scholarly journals Single-cell RNA sequencing of peripheral blood mononuclear cells from acute Kawasaki disease patients

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Zhen Wang ◽  
Lijian Xie ◽  
Guohui Ding ◽  
Sirui Song ◽  
Liqin Chen ◽  
...  
Keyword(s):  
T Cells ◽  
Kawasaki Disease ◽  
Immune Responses ◽  
Single Cell ◽  
Rna Sequencing ◽  
Mononuclear Cells ◽  
Healthy Controls ◽  
Peripheral Blood Mononuclear ◽  
Single Cell Rna Sequencing ◽  
Blood Mononuclear Cells

AbstractKawasaki disease (KD) is the most common cause of acquired heart disease in children in developed countries. Although functional and phenotypic changes of immune cells have been reported, a global understanding of immune responses underlying acute KD is unclear. Here, using single-cell RNA sequencing, we profile peripheral blood mononuclear cells from seven patients with acute KD before and after intravenous immunoglobulin therapy and from three age-matched healthy controls. The most differentially expressed genes are identified in monocytes, with high expression of pro-inflammatory mediators, immunoglobulin receptors and low expression of MHC class II genes in acute KD. Single-cell RNA sequencing and flow cytometry analyses, of cells from an additional 16 KD patients, show that although the percentage of total B cells is substantially decreased after therapy, the percentage of plasma cells among the B cells is significantly increased. The percentage of CD8+ T cells is decreased in acute KD, notably effector memory CD8+ T cells compared with healthy controls. Oligoclonal expansions of both B cell receptors and T cell receptors are observed after therapy. We identify biological processes potentially underlying the changes of each cell type. The single-cell landscape of both innate and adaptive immune responses provides insights into pathogenesis and therapy of KD.

scholarly journals Scalable full-transcript coverage single cell RNA sequencing with Smart-seq3xpress

2021 ◽  
Author(s):  
Michael Hagemann-Jensen ◽  
Christoph Ziegenhain ◽  
Rickard Sandberg
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Peripheral Blood Mononuclear Cells ◽  
Mononuclear Cells ◽  
Human Peripheral Blood ◽  
Cell Types ◽  
Peripheral Blood Mononuclear ◽  
Single Cell Rna Sequencing ◽  
Blood Mononuclear Cells ◽  
Additional Protein

Plate-based single-cell RNA-sequencing methods with full-transcript coverage typically excel at sensitivity but are more resource and time-consuming. Here, we miniaturized and streamlined the Smart-seq3 protocol for drastically reduced cost and increased throughput. Applying Smart-seq3xpress to 16,349 human peripheral blood mononuclear cells revealed a highly granular atlas complete with both common and rare cell types whose identification previously relied on additional protein measurements or the integration with a reference atlas.

Utilizing Single-cell RNA Sequencing for Analyzing the Characteristics of PBMC in Patients with Kawasaki Disease

2021 ◽  
Author(s):  
Xue Fan ◽  
Yuhan Zhou ◽  
Xin Guo ◽  
Mingguo Xu
Keyword(s):  
T Cells ◽  
Kawasaki Disease ◽  
B Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Healthy Child ◽  
Mononuclear Cells ◽  
Cell Clusters ◽  
Two Samples ◽  
Single Cell Rna Sequencing

Abstract Background: Kawasaki disease (KD) is the main cause of acquired heart disease in children and can lead to coronary artery lesions. This present study was designed to analyze the characteristics of KD peripheral blood mononuclear cells (PBMC) through single-cell RNA sequecing (scRNA-seq) and to explore the potential molecular mechanism of KD.Methods: PBMC was collected from one healthy child and one KD patient, and was used to single-cell RNA sequencing for cell clusters identification and differently expressed gene (DEG) determination. GO function enrichment analysis of DEG in B cell and T cells were performed to explore the most active biological function in KD immune cells. Results: 13 cell clusters can be identified in two samples. Compared with healthy child, naive CD8+ T cell, T helper cell and B cell in KD child were decreased, mainly immune-related T cells, and natural killer T (NKT) cell and neutrophil were increased. Cell activation, lymphocyte activation and regulation of immune system process were 3 GO function shared by all four types of T cells and B cell.Conclusions: Immune cell disorder appears in the KD patient at single cell level by scRNA-seq.

scholarly journals No detectable alloreactive transcriptional responses during donor-multiplexed single-cell RNA sequencing of peripheral blood mononuclear cells

2020 ◽  
Author(s):  
Christopher S. McGinnis ◽  
David A. Siegel ◽  
Guorui Xie ◽  
Mars Stone ◽  
Zev J. Gartner ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Peripheral Blood Mononuclear Cells ◽  
Peripheral Blood ◽  
Mononuclear Cells ◽  
Transcriptional Responses ◽  
Peripheral Blood Mononuclear ◽  
Single Cell Rna Sequencing ◽  
Blood Mononuclear Cells

ABSTRACTSingle-cell RNA sequencing (scRNA-seq) provides high-dimensional measurement of transcript counts in individual cells. However, high assay costs limit the study of large numbers of samples. Sample multiplexing technologies such as antibody hashing and MULTI-seq use sample-specific sequence tags to enable individual samples (e.g., different patients) to be sequenced in a pooled format before downstream computational demultiplexing. Critically, no study to date has evaluated whether the mixing of samples from different donors in this manner results in significant changes in gene expression resulting from alloreactivity (i.e., response to non-self immune antigens). The ability to demonstrate minimal to no alloreactivity is crucial to avoid confounded data analyses, particularly for cross-sectional studies evaluating changes in immunologic gene signatures,. Here, we compared the expression profiles of peripheral blood mononuclear cells (PBMCs) from a single donor with and without pooling with PBMCs isolated from other donors with different blood types. We find that there was no evidence of alloreactivity in the multiplexed samples following three distinct multiplexing workflows (antibody hashing, MULTI-seq, and in silico genotyping using souporcell). Moreover, we identified biases amongst antibody hashing sample classification results in this particular experimental system, as well as gene expression signatures linked to PBMC preparation method (e.g., Ficoll-Paque density gradient centrifugation with or without apheresis using Trima filtration).

scholarly journals Utilizing single-cell RNA sequencing for analyzing the characteristics of PBMC in patients with Kawasaki disease

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xue Fan ◽  
Yuhan Zhou ◽  
Xin Guo ◽  
Mingguo Xu
Keyword(s):  
T Cells ◽  
Kawasaki Disease ◽  
B Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Healthy Child ◽  
Mononuclear Cells ◽  
Cell Clusters ◽  
Two Samples ◽  
Single Cell Rna Sequencing

Abstract Background Kawasaki disease (KD) is the main cause of acquired heart disease in children and can lead to coronary artery lesions. This present study was designed to analyze the characteristics of KD peripheral blood mononuclear cells (PBMC) through single-cell RNA sequencing (scRNA-seq) and to explore the potential molecular mechanism of KD. Methods PBMC was collected from one healthy child and one KD patient, and was used to single-cell RNA sequencing for cell clusters identification and differently expressed gene (DEG) determination. GO function enrichment analysis of DEG in B cell and T cells were performed to explore the most active biological function in KD immune cells. Results Twelve cell clusters can be identified in two samples. Compared with healthy child, naive CD8+ T cell, T helper cell and B cell in KD child were decreased, mainly immune-related T cells, and natural killer T (NKT) cell were increased. Cell activation, lymphocyte activation and regulation of immune system process were 3 GO function shared by all four types of T cells and B cell. Conclusions Immune cell disorder appears in the KD patient at single cell level by scRNA-seq.

scholarly journals Single-cell characterization of a model of poly I:C-stimulated peripheral blood mononuclear cells in severe asthma

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ailu Chen ◽  
Maria P. Diaz-Soto ◽  
Miguel F. Sanmamed ◽  
Taylor Adams ◽  
Jonas C. Schupp ◽  
...  
Keyword(s):  
T Cells ◽  
Single Cell ◽  
Severe Asthma ◽  
Mononuclear Cells ◽  
Effector T Cells ◽  
Poly I:C ◽  
Peripheral Blood Mononuclear ◽  
Main Cell ◽  
Blood Mononuclear Cells ◽  
Quantitative Changes

Abstract Background Asthma has been associated with impaired interferon response. Multiple cell types have been implicated in such response impairment and may be responsible for asthma immunopathology. However, existing models to study the immune response in asthma are limited by bulk profiling of cells. Our objective was to Characterize a model of peripheral blood mononuclear cells (PBMCs) of patients with severe asthma (SA) and its response to the TLR3 agonist Poly I:C using two single-cell methods. Methods Two complementary single-cell methods, DropSeq for single-cell RNA sequencing (scRNA-Seq) and mass cytometry (CyTOF), were used to profile PBMCs of SA patients and healthy controls (HC). Poly I:C-stimulated and unstimulated cells were analyzed in this study. Results PBMCs (n = 9414) from five SA (n = 6099) and three HC (n = 3315) were profiled using scRNA-Seq. Six main cell subsets, namely CD4 + T cells, CD8 + T cells, natural killer (NK) cells, B cells, dendritic cells (DCs), and monocytes, were identified. CD4 + T cells were the main cell type in SA and demonstrated a pro-inflammatory profile characterized by increased JAK1 expression. Following Poly I:C stimulation, PBMCs from SA had a robust induction of interferon pathways compared with HC. CyTOF profiling of Poly I:C stimulated and unstimulated PBMCs (n = 160,000) from the same individuals (SA = 5; HC = 3) demonstrated higher CD8 + and CD8 + effector T cells in SA at baseline, followed by a decrease of CD8 + effector T cells after poly I:C stimulation. Conclusions Single-cell profiling of an in vitro model using PBMCs in patients with SA identified activation of pro-inflammatory pathways at baseline and strong response to Poly I:C, as well as quantitative changes in CD8 + effector cells. Thus, transcriptomic and cell quantitative changes are associated with immune cell heterogeneity in this model to evaluate interferon responses in severe asthma.

scholarly journals Different Profile of Interleukin-10 Production in Circulating T Cells from Atopic Asthmatics Compared with Healthy Subjects

2004 ◽  
Vol 11 (1) ◽  
pp. 33-38 ◽  
Author(s):  
K Matsumoto ◽  
S Narita ◽  
T Rerecich ◽  
DP Snider ◽  
PM O'Byrne
Keyword(s):  
Flow Cytometry ◽  
T Cells ◽  
Healthy Subjects ◽  
Mononuclear Cells ◽  
Interleukin 10 ◽  
Healthy Controls ◽  
Peripheral Blood Mononuclear ◽  
Blood Mononuclear Cells ◽  
Circulating T Cells ◽  
Normal Controls

BACKGROUND:Interleukin (IL)-10 is a pleiotropic cytokine released from various cells, including T cells. Although IL-10 is suggested to inhibit allergic responses, its role in asthma remains uncertain. The purpose of the present study was to compare the profile of IL-10 in circulating T cells from stable atopic asthmatics, atopic nonasthmatics and healthy controls.METHODS:Peripheral blood mononuclear cells were isolated, stained with anti-CD3 and CD4/CD8 antibodies, and then processed for intracellular IL-10 detection by flow cytometry.RESULTS:A kinetic study in healthy controls showed that stimulation with phorbol 12-myristate 13-acetate and ionomycin significantly increased the frequencies of IL-10-producing CD3+, CD4+and CD8+cells. Without stimulation, the frequencies of IL-10-producing CD3+, CD4+and CD8+cells were significantly higher in asthmatics than in healthy controls, while a similar trend was observed in atopic nonasthmatics. Stimulation for 24 h significantly increased IL-10-producing CD3+, CD4+and CD8+cells in healthy controls and atopic nonasthmatics, but not in asthmatics.CONCLUSIONS:The frequency of IL-10-producing T cells is increased in the circulation of stable atopic asthmatics compared with normal controls. The lack of enhancement in their frequency by phorbol 12-myristate 13-acetate and ionomycin in asthmatics suggests that the circulating T cells of asthmatic subjects are maximally stimulated with regards to IL-10 production; alternatively, IL-10 production by T cells from asthmatics may be regulated differently than T cells from other subjects.

scholarly journals Multiplexing droplet-based single cell RNA-sequencing using natural genetic barcodes

2017 ◽  
Author(s):  
Hyun Min Kang ◽  
Meena Subramaniam ◽  
Sasha Targ ◽  
Michelle Nguyen ◽  
Lenka Maliskova ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Mononuclear Cells ◽  
Specific Gene ◽  
Cell Capture ◽  
Cell Type ◽  
Cell Type Specificity ◽  
Peripheral Blood Mononuclear ◽  
Single Cell Rna Sequencing ◽  
Sample Identity

Droplet-based single-cell RNA-sequencing (dscRNA-seq) has enabled rapid, massively parallel profiling of transcriptomes from tens of thousands of cells. Multiplexing samples for single cell capture and library preparation in dscRNA-seq would enable cost-effective designs of differential expression and genetic studies while avoiding technical batch effects, but its implementation remains challenging. Here, we introduce an in-silico algorithm demuxlet that harnesses natural genetic variation to discover the sample identity of each cell and identify droplets containing two cells. These capabilities enable multiplexed dscRNA-seq experiments where cells from unrelated individuals are pooled and captured at higher throughput than standard workflows. To demonstrate the performance of demuxlet, we sequenced 3 pools of peripheral blood mononuclear cells (PBMCs) from 8 lupus patients. Given genotyping data for each individual, demuxlet correctly recovered the sample identity of > 99% of singlets, and identified doublets at rates consistent with previous estimates. In PBMCs, we demonstrate the utility of multiplexed dscRNA-seq in two applications: characterizing cell type specificity and inter-individual variability of cytokine response from 8 lupus patients and mapping genetic variants associated with cell type specific gene expression from 23 donors. Demuxlet is fast, accurate, scalable and could be extended to other single cell datasets that incorporate natural or synthetic DNA barcodes.

scholarly journals Comparison of clustering tools in R for medium-sized 10x Genomics single-cell RNA-sequencing data

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1297 ◽  
Author(s):  
Saskia Freytag ◽  
Luyi Tian ◽  
Ingrid Lönnstedt ◽  
Milica Ng ◽  
Melanie Bahlo
Keyword(s):  
Single Cell ◽  
Peripheral Blood Mononuclear Cells ◽  
Gold Standard ◽  
Mononuclear Cells ◽  
Rna Seq ◽  
Sequencing Data ◽  
Peripheral Blood Mononuclear ◽  
Silver Standard ◽  
Single Cell Rna Sequencing ◽  
Blood Mononuclear Cells

Background: The commercially available 10x Genomics protocol to generate droplet-based single cell RNA-seq (scRNA-seq) data is enjoying growing popularity among researchers. Fundamental to the analysis of such scRNA-seq data is the ability to cluster similar or same cells into non-overlapping groups. Many competing methods have been proposed for this task, but there is currently little guidance with regards to which method to use. Methods: Here we use one gold standard 10x Genomics dataset, generated from the mixture of three cell lines, as well as multiple silver standard 10x Genomics datasets generated from peripheral blood mononuclear cells to examine not only the accuracy but also running time and robustness of a dozen methods. Results: We found that Seurat outperformed other methods, although performance seems to be dependent on many factors, including the complexity of the studied system. Furthermore, we found that solutions produced by different methods have little in common with each other. Conclusions: In light of this we conclude that the choice of clustering tool crucially determines interpretation of scRNA-seq data generated by 10x Genomics. Hence practitioners and consumers should remain vigilant about the outcome of 10x Genomics scRNA-seq analysis.

scholarly journals FEM: mining biological meaning from cell level in single-cell RNA sequencing data

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12570
Author(s):  
Yunqing Liu ◽  
Na Lu ◽  
Changwei Bi ◽  
Tingyu Han ◽  
Guo Zhuojun ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Mononuclear Cells ◽  
Differentially Expressed Gene ◽  
Biological Significance ◽  
Human Pancreas ◽  
Sequencing Data ◽  
Peripheral Blood Mononuclear ◽  
Single Cell Rna Sequencing ◽  
Expression Matrix

Background One goal of expression data analysis is to discover the biological significance or function of genes that are differentially expressed. Gene Set Enrichment (GSE) analysis is one of the main tools for function mining that has been widely used. However, every gene expressed in a cell is valuable information for GSE for single-cell RNA sequencing (scRNA-SEQ) data and not should be discarded. Methods We developed the functional expression matrix (FEM) algorithm to utilize the information from all expressed genes. The algorithm converts the gene expression matrix (GEM) into a FEM. The FEM algorithm can provide insight on the biological significance of a single cell. It can also integrate with GEM for downstream analysis. Results We found that FEM performed well with cell clustering and cell-type specific function annotation in three datasets (peripheral blood mononuclear cells, human liver, and human pancreas).

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