Application Of Single-cell RNA Sequencing Research Articles

ScRNA-seq transcriptomic profiling of irradiated mouse skin reveals altered cell types, pathways, and cell-cell interactions

ObjectiveTo investigate the substantial changes in cell types, pathways, and cell-cell interactions occurring in the irradiation-induced alopecia and dermatitis (IRIAD) mouse model and to identify potential targets for patients experiencing skin adverse reactions to radiotherapy. MethodsMice were irradiated at 15 ​Gy, targeting the head and neck region. After a 14-day interval, living cells were extracted from both wild-type (WT) mice and irradiated mice for single-cell RNA sequencing (scRNA-seq). The scRNA-seq data, retrieved from the GEO database (GSE201447), underwent stringent quality control using the Seurat (v4.3.0) R package. Cell type annotation relied on previously reported typical markers and CellMarker 2.0. Differentially expressed genes were calculated to perform gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Cell-cell interactions were evaluated using the Cellchat R package. ResultsThe application of single-cell RNA sequencing (scRNA-seq) enabled a comprehensive characterization of the intricate cellular composition of both wild-type (WT) and irradiated mice skin. Remarkably, cells within irradiated mice skin exhibited a significant alteration in the intensity of cell-cell interactions compared to their wild-type counterparts. This change in interaction intensity was observed across various cell types, including fibroblast cells, endothelial cells, and dendritic cells. Importantly, these "interacting cells" shared common signaling pathways, notably the upregulation of the IL-17 pathway following irradiation. ConclusionsThe modification of intercellular communication induced by irradiation primarily involves fibroblast cells, endothelial cells, and various types of immune cells. This investigation provides a novel perspective on potential targets and holds promise for enhancing the clinical management of IRIAD.

Advancing parathyroid anatomy understanding through single-cell RNA sequencing in uremic secondary hyperparathyroidism

This commentary explores the recent application of single-cell RNA sequencing in the study of uremic secondary hyperparathyroidism, shedding light on the cellular dynamics within parathyroid glands. The use of single-cell RNA sequencing reveals new insights into the differentiation processes of chief and oxyphil cells, challenging traditional views and highlighting the potential of this technology in advancing our understanding of parathyroid anatomy.

Single-Cell Transcriptome Analysis of Acute Myeloid Leukemia Cells Using Methanol Fixation and Cryopreservation.

The application of single-cell RNA sequencing has greatly improved our understanding of various cellular and molecular mechanisms involved in physiological and pathophysiological processes. However, obtaining living cells for this technique can be difficult under certain conditions. To solve this problem, the methanol fixation method appeared as a promising alternative for routine clinical use. In this study, we selected two AML samples that had been fixed in methanol for 12-18 months. Once the cells were rehydrated, these samples were subjected to single-cell RNA sequencing. We then compared the results obtained from these samples with those obtained from the same samples cryopreserved in DMSO. We used a previously validated methanol fixation protocol to perform scRNA-seq on DMSO cryopreserved cells and cells fixed in methanol for more than one year. Preliminary results show that methanol fixation induces some genetic and transcriptional modification compared with DMSO cryopreservation but remains a valuable method for single-cell analysis of primary human leukemia cells. The initial findings from this study highlight certain resemblances in methanol fixation over a 12-month period and cryopreservation with DMSO, along with associated transcriptional level modifications. However, we observed genetic degradation in the fixation condition when extending beyond one year. Despite certain study limitations, it is evident that short-term methanol fixation can be effectively used for leukemia blast samples. Its ease of implementation holds the potential to simplify the integration of this technique into routine clinical practice.

Spatial transcriptomic interrogation of the murine bone marrow signaling landscape

Self-renewal and differentiation of skeletal stem and progenitor cells (SSPCs) are tightly regulated processes, with SSPC dysregulation leading to progressive bone disease. While the application of single-cell RNA sequencing (scRNAseq) to the bone field has led to major advancements in our understanding of SSPC heterogeneity, stem cells are tightly regulated by their neighboring cells which comprise the bone marrow niche. However, unbiased interrogation of these cells at the transcriptional level within their native niche environment has been challenging. Here, we combined spatial transcriptomics and scRNAseq using a predictive modeling pipeline derived from multiple deconvolution packages in adult mouse femurs to provide an endogenous, in vivo context of SSPCs within the niche. This combined approach localized SSPC subtypes to specific regions of the bone and identified cellular components and signaling networks utilized within the niche. Furthermore, the use of spatial transcriptomics allowed us to identify spatially restricted activation of metabolic and major morphogenetic signaling gradients derived from the vasculature and bone surfaces that establish microdomains within the marrow cavity. Overall, we demonstrate, for the first time, the feasibility of applying spatial transcriptomics to fully mineralized tissue and present a combined spatial and single-cell transcriptomic approach to define the cellular components of the stem cell niche, identify cell‒cell communication, and ultimately gain a comprehensive understanding of local and global SSPC regulatory networks within calcified tissue.

Single-cell RNA sequencing technology in human spermatogenesis: Progresses and perspectives.

Spermatogenesis, a key part of the spermiation process, is regulated by a combination of key cells, such as primordial germ cells, spermatogonial stem cells, and somatic cells, such as Sertoli cells. Abnormal spermatogenesis can lead to azoospermia, testicular tumors, and other diseases related to male infertility. The application of single-cell RNA sequencing (scRNA-seq) technology in male reproduction is gradually increasing with its unique insight into deep mining and analysis. The data cover different periods of neonatal, prepubertal, pubertal, and adult stages. Different types of male infertility diseases including obstructive and non-obstructive azoospermia (NOA), Klinefelter Syndrome (KS), Sertoli Cell Only Syndrome (SCOS), and testicular tumors are also covered. We briefly review the principles and application of scRNA-seq and summarize the research results and application directions in spermatogenesis in different periods and pathological states. Moreover, we discuss the challenges of applying this technology in male reproduction and the prospects of combining it with other technologies.

Macrophage heterogeneity role in NAFLD and NASH disease progression

Nonalcoholic fatty liver disease (NAFLD) is a type of metabolic stress liver injury that is closely associated with insulin resistance and genetic susceptibility. The continuum of liver injury in NAFLD can range from nonalcoholic fatty liver (NAFL) to nonalcoholic steatohepatitis (NASH) and even lead to cirrhosis and liver cancer. The pathogenesis of NAFLD is complicated. Pro-inflammatory cytokines, lipotoxicity, and gut bacterial metabolites play a key role in activating liver-resident macrophages (Kupffer cells, KCs) and recruiting circulating monocyte-derived macrophages (MoDMacs) to deposit fat in the liver. With the application of single-cell RNA-sequencing, significant heterogeneity in hepatic macrophages has been revealed, suggesting that KCs and MoDMacs located in the liver exert distinct functions in regulating liver inflammation and NASH progression. This study focuses on the role of macrophage heterogeneity in the development and occurrence of NAFLD and NASH, in view of the fact that innate immunity plays a key role in the development of NAFLD.

Single-cell transcriptomics of pathological pregnancies

Pregnancy is a complicated process involving various anatomical and physiological changes to provide a suitable environment for fetal development, to meet the increased metabolic demands, and to prepare for labor. While most pregnancies and births are uneventful, all pregnancies are at risk of complications. No less than 15% of all pregnant women develop a potentially lifethreatening complication or may also experience an unpleasant outcome. Conventional sequencing has been widely used in this field for diagnoses and treatment planning. However, it lacks the precise resolution to identify transcriptomic variation between the nearby cell types. Single-cell RNA sequencing is a novel approach that through single-cell isolation, transcript capturing, and development and sequencing of expression libraries allows the assessments of fundamental biological properties of cell populations and biological systems at unprecedented resolution. The single-cell sequencing technology is a powerful tool for investigating cell distribution and cell-to-cell relationships in human reproduction. Since 2016, the technique has contributed to the discovery of many transcriptomic atlases of human embryos, placenta, decidua, and endometrium and the identification of various crucial regulatory pathways in fetal development. Here, we briefly describe the application of single-cell RNA sequencing in the studies of physiological processes and pathological mechanisms of pregnancy.

Cellular complexity of the peripheral nervous system: Insights from single-cell resolution.

Single-cell RNA sequencing allows the division of cell populations, offers precise transcriptional profiling of individual cells, and fundamentally advances the comprehension of cellular diversity. In the peripheral nervous system (PNS), the application of single-cell RNA sequencing identifies multiple types of cells, including neurons, glial cells, ependymal cells, immune cells, and vascular cells. Sub-types of neurons and glial cells have further been recognized in nerve tissues, especially tissues in different physiological and pathological states. In the current article, we compile the heterogeneities of cells that have been reported in the PNS and describe cellular variability during development and regeneration. The discovery of the architecture of peripheral nerves benefits the understanding of the cellular complexity of the PNS and provides a considerable cellular basis for future genetic manipulation.

The Application of Single-Cell RNA Sequencing in the Inflammatory Tumor Microenvironment.

The initiation and progression of tumors are complex. The cancer evolution-development hypothesis holds that the dysregulation of immune balance is caused by the synergistic effect of immune genetic factors and environmental factors that stimulate and maintain non-resolving inflammation. Throughout the cancer development process, this inflammation creates a microenvironment for the evolution and development of cancer. Research on the inflammatory tumor microenvironment (TME) explains the initiation and progression of cancer and guides anti-cancer immunotherapy. Single-cell RNA sequencing (scRNA-seq) can detect the transcription levels of cells at the single-cell resolution level, reveal the heterogeneity and evolutionary trajectory of infiltrated immune cells and cancer cells, and provide insight into the composition and function of each cell group in the inflammatory TME. This paper summarizes the application of scRNA-seq in inflammatory TME.

Preliminary Results of Single-cell Transcriptome Sequencing in Renal Arterial Lesions of Takayasu Arteritis

Objective To explore the preliminary application of single-cell RNA sequencing (scRNA-seq) in the renal arterial lesions in Takayasu arteritis (TA) patients. Methods This study included 2 TA patients with renal artery stenosis treated by bypass surgery in the Department of Vascular Surgery,Beijing Hospital.The obtained 2 renal artery samples were digested with two different protocols (GEXSCOPE kit and self-made digestion liquid) before scRNA-seq and bioinformatics analysis. Results A total of 2920 cells were obtained for further analysis.After unbiased cluster analysis,2 endothelial cell subsets,2 smooth muscle cell subsets,1 fibroblast subset,2 mononuclear macrophage subsets,1 T cell subset,and 1 undefined cell subset were identified.Among them,the two subsets of smooth muscle cells were contractile and secretory,respectively.The results of scRNA-seq indicated that enzymatic hydrolysis with GEXSCOPE kit produced a large number of endothelial cells (57.46%) and a small number of immune cells (13.21%).However,immune cells (34.64%) were dominant in the cells obtained by enzymatic hydrolysis with self-made digestive liquid. Conclusion scRNA-seq can be employed to explore the cellular heterogeneity of diseased vessels in TA patients.Different enzymatic digestion protocols may impact the proportion of different cells.

Application of single-cell RNA sequencing on human testicular samples: a comprehensive review.

So far there has been no comprehensive review using systematic literature search strategies to show the application of single-cell RNA sequencing (scRNA-seq) in the human testis of the whole life cycle (from embryos to aging males). Here, we summarized the application of scRNA-seq analyses on various human testicular biological samples. A systematic search was conducted in PubMed and Gene Expression Omnibus (GEO), focusing on English researches published after 2009. Articles related to GEO data-series were also retrieved in PubMed or BioRxiv. 81 full-length studies were finally included in the review. ScRNA-seq has been widely used on different human testicular samples with various library strategies, and new cell subtypes such as State 0 spermatogonial stem cells (SSC) and stage_a/b/c Sertoli cells (SC) were identified. For the development of normal testes, scRNA-seq-based evidence showed dynamic transcriptional changes of both germ cells and somatic cells from embryos to adults. And dysregulated metabolic signaling or hedgehog signaling were revealed by scRNA-seq in aged SC or Leydig cells (LC), respectively. For infertile males, scRNA-seq studies revealed profound changes of testes, such as the increased proportion of immature SC/LC of Klinefelter syndrome, the somatic immaturity and altered germline autophagy of patients with non-obstructive azoospermia, and the repressed differentiation of SSC in trans-females receiving testosterone inhibition therapy. Besides, the re-analyzing of public scRNA-seq data made further discoveries such as the potential vulnerability of testicular SARS-CoV-2 infection, and both evolutionary conservatism and divergence among species. ScRNA-seq analyses would unveil mechanisms of testes' development and changes so as to help developing novel treatments for male infertility.

Application of single-cell RNA sequencing in head and neck squamous cell carcinoma.

Single-cell RNA sequencing has been broadly applied to head and neck squamous cell carcinoma (HNSCC) for characterizing the heterogeneity and genomic mutations of HNSCC benefiting from the advantage of single-cell resolution. We summarized most of the current studies and aimed to explore their research methods and ideas, as well as how to transform them into clinical applications. Through single-cell RNA sequencing, we found the differences in tumor cells' expression programs and differentiation tracks. The studies of immune microenvironment allowed us to distinguish immune cell subpopulations, the extensive expression of immune checkpoints, and the complex crosstalk network between immune cells and non-immune cells. For cancer-associated fibroblasts (CAFs), single-cell RNA sequencing had made an irreplaceable contribution to the exploration of their differentiation status, specific CAFs markers, and the interaction with tumor cells and immune cells. In addition, we demonstrated in detail how single-cell RNA sequencing explored the HNSCC epithelial-to-mesenchymal transition (EMT) model and the mechanism of drug resistance, as well as its clinical value.

Application of Single-Cell RNA Sequencing in Ovarian Development

The ovary is a female reproductive organ that plays a key role in fertility and the maintenance of endocrine homeostasis, which is of great importance to women's health. It is characterized by a high heterogeneity, with different cellular subpopulations primarily containing oocytes, granulosa cells, stromal cells, endothelial cells, vascular smooth muscle cells, and diverse immune cell types. Each has unique and important functions. From the fetal period to old age, the ovary experiences continuous structural and functional changes, with the gene expression of each cell type undergoing dramatic changes. In addition, ovarian development strongly relies on the communication between germ and somatic cells. Compared to traditional bulk RNA sequencing techniques, the single-cell RNA sequencing (scRNA-seq) approach has substantial advantages in analyzing individual cells within an ever-changing and complicated tissue, classifying them into cell types, characterizing single cells, delineating the cellular developmental trajectory, and studying cell-to-cell interactions. In this review, we present single-cell transcriptome mapping of the ovary, summarize the characteristics of the important constituent cells of the ovary and the critical cellular developmental processes, and describe key signaling pathways for cell-to-cell communication in the ovary, as revealed by scRNA-seq. This review will undoubtedly improve our understanding of the characteristics of ovarian cells and development, thus enabling the identification of novel therapeutic targets for ovarian-related diseases.

A First Step Toward a Cross-tissue Atlas of Immune Cells in Humans.

A First Step Toward a Cross-tissue Atlas of Immune Cells in Humans.

Advances in application of single-cell RNA sequencing in cardiovascular research.

Single-cell RNA sequencing (scRNA-seq) provides high-resolution information on transcriptomic changes at the single-cell level, which is of great significance for distinguishing cell subtypes, identifying stem cell differentiation processes, and identifying targets for disease treatment. In recent years, emerging single-cell RNA sequencing technologies have been used to make breakthroughs regarding decoding developmental trajectories, phenotypic transitions, and cellular interactions in the cardiovascular system, providing new insights into cardiovascular disease. This paper reviews the technical processes of single-cell RNA sequencing and the latest progress based on single-cell RNA sequencing in the field of cardiovascular system research, compares single-cell RNA sequencing with other single-cell technologies, and summarizes the extended applications and advantages and disadvantages of single-cell RNA sequencing. Finally, the prospects for applying single-cell RNA sequencing in the field of cardiovascular research are discussed.

Using Single Cell Transcriptomics to Elucidate the Myeloid Compartment in Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a dismal disease with a 5-year survival rate of 10%. A hallmark feature of this disease is its abundant microenvironment which creates a highly immunosuppressive milieu. This is, in large part, mediated by an abundant infiltration of myeloid cells in the PDAC tumor microenvironment. Consequently, therapies that modulate myeloid function may augment the efficacy of standard of care for PDAC. Unfortunately, there is limited understanding about the various subsets of myeloid cells in PDAC, particularly in human studies. This review highlights the application of single-cell RNA sequencing to define the myeloid compartment in human PDAC and elucidate the crosstalk between myeloid cells and the other components of the tumor immune microenvironment.

Pathological Osteoclasts and Precursor Macrophages in Inflammatory Arthritis.

Macrophages comprise a variety of subsets with diverse biological functions, including inflammation, tissue repair, regeneration, and fibrosis. In the bone marrow, macrophages differentiate into multinucleated osteoclasts, which have a unique bone-destroying capacity and play key roles in physiological bone remodelling. In contrast, osteoclasts are also involved in inflammatory bone erosion in arthritis and it has been unclear whether the osteoclasts in different tissue settings arise from similar monocytoid precursors and share similar phenotypes. Rapid progresses in the sequencing technologies have provided many important insights regarding the heterogeneity of different types of osteoclasts. The application of single-cell RNA sequencing (scRNA-seq) to the osteoclast precursor-containing macrophages enabled to identify the specific subpopulation differentiating into pathological mature osteoclasts in joints. Furthermore, an intravital imaging technology using two-photon microscopy has succeeded in visualizing the real-time dynamics of immune cells in the synovial microenvironment. These technologies together contributed to characterize the unique macrophages in the inflamed synovium, termed “arthritis-associated osteoclastogenic macrophages (AtoMs)”, causing the pathological bone destruction in inflammatory arthritis. Here, we review and discuss how novel technologies help to better understand the role of macrophages in inflammatory arthritis, especially focusing of osteoclastogenesis at the pannus-bone interface.

Fetal vs adult megakaryopoiesis

AbstractFetal and neonatal megakaryocyte progenitors are hyperproliferative compared with adult progenitors and generate a large number of small, low-ploidy megakaryocytes. Historically, these developmental differences have been interpreted as “immaturity.” However, more recent studies have demonstrated that the small, low-ploidy fetal and neonatal megakaryocytes have all the characteristics of adult polyploid megakaryocytes, including the presence of granules, a well-developed demarcation membrane system, and proplatelet formation. Thus, rather than immaturity, the features of fetal and neonatal megakaryopoiesis reflect a developmentally unique uncoupling of proliferation, polyploidization, and cytoplasmic maturation, which allows fetuses and neonates to populate their rapidly expanding bone marrow and blood volume. At the molecular level, the features of fetal and neonatal megakaryopoiesis are the result of a complex interplay of developmentally regulated pathways and environmental signals from the different hematopoietic niches. Over the past few years, studies have challenged traditional paradigms about the origin of the megakaryocyte lineage in both fetal and adult life, and the application of single-cell RNA sequencing has led to a better characterization of embryonic, fetal, and adult megakaryocytes. In particular, a growing body of data suggests that at all stages of development, the various functions of megakaryocytes are not fulfilled by the megakaryocyte population as a whole, but rather by distinct megakaryocyte subpopulations with dedicated roles. Finally, recent studies have provided novel insights into the mechanisms underlying developmental disorders of megakaryopoiesis, which either uniquely affect fetuses and neonates or have different clinical presentations in neonatal compared with adult life.

Benchmarking of a Bayesian single cell RNAseq differential gene expression test for dose-response study designs.

The application of single-cell RNA sequencing (scRNAseq) for the evaluation of chemicals, drugs, and food contaminants presents the opportunity to consider cellular heterogeneity in pharmacological and toxicological responses. Current differential gene expression analysis (DGEA) methods focus primarily on two group comparisons, not multi-group dose–response study designs used in safety assessments. To benchmark DGEA methods for dose–response scRNAseq experiments, we proposed a multiplicity corrected Bayesian testing approach and compare it against 8 other methods including two frequentist fit-for-purpose tests using simulated and experimental data. Our Bayesian test method outperformed all other tests for a broad range of accuracy metrics including control of false positive error rates. Most notable, the fit-for-purpose and standard multiple group DGEA methods were superior to the two group scRNAseq methods for dose–response study designs. Collectively, our benchmarking of DGEA methods demonstrates the importance in considering study design when determining the most appropriate test methods.

FSCAM: CAM-Based Feature Selection for Clustering scRNA-seq.

Cell type determination based on transcriptome profiles is a key application of single-cell RNA sequencing (scRNA-seq). It is usually achieved through unsupervised clustering. Good feature selection is capable of improving the clustering accuracy and is a crucial component of single-cell clustering pipelines. However, most current single-cell feature selection methods are univariable filter methods ignoring gene dependency. Even the multivariable filter methods developed in recent years only consider "one-to-many" relationship between genes. In this paper, a novel single-cell feature selection method based on convex analysis of mixtures (FSCAM) is proposed, which takes into account "many-to-many" relationship. Compared to the previous "one-to-many" methods, FSCAM selects genes with a combination of relevancy, redundancy and completeness. Pertinent benchmarking is conducted on the real datasets to validate the superiority of FSCAM. Through plugging into the framework of partition around medoids (PAM) clustering, a single-cell clustering algorithm based on FSCAM method (SCC_FSCAM) is further developed. Comparing SCC_FSCAM with existing advanced clustering algorithms, the results show that our algorithm has advantages in both internal criteria (clustering number) and external criteria (adjusted Rand index) and has a good stability.