT recipients and 18 LSFF recipients, and scRNA-seq analysis was performed on two LFMT recipients. Although flow cytometry results did not show significant changes in the assessed markers after rCDI resolution in either treatment group, exploratory scRNA-seq in the two LFMT recipients revealed distinct LFMT-associated transcriptional signatures across adaptive and innate-like lymphocyte populations. LFMT was associated with upregulated activation and regulatory genes (CD69, STAT1, TOX, RORA, FOXP3) in CD4⁺ and CD8⁺ T cells, suggesting enhanced immune regulation with reduced cytotoxic gene expression (GZMB, PRF1, GNLY). Innate-like lymphocytes displayed broad activation, with natural killer cells showing increased KLRD1, PRF1, and IL2RB and mucosal-associated invariant T cells (MAIT cells) upregulating STAT1, JUN, and RORA while downregulating KLRB1 and STAT3. These transcriptional programs are consistent with recalibration of T cell homeostasis and innate-like lymphocyte activation, potentially driven by microbial restoration. Collectively, this exploratory study provides the first single-cell immune atlas of LFMT in rCDI, identifying coordinated activation of regulatory, effector, and innate immune pathways. Given the small sample size, these findings should be considered hypothesis-generating, requiring validation in larger cohorts.
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An atlas of gene regulatory networks for memory CD4 + T cells in youth and old age.
Aging profoundly affects immune-system function, promoting susceptibility to pathogens, cancers and chronic inflammation. We previously identified a population of IL-10-producing, T follicular helper-like cells (" Tfh10 "), linked to suppressed vaccine responses in aged mice. Here, we integrate single-cell ( sc )RNA-seq, scATAC-seq and genome-scale modeling to characterize Tfh10 - and the full CD4 + memory T cell ( CD4 + TM ) compartment - in young and old mice. We identified 13 CD4 + TM populations, which we validated through cross-comparison to prior scRNA-seq studies. We built gene regulatory networks ( GRNs ) that predict transcription-factor control of gene expression in each T-cell population and how these circuits change with age. Through integration with pan-cell aging atlases, we identified intercellular-signaling networks driving age-dependent changes in CD4 + TM. Our atlas of finely resolved CD4 + TM subsets, GRNs and cell-cell communication networks is a comprehensive resource of predicted regulatory mechanisms operative in memory T cells, presenting new opportunities to improve immune responses in the elderly.