Single-cell RNA-sequencing reveals profound changes in circulating immune cells in patients with heart failure

2020 ◽  
Author(s):  
Wesley T Abplanalp ◽  
David John ◽  
Sebastian Cremer ◽  
Birgit Assmus ◽  
Lena Dorsheimer ◽  
...  
Keyword(s):  
Heart Failure ◽  
Flow Cytometry ◽  
Single Cell ◽  
Rna Sequencing ◽  
Immune Cells ◽  
Healthy Subjects ◽  
Patients With Heart Failure ◽  
Single Cell Rna Sequencing ◽  
The Impact ◽  
Classical Monocytes

Abstract Aims Identification of signatures of immune cells at single-cell level may provide novel insights into changes of immune-related disorders. Therefore, we used single-cell RNA-sequencing to determine the impact of heart failure on circulating immune cells. Methods and results We demonstrate a significant change in monocyte to T-cell ratio in patients with heart failure, compared to healthy subjects, which were validated by flow cytometry analysis. Subclustering of monocytes and stratification of the clusters according to relative CD14 and FCGR3A (CD16) expression allowed annotation of classical, intermediate, and non-classical monocytes. Heart failure had a specific impact on the gene expression patterns in these subpopulations. Metabolically active genes such as FABP5 were highly enriched in classical monocytes of heart failure patients, whereas β-catenin expression was significantly higher in intermediate monocytes. The selective regulation of signatures in the monocyte subpopulations was validated by classical and multifactor dimensionality reduction flow cytometry analyses. Conclusion Together this study shows that circulating cells derived from patients with heart failure have altered phenotypes. These data provide a rich source for identification of signatures of immune cells in heart failure compared to healthy subjects. The observed increase in FABP5 and signatures of Wnt signalling may contribute to enhanced monocyte activation.

scholarly journals Clonal Hematopoiesis-Driver DNMT3A Mutations Alter Immune Cells in Heart Failure

2020 ◽  
Author(s):  
Wesley T Abplanalp ◽  
Sebastian Cremer ◽  
David John ◽  
Jedrzej Hoffmann ◽  
Bianca Schuhmacher ◽  
...  
Keyword(s):  
Heart Failure ◽  
T Cell ◽  
Chronic Heart Failure ◽  
Single Cell ◽  
Rna Sequencing ◽  
Immune Cells ◽  
Driver Mutations ◽  
Clonal Hematopoiesis ◽  
Mutation Carriers ◽  
Single Cell Rna Sequencing

Rationale: Clonal hematopoiesis (CH) driven by mutations of DNA methyltransferase 3a (DNMT3A) is associated with increased incidence of cardiovascular disease and poor prognosis of patients with chronic heart failure (HF) and aortic stenosis. Although experimental studies suggest that DNMT3A CH-driver mutations may enhance inflammation, specific signatures of inflammatory cells in humans are missing. Objective: To define subsets of immune cells mediating inflammation in humans using single-cell RNA-sequencing. Methods and Results: Transcriptomic profiles of peripheral blood mononuclear cells were analysed in N=6 HF patients harboring DNMT3A CH-driver mutations and N=4 patients with HF and no DNMT3A mutations by single-cell RNA-sequencing. Monocytes of HF patients carrying DNMT3A mutations demonstrated a significantly increased expression of inflammatory genes compared to monocytes derived from HF patients without DNMT3A mutations. Among the specific up-regulated genes were the prototypic inflammatory interleukin (IL) IL1B, IL6, IL8, the inflammasome NLRP3, and the macrophage inflammatory proteins CCL3 and CCL4 as well as resistin, which augments monocyte-endothelial adhesion. Silencing of DNMT3A in monocytes induced a paracrine pro-inflammatory activation and increased adhesion to endothelial cells. Furthermore, the classical monocyte subset of DNMT3A mutation carriers showed increased expression of T-cell stimulating immunoglobulin superfamily members CD300LB, CD83, SIGLEC12, as well as the CD2 ligand and cell adhesion molecule CD58, all of which may be involved in monocyte-T cell interactions. DNMT3A mutation carriers were further characterized by increased expression of the T-cell alpha receptor constant chain and Th1, Th2, Th17, CD8+ effector, CD4+ memory and Treg specific signatures. Conclusions: This study demonstrates that circulating monocytes and T-cells of HF patients harboring CH-driver mutations in DNMT3A exhibit a highly inflamed transcriptome, which may contribute to the aggravation of chronic heart failure.

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 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

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 Quality assessment of single-cell RNA sequencing data by coverage skewness analysis

2019 ◽  
Author(s):  
Imad Abugessaisa ◽  
Shuhei Noguchi ◽  
Melissa Cardon ◽  
Akira Hasegawa ◽  
Kazuhide Watanabe ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Single Cell ◽  
Rna Sequencing ◽  
Single Cells ◽  
Assessment Method ◽  
Poor Quality ◽  
Sequencing Data ◽  
Single Cell Rna Sequencing ◽  
Gene Coverage ◽  
The Impact

AbstractAnalysis and interpretation of single-cell RNA-sequencing (scRNA-seq) experiments are compromised by the presence of poor quality cells. For meaningful analyses, such poor quality cells should be excluded to avoid biases and large variation. However, no clear guidelines exist. We introduce SkewC, a novel quality-assessment method to identify poor quality single-cells in scRNA-seq experiments. The method is based on the assessment of gene coverage for each single cell and its skewness as a quality measure. To validate the method, we investigated the impact of poor quality cells on downstream analyses and compared biological differences between typical and poor quality cells. Moreover, we measured the ratio of intergenic expression, suggesting genomic contamination, and foreign organism contamination of single-cell samples. SkewC is tested in 37,993 single-cells generated by 15 scRNA-seq protocols. We envision SkewC as an indispensable QC method to be incorporated into scRNA-seq experiment to preclude the possibility of scRNA-seq data misinterpretation.

scholarly journals Single-Cell RNA Sequencing Reveals the Expansion of Cytotoxic CD4+ T Lymphocytes and a Landscape of Immune Cells in Primary Sjögren’s Syndrome

2021 ◽  
Vol 11 ◽  
Author(s):  
Xiaoping Hong ◽  
Shuhui Meng ◽  
Donge Tang ◽  
Tingting Wang ◽  
Liping Ding ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
T Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Immune Cell ◽  
Susceptibility Genes ◽  
Primary Sjögren’S Syndrome ◽  
Healthy Controls ◽  
Immune Cell Subsets ◽  
Single Cell Rna Sequencing

ObjectivePrimary Sjögren’s syndrome (pSS) is a systemic autoimmune disease, and its pathogenetic mechanism is far from being understood. In this study, we aimed to explore the cellular and molecular mechanisms that lead to pathogenesis of this disease.MethodsWe applied single-cell RNA sequencing (scRNA-seq) to 57,288 peripheral blood mononuclear cells (PBMCs) from five patients with pSS and five healthy controls. The immune cell subsets and susceptibility genes involved in the pathogenesis of pSS were analyzed. Flow cytometry was preformed to verify the result of scRNA-seq.ResultsWe identified two subpopulations significantly expand in pSS patients. The one highly expressing cytotoxicity genes is named as CD4+ CTLs cytotoxic T lymphocyte, and another highly expressing T cell receptor (TCR) variable gene is named as CD4+ TRAV13-2+ T cell. Flow cytometry results showed the percentages of CD4+ CTLs, which were profiled with CD4+ and GZMB+ staining; the total T cells of 10 patients with pSS were significantly higher than those of 10 healthy controls (P= 0.008). The expression level of IL-1β in macrophages, TCL1A in B cells, as well as interferon (IFN) response genes in most cell subsets was upregulated in the patients with pSS. Susceptibility genes including HLA-DRB5, CTLA4, and AQP3 were highly expressed in patients with pSS.ConclusionsOur data revealed disease-specific immune cell subsets and provided some potential new targets of pSS. Specific expansion of CD4+ CTLs may be involved in the pathogenesis of pSS, which might give valuable insights for therapeutic interventions of pSS.

scholarly journals Predicting bacterial infection outcomes using single cell RNA-sequencing analysis of human immune cells

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Noa Bossel Ben-Moshe ◽  
Shelly Hen-Avivi ◽  
Natalia Levitin ◽  
Dror Yehezkel ◽  
Marije Oosting ◽  
...  
Keyword(s):  
Bacterial Infection ◽  
Single Cell ◽  
Rna Sequencing ◽  
Immune Cells ◽  
Sequencing Analysis ◽  
Single Cell Rna Sequencing ◽  
Human Immune

scholarly journals Single-cell RNA sequencing of immune cells in gastric cancer patients

Aging ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 2747-2763 ◽  
Author(s):  
Kai Fu ◽  
Bingqing Hui ◽  
Qian Wang ◽  
Chen Lu ◽  
Weihong Shi ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Single Cell ◽  
Cancer Patients ◽  
Rna Sequencing ◽  
Immune Cells ◽  
Single Cell Rna Sequencing ◽  
Gastric Cancer Patients

Abstract A10: Using single-cell RNA sequencing to assess the impact of pancreatic oncogenic Kras on macrophage gene expression in vitro

2019 ◽  
Author(s):  
Katelyn Donahue ◽  
Yaqing Zhang ◽  
Veerin Sirihorachai ◽  
Stephanie The ◽  
Arvind Rao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Single Cell Rna Sequencing ◽  
The Impact

scholarly journals Single-cell RNA sequencing of a European and an African lymphoblastoid cell line

2019 ◽  
Author(s):  
Daniel Osorio ◽  
Xue Yu ◽  
Peng Yu ◽  
Erchin Serpedin ◽  
James J. Cai
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
African Ancestry ◽  
Peripheral Blood Lymphocytes ◽  
Barr Virus ◽  
Single Cell Rna Sequencing ◽  
Suitable Reference ◽  
The Impact

AbstractIn biomedical research, lymphoblastoid cell lines (LCLs), often established byin vitroinfection of resting B cells with Epstein Barr Virus, are commonly used as surrogates for peripheral blood lymphocytes. Genomic and transcriptomic information on LCLs has been used to study the impact of genetic variation on gene expression in humans. Here we present single-cell RNA sequencing (scRNA-seq) data on GM12878 and GM18502—two LCLs derived from the blood of female donors of European and African ancestry, respectively. Cells from three samples (the two LCLs and a 1:1 mixture of the two) were prepared separately using a 10X Genomics Chromium Controller and deeply sequenced. The final dataset contained 7,045 cells from GM12878, 5,189 from GM18502, and 5,820 from the mixture, offering valuable information on single-cell gene expression in highly homogenous cell populations. This dataset is a suitable reference of population differentiation in gene expression at the single-cell level. Data from the mixture provides additional valuable information facilitating the development of statistical methods for data normalization and batch effect correction.

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