scholarly journals Cellular basis of omentum activation and expansion revealed by single-cell RNA sequencing using a parabiosis model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kazuhiko Ishigaki ◽  
Keiki Kumano ◽  
Kyohei Fujita ◽  
Hiroo Ueno
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Immune Cells ◽  
Physiological Function ◽  
Cell Types ◽  
Lineage Tracing ◽  
Mesenchymal Progenitors ◽  
Fluorescent Markers ◽  
Circulating Cells ◽  
Single Cell Rna Sequencing

AbstractAlthough the physiological function of the omentum remains elusive, it has been proposed that it plays an important role in fat storage, immune regulation, and regeneration of injured tissues and organs. Although the omentum undergoes expansion upon activation, reports on the accurate assessment of increased cell types and the origin of the increased cells remain limited. To investigate this aspect, the omenta of parabiotic mice were subjected to activation using distinct fluorescent markers and single-cell RNA sequencing (scRNA-seq) was performed to identify circulation-derived omental cells. We found that a considerable number of circulating cells contributed to the activation of the omentum. The omental cells derived from circulating cells exhibited morphological features similar to those of fibroblasts. scRNA-seq revealed the existence of a novel cell population that co-expressed macrophage and fibroblast markers in the activated omentum, suggesting that it corresponded to circulating macrophage-derived fibroblast-like cells. Lineage tracing experiments revealed that most fibroblasts in the activated omentum were not derived from WT1-positive mesenchymal progenitors. The cell cluster also expressed various chemokine genes, indicating its role in the activation and recruitment of immune cells. These results provide important information regarding the activation of the omentum.

scholarly journals Single‐cell RNA sequencing in cancer research

2021 ◽  
Vol 40 (1) ◽  
Author(s):  
Yijie Zhang ◽  
Dan Wang ◽  
Miao Peng ◽  
Le Tang ◽  
Jiawei Ouyang ◽  
...  
Keyword(s):  
Single Cell ◽  
Tumor Cells ◽  
Rna Sequencing ◽  
Immune Cells ◽  
Immune Escape ◽  
Tumor Development ◽  
Cell Types ◽  
Resistance Mechanisms ◽  
Single Cell Rna Sequencing ◽  
Tumor Research

AbstractSingle-cell RNA sequencing (scRNA-seq), a technology that analyzes transcriptomes of complex tissues at single-cell levels, can identify differential gene expression and epigenetic factors caused by mutations in unicellular genomes, as well as new cell-specific markers and cell types. scRNA-seq plays an important role in various aspects of tumor research. It reveals the heterogeneity of tumor cells and monitors the progress of tumor development, thereby preventing further cellular deterioration. Furthermore, the transcriptome analysis of immune cells in tumor tissue can be used to classify immune cells, their immune escape mechanisms and drug resistance mechanisms, and to develop effective clinical targeted therapies combined with immunotherapy. Moreover, this method enables the study of intercellular communication and the interaction of tumor cells and non-malignant cells to reveal their role in carcinogenesis. scRNA-seq provides new technical means for further development of tumor research and is expected to make significant breakthroughs in this field. This review focuses on the principles of scRNA-seq, with an emphasis on the application of scRNA-seq in tumor heterogeneity, pathogenesis, and treatment.

scholarly journals Lineage analysis reveals an endodermal contribution to the vertebrate pituitary

Science ◽  
2020 ◽  
Vol 370 (6515) ◽  
pp. 463-467 ◽  
Author(s):  
Peter Fabian ◽  
Kuo-Chang Tseng ◽  
Joanna Smeeton ◽  
Joseph J. Lancman ◽  
P. Duc Si Dong ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Endocrine Cell ◽  
Time Lapse ◽  
Cell Types ◽  
Lineage Tracing ◽  
Single Cell Rna Sequencing ◽  
Growth Metabolism ◽  
Time Lapse Imaging ◽  
Lineage Analysis

Vertebrate sensory organs arise from epithelial thickenings called placodes. Along with neural crest cells, cranial placodes are considered ectodermal novelties that drove evolution of the vertebrate head. The anterior-most placode generates the endocrine lobe [adenohypophysis (ADH)] of the pituitary, a master gland controlling growth, metabolism, and reproduction. In addition to known ectodermal contributions, we use lineage tracing and time-lapse imaging in zebrafish to identify an endodermal contribution to the ADH. Single-cell RNA sequencing of the adult pituitary reveals similar competency of endodermal and ectodermal epithelia to generate all endocrine cell types. Further, endoderm can generate a rudimentary ADH-like structure in the near absence of ectodermal contributions. The fish condition supports the vertebrate pituitary arising through interactions of an ancestral endoderm-derived proto-pituitary with newly evolved placodal ectoderm.

scholarly journals Cell subtypes and immune dysfunction in peritoneal fluid of endometriosis revealed by single-cell RNA-sequencing

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gen Zou ◽  
Jianzhang Wang ◽  
Xinxin Xu ◽  
Ping Xu ◽  
Libo Zhu ◽  
...  
Keyword(s):  
Dendritic Cells ◽  
Single Cell ◽  
Natural Killer ◽  
Rna Sequencing ◽  
Peritoneal Cavity ◽  
Immune Cells ◽  
Peritoneal Fluid ◽  
Control Sample ◽  
Immune Dysfunction ◽  
Single Cell Rna Sequencing

Abstract Background Endometriosis is a refractory and recurrent disease and it affects nearly 10% of reproductive-aged women and 40% of infertile patients. The commonly accepted theory for endometriosis is retrograde menstruation where endometrial tissues invade into peritoneal cavity and fail to be cleared due to immune dysfunction. Therefore, the comprehensive understanding of immunologic microenvironment of peritoneal cavity deserves further investigation for the previous studies mainly focus on one or several immune cells. Results High-quality transcriptomes were from peritoneal fluid samples of patients with endometriosis and control, and firstly subjected to 10 × genomics single-cell RNA-sequencing. We acquired the single-cell transcriptomes of 10,280 cells from endometriosis sample and 7250 cells from control sample with an average of approximately 63,000 reads per cell. A comprehensive map of overall cells in peritoneal fluid was first exhibited. We unveiled the heterogeneity of immune cells and discovered new cell subtypes including T cell receptor positive (TCR+) macrophages, proliferating macrophages and natural killer dendritic cells in peritoneal fluid, which was further verified by double immunofluorescence staining and flow cytometry. Pseudo-time analysis showed that the response of macrophages to the menstrual debris might follow the certain differentiation trajectory after endometrial tissues invaded into the peritoneal cavity, that is, from antigen presentation to pro-inflammation, then to chemotaxis and phagocytosis. Our analyses also mirrored the dysfunctions of immune cells including decreased phagocytosis and cytotoxic activity and elevated pro-inflammatory and chemotactic effects in endometriosis. Conclusion TCR+ macrophages, proliferating macrophages and natural killer dendritic cells are firstly reported in human peritoneal fluid. Our results also revealed that immune dysfunction happens in peritoneal fluid of endometriosis, which may be responsible for the residues of invaded menstrual debris. It provided a large-scale and high-dimensional characterization of peritoneal microenvironment and offered a useful resource for future development of immunotherapy.

scholarly journals Single-cell data clustering based on sparse optimization and low-rank matrix factorization

2021 ◽  
Author(s):  
Yinlei Hu ◽  
Bin Li ◽  
Falai Chen ◽  
Kun Qu
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Matrix Factorization ◽  
Data Clustering ◽  
Cell Types ◽  
Low Rank ◽  
Sequencing Data ◽  
Rank Matrix ◽  
Single Cell Rna Sequencing ◽  
Low Rank Matrix

Abstract Unsupervised clustering is a fundamental step of single-cell RNA sequencing data analysis. This issue has inspired several clustering methods to classify cells in single-cell RNA sequencing data. However, accurate prediction of the cell clusters remains a substantial challenge. In this study, we propose a new algorithm for single-cell RNA sequencing data clustering based on Sparse Optimization and low-rank matrix factorization (scSO). We applied our scSO algorithm to analyze multiple benchmark datasets and showed that the cluster number predicted by scSO was close to the number of reference cell types and that most cells were correctly classified. Our scSO algorithm is available at https://github.com/QuKunLab/scSO. Overall, this study demonstrates a potent cell clustering approach that can help researchers distinguish cell types in single-cell RNA sequencing data.

scholarly journals Sample processing and single cell RNA-sequencing of peripheral blood immune cells from COVID-19 patients

2021 ◽  
pp. 100582
Author(s):  
Changfu Yao ◽  
Stephanie A. Bora ◽  
Peter Chen ◽  
Helen S. Goodridge ◽  
Sina A. Gharib
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Immune Cells ◽  
Peripheral Blood ◽  
Sample Processing ◽  
Single Cell Rna Sequencing

Abstract 305: Single Cell RNA Sequencing of Adult Cardiac c-kit+ Cells in a Murine Lineage Tracing Model

2015 ◽  
Vol 117 (suppl_1) ◽  
Author(s):  
Bryan D Maliken ◽  
Onur Kanisicak ◽  
Jeffery D Molkentin
Keyword(s):  
Single Cell ◽  
Progenitor Cells ◽  
Rna Sequencing ◽  
Cardiac Injury ◽  
Mesenchymal Cells ◽  
Lineage Tracing ◽  
Tyrosine Kinase Receptor ◽  
Early Differentiation ◽  
Gfp Reporter ◽  
Single Cell Rna Sequencing

A subset of adult cardiac resident cells defined by the stem cell factor tyrosine kinase receptor termed c-kit, are believed to have myogenic potential and are now being delivered via intracoronary infusion to presumably promote cardiac regeneration and improve ventricular function after ischemic cardiac injury. However, recent studies have shown that despite these benefits, c-kit+ progenitor cells in the adult murine heart are more inclined to take on an endothelial rather than cardiomyocyte lineage. To better define the factors involved in early differentiation of these resident cardiac progenitor cells and to distinguish distinct cell subpopulations, we performed single cell RNA sequencing on c-kit+ cells from Kit-Cre lineage traced GFP reporter mice versus total mesenchymal cells from the heart that were CD31- and CD45-. Cells were isolated by cardiac digestion and FACS was performed, positively sorting for the c-kit+ lineage while negatively sorting for CD31 and CD45 to eliminate endothelial and leukocyte progenitor contamination, respectively. Following this isolation, cells were examined to determine GFP reporter status and then submitted for single cell RNA sequencing using the Fluidigm A1 system. Clustering of 654 genes from this data identified 6 distinct subpopulations indicating various stages of early differentiation among CD31- and CD45-negative cardiac interstitial cells. Furthermore, comparison of GFP+ c-kit cells to the total non-GFP mesenchymal cells identified 75 differentially expressed transcripts. These unique gene signatures may help parse the genes that underlie cellular plasticity in the heart and define the best molecular lineages for transdifferentiation into cardiac myocytes.

Multi tissue processing for single cell sequencing of human immune cells v1

2021 ◽  
Author(s):  
Daniel Rainbow ◽  
Sarah Howlett ◽  
Lorna Jarvis ◽  
Joanne Jones
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Immune Cells ◽  
Human Tissues ◽  
Single Cell Sequencing ◽  
Tissue Processing ◽  
Simultaneous Processing ◽  
Single Cell Rna Sequencing ◽  
Human Immune

This protocol has been developed for the simultaneous processing of multiple human tissues to extract immune cells for single cell RNA sequencing using the 10X platform, and ideal for atlasing projects. Included in this protocol are the steps needed to go from tissue to loading the 10X Chromium for single cell RNA sequencing and includes the hashtag and CiteSeq labelling of cells as well as the details needed to stimulate cells with PMA+I.

scholarly journals Single cell RNA sequencing of the Strongylocentrotus purpuratus larva reveals the blueprint of major cell types and nervous system of a non-chordate deuterostome

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Periklis Paganos ◽  
Danila Voronov ◽  
Jacob M Musser ◽  
Detlev Arendt ◽  
Maria Ina Arnone
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Sea Urchin ◽  
Regulatory Networks ◽  
Sea Urchins ◽  
Neuronal Cell ◽  
Cell Types ◽  
Molecular Fingerprint ◽  
Larval Body ◽  
Single Cell Rna Sequencing

Identifying the molecular fingerprint of organismal cell types is key for understanding their function and evolution. Here, we use single cell RNA sequencing (scRNA-seq) to survey the cell types of the sea urchin early pluteus larva, representing an important developmental transition from non-feeding to feeding larva. We identify 21 distinct cell clusters, representing cells of the digestive, skeletal, immune, and nervous systems. Further subclustering of these reveal a highly detailed portrait of cell diversity across the larva, including the identification of neuronal cell types. We then validate important gene regulatory networks driving sea urchin development and reveal new domains of activity within the larval body. Focusing on neurons that co-express Pdx-1 and Brn1/2/4, we identify an unprecedented number of genes shared by this population of neurons in sea urchin and vertebrate endocrine pancreatic cells. Using differential expression results from Pdx-1 knockdown experiments, we show that Pdx1 is necessary for the acquisition of the neuronal identity of these cells. We hypothesize that a network similar to the one orchestrated by Pdx1 in the sea urchin neurons was active in an ancestral cell type and then inherited by neuronal and pancreatic developmental lineages in sea urchins and vertebrates.

Localization of migraine susceptibility genes in human brain by single-cell RNA sequencing

Cephalalgia ◽  
2018 ◽  
Vol 38 (13) ◽  
pp. 1976-1983 ◽  
Author(s):  
William Renthal
Keyword(s):  
Human Brain ◽  
Single Cell ◽  
Rna Sequencing ◽  
Expression Profiles ◽  
Cell Types ◽  
Susceptibility Genes ◽  
Brain Cell ◽  
Cell Type ◽  
Single Cell Rna Sequencing ◽  
Brain Cell Types

Background Migraine is a debilitating disorder characterized by severe headaches and associated neurological symptoms. A key challenge to understanding migraine has been the cellular complexity of the human brain and the multiple cell types implicated in its pathophysiology. The present study leverages recent advances in single-cell transcriptomics to localize the specific human brain cell types in which putative migraine susceptibility genes are expressed. Methods The cell-type specific expression of both familial and common migraine-associated genes was determined bioinformatically using data from 2,039 individual human brain cells across two published single-cell RNA sequencing datasets. Enrichment of migraine-associated genes was determined for each brain cell type. Results Analysis of single-brain cell RNA sequencing data from five major subtypes of cells in the human cortex (neurons, oligodendrocytes, astrocytes, microglia, and endothelial cells) indicates that over 40% of known migraine-associated genes are enriched in the expression profiles of a specific brain cell type. Further analysis of neuronal migraine-associated genes demonstrated that approximately 70% were significantly enriched in inhibitory neurons and 30% in excitatory neurons. Conclusions This study takes the next step in understanding the human brain cell types in which putative migraine susceptibility genes are expressed. Both familial and common migraine may arise from dysfunction of discrete cell types within the neurovascular unit, and localization of the affected cell type(s) in an individual patient may provide insight into to their susceptibility to migraine.

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