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BACKGROUND: Single-cell transcriptome sequencing (scRNA-Seq) has allowed new types of investigations at unprecedented levels of resolution. Among the primary goals of scRNA-Seq is the classification of cells into distinct types. Many approaches build on existing clustering literature to develop tools specific to single-cell. However, almost all of these methods rely on heuristics or user-supplied parameters to control the number of clusters. This affects both the resolution of the clusters within the original dataset as well as their replicability across datasets. While many recommendations exist, in general, there is little assurance that any given set of parameters will represent an optimal choice in the trade-off between cluster resolution and replicability. For instance, another set of parameters may result in more clusters that are also more replicable. RESULTS: Here, we propose Dune, a new method for optimizing the trade-off between the resolution of the clusters and their replicability. Our method takes as input a set of clustering results-or partitions-on a single dataset and iteratively merges clusters within each partitions in order to maximize their concordance between partitions. As demonstrated on multiple datasets from different platforms, Dune outperforms existing techniques, that rely on hierarchical merging for reducing the number of clusters, in terms of replicability of the resultant merged clusters as well as concordance with ground truth. Dune is available as an R package on Bioconductor: https://www.bioconductor.org/packages/release/bioc/html/Dune.html . CONCLUSIONS: Cluster refinement by Dune helps improve the robustness of any clustering analysis and reduces the reliance on tuning parameters. This method provides an objective approach for borrowing information across multiple clusterings to generate replicable clusters most likely to represent common biological features across multiple datasets.

The heart, which is the first organ to develop, is highly dependent on its form to function1,2. However, how diverse cardiac cell types spatially coordinate to create the complex morphological structures that are crucial for heart function remains unclear. Here we integrated single-cell RNA-sequencing with high-resolution multiplexed error-robust fluorescence in situ hybridization to resolve the identity of the cardiac cell types that develop the human heart. This approach also provided a spatial mapping of individual cells that enables illumination of their organization into cellular communities that form distinct cardiac structures. We discovered that many of these cardiac cell types further specified into subpopulations exclusive to specific communities, which support their specialization according to the cellular ecosystem and anatomical region. In particular, ventricular cardiomyocyte subpopulations displayed an unexpected complex laminar organization across the ventricular wall and formed, with other cell subpopulations, several cellular communities. Interrogating cell-cell interactions within these communities using in vivo conditional genetic mouse models and in vitro human pluripotent stem cell systems revealed multicellular signalling pathways that orchestrate the spatial organization of cardiac cell subpopulations during ventricular wall morphogenesis. These detailed findings into the cellular social interactions and specialization of cardiac cell types constructing and remodelling the human heart offer new insights into structural heart diseases and the engineering of complex multicellular tissues for human heart repair.

The temporal lobe of the human brain contains the entorhinal cortex (EC). This region of the brain is a highly interconnected integrative hub for sensory and spatial information; it also has a key role in episodic memory formation and is the main source of cortical hippocampal inputs1-4. The human EC continues to develop during childhood5, but neurogenesis and neuronal migration to the EC are widely considered to be complete by birth. Here we show that the human temporal lobe contains many young neurons migrating into the postnatal EC and adjacent regions, with a large tangential stream persisting until the age of around one year and radial dispersal continuing until around two to three years of age. By contrast, we found no equivalent postnatal migration in rhesus macaques (Macaca mulatta). Immunostaining and single-nucleus RNA sequencing of ganglionic eminence germinal zones, the EC stream and the postnatal EC revealed that most migrating cells in the EC stream are derived from the caudal ganglionic eminence and become LAMP5+RELN+ inhibitory interneurons. These late-arriving interneurons could continue to shape the processing of sensory and spatial information well into postnatal life, when children are actively interacting with their environment. The EC is one of the first regions of the brain to be affected in Alzheimers disease, and previous work has linked cognitive decline to the loss of LAMP5+RELN+ cells6,7. Our investigation reveals that many of these cells arrive in the EC through a major postnatal migratory stream in early childhood.

Rheumatoid arthritis (RA) management leans toward achieving remission or low disease activity. In this study, we conducted single-cell RNA sequencing (scRNA-Seq) of peripheral blood mononuclear cells (PBMCs) from 36 individuals (18 patients with RA and 18 matched controls, accounting for age, sex, race, and ethnicity), to identify disease-relevant cell subsets and cell type-specific signatures associated with disease activity. Our analysis revealed 18 distinct PBMC subsets, including an IFN-induced transmembrane 3-overexpressing (IFITM3-overexpressing) IFN-activated monocyte subset. We observed an increase in CD4+ T effector memory cells in patients with moderate-high disease activity (DAS28-CRP ≥ 3.2) and a decrease in nonclassical monocytes in patients with low disease activity or remission (DAS28-CRP < 3.2). Pseudobulk analysis by cell type identified 168 differentially expressed genes between RA and matched controls, with a downregulation of proinflammatory genes in the γδ T cell subset, alteration of genes associated with RA predisposition in the IFN-activated subset, and nonclassical monocytes. Additionally, we identified a gene signature associated with moderate-high disease activity, characterized by upregulation of proinflammatory genes such as TNF, JUN, EGR1, IFIT2, MAFB, and G0S2 and downregulation of genes including HLA-DQB1, HLA-DRB5, and TNFSF13B. Notably, cell-cell communication analysis revealed an upregulation of signaling pathways, including VISTA, in both moderate-high and remission-low disease activity contexts. Our findings provide valuable insights into the systemic cellular and molecular mechanisms underlying RA disease activity.

Sample multiplexing enables pooled analysis during single-cell RNA sequencing workflows, thereby increasing throughput and reducing batch effects. A challenge for all multiplexing techniques is to link sample-specific barcodes with cell-specific barcodes, then demultiplex sample identity post-sequencing. However, existing demultiplexing tools fail under many real-world conditions where barcode cross-contamination is an issue. We therefore developed deMULTIplex2, an algorithm inspired by a mechanistic model of barcode cross-contamination. deMULTIplex2 employs generalized linear models and expectation-maximization to probabilistically determine the sample identity of each cell. Benchmarking reveals superior performance across various experimental conditions, particularly on large or noisy datasets with unbalanced sample compositions.

Single‐cell RNA sequencing and spatial transcriptomics enable unprecedented insight into cellular and molecular pathways implicated in human skin aging and regeneration. Senescent cells are individual cells that are irreversibly cell cycle arrested and can accumulate across the human lifespan due to cell‐intrinsic and ‐extrinsic stressors. With an atlas of single‐cell RNA‐sequencing and spatial transcriptomics, epidermal and dermal senescence and its effects were investigated, with a focus on melanocytes and fibroblasts. Photoaging due to ultraviolet light exposure was associated with higher burdens of senescent cells, a sign of biological aging, compared to chronological aging. A skin‐specific cellular senescence gene set, termed SenSkin™, was curated and confirmed to be elevated in the context of photoaging, chronological aging, and non‐replicating CDKN1A+ (p21) cells. In the epidermis, senescent melanocytes were associated with elevated melanin synthesis, suggesting haphazard pigmentation, while in the dermis, senescent reticular dermal fibroblasts were associated with decreased collagen and elastic fiber synthesis. Spatial analysis revealed the tendency for senescent cells to cluster, particularly in photoaged skin. This work proposes a strategy for characterizing age‐related skin dysfunction through the lens of cellular senescence and suggests a role for senescent epidermal cells (i.e., melanocytes) and senescent dermal cells (i.e., reticular dermal fibroblasts) in age‐related skin sequelae. [ABSTRACT FROM AUTHOR]

Background: Metabolic dysregulation is a hallmark of type 2 diabetes mellitus (T2DM), in which the abnormalities in brown adipose tissue (BAT) play important roles. However, the cellular composition and function of BAT as well as its pathological signifi- cance in diabetes remain incompletely understood. Our objective is to delineate the single-cell landscape of BAT-derived stromal vascular fraction (SVF) and their characteristic alterations in T2DM rats. Methods: T2DM was induced in rats by intraperitoneal injection of low-dose streptozotocin and high-fat diet feeding. Single-cell mRNA sequencing was then performed on BAT samples and compared to normal rats to characterize changes in T2DM rats. Subsequently, the importance of key cell subsets in T2DM was elucidated using various functional studies. Results: Almost all cell types in the BAT-derived SVF of T2DM rats exhibited enhanced inflammatory responses, increased angiogenesis, and disordered glucose and lipid metabolism. The multidirectional differentiation potential of adipose tissue-derived stem cells was also reduced. Moreover, macrophages played a pivotal role in intercellular crosstalk of BAT-derived SVF. A novel Rarres2+macrophage subset promoted the differentiation and metabolic function of brown adipocytes via adipose-immune crosstalk. Conclusion: BAT SVF exhibited strong heterogeneity in cellular composition and function and contributed to T2DM as a signifi- cant inflammation source, in which a novel macrophage subset was identified that can promote brown adipocyte function. [ABSTRACT FROM AUTHOR]

Purpose: By utilizing both protein and mRNA expression patterns, we can identify more detailed and diverse immune cells, providing insights into understanding the complex immune landscape in cancer ecosystems. Materials and Methods: This study was performed by obtaining publicly available Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) data of peripheral blood mononuclear cells (PBMCs) from the Gene Expression Omnibus database. A total of 94674 total cells were analyzed, of which 32412 were T cells. There were 228 protein features and 16262 mRNA features in the data. The Seurat package was used for quality control and preprocessing, principal component analysis was performed, and Uniform Manifold Approximation and Projection was used to visualize the clusters. Protein and mRNA levels in the CITE-seq were analyzed. Results: We observed that a subset of T cells in the clusters generated at the protein level divided better. By identifying mRNA markers that were highly correlated with the CD4 and CD8 proteins and cross-validating CD26 and CD99 markers using flow cytometry, we found that CD4+ and CD8+ T cells were better discriminated in PBMCs. Weighted Nearest Neighbor clustering results identified a previously unobserved T cell subset. Conclusion: In this study, we used CITE-seq data to confirm that protein expression patterns could be used to identify cells more precisely. These findings will improve our understanding of the heterogeneity of immune cells in the future and provide valuable insights into the complexity of the immune response in health and disease. [ABSTRACT FROM AUTHOR]

The basic plan of the retina is conserved across vertebrates, yet species differ profoundly in their visual needs1. Retinal cell types may have evolved to accommodate these varied needs, but this has not been systematically studied. Here we generated and integrated single-cell transcriptomic atlases of the retina from 17 species: humans, two non-human primates, four rodents, three ungulates, opossum, ferret, tree shrew, a bird, a reptile, a teleost fish and a lamprey. We found high molecular conservation of the six retinal cell classes (photoreceptors, horizontal cells, bipolar cells, amacrine cells, retinal ganglion cells (RGCs) and Müller glia), with transcriptomic variation across species related to evolutionary distance. Major subclasses were also conserved, whereas variation among cell types within classes or subclasses was more pronounced. However, an integrative analysis revealed that numerous cell types are shared across species, based on conserved gene expression programmes that are likely to trace back to an early ancestral vertebrate. The degree of variation among cell types increased from the outer retina (photoreceptors) to the inner retina (RGCs), suggesting that evolution acts preferentially to shape the retinal output. Finally, we identified rodent orthologues of midget RGCs, which comprise more than 80% of RGCs in the human retina, subserve high-acuity vision, and were previously believed to be restricted to primates2. By contrast, the mouse orthologues have large receptive fields and comprise around 2% of mouse RGCs. Projections of both primate and mouse orthologous types are overrepresented in the thalamus, which supplies the primary visual cortex. We suggest that midget RGCs are not primate innovations, but are descendants of evolutionarily ancient types that decreased in size and increased in number as primates evolved, thereby facilitating high visual acuity and increased cortical processing of visual information.

Mouse models are a critical tool for studying human diseases, particularly developmental disorders1. However, conventional approaches for phenotyping may fail to detect subtle defects throughout the developing mouse2. Here we set out to establish single-cell RNA sequencing of the whole embryo as a scalable platform for the systematic phenotyping of mouse genetic models. We applied combinatorial indexing-based single-cell RNA sequencing3 to profile 101 embryos of 22 mutant and 4 wild-type genotypes at embryonic day 13.5, altogether profiling more than 1.6 million nuclei. The 22 mutants represent a range of anticipated phenotypic severities, from established multisystem disorders to deletions of individual regulatory regions4,5. We developed and applied several analytical frameworks for detecting differences in composition and/or gene expression across 52 cell types or trajectories. Some mutants exhibit changes in dozens of trajectories whereas others exhibit changes in only a few cell types. We also identify differences between widely used wild-type strains, compare phenotyping of gain- versus loss-of-function mutants and characterize deletions of topological associating domain boundaries. Notably, some changes are shared among mutants, suggesting that developmental pleiotropy might be 'decomposable' through further scaling of this approach. Overall, our findings show how single-cell profiling of whole embryos can enable the systematic molecular and cellular phenotypic characterization of mouse mutants with unprecedented breadth and resolution.

Benchmarking single-cell RNA-seq (scRNA-seq) and single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq) computational tools demands simulators to generate realistic sequencing reads. However, none of the few read simulators aim to mimic real data. To fill this gap, we introduce scReadSim, a single-cell RNA-seq and ATAC-seq read simulator that allows user-specified ground truths and generates synthetic sequencing reads (in a FASTQ or BAM file) by mimicking real data. At both read-sequence and read-count levels, scReadSim mimics real scRNA-seq and scATAC-seq data. Moreover, scReadSim provides ground truths, including unique molecular identifier (UMI) counts for scRNA-seq and open chromatin regions for scATAC-seq. In particular, scReadSim allows users to design cell-type-specific ground-truth open chromatin regions for scATAC-seq data generation. In benchmark applications of scReadSim, we show that UMI-tools achieves the top accuracy in scRNA-seq UMI deduplication, and HMMRATAC and MACS3 achieve the top performance in scATAC-seq peak calling.

Rheumatoid arthritis is a prototypical autoimmune disease that causes joint inflammation and destruction1. There is currently no cure for rheumatoid arthritis, and the effectiveness of treatments varies across patients, suggesting an undefined pathogenic diversity1,2. Here, to deconstruct the cell states and pathways that characterize this pathogenic heterogeneity, we profiled the full spectrum of cells in inflamed synovium from patients with rheumatoid arthritis. We used multi-modal single-cell RNA-sequencing and surface protein data coupled with histology of synovial tissue from 79 donors to build single-cell atlas of rheumatoid arthritis synovial tissue that includes more than 314,000 cells. We stratified tissues into six groups, referred to as cell-type abundance phenotypes (CTAPs), each characterized by selectively enriched cell states. These CTAPs demonstrate the diversity of synovial inflammation in rheumatoid arthritis, ranging from samples enriched for T and B cells to those largely lacking lymphocytes. Disease-relevant cell states, cytokines, risk genes, histology and serology metrics are associated with particular CTAPs. CTAPs are dynamic and can predict treatment response, highlighting the clinical utility of classifying rheumatoid arthritis synovial phenotypes. This comprehensive atlas and molecular, tissue-based stratification of rheumatoid arthritis synovial tissue reveal new insights into rheumatoid arthritis pathology and heterogeneity that could inform novel targeted treatments.

To maintain a stable and clear image of the world, our eyes reflexively follow the direction in which a visual scene is moving. Such gaze-stabilization mechanisms reduce image blur as we move in the environment. In non-primate mammals, this behaviour is initiated by retinal output neurons called ON-type direction-selective ganglion cells (ON-DSGCs), which detect the direction of image motion and transmit signals to brainstem nuclei that drive compensatory eye movements1. However, ON-DSGCs have not yet been identified in the retina of primates, raising the possibility that this reflex is mediated by cortical visual areas. Here we mined single-cell RNA transcriptomic data from primate retina to identify a candidate ON-DSGC. We then combined two-photon calcium imaging, molecular identification and morphological analysis to reveal a population of ON-DSGCs in the macaque retina. The morphology, molecular signature and GABA (γ-aminobutyric acid)-dependent mechanisms that underlie direction selectivity in primate ON-DSGCs are highly conserved with those in other mammals. We further identify a candidate ON-DSGC in human retina. The presence of ON-DSGCs in primates highlights the need to examine the contribution of subcortical retinal mechanisms to normal and aberrant gaze stabilization in the developing and mature visual system.

Dermatofibrosarcoma protuberans (DFSP) is a rare cutaneous sarcoma characterized by the COL1A1‐PDGFB fusion gene. This study utilized single‐cell RNA sequencing to dissect the cellular and molecular landscape of primary DFSP. Distinct DFSP cell clusters, exhibiting fibroblast‐like traits, revealed variations in pathways associated with proliferation, inflammation and metabolism. Differential gene expression analysis during the differentiation from tumour stem cells to DFSP cells unveiled SMOC2, DCN and TGFBR3 as potential regulators of tumour invasion and immune infiltration through VEGF/TGF‐β signalling modulation. Cellular communication analysis highlighted interactions within DFSP cell clusters and with endothelial cells, implicating molecules such as NAMPT, ANGPT2 and PTN in pathogenesis and treatment resistance. These findings offer insights into DFSP intratumour heterogeneity, elucidate molecular mechanisms underlying tumour behaviour, and suggest potential therapeutic targets. [ABSTRACT FROM AUTHOR]

Pancreatic cancer is often diagnosed at advanced stage, where chemotherapy is the mainstay of treatment. Despite new chemotherapy regimens improving overall survival over the past decade, the median survival for advanced pancreatic cancer remains around one year. However, we occasionally encounter long-term survivors among patients with advanced pancreatic cancer. Analyzing these cases may provide valuable insights for understanding pancreatic cancer and improving treatment strategies. We report a case of 61-year-old patient with metastatic pancreatic cancer who survived for approximately five years. Single-cell transcriptome analysis of tissues obtained at the time of pancreatic cancer diagnosis and at 57 months post-diagnosis revealed changes in the tumor immune microenvironment. [ABSTRACT FROM AUTHOR]

Background: The lack of reliable biomarkers in response to anti-TNFα biologicals hinders personalized therapy for Crohn's disease (CD) patients. The motivation behind our study is to shift the paradigm of anti-TNFα biomarker discovery toward specific immune cell sub-populations using single-cell RNA sequencing and an innovative approach designed to uncover PBMCs gene expression signals, which may be masked due to the treatment or ongoing inflammation; Methods: The single-cell RNA sequencing was performed on PBMC samples from CD patients either naïve to biological therapy, in remission while on adalimumab, or while on ustekinumab but previously non-responsive to adalimumab. Sieves for stringent downstream gene selection consisted of gene ontology and independent cohort genomic profiling. Replication and meta-analyses were performed using publicly available raw RNA sequencing files of sorted immune cells and an association analysis summary. Machine learning, Mendelian randomization, and oligogenic risk score methods were deployed to validate DEGs highly relevant to anti-TNFα therapy response; Results: This study found PLCB1 in CD4+ T cells and CRTAM in double-negative T cells, which met the stringent statistical thresholds throughout the analyses. An additional assessment proved causal inference of both genes in response to anti-TNFα therapy; Conclusions: This study, jointly with an innovative design, uncovered novel candidate genes in the anti-TNFα response landscape of CD, potentially obscured by therapy or inflammation. [ABSTRACT FROM AUTHOR]

Recent advances in multiplexed single-cell transcriptomics experiments facilitate the high-throughput study of drug and genetic perturbations. However, an exhaustive exploration of the combinatorial perturbation space is experimentally unfeasible. Therefore, computational methods are needed to predict, interpret, and prioritize perturbations. Here, we present the compositional perturbation autoencoder (CPA), which combines the interpretability of linear models with the flexibility of deep-learning approaches for single-cell response modeling. CPA learns to in silico predict transcriptional perturbation response at the single-cell level for unseen dosages, cell types, time points, and species. Using newly generated single-cell drug combination data, we validate that CPA can predict unseen drug combinations while outperforming baseline models. Additionally, the architecture's modularity enables incorporating the chemical representation of the drugs, allowing the prediction of cellular response to completely unseen drugs. Furthermore, CPA is also applicable to genetic combinatorial screens. We demonstrate this by imputing in silico 5,329 missing combinations (97.6% of all possibilities) in a single-cell Perturb-seq experiment with diverse genetic interactions. We envision CPA will facilitate efficient experimental design and hypothesis generation by enabling in silico response prediction at the single-cell level and thus accelerate therapeutic applications using single-cell technologies.

Different plant species within the grasses were parallel targets of domestication, giving rise to crops with distinct evolutionary histories and traits1. Key traits that distinguish these species are mediated by specialized cell types2. Here we compare the transcriptomes of root cells in three grass species-Zea mays, Sorghum bicolor and Setaria viridis. We show that single-cell and single-nucleus RNA sequencing provide complementary readouts of cell identity in dicots and monocots, warranting a combined analysis. Cell types were mapped across species to identify robust, orthologous marker genes. The comparative cellular analysis shows that the transcriptomes of some cell types diverged more rapidly than those of others-driven, in part, by recruitment of gene modules from other cell types. The data also show that a recent whole-genome duplication provides a rich source of new, highly localized gene expression domains that favour fast-evolving cell types. Together, the cell-by-cell comparative analysis shows how fine-scale cellular profiling can extract conserved modules from a pan transcriptome and provide insight on the evolution of cells that mediate key functions in crops.

The enteric nervous system (ENS) consists of glial cells (EGCs) and neurons derived from neural crest precursors. EGCs retain capacity for large-scale neurogenesis in culture, and in vivo lineage tracing has identified neurons derived from glial cells in response to inflammation. We thus hypothesize that EGCs possess a chromatin structure poised for neurogenesis. We use single-cell multiome sequencing to simultaneously assess transcription and chromatin accessibility in EGCs undergoing spontaneous neurogenesis in culture, as well as small intestine myenteric plexus EGCs. Cultured EGCs maintain open chromatin at genomic loci accessible in neurons, and neurogenesis from EGCs involves dynamic chromatin rearrangements with a net decrease in accessible chromatin. A subset of in vivo EGCs, highly enriched within the myenteric ganglia and that persist into adulthood, have a gene expression program and chromatin state consistent with neurogenic potential. These results clarify the mechanisms underlying EGC potential for neuronal fate transition.

RNA-sequencing (RNA-seq) is a technique used for providing global patterns of transcriptomes in samples. However, it can only provide the average gene expression across cells and does not address the heterogeneity within the samples. The advances in single-cell RNA sequencing (scRNA-seq) technology have revolutionized our understanding of heterogeneity and the dynamics of gene expression at the single-cell level. For example, scRNA-seq allows us to identify the cell types in complex tissues, which can provide information regarding the alteration of the cell population by perturbations, such as genetic modification. Since its initial introduction, scRNA-seq has rapidly become popular, leading to the development of a huge number of bioinformatic tools. However, the analysis of the big dataset generated from scRNA-seq requires a general understanding of the preprocessing of the dataset and a variety of analytical techniques. Here, we present an overview of the workflow involved in analyzing the scRNA-seq dataset. First, we describe the preprocessing of the dataset, including quality control, normalization, and dimensionality reduction. Then, we introduce the downstream analysis provided with the most commonly used computational packages. This review aims to provide a workflow guideline for new researchers interested in this field.

Multiple sclerosis is a chronic inflammatory disease of the central nervous system1. Astrocytes are heterogeneous glial cells that are resident in the central nervous system and participate in the pathogenesis of multiple sclerosis and its model experimental autoimmune encephalomyelitis2,3. However, few unique surface markers are available for the isolation of astrocyte subsets, preventing their analysis and the identification of candidate therapeutic targets; these limitations are further amplified by the rarity of pathogenic astrocytes. Here, to address these challenges, we developed focused interrogation of cells by nucleic acid detection and sequencing (FIND-seq), a high-throughput microfluidic cytometry method that combines encapsulation of cells in droplets, PCR-based detection of target nucleic acids and droplet sorting to enable in-depth transcriptomic analyses of cells of interest at single-cell resolution. We applied FIND-seq to study the regulation of astrocytes characterized by the splicing-driven activation of the transcription factor XBP1, which promotes disease pathology in multiple sclerosis and experimental autoimmune encephalomyelitis4. Using FIND-seq in combination with conditional-knockout mice, in vivo CRISPR-Cas9-driven genetic perturbation studies and bulk and single-cell RNA sequencing analyses of samples from mouse experimental autoimmune encephalomyelitis and humans with multiple sclerosis, we identified a new role for the nuclear receptor NR3C2 and its corepressor NCOR2 in limiting XBP1-driven pathogenic astrocyte responses. In summary, we used FIND-seq to identify a therapeutically targetable mechanism that limits XBP1-driven pathogenic astrocyte responses. FIND-seq enables the investigation of previously inaccessible cells, including rare cell subsets defined by unique gene expression signatures or other nucleic acid markers.

BACKGROUND: A main obstacle in current valvular heart disease research is the lack of high-quality homogeneous functional heart valve cells. Human induced pluripotent stem cells (hiPSCs)-derived heart valve cells may help with this dilemma. However, there are no well-established protocols to induce hiPSCs to differentiate into functional heart valve cells, and the networks that mediate the differentiation have not been fully elucidated. METHODS: To generate heart valve cells from hiPSCs, we sequentially activated the Wnt, BMP4, VEGF (vascular endothelial growth factor), and NFATc1 signaling pathways using CHIR-99021, BMP4, VEGF-165, and forskolin, respectively. The transcriptional and functional similarity of hiPSC-derived heart valve cells compared with primary heart valve cells were characterized. Longitudinal single-cell RNA sequencing was used to uncover the trajectory, switch genes, pathways, and transcription factors of the differentiation. RESULTS: An efficient protocol was developed to induce hiPSCs to differentiate into functional hiPSC-derived valve endothelial- like cells and hiPSC-derived valve interstitial-like cells. After 6-day differentiation and CD144 magnetic bead sorting, ≈70% CD144+ cells and 30% CD144- cells were obtained. On the basis of single-cell RNA sequencing data, the CD144+ cells and CD144- cells were found to be highly similar to primary heart valve endothelial cells and primary heart valve interstitial cells in gene expression profile. Furthermore, CD144+ cells had the typical function of primary heart valve endothelial cells, including tube formation, uptake of low-density lipoprotein, generation of endothelial nitric oxide synthase, and response to shear stress. Meanwhile, CD144- cells could secret collagen and matrix metalloproteinases, and differentiate into osteogenic or adipogenic lineages like primary heart valve interstitial cells. Therefore, we identified CD144+ cells and CD144- cells as hiPSC-derived valve endothelial-like cells and hiPSC-derived valve interstitial-like cells, respectively. Using single-cell RNA sequencing analysis, we demonstrated that the trajectory of heart valve cell differentiation was consistent with embryonic valve development. We identified the main switch genes (NOTCH1, HEY1, and MEF2C), signaling pathways (TGF-β, Wnt, and NOTCH), and transcription factors (MSX1, SP5, and MECOM) that mediated the differentiation. Finally, we found that hiPSC-derived valve interstitial-like cells might derive from hiPSC-derived valve endothelial-like cells undergoing endocardial-mesenchymal transition. CONCLUSIONS: In summary, this is the first study to report an efficient strategy to generate functional hiPSC-derived valve endothelial-like cells and hiPSC-derived valve interstitial-like cells from hiPSCs, as well as to elucidate the differentiation trajectory and transcriptional dynamics of hiPSCs differentiated into heart valve cells. [ABSTRACT FROM AUTHOR]

Background: Oral submucous fibrosis (OSF) is a precancerous lesion characterized by fibrous tissue deposition, the incidence of which correlates positively with the frequency of betel nut chewing. Prolonged betel nut chewing can damage the integrity of the oral mucosal epithelium, leading to chronic inflammation and local immunological derangement. However, currently, the underlying cellular events driving fibrogenesis and dysfunction are incompletely understood, such that OSF has few treatment options with limited therapeutic effectiveness. Dental pulp stem cells (DPSCs) have been recognized for their anti-inflammatory and anti-fibrosis capabilities, making them promising candidates to treat a range of immune, inflammatory, and fibrotic diseases. However, the application of DPSCs in OSF is inconclusive. Therefore, this study aimed to explore the pathogenic mechanism of OSF and, based on this, to explore new treatment options. Methods: A human cell atlas of oral mucosal tissues was compiled using single-cell RNA sequencing to delve into the underlying mechanisms. Epithelial cells were reclustered to observe the heterogeneity of OSF epithelial cells and their communication with immune cells. The results were validated in vitro, in clinicopathological sections, and in animal models. In vivo, the therapeutic effect and mechanism of DPSCs were characterized by histological staining, immunohistochemical staining, scanning electron microscopy, and atomic force microscopy. Results: A unique epithelial cell population, Epi1.2, with proinflammatory and profibrotic functions, was predominantly found in OSF. Epi1.2 cells also induced the fibrotic process in fibroblasts by interacting with T cells through receptor-ligand crosstalk between macrophage migration inhibitory factor (MIF)-CD74 and C-X-C motif chemokine receptor 4 (CXCR4). Furthermore, we developed OSF animal models and simulated the clinical local injection process in the rat buccal mucosa using DPSCs to assess their therapeutic impact and mechanism. In the OSF rat model, DPSCs demonstrated superior therapeutic effects compared with the positive control (glucocorticoids), including reducing collagen deposition and promoting blood vessel regeneration. DPSCs mediated immune homeostasis primarily by regulating the numbers of KRT19 + MIF + epithelial cells and via epithelial-stromal crosstalk. Conclusions: Given the current ambiguity surrounding the cause of OSF and the limited treatment options available, our study reveals that epithelial cells and their crosstalk with T cells play an important role in the mechanism of OSF and suggests the therapeutic promise of DPSCs. [ABSTRACT FROM AUTHOR]

The choice of developing thymocytes to become CD8+ cytotoxic or CD4+ helper T cells has been intensely studied, but many of the underlying mechanisms remain to be elucidated. Recent multiomics approaches have provided much higher resolution analysis of gene expression in developing thymocytes than was previously achievable, thereby offering a fresh perspective on this question. Focusing on our recent studies using CITE-seq (cellular indexing of transcriptomes and epitopes) analyses of mouse thymocytes, we present a detailed timeline of RNA and protein expression changes during CD8 versus CD4 T cell differentiation. We also revisit our current understanding of the links between T cell receptor signaling and expression of the lineage-defining transcription factors ThPOK and RUNX3. Finally, we propose a sequential selection model to explain the tight linkage between MHC-I versus MHC-II recognition and T cell lineage choice. This model incorporates key aspects of previously proposed kinetic signaling, instructive, and stochastic/selection models. [ABSTRACT FROM AUTHOR]

Background: Renal ischemia-reperfusion injury (RIRI) is an inevitable complication in the process of kidney transplantation and lacks specific therapy. The study aims to determine the underlying mechanisms of RIRI to uncover a promising target for efficient renoprotection. Method: Four bulk RNA-seq datasets including 495 renal samples of pre- and post-reperfusion were collected from the GEO database. The machine learning algorithms were utilized to ascertain pivotal endoplasmic reticulum stress genes. Then, we incorporated correlation analysis and determined the interaction pathways of these key genes. Considering the heterogeneous nature of bulk-RNA analysis, the single-cell RNA-seq analysis was performed to investigate the mechanisms of key genes at the single-cell level. Besides, 4-PBA was applied to inhibit endoplasmic reticulum stress and hence validate the pathological role of these key genes in RIRI. Finally, three clinical datasets with transcriptomic profiles were used to assess the prognostic role of these key genes in renal allograft outcomes after RIRI. Results: In the bulk-RNA analysis, endoplasmic reticulum stress was identified as the top enriched pathway and three endoplasmic reticulum stress-related genes (PPP1R15A, JUN, and ATF3) were ranked as top performers in both LASSO and Boruta analyses. The three genes were found to significantly interact with kidney injury-related pathways, including apoptosis, inflammatory response, oxidative stress, and pyroptosis. For oxidative stress, these genes were more strongly related to oxidative markers compared with antioxidant markers. In single-cell transcriptome, the three genes were primarily upregulated in endothelium, distal convoluted tubule cells, and collecting duct principal cells among 12 cell types of renal tissues in RIRI. Furthermore, distal convoluted tubule cells and collecting duct principal cells exhibited pro-inflammatory status and the highest pyroptosis levels, suggesting their potential as main effectors of three key genes for mediating RIRI-associated injuries. Importantly, inhibition of these key genes using 4-phenyl butyric acid alleviated functional and histological damage in a mouse RIRI model. Finally, the three genes demonstrated highly prognostic value in predicting graft survival outcomes. Conclusion: The study identified three key endoplasmic reticulum stress-related genes and demonstrated their prognostic value for graft survival, providing references for individualized clinical prevention and treatment of postoperative complications after renal transplantation. [ABSTRACT FROM AUTHOR]

Adult muscle stem cells (MuSCs) are known to replicate upon activation before differentiating and fusing to regenerate myofibers. It is unclear whether MuSC differentiation is intrinsically linked to cell division, which has implications for stem cell population maintenance. We use single-cell RNA-sequencing to identify transcriptionally diverse subpopulations of MuSCs after 5 days of a growth stimulus in adult muscle. Trajectory inference in combination with a novel mouse model for tracking MuSC-derived myonuclei and in vivo labeling of DNA replication revealed an MuSC population that exhibited division-independent differentiation and fusion. These findings demonstrate that in response to a growth stimulus in the presence of intact myofibers, MuSC division is not obligatory. [ABSTRACT FROM AUTHOR]

Mature oligodendrocytes form myelin sheaths that are crucial for the insulation of axons and efficient signal transmission in the central nervous system. Recent evidence has challenged the classical view of the functionally static mature oligodendrocyte and revealed a gamut of dynamic functions such as the ability to modulate neuronal circuitry and provide metabolic support to axons. Despite the recognition of potential heterogeneity in mature oligodendrocyte function, a comprehensive summary of mature oligodendrocyte diversity is lacking. We delve into early 20th-century studies by Robertson and Río-Hortega that laid the foundation for the modern identification of regional and morphological heterogeneity in mature oligodendrocytes. Indeed, recent morphologic and functional studies call into question the long-assumed homogeneity of mature oligodendrocyte function through the identification of distinct subtypes with varying myelination preferences. Furthermore, modern molecular investigations, employing techniques such as single cell/nucleus RNA sequencing, consistently unveil at least six mature oligodendrocyte subpopulations in the human central nervous system that are highly transcriptomically diverse and vary with central nervous system region. Age and disease related mature oligodendrocyte variation denotes the impact of pathological conditions such as multiple sclerosis, Alzheimer’s disease, and psychiatric disorders. Nevertheless, caution is warranted when subclassifying mature oligodendrocytes because of the simplification needed to make conclusions about cell identity from temporally confined investigations. Future studies leveraging advanced techniques like spatial transcriptomics and single-cell proteomics promise a more nuanced understanding of mature oligodendrocyte heterogeneity. Such research avenues that precisely evaluate mature oligodendrocyte heterogeneity with care to understand the mitigating influence of species, sex, central nervous system region, age, and disease, hold promise for the development of therapeutic interventions targeting varied central nervous system pathology.

Background: The lack of reliable biomarkers in response to anti-TNFα biologicals hinders personalized therapy for Crohn’s disease (CD) patients. The motivation behind our study is to shift the paradigm of anti-TNFα biomarker discovery toward specific immune cell sub-populations using single-cell RNA sequencing and an innovative approach designed to uncover PBMCs gene expression signals, which may be masked due to the treatment or ongoing inflammation; Methods: The single-cell RNA sequencing was performed on PBMC samples from CD patients either naïve to biological therapy, in remission while on adalimumab, or while on ustekinumab but previously non-responsive to adalimumab. Sieves for stringent downstream gene selection consisted of gene ontology and independent cohort genomic profiling. Replication and meta-analyses were performed using publicly available raw RNA sequencing files of sorted immune cells and an association analysis summary. Machine learning, Mendelian randomization, and oligogenic risk score methods were deployed to validate DEGs highly relevant to anti-TNFα therapy response; Results: This study found PLCB1 in CD4+ T cells and CRTAM in double-negative T cells, which met the stringent statistical thresholds throughout the analyses. An additional assessment proved causal inference of both genes in response to anti-TNFα therapy; Conclusions: This study, jointly with an innovative design, uncovered novel candidate genes in the anti-TNFα response landscape of CD, potentially obscured by therapy or inflammation.

Objective·To identify the gene expression program (GEP) of cancer-testis genes (CTGs) during spermatogenesis based on single-cell transcriptome data from the testis and investigate their association with the prognosis of cancer patients.Methods·Expression profiles of normal and tumor tissues were obtained from the GTEx and TCGA databases to screen CTGs. The GEP of CTGs during spermatogenesis was identified by applying the leiden clustering algorithm to testicular single-cell transcriptome data. DecoupleR was used to evaluate the activity levels of GEP and determine the cell types and stages of spermatogenesis where each GEP was active. Subsequently, DecoupleR was used to evaluate the activity levels of GEP in tumor tissues and analyze the correlation between GEP and cancer patient survival.Results·Based on the expression profiles of normal and tumor tissues from the GTEx and TCGA databases, 917 CTGs were identified. By using the expression patterns of CTGs in the testicular single-cell transcriptome data, seven GEPs were identified through the clustering algorithm. Activity level analysis revealed that GEP5 was active in the early stages of spermatogenesis, including spermatogonia stem cells, differentiating spermatogonia, and early primary spermatocytes. The distribution of GEP5-associated genes was predominantly found on the X chromosome. Additionally, survival analysis demonstrated a statistically significant negative correlation between GEP5 activity levels and patient survival in various tumors.Conclusion·During spermatogenesis, GEP5 is active in early stages, and its associated genes are primarily located on the X chromosome. In multiple tumor types, the activity level of GEP5 is closely related to patient prognosis.

Diabetes is caused by insufficient insulin secretion due to β-cell dysfunction and/or β-cell loss. Therefore, the restoration of functional β-cells by the induction of β-cell differentiation from embryonic stem (ES) and induced-pluripotent stem (iPS) cells, or from somatic non-β-cells, may be a promising curative therapy. To establish an efficient and feasible method for generating functional insulin-producing cells, comprehensive knowledge of pancreas development and β-cell differentiation, including the mechanisms driving cell fate decisions and endocrine cell maturation is crucial. Recent advances in single-cell RNA sequencing (scRNA-seq) technologies have opened a new era in pancreas development and diabetes research, leading to clarification of the detailed transcriptomes of individual insulin-producing cells. Such extensive high-resolution data enables the inference of developmental trajectories during cell transitions and gene regulatory networks. Additionally, advancements in stem cell research have not only enabled their immediate clinical application, but also has made it possible to observe the genetic dynamics of human cell development and maturation in a dish. In this review, we provide an overview of the heterogeneity of islet cells during embryogenesis and differentiation as demonstrated by scRNA-seq studies on the developing and adult pancreata, with implications for the future application of regenerative medicine for diabetes.

Objective·To identify the gene expression program (GEP) of cancer-testis genes (CTGs) during spermatogenesis based on single-cell transcriptome data from the testis and investigate their association with the prognosis of cancer patients. Methods· Expression profiles of normal and tumor tissues were obtained from the GTEx and TCGA databases to screen CTGs. The GEP of CTGs during spermatogenesis was identified by applying the leiden clustering algorithm to testicular single-cell transcriptome data. DecoupleR was used to evaluate the activity levels of GEP and determine the cell types and stages of spermatogenesis where each GEP was active. Subsequently, DecoupleR was used to evaluate the activity levels of GEP in tumor tissues and analyze the correlation between GEP and cancer patient survival. Results·Based on the expression profiles of normal and tumor tissues from the GTEx and TCGA databases, 917 CTGs were identified. By using the expression patterns of CTGs in the testicular single-cell transcriptome data, seven GEPs were identified through the clustering algorithm. Activity level analysis revealed that GEP5 was active in the early stages of spermatogenesis, including spermatogonia stem cells, differentiating spermatogonia, and early primary spermatocytes. The distribution of GEP5-associated genes was predominantly found on the X chromosome. Additionally, survival analysis demonstrated a statistically significant negative correlation between GEP5 activity levels and patient survival in various tumors. Conclusion·During spermatogenesis, GEP5 is active in early stages, and its associated genes are primarily located on the X chromosome. In multiple tumor types, the activity level of GEP5 is closely related to patient prognosis. [ABSTRACT FROM AUTHOR]

Background: Epsin endocytic adaptor proteins are implicated in the progression of atherosclerosis; however, the underlying molecular mechanisms have not yet been fully defined. In this study, we determined how epsins enhance endothelial-to-mesenchymal transition (EndoMT) in atherosclerosis and assessed the efficacy of a therapeutic peptide in a preclinical model of this disease. Methods: Using single-cell RNA sequencing combined with molecular, cellular, and biochemical analyses, we investigated the role of epsins in stimulating EndoMT using knockout in Apoe−/− and lineage tracing/proprotein convertase subtilisin/kexin type 9 serine protease mutant viral-induced atherosclerotic mouse models. The therapeutic efficacy of a synthetic peptide targeting atherosclerotic plaques was then assessed in Apoe−/− mice. Results: Single-cell RNA sequencing and lineage tracing revealed that epsins 1 and 2 promote EndoMT and that the loss of endothelial epsins inhibits EndoMT marker expression and transforming growth factor-β signaling in vitro and in atherosclerotic mice, which is associated with smaller lesions in the Apoe−/− mouse model. Mechanistically, the loss of endothelial cell epsins results in increased fibroblast growth factor receptor-1 expression, which inhibits transforming growth factor-β signaling and EndoMT. Epsins directly bind ubiquitinated fibroblast growth factor receptor-1 through their ubiquitin-interacting motif, which results in endocytosis and degradation of this receptor complex. Consequently, administration of a synthetic ubiquitin-interacting motif–containing peptide atheroma ubiquitin-interacting motif peptide inhibitor significantly attenuates EndoMT and progression of atherosclerosis. Conclusions: We conclude that epsins potentiate EndoMT during atherogenesis by increasing transforming growth factor-β signaling through fibroblast growth factor receptor-1 internalization and degradation. Inhibition of EndoMT by reducing epsin–fibroblast growth factor receptor-1 interaction with a therapeutic peptide may represent a novel treatment strategy for atherosclerosis. [ABSTRACT FROM AUTHOR]

Previous studies have demonstrated the roles of both microglia homeostasis and RNA editing in sepsis-associated encephalopathy (SAE), yet their relationship remains to be elucidated. In this study, we analyzed bulk and single-cell RNA-seq (scRNA) datasets containing 107 brain tissue and microglia samples from mice with microglial depletion and repopulation to explore canonical RNA editing associated with microglia homeostasis and evaluate its role in SAE. Analysis of mouse brain RNA-Seq revealed hallmarks of microglial repopulation, including peak expressions of Apobec1 and Apobec3 at Day 5 of repopulation and dramatically altered B2m RNA editing. Significant time-dependent changes in brain RNA editing during microglial depletion and repopulation were primarily observed in synapse-related genes, such as Tbc1d24 and Slc1a2. ScRNA-Seq revealed heterogeneous RNA editing among microglia subpopulations and their distinct changes associated with microglia homeostasis. Moreover, repopulated microglia from lipopolysaccharide (LPS)-induced sepsis mice exhibited intensified up-regulation of Apobec1 and Apobec3, with distinct RNA editing responses to LPS, mainly involved in immune-related pathways. The hippocampus from sepsis mice induced by peritoneal contamination and infection showed upregulated Apobec1 and Apobec3 expression, and altered RNA editing in immune-related genes, such as B2m and Mier1, and nervous-related lncRNA Meg3 and Snhg11, both of which were repressed by microglial depletion. Furthermore, the expression of complement-related genes, such as C4b and Cd47, was substantially correlated with RNA editing activity in microglia homeostasis and SAE. Our study demonstrates canonical RNA editing associated with microglia homeostasis and provides new insights into its potential role in SAE., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 International Brain Research Organization (IBRO). Published by Elsevier Inc. All rights reserved.)

Neutrophils and eosinophils share common hematopoietic precursors and usually diverge into distinct lineages with unique markers before being released from their hematopoietic site, which is the bone marrow (BM). However, previous studies identified an immature Ly6g(+) Il-5Rα(+) neutrophil population in mouse BM, expressing both neutrophil and eosinophil markers suggesting hematopoietic flexibility. Moreover, others have reported neutrophil populations expressing eosinophil-specific cell surface markers in tissues and altered disease states, confusing the field regarding eosinophil origins, function, and classification. Despite these reports, it is still unclear whether hematopoietic flexibility exists in human granulocytes. To answer this, we utilized single-cell RNA sequencing and cellular indexing of transcriptomes and epitopes by sequencing to profile human BM and circulating neutrophils and eosinophils at different stages of differentiation and determine whether neutrophil plasticity plays role in asthmatic inflammation. We show that immature metamyelocyte neutrophils in humans expand during severe asthmatic inflammation and express both neutrophil and eosinophil markers. We also show an increase in trilobed eosinophils with mixed neutrophil and eosinophil markers in allergic asthma and that interleukin-5 promotes differentiation of immature blood neutrophils into trilobed eosinophilic phenotypes, suggesting a mechanism of emergency granulopoiesis to promote myeloid inflammatory or remodeling response in patients with chronic asthma. By providing insights into unexpectedly flexible granulocyte biology and demonstrating emergency hematopoiesis in asthma, our results highlight the importance of granulocyte plasticity in eosinophil development and allergic diseases., Competing Interests: Conflict of interest statement. None declared., (© The Author(s) 2024. Published by Oxford University Press on behalf of Society for Leukocyte Biology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Advancing in single-cell RNA sequencing techniques enhances the resolution of cell heterogeneity study. Density-based unsupervised clustering has the potential to detect the representative anchor points and the number of clusters automatically. Meanwhile, discovering the true cell type of scRNA-seq data in the unsupervised scenario is still challenging. To this end, we proposed a tensor shared nearest neighbor anchor clustering for scRNA-seq data, named scTSNN, which first makes use of the tensor affinity learning module to mine the local-global balanced topological structures among cells, next designs density-based shared nearest neighbor measurement method to automatically detect anchor cells, finally partitions the non-anchor cells to obtain the clustering results. Validated on synthetic datasets and scRNA-seq datasets, scTSNN not only exactly detects the complicated structures but also has better performance in accuracy and robustness compared with the state-of-the-art methods. Moreover, case studies on mammalian cells and cervical cancer tumor cells demonstrate the selected anchor cells of scTSNN benefit the cell pseudotime inference and rare cell identification, which show good application and research value of scTSNN.

The placenta is essential organ for oxygen and nutrient exchange between the mother and the developing fetus. Trophoblast lineage differentiation is closely related to the normal function of the placenta. Trophoblast stem cells (TSCs) can differentiate into all placental trophoblast subtypes and are widely used as in vitro stem cell models to study placental development and trophoblast lineage differentiation. Although extensive research has been conducted on the differentiation of TSCs, the possible parallels between trophoblast giant cells (TGCs) that are differentiated from TSCs in vitro and the various subtypes of TGC lineages in vivo are still poorly understood. In this study, mouse TSCs (mTSCs) were induced to differentiate into TGCs, and our mRNA sequencing (RNA-seq) data revealed that mTSCs and TGCs have distinct transcriptional signatures. We conducted a comparison of mTSCs and TGCs transcriptomes with the published transcriptomes of TGC lineages in murine placenta detected by single-cell RNA-seq and found that mTSCs tend to differentiate into maternal blood vessel-associated TGCs in vitro. Moreover, we identified the transcription factor (TF) ZMAT1, which may be responsible for the differentiation of mTSCs into sinusoid TGCs, and the TFs EGR1 and MITF, which are likely involved in the differentiation of mTSCs into spiral artery-associated TGCs. Thus, our findings provide a valuable resource for the mechanisms of trophoblast lineage differentiation and placental deficiency-associated diseases development., Competing Interests: Declaration of competing interest The authors declare that they have no conflicts of interest with the contents of this article., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Objectives: The aim of these studies was to characterise the molecular effects of a tool JAK1 inhibitor on cultured primary fibroblast-like synoviocytes (FLS) from patients with rheumatoid arthritis (RA) through both total and individual cell analysis., Methods: RA-FLS cultures from 6 (Bulk RNA-seq) or 4 (ScRNA-seq) donors were pre-treated with various concentrations (100 nM and 1μM) of ABT-317 with/without exposure to 25% SEB-conditioned PBMC medium to mimic the RA inflammatory milieu. Cells were subjected to both bulk RNA-seq (36 libraries) and single cell RNA-seq (scRNA-seq; 24 libraries) to identify biological processes impacted by CM and ABT-317 treatments., Results: In our bulk RNA-seq analysis, a total of 2,605 differentially expressed genes (DEGs) were identified between CM-stimulation and unstimulated groups, while 1,122 DEGs were found between ABT-317 1μM and DMSO in CM-stimulated groups using thresholds of log2 (fold change) ≥ |0.58| and FDR ≤ 10%. Both bulk and single cell mRNA analysis of RA-FLS treated with a combination of CM and ABT-317 demonstrated the expected changes in inflammatory pathways such as interferon and IL-6 signalling. However, other non-inflammation associated pathways were also altered by ABT-317. In addition, the single cell analysis highlighted that FLS segregate into distinctive clusters upon combination CM and ABT-317 treatment, suggesting JAK inhibition can drive RA-FLS into multiple heterogenous cell populations. Interestingly, one of the unique RA-FLS clusters that emerged from the CM and ABT-317 treatment showed matrix metalloproteinase-3 (MMP3)high expression as well as several gene signatures that are not found in any other ABT-317 derived clusters., Conclusions: JAK inhibition with ABT-317 is effective at globally inhibiting CM-induced pro- and non-inflammatory pathways in FLS cultures, but also results in several distinct fibroblast populations with unique gene-associated pathways. This study advances the molecular understanding of JAK1 inhibitor effects on fibroblasts that may contribute to clinical efficacy.

Uncovering mechanisms of endogenous regeneration and repair through resident stem cell activation will allow us to develop specific therapies for injuries and diseases by targeting resident stem cell lineages. Sox9 + stem cells have been reported to play an essential role in acute kidney injury (AKI). However, a complete view of the Sox9 + lineage was not well investigated to accurately elucidate the functional end state and the choice of cell fate during tissue repair after AKI. To identify the mechanisms of fate determination of Sox9 + stem cells, we set up an AKI model with prostaglandin E2 (PGE 2 ) treatment in a Sox9 lineage tracing mouse model. Single-cell RNA sequencing (scRNA-seq) was performed to analyse the transcriptomic profile of the Sox9 + lineage. Our results revealed that PGE 2 could activate renal Sox9 + cells and promote the differentiation of Sox9 + cells into renal proximal tubular epithelial cells and inhibit the development of fibrosis. Furthermore, single-cell transcriptome analysis demonstrated that PGE 2 could regulate the restoration of lipid metabolism homeostasis in proximal tubular epithelial cells by participating in communication with different cell types. Our results highlight the prospects for the activation of endogenous renal Sox9 + stem cells with PGE 2 for the regenerative therapy of AKI., (© 2024 The Author(s). Cell Proliferation published by Beijing Institute for Stem Cell and Regenerative Medicine and John Wiley & Sons Ltd.)

The pathogenesis of sepsis, with a high mortality rate and often poor prognosis, has not been fully elucidated. Therefore, an in-depth study on the pathogenesis of sepsis at the molecular level is essential to identify key sepsis-related genes. The aim of this study was to explore the key genes and potential molecular mechanisms of sepsis using a bioinformatics approach. In addition, key genes with miRNA network correlation analysis and immune infiltration correlation analysis were investigated. The scRNA dataset (GSE167363) and RNA-seq dataset (GSE65682, GSE134347) from GEO database were used for screening out differentially expressed genes using single-cell sequencing and transcriptome sequencing. The analysis of immune infiltration was evaluated by the CIBERSORT method. Key genes and possible mechanisms were identified by WGCNA analysis, GSVA analysis, GSEA enrichment analysis and regulatory network analysis, and miRNA networks associated with key genes were constructed. Nine key genes associated with the development of sepsis, namely IL7R, CD3D, IL32, GPR183, HLA-DPB1, CD81, PEBP1, NCL, and ETS1 were screened, and the specific signaling mechanisms associated with the key genes causing sepsis were predicted. Immune profiling showed immune heterogeneity between control and sepsis samples. A regulatory network of 82 miRNAs, 266 pairs of mRNA-miRNA relationship pairs was also constructed. These nine key genes have the potential to become biomarkers for the diagnosis of sepsis and provide new targets and research directions for the treatment of sepsis.

The quality of Recombination signal sequences (RSSs), location, and genetics of mammalian V, D, and J genes synergistically affect the recombination frequency of genes; however, the specific regulatory mechanism and efficiency have not been elucidated. By taking advantage of single-cell RNA-sequencing (scRNA-seq) and high-throughput sequencing (HTS) to investigate V(D)J rearrangement characteristics in the CDR3 repertoire, we found that the distal and proximal V genes (or J genes) "to D" gene were involved in rearrangement significantly more frequently than the middle V genes (or J genes) in the TRB locus among various species, including Primates (human and rhesus monkey), Rodentia (BALB/c, C57BL/6, and Kunming mice), Artiodactyla (buffalo), and Chiroptera (Rhinolophus affinis). The RSS quality of the V and J genes affected their frequency in rearrangement to varying degrees, especially when the V-RSSs with recombination signal information content (RIC) score < -45 significantly reduced the recombination frequency of the V gene. The V and J genes that were "away from D" had the dual advantages of recombinant structural accessibility and relatively high-quality RSSs, which promoted their preferential utilization in rearrangement. The quality of J-RSSs formed during mammalian evolution was apparently greater than that of V-RSSs, and the D-J distance was obviously shorter than that of V-D, which may be one of the reasons for guaranteeing that the "D-to-J preceding V-to-DJ rule" occurred when rearranged. This study provides a novel perspective on the mechanism and efficiency of V-D-J rearrangement in the mammalian TRB locus, as well as the biased utilization characteristics and application of V and J genes in the initial CDR3 repertoire., (© 2024. The Author(s).)

Single-cell RNA sequencing (scRNA-seq) data analysis faces numerous challenges, including high sparsity, a high-dimensional feature space, and biological noise. These challenges hinder downstream analysis, necessitating the use of feature selection methods to identify informative genes, and reduce data dimensionality. However, existing methods for selecting highly variable genes (HVGs) exhibit limited overlap and inconsistent clustering performance across benchmark datasets. Moreover, these methods often struggle to accurately select HVGs from fine-resolution scRNA-seq datasets and minority cell types, which are more difficult to distinguish, raising concerns about the reliability of their results. To overcome these limitations, we propose a novel feature selection framework for scRNA-seq data called Mcadet. Mcadet integrates Multiple Correspondence Analysis (MCA), graph-based community detection, and a novel statistical testing approach. To assess the effectiveness of Mcadet, we conducted extensive evaluations using both simulated and real-world data, employing unbiased metrics for comparison. Our results demonstrate the superior performance of Mcadet in the selection of HVGs in scenarios involving fine-resolution scRNA-seq datasets and datasets containing minority cell populations. Overall, we demonstrate that Mcadet enhances the reliability of selected HVGs, although the impact of HVG selection on various downstream analyses varies and needs to be further investigated., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: SN is an employee and shareholder of F. Hoffmann-La Roche Ltd., (Copyright: © 2024 Cui et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: The pancreatic vasculature displays tissue-specific physiological and functional adaptations that support rapid insulin response by β-cells. However, the digestive enzymes have made it difficult to characterize pancreatic endothelial cells (ECs), resulting in the poor understanding of pancreatic EC specialization., Methods: Available single-nuclei/single-cell RNA-sequencing data sets were mined to identify pancreatic EC-enriched signature genes and to develop an integrated atlas of human pancreatic ECs. We validated the findings using independent single-nuclei/single-cell RNA-sequencing data, bulk RNA-sequencing data of isolated ECs, spatial transcriptomics data, immunofluorescence, and RNAScope of selected markers. The TF (transcription factor) NKX2-3 was expressed in HUVECs via gene transfection, and the expression of pancreatic EC-enriched signature genes was assessed via RT-qPCR., Results: We defined a pancreatic EC-enriched gene signature conserved across species and developmental stages that included genes involved in ECM (extracellular matrix) composition ( COL15A1 and COL4A1 ), permeability and barrier function ( PLVAP , EHD4 , CAVIN3 , HSPG2 , ROBO4 , HEG1 , and CLEC14A ), and key signaling pathways (S1P, TGF-β [transforming growth factor-β], RHO-RAC GTPase, PI3k-AKT, and PDGF [platelet-derived growth factor]). The integrated atlas revealed the vascular hierarchy within the pancreas. We identified and validated a specialized islet capillary subpopulation characterized by genes involved in permeability ( PLVAP and EHD4 ), immune-modulation ( FABP5 , HLA-C , and B2M ), ECM composition ( SPARC and SPARCL1 ), IGF (insulin-like growth factor) signaling ( IGFBP7 ), and membrane transport ( SLCO2A1 , SLC2A3 , and CD320 ). Importantly, we identified NKX2-3 as a key TF enriched in pancreatic ECs. DNA-binding motif analysis found NKX2-3 motifs in ≈40% of the signature genes. Induction of NKX2-3 in HUVECs promoted the expression of the islet capillary EC-enriched genes PLVAP and SPARCL1 ., Conclusions: We defined a validated transcriptomic signature of pancreatic ECs and uncovered their intratissue transcriptomic heterogeneity. We showed that NKX2-3 acts upstream of PLVAP and provided a single-cell online resource that can be further explored by the community: https://vasconcelos.shinyapps.io/pancreatic&#95;endothelial/.

Background: Childhood acute lymphoblastic leukemia (ALL) is a common pediatric cancer. The heterogeneous characterization of B cells in ALL progression poses new challenges to researchers. We used single-cell sequencing to explore the critical role of B cells in regulating the ALL immune microenvironment., Method: We collected the single cell (sc) RNA-seq data of ALL and health sample from the gene expression omnibus (GEO) database, the "Seurat" and "harmony" R package was used for quality control and scRNA-seq analysis, in which the CellMarker2.0 database was used for cell type annotation. Subsequently, the FindAllMarkers function was used to identify the differentially expressed genes (DEGs) among various cell types and the DAVID database was applied for the biological process of DEGs. Then, the "inferCNV" package was used for copy number variation, regulons and cell communication were performed by SCENIC tool and CellChat package. The role of the target gene in regulating ALL progression was assessed using RT-qPCR, Transwell and scratch healing assays., Results: We identified nine mainly cell clusters after scRNA-seq analysis, in which the B cells had higher infiltration proportion in the ALL samples and were sub-clustered into five cell sub-groups. The B cells 1 is closely associated with cell proliferation and stemness (TNFAIP3 and KDM5B), and the significant CNV of amplification occurred on chr6 and chr21 that supported stemness of B cells1. RXRB is a key transcription factor mediated the proliferation of B cells 1, which in turn suppressed hematopoietic stem cells (HSCs) proliferation and promoted cytotoxic NK/T cells activation through diverse cell communication ways. One of the key regulators of B cells is MYC, which promotes the migration and invasive ability of cell line leukemia cell lines., Conclusion: This study reveals the stemness characteristics of B cells and their critical role in ALL progression, a finding that provides new potential directions for the development of targeted therapies against ALL., Competing Interests: The authors declare that they have no competing interests., (© 2024 Wang et al.)

Identification and isolation of antigen-specific T cells for downstream transcriptomic analysis is key for various immunological studies. Traditional methods using major histocompatibility complex (MHC) multimers are limited by the number of predefined immunodominant epitopes and MHC matching of the study subjects. Activation-induced markers (AIM) enable highly sensitive detection of rare antigen-specific T cells irrespective of the availability of MHC multimers. Herein, we have developed an AIM assay for the detection, sorting and subsequent single-cell RNA sequencing (scRNA-seq) analysis of hepatitis C virus (HCV)-specific T cells. We examined different combinations of the activation markers CD69, CD40L, OX40, and 4-1BB at 6, 9, 18 and 24 h post stimulation with HCV peptide pools. AIM + CD4 T cells exhibited upregulation of CD69 and CD40L as early as 6 h post-stimulation, while OX40 and 4-1BB expression was delayed until 18 h. AIM + CD8 T cells were characterized by the coexpression of CD69 and 4-1BB at 18 h, while the expression of CD40L and OX40 remained low throughout the stimulation period. AIM + CD4 and CD8 T cells were successfully sorted and processed for scRNA-seq analysis examining gene expression and T cell receptor (TCR) usage. scRNA-seq analysis from this one subject revealed that AIM + CD4 T (CD69 + CD40L + ) cells predominantly represented Tfh, Th1, and Th17 profiles, whereas AIM + CD8 T (CD69 + 4-1BB + ) cells primarily exhibited effector and effector memory profiles. TCR analysis identified 1023 and 160 unique clonotypes within AIM + CD4 and CD8 T cells, respectively. In conclusion, this approach offers highly sensitive detection of HCV-specific T cells that can be applied for cohort studies, thus facilitating the identification of specific gene signatures associated with infection outcome and vaccination.

The tumor microenvironment (TME) is emerging as a tool for the development of improved patient prognosis and the development of novel antitumor drugs. As the most important stromal cells in the tumor microenvironment, cancer-associated fibroblasts (CAFs) play an important role in the development of TNBC. The rise of single-cell sequencing technology has facilitated our study of the various cell types in TME. In this study, we interpreted the heterogeneity of TNBCs from the perspective of tumor-associated fibroblasts in the tumor microenvironment based on the TNBC single-cell sequencing dataset GSE118389, in the hope of providing help for individualised treatment. Combining the TCGA database and the GSE103091 dataset, four genes associated with CAFs in TNBC (CERCAM, KLF10, ECM1,HGF) were identified using the R package Seurat as well as correlation consensus clustering analysis. Meanwhile, qRT-PCR, WB and IHC experiments confirmed their expression in TNBC. Based on these genes, CAFs Score was established and validated to correlate with the prognosis of patients with TNBC, with patients in the high score group surviving significantly worse than those in the low score group (P<0.001). In addition, there were significant differences in immune cell infiltration and expression of immune checkpoints between the high and low scoring groups. Compared to Stage I & II, the CAFs Score was higher in Stage III & IV TNBC patients (P = 0.043) and higher in N1-3 TNBC patients than in N0 TNBC patients (P = 0.035). EMT scores were higher within the high CAFs Score group (P = 1.4e-11) and there was a positive correlation between Stemness Score and CAFs Score (R = 0.61, P = 3.6e-09). Drug sensitivity analysis combining the GSE128099 showed a higher sensitivity to Gemcitabine in the low CAFs Score group (P = 0.0048). We speculate that these four CAFs-related genes are likely to be involved in regulating gemcitabine resistance in TNBC patients., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Yu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Myelodysplastic syndromes (MDS) are heterogeneous and clonal hematological disorders. The role and mechanism of necroptosis in MDS remain poorly understood., Methods: mRNA expression profiles and single-cell RNA-sequencing (scRNA-seq) data were sourced from the GEO database. ScRNA-seq data were processed using the "Seurat" package. After cell annotation, necroptosis-related scores (NRscores) for each cell were calculated using the "UCell" package. Differentially expressed genes (DEGs) and their associated biological functions in NRscore-related cell populations were identified. Additionally, DEGs and necroptosis-related genes (DE-NRGs) between MDS patients and healthy controls were identified. Consensus clustering was employed to classify MDS patients into distinct subclusters based on DE-NRGs. The biological functions and immune characteristics of these classifications were analyzed. Prognostic gene signatures were determined using LASSO and SVM-RFE analyses, and a nomogram was constructed based on the prognostic gene signature., Results: A total of 12 cell types were identified in MDS and healthy controls. NRscore was found to be elevated in monocytes and common lymphoid precursors (CLPs). Enrichment analysis revealed that monocytes and CLPs with high NRscore were associated with mitochondria-related and immune-related pathways. Eleven DEGs in monocytes and CLPs between MDS patients and healthy controls were identified. Additionally, 13 DE-NRGs were identified from 951 DEGs between MDS and healthy controls. MDS patients were classified into two distinct subclusters based on these 13 DE-NRGs, revealing several immune-related processes and signaling pathways. Differences in immune subpopulations between the two subclusters were observed. A necroptosis-related diagnostic gene signature (IRF9, PLA2G4A, MLKL, BAX, JAK2, and STAT3) was identified as predictive of MDS prevalence., Conclusion: Necroptosis plays a role in MDS progression by inducing inflammation. A novel necroptotic gene signature has been developed to distinguish and diagnose MDS at early stages of the disease., (© 2024. The Author(s).)

Tumor-infiltrating B cells play a significant role in tumor development, progression, and prognosis, yet a comprehensive classification system is lacking. To address this gap, we present a pan-cancer single-cell RNA sequencing (scRNA-seq) atlas of tumor-infiltrating B and plasma cells across a large sample cohort. We identify key B cell subset signatures, revealing distinct subpopulations and highlighting the heterogeneity and functional diversity of these cells in the tumor microenvironment. We explore associations between B cell subsets and checkpoint inhibitor therapy responses, finding subset-specific effects on overall response. Additionally, we examine B and T cell crosstalk, identifying unique ligand-receptor pairs for specific B cell subsets, spatially validated. This comprehensive dataset serves as a valuable resource, providing a detailed atlas that enhances the understanding of B cell complexity in tumors and opens new avenues for research and therapeutic strategies., Competing Interests: Declaration of interests K.L. has the following disclosures (unrelated to this work): patent on indel burden and CPI response pending, patent on ctDNA minimal residual disease calling methods; speaker fees from Roche Tissue Diagnostics and Ellipses Pharma; research funding from CRUK TDL/Ono/LifeArc alliance and Genesis Therapeutics; and consulting roles with Monopteros Therapeutics, Kynos Therapeutics, SAGA Diagnostics, and Tempus Labs, Inc. Also unrelated to this work, K.L. is currently employed by Isomorphic Labs. J.L.R. has the following disclosures (unrelated to this work): patents filed for cancer early detection and consulting role for Achilles Therapeutics plc., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)