Single-cell Transcriptomics Research Articles

Machine learning and single-cell RNA sequencing reveal relationship between intratumor CD8+ T cells and uveal melanoma metastasis

PurposeUveal melanoma (UM) is adults’ most common primary intraocular malignant tumor. It has been observed that 40% of patients experience distant metastasis during subsequent treatment. While there exist multigene models developed using machine learning methods to assess metastasis and prognosis, the immune microenvironment’s specific mechanisms influencing the tumor microenvironment have not been clarified. Single-cell transcriptome sequencing can accurately identify different types of cells in a tissue for precise analysis. This study aims to develop a model with fewer genes to evaluate metastasis risk in UM patients and provide a theoretical basis for UM immunotherapy.MethodsRNA-seq data and clinical information from 79 μm patients from TCGA were used to construct prognostic models. Mechanisms were probed using two single-cell datasets derived from the GEO database. After screening for metastasis-related genes, enrichment analysis was performed using GO and KEGG. Prognostic genes were screened using log-rank test and one-way Cox regression, and prognostic models were established using LASSO regression analysis and multifactor Cox regression analysis. The TCGA-UVM dataset was used as internal validation and dataset GSE22138 as external validation data. A time-dependent subject work characteristic curve (time-ROC) was established to assess the predictive ability of the model. Subsequently, dimensionality reduction, clustering, pseudo-temporal analysis and cellular communication analysis were performed on GSE138665 and GSE139829 to explore the underlying mechanisms involved. Cellular experiments were also used to validate the relevant findings.ResultsBased on clinical characteristics and RNA-seq transcriptomic data from 79 samples in the TCGA-UVM cohort, 247 metastasis-related genes were identified. Survival models for three genes (SLC25A38, EDNRB, and LURAP1) were then constructed using lasso regression and multifactorial cox regression. Kaplan-Meier survival analysis showed that the high-risk group was associated with poorer overall survival (OS) and metastasis-free survival (MFS) in UM patients. Time-dependent ROC curves demonstrated high predictive performance in 6 m, 18 m, and 30 m prognostic models. Cell scratch assay showed that the 24 h and 48 h migration rates of cells with reduced expression of the three genes were significantly higher than those of the si-NC group. CD8 + T cells may play an important role in tumour metastasis as revealed by immune infiltration analysis. An increase in the percentage of cytotoxic CD8 + T cells in the metastatic high-risk group was found in the exploration of single-cell transcriptome data. The communication intensity of cytotoxic CD8 was significantly enhanced. It was also found that the CD8 + T cells in the two groups were in different states, although the number of CD8 + T cells in the high-risk group increased, they were mostly in the exhausted and undifferentiated state, while in the low-risk group, the CD8 + T cells were mostly in the functional state.ConclusionsWe developed a precise and stable 3-gene model to predict the metastatic risk and prognosis of patients. CD8 + T cells exhaustion in the tumor microenvironment play a crucial role in UM metastasis.

Single-cell transcriptomics of rectal organoids from individuals with perianal fistulizing Crohn’s disease reveals patient-specific signatures

Perianal fistulizing Crohn’s disease (CD) is a severe gastrointestinal disorder causing extensive mucosal damage with limited treatment options. Severe manifestations of the disease appear at higher rates in non-Europeans but the genetic and cellular mechanisms driving the disease phenotypes remain poorly understood. Herein, we tested whether pathologic determinants in the epithelial stem cell compartment could be detected at the transcript level in rectal organoids derived from a diverse patient population. Rectal organoid and mucosal cells from endoscopic biopsies of each patient having perianal fistulizing CD or no disease controls were prepared for and sequenced at the single cell level. After cell type annotations based on expressed marker genes, samples were analyzed by principal components, for differential transcript expression, cell type proportions, and pathway enrichment. After QC, we produced 77,044 rectal organoid cells (n = 13 patients; 8 CD, 5 controls) with high quality sequences that identified 10 distinct epithelial subtypes, that we compared to 141,367 mucosal epithelial cells (n = 29 patients; 18 CD, 11 controls). Consistent with mucosal epithelial cells, rectal organoids prominently displayed disease signatures represented by the stem and transit amplifying regions of the rectal crypt, including alterations in transcriptional signatures of metabolic, epigenetic, and proliferating pathways. Organoids also retained their gender- and ancestral-specific gene expression signatures. However, they lacked many of the inflammatory signatures observed in epithelial cells from diseased mucosa. Perianal CD patient derived rectal organoids reflect gene expression signatures related to disease, gender, and ancestry, suggesting they harbor inherent properties amenable to further patient-specific, disease-related experimentation.

LnCeCell 2.0: an updated resource for lncRNA-associated ceRNA networks and web tools based on single-cell and spatial transcriptomics sequencing data.

We describe LnCeCell 2.0 (http://bio-bigdata.hrbmu.edu.cn/LnCeCell), an updated resource for lncRNA-associated competing endogenous RNA (ceRNA) networks and web tools based on single-cell and spatial transcriptomics sequencing(stRNA-seq)data. We have updated the LnCeCell 2.0 database with significantly expanded data and improved features, including(i) 257 single-cell RNA sequencingandstRNA-seqdatasets across 86 diseases/phenotypes and 80 human normal tissues, (ii) 836581 cell-specific and spatial spot-specific ceRNA interactions and functional networks for 1002988 cells and 367971 spatial spots, (iii) 15489 experimentally supported lncRNA biomarkers related to disease pathology, diagnosis and treatment, (iv) detailed annotation of cell type, cell state, subcellular and extracellular locations of ceRNAs through manual curationand (v) ceRNA expression profiles and follow-up clinical information of 20326 cancer patients. Further, a panel of 24 flexible tools (including 8 comprehensive and 16 mini-analysis tools) was developed to investigate ceRNA-regulated mechanisms at single-cell/spot resolution. The CeCellTraject tool, for example, illustrates the detailed ceRNA distribution of different cell populations and explores the dynamic change of the ceRNA network along the developmental trajectory. LnCeCell 2.0 will facilitate the study of fine-tuned lncRNA-ceRNA networks with single-cell and spatial spot resolution, helping us to understand the regulatory mechanisms behind complex microbial ecosystems.

Single-cell RNA transcriptomics in mice reveals embryonic origin of fibrosis due to maternal obesity

Over 40% of pregnant women in the USA are obese which negatively affects fetal development and offspring health. Maternal obesity (MO) leads to fibrotic infiltration in multiple tissues and organs of offspring during their adulthood although the origin and mechanisms are unclear. C57BL/6J female mice were fed a control and high-fat diet to mimic MO condition. Embryonic somatic tissues were obtained at E9.5, E11.5, and E13.5 (equivalent to 6 weeks of human pregnancy) from control (CON) and MO mice for single-cell RNA-sequencing (scRNA-seq). To explore the role of AMP-activated protein kinase (AMPK), AMPK was activated by metformin and A769662, and knocked out in embryonic mesenchymal cells (EMC) using AMPKα1 floxed mice. Using unsupervised clustering, we identified three major cell populations with fibrogenic capacity. Compared to CON, the population of fibrogenic cells increased dramatically (by ∼125%) due to MO, supporting an embryonic origin of fibrosis in the offspring. MO induced inflammatory response and elevated expression of transforming growth factor β (TGFβ) signalling and fibrogenic genes in embryos. MO inhibited AMPK and its activation by metformin and A769662 inhibited TGFβ signalling and fibrogenesis. MO profoundly enhances embryonic fibrogenesis, explaining the origin of fibrosis in the offspring of mothers living with obesity. Our data underscore the importance of early intervention, before 5-6 weeks of pregnancy, in improving embryonic development, and AMPK is an amiable target for suppressing excessive fibrogenesis in MO embryos to assist increasing populations of obese mothers having healthy children. This work was funded by National Institutes of Health Grant R01HD067449.

Prediction of cardiovascular outcomes by subtle changes in the peripheral immune cell landscape - insights from the LURIC single cell RNA-sequencing study (LuRNA)

Abstract Background and Aims Atherosclerosis and its clinical sequelae, myocardial infarction and stroke, represent the main causes of death worldwide. Although preclinical evidence has suggested the existence of an inflammatory response driving disease, the extend of cellular alterations in human atherosclerosis remains enigmatic. Here, we employ single cell RNA-sequencing (scRNA-seq) on peripheral blood mononucleated cells (PBMCs) in a well-defined cardiovascular risk cohort from the "Ludwigshafen Risk and Cardiovascular Health (LURIC) trial" to define changes in the immune cell landscape in atherosclerotic patients. Methods and Results Of 3317 patients enrolled in the LURIC trial between 1997 and 2000, we selected individuals with stable coronary-artery disease (CAD) (n=31) and healthy patients (no CAD) (n=16) by propensity score matching, adjusted for CRP, NTproBNP, Troponin T, LDL-C, and Cystatin-C, in a case-control design. scRNA-seq was performed by droplet sequencing on PBMCs stored in liquid nitrogen. Individual data sets were integrated and changes between healthy individuals and patients with CAD were evaluated on numeric and transcriptional level. Single cell transcriptomes were annotated using an established CITE-seq reference atlas. While bulk RNA-sequencing of PBMC preparations revealed only minor changes between both conditions, we identified several leukocyte populations on a single cell level with specific transcriptomes that were differentially regulated between both conditions. Interestingly, we found that several subsets of Natural Killer (NK) cells, T cells with an enrichment of proliferation-associated pathways, and a population resembling hematopoietic stem cells were more frequent in patients with CAD, while naïve phenotypes of B and T cells were overrepresented in the absence of CAD. Consistently, most T and B cell populations in patients with CAD were enriched in pathways associated with cell activation, immune receptor signalling, and differentiation. In addition, we detected restricted repertoires of T cell receptor sequences in several adaptive immune cell subtypes from patients with CAD, suggestive of increased cellular clonality and antigen-specificity. Finally, in a comparison of cellular frequencies with cardiovascular outcomes over more than 15 years, several immune cell subsets and cell-type specific transcriptional programs predicted cardiovascular death in this case-control scenario in multi-variate adjusted regression analysis. Notably, addition of scRNA-seq derived parameters was superior to traditional risk prediction with clinical characteristics and soluble biomarkers alone. Conclusion Employing scRNAseq, we demonstrate that atherosclerosis is associated with a profound change in the circulating immune cell landscape even in the absence of measurable differences in inflammatory biomarkers. These findings propose the usage of scRNAseq for the discovery of outcome-relevant cellular biomarkers in the future.

Deciphering STAT3’s negative regulation of LHPP in ESCC progression through single-cell transcriptomics analysis

BackgroundEsophageal Squamous Cell Carcinoma (ESCC) remains a predominant health concern in the world, characterized by high prevalence and mortality rates. Advances in single-cell transcriptomics have revolutionized cancer research by enabling a precise dissection of cellular and molecular diversity within tumors.ObjectiveThis study aims to elucidate the cellular dynamics and molecular mechanisms in ESCC, focusing on the transcriptional influence of STAT3 (Signal Transducer and Activator of Transcription 3) and its interaction with LHPP, thereby uncovering potential therapeutic targets.MethodsSingle-cell RNA sequencing was employed to analyze 44,206 cells from tumor and adjacent normal tissues of ESCC patients, identifying distinct cell types and their transcriptional shifts. We conducted differential gene expression analysis to assess changes within the tumor microenvironment (TME). Validation of key regulatory interactions was performed using qPCR in a cohort of 21 ESCC patients and further substantiated through experimental assays in ESCC cell lines.ResultsThe study revealed critical alterations in cell composition and gene expression across identified cell populations, with a notable shift towards pro-tumorigenic states. A significant regulatory influence of STAT3 on LHPP was discovered, establishing a novel aspect of ESCC pathogenesis. Elevated levels of STAT3 and suppressed LHPP expression were validated in clinical samples. Functional assays confirmed that STAT3 directly represses LHPP at the promoter level, and disruption of this interaction by promoter mutations diminished STAT3's repressive effect.ConclusionThis investigation underscores the central role of STAT3 as a regulator in ESCC, directly impacting LHPP expression and suggesting a regulatory loop crucial for tumor behavior. The insights gained from our comprehensive cellular and molecular analysis offer a deeper understanding of the dynamics within the ESCC microenvironment. These findings pave the way for targeted therapeutic interventions focusing on the STAT3-LHPP axis, providing a strategic approach to improve ESCC management and prognosis.

Lipoprotein(a) induces spontaneous aortic dissection via increasing monocyte mediated vascular smooth muscle cell phenotype transformation in human Lp(a) transgenic mice

Abstract Background Elevated lipoprotein(a) [Lp(a)] is a prevalent, independent risk factor of atherosclerotic cardiovascular disease and aortic valve stenosis. Recent studies have reported that high levels of Lp(a) are strongly associated with aortic dissection (AD), independent of other cardiovascular risk factors. However, orthologues of Lp(a) are only found in humans, Old World monkeys, apes, and hedgehogs. The lack of a proper animal model has hindered elucidation of the true pathophysiological mechanisms of Lp(a). Here, we conducted the first humanized Lp(a) transgenic mice experiment to verify the pathological mechanism of Lp(a) in aortic dissection. Methods We conducted ApoE knock out and human ApoA transgenic mice via CRISPR-Cas9 and then crossed with human ApoB transgenic mice to achieve high levels of human-like Lp(a) particles in plasma. Plasma was assayed by ELISA for the concentrations of each lipoprotein. Echocardiography was performed to detect aortic morphology in vivo. Single cell transcriptome analysis was performed on the dissection lesion. Cell interaction was examined in macrophage from Lp(a) transgenic mice and vascular smooth muscle cell (VSMC) coculture system. Result Our results indicate that the concentration of ApoA and ApoB in plasma were increased in transgenic mice fed a chow diet. Low density lipoprotein (LDL) levels were increased and shows that LDL is the major cholesterol carrier in these mice. We were surprised to find that the dissection of the ascending aortic arch could be seen by echocardiography in transgenic mice as early as 2 months, and transgenic mice showed significant increase in aortic enlargement, dissection, and rupture in both the thoracic and abdominal aortic regions, resulting in a survival rate of only 58% after 12 months. Single cell transcriptome analysis revealed that Lp(a) transgene induced the inflammatory response, dedifferentiation and pathological VSMC phenotypical switch, and matrix metalloproteinase expression in macrophages. Monocytes isolated from transgenic mice with elevated Lp(a) remain in a long-lasting primed state, as evidenced by an increased capacity to transmigrate and produce proinflammatory cytokines on stimulation. Monocytes isolated from wild type mice cultured in media with high level Lp(a) for 24h also showed the ability to facilitated cocultured VSMC phenotype transformation, which was reversed by E06, a monoclonal antibody blocking the oxidized phospholipids in Lp(a). Conclusion These findings demonstrate that Lp(a) induces spontaneous aortic dissection via increasing monocyte trafficking to the arterial wall, mediating proinflammatory responses and VSMC phenotype transformation through its OxPL content. The study presents a rodent model of spontaneous aortic dissection and provide a novel mechanism by which Lp(a) mediates aortic dissection.Graphical abstract

GEEES: Inferring Cell-specific Gene-Enhancer Interactions from Multi-modal Single Cell Data.

Gene-enhancer interactions are central to transcriptional regulation. Current multi-modal single cell datasets that profile transcriptome and chromatin accessibility simultaneously in a single cell are yielding opportunities to infer gene-enhancer associations in a cell type specific manner. Computational efforts for such multi-modal single cell datasets thus far focused on methods for identification and refinement of cell types and trajectory construction. While initial attempts for inferring gene-enhancer interactions have emerged, these have not been evaluated against benchmark datasets that materialized from bulk genomic experiments. Furthermore, existing approaches are limited to inferring gene-enhancer associations at the level of grouped cells as opposed to individual cells, thereby ignoring regulatory heterogeneity among the cells. We present a new approach, GEEES for "Gene EnhancEr IntEractions from Multi-modal Single Cell Data", for inferring gene-enhancer associations at the single cell level using multi-modal single cell transcriptome and chromatin accessibility data. We evaluated GEEES alongside several multivariate regression-based alternatives we devised and state-of-the-art methods using a large number of benchmark datasets, providing a comprehensive assessment of current approaches. This analysis revealed significant discrepancies between gold-standard interactions and gene-enhancer associations derived from multi-modal single-cell data. Notably, incorporating gene-enhancer distance into the analysis markedly improved performance across all methods, positioning GEEES as a leading approach in this domain. While the overall improvement in performance metrics by GEEES is modest, it provides enhanced cell representation learning which can be leveraged for more effective downstream analysis. Furthermore, our review of existing experimentally driven benchmark datasets uncovers their limited concordance, underscoring the necessity for new high-throughput experiments to validate gene-enhancer interactions inferred from single-cell data. https://github.com/keleslab/GEEES. Supplementary data are available at Bioinformatics online.

Integrated analysis of bulk and single-cell RNA sequencing reveals the impact of nicotinamide and tryptophan metabolism on glioma prognosis and immunotherapy sensitivity

BackgroundNicotinamide and tryptophan metabolism play important roles in regulating tumor synthesis metabolism and signal transduction functions. However, their comprehensive impact on the prognosis and the tumor immune microenvironment of glioma is still unclear. The purpose of this study was to investigate the association of nicotinamide and tryptophan metabolism with prognosis and immune status of gliomas and to develop relevant models for predicting prognosis and sensitivity to immunotherapy in gliomas.MethodsBulk and single-cell transcriptome data from TCGA, CGGA and GSE159416 were obtained for this study. Gliomas were classified based on nicotinamide and tryptophan metabolism, and PPI network associated with differentially expressed genes was established. The core genes were identified and the risk model was established by machine learning techniques, including univariate Cox regression and LASSO regression. Then the risk model was validated with data from the CGGA. Finally, the effects of genes in the risk model on the biological behavior of gliomas were verified by in vitro experiments.ResultsThe high nicotinamide and tryptophan metabolism is associated with poor prognosis and high levels of immune cell infiltration in glioma. Seven of the core genes related to nicotinamide and tryptophan metabolism were used to construct a risk model, and the model has good predictive ability for prognosis, immune microenvironment, and response to immune checkpoint therapy of glioma. We also confirmed that high expression of TGFBI can lead to an increased level of migration, invasion, and EMT of glioma cells, and the aforementioned effect of TGFBI can be reduced by FAK inhibitor PF-573,228.ConclusionsOur study evaluated the effects of nicotinamide and tryptophan metabolism on the prognosis and tumor immune microenvironment of glioma, which can help predict the prognosis and sensitivity to immunotherapy of glioma.

Research Progress of Single-Cell Transcriptome Sequencing Technology in Plants

Multicellular organisms exhibit inherent cellular heterogeneity that cannot be captured by traditional high-throughput sequencing techniques, resulting in the unique cellular characteristics of individual cells being neglected. Single-cell transcriptome sequencing (scRNA-seq) technology can be used to determine the gene expression levels of each individual cell, facilitating the study of intercellular expression heterogeneity. This review provides a comprehensive overview of the development and applications of scRNA-seq technology in plant research. We highlight the significance of integrating single-cell multi-omics approaches to achieve a holistic understanding of plant systems. Additionally, we discuss the current challenges and future research directions for scRNA-seq technology in plant studies, aiming to offer valuable insights for its application across various plant species.

Resolving the developmental mechanisms of cardiac microthrombosis of SARS-CoV-2 based on single-cell transcriptome analysis.

The coronavirus disease 2019 (COVID-19) outbreak caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) developed into a global health emergency. Systemic microthrombus caused by SARS-CoV-2 infection is a common complication in patients with COVID-19. Cardiac microthrombosis as a complication of SARS-CoV-2 infection is the primary cause of cardiac injury and death in patietns with severe COVID-19. In this study, we performed single-cell sequencing analysis of the right ventricular free wall tissue from healthy donors, patients who died during the hypercoagulable period of characteristic coagulation abnormality (CAC), and patients who died during the fibrinolytic period of CAC. We collected 61,187 cells enriched in 24 immune cell subsets and 13 cardiac-resident cell subsets. We found that in the course of SARS-CoV-2 infected heart microthrombus, MYO1EhighRASGEF1Bhighmonocyte-derived macrophages promoted hyperactivation of the immune system and initiated the extrinsic coagulation pathway by activating chemokines CCL3, CCL5. This series of events is the main cause of cardiac microthrombi following SARS-CoV-2 infection. In a SARS-CoV-2 infected heart microthrombus, excessive immune activation is accompanied by an increase in cellular iron content, which in turn promotes oxidative stress and intensifies intercellular competition. This induces cells to alter their metabolic environment, resulting in increased sugar uptake via the glycosaminoglycan synthesis pathway. In addition, high levels of reactive oxygen species generated by elevated iron levels promote increased endogenous malondialdehyde synthesis in a subpopulation of cardiac endothelial cells. This exacerbates endothelial cell dysfunction and exacerbates the coagulopathy process.

The Contribution of the Novel CLTC-VMP1 Fusion Gene to Autophagy Regulation and Energy Metabolism in Cisplatin-Resistant Osteosarcoma.

Osteosarcoma (OS) is a highly malignant tumor, and chemotherapy resistance is a major challenge in the treatment of this disease. This study aims to explore the role of the CLTC-VMP1 gene fusion in the mechanism of chemotherapy resistance in OS and investigate its molecular mechanisms in mediating energy metabolism reprogramming by regulating autophagy and apoptosis balance. Using single-cell transcriptome analysis, the heterogeneity of OS cells and their correlation with resistance to platinum drugs were revealed. Cisplatin-resistant cell lines were established in human OS cell lines for subsequent experiments. Based on transcriptomic analysis, the importance of VMP1 in chemotherapy resistance was confirmed. Lentiviral vectors overexpressing or interfering with VMP1 were used, and it was observed that inhibiting VMP1 could reverse cisplatin resistance, promote cell apoptosis, and inhibit autophagy, as well as mitochondrial respiration and glycolysis. Furthermore, the presence of CLTC-VMP1 gene fusion was validated, and its ability to regulate autophagy and apoptosis balance, promote mitochondrial respiration, and glycolysis was demonstrated. Mouse model experiments further confirmed the promoting effect of CLTC-VMP1 on tumor growth and chemotherapy resistance. In summary, the CLTC-VMP1 gene fusion mediates energy metabolism reprogramming by regulating autophagy and apoptosis balance, which promotes chemotherapy resistance in OS.

Collapsible tree: interactive web app to present collapsible hierarchies.

A crucial component of intuitive data visualization is presenting a hierarchical tree structure with interactive functions. For example, single-cell transcriptomics studies may generate gene expression values with developmental trajectories or cell lineage structures. Two common visualization methods, t-SNE and UMAP, require two separate figures to depict the distribution of cell types and gene expression data, with low-dimension projections that may not capture the hierarchical structures among cells. Here, we present a JavaScript framework and an interactive web app named Collapsible Tree, which presents values jointly with interactive, expandable, and collapsible lineage structures. For example, the Collapsible Tree presents cellular states and gene expression from single-cell transcriptomics within a single hierarchical plot, enabling comparisons of gene expression across lineages and subtle patterns between sub-lineages. Our framework can facilitate the exploration of complicated value patterns that are not evident in UMAP or t-SNE plots. The Collapsible Tree web interface is available at https://collapsibletree.data2in.net. The JavaScript library source code is available at https://github.com/data2intelligence/collapsible_tree.

Single-cell transcriptomics reveal diverging pathobiology and opportunities for precision targeting in scleroderma-associated versus idiopathic pulmonary arterial hypertension.

Pulmonary arterial hypertension (PAH) involves progressive cellular and molecular change within the pulmonary vasculature, leading to increased vascular resistance. Current therapies targeting nitric oxide (NO), endothelin, and prostacyclin pathways yield variable treatment responses. Patients with systemic sclerosis-associated PAH (SSc-PAH) often experience worse outcomes than those with idiopathic PAH (IPAH). Lung tissue samples from four SSc-PAH, four IPAH, and four failed donor specimens were obtained from the Pulmonary Hypertension Breakthrough Initiative (PHBI) lung tissue bank. Single-cell RNA sequencing (scRNAseq) was performed using the 10X Genomics Chromium Flex platform. Data normalization, clustering, and differential expression analysis were conducted using Seurat. Additional analyses included gene set enrichment analysis (GSEA), transcription factor activity analysis, and ligand-receptor signaling. Pharmacotranscriptomic screening was performed using the Connectivity Map. SSc-PAH samples showed a higher proportion of fibroblasts and dendritic cells/macrophages compared to IPAH and donor samples. GSEA revealed enriched pathways related to epithelial-to-mesenchymal transition (EMT), apoptosis, and vascular remodeling in SSc-PAH samples. There was pronounced differential gene expression across diverse pulmonary vascular cell types and in various epithelial cell types in both IPAH and SSc-PAH, with epithelial to endothelial cell signaling observed. Macrophage to endothelial cell signaling was particularly pronounced in SSc-PAH. Pharmacotranscriptomic screening identified TIE2, GSK-3, and PKC inhibitors, among other compounds, as potential drug candidates for reversing SSc-PAH gene expression signatures. Overlapping and distinct gene expression patterns exist in SSc-PAH versus IPAH, with significant molecular differences suggesting unique pathogenic mechanisms in SSc-PAH. These findings highlight the potential for precision-targeted therapies to improve SSc-PAH patient outcomes. Future studies should validate these targets clinically and explore their therapeutic efficacy.

Bone-marrow macrophage-derived GPNMB protein binds to orphan receptor GPR39 and plays a critical role in cardiac repair.

Glycoprotein nonmetastatic melanoma protein B (GPNMB) is a type I transmembrane protein initially identified in nonmetastatic melanomas and has been associated with human heart failure; however, its role in cardiac injury and function remains unclear. Here we show that GPNMB expression is elevated in failing human and mouse hearts after myocardial infarction (MI). Lineage tracing and bone-marrow transplantation reveal that bone-marrow-derived macrophages are the main source of GPNMB in injured hearts. Using genetic loss-of-function models, we demonstrate that GPNMB deficiency leads to increased mortality, cardiac rupture and rapid post-MI left ventricular dysfunction. Conversely, increasing circulating GPNMB levels through viral delivery improves heart function after MI. Single-cell transcriptomics show that GPNMB enhances myocyte contraction and reduces fibroblast activation. Additionally, we identified GPR39 as a receptor for circulating GPNMB, with its absence negating the beneficial effects. These findings highlight a pivotal role of macrophage-derived GPNMBs in post-MI cardiac repair through GPR39 signaling.

Single-cell Sequencing of Circulating Human Plasmablasts during Staphylococcus aureus Bacteremia.

Staphylococcus aureus is the major cause of healthcare-associated infections, including life-threatening conditions as bacteremia, endocarditis, and implant-associated infections. Despite adequate antibiotic treatment, the mortality of S. aureus bacteremia remains high. This calls for different strategies to treat this infection. In past years, sequencing of Ab repertoires from individuals previously exposed to a pathogen emerged as a successful method to discover novel therapeutic monoclonal Abs and understand circulating B cell diversity during infection. In this paper, we collected peripheral blood from 17 S. aureus bacteremia patients to study circulating plasmablast responses. Using single-cell transcriptome gene expression combined with sequencing of variable heavy and light Ig genes, we retrieved sequences from >400 plasmablasts revealing a high diversity with >300 unique variable heavy and light sequences. More than 200 variable sequences were synthesized to produce recombinant IgGs that were analyzed for binding to S. aureus whole bacterial cells. This revealed four novel monoclonal Abs that could specifically bind to the surface of S. aureus in the absence of Ig-binding surface SpA. Interestingly, three of four mAbs showed cross-reactivity with Staphylococcus epidermidis. Target identification revealed that the S. aureus-specific mAb BC153 targets wall teichoic acid, whereas cross-reactive mAbs BC019, BC020, and BC021 target lipoteichoic acid. All mAbs could induce Fc-dependent phagocytosis of staphylococci by human neutrophils. Altogether, we characterize the active B cell responses to S. aureus in infected patients and identify four functional mAbs against the S. aureus surface, of which three cross-react with S. epidermidis.

Induction of a Müller glial-specific protective pathway safeguards the retina from diabetes induced damage.

Diabetes can lead to cell-type-specific responses in the retina, including vascular lesions, glial dysfunction and neurodegeneration, all of which contribute to retinopathy. However, the molecular mechanisms underlying these cell type-specific responses, and the cell types that are sensitive to diabetes have not been fully elucidated. Employing single cell transcriptomics, we profiled the transcriptional changes induced by diabetes in different retinal cell types in rat models as the disease progressed. Rod photoreceptors, a subtype of amacrine interneurons, and Müller glia exhibited rapid responses to diabetes at the transcript levels. Genes associated with ion regulation were upregulated in all three cell types, suggesting a common response to diabetes. Furthermore, focused studies revealed that while Müller glia initially increased the expression of genes playing protective roles, they cannot sustain this beneficial effect. We explored one of the candidate protective genes, Zinc finger protein 36 homolog (Zfp36), and observed that depleting Zfp36 in rat Müller glial cells in vivo using AAV-based tools exacerbated diabetes-induced phenotypes, including glial reactivation, neurodegeneration, and vascular defects. Over-expression of Zfp36 slowed the development of these phenotypes. This work unveiled retinal cell types that are sensitive to diabetes and demonstrated that Müller glial cells can mount protective responses through Zfp36.

Epstein-Barr virus reactivation induces divergent abortive, reprogrammed, and host shutoff states by lytic progression.

Viral infection leads to heterogeneous cellular outcomes ranging from refractory to abortive and fully productive states. Single cell transcriptomics enables a high resolution view of these distinct post-infection states. Here, we have interrogated the host-pathogen dynamics following reactivation of Epstein-Barr virus (EBV). While benign in most people, EBV is responsible for infectious mononucleosis, up to 2% of human cancers, and is a trigger for the development of multiple sclerosis. Following latency establishment in B cells, EBV reactivates and is shed in saliva to enable infection of new hosts. Beyond its importance for transmission, the lytic cycle is also implicated in EBV-associated oncogenesis. Conversely, induction of lytic reactivation in latent EBV-positive tumors presents a novel therapeutic opportunity. Therefore, defining the dynamics and heterogeneity of EBV lytic reactivation is a high priority to better understand pathogenesis and therapeutic potential. In this study, we applied single-cell techniques to analyze diverse fate trajectories during lytic reactivation in three B cell models. Consistent with prior work, we find that cell cycle and MYC expression correlate with cells refractory to lytic reactivation. We further found that lytic induction yields a continuum from abortive to complete reactivation. Abortive lytic cells upregulate NFκB and IRF3 pathway target genes, while cells that proceed through the full lytic cycle exhibit unexpected expression of genes associated with cellular reprogramming. Distinct subpopulations of lytic cells further displayed variable profiles for transcripts known to escape virus-mediated host shutoff. These data reveal previously unknown and promiscuous outcomes of lytic reactivation with broad implications for viral replication and EBV-associated oncogenesis.

Atp13a5 Marker Reveals Pericyte Specification in the Mouse Central Nervous System.

Perivascular mural cells including vascular smooth cells (VSMCs) and pericytes are integral components of the vascular system. In the central nervous system (CNS), pericytes are also indispensable for the blood-brain barrier (BBB), blood-spinal cord barrier, and blood-retinal barrier and play key roles in maintaining cerebrovascular and neuronal functions. However, the functional specifications of pericytes between CNS and peripheral organs have not been resolved at the genetic and molecular levels. Hence, the generation of reliable CNS pericyte-specific models and genetic tools remains very challenging. Here, we report a new CNS pericyte marker in mice. This putative cation-transporting ATPase 13A5 (Atp13a5) marker was identified through single-cell transcriptomics, based on its specificity to brain pericytes. We further generated a knock-in model with both tdTomato reporter and Cre recombinase. Using this model to trace the distribution of Atp13a5-positive pericytes in mice, we found that the tdTomato reporter reliably labels the CNS pericytes, including the ones in spinal cord and retina but not peripheral organs. Interestingly, brain pericytes are likely shaped by the developing neural environment, as Atp13a5-positive pericytes start to appear around murine embryonic day 15 (E15) and expand along the cerebrovasculature. Thus, Atp13a5 is a specific marker of CNS pericyte lineage, and this Atp13a5-based model is a reliable tool to explore the heterogeneity of pericytes and BBB functions in health and diseases.

Identification of HSPG2 as a bladder pro-tumor protein through NID1/AKT signaling

PurposeHeparan sulfate proteoglycans (HSPGs) are complex molecules found on the cell membrane and within the extracellular matrix, increasingly recognized for their role in tumor progression. This study aimed to investigate the involvement of Heparan sulfate proteoglycan 2 (HSPG2) in the progression of bladder cancer.MethodsWe identified HSPG2 as a promoter of bladder tumor progression using single-cell RNA sequencing and transcriptome analysis of sequencing data from seven patient samples obtained from the Gene Expression Omnibus (GEO) database (GSE135337). Transcript profiles of 28 normal tissues and 407 bladder tumor tissues were analyzed for HSPG2 expression and survival outcomes using the Sanger tools and cBioPortal databases. HSPG2-overexpressing T24 and Biu-87 cell lines were generated, and cell proliferation and migration were assessed using CCK-8 and Transwell assays. Western blotting and immunostaining were performed to evaluate the activation of Nidogen-1 (NID1)/protein kinase B (AKT) signaling. Mouse models with patient-derived tumor organoids (HSPG2high and HSPG2low) were established to assess anticancer effects.ResultsOur results demonstrated a marked upregulation of HSPG2 in malignant bladder tumors, which correlated significantly with poor patient prognosis. HSPG2 overexpression consistently enhanced bladder tumor cell proliferation and conferred chemotherapy resistance, as shown in both in vitro and in vivo experiments. Mechanistically, HSPG2 upregulated NID1 expression, leading to the activation of the AKT pro-survival signaling pathway and promoting sustained tumor growth in bladder cancer.ConclusionThis study highlights the critical pro-tumor role of HSPG2/NID1/AKT signaling in bladder cancer and suggests its potential as a therapeutic target in clinical treatment.