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SARS-CoV-2 Entry Genes Are Most Highly Expressed in Nasal Goblet and Ciliated Cells within Human Airways.
The SARS-CoV-2 coronavirus, the etiologic agent responsible for COVID-19 coronavirus disease, is a global threat. To better understand viral tropism, we assessed the RNA expression of the coronavirus receptor, ACE2, as well as the viral S protein priming protease TMPRSS2 thought to govern viral entry in single-cell RNA-sequencing (scRNA-seq) datasets from healthy individuals generated by the Human Cell Atlas consortium. We found that ACE2, as well as the protease TMPRSS2, are differentially expressed in respiratory and gut epithelial cells. In-depth analysis of epithelial cells in the respiratory tree reveals that nasal epithelial cells, specifically goblet/secretory cells and ciliated cells, display the highest ACE2 expression of all the epithelial cells analyzed. The skewed expression of viral receptors/entry-associated proteins towards the upper airway may be correlated with enhanced transmissivity. Finally, we showed that many of the top genes associated with ACE2 airway epithelial expression are innate immune-associated, antiviral genes, highly enriched in the nasal epithelial cells. This association with immune pathways might have clinical implications for the course of infection and viral pathology, and highlights the specific significance of nasal epithelia in viral infection. Our findings underscore the importance of the availability of the Human Cell Atlas as a reference dataset. In this instance, analysis of the compendium of data points to a particularly relevant role for nasal goblet and ciliated cells as early viral targets and potential reservoirs of SARS-CoV-2 infection. This, in turn, serves as a biological framework for dissecting viral transmission and developing clinical strategies for prevention and therapy.
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Single-cell analysis of preimplantation embryonic development in guinea pigs.
BACKGROUND: Guinea pigs exhibit numerous physiological similarities to humans, yet the details of their preimplantation embryonic development remain largely unexplored. RESULTS: To address this, we conducted single-cell sequencing on the transcriptomes of cells isolated from the zygote stage through preimplantation stages in guinea pigs. This study identified seven distinct cell types within guinea pig preimplantation embryos and pinpointed the timing of zygotic gene activation (ZGA). Trajectory analysis revealed a bifurcation into two lineage-specific branches, accompanied by alterations in specific pathways, including oxidative phosphorylation and vascular endothelial growth factor (VEGF). Additionally, co-expressed gene network analysis highlighted the most enriched functional modules for the epiblast (EPI), primitive endoderm (PrE), and inner cell mass (ICM). Finally, we compared the similarities and differences between human and guinea pig epiblasts (EPIs). CONCLUSION: This study systematically constructs a cell atlas of guinea pig preimplantation embryonic development, offering fresh insights into mammalian embryonic development and providing alternative experimental models for studying human embryonic development.
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Novel long non-coding RNA LINC02532 promotes gastric cancer cell proliferation, migration, and invasion in vitro.
BACKGROUND: Long non-coding RNAs (lncRNAs) are a kind of single-stranded RNA of more than 200 nucleotides in length and have no protein-coding function. Amounting studies have indicated that lncRNAs could play a vital role in the initiation and development of cancers, including gastric cancer (GC). Considering the crucial functions of lncRNAs, the identification and exploration of novel lncRNAs in GC is necessary. AIM: To explore the role of novel lncRNA LINC02532 in GC. METHODS: The upregulated LINC02532 was identified by processing the GC RNA-Seq data from The Cancer Genome Atlas. The qRT-PCR assay was performed to confirm the expression levels in GC cell lines and tissues. Cell proliferation, migration, and invasion were evaluated by the cell counting kit-8, colony formation, wound healing, and Transwell assays. The miRNAs downregulated in GC and sponged by LINC02532 were identified from and predicted by the data from the Firehose and RNA22 software programs, respectively. The miRNA downstream target genes were obtained from the TargetScan, miRDB, and DIANA online tools. Gene functional enrichment analysis was carried out using the Database for Annotation, Visualization, and Integrated Discovery software in the categories of cellular components, biological processes, molecular functions, and KEGG pathways. RESULTS: The qRT-PCR assay demonstrated that the LINC02532 expression level was significantly upregulated in the GC cell lines and 52 paired tissues. Kaplan-Meier survival analysis based on The Cancer Genome Atlas data showed that patients with higher LINC02532 expression had poorer prognosis than those with lower LINC02532 expression. The correlation analysis between expression and clinicopathological features revealed that high expression of LINC02532 was associated with a high TNM stage (P = 0.008) and poor differentiation grade (P = 0.023). Functional experiments showed that LINC02532 promoted GC cell proliferation, migration, and invasion. According to the bioinformatics analysis, LINC02532 may act as a ceRNA by sponging downregulated miR-129-5p and miR-490-5p. Target genes of the two miRNAs were selected for further functional enrichment analysis. Importantly, KEGG pathway analysis showed that the genes were mainly involved in transcriptional misregulation in cancer, cell cycle, and TGF-beta, mTOR, and p53 signaling pathways. CONCLUSION: The present study suggested that LINC02532 acted as an oncogene in GC and may be a promising target for therapy and prognosis management of GC.
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Significance analysis for clustering with single-cell RNA-sequencing data.
Unsupervised clustering of single-cell RNA-sequencing data enables the identification of distinct cell populations. However, the most widely used clustering algorithms are heuristic and do not formally account for statistical uncertainty. We find that not addressing known sources of variability in a statistically rigorous manner can lead to overconfidence in the discovery of novel cell types. Here we extend a previous method, significance of hierarchical clustering, to propose a model-based hypothesis testing approach that incorporates significance analysis into the clustering algorithm and permits statistical evaluation of clusters as distinct cell populations. We also adapt this approach to permit statistical assessment on the clusters reported by any algorithm. Finally, we extend these approaches to account for batch structure. We benchmarked our approach against popular clustering workflows, demonstrating improved performance. To show practical utility, we applied our approach to the Human Lung Cell Atlas and an atlas of the mouse cerebellar cortex, identifying several cases of over-clustering and recapitulating experimentally validated cell type definitions.
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Single-cell Expression Atlas Reveals Cell Heterogeneity in the Creeping Fat of Crohn's Disease.
BACKGROUND: Creeping fat (CrF) has been recognized to play a positive role in Crohn's disease (CD) progression, yet the cellular compositions within mesenteric adipose tissue (MAT) and their potential mechanism in CrF formation are poorly understood. METHODS: Analysis of 10X single-cell RNA sequencing was performed on 67 064 cells from 3 pairs of surgically resected samples of CrF and their uninvolved MAT. The results were validated in another cohort with 6 paired MAT samples by immunofluorescence. RESULTS: All samples manifested excellent consistency and repeatability in our study, and 10 cell types from the transcriptome atlas, including 20 clusters, were identified. In CrF, a specific vascular endothelial cell subpopulation highly expressing lipoprotein lipase was first identified, with a significantly increased proportion. This vascular endothelial cell subpopulation manifested robust peroxisome proliferator-activated receptor γ (PPARγ) transcription activity and an upregulated PPAR signaling pathway and was involved in lipid metabolism and the antibacterial response. A novel fibroblast subpopulation (FC3) with remarkable GREM1 and RFLNB expression was identified and validated to predominantly accumulate in the CrF. The FC3 was annotated as inflammation-associated fibroblasts, which are characterized by inflammatory responses and the regulation of Smad phosphorylation related to intestinal fibrosis. The trajectory of fibroblasts revealed their pro-inflammatory and profibrotic conversion tendency during CrF formation with corresponding gene dynamics. Additionally, we unprecedently dissected the different origins and functions of 6 macrophage subclusters within the myeloid compartment. CONCLUSIONS: Our results uncover the cellular heterogeneity in the MAT of CD and the role of these various cellular compositions in CrF development. This comprehensive understanding of CrF provides future directions for in-depth research on and potential targets for MAT-based treatment.
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Transcriptomic, epigenomic, and spatial metabolomic cell profiling redefines regional human kidney anatomy.
A large-scale multimodal atlas that includes major kidney regions is lacking. Here, we employed simultaneous high-throughput single-cell ATAC/RNA sequencing (SHARE-seq) and spatially resolved metabolomics to profile 54 human samples from distinct kidney anatomical regions. We generated transcriptomes of 446,267 cells and chromatin accessibility profiles of 401,875 cells and developed a package to analyze 408,218 spatially resolved metabolomes. We find that the same cell type, including thin limb, thick ascending limb loop of Henle and principal cells, display distinct transcriptomic, chromatin accessibility, and metabolomic signatures, depending on anatomic location. Surveying metabolism-associated gene profiles revealed non-overlapping metabolic signatures between nephron segments and dysregulated lipid metabolism in diseased proximal tubule (PT) cells. Integrating multimodal omics with clinical data identified PLEKHA1 as a disease marker, and its in vitro knockdown increased gene expression in PT differentiation, suggesting possible pathogenic roles. This study highlights previously underrepresented cellular heterogeneity underlying the human kidney anatomy.
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Single-cell profiling of long non-coding RNAs in the hematopoietic system.
Long non-coding RNAs (lncRNAs) play a crucial role in normal and dysregulated hematopoiesis. However, the functional repertoire of lncRNAs across various hematopoietic cell types remains elusive. In this study, we constructed a comprehensive single-cell lncRNA atlas containing 207,113 cells, spanning hematopoietic stem and progenitor cells (HSPCs) to differentiated blood cells, by integrating nine single-cell RNA sequencing (scRNA-seq) datasets derived from 30 healthy donors. The hematopoietic hierarchy based on lncRNA expression was highly consistent with that based on protein-coding genes. We identified 3,463 lineage-specific lncRNAs in HSPCs, neutrophils, monocytes, B cells, and T/natural killer cells; 23 of 30 selected lncRNAs were experimentally validated. Importantly, upregulated lncRNAs in pediatric patients with B cell acute lymphoblastic leukemia, T cell acute lymphoblastic leukemia, and acute myeloid leukemia were primarily associated with oxygen response and immune regulation, indicating the potential contribution of lncRNAs to leukemogenesis. In conclusion, our results portray the landscape of lncRNAs in the hematopoietic system, revealing the functional significance of lncRNAs in both normal and abnormal hematopoiesis and providing potential therapeutic targets for the clinical treatment of leukemia.
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Primary nasal influenza infection rewires tissue-scale memory response dynamics.
The nasal mucosa is often the initial site of respiratory viral infection, replication, and transmission. Understanding how infection shapes tissue-scale primary and memory responses is critical for designing mucosal therapeutics and vaccines. We generated a single-cell RNA-sequencing atlas of the murine nasal mucosa, sampling three regions during primary influenza infection and rechallenge. Compositional analysis revealed restricted infection to the respiratory mucosa with stepwise changes in immune and epithelial cell subsets and states. We identified and characterized a rare subset of Krt13+ nasal immune-interacting floor epithelial (KNIIFE) cells, which concurrently increased with tissue-resident memory T (TRM)-like cells. Proportionality analysis, cell-cell communication inference, and microscopy underscored the CXCL16-CXCR6 axis between KNIIFE and TRM cells. Secondary influenza challenge induced accelerated and coordinated myeloid and lymphoid responses without epithelial proliferation. Together, this atlas serves as a reference for viral infection in the upper respiratory tract and highlights the efficacy of local coordinated memory responses.
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A New Method for Constructing Macrophage-Associated Predictors of Treatment Efficacy Based on Single-Cell Sequencing Analysis.
Tumor-associated macrophages (TAMs) are highly infiltrated in the tumor microenvironment (TME) of colorectal cancer (CRC) and play a vital role in CRC's development as well as prognosis. The required data were obtained from the Gene Expression Omnibus database and The Cancer Genome Atlas. Univariate Cox regression and least absolute shrinkage operator analyses were executed for model construction. TME assessment and immune prediction were performed using the ESTIMATE software package and the single sample genome enrichment analysis algorithm. The results show patients with low a TAMs risk score (TRS) had a better prognosis in both The Cancer Genome Atlas and Gene Expression Omnibus cohorts. Patients with low TRS were more sensitive to 3 chemotherapeutic agents: oxaliplatin, paclitaxel, and cisplatin ( P <0.05). TME assessment showed that the low TRS group had less infiltration of M2 macrophages and regulatory T cells, but CD4 + T cells, NK cells, and dendritic cells occupy a greater proportion of TME. Low TRS group patients have a low StromalScore and ImmuneScore but have high TumorPurity. The immune checkpoint TIM-3 gene HAVCR2 expression was significantly higher in the high TRS group. Finally, we created a nomogram including TRS for forecasting survival, and TRS was significantly associated with the clinical stage of the patients. In conclusion, the TRS serves as a reliable prognostic indicator of CRC; it predicts patient outcomes to immunotherapy and chemotherapy and provides genomic evidence for the subsequent development of modulated TAMs for treating CRC.
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A differential single-cell transcriptome atlas of left-sided and right-sided colorectal cancer.
Left-sided colorectal cancer (LCRC) and right-sided colorectal cancer (RCRC) show marked differences in prognosis and therapeutic response, yet the underlying molecular mechanisms remain poorly understood. We hypothesize that these clinical differences reflect distinct cell-type-specific transcriptional programs and microenvironmental interactions that can be resolved at single-cell resolution. To test this hypothesis, this study analyzed single-cell transcriptomic data from 16 colorectal cancer (CRC) patients (8 LCRC and 8 RCRC), revealing molecular differences between LCRC and RCRC in tumor cells, T cells, B cells, myeloid cells, fibroblasts, and endothelial cells, and constructing a differential atlas of LCRC versus RCRC. Significant molecular and cellular differences were observed between LCRC and RCRC. MTRNR2L8 was markedly upregulated in RCRC tumor cells and associated with poorer patient survival, potentially regulated by transcription factors STAT3, ELK3, and EP300. RCRC showed an increased proportion of the CD8-EFFECTOR 3 subpopulation, which co-expresses effector and exhaustion markers, suggesting favorable immunotherapy response. In contrast, the CD4-heat shock proteins (CD4-HSP) subpopulation was almost exclusively present in LCRC, suggesting a potential correlation with a weaker response to immune checkpoint inhibitors. Additionally, APP-CD74 ligand-receptor interactions were significantly enhanced in RCRC, potentially contributing to worse prognosis by inhibiting APP protein cleavage and promoting its accumulation. Validation was performed using an independent single-cell transcriptomic dataset, bulk RNA-seq data from TCGA CRC samples, and qPCR on locally collected CRC tissue specimens. In addition, a spatial transcriptomic dataset of CRC and immunohistochemistry data from the Human Protein Atlas (HPA) database were also used to validate part of the findings. This study provides a comprehensive single-cell transcriptomic atlas highlighting the molecular and cellular disparities between LCRC and RCRC, offering novel insights into tumor biology and informing the development of personalized therapeutic strategies.