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Mediators of SARS-CoV-2 entry are preferentially enriched in cardiomyocytes.
BACKGROUND: The coronavirus disease 2019 (COVID-19) has spread rapidly around the world. In addition to common respiratory symptoms such as cough and fever, some patients also have cardiac injury, however, the mechanism of cardiac injury is not clear. In this study, we analyzed the RNA expression atlases of angiotensin-converting enzyme 2(ACE2), cathepsin B (CTSB) and cathepsin L (CTSL) in the human embryonic heart at single-cell resolution. RESULTS: The results showed that ACE2 was preferentially enriched in cardiomyocytes. Interestingly, serine protease transmembrane serine protease 2 (TMPRSS2) had less expression in cardiomyocytes, but CTSB and CTSL, which belonged to cell protease, could be found to be enriched in cardiomyocytes. The results of enrichment analysis showed that differentially expressed genes (DEGs) in ACE2-positive cardiomyocytes were mainly enriched in the processes of cardiac muscle contraction, regulation of cardiac conduction, mitochondrial respiratory chain, ion channel binding, adrenergic signaling in cardiomyocytes and viral transcription. CONCLUSIONS: Our study suggests that both atrial and ventricular cardiomyocytes are potentially susceptible to severe acute respiratory syndrome coronavirus-2(SARS-CoV-2), and SARS-CoV-2 may enter ventricular cardiomyocytes using CTSB/CTSL for S protein priming. This may be the partial cellular mechanism of cardiac injury in patients with COVID-19.
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Evolutionary Trajectory of Radioresistance in Lung Cancer Brain Metastasis Organoids.
BACKGROUND: Radiotherapy (RT) is a cornerstone treatment for lung cancer brain metastasis (LCBM), yet acquired radioresistance frequently leads to recurrence. The molecular and metabolic mechanisms underlying this adaptive evolution at single-cell resolution remain poorly defined. METHODS: Patient-derived organoids (PDOs) from LCBM tissues were established to model clinical radiation responses. Paired pre- and post-RT samples underwent single-cell RNA sequencing (scRNA-seq) to delineate transcriptional, metabolic, and regulatory alterations associated with radioresistance. RESULTS: Single-cell analysis revealed substantial population remodeling following RT, characterized by depletion of proliferative cells and enrichment of a resilient Hypoxic-EMT subpopulation. Pseudotime analysis demonstrated lineage plasticity, showing a transition from proliferative to mesenchymal states. Mechanistically, a viral mimicry response involving NF-κB and STAT signaling supported stress adaptation. Resistant cells exhibited a hypermetabolic phenotype marked by metabolic plasticity, including hybrid bioenergetics coupling glycolysis with oxidative phosphorylation, enhanced lipid turnover via simultaneous fatty acid synthesis and degradation, and increased glutathione metabolism for reactive oxygen species buffering. Pharmacogenomic profiling indicated concurrent chemotherapy resistance but collateral sensitivity to PI3K/MEK inhibitors and epigenetic therapies. CONCLUSIONS: These findings provide a high-resolution atlas of radioresistance in LCBM and suggest that targeting the Hypoxic-EMT niche or oxidative-antioxidant balance may overcome therapeutic resistance.
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Single-cell sequencing reveals microglia induced angiogenesis by specific subsets of endothelial cells following spinal cord injury.
Spinal cord injury (SCI) results in dynamic alterations of the microenvironment at the lesion site, which inevitably leads to neuronal degeneration and functional impairment. The destruction of the spinal vascular system leads to a significant deterioration of the milieu, which exacerbates inflammatory response and deprives cells of nutrient support in the lesion. Limited endogenous angiogenesis occurs after SCI, but the cellular events at the lesion site during this process are unclear so far. Here, we performed single-cell RNA sequencing (scRNA-seq) on spinal cord tissues of rats at different time points after SCI. After clustering and cell-type identification, we focused on vascular endothelial cells (ECs), which play a pivotal role in angiogenesis, and drew the cellular and molecular atlas for angiogenesis after SCI. We found that microglia and macrophages promote endogenous angiogenesis by regulating EC subsets through SPP1 and IGF signaling pathways. Our results indicate that immune cells promote angiogenesis by regulating specific subsets of vascular ECs, which provides new clues for exploring SCI intervention.
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Deconvolution of the hematopoietic stem cell microenvironment reveals a high degree of specialization and conservation.
Understanding the regulation of normal and malignant human hematopoiesis requires comprehensive cell atlas of the hematopoietic stem cell (HSC) regulatory microenvironment. Here, we develop a tailored bioinformatic pipeline to integrate public and proprietary single-cell RNA sequencing (scRNA-seq) datasets. As a result, we robustly identify for the first time 14 intermediate cell states and 11 stages of differentiation in the endothelial and mesenchymal BM compartments, respectively. Our data provide the most comprehensive description to date of the murine HSC-regulatory microenvironment and suggest a higher level of specialization of the cellular circuits than previously anticipated. Furthermore, this deep characterization allows inferring conserved features in human, suggesting that the layers of microenvironmental regulation of hematopoiesis may also be shared between species. Our resource and methodology is a stepping-stone toward a comprehensive cell atlas of the BM microenvironment.
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Single-Cell Meta-Analysis Uncovers the Pancreatic Endothelial Cell Transcriptomic Signature and Reveals a Key Role for NKX2-3 in PLVAP Expression.
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 NK2 homeobox 3 (NKX2-3) TF (transcription factor) 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 [sphingosine-1-phosphate], TGF-β [transforming growth factor-β], RHO/RAC GTPase [guanosine triphosphatase], PI3K/AKT [phosphoinositide 3-kinase/protein kinase B], 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_endothelial/.
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Single-cell transcriptional mapping reveals genetic and non-genetic determinants of aberrant differentiation in AML.
In acute myeloid leukemia (AML), genetic mutations distort hematopoietic differentiation, resulting in the accumulation of leukemic blasts. Yet, it remains unclear how these mutations intersect with cellular origins and whether they converge upon similar differentiation patterns. Single-cell RNA sequencing (scRNA-seq) has enabled high-resolution mapping of the relationship between leukemia and normal cell states, yet this application is hampered by imprecise reference maps of normal hematopoiesis and small sample sizes among patient cohorts. As a first step we constructed a reference atlas of human bone marrow hematopoiesis from 263,519 single-cell transcriptomes spanning 55 cellular states, that was benchmarked against independent datasets of immunophenotypically pure hematopoietic stem and progenitor cells. Using this reference atlas, we mapped over 1.2 million single-cell transcriptomes spanning 318 AML, mixed phenotype acute leukemia (MPAL), and acute erythroid leukemia (AEL) samples. This large-scale analysis, together with systematic mapping of genotype-to-phenotype associations between driver mutations and differentiation landscapes, revealed convergence of diverse genetic alterations on twelve recurrent patterns of aberrant differentiation in AML. This included unconventional lymphoid and erythroid priming linked to RUNX1 and TP53 mutations, respectively. We also identified non-genetic determinants of AML differentiation such as two subgroups of KMT2A-rearranged AML that differ in the identity of their leukemic stem cells (LSCs), likely reflecting distinct cellular origins. Furthermore, distinct LSC-driven hierarchies can co-exist within individual patients, providing insights into AML evolution. Together, precise mapping of normal and malignant cell states provides a framework for advancing the study and disease classification of hematologic malignancies thereby informing therapy development.
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Cell-state mapping reveals a reversible neuroblast accumulation in the aging mouse hippocampus.
Hippocampal neurogenesis supports learning and memory by generating new granule cells throughout life. However, both the rate and speed of this process decline with age. To elucidate the molecular determinants underlying the effects of aging on neuronal differentiation, we combined lineage tracing of adult-born granule cells (aGCs) with single-nucleus RNA sequencing. This approach produced a temporally resolved transcriptional atlas of aGC development. Aging led to a marked accumulation of postmitotic neuroblasts (NBs), revealing a stage-specific bottleneck in the neurogenic trajectory. Voluntary running reduced NB accumulation by restoring the progression through this developmental impasse, allowing neuronal maturation to be resumed. Notably, this effect involved a significant reduction of apoptosis at the NB stage. Together, these findings identify a reversible apoptotic checkpoint that contributes to age-related neurogenic decline and highlight postmitotic NBs as a key regulatory cell state capable of integrating pro-maturational signals to control the neurogenic output.
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Meta-dimensional data integration identifies critical pathways for susceptibility, tumorigenesis and progression of endometrial cancer.
Endometrial Cancer (EC) is one of the most common female cancers. Genome-wide association studies (GWAS) have been investigated to identify genetic polymorphisms that are predictive of EC risks. Here we utilized a meta-dimensional integrative approach to seek genetically susceptible pathways that may be associated with tumorigenesis and progression of EC. We analyzed GWAS data obtained from Connecticut Endometrial Cancer Study (CECS) and identified the top 20 EC susceptible pathways. To further verify the significance of top 20 EC susceptible pathways, we conducted pathway-level multi-omics analyses using EC exome-Seq, RNA-Seq and survival data, all based on The Cancer Genome Atlas (TCGA) samples. We measured the overall consistent rankings of these pathways in all four data types. Some well-studied pathways, such as p53 signaling and cell cycle pathways, show consistently high rankings across different analyses. Additionally, other cell signaling pathways (e.g. IGF-1/mTOR, rac-1 and IL-5 pathway), genetic information processing pathway (e.g. homologous recombination) and metabolism pathway (e.g. sphingolipid metabolism) are also highly associated with EC risks, diagnosis and prognosis. In conclusion, the meta-dimensional integration of EC cohorts has suggested some common pathways that may be associated from predisposition, tumorigenesis to progression.
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DisCP-Atlas: a comprehensive resource mapping cellular processes to complex diseases.
Genome-wide association studies (GWAS) have identified thousands of disease-associated loci, yet translating these findings into biological mechanisms remains challenging. Single-cell RNA-sequencing provides functional annotation at cellular resolution. Most current resources connect disease associations only to discrete cell-type categories. This cell type centric view overlooks disease-relevant cellular processes, which constitute the primary gene expression programs underlying genetic risk. These cellular processes function along continuous cell-state trajectories and routinely extend beyond conventional cell type boundaries. To address this issue, we present DisCP-Atlas (Disease to Cellular Process Atlas), a comprehensive resource that maps cellular processes to complex diseases. DisCP-Atlas identifies 990 cellular processes derived from 57 single-cell datasets across 35 human tissues, each annotated based on pathway enrichment and cell type-specific activities. Leveraging the sc-linker framework, we systematically linked 1072 GWAS datasets spanning 759 diseases to the cellular processes and identified 37 918 significant cellular process-disease associations. DisCP-Atlas allows bidirectional querying diseases to their underlying cellular processes or identifies diseases associated with specific cellular programs. All the results are presented in interactive visualization and can be conveniently downloaded. Additionally, DisCP-Atlas provides an online enrichment tool, enables users to submit custom genes, and returns detailed tables and interactive visualizations of enriched cellular processes. DisCP-Atlas is freely accessible at https://www.discpatlas.net.
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Targeted variant detection using unaligned RNA-Seq reads.
Mutations identified in acute myeloid leukemia patients are useful for prognosis and for selecting targeted therapies. Detection of such mutations using next-generation sequencing data requires a computationally intensive read mapping step followed by several variant calling methods. Targeted mutation identification drastically shifts the usual tradeoff between accuracy and performance by concentrating all computations over a small portion of sequence space. Here, we present km, an efficient approach leveraging k-mer decomposition of reads to identify targeted mutations. Our approach is versatile, as it can detect single-base mutations, several types of insertions and deletions, as well as fusions. We used two independent cohorts (The Cancer Genome Atlas and Leucegene) to show that mutation detection by km is fast, accurate, and mainly limited by sequencing depth. Therefore, km allows the establishment of fast diagnostics from next-generation sequencing data and could be suitable for clinical applications.