Project description:Study questionWhat are the cellular composition and single-cell transcriptomic differences between myometrium and leiomyomas as defined by single-cell RNA sequencing?Summary answerWe discovered cellular heterogeneity in smooth muscle cells (SMCs), fibroblast and endothelial cell populations in both myometrium and leiomyoma tissues.What is known alreadyPrevious studies have shown the presence of SMCs, fibroblasts, endothelial cells and immune cells in myometrium and leiomyomas. However, there is no information on the cellular heterogeneity in these tissues and the transcriptomic differences at the single-cell level between these tissues.Study design, size, durationWe collected five leiomyoma and five myometrium samples from a total of eight patients undergoing hysterectomy. We then performed single-cell RNA sequencing to generate a cell atlas for both tissues. We utilized our single-cell sequencing data to define cell types, compare cell types by tissue type (leiomyoma versus myometrium) and determine the transcriptional changes at a single-cell resolution between leiomyomas and myometrium. Additionally, we performed MED12-variant analysis at the single-cell level to determine the genotype heterogeneity within leiomyomas.Participants/materials, setting, methodsWe collected five MED12-variant positive leiomyomas and five myometrium samples from a total of eight patients. We then performed single-cell RNA sequencing on freshly isolated single-cell preparations. Histopathological assessment confirmed the identity of the samples. Sanger sequencing was performed to confirm the presence of the MED12 variant in leiomyomas.Main results and role of chanceOur data revealed previously unknown heterogeneity in the SMC, fibroblast cell and endothelial cell populations of myometrium and leiomyomas. We discovered the presence of two different lymphatic endothelial cell populations specific to uterine leiomyomas. We showed that both myometrium and MED12-variant leiomyomas are relatively similar in cellular composition but differ in cellular transcriptomic profiles. We found that fibroblasts influence the leiomyoma microenvironment through their interactions with endothelial cells, immune cells and SMCs. Variant analysis at the single-cell level revealed the presence of both MED12 variants as well as the wild-type MED12 allele in SMCs of leiomyomatous tissue. These results indicate genotype heterogeneity of cellular composition within leiomyomas.Large scale dataThe datasets are available in the NCBI Gene Expression Omnibus (GEO) using GSE162122.Limitations, reasons for cautionOur study focused on MED12-variant positive leiomyomas for single-cell RNA sequencing analyses. Leiomyomas carrying other genetic rearrangements may differ in their cellular composition and transcriptomic profiles.Wider implications for the findingsOur study provides a cellular atlas for myometrium and MED12-variant positive leiomyomas as defined by single-cell RNA sequencing. Our analysis provides significant insight into the differences between myometrium and leiomyomas at the single-cell level and reveals hitherto unknown genetic heterogeneity in multiple cell types within human leiomyomas. Our results will be important for future studies into the origin and growth of human leiomyomas.Study funding/competing interest(s)This work was supported by funding from the National Institute of Child Health and Human Development (HD098580 and HD088629). The authors declare no competing interests.
Project description:Recent advances in technology such as the introduction of high throughput multidimensional tools like single cell sequencing help to characterize the cellular composition of the human heart. The diversity of cell types that has been uncovered by such approaches is by far greater than ever expected before. Accurate identification of the cellular variety and dynamics will not only facilitate a much deeper understanding of cardiac physiology but also provide important insights into mechanisms underlying its pathological transformation. Distinct cellular patterns of cardiac cell clusters may allow differentiation between a healthy heart and a sick heart while potentially predicting future disease at much earlier stages than currently possible. These advances have already extensively improved and will ultimately revolutionize our knowledge of the mechanisms underlying cardiovascular disease as such. In this review, we will provide an overview of the cells present in the human and rodent heart as well as genes that may be used for their identification.
Project description:AimsThe artery contains numerous cell types which contribute to multiple vascular diseases. However, the heterogeneity and cellular responses of these vascular cells during abdominal aortic aneurysm (AAA) progression have not been well characterized.Methods and resultsSingle-cell RNA sequencing was performed on the infrarenal abdominal aortas (IAAs) from C57BL/6J mice at Days 7 and 14 post-sham or peri-adventitial elastase-induced AAA. Unbiased clustering analysis of the transcriptional profiles from >4500 aortic cells identified 17 clusters representing nine-cell lineages, encompassing vascular smooth muscle cells (VSMCs), fibroblasts, endothelial cells, immune cells (macrophages, T cells, B cells, and dendritic cells), and two types of rare cells, including neural cells and erythrocyte cells. Seurat clustering analysis identified four smooth muscle cell (SMC) subpopulations and five monocyte/macrophage subpopulations, with distinct transcriptional profiles. During AAA progression, three major SMC subpopulations were proportionally decreased, whereas the small subpopulation was increased, accompanied with down-regulation of SMC contractile markers and up-regulation of pro-inflammatory genes. Another AAA-associated cellular response is immune cell expansion, particularly monocytes/macrophages. Elastase exposure induced significant expansion and activation of aortic resident macrophages, blood-derived monocytes and inflammatory macrophages. We also identified increased blood-derived reparative macrophages expressing anti-inflammatory cytokines suggesting that resolution of inflammation and vascular repair also persist during AAA progression.ConclusionOur data identify AAA disease-relevant transcriptional signatures of vascular cells in the IAA. Furthermore, we characterize the heterogeneity and cellular responses of VSMCs and monocytes/macrophages during AAA progression, which provide insights into their function and the regulation of AAA onset and progression.
Project description:The attachment site of the rotator cuff (RC) is a classic fibrocartilaginous enthesis, which is the junction between bone and tendon with typical characteristics of a fibrocartilage transition zone. Enthesis development has historically been studied with lineage tracing of individual genes selected a priori, which does not allow for the determination of single-cell landscapes yielding mature cell types and tissues. Here, in together with open-source GSE182997 datasets (three samples) provided by Fang et al., we applied Single-cell RNA sequencing (scRNA-seq) to delineate the comprehensive postnatal RC enthesis growth and the temporal atlas from as early as postnatal day 1 up to postnatal week 8. And, we furtherly performed single-cell spatial transcriptomic sequencing on postnatal day 1 mouse enthesis, in order to deconvolute bone-tendon junction (BTJ) chondrocytes onto spatial spots. In summary, we deciphered the cellular heterogeneity and the molecular dynamics during fibrocartilage differentiation. Combined with current spatial transcriptomic data, our results provide a transcriptional resource that will support future investigations of enthesis development at the mechanistic level and may shed light on the strategies for enhanced RC healing outcomes.
Project description:Ligaments are collagenous connective tissues that connect bones. Injury of knee ligaments, namely anterior cruciate ligament (ACL) and medial collateral ligament (MCL), is common in athletes. Both ligaments have important functions, but distinct regeneration capacities. The capacity for recovery after injury also diminishes with age. However, cellular heterogeneity in the ligaments remains unclear. Here, we profiled the transcriptional signatures of ACL and MCL cells in mice using single-cell RNA sequencing. These ligaments comprise three fibroblast types expressing Col22a1, Col12a1, or Col14a1, but have distinct localizations in the tissue. We found substantial heterogeneity in Col12a1- and Col14a1-positive cells between ACL and MCL. Gene Ontology analysis revealed that angiogenesis- and collagen regulation-related genes were specifically enriched in MCL cells. Furthermore, we identified age-related changes in cell composition and gene expression in the ligaments. This study delineates cellular heterogeneity in ligaments, serving as a foundation for identifying potential therapeutic targets for ligament injuries.
Project description:Disturbed blood flow (d-flow) has been known to induce changes of the cells in the arterial wall, increasing the risk of atherosclerosis. However, the heterogeneity of the vascular cell populations under d-flow remains less understood. To generate d-flow in vivo, partial carotid artery ligation (PCL) was performed. Seven days after ligation, single-cell RNA sequencing of nine left carotid arteries (LCA) from the PCL group (10,262 cells) or control group (14,580 cells) was applied and a single-cell atlas of gene expression was constructed. The integrated analysis identified 15 distinct carotid cell clusters, including 10 d-flow-relevant subpopulations. Among endothelial cells, at least four subpopulations were identified, including Klk8hi ECs, Lrp1hi ECs, Dkk2hi ECs, and Cd36hi ECs. Analysis of GSVA and single-cell trajectories indicated that the previously undescribed Dkk2hi ECs subpopulation was mechanosensitive and potentially transformed from Klk8hi ECs under d-flow. D-flow-induced Spp1hi VSMCs subpopulation that appeared to be endowed with osteoblast differentiation, suggesting a role in arterial stiffness. Among the infiltrating cell subpopulations, Trem2hi Mφ, Birc5hi Mφ, DCs, CD4+ T cells, CXCR6+ T cells, NK cells, and granulocytes were identified under d-flow. Of note, the novel Birc5hi Mφ was identified as a potential contributor to the accumulation of macrophages in atherosclerosis. Finally, Dkk2hi ECs, and Cd36hi ECs were also found in the proatherosclerotic area of the aorta where the d-flow occurs. In conclusion, we presented a comprehensive single-cell atlas of all cells in the carotid artery under d-flow, identified previously unrecognized cell subpopulations and their gene expression signatures, and suggested their specialized functions.
Project description:PurposeTo assess the diverse cell populations of human corpus cavernosum in patients with severe erectile dysfunction (ED) at the single-cell level.MethodsPenile tissues collected from three patients were subjected to single-cell RNA sequencing using the BD Rhapsody™ platform. Common bioinformatics tools were used to analyze cellular heterogeneity and gene expression profiles from generated raw data, including the packages Seurat, Monocle, and CellPhoneDB.ResultsDisease-related heterogeneity of cell types was determined in the cavernous tissue such as endothelial cells (ECs), smooth muscle cells, fibroblasts, and immune cells. Reclustering analysis of ECs identified an arteriole ECs subcluster and another one with gene signatures of fibroblasts. The proportion of fibroblasts was higher than the other cell populations and had the most significant cellular heterogeneity, in which a distinct subcluster co-expressed endothelial markers. The transition trajectory of differentiation from smooth muscle cells into fibroblasts was depicted using the pseudotime analysis, suggesting that the expansion of corpus cavernosum is possibly compromised as a result of fibrosis. Cell-cell communications among ECs, smooth muscle cells, fibroblasts, and macrophages were robust, which indicated that inflammation may also have a crucial role in the development of ED.ConclusionsOur study has demonstrated a comprehensive single-cell atlas of cellular components in human corpus cavernosum of ED, providing in-depth insights into the pathogenesis. Future research is warranted to explore disease-specific alterations for individualized treatment of ED.
Project description:Elevated blood pressure caused by excessive salt intake is common and associated with cardiovascular diseases in most countries. However, the composition and responses of vascular cells in the progression of hypertension have not been systematically described. We performed single-cell RNA sequencing on the aortic arch from C57BL/6J mice fed a chow/high-salt diet. We identified 19 distinct cell populations representing 12 lineages, including smooth muscle cells (SMCs), fibroblasts, endothelial cells (ECs), B cells, and T cells. During the progression of hypertension, the proportion of three SMC subpopulations, two EC subpopulations, and T cells increased. In two EC clusters, the expression of reactive oxygen species-related enzymes, collagen and contractility genes was upregulated. Gene set enrichment analysis showed that three SMC subsets underwent endothelial-to-mesenchymal transition. We also constructed intercellular networks and found more frequent cell communication among aortic cells in hypertension and that some signaling pathways were activated during hypertension. Finally, joint public genome-wide association study data and our single-cell RNA-sequencing data showed the expression of hypertension susceptibility genes in ECs, SMCs, and fibroblasts and revealed 21 genes involved in the initiation and development of high-salt-induced hypertension. In conclusion, our data illustrate the transcriptional landscape of vascular cells in the aorta associated with hypertension and reveal dramatic changes in cell composition and intercellular communication during the progression of hypertension.
Project description:Efficacy of immunotherapy in hepatocellular carcinoma (HCC) is blocked by its high degree of inter- and intra-tumor heterogeneity and immunosuppressive tumor microenvironment. However, the correlation between tumor heterogeneity and immunosuppressive microenvironment in HCC has not been well addressed. Here, we endeavored to dissect inter- and intra-tumor heterogeneity in HCC and uncover how they contribute to the immunosuppressive microenvironment. We performed consensus molecular subtyping with non-negative matrix factorization (NMF) clustering to stratify the inter-heterogeneity profile of HCC tumors. We grouped HCC tumors from the Cancer Genome Atlas (TCGA) patients into three subtypes (S1, S2 and S3), where S1 was characterized as a 'hot tumor' profile with high expression level of T cell genes and rate of immune scores. S2 was characterized as a 'cold tumor' profile with the highest tumor purity score, and S3 as an 'immunosuppressed tumor' profile with the poorest prognosis and a high expression level of immunosuppressive genes such as cytotoxic T-lymphocyte-associated protein-4, TIGIT, and PDCD1. Moreover, we combined weighted gene co-expression network analysis and single-cell regulatory network inference and clustering (SCENIC) in the single-cell dataset of the S3-like subtype (CS3) and identified a transcription factor, BATF, which could upregulate immunosuppressive genes. Finally, we identified a cell interaction network in which a myeloid-derived suppressor cell-like macrophage subtype could promote the formation of immunosuppressive T-cells.
Project description:Heart failure with preserved ejection fraction (HFpEF) represents a global health challenge, with limited therapies proven to enhance patient outcomes. This makes the elucidation of disease mechanisms and the identification of novel potential therapeutic targets a priority. Here, we performed RNA sequencing on ventricular myocardial biopsies from patients with HFpEF, prospecting to discover distinctive transcriptomic signatures. A total of 306 differentially expressed mRNAs (DEG) and 152 differentially expressed microRNAs (DEM) were identified and enriched in several biological processes involved in HF. Moreover, by integrating mRNA and microRNA expression data, we identified five potentially novel miRNA-mRNA relationships in HFpEF: the upregulated hsa-miR-25-3p, hsa-miR-26a-5p, and has-miR4429, targeting HAPLN1; and NPPB mRNA, targeted by hsa-miR-26a-5p and miR-140-3p. Exploring the predicted miRNA-mRNA interactions experimentally, we demonstrated that overexpression of the distinct miRNAs leads to the downregulation of their target genes. Interestingly, we also observed that microRNA signatures display a higher discriminative power to distinguish HFpEF sub-groups over mRNA signatures. Our results offer new mechanistic clues, which can potentially translate into new HFpEF therapies.